diff --git a/.env b/.env new file mode 100644 index 00000000..17d71a22 --- /dev/null +++ b/.env @@ -0,0 +1,19 @@ +INMET_API_BASE_URL=https://apitempo.inmet.gov.br +WS_INMET_DATA_DIR=./data/ws/inmet/ +WS_ALERTARIO_DATA_DIR=./data/ws/alertario/ws/ +GS_ALERTARIO_DATA_DIR=./data/ws/alertario/rain_gauge_era5_fused/ +CEMADEN_DATA_DIR=.data/ws/cemaden/ +SUMARE_DATA_DIR=.data/radar_sumare +GOES16_DATA_DIR=./data/goes16/CMI/ +GOES16_FEATURES_DIR=./data/goes16/features/ +NWP_DATA_DIR=./data/NWP/ +AS_DATA_DIR=./data/as/ +DSI_DATA_DIR=./data/goes16/DSI +TPW_DATA_DIR=./data/goes16/wsoi +DATASETS_DIR=./data/datasets/ +MODELS_DIR=./models/ +WEBSIRENE_DATA_DIR=./data/ws/websirene/ +REGION_LAT_MIN=-23.801876626302175 +REGION_LON_MIN=-45.05290312102409 +REGION_LAT_MAX=-21.699774257353113 +REGION_LON_MAX=-42.35676996062447 diff --git a/.gitignore b/.gitignore index bf348460..76085280 100644 --- a/.gitignore +++ b/.gitignore @@ -1,9 +1,16 @@ -.vscode/ +clea.vscode/ data/ +datasets/ models/ backup/ __pycache__/ *.pyc + *.log + +src/spatiotemporal_builder/.github + +.DS_Store +src/.DS_Store src/__pycache__/globals.cpython-38.pyc src/__pycache__/globals.cpython-310.pyc @@ -17,3 +24,38 @@ src/__pycache__/util.cpython-310.pyc src/__pycache__/globals.cpython-310.pyc src/__pycache__/util.cpython-310.pyc src/__pycache__/goes16_utils.cpython-310.pyc +nohup.out +src/__pycache__/ +src/surface_stations/__pycache__/ +*.out +*.gif +*.png +*.nc +*.parquet +*.log +src/spatiotemporal_builder/__pycache__/ +src/spatiotemporal_builder/features/ +anim/dF_dt_2024_01_13/animation.mp4 +notebooks/GPM/imerg_animation_2024_01_01.mp4 +notebooks/GPM/imerg_rio_animation.mp4 +notebooks/GPM/imerg_rio_animation_2024_01_01.mp4 +anim/PN_GLM/animation.mp4 +notebooks/RJ-30m-DEM.tif +*.tgz +src/config/__pycache__/__init__.cpython-310.pyc +src/config/__pycache__/globals.cpython-310.pyc +src/goes16/__pycache__/__init__.cpython-310.pyc +src/goes16/__pycache__/features.cpython-310.pyc +src/goes16/__pycache__/utils.cpython-310.pyc +src/goes16/__pycache__/goes16_cmi_feature_extractor_extended.cpython-311.pyc +src/goes16/__pycache__/goes16_cmi_feature_extractor.cpython-311.pyc +src/goes16/features/__pycache__/__init__.cpython-310.pyc +src/goes16/features/__pycache__/fa.cpython-310.pyc +src/goes16/features/__pycache__/gtn.cpython-310.pyc +src/goes16/features/__pycache__/li_proxy.cpython-310.pyc +src/goes16/features/__pycache__/pn_std.cpython-310.pyc +src/goes16/features/__pycache__/pn.cpython-310.pyc +src/goes16/features/__pycache__/toct.cpython-310.pyc +src/goes16/features/__pycache__/wv_grad.cpython-310.pyc +src/utils/__pycache__/__init__.cpython-310.pyc +src/utils/__pycache__/util.cpython-310.pyc diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000..050031ed --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,13 @@ +repos: + - repo: https://github.com/psf/black + rev: 24.4.2 + hooks: + - id: black + args: ["--line-length", "88"] + + - repo: https://github.com/astral-sh/ruff-pre-commit + rev: v0.5.6 + hooks: + - id: ruff + args: ["--fix"] + - id: ruff-format diff --git a/Makefile b/Makefile new file mode 100644 index 00000000..3ecaaca9 --- /dev/null +++ b/Makefile @@ -0,0 +1,112 @@ +# === AtmoSeer Makefile === + +# Diretório base para os dados +DATA_DIR=data + +# Diretório base para o código-fonte +SRC_DIR=src + +# ========== Surfaces stations - CEMADEN ======================== +cemaden_retrieve_data: + PYTHONPATH=src python3 src/surface_stations/retrieve_data_cemaden.py \ + $(if $(IBGE),--ibge $(IBGE)) \ + $(if $(START),--inicio $(START)) \ + $(if $(END),--fim $(END)) \ + $(if $(EMAIL),--email $(EMAIL)) \ + $(if $(SENHA),--senha $(SENHA)) \ + $(if $(ESTACAO),--estacao $(ESTACAO)) + +cemaden_retrieve_ws: + PYTHONPATH=src python3 src/surface_stations/retrieve_ws_cemaden.py \ + $(if $(ESTADO),-e $(ESTADO)) \ + $(if $(IDESTACAO),-c $(IDESTACAO)) \ + $(if $(INICIO),-start $(INICIO)) \ + $(if $(FIM),-end $(FIM)) \ + $(if $(SAIDA),-o $(SAIDA)) \ + +cemaden_mapa: + PYTHONPATH=src python3 src/surface_stations/cemaden_mapa.py + +cemaden_mapa_chuva: + PYTHONPATH=src python3 src/surface_stations/cemaden_mapa_chuva.py + +# ========== Surfaces stations - INMET ======================== +inmet_retrieve_ws: + PYTHONPATH=src python3 src/surface_stations/retrieve_ws_inmet.py \ + $(if $(API_TOKEN),-t $(API_TOKEN)) \ + $(if $(STATION_ID),-s $(STATION_ID)) \ + $(if $(BEGIN_YEAR),-b $(BEGIN_YEAR)) \ + $(if $(END_YEAR),-e $(END_YEAR)) +# Example usage: +# make inmet_retrieve_ws API_TOKEN=your_token STATION_ID=A601 BEGIN_YEAR=2020 END_YEAR=2023 + +surface_stations_preprocess: + PYTHONPATH=src python3 src/surface_stations/preprocess.py \ + $(if $(STATION_ID),--station_id $(STATION_ID)) \ + $(if $(SYSTEM),--station_system $(SYSTEM)) +# Example usage: +# make surface_stations_preprocess STATION_ID=A601 SYSTEM=INMET + + +# === GOES-16 Downloader/Cropper === +goes16-download-crop: + PYTHONPATH=src python src/goes16/goes16_download_crop.py \ + --start_date $(START) \ + --end_date $(END) \ + --channel $(CHANNEL) \ + --crop_dir $(DIR) \ + --spatial_resolution 0.1 \ + --vars CMI + +# === GOES-16 Feature Extractor === +goes16-features: + PYTHONPATH=src python src/goes16/main_goes16_features.py $(FEATS) + +sumare-crop-images: + PYTHONPATH=src python3 src/sumare_radar/crop_image.py + +# Validates a GOES-16 feature based on the specified channels +validate-feature: + @echo "Validating feature '$(FEAT)' with channels $(CANAIS)" + PYTHONPATH=src python src/goes16/validate_features.py --feature $(FEAT) --canais $(CANAIS) + +# Summarize GOES-16 feature extraction log files +analyze-logs: + @echo "Analyzing log files in src/goes16/features/" + @PYTHONPATH=src python src/goes16/features/analyze_logs.py + +# === GPM Download/Cropper === +gpm-download-crop: + PYTHONPATH=src python src/gpm/gpm_download_crop.py \ + --begin_date "$(BEGIN)" \ + --end_date "$(END)" \ + --user "$(USER)" \ + --pwd "$(PWD)" \ + $(DEBUG) \ + $(IGNORED) + + +# === Alerta Rio Parser (placeholder) === +alerta-rio-process: + PYTHONPATH=$(SRC_DIR) python $(SRC_DIR)/surface_stations/alerta_rio_parser.py + + +# === Clean Outputs === +clean: + rm -rf $(DATA_DIR)/goes16/features/* + +.PHONY: format lint lint-fix pre-commit-install + +format: + ruff format src tests + black src tests + +lint: + ruff check src tests + +lint-fix: + ruff check src tests --fix + black src tests + +pre-commit-install: + pre-commit install diff --git a/README.md b/README.md index bbc027a7..ade82f6e 100644 --- a/README.md +++ b/README.md @@ -1,49 +1,142 @@ # AtmoSeer -## About +AtmoSeer is a set of Python scripts for downloading, processing, and analyzing atmospheric and meteorological data from sources such as NASA GPM and GOES-16. It supports environment setup via Conda and requires authentication for NASA Earthdata access. This project also provides a pipeline to build rainfall forecast models. The pipeline can be configured with different meteorological data sources. -This project provides a pipeline to build rainfall forecast models. The pipeline can be configured with different meteorological data sources. +--- -## Install +## Installation -In the root directory of this repository, type the following command (you must have conda installed in your system): +### 1. Clone the repository + +```bash +git clone https://github.com/your-org/atmoseer.git +cd atmoseer +```` + +### 2. Set NASA Earthdata Credentials + +Before running the setup script, you must set your NASA Earthdata credentials as environment variables: + +```bash +export EARTHDATA_USER="your_username" +export EARTHDATA_PASS="your_password" +``` + +> You can register for a free NASA Earthdata account at [https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov). + +### 3. Run the Setup Script + +The `setup.sh` script will: + +* Remove any existing Conda environment named `atmoseer` +* Create a new Conda environment using `config/environment.yml` +* Create necessary data directories +* Configure `.netrc` and `.urs_cookies` in your home directory for Earthdata access + +```bash ./setup.sh +``` + +--- + +## Usage + +After the environment is set up, activate it: + +```bash +conda activate atmoseer +``` + +Now, you can start running AtmoSeer scripts. + +## Running Scripts with Make + +To simplify execution, AtmoSeer supports running preprocessing tasks using `make`. Each data module has its own Makefile targets and README with details. + +### ✅ Examples + +- **GOES-16 Feature Extraction** + +```bash +make goes16-features FEATS="--pn --fa --toct --verbose" +``` + +See full usage in [`src/goes16/README.md`](src/goes16/README.md) + +- **GPM Download and Crop** + +```bash +make gpm-download-crop BEGIN=2024/01/01 END=2024/01/03 USER=your_username PWD=your_password +``` + +See full usage in [`src/gpm/README.md`](src/gpm/README.md) + +--- + +## 📁 Directory Structure + +``` +atmoseer/ +├── config/ # Conda environment and config files +│ └── environment.yml +├── data/ # Automatically created data directories +│ ├── datasets/ +│ ├── era5/ +│ ├── goes16/ + ├── gpm/ +│ ├── sounding/ +│ ├── surface_stations/ +│ └── +├── src/ # Scripts for downloading and processing data, and for model training +│ ├── era5/ +│ ├── goes16/ + ├── gpm/ +│ ├── sounding/ +│ ├── surface_stations/ + └── ... +├── setup.sh # Installation script +└── README.md # This file +``` -## Project pipeline +--- -The project pipeline is defined as a sequence of three steps: (1) data retrieving, (2) data pre-processing and (3) model training. These steps are implemented as Python scripts in the `./src` directory. +## 🛠 Requirements -#### Data retrieval +* [Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Anaconda](https://www.anaconda.com/) +* Linux or WSL (recommended) +* Internet access for installing packages and accessing NASA endpoints -All datasets retrieved and/or generated by the scripts will be stored in the `./data` folder. +--- -- **_retrieve_ws_cor.py_**: This script retrieves observation from a user-provided weather station. -- **_retrieve_ws_inmet.py_**: This script retrieves observations for from a user-provided weather station. -- **_retrieve_as.py_**: this script retrieves atmospheric sounding data. -- **_retrieve_ERA5.py_**: this script retrieves numerical simulation data from the ERA5 portal. +## Guide to Collaborators +Welcome! Please follow these guidelines to keep the project consistent and secure. -##### Script **_gen_sounding_indices.py_** +- Communicate and document **only in English** so every contributor can follow along. +- Never commit secrets, credentials, or private datasets. Store sensitive values in `.env` files that stay out of version control. +- Use GitFlow conventions: branch from `develop` (or `main` if specified), follow feature/hotfix/release prefixes, and open pull requests before merging. +- Prefer small, focused commits with clear messages; reference issues or tasks when possible. +- Keep coding style consistent with the existing modules; run linting/formatting tools provided by the project before submitting code (see the tooling notes below). +- Add or update tests whenever you change behaviour, and ensure the full test suite passes locally. +- Discuss significant architectural or API changes with maintainers before implementation. +- Respect code reviews: respond to feedback promptly and revise your changes as needed. -This script will generate atmospheric instability indices for the data retrieveed by the script **_retrieve_as.py_**. Data from the SBGL sounding (located at the Galeão Airport, Rio de Janeiro - Brazil) will be used to calculate atmospheric instability indices, generating a new dataset. This new dataset contains one entry per sounding probe. SBGL sounding station produces two probes per day (at 00:00h and 12:00h UTC). Each entry in the produced contains the values of the computed instability indices for one probe. The following instability indices are computed: +### Code Style Tooling -- CAPE -- CIN -- Lift -- k -- Total totals -- Show alter +1. Install/update the Conda environment so that `black`, `ruff`, and `pre-commit` are available. +2. Run `make format` for automatic formatting (`ruff format` + `black`) and `make lint` to check for style and static-analysis issues. +3. Optional but recommended: `make pre-commit-install` to set up git hooks that run Ruff and Black before each commit. -#### Preprocessing +--- -The preprocessing scripts are responsible for performing several operations on the original dataset, such as creating variables or aggregating data, which can be interesting for model training and its final result. +## 🧾 License -#### Dataset building +This project is licensed under the MIT License. See `LICENSE` for details. -These scripts will build the train, validation and test dataset from the times series produced in the previous steps. These are the datasets to be given as input to the model training step. +--- -#### Model training and evaluation +## 👥 Acknowledgments -The model generation script is responsible for performing the training and exporting the results obtained by the model after testing. -# r2t +* NASA GES DISC — [https://disc.gsfc.nasa.gov](https://disc.gsfc.nasa.gov) +* Earthdata Login Services — [https://urs.earthdata.nasa.gov](https://urs.earthdata.nasa.gov) diff --git a/WeatherStations.csv b/WeatherStations.csv deleted file mode 100644 index 61380ae4..00000000 --- a/WeatherStations.csv +++ /dev/null @@ -1,35 +0,0 @@ -,DC_NOME,SG_ESTADO,CD_SITUACAO,VL_LATITUDE,VL_LONGITUDE,VL_ALTITUDE,DT_INICIO_OPERACAO,STATION_ID -23,ANGRA DOS REIS,RJ,Operante,"-22.97555554","-44.30333333",6,24/08/2017,A628 -41,ARRAIAL DO CABO,RJ,Operante,"-22.97527777","-42.02138888",5,21/09/2006,A606 -97,CAMBUCI,RJ,Operante,"-21.58749999","-41.95833333",46,19/11/2002,A604 -108,CAMPOS DOS GOYTACAZES,RJ,Operante,"-21.71472222","-41.34388888",17,24/09/2006,A607 -109,CAMPOS DOS GOYTACAZES - SAO TOME,RJ,Operante,"-22.04166666","-41.05166666",7,12/06/2008,A620 -124,CARMO,RJ,Operante,"-21.938745","-42.600936",293,10/10/2018,A629 -178,DUQUE DE CAXIAS - XEREM,RJ,Operante,"-22.58972221","-43.28222221",22,20/10/2002,A603 -292,MACAE,RJ,Operante,"-22.3761111","-41.81194444",28,21/09/2006,A608 -335,NITEROI,RJ,Operante,"-22.86749999","-43.10194444",6,12/07/2018,A627 -338,NOVA FRIBURGO - SALINAS,RJ,Operante,"-22.33472221","-42.67694443",1070,17/09/2010,A624 -365,PARATY,RJ,Operante,"-23.2236111","-44.72694443",3,18/11/2006,A619 -381,PICO DO COUTO,RJ,Operante,"-22.46472222","-43.29138888",1777,21/10/2006,A610 -413,Paty do Alferes - Avelar,RJ,Operante,"-22.34722221","-43.41777777",508,09/11/2022,A637 -425,RESENDE,RJ,Operante,"-22.45138888","-44.44499999","438,83",28/09/2006,A609 -429,RIO CLARO,RJ,Operante,"-22.653579","-44.040916",516,02/06/2016,A626 -430,RIO DE JANEIRO - FORTE DE COPACABANA,RJ,Operante,"-22.98833333","-43.19055555","25,59",17/05/2007,A652 -431,RIO DE JANEIRO - JACAREPAGUA,RJ,Operante,"-22.93999999","-43.40277777",20,09/08/2017,A636 -432,RIO DE JANEIRO - VILA MILITAR,RJ,Operante,"-22.86138888","-43.41138888","30,43",12/04/2007,A621 -433,RIO DE JANEIRO-MARAMBAIA,RJ,Operante,"-23.05027777","-43.59555555",12,07/11/2002,A602 -458,SANTA MARIA MADALENA,RJ,Operante,"-21.95055555","-42.01027777",517,15/10/2018,A630 -498,SAQUAREMA - SAMPAIO CORREIA,RJ,Operante,"-22.8711111","-42.60888888",26,01/09/2015,A667 -501,SEROPEDICA-ECOLOGIA AGRICOLA,RJ,Operante,"-22.75777777","-43.68472221",35,23/05/2000,A601 -510,SILVA JARDIM,RJ,Operante,"-22.64583333","-42.41555555",19,27/08/2015,A659 -526,TERESOPOLIS-PARQUE NACIONAL,RJ,Operante,"-22.4486111","-42.98694444",981,31/10/2006,A618 -535,TRES RIOS,RJ,Operante,"-22.09833333","-43.20833333",295,07/06/2016,A625 -550,VALENCA,RJ,Operante,"-22.35805555","-43.69555555",370,26/09/2006,A611 -0,Vidigal,RJ,Operante,-22.9925,-43.2331,,,vidigal -10,Irajá,RJ,Operante,-22.8269,-43.3369,,,iraja -15,Jardim Botânico,RJ,Operante,-22.9728,-43.2239,,,jardim_botanico -18,Barra/Riocentro,RJ,Operante,-22.9772,-43.3916,,,riocentro -19,Guaratiba,RJ,Operante,-23.0503,-43.5947,,,guaratiba -21,Santa Cruz,RJ,Operante,-22.9094,-43.6844,,,santa_cruz -27,Alto da Boa Vista,RJ,Operante,-22.9658,-43.2783,,,alto_da_boa_vista -31,São Cristóvão,RJ,Operante,-22.8967,-43.2217,,,sao_cristovao \ No newline at end of file diff --git a/config/cemaden_stations.csv b/config/cemaden_stations.csv new file mode 100644 index 00000000..3419a67a --- /dev/null +++ b/config/cemaden_stations.csv @@ -0,0 +1,29 @@ +,altitude,cidade,codestacao,codibge,cota_alerta,cota_atencao,cota_transbordamento,data_instalacao,dh_cadastro,dh_inicio_inativo,dh_ultima_remessa,id_estacao,id_rede,id_tipoestacao,latitude,longitude,nome,offset,rede_sigla,tipoestacao_descricao,uf +0,0.0,RIO DE JANEIRO,330455734A,3304557,,,,2015-04-17 13:23:58.932,2015-04-17 13:23:58.932,2024-03-26 20:45:51.749,2024-03-26 18:40:24.000,7615,11,1,-22.7613,-43.1084,Ilha de Paquetá,,CEMADEN,Pluviométrica,RJ +1,0.0,RIO DE JANEIRO,330455733A,3304557,,,,2015-05-22 11:03:39.609,2015-05-22 11:03:39.609,2025-05-24 03:35:26.360,2025-09-09 11:30:21.000,7614,11,1,-22.875,-43.299,Pilares,,CEMADEN,Pluviométrica,RJ +2,0.0,RIO DE JANEIRO,330455732A,3304557,,,,2015-05-26 13:12:55.735,2015-05-26 13:12:55.735,2025-06-26 06:26:19.726,2025-09-09 11:20:27.000,7613,11,1,-22.869,-43.265,Higienópolis,,CEMADEN,Pluviométrica,RJ +3,0.0,RIO DE JANEIRO,330455731A,3304557,,,,2015-03-04 20:17:58.835,2015-03-04 20:17:58.835,2025-06-26 07:16:09.334,2025-09-09 11:10:29.000,7612,11,1,-22.948,-43.258,Usina,,CEMADEN,Pluviométrica,RJ +4,0.0,RIO DE JANEIRO,330455730A,3304557,,,,2015-05-20 13:03:35.902,2015-05-20 13:03:35.902,2025-09-03 13:04:55.200,2025-09-03 11:02:56.000,7611,11,1,-22.943,-43.241,Tijuca,,CEMADEN,Pluviométrica,RJ +5,0.0,RIO DE JANEIRO,330455729A,3304557,,,,2015-08-20 12:31:52.784,2015-08-20 12:31:52.784,2025-08-05 15:14:16.114,2025-09-09 11:40:30.000,7610,11,1,-22.9666,-43.2965,Alto da Boa Vista,,CEMADEN,Pluviométrica,RJ +6,0.0,RIO DE JANEIRO,330455728A,3304557,,,,2015-05-15 12:53:15.827,2015-05-15 12:53:15.827,2025-05-28 22:07:38.597,2025-09-09 11:00:21.000,7609,11,1,-22.86086,-43.30756,Vicente de Carvalho,,CEMADEN,Pluviométrica,RJ +7,0.0,RIO DE JANEIRO,330455726A,3304557,,,,2015-02-20 14:31:36.673,2015-02-20 14:31:36.673,2023-06-27 18:52:25.122,2023-06-27 16:50:00.000,7607,11,1,-22.894,-43.676,Defesa Civil Santa Cruz,,CEMADEN,Pluviométrica,RJ +8,0.0,RIO DE JANEIRO,330455725A,3304557,,,,2015-05-04 13:35:59.398,2015-05-04 13:35:59.398,2025-06-26 06:44:45.865,2025-09-09 11:40:26.000,7606,11,1,-22.8131,-43.3101,Vigário Geral,,CEMADEN,Pluviométrica,RJ +9,0.0,RIO DE JANEIRO,330455724A,3304557,,,,2015-05-04 14:11:06.152,2015-05-04 14:11:06.152,2025-09-05 11:38:23.659,2025-09-09 11:30:00.000,7605,11,1,-22.8076,-43.3584,Pavuna,,CEMADEN,Pluviométrica,RJ +10,0.0,RIO DE JANEIRO,330455722A,3304557,,,,2015-05-26 14:20:15.064,2015-05-26 14:20:15.064,2025-08-26 11:13:10.581,2025-09-09 11:10:00.000,7603,11,1,-22.923,-43.176,Catete,,CEMADEN,Pluviométrica,RJ +11,0.0,RIO DE JANEIRO,330455721A,3304557,,,,2015-05-26 13:34:42.170,2015-05-26 13:34:42.170,2025-09-03 13:15:08.103,2025-09-03 11:05:30.000,7602,11,1,-22.995,-43.269,São Conrado,,CEMADEN,Pluviométrica,RJ +12,0.0,RIO DE JANEIRO,330455720A,3304557,,,,2015-05-14 12:57:54.207,2015-05-14 12:57:54.207,2025-02-26 19:15:51.543,2025-02-26 17:10:25.000,7601,11,1,-22.796,-43.203,CIEP Dr. João Ramos de Souza,,CEMADEN,Pluviométrica,RJ +13,0.0,RIO DE JANEIRO,330455719A,3304557,,,,2015-05-06 13:19:01.353,2015-05-06 13:19:01.353,2025-06-26 07:03:35.434,2025-09-09 12:00:32.000,7600,11,1,-22.9922,-43.367,Jacarepaguá,,CEMADEN,Pluviométrica,RJ +14,0.0,RIO DE JANEIRO,330455718A,3304557,,,,2015-05-14 14:45:28.982,2015-05-14 14:45:28.982,2025-07-01 18:52:28.342,2025-09-09 11:50:26.000,7599,11,1,-22.989,-43.433,Vargem Pequena,,CEMADEN,Pluviométrica,RJ +15,0.0,RIO DE JANEIRO,330455716A,3304557,,,,2015-05-20 16:05:42.233,2015-05-20 16:05:42.233,2025-09-08 20:45:58.941,2025-09-09 10:40:24.000,7597,11,1,-22.921,-43.227,CIEP Samuel Wainer,,CEMADEN,Pluviométrica,RJ +16,0.0,RIO DE JANEIRO,330455715A,3304557,,,,2015-08-04 12:58:24.170,2015-08-04 12:58:24.170,2024-09-15 03:36:18.534,2024-09-15 01:30:24.000,7596,11,1,-22.93,-43.25,Andaraí,,CEMADEN,Pluviométrica,RJ +17,0.0,RIO DE JANEIRO,330455714A,3304557,,,,2015-07-22 13:24:23.687,2015-07-22 13:24:23.687,2025-04-24 20:20:05.277,2025-04-24 18:20:20.000,7595,11,1,-22.929,-43.228,Salgueiro,,CEMADEN,Pluviométrica,RJ +18,0.0,RIO DE JANEIRO,330455713A,3304557,,,,2015-04-16 19:27:51.603,2015-04-16 19:27:51.603,2025-06-26 07:16:15.456,2025-09-09 11:10:27.000,7594,11,1,-22.8689,-43.4507,Padre Miguel,,CEMADEN,Pluviométrica,RJ +19,0.0,RIO DE JANEIRO,330455712A,3304557,,,,2015-04-16 18:07:00.027,2015-04-16 18:07:00.027,2025-09-02 18:21:09.815,2025-09-09 12:00:48.000,7593,11,1,-22.864,-43.425,Realengo Batan,,CEMADEN,Pluviométrica,RJ +20,0.0,RIO DE JANEIRO,330455711A,3304557,,,,2015-04-28 13:48:37.861,2015-04-28 13:48:37.861,2025-05-24 03:11:57.786,2025-09-09 11:10:21.000,7592,11,1,-22.8897,-43.7175,Santa Cruz,,CEMADEN,Pluviométrica,RJ +21,0.0,RIO DE JANEIRO,330455710A,3304557,,,,2015-07-23 13:25:13.894,2015-07-23 13:25:13.894,2025-05-21 18:53:37.848,2025-05-21 16:52:40.000,7591,11,1,-22.9592,-43.6082,Jardim Maravilha,,CEMADEN,Pluviométrica,RJ +22,0.0,RIO DE JANEIRO,330455709A,3304557,,,,2014-03-20 16:22:50.814,2014-03-20 16:22:50.814,2025-09-03 12:53:48.571,2025-09-03 10:50:40.000,3215,11,1,-22.977861,-43.277444,Est. Pedra Bonita,,CEMADEN,Pluviométrica,RJ +23,0.0,RIO DE JANEIRO,330455706A,3304557,,,,2014-02-28 11:59:31.127,2014-02-28 11:59:31.127,2025-09-05 12:44:17.999,2025-09-05 10:43:01.000,3044,11,1,-22.839,-43.279,Penha,,CEMADEN,Pluviométrica,RJ +24,0.0,RIO DE JANEIRO,330455705A,3304557,,,,2014-02-21 16:51:32.524,2014-02-21 16:51:32.524,2025-07-18 04:56:25.882,2025-09-09 11:20:34.000,3043,11,1,-22.918,-43.361,Tanque Jacarepagua,,CEMADEN,Pluviométrica,RJ +25,0.0,RIO DE JANEIRO,330455704A,3304557,,,,2014-02-21 19:51:52.896,2014-02-21 19:51:52.896,2025-07-15 19:07:56.094,2025-09-09 11:10:30.000,3045,11,1,-22.896,-43.352,Praça Seca,,CEMADEN,Pluviométrica,RJ +26,0.0,RIO DE JANEIRO,330455703A,3304557,,,,2014-07-31 20:39:13.358,2014-07-31 20:39:13.358,2023-05-26 20:16:22.557,2023-05-26 18:09:53.000,3042,11,1,-22.885906,-43.297753,Abolição,,CEMADEN,Pluviométrica,RJ +27,0.0,RIO DE JANEIRO,330455701A,3304557,,,,2014-02-28 18:07:10.559,2014-02-28 18:07:10.559,2025-09-03 14:35:49.411,2025-09-03 12:34:16.000,3114,11,1,-22.915,-43.176,Glória,,CEMADEN,Pluviométrica,RJ diff --git a/src/commands.txt b/config/commands.txt similarity index 63% rename from src/commands.txt rename to config/commands.txt index 9929153b..9542b093 100644 --- a/src/commands.txt +++ b/config/commands.txt @@ -104,10 +104,11 @@ python src/retrieve_ws_inmet.py -s A627 -b 2018 -e 2023 --api_token python src/retrieve_ws_inmet.py -s A636 -b 2017 -e 2023 --api_token ========================================== -=== retrieve_as +=== retrieve_data ========================================== -python src/retrieve_as.py --station_id SBGL --start_year 2023 --end_year 2023 -python src/gen_sounding_indices.py --input_file ./data/as/SBGL_1997_2023.parquet.gzip --output_file ./data/as/SBGL_indices_1997_2023.parquet.gzip +python src/sounding_retrieve_data.py --station_id SBGL --start_year 2023 --end_year 2023 +python src/sounding_gen_indices.py --input_file ./data/as/SBGL_1997_2023.parquet.gzip --output_file ./data/as/SBGL_indices_1997_2023.parquet.gzip +python src/sounding_gen_indices.py --input_file ./data/as/SBGL_2023_2024.parquet.gzip --output_file ./data/as/SBGL_indices_2023_2024.parquet.gzip ========================================== === retrieve_ERA5 @@ -146,50 +147,109 @@ python src/train_model.py -p A652_A621_A636_A627 -t ORDINAL_CLASSIFICATION python src/train_model.py -p sao_cristovao_tijuca_tijuca_muda_saude_grajau -t ORDINAL_CLASSIFICATION > sao_cristovao_tijuca_tijuca_muda_saude_grajau.txt +MONAN Meeting 2024 +================== -LAFUSION 2023 -=========== +1) +python src/retrieve_ws_inmet.py -s A601 -b 2019 -e 2024 --api_token +python src/retrieve_ws_inmet.py -s A602 -b 2007 -e 2024 --api_token +python src/retrieve_ws_inmet.py -s A621 -b 2007 -e 2024 --api_token +python src/retrieve_ws_inmet.py -s A627 -b 2018 -e 2024 --api_token +python src/retrieve_ws_inmet.py -s A636 -b 2017 -e 2024 --api_token +python src/retrieve_ws_inmet.py -s A652 -b 2007 -e 2024 --api_token + +2) +python src/retrieve_goes16_product_for_extent.py --date_ini "2019-12-05" --date_end "2024-06-15" --prod ABI-L2-DSIF --vars CAPE LI TT SI KI + +3) +python src/preprocess_ws.py -s A601 > preprocess_A601.out +python src/preprocess_ws.py -s A602 > preprocess_A602.out +python src/preprocess_ws.py -s A621 > preprocess_A621.out +python src/preprocess_ws.py -s A627 > preprocess_A627.out +python src/preprocess_ws.py -s A636 > preprocess_A636.out +python src/preprocess_ws.py -s A652 > preprocess_A652.out + +4) +python src/gen_dsi_dataframes.py + +5) +python src/aggregate_through_time.py --input_file ./data/goes16/DSI/DSI_CAPE.parquet --output_file ./data/goes16/DSI/DSI_CAPE_1H.parquet +python src/aggregate_through_time.py --input_file ./data/goes16/DSI/DSI_LI.parquet --output_file ./data/goes16/DSI/DSI_LI_1H.parquet +python src/aggregate_through_time.py --input_file ./data/goes16/DSI/DSI_TT.parquet --output_file ./data/goes16/DSI/DSI_TT_1H.parquet +python src/aggregate_through_time.py --input_file ./data/goes16/DSI/DSI_SI.parquet --output_file ./data/goes16/DSI/DSI_SI_1H.parquet +python src/aggregate_through_time.py --input_file ./data/goes16/DSI/DSI_KI.parquet --output_file ./data/goes16/DSI/DSI_KI_1H.parquet + +6) +python src/build_datasets.py -s A601 --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A602 --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A621 --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A627 --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A636 --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A652 --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" -python src/retrieve_goes16_tpwf.py --date_ini "2019-12-01" --date_ini "2019-12-31" -python src/retrieve_goes16_tpwf.py --date_ini "2020-01-01" --date_ini "2020-05-31" -python src/retrieve_goes16_tpwf.py --date_ini "2020-09-01" --date_ini "2020-12-31" -python src/retrieve_goes16_tpwf.py --date_ini "2021-01-01" --date_ini "2021-05-31" -python src/retrieve_goes16_tpwf.py --date_ini "2021-09-01" --date_ini "2021-12-31" -python src/retrieve_goes16_tpwf.py --date_ini "2021-09-01" --date_ini "2021-09-30" -python src/retrieve_goes16_tpwf.py --date_ini "2021-10-01" --date_ini "2021-10-31" -python src/retrieve_goes16_tpwf.py --date_ini "2021-11-01" --date_ini "2021-11-30" -python src/retrieve_goes16_tpwf.py --date_ini "2021-12-01" --date_ini "2021-12-31" -python src/retrieve_goes16_tpwf.py --date_ini "2022-01-01" --date_ini "2022-05-31" -python src/retrieve_goes16_tpwf.py --date_ini "2022-09-01" --date_ini "2022-12-31" -python src/retrieve_goes16_tpwf.py --date_ini "2023-01-01" --date_ini "2023-05-31" -python src/retrieve_goes16_tpwf.py --date_ini "2023-06-01" --date_end "2023-12-31" - -python src/gen_tpw_datasets_per_wsois.py +python src/build_datasets.py -s A601 -d DSI --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A602 -d DSI --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A621 -d DSI --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A627 -d DSI --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A636 -d DSI --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +python src/build_datasets.py -s A652 -d DSI --train_test_threshold "2022-05-31" --train_start_threshold "2019-12-05" +6a) +python src/build_datasets.py -s A601 --train_start_threshold "2019-12-06" --train_test_threshold "2022-05-31" --test_end_threshold "2024-06-15" +python src/build_datasets.py -s A601 --train_start_threshold "2019-12-06" --train_test_threshold "2022-05-31" --test_end_threshold "2024-06-15" -d DSI + + + + +LAFUSION 2023 +============= + +1) +python src/retrieve_goes16_product_for_wsois.py --date_ini "2019-12-01" --date_end "2019-12-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2020-01-01" --date_end "2020-05-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2020-09-01" --date_end "2020-12-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2021-01-01" --date_end "2021-05-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2021-09-01" --date_end "2021-12-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2021-09-01" --date_end "2021-09-30" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2021-10-01" --date_end "2021-10-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2021-11-01" --date_end "2021-11-30" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2021-12-01" --date_end "2021-12-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2022-01-01" --date_end "2022-05-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2022-09-01" --date_end "2022-12-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2023-01-01" --date_end "2023-05-31" --prod ABI-L2-TPWF --vars TPW +python src/retrieve_goes16_product_for_wsois.py --date_ini "2023-06-01" --date_end "2023-12-31" --prod ABI-L2-TPWF --vars TPW + +2) +python src/fuse_goes16_tpw_data_with_wsois.py + +3) python src/retrieve_ws_inmet.py -s A602 -b 2007 -e 2023 --api_token python src/retrieve_ws_inmet.py -s A621 -b 2007 -e 2023 --api_token python src/retrieve_ws_inmet.py -s A627 -b 2018 -e 2023 --api_token python src/retrieve_ws_inmet.py -s A636 -b 2017 -e 2023 --api_token python src/retrieve_ws_inmet.py -s A652 -b 2007 -e 2023 --api_token +4) python src/preprocess_ws.py -s A602 > preprocess_A602.out python src/preprocess_ws.py -s A621 > preprocess_A621.out python src/preprocess_ws.py -s A627 > preprocess_A627.out python src/preprocess_ws.py -s A636 > preprocess_A636.out python src/preprocess_ws.py -s A652 > preprocess_A652.out -python src/build_datasets.py -s A636 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A621 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +5) python src/build_datasets.py -s A602 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A652 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A621 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" python src/build_datasets.py -s A627 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A636 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A652 --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A602 -d T --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A621 -d T --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A627 -d T --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A636 -d T --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" -python src/build_datasets.py -s A652 -d T --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A602 -d TPW --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A621 -d TPW --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A627 -d TPW --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A636 -d TPW --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +python src/build_datasets.py -s A652 -d TPW --train_test_threshold "2021-11-30" --train_start_threshold "2019-12-04" +6) python src/train_model.py -p A602_T -t BINARY_CLASSIFICATION > ./data/goes16/tpw/out_files/train_model_A602_T_LstmNeuralNet.out python src/train_model.py -p A621_T -t BINARY_CLASSIFICATION > ./data/goes16/tpw/out_files/train_model_A621_T_LstmNeuralNet.out python src/train_model.py -p A627_T -t BINARY_CLASSIFICATION > ./data/goes16/tpw/out_files/train_model_A627_T_LstmNeuralNet.out diff --git a/config/environment.yml b/config/environment.yml index 2c87a54e..71a8d38d 100644 --- a/config/environment.yml +++ b/config/environment.yml @@ -1,62 +1,35 @@ name: atmoseer channels: - - pytorch - - anaconda - conda-forge - - defaults dependencies: - - pip - - pip: - - asttokens==2.0.5 - - backcall==0.2.0 - - certifi==2022.9.24 - - charset-normalizer==2.1.1 - - colorama==0.4.5 - - contourpy==1.0.5 - - cycler==0.11.0 - - debugpy==1.6.2 - - decorator==5.1.1 - - entrypoints==0.4 - - executing==0.9.1 - - fonttools==4.37.4 - - idna==3.4 - - ipykernel==6.15.1 - - ipython==8.4.0 - - jedi==0.18.1 - - joblib==1.2.0 - - jupyter-client==7.3.4 - - jupyter-core==4.11.1 - - kiwisolver==1.4.4 - - matplotlib==3.6.1 - - matplotlib-inline==0.1.3 - - metpy==1.4.1 - - nest-asyncio==1.5.5 - - numpy==1.23.2 - - packaging==21.3 - - pandas==1.4.3 - - parso==0.8.3 - - pickleshare==0.7.5 - - pillow==9.2.0 - - prompt-toolkit==3.0.30 - - psutil==5.9.1 - - pure-eval==0.2.2 - - pygments==2.12.0 - - pyparsing==3.0.9 - - python-dateutil==2.8.2 - - pytz==2022.2.1 - - pyzmq==23.2.0 - - requests==2.28.1 - - scikit-learn==1.1.2 - - scipy==1.9.2 - - seaborn==0.12.0 - - six==1.16.0 - - sklearn==0.0 - - stack-data==0.3.0 - - threadpoolctl==3.1.0 - - torch==1.12.1 - - tornado==6.2 - - tqdm==4.64.1 - - traitlets==5.3.0 - - typing_extensions==4.4.0 - - urllib3==1.26.12 - - wcwidth==0.2.5 \ No newline at end of file + - python=3.10 + - folium + - gdal=3.7 + - geopandas + - joblib + - matplotlib + - netcdf4 + - numpy + - pandas + - pillow + - pyarrow + - pyproj + - seaborn + - scikit-learn + - xarray + - rasterio + - s3fs + - scipy + - metpy + - requests + - ipykernel + - pip + - tqdm + - pip: + - black + - boto3 + - pre-commit + - ruff + - torchvision + + diff --git a/config/station_systems/alertario.json b/config/station_systems/alertario.json new file mode 100644 index 00000000..e552948a --- /dev/null +++ b/config/station_systems/alertario.json @@ -0,0 +1,409 @@ +{ + "column_mapping": { + "datetime": "datetime", + "temperature_mean": "temperature", + "humidity_mean": "relative_humidity", + "pressure_mean": "barometric_pressure", + "wind_speed_mean": "wind_speed", + "wind_dir_mean": "wind_dir", + "precipitation_sum": "precipitation" + }, + "features": { + "add_wind_related_features": true, + "add_hour_related_features": true, + "normalize_predictors": true, + "impute_missing_values": true + }, + "predictor_columns": [ + "temperature", + "barometric_pressure", + "relative_humidity", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos" + ], + "target_column": "precipitation", + "stations": { + "alto_da_boa_vista": { + "name": "Alto da Boa Vista", + "state": "RJ", + "status": "Operante", + "latitude": -22.9658, + "longitude": -43.2783, + "altitude_m": null, + "operation_start": null + }, + "anchieta": { + "name": "Anchieta", + "state": "RJ", + "status": "Operante", + "latitude": -22.8269, + "longitude": -43.4033, + "altitude_m": null, + "operation_start": null + }, + "av_brasil_mendanha": { + "name": "Av. Brasil/Mendanha", + "state": "RJ", + "status": "Operante", + "latitude": -22.8569, + "longitude": -43.5411, + "altitude_m": null, + "operation_start": null + }, + "bangu": { + "name": "Bangu", + "state": "RJ", + "status": "Operante", + "latitude": -22.8803, + "longitude": -43.4658, + "altitude_m": null, + "operation_start": null + }, + "barrinha": { + "name": "Barra/Barrinha", + "state": "RJ", + "status": "Operante", + "latitude": -23.0085, + "longitude": -43.2997, + "altitude_m": null, + "operation_start": null + }, + "campo_grande": { + "name": "Campo Grande", + "state": "RJ", + "status": "Operante", + "latitude": -22.9036, + "longitude": -43.5619, + "altitude_m": null, + "operation_start": null + }, + "cidade_de_deus": { + "name": "Jacarepaguá/Cidade de Deus", + "state": "RJ", + "status": "Operante", + "latitude": -22.9456, + "longitude": -43.3628, + "altitude_m": null, + "operation_start": null + }, + "copacabana": { + "name": "Copacabana", + "state": "RJ", + "status": "Operante", + "latitude": -22.9864, + "longitude": -43.1894, + "altitude_m": null, + "operation_start": null + }, + "grajau": { + "name": "Est. Grajaú/Jacarepaguá", + "state": "RJ", + "status": "Operante", + "latitude": -22.9256, + "longitude": -43.3158, + "altitude_m": null, + "operation_start": null + }, + "grande_meier": { + "name": "Grande Méier", + "state": "RJ", + "status": "Operante", + "latitude": -22.8906, + "longitude": -43.2781, + "altitude_m": null, + "operation_start": null + }, + "grota_funda": { + "name": "Grota Funda", + "state": "RJ", + "status": "Operante", + "latitude": -23.0144, + "longitude": -43.5214, + "altitude_m": null, + "operation_start": null + }, + "guaratiba": { + "name": "Guaratiba", + "state": "RJ", + "status": "Operante", + "latitude": -23.0503, + "longitude": -43.5947, + "altitude_m": null, + "operation_start": null + }, + "ilha_do_governador": { + "name": "Ilha do Governador", + "state": "RJ", + "status": "Operante", + "latitude": -22.8181, + "longitude": -43.2103, + "altitude_m": null, + "operation_start": null + }, + "iraja": { + "name": "Irajá", + "state": "RJ", + "status": "Operante", + "latitude": -22.8269, + "longitude": -43.3369, + "altitude_m": null, + "operation_start": null + }, + "jardim_botanico": { + "name": "Jardim Botânico", + "state": "RJ", + "status": "Operante", + "latitude": -22.9728, + "longitude": -43.2239, + "altitude_m": null, + "operation_start": null + }, + "laranjeiras": { + "name": "Laranjeiras", + "state": "RJ", + "status": "Operante", + "latitude": -22.9406, + "longitude": -43.1875, + "altitude_m": null, + "operation_start": null + }, + "madureira": { + "name": "Madureira", + "state": "RJ", + "status": "Operante", + "latitude": -22.8733, + "longitude": -43.3389, + "altitude_m": null, + "operation_start": null + }, + "penha": { + "name": "Penha", + "state": "RJ", + "status": "Operante", + "latitude": -22.8444, + "longitude": -43.2753, + "altitude_m": null, + "operation_start": null + }, + "piedade": { + "name": "Piedade", + "state": "RJ", + "status": "Operante", + "latitude": -22.8918, + "longitude": -43.3101, + "altitude_m": null, + "operation_start": null + }, + "recreio": { + "name": "Recreio dos Bandeirantes", + "state": "RJ", + "status": "Operante", + "latitude": -23.01, + "longitude": -43.4406, + "altitude_m": null, + "operation_start": null + }, + "riocentro": { + "name": "Barra/Riocentro", + "state": "RJ", + "status": "Operante", + "latitude": -22.9772, + "longitude": -43.3916, + "altitude_m": null, + "operation_start": null + }, + "rocinha": { + "name": "Rocinha", + "state": "RJ", + "status": "Operante", + "latitude": -22.9858, + "longitude": -43.245, + "altitude_m": null, + "operation_start": null + }, + "santa_cruz": { + "name": "Santa Cruz", + "state": "RJ", + "status": "Operante", + "latitude": -22.9094, + "longitude": -43.6844, + "altitude_m": null, + "operation_start": null + }, + "santa_teresa": { + "name": "Santa Teresa", + "state": "RJ", + "status": "Operante", + "latitude": -22.9317, + "longitude": -43.1964, + "altitude_m": null, + "operation_start": null + }, + "sao_cristovao": { + "name": "São Cristóvão", + "state": "RJ", + "status": "Operante", + "latitude": -22.8967, + "longitude": -43.2217, + "altitude_m": null, + "operation_start": null + }, + "saude": { + "name": "Saúde", + "state": "RJ", + "status": "Operante", + "latitude": -22.8961, + "longitude": -43.1879, + "altitude_m": null, + "operation_start": null + }, + "sepetiba": { + "name": "Sepetiba", + "state": "RJ", + "status": "Operante", + "latitude": -22.9689, + "longitude": -43.7117, + "altitude_m": null, + "operation_start": null + }, + "tanque": { + "name": "Jacarepaguá/Tanque", + "state": "RJ", + "status": "Operante", + "latitude": -22.9125, + "longitude": -43.3647, + "altitude_m": null, + "operation_start": null + }, + "tijuca": { + "name": "Tijuca", + "state": "RJ", + "status": "Operante", + "latitude": -22.9319, + "longitude": -43.2217, + "altitude_m": null, + "operation_start": null + }, + "tijuca_muda": { + "name": "Tijuca/Muda", + "state": "RJ", + "status": "Operante", + "latitude": -22.9328, + "longitude": -43.2433, + "altitude_m": null, + "operation_start": null + }, + "urca": { + "name": "Urca", + "state": "RJ", + "status": "Operante", + "latitude": -22.9558, + "longitude": -43.1667, + "altitude_m": null, + "operation_start": null + }, + "vidigal": { + "name": "Vidigal", + "state": "RJ", + "status": "Operante", + "latitude": -22.9925, + "longitude": -43.2331, + "altitude_m": null, + "operation_start": null + } + }, + "quality": { + "enabled": true, + "flag_column_suffix": "_flag", + "include_flag_columns": true, + "checks": [ + { + "type": "bounds", + "name": "temperature_physical_limits", + "columns": [ + "temperature" + ], + "min": -60, + "max": 60, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "bounds", + "name": "humidity_range", + "columns": [ + "relative_humidity" + ], + "min": 0, + "max": 100, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "bounds", + "name": "wind_speed_non_negative", + "columns": [ + "wind_speed" + ], + "min": 0, + "max": 70, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "bounds", + "name": "precipitation_non_negative", + "columns": [ + "precipitation" + ], + "min": 0, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "zscore", + "name": "pressure_zscore_outlier", + "columns": [ + "barometric_pressure" + ], + "threshold": 4.0, + "actions": [ + "flag" + ] + } + ] + }, + "preprocessing": { + "scaler": { + "type": "none" + }, + "imputation": { + "strategy": "ffill_then_zero" + } + }, + "report": { + "enabled": true, + "fields": [ + "missing_fraction", + "imputed_fraction", + "min", + "max" + ], + "summary": [ + "rows", + "columns", + "missing_fraction", + "imputed_fraction" + ] + } +} diff --git a/config/station_systems/inmet.json b/config/station_systems/inmet.json new file mode 100644 index 00000000..1ab8c713 --- /dev/null +++ b/config/station_systems/inmet.json @@ -0,0 +1,365 @@ +{ + "column_mapping": { + "datetime": "datetime", + "TEM_MAX": "temperature", + "UMD_MAX": "relative_humidity", + "PRE_MAX": "barometric_pressure", + "VEN_VEL": "wind_speed", + "VEN_DIR": "wind_dir", + "CHUVA": "precipitation" + }, + "features": { + "add_wind_related_features": true, + "add_hour_related_features": true, + "normalize_predictors": true, + "impute_missing_values": true + }, + "predictor_columns": [ + "temperature", + "barometric_pressure", + "relative_humidity", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos" + ], + "target_column": "precipitation", + "stations": { + "A601": { + "name": "SEROPEDICA-ECOLOGIA AGRICOLA", + "state": "RJ", + "status": "Operante", + "latitude": -22.75777777, + "longitude": -43.68472221, + "altitude_m": 35.0, + "operation_start": "2000-05-23" + }, + "A602": { + "name": "RIO DE JANEIRO-MARAMBAIA", + "state": "RJ", + "status": "Operante", + "latitude": -23.05027777, + "longitude": -43.59555555, + "altitude_m": 12.0, + "operation_start": "2002-11-07" + }, + "A603": { + "name": "DUQUE DE CAXIAS - XEREM", + "state": "RJ", + "status": "Operante", + "latitude": -22.58972221, + "longitude": -43.28222221, + "altitude_m": 22.0, + "operation_start": "2002-10-20" + }, + "A604": { + "name": "CAMBUCI", + "state": "RJ", + "status": "Operante", + "latitude": -21.58749999, + "longitude": -41.95833333, + "altitude_m": 46.0, + "operation_start": "2002-11-19" + }, + "A606": { + "name": "ARRAIAL DO CABO", + "state": "RJ", + "status": "Operante", + "latitude": -22.97527777, + "longitude": -42.02138888, + "altitude_m": 5.0, + "operation_start": "2006-09-21" + }, + "A607": { + "name": "CAMPOS DOS GOYTACAZES", + "state": "RJ", + "status": "Operante", + "latitude": -21.71472222, + "longitude": -41.34388888, + "altitude_m": 17.0, + "operation_start": "2006-09-24" + }, + "A608": { + "name": "MACAE", + "state": "RJ", + "status": "Operante", + "latitude": -22.3761111, + "longitude": -41.81194444, + "altitude_m": 28.0, + "operation_start": "2006-09-21" + }, + "A609": { + "name": "RESENDE", + "state": "RJ", + "status": "Operante", + "latitude": -22.45138888, + "longitude": -44.44499999, + "altitude_m": 438.83, + "operation_start": "2006-09-28" + }, + "A610": { + "name": "PICO DO COUTO", + "state": "RJ", + "status": "Operante", + "latitude": -22.46472222, + "longitude": -43.29138888, + "altitude_m": 1777.0, + "operation_start": "2006-10-21" + }, + "A611": { + "name": "VALENCA", + "state": "RJ", + "status": "Operante", + "latitude": -22.35805555, + "longitude": -43.69555555, + "altitude_m": 370.0, + "operation_start": "2006-09-26" + }, + "A618": { + "name": "TERESOPOLIS-PARQUE NACIONAL", + "state": "RJ", + "status": "Operante", + "latitude": -22.4486111, + "longitude": -42.98694444, + "altitude_m": 981.0, + "operation_start": "2006-10-31" + }, + "A619": { + "name": "PARATY", + "state": "RJ", + "status": "Operante", + "latitude": -23.2236111, + "longitude": -44.72694443, + "altitude_m": 3.0, + "operation_start": "2006-11-18" + }, + "A620": { + "name": "CAMPOS DOS GOYTACAZES - SAO TOME", + "state": "RJ", + "status": "Operante", + "latitude": -22.04166666, + "longitude": -41.05166666, + "altitude_m": 7.0, + "operation_start": "2008-06-12" + }, + "A621": { + "name": "RIO DE JANEIRO - VILA MILITAR", + "state": "RJ", + "status": "Operante", + "latitude": -22.86138888, + "longitude": -43.41138888, + "altitude_m": 30.43, + "operation_start": "2007-04-12" + }, + "A624": { + "name": "NOVA FRIBURGO - SALINAS", + "state": "RJ", + "status": "Operante", + "latitude": -22.33472221, + "longitude": -42.67694443, + "altitude_m": 1070.0, + "operation_start": "2010-09-17" + }, + "A625": { + "name": "TRES RIOS", + "state": "RJ", + "status": "Operante", + "latitude": -22.09833333, + "longitude": -43.20833333, + "altitude_m": 295.0, + "operation_start": "2016-06-07" + }, + "A626": { + "name": "RIO CLARO", + "state": "RJ", + "status": "Operante", + "latitude": -22.653579, + "longitude": -44.040916, + "altitude_m": 516.0, + "operation_start": "2016-06-02" + }, + "A627": { + "name": "NITEROI", + "state": "RJ", + "status": "Operante", + "latitude": -22.86749999, + "longitude": -43.10194444, + "altitude_m": 6.0, + "operation_start": "2018-07-12" + }, + "A628": { + "name": "ANGRA DOS REIS", + "state": "RJ", + "status": "Operante", + "latitude": -22.97555554, + "longitude": -44.30333333, + "altitude_m": 6.0, + "operation_start": "2017-08-24" + }, + "A629": { + "name": "CARMO", + "state": "RJ", + "status": "Operante", + "latitude": -21.938745, + "longitude": -42.600936, + "altitude_m": 293.0, + "operation_start": "2018-10-10" + }, + "A630": { + "name": "SANTA MARIA MADALENA", + "state": "RJ", + "status": "Operante", + "latitude": -21.95055555, + "longitude": -42.01027777, + "altitude_m": 517.0, + "operation_start": "2018-10-15" + }, + "A636": { + "name": "RIO DE JANEIRO - JACAREPAGUA", + "state": "RJ", + "status": "Operante", + "latitude": -22.93999999, + "longitude": -43.40277777, + "altitude_m": 20.0, + "operation_start": "2017-08-09" + }, + "A637": { + "name": "Paty do Alferes - Avelar", + "state": "RJ", + "status": "Operante", + "latitude": -22.34722221, + "longitude": -43.41777777, + "altitude_m": 508.0, + "operation_start": "2022-11-09" + }, + "A652": { + "name": "RIO DE JANEIRO - FORTE DE COPACABANA", + "state": "RJ", + "status": "Operante", + "latitude": -22.98833333, + "longitude": -43.19055555, + "altitude_m": 25.59, + "operation_start": "2007-05-17" + }, + "A659": { + "name": "SILVA JARDIM", + "state": "RJ", + "status": "Operante", + "latitude": -22.64583333, + "longitude": -42.41555555, + "altitude_m": 19.0, + "operation_start": "2015-08-27" + }, + "A667": { + "name": "SAQUAREMA - SAMPAIO CORREIA", + "state": "RJ", + "status": "Operante", + "latitude": -22.8711111, + "longitude": -42.60888888, + "altitude_m": 26.0, + "operation_start": "2015-09-01" + } + }, + "quality": { + "enabled": true, + "flag_column_suffix": "_flag", + "include_flag_columns": true, + "checks": [ + { + "type": "bounds", + "name": "temperature_physical_limits", + "columns": [ + "temperature" + ], + "min": -60, + "max": 60, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "bounds", + "name": "humidity_range", + "columns": [ + "relative_humidity" + ], + "min": 0, + "max": 100, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "bounds", + "name": "wind_speed_non_negative", + "columns": [ + "wind_speed" + ], + "min": 0, + "max": 80, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "bounds", + "name": "precipitation_non_negative", + "columns": [ + "precipitation" + ], + "min": 0, + "actions": [ + "clip", + "flag" + ] + }, + { + "type": "iqr", + "name": "pressure_outlier_iqr", + "columns": [ + "barometric_pressure" + ], + "k": 3.0, + "actions": [ + "flag" + ] + } + ] + }, + "preprocessing": { + "scaler": { + "type": "minmax", + "params": { + "feature_range": [ + 0, + 1 + ] + } + }, + "imputation": { + "strategy": "knn", + "params": { + "n_neighbors": 2, + "weights": "uniform" + } + } + }, + "report": { + "enabled": true, + "fields": [ + "missing_fraction", + "imputed_fraction", + "min", + "max" + ], + "summary": [ + "rows", + "columns", + "missing_fraction", + "imputed_fraction" + ] + } +} diff --git a/config/station_systems/websirene.json b/config/station_systems/websirene.json new file mode 100644 index 00000000..3338dede --- /dev/null +++ b/config/station_systems/websirene.json @@ -0,0 +1,68 @@ +{ + "column_mapping": { + "datetime": "datetime", + "chuvas": "precipitation" + }, + "features": { + "add_wind_related_features": false, + "add_hour_related_features": true, + "normalize_predictors": true, + "impute_missing_values": true + }, + "predictor_columns": [ + "precipitation", + "hour_sin", + "hour_cos" + ], + "target_column": "precipitation", + "stations": { + "22": { + "name": "VIDIGAL", + "state": "RJ", + "status": "Operational", + "latitude": -22.9904, + "longitude": -43.2405, + "altitude_m": 100.0, + "operation_start": "2000-01-01" + }, + "34": { + "name": "ROCINHA", + "state": "RJ", + "status": "Operational", + "latitude": 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Unnamed: 0DC_NOMESG_ESTADOCD_SITUACAOVL_LATITUDEVL_LONGITUDEVL_ALTITUDEDT_INICIO_OPERACAOSTATION_D
023ANGRA DOS REISRJOperante-22.975556-44.303333624/08/2017A628
141ARRAIAL DO CABORJOperante-22.975278-42.021389521/09/2006A606
297CAMBUCIRJOperante-21.587500-41.9583334619/11/2002A604
3108CAMPOS DOS GOYTACAZESRJOperante-21.714722-41.3438891724/09/2006A607
4109CAMPOS DOS GOYTACAZES - SAO TOMERJOperante-22.041667-41.051667712/06/2008A620
5124CARMORJOperante-21.938745-42.60093629310/10/2018A629
6178DUQUE DE CAXIAS - XEREMRJOperante-22.589722-43.2822222220/10/2002A603
7292MACAERJOperante-22.376111-41.8119442821/09/2006A608
8335NITEROIRJOperante-22.867500-43.101944612/07/2018A627
9338NOVA FRIBURGO - SALINASRJOperante-22.334722-42.676944107017/09/2010A624
10365PARATYRJOperante-23.223611-44.726944318/11/2006A619
11381PICO DO COUTORJOperante-22.464722-43.291389177721/10/2006A610
12413Paty do Alferes - AvelarRJOperante-22.347222-43.41777850809/11/2022A637
13425RESENDERJOperante-22.451389-44.445000438,8328/09/2006A609
14429RIO CLARORJOperante-22.653579-44.04091651602/06/2016A626
15430RIO DE JANEIRO - FORTE DE COPACABANARJOperante-22.988333-43.19055625,5917/05/2007A652
16431RIO DE JANEIRO - JACAREPAGUARJOperante-22.940000-43.4027782009/08/2017A636
17432RIO DE JANEIRO - VILA MILITARRJOperante-22.861389-43.41138930,4312/04/2007A621
18433RIO DE JANEIRO-MARAMBAIARJOperante-23.050278-43.5955561207/11/2002A602
19458SANTA MARIA MADALENARJOperante-21.950556-42.01027851715/10/2018A630
20498SAQUAREMA - SAMPAIO CORREIARJOperante-22.871111-42.6088892601/09/2015A667
21501SEROPEDICA-ECOLOGIA AGRICOLARJOperante-22.757778-43.6847223523/05/2000A601
22510SILVA JARDIMRJOperante-22.645833-42.4155561927/08/2015A659
23526TERESOPOLIS-PARQUE NACIONALRJOperante-22.448611-42.98694498131/10/2006A618
24535TRES RIOSRJOperante-22.098333-43.20833329507/06/2016A625
25550VALENCARJOperante-22.358056-43.69555637026/09/2006A611
\n", - "
" - ], - "text/plain": [ - " Unnamed: 0 DC_NOME SG_ESTADO CD_SITUACAO \\\n", - "0 23 ANGRA DOS REIS RJ Operante \n", - "1 41 ARRAIAL DO CABO RJ Operante \n", - "2 97 CAMBUCI RJ Operante \n", - "3 108 CAMPOS DOS GOYTACAZES RJ Operante \n", - "4 109 CAMPOS DOS GOYTACAZES - SAO TOME RJ Operante \n", - "5 124 CARMO RJ Operante \n", - "6 178 DUQUE DE CAXIAS - XEREM RJ Operante \n", - "7 292 MACAE RJ Operante \n", - "8 335 NITEROI RJ Operante \n", - "9 338 NOVA FRIBURGO - SALINAS RJ Operante \n", - "10 365 PARATY RJ Operante \n", - "11 381 PICO DO COUTO RJ Operante \n", - "12 413 Paty do Alferes - Avelar RJ Operante \n", - "13 425 RESENDE RJ Operante \n", - "14 429 RIO CLARO RJ Operante \n", - "15 430 RIO DE JANEIRO - FORTE DE COPACABANA RJ Operante \n", - "16 431 RIO DE JANEIRO - JACAREPAGUA RJ Operante \n", - "17 432 RIO DE JANEIRO - VILA MILITAR RJ Operante \n", - "18 433 RIO DE JANEIRO-MARAMBAIA RJ Operante \n", - "19 458 SANTA MARIA MADALENA RJ Operante \n", - "20 498 SAQUAREMA - SAMPAIO CORREIA RJ Operante \n", - "21 501 SEROPEDICA-ECOLOGIA AGRICOLA RJ Operante \n", - "22 510 SILVA JARDIM RJ Operante \n", - "23 526 TERESOPOLIS-PARQUE NACIONAL RJ Operante \n", - "24 535 TRES RIOS RJ Operante \n", - "25 550 VALENCA RJ Operante \n", - "\n", - " VL_LATITUDE VL_LONGITUDE VL_ALTITUDE DT_INICIO_OPERACAO STATION_D \n", - "0 -22.975556 -44.303333 6 24/08/2017 A628 \n", - "1 -22.975278 -42.021389 5 21/09/2006 A606 \n", - "2 -21.587500 -41.958333 46 19/11/2002 A604 \n", - "3 -21.714722 -41.343889 17 24/09/2006 A607 \n", - "4 -22.041667 -41.051667 7 12/06/2008 A620 \n", - "5 -21.938745 -42.600936 293 10/10/2018 A629 \n", - "6 -22.589722 -43.282222 22 20/10/2002 A603 \n", - "7 -22.376111 -41.811944 28 21/09/2006 A608 \n", - "8 -22.867500 -43.101944 6 12/07/2018 A627 \n", - "9 -22.334722 -42.676944 1070 17/09/2010 A624 \n", - "10 -23.223611 -44.726944 3 18/11/2006 A619 \n", - "11 -22.464722 -43.291389 1777 21/10/2006 A610 \n", - "12 -22.347222 -43.417778 508 09/11/2022 A637 \n", - "13 -22.451389 -44.445000 438,83 28/09/2006 A609 \n", - "14 -22.653579 -44.040916 516 02/06/2016 A626 \n", - "15 -22.988333 -43.190556 25,59 17/05/2007 A652 \n", - "16 -22.940000 -43.402778 20 09/08/2017 A636 \n", - "17 -22.861389 -43.411389 30,43 12/04/2007 A621 \n", - "18 -23.050278 -43.595556 12 07/11/2002 A602 \n", - "19 -21.950556 -42.010278 517 15/10/2018 A630 \n", - "20 -22.871111 -42.608889 26 01/09/2015 A667 \n", - "21 -22.757778 -43.684722 35 23/05/2000 A601 \n", - "22 -22.645833 -42.415556 19 27/08/2015 A659 \n", - "23 -22.448611 -42.986944 981 31/10/2006 A618 \n", - "24 -22.098333 -43.208333 295 07/06/2016 A625 \n", - "25 -22.358056 -43.695556 370 26/09/2006 A611 " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "df = pd.read_csv(\"../data/ws/INMET_WS_Stations.csv\")\n", - "df.head(30)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "97055fd9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[1448.5144720223163, 6854.21376278946, 1366.5493798571713]\n" - ] - } - ], - "source": [ - "from math import radians, sin, cos, sqrt, atan2\n", - "\n", - "def haversine_distance(point1, point2):\n", - " R = 6371 # Earth's radius in kilometers\n", - " lat1, lon1 = point1\n", - " lat2, lon2 = point2\n", - " dlat = radians(lat2 - lat1)\n", - " dlon = radians(lon2 - lon1)\n", - " a = sin(dlat / 2) ** 2 + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) ** 2\n", - " c = 2 * atan2(sqrt(a), sqrt(1 - a))\n", - " distance = R * c\n", - " return distance\n", - "\n", - "def distance_matrix(point, points_list):\n", - " matrix = []\n", - " for p in points_list:\n", - " distance = haversine_distance(point, p)\n", - " matrix.append(distance)\n", - " return matrix\n", - "\n", - "point = (52.2296756, 21.0122287) # Warsaw, Poland\n", - "points_list = [(51.5073509, -0.1277583), # London, UK\n", - " (40.7127281, -74.0060152), # New York City, USA\n", - " (48.856614, 2.3522219)] # Paris, France\n", - "\n", - "matrix = distance_matrix(point, points_list)\n", - "print(matrix) # output: [1464.580386325907, 6698.945740763303, 1319.1667457437978]\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "e70db946", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Distances from A652 to all other INMET weather stations located in RJ:\n", - "113.92\t ANGRA DOS REIS\n", - "119.70\t ARRAIAL DO CABO\n", - "200.84\t CAMBUCI\n", - "236.90\t CAMPOS DOS GOYTACAZES\n", - "243.62\t CAMPOS DOS GOYTACAZES - SAO TOME\n", - "131.50\t CARMO\n", - " 45.31\t DUQUE DE CAXIAS - XEREM\n", - "156.97\t MACAE\n", - " 16.21\t NITEROI\n", - " 89.78\t NOVA FRIBURGO - SALINAS\n", - "159.30\t PARATY\n", - " 59.13\t PICO DO COUTO\n", - " 75.00\t Paty do Alferes - Avelar\n", - "141.84\t RESENDE\n", - " 94.77\t RIO CLARO\n", - " 0.00\t RIO DE JANEIRO - FORTE DE COPACABANA\n", - " 22.38\t RIO DE JANEIRO - JACAREPAGUA\n", - " 26.66\t RIO DE JANEIRO - VILA MILITAR\n", - " 42.02\t RIO DE JANEIRO-MARAMBAIA\n", - "167.40\t SANTA MARIA MADALENA\n", - " 60.98\t SAQUAREMA - SAMPAIO CORREIA\n", - " 56.75\t SEROPEDICA-ECOLOGIA AGRICOLA\n", - " 88.09\t SILVA JARDIM\n", - " 63.54\t TERESOPOLIS-PARQUE NACIONAL\n", - " 98.98\t TRES RIOS\n", - " 87.16\t VALENCA\n" - ] - } - ], - "source": [ - "A652_Latitude = -22.98833333\n", - "A652_Longitude = -43.19055555\n", - "A652_point = (A652_Latitude, A652_Longitude)\n", - "\n", - "print(\"Distances from A652 to all other INMET weather stations located in RJ:\")\n", - "for index, row in df.iterrows():\n", - " longitude = row['VL_LONGITUDE']\n", - " latitude = row['VL_LATITUDE']\n", - " ws_name = row['DC_NOME']\n", - " ws_name = row['STATION_ID']\n", - " ws_point = (latitude, longitude)\n", - " dist = haversine_distance(A652_point, ws_point)\n", - " print(f\"{dist:6.2f}\\t {ws_name}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "8338b9ee", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Distances from SBGL to INMET weather stations located in RJ:\n" - ] - }, - { - "ename": "AttributeError", - "evalue": "'float' object has no attribute 'replace'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[11], line 7\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDistances from SBGL to INMET weather stations located in RJ:\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m index, row \u001b[38;5;129;01min\u001b[39;00m df\u001b[38;5;241m.\u001b[39miterrows():\n\u001b[0;32m----> 7\u001b[0m longitude \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mfloat\u001b[39m(\u001b[43mrow\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mVL_LONGITUDE\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreplace\u001b[49m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m'\u001b[39m))\n\u001b[1;32m 8\u001b[0m latitude \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mfloat\u001b[39m(row[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mVL_LATITUDE\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m,\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m'\u001b[39m))\n\u001b[1;32m 9\u001b[0m ws_name \u001b[38;5;241m=\u001b[39m row[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDC_NOME\u001b[39m\u001b[38;5;124m'\u001b[39m]\n", - "\u001b[0;31mAttributeError\u001b[0m: 'float' object has no attribute 'replace'" - ] - } - ], - "source": [ - "gig_Latitude = -22.809167\n", - "gig_Longitude = -43.250556\n", - "gig_point = (gig_Latitude, gig_Longitude)\n", - "\n", - "print(\"Distances from SBGL to INMET weather stations located in RJ:\")\n", - "for index, row in df.iterrows():\n", - " longitude = float(row['VL_LONGITUDE'].replace(',','.'))\n", - " latitude = float(row['VL_LATITUDE'].replace(',','.'))\n", - " ws_name = row['DC_NOME']\n", - " ws_point = (latitude, longitude)\n", - " dist = haversine_distance(gig_point, ws_point)\n", - " print(f\"{dist}\\t {ws_name}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2121492e", - "metadata": {}, - "outputs": [], - "source": [ - "df[['CD_ESTACAO', 'DC_NOME', 'DT_INICIO_OPERACAO']]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d13bfd62", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "df_A621 = pd.read_csv(\"../data/ws/A621.csv\")\n", - "df_A621.info()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ad5781b4", - "metadata": {}, - "outputs": [], - "source": [ - "df_A621[df_A621.CHUVA>=5].shape, df_A621[df_A621.CHUVA>=25].shape, df_A621[df_A621.CHUVA>=50].shape" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.9" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/.ipynb_checkpoints/ie01-checkpoint.ipynb b/notebooks/.ipynb_checkpoints/ie01-checkpoint.ipynb deleted file mode 100644 index f1390f5b..00000000 --- a/notebooks/.ipynb_checkpoints/ie01-checkpoint.ipynb +++ /dev/null @@ -1,871 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Qd5xVRuUJ8E2" - }, - "source": [ - "# Conceitos básicos da Inferência Estatística" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "W1G8GZXCKAWO" - }, - "source": [ - "\n", - "## População e amostra\n", - "\n", - "\n", - "* **População** (*population*) é a totalidade de elementos ou resultados (escores, pessoas, medidas, etc) que estão sob discussão e dos quais se deseja inferir alguma informação. Na Estatística, o termo \"população\" tem um significado ligeiramente diferente daquele que lhe é atribuído no discurso comum. Não precisa se referir apenas a pessoas ou a outros seres vivos - a população da Grã-Bretanha, por exemplo, ou a população de cães de Londres. Os estatísticos também usam o termo população para denotar coleções de objetos, eventos ou procedimentos ou observações, incluindo coisas como as quantidades de colesterol medidas no sangue de um grupo de indivíduos, visitas ao médico ou operações cirúrgicas.\n", - "\n", - "\n", - "* **Amostra** (*sample*) é qualquer subconjunto de uma população. Dado um inteiro positivo $n$, uma amostra corresponde aos resultados de $n$ experimentos nos quais a mesma quantidade é medida. Por exemplo, se queremos estimar a altura média dos membros de uma determinada população, inicialmente medimos a altura de $n$ indivíduos.\n", - "\n", - "

\n", - " \n", - "

\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "i25MHZRXKX3H" - }, - "source": [ - "População e amostra (exemplo 01) - Considere uma escola de 5.000 alunos. Se quisermos fazer um estudo das estaturas (e.g., qual a estatura média?), podemos colher uma amostra de, digamos, 40 alunos e estudar o comportamento da **varíavel estatura** apenas nesses alunos. A variável a ser estudada poderia ser inteligência, número de irmãos, número de cáries, notas em história ou renda familiar, dentre outras.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cdp3rGP-PdnZ" - }, - "source": [ - "## Parâmetros versus estatísticas\n", - "\n", - "\n", - "* Um **parâmetro** é uma medida usada para descrever uma característica de uma população. É uma medida numérica, normalmente não observável, que descreve uma característica de uma população.\n", - "\n", - "\n", - "* Uma **estatística amostral** (ou simplesmente **estatística**) é alguma função computada a partir de uma amostra. Uma estatística é uma variável aleatória, pois seus valores são resultantes de alguma computação realizada sobre amostras aleatórias retiradas de uma população.\n", - "\n", - "Um parâmetro está para uma população assim como uma estatística está para uma amostra.\n", - "\n", - "Por exemplo, considere a porcentagem de eleitores de uma população que preferem um determinado candidato. Essa porcentagem é um exemplo de parâmetro populacional. Note que é (na maioria dos casos) impraticável perguntar a todos os eleitores da população quais são suas preferências de candidato. Sendo assim, uma amostra de eleitores pode ser consultada e uma estatística (nesse caso, a porcentagem dos eleitores que preferiram cada candidato) pode ser computada. Essa estatística pode então ser usada como um estimativa do parâmetro populacional.\n", - "\n", - "Da mesma forma, em algumas formas de teste de produtos fabricados, em vez de testar destrutivamente todos os produtos, apenas uma amostra de produtos é testada. Esses testes reúnem informações que permitem estimar qual a proporção de produtos fabricados que atende ou às especificações mínimas.\n", - "\n", - "> Repare que enquanto um parâmetro é um valor numérico, uma estatística é uma variável aleatória.\n", - "\n", - "Para entender isso, considere o experimento aleatório de produzir uma amostra aleatória de tamanho $n$ a partir de uma população. Podemos interpretar cada amostra (i.e., cada resultado da realização do experimento aleatório) como um elemento do espaço amostral correspondente a todas as possíveis amostras de tamanho $n$ dessa população. Se por definição cada valor de uma eatatística é uma função dos valores contidos na amostra aleatória correspondente, então faz sentido dizer que uma estatística é uma variável aleatória." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yXXc0W14PfJM" - }, - "source": [ - "Alguns exemplos de parâmetros e suas notações:\n", - "\n", - "* $\\mu$: média populacional,\n", - "* $\\sigma^2$: variância populacional,\n", - "* $\\sigma$: desvio-padrão populacional,\n", - "* $p$: proporção populacional.\n", - "\n", - "\n", - "Seguem alguns exemplos de estatísticas com suas respectivas notações mais usuais (em todos os exemplos $n$ é o tamanho da amostra):\n", - "\n", - "* **média amostral** (*sample mean*, *empirical mean*):\n", - "$$\n", - "\t\t\\overline{x} = \\frac{1}{n}(x_1 + x_2 + \\ldots + x_n)\n", - "$$\n", - "* **variância amostral** (sample variance):\n", - "$$\n", - "\t\ts^2 = \\frac{1}{n-1} \\sum_{i}(x_i - \\overline{x})^2\n", - "$$\n", - "\n", - "* **desvio padrão amostral** (sample standard deviation):\n", - "$$\n", - "\t\ts = \\sqrt{s^2}\n", - "$$\n", - "\n", - "* Considere que $k$ é a quantidade de indivíduos na amostra que possuem uma dada característica de interesse (sendo assim, $n-k$ indivíduos dessa amostra não possuem essas caracterísica). A **proporção amostral** (sample proportion) é uma estatística dada por:\n", - "\n", - "$$\n", - "\t\t\\widehat{p} = \\frac{k}{n}\n", - "$$\n", - "\n", - "Repare que os valores de cada uma das estatísticas acima são computados sobre amostras aleatórias de tamanho fixo $n$. De fato, cada uma dessas estatísticas é uma função que mapeia elementos de $\\Re^n$ em $\\Re$.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0p-MiOJkL45N" - }, - "source": [ - "## Objetivo da Inferência Estatística" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e1nrVssHLVHF" - }, - "source": [ - "> O objetivo da Inferência Estatística é produzir afirmações sobre dada **característica** dos elementos de uma população, com base nos dados contidos em uma ou mais amostras dessa população.\n", - "\n", - "A característica sob estudo pode ser representada por uma variável aleatória, que possui uma determinada distribuição de probabilidades com determinado conjunto de parâmetros. Seguem alguns exemplos:\n", - "\n", - "1. A altura dos indivíduos de uma determinada população é uma característica que pode ser modelada por meio da [distribuição normal](https://en.wikipedia.org/wiki/Normal_distribution) com média $\\mu=1.65$ m e variância $\\sigma^2 = 0.2$ $m^2$.\n", - "\n", - "2. O tempo de atendimento em um quiosque pode ser modelado por uma [distribuição exponencial](https://en.wikipedia.org/wiki/Exponential_distribution) com média $\\lambda = 5$ minutos.\n", - "\n", - "3. A quantidade de defeitos em cada peça produzida em um processo industrial segue uma [distribuição de Poisson](https://en.wikipedia.org/wiki/Poisson_distribution), com média igual a $\\lambda = 0.8$.\n", - "\n", - "Repare que cada um dos exemplos acima presupõe que foi feito um estudo para (1) identificar a distribuição de probabilidades (normal, exponencial, Poisson, etc) mais adequada para o problema em questão e (2) identificar a combinação de parâmetros mais adequada para aquela distribuição.\n", - "\n", - "Quando a função de massa de probabilidade (no caso discreto) ou a função de densidade de probabilidade (no caso contínuo) da variável aleatória é conhecida, o problema de fazer afirmações sobre a população está resolvido. Ocorre que muitas vezes não sabemos nada sobre a variável ou essa informação é parcial. Por exemplo, no caso das alturas dos indivíduos de uma população, podemos presumir que elas sigam uma distribuição normal, mas em geral desconhecemos os parâmetros que a caracterizam (e.g., média e variância).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YFLiNSCCM59t" - }, - "source": [ - "Em geral, pode acontecer de\n", - "\n", - "*\ttermos uma ideia de qual deve ser a distribuição de probabilidades adequada, mas desconhecermos os valores dos parâmetros dessa distribuição.\n", - "*\tconhecermos os valores dos parâmetros, mas desconhecermos a distribuição de probabilidades.\n", - "*\tnão conhecermos nem a distribuição de probabilidades nem os respectivos valores dos parâmetros.\n", - "\n", - "Em qualquer caso, o uso de uma amostra pode nos revelar informações sobre o comportamento da variável sob estudo na população." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "blSKWnohNBH0" - }, - "source": [ - "## Problemas alvos da Inferência Estatística" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lRHRosMhNEgo" - }, - "source": [ - "As técnicas da Inferência Estatística podem ser divididas em duas grandes famílias:\n", - "\n", - "**Estimação de parâmetros**\n", - "> Conjunto de técnicas para **construir uma estimativa** para um parâmetro de uma população por meio de observações de uma amostra.\n", - "\n", - "**Teste de hipóteses**\n", - "> Conjunto de técnicas para **verificar alguma alegação** acerca do parâmetro de uma população por meio de observações de um ou mais amostras.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bYxtW5OGNLdl" - }, - "source": [ - "## Planos Amostrais\n", - "\n", - "Dada uma população finita de tamanho $N$, a quantidade de amostras de tamanho $n$ que podem ser formadas a partir dessa população é\n", - "$$\n", - "\\binom{N}{n} = \\frac{N!}{n!(N-n)!}\n", - "$$\n", - "\n", - "Um **plano amostral** é uma forma de produzir amostras a partir de uma população. Existem inúmeros planos amostrais. Alguns planos amostrais são:\n", - "\n", - "* Amostragem aleatória sistemática\n", - "* Amostragem aleatória estratificada\n", - "* Amostragem aleatória simples" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Uf0eMpxeNkK-" - }, - "source": [ - "### Amostragem aleatória sistemática\n", - "\n", - "Os itens ou indivíduos da população são ordenados de alguma forma - alfabeticamente ou por meio de algum outro método. Um ponto de partida aleatório é sorteado, e então cada $k$-ésimo membro da população é selecionado para a amostra. A varrecura sobre a lista ordenada é realizada de forma circular.\n", - "\n", - "

\n", - " \n", - "

\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZyxieVkfNrgr" - }, - "source": [ - "### Amostragem aleatória estratificada\n", - "\n", - "A população é inicialmente dividida em subgrupos (estratos) e uma subamostra é selecionada a partir de cada estrato da população. O objetivo é fazer com a amostra resultante contenha proporções similares dos diferentes subgrupos da população.\n", - "\n", - "

\n", - " \n", - "

\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jWCoLscvNz_G" - }, - "source": [ - "### Amostragem aleatória simples (AAS)\n", - "\n", - "Na AAS, cada amostra é escolhida de tal forma que cada elemento da população tem a mesma probabilidade de ser selecionado. Dessa forma, se a população tem tamanho $N$, cada elemento dessa população tem a mesma probabilidade igual a $1/N$ de entrar na amostra.\n", - "\n", - "

\n", - " \n", - "

" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bS2H8yH4O1SZ" - }, - "source": [ - "Uma AAS pode ser recolhida *com reposição* ou *sem reposição*.\n", - "\n", - "* Quando a amostra é recolhida com reposição, cada elemento eventualmente selecionado pode ser selecionado novamente.\n", - "\n", - "* Quando a amostra é recolhida sem reposição, não há independência entre os elementos, fato que tem impacto na fórmula do cálculo das estimativas feito a partir dessa amostra." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UxwX0zBaMMOT" - }, - "source": [ - "### Geração de amostras com Pandas\n", - "\n", - "Amostras podem ser geradas por meio da biblioteca Pandas no Python. Em particular a função [sample](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sample.html) permite gerar amostras aleatórias de acordo com diferentes planos amostrais.\n", - "\n", - "Para ilustrar produção de amostras por meio de vários planos amostrais, vamos supor que a população corresponde aos elementos de um conjunto de dados que registra alegações de avistamentos de OVNIs. Esse conjunto de dados é publicamente disponível no portal [Kaggle](https://www.kaggle.com/NUFORC/ufo-sightings). Esse conjunto contém vários atributos, dentre os quais:\n", - "\n", - "- $\\texttt{datetime}$ - momento do avistamento, no formato MM/DD/AAAA HH:mm.\n", - "- $\\texttt{city}$ - A localização do avistamento do OVNI.\n", - "- $\\texttt{state}$ - o estado (unidade federativa) do avistamento.\n", - "- $\\texttt{country}$ - o país do avistamento.\n", - "- $\\texttt{shape}$ - a forma do OVNI visto.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 576 - }, - "id": "vgyVsIrXnu6s", - "outputId": "feb020a1-56c2-4969-cc02-84f253ca1504" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (5,9) have mixed types.Specify dtype option on import or set low_memory=False.\n", - " interactivity=interactivity, compiler=compiler, result=result)\n" - ] - }, - { - "data": { - "text/html": [ - "
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datetimecitystatecountryshapeduration (seconds)duration (hours/min)commentsdate postedlatitudelongitude
010/10/1949 20:30san marcostxuscylinder270045 minutesThis event took place in early fall around 194...4/27/200429.8830556-97.941111
110/10/1949 21:00lackland afbtxNaNlight72001-2 hrs1949 Lackland AFB&#44 TX. Lights racing acros...12/16/200529.38421-98.581082
210/10/1955 17:00chester (uk/england)NaNgbcircle2020 secondsGreen/Orange circular disc over Chester&#44 En...1/21/200853.2-2.916667
310/10/1956 21:00ednatxuscircle201/2 hourMy older brother and twin sister were leaving ...1/17/200428.9783333-96.645833
410/10/1960 20:00kaneohehiuslight90015 minutesAS a Marine 1st Lt. flying an FJ4B fighter/att...1/22/200421.4180556-157.803611
\n", - "
" - ], - "text/plain": [ - " datetime city ... latitude longitude \n", - "0 10/10/1949 20:30 san marcos ... 29.8830556 -97.941111\n", - "1 10/10/1949 21:00 lackland afb ... 29.38421 -98.581082\n", - "2 10/10/1955 17:00 chester (uk/england) ... 53.2 -2.916667\n", - "3 10/10/1956 21:00 edna ... 28.9783333 -96.645833\n", - "4 10/10/1960 20:00 kaneohe ... 21.4180556 -157.803611\n", - "\n", - "[5 rows x 11 columns]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "\n", - "link = 'scrubbed.csv'\n", - "ufo_df = pd.read_csv(link, encoding='utf8') # dataframe\n", - "\n", - "ufo_df.head(12)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kDxNG1Ox6_Nc" - }, - "source": [ - "Podemos primeiro inspecionar os detalhes dos atributos desse conjunto de dados." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "YfNQLfSf7A4E", - "outputId": "08252021-910a-46ff-877c-6de68c3602bd" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 80332 entries, 0 to 80331\n", - "Data columns (total 11 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 datetime 80332 non-null object \n", - " 1 city 80332 non-null object \n", - " 2 state 74535 non-null object \n", - " 3 country 70662 non-null object \n", - " 4 shape 78400 non-null object \n", - " 5 duration (seconds) 80332 non-null object \n", - " 6 duration (hours/min) 80332 non-null object \n", - " 7 comments 80317 non-null object \n", - " 8 date posted 80332 non-null object \n", - " 9 latitude 80332 non-null object \n", - " 10 longitude 80332 non-null float64\n", - "dtypes: float64(1), object(10)\n", - "memory usage: 6.7+ MB\n" - ] - } - ], - "source": [ - "ufo_df.info()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "sLVgJzzKn5DN", - "outputId": "91ae872f-89aa-428c-8897-d4516b8ebba0" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(80332, 11)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ufo_df.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ArEZtHuYl0jk" - }, - "source": [ - "#### Amostragem aleatória sistemática\n", - "\n", - "Agora podemos gerar uma amostra aleatória sistemática de tamanho $n=100$. Vamos realizar essa geração usando um deslocamento entre amostras igual a $5$." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "EeX4E6GKl05t", - "outputId": "ff69f4cb-499e-44f7-ac8a-f5ca39d37307" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(16067, 11)\n" - ] - }, - { - "data": { - "text/plain": [ - "(100, 11)" - ] - }, - "execution_count": 88, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = 100\n", - "deslocamento = 5\n", - "\n", - "sys_sample_df = ufo_df.iloc[::deslocamento]\n", - "\n", - "print(sys_sample_df.shape)\n", - "\n", - "amostra = sys_sample_df.head(n)\n", - "\n", - "amostra.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sisqtA3f9IvY" - }, - "source": [ - "#### Amostragem aleatória simples\n", - "\n", - "Agora podemos retirar uma amostra aleatória simples de, digamos, tamanho igual a 100:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 610 - }, - "id": "ipUkWkWZoU8u", - "outputId": "567956a9-87f1-4f2f-8c74-a96a09f22ac4" - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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datetimecitystatecountryshapeduration (seconds)duration (hours/min)commentsdate postedlatitudelongitude
347473/5/1995 12:00anaheimcausother90015 minutesIn March of 1995 returning from St. Joseph Hos...10/31/200333.8352778-117.913611
2065612/26/1997 21:35bonhamtxusunknown1802 to 3 minutesRed object moving west to east&#44 person look...3/7/199833.5772222-96.178056
744259/14/2010 22:00fentonmousfireball36001 hour or morebright flickering red lights orbitting around ...4/3/201138.5131-90.435833
686878/2/2012 21:30oregon cityorusfireball1803 minutesSaw nine fireballs flying in the sky from the ...10/30/201245.3575-122.605556
378924/20/2000 21:00melbourne (vic&#44 australia)NaNaulight3005 minutesA drifting flashing glow of orange&#44 which w...4/26/2000-37.813938144.963425
\n", - "
" - ], - "text/plain": [ - " datetime city ... latitude longitude \n", - "34747 3/5/1995 12:00 anaheim ... 33.8352778 -117.913611\n", - "20656 12/26/1997 21:35 bonham ... 33.5772222 -96.178056\n", - "74425 9/14/2010 22:00 fenton ... 38.5131 -90.435833\n", - "68687 8/2/2012 21:30 oregon city ... 45.3575 -122.605556\n", - "37892 4/20/2000 21:00 melbourne (vic, australia) ... -37.813938 144.963425\n", - "\n", - "[5 rows x 11 columns]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "amostra = ufo_df.sample(n = 100)\n", - "amostra.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "bU5JbgIXBmqb", - "outputId": "cd364fb0-f23f-4da9-eb9e-efdf9d7efc39" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(100, 11)" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "amostra.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kR7ixymoKpi8" - }, - "source": [ - "#### Amostragem aleatória estratificada\n", - "\n", - "Vamos usar o código acima para produzir uma amostra aleatória estratificada levando em consideração o atributo `country`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 282 - }, - "id": "5Pqpxwl5rJUm", - "outputId": "b15c8288-b6df-44f6-9764-df0af16ed624" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "ufo_df.country.hist()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OIxv2nKCqXnT" - }, - "outputs": [], - "source": [ - "sample_df = ufo_df.groupby('country').apply(lambda x: x.sample(frac=0.1))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 282 - }, - "id": "FoY5wzatwcfO", - "outputId": "a8e9dc93-a918-474f-e2f3-3d07d31adf7a" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 85, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sample_df.country.hist()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2gSWVrOoLRpa" - }, - "source": [ - "Podemos nos certificar de que a amostra produzida realmente mantém as proporções de países existente na população." - ] - } - ], - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.9" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/notebooks/DSIF.ipynb b/notebooks/DSIF.ipynb deleted file mode 100644 index b10bf4a3..00000000 --- a/notebooks/DSIF.ipynb +++ /dev/null @@ -1,501 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 38, - "metadata": {}, - "outputs": [], - "source": [ - "# %load ../src/goes16_utils.py\n", - "# Training: Python and GOES-R Imagery: Script 8 - Functions for download data from AWS\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Required modules\n", - "import os # Miscellaneous operating system interfaces\n", - "import numpy as np # Import the Numpy package\n", - "import colorsys # To make convertion of colormaps\n", - "import boto3 # Amazon Web Services (AWS) SDK for Python\n", - "from botocore import UNSIGNED # boto3 config\n", - "from botocore.config import Config # boto3 config\n", - "import math # Mathematical functions\n", - "from datetime import datetime # Basic Dates and time types\n", - "from osgeo import osr # Python bindings for GDAL\n", - "from osgeo import gdal # Python bindings for GDAL\n", - "\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "def loadCPT(path):\n", - "\n", - " try:\n", - " f = open(path)\n", - " except:\n", - " print (\"File \", path, \"not found\")\n", - " return None\n", - "\n", - " lines = f.readlines()\n", - "\n", - " f.close()\n", - "\n", - " x = np.array([])\n", - " r = np.array([])\n", - " g = np.array([])\n", - " b = np.array([])\n", - "\n", - " colorModel = 'RGB'\n", - "\n", - " for l in lines:\n", - " ls = l.split()\n", - " if l[0] == '#':\n", - " if ls[-1] == 'HSV':\n", - " colorModel = 'HSV'\n", - " continue\n", - " else:\n", - " continue\n", - " if ls[0] == 'B' or ls[0] == 'F' or ls[0] == 'N':\n", - " pass\n", - " else:\n", - " x=np.append(x,float(ls[0]))\n", - " r=np.append(r,float(ls[1]))\n", - " g=np.append(g,float(ls[2]))\n", - " b=np.append(b,float(ls[3]))\n", - " xtemp = float(ls[4])\n", - " rtemp = float(ls[5])\n", - " gtemp = float(ls[6])\n", - " btemp = float(ls[7])\n", - "\n", - " x=np.append(x,xtemp)\n", - " r=np.append(r,rtemp)\n", - " g=np.append(g,gtemp)\n", - " b=np.append(b,btemp)\n", - "\n", - " if colorModel == 'HSV':\n", - " for i in range(r.shape[0]):\n", - " rr, gg, bb = colorsys.hsv_to_rgb(r[i]/360.,g[i],b[i])\n", - " r[i] = rr ; g[i] = gg ; b[i] = bb\n", - "\n", - " if colorModel == 'RGB':\n", - " r = r/255.0\n", - " g = g/255.0\n", - " b = b/255.0\n", - "\n", - " xNorm = (x - x[0])/(x[-1] - x[0])\n", - "\n", - " red = []\n", - " blue = []\n", - " green = []\n", - "\n", - " for i in range(len(x)):\n", - " red.append([xNorm[i],r[i],r[i]])\n", - " green.append([xNorm[i],g[i],g[i]])\n", - " blue.append([xNorm[i],b[i],b[i]])\n", - "\n", - " colorDict = {'red': red, 'green': green, 'blue': blue}\n", - "\n", - " return colorDict\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "def download_CMI(yyyymmddhhmn, band, path_dest):\n", - "\n", - " os.makedirs(path_dest, exist_ok=True)\n", - "\n", - " year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%Y')\n", - " day_of_year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%j')\n", - " hour = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%H')\n", - " min = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%M')\n", - "\n", - " # AMAZON repository information\n", - " # https://noaa-goes16.s3.amazonaws.com/index.html\n", - " bucket_name = 'noaa-goes16'\n", - " product_name = 'ABI-L2-CMIPF'\n", - "\n", - " # Initializes the S3 client\n", - " s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", - " #-----------------------------------------------------------------------------------------------------------\n", - " # File structure\n", - " prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6C{int(band):02.0f}_G16_s{year}{day_of_year}{hour}{min}'\n", - "\n", - " # Seach for the file on the server\n", - " s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = \"/\")\n", - "\n", - " #-----------------------------------------------------------------------------------------------------------\n", - " # Check if there are files available\n", - " if 'Contents' not in s3_result:\n", - " # There are no files\n", - " print(f'No files found for the date: {yyyymmddhhmn}, Band-{band}')\n", - " return -1\n", - " else:\n", - " # There are files\n", - " for obj in s3_result['Contents']:\n", - " key = obj['Key']\n", - " # Print the file name\n", - " file_name = key.split('/')[-1].split('.')[0]\n", - "\n", - " # Download the file\n", - " if os.path.exists(f'{path_dest}/{file_name}.nc'):\n", - " print(f'File {path_dest}/{file_name}.nc exists')\n", - " else:\n", - " print(f'Downloading file {path_dest}/{file_name}.nc')\n", - " s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc')\n", - " return f'{file_name}'\n", - "\n", - "s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", - "\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "def download_PROD(yyyymmddhhmn, product_name, path_dest):\n", - "\n", - " # os.makedirs(path_dest, exist_ok=True)\n", - "\n", - " year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%Y')\n", - " day_of_year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%j')\n", - " hour = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%H')\n", - " min = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%M')\n", - "\n", - " # AMAZON repository information\n", - " # https://noaa-goes16.s3.amazonaws.com/index.html\n", - " bucket_name = 'noaa-goes16'\n", - "\n", - " # Initializes the S3 client\n", - " # s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", - "\n", - " #-----------------------------------------------------------------------------------------------------------\n", - " # File structure\n", - " prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6_G16_s{year}{day_of_year}{hour}{min}'\n", - "\n", - " # Seach for the file on the server\n", - " s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = \"/\")\n", - "\n", - " #-----------------------------------------------------------------------------------------------------------\n", - " # Check if there are files available\n", - " if 'Contents' not in s3_result:\n", - " # There are no files\n", - " print(f'No files found for the date: {yyyymmddhhmn}, Product: {product_name}')\n", - " return -1\n", - " else:\n", - " # There are files\n", - " for obj in s3_result['Contents']:\n", - " key = obj['Key']\n", - " # Print the file name\n", - " file_name = key.split('/')[-1].split('.')[0]\n", - "\n", - " # print(f'File name: {file_name}')\n", - "\n", - " # Download the file\n", - " if os.path.exists(f'{path_dest}/{file_name}.nc'):\n", - " print(f'File {path_dest}/{file_name}.nc exists')\n", - " else:\n", - " # print(f'Downloading file {path_dest}/{file_name}.nc')\n", - " s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc')\n", - " return f'{file_name}'\n", - "\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "def download_GLM(yyyymmddhhmnss, path_dest):\n", - "\n", - " os.makedirs(path_dest, exist_ok=True)\n", - "\n", - " year = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%Y')\n", - " day_of_year = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%j')\n", - " hour = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%H')\n", - " min = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%M')\n", - " seg = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%S')\n", - "\n", - " # AMAZON repository information\n", - " # https://noaa-goes16.s3.amazonaws.com/index.html\n", - " bucket_name = 'noaa-goes16'\n", - "\n", - " # Initializes the S3 client\n", - " s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", - " #-----------------------------------------------------------------------------------------------------------\n", - " # File structure\n", - " product_name = \"GLM-L2-LCFA\"\n", - " prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}_G16_s{year}{day_of_year}{hour}{min}{seg}'\n", - "\n", - " # Seach for the file on the server\n", - " s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = \"/\")\n", - "\n", - " #-----------------------------------------------------------------------------------------------------------\n", - " # Check if there are files available\n", - " if 'Contents' not in s3_result:\n", - " # There are no files\n", - " print(f'No files found for the date: {yyyymmddhhmnss}, Product-{product_name}')\n", - " return -1\n", - " else:\n", - " # There are files\n", - " for obj in s3_result['Contents']:\n", - " key = obj['Key']\n", - " # Print the file name\n", - " file_name = key.split('/')[-1].split('.')[0]\n", - "\n", - " # Download the file\n", - " if os.path.exists(f'{path_dest}/{file_name}.nc'):\n", - " print(f'File {path_dest}/{file_name}.nc exists')\n", - " else:\n", - " print(f'Downloading file {path_dest}/{file_name}.nc')\n", - " s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc')\n", - " return f'{file_name}'\n", - "\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Functions to convert lat / lon extent to array indices\n", - "def geo2grid(lat, lon, nc):\n", - "\n", - " # Apply scale and offset\n", - " xscale, xoffset = nc.variables['x'].scale_factor, nc.variables['x'].add_offset\n", - " yscale, yoffset = nc.variables['y'].scale_factor, nc.variables['y'].add_offset\n", - "\n", - " x, y = latlon2xy(lat, lon)\n", - " col = (x - xoffset)/xscale\n", - " lin = (y - yoffset)/yscale\n", - " return int(lin), int(col)\n", - "\n", - "def latlon2xy(lat, lon):\n", - " # goes_imagery_projection:semi_major_axis\n", - " req = 6378137 # meters\n", - " # goes_imagery_projection:inverse_flattening\n", - " invf = 298.257222096\n", - " # goes_imagery_projection:semi_minor_axis\n", - " rpol = 6356752.31414 # meters\n", - " e = 0.0818191910435\n", - " # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis\n", - " H = 42164160 # meters\n", - " # goes_imagery_projection: longitude_of_projection_origin\n", - " lambda0 = -1.308996939\n", - "\n", - " # Convert to radians\n", - " latRad = lat * (math.pi/180)\n", - " lonRad = lon * (math.pi/180)\n", - "\n", - " # (1) geocentric latitude\n", - " Phi_c = math.atan(((rpol * rpol)/(req * req)) * math.tan(latRad))\n", - " # (2) geocentric distance to the point on the ellipsoid\n", - " rc = rpol/(math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c)))))\n", - " # (3) sx\n", - " sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0))\n", - " # (4) sy\n", - " sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0)\n", - " # (5)\n", - " sz = rc * math.sin(Phi_c)\n", - "\n", - " # x,y\n", - " x = math.asin((-sy)/math.sqrt((sx*sx) + (sy*sy) + (sz*sz)))\n", - " y = math.atan(sz/sx)\n", - "\n", - " return x, y\n", - "\n", - "# Function to convert lat / lon extent to GOES-16 extents\n", - "def convertExtent2GOESProjection(extent):\n", - " # GOES-16 viewing point (satellite position) height above the earth\n", - " GOES16_HEIGHT = 35786023.0\n", - " # GOES-16 longitude position\n", - " GOES16_LONGITUDE = -75.0\n", - "\n", - " a, b = latlon2xy(extent[1], extent[0])\n", - " c, d = latlon2xy(extent[3], extent[2])\n", - " return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT)\n", - "\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Function to reproject the data\n", - "def reproject(file_name, ncfile, array, extent, undef):\n", - "\n", - " # Read the original file projection and configure the output projection\n", - " source_prj = osr.SpatialReference()\n", - " source_prj.ImportFromProj4(ncfile.GetProjectionRef())\n", - "\n", - " target_prj = osr.SpatialReference()\n", - " target_prj.ImportFromProj4(\"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\")\n", - "\n", - " # Reproject the data\n", - " GeoT = ncfile.GetGeoTransform()\n", - " driver = gdal.GetDriverByName('MEM')\n", - " raw = driver.Create('raw', array.shape[0], array.shape[1], 1, gdal.GDT_Float32)\n", - " raw.SetGeoTransform(GeoT)\n", - " raw.GetRasterBand(1).WriteArray(array)\n", - "\n", - " # Define the parameters of the output file\n", - " kwargs = {'format': 'netCDF', \\\n", - " 'srcSRS': source_prj, \\\n", - " 'dstSRS': target_prj, \\\n", - " 'outputBounds': (extent[0], extent[3], extent[2], extent[1]), \\\n", - " 'outputBoundsSRS': target_prj, \\\n", - " 'outputType': gdal.GDT_Float32, \\\n", - " 'srcNodata': undef, \\\n", - " 'dstNodata': 'nan', \\\n", - " 'resampleAlg': gdal.GRA_NearestNeighbour}\n", - "\n", - " # Write the reprojected file on disk\n", - " gdal.Warp(file_name, raw, **kwargs)" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "path = '../data/goes16/'\n", - "file_name = 'OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.nc'" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "root group (NETCDF4 data model, file format HDF5):\n", - " naming_authority: gov.nesdis.noaa\n", - " Conventions: CF-1.7\n", - " Metadata_Conventions: Unidata Dataset Discovery v1.0\n", - " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", - " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Services\n", - " project: GOES\n", - " production_site: NSOF\n", - " production_environment: OE\n", - " spatial_resolution: 10km at nadir\n", - " orbital_slot: GOES-East\n", - " platform_ID: G16\n", - " instrument_type: GOES R Series Advanced Baseline Imager\n", - " scene_id: Full Disk\n", - " instrument_ID: FM1\n", - " dataset_name: OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.nc\n", - " iso_series_metadata_id: 158fae30-affd-11e1-afa6-0800200c9a66\n", - " title: ABI L2 Derived Stability Indices\n", - " summary: The Derived Stability Indices product consists of the atmosphere convective available potential energy (CAPE) with respect to the surface, the lifted index between the surface and 500 hPa, k index, showalter index, and the total totals index. The product is generated using a regression retrieval followed by an iterative physical retrieval that makes use of a radiative transfer model. Product data is generated both day and night.\n", - " keywords: ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR PROFILES, ATMOSPHERE > ATMOSPHERIC TEMPERATURE > ATMOSPHERIC STABILITY\n", - " keywords_vocabulary: NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 7.0.0.0.0\n", - " license: Unclassified data. Access is restricted to approved users only.\n", - " processing_level: National Aeronautics and Space Administration (NASA) L2\n", - " date_created: 2022-04-01T17:11:48.0Z\n", - " cdm_data_type: Image\n", - " time_coverage_start: 2022-04-01T17:00:20.5Z\n", - " time_coverage_end: 2022-04-01T17:09:51.3Z\n", - " timeline_id: ABI Mode 6\n", - " production_data_source: Realtime\n", - " id: 39cef219-d6e0-4088-b67b-12af7de23854\n", - " dimensions(sizes): y(1086), x(1086), number_of_time_bounds(2), number_of_image_bounds(2), number_of_LZA_bounds(2), number_of_SZA_bounds(2), number_of_lat_bounds(2), sounding_emissive_bands(7)\n", - " variables(dimensions): uint16 LI(y, x), uint16 CAPE(y, x), uint16 TT(y, x), uint16 SI(y, x), uint16 KI(y, x), uint8 DQF_Overall(y, x), uint8 DQF_Retrieval(y, x), uint8 DQF_SkinTemp(y, x), float64 t(), int16 y(y), int16 x(x), float64 time_bounds(number_of_time_bounds), int32 goes_imager_projection(), float32 y_image(), float32 y_image_bounds(number_of_image_bounds), float32 x_image(), float32 x_image_bounds(number_of_image_bounds), float32 nominal_satellite_subpoint_lat(), float32 nominal_satellite_subpoint_lon(), float32 nominal_satellite_height(), float32 geospatial_lat_lon_extent(), float32 final_air_pressure(), int32 CAPE_outlier_pixel_count(), int32 lifted_index_outlier_pixel_count(), int32 k_index_outlier_pixel_count(), int32 showalter_index_outlier_pixel_count(), int32 total_totals_index_outlier_pixel_count(), float32 minimum_CAPE(), float32 maximum_CAPE(), float32 mean_CAPE(), float32 standard_deviation_CAPE(), float32 minimum_lifted_index(), float32 maximum_lifted_index(), float32 mean_lifted_index(), float32 standard_deviation_lifted_index(), float32 minimum_total_totals_index(), float32 maximum_total_totals_index(), float32 mean_total_totals_index(), float32 standard_deviation_total_totals_index(), float32 minimum_showalter_index(), float32 maximum_showalter_index(), float32 mean_showalter_index(), float32 standard_deviation_showalter_index(), float32 minimum_k_index(), float32 maximum_k_index(), float32 mean_k_index(), float32 standard_deviation_k_index(), int32 algorithm_dynamic_input_data_container(), int32 processing_parm_version_container(), int32 algorithm_product_version_container(), float32 retrieval_local_zenith_angle(), float32 quantitative_local_zenith_angle(), float32 retrieval_local_zenith_angle_bounds(number_of_LZA_bounds), float32 quantitative_local_zenith_angle_bounds(number_of_LZA_bounds), float32 solar_zenith_angle(), float32 solar_zenith_angle_bounds(number_of_SZA_bounds), float32 latitude(), float32 latitude_bounds(number_of_lat_bounds), float32 sounding_emissive_wavelengths(sounding_emissive_bands), int8 sounding_emissive_band_ids(sounding_emissive_bands), float32 percent_uncorrectable_L0_errors(), float32 percent_uncorrectable_GRB_errors(), int32 total_attempted_retrievals(), float32 mean_obs_modeled_diff_sounding_emissive_bands(sounding_emissive_bands), float32 std_dev_obs_modeled_diff_sounding_emissive_bands(sounding_emissive_bands)\n", - " groups: \n" - ] - } - ], - "source": [ - "# Python and GOES-R Imagery Exampe: Cropping the DSIF imagery \n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Required modules\n", - "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", - "import matplotlib.pyplot as plt # Plotting library\n", - "from datetime import datetime # Basic Dates and time types\n", - "import cartopy, cartopy.crs as ccrs # Plot maps\n", - "import os # Miscellaneous operating system interfaces\n", - "\n", - "import pickle\n", - "\n", - "# Desired extent\n", - "extent = [-64.0, -36.0, -40.0, -15.0] # Min lon, Max lon, Min lat, Max lat\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Open the GOES-R image\n", - "file = Dataset(path+file_name)\n", - "\n", - "print(file)\n", - "\n", - "# Convert lat/lon to grid-coordinates\n", - "lly, llx = geo2grid(extent[1], extent[0], file)\n", - "ury, urx = geo2grid(extent[3], extent[2], file)\n", - "\n", - "dict_indices = {}\n", - "for instability_index_name in ['CAPE', 'LI', 'TT', 'SI', 'KI']:\n", - " # Get the pixel values\n", - " data = file.variables[instability_index_name][ury:lly, llx:urx]\n", - " dict_indices[instability_index_name] = data\n", - "\n", - "data = file.variables['DQF_Overall'][ury:lly, llx:urx]\n", - "dict_indices['DQF_Overall'] = data\n", - "\n", - "# open a file, where you want to store the data\n", - "temp = os.path.splitext(file_name) # given '/home/user/somefile.nc', returns ('/home/user/somefile', '.nc')\n", - "pkl_file = open(f'{temp[0]}.pkl', 'wb')\n", - "\n", - "# dump information to that file\n", - "pickle.dump(dict_indices, pkl_file)\n", - "\n", - "# close the file\n", - "pkl_file.close()" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#-----------------------------------------------------------------------------------------------------------\n", - "# Compute data-extent in GOES projection-coordinates\n", - "img_extent = convertExtent2GOESProjection(extent)\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Choose the plot size (width x height, in inches)\n", - "plt.figure(figsize=(10,10))\n", - "\n", - "# Use the Geostationary projection in cartopy\n", - "ax = plt.axes(projection=ccrs.Geostationary(central_longitude=-75.0, satellite_height=35786023.0))\n", - "\n", - "# Define the color scale based on the channel\n", - "colormap = \"jet\" # White to black for IR channels\n", - " \n", - "# Plot the image\n", - "img = ax.imshow(data, origin='upper', extent=img_extent, cmap=colormap)\n", - "\n", - "# Add coastlines, borders and gridlines\n", - "ax.coastlines(resolution='10m', color='black', linewidth=0.8)\n", - "ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5)\n", - "ax.gridlines(color='black', alpha=0.5, linestyle='--', linewidth=0.5)\n", - "\n", - "# Add a colorbar\n", - "plt.colorbar(img, label='CAPE', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", - "\n", - "# Extract the date\n", - "date = (datetime.strptime(file.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ'))\n", - "\n", - "# Add a title\n", - "plt.title('GOES-16 CAPE ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC', fontweight='bold', fontsize=10, loc='left')\n", - "plt.title('Reg.: ' + str(extent) , fontsize=10, loc='right')\n", - "#-----------------------------------------------------------------------------------------------------------\n", - "# Save the image\n", - "plt.savefig(f'OR_ABI-L2-DSIF-M6_G16_s20210632010164_e20210632019472_c20210632020547.png', bbox_inches='tight', pad_inches=0, dpi=300)\n", - "\n", - "# Show the image\n", - "plt.show()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "atmoseer", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/notebooks/DSIF_CAPE_2024-01-12 00:00:00_to_2024-01-12 00:00:00.parquet b/notebooks/DSIF_CAPE_2024-01-12 00:00:00_to_2024-01-12 00:00:00.parquet deleted file mode 100644 index 2a690c4e..00000000 Binary files a/notebooks/DSIF_CAPE_2024-01-12 00:00:00_to_2024-01-12 00:00:00.parquet and /dev/null differ diff --git a/notebooks/era5.ipynb b/notebooks/ERA5/ERA5.ipynb similarity index 65% rename from notebooks/era5.ipynb rename to notebooks/ERA5/ERA5.ipynb index 9338d96e..27a42c31 100644 --- a/notebooks/era5.ipynb +++ b/notebooks/ERA5/ERA5.ipynb @@ -5963,7 +5963,7 @@ " # Select ERA5 data near the station\n", " era5_data_at_1000hPa = ds.sel(level=1000, longitude=station_longitude, latitude=station_latitude, method=\"nearest\")\n", "\n", - " df_NWP_data_for_station = pd.DataFrame(\n", + " df_ERA5_data_for_station = pd.DataFrame(\n", " {\n", " \"time\": era5_data_at_1000hPa.time.values,\n", " \"pressure_1000\": 1000,\n", @@ -5976,15 +5976,15 @@ "\n", " # Create a datetime index for the ERA dataframe\n", " format_string = '%Y-%m-%d %H:%M:%S'\n", - " df_NWP_data_for_station['datetime'] = pd.to_datetime(df_NWP_data_for_station['time'], format=format_string)\n", - " df_NWP_data_for_station = df_NWP_data_for_station.set_index(pd.DatetimeIndex(df_NWP_data_for_station['datetime']))\n", - " df_NWP_data_for_station = df_NWP_data_for_station.drop(['time', 'datetime'], axis = 1)\n", + " df_ERA5_data_for_station['datetime'] = pd.to_datetime(df_ERA5_data_for_station['time'], format=format_string)\n", + " df_ERA5_data_for_station = df_ERA5_data_for_station.set_index(pd.DatetimeIndex(df_ERA5_data_for_station['datetime']))\n", + " df_ERA5_data_for_station = df_ERA5_data_for_station.drop(['time', 'datetime'], axis = 1)\n", " \n", " # Temperature in ERA5 is provided in Kelvin; convert to Celsius.\n", - " df_NWP_data_for_station[\"Temperature_1000_Celsius\"] = df_NWP_data_for_station[\"Temperature_1000\"].apply(convert_to_celsius)\n", - " df_NWP_data_for_station.head()\n", + " df_ERA5_data_for_station[\"Temperature_1000_Celsius\"] = df_ERA5_data_for_station[\"Temperature_1000\"].apply(convert_to_celsius)\n", + " df_ERA5_data_for_station.head()\n", " \n", - " joined_df = pd.merge(df_ws, df_NWP_data_for_station, how='left', left_index=True, right_index=True)\n", + " joined_df = pd.merge(df_ws, df_ERA5_data_for_station, how='left', left_index=True, right_index=True)\n", " \n", " return joined_df" ] @@ -6176,7 +6176,7 @@ "metadata": {}, "outputs": [], "source": [ - "df_NWP_data_for_station = pd.DataFrame(\n", + "df_ERA5_data_for_station = pd.DataFrame(\n", " {\n", " \"time\": era5_data_at_1000hPa.time.values,\n", " \"pressure_1000\": 1000,\n", @@ -6295,7 +6295,7 @@ } ], "source": [ - "df_NWP_data_for_station.head()" + "df_ERA5_data_for_station.head()" ] }, { @@ -6306,9 +6306,9 @@ "outputs": [], "source": [ "format_string = '%Y-%m-%d %H:%M:%S'\n", - "df_NWP_data_for_station['datetime'] = pd.to_datetime(df_NWP_data_for_station['time'], format=format_string)\n", - "df_NWP_data_for_station = df_NWP_data_for_station.set_index(pd.DatetimeIndex(df_NWP_data_for_station['datetime']))\n", - "df_NWP_data_for_station = df_NWP_data_for_station.drop(['time', 'datetime'], axis = 1)" + "df_ERA5_data_for_station['datetime'] = pd.to_datetime(df_ERA5_data_for_station['time'], format=format_string)\n", + "df_ERA5_data_for_station = df_ERA5_data_for_station.set_index(pd.DatetimeIndex(df_ERA5_data_for_station['datetime']))\n", + "df_ERA5_data_for_station = df_ERA5_data_for_station.drop(['time', 'datetime'], axis = 1)" ] }, { @@ -6422,7 +6422,7 @@ } ], "source": [ - "df_NWP_data_for_station.head()" + "df_ERA5_data_for_station.head()" ] }, { @@ -6543,8 +6543,8 @@ } ], "source": [ - "df_NWP_data_for_station[\"Temperature_1000_Celsius\"] = df_NWP_data_for_station[\"Temperature_1000\"].apply(convert_to_celsius)\n", - "df_NWP_data_for_station.head()" + "df_ERA5_data_for_station[\"Temperature_1000_Celsius\"] = df_ERA5_data_for_station[\"Temperature_1000\"].apply(convert_to_celsius)\n", + "df_ERA5_data_for_station.head()" ] }, { @@ -6554,7 +6554,7 @@ "metadata": {}, "outputs": [], "source": [ - "assert (not df_NWP_data_for_station.isnull().values.any().any())" + "assert (not df_ERA5_data_for_station.isnull().values.any().any())" ] }, { @@ -6575,7 +6575,7 @@ } ], "source": [ - "df_NWP_data_for_station.shape" + "df_ERA5_data_for_station.shape" ] }, { @@ -6585,7 +6585,7 @@ "metadata": {}, "outputs": [], "source": [ - "joined_df = pd.merge(df_ws, df_NWP_data_for_station, how='left', left_index=True, right_index=True)" + "joined_df = pd.merge(df_ws, df_ERA5_data_for_station, how='left', left_index=True, right_index=True)" ] }, { @@ -6772,6 +6772,1243 @@ "source": [ "joined_df.dropna().shape" ] + }, + { + "cell_type": "markdown", + "id": "b470d6cc", + "metadata": {}, + "source": [ + "# Instability indices: ERA5 versus SBGL" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b1499378", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import xarray as xr\n", + "\n", + "filename = \"../data/ERA5/RJ_1997_2024.nc\"\n", + "ds = xr.open_dataset(filename)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "003bd45e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "Dimensions:    (longitude: 9, latitude: 5, time: 239568, expver: 2)\n",
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+       "    kx         (time, latitude, longitude, expver) float64 ...\n",
+       "    totalx     (time, latitude, longitude, expver) float64 ...\n",
+       "Attributes:\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      2024-05-13 03:16:33 GMT by grib_to_netcdf-2.28.1: /opt/ecmw...
" + ], + "text/plain": [ + "\n", + "Dimensions: (longitude: 9, latitude: 5, time: 239568, expver: 2)\n", + "Coordinates:\n", + " * longitude (longitude) float32 -44.0 -43.75 -43.5 ... -42.5 -42.25 -42.0\n", + " * latitude (latitude) float32 -22.0 -22.25 -22.5 -22.75 -23.0\n", + " * time (time) datetime64[ns] 1997-01-01 ... 2024-04-30T23:00:00\n", + " * expver (expver) int32 5 1\n", + "Data variables:\n", + " u10 (time, latitude, longitude, expver) float64 ...\n", + " v10 (time, latitude, longitude, expver) float64 ...\n", + " d2m (time, latitude, longitude, expver) float64 ...\n", + " t2m (time, latitude, longitude, expver) float64 ...\n", + " cape (time, latitude, longitude, expver) float64 ...\n", + " cin (time, latitude, longitude, expver) float64 ...\n", + " z (time, latitude, longitude, expver) float64 ...\n", + " kx (time, latitude, longitude, expver) float64 ...\n", + " totalx (time, latitude, longitude, expver) float64 ...\n", + "Attributes:\n", + " Conventions: CF-1.6\n", + " history: 2024-05-13 03:16:33 GMT by grib_to_netcdf-2.28.1: /opt/ecmw..." + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ds" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "d25ad76e", + "metadata": {}, + "outputs": [], + "source": [ + "ds_combine = ds.sel(expver=1).combine_first(ds.sel(expver=5))\n", + "ds_combine.load()\n", + "ds = ds_combine" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "4c74e330", + "metadata": {}, + "outputs": [], + "source": [ + "df = ds.to_dataframe()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e6186860", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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timeERA5_CAPEERA5_KERA5_TT
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" + ], + "text/plain": [ + " time ERA5_CAPE ERA5_K ERA5_TT\n", + "239563 2024-04-30 19:00:00 1.136868e-13 10.794844 42.016554\n", + "239564 2024-04-30 20:00:00 2.699898e+01 10.167083 41.618712\n", + "239565 2024-04-30 21:00:00 1.032476e+02 10.052035 41.541600\n", + "239566 2024-04-30 22:00:00 1.522489e+02 10.535986 41.747004\n", + "239567 2024-04-30 23:00:00 1.997593e+02 11.028691 41.923064" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_era5_data_nearest_to_SBGL.tail()" + ] + }, + { + "cell_type": "markdown", + "id": "480d94fb", + "metadata": {}, + "source": [ + "Now, retrieve instability indices computed from radiosonde data." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "ae2b78a1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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timecapecinliftktotal_totalsshowalter
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" + ], + "text/plain": [ + " time cape cin lift k total_totals showalter\n", + "0 2010-06-04 5.976469 -86.096963 6.903069 25.9 36.7 6.503206\n", + "1 2010-06-08 0.000000 0.000000 6.659465 -20.3 23.2 14.967601\n", + "2 2010-06-09 5.984759 -42.414604 1.985130 7.9 39.8 7.232244\n", + "3 2010-06-10 20.304654 -58.706423 6.056000 19.6 35.9 7.704037\n", + "4 2010-06-15 0.000000 0.000000 9.906158 -6.2 34.5 9.217685" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_SBGL = pd.read_parquet('../data/as/SBGL_indices_1997_2023.parquet.gzip')\n", + "df_SBGL.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "01a71d1c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 15938 entries, 0 to 15937\n", + "Data columns (total 7 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 time 15938 non-null datetime64[ns]\n", + " 1 cape 15938 non-null float64 \n", + " 2 cin 15938 non-null float64 \n", + " 3 lift 15904 non-null float64 \n", + " 4 k 15904 non-null float64 \n", + " 5 total_totals 15904 non-null float64 \n", + " 6 showalter 15904 non-null float64 \n", + "dtypes: datetime64[ns](1), float64(6)\n", + "memory usage: 871.7 KB\n" + ] + } + ], + "source": [ + "df_SBGL.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "aa616f0b", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "def join_dataframes_on_datetime(df1, df2, datetime_col='datetime'):\n", + " \"\"\"\n", + " Joins two Pandas DataFrames on a datetime column.\n", + "\n", + " Parameters:\n", + " df1 (pd.DataFrame): The first dataframe.\n", + " df2 (pd.DataFrame): The second dataframe.\n", + " datetime_col (str): The name of the datetime column to join on. Default is 'datetime'.\n", + "\n", + " Returns:\n", + " pd.DataFrame: The joined dataframe.\n", + " \"\"\"\n", + " if datetime_col not in df1.columns or datetime_col not in df2.columns:\n", + " raise ValueError(f\"Both dataframes must contain the column '{datetime_col}'\")\n", + " \n", + " if not pd.api.types.is_datetime64_any_dtype(df1[datetime_col]) or not pd.api.types.is_datetime64_any_dtype(df2[datetime_col]):\n", + " raise TypeError(f\"The column '{datetime_col}' must be of type datetime64 in both dataframes\")\n", + " \n", + " joined_df = pd.merge(df1, df2, on=datetime_col)\n", + " \n", + " # Set the datetime column as the index\n", + " joined_df.set_index(datetime_col, inplace=True)\n", + "\n", + " return joined_df" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "id": "0aeac4f5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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ERA5_CAPEERA5_KERA5_TTcapecinliftktotal_totalsshowalter
time
2023-04-21 12:00:002.273737e-13-19.02897224.54313616.169118-43.4784596.370470-33.317.217.967601
2023-04-22 00:00:004.016305e+00-4.07884230.3601994.834031-63.3989395.8060742.635.36.534496
2023-04-22 12:00:005.910953e+011.45098330.59315859.958619-6.9907022.261458-3.134.28.473954
2023-04-23 00:00:007.801235e+014.71914535.88845794.621510-14.5748743.2148201.437.74.690950
2023-04-23 12:00:007.888546e+01-2.68421630.826649364.6334710.000000-0.090562-17.334.07.741201
\n", + "
" + ], + "text/plain": [ + " ERA5_CAPE ERA5_K ERA5_TT cape \\\n", + "time \n", + "2023-04-21 12:00:00 2.273737e-13 -19.028972 24.543136 16.169118 \n", + "2023-04-22 00:00:00 4.016305e+00 -4.078842 30.360199 4.834031 \n", + "2023-04-22 12:00:00 5.910953e+01 1.450983 30.593158 59.958619 \n", + "2023-04-23 00:00:00 7.801235e+01 4.719145 35.888457 94.621510 \n", + "2023-04-23 12:00:00 7.888546e+01 -2.684216 30.826649 364.633471 \n", + "\n", + " cin lift k total_totals showalter \n", + "time \n", + "2023-04-21 12:00:00 -43.478459 6.370470 -33.3 17.2 17.967601 \n", + "2023-04-22 00:00:00 -63.398939 5.806074 2.6 35.3 6.534496 \n", + "2023-04-22 12:00:00 -6.990702 2.261458 -3.1 34.2 8.473954 \n", + "2023-04-23 00:00:00 -14.574874 3.214820 1.4 37.7 4.690950 \n", + "2023-04-23 12:00:00 0.000000 -0.090562 -17.3 34.0 7.741201 " + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_joined = join_dataframes_on_datetime(df_era5_data_nearest_to_SBGL, df_SBGL, datetime_col = 'time')\n", + "df_joined.tail()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "99efe4ce", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "DatetimeIndex: 15938 entries, 1997-01-01 00:00:00 to 2023-04-23 12:00:00\n", + "Data columns (total 9 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 ERA5_CAPE 15938 non-null float64\n", + " 1 ERA5_K 15938 non-null float64\n", + " 2 ERA5_TT 15938 non-null float64\n", + " 3 cape 15938 non-null float64\n", + " 4 cin 15938 non-null float64\n", + " 5 lift 15904 non-null float64\n", + " 6 k 15904 non-null float64\n", + " 7 total_totals 15904 non-null float64\n", + " 8 showalter 15904 non-null float64\n", + "dtypes: float64(9)\n", + "memory usage: 1.2 MB\n" + ] + } + ], + "source": [ + "df_joined.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "ff62394c", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "def plot_cape_values(df, start_date, end_date): \n", + " # Filter the DataFrame to include only the data within the specified date range\n", + " filtered_df = df[start_date:end_date]\n", + " \n", + " # Plot the data\n", + " plt.figure(figsize=(10, 5))\n", + " plt.plot(filtered_df.index, filtered_df['ERA5_CAPE'], label='ERA5')\n", + " plt.plot(filtered_df.index, filtered_df['cape'], label='SBGL')\n", + " \n", + " # Adding title and labels\n", + " plt.title(f'CAPE values from {start_date} to {end_date}')\n", + " plt.xlabel('Date')\n", + " plt.ylabel('CAPE')\n", + " \n", + " # Adding a legend\n", + " plt.legend()\n", + " \n", + " # Display the plot\n", + " plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "69f08be7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "start_date = '2023-01-01'\n", + "end_date = '2023-03-21'\n", + "plot_cape_values(df_joined, start_date, end_date)" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "e25abf3e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pearson correlation coefficient: 0.5060652443432566\n" + ] + } + ], + "source": [ + "correlation = df_joined['ERA5_CAPE'].corr(df_joined['cape'])\n", + "print(f\"Pearson correlation coefficient: {correlation}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "60db7fb9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Spearman correlation coefficient: 0.6526149877924042\n" + ] + } + ], + "source": [ + "spearman_correlation = df_joined['ERA5_CAPE'].corr(df_joined['cape'], method='spearman')\n", + "print(f\"Spearman correlation coefficient: {spearman_correlation}\")" + ] + }, + { + "cell_type": "markdown", + "id": "83d3e19f", + "metadata": {}, + "source": [ + "Just as a sanity check:" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "716750ab", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Spearman correlation coefficient: 1.0\n" + ] + } + ], + "source": [ + "spearman_correlation = df_joined['cape'].corr(df_joined['cape'], method='spearman')\n", + "print(f\"Spearman correlation coefficient: {spearman_correlation}\")" + ] } ], "metadata": { @@ -6790,7 +8027,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/notebooks/CDS_api.ipynb b/notebooks/ERA5/ERA5_CDS_api.ipynb similarity index 100% rename from notebooks/CDS_api.ipynb rename to notebooks/ERA5/ERA5_CDS_api.ipynb diff --git a/notebooks/ERA5/convective_flow_animation_example.ipynb b/notebooks/ERA5/convective_flow_animation_example.ipynb new file mode 100644 index 00000000..fb365e52 --- /dev/null +++ b/notebooks/ERA5/convective_flow_animation_example.ipynb @@ -0,0 +1,754 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['pillow', 'ffmpeg', 'ffmpeg_file', 'imagemagick', 'imagemagick_file', 'html']\n" + ] + } + ], + "source": [ + "from collections.abc import Callable, Generator\n", + "from pathlib import Path\n", + "from typing import Optional, cast\n", + "\n", + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import matplotlib.animation as animation\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import numpy.typing as npt\n", + "import pandas as pd\n", + "import seaborn as sns\n", + "import xarray as xr\n", + "from IPython.display import Image, display\n", + "\n", + "np.random.seed(42)\n", + "\n", + "print(animation.writers.list())" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "event_days = [\"2024-01-13\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "def _handle_expver(ds: xr.Dataset) -> xr.Dataset:\n", + " if \"expver\" in list(ds.coords.keys()):\n", + " print(\"expver dimension found, removing it\")\n", + " ds_combine = ds.sel(expver=1).combine_first(ds.sel(expver=5))\n", + " ds_combine.load()\n", + " ds = ds_combine\n", + " return ds\n", + "\n", + "\n", + "def get_uv_wind_components_with_speed(date: str) -> Optional[xr.Dataset]:\n", + " print(f\"Getting u10 and v10 wind components for {date}\")\n", + " year, month, day = map(int, date.split(\"-\"))\n", + "\n", + " month_data_path = Path(\"RJ_2024_1.nc\")\n", + " if not month_data_path.exists():\n", + " print(f\"File {month_data_path} does not exist\")\n", + " return None\n", + "\n", + " ds = _handle_expver(xr.open_dataset(month_data_path))\n", + "\n", + " if day not in pd.to_datetime(ds.time.values).day:\n", + " print(f\"Day {day} is not in the {month_data_path}\")\n", + " return None\n", + "\n", + " ds_day = ds.sel(time=f\"{year}-{month:02d}-{day:02d}\")\n", + " ds_day = ds_day[[\"u10\", \"v10\", \"tp\"]]\n", + " ds_day[\"speed10\"] = np.sqrt(ds_day[\"u10\"] ** 2 + ds_day[\"v10\"] ** 2)\n", + " print(f\"{date} - done\")\n", + " return ds_day" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\"\"\"refer:\n", + "https://scitools.org.uk/cartopy/docs/latest/matplotlib/intro.html\n", + "https://scitools.org.uk/cartopy/docs/latest/reference/generated/cartopy.mpl.geoaxes.GeoAxes.html\n", + "\"\"\"\n", + "ax = plt.axes(projection=ccrs.PlateCarree())\n", + "ax.coastlines()\n", + "ax.add_feature(cfeature.OCEAN)\n", + "plt.show()\n", + "plt.clf()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Getting u10 and v10 wind components for 2024-01-13\n", + "2024-01-13 - done\n" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "FPS = 5\n", + "\n", + "\n", + "def _get_variables(ds: xr.Dataset) -> Generator[npt.NDArray, None, None]:\n", + " return (\n", + " ds[var].values for var in [\"u10\", \"v10\", \"speed10\", \"tp\", \"longitude\", \"latitude\", \"time\"]\n", + " )\n", + "\n", + "\n", + "def _get_update_fn(ax, quiver, scatter, u10, v10, spd, tp, time) -> Callable:\n", + " def _update_fn(frame):\n", + " quiver.set_UVC(u10[frame], v10[frame], spd[frame])\n", + " ax.set_title(f\"Wind on {str(time[frame])}\")\n", + "\n", + " scatter.set_sizes(tp[frame].flatten() * 2000)\n", + "\n", + " return quiver, scatter\n", + "\n", + " return _update_fn\n", + "\n", + "\n", + "def animate_wind_tp_components(ds: xr.Dataset):\n", + " u10, v10, spd, tp, lon, lat, time = _get_variables(ds)\n", + " fig, ax = plt.subplots(figsize=(12, 6), subplot_kw={\"projection\": ccrs.PlateCarree()})\n", + "\n", + " ax.add_feature(cfeature.LAND)\n", + " ax.add_feature(cfeature.OCEAN)\n", + " ax.add_feature(cfeature.COASTLINE)\n", + " ax.add_feature(cfeature.BORDERS, linestyle=\":\")\n", + " ax.add_feature(cfeature.LAKES, alpha=0.5)\n", + " ax.add_feature(cfeature.RIVERS)\n", + " # ax.add_feature(cfeature.STATES.with_scale(\"10m\"))\n", + "\n", + " quiver = ax.quiver(\n", + " lon,\n", + " lat,\n", + " u10[0],\n", + " v10[0],\n", + " spd[0],\n", + " scale=30,\n", + " cmap=\"cool\",\n", + " transform=ccrs.PlateCarree(),\n", + " )\n", + "\n", + " scatter = ax.scatter(\n", + " np.tile(lon, lat.size),\n", + " np.repeat(lat, lon.size),\n", + " s=tp[0].flatten() * 2000,\n", + " alpha=0.5,\n", + " edgecolors=\"blue\",\n", + " c=\"black\",\n", + " )\n", + "\n", + " anim = animation.FuncAnimation(\n", + " fig,\n", + " _get_update_fn(ax, quiver, scatter, u10, v10, spd, tp, time),\n", + " frames=len(time),\n", + " blit=True,\n", + " )\n", + " plt.colorbar(quiver, ax=ax, label=\"Wind Speed (m/s)\", orientation=\"vertical\", pad=0.05)\n", + " ax.set(xlabel=\"Longitude\", ylabel=\"Latitude\")\n", + " return anim\n", + "\n", + "\n", + "gif_files: list[str] = []\n", + "ds_days: list[xr.Dataset] = []\n", + "for index, day in enumerate(event_days):\n", + " ds_day = get_uv_wind_components_with_speed(day)\n", + " if ds_day is None:\n", + " continue\n", + " # print(ds_day)\n", + " anim = animate_wind_tp_components(ds_day)\n", + " gif_file = f\"gif_{index}_{day}_dale.gif\"\n", + " anim.save(gif_file, writer=\"imagemagick\", fps=FPS)\n", + " gif_files.append(gif_file)\n", + " ds_days.append(ds_day)\n", + " plt.clf()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df_toy = pd.DataFrame(\n", + " {\n", + " \"tp\": np.random.rand(9),\n", + " \"latitude\": np.repeat([45.0, 46.0, 47.0], 3),\n", + " \"longitude\": np.tile([-100.0, -99.0, -98.0], 3),\n", + " }\n", + ")\n", + "\n", + "df_toy = df_toy.set_index([\"latitude\", \"longitude\"])\n", + "df_unstacked = df_toy.unstack(level=\"longitude\")\n", + "plt.figure(figsize=(8, 6))\n", + "sns.heatmap(df_unstacked[\"tp\"], annot=True, cmap=\"viridis\", cbar=True)\n", + "plt.title(\"Heatmap of tp values by Latitude and Longitude\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "time_heat = \"2024-01-13T20:00:00\"\n", + "ds_day = cast(xr.Dataset, ds_day)\n", + "df_heat = ds_day.sel(time=f\"{time_heat}\").to_dataframe()[[\"tp\"]] * 1000\n", + "\n", + "df_unstacked = df_heat.unstack(level=\"longitude\")\n", + "plt.figure(figsize=(8, 6))\n", + "sns.heatmap(df_unstacked[\"tp\"], annot=True, cmap=\"coolwarm\", cbar=True)\n", + "plt.title(f\"Heatmap of tp values by Latitude and Longitude at {time_heat}\")\n", + "# save the plot as an image\n", + "plt.savefig(f\"heatmap_tp_values_{time_heat}.png\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/gif": 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", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "for gif in gif_files:\n", + " display(Image(filename=gif))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "24\n", + "Variable u10 has 648 missing values\n", + " Size: 8kB\n", + "Dimensions: (latitude: 11, longitude: 21)\n", + "Coordinates:\n", + " * longitude (longitude) float32 84B -44.0 -43.9 -43.8 ... -42.2 -42.1 -42.0\n", + " * latitude (latitude) float32 44B -22.0 -22.1 -22.2 ... -22.8 -22.9 -23.0\n", + " time datetime64[ns] 8B 2024-01-13T12:00:00\n", + "Data variables:\n", + " u10 (latitude, longitude) float64 2kB 0.124 0.2645 0.2656 ... nan nan\n", + " v10 (latitude, longitude) float64 2kB 0.2707 0.3147 ... nan nan\n", + " tp (latitude, longitude) float64 2kB 0.0005485 0.0005728 ... nan nan\n", + " speed10 (latitude, longitude) float64 2kB 0.2977 0.411 0.3826 ... nan nan\n", + "Attributes:\n", + " Conventions: CF-1.6\n", + " history: 2024-05-01 08:37:28 GMT by grib_to_netcdf-2.28.1: /opt/ecmw...\n" + ] + } + ], + "source": [ + "ARBITRARY_HOUR = 12\n", + "\n", + "if ds_day is not None:\n", + " print(len(ds_day.time.values))\n", + " u10_missing_values = ds_day[\"u10\"].isnull().sum().values\n", + " print(f\"Variable u10 has {u10_missing_values} missing values\")\n", + " ds_arbitrary_hour = ds_day.sel(time=f\"{day}T{ARBITRARY_HOUR:02d}:00:00\")\n", + " print(ds_arbitrary_hour)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.plot(range(len(ds_arbitrary_hour[\"speed10\"].values)), ds_arbitrary_hour[\"speed10\"].values)\n", + "plt.xlabel(\"Index\")\n", + "plt.ylabel(\"Wind Speed (m/s)\")\n", + "plt.title(f\"Wind Speed at {str(ds_arbitrary_hour.time.values)}\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 6), subplot_kw={\"projection\": ccrs.PlateCarree()})\n", + "ax.coastlines()\n", + "ax.add_feature(cfeature.LAND)\n", + "ax.add_feature(cfeature.OCEAN)\n", + "quiver = ax.quiver(\n", + " ds_arbitrary_hour[\"longitude\"].values,\n", + " ds_arbitrary_hour[\"latitude\"].values,\n", + " ds_arbitrary_hour[\"u10\"].values,\n", + " ds_arbitrary_hour[\"v10\"].values,\n", + " ds_arbitrary_hour[\"speed10\"].values,\n", + " cmap=\"cool\",\n", + ")\n", + "ax.set_title(f\"Wind on {str(ds_arbitrary_hour.time.values)}\")\n", + "fig.colorbar(quiver, ax=ax, label=\"Speed (m/s)\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots()\n", + "\n", + "time_values = np.linspace(0, 3, 40)\n", + "\n", + "initial_velocity_1 = 12\n", + "initial_velocity_2 = 10\n", + "\n", + "\n", + "def s_v0t_plus_half_at2(v0, t):\n", + " gravity = -9.81\n", + " return v0 * t + (gravity * t**2) / 2\n", + "\n", + "\n", + "position_1, position_2 = (\n", + " s_v0t_plus_half_at2(initial_velocity_1, time_values),\n", + " s_v0t_plus_half_at2(initial_velocity_2, time_values),\n", + ")\n", + "\n", + "\n", + "scatter_plot = ax.scatter(\n", + " time_values[0],\n", + " position_1[0],\n", + " c=\"blue\",\n", + " s=5,\n", + " label=f\"v0 = {initial_velocity_1} m/s\",\n", + ")\n", + "line_plot = ax.plot(time_values[0], position_2[0], label=f\"v0 = {initial_velocity_2} m/s\")[0]\n", + "\n", + "ax.set(xlim=[0, 3], ylim=[-4, 10], xlabel=\"Time [s]\", ylabel=\"Z [m]\")\n", + "ax.legend()\n", + "\n", + "\n", + "def update(frame):\n", + " current_time = time_values[:frame]\n", + "\n", + " scatter_plot.set_offsets(np.stack([current_time, position_1[:frame]]).T)\n", + "\n", + " line_plot.set_xdata(current_time)\n", + " line_plot.set_ydata(position_2[:frame])\n", + "\n", + " return scatter_plot, line_plot\n", + "\n", + "\n", + "animation_obj = animation.FuncAnimation(fig=fig, func=update, frames=len(time_values), interval=30)\n", + "animation_obj.save(\"projectile_motion.gif\", writer=\"imagemagick\", fps=10)\n", + "plt.clf()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/gif": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df = pd.DataFrame(\n", + " {\n", + " \"longitude\": [10, 20, 30],\n", + " \"latitude\": [5, 15, 25],\n", + " \"precipitation\": [1, 2, 3],\n", + " }\n", + ")\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 6))\n", + "scatter = plt.scatter(\n", + " df[\"longitude\"],\n", + " df[\"latitude\"],\n", + " s=df[\"precipitation\"] * 100,\n", + " alpha=0.5,\n", + " edgecolors=\"blue\",\n", + " c=\"red\",\n", + ")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "latitude=15, longitude=20 value: 4\n", + "np.tile(lon, lat.size)=[10 20 10 20 10 20]\n", + "np.repeat(lat, lon.size)=[ 5 5 15 15 25 25]\n", + "tp.flatten()=[1 2 3 4 5 6]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "data = xr.DataArray(\n", + " np.array([[1, 2], [3, 4], [5, 6]]),\n", + " dims=(\"latitude\", \"longitude\"),\n", + " coords={\"latitude\": [5, 15, 25], \"longitude\": [10, 20]},\n", + ")\n", + "print(f\"latitude=15, longitude=20 value: {data.sel(latitude=15, longitude=20).values}\")\n", + "\n", + "ds = xr.Dataset(\n", + " {\"tp\": ([\"latitude\", \"longitude\"], np.array([[1, 2], [3, 4], [5, 6]]))},\n", + " coords={\"latitude\": np.array([5, 15, 25]), \"longitude\": np.array([10, 20])},\n", + ")\n", + "\n", + "lon = ds[\"longitude\"].values\n", + "lat = ds[\"latitude\"].values\n", + "tp = ds[\"tp\"].values\n", + "\n", + "fig, ax = plt.subplots(figsize=(10, 6))\n", + "\n", + "print(f\"np.tile(lon, lat.size)={np.tile(lon, lat.size)}\")\n", + "print(f\"np.repeat(lat, lon.size)={np.repeat(lat, lon.size)}\")\n", + "print(f\"tp.flatten()={tp.flatten()}\")\n", + "\n", + "scatter = ax.scatter(\n", + " np.tile(lon, lat.size),\n", + " np.repeat(lat, lon.size),\n", + " s=tp.flatten() * 1000,\n", + " alpha=0.5,\n", + " edgecolors=\"blue\",\n", + " c=\"red\",\n", + ")\n", + "\n", + "for i, txt in enumerate(tp.flatten()):\n", + " ax.text(\n", + " np.tile(lon, lat.size)[i],\n", + " np.repeat(lat, lon.size)[i],\n", + " str(txt),\n", + " color=\"black\",\n", + " ha=\"center\",\n", + " va=\"center\",\n", + " )\n", + " if i == 3:\n", + " assert (\n", + " txt == data.sel(latitude=15, longitude=20).values\n", + " ), \"third tp should be lat15,lon=20 value\"\n", + "\n", + "plt.xlabel(\"Longitude\")\n", + "plt.ylabel(\"Latitude\")\n", + "plt.title(\"Precipitation Values in Circles\")\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 6), subplot_kw={\"projection\": ccrs.PlateCarree()})\n", + "\n", + "ax.add_feature(cfeature.LAND)\n", + "ax.add_feature(cfeature.OCEAN)\n", + "\n", + "scatter = ax.scatter(\n", + " np.tile(ds_arbitrary_hour[\"longitude\"].values, ds_arbitrary_hour[\"latitude\"].size),\n", + " np.repeat(ds_arbitrary_hour[\"latitude\"].values, ds_arbitrary_hour[\"longitude\"].size),\n", + " s=ds_arbitrary_hour[\"tp\"].values.flatten() * 1000,\n", + " alpha=0.5,\n", + " edgecolors=\"blue\",\n", + " c=\"red\",\n", + ")\n", + "\n", + "precipitation_values = ds_arbitrary_hour[\"tp\"].values.flatten()\n", + "percentiles = np.nanpercentile(precipitation_values, [50, 75, 95])\n", + "sizes = percentiles * 1000\n", + "labels = [f\"{percentile:.2f}\" for percentile in percentiles]\n", + "\n", + "legend_patches = [\n", + " plt.scatter([], [], s=size, edgecolors=\"blue\", facecolors=\"red\", alpha=0.5, label=label)\n", + " for size, label in zip(sizes, labels)\n", + "]\n", + "\n", + "ax.legend(\n", + " handles=legend_patches,\n", + " title=\"Tp\",\n", + " loc=\"lower right\",\n", + " # bbox_to_anchor=(0, 0),\n", + " title_fontsize=\"small\",\n", + " borderpad=0.9,\n", + " framealpha=0,\n", + ")\n", + "leg = ax.get_legend()\n", + "leg.set_alpha(0)\n", + "\n", + "# plt.subplots_adjust(right=1)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 6), subplot_kw={\"projection\": ccrs.PlateCarree()})\n", + "\n", + "ax.set_title(f\"Wind on {str(ds_arbitrary_hour.time.values)}\")\n", + "ax.coastlines()\n", + "ax.add_feature(cfeature.LAND)\n", + "ax.add_feature(cfeature.OCEAN)\n", + "\n", + "quiver = ax.quiver(\n", + " ds_arbitrary_hour[\"longitude\"].values,\n", + " ds_arbitrary_hour[\"latitude\"].values,\n", + " ds_arbitrary_hour[\"u10\"].values,\n", + " ds_arbitrary_hour[\"v10\"].values,\n", + " ds_arbitrary_hour[\"speed10\"].values,\n", + " cmap=\"cool\",\n", + ")\n", + "\n", + "fig.colorbar(quiver, ax=ax, label=\"Speed (m/s)\")\n", + "\n", + "scatter = ax.scatter(\n", + " np.tile(ds_arbitrary_hour[\"longitude\"].values, ds_arbitrary_hour[\"latitude\"].size),\n", + " np.repeat(ds_arbitrary_hour[\"latitude\"].values, ds_arbitrary_hour[\"longitude\"].size),\n", + " s=ds_arbitrary_hour[\"tp\"].values.flatten() * 1000,\n", + " alpha=0.5,\n", + " edgecolors=\"blue\",\n", + " c=\"black\",\n", + ")\n", + "\n", + "precipitation_values = ds_arbitrary_hour[\"tp\"].values.flatten()\n", + "percentiles = np.nanpercentile(precipitation_values, [50, 75, 95])\n", + "sizes = percentiles * 1000\n", + "labels = [f\"{percentile:.2f}\" for percentile in percentiles]\n", + "\n", + "legend_patches = [\n", + " plt.scatter([], [], s=size, edgecolors=\"blue\", facecolors=\"black\", alpha=0.5, label=label)\n", + " for size, label in zip(sizes, labels)\n", + "]\n", + "\n", + "# ax.legend(\n", + "# handles=legend_patches,\n", + "# title=\"Tp\",\n", + "# loc=\"lower right\",\n", + "# bbox_to_anchor=(0, 0),\n", + "# title_fontsize=\"small\",\n", + "# borderpad=0.9,\n", + "# framealpha=0,\n", + "# )\n", + "\n", + "# plt.subplots_adjust(right=1)\n", + "\n", + "plt.savefig(f\"wind_and_precipitation_{ARBITRARY_HOUR}.png\")\n", + "\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.19" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/goes16.ipynb b/notebooks/GOES16/GOES16.ipynb similarity index 100% rename from notebooks/goes16.ipynb rename to notebooks/GOES16/GOES16.ipynb diff --git a/notebooks/derived_instability_index.ipynb b/notebooks/GOES16/GOES16_DSIF.ipynb similarity index 100% rename from notebooks/derived_instability_index.ipynb rename to notebooks/GOES16/GOES16_DSIF.ipynb diff --git a/notebooks/DSIF_results.ipynb b/notebooks/GOES16/GOES16_DSIF_results.ipynb similarity index 100% rename from notebooks/DSIF_results.ipynb rename to notebooks/GOES16/GOES16_DSIF_results.ipynb diff --git a/notebooks/GOES16/GOES16_GLM.ipynb b/notebooks/GOES16/GOES16_GLM.ipynb new file mode 100644 index 00000000..5b90d2d8 --- /dev/null +++ b/notebooks/GOES16/GOES16_GLM.ipynb @@ -0,0 +1,2407 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 4897, + "status": "ok", + "timestamp": 1687642385810, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "obCShOodaMFY", + "outputId": "5a61791f-a759-4b5f-bb8b-bbaea3a23085" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mkdir: cannot create directory ‘data’: File exists\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mkdir: cannot create directory ‘data/meshes’: File exists\n", + "--2024-08-18 14:23:19-- https://docs.google.com/uc?export=download&id=1V4vOD9TevqZoZCtD70Yz7y62zunGoAU-\n", + "Resolving docs.google.com (docs.google.com)... 142.251.132.14, 2800:3f0:4001:833::200e\n", + "Connecting to docs.google.com (docs.google.com)|142.251.132.14|:443... connected.\n", + "HTTP request sent, awaiting response... 303 See Other\n", + "Location: https://drive.usercontent.google.com/download?id=1V4vOD9TevqZoZCtD70Yz7y62zunGoAU-&export=download [following]\n", + "--2024-08-18 14:23:19-- https://drive.usercontent.google.com/download?id=1V4vOD9TevqZoZCtD70Yz7y62zunGoAU-&export=download\n", + "Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 142.251.132.1, 2800:3f0:4001:833::2001\n", + "Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|142.251.132.1|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 3423788 (3.3M) [application/octet-stream]\n", + "Saving to: ‘data/meshes/meshes.tar.xz’\n", + "\n", + "data/meshes/meshes. 100%[===================>] 3.26M 13.9MB/s in 0.2s \n", + "\n", + "2024-08-18 14:23:30 (13.9 MB/s) - ‘data/meshes/meshes.tar.xz’ saved [3423788/3423788]\n", + "\n", + "RJ_Mesorregioes_2020/\n", + "RJ_Mesorregioes_2020/RJ_Mesorregioes_2020.cpg\n", + "RJ_Mesorregioes_2020/RJ_Mesorregioes_2020.dbf\n", + "RJ_Mesorregioes_2020/RJ_Mesorregioes_2020.prj\n", + "RJ_Mesorregioes_2020/RJ_Mesorregioes_2020.shp\n", + "RJ_Mesorregioes_2020/RJ_Mesorregioes_2020.shx\n", + "RJ_Microrregioes_2020/\n", + "RJ_Microrregioes_2020/RJ_Microrregioes_2020.cpg\n", + "RJ_Microrregioes_2020/RJ_Microrregioes_2020.dbf\n", + "RJ_Microrregioes_2020/RJ_Microrregioes_2020.prj\n", + "RJ_Microrregioes_2020/RJ_Microrregioes_2020.shp\n", + "RJ_Microrregioes_2020/RJ_Microrregioes_2020.shx\n", + "RJ_Municipios_2020/\n", + "RJ_Municipios_2020/RJ_Municipios_2020.cpg\n", + "RJ_Municipios_2020/RJ_Municipios_2020.dbf\n", + "RJ_Municipios_2020/RJ_Municipios_2020.prj\n", + "RJ_Municipios_2020/RJ_Municipios_2020.shp\n", + "RJ_Municipios_2020/RJ_Municipios_2020.shx\n", + "RJ_RG_Imediatas_2020/\n", + "RJ_RG_Imediatas_2020/RJ_RG_Imediatas_2020.cpg\n", + "RJ_RG_Imediatas_2020/RJ_RG_Imediatas_2020.dbf\n", + "RJ_RG_Imediatas_2020/RJ_RG_Imediatas_2020.prj\n", + "RJ_RG_Imediatas_2020/RJ_RG_Imediatas_2020.shp\n", + "RJ_RG_Imediatas_2020/RJ_RG_Imediatas_2020.shx\n", + "RJ_RG_Intermediarias_2020/\n", + "RJ_RG_Intermediarias_2020/RJ_RG_Intermediarias_2020.cpg\n", + "RJ_RG_Intermediarias_2020/RJ_RG_Intermediarias_2020.dbf\n", + "RJ_RG_Intermediarias_2020/RJ_RG_Intermediarias_2020.prj\n", + "RJ_RG_Intermediarias_2020/RJ_RG_Intermediarias_2020.shp\n", + "RJ_RG_Intermediarias_2020/RJ_RG_Intermediarias_2020.shx\n", + "RJ_UF_2020/\n", + "RJ_UF_2020/RJ_UF_2020.cpg\n", + "RJ_UF_2020/RJ_UF_2020.dbf\n", + "RJ_UF_2020/RJ_UF_2020.prj\n", + "RJ_UF_2020/RJ_UF_2020.shp\n", + "RJ_UF_2020/RJ_UF_2020.shx\n" + ] + } + ], + "source": [ + "!mkdir data\n", + "!mkdir data/meshes\n", + "!wget --no-check-certificate 'https://docs.google.com/uc?export=download&id=1V4vOD9TevqZoZCtD70Yz7y62zunGoAU-' -O data/meshes/meshes.tar.xz\n", + "!tar -xvf data/meshes/meshes.tar.xz -C data/meshes\n", + "!rm data/meshes/meshes.tar.xz" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 9781, + "status": "ok", + "timestamp": 1687642411479, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "ygWPtPLVoUit", + "outputId": "603d04ea-7090-4e37-e67c-d747aa2ddf02" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: geopandas in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (0.14.4)\n", + "Requirement already satisfied: fiona>=1.8.21 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from geopandas) (1.9.6)\n", + "Requirement already satisfied: shapely>=1.8.0 in 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"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from requests->folium) (1.26.17)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from requests->folium) (2024.2.2)\n", + "Requirement already satisfied: charset-normalizer<3,>=2 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from requests->folium) (2.1.1)\n", + "Requirement already satisfied: idna<4,>=2.5 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from requests->folium) (3.4)\n" + ] + } + ], + "source": [ + "#!pip install numpy\n", + "#bibliotecas necessárias para rodar os códigos\n", + "!pip install geopandas\n", + "!pip install folium\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "from shapely.geometry import Polygon, Point\n", + "import geopandas as gpd\n", + "import folium\n", + "import matplotlib.pyplot as plt\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 224 + }, + "executionInfo": { + "elapsed": 1352, + "status": "ok", + "timestamp": 1687642412825, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "k11jt3uyaRZc", + "outputId": "bbd6547f-5631-44e9-d31c-9e857310d95d" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(92, 5)\n" + ] + }, + { + "data": { + "text/html": [ + "
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" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import re\n", + "\n", + "#rj_city = rj_state[rj_state['NM_UF'].str.contains('rio de janeiro', flags=re.IGNORECASE)]\n", + "rj_city = rj_state[rj_state['NM_MUN'].str.contains('rio de janeiro', flags=re.IGNORECASE)]\n", + "rj_city" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 493, + "status": "ok", + "timestamp": 1682185660487, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "hv4Tcn71aDDY", + "outputId": "9fbab371-4d8a-4ac7-c639-434607aa00f9" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "\n", + "Name: SIRGAS 2000\n", + "Axis Info [ellipsoidal]:\n", + "- Lat[north]: Geodetic latitude (degree)\n", + "- Lon[east]: Geodetic longitude (degree)\n", + "Area of Use:\n", + "- name: Latin America - Central America and South America - onshore and offshore. Brazil - onshore and offshore.\n", + "- bounds: (-122.19, -59.87, -25.28, 32.72)\n", + "Datum: Sistema de Referencia Geocentrico para las AmericaS 2000\n", + "- Ellipsoid: GRS 1980\n", + "- Prime Meridian: Greenwich" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "rj_city.crs" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 337 + }, + "executionInfo": { + "elapsed": 9, + "status": "ok", + "timestamp": 1682185662205, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "P6TZnhSdavZ1", + "outputId": "9f732577-4013-4bf6-e7bc-c0c5f7a8ce4b" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "rj_city.plot()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 466 + }, + "executionInfo": { + "elapsed": 1806, + "status": "ok", + "timestamp": 1682185683834, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "tugHrvOjcdcq", + "outputId": "bf9be748-c0cb-4107-c817-e9479b128f0b" + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def plot_rj_city():\n", + " plt_args = {'color': '#CCCCCC',\n", + " 'edgecolor': 'white',\n", + " 'linewidth': 0.5}\n", + " ax = rj_city.plot(figsize=(10,8),\n", + " alpha=1,\n", + " **plt_args)\n", + " return ax\n", + "ax = plot_rj_city()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tUotd3HpDBwN" + }, + "source": [ + "## GOES16 Data on AWS\n", + "\n", + "Beginner's guide to GOES-R data - https://www.goes-r.gov/downloads/resources/documents/Beginners_Guide_to_GOES-R_Series_Data.pdf\n", + "\n", + "GOES16 filename convention - https://docs.opendata.aws/noaa-goes16/cics-readme.html\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 5687, + "status": "ok", + "timestamp": 1687642078862, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "IXqF1OH5DDHl", + "outputId": "8af4ee56-4430-4c2b-a2e9-48f2c06e45ed" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: s3fs in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (2023.9.2)\n", + "Requirement already satisfied: aiobotocore~=2.5.4 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from s3fs) (2.5.4)\n", + "Requirement already satisfied: fsspec==2023.9.2 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from s3fs) (2023.9.2)\n", + "Requirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from s3fs) (3.8.6)\n", + "Requirement already satisfied: aioitertools<1.0.0,>=0.5.1 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiobotocore~=2.5.4->s3fs) (0.11.0)\n", + "Requirement already satisfied: botocore<1.31.18,>=1.31.17 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiobotocore~=2.5.4->s3fs) (1.31.17)\n", + "Requirement already satisfied: wrapt<2.0.0,>=1.10.10 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiobotocore~=2.5.4->s3fs) (1.15.0)\n", + "Requirement already satisfied: aiosignal>=1.1.2 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (1.3.1)\n", + "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (4.0.3)\n", + "Requirement already satisfied: attrs>=17.3.0 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (22.2.0)\n", + "Requirement already satisfied: yarl<2.0,>=1.0 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (1.9.2)\n", + "Requirement already satisfied: multidict<7.0,>=4.5 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (6.0.4)\n", + "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (2.1.1)\n", + "Requirement already satisfied: frozenlist>=1.1.1 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (1.4.0)\n", + "Requirement already satisfied: urllib3<1.27,>=1.25.4 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from botocore<1.31.18,>=1.31.17->aiobotocore~=2.5.4->s3fs) (1.26.17)\n", + "Requirement already satisfied: jmespath<2.0.0,>=0.7.1 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from botocore<1.31.18,>=1.31.17->aiobotocore~=2.5.4->s3fs) (1.0.1)\n", + "Requirement already satisfied: python-dateutil<3.0.0,>=2.1 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from botocore<1.31.18,>=1.31.17->aiobotocore~=2.5.4->s3fs) (2.8.2)\n", + "Requirement already satisfied: idna>=2.0 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from yarl<2.0,>=1.0->aiohttp!=4.0.0a0,!=4.0.0a1->s3fs) (3.4)\n", + "Requirement already satisfied: six>=1.5 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.31.18,>=1.31.17->aiobotocore~=2.5.4->s3fs) (1.16.0)\n" + ] + } + ], + "source": [ + "!pip install s3fs" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "id": "ILH32QZvEecG" + }, + "outputs": [], + "source": [ + "import s3fs\n", + "import xarray as xr\n", + "import datetime as dt\n", + "import argparse" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "E9x2G40XQ145" + }, + "source": [ + "# Nova seção" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "id": "viJTgARNFBLk" + }, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "noaa-goes16/ABI-L2-DMWF/2021/0/0", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[14], line 31\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m hours \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;241m24\u001b[39m):\n\u001b[1;32m 30\u001b[0m target \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnoaa-goes16/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mproduct\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mdata_year_current\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00myear_for_days_current\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mstr\u001b[39m(hours)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m---> 31\u001b[0m files \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(\u001b[43mfs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mls\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtarget\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 32\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m(\u001b[38;5;28mlen\u001b[39m(files)\u001b[38;5;241m>\u001b[39m\u001b[38;5;241m0\u001b[39m):\n\u001b[1;32m 33\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mrange\u001b[39m(\u001b[38;5;28mlen\u001b[39m(files)):\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/fsspec/asyn.py:118\u001b[0m, in \u001b[0;36msync_wrapper..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 115\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m 116\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 117\u001b[0m \u001b[38;5;28mself\u001b[39m \u001b[38;5;241m=\u001b[39m obj \u001b[38;5;129;01mor\u001b[39;00m args[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m--> 118\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msync\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloop\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfunc\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/fsspec/asyn.py:103\u001b[0m, in \u001b[0;36msync\u001b[0;34m(loop, func, timeout, *args, **kwargs)\u001b[0m\n\u001b[1;32m 101\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m FSTimeoutError \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mreturn_result\u001b[39;00m\n\u001b[1;32m 102\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(return_result, \u001b[38;5;167;01mBaseException\u001b[39;00m):\n\u001b[0;32m--> 103\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m return_result\n\u001b[1;32m 104\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 105\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m return_result\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/fsspec/asyn.py:56\u001b[0m, in \u001b[0;36m_runner\u001b[0;34m(event, coro, result, timeout)\u001b[0m\n\u001b[1;32m 54\u001b[0m coro \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mwait_for(coro, timeout\u001b[38;5;241m=\u001b[39mtimeout)\n\u001b[1;32m 55\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m---> 56\u001b[0m result[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mawait\u001b[39;00m coro\n\u001b[1;32m 57\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m ex:\n\u001b[1;32m 58\u001b[0m result[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m=\u001b[39m ex\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/s3fs/core.py:996\u001b[0m, in \u001b[0;36mS3FileSystem._ls\u001b[0;34m(self, path, detail, refresh, versions)\u001b[0m\n\u001b[1;32m 990\u001b[0m files \u001b[38;5;241m=\u001b[39m [\n\u001b[1;32m 991\u001b[0m o\n\u001b[1;32m 992\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m o \u001b[38;5;129;01min\u001b[39;00m files\n\u001b[1;32m 993\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m o[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mrstrip(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;241m==\u001b[39m path \u001b[38;5;129;01mand\u001b[39;00m o[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtype\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdirectory\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 994\u001b[0m ]\n\u001b[1;32m 995\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m files:\n\u001b[0;32m--> 996\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m(path)\n\u001b[1;32m 997\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m detail:\n\u001b[1;32m 998\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m files\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: noaa-goes16/ABI-L2-DMWF/2021/0/0" + ] + } + ], + "source": [ + "fs = s3fs.S3FileSystem(anon=True)\n", + "product = \"ABI-L2-DMWF\"\n", + "products = fs.ls('s3://noaa-goes16/')\n", + "\n", + "# extraindo os dados da data de inicio e data de fim usando args do python\n", + "#parser = argparse.ArgumentParser(description = \"Entra com a data de inicio e data de fim. Para colocar a data no formato dd/mm/yyyy \")\n", + "#parser.add_argument(\"datei\",type=str,help=\"data de inicio\")\n", + "#parser.add_argument(\"datef\",type=str,help=\"data de fim\")\n", + "#args = parser.parse_args()\n", + "#start_date = dt.date(int((args.datei).split(\"/\")[2]),int((args.datei).split(\"/\")[1])),int(args.datei).split(\"/\")[0]))\n", + "#end_date = dt.date(int((args.datef).split(\"/\")[2])),int((args.datef).split(\"/\")[1]),int((args.datef).split(\"/\")[0]))\n", + "\n", + "# extraindo os dados da data de inicio e data de fim de forma normal\n", + "start_date = dt.date(2021,1,1)\n", + "end_date = dt.date(2021,1,1)\n", + "arquivos =[]\n", + "data_year_current = start_date.year\n", + "if(start_date == end_date):\n", + " days_traveled = 0\n", + "else:\n", + " days_traveled = int((str(end_date - start_date)).split(\" \")[0])\n", + "if(start_date == dt.date(start_date.year,1,1)):\n", + " year_for_days = 0\n", + "else:\n", + " year_for_days = int((str(start_date-dt.date(start_date.year,1,1))).split(\" \")[0])+1\n", + "add_days = 0\n", + "for dsp in range(days_traveled+1):\n", + " year_for_days_current = str(year_for_days+add_days)\n", + " for hours in range(24):\n", + " target = f'noaa-goes16/{product}/{data_year_current}/{year_for_days_current}/{str(hours)}'\n", + " files = np.array(fs.ls(target))\n", + " if(len(files)>0):\n", + " for i in range(len(files)):\n", + " print(files)\n", + " filename = files[i].split('/')[-1]\n", + " arquivos.append(filename)\n", + " fs.get(files[i], filename)\n", + " ds = xr.open_dataset(filename)\n", + " if(int(year_for_days_current) == 365):\n", + " data_year_current = int(data_year_current)+1\n", + " add_days = 0\n", + " year_for_days = 1\n", + " else:\n", + " add_days = add_days+1\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "uQOo4x9Zzz07" + }, + "outputs": [], + "source": [ + "listaValoresWind = []\n", + "i = 0\n", + "def filter_coordinates(ds:xr.Dataset):\n", + " return ds[[\"wind_speed\"]].where(\n", + " (ds['lat'] >= -23.082616) & (ds['lat'] <= -22.768942) &\n", + " (ds['lon'] >= -43.823426) & (ds['lon'] <= -43.154634),\n", + " drop=True)\n", + "for arq in arquivos:\n", + " if i==3:\n", + " break\n", + " ds = xr.open_dataset(arq)\n", + " i+=1\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "executionInfo": { + "elapsed": 266, + "status": "ok", + "timestamp": 1687642316783, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "7TYc88jpySiY", + "outputId": "61ce422c-0a16-41db-e591-97b986c13ec2" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "oi\n" + ] + } + ], + "source": [ + "print(\"oi\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + }, + "executionInfo": { + "elapsed": 449, + "status": "error", + "timestamp": 1687640656784, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "dNlW_wWoKvbZ", + "outputId": "2dccf62e-dae3-45bf-88ec-0d1ea3af90dd" + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "ignored", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'lon'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m>=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m43.823426\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'lon'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m43.154634\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 17\u001b[0m drop=True)\n\u001b[0;32m---> 18\u001b[0;31m \u001b[0mfilter_coordinates\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 19\u001b[0m \u001b[0mds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"wind_speed\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mNameError\u001b[0m: name 'ds' is not defined" + ] + } + ], + "source": [ + "# rj = dict()\n", + "# rj['coords'] = {'n_lat': -22.768942,\n", + "# 's_lat': -23.082616,\n", + "# 'w_lon': -43.823426,\n", + "# 'e_lon': -43.154634}\n", + "\n", + "# def filter_coordinates(ds:xr.Dataset, coords):\n", + "# return ds['event_energy'].where(\n", + "# (ds['event_lat'] >= coords['s_lat']) & (ds['event_lat'] <= coords['n_lat']) &\n", + "# (ds['event_lon'] >= coords['w_lon']) & (ds['event_lon'] <= coords['e_lon']),\n", + "# drop=True)\n", + "\n", + "def filter_coordinates(ds:xr.Dataset):\n", + " return ds[[\"wind_speed\",\"temperature\",\"wind_direction\"]].where(\n", + " (ds['lat'] >= -23.082616) & (ds['lat'] <= -22.768942) &\n", + " (ds['lon'] >= -43.823426) & (ds['lon'] <= -43.154634),\n", + " drop=True)\n", + "filter_coordinates(ds)\n", + "ds[\"wind_speed\"]\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uXdY1V0SB6W7" + }, + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "jZbP6M73K1Wk" + }, + "outputs": [], + "source": [ + "# try:\n", + "# ds = filter_coordinates(ds, rj['coords'])\n", + "# except ValueError:\n", + "# print('Value Error')\n", + "\n", + "try:\n", + " ds = filter_coordinates(ds)\n", + "except ValueError:\n", + " print('Value Error')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 368 + }, + "executionInfo": { + "elapsed": 4, + "status": "ok", + "timestamp": 1687629042330, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "_CezZNImFLeu", + "outputId": "6cdda980-8cb8-4c30-84ae-1d38029a8db1" + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
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wind_speedtemperaturewind_directionlatlontimepressurelocal_zenith_anglesolar_zenith_anglelat_imagelon_imageretrieval_local_zenith_angle
nMeasures
0NaNNaNNaN-22.868574-43.6167562021-04-14 13:00:18.604036992NaN44.18277742.5005530.0-75.090.0
1NaNNaNNaN-22.961721-43.3599402021-04-14 13:00:18.604036992NaN44.46288342.4019280.0-75.090.0
2NaNNaNNaN-22.961721-43.3599402021-04-14 13:00:18.604036992NaN44.46288342.4019280.0-75.090.0
3NaNNaNNaN-22.964491-43.2829862021-04-14 13:00:18.604036992NaN44.53171942.3546070.0-75.090.0
4NaNNaNNaN-23.032961-43.7166332021-04-14 13:00:18.604036992NaN44.19536242.6822740.0-75.090.0
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wind_speedtemperaturewind_directionlatlondatepressurelocal_zenith_anglesolar_zenith_anglelat_imagelon_imageretrieval_local_zenith_angle
nMeasures
0NaNNaNNaN-22.868574-43.6167562021-04-14 13:00:18.604036992NaN44.18277742.5005530.0-75.090.0
1NaNNaNNaN-22.961721-43.3599402021-04-14 13:00:18.604036992NaN44.46288342.4019280.0-75.090.0
2NaNNaNNaN-22.961721-43.3599402021-04-14 13:00:18.604036992NaN44.46288342.4019280.0-75.090.0
3NaNNaNNaN-22.964491-43.2829862021-04-14 13:00:18.604036992NaN44.53171942.3546070.0-75.090.0
4NaNNaNNaN-23.032961-43.7166332021-04-14 13:00:18.604036992NaN44.19536242.6822740.0-75.090.0
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Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 wind_speed 0 non-null float32\n", + " 1 temperature 0 non-null float32\n", + " 2 wind_direction 0 non-null float32\n", + " 3 lat 5 non-null float64\n", + " 4 lon 5 non-null float64\n", + " 5 date 5 non-null object \n", + " 6 pressure 0 non-null float32\n", + " 7 local_zenith_angle 5 non-null float32\n", + " 8 solar_zenith_angle 5 non-null float32\n", + " 9 lat_image 5 non-null float32\n", + " 10 lon_image 5 non-null float32\n", + " 11 retrieval_local_zenith_angle 5 non-null float32\n", + "dtypes: float32(9), float64(2), object(1)\n", + "memory usage: 428.0+ bytes\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 368 + }, + "executionInfo": { + "elapsed": 313, + "status": "ok", + "timestamp": 1687628609480, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "Biyep76axtha", + "outputId": "45c7ef81-2988-4f98-ce86-15bf024f8df8" + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "
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wind_speedtemperaturewind_directionlatlondatepressurelocal_zenith_anglesolar_zenith_anglelat_imagelon_imageretrieval_local_zenith_angle
nMeasures
0NaNNaNNaN-22.868574-43.6167562021-04-14 13:00:18.604036992NaN44.18277742.5005530.0-75.090.0
1NaNNaNNaN-22.961721-43.3599402021-04-14 13:00:18.604036992NaN44.46288342.4019280.0-75.090.0
2NaNNaNNaN-22.961721-43.3599402021-04-14 13:00:18.604036992NaN44.46288342.4019280.0-75.090.0
3NaNNaNNaN-22.964491-43.2829862021-04-14 13:00:18.604036992NaN44.53171942.3546070.0-75.090.0
4NaNNaNNaN-23.032961-43.7166332021-04-14 13:00:18.604036992NaN44.19536242.6822740.0-75.090.0
\n", + "
\n", + " \n", + " \n", + " \n", + "\n", + " \n", + "
\n", + "
\n", + " " + ], + "text/plain": [ + " wind_speed temperature wind_direction lat lon \\\n", + "nMeasures \n", + "0 NaN NaN NaN -22.868574 -43.616756 \n", + "1 NaN NaN NaN -22.961721 -43.359940 \n", + "2 NaN NaN NaN -22.961721 -43.359940 \n", + "3 NaN NaN NaN -22.964491 -43.282986 \n", + "4 NaN NaN NaN -23.032961 -43.716633 \n", + "\n", + " date pressure local_zenith_angle \\\n", + "nMeasures \n", + "0 2021-04-14 13:00:18.604036992 NaN 44.182777 \n", + "1 2021-04-14 13:00:18.604036992 NaN 44.462883 \n", + "2 2021-04-14 13:00:18.604036992 NaN 44.462883 \n", + "3 2021-04-14 13:00:18.604036992 NaN 44.531719 \n", + "4 2021-04-14 13:00:18.604036992 NaN 44.195362 \n", + "\n", + " solar_zenith_angle lat_image lon_image \\\n", + "nMeasures \n", + "0 42.500553 0.0 -75.0 \n", + "1 42.401928 0.0 -75.0 \n", + "2 42.401928 0.0 -75.0 \n", + "3 42.354607 0.0 -75.0 \n", + "4 42.682274 0.0 -75.0 \n", + "\n", + " retrieval_local_zenith_angle \n", + "nMeasures \n", + "0 90.0 \n", + "1 90.0 \n", + "2 90.0 \n", + "3 90.0 \n", + "4 90.0 " + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head(32)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 235 + }, + "executionInfo": { + "elapsed": 273, + "status": "error", + "timestamp": 1687628674284, + "user": { + "displayName": "allan jose", + "userId": "15792183204536819831" + }, + "user_tz": 180 + }, + "id": "SS0L0TlmoeJG", + "outputId": "31474c7f-6ade-4d36-b8d5-33cbada9210a" + }, + "outputs": [ + { + "ename": "NameError", + "evalue": "ignored", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0max\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_rj_city\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m gdf.plot(column='wind_direction',\n\u001b[1;32m 4\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m legend=True)\n", + "\u001b[0;31mNameError\u001b[0m: name 'plot_rj_city' is not defined" + ] + } + ], + "source": [ + "ax = plot_rj_city()\n", + "\n", + "gdf.plot(column='wind_direction',\n", + " ax=ax,\n", + " legend=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 671 + }, + "id": "H0CLHdeQnljm", + "outputId": "1c913a5a-7073-4629-9797-9a7d4c4559f2" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = plot_rj_city()\n", + "gdf.plot(column='temperature',\n", + " ax=ax,\n", + " legend=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 684 + }, + "id": "ZQf-2SGEJ3x0", + "outputId": "323a68a8-1760-4e0b-8948-e5a86ad902a1" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = plot_rj_city()\n", + "gdf.plot(column='wind_speed',\n", + " ax=ax,\n", + " legend=True)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "eGIQV3dQyndx" + }, + "outputs": [], + "source": [ + "import json\n", + "p =gdf.to_json()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 787 + }, + "id": "V8C56K4wtfyn", + "outputId": "0fce0c40-4726-4b80-db03-f6c78c111f90" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_dict = json.loads(p)\n", + "coord = []\n", + "\n", + "atributo = [\"wind_speed\",\"wind_direction\",\"temperature\"]\n", + "nameAtributo = [\"Velocidade do vento\",\"direcao do vento\", \"temperatura\"]\n", + "options =0\n", + "\n", + "for k in range(len(data_dict['features'])):\n", + " for t, valor in data_dict['features'][k]['properties'].items():\n", + " if(t == atributo[options]):\n", + " dado = valor\n", + " if (t == \"lat\"):\n", + " latitude= valor\n", + " if (t == \"lon\"):\n", + " longitude = valor\n", + " if(dado != None):\n", + " coord.append([latitude,longitude,dado])\n", + "\n", + "m = folium.Map(location=[-22.9035,-43.2096], zoom_start=7)\n", + "for b in coord:\n", + " folium.Marker(\n", + " [b[0], b[1]], popup=\"\"+nameAtributo[options]+\" é : \"+str(b[2])+\"\", tooltip=\"É só clicar!\"\n", + ").add_to(m)\n", + "\n", + "m\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Teste" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "from netCDF4 import Dataset\n", + "import numpy as np\n", + "\n", + "def crop_full_disk(file_path, extent):\n", + " \"\"\"\n", + " Filter GLM events in a NetCDF file based on the provided coordinate bounds.\n", + "\n", + " Parameters:\n", + " file_path (str): Path to the input NetCDF file.\n", + " lon_min (float): Minimum longitude of the bounding box.\n", + " lon_max (float): Maximum longitude of the bounding box.\n", + " lat_min (float): Minimum latitude of the bounding box.\n", + " lat_max (float): Maximum latitude of the bounding box.\n", + " \n", + " Returns:\n", + " Dataset: A new in-memory NetCDF Dataset object containing filtered data.\n", + " \"\"\"\n", + " try:\n", + " lon_min, lat_min, lon_max, lat_max = extent\n", + " \n", + " # Open the original NetCDF file in read mode\n", + " dataset = Dataset(file_path, 'r')\n", + " \n", + " # Get the longitude and latitude variables\n", + " longitudes = dataset.variables['flash_lon'][:]\n", + " latitudes = dataset.variables['flash_lat'][:]\n", + " \n", + " # Create a mask for the bounding box\n", + " mask = (\n", + " (longitudes >= lon_min) & (longitudes <= lon_max) &\n", + " (latitudes >= lat_min) & (latitudes <= lat_max)\n", + " )\n", + "\n", + " # Create an in-memory NetCDF dataset for filtered data\n", + " filtered_dataset = Dataset('filtered_data.nc', 'w', format='NETCDF4', memory=True)\n", + " \n", + " # Copy global attributes\n", + " filtered_dataset.setncatts({attr: dataset.getncattr(attr) for attr in dataset.ncattrs()})\n", + " \n", + " # Copy dimensions\n", + " for dim_name, dim in dataset.dimensions.items():\n", + " filtered_dataset.createDimension(dim_name, len(dim) if not dim.isunlimited() else None)\n", + " \n", + " # Copy variables and apply the mask\n", + " for var_name, var in dataset.variables.items():\n", + " # Create the new variable in the filtered dataset\n", + " filtered_var = filtered_dataset.createVariable(var_name, var.datatype, var.dimensions)\n", + " \n", + " # Copy variable attributes\n", + " filtered_var.setncatts({attr: var.getncattr(attr) for attr in var.ncattrs()})\n", + " \n", + " # Apply the mask if the variable is related to flash events\n", + " if var_name in ['flash_lon', 'flash_lat']:\n", + " filtered_var[:] = var[:][mask]\n", + " elif 'event_id' in var.dimensions or 'flash_id' in var.dimensions:\n", + " filtered_var[:] = np.compress(mask, var[:], axis=0)\n", + " else:\n", + " filtered_var[:] = var[:]\n", + " \n", + " # Close the original dataset\n", + " dataset.close()\n", + " \n", + " # Return the filtered dataset\n", + " return filtered_dataset\n", + " \n", + " except Exception as e:\n", + " print(f\"An error occurred: {e}\")\n", + " return None\n" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "lat_max, lon_max = (\n", + " -21.699774257353113,\n", + " -42.35676996062447,\n", + ") # canto superior direito\n", + "lat_min, lon_min = (\n", + " -23.801876626302175,\n", + " -45.05290312102409,\n", + ") # canto inferior esquerdo\n", + "extent = [lon_min, lat_min, lon_max, lat_max]\n", + "\n", + "file_name = \"../../data/goes16/glm/OR_GLM-L2-LCFA_G16_s20233220027200_e20233220027400_c20233220027419.nc\"\n", + "# file_name = \"../../data/goes16/glm/OR_GLM-L2-LCFA_G16_s20233220000000_e20233220000200_c20233220000221.nc\"\n", + "filtered_ds = crop_full_disk(file_name, extent)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "# ./downloads/OR_GLM-L2-LCFA_G16_s20240390111400_e20240390112000_c20240390112014.nc\n", + "\n", + "lat_max, lon_max = (\n", + " -21.699774257353113,\n", + " -42.35676996062447,\n", + ") # canto superior direito\n", + "lat_min, lon_min = (\n", + " -23.801876626302175,\n", + " -45.05290312102409,\n", + ") # canto inferior esquerdo\n", + "extent = [lon_min, lat_min, lon_max, lat_max]\n", + "\n", + "file_name = \"../../downloads/OR_GLM-L2-LCFA_G16_s20240390111400_e20240390112000_c20240390112014.nc\"\n", + "filtered_ds = crop_full_disk(file_name, extent)" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "def plot_filtered_dataset(filtered_dataset):\n", + " \"\"\"\n", + " Plot the filtered GLM events from the in-memory NetCDF dataset.\n", + " \n", + " Parameters:\n", + " filtered_dataset (Dataset): The filtered in-memory NetCDF dataset.\n", + " \"\"\"\n", + " try:\n", + " # Extract the filtered longitude and latitude variables\n", + " longitudes = filtered_dataset.variables['flash_lon'][:]\n", + " latitudes = filtered_dataset.variables['flash_lat'][:]\n", + "\n", + " # Create a scatter plot\n", + " plt.figure(figsize=(10, 6))\n", + " plt.scatter(longitudes, latitudes, s=1, color='blue', alpha=0.6, label='GLM Events')\n", + "\n", + " # Add labels, title, and legend\n", + " plt.xlabel(\"Longitude\")\n", + " plt.ylabel(\"Latitude\")\n", + " plt.title(\"Filtered GLM Flash Events\")\n", + " plt.legend()\n", + " plt.grid(True)\n", + " plt.show()\n", + "\n", + " except Exception as e:\n", + " print(f\"An error occurred while plotting: {e}\")\n", + "\n", + "plot_filtered_dataset(filtered_ds)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [], + "source": [ + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import matplotlib.pyplot as plt\n", + "from netCDF4 import Dataset\n", + "\n", + "def plot_filtered_dataset(filtered_dataset, extent):\n", + " \"\"\"\n", + " Plot the filtered NetCDF dataset on a map.\n", + "\n", + " Parameters:\n", + " filtered_dataset (Dataset): The in-memory filtered NetCDF dataset.\n", + " lon_min, lon_max, lat_min, lat_max: Geographic bounds for the map.\n", + " \"\"\"\n", + " \n", + " lon_min, lat_min, lon_max, lat_max = extent\n", + "\n", + " # Extract filtered longitude and latitude\n", + " longitudes = filtered_dataset.variables['flash_lon'][:]\n", + " latitudes = filtered_dataset.variables['flash_lat'][:]\n", + "\n", + " # Initialize the map\n", + " fig, ax = plt.subplots(figsize=(10, 8), \n", + " subplot_kw={'projection': ccrs.PlateCarree()})\n", + "\n", + " # Set map extent\n", + " ax.set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())\n", + "\n", + " # Add map features\n", + " ax.add_feature(cfeature.COASTLINE, linewidth=0.5)\n", + " ax.add_feature(cfeature.BORDERS, linestyle=':')\n", + " ax.add_feature(cfeature.LAND, edgecolor='black', facecolor='lightgray')\n", + " ax.add_feature(cfeature.LAKES, edgecolor='black', facecolor='lightblue')\n", + " # ax.add_feature(cfeature.RIVERS, edgecolor='blue')\n", + "\n", + " # Plot the data points\n", + " sc = ax.scatter(longitudes, latitudes, c='red', s=5, alpha=0.7, transform=ccrs.PlateCarree())\n", + "\n", + " # Add labels\n", + " plt.title(\"Filtered GLM Data\", fontsize=16)\n", + " plt.xlabel(\"Longitude\")\n", + " plt.ylabel(\"Latitude\")\n", + " plt.colorbar(sc, label='Flash Data Intensity') # Optional: Customize this for specific data.\n", + "\n", + " # Show the map\n", + " plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# file_name = \"../../data/goes16/glm/OR_GLM-L2-LCFA_G16_s20233220027200_e20233220027400_c20233220027419.nc\"\n", + "# filtered_ds = crop_full_disk(file_name, extent)\n", + "plot_filtered_dataset(filtered_ds, extent)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import matplotlib.pyplot as plt\n", + "from netCDF4 import Dataset\n", + "\n", + "def plot_filtered_dataset(filtered_dataset, extent):\n", + " \"\"\"\n", + " Plot the filtered NetCDF dataset on a map and include the file timestamp.\n", + "\n", + " Parameters:\n", + " filtered_dataset (Dataset): The in-memory filtered NetCDF dataset.\n", + " lon_min, lon_max, lat_min, lat_max: Geographic bounds for the map.\n", + " \"\"\"\n", + "\n", + " lon_min, lat_min, lon_max, lat_max = extent\n", + "\n", + " # Extract filtered longitude and latitude\n", + " longitudes = filtered_dataset.variables['flash_lon'][:]\n", + " latitudes = filtered_dataset.variables['flash_lat'][:]\n", + "\n", + " # Extract timestamp from the dataset's global attributes\n", + " timestamp = filtered_dataset.getncattr('time_coverage_start') # Example global attribute\n", + " timestamp_formatted = timestamp.replace('T', ' ').replace('Z', '') # Format timestamp\n", + " \n", + " # Initialize the map\n", + " fig, ax = plt.subplots(figsize=(10, 8), \n", + " subplot_kw={'projection': ccrs.PlateCarree()})\n", + "\n", + " # Set map extent\n", + " ax.set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())\n", + "\n", + " # Add map features\n", + " ax.add_feature(cfeature.COASTLINE, linewidth=0.5)\n", + " ax.add_feature(cfeature.BORDERS, linestyle=':')\n", + " ax.add_feature(cfeature.LAND, edgecolor='black', facecolor='lightgray')\n", + " ax.add_feature(cfeature.LAKES, edgecolor='black', facecolor='lightblue')\n", + " ax.add_feature(cfeature.RIVERS, edgecolor='blue')\n", + "\n", + " # Plot the data points\n", + " sc = ax.scatter(longitudes, latitudes, c='red', s=5, alpha=0.7, transform=ccrs.PlateCarree())\n", + "\n", + " # Add labels and timestamp\n", + " plt.title(\"Filtered GLM Data\", fontsize=16)\n", + " plt.xlabel(\"Longitude\")\n", + " plt.ylabel(\"Latitude\")\n", + " plt.colorbar(sc, label='Flash Data Intensity') # Optional: Customize this for specific data.\n", + "\n", + " # Add timestamp to the plot\n", + " plt.annotate(f\"Timestamp: {timestamp_formatted}\",\n", + " xy=(0.05, 0.02), xycoords='figure fraction',\n", + " fontsize=10, color='blue', backgroundcolor='white')\n", + "\n", + " # Show the map\n", + " plt.show()\n", + "\n", + "plot_filtered_dataset(filtered_ds, extent)" + ] + } + ], + "metadata": { + "colab": { + "provenance": [], + "toc_visible": true + }, + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/notebooks/Projecting_GOES_ABI_L2_ACMC_onto_grid.ipynb b/notebooks/GOES16/GOES16_Projecting_GOES_ABI_L2_ACMC_onto_grid.ipynb similarity index 100% rename from notebooks/Projecting_GOES_ABI_L2_ACMC_onto_grid.ipynb rename to notebooks/GOES16/GOES16_Projecting_GOES_ABI_L2_ACMC_onto_grid.ipynb diff --git a/notebooks/agrometeorology_course.ipynb b/notebooks/GOES16/GOES16_agrometeorology_course.ipynb similarity index 100% rename from notebooks/agrometeorology_course.ipynb rename to notebooks/GOES16/GOES16_agrometeorology_course.ipynb diff --git a/notebooks/GOES16/GOES16_animation.ipynb b/notebooks/GOES16/GOES16_animation.ipynb new file mode 100644 index 00000000..42fe51e4 --- /dev/null +++ b/notebooks/GOES16/GOES16_animation.ipynb @@ -0,0 +1,1188 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# %load ../src/goes16_utils.py\n", + "# Training: Python and GOES-R Imagery: Script 8 - Functions for download data from AWS\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Required modules\n", + "import os # Miscellaneous operating system interfaces\n", + "import numpy as np # Import the Numpy package\n", + "import colorsys # To make convertion of colormaps\n", + "import boto3 # Amazon Web Services (AWS) SDK for Python\n", + "from botocore import UNSIGNED # boto3 config\n", + "from botocore.config import Config # boto3 config\n", + "import math # Mathematical functions\n", + "from datetime import datetime # Basic Dates and time types\n", + "from osgeo import osr # Python bindings for GDAL\n", + "from osgeo import gdal # Python bindings for GDAL\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "def loadCPT(path):\n", + "\n", + " try:\n", + " f = open(path)\n", + " except:\n", + " print (\"File \", path, \"not found\")\n", + " return None\n", + "\n", + " lines = f.readlines()\n", + "\n", + " f.close()\n", + "\n", + " x = np.array([])\n", + " r = np.array([])\n", + " g = np.array([])\n", + " b = np.array([])\n", + "\n", + " colorModel = 'RGB'\n", + "\n", + " for l in lines:\n", + " ls = l.split()\n", + " if l[0] == '#':\n", + " if ls[-1] == 'HSV':\n", + " colorModel = 'HSV'\n", + " continue\n", + " else:\n", + " continue\n", + " if ls[0] == 'B' or ls[0] == 'F' or ls[0] == 'N':\n", + " pass\n", + " else:\n", + " x=np.append(x,float(ls[0]))\n", + " r=np.append(r,float(ls[1]))\n", + " g=np.append(g,float(ls[2]))\n", + " b=np.append(b,float(ls[3]))\n", + " xtemp = float(ls[4])\n", + " rtemp = float(ls[5])\n", + " gtemp = float(ls[6])\n", + " btemp = float(ls[7])\n", + "\n", + " x=np.append(x,xtemp)\n", + " r=np.append(r,rtemp)\n", + " g=np.append(g,gtemp)\n", + " b=np.append(b,btemp)\n", + "\n", + " if colorModel == 'HSV':\n", + " for i in range(r.shape[0]):\n", + " rr, gg, bb = colorsys.hsv_to_rgb(r[i]/360.,g[i],b[i])\n", + " r[i] = rr ; g[i] = gg ; b[i] = bb\n", + "\n", + " if colorModel == 'RGB':\n", + " r = r/255.0\n", + " g = g/255.0\n", + " b = b/255.0\n", + "\n", + " xNorm = (x - x[0])/(x[-1] - x[0])\n", + "\n", + " red = []\n", + " blue = []\n", + " green = []\n", + "\n", + " for i in range(len(x)):\n", + " red.append([xNorm[i],r[i],r[i]])\n", + " green.append([xNorm[i],g[i],g[i]])\n", + " blue.append([xNorm[i],b[i],b[i]])\n", + "\n", + " colorDict = {'red': red, 'green': green, 'blue': blue}\n", + "\n", + " return colorDict\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "def download_CMI(yyyymmddhhmn, band, path_dest):\n", + "\n", + " os.makedirs(path_dest, exist_ok=True)\n", + "\n", + " year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%Y')\n", + " day_of_year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%j')\n", + " hour = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%H')\n", + " min = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%M')\n", + "\n", + " # AMAZON repository information\n", + " # https://noaa-goes16.s3.amazonaws.com/index.html\n", + " bucket_name = 'noaa-goes16'\n", + " product_name = 'ABI-L2-CMIPF'\n", + "\n", + " # Initializes the S3 client\n", + " s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # File structure\n", + " prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6C{int(band):02.0f}_G16_s{year}{day_of_year}{hour}{min}'\n", + "\n", + " # Seach for the file on the server\n", + " s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = \"/\")\n", + "\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Check if there are files available\n", + " if 'Contents' not in s3_result:\n", + " # There are no files\n", + " print(f'No files found for the date: {yyyymmddhhmn}, Band-{band}')\n", + " return -1\n", + " else:\n", + " # There are files\n", + " for obj in s3_result['Contents']:\n", + " key = obj['Key']\n", + " # Print the file name\n", + " file_name = key.split('/')[-1].split('.')[0]\n", + "\n", + " # Download the file\n", + " if os.path.exists(f'{path_dest}/{file_name}.nc'):\n", + " print(f'File {path_dest}/{file_name}.nc exists')\n", + " else:\n", + " print(f'Downloading file {path_dest}/{file_name}.nc')\n", + " s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc')\n", + " return f'{file_name}'\n", + "\n", + "s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "def download_PROD(yyyymmddhhmn, product_name, path_dest):\n", + "\n", + " # os.makedirs(path_dest, exist_ok=True)\n", + "\n", + " year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%Y')\n", + " day_of_year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%j')\n", + " hour = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%H')\n", + " min = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%M')\n", + "\n", + " # AMAZON repository information\n", + " # https://noaa-goes16.s3.amazonaws.com/index.html\n", + " bucket_name = 'noaa-goes16'\n", + "\n", + " # Initializes the S3 client\n", + " # s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", + "\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # File structure\n", + " prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6_G16_s{year}{day_of_year}{hour}{min}'\n", + "\n", + " # Seach for the file on the server\n", + " s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = \"/\")\n", + "\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Check if there are files available\n", + " if 'Contents' not in s3_result:\n", + " # There are no files\n", + " print(f'No files found for the date: {yyyymmddhhmn}, Product: {product_name}')\n", + " return -1\n", + " else:\n", + " # There are files\n", + " for obj in s3_result['Contents']:\n", + " key = obj['Key']\n", + " # Print the file name\n", + " file_name = key.split('/')[-1].split('.')[0]\n", + "\n", + " # print(f'File name: {file_name}')\n", + "\n", + " # Download the file\n", + " if os.path.exists(f'{path_dest}/{file_name}.nc'):\n", + " print(f'File {path_dest}/{file_name}.nc exists')\n", + " else:\n", + " # print(f'Downloading file {path_dest}/{file_name}.nc')\n", + " s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc')\n", + " return f'{file_name}'\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "def download_GLM(yyyymmddhhmnss, path_dest):\n", + "\n", + " os.makedirs(path_dest, exist_ok=True)\n", + "\n", + " year = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%Y')\n", + " day_of_year = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%j')\n", + " hour = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%H')\n", + " min = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%M')\n", + " seg = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%S')\n", + "\n", + " # AMAZON repository information\n", + " # https://noaa-goes16.s3.amazonaws.com/index.html\n", + " bucket_name = 'noaa-goes16'\n", + "\n", + " # Initializes the S3 client\n", + " s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED))\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # File structure\n", + " product_name = \"GLM-L2-LCFA\"\n", + " prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}_G16_s{year}{day_of_year}{hour}{min}{seg}'\n", + "\n", + " # Seach for the file on the server\n", + " s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = \"/\")\n", + "\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Check if there are files available\n", + " if 'Contents' not in s3_result:\n", + " # There are no files\n", + " print(f'No files found for the date: {yyyymmddhhmnss}, Product-{product_name}')\n", + " return -1\n", + " else:\n", + " # There are files\n", + " for obj in s3_result['Contents']:\n", + " key = obj['Key']\n", + " # Print the file name\n", + " file_name = key.split('/')[-1].split('.')[0]\n", + "\n", + " # Download the file\n", + " if os.path.exists(f'{path_dest}/{file_name}.nc'):\n", + " print(f'File {path_dest}/{file_name}.nc exists')\n", + " else:\n", + " print(f'Downloading file {path_dest}/{file_name}.nc')\n", + " s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc')\n", + " return f'{file_name}'\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Functions to convert lat / lon extent to array indices\n", + "def geo2grid(lat, lon, nc):\n", + "\n", + " # Apply scale and offset\n", + " xscale, xoffset = nc.variables['x'].scale_factor, nc.variables['x'].add_offset\n", + " yscale, yoffset = nc.variables['y'].scale_factor, nc.variables['y'].add_offset\n", + "\n", + " x, y = latlon2xy(lat, lon)\n", + " col = (x - xoffset)/xscale\n", + " lin = (y - yoffset)/yscale\n", + " return int(lin), int(col)\n", + "\n", + "def latlon2xy(lat, lon):\n", + " # goes_imagery_projection:semi_major_axis\n", + " req = 6378137 # meters\n", + " # goes_imagery_projection:inverse_flattening\n", + " invf = 298.257222096\n", + " # goes_imagery_projection:semi_minor_axis\n", + " rpol = 6356752.31414 # meters\n", + " e = 0.0818191910435\n", + " # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis\n", + " H = 42164160 # meters\n", + " # goes_imagery_projection: longitude_of_projection_origin\n", + " lambda0 = -1.308996939\n", + "\n", + " # Convert to radians\n", + " latRad = lat * (math.pi/180)\n", + " lonRad = lon * (math.pi/180)\n", + "\n", + " # (1) geocentric latitude\n", + " Phi_c = math.atan(((rpol * rpol)/(req * req)) * math.tan(latRad))\n", + " # (2) geocentric distance to the point on the ellipsoid\n", + " rc = rpol/(math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c)))))\n", + " # (3) sx\n", + " sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0))\n", + " # (4) sy\n", + " sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0)\n", + " # (5)\n", + " sz = rc * math.sin(Phi_c)\n", + "\n", + " # x,y\n", + " x = math.asin((-sy)/math.sqrt((sx*sx) + (sy*sy) + (sz*sz)))\n", + " y = math.atan(sz/sx)\n", + "\n", + " return x, y\n", + "\n", + "# Function to convert lat / lon extent to GOES-16 extents\n", + "def convertExtent2GOESProjection(extent):\n", + " # GOES-16 viewing point (satellite position) height above the earth\n", + " GOES16_HEIGHT = 35786023.0\n", + " # GOES-16 longitude position\n", + " GOES16_LONGITUDE = -75.0\n", + "\n", + " a, b = latlon2xy(extent[1], extent[0])\n", + " c, d = latlon2xy(extent[3], extent[2])\n", + " return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT)\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Function to reproject the data\n", + "def reproject(file_name, ncfile, array, extent, undef):\n", + "\n", + " # Read the original file projection and configure the output projection\n", + " source_prj = osr.SpatialReference()\n", + " source_prj.ImportFromProj4(ncfile.GetProjectionRef())\n", + "\n", + " target_prj = osr.SpatialReference()\n", + " target_prj.ImportFromProj4(\"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\")\n", + "\n", + " # Reproject the data\n", + " GeoT = ncfile.GetGeoTransform()\n", + " driver = gdal.GetDriverByName('MEM')\n", + " raw = driver.Create('raw', array.shape[0], array.shape[1], 1, gdal.GDT_Float32)\n", + " raw.SetGeoTransform(GeoT)\n", + " raw.GetRasterBand(1).WriteArray(array)\n", + "\n", + " # Define the parameters of the output file\n", + " kwargs = {'format': 'netCDF', \\\n", + " 'srcSRS': source_prj, \\\n", + " 'dstSRS': target_prj, \\\n", + " 'outputBounds': (extent[0], extent[3], extent[2], extent[1]), \\\n", + " 'outputBoundsSRS': target_prj, \\\n", + " 'outputType': gdal.GDT_Float32, \\\n", + " 'srcNodata': undef, \\\n", + " 'dstNodata': 'nan', \\\n", + " 'resampleAlg': gdal.GRA_NearestNeighbour}\n", + "\n", + " # Write the reprojected file on disk\n", + " gdal.Warp(file_name, raw, **kwargs)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "path = '../data/goes16/'\n", + "file_name = 'OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.nc'\n", + "\n", + "# Region of Interest - Rio de Janeiro municipality\n", + "extent = [-43.890602827150, -23.1339033365138, -43.0483514573222, -22.64972474827293]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## NetCDF to Pickle" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", + "import matplotlib.pyplot as plt # Plotting library\n", + "from datetime import datetime # Basic Dates and time types\n", + "import cartopy, cartopy.crs as ccrs # Plot maps\n", + "import os # Miscellaneous operating system interfaces\n", + "import pickle\n", + "\n", + "def netcdf2pickle(path, file_name):\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Open the GOES-R image\n", + " full_disk_ds = Dataset(path+file_name)\n", + "\n", + " print(full_disk_ds)\n", + "\n", + " # Convert lat/lon to grid-coordinates\n", + " lly, llx = geo2grid(extent[1], extent[0], full_disk_ds)\n", + " ury, urx = geo2grid(extent[3], extent[2], full_disk_ds)\n", + "\n", + " dict_indices = {}\n", + " for instability_index_name in ['CAPE', 'LI', 'TT', 'SI', 'KI']:\n", + " # Get the pixel values\n", + " data = full_disk_ds.variables[instability_index_name][ury:lly, llx:urx]\n", + " dict_indices[instability_index_name] = data\n", + "\n", + " data = full_disk_ds.variables['DQF_Overall'][ury:lly, llx:urx]\n", + " dict_indices['DQF_Overall'] = data\n", + "\n", + " print(f'Shape of sliced data: {data.shape}')\n", + " \n", + " # create a file to store the pickled data\n", + " temp = os.path.splitext(file_name) # given '/home/user/somefile.nc', returns ('/home/user/somefile', '.nc')\n", + " pkl_file_name = f'{temp[0]}.pkl'\n", + " pkl_file = open(pkl_file_name, 'wb')\n", + "\n", + " # Extract date\n", + " # date = (datetime.strptime(file.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ'))\n", + " # print(date)\n", + "\n", + " print(f'Created pickle file: {pkl_file_name}')\n", + "\n", + " # dump information to that file\n", + " pickle.dump(dict_indices, pkl_file)\n", + "\n", + " # close the file\n", + " pkl_file.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "root group (NETCDF4 data model, file format HDF5):\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " Metadata_Conventions: Unidata Dataset Discovery v1.0\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Services\n", + " project: GOES\n", + " production_site: NSOF\n", + " production_environment: OE\n", + " spatial_resolution: 10km at nadir\n", + " orbital_slot: GOES-East\n", + " platform_ID: G16\n", + " instrument_type: GOES R Series Advanced Baseline Imager\n", + " scene_id: Full Disk\n", + " instrument_ID: FM1\n", + " dataset_name: OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.nc\n", + " iso_series_metadata_id: 158fae30-affd-11e1-afa6-0800200c9a66\n", + " title: ABI L2 Derived Stability Indices\n", + " summary: The Derived Stability Indices product consists of the atmosphere convective available potential energy (CAPE) with respect to the surface, the lifted index between the surface and 500 hPa, k index, showalter index, and the total totals index. The product is generated using a regression retrieval followed by an iterative physical retrieval that makes use of a radiative transfer model. Product data is generated both day and night.\n", + " keywords: ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR PROFILES, ATMOSPHERE > ATMOSPHERIC TEMPERATURE > ATMOSPHERIC STABILITY\n", + " keywords_vocabulary: NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 7.0.0.0.0\n", + " license: Unclassified data. Access is restricted to approved users only.\n", + " processing_level: National Aeronautics and Space Administration (NASA) L2\n", + " date_created: 2022-04-01T17:11:48.0Z\n", + " cdm_data_type: Image\n", + " time_coverage_start: 2022-04-01T17:00:20.5Z\n", + " time_coverage_end: 2022-04-01T17:09:51.3Z\n", + " timeline_id: ABI Mode 6\n", + " production_data_source: Realtime\n", + " id: 39cef219-d6e0-4088-b67b-12af7de23854\n", + " dimensions(sizes): y(1086), x(1086), number_of_time_bounds(2), number_of_image_bounds(2), number_of_LZA_bounds(2), number_of_SZA_bounds(2), number_of_lat_bounds(2), sounding_emissive_bands(7)\n", + " variables(dimensions): uint16 LI(y, x), uint16 CAPE(y, x), uint16 TT(y, x), uint16 SI(y, x), uint16 KI(y, x), uint8 DQF_Overall(y, x), uint8 DQF_Retrieval(y, x), uint8 DQF_SkinTemp(y, x), float64 t(), int16 y(y), int16 x(x), float64 time_bounds(number_of_time_bounds), int32 goes_imager_projection(), float32 y_image(), float32 y_image_bounds(number_of_image_bounds), float32 x_image(), float32 x_image_bounds(number_of_image_bounds), float32 nominal_satellite_subpoint_lat(), float32 nominal_satellite_subpoint_lon(), float32 nominal_satellite_height(), float32 geospatial_lat_lon_extent(), float32 final_air_pressure(), int32 CAPE_outlier_pixel_count(), int32 lifted_index_outlier_pixel_count(), int32 k_index_outlier_pixel_count(), int32 showalter_index_outlier_pixel_count(), int32 total_totals_index_outlier_pixel_count(), float32 minimum_CAPE(), float32 maximum_CAPE(), float32 mean_CAPE(), float32 standard_deviation_CAPE(), float32 minimum_lifted_index(), float32 maximum_lifted_index(), float32 mean_lifted_index(), float32 standard_deviation_lifted_index(), float32 minimum_total_totals_index(), float32 maximum_total_totals_index(), float32 mean_total_totals_index(), float32 standard_deviation_total_totals_index(), float32 minimum_showalter_index(), float32 maximum_showalter_index(), float32 mean_showalter_index(), float32 standard_deviation_showalter_index(), float32 minimum_k_index(), float32 maximum_k_index(), float32 mean_k_index(), float32 standard_deviation_k_index(), int32 algorithm_dynamic_input_data_container(), int32 processing_parm_version_container(), int32 algorithm_product_version_container(), float32 retrieval_local_zenith_angle(), float32 quantitative_local_zenith_angle(), float32 retrieval_local_zenith_angle_bounds(number_of_LZA_bounds), float32 quantitative_local_zenith_angle_bounds(number_of_LZA_bounds), float32 solar_zenith_angle(), float32 solar_zenith_angle_bounds(number_of_SZA_bounds), float32 latitude(), float32 latitude_bounds(number_of_lat_bounds), float32 sounding_emissive_wavelengths(sounding_emissive_bands), int8 sounding_emissive_band_ids(sounding_emissive_bands), float32 percent_uncorrectable_L0_errors(), float32 percent_uncorrectable_GRB_errors(), int32 total_attempted_retrievals(), float32 mean_obs_modeled_diff_sounding_emissive_bands(sounding_emissive_bands), float32 std_dev_obs_modeled_diff_sounding_emissive_bands(sounding_emissive_bands)\n", + " groups: \n", + "Shape of sliced data: (5, 8)\n", + "Created pickle file: OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.pkl\n" + ] + } + ], + "source": [ + "netcdf2pickle(path, file_name)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Pickle to PNG" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "def min_max_normalize_masked_array(masked_array: np.ma.MaskedArray):\n", + " # Ensure the input is a MaskedArray\n", + " if not isinstance(masked_array, np.ma.MaskedArray):\n", + " raise ValueError(\"Input must be a numpy.ma.MaskedArray\")\n", + "\n", + " # Calculate the min and max values ignoring the masked elements\n", + " min_val = masked_array.min()\n", + " max_val = masked_array.max()\n", + "\n", + " # Avoid division by zero in case max_val equals min_val\n", + " if max_val == min_val:\n", + " return np.ma.masked_array(np.zeros_like(masked_array), mask=masked_array.mask)\n", + "\n", + " # Apply the min-max normalization\n", + " normalized_array = (masked_array - min_val) / (max_val - min_val)\n", + "\n", + " return normalized_array\n", + "\n", + "def split_filename(full_filename):\n", + " # Extract the directory path and the filename with extension\n", + " dir_path, filename_with_ext = os.path.split(full_filename)\n", + " \n", + " # Extract the base name and the extension\n", + " base_name, file_ext = os.path.splitext(filename_with_ext)\n", + " \n", + " return (dir_path, base_name, file_ext)\n", + "\n", + "def pkl2png(file_name: str, product_name: str, extent: list, output_folder: str, show_image: bool = False):\n", + " # open a file, where you stored the pickled data\n", + " file = open(file_name, 'rb')\n", + "\n", + " dsif_data = pickle.load(file)\n", + "\n", + " # close the file\n", + " file.close()\n", + "\n", + " data = dsif_data[product_name]\n", + " \n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Compute data-extent in GOES projection-coordinates\n", + " img_extent = convertExtent2GOESProjection(extent)\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Choose the plot size (width x height, in inches)\n", + " plt.figure(figsize=(10,10))\n", + "\n", + " # Use the Geostationary projection in cartopy\n", + " ax = plt.axes(projection=ccrs.Geostationary(central_longitude=-75.0, satellite_height=35786023.0))\n", + "\n", + " # Define the color scale based on the channel\n", + " colormap = \"jet\" # White to black for IR channels\n", + " \n", + " data = min_max_normalize_masked_array(data)\n", + "\n", + " # Plot the image\n", + " img = ax.imshow(data, origin='upper', extent=img_extent, cmap=colormap)\n", + "\n", + " # Add coastlines, borders and gridlines\n", + " ax.coastlines(resolution='10m', color='black', linewidth=0.8)\n", + " ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5)\n", + " ax.gridlines(color='black', alpha=0.5, linestyle='--', linewidth=0.5)\n", + "\n", + " # Add a colorbar\n", + " plt.colorbar(img, label='CAPE', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", + "\n", + " # Extract the date\n", + " # date = (datetime.strptime(file.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ'))\n", + "\n", + " # Add a title\n", + " plt.title(f'GOES-16 {product_name}', fontweight='bold', fontsize=10, loc='left')\n", + " plt.title('Reg.: ' + str(extent) , fontsize=10, loc='right')\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Save the image\n", + " dir_path, base_name, file_ext = split_filename(file_name)\n", + " png_file_name = f'{output_folder}/{base_name}.png'\n", + " print()\n", + " plt.savefig(png_file_name, bbox_inches='tight', pad_inches=0, dpi=300)\n", + " print(f'Created pickle file: {png_file_name}')\n", + "\n", + " if show_image:\n", + " # Show the image\n", + " plt.show()\n", + "\n", + " plt.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# import os\n", + "\n", + "# def split_filename(full_filename):\n", + "# # Extract the directory path and the filename with extension\n", + "# dir_path, filename_with_ext = os.path.split(full_filename)\n", + " \n", + "# # Extract the base name and the extension\n", + "# base_name, file_ext = os.path.splitext(filename_with_ext)\n", + " \n", + "# return (dir_path, base_name, file_ext)\n", + "\n", + "# # Example usage\n", + "# full_filename = '/home/user/somefile.pkl'\n", + "# components = split_filename(full_filename)\n", + "# print(components) # Output: ('/home/user', 'somefile', '.pkl')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "ename": "FileNotFoundError", + "evalue": "[Errno 2] No such file or directory: '../data/goes16/dsif_data/png/OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.png'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[7], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m filename \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mOR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.pkl\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 3\u001b[0m output_folder \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m../data/goes16/dsif_data/png\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m----> 4\u001b[0m \u001b[43mpkl2png\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mSI\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mextent\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43moutput_folder\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshow_image\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[5], line 78\u001b[0m, in \u001b[0;36mpkl2png\u001b[0;34m(file_name, product_name, extent, output_folder, show_image)\u001b[0m\n\u001b[1;32m 76\u001b[0m png_file_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00moutput_folder\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m/\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mbase_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.png\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 77\u001b[0m \u001b[38;5;28mprint\u001b[39m()\n\u001b[0;32m---> 78\u001b[0m \u001b[43mplt\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msavefig\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpng_file_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbbox_inches\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtight\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpad_inches\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m300\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 79\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCreated pickle file: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpng_file_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 81\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m show_image:\n\u001b[1;32m 82\u001b[0m \u001b[38;5;66;03m# Show the image\u001b[39;00m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/pyplot.py:1134\u001b[0m, in \u001b[0;36msavefig\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 1131\u001b[0m fig \u001b[38;5;241m=\u001b[39m gcf()\n\u001b[1;32m 1132\u001b[0m \u001b[38;5;66;03m# savefig default implementation has no return, so mypy is unhappy\u001b[39;00m\n\u001b[1;32m 1133\u001b[0m \u001b[38;5;66;03m# presumably this is here because subclasses can return?\u001b[39;00m\n\u001b[0;32m-> 1134\u001b[0m res \u001b[38;5;241m=\u001b[39m \u001b[43mfig\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msavefig\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore[func-returns-value]\u001b[39;00m\n\u001b[1;32m 1135\u001b[0m fig\u001b[38;5;241m.\u001b[39mcanvas\u001b[38;5;241m.\u001b[39mdraw_idle() \u001b[38;5;66;03m# Need this if 'transparent=True', to reset colors.\u001b[39;00m\n\u001b[1;32m 1136\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m res\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/figure.py:3390\u001b[0m, in \u001b[0;36mFigure.savefig\u001b[0;34m(self, fname, transparent, **kwargs)\u001b[0m\n\u001b[1;32m 3388\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m ax \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39maxes:\n\u001b[1;32m 3389\u001b[0m _recursively_make_axes_transparent(stack, ax)\n\u001b[0;32m-> 3390\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcanvas\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mprint_figure\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/backend_bases.py:2193\u001b[0m, in \u001b[0;36mFigureCanvasBase.print_figure\u001b[0;34m(self, filename, dpi, facecolor, edgecolor, orientation, format, bbox_inches, pad_inches, bbox_extra_artists, backend, **kwargs)\u001b[0m\n\u001b[1;32m 2189\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 2190\u001b[0m \u001b[38;5;66;03m# _get_renderer may change the figure dpi (as vector formats\u001b[39;00m\n\u001b[1;32m 2191\u001b[0m \u001b[38;5;66;03m# force the figure dpi to 72), so we need to set it again here.\u001b[39;00m\n\u001b[1;32m 2192\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m cbook\u001b[38;5;241m.\u001b[39m_setattr_cm(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfigure, dpi\u001b[38;5;241m=\u001b[39mdpi):\n\u001b[0;32m-> 2193\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mprint_method\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2194\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2195\u001b[0m \u001b[43m \u001b[49m\u001b[43mfacecolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfacecolor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2196\u001b[0m \u001b[43m \u001b[49m\u001b[43medgecolor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43medgecolor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2197\u001b[0m \u001b[43m \u001b[49m\u001b[43morientation\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43morientation\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2198\u001b[0m \u001b[43m \u001b[49m\u001b[43mbbox_inches_restore\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_bbox_inches_restore\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2199\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2200\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m 2201\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m bbox_inches \u001b[38;5;129;01mand\u001b[39;00m restore_bbox:\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/backend_bases.py:2043\u001b[0m, in \u001b[0;36mFigureCanvasBase._switch_canvas_and_return_print_method..\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 2039\u001b[0m optional_kws \u001b[38;5;241m=\u001b[39m { \u001b[38;5;66;03m# Passed by print_figure for other renderers.\u001b[39;00m\n\u001b[1;32m 2040\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdpi\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfacecolor\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124medgecolor\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124morientation\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m 2041\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbbox_inches_restore\u001b[39m\u001b[38;5;124m\"\u001b[39m}\n\u001b[1;32m 2042\u001b[0m skip \u001b[38;5;241m=\u001b[39m optional_kws \u001b[38;5;241m-\u001b[39m {\u001b[38;5;241m*\u001b[39minspect\u001b[38;5;241m.\u001b[39msignature(meth)\u001b[38;5;241m.\u001b[39mparameters}\n\u001b[0;32m-> 2043\u001b[0m print_method \u001b[38;5;241m=\u001b[39m functools\u001b[38;5;241m.\u001b[39mwraps(meth)(\u001b[38;5;28;01mlambda\u001b[39;00m \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: \u001b[43mmeth\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 2044\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m{\u001b[49m\u001b[43mk\u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mv\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitems\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mskip\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 2045\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m: \u001b[38;5;66;03m# Let third-parties do as they see fit.\u001b[39;00m\n\u001b[1;32m 2046\u001b[0m print_method \u001b[38;5;241m=\u001b[39m meth\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:497\u001b[0m, in \u001b[0;36mFigureCanvasAgg.print_png\u001b[0;34m(self, filename_or_obj, metadata, pil_kwargs)\u001b[0m\n\u001b[1;32m 450\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mprint_png\u001b[39m(\u001b[38;5;28mself\u001b[39m, filename_or_obj, \u001b[38;5;241m*\u001b[39m, metadata\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, pil_kwargs\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[1;32m 451\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 452\u001b[0m \u001b[38;5;124;03m Write the figure to a PNG file.\u001b[39;00m\n\u001b[1;32m 453\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 495\u001b[0m \u001b[38;5;124;03m *metadata*, including the default 'Software' key.\u001b[39;00m\n\u001b[1;32m 496\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 497\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_print_pil\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpng\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpil_kwargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py:446\u001b[0m, in \u001b[0;36mFigureCanvasAgg._print_pil\u001b[0;34m(self, filename_or_obj, fmt, pil_kwargs, metadata)\u001b[0m\n\u001b[1;32m 441\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 442\u001b[0m \u001b[38;5;124;03mDraw the canvas, then save it using `.image.imsave` (to which\u001b[39;00m\n\u001b[1;32m 443\u001b[0m \u001b[38;5;124;03m*pil_kwargs* and *metadata* are forwarded).\u001b[39;00m\n\u001b[1;32m 444\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 445\u001b[0m FigureCanvasAgg\u001b[38;5;241m.\u001b[39mdraw(\u001b[38;5;28mself\u001b[39m)\n\u001b[0;32m--> 446\u001b[0m \u001b[43mmpl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mimsave\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 447\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuffer_rgba\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfmt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43morigin\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mupper\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 448\u001b[0m \u001b[43m \u001b[49m\u001b[43mdpi\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfigure\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdpi\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetadata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetadata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpil_kwargs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpil_kwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/matplotlib/image.py:1656\u001b[0m, in \u001b[0;36mimsave\u001b[0;34m(fname, arr, vmin, vmax, cmap, format, origin, dpi, metadata, pil_kwargs)\u001b[0m\n\u001b[1;32m 1654\u001b[0m pil_kwargs\u001b[38;5;241m.\u001b[39msetdefault(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mformat\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mformat\u001b[39m)\n\u001b[1;32m 1655\u001b[0m pil_kwargs\u001b[38;5;241m.\u001b[39msetdefault(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdpi\u001b[39m\u001b[38;5;124m\"\u001b[39m, (dpi, dpi))\n\u001b[0;32m-> 1656\u001b[0m \u001b[43mimage\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msave\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpil_kwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/PIL/Image.py:2317\u001b[0m, in \u001b[0;36mImage.save\u001b[0;34m(self, fp, format, **params)\u001b[0m\n\u001b[1;32m 2315\u001b[0m fp \u001b[38;5;241m=\u001b[39m builtins\u001b[38;5;241m.\u001b[39mopen(filename, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mr+b\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 2316\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m-> 2317\u001b[0m fp \u001b[38;5;241m=\u001b[39m \u001b[43mbuiltins\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfilename\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mw+b\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2319\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 2320\u001b[0m save_handler(\u001b[38;5;28mself\u001b[39m, fp, filename)\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '../data/goes16/dsif_data/png/OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.png'" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# filename = '../data/goes16/dsif_data/202401010050.pkl'\n", + "filename = 'OR_ABI-L2-DSIF-M6_G16_s20220911700205_e20220911709513_c20220911711480.pkl'\n", + "output_folder = '../data/goes16/dsif_data/png'\n", + "pkl2png(filename, 'SI', extent, output_folder, show_image = True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Animation code" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# conda install -c conda-forge ffmpeg" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import matplotlib.animation as animation\n", + "import pickle\n", + "from datetime import datetime, timedelta\n", + "\n", + "def generate_timestamps(initial_timestamp, final_timestamp, interval_in_minutes = 10):\n", + " # Parse the input timestamps to datetime objects\n", + " initial_dt = datetime.strptime(initial_timestamp, '%Y%m%d%H%M')\n", + " final_dt = datetime.strptime(final_timestamp, '%Y%m%d%H%M')\n", + "\n", + " # Generate timestamps in 10-minute intervals\n", + " timestamps = []\n", + " current_dt = initial_dt\n", + "\n", + " while current_dt <= final_dt:\n", + " timestamps.append(current_dt.strftime('%Y%m%d%H%M'))\n", + " current_dt += timedelta(minutes=interval_in_minutes)\n", + "\n", + " return timestamps\n", + "\n", + "def get_frame(data, extent):\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Compute data-extent in GOES projection-coordinates\n", + " img_extent = convertExtent2GOESProjection(extent)\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Choose the plot size (width x height, in inches)\n", + " # plt.figure(figsize=(10,10))\n", + "\n", + " # Use the Geostationary projection in cartopy\n", + " ax = plt.axes(projection=ccrs.Geostationary(central_longitude=-75.0, satellite_height=35786023.0))\n", + "\n", + " # Define the color scale based on the channel\n", + " colormap = \"jet\" # White to black for IR channels\n", + "\n", + " # Plot the image\n", + " img = ax.imshow(data, origin='upper', extent=img_extent, cmap=colormap, animated = True)\n", + "\n", + " # Add coastlines, borders and gridlines\n", + " ax.coastlines(resolution='10m', color='black', linewidth=0.8)\n", + " ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5)\n", + " ax.gridlines(color='black', alpha=0.5, linestyle='--', linewidth=0.5)\n", + "\n", + " # Add a colorbar\n", + " # plt.colorbar(img, label='CAPE', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", + "\n", + " # plt.close()\n", + " \n", + " return img\n", + " return plt.imgshow()\n", + "\n", + "def gen_animation(initial_timestamp: str, final_timestamp: str, input_folder: str, product_name: str, extent: list, out_file_name: str):\n", + " def update_frame(frame_number, img, images):\n", + " \"\"\"Update the image for each frame of the animation.\"\"\"\n", + " img.set_array(images[frame_number])\n", + " return img,\n", + " \n", + " # fig = plt.figure()\n", + "\n", + " i_timestamp = int(initial_timestamp)\n", + " f_timestamp = int(final_timestamp)\n", + "\n", + " assert i_timestamp <= f_timestamp\n", + " \n", + " timestamps = generate_timestamps(initial_timestamp, final_timestamp, interval_in_minutes = 10)\n", + "\n", + " # images is a list of artists to draw at each frame\n", + " images = []\n", + " for timestamp in timestamps:\n", + " # print(f'Current timestamp: {timestamp}')\n", + "\n", + " filename = f'{input_folder}/{timestamp}.pkl'\n", + "\n", + " # open a file containing the pickled data\n", + " file = open(filename, 'rb')\n", + "\n", + " pickled_data = pickle.load(file)\n", + "\n", + " # close the file\n", + " file.close()\n", + "\n", + " data = pickled_data[product_name]\n", + "\n", + " images += [data]\n", + "\n", + " num_images = len(images)\n", + " print(num_images)\n", + "\n", + " # Create a figure and axis\n", + " fig, ax = plt.subplots()\n", + "\n", + " # Use the Geostationary projection in cartopy\n", + " ax = plt.axes(projection=ccrs.Geostationary(central_longitude=-75.0, satellite_height=35786023.0))\n", + "\n", + " # See https://stackoverflow.com/questions/67855367/remove-axis-from-animation-artistanimation-python\n", + " # ax = fig.add_subplot(111)\n", + " ax.get_xaxis().set_visible(False)\n", + " ax.get_yaxis().set_visible(False)\n", + " # ax.axis('off')\n", + "\n", + " # Add coastlines, borders and gridlines\n", + " ax.coastlines(resolution='10m', color='black', linewidth=0.8)\n", + " ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5)\n", + " ax.gridlines(color='black', alpha=0.5, linestyle='--', linewidth=0.5)\n", + "\n", + " img = ax.imshow(images[0], interpolation='none')\n", + "\n", + " # Create the animation\n", + " ani = animation.FuncAnimation(fig, update_frame, frames=num_images, fargs=(img, images), blit=True)\n", + "\n", + " # Save the animation\n", + " ani.save(out_file_name)\n", + " print(f'Created MP4 file: {out_file_name}')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# import numpy as np\n", + "# import matplotlib.pyplot as plt\n", + "# import matplotlib.animation as animation\n", + "\n", + "# def generate_random_images(num_images, image_shape):\n", + "# \"\"\"Generate a list of random images.\"\"\"\n", + "# return [np.random.rand(*image_shape) for _ in range(num_images)]\n", + "\n", + "# def update_frame(frame_number, img, images):\n", + "# \"\"\"Update the image for each frame of the animation.\"\"\"\n", + "# img.set_array(images[frame_number])\n", + "# return img,\n", + "\n", + "# # Parameters\n", + "# num_images = 10\n", + "# image_shape = (10, 10) # Shape of the random images\n", + "\n", + "# # Generate random images\n", + "# images = generate_random_images(num_images, image_shape)\n", + "\n", + "# # Create a figure and axis\n", + "# fig, ax = plt.subplots()\n", + "# print(type(images), type(images[0]))\n", + "# img = ax.imshow(images[0], interpolation='none')\n", + "\n", + "# # Create the animation\n", + "# ani = animation.FuncAnimation(fig, update_frame, frames=num_images, fargs=(img, images), blit=True)\n", + "\n", + "# # Save the animation as an MP4 file\n", + "# ani.save('random_images_animation.mp4', writer='ffmpeg', fps=1)\n", + "\n", + "# # Display the animation in the notebook (optional)\n", + "# # plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# N.B.: timestamp format is YYYYMMDDHHMM\n", + "# plot_anim(initial_timestamp = '202401130000', final_timestamp = '202401132350', input_folder = '../data/goes16/dsif_data')\n", + "gen_animation(initial_timestamp = '202401130000', \n", + " final_timestamp = '202401132350', \n", + " input_folder = '../data/goes16/dsif_data', \n", + " product_name = 'CAPE', \n", + " extent = extent, \n", + " out_file_name = '../data/goes16/CAPE_2024_01_01.mp4')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# import numpy as np\n", + "\n", + "# def min_max_normalize_masked_array(masked_array):\n", + "# # Ensure the input is a MaskedArray\n", + "# if not isinstance(masked_array, np.ma.MaskedArray):\n", + "# raise ValueError(\"Input must be a numpy.ma.MaskedArray\")\n", + "\n", + "# # Calculate the min and max values ignoring the masked elements\n", + "# min_val = masked_array.min()\n", + "# max_val = masked_array.max()\n", + "\n", + "# # Avoid division by zero in case max_val equals min_val\n", + "# if max_val == min_val:\n", + "# return np.ma.masked_array(np.zeros_like(masked_array), mask=masked_array.mask)\n", + "\n", + "# # Apply the min-max normalization\n", + "# normalized_array = (masked_array - min_val) / (max_val - min_val)\n", + "\n", + "# return normalized_array\n", + "\n", + "# # Example usage\n", + "# data = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])\n", + "# mask = [0, 0, 0, 1, 0, 0, 0, 1, 0, 0]\n", + "# masked_array = np.ma.masked_array(data, mask=mask)\n", + "\n", + "# normalized_masked_array = min_max_normalize_masked_array(masked_array)\n", + "# print(normalized_masked_array)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "df = pd.read_parquet('../ABI-L2-DSIF_2024-01-13_to_2024-01-13.parquet')\n", + "filtered_df = df[~df['CAPE'].isnull()]\n", + "filtered_df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "df = pd.read_parquet('../ABI-L2-TPWF_2024-01-13_to_2024-01-13.parquet')\n", + "filtered_df = df[~df['TPW'].isnull()]\n", + "filtered_df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Reprojection with GDAL" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "File ../data/goes16/curso_cptec/Samples/OR_ABI-L2-DSIF-M6_G16_s20240132300205_e20240132309513_c20240132311347.nc exists\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages/osgeo/gdal.py:287: FutureWarning: Neither gdal.UseExceptions() nor gdal.DontUseExceptions() has been explicitly called. In GDAL 4.0, exceptions will be enabled by default.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "type(ds): \n", + "( >, None, None)\n", + "type(raw): \n", + "Station ID: A627, Lat/Lon: (-22.86749999, -43.10194444), Grid cell: (1, 6), Pixel value: 5000.38134765625\n", + "Station ID: A652, Lat/Lon: (-22.98833333, -43.19055555), Grid cell: (2, 5), Pixel value: 5000.38134765625\n", + "Station ID: A636, Lat/Lon: (-22.93999999, -43.40277777), Grid cell: (2, 4), Pixel value: 5000.38134765625\n", + "Station ID: A621, Lat/Lon: (-22.86138888, -43.41138888), Grid cell: (1, 3), Pixel value: 5000.38134765625\n", + "Station ID: A602, Lat/Lon: (-23.05027777, -43.59555555), Grid cell: (3, 2), Pixel value: 5000.38134765625\n", + "Station ID: A601, Lat/Lon: (-22.75777777, -43.68472221), Grid cell: (0, 1), Pixel value: 5000.38134765625\n", + "Station ID: vidigal, Lat/Lon: (-22.9925, -43.2331), Grid cell: (2, 5), Pixel value: 5000.38134765625\n", + "Station ID: iraja, Lat/Lon: (-22.8269, -43.3369), Grid cell: (1, 4), Pixel value: 5000.38134765625\n", + "Station ID: jardim_botanico, Lat/Lon: (-22.9728, -43.2239), Grid cell: (2, 5), Pixel value: 5000.38134765625\n", + "Station ID: riocentro, Lat/Lon: (-22.9772, -43.3916), Grid cell: (2, 4), Pixel value: 5000.38134765625\n", + "Station ID: guaratiba, Lat/Lon: (-23.0503, -43.5947), Grid cell: (3, 2), Pixel value: 5000.38134765625\n", + "Station ID: santa_cruz, Lat/Lon: (-22.9094, -43.6844), Grid cell: (2, 1), Pixel value: 5000.38134765625\n", + "Station ID: alto_da_boa_vista, Lat/Lon: (-22.9658, -43.2783), Grid cell: (2, 5), Pixel value: 5000.38134765625\n", + "Station ID: sao_cristovao, Lat/Lon: (-22.8967, -43.2217), Grid cell: (2, 5), Pixel value: 5000.38134765625\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Training: Python and GOES-R Imagery: Script 14 - Reprojection with GDAL\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Required modules\n", + "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", + "import matplotlib.pyplot as plt # Plotting library\n", + "from datetime import datetime # Basic Dates and time types\n", + "import cartopy, cartopy.crs as ccrs # Plot maps\n", + "import os # Miscellaneous operating system interfaces\n", + "from osgeo import osr # Python bindings for GDAL\n", + "from osgeo import gdal # Python bindings for GDAL\n", + "import numpy as np # Scientific computing with Python\n", + "# from utilities import download_CMI # Our function for download\n", + "\n", + "import pandas as pd\n", + "\n", + "# Check if the point is inside the bounding box\n", + "def is_point_in_bbox(point_lat, point_lon, extent):\n", + " min_lon, min_lat, max_lon, max_lat = extent\n", + " return min_lon <= point_lon <= max_lon and min_lat <= point_lat <= max_lat\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Input and output directories\n", + "input = \"../data/goes16/curso_cptec/Samples\"\n", + "output = \"../data/goes16/curso_cptec/Output\"\n", + "\n", + "# Desired extent\n", + "# extent = [-64.0, -35.0, -35.0, -15.0] # Min lon, Max lon, Min lat, Max lat\n", + "extent = [-43.890602827150, -23.1339033365138, -43.0483514573222, -22.64972474827293]\n", + "\n", + "# Datetime to process\n", + "yyyymmddhhmn = '202401132300'\n", + "# yyyymmddhhmn = '202406131800'\n", + "# yyyymmddhhmn = '202102181800'\n", + "# yyyymmddhhmn = '202012161300'\n", + "\n", + "product_name = 'ABI-L2-DSIF'\n", + "\n", + "# Download the file\n", + "file_name = download_PROD(yyyymmddhhmn, product_name, path_dest=input)\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Variable\n", + "var = 'CAPE'\n", + "\n", + "# Open the file\n", + "img = gdal.Open(f'NETCDF:{input}/{file_name}.nc:' + var)\n", + "\n", + "# Data Quality Flag (DQF)\n", + "dqf = gdal.Open(f'NETCDF:{input}/{file_name}.nc:DQF_Overall')\n", + "\n", + "# Read the header metadata\n", + "metadata = img.GetMetadata()\n", + "scale = float(metadata.get(var + '#scale_factor'))\n", + "offset = float(metadata.get(var + '#add_offset'))\n", + "undef = float(metadata.get(var + '#_FillValue'))\n", + "dtime = metadata.get('NC_GLOBAL#time_coverage_start')\n", + "\n", + "# Load the data\n", + "ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float)\n", + "ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float)\n", + "\n", + "# Apply the scale and offset\n", + "ds = (ds * scale + offset)\n", + "\n", + "# Apply NaN's where the quality flag is greater than 1\n", + "# ds[ds_dqf > 1] = np.nan\n", + "\n", + "print('type(ds):', type(ds))\n", + "\n", + "# Read the original file projection and configure the output projection\n", + "source_prj = osr.SpatialReference()\n", + "source_prj.ImportFromProj4(img.GetProjectionRef())\n", + "\n", + "target_prj = osr.SpatialReference()\n", + "target_prj.ImportFromProj4(\"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\")\n", + "\n", + "# Reproject the data\n", + "GeoT = img.GetGeoTransform()\n", + "driver = gdal.GetDriverByName('MEM')\n", + "raw = driver.Create('raw', ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32)\n", + "raw.SetGeoTransform(GeoT)\n", + "raw.GetRasterBand(1).WriteArray(ds)\n", + "\n", + "# Define the parameters of the output file \n", + "options = gdal.WarpOptions(format = 'netCDF', \n", + " srcSRS = source_prj, \n", + " dstSRS = target_prj,\n", + " outputBounds = (extent[0], extent[3], extent[2], extent[1]), \n", + " outputBoundsSRS = target_prj, \n", + " outputType = gdal.GDT_Float32, \n", + " srcNodata = undef, \n", + " dstNodata = 'nan', \n", + " # xRes = 0.01, \n", + " # yRes = 0.01, \n", + " resampleAlg = gdal.GRA_NearestNeighbour)\n", + "\n", + "print(options)\n", + "\n", + "print('type(raw):', type(raw))\n", + "\n", + "# Write the reprojected file on disk\n", + "filename_reprojected = f'{output}/{file_name}_ret.nc'\n", + "gdal.Warp(filename_reprojected, raw, options=options)\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Open the reprojected GOES-R image\n", + "file = Dataset(filename_reprojected)\n", + "\n", + "sat_data = gdal.Open(f'{filename_reprojected}')\n", + "# Read number of cols and rows\n", + "ncol = sat_data.RasterXSize\n", + "nrow = sat_data.RasterYSize\n", + "# Load the data\n", + "sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float)\n", + "# Get geotransform\n", + "transform = sat_data.GetGeoTransform()\n", + "\n", + "# Get the pixel values\n", + "data = file.variables['Band1'][:]\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Choose the plot size (width x height, in inches)\n", + "plt.figure(figsize=(10,10))\n", + "\n", + "# Use the Geostationary projection in cartopy\n", + "ax = plt.axes(projection=ccrs.PlateCarree())\n", + "\n", + "# Define the image extent\n", + "img_extent = [extent[0], extent[2], extent[1], extent[3]]\n", + "\n", + "# Define the color scale based on the channel\n", + "colormap = plt.get_cmap('rainbow').resampled(240)\n", + "\n", + "# Plot the image\n", + "img = ax.imshow(data, origin='upper', extent=img_extent, cmap=colormap, vmin=0, vmax=8000)\n", + "\n", + "# Add coastlines, borders and gridlines\n", + "ax.coastlines(resolution='10m', color='white', linewidth=0.8)\n", + "ax.add_feature(cartopy.feature.BORDERS, edgecolor='white', linewidth=0.5)\n", + "gl = ax.gridlines(crs=ccrs.PlateCarree(), color='gray', alpha=1.0, linestyle='--', linewidth=0.25, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), draw_labels=True)\n", + "gl.top_labels = False\n", + "gl.right_labels = False\n", + "\n", + "# Add a colorbar\n", + "plt.colorbar(img, label='CAPE (J/Kg)', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", + "\n", + "# Extract date\n", + "date = (datetime.strptime(dtime, '%Y-%m-%dT%H:%M:%S.%fZ'))\n", + "\n", + "# Add a title\n", + "plt.title('GOES-16 DSI-CAPE ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC' + '\\nDomain: ' + str(extent), fontsize=10, loc='left')\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Save the image\n", + "# plt.savefig(f'{output}/Image_14.png', bbox_inches='tight', pad_inches=0, dpi=300)\n", + "\n", + "stations_filename = \"../data/ws/WeatherStations.csv\"\n", + "df_stations = pd.read_csv(stations_filename)\n", + "\n", + "for index, row in df_stations.iterrows():\n", + " station_id = row['STATION_ID']\n", + "\n", + " # if not station_id.startswith('A652'):\n", + " # continue\n", + "\n", + " point_lat = row['VL_LATITUDE']\n", + " point_lon = row['VL_LONGITUDE']\n", + " if is_point_in_bbox(point_lat, point_lon, extent):\n", + " # Plot the point\n", + " x = int((point_lon - transform[0]) / transform[1])\n", + " y = int((transform[3] - point_lat) / -transform[5])\n", + " pixel_value = sat_array[y,x]\n", + " print(f\"Station ID: {station_id}, Lat/Lon: ({point_lat}, {point_lon}), Grid cell: ({y}, {x}), Pixel value: {pixel_value}\")\n", + " ax.scatter(point_lon, point_lat, color='black', s=20, edgecolor='black', transform=ccrs.PlateCarree(), zorder=5)\n", + "\n", + "# Show the image\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "ds.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "print(data[0,0])\n", + "print(data[0,1])\n", + "print(data[0,2])\n", + "print(data[0,3])\n", + "print(data[0,4])\n", + "print(data[0,5])\n", + "print(data[0,6])\n", + "print(' ~ ')\n", + "print(data[1,0])\n", + "print(data[1,1])\n", + "print(data[1,2])\n", + "print(data[1,3])\n", + "print(data[1,4])\n", + "print(data[1,5])\n", + "print(data[1,6])\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "input_folder_path = '../data/goes16/DSI/'\n", + "\n", + "i = 0\n", + "\n", + "# Use a for loop to unpack the values returned by os.walk\n", + "for root, dirs, files in os.walk(input_folder_path):\n", + " print(f\"Root: {root}\")\n", + " print(f\"Directories: {dirs}\")\n", + " print(f\"Files: {files}\")\n", + " if i == 10:\n", + " break\n", + " i += 1" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/calculate_lat_lon_from_GOES_imager.ipynb b/notebooks/GOES16/GOES16_calculate_lat_lon_from_GOES_imager.ipynb similarity index 100% rename from notebooks/calculate_lat_lon_from_GOES_imager.ipynb rename to notebooks/GOES16/GOES16_calculate_lat_lon_from_GOES_imager.ipynb diff --git a/notebooks/download_ABI_L2_data.ipynb b/notebooks/GOES16/GOES16_download_ABI_L2_data.ipynb similarity index 100% rename from notebooks/download_ABI_L2_data.ipynb rename to notebooks/GOES16/GOES16_download_ABI_L2_data.ipynb diff --git a/notebooks/GOES16/GOES16_plot_crop.ipynb b/notebooks/GOES16/GOES16_plot_crop.ipynb new file mode 100644 index 00000000..34837b09 --- /dev/null +++ b/notebooks/GOES16/GOES16_plot_crop.ipynb @@ -0,0 +1,925 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "6XFX7y4NOVzh" + }, + "source": [ + "## Full Disk\n" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "id": "iBvdM4pXOxA5" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(5424, 5424) (5424, 5424)\n", + "(5424, 5424) (5424, 5424)\n", + "(5424, 5424) (5424, 5424)\n", + "WV_rain - min/max values: (185.03513, 266.7496)\n", + "WV_norain - min/max values: (189.81944, 267.3847)\n", + "IR_rain - min/max values: (184.0123, 299.3602)\n", + "IR_norain - min/max values: (190.342, 300.8965)\n", + "diff_rain - min/max values: (-55.02997, 6.042282)\n", + "diff_norain - min/max values: (-54.726624, 5.1987915)\n", + "diff_rain - min/max values after scaling: (0.0, 61.07225)\n", + "diff_norain - min/max values after scaling: (0.0, 59.925415)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Training: Python and GOES-R Imagery: Script 1 - Basic Plot / Extracting Pixel Values\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Required modules\n", + "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", + "import matplotlib.pyplot as plt # Plotting library\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Open the GOES-R image\n", + "# Download files at this link: http://home.chpc.utah.edu/~u0553130/Brian_Blaylock/cgi-bin/goes16_download.cgi\n", + "# file = Dataset(\"Samples/OR_ABI-L2-CMIPF-M6C13_G16_s20191981200396_e20191981210116_c20191981210189.nc\")\n", + "file_WV_rain = Dataset(\"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C09_G16_s20240130140204_e20240130149518_c20240130149599.nc\")\n", + "file_IR_rain = Dataset(\"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C13_G16_s20240130140204_e20240130149524_c20240130149589.nc\")\n", + "file_WV_norain = Dataset(\"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C09_G16_s20240430140205_e20240430149519_c20240430149579.nc\")\n", + "file_IR_norain = Dataset(\"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C13_G16_s20240430140205_e20240430149525_c20240430149589.nc\")\n", + "\n", + "# Get the pixel values\n", + "data_WV_rain = file_WV_rain.variables['CMI'][:]\n", + "data_WV_norain = file_WV_norain.variables['CMI'][:]\n", + "data_IR_rain = file_IR_rain.variables['CMI'][:]\n", + "data_IR_norain = file_IR_norain.variables['CMI'][:]\n", + "\n", + "data_diff_rain = data_WV_rain - data_IR_rain\n", + "data_diff_norain = data_WV_norain - data_IR_norain\n", + "\n", + "print(data_WV_rain.shape, data_WV_norain.shape)\n", + "print(data_IR_rain.shape, data_IR_norain.shape)\n", + "print(data_diff_rain.shape, data_diff_norain.shape)\n", + "\n", + "print(f\"WV_rain - min/max values: {np.min(data_WV_rain), np.max(data_WV_rain)}\")\n", + "print(f\"WV_norain - min/max values: {np.min(data_WV_norain), np.max(data_WV_norain)}\")\n", + "\n", + "print(f\"IR_rain - min/max values: {np.min(data_IR_rain), np.max(data_IR_rain)}\")\n", + "print(f\"IR_norain - min/max values: {np.min(data_IR_norain), np.max(data_IR_norain)}\")\n", + "\n", + "print(f\"diff_rain - min/max values: {np.min(data_diff_rain), np.max(data_diff_rain)}\")\n", + "print(f\"diff_norain - min/max values: {np.min(data_diff_norain), np.max(data_diff_norain)}\")\n", + "\n", + "data_diff_rain -= np.min(data_diff_rain)\n", + "data_diff_norain -= np.min(data_diff_norain)\n", + "\n", + "print(f\"diff_rain - min/max values after scaling: {np.min(data_diff_rain), np.max(data_diff_rain)}\")\n", + "print(f\"diff_norain - min/max values after scaling: {np.min(data_diff_norain), np.max(data_diff_norain)}\")\n", + "\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Choose the plot size (width x height, in inches)\n", + "plt.figure(figsize=(10, 10))\n", + "\n", + "# Plot the first image\n", + "plt.subplot(3, 2, 1)\n", + "plt.imshow(data_WV_rain, cmap='Greys')\n", + "plt.title('WV (Rain)')\n", + "\n", + "# Plot the second image\n", + "plt.subplot(3, 2, 2)\n", + "plt.imshow(data_WV_norain, cmap='Greys')\n", + "plt.title('WV (No Rain)')\n", + "\n", + "# Plot the first IR image\n", + "plt.subplot(3, 2, 3)\n", + "plt.imshow(data_IR_rain, cmap='Greys')\n", + "plt.title('IR (Rain)')\n", + "\n", + "# Plot the second IR image\n", + "plt.subplot(3, 2, 4)\n", + "plt.imshow(data_IR_norain, cmap='Greys')\n", + "plt.title('IR (No Rain)')\n", + "\n", + "# Plot the first diff image\n", + "plt.subplot(3, 2, 5)\n", + "plt.imshow(data_diff_rain, cmap='Greys')\n", + "plt.title('WV - IR (Rain)')\n", + "\n", + "# Plot the second diff image\n", + "plt.subplot(3, 2, 6)\n", + "# plt.imshow(data_diff_norain, vmin=193, vmax=313, cmap='Greys')\n", + "plt.imshow(data_diff_norain, cmap='Greys')\n", + "plt.title('WV - IR (No Rain)')\n", + "\n", + "#-----------------------------------------------------------------------------------------------------------\n", + "# Save the image\n", + "# plt.savefig('../data/goes16/cloud_depth/Image_01.png')\n", + "\n", + "# Show the image\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Brazil " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "id": "CQzKYxsjOxO2" + }, + "outputs": [], + "source": [ + "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", + "import matplotlib.pyplot as plt # Plotting library\n", + "from datetime import datetime # Basic Dates and time types\n", + "import cartopy, cartopy.crs as ccrs # Plot maps\n", + "import os # Miscellaneous operating system interfaces\n", + "from osgeo import osr # Python bindings for GDAL\n", + "from osgeo import gdal # Python bindings for GDAL\n", + "import numpy as np # Scientific computing with Python\n", + "\n", + "def plot_extent(file_name, extent):\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Variable\n", + " var = 'CMI'\n", + "\n", + " # Open the file\n", + " img = gdal.Open(f'NETCDF:{file_name}.nc:' + var)\n", + "\n", + " # Read the header metadata\n", + " metadata = img.GetMetadata()\n", + " scale = float(metadata.get(var + '#scale_factor'))\n", + " offset = float(metadata.get(var + '#add_offset'))\n", + " undef = float(metadata.get(var + '#_FillValue'))\n", + " dtime = metadata.get('NC_GLOBAL#time_coverage_start')\n", + "\n", + " # Load the data\n", + " ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float)\n", + "\n", + " # Apply the scale, offset and convert to celsius\n", + " ds = (ds * scale + offset) - 273.15\n", + "\n", + " # Read the original file projection and configure the output projection\n", + " source_prj = osr.SpatialReference()\n", + " source_prj.ImportFromProj4(img.GetProjectionRef())\n", + "\n", + " target_prj = osr.SpatialReference()\n", + " target_prj.ImportFromProj4(\"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\")\n", + "\n", + " # Reproject the data\n", + " GeoT = img.GetGeoTransform()\n", + " driver = gdal.GetDriverByName('MEM')\n", + " raw = driver.Create('raw', ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32)\n", + " raw.SetGeoTransform(GeoT)\n", + " raw.GetRasterBand(1).WriteArray(ds)\n", + "\n", + " # Define the parameters of the output file\n", + " options = gdal.WarpOptions(format = 'netCDF',\n", + " srcSRS = source_prj,\n", + " dstSRS = target_prj,\n", + " outputBounds = (extent[0], extent[3], extent[2], extent[1]),\n", + " outputBoundsSRS = target_prj,\n", + " outputType = gdal.GDT_Float32,\n", + " srcNodata = undef,\n", + " dstNodata = 'nan',\n", + " xRes = 0.02,\n", + " yRes = 0.02,\n", + " resampleAlg = gdal.GRA_NearestNeighbour)\n", + "\n", + " print(options)\n", + "\n", + " # Write the reprojected file on disk\n", + " gdal.Warp(f'{file_name}_ret.nc', raw, options=options)\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Open the reprojected GOES-R image\n", + " file = Dataset(f'{file_name}_ret.nc')\n", + "\n", + " # Get the pixel values\n", + " data = file.variables['Band1'][:]\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Choose the plot size (width x height, in inches)\n", + " plt.figure(figsize=(10,10))\n", + " \n", + " # Use the Geostationary projection in cartopy\n", + " ax = plt.axes(projection=ccrs.PlateCarree())\n", + "\n", + " # Define the image extent\n", + " img_extent = [extent[0], extent[2], extent[1], extent[3]]\n", + "\n", + " # Define the color scale based on the channel\n", + " colormap = \"gray_r\" # White to black for IR channels\n", + "\n", + " # Plot the image\n", + " img = ax.imshow(data, origin='upper', extent=img_extent, cmap=colormap)\n", + "\n", + " # Add coastlines, borders and gridlines\n", + " ax.coastlines(resolution='10m', color='white', linewidth=0.8)\n", + " ax.add_feature(cartopy.feature.BORDERS, edgecolor='white', linewidth=0.5)\n", + " gl = ax.gridlines(crs=ccrs.PlateCarree(), color='gray', alpha=1.0, linestyle='--', linewidth=0.25, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), draw_labels=True)\n", + " gl.top_labels = False\n", + " gl.right_labels = False\n", + "\n", + " # Add a colorbar\n", + " plt.colorbar(img, label='Brightness Temperatures (°C)', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", + "\n", + " # Extract date\n", + " date = (datetime.strptime(dtime, '%Y-%m-%dT%H:%M:%S.%fZ'))\n", + "\n", + " # Add a title\n", + " plt.title('GOES-16 Band 13 ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC', fontweight='bold', fontsize=10, loc='left')\n", + " plt.title('Reg.: ' + str(extent) , fontsize=10, loc='right')\n", + " #-----------------------------------------------------------------------------------------------------------\n", + "\n", + " # Show the image\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "( >, None, None)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", + "import matplotlib.pyplot as plt # Plotting library\n", + "from datetime import datetime # Basic Dates and time types\n", + "import cartopy, cartopy.crs as ccrs # Plot maps\n", + "import os # Miscellaneous operating system interfaces\n", + "from osgeo import osr # Python bindings for GDAL\n", + "from osgeo import gdal # Python bindings for GDAL\n", + "import numpy as np # Scientific computing with Python\n", + "\n", + "def get_reprojection(file_name, extent):\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Variable\n", + " var = 'CMI'\n", + "\n", + " # Open the file\n", + " img = gdal.Open(f'NETCDF:{file_name}.nc:' + var)\n", + "\n", + " # Read the header metadata\n", + " metadata = img.GetMetadata()\n", + " scale = float(metadata.get(var + '#scale_factor'))\n", + " offset = float(metadata.get(var + '#add_offset'))\n", + " undef = float(metadata.get(var + '#_FillValue'))\n", + " dtime = metadata.get('NC_GLOBAL#time_coverage_start')\n", + "\n", + " # Load the data\n", + " ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float)\n", + "\n", + " # Apply the scale, offset and convert to celsius\n", + " ds = (ds * scale + offset) - 273.15\n", + "\n", + " # Read the original file projection and configure the output projection\n", + " source_prj = osr.SpatialReference()\n", + " source_prj.ImportFromProj4(img.GetProjectionRef())\n", + "\n", + " target_prj = osr.SpatialReference()\n", + " target_prj.ImportFromProj4(\"+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs\")\n", + "\n", + " # Reproject the data\n", + " GeoT = img.GetGeoTransform()\n", + " driver = gdal.GetDriverByName('MEM')\n", + " raw = driver.Create('raw', ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32)\n", + " raw.SetGeoTransform(GeoT)\n", + " raw.GetRasterBand(1).WriteArray(ds)\n", + "\n", + " # Define the parameters of the output file\n", + " options = gdal.WarpOptions(format = 'netCDF',\n", + " srcSRS = source_prj,\n", + " dstSRS = target_prj,\n", + " outputBounds = (extent[0], extent[3], extent[2], extent[1]),\n", + " outputBoundsSRS = target_prj,\n", + " outputType = gdal.GDT_Float32,\n", + " srcNodata = undef,\n", + " dstNodata = 'nan',\n", + " xRes = 0.02,\n", + " yRes = 0.02,\n", + " resampleAlg = gdal.GRA_NearestNeighbour)\n", + "\n", + " print(options)\n", + "\n", + " # Write the reprojected file on disk\n", + " gdal.Warp(f'{file_name}_ret.nc', raw, options=options)\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Open the reprojected GOES-R image\n", + " file = Dataset(f'{file_name}_ret.nc')\n", + "\n", + " # Get the pixel values\n", + " data = file.variables['Band1'][:]\n", + "\n", + " return data\n", + "\n", + "def plot_extent(data,titles, extent):\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Choose the plot size (width x height, in inches)\n", + " fig, axes = plt.subplots(3, 2, figsize=(10, 10), subplot_kw={'projection': ccrs.PlateCarree()})\n", + " \n", + " # Define the image extent\n", + " img_extent = [extent[0], extent[2], extent[1], extent[3]]\n", + "\n", + " # Define the color scale based on the channel\n", + " colormap = \"gray_r\" # White to black for IR channels\n", + "\n", + " i = 0\n", + "\n", + " for ax in axes.flat:\n", + " # Plot the image\n", + " img = ax.imshow(data[i], origin='upper', extent=img_extent, cmap=colormap)\n", + "\n", + " # Add coastlines, borders and gridlines\n", + " ax.coastlines(resolution='10m', color='white', linewidth=0.8)\n", + " ax.add_feature(cartopy.feature.BORDERS, edgecolor='white', linewidth=0.5)\n", + " gl = ax.gridlines(crs=ccrs.PlateCarree(), color='gray', alpha=1.0, linestyle='--', linewidth=0.25, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), draw_labels=True)\n", + " gl.top_labels = False\n", + " gl.right_labels = False\n", + "\n", + " # Add a title to each subplot\n", + " ax.set_title(f'{titles[i]}', fontsize=10)\n", + "\n", + " i += 1\n", + "\n", + " # Add a colorbar\n", + " # cbar = fig.colorbar(img, ax=axes.ravel().tolist(), label='Brightness Temperatures (°C)', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", + "\n", + " # Extract date\n", + " # date = (datetime.strptime(dtime, '%Y-%m-%dT%H:%M:%S.%fZ'))\n", + "\n", + " # Add a title\n", + " # plt.suptitle('GOES-16 ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC', fontweight='bold', fontsize=12)\n", + " # plt.tight_layout(rect=[0, 0.03, 1, 0.95])\n", + " #-----------------------------------------------------------------------------------------------------------\n", + "\n", + " # Show the image\n", + " plt.show()\n", + "\n", + "extent = [-45, -25, -40, -20]\n", + "\n", + "file_WV_rain = \"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C09_G16_s20240130140204_e20240130149518_c20240130149599\"\n", + "file_WV_norain = \"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C09_G16_s20240430140205_e20240430149519_c20240430149579\"\n", + "file_IR_rain = \"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C13_G16_s20240130140204_e20240130149524_c20240130149589\"\n", + "file_IR_norain = \"../data/goes16/cloud_depth/OR_ABI-L2-CMIPF-M6C13_G16_s20240430140205_e20240430149525_c20240430149589\"\n", + "\n", + "# Get the pixel values\n", + "data_WV_rain = get_reprojection(file_WV_rain, extent)\n", + "data_WV_norain = get_reprojection(file_WV_norain, extent)\n", + "data_IR_rain = get_reprojection(file_IR_rain, extent)\n", + "data_IR_norain = get_reprojection(file_IR_norain, extent)\n", + "\n", + "print(type(data_WV_rain))\n", + "\n", + "data_diff_rain = data_WV_rain - data_IR_rain\n", + "data_diff_norain = data_WV_norain - data_IR_norain\n", + "\n", + "print(data_WV_rain.shape, data_WV_norain.shape)\n", + "print(data_IR_rain.shape, data_IR_norain.shape)\n", + "print(data_diff_rain.shape, data_diff_norain.shape)\n", + "\n", + "data = [data_WV_rain, data_WV_norain, data_IR_rain, data_IR_norain, data_diff_rain, data_diff_norain]\n", + "titles = ['WV_rain', 'WV_norain', 'IR_rain', 'IR_norain', 'diff_rain', 'diff_norain']\n", + "plot_extent(data, titles, extent)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plot Crop" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# %load ../../src/goes16_plot_crop.py\n", + "from datetime import datetime\n", + "import re\n", + "from netCDF4 import Dataset # Read / Write NetCDF4 files\n", + "import matplotlib.pyplot as plt # Plotting library\n", + "from datetime import datetime # Basic Dates and time types\n", + "import cartopy, cartopy.crs as ccrs # Plot maps\n", + "import os # Miscellaneous operating system interfaces\n", + "from osgeo import osr # Python bindings for GDAL\n", + "from osgeo import gdal # Python bindings for GDAL\n", + "import numpy as np # Scientific computing with Python\n", + "\n", + "def change_extension_to_jpg(filepath: str) -> str:\n", + " # Use os.path.splitext to separate the file root and extension\n", + " file_root, _ = os.path.splitext(filepath)\n", + " # Append the new '.jpg' extension\n", + " return f\"{file_root}.jpg\"\n", + "\n", + "# def extract_timestamp(file_path: str) -> str:\n", + "# # Use a regular expression to find the timestamp (12 digits)\n", + "# match = re.search(r'/(\\d{12})', file_path)\n", + "# if match:\n", + "# return match.group(1) # Return the matched timestamp\n", + "# return None # Return None if no timestamp is found\n", + "\n", + "def extract_timestamp(file_path: str) -> str:\n", + " # Use regular expressions to capture the date and time in the file path\n", + " match = re.search(r'(\\d{4})_(\\d{2})_(\\d{2})_(\\d{2})_(\\d{2})', file_path)\n", + " \n", + " if match:\n", + " # Extract the date and time components\n", + " year, month, day, hour, minute = match.groups()\n", + " \n", + " # Create a datetime object\n", + " dt = datetime(year=int(year), month=int(month), day=int(day), hour=int(hour), minute=int(minute))\n", + " \n", + " # Format the datetime object into the desired output format\n", + " return dt.strftime(\"%d/%m/%Y %H:%M\")\n", + " else:\n", + " raise ValueError(\"No valid timestamp found in the file path.\")\n", + "\n", + "# def extract_band_info(file_path: str) -> str:\n", + "# # Use regular expression to extract band number and suffix (CMI in this case)\n", + "# match = re.search(r'band(\\d+)_(\\w+)\\.nc', file_path)\n", + "# if match:\n", + "# band_number = match.group(1)\n", + "# suffix = match.group(2)\n", + "# return f'Band {band_number} {suffix}'\n", + "# else:\n", + "# return 'Invalid file path format'\n", + "\n", + "def extract_band_info(file_path):\n", + " # Use regular expression to find the 'band' followed by digits\n", + " match = re.search(r'band(\\d+)', file_path)\n", + " \n", + " if match:\n", + " # Return the band number as an integer\n", + " return int(match.group(1))\n", + " else:\n", + " # Return None if no match is found\n", + " return None\n", + "\n", + "def convert_timestamp(timestamp: str) -> str:\n", + " # Convert the timestamp to a datetime object\n", + " dt = datetime.strptime(timestamp, '%Y%m%d%H%M')\n", + " # Return the date and time in the format YYYY-MM-DD HH:MM:SS\n", + " return dt.strftime('%Y-%m-%d %H:%M:%S')\n", + "\n", + "def plot_crop(filename: str, save_fig: bool = False):\n", + " \n", + " # Open the reprojected GOES-R image\n", + " file = Dataset(filename)\n", + "\n", + " lat_max, lon_max = (\n", + " -21.699774257353113,\n", + " -42.35676996062447,\n", + " ) # canto superior direito\n", + " lat_min, lon_min = (\n", + " -23.801876626302175,\n", + " -45.05290312102409,\n", + " ) # canto inferior esquerdo\n", + "\n", + " extent = [lon_min, lat_min, lon_max, lat_max]\n", + "\n", + " # Get the pixel values\n", + " data = file.variables['Band1'][:]\n", + "\n", + " print(data[:4])\n", + "\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Choose the plot size (width x height, in inches)\n", + " plt.figure(figsize=(10,10))\n", + "\n", + " # Use the Geostationary projection in cartopy\n", + " ax = plt.axes(projection=ccrs.PlateCarree())\n", + "\n", + " # Define the image extent\n", + " img_extent = [extent[0], extent[2], extent[1], extent[3]]\n", + "\n", + " # Define the color scale based on the channel\n", + " colormap = \"gray_r\" # White to black for IR channels\n", + " \n", + " # Plot the image\n", + " img = ax.imshow(data, \n", + " origin='upper', \n", + " extent=img_extent, \n", + " cmap=colormap)\n", + "\n", + " # Add coastlines, borders and gridlines\n", + " ax.coastlines(resolution='10m', color='white', linewidth=0.8)\n", + " ax.add_feature(cartopy.feature.BORDERS, edgecolor='white', linewidth=0.5)\n", + " gl = ax.gridlines(crs=ccrs.PlateCarree(), \n", + " color='gray', \n", + " alpha=1.0, \n", + " linestyle='--', \n", + " linewidth=0.25, \n", + " xlocs=np.arange(-180, 180, 5), \n", + " ylocs=np.arange(-90, 90, 5), \n", + " draw_labels=True)\n", + " gl.top_labels = False\n", + " gl.right_labels = False\n", + "\n", + " # Add a colorbar\n", + " plt.colorbar(img, label='Brightness Temperatures (°C)', extend='both', orientation='horizontal', pad=0.05, fraction=0.05)\n", + "\n", + " # Extract date\n", + " dtime = extract_timestamp(filename)\n", + " # print(dtime)\n", + " # date = (datetime.strptime(dtime, '%Y%m%d%H%M%S'))\n", + "\n", + " band_info = extract_band_info(filename)\n", + "\n", + " # Add a title\n", + " plt.title('GOES-16 Band' + str(band_info) + ' at ' + dtime + ' UTC\\n', fontweight='bold', fontsize=10, loc='left')\n", + " plt.title('Reg.: ' + str(extent) , fontsize=10, loc='right')\n", + "\n", + " if save_fig:\n", + " #-----------------------------------------------------------------------------------------------------------\n", + " # Save the image\n", + " fig_filename = change_extension_to_jpg(filename)\n", + " plt.savefig(fig_filename, bbox_inches='tight', pad_inches=0, dpi=300)\n", + "\n", + " # Show the image\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[233.92693 230.24689 229.1861 224.0524 222.45467 224.0524 218.63058\n", + " 218.63058 218.63058 218.63058 218.63058 218.63058 216.27327 218.63058\n", + " 220.66049 224.0524 228.04674 230.24689 230.24689 230.24689 230.24689\n", + " 230.24689 229.1861 232.19823 232.19823 229.1861 228.04674 226.8288\n", + " 228.04674 229.1861 229.1861 229.1861 236.95213 248.7649 256.51782\n", + " 260.761 263.24927 266.28757 265.16132 264.99106 264.48032 264.48032\n", + " 266.6019 270.58313 271.7356 271.47366 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263.06592 261.7563 261.7563 262.33252\n", + " 262.13608 261.95276 266.44473 273.63455 276.8562 276.45023 276.04422\n", + " 276.04422 279.14804 282.003 284.19006 282.56613 286.96646 289.4678\n", + " 290.01785 290.01785 290.85602 291.70728 290.9608 289.96548 290.2012\n", + " 291.82513 292.71567 292.6633 292.6633 292.44064 292.38828 292.5978\n", + " 292.87283 292.76807 291.77274 290.43695 290.43695 292.5454 293.3574\n", + " 293.40976 293.3574 ]\n", + " [256.76666 256.76666 254.69746 256.51782 259.29422 256.51782 251.1615\n", + " 240.68456 232.19823 233.92693 234.73888 229.1861 229.1861 226.8288\n", + " 229.1861 228.04674 226.8288 226.8288 226.8288 226.8288 228.04674\n", + " 228.04674 229.1861 229.1861 228.04674 229.1861 229.1861 229.1861\n", + " 231.2553 236.24495 242.80612 248.3851 253.29617 253.29617 259.51685\n", + " 262.13608 261.7563 259.72638 262.69922 271.7356 276.96097 276.96097\n", + " 272.22015 273.29404 270.45218 270.05927 268.81516 270.976 276.04422\n", + " 275.08823 270.71408 280.22192 284.7139 284.7139 280.66718 279.69806\n", + " 278.03485 278.32297 278.2182 275.93945 269.78427 265.31845 265.31845\n", + " 265.16132 265.16132 264.48032 265.97327 267.06024 266.9031 269.37827\n", + " 271.9713 271.9713 277.35385 281.2565 281.59702 279.23972 274.31555\n", + " 270.58313 267.9508 265.803 265.803 265.31845 265.16132 265.97327\n", + " 265.97327 265.4887 274.21075 280.22192 281.42676 281.42676 282.3304\n", + " 284.6353 286.21997 285.65683 284.56985 287.0974 289.8345 289.8345\n", + " 290.79053 291.07864 291.1965 291.6025 292.16562 291.02628 290.38455\n", + " 290.38455 291.943 292.49304 292.6633 292.5978 292.49304 292.76807\n", + " 292.9776 292.82043 292.82043 291.3144 291.65488 293.09546 293.14786\n", + " 293.0431 292.76807]]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_crop(filename = f'../../goes16_data_cropped/CMI_band7_2024_02_08_23_50.nc', save_fig=False)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "type of dataset.variables: \n", + "\n", + "keys: \n", + "dict_keys(['CMI_2023_10_31_08_20', 'CMI_2023_10_31_04_30', 'CMI_2023_10_31_08_10', 'CMI_2023_10_31_09_10', 'CMI_2023_10_31_04_40', 'CMI_2023_10_31_04_10', 'CMI_2023_10_31_07_00', 'CMI_2023_10_31_05_00', 'CMI_2023_10_31_06_00', 'CMI_2023_10_31_08_00', 'CMI_2023_10_31_03_10', 'CMI_2023_10_31_08_40', 'CMI_2023_10_31_06_10', 'CMI_2023_10_31_01_00', 'CMI_2023_10_31_09_00', 'CMI_2023_10_31_08_30', 'CMI_2023_10_31_02_00', 'CMI_2023_10_31_07_10', 'CMI_2023_10_31_09_20', 'CMI_2023_10_31_03_00', 'CMI_2023_10_31_08_50', 'CMI_2023_10_31_03_20', 'CMI_2023_10_31_04_50', 'CMI_2023_10_31_04_00', 'CMI_2023_10_31_04_20', 'CMI_2023_10_31_02_10', 'CMI_2023_10_31_05_20', 'CMI_2023_10_31_06_20', 'CMI_2023_10_31_01_10', 'CMI_2023_10_31_07_20', 'CMI_2023_10_31_02_20', 'CMI_2023_10_31_09_50', 'CMI_2023_10_31_09_30', 'CMI_2023_10_31_05_10', 'CMI_2023_10_31_03_30', 'CMI_2023_10_31_06_30', 'CMI_2023_10_31_09_40', 'CMI_2023_10_31_06_40', 'CMI_2023_10_31_05_30', 'CMI_2023_10_31_01_30', 'CMI_2023_10_31_06_50', 'CMI_2023_10_31_01_50', 'CMI_2023_10_31_02_30', 'CMI_2023_10_31_01_40', 'CMI_2023_10_31_03_50', 'CMI_2023_10_31_02_50', 'CMI_2023_10_31_05_50', 'CMI_2023_10_31_07_30', 'CMI_2023_10_31_03_40', 'CMI_2023_10_31_05_40', 'CMI_2023_10_31_00_00', 'CMI_2023_10_31_00_10', 'CMI_2023_10_31_07_40', 'CMI_2023_10_31_02_40', 'CMI_2023_10_31_00_30', 'CMI_2023_10_31_00_20', 'CMI_2023_10_31_07_50', 'CMI_2023_10_31_10_10', 'CMI_2023_10_31_10_00', 'CMI_2023_10_31_10_40', 'CMI_2023_10_31_01_20', 'CMI_2023_10_31_10_50', 'CMI_2023_10_31_11_10', 'CMI_2023_10_31_11_50', 'CMI_2023_10_31_11_30', 'CMI_2023_10_31_00_50', 'CMI_2023_10_31_00_40', 'CMI_2023_10_31_12_30', 'CMI_2023_10_31_12_20', 'CMI_2023_10_31_10_20', 'CMI_2023_10_31_12_10', 'CMI_2023_10_31_13_00', 'CMI_2023_10_31_11_00', 'CMI_2023_10_31_12_00', 'CMI_2023_10_31_13_40', 'CMI_2023_10_31_11_20', 'CMI_2023_10_31_13_10', 'CMI_2023_10_31_10_30', 'CMI_2023_10_31_12_50', 'CMI_2023_10_31_13_30', 'CMI_2023_10_31_12_40', 'CMI_2023_10_31_14_10', 'CMI_2023_10_31_14_00', 'CMI_2023_10_31_14_30', 'CMI_2023_10_31_13_20', 'CMI_2023_10_31_14_20', 'CMI_2023_10_31_15_00', 'CMI_2023_10_31_15_20', 'CMI_2023_10_31_15_10', 'CMI_2023_10_31_14_50', 'CMI_2023_10_31_15_40', 'CMI_2023_10_31_13_50', 'CMI_2023_10_31_11_40', 'CMI_2023_10_31_15_30', 'CMI_2023_10_31_16_20', 'CMI_2023_10_31_14_40', 'CMI_2023_10_31_16_50', 'CMI_2023_10_31_17_10', 'CMI_2023_10_31_17_20', 'CMI_2023_10_31_16_00', 'CMI_2023_10_31_16_30', 'CMI_2023_10_31_16_40', 'CMI_2023_10_31_18_00', 'CMI_2023_10_31_17_50', 'CMI_2023_10_31_15_50', 'CMI_2023_10_31_17_00', 'CMI_2023_10_31_17_40', 'CMI_2023_10_31_16_10', 'CMI_2023_10_31_18_40', 'CMI_2023_10_31_18_50', 'CMI_2023_10_31_17_30', 'CMI_2023_10_31_18_20', 'CMI_2023_10_31_18_10', 'CMI_2023_10_31_19_10', 'CMI_2023_10_31_19_40', 'CMI_2023_10_31_19_50', 'CMI_2023_10_31_18_30', 'CMI_2023_10_31_19_20', 'CMI_2023_10_31_20_40', 'CMI_2023_10_31_20_30', 'CMI_2023_10_31_20_50', 'CMI_2023_10_31_20_10', 'CMI_2023_10_31_20_00', 'CMI_2023_10_31_19_00', 'CMI_2023_10_31_20_20', 'CMI_2023_10_31_21_20', 'CMI_2023_10_31_21_00', 'CMI_2023_10_31_21_40', 'CMI_2023_10_31_19_30', 'CMI_2023_10_31_21_10', 'CMI_2023_10_31_21_30', 'CMI_2023_10_31_22_20', 'CMI_2023_10_31_21_50', 'CMI_2023_10_31_22_30', 'CMI_2023_10_31_22_50', 'CMI_2023_10_31_22_10', 'CMI_2023_10_31_23_20', 'CMI_2023_10_31_23_30', 'CMI_2023_10_31_22_00', 'CMI_2023_10_31_23_10', 'CMI_2023_10_31_23_40', 'CMI_2023_10_31_23_00', 'CMI_2023_10_31_23_50', 'CMI_2023_10_31_22_40'])\n", + "sorted keys: \n", + "['CMI_2023_10_31_00_00', 'CMI_2023_10_31_00_10', 'CMI_2023_10_31_00_20', 'CMI_2023_10_31_00_30', 'CMI_2023_10_31_00_40', 'CMI_2023_10_31_00_50', 'CMI_2023_10_31_01_00', 'CMI_2023_10_31_01_10', 'CMI_2023_10_31_01_20', 'CMI_2023_10_31_01_30', 'CMI_2023_10_31_01_40', 'CMI_2023_10_31_01_50', 'CMI_2023_10_31_02_00', 'CMI_2023_10_31_02_10', 'CMI_2023_10_31_02_20', 'CMI_2023_10_31_02_30', 'CMI_2023_10_31_02_40', 'CMI_2023_10_31_02_50', 'CMI_2023_10_31_03_00', 'CMI_2023_10_31_03_10', 'CMI_2023_10_31_03_20', 'CMI_2023_10_31_03_30', 'CMI_2023_10_31_03_40', 'CMI_2023_10_31_03_50', 'CMI_2023_10_31_04_00', 'CMI_2023_10_31_04_10', 'CMI_2023_10_31_04_20', 'CMI_2023_10_31_04_30', 'CMI_2023_10_31_04_40', 'CMI_2023_10_31_04_50', 'CMI_2023_10_31_05_00', 'CMI_2023_10_31_05_10', 'CMI_2023_10_31_05_20', 'CMI_2023_10_31_05_30', 'CMI_2023_10_31_05_40', 'CMI_2023_10_31_05_50', 'CMI_2023_10_31_06_00', 'CMI_2023_10_31_06_10', 'CMI_2023_10_31_06_20', 'CMI_2023_10_31_06_30', 'CMI_2023_10_31_06_40', 'CMI_2023_10_31_06_50', 'CMI_2023_10_31_07_00', 'CMI_2023_10_31_07_10', 'CMI_2023_10_31_07_20', 'CMI_2023_10_31_07_30', 'CMI_2023_10_31_07_40', 'CMI_2023_10_31_07_50', 'CMI_2023_10_31_08_00', 'CMI_2023_10_31_08_10', 'CMI_2023_10_31_08_20', 'CMI_2023_10_31_08_30', 'CMI_2023_10_31_08_40', 'CMI_2023_10_31_08_50', 'CMI_2023_10_31_09_00', 'CMI_2023_10_31_09_10', 'CMI_2023_10_31_09_20', 'CMI_2023_10_31_09_30', 'CMI_2023_10_31_09_40', 'CMI_2023_10_31_09_50', 'CMI_2023_10_31_10_00', 'CMI_2023_10_31_10_10', 'CMI_2023_10_31_10_20', 'CMI_2023_10_31_10_30', 'CMI_2023_10_31_10_40', 'CMI_2023_10_31_10_50', 'CMI_2023_10_31_11_00', 'CMI_2023_10_31_11_10', 'CMI_2023_10_31_11_20', 'CMI_2023_10_31_11_30', 'CMI_2023_10_31_11_40', 'CMI_2023_10_31_11_50', 'CMI_2023_10_31_12_00', 'CMI_2023_10_31_12_10', 'CMI_2023_10_31_12_20', 'CMI_2023_10_31_12_30', 'CMI_2023_10_31_12_40', 'CMI_2023_10_31_12_50', 'CMI_2023_10_31_13_00', 'CMI_2023_10_31_13_10', 'CMI_2023_10_31_13_20', 'CMI_2023_10_31_13_30', 'CMI_2023_10_31_13_40', 'CMI_2023_10_31_13_50', 'CMI_2023_10_31_14_00', 'CMI_2023_10_31_14_10', 'CMI_2023_10_31_14_20', 'CMI_2023_10_31_14_30', 'CMI_2023_10_31_14_40', 'CMI_2023_10_31_14_50', 'CMI_2023_10_31_15_00', 'CMI_2023_10_31_15_10', 'CMI_2023_10_31_15_20', 'CMI_2023_10_31_15_30', 'CMI_2023_10_31_15_40', 'CMI_2023_10_31_15_50', 'CMI_2023_10_31_16_00', 'CMI_2023_10_31_16_10', 'CMI_2023_10_31_16_20', 'CMI_2023_10_31_16_30', 'CMI_2023_10_31_16_40', 'CMI_2023_10_31_16_50', 'CMI_2023_10_31_17_00', 'CMI_2023_10_31_17_10', 'CMI_2023_10_31_17_20', 'CMI_2023_10_31_17_30', 'CMI_2023_10_31_17_40', 'CMI_2023_10_31_17_50', 'CMI_2023_10_31_18_00', 'CMI_2023_10_31_18_10', 'CMI_2023_10_31_18_20', 'CMI_2023_10_31_18_30', 'CMI_2023_10_31_18_40', 'CMI_2023_10_31_18_50', 'CMI_2023_10_31_19_00', 'CMI_2023_10_31_19_10', 'CMI_2023_10_31_19_20', 'CMI_2023_10_31_19_30', 'CMI_2023_10_31_19_40', 'CMI_2023_10_31_19_50', 'CMI_2023_10_31_20_00', 'CMI_2023_10_31_20_10', 'CMI_2023_10_31_20_20', 'CMI_2023_10_31_20_30', 'CMI_2023_10_31_20_40', 'CMI_2023_10_31_20_50', 'CMI_2023_10_31_21_00', 'CMI_2023_10_31_21_10', 'CMI_2023_10_31_21_20', 'CMI_2023_10_31_21_30', 'CMI_2023_10_31_21_40', 'CMI_2023_10_31_21_50', 'CMI_2023_10_31_22_00', 'CMI_2023_10_31_22_10', 'CMI_2023_10_31_22_20', 'CMI_2023_10_31_22_30', 'CMI_2023_10_31_22_40', 'CMI_2023_10_31_22_50', 'CMI_2023_10_31_23_00', 'CMI_2023_10_31_23_10', 'CMI_2023_10_31_23_20', 'CMI_2023_10_31_23_30', 'CMI_2023_10_31_23_40', 'CMI_2023_10_31_23_50']\n" + ] + } + ], + "source": [ + "import netCDF4 as nc\n", + "netcdf_file = '../../data/goes16/CMI/C07/2023/C07_2023_10_31.nc'\n", + "dataset = nc.Dataset(netcdf_file, 'r')\n", + "\n", + "print(f'type of dataset.variables: \\n{type(dataset.variables)}')\n", + "print(f'keys: \\n{dataset.variables.keys()}')\n", + "# Sort the keys\n", + "sorted_keys = sorted(dataset.variables.keys())\n", + "print(f'sorted keys: \\n{sorted_keys}')\n", + "\n", + "# dataset.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\n", + "float32 CMI_2023_10_31_00_00(dim_0_CMI_2023_10_31_00_00, dim_1_CMI_2023_10_31_00_00)\n", + "unlimited dimensions: \n", + "current shape = (94, 121)\n", + "filling on, default _FillValue of 9.969209968386869e+36 used" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.variables['CMI_2023_10_31_00_00']" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "netCDF4._netCDF4.Variable" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(dataset.variables['CMI_2023_10_31_00_00'])" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.ma.core.MaskedArray" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "type(dataset.variables['CMI_2023_10_31_00_00'][:])" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "masked_array(\n", + " data=[[284.12457, 286.28546, 286.28546, ..., 292.5454 , 292.6633 ,\n", + " 292.6633 ],\n", + " [282.40897, 282.08157, 278.598 , ..., 292.49304, 292.49304,\n", + " 292.5454 ],\n", + " [284.3472 , 283.74478, 279.8814 , ..., 290.67267, 291.77274,\n", + " 292.71567],\n", + " ...,\n", + " [288.2237 , 288.1582 , 287.89627, ..., 222.45467, 220.66049,\n", + " 222.45467],\n", + " [288.1582 , 287.96176, 287.76532, ..., 222.45467, 222.45467,\n", + " 218.63058],\n", + " [288.2237 , 288.02725, 287.96176, ..., 218.63058, 218.63058,\n", + " 218.63058]],\n", + " mask=False,\n", + " fill_value=1e+20,\n", + " dtype=float32)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.variables['CMI_2023_10_31_00_00'][:]" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(94, 121)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.variables['CMI_2023_10_31_00_00'][:].shape" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "type of dataset.variables: \n", + "\n", + "keys: \n", + "dict_keys(['CMI_2023_10_31_08_00', 'CMI_2023_10_31_06_10', 'CMI_2023_10_31_04_10', 'CMI_2023_10_31_07_00', 'CMI_2023_10_31_00_00', 'CMI_2023_10_31_09_00', 'CMI_2023_10_31_04_00', 'CMI_2023_10_31_05_10', 'CMI_2023_10_31_00_10', 'CMI_2023_10_31_09_10', 'CMI_2023_10_31_04_30', 'CMI_2023_10_31_01_00', 'CMI_2023_10_31_08_10', 'CMI_2023_10_31_09_20', 'CMI_2023_10_31_06_20', 'CMI_2023_10_31_08_20', 'CMI_2023_10_31_04_20', 'CMI_2023_10_31_07_20', 'CMI_2023_10_31_03_00', 'CMI_2023_10_31_00_20', 'CMI_2023_10_31_06_00', 'CMI_2023_10_31_03_10', 'CMI_2023_10_31_01_10', 'CMI_2023_10_31_03_20', 'CMI_2023_10_31_06_30', 'CMI_2023_10_31_02_00', 'CMI_2023_10_31_08_30', 'CMI_2023_10_31_02_20', 'CMI_2023_10_31_02_10', 'CMI_2023_10_31_02_30', 'CMI_2023_10_31_07_10', 'CMI_2023_10_31_05_20', 'CMI_2023_10_31_01_20', 'CMI_2023_10_31_04_40', 'CMI_2023_10_31_08_40', 'CMI_2023_10_31_05_00', 'CMI_2023_10_31_03_30', 'CMI_2023_10_31_04_50', 'CMI_2023_10_31_01_30', 'CMI_2023_10_31_09_30', 'CMI_2023_10_31_02_40', 'CMI_2023_10_31_00_30', 'CMI_2023_10_31_08_50', 'CMI_2023_10_31_07_30', 'CMI_2023_10_31_06_40', 'CMI_2023_10_31_06_50', 'CMI_2023_10_31_02_50', 'CMI_2023_10_31_01_40', 'CMI_2023_10_31_03_40', 'CMI_2023_10_31_05_40', 'CMI_2023_10_31_00_40', 'CMI_2023_10_31_05_30', 'CMI_2023_10_31_07_50', 'CMI_2023_10_31_05_50', 'CMI_2023_10_31_07_40', 'CMI_2023_10_31_03_50', 'CMI_2023_10_31_10_00', 'CMI_2023_10_31_10_30', 'CMI_2023_10_31_10_20', 'CMI_2023_10_31_09_50', 'CMI_2023_10_31_09_40', 'CMI_2023_10_31_01_50', 'CMI_2023_10_31_10_50', 'CMI_2023_10_31_10_40', 'CMI_2023_10_31_11_00', 'CMI_2023_10_31_11_10', 'CMI_2023_10_31_00_50', 'CMI_2023_10_31_10_10', 'CMI_2023_10_31_12_00', 'CMI_2023_10_31_12_30', 'CMI_2023_10_31_12_10', 'CMI_2023_10_31_11_30', 'CMI_2023_10_31_11_40', 'CMI_2023_10_31_11_50', 'CMI_2023_10_31_13_00', 'CMI_2023_10_31_12_20', 'CMI_2023_10_31_13_10', 'CMI_2023_10_31_12_40', 'CMI_2023_10_31_12_50', 'CMI_2023_10_31_14_10', 'CMI_2023_10_31_13_20', 'CMI_2023_10_31_11_20', 'CMI_2023_10_31_14_20', 'CMI_2023_10_31_14_30', 'CMI_2023_10_31_14_40', 'CMI_2023_10_31_14_50', 'CMI_2023_10_31_13_40', 'CMI_2023_10_31_13_50', 'CMI_2023_10_31_13_30', 'CMI_2023_10_31_15_00', 'CMI_2023_10_31_15_30', 'CMI_2023_10_31_15_50', 'CMI_2023_10_31_15_20', 'CMI_2023_10_31_15_10', 'CMI_2023_10_31_15_40', 'CMI_2023_10_31_16_10', 'CMI_2023_10_31_14_00', 'CMI_2023_10_31_16_50', 'CMI_2023_10_31_16_00', 'CMI_2023_10_31_16_40', 'CMI_2023_10_31_17_00', 'CMI_2023_10_31_16_30', 'CMI_2023_10_31_17_20', 'CMI_2023_10_31_16_20', 'CMI_2023_10_31_17_10', 'CMI_2023_10_31_18_20', 'CMI_2023_10_31_17_50', 'CMI_2023_10_31_18_10', 'CMI_2023_10_31_18_30', 'CMI_2023_10_31_18_40', 'CMI_2023_10_31_19_10', 'CMI_2023_10_31_17_30', 'CMI_2023_10_31_19_00', 'CMI_2023_10_31_18_50', 'CMI_2023_10_31_19_30', 'CMI_2023_10_31_19_20', 'CMI_2023_10_31_18_00', 'CMI_2023_10_31_20_00', 'CMI_2023_10_31_19_40', 'CMI_2023_10_31_17_40', 'CMI_2023_10_31_19_50', 'CMI_2023_10_31_21_00', 'CMI_2023_10_31_21_20', 'CMI_2023_10_31_20_10', 'CMI_2023_10_31_20_20', 'CMI_2023_10_31_20_40', 'CMI_2023_10_31_20_50', 'CMI_2023_10_31_21_10', 'CMI_2023_10_31_21_50', 'CMI_2023_10_31_20_30', 'CMI_2023_10_31_21_40', 'CMI_2023_10_31_21_30', 'CMI_2023_10_31_22_00', 'CMI_2023_10_31_22_40', 'CMI_2023_10_31_23_00', 'CMI_2023_10_31_22_20', 'CMI_2023_10_31_22_30', 'CMI_2023_10_31_22_10', 'CMI_2023_10_31_22_50', 'CMI_2023_10_31_23_20', 'CMI_2023_10_31_23_10'])\n", + "sorted keys: \n", + "['CMI_2023_10_31_00_00', 'CMI_2023_10_31_00_10', 'CMI_2023_10_31_00_20', 'CMI_2023_10_31_00_30', 'CMI_2023_10_31_00_40', 'CMI_2023_10_31_00_50', 'CMI_2023_10_31_01_00', 'CMI_2023_10_31_01_10', 'CMI_2023_10_31_01_20', 'CMI_2023_10_31_01_30', 'CMI_2023_10_31_01_40', 'CMI_2023_10_31_01_50', 'CMI_2023_10_31_02_00', 'CMI_2023_10_31_02_10', 'CMI_2023_10_31_02_20', 'CMI_2023_10_31_02_30', 'CMI_2023_10_31_02_40', 'CMI_2023_10_31_02_50', 'CMI_2023_10_31_03_00', 'CMI_2023_10_31_03_10', 'CMI_2023_10_31_03_20', 'CMI_2023_10_31_03_30', 'CMI_2023_10_31_03_40', 'CMI_2023_10_31_03_50', 'CMI_2023_10_31_04_00', 'CMI_2023_10_31_04_10', 'CMI_2023_10_31_04_20', 'CMI_2023_10_31_04_30', 'CMI_2023_10_31_04_40', 'CMI_2023_10_31_04_50', 'CMI_2023_10_31_05_00', 'CMI_2023_10_31_05_10', 'CMI_2023_10_31_05_20', 'CMI_2023_10_31_05_30', 'CMI_2023_10_31_05_40', 'CMI_2023_10_31_05_50', 'CMI_2023_10_31_06_00', 'CMI_2023_10_31_06_10', 'CMI_2023_10_31_06_20', 'CMI_2023_10_31_06_30', 'CMI_2023_10_31_06_40', 'CMI_2023_10_31_06_50', 'CMI_2023_10_31_07_00', 'CMI_2023_10_31_07_10', 'CMI_2023_10_31_07_20', 'CMI_2023_10_31_07_30', 'CMI_2023_10_31_07_40', 'CMI_2023_10_31_07_50', 'CMI_2023_10_31_08_00', 'CMI_2023_10_31_08_10', 'CMI_2023_10_31_08_20', 'CMI_2023_10_31_08_30', 'CMI_2023_10_31_08_40', 'CMI_2023_10_31_08_50', 'CMI_2023_10_31_09_00', 'CMI_2023_10_31_09_10', 'CMI_2023_10_31_09_20', 'CMI_2023_10_31_09_30', 'CMI_2023_10_31_09_40', 'CMI_2023_10_31_09_50', 'CMI_2023_10_31_10_00', 'CMI_2023_10_31_10_10', 'CMI_2023_10_31_10_20', 'CMI_2023_10_31_10_30', 'CMI_2023_10_31_10_40', 'CMI_2023_10_31_10_50', 'CMI_2023_10_31_11_00', 'CMI_2023_10_31_11_10', 'CMI_2023_10_31_11_20', 'CMI_2023_10_31_11_30', 'CMI_2023_10_31_11_40', 'CMI_2023_10_31_11_50', 'CMI_2023_10_31_12_00', 'CMI_2023_10_31_12_10', 'CMI_2023_10_31_12_20', 'CMI_2023_10_31_12_30', 'CMI_2023_10_31_12_40', 'CMI_2023_10_31_12_50', 'CMI_2023_10_31_13_00', 'CMI_2023_10_31_13_10', 'CMI_2023_10_31_13_20', 'CMI_2023_10_31_13_30', 'CMI_2023_10_31_13_40', 'CMI_2023_10_31_13_50', 'CMI_2023_10_31_14_00', 'CMI_2023_10_31_14_10', 'CMI_2023_10_31_14_20', 'CMI_2023_10_31_14_30', 'CMI_2023_10_31_14_40', 'CMI_2023_10_31_14_50', 'CMI_2023_10_31_15_00', 'CMI_2023_10_31_15_10', 'CMI_2023_10_31_15_20', 'CMI_2023_10_31_15_30', 'CMI_2023_10_31_15_40', 'CMI_2023_10_31_15_50', 'CMI_2023_10_31_16_00', 'CMI_2023_10_31_16_10', 'CMI_2023_10_31_16_20', 'CMI_2023_10_31_16_30', 'CMI_2023_10_31_16_40', 'CMI_2023_10_31_16_50', 'CMI_2023_10_31_17_00', 'CMI_2023_10_31_17_10', 'CMI_2023_10_31_17_20', 'CMI_2023_10_31_17_30', 'CMI_2023_10_31_17_40', 'CMI_2023_10_31_17_50', 'CMI_2023_10_31_18_00', 'CMI_2023_10_31_18_10', 'CMI_2023_10_31_18_20', 'CMI_2023_10_31_18_30', 'CMI_2023_10_31_18_40', 'CMI_2023_10_31_18_50', 'CMI_2023_10_31_19_00', 'CMI_2023_10_31_19_10', 'CMI_2023_10_31_19_20', 'CMI_2023_10_31_19_30', 'CMI_2023_10_31_19_40', 'CMI_2023_10_31_19_50', 'CMI_2023_10_31_20_00', 'CMI_2023_10_31_20_10', 'CMI_2023_10_31_20_20', 'CMI_2023_10_31_20_30', 'CMI_2023_10_31_20_40', 'CMI_2023_10_31_20_50', 'CMI_2023_10_31_21_00', 'CMI_2023_10_31_21_10', 'CMI_2023_10_31_21_20', 'CMI_2023_10_31_21_30', 'CMI_2023_10_31_21_40', 'CMI_2023_10_31_21_50', 'CMI_2023_10_31_22_00', 'CMI_2023_10_31_22_10', 'CMI_2023_10_31_22_20', 'CMI_2023_10_31_22_30', 'CMI_2023_10_31_22_40', 'CMI_2023_10_31_22_50', 'CMI_2023_10_31_23_00', 'CMI_2023_10_31_23_10', 'CMI_2023_10_31_23_20']\n" + ] + } + ], + "source": [ + "import netCDF4 as nc\n", + "\n", + "fa_netcdf_file = \"../../CMI_features/fluxo_ascendente/2023/FA_2023_10_31.nc\"\n", + "dataset = nc.Dataset(fa_netcdf_file, 'r')\n", + "\n", + "print(f'type of dataset.variables: \\n{type(dataset.variables)}')\n", + "print(f'keys: \\n{dataset.variables.keys()}')\n", + "# Sort the keys\n", + "sorted_keys = sorted(dataset.variables.keys())\n", + "print(f'sorted keys: \\n{sorted_keys}')\n" + ] + } + ], + "metadata": { + "colab": { + "provenance": [], + "toc_visible": true + }, + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/notebooks/SBGL_GOES16.ipynb b/notebooks/GOES16/SBGL_GOES16.ipynb similarity index 100% rename from notebooks/SBGL_GOES16.ipynb rename to notebooks/GOES16/SBGL_GOES16.ipynb diff --git a/notebooks/GOES16/goes16_custom.ipynb b/notebooks/GOES16/goes16_custom.ipynb new file mode 100644 index 00000000..96453f2d --- /dev/null +++ b/notebooks/GOES16/goes16_custom.ipynb @@ -0,0 +1,1848 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "GOES16_AOD_and_TrueColor.ipynb", + "provenance": [], + "authorship_tag": "ABX9TyO8Id5DwtFibDOUmR4O07Gv", + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "\"Open" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "e1X1l7zYmPbM" + }, + "source": [ + "# Custom GOES-16 GOES-17 AOD Processing\n", + "\n", + " author: Barron H. Henderson\n", + " date: 2023-05-08\n", + "\n", + "Download, process, and plot GOES-R L2 Channel Radiances, AODC and L1b. Produce a figure that is comparable to NOAA's AerosolWatch website. https://www.star.nesdis.noaa.gov/smcd/spb/aq/AerosolWatch" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "j5peuH7Kt9zt" + }, + "source": [ + "# Installing Package\n", + "\n", + "Google Colab needs netcdf4 to be installed. If you are not on Google Colab, skip this step. Otherwise, run teh command below to install `netcdf4` for netcdf file read.\n", + "\n", + "To make quick easy map overlays, I am including pycno. pycno allows you to use NASA overlay formats to add coastlines, countries, and states to maps. It is very light weight compared to basemap or cartopy." + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "C4ufNfWjm-yo", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "aad0e9ef-8f18-4ea7-c6b0-452545396994" + }, + "source": [ + "!pip install -qq h5netcdf pyproj s3fs geopandas" + ], + "execution_count": 2, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.7/7.7 MB\u001b[0m \u001b[31m23.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m21.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m72.7/72.7 kB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.0/1.0 MB\u001b[0m \u001b[31m10.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m160.1/160.1 kB\u001b[0m \u001b[31m8.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m16.0/16.0 MB\u001b[0m \u001b[31m12.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m10.4/10.4 MB\u001b[0m \u001b[31m42.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m114.5/114.5 kB\u001b[0m \u001b[31m490.6 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m268.8/268.8 kB\u001b[0m \u001b[31m10.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m149.6/149.6 kB\u001b[0m \u001b[31m8.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25h" + ] + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "abyWrjOIuEtP" + }, + "source": [ + "# Import Packages\n", + "\n", + "Not import all libraries that will be used.\n", + "\n", + "\n", + "* `warnings` is used to warn when cahced files are used\n", + "* `xarray` is used for netcdf file manipulation and plotting. This implicitly uses `netcdf4` from above.\n", + "* `numpy` is used for numeric array manipulation\n", + "* `pandas` and `geopandas` are used for CSV and shapefiles\n", + "* `matplotlib` is used for plotting functions.\n" + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "uRwVup0flkSi" + }, + "source": [ + "import matplotlib.pyplot as plt\n", + "import warnings\n", + "import s3fs\n", + "import xarray as xr\n", + "import pyproj\n", + "import pandas as pd\n", + "import geopandas as gpd\n", + "import numpy as np\n" + ], + "execution_count": 3, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "# Grab States and Counties for Plotting Later" + ], + "metadata": { + "id": "DZaV2ik3yMZq" + } + }, + { + "cell_type": "code", + "source": [ + "!wget -N https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_county_5m.zip\n", + "!wget -N https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip\n", + "cb = gpd.read_file('cb_2018_us_county_5m.zip')\n", + "sb = gpd.read_file('cb_2018_us_state_500k.zip')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "0EMTqHTvpEBD", + "outputId": "41f06eb1-2813-4e4c-91a1-d161ddf49889" + }, + "execution_count": 4, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "--2023-05-08 17:32:55-- https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_county_5m.zip\n", + "Resolving www2.census.gov (www2.census.gov)... 104.66.235.36, 2600:1408:7:1bd::208c, 2600:1408:7:191::208c\n", + "Connecting to www2.census.gov (www2.census.gov)|104.66.235.36|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: unspecified [application/zip]\n", + "Saving to: ‘cb_2018_us_county_5m.zip’\n", + "\n", + "cb_2018_us_county_5 [ <=> ] 2.65M 14.3MB/s in 0.2s \n", + "\n", + "2023-05-08 17:32:56 (14.3 MB/s) - ‘cb_2018_us_county_5m.zip’ saved [2781997]\n", + "\n", + "--2023-05-08 17:32:56-- https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip\n", + "Resolving www2.census.gov (www2.census.gov)... 104.66.235.36, 2600:1408:7:1bd::208c, 2600:1408:7:191::208c\n", + "Connecting to www2.census.gov (www2.census.gov)|104.66.235.36|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: unspecified [application/zip]\n", + "Saving to: ‘cb_2018_us_state_500k.zip’\n", + "\n", + "cb_2018_us_state_50 [ <=> ] 3.15M 16.1MB/s in 0.2s \n", + "\n", + "2023-05-08 17:32:56 (16.1 MB/s) - ‘cb_2018_us_state_500k.zip’ saved [3304931]\n", + "\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yg-00cIyuG9B" + }, + "source": [ + "# Explore Data on AWS" + ] + }, + { + "cell_type": "code", + "source": [ + "awsfs = s3fs.S3FileSystem(anon=True)" + ], + "metadata": { + "id": "2QaGDnTtelNm" + }, + "execution_count": 5, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "awsfs.ls('noaa-goes16/')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "-83wglIKiQ4u", + "outputId": "9443b71d-f133-46e2-bec0-017aaf148236" + }, + "execution_count": 6, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "['noaa-goes16/ABI-L1b-RadC',\n", + " 'noaa-goes16/ABI-L1b-RadF',\n", + " 'noaa-goes16/ABI-L1b-RadM',\n", + " 'noaa-goes16/ABI-L2-ACHA2KMC',\n", + " 'noaa-goes16/ABI-L2-ACHA2KMF',\n", + " 'noaa-goes16/ABI-L2-ACHA2KMM',\n", + " 'noaa-goes16/ABI-L2-ACHAC',\n", + " 'noaa-goes16/ABI-L2-ACHAF',\n", + " 'noaa-goes16/ABI-L2-ACHAM',\n", + " 'noaa-goes16/ABI-L2-ACHP2KMC',\n", + " 'noaa-goes16/ABI-L2-ACHP2KMF',\n", + " 'noaa-goes16/ABI-L2-ACHP2KMM',\n", + " 'noaa-goes16/ABI-L2-ACHTF',\n", + " 'noaa-goes16/ABI-L2-ACHTM',\n", + " 'noaa-goes16/ABI-L2-ACMC',\n", + " 'noaa-goes16/ABI-L2-ACMF',\n", + " 'noaa-goes16/ABI-L2-ACMM',\n", + " 'noaa-goes16/ABI-L2-ACTPC',\n", + " 'noaa-goes16/ABI-L2-ACTPF',\n", + " 'noaa-goes16/ABI-L2-ACTPM',\n", + " 'noaa-goes16/ABI-L2-ADPC',\n", + " 'noaa-goes16/ABI-L2-ADPF',\n", + " 'noaa-goes16/ABI-L2-ADPM',\n", + " 'noaa-goes16/ABI-L2-AICEF',\n", + " 'noaa-goes16/ABI-L2-AITAF',\n", + " 'noaa-goes16/ABI-L2-AODC',\n", + " 'noaa-goes16/ABI-L2-AODF',\n", + " 'noaa-goes16/ABI-L2-BRFC',\n", + " 'noaa-goes16/ABI-L2-BRFF',\n", + " 'noaa-goes16/ABI-L2-BRFM',\n", + " 'noaa-goes16/ABI-L2-CMIPC',\n", + " 'noaa-goes16/ABI-L2-CMIPF',\n", + " 'noaa-goes16/ABI-L2-CMIPM',\n", + " 'noaa-goes16/ABI-L2-COD2KMF',\n", + " 'noaa-goes16/ABI-L2-CODC',\n", + " 'noaa-goes16/ABI-L2-CODF',\n", + " 'noaa-goes16/ABI-L2-CPSC',\n", + " 'noaa-goes16/ABI-L2-CPSF',\n", + " 'noaa-goes16/ABI-L2-CPSM',\n", + " 'noaa-goes16/ABI-L2-CTPC',\n", + " 'noaa-goes16/ABI-L2-CTPF',\n", + " 'noaa-goes16/ABI-L2-DMWC',\n", + " 'noaa-goes16/ABI-L2-DMWF',\n", + " 'noaa-goes16/ABI-L2-DMWM',\n", + " 'noaa-goes16/ABI-L2-DMWVC',\n", + " 'noaa-goes16/ABI-L2-DMWVF',\n", + " 'noaa-goes16/ABI-L2-DMWVM',\n", + " 'noaa-goes16/ABI-L2-DSIC',\n", + " 'noaa-goes16/ABI-L2-DSIF',\n", + " 'noaa-goes16/ABI-L2-DSIM',\n", + " 'noaa-goes16/ABI-L2-DSRC',\n", + " 'noaa-goes16/ABI-L2-DSRF',\n", + " 'noaa-goes16/ABI-L2-DSRM',\n", + " 'noaa-goes16/ABI-L2-FDCC',\n", + " 'noaa-goes16/ABI-L2-FDCF',\n", + " 'noaa-goes16/ABI-L2-FDCM',\n", + " 'noaa-goes16/ABI-L2-FSCC',\n", + " 'noaa-goes16/ABI-L2-FSCF',\n", + " 'noaa-goes16/ABI-L2-FSCM',\n", + " 'noaa-goes16/ABI-L2-LSAC',\n", + " 'noaa-goes16/ABI-L2-LSAF',\n", + " 'noaa-goes16/ABI-L2-LSAM',\n", + " 'noaa-goes16/ABI-L2-LST2KMF',\n", + " 'noaa-goes16/ABI-L2-LSTC',\n", + " 'noaa-goes16/ABI-L2-LSTF',\n", + " 'noaa-goes16/ABI-L2-LSTM',\n", + " 'noaa-goes16/ABI-L2-LVMPC',\n", + " 'noaa-goes16/ABI-L2-LVMPF',\n", + " 'noaa-goes16/ABI-L2-LVMPM',\n", + " 'noaa-goes16/ABI-L2-LVTPC',\n", + " 'noaa-goes16/ABI-L2-LVTPF',\n", + " 'noaa-goes16/ABI-L2-LVTPM',\n", + " 'noaa-goes16/ABI-L2-MCMIPC',\n", + " 'noaa-goes16/ABI-L2-MCMIPF',\n", + " 'noaa-goes16/ABI-L2-MCMIPM',\n", + " 'noaa-goes16/ABI-L2-RRQPEF',\n", + " 'noaa-goes16/ABI-L2-RSRC',\n", + " 'noaa-goes16/ABI-L2-RSRF',\n", + " 'noaa-goes16/ABI-L2-SSTF',\n", + " 'noaa-goes16/ABI-L2-TPWC',\n", + " 'noaa-goes16/ABI-L2-TPWF',\n", + " 'noaa-goes16/ABI-L2-TPWM',\n", + " 'noaa-goes16/ABI-L2-VAAF',\n", + " 'noaa-goes16/Beginners_Guide_to_GOES-R_Series_Data.pdf',\n", + " 'noaa-goes16/EXIS-L1b-SFEU',\n", + " 'noaa-goes16/EXIS-L1b-SFXR',\n", + " 'noaa-goes16/GLM-L2-LCFA',\n", + " 'noaa-goes16/MAG-L1b-GEOF',\n", + " 'noaa-goes16/SEIS-L1b-EHIS',\n", + " 'noaa-goes16/SEIS-L1b-MPSH',\n", + " 'noaa-goes16/SEIS-L1b-MPSL',\n", + " 'noaa-goes16/SEIS-L1b-SGPS',\n", + " 'noaa-goes16/SUVI-L1b-Fe093',\n", + " 'noaa-goes16/SUVI-L1b-Fe131',\n", + " 'noaa-goes16/SUVI-L1b-Fe171',\n", + " 'noaa-goes16/SUVI-L1b-Fe195',\n", + " 'noaa-goes16/SUVI-L1b-Fe284',\n", + " 'noaa-goes16/SUVI-L1b-He303',\n", + " 'noaa-goes16/Version1.1_Beginners_Guide_to_GOES-R_Series_Data.pdf',\n", + " 'noaa-goes16/index.html']" + ] + }, + "metadata": {}, + "execution_count": 6 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "Choose a date and space of interest. Make the map box bigger than the databox" + ], + "metadata": { + "id": "oPGYrePeXczE" + } + }, + { + "cell_type": "code", + "source": [ + "date = pd.to_datetime('2023-03-08T17:00:00+0000')\n", + "mapbbox_lonlat = (-90, 25, -75, 40)\n", + "bbox_lonlat = (-85.5, 31, -83, 33)" + ], + "metadata": { + "id": "ITraOvRbyR4D" + }, + "execution_count": 8, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "# AOD Example Plot" + ], + "metadata": { + "id": "CZBhie6kiM37" + } + }, + { + "cell_type": "code", + "source": [ + "aodpaths = awsfs.ls(f'noaa-goes16/ABI-L2-AODC/{date:%Y/%j/%H}')\n", + "aodpaths" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "CVXZw6eces5w", + "outputId": "3587610b-9469-486d-c8a6-6a1a20acd862" + }, + "execution_count": 9, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "['noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671711171_e20230671713544_c20230671716186.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671716171_e20230671718544_c20230671721268.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671721171_e20230671723544_c20230671726328.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671726171_e20230671728544_c20230671731228.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671731171_e20230671733544_c20230671736300.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671736171_e20230671738544_c20230671741168.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671741171_e20230671743544_c20230671746046.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671746171_e20230671748544_c20230671751157.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671751171_e20230671753544_c20230671756102.nc',\n", + " 'noaa-goes16/ABI-L2-AODC/2023/067/17/OR_ABI-L2-AODC-M6_G16_s20230671756171_e20230671758544_c20230671801127.nc']" + ] + }, + "metadata": {}, + "execution_count": 9 + } + ] + }, + { + "cell_type": "code", + "source": [ + "fo = awsfs.open(aodpaths[1])" + ], + "metadata": { + "id": "F034zidoe-Vf" + }, + "execution_count": 18, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "ds = xr.open_dataset(fo, engine='h5netcdf')\n", + "# Convert x/y from radians to x\n", + "h = ds['goes_imager_projection'].attrs['perspective_point_height']\n", + "ds.coords['x'] = ds['x'] * h\n", + "ds.coords['y'] = ds['y'] * h" + ], + "metadata": { + "id": "1jdxqqEFfyWO" + }, + "execution_count": 19, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "proj = pyproj.Proj(pyproj.CRS.from_cf(ds['goes_imager_projection'].attrs))\n", + "bbox_xy = proj(bbox_lonlat[0], bbox_lonlat[1])\n", + "bbox_xy += proj(bbox_lonlat[2], bbox_lonlat[3])\n", + "bbox_xy" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "2Eg43rt1hPUn", + "outputId": "513253ce-d19a-4e6f-9f72-768fc7a446a8" + }, + "execution_count": 23, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(-966105.8604694902, 3168995.264621943, -720198.6969389474, 3343396.6886203517)" + ] + }, + "metadata": {}, + "execution_count": 23 + } + ] + }, + { + "cell_type": "code", + "source": [ + "ds['DQF']" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 488 + }, + "id": "dRDzqiT37hZn", + "outputId": "d71b9e4f-c91c-43a8-b41d-8d1796212e50" + }, + "execution_count": 24, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "\n", + "array([[nan, nan, nan, ..., 3., 3., 3.],\n", + " [nan, nan, nan, ..., 3., 3., 3.],\n", + " [nan, nan, nan, ..., 3., 3., 3.],\n", + " ...,\n", + " [ 3., 3., 3., ..., 1., 1., 1.],\n", + " [ 3., 3., 3., ..., 1., 0., 1.],\n", + " [ 3., 3., 3., ..., 0., 0., 1.]], dtype=float32)\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float64 4.588e+06 ... 1.584e+06\n", + " * x (x) float64 -3.626e+06 ... 1.382e+06\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " sunglint_angle float32 ...\n", + " retrieval_local_zenith_angle float32 ...\n", + " quantitative_local_zenith_angle float32 ...\n", + " retrieval_solar_zenith_angle float32 ...\n", + " quantitative_solar_zenith_angle float32 ...\n", + " aod_product_wavelength float32 ...\n", + "Attributes: (12/13)\n", + " long_name: ABI L2+ Aerosol Optical Depth at 55...\n", + " standard_name: status_flag\n", + " valid_range: [0 3]\n", + " units: 1\n", + " grid_mapping: goes_imager_projection\n", + " cell_methods: sunglint_angle: point (no retrieval...\n", + " ... ...\n", + " flag_meanings: high_quality_retrieval_qf medium_qu...\n", + " number_of_qf_values: 4\n", + " percent_high_quality_retrieval_qf: 0.1216988\n", + " percent_medium_quality_retrieval_qf: 0.0666473\n", + " percent_low_quality_retrieval_qf: 0.099898\n", + " percent_no_retrieval_qf: 0.711756" + ], + "text/html": [ + "
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<xarray.DataArray 'DQF' (y: 1500, x: 2500)>\n",
+              "array([[nan, nan, nan, ...,  3.,  3.,  3.],\n",
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+              "    x_image                          float32 ...\n",
+              "    sunglint_angle                   float32 ...\n",
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+              "    retrieval_solar_zenith_angle     float32 ...\n",
+              "    quantitative_solar_zenith_angle  float32 ...\n",
+              "    aod_product_wavelength           float32 ...\n",
+              "Attributes: (12/13)\n",
+              "    long_name:                            ABI L2+ Aerosol Optical Depth at 55...\n",
+              "    standard_name:                        status_flag\n",
+              "    valid_range:                          [0 3]\n",
+              "    units:                                1\n",
+              "    grid_mapping:                         goes_imager_projection\n",
+              "    cell_methods:                         sunglint_angle: point (no retrieval...\n",
+              "    ...                                   ...\n",
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" + ] + }, + "metadata": {}, + "execution_count": 24 + } + ] + }, + { + "cell_type": "code", + "source": [ + "qm = ds['AOD'].where(ds['DQF'] <= 1).plot(vmin=0, vmax=0.5, cmap='viridis')\n", + "sb.to_crs(proj.srs).plot(facecolor='none', edgecolor='k', ax=qm.axes);" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 406 + }, + "id": "VCB9EPOFgA2W", + "outputId": "f55041ab-c253-4f6f-d22f-676f3dafd95a" + }, + "execution_count": 25, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "metadata": { + "id": "T0ss4aCfVaXK", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 423 + }, + "outputId": "57e78282-86c8-494f-8ba8-dc7d70d35bb8" + }, + "source": [ + "qm = ds['AOD'].where(ds['DQF'] <= 1).sel(\n", + " x=slice(bbox_xy[0], bbox_xy[2]),\n", + " y=slice(bbox_xy[3], bbox_xy[1])\n", + ").plot(vmin=0, vmax=0.5, cmap='viridis')\n", + "cb.clip(mapbbox_lonlat).to_crs(proj.srs).plot(\n", + " facecolor='none', edgecolor='k', linewidth=0.5, alpha=0.25, ax=qm.axes\n", + ")\n", + "sb.clip(mapbbox_lonlat).to_crs(proj.srs).plot(\n", + " facecolor='none', edgecolor='k', linewidth=0.5, alpha=0.25, ax=qm.axes\n", + ")" + ], + "execution_count": 34, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 34 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Color Example using L2 MCMIPC\n", + "\n", + "The L2 MCMIPC files have all color channels in a single file.\n", + "* Usefully, also on the same grid.\n", + "* Channel 1 and 3 were at 2x AODC\n", + "* Coarsened Channel 2 to match Channel " + ], + "metadata": { + "id": "mauysA_RiMuk" + } + }, + { + "cell_type": "code", + "source": [ + "mcmippaths = awsfs.ls(f'noaa-goes16/ABI-L2-MCMIPC/{date:%Y/%j/%H}')\n", + "mcmippaths" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "aDLnmvwvihnI", + "outputId": "8f3bdfdf-e8e8-4939-89eb-470b064082dd" + }, + "execution_count": 27, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "['noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671716171_e20230671718546_c20230671719066.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671721171_e20230671723550_c20230671724094.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671726171_e20230671728559_c20230671729062.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671731171_e20230671733550_c20230671734083.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671736171_e20230671738556_c20230671739082.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671741171_e20230671743548_c20230671744097.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671746171_e20230671748544_c20230671749062.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671751171_e20230671753556_c20230671754086.nc',\n", + " 'noaa-goes16/ABI-L2-MCMIPC/2023/067/17/OR_ABI-L2-MCMIPC-M6_G16_s20230671756171_e20230671758548_c20230671759067.nc']" + ] + }, + "metadata": {}, + "execution_count": 27 + } + ] + }, + { + "cell_type": "code", + "source": [ + "foc = awsfs.open(mcmippaths[0])\n", + "dsc = xr.open_dataset(foc, engine='h5netcdf')\n", + "# Convert x/y from radians to x\n", + "h = dsc['goes_imager_projection'].attrs['perspective_point_height']\n", + "dsc.coords['x'] = dsc['x'] * h\n", + "dsc.coords['y'] = dsc['y'] * h\n", + "dsc" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 204 + }, + "id": "M9juUGuTkX11", + "outputId": "8fe63f61-5a4c-443e-a180-c3b56db0c1ac" + }, + "execution_count": 28, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "\n", + "Dimensions: (y: 1500, x: 2500,\n", + " number_of_time_bounds: 2,\n", + " number_of_image_bounds: 2, band: 1)\n", + "Coordinates: (12/37)\n", + " t datetime64[ns] ...\n", + " * y (y) float64 4.588e+06 ... 1.584e+06\n", + " * x (x) float64 -3.626e+06 ... 1.382e+06\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + " band_wavelength_C01 (band) float32 ...\n", + " ... ...\n", + " band_id_C11 (band) int8 ...\n", + " band_id_C12 (band) int8 ...\n", + " band_id_C13 (band) int8 ...\n", + " band_id_C14 (band) int8 ...\n", + " band_id_C15 (band) int8 ...\n", + " band_id_C16 (band) int8 ...\n", + "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n", + " band\n", + "Data variables: (12/124)\n", + " CMI_C01 (y, x) float32 ...\n", + " DQF_C01 (y, x) float32 ...\n", + " CMI_C02 (y, x) float32 ...\n", + " DQF_C02 (y, x) float32 ...\n", + " CMI_C03 (y, x) float32 ...\n", + " DQF_C03 (y, x) float32 ...\n", + " ... ...\n", + " mean_brightness_temperature_C16 float32 ...\n", + " std_dev_brightness_temperature_C16 float32 ...\n", + " percent_uncorrectable_GRB_errors float32 ...\n", + " percent_uncorrectable_L0_errors float32 ...\n", + " dynamic_algorithm_input_data_container int32 ...\n", + " algorithm_product_version_container int32 ...\n", + "Attributes: (12/29)\n", + " naming_authority: gov.nesdis.noaa\n", + " Conventions: CF-1.7\n", + " Metadata_Conventions: Unidata Dataset Discovery v1.0\n", + " standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)\n", + " institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n", + " project: GOES\n", + " ... ...\n", + " date_created: 2023-03-08T17:19:06.6Z\n", + " time_coverage_start: 2023-03-08T17:16:17.1Z\n", + " time_coverage_end: 2023-03-08T17:18:54.6Z\n", + " timeline_id: ABI Mode 6\n", + " production_data_source: Realtime\n", + " id: 3de7fdfe-ba15-4887-9cea-69c433902434" + ], + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.Dataset>\n",
+              "Dimensions:                                 (y: 1500, x: 2500,\n",
+              "                                             number_of_time_bounds: 2,\n",
+              "                                             number_of_image_bounds: 2, band: 1)\n",
+              "Coordinates: (12/37)\n",
+              "    t                                       datetime64[ns] ...\n",
+              "  * y                                       (y) float64 4.588e+06 ... 1.584e+06\n",
+              "  * x                                       (x) float64 -3.626e+06 ... 1.382e+06\n",
+              "    y_image                                 float32 ...\n",
+              "    x_image                                 float32 ...\n",
+              "    band_wavelength_C01                     (band) float32 ...\n",
+              "    ...                                      ...\n",
+              "    band_id_C11                             (band) int8 ...\n",
+              "    band_id_C12                             (band) int8 ...\n",
+              "    band_id_C13                             (band) int8 ...\n",
+              "    band_id_C14                             (band) int8 ...\n",
+              "    band_id_C15                             (band) int8 ...\n",
+              "    band_id_C16                             (band) int8 ...\n",
+              "Dimensions without coordinates: number_of_time_bounds, number_of_image_bounds,\n",
+              "                                band\n",
+              "Data variables: (12/124)\n",
+              "    CMI_C01                                 (y, x) float32 ...\n",
+              "    DQF_C01                                 (y, x) float32 ...\n",
+              "    CMI_C02                                 (y, x) float32 ...\n",
+              "    DQF_C02                                 (y, x) float32 ...\n",
+              "    CMI_C03                                 (y, x) float32 ...\n",
+              "    DQF_C03                                 (y, x) float32 ...\n",
+              "    ...                                      ...\n",
+              "    mean_brightness_temperature_C16         float32 ...\n",
+              "    std_dev_brightness_temperature_C16      float32 ...\n",
+              "    percent_uncorrectable_GRB_errors        float32 ...\n",
+              "    percent_uncorrectable_L0_errors         float32 ...\n",
+              "    dynamic_algorithm_input_data_container  int32 ...\n",
+              "    algorithm_product_version_container     int32 ...\n",
+              "Attributes: (12/29)\n",
+              "    naming_authority:          gov.nesdis.noaa\n",
+              "    Conventions:               CF-1.7\n",
+              "    Metadata_Conventions:      Unidata Dataset Discovery v1.0\n",
+              "    standard_name_vocabulary:  CF Standard Name Table (v35, 20 July 2016)\n",
+              "    institution:               DOC/NOAA/NESDIS > U.S. Department of Commerce,...\n",
+              "    project:                   GOES\n",
+              "    ...                        ...\n",
+              "    date_created:              2023-03-08T17:19:06.6Z\n",
+              "    time_coverage_start:       2023-03-08T17:16:17.1Z\n",
+              "    time_coverage_end:         2023-03-08T17:18:54.6Z\n",
+              "    timeline_id:               ABI Mode 6\n",
+              "    production_data_source:    Realtime\n",
+              "    id:                        3de7fdfe-ba15-4887-9cea-69c433902434
" + ] + }, + "metadata": {}, + "execution_count": 28 + } + ] + }, + { + "cell_type": "code", + "source": [ + "proj = pyproj.Proj(pyproj.CRS.from_cf(dsc['goes_imager_projection'].attrs))\n", + "bbox_xy = proj(bbox_lonlat[0], bbox_lonlat[1])\n", + "bbox_xy += proj(bbox_lonlat[2], bbox_lonlat[3])\n", + "bbox_xy" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "MbO7l13_tlEH", + "outputId": "de403a6e-5ee2-4e75-eecf-d3b70fcba54a" + }, + "execution_count": 29, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(-966105.8604694902, 3168995.264621943, -720198.6969389474, 3343396.6886203517)" + ] + }, + "metadata": {}, + "execution_count": 29 + } + ] + }, + { + "cell_type": "code", + "source": [ + "chda = xr.concat(\n", + " [\n", + " da.sel(\n", + " x=slice(bbox_xy[0], bbox_xy[2]),\n", + " y=slice(bbox_xy[3], bbox_xy[1])\n", + " )\n", + " for da in [dsc.CMI_C02, dsc.CMI_C03, dsc.CMI_C01]\n", + " ],\n", + " dim='band'\n", + ").transpose('y', 'x', 'band')" + ], + "metadata": { + "id": "lDZRM5NAkdsv" + }, + "execution_count": 35, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "gamma = 1.8\n", + "coda = np.clip(chda, 0, 1)**(1 / gamma)\n", + "# Optionally apply PseudoGreen\n", + "coda[:, :, 1] = np.clip(0.45 * coda[:, :, 0] + 0.1 * coda[:, :, 1] + 0.45 * coda[:, :, 2], 0, 1)" + ], + "metadata": { + "id": "QnMze4_Pvy1q" + }, + "execution_count": 36, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots(dpi=144)\n", + "ax.pcolormesh(\n", + " coda.x, coda.y, coda.values\n", + ")\n", + "xlim = ax.get_xlim()\n", + "ylim = ax.get_ylim()\n", + "#tcno.drawstates()\n", + "cb.clip(mapbbox_lonlat).to_crs(proj.srs).plot(facecolor='none', edgecolor='k', ax=ax, alpha=0.25, linewidth=0.5)\n", + "sb.clip(mapbbox_lonlat).to_crs(proj.srs).plot(facecolor='none', edgecolor='k', ax=ax)\n", + "ax.set(xlim=xlim, ylim=ylim, aspect=1);" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 604 + }, + "id": "qpPeGx8inA9M", + "outputId": "002a4468-e217-452d-a647-d62fcaca1612" + }, + "execution_count": 37, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "# Color with L1b\n", + "\n", + "* Using native Channel 2 resolution\n", + "* Interpolating Channel 1 and 3 to Channel 2.\n", + "* Using extremely simplistic conversion to color" + ], + "metadata": { + "id": "daQG5AJC0Fs4" + } + }, + { + "cell_type": "code", + "source": [ + "radpaths = awsfs.ls(f'noaa-goes16/ABI-L1b-RadC/{date:%Y/%j/%H}')\n", + "radc01paths = [p for p in radpaths if 'C01' in p]\n", + "radc02paths = [p for p in radpaths if 'C02' in p]\n", + "radc03paths = [p for p in radpaths if 'C03' in p]" + ], + "metadata": { + "id": "e9dIMQwK0FEp" + }, + "execution_count": 38, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "foc1 = awsfs.open(radc01paths[0])\n", + "# First Channel 2 file was all masked, so got second\n", + "foc2 = awsfs.open(radc02paths[1])\n", + "foc3 = awsfs.open(radc03paths[2])" + ], + "metadata": { + "id": "LA3i2AcU1Wzl" + }, + "execution_count": 39, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "dsc1 = xr.open_dataset(foc1, engine='h5netcdf')\n", + "h = dsc1['goes_imager_projection'].attrs['perspective_point_height']\n", + "dsc1.coords['x'] = dsc1['x'] * h\n", + "dsc1.coords['y'] = dsc1['y'] * h\n", + "dsc2 = xr.open_dataset(foc2, engine='h5netcdf')\n", + "h = dsc2['goes_imager_projection'].attrs['perspective_point_height']\n", + "dsc2.coords['x'] = dsc2['x'] * h\n", + "dsc2.coords['y'] = dsc2['y'] * h\n", + "dsc3 = xr.open_dataset(foc3, engine='h5netcdf')\n", + "h = dsc3['goes_imager_projection'].attrs['perspective_point_height']\n", + "dsc3.coords['x'] = dsc3['x'] * h\n", + "dsc3.coords['y'] = dsc3['y'] * h\n" + ], + "metadata": { + "id": "UVlDvcVR1h02" + }, + "execution_count": 40, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "proj = pyproj.Proj(pyproj.CRS.from_cf(dsc1['goes_imager_projection'].attrs))\n", + "bbox_xy = proj(bbox_lonlat[0], bbox_lonlat[1])\n", + "bbox_xy += proj(bbox_lonlat[2], bbox_lonlat[3])\n", + "bbox_xy" + ], + "metadata": { + "id": "vC_DDNoccElh", + "outputId": "330265fd-6a4b-4269-8d40-8969e2db389a", + "colab": { + "base_uri": "https://localhost:8080/" + } + }, + "execution_count": 43, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(-966105.8604694902, 3168995.264621943, -720198.6969389474, 3343396.6886203517)" + ] + }, + "metadata": {}, + "execution_count": 43 + } + ] + }, + { + "cell_type": "code", + "source": [ + "refc = dsc2.Rad.sel(\n", + " x=slice(bbox_xy[0], bbox_xy[2]),\n", + " y=slice(bbox_xy[3], bbox_xy[1])\n", + ")\n", + "# All values are really between 0 and 1000, so normalizing by 1000\n", + "# Channel 2 has twice the bin-width, so divide by 2000\n", + "rgb = xr.concat([refc / 1000, dsc3.Rad.interp_like(refc) / 1000, dsc1.Rad.interp_like(refc) / 1000], dim='band').transpose('y', 'x', 'band')" + ], + "metadata": { + "id": "TAswoqFd30UW" + }, + "execution_count": 44, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "gamma = 2.2\n", + "coda = np.clip(rgb, 0, 1)**(1 / gamma)\n", + "coda[:, :, 1] = np.clip(coda[:, :, 0] * 0.45 + coda[:, :, 1] * 0.1 + coda[:, :, 2] * 0.45, 0, 1)" + ], + "metadata": { + "id": "IZOjlYgi5vs-" + }, + "execution_count": 45, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "fig, ax = plt.subplots()\n", + "ax.pcolormesh(\n", + " coda.x, coda.y,\n", + " coda.transpose('y', 'x', 'band')\n", + ")\n", + "xlim = ax.get_xlim()\n", + "ylim = ax.get_ylim()\n", + "cb.query('STATEFP in (\"13\", \"01\", \"12\")').to_crs(proj.srs).plot(facecolor='none', edgecolor='k', ax=ax, alpha=0.25, linewidth=0.5)\n", + "sb.query('STATEFP in (\"13\", \"01\", \"12\")').to_crs(proj.srs).plot(facecolor='none', edgecolor='k', ax=ax, alpha=0.25, linewidth=1)\n", + "#ax.set(xlim=xlim, ylim=ylim);\n", + "ax.set(xlim=(-0.95e6, -.85e6), ylim=(3.26e6, 3.32e6));\n", + "# Add custom dots\n", + "ax.plot(*proj(-85, 32.5), marker='o', markeredgecolor='blue', markerfacecolor='none', alpha=1)\n", + "ax.plot(*proj(-84.65, 32.5), marker='o', markeredgecolor='red', markerfacecolor='none', alpha=1)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 390 + }, + "id": "cpxPZWnv2Kos", + "outputId": "68f06a3c-bc52-4c81-ddbc-c7230eb6b989" + }, + "execution_count": 46, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "[]" + ] + }, + "metadata": {}, + "execution_count": 46 + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
" + ], + "image/png": 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\n" + }, + "metadata": {} + } + ] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "cvUWAgfGZv4U" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/notebooks/GOES16/index.ipynb b/notebooks/GOES16/index.ipynb new file mode 100644 index 00000000..b216f5d3 --- /dev/null +++ b/notebooks/GOES16/index.ipynb @@ -0,0 +1,1527 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "GOES-16: True Color Recipe\n", + "==========================\n", + "By: [Brian Blaylock](http://home.chpc.utah.edu/~u0553130/Brian_Blaylock/home.html)\n", + "with help from Julien Chastang (UCAR-Unidata).\n", + "\n", + "Additional notebooks analyzing GOES-16 and other data can be found in [Brian's\n", + "GitHub repository](https://github.com/blaylockbk/pyBKB_v3/).\n", + "\n", + "This notebook shows how to make a true color image from the GOES-16\n", + "Advanced Baseline Imager (ABI) level 2 data. We will plot the image with\n", + "matplotlib and Cartopy. The methods shown here are stitched together from the\n", + "following online resources:\n", + "\n", + "- [**CIMSS True Color RGB Quick Guide**](http://cimss.ssec.wisc.edu/goes/OCLOFactSheetPDFs/ABIQuickGuide_CIMSSRGB_v2.pdf)\n", + "- [ABI Bands Quick Information Guides](https://www.goes-r.gov/education/ABI-bands-quick-info.html)\n", + "- [Open Commons Consortium](http://edc.occ-data.org/goes16/python/)\n", + "- [GeoNetCast Blog](https://geonetcast.wordpress.com/2017/07/25/geonetclass-manipulating-goes-16-data-with-python-part-vi/)\n", + "- [Proj documentation](https://proj4.org/operations/projections/geos.html?highlight=geostationary)\n", + "\n", + "True color images are an RGB composite of the following three channels:\n", + "\n", + "| --| Wavelength | Channel | Description |\n", + "|----------|--------------|---------|---------------|\n", + "| **Red** | 0.64 µm | 2 | Red Visible |\n", + "| **Green**| 0.86 µm | 3 | Veggie Near-IR|\n", + "| **Blue** | 0.47 µm | 1 | Blue Visible |\n", + "\n", + "For this demo, we use the **Level 2 Multichannel formated data** (ABI-L2-MCMIP)\n", + "for the CONUS domain. This file contains all sixteen channels on the ABI fixed\n", + "grid (~2 km grid spacing).\n", + "\n", + "GOES-16 data is downloaded from Unidata, but you may also\n", + "download GOES-16 or 17 files from NOAA's GOES archive on [Amazon S3](https://aws.amazon.com/public-datasets/goes/).\n", + "I created a [web interface](http://home.chpc.utah.edu/~u0553130/Brian_Blaylock/cgi-bin/goes16_download.cgi?source=aws&satellite=noaa-goes16&domain=C&product=ABI-L2-MCMIP)\n", + "to easily download files from the Amazon archive. For scripted or bulk\n", + "downloads, you should use `rclone` or `AWS CLI`. You may also download files\n", + "from the [Environmental Data Commons](http://edc.occ-data.org/goes16/getdata/)\n", + "and [NOAA\n", + "CLASS](https://www.avl.class.noaa.gov/saa/products/search?sub_id=0&datatype_family=GRABIPRD&submit.x=25&submit.y=9).\n", + "\n", + "File names have the following format...\n", + "\n", + "`OR_ABI-L2-MCMIPC-M3_G16_s20181781922189_e20181781924562_c20181781925075.nc`\n", + "\n", + "`OR` - Indicates the system is operational\n", + "\n", + "`ABI` - Instrument type\n", + "\n", + "`L2` - Level 2 Data\n", + "\n", + "`MCMIP` - Multichannel Cloud and Moisture Imagery products\n", + "\n", + "`c` - CONUS file (created every 5 minutes).\n", + "\n", + "`M3` - Scan mode\n", + "\n", + "`G16` - GOES-16\n", + "\n", + "`sYYYYJJJHHMMSSZ` - Scan start: 4 digit year, 3 digit day of year (Julian day), hour, minute, second, tenth second\n", + "\n", + "`eYYYYJJJHHMMSSZ` - Scan end\n", + "\n", + "`cYYYYJJJHHMMSSZ` - File Creation\n", + "`.nc` - NetCDF file extension" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "First, import the libraries we will use\n", + "---------------------------------------" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "from datetime import datetime\n", + "\n", + "import cartopy.crs as ccrs\n", + "import matplotlib.pyplot as plt\n", + "import metpy # noqa: F401\n", + "import numpy as np\n", + "import xarray" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Open the GOES-16 NetCDF File\n", + "----------------------------\n", + "\n", + "Open the file with xarray.\n", + "The opened file is assigned to \"C\" for the CONUS domain." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Error:curl error: Problem with the SSL CA cert (path? access rights?)\n", + "curl error details: \n", + "Warning:oc_open: Could not read url\n" + ] + }, + { + "ename": "OSError", + "evalue": "[Errno -68] NetCDF: I/O failure: 'https://ramadda.scigw.unidata.ucar.edu/repository/opendap/4ef52e10-a7da-4405-bff4-e48f68bb6ba2/entry.das#fillmismatch'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/file_manager.py:210\u001b[0m, in \u001b[0;36mCachingFileManager._acquire_with_cache_info\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m 209\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 210\u001b[0m file \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_cache\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_key\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 211\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/lru_cache.py:56\u001b[0m, in \u001b[0;36mLRUCache.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 55\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_lock:\n\u001b[0;32m---> 56\u001b[0m value \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_cache\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m 57\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_cache\u001b[38;5;241m.\u001b[39mmove_to_end(key)\n", + "\u001b[0;31mKeyError\u001b[0m: [, ('https://ramadda.scigw.unidata.ucar.edu/repository/opendap/4ef52e10-a7da-4405-bff4-e48f68bb6ba2/entry.das#fillmismatch',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False)), 'c45260cb-08d9-4654-ba28-407559c94ae2']", + "\nDuring handling of the above exception, another exception occurred:\n", + "\u001b[0;31mOSError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[2], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m FILE \u001b[38;5;241m=\u001b[39m (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mhttps://ramadda.scigw.unidata.ucar.edu/repository/opendap\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m/4ef52e10-a7da-4405-bff4-e48f68bb6ba2/entry.das#fillmismatch\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m----> 3\u001b[0m C \u001b[38;5;241m=\u001b[39m \u001b[43mxarray\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mFILE\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/api.py:526\u001b[0m, in \u001b[0;36mopen_dataset\u001b[0;34m(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, inline_array, backend_kwargs, **kwargs)\u001b[0m\n\u001b[1;32m 514\u001b[0m decoders \u001b[38;5;241m=\u001b[39m _resolve_decoders_kwargs(\n\u001b[1;32m 515\u001b[0m decode_cf,\n\u001b[1;32m 516\u001b[0m open_backend_dataset_parameters\u001b[38;5;241m=\u001b[39mbackend\u001b[38;5;241m.\u001b[39mopen_dataset_parameters,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 522\u001b[0m decode_coords\u001b[38;5;241m=\u001b[39mdecode_coords,\n\u001b[1;32m 523\u001b[0m )\n\u001b[1;32m 525\u001b[0m overwrite_encoded_chunks \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124moverwrite_encoded_chunks\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m--> 526\u001b[0m backend_ds \u001b[38;5;241m=\u001b[39m \u001b[43mbackend\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 527\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 528\u001b[0m \u001b[43m \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 529\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mdecoders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 530\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 531\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 532\u001b[0m ds \u001b[38;5;241m=\u001b[39m _dataset_from_backend_dataset(\n\u001b[1;32m 533\u001b[0m backend_ds,\n\u001b[1;32m 534\u001b[0m filename_or_obj,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 542\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m 543\u001b[0m )\n\u001b[1;32m 544\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:577\u001b[0m, in \u001b[0;36mNetCDF4BackendEntrypoint.open_dataset\u001b[0;34m(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, lock, autoclose)\u001b[0m\n\u001b[1;32m 557\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mopen_dataset\u001b[39m(\n\u001b[1;32m 558\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 559\u001b[0m filename_or_obj,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 574\u001b[0m autoclose\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[1;32m 575\u001b[0m ):\n\u001b[1;32m 576\u001b[0m filename_or_obj \u001b[38;5;241m=\u001b[39m _normalize_path(filename_or_obj)\n\u001b[0;32m--> 577\u001b[0m store \u001b[38;5;241m=\u001b[39m \u001b[43mNetCDF4DataStore\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 578\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 579\u001b[0m \u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 580\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 581\u001b[0m \u001b[43m \u001b[49m\u001b[43mgroup\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 582\u001b[0m \u001b[43m \u001b[49m\u001b[43mclobber\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclobber\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 583\u001b[0m \u001b[43m \u001b[49m\u001b[43mdiskless\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdiskless\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 584\u001b[0m \u001b[43m \u001b[49m\u001b[43mpersist\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpersist\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 585\u001b[0m \u001b[43m \u001b[49m\u001b[43mlock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlock\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 586\u001b[0m \u001b[43m \u001b[49m\u001b[43mautoclose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mautoclose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 587\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 589\u001b[0m store_entrypoint \u001b[38;5;241m=\u001b[39m StoreBackendEntrypoint()\n\u001b[1;32m 590\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m close_on_error(store):\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:382\u001b[0m, in \u001b[0;36mNetCDF4DataStore.open\u001b[0;34m(cls, filename, mode, format, group, clobber, diskless, persist, lock, lock_maker, autoclose)\u001b[0m\n\u001b[1;32m 376\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mdict\u001b[39m(\n\u001b[1;32m 377\u001b[0m clobber\u001b[38;5;241m=\u001b[39mclobber, diskless\u001b[38;5;241m=\u001b[39mdiskless, persist\u001b[38;5;241m=\u001b[39mpersist, \u001b[38;5;28mformat\u001b[39m\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mformat\u001b[39m\n\u001b[1;32m 378\u001b[0m )\n\u001b[1;32m 379\u001b[0m manager \u001b[38;5;241m=\u001b[39m CachingFileManager(\n\u001b[1;32m 380\u001b[0m netCDF4\u001b[38;5;241m.\u001b[39mDataset, filename, mode\u001b[38;5;241m=\u001b[39mmode, kwargs\u001b[38;5;241m=\u001b[39mkwargs\n\u001b[1;32m 381\u001b[0m )\n\u001b[0;32m--> 382\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mmanager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgroup\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlock\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mlock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mautoclose\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mautoclose\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:329\u001b[0m, in \u001b[0;36mNetCDF4DataStore.__init__\u001b[0;34m(self, manager, group, mode, lock, autoclose)\u001b[0m\n\u001b[1;32m 327\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_group \u001b[38;5;241m=\u001b[39m group\n\u001b[1;32m 328\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m=\u001b[39m mode\n\u001b[0;32m--> 329\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mformat \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mds\u001b[49m\u001b[38;5;241m.\u001b[39mdata_model\n\u001b[1;32m 330\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_filename \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mds\u001b[38;5;241m.\u001b[39mfilepath()\n\u001b[1;32m 331\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_remote \u001b[38;5;241m=\u001b[39m is_remote_uri(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_filename)\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:391\u001b[0m, in \u001b[0;36mNetCDF4DataStore.ds\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 389\u001b[0m \u001b[38;5;129m@property\u001b[39m\n\u001b[1;32m 390\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mds\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m--> 391\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_acquire\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/netCDF4_.py:385\u001b[0m, in \u001b[0;36mNetCDF4DataStore._acquire\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m 384\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_acquire\u001b[39m(\u001b[38;5;28mself\u001b[39m, needs_lock\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[0;32m--> 385\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_manager\u001b[38;5;241m.\u001b[39macquire_context(needs_lock) \u001b[38;5;28;01mas\u001b[39;00m root:\n\u001b[1;32m 386\u001b[0m ds \u001b[38;5;241m=\u001b[39m _nc4_require_group(root, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_group, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode)\n\u001b[1;32m 387\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/contextlib.py:135\u001b[0m, in \u001b[0;36m_GeneratorContextManager.__enter__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 133\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwds, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfunc\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 135\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgen\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 136\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m:\n\u001b[1;32m 137\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgenerator didn\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mt yield\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/file_manager.py:198\u001b[0m, in \u001b[0;36mCachingFileManager.acquire_context\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m 195\u001b[0m \u001b[38;5;129m@contextlib\u001b[39m\u001b[38;5;241m.\u001b[39mcontextmanager\n\u001b[1;32m 196\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21macquire_context\u001b[39m(\u001b[38;5;28mself\u001b[39m, needs_lock\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[1;32m 197\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Context manager for acquiring a file.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 198\u001b[0m file, cached \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_acquire_with_cache_info\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneeds_lock\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 200\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m file\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/xarray/backends/file_manager.py:216\u001b[0m, in \u001b[0;36mCachingFileManager._acquire_with_cache_info\u001b[0;34m(self, needs_lock)\u001b[0m\n\u001b[1;32m 214\u001b[0m kwargs \u001b[38;5;241m=\u001b[39m kwargs\u001b[38;5;241m.\u001b[39mcopy()\n\u001b[1;32m 215\u001b[0m kwargs[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmode\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode\n\u001b[0;32m--> 216\u001b[0m file \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_opener\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 217\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mw\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 218\u001b[0m \u001b[38;5;66;03m# ensure file doesn't get overridden when opened again\u001b[39;00m\n\u001b[1;32m 219\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_mode \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124ma\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", + "File \u001b[0;32msrc/netCDF4/_netCDF4.pyx:2449\u001b[0m, in \u001b[0;36mnetCDF4._netCDF4.Dataset.__init__\u001b[0;34m()\u001b[0m\n", + "File \u001b[0;32msrc/netCDF4/_netCDF4.pyx:2012\u001b[0m, in \u001b[0;36mnetCDF4._netCDF4._ensure_nc_success\u001b[0;34m()\u001b[0m\n", + "\u001b[0;31mOSError\u001b[0m: [Errno -68] NetCDF: I/O failure: 'https://ramadda.scigw.unidata.ucar.edu/repository/opendap/4ef52e10-a7da-4405-bff4-e48f68bb6ba2/entry.das#fillmismatch'" + ] + } + ], + "source": [ + "FILE = ('https://ramadda.scigw.unidata.ucar.edu/repository/opendap'\n", + " '/4ef52e10-a7da-4405-bff4-e48f68bb6ba2/entry.das#fillmismatch')\n", + "C = xarray.open_dataset(FILE)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Date and Time Information\n", + "----------------------------\n", + "Each file represents the data collected during one scan sequence for the\n", + "domain. There are several different time stamps in this file, which are also\n", + "found in the file's name.\n", + "I'm not a fan of numpy datetime, so I convert it to a regular datetime" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Scan Start : 2018-10-10 14:32:20.300000\n", + "Scan midpoint : 2018-10-10 14:33:38.900000\n", + "Scan End : 2018-10-10 14:34:57.600000\n", + "File Created : 2018-10-10 14:35:08.800000\n", + "Scan Duration : 2.62 minutes\n" + ] + } + ], + "source": [ + "# Scan's start time, converted to datetime object\n", + "scan_start = datetime.strptime(C.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ')\n", + "\n", + "# Scan's end time, converted to datetime object\n", + "scan_end = datetime.strptime(C.time_coverage_end, '%Y-%m-%dT%H:%M:%S.%fZ')\n", + "\n", + "# File creation time, convert to datetime object\n", + "file_created = datetime.strptime(C.date_created, '%Y-%m-%dT%H:%M:%S.%fZ')\n", + "\n", + "# The 't' variable is the scan's midpoint time\n", + "midpoint = str(C['t'].data)[:-8]\n", + "scan_mid = datetime.strptime(midpoint, '%Y-%m-%dT%H:%M:%S.%f')\n", + "\n", + "print('Scan Start : {}'.format(scan_start))\n", + "print('Scan midpoint : {}'.format(scan_mid))\n", + "print('Scan End : {}'.format(scan_end))\n", + "print('File Created : {}'.format(file_created))\n", + "print('Scan Duration : {:.2f} minutes'.format((scan_end-scan_start).seconds/60))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "True Color RGB Recipe\n", + "---------------------\n", + "\n", + "Color images are a Red-Green-Blue (RGB) composite of three different\n", + "channels. To make a \"Natural True Color\" image we assign the following\n", + "channels as our R, G, and B values:\n", + "\n", + "| -- | RED | GREEN | BLUE |\n", + "|----------------------|-------------|----------------|--------------|\n", + "| **Name** | Red Visible | Near-IR Veggie | Blue Visible |\n", + "| **Wavelength** | 0.64 µm | 0.86 µm | 0.47 µm |\n", + "| **Channel** | 2 | 3 | 1 |\n", + "| **Units** | Reflectance | Reflectance | Reflectance |\n", + "| **Range of Values** | 0-1 | 0-1 | 0-1 |\n", + "| **Gamma Correction** | 2.2 | 2.2 | 2.2 |\n", + "\n", + "\n", + "Some important details to know about...\n", + "\n", + "**Value Range**: The data units of channel 1, 2, and 3 are in reflectance and\n", + "have a range of values between 0 and 1. RGB values must also be between 0 and\n", + "1.\n", + "\n", + "**Gamma Correction**: A gamma correction is applied to control the brightness\n", + "and make the image not look too dark.\n", + "`corrected_value = value^(1/gamma)`.\n", + "Most displays have a decoding gamma of 2.2. Read more about gamma correction\n", + "at the following links...\n", + "[source1](https://en.wikipedia.org/wiki/Gamma_correction) and\n", + "[source2](https://www.cambridgeincolour.com/tutorials/gamma-correction.htm)).\n", + "\n", + "**True Green**: The GREEN \"veggie\" channel on GOES-16 does not measure\n", + "visible green light. Instead, it measures a near-infrared band sensitive to\n", + "chlorophyll. We could use that channel in place of green, but it would make\n", + "the green in our image appear too vibrant. Instead, we will tone-down the\n", + "green channel by interpolating the value to simulate a natural green color.\n", + "\n", + " TrueGreen = (0.45*RED) + (0.1*GREEN) + (0.45*BLUE)\n", + "\n", + "Now we can begin putting the pieces together..." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ABI band 2 central wavelength is 0.64 um\n", + "ABI band 3 central wavelength is 0.87 um\n", + "ABI band 1 central wavelength is 0.47 um\n" + ] + } + ], + "source": [ + "# Confirm that each band is the wavelength we are interested in\n", + "for band in [2, 3, 1]:\n", + " print('{} is {:.2f} {}'.format(\n", + " C['band_wavelength_C{:02d}'.format(band)].long_name,\n", + " float(C['band_wavelength_C{:02d}'.format(band)][0]),\n", + " C['band_wavelength_C{:02d}'.format(band)].units))" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# Load the three channels into appropriate R, G, and B variables\n", + "R = C['CMI_C02'].data\n", + "G = C['CMI_C03'].data\n", + "B = C['CMI_C01'].data" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# Apply range limits for each channel. RGB values must be between 0 and 1\n", + "R = np.clip(R, 0, 1)\n", + "G = np.clip(G, 0, 1)\n", + "B = np.clip(B, 0, 1)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# Apply a gamma correction to the image to correct ABI detector brightness\n", + "gamma = 2.2\n", + "R = np.power(R, 1/gamma)\n", + "G = np.power(G, 1/gamma)\n", + "B = np.power(B, 1/gamma)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# Calculate the \"True\" Green\n", + "G_true = 0.45 * R + 0.1 * G + 0.45 * B\n", + "G_true = np.clip(G_true, 0, 1) # apply limits again, just in case." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Simple Image\n", + "-----------------\n", + "\n", + "Use `plt.imshow` to get a quick look at the channels and RGB composite we\n", + "created.\n", + "\n", + "First, plot each channel individually. The deeper the color means the\n", + "satellite is observing more light in that channel. Clouds appear white because\n", + "they reflect lots of red, green, and blue light. Notice that the land reflects\n", + "a lot of \"green\" in the veggie channel because this channel is sensitive to\n", + "the chlorophyll." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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+JsYo131Zv4+RMcj6tYLexen32so1sqr0dJ3tX6EppTvXtIuJR7eO3kcZ5uT9cWH+lFxDMgQsYTVYrQhJnjdKQefkuw0uEJOcMxcixihqo9Fa0bvA6CKV1Ry3Fb0L8zWYN+CDfG7a/5JvZf/zdy3H78VISfan/C7Pdjkne8PV/FyXzxuj3vfZkI9BjPl5tzcmltdAa5XzT6G1ysN1RW01Nn/nsq8ARqspj5tK48N8L2lqc+c4tZXhZFFhlOxXSImbnSMm2A2eyuppfPP6+YK2Upy0Fh8Sz7aO3RiprcKFxHFjWFSaxmo2Y0AruO0DNzvHV9695ey44cFpy6K2vPV4zZPnO8Yx4H2YjuEX/5m/6UPz72MNFtPmMk3gpQDF9AJQ9A6ih/AiUHQQA8mNsqzPgDLkZcZRQEK9hKqGsYfry3md3sv73VZemwBVEJCojQBDpeWq9o47+xqjrDd4AYQhzP9B1lEGW97PQFEpASAhb8e5+WeMpN2O2I3oppLFK4NeLQQAbbak0QsoOlqB9yhrSD4Qe48yihQkKZSRi3DKyjgDNGACX8RE2hvVTq/nwXlygTgI8NSNRdcWtJqBaAac5S5UtptcBqK1QVeWtHfjwuX9iIngPc5FINAsLFiDipB8kHWhBYgGOe6pd9iXjkkxEdY9qraYZY166T4MAxwdAaDffBNOzufryXvS7Q28/joAZrslfusd9Cdel/NzfQ2vvwG3V6SvflVeOz9HvfbGfB77jvTNt+RcPnvG8GvfxD3fMHQee+rw7zzB3NxgTxcs7q1YALtn2zxP8PGrHd75zbRTMvAT8Fd+LwPRNAHDIK/HMC0bUiDkwekYR0IMDGFgCIMMhIxBK8NCW571z0gpMUaHj57WNKzHNQqFTzKg6HyHj57GNAJg8x6GGCZAK/ubqE2Nj3kgkiIu+umhZLXBarn9uZAHyilhtaG1DUMY0Uqu1cpUDGHEx8DG9WzzQDQBlTGcNi1GGW6GHZ33HNU1Z+2SGAXoAPTey8A0Dyw1M/Ar+1vee/Fhr/YGtGVAmPK6XIx0zqGUYllZKi2Dx33g5+M8ADdKvv8YZLBSaU1r7bReYAKKMSZCmAdzdV1RWYPKy4S8bxoZ3CQSQwjcWywE8I0jlTEsjeGl1TE+epa2JZH47PlrvLp6IMc/Xx+bccebJzLIvR7WfPXqET9571VcDOx8z732lJ3reXv9HB8jZ23Lw9U9rDa8unoZqw1fvfkaIQXeWT/h5x99k8c3a4Z+oKksz3Y7fuXZV3lpteLytAfg+fV6mij4OMaUgykJOMwgrEzaxAkkSp4VkOijn14voDFMEyUen5dXSlHrGqsNYxjZuG3+XMQnj0LRezlWLudSSBGrjYDEvF9KqQkkyu4KULTK5vXoaZKmADGjDSZPsob8ncrrjanydixj9NT5p4+erRvpnKPO993KGFZVhVKKzTgy5Bw8qRtCilTG4GKk955K6+n6LpMYJV7Mv3KvKLlTfi8A2yg95VfvPUZrWmumHCy5H5KAsDkH5fUxhCkHqz1QBzmf9nLQ50nPuq7A6AmE6jyJo/e3FQLHdQ3A1jkqrVlWFS8tjxmDY1ktAPjk6TEn9ZFMrkW5V6/HHcuqBeC87fjmzTM+efoSMQVuhy1H1ZL1uONr12/jYuT+4pjXjh9MEwlDGHlv+4QQI093l/z65XOeb3eMo6NvGt6+veGq7zhpGk5Wsh83m51cMx/DZ2Dn5CqIaf/6yJN0BQSG8nMGiT7OQNHFiIvyXsigJqQZ/FmtAM0YI0Oal3MZLKaU8AWoJnAxsKrlGnsRJAJ3nh1GKQLkyQSmdcdUQE2+bvKx1zIXT2s1MUFlFL2LGK1w+ft0Y2D0gcrIBIPWisYalILeBUJItJVh0RiZkNEKH2F0EWvUdFx0fobt73/5vimBnyZs7gLD8pn8KJNj7yNaKyqrMVrlyaYZLPog01YKJjLDhUiMCWMU1uo7Y7CUZhDqXMQ5maypa5MBpZxHiFg0eg+Ijj5ytpKxRT8GjFbUleFsWeNjpK3kvvXaWcOyMvm6knOwHgIvHTfElOhay9PbngenC1JK3PaeVV2zHQLfuOzxIXKyrHnlpJ7OYe8jTzduAp3vXu7Y7EbGMTK2lme3PbU1NJVhtapYrSrW61Gum++Qfx9bsDgxiikBGXztA8UQ7oLEcJdRTBNAdHnZ8j8JaFAZyrvM+N1cQ9/LNpSWZbXKQC4DvBBI44AqjOLRaWbStFy5KZCnImZwut3I9pyT16tKvkvfy+9dB207s5xVNV+pXSevey/r6HsBirWdGbOYSONI7AWs6kWNamr5fiFM4E+3dmIiUxAGUCkFRs1MXviAAVMBkgVY7s8ABfmcPV1glg2xG2V5mBlEMqP5vhMsQJeQiD7OIDTvy/4NommMzBhpjbIa3VYZnFayrAvo2qKsIfYj+ngFiwUmJTme19ekp89Q1sgkweuvwxufgtML2UCeWFCNPLzIEwzmNw8C3PfB/NChLl4iPXkP1S5kQkBrMFY+pzXxi79G99Un7G56RhdZtIawHajuHaHOzqBtWTx8AOs1+uuPISZ2j2+/1xT5oca3A4phj8koLN7+64XBSCTGMORBWZjA49bvsMrIjHnyVLrieX/J1u1QSmGV5FecmJMMkEhs/DYPIEdqXU+Dzf3lrLYT69KHARcDgx+x2mKNIaTIzvXUpmIzdhzVC1z0GGVoTE1IAaMMnetxMTBGz+BHdn6YgOKQGbuY0jR4BTiqaxpj0CiGGKZZ6NoYQozTALGArDJgjXlAKd/7LsM4vZ4H5iCEfRmInLUtq6pil1UIGmELK63zzHKYPlMi5oGEgLw9EDrNqM5srbWSfzrndpMHxOU7hZRojKG1lp33nLUtS1vlgXrFeui47LYYpei953MXr/PbX/6rOG8uUCjGKKxvawRIPu2fsB43/My9L3DanFLparomdn6Hi45Hu8c0puGoOkIpxcK0XI83aKX5c+/9Kr/y9Cnr2y3j6KlriwuB06bh4eqCVbXkEycPuepv+VX7iJASj64/XvkHcw7GzPgVYDZNzOzlm09uYgz3gWIBh/ssv7DKo9z/E/i8rq3fTeeibFehBDjmiZZIYoiO2sj5WNnVHeUJyP1CK0OIjkiZHBoZgxeWWxsiid4P1Lal8wML20zqgspU0z50fiClSOdlHZ13E1B0e9ds7z19vv6XVUWdGTe390wrkyKuMPtKzQqZkoPTAHVmGWFWBRSgCRBVnK7/k6ZhWVX03k/rLIycfG7+fBmTlRwskz77ExYxJmKcVT1VZTPLKGBzWVUYrWmMme4ddWYMe+/z/rTTBNj1sOXpbo3VmiF4Xj9+wCurhxxVqzwZF2SC7UQmoV30hOj5qXuearqf5ommOHLRnvK8v6IxNY2RwapRwvIrFL92+Q5fvbpiu+nwPlA3FVvnuFgsOG8XLGzDw9UJW9fzNXtFTInn6+33kh4/9NiNcqZ9iBOIKYP6O4xhiO8DjDHJ51xhFCeQlvIzM4Mi9ib9fGAMM/vnQkIrMkgrYBVckMnREBMnjZmukXK/BnkGBOR6G0Kk97IvAEYpjIIhJGoFY0jURpEygKztDCB7l9lQnxhcZPQCFK3WGSxlQOXjlGuV0VQ2T2js5Utd6Qzc5HpVSk1KlQmQfwhgKa8nZmBbJtljTCwaS1sbBhfmiZOYyEPQCVSX5/HE/GuVuZ04sYyyvbtj0LrWcnyMFhbVGoxWWKOma6LKijYXIovasqgNKYE1ipud46YbMUrhfOSl44az1rKstQzV8/l9OedfCfdwkYH+fN8YQ+RzD5Zcd57W6omjMlplVRS887zj8dWO7dbhXKBtLYMLLBrLsrFUVnN+VNONgWeVIcTE7e3w7dLh4wcW74DEVNjEdJdNzCBRJKYvyE5jEKDoxrxc/tw4ZF47M3UhyJVwey3L7jYZ9ClhGTNwSOs8iCjgMiXSMEAIcqGfXsyMZwFo5QrzTpjJcRTQApOMdFrm+FiAZNlGYR+9l8/FCLsdYd3JMkYTx1mamsZAGORBblaZUXQFMO/JPDNbl1KamD9V5Jt7Es4kV/5849kDiirPiBSAVgBeChF/vSV0TpjFfRmAVsTeC7tZZq+shpjQyxqMgjEKU6jUtG/J5xuwi9hKE0NiHAeM1VS9Q+WHsKoNuq0IWY5LiPinN9iLAHUNux3j42vS6NGLGrNq0Le3pK9/BfXmZwXw2wpUnc/P3qSCMTKJYK2AQmPg+FTO/fGpLD/08OyxXCfGwNe+Rho91b0jjpc128dr2rMFZlETdiPuS9/AHreY0xVoTfPJB4zvPKc9W3yfGfODjSI7LbEPFMsg1SefB6syiH1Rclr+F6bAR0/ve4w2mV2S76qVZuO2hLjmZrzFKINRhp3fscqDmEf9E4zSGGWIec7UBZdnHxOtbSc5W23qO9I2GRQ7ej/Q2mZiPzbjFpXlc+ftCUOWqKLARYeLnhhlgJpIrMeO675HITO0vffy0M+/d84RgeO65qReZBbSTwPSMqCMmbEozJ/OMtHyMDVamAqdElEVWe08wCgD9JBnqvflZddDz3ac2RatFPmOwRACIcT8AEwYY0gpsWrq6fuEnMs6TyKllKVVzqONJsXELv8+VlYe9FkWVwbhQ1ZNPNvtJtC8c44n2y0uRpZVxVkr4ODXr7/M585+gqPqWBjcPOkAcFQd0+iG6/Gav/z8VxmD57w94ZXly5w352ilOW/OAehDz6PdI97dvotRhl9+8mt0zvHScsmysjx+fsPqaEFjLY82G37t+XNePT7mlaNjjDJ84f5Dvnr1bGI5Pg5RQKIw52kCinMelokXP8lO/d7PMnGzLz2NKTLGcQJ/WmmZXFGwdRtc9HRerhitNC46Ki3PrO2wnvYt5v0ZwjgBoKNK1BpFipry74mET0EmXcIMMAXcDags9z5pjnB7cu+QAjFGmeTJublxPethyPunGMPMUBbWEGBV16yqGhfvspglZwogLAyf0Xp6HWQgnXL+afbkqMhg7UXGfproSZHrvqf3HrvH9JVwMU45CJI3KSUWtRxjH+P0fFR7IDaESAxRcjAl3Jhz0IdZDpcnaoZhoMq5/XS346yNeQJn4NFmg4vy93FdcztseGfziNePXmFpF5MUX75bnEGH0mz9Dq00VlmsNiytMB2ragnAGEauhhvW4w6jNF+9fpcxBC7altZaLm83HC3l951zfPHZU06ahtOmwWjNm2dnfOv2ltWi+V5T5YcSnUt5yJMyo/gBstMPAYn7/8cYJ8lnTAIaU5pLOnweT/qYGEOg9zMg9yFNrJ8LcZrH35fDFrB22s55tR9lbn87RlxImL1Lsvcps4iK40ZP68sVQtPfQ1ai7QZPN5bSDe5MwvggjChAWwujWD4vDCITSCzfoUinjVbC+pXrLX/nmJnHAgwLyLNaWLx92Wk5V+tOgJExmhfSjxBSzr95Oykl6trmYXeacrPkX4yRGMG5OElYxzFgrWa0YXpWGqNoKoMPAZtB9/V2JMSKymq6MXK9HfAhUVtNWxs2Q+CJgpePK9pKYzRUubhE5OAzqBXQq6i1DNUrI8d3UcmY1cXEdefpRmE/37sR1vF4WVNVhpubnuWyoq4MzkceX3dynjI7fe+44XI9sFzeBaovxscKLKb18xd44A+QnYY9oFhqD/04y04LE1iYRpDfY5ApGRBQaJC6RO+EtQORlkJmi5TULu7vT6kfTMJOJu9RMcH9B7LOvhOWyY2wkQdsKgxiSpm5zGxX08zsoTHyuRgFKA6D/A+BsOlIPgqjVhni6EkhoWuDu9wKo2aEbdPLFpQi7nqRox4vCGv5/AT4ShbF/DhPSQBiSsRxHmi/OFusjAC82DliBnYpJaILjLsRm5MphigSWa2IoxcWNCV5zQdCYTYBvxmmm0EMKZeFKmK4qz3XStgWnWdy3BgA0WSblEhjQC8qUjeSxoBf97irDdoaAcAuUL9yhnrpPurTn5W6025L+vpX4PlzOfanp6iqkvO1Xst5OD5GPXgIFy/JOb3ZitT05kqAfAH1Z2eok1NwI+mVVzCrW8x2S/fl99BG4dZZxnW1xRy3hHy+wmYg7AbCZsBt+u8jY36w0fltmmRkFDnWPDidAGKpSdqTmsa9AWr5zBCGSUKaSPS+J5EwypKIGSh6utCjlZ6kpQu7QKFYu/Wd/fN7QHDjdlRZRnp/cZ8xjPShp9J2Yg4r4+nDSGPlJrhz/cR2rarFBBx1qSVKARdiZjAGfAzcDFJzWBtDY4wAq5RoM/hYVHKLX1UVJ3nws+0dQ2bYrvv+DgNS2MTCBkRmedO+PE7DNGCVENDZey91fBlYOufZdQPWmokVrHLt7+A9lTHEGKmswQdwLkwPxU0/TA/PkGsLy0My7d0rtNaEGFBaYYzGOU+ppbLWsA2R2sqx8TFy0/XUlaW1ZpLqffL0lNeP7/NT9z9HaxY86Z7wx9/+0zzdXRJJNKae2KXODyxty8PVBa+sHnJcHdP5jvd2j/jy9VenffIxMAbH/cU5580ZQxj59NnrnLY33PRrfvHxI7TW9N1IamG966lry9PdbgLJvffcDAO73Y8+/2APKJaaxD3ZabyTb1IHvA8SQwaH4X2sYqkllryEPCBCMWZ59RjkWWmUIZGodIVWWnJYzfVwRdYtvw8T43jWnE4ssVGGkAKd72Wg6XustkQigxdQaLWltbW873qph1VlEBj2cjCyGcepvrA2ZmLnrdZcdd3EqLW5dlhrQzcODN5z2rbcvJCDZu/Z5orcM+deAX+FdSyAUSFsTEzCYroQJsDnfeCyH+cc1GmSa7sQsC/koPdzDm77YWIGXszBWTfH9JrSCmvNJA1XSpEqYaYaI7I/FyM3w8BV31FpI1LElHj56IiXlsd8+ux1Kl3R+4Fvrt/heXeDUZqT5ojaWDo/sB07Qooc10teWl5wUh8TU+Bm3DKEkdthOwH5kCIn9YqTZoULnteO7nFUb1kPHV+9ukJrza6XHLzpelZNzdY5GmPYOsfOOdbjSN+PP/iE+h7jTn1imoFIyMBkZhPvgkQX5mV8Vnz4FCegWOSnBSgVcFSAotQnzsNfk2vjQpTfw956QICg94mwk+1eLKuJyQPZ9z5PuG/HgNGgk2LIgK0yitYKsBm8TGrazLIJE5kYfcCHJDWHQeSkVusMXhPWKDa9x2bQ1FSatjIyUenkWbpqLdve40Oc9nt/IqXIQwtzW6S2SpU65ixDZZ7IGX2caghBnmnD4CdAJ9JSPYFAY9Teaynnn2xjGPxcR+njNAmaMsspEzJS7+h9ZvaNYhwLWISqMoSQqCqNj7Ke3eDZ9i6PWTU+RM6PGs6ybLQyUmf4aO247jzWaE5bQ6UVvY9sxogPkbbS3FtWnLQGFwQYjj5yufN0xfMjwVFjWDWaEOHeUUNbGbox0F3tpD6y96QEGzfStgKQba6b7F1gHANdt+eP8gHxsQCLE0ickiW9X3Ya4wwCP6A+MQU/AcapRrHIVVOuQ7SV/D6OuW5xmGsIlZ5ZzGKEszqWxO52Aur2is8nBnDohF1Seq5zXN8I4CzyxZRgt5PPFylqCLLOpczO4f28nPekcSTc9iijJull7B1hM6CbCn/TYRY1qslg8UjWE69vCeue6sEp/npLHPKM7V7hrrYCOnNV7iz9DPPMStKZQRwDKJGcxsHNhcCVodu6LFPTpHxDSzFiS5JZQxwcQXQTOB+nugSTZ0q1kt8d8p7PCVASvGjGIV8CUTTx1uo80M5FwMFAvuEoo+XY5Ie3AmEur65Iv/yLuMdXxG6cjok5bjHLZ6S2lfNRVajX34D7D+WaaRo5vyfnIkPVivTuO/Dee3Lu1mv5bFWBc6SbG/pvPGP7dJPJ6IRSeVa896TaMrx3TbjtGXYjdT0bhfwo4n0mNsWcYhqgzmAw7b22DxJDCrjops9Ncrco10hhKmJKjHHEZQONJFWnmekI2WQjsQ1bjmthf7Zux8btMGpmzVJKjMHl+sJhqp9SWnPTX9MYqcPqlZjRbPKst1GaxtS44Nm6HYuqRaMzyE3ZxMbTB89l12GzWURr7QQsllXFs92OVVWJqYbWnLcLlNI82625GQZeOz7m+W5Hn+8v+wY1VWZGJgYvMxT75hhJqWxyMMtdh8wAppRI1ggISgltdJ4FlQdhyNu01sgDP7P6ZYCZkoC++EIuppQIWd6ujSbmbZXXYpZVhRCw1hJDZIwRY0odRx6MG80qSwELs9p7z1evH/PV68c87zrG4CdjlIWtqIyhNQaTB+A/+/JDftP9n8FqS2PkHH3q5NMMoee93Xt84/ZbfPXqWwA87645qpc0pmYII8921/z65XMur9fTPaSEDPgib9/e0g0jQz9iKzvrlH5E8SKbGF+Une7VJ4pJjXtffeJUm1jyMu5JwjNgLNMPUj/sGbPxVJGklntAMcJpjdSv7VzPEO4O5kMUGeZgBHAW5h5gM27FfCiFzKhHOtejlcmGS9XE3i+sMEohRVyK7LwwkUMI3A7DxAKWHFyPI3VmrRfZNMlozUkj67nud9wMAy+vVsL27eVgkXhbre/kVpmo2Wfry3vFoComGUCX/BJvvA/PQWEdNC7/Xd6DMgAt5hVMbH9KiVhY/v0cDHMOjtERo7CNlO9jDVWeQCry1tZYqqw0UFl+e9Vv+eUnX+bRdkvn3AScj5uGhb1lWVW0tqE2Fa+tHnDRCpNf6xqlFEfV0TQh8N7mKe+snwNwW21oTE1tLGPwXPc7vnFzw9XtdvpeJYY8+fZou2EzCEisqh/tULT3pFnJkeWNe6Bxkp1+CEic6hXzsj7FbGQzK0MKUASyMiTlWsb370/BU22lSEnGVs6Xmj55r+zfkLdjlMqMJKyHSGXU9H3kO8bpfFdGahjHEGmzYY7PQK1zkTGP13aDl+tTi0maC5Fu9FRGsxukbrG2Is1c1BatYNt7toPn/Khm23sGN09QQX5GaJFrlmdgAYqzDFVNOVmWk/yJ0zPQWkPXOVKS8eIM8iLWzs8272N+Dqjpd63lM3P+ZVYvJkJIE0AszKXULKrMQIYJfMr3EbbRZFaxnL+6Mlgt58BoWdemd7zlAlebgd6FiT1e1JabytDUhrYyNEbx8nHDUS2TaEbLuKCxCpeBZucilxsZV24HgzUqy4Mj297z9Lbn9nbIPNceE+wjldFc70aGIdD3nqp6Pxv7YvzIweIdNpEiPc2y0xTn2sSpVtHPjGIBin7MYCvOn/HjXSCossnM2MuyLn8mz3SSIqAF+AUvbqc3l8JUei9AQOsZNNY1qqpExqi0gMYxz04vjwSAXT6f6w5LraK1TNMaq5Usn81r2O2EsXSesJX6v5TALmrCpidsBzDiDppGT9QKbTRm2UCMhNstyUmtYBrdBIhSiETnJhlp9FlCmk1hSuzXGKYh3jW5yQ8501aE3kFMLFbV5FYaY5qAoHOSkIuVJvqI94khg1abC6f9ELBW9N7DThK+SANADof3RZIRp5m2gr273tM2Bu8SMSTqNDAMsh/LZUVa1tN3iYPDXW5JIVJdrEguEHYy8NG11BPa0yX2NMBmi/r85+DBKzKp8N635Fy1C5Emey+M8/GxnNNHj3DvPMOvO5I8ce6Abq3le/S9Z3XSglFSXwqYo4ZFa4ljIGy+vV78hxXfTnY6mWhktnB/8BpyjUsBiSEzDuX9IQyTrFBnl1MfxeTGRT+5o5b1pJTwCMMxhJHT5oTr4WYyn2lNjdWW21EcMMUV07K0C6wyDGHARUcfBpbVgtrUPNk9Yzt2uBhorAxOpd5Rjv+qWuYaA9nGxnUMfpwGpGWweNI0bMeR676fZGu9l/orEyMnjTBi191uYkDGENg6h9FaahVzTREwSUj3C/yVUlN9k4uB3s9ueUXCBtDUFcMokzbtohaGzZdjKOfIOxmc6mVLCJEQAm4U0G5sruVyHp231+36iSlMe/vjs9QthDhJbkotxzCM1HUlNdMl70cZxDZtQ6xrQkpsRjmeTzZbYoysWineHzJwNUbT+0BrDTQtyXt+68uf4qfv/QZCCrx9+w5aaVrTsLBSW7pxW47rI37y3qd56+Ydvnb1jOuhZ5cZz7CXf8aIk51znsVSpMhl8N82NcYYQgiM5TnwI4i79cF3ZacF5IUU5kmaIjvNQDFMP8Ocn1HysoC3AgZjClKPlnzOQ8++MQ3MUuzG1KzdhuIgbLPypvMDRhkqY2lNzXF9lI/riMu5tchGRpf9zWQOVWoRrTYTs7aqRf7rguzLzvX0QdjznXMTC7GoKrbjyHocpwFRAXtWa1ZZCn07DNPA+YNysIAnn4FukXuXKNtze/XFk5Q1X1d1XU3seruo8yDybs2h9wES6LYmZBm4G/2Ug8CdHOy7QQCgvutQHopMPdyVxxVGs66radJGJlY9KSbaRUOoEyrfa3rvebbbkVLifLGQAWUuf2mMYec9p01DSIn1OPKFe69z0Z7jo+dZd4VWitY2NNk0rPcDR/WSN88s722e863bW2EHvZ8UDnLh5cnnkHCjY7lqJ1YfYFnXYkAUwjSZ9VHHDBSZasNerE/cN6zZB4oTSHxBblrcTyfwkGvJZtfcYnyT7oBFKU1Ik/SwsIMulElV6LMzbmM0baU5Wxg0AvxclHrIZaUZQuS2D4xeHFGtnoFiSmA0rExRoURCgt0gNYljiIx7zFVlNL0LDE4mQXxmuJpKgOyilrr27einfXc+0ucawpAnUgo48vk488JEwiyFlmM71Sru3derykzs/GJRTc+olOYcdU7yoW1VfgYKCCzkBsA4zvLSrvN36vL32cYX963sj/eeqjITwJQJ2TiNQWOd8Hldgw+sd/IMXi0qec2F6Rk1+ohrLCElutHziYsFR7XGxcTzreRpazV1HjOPIbGqDfXZgme3A8/XPd0Y8D7ezT/mRgvjGFitarSW7UEx7BEQPO4pCz8ofmRg8UPZxPJzDxxKWwwBjynGGSi6UdxOS1sMpTNbKGCGus31iv3MNnovy/g945viahpzW42qJm3W88VhDMpa0vW17Ft2GuP4VNi5zY2st26EiVrfkDZrAYrOCVvVNHdlqHUtUtPNRl53jrDpIAkzpoxCVYbYe+LoGZ/ciqSzdwLqjEZbgz1u8zHxE6gzxy3+eifLaSUPmiwjLcd7fi+zfWUGfu8mT0z4wU2Fv3Vr6dcCaqpKo3M7i5QHq1UuYC7tIIacgLbSxKhoW0msvhcKv+viNBsTosgFRifyhgIUC6toaoXzs0wPYBjFXUsp0fjXtcHUln47YnzArprMmCYB1zExPL7F1BZddP4xoTS4yw3+Zoc5aqm/9jXSZoM6Pyf88l+WY1kZqlfvl6kr0q4TUKgUqrbY0yWcyjEb3r5kt3OMTgbZq6WlPluiFzX+cosbelx+r9QqKv0dpnV+wLEPEvfZhLg34NwfpJb6Qxl8FhDjsiFGYcQMve+nwWYZMHa+I8TSNsNPlvz79VQgtYhjdCxsy+24RqNF6oilMpanu6tp0JpS4rhaoZVh63d0vsdqw8ou6X0/AcUhjJw0RzSmZud6fPTURmbPBz+yHnds3Y4xCEAstvaV1lRZdupC4J31mtoY+uCzCYfM5F8sFtkAQAZJQwicNQ3PdzuM1iKdUQqdmYMy8LT5vcIoplw3NTtFakII9MM4zaQ2Tc1m20ECWxm0NhPLGkLEWjPVGQKMg4C3Mjht2pqUYBxGkWcOw2ScIZM1mnEU6YxzMqPsXHFhtO8bzMmyGmNkX7XR1E2FG0WqW1Fmv9M0mL7ddmitqUr9c/7O29HhgtRUvbt5yl988ku8vHqJP/n2L/I8M7yfPrtPca29HTtCBty1MZy3C86FBOPrl1d0u55xFLORxaJhsWxorWXd9QxDIGQpfdPKvfxF2f1HEXdA4p7se789xt22GLORlJ8kp+KAWoAiiFTUR5/rXMWwaQwus4XymTGMmfWb642VUlPuCqPfUZqlSD2x5mbcyDWVWeOjWmqLi0txpSuMFjXA7bCh8wMuOBZVOzG/KYnDcG0sg3ds3Y6d6xljYLOXg6WmUGR6gSe7LZU2U12gyUDxqK6lJjFfSy4EjpuGyzy5o4GklJiPvZBjBUiSP19cKmGujXTOTwx1XVd03TAxG1qbnKsxMxzyDCxs/DCMAhqzR0DdyEDR5dwZxkFY+gz25okchc+AqgyArTUTMwmSO+PosumGPFutNVSVpe9HXFuzqKpJmlpy8Nlmi7VS57jvznzZddwMA6uq4mvX77Eed1y0p/zSk69Nct/Xjo/nnHVuMiqpjeE01yHGlHj35pahHydA3C4aTnLd4lXXsRs9MYis9mjZ3qnT/Kiic3Ih7IND+f/BbTHuGNu8ABTdXv2qCwIUFcIIhSRgbR8oDiFOgKkwhEqBC7KsBrbjzHxrpVBaXosJqjx5ftKKmVrn5bqtjQDK6y6wHsJkbNNaRWs1454M1ZoseRwC3SgGNb0Lk/yyTNAXNvVmO06GMOV9rRTLxuZyIvkePiQWjWHdyWSPVlJSIe0h5rYYRqsyzJzkpzJZNtc1xhgnNjBGGeMVNrGqBPRJa4vCsOfa3jxuHIaQJ0Ll2mpbK+PAIeTnXJicUAtYLM6qBSiW8a+1aspFIDOOc42k3B/kedj3HtdaVtYyZjBZWlTcboacp3rmxpCay03vWNSWbwI3XeB0Yfja0y3b3mON4uJI1BMxMcmElRIwrxoFjezH5U1P1/ksrYXVqmK5rKmMZts5hjyu11pxdFSjVPqO+fcjAYt3eifKKx9QoxhnkBg9qQC7FN8PFEstU8oyVZ1dRYMToBjy+uCugczkkhohDJn5EwZQFVOT9a3MfpTawtUKZYwAtL7LywdYHcv6t2uRrZZtNg3q7IzkHCwWAh6VgttbqY1zezPaGazFELAnC8JWmMrxvWt5XyvMos1fNWLyhZNcIHZOzF4aSxxmx1PCHtO1D0hSyhLTDBgFsU0Op8REGP304LRWWMLCBgJSf5gHXaa2YjKzd8F5H7FWUzUWawJ9L/133BhYLCw+RJTSOC/9BkuylhuHNQpjpQh6mqHL628bw+jmonJcpKkNwzDgfCS8d4t9upEaD6PQlUX7gLIGvaqpH54Se2k5oJc1cTcSNr0Y9BhD/+d+hfZ3/lXo116B26/hnkr9nG4rko+ETS9GQLXFHLdys/ARt95xux5pasO9h8fo2qJXuXA/ikmQdp52WWGWNTq7yFYfpEX5IcWLslPZtbn1xX59Yhm87rMPIdcjjlGchPdlbGOUlhNH1YqQAr0fkFYaaWJJisQtppjNcua2FrWpZJCrKxrTcDXcAIH1uM11NatJRtqFHqssfRhYVUtxMPUdO99nJsFTmYrT5pgh1y6GKMzaetxy1a8nY40y+5kQS/t7i8XELn7r9nZaZlmVm3XirJVcdJnBqLOUsvd75jbMToovml4UR9Uy+AqpDD5kPwqDKNJOYcAK+ycPPIfTIddNWMbR3amHcc5TVZamqfBGMw4O5zzj6Fksaoq8zfvAOPqJ2ZhNAKQmUal5prWsv7ArkFkUH2QfBof3gaeXNxhjQM3rkXVKzdW9xWIyxGn2WhuUn//J13+V/9YXfjufPX+Ny/6rvLfZAOI2O3jP7TDcMc3RmQV6ttuxWe+w1nD/pbOpbUCJnRFAXTdS/N9YO9WzfZRxZ7Lmu6hPDHvtLyIxs4puAoqFxRcppUdncOeTZwyOkOa2MSHFyWl4nrBJsu7MvhcGsNKW9bglpsQueDSaRd1MywxhpNKWmOJkXLXz3VQfHKLUCJ81x/gYcssH2df1KIByDLn+jplR85mx346iAHl3LfdfpRTHTTPlTGkREVJil3OwRlrVhL0cdOGuFK7EmN1LJwOqxB1DqiLhLvJqAcqzA6FzYaqfqiqDc2EaOIJMRhprqGsreZbzwzlPk4FjycGyLa3VXg4q6a2Yn937Ur6mqSeG0zmP9x5bWbwLeO95erXmudlOctiSg8ZoVnXFg+WKLn//VVXR5drBKk8E/Ll3v87v/MQXeOPkHrfDuzzdiltpm/O1cw4XI7UxHNf1dA+9GQa6XY+1lpdfOp8APWSTEmPwOlBVNbU1HNU1O+cIH6EUtfekfQlkkWAWoPh+x9PZUGWfaZwZwliGbxOzrbKUsgDFMklRwGHZZmEzI8XBU1olldYW3ZiyBFpAY1OpySNi9BGsTIKsapmQ3I7xTk/FxiguljbXP85GM7d94Lb3k1nN/n0+xMSqsXSjgK3LTBKYXIMHcg0uGrmmQkpTb8Xaypgu5WXKd4TJLH/6vI+lhjOzhwWol2MTZqBYQF0hGAq7HoKAWqnlLfkn2yj5WmfmcxiEfRNW3mbJaZpeS8l8QP7Nqrf9/KtrcwfIeh8z0yj3hOeXHddG5XWovf0Xk5vzo2ZiF9va0I9hkvharfn19274mU+cc/+4pRu33O5krFJbgw+R0UtdY2U1i9oCch/fDIHt1lFVmvPzJVXenlx7TK1C6lruWbJtcXz9dvGRgsX3GdjIL3N9YgGK+60uQnb19OPMOI7D3D/R5X6JSgkAXBzlesBNZiD3qNWQmUrvRG5a9qOAzaoWxi8mGHLfva4TkNe2Ij9NibTdSm1a1aFOTgQwDp1ISIde5KRFcnpyQlqvZwfWcRSAuF5Lr8JhRC1aUtdLPeKiRteG8fGN1K5kJtFeHE1S0DI149c99kQe0HFw1KcL3NVWWlWkfPcpdYkwG/iQGbXcgxHyIDCvWxlpBWLaCjU4ohLgZ/KFP/WPCvOMWNlGyEwiCNhT1kCI7HZegKNVHK2a6bMh3yyWiyzRczIDWtVmLhjPjqiL1jCOMUsMZPCtNRPjWGZRUpKePuX1ymq0DtS1RkWpqxx6T/XwBPuZN+D0FP3229hzh7/eQVVhL44Y//wvU3/uk9R/7W+jdo701a8StwPKauzZknDb4S+3+Et5iEYnfS1XS/ku9nSJXtaE7TD1oTRHDcpI1bQ9XRK7UUyDPqi9yA84XpSclvggoBiSzzf72cymyFCHMDCGQQat0VMac+/CjqWV2tmt2zLGuZapbMdnhnHfot9FGYRW1k61MZ3vuOyv2bgdx/Vqkp0CXPW30yD1tDnGKDFg6WNPn80ZfPRYbbjXnnIzrEX6lge3PgauhzUaaUx9VNfTQGmZ6xALQOy8Q6F4sFpNhjQpz/Re9z3niwUJ2DnHvcWCp7vdnbqnwh4Cd2SnIUviXAh3+i1OslSKXb4D9AQURQ6qM9DbA/ux1HXMTGJtzMRGdDuZzTRGc3K6IsVEjG6aKW0zwzaO8lpd22m9hTFp2ho3+kkCJDJrNcl7ymvzQzxOLJTTSgBvHpA89huOFy2fPD2ltdIDcZXPw0nT8nAV+P+89Qv87MM3+dt+4r/EGEZ+4fGXuB0GGmt5yVouu46nux1PdzsBO0EGBoulgPiXj444axquh4FK68kpdldJnelxHqSWWtCPIvbZRGByDS1AcX+CJuSJlP2a4MICujhO7KLP/RJlcBpobUtMcWL5YwaHGjXJWEM2kSlRwGZlqom5H4JM0nR+oDE1rW2mZtO9HxiDE+a+PpL64DDgomcIIzvfEWOk0oaT5oj1uMs5GBn8yBg961Hum5330vrFObbO0VqL1ZpHmw2lZtDmmsSpjYyS6svbYeAks1l9NpW67Lo7dYZG6ynH9qvDC4PpYrwzCBRDGzHUoLKAnwaEQlCqCbztXzfl/RhnubfWc33wODh0Bm3topkkpmUQ2uTeySKbi3usf8oMiKFuKrzzk9ysyMOnQXUxEomJENw0uVTYR5Pr+Ncx0fvAg9WKz57f57Q55u31k8mUq8p12H/+va/xExcv8Tve+Dxj8Hz16t2pd2PVNNwOA1d9z1Xf38nBppVJtZOmYVVVk3y4mBAV1vi4rifTro8iB3s/z5CWusR9V839+sQPqlMsLJgPs9NpmWxSCkhMtaNjDBNQLBsNaWYafZjrCcs3r3SZHJfeil0GfpVW1EZlNk/qD0MUFu9sISCuc1In2fvILk+kV0Zx3Bi2Q5yMcnofGUJiO2QFSploH8XspM69Cks93Ojls8ummg0J8zXbDYFVk6XbIXLUWtady0B4nmCcZJFF5pn/FDfUu8MSGVPO5jFSL8Wd/JsMFuOLz8Ai3ptZxzLJ0/d+an2xWDTTc6vkUdNkt/HsjFoMqwpTaa2maQzjGCbuqZjcFBnqPhspdcuyP6WmUdjExC6m3I+x5tWLJRdLwzvXA0fesuk9WsFRW/Hl9255+XzJT712gguJd687htz3clEbuhE2nWOT2dZSMrLI4+lFbWkqk0EpWKNpKjMdw2VjGV3ItaAfODyc4iMDi+9nE+EOUCys4T6jmKK0wQiFBZRawzT2TP0TS0P0lER2OvbQbwUoFjfUUqOYkoC1bjezgd7LZ6pa/gPp+eMZZFaVyFDrWtjFcZzdU50jld6IwzAb17St/N00c49F5wREbrdT9XIaBSjiHHGUxvZh0xOSALbQjRAi5mhmE7UVtzrdVNiLY1I/4G87zLIGayejmlJ/CEzOpKpMfSEy1OjDLD/NclRVG3lv9KgAZtUQ1z02u7ESooDMGNFpb4Yn9wSqrEhki+w1xaIdN3nTWly8QpQiY6WnWZuUpXA+KIIXeah3c3FzcbZSSr/vwh7HOC3rsoygrjXWyCxXs28iU8DubUf64lvSm9JqzMkKc9TgH13ir7fcvHND+83nLF6/oH7lfKq9iP1wZ3AResflZS/yi4WlqTXtssI9Xcv6bjpSHjwXia5SYK7EbTf4ubbhhxUfxCa+38hm7qNYeqyV71gkclJT2E+upwo1DVYXZoGPnq3f5tYRTppxR08fCtMgFv0uei6a81zbGGlNQ21qtNJ8a/3uJE2ttQxeG1PTuZ6d7xm85PXGd1htqHXFdVhTm4rBC4MYfWRlG/ow5p5hkfW4ZT3KMddKsfWOk7rJNYIibVuPI7fDgNWarXO4ELi/XGagGWitxSfpm/jK0TFbN3LZdRzXNZU2k6xU5Dd7LF8I00AXRAJX3EOhOO/JwLbO8reQEoumZrPrJ3ZuZjgyc5FFGUWyJtI4PS1TwF7dSL2YTmKaIeBTiZRV60kGZ0w9Ab2UZLZ1eiDm3+va3qklETmcMJYi3wmT1LTUVBbZKci1X2oHv3FzIwYlSrHIQP3Xnj8jpsQ7Ty/5+rNL3rx/wSdOTicH2PUg+TcZkIyOq8s1wQfaRU3T1DRtzZPtlt57rrpOpGReajdlHxRXGVQH/9EMVD+oPrjITT/MyKZITSfZabwrPS3y0TKRY7XFRz/V8LroJ9diYe+jtLPwPSEFVtVycjS12kwTMk+7y8mUo7S0qY1lCCODd1Pd786Jk3GlLWNwWG0JKbCwDYN3VPkzRRq7dR2bsZuOwRgCq6qaGGWlFOthEGZFKTrviImJxS8uqCkzWi8tl+yc4zYbT5XeoUW6974c3JP1aaVwuQ1OWTdIH1Fxis0AuqnZ9sOdvCo/9+vsC8MoOajuqABSSlR1Nd1HQwikmCYnZltlg6E0qwjKNVnWW3wBJLfUZHpTzr9zfpJ9lnrjuq6mnDRmln6rXD93O/T86tNHLKrnVFpz3DSs6ppHmw3XQ8/j5zd86/KaV89OePlIWqS4GNkVMI6Abuc8tzdbvA+0bU1dVzRtzfOuE2Owvs/P8Fkmr5TiuhiLvFDz+cOIF4Hi1PswzkxfcT714f29FPcBZJGa+j2wkrK8sjCNbk8lUsxvUgaKpX9hMZcpPRULY/h8G6YxgVQdqclBc5frGMvn9t8zub2CSE6l1+7oRfZKkDYaBSSCgM2mFrWFC/Lc2g0+j8UUo5NewW1TmKm5R6HVipNljfNiqFJbPSnDSsuMiYRAvCdUnKlFo0sfxplVTImpR6PL0u62rei67PNQjBG1IsbZCCilGUwKqaEnoFbGlk1j8jGdTW8KaNpfVtatpjFmyDWiZcKouKru18aXCR2XmcJ9tYE4qcZsYlXAsGxrO3i+/mTNowzgVrlf5PV25HY3cnnZ8eT5jouzBedHUkbiQpzdZWOplQzc3Ax4H2kaS10b2taw6aS8Y9e5vWXnPFtnAqjUWn67+EjA4vuAYkrc6Z+4Lz2NxdCmmNXMwJGUsuvpOJvJKC2MmVIwrmdX0ZTkvW6beyyaqQ8jSokJja1ESqo0LFZSa/j8mQDQ5VJqCbUW2WnXCdgr6y5XapGzZuZQrVZiiqPUzCLGCFdXJOeyvLUC7wWAjuNkeJJSrjlcNiQfsMfSzygOUpegKzv1IRThekXa7Ijbgfr+MWkYhVWEu4AxZjAYpN+iXokEbQKK03nJhzS3dojbkZRnSkxbSVIUELjnZFUKl+2qmaeMgKRBG0tUAZMSJu9XjIkmD17LjE1JxhASbSvJvOtKsTR4JwyhMYrtzsvMysLkS2aewTJWBsAm20KXpOp7cVGtKk0c8ozPdZelEypLFeQYD7uRXScuq85Fxq89I37lKW1r5O+cWNZokeXmm2PbGpZLizWK5vULwqZnfLZmt5Ob82JhWZ62KKshgbLZfGjwdJsfnm34BzGKMhAMdwaqwnAISChOlQVcKqVRKU11ikMYJkZRKYXB0IeeIcxGPVZZtn5L78UF0aciN1Oc1SdYbdh6qQE8qlZcjze8t3mKUYaTZjVZ6lfa0rmem3GTB1tiry8DOgGCVlsGP7KqF8QYiUaWKfLWd7dPGUMQ100rJg2rqmaMYqRR2lmMwXNcN1L3lKVTO+c4rutJzlhqfRpTczP0bN3Iq8fH9MFPcrcQI9rMACnkh+GY17tfv1iiMJFWS9/BMTcPF8lZdZf9iPv5J/LRtq3vzOYqlfLDNUwPz5iBYVs3eSZS3jNWTEdSlEFtDJG+H6YHbWE2rLVsNgK421wD+aJkrqrUXisPyb8x1wwXqSqIsY4MYoX1KKyLGz1dN4hMyAe+8t4TvvSt94SN8YExm/VoranrCu89IQSq2rJYtlhr+NTFObfDwNP1hi63xWjahtPTo0kZUerVBu/ZbX+4rTM+zEiqgLwXgeIsDy0AcZaFF+BV6hJBTKRA+k7K8pLPSikGL3LV4lZaAObCtBhlcGR5k6nZuY7n/TUazbKSnphaKSpthDF0/TRBEPJ9wgVhQK2WlhlH1VLApIUxeFxwRBLPdte4KI3qG2PxUSZfhhDosplNGTQuqgoXAieNNJbvvUdbO7HDrbVI03uDiwM757i/XDKGIAP0vJ4PykEXwiSLnM7HVLedUEnRWoPVms04TsxRVVmZoNB3mXRgGkQ29d1eZREZ/Powm6kX11RTF4VAvOPGGGOkqi0hxDvGN96HaTJot+tFvpZzvkz2FPVBXdvJLKfkZ9+LusBWFpdLRrYpTTmojaaqLMZohsHR55Y8MUS+9eyKbzx5Tt3UhCyjLQNra+0Ebpumol00GKN59eSYzThyud3Rd/JcaNqa1dFiysFiVuSCqB9+WLEPFCfZf2H90tw78dsZ2twBjylOTqaJND0vixw1pFkl4rLxjGx7FnrVRlMZxZD9GWqr6V3kuvfT+2Ne2Ggm1nCWSws4kj6hwjrGBKtsjKKVpveRMbuoXu7cBGJqq/ExUVmZXB/9zMSnJPsSU2LZWFL+DmLCtn/vFH+J3olZy8miwvkZQMfEnd6OAprz+K8y07bujEFzWKMw2tCNs+qjqkwGh7NTfpGMlt/r2kxgrBxvnWuKy9/GzEBRJlrjZHojqphE06jJmFD2T03Laa0YsktsXdvpGVgAtjzPZun4nH/CbFaVZhhm1rGo9soYtNQ8dp2fzGeePt/x+OmWppExqHNh2p61elIjNI1lsbBYq7k4XTC4wGY7Tm0x2tawWlXTvpVjUFWR3e7bm7z9UMFiWj9Pd85aStypTyzgcHI9lZrDNAHEdFeWWljDsZ9lrH4URlApcavUoxjOxAi7TQZy1bwtEKlpCDDcynvGwO0V6fJSWMFiPuM9rFZSL5llaSgl77VtOdPyu1Koo2NZ3+5SQOIwyDKbDakfUMvFPK3g3MQcpiAgMXbj1G7CrFpU1mZHZvAnPReN1CuOI37dk6dwhA3UajJeSSHCGLP7aSK5gF6JzA+tiM4J+FRiwqFqPfcmzK01VIT2wYm4sI5e6iFjkL6JgBpE6qIbqcFLKUndH1A/PJVjG4J8PxcI2wF/tZXvERN5NUTnpxkbINcaajajw2u5UWx3fpqdNI1lt/PTzUIrcF4essYqlksrs4M+st16qlqSNIQ4NbwdhpCXUTQNaKMgODYbl0/TrO+XUzY7etW5ODmEhPORk+Oao5ePIUTiGHDP1sTdyDjO0ohhCOg8q9M05s7MdNP84Ntn9GGXPuhGDLBfh7jPKBbp237tW8oD1DGOdGE3AUKRyoiphU+eWtckk9i5HTFFbsZbEgmjZ0mjVYbWtvgU2A03VLqitjWXwxWPt89ZVi1Lu2DnO3wMLKsWFz3PumtAmOid61lWMoj00dNUSxKRVb2gNQ3X/nZyVwS4HtZsneOsaSc5no9R6mRyfZLL7ou1EXv+o7rGZiYLMuswa0+yfGrguu9zDzY1OaQWBrFITF0IuDyIPaol/zTieqrI7Adiv18b6Rnn4txa4+HZCZXW9MHT+yDNf21hCQqIk7qh/X5rF4vFJIkqBgy991z3/WSas/9AM0ZLy5yUQImdv3cComxl2e0GUuoJPtC0NX0/Tqyk5IdnsWgwRmR2xehju+2oKjv1hyuDX+f8ZMxT15Lzznm2W2GexMxjr/dcmC3Ty0DYe2E0V6sFp2cCBEcfeLLdsh1mg42UxFSksDF1Xe3VaEbq5u4g/wcVO79JE0NPGTDOQHGf0Y8pEBD2vdQoFnA39U7MeShMY5zk4VbLBEataxye0W8zyOqJKeQaQ+n9VoBdItHnHqeVrdi4LVf9bW6BICx9SIHGLAgpcjuIbFQpxRBGWttMOVjlFhvH9QqrDRu3wwVpzZFS4nbY0HvPKk+UKKVx0d3NwcwullxaVRWV1tMoP8qFKgAs18GNwbPJtcVaKXYlB6eB+pyDIYrDaQGKU56hMEoaa5QcrDLzD6JCeOlYrq0+eAYf8CnR1NIKyDkvhhU5B2NKE6h9uFpNkxLlPrN1jsuumyaCSi4X0FaGTKXWsOskD6rK0nXDVOfYNCUHVWZV1CRfLbLxECIxRHa7XnKwshOLp7XORhdZ4lpXBC2DzjJ5UgahhX0JWYIug2Kbwa7UWx4dLbg4PZqkw5ddRze6KQdjjJOMHSQHu7wfwrz+4Iej+yBRLp8sPQ3pDuh6kUUszGIBlfvvj2HuoSjAUBreJxKV1lnWmp8BMU31h4XJLHWJWsHgc/swq9i5yG0v13+TgWNhCWOC9RD2vle8w0oaK+tb1UbaV4wCZkcv+7wZgiisKj3N54dsaFM8IqQ9h5xbFyJtZbBG35GeluGE0dDWZmqvQf6O0rNx5gymUqLMhoWQaGsz9VB0mYzQWkmCZ3WaNfpOy42To2Zqt1FcUquqMHXCmlsrEssitwS4yJ+be2BGujFwuxvf5446KwPI22Vi3ZQSKWm3x9BVlWEY/F7+kfPPTFLQIk3d7RxVZabaybL8OIZpskhgSXkGjnkf9CRnFfOrogCaFXmimomsVjXn54tpjLzpXFb8hDtj0MIs1rnGtQDGH1nN4vvdTuEDgWKMwiRm19MJKBaQCPK+d6Shmx1Nyxmtc3P73HibcRC2sLiTjkPRPWW2b5jlq6XvIkbqEBcL2Z/CFpZZyetr+ex2O8lSsVYAYdvKZ6RxC2mb2c1huLMu1dRzHeMwELqRlJMs7GQfzVGLrgyhd6hKi9yzc5g2f7dsWFMYqbTrSb3DniylrjPMfQxLLWIKkZRnquzpQqSnIMYsViSnYTdgj5ZUD06lhrKpCZtO6iW1xpy0qJMT3NffQ7dB7MDXHRhN3A2Y4wX16/fl2Jyf35HpMo7QtqjlUtznbm+pnSM8vZSWHw8fyueePME/vcnscRRw+Y1LjFUibaU4ZqU7UlNrFNooYkhY5Eaz3Tp8SJN0Yp6vEJmorqzImJqQpatZShATXR8ENCLy0LJuHxLbrZtkEG1rJ7ewRWtpVzVhI/K4sXf4DCx9kJrLkBNYZoMN/RCoK83iqBa32/EHK8H5cDYxTrK0Mmgtg9BEumOUIXOBZbY/0PldlrZJz0R5OFaEFKa/O9+JM2LytKahD8JMKBRBSV1TAaOVntmy637Ncb0St9To8HG26n+6u0Ipxe2woTYVVZaeDmFkWbWEJMYZrWnofI+PQfrHRRmAC+isCHmQLAyJm6z5b/P1etw0NMawGcfJDXXnHKuqykdCjkgBkbfjQO/97IgaSk+5efa61FIl4HyxYAwyU1lZ6YFW2IvjuuW14xN2XppVP9psaI2nMobztuXlo3O+9PwRCyuD3cuuQyvFZhw5a1s+c37BwjasqiVPd5eEPPPtMpu6rBo0itux46JtuRkGKmO4aFtqY7gdBp530makDA6eXt5MrGNh/lPcd2zUufi/1EWJE+Nu1+NcyLOucxNqMZapplqsFyVpJGE/CjtSHqJFFrvddpOUrjAnSsFy2dK0Ip/1iAtsYWT2jUNK77umqRhyb7flqhW/sx+Cbf+d3ok54h7Ae5+Z1NQr0c9s4tQ+Q94fowA4n8SxNCadGYU05UsxvnHRU2nLpDrKSgDJd8kFhbCNRhl2rmdhG3FMjZGQXweZcAEmtr8ALJ/CBBpR8trWdXdysADbJre3qLRh8JKDBZBtnUODAMRsErXvSNxau3cM0zQJss3rOMogLWQJ6ofl4Fnb4mKpzzRUWQK9dY5V3fLyakXvPY21rAfJb6Olb+hpu+QbN1c4K4zoZhzls0bqnt84OaGxNaf1atqGi44xOBpTs6yEyV3nxvZPthuWVcWD1Rm1tjzrrnm83WZAIeZAb19eC+uu77bNKDko4LL0eBOzDuk/N4iJR54EKVJykrB71mb31MpOzsBkadzQj9NzrtRAlRY8MQ7TBFORuBZX4cWiocsqjb4f2WVQWiTg5feSg+PgqCqb6zfjDzwHX2QT0x4wnJnFmVWc3E1fMLPZB4xl0s1HYRNRCatmaTMw3Xt9THdk0GjFGObtTuOMDB67UWSjs8x15lpue7metmOYgGaRnDbm7iC/1Cv2ruyz7G8BTQV0DT5OYK3P8slFLdfa6CM2AxIfpC/f/rEsQKW001hlR9RS11mOdzEMKq0alu1cwmCNgEKtFIMLLFrL+ZHIWm1u1dHn79tWhmVjeXzT5VpMTTf6fNw0y8by0kmLNYrjXHuolLSY8CHRVJpl7iW4HcUc5nIzUFvD/aOayiiebR3Xm+HOOX/8bMcw6GmMWBhEmOsDi5S85J8xwjwW91bYyz+E3SsydmEF0531i1NrmQwtz0AZT3bdPMFbTbWHsFhULBZ2AoZ9X+qamcBkAZFKCQM7DIGq0hOo3ZenflD8UMDiJDstcLYMPGOcf34YUCy1iMC+6U0ah1l6agzYGtyQJaYKjIV+J7LTEqVW0VZZjjrOn18ewdUz2Yy7FVno2Tnp+kq2v1iIuc3VVWYeb0ul6vy9rDhnorUweduNAMoQ5Gc5BvvgMgTS6KRnIhC7UeoPz5bopiJsZ9MakYPaiSkkJWEbBw9WY+6foa53qErnfoKZWXTxTi0iWqFqQ8wPBVUZceJc1CQXpFVHbeD8HP3yK7A8wm5u8rHK37FdUH/+J0lvf1PAs1bo2qA/+QA+9SnU8amA9AevyDH9+lfg8lKOY24Nwvk56lOfEVfXl56hlkt4+Kq8/8abVEqJm+zzZxAC937DyPLnv8Tzb14jLnhCwZcbni+1HJndM1rRdZ7j4xprFbap2GUXL59Ncera4Aepg0l5dqeqpI6y1D2CzHj5veRRetbL2/IgjVBZJVJU5zGrRhhR5xmHJNbFxaraaow203qN0TgVUduRqtI/UGbxfZK3PUYjTQPULHuLnmxtQ0x3TXbS3sOqDz07v5teb01L5zvWfoNGYWs71SKWCEmah1tdTUCzxNIuuRluUUpx5W/wMXCxOOXJ9pKYIqtqwc71PN5eYrTmpl8TUhTX03wjNUpjlEEhD+Wd69i4Dhcct4O4Z1ptxdVRaVxwk6TtdhjyYHOkNZZ7yyWttdwOAxeLRV6/NAIPUXonFplo5xzeGF49OuWy66iNYfB+Zhb3Bqkp75s0NA4YJU5nq6piUeU6QqVyG45TfvroAX0YOK6f7NVWGe4vz/iZ+5/n7c27PN5eooDGWk7qhk+evsonjl9nCAOvrl7hafeUv/D4L7EZO7S1uBDYjD1LW/HS8pSUIueuwyjZpo+Bo3rgE6f3GfxI56VX3ZtnZ3zx6VOeP7uRgcSimtoI3K2bTFOd4m7Xs1g0IketLUMv99xiG1431R37/yI/LdK2sp6+d1P7AciyWp0NfIyeDD2M0aBETnu8aDFacZMSfTfQ92Ou3VJ5JtZOA9fSZqTbDdjK/sBZjQ+arNk3r9mXgcdsZrNfn7hfR1wmdspEDYBCrv2QRCYpoE+JyUyYzaN8NsYxSk8GNJIXhtrU3A5rsW2PW3wMnDXHXPW3xDSysA2dH7gZpI3UehS2srFLkd2llK9nSyKi0KzHnZjfRMd63JGSOF5LrgqbHpEc3OTn8S6b2lwsFtTGsB1HTppmysHaGCZn05yDvZeJlPvLJZddJ7VZucXGizkY0l4ORsnB2hhWuUY2ZPDVGMN5e8LD1QUL27Jxu7wPOtdsVnz+IvDO+gnXw5pnux1Wa948O+OTp69wUh8xhJGL9hyAb63f5br3LGxDHxx+2HLenvDJ01eFrVzesLAN9xbSz/C144f52um56m/xMfAbXnqZv/De2zx6KhNmxeCmDFQ/KAf7fmS5ajFGXFiLvLPkoK0MY+75WICnsVIn6UY35af34W4O5oExzBNEMv8tMnLvA8tGXFG9DfTOMwzz+ooioORgmQjquwFjzQ80B19kFAtQLMYrMTEDxRD3AKM0gS+A5y5QTJPEsshofbwrYe5DzLJQ2W6IswR1DDNoqozUGV53IW9D5KTHjeG6E0OqUnd408tzZTOEybSmOIgaLZLNAmC2YxBWMQibWJQxWuUG9XnfRjczgoMLNJVh1Yqx1OCCyE/z87+wi2XYWybrk9GcLCsxZNFqco3VSo7L5Cyb5vYOIQNoawSY1nnSwmghBU4WFS+tLKva0BfWUcnxroziU/daHq1HNkPgZivreXC64PXzhtZqXEicLSyVUTxZO8m/SuS4LiTuLy2fvpB7y/NVRVtp7q8sPiY+cd6g1RGbMXK187iQ+PTDY770zg2Pn2yz7NRMZjBlEkWurzS13BjHIG0qKqnb327HzPqnrARSeeJlNuixVgBhkZhCcVqeL+N9Y63ys7CMpZ9w01iUUtO6+n5ufVdcUKWNR8y1lNJj0lo9mQJ9WPxAn5ATSCxX7j5QLIzii/WJ3jG1xvDjXTZRYDHJjzDsoFnK57sNbG/mZZUWoDIOk0nNxF5qA1sZOKK1gEQ3QorSzqLs62olP70XpislcSw1RoBOVcl/rQX4pSR/xzjXJa7Xc/1iAZOFZTOGNIzE0U9AkRBp33xQ+G7QctMlJal7jGmqO0wxkUJCN5awG7GLSqSvRpNCAgJolZfba4VRHiZjQBmFPl6gjMacHcPDh6hnz1DVTmYWvYd7D+Q4ro6haQUs1lnme3KOeuPT8NavYY++Jd8tBNSrb8DqRI6tNuB61NNH8jmtheH1nnRzLcyrUmL+A3LHrpv5mBmDciPprbdgsWDxmz7L65/riOst+ngF40j3tSckHycGcrsep1m646OK4595HVVZwrrDXu9YbQZUbUhjIA6O65uRutLECNudJJPUTmZnuVxAXkxyqiwDqWuZQSqNZYE8iyo38UVOysJEgtzIYxKZiZTdJukPaRNxSIxW1hli4uKvMP/2Zaf7MlIQoBgml8UwsYouuXwaZFA6LZ/rMEIMDHFg57esqtXUI3Ht1sQU0blmsfMdve9nyWkeAFtdTSBTKcXSLrOpTZgkagCnrZgn+OgxWnL4sheZqguOylQcGTGRsdoSiTS29JCTh95Vf0tIkTrvQ5HSAdMAs/fSTxHk4fyZ8wvp1ZdZGd3KuS0sodVzLUNISRiHcWRRVXf6tJVB1z67IYCAvD5xXiwy1LO25c3T13i6u6QyOwYvUttPnLzK5ebJ5EpZGNYxOD598im+cP4Fvnz963y5/Tqb3NLgvD0lpsBPnv8krWkx2nBSv5VZpEjV7DvBehSKpW2nc63z35EEtiaSeHd9g1GKT5+f8+rJCeth4P5ySe8979zcUoxzYoy5HslOjMEr984m2ezamDsujADr222uWUZkdSFOLInUZo04LzPKVQZypd5xNiRQ04PSO58bnpcy8rD3EJ5NgVISqWzwxdTCZWbmbq78lcS3dRwuQPEFIFiAoo8uM4thZhMp7Lj0RiwMvouOrd8R87IiDZV2NlbZ6ZqNua1NH4Zp4qI17aQgGKObBpQL20w1kZURieXtsJF8ix6rLbWpUEgNI4h7akhB6hYRqWpIwh7GKPLX4rpqc4/EMUsx5bjIpIRWaso1nd1NXQgTkz9/H5F4OudYVBUaRWXMVA9V1jnVDqe5Lr/k4Cq74Z4vFry8us/T3SVWZ1ON6DhtTnJN84JKV2ilp2N6VK14Zfky72zf4+36MZ0fSCnyYHmfpV3QmkVWLwwsbUuzkntZaWZ/M27Yuh0KTWPq6XsZJWoJOU5Sz/nWzTssbMNvefgq3b173A4Dx03D4D1fv7kRaW1m/3bbbsqLxbLhp15+SJUNu66bnvU4Ti1qRuen9jLiEimTKjHEqR9kMX3SWmGzhDwlycHi8lpCKcU4jBNzAXNd5px780/nouSgFdBacvAHYXDzIkgsx7cAxe/UGqOwi4UV2weKLsvtNQoXI0MI7Pvs+cw6zgxjmtbl8noAFvVe65Uw167XpW41Sd1sSsIoGqUYs/S3zmOUKtcntlbGDqV/4k0/t18pk+pDAetaQJ4LkX6cFUQvny3unNN92WZkr1Qhfx+prUy0tbozHprKgdKsAiuHRylhM7UWkGi05nhR8dJRzfOty/2y8zhoaTO4NNkdVp7fEThqDPdXlkdrx5PaMDiZeHv5uGZRSU/Vcj9vK80DW2G0ojEKn+C689z0Aa2gtvM1bDNbC3DaGHxIvPW8p6k0n3v1lE+8dMRu8LSVtK14fN3JpEIUn43tdpwk5KtVxadfOcUaxab37BYVuyF7YHgBg+v1ONUj9r2b1rPvrlr8BKzVuX8kU83kvikPiLw0hDixg/u5aIyay0xK/oVIjJpx3O8T+e1z6wcGFj/Q7XSfUXwRKBYWMYa7QDHkPoQxSL/CGASAFKC428Dmdt5GDDODqI2suytGNMKwMXQCSE7PYSuALq1vhDlsxY2UlKBdyD6UmsXSkgNmcDOPSOTv0n8x9wGbIgTSbieGNjGSup44esyJgFL35Jb2My/LektPxiJnBVSMoJnkpSQBiskHUu/Qr1yA9/m1iGpq0m6U98N801VaETon/RCtkdYci1oMfG5vZR+bRhhAa+HpewIQm3Y+vvn7kCK0S/j8b0SVHpOf+LS8P3RyDppscvPSy/l85uPUtKjze3MLkSIbNgY2a1mubgTsGwuf+AQ8f0587zHu+Ybmd/xW1IOXSY/epU0J9alPTVLf1aNHdF95TPuJe5jf8pum9VhjRJpVrqGbS9J6zdFmM7UucY+vGN6+pN85+iEQfOL+J09p37wv9ZWXW4a1NDjVSuXZGi/JnO2rjRZJidQ65lnEMeYbqbynlTiPlYQvPZTKDdL9FbbO6MPuhZnUPEmQ/+0DxZgbeLu99hUplYHW/HPnhR23umJljwjJs/Mdnd9htEVnMOKDow/DJCstUtPCVO58R2saLpoLbsYbQgpshx3rcctRtWTIAPSoEvnWQmk6P2C1zQ9ew1ElICaS5kFncmzGjtpYrofN1EC8fP/LbkOVZYvrcWAMgfPFAqM137y54Qv3709mNzE/1srANKZEpZTUGua/l9l0Y+tGPnF6yhjc1HPsqK7ZZXfTF4HiGOYHeGstx3XNxeKUTXZnNUpxXMv95a2bt/N+GDSaYvo/m5Is+OmLn2Hrd1S64lMnb/K1m6/xS0+/xNduvsmnTt/A6ooxOl4+us8YHJtxR2UsTaylfcK+LDLLDaWOUmXGKPJgtaJzjqe7HZddx09cXPC5i9d5Z/OEIQRePTqanF+v+57H6w0ni4ZPnJxSGSNtO3Kd3Bg85+0JW7fLbHOktTVL2/LW9RO+dnVFtxsYhpFhcNx/cMb90yNCTGz6ATd6hmHMrERgGBxxT9pWQOZ221G+Wuk5Wd7bt2+3e6CzHAM3/pVL4O70TnxBevpBQHG/h6KPfgKKIRaziVl2KgDtrtS7XOchA06X29gkJe1t5t6mkT4M1LriuDpm56WmuPfD1BbDRwGdrW1kgKikLtHoIuXXLLKxEwiz5IJHRT9JU7d7LqcAkcTNsJuUALvcl++slSbsT7ZbPn1+PuVguRcZNbdnApm42QeKPtcenjZNdlKWHGxzDo4h3Mk/gMH7KQeX1rKsKo6qBbfDRtQF1rK00p7nsr+eXJaLXDipNN0ja1Pz5vEn6P2AUZpXVg+RlkLivFznya6L9oxIms5nbWpOmmM5R5mVLcd253dYZTHaoDMT+4mTl7nsbnh3e81l3/PXvv4T3F+c8Xj3HIA3zx7igkh8H22u+OrVFW+cnPCbH36GxlZU2k4mZOX+cTts2bod63HHehQp+6PNhndv1wz9OLXOuXjlHm+enbEZR676nl03MPRjHsgWxiLmGsY0Ab7drp9Z7fxMM0ajJhltBpC2SOiKCU+clv9+44OA4lyr9u2BonvBxKaAxeJ6mtLMJvYhsPNhYq6n9hsTi6cYwuxwXtxPjVactIbeyza2e20xIokUoM1eCFrBUJRT+bs0Zv5d2LuEC7ALwrpvxzDtt86GO5veT2Bu5zwhiWkNwO3O8fBsMZndzBPNMsntYarvBxn61lZP9YeFfaxz/8CmlhYNPhTjrj2TH7f3DKwMTSU/10OgG4PIRGtDbTQ3faDSwiRqJcNiYxTFYbU2mjdOa8YQMUvLw+OK2qgJKJZ4eFxJ7WlmNmujOW0MxR+yHBcNrMeA1WLgo7LE95MXDU+3nqfXHevO8bNvnnHWWp5u5dnyxkWbr53E0/XAu1c7Hp4t+I2vHdNaTVHu2sy6piRgvvS3vM0Orzfbket1zzCE3JYjce/ekgdnC3oXWO9Gdjs3meIIa5jHoGFuT6UUk0lNURrIJMBdGS0w1TzuG3R9JDLU7wkoFgCR5afJO2EXU8qvZYZstxEACSI3Bfn8PlAsvRZDdji1FnZ78s8ioVgshfXyXqSowYuzaR5IquNj0u2tgNNSgxj27MuMEalkSgKyQNZT2MW+n2Wm1k79GAFoGuLVjQC1VtjJ5CPtpx8KsCrgs2xH67m2MSVUYRitQS1a/NMbqpeO4eICuo707FZqGEdPckGMacopiEmApJH9UUphz1eQEuHdx5jTI3Fi7R3pyTV6UaHrGnV+LmD6XRm4qldeJV0+R33up+BiIUzu8Sm8+gl4+khAtlIC0nebuZ9jAY/5gUC7VxPqRgF1zUL+Xz+X6+D2mrRZy3G4vRWzmMst9Ze/gnr4qjCZDx6gjk/g5aNpgmBZVajPf36SwWbd6Hxsl0fw0suoAh4vn0JK1EB9fcnRW1/DP3qO/anPoV7/pIDNcaAJgVWKpOtLOc/X14THzxjeuWL7fEfX+Un370ZhJK0RSYXdo/WdjwxDxGgYhpn9m5N3vsl9r/EiUIS70tMwuSyW3m2z/I1cx1gGFFL/p9n49dRDcSx5CPShQyuTZ1cdPtc7mmyfvx4303cL2S1wZZcc10eTjM5Fz+2wneqhztsTnuwuWY8bllU7DVxrbYkkam3Yuo6YEmfN8d7ALNAYMZqptWWMnkobjDaEJKBtVbU83a0nOVutK3Zuw2fyIDVldjSSJrlZSIFlbhBtlJtqpI7rhnfWt7y0XPHS8pzt2E1W/oMXJ9TSaF6OvcxGGy2OpCklTpsGqzXfuHnKxWLF1jnGECZjj5Aip80xIUZ2XlqUnDXHpCRmJEf2GICz+pTXj17nF579Il+/eReQJue//PTXxFQoGwGVAW3vRxojdZuFiWpMzSdPXkMrzdeuv8n1sCYlcYStjZ0G99tu4L3NhovFNdd9z1nTsKiqiQkBmUV/9eiIVVZ2aC3XiNKWVbXkr3/9r8FFz9IuOK6OuRlviCnx178eueyv+OLlV/iL732DB6sVD1enWG3pvNz3f+r+ZwGR5z3dXfKt26d89eqKy5sNu+yoqpSa5HmlAXnpNwlMDdG1VpMba7lGgQnQfL/x3TKKcy5KDhY2sTib7k+yDHG483q5pvaBonw2TEoAozQ7303g3+V1taZhYRcUp9UxODauQ+bi4bhecjtscy5VuWZRJJulHrL3It0+qhb5OpE+i8WJ2GrDmO8FRaYKsLAVV71IRZs8gedj5M2zs7s5qETyqZQWVrKwwnsDwGVV8Xi75f5yyXl7whBGnmcZasnBYhwzWdrHKI3gkZn684Xs/7duLzlr20lx8CRs5R5hLGfNMWu/Y5N7QT5Y3eOqv+XTpxV1ZgSP6iX32nvcDDdU2qKUpvc9gxomQBiyuVC519W6lom6JPdOq6QtUGNqbsc1IQY2bssmy8TX4w4XI5e7Hb9++Q73XzvDx8DD1Smn9RGLXAcJwsR8/uITXLRn0/Utyg+dz8OCi+ZiGiDejrfTOboZ13z9+h3e3az5qfuv8erxA6yyco/PZlu3w4YhjFz1tzzebnj79pbb9W5iJkFqf4t5jjEam+uTQXLQO59ztZiXzMYi+2zl9xofBBSLsUrcYwlj/HA2cf8/CFib2muU7xATXZiBYqlf3Ff0FPmkyoBOKwGB9V6N4hASuz1wvKwMmzHQu4g1ihBluXJXUrneMSZY5nGFz4yi0UqAU641LDWNMUtGa2tY9w6rVa4DFjloAYoFCAfkp1JMqppEwgTFQMAYAXg325Hzo4aThfRdXHdOWLM9OW85XinN5mkgzOJJNkJ8etuzaitxiw2R6+1IYw2VWXC2MOz6yCYDpIdHFY83jtdOa04amZhY1YaLhaX3kSb7Wgy513bpVelimhhH4M45GIOUl2gt69qOwuLeDGHqS7nupZRovXO89bTjt33yhJTg/lHNaWs43vPFqCvD5x8suLecYVXJtYbsmVFpXj6uCClx24dpQms9BN656rnZOT778IjXTmvpAhCk32bvItedZwxyvK+2I1frgfV6YBjm+kSpTSz5ZybzHiAzj5LL+8Cw+BCo75B/f8Vg8Q5QLADpRaBYDGteZBS9y4BvlpwKjz3Oy/txZrcK6ChsYlm+SE8LUExxmmGWthiZJVvfkIZe2MAiNTVG2LXTUzG5Kd+hSENDkOX3v+M4yvYL27jbCRuZkgBGEPdTQQYvHLCEfelsdmRNaZa27j0U92shVWHjqgr76n148ABubuDoCHiMqgwxs4cAyc0STXPUZJmqGNyYZUNYdyQfGb7xZHJgVbWVlg6bDWm3Iz17jnr5IdQ16a2vyffdiskBFw/gM79BzqP3WUocRe67WAooHHphG1dHuU2JzRLVkfQX/jRsNqiXX4af/M0CFt0I65vcfuSI9PgR4WZD7Eba1y9QJ8dwc0n44pcJu5H6+hpefx3qGvX53zCzki8eQ1vN2y7XQwwCdt0oLGYIqDfewO528K1vkW5vUa+9JsBzdSI1n8sjePwOabfDLBvsyYKjyrDsHONuxLvIMAZxWPUxG/xKQlqr8S5NM01yytV0maW9Wa7vNT4IKJaYzDPyALUY2UTKwDPOv1Pq6/TkIiqg7K4hjaxXJHPFjbH0R9y4LcWevwzWAFaVTLDcjrfsXM/O9bRWcsdqw3W/5rw9YZedN3WeTVX54BSgKK9HccAMnsZKfczNsJskXS4GXG6HIb0MZYBbBpwhBR6uVtPyPiW0NljUZNxBFPBQZv5PtGEMHq0Nrxwf83B5j53vOa5XwHPqbMIx9UyM2eDAB1ZNLX0Xtea0aThpGrbjyBgjX7l8JiYZWgb5pY3AZX/L0+2Wl1YrTmo5ds+6a/7Me3+eB8t7/PaHv50vnP8kW7/lW7eP9pqoi0yxuG8OYeT144e8snqZlV2xtEsikT/57p/lyfaS+6dn/OT5T1Lpiqe7Z9yOGzbZaXbrRLrWe8/F8ZKjumbret5Zr3Eh0IfARWaILtoFD1cn0zmvtOG0OeZiccpL7X0eLB9wXJ1k51c9gR8XXXbxjHzu/FM83YnBR++fc2+55F57yl/98m/hwfIhG7fm7c073AxrVlXNWSv1idtVS9cNU83jMEitY0ppqrcy1kyD1JRmy3n2BjSldcH3E98No/jBrTHCBBT3W2PIdSl1i4k0vX/HLGia+Mn3dmVAQRf6aRlPGbQKI61QbPxOzGV8T21KPa6Y25y2R2xyH9ISJQdLHkkOZfOuGGis5NHWdSJdjYFIwMHUN3EI836WeLBcZQlrceWVHJyYAV1qBTUqjCJrRVxfP3Fyzv3lGbfDhqN6SUyXtNbeycEiCQwhssyupRjDSdNwVNfc9NLP+OvX12ydyyBRzG7W446t63i8veXVozMaU/Ot2/cYg+fVo57bUXFSn/DG0etTv0uDIUZRWLSmwWqLSzI51pqW1rbSU1hpQgz88rMvsnUdD5b3+OzZm+Jim3vQhhQ5qhY83l1y3ff03vP6yQlnTcvtuOGLz94VV+Nhy2tHL9HYis+efYKfvLBoZe6wK3IMpW7bqHm4l4is7BIX/eSM+8bJK+y84+31M27GLa8e3ef+4oLzZplLCBY87Z5nIyTLadNQGUPn3JR3znnGUveYuJODxUhHrs845WO5XrWeJ3e+l/hQoBjT9wwUy+B9ap2RwaDk292egC7EyfhMKeknOGSgGEmwxwO0WWa5GQJDSGz6QG00niIVjZwtLLe9vzMEVUracDg/A9IQEw4YvRi3gBjUaFXahWW2NDuTlrYY07lPcL5qMiid6+prfVeOaDLzq4hTOY3ViodnC+6tLLd9YJUdNK0WQ5riNlvq8UJIk/O7MZpVa2krw26QtmiPrnb0LlAZTZ0VV+shsB4CV5uR+ycNjVF85bm0cXrzIl8rSvHKcU1IiSrl0pGYJpdYke4K69daORElL3yM/NrTjs5FXlpVvH5WUxsxwBmzQ+qi1jxZO7a99Cl86bRl2ch3/srjjYDbruW1s4ZlZfj8Swtp96HUZIQXpufLfHnOwzzFotKTM39K8PJpwxgi71333Pae104b7q0srRK5cWUUVztP7zSL2jC00iLDuTAZ2pSaRwGPs6GN1CemKf9gzrvyt/4OE6bfN1j8wN6J08/vASimKAP4lIFfmaWJQWoT056cNGZW0rvZrbT0T4RZ4ljAnDZwfCIAru+EXWtaqVUcx6mFBd6TyoEqLGUoLTvi3e9X1l9e7zoBhintSSzFlEa1Uouni2y1bG+5nPtBKjUDw7KNUhtZnFe7rnDxAhB3mQG9upo+Ewcnx640Eh099qgRE5sQ0U2FXtT42w5dG5KPUjuZQC8M9nQh7TCCAPHQOdTX38bcP5N9vriQYxgCnL8k++KL7DTLZ49PZgfZqoY3fwKqF+SsAMsl6RtilKNsBZ/5wuRUm3Zb1HIFmw3++UYcRitN//Yl+ue/QuhHzKqh/sQDaVUCIpktEuLpGNazY67S80QDyHWxOp7P6+oIHr6KeuNTpD/1x9n92S9SPXyH6qVT0Jq42eGvtsTeZZlvmq7TFCJVbajbitZ5nBPnKZAicq0VwYt7qtgWB1aNmcDhmK2Q95uWfzfxgWxiuTndMc8IE5tR3BWBSYqqivQwA0WRj0hN1HoUYwuV5+V632c2Q8CiQtGYRtjFFDFKE1JkDOPk1nhSHwuTOK7ZeQGJIQWRuCktDGFwe4PgQEp6clAMe4xKRORKpfaupWHnerbOZYma1PpURpp8L6uKylScNuy5Lo6c1Iss0YtobaZBaQmrTa6hsrQgdUnIwGtRr1iPW5ZVm41AUj42MiAucjnnPMumZlXJLGIx1FgPA621bHMjcWEm7dTTcQzFiTLxaLPBLWSAZbXmdhATEv+SpzENLowTUBwzC2Sy8cTrxw/5Tfd/I0fVcZYhdtITLzou2lO+fPk2X3z+dVbVkqNqxU1mhIt733qQtiB9lnM+v93yVjakqHNz8dJvUmsjAHPs8NFzXC/57a/8No6rE0lFXU01XyWOquMJNC7skoeLl/n0yaf4f7/1/+U//uqXuB0G/Gnkj739Z7gZdjzaiFzQhTjN9JeHYV1X4tAcIq3z0wBV6iClXUfb1mK24TyLRT25qvrcL85W3/uj8MOMpCS/vj1QDFl26vPkTZmsIZVep1k+6vv8+Tmn99nEwuL5zCAWZtxFN03yrMwKn6TmMaZEZSp0GBm8nNvRd+z3DCz1jCHFyVG4HO/yeunzWCdLH9x0/Zca3kobQkqsrMUoaTVTBk9j8FlBUHr1CQtdQIt8DzkfZUKo8wM+BBqjOa6X04TTZXczHfOyDyHKIN45z1HbvC8Hr/t+qnss9csmT+bUxkxS6TEEvn7znPvLpbSiaU/yMYwcV8dTb8va5JZRSrO0i+leUumK8+ZskucXhi6qyLJq+cbNE5HKa8NrR68CMsEzeDEX2o47nncdm3HEas3bt7f8/KP3GEbHsqlRCCMs+2+wWaZczlNjmun+oJW+AyJJmoVd0uZrrTUtZ80Zr6we8Gff+0X+/Ltv82B1xUvLZQbQI1ddRx/85Aoq13lpI2Cpa0sdKhpf38nBIh9vmmoCku2imSZMfZ7csfZ7fAZ+SH1iStxhuPalqOEFoLjfQiNmFqwwhiB17S6XFpTeiT47nSbm+6XPyxeJYwjzpNSqNpNTqFJgMwgsDKTzpYn9zHoBc2uOMtYoQ9AkIKi8PvrEkBnJUm9YVEu2EkO1/brskBJtJWZ7BSjqPWZX5bpMkXzKs6cbs9zRas4Wlt4JS3aVe0hHijFQAdRMDeLbSr5/UxnayrDpHdaInLUb87mvxdG0tmYC7oMPvHfVcbqscSFysapwQZ7by8qgEAnpwurcTkdh9owCtYKz1uQxDBOwB2is5r2bntudQyl481wUP7e9YzdGlrVmOwbWnaPLjqxPb3p+/V2Fc4GmsTw8E9NFpcRox+bzl/J16MO+KdBMCEg+CkMc82OntZqzheGlVcVfenfDr71zw6PrmuPcCaF3gd0gbXsKEC/XQ3FdbRo71S2WMajPTGsxvxlHAZJVVe3lX5ZZfwd12/cFFu8Y2dy5Ae0BxdI/cb9PYvQzUPTZGXEapIUZ9LlRnE9d7qGIBtcxmdYoDcfZqKbbzTWEMchrZT1n57nXYYSTMwEU3/ra5Eo6XdUxCgDMTJ7sl5pljAXIFYBXmMBibpOStJyoKgFxmw16tZA6wMw0UlWkrkednubvoO6wh5PByzStY+b1OyfrSpm53O3g/Jzw9EoGFZ0jjn5iFgG01ZijNrujirGLPV3cMcAxq8zunK8wD+7JWXjyHP98QwqRsBtpjZYWF86R1jcoY6TXpdJwe5U3lsGYVvIzBDlvbpzbmMQZeKvjE3jtVXj0iLTdoDa53+XFfZQbwTvUZz5Lc/++uMoW1na5JH35KwzvXGXevxZDnrLNIuGNQeoTH70jwPPeAzi9uMs8KpOPdZTry2pYHaN+8jfQXt/inm/ov/pIbtJjEIlvzIxt4s5NACDmmZxSmyF2yGq6xF3up1NVhspq2WUv1snFqey7jQ/rn1gGnPsmNvsSVFKarPMBgYmqmEeEyWlxCD1Ddk5c2BaFogv9BDABlnY11VQp9DQ4HeM4NQC/aM7Z+Y6d30mdT3uPd7ePGLzMxnsKCBSWwig9yeLkBq+wSsBc1HmwjPRoq0w1yVFjSnRemMZVVXPZbziqa1bVYnp/UVXcDgMPVyeT9FApTZXbB9jJmEeOjVZiCuOitN44qZd58Bzo/cD95RlfvnyPlBK7LCUtAyh58GpOsuTU5TYdxWW1gJ1VXRNiZFULUwZwMwxc9R0xwS4PZBfWctw0+FwftnFrnvZP+JXLL05gWqGwprozYfC127e4HW95vH1OnyWdSmlaW2O05vF2y59771c4rhe57caCzdix8wMnTcNPXFzQ5bYFQ3Z6fbrbcd3107W9sA1KqYkVPmmO+K0PfxNDGPjqzS9yXB3xYPmA0/qMRjfTeZ1kW/nxbbVloZb87MOf5vH2ikebDV++fE5MGQTE2fp7ut73ZkX93sw7zKx+6Qk3jrKOqq6miRnvQ24Lor7ngWoBimXCZdqnUif4IUAxpvg+oLj/2ZBzzCc/SbYL+HBxdrAUR88aF91kIJPy5EphuxSK4+oYn42kVtWKSlve2z7OtW6BFNNU2+iCvzPrrJM8+3QSR960V3+nUFRGBjIuOEoPz+O6obYNG9dnt9FmUipUWrNzjrPlSa6TFQagMPriqjrXBmolQKfk4CpPPPoY2LiOe+0pz3Zi8vRiDirknnpUC9h0WWp61rYzoMw5CHDRtjxcnRBJPNtteLbbUVpzGKVYVFWeQJMazItG2iTtfDedj3zgUJk9N8rgomcIAz6f+/LdVtWS147v8d7mkvW4o/M7dJlcCw4XA588fZWLxamwtroipsCiavny5Xs82mymCa3T5mSa8CvnDmDjNjzePWNZtZw3ZxxVK2xWh0zAMWlQWQGDYWkX/OS9T3M7DDzd7fja1RUhpWkSSwaqd2W+ZV0F0BT2Yn8CQqRvPrcLMFO+7dc7fk/PwA8BijG9vz3GnRrFvfrEfaBY8iqkWXZagCIIACzy5pC/Y2u09AYN8zJiaiPGNVrBSWOz6Q2sKpkkfud2mAxvUgGpSVix/eGnKGkStVEkrXK/0AJK7zJlKSWcT5ja0FhD7wKLxlAZPZntGaMZXeB4YSYga5TUrukXwExMAr5Skm0WgEneh80QOF0YbnYjKcmkt/NxAroybFYsGysd32KaXFZ1vv/HBG3ui3i8qLg4khY8V9uRm+0oUlEfpjpH6Rcpx6iA2BJFObR/Fzd7LFq5WGK+Xs+XlsG3PF2Pcr4BnRInrREzo5D41L2We6uKba5nTEnMib72dMfVRp6ntdGcL+7CKCkViPQu8nTraa3mpDWsan3nvAGULrIRsEqxajSfvr+ky0D18Y2oqkrri30H1bKtOf9m+fN+78dStzj3dFSTPHWWCP8QwOIdRnG64aSZASyAbt/xtADF/RrFYjqSEoT9HoqjgAyXDW/UXt/Fsr7iaNp3M1s3AdLM8B2dyuvGwNEx1C1cPiWt1zNA63MrjvJ3YRuL2Ux5b9+lq4DHvs8gKBJ7J/WIuW4x9iP6yMoyxUCnyj3lirNqAakxyt9lWynNLqsF9C6Xc/uOthU27/KS0DtSn8Ho3gUUnccsa5RW+NuONAZ0a4mjHJ8UI7oyQI2yBnNxCrsdyXvibgSjSYNDWY17tsa8UYuBT9uSlkv41V9EXdyfXUxjmvl1awX4FWmwSnBzKeeqqkWmenIG61vCW9/EpCSA//Ipqe8FHK7XqM/+BOrTnxNAWCYWtEGdntF+9iozrjsxxykuuKfn8vp2LcDo9U/K+4ulTD6kKJJXpTOjreQuUsyRMhutX30Z032LAMRNL6wtkLL7FYjnEOzLCpic45pjMy2ffBCg6CPez05UKipspWmNmmoev5v4sNqoAhT36xHLILWwhXPtU8r7ngeASeRPPjpp+D0xF8WEYwacMmhb5j5qAhTHOOb3ZDBbm5qT+oQu9IxxpDWN2PS7NbfjBqsNllwDNdUKasbo0OjJcKY4rSakf5H3fmIgtuNukgb13rOsKursvNg5x0nT0PshD1albuikgcGPNLZGlcFBjFN/OklvPc3Gl0HusmqpTcWz7oaTesmqXvJsd80uD0Cn868gohi957itsVpzk3u1NcZMDqshiVmOVuKeelTXuCgmBWMIVFp6Per8+YW1bHPvx8bU/Nxb/zF1bohd6ixH5Bp9eXWf0+aElV1SmZpa17yzfsJ6nNsA7JzI6scMAH30PNru8FH6Mvbe89JqJaYfVSX1qIsjQopTjRdk0EvC5Xo1qy1vHL88GQ196uRNNm7D0i5xMQNfk9sCqXlw24deGLHoscrwmfNX2blvoEbpgblvT/5BP0sYo6XxuJZHsDxkRRrXxjS15ig1jlV2efQvyLS+2xyc6oI/gBWcgN+eFLwwigXMzXLwlB1F5x6KPi8nEzRzP8YiQV1Yqe0dg5sY4yJbTUj/06VdCmhUmpVtqXTFzXjLehT3a6skX8p1JI6FbmLB9uuwNHKbn2ojtaEfh6wASAy5N6HWhjHK5MhxXTOEkcbUjEEcVldKMUZPre00URRjmByMZQLLTCqBMhkiPQo1N8OWhW1oTcXz/uZ9OVjChcAyA8HbYWAI0huxOIgWsxyQWr97iyUb1xNipHMOqzVb56i05uluxxsnJ6zHjtZuWNiGr958g/P2JNcj3gU5Jk9wFRMwgM14k2XilsY0LO2Co3pJ75/kHBi4Hm6nOuP1uOMz52/wiZNXscrgM/hXSnHWHEvNtxYjsNp006TCUXWE1YbO9yQSr64e0IV+MjECJgMegKiApEUpotSkEHn16Iydc3TAehR3YmACimkPYKkXn4HWYhfNlIMhux2LiY2f+qaWSRpjKkJxcP8u4sX+iQXsFdCV0r4MVUDhLD+N098hs4Mpze+XPopjrr8rDOKkZMjbaq3JjqiZHXwB+DVWsarMVAJRGWH4rnvHehA3TrRi9LKPxVhl9NlRNNw9FkqBzsMsyUdhE30GYmNuhaCQ+sXBB5QyxCT1fD4KsClGe6XdRkwJYjbhm64JxdKqLL+V19rKYDWse8+qNtQ2SyLHgAvvH794H2mzkc4219TV2Um0XDt1BizWKE6yY6gPkdEJQCzuqTfbkeqkZd0L8FpUmkdrx4OjikrPzth3j9ceUEyJ9Rim772sNPeWlt5F3r0WDNC5yOXO07nIzkW2g+cz9xd86qKh0mo6v0bDxULkqErJ5xobGLyUGR3nvoq9i/gED46qXFMp7XxSkO+7v593WOM8LL04aqY2K93oc9uN/f/5XMWEKbwHkn9ta/Zaa8x9Fr03+Wd8If/UtP5vF98TWEzr53fvDHff3QNA+0DRT/LRO0BR6btAsbCJu1swe06ZpbdiWZ8t0szCQjpZpoAlrWCxmhlNY2RbYw+318LQgUg7rZ1llNvtDAwLaEtpbs+h55lDgNR14iKaT4jYXmpwTuSc3sv6S71j284mOfuSU+/lOxTZaaGs9rcJ8tnyfYZB2EUg+nAHKAICFGtL2A7EwRP3CqmVUbjnW8yqIbmAOWpxbz9FWUOKkdiNmKMWXc+F6aEbMUcG9cYn4ewCnj2RbSoNJ+czY5eS1ACWwff6Gt5+S4yDxhH10sty/pRCPXwV+9edCZBLifSlL7H94rvoRhjWxRtvSK1m6Y1Z1/J7u0C1HTx8bTYIOj6VPppuhOZE3ivXzepEtuG9mO94n6+f7Qw0j09guyV96VcIj5+RxkDYDeIgazS6skTn8+WQ7vR6NEbkG0orVIIUI0qZaSpLWUOlFM2xlV6WIZJcxHfjNFuktaHr3j/geTE+CCjuG9ns2/GXAeo+y1EGr5PkNIPLnd/ho2MIA2u3pjUtlbbEVDOEIa9fpKnlkRKSRyvDGEaGMNwZWNZaPrd1W3H2Mw1aaYYwcFIfEYlsx05knrYhEbnuRY7l0syklNooEJmYLg+AJP0RV5VIsWJKwiRosWJvrZ1nhL3UJh2biq7UUmaJTczbCCmisxGF2hv4lZoqhWLjOnyUdh0+BtbjDg132mQUsctRXVMZAXydm/uMiQTQ8HS9FoAYArW1PNvtaK3Fx8jtMLCoKo6bZjqmfQgsreVnXvoJjutjvnz1FkYZHhxd8IXzz7O0K1KK9KHnuDqhMQ1DGPj6+i1++dkXedbdZAfS/z9p//VsS5anh2Hfsmm2Pe6e6+uW6+ruMd09pgcDkCBBAgwZUlSEnqgXKPQvKEL/jJ75KAlSQAyJDAYJAdAMQWEGY9qU6eoy1x67Xbpl9fBbK/c+t6q6h6FdUXHP2WfbzFyZ61ufk6l2JKKSimpD0lh9vdvh9WY7lnUfVdVduS5j8JEqAAbvMVEaE1XDBjuGC2mhcFQc4X79YGRoZ2qGStYw3qCxO7hgIZhE7zts7RaDH7DQC2ztDv/m9V/i680VhlRv4lI4kJICNknV8oQzJ+sJQV49mhgk6ZXko3dNJuawVHI8Lqz36FLUfw4D6Pt9iNNvurVu9y2MBske48F4yyzSHRn4AVDM7D5A/kTrzQgSuxRQk/d/ZhTzmMi+VB9d+jt540ZmKcnD82cg3xGH8Qa7JKGm1e9hn/qJmJJ5KdlQpNL7CFpcBGhxif6liU/rqB8xS7woxZRjSMeajxE8xpHVLoVCn7ZXHss8kuzVBT8yZRm0MMYgwEd5Xp8YTME4hhiwS+d4H/Zy9XyrtUYhBDpHEtk8BvPnvO5aVFLBhYApY3ix3YwS2tY5TJSiSo4ELHvnIDjHo+k9zPQMG0NBexwMMz0bZbMRAZLJ8fza2Bav2tfUPekdTqsl+UsBnFXH+NNH9ejf/sXVV/jk5gZlkuI9np1DlmL8boJxuOhRygLGO5xUy9FHXgGj/L9gBY7Lo7FTs5I1ClGkRcEejtNiyeCH1I1rUckKgx/w8fUXeLVbU7CVtcj9lodjcJ+CSmMn121kD2IIEVywUaJPzAVJDPM2Hbwfk1djiOCcYxh++xjsHe6oarJ09NBPeMguZhCYZaDfBRRz6qkLEV1KOk1LQMTcYc9O5YL6LAPNTFT+WIIzFJIWrA5ZpN55rAePUmZbR4ASDDrV+mxTmMtBrTYC9otimT3jADzIi6gOAkyIpafwkvyajOXQF5ZACo1rGn90/GY2kDPyJCrG0vr/Xea4t2Ffj+GJKaSQsD3blfd5WUgK3LE+ySLT+Iu0fW53BlrljkWJi3U/htIMLqBUxIrSwht9V8ElTqcKy1IkbyGBdMWzEml/GyX1IeCydTAuwLiI06kcF7/OphI/fWc+Vpl88qbB11cNhf4AeLQgoJiPLcFp35TJ23hSyxH4VRLoHHVqCs6wqCQx1yBGVqdQod4F+EjbvrcRnQ0YXMCkEOhtwBc3PdaNgfNh9IAeeg6zDzTPHYnBZ+NjAIzXwMPkUwAoSzn2I3sfEtMY07U0Yhh+8xz07wwW4/b622FnjG+xiW8zigko+gQaY9yDCX/gW4wBSFKmMTgl3/LPRUWexWZHj3eOGKvD92QkJ0Q1Sa9pgDcvgOmcQEv2HKbAmOzRGxnF/G9+3wz6MsDb7YDlkiSnyVvItQBbLulxZUmvXyUZ6vU1PW4Y9uwlsH9vxvb+SH0gk+R8X8dhDAEcpQjUdh2CcXuQGMmrKGqNMFiSmvYWobfwaZWGtmsA9J71CoOFvW3gLaUyFbPkL+QM+sES9prePxoPv20hzUBg/+ycQN9uA7z4kuS95w8BnfZPt9snnjIO3NwAxiAyBrx+Qdvl9WvAObB33gHmy+SrlCgeHcG3Bv6vfwYxDMAwEEiNEwLMm1tgMkX85d+Cvfs+7esQ0pnVEyCcL2nblBUgdTq+DCWtXl8Ab94g3twidAYhnfDAGEJPPZh5+9yhD9OJM1P7+ZYHbFEqyKMa6nQGfno87iv76hruZr8dwei1nQvoBw8zeFgX7lxUvu32m/xRh0Axxlwwcch0hDsSJZ7EGi7aEQyGGMafKS3RjBPW7JPKvrOd3Y3S0851I4sSkseJa46SF5hr8vVc9zc4KpbYmRY2OFjvxi43G+woC81JivagOiCXaAuu4WPATbfGvckJtBCjDE5xjtN6BskFKlkgYkApNaaqwlW3huYCnRvAGE2YmSdPkPF0n/WWJkSMjcmoSkhshmacVCsuUAgKAnGB2Iw8PSV5XsRESfTejX6n3rqxKylLnIq0n6nA2eG660Z5Vl0VFDjCGe7VE1x3FG3vQ0DvHG77DbTQ+J2TjzDXc4TocdFeopY73K8fYKmPcGtu8OvrL/B8+xqN7TA4QymRIVAIQUrS7KzF4O+G/ZSaQKr1Hs83GzxdsJG1zTLdzg2Y6woXLYVdEbPCRu/ci91LPJo8TDKtCqUokZM8V2aNi/YCX29f4eXuGo0xGFKJOmdslBICSL6gME4C8uRp7I0dGQSasJaVxklV4cFshkfTEyihsBl2+GJ9jYuGgpcyA+UCrayawWIYzMg0/rbbtwLFNLL+LkAxV2MEhHFsZbYxT01NMDR6QxjBII3BfaqpDRZ9Co1x0Y3MfmY/GGOoE2CMIDXAzXCDSpTk/QukHMhjkDzKbkw+pW2U94ODDcR2Z7C4NVQurziH5goODpJzHFdTSC5p8cVb1KpEITSuuzW0kGMfav5XCwWTAI0JFEhVsL2/ijGGTUoj7dwAwTm0EEm2OYzyuywl9MmnPKRt1js3LtbkMehCQJEYRZ9Ay+16PRbWT6ti3AYPp9NxDA7eIwxD6qUMOCqWEEyicQ3etBcoBAG0MajG92lxwIGDY9VTkihnDG/CNQqhcdHcwAWHJ/MHmOl69FXen0zROoe/vviCPIze4tH0HipZwgRDnmlZ4dPbL/HO/AHK1JmaJdC970d1hBbkF6ZjKqJ1LW76Fd40N7juduidozEIjGMkj0GS3ecFiIMxGA+vPfS6TFDH6rIscVrXOK2nSSHR4XXT4LYjOV3uv8yycmssjHF/pzHY2Rj3bNH+/X8bUPy2tNNDoJiDbDKjmNUfY6In9iAos0wujXsfiA08DMcJEZhpNoIdGyKuO4tScphUDp9lqEWayLtIIINkkhgZPevp80vBwQS9dmM85mniLzmVZAhBKaOcATrSOC4V9RSuOjvKUWkfELuXA25onAfIKCDfCtrbpdRM4yksR0mO7eDRW5+qwNK2B233UonRuxh8HD1ynO/DxQSnMKAQyJe4bc3osasqNe7Xk1mJTUvzZecjujQ34wyoUrDPbvC4tgGFYDiqJJTgd7gTUlAAF50fZb6vt7QvXm8tnA94elRgVpDHWgiGk3mJ3nj88vUOxhN4fbzQqDSHcRHbwaNWHB9fdnjnqMBEc9j9VHxkMAMi+SgZS6CfmMhV53G1s9j2FsZ6uIMxZn0Y54PEiodxISYf+4cy1PyejAFFIVEVEvNaYVZRv2RvPG4bg6a3I8uYn0N1GX7cR7/tEvh3Aot/pzCb7FG8E2qTPIqHbGMOQEmexOgt0Gz2QM8n3yFAgCS/ly4S+zjQz8NAMsRcu+HIl8EWx/T4NgGt3ZaYr5tL+j0Ds/mcWL/sQ8zpqkLQv0Wx9w1KSUxeBpG0Z0a/YjAePMZ9nUZmwbwnYHToj8w+yBDo/auKXisX2B98xrjbjT2NABC7HnHbgC/nQKRJH9fJa2Uc3LZPNRoeIU1AhUheQs6IhUySSpt8idYGdD0ZeIs5wBSdkfxugJyV8LsBvulR/P6HwKN3SAIMEDPXNogvn4MdHRGjOFvsQXwMwHaD+PlnwGIB9vgp4tUFsF7D/ewTuJsdgnHQLy4hH53B7wYCaIyBSQF3vYN49Qp4911aXNhuEC/f0OZ/+JQYoHwMMEbvDSD+9V+APXwMlBXiF78C+8M/pRTT1y9JxmvMKD8WiwnBphCAkxPaH/n4iHF/HPQ93KqFW7coBaclphhTaJACLxTYD74P9uwDAqg8sdnBQ1++hvqrv8Dw6XP4pHNnWqCAhi4DdhuD8FtYxd8GFHOH4tugMSDsxw+QGDWSnho/oPPkt9nYNW0PTpI8kzxQWugkSXMjo2iCQSUr7GyD3vUjSKSuxICjYgHFVWJAJDZmi0IUuO5v0+eNMMHipFxgZ7uRNckT2FxEX6sSERycBUgusRl24wo7ZwxTXWFwJgXqkEQry1pzb9vOdqiTZ4omOMRUsTQpzuykEmpcoc+f0QWP9dBCcQ7jPfXIpUCMs3q2X2XmHAoclgWsh4FqNLw/6AAkT0ZmLdbDMHr/siSy78j/NKtLKCnBwNBYi2VZUnKq9/jpw/fxpw/+GFM1g+QSrW3wvHmOn119QosV4udwwaOx5H1ywcEEh5uO6gDmRYnGmrE7cWsMvA+47TsclRVNGq3DLKklVn2PSimcVBUKIWG9xWXbUGqekFiWJYY06e/T/lJc4OObL9F7g3fnT/Cr9Zf4x0/+Q7xsXuLL7de46lZjEidnDCdVPUoeH83uYWe68TjK/rtalujdgIu2wU3XEdOYtmWlFKZao5QSP33wu/ho+T1oUYAj9SrGgMvuAv/65f+Iv3z91bjtSynBKgat88TE/NYL5Xex+rTy/S1AEYcBN35kEzMDnX2JPiWd9r4fARotktC2zSwUjU+qMjDBQnMFEwbywyXJaJZNzwsK7+o9nedyh98qsWER9Nh5MUXnhnEM0liyY1BVITQBSEYhTI1t7ygIKlnAJD9kZtgHZxBjgBKKxmcIqFJ3Y050VVyAMdqHnbOopEIlizEIJjOLzjtsDNViZJaytRar0OOkqtGkPIAM/gbvsTUGgrExjTgvJjBG3si8kBMicNO2JFd0HkNvaFG1KlBKUtU01qYUYIvGWvz4/DHu1/dQJin14Gn7v9pdYlHSNq9llRbP6JhoXINfr19gXkxwf3qCm26N1bDDy+0a110L6wNebDd4NJujMbS9GKMJ5m3f43Vzg3fm98EYw842uOpWAICz6gSPZ+cJTNL5OqdO//z6MzyYnqKWFb7cvMTvn/4A1/013rTX2AwNrLdonQUDME/jPcSI02qG3ltYbxOzhhFc987hpu+xTWMoB2lpIVArhVJKfHT8GE9mD6GFGhcWYoxYmzX++uJjfHJzja0xYAAKKUcpOHb74+q7bll6epdV3Pv+vg0ofptfcV/pcHB/3PsT86JNBovigOEXjCSeeeFtcNSTSK+Rqi4YMFF0fWmtQ4jEIErOsEpVCRk0LUqJIbFR+T6bXsMF6lXMXkLJgc74pKLJ4TN0PGd2NYQ4LmBKzkmmmvx++fUjYvLNZfmqh5aCWN90P5BAsCc5pkyl7pEzGBuwDRbzSqMHna+UTAsxPqIdHIX6pQXxrABhbF/J0Qy00LVtTRp/1F3NOUNVqQSyQR7HUqLtHTrj8OzeDItCjF5F4wMGH3HdOBzXEsZHKIHRIxkB7IzHF7cD5qXAwzn1Jq46h4t1j21n4ULAxVrjbF5iSD2VdK5l2LQWrzcDnh3TeN8OAVc7CsS5N1V4vNAYfESfQn4mWkAw4JcXHc6m1P349drgo7MSV43DbevQJNluth7lzssYybdpktVplFUHAp6DC2h6CtthwAi+pWBp/3E8Palxf6agJRvVGCFSRcenFy1e3rQYkspQSg7GJLQW2O3Mbx1/wG8Bi3F3kx3LdMfhFfVtoPhtHsXgEb0npvAwgMT2KaGSEehwZi/3dG4fepPTN7VO8ssUnNJsCSSkzxHNAFaUlKw5dPR+1YQYyKFD3FliArMPkDFgtaLvMAz7bkWl7oLCfH/+7vn/1epO4AxjoOdWFT0/S08z6DgEyVluut3S4zPAbFtgsdhvAyHAOEd0jv7tBwqxMR780QTx8jZVZhgCgqnCoZgUAGeQ84qYLLFfporGwV5uYR0lZ5F/LkKnVZroAsqnJwjGk5R1PgOve9r+sxntq3pK++XFl8DRCdjv/UECv2m/M7YPt5nNqdai3aWaCoG4XsNebwEfEAaH4cUt/K6H7wyY4PDbHureAvKPfgSmC8Rmh/j8y1QTAmJqXz8H7j+m17y9pvfNwHGxQPz1r4BhgL+8JTB4e7tPllUKWCzAn75LAUgXrxC//or20XQKVBXYySnwOIFUzgAuoKyBMsM+TOn2GvEXf0vve/8+2JN3qbrlzUvqiYyRjoP1Gv56BV5pIESIaQn5wVOgruE//gzi1QrqqsHt6q2KFXy3P3E/BL/Z4XYIGrN3Kowgi+MwGVMyiVt7A5OYNYAmqiL5iVrXIUQPzgQ013BJrrQx27HrLZd7l5Li4jPLMVUT7GxDARzJJxgSUBSM47bfwMeA1vaY6Iomp1Jja5rxxDXT9ciKsuQzFYzjTXONeTFNq5fEgHLGMFETtK5HY9pUJpzYEkTqjkuJoZUscN1tMNVlmtxGtLYfkwUjaHLM00o7Zww7Qwyd8R7vLWu83q3HSSlnBO7abkBd0eRrWhJDJ/leEjl4j6u2HRMCnfPwKV00hIDeOjxdLoiBTDH/1ItFHq7WtZiqGV63r/DZ6vMkJTMw3kHyPskDA+0vQZ7I88kcxttxm2bAG9JketV06J2HdR5C8BRSovHB8TEKIdE5i/XQo5QSSgiSyVqDWiqUUsN6YiiPqwJTPcG8mOLX6xf4evMaq76H4v8ar5srFEJDC4lCapzWS/zg+COcFMd40bzEL28+g/EWM13joT7DeX0Pz+bPIJlME2eSO5tA/XU2WNz0t/i3b/4KrevxbPEI783fxc42WO2eY2t38NGjsR2u2hVe7W5GEDwvCvzk/nuY6Qn+v69+iS/KFa5WO6xW228dY51r4l5i/Pb4+w6gONbVEDvoEquYx2HuV8y3HAqVK2d88CPDPfhhlJ5KJjDEAYIJNK69IxE3waIQGpKLFE5liUn0PQZv0IQOkuekVAqyyb2agzeUUhw8tFBoTDuG3tQ5zRpIEm2Std50a9SqQnB7kKoFHROd7ceOTBeociYED87FOIXQXGJjSApqPIHVNvZYJKBLHa9s9PGKFI6Tma/ZYoKLZgeZ7qd95dD1BnVJoTbTsqDnMpKSsTQGrxtaqBEp3Tf4QKAFxDben07hQsBEKcyKClNnUAiJma5pWwmSbF50l5ipCT48enfvPUrLSJJRr+NETvDh0dPUmUrs2bpvcd21KfHR4cV2O9bUCM6xMwandY0/vP8eKllga1q82l1iomjSettvcKmvcVadwEeP9bCFj7TvhmiwKKb4cv0Kgze4SnaV234DySVU8hY/mM7weHaOqZritl/h+fb1uDhTV0sclXOc1/dGxQBjDDa4MQXbRY+t2eKXN19gcAb3pyd4ND3H4AdcdddoXZ8AU4+daXDZNqgUVZhMtMaHR2eoVYmPr1/idaFxs9lhs26+McbeDrLZb+fsD/xuoOje+n30Mx6CTOwTT10CU9nrGAGYBMYkZ6PHnAK9qBMRwAgUi5RG2pkAK4g17B0BGkoITtUWkWSg696NoKxMiZ6CM7SDTwtRHGUKwMvXOIAWS1edQ6k44PbXl0JxlJKhsxSukr+L5HwMtCGgSdaZdnDQUqQKkIjORCwTs5fTYLPHkTMKsRkcMYrTpcCmM5CCo0/jrzcOw+BQlrToU1eK6jsSeGSM8hk2jRnHXwaVh4ErJ0cFvI+otEBdSFRaQgtKC7Uhokifb9V7LAqBexP1jbOz4OS5nCiO909K9AmUMwZsOzsCRWM8rm2PdnCwqauyGxyWE43ffTRDqSgV9eVmXxNy0zhMtMX5VMEGAmMuRAgW0MSIScHx1e0A4wPWDc0vNh2BbsmJDZ5NJe5NFSZaYNN7vN5SoE+txRiIczbde57zPhmSpzVEYNN7fHHTwbqAk1mBezMF4yNuOkfptQAGG9AZh21noZVABFAogfNlhVIJvLxpURQS63WPzeabc9DD229nFr8NKAL4OzGKh0CRjgT6uyoJxPUJ8IWYgGGqu8h+w9yj6D118OVQk77bv5b3YIsjmsB3yXeoNLDbkOwUIJYu9x3GuJeUDsNdiehuR6+bfY1ZMso53RcCsYldR1USACAExCIQ2MvAMKelZiAo9qvD42Nms5F99KsdVVTkqoeypNdTCuh6RO8Qegu36aDPFxR4k7YbExxuSyEs5ckEsXcoHh7BbzsEziCmJcyLWxjjoS0VyAdPZa5FJQmIJtZTHU/otZoB9sIj+gvwSqH88BEBxs2K9o8Q1EEYI8Zak7yP8yJA9qbO5rQPNyvg4gJ+N0CdzMAEg7tpSAbbGvIIRsCuO5jXa4gvLlA+u7dnW1crYD4He/ddAor1lD7H0Qnw8mvE1y/o85QlscbrNcQHzwgA5u3a97Ttt1vEV8/BdmvErgOWS9r3Su0lz7ogCWveZ0JRSFIGxPMl2Ok94ItPEb/8EuHz/wr2ege/60ewLRc15JNziHefgn31HH7TwVxs4LvPIJc1RKVRvX8O8Av0w3eHbBz6l77No/g2aPw2oJgDRSIiClFi8D1a14zpo61r4YMndjF1KPo0CQQDWtegEAV2thm7F33yQZ5Ux+SHSj2LhabHNa4FB7EU62GHbM6WnJgqFyjBtLU9BOPYDDvYEDBV1N+XJ5yac9SyHMM4WjegluS74ozhuKJ0RBoS+8L5zFJlCWW+GW+xKGrYQGEXt22Do3I/Kc4l44IxGNBkwniP9TDgfDIZJ9A+krdrMwwYjMXJbILGWjyazbBJ55tlWeLlZkNSqxBgTGJSnUVRaJSlHiVZy4rCY8hnRavIhRB4MJ3isr3Fv+z/DQqhxs67/L0KqeGDTyvhfASNtOsIbLnosEsT0llKiNwJg6ajz549JX1vsBEdLts2sYoCAZRIOi8KvLc8x++efh+VKOGiQykqXHaXeNNeEhBXJd5bPsa63+LxrMC8mCQmiY19mat+h19vvsCtvsHWNrg3OcZNt06yxMQW8WKsJACop01HjRADKlFjoZc4r+/hV+vP8fHNr/Dzq3+Ol7sdbrsONgTMUsLsh8f38cPTZ/j09museuqJbOzHOKkqTLTG75zew8/B/k5+qXzLEu/fxChmoJgDaw6BYogBgssxUCp/R/KcZW9PTIxkSMeag3H0GQc/wHhiofJYX+gZXHSjP3CiarSuG3/3IdDCSAKBIiWNDqnrsncDMdqmhQ1+TLnNrFXBJWpZjtLw3lvUKSl58AbLMqC1XQLLtLijhUgLFWGsx8iBOzlhmMZoxKptcFZPINL5vpAVmsQqWu/hvcfgHFbDgPuTyejziwdj0FiHo2mFwflxDHIGzHSBl5strHWwifWPkQKPikKNEtUYI47KEjtj0FqLN00DH25QK5UWTzR2djeOq4Wej8dESOdChH2Sc76vlomZMC0u21s01uKorFLgSY/brkNjLQZDx/626/F6t8MXqxXeWSyg0vxhNWwx11O8M3+I8/oEpSzBwLHQC1z1V7hqVwggRnheTLAZgA+OZpioagzxGpyFYH4EoPOCjpFlOcdmaFKwUE6vlXcqb7igRcMQPQoAUzXBXM/xYvcaX25e4tObV/vv4j0mSmFRFHg8X+Dd5T18tbnCdhhw2TSUTFsUqJXCe8slgZFhv4DyXbexxy+xLr8NKB5KUA+BIu2zmBJO6bVzuE3+W5ZWUvBTwBBTv2KgSXuIyfceImYFhdl0lkCRZgytDTBJ9udDHMFljKliwydZJmNJIklA0ce4L5lPQK0UDCJ56wYfYWxApTgEixg8w6REqqHgo99QcDayqTnpNCTGFAGYlhJDyl9oB4dFraFSn6LmDI0JBOishwvA4Ki+4XhaYFLsfZuCMzSp5282LeB8wMmsRDs4MABVIXG16sZgFZ9ksMZ4lKVEUciRHZ7XCm3v0FuPm10cpa1PTieYHdRiSMZwPlHjSkIEXY9jwAivskR5WtAi1W4IuNxa9NZjVikwBjS9w7Y1MI7kmDFGNK3B7W7A61WHe4tqZGJXHcOskHi40FiU9JqV4tCC4apxeL0lRl4J6lAMMeLBUYVKcaq1iRgB627wSfZNXsp5KdAYWlDIx2f2oOabSIsW+XitFces4Hi5sXizGfD8usWutxgseRGLBLZPZgXuLSpcbnoM1mPXkfx2UkiUWqDUVXLI/eagt98OFr+Nnjz0KI4g8S7DGEMgoJjBWfaVcUHMok8nBjsQyMvArqz275ElocMuhdSQh22sYmCMOvLKiu4XIpXB94htA8QIpjVi9h7GJDfNLCOw/1yM7UFdTizNktE8kcxS1cmEfp7PCWQwRs/JYPLtBNVckWHtviLDWsTNFm6bJJF9TyA0p6cm8MkKjdDQRNjvBrA/egxcXSG6sJeWhgg5owk2tIA8P4KYFvCtQRjsqFP2iYKmzhVBSag19TAywYm59AF+24MXCmJaQExK4PSUSumzBPXwmMggMQcJ5e04pDAiZxEvXgN9D39xA4BCdszFhsDSu2cIg4Pd9aNvMlqP9vUGftOjfO8M4mhO4Lpp4L/8GvzRBXB0BHAOdu8BeSdXK/ossxn9f3oKhAAmBKJSBMyXSwKM6fd4c0P7pW1pP56ekj/y8bv7AKbMJudjcnMLvHqO+OknMM8vIUoFce8Y7NFD6OoGOD4GOznZb6sFfU7xez9BZZI/1wwkj5YScA7V+SXOl5//hiH4lgoceyD47aAxjo/JE5f8PM44ugNWwgQKHmldR5MDrsCQVxVpPHSuA2ccjW2T7M0lhlBgpqZQXMJ4g6majH7HnW1HCVr2KQLYd40hXbRyWiuLo+QtMx0iTXCy/0bwEq3tUafV9nkxAbPk6cuTWvI9ilHSB2BMUA0hQnNKWbQxYNW32CZQ1zkHLQy0UClkJHcgcnQpPn/V9/jpg2d409xgSIyFTZHy07IAZwyFEDifTDDVevTgjauqNqWIOg+pyHMyUSoFuRDA2xmPXT9Ayj2zeFxVIzBsEijOwRM+L9QBaYIaDwAGMbEb08GHgJvkG+KM4bbroITA2XwK4z1uNw1CCCirAiEE7LYt+t7gbD7FWV3jfDKHCw6f3rzCathhoalU/YfHH8IEg9WwhQseR+UMy2KOWpYjIxZkQOcGnFZH6FIZfE59ZODYmQa3/QYPZ/fwwfJdPJs9S9/Rj8cA0mRiY9Z41b7Cv7v4BT65eY1SSjydn+LZ4hEKcYk/eXiMx9MHmKoJQgw4Lo/BGMNP7/8BrKcQmM712JgNFJewweHJ/AL/tv7sO8dfHjvj2DsAiuPv4zj0I0ig4JZ9OE0esyS9teOk3AaH3vWjbDTXG9B4pX3aum6Ur9pgU1IojaVSFihEARYYhBJjnUZeVMgAwAViPF3wYMlTwxhHjlwHcCDXJD8jpaTyEZy54BBsj4mq4KPHvJigsTwxgDapB1wKzthXLOTE4xBIhpoftx76cQy2zqJwAwqhYb1D62h7lFJiawwigO0w4E8evourbkVsYRqDIUZMCk3hPlLgwXSGWZKQ9o68w4yxcVHEOw+lJWTqXsxjxSVpbGMstBCYaY2J1jirjzBRFQpRfOexIZgYz7ecMZjgx97Lq25FcuqG2DPFOS7aBqWQePfoCK21eDFQDUFdargQcL1tsDMGz5ZLnFQVZnqCxrb4cn2JR7MbHJVzMMZwrz7BznRpDJK8eKIqnFbkR6WwMpIYL8tpCjai8+BtvwEHQ+t6bE2H02qBx7Nz3KvOwMDHtGqA0jhtdEkOe42Pb77Ei+0WpZS4P5ni6fwUM73BUTnHSbUYF9WmagoGhh+efDAunNhg0dkenHOEEPBgusLPipe/eQzGDHbugsbfVJWRvYRvA8XMKsZIfYZZXurjvu8wRIzese4goCV7DvO4rhUldOauRJNqE3KPohJsrJ8IMSedsjvTqBCpRoExCrDJvjeVUkpLxcDBMaSe2VlJypdlJVK1A1KyKmBcSOE0+9fP9RjOZwkjJajuBosuLVQb59FaAj/eAW0CT0pyksCGiM54PFyWuNq5kXHM1RxlSWFXUnCczArUhcRg/UFQC+70/2ktIARHqcUoV3WJhe2Ng5Q8MYsC92cE0CrJk3/2mwmogrHxb5wB1oVRVXC1c+hdwDp5IKWgkB0lOR6eTNBbj4tEXpWlRAgRt+sebe9wflRhVinUWmDdO3x90+JsXmJZSTAGLCuJnfFYd24Ep5Xi0FKmhQE2gvxZITC4MPZhUqoqw5ASWBe1wv2ZwtlE3UnaR/7OIaIxHm92Fs9vetw2A7QUWE5ISlsXErNKYVGKMUhploD9985K2LAfM60NY4APLQD8Zjj4P606I74lPf1WoOgRU6jNONn2B4i1o3CaGDwwtONEBz6BuAxEgRRGkxhBs6+qgEuVGFJRRYZ35C27vUa0hoBBCqaJm83+tby/m1Cak1C93/chxkiAIgO8sqTXyiBVa2L2OAe7/4gCU66v6b4MlLpu/x0OuxuFIGDCGDGdjCEaRx69bQ/hA9hyMdZYREOS2egD3KpF+ex0DNBhkiMObmQXoyW/X+gs/O0G4vQIbLiBX7dQdYHmqsFsqsAiEASHMQEAST/FrCRZqHFggqN4eAT1vXdGBpadndN+2W2BuCZWMQNDLfaLAAddiqinKeSmBV6+RFhvIZ4+RLy4RDAO1bv3gLKEu7gFrxTqd07Baw0xn8C+vgXfdvC7Ad0nrxHjK8h5BaYEovVgr9fgk4KA2uM3+32VgXg+3voeMQP/dB/VaSSPbFlRcipj9N0WS2Klndt3SZY1yZ6vXiP+9b/D8KuXCO0AeTyFfuc+cHQENp8DZw+IQe37fU3H4ngftCQVME0prNWE3jdNhNn5LVRmqr9t2B16FEET0zGWPwNFjLE2dx5/pwMuRmztJk1aPYawTzF10UEzdfAqadgFMyaZuhTE0bsh+fwkZnqG3vVJnrqBCRaDo3RGxRVuexp/FLEfoIREl4KsspfJmY4qANg+6KQQNPHTggIzrLcwnpjIUhIbtyxm0ELBpjANer5Iki+asOZKAM4YFBcj2MphJ0OSim4HCsxYFAVNLiNJxIAseenx3nKJia5w0d5CcY7e+yRZpb4twUm2et11uD+dY3AbrPoedaFxs9qiqokNFVLAOw/D6AI31Umim47R40mN946OxgtdnhRuTQsX3MjM5n66LJMcgRWIeaYYdYdV32NnDE6qCqthgPUep3WNSinc9h2lt81qmhwXBW67Dm0qs7/c7HC1bfB1tYFKiW5vmgZTrTEvCvjowUFAQEqRJnB0DmhtD+stpcqm88Kz+VPsbEMMoazwsH4Azji2douFXkByBRcsOt+CgaGSNdoUIvLnr/4Cf33xHDtjcG8ywfeO7+N8coyjYoGHk4f4yRmxbp3v4aLHcXGEUtCEVXAJoQQ616IUJR5MHozexkfThzirv3v83RmHbwHFw+Thu0DRJbY3jM/NPxs/jIs5lGK6B/eS5QTO7F+k0Js8FnOQDck7ORSXmKopQgLm62EzLuaQPFmMLHceg5KLcQwWQlP9ie3HhNYYI/pUN8MZhUa54DB4C+NpbE41Lereq09w269xHUjCCADcM/TeIgTqRZVMjBNwqm6hns7Okm+Oxg7JL30IWJQ1emdgD3oTfQg0Bo+OUKsSb5ob6m10dE4SjI2BSDQGW5xP5hj8ButhQFlorNe7cQzyJEHtQQqCmdYIoPAdwTgezGb4/sn9ESid1yfwMaCxLQICjosj+q6Jyc+LMOFgAluKYgwSet1cYdX3eGdxjDfNBsZ7vLs8QiklLpoGtVJ4crREJSUWZYnXux22ekBjLD6/ucWv4g2mZTGeE96k59RK4dHsdlQUFEIn/2iSvjsD4+0YPBRixKPpOVkMAkn/83fpfI+JpC5OFz0GPySVRoHe9bgZbvCzy8/w6e0NOmtxVFV4d3mEo3KOmZ7guFyOHvfcbztTFKBFi31UM0LS6gLHxfG4fY9Lkr5+59iL+6tSBooxTXozW/ZNj2I4kKnugWL2s/lICaj7pVVipfJ7jUmciQmzfj/RzosgijNME+MlOEPfe9gQYRyxlorzpBLJoJZYxdYGcABa7oFEBl0AkiSSPHC15vAB2FoP6yNKyTDVxGzdm0nctgw3rUOVIj44S8ml6VjMHsd86xNpYF0YF3U4Y2gGBx8ipqWiuobE0AKA8wGd8bh/VGGiBa4aS146uwfN3kdwSQmo297iaFLAhYB256C1wGYzoEqdhDyltjLmxj7G7HtkDDidl3jv3jRnC+L+XMEFkp7GGHFSJ38zMMoy878x4Y6cKty5gFcbg91gcW9R4nZnYH3Ag6MKWgrcNgNKJXB+XKNQApNS4mY7oFUCvfF4dd3iZYyoK5WqpkheqpVAITmOZ9SnzBipoFwgzydntF+tj2PSKwCczxR6S8ejFAzHtUz7JaDWHDIBODr1UUiO8RE3rcOnFy1erzoYFzAtJc6XFWalxEQLLCsBwcrx+AOAieZjRQlnQMVSb2YgkJu377IMWJS/uWv4N4PFQ+Qek+Rw/PctoOjd3ftjSKwMp6bMGIFmg9g3JOnzSaaYb1VNIC+H2wwDxt7ELEtlyRtXlAmolImpMQTacv8hsE8yzaX2GVB03Z4xzI9t27tgQwj6mTGw+Rzx+vqbfk3OgdsrknFqTdthtSJf3nYHVmh6jcxWKgWs1wCAsKMVDK4lxKwksOcDmBTEwO068FLR75zBvFlD1AX4g/MRDPnWEJjEAfPkAngpAR/gXl+PGcz9todWtKq7axwYA2ZTBWsDxGARfYCYFgidBVMC5U+eEkNWTyiBNtd+cEZBMkrvFwJiJIlpUe7Dh3jaP+0O8dNfwl+tIO4dA20LdnoCfnsL9tFHiF9/Td5K6yCePCS58O0t5KICrzW6bQq0YQzyaAImyaMZjQOXZNru/+ZXYIJDHk3AtQRbLihw59E7dCwpTb5EKQkozo+Ap+/v5bT5exyd7SXC6OgYFRLoUwfkz/4GGAYK+pnNRrkxOz4l9vDolB6fe0JzyI23ZGpwFnAdAcl8LE+m9D7LY/r5t9wyULwDDg8mrXkym28s/Zf/vrUbdK6F4jmF1CcgxVHLihgHEGgzqfONDqu9jM56h1JSFUYlq3Fi+6a9TBM1mpja4EbGz3ibLnwcO9NSPH6Sr4UYxxALLWSSzPBRjrYsZrhob8cLX4zEjGiusDE7aK5GMHLbrVHJAjddg1JKaCGgGa3AKqGwS8A1B51k5gDAyCL2zqFJPWs53v9it0UpJJ7MjzE4iwjy/mVwF0GT+sF5VKkz9eWW4ucZY9i1PYQkENC1PWIEJtOKwoScxzoOmCiFzlJi2fvnR6iTDLBIIUNDkiDm0JGcXCkYXewlF2M4ST5WfAi47RtshgEzrdF7j5nW2AwDHs3n2AwDJkrDeI979QQAxuoOLQQuzHYcf/enU6gU8jN4Dy0EfAj4s+e/gmAMZ5MJtBC4Vy9xf3KGd2ZPYbylEvj2NRSXeHf+DAu9QC0nBETAR6B7XJzQZ44ePQDJJBRXaF07AsWdafAPHn8PR+V8DEM6rU5xWp5gWRxBMvLM+uDAGAdnHD5QWmgMEX3oRg8gHb81NNdY6CV+eDT5zjE3/vxtQPFAdpqB4th1OsZN7MejCQOGMIyMUx5XtG+LJAFPSafBjrLU7GfMn6OQGpxxSEaTLBssrrsVONvLt30k+ab1bhyDDIxk3+nnPAbpPr5nkRLDKDjHvJiMwSr84DrIGcdm2EIwPi7qrPstJJfYDh20EFR5kxasJJdozW48zqgqg2Om6Rj3CTQOzmCXekVzXcDrrsNEazyaHSOnVW5T+FMeg3R+oj5FHwJebFdwgVIc226gRRofMPS0feoJjcEhLQ5NlEJrHRTn+PH5IxyXCxRSoZbE7Ofgr0qSrPMQIHZJmWGDg+ISOiUM977H56vnuGpb3KsnaG2P02qKm77B944f4/nmDWapZ/Xp/DglPu8w1RqVlPhVfzsCk+OyhEjnKOpjJSb0by5eQXCO47KEEgLLssZJtcB5fTamWN8Mt2itwMPJPdRqgvP6fPQj5tsc8/FYQwA4F6MHdm3W+MX1r9F7hx+fP6b01rS/jso5pmqKmZqCM4Ec0JQX6ojRdrRAmfy0MdK4l7KEYLTomFNdvzEGDxjEO0DxLZB4WIuxZxTjeEmkiX6EyaqMBN7y33UKJ8tdiuRlzPLVu58pdxaqVFdgfMB1kwK/XF7goG1JwDGmxFnAOow/946u4b31KYcw1VZwqrrgjGFeSlztLDiA3JTBWAphSX1/KiWbrjry+naGajVyQA6QwGwCijlZVHJi76iCgUDN4IgNVIKnYnvgZmtRFxL35iWB88Qy5qCWfIw6T32K3kdcrLtx2/a9G2sbuo4805OJgnMB1nrsQkSpBQbrIQTDO6cTnEwkSskx0RyKM/SeUk8Lye/IM0MEOushBTGTWjCIdFy3zuOzqx7r1mA50eitx2Kise0s3j+r8Xw1oNLEJN5flnAB2LQGdUkSzRdXTdreBGg5Y2NATWYHv7zYgXOGWaUgBW3PZSVwPlWjTHfVebSWgnFqxSEnbEwgzrdpbiqIkcYfy6FKEeve4/PrHj5EvHc+w0TT+UdyhnkpUCuOaSFSuA+S6iKPHyTQz2DTsUjjARCSwrQmBUeZu9G/4/Y/QYYaDzxq3xJok+4fKzIAjOXnuUPx8Ln5m4QEzsoKwEFwzSGQ5AJg+X1i8pMlmeh2Q2zNZgN2fp+YxPzaSeY3ppoyRqBtsyEPYgZBdb0HjjmApqoArRHfvNk/frGg4JmTU8TNmnbqMIAtFoir1QhOWVmMUkdwvgeiPkl0fQBXgtI/ASpv9xHRJubUB2LQOINf94g+QD04JvmrUnCbDtE4+M4ASSoBzohtTMExftfDbToCWCHCuYi2NdBaYDpVSTseYXoHpVKUu/MQ0wLu8+cIn3wJfToDPvoIrHhA780Fga+8T7KfdL7cgy+VwohCpPCZ21uI4/kesFsL9vQpAXBrEXoD3xpg/eUI+sA5hJIoHpKcls8mCLsW7raB/t5TYLfD8OUlxLSEmJZQD07AfvA7dIxVE+DkHoEza4HjM0BpsGpCx02M++8A7GXIGeRVU/rfOeDN8yRtXYD9+A/pGM0LIFLuQaHWyV8ryFvbd/Tdj072gUw8HeP1lP4GHKT+6n236OHQ+xZGcZygviVBzePzbVYxIsKEAa2jxLmAgNa3o1cRINZlmvw4g6cQkT3LEBIwyQA1QKdKBMUVtnaL1na47Td4Mr8/ypqo94dDBE7dftEjgCRzFI5RopYU5b8oarS2R/YgTpRGLUsoofCmvaEwGlWiViUkF5jpyTjJ3ZoWcz1NgTkRO9ujVgqaC9jgEXgEiySlMkmu5kMAF2Lsz8or09Z7uMxQpG3TWQvrA95dzsCZQCEVVn0PGwJaS8FADHRSL9JK5uA9GmOw6vpk4qcgm6E3EIJjOqvhPQVrWDiEwNEAcM5jUhZ40zR4udthpjWezI9QMZLkVlzAp/MiT3I3ExwUFwlo7YGHYBwmWAKEaTKaE1nvT6fYDgNaa2ED1XJ8tdlAMIZ5UaBMQHA+qTDTGk8XC9gQcNE0+NH5E6z7LT69vcGiKDDVGu8tT/FH938PgzeYyBqn1SnJkYPBcXEENVWo5QRa6JEBy6EZmX0zwcAFi1pOMJVTuOjwsn0BFzyWxQL//qOfohDFCHIkk6MMs+AUzsI5R2N36H2Py+4KJ+UJFJfY2i0kkyhliYma4Ha4BQD44OAYJ38k/80XyrGS5m2gmIHhwb9v9ygScPdw0Y6yVRvtKBvO0tRaVGgdxvCow/3JDyolAgIqXoKnRYOd3aF3AzZmh/P6BJsh+eoYG6WRggtim1P40WbYoZQFKllg8AZTXaG1PcDSxEhoTFQFLRTeNDdYD1vUqsSimEEwjuNqgc3QICSlwbKYjaFVxg2p01PAeAfPPAQ4FBcpvTGOQCunqCKxOC5Q/Y5LE/ocLhVixMPpFLUsIRixpfnYzT2rAMYx2KcxuO73Usc8BpWSqOqSxmCgyWoI9Brek9/189UVPrm5wGld4wcn7+C4XKIUBRgjNjePMdo3BCB5UjbIdIwCwMbssB62OCrLJEsl3+azxT3c9lvY4Ol8YS02wwUEY1iWJcrks78/m47+2/UwYNX3+OjkHramw1frNSZKJRA9w/eP34UJFpUssNALUJCSw7ygWqFiWiTvFLG9YxR/Wohwkao+KlGOPZ3X/U3yXdb4/bPvQXNapMjfPx+jiqvxOG5dBxMM1sMGc53Sm10LwajTsxIldpYm4S7QPEdyNXZVfvv4+yZQfDvp9A5QDHEEim9LV2ME7AHjn32KhaAFOOt8en2kcZRyAg/WfkpFjKBgBNh6F7DpPU4mEtshT8ZZAoAEDgOIN1GcYdNTQE0pOQYP1FqMQE4wBiU5ZoWAFgyvNyY9XuA4SR/PZwo3LQXkDC5gXgqsOhoLxgUoSQyV9QGcEWBRSeaZt4tIADEmcJy3I0vbkHP6HkOSqZ7OqSZCpHAc5ynwJiZwC1AHpU+foTMObe+SuJC6/fo+QCmOyURTwJuP+/HHaPzVhcZX1y1+fRmxnGj88MEEx5VAJQkCZqCYxzxVaRALaxkBKAZaQNr0HtveY16rFEJD59Anx+W4vawP6I1HMzhwBkxKBc0ZIICTeYkyef+a3mHXWzw6nqAdHK62PUpFfzuaFnj3pIINYQzjiZE8ihMtcDJhuM/V2MuYJbNAlkPv/bBa8NSTSUyqDxETzfH985qqOHj+3nt/oxIsHcfkg7SeKj4mBaXckpeWjr1Skh8Vgo1ybKr4+M7hB+DvLENNjEs8+P8t6SlJS9N9B8XWiJEm8cGTdzDLFO1B8s50kcTgSULatbjDm+eLpjU0cs0w9vjFoScWcjpFNMM+YTSHy+SE0uwpzN7FptkDRmBfep/Db2IkH1v2JHK+71wUyfPYdeQ9BOhnrfcBKYey1hjp8yQvJ1fkF/SdQfTUUcQYqPMv89cAAb3BghcJSKTeQYSIcGAGD6k8nthJDvN6DXCGrrGoKlrx6XuLupaopzQpsn1AWQo4H2FMQOg7TI5r8FKlzkP6l61WBHKOTwn4yINDhnFAif3PmZllDNitEF++AKQE+/B75F1sW7CqQmzbsYuSW0uJqM0Auawh7y1HRlYVBck833kXQhfgv/4M4Ve/Rugs9KMjMM7hNl2SC1fAwycE1LqGElSbBsz0wIe/l5jl7H8Ke98rQOzf6obSTOsJsY+mp+87Sx5aKdP31SkizO09tcYAwtPxuVkRIDy7T49td3Q8h0BA8vgshR8N9Hip6PHyt5H83w4UiW34bvlpiAGta+9MaAGgcc14gZ+qCXJ0fowNOt9DHET2Z6GO9dQZZlMIyc7u0NqOuveKCXo3YKIqinN3FJIzURW8aVOf3t7Hcds3mMyqMUijtT1yEXf+LINp0Nr+LuvIBJSQoycrd7ZRSqEcOxpNriEI1DM6JD+VCwFKiCQPotAZmQrIfSRgKTmV8mohsBoG1IrkJ4M32JoWuaQ7swo2dSn2jiaDr1M/6tAb6EKl8WdQVQWqms43znrIVEpsrcPQG0xnNUpJCaQTpVPwAZ0nFd8Xouc9DJCUNx8fjGcWmfbXbZLbP5xOR5mrSIEhWSLlQ0BrLIyxKAqF6Ww2pjKe1TXeWRzjHz7+KSpZ49PVZ/jLN5+gtRbvLUlydpt66CpZ4/HkMUwwaF2LX2++wHrYoV/0+MHRD1If437l1IS7zPXarLCzDWZ6iqmawXjyVc3UjKS+KRlVcZ1AloeAQIhhZOpsMLgdVpioGvfrc0gusbM7NJYWINdmg7PqFIJJ9L6HCQbSS0zU9E6QxzfG3oFMbVy0GWsx9v++DRQzE0g9pXZkHvM4HbwZJagTOQH5yywcl+iSXy8v+OTXypUaJhhKpQw+1V9YTFQFEyyVtgcL6x08I99wa3sMSYZKwTgRje2o8kQoFGDJpxtGJjCmxZitaUbfoQsOUhbEaCKgMcMYStQleTpLPk3j3TgRyh7FvFiTUwGz5DvXY9jkLcxHOY0Bd1CPYVLXYRyl5HQMZQkqMW6vdzvwNO6KIrHzg01jMPkvD5KIrXUwg8UijUEf41ihkYH1TE0IfION56ncWytYBue0XRg4Gtfg9e4KjDF8dPQUPpJ3d9wfrkme7oAX2y1aY7AoS9yfTkdW7slc4Kic49niESSX+HLzAr+6fY02BWnlcB+RfKX39CmMp/7c180ltqbFMDN4Nns6Ljjkmw/7AKUQPdUh+R69KElpEoklrThdAwkE8xEMu0iVYSHJrkNkFKRldyhFgaOCZOW978fzWANgUczBGYdLCcAmGFSivCOjH8feIasY9/LRXBVx6Fc8ZBkzKIzjd43jhDzf7EGVRikkskdYpooIAGMqcZ7WWE8MYZ+K9Yz3GByBrErxJBPloxTQB1DSaSQ2ygPJy0uewEpxFILQ6GDD+D60TyI2fcB2cKOU1AZ6fZYkl+3Yd0gdflQrQfLb3KeYmdHDsB3BKBHVOD+yX4ztx1H2PCrBsXEWSlJwjnFxfI5xe/Tsk3zUgtJPb7YkNW9bS15GhjEpdTJRafxFFAVdA43xGAaP+byAkmR3yPLJVecozEUTUDzENIdSVAZAiz2QbJ3Hyw21FXxwWsEHknpWmhJOjY/QUqCQAdebHr3xmFZqlJUCSKBd4v5cQXGGr1cGL1cdBhtwPCNZeGdojqElw71Ko7e07y8bi8YE9JOIp0t957yW92/egjFGeqwL0CKiVnQ+VIKhVFmZcfff7K8NiTnkjCEy8iIWgmFRCmKK/T5cqQMwTfdnWTUQkyf2N6PFv4MM9S2geMgojuAxElCMgSbk48gyiM167zG0/T7dMnvcOCNWJ8TUS1gnNtLS8xjf9y3S0gP50GLc+w05BysS26gLxNevqC5hMqFQEzoyR2YPwL4ncbulsBTn9p+tKAgkGrMHit4TIBwGev/0WdD3e4CYpKsji5aYtPGxMYIl5jImMClSVDEER7QeobMjmxsA+M5AnVCcODu7h/jlF/DtQN2OlUJoDOAD+LRA7Ck11fT0eYSgqOKud9CFQFEIcCUBwaBdoETO9NihudtziOSfZEdHJD3N+8A5AkHeAzIdXJlBjnEPyLoW0Brsg48QXz0HnCPmt2tp3wwDMbVNA3k0QfW9h2AffABMSQoTP/uEWNxn79PrhQC0LfjD++CzGfDiBVCWkA8egL33IXB6DlxfIF68Anv8DOzRU/Ihzpd0nIkDUEsbh2pWTE/fzRoCmrqg+/qO7vfJ21jTPoDp6G+ME/gbpdkxMdI1/S8VAcW+I5nqdkP3dy1VdkhF22pzuwev3zkMwwjYDsNr7jCJMcX7H2gPbDBY2zV8Cn3J/kMGNq4ck6+NfFM+OEqgBJV0kx+NWJzA0qQCAZ3t0aBLDAB97lpWVKotNL7avMab5haLosZ5fULDL5V7k28qYq4rGO+wHrY4q4/G7ioWIwpFQTa5ww1A8l9FNHYf7OEjyVzzZ8ghMHkClDsbERxCkvsIRvLTHIpRpzj3LKvME9DcdZa9OQBwUi1w3a3H7sNSCvSG+kynhcSQJG1DWshhnCGEgKE3KAo1htpwxuCkwCylnzLG0HXDyKwqTjI6JcSYYngoeXt7UuWDH0EihcokVjVGPJrNsTHkU5wXVCWQJbRZgnt/NgX1Hlb48PgxKlng3735DKWU+IePfwrBJXx0uO03eP/oIRbFDJ+vnqNOyaffP/oQZ9U9XHWXeNW+xrPZO3g2ewfbcoujYnkgtUwXckb7qrMdrDcQSerW+w5VKGH8kIrFiT0sRYVSlaBwmg6D78EZx8qs0qFO7JwWGrWsUMsakkm0vkXvehyXR9iYDSpZY2d3OC6PoZiC4AKb1D3oosOH3zn+suT7bvLwnUUbZB/xvkcxv27vOgSEBO7c+HfanyQVc9GN36MQBfl0D6TiggvEtIocQkCbwnB8pIAl8ndSfY3mCi93l7jtN5jqCifl4htjMMZIoNI7bMwOJ+Vi9JVm+eHWtBhyNQ0YLcS4AYO3Y2CVjx69G8ZAqbyoQbU1bPTXsgRUs8xcM6rEiGkMAkDJ2MjYH946Z8dOzrP6CF9tXt8Zg0NiJualpjRhS0Xv9F3Im2gGC63lGGojGINXAfOqQO+ou6ztzQgmVFpAWhQ1FuVsZBXzsXzYf3l4nGSgmKX8kkv8zun7eL27go8B9ybHaG2P1bDF4A3mxRTc9jguS3x0coL3lg8x12RJ+PT2K0gu8WzxKJ0D6Nz7aHaMma7xYnuBQmg8nJ7gyewBjoolVmaN626FB5N7uD85w7zoMFOTUXqd+3Ij6Pdc28LZPhhJpj5PGxw4y32KCiqBRqqxIVVM67rxmgQQA14KClziTIxdlHM9Q2NblJL8jzM9G9nNvJjj7TevgXEEiknu/xZI/GaYTfYb7h9vk3cRwOiBzZgxs39hvK4iKSv2MlQOdsB/EODsTfZD0nMZI2+h4gxBAi8TG1hrMQah2BCTXywBVCVgfcRu8FhWcjz2JKNexU3vMbgw+spcIK9jbwOGA+DX2jBO/DlnkEh1Goxk3sYHMB/gcvoqZ2OYTP4cARGacZLpWvJYaslhEWCsx7zW4Aw4m0p8cTOgtx7OByjBMTgaf5NKkUTTBgzDfg7qHAFBrSWKgkJtOGd3nkPXQDsy/FrS+JtXEstKopR07YuBriKS3wU27K2fOaNuQsUZnp3XuNhZ+BBxb6rQ2oBVR1LbWSHRMoZJqfDkbIoPTqsxrOjzmwESHA8Wely0GDyFwcwKgTebAUpSmM+jhcaiENgOHjedw/mUQmomOmCq+cgq3/nMjFFCbMx2Ejo+FE8sYwLgAiwxfywdw3svaWvyvCyrwOixGWjbBBSnpUAzeJSKw7hAnZAcKSMiABbj+f+7br+FWYx7wDiyiQdAMf0eM7sI7BnCPBnPFQrO7H8GDlidA7lpBlh8TgyNlHtQmYBjDJYCXsoyVXN46sWLJE+N69vkB5uQ7+7xM8SPf7YHlxmkZN9YYgyj82A6pZim4vboPNikJhAwne69jcOwB5J5cp6lrolBRFnuQabWewCpiZ1jnuQXAMlQGUDvJxiii4g2wK2JGZDLyX7bAAipkzD2DsE6xEgnGG8dhs7B2oDpooDpLKzx8C6Ca0rK871J8q8I5QNYSYdAqfZBPOZijegCgvPQnAOvX9O+mE4JAJ6eE0MGvCU1HggQAYhXb8CWS8Rf/ix1F54g/s1fY/jyEtEHqpXoe6AsoX70A2J550cEnpQGhgHu9Q3YyzcQ8wnYT/8U7MFDxPWKAOS7HyaJaUqnswNQT8E+/J39azx9j8BfUd39rAAdV/WUFiu6ljyXAHkH88LBfAmUycsUA7BdATeXqdOxIRA9mSYg2xA7WVaIn30MdnwCzBaIqxswIei1rKH9PwxJnrqh43Kz2n/Gt0dg3PcnhoOJKsniaIzeSQWLJDtlYOh9D5/8htkf5d/yQB1OUiMidGJubNiN3W55oiE5lTO3jtIQHShh8cH0DC4Bzc2wBWcMs6LCUTnHk9kj/Oz64/Hjtc7itJqNjGD2tGTZGYAUkOAwOIeJ1tBcYaIrDM6AMQ7j3chuHnZPBRALSqyATtJTh1KqEVAelrrTdiCmIzKScYiDv9301BW2LIpR9skZQ+soErx3PsWAE0AwzmMYDKxxmC8mGAYLa1xKQxWQUmAYbLpQktROC/IeTOty9OCsh4EusH4fcqI4pyJrUFVGeSBb5mmSPXiTJjYSrSX56cvdFpJzTLXGF+s1btoWMQKTgoDiRCn84YP38GJ7AQB4ub3ATx/8CEflBC93a/yzz/47LMsa/8k7/z7eXTzBdX+Dj5Yf4vtH38NJeToeL73vMVVT/PDoB1iZFbTQeFY+gxYFSlEeMBp0rFKS7gwNGnS+RSUrkj/KmhYpGMdSH6ESFXJi59qscNlfonc9WtdhUSzG1NOd3eG2XaGUJX55+wlOq2PM9Ry3wwqSKxwVR+j9kMI6BmitsTWUHnnrVmO9wdu3t8fcoT9x71f04/jKU858vJEHMYP5/TgEcGcs7vclB2cCtQR2NkAKuWfbQWFCDh7Gk9wwv/ZxuRjH79psobjATNc4Kue4P7mHT2+/GFkUEzyWRQYQBARNIB+cFmJchOmchQ8BE6WhhMJMk1ycvF3kRaZ9ufc5ktyPAGytypGN1ELBBgqTKoQEYxw+DuNx4UJAYGzsJs3s92EFDQVW0TWw9wRGB7evwgDIszgMFs46TKYVVdZYSkOVMo1BY0ePlg8RpSSmTE3EKGi6aJqxMocxhhe4gOICE1VDCYnjcoG5noEfTAEppdZSMi0YrrsVluUUH998iUoWOC4X+OuLX+Gr9ToBUQrTKqXEj8+fEXupa2xNi0JScNfL3RYvtyssyhJ/fP938GB6htWwxePpfTyZPcRcz6BSeq7xBqUo8Wz+BI1rILnEeX0Pmmvob7E5cCbGACjjzeizrEQ5qjymagotFBg4IgJ2tqEgs6TsmOoJSrFfyGltByUUfrX6CscVjc9Vv8VxxTFRNLazZ14Kgd71iIjY2d23Js3uay+yDBXwCUC+3aN46FPMx3qIES6zjnH/mPw3loBi9vdLlhUbAtEBgsUDtQuxioacQtCSwThi9Y5qCgspJcdN56AEw6SQWJYCD+can1x14zHqAqWZ5sVBOm5JpilSIb1xcQyZqbSETt49qrNg6G0YAUM+ZkVKeLFpW1SaPpMLBL5cClrRMoUypb7VANq24BhTSYOngKC+p3PUrCLrAHkYKcQmV4q4A4bRWo++pznobKZhjIcxVJfBuYCUHPYglZ/YM1pckRNi3yKAm90Al7yBIQJf3dL3mxV0/T6ZSMwLCZkYxZj2p/UkA40ArhqHZSXwyWWHSnEc1xJ/83KHi3WfgnyoOkRJjo8eTLEoJeYl9R6SnNfjajPgctOj0gK/92iKs4nEdvB4MNd4MNeYFXxkIV0I0JLhyVKjM+RpPJtSR6Rkd8EtgHQtJzBv0r4pJQXS5H1bK/q++dY6j+0QKHE3gb5ScvAY0XtgmzzXn98MOK4FJprkyUtITApSEmZ/K3lYw8hqZoD5Xbffzix+m0cxh9nkLsURKCbQ4C3g+V6SGhKAciaFfiRGkXEAyYcoJYAk2wMSIxT2DM12TTJTACgKYjIT2EDf0aS9a8GUAt79YP+Z3rykybklkInFYu8hvL2ln29uwCY1YtMmCaYn4CbThaAsiW1crfbMZAabOWkzs25Zyuo9/Z6SU+mMckSgKElgOecIbY8YIvJCZcya8oEYRjEt6TWEoG1rKZAGIY5AkTEgDPtVuaoSMGmVBqC/l4UA4xy8VAitgSokYogIbQ91NIG3HkxxhMFi2PSU3vR6DfNqhegD9L05QmcgpiWYFFDPHoC99z7w4Alt69trxEsKpMFuBwwDwmoNdnYKcI7hv/szuE2HkKKLw+DACgkxmRD4a7b0OkojXl0C3sNcrBEGB7VsILf/LeRPfh/swWMCVq++Jk+gEMDmhpjp9Q3w9APgs58jGgP2uz8hP+AdWXQALl4QWDs6A+o5yYp3awqo4QK4eEWS1qLag8vdGvj8Y/psbQv3/A3krATu36fjqkh+yNSRGa0FUxos+xkn0z3DLBUdf/WUAPZs8a3D7zAoIyTW4tCjeKciI62tDUlel32HkisMiYUwfn//KEmKGFmZw1XeUpA/kErQHVrXUhQ/4liL0NoetSqxMw2mekJ+R87x/vIpBj9AcYU37QUGZ9B7i8EZHJe0al6rElcdFdu/bm4x1wW2ZoDxPpnI/dgvVsqCAm38DiLQfXmiTWxilhgR6CQvhocDpacKxuEZx1QXKIS+U6vRJhm54MlbGCiWxNg0UdYapZQQnKekVzOCSZeYkZzASGONoZ6UMMYhpMcxBiidOhELBWsdlJKIADpjsahKNJZYVBsCuo4m0Zt+wLrr4X3AYlKhNQbTgr7PsixxXFWY6QqCcfRuQJMYmdXQU1CPMdBSomAMP7u8pJ45uw/FUpzjyXyOD5bPcNtvkpzR41+/+AvUihIZe+dwVFXYDv81/r3HP8Y7sycoZYnnu+c4Lk4gmMDKUAjHyqzxbPYMv7j9JQY/4CdnP04epyQ/TfvpVfcSBS9wVBCgk05iZ7cQjI63V+1rPJ0+GSehMXps7RafrD/Fy90bNLbF56s3OCorvLN4OB6HGaBszA6dG/D+QkMLDR8dKllhqqZjmqzkChNFx+w8eSi/7RYzUES8CxRTAqpPDPweVNICzCEQzN5MYuwtGDhCzHLL7GYiyaniCr3rERBHeThnHL3v0Tg3Sj4JKAYMzqKQivyiqkbvB2iu8M7i0QhYr/tbSkcNDtZbHJWkkii4xHW3BmcM190GE6XRWGLXtAiw3tMCBWOoVYlCaKyG3cjcZ8mq5AKI+ftRD6Pg5GdzwaGW5cj6V+UMtSzH80z2JMYYwQ8mXQAlFgdQT+I0+ZVd+g6ZRXIhjM/NYTeMMRSlTl6oMN6nCw2eFl1666DTmNwNBkdVBecofdx4j03bg3OG12GHV9stQog4nU7QO4eJUlBC4Ol8gXcXj3BWnyLGiLXZ4KZbAwAa26L3Fqu+xUlF1RH//Zc/w9YY9NaN308Lgaku8GT+AI1tCfALicv2FgERV21LnYRlie3wF/iD+x/gweQMhSjwprtMoTIcO9sgRgJdDyYP8NX2OYy3+PDoPUguRpAdEvt53d9AcYm5nqOSFQST6FwLIWlhZzNsRs8vpUsGtLbFi91LXHUrtLbHl+sbzLTGg+kxBm8o3TpGFFKhcwPeNDfQc4VCEjNTpV7OnMibpd88uO9crBmBYpJSjv2JvwEovv1zjKmDL/2bt0MGaoeJ0jIFqUQAtaQScwagc54kmInt2aeYBhSCZKdTzUcJ4HvHuaYg4qqxFHLjCcwskiyTc45VR+P5trXQUlDfX4jjYoZKktNSkr9x3fk92E0+PyXYGFrifByrmEICjrUWIyt1rBVKxbEbPAAJxvzoleRg8Nj7PYfEPNaFRKkEZHof6/Z9lD7NVznnI0PIOUNVSdjU90fflZGyjTMoJaj3O42/bnCY1RqDC5CM1HC7xoAx4MZHXG8oFG4x1TAuoNKUrvzgqMa7JwXOpzrJxf0YMrQdyEe67SyOp9Qr/Ge/ukVn3NgnaD0BxVIJPFrokW3WguFiR0B90xkY41GXCv/GeHz0YIqzqUIhGS53DhPN08Ix6Ut2Q8D5TOFFZ2BcxLsnxQiwx2tKjFgPDpIzTJRAITgUp9RWkSpONn3AUS1GS0x+j1dri1Xv0BqPN6sOlZY4nhYwPqCQtNBQKA7rAq4busaXis6rpWRAOm7FgffRB4by72BI/C1g8S2gmMNrEliMLklFD0ElY4AsAG8RvQXcQBNwZ4mlCQHoboDJ/OC1k3xRlzThB1JNRUHP69q7gCynmoYAdv6QJujbDU3Aj04QX35NyZuzGWLfEyOYg0yKgqouOEcczD6MRgj41lDvoKWLBoqCXlsp+n8yISBEI3XvWctexbK840+8AyBDIKAoJfUznpwAFxfg3iMYR3nKjO0F5oIDIZJfMfUHRufg3tzS21s3BuUAAJMcPEjItOITAmnHm8ahKAS0FpBHVO8R02CJxkPMSupjNA5+20NoCSU5wBm4lgiDhZgUCJ1B6B1i6DBsesTPL1H8+S9R//AhVUeEAPfiEvZmh/62RXVvBjmvIZcW5pMv4dYdymenCIPD9pPXKLWAqPQ+kbSogGaL2Hdg5/eBP/xT1LN/gXhxSYE+LiB+/DHYH/892v5VDegK4JKOm4uXFGyjNCWT/tm/Au4/Apb3DkwAnh5//mR/3DZrYiJnC1qUsBG4/5iO1avXdN/RKXB9kTyGEsPPfo3m1RrTd0+hv/c9sNNzDP/Xf45oPfku/+QPKY21bYDZnCo0dEqI9Y7kq0OqbyEkQUzlW7c8Ac0JixksjpPXNGkF9hc8SjatSVIUSdoH0Kp3LWtERKyGFSaJkfHBwwZKSqxkhZ3dwY5SOQojaW1DkrgYxrS/rWlgvMPDKSXhEYsZcFQscdldY2sanNcnaF2PXSrr9jFioiu83l0jV2RMlEIpJZRQ2AwbLMsSNk36tBCoZQktKCyjVhW2Zr+deJp4KC5SmilNbMivmKPD0+QyRhSCTneSC2hRA2hHn9TYrYW91yz3JuZExxgjXje7JHEh+amUuQuSI0rA+7xqSj7GXdNCa0m9iVWRmJcUxe485lWBzjk452Et/SvSWVykeH8hOJqBJtS982jaBm9uN5BK4NFygVopWO9x0/forEXb9JhMKwjGcCoEfnV7i2GwOJtPYUPAzXpHHY+pCzLGiHv1CV7sLtC7Hmf1Av/Zu/8Jjsp/iefbC9ykovu/fPNz/KOnf0rSQTkZpWaaF7joLnBankBxhZPyBP+vL/4Fnkwf47g4GVfmYwJOD6qHI8Da2i02Zk0so6Oux0eTh6hkjav+Elu7xUlxgovuAiZNSP/FVz/Hi9s13j87wY/ufR/fP/oQ/6e//r+PlSD/+J2f4unsCXZ2h7meY1EsRwbFBYet3YydhpxxAmjp928bgzTW/B2gmMeki26slMl/p2OTj49zaQXfB49CFGlSP6CWVfIJZ/kwJcBuwxYRER4MIoVD9Z6knrSgQLLyLAE8q+5DC43OdRCMY1bMcNleYWc7zFLxPQVI0ZjQXOKqW6VFBjcmB0su0dgGlZTEqAHQXCR5K/19qqoxQCd38LHIxn7SShaIMaQKipAAo4cJDjGG1J/KMdUTLLnAZXsLl1h2wdidccjTcUMeQo+JrGCDx+uG3t96f2cMKsERooDjuVOR6kXaroNSEkpJLFNGgU0gs3cO02LfiZoXcqSkagItBAbnUGlKKx7SAtGm7fHF1Q3+TfkCH52cYJGUKV9t1rjtOmzaHqezCWZaY1GU+PTmEuthwLPlEr1z+PzqBrNSo1ZqBHKlKLCz5NM+r0/wo7MfYqr+Cm+aNVXehIBfXH+JP37wAwAk/ddCg4FCd26HFZbFApIJLIoZ/vzl3+KsPsZMzcbjOctkT8rjUV3S+x6NbVHLCr0fEKLHSXmCQhS4HVYY/ICZnmE9rMdqkb968xJXmx2enhzho5MJTqvH+D9//GfwIWBZlviTh9/DeX2GwQ+YlDVqNRlDpCKogsTCjYtttKh5kGMxjr+7XYrfLT/FyBRnnU2MgItUj8HB4BBGebFJIC8H3ERE8p2C3UnYVZzDxYjhQMpqHAGgHBryaKEgOUdrPQQH5oXCm52hgBEtYBxJRbP8VEuG64bC0TKzJQUVsHeGUkjzeNCSo9ICWlLnYq05tv3e95wTu4sE5IpUBm99yG5nWB9hErtaSgnJKEFTcY43SZ5JXsW8zdP1lRGLmz2E04Jksze7VMXjwlvXQIYoCCwyBlgbIQTDbmehtYBSApNSpTXzdA20AVUhSdbqqOOUFAD5GsjgXITWAsaRJNYHCmt8fd3g519LPD2bYloSc/561WHXW+wag6PUO2hcxBeXW7SDw/2jCsYGvLjcoS4VtBRj6IwSDK0JaG3AvanCB6clKi1x2wxoewKPX113+J2HtOBdKgadWVHBsO58qq9gmGiBX1/ucFRLTOYSh7UejDEsClosjiAvaWMCJpoT6IzAsqJgmnXvYH3EpODYpFoWAPj8zRbr9YDz0xpPT2oc1wX++19ekbWmkPjBwxnOpwqDj5hoiVrz0c8ZIgHPJO4aU30Hd6BQ+5bbbwaLo+w07oFiDrPx7ptA0SdvmLc0sQ6RJueMAUXqIcz9daYngMA4wJPf0VuaVLe7PVgMKW1zvgS7uSSZaQqpYY+fErvEBd3HGMAF2KN3gL6jkJMUbhO7Hmw2TV5IYvxYXe3BirVg2RxbpC5FpQgACkFhKaen1I+Yk1OlpMcUxZ5NzMsT+eemSSmhal/XoRSVxSdZKlcKoekIxInEQpqUEnae+r9WK+DmBr7pR/mqqAsCeakf0fe0SjUMFGkcIyAVJyum4PDNQImjxxP4bY/6owfwTQ97vSOwmUs5I2hbCA7mA5gS0PfmsJdbmJuGwKTgaLcDzF98SWlfaSXLuQguqO8xVA7+1SXUyRT6/hFtWz5A1xrqaEoVFKentH+VRvybl8DlJfD3PgSmC7B//J+CrW+grQGKEvHf/jkB9qIkVu6wy9M5Shl1CYydn6dgGUfMYYz747WoAJWOQV1QdcVum5jBAvj6C/Lbbta03776NdjRCVCUYJyj/Kf/BcpXX9Nx97t/BMSA4n//TxH/H/8M9raB+X//D1A/2YL9g3+cZNVpu4b0eauaAGKu1gDo+7x1Gz2KWT4a996QXFmRf6cQDTfWEXSuHdkNHz0011BcofMdhT14gypFleeJbB97KK5gvEXve8z0FIMfKBZdz7Aa1lgPG9jgYbzDo9k9LPQciiv46DHXxAwdl0s8mtzHl9vno+9pMww4riYYHJVkz4sSE6WgE4CjPj666GghUKsSWigUgtL7WtdjUUwxODNWA8jEGlK6ZvJEpe2RJZ3G2hSMwpP0jSbzgu97mrQgee3gPZLWgSStMWJeFOBgiXG5xTYlMwJApRVJ1ZKsLbN21pL0LV9IabWVAnAAYFYU2A4DPjg+RuscrG+hlRwT5bKn6lBie1bXWPU9Nm0/vmbfDfjyihbXOCdvUfBh9EoKIcZ+RVQVcuG6kAKVUphpjbN6jrPqDE+mT/DPf/3f4LLZ4u8//CPM9QL/+Xv/S6zNapSo/auXf46pmqIQBSaqHpkrkhJbXPXX8NFjbdZ4Mr9P4C8GcCZGVi0iopI1WOTofYdCFFjoJXaOAFIlKny5/RLGW9wMtyiExq/Wv8ZZRZNXwTj+D3/8v8Xz3QsAwE9Of4KIiP/jH/9T/Je//L/gqm3xzz79V/hH7/w+/tGj/zAF4/B0TBDjV4kKSmiSdCYZdiXrb4y/fNuDxLtAMQPBQ6AYoh8X/XIBeS5qz5UxJpAVwAQDzTVc2oa5rFxwSexi9JhylVjGKSZygo3ZYJ3kswDweHYfy2KRQn8CKQKYwL36DMtg8HL3hsJUvEFnLWZFBZN8w4WQmGmMYN4EOx53SghM0hisE9vUug7H1QKdG9DaHlSvIaC4QCk1rOfj5wIwMvitG8hLk6SQgzNj4JFgHEUKnMq1LJJzRO9h08Qq17qs+y1u+w0aY8aV+kqrEeT1nMPkMWgcMYUAhBDgnHxSjTFjzcTWGHzv5ASNMbjuOkpylBSkBUFqA5ow04LR+WSCq7bFqu0gJbEkbdPjr4fXI1PkfUBIISGttdBC4NVui+Oqwv3pdBzPRaGwLErMigrH1WLsN7xor3HZ3uKd+WNMZI1//9GfjAt4ikv81eUvUxiMHL2tgEtsdcDW7OCCx840uFcvD0KU9h2oMXpoocnH7g0kV5iqCS0+JCnzm/YCJlhsTQPNFb7avsRROU/n6xr/9Pf+Y1y0FN7z4ZJyBf53v/tP8F9/8We46Xv8y69/gZ/cb/FH9350J1gnh1uVY7Ixh4+0nyrxzeqM+B1A8RBAZqCYQ27G5yU2MQd3jAsRIUVLpJAvjNdQAMgVSh4RgOZk8ZlpiYkiRmjd+9SdBzxZFJhrlc4vETUjz9iDWYF56fBqbbFLFRPG+RG8ZE9gpfff0/gwAq1SUspmIRgqTTLG1gacTRW65FtkjAAkhaBwMLeXpubPA2AfwJLqPnoXEjilKg4lOWQkoOp8roTAWKVxNCkQEbHpHVadTTUfCWApDu8j+YI5GyWmw5CTTiNEAlQ8VXcIzjCtFDrj8fR0gt56bFoLLzhCqoTI0zpKLyUmbDnR2LQW22YYx1/TWHw6rMbXzyn/nDN0xkEKhqttj3mlcDLby5yLVF4/LSVOJnKUe77eWFy1Dj96UKOUAn/yZIrGVuQlFAw/f9OhlDxlH6RrLlLabQR2hvZBZwKOpjrJlONIWMQ0BiRPkv1IPYqzgljpGAm4vdnSAnczBAJy64hFQT7DSnH8L37vHNctJc2+f0Lj5j/90T38fz5fY9tZ/O3zDbrzKX70cHKnoiMHIiqx90BmyFJ+U6l+5/Z3YBYDTXIPehTH1NN8uxN2wxDbHcA4WKooiNYA0QPdjsBiPU0Az1Dped/SxJlxmkhnySWhHXoPxoDlMZhziFcXYE+eEWvjLABLzFAIJGfUBeLVG2IBb24QjAOfJ6CYWULGCBDmkBohqOsvB40k0z0lXQpKW724IEYzS01DoH+FoKCcriMAKSW912SyT0WVcl+lIQRVbWSztTGILklfMzcMgJcaOD9H+PhT6hYsFf09sZDR0nNkoeB7m45HAm2cMUhF1P9h2SuvNIoHS+DdEmGzg9/2lC56bw758JQ+8+0tus9eITQGu3UPf92iuNiNxKeUDG7wY5qq9xF9T6lcSjIwxtHctKg6A15pqLMZ1OkcUArBNFDHE4gpJZ0iRuCLT4H3v08LAB/9gJg4xgjkVRPg1deIF2/AHj8hBjlEOj6aDS0sHAYg3V5TiM7FBfDu+yTzLA5kqDl1dGT0dlSVUU7o2Hz1nD5LNQULngAlQMfmr35Ox+10DnzwA/pZSgKDSoP9z/4zaK2B9Qp48JQ+FztgjBlPFRrJg9ru6PWd28uvD4ffyCxSR9WhVG6fo3UYcELJkDu7heYahSghohiZw53bYWt2mGmSLhlvUKsaG7M58CUqTBRNnHOXXT7RTNUUNli83F3gncUDTCRN4lx0I3OzszvM9AyvmzdY9Tu8aW4xeI/jsoL1FpYLFGkfTHUFSjWkNL/3lvfGyWb22GRv41RXWCWpZE4BAzCWUZvg0DsDmbrZBu9RSwXD9lUTMQa4GIiVsd0oJ7UhJD8LeRdp21PozUQpXLTNKAWjdRc+Pi8zEcYcpBOn8AEhOIpSw/ssM6Ro/7O6xpP5HI212A4DBucwKwqcLxYopURrLb7ebNBbh64lGequ6UZACHB476ALNUrN3QErKZhA2/SQSsIoj1mpMS/os6+HAVVJ0tpSSvRuwMerT/BHZ3+IWpX4j975AzyaPEr+TI5CkOT0dXOB9xfPsE6BML2n4yx7o3ykipXr/hqd6/C6ucYPjz8aq1jyLfureKqsaFyDiZqgljVa1+J1+wofLb+PSlSIoIllZno/WX8CxRUmcoIPFu9DMJFAh4TmGv/FR/9r6vgzWzyoH6ZFhH3vpGAkfVNSgTNKqxx8TwmOZgccfWMIIofYxAPpaRKkjn7BESym/1hkI0simICAgIs5tXdA7wcKTAGlRxaiQOf7EVRWInv9/MjeAUgesglcdLjuVngye0C/p2txlq02roXiEjf9Cpthh5t+lwKOSgqYCnL02dSqhA1+HIPvLM6SVJbAbU4BZoxhpmtcNNcpuXjP4HAmwMHR2h6tG2gMpg7AiSop4IaxVJ1B5zHGGNbDdlzsMt5TdU1i/DLDXymFs/oYH9+8gA9hlMVmaZcN5IfSWo1exKysYYxBSAGt1egtBoBaSjyYzfCulNgMA0lDncNZXePxfIFaVbjtt/j05hqNsWh2VGB/u23G15ZSwJgAlTravA8wg4X39DcuOLa7DoN1KJTE2WSCk6pCIQS23uO4LDErilES/GL3Eu/MnwAAPjp5hqkiYCm4gBYab7pLXDQ3eDI/R+uyWsShdz3JR7NcNJ2DOzfgol3h2eIhjLfQAuNYyPUzAFJaKS3aaKEx+AHX/Q0eTx+ilOW4gEHnL46vd88hGKlQns4eE6vCBFWGaIF/8uzvQTCJxjU4KU9GQDjeGC0eZS/u4IfU6Ru+ld3Pi36HSaff5VGkn+l5LuyTT3MwGEDeQBM8ZLpukCSWWLksRdWcg8k92GKMQYCAy1RLuBBx3Tg8OypQJztBiBGz9PPOkp/2unFYDx7r1sL5gLqQ5KlLtRYAUCXGLPcaPliQfJUzYuo4I1+k5xGzQuDVxqA/qJogMIyR6cxgTKQAm7qQsI5YQykoGTM/ftV5ZLuhdQHOh5SqibRIHaGVxOlU4ddXLYFHketAMvCmY5+kpcTkMxbH65LWpGrL4y/GiEJJnM4o9bQZHNrBobcex9MCZ/MStea4bS2eXzXojcd2OyCEiNWajo8YaXo+DAFa80RSULBOjHEM0NlsBlhLVR3LSYFFrSjVNUTMa4VKCxzVNBd5ubF4tNAIiHjvuEAh9+dcncDbZeNwf0ZgnewGQO8DOkPgO8/Icqrp9W7Aw7mGixEIe8CWZ3E8zddtjKlvljoVr1uHh3OdZKV3exG/XhnwxDDXWo+AmgGYFxJ//70FJGfYmYCTWo6AMPs69wvkNCqN33tc+wPv6bfdfguz6L/pUQyJAczMmbf7tFPG975CzhKw9EC72YfUzNIV2dnE7GR5nk18qN7XHLg0AcshN80OsIZ8a4tlKjpPdRa7LbFTF6/ApjPg6gpYr4m5m83It5irHcqSnmfMHkBmX6LWxEZuaFKEuqbnrVb0GvmWwnVwe0vvBdDnzp9H630y6mRCr2MtgcXNZv98Y+B3A0I7ULdiqUYZKq8UcHsLriVQFQhtT6mpPbGJQnAwKcAnGm7IF0pa7Wk7h/nJFPrBEgBgr7fUS1hr6mK8WsHeNuBaonhyDDGrETdbsK4DplOo5YQ6YkKAtx5CCbQ7g+vrHroQiUnxkJKngRqhNYdMg5Gn+OkqS159gJgUVBUiBbG3aTvEhw/BXn5NkmJryI+4OAKWp0BRIbYNNv/Vn2P246fgP/17JOGsamISzUDHpqL9Fm+uwSYTxMWCElU/+4T2p1JgP/4jAnHZ7O8sAUUu9gmo0xmF5jAOSEGPbVbAV58ivnoJ9vgdYi5P7tHfMhgUiuStMQKL030qLED39Q3G5NTcr3gQbDFqQA5uHgEu2HHyNrKKeCuoJv3no6eJAxM0UWbkiWpdC5tiys+qUwAUvT/4AQWK/epuyOBr3yVGvWHko9rZHXo/4HxygpmajWXn5Gu04GC4HdaIiHixu8Btv0UpJZblJKXsiSSF0cSWplAWldiLShYIUGhMh9VAhfCVJJ/h1rQw3qULfEzSNQKIeYKZJ6giMYnAvqRbCZVkkDx588Iof+usHZnFQojxpF8IMT5uWZbJC0LSPWs9hCCvRqUUhsHu5aNSYGgsFsspzmdTSM5x03WYaQ0lyAezGQZcp2qLB7MZJkqRz9BaHJUlFkWBNQaEBDaVkhh6g9XtFkrLkcmUUlBflfMQUowBCXQekAgFXVAYiC2i94+oEyjtnYMPAZ+sP8Xj2X1M5ASvmpdYFkscFyeoRIXGtvgv/+bP8CdPHuM/evKnSapY46q/xuAHRFCC58pscd3fYK5nOCpn+NvrX+Bvr3+B1vYoZYE/uf8HeFA/HPvUXHSYyAkElxh8j8H3mOppOnapQ1AwiY1d46vtl3i+fYFn86fYmA2OyxPyQ1KkDyRXuF8/RIgBR/p49EnSeIloE8uZaywOxxMD+9bYfgB3A2wOfnbJqxhBHYpZDg5gZFA54/tFHD+k5FKPSWIxQwyURMwpcTEvznDGk9fT7WWtjMMHj873cMFT0qWeI9cWcMaxNS04E7jsrjFRFS7bW6yHBloIzDQt1oj0mQqh0wTdJlZf0ViTCjpKNLbDxtAC1lRVKGWBVb9D7/eLInkM3vTD6DOUKSBKcA7NRQpf8phqeg0XiJXIHY0UZuWxNQattXdCnwTnqJXCatiSHFwptNZCco7Okf9WCDrmayWxPkjTlEqi7wYsFlM8SIzedRqDtVLwIeC6bXHdddBC4Ml8jnlRYD30aKzBVJdYJmlpnMS0ECPQdwPWq93oQXbO3xmDOfE4XwOtdXBlWjSPEVWq5VBCoJQSm6GBjwGFIDbvXn0CGyyu++uk6CAmv7U9/p+f/hy/d/8af/Lwh+OCw8ZsYIJJDIVE7wdKwVU1jsoJPl99jc9XX6O1lC78+/c+IhAnsvfbJcaeWEaSelfjQoviAoJJtK7Bm/Y1XjdXeDS9h851FPCTEk0pVVTipDwh4KSnYOB3gFo+V8QY0R8w0Pn2bb7ht5NPD9NQY/ymRzEDtywtpe1O3sKcGK3SgiJdR+IYEBMjAEYLkVpQyEhmgkg9ESjULABPjwrMVE7fpvfZWgcO4GJnUSuOy8Zh2zuoVNRuHSV+xxghc0F9AmhKkNy0VBw6UuDINoXL1IWAEhzXjYM5kApm+eht63HTxDRt3IeXKMHHz1crKm63KUhl01M/ogsUItMODkMCjDrVZEjBoRXHqqPvwCV1OjLGMFgKluKcQwiOUpNHMS9YaC3Q9w7TqcbJrCTpdmdRaYFKS/gQ0bUW245qOc6XFaalxK636C1ti1lqCohTnQJyONrWYr3uoRRHThMlqSoxilJyiNQfSNPvgKqS6XwbUWlKuuWMuiw3ieS4N1W4aizOJgq9C7hpLSZaoFLkG+xswF9+dokn92b4/cczDB4oBG1H6yOCIUawtwHblDo6KxW+uh3w1e2AzjhwzvA79yc4qiVYZONnyuE3EbmXkSSjDBglxq3zeLVxI2DtbcC0EGOVSAaBy5KUWBO1X+TfByvtE3wPK2SAnNX57b79fPvNYNH7BAzdXnrqswfP7SWojPx1h6mlCBGxXRN7CCQWBjTRl5om9y4F2ugisXV+H4ATU7gNZ/v0ySFN5uvpHkhKSe+buvnYdIb4i58TAOScvIGMEZCbz8mvKBIjlCShUIoARdcR2HMOMQQKy7GWHkdbc9+3CIx+xJi6EVlmI3PCa1HsgWgOxslhO1UFeA/35ha+HfZLYiECnEHOSvIMXlyBP3kE8zefQkwLREvhQIwxFI+PEX2AbwcILWEHB59WB5ZHJeqffgRwDv/qAtWHD2Be3mB4fkusHoBoHFxnEUNENB7yeAqcnQGrFeyqQTQeQ+fABYPvyXfz5NkC7XZACMAunbCVEhCC2MW8shNCRNNYdJ3DwkeIdQdrA6TkqOYlwmBRPPLAvXtgj58BQw+cPaD93u5oUYFTwiz78Z9g/uWXWP/5J1hwDvZHP6VtlTyEY7eh0mDeA9MZWFESw7heU6gRY8CbF/TYsiKwFwMtVsyO6N/Th2kfJEaxbyggabtG7FoK4nn/h/Q8LjFWxRwG6DAAEHeBINJxb80+JEppes88Sc3psgc3AooGMZJuJg/6w642gCbDLuwnllTEzbExawzejJNJzTVa11LAB5PQQuN2WEEnqWcge/veR5K67ZoEEim0Zt99B2CMVqefBY6KBf7m8pOx8uHe5BiCCayHLaa6xk23hmACgfERKGousTMNWtfDBTeCOMU5bPDYmTUUF+CJ5cyTD38A+BgAnSYteTVaAXfqJ6j7zYx9g5JzrIcBnbXja+a9lpm3667DWV3j680GtZRUbp8WZU4mFOffWXtnwhhCwGRa4aOzUyxLCop5/+gIL7ZbXDYtaq1GVsQl2V0OzjgqSxjvKRE1BFjjAAYYYxFCwPmDk5FtdCmNlSQ5HNbQWOaCA6A6jr438L5C1w7jxLYoNQbncT6Z4P50ig+XH6B1DZ7NfggXLBrXYK4X4Kkq4A/O/gD/8Xtf4L/57GMIxvEfPP4TALTgoIXC7bDCTM1wVFBv51zPoJfkobvub3FUziEYx4vmJVbDGqUscVaegoKVSIZaiBLn9YNRXm38gM53eNm8xMZs0LoWHy7fx4eL7yEgQDDy8rG3uuN4Vqgc3GIM6H0H4804fgpRQPOCglGCwXFx/I3xB1DIlD9IPc0gcQy1SYxiHoc5WZglj2ufmEs6NXAITttNMpkknDLVhKi0CER9hiG9VmZlM4tkvEEtK0xUPQJUnlhIngKCJqrCL65/Dc1l6ss8AgdHY1ssihku29vEjlMwUh6DuTPVekuMXQJuxju0NjGfjFhDm3pGbUoy9inNWCZ/r490NgGoTqMQejxP5LqbUpKs+KJpsDV7BjmHj8y0Jl9Vs8GT+Ql+dvkSk+TPZSDZ56PFnDygxiS2z42+4fligj9++BiaS7zcrfDRyQmebzb4erMZa2Ns2Nfl2BBwXFU4q5e47TdYDT3V4QyWxpela+CDR6fo2gHee3TdMMrN8xgMgUMI6o9r2x7DYBB8QNMNcNZBKolJVWDwHo9mAffqJR5Oz2G8wXF5NC4uTFQ9BiD98Pgj/PHjV/gfvnoOzhj+6MH36RoRk3/VNqjKEjNOvZG1qqAEKQdW/Q7zYgrGGC7bG+xMg1IWWOgFQkonnagptNA4FsfjGDHBwHqDq/4are3Quh7vzB/i8fRROjbF6IE8vBHrJO78HpL81CfZto8BMi1qku/VQYsZ3r75A3CY/3cZNB6wiTHuwaMLefE03ulSzItm+fcsuc7n9IgIRAawOE7H8kTcR/ItuhAxLwWmiUVk6fsNPoCnn0vJ8Ys3HbQkBvx0Sj693jIsK4nXWwvJSTxsLKV3SkEy0MGGEcARYGMwjv6Wt2VmDTnDHRDN3wKIQESRGMoyAUAg+dVCRKk4eBC42Q7j69P4o2l3lYJxbhuDB4sSn73ZolACzocRXJwtK8QY0Rk/jj+XPJ2LRYkfPF5CCYaLzYDHtcb1tsebVYc6WZ6cDxhSmrHzAfNa42yqcNM4bDsL6wOM8cnnSHLaR4/maBpDYLuz4xyUc3osjT8GugbadE6gx2amsa41XIg4m5c4nijcnytYH7EoJaYxYnCBUkYTe/vRvQovVwt8+nwFxoDfeThDmbycgjP0xqNUErNCEB+lONScoXcBm95jUipwBly3DtvBo5Acy0pkXgi1pIW1eSHHRY9c3XLberTWozUBjxcaD+d6PDaBb4K8b/udFlUwhi75QO9LclQAgWFW/P8DFg89imMSagKQeTKcgVGMxCICewbFp45BqQlkilRsbnsgapLjWUPgIElWAezZRWvuMjR9t5coOk/etfUK8fYKbDoHOEP89JO9L7Esib26dw/s0RMCgbe3d6SnYAxjX+MBIGQx7kFhVe37EovirvyUJ0W8lMQgDgOBToAAaAaMWbaaE1yNQby5hVs1AGcQ0xLRuDGFlWmJ4fkNih9/DwgB6mwGt2ohKg2mBJCkAvZyCzdYhAiYwUMIhnKioe8vxgRXd9sg9BZu04FpAT4poM6PENsOvjEETs+WxIY2DfzNmuSpjgaWMR5d51FVAptVD2sClOaoKjqwnSUZX1EQ/Z9XdXRa/fE+YkgnI+cjCutQPzyibbLbIf7l/wj2ve/TooHSFH7EE+DqdoAuwf7n/zkW8Z/BbxrIrgXe+z6AF4i//gzs7JyYxsUxyZF1AbQ7sLJKtRjVPlTm5B7d9+uP4f/i34GfnRDru1iAzZfAg8fA6gbx9QtgvYb/4muI4wXYe+8RoOMCBAbjN4HinRHK915ekxYbZsu0kJLuW13Rd50uvn34RU9A8fC+lMg4MhcxjqyhO2A0bCo9D8mvyBiD5jqxLMQ+Zu9ZDsrI6agAyQWzbCSHcDS2w6KgC3r2sfWux3V/i5mmAIOPb36NwRsMHpjpCut+h+NqgUfTeyhlgZtuDR89Bu/GiSXl80WE4BJPhBH0Dc5Ai73ESnMFz8No7OeJRRScp4JrD+9Mmpz45C1InpI0ia0U+Zx2xmCV/MellOBxH3ajtcbrZodHszkAkq71zqGWEopzXIMmG5dNC2NsGgfEdBSlxsl0gkVRoLMWmwRIN8MAlfyCJ1U1MppKCEw1TaZ750gWZyycI99y8AGDMdBaoW06GEOMYlHQPnIJoIo0Yc37LU9gQ4iwic32qbLnfDaFjxGttfhvv/qX+OmDH0NxhVKUmKrZyIq1vkXBC/xvPvxfIcT/G667LXo/4P3FB+Adwyerz/CgPketaszVAnM9h+YajWtQihK971GKMknjepyWJ+h9j19tPse/fP5v8WB6goWe4qQ6xkIvcF7fw2pY4+vd17jpV/jk5jnO6gV+ePIBTsqTJHmkSapIixnAPuDp7Z8pHKYHA8OyOEppjDQRvh1uMNMzzPW3j7/8/Pz/Yf1M7lSkCWYOnop3FnLosTSZJlY9gKVLrgkGItKCjYseNiUV5xmAYBycK7hIfrR8/BtvsdDz8fUFk9jaLVbDBhNVgYHhs9uv0qKLQyE0NkOD88kxHs3eTUzgGj5QQbw4BHfJSiIYR2CRqixCAPcGpSySnHQ/BgVP7C/PrCIF4ORAnRAjOkfprEpIcPBREVEUmnyp3Q43XQfOGCZaw3o/ysy1EHix3eL379Ei3klVYTUMSSkgxrF72bboB5NEGxZccFRVgfvTKSpZYNVvcd11aKzFzphRXv5gNkNjDBpLYSOndQ3NFbamxXXbYjeYcTHGWkddjYXCdtPsF14KPY7BGANk8h4fsvvkpfKjp9l7A60lHk6p37R1Pf7q4hf43vGzBJ4kVcmkuorBD5Bc4Z+88w8Q8a+x7nsMzuDx9DHQ3+DLzUuc1UcoRIGpmqBOzGDne2iuYaYGiku0jhZMFnoOEyy+3r3Av331Kc4mM1SSJLEzPcFpeYqd3eFNe4X1sMMXq0uc1DXeXTzCXM8okIcRqM/hPJkVPFzEzDcfPXU2gqFQk/F4c8FiY7eoZYVK1uMxfue5YZ98mqWoh0DxLmikmowxtCbS58lSvUNZqgsRMQGpENNxzhg4SzUajPrt6FgETEJag4tYlmJc0ACAVU8JlZPkt/vVNVUzdIYCZ9a9x+OFxvsnJQYXcNVYuAB0xhEzxDB+v1zjwVMiSggEXGotMNgAMApyGvsSGYPgMY0/jlpzGB/RpvlWDtBRyaPoAwNsQF1J9C5g3RhsO1KlVVqMQJwLAp6Xmx4fPZwjAFjUGtvOplAYjh234Ay4aQyGgTz6JlV71LXC0bRAKSnxdd0YdEl2qlJoz+m8TACZPuui1igUx3YI2HQG3ZB9/zQH7XuHopBYr3s4R9JXrdMcNJEkBBrTNSGp7GgOSuo3Gn8RWgecnhbkOzYBf/u6w3vHRZpPMBQHdrDBU1/jP/xgiRhpv/UupATViK9XhhJSBcNEU/qo4gQUc71KDs8xnhYbjAv4emXwi5dbLCcaWnJMC4FZIXA2VWgMJbtueo+LdYdJqfBwWWBZifG4G+dswBig8223PC4A8jty0GKCDRHbIaBWnJJSf8vtt4PFDBSz9DS4O0AxZhmgEHt2MXuzxv85ELJvCzRZV1naGsmXlj2KjNFr9B29Zt8RG6QLSqnknO4bBuDiFVV3WIt4dUFAzFoCbs6NfkG2WBKbdEOVDEjpnZCSfm8pxnvsXMxx21oTAJTyIKk0PY/zfDQS2KjrBCA4fY789+l0DxY53yenNg38biCgNq8hlzWBusGCFwqht1BnM6BpEFYbhN4hdAbFew8Quw7upoHf9ZBHNXhnYNYd5g/n8Nse6ngC/eAY4cUrDM9vYNcduBJQyxr60REdYLMZ2GwGcXEJt6IQIPbsGaA0/K9eQMxKYDcgWA8hOaoK2KXkrByt7EOEVrQ6kg9andJZi4KnzcHQ9x5KcczPJlAnU0TngeME+rsO2GwQ//rfgdVTkom2O2IKQ0D8+b8DnAP73Z+A/Xv/AcQv/pb+xjhw7xFYXkzQJf0/dHuvazmh+1RBgCx3YR6fAyf3IGKkBQydWL7ZHLi5QvzF3xIbuVhAnO6AR4+oCuPXH9PrP3ofJEJ/q5Jj6GghBABUSfeZYe9LzBJlkZJ/7z0iMLxb75nlgxs7SEPME9PsT8xAkZgLO7IcnFFoh+Lky8pyvByAU3AqReZMoLGULKq4hE1F3Zzz0afCmYALFju7g2QSx+WSEkeTtO6yvSJwFgKuu3UCicQWWm9hvB0lVkqoMc1xqicA2jG9dGdocYXqKfwoaSuEQCmLcWWa2M84TnBzWXkhNXSSzQ7epACNHBdN7EWWtcko0rG7ZxQmKeylSWE4Ir3fPMnQLpoGLgQM3uP+dIoQ4zj5nJcFjJJY71ocLWcYrMO0pInqTdfhxXaLbQqlKZTEw9kMOZVuqjWu2ha3fQfrPU7qGkut8Wq3GxPmvA/ggqOsCrRNjxDC6FfZB+iEESSqNP6Ukns5eJKsT6YV6kJjSAmYkvMkh32D1fCvcfTREg/qh2hdi4mcwEePv7r6K7jg8OPTH+GfvPMP8ddXP8NE1RBM4Ly6D5HCaxRTKESBwVNvmuIKlaxRiBIFLzBTc0guEWKAZBIn5Sl8cBBcohIlSlliqqa47q/xFxd/g3v1MU6rY2wmDd5fPoULDr/afI4hDHg8eQpEPnr8DiXYQ+oYLUU5engH348ALwfeaK5xrzpH51tszeZbJ7l53OT/fTjoU0zjMcaQZIBhXME9lI7SBHR/nsi1AcYbCB5gAl3MldDEuqQJQB6DOQhnZ3fQQuNefQoGYkONN9iYLaWNeovW9ujdAOMtJJdjzQRjDPMkZ+xcDxs8FnqSqnXIb9rbYVykMTHcGYMzXY/+xTwOVWL5BRNjCE4p9wESnRug0vee6RqKS5K3Q6bORYed7bA1Jq2oFziuKly3LYbU92hSum3reqx6qoPpncP7R0forMVN16ExBsuiQCsENm2He8fzsQrj0WyGF9sbvNhusE5jcFmWeDSbJQ/mBDM9wevdLVbDgN45PD2+j0JofH57jVlRYGfMKEHVBdA2Pe3jpKrx3lMNTowjSFRJnqhT8AljDMNgoJTEYj7BaV3DhYCTakZg0fbYOIO/ufwEpShxWp2gdz1KSfK9T1efwwWP7x29j7//8Ef45PYLVIrOTUflXnKd03QtdwiIkGlBUAsFySQmcjIuAnHGMdezxB7LcT9OFIUo/fLmcyyKGeZ6grO6xcPZPdjg8Hz3CsZbnNf3kLtnx0sgknIj0MKU5jpJje3oS8ze5pyAelwco/cdWtt8B9C8G3CTAdWhV9H6vT/xECjmW/Zt3X3dgAhaHKXzFb8jzYsHUr3BB7SWak7upxqGwQfY4HHdOhgXYD2FkbQ2jH2GLlAfHmcMy0qgFEn2GIBFSQydFBzO0+MYIxmp9fvk1EJxTFLQDZ2PckAKH4Gm5tTBWCsCq40Jd0JoqJuQGEktyK9mQ4QdqMuRMTaGvaxbC4sALQWsDziaFuhMwLa3MNbDuIBHJzUGG7DrLTrjMasUlODYtQanxxW6wWFaKZzMS7ze9Lha92g6smlMK4XTXA4sQgABAABJREFUeQnBGealxLQQuN4RYHUh4N15CS0Ynl83mFQK3eDgHCnSikKibc049mKkvAylxAFwot8ZIynsfvw5KCWwXJZY1BohRhxPiKDKXs9PLjuUiuOoJG8ppSsDX9wOcD7i/ZMSf/TOnB6XPI2Lar9gqQRL+4XAr0ihQopHCMZQST5eI6ZaYFrkcUvPl4JhVghsB4/Pr3pMC4Fac8wqhbNZAR/Is3hvGnFSq7RYnmBXOnR9YiPz6wYQQZMl1yGNV5FA8XEl0Ke03t92+61g8RuMYmYPvSdZap4cRzU+ByyF4uSLZH6NDAjzBD/z3dbc9Wy59Ny+o0n/dJYcubdAs0G0lryCOXxGiH2PYg6fSSEaYb0lUOCT9K8sCQBmyekwIDoHlhnD9LnGRNTjY7DjU8TXL+k9M6sIEOMYI733ZrP3LGZgCIz+RZaCe+Krl8DVFcKuhd9SMiWvFAE2RqE18n4NlCXc6xu4ry+gH58BbAdeEns5rqYLjmg9iicn0OcOvhkgaur787db2OsdzKqFXlTU1wiAnZ3R9woB2GzA7p9D4g1Qloi7HVAUKP7hT4GiRPiLv0D0AcPzG7RXDa2WdWSuDgUNznVHq6+FFihLsZcaDQH/P9b+7NmSLM3uw37u22c/051vRGQMOVRldtbQXY3uRgME2WiQICBBRqOMlNFEo970oH9D/4ie9KAHmWRGo4kGUC00AWKoHqqruiqzMiunyBhv3OnMPu7tWw/fdj8nIrO6WgZ5VVhE3nuOHz/ue7vv9a31rRXHkhGkArmpudUI4dFIroFS4ogauf7FYuMyCcdDwcH77T8QVnBxC+Mp3r23hDF9+USccJNUrmvbCChLconC6IPuxwcOrDWgcVEnzmX3O98TQDc9do6pwoh7b70jAK6p4Lvf3/XLgoDOXnrdNzsYs5Nb9yy6cey2UlIMKTbyPq3luHQj38laOf59wyi39bK2/t+603R04nhqxW2xZxD71/YL095go2fgdCfyrFKXr/VzeZ5H43qZoJfxyLH0IHEUjlCeT6FLlvUK3Wkui7kY53g+oQqptQBFYbXMIP2clyUPJrueQs/zHAMoOYaFrmmNIXV9RP0xRA4ojsKUaTLmtlyybrbDYgMYcr1MZyg6sXQf3E7dwlYW62owFCjaajC02DQNvgdZGFI5aWrRthzmOZFS3JQlL9biZChZcyHjOHWS357pEZB3lGXObTKmNYZVXYt76bYkz8T5FYQdiYOI1rQsqoosFEv+3jTH8zzePThgFMU8Wy0ptGZRVRSFAMWmbp38NEApRVO3Q+9iFIfDIqmuW8JQHmR9pdX3fULlE6lY2BnfJwkCJlGM7yvWzZqztBvMNUIv5PdOf491s2Jez5lEE+6PxTjm+fY5h/GBk3NGQw9sEqSsmxWLZkmsEmbRTEwsOllEGmuIfbn+7x+8j7WWg/hQZJhWOOYHo4ds9YbKVPzWwQd0tqPQUtAbBePXxrncrjta5zAa+ZH0FLpIi8ALUEFOoSWHziARDLrTLJo5ne0GN99v23qDm75ncQCLDijKHHSMvpPj9cBRuwiafkz3PYuSg7qTRgOYvR6uXqbXz+PACwbTqW1bUOiS1rTcVEtaI0Wd0FfURvJMZZ+dK8Z0rOpq+IzARWHkUUqpJY6j7/tNguAbczAPxa1zFk94tb1hXq0w1uD7uwxUQPIVm2LIV+yLOZ7ny7jzQ7KwL77ccF0uWDeNm4Myt27LUvqO25ZZkpAFIRfbDc9WK+6Nx+7zhL3s7wG9jPD+ZEKb56ybhjyMhoLOdVGw2JaM04SRk56e5jPyMMVYw6recj46wDKXnMmmxAQd/+D++8Qq4qevPsdYy9PVivlaxlBdyYLVuL6gpi7R2hBFIXESDQvXpmmJohDP94Z+5sDdA4+zjCxMUJ4iDzPiQBjNyggY7d15PQ8+OPgupS7YtBvyIOfe+JTIj7ipbpiE4wEMypg3rt1gy7YtBomp7lqRQ1sZn4EvkvG3pw+wVnoM97MYT7NTSl3QmJZ3Zw9FauiOrR+LbwLF3ghH9m12bsB4xCqW74aYjCV+irHa5UPujufN7U3n0zczFE1nB4My5UnAfA+09o9xv1fLWrs3L93nvAEU+47HXqKauYLAutGUbUdtLDcuP7HPrGu0ddEHbrHu+se3tbhWSm+iRxJ4pKEwUI22NE4WGof+cOxiLqPIIsVJHnCYBbxYNdxs9cAqgjBFIMY9SyPZfX1Pnjz7HWgJJM4B4GLdcLVpKWrNthZ2Mwp9NpUW8NFJYH0UKG43NZfLkpNpwtYTMiCPAwKnJhCRn+V0mnI4jilqTeqklKuiYVW0bIqGNA3JnfT0ZBwxjiXualF2HI0i4YwiCbxPAp8/fOeASHn87PmGrrO8WpYslpK3WNdmMJnyPITVNGI2Fce7tU3bdkSRQinPObIy5BiOkpA8lqLzJFHEgc9toSnajlkCUe8/4MF3jhJKLYWALPS5N41IAp95oRnHijiQfM7eVClS0uO4bQzhIAF2BQ3b95bKMT44kHtSFrzeY3jqXG8b3fHOUSJKKS3GX1n4puy7B4xOXu072akVuanniaOvMPTynjAA08G2kdzOUHm/lpnst78RLNpehqrb3eJXfrH7eRC9Lkv11Q789cydtUPcxbD18tWu12vsSU+9HkD60svWNtiXz3YGM0oJ6BuN8OIYe3Ulv3OM2RBjUZYi2QwjcUe9vcV7730BnH0siJFMJtp2AJ4eDP2O3v23IQjE2XU0wroojoEl6rqdWU4Y7tjFfib139la7KUcg7ld0d4I+AimGWZb48cBXdmKwc3BAUSRNL46B1U/CjBlA1GE+fo5wSwj+t0PZd9aw2JBc/1UmMWDXE75uiIcJ6hxKn2KPSBvW2E881wiQQK1c3TVGh69I0ZCb93DKwrCoiHe1kw6SxQamtY4yY8hUJ7DX8pVTSSuQ/ke49MRfhphVvKQ8ZSPbTReKgZD3uHRLjIiirFXr4QpvPtA2MAglPGVu9ekOTz6jlzrLz8Rk6OLZyItTVIBiLYTKerkAK5eiGPqeLoDg4E4lwpIc1bdvQkTQDYR1m/qMjQX17LvroPTt16XRfezy/PlOH3n+KuCXY5i08KvPpLjOTzGfvVL+fligXfnrhzH0akA3zfnHzunxZ4Z8Txv6JEy1qA8NUji+puNSFI1yle71zgAONyQcA3/XTcAu/69/XWM/GhgUV4Urwa7fA8BfBOVkwYxr7a3zjHRJw8T6WkyrbALDvTVpuF6s+Dt6T3azjCvVkN/onKmGH0lFJdtOI4yTjLpoZnGYwJfSXW6k/4xMVcQEN2zKbDrkbHgqtAG3wtY1RtxIG0aVnVFZ2HssgZDpWhd/+A4jsWowy2Y+xzD2hhGYcqvbi/IwoDvHZ/uLeoNn5clRdMyTiIxq6kbRpmY1fQgEiQmpA/klh4XyblTnudcGSf4nuJ8ZFi47MTSE7v9vjdSZK9mkKP3pje9/NTzPCbTnDwKWVeNc4eUAPKz0QjTdZxmYw6SCcfZDICv109RfsC9/B6xL9b2oReSBVKgSlTKO5N3aUzN58vPmcVTnm+fc5qekqiEVbuUhWc4YRxNuKmuKXVBHoxQvhSS+l5ZuU59SLdh47L7xuGYWMUiaewMi2ZOpMS6/Sy9Myxo9zflKTw/prOGjZYCR9M1bgHb8PH8lxzGhxwmB3y++JwOy1Vxy/3xHQBO01Om0ewb+5X5YIa5t29q00tP35yD/RwznRmY734RLP2N+4tSAcfD9/CDQaIHuLxTMY9qO81leU2tm0F+nQUJQTQiDkIut7diAIXHKJbiTtsZtq0AuNAPua0W3FRL3ps9YNNuHdNjhqJKbw7Vs/ChrzjOZtzNz4UVHIfkUTqwl70hj7WWxsleQYykfF/J37zea31bLrmplgOQA5glCVsnD62cIdVhMiIOZJw07nOSIKBsW2IV8fXyhsM05UfnDwFxbp5XKy6L7cAsdlZ6GcdpwiSOhz7Ffg4mQcxJdkClazf/FJu2xNiOB5M7GGt4MDlh3RQiV60b8jwd5mDXWYwz+QDj5qDc0ntHxsPpiDQMWdc1lp45Ms7opuMgmbjeRI8kiLku5/iez3Fy7NhY5b67PKsiFXInO6ftNE/Wz8iD3JlKTcQIR2/prCULUrIg57a+pTQVeZANBQrfg8BTWM8S+bsCR6V7SX5C5Eeo0McGlmWzInExHUfJ0QDU9zcPbyi6tE65ort26L19vHrKJM4Zh2OebV7QWeuA+hHWWg6TA0Zh/o39/jr30/7f2lrXi4j7LAZgJsqcvSXYAAH7uf366ngwukH23e65ZevO8nLdOHCIk00rDjNhj16uGmrHKOaRRBy0xlI0EkUR+h6vti3Xm5b3T1KW9c6JVIpfArr66IwAcUw9H0fcm0QEvkd0IGzctjY0Rs5BP950Z2n2Xe/3yJcBEHfitHmzbVkVDcut3EvSWFHWhjj0qVtLGPhMs5AkEIDVmm4w/al1R6w8LhY1syzi+/cmDqDD9aZlvmkGZjEKoKz1ABSzeMfCNcaShj7nY5+tcxP1PVjXkqP46DCmNZa3DhLWtRHp554ste3XoK04gHdGgGH/DFRKjHcOZglxqChqp5zyBEynUUBrLCe5ZBD2MGRVaQIPDrPQAW45l8IKdkTK43wc0nYiP81jAZmTRBEqj7KVYkEWivHd3AHQPPIHgO8jpjbW61VS0v1Tu2itWElUyihSmNBnUxsiJxOdunP4puy0d1a1yPVSvkfjsiyx8PW8Jo8U00TxdCFtOkXTcTaWAvMsVUMx4ddtv8HgRr8OFPd6Em3v6NhUsrDv+xP3J6DWztAmGN4nC2snE+1z7+B1GWrgFvbrlRjbVOUuW3F24HrrNpJ5mI92BjTWiuvlbIZ9+XKXh+griVLoWZr1enAi7XsUiaLX5aVpinfvgbBYAFkOWY5XbIW5CkIxUGlb+TOdyt/brew3jncSVNj1Sbr/7moxrmgXW/w4JDw7wAsK/HfflgzIyQz72acQhpjnr1CHE7r5Fv/FC/A9ou/cxzs+wRZbvCyX+I1G+h3bRYEpG5L7R3iRQo1SzHKLFynMk+fCPj54IKf9558Snkzhzh3p2SsL7PwGvviC9mpJ82IhslH/9d7D7VZkBXHsESPBpnEsTlNVZcizAOtGs3LMphrFeA8e4B0eYV9dYDdrsfTdrAWkH51K5uJ6Kdfg4MQVBnJxPgWRMFel9J7+mz/F++N/KuBsvZD39j2BnicMXu1kzJMZRKmM1bYWpq9/Xc9Mpi4+w1fCLM6OpS82COHU5Xnus4nwuhS1cmN1NJVexGorMtr1Gk/Je72zu9hXL/COjuTaPXzXMY3fdIfrg8D389xwkl+RifrUzjxDWz04k0oEhgRZV1oiFKRJvyPAafgHi3qL7fp4DnmYBm5RITb/FY2TlAJMotFgnLBtS5IgZhztMupCXzFNxlxubyi15LYlKubF+pLKAbp1U9BhaTtD6ItUL1ShSNtcxTfwAw6SySDjS50c1VgzBENrJwsEBnfHoi0HV9NYRcPCppfE9pKkWotMZ900KM9jGsfU7u/MhZCXbcs0jrmtKg6ThEJrLrZzAB5NZ5xkh1wVt07qKg6rSvmsqwbf93hrNiVWijQImFfV0IPVdh1HaUoWhjxZLpklCUdZxihMqRzIvtxueLnZsHKMouTE+dTO9bgsanzfI3Bh4/v9U3XdEschkZLzmYQBoZJu0FmScJxlrOuajTMteVXcMI5yHk3vMo0mbNsNhbflMBbr+8zLWDRzUpVRmZJKV1yVtzzf/Cv+6cN/jPIUq3bJNJoN4K9nE2pTs25XjMIxWZAR+hGNqdnqzcA6hCqiNQ1JkLLVW7doX3MQH7oerp3kdTc3dlLPfitMQW0qonDCKBxR6IK/vv2IZb1ypk8eZ9k5L4uXnGVHFLrkncnbTrL67cyidtmMA1DsWcU9JqWPptmXp/ab6cwg6d7fRGq6k7QCaFMPRZ8+G07iPerBFMZiOYgl27TUkp+YBxmTuB7mdeArZvGYi+01tXMQ9jyPi+318PnbVvqUe4dhD4hU4KJIfFfEiLmTnw3OyGmQDAzRpt06YxUxpfI7n1iNaI1m2xbUuiEN4iEvFaDrOuq9ok7j+oPnVUmiAs5HI9ZNw9vTU/IoZRzlYsBjLS/WCw7TlHlZ8mx9je95fPfwlNPskE1TkgYxtW5oTUegFPOypGhbHkynhK4AtKwq4iDgyfKaJAh4MD3FWsvPL59ykuecj46YRCMxhalXfLl4wavtlpfr9SD9NsbQNMIUVWWNUj5BGBBFIUr5RJEw5FXVkGW73MBpHJNHEXkY8nB6ymE65XJ7OxgH9YW4w2TKKMwpdUEJTKIJEmETs2rWJCSOqW9Z1Guuir/m7939O/jO5CZzcUaWzhV4YhdzsxUGU8UoL8ZYTWXK3Rx0/bGRH7m4G9nfOBoTqQjf878BFHcqjv3+rpq202RBSBDIsX4y/5xtWw6FxuP0kJtywVE6pdI1d/NzIhUO+9vfTCfGJz1YtLYvAAqIs+5v3xU4+9/JObCYbmdo07OLr+3f7tj9zg4t+wNnWrSayrF//XtnaUASSO5hpcW98iAL8DyN6SAKPKaJ4sWqpdbOnKWD58tmsALa1lJckt8LQIxddmDgy/0hj3zuTqLBtCYNFHfHiiIxbGp537YRd9badMxSn8Z0rOuOxnTEgU8eKYlJ8ESSWOtuYDxbl+u4LluiUHE4jvF9zYPDlDyS/rmiFXfUy2XFJAtZFi0vFjJmHx7nHOUBRStmMNvGDPvcuDzG01k69CgWtTCfLxYVceBz/zDBdPDpyzXTPOJ8HDJJFGXbcVtovrgumW8ablbVMP+07qhr7Z6BDb7yCUOfMJLe4ChSjn3UpKk/yOazOCCPA9JI8fAw5SALuFg3VLrD9yQfEeAkD8kjAcUdljwMhDnGY1UbIiVAt9aWVWX42fOC37svxdRadwPTO3gsBB6VtmxqwyhWIgdWyrXBSDuM5wlAlOK0KCXEOK8jD/3BKCmLd+zjUDSxrxva9IWN0PdIlPSvfnJZUmkBkH4NJ6OA20JzkAWUbcf5OCQKXpdhf9v2m3sWe+mpc2TE7hnZ6EYW37bbyTN7o5je0KXfT2ec7LQTc5qBWTS716W5gM+2EangyZlk1o00XlXKor6Xw44mUFzIxD4QkxL74oX8PZ8L8+h5eEmCvbmEyUTAXxTLsfUmNL4voG4PbAJ4xyfCKFm7+26eJ5EOozFsN3huwT0witvtDhBmGd7Dd4T9kqeMAMCP/pp2vkVlEX4eE0xSvPMzaFv8np3UGnt7Lb2ViwXq5ACsJTzIaV4tUZMUDg+xT5/gPXgEswP44nOCWSYOp+uK6GSCmsjDSt9K1d4sCqw2mKLBX3zCMOqMkb7B7Rbz2Zc0Lxc0i0IWLS4Koypaqkq7hn+f8VgWpl1nmc1i4kTR1Ibloh6obnu5RamCyYMDMdA5Ppb+0emBANO6FpBeFnjjCRweC7DrZc+9c2mfSXh8vvv5ZCK9poHrN+wBX2+U1NRS7GhbYS/7gkOG5HraTkxxOicD7fts05F8XpztxuJ49jpQhF2Pbl3siiXLWyczjeHqFq5fUf6LfwNAfGeG+oPfl57M50/g9A7eg/d2sTDfYt3/mpkGO+ldn0VYO1mQx07yJg39u+PsQaLvJJraGnSfm+V5dM5F1diO0A+k56/Tg/mNLDhkwZeoxJnTNORhxqoWWdYsGZNHKS/Wl4QqYVmtCVXILBbmcVGvCPyAB/nRILesnGzXA/IwHdjAvidyloyIHQNVaVkICyA0YrDhFu3GGCLXdyWgVrusRZ88Sl9byGRhwrP1Nau6Ig4UkQrIgoCjLBtkIkkQODt/kbPdViWzOBagkee8WK8JfZ/TfMaLzRVpEJMGMeumYByJ/G1RVkMcBkjPo/J9FlU1gNOeSe0t2Rtj2FDyZLnkcrulLGuwEEYB1nroVlO7HDelfNIsdj0bHeNJRpLGaG1YLbYOcMDtYo3v+8wmOUdpRhaGAgp8xUk+JgsSjrMZ18WC+5MzPjz4LVbNapCPzesFWZAisQxrDuMjOtuxaJYcJjPW7YbAD0hUIr1SXTvkKNZdTdu1VLriID5wfYOaUTAeYiwSldLRDe9RniIPRq44kFGbirZrnTPr6/OjnwuVKYfPXjYLTGeI/Jjr6opXxSv+bx//KwDemkz4Rw/+gO/OvsvTzVPeGt3jweihOPPa7lsZS2CYfz1QhH4RagZpac+a9gB236jD85yBkzWDUZTM7Z0Rjhn22xH5EW2nMVgBfdGUQpfkQUcdiBuxdsA2DzM2rdynD5MZWZDyfHMpDrXVilhFzGKRit6UCybxiDv5KZGK8PAodC0soicZivtz0Pc8TrLDASj2x6o8n1GYD+ZF1lpKjVvsG5qupTItkQpIgpj7E4lj6fswR1HOL2++5LYsycKQNAyZxTHnowMXhaMJlUjS59WKUZSxrDacZAKCDtKUi82GWZJwkEx4srrgrfEZ4zCn6SQLtXFRHKd5PrCJt+55v6iqoZi0qJ7ItUBs5ddNQdFWfHb7khebDatC3hMESgxqGpmDnSsKZXkyPANH45Q4iWmblvWqGHIeb6z0gd89mnGa5xynM2bxmHE4Ip9mQ395rVvGUcZBfMCm3Qxy560uBoOyUpdMoykW6/JsM0otMuXADwkiNfStgzDTuhPpcxomIv23HVmQUmm5drGS+0jgh3hWJPtpIIx/5EforsV0mtyNj/2tj2ERWbX0um/a7SB33rRbbspb/t+PPwLgPB/xB3ff58H4LV5trznNjrjjWOv9435t/jkGsQd6FicndcBxHyj2jOCbvY/9z/tiqMy/HTDcf/W+KiXwPCZRSBJ0g9zVc8yUzBnFqmpQfsBJLn2Fz5aNjK3SkIU+PiFp5HNTaA7TgHvTcFCU9HmJvu8xTvaUIc645mwUDv1sfRHJA0ZRQBYqChdVUWmJYumspWotdSvZkWno8+AgYhIHwrxayyjy+fnLgk3VkkYBcagYJQEn45jayPMkdgY6i1JklsvKMHP9faMkYL5tmGQhszTg63nNo8OYcaRotGWchtStoWokNzGLA2EMSzGRWpfiPF75PuuyHa5F1wn4WteGx9cFN+uabSFrBKV8jOmoKu3cTiXvMcsjue7WMhpFpGlAXRtWq2rgnW5vhWU8O86YZhEnDpBOEuUyZoUpFvZP+gg3tRn6YPsMRZDXjGIxAdo2hjzyqbSMBeX7BKGMHa9/rjsZaC8p1m7Mxt6OBe57H5UPnpX3Be79QbTbRxq97voNO5Boul2//LbphvG5bQzXheZnT6TAfTiK+fDOmJM85GqjmWaKO+NweO9/WHSGbncL932Q2DaOcdxjB13MgfR94Rgcly1n2MlLtQNf1gqTV5eyUI8cgxc6A5jlXP70kQLjiTAwixvo9sxlOgt1iX32TMDI4TH2xTPpE3zwCLu4xctymB3JAn9+I72H/dZ1g9STON71HPYgcXdlnMOl3ZncjCZ4vo+9ud6Z63Qd3L0rx3ZwtDNVMQb75Cv0kwuS9+/LPo+c9PD6GnO7RJ0dy+vrGu/kVBxTe/OdIMBui53YeT6X9yuF/fRjmi+eo7II43vE4xQ/CfCCALPcDswg1qLyhHa+od02BNMUL1RiqnN5iVlu0YsCs66IDnNuniww2hKEkm8zHkUEoc9m3ZKmAVkW0rjG2KLQFEVL32Qs7lMdWRbR3mzw0xvCMMSmKTz7Gi8fCWN3fIo3O9oxy4cnAgxfPcdW1dCD6p2ew/wKDk8lIiPLsZ99Ak8+hwfvCWAM7M5BVwXijppmIi0d+gz7ftZE/ntzK/tMnEFR/8DylYy3g5NdLuMwZuzQ3yj9jAt5/eHZjskMQsyf/Tnh0Zjg7BDv7belR1IFeD/8fenLdAux4Zry5sfszDWAgbHRVmM67R7+vYW/xWLwrOwr8iMq1+/kex6VC7ffZ1CMlZxDD2+Iz1CeosMb+hOn8YSmk+ytLEgdo9Czl7sel6erCw6SCYfJlIvtNYHnc//gAYta5L13RidiDKAb1s12OAYLLoNRjC/649Od2Vugus9xkr1eyteHewu70bM/llmc4ztwCSI5A1jUa66LgvuTKcAA5oq2ZVHXTOPYGfHoIay873PKgphlXQzH/XIzJw9DlO+zbLZ8tViQOrnq6SgndIYz66bBWJH7Vs5YxnQdy6piFEfDjf2mKFjUFYUDhQfjnBevbtlsCsIwoCzrQQK3WRfESUSWJYP5RttoyrLG932Mi9Tw/Y4ojijqhltVojyPwzTFWDHJqU3DBwff4fD8UJhpa5nFM0pd8rK4oNSl9Kd5PqfpCYtmzlF8TORHLMIFtzef8Hj9mEfjR8R+jPVl4ag8ka9OoxmJShiHk0He3BtbgDzsNs2ao/iYTGXSj9sH0OMRq0T6Gb3X51/fn9vnjZZNifIVR/GxsF56jfIUf/LkxxxnGfcnR3x49B4fHHxA4AX86PhHjMKRA6D2WxepuzliBlOpXhJusUNPZD8nLXt9UHvjVjvTGgGYengw7/cYd05eHrj8yV5uvW7WbHXBQTzD4jEKc0I/ZOkMecSYI3ALxponq5ecZIccJBNebq4IfMX9yR2W9ZosTBiHpwS+YtmsmFerb8xB5YlZ1M4kxL72ffb7L0GkjKmTR86rlcsvbek6w/nomFhFQ7+zVPg7nq5e8nQ157eO5bl+kIiz62255KYsOMsnBK7/8iiZDVmqnvEIfcW6qQfzqnm1GtQHXyye8OX8hiwU+djI5Sn2rqltJ9EGuuvIw5B5VbJtpDcy8H0aY3i1nbOoxExnU9VMspSLq/ngiCpzMCEIFMW2Ik4i0jQeIjUqF1XTS8P7eJt8FHFbFGSBMLdJEFNsL8nDFOUpDuNDDuKZc7U2jKMxla64Lm+oTDNkUx6nB6zb9cA2Jirhy+VTLopXnGdnw7zS1qDc/XkcjYhNTBakdNiBse5zRT08trpgGkcyh+1uHPturo6jMYEfvNaj2I8LKbJ1jo30mUQTWtOwabf4ns+PX3zKQZJydzTm0ewejyYP8D3FB4fvkahkKAJ9m7QVdtEZ1gG43uRG225gUfr518df9LUafyjUsOsZYw8k2t5Mqp+vu+9trWXVtBRtx3EW4SuRYfqex6Jq6dyx9P1hq8rw9aLhfBxymAY8XdZEyuf+LGJZCbCYxqLwWFQtN0XrAI0A3aoV5icJhPXr2DGk8M04BBADkzwSg7Oboh3cNjtrueNC3ad70s/OWh7f1lwuKx6eSGvPQSbrg+tNy7pqOcgjlC8GPsdZQNtZqrZziiXYVgz9/7el5iSXe9YnVyUv5gWJM1gbpyFxoAgDn23VuqgPuYZRoFgVDVVjGKUhYeCjjeVy3bCpJHuxrES+enm5HeZfVbVkWUQQyHo0SQKSJKBt5dlSFJqqal0RXHIXjbFkmWJdtNyEFWHgk4U+T+Y1eawGyen9qXJxQcIUF23HzVbkvq0Ddkd54ECieCBEgeznctty5oyPvP7+6AkbOI592k5Yvv1N/lMY5W3TiYzVe/1ae554Z+eh/41CTT9+wRW7nEFSHvm0Dsx6nsfHz9eME3GmvTuLeXAghafvHCfEgT/M6N8EFOFvxSx+C1BsqiF7cVg4xyn0JHsfG1CX3+jbw/OELdquoWx2bqlRJPvSemAmbV3hFRsBUD17l40k9245FxDYx18cHwugiGK80zMBItu17PvO/Z2EVjsjnCDYk70GAhSzDC/LpL9sPHm997D/TrBzWvU8AYJRtOtjjCIBQifn8lltI9LOv/gxzcvbvowi73n1ajg36tF9x4SmWM+T99zcCOtZVXBxAdYS3T3CLNbSm2mMSEatxU8jrLGYTUV4/wgvTbBFiTWWrmzoGo0aJZh1SXWzRbcdk2lKMMvwlE/99BqVJ5hNTV0b2ucrFouG6SSiM5Y4UsSJIjTSi6F8j3QUwaZhtW6GsFxt7FBtrWpNVPpMzseExxNhezebHQiuKtiu8T74gfQV9nEZcSzX8dUL7NOv5ZxPDyBuhBW8fIld3EiG4mQmJku9Yy3Ia2DnOhoEwjQuroSdjBJQRmSjsyMZK/3YqAthFX1P+g1918/55ryotlLguL0UYLpdS6Hj6gK7XND+7JfUz24Jj8cE353Chz8SOS3I/v8Wk3OfVey3tmtpTD0s7i12MLMBsBisc4rcthuyMHvNvKN/OJe6pLOWyA8da6kkZ9EKoyEV41Z6v3oQ6cxArLXMq6WThoocdBqPOUymJEHCYTp1n1HRGM1RKpl9nuvHEnC4iwMI/IBYRU6yFpAFKcrfSUj2TX36nkXtquadqyx3jlGV3opwAIrWWvIo5RdXX3NblsOCQXkiQW2dsc1Jlrmf+2hEtlobTawExC7rwuWijbnYbkmCwElPGtrOkIdSobup64HRWNbC3NTGULYteRTi4bEoKtqmJQ1D8lDO58V2SxoEEuLdai5vlmzWBfkopessURQSxTJOc+sMd/KEsqhd1puLbjBmWKha6xzoxhnjWExtaqfoyIKQbVvxk8uf80f3/j7ZnlNirERu+LJ4yRcLmX8H8YzGtFSm5KK44Ka6ZV6tmEYTyQn0dovJ0pnR+J4i8qX/sDY18/qWk+R06EksdcEsOhhccTvbUeqCxLGZTVejXHbga9PPGgpdkKiEm+rayVbFLfRVccltNeffPPuIL+dzTvKc3z0/4AdHPyBVqeu3TdkJzf7medjnKFq7i6zRrlAjBY1uOPa+F7PvARSZp1TH+wLHbsyHVFoyGIcFs2Moe4MY31PUuqFUlSz+laLDkgYJhS5ZORDoucr2WX7ESXooTEcm57XQJcrzOUoO6aMYWqMdOPSGBXI/B8eRGK+Mwnzopeu3faArJkK7HurAV4PMMFShGOO4zEDTaZqu5S8uPuZisxkARuAHXBXzYbH+cCoFpcSdx9o03JRL8jAl8BUvN7dYhCWelyV5lKI7w6Ja02HJwnDoU7w/mZBHEZtG+nPKtqU2hrH72XxTYrRhliTMEgG8fZbqthXTqKuiYr3aujnYEUUBYRQSOJDRM/wUsN2Wbs5ZOietMcZQ18JMHh9MOMoy0iBm25ZDT3elawpd8t70bRKVDuc4jAJCP+C2nvNkdYG1HdN4LP2rpmFeL5hXK5bVmvwoG9oSPM8DuzM46wuBylcY07Js18ziKaEvpjilqZy5jT+M06ZrhM3Eo3MZvW8CxR4ghn7Asl7ie767Dyjm9ZJFveavLr7mxWrNSZ4xiUe8O31ErIQUiPyIv83WO5727JMYsFkal3nYm0F5eHj+jmHs53bvngqvM4jKg9YyGDr143t/jipPYg9qbQiVP8yVUaTYtoaFA4EAUSDGJ+KWCqejkFB5bGsBgceZeFBYBBhWrTBWvcdjoCS+YJoEpJHPNFaMIvXaIt7b+w66k+gDzxUmpJ1DAFmgfMax4iALJDLBCnj4ydMNtxsZF6Ig8LnZtgMovTtLZP6FYkxVacutM3Ep2o5XK3nv6TRlXbWMYzHomRfGyW+FkawawzSLBump6SyNNrS6I40DNlXLalPTth2jNCRPBIZcLkuSUFE1hrrWbDYN63XNaBTTdeJyGscK49agvi8RHUXRst02mL21p8w/kawGgc/RYco0j0gCj3VtqLSlbMW0ZlkZ3j5MhiKUrBkEEN4WmhcrMQ2bpcKexsqyKA2LUrIg05NkyIXur1Fj+jYJAfW+Yxq3jWEcKad+slRG+hn7J1wH4Hwc+jHbA8Ve2NZLULVThawqg+8J86l8j1WlWdcdn71csVjXTB3D+85hTOj2G/wtojLe3P5WzKK1TqpoO1lMO5YCFYIuhZUxeiel67+Vr1wvo78DAi7IfugV68GkMbKIbyrZ78ExnufvPqsHa1EMZ/dExtjU8t9JineALNqbWhgl3xPAcXAk772Zi1HO1aUAzziWPw6YEsd4s0ORdPayxJ6N+rYtSeSYlcvcm053Zj7n9+S4vvhEegk/+5zm1RKzdRP102d4oSI6neB970OJjIhdxuD8RiSh6zXe2+/I+d9s6BpNV7Z0i0LcRMtyMEixX8uCrms14SzHi0Jn2OOYUN8jPBqjVwXdVhwgfd+jXRR4UUAwy+iqlvZqTdMYtHP0OjlOSNOAppHoizCL0WVDFPk0TYcfBeRHAXVjKAqx59dOgw8QOoq9mheol3Oi+/dFFmyMSFAnE2EVe3mx58HlSzm/x6cyFlYrbFFC1+GdnsJ2jX3+FO/omOpXz4iTf4P3n/6vd9elv15R7MaclTGxvJVeyCSFiZimML8RkNpf6/71thP2+k1GcfgMGVt4PhyeYv/ifxE2eDKRYoZS2EYz+uMfSUTJb/1Q2M39rS9U/A3bm6wiMEjzhKEJXAZXQGXq4YGvfEVtalkgdCKT28+26nutelagMQ2dixWorTCNiUo4SY+G45BjELneKMyJVCTH4RYRp86IptQlseoXGh2jPHc/l/iCeSWS1MjzXLxHzzaJRX9/TAAeHdazeNZzfWNOEth1OzmRq24n7lr1oFMWjVvazvDqdsV1UbBpZOEu7qMeszjh4fRwiOeQXkzJiFu1Nee5gF6LHWz7ewfT27Lkzkgq7ou6GpxUx47RqJ1ZDsit6DjLKLXkvEkDvmJby/HkYYg2hqttCVYecl3XcXA4Fnlpa/CVTxyHNI0mzRJ0K83+41GK1pq67l6rSAIoV+Qoy5or3+cwScjDiLP8iFhFxCribn5OFuR0jkG8Kq+wdBwnJ1S6Yl6tWDcFFsvd0Rnrds1XyyfcyU/56aunJMG/4589+ifDIrcHdpGKCbyAzuXELZo5y3pFohIOIhkry2bJ2GU69lLQPkfU93wCL/yGpKwfGf1i8zA+4s8u/4xtW3AQTx0Loii15r98/0ccJBN+ePQD8mD0a+fZmwvh/a2Xn/aS8F52J2PfFwMa2zgDkP2+x51tey8z7c9RZzusm4OSG+m5cSyukNoB+nE0GljG/S3yI5I4IQsELIV+QKxiJtHEGdtoZvHUvTYc3G2XzYq2a7kqbolUSBrEMlc9icAIVeB65kavmV79uq03NPGRIsMkzocCz1EiEtYn6xe0Xctnt8+52G4pW5Gh9aZSZ3nOh8cPJBtQSfTDql6zaQrWzZa3p/dcL3KF7jpRAVSVyymtOM+P6bB8vZKWlLbrmCUJcRDQGLMz7PE8TrKMVV2zbhpX//WYlyWB7zNLEsq25XojGYrGmUgdHE6I4nBg8NMkom7aweRG+T7TcUbTtBjTDGYb/fXuzaaW25IX4Zr7Y8mbtXQ0RjOJRhwkE2dGpgm8kEU9p8NyEM+ot81gzNVZy1kusRrPN5ccJVM+ubkmVD/nj976w90cHPq+JfDeWuuiSjaUuiRSEaMwp0PYaykK7NyY+4KFcr3vv/76y+8m0YRf3PySWjeMopxRlOLj0xrDP3z0LpN4xHuzh2TO4fVNYxmZB963/nyQoXY7+//aGJGEuu+pO0sWqEFm2gMw+azdvvqFvLgi71jE/W0fkOVhQDT+5vov9H1mcR9VIUxbGlgOU2+Qex5nvSKlI3UxSOtWU+uOV5uWKPAdk9hnJYoD53EeMIqCQX66v715dmLlO4Mfee0sVZhOPus4Dwl8j8fzikZbvrgquN3UVC7TsHLmhAd5zPvnOZnrjQuVgI9NLZLQR4cS2bCuJdKqcZEZszxiW3ecT0I6Cze38izTpmOSCVvYG62AjKtpLjmNlWO9+t7GMPDJ4oCqNSzWNVp3aC2Fl4ODlDhWtK20PyWJrEejyKdtRQ4+mcQ0jcEY7SSrfR+oR+DWoOtNzU0ccG8Wk4WKRHdUuuMwDRg7B1XddQS+z6KSuT9NA0wHRa0pG421cDwKaIzlYt0wSwKe3xYo5fP3H413Y8ip60LfG+ZTDxTLtiNU3m5MuJzDnqHeL1j0xe9+e9OttC9ejGOfj1+VNEZY0V7aajrL9x4eMk4Ujw5jIvW6A/f/r9tvjs6wdidH7SMIQBbKbeNkpo4N3Jf6tc2uTxGzMxNx+8VzUtLO7PrMbLdzqqzKHQPZAwlrd3LR3tWydfEZQQiblQDBKJJjzl0e33opQHF+gzebwdm5MFJ9v1iSvt471h9n38cyLOzdjSN1hh6uR87r3TqDQJwts5FIKcMI85OfoZelMHt5DJ0lPBnjzyZwfi5gNh9DXWEvngtbmucwmUjMRllCWQrQ7CxmVWIbTex54ui6WmHrBk95dGVD9OgUqzXdtsZULZ7yUeMUsy7Ri4LNqiEIPJJczrNeFuhFQbupaBqh7otSk2fSMFzXhroR56kg7ohPxmxfLgVQNprk4THpvKQstVvkigY/z8Od/MFYbKPluxwd4x2fy7W7fCnX0lcQKLi+kGsQxXL9Jwdw9y4e4J3ekV7RMMI7PIabS7xQUfz7j8l/8COYHUrRAuT8GyNGNraTvsbJTIoInYH1XK5pfx2NYxB7cxxr5amxXyjYfwJ5PgQxrG+wP/9LKVyMJ9KPGIR4F0+JJ1N4/4ey3yjZfY61AkL/lsxiX8XvnMnGvk3/pt0MlX7lqr/94ro3KejD7neSBfm7X2z3zIe1Fo0eJJ+1qV1P1HaQ2nl49FEUsfKIfMlL6/uReimS8pSL1ZCFUg9Ot23JJM6ZxDmxigYTHh9/MMHot8a0Q9D5ayDISh5jH+8BDOYI4igoDJe1HZ7n83hxybZtBwmoxTKOYkZRxFGacZhO8T2JD9k0kv2YhQlZmLCotxhny752IK+PxDjOMrZtQ2PK4Tg2TcO98ZjCfZ5xFd9xFFO0LcuioiwqWXRmMdbKA+q2qqQf0clH67olTSN836dtNE0jDGEQKA5GKTcuFFxrw/l4xLasaRot7GIn5ytJ9ir31rn3hRF/5+x7PJo8IvACXpWvSJQwU5Efc1NdY6x2JiYl03jKw+ldrLXcG91hHI4JVchJesxVeU2sFH/y+Jf8/tmPmEYT0kCYKLHq184qXzIXJ+GUaTSjsx3LZoHFDlmIvXRVppmweHi7HMU3N+UpfOWzblf81dVfMYnG3Mvvci9/i8APmEZTJh9M+P7h9wdzEA+P1uUhSpHiN4MhmRc7oCjh4rtii3XAtu9d3N/k8/TQp9i/tv8+xslye6AYuLxKYfF9x0q2BH6I6Y1v+gWF76P8gMzLh7iYpmvw8VzRSA0APA2k77hwkuJlveEwnXKujp0UV14XuXMiSVyvL5D3HVv77xY5yWPbSZElD1OnSgiYxpPB3Cj0FT+5+JxVvYvIsdZynGUcJimn+RGzeEIapNSm5rK4IQsT8jBlEudcbK8pdc22bVjXNR2wbuqBIRe5bkmttevTaXjn4IDWGJmHDjCO45hlXXNblJRFJdmlbo5smoZVXbOtalo3j6qqIU2lV1m3hqZpCUOLiQKORzmvlmuMNmhjuDebsdqWVFUzFHp83x/eL2xH57JaG06yA2bxlMAPWdQLJ/H0ifyAeb1w/eMhtakZRTl3RidYaznND8kCyTidHE5YNktC3+fHz5/wg5PvMgolS9NnlzPadsKKKF8ikEbhSJj5thhYajmPPYOonBHaN+XHr89BkcZt2g2fzr9gEo3I84yj5IjAV850KeftySMHOp1E1pk09c+J/e3bpHZvAsWmM4NLaS+XFmfIHVDsj7lnFXe9jPvz+vUF8/5n7wCzsG/a9YT5e88h5Umhp5e+Grdk6PsaB8Y+EMa90IbGdCxKw0kecn/mM3H9fKazzoDsb78NYLKT2IM88umAwIODNHDOpQble3xysWZba7TpSJ0BzDSPGCchZ5OQWarIQmESL9eaNBJjnFkacLFq2TaGujWUzpSnbAy6E+Kj7SzbWtM6A5Wt7jiaJNJj2Bpqx3b1LOO2bNlspKiSpi5nuRJ31r4n0RhLVbWkqYyZphHwKNcNpuOY+bJyMtOOs4OMzaahrvXA7vu+R5qGwzLLWmh1R9F0TJKAg0z6QW9L4zq0rMsdlrVSoDy0saSRz/EoorMhx3koofYevHecsCiFcf7s+ZIPzzLGsWRYggB5yy6qRXkiGc5CcV7tDXSkWICLOxGE0QHfLFG8vvX9q9tW89lVJbmNieIwVa6tRTONDwfZadCvxW3f/vD/Z2ZxYBSNk1Nql2Po+VBvdqYf5XYHuEBeW5d7fYo7aSmeJ4tls/dwHfIY3UL99gp78QLv7feELez3oRSobhdbYe2OlSqLncFJFAtY9JX8rRT2+lKy/O4/gLO7O7DaA0Fr5bN66WkvT+hvKvtMUP8apQSY9L/rjBxbsYHnX9N99JHEYShfnEnHI2Ga3vnO61EJusU+E3bQzm8F8DYNaI1+dUtwMCI8mdI8v6FZFISjhK7R+FrD0RHd46eocYZtjLjBumP3A0WnDXq+xWxr2sYQJ0owj+lA+ZhtLTdjY2ndhMzSAG0sAU6lq3yatsOuKiaThGSaEhaOJS1qkjxiojsur0pq3THJwyGgWCmP7CiTSJAsE9Cm1M48ab6R63b+loyhtnGRGSGcnOGNxgLqetB/fSFGSJ5P9DsfYH/yS+zTr/CWt/D2+3I9us4VELLXx1Z//YyB1a30I95eSh9smknvYv+auoCvP5OfTw7EHXUyg9GB7OvmAr7+XIx5jBGGcruWfR6eiNw1zgSw9pmjxkgvbz9P+r7Hfvy9Of/c4rHvT9zPrVq3a5nAfkhlSgIvwDiDjEpXAwhUfoB2DGDvwNgvlPcZD90ZFLIA2LYFL7dXPJzccwtrf+iR0l1H59mBefA9H230kJuIjxxL1xEG4cAYXdVzNs2W0/yIPExl2Hdm6OsqWi2h7cjCtaNzmWHhEEsg56KPIbCD/M1aYR/7BUDTtWybkufrOZUWMNtLQ0OlOE6nhGoXswGwbgoxttENcRAN7q+3VSUGHHnOk+WS1baUwHt3wz3LJ3y1kF6pvr9RWEpFCDRas2pbNlVN22riJHa3FwF1VSOmNTIs5e/YMRm9ibT0YFiKbUkeR8RxSO+gt24k7DvLEhbzNXXTkmXJ3vxTjEYpkzjm/aO3uT++PzB4bdeyacVt825+d1jgK09iBE6SE8bhmDQQ+eam3fCqeEXuHBf/o/u/xb968jGP14+ZRVPemb4rvYdOYtgbqchYM8O/O79j1S45iA+5qa+ZF3PSIOU4ORmkdLWp+Gr1JVmYMQmnbPSacThhEk7prOG6uuLL1VeMozG6a5lEE7Z6w1F8zCw+4Dg5IVHJkO3oO+auB4o7SWXH63zC61vP7vc9itJXJtepMbu8xNrUQwFGzA20gEVnRvUmQ9qDPG9v7ssCV4xwVs2Ky+KGR5O3CDyFGRhXsNZ/bR4r1/dYO7Mq3/MHsNEzm8rzuSpuWTVbHk7ucJgcfCsofJNh2geK3zDucUxyb5LS30eMNVSm4rK45uPrx0OG6f08ZxIn5GHGo+ldB1Z7dshwsb0WibtZEfkhjRGw/Worhjanec7z9ZplUZHFEW3nFDDZjK8Wl4zjeGD09/vQjLXMiy3bRjJKezm31J49trVEy8hzUNYlSRINZlKiBBDVTLGtmMQxeRpTKSf3bwRYGm2Y366oG81olO7yTZXPbJSRBIEDwvnQq6o7cY9tTMNJekykxJVUZL2KaTQlDdLXTG7m9YLEyTl/985D/uLl17zYvGISbbk3ukOikgGQxX48XNNdv3qAmOdsGYdjls2KdbMhVjHTeDoU59qu5cX2JbGKGYU527YgDzNGrhi0bJY831wwjnKMNWRBSqkLpvGUaTzlIDkcTHLE0Mn7VqC4k4l+0w21l6G2XTdIT3sTm7azKE8cTZvOvNb32APJ/T7FwSRmn7158/MQwLesW642mncPE9f7+Lq8vMPb1Y5dcVK7Y+2B5c6FVY7zcq1ZVpp3jhKO0nDX4/ZrkME+0/rm3amff8oZ2fTHNhizaMPLVcMnF1vqVkDj2SwliwNGsTBN03i3/NfWcrGWNV1dislN1UrA++2mZpyGHIwirlcVm6IhSQK0kfvdySji6bwkT0JZN/oeXefULS73sag1Za3RuiNxstN+/tW1GYiGXkqapuFAPIBTwrUd221DGotfRu+KWrWGLAvRuuP2tkC3mnyUDEs5pTxGo4go8IkDfwDaphOQVmpxtj7KAkLlYTphiz0PprErjAdS2Otlq4lzPX33fMxnL1e8WDWMY8W9aUSs+r57BtkngO/Wev1Y3LZWTJIcixspn0mymxem67jYtMTKI418yqYjjfyBRV/Vhot1yziWAkDv0DuJAyaJyJADb2fYxH8AUITfxCzaDnQtC3ijpczj+bLIN2ZvUR7uzF98T3rGtOvpM2bH2PWrH+36HbXZ9YspJaDz+dfiZho7mZ/f7YxA+ger6d0j9xxVexAbRgLWtAbPgdX1Em5vhbE7PN4BxX3H1oH1dM6n/e/2SxP95O0NekC+UxDAeIr98lfw8UfY9YbO0f3BNBWQaC0kiRjXZLnkRyapRHB8/kvs51/gfe9DePZM8h1HI+zVlbiIZhndy1f4SUR0mJM+OoF33sHLR9inT1CHU9BashSjSPo951tMUdNV7QAUlZsA/eLTaC2sn7WEoc8ol0qMHwbCWgJ+LCZC9bZGtx36VqI+ouMxXhLixyHBQcc4VFxelXiAcTbTnZH92rbDDwX022df452cCwgzBrtcwO0NXhRLn2cYiWy0Kl2gfSbXutgIENQtFFvp7zy/S/KPj8F2tH/6bwjDCN77noxVw57U2d8VD9YLYciDUACf7z5Dt9h/9S9gtcL70e9JrmdZQprC48dw5w60Ld7Dd7Dza8ns/L2/J+N4tRAzpn4sHpzIZ/dMfBfI39nkdddTayXfMYzlz7ds2raDkU1vPiAB4c6Awsnh+gWh73mUzj0UkDBmJ1UTRtCBFdvRaHk4+OyqptflLTfVwh1eN/y+l5Va2+0tJK17KPbGMx0Biq0u8PH3XFsb5tVqkL71n6/3DD86duxMpcWo5U0pXJ8zCaDcAqg/L7GK2LYll5vFkGmmu45xLCxiHzqehymxiujoBgbmplzw9fKWh9NDbsoNU89jHOU0ZslZnpMFMS83S5IgIEkiTvOcR9MZR9mM23LJKIokIiQIXK5kwG1VsW0aGmPY1o0Df8rJb0Qq03XS39R1HSpQpFkyzM8eOAbOTr2qGnSrWWwKgkAxG2X4HoyjWBT3gWIxX8v16POVgCgOCX2f4ywjVhFfrR5zlkrfoO4Mt9Wcm/KWSEWcpKccJoc0phlYYjGh8Cl1SR7mtF3rrq/HW6M7/O8+OKGzHf/95/+a/+q7Id+dvT8wb57nEfvS19p2LYEXsGwW1J0Aq+vqCuUp0iClsx3/8vmfclsu+YPzH/Fs+5yylX6qj64/5+H0Do3RvH/wHlflFZfFDf/g7h9isczrOYt6MUg5Z9GBSLG7msY0zqWzcZLXvfBjBJTFKh7mxZvbvpmN7pU2CLjpgaTy1WBOI6y/oumaYXHe91X5eJKl6Ink0KePwNlJVoVdu2ZRr4lUIIUaxzb2W4d1C49v9kKCGM/UphYw6ubgti24raT/bxJNvgEUgaGnUXbof/vP+/Oy93n9PMrDnKfrF3x68xWrpka7Ptqpm4MgMvHjbDbIdn1PvuOzzTN+dfuc75885Pn6ksN0yjjKuS4XHLtYmRebBUkQMM0SHk1nvHtwl1GU8WJ9yVGaoZ0hVeTkl7dlybYVh+RN3QyZbP257roOre3Q7xsEisSxgUGght6nKFBYoKwajDYsyoowUBzmAgCTIKBDgOn8diX7dnOw36/uuiHK5uX2FUfJAUmQSGGg3jKvVoR+yEE8IwgD15veoDxfMg89n8rU4kgdSiSS7/mc58f8k7endFj+9MnP+c8eKR6M7w+MtrAKyhUwBFBt2g1tp11/4YLAl+eCtpofv/wJ62bLD0/e57K4odI1cRDxeHnBnfyQtjM8mJwzr1bcVkt+5/RDWfjqLZt2Z1w2jsaIS3fromUCtGlJg/QbQLEvdvbs4/7WWWg6MbMxdudmqrtdL2MfQN/Ptb5A8BrYGooH8t99JGHf9+Uhi/vaGF5tGhalAIJgb7Hf729QurwBNftP66XPxu27s5Zta7jatrKId2Cpf7f3xvt74LcPOH99OUs+L/A9slDx9bzml68KtpUeGNFREpLFoqpJQp+TUUgW+rSuz075Hl9eV3xxVfDB2Yjny5rjUcg0UVxuLLM8IosUV+uaOFSM84g7BxkPDxPGseLpsmGaRi6/UBEFsg5Zu/iMxrmjtq0ZwN/+/LOOPQ4CYRs9T557Q3+3M/2pqhatLduyJQh8JqOYOFQSBZIKQTGflzLW9f78E0f/XhJ7tW2ZpcEQbr+uDYtSZKPTNEB5fV+sOKX2eZOVFsmotZbCOc6ejkJm7xzQWfjpkyXh2zPemsa7++MeOOsLCUUrbqvK91hUhtCZJ7Wd5S+ebigbw/tnGTdbTaUl2/HlsuJoFGM6y/k4YllpFqXm++eijivazmU8AmjGrt9VCi3yPUxnidTrrqrWFWKU5/1GEPk3g8W22eUr9n0TpnWgcQ+4BY4pDCNhFOtqx/rF7nd1uWMAdet+5+R5QbADfGf38KaHIjlMcwENe5Kz4VhsJ/+u611Gnec51sqDyBmTvHqBff5Mfj2divRxciDM3r7b6T6zs88g7rOl+6/1nCw1Dgcw7IUhtm0xZYvZVMR3ZvD++/D5504aq7HXV3IOjMG7/wiKDfrPfyZA79kzid8IQ+x2i12t6coGNdP4o4z62TPC06kAxekB9uZK4iMODtC/ekxwfghpivnqCe3Nmq7S+KkAuv42bF0FByBKQrpWU1VmqNwk44TgMKerW2xr8JMQaySINU0co5GE2EajkpDq6xusNnhRwNFRwvV1hekEKEau+Ts4zPGUB+u1FAG2awFo46lEkOQjl1fZiAlM747rKwf8XPzF/EbGTFPLa87uSeal1oT/7f9+F4ui4t247MeK0Tv33s1aPuvBOxAmcPlcDJo2G+cwG4gc+OG7rhDgJMHrNfav/gJ9u0ZlEd6LJ9gvPsdcz1G//X2873y4J201sLh24N1lRfZS5358eZ5IZJtyx1bvbf2DVgQLcs16QOXjYbDDYtPS4XsBhS7o3VFTlRAFEudQaHExLXVBY1pCPxgiCwLX49h0LZNoROaYv8APByDYy2GtlYWq4fX8x/0Hc2+aIyY7JVeFAOlxlLGsN0Qq3PViWamgKd8fFtTAYD3feQLqaidVlEqycfIjD98LaJGsOOX5GBdDsW3F6fD+5ICXmyWB71Mbg+ftnFNHkTBkn95cumiLLa0xbN1cL7Vm0zTMko5pkvCLy0vSMOT9o1PyUHqmbsqCozTjq8WcSRwziWIuthvmZUmlNZFSROGeI13XDUAxCBSttZi2IwgDjDYkacQ0SSjadlhgGmuJ42iQtSWByHfyKOblej24xY0nGYv5ms7d10L3ucdZhgcOsEt/21l6yjSasGk3jMKRM2xpSVTqjGkkW013Gm01WZAxrxcD++h7ijvpHRb1grbT/J9++78RCdwe09QbtvSmMMYT1qloC+ZmzoPxQxKV8Kq8IFYx1+WC8/wY5SvG4Zj3pu8S+iHjaMTXq+fMqxX/87N/z1WxZhLHPN8+56+vPuXF5pa/f+/7fO/ww8EkRHeaRT13UmdNGmQoL6CzxvUayvIwUhGVqb5horObgwIUxdxm17u7v3W2A4+BNenjBmThGrwmFbWuh7MPtB9iQ/xA3mNdQHmUkzqjIdPtFYeQB7z1do6w+3LXXkEgknH5TjfVLc/Xl3h4HCQTrqsbxk6SODzS3pSauiKORy8HFoD75ibzLsSqPq8voOlEArptGs5HI94/us+XixdEbs7PqxW1FpfPu6NTSl3xFy+/YBRFPFu9otAtgb+lbCuWVSGS7qRjHEU8Xa04yTLeO7jHLBlzUy5ZNwUHyYRf3V5wno/IwoSvFpfcuDmYhQFxsFvqiBnb6yx+U7f4vrCHWRpxkCSDlLx3MO4LQmKiJe6JWRjyeLEQA45AMZ2NWMw3rwFQgMNU4oHWTeFMvCqSQFjWbVuQBZPBNKife6EfDmxtZw2Jilm1a8lE9LXb7yFbvUV3mv/6/T8ajGkCT2E9OxQbAEyn6Vxxr9QlutOcZ2eEfshtPSfyIzZt6aT5PlmYcG90hu8pJtGIF5srVs2Gn17+aog+uSqu+XzxlOui4LdPH/HO9MEg++5sx7pdu3nXEaoI5SmnMtg5PPqeFFe+zZGxdzw1vfm4lfnXM33gOkZc36wUU2WxL/vGzQWRTHaWAXj63k6e1zOUAMd5xCg2ZKHk4vU/H0Cd3estcxLUXm7YywOBwdDmctvwdNG43vWAV5uGaRowDvsC0/695NdBwm9uvSoh9L3B2VL5kp9YtYaqlfiK75xmfHVTEiqRQM4LTdXKObg7idg0HT9/tiKNAp4tpK9xUUoY/KZqabSAkDwOeLzccDiKeXiYcJgF3Gw1RW04yAIeXxcSlxH6PFmXLIuGVktOY7iXP9gbFXmey+Y2lqrS+L6AvDQNmWQhtQu4l+MWlrEHomHg0+qOJFS8vC0GsDmbpdzebl8DigB5IvfZdW0kgzAQ4JeFPutAgLa2ThLsy3jZN7yR+4CckygQYAfiJls2wsD+4w+PiZR7srhrvz+ijSOcdCdgszWW87HIYRfGECthSadOIpuFPufjEN8TU6XLTcu21vyqaNlU0ut5XUQ8va1Yly3vnY14cBA5cCv373VjCJzKKFB7bq1vjKPGWKLf0Jnxm5nFXhra2R1DWLucOuP6/fobcVPJQh52jFtT78ChtfKzPk5itRDJZQ80B5bSAdE4FeAZy+JVJIqB9IDtP7AT97p+60Heeol9+kQAZRxjb27wTk5cvt6bMlPXb/mm8yUMUtZh6xnV3hgllt5K+/Iltm7oykY47iQZwB9a4z18iG1b+VkQYH/+U5rPnwqTUDToF08kvL5u8QJFc7kiOp+ir1eYssGLAlQaCkDMcri6grMzePFCMhWjCJZLib8oGtQ4EVZwXdE2ZiBKo1gRxgFeqAjyiBHQlS1xaOlaTXO5Ihgn+FFA1/c95jEqT7BdR3g4or3dgO8RTFM6bfCUz/HRiK57xXbb4vkwuTvBtgbl9kVVQVFgswyvrqCu8PrrX2ygORDgv7gVMJ9P5NzaeOdw2o+lfOx6RM92WYhtvctGzCe761NuZJ+9zPXAmeqEiQDRNBOTpP/yv3Usegv335FjCSMpWmw3cvLKkuDkBDYb7JdfoF/eENw5wrv/Npzc25s7Vj4PHPh1UR3WFU76OXJzIQWRb3lQ7ssve2OMwA/YtFv6QG9ZVAQ0nbBBfURB6CkCF9xtrCZwLqaRHxGrWGRIbSEyzm4XWRD4Ib5VdNZIlmKzHgDqvozn9fw592Cmd/CSh3alay421yInVQGbpmQUpcO+etOd3SmzGHah5MZ2BK4KHfiu/9FIX6VSitYt4qVHUrOo19TGUGk9MImlrgmdNf5RKovjyjGq1+WSp6uVVFc9j8fLBYkKhve/2m45yTIJ+HY/O8lzSl2TBQmvtksOk5RlXTmJWci2lf6nomnJY8ki3ZS1M6SRaxOEAUGgCAIBknmW0GqDDSxaG242W9I4IgnkWADCQJHu9VwWzvAiDgL8UK7J5PiArrOUZY3nwd2jGa0xTJ0T6qqRHtdRmFOayvWUCbDftFsOYilOzOs5h/EhIydBtdZS6GIAJiJLG6E8xXFyPGQhNl1DZSp01zIKx7IwxLBu16ya5SALPYgPCP2QWMW0XeuYvYT/7v3/ZjCPeTh6hLFmeN2iXgKwabbcPztjUa/56OYzvl5e8XB6wjuTtzlNz/uRJGPdyWA9PCfHc26Ers809EOuqytKXeLh8fb4/W/Mwb5Q0+3NQR+Pumsck2mIvGiQapvODMyqyO38QboaeAKeAy/AV8pJkYqhcBJ4Ij1ULucQpLd42xXSk+wW+r4nPYv9faGfH/oNFZ+Hz1ZvebK6GOTV1+WCk+zgNSa1B4q7xe43gXMf7/Emy+gjhapIRRS65GJ7Te3MoIy1pGHItikHoHg/PxbZua7w8fj45gs+u72Svq625cV6TR5Fkrfo+1wVBWd5zlVRDD/LwpBCV2Qm4XJ7w2l+yMXmhnEUEQcRq3rDoqoomoZxHGOxQz/iwLaFgbib+j5ZGkAaU7TOpM0YrrZbxnFMrNRgiJVHEZljEY/SlJtSlDSzRGJ2lOdzcH7CF8Mc9Dg9nNAaAbqRUs79tCIPM3IjY72X3Ve6xoSastNs2i3jaESiUtfPHQ4Op6bTjpFPUJ7PNJqgO7lft87B2nTGycd98DoqXbFptyJz7QyTaEzgBc6kqCNWEZEf8U8f/ZG7rxrOs7OBOU+ChE1bDMqVs+xAIoOWz3m5XnNnPObe6IxZfDAwYn3RCWRBGu6Z5ei9ObKslwIWv6Vrr+857P+3L+3s5Xz9or7v2e9f43tSzOhZyF5OqvaetaV2i2lXppQCJOKhQC8NF8ftwN+5l755rOpbnt8ARat5fFtTG0usPF5tWs5G4TeiFPrvBN/euynHItv+Ur8HrbHy2TYiS2zajkZLQTIJFdtmJ82+O4loTR+tAL+4KHl2I9m8NJqrVUUaKTGn8TxWZcPhKGa5bWi0AKUo8Kl0R+2MXs4mIS+WjWMVvcEltG4MaSz3qaJoh4xE3/eIIkUYKpTyiUOPLAmoW0MQSKbifF2TJaHEeGg5/jRSJM5UaJqFLIsWz4NRGqJNh+97PLg7ds9AMQE8PsrQpiOPnQdH21EDeezT6A5t5dx1VlxqdSTh9Nu6I48tifJRvo9vxaQGGOKuskjWDaNYCrqpUxBoK6kA8R5oq03HtumIA5G5ThPpLQx9jw6IAxlf//Dd2cBKH+fhIBtNI5/afcdWdxyMIra15sWiZlk0TLOI83E4RKUMYHxvnPX5jXbvu/jAqpJ+2m8r1uxvv8ENda+S2DM0zsHvtYW056SeQSiLe6VeZxOtFfOZ/f4x38VhhJH893Yl7y23wjipUN6f5vLzaq8v0rSwLXcATrdu5jjpaJxAVWJfPBVgBeKmefce3Hu46y/8tn62Hgj27GFv7rPP/AThzuzEud71styubrGmI5gJIO2++Ar/cIb3wW/B4QneagGzA+x6hf7oM7ptTXA4onm5wDrpqh8HtLdbwsMcLwzxM8fohAleluKdnWMvX8kxaY3VGs/1g+pXc5rLFV6g0IuCpumo6t2CHkAbC4VG+R5Z1uvHLSoUcx+VhpTXG8LAx08j/CgQB1bAUz4cHxOOx+D7qOmWbluiV0L/J7EiUL6crs6S/aPfhyzD/OXPaJ5+SfLWIV6aurzDcBdN0fcxRhGc3tmx1J63y00cjWUMeL4wimXhxkoKxVqYxcgxj8++EkfVMIFPf4FtarzxRNxw0xTv0Xfktb7aZSlaK3LRphLGLxtJkeTgDO8P/kiA5GouzHRdYv/y3xFkGd73f1sAqLVQrt0YiSAdiby0qVwBpBPZ6fOvpf+x3GI//VikyXfe+sb06636geFhWbSFgCrnchr50bBI7VmdJEjQnXlNCrdtN4OZxU6y6g+V562LIuhD75WfUOpy6C+pTDVUvHvjhF4S25vNDBJRT1HqittyOQAz5ftM4hHTWFzDWtPS9HJFJ1ntDXF6yZ1vXd6i1cPDvrO9WUi/eBeJ3s4URAwQxrEshi82G8ZRxEk+ZuQY01hFdNbwyc0rKq0ZZxnP12tabehiSMNwCP4OfZ9QKWzbcpCmJEoxi8dsWhfY7Qe0pnA3flncXm+2KOWzLiu0NrRNO1Q65dbp5rnvEcXRrv/L7x3cFKt1MYDKMFDM4nhofB9FEWkQSBCwA7rbtiXwfaI4FLmrM0P5L777dxiFOf/66U/5Yv6YR7PZELcQeGowRgp8iUaJVcx5dk7oR9SmonfKDJxBRqLkHK7bFZ3pyIMRkYrZ6g2RL3LOddfw9foxx6n0DX4y/4TGNIzCnIviknE04r3pu1KY8HwO46MhkqUxDW3XEPoheTCisx3HySn/8Z3/mLqrWTcrJtGU2lT8u4sfkwUJv3/2Iw6TI0DCyvvrkgU5kR+53j0Bc+t2zfPtc2bxlEIX/PTqF7w1usPd/M435h8gGYt2Nwd7R+EO6SUO/VBAqedRtpL3GPoSVTAYjCAy68ZUwyKzlwT28nBrLYURp8rGNA4IBEOMQV8Qiv146EPUXTvMuf5e0c+dwL335eaSbVO4MdZxlp1ymh2/BvrerDRbutdkqF0vgfe84T37gFJKO7ue4kprjHMltdby1fKSwzTnvdkDZtGErS6Y2BHbtuCj6+cUbcthmvJivR56zBKlmJclB2lKpBSZM8YZRRF5GHKWHXFV3OL7is7JFJUvY/liu+HSzcFVVdM0LW3TDn3C/RysKwF0SRoP50EpkX0nQcCtk3xHgSJSIUdp6hhzn5NsyiSSiJ9ZUrJumsFteZiDnoCLf/ToffIw4ycXn/OzyxfcG09Ig6UDIE6ajj+oKyIVcZgcoLxguMbK8wk8iRXqAVihyyEDN/TFxKgfK9uu4FV5yTSaEPkRj1dPaLqWPMy4LuekQcxbo7sEjr0ch+LsLNJO42SqokKwWKbRhB8ef4juzKBGqE3NL64/ITtKef/wbcbR2B1XMYxBickJ0c7wrLOWSldcllfDPn41f8xZdshxuufj4LaeVQSGHsReYtq73PY9aIUrJgT+zmCmL0b2bQn7+xX2SOR3Zm9/jelInDFNL1MVoGiHjEHr2MTdnGEAopYepHY8XTZsagFmsVKcjyVe401w+W1A8c2exTdlq/ubR+8MLsyi6SzjVAqBT25LZlnEu0cps1SxriXXb10bPrvYSN5hEnC7qd0cgThUrOuWSSbyzj4/UfkeSaQ4G4W82kgRpTV2AIGe53G7qVmsa5Ty2JYtbWuoazMo2rrOulxAjedBmu56GAMHsMLQZ7mu5PkX+qjAY+IcZpXncTSKyJOQwBfWsO+JBIgihVKuqN1ZfvTokDTy+fTlhq8u1xyN48Gpf7+nsC8GRL7HzBnFCIPYOQWFgLZ+vFVapKpp6ONbMa0JlLxOY7ktWkaxsNPPFg216cgjxaLUhMrj3lQKSD6Qh7v2CNN1rh/XDmxwHgZ8cCJAtmiFFW2M5eNXJWmkePsoGVxdKy2mPcrziNROzrwPXK+3mjwS0P/VTc3xKOAo+zXu/277m013+qp/b8TRS1I7FxnRVDC/FlmhUsL2JJkslHsw1TZi1gK7bEZwjqbOyCSMdm6mq4U7Mk/+2/ccHZbszG56B1RwmY9mB2zDaPenHwjGiLzwzlt7pjb+DgB73g447jOI/WQNo51L6n7vZZ8LqbXLc7wDnSW+e4B66xx9tZSev7t3pR8vzcQttSzgq6/Qiy1+HmM2FXQWL1KoLEY9fItgnNBcrtj81VeYdYUXKPw0gnv3sDfXcH0t/XTX1/QaDf30guLLS5qmo2slzqKs5LyIq1tH0+wWCKazlKWmqjRt21EVLU0prGb+UG7cPYC1ncVz1bYBTJ+e4v29f4D/8D7Rdx8Svn2X/GRE7Jp0PeXD1RXe0Snqw+/iKZ/tL1+I0ZDvY13voX11gX38FdxeCwPYuvzNJHMAbLMzV+qsFBSMEUZuvZRxEcUy7vqiw8m5AMVihf30E5p/+5fYrx/Dcok3nsp769KNSbvrxbWdMNFGu+Nw41iF0nN4cneQJnvvvo/34Q9hcoD9038Bn/xU5sLNpYuS6cefc0E1LfbP/jX2Fz+TIsT1K7x3v4u9vXmdGe+HH7vAYdGWt06CI+yC5N6JrDJ0AdhZmA3mCZJv1rhoDAlhL3SJ6fTAegSeGJHkgRiTbNoNoR+SqoRSV24qeoPEsGdKRJohQFH5vqtiRUROahSpEN/v+wo7siDhIJkM75OexMDFYHSDdX8P+voFbK2bASD2x9L/ve+SqnyfaTyms5bTPOcky7gtS2KlmCYZ4ygj8AORmnWaV9sl66ZmHEWsXRab50ESBNwdjcldPMZfPX/JdSFgMA9D3pocUOqam3IjERrVVgK/PY9X2y1P5wux3jcdTd3S1O1wPbUWV8V+/nWdpW1amlp6odpG0zZaFqMH4+E8KM8buJzOfXeLgMYPjs44H4343sk5f+f8IeezyWDgoTyPF+tLTtITfu/OBwS+z89evWJRrfE9n0KX+J7i5fYVv5p/xVV5zbyeD5ltycAqbgejGGs7alPRWWFCNk4WF/ribrttBTSepmfEfkyht/zVq4/5f33xZ3y5fMJtuWQSTSSDs6uHseThD5LruqudmUwzPOCUpxiHE07Ts4HFe//gO/zo9AdMogn/4smf8PH8I7Z6w3V1Jf2wAzDTWNthrObfv/oxf/7qp+hOc1G84ntHH3BZXr+WVfrmHJRbvRjPGLuTfPbyuT6SwPM8EpUSq1gKH7gqbmcGoxvd5xPioTwBioG/+1Pqkk27cb+XXtF+jPeyxN4Ip1cDiIHIbs4IO6kcA7mbg0fpASfp0WtA703TGngdCPY5kr6n6KNC/L7I4MBj51ybPc/jzugEgDvjMfcnB1wVBZFSnOdHHMQzIhUxiSZUuuarxQsWVcUoiti6NUKsFHkU8Wh2wjiOuS4KfvLyJeumQfk+aRBwb3zKTbXgulyQBiJfNs7s5snqlq9u58McrMqaumqG79fPQc9jkMPVVUNTi/lNXTfUtRRe3jqYunMnhSrTdYRqj3HCcpTO+P073+ft2SkfHJ3xncMTjqcjwmg3B6/LBYfJlO+dPEB5Pp9eX7OqN65/SQoyr4obvlo8Z9WsXE+hgMTQZU5WuhoY6j6+pbMdjWnYtgXKl1zGfgxFfiTn2xfG99Pbr/lfnn7K18sXrOqt9GR3zZ75jB3GVb9f44yd+nmkHFg9TA4Ghcnbs/u8f/g2eZDzb1/8JV+tvqLSlVOkdMMY0a7g11nDz64/5uObLzHWcFsteHd2n3m1oun2Wn3emH89O7gPFj13bbatpjJG5Im+T+D5rgfL3TPtXtbicE/FZRN6Q8HN9zwqbSi0BGsoj8F1t3cC7/8t82y3/x449kVN5VjN3ijFWjgdhy6H0RvAZT/73uxRfHN7EyDuejT7z5exdnci4+5kknA6TZhvGiLlcz6OOMiESZ8lirLt+OqmZF22xKFP2cj3jEJFGgXcO0jJ44Dbdc3nL1aUjR5A5N1JzNVWc7NtSUOf261kKVoLL+clL657t+6Osmwpy34NKiZurVtT9tncVWWoKkPbdpSllmxE3+fsKN+9zl23Hqz3RkPHecjffTDmrYOUhyc5dw8zDmYJcdwrkjxutw2HacC7pzm+5/Hsasu2cg7t7ntfb1uezOshNqSXmfbAsDauZ9ZdnraT9XNrJK9Red4AFHvQOEkEKJZazvUvnq14Oq9ZV4Y8kszGxux0Gr2rrwB++Xnvktp/50ipgT30PHh0EPPuUcIo8vnzp2sez2saY1lV5rViRi+TtsBHr0o+uypojeRFPjyMWVW77/zrtr+ZWQRZ6Gq3cNbtjin0PAF4uhWJ3ngqjE7P0rXN6wYxff9YGO16xny16280Rhb9aS5garvZmZO0tTO18XZRBMbA7dUutqNfmKcu+LzYiNxTKbxHj8ShEpxRTff691BqByLfnKy+k6Z2dmfGs/+a1cKB1Rbv/B7q7bkYt1xdY7sOU9So1Qr7yS/wzu5gl3P4/HOaqxXBNMNPQ5GAvn0OdU17vcY7OUHN53StoatawvunNE9eEYwTuLlxmZTRcCxda+jWFfWTG8pStN+bbYtuO4LQJ44UZaUJQp9ASbOuNq5KlEiGTV/1UYHP9tWa9EATHOboZYleV3ihQt07ks/dbqX/cDSCiWtqPznBi2LS42PiX37KxZ9/TXm9wQtfoq7+J8Lf/x2Sv/sD9C+/oPzVc9KmwfvR38Eu53jHJ9gnX2M//5WwzaMR3mQqDqmzIzn/m7X0LBaP4Tvf20lKy0IkqqOpAEWtIXWxKs++kmPLMqK3E7zjY4lTuf/OzuE3c/k4tpOxrLWM5c7A1QthEXv5c7/1+Z7Hp3L9ry7g5obiL/97sv/qf7Uba32/q+eLI+rlc2G4Hz6Cg2PZt+3wgkD+/W3Tz5pB2mbsbmHWy0+1FRvrSTSRRay7jr0TooePtq30RnWQRxmLZkljBBC0uqRzC1hhczJKU7FpNwNL0ffM+K7fpI+8EObRG3oO+z6ppmuodUOlG3xfcZoeMQpT91ATgNlLSEEWp0NGpJMu9lscRJiuG4LbA1/RGesWTjuDnc7CJM65O5LreVlsXRVbHE67zjCJR9Sm4eVmybwsmcUJkVKsm4Z3ZiL/WNQ1k3jEtm1oO+kFvDseC9OoFJumHBrC+wZyMTBoebFaU1cNvvKpytpls/kEYUBTSzabUrLgN6ZzkvBokKjKbTJgvS7QWUyWxpRVw7YSIHOSZYRK0RpDbQxZEPPO7D435YLT7IhYxdwbn/EXF7/kx1894XKz5dPgklfb/4k/evC7/KNH3+enr77go6uXVLrm79/7Xeb1grPshM8Xj/no5lNiFTGJRxwlB9zN7zKNZigvYN2uWNQLnunnfHf6HSIVo7uWUpeUumAcihupsYbUl4LF081TQK7L+0cx5/kJo3DEw/HDoR83j0Sx0C8oTacHRvGyfMU4mtCaZmBAhK1riPyYk+SUjV5zXV3zYn3J/+fxx/wff/ufcpQcCXPqB8OYNNZwWb1Cd5r3D95hGs343sEYi0izx3v9e29u2mq0K770xZqeaeuZ9tJJC5vO5Wh6PvqNHr8+3Fz5AaUuUdZ3/SK7GAjf80mDdJCV99/bdGZYfPdFHkNHobff6KHcxeKIK3CoQh5Mzjlw2Yv98e87tP66rEnpWdwByX2D/x5obnXhpE2ak+yQt2en6E5zVawwXce2aVjVWyr9NWf5EYtqzVfLl1xut0zjmDQMqbTm7YMDKq25KUtOsgMW1ZrWycrvjyc8Xi6YxDE35XKQTvYRCW3Xsaprni5XVGWNr3zKoh2Mpd6cg3L8EnERJxFtq4d7p6c8rlcbJnnKLE1Y1TXLuibwfaZJQuQrtm3BpqkZR6UUV/A4zY+I/JCjdMYvrr7mp18/43ZT8IWac7H5c/7evff5+2+9y8fXz/nk5pqibfm9Ox+wqjccpzOerC74YvGUwA+G6JDj5IhxNB6KO1KYuOLB+C0iP6J1BcHa1HLv1iXGdiS+wiPgoniF53lkYcI7BxEn2SFZmHCWnmIc850EyVCU1K4okgUplo5FvSALcmEG9wzH2k4T+gGzaMqm3TKv59yWG/7i5b/jv/7g7zKNJntjXv501nBT3dJ1HQ8m54zDEflEevzVVJGH2TfGnzB4UgjQLkKjX/TK+BQgqTtDEkgfacPOyObN9a/nGKJKG0DmUx/F0T9PEpdfqE0fdr+Tw0pPsFvWWo+2M8Ox9PeE/rNr07GsNFHg8+5R8huZm7/N9m0S1W0rwMB0cDoKuXeQ0naW+abBdNb1IGqK1nA2ClmUhifzittNTZ6ExKGPNpa3jnIabVgWLafjkGWlabSwlMeThFeLkjyG60Lk3JFjX3uX9G1luFxIjJpSHnXdorXkI0aRcj/3d6yfcxt+cw3q+z63i5LJJGaUhZS1pmoMRaA5maZESnoHt7VmE6uBUTvKQkLlcZAd8sXllk++mrPa1ATK519vG35wf8L370/58nLL05stVWv43t0xm9pwkAa8WDY8vq0Gh9lRpDgeBYwjSRCodce6NmzrjrdmEXkkzGNrBPQlTp5rrCV2JpqX2xYfSELFnYOU41FIpDzORiEdYj4TB68X76xlMNJZNgIstTPb6TfTSXFgHAtDfFuI9PdPL9b8ww9OmKW9W/3e/Rq4LVpMZ7kzjZkkcu46LMqPB8OfX7f9BhlqswOKPbjqjWj63sI+AqPcymI7CGVh3b++ZyN9bwe2UscY9Y6jSu0Yxyhz0ReO8Sl3DltyFt1DvdjsQF8YYl88xTu768DoEvvqBcznAmjy0U4aC6+7mfYAsf9ufe9if5J7prFnOPfPvG6habAf/TV2ucK7cw63t+ibtbCFvodtNOajz4nOD9Cffi4sYRSgXMOtNR3B7/82dB3m5x/Le7QGYyQ38WRC/flzukbTTVK6JxcE796XGIqtk4AuCrq6ZbORaknTduJ+qsQFqqrFwMZoS+3ChpUDjWUpEol8ElMXAjCV8qgWJdaW5Gey+PbjUJhMraX38P33xZQmivHe/S5sN9jVAu/8Hn7TcPf0mKt//lfgeTQvF4SA99ZDwtMzgq++5NX/+BOO3HFHv/W29F4aI1LRVxfYJ0/o/uzPUb/9A+xqJYH3J+e7az+eimlMnAq72LOQq7kAR8B++hHe2+/h/dF/JmBzPJWx/Oq5/Ht2JPEWsOvN7RnKxkW/fPEx9tlTyHPJdzw+k7xGgC8/Ac/HfvUFzaslqxcr0q8fS45kFO/Y6nQEiyvsL34qY/LB2/IZSSCM5eRIwOub06973a6/r/pq6+RvfkSrNZaOUkt1OfKjAfwFqMFJ1RgXU2H1IDftc+N6Kap2srqeBQGGf0uVWQClh7g29gsMz/N4tb0RB8NwhLGGZbNhVW/IwoRIBXTI/hsj36mXwloscRAO7FH/u15iKlOtw0fRWonT2JfPtdbwcnPDsqo4cqHbi6qiaNtBCvRkueQgTXm6XlG2rbiiRlLh3bYt7x0eozyfLxc3Mn/ctWiMYZYmPF2thsiOp6sVj2YzsfbvJE+xz3EstsIC6VajtbCn1sp/B4HCmA7tekmU8vF9n6Zu6DpLlic0tcjlgiCQzDZtGE9yrBU5Sp9RV2jN+4en3Bmd8NboHm+N7onbZX3L3fwuHx6V3Bsf8//8xV/hA09WS6y1PBrf525+xqfzL/l//Pwn3FbiFvm7Z4+4P76DtpppNOH55oJ///JnbJof8/fv/ZBFvWIWTzjPzpxcsiALcseiJWzaNa0VueWiXpAHIzw8Prr9Je9N3+E/f/DHg02/tpqL4oJxOOIwPiJWiZMziyFMrJIh9qHtWj5ffs5XyydM4pyj5Ijz7IxpNMNYwxfLzwm8gE/mn/N8veLlzYIvFl9zcudkr0fRkgc5i3rOT6/+mpebK96ePHJsqLDNs+hg6DN8c5NcRQGxr83BPYfh3vil0tUgQQUBkcKkC6ui2DnRxSr6hvxTHuzS29WDQbkP7I7NdhZUhI/n2KXeDt3nqrzmKD0URtJUXJbXzKuVBKWHuchd2TGQ+yxGL4uThfjOdRheZxrf3HpX449vvmRZFZyPDphXa662W7atsGO1MXx8/YLz0YhPb16wqmuSICB1BTjTdfyd83cA+OvLx/ju3mfcWD9KU351e0PbGRqT8PXylvcOTgZzmHXTsKgqKq0pi0ruZa0e3E+7ztLUOzaxcbJw35dg8J55zEfpMO985bMuKlbWcjwZuWumSIJI7svG8MHRQ4w1xCrm7dl9Sl2ybracZkd857Dh7mjGP//kl/iIHB7g7uiU4/SAr5bP+Re//CWLuqbRmg9PzjnLDzFdRx6lXBVzfnH1im3zCb9z9i6bZsskHnGYzCCAUldkQTo4+RZ6i3Yu2Zt2Qxak4MFn8695Z/YWf3jnR1SmIg1STKe5redkQcY4Gg/39L7oEPkRga+cJFzzdPOM5+tLslDUIQfxjHEkyodnWzEP/Hr5govNhuv5iqerl8xOpq/1KMYqZtWs+HT+JfNqxf3JHZQfELs+3TwcfauBUuskxvtAsWcZle+jvN04ro04VAae5xQkOzayl+F5btyHyv/G/AMcc+UN5jTCXgL0MRuuoOCJk+r+HuaV5iCRfuPGdFxsGuaFZpIEzBI1sGI9KO3//c059e3xBt+eQylA5aOLgnXZcjKOmReSW9izha3p+PJyw+E45qurgm2tCZxZTL99/56s8z652IgZkMswrFvDJA15er3FdJYs6dgsSh4cZeSxz7buBLSVLXXbsd2KUqRt7WvzrzewEWZRDKZkDSrqNs+TeIu6FpVbEHhsNjIvD6ZihBkFijgQYGus5TunGY3pUD7cn0UUbce2MRxnAc1hxuEo5scfv5Jrs5GC6/kk4jAL+Pq25s8+fsWmkvzJB8cjDvMAayENfW4KzRdXBR+9MLx/Z8SmNkwSxWEakMcCCvNIkSiPSEHZdgTuWm6ajtSd269uKh4cxPzu/ZyqtSSh9CzeliIDHUf748KNQcdQNqZDG8uzRcPFuiEJfGZpwCxVjGIBkC9Wco6eL2sW24b5vOTZomaWZq85+Ya+z7Y1fH5Ts61a7k0jlJNrezDEcfxN298MFh1jRueMbvaZRd3uGJYk3bFdcepYPbc4V2pnatMziPsH1f+sB6Aq2Bnh9M6pvr/LQGxEsklV7ljCPncxjFzGYyXSV2tFftozkUHHHmkhP2tqMaIJ3H/3++mBaP+6N1nF3gwnjiXqwlrsxStnLlMP8k0QOWb1xYUYwoxTYRMrje2kt9EbTbDzG9TRDKU1rFbUT2/otMGsKtqiJhwndGVLcDQW0NY0YhbTCqjUq104eNsYOivdlJ0ReV3TGie7ceYifoff7qR8VWVIU8lr6TpLlgWoJMJTPsHRCD8Joa6xZYV3944A855NTjO5Ni+ewRl4v/UDuHjOyT8BezunKhvs11/DSYE3HuN99wMOH7/go3/5Be//7h3qj74kvr+Chw/h/C28JIXDQ/xf/Qr74gXmxSV+EuL/8TmMJ9Lv1wM6FUoxYLMUU5u7jwR41SXef/THcH2J/emf473/Pbmuo+lO7hzHu55Ja51RjrB9tLWw1HUF19ds/uQvqYuWoz/+Pty9i/fWQxkO6yU0DV6g2GxbzooC+/gzAYye641dL7H/9k/xzs5hNnOxMJ4wonEq8yv4ZtVR3PH0ABBNZ5ykTpi12lmpp0E29CZ21rBqVpSm4jw7o9Clq8D7w0IXGACiyFkbLJYA5xbppKa9+UjPQvSf2xt9gFSYAfpsvj5Prwd7oyjDQ1xKleplcYFMN9e31Vdk9410YGe8AZKdaLpdbIfv+eCLu2geJnTWMi9LlnVNqVtas3uv8n2KtfSSjl2/X6n1EBKeBQmFrpjGMdM4xtiOp6sV60ZCtpumJc/EHXEaxwR+QNO1lM5kptKadVkNc6lttevh6L+LRF/07KHkSb2e99W2mtjJR9tWk6QxkZOyzZLEmWOIccg7swP+8M7vcie/w7bdOjv6gC+Wj7mT3eEHx9/jonjF//b7cLm9Zd00/Gr+2EkBp/zg6AM+u/eSf/lXv+SHHzziJ68eM69WvH/0iDv5HWIVc5Ie8tPLT/hq+Yyvl1dkYcg/e+eESTRhHE4IvIDaVAR+SBpkbNsNWZBzL38LbTW1qfhP7v4DrqsrfnL1Uz48/ADlB4zVhHWzZtksBxv9/T7YaTgVKWo/tlXCs/UFf/GrF2yLiv/Nb/2AB5M7vD15BMCyWYm7r1JstxWrZsuXy684Tc5cD1bHolnwJ8/+Z+6NzpnGE9IgcUyN9OnKGPl2KzjjWPW+17f/ux/7na2JnDmIVGjV0CdZ6orUsTaB7w+9if3+vGH5ad1873uJd/mJbdfSDdJrJcZPnUZjh3nbOxUHfjAUhEynaYz0Vh5nM0I/eMP8o+/V6nb3BMfSKccG7c/B/VzHblgwe3hW5LFHiRToLjZzFnXNtmkGxka+i8eX8/luDoYhjTFDb+M4yplXK06yHGM71k3Bk+VSjKbqmrJuGKfiEnycZaRhQm0aNm2J6TpK3bIq6+G4GmdmI/PNgW5tBumpLFYVWptdL0/dkiTR8PskjYlCWfwfpSlZGNKalnXT8GByzFl2RBbmNKYZcg+fry85Tg/5zuxtrqsb/vMPLFfFmkJrvlo+5yw7YhxlfPfwIV/eueHHP/+MD7/7gF9cXXB/UvD29A6n6TGJijlIJnx2+4SXmyteuOie/+T+75AFGXmYEfrhkPWZqIRSFyQq5TQ9kedG1/H75z9kUS/5+PZXvDt9SOApsiil0CWFLqS4sde7rruWLMixjnWLVUQaJFwWC37+6hV13fKfvPM2d0Yn3BmdAhLLUhuRCZdlzaYteb55yUE8GwyQirbgL1/9Nef5MbN47MaqL/mkrnDybY7EIjt9XW7Zj2HTdTTWur7yvldXYgh0Z2m6Dg+GHsJ+6/fV/+RNKbZ6DSgKkdBnInqOSTMdQzRMrzAJ/Z3axFhL4+IbTsfh4Oip3gCJlh0jORyD+3tflvrrlvEeEgR/5IDO1boeIitMt5vvyvMonalNGgUDmyhxFwHjWHFbaiZphLEiY7xYlFgLt5uautakaUjTdkyykDTyqVrLxvUiVo2hqHZgv23N3vyz7mf6tb5F3+8G0sJaqGtNksj3aBpLmgaErlfyYBQTBz6t6Shrw51ZwskoIFI+jemIlI/pLC8rwywJeOco5nqr+b0PTlkWDVVreDavOcw7RpHineOEi7tjfvqLC97/7glfX23Y1DH3Ziln45Ak9Jmliq9vKi7XDbfrmjDw+f2HU9LQJ4+kp1E7lVGkRH4aBz4nWTBISH/nbs66NnxyWfHOYUzoe6SBZFhum87JlHe6DumB7FlBSEJxXl0UDU9ebagqzQ/ePeJ4FHE6lvVB2Xa0WlphqkrTaMOLVcMkdnnCiJHTT59vOR1LJEroyx2+Md0gtf0PN7jpcxLNHsrqAV7fG7hZObObbLfo1tpJTDs3W/3dPnv2rndMbRuGjMTeybSXs/ZB975zwVwvXVlH70xSdCt9aD1r5Pt4B0fCSI0mTjIbCMj0O/m7LndAQWuRVo7G8hngjm/v5mU7KTH5e/2N7jt45/ewWtM+vsA2Wv4YK3ERCFj004jweAxKUX31Ci9QksF45w52fiOxDW+9BasVzS8+o2s0VncUyxIV+MR3Zlhj4fBQGL2ioFuuRYJatjSNMIJlKfrxMOh7vwQo9j1Sb247h0soCpGqytpBkwFtUZMon+h0IsYwWSZsbd9bGiewXMDBMd6DR1IoOLsH353hHZ/Cz35CGktsiDceC3AfT4n+yX9G9mf/FxbPlhy8c8TmL79kFAQyhg4cwH/0iO6jX6JXJVESSj/jvYeufzXcyaB7t9zOuPiNTK6pCiHN8M7vuWKDY5fjRNxrf/y/4L3/IfRjJBuJ029fGGkbMaFpWjbLmtEkwnvnXbj/NvbnPxGQeOcu/N7fJTz+gvvWSh/nvYcu97OFq5cinx2P4dF3pK/XaGHtAb761MlcQ/jD/+K1a9PtLU472+0y1RAjiUiJs+m6XQ9ZXCItEoB5WVxKJpsXDz1GjWmxeyxhv7/OSbKM7VDsejtMt3M9Fdmq3knSPG8AiOPI5f24HqssTBhFkmnY9yT20Ri+ryh17eS0amAbRcq667NSKCc/0oOJDjDkLwauL2sSi2HO02olEk0tspzQOcCFHoS+kmiLOObxYoGxVowy8pxCV9S64SgdYWzHZ7dX0sfYdZRFha98TvMcYy0HaUqtGyywbhp011G2InfzlU9dNUOUxXAOTfdr5x/ITbrPUhQ20rqpFdHULcrzmCUJge9zdzzm3YP71KZm7uzul82SWTTjvdnbbNoNd7JzJtMJx8kxf3bxE5IgRneag3hKpCLG0Zj/+rv/Kf/uky94fj3n3fMT/u2zr1G+TxZkHMbilvm94/f4dy9+zm1ZkgQBi3rBdPyARCXSY+pLgHjiJWxwxY2uJQlSdCfxLFmQcTc/H7IItRU31U275V8++9f88PhDl/vnkQU5lanceNO0thUTD6NZLjeMxhkfHL7Lw/ED/ur6Z1S65q3RXf6ju3/AWf4FrTHcG526nDmJR3lVXnBb3TKNR7w7eYfcxYT0Vv1frr+UBasf8XD0nW9cG/PaHNwVMzrH4shiO6A0FaEf4BENcr59gxv5v1xXYcdF0hY4sKy7vT5Gdq51vfRW2IZu+Kz9e3cPtkdRTmc71o2wWAfJhFW9ZRRmeD0goI8X6IYszX4Ol7ohVvHQGwng9QZuVsZlL7p7rV/Y8znND9Gd5sv5DY0xNMagu26obgdKkYZiEhP4Po8XC5TnMYlj7owOmVcrtm3B3fEpm6bg55fPqI2hNYb1tkQpxZ3RCGMth8mEWrdUumZV17RdR6XNMAersqZzEnKJsGCXa+oKTvsLo6HX0/coy3qIu6jKGmstVS1AKA4CYhWR5QmTOGfrjFyUH7BpN0yjCfcn55S64jA+4OH4PgfxjJ9ffUoSBGjHGgZuXvyzd3+fn33+hIubBQ9Pj/jJ8xeEvk8axEziMZEv8uGPrp+wrGsipdi0W87SzJmNKZJArr3vhaD73lqZY5XuizkJ5/mxu1/KfTj0Q4qm5K8uP+I7Bw+FiQSSIBmM0UwnLQOlrkRmuCnJ8pR3Zm9xnp/yye0XNEZzPjriR2cfcpy+pLOWk+yA8+xEZNMY5vWCdbtmFOXcHZ2TBhnGKWYAXmxfShaj982CzT47aPeulbCF0lOmfGFh+kgFa3d9ivvgzPNeB2r9NhiAwO7PILveGesoh2rq7vVjwb1nFMk9v3QGZodZwKI0zBK1BzR3W6kNgSd9jbqzVFqktPsOlm+yid9mhKNc3l+jLc9vt2gjQFUULJ6bf+JiOstlfXu5rPB9j1EScDaJuS0126bjrVnMstL86mKNcX1563VDGPocj6Uoe5RHNFqMVjZ1S6s7cRbVxq1BzfAM7IszxkW29c/Afg72xdT+Z2XZDvOv73Wsa02gfII8Ig/EETULfRalIQslr3BrDNM04F5nqXTHURZwfxoxSxUfX3iESqI2ssgnUB5J4PMff/eITz6/4fJqy73zMV8+XxIpidMYJYrQ9zmbxDy+3rKtNVMVsW06skjC7pXvDQXAWHn4XufUTgh4xcpnhT5no3CQ84tSyGPbdPz8ZcHbR8kgAU0CkUXL2kvGf9VajLFsNg15HnJ3FnM+DvnVVYU2ltNRyPfujoZrO81CTvKQzp3ZVa1ZVYZRrLg7iYgDAdZ9T+PLdetyH78x/V7b/maw2EvzrHWSU7uLnOgdLCvHaPVSz75MEIavs4m6FZDT9wAGe4v9INz1Nw4Asd2xeH3GYbVnAtL3MIbRjllsHZvoO1nrdCosjnXH7VkGsqJncjYr7HolEsM028lV99lE//UJO2zOXMf+8he0Ty6wTuJpjcULfPwowIsCojsH8N570m84nxPfmeGNR3jvvgcnZ9ivvxRTlZsbqCr07RY6y+qmIAx9srMJ6uRA2ETfl37BosCaDrMqMY1Mqq6z1I0hdI5SZo9dsU5207+u/yNSHDk9YaRInP7bVx7aWLbblu7FArOuSK0Vqe1iIeye1jCK5M26hcMT7Oe/xNssXTC9L+f/+BiyDPvZZ3SbAv/dt/HuvMWDH97h6c8viJ7NubouuffnnzHKcwH+h8fwi7+m+vqa4CDH+/C3YHogbF9/fT1f3EY7LVLP+ZXrfVXCIK7nMDsWcBinOxfeKBYG8+33Xc9quOtdrQpY3orUtDNwfI7/u7/Lwasl8fsPsFUJn/8S7/BIXFvrCvIJ3v1HRPP5ziUYdnEfh8cCIJNsN+bBmSK9Jc69//x/gP/u9eG136e4u452YCpCPxj6hcbRiEpXdOwWkP3rG9MQ+HboY1SeInT9U9aKlb/19oCo7ahMvfdgFqlZvykUHSINUp6iNZpQBbSmHdiRzlqSICb0A8c+GrC85sIorKamaCtCX5GGCcpj+KweOPpeuNcv4g3H1ct1nq+veb4SoNh3YsVKoXxvAIl3x1N0pynblmkcEyrF/ckBoyhj0xTUwLIuCJyjqdaGzVrcEA/GObM4Ztu2KM9nq3esybqpB3fTznS0rXaOiv7w8357c/5BP//kWkVRSBgGu4zJrqN0bEndaswo5+5oyropOM9ELpsHuQMnmuPkiE/mn7JslhwmR/iuVykJYsZRxi+uP2PVFHx4/Db3R/f4nXcf8LMvn/Lkds7N9ZJ/6/scJlMm0ZiT9IQ/u/hrvpjPOUpT/uDO95jFM1KVDvJO3/OJvAhjDXmQM69v0Vaj/IBJNGXdrJhFB0M0Rtu1xF5MpCLu5Xd5d/quG8vyGOpddxf1nFl8QKe3nGYn/MP7f8DT1YofnT+gMhW/WnzGaXrMeXZOoQvyIOftySN+eHaLdtEesHNlPE6PuT9+QKpkoR54wXD8d7I7NKbm//7Z/8A/fuuffeMWPxjaDAyb613yfAIH9vo+xb5g08+rXb9Wz/5J0aMHWH7fe2g7Av91hqHvAdyNdenLbdnNQ+sKscoP0J0m8IPhPf08mSUjx9x0g5Cuc99Fwtp9tu2WVbNhFk+IXE+tqAm6gWHcP659oNV2mg7LL2++4uvl3EkG5U+oFLFSYnAzGvHewT3m1Zp5teZ8NGIURbw3u88smfJi84rKtIOD8nVRYIHlckMQBpxORpxkOZWRotKq3rBtG4zrVWxa+d6dM9AY3Ei7PnrI3btcW0nXde6P9Ej5vrw2DIPBIMr3RUJXFhWvLKzrmkezjkfTE+bVmnGU03aaJBB2WneGWTTlq9VTtnExFEHiIOJYhWRhwme3T1g3De8dnHN3dMpvPbrLJ1+/4MVixe3Nkj/3ffIwJQtTpvGEX1x/wZPlklmS8P2Th4zCfHDfHe6RntxTkyBh1awG1joLM4q2cE6n4dCiEHohoR9wkh5xL78zGBb19+Ta1GzaLaNQig+zeMqPzt7jYrPh/aNjKtPwePWMg2TCUXJI0zVkQcq98RnvH0nOq3JzujeOmkYTTtMTmSO+2ilKfE/2YRr+5MmP+T989/X514O+ndpk50KqnJNpryIJ1H5H7TdNYaxjJiX64nVTmd50xt8b5994796/dxDn9f8W1rIvKMFRHpAEavd791oBunLOl7VmURoOMjWwPPug8Ntkqf3vtQN0H1+UvJwXA1vYA8XQgcTjScK7xyk3W828aCUPMQ547yRhlgQ8XzbUbceNbSkaw6posBaWy4ooUhxMEmZ5RGs6fE/yCksXhbGttWMSwZhefuoNhjZyjvr5tyMxjItr8H3c/BOAmabBkJtoTEdRyD2vqEWafmeasKg0SSgxIEng03bC5E0SxZN5w7oxTGIZg1HgMcsjstDn8XVJ1RruHWbcnYS89/YhXzyec3VbcHsrJmVRoHgnSpgkil+92nK1rMiTgLdPMtLIH9jAPkYFz3P5jCL1FDzcESsnVw3FQTVQrgDo+4TK42QUcG8q91sfBoaxj9nIIx/TwSxVvHeWM9/U3DvKB2nqLBVZbNtZstDn7iRkW2eiKnTjqHcAniSKkzwc3FF9X6CQ8uAgU7TG8uOvVvxN22+WofZuodbKv3uGsA9R95WArDAS2Wia7aSk/dazeL1JSN/vqFuG7DnfF8alz2Csa5G39mC0B566lZmm1A5EDjOo70kEmhrv5HzHJqJ2IMN9N3tzCa9e4X3woZiSeP5OJqv2AEk/KnrQaDsBbos59qO/pv7sGV3Vyu9Nhx8H+EmImqSoR/fxvv87EEbY5hcwn+P/4d/bsaMvn8GrV+jnVzRXK8k2dDmLYeiT35kQ3z+CyWQHtj1PpKibiq7WaFdFqmsBikHoY7Td3bRcNcdo5wQW7Kj/fuFaNB1hYDBZQJYFxHlCdO+A6MkNy3mJbgtM8YzxdIL33nfkXCepsGbnb8Hjz+Dufbx335f+wNkRHJ/jPdxgb66E3fvh7+H/yf+I99774hr73j3uLArmV1tOjlMW84rn/9d/zQf/5/cFhJ2fk7nBbj/+JTx+jPe7vycgbXa6uz59kSBw8Rc3r2BmhIGstgIO900g0lzGUbGRMXF4truu+VT6ZJtKmMZ0hP3qV8R//IcAeO/9loz12yuoK+zTx3jfO8BePEc/fkFwOvv/kvanvZYkeXon9jM3389+7hL33tiXXGuvrqpmk8PuJociR0NIGGgWiYKAgSABeiFB8wH0IfQBBOiFIEgYzIuZEQYUhmwu3eRUdxdrr6zcMzL2uPs9u6/mphd/cz83Mqu7B9BJJCLiLuf4cTc7bo89G8Uv/9+E33sf9f535DmTvjCKng+XJ9jPfgvPnkEQoP7eP5Ljf/Dg69PPNm8s/NquM09pClN0ITWDcECsZaGg8LpC5tr5wNrSbpBFp69893fj2EjHmNAm4snrtowUvClRaBxTWDTlG9+rHAuJC6Np00/bR5t+CiINLeqKi3zOKOwR+aHzGNbd9z21lbO27Evr+wo8n8KUfH71mmfzOXlddx7FUMuuYC8MudHrcWd4A9/TXGZzLjYb3ts9kmADFwAyLza8Wi4532zohYFLS5QKi9Gwx0G/zyTuEfnbGpBAa8qWxTQSLNQCxSDQHZsI24VHu3D1PK/zT4kktaYxDZ72iKKAKAqJ4pBJmnAVZqyWG+q65nVV8/7uDe6PblNbQ+onXOQX3Ozd5PHiMUe9I96ZvM2iXDCxU3bjPR6N73OWnXPUO+R7e9/ln375z3lv8g6Ntby3e8TZZsPlbMnO7oj5fMX/7d/8K/6v/9HbrOsNd4YH3fX4yevfMoq+5O8c/YD9ZJ+deJe2869NZvSUh2c9LvJzTDiWnk+zwVfBG7LLWCcYW7OuVviez9Tf6cbmIBiwqdcUJif1U1K/xxfzx/zH7/wdLJa3x28ReiEX+QVZnfF0+YzxzpiXq1d8evGKg/6IP33+/+Lfv/ttvrX7DeeDjOj7fTzlcVVc8vHsEz65/JLQ8/nH9/8hZVPyzb2vs4rXr51scmzDpWS8V1S1bCC0jFxhCpeG6tE6Da2TjHpqG4/eAskuMdLiFiAGT7UeX0Oow86zqJQCS7d55DnJKe4a2c7rK+e6bCr2kh35mgLVHrubkgbLLLvkeH3OW5N7DMK+vM+/Aih+9Zw0VmoUPjz/gk8vL9wclEVb7PvEvs84jrkz3OW9nYdopSnNMy6yBb9/9J4cQ9NwtrnkZH3Bi8W8S0+tjEtMDnz2RwNuDYcMoz5pUzvm1SP1A9ZlKXJWN98q5w8Wj7DpJKjdxpeRTStPbzvQWtBYVwXa/V6cRCRxyM3BQCTpizWmNnxS1eymfd6a3ME0DVEQsSxX7MRTXq5fs5fscGdwk6zOGAQDRtGI24MDLvM5++kO703f4k9f/IR7I6lKemtnj8s8Zz5bMd0ZsVys+S///Cf8X/7DO5Sm5LC/0wGmD8+f0Qte8+39t5lGU4bhsLtOVVO7DQqpbFmUC7EWuDF53T8IdF27ucnxlMcoHLux2tALeq7vVIBwomOeL1/x9++9T2Mt94e3CbxAJOBNyavVKW9P7nO6ueDJ7IL9Xo9fnPxrvn9wl7cm991nf0ispbJnUS54PH/Gi+UJWnn8ezd/SNXUPBgffX3+uT/bGgR7jS0sjaVGGJG2K7dy8uKvsnjG/aNdwl0f09eZRWMtvvtebbfqlPa5rofrtMfXLg/bv7dArjKWw4GTNdO2vLZAVYDe+bri5bzk3f2kAzfXmc/rvZJfBYzGWuZFzQevN7y4WFPWTRf4EwWawPcYJAG3Jgnv7osyJa8brjbwg7vD7v2crSuOlyXni5zZppT7aC0S0TDUTEYxN8YJw9jHNLaL7gh9j6wUT6Tcx7ZAsfXoW7tVKQHUrgzW81TnZ5Tfbdxrun7I2CeOfXaHMaezjMWioKoaytIwiAPu78SYxhL6HsvCsJP6vFyU7PUC8S+WDUQwjHxujkIuNzU7vYC392J+/GTJ7ZFs6N/cSVllFbNZznSasFqV/PM/f8r//h+/TdVY9odRt1Z+cr7heK5550aPnRR6oe58hi3TrN1YWhUGIvEfll9h7ay1hFq8i3lt8ZSlH24r7GJfu9Am8TjG2uP5rOT79ydYC3cmEdqDZSEVG8eLioe7mot1zek8Z5SG/POTJQ9uDHhrt/V7Kul9BJal4cllwcmiQHuKH9wZYBo4HMf8dY+/OQ1VeVuvorybbeCN8iB0XsK2usLT4mNrPSDZxjF/QJt2pf0tsGt7FtvfbRnFKNqCyxYgtcdTZWDcv9vXbeszPA2+ksV5tsbmGWo02XYjNo5xef0CXrwQD9lo6gBxs2VR29e6Dhpbf2S2xr58Bo8fUzw/7/yJSnuo0CfYHeAd3hCJ42RHXvvFl9jPPkfdPMK+eoHavwF7B9g//RfUZ3P8nQFNWWOWGb33b1JdrdH9CH/cc946D3q9LesZRaA9bGVQnsKUjcNLHo2x1Ndof9tIt2LnDSsliVF7quu4qWspc1V5TRRpskWOv1vR+8EjzI8/pigMWVYTfv6S6OgINdkVKWrakxTS/mA7RqrSgckYbt5F9Qbys8dihrf/9k9R//P/BPWt75AulmSLJ0y+d4fggxdkWY19+qWk2I5G2DCE42Pyz16TfO8t7ItnsuQcTIQRrAoH6Cu59r0BDMaO0XaAEAT4rZcy9rKNhOW0YLIqHFPu2PDeED74qdScTEG99x0BnOulMJZhLD7En/yY4pNnxFGEGsuibP2rJ+TLgnT+U9LpjhxPXctzNjX23/5Lsp9/Sng4Rt88wP63/5X0YZ4tGP4Xv3sKyo5o07FyeZ133sLAC6Qk3Gz9Om2KYqhCqdawNT4+sR9jmtrdeIUREB5EdUCxfY5A+93XgW6xIR69ggoJ7bDKdixYKzfVyqMXJuR1QVFXRH7QSYzEp6hZlWtON1eE2icJ4u5G2FZxyAJpy5K0nWQCCA0X2ZxXq0teLZcdy6c9YalGUcROmrKfjgm0T+p2/p/ML5jEMasqI/A0/TDli6tjLrOMcRxTNw2zPOf2ZMy8KIjDwHkU22oQN1eahn4YduC0e//WEgS6u/m1Ejj5eDJSP+MpWbC689z6FNtgjQIIXHJjGYW8s7fLB9WxBHaUFZ9dnvHeTsY0mnBVzOgHPZbVkjToSYG8tV2pdqQjjno3GQQD5uWck80pAP/s6Z/yn739H/Gjg+9xlS/48SbnR7dv8fPXr8nzks9nX6KVxyga8t7OA54tjvnt2RP+zq0pjxdPkd61sfNulh2TppUm9COG4ajz2WZ1hkXYv2W1xPd88rpgN94lDCIKk3chS76rkugHA355/kv2kz1sZPnm9BsEXsiqWtIPZGNkVa340xc/5hcnz0j8hJ14SmMtf/HyGat1xiz/CbvJ1CU51vR9CXD4k+d/yr96+hH3RmPujw/5f3z0X3Gx2XC8XvNPHv3nv3sCIovorrPN2o5NbDdvxHO7ZcyvB+bULskUINZxt6hvF1Atq9P+vf3Z1k/WcokKoUTamhFlpUahcd9rnHdRuf8GrsduU+eMwoEsot1zWGs5Xp/xYnnCOBrQC9I3WP/f9Rm0lfEZCdDZnPPl7BVP5nMqN6a18ggDj7005ag/5tFE2DCtfM7zc764esVhf9oFYk2iMb89/wVnmw07adqlmr63t8dllpGHIeM4JvbF4xYEMU0jSofUj9Fe1tUbNA4wtvLTrfSt6VjHTtrbylE9RRyH3e/XlSGnJIpC1pucPEn44eERP66eUZU1ZVHx2cUZN/v7jKJ+FyaTGwmc6RbFVoLHAhWyn+yR+imrasVZdg7Aj1/+iv/w/h/y/s4D5vmGn29yvnPzkA+OT8jzkmeL1/ieZhj1eTAOebU85denJ/ze4S1er85QqC60yFgB0AbxmwZ+Qi/ou/tGLbJlA4mO2dQZvqfJTcEkGpN6PQpTYFxFRpsgHOuEz2ZfMI6GEMGj8X0Cl+KbBr1O1fLT49/wycU5ofYZRwMa4JcnJ2SZSIQn8ZBeILLT1E/Awl++/hU/P37JjV6P28MJ//Txv2FRFJxtNvwX3/4r5p+9tn6xltIBEaUgdPPnOsi63qnYXPvdbf0Fb/y9BaDXlSu+2nrJ1Fe+L6DpOgsoVR3Wbr2Qk8RnUxk2pcgiva8wny/mBU8vCyapTz98U4J7nbn8aqVGY0Xq+mpR8eVFxsksk+5sBIQlvseoF3IwjHm4GzOMfDwFp6uSJ+cZ+8OI01XFTiphKb95vWa+LhmmIXVjWeUVd/cHrPKKNPLpxT6h76E9AYjWug2hwGPpKYy5vhnKV+6B25wMY7Yy8KaRd6e1ImpBclNRVVLREYaazaaiTEPevTXmgyeXFIUhz2teXIj3bhz7ZFUjKaRGugdbq07lZJaB57GT+sQOVJ6t5fs/fbbgH7wz4cFOwrqo2WwqHt4a8exkSZZVvFpUBFoxiDxCP+ZkUfLydM1bhyNOVhKWFfse2pNNDBCOSikJyOkFXudbLEyDrenSUrWnyKuGcSKd5EXdbGXQSsZR5Ht8cZEzijXE8GAnItSKTdWQBB6+UmRlw69fb3h5sUZ7E4axxjSWJ+49ZKVhnOzQCzWmUSSO4f75ixVPTpcMk5DdYcS/+fyKTVGz2PzukLf28deDRaWE7WtTQmHrY7QW4mhbE6CueQ1B/mwZxPZ3PW8rpWzhuqeEcfH01ofYAtG63oI1a7dACbZ/BtfqCYLQSVkdINys4fVrbFGgdvZcMIoDqlnmJIPB9lhaGeyXn8Lh7W0NR8teXV1gnz+B42OqszlNXtFkJV4cELgQGDWdwHSKuv9IQGi2gbLAnhyj3nqEunlHmKsowf7pv2D9iy/xpz3MpqA8mZO+fYB69JAoTbGbDeQ56sYBdrmAjZM19vsQxzRPXmEbGXxtT1wLDK8DRWvb3aDtR5UxMnlNUxEEHr6vyEuDKmG5qhj0A1ZfnjMZpwSTlPz1gqaB6mJF9Pw59PrYxRwVRsICh6438/lzuTbZRkJowkS6CftDSPqo3QPsr/6dfP/OI9TTLxmeL1HvvM1gOOD4v/4ZzZNneHdvSzpqfwDf2CeJIspPnxJ+/xvQhsdYl6Tbgnqn/pQeThdU5Ifw6QfQW7v0UydL9kMBfelQQOXiUn5+cSXfv3lX2MOrC/jG9+V5d1waa8uwVxXRnT3W/82/IrozxZY1yveIEp+mNBiX5srNu44RN6i790iWS9Qf/j3sT/6cs794jNbCLAy/Mv08FDXG+Z/MdgcZKfnu6ZibPdmNbdwOs4BBYeV2411eb467hauvNHmTdyDRNAbP8ztp6nUWs2UfBQg0FKaSwBAaF7zhWEQ01hoiLT177e2wcvLSy2zOMOoT6ZDYj0h8CczJavEaBV7LoPiux8xnli/oBSm+pzu/F0pRmJJ5vuIyX3O+2VC7AvBQawYuBKYfhowi8ei03s7clJyuL+mHIbvpmHUpoT8fn7/ki8srBnFIuTaczpccjIcc9PvcGY6oGkPVNOylI0xjyBthYmPfpx8kvKgXnZR7uwjdehTbm2TTiFzwDZ9UI9LEPJOqDUlGleuUZQVJEnG1WLOTJPTTmMurJdZaTtdrPrn8ku/tpyzKBZGWkvZEx/jK5+XmFcYacpMTaNnNj+KIxE/oBwN24x1+fvZL8jrjVv8Wb03ucLJe890b7zCJh/yXZ3/JZ1fPeTA+wmIZhAN+eLBPGsT84vhL/vDON9hL5DPfIgDRV77rFYxpO+ACLyAkJPIiPpl9wsbfMIkmhE4iGngBkY4YBENqW3FVXHbJqsYa7g7ucJadcZlf8e2db2Ox7Mbyum0gS1YXPJrs8n//1b/gwWRC5sZCHIfkdc2fPJU01zv9213gx6PxXc42l/zPHvxP+NcvfsyfffYY7cDF73oopbBNm8Jr35CHWiyRFzF0NQHX/YPb8/O7QjsalJvPwjn4ThIqrL7ngF8LQNv6j/Z5WyXA9bCq9qGvsZfWWtZVxsvlKUVaMk1G9PwevqcxSE+m+ApdJ+Q1oPhi9Zr9ZLeT9LYbTMtqxYvlMcfrS87WazYudCn2fXajiNj3mcY9psmIO4ND0kDASN0UnKwveDA+5LC/R14XxH7E//DyF/zq5IRpHPOyqjhdrXm4M+XR5IhkLyKrCwpTspdO2FQ56yrDQzEIe6R+TF6fy0aF9iivAcGvAsXr869b8BsJvMsaYRQ97ZG71NT1OiNNY55fzhjHMaM05qwQieVFlvF08Yr3dh6wKFaEvRBMKR2zns/ZWipa8jrHD6THdqpDUj8h9mMm0YTfXnxCYQoOe4fcGZ5wtrPhnektRlHM/+f813w5O+X+eB9rLWkQ8829t4j8kE8uTvm9w3uMXQ1Kd/0VeNYjcEu6qqmluxON7wU8XTwj92MGYZ/ACxxTJWFMqZ9Q25pVtcZX4osEuJHuMS8XzJcveGv8EIBxNO7GlkI27u6MRvzXn/yCu6MRZV0LGxcFFMbwk1ef8N0bDzno7XWWijvDA5Zlxt+++R1+cfIhP3/2Eu+vSCeVcb5NQIV241tYvMT3OplnG0Kz/T1h079qFf9aoMw10Oi+cI09F7aoTVRtn7dlktT132Mr/xOXgWVVNjy7Ksjrhr1eQC/U3c+vS5Fr+85XeF3K+nyec9APCV0wjlzThkVR8/Sq4GRRMluXlLWhrBtC36Mfh4S+xzAN2U197kxC0sCnMsJAna1r7u0mHA1D8kp+598+XvD4eMEgDTlb5MyWBTd3ezx0ksusbChMw41+wLJo2DhipB9p0tDj5WXTzT9r604xs2UV31S3XfcLt4y+MZYg8NDO818pxWZTkqYhJxdrerFPLwnIcwnIWW4qXs1L0kBqI/Z6irIWIKuV4nhVUbf9h6Fy3ZIeSeARaQmu+egkI68tR8OQk1XMbCfl7k5KLw44O9vw6nLD0VTIrV6oeedGiq8VLy/XvHM47KopGruVjyrormU7brQWb+PTy4Je5DGIJP3UNBKkpD2PKBIP4aY2aKVYFaIg2+sFLHLDPC95MJX7/MgBa+vGWm0adoYxf/HpGbujhNo0HQA3puGjVyvePuiz3w+6NOGjUUhRpnzn9oAPX6/57NkM3/f+ykyF9vE/omfRvFmD0TJ/vi+L9lBuJswuRILaSkSNk32OXc3A7FKCUOJYFvLtIr+VfpryzRAdcFJTtr7JNhDHVFBbWdzrVl5qtz5KF3qibt7B+r702FmX6Fo5gDEaCRCb7mC/+FjSLXtDOD/GvnyJuv1AwnQWM5jsYH/2lzSn59QzB9iUoinkXIQ3RqhBH3Z3UTt72M1KgIgfCOP26jmkKeruQwHLgP3Jn7P62WP8cYpOQsqzBTqN8P/23xLWS/uotkMyjFEvvsRmGWo8hqbBlqUwms01PX+3g9NQV003OU0jE7j9fGx/DnARxw1R6NGLfbK8Js8NddVIGtUHL0ju7dFbl3iJk3keHXVyYfv6hUhMQaSbg5Ec87PH8M434YuP5XtHdyBwjKPvw/kp9Eeo/RuE3wUWope+sZ9SzzOiW3ck+Gc+R+3uob71PcI4FpD29HNhCuOe25xwUulW7lyKjxCA54/l621g0mYlmwDjHVhcyM/pQK51nsn7Kgrs+QlqMsWulqgi26aktiewLGE0Qr3zPkn1L8kfn6JCkR9HNyeYTYk1DfbsDPXgHZkfo6lsYLRS7p0dJu8eYDYF0aObv3P6tZJQYFvK7AIK7gxuEzmm4iQ77hZKWmkiLYvYUIun7MXqJVfFrAu1AVlkXJentr6nr36/dmykFIdHbOoM6wJM5GsOWFqDh5Tea+UxCHtvLACuszORH5L6Ab0wZVGsGIQ9Ij9gXWbMijX9sOeqKUoGYcqXs1dc5TnzYluenjtVwdQlFQ7DiH4oTNIg7DErlviepjBSKH+zv0PlgOkXVyd8cnpOGocEnmaW5/i+5v54zDgeCFB1xz6MeqzLjE2dE/sRQx1I36Pd3gBlWGylbuYai8G1+dZqmN6U5ojHKopDilyCV+raEIYBj88vuTkZkaUlYRgQ+z4PxrfwPU3dGJ6vXnDTJZh6RiTJHoqny2e8M3mHT+YfY7Ec9Y4cgyDM7UV+QS/os5/u8bdvWa5ymX87u2Nmec6D0T0u8gsushmHvX1+b//bpIEE23y5eEJv2ifxEgk+cvx0bnLxzTUVkRdhsTxdPSWrN12gzLra0AtSxuGEWXlF35dkxFW14jy/wHcS69ebY3bjXZbVktxkDIJhB9ZkLtTspmO+tfM+ZfMv+ej8jFCL9PH2cMjSyRNfrU55a/SIWXnFOJywrjbS2YnlsL/HN24esCxLvnvj9u+cfy07cx0omqZl0TSjaFsRsCxXIu9DFuLayT57QYq11iVQZl04icgptRsWthsT7e444BgjOoa/9Ym2QUDbNEu3saIcy2gNWgfsp1IL0/piGyvlywrFMOqzqXLG0YCnyxccpHskfspVccXr1Rk30j3W9Zp1tWEYDvjl6UecrBfMXHaAVATIHDzo9RiEEXvplEk8JKtF3aCVR6JjqWoIYo56B13h/E+PP+Tnr14zjAVkXmQZUeDzBzffZSee0vZjKhShDjjLLshr6UGFtlqoZS/elHwb03SSU1S7MHUbqtc2ctr5V1U1YRiQxCF5UaIKCa2KopCPTs+4Mx6x6QsoBrjZ3++qf07W5+ylU0KgRHV9ga/XJ9wbRrxYvQJgL9lBN5IOGuqAq2JG4qfspVO+d2BZlALSpjtD5kXBrcENrvIFs2LJXjrhG7tvCZuqNK/XJ8TDhEhvN/naeaGV1wVMWSwnmxOyupANRaXI6pzIBV2tqxWJn+ApzaZaUzqWvzQl59mMSTxkWa6pTEnqxnH7qJqKUTTgrcldSvMLnsxm+J5spt0cDFi7tOizzSV3BkcsyyX9QMZcy+RN4iGPbuyyqWvemky/Nv+uJ6A20NUmgITbpL7eylKbRs4HrWTTOhBJ5yurjBS7X083bQHa73q06aZc+1mlRALbWgpaD2QL9pR7bc/zOOiHeECgHfN/DTSNE82mChgnPl9e5dwchsS+5jITaepBP2RdSTjJKPH52Ys1lyupPmilr5VjpVoP4v4gYJr45LXFd9JcpT0usope6HFzGHbl6z99tuTzV3PSOCDyPWabkjDU/OjeiL1e2+/aONuHQqmKwjTCdiEy29p8df7h5p/tJKft169vyHX3PyuJ03VVE0YBcRJRFhVFYajrnCjyeXq85GCadqDYIhUY7Xr2bF0zSX0ioFbQD+Wz7nhZcn8a82Ima+79gd9dy9j3uNzU9AJhHh8eDFjk8rm+u5uSlTVHQwFri7xiJw34xkGPNJQshONFxb2JeBFblvn6+aoaCb0BOF1VVM7qBbApJTW1H2nKynTyUAHm7v5mGmZZzTjxWZcNppHwG66N1cJY+nHA/Z2Iqm64WOb4WpKBdwYxuQP2F2upyli7zsa82mKBYeJz62BAURkOxslfMQvk8deDxbK4Vp3RvAkUGydHbZMoEycxNU6yGifyf+DAZBjBxakDdw4ktgJyraXSwrNv+gqtdb5GtQ0NAbqtopZJ9P3tMYKANBdWo6JY/G8tsHQMoto7wJ6fY798LF+7cSTy0k8/htUK+xf/BntxiVkV+Ic72OWK6mJFU9Z4/vYD2hskNEWF3VziXc3xNhvU2+8JSISOiVV3H8q5Ugr7k9+y+tljVOgT3ZqCJ3HP/nfedyxU/WaVQivH7fVEBlnmUBSooI1id7s5TRsLvmWIOs/Nte2vNxbwVozbqmpIU7/zWwWBJi9q5gsFT87QcYjuRdIfeXkJ730bNd2D9UoAWF3J9da+XNe3viHjo+0k7A3k/c8vUUnixonrabx9D8oce3lBfDTGH0vXprpxBNZKZ2ZZoB68JSE3l+fw4ku482hbl9IYAYVlKWFLrd92PHWS5kA8hqsl/ObXcP9Y/IcXJwJw+wMYjLC/+EtJxl2vsU2Devt9kZ/2htvnbIxUdSiFPX6J96O/RfLoXFjjy3NskaOzTJhgawWExgmcvBT5bq+P/elfwu4uwf/qf0lg6m1/6PXp15TULrq/jce3VsIDrBUfVOqL/LD1oBSIZ2kUjuj5ffqBjMPIi3i8+JKyedPnKx9wppOgtt4z+cCrqByj2CaQGis+IIVHoH28LmDBIiyjjL1Qy+619HXVnfetHXupH7P0NszyJRZJT60bj4t8zqaqeLY4YVkUZHXNJI6pmobLLKM0xjHpcuy9IMA4+eiqLNlLDZN4yKxYug60kEW5ZhD23E1P88XsnE9Oz9HaY6/X61rkHk4mjKKB6+/yOBrsc9g7pOenfHD5IZ7n8WB0B095zIo5afCq20ltF6Ct9PSrPq/r8qbr87L9HWMgCkKCQHYEQ1+8k9km55USD0i7UD3dXPLtnW+xG++yqtasqlXnL/Jdb9k747epTMkoGqHw6Pl9Ej9hUc7p+WnXHRjqkPtD8Ued55fcHr1mEseEXshheshhCq/WryibkncnbzEKR5zn5zxbPeX+4IHE9zelYzMzqkpCd1q/7CgcEnh+F/O/qlb85PiXvL/ziLfGjzgvzhgEQ/pBn1E44icnP2VWLFkUKxjDe5N3WVUrer70dzY0mMZ0/txX69f8/dt/wLf3Lrjdv8VFfsmm3rCqNizLNcYaNnVG4se83rxiGk/44cG3+NMXf87t4QH/x+/9E+qmpuf3vjb/4HrIVCMprY5h1A6cmaYm9OTe1LK8jVMC+F4gbJNj6X0vYFktt/K36+zGNcl3G/7RPmoHmNo52I4hT3mdbPA68wjiZ4x0hIci7AUd03T9dSbRiLPNFc8Wx1KxkUwpTMHj2XPmxYafn/yWi2zFqiw56g9YlAUXWUZlDL6TiisUgzCQjsO6Zlbk3BzkPBzf7uok2o7Vw96NDsB8dPGYn796jdYet4bDbpf92/t3uZHu0VZ4tEA41HI/TIOYUSh9nfNi2aWttve969UY25Plzomn3jiv189lbRpUW1nTyBzUvqYsK9arjGdAFPj0goB1VXGVL3g0vs8wHJKbnKwW8D7SYccm3xveobaGYSif7YmfEuqAVbUm9eOOafM9za3BDSpTc5UvOBheMI6lb3Q/3cEigKuoK+4MjxiEfRblkrPsjMPeAVrJBk3jWP26qYh13I2HQdDvgp2qpmJdbfjg7HPuj2fcG97uamwSPyVVit9efMK6zFhXGdZaHo3vsakzYj/uNjMaN68ATjbn/P7Re7wzXXLQ22NeLMhNSVblXep16+W9yC9Emhom/PL0Y3aTMf/pu39M1dQk/tcXq1Uj6pBW0nc9BVWOY+thDDxZdDdW/HzXg2zAhfb9DvakBXnbucjX2EWg8zK2rGIDhOrrm4UyN4XRCjy4OYy43vPYHsFO6nOyrHhyKWFy+/0AZRo+O89ZZDV/+XzFfF2SlTU7g5hVIf2JUtAugEQpRT/yKeuGvCpY5hXrYcxbe3GXqmrde7g5DF3FSMOHJxs+eznH9z32R7FYOLTHuwd9DgZhdx7sdTWMlTCZXiiBKHllOiZ1O/8ad09rN2a25/V60nc3D5WobJpGwuGSJKRpfIwx+H5AWRpWq5ITpQgCjzjUZKXhcl1zdxwxTgT8ZJVszoa+7tYH9yZRF3oDEDsgtXZSTmtFOhpoxdEwpKgbloVhMoxJI5Guhn055ot1TWEabo5ChrFmkRvONjX7vcAxhTIWSyOWoVBvPbODSBM5hrFwjOcXZxtmWcy9acSqNMS+pKYmIXx8mpOVEiBkLDyYRmwqAZjdZpi1rAupQjlb1Xzn9pBF3mN/ELDIa7k+taWoGkxjO6B9sakZJ5pemPLxyYZR7PPvv7tDZSxp+NfHof71YLH1JrbVGe0FbqwszJ20rltAl+WW2Uv7IvWTUSJM2/WR06ag2mrbxdioLZPZRnT6wTZl9XrFRvs7bd8ibGWJdS1AV2s5pvbnnVwD20DaQ73zPvbsWFJWkxT7+FNYLGg2OXaVoTyF7keYixlmVeAlIdHdfeqzubBGpkEFmqao8QKNd/MQ9e43JMkzz+TYl3MBT9lGmLg/+5dsfvscLwmljsKF4vi3D1D335LfMdeAz8WpeOdaSW8LxquqA82NEblpt2httpOxrJo3Fqpe2+vSqoA9+b26saxWVfd9z1OUZUOeGzyvYpyKR9JLQpqTM/STz+D2AwFmSYp98QRml6g7D+T8t4moSR+WM3kfSYr9038BN2+itCukv/eWsLejKWq9IKxrODuT8zaawOFt1M6+jJeXT2VM3Lon389WoAYyDko3/hojAHYcy5jbOXDg2o3XszP5+flcniNO5NpoDaevoSgoP3yM7kXogwP5vufGn9aAhso6aXLF5r/7M5RWRLd38LRGjSaoyY4A0LNjOReLmfz+aCys8ekr1HvfFD+r52F/8XOp4PjKowWKxi1U7bXFYO68XrWrybBW5JylkdjzXtB7YzGa+Ok2XVG5HWhPdywJ0C2AgU5m1wLFrVRH0jsjbxu5b6wLiqDBcwEZssPt6jLcQvB6uXfkh9xIpyzKNaWpCHXALF+SVRWVi96X45ZOxKUr8j7o95nleedD0Z5H4RavoyhiP50Q+xGFKSlN7c5LTRymeHh8fPmCL66uiKKAaRwTaU1hDDtJws3BPp7yWBRrfF9zmc9FihkMmERjYh3R72R1dbeLfJ2puL4Y9TyPuqrf2LhpdyCvS3HagJOWVezM/y5dNc8KBkPZjAs8j+eLM76Yf8G94T36QY9ekPJ0+Yx5Oefe4C61rVlWSybRlF7QZ1ktuCwuSE3KP3v6r7k3ukmoQ3wv4MHwActqwTAYcateUzc1L5enXRXAQXrIXrIrX1+/xFrLrd5tVvWSTb2mFzhZm2m6TtCN2RBpAZz7yQ1yk1OYnFkz5+XqhEiHnGdXHPaEiStcyMZJdkphSn5x/CXDKOL++KYLi5Hxp9F4eDRKzlnd1Pw/f/tnaKV4aypM1DSasBNP6Qd9TrJTJ50UhnkcjtlPbnCanfCDG99mEk9QKP7dyS+4O7zJN6e/9/VboPN/toCxmx/IZk0rEbdOHF4bkRDV1hCp6A2JaMdWq+38bjdaWgmrdZs919nFVqLadqUCLlFSd/5Ije4+H7TrlzRNTeOkrC1QbOewzK2Ytyf3OM+uKIzUZjxfvmJZbsjrmk21wFOKQRhykW1YliWp77M/GnG22UilQNMQeB6lMYRac9Qf89bkLoNg4LyomqzedJtPAD9++Qt+e3ZGHPjs93qdzO/uaMq94S208mls1Z37RbliFA2dksHvzlHLaso8usbMXgcECuprncfCBinnOGnnoPy9Ng3rdYbvAlLa+VsUpXjBxoOOOTtez3m5esVh74ZIvXXE8fqUebHkZv8Q09Ssa0lETXTMul4zL+dEOuTHL3/OYX+PgRK/61HviFW1op/22U8zjDWcrC9ZVWsGYZ+9eI9xNKZuKk42ZwDsJbtkdUZe58R+jPY0TVMLaLTWhdoEaE/Y77TpUZmSVWU421wReJpFIaxxqENKI9fmMr8kr0s+PD8mDQIOeryR8osCTZv2K3Pwv/vsV3hKcWc0clK5PsNoQOonzIo5dSPAUimPftBnEo25Kma8O73XJcZ+ePE5h/3dr80/0zRunG3rMkA2IMraYoLtIrat2GhDaeDrm3Zc+1mAbvvlmoS1BYPt47qfsavk8DwCN4bqxna8h7GSMGntVrYq7ObXjyP2Ne/fSDhd1eSVpGc+nRWSLlo3XNUFHopeHLDISrLSEAea6TTiclkIOQBSvWEaAt/jYBjz7n7CIPK7YJ6sNvieBK00NPwPXy748mQp4TW9kDY86HCScH8adR7JqrHUTcOlq/+Q9FlhFCvnxZM5tfUrbv9+jYGutnVbLRvb3gOtteCBsorGNGzWBeraGrSqDEVR43mKySTBU4rQ97haFxwvQw4GAZEPka85XlTMc8PRMIRGqj2GkU+UeGxqw6IwxL7l3z1dsDeIiANZkRz0A9ZVQy8IyJ189mxZsCwMo1gz7YWMY0kdPV7KZvtuL6CoG0ojG+fKLajbMVoai+/JdR9GPiZo3MaH4WojVSCrsmFVNkRaUbqPqIt1TVYanp+vJcW2HxJo9cYYbE+6p6Sx4Cefn6OUYncY46ke/UgzjD1iX7HIDaaBjcMBg8hDx5pZbrg3jRnFGqXg8/Oc3f5fDwf/ZhmqtVsmr0UYjRGmKHYM0XolXYtRDF5MV5mg1NaDuFkJ6wTb6oAaFzxzzdzbSkmNESAShltA2IbMRJGrzHBAs33OIJTnCtS2LL79vjFQF1s2s66hP5CaBve66q334cHb6LULRalKKAu8ukJ/+qmcjrJEhRqbCVAECA53UG+9Dbv7DkgX23O3Wgoj6IJ/6vMF1jQEO338vZEwZ1QCHtpz5Xoq7fMvUZOpnIM1qFa+KDMSL7kWc97ugrUA0kJeGpbGMA0D2fUBtKXzyHnOnNxKGoz7/dDR3YHrfikLQ5OVhLfuQV3TrDNsVaHaipMgFIA0uxQWLkrEH1pkwii7DQD74a/kPN++565xJecqzyCWXUr14C1ZJt1/Cz7/SJ6nP5Lzt3MDnn8hrxGGW/8pbBN46xrigK5+pa1osVYqLr73Q1guBKhFkQDF189EUu3GRfQf/H2ptFgt3FhOpJZDeZKc2jQC4J88pilr+ZBYF3iXl5LUapzk9e4j8UDmmbzmciHgeO8Anj+BOBH/5mqFXcy/PvXYdizK9POw7t+jcETi+uyW1ZKL/NL9jiTgBd6WiW9sw1Vx2QHAluUzLsb/utOjZSzKpnSLBL1NKFVaFoB4XcehMWbLNipFo9xCt2kIfH+7QG7aY2llFiW+p5nEA/FaWmEEp8mIwpR47mulkQXjyXrugg0MgQOI7c17FEXsJCmTeLjtilSaSZxyvD4n8SMOe3vkpuikq+M45nAw6MJq3t+9xzxfMk1GsrhxfsvAsbipn0j/HNKFp5QiDdr5xxvnr/2zLCpW64zxuE/j5DrXqzLaD37TNBLq4+ZuELgqCV9jrdxsq8owHsad7EwSbg1VUxPqgEk0ZlbMWVZLYh0zCAbkJiP0IifXq/nNxQf4ns/dwR1J0nR9g1mddbLRRyNJ5X04esAnV5/IQtPv0fN9JtGU56tnbOo1gQq2Y8Oj87waa/CRCgdlFT4+gQpovIZekPK3D3/IolwwjsZSJG4ynq+es5/s01hDaSr+s3f/Hjf7N1lVKydBjLgqLlEodmLxou4ne3w++5LSGBprmeU5Z5tLDtMDqqbGUx73BvdYVguyOmNRLliUC+4PH7AT7/Jy9YJYx/z09Odc5QuG0e9mFsGlEjvw1jJzjZWqAqkjaMhMzqZab3sKUWjP7zZILNteQ1lwOt+hLDU6UNkCx3ZBHugQo7TzKm+9kIEX4F/rLpXnss47qhyIlLHhqW2IVdtX2ioVEj/m9uAQEInrveEtbg+OyGuRmta2pjDSOfrZ1TO3ey5z0Lg/AW4Ohjyc3GYaT7CuX7J9ZCYn0THa8ylNyUWWYaxlJ0nYS2UTpGoa3pnef+Mzq2oqXq9Pmcaj7vxox6C2m0WR1tekpe090HmGG0teVKyznMmwJ9LUxqKtbMZs56AwG21VRmUNUejL/qDrfCvLmryqubk/wFjLqiydb7txcmCfUTRgUa7I6gzf8xn6qfucCzpm+vPZE5RS3OzfcO9F5nDLCALcGR5hbMPN/hFPF8/p+SmJn5LomNF4xPHmpOtQvG4laCuLTJdy3aCscuFRGusFxH7Mt/feZVNLpUab4HuanXU+SNMY/oMH32M3mZLVuSgydMiyWgIwCsdYZRmFI+ClVBZZWFcVs3zBXjKlTeQ9SG+wrjeUpmRTb9jUGw7TQ8bRiJPNKaEO+ejiM9blhkWx/trcE0aRbvPEU445bERK6HtbYNP2FLply9f8hNZadLvW5ivSUbZf344LYROtEhDYbbgrhe/RbXJsx+ybv9v2jF5/7rbmowWkia+5O956Lh9MY+6OI/K6cbJVKGsBGp+dZbK8rBp87blzLI/dYczbewm7vcAdy7X7kGlIXGd4aSyzVUHTWIZpwMh189UG3tqNu/VkZQSkv5xXjBOp9MjYejLluXE1bW9am7o1aCP3wGyd0R/1u4ApLJ1H1XOfI9v5J2M2COV9+O1xl4aqMuwdDMTfVwjTJ6oF6S1sGb9N1eArGCV+VzpvrTDTX1zI59rBIJBwGrs9x6EbHIcjkeoeDAOez0ph/HyPyPd4ayfhbF1R1A1aqS4FF9t24srreLrdQN9WtAQeJKHHezcSAbKxJtCKvLKcr2tGse42FX70YMJOTwJ8lMKF28hndy8Q6fU40byYieTX2oa8MixywySV1FpPeez3A7Kq6RjNrIL9vs8o0s63qvj0NCevDOvir2cW//rvtrK7dmTUtfzb0wIUy2JbW7BebT2Nvg/BtRhW7X6+7UX0gy6EpmP8gK6morHbcBIdbJkd35ffbQFIG7bTft3zBES0UteylON1oI+qhLMTSTJtazcaB2RbNjNKBEi0VRqDEdy4ifr9vw3jMSqKoLH4o4Tg1j7BvSPUgwcCANr3sVlJiM3ZsbBafiDg77OPKU/nBNMe4V2pa7B5gbp9W1JFWwluFEuZ/GgiIKZpsMs5tijkPDcGwhA9SFFuQdmyhXKpZHe1aCyp5/Hg0ZgGGdS1bVOprMPyMuB9TzHsiQk28D2SxO+ezzSWxbKkePwabt/GS2PphFzMsB/8SjyZg5HbLHDXWnkCkqpSvre7L+Mky7Af/kaknu11DsNtlUW2lut5dgK7N7CffyRS0ZPn8PoZ5k/+uXytfe6ykIJ7z9te0zZhtyq+Xq/ieTAYyusoTwDu/Xdgui99iH/8D+HhuzIO9o8kWdXT29crNhL6VOYC9GtD8nCf4Pe+BcOhpOxGkbCUtoHhRMDleAIHRzJ2e2O4/7b0Lr56Rf7hU6qf/eZr0+8NJuNa16GnPGI/lvoMV1uwrJbdAjTWEZHngimQ8Jpe0HtjwQtbH1Q3ZhwQbWzjGEW/YzvqxnQLQKUklj83Rbf4bGs+tNKEXtDVZDQuHKRdxBSmZFGuHGtgO6AYeD6RH7oi94TIl+eQ1NIet4a7xL6P73kYt0icJgm7aerSEp3kzcnPpAogZTcZ8/uH3+fB8D5N03C22bDf6/HNvQNSP0ArxaPJTX5v/7vcG92SAA2lmMRDdpMJN/sH7Ca7LKs1ZVPKwqcpCTyfQZQQeG9KBq8zjEVZEYYBD+4edl+/npSKkt437Ym5v9dPxP/gKcJwK0NvmoZsk/N6uWTsgnxer8+YF3N+cfZrTjYnnT9VK580SGnrVYyt6QV9duNd6sawLNf88uwDNvW6Y45DL6RqKlbVinW9RivNaXbGfrrPp7PPmJczTrJjTrJj/tsv/oTP5p93zHbZFB0IasdHC6BKU0pqKNukXaCT7imlmBUzHg4fsRPvMo2m/IM7f4+Ho0eEXshuvMcwHHX9i5WtyExG3dQUpnDsWcP7u7v88d3vME1GvFi/JPFjTjYnjhUeSv9dNOYwPST0QobBkHvD+0Q65un8FT8/fsa/ePLLr80/mYNv+uhre20O6oi6qTrGPjeFAw/C5F2vK9AuTGSb6qtpayqud6JeP09tH513jVn0HJvYyjmNYz095XWgsZVvCuth3GK6pmpqalszK+acbs4x7nuNO/Z2gR94PoOw76o0FD0/ZRqP+f6N9xnHA2LfxwKjKOL2aMK98Q53R0dMolF3/K00eV4uugoQay2P5885Xq2YxDH3xxM8pcjrmrvDGwyCPqEOsDQEnk/ix4wiYfUVik2VUZjSnWdDoH2GUYT/Fd+e+3CTRW9VEwU+t+7c6ABmbbYBOC2D4Xkega/p9xNZuGqPMAzeUABs1hlfXF1xa7BPPwy5yK7Y1Bs+uviCV+sTEj8hdAAudpJkOQ8isRyHIxpryaqKTy4fk5nczUEJiaqthOJkdY7vaWbFjGk85svFc+blnIv8gvP8gj958lO+XDzvmO26qaS/E9WFH0mIjXxmt9LpdgwpFKmfdr27q2rFzd4h43DEOBrxB0ff51b/iNALmURjen6KVh6FEVuEvKemszQY03BvMub3Du4zjPqcbi4IPfFkWiw9P6WxDf2gzzSaumubcNST13i1OuO356f89PXjr82/1uMnc5FORqo9SYxsg28EFNmO0WtVH9cf1+XfWim+KgdvX6lTgSDLznY79Y0gk69IT0Xuuu1w7I7fsXvGAbDaWi6zmpNVSdW034O8NtSNvGagPfqhZuSSsnuhZrcX8MPbA8aJT+TQcC/yOZwk3NpJub8Ts9sLutcujITRXGYVWSky3tw0fHiacbUu6ScBB2PZqCmrhluTmF7gdeck1J4Ex0Ueo9inQQJ5ylpAR22seEYjv6vAeCPAzTGMVVnh+z537oy782qMEeDYrUHFU+1pj7QX01wLadnOPymlf3W54c4kJgl9ZplhWTR8fJrz7KokDT18rfCVhN14uB5KayUh1iX/l6bh8/OcddmqNOiAY15Z8koA5iwzjBOfJ5cFV1nN5abiYlPx4y+ueHJZOKZQNgW66pVGyJd2I+F6MFL70J4iDTzyWr6+LAwHg4BhpBknmh/c7nNzFBJp8VMmrjM2rxrxibrnbf2NdW3YHSe8fTAgDT2uNrU7/hprcZJbSy+UcB9RR3jcHIUEnuJ0UfDsfMWnx8uvzb/rj7+eWWxZG9u8mUJqDDCQBX5/JOzMYCggoTGSfHl9orZ/D2MBAq2EFFxgjUs/pdkG1hSZBJjoa8DUmO3PtMcWOVDaspFFLs/V1ne0bN3iCrtcCsBsGaWqFLlsb7BlNPU1Vmqy45I1tTBcSUL92VO8NETduS19gcuFvPdXz8QfF4RuyyXEfvkFancXZpfYX/yM/Itj4ru7eIc3hG08P0fFMWo0gs1aZJfKo9v+unlX/lzMxP9WOxlh4BaSaYrXC9GbssOp1+sEU+2RJJqnX86dx4tOmtDurHpukgTOJxNpj6I0DFRI4HtUtdDy2lMSqKOUhAPN59irC+rPn2F+/Rnx/+4/F1DYNHJNq1J+dr2E/Zvw6W/g6orsyRnJ1PkYWx9q2hdw5f6ufu+RSE7nl+I5LQv5mSDEe3if5je/Rd84knHRgsFq4eTFfUgHW39qexyellCbq7POv0jSh0ffkHEJEmLTONl1fyS1GmUhv9/ry9ioS3nOk1eoe/cZ/m+OsEVO+W9/Svi991Df+I68zv7N7Rya7krq6tkrec+9sVzns1eYywXx3V3qefa16bcNnzEdu1FbQ22MJKU2NcNwxKJcMAgGsptsGvaSva/dKE1j8JWmahdVVhZ07UL1updpewNUbvEYkNdFl5UokthrAS3Ndicb53FsF7Ei1xQgkdUFlalQSpjJvC4kTdOFxVi30GlN4p5SBDqgchKpwPOY5TmR1l01xqYS0LGp8y5VNfJDRuGIz2dPeTS+S+D5/LOnf8ovT17y7u4ud4Y3GEcDjtfn7KQ+94e3MY3hWzvfYj85pjAFk3hC4AXULgGyMKVE+UeFK6u2DMKUXhiyzos3Nmra3dMkDgmjgCfPTzoQK3KhrawXhUswkxtuFPqY2t3EtEddm24zyBhXdu55nG0uuexf8fHFc3558iX/p+/9E8bhqGNVKxcos6pW7Cc3+Hj2MRf5jM8vL7jR23HXNcRiSX3LSXYCCJC7N7jHy/VLrvJLJxMtSPwEX/l8c/chf/HqNxw8EvmdaQx4sK5XNNbSC1J6QR/t+t7aag2lFJNwyqy86tiM1O/xaPRWt7ExDEfd2BoEQzKTdQvSRAuzK4vfmtfr1zwa3+P//IPbZHXGP/3iJ/yd2+/xvb1vMwrH7CX7bu407MY79IMBZ/kpvhcwDET6dpGfc7pZ8M7OLhfZ5mvz7/ocbMNtZLy3sipJkYy9mLzO6bnCdPkcjTpW8boErWWldWuJYCtlfsMuoDyRZzsJYOD5Au6wYNs93sbNi8D9vigP6m4ebWWaxjYsqxWrctOlDudusynWMYkf03Y/auV1vrR+IF5RT3mEOiT2Qz67XJMGAXeHe26DZUMaJJxsLhhGvY5ZDbTPJ4vX7CZjVtWanx1/yGeXl9wbjznqj+mHPc6zGVM/YhRLzUc/EH+f8uSz56gnio9ZMWdVZU52bzvGvx8mIlXXGqXe9EVba7s5+OrFWVcC3jQNjac6v6OwGyWByyKIwoCqrFE98QrLHLROSivndhz1mBdr5sWSTy+P+fnxM/633/qHEmaEbAC0XvBNLVU3z1bPmRdLnsxnTBN5n74LHEv9hMviSsa6H/Pt3fc4zc5YlCsSP6JyPkTf07w1PeQ3p0/YT3fkM8rKHDSmxjrGO3bXs7MEuBiqftDD0uApTWlKEh1zZ3D7jeCz1kuZBgIoKzfe29dvwelFdsXd0RH/62/vUtQl//b5J3z/8C7vTB4wCPuMo4lcBxqG4ZDUT7gqZvieJvV73WbRRZZxbzTugpOuP9p1tmnc2sXSsUGxFuYm8GRDsxd4hNcY4+t3wOvl9tfDbVpQaL/yunKtZdMCZdE4FvENQOTWUtdeqE1glfOI5B1buaddZTXz3GCsJdQe67Ihr6XyIfZ1d0xaKRrk/Q6dnFQBUSjs1uWyIAl9bk1jHu7EZJUUuL9aSFF7qIXh0p7iy4uCcSIbEb95ueJklrE/ipn2IwaR5nJTMUgCBpFmXTUMxITpzhnsOuZxUdSsSiOVGVZAZYMlCX2iQJPrN89L+4jiiDDyefFisbVcNBbrWbxr16pxHmFrLX7oU5Y1vV6I73vU9TYsrq0IGaUB803FKvd5ebHm47zizg8O6Yde52mtHBjdVA3jOOB0WbDIDSezjL4D4trJYZMALjbSExsHwv6dr2sWeU0SeFSNJQk8Aq24tZPy+cmKnZ7POPYxDeBZBx6lUiTy3+yJbs9p6kt6fOgrytoSa48746i7RyS+fKqLqsSjauSer5UiCSWwqA15ulhXHI1Cpt86oDKWD57PeXQ45K3diF7oMfG23Y2DSBP5HovcoJXUjQAscsMqr9gbxmyK7f3idz3+x6Whthe/TZRsAWNZSLKkMQIUQNJGv7JQBRwT85V48uuMYvtn+6suDAZPg3YAJAjd6+Zb8Hq947HM5XfixDGOgYC+bINtazjiWMzLZ6ew2aBu35Fjb+WqLfi47o0scuyHv6L57Av0IJZ6jNh5MD0lASwnJwL+3n4PqlIYN62xV1fUf/FzdD8i/r13Ufv7Ak7LAnt8jPrGt7CLGSpby3P6AZ0utK0NyTPss2eo4RCSBBUEWGOgafBHKeEyJy/M9jJ1cgjYbGoJsFHbwlmtPTxP4fuKomgIPel66fV8tLbMiopkXTEchDRZvY2DzlzA0WgEdY0KQvz3HsJHXwig7apJrDBxedbJUu3Ja1gsSO7vS0DOYAjzS/mddAATB+qyjTCM44l4/KJEAGCRwYsvUaMx+o/+CPvZx6i/8/e2vtirM5GpKrUNB2pZgczJiuOePFcygIvXAgajpGMJne7IjT1PwOHpSxlL/YFjIq9kTN66J2OlquDxZyhfw2Ag77n9/Wwlx1fOQWcyVl8+hZuI/Pb8BD0ZCEtsv3q7aq/lmwliInUQ9mJRLkj9lNoaYj+WsASru0XCdV+ApCc2ney0bEoBZd5WAte9TitnU9K7ZYzs4re+SJEbbqVPLZtSNTW+H+F7mk2ZufANSUdtPTECJBtW5YasLkj9mF6YdM/nKeUCDbYpsMY2zIolx6sVaRB07FppJNTBNoasqsioeH/3Hge9ff7y+OdEOuR4fcp/89m/YRhF/PHdd7nVP6Af9KmaiqeLV/zw4Dtc5ldc5Jf0gh63+3eoGgG8VVNRqZKTzQmfXT5jJxmR+DtoTwK5TNMwjiIWUdHVXrRgsT32PCt/B1Dc7qbWVU0YaIpSwjWM9pjP1wRhQJJEGNPguflX14ZIa7dTGhHpiO/deMQvTj5nXswZhkMCLxAGtynYVBtWThp5sjnlKl/y1s4ep5srfv9gwLycMQiGpH6PnXgHD49NvSEzGeNo7PxWEnxRNgVPl08ZRyP+8YM/4qPLT/nDm/8evgM/V8UlO/FOx2Rf98dlZiPj0Zf+tn7Q5yI/Z1OvCR1QbFktX/kEWhgdX/mcZicYKxJWYw2rcoVSituD25289nRzhvY8RuGAVbXmRnKAQrGu124xXZMb2Yx5sXrOzf4tKlNyvDlhJ5FaF/PVe9NX5mC7kdIeZ3NtzEe66hiUdkNH/Q7RTtVUWBr039RYRbu7H3Tz1UNjVVv63HTBO0D3mWDd8SgHLguXllo3tfStNgL6IrdJd55dkVU5R4N9Uj/pjlk2pho3XzWeVZSm5PHiFZ9dvqYfhuylAyJfGGTteVxkM043F1zmc96a3MVYwy9PP0QpCa36ty8+oh+G/PDoLnvphNSPqRvD69UZ7+2/zarcsK43+F4gfYXXVBBtefyT+TGTuEcaCGiRkKaGcRyzKkvKYqsi6Ta8lCLLio75kOAMH19rYRS1R1XWRGFAUVbESYjxFPPFhigO6fXiTiIHwgAB9MMeVSOfi9/cu8UHZy9Y1xv6QQ9f+R3zJvJLScA921wxLzbcH0+4zFake2mXEBr7MYOmLwyCYxf7QZ+e3yPSMtfLpuRkc8o4GvBHd/Z5PHvO7934Vgc4F+WCkZOSXv9MbxnOdhMj0hGxTpg1V+Jt1CE0VXfOtPJk7CHdp5fFFcYaUj/BWMWmWqOUx410TzZLdMST/CXa8xiEaWdhaN+L9nyMzbou4LPsnP1Ejukyv2KaJISefkPSef3Rft3a7dLIOFuNMQ2++3xMA1/Ynb/ieb761W5T4avzz61fA5d02ljVAUb5eUloNdcYTGHo5Z6AJ/JYK2ZYGmtZlobaAbjYgaSLTcW6aLg9Dkn6rXpgu6Evn4HyvnPT8NlZxpfnG9LIZ9oPiV3noVKSCHq8LDlfK97aiylry2fnOY2V13n2bEMcah4dDpmmmjSQkJqTRcHDg4S8aliXwrIl/lc6H61lXTY8v8wZJIHrFwTTSFVUP/bJCp+iMJTlmxvOqO098DoobOuiWl+iH/hUZUWSBBijWS/WZHFArxfSNLYjN0o3/8axdnJcxYP9Pl+crlgWDaOolaULq1gZOfZIGy7WNau84nCcsswremHKsjQMQk2kvS7lNa8ExPcjj17oEfoSQFkby/Gyoh9pfnBvzJPLgu/d9LsNinled+zlVz2qpZMfh1oR+Z7I+Jua0lhC3bl0nAWBbu2mleIqq2kspKGHwbIuGjwFB4MQ01gi3+PFvMR3vZClaZhomQuFkWq9umnQRry1F5ua3Z5P3QjLPUgCfO3xV0yb7vE3y1CV57yKDrDVrnexLETmWbi6hPaVrBWA0FwDmcoF3FSlgAFjtoimnf2eckE61ZZ9vC4RhW2AjbWySG8lsHUt/4exAMXcsTRNI7JNY1B7B9LZpxSqP0Dt7MLOjjBGSvEGNdf+3xh4+RT707/AfPQpTV6j+j3U+99CPXxHPJFpHxUnsLODuv8Q1kvs8SsBA1UFWYb/zbfx/u4foR69vWULD27BaIR9/lS6CuNk+57KXM5tK7XtD7Clk9w+fYpdrYRdjCL8QYw/TOj3AsLAEyVvlwq3HYSNtYRK0Yt951m0VJX8XNVYQr0FFgO3w+N5kDo56mCaUmclXF6ipi6Y5dlTsBZ/2pewmPa6ai3gEQQYF5n48qoaJhMYj52P0J3juhS5Z55Jt+H5sfN4ljIWLk6wH/zcdTf68lq+L8mlZSGy0HZjIEq2HtgW/PnBNsG0MdDUkm4aJdvgpbbqJIjc+HYbD3WF/cmPtwzjeHcreb26gCJH3blH+J/+L+DFC/naeinjKenLeLZWZK87B8I6umtslwvUN78NBwfC2n7l8YZXEYv2dLdA3tRrclNQNFKu3PkFbMNZdiY+wg6AecQ6pmoqClO4gJZr8lH3n7r2X/tcpSmpm5rK1KyrDO0WTaZpKE3VjZl2t79l+bqPEGuoG0kljVxS4CBMu39LN6PXASyJSBfpat0YFsWa082M18ul25HVDMLEFXJrAhf0cdif8sPD99hLppy7iP1NnXOezfjR0dv84wd/xPvTt7kzuINSiqPeEdN4xKdXj0n8mNRPWFdrSfRsSnKTUTq52ygakdc1xjZ8cPYZ82Ihx+8HjOKYYRSRpDG+YwzbdLfrRv8WKIZR0O2gtj7GsjKEge5upn23QFUKokgAw2CY0piGk/Wa1I/YVDmfXj7G2IadpM/S9ROKX0kkbACDsE9ucq7yBZWp2IlH7MSja0EhIlXrBwMyk3GRX3CWnXf+VN/zuSwu+NX5r8nrnMDzmRdzfE/zs9OfUTUlVVM5UFKR+Ana1UG0wNFzLOOyWtDQOL9fQuSCQay1xDom1CGhDp1PrqANRfnXL35MaYQpHYUidTSN4SK/IKsz7o/u8n/4zn/Ml/MXXOWXrKolngvTaAOgcpOzF+8ziSdUTh67rJb8/uF3uDs6fKPE+6tz8LqvV3yazmdm5L2XRt73NvymITcZEnzTdOdCzpHp5KrXNxa2UjiRg3vuvFlrneTWeQ3tVrZq3GdBG+JkbOOSZ8UbKD/fOMlwzTQe0w9SlFL0goRJPGQcDzvJZCf5uqYcaGzDyeaMX519wscXLyiNYRhGvDW5y+3BEZGOCD2ZCzvJmPujm2R1zuvVGVldUJqKdZnxzb1b/N1b3+Hh+DY3UlE+7CZTRtGA54tjAu13ybrtZ1QrsTe2IfET8rqmagyPZxLCE+qAyA8ZhCHDKCJOou0ctNt0xu5aNg1B4JMkoeuFa+dgQ1nVhIHfJTb2ewmtpyqOQzxPMRr2KMqKy2wu/mileDp/jbWWaZKwqbLueLXyWFfCVsd+TNmULIoVpTFM4z7TpN/Nk8Z9RqZBj9JUzMoFV8VMKjCsVGEsygWfXn3Bpspd1cwG39P89uJTF2ojyhHTmG0oFFufZ+ttXNdrx4g1JH5KoMOOpfW9oPu/UwUoUbD89PgD5yVX9IM+bT3LolxSNiW3Bjf4T97593i5PGVRLMnqDIXXbWI2VpJaR9GIYThw86diWW745u5DDvq7v3MOGuukim7trT1X2WC3NRp1I5LI64/r7Fb7UO7rdSMOSPs7frZx39ftktRKJcebz7O959XuM75NotcOKNatxLSxjpGT9NNBpPEU9EKPaeKz0/NJQq87vvYYrt8PXy9LfvFyzWcna2rTkEY+7+4n3J/GxL5ICiOt2EkD7k4ilkXDy3lJXhlq07ApDXf3enz/zpB706hLO93p+fTigNeLUthWJf65rDZsKkNWm05KmQae9DXWDU8uMpaFwdeK0Bcpahr7pGlA0N7H2rnXERdyX/QDn/ja/DNGvMV1XeMHPp4nzH/ci4WL8RRx7DtBW0RZGi42NdPUx9eKV/OSBqT2rdwGg2kPVq6qomUGF7mhMo0wqXGAw3idVDTxPSpjmeeGq43BU4rKyAbdIjd8cpaxqQyBp1iVhkArPj7NKJ2/U7tU1HaToX3fEvAnvsms3n62JoFHqLdy6Jb19pRyY8cBbAu/ebUir8SfPojkHJvuPVmOhgF//O4up8uSZWEoXG1JdK2/tDAN/UjTj0S+XdQCPB/upUx7AbX5qzdM4W9iFq0Vjr3xZPHbeRJdMmfsJIKjqSzQs/WWeVw7/etoumUUPe3YmNJ5DJWgGc9JUdv6BWu3SayRK333XYCJdczldQbJVMICJal8vfWslYWAmrNTOD+D4RA1GGKvLlG7N0TiGEZbBq+x2xAda+HJZ9iPPqLJBZT6OwPY3d1KaKtS3tP+IWowkmTVx4/ld8dj1N17Imec7DiWMthKJYsc9d0fyPO0FSBaCxC6PN9KOusaJjt433wfnj6Vn5nPBUh5HmrQJ9g3WNPQq9rYfkNZNs4fJbtfSaAJ3YeSZ0Ui0TSiofcVhIGH9hTTaUyW1dQuPUkqKZ206sbwzfCe9ZrNTz7hi08u+FYUofYPtwztaLK9xuuVpMSaX6PuP5AwlzKXc1fXUGdyngBu3NxWbiQ9CZ9Zr1DDMXa9hNNTAetxgn39SoCoUm7TYvwmS20bAZJVKdc2W0vgzHTPpey2gUslLC5hOBUA6UtjFkqJF3XoZMaTXZGUehr7m38n4+ntb8Dzx9jPPmHzs89JfV82D+69JWBRu67NupbXCUM5totTWC6xmw2s1+g//MOvTb+2R61j2NwiNXBewsSPyOucaW8Hay1XxQxPeeQm56I4R6GEZVGKxi1aK7e4BGH52pS7UIedJ1Ip531x07YFlnIMWwZQexJyktuC0tQMwtQtOqRDrmrkA1ckojWpHxPooJOOBt42ffW6BK99vU2Vc7JeULnX7AUBg1B6EcfxkFHUJ/RCduIpSiku8kt+efoxxhp2kwnvTh8xDIdMojFa+Z3UKvETClPwB4c/FM+QkvOplWZezjnNzhgEA6yradhJdviDm9/k44sv8T2f82xGYcS3OI56VH2DaZpOrlYqRV25Rbz70I6jAD/YykJkMSvpmdpT3Y1yNO6TZQVVWV+7WYYY05D2YkpjyGqZg/NyzZ89/5wvvnxF8ncj9m/vd4m2o3BE4PxT62rNt3bfxVrLO9MHLMqlkwDLYrQ2OQOXSnjQO6AyFcNwRKITXq5fsq43jMIh63rDy/kzvrv3TRI/5fnqZedXzOqM3XhPrqWTnWLF4yex/k0XNNPEBu3Oectyz8tZ95qhF4pEGo/dZI9pPOLl+hXTaMI0nqI9zV+++hnTZMR7k3d5unzGR5ef8WfPPkcrj0hHPBw9oueLJLLn9zq2ta25OMvOmRdLFsWaRbnif3r/6/MPBLx5eF0aRhtU4ruNkUAFDmz3qK2hMiVKxGcdk9ILtuE5kiBpME2NVXqbhuoWoCKlDhx7X2OVLOJN82aqrswZr9uFbp8j1CFtuI5sBMqcnucrLjYzhlGfXpAwK5ZM4m2tSeuftGzTsy2Wl6tjPrl8xsZ15k2ThGky6vzMjW0IdUgvSCnDkvP8ii+untNYyzgecGd4QOInjMIhWm0reFI/oTQl39x9281BAcdaeWzqzFXTSJVCYxsGQZ9v79/j2eIYrRTzYkllKrTyGEaxW9S+OQdBSrxNLWFYSRx2cxDHPhjTdDLwwM3B4ahPnpfd72mtCaMQYy27/R6FA+KNtayrnL94+YynT14T/y2fydGY0G2o9YK0kx0XpuCd6X2M/YK7oyPW1Ya6EUl+bQ1NU3b1LbvxDnVT0Qv6RDriLDtnU2UMwz6rasOL5THvTB845cR5t5FSNTXptbHWfq5Wpu4Ckkoj1RkjO0R7GuXyQFvPcj/oE+oQWRrWKBTjaMQw7HO6OWccDRmGQzzl8cH5J/TDHg9Gd3i9PuHT1VN+8uolWmkCHXCz57k6H/GfGpfQ256TeblgVa7ZVDnrasPfvf2tr82/xkKgFI0S0NimorbgsPWGRS7cx8qldXOi3Vz5CpBkywq2ktT2c3mbpupCYrxGQm6uKVCve9Cu+x0lxMQt9pUwjbX72atNzemqYhhreqHHLDMd4Am198bzbANyLC/mBZ+ebiicHWGQBOz2gy4ds2qEZRolPnHQcL6u+fIio2ksgyTgYBCQBh7DWLxqndwxEAbq/RuJbPRqcbNqD/LaMstq8dUpAcK9yOPBXsrxQpKBW5CilCIJfSb9SFL166Y7V1UlwA+XNhzEAibbq9DdA+sarTVBIONiPE7I87qTjWstgNFaGA8iChf6ApCVNR8+X/LkyRXh799hpzekneJ9J9tUSoJ93t6L+aiRUvqsku5CV0ZARUOs5brv9Hxq08qaFefrmk1lGMU+69LwelHy9l5C4CkuNnXnizSNJQy3rGy72dC477UJvlnT0AvBd9JdmaOGvJbX1F4r85WxPIw1Sehztq4pjHVBOPDhaUY/0tybRrxalJyeZ3z+aoH2RoTak6RYLecg9r3uGAP3urOsZl0askrCcb57Z/S1+Xf98deDRa/1D27knZfVdhe0rh2wazqPnjBijoGpym33YgsQs81WNmqtPLevtq/TetiKTJie60xVXbtOPce2teBRKQFfLftZGwcWwy3gjOOu886enrhgnEpYHq23LGcbhlOV2KeP4csvMcsMLw7w+u69XFxgz87kOcdjYRhBwNvr1zSrDfr3fyRgbzQVEKRbkJwLEPF9uFoJMPr0A+yHvxWG6fCWgJjeQJ4vjgWAfvk56pvfESmt5wlYbM9BWeIFGj1MSOqGIPBYrirCQBbctZHAGs9TlJURJqMUA3HTgGrlOQ34gRiEw0ACboyxhKFHOO1hK4OXhAKWjYEgoHx9hclLbh71tjUlYSVgyLj6kv4Aohj7+FPUrVtSkZH05H1engkgVF6XFsvpa/lenAgA3NkXAF0aYWDv3oPzE5HhbpzvdOLA3/PHck77I/ecPkQutKgqZeNhMZPnm+7JhkK+luveH8mYuJjLa/uhjKN0iPqjfwSzcxm/6xWcvIJ+X8bTn/0L2N1l8+e/xeQl6x9/SK92nqZH33DhS65DsfXR9kfQWNS9B+2KZcuGX5+cysdXmo3JukV1yyxUTe0Ajez+D8IhmzojqzcSWFHnjMIRFsuinHO8OemYRgF026TStgbgOrvYsRfWdOBR5HqmA3NS/lx3YTbtZ4OHh1Wy8Gy7Flu/1brK2FQiUU1cKE3rAWurODwU83LN+WZFXtdoz6MXymdDVtdk9ZxNJSzXu/vvoBDvS9sP9/fv/siFNYzpBwNhg2zdgQWtfNbVJQfpIZ/OPuEvX/+KHx1+m6PekWOkes5Tl3Ccn/Dx1ef88Mb3KE2F72nONleURnrrclMRaM3YdUH6vmazzqgq10tp5Gtae5RlLTfHqukYDE+5FLju5zS+r7tEVM9zwTdGvIqDMOzA8/H8iqyq2D+YugCKwi305LoVVckg6BPogOPFCXeHR0yiCT2/h+9pLvILV8jt4SGbDLPNHO0ClKqmYi/ZYzH/AoP0CT4a33fMdcO6zKiaikk0RSvN89VzDtIbDIJhJ2H2lEeik06atqyWLEup9TCNIbMy7vvBgLqpOatOu9oN5SkGwYB/cPvvMS9nXZriyeaUSTzEWss/e/qvOezv8d8//oC8qvmTJ59QNjXa83ln/A5aiT8KxKPbKEPfH2B5zqPR/c6bl9Vfn3+A20TwyE2BQnWbLeKBavC17th5X2kqwFhJY62tcWE/lsZK4mUL3trfUSrA5ZcKk+xqG+qmwncbRdfl51r5GFdRIuFTTrLqZH8gvYy+EtmqQTYyIj+gLiVB9zybUZmKQdhjFA7dwnq7q9x2cL5YHfNkfszC1dYM3By8yhecZzNSP2YSD7k7vOWYo4qXy1OWZcmPDt+lF6QipQzSTk7astCeG6+TeMrTxTN+e/4F395/i51YKlDSIJHKGx1xks14PHvBezsPu932ebESGajrcdVKMYxiqp6whzIHfTcHDb6v8TyPqqodm186n/DWH9002zkYhj5eHIoEPwyYuPCpJAjYTcYYK6D+s8szyqpmd3+C52lhez3xaUuwUO78vpqTzTk3B/sMQ6mV0J7PrJgT65g2fr9qKhblEu16MsumYhyNWFUbykYqhm4PD7nMZxgrqc1VUzOKRniq4HRzyjSedGNenkc2UOqmIvQq1vWGTZ0xCPs01lB0NUUpxjZcFVdEOpJNNM8j8RP+1uH3WVZLClOQm5yz7IIkkN7FH7/6ObvJmL98+Yyqqvnxi6ddIuvt/q1O2dKOLa2EKbbWcncklVGmaToQfv2hnbCtqtsNU+vyFxxI1O0mx5Y5bBMovxZ6hAAwUQrYDuDBFmCGSgL/ascQwRYkXgeMxn0GtP7EVorYeiN9TzaMjHEgwldUpfz9fFV3/rZxvA1xacFt3UiIybOrgqeXOZuiJtCyJgO4XNecLSuSUEDg7VFEQ8OmbHi9kIqNbx716YUCTGNfb6W77rg9oKzl9Z/OCr442/DOjR67PR/tSahO1VhiLbLFZzPDo924OwerQjoAtZKEV62EYawbi+97rNdyv2u99jL/RHJqXMBUew9sVQ2N+13ZuNHEsfSdRpFm0JPNmjjQ7A0CEYNpxeWqoK4bdnd78vwueKe9ToURf17gKZ4tK24MA0axFiDpwSwzhP02kVrYuquN9BfGgUdeNYwTzaYyFEZkrzdHEZdZTe26JitjGUYaD8vpumKaaGIn5fWUJL9qD6e+ajqval9r8aY2DY0VAN8gADh0dRlKKSLt8YPbPZaFVHXkVcPZuiYJ5ed/+mzJKA344vWCqjJ89GxGbUZ4Cg6HIVqpLum1bhqsVa6zseLmKBIBnbGdH/SvevzNnsWqFMbvetx7Kxe9PBPmxTZvSk3BpXq6ktXGOHlgy/uaa12JwTWpq2MOy2t9im3aaXHN/Oz7WybQU1sWqX00pgOn1hh5PpAEz9EINZ64kST9igIaMnj1DPvqldQ8rFaYRY4KPGxjIctRgS/BNFGEmkwkXGezFvCRpKj7D9C3b0tlgjEuSdMT8AtyvFdn2CefS9JpWQjLduMGdn4lMtndAwETTqqo9g7gxhHMrlDjKfbqAnV4hC0LWCxgMkHNZujUpfRFPkO1pqo0eWFI9bazpllZCmM6hjHLZJD6HoShh6llIPmBR78XsFpX3XE3mxKzygmqSo55NALXh3N+kTM6vZDB1HpD60r+7mkINWQZDGXnwp4dC/A7uOk2Ia6lmN5/S5jVKIGzY+yvfw7zOerb3xVJ6G8/EGB9dYH64R/INaxK+fnxVJjD2AH764FFbbiSf411jhKRptaVpJaCjIc2fRcklEZrka2CfO/OA5Tvw3qFzTLMh58SHY0pXs+oVwXZb5+QDIdSJ9Ky7qbePmddi/wZ4PZD2CzhxZe/c/q1cizfFXtrT9JDTVNzkp1ys3fUgbx+0GNRLrokzJ6TCxVNwZ3+bZblUpITves7mfYNaVubfkp3QzbuhqrfYDWMNSgrQR0eisSPaLD4SnbGjDEUdeUkrDKOFsWKyLEQ4vtougLrujGsTca8ELC7LkvWVSVJoUBlDIHW7KUDYj/i/ugWkY5cJcKSxE94Z/qAR5O7PBw+EPloOO5YL3lPlqviki/mj5lEY8qm4LK44s7wgKtixiAYsJfsdR1xucm5kexz1DviIr9gGk84zy+4N7pFYQqu8gX76YTzzYwiqGmShNgXyUxdG8qiknPt0hbbm2TLbpRFJRHXHviB37EiQeATRiHZJu9qAOS5JDky1JpRnHK8WmGt5fJiwcnmqltsthJS0xi0p/Gsx7rKuvCQk+yU0As57Im3r7JtgFDAvcFdWSx6EWfZGZ9cfcFlNudHh9+lbip+dvJrfnDwHWbFjL9z9CMncSyJdMwkGjMv58RaPve10p2Hsl18tqE6pSmIdMzKyWfbsRrrRDyhCEN5kh3j4XWsi6c87g7uoJUmMxmbOuenrz/m3mjEs8WcRVbws9fPmMYjduMdBsGwk2+3GyG1rbvnuzu4R1ZveLJ8+jvnH9DVlHQ+TMfiCBO9YBxud2R9L+i8wdZapwIQz0ikI9bVppN9t0xaFzJ1bWHbpltqJxH0nMTQsE1jbYu+WwnZV+s9aitdf3Ujc1EpxVW+ZBCm7KRjPKU6EN9Kzs+yS16tZDNgnku3Yttbl7mxJxLskJ14RKADcpOzLFckfsz90U1uD2rpGrQNPV9kr61n2VrLrJjzcnXMMOrRNyXLcs1Bf4dZLrUvk2hML0g7qe9OMmY3mbCqVozjAVf5gpv9fQr3uzvJiKt8QWkMNknY+LIAr6qaqqzw3MZDG25jTN3NQQGPDb72r81B8H1NFIfkmbDDjYV1UeJ7HmVTsyo3DMNed+5nV0uOVwvYxwH5VoIvMlKtQ7K6oB8KcL7MJehlN9npNgdk/Pgc9Q5ZlAtCHXJZXPHhxTFX+ZLv7L9F1dR8eP4F39x7xCxf8r3997vQp8j1wK6rDZGO3Oe758KmhKHWnu7GVNmUbkyuumsFEOkIT20ZklkxQ6FIHODTyuOodwPd98lNTlYXfHD2gqPBgOPVik1R8sHZCYOwxyAc0A96bvxu+/ZqV9sCcJDeYFNnnGxOf+f8q13qJDghmoKqsegGqsLQj7R7r9tgG9X+my2A++rjetANbKWucnwWz9rOD6lQzkePOwfbwJv2Na4/WhZHeu6EUVIKLjc1o9hn6PrtCiP9io0V0PV6WfFiXkr6Z16xKaSTr8FSlIbA9/BDRRpKSmnoKzZVwyI3JKHH7bHITA+HogZrg3OqZuslXFWGF/OSUaypmoZ1adgbRMzzmthXTNOAxBdgUTWWnTRgJw1Yl1L3MMtqDgZSYr8uG0ZpwCKriIxmgKS5KqWoa01RGDynwlAKdw+EMJT5V+Rbr2wQeF0NhO8S+bOs7q5tWRrWWkDaPJek0vbazWY5F8sC6NNg8azqxo1ABEVeN/TCAKUEJColLKJW6lrKruJwFLDIpZtyVTZ8dp6z2FS8fUOC7T47XfP2jR6L2vCtwx6Vk0OHWtEPJbgouIaXWpedSEw1OhLWsDbyO+tKKn16bl1+HSgCLF1qaxqIvFUpOBwG+F7IpmzISsPTsxXjfsR8XZLnFU/PVqSR320YiAx2OweMFba4sXT1GqfLbd3R73r8zWmottmCvPZhnU/w8PY2jVSpbS0GCPgyLVhwP5OksriPk+3CuWUElevdyzbbIB2Qs1zXIt9rw3ZaJkrZrb+wBYxNI0BgvRIAFyVYTiWQ5caBsIbzmfQXtszn6WvsZ5/QnF3QFLXw0krhj1MBRW3C53gshxzHAjSSVNilqkTdfSigJXTSVuVtz1sQyd9ffIl9/CnkOdx9CK+eoW7fw758hnr03hbkVqWTprrqjmwtUlalBKSUhYDIMMKuJOHVK0rMMseLA4KdPt4iJ0wsSnvY2lCVRopNxxGLZclsUXa7Y4ArKlb0egFhHKACze7RmPJ0gQo0Xhrij3vOsyrnOdwbcvXpKS8XOZNfvWDvO8/lffi+HPtw3G0AqD0X7FNXAnJ3dl14UQBeLWEw2UZY4htHcq2TFM7O4Ej+bS8vaBYrvJfPIXHnv662jHBvIMeWb+T6FBnEblx4GvxIvmebbSfnzoGc9xdfildyNBWGVzv/Yq8vYzkIhQVdXG3Z32wDsxl6OqQ+m0vXoqdYvFrg/bvfEqUp6sHbIndt03pbifWNIwGu8wsZLw/e/fr0s8YBMP8rX5fEw/vDeyRuYa5QJH5KpCNyk7luK0kb3Ymk7FgAUkkbUCNeCwmTkR3obTfjdfCYVXnXgdQuhI1pCN2YadlEYw2Vqcnroluc9sIEVSlKI51vwnoWhNrvFiTGNpxuZiyLQnrzkJtaLwjohVI3EGufnXRMpEP20x1SPyH1e0g3X8n94T1KVyweeCGx64FsbOOSKRUv1i/4ZPYpmyrn/vAez1cvuD+8x5PFU96dvCPH77oHW/ZD/Iq5Y8+8LsnzRnqDSEfMiwVVU5PVBTPHwOymKfOiII5kV69yElXP8xiOemzWOcuF+E/aG4JScmNJ0pgoDCirmr2dEYu1bDR52nMsltyYNlVBPwx5fnHFydkVf/n0OT88eMU7k7fx3AKxH/XdtTbcSPfoBz2qpuIqn7OXCBuoPU1tajIjrF3P77Gf3sA0Evf/YnnCo/FtTFNznl0yK9Y8W76gFySShuoK6aumpOeSM3OTEeqI0pTdNQhUgNY+mRHg7jsJ8268h7GGl+uXnGyOGUcTDtMDtOcTqYhUpxRNgXZx+7NiTqgDhsFIGI7NFTd6I16tZixzkUi9vpjxr73fMghT3ho/kvepdBeaVDYl++kNQi9kVl4ReiEPRw9/5y2wPX9dv2Lbdei+vhvvdrJRYVM1dePCGGx1TbYq98VQB52U/HoIjqVBoWm7JhtrUCpwY0NhXHdkY8WXIzUa18KvWikrbUWN+D5jHRG49OzSVOwmE+qmZlGsGUcDQqfmmRVzvpg952yzJK/rzj82TRJGUYppGkLtM45l0yzWIbEfdemvdWOYRBOqpuoqXMJrm1Ktn/l4c8nTxUuKuuJm/4Cz/JzD/j7H6zPuOYZSEp8r1yOoOsnqIBh0CoSqqdlJJkQ6ZFmuKU1FXtfMi4JQa6ZpwrIsMVGA9jxqY7ZzcNhjvc5YLDYYY7rwmrZCI04iokikfgfDAWfrjUsjDJgmSVc5Ym3Dbpry+OSck7MrPhwe8/2DM+4Nb+O5kKdekDq2y7KXTuj5KbWtWRQrJvGwqzkxSBiMXLOYnVi6CmMdc7qecTTYobGWq3zBvCh4tTpzvu/IeQIbaGoSP8XWa0pTOg9oJeyb+4xX+BS22G5koBg7z/tJdspFdsUoGrATT0U2TECkI+dfDoiwrKoVWmmSMOn80NMk4WyzYVOIJPb0csFP1BPSIObO4GbH0IsSxlI1FdN4gu8FLKslvhdwq3/0O+bflhN4I+YCi2kUk8TvWMR2LdMyhq0s9auy0Xbh/sbruOe1iLSzC7+xjqW8Nr9aZtO79twtY9dW0dSNlNanTsoo1RmW3dSntlKXMPYkHMUCl1nFp2c5V6uSojZdINMwDRkmPnUDgVaMY6lK87UicsErrWdymggbGHhbsNGC5hb0nq1rnl0VFMZyaxRythbgd7qquDMJZWnvQGIr9U0Dj8I0XQBM683b6flEfsOqNFTGp6wa1kVN4Hv004C89ISh91ySdy1hbcNhzHpdslxkNEZC9lBtqAukqU8YSrbGzjhhviokGCjyGaWh84nKOZ/2I569WjA7n/P0ZcTpzSH3JhHaA69RRIHqPq930oAklCCXeWEYu17DdpOgMMLcpYHPTupLqEzgMduU7PRl82WWG7LScLysiH0n72yMG5vW9Vk2ojJyaybPbQZo5ZhYdzy+I3KGkWzenK0rCZyJNDupMLyBJ+OnbuTnQ1QXcJMGHhuQsJ44YLERoKiU4vIy41NX0XFzFKI9XCepMMyBlbmjPcXa+S9vjbfrv9/1+JuZRU+DMl0CqrUW1YKnwagLG+k6Ao1x3YlKFtl+KAt4zxO54NWZC6px/YmtHDXfbJ9rMRNP186+BIrIO2xnu5Ob1lt/XMtCblaOyXP9epMdsFY8ZG1RetNIOEzLIJ2+7gJYzDJHhXLhgnEqoTX3Hmwlta0U1jYid0wHUBXCCI53Hah0TGkbW6486ZysRZKpbt/DnrzC/uYXqFt3YLMWQBFFLhCl3p6/IhPWLc+hH2yrSUwqXwtDkWIag9rbxa+NyEWjAJ1GNJnEWzVFxezZTNhDY1kuq+4DtR/7xLEmjDTj3R7WNAQ3hni+pp5v8IeJLIImPXQSSAhPEAjgSxKurgpiz2O+KNnbuPj51oPZyj2NhTsPBGy1DJpS207OytWWTHcdi+3Y4stzCSEC7JdfgO+jv/89sA32+Bj7J/9fuUbf+5GAujKTc+KpLfvcVp9YK9uM6RDOX8mmxd7RdswORpCk2I9/g6pKOe4yl9/tj6Ax2J/9OerO/a109uVTAfA/+gOCssT/4lO4uCCebVCRL+MiSuR8rOZyPrINPHpPklnLXLoqX79ADYbwx29OvbZk2yAL8k7+6QloGQYjFtUc7flsS9Fr2mCKWTkjcR1XSilu9W9zWVxJOum19DvcWMjromMqNk0mfY0ugKRwvpjAvZaH6mQkAjo8Mal7mqIqyeqCcdxH4eFf65srTOU0+fI7ppGY9ryuWRQFSRBQ1TVpEJAGAdO4zyQe4ns+k3jITjwF4DA9pB8MyE3OIBwwDoUZbmP725oD8WX61M5Xdn94j9fr1/z09BfcH95lWa54e/xWlxDYBsS0PqPSSGn9IBwQ6YhB2KdnU/I6J/QCVtWGytQc9HcojQQCVL7PIIpYlSWB1uR1zfPTC4LApzENq+WmY4WSJCSOQ8IwYDLq01jL3dGIeVFwkWWEYUDTWMLQJ/H9bnHSMozz2Yo4DFgu1ixLYRpDPyIzGctyyU68Q21r7g7uEOuE56tn7nqL5NdXAbWq8ZRmJ94RltHIJsF5dsFRf48Gy2ezJ/ie5u/e+j1MU/NydcI/ffIn7KUTfv/GD0n8lMLk29oEFYCHAD0H1DQSOnOWnVKYgv3kxlZGHfRJhvf47eWH1E3FNJ5SNSWe0vScjPsvjn/Cg9F98YJ5muerFwD83Zu/T9VUfDD9hNP1BRfZhlBrSZnUMYEXsKpWLMoF63rD2+O3OxA6L+a8WL9kFA55b/ydr93+2mTgVsLdNI2bl56TuCZs6gzP1x30a7CuzU6Yu8RLHBiU978s3+yzaoFm5ZIzfU+zqTPm5YJROGQQDrBKY9qORxQ1plugbuew7jykrVx8HInUUMKkXDCClR7INm11VswdS5cxL4oucXcnSZjGfe6OjjBNQ+xHbszIfJ7GExI/6QJ+BmG/k7hL59/W3+x5HnVj6Pk9bvUPOMsu+ejyc8cQFtweSOdepKNOcaBQlFb6GsumItbSVdn4DbFtKJuKQPtsakl63kuHFG6NUhhDLwhEnaAUhTG8Wlzh+xpjDOtVRhtgk6YRURQShj6jUR/TNNzo9Zw3smAYS7S99Ln61I3B9zSLYk0vCJnPV8RhyGqVsaly8XE6b+y62jCORtim4SDd7zyIcgsU/2rq+3hKkmqH4UCus/N5zYsFe+kQD8Xj2QsCT/ODg7dosByvzvk3L37CNBnxjZ13JEjHlPieXFftScxi3VSy0YCEdcQ6YVZcUTU1k2gsY9Y29PwecT/is6snrpZp2P2u3EcMvzn7iNvDQ+JAqmGO12cA/OjwG9RNzReT55xvlrJxpjW9ICHUAb7y2dQZ63pNYUpu9292IHRdbTjdXNALk6/Nvy791M0T44ACjq0JtXjvtGoFoV+Zv9e0owqpVLjubZQ1fluL0ojU0JMC9HlRM44Dei6jogWKLQBtfY/tQ/EmeLRW5Jx1Y50Usk3kbQi0Ig7kXnuxqchrAVrrosbXAsbGvYBJGnBvGlEZSxqKLLJVLYwSn1hLWEkSeiS+JuaaZ9Pa7rhaIJsGHoejkKtNzSdnOTf6AaVpus69sOsstXhAhYDevLakgSL2BYCAFNn7WpGV4vud9EMnc5RAtzjQ5JV48mtjeX2yIgg0xjSsV7JhoTzlNmdE+j0exxjTMOyFBNpjU9SksWwaxZEmdN2agVbMc0McaJbLgiAKWK9LNpUA3RbQtjJS08DBICDU4jNsH6aRz3KlJCl0GGvHwsqVXeSGQRzgKXh6leN7incO5X50tqz48ycLhonPezcSQve52QL11ndoHPBvnzXSHouipjINw0h346kXeYR+wBcXBZWxjBNNpG3XKWoay2+PM46GIf1IrsHZusJD8Y2bferG8uxKWNCsFPtOGnhEvmwebCphkSUQJ5SE16YhqxqeXdUds/lXPf6GDG/H6rnUUWtFymUBFcayYE4c26QDWQhnawE1Wm9Bg+e5VNNKQFdZbv2JIAvp2eV2Yd8CroHzkZnqzQqP68mlynN+uXz7vf5AvucHkk45GGFPX8N8JkCnZUafP5Zk0aqiyQqsEcTutvmhKASkGCOg5Oi2MF91tZU6blZbxuzsNRzeAd8xZsrbSnaLDJ58Bo/eF8/dy1fCdE535TnDSNi1uAerxbbMPgi3Ca+XcpMhCAQUrd35GgzA9/EepvD6tZzvO3dgNpMPrlfH5J9eQAymtkShR6KlQiPwpYsxijReL0Rpj/DRbfA8qp9/IimdxhKNXXhQFKGGI2xRQNPQ6wVcZRV7u7EL5KnkWK2VsTG/lEqL9pFt5JjDcJtSCo5ldKAuHcrX40RA3/m5fKA/fIidz+DVK7hzB/X9H0HTYH/9M5EWP3p/K4XONwK+20dVyHNHCUz35VzP3PmMYjnPF6eonV2RBG9W8P73ZJwUmbC5b70rXZe/+Anq7felt9P3sa+eC1Nd1xSvrrCVobhYMXp/jlpcycbCco49OxFW+uVTAaN7N+HmPfjVz7fdmdcekrxYu8h9YTU854VJfJHrxToWf5PyWVYL1tWmC8CJddwxhOtqRdVUHKQ3uCpmXZKp72kKI+BOgJ9H5IdopYndwg1aL4hF42GQa9b6faC9eTb4ShYIjQORhSm71xCfocY0Df0woKirLvxmU1Xywepuwp6T+cyKNesqYxj1eXvygHE0pnY76ACbet11wZ1lpxz1bhJ4AYEK3XE3GFuTmYwv5l/w9vhtTjenfDl7xc3+ITvxlNRPCbyQrN6Q+Cmz6oqqqRiEAwIvkCRGk3ORXzjALImBwkAKiA20zyjs82TxGq083p7e5WxzhbWWp4sTPnv2migKZKEQ+kSeeDO09ojjiDCS8B7teby3K7UQ//3jj7BWisX7aYxFfDTf2X/A2eaSZbkhjkOWyw2T6VACPmxNeS1YZVEumMY7HdhpwUioA3zPp0GqIFr2TRjdvgsuCfA9zevVGY21fGvvbS7yS57MXvH29C5/6/AHWGv52dkv2I2nPBg9JNIxVVOyMRv6fr+TRkrYS8ua7LKu11yVl4D47XzP52xzxk485aqYsa43vD95X5g2K6D93ck7NNbwk5Of8f70Ha6KGaHn83z1QkBxU/NsMacyhuPFkh8cLpiXcw7SQ5bVkpPslETHvHQ/fyM54Fb/Nn9x/HOC0dfnH0BbdF43Blfo0s2HUId4LlDHNDVae12Sp8xBLWEeDkZKQmrjwqRMJ8Fuz8+qWjvZonZJvwFp0JNgkHYTqJOaenANMIqPueqOOdZx52tcVSt6QcpFdsW8WolX2f13sjljXUp/YV5LFQV6C3xzU/F0/sqF24w46O2RaAkraaWO0sMpnZtXxYzdZEf81l6b9inpxoUpeLl6xZ3BLS7zOS8W5+ylEybRmETHBDokMzmJjllWmWO3U3w0oWPJFuUCoNu0amWegzDF93zemaa8XJ0xBO6Pj7jKBZi/XF7y5YsTokh8iGEYEHnKzUFNHIcEoU8vkIXpw8kugaf5d6+fUbm0w3Ec4ylF5IeMo0G3eZckEcvlhvFk0Kk2JMlV5NetVLn9rMzrAs/zuvnVpuZ6LsFUYUn9hAZL5Id4SnOezWis5cH4Flf5gperC+6NDvj23rtYLB9efsokHnKnf6vr5CwoOkk4iJfWWNlQaxUTy0rOj6Sgaq6yK6bJiFmxZFPnPBzdE6+pS/69P5ZO2g/OP+Xh+A6rck3gaY7X50ziIaZpeL0SP+nTVcY39jYMww3TeMKm3nCRzYh9AczDcMAkmrKX7PHrs0+45R18bf61/sHKWKc4wY0pYdoUuEWvBPW1FRZ4W3lpC+hKI7Mn8N70M1qgNIZ1abrFvq+FcUq07oDhm58LXz1O1YXZKKUItOc+W2FVGoaR5vWyIq8kRdQ6/uP1smBdCEgtq8aBTdXVleV1w5PLQjZv0oBJKh7UBvFrgjChsfYwVvoQx7GPx5vhO8LmWl4tSm6PQxZ5zekiZ5qIVDEJPHylKI0h1JrCefGSwMPTikgL8zbLZI3saznGqpZqhn6kCbSit5tyshD10t1pwiwXYHa6KHj6fAZI8JbcAwO0W4fGsU8YaqJAQ6A5mqQEvsfnrxfCdBoJ91FK2NQk8NhU8rpJErBawHgsCkbTWKpGUnMDrbjMDKNId+mned3gIeNHe7LOsNZJiwGrrPP0idfU1x7zTUVj4cYkZpEbLlYFB8OYOxNZh3x8mjOKNHenUcckS5/t9jPeXJO69kNfxlzVuM8zAXSz0jBNfFaFBM883IkcTybX794komosH51k3N+JWZcC2E9WFeNYi9NtVVA3lvW65P5ej2GpGSearGqYZYY4EMDcjzzGccBOCh+fbNDe/z/MYus/bL2DVSVMinLMTfvnYiU/2zInLeBrmb8yF0AYhLJYj9qkykaA1Mun8vzjqchHlSf/zjYCPpS3fT2ZjdvQmDAS8Nm44BtttwxfVWI3K2EWr67kd9IUNd2TxXtVoQYD7NUVtjboNETfOYKrK+pFhq+1hNj0euLNPLwjgShpX0DJ1ZkAo7QvoCgIYXkFo10HaEUaIkE9W1Ckxjuwt4vNNqizk62vTXlynvxA2NU2GTZKtgDLGAHArmxeTSbyMzv7AmQ2LkTI1XYQx9jGcvtbB9SXa1bznDQVyUBRGLSvSAcR+bokAqJvPhRgrDXR0SnFqytUqFCBRo1H8nyXFyIDff6cXs/ntpcy+qNvybHkmVyHtmexP4CzY5cC6j68bxxgV0tUlAjbnA7lOi/nAqjf/baA5tEEdeMIXjyRa1nX0jc5Gsn1bBqY7KK+6zye7UZFG7YURBA5UN+4tF1TiRy15/ogi0yul6lEGnp5BleX2LpGPf5YNgL67vhuPYTTl6g//IdyHRuDPX2N8n3sF59DkhDdkURIL75w9SaxvK8oEQ/jZAd2D2X8NAayFep7P9jeBa892vj7Nqm0tBWNatDobuc98ELm5YzCFJxl513lQLtgtNZS2YpFtSD0QvbiPbTyOc8uEBufdYtF0/UdtomnrVerXRS1i79YR2Q27264xhpqY7oEVZGKyYfkqswYhCnLUljnUAWkQUxRV65oOmDjuhtj32cnSciqqmMEEl969765+zZ3B/coTI7nC0g+z8/Em+n3mZczfM9nUc4ZRxOpoFbCMLZSQBAAvhNPOejvkNc5Z9k5k2giyYCNYlUt0Z7mqph1i+FQh6QqJXCR8hf5hfTZodhJhNHci3epGomCvw6O2xCfbz24zcVmw3y5IU4i6qqmKCp8X9PvJ2ycN+qHhw/YT6cEXsBb0xMeX111N/3ED0gC8QAa23CZZURxyI0bU/7RI6kNyescqy2bOkOrgl7Q4yI/d8C9wDQ1h70brKo1SblkHE4YBAPpg7OGLxaPeW/yLpGO2Yl3OOod8Wz53NU3NHx6+ZTdZMzZ5opHI8M4mvCD/e+7WpacSMf4XkBlSmpdd8EWbbhJ3dQEXiDhTK7WYRJNqZuag/SAWTHnqphRVRVfLD5nGA7p+T1qW3Onf4fT/IS/f+uP8ZXvGMlTAi/gk6svSIOYB2PxgIW+38n0FuWc0AuZRGN24h32kxtEnrBkm3rN3z78QQdqv3YLdAAs0MIoVbbupNdt9UEbLtTYhk2dUTal8yLipHeSqpvVGVr5Iov2lJSpu3l/ll1grGEQ9CUJ1orktK3NUHidPxigcVI6Y4WxrBuRIjZOFmxtg+8Jo76pcyIdcZUv0MojDWJG0cAlckqK8axYUjk27vZwyqxYM8tzAs9jEg/oByk7yYS9eFcqFZBNk3m5oDAFkR6yckB0U23oBX1ayCkL+G2NiMi7+8IE1hWX9or+oNe9v3W9RiuPlcmvyXdDInfOpYZlSdXUeHhd2NE0HlNbw6bORV3QSHJw4kc01vLevZtcZBnrVUYcR9R1TVnW+L4m7cXkuXzefnv/iN10jO/53BzMeLUUQBV4HuM4JfZDrnKpz3m2OCHtJdy4ofjjBw+ZxEOqRuTHZVNRujqZWTnv0pgbGvbTKatS+hcHwcCFy9Rs6prny9c8HN0VJUMw4Lv7U443p12q6dPFGeM45SpfcHdoGYYDvr37Xiehj3SEdj2UoWe2r2tlzHlOPZG4XtBW4mtszW68w7xccJUvqBvDi9UrJ/lPqK3hIL3BZX7Fjw6+h3ay6CSICTyfx7MXIjsdiYf3pV7gu00P2cQMmMRDBsGAaTxBK582Nfi7++/9zjlYudCNwLFtLSckc2sL2Ron82yBnVTPbMGSsM0CbDyraDvkW5bxbC3+8WGsKY11gSRSm9ECyOuvB1tmsvUvtkE71gFWsSAIu5UEHjPXWd2LJJhmWTRURhilKpPKjjjQHE4SVzhfobXHxFVuSDCL7+7PwlxltaE0whiuq9qlmRoSf9vbeP24WlA0iDTjVMLSZhn0XR2DUoq8Fj9fXjddcmaoFbHy8D15b8tCvJieUh1zN0lFIrsum85XmpWNk35aHt6bsMoqlsuSOPapKkNZGrT26PVCskw+ax8eDJikPoGnuBpGXCwKcblpj1EaEAeKq01NGmheXG3o9QK4MeJ7b+11gCkr5bpVlbC661IYTu2kmDs9X7yF2tAPQ2JfOZDZ8HxW8GAaE/keg0jzrUOf02UggL62nM5zerHPsqiBiGGs+caNBGMtpRHg3l577dGNNdXJlFtWXANy/ZJANiV2Up+rrGaWyXh+OZcgozQQZnGvFzDLa35wuy/bhY3lwvVePp8VxIFmfyTHcqk9Aq0ItLCKoVYMYy3XPhZll7WW0ljeO+h1YPavevz1vGPL9LhuRRWGqMCBwN5gGxSSZwJujNl6FNsqjbqUlErYSkWrcgsqQNi1ViJ6eEuSRkdj+Xfad2mnnoCo9v+W/bPuzFu7BayNgbQHYYTa2ZfXDAIBT+s19vULATzGYBeLrsdRDxIJsPF9/Jv7cPcu6sahdCNO9wSYjve3NQ91JccWpwIoqhL721/Cr/9SQKWpXC2I64F8+K6cu6PbErQTRgIelnN5vqS/lfMOxyLFXS3FJ7dayDlr31+cdP5Qm2Xy2q9fCCibTgVMFZJMq3cnREcT9DBmfH+nA4q91GfQD/BCt6tzNOkkprYs8W7fJLm3h+4L4KTvmLqXL/9/pP3XkyRbnt+JfY4f1x4qI1Jn6aqrRcvpaUyDmAEws4sFjDDYUhkNLyT/Chr/EJrxjWbkmpEPa+QaQQLYJbAD7CxmBphWt/tqUbpShw7Xgg+/4x5Z9zYaD/RrZZk3MzLCw92Px/mer+rSZaNbOzJYQc57vJHjGa+39SmuC2cvJXBouYA8l/cO8PUnArrrCnYPaWYz+OK3EC+Fmbw4leN/cAzPn6N2diienlK9OpfnTxP52/GB/PMjAYl+JMe9KuT32tnWlxSpJPyGPWG60812AcJ0OSrXlXPu+fK49m/7Q7nmgwj2j6RbsWlgvQbXRX3wPQhD5t9cmUWMWs6dbYtPdWdv2+1YFrKffiDH69vDz9rGmjc0XTehVDaMOn/YNJ1xFp9RmYmsY2SfZ8k5aZXyzeLrbnK3LtesilU30RXmb1vpEDmBWRmVnzmWI15Dms4Ll1eF8X5tDdESulOzLuKuGqNd8RdGTFNU0kmXVTnrfEPdNORV2fkg+67bpUHu+D6TICSwPSb+kOPoSMIv3DF9p298myWhHRLYAT2nT9VU/Pr6I35x+QviSibCtrINSCl4Y/QGltIcR8fsBju42mXs7XSywNCOJOCnadjxRlwml6yKlcgXiw1pmTLPFoZVcTvwnBiA8GL9Cs922A8nXGymMmlVisNohzuDIQPP48HBLkVekGUFQeARRgG+ST+9NxrhaJt5tiStUt6Z3Oa43yd0HRpg5PuUdc2/fvIJ55slDbA77OH5krjpakkbTauUi/iCbxZPWOYrirro0nBn2YJ1sem8Tt8sv2aaClAZexOukxlfzL8kLRMCHXARX3C7d4tbvRO+mj3jIJzw2fUrvpmfsi7WZJXI7ibeLhNvF1/7eJaHbwcdK94m5rYMYl6LtDe0IwIdEJcxlhJp8qZY41jik9r1dw2zG3Zsbs/uk1fCmByGR3yzeE7dVEyTBaEd8NPj79NzAr4+uySrcgMs5DnvDx4w9iZ4lmd8lgW+DgjsgHXx3fEH28CnohJmz9E2rvFb+trvgmSKWlImJbjGEikglgHoFefJhRlPNmmVUJqQqrbTcOD2paIDGHuyWBA528CRduHCMoE47WIR0E2yZV8q4jKmpsG1pLdyxxsSl0kn2YyLlIv4mlm6pKprVnncLQj1PY/IDdBKcas/4s7gkP1wzEG4x8gd4moBN20dSN1U+LaPq+U8lXXFF/Nv+Hz+hbz3pjasS0VVV9zqn2ApzV6wy8jv42qbgdt/rZOw9TL3nB7LfElSJqyLNWmZkte5vL+m+dYYzCjqkvPNFbalmQRDruI5aSkAcD/sc9zv03ddbu/uUBQCFH3fJQg9XJNCfNLv42qHVR6TlTl3h3vcG43ouTLG2nqgZ8szNoXsx9GwTxD61DQS+GN6ZjMjK27vvVfJNVmVsckTsjLHNbzFjDIAAQAASURBVPfY5+sXLPI5VVMz8kZM0wWPl89IqhRXO0zTGQfBHnvBmBercyZBj6eLGS9Xc5Iy6XpzB+6AoTvCtdxuDJVmYUnOg36Nkc3rXMar9jr5cptSK+oDm6E7wLEcU4GhsZUtwLEu8LTH2N/h1eoCKZ6Xa+zDvUeEjsezy6mMGxqSUhKwj8JDBqZGBeh6IV3tEhffTSRuJ/cCBDFVEwLcPNvq4OVNCahtmcoE87umabiK5bOq9ZDDFiiCyA9b79o4cLAti8hM4H1t4ZruPMv4zto+PG68bgOdV1Hk2FKlMQmFKbLNpH2T1ZwtC+ZJSVXDJqu7ibqEkkgq/f4w4N7Y57DvcNx36bkCoELHxjNpm6JwUNiWwtfSE/jlVcpX1ylFVXd2h8rUO9zZkdTk3chh4GscS4BrYhguT1sdq9n3NIu0Is4lyCYpBNzGpqLNNyAFBFhWNZyvCxxLMfJtZnFJXoqfbxC4TPo+vmtztB9RFBVFUeH7NlEkDKNtW0wGHo5WbHKRkx4OfI52AnxHU9PQN2FGp8uc2HRT7+6ERJEjcyTbIi1rXFt8go3xHQauxfWmJC3kfeRlm5qqeDbPWGYlDTDwZL+/maYkZYVrK643JXs9m73I4XKV0QscLhYpV8uMtKy7nsXIsem7dld94eptnYvYvtrrZptM23oSq7o2cmHISpHROgbcOZbIf1smNHAsaTnQFqNAc76UheYkL7EteLQfEriai6sNmRk3SSELJYd9Oe9tX3bdyDFzLEVa3AgJ/R3b72cWy3ILyrAkyEVrqZzwTYBIKz+tii07Vpu00xYM7h4K4Gk7Db1AJtHJRibdnvHibVbybzCSdErX2yakwhYcggClPJMJd1EIk1Q3W/YSTNXBSqSLaSoAx3EEDOzuSbqmeZ/6wV2Kj7/CLp6gDvZRd+7JfkSmlsPSAvwALl7K6/TFy8bnH4EfCMt0ckdA3vU5nDzYBv9Y2hwvW1jIshSfolJGblu+HoTi+cIWXpyCMiAtCDu2t5leicy0LKWvz3G2tSRnZ9DvUzw7o/j0JfYwwL13iHc0In16RW0qMcR43BDtD9DrFPXwgYAex9mCJ9umTnKcSW/bdzkeQ55TJTnKUjieOS51RbNeiv9uMBI2tshFYuz5woSOJyZsRs4Dg5EcF9sG10cdHsk5Xa9g/4Tmy49RD96WXsrv/QCUhaM1WBbNqxeoNBHQ5q7FH9uG17Ssdl1t87dtb+uXNSE9uIGkka4XctwPTlBhTwBu1N8ubCxmss+D8ZYBVhYMh8T/7M/ltb46JfjpB5CmTD44Qd26K+NksGMWLEwwUplvPbTalnM2mnx3+Bn2ql1NL02txK6/S6AD0jLBsaTnLSmTzqfQTvySMkYpxVF0xCyb4WsfrTSHJsBkms2MP0g+HLIqJ6tyQtuXYAzLpjaBGbAFhLDtWyxrSfzLKxnrukt4VN0kRQJvcrKqwrZEZhc6PnXTkNUiU31n95jfXLxgmiTshiFDP8Q1xfFKCUvasoVnm1PDTg2omorP55/haY8X65fc6d3mMrnkOr3idnRHWCbLNcyaFFovswVVU3Uy3b7b7wDNze64vWCPs/i8m7RHdmRKwxsuk2umyUKkcdl669usK54sXzIOhnw9O+fX56eMfZ83J4fcHgz4ejYTGY5jo4wc6jDqETk57+4+ZJGt0ErCdULHZz+KeLlaEdiyoqyVMhNazSYXBsvzRDpX1hWbcsnAHXAYHnAQHpJXGfN8Lv17SnEQ7rHMV4y9HWxl0/fE99nKlm/1jijqkk25YdffY5EveTB8SJ7m/OTwe53X1FIWL9aviMuEo+iQTbnpmNcWFLbeWfG4ityv/f9KCRPmaZ9NuWZdrKibmsPwkNAJcS2XntMzss6UWTbHVjYjbweFYlUsaZqG3WDE//XjP8dSik+vL/h7d99jXSR8/84Jt3u38LXP0B12+9fWeEjKr4VGJs4T/7vjr73mJZVUPvjrqqZRDUNvgKsdE+KjSast0y7XUGV8oTJORu6QTRljW8IStkXoknQsk3hhOhPiMpHaCR3dYKO2EfPbnkUpuq6Q/jrp0msEWJsuu9RUHSyzNUkhyZWO5eBYmnEw7O4VZW3xaOeQjy5fkFfnHEZDbvUP6bmRGT9WF9qilOI6uTahQ+Jle7p6hmu5TNM5x9E+03TOLJtzGIoFwTGdrnkl16zITGXRRSkJgmmluVpZZE1tFsWGXKczfDwqBExWdUVBacJe1qbcXcBI64M+21wx9Hs8PZ/y24sLxkHAveGI436fp4tFV5MhvmvYjyLWjsMb4xPWeYJjUp0l1MoiLUsmQUBW5kRuwG44oqzFa62U6tIdq6ZiU8RETkTkhOx4I4q6ZF1IErRCMfL7HYDUlu6SX526wLVcDqMJVVMTFxsm/oQn+XNOeicUdcmHe292iwXa0pxuLkmrjIk/FpDXpWbrzoLQXouS/mnTJfEaKbKr3a52qWpqJv6k60cM7UAYy0oWQ3Ru03MiFFYHhId+n//3V78C4MvplL91cp+0zHnn5JDj3j6u5dBzIpIyRZtFo1ZWrZQSa0NdMvQG3xl/RSVeska10RUNjYKRb2NbEvxhKdgUlbB/Fmi2gTPtWBl4mqSs0VbzreevDagTcCGgKCdyLSLH7UJeoI09UOb43WhcQ0BiCxq1Ul2gTFE3JKXI/zYmudIzk/5JaFPUDbmZZt8eh3x5tqKsavb6Hnd2hLXytNUB3xagrnNhKduk4mfzjMCxmMUlxwOXaVyyyEp2QxeFhJsoJemnCjrg5/hGteJYnQTWMu9VG9bwelPS8kqhKwxXpWCalCzTirJq2GTCalpKEmsvN9IpeTqLeXq5JvIdDkYB477HxUJ6ILWWOWjTNIwij9jW3BkHwvgZYC4uNkVe1uzYmrioGXqa3Z5DUTVkpdy/2v7GshZ2TypDBAhXdUNeNPimmqLv6a7j0FYwDqXyo6xrfFuz33eoamEnx6HDMs04GbgUVcVbB20ljUiVz1YFaVEziWwKbTo52SbtyvjbJu22X1tPpdwbBeBWTU1ZN+xGNqHpPQ8dS66RqmGd1yhVEtptpoLMB/qBw199eU3TNJxOY94+GZEXNXePBxwPHJEHu7Ywxdb2s6wdGy1D2QLx/9j2+5nF8oZX8GY1RSsB3axlEtyW1Lc+xDYAp92GYyk07+/I8714bCR48TbkZrIv3x8cy+Nb6aZZOewAgGEBOwBnPBYdUGx9bk297XycTuWf70uR+tgkoQ52pMLCtkn+6jecfvQKdXQooSpFLgButdh6KdvXHe8L25RnNH/9P9B88xX4gSSB3nkkXrfJgQHaloCYIoVnX0niZl2jfvS3tp7PphH540Y8cPQGAiqGY7h1H3b35efnr7bHt5WlBoGAt8JUVRgJSPP8hXT52RZW6FFNF8x++YznX07ZbApGOz69wz7RrR3KRYx3/2ArX+31xANYVTRFIYxrvy9gWynDIFvo0MPyXYKH+9Dv01xfmWN9JYAZhEW7OKXrUawqAYit7Lhlg/s7AsC8QDx+WkO8RDmugPPD2wIK4zUkCWpvDzXZk58FkYAukNdYTgXYK0uOVZHB/FJChmALVusbYUwtc3t1ZoKSDMsYRHItuZ5cty8fy3PEayMJnmH5DsE/+NvCzE6nqA8+xP5bP5G04N1jeU+9vglHMoxikcrrzy6lIuTzj787/IwMtDJpd00jiWy2pcnrnFWxZl2s8Q3r0CZ4AkbCllPVJSN3h7E3pu8OaGg4i8/pu31AQF/bH5hXhVmtl4lraUCiQuGa0IS8Kkx5ryUThiLtKjLahEjPbjsR5XjPsxXTNMG2pD+t74Zd8qqnXUIn4K9fPuaXXzxhHAQS5FJX3cRXJmzbHrmJv0toRxR1zl+e/RW/vfocX/u8O36Hu/17fDD5kIm/ax4vReV5nfN49Zir9JK6qfnDgz8AILADw7hN2RRrM0EK8bXPwB1yt3+HXX8XW9m82rwyAEgCLnzbI3IC9sIxhZmsj30Zf19Onxl/jEXf87iMF/z75y/48ukpcZwyGEYcj0fc3hkxTVPeGO9hmeM78CJ2vBFxkYrvwbIYBwGWUuxFffpegGNpAsdh5Pu8s7vLOBhykVxxtrniOp1ymV7J8dMuZ/E5Foq8ylnmK+7271I3NTvejvnZkoE7ZF2scLXLYXiAVI6IdOwyueAwOOIwPCQuN6zzhMNoj71gwlF02C1CtKmoy2LRhQS1DN40u5bycKR/sa3U0AaArHJhRM+Tc1b5GktZxMZD2tDga4+nq6e83LwwTEVMTc1lPMO3bf4Xb/+Mu8Mhl/GUPzj8gD+79xNOohP2gwNc7RHZEZ5lej2Nr7OsS6bZNWfxOb+5+u74a8dHK82uTDpxK0Gt6oq0SkmrpGMgbbWtmLGV7qSXkdOj50REdkhDzWVyRZvka5lqg4Hbx1KKHW9Ez/hG29cDOv9j6z9tu/m6/lQTxmMrbbxwdbfgNE0XXCUrPO0y8CLGwbC7fgdeD8uy+LfPv+KTpy856u0wDobdfUfAdd2BVYChNyTQPkWV88uL3/J4/gJXu9zuH7Mf7vNw9KALT1FKdQz/aXzGLJsD8P6udBS3969FviAxCxeB6doM7YiDcJ+hN8SxRD7f1v1opXEtm9DxmQQDyrqUUB9fgqKeLS6oAUdrQsfhOon59ctTnjw/J0kyBsOIvVGfo2GfeZpyfzRCujQLIjdgaHyJRV3Tc136XkBcptIj2zRG0itBXA93dhh5PWbpkmmyYJEtmacLc1+2maZz2mqboi7pOT3KxnytKzbFhsAOiMsNvu2xF0ywlDYeY5tZOmXij9nxdtgUMWmZsRuMmPgjdv3Ja3UXeZ2zytedekQScksW+bIL/morW0TGLE7JVkI9zaYkpVzTaZXh2z51I3LW8/iCC1Nx0Xpwp8kC37b5zx+8z3FPjsEHe4/42a132A0mjDxJPQ1sv1O9VDeuq0W+ZJrO+WL2+Dvjr+0jrBu6JtCuhsHIBotKStrbAJ/2cV0iqFL4tiZ0NL5JDz1f5+SVeAXbBZiWXdwJHCLHfk22Ca+ziTc3SWI1+2YeJ/YMSRZVBlgt4gLfEQCzF9n4jkVkuhK1pfibb6755vmC/YHHXs/pJvNl/V2BbuQIiCzqml+dxjyfZzhacTJ0mYQO98c+Q89+DWRWdc35qmCRyTXw3mGIUuCbxNBlVpJX0qvs2cJ4hbbmsO+wE0pNx9XGVFk0YCtheQPHYidyaHMohwZ0vJylApwshe9o1knBNy8XPHu2II4LhkOfyU7AZBSwSQsORvIZVxpp7sC3qRooyprQswlcTWJqJGQRQeHZGt/RHE8i+p7NPCmZxhXLtGJuajdcbTGNBcyWlSTVekbW3PPk3rvJa1wtfYqhI+dHWyLztbVilogXtO1czMuKndBmHNiSCqtFFyILBzWbouyuiTaYaZNX3QKDMtdxx4wriPOasmqYJxVpWaOttidSmfuI4mJVcrkRZVdWCsO72OQ4tsWPH04YRR6rRGo+vn9nyCS0GXi2YSetrTTbeFhrpJpjnpZ8M82+c23f3P7Taai1SUGta5RlJt9pIqzL5EBkhFEf4moL1vQNhJqZRNTl7PX+Oj8QySIIw3b+UmR/IMBpMBJAp5QwMnUlz9XU2+fX2kgNq20C5s16jeEOLGao+w9onj4x76emSVNYrcSvGMcUH31Ger3h4I1dAUTj8dZjePPm0H7veMIOza5Q9x/BrQfysxYcNo2wje/8YAvH3UAA8eRQ/vbsBfQHWxCemEqHwn/9GGotx6032Ab2+IGE9YShqQrJt+/76VOaNANtYY8jnIMR2bNL5k+mZJmZ/FuwXuYMIw/d8ykuFjS5YY0BNRhC2BMPYhhir82CQK+HchyaszPq1Yb02TXeyQ763m2YzSheXHZ1I+rwBJ4/EYnx7oEAQkvD4a3tuQSaTz6S0JzDW2A7NNcXcoPrD8SDeXkhtSSWhlfPqX/1S9Tdu/KcZQnzmQC6dlHBC2CVCkB0fSjW217P9txg2EVljltvaIKFFnIdpek2nTZZy3EfjrcJwLn5/cun0OuhQw919yH6vR/SfPQfBOxGffFith2i0Wi7j5aWa7pIYX5N8+UX362naYefYefaVdgG8aPtNDX7wT4fTz9mYIq1+44EiojPSf7+OrvGtwPm+bwLMKmbSqRkdsgq34j3ocrxtDAIeV1sPVkKIxNqzCR+m6ZoMjY6UBjYhiExrGPPkcnVXrgDzLqEyKqpWRcJjXlfn11fcTZdcPf2gfQpej6WpTvfY2mAYxsr4GufZbVkmk55NHzAnZO7Bihv7zufzD7h/fH73YTJ0x77wT67/p6ZtL6S9EZzu94UGyNtE3mVulEd0rKPtuWYIvuQWbag5wYCtutCKiSahi+mT0nKDEspdsOQ496Qb+bXPL64Js9FCmVZFvEmZeT7DD2PVZaRmZoJkIqTyI44iHYZeD0OojFpmZFWBRN/yNPlOcss49VqxRvjMW+Ob3Gxuear2SXjIOAgFBD3fPWMSTBhL9hjmYtf7U7/tpFCirf1l5e/IbA9jqIjbOV0SY1Dd0jZlJxuLrg3uItSihebl/y7l7/g0fgOB8E+RV0yS2cchocdOHRNb5v42DwjGazQpjqhaiosLAEPqqBsSvrOAN8O2BgpqCTNugR2SFLG2Mpm6A7RSnf+SsdyeLl+wcCL6Lsu9wf3+HD3Q35x+QuOo2Miu0fPdDdaWAzcYcdMW1g42qWocmbZjN9efd6d79+1tee2amqJH2nE5yULCgNerF9KCFKdEtoh7g1QpbDEw2gSTvWNGhzXBLqALPTMsjkDs4izyldEToiHZ1ioLRPZbq3Uu71HtD+rEZZDoQjtkHWx5sHoFk8XstjYNI2pelnRc0LiIuVX589YbBLuH+8TFwljf9gtTm15je1mK5uCkmWx4u7ghMPwoEtBbd/7k+VTHg4fdHJZ13IZukNG3pDKeH9bOStsPdqlZXfgp32PbTWQpTSrYoWrHebZisDxjR+27I7B4/kr0rLEUopJEHAYRTxZLHhxOaUoyu44xZuUnufS9zw26zV5VXXyrIHbE5llMCRyWpAoVUCu5XA+v2aeprxYLjnq9bg/2meaLHi+WjL0PBm34S7n8QVDd8DIG7AuNmil2Q92RVVh3u/ns29wLYddf4KlLK6TOY3fmAWDiqt4zq3eEUoprtIrfnX+FXeH+4z9UeffnOhJd790LZei3lDURVf1UxumFlrWTc5hm7QdOlK7tCk33blo5aepYQR7JtCplaE6lsNFcknfDQmcNbf6R7y185DPZl8xMUm5vhYAoJWFa0fdZFUrCyyHsi5YFSs+nz7tjv23t7JpJ9ytuEyYFlfLZ875Osd3FHkpJfL2jTlbJ09ViqyssRzdXZ83mUfbUkyT2lRTNKzyip5r46mWgZLFoLaPr72GVNPWc2x/1oJMS8n+VXnFG7s+X5s8vbqBuKiZJiWRq9nkFZ+9WpGmJbeO+iSFAb/Ndvp4k51q9z2vpF/x9tBlv+ei1TbUxrbg2Tzj7kiSfBskRX0UiO+xbhpmyesJmHkpcyNHN7h6W3sjY1CZnj/FKqtwtWKR1viOMPNF1XQexmezlKKU9zAIHMY9j/N5wunFmsJIHS1LsdnkeJ5m4NokedYBaxD2z7eVCeCRFFhHK4a+ja0Vp8ucdVZwPk/YiTzxeaYlV8uUwJW/Peg7XBmGM/I0aSFeyr2eTVXTyS6/upKU00loYynpwhwFmsgVL+Z0U3JrKIvVV5uSL883HAx9RoHck9dZjR9tgZhtWeRVJaFLliKrzeKh3p7AVpbaXje+rXFCRVrV5n4mPl1fW6SGQYxcE7pkWGCtFJebgsi38WLN8cDljT2fLy9TdkJtalt0dw59e3uuxa4EeSVdoI8vEyzru/f5m9t/GiwaoAgIYPRM2mTbpxhEAvq03tYNJPGW6StNh958JmxcfyipoVUlAKiuwAmkyP7iVJ7HD0wXo7WdYMsOmMm31UkkpUbDeKcsa5u86nry2m1txmZjiuQt+b4sxet3fU1TVAw/uEV+vqBZr7FCI/ssC3kPRf46swoQ9CXwJs+2PZLthKOq4PaDG8ewkHROgOmFyHKP7hhmydxB9gygylOR5/aH2+dqGVWlBETnmbCkSbKV5eY5xDH5qynOXp/iYkk5i1G+zfWzOfN5LqtIvqYXuTiOhTORiYnuB6jdXTg/F6ZyTxi8Zr02iwMp9PuoSNhUigLLdwk/uCeMo+dRXc4o5xuwFM7Tp8IQg7Cfni9S1Dfek4WD3/4NzWefoixN/fQ5Vi+k4d/TfP0N1g9/CA/fkevq+gz1Bz+Tc7CcSkrp8bHIYT0fVhdybrLUMM8iZWW0Kz+vKyNNTQ0LXcnd1zKsYitXbr9vaphfyzGeXsGBCRRSzVZO/Plvpafz3kOaF88ov3yKcrXsw2IuibnDiVk8MNeDY+SvmGvZ9c01UcH9t1F3Hr2+KGG2ljWQFMQaGvB0YOLR7U6+tSpWOJbDSXTCqlhxGp/JKnZVMM/mDN0hV8k1PafHwB1yFp8BcBQdsSo2LLN1xxzGZYpve9hGxqQNO9JOxjrGyFx3rrYpa5u8KsX/2EjaqWc7FHVlpIkNmzxnx49wLM26SIiLjKquWWTia3rjcI/LOGaZZRz0BvTdEK2sLoWyTfgEkTb2nJ6ZCKXGz7U9fmVdcqd3Wx7diKcsNpOgaXbN2JtwFB5TNRWLfA7AfrDPqlibkultgX3LfolsUTHyhhKq44RsiriboGZlwTrf8Gw54yCKON9suE4SPK15fnHNaimSYNdzCEMf29HsRzJRHnoeB+GEF6tz+m7IQXhAXMTMs2UnK747PCYpM+IiJSkK6qbhewcH3B4cEjo+n09fcJ0kRo75DcfRMVDhWR4Tz2GZL3lj+CaO5fCb6W/4+dlvsZTi8+kzhp4Up396/Q1/dPxDHg3fwNcBs+yanx39IbZls8jnTNMp90YnZGWBb/usk2vSKqVoJFij9SU67g5ZneE0krhaVHXXw6mVpq12aMNvqqaSeommYZrN2PF3mGWzjn1sAb1jOXw+/4J5tuDB8B5PV8/55dk3+LaUgy/WC25FJwzdkQEbVpdaWjd15wH2tU9RF6RNwsPBI+7173cTo9+1tUARhL3wLIeykZoYZZjrlokRpqjoQk60YW+yKmOVr/AMyzlNRQIe2nIP0spi34B6S0k1jmvYdAmqsKiRsKY2wMpCdWO0UhXtMrU2sthWFuxrj7hMWOUx42CItizxzVU5aZlzGS+o6pr3jw44W69ZZinh2O+AaAvyt91zTcf2tsFOrVy2/X3d1ByE+68dv6xqlQYLxr6E5VQG7LQ+4U0ZU9QleZV3icdbSa9IPiNbZJuB7UlVheGSikrCfF6uVuyFIZdxzDRJ8G2bV5czVstNNwaDwMN2bCama3ngeeyFA843UwLbY8cbmXO26ULAhn5PJKNVQV5VhI7D+/v7DNwevu3x1eycWSKVHN/MT9kNdjoZva20Gce3cSyHL2Zf8cn1E7TSPF1c0nflXH8xfcmPDt/gTv+26XFd8P39d0z9y4ZFtubWYJeskmM+zxbCqLoFRW13vsS+05cAIGUWZpoCZRhRVN3JUV2j8KiaSsYJDeti0/lFHcuW429Eq7bSPF4+Y5mtud0/4nR9yZfTCzytKeqCy/SKw2iPvtPvejLlmrQNy667sazqkqzJuBWdcHj/oEsNvrlZtAX37bUlEr6i2tZWeLYyQAcjkZeh0KZqt72HLcjxtEXZYHzeW+C4Hzks8xKtxG/WFaujXnNAdT8zTGZjdqyt6VBKGCnHEimhZ1tUhaSt7oQin11lFWlRE+c1001BWTfcPx4wX+dSF+EEEurTNCKrZStBbX1wAnAcSuOPvLnVDRz0TaZFOwbrmrrZJqaOA5sGSWtFw05od9UKeVlJEqoBNI3aFtxHrkVVi2ex9SrK+GtIiorrVcowdFnEOcu4wLUtzi42rFYSVOO6kmDquppBID2toWezE3lcreXxI98mq2pWhuCI85qBLyCwqBsKU81xb7+P78jPX2xylnFOWdmcWopRIMe6qoWFToqaN3d9tGXx1VXCFxcbtKU4mwvA/Ax4ehXz3nGf20MP21Ks84oPj0NcLcE/m7xi0vc7z+MsFrVJWWu0JdeDpVTnd60b1aWsWu29EQlYas9he77a5NQVIqNdphVOKMm5tWqwGvEtPp5mrLKK2yPpxzydxdKhCFxvSg76Dn1Xd2OhvWKbpuk8wG2tBzScDFwO+787Dfzm9vvBopF8KtsWRq6uadKkY6CwtATJzCUCvfMgVpUwiYMd+bnWElwzGG8L042Mk7LYAr+bCavKkmqDnT2TbGqYvpvyVsvUc9iOsJ0gtRRJIqBQa1QYyWNGI9jZQfUHNJuNyCXffBOShKaaoRwJeFFK0Zy+FE+jbYPdyPtpO4CyRAJR/GjrzTQ3iW5rJbMt0K0qAa/egQBnA76xXQGOsAUseSZgt2lE5tvKJPNsK2EElOt1NyemUyO3LAQoXq5AWzh7fc5+c8pyJVHGvm8zHvv0Hx3QlBX2uAd1Te1qCfZJEtS7HwjAyzRqtEPz4rkcS1u8dc1yKZ7GMISDA1SvT3N+RlM1WKGH8+gO9ek5erUQJjWJZRHh4lR8nNGAJs9gNKL8d3+J3t2hns5J/7u/Yna25uT4CPWhI6OnDcFJ4s6rqXZ2aIqC5t/8K9KvT3F2++j5DPXOBwIWLcsExwTba6Qs5VjHa7nbtd5BMIDOsLJ+ZM6Tt+0O9QPj3bWEgZzso8a7cHIflSboJ09Jn12j//1fCkN6cgL339kGFbWbMgnATSNA0dTRML2AV89k3Pyd14ffzV5FjUVRlxJUYVaIhTEZME1nwjhWMT2nx8QfcxafG/Ank9g7/dvsuGPickNoR4R2xGUiISDtRJhGJg1WZRHYEnogHUQSyy/l0cKuVE3dheC42jFpjA2bIqGoKwLbM2yAAM+hHzLwIkLHZ5FvWGWZFFw3DbM0wdWaSRhiAVmZ03MCKmSy3XNCeo4sbKRVSlomeNqnbEocAwSElTMMhnY7n5yY+ys87RPaEYkJIWklrhN/V4ZoXeFqT2ofzGM2xabz+qRVxs0eSwmIkde9jKeUdUVelxz2epythYE9iCI+evqy63RzPYfRTp939vfIq4rdoGei/xVDv8cmT/je7gc4SljSXX+Hx8sXHXDfD3b57eZzHK3xbZt3Jg/YD3d5tT6jqCr6rsuH+3d5sjhjmS85DA8M4zzAVpppdk1oh2RVxjgY8i8e/yWH0ZCrZMV/88V/4NXVjLuDY36w+wOgQSsbrW0SExakzT7ldcE/f/yv+fjylMNejw/2pny4+774pAwodC3XfDhpyqbEs2zx0CLso6/9joVq5Y6hHUqFgnIMWy4+ytKAhL474CDcZzeYcBLdIi4Thv4TvpnN+Lcv/grf9rg3vMXD4aPO59t9VBjgI+xAaaoNaqbZNS83rwi0z1vDD/j21oKkmyx3WkoASAueAu2zKWKTuJjhakc8Z2VCaAeGobOY+BN6TtSxroH2yeucsq46QGEpq/M9gjCMcizYsocte9dIt6JtgaU8cnP9XydT0irH1SLhDmwf27IZB0N2/AGRE7DKY6bpmkc7J8RFQlWvOj+stizONlJrYSkLq5FEV1fLhKKoC1KzSFM1Nbr1Ft9YsGkl8e3PagNGXO1KYm8jNSC2pTu5atXUjLRLWRckZYokZRrGvak6AN6CVUfb+I18RszSJZLsWbAfRVzFcTcGP3l++toYHAx7PNqbUNQ14yCgrEWC1nMjNkXCW+MHxgtesuMPeLE8l4mXATOLfI2rNaHtcxBNiJyA8/iasq4JHIc3x/u8XM1YZGsmwYi8Khh5O8yyBYtsQehE5HXByIv4i+e/5aA34Cpe8+vz33I9XXLSH/PWzhsmJMXBxjFhQcKKDly5b/yPL3/Bl9Mpe2HIm+Mlb44fdCxsaWo7gA70a8vuALsEl7nd9STnSBYAxEProB25FtugHKUUoROx4w0ZeeKLLuqCb9xzni0W/PzsY3zb47i3x0l08h3JZgsGa3MfLU0K9iJfchFf4pvk6NfHn0kWbdfh621KZ4vdPNsizkvTaVd3Kp2iqvBNEIylBAx5tqaoajwt9Ratt6yd5MvXG97AomDgSnesdCxur3MBpQobw2uYMXuxzilMt6I24SS2pZhEIufsuRaLtGSRljyY+MR5be4xit2BL778VcF+zxEfpm6lrhZt2mtWbf1xtnq9CkTOOegb7GDLLA48Yb1aRsu2pBS+BYVDTypAslLuNWm5ldi2IUPtfU/qJQAN87SkbkTmOYo8FrH0Mo8il2+eL1ibXkXPky7Fkz3pBez5JkjPrum5Fusc3tzzsbWiqMUz+Wopc96yFunkIq1wtEXP0wIgHYvLtaTZeo7mZBxxvUpZppWRjdbsRQKEZ0lJz5Muxb7v8KtnC8Z9j2Vc8DdfX3N9nbA38Hm0G9x4j8JkF6bjs+8JWP75syWvZjGj0GWZhjza9V8rvvdtCxez2GY8moWpG6vV1tfanrUWMNpKWMW2F9fVdKx6YNJxR4FmP3LIyoZXjuZqmfKbl2s8x2K/73LU915jLqElH9rXkuuopmGZ1Zyvi9eYx9+1/Sd+K0xdY4puBeKaD+CLU5FTgkgNQaSVL5+KNDTewGa5BVFBuJ0ot6xZ6xNrE1IPbwmL1TJ58cY8l0mqa9mhdonHsrbhMe3meqjhCDXZFz+iSeZUd++LxHQ0kRCVXg+uryHPsfu++PtcB27fllWixZzm8lz2fzQWdgjkPbu+gImg/7uPm3bkXyuHdX35p5Tsa5EJmG59a60309ICVtq01barUs709v2WJTS1JHYWhbCM5vviek21SihnGxZfXbDZFHieZjT02N8LGH3vNvZ7b+DsCiNYpzmW76L6fdS7H0JkTOarpZyz8Rj292VfBiPUaAf16JGA7yTprkb7xx/i/eQDAd95SXP6SoDWekXz1/9WQoZaH+pySfzvfov9U+lJRCks3+Hwx3dE+grbIJoWsNXik2xevkS98a4ci7qhnMcCdKeXcj21fsQvPhZgr9QWGPqhBOc8+0rSVm++TlXIubVtWMxpPvuNsIxVZfyvqVyLBydw+6F87wdYf/L3CP7kx5TnM5JffyWMagsUu+5PtQ1nqgp5/cefC6ucpxKi9G3mmq1HojarggC1+fpy/bKTpO2H+ygUT5dPebx8LPIiE6Uf2ZLeF+ig848N3D5FnXMan+NaDp52O58V0E2y87qgbKpugiFhMU7nabw5iW4DBRzLYehGDFwBhrWZ8B2EY+IixdMuI6+Ho8Vsn5YlkePSAJ7WHPVlTOVVwSJdMfB6fG/3fQIdACL/c7Sk/fXsGz2aN4efstGmSw5Ul9DZyuqyKmNVLMlNUmVVS9iJMGMSVy/H3xSXo7rgDdsECrUr8VmVE9genu2QlblhZjKmScIXF1fEcYrtaPqDiPFkyI9PjvnhwSMOewM82yUuC3qux8gd8IP9D+gZWd4inxM6EQfhhFv9QzztcdI75o2de/z0+F0+2HvwGtvzd+/+gD+9/yHrfENeVTxbvSS0Q87jC/675/+Kq3Rq0kszrpM5f/70M/7hg5918ktXa/7o0X12TRWITFRt0+UZdMzc0+Ur3hq9KeccmKYpfbfHVXrFMl91zOHn8y8o6hwLC88wiL4OWJdrnqweC5tE6+2zTfWGJDIuiyWfzD41CZGVuR6k523X3+MkukVRF4R2wD9++Pf5x2/8mBerGX/18htOouMOKLbXrWUE0C1QfLZ+yjfLb1jkCxPoFHT9hb9ra5n0jl00x3yWzTtfbysfvU6vuUquqZpSWOoq7SZs7eS9vsEotiCgqMWHMvKG5FXeve+syihN6rFck1Z3fuS9iR+w/TmAb3vs+AN2vCF9VzpIsyrn7uCYuEgZugMOwgk9x2eWrsirkr4n++bZNncHEkqzzDZcJVLd0nN62Mo2XpfShN7YBLb/O49Zy3i2x09CdWQsSSdkSVxszFiqO4lvO8YiJzTcqYDolkm1TQdle+2LsqHsFqXyquQqjllkGfM05evLa5Ikw3Ftev2QnfGAD48P+WDvDnthiKdt0rIUsOgEvDN+QGDOzabc4Gs5lnuhLCSHdsDEH/FodJuR3ycu0o75/snxI3568oC4TClMyE7rvf3l5W9YZhsJDKtLltmGf/vsG354+IiyFsls6Dh8794txv5QWECa7r7TLshZSnG6vuT+8LaRFzbMs4zIDZhnCzZFLAsISvN48YzSWAocAwzbMJuz+Jy4FLWTMIZ2dx1qy2ZTbvhm8YxVvu4+DwSsV+wGuxyGB5S13AP/+Pb3+ZO7b3K2XvOr85dMgp0ObLXVM699ljUlZ/E5LzcvWRdr8joncH73dSR/24bbtDUs8vN1XnVjMTIl5bOkZJYI85uU4klst5YpbBApXytRrZum60gceg55tf28bZMuM0OctMe8PeetR/FmrUbkanYCm5Fv03N1F1Byf+yR5DVDz+aw7xK6mmlcyiKDK0ohx7a4syPhb/Ok5GxVvMYqiieuwVbKBNyo33nnuukv3u7j9nd105CWdSerbY+pthS2UoTOFmSL99Pk8VnymLIx+6FVB4wdS1FUNYtY2NF1WvDyYk0c5ziOpt/3GI8D7h0NeHTQYxi6uI4mL2tJn3U1b+35hI6cp7iQVNO+ZzGOxL/oaotRYHN/4uM7Fpt8e37fOe7z3q2h9KLWDZerjLxsKCsps99krUpCAOdH31xxaxJSGGDsOZpHd0cMgy2eaL2Ftt4G0pwv8y5VFmCVFESuZhZXrLKqO0ZP5xm5YcDboCTHskiKmotNIX5Z8zpabb2NtlZssppvrjOWadUxt20H9V5oc9BzqQHfsfjR3SEf3t1hvsn4+mzFKNiC/3Z83CSe66bhYlPwcpF39S3tMf992+9nFrUNTYPSUv/Q1LXxf0mHYVcdMdoVMDGf0SymqGQjfsH1SibqJvBCKguybbhN1JOvmZlUO64ElrQAKjRetNVCpIEtSFRqW3PgmP6+Vnba/nw4FoZovZJ93ZlIz13Ul9ddrwRordc05mKh35eqjLKgef4MBgN57aM7Mql3ffGhJSvjk7TldetSAMfN7SaABQGNqdnfzXLribRdAR6WNqyYOSu5Mh2T5ixrkzRr+hU7L1y7pSn5y2vQFpbniLTU0fiRHHvLtfGOR6h33ka5Lk0b+MMC3nhDAoiiXndVNbNr8Qq+fC7AWqmtl3J2bUCYSbc9PYV791Af/ojm13+DNgsLzVefyvl+8QL1wYcC/vMMNZkQ/uwDAWZHR2SfPqPJK/Rbj+COke8m6234ke0Kw/zNF1Qvz9GffoR68AD11Su8H72LuvNAro80kQWLeC0y1WQjALFNmQVZqLiZ1NumpWpHGOPBDjz5Uq6VlrluGdz2HKebrcRZ26i33sO2bZz+AA7vCPCrjDS6zOXv8lSY8iQWAP3NVzAeS2LqYCRdkt/aWhmZY1mGDam7QIJ2ktlzeoy9SRf+MM1mbMrYTApi4zsJUCiSKpHURsT7dBDus8pX3U1vmYsc9ebEE+QD37Vc4jIFqtcAZiuJc00PnbYswxjYuEoCW/K6QFsWB9FE5Gb+gJG3IK8rytrEewOh49BzApSymKcrjnt7HEUH7AX7ZHXWJWRuyk0naWz78m56pQBs1Upw2pulRVolOJbLpjQTICUSwqIutvUhqgHEe1XWRfchbRmGNa8lkMRCveZzy8qCx4upkTBphp4nwRq+AGHf1twZDPnR4bu4lsNVMsfTLpZa8sHem0z8CaEddtLJWTbn0fAhL1YvGXoCdB3L4W7/DhfJJQ2Lzqf5ePGS93Yf8cO979M0v5TLumn4YvEly3zFJ1dP+OPbPyIx/XOH0R5/ev89bGVzb3jML8+eU9QVH+494sHwPgBxFZvVdEk3HfsTvlp8zZPFGZ9En/Lu7iM+uz7nj2+/y/3BPfpOn6zOeBWfmuRHj6QSBlgbpgKg5/RxLZfanLOyKTuWY1Ns6LsDniyfsOfvSliL5RgW2O08cWmZmNoLH21p3hm/hW1pkwJ7RNvp2C6OaKXJ6oxFPu9qGD65/pK9cCyMu7fD8/WL74w/ENa8/cCtmoqiKinrUq73RqovfNunb/WxlMW6WLPK16RVxsDtk5SJSYcVwJNXRbdvLcOYm4qPkhJHOQzdgTmHUnyvTdhQZEfS52bYjTYwpS1zt839wrZssiqn50jNjviEpcOxN4oI7ICT3hHrIiarcpPiKxUXAzdkL9yhamperM4ZuBGbIu76FR0TVJKUKVZTYak23bLqkjjVjTHTbi3gzqoMbdmkZdqBb1tpyqbqZMKimNGAgJOyaZ9Pm+NSdu+/Zftqaoqq4PlyiW1ZeFoz8Dxsy8L35TPQt22Oej3e3b2Dp12CxDE9qDFvjm8x9AZS3WGmcLN0ya3eEa+qC0LLxzL3C60s5vkShcKzBQC/XF1xf3jEu+M3+W39GVUt4UJfz59hoXixuuJ7B4+6qotxMORP7j4ksD0Oo10+vfqUrKz42e1HHPcErKdVhoV4UB3LYegNeb56xbPljB3/CQ9Gt/hyOuXHR3c5jg7pOZLWfJVeycKc7ZBUKY5u02zlWEVO2AUgtR5ybQB9WmVEdshpfMbIl2taW9qIR+3uHLe1KK4lPsZHo3u42pHAL6PWaEPPBAzrzp+YVhlxkfDN/AU7/oDj3j49p8fZ5uI7488xTI1jSdhNXbXl5qpjuhzLwtcWFiITjIuarJLOurioGJigF63oUi+bRp6vncQL0y3AaOhtq6RcLQsWaVURtUzaja2tpsD8bd3IZL+tNmj9k3lVM/Qcers2oa25PRCvYlrWrNItEOn7Nvt9Sfp8Ps/ouZrzVcHJwO08cK62yCuRlGol7KAckdc39e3vlaKqJDU2KwUEy7iie65u/DbCKJZ1gzLTsLb2oawbcfOoNswHc000XC7Trs9w6LvYlkUQyL3fti3GPY83DiJcbeE5Fo62WAN3dwMGvia4AVrmiSS7npYNviNgV1vCvs3N/M21ZZ8ulhnHI5+39gJ+XUpKal7VPJ0mRL7DbJPx9kGPTV6xymAUaL73cFfChZTi19czyrLm3dsjjgcubU/kFswpBp7mJXC9Svn62uHWjs/pLOaN4yGHfYfIleTSy3VJWtZ42iKrpN+wDT0CWajQ1nbBrz132oDt0LGYJ4UJPuKG13G7KFHWIv/1tELZiocTYTVD12Iv3F6/22tbAo42RU1a1GyyiufzjKFvczhwiFzN2Wrrh/9d2+8Hiy3j5fkC6ExvX9M0qDyVbsW9IwE7XgB7LiruSYXEZi3gozISvqqQr6OJPO/ZC5Fg9oYyqW+vOM+Dqwv5Gg2EHaqrToYotQeVYey8bb1HK/3UY9mXqoRC3QAHhZGz5tvk0uklTVFQfvmSchHjD/rCprkexBvUaCLdeF6wlRG2skZlmfoH40dr/XC/KyhBWUAtwKVpBPhk3+0UAoxM1dyRPF8AUOtbHIzkvZal7OdqIc8Xx5RPXqH7PkpbNJGHHvaw33kIFxeUV0vqrMAKXGFutbyH+vQc6/13UbfuyTFqg2CKXPopz1+KF3I2M2moa8gy6ajs9yWptKnh+Bi1fwSOizo6ofE8kacuFxS//gylLezPP4OdHbi+Rn3v+7IfWYbaGePu9tE//FDe1/UFHD+A2rDJs0uaZ9+g9o9QR7ewg5Dm009odnbw/8EfQxDSfPQL1Ic/NKm7E5qrC9TD27KIkSVyjbVAz9KywNEy1KIf2QL/zUoWFCwlAE87W/mo1vJ8WSbX585exwiqD360PU9lvmXLN0s5ptMrM5Y8ePg2qtcX0F2WEPYEvH9ra+scfO2TkZGWmVkZq0mrjFk24yg8pqyl/PwoOiTKQ56vX3YM4KbcTvotLCb+LlVT8XLzkuPwiI074KVJ+Wy7zoqqZJVvTKS7gN524mIZ4NpueVWiLYvICkWqaKLrZULtEDo+IX4nU62bCs92mIQjpsmCke/z9WzGOs95aFhlhWLoRTwY3eH98fuvMTLbGpESB8eUdksKq9W0E1XVgcRuCKII7Yi6qRl7k67q4DvD74ZMte0fq4z3bOBGWJWiqkuww85rtcpjPrt+wcgAxKquGQc9fnS0x4vlOeebJZnxOMVlgu0KG3K2mfHT4/e517+LowUUWcoCBXd6tzmPL0irnCKZMfR6rIs1SyPZGngCuhpq7g9POAj3cSyHO/1bBLbPjrfDMl/yF88/Ia8qfn7+MYfRhMt4xh8efY9NIRUNQ3fAYa/H37n9feIiYZpOOQ5P2JQbLGUxz2Y8XT3jINznVu+E6G7Ez89+y164w//y7T8mtAN+fvFrfrT/PQbukB1vxNnmnLd3xDuY1xk9uy+sFJJg6euA2vzXuu9sZZmAjTU9J8JSugPxreyw9eK1CwdDPeqA0/d3v9eF50gXn7BW62KNa7lcpVfYysa3fR4MHopvMJsJ624HnG0uf+ftuKhLHJPeWtQFWVl0ZcZFVbIpYna8URcgMnKHeNpjms4lzVX7HTBuGZqe06NqambplKE3xLd9crO41PWhFmuqpiZyRDbcem9BmPP2OW0loFXqOBzj7wtxDXAs60pYQUt313FVV9iWw73BLWFH64ovrq9ZZhlDT4JObMtm7Kfs+AMOwoNOslgbNUEL4mxsI8m1uuf/tiTu5hj0tHRc9t2eVH3cYEjbv8uqrGN6bcvpJMOWsojsCKsWWaUPrAsZr0mR8tXskqHnoS2Lnusy8n3e27vF2fqayzgmryp82yYrC6OOqHmxmvH+noAt8efVoGSBbMcfcJ1OyapC2Fc3JDELFdNkQd+NOin+SX+XvXCMbWn2wrGRb7qUdcUvzp+gleLz6yfs+AOukgUf7D0irSRFehIM2Qsjvrd/z1wXcw6CfeqmAqVZ5kterc+ZBCP2wwl/dMvlk6sn7AZ9/uHD7+PbHp9cf8W7k0f03R4Dd8BVPOdeeIuBO6Cochwn7Jhey4xBEaEZhsws+jmWTVkXBHaAZRbMbGV350MSsfNuAXHgDpCpqMWbO3Kta0vqaNIqFcmyCci56ce93T8hdALm2VI8y9rnOll89zOwkXoD17agrMnK1ocok/m0rLrAFlsrhoFNVtYs0oqkkCTJusHIA41s3NZUxrs38MTXdvOzwLYs1oX07vlak9cmN6ADV+Ijk/v19nlbKWuoFJUW1UQFRI7NwDUyQ7MftqW4v+NznRTkZcOL6w3rtJDSeVvRczVpWePbFiNfm+qL7Ripbrxm65v8j427m5ujpSIkcvVrYT3QWZ67Hkp5vPhBq1r8bq5jiSTeeBY3uQDvuKh5NY2JPBvLUgSuJvIdHu5HXK5zZuucoqpxHYu0aNBKnnO+SXnjoMdh3xEvqQHEeSmg6XJdiEcxq4jc7etN45KeKxUYdQP7A49JZKMtGPqaopT5XuBaPLncYFuKx9cJPd9mts556zASNRSK/b7DIHB5sC+qnstNwV7kdosoy0wY3pFJPv3g9pBvLmMGgcMfPZrg2orPLhLe3g8YeJpRoHl8XbK34zDwbPJKzmOL+SrA11Lj0R5z1cqhLYuqquiZ4KG8bOi723OkzPmRgCdF70bdxVt7opCxjOy1qKWrMi0atAXLVJQJtlbcHrlEnu66PkPfYpFUv/fa+f1gMezJZLYstmmNliVAYLVETS+lEiAwoDCJRQY62ZeJtlIiM6yKLThyfWF6hmMBiVFPJtWWCc5pE1VBvq8rmVQ7rkzmq8Isg+gt21be8IA19bYbsTIgM14buaol+5PE8hp7h3B5jhW4uA9voT78QQckVBDSXJ1Lx99NANh2Ai5nMFRgmxCVdCOg8tsM42tH2zGex3y7z3kmgOzgRHyZbaBObnyOtQGirr/tXzQAuSkKuJRJjn2yt5UIF4V8bwCI/eBWV62R//ITdOhieQ7WowdbT+fNm0yykYCbxYLy8QvsD96W37cgKYoEKLbps2FIM70Ub2vrHd09gOsrmqrGOdxh+ddfMp9n3PrZA3Sekz9+heu6qL097P/sz+T9L6YC/N74QCSa/aEwwI8fU/781+jjfchziosFThTJ75cz1JvvwOkLOf5BKGyd50u6aX8kjG44MOxoJOdqeinXbXu+WrlwWW77M8tC3mOWyM/zdAsuW9lMm27oBQI4WwlqbwjTczlmm40AUK3ldWOzILB/BIbBVLfvfudy6bt9KTU3ni3ppFIM3YHxeVwwcAZdIf0yX+Jrn7G3wyJfggk4kLj27aqRYzlMvDFlU7LjjdkUG3LjcSq61WDxnjnYJGWGp+XmWVV1x+qJl05RG09TK29pvU0tsM0rYehcy6FGJtmedk1PXdlVQ/S9wMiUtuENNz/8LMPsaaVZ5UuU28rbJGDE13638n3jNgzI6qdjOSRV0iV05nXOIp+T1zn7wYGZ8Dsd8+Pb4h8p6wpPu9QI01PWcj6KrODV+hJLKe6P9rtJg5TBN1zGM7Rl8c7ubYqqoKgr/t2LT+m5Lr5t8+H+Q3pOhGOkriCSybiKWRcblvmSz66f89PjdwFY5QJ82u67NiFz4PW5TqeG/ZXxtxfscpVeEToOR70+/+PTJ6xXn/D33nmDoi75anpG5AQcRnv8z978Mw6CfZb5kr86+zkPBg9Z5PMu5OKT66/4N89/yf3RAVlZcL5ZmhTSHst8xXuTt3i1OcXTHqEdcndwR4Bfsabn9MVLq3popQltmXBP02sie9sjCOBpn6qRcvFuQUA5pHVKZeouWnljK21t5aWBHXS/q5sa27G5zq7Iq4K4iE0RuOY6vSYtU8qm5Cg8ZOiNsLB4OPzu+AOI7LCrr2k3hVTArIuYZb4ksH18LamcaZUZJnbULao0SOBLKxtXjTJeXOmR9HXQhcS0oMg2x0U8s5rrdNr18rW+2Tap11EiUayasrsGJdFX0aYfb4rMJBjL8+Z1jqc9Cb+y5oSOw4PRhPd2H3WBQIHtcZXMOI6OboxBZdJdbeJiY2p0pKy9ZUpbwNgdr5uMv2WTVzm5kTQWdcmqWFHVJTv+mKYWnyt1RdGUrwewGDBsWxq7ljTmsi65iGcA3BnsdKAmK8WnP00WWErxxviArBR578/PHhM5Dq7WvDE+oueEnQ+8HYdxmZAUKfNsxdezCz7cv9sxua7lEjo+jrZN+FVNzwlNR6omMYt6++GEx4sX5GXJneGQv37+gtVywx88ukfVVDyZT3Etm4Nowp/d+xFjX+7bn1x9xYPhPVb5mtAOSMuUJ4uX/PzsK457Q7Iq52KzYeAG9NyIdb7h0c4drpJrXO3gaa/rN0xM/Ux7nWll4VouWZWxNIFL9o2EXsdyqHVNZEdmQUAk+qUB7IW57trFCTm/4t9t+xe1smhUQ6ACilyqQtIq6wDoMl+TlLJAuevv0HeFwbxt5M83t54rAKKq2w5TuaWHRoIolQfSH9d6y2xLUjRvSstlccfMj0zwR+CIfw/EEhHYumN5WkZQgCRc5SJVdsz/t9eKpczkvNlKWuU4WrRpq03TkNWNYYXkeSV5WzMO4Gpd4jma43HIB4chjmUZW4akXY4D+7UxVJrnSsoKZWvTbyhyUNt6XbJK94rb72XhaVufEBcNRdUwMv5Bbfa7MOAWG6paOiyrRl5b+ioVRV1ztS5QCvaHfndsikoA9jSWRbBbk5C8FBXR56dLPEdja4s7k5DAsXAMkmrf5iozrGtW8+I65tFBD21YYN8WBs3Wqjs/oWuxyWq0qshKKaDfCW0u1znrtODObo/Pns1YLjPefjCmqhtOZ9ITutd3+KNHO4x8zTyt+Ooy4Y1JzdoA1LRseDlL+eRlwbjvkRcVs3VG6NlEnrzu/YnP9abEtSVA6XDg4NlyjgJbri/L9GU62qKo5PmdYAsi5djLtRO44o8sTcJsaa6jwvSKKiWLGjc321bbMWLGpVR6NaTlVmq6SCs2mQDH3dCm50llzNHA5fdtvx8sHt0Slm+zEvDRNCJB3awhjmmKArWYG8Yk2Pb/2TbkbJNI8wyi4RbMlblMpi9fifdxOZeJc8vMDMcCCmeXwkSulyJrDULDCN1IlmwDb9pgk3hjAExPvrbA0zf7V5XQaAgkSVXdvoe3uw8nd28EydTgBQKIulGmRBrj+oAvIKPMBTw4llQj3Aww0c7rAAy2bGhVCWB2XFPvkIuPbTkXkNWClaoURreV/3o+FLVhrFbyWsfHKM+nWa/Eg7ley7FwjXxyXwBWfT0j/uKM8M1Dqk2GfngPNdmF4zvy/J0fUsB4s1lTffE11SrBGe3QxBuazQoVhKjdA9NDWcnxf/yNyHkvL1Ent1D9gSwqHJ3g/Wd7NFeX+CfXnLztY3kOzXpFebXG/clQXn+8J8djMEK98Tb86i/lfOQZzekLvvpnH1HXDY/+rqa4XFHMY5yHt8TjenhLjulwbLonPfENtgx0bY51nm7rM9oFiXQj5+3m+fEjOa9Fvg0cqithCIdj0xv5Uq55rbfBR9aNodQuZOzsyeNb7+Jqsb3ONyvYP9km6b753XCN271bnMVnrItN55nytCsMU7Ymq3J2gzna0gQ6oHbkZtwm5NmOpD7OsilHoaTTtpPWgTvkPDnjND7lIrlEK03PDbnYTHG0SNc2eYL2NGkpQTeh43fdf7Ztd6Bom3inuwJnzxaZqqOlSsPVdvfB2T5WvDg2b04mnay1lbLuhiOOwoMtiLoRC9/6n/I6x2osPCXVCHVTywTHMLLyN69/ZHqWZ/w5FdpI6PI659nqKct8yV6wR9/tU9UVJRIoVDcyEfe0yEHbHrO6qXkwuoWnPZb5irPNFas8xkLh28KgnPT2Saucl6sLPr264p3dXVZ5zru799gPdrnVu9XJwVztktUZSZlwkVzyN6efMU9TRt6QjQEme8Eee8EueSWTbcdyeL46ZZaueBVccH94u/PPHYWH/JdvnHCVXvHV9Jr3D/axLc26WHMZx4z9ISfRMWNPIvt7To+T3gG/uPwFd/q3KeqCl5tT/p+/+JUEZH1gc7ZecxXHvDk55jg85ihscLXHyB0Z1sDlMDhAG19rywa3EsaWOWsTRB13u7BAA6EdmtCXAk95ZHVG3VSsi3WXcnqRnAtQwuok1jcljy3A2nHH3fltmoZ1seYwPKStG5AORrnHv2F8mN/edoMJi2zRgfCG2kzCUzZ5Ql4VXUWHyGtv+nhrXLPIUhi2pmVJy7oisANm2ZxpOWVTxEz8HepGjk9oi8d4la/ou33W+YbQDunrfsdQyv40BiQ3KCVgKq9ksUMk2mU3qXfMYo2wkhaWZWFbmuPePuP7Q/aCCbAN1nK0zcja+vLbsehYDg50acWqUShLkpnb93ezQ/PbDL5tOVhNRYNGWzZObVM2FefxOet8w9gfETqRCazJhVk1z9kGJ5VNRVwk1I2MMc922OQJV8mcVS6pwG0I0V64Q16VTNMNn11d8fbuLqss48HOAbvBDnvBpGNlHEuAt23JItmX01NWec6OPyAtM9Z5wiTwmPg7lCakxba0GfsJA/eag2hC341QSrEX7vCz23LfPB6u6O/t4mnNMttwvtnw/QOfvWDM0BtiK5uB0+fRzh0+vv6co2ifoi54tb7gn//qE5qm4Y/eechlHLMw3awTf8zEH2NbDn2n33k+J/4YyyRZy8KCyEDprgUb13KkY9d+fRroWi6FLihqhavcbgExLhN6jixUbcoYXW0DcNrE3pvXiq1sBu5guwBnnmPHVH4kZcLEnxipec3d/p3vjL8d32FTlJ03TUJAFHFRExdV57dStoVttUE+xmNciRe7/Yxy9dazWNUNvrZY5xXzoiAtGw57AnJtyyIwwTjLvKTv2GyymoErCxat8sRSCppWhmmk4UBpQGPL+Nmmqb4NP2mlq7ZhBU+GLpNozJ6xDJWmakEpYRhvMoqyYGxSNx1TU1WD1jfeXyN88bdB43b8yX7VjYBdx2pwdcPlpmCVVYwNgGgayOumk/tWps4hr8UHmJby86OBi+/IsZxuSpK8NPcPTdU0TCJXaj6SgheXa27t9UiykuOdgHFos99zOpDpaouqbohci1VWcTpLyArZp6ys2eQVXiBJrtLBKdLUq7W8buDaDHxNz9O4WtH3bG5PIhxtMRkFnOz1cGx57vkq42QcshvaDAMbWylGPjzaC/jsMuGwL/7Vs2XOv/vVK5oGvvfOPos4ZxPn3N6NmIQ2k1CAW98Td7yrFbuRg9ETduFFLWsKwiC6tvT3am29dn5ta3scXC0L8E3TEBc1kauxlSIuSrSqu2MGry/KgXAaoS0y26oR8BnnNePQpm4gKWp2ArtTytzd+W7A1GvXze/9reMKSweQJSh6Evxi2wJK+n1hXV49F4YRREYY9Y301KzGut6WmawNK6M1RD0pI59OUUEok/G6AQzYGu/LpPzh28YjqLdMUGMAVN0YWaoS5i4IBfC0ssHChJYU+RbM3nx/4z35XbIR4Or62zTMvBLg17jGQ8EWAHaBNUaeqjWgZX+KTN5DG1rTbm31h9UIEDRBNVhKJKZttUiWbsFhEMrjXE/2N1536aTKMHvNaimPjyL5B+ZvXLi6grrG6oX03r8FvgA24AaYT8WrZ9vw5Eua5YLqk89ZfPyK0fduSwKovpbQmvGusH1N3dWbqHv3aT7/TLyNvYE8xnHl/C2mqOEY9+oKfJ/y6Sn5f/uXPPt6xjtBsA12cVxhACf7VH/+36PvPpIKiixjMvE5O92w+vglp6cxt+8Nha2bX5mORSXPc30NR7eFzStWciyLfAvqChNO5PiyWNHUry88dCNsAKuZPL79+zSB0DDBrmeCeuYCAHt9OX6OKyxz++Fbllu2vCzlMW21jOu9vpjwOxjpVuajEM/S0O1znc7wtMsy37BjiUdqU8Smu6zi1ea0u+mUdYVjSUddm0x4M20xsiN+cfERZ5sr3hrfI7SDbgLoWDahLfH5Y3/YyQAlRKIgLTPyqjDBC42ZpMhqcztBAZG0OpbExudVYUDcdnW1DZCRaP1cvF2NsJClCVy4yT61k5LW2tCmXLbBKgA1uZHEaiO9UvBaKIFIAoWJEXnu0BsSOVHH9rQT/bHnd5NU26zUt5PKNnRiVawo65KB22PkbQN6AtvjbHNF1dQMvYjvH7oEtkdgC8PkGyYtr3L6Th9LaZ6tvmGWzfmb08/49aszfnLnFhPTv/ZqfcZuMGGVr4X51H7nF/r1xacMvIieE7Hn7+Fqj11/j3WxYj/Y4xc7nzBwezxbXvH/+Pyv+frZGcEHgTleNb7lk1YJb43e5P/y6X/N/cE9Bs6QuEjZGQ+4OJ/yi1enXF/NuX28xzqPWeQLYV8Nu3eZXnEcHpPVGUUprGJhmGCtBTB6lodrufSdAW3FgmWAokyKFH2n3zG+recwrVKipqAo8o75WhUrnq6f0Xf6jLwhWolctAUp7fVjK5uSsmPqN2Xc1VJ0HwXWd8df+3NhmC2yKqPvRszSJbal2RQxA6tHXudcp8KcNDTM80XnP+0kam2CsZnAO0ZW5muPL+ePmaUrgj2fqKuLkEChvtvHVppb/ZMuUKpRNrXpxxM/Si3yI2RB09Xy9x1IaMrua8tcNrR+QZu+2yOoA7IqZ5bNDZBwu8qFqqnRTcuMvA4aW+9gy3QqtQ0SqtgCxm9vSinquqaqS5l4o+g5Eb72O/m7yPU0vh503lbbckiN99ZWGkeLdHSVbwzDF9Bz5Lou6gpX21wlc6q6pue6vL+/T2gLq2ihukWqvC6I7BCtbF4lZyyzNR9fPePT80vePdxn5A1ZKVkQGvtDNmXcKQ4Abg8O+Wr6jIHXo+eG3fnvR31WxYqiLlhmazzb5eliyr/4+re8fH6B/+b3OzCmtYYKdrwd/s2zX3Py8JC+25fk1J0+15dzPj2/5PpqztHxLpsi7epYZAzWzPMVu/6uYRQSIieUypFGoU3SrG0W20In6sB9e44UChQm1Eqk3CUVWlkSvKR9NnWMbRjVpIg5Ly/wbd/UGdld4FKbRF3Wlel0rM25LcmqTK6f7pqyukWWm1vrAVeeMgmdIp2zlISARJ4Ul7eSTYB1VjHw9NaD1/5rx3uznbTbWvH1dc4yreh7FgPX+L0QsNV3RKZ6e+ib8SvP+F0Dw/Z3jtoukCjDOioDFlrmsk2y10oATeQ25FXN1aaQfj1bfG1KbcPjOudauzhL07Gkr3kWO0VB8/r7/tZ2U1qrlJJuQ8cicqwuKdNuqz+Mv1MYzNqAHbrglySXUJnQtQhdVziTRjyf15ucum7wHc3d/T6eu5XVusYHmlUChLRSnG8K1nnF1xcbnp4tuX3QZxRo1rnibJkz8iURNy0lz6Fu4Hjo8vi6kk5Ft/U2N0wiG0e3KaAhSsHFIuU/fHXNixcLfvRowiKVv9Pawqph6Gn+3Vczjt4eEzkiWd7ZCbi6inl+vuLycsPRUZ9NVjJPKnzHwrdFHrvIK/ZCm9KkpwbmWLZsdSvn1Urk0C2wf439VcJOxnUlElyzOJCXDZ5uyKkNmy3HfZ0XhI5F5EnIkG1tm3EbtmxwRUPkWeSlhBvZ+kYIkvpdd+nXt98PFqeXAsD6Q1NnsUE9ehsuTuUNhqYmIwgF6MRrAUOeYUuaeptW2noGWyloWyavlICa4dj45gowEqOuy1Ebh20rZb0Z7tIGlcA2kKSut/7CqjRsX+snu/H4m8+zXtGcn4mP7ns/lL9N4m2ozrc3pSQh9eqVgGM/2gay5ImAhHCwBZWtrLHtTNwsBWQHoaStWhpCfwsK25RO2Po9y3ILHMtCmK/NSvxvWdr1YZLn8i8ItrUXt2/L315dSZJpzwBTpcQbmibgeTRnp5Cm6GEPrRXWsA9+ILLjgyM5z+sVTVnKxVXk8v77fdRwJHUZsD3vPfGdqjfepFnMsd/0+PTP/xVZWdO8fAlpilqvJNjGdCbqH3yP5vEXKD9AHRxydrphmhRkT1asqwr3dM3x4Aw/+hupQxlP4P5b8rqttzXsCXDT9jZFN1nLVz/aypTb89sCeZDjNdw1XtkMiozmxVOpjBnvyfPF6+6abT79SIBqXaP+7B9u5c/D8TbZNt0Im5jnNK+eo+7chy8+gntvyHXy7UAk4Dw5x7VcRt6wm5y+P3mH080ZB2FDzxUPXuSEpnx7g6elI+wsPievCvpOhGPYFalkEEamZRgtpeg5AW+MHvFy/aoLx5BLXG3DNNh2rbWhHwplQm8gsL0OBCqTmnjzRkRj9PhNRWsb92yXVR7jWJodf8DXs1c0FIz9iJE37MDE1n/4uiTVtVwu0wtCW0I7Wi9XWqUUVU7P6Xfl3mVddsCjairWxYrn6xdETsiOJxUBoR3iWh6O5dKYqHmgkyCKLKs0pdcFvg5Y1auu87GdeInXThMYkOFZNg9GtynrktPNJbvBiJ4TmoUARWRHppew5unyBXGZMg56WJZi7A/wtc8qX3PcOyS0Q1b5mqIu8LSc177TZ8cfMPZ22PP3ZPXZgOee06eh4c/u/m2erp4z8CL+j//qvyXNCp4sXnS+vuPomLzOyaucPzh6ny/mX/Le2OFO/5iL8ymLxYYiL9nEKbat+dR1GXo/ZxIM2fV3uTe4x8gdUjZF954cy8FWdnfM43JDpSsiJzJgrujAC61nDYVWNmNv0p2zoi54tnqOVrYA58YirVIG7gDbsvno+rdcbKZUTc0/fvCfd383dEfd+0/LhE25oW5qnq2ec39wl89mn3Gvf5ee0/9OqFO7tT6rVuaqSsWD4R2uU5E+ttUYrnbxtUdaZYZldDoQbZt0Spkgir8LVXc+RK00rmULWDFeunbibJteUwtFrbbF9e0YaCWu7aaVrG6XbMvnm0YY0ZbBFga+wdMmuKmxAFm0uIxnZGXOO5OHAhDqXLxzv2NTKGzLZpbNCOzQJKTKPgnQLwntoAOVlWH+W3AZlwlX6RWe9sxiiYVvCyDUyqbRNW2YlN043RhsGfU2fCkuExPaktPYHnUjY9AyKakk0gd7Z3BE1VRcxjOGfp/IDbrk08AOOn/26VoqhUa+j1Iw9gNcS+5VB9HEeGtjqrqmsZouUbfnRgy8iB1vRFGXaAOYfO3TNA0Pd24zz1a8OXb5Hz/6giwvuNhMScuMTRlzp3fLXO8lPzx8xIv1K1ztchjtcnUxY7HckGa5pLs6Nl+5LpHzuSTf+gNOoiN6Dl3FRmCLLL9WTScNjssE325wLbc7nrD1u7X3WtvS9J2+SaqV8XS6uUApxcgdYllSJ9R3pU/xy/ljpsmCsq74k9s/7SSsPSd6Lfk3MX7Hl+tzbvePeLx8ynF0SGAHrzGT7ZaUlTmG2yijezse17EkAQbG2+XaAmpyIzVVSior2u+/zc61YK6dvFuWMqmfqmMFZYy1n36yFSYIqhsDiu5xTWNSLWmoOvC9ZfZaUND6DZ32+c3/x0XFxbogqxreOwg6iaXs6+9ecNE0LPOSwNbdApQodJquEsbuMHJD1WyDbIq65nJT4pvEUaVE4tkm196UtNpqOw9uvZdN0+BpxaZqCFwLXYpXU55b6jd8xyws2RaHRuZ4sSro9Vwi1+qkkaEj587VFufrgrysiXwHy1L0fAdXK9ZpxW7kELrbfkeLhqxq6HuayLOJXM0kspknpRBT5tooqoaDgcMqq7m7F/Hzj15R5iWrtCQ2QUNv7PqSXFs2vHvS53RZ4I8tDnoOl5cbNsuYPCtI4xTH0XiezWeezShwGPia44EjtRrmfPq2CaQxQKwBslICbxzDJn43A5/uuokckUW35/LVMud44DLwNZYlALvniW/z8XXGLC4oq5o/eiBzzrJuiFzdgVJM7UxRNZytCk6GLk9nGUcD8Yv+p/yuvx8sbqTImiA0EkhTUj8YCasVRNAfbH2B00sBJL2h/E2bVnoT5Gkzcc8ziHqoH/8MLk9N+mlPJtWw9TuCAC7fhIsU+VYC2IK9Fgy6ht1rwWpZbD1/ZQlxLkAriLbpl2UpjxmMUO9/H54/7kBqM7sWX+ZJb5uI2Z1NQzIPxlsGs6llX4MeRDcObSu/tQzgS9ZyvKKe/Oz8Jc1ygbr3SI6Ba+Sv7ftv5a1tgmrrC4x6woJuNhIuE/XlMfEaXJ/m+kKe/+QE5bg0ZUl1donen6COTraAM14LQJpewXJJdTmjzkryvO6qRzg9hR+c0Dx/LMyd70MSU3/8MdZ778nf70y2TNzVGRzfk1Cf/ROYz+DVK4rLBYO+y2Tib6+x0Q5cnsl5Wy1lcN17BEVOc36GpRVpLbfgHd+R7qLbE3Ac1GBIM71GbX4uwMsx16tlgmZsd3vsynIbOGNp+V1dQq2/nS28vQabRhJP+wOazz9BPXpLztHhHbkGbBv1xjswvqD8i7+k+a/+K+zvvStdjG0673wqf2O8j8r3YTmn+vf/QSaFwx0ZKz/5R68Nv3WxQRETOaHxygnDteOJ5K/v9hm5Q/I6Z5kvuUqvKeqCR8OH9J0+n8+/JC4TzpMz6qbmKDw23WgVWZUS2CF/5/hnXCQX1E3NG6NHXKdTLuOcpMxo6yRsy+rqDYq6MhPPpgsfaYGjhB8UksB4Y3WzUY1ZTc6FtTCBNZ522ZDgmbS+viu9bUopht6Qp8tnTPwJkVkBf/1mJvKfgTuUUJMqp0H8YpEdoZ1B+ygaAzjbMvi43BCXCX1XZFtn8RmrfM39wT0CO8SztoE67ddWBgfS9aiwiJwQVzvEhTBVfbdHVVfEZYKnPS6TS7SyuDc8wbVcyrrk5eqKo2jMrZ5MXH3lsyk32JbNdT5lmi44XS9Iy5KikOTNTbnh2fIVf3j0Qx4vn5BXBb4tReu/OPuYHx6+h6sdxv5O5+m8Lq44iW4ZBk0+kL+Zv+RsvSTqBRzf2gNgli4YuAOu02tJMC0llOLN0RsmCOkMrS3SXKScw2GEZVk83Bl3CaRX6RXrYt0lqbYJqGVdGulj3fn+4nLTdfA5bYrmdz6GGsOiaQoKtKUZeUM+nn7Ku+O3CO2Qw+DISHYc3hu/w35wyb98/Jf8nz76v/FHJ+8z9sedFHKezQnsoGOMQ1tqBv78+X/gz+7C2N8hLVPu9B7x7S0xiyGe9nAsm8qyjeQvwra0XG+GLUmrjGW+pKwlIdVrGtIqxVK6q/HwtAdKgFu74PDB7ttM05kwY9onqdIbtyJhvttEy7zKJTlUWR0b285GaxpsJCBJmlkFoN2UvrahQZ4W5jCp0w4kBXbAG6O7nMfXaGWhLZtZuqTv9PGD4DvHpn3tntMzY6s0Uiun86++fla34yktU+OjE/XCNJsyS5fc7ss9qvU9d3U+LYvatLU++Y3z4pBWqSzQaJ+ahrRMcSyHabpAK4uT/r5I4suK0/WC3bDHcW9PGFztkZYplrJIihXLbM1lvCGtKsqioqilPuh0fcn399/m1eaMvJJE3Lwu+OjiGz7Yuy89du5WJrwuNoy9HQLbx9Uuq3zN6fqa881GxuBIFnbSMqOsKy6SS1ztssxXVE3FSe+Iuqm42FxjaYs0N/Uqwx6WZXF7MMDVDgNP2O64SLndF3+pq52OTW4rT1qwnpQxtiM2AMtyXkuy7c6VOe6WYcQsY1N4PH/O3WGNr332gt1ucefB8A47/py/eP4J//fP/hXfP7jHJBhS1SXKpAT72u/AcGgHrIsNf3P6BX/rRHWKjm9vhSmSd7WFtixsq5Hj7GscLSXlgS0T9LIWH1hRN+yorXer9Q6+fi0KUPS0xVt7AbOkNFK9FjTLhF1YPfGR2ZYy+9N+3m1Z9m9LU7UBV9/utcurWhJNjadREs5Fzhk5mrf2A85XhdRT1A2LtKTnWYyD372YpZQicqQqQQJrhA20LYVzI124fU+WgqqBvKo6H5u2FNOk4npTcHvkSVak9TrTVJnFvPYo5kaa6toKR2vSQuS/nkGicSGBX/O0RFuK/b7bpbjONzmD0OGwb2T7liKv5JnXWSWM3SanKGtyw1jmVcPZKue9w5BXy5y8bLqU0C/O1rx52MNSknJqKQlEmiclPS1MY9PA1abgapmxSgt6PY/hcNjNKdKy4cksI3Q0l2s5/nd2ZB5+uS6wLEWe5dR1TW8oC7l7Ax9HW0SuxTKVJN67Ox51I4xrK/9s+zAbw9amVdMBcsXrSbT/sa2VJD+ZZdweuQSOxdikzMq+evQ9za+fL/jnv73kwUGfcWCTm57MdV4bQG5AvK3YZBWfnq6BPn3PIi7+Y9BVtt8PFttAD98X4OKbOoLNasuEtFLQPBYWaXYlE/LxgQCyVsrXNMLowNa7pyyZ0B/flcJ2kMc039rp1g8Z9MDJt8CsXQ1u/ZR1Y3KAzX4pWTHFdgTELaZb6We8lkRW25aJvOMKG2dZIrPsD1BhuGXK4HXA2AK3tsPPvvkYk/56+UrYJQM4uiAZ33yIxmsDcn346uc0qxXqrfekqqPMt8e49ShaRg5pKXldP9iC57oSpnA+NTUSKSrq0/gSjNMksUiHm0bAnqXowlraFNTZFRwfo4dDuSFnBU2coKZXslAwvRJ/ZCrhRc3ZGZuPnhMB1k9+upXNxmua3/4aFUQwOQQvhAdvwvUlzaspJz+6jX28K0Bxf19ScaHzlzaXZ6iyFPB6dcXJcY88r3mV5ORxTlU15BdL3Hv3oCxQhyc056/g419JyupggDq5I+e9ZayVtWX5skSAYnuMvz0Kti20W0/hWx+i3M/FE3twYhY9GnmvT75CDUbYf/ePab78HJ49A9el+fg31PMl1u5YWMc//BnNp7+BMES9+R7W82c0z5+S/tf/HxYvF5z80//9a7vR9s6FjfiyfFuAxSJfdsxD2ZTiiapyBm6fq+SaTbFhPzggLhM+m33BR1cfE9pB51sUmYPfBTYcRydcp1d42ufN0SNO13+J3SYDQscM2ZZN6PgUVUFsirW1kvhrgLTMujLrloGU4BsjwcPq+qvKuiQu0i6E4DKekZvEVK9pCLRPz42Y+Ls31nVvMozywe5rH278fjsxLrlIzxm6I9lPM7GX4BqRCyZlQmXKq//q6ldM0wUf7r7HYXjYsZACEkvWxRpLWWZSqfFtD8/yOplj1dT0nR6LXMCXSBZ7+LYE4myaDctsQ1XX5CZKvmWzWo/lVXLFg9EtdvwBRV2yzDIu4iWnmzNWecxFcmmSMmMCfJ4vT/mrFy+oafiT2z+Vonc7IC5j/ubiVwTHAbv+HoqG27073B8+48Vyzg/v3+bucI9lvua4t89esNsdS9dyebl5SVqmrIsNZ+srDg8nFHnJ2eWMoqqY1A2n6xVvju9R1SXH0RGnmzN+dfmRMDLegFu9E7SyGXlDHBOvH5lezMzE+ZftMW4aUK+XuitlUdQiOW2ahrdGb+Npj1W+5iA47ABwUsY8Xj5h4Pb5nz78Yz6ZfsmXs6e8O3H4xflvuUoWHEVjOUa3/ohfXf6Gnhvy1uhN7gye8Xj5lP/zb/4Fz69m/PX/5r/g25tUU1gd4yLdmhlxmXRSu5sAJrQD5vmStBTms11AuQlu5ApWHeNWNhX7wR6LfNl5wEoD4EReSpd869s+RV128s1v6+FaprYFittbmoWnbeMHLcV3WaVcJVcopQi0j2UCEQCSKqVv9fFtj4Gp8rgpVwS6sdayVO2v5FjJPWOazug5PXMfkRoGmu1xSCtROTiWw1ezl6zzmEc7d9kP9sS/bM5zVYt/WNjOgja509MehQmcaprGgJA1kRORVzk9NyCwPaq6Ji5SNkVCVUvNRssZWYYB1spini64NThgx08MkCtJypJFvqSsS2bZAt/2JBVXaS4213xycYlWip8cv4tjgHJcJnwxfcIHexIipBUc9w6ZZyteLJd8cO+Ek/6AVZ5wb3jIXjARRloLYzpLl/I1m3OVzNk/GFMWMgbzsmQyGnAZxzzcOaauaw6jXS7iaz6bfk1aZgy8HkfRPrZl03MibCP5DAyAz+u8WwBUgnpe29pJtPjNZVJ/r38Xx7JJypSJP+6uhaSMeb56Rc8N+bt3P+Sr2XOeLc9xtc1vL79inqbshrLg9+PD93m2PCV0fO6FtzmMznm+POevX/0V59cL/ukb/9vX9iOvGrNmK3MvT8tnSGLASTsdU0pkqoFrkSUVeSXBIjfVLbXQdN1zt4EpVd0wCR2SovodGhbZWl+YZzyQN5NERQ7eLkyaKWLzeiJ3Cw6SsqIxYIGq4jLOxfniaBRSag+wySuRgGqLvqs76ervYn9aSa1lEEdjZI8NkvgqnYlGCmkJiHa1RqmavBL5pK3g2TRhk9c8GHvsRu5reQR10xAXsk951QJo8ecJkyZy0MCxumCYvBRmy7UFrKWlBBLVTUNR1uLiMs9fGuB+lZYcDlwGvsh/i6qmrGtWWWXAc0XoaPKyxFYSAHR6HePYFh+e9HG0MMxF1XCxyvF3fHqu3KePTf3IdJ3x6N4Ok75PkpfsD3yOB4659ypST3MVlzSN6e2MCw4OehRFxfxyzqJcUI16LOKcW+OApoG9ns31puTLy5RNXhG5mpOhi6MVkSsWnZYhB/G12gZMinr59fPanufGSKatRnF37KHniqxsmITbxYOkqLualR/dG/FkmnK+SPF0wJcXG9ZpySiSz9EPjnu8WJT4tuLe2OF85XG+Lvjzz+ZcX8f8H/7+dxdMu+vsP/obEBCVxML2RD0JX4nXJvTDsGWnz0266Y6ARW0LIMsSAYQtq2hp4/8zIK9poC7g1TPY3Rc/V1WIt6yVjrYjr2XYtIZKbT1hlQGCbSJqU0N9wyuplPxN22E4mgiLWUgwTbNaSJcgyPtKEwlWyVL5/s5Dw0zdAK8N2/9XFnxbOtHUW5AdGr9nmphjuRaPm6WF3QwMaOz1UX/6D+Tng5E8DuSxrkfz2W+kmsKWEBip7LC3abFBtGXOwp5hOk3PXxiiJns0j7+GxQL9/jtyXI7uyN+DCXtJaC4ME7led2+nmMe4lxfQ69EsFxDHsmjQNFCW+Hd3iT95RfTWDHVwIvtw/or0bz7Ft23U3fvyPncPUQ/fRH/2JVbgkn7yFP+DB6hWJuv6wkxPL0XumsTCWh8dEb4d89bhEP9Xr/hmlvAqzXl4vcYtTT9lnsJqhTo+ofntb2hOz+R4KQuefyPHbGci/+94N0KGHDnW7UKGdeM8VyZIqZW1tvUpg4F0Ij406aevnkty7nyKuvcQ9bf/Hlyd0bx4Rr1Yof/+n0pfKMh5OzsTgKwd1NEx3LqHn6Z4t2bfGX6RHRKXCct8Sd/tcxgesik2pLZ0JVZ1ybPVcxzLYccbMfJG2EomhGmVcBKd8GrzilUesy5ikjKmTVCsqamqiufrZxyGhxKxXhdM/AmOdihMlH9hkkxbz2PTNHh2m1BYEzo+SSm1HrZld+xB++GssLq+Lc92iIuUVS6BPZtCfD+V7b2WXDf0xQf2cPDAeCDld+3kdLvq3bIrN4dnY5g/kUICpFVCqCI25YZ1sTL1Db4BmhDZEf/owd9HK03fGZCYsupZMcXVLr+9/sRUU4j/0zG1JLZyaL2cVVNRUxM5kWHVhAUYeBH7wR6fz75mli75yfG7KBQn0XHXG9jQ8HT1jF9dfMqmyFnnOXFRME9S5klKWf+cpmn4m7PfkhQyuXs4OuY6XXBvZ8TPT0/5wf6CIwNyX21O+fOnn+JYNo9G94lsAd3vjt/mV+dfEToOH1284A+O7ws7p2wc7TDNpkzTGYfhQQd67wyOmO6uOer1+PU3z3n6/JyzyxmXcSzXhqtNsuKaO/0TfnH+MU8XpxyGhyhL8Wz1nJE3ZOgOUUY6rJVnQI0mLjfU1IQ6RLW+cJSRG4pUWiFSPoVixxvxfP2ch4OHaEvzcvOSwA6YpjMeDh/wd2/9ba7SK54sn7HIVvyTR39KaIe0xeNPF6+4NTiQzsrBCXf6t8nKgnujq++MP6BjJJMyoTbpoWmVdGCnaRoukiscyyawAwI7NIyOpO22yZPtRK9sKsP5mRAOaq6SK4bugMgJO79whamV6ACYGVcIEGy6Y2Vkdk3dgUNZ4NiOQ8t4spUSX+A0nXVs4iqPOYz2hFUztRB74bg79iemUqK7LXavIXLatqT821srlw1sGWNt+mppjmUrI/fNcQwJ+Ht3foKlpOImLVOUUizzGMey+XL+hP1wjH1DrmsrCchp+yhbmfhN6TlA4PhMghFPFq+YpUs+3L8HIPc6o4JwLElzbZNV2xohgGmScLa5InR85tmKpEglHblpKOqKO6MhH19e8tZkxcSfdPUXvzh7gW3Z3Bkc4mqXkTvk7uCEz65fEdg2H19d8P7eAW2Kr2M5bMoNq3zNUbRHVmWEdshRb483dzP2exGfeC7PXpxzfjXjKj7okpmzKmeVxxz1dvno4mterGbsBjsopTiLz+k5PfpOr/NbW8oxvli7uz7boJp2E0VF3VUpCFtp0XNCzuMLbvduYSnNZXKNb3ss0jW3B0f84dH3mGVzXq0umKcpf/fuDzq5r1YWp+sp+9HIhCvtsR/ukZYZV/3B7xh/FmlVk5Q1ttXQc6WKwLVV14d5HQt75dnKlLbL9LSsG+NXM949vr3cKI+bpyUDT+Mbb551g+ZpHWUtxhRwIwBWehVbn2fzmmNp2++7ZRcboOfYXCe5MHM0LNOKo76DAuKyIi8bDvoOmZELHg0dCSBp99m8yO8Wpm63Fsy62iSbGjCWVzVpVXdBLB0Iti3+Jw9HMhYd3Z3zZVbiaYuvr1N2ew62gp6nRbprjkcNxidtgoNskbSWVYVlpK07oc2LecYiLnhoKiomob31btsiz53FJUoJAFJK+hqTrGKeVIwCm7SsSfIa37E6ZnFvFPDicsO9ScheJCz6Iq14crHGtiwO+g6WUowCzdHA5dmVxnc1Ty/X3JpEN/ZBfIE1DbdHLlklnsPdnst6N2LU9/jSszl/ccXiasFqMzJ+VMjKhlVWsRc5vJonXK8a9noOloJXy4Khr4kMaG2DjZpGFgKLWpYEHet1f2ljGOf2nDuW+FhDx+JiXXIykOe7XBd4tsUiqzgZuvz4do9pLHUfq6TgD+6PiFxhXLWlmG0yhoGLhWK3JwFDSd5j3Pv/J+AmNwxU6z3TWkBdWQrQWEwFgGWJ8cmZ5MgkFvC2f2yCWjxhvJLNFiQpS57XD0xvoKnfSOMt66XMSLP01mPWbtoxd4R8m3ppGUavZf1aZq5pZH+qimY+A61Rwx3U4S35fQvsIhPSMxrL/oJ41hp3C3Jbz2Gb6tr638pyy1Q1JqKpZUmDcBvIkyZyfHYmBuia99pWgyhLjoVSwoSVBeoHPzUSxmKb+mqpbSKpb+6OWSLsXhuC0+uLn3G9AqBabrDDSNJCW+lwvKa5voRXr7Yg3HGkT7GocA+GMJ+LNNa2BbjHsbzfNCV9McXu+6ij23Js4jXNyxfUWSn9jLt7UJY0n38iIBNQnsf511NORhG2UgLsQnPOtN4G/TQ16s59rKJAf/OUO+8dEHxzTVODPTThPL0BrBaov/V3YL0Sz+C/+H/RfPIb1J27Eo60nHfHgJ4JX/ICufyVBfFSrpm2+sRS20RT0m5xgf5AmMVWFpynkhj85EvUBz8USXLTQH+EGo7Rx7dlgaU3fC3BVt19IOf73hswmqB+/FNU/l0JTm4kY1pphq6k5Q29EVmV4WqXWTZj7I87SVdSJpRNSZwnFHXJYXjI3f4dnqyecr655vP5F7w1erNbXbYtm8AOKZuSvj0wlRHwcHSHT66+Ii5EDlfTENqvy+Nsy0Y1FXlVUlRld5PLq7JbLRQJU9X5laghMyBUK8vUcaTdpM425eB3+scdm9MmIbaT7Q6YmclsZEdYtPUgW0+ireyuV7F9v42Rv23KWBIElW0m0xLM05a8O1ZkJtYSiPLj/R+SVmkXpFM2JVZjUVKIlFQLU5maAvakSjqZcN/tsy7WKKWYZxsiO+IoOiStUq42V3w9f8rjxSlP5nN8W8J/XK27hLJB4LHMMtKyZJ6mnQzqbL3GUoqnV1N6UcBhKJPOdbHm6fIFaVlyvrnmMNonrwo+uv6YniPHIXR8vn71JWMjLTyOjrrJHEBoR11q6N3BHeIy4fPr57x15wjPc6jrhpHvU9RVV5/xs6OfEpcx/+jBn/LffPUv+fXlxzwc3eXh8AGrfMWmFHtBZEcoZUnNiWVTNgVxsaEy6aASNKOwlMbTFlRbyWF7LFsmL6syjsIjHi8f873dDxk4EsTUdwaMvBF3+7eZ+BN6dp/CvA7AG6MH2JbDw8EDBu6Qv3X049eu7ZtbYVgsYWUkACoy15VtOazyFSN3YKog6q52Ja+kamDkjeSWajksixVFXRJovwObttJdYqpv+SY5VcZD3dSopqJoJOhFFha2n4Ftd2Jt0hNb9qUyk3y56K0O2FW1qBCW+bpLP94Ndrrnu7mA4tlet2hS1CW2JWxKG44lATpbcKZoZahbT6Jt6S5B+Ca4TquM3Cgh2hoGkRRrE1BkYZvgpMAOqJua9ydvCaNqwnqqusSyFE0tATyudmgaCVGSpN0UbbymdwcnJCbNdpXnhI7PbjBBUnYz4jLmOplzur7EMfJXVzskZUZRVRxEEYt0haMdekpT1BVVk1LUFWmZ8XyxoO95HIZ7aGURlwkv1xekZckyX5OWcg/75eXHXSBO6Dg8P71m4IlkezfYkVAc5B4X2AGRHVLTcNzbJ6tyvpmd8+jOIZ4n/uiR73ddnOt8ww/33yetUv707h/yLx//JZ9cf8P94TG3eydsyrhL9A3tAKVU5zEtESa5MqDbNvOmdmGxlY5qZRPZEbHpogUo64K9YMKL9Slvjx/RcwQI9JwePafHcX+fkTciskNKI4Gtm4Z7w2O0sjnuHdJ3+vzg4N1uAeP18dcYv66AHQDP+L1ck2ba9zRF3XRgxUKJp61pGBh2yrc1cbkdO+1z2ZbCtYXhaRUyZd2AJZPjGhPooiwDDreIsK3O2ILBpmMXZfx+290iUtl5UqEt6Hua/d52Ch7YGtOnjnY0s7Ls/q59zrYaoQUR9Y39rmpjCWnZVARgyPVsElCR7r6squl71g1vphyLVn7aHh8/sKgaePcg7IrgLSWvJck6TRd+o5UwwbZWXX2FUoq7O14ncdxkJaETMjE2raJuSAoBg2erHEcro6KySIqasmoYRQ7zpMS1ra7bMS1EnlpWDdNVSuDZnAxdUylSc7YS/16Sl1SNjbYUX16lHZvs2RanpysC09XY9zSeFhDsavFSBsZPedh3SMuAs3nCvTsjPM+mrhuiQMZhW9vx/eOItKz54zd2+NefT/niIubOjs+tkSv7XIpM2DcVF44lPtxWntw04mXcZj8obAVljfHRSj9mckMuWtU1ez2Hl4uct/Z8IkfGbjjU9D3NYd9hEtmEtjDim6KmqhpujVxsLWxr5Gg+PO5RfKt389vb7weLbUjMYCQApyq3ITKz6y1gcU26aZ4JIExi+dv1Up5nPhVAM5/RvHiC6g+FibQdSU+9/cD0DyZb1mw1FSDQSjfbN9JWIlimoqMq6FyinRzV+BSVCbWxJWUM24C962vpKGzOBTgeiDwPyxIWSDsCGMPBFoi2tRIt63azLiQ3ibCLKV3x+u7hFsy1yaG2s2Xzmmb7O9c3AULW63UPlen2a0Flm67ZPq4yADkayHt1PTkHIKBmZyI/S2JwHPTJobz+ZiV+wBfPBfjVtYThlKVIVA8P4eVLvJMd1N078PKlgMXNRh7vOFBVVIs1/q0x9uFYXvfyDOoKtbtL+OahPJfryn5cXcA331AuEnTkc/d/9TPUvQc0X3wm0tGWxT6+I8eiBedhBLaN3p+gH9zl1o9qOD+H8VjCYp5+s2Uie33xbv7P/6mwlLNrePmUZnolIO3gWK6x0ViObwsaGw9Wc5FCTw62YUWWknNj2duwpvxaQN56AS8em17O2rDAvjCXRSb/f3xbztPVGayXNH/xb8ivVnjxWpJch2M5nzu7sj/fHn5m5XfoDkyiXmlAlsd1eg1A2RT4JrU0KROSMmVdrBk0fTbFWuSN8ZzdYIeGht9Mf8vIHTL2x2iluUwuiZy7xOWGrBJ28G7/Dk+XL0mKVCauJhOq9RamZYZve9Rm9bGNra9N16JWAnZKIyt1te7GqG1pFumKqqnZFAW2ZXXPWwK+7XKnf5vIjoicXud1az1/y2IhtwGl8c1EMi5jXm1ecZ1edzKw/XCPwlQItKmrbWWDHNuGWtU0tUxkXSXePklJrUxpd0VeZWjL7sre86boPDCV6SDrOX3KWibNre9mXWyY+GNcLQEcrna4NxSW5tXmlF+ef8LTxZRNURA4Doe9Hn1X+tse7dzh8+snDD2P24NdPr8+7cDjKs/xbZuqabiKY2wT8f5k9cwkSNYc9w54Z/ecTZHgWDa7wYTz+IKPLr9glqYM/ZD/3U//hPtDiehPy1Tkq0XMrd5J53ES6WjI2B9xq5/w1uQ2f+cOvFieMw6kzuOr+WNOeockZdKF2vyv3/4vWWRzrtNrXq5fcple0TQNR5E8bsfboTSJiZ72aayGVbFkml0z9iaEthSIK/P7Vg4sHX0F9/p3WZcrnq2eE9oBpanWsA3gL+qCRbbkKDqiqiuusysW+ZL/79P/gbPNmnWxYZ7PGDhDCcLxRkzU7/4obBcpIjsUX6yZtbVAUcZg1S3qlHVBWmWkVdZ15CkslsUKX3tsipjL+IqeGxHaoYDIfMlBIDUJWZVJKJAJtBJQLQnBFqoDa5UJq7FQVGz9g623r2XhZborAR4KhUZYrOtkQVJm0qVq2ewGO50sugUMPaeHb/sm5EQ8SOLJFRBpKauTCWd1wmVyZYCohasdhu7QhGJJWqskCgsgtGgn3jVQYysJQ+oWlho6X6b4cG2UqqjqmrKWMdaObRAAVFF3VSlA50tu2V1X2xz3RqYWIyGrcl6szknKjKapidyQsi7Jypyj3h4v1xfcGgy4Pzrg5eoKR4syIi5SXFMJNE0SjgcDDqOIoi6ZZwuqpmI3GPH27i55VeHZkmp9Zc15PD9lkWVEjsM/+cH3uTs85svZM7Iqp+dEpFXGfriLpXSntmgB/CQIebRzyI+P7nK+mTEJ+hRVwfPlKfvRhLzOzYKLzT954++xyBasig0XySWzdElDw34ojxOfqe4+T9pqmWW+ZOAOur7MlomU/lJZACjqkuPokE0Zcx5f4GsJFdqUG+NJlwCwpEzY83epmppFvmBTxPzFi19zGcdsioRVsaLnRJRNRd/sz3fHn3yNHPs1+adjgCLINe/ckKS2SZkgTJpSiriscCyLZVayyipCR4CHZ4vfbD9yxE1VVdiWJHTGJnBFOhMlHMZS0AbetHLTlq9sfYxNBx7pFlhaZtNS8pjLdckmk3GhleKg73T775uwkb5ndZ2LDQLmqrohvRHi06aBVnXNZVyyTiuUkoqLUWAbAGkYP0fSMrWl8MyxvSm8bYFtu98taKlMqI9SyiiS5HFtHYPcM2Q/XU0HOuKipm8qLDLTf7nb99EWFJVUcjyfZ53/MXK1nLu8ZL/vsspKxj2P22Of00WGoxXrrCLJK7SlKGrFKi3YGwZM+rIYtSlq8rJmHGpu7/aoG2FKe554GE8XKUle4ruaP/r+MbeGHs9mqUl4tcmKmoPe9lwA+I5FXtYErs3JOOSN4yHTdcYodClrYQ73IpusqqUz0lL8F+/tskhK1nnNxbpgmcpB2wlt8lKZ5NemA/QNEua0NEm+7o3AmS7oCPBsxTJtOBo4xGXF2bIgdCV1O84lPKdddI+Lmr1I6pIWWUlS1Pz86ZJFnBMX2x7JumlMwNHv46r/U2Cxjfg/fyUAqGWxklg8cE0jHrZ4gwojmizdJkb2+gJ22m7Ei1O5JMd7MsosSzyDuwdb5jGItomoHdBKhWlrpZ+tH9EqboA4M5ttZatNI+DSNhLWtjOvrkSeaVkiBwwC1P6+PN62ab7+Qlif4Xj7+NmlMEPaFkBU5AIaJ4fbMJk2pGTvgK4ypJHQHPJMHtM0AlTa3sc2pAe9lcrW1ZZVbcNZWs+cbzr/ZvOtBLX148mdYwvWy1JY0lbm2hdWWB0dQVnQnEoKKZbUXhD1IAhp/uLfUK9jrMFAwmPu7UvgTZyhD3xJUrVtmuWSapnKqtI6xa4qmq8+l78ZG8Z0bw8c6VRUQYQ6PKaZTuGFYWw9T0Cc7xt5ciOVG20/pqXkmnj5FJ4/l+drOzyDACZSqwHQXF+iBiPTnxgJwPYDeY3ZNcr3aa6vaa4vUJN98Wa2VRetvLQ3lNdeTGE523YktuemUQIkR7uwnIpU+eDEJOEGsq+tvHgxlf0sS/kar2mePSZ9eoX/t38g1/v5Kzh9IY/3fdg7/M7wa4NSTuMzPO0xa+YE2mdTxl3whq891sWGvtsjKSXkYc/f7WSlrna5N7xFXuWdXLX16rzcvOIoPMSzPJbFkkAH2EZydndwwnUy49X6kuPenqnUKKkMc5HXhQTuaOkjsy2bGgnjaCWotqWpDftoGe9WUYmM8jpO0EqZcmyHqhafyUlvnx1P+vGqpmKWTek5fRzlkNWZ6TYr2fUlnGJdrlAoRt6Q/UACI6paagWGwYisSmUlvJHQizZmvpV+oTDJobKvDVYXhNOBGcTPl9c582yGY9nmWO50Kagi44slibUuGLiDjq1r+88eDO+wKWP+9dNfsMwy6qbhznDI/eERPzn8If/iyX/PIotZ5zGutjnq7TBNJOxmEgTMswxtSZF0nIhntCwrCl3xz776OSNPEml3goCR32c3GHXBHbd6x5zH1/z/SPuzZ0myPL8P+7gf3z32uHvem5mVWVlrV3dX9zRmerBpAAwIiCJNEk0Uzfgio5n0IDP9TZLJ+CCZFhoJGSGbEYYAORhgZhrTa3XXXlm53f3GHr4eP3r4HffI6m40HxhmaZl5Fw/340uc7/luT+dzQNJr7/I7Ei/uPKbTeCp9nfY8LsoFLzYv+cXN5/SDxIYdKRI/YhIPO+b5KrthEAwITEDkxpS6wFcCzG/zOwI34HJ7g2/73+7yO0bhyIL30IKxHrGXsKwWrKolk3DayQlbsDgN9xgGI5blglKXHCYHpF6PxE+4ze9wHZdSSciM73pdwM4iX/D18hmf3t3yTx9/l1AFvNqcc84FsSds2l68/1s/AnNd4Lsed8WMwA1Ym3XnW8zs8YdewLrM6AUxRV0iAU0DEi+mMZpABcQqYlbI2A9Dkdspx+UmvxFpswpYlSsCJRUt2tQ2mKmxE1j50MdYpsVoGuPKZNP1qKzss/M1mXY1euf5812fykgPqus4XG1EPrifTDpW5NnyFff6h6JkUMoykUtSL8GzPaptv+A4HMlijc5wcej7PSahSB9rG4TV9/pUuiTTuWVcqy68Zidvl9qENqm1rcdpw1laT6TvepS6ZF0LM6qaXbWIfAQ6VLqm1LKPiRcTvyY1d5wbjnp7NmjqikJLGvQbwxN7HYT8+cufsCwK0iBBOS5vjA5Zl1s2ZclBMuImW+AAyyKXexjYlCU6Sfhs9pRQBYyjAcpxOUrHhCqgqEsKVXCYTpkXK16uVuLN9gJm+VISWxGJ79ACtdZ7uirXXG6vebG84TAd2uvNJ/UDJvGQStc0NNxlC1I/wXc9XEc8r6FN513Yyo67bMFdPmcSjViVK4xvumeZPBMSQrvwsq03ck/bihnHgolhMKTvC8NfNTV70UTCnFTIulqzdjyCpmRdbXCd3TlcVzkv1hc8Wy74u2dPCFyfm+yWy+01if39sWXhv/EZWDWEnsM8r8SvaKR7blsJU9MyjFmlif1dGuog2qVAtn7BWVahG0nO1I0wYFebilHk4StXfIJKflYbSa70baiN7yq7ONGyiTtGsQ2NkftP/m6Zv5ZlN/Z6r43pQkcuViVxoDjs+Z1k9tms5KjvM4y8riNyXcqxuUY+V3UjQK0XKCsxlWPuhy6TWNnPQAFyvUB1wAEEyAXKoXbopLTtMXR9fHbstZEwIWXZSQ+ocVhYkO67zjfYSQfpZSwtEBRALt/rBcKYDWOFbuB8WZLXcq8/moR4yqHWhr9+tmST1/ZZAPencQcQ93sBN5sK5Thsi5pNIb7CrKxpTMDTu4LAk6L5UeSx7QeEnkvdGLJKGLhVrrldFjSNIbR9i4Hn2moKYVtDG5jkAqtSc7GqmG9Kpv1WJeEQ+Ypx4tkOSsPdtiYNpFcycFxMI/7ZyvosI89lntfMs5pJ4rEpdbfI4dnxjZRLoATwZnVDL/A6P6pjcU3qK5Kx6jpGD/uSFOu7DuvShgx5IolVrtPVZuR1w6tlxfUy5/2zEb7rcLupuVhJp2XguYyi31ysef31u8FiC5CaBlPkArSaW/nbTtxN08hkPNvKJH/v0E6QNzKh3qxlcuwHu97GuhLg5AfyM20SZgeknJ3frwVLjisgIIh2zFp7V7pK/GauuyuKh11iagsyvvoSsqwDSgQBxCnm4iXOYCjH8/QLnOFYQMFmKfLFlmUqc9lObyhy2eVMgHFZ7N5blztw2LKRytvJVxvLULV9j8Z6P7Gg5HWw2RQShuO6so1Uw8VLyLTIK/1AWFDT7AC5qwQkjqey/boGz8cZjaHRmLKwTF6C8+iJsLcARYbJctxegnN0jLm7hVev0OuMZlui7u5oNhnusI8zGNBcLVGDGNZAksDdHc02x41j6cycz3GePBEwNruB/hDnD/4OYVXx/J//jOHwKf44If7jP9wB55dfw3vfk+TbWnyrZj6nvFrSfH2D4yuquw2bZcHh3y3h5ATz1VOcJMYoJb7Fd94XkD67xdzd4LiugNR+X56OQbjr3XQdyJsdc+sqWeTYrOHqpaS4hhZw60rOpdy5FuRZ2erRfTg8FbYx28L9NwUwNhpWG+gNcL79e0S+j3N8KtuJU8zHHwmIv//wm5Uu7c3Z+kmQyPNK1zTGdH2EgZIku8gTwNg0DYfJAZ7rs67W5DonUhGTcMy6WhOqkJ7fE6lqLazTpt50K9JhK0FzHe73zsitlEsbje94bKucSAXdpAyEVQEp8K4b3bEaXReUlZPqpmFVbiXspSpxkCoNX/lcrGdM4h79IGZTZWyqNUE4YVOtu0mHgyMgxPUZ+ENynbMsF4zDCYX1KGqjaZqGTS2eyJaN9BwP1xY2t+Pa9r/J2m6bZKc6oGhMg3YcQjcU2Z3j0aPhfHNBVm95MnqC50gyJki9xvn2HM/xSP0eo3CIgyN9j44rSaW6ZF4sKbXmnekhf3D8IeNoTM/rsdVbVmXGMEy43z8lVAGf3j1lU1UEStEPQrK65qTXI1CKX1xeoZSLrjV+qlgVBbebLYMoJK9rflVcc38w5K1JhesoEi/mH5z9HSr93/HPfv4z/u3gGeM45n/11u/j2T7K5+sXfGvyrU56ZjBcbW94tVqwrW7wXJeb7ZbVOuMfvlXzYHjMr26fkvoRLi6zfMl3D77FMBhwl99xnd2gHMVNNmMS2YmuTa9s2Z/WN+VY+V07Ftf5FXvRPrGKbUhM2fkX2yqL0MqGD+MjDuMjluWCXOec9s5YlgvaLsae3+PD/e/gK4+zniycpF7Kz29/hes4PBo+ZNz85v3XXr+lrmhoyOqCupF7sNK1TWdUNLUh9kK2VY42moNkD8+RCppSlygtyZy+66NcRWSTjdsAq0IX6EKSW1u5pov7mlx854uvm4rADUSKaYFVJ9HuygVMx9K0vY6t1PMyuyavC0k7ts+Q0PO53s66BYGXq0uGwYB+0Cev8+45IIFYIgMdBimFlsqHQTCgtkEpIovVAg6NwXd9tGnwXluQgV0liIPIZI2R7bfPDVm4MdTUHWBxjYvxDHf5jKzJud8/RbmqY+GMMdwVd7aKxKcf9GkDhFzHZRT2qRupdKiaikGYcr9/IvUniDw2r2sGYchePGLperxc3bCtKrZ1zbxYsS5LhmHIMEq42mwYhCEboOdH3GQrNmXJBwcBoQq4yRY8GZ/JYkK1IVIhPzj6gEpX/MlHH9PrXzJMIv74jW9ZmaPL+eaSx6NHHWA0GGb5kuvtlmfLBYHyuNtu2awz/uBxxdlgn6/ml8SelGsvizVvTd6g56esqjXzYolyFLN8SS9IcLAJ1zbcBnbySdd6QBMvJtc5d/mMSTTuvIx1U3fP+zaIKVDCCO/FU/biKdtqS64LjpJD1tUaYwxbnZF4Me9O3sR3PQ6TPWpTEzsRn9x9hed6nA0Ou21/4/5zxQ8mi32a2k7Oy9r21bnyDAmU09UC7PfEC1fqxoaxyPeVZdUC5aBd8cW5SAVBUwq4il3VySxbT5zn7IJrqqaxNQO7/rrfpt5rOxfbsWp/5HItIGlrA3rakJibdU0vUigXns9Lgj1JOS3sz7qOCJzawJ/EE19hVjX0LEhxsc4s3XRjJj2IwjQqp63i2IFEsNwKr2U3vn4gTYOv3C6EJfRcyk1FpcXX57k72WRjDLOsRjmSUtsLVSezdBwk9Mai6ryWXsWDnk/iSxJnoQ1aG+JA0QsVhTY8u82om4as1NxsKrZFTRJ6xIHH3bogjXyyEpJAcbetyMqa5LhH5Lmscs3RQUBoFxeU6/C9sxRtDP/2Z+f0+wFJEvC3Hk/wlYNnwfobk5DIa5NkRSK72JZcL3MCz2W9rVitCt57POV4GHG+yAk9SctdFZrH04g0dFkVDYtcfJvzvBbA7zgdu1tp241rFVkucl5i36WoG2bZbiFD7tPXPLeOJNEGSoDuXqrYSyGrNIVuOOwFbCst7rRaklDfOYjw3QnTVBhnXzl8fp0zcx1OhgE6/O2Ju+3rd4NFOyFsvRCEoYAtxxGg5fsdm+eMp5ibK+mjS1PxnCU9mUArJf/3A5mkx6kwYC2YGozk+6FN91wuJQmzDXRpAU1Z7CSbbaBLK0f1PJmot1d/XVn5ainbLgvZz719eONNUArz7CvMqxfgupgggCzDmU7lvVsJ7GSPruNQqV33oeuI1LSrYNACEBYzGRfPk/24OhcGyvPg4kv53d7Q1mYIs0FRgG+srBYBpcbIeOgaurQ5V36v7XXsbngXqky+7joCflqZaivtdRyM1jK2bVpom/S6XcP1Jc50AkmCub6iefqMpqgxZU0934Dr4PUFTOjza1QagjFsL5eET0ryp1f4e+L5NNsNxLF0MQYNpqrkYbNesf3pVzy92vBIOYyCkvzP/i3R738gjN+7H74GzrQAN2Oo51uuni9wXYdPr9ZoAx/8q084+Uc+znSCuZvh3NxAlmF++jc4Z2eWaS0xQYAzHEoH5YsX9jq2CxBNI2D/6HTX6dnWahQZLG5hP9qdd8e10tVEwGNovaK62oUt9SwoTfs7EGoM5Buc7/1Qfscyjs7eIeaXP5GOSf2bH5RteIFuxCvn+x7rUhIBIxUQejZ62lHsRVMutld8tXjGMBSwIuXmS3q+YhTKKncLINuOMqkSSEj9XhfmsanX3BUzykZqC4pavJN1o2mUsBW10bYKw8d3PZTjstJy/2mjUSi7kiofPQ2yOht7IaOwT1YXLMstqyKzsec1yyLn8XhgpbHSXTgJxxYI1l2oTGOldfvxAS4SlFGbmmW5YF4uutXyhobL7SVHyRGe6/H16hkAo3DY9eZ5CFsRqED6J3GomrIbn5ZhlLtM6jKGwZDIgpj2VdXSdyjsm8j1GppdJH+dkeuCl6srPti/z7vTJ9zr3cNBEmk/m3/OIs85Sie82pzz0c1XbKuKUmuWRYHnugzCkGGYcLlZ8mA8otSa25sFgVLMVhsBj8awrWsaA1ebDcviC16ur/je4Xto0/CXr57x/PkV9+8fEijFf/PZX/GPHn7AJJrw/uR9KZY3UlHQpljeZRkvLm9RyuWrry/QuqFpGv7pe4qjdMLl5o6X6yuKuuTfvPp3PB6d4TouuS6IVMg0Fgbqi/lzut455D2m0YSj5LhjNyR8Q1E2BYtyThiHKFRXt+Fav6Ok2EaAdOpJoqxPaiXDiZXEtgsCeZ3xe/u/1/2uchT78T4/u/05D/oPML+ewN3dg9aD1xjrpRNQKJNlkVW2YG0UDrjO7ni1vqQXJKReYpMxt7jWf9fK+FrJctsX2AbkyAJHRaYL5sVCEojtteo6Sq5V6zXTRkrtu2RdB0rdAoBd4I02DZGS69zFZRIPORtIxcLL9SXn6xsrHRWVwDgasCiXRJ5IYPtBz3oeJZ1UArLkmFulgqckbXhtF3iUq7pqnVkxYxyO8VzFxVaChFIvIfIiu2IuEm/P+hWFLakx7J5RqgWXjiMsoGWjXu/MK5qSxEu6BYU2QKjQRQd2G2NYlmsGQY+T3gGjUBYxsjpnWa7YT/pdkM1X8ytKLYqHeS4s8jCU97xcL0ltxdX1ck0xKXk6n7OfJDTGkNUFkRdQaulcbbsYszrnby7OefnymtPTA3zf48+e/pIf3nvEOBzxZPSYqA0F0qX1bBrmec7l1QzXdXj67BKtNU1j+KN3FNO4x1225nJzy6Yqya8/5f7gCBeHoq4IPRiFfbTRvFhdAMJOgszthuGAaTTtGFpPKXsPlqzKFX4k957neDgWHMh50d19W5vaLvwoEie2CzpJtyjQmIZSl3xr+m6nJHEdl3E44tP5lxwlh915fP2lW0GZ2AiJPId1abrJsu9KwEpbm3C9rrlYVqShIvIkTVQkqXQsl7BrLiUNvgVToXIIfRdlWcJCNyxzTRq6DALxkiuk6sJ33Q4kdi1bVoL6egJxezSNEQaplY9OE6+rZXg+L3m1LMU7WTvklTCfy1wTKdd6G9t0Yxus06afAoNQajM8HHxXwMK6bDpAYoxhUWhGkfjxLlfyfEgDkeHunnMClpUr14RuZNEpUiJz7RguhDEMYlfsJa+fK2M6QNReWxoBuC2ABFgVwpROE4+BZbP8xiGv4WAYyVjVDdfLnFrLQvM6FyySRvJMEeCmaBrD7TzjdJpyfrdl1AtojIDROHCptTCBupH9rrThi/MlV+czHGdCEHj8zVcz3jsbMU093t6PO79mY4/HGENW1FxerlHK5eXXVzRavOLhuwf0I59VXnG1KsnKmko33BvKol9ZGwJPgDPAxbKUKWj3HjXDSDFJ/G9kPbgeeK5hW2uG9mcFaMpYe4EAvva8GHYLHMoVCBp7bicfbhnodw/jrsrDAUaRxxe3OUd9n99y+33j9TvBoqkqnCTFSXYTaJNlu/CPspTwkjwXTfbBsbBxxsiE3DRdiTt7BxKGs7izBfDxTu5pzC51cnaN+eQjK7X0pbC09folr8lRtbZskAOoXZ1GG2rjuMLIuTZIJ7beueVcZH93N3BxgclynMePdn7HwVjee3Fn/YiFAFbHE7+eq0Si+Oses0YLsBtPZT8dRwDHeCpjlW1lO0Wxk/Rmm9cAhZXLrlfyfTtBlXTZ10J7RnZ7pQ1k+PoL6SkcTgT4NFrYWj8ApwZVyr/vPZAQlfFa9i/pCcvWnuvbmx1jfHWFuzeh+vhr9LrA8VzcSPazvp5T360JjoYU53PS07FcB42hulnhhXabb78rf/sBXJzLB8HFBdU6Zxh43PsPv4fz4CHm5QuRrsKOIXWVeP/8AFwXf9qjfjrn6k4YpMJoXl1uOVqucd8+pnl5SbO8wPUVyvMwV1c4Bwc4J2cy7mUOz5+T/fwr/ItbvJN9YRrDEGf/SFjiMN7VoLRexmIuQHCz2IUsBZHsoxfs9rkqpSYl7QmonN8K69hWdjhAb7zbthdCthJW8b3v0lW8/NqrbCp6fiohLpaB2Dq5ZTRkYqebhrwWOe699Ih1taGNs28w9IM+q1K8IeNwwrycib/MT5lG045NrKwfa1bc8bObX+C5wiQ6OAIaa7fz6biuYyfrge0eVBZY2oCAuqY2Nb7x7CTXJtLZa7psavK6YFUUzPOco16PTVWS1XUnU12UcwCyOpMkTRw29QblKCahJLa2jCC0CZCaSTgmsSmohc6ZRJKgmOuc8WvhQLLivaUtr29MQ0PDplwQqEBcKY5jQ1h25fB9v2/rQUocx+WLxedMoymDQCZcbfCOb/vLpE/Q58noTUpdcZIe0/f7pH4iPiwctKP5evmKeVGwKrcsiw2H6ZgfXzxjU1X4rkvqy4fJ+XrBbZZxr9/nxXLJ+w/vca/f56daU9aaH957g7qp+XJ+Q900xL7Ps8WCm+2PiD2PxSajl8b8bz78AW+OHvLl/BnTeCKPMNNYJlTAmTCnHodpytf6msvLmfjTyoqb6znLcsuD4Qlfzi+Z59ekQcAw6rGpt/T8lPu9U7Z1Rt1UfDx7xo/Ov+bZ8oaHw30m8ZDYCzmIDyh0K6m2AViOQ+CG5FrCj9Z63QHFFjy0k9Q2VOYmv+68jvNyRqgifPyOkeoHgw5EAGzqDQ4OH0y/1V0/v+1VNzWxLxJF1xFQs63yjgkqdCn3oC4xvnjCsjrvvIBAV2fSd316fo91tbZBLD49P+2ux9oIQFpVK75cPLPXjkcTNt11FNvQk1aKuguzkICZdvzaD34JSVBWUh0yCOT8BK7PrFhwtbljW1U8Gh2jG+nh6wcyjmsbCFQ1lZVxOmR1jus4DNSgAxftq8GI/yzoEanYjl/FwPaZFrrogk48K9/OdGbvQVsm3vYAWuAIoFxlvcRWbmfBa8t+v9pcMAj69PyUvt/rAoaUq3CMhJN4rs9hvE9tNON6IGE+XtQpA2IP7rIFla5QQcLl5o6DpM+vbq/YlCW+ckk8D+U43Gy33GUZB2nK+XrFvfGwkwJeb7fEngDKt+MHgCyAXG9n1lc2IytK+r2Ef/qt93kwPObl6opJPNyNo5Wgeq5nF74Ue0nCK33L9bXkQBRlzfX1nMUbhfgrV3Nm+RzliKztejtjPxlz0jsg14V4G1eX/OzqkvP1ipP+kGGQEnoBk2gsXmvbJSochzC6a13aftStLEog3aaN9em2QFA3mrti1nlsV+Va5MYdw+2S2vAbWVzwyLQspL01ekSbCv3rr8pO8hNf2LxSG9yqwThO18/X+hgbIxUGWdlQNRL80oLKrJQFhzRQUGtKLYAqjhSe2wI/2U5Wab6eF3jOrv9vGEo3YvwaQGoseGsrRFppqnJ2x9L5FJHahFGk2FQNkXK53tZcryrySvNgGom8tDEMIpHJrqzcUzeQ2HJ7KWgXOaL7muIAoE097Ydu53sUuaqL6wjDlAYCmJTr0GCo6lamS/de20pAtGqBidt69OV5Mow9+7MNDfByUTKMFINQ0Q8UDVIB4lmfvXIEhB5Yue3WppnGvisBh46D68OzWdHJhO82JeM05MXthqyUMKvAE9C83ErK5ygNuFsXTEcx26JGN4a7VYF73EO5Du8cxOLfdB1eLUVy/mJRUhQ1cS/mb33rkPvjiMtV1UkwXQuklP3bdwXk9pOA88Ywu1kIy17V3N6sWGVjHh2E3K5yFpvSyoRlTI/6AUd9n1Ib8qrhxaLg6dWKu1XA3iAkDYUBnyRedz0qV86VRupahB00VLqV58tiQQvg2wUw3RjusprIFwZZPLpOB0Al7VV112R7bykX3tyLviGl/ve9fidYdMLI9gBaUFZXwpo1DU4gJe8EVlJpjICw1qvl+8Ig1pUwcGEsP7eYSWhJaOWkRSZBJMORTOrzDKfXw9zeChDdbOQD8fh0lzQKv5lM2slRXTCWbVSW3WtZwcFYakDyXIBbHOOUZZf+SWL9lVEf8+WnIt1UvoSVbFbyXvceQPVacp7flsuvZJuNBb6tl7CuBbxt17uv57ZOJIxkfOp613UYhrv6Cy+QsBSQ34ddgE1ZwMVLzNWlFMC//goCAZ1lbv1/yibNZvL1OJH3MWYn2x0McB6/hfn5TzBFgXN4SPj4BH07h8ag4oDyaokbeETvnAkL6zjCJiYJ0dunu7oOx9mljma2amOzgaYhyzSP357A3p6ApQ9/APsnu1Tbqtixi40h+/OfEL97xnh0je+53Mykx+brvGDwZ5/x1qCHOjlAAfrVFfX1HG80sum2Vsqc9qCuCa7v0OtC2PEwxBkMZFwvXwrYPn1D/LGtX3U4gburHcup/B3r2zQCaEHqN1pg2ILORu/6RdvvmQbKzc6P6rg7z2bzm2AxsQEuEmrh2OAVhTISIFE2FaEn4QNAt9reJgL2/B51U3MUH9pIf5e7/I6e3xN5JS6FzjsPWa6lW28Q9rnYXHOznctpwHTBFIaGsismllU/x3XtRLPtXfStXK+xzA7dvteNpqhLfOXjK/lgUa6YrGPP6ya/n8w+ZRpNOy/TutrQGM1Z74yy2QWNtIE162pF3x9gMFSWpWgBZNmUbOtt55fK68Ku0vlWWlV38khfyYS89XUuywXX2TU/uvwZy2JN2WhSP+Io3UMbzS9vnvGPH/4+o2DUnTfPEXlvrnNhYwKFbjS5zlhXa3p+SuiGtB2OnuNxmEz5z997xC9vP2dRrLgfHfHe3hHX2yUGiH2f89WKyPP4zsFJx24d9XpM4iF/eBpTNjVPxjJB9VyPT+8umGUZDbCtKvK6Zr3asrc/oqgrSl3yg6PvcpQcd+E4VVPhdrIXw598+TO+fXDCYHiNUi6L+ZqiqHh5ecuf/uxXDH4v4cFwHxeHZ8trvppfkuzFHCXprl/P7fPmWHO5mbEoCtZVRuSFjMMh23rD5faCUTjmtHdK6snYNDQMnRF3xS3aaFJPuuJaWfbrgDGrtx2LGKqIQIVoW0AvErUA14i8WDx7hfVKukS2K1P/lvtP7imRAzrdB7OwgJJCKPdgoATYNJYJc32XthqkrXQYJIednFIkiZHss5XYrux1UTW1DceJuM0XsqpebaGHdNu1ki8rNZV9kn3vKmVwMLg2QGF3Ll3HJfFTtpblTv2EyBPZsufKgk/sS6BNT4U8X71iFPY7gJ3V0lF4kOwJULOM6uvnoeendmIp6Zlg2VmqDkSLSqGiBlQbJNVofLfpAlJCC849R0KNDE1XZ9F2UBaO4ja/43Jzx3A6+MZ5813fVoGI97MNBSp12XnBAzewfrIG5Xj0g5T7gxN+dfsFVdNwFPV4a6K52W5ojCENAi7WawKleHdvn01VohyXvSQh8cMu0EYkZU6XZlroAl95bO3xF3nJ/YdH7CUStvOdg3cZhyO5XhGVxetBXP/d15/ywcEBT4cpnqeYz9dkecHLyxv+/KPPGH0/4sR2CD9bzrjcbJhEAxLLwLafJfd6mov1knVZktclsRcyUD2yOuM2u6Mf9DhIDoisvNQYWWxcltL5GHsx2BCnRtKUOrlzpvOuhiRwAwJXWLbaaEwj3kgR1Tbdvem7PhqRpgsz+Zuz1chzurTNVh7qK/m374rPrP1/g3zN+C6eTUVV9hvTxO8m15uyIbI+NQcBYOtSk/ou2jgUWr6/zDXrUrOtNAxhLw53Uk1DB7L0a/v9evqpw646o5X6pr5nF0YbeoGL77mUtUY58r5x4HYJmy8WJX1bU7GtRHJaN0Y8jqb1LwMWYBS6IfVdGxkFLaxtjACDvGqojYxRpYU9FOBhqDSEnoCkyN/JGz37fdcqpFyHb5TMX60r1oVmv+d1slx55ktgi7ZJnpEjqpeiNuS1rb54Tb7qOk7XTfjxVSagMVKcTlMW2xLdGOLAY74R3/79/ZSs0DjAIAkIfMXJJKGqGytRlsRT33XJa/EMtoFIeV7zxhsTjochke/y7ZOEQehZdtV0slzsOP7kqzveOOxzMYjwPJfFfEuZl9xd3PGTX0YMkoBpP0Ibw+U8Y5VV7A8i4sAlsGx25ClqE3C3CihrTVE1+Kqhn3psq4bbjciQ9xMPpaS7ug3n2ZRaWFvP3flR7RXmspP1tuC+rUPRxgaAtefP2S2K1E3T2RsCq0jaceG//fW7Zagtw9WCisEYJ9oBJcdxd5JUELAQRV1gSheI0/rDiETyl23Ei+fZyXdgmcsgEiZOa5ykh/npjwXADUYW8Pnf3L8u9MYGorTyQtd+8LvuLhm1KGTSvnco3jjLjBrd4CyXcHsrHrntVvrvXr4Uqnb/ULYbRt8Eg42R8SkyYSFbv6Wu6HofXSXs3XYt/259mo67GzPHFbDmurvaizyzjGhhgXhjewEtuzW/BVdJsNCjJztJrlIytuuVgJvBeOez07buZDyVr7cMrGUpnfEU8+Jr2Gxw7t/HefQWxnHgboGpNQQB3jDGvXcsXYO3t7jpCmcyxvlbf4j58lPIMsr/4a/wf/BtnCCScalKGaeyBKUYHKQk79+XxYbPPoW7W5y0J4B872jH3FnGrslr9HzF5AcPuf5vf8VVVVHalcSXy5wn6w3Ok2MwBjWdwrNnshjQAvKyAFfhDCd4v/ch5i9+BHt7IkcejITx7g+tZHcj5y/u7UD2xAYgKV/+Xxd2gcLAZi7nL8/kev/qU9nW9EDOu8EeTyNP7jIXFhNkG/3xjjX+9WsbCKwkr5VTDYJ+J+FrPV7th3PrJ0q8mH7Q74JKYi8Wr5cWVuZeeo9tvbUSIY+iKbqJdm0q9mNZeOj5KS9Xf0XVNIzClKaRsI02WbSoSypT7Tx+CFBUrouy/WstY4dpPVgyyTamwXM9Kr0QT0PTsCgK6qbBda4ZhM94sbzkrQkcJYe2vy7+BhjUjcgQC23litbrVdsSdd3swjE2lTCIuV52E/s2yEe8XrvV4qvtNbPiU16tr1gWG9ZVTl7X6KahsEl515sNXy8kqMl1HD6ZfcmD/v2OwVyWS/p+n4E/sMyrvCTgZcowGHaTLOlIyzlJj3i1uWBdbng8PuOt8ZsSBJStyOtagjPimEejY8bRgMvNLel6xVE64e/d+yGfL75gW2X88y//in/48Ls8GT/glzevcByHvKowShEoRRQF9PsJn88u+eT2nDQI+F88/js0puFeeo/9+KDb56oRgHmbrfjbDx7wz/7m59zMlhSlPFOurmasyi33B8c0NBykUz6bPWNdbiQFNHJEXmgaRsGQv3v2IX/29b/jXu+Aw2TKMByyH+1bz5swSrqpSby0Y2Un4RSD6RIZC110nZaraonjuGQ6I/ESPl98wSAYsB/t2ZAY3QECHCiagsJ66RrTMAiGtgNU5HO/7eW5XgeWGtOQeols036wtiu3rZy0DZVSLQuKwXdEdldR47se02hCoYsOEFWWzXUQFnDg92XC6Mf87PpT9j2pVagb3TFhIFJTzG7fHMfBd3bXdd2wk6vaP8pK/y6za7tYVKKNYVVuucuXNMaQ1yV1WvNidQnAXjwmcAP8wO/AYBuKFChfQmeqTRdc03qDNTVth2Gm865WQoKlnM6r2nqS5fg98qboUoVb1ub17TYY1qUsIm+qjPuDoy50R7Xsby0+uRaw2Ycunut1LOSOlVVUumQUDni1vmJdZpwN9nljcIrvetxsNzbkRKTgZ4Mpw7DHbTbnZrtlGvf43uH7PF+9Iqty/ofnv+IHx484sEm3ZVMRuL74XB3FaNjjWwcH+K7PZ7NnjKM+70/fZlttGIVjfCXXUmOZ1lJrbrOMD09P+LOffczN3YKykj66y+sZy6Lgnek+jTHsJSO+nJ9T6JJCl/Ttfew6LoMw5QfHT/iLFx8ziQYcJGP6QY9hOCT1Cxojkl3d1ESefM64OAyCNpBJdX5mxzTdz7cLHpEKebF5ReolDMMhvuvJWulrXblVU1PpUoBjY+y9XmOa1r/1zZevBHg3GJoGG8axY85bSORbqWFeG5sIuZOo+q4Ey9BIIP4wskyO9eJpC6AcC476gbJsnsvHV1uSIKAfeNRNQ+B+c8rc9iw2xnSfyzu2sX1GyM/WdtI+jjzOV6XwL1oqIFaFZp7JPZWVEsZysSxhEDCKPXzl4CvV1TloOwdyXbGpzEttvZSOWG7YaZWUC3klCztlpfF8t/Nvus4O9DqOVGxUjYBG14LpnTyyfe5I/yJIqukb07CT5Qr7K12IaaAI/J1MXBs5T/1QkfqvpW9aUNMPXV4uSrJSczSMOBsFXKyqDix6yiEJPab9iGGkmLk1q7yiH/l8517K83lBXht+8nzBO8diiWo9fKHnUpXiHxyPY948GjCKPZ7eFWSJRzpVrEttZb2761BC5BoW24on90f81U/PWd4t0aUoIec3C9b5IY/2UxoDe6nPs7uMSku9h9S6iOe0Hyreu9fnp88W9CKP/dSnFylGkSIPGozB9m/Ks8YYSUtNgx3rKdfcrn+xaNr7SqplXi1LIl8ziiVRtYEOlLe/24ZA1U1DoNRrORO/cft94/W7wWKeSTdhWQp75TjCFipvx6T1rXyiKgWgrBbi12oL49tewaqEqLaF6LWwMWFsax0CqX9wlXTVBRFUJc52Dcdn8p5FtquXgB2IaqWnr68MKwVuuAMMYK/iXABZK0f1farZhiC4wRQlzuk9Od4vv6BZrnF5KUBnOReQ+/JrOd5WUtqmxXqeHHPL+tXVjkkqsl03XxDtuhxdC7S1tjUfrq3FcOT9Wvmq5+2kq42B+S1mtYSyxNk7kKTTNhzl7lr+PjiWMc22AhyV2jGdrSevKmV8Gg2TQ+hvcfJMWMW33oPRBGfvAOX7nc/RbRqcJMEsFlRPX8n+9PsChlwX1mvy57cEfzey57QPl69w/EAem3VN/OgAhkP5+X5f/r6+lJqVMIZ0ZHlyuUHSP/4BXF1RPL0iLzSR6xK7LqHrEjkOxfmcaGxTVQcD2abnYS4v4NnX4l9MB+I9PTjGPzwRMAm7gBo/gPWtnL8klfGMkl3gUBuU1GiRkOqtdDM6VuJsOyEZTeV8RcnunLaMsa4g7suffLO7XoNox6T+2iuz3X5FXbIXT3FwSbwYZWU+43DEKBx1sqthMGRezun5PXzrtyt03vUvahURuCF1s2Rbb6zULyNQAYNgKBJNN8C3vqlvH8z5av4CX/nWH9V0Hsr2JRNYhW6arp9LWEdJRBQvmdcxoGvLDhS6xFeKTVVxl+foppHEzzzn07tnVFrz2eyZpMAWc856p7zYPGcQDFhXG8bhiExvbRy/dCq2IRut11Pep2BTCSvfBvy0L9cmLmqjuc6u+ejmU27zBVlVUegdW6PctgfOpbJfL7VEseM4jEK5p6+zG2H7kiM8xyfTW1bVqpMA0mD9ZoqqKYV5NJpptMcgELbndJDx7en7DIIBe0d7xF7EbTZnHA26TrW7fM7Ht6/syn/aBWHc5guezuaEj0MeDx7xDx6u+ZMvf4oxhrWt3Oj3ExyEaaybhm1d8//+9F8Rex5/dP/77McHeBZwGAz/0ZMPebW+5sv5LUVe4vseo8An9D3CQCSu4+iaXhAzjgaMwh6e6/FifcFn8695PLpPz++xF005SA64995JV72QeDZh1XidNDO1vZ+Ran16bsect/UkWZ2xtuOqgJ4v4z+NJviuT+TFaOs1bGjwHV+6RP1+F6DTMomhCjv56297FboU9rnRjMIBjutaMKhsXUjSBdFUTUXsRVJ54UUo69krm1LYJSOpfb7rk5nMVtX4VDawqt1O6ve6RNQ3RxnTeELsRba7UXds4S4cxnQyvm7CimP9kXax0LSyNGFk+36PTSVy1Hm+JFCSunt/IGmhXy1esS5LXq2uCJTPslyzH0+5zm46b3PPTzvfZetRa1m/ttpDjr/qit/FmxnRdle2x9CCo9wuBqwrkcq3wThVU9l0ZcOyWLEpM8qmYhqNSGzqsMjXlziOwyQcd4XzWZ3h4NiE3EoCr+yCUstUD4IBsZZruNIVb44e0vNThuEQz1Usiw29IOGeaUj9mHmx4svZjUxyAzlvruOwrjJezBf8nVM5z6mfstneSFq0Edbw0XjMwP5Oz49xEcVHZtOaU7/1Xcrz5z949C6X2xlP53PKoiIMfaIoIPR9gsDj1WrFJJ6ReBGDMGUS9VCu4nJzx9eLc04Hh6R+LJVJ4YT9JxNKe57ahQ3PUaxrSXJuPe2tJ7RNq5Vnu1w/pS67FFzXfi4BVnK8Y9QdrBTRJmPHSiTdpS47WbHv+l3i7a+/slLYsFobxomyiw8S+rStpAIjUI4FrFJ1UdSNLYZ3cI2RBFItgWXGLmQaA5VuUK5raxMsYARCTzGJBQA+nETcGwRESlE2za6yxmm9Yr/JxhgLmhzrM2xfDtBWSY1i8SV6ymWVVXjKpaob7o0j6sbwbFZQlJqrVYnvOmwKzSTxuN3WJF2Vg4vR4Flw3KZ4ynmii2attMhTay2sbGQlvcK82tgFywpKz69jJasy3spxOqALsMirrutwmnrEnqLUAoiWNtBlHHvd2OY2/VU5DhrZh3YeUVmvZBoo4sBlFEvC6KNpSOIrRpGHcmW7g0hR6YDEV6wKzavZtmMgQYDobFtzM8/wTgfUNgworwVoGiMg+94kYRh7uIjP1VOSeNv2VMoit7HnC37w1j63q4LLeUZZVARhQBAFeL6HH/jMNyV3aUDgKYaRYpQEuK7D7bbm1aLkeBDYY1NMYo+9ZNrVi4QtS64cVkVDpTWRL0Fer4cHve4DbW09hR1zoPNWtkx0ZIEi9ppTrtsx9KLwMnZbWLvN705Chf8xz+JsZn18AwFArcdN20qA/tD2B3oCEos2gMZKN6P4tTvH2QFIgMUcjge7r1XlrpRea8wv/gaqSqo4tmsBonfX8p7Klwl8Y3bbayfmRSZgNox2slSQ97m7FnnixNYw9C5RSQBNg84qGQw7EXb3p7DdYl69gijCGU0lJdNVIoktCgGfSU9klK3ENNvsmEVd70J32joLXe9kim0oSmUs6A3Ad6z37bV01BYoZgvMeiWVJUkiLGlZCKtV5vLzw5GM+Wohf7sWkDqVbNdxZF+3ayvF7ckYPf+K5qNf4rzxcLcAcCMSTOfouGOIzc01FAVNLh82zmgsx7BcUnz8NSoJMcslTraR93v0FsxuJSF1MhUcOJB9dNpkWM+TBYHbqx2wtWyxc3gsbG80480nIwBUGqJ6EfViiylrys9fEByNcN58W8CzH2A++wRS8UhQlZgvP4GLC5z7D6T/cGsDli5fyv4cnVrpsi/ALt8K6DNKVu8d7OKEI+OVDESOnAzk65m9Rj1fwOnsGvPv/gLn+38o4NBxIbKg2jQ2XdUDZVnj7eo37r/rrXjEJvFQpJLYiPVGE6qQUTjqys2XZkmmM/m/47MsFyResptIGoNyxH/nOA6zYsZpekZjewzLpnytOLvhxzc/4WJ9gzYNbtMQej7LckPiRaCsxMgyIpWWbRok2MHFxVee9bfII2YQ9Jjlksw3DPsUumTlZcS+sBHbquKo1+tCI076U1bllqeLF6RBzDSasirXOLjcS+9RNgW5zolVwl64T2UqPNcnrzPayPa6qdnUGyvtqhj5I0mPVZHUgBiN54gM7qObT7nazroP224Vz/67lUi1H6q+jRQ/7vX51vQ9G9ChGAZDGtOwrBeY7oNHxir1U1zrtdrWW/p+v5MHP1s/56/Pf8E704ekfoqDw01+Q6krTvvHNpil5tXmkqIuye0C0UGyh3Il7fDHF8+IfI95vqDslXx//0Me9h9wm99yl8/xlcfXi3O+nN9KVLjWnRm+H4R8MX/Gi/UF03jEQSyM373eEetqS6TmPHp0ggH6QUAvCJjlGbmu+eXNK+4Phrw7ecIgGOC7Hr+6+5xBIMC8biq+WHzJ89U5T8ZvcJxIR5vnepxvzxkGQ46SI5T1SNZNTa4zIhV3/i0Xt5MVO45D6veodEnq98R/Wm/o+T3xJXk95sUdf3nx1/zg8PvkJrPXtemkpI295j3HozENmd5yxuPfuAfvsoVIYoNe58N1LJuuLMALlFUA1I2V13ko1yOrtx2z2TJkbYopSBfnXjSlsT2KdSPXsPhmGj6bf0lRV+wne2R1TuLFLIoFiQVRbXBBy7i1/y+bEtdRnf+sXTgJ3IBFuSBUAaNwiHJc+kFC7C0so1jbVWu51veTPtsq52J9Q+yFDIM+Wwu89uIpVVNbRilmEo2pbMhQXuedPLZuNKWt9agbTS8QmWvb7WdoOvVEY6XqIKX0yob6QMtONeQ66ypbEi9mGA7svSVAVTkuPetb3FrPZQuka6MlVMeG9WRaxjRSErRzvrnkF9df8Wh0LMX1uMyLGXWjOUgnRCqkampushmVrrt7sK3KWBYbfnlzSRz4rKttB7zu909ZVSv6QdL5yxM/7q6xQMl1H3u7epVW2itS8z0bmLPm7MERZ0AaBqS+z9IqMj67vea43+fR6JSen+Arj89nz+gHCa5duHu2esX5+pr7gyP2kz1bp+Rxl89I/YRJNLb3oOrSekMVYpymW4JouzEdxyG2naaxl8i5sddom768LJf87OYjvr33Lkab7jPCaZlCo4VVRJ6Ref2avce+5pmmNoZhpKi0wXdN58VTjtOlUO66b0WC6NjnWyu1cy34drrnAGR1wyAUOaRYJV7LDAS+uMvFg+i6FFoTe4plWZN4irbsvv1MgJ1Xse0o9FynU/a1DN6iqAmUyzAMUE5FP6yILHNU1NoCN/mdQeJT1A3Xm5rQMnK5TXCdJh5VI8frOS5haANPHKdjm4wFgaVNRm2MIVYCFNpwG5GigjFWetoG2dhwlFZW2kpPs1qzKWVhJw5cRpHXMWetBy6x7Gde624KKrtkupAhkaQ2xJ7bMbzni4rPrjecjWORXAKLoqbShoOeT+AJ4Lnd1JS6odbCxglAEkD5/GZDEMg4aQv4ponHutCME4/Ic3k4CZkmO+gT+RLW0/jCmLbXk4Ash8OeT1k3zDYlZ/dHwIgo8ol81XklX95uGaYBDycD0kDG8eu7giRUwgk1hufzkotlyckw4KgfdBLqu0zTCyTwpwXsrVS0XZDualjaE4uE5NTGdGE5hW5IApEPB8plU2l+dZnx7mFM1WgLLK0twRi55pv2M1HOx+96/W5msWkkQdTzdgmbSonHMLKAZ7XY9f45rk3jDCxro2A4lYl0XYss0XFEkpj2xLulK7mSlEdXft5o2G5x3v1AKixa9nCyvyumX2c7v19bEwGynctXAuhaRgiECfV8AWs2RdV59ASV59DryUNls4H5nO3HL4nf2Mc5PhIv38GxJJrOb+VYX34tLFIUy/u1oKdphCELlJXYFvL+cbJLR822OyZUed8M7HEdAYxlIWPiO7uUTNOI93E+F5lsW9kRhPDquYAkx5Wx1bXthlSwVVYGaUGYMfDlJzv2Udcwm2GePaM8nxO+af2nyznmv/8z6vkW7wffkamOfUA6b7xJqLWAWOuXdA4OUelTvHGKMxzK8beBMZVNpN0/kvFZzgXA5TnOaCLjWNfCYFalXF/Z1qboDnAePCR84zFhmWPyXDyzcUw42cf8238t/sPv/UDA+MmZgPrba5wkRf/Nj3HP7uG89S70B5jlAme7gcVMqiuKAo6P5RofTcWT6tn+Ra1hNbfhShYUlpVlAxXU0c5TqnyYjnby3mwj11Mrt26vw+1StqPaa7GU+yJOf+P2a1MbfRt13k6mZoXILrXRLMoFbdl8O6kOVEBiElwbBrOuV1RNxbyYSUiHllLmsiklVMOIVM5zvG5C/nx5ybbOib3QypFcIk/YSqdxqHRFoUvr5YnhtQ+5VbkhDeIuuCJUAfNiJRH6Nq7fYLjX26fSYuCexrE1ajf8/OqKd/caHo9OmMRDjpNjTtIT7oo7fNfjxeY502ja+b5a9sg4ho1Zd2xUYQpcR5F6QSeb21Zb2j63tr9vXW1YlBvyuiaykvD2g6Y1urcfnJXWBIFM1PaSPr93+AGfzD/ljcFDlJVo1U1NP+jjOoptveneq5UvfrGQ9L9WKrko53w+e8azxYL390SOuKyW/POv/jtusy1/9ODDjokBeHv8mLKpSLyYaSThNKe9Y4bhU/aThFE0RDkCZO73exga7vfP8F2fg3iPL+f/klJLwXnkeRjgNtvy5XxGqEQ2M4oiEt/n948/4MHgHk9Gb3SF8y3g3ov3+JfP/w2xF/L7x9+j7/c4SYU5vE3uSL2Ev3j1Ux6NTnh38jY9P2VeLlhXG1bVil/c/MrKCCUNdRKNuZeeErhBl1q6rlZ4NhimBd2tfLN2w65OQ7keU79vWUhDrnPpsFNJJ58zGDbV2kqmJbFWI+OfeL+d3W87J9u6AW0afEexqlb2fIqXzrMVDi4Ojity0rbioh9E5LWoBLa1AJi6kTGsmtom5wr70lbNNKZhU2a8MTojtfumXI9hOETb+oeylvCRuqkZWqlgm1J6m9+yF+91/jmAbb3pFi9kIUPxYHiPrC5IA2G4tnXOvNjw6e0tb4xG3OtPLVs1YhpNWCxXKFdxnd0wCPq2F1J1rGEL+pTjCQi0UtTACTrGutTi9Wu7WFuZWmPDsjxXUbf2iV9/JjaaRbHmKJ0yCCThM/YirrNbUt8CI1NTa90BF0dn3fH6rjzjXq7PGUcjG9bSsKk2PFuec7HZ8GTiduP15y9/wl2W8fsnbwGiRgB4OLxnr8WAsa3JOUgnpP45kyhiGPRswqxvZbsVqZ8yicZs64xFsaRuNHldMAjTruZnYxnVebnoFuESL+b+4JgHwxMqXZFrSWuOvJBROODfvvo5sefz3YN3SbyYvWhKrnMm0ZDEj/jr80+5P9jjzfF9Ej9iVW4odMG62vDp7ClZXXDS28NzPYZBn/1433pHZWy21VZSTi0orBrx5vqeT2ACkaXae3DoJR0LWeiCTZl192vLiOf2fIhftaFuNKtq1S1WfvP+EwDU+ud0A54SYOArKZcvtAColkl0XEk19a0iJFAuldN0bIzcfyJXbdmkBonmaLGi+PgMb+3HJJ7qwN4wEL+gsJVaGBpgEOym0mIfKJnGsvDZsj/bWnfpldjPlMfTiLyWrjvXCdmWInl8cbvhcBhLEErgMoyk1281K1Cuw/W2ph+6nXwWbBANoGsB0sqFqpb3V654mEX6aqjdHcAVQEy3qOU6DjWGtgWh5UZbCeM8qzkeBML0WXLlLtOESiS44pFsiD2FY89POw7Kkf19sSgYxZ4FRgIsXy0L5uuS+5OYBijrhr/+esUqq/j26YDGNN34nY5CKm0IPJdJIgvT08Tnma9II49eoLoxqLXIfNNAMez7FLphU0rNyrZqhF20263tJGZdSok9SGfnvWHAvWFApUfkdYNuIPIdBpHHj58viXzFB8cpceASJR65bpjHisRX/PzlkoNhzKNJSOK7HSu7rRo+u8mpdMNBP8BzHHqR4iCVBcPIU93YSIq42127nuvguC6eMd28SzkOg9DrruG8btiUmkC1tiDsfWnPhz2nGAlTakHnv+/1u8Ei7PoAg1DAQX8o4Gd2K51/YSTSPVdBHO1+vq0iWNzaPc926afZWkBmmwh69ngXVFOVcHuF84M/tKXoFmSZ5rUJ9xpePcPc3EBR4Pzw7+5CYZYzAWZ5tgNIrRQ2sRPyNrBmsofz4Q8wz7+i/PMfodc5epXjHwxwxiMBEouFHO/+Ibz7HdnP2yt49gW89a1d6qrjCAAMgtfylJ0dkG5rQlrpahDuAPfrgThtSErLnIIFKQXm2VcSxrN/JKCwyAQwpj0Z7/F0x4yBBdOVhPr0+jKeRkstiOfL78/vMM+fsv3JlwTHI8hzYXWbBlPVqNQCTOv/dI5OIE1xzu7vaijiBN7+AK+wgTpvvifvaxNDzdMvZRzPzuDiQrytp6c4USTArjGyf77fAUWztoFCVSV1Jt/6jgB81xUWtdFwc4Xzt//+7thaRnJ+C76PubnGff9d9M8+khUyzxMmdDHDnL9i++c/B9chPLnGjXycR2/ghKEsULRy3bqSHtD7b8o1VtewvJNEXGNDbqpCzlnbwxlEcHCK83s/lGu90TDck3PTG8tTs8x3UuXJ4TdDk157tQxX9Fpxcc/vcZ3d8GL9klCF9IM+vvIJXQntkN8TIHRb3GAw5HXBOBwRqZhMb5kXCzt53vCw/0bnA6uaiqvsmh+efJ+fXP2C0PMtO1BR2m650HHZNDV3+ZpSa05ek5m2Rde1rY6IbDLgutyS2tX0UldUTU3shbwxOuYuW/DTq1cUtSYrSuIwIPUDNlUmYRt+D21qPph8gDY1N/kNny++4L2xJO66lj1pS9iN/aBrPWCBCgiUTGq21ZZAiUQsVAKEF8VCvGuIvFRWSnfyj9YovqkqO/mQ3sNv779D1dScpMd4jpL4eddH284+bYHAolzQ9/sdm9IPRKpZ6oLb4o5nq+f8xYsvudfvs662/PjmJ1aSV5MGQedHM8Zw2jsm8RPeHD3sfHGxinln/A75A5G1vj16i6qpOpD0yexzbrZz+kHKv37xGXfbjH4U4LuKVSlpnoFSXe1GqBQXa5Huvlj+aw7TlP/9B/8Zqd/DwSHXOcY0XOfX/IOzP6Qf9Dv5ckPDbS5ddxfba753+A5/+eojHFx8VzGJRizLJc9Xr/iTrz7CdeDF6pbI83hv7w17jY/xHOkkrE3N9faGs94ZqZdKxUq5YBSOOy9jy+C0TGGgQvbjA/7e6Q/Z1hu00YzDCZ7jMQxG1idadIzTNNrreh9/26uVsypXAGDixYQqZFWtuMtnIrO2clalBCQ5jkyeXZwuVbSVbgauVNhs64zGCINzkBwI0+aIVHFRLvnO/nu4jtulpbZdgu22rrc3XG1nFLrkB0cfyPs7LlvbTdpWRijHQ9tu1VZyu60ztvWWnt/j2/vv8GpzwZ8//4RVWbItS/aShHGUktUFjTGWjRzxaPAAg2FeLHi1vuDB4KwbIweXhtou4Lwuv9uF4NSmlrTgxu8qbrpAnNf8YG0icdsRKSCl5sX6Qhj8UCaPlZYQo8SL8RxP7i0L6kXeqi0Y3BJ7cZdQm/jCXFa6ZF2tebm+5McX55z0+xR1ySezLwTkaU0vkEWBFigeJlNCFXLaP7LydFmse9h/QH4i4/VgcEbd6G6B6Pnygnmx4rR/yMXmlqIuudc/IPR8NlUm4E9FjMIB62pNVhesSunOLZuavXjEO+MnnX+2rRZZFAv+zr3vEnmRSNwtYF+WKzzX43o741v7D/jp5Vd2wctlHA1YlWvO19f8q2dfohyH08GSyPN4PDomUAF9v4eylUjaNMyyOUeJR+SJRHVVrRgEA2Ff7PXV1r4YV+E7PuNwwncP3iOvc7RpGATCwLbJul3PozGMguFOMv365x9tJYWwgZ6SOoxJLImPC1up0HbOtema7TWpHGHshGk0NvTEoWoMWa0to9kwjW2ViN2fVal57yAh8b2ORXxdclpozcWq5GpdUWjDH5z1iZQs9GV1jXKhbBocRDJbNQ1FrQltImWhNdta0w88vneS8nxR8FdfzcmKmrzUjHqBMItV08kH68hwfyyfIaui4WJZcX8cdoxp+xnhd+muu3FULrZKw1aHWJ+myDNbcLkDC4H6poO0sazti3mJpxzGsfg+17b8PbQ9lr1AfUOJ0/5eVops1rOMZuK7VgJrWBU158uKLy5WTHohZW344ja3OYKGOFTUxhDY7U5Tj8R3uTeU+WXbkfhgHJLXfbn/JiG6MRIs05jOC3l/HHGzral1w+koJPQclrkE8cS+wncdVmVNXhnmWY02hrwyTBKP0+FuMaO14iwLzR88HBJ5Iodu01RXhfQ6Xm8qHh+kfHYhn6eeKxLdTdnwclHwy2dSh3PTjwh9l3vjmMgT36xxWrmuMKwHqS/nxYYHJb4s9CpnByBbVls5MIl9vnWcUNSNTcYXINkm5davXSCD0KF+zV70216/GyymqUzs41QAQVXKpDiyheTPvoT1ErOYSdl4FAOWNcs2Aow8+xaDkZX1GeiPBCy1Pkfly7+LTCbPx2cy4dZ6lzRZld8ArqYsYT6Hx4/lZ+taJvZtuMl2LemWbR1FnNii92YHPrNtJ5E1tUZvS+Inh6hHD+S405Tmsy8ofvQr4j9aCwu2fyigd363G6fWo+i4ciyNTfa0qL3TNjiujEt/YCWhLmgXAsvVt2mvLQu5Xcsx27Fyosgyinas0v7u55JUtrdZyvG2r+tzTJbhvPX+7rxs17t97vVhsSB564jifI568RKMoZpvcT2Fd3YIRSEdjZ6H0x/KGA/Huy5Km9zqvPddmv/X/w0nSeHkvrBmd9fgeejrGWo0wnn7XczdDY7vY776Cuf9D+TYoxjzxdciTx2OBbSlfdn2wT3ojboPARPGchyuIxUo/aFcW364CxiqKtnfo3t4pw8wP/4R5uYWo55T3a6ZfXrFpy9WbJqG6c+uuHeUcDLow+O3dmPUHwpwHO3JtVjmwn4rZRN/22Cnwi4URFKJUWRyHcTJLrBndm0XW6Z2gcF2gzZGfJDBb/qmRlaumfopqZdQNiWxSki8lNiL+Wr5lHW1ZlbMud8/I4xCPMelbmq29YatlcEBjMMRiSf+tmEw6nyJiZfaAvGiSzhUjstdMSPxI7K6nXAqDFUnaTKmodS6K4NuGqmeqBttJW0Fw7BP7IXcZCKBLLvtC5uwKTNcK+dsDGRFyThNeDAcsihy9pMJn89e8S+e/or/9N0/YBpNOEwOGQUj7vKZXAsYKlPhGJFJKetver1So51gKUexrTMGwYDU63UsS9VIn2H7gdmms7W+RddKQzxXQnpCpfjW/hMO4gMMTQdAHcdlW29YlavuvS+3V2yqLe9PRzIxsYmzpa0I6fkpN9mM9/f3eb5c8nRxTmMMt9stvlK8OT4k14VdVZXJcFZnjMMRqQUeypFOu29PP+D//NH/nZ7f4ySVhNNFOUc5ip9cvqQxhv0kYRCG7CcJL1crvrV/D4BekPDLm2eUWvNodEAviHkyekTkRexHe+xFBx07F6qQeTlnXa356OZT/t7pD+01ZetCkIoFB5dJNOE/eesf89eXP+F8fYtynnG93fLp5TVfffmKbV4wHvY5OpowiQa8NXrTgtGM1EsZ+EOGwagL05C4frdbGAA6SXGoQjaVpNAqV1nmWdjwu+KWwA0YBWOw10nbAwj8VlYDoOcnXXBUrCJKm+IY2pqBy0zO77JcsxeN8d0BWK9ZpUtyC9gMputdNEaCPQJXFjAiL5LUT1N2ks1JOOlYt7zOOw8jtGyLItcli2LFo9GplZhrdFNTNhWlrsj1HUfJAdrUXQJrY5mcxvob24AS5YjvOKsqHo3HPB4fdvLOT+5e8pevvuIfPswYhn2m0Vgqeap1J68VKWzr53ItSNNWaipj3IZJ5XVBYnsW2/tEklPr7l5t/27vE9/10HaBaRj2rZS4IbWBO3JtKBwkRCertziOizENd/mcrC54Y3hG6+/eVhl1I+8XqYhFseKdvT1erVY8W4r3f5bneK7L/cGYUtfoZoPnekzjEaUuGQQ9Ii/qPJueq3gyesR//fm/JPZCDpN9qqZmVa1QjsvNdssg2PBkfJ+7bEGgPJ4tL3h3KtURoQr5evkCx3EYRwNCJQsTAvAmxN6u2zW0x+w6irtixomfEqqwk3G77T2iPA6TPf7powN+ev0J11s5vuvtlq+vbnn69JxtXjAa9Dg6mjB8N+LB4ES8nDon9mJ6firBRphvLEK1fnUArWsaowlUQFbncj4cj0iF+CrAbWoW5ZzAlZTu9lnd9mHCLtn69Vdsqx5i3yXxlCRpKgEznutwU1eWQYFRDJ6/Cw4zTcOmk9btgKKBjm1prIyvXRSU2gPYSwICV95DuhXbiTjdZ8K2aphta54cxHiuSAIbyzhuq4ZNWXLcC8UbXtXEntzPtRGQZMyOFW07EYtKc28v5f4ktsyZw9e3GZ+8XPDhwzGDSDFJPNLAZVW0XO0O5IKA09JKNNswlHafcSTsJvIMaVva5zj4aic7bf16QOeLUxZctN67umm6VNPGCAsYePI0yGvddVsCzLby/4dBSFvvsbXJrBtEOrkqNKfTlLt1wdVS1FqrvMJzHfYGEbU2bIx4SyexR1k3DCIlqbau08k3H09D/vTjOyLP5Wjgo23SbeC5XC9zCh3w9n7E7UaepZ9f5zw5iNlWEoLzfCHBQ6PY6/x/IO/5DebNJohGWnose6Fj2dudwsoYCQw66gecDCb84nzLzbbkcgHzTcn55ZqXz24o85J0kLJ3MCB5/5AH45BSG7QRmW7sK2LfXjv2Gmylo7swHjnPnutQ6YYKm2xrr/kGAcGBcontgoVydgsMYq353b7F312d0etjZneY1QKnroSNWtzJJLk/hgdvys+dv5BfqCxIaoz8zOsBIq0vy3FgMBXAaYwApDKXSf7afr+dnINNpqzh5lIkj1a+56Q9+Qh6/lz8Zv2hyBsbjVktJfwF4Orclt3XmB/9JdX5LSoJcHsJzuPHso+Xl4SPTwg/SCR91UrRnPEE9WGPeO+5MIZlLszX8Sm89b4wZ40NqGmBXpvkmW0EUOSZgLv+QI4j6cnxtb/rWkayfVC2Xsa6FsDSylsBzt7YsaLDsex7K2vNtnD+QkBo2+e4Xsj5SZKdNxBkrNoOySiWKgnHITwVOW+zzQUo7g128lBjYDyWcxwnwihqDZT2WG8lBRQo/sWfE/5v/9e74wlDvD/+R7JfvT7OyX2Y3eAEEkK0+X/+Cel//h/h/ODvyTZ/9WPMcgG3NyKDPrj3zQtzNRMpcAvo5rdw/sz6Za1/9sUL2NvDfPYx5sVLCcI5m8L+PkGast+P2Pu25vbnLxk+nOIGHkyncu1GsYDcMLT+0kaAb2HZ6nS4WxwASPq71Nkg2i0O9Mc7L24yEAmqrnYLA22qqq5k27/2GgR9rrNb5sWiK46fFXeEKmQYjHg0eAOAF+sXndSpTSYNVdglnkYq6krrxWcV0/N6Molxle2zq1jXIuG8zm/45O4rQuUTeSGVrm1oh7CEiR/Z4uoNmU0KVcqjtv7hdhIReyHbOrfeRpevFldcb7cStBIE3OtPMLphVWYcpSn3+v1OOoQxbKqMv3v6HU77L7pU06vtNffSE94ev92t2reTI2Eo5Pi39Va8b3VuJ3YDSl2S+okkDtragnW14uX6klJrIk8S75RNImvjpVt5bKgUkeeR+gGTSEJHpH/MZVNtebU5J/USxtGYvM5ZlSsMhl6Qdr2Fxhi7Ii+MUuzFbEo59w+HI7m8ywJfKQ5TqT6Z5UuMMewnE0pdkfpJJ1urLYvZlA3TaA/XcfivP/tz/osP/mN6vhG5oxfyv/vgj+kHfSbhWDyV5ZJ5Kb7K/8vP/3/8Hz/8j/gPH/4TtNF8PPsVi3LJVXaNMYaz3tk3rsuf3PyE/+HFXzEvcrZVxcv1/4d3pw84SPZIvYQfX3/EL65f0g8C/uLlJ2RVxaIoeG9vj9PRMYm/YhCGfHh6wt88f8mTw31CpTjqyfMndEMrOZawmvbaLkyO47j0/b6wyZZR7hIVMSLHtlOowBcwFrgBPa/Hpt7YtNJQwJEFM9qei9/26gUJd9mCTbXtZOGbeoPneCR+wmF8YGWfd7iO9AGapqIyJa71z7U9f43RXdhKz++hVCjy006+LImwrqOIvEgqJxyn+/esmDMIpN+wNCU9X+Spz1eX7McTYi9hU8t+rspN1903K+adj/dvLj7i1XpF4vsMwpA3R2f4yudyc8vj8YT390MSP7JpxZKg+eHhY/aSS2FxdcWiXDKNpjyw0mYZQ0la7WCoMV04UGn/Tn1hhiMvpO/vGECcBm1q64qTvkiZ5MriSru4BHCU7LOtJRxoEAwI3KADvFmdc5PdEXlhV0OyrTMajD0m34JSeQ604CdQPpn1Ep4OBjjApqrwXJf9JEEbzbIQ+fI4GohPT0WdhLU9d41lzwD+5Muf8p+99z+Te9M0xH7EP3r4PRIvIfUTjpNDltWKxIupm5r/8pd/yX/+/h/y4cEHNKbhy8VT5sWKOyO9btNoatlb+WxZVWtu8pvOyzov5lxurwht+NKm2vJidclePOKz2de8WN1ysV5zNhhwkI7oByHDMOTde0f86uUFp/sTfNdlEg9p7H20KJfCmtoFx9frUpLX6oWAbiFC2P5dBVLqiirE9yJiEnItapE2vKr129ZN/VvZ/TRwLdgwuI4sRAba6WR608TvvG1dQbmVkBrE16Ve8zS+HiwiDGPrqROg2IKjQeCLBcFA4LqWTS8ZBFLBkTXSXwjSD3iQ+qS+x6qsqBrDMtdMU2F+rrcloXKpGsNfPltxvcyJfEUv8nlzLyLwHK5WFfcmKW8e9oWBcxyUaxjFCl8l9CKPwBOWaVVoponH2TDo2MDWe9YePwjQq7WxwMOQBqoDoCJ7dbqU38Z8M+207VXMbV9fY9/nuB+wrfSufsSVBE/HcShrw+2mIPJc0lBA/qaU8xtbJlHAjekSPiWUyKGoZNz3B7KAlFca13EYJIFlH8X/OIwVtZFKFf+10JrSiKx0EMoc9998fsd/+O0DYk++n/guf/DGiH6oCD3Xgu2Gs3HIptD8yU/P+YffPuKd/YTGwNNZbtNpBchP4p28E1rPpcx39q1/9HZb4lkABnC7qdjr+VysSl7c5dyscvb6EcM0IAk9epHPG6dDnr5ccrCX4CmXUewL6FMO27zBcw1+G89idn7y8NeYX1/tFl0kkV5eiS+dncoRRr7SbcWZ03kh5XjoJMX/vtf/CLPYx2kTOlvJnNbgIxNfkIl5fyAT9sVMJsGP3rJFNGpXKl9ku5Abx9kBINhtH2yKpCOTc2MEVC3uMM++wukNIACuLzBXlzQbYSZwHSgyzFefQ08CW8xiJvszn+NMp5ivvsRkGSoNMbqhupjhH67h1SsBc0dHOKcPbDCOlZXOZ/DwCc57H+7qEZSU07cmU3QpIPL1l1LW87YWaagfiN+w3bZSAhxbiW0b7OM6u0CcbGN9jBaMtuyqq8B35fc66aojQHk4tmxjI+A2jGW7RS7bbv2eTSOAyAb1OI8eYT76SIBynjP/2QuG7x7D6Sm8eIG+nolMczrdSWYjx/ooK6niWC+gKnG/8x3q/+pPCT1fzt39t3BOHtpaCi2y0yAQD2jTYH76N3z6yxu+85d/ifPqJSjF8p/9a9abipP/4Ds4T97q0kLbDyrSETxORQ56+VJkq9dXMhY3NzCZCLDVGnwf5+yUaDJGX1xT/+wz/EmKm8aYvGC7rRkpF/+tB5Ko2nYjVhV8/it48v5OQtwCwY7tRo6x9ca6DtQIawgyPolN36xKOd8tKFS+vE+Zy9daf+drr9ZXqBzV+UC0/UBeVctODjQMh9xkt90E+63hE5HN2XL1sinJtQS/+G4AON3k2hiD0+ZmI56gaTSl1J/KA8KuVK/KLbHtFL3e3rEoNtxst12AgDGGebEi8SIBWxhusjnLYo2vfBbFhlJrhmFIpTW32y2TOGVd5pRac9wbivcR2FYiW7rNlvz+0YQP9z+k0DmRioVZsvLBFkSUr030W5YkUhEbs2EcjTvZX+zFqEZ1E2cPjz9/9W95urjoHrztanO7uvq6pMZxHIZhwrcP3u5kbzJpclmUc4bBkH4ggSuBCiRMw3FEmmuTV8tGEi1DFXKcHFM2Je/tvclfn/+cNEjI6oKfvDzng5MjHo/PeDp/xcXmksjzbLdjTdVUHUOlTcMoHLKpNpS64IcnH/J//cW/IHADQjfkYf8hJ+kJWb0VObLO8R2fo+QYbRr+5upn/PLTZ/yL6V/wfP0Sx3H4L3/2F2TbnP/ltz/k/emTLgCkDZt5b/webw7f5K645U+//ld8fHvJny5/LhP2qhLfJ1DWNb5S3arvzy4u+fHLc05GA96c7JHXJUVe4rku7+/fJ1IhhWVRS13y6fwz3hm/3YUQ+bYiZltv8Zxdp1tbveA6LhVVV+IOdF7EUgt4K5odk7ZLKs0J/j3MYqwi+oEtu6cNx2lkhd4GcqyrjQ30WLGu1jiOw3FyjPT3uShXoY2Aptbb5VipdnvvvF6wLd2birzJZebm+iKVXF2SjhNwBQBebm9ZlSWDUK7esil5tnxF6icoVwJXlsWGZblmGg15unjFtq7oBQF103C+WnGUZizWVxR1yVFvj6N0/xvJlKtqxb3eCU9Gjyl0ISmvdrxbxrBBZKStrMmxcsdQCavbD/r4rkdl/aZtcE0LMMtmxyg6jkPdJg43ZVehIgoBSdRsF3qMEc+j40Q42mFTbUj9hMSLLVupLOPvUOka1z73Sqs8CNyAaTShamoejU75+fWX9Hxhj39xfsnbB3vcHxzxbHnB1WZN6Amr2BjpD/TwrcyuJu2Aes2Hh2/y//jVX9nnrcdxcsR+vNclwuZ1Lh7baIoxhp9ef8KXX7zkryYfc7m9RTku/+zjn5FtC/74vbd5Mn7QsW7tPZj6CbF3yqbacJPfsqm2NozJcLOdM42HDMM+VaPxXcWD4T6TOOXVasHL1XOmcUw/DKV/NS9xgXemh8SedJQaY9CN5uvlc94Y3O/uqba6JdcFng0fer1e5nUVx25i29YaSaBYCwrbz7TKpuX+tkTUyHNJg52k0RgbOoaAIeXAptLEnsuqFBBjjGEvDezze5dC2l6fuyTTb766DtN2amfkCveATV3zfF7y9r6HYxxmWcX1piYra5TrW2+e5umsoB+KFHOZa5Z5xjzT7Kcen93k5JUmDjyaxnCzyjkeBLxciD/usO9zNgq6OgPYyQ8fT6JORuuwK2Zvw2Na71n7EmmoMOuDSNglbQyR71gWXBr6fNftevnaqox2nEot/X6uAdcY6xkVr2c7PoHjYnEfa1uXkQYuxggg1x64jgC5lg1rtx96DuM4QFvZ6CeXW9JAklW/erXg7LDPySjk1bxgvsnxlMs4ScRz6Yj8tMGgNdKR2UiozXvHff705xcoV3yuB2nAXuJ3lRGZ7bUcx/I59dHFhmdfz/jVXo/bTU3kufzFry7ZbCp+8P4hb0xj/K57mC7LIPE9fNWwrYQ5XeeyVHa1EpA4TX07Di5v7MdM+wGXi5ynVyv6sU8SehSVJs9FPXG2J57HyiaV6sbwbF7wcCzVJNpIQmp7jtruy5YhfL2K5PW+zzZAqGUi68YI12F/vm5Mt2jwu16/Gyz2hwJu8kwATctEDSbCErZ9g5OJSBLrCl483aWOlthS9ngnAw1tQmpZ7MASCAgaTSWF0vNF2ldXEohSlTjjyY45/OgX4Hm4776Nc/aGBNokPYhjkTfO5zj7+3B4In9uLmnOL3GjAOfBCfqzr3ACD66ubO1FCssl5pNfyu9NbAdfnAhoC2MJjGmZOWMEiOhKxqAFYSDALOkJAKhrWF7sEk3bUJrcym3bYBfH2S3rtImqni+gbjmH0XhXj+G6Mm7DyW5/qlJkn6/TyKaB2S1mdiu+P9tz2KXBFrYv8PNf0vziI8qLBd6koMkqHNdBvXGGMxxhrq5w44CmrKVGQ+tdwuxyLtuLEhmjIkP/zY+5O1+RXp2LfHRxI/s+msrvDvdgY9nRPIMk4bv/hz+C6RRnso/5+kvC/T6DH56IH3H/ZHecgGnTb/0A9k7kmK/PhfmOYtg/wGw3cszDkQDoq3MYj1GbDcXLGY5yMdcrgqMhcexx/ckVJ/t93LP7mPMXOIs7y1YPdt5FDzlPrVy0zGVBw80FMHr+rtioKuT/bdcm2NoNf8dA62pXrdL6eH/tNQ5HKMcl1wWRCsl1QexFjIIx62pFY8ORp+GUgT+gMhVfL7/mOr+m5/codNEl2sUqRqOJVYyxK/ZtN1zrKZqEU7J6yzicEHshhS7ZVBmeqwhVQF7LNf5iNcN1pBB+HA26hL/Yk0nBuszoBwmB63GQTrjLFlxtNkSex9lgwmd3VyjXZZ5vcYDE9yl0SbYt2EtGMnm2yXvLUhJUe36/C8hoJ+xVU1HZkB7xHJouvGdrC7nnllUJVcjUBj/kddaB6Reri268pZzcJVSKbdPgK9U9YI0FPIkfdUylyKtcarfmrHfWTZTkEWG4y2fc5eIpu9+vUCh6fo9pOKVoJLL/k9mn/OX5L3i5XDJNSrbWF/nO9JRpNOHCuyXyCopaZJd1o8UTZ0Nwen6PxEsJVUSlS/7Nqx9zcbfgKrtiPz5gXs5sAIpUrAyDEetqzaZek+uM1E/4P/3jf8JBMmUvnvJ0+YyTQZ/3Hr3NH53+bQ7iQ5Szk2tqO1kXX9OAv39a8mL139JGrEeeR1mL1yP2fUZRRF6L1/WWjNvlgudasy5LDlKREH704pyDJOXR8D7PVy+ZFXNO03u2tkC8sBin8wyCePYqXVI4Ut3gu343+yt12S1ytLUb0l3l20msXPNttUygQjJb5/Hrr8RPcaz/r92m5/okftKF1kgnYtp1oF5sL1lVK0mLpKYoZSLc1gm0Calteme3Iuy49IN+916mlsWAtsx+GPVYVxsMhl/efIFyXN6dnnGvd8hdPif2IyIvxHcVN9mKvXjENJ6wF49ZFEteru5IfJ+zwT4f37zEV4qrzS2e69ELUlbllm31nKNUKltSPyGyXaaxkv+3QSXS8Qi10dSWWWsZwdpKa0tdWf+cLCwHbiAMf1NSNiXGiAKi9aq1NQueq3bA2lFsq4zU381+ZLLr0fNTAd5NTe247Md735A1goDdRbGi1DUHyR6uTVoduP0u9OrZ6gU/u/qSy82GLKq6lNM3RgcMwh6hF5D4Wq5jR1E19Wvezy2hCglVSKACSl3y7y4+4/ZuyU12yyQcs6pW1nst13v7fMrqLWVTkngR/8U/+PtMoiHjaMDz5TnTXsqT+2f8rePvMI0m3XXcLtq0YzMMhxLs4tzZlNmA/WTMtsopdMko7DMI+tzlc0Zhn3WZ82q1QjkO19stR70eURTw5fk1B2nK/cExl9sbVuWavXjKcXqIsuFNjuXzvU7+XdlncI3nKmFt7dCLXNWzUuR2oi2+X6+tfOnuQfmM+m1pqJGncGOpP1Cu1EAoyyoWWkrqtTFErmIUyfvcbEryWoI9GgNF3VZjCEBqGcjm1ybVriNMTBta01iwuLFBNqPYY10K2/SL8y2ecnjrMOVsGHC9qUhDl8T63uZZzTTxOOgFHKQNs6zmclmIL20U8vnVFk+5XKxKfOUwiBRZ1fDFbcHxwJcqCU8JG2g79CJPfIHCzX0TKDbswlkqC+haFnVVtDVB8j4lpvOnBdba1QJF2EkZlePQOLApGwahQ6N3i0Gh53T+UMcqb/aTHaMMdgE5b1jkmlobDnoG44g0M/FVlyL7clHyq4s183VJEUvyqOM4nIxj+qHCVy6hpyhq3fkc22yGVdFYltFl4Apg/OjViru7jKtVxSjyyOu21F5h7DVV6Iaibih1Q+Qr/uN/8IRx4jGKPV7MC9I04MnpiO+f9aW+wx7XTvSJfaa5qMAhUCL7DTyRnW5KTV4JMzyKPK43si/rQnO7KshKzXxTMkoD4tjn5fmKcS/gdBRyu6nYFJr9ns9JEHSLrY49R10YTyNBS5o2wGh3LevGfGNBwdh9fv36wV7fLVBsg2/+fa/fDRazjfxpKyriRCb4q692he/hayuycQoPHgtT13q1QNikFlS0iaeukgmyaXZVElEqslMQ/xnA4pX4BINQQNqNndxpLd2P42lXWeAcHIuXsKpkm3EqQnbl4Z5K6Am9HurJG1DXNC/PcUcDAYsWkJjLS5yHT6xvsBGgMZyA8xpQhN33Hcf62UoBgmvLuG43mOVc9jFOBFjVlYyfM4OpeAHlaeXumFvTCJACAdpFLmPsuMJ8NQ1CX7Fj+V4HicrKG19+DabB6fUtI6q+WcfhOrIvrosTBjS1xvEUqq8Yfe+B1FB4Hs7Dh/D115iLW0n3jBObkut2FRho2595t6S6WvLyasvpr36Jc/ZIxunypZz/zVJA9+0lHJ5JQM3jtySwp8ghTnHuPyb6o/+5ALC6BD+Sa3B2DScPLQOtdyyrruQcJD3MxStJ0T08lG0aA46Lef6c5m6O++Qxyf37Iru9kOvo8D/9+/Lv6RTKAufRW+KDPH8u3tlWDt3KhrP17tqsa+ilAhyVTZGtSjmH9Wv713plHXd3rspctrVZw8QTKeuvvTb1putabGgnGVvW1doWmdfWxyKSnkSlvDl8k8rsurKyOmddrUm9HqGt2Wj9b21SZ5u+mHgJrt/Dd32+f/gBf/7yR2R1wSjsdV1i60qS7HAcEi8i8SJCu+qtjU9el/hd9HpJ6iaMwj7OUCYakRfyZHJAVhecr1f0g4DEC2Wy4SouNzMCJUyq77o8W53z/uRb3ep0u7/KUWhHd5P+tsuuDRNZVSuW5Yr9eI/ES1iUy06WumBBP+jzV5c/YlHkEu7y2rjnFuy0Jvb2EepbSWpboq4tcOhYEZyO/Xi+eUFjND2/x2GS4OJahljJ+cIl11IxEHu+rNIqRaAUP3xwxnuTt1Cux1uTh3xuZWRry5y0lRyjcGRBh4RLzOo7Xq3XnJ/f8rPrTzjrndl6iosu2Cj1esyKO/bjA26yG96ZPGEvmlI2pcT89x7wD0//QcdIhxZILco5x8k9yyjtJsmX2RVZJaBgVuToxjCOY0KlGIQhkfJ4Op8z32b044jpdNiNcV7X/Cff+z3u8iVHvT1yXfDO+C1u81tebF5ymt7DmIbGLmboRrNpNoTu7lpIvHQnVbSywsY0HSNfNzWV2cnn5Cp0KJqCbSW+3lE47roaf/3VLrhoo3GNS+D61E3FdXZD6iVdVQaI985zfY6SQ+pGqjVcYyiAXOe7EJKOKXOtP9MQEqJNQ+D6HRCJPElRnVVrxuGYg3gPbRrmxcJelyKL7AdSweI4DuNwJJ7YpsJXEiLT9yVQ6cFwH89V9PyEd/buUTeaF8sbhpGiF8SdB/TV+ppv7b3VyQRnuZW/8hpQREK0FAaN1GRUTW1DpEQ9kemcdbllGPaF6a83loGs2VYbBsGAXGcdW9YxO41hW2d2/EtKXVsG0fmG9BwkREq5Hm6zW6iRcK+Gi+2l9YfGTKOoAzuuZTaVI9eJPJc8Klsl0w9DPrx3zJvj+7iOy8PBMU+X56xKkSMn/sSeP/Ect5JZ5Yon+mqz4fLyjo9vn0r4lau4zW87QJR4MYtywTSaMC8WPB6dMQ5HnWLgODniD46/j+d63eJMoQuW5ZL9eL+71upGWwmzjEXshVxubtlWOYfplP14Yp+VLs+W51xt1rw9PeFssE9el1ysZdHvP/nO93m1vuUgGVHokgeDU5blkqvshoN4r/Odeq6wwbnOukWbto+xampcK4Wrrby7RvavNnW3qNKyziCLOpnOhWl1PGLvN9U12vb0SQm9TUQ1hru8JPbEO6ectkJG+uQmic/rfXQt+xQoCf5o59QOIoNs7LPdWPbMc51OqucAq7JmFPocpD7awCyzXaKNgIFe4JP4IlOcRLAqK/Ja+gQ916Hn+yjX5XQc4bsOaejy5kFCpQ0Xi4J+7NMLFaGtlXi5KPnOcQ/Hvsc81xymbjfR57X9bwGjtqC5lX72Qpe8NmwKTT9UJIHLupQUT93Iz4wirwMSsGOaTNOwqeQTMa+kCzGw+xbYc1w1BuUpGmvbeA0jdmDkaiPj1AsUked03kfH2cmCW9AaeopaN7iuQxwq3rw35OE4xFMOZ+OQ5zPIyppN0ZD4LfPqdFLgxogHb1030nt4s+KL6y2nowDfdh4e9SRoKFCKRV4zjn0Wheb+OGQSK3Qj18hh6vN7p/1vXAdV07AqaybRjv1uE9OrRv6OfZfzZcWm1Bz1fQ5GfgeIn84KbtcFbx2kPBhH5HXD+UKUBv/4+/d4Nc+Z9AJK3XA2ClnmEqB00PPlaWuv7XbsPZuCq3WD74nf3LWLI8LAG5q2rsbsfJRABypbmXFuK2Qi73+CZ5HFTKoEZreSMuoqmYRXFXz5MV0Ze9NgNhtJyhyMhGV8vaR+diNAyTQCLMpcgGG2kU66FvRslnbS3ezA5uGJMJV1LX/7Ady/D9vt7j1c1clbze0VTmqZvWwjYGWyj3N4hLk4h8tL2e/VCreXiCRys5HthSHOwzcEEGkNmxVmMccpMgELLVBUvg2isfUHbfCO7U00n38CSuGcPRQw+/UXmCLHCWPZ36rcyRPbPsi2QmO9wlxd4AzHNpG0gqsLnHv3BVxu1+INDOOdHLZlrFrvW7aR7SrPBq+Eu/CdFqiH8Y7NPTsjDkMptA9DYVzXS0h7mPUafTPD1Brz9GtIEpEmN1oYSs/7RpqrN0qY9AORA5c5HDwW71623u2nH8DnH2Ha/sX9I9nf1Kaa2omDaRN1/VDA5d2lXIv9oV2oiOQ6cucQxTgPH2P+3V9h6hpnfotZreS6GQzIf/IFyemJSGlPH2CGQ/G7Wna5+uUX+GcrnN4Qs14KoLz8Ec6jN+X9kt5rktJiV69RVzu5r9G7VNSbC8u2W8Y5iKHMRL6dZzIObWiT8n8rszgr5jzsP+A6u2FezPFcj6PkkG2d8Wpzzuv1D7N8ycPBGaNwSN/vMwiGZHXGIDDc5XfUpqJpGqqyotA5iZ9KGqLXo2pKPMdnVS3tanDDw/4bPBu84OvFuaSSNg1ZXeC7immcoE1DP0i7xFLPlQfWptxa/5AETjQ0TJMRoRfwan3NxeaO2gZpRJ5H5HlkdUFuJYux59sPEfmw+sX1M94ef8m743cxtJMNYYd8V8rWVWNDFhqN5yh+efcJnqt4c/iIYTjk6fLrLuwn0znn20uuNre8XN9SN803Jgal1l2FhnJdNmVJA4zCkF4QsihWfHjwflcaL5MorwuUqEwmgTdugO8lNvU12kkfLUgIVYQyikk45vH4rAvuSPyIF6tLVtWa1EtYlisuNjOKuubj26f0/NQWWtc2fdWjakqR5uEwiSLG4z6jSCTMB/EhPa/Ptt50Uk3P9fh88Tl3+R2Jl7AXTQndkJ7XJ1Bh93PKLpBJ5cYhd8UNi3JB7MX88u5XGAyPB494e3rMJ7fn9IOQy80G3TQUwMvl0kp3Q65mS8pA5Fq+Xbh6MVvwYrbAceCvecEPH9wnPU1ZVWs21Zbz9RVPxo/o+316fkqkZDJZNC2bGHRJqK1ENLR1Grf5DYmXULnCUAUqpNQF20YCcNrzpVwJutlUv3n/AazKFXvxHutqzbJcoRzFyDKMz9cvuwmwMYZ1lXGUyuJE7EUkXkKpSxIvZlWu0E2NcRR1k1FbYFDoYpfk+lpHYZv0WruasWWnBLgtCZTHaf+QvBZZqASduPhOQIPDbTYn8WLyurAsq88g6HOYTHm1vmZT3qKNeIXTICD2QtZlxraeESmfs8ExkQqpTU1WSwXJUVrgWUmvwy4cpAVewjzVFjS5fLV8gXIU93qH9Pwe59sL8rqwwKeksPvVgpk2qsMYkUrfZHMGYdpJzW+yOcfpPtpotnXGNJp0ialAx7ZLrUhBoUsCN/gG4JKE2p3Ez7P3zCDsc39wSKg8+kFK4kdcrG9kccZLWFcZN9s1uml4uriiH4j3UjyKfQJX+msVIj8cRRGjkdzL2tRMgjGJl3bptK089fn6hdS7eJJyHaiA2Eu+4fnz7BTNs7LVRblgVa5I/NQy05JQ2qonzvrH/PTqY6uqWLKuttSNZhD2+PHFOWeDnHE04N7okEGQ8mJ1yav1La7j8JPL5zwcjegFCYtiTV4XXG1ueWN0SuqlXSK3g9uxib6StOZA+XYhQdswIvHYRl6E1+yAftmUbJusq0+prARZOS5Z/Zu+/WWhGUUe21qzzHWnYNANnK/KbkpWN4asathPPdJAdf2LjZH0x03VdDJWjQBL3/oIAyWMlJTIt0q3Hds2Cn1WpSwgzraawAKYTalJfJdSi7+uZS6vNzWx75LXkoDqOQ49X3HQ8zlflqwKYbrWhUhSI89lXWguVg2JLz2Aga1vWheaTaExqTw7u6TXdoAsKG4ZUm27Dp/NSpQLR/2Afuhysaooa0lKLbTBfT0qtduUfC3XDTebmn6oLDNruF7XHPV9als3kfgyvu39p1rwYuWTpTZd+IyMdXufOp0nspUDDyPF8VCAYRpK0un1upT3wWVTapZZiW4M54ucfqiotJzbQaQ6z6kAUehFHr1BQuC71I2kgJ4O5N+OHavAc3i5LFgVtjIiVnjKea1mwjJwrzGuo9BnXdUssppeKAyyr4TRy23y6sOxy1+/WFM1hllWsyqkamYUKz5+mXM8jNjv+ZyOIgaR4tms4G5bEQceT683THoh/VDAbFkbfrHa8ngvIvZdIs90XsXWo9qCd/81D6OkosIil+vQmB1A101D3hg7FsLUu6/NfX7X639chrqcS9JmEO78d9lWQIurMOcvBWiBlKef3RcQkW8FmMzvZIJf1/L1xZ1sa2N9X6aBj38G735XJs9eKoCqLsWb5ipIbPVF2hMf5WQf84ufyITcOxXQsJzJJLyuZZKuPAnMqWvwPEy2xVyKr81R1jfoecLWLRaUTy8IvvuOALGigDLH/PQnOH/wty1zmO1Yz/bVNLu6j2wrYFdrAUra+gyXc8ztDVQVZr3GmUx2tRVayzj2BjtAF8mEyKyXOGEkjGWSCDBM7fuPJgIMPRta0x/JeGdbGQM/kOPwA9l+nu0AXctEOp78fLaVAJyHD2Uf8gxzdibvcXcNiwWqn1DPrnHu7QuIBcs2W4BrGgFISQ/vh3+LJ+8+wfn+D0VyCjZ51dkxblfnmI1MzszFuTC5vaGwzlUJyse0ALwq4fI53F3LtXZ5KcFEJ/clKMhxBOC+/FpA5re+g3n2Fc2Ll5TXK8IffAs8D2+YMPv//jX9t47w3n5kk3Yziue3hI+O8A9HNPMlqshsoE0tbGO7D3Ulvsz2vMbWX9r2iyol59/zBayXhbClRAK8y0L2tU1YzTdyPqPUhgb92rUFDPw+82JOP+iR+gl70R6+G9Dz12S2fP7r5QtW5RZjGtblhifjN5hOZHJrMMyKGbf5LbWpOYwPucpviWwwi6+ko/AXtx/x7ekHVE2Fp3wKneM6ij8++0dc7l3w4+uf8WJ5iXJdfOUTKJ/r7YLL7S2jsN9J6QpdUjWaQHmEXiDsYl2R1wXrMuN8tUKi5lt/cmON8TXPlgve3dvvwiYKrTlfrRjHMT+7+RXH6RE9G2zSMiCNTTaumop1tWFdrWksiAWkrL6Y82ItwHpRrJnGI16urjhf33WejVJr3NfkOG2iXaAUDRAqxelgj714xMXmlnvpye4B6nj0fWFItvWWbS29YnvRkECFbOsNWZ13QSue41t20SGvMrZ1Rt/v8WScdEzS49EZo3DEbX7L7XbOMEy42W55IxowDIe/cZ20QSCRivij+z/gw8O3+FuHv8cgGGKMIdMiu22lu+ebC9YWHL3aXPDG4KGMrePahYPdx8KmXvPn5/8agJtsxvV2xgf7TzjrnTIOxyhH8YOjb8t21wv2koSL9Zrr9ZrNOuPJ0T7KdYnikMvLO3r9hDD0Ca2SI9vmxIkwaf/9Z1+yn4w5TKbUjWY/mQBY2aLfdYK2vtWW4WiB+LbeoFyPwtZSeHbSvamEoVeOyyAYMArH5HVG6vds16GkAv+2V+qnbKsNsYpQoWIQ9Lv04G2doRyX8/U1Wyuh21Y5Z4ND+kGf3HrU1pX4BrVpGAZSjeC5vvi+rNLgq+UzHg8fUhtN6IZdaEpi6x5aX1fshaR+wiDo8+nsKXf5nP14iu96rKtN1/MZe0NSP2Fby2KO7/ps64zLzczeGzIp8lyPwPWYFyu+ms/43tEDhoGEuJRNxS9uvuB7h++gm9p6Dq0ccidmAsRn2daB1I2m50swjOd6bOoNd9mCUtdsKwErbX1J6y0VGacAjvb+3pQZoRdQ6orElwWXlnXt+Sl1I8BEulQlLTqvC6nmcH1GVsac23RO3dT4rtdVQjg4FKawgD7ijeE9Qi+gqEtOB4cMgj6LYsmiEAXEbZZxOhh2z5dfvwdbT+Yfnr7LO9MTvr33LoNgYBcy9M4jZDS3+YxVKSqI8/U193onJCqSCZ3RuLidYkE3muvshlW14mJzw8X6ljfHZxwm+/RDuW8DN+A6u8FxHL61/4Rny3OeLW+43m75/ZM38FyPQRjyp599wqO9CW9PtzRGs60qni+XPBqPOer1uN1uKXTZLdi1IUlVU+E3HpllDcV3G9rUU9VNwoXl98h1Rq5z6R91JXyo1DMcxyH10k5u3QLQqqm7dNxv3H+By7bWRMrFhJD6klBZN4ZNqXFch5t1xdZ24uVVw9HA57gfipzUGLK6EYDWGHqhYlNKR2OuJeUU4Nm85MFYkksDW1yvG92xLYGShNHYd+mHkgj6y8ua223NQSqgoaxqasvuTWL5uU3VoE2F77pkVcPlUjzTrivj5SmHwHOYZ5pXd1u+fTroiu4L3fCLiy2/f7/fSQ9fZxZfh3stqNtWwh6mgYBNX0lq6zzTVDYZdC/1ZQyNobDjJvJZARytd21TaiJPjjsNlMgslSRrRp6EpbQpqpEF3qVuKGsbouPL4kltpPBdNxK30XouHSDXhryWcb0/jvCVQ6UNR4OAfqhYFZpFJqB6ua2YDjx60Y4BE/FYy1LKwsB3zoac7aW8dxAzCL3uM70NztONgP51KdfEy7VIfxPPkhSvjWv7lMtrzSyruVhVXC4LHkxiDvo+I7Vb5Lpal0S+y3dPEr64LXgxy5lvCj68P8JTDkno8Re/uuL0oMeTwx66MWSl5ny25WwvZW8QkZV155mtGsM0tZJvbdBKxkpC0cST2jLrjhHWvLL/b0OIlL3O8kp8o8ZIuFDqixQ3Clx8JUD6f5pn8U4ipHny/q5f0BgBMNMDuLvGOb6HWc5hvYY4FkC5WQnI3KwFFB2d7rZ58gC++lSkoy3L1rd+QNfKEJSyReVtf+A+hCsLkjQ8/xL9/BUqTXH6K5mUt8Dl5gajNc54amWDWwtIHsHJGpIE89nnOJ6H89bbmKtL0JrgW2/i7O3v/JVffoypKqmBcFyRow5GtsrCPtRMIwE/2Va8lK8VxpOkErrz8rns20bSUU2SwPZOLtwoxnz1Bc54LGEzwwn4gTCjjYaBrYsIApH9toEpNmgEzzKFrcS0rgTojqc2AVbL18rC1jiEOxmk68r32uAc02CyLdS1yHnTPubqXPyfgwHeKIGjIwGeLavouvJ+rR91s4LjU5zH7wjDdvPK3nGuvIeV4prbG5yHjwUAXl/D57+U43dc2cfhREJt2kqK7RpzcwVXV5TndwRxLJ7EVvtg/YDm7haWCzmG4yPCeycC0PKc4HhMdb2ivJiD/hzv3j56WxA+uSdVIK6L46uu25HhUGpCjJExvz6X7sfLSxgMxEPbsqSjsVw3ZQmBFhnrydlOvt1o+X7al+u6KuVY61ruEV3D9Og3br+b/BaAD6bfwhjDZXbVyb0O4gNu8hseDs64y2fMixU9X0rat/WGu3zGqlpR6pKz3qkEwmA4693n88VnpH4Po0sqXXXeMMcyZcrxmJczEi/hODlhfDrhR1c/4pO7rwCJs7/abDgbDLqJXKElVXCebzpJJYCjHT6fvWQaDxiEIYnvc7mRsJv7w6FlDhoeDkf0g7QLV9iUJYXWeK7LsljzX33+z63vJ+YHR9/hID5A2XL0TbXtkibbmgNtND+++jmX2zu2VdHVYijX5dX6jm1Vkfo+m6rqghjaZLl2hbj9dy8I+P7BB1xmVzwZPyD2xLvlOV4niXVtZUfZlEyisa2RqLtJvkz6g294j2pTd3JPF5dNJZ2Ah/EBfb/H+eacm2zOJB4yjiIeDI+tT05CiAyGopEaAqlHWHPau8dboycox+NfvPgzrja3XG5njCORWQ6ClFm+5G/f+z0WxYJtlfPp/DOO0yMcXCIvZOAPOy/ZvJzxNxefcJfnZFXFxXzJV7MZ++lHnA326AcJn89edrLS1ss6iiLmccw4jqmbhrPhgKKQSehekjBNEu7CjMnxIduq4ny9JnfAdyVVdxJJn6j0hnn8sy/+lG1dsCoK9pLU+upC9uIpJ+kxoRJG0dEOF9uLToKrG4020sOXeimLctl55GojFTMS6rT3Wz8CF8USbXSX/LkoJEREN5pROGRZioR2VW46cNP3++RW/i0y1pJpNOm2uRfv8WpzboGqyJp7foLrKEleNBLmsipXXR3CJBp/Q4Z8mV3zbHFD4kWk/rYD+AbDXb6wwUd9GhoKXXKxueXh8ITj3oTEj/js7iWR5/Hm6IybbIY2Dd8+OGUvHhMo8YB+vXpBUdedPPA6u+58iy3DBJDV267epahbsBoSeQImXq4vqRvNptqyKLQtht9iYulvfLa8YBT12Isn9PwU3/Xo+bG93xNcHHzl0/f7GBrCcNQBSpHVm85TJ9UgNQO/j3KkbuP1UCjP2YWxiP9PAK3rilRZwrU002hM4sXcZjPusjWjKGUU5hz39rtFgEEg91Qr19aNMLF70ZSz3j0CN+DWPsMN4j/dWM/pTTbjfv+EWSEg+qvFM47Sfesf9+j5PQJlE4/ts+16O+NifcuzxUJArS67kCFjZOFtka9ZIAsTp/0pp/0pbf/tSb/PzXbL5WYDnHM6GJLXNe/s7ZFVck/4SiwEdaMZRwNSX9KIYy/iJr9jVW642twxCFPG0QDPAu9BMCCyzwzX0cyLBfvx3jfCyAJbBdIuagjTIdaA2mjG4eg37r9lrim04aSvuhAbEEZkEKkudTQupWg98h36oerqK/LaUNaNLYCXbU5iv5vYl1oWBmObDup395/Dpqo7xqat6ugF4t++XJecL3KSwCUNFP5rOr/bbW0lqvKzeQUXq5xH05CjYUjiK7682aI8xZO9iOtNRdMY3j3ps9fzusqOr2Y5WjfEFnSty5rUV68F8eyCaEoLBCqbfBoo14I1eLWscB0oKvHoCXMl6aOR7/L0rmCceBz0fHq+Z4/TpX6NufOUQ+jJGPUtQFI4HTsofjqDbuTc9GzIj0GATqUNQeB0VRTtq+2Q1NaLWNYyH5jEHrHvcretWWUVaeSRRh6H/YDSAs9BpCQLUxs8JUAw1w3T1OPe0CdQAog8m4aLBa1rbVjkNYc9n7tMgrmezgqO+r69BxwST1nPq9xh2hjWZcPdtmK2KUkjAdxt/UigFIHXMM/qzid7PAw5GYWSiVg1TPsh83XB3brgk8ZwMIzZFjX3pil5qfGUK5JXLeM4isWz2hhIA1nkWJcNF6uKXuAyTrxOhjyMhE0vrdd0VWgO+z4urY1GFg5iX7G2zDb2uLK6oTHQDxS/6/W7wWLTSGpl3BPwMRJfF8uZhMrkGYz3cKIYemuIE8wXn8qk2XFwDo/gO38ggSarxY5ZSlPLyFUC9A6O5f2i1BbJl/Jem5UwTn4IPVeAp6uhP8T74e9DkWN++mM4ORGvWdMIaM0y6A8kIXO1Er+a48BoJODP96SfMU5xjk+ks3Fguw8vXsDZI2Ew43gnPY0TYSpNs6sFcVzbM1gIyEtSTFmI/DEocKIYp9+HMMakM5wgwBQF5vkLWK9xHj0W1nD/SADGZiMg4/E7AjDaLr8WCIaRnAvHEaDWSle1revoDy3Qsh7QYiv7OByLf9NVu3AaxxHf5GAsrGBZwMc/l7HzPGEkFwucwQDyHHW4hxNFmCIXv+j8TsYgCLueRRZzYfn2T0SmHEUCJpUSxvL2Wv5dlpirc7i9lTE4fQPOn2E+/URY6n4f54/+iV1AUNAf4iQJ1dWcJivFS3l8KuOjlBzbvRTn3gPIM6r/+r/BDRQ4Du7RAfrFOfNfvJKC19RH9UIJvPE8nLP7Eojz4gXudz+ER+/grBaYf/n/J+2/mmRJ8/RO7OdahY6MlEer0q27R89ADIRB7FIYsaC4WjOSZuQlvwO/BC9ovCLNKJaLBYjBzgAY3TPd02KqqksenTojQ4drxYv/656nuhuNC/jYWJ2ODOnur/v7vI/6Q2FbDUM8l7byi7ouXFxQX1zIudHriXS5P5JzRDfkGGo6OPaNd7E/kn26XgrQpoLrmci8beembuONrabmTuc2HauLpVuM3R2SMmGVLTnenhDmIbveBNM36NkdfCvg08UXRLmwKHd6R3xv93ts8jWrTCa9aZUSWMJiJsqPte/vUdUVnuGR1zl5mbUhOl2rh2/4fHvybU63l8R5gkbNg+EY17A42y6Z+BVDt0eYx+RVxSpNudMbskojkqJgmSTkZUnfldAbCJn4Pp7pKM9hTdf2cAyLTSngres4bLKMoqrYZikgZddRnvInx3/N49Ed3hu9q0JHcpIi4TpaskjEMxwVKV3bYxpu2pAa2zB4tjjmYrslr0oMLWgL6Q1db+WnjnkTk+2qXsXT8Jxv7Hyt9VZpSFF745msVWz+wBngKL9oruSBA6ePZ/oto9j839jZoWf1ySo5Dh9ef0xUxBwFFmEeMk9Wsl+zmFu9nTbVtaxvJF6O4aAj1QzL7ATf9NhxJ3y6+JS6rlllIdMwZJkkbLMMxzBYpSlX0Zq+4/KN3Xd4MnjMaXjKz66/YJvHDN0e//DO30XXDLpWj3/59j/lJ9MP+bfPPsLzHN4a7/JgcIt1tiUtcr6594TA9DF0k8toyv/9o7/CsaSG5N5gwDJJeH49p65qXM/hdr/P26O7zJIVDwd3iIuYj6dPeTK6y28e/AZxEfFvX/4HngzvYWg662zNi9WcaRiSlyWfXk7RtJdUVc3t0YB/8fbvMXQGdGzpb7vbvYupmSI9Rdi7vj0gKkKm8ZR9X0I7ZsmMo+AIq0mV/mW3QCrG7qgFbV27q5jsrYQXFRk9p4vjOQRWgms4vN6ckhYZuq6z4w15a/iYKI/aGodGOguoNN+MkQKTtmHRdCEKOxnjqwqcjhUQK6YwMH1+7eht8rLgZ9OnHHZ3ud09lITkLCbKE7q2zzRasM1j5rHIkAduB9/0cEyTB4NbeKbLfrBDVhZKBu0xTxaM3bEki1oWtfIJi381kUWKMsMxbEzNlEqNqqDSK0nBLmCTRZi6wdgb0LF8LNfENR0cQ0DOq9WUdbrlfv8Iz3QYuQPW6Ya0TBm7Iw47+23arwQTSXejbUhQUAP4bsq/BUT4ptdWy1TK19dUlTRyzRspn646V4M2qOXZ6iVxnjDxxiRFwjoVoJgUKYfdAbZhkRZSUaRpWhtsI9JSi6t4qq7VY062JxgqrEdX9SizeCWSyzzhMrpmmay5NzjkMDhgGk/5cv6adRbTd3x+5+i74sdEo2t32GRbLsKQpCywdIM9f6etc3EMhz1vwp43IS1T/tXT77cs8FF3yPF6zqcXV1Rlhes5BLbNyOtjGxa3untEecLJ5pJv7TzkTvc2UR7yZ6d/w/3+EaZucB3PVQdthW2YXITz1lLQd3weDG7Rs7tyTugGe/6uYoklBVfTNLpWl/gNz31VwzbfsOtN6Cjw/wvjr5ZJs3i0xFdV1jVRXrJMSvKyputI355vS53D2TojyUWOOfBM7g9dEhVoAgJQXDXJz8uGCWySXQXglFVNYJmq2kFX/kCt9dwFtsG3b/fIq5qPzyMO+zb3hi5VXbNJCiLlFbzYiIdtHQlg67kCAAxD59FE5IX7XZu8FP9j1za4jjN2PJvA1rFNCVnTkFCYxmPZhMtUtSRkWnqF3nQelrJ/dA00R2fgmTiGRmCX2KZGklecLhI2acWjsYNn6Yx9k0VUkNoVY8/mVs9t02Cb368pGaP5S7xtjYTVs3QCS9iqqoaiqkQUZ+vYhsHPz3ICy5BjqpJMXy5SoqxiEmhkpVRmdD2LJC8ZdRxhOgsJdtmkkqgqXlTxh86iAl2DkedwsUnxmmRWBaTmUaEWKSS9dRmX3Bu57HctrsOC57OYbVLQcU1+616vDZYB8Yder1PitKCqaoa+hA9ZitnsOSZdW87Pj083sg+oGXccLpYxL06lAst1TayeS8cxAIeDnk1SVFysUz446rDfkf/9/Zdrbg0dLF1nFhUMPIOkkMqWRVSwiCTUz7UMyspqx4Gha+x15J7W9IOCeEfjQhjHnmJnN0nJbsdqz6dftf1KsFiHIZph3IS4GIpJGU6E7dINAXSN/2q7kQm1ZclkvmEk01Skd01yaLcPZ8c3sjzLlsl4kzoZbwXw5KrbznZEtgfy3P1bsLMn1QaOIyyi3xH5386OMHjLBdnHX6I7FsV8i6ukTvVmA7dvo/VHN2muw6GAqPVSPivPBMBNzqiffob27teFxdN0VQb/RiBNlgpAyjN5TpbCcin+v+1GAETQle+4WaGZEbiOvMY0BZCCgAbzjcL3Rj9cFm1PpPxvVTrfxEwXxU2QUFULQIGbvkd4I4WzvgElzfF0A9mnZz8Ttu7wSD4vDAUI7UyoP/tUWMVmi2PqOEYbjGS/N7x5lshnzi6pXz4TKer+QMJp4kgYU8eFTo/64oztH/8U9+4J1n9zh/rygvAHn+M/2Uc/OlIyXRNePaP68Y+5/uFLrqYx9x+PVKprIL9reiGM96N3VI1LH+sf/QPqn/wN0U+eE/74NWGY8/Q6xNF0OobOrTBnovZTfXZK/MNP8Z4cinfw+kL6Kh1H/KLLpSx83LqDNtyRrss4oj4/gSxDe/t9YZybrs08g9pqZdp4/o2k1zBgZ19AtusLyK1KWaAYjn9h/K3SDXrXkNqFqsDUZWI2dnbayoBtLt2IF9GF8kVVeKbD3d5t3hu+1wLEJkChqHJ6dpfj7TEaAmQs3cIzxYNHBVEV4hiGqtwQeWNR5Twe3OeT2ZekZYZnOlKGXklwwSrdYOkWviVx8nGR8mq1wrcs5nFM4fstYJv4PrZhKm+cRqB63Zo0v6Iq6NoBlq5zGYb4lkwkbE0jzHPyMuTj6VMMzeAynHEdL9A0nXkcyqpaJnUMRVXhWVYLApsLv20YcoNVk6kGHLqmKWE3VdU+V1fMJ9CyiE2gDAg7VVZlGxLktP45YUg1buodamoM1YDUSPR808eqLI63J2RVzt3urVZSOHR7HAa7/PTqM253b8ZfnCfEecJg5Iy3AAB08UlEQVTQGRCYQcsuZKWEdczSa16uj/nNg+/x6/u/xh+8+iOeLs4oVFfkUbdHVpX8+cuXnG7WPPrWQy6iK/70+CnvTSbc6R60oTGvNq/5y7Mf8xcvXjGfrbh/Z5/9zph3R29j6iaX0RVZlfGo/5BtvuV+9x62bvEXJz/jy+sZf/bsBWmS8fL1BY5l4XsORVHim9IxeLK54I9ffcb7u/scBgfMkznn0TmOYZFXOYs8Iitz3ts5JB1mdGyfpMg43cwxNI1/+vB3OfD3xTuqiXcMYJWtMHXpGO1ZPRbpvGXoPNPDNyW9tKxL5vEFA3vwS++B2yxi7I6UH6dUIUWm6js025AaDY28yiW5tKqwDIv9YIfbndtUdUlRFyKdrEsVzOO1yoHACjA1Q50nmjo/UmzNJlU9hZK0maOhYWoGQ2dAz+5xuj3DMW36TqedmO94fYqqYJlu+HgqDOI8jttKk40ecdSZ0Hc6Iu1VQTmWbrDJtgqwCrs28Ye83pzzaHC3DZlpOinruqakaqsQmgljjXgrA9vDy2Nc08E1HHp2l7iIsQoD37IUsBAQqaEx8XcwFUtf1cIIN2NFglJKbFR9UF1jKJVMpfZpjUi0HCVNrlTwCyBySG5AYvM6XTNwDBNTt7jeHpOXBfudHUxdpMY9p8PYH/Dp9Qv2gpHUbwBJkZIUKV2rg2e67W/PVSrzKlvyen3GB5N3CDyfRbpkla3oWJ5adAi4jGb8x5dPudW74r95Z5fLcMb3T1/z1njM7e6eKA7qkovwkr+5+JyfvD5lMV9zdHu3vWabSmq/Kgtud4+Ii5iu3eWfPPweP738lB9dnPPx6QVxnPLq+BLbNPB9lzTJ2uvq6eaKH5y95u2dHUzdYJkumcYzHMNW3kcJ3DvsTBi5fW519knKlPNwSl4WvDV60Ca9NpUwpg5REWIqINuxAlbZCl3T6dt9XJUg6xoOVV0xS2Z07V8Mmdoo0PXmRFbuGSJH1Wl6/gT4NTJMy9CYBCZ7HbsFf00CZ1VLBcUiKqiAji1VEm9KPfO6ausKmsXGvKyodbl/DF2LnmNyrBJO+67R9jZOOhZZUbNMCp5ebrFNnU2c4yjmJswkxKTnyvfRNRj5pqSoJiWOKYB17FvsdCxeLVKe7HgCVA2dpBQW2dI1auR7eZawqblKQV0nJZUDrkoL9S2dvmsS5dKbaFtGm67qq5CY/e5N8mbDqDUhNJZKGm0AanMc2uvAmwEqb9RptY+9cfze7IPUNA1Lk/F5sUnJy7qVySa5sKAj3+TpNGa3e7OgkOQVcSZ/98wmAVkApqHDNpOqk3f2PAJbZMWpYugMHTzL5nyd8ZNnM0Y9h3/2wS6X25zPjpccjgOO+o56r5qzdc7PzjZ8/nLBYhFz+3YfTbtJJb3Y5uRlzZ2BQ6IWF/7OkyE/PQ354mzF5y8XxHHO+fE1pmXieA5xrFhrTeN8DZ+frTgaiSd8lRZcb+Xv0qupAqwsnY6js9txSYpaLYpU3Bs5Siasxl9Zg6FSgDVhhANLZxELkB54BrYh57Fraiq5vaTr/BfIULUHT1R9xFYYPriRe3qdG3mmoSbJ6mak3b4nbBHA9Ewmx4YBsSokb4Jabt0TsCilH0qyV8mkHVTQTA6LtYAivwO2eeN/2zuELJWglK34xbTDW+L3MwysYUBdVpiDgPT4GqffRzu6JX450wTTlSCabo/6+KXIaMe7AlwNQ1i/+fymLqKuZOLfROSXCNBq9kmWwGYj7FNdUyuZreao329awqJOr8TD2HQDRpGAyd5A3v/N6gzHvelo9Do3YTrN4DNUsE1ZiswRBFim6Rt1G2+sBDUDuCwUANYEmGWJ/N6dfWHSJvuS5LpeSqCQpgl4apjCPBcw7HcE+E7n1JcXIgGtSnmv01fwpCvv2e3fLCwUOcymfPrZHP/FigfT/wvFOqb7vcdov/f34fyE+ic/QDs8or44Z/Y3L8mLiodf28P9nW+h7e7Lb0ti6uUcbf9IFh8W19KxuVhw9R8+ZjZLeL1NSeuKbVlhaRp2obF9vSbLP+fg1+5Rb84BSF5e4d67gmdLiucnmPsjePVKzhNLgb93viH7K9zIvvGVXNhWDHSZU3//T9B294Q9bKtRdDmvmkTV7Up6SZuU20Yy/XPbO6O38EyXbbGhbw9E0tOs4Ckp5Hl0riSQRSvNejS4z73ufSTG/1z6BTWTuI6xsEirlE225X7vHl271yZEllVJhSSlAniGT1HlzIotWZnxoHefx/1HnEVnfLF4zlU0Y+z5KhigJK9KAsttE866joMOTIKAWRTRsW32giHbLGwlr7pm0rUdQpWg6Jo2eWWxTDdSG1IU5CpAIHtDOmHqBn979XkLBCsFEhopZFqWVGmqLpYCFJu/+QpAZmWJa5ptZUaT0AbCWFi6jmeJdPROVxjehhVswZ9mUKhgjyZRs+lTLFTReNMDCLTArul5BFSdR0Jgeez6u5yHF+x6EybeDqtsxePRHRXZL+yHruvkpchOAyvA1m3W2ZqL6IqszHlQF3Rtn1eb17w9fJt/dv8fE90KmSZTNHQ80+WT+Wf8d3/5Y66vlvyf8/8byyTh9+484B/c/T1Ot6f89cWPuNM95HR7wfdfvaYsSr7++C7/8P432PN3KeuSJE9YpAuOgkMuogtmyRwNjaiI+fD1KZt1xPnVnLwoSeIUzdCwTJMwSsiznN9+dJ8XSxl/X86mvDOe8/niGV/MT7nVHfPl4lXrqXtr9IC3B2+haTpRIQuHvhlQ1SWu4bUJmX/w4t9z2NnldueWsM61sBojZ9zK+jb5mmW2wNGFoRrYA8r6l5v773SP8FR9RNPZ2KSBuqYsDCzSpYCZqmwnSoedXfa8XWoq5ulC+gV1k6wQQN+khu4Hu/hm8BVpWZN2Wyk2r6gL4iyhVJ44eayEMmPkDsiqnGWyIcrFI3bQmbDJQizdZOgKQzBwXY7XawZOwFH3kDCPBPjqhmItO5xuLyRoye5jG1LvEVh+K2ttrj+BSl5tklE1blali6okzAQg1mrRKFOJsQaSBjxw+4xUuf0sWcoY2Kb03Q4dK1Aps0U7xpr6DkOB/zeZQaCdwDbJp833yKuCUgHGN2ttmmPYpEKDqmKpRFI/dAbMkgVDZ0DX6hAWEXd6ItPOqpyslDTkrMpJyoSslCTZRbrkKpyRVyV1r8azXKbxFK9zm5E7pGN1iIuoBcOLZM2zp6ece9fMk4RtkvKdo0N+59Z3mMbX/Oz6C/Y7O1yE1/zk+JQ8L3jy4Ijfu/MWu8FIvMpFzirdsOvvcB3PWGUC7FbJhv/4xVNWyy1nlzOyvCCLM9A1rE1EFCXkecF3HtxhlcwBeDqfc6+/5kVywvPlNftBh5erc0xdUoDTIuNB/74KMItaxURzXsp1reSHFx+yF4wYOn1Mw1CdlAZ9u4+li3Q/zCM2+aZddOtYnXZx4M3tsGfjKH9c0wfYbE3YxyZT6aT1TRXGftdi6Emo0TrN2+CSopIE+7IS/9cksHBN/Stg9M3wFQFJNWldUVY1NTqadvM9x75JojyBUZ7gGBpHfZttKnUdXc+iqmp8x+RyGdN3TW4N5O+WrrUgtWObnK5TXFOj7whwNDSDrmMoaePNd+pab1SJARhNuqwA5k0qXsNasYx5JWEzIABnJ7DYCSzysmYWyvgI04yhb9JzDTqW1nZYaprUlCSFeB579lfrMZrx19QwOEbjs1W1Dm90r76pQG0ApgpZVV1/8j2HvsEiKhn68vujvOJw4KjrpnjvTBXUEzdhO4bGOi2YbnPyqqaqwbOFkXN7Ur8RAKYuPr6mZuT50ymnnsMmzkmSgoeHfX7rYZ/ptuCTq5i9jsV1mPPl6yVlWfPgwYhv3x8x6ZhUNSTKDzsJ5HlNTck6Kfnhp1cslzGzizlFXlBGIRgGoe2Qxil5XvLuwzFxJsfgYhlze+Txcp5yvogZdmxOFgmGCtJZRAUPx03nccndgTCtTVhTs99/chEyCSwGnoFhyoKHDgw9sz2HkqJkmxVtZ2bX0VvO5z+1/WdkqCW8fi5A5fH78lhTzdAwVZN9mfxvVmC7aAdHzRkkzxtNZJLc9CcWhYCIwVgkkIaSGm6WX01HNc2bybVvyGQ9DmF5LRUK8RaqEs00qYuC+vlztG98m3o1R5vsCwgcX5B98gJzGGB3+gLk6lqCY4riJq3VstEcR8Cargv4evG5+A/vPbgpUm/SMN/cP5r2ButXimzTUSzmyxdoR0cib7VUF59hqu82pm46FqdT6rWE42j3H8g+Nc0bUNr4JOtKgmmax5tkUze4qcSYXwqICzrtZ5FnwtS+mdpa5lA7gHHD8EYh9XP1u3cP5Hc5Dtp4ApuVeDJjtS96PQGYKqG2bpji62vxeu7vS3VIovrLmu8YbuDyDK3bxdTgIsp48dfH/OajEdq3v6ekzhm8eE59fc3sL75A0zQ6gYX7YE9A9slrtHEo55ttU796Lqmmug6Wxcn/8De8uAjRNFiXJWlVtxHRrq6z13OYvLOHvr9L9tlLym1KlkW4YQieR7EMMfse3L8PJydUqw26rqPt7Mt+TZOvhgcFHfnOFyeStuq48rdwI2NjvKtYXE/5W6ubc8L2YDWTcfbzw68uebp6RmD6vD/6oE3eLKuyTQTd8/Yo6oJVusIxHO72jlrAU9YlQ0dSA5MibpmXl+tXTLwJfXugPCcGy2xBXMQEliT9maaFrUupttFMqCoJg3jYe8TEnXCdzDgLz9hkEX999gX3B2OyMqdju+hojL2Kl8slXcdh4vskhcTm67pBXVcobz2WLkmGjmGpUA+XtMiIipy+47QSUQBTeQhtw2KbpViGQVqWbc1FVpZYhpj1I1XpENS16kgTyNawiIDyCJTte3RtG9c039D0S2BOz+5SVmU7KQJa4OgZXutFXKRzNvmGwAywDKsFeY7h3gRWqG66WndaWWpPBZ98vvgCgD1/t/VZTbwJm2xDVmWEuYyngdMjLVPmyRxTtzgNTwG4CGekZcbt7gGrbEVSxHimT98e4JoeURFyuj1l5A4xDYOr2ZKT8ynf/MYTfuPw2/TtAbmf89n8BVfRjP/w7EvqGjzf4cFwTFblvFwfs+dHLTPwYv2K1+tzTN3EMS3+nz/5IcfHV+i6ThgnVIV08tU1uI7N7u6Qr90+5Ki7y08uXrBJUxZFyTaL6Fge0yhi4Li8Nb7P8+UJs3iNqZttDUpWZliGRVxEpGVKYUo9xnl4zt3eEZ7pEhYR2zykqkt2vB0MzcAubQn7UTUx0hfpsMnX/O31R3xr5zd+YQzW1JxHlziGza3OkTpnjJuy+Lpm4PTFj1ZEWLrFXiAqgSYltWf3sBRTZWrCoF/GU/pOj8DqtAmZURGSlRmu6VJWErpk6SZVLYmjKeKP2+YhE29CXmZomkzkkzrj+fKEr+0+YZtFTDxhQyd+j4+m54w9j/1A0oul31DGdlEWpKSKqXLo2p32vL8ILynrkju9fek91DRcdf7fsHPCwjeMWllVBLaHrRaujjeX7Ac7uIbTdmYKSNUZezttDc00mrPOtlR1zZ3ePkOn36aCFlWJa7r4piwK6Cp1VD5fFmwMwyBX42udrYmLREmHjXYxzTbtr7AaRV1g1hamLmmcnukR5QmvN6dUdc3QGbQy2LE3YJtHJCqwC6DnBGRlziqT8/MinKJpGlfRkrzKOehMWKVbMj/D0Rw808XQdKIi5jqZ07V9DEPn8nrJ67Mp3/jaI769/y5du0tR5TxfnnAVLfj+y9cA+IHLg+GQoio42Vwydvs4po2tW5xsLrgIrzE0Hduw+NcffsTJyRWaprHdxtB2qGk4tsl43OfR4S77QZ/PZpeEaUahxqBrOszjmJ7j8GBwwPH6kqtEwsnG3kh5bQtMzSAuInLlqyyrgmk8Y8cfSC9vmRKXCYXy9xqayOWzMqOqq6+kuK6zNefh5S+MP4B5lGPoGpPAbtkTuAl76TlyvY5zAWBjX67tuoZa8DAxNAEkDVs4i4qvyPY0pEajkZ3WtTzX0FQiZq1R1yVZWbFOC3Z8m7goiXPx/mVlzYtZyjeOAjZpyU4gfrJRx+bpxYaeb9FxTcKslOupddMBmSKeQNfU26L4soazjYRm3Rk6ZIpNdAzx0ze//c1qB3ld3bKcAK+WGUd9G9c0FDgV5tDQNXY6VgvmrjY5KwV07g5sxr6FrhZQQboJLdU/qb3x+c1m6RplLY9vM/GLupawn01KqvVzr6rrWond5HHP0omyitNVRlnB0DeolNdu5JkSUlSK/w+g4xjkZc0qFbb0YpOhabDYZmRFxUHPVsFGUs1jKyYvKUoutzmepaMbOsvrJT88nfLWB3f4+u0ugWWQezWvFgnzbcbPnosCxPdNjka+hOKsMoaeiWvpOIbO+Tpjus3ahNI/++kZl2eyCJNutzIPBMDAsi16wy63D3uMuw6vr0PStKBQwNM1dbZJTuCY3Bq5XKxSVpGoN3Y6pgodEgY1KVS1iapOmW4LRp6JbQqYTkvpuGy8p7ahkRS1OqYi37UMnWUiQPtXbb8aLBaFTGp3DyDa3CQ2NuEoVXnjK/M7ElrT7St5ZwmNtrlSlQKWLWCvKgWoNR7GPIPjl8KwNHUCeSZgUTcEtLiefP78Cq4vqF98gabr4u/7j/8j3L1LffJKwASg9QZo736Ae/eepLZGW3j+nHqzFumn41CfvkazxRNYr9fyfo3vbPcA7epc/V6jrYYQ+SY3fsWmJzKOZJKeZcK6PXummLq9G3CRxAIigkD212qBFnRhV6NWXsv6k5+B/ikcHaHdfXgj0e0O3hhlqrNP04WlMk0BYxuVCDtQ/jlNfwMYVrTA0DBgvro5nnFEfXkmLGpVoT18LAm2lt12WLZex+b417WAQgUitcFQGNu9PZGuzq7R7j+Sz7BdCJfQHcuM8c4DqCve+mCXfJvQ++ZdtLt3pU+zKKjPXrP+80/44vmKnYHDnd9+QF3V0O9DHFOeX8HzV+iejTYYiM+x3xe/apoyGLq8Zem8PgtxdI2JZVIDHd3g3XfGuA8mGMMe5DnZ5Qpr0mX1bMbmD/4aa9whutpQxTnWIiS/3hAvYsa/25W7z2ZF+v/+V9hHY3jwAG00kf3jd+R3JbGwscofWp9cSVCOr5j4xvs6vRTJs21Tv35O9eHH/LwToKxKulaXW50jNvlaQmlaqU/RAjmjNujaHXp2j47VVSXZstrbyOccw8XQTRbpHOlfjKiUhKyocl6sXzJ2x5KIqkkdg60CWeS9XAIzYJZcc51Mebp6hobGu6N3+Lcv/wMf7N7mKpyLuV43sE2HoRtwcGtE0wV4tl3K6YOGadhERYKO1Gw0aZKe6WAZloQnZFELAh3DaD0TRVUxV1UjqSp8twwDvapaKenpZkNWltzq9dhmGa4pE89NlhHYdhusU9V1K1VF11mlKctE6gtGnkdZVTweDumYXXIVZNGABE3T2roRz/BY5yuSMmHgDPANSTCuVeBGU3PSMI3bfNsykUkZcxaecRnNqOua98ZvMUtmbYm5pafKs6VWaRHGJa8KVtlaVQkMsfSQo84u+8GE8/CSt4aPCFRvZphv6Sup5Z3uHeq65u3Ht1jHKb9x+zZPRveYuBPKuuB0e8a/f/E5L1+cMxx2+d23HwGw4w0Is5hX60s+uX5JYEsBeJiJz3GdhaRFTr/f4cFDk7PTayzTpD/wKesa33V45607PBmPGbkdkiLlbLtlr9Ph+cWU/9dnf8PE97labwizjKsoZBqFLLYxo8cdCTTKNvxfP/7X3O2PeHf8kB1vjKEbBGbAnc4d0iplla4k8ETTONme0LN7bUiLb/os0yUn2xMGzhBLN3m1ec3fXn0Jb/+SW6CqPhk6AxIFQKROXG/lj4ZmomsVriGAxjXFsypAw0SvpdbD1m0qrWKTb6jrui2mL+qSsk65jK6UJ7LA0HTp8dQMdE1XHYx2O7Fepgteb84wdJ173dv86ekPud3b53w7JSuFieg5AW+N7nOnd4Ch68RFyrPFsUrstbENm/PtFZ7pkGhpKze0XRtTM9hRgFMK4PV20Uiisio0ldhZ1zW2AgEAWSny9KeLUzxLgFau+hCzMiMpUwLLwzUd8kzCcCb+iG0WEhcpX8xfAXDU3eWws4elWziG85UevoZpkSCSULGODmEugDuwfDVWlaRVScUbhl/YsVhY6bomLVOm0ZxFsqaqSx4MbqvUWhPf9MiVd7DZGjazqEq2edSmvIZ5xEFnxMQfMouW3O0f4Rpum0YbWD4VNQf+HgCPH90iSjK+frjPg8EBI2dIWRWcbi/585cvefXyguGwy/ce3wNg5HaIi5TTzYKn9QWuaTLyOkR5wsDtsk4l3KbbC7h//5Dz8xmWbdHtyO8MPJdHj2/xcDhU4VMll9st48Dn9eWMf/f0U/qey2wTEhcFizhmGkWsw5j+fVko2OZb/rsv/pKjbpcHg1uMXAGCruFyGOy3CxqNomIaXRJYPoZaaLANm7iI2zooS7c4217y08tn/O/f++r4yysJL+k54h9sQFCzEFNzU3HhmjqemrxL96WSCqrnmY1sM5cUzFyxS6UCQddhTuDoLRPzZqVSrZQmwuAUbNKC01WGoWvcGzr8xcs1Bz2b46VUPDReyw/2Pe4NnTaV9MurmDCT9E/b0DlZpS1gXUSyIDoJLAwNJoGNpmXoGiq5+M0FEgFhzZzB0nUS1RacFjW5VvPlVYTvmIx9SVc1dUP16tUEto5v6ayTksDW2e9ZrJKSJK/47CoGYu4MHW73HUxdQIVhqPqFuv4KYE3Lqg0BSktJcRWP4o1ap3rjWDVbUlR0HQWOq4pZWLQ+1HsjhzAVFtC1NJXqqbXpyW1/YCVdkklRtTLbcddmJ7BYRAW3B3b7PbKywjVFrnnYE9b54aMdkmTA/cMeR0OPkSce0eNlxsfPZxy/mtMfBrz3eAdNg54vfsKrVcJJXWNbBl1XPJVdzyJMcuKyotezse0JF+dLdNvBGw4AcDyHB48mHIx9Oq5UkSw3KR3f5vxyy4++nBL4NutNSl5UbJOcVZSx3Wa8d39EXYuM+Q8/mTLuutweuYw8qfmyDZ3DnkVe1YSpLGJomqQFe5aOY2ptl2RSVMzjClMD29Q5XWV8erb5xRvgG9uvBouu8hFmmbCAmqZYLQVW0u2Nd2+yr4CUdSOBNJRXrpFB1qqSwDBVMIolksc4kkl0p3vTBdiElwDkyHtrOvTHUGRoe4fUP/oB2u37lNcLzN/6Peqnn8l3Xa1uJK4LWyR/jXxyOqXe3YWLU1guqRcLxSaWUm2haTeT/6IQABt0bpjUWslkFTNBXQuwLUtYrwW4bLekJ3Ocr4/FT9ftC5vUgIbFvO2FJA4lJGhnT4BGrLyZe0cCkE1TfZ6S5jaS3bqGqhDwfXT/BqDnKuHUfSPeu/E/FrkAt6YoXtVUEIeyz9IUgoD62ZcQBGhP3lUhO5YCy5H8u0kMbWR7zXF6IzxHG43knLBdCdoxbekYjLZw+oo62lJlBVbHRfM8tNFYQJRpStiMrrWK2TovMb75AVxdoR0cYNS17Gu1aU+eUM/UMR6N6Pz2+zgvz9iGJ+xoDre+d5f0ZI7uWbi3x4SfnrGcv0LXNZKkZPtsRVKUnF9p7K8zyqKmLGsCQ8MadTACRwD++Ql1WaJ7NvHnp3hFQX0/h9PXwsDawh7Xi7kw2Ee30SZ7csyb6pKgC6sl9cUp9fPn6L/5O1AU6MP+Lw4/023TMvv2oC12r6kptbLthtM0jT1PQmpMzSSvpYevrM12JV+GX93GzXsqNOM8OiPMozaOv3n/Qq34N1utZGh9e0BRFxz4+/zZ6V9zt3uHq3DJ/+qdf85Ppx+15c9jv2biS6LgNgvJaklIXaYhXVsmKWVVcRat2tXejl0wUkG/jmmzySJ8y1LguCJVMtKiqlRqn3jwXNPG0g1WqXQ8LpKEVZJwq9cDwFOhNUVVMXBdtsrTaGgacVEo7b4pN9yiIFbSVpAbs2e62MpfZajJe0VFWUvq31FwRFZllHVJVmYMnSHuVya2coMravE61ioBM6syTMMkLmLmyYqkyOjZAR9ff8bQ7fH++N22I85UTI2tW+RVSVpmaEbTx9espCtZHhr7/oRdb7cNxbEMm22xJS4iTrYnREVMWpT0PAffctnxRoRFKB2My9fout6Ov7ws+Y2j97kMZ9zq7qvfvaVWv+v9ncdcRjOiPGbij/j9e2/x+fycKEwYDjv82uP7vF6tcE2Th8MhP728ZD5/jmHopGnOSXxJnGRMp0s2kwFlWUnZsKEz9nwCy6bndDgNzyiqAt+y+NvLM/Iy552dB7zaHOMqMGFoBvNkAcDt7hF73i6e6Un0v27hGT6atuI6mfOnJz/kH977Hcq6xGuurz+3yb6XhMjA8mn6quS40vr1AAaOpPuamklapcq32tQK3ASylGrhQBZjdObpgrRMcQwH3/RaQFPUJV4zdutaeey01vs48Uf85PITDoM9Lrdrvrf/NV6tT8jKglW6YT+YEJg+thGxzjakhXTbXYZz9oIR02jOKt3wYnXejsFtFrXnkmeKpzOwfCW5Fdlpk9Yq5epGG0RTU7PNQqIiYZPFnG42fGPviEWyomP7aiwKmF4ka1V7IYtFTbpmWmYtczf2hqorUT6rTRJWstfmc1umtcrbCouuApiymdR6Iy+vsHRVjVBXlHWBqTskZSqBTWVGx/J4vjwmsHweDu6KB08zsAwLiqQtp8/LQqUsgm00SoWbHseh22Ng91v/Y8MqpqUsDES5BH/5ro1vWYy8vmKnTU63wsw3W1nXfGv/AdNowUFnQllXrNLmWGm8pQKj8qpi5Hb4nbv3eb6cEccpg0GHbz68w+lmg20Y3Ov3+fT6mtWLY3RdkzEYXREnKYZhsLPTpywrqrJipuuMPI/AtunaPlfRtSROWxafzWbkVcXDwSFFdYVlmLjqOtkEjR10Juz6I7yGjdQtPMMlykMuwmueLc74rVtSvTNwf7E6w9IFKJS16pj7OQlkE95R1zV911ReVpEZ6oq50rU3mTjZlyLtk/depwVpIQyW+8ZnlHWN3cqX63axLrAMyhrGgcnH5xFHfYvZRljFs3VGWtQs44LDro1vmZh6wTotiFWVwcUm46Bnc77JmEcFS+Ulq2paGeNeR75LWUHPMX6hML3tVtSkb7ABx6ukJM4qNmnB9Sblna7DQrGomOBbJq4p8lPbkF7CpKgYuAIqk6ImUczdJLBaoPWmDFYD3mT2t1nJyLNaKXhR1li29oZsWFVXcCPxrYFK7VOprxL5bJpX+LbOyVJA9P2xQ12L0tYyNMgF9Je1SG41DXSankfaBZ0mTEgYNa3tz0yKkrSURNGkqChLCZxxLfFGhlmFZWhMNym6/oYns6p596jL9TbnoGcLSE0E3GsaPJr4zGNJwe16Fl9/sMPpPCSOc3p9n3ce7TDfJBiGzv7Q4/hqy3KZqPFX8DrKyNOc66nGaNyVTuy8Qtc1up6FYxkiZd7mKqDJ4GQWUlU15cjlbC0+XEvXRJKblFS1VJCMA+muzKsaUxeWOMwqLtYZp4uYb93pkRYVXe+X3wOb7VeDxd5QWLE8E4DXnqkm1BkE/Zu0x1qFpyym8jrTvpFJZm+UrU4vJBzn8I6AFl0T71Z/JADHMOU9oq1iY7SbBNKmJiJXs5iqov70I5IX13RsR0rZv/wMrdOR8BDDEAZTSSzp96lPRQIpjKgucsr1WsleTerLS7RAJplM9m7CYTRdmLvrS5EVDsfyeBIL0/nl55Qn5xg7Q6o4xT4aCrDSDWEeT18JC7pZCTAbT9AObgvAK5WcdWdP9qPjqBRUS6SeoPaleQPYa/W6nX15vIgELO0dQneo9o96X8sWBjLawuRAPsNQ0t+6lu9mWbC/j+Z61MuF+E57Q3ld05Oo6wJ636gCwfNaybFmGNRNdcn+gaTmNsmsuiH/7fThra+hPf+Mzj//HXlPw7jp9ASYTOj8/YAPBp8xe70kn22pf/wR+WyDf+sW1XRGejxjdrpmfNTDsyzKlycYk6G8XxBg/9Z3eXC4I12J8znp6xner70PsxnzaYTrGmR5hWXqlGVFVFWYmsb5VUzHNXBdA/fOGL3fFYbYsqA3RItDzMMJ2cWSYhFi3q3k/HFd6kjAtPbkHRkzvkoRVsE7gJzbhoHW68ODB7Bdox3epvr8i18YfkNnKF6aMv9K912zmt+3B6rLylRyMJ15OqNnyQSl8dTFRdS+9jK6wDZsDoNDiipH13RcxZw0AHKWXhPmYeulqhD2pJHBpmoyV9U1H85+xmczYcHeGT0hLlLVl6aRFBnbLBIPT13Rsz1ONst2Yl5D6xkEkZiu1WRVJI02WZVj6xLpnZg5WzUefNNpJ4xFVXCdRFyEIV3bpqgqJkGAa8rkwTIMojyna8vkvEkFtQyDjm23n92A0Z7j0FWPJ0XBLF4q9uQmqKZGZGxjd4wUvOciPQsO6JjdltHV0TF0g22+YZtv2fP2lVdTY52tqK2aV5vXWLrF3d4BgRUwi+fc79+lZ/dYZ2t1zIXdSWoBqes0o7BKAkvARTOhvYpm1FQcBvussw2OCnExMNTEv8Pbw3d4vn7G//r935LAFN0ksDqssmaCt8N/9Tjg+77Pi8trrsKQ759+zDSKuPv2IZfhnGeLBWfXC25NRth3LL6Yn7AXCMPgu13+4f0j7vXH7AZjrqMlzxcL/s7dd7gK51xfL3E9hyIvsG2TcBuTppIeenW1xPcdbMfi8WjMwAnoOR0cw6ZndYmKmDu9Hc42G+ZJTFXXrJIthV1ytr3CNizeHT1RFSo+pm6yybdtzcEyW2BqJkNnwPuTR2yyLYfBAT84/9kvvQV2rIC8KlTU/w0Yl/O3xjM9yqr8yiS2KU031cKLhkZW3kh8lukKUzfY8XZaL6CtW/jKf2roButsTVIkeG949Iw3aiJq5cWr65rPF895sVxi6RZ3ekc8X77GNR1sVUQv/YwuYR4xdHu8Wk/p2rJvdM2ga3tssljJ7nSm0YKOFaBrGkNnoNhwCYgJi4R5sqDv9OhZcp7nlUgxX6xOOV7P2PE7JEXBUbeLZQjYtnWbaXTNUeeQpJSU0bHXZ+KNVTiN+DSHzoDakQWQJkAor4qvhGW8ua+ruqSvJI5pWZJXOWN3RGAF7TVK9p1GVEQkRcLAGbbHsZF1X0VTSfEMRvimxyJZc9TdI7D8tppHV6BfJo8VYRlRVDaeddOPaGg6s3glE7XOWMCf8n82fbSB6fOgd4/j7Qn//MnXlVRWwzc9wlwWiyf+kN9/GPBDz+VsumAahfzN+TNmccR/9XiPabTh9WrF5fWSybjPb902ebGcsusH6pg6/M7tXW53e4y8Pst0y/F6zW/desAsXrGYr3Ecm6IoMU2DoixJshxTL5lOlwS+i22b3Or1GLguHcuT+hI7IClT9js9zjYbZnHMvX7FOtvimg5X4RzbMHk0vEtRFbiGi6kbbe0LwCpbo2k6PSfg8ehI2Nhgl89mJ78w/jxLAseysqap12uBH7T1BlLc0BxT6Uc0lPVEgzaApa4l/MXQNYaeRaWmrYbehJ9IyXqYSx2Fpeut167xI2uaRq1SPsu65otpwsU8wjbG3Bk4vFykb5TWi9TUt3S2RsXQNzlZJPRcow2T6ThSZ9CUyl9sMgauJIeOfatlFgHCvGAe5Qw9k44tws68qlimOc+uU86XCcOOTZpX7PZdbFNAsWPqXG4zbvVcolwA6m7X5LBrUyiQJ2oaEzxJW5XvLxLXN8Gh/pXxJymgGlAoj+TQM3FM+f7N/jc08UFmZUXXVoubiCRUM+Fym4ufsmPiW0ZbbeGbBklRUVCr46SRFfJ9o7ymrDQ8+8avZ+gaizCnqgXshlmFpVft96iRTskHI4PjVcpvvDXBUqBZ6ikEKI8Cm+88mdAJbC4ut6zjjE9ONyzDlFuDXVZRxuUy5vo6Yjz2MY0hF4uIfmBj6JLQ+p17Q3Z6LgPPYpMWzNYJ790esIlzFosE2zbIcxl/VVmRqXvg/HqD6ztYlsG469BxLTzbwDI0Bp5JnFWMug6zTcoyyjgaukRZRVHVxFmFaWjcH7sCKk3xxW7SksCRc3mdyuJE1zG4PfKJsorDns3J/A2c9ku2Xw0W60p8V0l8w7Y15fFXpwJCun0FDGvx9iWxAL+6UkCouAEKm5XUOOypUuvFTDyKVXnjByyym+TUJrjFeaPCoq4FUO7so739DvmffR9rr6cCXuS/dZqiWbZ8r/4QbButN5AwnstLAau2fVO+3uuppMod8TVWZcty1R/9VICC5xH/4fe5Pl4z3PHofO+JpIWORtIV6DgYjx/A1RX6oHfDrg3HInMNt2jPPpM+v8Mj6ukl2h3/RhbqeiplVZP9ZVg3wNCyBRC+eVxAjolpicSzLG9qMxomt5H06rqAzkY3baiUztVSjslkH02/gve/A3WFFkc34S26cRPg0wDshl00TekobCpGDJMqjIl++pLOb0opvdZIYfdviSRVFalz9yHa/qEA1dHkRqqbZxQffkaVFeiuxc7DMeYwYPrjY6K44Ojf/RmvPr7Ec00GA5tik7D5ox+x3uTsPEpwntyWc+D5c9jdBdcl/asPZbednoGmsXOrx/Jyi2XqdEc+u092WL9e4AUW11cRx7OYsoJxVqJblpwXIGDbcWC7xTkYYDy+j3bnPrXxmuLHH2MENlq/R/3hT0g/Pya73uDcGmHf3oXJBE5PYTRq95822RX2dbtB/9oHvzD8qrpSvrMEQzfwTR/PkGCb0/AE13TpWN1W3piWCVEeMbCHyj9UkpO3UqxtsaXv9Dn0ZfzN0wVdqysgwuxQ1RVZnTG0R+SlJKdWVNi6o4ZerZgsix1vh2/svsv/77nIkSqkOsIxbO71j/jGztdYZ2v+4uyHXEczurZD4Hjo2oqiKlUSoqR1uaaJqesElktSpC2zaesmYZaR6AW7/oC/OXvBVAGNx3sTOraNZ5pssoysLBl7HllZ0rFtJYsxcEwTQ9PIFLse5hl9xxEtv6rNeLMj0FCMY1IU7UTz3fGTNgijCagBsDQLy7DY5hvV7dZv2S0Q1qmmxtIsKQVXISq6phOYActsySpbs+vvomka39j5hoRW9GI8wxeQrhuUym/UlMz7lktVSThHnCf4lni5DN1kk8X89elr/t69pGUzyrpi19vFN/wW6N7u3GHiTTjZnjDxJiRFgqm8XT84+5ysLLENgycHuwxcl795dUKSpPx/9L/go+fHuK5NtxewTBL++y9+SriNeXSQ8t6O9CROowW3uvvYhsUfTwWIvVydowG39sdczdeYlslOv8PbR/u8mC3wXZvr2Yrzc5Hj5nfkPNnzZfxFRYxtWER5wr3BgHd37vGgdw9LP+H7px+37MyPrj7io6sTrqOI270eT0YHHHQmPFseM/ak/qCoCo46B+wqP+hvH33jP3kbjIuIrMoxUllYqXQBePNk0bL0tm610tK0TKUjkrpNDG0WNuJCWPyRI1UZm3yDb3oUdYGn6jQa+bl4wQrqqm4DZ+QcFEnZ0Bnw1vg+f/L6I3YDCfvx1OJA43e1dAvf9EUm2HHZ5BtOt7O2S1H8swV9R54z9oaEeURZl8SFyLE/n7/A1A0Cy+MPnn3ExXRBr9/he7eOGDhdhm6PWbzC1k0eDfe5jpf0HRdN0xm6PXp2F1M3iYqEs/AcTdM46u5yHS056u4JU6+8gTIRVeD0jT5E6XXUvjL+mjFhYkotSV22/YTNa4sqU+BSzu0mREXTNAkPy0MJa3FlMe/x4CEAh0HaSo4NTSdVr2vqbzzTaRONkyLFV93Hpi7Xox+dfc7v3L1PGkiCbdON6plue105CA4YuSOu42t6do+sylQNSc6Hl6/Jlaz+zt6Ysefxt69PSdOcf6P9hC9fneM4Ft1eQJzl/OHTz4jChLv7O7wzNmUBLV6yH+zgGDZ/dSqe+JPNDA042B0xna8wDJ3hsMu9gwnn8xWOa7OYr7m4mFFVFdmtElu3GHtDNRYS5RdP2O90eGt8wK3uPqZu8MOzp6qSI+Cj6Rd8ej1ltg056Pe42++zG4x4vbpiNxgIO1tV7PpDRu6QqIj4+u6DXzr+krJqqzAs/cZjuMkKdf8wWrlpUdUCLE3aM6VU7GJVoySSUlGha6p43tAxtBtgWNao5NRCycRvki+Blr3sOSaPJx4/fLFk0HUoK6loKMqaTSWBMLomSaWWrnFvaLJMci7WKZauY6vwkbLS6LsmmiZJqnEm9RhZKSDnw/MIQ5fv9CefT7m6ChkMXN65PaTvmUw6JrOwwLd0Hk58rrY5XU9A5o5v0neFwQ+zkuNVjKZp3B7YXKxz7g3lflcDlqFjag0zp31Fst1IeX9+axjO5rsG9g0IlvEngUKa+nf5xvvYhkZcVCSF1ELUNTwcq0qh0sJQx8PQoW6yGjWZFruqSN5Uqamu8oAaOqR5yY++XPLB/TF5JcmqZVUz9KxWxgxw2LXZ7VhcbXP6rvgfbZUm++xqS6HULQd7HfqBzZevliRJzp8ZOi9eLXEck17PJk0LfvzllO024+igy52dDmWlMQ9jdjo2rqXxsxNZBLrepHKcJz7zeYxh6HS7Nof7HaazCM8zWSwSri+XVFXddkiOA5l/xIr5DNOCnm9xd9LhoCdy5U9O1ziWwSCw+fQi5NV0y3qdMhp4THou467NxTJh1HGwTelzHPomI98kyise7b2hRvwl268Gi6CK3VXfX1XC9FwAouNJkIfttTJOTFMmv1Up0lLDkIqAxneYxCpExhB5pqYJ+zRRsfBZoiozVPpnnjWjUzGLSvK5XUmwiu1iffcb1GdnsF3D4V3pdkxiePmlyFqLQj4zDqm//FxuuC9eUGcFuu9SrkKMW/tU55dUr84w33sin9EfSt3D7i71p5+CYVBGGXlR8erFisHiQwYjD3MU4PzmN4Up0jRqx7nZHyAMp2mivf9NmF9T/+2PJfSmqm469xrfZwMcDeOGcWw8kTJq1X+VFLhGKkWWc9lfjnfjTSxUSFADMgc7iiFUry1LAff9kXzWu9+U12v6DVCtK3kPzxd5b7iVY9BIU3Vd5KimCU5J/fIlVVKQhBn+dIYex9RZhtZVYPzwrrx+NRfgZTtw/y0loa0E+PYGmF97m+zHPyO7WJOEGUGSc3IRsilLXvzFK+6NPMb7HbxHuySvZ2yvtuw82hGg2O3KQsBiQfHR55gHYzB0ok2KOd3g3N3FCBw6QUpRVITLGJYxvTtD7L0+hj8VP0NWkc82mMOOhPpEkQQS9Xpo3/4uZl1Rv3pJ+Ud/iH50gPnojpwjz1+hGTo/+MvXLMsS57MZffM5vmXQ79nc+a+/Q/bxU4yui3F1BZ9LH2X80XO6/8dfHH6Np8nWbaq64jw6p688WI7h4Bk3sjVdM9j1JfAmLaT6oOn3k/TFiKEzRNcMrpNrdE1jla2YuBPlgctwDJeskqj+vMrbVfwmtS6vcjb5Wjx1hs3fv/ttXq5O2GZbDoMjDgIJZjneHtO1urw7fsxRd5eszPls9hINmEYRebXFMQy2WcZ+p8MijrnYbrnbF5bAs8T3NfI6HK8XwJKskHCA5XzDz9KcTtfHNA32Ox3GnveVFLumKsMxTDRNp2PLeFzEMQPXVRK2mjDLMHSJTgeU4VskrmVV8WR0xN3uvZZRAFrfYVEXJGXCZXyFqybmURHRsTpkZYapmS3IHDqjNpmzYfmSImHoDimrkg/GH+AZMs5N3URHF5mqJp6pospZq6TDoipb1iircszSxDZsPp8/JykKtnHKRTgnzGOSMmXg9NE1jQNf9fDla6kwMCwe9h628j1Tt+gbFr9x9C5/dvwxZ5sNUZJx0O9ycTFjE8a8Prni9tEu+zsDnozGvFguuVxteHSwy9cmt+i7XWzd4nqx4K/OPuV2b4yuaWyjhIvtlsejCV3bYRu4lGXFfBOx2MbcHw856vb4wrapqpo8L7gMQ8Zel7hI2GQhWZUzdHv85tG3qeuaF+tX/Ovn/557/SPe2bmDqZt8cv0SS9f54x/+jPU2wrJMuoGH7zl0uj7/4lvf5ccXz+k5Dmfba1zDwjUdfnj2gv/Fw//NL70FVmrxwlKAcJEulbzTUiE5lpJoShXDwBlS1hVFmatgBQEvZVWSlimBGWBoOstshYbGNpdFnGZ82aqywNbtlrV8syqirEqiImaVrbB0k18/eovTzRVhEbHn7bIXjImLlPPogsD0KeqyPYeeLY4BeL48JytLfMtilSTc7o042y55uZrx/uQOZV3SM2Xf7/kjPpm9xNCWxHlOWVZcnF3zH7cRvX6Hkevy60eP6LsddHRc82ZxSUdAma7pPBrcY5Nt+ej6S253xbO3zUPp59NvuhMNTfyBje/TUCEoco17g93V5DOyMmOTb7CU/03YDxQb3MhlhSWulDxcQxZRsjKja3coqpIH/ftf+RxN06ASX7hjCDisCW/CcZSMtqhKsrLA1i2er09JioI0zbgM10R5QlpmDJwuumYw8SbUiHQ2KRIs3eQwOBRgUtRtn+Y39+/zg7NnTMOQJM5I+yWXlwu2Uczx6RVHBzuMx30eDoccr9fMV1sFFHfpOQG2YbFchfz08iVH3R6GphFFCZduyIPBAM+y8HwZg9ttzJaYg1Gfg06HF7ZFVVUUecksjhh7HkmREuaiEuk5Ad/Zf5uamhfLU/7o5d9wp7fDk7GAxqfzCwxd5/s/+pTVNsKxrXYM+oHHP/v6B3w4u6LrOFyGCyzjFY5h8uHVJf+H97869hQGFNZIXds3WYHXBra8UXmhaRi6BN6IJ11VM+hNWm8DJEV+GmbNAmJFR9VaNACkKYsvWv+iCrupJcUzK0uWsQSrfHCrx+VGkjA9y2CnYxGmJeebjK5jUFYikS2qis+nCXUNL2YxRVnh2gbbpOCg73K5SjldxLx32CUrKzquzTYv2O1afHoRyvU+KynLitPTNet1ymDg0g9svnt/SF+V1LuWLqynkl46quz9rZ2AVZrx07OI2wO5n6/TkoFrYhk3YTYNAKyR3/omq9/4Q9/cyromKkpsQ/9KiE2p2MrmEc80aITGolgSf2Vg69S1xv2RhdWwt81zlD/TNSWVNkTBgLJuGcFCgaragFeLlKyoSNOS+TYlzkqyQgJeDF1jpKSWUV4Q5RWOoXPYtdUCjsiEe4bGk/0un5yuWG1T4rigqGqmV2uSMOHqbM7kYMRo5HE49pmuE5bLhMN9AYpdV1jATZzz9HLLqOuIsiHKWWxTDoa+qrCxyPOKMMwJw5zJ2GfUdXAcU90DS9Zxpnoma8JMvLaBbfDegZBrL+cJf/50wW7f5dY4wDZ1TmYRmgYf/uSYaBNh2iZe4GG7Nr5v81vfPOLFVYhrGcy3Bi+uNRzT4OXVBv7xE/5T268Gi5ou4TYNu5VnsHskIKKpcWgAjGneJIM2aaaukoJWlTzW6QnwOD8W4NIbgDe86aezbGEy1wsBDrZzUyZfVRJuk8SqNuNIHp/soT18m/qv/gxtswLboX7+jPLsCuPWvoCZbheur8nO5pRRqroXQ+qixLk1Iv4TYZ6qqqZ3e5/a89CuL6mPXwsg2tmBxQLdMul2LIpCfBvTiy29KMM5PaU2TfGsRZHIFmsVADOfKnZRgevBQAJoZjPq9UoY0N7gxpNY1QpolvKY05F9Vdc3oLHpUGyYQi+QfyfRV0G1poFZ3zCNDeCPtrBaKNbWAb93k76qaeIzzBIBhbYrjwc5WplLauv1tQTKDAZokwkYptSEWBbm+0/YGXepwpg6TtCa+o4iFzY6ieVYHt5VSbDnck44roDeJEYbjanClCTMWK0zPn11xkWeMzQNHE1ndyL7IT1dEM9COvtdnIeH8n0XC+oo4ur7z+lOAvEOWgampVMsI6xxRLGKSdNSYXONPK8ow5QyynDvTdhZxVzPEtzbY3j4EK3TBU2nvr6SOo0PvkX9g78g//wl5kitxjgO2mQPI88pnp/wrQ92+fBnU8q65u5BB9vWsW2D7OkJ9vuP0D74JvXpKzTbgZ1dPPsXi8E1NA6CAzQ0LN0mrzIO/ANqanwzaFe523oGTYJvskrSDV3Da9mDvMro2l08w+MkPCavCkbOEN/20TWDosqxdJsw36rgAZlEe7rXevTm6Ywoj6ip2ff3MTSDtEx51H/In5z+JctshW1YfL54zqvVlPv9XbKqoO90ON9OuQpDVqkkmM7CiDwv2B/0+MnpWTv+Jr5PYEnp9/l2Rl6W7AYBSVFgmQaeLz19gJJSWYxVEE3jrbB0va3bMDQNxzBacNj0LG6yjKZOwzVNLFMkfpqmsUnT1iP0G/vfk5tLEeGpMIymU1FAVkmgKhXyKqdn99u/aZrWSoEbhrGqK6IiZJ7OKeoCR3cInE4rM9Y1HUd3SKuUsi6wDVsxGR59u8cq3XK+nTLy+kz8Ibv+DqZmCithmHxn/y3GXqctZi+UXDGvcqbJFUmRUNQlh/4hmqYxS67bYvFVuiYtpZNzm2VEScZ2E/GXz8+4nC3oBj6ubTEai0z/eL1mutmyP+jx9nifrCq4Cmds85g/e/qCnYEEMtmGgWkaLJOEbRazSlOyTAFnQ6coSjZZRphnPBqNWMQxy8WGB4Mhb48f0LW67PlwFU95tjjmW5Nv8Jfnf83H01cMXY8a6efc93dJipQv56d8++uP+OnHzynLisPDHSzbxLJMPrk+5Vv7D/j27tc53p7gGi673gS7qWv6JdvQGaA5OqYuiy4jR5j7JkBFjpuGrplotVTQFHWBoTfdiQY1lbCHpgSvTJNrSuWD7FgdGYN10QahRCq0pempawDjKluQVVIKP3ZHIt0sc+50b/Gjy4+IVK/h8+0JJ+sFd/tj8qqka/tMowWnm00b+LRIEvKi5Kjf449fPgNkYninN6JjeSxY8np9gYbGrj9gFq+wDAM/cCmKkqqquZ4uiTseZ/0plmFiGxZhHhMotjspM1bZmq7VxdQl3XXgdOjYPtfxEi3VsHSTwPSlxxGNmqqVDTbMbVlXVHWJbah+XMXaFlVBRY1nuG1lTcPCCtCugJvIeJHTV6RlKr20dYmpmXQVmGtkww3DV9QqZEiBxZ7dYZ2GXEVLBk7AyOuz4w3aOhtLN/j67l12fJ9tlhEXEkRWId9/lszIKkkDnXgT8awmC8UCS79qVmUM3R5RnpPEGdttxPPnp0xnK3q9AMcyGY37aMDZZsNyG7Ez6PBkNKaoCubxijDP+OHLY0Z9mVRahiTGLpOETZaxTlPyrAANNF2jLEq2WUaY59wbDNjECavlltu9Pg8Gt+jaPrvaiGm04MXynLeHD/nJ1c/4bHYpC3XUOIYkAedlztPFlPc/eMhnn76iKAoOD3cwLRmDX8ynfG3vFu+NH3MeXmEbJkOn/58cg4Fl0LFvEk17SsbY+ETfBC+6AoXCJioppTr2ZVXjWTqWrjOPc8oKfEtCcZogFl3JJZuUU1MHw7iRom4zYQzLSlgZQ9PouQZ3hg4/OglJCmEup2HB1SrmcOiRlzVdx+A6zJmtE5K8xLEM1lFGUVTsDjx++PRawFFVczT06DoG0yrj5TxF12DSsbkOcyzLwPdtNQeF6VSSNI8HPubYxTY0tllJxzYUk1qzyQq6tomp7n0Dz2DgmszChFVSYqkAobY3kRvZLtyAtrKuW+bxzYAhECBYVJLM6Zk3/uzmmDTHqPmMvKxa8GPpWptU+uZranXMNE3DNCSIpesYrJOS+VZA1NA3GfsWhi4A0tA1Hu116HoWaV6SFSWFChwqq5plkpMqGau8TmOZFEquqbFNS5Jcei+TvCSKcsIw4/jllM31HLfXxbItRiMPTYPZJmW9Tun3XW7tBJS1+FXTrORnz2cMh2oRW5eAoCgpiNKCOC1IlT9V1zWKoiLNS5KsZG/gESup6k7X5e7YJbCNlkF+NYt4PBnyk5OQ4+uQvm+3Cbu7XYuscDmdR7z93iFffHZBWZTs7g+wbQPL0jmfRzzc7/H2rsvFJsfUNAaegWn8/DLAV7dfDRanF3BwS+Sc4UYm9Q3gkDPmqzUODSNWVzcdfg2I2a4FLDbVAZ4vQCTPRILZgNHTV/I+w7EwRE1i6tWZPGcwUjx0IAxkT+Q8zGaSyvl7v0/9V9+nLirY26P80d9KB2BZU8xDNvMI2zEoiwrL0knPFpRlhT3wcSc96HTg7EwYwvmcMs4ow5TsfIlumQQjn6qqWW8yqqrGMDTiz04wjqcUqxh7t4f5/hMBqXGsQnN0qGcC0lxXGLogUKycdRN2AzdhMU1IjW60NSEiKTUkKEbT5bhougC989fU0yu0W3el49IwBVy7HvhdeW1RiLR3eX0D1jX95jPrCjS1AGCakCj5aVXKsdIN+d4qfVTr9QWoAlq0pbZtkfGaJvpkTHF8iXl5ST2fU4d/izYcgudJSurrpzdVIptV6++r/+JP2+CcLK8IfIs7hk5nkZDVNZ5poDsWVZoTrWJ693cwB758J02jjFIMz2b01h7WgyPK00vSl1Msx8QaBej7u7hFCS+usfZ6mF2XKs5JTsTXGPy9b9HTNcxPzqjLCi1NoT+SpF0geX2N++mH0O9j/y//hTDkO/uy7y7PwLIwAps6K5j0HPb3fNx7E6o0x373AeQ52rd/HQY7aONd2bfnJyLn/bntKr7iqHNL9eitCJTEqmEb3uw3E0+MQalJGbypW0qampKUsUrf7BCVktrbsQIp+lZsoqlbFFXOq81rTN1g7I6xNEsxjjnT+ApLtxg6QyRC3yOrstb/M42EyfpHd/8O8/gHZGXJUXePvzz9mPPtgqKqmMUx89UW27HIc+kLvN6KSdt1bUaui2UYTKM16yximSTt687WGyzTYNgNqKuaMIwpS0n9WyQJSVGwSVM8y+LeYNDGiadpysjV8SyLOM9xTUmGs3RJvatowgHkxleo4uGvTe7wd49+F98MiMuYspbAH1Mz2RYbte+l0sA1XF5sXnIRXnHU2edh7yG6ZvB09SUjZ8SuJ1K7Rh44S2bkVdHuyzc74BrvlqmZxG+Ukjc9fV3bZ217jL0+Xavb+oC2eYhj2Co4xOAgGPFidcXJ5pLLcE6YR+x4QwLb41H/Acfb1y0YkfTIAFM3+KNXf37jBc0LXNdmb2+I59pkeYHn2tiGQZQXLLYxT3Z3GLgusfKxbtIYz7J453CPt0YHvFpP+XI2x7JMhp7HYWdCXlU8rWsOOh36KnDo9WrF8+WSf/Lw6xiazt9aF5R11YLXV2thxF6s5nw8+xkDp8d/+/7/jGl8zcQTmeppeCayS8siKUpGox67u0MeDodEec53Dh6Slhm/vv8d+vaAoTOirisu4kui/BfHH8AiXcpY0CWISOoYzF8opm42TfWw1VXdpoeWdUFapsRFgm96pGWK1FdInURe5ViG3VbbTOMpuqbT1bttd2pRlSzTBYYuzBOAq1QAHUu8xdNoRVyk/PbRd5jHW/KqYjcY86PzL7nU1pRVxTyOWagx2PjVztZrqqqi67nsBQG+5XK8kbqQWbwmynPCPOdsvcYyDPodn6qsCMOEqqowDJ3PZjOO12vWacrE9/lg9zaFCmKK84SjrqYWShJc0xHppulKlY5KWm1lb6qWw9JNBaR1kjKhrCtM5fGMy6R9joFOpRtMo2um0YLDzi77/h6GKph3DRfP9L+SYLvJtlR11Xobf1l3nK7Cahp/sq1bxJpOx/bb9NOuHeAqMB8RY+kWmyzE1g32gh6vVnPOtzPm8Yp1mrDjd3FNh/v9W1xGlyqATCcuIlzTxdQM/vz0p2qyXFMUBZ7ncHCwg++75HmB5zqYpkGaF2zCmLs7IwauS5hnSm4oiwEP9yc8Gu5wvF7wcr7AsgxGrst+0CcrS15WFfudDh3bJs5zTtZrXq9W/P79t9CAz+wZVS0Ld32tw9n2irquebVa8eXyJQO3x7985x1W2YqRug9cJ3MsQ8ZgUZQMh13GO33uDPokRcEHu4dkZcE3Ju/Qtbv0nb4C0fOv+HqbbZkU9BwBirli/Rog8auntuJvA1RqbU1aVLim3tZMOKaEgRRljaXL84uq5jqUhb6uI5JXWXiQsnRd0wgsOT9tQ0JDAksWbRdhSlaU/Pb9PutI5oe7HYuPTjcsQnmfdZyzXCa4rkGeyxx0ukqoqprAMxl1HXxb58U8wTV1ZmEmoCUpmG9SDEOj13OoqpowlM/QNI2XVxsulhFhWjAMHN477JKWFUkhjNS9IW1Kpm9Jd6Fn6WRlpbzKN4Cu8fYBNPghrwRgocmco7F1NIocXYNlXDINE476Nju+rewc0j1rtWmmcp+NipKygsDRaUpd3qxFefO5pQqYsQ2NRNMIbIPIlvCaji3F8gCJVmObwhibhoZn21wuY67WKYsoJ0oL+r6Na+ncGThchrkKUIIor9tU2h+9XLfhNmVZ43kW5v4Ap/HZuzamqZPnJdttxv4koONapJkQEEle4pgGtw+63BoHXK0SLudbLMug41mMOg5ZUVFVNf2Oje+YZEXF9TLmepXwzYdjYcQtSWZN8pqeq3G+yijrmqtVwpfThFFg8s1beyzjkrEvMubrsMA2dVxL7Cu9QYfx2GN35JMVFXcnHYqq5oMDj65t0nfkXjaLiv/CnsVoK1LJ8b7038FNaEozwdF0SeUEAXvZG2Xwm5U8N0uFJawruL66AT4g/01iAS9lIX7GqhSQU9XSG5gmAh5HewJimvdvgM7xcwlnObolXzErqLICplOqtKAuSopVTLxOSNOyzeKp6wobCB7vY949hKqi/OwpVV5SbhPqvMQadQhfzbi6iuh0bDqBiesa6LqDrksS1fZqi2lFsvpU1Zi3V2p/5JAkFM9fobuWVHb0+9RhKIyl40gSaV8utG33o2He9CqmqiMxz0Q2qmkqWEZ5CtNYGLneABZz6uOXwlZ2urIP8wzC1U0IkePJe/dH4hldzm9qOeoK6jePq5LClqUwjYaBNpQqBG2gQLplyTFYLwRoFwVst1SrDYtPz+keSULllz8+587tDt69HSzHgeVS5LjDHVlEcFxhO3Wd9PWUcpNw8BsPKJYR0atr7vzeI7KrNYYnwFqzDTo7Aj7zL1+h9zpoDx9i1jX1xQVGVlBNZxSbhDAs6O+75PMQ62qK0fVbRlB/5y302QzPNtAMCfCpkhznzpgqLdCXS0la1XXwfdy/9+swm4FlUfz3/1+oa4xvfg1t94D65BiyjGKTgK7x6H/3j9Hu3Bev7HBHxtNo56Zj0bJhPZdxsrv7C8Nvk29ZpUv2/H123Imc2yrI5k05VuOFy6uctEwo6gIq2ORrmWgVKY5abZ/G11R1iVUJmBR2MCFXbMVhIMylq7xPs3hOWqaM3RFjZ0eKzquCqinjRuN4+5o7vQPu9m4DEgqTlxI4khQFaVmyTBJWYUyeNwliGlVVUVUaDydj9gJZlTtTlRdRnpNXFYedDifLFfPZGt938HwXx7XRdA3DENnNdhsTNn1OZUWkQGEjMX2+XKCrVVVTl4AbQ5NU1cZf8eZ1silFv4gvuY6veX/8Pq83x/zo8kM+mLxNmIfs+btYusU8WRAVEcebC57OL/iT/BPu9X+MrhvM4xDXNHlv5z6e6bLn73KncxfP9Bi5I2bJjEW6oGf1b46tqsVogzTU5LbxHw6dATV1GzwiPi+dVbqi73TIq4JlumGZLvj4/JL5IMbUdX7y+UsOjnZ4NBrhGDbzeMXd3iFDd0TX6uAYDst0iaHrPF1ISfjvPLrPPI55Nl/w9999wulm0wYCOYbBYXeMb7p8ePWSQT/g7fFD6rrm9eaMpCg43c5YpSlxlLA36jOLIk63Uzq2y47vUwPf2H3CRXjdptHWVMRFzv3BgCjPuY6WXIYzDM0gsD3+6cPvchFe45kO/4/P/wcAfu3gA/b8XV6vT0kKVX0C/J/+3j/nXu8uF9ElQ2dAmEdMvB0CM2hl1et8xTpbc9T9xfEHUtYeFSF9u09XheR8NRmwWY1v0jbLVtZLVRCVIbpmKD+ahEStshVVLYsSOhq1ZpCXGUUtFStjd3RTtUHNKl0q1rpLz+5haCalMvFIfYXBVXzFQWfEYWeivndJVop3NCkKCcFIEtY/NwaLQhaeHu+MudsfU9U1n8/OyEphe8u6Yuh6vJotmF0v6XS8dgzquvSU1TXMV1tWpozHqq65m4pHJ6tyqexYXmLpOoFtM3C6hHmMjoZj2iTFjcezrCsqFSYk0k+p97F1W1UybDEUk+6rcKG0TAmLCN/00bUlr1an6JqOp7pNkzJp9zeIpN42LDpWwCbfEhYRgdV5I6TGaFmmqq7a41JU0q3Zd4QxH7hduYbqhure3NK1fYqqZJNFzJOYLy+mLAddTF3n4y9esXcw5s5oiK1brLMtR51d+k4P3xQVyKbaYmgaL1crNknGdx/cZZkkvJ4v+c23HnAZhgSWLCBYus5ep4dnOnw2u+Cw0+Hx8A4AF+E1eVVxGa7ZpClJnLIz7DFPEq6iNT3HYex5VHXNezt3uI6XWOr6WNU1WVlyu9cjKSRZdx6vWr/0799/j3ksKpJ/8+wvKOuab+8/Ys8fc7w+JysLwkwsRP/tb/8ed7oHXCcLerbU5fSdXpv0bdQ1Yb6VRFt/9AvjLysqEqMksIy28F3O+5utARbNtVuqK2qoxKOoa1IzaegCglaxmhib4CCPl1VFVgsDNfbNtmKgrGuWqTBmfccgsI2vgClNff4yzZl0HXY7KnSmrMjLimlYkOZiadgmBWGYkWVlyzZlKlDl9m6XWyOPuoanVxF5URGlN+maF7OQ6VTmoEFg4boGmiagpa5rZosY226Sk2Eei/qqKGvirOTZNMI2dDzbpO8ZbLPGrqET5RVdh3axtFQeTdfQW5+wa9yUtjf72jZukn+zsmQnsIjySjyTtoFjGnRsi1zdZ5vuYjl3NXzPIMylq9JXaa9lXbf712hIA+XZb6pCe65BVVsMVCeloRJzt1lBYIvsd5sUbOKU1+cbxiMPDfj8y2v297tMRn7LIh70bAaepIVausZWVbVcLGPiOOfdhyO2ScHldcjX3pqwDDNcS76raej0AxvXMji+3uJ1HB7syOLt5TaXiq9tyjbJiaKc0chjG+cswpTAMYl9S3yauwGLqJCFEIUp8qJip++RFxXrpGAZi/fZs3V+/dGYWZiTVzp/9OmMsqp571aP/a7F60VKWdUkueCc/8nv3uf2wGYWFnRcgzirGHiGkC6ahm5oxEVJmFWM/P+SNFQQBrAJVIEbSWNTmdEEljR/07WbTsJOV5hEENC5nAkQGoxU1YSSm2apVAqAgIbGw1eVkjxa5JLwaRg3yaGlquDIM+ovPrkJeAm3GA/uYgDFFy+oy4r4dIGtwIFp6WzDHEtR5WbzXbdbitma9GROsklxPBNN18nnW9xxwIN7O2yeT8nziiQtqSsIApPZLGG5ybh9EBD0HMokI/38NbpjUSu5nO5YFElO+uExwXtHaKZi727dEnA1PZf+x/7wBkQEHYjVSltVijfRspVb2xBWtSjg5IXsOztAe/uDm6AYw2gTXqXqIpNjFq4F+Ne1+rt1U1OiaTfAHwRUNhJYS7GYcYTWH9wk1BqGpLB6gbyPrsNwyPWffU6SlPRtk+xihWVpGK5FMd9iPnuO/sH71GGI1hu2ixL19SV1kqK7Frploo1HWO++Q7crARnOr30N0pT64oJiGWF0u9DtYu2uYDiU7+v5UKpgmqLA8V12Oi7m/lhCZooCTk4otwmUNXYcw3CIkedod+6AZWMEAcVHn0FZsf2TDzE6Drpn4xyNYG9PfrPvY7z1CC4u0IZjWMzIPnmOfW8f63AH69EdtK9/VxZJGuZ890COnWkL+E7VIsnhHZEr/5LNN/1WKtWACF2tvEvbWdVKspq/NWxEx+wQlzE1Fct0yTxdYOkWA0fqLxq5aVqmbRm3q/oYG9AycU3KuqRr9drORUmDk2TUvMr5ZP45WZnTt3tERcTb47sA/O3Vc/Ky5HixZKcTqNUykzhOMVXfkdX1cQwDx7A5266YxTFhlGDbFpZpsEpTdjoBj3bGPL2eURQlWZrJ6esbbNYRy+WW3d0Bni/yuIvtFt+y2CqpaQMSX88WHAz76EiC3MiTm4ilQm5MXadr2xx0hrxcnfP57JisLPnp1acskpi8LDnZfF/ORcMgsGyWaXITjqNJWM8sjqjqmsC2ifKcj6bPcQwD33rFbx/Bve79FgyYurBJTUhRkwwJUtug1bKvbd3GsAxCBLiApGPqmk5W5njKm2ZoBhN/yH/48AekSYa7Y3K+3WKYBp5lMYtjPp095zv77xMWEf26T5iHrLIVl7HE+buGgWMY7AYjvrW3T9+V8ff7977ONo842VwyiyJ6doeeE3DYHTDxR219RVmLp7KoSnr2mq5tc6s75rAzoaxLXqzO2GYZeVUSFQkTf0RRlTwc3MExHLp2wA/OPqWsa/7g+c/oOQ6+aXK3P+KoW2MbJoHl8f7OQ042FwydAfNkwY8unvNktM+d/g4f7N7jGztfx1LdhKZmsuvtCmur6mjSUmS6R8HhGzULX92acJUbMFh/JfyhHYe16h7UNDR0mnmtZ/qkpbCuYS4VFoZm0LEDqroS8KPGURNwY+kWhmYqWVZJ3+5R1lXLIFZ12Z4rpi7hVc+WrygrCZlKy5THowMAPr0+paxrTpcrxp2AjaZhmgZRlKgxCEbXkNX+POEqCjler4niFNs2VX1DzLDjcX885MVsocZgTl3XuJ7DarlhvY7Y3x/hBy5pXvDp7EpYfMVAuKZJXNf87GrKu7uTtifuVncH13RYpis2WUjf6ai6ElP1xeZU1OR6Tlqm6JpBWQsQSYqEiprL6ArPdHEMhwf9O+SKrQQwNZNKa0BoqaT6EiBUU2MURrsPa3VMm2uchpwrWi2vQQcXFw2NniPXS11VeuRVjms6FOozhm6Pv3j2IWma4RgDpmGEYRrYtsUsini2POcbuw/Z5jFdu0NcJoRFxCxZvCGNN5j4Xd7buUfPeYEG/ObRIyXRnzNPEjqWR88J2As27HgDHNNuQbapm5R1RWBZBLbNQafLxB9R1iXH66laDKiJioSx16eoCm5193FMC99y+fBKzqk/fvGMwLFxTUlH3Q+G0j9pubw9vsVFeM3Q7bHM1nx0dcbD4YiDbpfHo13eGz9R4NzG0EzGrvEVma8Ef1XsejvY+i9OVpuS81+2NSCxYaB+/m9yndYp6hqoifKKZSypmx1HainCTGSYUSmJpXUt4MMy5fzUamF16rrGVQmfcMO+Nezls+uUohL5YlpW3FOg4dlVSFXXXC9juoGjRFs6cZzf3AMtRyoo0pJlmHG1iomiHNs2MFTaa7fjsD8OuJiF5HmlSI8ay9JZLhPWq4j9gwGdjgSuvLjaYhk33by2qZPlFc/O19zf77VVE0cDh7oWWe46KUWOqIvP0zX09rrX9CsaWiPvFRxQoTGPMjq2gW3ovLXjUyhLiKmSZZtKNQNUXVWJb6maE03DNvjK8cvKCkPXqbW6Pf5lVaProNs6USadinADFPOyxrUkXEjTYBhYfPT0mjQtsIyApaqtsG2DTZRxMo9556BDnFf03ZqkqIhymMcFaVFhmzqmadDzbB7vBXzhyPX4g9sDsrJiuknZxjm+YjjXvk3ft7AMDc+S72vqLlUNtmng2cIa7wQWeVlzsU5IlP80zisGnklROez3bBxDOjC/vNhQAx+9mOE44ivd7XtUHRtTPefeJGC6yRh4Jouo5MXVhoOhz6jjcDj0eX/fl2Npyj1JU9JpU78B4mVVM+mYUk3yK7ZfCRbrKESragEUeSaTcfgqUCyKm9TMpkbDVIE2Dchsgmpu3ZPE0q1iHPNMwnKKXP7teDK5bt4P4PQZ3H9yU51RlQo0FQpoJgJmXFfK5a/Oqc/O0CYT8tmGOikoy5o6Kwn2ulTnazzPZLvNqEqZZNuvZ+TTNdG1SOLSrCRRnjZzndA96FFsYqK4YLnM2Bm7OIFofKfrlN2+QxBYEqJi6hjblORCVuJ0U8foulDV5EVF8uqacptiTbpUzy6xxl3MgU9+vcG6syel9rfv33g4m35JKdNproQS4NN4GA1DWEpNl/3XAOCGQm3CdkCOYRLJY656fZGB5tywvc0xNsyb4KKqAqNWSarKp9ewjtXN+2t+QB1F7P7d98hOpmxfXJPnFZ4rg00zZUGhfvlSUmKbOo7tlvLlCenJAv/bj7B2enKRmc+lvqIspZZi/whtPMbKJSlXc1xqz4Pzc+osgyxDe//r8PbXJNTo1TOqP/3BG68/pA4CfMuiCmPpbnznXerNRnywng/PP6fOCqy37uE0Jm1VHktZQqeDNp7I/nv0disPdv7l/1zOW8uWRY+m/mS8D6uZSLEHI5F065owil4Ao90b5v6NbZtvW69b1hTCK6AoHpiqZQQb35quGVi6TVEV7YU+K0VWc697l67VZZ2vW4lqz+6SVyIHE9+M3aZwVnXF8faER/1HrQ8or3Ms5KZuaiZZLf2CjmmzzbdcRle8Wp9x2JlwHUWSKlrVJEXBXr/L+WKF69pEkUhvIOKVvWIaRVxvQsqyJM8K8ixH13W2hs7BsM8ySYijhM06YjDsYjsWpmkwn68ZDrt0ewHhNkbTRSKziRI1NHRKFTFeVzXzKCLLCnzPYRnLDWTkusyThJHrsuN30BDfomua2IbRAkXLMPAtC8cw2WYpUZGTlSWuadK17dbX0fglQVb/y6rCsl0Cy2OTbbmKLylVciNIauqbAR+AYixMylIxHXrdShsb6WlZlSoE5GaBJ7ACNlnIP37rXV4spzy9npErOamu0dYjPF28aqXMwoSEfD4/4eVyyW/ffshep4eOzlU0Y+AE4gU1TJ4ED9gPJqRlSlVXeIbE6r9anYnksEj59u4HvDt8h6RMeLl5xb95+teSbmtY7HqHdO2OJN3mMSfrS7619x5ra8tBsI9neiSrhKwseX9yl6quMXUd22hWnku6dsDYHeOaLm8Pnyim3eB/+7X/KaZuYOqmqqAwMXSDkTNmlS2Jioie1SMstipYJsQzXUbOmL49+IXxBxDmMbVbY2jCqJtvyCWb8VVURcv4F7WABVOz2uRNOVZyjPb8CZ7pEeYRhqqFaEJoStVDZ6ogHR0NNIOL5JLD4LCVv1YUGNpNXU5TLeGZDmmZMouXHK+n7AfDXxiDk16Hy+Ua17UJw4Ra3VNeOSumUch8E0mMe5aTJhm6rhEZBpNBl5ViqDbrkMFQvDuGobNYbBgOu/iBSxylGKZBmGVcrTetL7XrOEpWWfJqtSJMM8aBz7PFgrHnMfI8rsKQu/0Be8GYw86e8gs2faeVksFJ5L6maZyFF7hvBNLYuvh7Td1qa0ua/VhStwDQ0uVaWVY3Hsi8KlTvo0FNqSRxYGi6CjfRqdHRNVmU80y3/V4N+99sHcsnzhN+9/EDXq9WHM+X5FmuxqCmit3h+fIEXXVIlnVFlCc8X15xvF7znYNDJr6PhsYiWTNwXCpkDB50Jux4A5IyU3JmG990ON3OpKeyzPlg5zEP+ndJy5TT7QWvVx9T1hW2YTJydxSTqRPmOZfhQqkfHPb8MY7hkKpr29vjPSqky64Zg1Vd07E9Rm4fx3C437/dql3+5bt/B12TffzmGBw4AzbZlrhI6FgdkkKuz2ER4Ri2MPdW9xfHX1YycFW3bf2LtQ3NfxtZaqnAXvNvGai1klHCXsfCMXXiosQ1RXbqmwaVIc8xDUnEbhgzXdO43Gbsd+z2s5vvUSsWrPEwdh2dvKyZbgtOFwmTrsM6yslLkRzmZcWg53JdxDiOSRTlVEre6TgmqzBjvU0piposK0mSxtetMR56RGlBFBWs1wnDoYfjmBiGznK+ZTDq4PsWYZhhWTpRWpAkeTv+fNeUoKCy4mIRkWQlvcDm5DqkH9j0fJvlNmV/6LPXsbg1sIVhVCDxTRjRXP9Ot4nye8p+slV6qaWqYOqaFmC+6YF0TYNSSYNtQ4Ju8lLCZfRG6aPmrm3oji7vVVXSt9h4SJuOySbMB8SHGmcV33gyYbpOuLwWgO2qOaipiKLXC0l7FpUhRHnF2Txiukp4fNSn70sNxjIuCdT+swyN/a7D0DPb4+4oxna6SclLOc5v7/rcHzkkZcXpyuCHz2OqysY0NHY7FoEjoXppXjLbZDzZC9ikJZPAwrd0UsVM35102nPRNg3VTQldR2fkm9iGzr2RI/sE+Ccf7LbVHY6ht/t04FpsspysFBY3VTRtnFdYukbfMenYv5o7/JV/1XqDGy+h/gaQaIBik6hpO0qaqglr0iSf1pVMiC0bPFMm11kiyZqOcwM2NF06/XTj5nOWMwGR9x6Ld6+RRerGDUAN1yLxA7TH78jnz2Zoug7bLbppsF5uiOOC0XfvU6U53ibBTAsMXSNJClzXJAkz6m1KFMkNPVUpWZaps8lKrqZX3H88pCpr0rwkzysm37xFFefsTmOKouL5izXrvOD+fgdNT0iTkiwryfKK4vWGTtciCCzMUQfv7VtSoXB1RfziinITE12u6XkWxq1b4tVMU9mHcSSeONNUDGMsLG2nL8elUKC5LCVf2LJvZLpwE1zTHMdoK/s1VVUab4KUBly2EtRCxZGp+o1cdSyqdFnqSqS2242E9Ux2qdcr+e6jEbam0bNM4hdXnJ2HdHs2w3/wPTn+nkf2Nx9Rf/5awPJsS7GKsUaSHpudL6iPrzEHPsb+RM6XMIQxsH8LbbsB26a+Opf9tbd38xzLkt95fQXzOWga0U9f4Hc6wtgWBUwmGI8H1JeX8tMvr6jO/gDjW99A2z/C/l2L+vIS61vvo032qZ99QX15hbbZSFVIWQqj2+neAMQGODeLK8u5/N1/Q3Za1fI6NxC/bRJ9dWHljW3kDLF0i7RKW+apmaBKSXdFWibYhtPerC1dagHiQoJolqnIhWzdxjM90iolKyUEQqRVsgrfs/vKP2Oo3rQleZnzoPcATxWFN72BZV1S1iVZIeXSZVXx9Z13xGsWfoKOxixeYeo6y21EmmT85r07JEXBMknIslwlu+U4jk2UZISxTESbx0GAXpYVLOcb7t7Zk9ymvKAoSr599xZxUTAfrSmKktPjK9abiMPDHQmbyPL2uUVR4vsutmPRd116felRnMUxZ6s1szpmuxEFxNlmhaGt8S2VNloUrXzN0qXyd50msthQ13Rsu2VGt3ki6W26TlaW7aSiqmuiXGSkH04/w9Sfss62vDN+wDd3vi7XL+VRaqS9FVUriQMBSXUtE4u+LWxgpUma4zYPWaRL9rwJq2xNXKTs+SM0hOn87Pqa66slna7Pf/2175AUKYHl8yevpWJi7HlchiGLJGE3EO/iyXrJy+Wcoetyq7eDoems05CJu8OBf0CYbzF1i6v4CsuwOOzu4lsu63SLbdhERcR1cs1lKMENPzh7zdDt0bE6FFXBfmeHodPnPLyiqktOt1e8Wv8hv3X0TQ78ff7R/e9xFl7xW7feY9/f47P5U063VywSqZqo6pKu1cE3fTRNbxc3Gu9uXuUs0yWBFeCbAZYuyaU1NYHZUYFB0lPayAx/2daxfAzdaDtJmzHYTJjKumwrDzRNQ6+19rvkZUZFTViEkpqqpJVS4VAqAFK3n+1bAboKqyoo2eZbirrkwD8QX5ziM2TiXEoxfJEzTxdU1O2kfRYvpFsrC8UDvNqQJhnfvXOLpChYpymZYaDrOmma4zgWSZIRqzEIkGWq+9Q0yLKYxXzN7Tt7VFVFmsm4+trtQ6KiYKHG4MnrKzbbiNu3dwl1jTTJ2jF4UZQEgYfnO4xcl3d3dhi6PS7CBS+WC7ZZxtV6i2eaHHV31TEsyClIioS+0289hEmVERURXdWBWdd1q6YoqwJdM2QxrWFFFLjUEAax8T8mRUJN3TL1IDLiBlRK0E7VhhhptQ6U6hwSxjiv6zaddp2GjL0+mywkLlJ2vAGGJgsdL+cL6S/s+PzDd79OWuT4lssPzp7x+WzKwHGYxTGrJGHkSwfmxXbB8XrNwHE47A7Ej5jHjNw+O96YpEzU8V5iGya7/gDPdNhk1xi6QVwkrLIVs3iFoev85OKCrh0QWKJW2QtG9JwOV+EMgItwxfH6B3z34Al7/pi/c+c9LqM53z14wK4/5uniFRfhinW2xTMF/Pumh2u6skhZWJS1VA6ZmkleFWzyLZ7p4RmudGfqEvbkKiY4sDrtwlNzvN7cfBU+8/OApZ2ycJNgKrLuG0BZVXI9iPOqrd2wDU0lXb8R1aDeq5lcy7iGOC8p65q9jo1l6C2bqPFVuesykfni7YGDbWg8myVt2qppaMyXKUlS8M7dEWkh/sM819tCdscxieOcGAjDXJxbag5qmjphWDKfx9y9O2i95EVR8eTukDQvmY+75HnJ8fGSeBtzcGuEpsn8Ns8rdQ+sCAKRsPZ8m/t7DuPA4mKdcjaPiLOS+SrGtgzuDm1VTVGRA3FRMnSsFvQVVUlSlPQck7Kq2v3fBOMYCny9yfdqcpNT8xb5/7yqiHIJBJKxJ0ejeS/Ufn5T9ts8L7AF8BSlJKFGecU2LRn6JmFWkhQVo8BC14VFu5iFXE83BIHNdx/tkxQ1vqXzyemKk2uR+q6jjCgpCDwLQ9OYb1Om64SOazHuOuiaRpRXDJGKk0SFIM3jAsvUGVty/KO0wDI0krJiGUtqrqFrPDtf49lDOrZBWcFOx6bnGlxtZb4z36b8+Srh/aMuex2LX3sw4nKb885hj52Oxct5ymyTEKUFvmVT1TI+HFNXbHDZLoo0/aNhWuKZOo5pYOk6CifjGgJWfVOxi/8ZvyL852So+7duwlfKXCa0DZirSjkjGiaw+d9NwE0aS1ehH8gE3XbVZLqWSf1mDd2evL9p3oDMeCsMTG94w5ypE00qHQopNlfsZv3Fp5I8+uGP0e4/RNvf5/p//Anj33xMleakWYltG6x+/BJd19hsRYK695sPqLOC7SdnbMOcIpcbdpqVFHmFYery76JuKxYMtacNU6OMMorrrawMVUKd25pGVda8fLnGNPU2KKIs5cIi6UdTeq6FYVkwHOLt74Pv46xWUsswHMs+DjfymxuW0FQAqFJMX7cv+9hxhAFs9lGRg2vKfm5yp3UNcsX+1ZUAv3Ar79NIe3+ZXNkw5ZhU2c13MYwbRtnxoCoFIBqGYp5XkvgaReA4mI/u4AHjRSrSX9NEG+9Q/+xj8ss10SbFvVpj7/bQTYMyTMEwsO/tk35xgtH1if7mC/wn+/DgAfXiGm0wlKAdkM+xLLSj2wKkhyP5bpsr6p99xPqvvyTLSryeC8sltaaRffoc++4+ddOt2emiPXmMtlpRX1zAfC4VLGEoAHEwQvv6t+H4BTx9KmC4WdoqSzkvuwPZV2evb6TSg9FNL2mzItqA9zK/8afWtZz/P7cddY4wdQtDk8lnXMatHLVJubQNR0BjlVJRodcC5pIyaUNtAjNQzyvbYI1VtqJv99uQjQZkRkVIWIR0rS5D+8ZD0gBRKlhk81YG9+H1JwD8+OpveTx8wJ3eIf/q0w/53QcPxCuV5ViWyV8fn0gIRBhjmAa/8+g+aVny4cUlSZy23qk8LyhLCc3I81KNn5LVNsJQK/KGISviV2HYTghS9TmaBpfnMywlc5HXV0R1Qprm1FWNPh7IhdKyeLwzFhlqv99KVg1NVpcTBRR9y1IXWoOiEsN+Awod06aqSqIipVQ9Uhri4dCAWpMqDtmHGlGRsEwSdE1jHq/I6xyzvmGJvjL8NENNvsQfahkWHQUwyrrCNVyKumSRLjE0A9d0WWVrdrwBYR7jmQ7v7oiHab0KMQxZ8d/t7vDjy59xsd2yiRIunC37nY6kxKYppm7yZLTPh1cn9F2fPz9+xgcTqWS4TmYMnAGB1aFGyrhtw+Re7zZJkTDaGSqgtuJHlx/zpy+fUxQlXd9lGi3QNI2fXr7g0XAPHY39YELP7vHezkMWyZrjzRmzeM5BsMc6DTnbXDG+NeK7e99k4r/ik+tnxEXaAniR81p0rR5lXXIRXbQe3oEzwNLtFoDLMTBoUoPFB6qSan+JBA5gxx235fCV8s81x6kBeU2lRqkAnF4LM5FVGVER4xourhpnNXK+2rqlfHYehm5gaQamGudJmRAVMYHp03tDHiu1KzplLX7khpF6unhNTc3PZl9yr3/IfrDDv/vis3aBJs8KLMvkx6dnaJpGHCUYhsH37t8hryo+vZoSR0mbMpxlBWVRYpgGWSZjJs8Lttv4K2MwKgqmYdiyI1kun1NVNSfHV9iW6iZVY7CuarIs50WN6lY1GLkdDm6NCCyPVSqev4Ejkve4iNX+lSoNXTdISgF4bS2QSj81VeKsHJeyrct4c6vUeVGphba4SLAMUy3U3PQvig9UUxNfXSWxNl2nBr6m/GB1iaWbVNSs0xBdSZY3hAzdXusVfzKSarDtJmrH4E53yEfTp1yFIXGUMrVNJt0OpiGsrKHp3B8M+fR6Stdx+OHZMU/GYx4O+izTNT27i4tLTU1UxDiGzWFX0oD7rnTmrrIVH0+f8levj9sFs0Ui4VwfT095MJQgjbE3JLB8noyOWKdbLsJrFsma/c4OYRZxsV3Qd7p8MHmbkXfO08UpaZndMOzqWhhY4te8Tq5bj2jX6rS+6pvk7hvJfVHlAiDrGlMzfv6QMfTMlims1bF7M9RNjomACwEizbRHJsFxLqE2tnHDUoFMkcJMQl5EKSmSyRphueJCgmBM9dmNN7FSC+pRXrTzuxfzhKqGTy5j7o1EavhXn17x/oMxeVGRZSX///bOZDly44qiB4kZqHkg2WRL6lGOsLVwhBf2B9jhb7D/wF/qhULWxlZY3ZJ6YHdzrgkoFIZMwIsEqii1w/JeeVZkBAskASSQN+/L+xxH8O35EiEE26127L94OkU1DW8uE7KsQsq6HX9a3Nn2oVWGkjpM5f74KyrFug3SAZCVxGnH3/nbJY7r7P/GunU39X5J8FyBYwvGkcuDoRYwq51kENhMI6d9VykE7PeK6qRYRdN+HTk2Za3LRLuF1LppUFi0mTP7aVJ3fRoOwi9r59yCgwi39mPwcK3vt+6wLYvI1W6gqsGxtYOZtpWAgSO0Gx065FWNZws+mcU0QJKUOI7AtS1mscs3FynrtCTLKja+zaDnY9sWRaWPdTKOOL9JCT2bFx/WnE1iJnHIaifp+17b27Eha3sfng50i4tR6Ojk1V3Nt1cZ/367pCwVceyR7CoubYvvLhNOxhGWBdPYIfQEj2YRm1xxnVascsVxz2VXShapYhDYfHES8iGyeXWzI5fd80qfFwvt2Lp1w9W2ous5Gbv2fqGj65dptwsr+4Rb8f8FRv1vsdgbtgmZArpnb3fhVOte7d2U9lBb3QuM22uaqwusJ8+10ImHUK4Pn+kPtOBxvEM5KcDyFo5O2/6M90QQHNxMx9WiKEths0Fer3BmA5qX30JdM3g610LsqaR+uyYrJaOHQyxb4OYr5n/9I1bco0k2OG/vcAsdA65kQ1HURJFDWWhXUCldQuk4AtuGOHBQsuHVl+ckmST2bQZDH9uxCHyHTVIiG3AtHYcrhG7yadcNaaofCP5gQei29e9VhTWdadHn+W1CqA3pRrt1z399+N8tC9YrmusLrKh36HvYH2q3TrRlqKoNEOrKhYtCC0vRCrpkrb/vHx/2M3ptf8juM3AQOa6nRXq3GCBs/TvbUmLr08ewXtLcXetj7Hba4ZMSfB879pgexYTPj7F8n2ZxR/Hqilffr9oJPbjvUuLYZbEs+GzzD4JxRLnKsIcR/sOxdvOSBNIUpnMtVG8vYbmEk5O9s93kOzh/C4sFjVSEj2aEQP7mluybd/gPt3jzAdlX3xE+O8I6PtJO5XQOj5/rti7ChoePsY4eYL1/o+/NNMGaHevWIXmur81woq9bd/7Cnu4bmaU6cTbd6D6awtbXNd8dgou60uz7Jdw/YeAOD0Ey7Yu229Ome341NHW9L0MFSCs9/m52t7xPL/l8/ARXuPS9AUm52X925I/ouX29b85yyNt0wWWx5Cg8bsMiupeEACxUI/e/SzZS93orEs43S056enJU0/BsPuU4miBnkvfXC6qq5Gw2xrYszouSv/3+T8RuzLrY8Gq1pKpkG3ajJ6Vh6FOWFap1BbuSUxybIPRpmoavXr4m2+Z4vstgECOERRB4pOlOl31aICulx59UWnzutHj120TP2HUplcJvy01Bv4x8x8FCB/XErm4UrhPgJLYQ7KqKXtxHYLEuslZ8dBPVZt/QXtU1ddPsv75I1wx9n1nUo64Vp70jXdpbV3itKLi/F65LXO1E+qE0SjBow1ZkLXk8eMS6WHO7u2ubgqdsipSylgSOT8/zmE0G/GY+x7d9bncLXiyuef3msn2kN1w6d0RRwHqVst7lzHoxd9uMSRjyZDQicgNWecKm3HIU6uPc7G64zVZ8MjhGp4AKClXw/c0bbrIlpVI8m05ogB8WS76++sCTUcZpb8jf3//A55MpZ/0jHkQnzMM5z4ZPudheICybs94Z83DO++0HcpmTiIRZMOVBb0MuCzZlwrh13qu6xBUekR3xqP+ITG5ZFku21Zahr/e/1TiUqsBFO+pVo91t1ai2lPPjJEaA0An3K+T3EzO1ODyIE71nWN9DO6kbX6+KNVfZHZ/2T7EtQeRGewGkmprICYkc7eR25aQASZkwDiZt242fpB63O5UdYWt3TOVsypTLNGUeRXxfn9PQ8GQ2YRwMeD6pubheUFWSB9MRthB8KCv+8ts/0Pd0yfL5ZkNZ6pK4uq51yWToa1ewklRSEQQetmMjbEEYeihV8/WL12RZQRh49Pohtm3j+y7bVCcV44KUSjv97RjMtlqUvo8CPNtmGAhkqZgGQ7xIB7/Yli5j20n9vz1qg7O6PdubMuE6W/BsFOzdQR3I1bqhwqWmLeNF98lUtdyf364MtawrBl6vDSVq9wjzY1HRCXSEi9VI9BxNC6GuZY5qah72T0jLLct8rYVuXZCUGbKWDHyXnucxGvd5NpkQOD7LfMPr1Yp3b6+0C9M0XDsLoliPwSTLGfUiNpnuC3vW7xM5LkmZkZZbJsEI3/a52y1Y5gkn8aFCqJAV7zY/sMhTZF3z6WQMwPlyxT+vr/lsWHAUx3z54R3PJxNO4iHH0ZRpOOKzwUOushsEFvNwzvhsxOX2uq1W2TENxmyiLYUq2ZQpfa+P226HcIVL6AScxWfkakdSpmRyx9Bz29Jsh0IVOLZe8OzGXNdLUzb3tsu0dPsVu4nufbrvuhLEbox0gSirXHGbVpwNPUDQ88SPwlICR/yoVE+2x0lKxbDdI9bdCeInY78LbMllQ5JLlmnJKPZ4vdA/czrvMQwc6mnMxVVKVSmO5zGidfz+/LtTRqHDtlDcrPNWFLaLLqUiDB3KUlFVCiUVfuDhODrUzQ90L9p/vbgl2+b4gcdgEOz35OmUVH2PKqmwhIWUEmELtlvdX7oXe/rcBnpv+Tx2CRxXl+G25Z/bUrHJFU8nB9PGEYJlXnKZVPxqZrNrF5h06wx9/rToPlyrrlS0qmus9hiVqimlbilS1Q22YP+ehYM4t2hoLIt9ZCrN3gWLPdHePw1nQ49tWbPMJALt6qWFQtY1nuMQejaTScjJJCJwBKud5Gq14/xcz0Fp4LLtfbhZ70jTksHAJ8tK4sBl2g/wXEFaKJJcMgodAsfibivZ5JJ577DYX6qal7clya5C1g1HE/2cuF5kvL1JyauQcezz8v2a02nEOPaZxy6TyOGTkc91ot3lo57DNBrwYVOiasjKmmnksukr8qomKRTDwMYVDbLWiyaeLXg48KlUTSa1w9r10LSthrJusDkEQt3f2fZz7qLVND/zEwaDwWAwGAwGg8Fg+MXx32OmDAaDwWAwGAwGg8Hwi8aIRYPBYDAYDAaDwWAwfIQRiwaDwWAwGAwGg8Fg+AgjFg0Gg8FgMBgMBoPB8BFGLBoMBoPBYDAYDAaD4SOMWDQYDAaDwWAwGAwGw0f8B5rJDZ9TWts9AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, ([ax1, ax2, ax3, ax4]) = plt.subplots(1, 4, figsize=(16, 3))\n", + "\n", + "ax1.imshow(R, cmap='Reds', vmax=1, vmin=0)\n", + "ax1.set_title('Red', fontweight='bold')\n", + "ax1.axis('off')\n", + "\n", + "ax2.imshow(G, cmap='Greens', vmax=1, vmin=0)\n", + "ax2.set_title('Veggie', fontweight='bold')\n", + "ax2.axis('off')\n", + "\n", + "ax3.imshow(G_true, cmap='Greens', vmax=1, vmin=0)\n", + "ax3.set_title('\"True\" Green', fontweight='bold')\n", + "ax3.axis('off')\n", + "\n", + "ax4.imshow(B, cmap='Blues', vmax=1, vmin=0)\n", + "ax4.set_title('Blue', fontweight='bold')\n", + "ax4.axis('off')\n", + "\n", + "plt.subplots_adjust(wspace=.02)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "The addition of the three channels results in a color image. Combine the three\n", + "channels with a stacked array and display the image with `imshow`." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(-0.5, 2499.5, 1499.5, -0.5)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# The RGB array with the raw veggie band\n", + "RGB_veggie = np.dstack([R, G, B])\n", + "\n", + "# The RGB array for the true color image\n", + "RGB = np.dstack([R, G_true, B])\n", + "\n", + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))\n", + "\n", + "# The RGB using the raw veggie band\n", + "ax1.imshow(RGB_veggie)\n", + "ax1.set_title('GOES-16 RGB Raw Veggie', fontweight='bold', loc='left',\n", + " fontsize=12)\n", + "ax1.set_title('{}'.format(scan_start.strftime('%d %B %Y %H:%M UTC ')),\n", + " loc='right')\n", + "ax1.axis('off')\n", + "\n", + "# The RGB for the true color image\n", + "ax2.imshow(RGB)\n", + "ax2.set_title('GOES-16 RGB True Color', fontweight='bold', loc='left',\n", + " fontsize=12)\n", + "ax2.set_title('{}'.format(scan_start.strftime('%d %B %Y %H:%M UTC ')),\n", + " loc='right')\n", + "ax2.axis('off')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Plot with `Cartopy` Geostationary Projection\n", + "----------------------------------------------\n", + "\n", + "The image above is not georeferenced. You can see the land and oceans, but we\n", + "do have enough information to draw state and country boundaries. Use the\n", + "`metpy.io` package to obtain the projection information from the file. Then\n", + "use `Cartopy` to plot the image on a map. The GOES data and image is on a\n", + "[geostationary projection](https://proj4.org/operations/projections/geos.html?highlight=geostationary)." + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# We'll use the `CMI_C02` variable as a 'hook' to get the CF metadata.\n", + "dat = C.metpy.parse_cf('CMI_C02')\n", + "\n", + "geos = dat.metpy.cartopy_crs\n", + "\n", + "# We also need the x (north/south) and y (east/west) axis sweep of the ABI data\n", + "x = dat.x\n", + "y = dat.y" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "The geostationary projection is the easiest way to plot the image on a\n", + "map. Essentially, we are stretching the image across a map with the same\n", + "projection and dimensions as the data." + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(1.0, 1.0, '10 October 2018 14:32 UTC ')" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 12))\n", + "\n", + "# Create axis with Geostationary projection\n", + "ax = fig.add_subplot(1, 1, 1, projection=geos)\n", + "\n", + "# Add the RGB image to the figure. The data is in the same projection as the\n", + "# axis we just created.\n", + "ax.imshow(RGB, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()), transform=geos)\n", + "\n", + "# Add Coastlines and States\n", + "ax.coastlines(resolution='50m', color='black', linewidth=0.25)\n", + "ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.25)\n", + "\n", + "plt.title('GOES-16 True Color', loc='left', fontweight='bold', fontsize=15)\n", + "plt.title('{}'.format(scan_start.strftime('%d %B %Y %H:%M UTC ')), loc='right')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Using other projections\n", + "-----------------------\n", + "\n", + "Changing the projections with `Cartopy` is straightforward. Here we display\n", + "the GOES-16 data on a Lambert Conformal projection." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(1.0, 1.0, '10 October 2018 14:32 UTC ')" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 12))\n", + "\n", + "# Generate an Cartopy projection\n", + "lc = ccrs.LambertConformal(central_longitude=-97.5,\n", + " standard_parallels=(38.5, 38.5))\n", + "\n", + "ax = fig.add_subplot(1, 1, 1, projection=lc)\n", + "ax.set_extent([-135, -60, 10, 65], crs=ccrs.PlateCarree())\n", + "\n", + "ax.imshow(RGB, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos,\n", + " interpolation='none')\n", + "ax.coastlines(resolution='50m', color='black', linewidth=0.5)\n", + "ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.5)\n", + "\n", + "plt.title('GOES-16 True Color', loc='left', fontweight='bold', fontsize=15)\n", + "plt.title('{}'.format(scan_start.strftime('%d %B %Y %H:%M UTC ')), loc='right')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Plot with `Cartopy`: Plate Carrée Cylindrical Projection\n", + "---------------------------------------------------------\n", + "\n", + "It is often useful to zoom on a specific location. This image will zoom in on Utah." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(1.0, 1.0, '10 October 2018 14:32 UTC ')" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(8, 8))\n", + "\n", + "pc = ccrs.PlateCarree()\n", + "\n", + "ax = fig.add_subplot(1, 1, 1, projection=pc)\n", + "ax.set_extent([-114.75, -108.25, 36, 43], crs=pc)\n", + "\n", + "ax.imshow(RGB, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos,\n", + " interpolation='none')\n", + "\n", + "ax.coastlines(resolution='50m', color='black', linewidth=1)\n", + "ax.add_feature(ccrs.cartopy.feature.STATES)\n", + "\n", + "plt.title('GOES-16 True Color', loc='left', fontweight='bold', fontsize=15)\n", + "plt.title('{}'.format(scan_start.strftime('%d %B %Y %H:%M UTC ')), loc='right')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Overlay Nighttime IR when dark\n", + "------------------------------\n", + "\n", + "At nighttime, the visible wavelengths do not measure anything and is just\n", + "black. There is information, however, from other channels we can use to see\n", + "clouds at night. To view clouds in portions of the domain experiencing\n", + "nighttime, we will overlay the clean infrared (IR) channel over the true color\n", + "image.\n", + "\n", + "First, open a file where the scan shows partial night area and create the true\n", + "color RGB as before." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# A GOES-16 file with half day and half night\n", + "FILE = ('https://ramadda.scigw.unidata.ucar.edu/repository/opendap'\n", + " '/85da3304-b910-472b-aedf-a6d8c1148131/entry.das#fillmismatch')\n", + "C = xarray.open_dataset(FILE)\n", + "\n", + "# Scan's start time, converted to datetime object\n", + "scan_start = datetime.strptime(C.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ')\n", + "\n", + "# Create the RGB like we did before\n", + "\n", + "# Load the three channels into appropriate R, G, and B\n", + "R = C['CMI_C02'].data\n", + "G = C['CMI_C03'].data\n", + "B = C['CMI_C01'].data\n", + "\n", + "# Apply range limits for each channel. RGB values must be between 0 and 1\n", + "R = np.clip(R, 0, 1)\n", + "G = np.clip(G, 0, 1)\n", + "B = np.clip(B, 0, 1)\n", + "\n", + "# Apply the gamma correction\n", + "gamma = 2.2\n", + "R = np.power(R, 1/gamma)\n", + "G = np.power(G, 1/gamma)\n", + "B = np.power(B, 1/gamma)\n", + "\n", + "# Calculate the \"True\" Green\n", + "G_true = 0.45 * R + 0.1 * G + 0.45 * B\n", + "G_true = np.clip(G_true, 0, 1)\n", + "\n", + "# The final RGB array :)\n", + "RGB = np.dstack([R, G_true, B])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Load the Clear IR 10.3 µm channel (Band 13)\n", + "-------------------------------------------------------\n", + "\n", + "When you print the contents of channel 13, notice that the unit of the clean\n", + "IR channel is *brightness temperature*, NOT reflectance. We need to normalize\n", + "the values between 0 and 1 before we can use it in our RGB image. In this\n", + "case, we normalize the values between 90 Kelvin and 313 Kelvin." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "[3750000 values with dtype=float32]\n", + "Coordinates:\n", + " t datetime64[ns] ...\n", + " * y (y) float32 0.128212 0.128156 ... 0.044324003 0.044268005\n", + " * x (x) float32 -0.101332 -0.101276 ... 0.038556002 0.038612\n", + " y_image float32 ...\n", + " x_image float32 ...\n", + "Attributes:\n", + " long_name: ABI Cloud and Moisture Imagery brightness tempera...\n", + " standard_name: toa_brightness_temperature\n", + " sensor_band_bit_depth: 12\n", + " valid_range: [ 0 4095]\n", + " units: K\n", + " resolution: y: 0.000056 rad x: 0.000056 rad\n", + " grid_mapping: goes_imager_projection\n", + " cell_methods: t: point area: point\n", + " ancillary_variables: DQF_C13\n", + " _ChunkSizes: [250 250]\n" + ] + } + ], + "source": [ + "print(C['CMI_C13'])" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# Apply the normalization...\n", + "cleanIR = C['CMI_C13'].data\n", + "\n", + "# Normalize the channel between a range.\n", + "# cleanIR = (cleanIR-minimumValue)/(maximumValue-minimumValue)\n", + "cleanIR = (cleanIR-90)/(313-90)\n", + "\n", + "# Apply range limits to make sure values are between 0 and 1\n", + "cleanIR = np.clip(cleanIR, 0, 1)\n", + "\n", + "# Invert colors so that cold clouds are white\n", + "cleanIR = 1 - cleanIR\n", + "\n", + "# Lessen the brightness of the coldest clouds so they don't appear so bright\n", + "# when we overlay it on the true color image.\n", + "cleanIR = cleanIR/1.4\n", + "\n", + "# Yes, we still need 3 channels as RGB values. This will be a grey image.\n", + "RGB_cleanIR = np.dstack([cleanIR, cleanIR, cleanIR])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Show the true color and clean IR images\n", + "---------------------------------------\n", + "\n", + "We want to overlay these two images, so the clean IR fills in the night sky\n", + "on the True Color image. This way we can still see the clouds at night." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(-0.5, 2499.5, 1499.5, -0.5)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 6))\n", + "\n", + "ax1.set_title('True Color', fontweight='bold')\n", + "ax1.imshow(RGB)\n", + "ax1.axis('off')\n", + "\n", + "ax2.set_title('Clean IR', fontweight='bold')\n", + "ax2.imshow(RGB_cleanIR)\n", + "ax2.axis('off')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "To fill in the dark area on the true color image, we will set each RGB channel\n", + "to equal the maximum value between the visible channels and the IR\n", + "channels. When this is done, where RGB values are black in the true color\n", + "image RGB = (0,0,0), it will be replaced with a higher value of the `cleanIRRGB`.\n", + "\n", + "Note that if the clean IR has really bright, cold clouds in the daylight, they\n", + "will replace the color values in the true color image making the clouds appear\n", + "more white. Still, it makes a nice plot and let's you see clouds when it is\n", + "night." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# Maximize the RGB values between the True Color Image and Clean IR image\n", + "RGB_ColorIR = np.dstack([np.maximum(R, cleanIR), np.maximum(G_true, cleanIR),\n", + " np.maximum(B, cleanIR)])" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(1.0, 1.0, '00:17 UTC 14 September 2018')" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 12))\n", + "\n", + "ax = fig.add_subplot(1, 1, 1, projection=geos)\n", + "\n", + "ax.imshow(RGB_ColorIR, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos)\n", + "\n", + "ax.coastlines(resolution='50m', color='black', linewidth=2)\n", + "ax.add_feature(ccrs.cartopy.feature.STATES)\n", + "\n", + "plt.title('GOES-16 True Color and Night IR', loc='left', fontweight='bold',\n", + " fontsize=15)\n", + "plt.title('{}'.format(scan_start.strftime('%H:%M UTC %d %B %Y'), loc='right'),\n", + " loc='right')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Adjust Image Contrast\n", + "---------------------\n", + "\n", + "I think the color looks a little dull. We could get complicated and make a\n", + "Rayleigh correction to the data to fix the blue light scattering, but that can\n", + "be intense. More simply, we can make the colors pop out by adjusting the image\n", + "contrast. Adjusting image contrast is easy to do in Photoshop, and also easy\n", + "to do in Python.\n", + "\n", + "We are still using the RGB values from the day/night GOES-16 ABI scan.\n", + "\n", + "Note: you should adjust the contrast _before_ you add in the Clean IR channel." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "def contrast_correction(color, contrast):\n", + " \"\"\"Modify the contrast of an RGB.\n", + " See:\n", + " https://www.dfstudios.co.uk/articles/programming/image-programming-algorithms/image-processing-algorithms-part-5-contrast-adjustment/\n", + "\n", + " Input:\n", + " color - an array representing the R, G, and/or B channel\n", + " contrast - contrast correction level\n", + " \"\"\"\n", + " F = (259*(contrast + 255))/(255.*259-contrast)\n", + " COLOR = F*(color-.5)+.5\n", + " COLOR = np.clip(COLOR, 0, 1) # Force value limits 0 through 1.\n", + " return COLOR\n", + "\n", + "\n", + "# Amount of contrast\n", + "contrast_amount = 105\n", + "\n", + "# Apply contrast correction\n", + "RGB_contrast = contrast_correction(RGB, contrast_amount)\n", + "\n", + "# Add in clean IR to the contrast-corrected True Color image\n", + "RGB_contrast_IR = np.dstack([np.maximum(RGB_contrast[:, :, 0], cleanIR),\n", + " np.maximum(RGB_contrast[:, :, 1], cleanIR),\n", + " np.maximum(RGB_contrast[:, :, 2], cleanIR)])" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Plot on map with Cartopy\n", + "\n", + "fig = plt.figure(figsize=(15, 12))\n", + "\n", + "ax1 = fig.add_subplot(1, 2, 1, projection=geos)\n", + "ax2 = fig.add_subplot(1, 2, 2, projection=geos)\n", + "\n", + "ax1.imshow(RGB_ColorIR, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos)\n", + "ax1.coastlines(resolution='50m', color='black', linewidth=2)\n", + "ax1.add_feature(ccrs.cartopy.feature.BORDERS)\n", + "ax1.set_title('True Color and Night IR')\n", + "\n", + "ax2.imshow(RGB_contrast_IR, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos)\n", + "ax2.coastlines(resolution='50m', color='black', linewidth=2)\n", + "ax2.add_feature(ccrs.cartopy.feature.BORDERS)\n", + "ax2.set_title('Contrast Correction = {}'.format(contrast_amount))\n", + "\n", + "plt.subplots_adjust(wspace=.02)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Can we make plots for a Mesoscale scan?\n", + "---------------------------------------\n", + "\n", + "Yes. Yes we can." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "# M1 is for the Mesoscale1 NetCDF file\n", + "FILE = ('https://ramadda.scigw.unidata.ucar.edu/repository/opendap'\n", + " '/5e02eafa-5cee-4d00-9f58-6e201e69b014/entry.das#fillmismatch')\n", + "M1 = xarray.open_dataset(FILE)\n", + "\n", + "# Load the RGB arrays\n", + "R = M1['CMI_C02'][:].data\n", + "G = M1['CMI_C03'][:].data\n", + "B = M1['CMI_C01'][:].data\n", + "\n", + "# Apply range limits for each channel. RGB values must be between 0 and 1\n", + "R = np.clip(R, 0, 1)\n", + "G = np.clip(G, 0, 1)\n", + "B = np.clip(B, 0, 1)\n", + "\n", + "# Apply the gamma correction\n", + "gamma = 2.2\n", + "R = np.power(R, 1/gamma)\n", + "G = np.power(G, 1/gamma)\n", + "B = np.power(B, 1/gamma)\n", + "\n", + "# Calculate the \"True\" Green\n", + "G_true = 0.45 * R + 0.1 * G + 0.45 * B\n", + "G_true = np.clip(G_true, 0, 1)\n", + "\n", + "# The final RGB array :)\n", + "RGB = np.dstack([R, G_true, B])\n", + "\n", + "# Scan's start time, converted to datetime object\n", + "scan_start = datetime.strptime(M1.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ')\n", + "\n", + "# We'll use the `CMI_C02` variable as a 'hook' to get the CF metadata.\n", + "dat = M1.metpy.parse_cf('CMI_C02')\n", + "\n", + "# Need the satellite sweep x and y values, too.\n", + "x = dat.x\n", + "y = dat.y" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10, 8))\n", + "\n", + "ax = fig.add_subplot(1, 1, 1, projection=lc)\n", + "ax.set_extent([-125, -70, 25, 50], crs=ccrs.PlateCarree())\n", + "\n", + "ax.imshow(RGB, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos)\n", + "\n", + "ax.coastlines(resolution='50m', color='black', linewidth=0.5)\n", + "ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.5)\n", + "ax.add_feature(ccrs.cartopy.feature.BORDERS, linewidth=0.5)\n", + "\n", + "plt.title('GOES-16 True Color', fontweight='bold', fontsize=15, loc='left')\n", + "plt.title('Mesoscale Section 1')\n", + "plt.title('{}'.format(scan_start.strftime('%H:%M UTC %d %B %Y')), loc='right');" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 12))\n", + "\n", + "ax = fig.add_subplot(1, 1, 1, projection=geos)\n", + "\n", + "ax.imshow(RGB, origin='upper',\n", + " extent=(x.min(), x.max(), y.min(), y.max()),\n", + " transform=geos)\n", + "\n", + "ax.coastlines(resolution='50m', color='black', linewidth=0.25)\n", + "ax.add_feature(ccrs.cartopy.feature.STATES, linewidth=0.25)\n", + "\n", + "plt.title('GOES-16 True Color', fontweight='bold', fontsize=15, loc='left')\n", + "plt.title('Mesoscale Section 1')\n", + "plt.title('{}'.format(scan_start.strftime('%H:%M UTC %d %B %Y')), loc='right');" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Can we do this for a Full Disk Scan? It's possible...\n", + "-----------------------------------------------------\n", + "\n", + "but data files are so large that plotting is very slow. Feel free to\n", + "experiment." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [], + "source": [ + "FILE = ('https://ramadda.scigw.unidata.ucar.edu/repository/opendap'\n", + " '/deb91f58-f997-41a3-a077-987529bf02b3/entry.das#fillmismatch')\n", + "F = xarray.open_dataset(FILE)\n", + "\n", + "# Load the RGB arrays\n", + "R = F['CMI_C02'][:].data\n", + "G = F['CMI_C03'][:].data\n", + "B = F['CMI_C01'][:].data\n", + "\n", + "# Apply range limits for each channel. RGB values must be between 0 and 1\n", + "R = np.clip(R, 0, 1)\n", + "G = np.clip(G, 0, 1)\n", + "B = np.clip(B, 0, 1)\n", + "\n", + "# Apply the gamma correction\n", + "gamma = 2.2\n", + "R = np.power(R, 1/gamma)\n", + "G = np.power(G, 1/gamma)\n", + "B = np.power(B, 1/gamma)\n", + "\n", + "# Calculate the \"True\" Green\n", + "G_true = 0.48358168 * R + 0.45706946 * B + 0.06038137 * G\n", + "G_true = np.clip(G_true, 0, 1)\n", + "\n", + "# The final RGB array :)\n", + "RGB = np.dstack([R, G_true, B])\n", + "\n", + "# We'll use the `CMI_C02` variable as a 'hook' to get the CF metadata.\n", + "dat = F.metpy.parse_cf('CMI_C02')\n", + "\n", + "x = dat.x\n", + "y = dat.y" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "source": [ + "Geostationary projection is easy..." + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "cell_marker": "\"\"\"", + "lines_to_next_cell": 0, + "pycharm": { + "name": "#%% md\n" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "\n", + "# Coordinates for the region of interest\n", + "lat_max, lon_max = -21.699774257353113, -42.35676996062447 # Upper-right corner\n", + "lat_min, lon_min = -23.801876626302175, -45.05290312102409 # Lower-left corner\n", + "\n", + "# Create a figure with Cartopy projection\n", + "fig = plt.figure(figsize=(10, 8))\n", + "ax = plt.axes(projection=ccrs.PlateCarree())\n", + "\n", + "# Set the extent of the map to the region of interest\n", + "ax.set_extent([lon_min, lon_max, lat_min, lat_max], crs=ccrs.PlateCarree())\n", + "\n", + "# Add geographic features (optional)\n", + "ax.add_feature(cfeature.COASTLINE)\n", + "ax.add_feature(cfeature.BORDERS)\n", + "ax.add_feature(cfeature.STATES, linestyle=':')\n", + "ax.add_feature(cfeature.LAND)\n", + "ax.add_feature(cfeature.OCEAN)\n", + "\n", + "# Add gridlines for better readability\n", + "ax.gridlines(draw_labels=True, dms=True, x_inline=False, y_inline=False)\n", + "\n", + "# Plot title\n", + "plt.title('Region of Interest')\n", + "\n", + "# Show the plot\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "\n", + "import datetime as dt\n", + "import logging\n", + "\n", + "import xarray as xr\n", + "\n", + "def LonLat2ABIangle(lon_deg, lat_deg, z, H, req, rpol, e, lon_0_deg):\n", + " \"\"\"\n", + " Computes the GOES-R ABI Fixed Grid image coordinates given latitude and longitude (degrees) of a ground point.\n", + "\n", + " Parameters\n", + " ------------\n", + " lon_deg : float\n", + " longitude of ground point [degrees]\n", + " lat_deg : float\n", + " latitude of ground point [degrees]\n", + " z : float\n", + " elevation of ground point above GRS80 ellipsoid [meters]\n", + " H : float\n", + " satellite distance to Earth center [km]\n", + " req : float\n", + " Earth semi-major axis of GRS80 ellipsoid (equatorial radius) [km]\n", + " rpol : float\n", + " Earth semi-minor axis of GRS80 ellipsoid (polar radius) [km]\n", + " e : float\n", + " eccentricity of ellipsoid (e=0.0818191910435 for GRS80) [unitless]\n", + " lon_0_deg : float\n", + " longitude of projection origin (longitude of sub-satellite point) [degrees]\n", + "\n", + " Returns\n", + " ------------\n", + " x : float\n", + " ABI Fixed Grid x coordinate (scan angle) [radians]\n", + " y : float\n", + " ABI Fixed Grid y coordinate (elevation angle) [radians]\n", + "\n", + " Examples\n", + " ------------\n", + "\n", + " \"\"\"\n", + "\n", + " # convert lat and lon from degrees to radians\n", + " lon = np.radians(lon_deg)\n", + " lat = np.radians(lat_deg)\n", + " lon_0 = np.radians(lon_0_deg)\n", + "\n", + " # geocentric latitude\n", + " lat_geo = np.arctan((rpol**2 / req**2) * np.tan(lat))\n", + "\n", + " # geocentric distance to point on the ellipsoid\n", + " rc = rpol / np.sqrt(\n", + " 1 - (e**2) * (np.cos(lat_geo) ** 2)\n", + " ) # this is rc if point is on the ellipsoid\n", + " if ~isinstance(z, int):\n", + " rc = (\n", + " rc + z\n", + " ) # this is rc if the point is offset from the ellipsoid by z (meters)\n", + "\n", + " # intermediate calculations\n", + " Sx = H - rc * np.cos(lat_geo) * np.cos(lon - lon_0)\n", + " Sy = -rc * np.cos(lat_geo) * np.sin(lon - lon_0)\n", + " Sz = rc * np.sin(lat_geo)\n", + "\n", + " # calculate x and y scan angles\n", + " y = np.arctan(Sz / Sx)\n", + " x = np.arcsin(-Sy / np.sqrt(Sx**2 + Sy**2 + Sz**2))\n", + "\n", + " ## determine if this point is visible to the satellite\n", + " # condition = ( H * (H-Sx) ) < ( Sy**2 + (req**2 / rpol**2)*Sz**2 )\n", + " # if condition == True:\n", + " # print('Point at {},{} not visible to satellite.'.format(lon_deg,lat_deg))\n", + " # return (np.nan, np.nan)\n", + " # else:\n", + " # return (x,y)\n", + " return (x, y)\n", + "\n", + "\n", + "def subsetNetCDF(filepath, bounds, newfilepath=None):\n", + " \"\"\"\n", + " Crop a GOES-R ABI NetCDF file to latitude/longitude bounds, add datetime dims/coords.\n", + "\n", + " Parameters\n", + " ------------\n", + " filepath : str\n", + " path to a NetCDF file\n", + " bounds : list\n", + " list or array containing latitude/longitude bounds like [min_lon, min_lat, max_lon, max_lat]\n", + " newfilepath : str\n", + " path and filename for a new NetCDF file to write out to, defaults to None where it will overwrite the input NetCDF file\n", + "\n", + " Returns\n", + " ------------\n", + " None\n", + "\n", + " Examples\n", + " ------------\n", + " Subset a GOES ABI CONUS image so that we only have the western half of CONUS within latitudes 30 and 50, and longitudes -125 and -105.\n", + "\n", + " >>> bounds = [-125, 30, -105, 50]\n", + " >>> subsetNetCDF('CONUS.nc',bounds,newfilepath='westernCONUS.nc')\n", + "\n", + " \"\"\"\n", + "\n", + " # get bounds: [min_lon, min_lat, max_lon, max_lat]\n", + " lon_west = bounds[0]\n", + " lat_south = bounds[1]\n", + " lon_east = bounds[2]\n", + " lat_north = bounds[3]\n", + "\n", + " with xr.open_dataset(filepath) as file:\n", + " f = file.load()\n", + " # Values needed for geometry calculations\n", + " req = f.goes_imager_projection.semi_major_axis\n", + " rpol = f.goes_imager_projection.semi_minor_axis\n", + " H = (\n", + " f.goes_imager_projection.perspective_point_height\n", + " + f.goes_imager_projection.semi_major_axis\n", + " )\n", + " lon_0 = f.goes_imager_projection.longitude_of_projection_origin\n", + " e = 0.0818191910435 # GRS-80 eccentricity\n", + "\n", + " # find corresponding look angles for the four corners\n", + " x_rad_sw, y_rad_sw = LonLat2ABIangle(\n", + " lon_west, lat_south, 0, H, req, rpol, e, lon_0\n", + " )\n", + " logging.info(\"SW Corner: {}, {}\".format(x_rad_sw, y_rad_sw))\n", + " x_rad_se, y_rad_se = LonLat2ABIangle(\n", + " lon_east, lat_south, 0, H, req, rpol, e, lon_0\n", + " )\n", + " logging.info(\"SE Corner: {}, {}\".format(x_rad_se, y_rad_se))\n", + " x_rad_nw, y_rad_nw = LonLat2ABIangle(\n", + " lon_west, lat_north, 0, H, req, rpol, e, lon_0\n", + " )\n", + " logging.info(\"NW Corner: {}, {}\".format(x_rad_nw, y_rad_nw))\n", + " x_rad_ne, y_rad_ne = LonLat2ABIangle(\n", + " lon_east, lat_north, 0, H, req, rpol, e, lon_0\n", + " )\n", + " logging.info(\"NE Corner: {}, {}\".format(x_rad_ne, y_rad_ne))\n", + " # choose the bounds that cover the largest extent\n", + " y_rad_s = min(\n", + " y_rad_sw, y_rad_se\n", + " ) # choose southern-most coordinate (scan angle in radians)\n", + " y_rad_n = max(y_rad_nw, y_rad_ne) # northern-most\n", + " x_rad_e = max(x_rad_se, x_rad_ne) # eastern-most (scan angle in radians)\n", + " x_rad_w = min(x_rad_sw, x_rad_nw) # western-most\n", + " logging.info(\n", + " \"Corner coords chosen: N: {}, S: {}; E: {}, W: {}\".format(\n", + " y_rad_n, y_rad_s, x_rad_e, x_rad_w\n", + " )\n", + " )\n", + " # Use these coordinates to subset the whole dataset\n", + " y_rad_bnds, x_rad_bnds = [y_rad_n, y_rad_s], [x_rad_w, x_rad_e]\n", + " ds = f.sel(x=slice(*x_rad_bnds), y=slice(*y_rad_bnds))\n", + "\n", + " # while we have the file open, add datetime dims/coords to the file\n", + " # parse the start time from the file name (the part \"s2022__________\")\n", + " print(filepath)\n", + " this_datetime = dt.datetime.strptime(\n", + " filepath.stem.split(\"_\")[3][1:-1], \"%Y%j%H%M%S\"\n", + " )\n", + " ds = ds.assign_coords({\"time\": this_datetime})\n", + " ds = ds.expand_dims(\"time\")\n", + " ds = ds.reset_coords(drop=True)\n", + "\n", + " # Close the original file\n", + " f.close()\n", + " if newfilepath is None:\n", + " # Overwrite the original file\n", + " ds.to_netcdf(\n", + " filepath, \"w\", encoding={\"x\": {\"dtype\": \"float\"}, \"y\": {\"dtype\": \"float\"}}\n", + " )\n", + " else:\n", + " # save to new file\n", + " ds.to_netcdf(\n", + " newfilepath,\n", + " \"w\",\n", + " encoding={\"x\": {\"dtype\": \"float\"}, \"y\": {\"dtype\": \"float\"}},\n", + " )\n", + "\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "../../goes16_data/OR_ABI-L1b-RadF-M6C10_G16_s20233220000205_e20233220009525_c20233220009561.nc\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "'str' object has no attribute 'stem'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m bounds \u001b[38;5;241m=\u001b[39m [\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m125\u001b[39m, \u001b[38;5;241m30\u001b[39m, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m105\u001b[39m, \u001b[38;5;241m50\u001b[39m]\n\u001b[0;32m----> 2\u001b[0m \u001b[43msubsetNetCDF\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m../../goes16_data/OR_ABI-L1b-RadF-M6C10_G16_s20233220000205_e20233220009525_c20233220009561.nc\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbounds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mnewfilepath\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtemp.nc\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[4], line 160\u001b[0m, in \u001b[0;36msubsetNetCDF\u001b[0;34m(filepath, bounds, newfilepath)\u001b[0m\n\u001b[1;32m 156\u001b[0m \u001b[38;5;66;03m# while we have the file open, add datetime dims/coords to the file\u001b[39;00m\n\u001b[1;32m 157\u001b[0m \u001b[38;5;66;03m# parse the start time from the file name (the part \"s2022__________\")\u001b[39;00m\n\u001b[1;32m 158\u001b[0m \u001b[38;5;28mprint\u001b[39m(filepath)\n\u001b[1;32m 159\u001b[0m this_datetime \u001b[38;5;241m=\u001b[39m dt\u001b[38;5;241m.\u001b[39mdatetime\u001b[38;5;241m.\u001b[39mstrptime(\n\u001b[0;32m--> 160\u001b[0m \u001b[43mfilepath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstem\u001b[49m\u001b[38;5;241m.\u001b[39msplit(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m_\u001b[39m\u001b[38;5;124m\"\u001b[39m)[\u001b[38;5;241m3\u001b[39m][\u001b[38;5;241m1\u001b[39m:\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mY\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mj\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mH\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mM\u001b[39m\u001b[38;5;124m%\u001b[39m\u001b[38;5;124mS\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 161\u001b[0m )\n\u001b[1;32m 162\u001b[0m ds \u001b[38;5;241m=\u001b[39m ds\u001b[38;5;241m.\u001b[39massign_coords({\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m\"\u001b[39m: this_datetime})\n\u001b[1;32m 163\u001b[0m ds \u001b[38;5;241m=\u001b[39m ds\u001b[38;5;241m.\u001b[39mexpand_dims(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mAttributeError\u001b[0m: 'str' object has no attribute 'stem'" + ] + } + ], + "source": [ + "bounds = [-125, 30, -105, 50]\n", + "subsetNetCDF('../../goes16_data/OR_ABI-L1b-RadF-M6C10_G16_s20233220000205_e20233220009525_c20233220009561.nc', bounds, newfilepath='temp.nc')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.18" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/GPM/plot_half_hourly_data.ipynb b/notebooks/GPM/plot_half_hourly_data.ipynb new file mode 100644 index 00000000..8e0251ef --- /dev/null +++ b/notebooks/GPM/plot_half_hourly_data.ipynb @@ -0,0 +1,2216 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: imageio[ffmpeg] in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (2.36.1)\n", + "Requirement already satisfied: pillow>=8.3.2 in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from imageio[ffmpeg]) (10.0.1)\n", + "Requirement already satisfied: numpy in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from imageio[ffmpeg]) (1.26.0)\n", + "Collecting imageio-ffmpeg\n", + " Downloading imageio_ffmpeg-0.5.1-py3-none-manylinux2010_x86_64.whl (26.9 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(3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S203000-E205959.1230.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S210000-E212959.1260.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S213000-E215959.1290.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S220000-E222959.1320.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S223000-E225959.1350.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S230000-E232959.1380.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n", + "Loading file ../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S233000-E235959.1410.V07B.nc\n", + "precipitation.shape: (3600, 1800)\n", + "(3600,) (1800,) (3600, 1800)\n", + "(1800, 3600) (1800, 3600) (3600, 1800)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_15718/1429182320.py:60: DeprecationWarning: Starting with ImageIO v3 the behavior of this function will switch to that of iio.v3.imread. To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.\n", + " writer.append_data(imageio.imread(frame))\n", + "IMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (1000, 600) to (1008, 608) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Animation saved as ./imerg_animation_2024_01_01.mp4\n" + ] + }, + { + "data": { + "image/png": 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WW6iqmmW077z9yO/aWMdyu92aV0ND4zhHy9nQ0DiOueCCC9ixY8eYSagHmksuuQRRFPnwww8PqCEwkmuuuYa3336b+vr6rNnjA81tt92Gw+Hg9ttvzyyz2WwsXbqUd955JyvR9kDT1NTEueeeS2FhIS+99NKYXob0uY8sZAjJOPvOzs5R12ZoaIizzz6bWCzGK6+8Mmb8fXt7Ozt27KC2tpaamhpqamq45pprgKTKVU1NDX6/n1mzZvHaa69lvdKz7bNnz2bNmjUoipK17xUrVmC1Wpk0adJeXYtDeaw98d3vfpfHHnuMX/ziF5nrMl4ikQiqqu5RuWp32wNZoXr7e/6zZ88mHA6PUiRbsWJFZj1AWVkZBQUFo75rkBQ/OJi/Qw0NjaMDzdjQ0DiOueWWW7BarXz+85+nr69v1Pp9zSUYC7vdziOPPMKPfvQjLrroogO235F88Ytf5I477uDnP//5Qdl/GpfLxZe+9CVeeeUV1q1bl1n+wx/+EFmWuf7668cMpxrreu6N9G1vby9nn302oijyyiuvUFBQMGa7adOmMWXKFH73u99lhXs98sgjCIKQFcIWCoU4//zz6erq4qWXXtplsbe77rqLF154Iev14x//GEh+j1544QVsNhu5ubmceeaZWa907P7ll19OX18fzz//fGa/g4ODPPvss1x00UV7PQN+KI+1O+6//35+9rOfceutt3LzzTfvsl1/f/+oZV6vl7///e9UVFRQWFiY1dedpW8HBwfH/A6lQ95GKkLtzfmPJX37yU9+EoPBwMMPP5xZpqoqv/nNbygrK+PEE0/MLL/ssst48cUX6ejoyCx74403aGho4Iorrtjl9dDQ0Dg+0MKoNDSOYyZOnMhTTz3FNddcw+TJkzMVxFVVpaWlhaeeegpRFPdKynV3fOYznzkg+9kVVVVVu0yqHYvnnntuTM/AWWedlYmJ3xU333wzv/zlL7n33nv561//CiTrbzz00EN8/etfZ+LEiZkK4vF4nIaGBp588kmMRmNWVe6VK1dy2mmncccdd+yx7+eeey7Nzc3ccsstvPfee7z33nuZdUVFRZx11lmZz/fffz+f+MQnOPvss7n66qvZtGkTDz30EF/84hez5Eyvu+46Vq5cyec//3m2bt2aNZNtt9u5+OKLAUZVgIePK60vWLAg0253XH755SxatIjPfe5zbNmyJVPVWpZl7rzzzqy2y5YtY9myZUAyTCsUCnHXXXcByRC+JUuWHBHHeuGFFzIJ+vX19TzxxBNZ60d+l8477zzKy8s54YQTKCwspL29nccee4zu7m6eeeaZrO0eeugh7rzzTt56661MfZUnnniC3/zmN1x88cXU1tYSCAR45ZVXeO2117jooouyQrf25vy///3v8/jjj2dC0ADKy8v55je/yf33308ikWDBggX84x//4N133+XJJ5/MUtm69dZbefbZZznttNO4+eabCQaD3H///cyYMSOrgrqGhsZxymErJ6ihoXHEsGPHDvWmm25S6+rqVLPZrFosFnXKlCnql7/8ZXXdunVZbcdbfTtdQXxk5e6x2N8K4nvadqx+pM9hV690pe5dVRBP89nPflbV6XTqjh07spavXbtW/fSnP61WVlaqRqNRtdls6syZM9Vvf/vbo9q+9dZbKqDecccde7wGu+vzWFWvX3jhBXX27NmqyWRSy8vL1dtvv12Nx+NZbaqqqna5z6qqqt32J9338VYQV1VV9Xg86he+8AU1Ly9PtVqt6qmnnjrmd2R3/6PxXKtDdazxfpdUVVUfeugh9eSTT1bz8/NVvV6vFhQUqBdddJG6bNmyXe535ParVq1Sr7jiCrWyslI1mUyqzWZT586dqz7wwANZleL39vw/85nPqIDa0tKStVyWZfWee+5Rq6qqVKPRqE6bNk194oknxrwOmzZtUs8++2zVarWqLpdLve6669Te3t7dXjsNDY3jA0FVD2CchIaGhoaGhoaGhoaGRgotZ0NDQ0NDQ0NDQ0ND46CgGRsaGhoaGhoaGhoaGgcFzdjQ0NDQ0NDQ0NDQ0DgoaMaGhoaGhoaGhoaGhsZBQTM2NDQ0NDQ0NDQ0NDQOCpqxoaGhoaGhoaGhoaFxUBh3Ub9oNEo8Hj+YfdHQ0NDQ0NDQ0NDQOAowGo2YzeY9thuXsRGNRnG6ykjEPPvdMQ0NDQ0NDQ0NDQ2No5vi4mJaWlr2aHCMy9iIx+MkYh7mn/E3dHrbAemghoaGhoaGhoaGhsbRhyyF+OiNK4nH4wfG2Eij09vQGzRjQ0NDQ0NDQ0NDQ0Njz2gJ4hoaGhoaGhoaGhoaBwXN2NDQ0NDQ0NDQ0NDQOChoxoaGhoaGhoaGhoaGxkFBMzY0NDQ0NDQ0NDQ0NA4KmrGhoaGhoaGhoaGhoXFQ0IwNDQ0NDQ0NDQ0NDY2DgmZsaGhoaGhoaGhoaGgcFDRjQ0NDQ0NDQ0NDQ0PjoKAZGxoaGhoaGhoaGhoaB4W9qiCuoaGhcbShyHHCwVYUOYqiJFDkBKqSQFHiqfcEAIKgQxB1yffUi/TfOy0fa5lOb8VgykUQtDkcDQ0NDQ2NNJqxoaFxGFDkOImEHzkRRJJCyIkgipJAVWVQFVRVRk29C4Ieq70SVZWQEiFkKZR6DyJJYQQERJ0RQTQiikZE0YAgGhB1yb9FMbUu63NyvU5nQdSZEQThcF+ScSPFA4QCzYQDzSRi3pRRIKYG/WLqpUNRJXxD6/ANrkGRo4ekb4JowGQpxmwtTr2XYLIWY7Yk3w1G11F1rTU0NDQ0NPYXzdjQ0DiASPEAIf8OBFGPqDNjshRgMLpQVZnu5mcZ6llGNNJHIja038fS6W3o9FZQVRQlnjRWlHjSYNkLkrPyNvQGO3qDA7OtDIutArOtHIdrChZ7xX73dV+R4gGGB1YQ8ieNi5C/mXi0P9VvffLaooww0tKGWvIaOFxTqZj4aXLyZqPT20YYYoaUcWZAEPQIgpC1rarIH/+tyjDGsp3bSYkgsUgvsXAv0XAPQe9WBnveQk4EM+eT/E4UYzTnISdCWJ211E6/GZ3OdFiur4aGhoaGxsFGMzY0NMaJLEeToThyAlkKk4h7ScSGScR9RMNd+AbXEvLvANSs7ayOWgRRT8jXSF7JUlwFCzBZijCY3OgNyUG+Tm9LeidIzdKLOgSS77IUJRJsR9SZ0BtsGSNjV+E6qiqjKBKqHE8ZIfGPQ4YyyxIocgxZiiBLaW9JkHjMw3DfBwx2v5nam8CJF7yROZaqqqhKPLVdGFkOp95joCoj+qBmroPJUoTVUZOZ0Y9Hhwh4txH0bSPo3Y6qJLDYKzMvq70So7kAgE0f/g8hfyNGcyE2Zy0FZWdic9ZiddRisVciigfuFpb2ioABdMllkVAn3oHVGIw5KaNCQpajyFIEJXUNFCWG3uBEEA2oqoyoM2GxV2C2lZGjKiQSfqKhLqKhLhLxYSLBViLBVgCCvm2U1V6J1VF9wM5DQ0NDQ0PjSEIzNjQ0dkPTxgcIDG8hFulHSvjHbiSImMwFON2zKKm5FIerHlCR5RiRYDu+oXVEw91MX/wLcvJm73Uf9AYbjtz6cbcXBB06nQ7GmC1XlAQhX2PSSEoZSmmjKRruJhxsQ03nMIgGzJZitn50O/FIP/HoIFIisNeeEwCjuQCbo5ZQoIl4dBAAgzEXu2syOmMOfs8m+jpeyhwbQcwyXuLRfuLRfhQ5jsNVj81Zu9d92Be2r76TkL/xgO+3vO563MUnY3PUIuqMQNKYleI+EjFv5v8ixX2pv31IiQA6nRm9wYEu5YVKeqPs2HMmYzTnHfB+amhoaGho7C+CmpyC3C1+v5+cnBxOOOc/6A22Q9EvDY1DRtqQUBQpFRqTAATMtnI+ev0yIDmAL6q8EFf+/GSug96C3ujCYHShN9iPiqTgHevvp6/jP6OWmyxFWOyVGM35GIy5GEwuWrc8DIDVUY3JUozJUojRnI/e4ESnt+70sqDTmQEh+Up5MASS7yF/E8MDK4gEO7A5J2B3TcHhmoLRXJiVv6CqMrFIP5FgO9FIL3IiTCTUwVDP28hSOKvPM0/+DQ7XlINzoUaQiPvp7/wvUtyfOk8LOr0VUWdO5cAYQRCIRz3Eo/3EIgPEIn2ZvwVBxGKvwmKvRBB09Lb9I7PvworziIY6iUX6ScR9Y+aViDozBmMOemMOeoMdRY4hJQJIiWDS8EsbZ8CU+T8mr/iUg35NNDQ0xo+qyiRiXuLRQUS9GYutUsvb0jgmkBIhVrxyAT6fD6fTudu2mmdD47hEVVUCw5sY7H6Lntbnx2xjMObiLj4FWYoQ8jXQ2/ZPQr5GiqsvxmQtwWIrP+KNDEWRiIY6CPmb8fR/MGq9Tm/HmTebsL8J3+CaUV6LqQvvw2Qp3K8+GM155BYu3GM7QdBhtpZgtpZkLZ846xYg+T+LR/sJB1qx50zarz6NF4PRSVntlfu9H1WVWf6fMzKfRdFI2N+CxV6O0z0rZVC4MBhzMJhcGQMjacQlUeQ4kdT/MhxoJhxoIejdTiI+DEDnjqc0Y+M4QlVVZCkZ+iglgqmcJRWd3oLVXklgeAuhQAtS3JfJw7LYKw/ZhKGo16FIe+8FPZqRpDD+oXV4B9cQ9jcRCXUQj3myvLQGUx6u/Dnk5M/DlT9vv++vGhpHA5pnQ+O4I+RvomXLr/ENrsFgysska09f/CAGowNBMCDLYfo7Xqa/85XkrLqgx2B0pvIcQkAyzMhiq8BsLSUR86Ao8dQRVNK/KkEQMzPisegg4UATFRM/Q+Xkzx2081NVFe/gR3TteBq/ZwOqKgFgMOWiNziR5SiJ6GDSsBBEbI4abDmTsedMxuacgMGUi8HoRKe3HfHG1NGEd3A1qiJjd01Cb8gZNbupqvLHuTBSCEkKIydCBH3bGOx+i0iwPWMMpnNYrI4arI4abM5aLLbKTEjW8UY8OoRvaC2yFCERGyYe85CIJ0MFpUQAk6UYq6Mas7WEgHcb3oGVqIqEwZSH0ezGaM7HaMrDaEmG+1kdtUfss05VVZb/57R93n7xea8et9+Tg0HQ10D79j8Si/RlfqMmSxH2nMlYHFWp71Y+JnM+ibgX3+BavENrCPmS4ZnuohMprr4YV/487X6rcVSxN54NzdjQOK4IeLex8f2vYjC5qZ3+DdxFJ+32Bp+eqYqFe4lG+ohF+pLJvpGejMqQIBhQ1cQu97EzJmsJ809/er/PZSSqqiAlAviH1tOx4wlCvgbsOZMpLD8Hq3MCIf8OWjb/X6a9wzWVvNLTyCs+GZOlWHPrH0ZC/mbWLfv8LteLoom80qU4cqemBsLV6A2OQ9jDQ4six5O/s3A30XAvsUgvTvcs3EWLgORgu7/jZfzDm1AVCVVNEBjeRizSk7UfUTRhd03G6qglFu4hHGwjFunFYq8kt3AReoM9Gf4WGyIRHSIeGyKeNsJT5JeeyeS5tx/S8x8P77+4FEgq0qUnPwCsjgmEA02Zz4JowGQuRKc3I8txymqvorjqwkPd3WOaNW9/mkiwPfO5bMI1VE25cY/31ETcz1DPO/S0/oNwoAmzrYKSqk9SWHEueoP9YHdbQ2O/0YwNjWMORUlkJEr3h0Tcx9ZVtxLwbiW3YCG5RYuxOyem1qpIiRBO9/SkpOye+iTH6O98jaaNvwAU0upLOXlzcBWegNGUi5QIEQ13o9fbcLpnYM+din4c+4ZkCFQk2J6sGaHEUOTUS4kTjw4y3L+CSKgLKe4lEfen+pA8fnnddeTkz8tcL79nI9tW/wiD0ZFMOI4NZ45TM/VrlNZePt5LqHGAkaUwDWvvJhxoIRruzizPLVzMhBnfSoVTHfvSuL1t/6aj8c8pAYHkb0kQdBiMLuKxIcy2cgQEIqFOQMWWMwmdzowg6omGuolFesfcb0HZ2RjNecncKtGIwZiT8trpUupyUWQ5hiJHkRIBPH3LCQeaAbA565i95PeH6ArsG97BtXj7VxDy70BVFcy2MmyOGgrKz9YGrYcAWYoQDrQSDXczPLCSgc5XqJj4GYqrP4nR5N7j9qqq4vdspLftBYZ6lmF31TPzpIeA5GBOSviTOVvjfG5oaBwqNGND44hGSoTQ6c3JYmzjIBH3s+q1S1FVKZWQ7UBvzMFkKcRsLU2+bMl3ozk/y1ORjPMfSNa9EA2ZuhS97f9msOcd/J4NWfG0AKW1V1Iz9SvjPJcAzZt+xUDX61nLTZYi5p/xzLj2sSsa1t41ar8fI+B0z8DmnIjBlJO8LsYcLLYybM661OxwP9FID9Fwd6r2QzfRcA+xcA9SIpDZ07zT/4rZWrxffdXYP1RVpbftX7RsfhCro5YJM799SBLgjyQGut+kYc3/YrFXUjv9m5itpZjM+SDoGOp5B//wpkzBxqQE8oSs7SOhTob7V+Id+IiQr4F4LKl6Jgh6BNGQqUeTNsqzEMRMgUujKZe8kqUUlJ0xKn9IQ2N3qKpKR8Of6Gh8HACztRSHewZWRw0mc34ypCr1ys7HiiFJIbas/H9YbOXkFi6mbetvR3yHdRhMuThcU3HkTsPhno7dOVELh9M4rGjGhsYRRzw2TOuWhxnqeWdEbkOS/NIzmTTn1l2GM0XDPax+85pR28SjA0TD3VkzoTq9jYqJn6a05jIEUU93y9+zwocEQYfVOQGneybuwkXYciYSjw7S0/I8fR3/QRANzF365z0OMgLebfS0/pPBrtdSORFCpg8ANdO+TmnNZeO/QGMQi/TTsO4e/EPrACgoO4vKyZ9H1JkynpfA8JZUiFdPpphcLNJLPDr0cX8EEZOlKJl8bSnBbCvFlPrb6qw9LmbNj3R6Wp6nefODlFRfSvXUrxzQ+iFHE30d/2HH+vuxOmooqb6MgvKz9vr7KcsxeltfYLh/Bb6htVnrqqZ8GXfxScQivZitZRiMjqSymGg4kKehcZwTi/TjH95EwLMZ//BGoqHOUYp6OoMdQdAhS+EsVTlH7jQCw5vJLz0Nd9HJGIw5xKIDRILtBIa3EPRuQ1FiALiLTqZ+wV2H9Nw0NNJoxobGEYWqyrRs/vUuVZ8AFp//+m4HWI3r76O/46VRy43mglQMew46vYWgdxshfyMWWwWzTvkdw/0r2L7mR9hyJlFQdhaCIDLQ9TpB71YAJs25nYKyM4mGe2nd+hs8fe+jKolMRW2d3p6Rtk0W9Ysli99F+9Hp7cjSx9WhdXor5XXXU1Jzadas1d6SDp8K+XcQ8jcx1PNOMm49bzYzFv8y027ziu/iHViVug75mCzFmK0lmKzFmC2pd2sJJnMBwnE6eD1a2LHh5wS9W5i95A+HuyuHHd/Qerqb/4anbzl6g4OiygvJLzkVq6NmXDO5jet/ykDX68kEXXsler2V7pbnRrVzumdQNuEaLPZKzJZi7TdyFCCIIqoyhmfqKECSwsSjg1kvVVXQ663oDHbi0SG6W54jERsiv/QMcgtPSElc+5Ny1/EAUiJAIjZM0LcNALurnlknP3KYz0zjeEUzNjQOGom4n1i4J1nlWhBQVSVz4xR1ZgrLz85qP9y/gi0rv5f5LIhG1J08G0WVF1I38zt7OK6P/o6XMZoLUFUFUlWyo+Eugr4GQr6GrNAggPKJn6Zy0mdp3/5HOnc8RTJ8QmSsMApB0JFbuIjq+q8Q8G5KqdgEMy9QEHVmdDozos6M1VFD47q7d9nf0porqJ76lb3KMVFVhcDwZhrW3kUs0geAyVKMI3caBWVn4CpYmGWQrX7rU0RDHQCYrWXYnBOwOmowmHJTxlK2wfRx5XEtGfxIo3nTgwwPrGTu0sfHHV54rBMJddHT+gL9HS9nJUHXzbqFoorzswaeUiJEd/Pf8Hs24BtaS92s71FUcR4Anr7lbF11K5BMoC6p/iSJuJf27X/MOt5JF759aE5MY69I/58FMen5PlqNjd0hy1FWvHJRlocDkgn+eoMTvcGOmPLwqYqclAm3lVBcdQlO9/Tj1hOqcXjR6mxoHFBikX48ve8x1PsePs+6UTkOaQRBT0HZmTvlTGS3HWlo6A1OLPYKKid/YY99MBhzKJtw9S7Xq6pKIuZBSvhJxANICR8O11QEQaRqyhcpq70K7+BHRMO9DPevwO9Zt9P2Mp6+9ympuZTC8nN2fRxFIh4bIhr6OJF34uxbiUX6CAfaGOxO5lh0tzxLcfXFWGxlezy3/s5X6Gr6W0ZFRm9wMn3RL7DlTNxtguecJX8gHGwj7G8i5G/CP7yJod5lezwewLRFv8CVP2dcbTUOPnbXFHpan2fdsi9SNeVGcgsXHfdGocVWRu20r1E15QZat/ya3rZ/ATDU+x4FpWcg8nF4Vdu239Lf8QqugvlMmPmdjKEBSXGJNOFAE00bH8h8TudzuArmH4Iz0tgX0sbFsWhkpNHpzExf/EtURUrmJBocyHKUvvb/4BtcRTjYnjFEDKZcErFhQv4GhnreAaCq/ssUV15wTKvUaRzdaJ4NjTFRlESq4N0LBL1bEQQdOflzcRefjMNVDyRnWBQljpTw09n4BIoSY86pfxpzf7IUJujdTizaj9lahsVegd7gwDvwEUM97yDqzZgsRRSUnoHRnLfP/VYViVCghWioKzUTJBAONFFc+QkQdaz47/m73NZir8bumszIIZ7O4KCg9HTsrnoUJcZHr1+JlPBn1pssRcw86eGsPquqgpwIoTeO78a/6YP/wTe0JmtZ7bRvUFJz6bi2T7P+vZsy4WGQNFp0Bhs6nQVVSaAocRQ5htGcz9SFP92v66yxf4SDbQz3ryDkayToayQa6siSXK1fcA/uohMPYw+PLCLBThrW3kU03I2U8COKJpx5szAYXShKjKGed6meehNltVfsch8jJXV1ekuqloam1nQwUVUlmWvg3UpgeEvq/xdATnmM9QY7FZM+l5qkOr6N65F0NP6ZjobHEXVm8kpOTXmta7E5ajCYXDSu+wn9na+M2q5y8uexOmoJ+XfwcbEnEQEBhKQH32KvxpFbPy6lLA2N3aGFUWnsM5IUpm3rbxjqfZdEbBhXwQIKy88ht+AEZDmSSnrbhH94U+qGlpxtMpoLsLumEAm0koh7MVkKMVmKU+9FyaJazhqs9iog+RBa/+6NhPw7MNsqEASRWLgHi6OamSc+NG6VjbZtjxIN9yCKBmLRAQLDW1HkyKh2emMONVO/SvOmX6aK9ImpXIbkcdLhSIKgxz5CBSiZbD2YSWJf+erFGWNDZ7AnZ6H01lT1ZxeizpgqyhbOFGeTpQiKHMdgys0okZjMBRjN+chSOJXImm1sTDvhZ3s92xoOtNLb9i8Gut9AivuwOmrILVyMq2ABVntl0thQ4ihyHFWJoygSqionX0ryHVUGQUAUTYg6E6JoRKe3YLaVaUm0B5BNH/4PvsH0/1wgt2gxeUUnJa+5zoSrYMF+5f0cq6iqSjjQgndgJd7B1ShyDFE0YraVUTPta9p39BChKhLhYDshXwORcBdyIowsBTOFKJNFKUMkYp5UYrSA1VGFxV4Fqkoi4UeK+4kE21BVeZ/ud0cyUiKYyfFLy5UrcjyZQ2cpQJHjBH3b8Xs24PdsJOTbgYqCgAiCQDw6SGntFVRM+uyYkrfJ6vHhZC5H6tXf+QoDKQPEYMpFEPSgqqiokHopcjwTkpgM0a3HkTuDgrIzMRh3P1g8mlBVmVikn0RsGFVVEAQdgqhPvgs69AY7BpNbM3D3E83Y0NhnpESQFa8kiz4Jgg6bsy5ZjTfmycy8mq1lONzTceRMRmdw4B/eRF/7fzAYnbgLF2O2lRKL9BOL9BGL9BIN92UMAIu9mvzSpeSXLE2FDz2N0z2Lulm3ICeCbFj+NVQlgcVeSSzci6gzoTc4qF/4k4yhMpIPXj4Xvd6OqDMi6kzk5M8jr3gJVkcVipJAkaMANK67F0WOMeuU3xENd+MbXE0s0kc8NowU96OqEuFAC7FIH073TOoX3I3e4EBVZZb/5wwgmVBqshRhMLmTXhNVSXoxpDCJuJdEzIuiJFLxs0Jy0C7oQdCBqiBJIRQ5gixFkKQQciKIKBqxu6Yk5Qxzp+HMnYbB5Nqv/6GiSHgHVjHY/SbegVUk4t792h8kY4ftOZNS0otTsbvqMVmKtJv1PiJLYbyDaxjuX8Fw/wri0X6qptxAed11h7trGhpZKHKcUKA55YVrIOTfQdjflFEVNJoLMjlher0NncGKqkIiNkQi7k/ljjlIxLxEw11ZuXUmawkl1ZdSUn3JUZd3EIv0E48OIcvpiaVI6ne9Gk/vu7vczmwtJRYdQFUSiDoLztxp2F1TEEUjKslnitHoorjqE3slWiBLETx9y3HkTt2lmqKqqsQifQS9WzPepqBvO4Kgo2Lipymvu3avr8ORRCTUyfbVdxIOtKRUIneNTm/FbCvHYivPvCdfFeOOSjje0YwNjX1GVSSGB1YSDXUTDraBqmAw52E0uTFZCrG7pmTcr/HYMI3r7sE7sIqSmsupnnJjlkdCVRUUJYGqxInHPPgG19LX/h+i4S5kKYyoM6PISd17UWdmxokPIktRvAMrkRJBLLYyEnEfnU1PUT7hGqqm3DCqv6vfvDarEJogGlh0zn9G9WPj+18DQWTmSQ/hG9pAT8tzhPw7Mts6cqdTWnMFgiCybfUPshJMg74GvAOrCfoa8A1+NCoRXdSZk8nXOlPmIZJFSsNfEPWpma5oZpXNOYmyuqspKD193/5he0BVFUL+JuLRAUTRiKgzIohGRNGYrD0i6BFEHaRmfJLJyQqKHE/NyMWQEiFCvsbkw8m7JSkQAJhtFcw59Y/abPJ+oCgJIsF2mjY+gKrIzDrlN4e7SxrHOVIiQGB4C37PRvyejQS9W5OGhSBitVdjz5mIzTkRW84kbM7ajCRrJNROONhOJNhOIubJ7M9oysdsK8NsK8NiK8NsTf5ttpYe8eOJpAchhKpIyHKEwPBmvINr8A+ty3rupEkWocylfOJ1mCxFKe9w2ktsIBRoJuDZhNlamqqTNOGwqqCln/cN6+7B7pzI9MW/OGx92V9kOcqG976KIkcorb0Cs7UsVXdLh6pKIzz4Eom4l0ioi2iwg0iok0iok0RsKLOvupnfxVUwny0rv48g6jEYXRiMOcnoBFNeVr2UZM2U41M+XjM2NA4JHY1/zii6JFUzHKncgASqksiKQR9JzbRvYDIXMNz/IQHv1ky1XnfxKej1NuTU7L8iR4mGupHlMFPm/xhX/rxR+wp4txENdaHTW/B7NtHV9BRO9wzMtnJURUaWQsSjQwR925i++JcociyjjuUuOoncwhPQ6a30tDxPwLuF2Ut+T8uWh4mF+6ic8gXMqRCwpFtaRJHj+Ic3IUuh1IA8mnRnSyEUKYrRnJ8sMGgrw2h0I+pHa/gnvSERvAOr2LHhfmQpxLzTnz5qCojFYx7atv2e/o6XyC1cRF7xKbiLk3rwGntH86Zf0dP6ApAMa5h/xl8Pc480jme8g2vY/OH/AMlQHGfuDJzumThyp2J1TkCnMyHLMXyDq/H0vo+nfzmJ2HAqlK0Ci70Sq70SS/plK0entxzms9o3/MObad38awLeLVnLrY4acvLmkJM3B7OtFJ3Ogk5vRae3IIjGI9rbm4h5CXi3EvRuy0weyYkgOr2N+gX3kJM363B3cZ8J+ZtZt+yLCKIOV/588ktOxV10EooSJxruIhLqShnBSSXNj3NZku+yHKFzx5MYjC6mL/4FvW3/pnPHE+M6dsXEz1A5+XMH9wSPQDRjQ2PcBLzbiEf6UwP8KLIcQZEiyKmwJ0HQY7FXYLGVoTe6EEVDKv7RgCAIRMN9JGJDRMM9SIkgomhIthGNBL1b6e/876hjmm3lxMK9GTfnx9J+FnR6S1JeVm9Bp7OgN9gpqb4Ei71ij+eSiPvpaX2eSLA9lcehz8i+Ot2zKK66kKHe99n20W07bSkiinoUJc7cpX9BRWHzh99OFQtMIogGTOZCTJZC9MYcDMYcdHprKpxKRUXJVCjeOWdDSoQz1c+N5jxUVSGamk1R5CgGk5uZJ/36qDE2IDmL1Nv6Dzx97+P3bMZgdFK/8N7jrur1vpKWbY6Fe2na+ACxSB/5pWcyYeb/jBmjraFxsAn5d9DV9AwDXa9RUn0pNdO+nhk4K3KMge438fS+j3fwIxQ5itlahrv4JNxFJ+PMnXrM1ClRVZWmjQ/Q1/5vbM46SmuvQKe3IYpGbDkTMZpyD3cXx42qKngHVjHQ9Rr+4c0Zr7TemIPDVY/DNZWc/Lk4XFOOif9fLNLPUM8yhnrfwe/ZxMhCu0BGrSupkqmmZPST+SwqKlZHDfUL7sFkzkeWIgz3r8gYZ0Hf9qyohDQ6vY2ZJz2M1TE6zPtYRzM2NMaFIsf48JULM2E/gqBLDfLNSQUjklK16ZoPYyKIOHNnkFu0mILSMzBZCjKrZCnMumVfRJZjyfAdRIxmN1ZHLVZHTepVfUBnxGU5SmB4S6ZidlqGV5ZjyIlgJiksEfcy2P0Ow/0rCAdbkOK+5PmLJgQxaUwZjW50Rgc6nRlB1KM32EnEPCTifqS4D1kKJ8PABAFSah8gYDC40BuSNS3SalCCqCMeHSYRG0pppJdhtpZgtBTiypuDzmBPhjYdwbNiuyIWHWT76jsI+ZuYPPeHmorSOGje/BA9YxSamzj7+7uVXtbQOJDEIv0MdL3GQNebhANNGIwu8kvPoLzu2oxanX94MzvW/5RIsANH7lTcRSfhLjoJi73yqLpfqapKIu5N5upFhwAVQdAnc0VSIaSKHEWSgjSs+V8AXAULmbrwp0fVeY6kdetv6Wp6OvNZp7dRWHEu7sLFSIkAIX8T+aVLsTnrMm1kOYqcCGXGAiOl7MeLqkioqIc1xDYWHcQ7sAq9wZ4J3ZMTQWLRAaS4H1Bx5E4dt1ywqkgk4r5kvmWq6rs9Z/K4xWyORTRjQ2PcBLzb2L7mTmLhXmae9GscuVNHtZHlGNFQF1IiiKomUBUppWQkkYgNMzywEu/AKlRFxlV4AmU1V+DMm7FfN5p4bJimjQ8Q9jcj6gxJJQ9bGe7ikymu/MSom3803Et387P0d/43o7Yh6szo9XakhD+TzOjKn8/UE+5noPMVdmz4GXqjA1f+AozmPHR6a0adSZFjxCID+D3rM/HHyeszjUTcz0Dnq/iG1hKPDiWLGsY8pIsFTpn3v9hdU/B7NhIJthMOthIJthEJdoIgUD7hWvJKT2f9u1/Mzu9I5XbojU5c+fPJKz6FnPw5R0VOhCzHaFh7F57e96mdcTMlVZ883F06opASAeKxYUAFVSUcaGX7mh9l1s848UFMlmKM5oKjdmCjcfSxddXtePreA6Bqyg2U1l6VSdSW5Sjt2/5Ad8tz2HMmUzfrFmzO2sPZ3X2mYe3dDPa8PTqfbg8YjLnMP/NvR8U9eCyi4R56Wv+RVHuM9BMJthEOtmWuQzLf0EJO3jxC/oZkwvuIAprJNukwMWuq7Wyq62/a7X1q4/Kv4/dsRKe3JXMdjC70O6ldWR015JWcij1n8kG/53n6ltO86UFikd6d1og4XFNwlyyhrPbKfTKsjme0on4a48Y3tI5YuI+cvNlY7JVjttHpTKMeMooiEfBsxD+0gbC/OXPz8vZ/gLf/AyB5I5t50sOIOmMyzCrux1UwD4PRBSTl6byDa9DprThcUwl4t9C29XeEg62pfIiPJWwduTPwDqzCN7iWvOIlGVe2IseQpBCtW3/DUM/bmK1lTF/0AIm4j3CgGUkKo9OZ6Wh4HEWJEQl1oCoJWrc9Sm7RYibPvSNLBUVVVeLRAcKBVjx9y0nEvFjsVdRO/wZ211Tatv2eruZnQFXJyZuNzTmB3MIT8A9vxDe4BlvOJEBgzdufToVI5WK1V+N0z6a48hPEogN07niSvvYXM9esuOpiHLlTiUV6CQfaiIV76Gv/N33t/wagvO66MZPjjyR0OhNT5v2Ils2/pnnjL4iGuqmacsNRpzBzsNj0wbeSUtE7oTPYKZ9wLU73zMPQq2OHkdXE05Wm4dguBLc/pAehaUND1Jkpqrgg83tNDs5+RSI2THX9lyitufyghtmE/M14B1aSiHmTgiTmPIymfIxmdyoB92MZaFVVU7VSrOMOaQoHmnG4plBaeyUmSxFGUx4IYnIGXpUzCcS6tNiH3npMDDzN1hJqpt6UtUxVJKLhHnQGGyCw/t0v4R9aR17pqalrnofeYE+pa0VGqG2FiUeH6G7+G0FfA3q9LSPVnUyCNyaNF52JkL+JvOIlOHKnkoh5ScS9WcIqKip9HS/R1fR0sr5W+TlUTvrsQbvm7dsfG8PQAFAIeLcQ8G4hxz0DR+60g3J8Dc3YOK7p3PEkbdsepbzuOionfz6lRLRrVFVhsPsthnreYXhgZVb8oqizYHdNxpU/H5uzlq2rbkWRo6xb9vmsfQiCjtzCRThyp9LX8TLRUCeQlAN05s3G71lPTv48cvLmEPRtZ7h/BaoSJzC8EYMpj/r5P856wGxZ+f2sGhXRcBedTU8xZd6d5BYuBJIFwTp3PAlKUu+8adMvEHUmZCmcdXMLDG+hcd1PiKRqbuj0Nqrrb6Sk5jJE0UBX0zN07niC8rrrKam5LKsfQV8jm1d8h3h0kG2r78BdfBJ1M7+dMaxGUlhxLk0bf0U8NoTRlE9v2z9S1ZHHHhh17niSikmfRxR3//853AiCjtrp38BsLaFlyyN4B1YwdeF9mCyFh7trhwVVVRjqeQf/8CacebOJx5JhdAZjLtMW3Y/JWqrlZxwgRhoV+2JgjDRWjnWCvkbWv/cldHorZbVXU1z9yUy+WCzSR/OmB/H0vY+rYAHTFv0ci638oPanv/NVGtfdgyiaMJrziEeHUJTYiBYCE2ffSmH5WQAMdL1G47p7QBCZtvC+XdbnUFUVVZWTClEmN4KgI6/4lIN6LkcDgqjPyoGcc+ofEUTDuBSVVFXF6qgm5N+BIseScu9yFEWJIY9QMASBosoLyC08Ydf7UiR8ng0M9bxNZ+Nf0OutlE24+kCcYgYpEWSg6zUEnZFknHM6kEdA1JkRdaaUgWmlu+V5jD3vJGtnGZ0YDM7U3znoDQ4MRieizqJ5nvcRLYzqOKWr+Vlat/x63CoKvqH1tGz5NSFfAwaTm0TMg9VRQ0nN5TjdM7DYKjI/QlVVadv2OyLBdnILT8BsLU0VhTMy2PMOA52vEvQ1kFeyhLLaK1DkOJ1NT+Ef2oDB7EZOhJhz6mOpZGqZ4f5VNG34GQZjLrOW/CbLKNqy4nsMD6wY0VORmSc/PCpRWVES+D0bGex+k772F6mc9HnaG/5Ifsnp2HImkogPZ8IFyuuux+aowWQtyhwr6N3O+ve+THndtbv0MsQifTSu+yn2nElU1d+wW+NNVVVWvX4ZomhCb7ATDXen3NciTvdMDEZXSpq3C1DRGxzkFp5AfunpuAoWHNFu/Xh0iM0rvkM01MWMk36NPWfi4e7SYaG7+Vlatvx6zHWzl/xxn0NSdp65H/k5vSzd7ngZQO/Mrq7J8YwkhenveJnh/g/xDqxizql/wuqozmqzbtkXiUeHqJ1+M3klpx70gVUk1Mm6ZTeQV3wydTO/i6gzZuRm47Eh4tEhWjY/hCgamHXKbwHo73yNxnV3J4vWAfUL7ibkb8bv2UDI14gsRzKqiKBiNOUTjyXFPiomfoaKSZ/VBoxHELFIPxveT9bXWnDW8wf0f9O27VE6dzyJ0z2DgvJzMFuKUwUlA0ipwpJSwp/Mw0wEkOI+pESARMKfKVg8EkHQozc60RucmG2lVNd/GesuIkKOBw5aGNVA56sYzfnYciZqBb2OYsLBNlpTg6B4zEN/56s4cqdhtpaO+T8d6HqDhrU/xuacRE7eHHxDaymvuz7lDRnt9hQEger6L4157NKaSymtuRRFkbJCbOy5U9m0/GaCvu2AQCzSh9GchyDocBctQj//Tja+/zV6Wl6gtPbyzHb1C+8hMLwFT99yPH3LiQTb2Lj867gLF1M5+XNYHTXJPiF8rB4FuApPYLDnLQZ73mSw500AjOZ8isrPxVUwf9QsT1I5S8VVsOuZGpOliOmLH9jl+p2x2MqQ5RgWWxm5RYux2MrJLViYVdRPlsIEvFvxD21IGmpdr6M3OJm68CeYrCXEwn3EIn1Y7JVHRDx1LDLAhve/ihT3MnH295HiPob7V5CTP++4CqmS5RgFZWchSWHikX58nvUZLx6QJaQwHtKDZ0EUUBV11PKx2qb/Ph4H2vt7zqJel3Wdj4VrONy3nJbN/4fZWkpZ7dVYHKMV/kzWEkSdmbySUw7q8z0R99Hd/Cw9rS9gNLmpnfGtTKKtIAipIoEWelv/STjQTHHVxXQ3P0d/58uE/E0YTLno9HaioQ62rPweos6MI3cahRXnojfYU7WE9AiigZC/CU/f+8TCPXQ0Po7OYKes9oqDdm4ae0dv+7+JR/txF52MqsQRdnr2tm3/I/0dL+N0zyC3YCE5+XORpQiRYDuRUDvx2DAWaymWVIV6vd7GUO+7RENdpOfSBdFIUcV5e4zeSJM2eKVEIJkUnghkDBMpHiCRSD7X1i+7gYpJnya/5DTMttIDfm2OZJIh5/3jbr9Xno2dKa29kpqpX9m7Hh4GZDnKcN8HDHS/id+zAaMpP1lcyFZGUcUFWOwH1018pKGqKgNdr+If2oB/eDORYCuQ1PmfNOdW9AYHIX9T6rWDoHcbOr2NaYt+zrp3PpdJth6LhWf/Y8zQofEQjw7RtPEBiqs+mQmBGknj+vsY7l/B/NOf3qUCRCTUiafvA3pbXyAa7sFozsdgdBIJdaHI0Yx8YTjQiigaqJz8BXR6K7FIH4HhzXj6lqM3OKib9T3yik8acc0UVr1+OUZTLnpDDr6hNUye+yPyS5fu07nuC6qqEg60sO2j28coKCVSUv1JKid/Ab3Bfsj6tDPhQBtbVt4ySsHMYMyloPwsCsvPzlI+ORaJxzyseu1SdHorU+b/mJy8uQiCQMjfTFfT0wx0v0Fh+blMnHXLqG13lXuws5GRJu3ZGM9gOL2/vR0479wnQRRQpNE1dHa37khGkeOZSY6kbLcBVZWJRweIRQaIRwdAEHDmTt8r9ZojjWi4h9VvXguo6Ax2LLYKbM46qqfelAnnS4c0JSt7X0JRxXkH9HwTcT9dTU9nassUV32SsglXj5l70df+H3ZsuB+nexYGYw5Dvcuw2Cuprv8yOXmzWfHKJzLy6VMX/nT3ITupe2dP6/MUlp+t5UjtBWa7jWgwtOeG+4gix+jc8RSdO57EZC2mpPoScvLmYHXU0NX0V9q2/ZaCsjOJBDtTv9OP74M6vQ2DKTdLSj8dLmUw5SHFfZnls07+LXbX5APWb1mO0rrlN8n8S1XCYq8kt3ARuYWLcLqzBXIURcqUFJBT74ocR2+wpxLoc44a6WEpEaSr6a8M9bxDJNQNyAdejUpvzEWKD2eWF1d9ggkz/me/O38gUFWVWKQvVfV0A4HhjcSjHvQGB/HYEIocxZ4zBVfhQqRU9ciwvwlJCuFw1RMKNKcqLJtQ5ChFFRdQVHlBJpEsEfOgqjImS+G4reMjBUWOZ+pijEUi7icwvIXOHU8QGN6UWW6yFGF1TsDmqE39gKajyDGCvgY2Lv/6qP0Igo6pJ/wMUDP5HEZzASZLEXqDY79nysKBVtYu+zx6vQ1XwQm4ixbhKliIwTj6S67IcQZ73iIS6kKKezGlKrbacyaxZcX3kOUI0xbeh96Y/SCNhrpp2fIwnr73qZpyA2UTrsn0u7ftRZo2/izTtnbaNyipuXS/zmlf8Hs2EfRuw2RNFhw0mQvo73qN9u1/RFWlVFGtaqz2KiyOKmzOCQc97nokyQd7E/6hDXQ2PZ0crO1ETt5c6hfche4YzFlQ5BgfvPyxfK09ZwoVkz6N1VFDPDpId/OzePreZ97pT4+Zz5IetKfZmxn2nQ2PvQ0nSm+/vx6RkZ6BI9UrkM5Ba9v++0z9gVEIIiZzQTI+Pe4FBKyOWpzuGZnX0ZSTFAl2Ego0Jev8BDsY7Hk7eX+wVyKKyfj1cKAlKzQ1r2Qpk+fecUA8Hc2bHqSn9XnK666ntPby3U5MSYkAbdv+QG/bPyivux6/Zz1+z0YKy8+hdvo36e94OTNZVlp7FYXlZ+93/zQOH+FAG61bH8E7uBpVSaA35iDFfZRP/DRVk5O5n4mYF79nA3qjE4u9EoMxF0EQMknv4WA78egguQULMNtKMx4KWQofNKU/SQrjG1jNcP+HDPevIB4bRKe3ojc4MobFeFTQ9AYn7qLFlE/81CF9Xu8tg91vZykpAgfe2CibcC0GYw4WeyWO3GljDvIOJeFAG90tzxIY3kIs0peRbLPYq1IPgWLkRBC90UFeyamj/oGyHKWz8S8EhreSkz8XVAVFiSWTiXeBIBowW0ux2Cqw2MrRm1ypQnTJgnTJ+g5lKT3vXqREEKujOpXTcHDVLaR4gEionUiwA4PJjatgAYmYhzVvfwpVVXG6p1M56XNZ8raKIuEbWktO3mxQVYb63sNocmNzTBg1EE+jqio71v90zIJ9e2J/835C/h0M9rzDcN+HhPyNgIAtZyKu/Hnk5M/F6Z45KgQqGu4hFhnA4ZqCqDOybtkXcOROZ8KMb415DFVVaG94jM7Gv1BYfg51s/5f5ibVuuU3dLc8iyDoMFlLMJrcGExJxRSLrSyTn7K3RqksR/ENrsGRO32ff1exyABDvcsIB5JSu+FAK1LCD0BO/lzK6z6FK3/OPu17b1FVlfXvfQkpEcBduCijIOMdWJlpUzP1a1khcccC7dsfo6Px8cznnPy5+AbXjGqnM9iZvugXOHJHz7SNNDSAfR60j9eTkW6nM+hRFRU5kTgo4VeHI6RLURKEAy0EvQ2Eg60ICIg6E4JowNP3PiFfA7lFJ1JRdx06vTUp6a0kkjLUeht6gx2jKTf5/Q114R/eSH/Hf/F71meOMWHG/1Bc9YlDel4HisHut+ht/3cysVeOImfeo8iJIABWxwRmL/n9ARmo9bb9i6aNDzB98a/GXa1684pbkBIBZp7066SEbfcbTF/8IDl5mnfiWESWYwSGN+EbXIPBmEtJzWVHTci+qqqE/DvwDqxElqOZcaFOb0Wns2SKFSerzRuQEwHiMS9S3Ess0k9v+4sk4sPMPuX3BzwsOj0JKIhGjMZcdAb7Pl1XRZFo2/Y7ErFhBFFPf8fLx26djeRg9176O1/BaMrHXXwyJksRFnslTve0fQ7jSSPLMWKRXuKRAWKRftIuOUEQM5WfI6EOIqFOpEQAWQqPmUw0ElFnwZ5Th9lWgdlajMlSgtmafKULze2JdE0HvTEHg8mFqiQYHljFcN+HeAc/ytSDSOPInU4s0ossRSivu56BrlcJB1pwF51M5eTPE/I10NH4Z6LhbibO/j4FZWfj96ynu/k5BFGHTmfBbCvFlb8Au2vSqMFzNNzL1lW3EQ40jT5f0Tgq3MqZN5tpC+87YEVwYpF+vAMfMTywEk/ve6iqRG7RiUxdcE/mevW0/YOupr+iKglEnZkc9yxCgRbiMQ/uwkUUlJ9FXvEpowzBli2P0N38DADzTnsKk7Uk8z+KR4cY7H6TaKSPRMxDPOYhHuknGunN+h4IgiEjB6jX29AbnZitpcl4Y50ZWQonk9MSAYLe7SRiQ4iiidzCEzCY3Nhy6igqP3ef3avpIla+wTV0NT9DyNfAhJnfobjywn3a396gKAk+eOksamd8a1TNjUiwg972Fwl6t5Ffehol1Rcf9P4cKkYKFhiMLlRVzpJ8THPSRW/t0hhNGxt78miMzOMY2X5fEsTHKxdrsJhJREZX0d1b9jWkazwkZV1fwDe0jnCgJTWrKGK2lSEIYkoxJ47FVkbl5Bt2OWhd9drlFFaeR9XkLxD0bqe94TEqJn6KwPBWWrY8BCSNxsLycwj5GrE56ygoP/uQ1A043CTiPjoa/0wi5kvK1JrzR8jV5mEyF4x5n1dVmQ3vfw0pEWTeaX8Z17Ea199HyL+DCTP+h43Lv56cAJr5nQN9Shoahx3vwEdsXvEdpsy/G3fRIgRBl5pE7kCSQqiKDCioqozekIMp9btL56KqqppUBpMiGIzOzDNGVVWaN/2K3rZ/ZI4lCHoMJhcGYy4GUy56gw1VkVGUOIoSR1UkDCY3Vkc1Vns1Vkd1Sujn4/CwY7qoXyzST2/bv+jc8QTVU79KSdUnD3sFx+Q/OI4shYiFe4iGezAYXZgsxegMVsL+ZoK+RkL+RqKhrmTNidSMM5DJI3AXnZiqzFqVeViFg230tv4L7+DqTG7FzlgdyVoPtpy6jMfFO7ia7uZnsTknUFhxHvaciaiqzEDXG7Rv/2NGc9pdfArB4a2ZL5giR7E5J2AwuZGlMOFAK7IUQm9w4syblfLSVKZCdSrwD29my4rvAlBedz1mWxlS3I/FXok9Z1KmCu3ekoh7iUc9KRekhNlWhtGUl/UQD3i3seG9L2dtV1R5EXUzv83G5TdnZh/L667HXXwyvqF1ePtX4htag85gx2B0EQ11YnfVUzvtaxmNbVmO8uHL52btV6e3MfPkRzAYc/ANrsVVuHCUbKmiSPS0/oPWLQ9hdUxIzRBGUpXGYyRjTZOSe4JowGhyoTc40RudmMyFFFaci3dgJd6B1UiJIOFAMxZ7JbXTv4Erf94+Xcc0I282E2Z8m+Kqi7LWH4xZ51WvX04iNowjdxq2nEnEI/0E/Y3Ewj3JuHglQXnd9VRN+eIBPe6RQCTYiaf/Azy9y/B7NoEgkpM3C3fRYvKKT8VsKx7Xfg6mJ2C8/3OTzQKAoqgHxNA4WAS82+hqeoahnnfQG+y4ixZjdU7EZC4iFu2hqPLCPUoNB4a3YLQUYjLnM9y/ErOtDIutDN/QBryDq7DnTMZddBLtDY/RteMpVFVKTmLkzSHoayARG8JiryKv+ORUvljuTg/0/Q8nPRJY9+6NhHwNGE35iHoz8ehglhS6IOix5UzEkTuNHPespOiG3oKqKiz/z+kA5BYuIidvDmUTrtrtsda/d1OyBpQq4xtcx7zTnzrsz3wNjYOB37OBTR9+G1VJoNPbEEVDKnxz9+gNDlRVQZYjmQlPs7WMikmfoaDsDBIxL6tevwyztYyaaV9LhYUOp2qgDBOPDSMnggiiIZW3ZkQUdcQiA0SCbZk+CIIOs60CR+5U3EUnYXfV89Hrlx54Y6Og/BzK667Hah+tYnGgUeQYHY1/IZpK/EmWivcSGN6MKBooqryAmmnfOGpv3JIUzhgm0XAPfs8GvAOrUOQoRnMhJkshomjAN7QOgykXd9GJ5OTNwWIrJ5Hwk4gNg6qQkz93r2OGFSXBUM+ylEEwkf7OVwkMb8FsK80oIqVn0xVFIujdinfgo0xF7LSMICQVnIymAqSE7+OkZUHM+sJPmvsDHK4pH1vdiRCSFEq9B5PviSDRUCcB33bCgRakMX5gOr0Vi60Ss60Eg9GNTm/OhLwVVVxAfulp2F316A02GtbexUDX60Ay8V1R4siJILacSRhMuQz3fYCqSkycfTvdzX8l5N/BzJMewZFbDyQ1wOMxD/HoIEF/I80bf0Fh+bl4+pYjJfwYjC7KJ36a4qqLsiz9dFLjiRe8kTVzraoKsUg/g91v0d/5CpFgK7OX/H63ydJt2/9AZ2Ny9m/aogewOWv32munqgqe3vfwDq7GN7iGSKgDk6WY+Wf8da/2sy/EIn14+j7EN7iakH8HJksxVkcNjtx6wsF2Ohv/fMyEQyhyHJ9nfTJut+9DouEuBNGAq2ABecWnkFdyCkbzaJGNsZK+k8uzjQCdwYCcSMb9GixmpFh8VG7GkZobMZID3U9VVRjuX0lX81/xD63DbC2ltPZKCivORacz4x34iK0f/QBFjlA5+QtUTPwUA91vgqpQUHYmqqrQ2/Yv3EUnYrIUsunD/8FgzGHy3DuyjuPpW8G2j26jeupNlNZcRsjfRF/HS+QWnIAzbyY6nRlVkfAOrqG/8xX8ng0kYsMjklaT6I055BYuwl24GFfBgsM2eacqEiF/Ez7PBmKRXhQ5TuWkz445OaSqCkFfA97+lQiinuKqT+IbXEPDuntQlTgTZn6HwvJzk3K10SHisUEiwXYCw5sJDG8hGu5GFI24ChbgLjqJaLibWKQX78BqEvFhCsvPoWLSZzO1PnZmxSsXYcuZRG7BQlq3PoIomjCYXNTN/O4ua2xo7D2781oe7CTxsXAWuJESEmGvf8+NjyFkOUrQuw2/Z1My8dxWkcpPcQIigqgDBKS4j3h0MPmKDYGgS4X0WxFFAwNdr+Hpex+LvZKy2qvo73wVv2c9rvz5TFv0sz11I4tEzEs42Eo4kHz5BlcTCXUgiCZUJXbgjY00Or2dnLw5lE+8blQ9gwOBqspsXvHdZEVm5wT0RheioEfUmcgtXEReyZLDqrizvzSu+wmCaKRu5rezlityDO/gWvye9cRjnlS8+4kUlp99RM3kSIlQMows2E4k2E4skpRfjUc96I0OZClKJNiSjFPU20jEhtHpLUhSaLfhZoJoRN2l0pWILWciZmsJUtw3wir34cybxdSFPx2Vq6HIcQa636JrxxMk4j4UJZ6My055GSomfY7SmsvpaPgTXc3PMP+Mv42ZLxENdbP6rWsBKKw4n5Lqi+lpfYH+jv9SVHlh5v8oy1E2Lf8mUsLPvNOfGvMsVEWiveFPdO54gmmLfr5bj0VaT34kRlM+uUWLyCs+hZy8OXv8XiTrg3wsQ+xwTaWq/ks43TMPqaEuSWG6djyFd3B1UlFEVSirvZqq+i8dNRMGiiKlFIr6U9/51Hu4B//wJhQ5islSmFQkKVqEK38uemNyMKkq6qhcjPRyyA6FGlk7Y1fhU+k2aZUqUadDVZX9UoIy2SzEQpHMZ1Gvy+zPYElWcD5SPBuKHGOg63W6mp8lEmzF7qqnqPICCsvPRRT1NG96ELO1lILyMxnuX0HQ25BUPTLns/7dGzCa85m68F6i4R7WvP1ppi68F1f+PMKBFozm/FEKTOuW3YDR7KZ2+rcwW8fplVJVZCmYNXsY8jXi6VtOONCMIOhx5s3CXbgYd9GJu5XO7Gz6K21bf4PJUpyUnk9NSJkshThyp+1xwkmWYwS9W/F7NqREVDahyJGsNnUzv0s42EY01I2qyskcRlUi5GtESvjR6W2Ze2hB6ZkMdL2GqspMmnMb7qITd3nsSKgTT+97DPW+R2B4MyDgzJuJu3Ax8dgQ3c3PodObWXjWC5lwkJH0tP6Ttu2PoioyroL5GQ/pzJNG11PSODgcLZMZGtkEvNvo2P4YwwMr0Olt5OTNprDiPPKKT97vfYeDbXj7P6Jly/8deGNj+uL/o7ftn3gHVyHFfQDk5M1Jdr5kCTqdeb9PAJIqFOvevTGjEGJ1TKC46kIKy89Fp7cckGMcTvo7X0EQ9BSUnXG4u3LAiUeHaN36CIPdbyeVkRy15JcuRZFjySJMgg5BEBEEkUTcTyzcjcM9E5OlgO2rk7OJroIFVE25Ab3BgdFcQDw6wGDPO3Q1PY0iRbDYK0jEk3Hwjtxp5OTNxVUwB5OlmEQsmdeSiPsAgYB3C52Nf6Gg7GzM1hKC3m0EvFuREn6M5kJUNYGUCFJceSG1028e85xUVaa94XHchYszno9YdJCP3riS2mlfp6T6EmQ5SsPau/EOrGLGiQ9iz5k05r7aG/5ER8OfKKw4n7qZ395tEvmODT+nr/3fmc96g4Oc/HmEfA1Ew93o9DZqpn2Noorzdvs/CQdaGe5fgXdgFT7PelQlkZR/dlRitiYloPOKTj5oEtCqIrF11W34POtxF52IM28WOXmzsdqrDsrxDgSJmJf+rlcZ6HyFkL+Fsaq76w3OZP6VtQinezru4hOx5dRmlBnVlGGdzgdKf04bFJAc0KdJL08P8kcaHLuqszGS9LZpw0bU6ZBiu5ap3l/0JmMmofxQIUlhepqfo6f1BRJxL7mFiymbcDVO9ww2vPdlXIULqZr8BVq3/g6ztXjMxO2mjb9AlqNMmv19IGm4IOh2WwdGUSSUlFyld2AV+aWn79cEUDTcw3D/h3j6luMbWoeqJLDYq8gvWUrZhKtGqbSNnDSwOSeiKHFikX4UOYLe4GDaCT/LkvWUEkH8nk0p42IDQd/2TGjGSCWtzR9+9+Nq3YKIXm/D4Zqa9Gyn7tMWWwW5hQuxu6aSiHnoaHicga7XyC87k6opX8Roco/7vOPRITx9yxnqfRff4JqU50ekasoNlNdds8vtwsF21r79GYoqLyAa6ibkb2TGiQ9hdRy595BDyd7mUulNxoN6bziasLqcx7z3JBYdxGh0HXB53UOSsxGNDOAbWEV/16v4h9ah01vJLzmNworzcORO2+/ZyqR6TRcBzyY8/R8y1LsMvd5GzbSvU1B21lEzG3q84R/ezPaP7sgKtdoVgmjAYqsgHGjG6qhG1FkIerdiNOUz57Q/j4qvlhIhelpfSCXJO1DlBD7PeoLe7Yw1GBzJ7CV/wOacAKT15pMPtrIJ1yCKRoqrP7lXD82gr5EN730Zq3MC5ROupX37H4hF+pg094e7nTUIB9vYuuo2EjEPs5f8YZehA0O977Pto9uomvIl8opPIejbRsPauzIVcMOBFrqbn6G/8xXqF9yLu2jRuPoty1H8Q+vxDSWLzEXD3URCnaiqTOWkz1BaexU6fSrZ7ADNZDVvepCetn8wbeF9R0XYw1Dv+zSu/wmKHMNddFLSg6TXJxXIzPmYbaWp2W/bmMncI0kbGGN5HNKGxs7iBIIooMgyqqKiM+gzs4ojvSBSLJ4VWgUfex90Ol1m/+m2siQflMFF2uBIHyfZv4MzCxoOtrPto9uJhXsprDiXoooLadr4c8omXEN+6VK6m58lt+hELLayPe5LVWVikX7i0UGc7hnj7kN/56s0bfwFC8782wGrP5GWzvT0L2ew6w0Mplwmz7tz1Kz99jV34un7gLlLH0dvdLF15fcJ+rYhS2FMliLmn/EM3sHVtG55hJC/iaSwiRune2bqNQObszZrgiOc8k4nQ74UCsrOOGRRA1IihHdgVco7M3WX7cKBVrav+V/i0UFmL/k9Pa3/oKvpKQrKzmTSnNsPSV+PRA6UWMOxws6eWY2DzyFPEI+GuunvfIX+zv9minnllZyalA7U25LhNAYbBmMO7qKT9ulmFg330r79Dwx0vYYzbzb5Jael4mz3rhLvkUAk2IkgiMd0xUlFjhOL9hOL9CMnginJNzOizpySgDNjMLoQRT0B7zbatv6WeHSQkprLKKw4b1RI1O5IzuJtIBHzZpRR0rkNqiojCLqsWOR4bJhVr11Cac0V1Ez76j6fY9C7nYZ1dxMJtmPLmcSkObftdrZeVVWC3i10t/ydwe43mX/G33YZ/uAf3szG97+K2VaBqkrEwn1Y7BVMmnM79pyJyeP7Gtn4/lfJyZ/H1IU/2efzkOUYHQ2P09X8V6z2KoqrLs7IOZttZdhddbsN59kdvqF1bPrgm7gKFlK/4O6s/JYjjaSk36N0Nz+Du+hk6mZ9B7MteX9RVQVBEDPvI0OiBFEcZUwkjYXktdEZDBmjAz42LtLGRnpbUa9DFAXklFdDp9MRj0ZRJDmzD53BgJj2WiQkRFFAEESklFytnEigSHJm3yarhUTKCFBk+aAW3DuYoRaevuU0rL0bozmPKfPvwmqvRFUkWrY8QlHlBfskE9ne8Cf62l5kwVnPjat90NeI0ZyPIIgYjKPzb0aiyPF98nxEQ91sWvFtctwzmZjyvEBykmDlK5/AaM6nfuFPEEUTq9+8GrurnsLyc7DYyjGYcmlYezeCIFJSfSnOvJmYrWVH7cScqqr0tb9Iy+aHMFlLmDz3h/S1/5uetn9SXHkhFZM+u1cTRBoaGgeWw6ZGpaoKq167NFP8yO6agiyFM0VVZCmMTm+jpPoSSmouG7Nq6KiTkcLJ0JfhLYQDLQx2vwmomSTkkupLqZ560xE9iNmZzSu+i05nYcr8/z3cXTluScS8GEyu/d6PLMfwDnxEbuEJiKKe3rZ/ISWC5BYuwmIrIxYdJB7pxze0joGu14iGuzGa8impuZTyumt3u++u5r8RC/ci6syYbaUUlJ2ZTERVVXrb/kXLloewOmqYPPeOcc3mynKMRHSIeHwYq71y1Mxs0JdMhA94t5KOBdLprSw696VxS6OOOqYUoWnjzxnoep2Js289IgtvhYPtDPUsY7D7dSLBDqrqv0xpzeXojcZRngtBFBBEEVEUsjwLUlzKtE17HRRZxmy3YrJaUBSJSHCQsL+PaHgAq70as60IAL1BnzlGPBrNGDUAckIi6NvOcP+HKflmE3qDFXfxEkzmo6eY3L6iqgqdO56gfftjuItOZOLsW9HpzcQi/bv0Co6XRNyPIkcwWYrG1b694XE6Gh5n4VnP7/Le0dX8N1q3PAyQko2sSUpHOmqSL3v1Lp+hUiJAT+s/6Wp6mpy82ZTWXknY35Sp9i2IOras/D6qkmD+Gc+w8YObCfka0OltmRpTycKq9+PKn7v3F+QIIhH307ThZwz1LsPpnoHBmEvQt51YpI+qKV/abcjVkc6+hO2Y7TZEvY6w1z9qBj8dErW3ng6L046UkDTviMY+c9CMjer6mwh4t1FWe3lGJnRnmjY+QG/bv7A6aphz6mNZ6+LRIbqa/0Zv2z9BVSmqvJDKyZ/L8nTIUgTv4GqG+1cQGN5EONAKqOj0NmzOuoycqbvoZLyDH6HIURy505i++JdHjcERCXUicGx7No5HfEMb2PTBNxAE/SgVGp3eRl7JEgrKziInb9Z+VaFPJ4sWV11MzdSvjGsGdedic3pjDtX1X6aw/NxRM5/pwkRbVtxCbuHCzAzrvs5ct23/A107nmbBmc8dEANvf0jE/YQDzSRiw4QDrakiiC2IOjO5hYson3g1Tvc0BEEc5XkYaUwYLGYUSUZOJLLin0W9DlGnQ6fXoaRyMDy9H7F15e1ZcteCoCO/7HRKqi7B6qjB0/c+A52v4RtamyqaOh1B1OPpfZdYpA+9wZFM0JWjJOJebM6JzF7y6CG+evvH3n5/JCnMjnX3MtS7jIpJn6Vi4qcRBJHOpr/S1fQ08057ap/VnGQpnAohakMULbiLF+/x+aEqEkFfYyZvaywGut6gYe2PM5/1xhz0BgfRUDfpUE+TpSilW1+DqDenCnC2Ewm1ZyoNpw0IQdAlk7UBs62caKib0prLqJn2VVRVxTe0joBnIyZrcbLYrL18v+tMHQk0rL2bga7XEARdSiY8D3fxSTjdM3EXnXjQC+QeCdjcOYQ8vszfiiQT8ScLLVqcyTFT+nOanQ0Ok82CLMnoU57RWCiihV9pjGJfn+0HzdhIU1h+DkWVFxGL9iMKBiyOSizWskzySSLuB1XJDCxkKULQ14gsBZESQYK+Bnpakq7rKfPvJq/4JFRFYvua/8XT/wGqksBsqyAnbxYO11QcuVOx2CsRBJGOxicY6HodvcGeuhHpMBhdTJz9/aPG2NA49vD0fcj2NT9KJlTaq7E5anHkTsVkLUopxxTtV0KpokjIUpBYpJ/1795IbuEipi68d9zbr1t2A7IUomba1zCY3HQ3P8dg9+s43TOonf7NTD6Lqkh0NT9De8OfMFuKmbrwp/ttFHc3P0vLll/jdM+ibtYt4/LCHAjCwXYCnk2Eg21Egm2E/M3Eo/2Z9Tq9DXfRYvJLT0vWTTGMLXAhpnIgpFgcvcmYCUfSm4wYTMYxZwd1huS9yDe0gY3v3QyCjrySk3Hk1mNz1BH0NdLT8nei4e5MzRFH7nRyCxclJaCHNyNLEdzFJ5FXcio57pmZ++vqt65PzmAv/GkyQd1mQYpL+5WonfbSHMxie3tDONDCttV3EIsMMGnObVl5UFIigG9oA3nFJ+3VPlVVobvl7/S0PJcJ902jNzhwF59Ced21WGy7F0oIDG9luP9DCsvPGfO3kVTBe4Pu5r8RDrYx77SnMJhyiQTbCQdaRrxaUeQoFnsVeqMTT+/7JA0SEXfxSZRUX0xO3lxUJY5/eBP9Hf9F1JmYMONb+zVZcTQQiwzgG1pHLNKDokiUTbh6jzVSjkUcebkEhobH9IZYXc6MYIROpyMajpCIRLE47aOMkDS7W6ehsbccNGNDb8zFaq/A79kwqo0tZxKzTnp4zGz35k2/oqf1hcxnUWcmr+RUSmsuy6j2pI2Nod5l6A0OKiZ9jpLqS47aeNPd0dfxMqJoPCbVqI5HBrrfpGHtXdgctYT8O3AVLMA7sAoEEYdrKkUV55FXvAS9cc8JpYm4n62rbk1WPlZlUFVUlMyMZxqjKX/cseYAHQ1/pqPxcQymPMrrriO/9FRC/maaN/6CSKgDe85k8kpOZajnHYK+RsomXEXFpM/uVe7M7vANrqVxw30kYsOpweMpB2S/Y6GqMp2NT9Le+CdQVczWEiz2SqyOGmzOOmzOCZishYiiGVH38f1q5AB7LEWodGiUsyCXWCiKqNcRj0TRGwzEo9Gk/KyioshyZpuhnmW0bv0t0XBXVh+nLvwp+eUnMtDxLpFQJ3nFp2SFBY30lhgs5kwuBiQT2Js3/QIpEaBm6tconXDxQc3FONQkk7AfwGwtZvK8O7Haq5DiAZq3PER1/ZfHFX67M4mYl4Z1SbW4worzycmbhdVejcVeSTTcTV/7S/S0/h1XwQKmnXD/bvfV1/Eyfe3/YfriX+x2gistRDF14X3kFi5MLeulv+NlLPYKcvLmZHLJOnc8Sdu2R3EXnUzt9K+PO7RL4/hidzPQJXWVSXU4WWagLVnzKre0kGgwPMrAOB4UmDQOPtFIP6vfuHJcxsZe6WBNmn0rroJ5BLxb0eksmCwFKHIcv2cj29fcycrXLsHuqsfpnk5h+bmZ5FcpEcDuqqd+wd3o9fYxZ3gFUc+U+f9LyN9Md/MztGx+EP/QOlwFC7A6qjBZipESQaRUvQRH7lQiwXa8g6vxezbiHViF1VHL7CW/P+JdrL7Btej0Fs3YOMpRVRVP3/s0bfg5+SWnEo96ycmfS/38u2jd9ihGcz7egVXs2HA/TRsfwOmehatgAa6C+dicdaMMaUWOse2j24gE2ymf+ClEQZeUn0RA1FsQEOjvfJXcosUUlp21V32tmPRp8ktPp237ozRv+hXNm3+FK38elVO+CKrKQPcbtDc8htlaysyTHtqtOsy+kJM/hzlL/sDmFbfQ0/rCQTU2mjf9H71t/6J84vWU1127W0nuXT2404P39HpBFDNJ30GPH6PFhC5lXKTzK8ZSe8orWYKn/8NRxgaCDKpIUfXpJCJJwyV93xqp7ASja1vYcyZiz5mMp+99fENrR1WDP1qR5Rgtm/+PvvYXKSg/hwnTv5mROpekICHfduLRgX0yNvo6/oN3YBVTF/6U3MITMstj0UH6O1+hr+MlAPSG3Sd+AxRVnIe76MQ9etLTSeRSIinT7R34iK2rbgNByFTbttiryMmbg901GVFnwe9Zj6g7+uXdNQ4Ou/M49jZ3JpXsRkw8DHf3j9lWMzQ09gZFjtPT+gI6vQWDKZd41MNg95sEvNvGvY8DliAeGN6Kd2AVAe8W/J4NKHIMp3sWOr2VwPAmHO4Z1M//8ZjbjkV/56t0Nv6FSKiLMWVNUwniOoMdOfGx1X7iBW8dk94QjcNPIu4jGupCliPIiRC9bf/CO/gRroIFTJrzQ1a/eTXldddSXndd1nbRcC+tWx9BSgQIDG9BkaNUTbkxZXRMyIREhAOtrH3nc+gMNnILFqLI8YzAgiSFiYY6Mvs0mHLJKz6V/NLTcLpn7JWBHY8NM9SzjIGu1wgMb6J84qeomvwFZDmGKBoOqrHetu1R+jpeZsEZfzvgmt9pNi5PzgzvjSxmerA/so7FzkX4VEXNqouhN+hRZHmPcovhYDuNa+8mFuknER9O7dvArJN/u1sVpfTsoyLHQdfHUM9HDHSsSE5WGKxU13+ZoqpzUeXsW/jOkrhHOqoi0d/5Kh2Nj5OIDVM7/WYKK87P3MeleIBopDf1W9n772Ys0k/L5ocY6l3GvNOewmwrJRLqpKvpr/R3voIoGimpvoSiygvGlXQe8jez6YNvMmHGt8gvPW3X56WqfPDy2RhNbnLy56HTmelpfR6juYDpi35B0Lcd39BafINriYa70Olt5BYuYsLMbx+XIUMa+8bI4psaGgeDkeUCABBEXPnzcBedRPOmXx56Nao0khSmv/0/+D0bUZQ4BpObykmfQdRZ6Gt/EYutgnjMkyzstYuiPOnwBUWOEQl1Eg31YTA5M7NFvsG1CDojuQULCPoa2LLiexjN+cw/42/jfiBpVTE1xoMsx+jc8QTdzc9mZiQBzNZSqqd+FZOlmO2rf0A03E1p7ZVUT7kRQdSjqgqevvdp2/Z7IsE2HLnTKK+7nh3rf5pSbEsycrY1Euygt/3fBL3bUhXYk1XYdXorer0No6UAq72SwZ53GOx+m3i0H6M5n9zCRVTX3zTq9ylLEZo3P0hO3lzyS0/LKlymqiodjY/T0fDn/fZmjPe3FBjeyoblX03KDk+9aZ+PtytC/mY2vHcTpROuomry53fbdmShPBgtSQtkZGYTsXimgN2+DubjMQ+rXrs089lVsACztQyTpQCjuRCTpQCzvQSz1Uko0Mhw31pikW30ta5OVW62kJM/E1fhPMrrLkMQLEd1YS5VVRjqeYe27X8kGuogr+Q0Kid/Dqu9MrVeRRAEhvtXsHXVbUxf/Iu9qokRi/TT1fQ0ve0votNZKJtwDUWV59G65RH6O1/DYMyhtPYKiqs+sVdy7IqSIDC8BVVVcOXP2W3b4f6VePqW4/dsIBxoAVQE0cAJ5/w7y+MWj3nQG5y7LSyooaGhcbiIBDto2vgAvqG1TJpzOwVlZx4+6dvdoaoqy/8zehbIYMoDVaG4+mIqJ30mu3Mj5DYVOc7wwCoScQ96gx1RtNC65TeEA82AAKg43TOZvvgXR3zyXOP6+9DprdRO+9rh7orGOOhqfpa2rb+htPYqCspOTw7+dRb0RgeCoGP5f87MUp8qrDgfg9HFQNfrxKP95OTPo7D8HNq2PUo8OjBq/+V111M15Yt73S9VVQgMb2bj8q8DUFZ7NVX1N2YZ27HoIB+9fnnmc0HZ2eSVnIqrYD46nQlVkVj//lcQEJl1ym/2ug8jGe8gvKv5WVq3/Jr80jOZMOObB6SImCzH6Gv7N51NT2Iwupl58q93GT4liGIy0VuSszwZI2thwMeJ4YosZ8nRCoK4y/PcndGlqgr9Hf9FUYeIhYcJB7qJRfqJRfuzvLNpDKZcnO6ZuArnkFcyD71Ygs5oyjr+wZowOVj7VVWVoG87Qz3LGOpdRjTUSW7hIionfyFTPwaS3rdtq25jwsxvY7aWEI96MNvGVzMi6Gugu/lvDHa/hU5vpbT2KkpqLiXo3Urj2p+gKDEqJ3+eworz9zknKRYdpKPhcSonf27ctR7iMQ9DPe8i6owUVZy3T8fV0NDQOFyoqsrWVd8n6N3G9BMfxGjKO/KMDYCOxj/jHVgNQCSUrFqaxmguZMGZfxtzO1VV2b76DoZ6l5E2LADsrnpKay5HkoI4cqZgd03e574dSnra/olONFFYce7h7orGLohHh+hseoposJOgvxGD0cWcU/84ZttIqJN41IPRnEd/53/pbPwLeoOD/NLTyC87i7B/BwNdb4CqkEj4sdqrcLpngiCSX3LqLgv7jRfv4Gq2rrodRY5gtpbiLjoJV8F8nO6Z6PQWEnEfW1bcQtC3PbONqDPjdM/A4ZqKp+89dAYHMxb/cr/6sTcMdL1O08ZfoDc4mDT3Bzh3IaW9JxRFoqfl73Q1/5VE3EdB2VlUTf7CLq/pyHApIMvQSFfCBkYlh4+1nz2FLoxM8k6TW1o4Zhy1JIWJRweIRwaQpQi2nDpMluJjIiRUVWV8Qxvw9L7LUO+7xKMD6A1O3MUnUVRx/pjeCu/gWob7llNWd+24czT8no20bf8D/qF1mCzFlNZcRmHF+egNtqRR/sE3cbpnMnHW/9vvYrC+wbU0bXyAmSc/csgqbmtoaIzNjCWz2Lhs/eHuxnFBPDbMxve/Siw6wNQFP2Hziu8cecbGSFRVIehrIDi8BVtOHXbX1DFdyIm4j6aNv2So5y0mzfkB+aVLScS8RMM9OHKnHvHJ4BpHF6qqMtD1Gs2bH0QQdDhzp2M0F+AuWpyVWLrL7RUJ//AWHK4piDojrVt+Q1fzXzGY8kjEhgCwOeuYveT3AISDbXQ3P4fR5Kas7lpUOU7b9j8w1PsuoGK1V2GxV2KxVyYroxucqbyojTjdsygoOxOTpQBVVQkMb6Kv42W8A6uIRwcQRAOO3GnkuGdhsVciJYL0tDxHJJX74cidRiTYgZTwM+2En+EqmH/QrutYRMM9NKy9i4B3KzX1X6G09vI9b7QTw/0r2LLye7iLTqZ66k27lNVN178YmdANZBkM453NT+9rb0KYjte46miom4Z19xAY3oTRXEhe8SnkFZ+czDM6gCFDUiLI6jevwWQporzuevKKT87a/4b3vkIi4WfOkj/ulwT1SGKRfga6XqO09kpNdl1DQ+Og07bt9wx2v5USnVCZdcqjmK3FB+VY6TG6b3A13oGPCAfbMJryMFkKMRhd9HX8h7IJ19LV9NSBV6M6kAiCiMM1BYdryi7bJOI+1i27AUWOMmnuDykoPR0AozkvIxl4NJLUeBf3e3ZN48CiKBKN6+5hsPtNCsrOpGba1zM5QuNFEPXk5M3MfI5GegBIxIYwmvIprb2CopR6UDw2zKYPvkUi5gGS1bqtzlp62/5BYcV5GM0FRILt+D0b6Ot4KSN/K+rM2HMm09HwGG3bHiWv5FTK667F6Z6B0z0DVVWJhNrxDqzGO7CKntYXsgrKpbE5JzLjxIeQEgEMxt3fKA4GZmsJMxb/ipatj9Cy5dfYXZP3KiYfICdvTqqGiWlMQyOTlyGkc8CyVaZGMt6wIUWS92g47Kxnf7QaGjtXK94TaYNN1OvwD21j0/JvoDe5mLbo5+TkzR23p0ZKBImGu7E5J45rm+6W51DkGPUL78Vkzh+13l18Cu3bf08s2r/HOhrjJRLqoLvlefKKl2CxVxyQfWpoaBxfqKqKlPATDfeAqmB31Y95z+vvfI3OHU9QWHE+w33LEUTjAS2Sm4h7iYa6CQdbGO5fhW9wDVLCj6gzk5M3m6LKC0jEvMQiffiHN2NzTiC/dCldTU+Na/9HVDbayBwNVVFo3fpb4rEh5p/xF0zmw1NtW0oEicc8maTFA0Hj+vvQG5xMmXfHAdunxv6hqjKN6+5hqOcdJs+9Y7cqM3vD5Dk/IFR3HaqSwOacmDWrqtdbMRhzSMQ86I05FJSdmck3cuXPz5JGVlUFKREgEfNishaj05mQEkEGut6gu/kZ1r97A3klpzF5zm0Ioh6rvQqrvYrSmmRCshQPEAl1Egl1EAl1EvRuxZGbvKkdDkMjjSDqqam/ieDwVhrX/YTpi3+xVzUGBFGXrLY8Rs6DqE95MhQlqWcnH7pideMpnHWkeTvG6k/a0BBEMSOrudu8lNRyRZIJ+RqR5QgLlj6LwZizV+ca9G5j84rvMPOkh/coXJCI++hufpbi6ovHNDQASmoupXPHE/R3vrpH4YDd4fdswtP3PtX1X8KVP495pz91wGrRaGhoHPuoikRP6z/wedYTC3cTDfcgS+HM+omzb6Ww/OzM55C/mZ7W5+nvfIWCsrMoKDuT/o6XmDTnB7uVdR9XX1QV39Aaupr+mqwNBoCI3TWZ4upP4sqfjyN36i49t1IiNO5jHRHGRvrhpSrKCIUYEXvOBAa6RDa8dzOzl/x+r2eZ94dIsDMZztLzFgDTFj2AK39uZr2iSKmKsM2YbeXYcyaPe9auZupXEcQjO4n9eEJVVXZs+DmD3W8zee4PyS9desD2LYj6TOHKnRF1Jmae/Aj+ofWYrMUZb53JWkLQuy3L2BAEEYMxJ+s3oDfYKan+JMWVF9Df9Ro7NtzPildXJhWsdGZ0Bjt1M7+DzTkBvdGBw1iPI7f+gJ3bgUIQ9UycfSsbP7iZNW99ipKay0dIwiZ/U47cqWPKkg50vU440EzdzG+P2F/KizFicHskqM7tPJg/kgwNSPZn5yT/9Ofk/Tm5bLzXMl1dOxYaQifuXV6Dq2A+s5f8Hpuzbo9tI6FOZCmEqsoZBaudUZWkjLTFun+TVrFIH76hdchSOPU70wwNDQ2N8REOtNC47l6CvkZc+XNx5E4jv+wszJZizLZSupr+Ssvm/yMnbw4hfyPdLc/hG1yDwZRHac3l6A12Gtfeg8M1lfxUpM++oMhxBnveobv5b4T8jdicddTN+h42Zx0WRwU6cf+MmLE4QowNAfhY416KBwiHWnG4pzBpzi1sX303A52vUlx98W5jYw/UTGFfx8vsWP/TrGW6Ebrn4WA769/9Eor8cXiBxVZBfunp5OTPwe6q3+1DyOqoIRruyjywNA4v3oFV9He8RN2s7x1QQ2M86HTmUbkgDtc0vIOrdjlw2hlB1FNUcR5mSzEB71ZkOYqcCNHT+ndC/iZszgm73V5VVWLhnszg8HBgsZcz97S/0LXjKbqb/4aiZOdDCIKe4uqLqZj4qYzBpchx2rf/EXfxKThGJJgfCYbFWBxpxsVYpMPM0qQND73JiCPPha9/6OOk+p2uc3rSSG8yosgy5tTAPhru2qXE+e4QRCPhYPsevcrO3GnUTPs6LZv/j0TMS83Ur4wKsw0HWgE1U7yvoPysUaqFqqoSj/YT8G4jFulHkSPIUpRYuAdJClI//y7yS08nv/Q0LVdQQ0Nj3KiKRFfzM7Q3/AmztYSZJ/16zIm/2uk3s/adz7L6rWtRlQR2Vz1V9V8mHhmgt+1fKHKUvJKlVE354m7HBoocS4ps9H+AqiqU1l6B1V5JPOahp/UF+tpeJBEfxpU/n2kn/Iyc/HkHXYzksCWI74r2hsfoaHg8a5nB5CYR82A0F1Iz7UZszjrC/nZikX7cRScesEGSLIXpbn6O9oak6pDe4GTO0j9lpA1VVSUW6cU7uJqmDT+jvO56SmuvJOjdxkDX63j63keWQghCcjbbnvoyyYkgshzDYq/AnjMZKRGgt/UflNZeSUHZGQS82wj5dlBUed4RL9t7LLJx+c0oSpyZJz18RKj/+AbXsunDb1G/4B7cRSfu0z6kRJAVr1zIpDk/2G2l+njMw4719zHc/yG1079JSfXF+9jrA4eiSEkp4dStSVES9Lb9KxkbKojkFZ2MoiSIRwfwezYx59Q/YnVUA1rtnP1hd/kZzgI3wWFflsE0MkxtLFRV4YOXz6F66pcprb5sr/vTtv2PeHrf26UK3M70d75Ky5Zfo8hxJs25NatKvapI9HW8zED3G/iH1pNfegaF5WcRDfcQDfcQCbYT9G7LFF0UdWZ0egs6nQUEA9FQG3qDi6opXzhmKrZraGgcfMKB1pQ3o4GyCVdROemziLuZjPYOrmGw6w0Kys/G79lAZ+MTCDoDxZUXUVJ9CbIcQRQMGM15KHKc3vZ/4x34iJLqi5ESATx9y/EOrkaRo5itpShKnHh0iLySpQS9W0nEfRRVnEtx1cX7NAk0kr2ps3FEeDZGUlB++ihjI7dwIRWTr6N186NsX33XxysEHS1bHmLCjG9TOuHiMWcORw4+djUQkaQwva0v0NX8N+REiJLqy+ht+wdlE65Cr7cx3L+C/s7/Mty/ElkKpfZlwOqoxmB0klu4kNzChaiqTDjQgt+zCb9nI8P9KxAEfaouiIG+tvV0xv8CgM7goK/jJaLhbgRBR1/HyxSUn4VO97GxEQl10b79MWqnf2Ov4urTRcmOhpnUI4GQfwflddcfEYYGJI1rUTQy1PPOPhsbOr0NozmfoG/7Lo2NRNzPpg++iRT3k1e8hOZND2KyFO7zMQ8USVW6j29NOixUTLyeosoL6Gz8M4HhrYh6M3qDndrpN2cMDThyvRpHA7FQZJfeYf+AJ+uzzpDyMIsKMPZ9VRBEzNZSIoGO3R5X1OuQExJ+z0as9spM0mN53XV7JRhQWH42ihylaeMDJOK+7L6IeoqrLqK46iIGu9+mYe1dDHa/DohAuu8CBlMeNmctTvesTNielAjQueNp4tE+AsObNWNDQ+MYRlVVZCmMIOoRReOocYGqqhnRlkRsOClYZMrDnjOZvJJTstom4j7Wv3sjgmhgxkn/Ny6Jd1f+XFQlwY719xGL9FJSczkVEz+N3mDDP7yZje9/9ePGgogg6LDYytm2+oeAgCN3GhUTP4276EQs9ipUJZGU5N/xFIocY+5pj2My75/c/r5wxBkbFmsVJ134NvHoEL6hdVjsxTjc0xAEHfUL7iIcaEKWY5jMxegMJj74z3nEor1J6U/vRiLBbtzFJ2AwuRCEpKa+KgrI8RjxqG9MFauWzQ/R3/ESzrzZGQ32/s7/0t38HG3b/wCqgtVRQ9mEq7A5J2Fz1mI0549ypQuCDpuzDpuzbswZ4qSbfoCgbztB73aCvgY6dzwFqBRVXoQiRZATQTz9H1BUcQE6nZlIsI14tB9RZ6Rt26OUVF2CzVW1W0NCMzLGj6qqyHIEVUkgSxF0esth7Y/fs5Gtq27FbCulcvIX9nk/giCQkz8P78AqEnHfqHwnRY6z7aMfkIh5mXnSw5htJWxffSfbVt9B/fy7xiXze6gxmnKpnX7z4e7GMc2e7h3pRPG0fPDuPBuQlFf2Dn40KiTQ4rQjiMnihMN922nd+jDDfR9iNBfhyK2nYuKnsTlryS1YMK5+q6qCb2g9LZsfoqDsbIoqLthl2/zSpThyp7Fjw/0EhjdlkjP1BgdGkxspEaSr+a9ZogMGUx4zTnwwWR9HQ0PjqEaR4wx0vU403EU8Nkwi5iERG07+HR/OKD8Kgh6d3oreYE/maOltxGMeoqEOzNYyrI5qwoFWPL3voygJFhW/hCJHkRJ+YpEBYpE+dHobifgwfe0v7tHYkBIBmjb+isHu18nJm0P9grszk2lSIkjrloexOqqpmfo14tFBZDlKXskSDMYc/EMbsDpqRilUCTojxVWfoKjifGQljj4Vun+oowCOuDCqXTHWhVFVhQ9fPhercwKyFCYSbMusc7pn4XDVE/BuQae3Mdz/AQCLznsFvcGSKd4FSTfX+mVfQZJCLDzreQxGF93NzxEOtmHLqcPhmorNWXdQZr7TSirdLX8H1FTtg3bmLP0Lev3HSToh/w62r/kxU+b9CKujBkWRxqxLorF3qKrMh/+9AEWOAsnQuZppX6ew/KxD3pd4dIjVb16DzuBgzql/3G9BhMHut9i+5k4gmVM0ae4PsNqr8fS9T3fL3wn6tjN90QOZ2WNFjrNtzY/wDqxiyrw7D7uHY2cyA909DHA19g5VVeht/QeSFEJvsKCoEomoD1f+vKzaK+nrP1a+wljGhyCKeHo/YMvK71G/4B5yCxdn3UOlRIiOxj/T0/IcRkshFRM/TWfjX4hF+lLtsw3eXT0cG9fdy1Dfe8iJIHZXPTMW/3K3YQppPnrjKvQGB9X1X8bumpJVnC85uxkCQaS/47/Yc+o0Q0ND4xhguH8lzZt+RTTcg8lSgMHkxmDKxWjMxWDKTX425qCqMrIURpZCSIkQspR8CaKRgrKzyMmblbkXtm37PZ07nkAQ9MkQ4BHo9DZMliJy8mZTO/0bu+yXb2gdjet+gpQIUjv9ZgrKzsrcL8PBdratuo14zEP9gp9kyesfTvYmjOqoMTYg6bpXVSUz+ybqdbRs+g2B4S0YzflJ/eH+D+lrfxFB0CHLESy2SsKBFkAhv/RMJs+9Hfj4wRn0NtK6+bcMD6ykrPYqyiZ+CsNhOMeRRociRzCY8nDkTkWnMyXzOAQdos6C0ZhDftmZNK67h8rJn8OVP++Q9/VYIx7zEAm0EYsOMND1GiF/E/NPf3pcA5YDiarKNG38JX3t/8aeM4W6Wd8ZlxrPrvenZhTTOpueJhJoQ9SZkBJ+HLnTqZj0mVEzx4qSoGHNj/H0LWfyvB+RV3zy/p7WAUNnMGTCfEYqJmnsO6qq0rTxAfra/4PB6ESWoyhyDFApr7uOqik3jNpGEEV0Bj0Gk5HEiMKGqqJm/i+ZUE5FYu1bX0ip9lVQUHo6ipIgEm7DP7QJRY5RMfF6yidejagzEQl289Eb11E15XOUT7huj/2PRfr56I0rKaq8iPzS03DmThv377Z580P0tDwHQEH5eUycdcuYE0qKHD9ghQA1NI41zHYb0eD4JVAPF7FIHy2bf81Q7zJy8uZQO/2b485Z2JMXIBLsYLDnbfR6GzqDA4PRidFcgMlSmDWJsTOSFCYa6mSw+y26mv6K0z2TibO/n1WoLxxoZcP7X8Vozqd+/t1Y7AemTtCB4Jg1NvaGRNyLLEUwW0to2fIwg91vM/+MZxAEgUioE0/fcga6Xifka0i5x+wkYh5UVcJir2Tqgnsx20qzan+kZ/UO5EBn5xhpKRHC71mPb2g9YX8TipJISTomrexYpD/lvqukpPpibbbtABMJdrLm7U9TM+2rlNbsfVLrgcDv2UTTxp8Tiw4w6+Tf7rIq9t4gyzE6Gv4EQGHFuVjtu77JKopEw9qkwTF14X248ufs9/EPBAZL0tOXiEQPc0+OHToan6B9+++pm/U9iqsuYLDrbbat+RE6nZmiyosQBB1WRxWF5edkbTfWfVFVlVFej6THQ8U7sIa+9pcZ7H4HvcGBLWdCKtz0k5htxSTiAYa630FR4oQDHfR3vMT8M/6K3rD7B1jae7fgrOczQh7p/o01OAj5mxnsfhOLvYKCsrMZ7v+Qrau+jyAamH3K77A6agj6GtDpbVhsZTSsvZt4dIjpix/Yh6urcTTxsey+oIUiH0MoSoLu5r/R0fgXdHobNVO/Qn7p6Yc1R7O37UXaG/5AIpYUpBAEPZWTP0fZhKtHiQT1d75K47qkZzgnbzaFFedgMLrG3O+hrt10VCeIHygMRheqIrN9zf8y2P02RZXnIwgCOzb+nL62fyOIBnLy5iAIehRFIq9gDhZ7CR3bnyISbKev4yWqpnwR+DjpVE1XBhuDfY1/2/mLoTfYcBeduMsQlnSCUHHVRTjdM5Pu/kQQvdGx18fWGI3FXk5RxXm0b/8jeoODWKSPaLgboykPp3sGjtyp6A0H91o73dOZceKDrH/vJrZ9dDszT/7Nfuv563Qmquu/NK62oqhn0pzb2brqVrauupXpi3+BwzVlv45/INCMjAOLqsr0tD5PWd1l1My4iog/SOvW34KqIIoGPL3vEo8OYTDljjI2Rt7rsu+LMqI+mSsniAICyQenu3gheaWLEAQyD/lQoIvA8Db6O1+lY/ufUZQYAIvO+zf9HS/9f/bOOjqO62zjv6FlEjNasmSZMQ5jA02ZuU2Z0jZNuc2XJikzp01TZuamTZqkISdmBtmymKWVtEwD3x+zuxZbsmVbSf2ckxN5d+bOndk7996XnoeOI9+ncdPHgZl/++DoAWyO0pMaGoah07zrDvx9j5gikGqEWKSH4srnABLevLVZGvKOI/ciyXYa19+BqkbOayI9w5AxKsaPEdlqQbFaSERj6Kq26AQ3z+PUMDa0g9YDXycW7aG05iVU1L/+nDvM1WSI/o4/o1h8VC97J3ZnOXZXxYwRkJzCTZRUv5hw4Ajth+/GMFTK66ZGfeczZs/F+D6nxobd45qT0u50mI1xKR7tM7mEO/+BKFmpXPoGZMXFwa0fZGxoO9VNb6O40tTs2P6fl6BYc0nEhhnsuh/Z4qG64R2U1Dz/BEnJHHC2csg9OcsprHg2rQe+SmjsELLiIjC8i9WX3jOrBskzGQtd6FS17K2MDGzh2J7PICsebI4SRuNP0d3yc0DA4a4ht+giCiuux+48MyFNWXGzdO0n2Pf42wn695z1gm1RVGhcfyf7t7ybI9s/wYZrfrdo2LrOY24YH32Y7v0I+PeSSoyQV3Q10bEgAJe84DeE/GPIigs1FWb3IzfNe+yZc/KJVFdDNxAlCV1LIabZ9kIjzex97F3p4myRgrKrGer5Dw53FZLkpmbFu2jZ80VyijZRVDV9/ZSuJRkdeBL3JMaq6e61u+UX+PsepW71hykou4be1t/RceQeuo/9FDCFVjPK9Y0b7iQW7sIwdNzeRuzuqjlr3pzH4sf48ZFZO9R0OqAgiNg9dlKJ5Hlj42mMZNxP26FvM9z7EJ7c1TSsv2OcUOy5QzhwlMPbP46mxWhcf8ec0uAVi4/aFTdjGBpb/vmsGZ2d8xmv52Jsn1Nj41QNDQBRMukSx0PT4rTu/yqD3Q8gK06Kq56HrifpPPYTMAxyCtex/MLbySm8CgwBQ9dZtvHTdBz5AYahUbf6Q+SXXI5scY2LZiy+QtS6VR/Ak7Oc9sPfzQq2iKJCKjFGMuHPirj9r2gOLPQ9KhYv664wNyGZiJFhGMSjPQRH9hMc2Udf+5/obvk5uUUXU7vyFqy2/AXtA5CdVFLJsQVvey4wDI1EbOikooDnMT1sLme2rsFit+L0uuhv7T4r76QoS1gdJrOaoRsIokAqkcxuqgBTQwKRga77cOc0ARALqllD4+DWD6JpMUqqX3jK/cgsalr6nnVVw+5x0Xboe1hsBay48GvZYsyhngeIhtrpbfsdpbUvY3RwG0d3fQ6Hqy5LQ5tKjhEaPYxi8TAy8CTxWD+NtZ+a8foZDPc+TE7RRRSWX5uliiyufhG+/LUolhx6Wn9tpiiUX4ck2XB56wGoWPo6UskAyfggFmsewnlSjmcUxr+LmXcjlkph97iQZIlUIplNnf5fWU+fzjAMjf72v9DR/ANEUaF+zUcpKLt20TgKOo/8AEl2sOrib2O1z51+Nhn3Ewt3gqGjWHNOqw/nKmr3tJ051UQSXU8x0PVPRgeeIpUYIR7rR00GqF1xMy5fHUM9D9PX9lfK619CzYo3oVh86Gn1W13VcOR4sbk24clbmfW4ZfKOtUU8qQiCSFHljeQUXcTBp24hEjgGwGD3v+ls/iGbrv0TkuyY1oNzHnPD5LQ0QRDMcKfTTLOqXfE+/L0P037kHnb/93V489bizmnCk7cGt6/ptCe3ZNxP887bsTpKyCm88LTaOlUYhobFlkvAv5s9j76J0poXU1hx/XnhyTQyNSSyIqOm1CmF6/FwJFs4GQ9HpmhVTMZCLgKGbpCMJRBEgeoVtfj7RvDm5xANRYiFo6iJJO6cZdQsfzttB79Dcc1m7PY1SLKZYtC8607CY4exOcoIjR2coGVyulBTKloqisvbgCW9cI4OPpX9fmRgG0M9DxEeO4wgyPS1/ZGa5e9C0+Ls3/Iec9FNo7T25XPyWKqpENGBVsKBY7h9jURD7aTiw1nhv65jP8VqN4syQ6OHQFBw++oJjR5i35Z3Y7HmkV9yBTXL38XY0A50PUVu0bl5L8/jzGO8I9TuseMqLWCoo/cc9ug8TobQ2BGO7/8KkcBRiiqfS1XjW+alT3amkUqOMTa8g5rlN8/L0AiO7OfAk+/DMMy1weY4PRHrzBojKcpZJVp5Whobybgff/+j9Bz/NYnYAIIgZX8IgNYD3wTAai+ksuF1VK94M7KsZL0UmRSsZNzMA5YU8zFoKRVJkTF0A9lqQde0CV4NM5qyeFhwLNYcCsqvp7P5B3S3/Iq8kivw5q1BlKZqRZw3NBYWkmSlsOJ6coouoq/9jwRH9tPd8gu0I9/H7qqksPw6LLYCRMmKKFqRFSeKJQeLPR9Jss3YrmFo9Hf8jY4j30cUFZZv/tI5mzAVi5c1l/2IwPBO+tr/RMu+L9Lf+Xdql9+My7v0f9rLK4hi1rhQExNzwJduWEbLnqOIkpT1lk5W57a5nAiiMGFTM9nQOJU0U1GWaNi4jO6jPSTjcTRVo7u5i1QiiWyR0VSNVCJCKhFCVty4cxsA2PvIx/HmN3Dhc35LNBCmoPQqbM5i4tE+WvZ+CYennPzSzTMqjM8HqVgcUbRk1bpDo4c5svN2fPkbMIDA8HZyiy6msOLZDHb9k4GufyJIAuFAC4nYACsv+paphyOoOD0NZorWSYw0h2cJsuzCniZGqFj6ugnfL7/gC9m/O5t/xNjwdlZdfDdO71Jql78Xm6M4a4wE/LsZG9px3thYQAx2348kO8krvhjDMDD01KJhAIsFw6eVhXEeZxZqKkzHkXvp7/gLTk8tqy7+Nu45iOedbfj7HsXAIK/k8nmd19H8A+yuaupXfwjZ4p3AVAWn7kg+23vZp81uQddV/H2P0N/xZ4Ij+yd8ZxgaVnsRuUUX48lbjaZGsNqL8RWsM42FhIqe0tM/yAnvo65pU34kNZE0c521zHXTVI6ShCAKWJ12ZKsFMVMAKQqkEimS6QJGXdNO2Tt5KoOmuPJGIoFjdB39EZ1Hf4g7ZzlOTx21y999Sn34X8JCWPaKxUPl0jcA5jgM+Pcw0Pl3Oo/+OCsMNOGaspNN1/55Qn2NpkYZG97F6OBTjA4+RTI+TFHlc6hqfOs598wIgoCvYAO+gg0ER/bTsu/L7HvinQiCjN1Vjt1VTUHZs8gtumjRhKrPJGSrBUEUScXi2einIArc8MoL+cfPHgfg6I7DwETjYfImPR6OZJ0ezlwvkZGJitdwammmuqpx+MkDEz5TE0lEWSIw3Errvq8xOrQVAIstn9LaVyIrHtRUkNBoO/7uFqzOAmpWv5x4KIqaTNB26A4Ob72dTdf/ApurEMPQScYSp+XAyC+9kpZ9X2RkYAvxaD+GnqKg/FlYbPkER/YSGj2I1VGCJDlQLF5GB7YjSjaWrv0Y3nyTgc/QdTDMRTMSbCEaasXqKMbhqkax+FBTIXpaf0vQv4/w2GEMQ+fYns+wbMNds/atYcOdbP3XDUTD7bhzllFS/fwJ31c2vJmyJa9kuPe/+Ao2zEpt+XTFmYiEG4aGrqdMsdpID31tv6di6U0oFg/+vkex2PLIK76YZHyYlr2fZ/nmLy3o9SdDsdsm1GtMRsWyGvrb+84TUyxSGIbBcO9DtB36Npoao7rpnZRWv3DROsGScT+y7JyXfpauJQn69+BwV+P01k9g+8u8o+N1jRazU/lpQX2biA2x48GXTvlctngpqrie/NIrcXoa5rzZOdUfRZSlbLqVJEsmg4XFjIBAmmc+bcDEgmFEWUKxWqZdmDM6H4rVgppUUawWDENHU7Wssm6GTnIm4yVzH4IokkoE09b9nymvfy1V81SfXuwD9WxgIZ+B6Z1LomtJND2BlgrTc/xXjAw8yaZr/5Idq4ZhsOvhVxOP9mJzlJJTdBEFZdcsCvan6aDrKYIjB4iF24mGOgiPHSYcaCa/9Eoa1t1+rrt3RpEpdp7LGCmsKWOwrecs9Ork0NQY3cd/Se/x3yApbtRUkIqlbyASOIq/7xG8+RsAncDwLsA0iJddcCubn/0eErEkihLl11++FF3VyC25iMaN70eSzbo2NV03N98NmWEY7H7kJrx5q7A7K+lovhddi1Ne92o8uasZ7n2IwZ4HyCu6hKKq5+DLW5vdRIiyhJoMMtz7BKODTxEc2U0yPjqh/bySK0gl/IRGD+Mr3IA3bz2GriJKFty+RuKxAXIKL0SWT0SBDV0llQpiseYSDXdisxfNqtmx48FX4MldxdK1H5vXvf+vIJUMEI/0ZOuBdjz4cgrKr6Oq4Y1EQ20077qDhvV3TKHhHuz+N4Pd/6Zx/V0E/HtwuKtmJeKIR/sAsnU9J0OGLU2UJURRmNVwdvg8SJJEyD867fdgrhuy1XLeKDnLCAeOsfexjA6QiGL1UtnwpjTDnDnHJOPDSJINSXFMSf9NJQMERw6QU3jBWRFIHhveycGnbmXNZT88aepnaPQQg933Mzr4JInYAACbrv3rOXc+TsYzjvpWkh1YbIUkE8Pkl1yJw12F01OHL38Dis15QlU4vTEfvwkXRAFJOeFFliQpaxBk2Foyno2TbSJ09UTUQk2Y3krZakFOi41lIMoSNpcz+7ecrhOR0tERNaUiioJpWAgiitWCpmnIioykKEiShG5Y0VUNNaVOa7Ac3PpBoqF27M4K1FSAivo3UF73Svo7/kpwZD+xSCd2Z+VJn+1k63g+eKYZKAt5L4IgIEhWRMmKjBts+SCIWO0FE4xiQRAoXfJy2g58E7uzYtFHpERRwZe/doL2Rl/HX2jd/1XKal+By9dwDnt3ZjHZ0Jht/M9kaJwOA9+pYLj3YdoOfZtUMkBZ7csprXkpIwNP4PI1kIqPIMoORFFm2cZPEw11EI/0MDL4JAeeuJNENETDxrdQVlvM2+94gCfu+y67H/0Jx2QrjRs/DJhzmppKIVstaCl1Tu+QYRgYhobDXcPo4FZqrrwZm7OUwa5/0d3yC+AXWGwFYGiMDW/H3/8IiiWH0tqXoFh8DHTdZ9ZVoOP0LqWw/EZ8BRtw+RpJRAdo2fcFwoFmU5xQEKlc+iZc3no6mn9IX/ufWLbx0+hqnH2Pvwtf/hqKKp+D01NLb/sf6TxyL2uv+AkO18nnzhUXfhWrvXjRpf2cTehagkR8CLuznFQywL7H30HtiveRU7gJf98jHD/wNS569gMIgkR10zuzmkEOdw1rL//xtG0Wll9HYfl1JGKDHNnxcVZd/G1wluPvfxy7swyHuwZdVxFFGcMwOPDk+/AVbCKv+BJ8BZtO6nTMsKXNJaodHQtidU5NSx4PQ9fPGxrnAE5PHasu/jbJuD9dD7GL1v1fRVdjuHNX0n3sZ4wMPGEeLIiU1ryEqsa3ZsfN7kfeQCoxSu2K954WCcZc4c5ZjiDIBP17ZjU21FSY/U++F4s1l9yii8gp3JxOj5/e8fF0oWl+WhgbsuJk4zW/nfY7w9BBF7G5HeiqZm7KDR1JsWDoBrqmTZgIJk8v44V8YP6bZ3USw8t4dd3MpiLj+RBEwTQ+gETUTKsQ0mkZAMlYAovdipo2hERZwqYoqGl2jEQkhq5pKDYLY0PbAfOFi/iPk0wMY7VfStOmz9J68Bvs/u9NVC17G+V1r5j1nk5ng/1MMjTOBjw5Kxjs+jepxBiK1Zf9vKTq+UiSjWN7Pks82jdnD91iQXHFjfQe/w17H387dmc5NSveM0WZ/JmAKdoNpzD+z4ShMZPRYxgGx/Z+HpujlJUXfTM7rooqn01o9DCDXfeha1Hq13wEEAmNHkRTI7h9TYRGDzLQ8SCFZc/H0A0kWSav4m0s2+Ri32NfomH9m3F4KtB1nXg4mk5JNaYQaxi6SnD0EAH/LgxDY6T/CaKhDjJ5qnZXNYahZ7WFBrsfYKjnAZyeOjy5K8gpvIBIoIWBrvvoOHIvYJBTcAF1q26lqPoK0CdG2h3uKnNzOuk5AJTVvpTiqudhteXj9NSRSgboOvZj7K5SnJ5aCsquwZO7as7vX+a4Q9s/RmTs6GnRQyt2G5IkPS2UmMfj8I7biEf7WHfFj5FlJ3nFl2FJM/PllVyWFp01n0n+PHPVrfZCNlz9Gyy2QjQtTvOuO1iy8v0k4sMc3XUX6678GYrFS+OGTxELd3Jo20dYe/mPZiUzyNROTf7/bFiIOqX/FQRHD5KKj5BXYhIvRIKtWO1FZyQjRhCECbUZhRXP5ujuT6VZOjUk2cmSVR9AVtxEg610t/yc0OghGtb9H2oqDJj7ru6WX50VY0OSbLhzmgj491BS86IZjxsb2o6hp1hx4den1GdMh6eDoQFPkzSqk2G8iBSQXfgWw2Z4uo3A+GJzQRSxe1xoqRSpRDIbhRkfBZEVOWuQ6KpGKpGkeddnGej4J+6cpYRGj7D2ip9mvXG6lqBl/1cY6X+CC677azbPbzoxo/M4e0gmRtn+wIuoXvZ2yutfeSIip+toapRt97+AyoY3UrbkFee6q/NGIj7M2OA2hnr/Q3BkPxuu+jUWW9657tb/PFoPfovBrvtYf9WvpoTgh3oe4ujuO9lw9W9RU2H2PPpGRMmGrpnOmcqlb5xSSK1pCXY/8lrcOfWsvvx2rLZiBFFC1zQ0TUNLqqQSSUQZWvZ8jf72f6OmgsiKB0FUUJMBCiquBz2FJDuoanyrWew9B3Qd/Rl9HX9mw1W/nDW96WTIeAIzc/NstVs2l/OkBkBv2x9pO/gNLrrxoSkK6vPF0y1aHBzZB4h4clec0etkU2JkO7qepL/9L5TUvHjCmI4Ej2dpujUtPiMRx/hnnMlMeLoZeYsF8WgfzbvupH71R3C4q2g/fA8j/Y+x7sqfAbDtgRdRVPFsqhrfjKbGUFPBrJ7NmYKmxQmPHcXmKMFqL8h+Hhw9SPPOT6JrcVQ1htWWh9NTz8jA43NKbTpdCKJI++F76W//M5uu/fOEuSI0epCAfw/RUDsB/x5kxcPay39wStc5myxT80mjOr2ZcZFAVzVzsUupJiWuOrXwezLGC16dSUzrcdT17GAwdJ3oWNCMWqhmFEZNJNE0M0qTsVp11UyzEmUJq9PO8gs/Qf26txMaPQLA2PCWrAdPlKwUll+LpoY5tudzjA5uRddTT6tF7JkIizWHkprn03n0xyTiA1lDQ5QlZIsLX+EFDPc9cq67eUqw2vIpqnw2NU3vxtBTJGL957pLphPiLL3nixX5pVeiqRFG+h+f8LmaCtPd8lNsjlJki5dI4CgAKzZ/mYtufJALrvs75fWvndKeJFlZsuJW/L1P8eAvr+VfP9lA844vYOgGdqcDV44HV66H3uN/oLvlDxRVPodVF3+HTdf+mY3X/I7KhpsorrqB+jUfpXbFe+dsaACU17+G1Zd857QMDTDnUpvLSSzWTuexuwkHj2J12ieMFUEUUew2FKuZGuUtmtlwdrhrKKy4bkK67qnidOboczHWgyMHOLTtwxi6evKDTwOCIGC1FyArLizWXCobbppiPGcMjd7W37Hv8bejadOnNmWesSibbHHnDY1Th2Lxoli82XeyquGNrL3iJ4BpIC6/4EsUpWsoBnvuZ+dDryYaajujfZIkG968VRMMDTAFkddc9n0MXQNDpemCL9Cw/nZkxcNw70NntE9gjjtf/nrUVJBwer4F0zl84Klb6W75JfFoHzkFm6hb/cFTukam3ne278/Vmvi0SKOaC6aLHkw3cUuKgmK1pDciAolIbEKu8WLwLI3PARVlKZtylUokcXhc2Fx2FKuCzfkODD1Fy57v03bguxi6SsXS16OrGt68tVQ2vInB7vsZ6rkfh3sJay//wTm/t/9lCKJIddPb8fdv4ejOz9C44U5kxX3C6BBl1FToXHfztKDrZkqhGaY+t3i6hJenw0LMQ5oW5/i+r2BzlJFXchmQpg3ve4SBrn+QiA2x6pLvAAaplMmGdWj7x9h4zR9mZVhquuil1K6+An/vfvY8chvJeD+efC/RkJlOlYj5ad1/D9VNr2DtVXcQD8eyGiP16952yqlkgiAQC3cxOriN4qrnnlIbGSSiMRTFQXjsOJWNPiRFwYgFka0KYMHuchLyj2bn4cCAf9p2gqOH6Gv/IxgGhpECRFr2fYloqJVVl3wbQZCQFHlGxqOFxNmc2wP+vYBAfumVZgH4ImKi8xVuAkAUZzdK3Xk+UokU0bHg2ejWSaHrqQkshU8HxKP9E9KkxjNBCYIwIVpQWPYsPDkrcLhrzno/MzAjrBJo5t+iqGC1F5219cqTsxxJcTE68GSWBCbg34OuxVl7+Y9PW8/oZHPAudz/PePcfhnLzaSlnZg+BGaNRyqRJBGJTbsAjC8cXwzIFKVnCuBTiSTJeAKH205JTTHrrv44l7zgu1jtuTg8+VlDSrHZqKh/Leuu+Cl5xZchiOe9vKeLTFRpPBnATJjuWRu6jijYqF/9YcKBZnY/8gaG+x5B1zRCY0cY7n2YivpXnYmun3HEo3207PsS+554J6JkR1Wfft7C+b4fcxkHp3r98c6PuRw/HXpafkU0dBxBlGg98HX2b3kv2//zEtoOfRvFmkfTBV/A4apisPOftB+6G4Ccgk0k40MzeqrtHlMF3eUrpu3gz4mF+6hadiMFpT5cXidqIs7BLZ9BlGRWX/ZBEtE4VoeN/s5fcHjHJ3C45dOKAIwMPnWi6PM0YOg6kphPfsl1WKzFKFaFo7s+x57/3oLFbiM4PELL3i9madY1LUEk2GKemy5wBwiPHiI0epCx4R0Mdj6MYreRX3IFFfVvQJTkCVorwIQ1SbaenYLyVGKMjiP3koybBtNA1320Hvgmc8ignha6luDAk7fQ1/5HbI6SdOHr4hH6dLiqKK19KYIgEA4cM+s6mfq+BAb8WS+w3eNakMjUfJH5DVKJMbY98ELGhnYAJgNnMjEzA9ZigSQ7GB3aBnMYSpLswOlZgmEYjA3vPPOdmwZdx36adehpaQND11NnbfwKokxOwUZGBrYAptHeeuAb2BxlWQ2g02t/8e7xnjGRjQwyxoKhG4iShJGu4xBEczBlmCgEUSQZ07LnTG5jscFkjDI9csl4nMhYCMVqwZXjwVd4Gc992w7sLhtBfwhBFBgbHMHqtJOMJbA5yxkd2kYs3PO0Kz5eTNBVjYQ6t2LB2caQL389ay//Ma0Hvk7zzttxepcSDR7H4a6moPTaherutMgsqKeb05mIDTI6uJXQ2CFCo4eJhTswC0F1dC1GT8uvKCi96vQ7fBYx3/d+oSMnM6Vczuf48cgtvgRNi5GMDxGP9iErLhrWfxRv3uYJKSgF5c+ir/1PxCJdDPWYBdo5BRfQdMHnp7QZC4ZR7Da6mztQkwKCaEFTPWz5+90Mdj3FUPcTJBMj+PKbGOz6F7nFz8Pf28faK19M884nSaVUU1zwFMdfRf3rslSnp4u+jr/QduAbKFYLJTXPprLxtehakuhYEE2LEYt0oqlRAIa6H6D98HfYcM3vEUUL2+5/Ho0b7qK09iWU1r4k22YqFsdXsIFEfJjj+75Jad3zsFpO0LZKiowkS2iqmfZrfqagaxo2l4NYMIxstSxoJCSVDNDX8WeKKm8EwNA1dD2BIAgYhkHrga9SWPHsKXTbmeJ+h6sSxerDMAwEQUCUrGx81u/TWiZhdj70SirqX0dp7VR6+nOBTM56IjbIvifeyZKV7yce6SEc2Mfqy76JmjB3xpnicMMwzolon5oKc2TH/1Gx9A043NWU1bwMp6cOgL72PzLU8+CMxDjnGqnkGKJkw+YoZvUl30O2uOd8bsC/h4NP3cryzV/Bl7/uDPZyIsaGd9F19CeU172Wwe5/03b4bpo2fgaHu5qx4Z3Z8X2mkV96DUd2fJzD2z/OyMATuHNWULf6Qwty7enWhMVSq/uMMzbGP1htXJRCyBodYrYwVxCFp12qRcbo0NOLVTKWQLbIxMNRRvrMe7HYbFjsVpKxBEH/AdRUGFFUOLj1gxSWXYsndyUuX+O88qXPY2FhtRfSuOFT+PsfZaDz71QveweFFdcvqCDRTJR4p2NoGIZGb9sf6DzyA3QjhdO9BKu9iFikC7dvGcmEn2R8mLpVHzjla4ynrj7VCXIxpEPOhrNBV1hUswGXt/7kfZHs5JVeQfexn4Eg4vTUkVd6Bf6BR3C46ohHuomGO4iFO83iccHUuRgdfBJZ8bLlb28AwOoopKzueupWv4be1j9S07gSd34JD+/+Mq37+6lf/yGSUQM1qWY3hHMpZgyOHEh7RWvpbvk5/r7HcPmWkl96FQVlV57y71xQehVaKoo3dzPxcASbrTr7nSw7WHnRN7P/9uavZcWFX0OWHQBUNb6FWKQbX/76aduOh7uIBltJxWJ4ci1EAyEUqyPrBMswHNlcTmwuB+HRgJkm6/OkVenNdk51HA/1PsRg1300bfoCDncVG6/5A1I6r7646jmAmUevJgOExo5kVY2DowfRUmFyCi9A0+IcePI9NKz7JPmlVzDUcz/9HX9jxeavoKkxmnfeTvWyt1O36oMT2PXOJcaPJ6u9kKaNn8WbtwZVDTPQZSDJNiDOtn+/lsqlb0zf138Y7PonyzZ9dsai8tmg6ypaKpw2yDRCowfnFO0RRBlZcSHJNhSLZwIZQ0nNi8ktusg0hMLtWO1FSOmxtxjQvOtOJMnOso2fnrf2gy9/7YKkDM0XowNPYnUUU9lwE05PLc277iA81kxx1XM5+NStBEf24s1bc8b7kVt0Ee6cFYwN76J2xXsprnr+aRNLzIbFsg4+44yN6dIPMhv0E/+e+P+nKwxdRwfUJICaFh3TScbTauaqRn/n3xns+icAaipE59Efps82aePqV38Yu6viXHT/fx6CIJBfcvm8KSHnisxm1uq0o+uGqXqdSiFZRLqbf08iNoiqhtMpIaYxLsl2LNZ8LLY8LNZcFGsOaipCKuEnGfcz1Psg4bEjlNS8iMqlb0TX4ux65PXkFGzCm7+W9kPfoWb5zaeltzFZy2LyZ/Nt42Q42YYu8/1CCvXNZGiU1FUSGB5DVmSCQyMT+jZbP6f7bjpV8slIxAbYv+U9WeGogtKrESUbx/d9KZsqBGb+u91ViaQ4wdARBJGa5e+i4/D3qVvzRjZc9SK8eZWUVDZy36/u5oZXfRBDKmV4IIS3YCNHd74DV04TxZUvmiBUOhfD9+ieT1Nc+VycnlpKql5AYcWN9Lf/CQwDXUux9f7ns+maP5iGumFMzBufhRZ4sPv+WfnrxyOjD5HBZKpMxW6bQLHuzV+LN61F03n4L7Tu/xobr/0Tsuxg77bbsbuqqKh/LfFwZEKBsjwplWe+4z4e7UfXE1isudgcJeh6whQ1m+EeFauPNZfek/33SP/jDPc+xPqrfoUk21l7xU9MzRPAaivEm7caUbIgCBJWRymKNXcC/ei5xuTx5CvYAIBi8VFR/zYSkRiCKJJXchk2pxnlt9oLcPkaEUUFTY0iiAoWu3PO0aVDWz+EbPHQuP6TBPz7OPjULay74ufYXeUM9z6MYvFlx8KEvqoxlqy6dVpFaastH6stn0RskN2P3JQ1+BLxYZLxYdy+RgxD48CTt1Ba8xLySi5DTYWIhbtx5yyb51Njglc/mRjBYs2d9fjqZW/PpqedCjKGxmysYQsNNRXEYs1DEEScaSeMpkbx5q3D4a6ls/kHrLjwG2c8uiEIAk2bPodhqCgW3xm91mLCghgbGWXd8VSe5xqLoQ9nA5kIjukpNSM4alLNRnJKa5/PYPe/kGUXhqFidZRhteURDjQTGj3I7kfeQHHV8ymve/V5qtJFjpk44U+WdpE5R7ZakOQkOx54F6HRQ1jtxciKC0GUSUQHSCaGESU7hqFh6FPbE0QFp7uWlRd9M0t1eWTv5xEFmdLal3LwqfcD0Hbwm6ipEJVL33Ba9zudgN6ZiFjM1F7GS2roOnnlxWdUEVxSFBweF9fcUMOv7nmS6FgST0EuwaERFLvNpMkWxCk6FhmYc+/s15ju2Q33PZw1NKz2IuKRHpIJP2VLXklB+bVEg63EIp0UVT4Xqz0PXU8Q8G9noPM/dBz5AQgivrzrGewpIJ6wIVuHOLz1q9htQZZffDNB/1FadpsRgmR82NQ+mmNExzAMEtE+Gtd9EqfXTC+xOUsBWLLyfYBZK6QoXlLJIIlYH/u3vI9lGz9FTuGFs24aNDVKX/ufUZZ6T2lzNhmzibp589awZNX7s1ERxZqL22dec6DzHwRHD1C3ykyjOFVmpNDoYVy+RnqO/4rRoW2sv/Lnp+SlrV72Niob3pT1tI5X9x5vQNkcxSxd89FT6uu5gpFdJzWqGt6cnU+9eWuyz2qo5yH8/Y+wbONn0dQIvW2/p3zJqyZkAcSjfRzf/xWWrLwVm6OYiqWvQ5LNAmlv3mpWXvRNFFtu1qBVrDl489cSC3fRvOuTLF37f9hdFRx86hZc3sa0zs30sNoLWbH5q7jSY7Sz+YdEgi2sufQeBEHC7qpCSpM5DHb9m44j97Dhmt/PK9rQ1/4XxoZ3sGzDXem0uFex7oqfIlt8tOz9AjZHCWVLXo4oWek4ci85BRuzRtzpoO3Q3cRC7TRd8PmzksKUTIxkDTtdM9c3UbIiCAI1Te/k4NYP4O97hPzSK85oP4BZCTjOBc5GJsApGxvj05NESQJpvBr1iWqhs8X3u1hwrtI3dFVDlCHjjNQSZl2K093Aigu/zEjfFkaHthMNHsfta6Cx7lV0HPkBodGD9Hf+nf7Ov1FS9QLK6l55Uq/GYkR+RQnDXQuTy71YkYwlpv38ZB44wzCIho4z1PMgg933Y+gp6td8NK0+H8LAoL/jr4z0P4aunTBmZIuPwvLrKKp4NhZbLpLsmrAgDPc9gr//URrW3Y4gyCjWXArKrqG39bd0Hf0xQf8+woFmfAUbKCh7FnnFl5zyvWfeqbmyzmW+O51UyfFzlzvXjb97bnS+4yNJc4FstXDxs9fxyJ+e4mffNKmPRVki5B/D7nGRStN5C+LMVZjm+z99atZsRYOlNS/F4aohlRwjv+RKJMU24XmmksM07/oh3S2/wJu3moB/P7oWw5PbSGXD68krvgKHpwxRkogEwvR2CFz43N+iWByM+SPseuhrxMJ+LLZcQiNHUewiNrfXzJXXDWSLPKNo2ujgVg5v/wjrr/rVjCkpNkcJ66/6hXmfgkjtivfSdujudHTmyyzb+Gkc7mr62v6IpLgoLL8WwzDTadZces9ZSSW1OUom1MrVNL0z+7dizcHQNQRBQE2FEUR53p7eSLCVfU+8g2UbP0NN0zspib7gtApexQVM5VxsGP9+TDfu7M4yPLkrEQQJQZDpPvZLrPYiwmNHsTpKqKh7JYrFh2HoqMkAOIonGHWCIOLJXZn997KNn0LPkC0IAi5fE4rViyCIprEyKWI2HcZHRcrrXjVho1q36tbs3yU1L8STtxrF4sHQVfra/0xh5bORZQfxaB+CIGO1F6BpcQ5t+wjlS15FTuEmLLZ87M5yDENDEGWKK5+LYWjoWoxYtIfw2CEq6l+LIMjZ2sKFQG7hZmLprIrgyF6O7v4UjRs+NaV2aCGga0mCI/upqDdT1VJJM+oryXaGeh9CQMTlbaT98HfJLbrwtOm1n244G3vWeYn6Xfy8B1Cs7gmMTaIooKeNC0mSsqE1TdWwu5wmvWw0hpbWwhAEMS2698yKPJxNIZXZML4mRcwIA6Y3o5qWoKfllwx0/YNkfISapncQCbYw3GduMjO0e7LioWrZWygsv47g6EGO7/sSTRd8Eastn65jPyUSbKVx/ScB2L/lvRSUXU1x1fMIB45xbM9naNzwKezOMnqO/4aAfw9Nmz4LwMGtHyKnYBOltS8hGu6keeftLF17G05PLX3tf8Lf/xgrNn8FMJVp3b5GyuteTSI2wKFtH6Fu9Ydx+xoZ6PwnA13/ZNXF3wKgeZd5vcqGm0gmRjn41PupXXEL3rxVDPU8SE/rb7KpAsf2fgHF4qV62dvSDCAvoOmCL6YFgIoX5UJ7Ovn9qhrl6M47GB3aOu5Tgcn0IXZXNcWVzyEwspeAf3eWqQNg07V/mRLqH+79Ly37vog3bw2NGz6VNUIMQ2Ow61/4B55ATYzhzV/LYPcDJOPDXHDtX+ZVSDgbxguzZQQyF6LNyexBYL7bgiggyRLJWCLrIT1ZFNfucc2p8HTyPXiL8sy8/mg8S8spiCKSImcjyNP1Ude0rPNn/PeSokxIXZru+pIik0wMExw+RCLeTTTUj8WSj9VeSPOuO3HnLCO/pBDJupIVF72KaMhOdCyEoevIVguCKOLwOLPiqoZuYLFb8OY6OLz9j3Qfe4D+tge44qUPEAum2L/l3RRXPY/C8utmfC6GoTPc+xD5pVeTiA2gJgM43DUc2XEbdlclNcvfRTzaRzzSRyzak05HNDiy83Ya191B68Gvs2TlrShWNwef+jCevNWUVr+IQ9s/SmB4Jxuu/i1We+FJf5+zgdDoYfY98Q6Wrr2NgrKr533+2PAuvHlrzmju9/8iju//GsGR/SRiA3jz1rFs453nuktzgsk49nXWXfFTrPZCju35HPFYPysv/BqGYXBsz2coqnwu3rxVJ21rfNThTEUgYuEuRgaeoLT25QiCQMC/B0/uqgUbz2PDOzn41K2suexenJ462g9/j8Gu+1i++SvsefSNE46tWX4zpTUvXpDrPt1xMuf5fET95rWzyiyugiji9LqRZIlUIomaUrMLmSiZi7AkQzIeRxBELDYbmmaK0kWDYUROsETB4uDDP92IxGIwNCBjoZovqGK1mB6YtENcVuxUNtxERf1rObrn07Qd+jYgoFhz0LUoup7Em7eWgH8PYtq7JituvHnrEEWTptHurEQQT1A2enJXYrUXp4914c1bl/XM2ZxlWd0FAHfO8mwahCTZzWPTqQVWewmenBMeIbdvWdbrI4pWvHnrsh4dq6MIT+6JSdLlW4rFmpc+VsGbty4bRrbYCiZ4nlyeuuw1RdluTm4I7Hr4Nay48Gt489bg73+M4Mh+qpe9HTCVaRWL95xtTE71/Uglxzi09SOEA0eyn4milfyyq8gvuQLFmoOsuAn693Js7+foPv4LNl7zBwCioTbzvq05UwyNnuO/of3w3fjyN1C/5iMTFh9BkCiqvDHLfAPg738c0Nn96JvYcPVvFmSxGv9MMoXG442yzMZ7PmmdGZppOGEACKJgsgZp5mdWh0l9nEokp41cjJ9H5sosZF7DnD9sLicOt5P+1m4MXUex2/Dm55CIxtENnXgoisPjIhlLoFgt6fk3Ne4aIoZgZGlVDd2YMjeNN0wyTgnJIvDUn16MoaeQFRdWRxHxSC9amn3NnVtH/YY7kSSJ4a4xJCWGxW7N5sDbXQ4SkThqKoXT5zZTvlIa0XCKkprryCu5gvrV7ycZMwAD2eJBVmZfnARBpKDsGgL+PRza+mEa1t+By9eAr3ATbl+T+YzDnRza9mEAfHlrcHiqshuqyqVvRBBlYuEeAv7dlNS8iFikm0ighaLK52OxTR/B1dQYkVA7o4NPUlH/OkRRPmObrEyth8vXSNOmL+Ar2Div8w1dpbf9jxSUXXPe0JgnMkaymkhOmCOCI/vQ9RS+/PV481bj8NRQXPk8M/qkRrPpcIsZRRU3UFRxQ/bflQ1vygqtCoLA0rUfn/FcTYtzdNddVCx9Ay5v/aT5/cykOtldFZS5XgGYtL8Hnnwf9Ws+TmH5syYcp6YiSJIVQZTpbjEjmuV1rz5p+/6+x1CsuTjcpvBjPNKDw1NLf8dfUKy5rLr4O0QCRwmNHc4ygp3H7BGP+QoEziuyccF1/8DmykFNmPnEYBoXFruFpnWV7HmiBafXSXgslE2lytQOyIqCpEjEgtFsAXMm2pFZ8HRt4qbqmRb9OBvIbHYyGgCCIGajTZM3XonYIK0Hvj6Ot17A6VlCJNhCddM7Kat92dnu/jmBrqsE/Xtw+RqQFTcDnf9gZOBJlm38FIZh8NS/bqCq4U2U1r6UgH8fnc0/YPnmLyOKMsf2fgFP7soJE/u5htVpJzjczoGnbiUe6QZMdd2iyudSUHbNhDB8OHCU/U/cjNVeyNK1nzhpYbdhGOx7/O2EA81UNryZivrXzHq8riUZ6PoH0VAH/R1/ZtUl313wMHlGs0BWZGwuB8l4guhYKP2dkI2AyFYLkiRl559MNDLzfcZLLysKqUQSxWph0zUr2XLfLnRNOytOkaoVdQRHgiTjCZKxBIWVpiHv7xlCssgsXVuLmtJpPdCOmkgiKQrldWX0tPZmU6nATK0TJYnKxkraD7ahpbV6wIwYCIKI1WnHYrMiiAKpeJIHfrmZgrKLWXbBe/DkLkUQRWKhAYIjx7A5K6hatorBzkGsDhuJaBzFaiEaDJsCeVZLNsKtpH8LQzcQZdNoS8YTMxasn2wjr6pReo7/iqqGN035TtdV9j3xLrx5ayiquAFJdmK1F9Db9gf62v7A2st/nN6Y/JyiihtBENj18OtwuKtxuKupW/UBNC1OX9sfKa15MYKosOfRN5tG+MhemjZ9gZzCTRzZ8X8gSDSuv/2UftfpnFmFNWW4vE4OP/kEkeBxcos2z7tdNRVh18OvpnTJKyhf8opsXvpC6QYsdla3+WCu93J8/9eIhttZeeHXJnwej/az97G30LjhU3jzVqPr6qKMhJ8uErFBju6+i7Ilr0IUFdy5KxFFC807b8ebt4aSmhed8T6ERg/i8jUSi5h1cg5XJaHRw+zfcjOrL/0uTk8dR3bejihaZjWcAHpaf0v7oe9QsfQmKpe+HoDWA1/H3/84aipEWe3LqWy46Yzf0zPpXcrgjEU2ACx2G7KioGkaoiDiKfSQjCVp3tuDIAqMDowgiAKeXC++Ag/RUJyK2jyqKmz0DSRpOTxoFjVrusm44g8SCZiaEVoqRSrtoRMEEeNpQE272AZQJvJ0wkNr4PC5iQXDU/pptRdSXv9aRgaeoLjqBdhdFXQ2/wAww/r/KxBFeULB23jPvCAIrLr4W1jtReljJWyOYrRUGMHiQRCkbPpZPNpHJNhKbtHmsypyNblwfKh7BwefutWkKQUqG99C+ZJXTbuhM/QUup5gyapb58QgpetJIsHj5nV67md0YAuCKGHoGqoaBUPDldNETsEmNDXK8f1fxumpZ9UldzM2tI3e1t/QsO7UNmwzwdB1c+Odjqp6cr043E4S0bgpghlLoGsaqVgcVRSxe1wIokAylkBSFGpW1tFzrDvbniAKWOxW1JTKo39+atznZ/5dj4aiyIpMYNCP1WEnEU0QHg0iyhIOt5OWPe1mJCSpmnOkriOIAiU1JYwNBvDmewgMB4lhprV2t/Skn5FZH6GpGrJswe52ISsymqYRDYQQBJGy2ufQ0/IXBjoexGrPpazuOhovuJXc4k2oKZXu5i4Uq4Wiinw6m7vTdQZmPnomvczqtKeNPnvWuDHTwUzjr7ftj7Qd/AY5hRfQtOnzxCLdHNjyPpKJES647m/EIl30tPySulUfRLa4ObLzDgpKr5rW0ADz3ZVlB2oqRPOuO/HkrmTJylvw5K7C6a5FEBUEQcjmasfCXWy46lcMdP0TWXGnn41K59EfkVO4Caenjvo1HyWVGCM4shJv/loMwyCn8AIc7loMw8gyPM0H0xXwD7b1MAjEwh0077yd+jUfnXdxqqw4WXflz7L3sv+Jm/HmraFu9Qfn1c5MWExr2+liunuJhjtRLN4J0dvKhjdOqF3LQLHmULbkFdidpm5KZ/MPUFNhlqx8/1nRZzhbsNoLWXHhNwiN7mf/lvdk0w1dvmWI6RonUwhPPmP3nWE46zj8PQxDp2nTZ3F566lZ/m4stkIMQ6Nx/R0nbafr2E/pbP4h5XWvzs4BALLFSzI+BIA27rc+k3P82XyX5nMf8z0WTtzLfIQw52Vs5JUXAwqlyyrpbe2jtLaEsaEgeSU+eo73o6VUpHTqQXg0RDQUweVz09Y8wFB/monDIpNT4CKVUBnoGsGb72XV5iW0HxsiHo0THBpDTaWyUY7xheiL1fCwOu2IkjSn/OyzUdsxeeCYhsb0ASy3rxFfwSYiwRaWrHwfuhan48j3SSX8Z7SPTyeMD6u6c5ZPoHocX6Dn73uE7pZfsvGa3yFIZ8/YGG9odBz5fja8DJBTeCGpuH/GRcHla0S2eBkdeBJZ8aBYfdMSBETDHUQCLRSUXU3jhjsZHdxmslal/xMQkBQn0VAbQ93/Zqj739lzU8lAOpdfwdDPzDts6DqJaAw1lSIWCiMpChabFW9+DqMDwyY9dLqmLB6OTJhLju9unvM1wEy/0FJq9t+TaU8zmExbm2ljNjKDZDxBYMB892LBMLFgGFGWUKwWwqPB7Lyo6waiKKAmNFr3twJm/VxoZCyd/iWiOCwYsQRqUsXpc+PN9zLcM4SuaWYdXdpplIl+Nmz4CPXr3k8scpTR/m0c3/czelsfZv2zvobT04DVaSM8EqT1QDuyIqOmVERRIDUucmRzmfN8JBA209I0zUzbUpMIokx47DAOdy3efNO4FwQJQbIAOrLiJB7pMRd/UaKj+YfYHCUM9f6H3OKLp6QJaVqSVGKE6mVvx2IvRFdjkB7n0+mLjA3v4uBTt7LqkrspW/Ly7Oey4jKL0Jl4bk6hmdIUDXfgK9iE1V7AyMBTjA5uYcnK988wSqZHNr1PVxnufYhY9AgDHQ+TSqtE16+97ZRZcDKGBkB109unsFAZhkF47BDDfY9itRfhy1+HIMjoehKHu2pRqX+fTaSSAQ48eQv5JZdRu+K9JGKD9LT+hpqmdyFMw+YkSdYJKTt2ZwW6kXpGGRoZCIJJjb/uyp9nqY/L616JriXR9RTH938VTY2myUHO3P3XLL/5RJ9EmZLqF9Df8TeCI/uoX/OxWa/d2fwjuo79hMqGN04wNMBUbHe4l1Bc9WxaD3wTxeKlvO7VZ9wgGM+qmMGZuOb8qN9PzmQ4/tjMXCZbLVgccy+kn5exkYwnUJMpIsEYuqrTfbSHvLL8rKFhc9lxuB1EApFsx0b6hrHYreQXeyksdtLZNsZwf5Bk3IxgJKIJ9m9rRU2Mi2qIIlLaOy9IZtjfLIw8sz/QqcDQ9axXby4427UdmRqO2fpXUHYNx/Z8hlRijNKal6CmwhNy7s9jbihb8goKyp6FKFkJjhzA3/8oVY1vyUY+JmM+HoW5sG3Fwl1ZQ8PqKGXZxs8iYBCP9hOP9rN/y3toWPd/WdpaMDd7uUUX09fxZ3paf4PNWUFF/WtQLDloWgy3bxmGobP7v2b4uaDsanKLLiK36KJp+9Cy94tkkmWWrr2N/o4/Ew4cY/+Wm4mFO6hb/aE53e+pwND1rCqzqdCcIhlPYHe7MAwdp9fFaL+fZCyBIE6t5ZhcX5FxDIwv4Lan6yUEUUAQzRqRmVinxrc//u/pfsdMcXrG0ADTiAGTVjWFmRYlKwpqKmXWxVktCKLJeiUpCka6iF1NO30y7FmK3UYqkWRkwNTt0FMquq5mjYXM81KTKorVgjd3LU73CvLLb+Tglo+z9R9vZtMN9+L0LEWxWogFw1jsVnTdyD4vUZJMFi5VR0unnCXjZqpVcLiLvY+9m9WXfpOlaz8+obbG5iihvO5VeHJW0LL3iwz23M+yDZ9Glh3EQu1489dSveytRIItJGLDiLKKN/diBEHgwJb3oOtJmjZ9Dos1B6w5s44Pb95qGtbdjss7NYJnteVP/xsaBkd33YnVXsySVR+g/fDd5BRuxjB0Oo/+mNDoAZLxYZasfP+0VLOGruLvf4zBrn9lBS9TybEpx9nsBbP2fa7IK76URGyQ4MhBkokR4pEuRga2EAt3oFhyTPY5Q80ev2TlB9Iif/8bGD/2FIuXNZfek60rTCXHCPr3EvDvmZOydVHls89oX881MkZoYHgnvoIN2ZSZpev+j/zSK4lHzhwVeAY2R/GUzyTZgWLNmdXQiIba6Tr2UyqW3jTF0ABIJUYQRZnB7v8AppMuv+TKbE0pnLkox0x1DueSyXQ+x2bWKqfPjSfvDBkbqXgChycPTdWIhSNIskRoJEQqab6sNocVwzDMFCtRZKRn0CyolCSKSlwoioCaMnOHFYtCQk0gyiKGbmQLHaX0ZCDK0oQCRiSy9R3j+bIXAxaL4TMTTtY/p8csmopFe/DkLKd62dvORreekcholYwMPMHY0A7K617DUP8D5BRdaG6IxmE+42YutL42ZzmrL70HLRXhwFO3kIoP4SvYgMNdTSoZpKjihmm1VEqqX5AVfoxHuji257PZ7wrLryc0dij7757W31JS/aIZc5WXrLqVqmVvQRQtSLIDl7eBoZ4HiIbbqW56F54zLACWSakC0FIikqqRSiQRRYFEJI5kkbN1DdqkGg1ZUbJsT7qmTXAMZP6eLXo5F4NwydqGKZGUzOKTU5zPUEdvlulKTDNLGbpZyCorMrqmoSaSWJ327GY+U/BttZrF6y6XwyxgTyTNhUEUKKsvp+NQe9a4MOtUBDQdMyKtyChWCxa7NT3HGtidJSzb+AUOPnkr2+57C6su/RZOT206vSuGKElZat5ULG5GYdK1d4ZuICkmra2ajOLNXUU8PAwMTEjXazv0Hbx5a3C4q9G0GKU1J+rEale+D9IlhR1HfkQi1kciPsjm6/4OgNNbx0Dn34lH++k4ci8FZVeTU3gBaipCNNSGJ3cFhqGz59E3U1L9Yoqrbpx39MAU4PqCaVhqSeLRXvKKL6Wv7Q90H/specWXEQjv4sCT78PhrsHuqkZXo9hcFdQufzf7t7yH0NghPLmrcOesQFZc5JVcxrE9nyMaaqWq8a2ULXnlgnqHA/69HNvzGcDAYsvHm7eGmuXvxpe/Dk1LEB47jCBItB/+HqODT/1PGRtZMUktjq4lJsyHLu9S1lx277zaO7b3C3jz1k4pZH6moOPIvSSiffgKNiDJDupXf8Qkb3GUwDzJDBYKBWVXz8rYlkoGadn3JSy2fMrrXjXtMXZXJf7+R7P6KACGMHE9Pt193WzGw7RCo+d4HzlXAd2M08vQDYZ7hufc/ryMjYYNddx4TQnf//5RZEUhGY8TGQtlPVldIwEkRcHmdqBYLOkCQQlJktj5+HF0XUeSJMrritA0g/5QFKfXgazIuHNcREMxYuEoYHraJFnKUimqKRVFltAmscXMVeVzMWCx0ONORoYDPh7pOeObwf8VVC97G5VLb0qHnL9MjfEeSqqef8aulzG+Xd6lGIbOigu/NoHvXbF4qGy4ien4IFzepdQufw/dLb8gOSl9brD7XygWH8s2fo7mXXfQfug72Bxl5BVfPG0/BEGcoIpqd5WfleK7CX0Y5znKbKRV1TQiUolklrQCTAdGPBtRFUymqWkiFZl5baYiZ0EUpzU0Ji8406VsVa1YQvu+Ywx19AJmfYXVYTcZ/KwSkiaZqVtJNRv9TURiKHZbNqoqiKLprDF04tFY1pjQVQ3RItNxqB2Hx0k8HM3WeWSejaSYy4BpuMgkonEsdiuxcBRZcdK44bPsfuQN9Lf/hSWrbiERjSEpMoIoZlP4rE57WkxUxEinmGXmZpujhLrVH+TIztvx9z2CxV5I4/o7cfsaiYW7cLiqAWjceDuGdmJ8KhYfo4NP0b//74QDR7E5ylh/5ddRUxGzzmjl+ymuej42RymaGsmO7Z7jv6S/429setYfiUV7iUW6EaUTDHrzgSCKWGx5jA3vxpNrCraFx5ppO3Q3JTUvoXb5u4mG2ggM76a/86/4+x4GoCBN8ZyID5JTeBG1y99NKhXG5ihCQEQUFRSLl9ziSxbM0Aj499DX/iciwVbAoGH9neSXXDbhGFl24PY1IYoKoijP+bkYhsFA59/JLb74aanDNBmD3f+m/dDdbLzm96cssGYYOqTJFp5J8Pc9imFo5JdemRYcNMenIAgUVlx/zvplGAa9bb+noOyaKY67DGKRHg5t+whqMsCyjZ+ZMavAk7cMsc1G06bPIggKQ70PTNDCmQtOpvE0H0PjbOBU+zv+GEEUkBUFu8esiUzGptdImg7zMjb2/ncfx/f2Zz1garqgW9c0LHYrWiqFlkoRGQlkF3w1kSSSjlRkGErUlM5gj59UIoW/b8TsiCIjSiIWmxXDqmQFzKwOOzaHjVgkSiphbtQFwVxYM9Rb59oinCsWo6EBIEp2RNFiihSdx4JBlCwIosKKC7+KO2cFaiqCpoazxeanglikB11L4PTUAhAaPYTFVoDVXkDrgW+g6ynqVt06bUqHpiU4sOW9WB0lGHqKVHIMXU+m6yh06tZ8BFGQ8Q88gShaAYNoqBVNjXBk523IiovqxreQW3jBKff/bGDyfKAmkuZ8pE1UEc4QKdhcTuLhyIyOC1GSEGVpRkNjumue7PPxCI+eiJZk581UCofHZTpydMOMEKQjFRlCAC2VMtO7dD27uVcTZrF2NkJhmNGbeChKyD+WpqQ9kRomyRKJSMxk6lJkPLkeOnoHs30xdD29GRMQJVNHw8CsxRA5keKaiJhzm2K1kJrhnosqno2uJU317HSScEaDB5hgaAC0H/4uva2/xeVtJJUYJpUY5ujuO9G1BOHAMdZe/iNc3nq6W36FzVlObtFmDMPAYi+ifu0nGOj+F8WVz2HjNb9DsXiJBFuRZPuMm4rp1hJD11HVKEd2/h+5hReQV3w5rQe+SlHlc7PifA53DQCtB78BgMVWSM3y9wCQV3wZfe1/ZOfglgntyhYPyy/4Mg5X5bR9mS8Cw7s5tO3D2F0VpsJz0zumpDr2tf+F3tbfEI/2ZuunqhqnL7wHGOp5kOHeh1i28dMIgkBf+59JxofPuvNgoTA2tIPgyH4qG24iv/hyFIvvtJScBUHMqn+3Hvg6OYWb05G1MPFoH053DcIiZasKjR7CMPR09M8gMLwTb/5aBEHKUpXnl145byKEhUZwZD/H9nyWZRs/jaS46Wn5BVZbwbQRyuDIfg7v+ASy4mHVJd/JFvJPhiCKDHTeh64liARbKal+Ad6CFfPKlDnZvnMxGBpzjVTM5xhBlMw1KR1gSETmJlwL8zQ2MqlN8ai50I2nUh1fpDo+xSmVSGaLk105XuweG4M9fiRJQrEqJiPVSIBENGYuYJKE1WHHYreiWCymNzJpLqqQSlM4qtn0gAydZSIae9oYHQAOn2dahqhzATUZQNeTp7UJPo/pIQhCVhPk8I6PIytulm24a8IxJ4t4jacG7T72M2KR7qyg4cGtH6Si/rWU1r6c3OJLCQzvmLGdVHKMcOAI4cARfPkbiIU7UFMmS5A7ZwU2ezGpVBAMjZH+R4lFugABl7eByqU3UVL9gqxGydnCQqVLjn/PMu1lPouHIxOOnbyQZJwome8y5y5E38ZHRKxOO64cL/FoDJvDjpaOTsRDUZOuNm0gZOZaQzfQ9RQ2lxNPgY94OEZwaARD18epjovEQ9FxQqrj7l0yRQqtTjuSopBXkkv30c4pz8wwdFKJUSzWvKymia5pqGpywn0Yuj7lWY5HTuEF5MzDUFVTYeyualZf+l2ad32K4d7/EBzZj67FKVvyKlr3f5WKpaYOxvhNUev+ryCIFqy2fIorn5NlGuo48n3cOU2ULXkFqcQY1kl1Epn7nfy7yrKDJStuoWXfFxnq+Q+S4prCQGR1lFBa+zJGB58iFu5kbGg7hqETGpue1c/lbchqmMxFi2U2hMeaObj1g3jz17Jsw6emqB+Hxo6QjA8z0Pk3JNlO3eoPo6kx4tEe8ktnTkeRZGdaLVtDECRWXvQ1Ml7uvrY/Ehzdz9K1ty16z76hqyTiQ8SjfYwN76Ri6RtQrL60COQCtG8YxCLduNNzaWj0IIe2fZg1l/0w6xRabOg5/mtUNcKKzV8mFu7g4NYP0Ljh0+QVX0z9mg8vGtIAp6eOnMILsFjzkS1u1l3582kNxKGeBzm293O4fU00brgrq7M1HRKxYUb6n8SV00Drga+RiA1Q1fiWOY3jzDx3Mv2JxbCvm85xcjoQRBFBEBFFgXg4mg0IzBXzMjZ0VUNNqVNEcMZ3xtBPKNWOp2BV7DbUVIpkLIk9TYuoazqBwBgOt5NYxEyfUlMqmakyGU9gddiwOW3ZonMpnUqlJpLIVovJhpJI4vC5Z/U8LibIVgv5ZQUMQ1Yh+FwiHjULvcYXR53HwqNm2Tsm5IhmMJuhoWsJjuz8JAXlz6Kg9CoqG96IoZ8o8Fx1yd1pXn0BX/5afPlrJ56vqwSGdzLc+zDDvQ8jCBKlaf2UseEd+Ao2Ul73GtRkkOZdnyQSPG4y1hRsorLhTXjz1806cZ9pjNfAOBvIXGsmA3A6o2W+8BTkEhwaybaXYZuyOuzp2hE5S9mb2bwLoogrx8vaSxvY9p/9xMORbF+S8TiDbeY7nNm4jjeotJm8bIaOzeVI16HEOL57+rkoU1ScSZ852XOZCYnYEG2HvkNJ9Qtx+RroPvYzxoZ34slZQVHlc7C7Kids4NVkEDUVQNdTLFl5Cw53JcWVz2P7gy+l5/gv8eStQbHmUlr70uw5giCw/spfMtz/GNKkFKHc4ovJL7mcw9s/ztjQNi668cHspmr8GNNVjXi0D0GQskKegiCiazFKal48LY20JNmoaXonLl8jR3fdybG9n8PQU3jz19Gw7nac3qXYHMUYhk7XsZ+Z9z60HVGyUVL1QqqbTr1OTlXDGIZKRf3rpxgaAEd2/B/JuBmtKq192Uk1gQ5u/SB2VyW1y2+eoP0xnvVKseZgc5RlN2hnSvRwIdB68BuMDe9m3RU/objquQveviAILL/gi9l/u3NXsvrS7+P01GbVunMKN5+SMvyZQDLup2b5u7MpdA53NasvvQenx2RhWyyGxkDnP1HVCLUr3pv9bLKhYRgG3S0/o7P5hxSUX0fdqg/MmDqVQWhsP4ahseayr9DfcT8te0zNjZLqF5BTeAFD3Q8QHD1A06bPT6lNXKgowdMNE1hh5yGUOx6nFOOba4ho/L8tdivJWAIxmcTn8JGMJ0kGTMsoGoqgWBWMNE9+IhqbUKhoGAaxkJlqoOtGVv02Y/RYnXbURHJGCsrFBjWRZGxwlOQi6Ws8mvas2ueXs3ge88PJdCx0PZWdKMeGd2F3lmO1F2JzFCNJGaX1iSrm06VhGIbOUM8DjPQ/wdjwTjQ1gs1ZTnn9qymuej6Kxcvx/V/B7qqipumddDb/CH//o/gKNtK06W34CjYsKm/l2Zy8ZzM0FirKkjE0Mhtcq8OOmlJxuJ3ohk54NDQl6mnoOiH/6ATdjwzG92k2D3k4cIzRwa1Y7UXYXRUoiodIIE3fa82dURl5dHArAJZJY2++kBUXairI2NAO2g5+k1i4k5yizQx2/5vett9hc1aw6qJvolh9AJTXv4b9T7yL3Y/cRFXDmymvey2CIFC36kMc2/NpRNGCxZqHmgqRTIxm3wVv4RIs9nwQTjwXQRQprjQLoWPhdvJKrmTf4++ivO7V5JVcSiRwnMDInrRStMSBJ99HfsmVVDe9nVi4m+6WX2KxFVE7jopzOuSXXImyOYfQ6EHyii/B4a6e8L0gSFQ1vJHiqufR3fILhnsepKf1Vwz1PkjTxs+SV7aCeHjuedAALm8jLm8jh3d8nJUXfn3KNYurnkdn872IopXKpSdPgTKFP72zHpNfeiX5pVcC5qbQ3/8ojRvuQteSBEf24slZiWxxExzZRzzaT0HZ1edsE1tS82KKKm48a3OaLDuy9MmaGk2TZUx1Mp0LGIbBkR23YbEXTRCodHmXnsNeTY9UMkAkeGzG7w1dpWX/Vxjs+ieVDW/Mzg+zQVIUwmPNWO1FGJqDovIX4HDW09P6O9oOfZu2g9/MHhsNtU1Lof10x6mwumaOy9T5zefc7HXnoyB+0XPuR1aciLKUXYzH5zxPaHicJZRhJrHYbQiigNNrCkoNtPVmj8l69tLMVlpSzSrdapqGYjVTqjKaEeMVxzO0i8lYfNEXjDt8nnMSzZAUBcPQp90stez7EmND29lw9W/Oer/+l5CIDTHQ+Xdyii6coqLd1/4n2g/fw+br/4EgiGz5x9XULH8PJdXzLypvO3Q3va2/wZ2zHF/BJnKLLsLpqZswEXce/QldR38EgGLJoXbFe8gruWLReicXGnMxHCYfkymQy7DlnYrhkXGICKKIO8+HYrXg8rlQrDL+vhGCQ6PomoZstZBXUkB/a1f23Ez60nw0hwRRJBpuo+PQD/D3P4oo2bJij5NhseWblMdqJJs6I4gysUgvecWX07DuE7OOD8MwiIU7CY0eJDR2iHi0F6u9GJujFJuzFAGBjiPfJx7rx+VZagpJeuvRtQSjQ9s5svP/WLLifRRXPS/bZiTYQsfh7zM6tJXaFe+lpPqFAAz3/pejez6NxZqHpDhJxodZd8XPUCweRgaepOvYTwmPHWHdFT9FlKxY7YUodhuGrjPc+wQOdy1dzT+huOr5OD1LGOz+N8f3f5XN19+HIAjZDYli9dG8606Gex+iuPpFLFnxnjk997lC13XaDn6D/o6/AGYx/borf44giHQd+zkFFRdisy05aTupZJDdj7yBvOJLWbLylinfjw3v5OBTt9K44S7yii9d0HsYG9rB6NA2qpe9g1i4g92PvIGVF30LT+4Keo7/msHuf7H60ntPW23bGFeMnUyMpiO6czMgdD2FriWRZPs5c6SoqRCaGj1n6cqp5Biy4iU8dhirvWhaZsLFiNDYESKBoxRVPBtBlDEMA1Vrp2X33YwM7qR+9YcoLL9uwjmT52ddT5rMWrF+giP7ySlcT/3qT0w4R02GCAePEo/0cnz/l6lb9cFnvATAXLMGMseJadKmDJHKGVMQF2UpexHFbkNKF0463E5sLgdj/UPjREsyRoaCJEkk4/ETBY0pjdF+v/lvWULA5IZPjQZMnvikmSZiGDoWm81Uuk2lJtSFIEkn8qY1jehY0OxTekFerKGs1DkyhmYyNNRUiKGe/1C+ZHqKuMWOyerZixnxaA/+/keyaUwZGIaBy9tg0vQZOghiOjd1/ulLg93309v6G2qW30xpzYtnPK6i/jXkFl2Emgzg8jYgW9wzHrvYMV4oaXzevTFLuHcum/XJx5i5unM/fzpkIrAWu9UUAg1Hcflc9B7vzdLqGrpOKhaf1tAAkzQjc+zJjJ6xoV0cePIWrPZC6lZ/mMKyZ6FpCeKRbmQ7xENm+moyPkQs3ImqhpAkh7mo6yq6lsKbp1HT9HZSqS6GurZQUvNiRFEhNHoYp7c+u4nsaf0NHYe/CwgmDayznGjwOCP9j2Vrg7x562ja9AXsrnIMw2C47xG6j/2M6qZ34s1dw0DXfRSUX4eUTgdyeupouuDztOz9Ih1H7iW3+FKstnzyS6/A5iyjv+Ov+PseQ02F6W75OXnFl6Jp/VjtRSRiQ6hqkINPfIS1l30fKCYRG8LQDJKxkQnCfIXl103YsGSikPFoP/6+RymqfC616YLwhYQoiixZ+T6Kq57Lsb1fJBI4wrb7n095/esZ7PonFmsOtsolhANHGRvaSXH181EsLtRkBIvdk3X6mamOApmaisnw5a/Hm7eOIztuw+VtILf4UsqWvHzalJNI8DiCIONwV2U/MwyD4Mg+rPaiKdoHvoIN+ApMkUa7s5wN1/weS5qRrmzJKyiufiGiKBMLdxOP9pJTuGlOz8YwNLqO/pTcootw+RpoPfANyutfg9WWT/POT2Kx5dOw7jai4U4Ob/sIDevvwOWtZ7D7AcaGtrJ07YnN5LE9nyMWbmfp2k9kC/rPJgzD4NC2jwKw8qJvkoj2ERo7TF7xpYiSZYIhZRgasXA3VnvBgtXI6XqK3f+9iaplbz1pGt25RGjsCDZHCd0tv0TXEqipAMO9JsPbUO9DFFZeyED7w4RGj2B3VdK08bNTxpO5Dkz0oXccuZe+9j+RX3oBntxVePM2IYgido+L6FiQeLSfw9s/RjTUmm5DWTTRqIXAdAKzMF/xP/M8PV0gPl/MT2cjFsdQJ4ZCY8EwyVg8++NmOm91mLL2GU57xbCkWaTUdJH3ifzYTF52JjUqo9BrCmcJ03Lbj09zyDCyLPYUKm9RHoEBP4rdls3LXohIzEzW6Xgxspk2JPFoH7oWP2mKz2LF08XQAPDmrWHNZWY0IZUMpBlyWji84zZWbP4KFfWvzR47Xxq+DEYHn8TlbaSk+gWzHicI0jMmRGzOFxPHeObvzGb8XKdYirJJfFFYWYzVppBMqgx2DhAdC9Izzfw5GYVVJYwNjmRVxTOYzdAQZQmHqxqbs5SC0hpKap6DrmqU1FQy1GEupE7X1JSxmQyYke599Hf8ldLal6Omwux/8j1UN76NsrqXMdTzMH2tv8eTu5plmz47JSVLTYZIJkexOyuy0ZHhvoc5uutOEERG+p+gvP7VHN72MQ48+T4a1985oYC7atlbGRl8ir2PvY2laz+GL389Lm89datupXb5u+k+/it6W39Hb+tvAYEX3/xnnvjbD9n3+LtwehvQtCSHd9zGSP9jWO1lePNWU79mosDkdOlzg133gSBQ0/SOM8os5PQsYfXF3yIwso/h3odpP/QtaprelfWshgNHGRl4gqLKG9BSMbbe/zzqVn2QwvJrs20UlF1Nb+vv8OatzqY4jUfjxk8x0v84o4NP0nn0h4iSnbLaFxOP9hGP9ODNX4cgiLQd/BaKNZeGdbdlz9XUKEd2fIKK+tdTWvsSNDWGKNmmRLoEUZ4ikJgxHA88+T7Klrz8pMZGIjaIrmvY7AWMDm5FsXhx+RqQZDsDnX+ncukbJhT0yrKTvJLLs0QAJqWvSRig6yla9n2RnMLNlNe9+pwYGmDWdTSuvwNdTyIIAqGxQxzd/SkuvOF+AJp33QFgHqMl2f3I66lf81EKy68jHu1DTYVOmuqUjPvpbP4hZXWvwu4so7/j7wz13M/Ki76BKCqU1Lx4RjHWcw0zwcbg2J7P4fTUkEoGCQzvxGLLp27Vh7A6imjd/zU6Dv0Wp2cJTZu+MGO67/hNtaHrJGJD9Lb+nuqmN1NW+yr62v7IsT2foa/9T5TWvARv/loObfsQhq5Sv+ZjOD112F2VEyJx7rwcQv7Rs/U4FhyTn8lMwoInb8c45fPnlUZ1wXX/QFbMRWr8xCxbLdhdTrR0hCGDlZetJpVU6WvrJzIWwpJWxLXYrEQCoRkX/+mUe6ft/CRmmNk8mecSE1RL7TY8eT4KyvMIDIfoa+k8ydknb1tSlHG0wql5GTCGYbD7v6/D6a2nYd3/nVZfzmN6pJIBOpt/RGntS7A7yzm07aNYrLnUrf4gmhql7dDdlNe96pQNjPFoO/Sd9IYLqpveSdmkKMq5wuTw61xwshCvKEu4cswNRiIaQx2fejnDnCEppid3pkjfQiIzjxVUlZJfmkskGGOoawDFaqG4qoj+jgFC/jGzP7MQbkyO2Myl36Is4fR6CPlHad59F/7eR1i++Su4vPX0d/6N/JIrp7AxzQXjPbCRYGs69cqDv+8xju//Cq6c5TRt/NSc2jq49YNZoxtg+QVfJDR2hCM7PoGuJVmy6tYJjEHJuJ+jez5NYHg3uSUXISBTXPncrFdd0+IM9zxET+tviUd7KF/yKiqXLWHL3++ibMl1dB/7O7Lixe4sp2nzl5Hl6Wk9/f1bcLirsTtLs9ogJ0s/0rQ4geFdBP37CI0dQlNNBjHD0FEsXgorrp8XlWjzrjuIhjpYe/kPp3ynGymGux/Ek7caQVSIBI7izVuPKCkc3f0ZhnsfpmnTVI9vBrFIN7sefg2CqGC1FyMIMrFwW5Y9KREbRBAkdC1BV8vPqWp8MxZrLvFov5m6JCp0HLkHX/76ebGLJWIDSJJj1ihqNNTGwa0fJBkfprrpXZTWvATQEQSJ0NgRLNbcKXVrsyEcOMb+LTeTW3gxDetvO/kJZwmGoaFpiaxRPjLwFKBnjYGAfx8OVyWK1Uf74e8x2P0vNlz9O0RRpv3w98gp3Iw3bzX9nX9HTYYor3slairC/i3vYcnKW/DkriDg38vY0HYq6l93yjozZxKGYRDw7+HYns+wdO3H8eatYXR4B8d2fYZUcgSHu5ZVl3xnXvS7mX0gnJhTE/FhdvznJSzb+Bl8+evZ8dCrsnVNgeGdCIKEJDtZdfG3sbsqTnqNxcI2dTo41XuYnDmkaTGeuu+GhU+jGt/J8YaGmkgSF0WcXjfW0kKTFjGlMtw7iiiZIS1ZUbA6bKiJ1ElpajOGxmxMKrAwzDBnA+P7lorF8Xf34+/uP+12ZaupLKxYMxOJnn3R5ropEQQBb/56QqP7T7s/5zE9RMnK6NBW0wvphMKK67OiRJLsoG7VrafctpqKkEwMk4wNEQ40Ew21Zb/rb//zojE2zLGozcq8NRknFRkSRJMyO+1kMA2ZFBl61+kw2/XPhOim1WknEggjKzLDPYPYXQ5KaooJDIeIpQX2ZsIJb5SAKCkTojcnWyx0Vct64gTBgqy4sDmKSCb8tB/6DrmFF5GM++edtz3ek5ih9dTUKKND20glR3FOKk6eDd68dXQd/RFRDKoaTL0Ht6+RNZf9gOP7vkzzztsZKrqEyoabsDnLsNjyWH7Bl+ht+z1jg9sYG34Cf98jbLj6t1jthUiSjaLKZ1Nc82z2PPI2uo79hLySH7Jsw6dQrHnkFN6AJ7cRXROIhlpJJUdx+xqRFTdDvQ8hSTZyiy6ieedtIIgs3/QFCsqeZYr4HfwW8UgvBWXXoFh92WJnQ1cZ6LqPzqM/JpXwY7Hm485dSW7JCpODXhCJhTto2ft52g59m8KyaykoexYu39IZC6YjwePEo/3EIt2MDe3AV7ABXUsiiAqCIKBrKfJLr8QwdA5u/SCh0QNY7UXUr/4IJdUvxN/3MIe3f5ymCz6HL3/9lPaNdC6goadwemrx9z1CSc1L0+xJGonYEJoWJRkfBkMjHunFYs3Npk8ZhkF4rBlv3hrUVIRUYhS7a3pNg/Gw2ovoOvYzZMU9IfKaiA0y0HUflUtfj8NdQ93qDxEJHE8XlQuAlB0bc0Es0sPRXXex4qKvp6NfH8TlXVyRe0GQJkT/xrN+AXjzVmX/rmp4E4UV12c97WPDO7MRmmRsiFRyDABZcbL28h+Ma2M13rzVZ+oWTguJ2CCHtn2ImqZ3U9P0rizFcsuez2Gx57Piwq9k3+n5YLo9j8WahyjZaNlnMoalEmNUrPs/vHmriQRbGez+FwVlV08xNObCSDgTMo7ys+HUOhXMl7o9W684ztAQRBGRuZM+zNvYyFzI5nIiWWREQSQpS9jdLhweB6lEChVQBJHgSABPrtdU/7Za0DXNrN1QNbSUOqfrPJ2Q+UFm86w6c71TKHpPZZNjdZppaoJgCiHqmpZVR854bwVxbpEeUbKgafPjTD6PuUOSbKy7/CdZ79JC8Lv3d/6d4/u+NPFDQcSTswJP7mrsrkoqlr7+tK9zOnD4PCaNaDhyRrxB5pjPbJxOGqA9KRbS0Mi8g6lEkpIl5bTvO4YoS+QU5RIORBns7J0y0c8UnTV0A4Op9SNzRW7RZoa67yOVDOB013LBdf/g6O67SCVGWXXJd0+JFCASbKWz+YdEw+3EI72IosKSle+nqHJu1KLRUDu6FkeUbKipMC5fU/Y7xeKlYf0dDPc+RPvh77HnUdMQKSy/jiUrb6Ws9mWU1b6MjuYf0n3sp+x48BXkFl1ISc2L8eWvw9Agr/hyYuEu7K5K4pFuRvofJ6/0CjAkRgcfo3nXnYiijRUXfgVJGqO39XdgGAiCRPXy9+BwVWJ1lBAb2oFs8RAJHKX98N20H74bAEl2IVvcGHqKZHyYgrJrKK977RT63gzikV76O//OYNd99LX/EVlx481fh8WWTyLaTyI+hKy4MfQkwZH9KNYCPLmrsnnjnUd/hKHrlNS+iJ0Pvpycws1IspN4tJdN1/2d7mM/xeGpRZKdVNS/jsDIXg5v/wRrLvv+FHGz8Qx2tSveh8VWQF+b6TWXLV46Dt8D6Gy4+rfT5vcLgsDKi74OmMQWbYe+w0XPfmBOv7uaPJH50H74HmyOYkTJymDXP8ktuhiXtw41GaTr2E8orX1putbhwxSWX0tB2TUztjvYfT+h0YMsWXkLhq4iKQ40NYokWRcN5eypQhBlHK4T9TNrLr0n+/diEVgMB44SDhylqOKGGY1oNRWms/kHFFe/AEmy4fTUY3dVZiNVupZMi0a+aQqj2ulAEATK615J59GfgWHuO/va/4g3bzVOT21WnHMyTmc9OJmjfDHgVIygTMkCmPdoc9nnfO68jA2H100yaob1U4kkiWiMJWuXEhgOEh4NYnfZiYYiSFJaZVDViIYiyIps1mOkVHKK8hns7H1aGhMnw4kC0pl/RLvTgZZUUVMp3Hk+XF4nXYfbZjx+OoiylBUzzNS1OF0u4tE4uqZldUjmmlcXCbRgd548fHgep46FDGPvfuRNREPHp3y+5tJ7cHrqFuw6p4vxKZVn4n0fX7C9mCCIIrqmmRSBukjHAfO3khSFjgMtM56XqV2bjNN9dplc72TcjydvGYIqU9P0LjQtfkqGhq6naD98N2ND2ympeQkOdzW+/PXzSgMc6n2I7mM/xempR7F4Obbn06y59N5sio0gCBSUXU1u8cWERg4QCbXScfge/P2PUVjxbGqa3kXN8rdQtuQVHN/3FYZ7/8PIwBPkFV9GzfJ3k4wPYbEVIooy4UAL/R1/IhbuoGH97dgcZRRV3EhB+Q0c2vYRUgm/2SlB5tC2DwOwZOX76Tj8XcKB5gn9tjlKKa97NalUCC0VQtPiFFXegNNdNyH911OQQ2DAf+I8ZynVy95KZcMbCY8dYmxoJ2PDO4gGW7E5SnH7GkglQ+hanKVrbyOv5PIJOeMOzxKO7f4UntwV1K3+MINd/8KTtwZv/loUxTVhw1Sx9PWUqFH2PvpmDm/7KPllV1O+5FUT5qCqZW+n4/B32f7AC7NEFAH/HpZt/Cy+gk3Isj2rqzIbcosuwelZks25B2HWMVWz/F3j/mWgpkKUVz0Pf/8THN7+MRrXfxLD0Khd/h50NYaaCmF3lqGkI8HjMdh9P+GxI9SueA8YOnraYeZwV7Fi81dO2vfzOH0E/HtoP/w9wmnxyqB/L/VrPjZhDGQ0WCTJRjhwjPBYM4Xl17J07cezx0RDbRzebhb0y+MKs8czAM5U5Ayzz5GGYeDvexSnu4olK28l4N9NZ/OPSCZGsxkGmUjEdGm+p+ooeyakW8GJZ2PuNUVsbkfWYZ6pzZ4L5mVsRAMhZMVpCvcBkiIjCgJXXFfHwGCSLfftQhBF5DQPr9Vhz/LyWuwWhFiS4EhgwcNK4z2Ci/0HzqgFF9aUMdjWw2jv/AalIIrYXE5EQURSZKw2K0UVufS2D+FwO4iHo+i6Ma82o+E23DkrFrUwUwYLpXXwdIVh6FlDo6T6hdhd1bhzmnC4a06bWnI2nI3nfibSmM4GJlN/Z9678bVTgihmF7HZnuWZmLtGB59CEGTcOcuz151LbvJ0yPD0B/x7sorDp4K8oovpPvZTapbfjCTb2fvYWwgHmrP1FxlIki3LdpRTsInB7vvpOf5LkvFhaprehZoK4e/7b/Z4f/+jxCLdFJQ9i0S0l+H+h8gruZRkcoTS6hchyhLRUBv9HX8m4N9NKmmmmlU2vInyuleRiA6w9/G3c3z/xM2qIMgoFh8N6z85Y6FuZuwauj7B0BgPUZTx5K7Ck7tqXl7pgtKrcLpr0ylcIkUVNzDU+9CMfZFlB0WVN9Jx5Pt0Hf0xmhqjpukd2e/j4S5EyUZu0YXYHKX4CjbhyV1pRsrTOidzgdVegNVeQCI+zIEnb2HJyvdPERadCdXLTggZNq6/nZHBbXQf/yWJ2CCrL7kbLRVl539fw8oLv44nd2WavexhnJ4lOFxViJKVRMwUKyysuJ7Ciuvn3O/zOD2kkmO0H7qbwe5/485ZTv2aj9Fz/NcM9T5IddM7sVhz0LUko0Pb6T72U5auuw27s5yVF30zu8cwDIORgScY7n2IkYEt2BylrL7kexPIasY7lCbrDslWC4rVMi2B0AQYGtFQO9VN78Kd04TNWU7n0R8z1P1vypa8ItueNq48YMLppzgnTy7KzmB8rfFiw0z7RsPQMTSQRHECKc9Iz8Cc2z7l3YlstaCrGp5cB4W5MBYQyS8rIjQWRFc1nF43mqahplLY0orhWko9+cA4BeiqZm5UTiIjvxiQMYwyir+zGQWSopBbWsBQR++J8yUJxaqgqzpqIoXD7WC4P4CsyIRGgqgp1dQBGBfuOhmqGt9Ky97Pp9kZXnT6N3kG8b9qaERD7YiSDcXqw+6swOldOkFZ9UzjVJ67IIpY7FYsNlNfJzg0gt3jmnEOeDoaGqIsTdEYGo/M+z1TfdmZdo7oWoLh3odw+RqySvBth75DLNzJso2fmbfmwOjgVkYHnzotQwNMEUEw6z0EUZrw2UxwuKupXvZWrLZ8uo79jOP7voTV6cEwVJau+wBqMkHrgW8iSTaKq55LwL+b5h130rjhLupXfQAwn32mMD4W7si2bXOUIAgSNmcplQ030Xrg61jtRazY/FXsnjIM7fTT9DLI1DnOB4Ig4vTUMjq4jSM778BqL0BNhcgtumhCzVc80ksiNoA3fy2RYBs2RylFlTeSV3zZhPYstnwwDEb6t7D5hn+dtpPJYs3D5W3I1vGMJxKYDb1tmXSWJSTS6W61K96HIEioqRA1y96Jy9uApsYYHdxG++F7KCq/jsqGm8gvuXxBUlLPY35IJkbYv+W9qMmAyYhWcQMHt36ARGyAZRs+w2DXv/D3PUIkdBxDN+f01gPfoLD8ugkpbT3Hf0nHke/j8jZQWvtSype8ck5Uv1mSD92Ydi3JOHNORBplbI5S4lFzz6VYPHhzVxMc2Z81Ns4kpjM0xvdzJpwLx/m0hsYEg8/UuMsgr7x4yvEz4ZSMjepV9cTDcSKBMB3NfchyGaIgYHVYsbkK8fcMI4gCsihjsVsZ7R8eV8R8ZvB02aiMH1zTiSGOh2HojPYPZ/8tiCKuXA+pRIpkLE5OcT6GYTDa78fmcqBYLUTGQvPWGSmquIGhngcI+vdMMDYWe5TofwHB0YPEIz10Hf1JdrIUJdsEDvmFxulGMTJhV3eeD5vDxtjgCGr6/TwTzoZziZNRz07+fnIqwPj3K7M4ZujCF8Kw7jn+G0JjR1i28TPZz7x5a7DYCk5J3Gyw65/YnRWnTaEppulQh3v/w1DPf4D0BngOKKl5ERZ7EUd2fJwS14txeRs4uutLbLzmD3jz1qFYcpAVF8s2fobd/309nc0/xlewMVts6s5ZicNdSzTUysqLvoU7Z/mEzba//3EAalfcgs1ZuqCGBsyu8j4Zk8eQpiWwWHMQBJmmTZ8zRRH1FNFQOy5vPcnkKAeeupXVl3yHgH8nBWXPorzu1VParWy4idGhbSTjQwRH9p12IbEgCDSsM+ckTY2y74l3U9P0zimRqgwMQ2eo50GGe/5DJNhC/eoPoWkJPLmrKa56PoZhsG/LzVQ1vBFRsjA6uJXmXbdTVPmcRVOn8L+EZNxP68FvkogNkIj2IwgSqy65G7uzDF1LEBjeBUDHke8SDXeSX3IlBeXX4vI1EPTvpbP5h4wNbSOn6EJk2YEgigz3PQLA8gu/OoUqezpkM1gMfU4aStlIo2GAIKImT9TKhsYO4yuYmYJZUhQUq2XW/dnpYPwGfryG0uTozdnCTIK1U6MywoS9dnh0bM7XmPdqY26Q40iKRNOmJazZXI3VKtHW3M/Y0CjdzR0k46YhkojGUVOqufmQpTNucDxd4PCZHsaTCfzpkwrpDV3H5XPjyfXizvOZQohpdq/g0CjRYPiUBQ2dnnrGhncSDbVPuN55nFvsf+JdHNvzGUrGCfQt2/jpM6qLcjqb3I3Xrefi52ykqKaUkH+M/taurJ7MqXJ7P52QMRQEUcxO3Jn7lq0WJEXOzoeT36/MgpN5/vICzJfRcDtuXyM5BRuzn1lsBZSmlbjnC3fOcmKRLkKjB0+rX7Liwpu/nqGe/+DNW0tJ9QuRlZMLS3qL8vAVF1BW/ywA+tr+QCTUhqy4Uaw5ONw1KOk0IFGUWbruNuJRk53IMNILqCDg9Jiq3NFw+xSvfv3qj6BYcuhs/gGnggx5x0Jg8ruYV3wJ66/6OWsuu4fRwa3seOiVbHvgxRx48hZ0LYHb28CqS+7m2N7Po6kximcp2Dc9yS4OPPle4tG+BeuzYRi4fA3YnGWAqfY9mWE/Gmrl2J7PUN30DupXm3onFfWvYeVFX0fXE2ipMFWNb8aeLox25zRR2fgWQqOH0dQYhj47wcx5LBw0Ncr+LTcTGjmAw11DQdk1rLjwa9jTv29v2++zx1ptRay+5Hs0rLuN0poX4clZTtmSV6JYc7C7qrNGhSAK5BWbDou9j72NWKR71j5kMmkMXc/+f64Y6X+cWLiDogpTs6bn+K/R1MisoreGoS+ooWFu5qc6bwVRnJB+ea6QMTTMfpx4V8c7xhS7bcp8lIjMXbtqXpEN2WohpziPdRdWMjgYo69zFLXES+exfsKjQbNwWVHShoVCPBzNMk+5cjwkovG0svh8rvr0x3irEczC2fH56TN5kqf7XEtplNTkY7XKHD/Yw0jvUJZWNHYa0Z2KutcwNrSdg1s/wMoLv4HNWXrKbZ3HwqDr2M+yfzs9tYiihZzCzdPSWY5HZlKbTchOlCW8hXmM9g7Ou1+ziUjuefRg2kg+MRbnO5ku9tqN2SI/JyZsPWtwXHTjJg7uOD4hj3+6OXByqtVkL9OpwOlZwnDffzm07aM0rLsNQbSw/4l3U1b3SiqXvmFebSUTo/S2/QHZ4j1tZWNBEFl+wRcIB47h8jZMm8ZjGAbDvQ8BZLU4BrqGSMaGCKULUgF8+euoanzztJEat6+RhnWf5PD2j9F97BdULH0dANXL3k4s0s3x/V9BTQYmeP+j4XZSyVGqx9U4zAdq8sxthEcGniAW7qS87lW4vEtJJUZBENJK1Ga0yGovSueov2PW2py8ksvQ9RRHd9+VLRI3DB1NiyNJNgRBJB7pRbZ4kBXXnPsoK07qV384296BJ99HTuEF1DS9M027K+D01LHhmt9NKUJXUxF2PfwayutfM2EzKCtuKupeTUXdqzF0lb2Pv43aFe/Dk7tyzv06j1OEIGEYGootl4r616a1WU68r0WVz8GdsxK3r3FaIhR/3yMk40OU112X/UxXNSrq34Bizef4vi9zaOuHWHP5j7ICkBMunybcmFNXJ61NqWSQzqM/wJu3Dm/+WoZ6/kP74e9SXvcaPLkrpm1jIesTZ6rPyKSCnSlDY75ZKTPdb+ZZiNL0hfPzcSDOy9WoWBWWNJXQ3hqg7ZBZR7DviUOE/IFsYbggCkiSZFLgJlW0lIqh64T8YyRjcaS0MZLxAD7TsfG69WkDy7QWMz/Q+M3UTD90ZkCOh27o+PuDhIMJLDaTTnghPMayxc3yC76IKFrZ+/jbJug1nMe5gb//sezfB558H7qepHycyvhMyEwy0xka41N0Jhsa04238ThZYZuh66iJ5GkbCovZ0IC5RX7WXr02y96x5R/bZiwYngmSomSNldNBae3LqKh7LaODTxIea057+00l6PlA1xL0tf2BVGIkzXpWe1r9AlBsdty+xhnrBcJjhzi6+y6O7r6Lg1s/wMGtH6Bl7+fpPv4rRgefBECSndSt+uCsLGy5RZuzqaIZRIItJoOOodNz/DeT7jUOiAx2/SurYXAyjJ+DJ4/f6d6rU13/eo7/OquOnVO4idoVN1O7/N0T0qDi0R6s9kL8fY+gqbGZmkof24ekuLJivf7+x9j6r2dnI9ydR3/Ioa1m5MEwjCkRipNDoHbFeykouwZDVxnufYihHlM1OxkfZmxoO4ZhoKlRgqMHkRUn1U1vJ7fwQhKxgWw0ajxUNYrFVoCcNkDP48xCkqw0rr+TWLiTnQ+9kp0PvQJVjQKmGOGRHbcxOrCFZGJk2vER8O8BoLvl52z/z8to3nUnR3Z+El1L4svfQHndq0nEhmk7+K1prz+fTfP4Y4Nju9j9yE0k4sNUN70dgIGu+/DmraUyreszHRayLjRTrzd+Yz5epy4zz2cw09+nct2FODfDAjbdmixKU6Pzs2Fed+PwuDmyuxN/3xi+Qi+pRAqn122qWEsS0WCEVCJJKr3h0FKpiR3XNMS0DoQgiNlJeCHSBRYrMp7ejNKxK8drUmJy8sEkKzI2l3PCZ4lonMDwGF3Hehho700PZGFBjDeLLY9Vl9yNmgox0HXfabd3HqeHNZfeQ1XjCcaWJStvxeWtn/UcQRSxe2b2Qs42kZ5sk2/oOrVrpme/GX/MecDuB3fPO9yfgShLU+bOU4UoKhRXPx8ANRUiOHoYARlNnXuKgL/vUbbe/3y6W35OQdnVWO1F8+5HMu4nOLKPgH8vsUgnNpeTVDxOInmMlr1f5OieO+lu+RWaFs9u8BOxIcA0KPJKrqBh/R1svv6+bESmdvl7WX3pPXMSJswpupBYpIvwWDO6lqS/46/Z7+zjdCcA8oovZcXmLxMJttB64Otzuj9XjnfaOXimhXqm93C83tHo4DaGeh5m/5abGez6FwArNn/5pEXRnpzl1K54L6HRgzz17xvZ+/g7CM6Q9mZzlKClwhzf/1UA8oovo3H9nVntg8qGN2WJKKKhVp761w2MDGyZ9frjkUqOIskOXN6lHD/wdVr2fRldS9HX/ie6mn9C26HvAAatB76RfdaF5dcRj/ay48GXk4gNoqZOjNXmXXfRceReKhveTGj00Jz7cR6nB5evgQ1X/Zqa5e8hERugZe8XObLzDg5v/wi6nqK/82/sfOgVbPnH1XQd/emEc2uWv5uSmpdgseYjyXYzWmno6cLtYqoa30ztipsZ6Pwbo0PbJ5yb2aTPxQDobfsj/r7HUNUoLXu/yP7H34/Ts4S1l/84y9omCCKyxXNSQoSTOd7mi8kkIcC0e+RzVbMxE2aLkGipFN6iudXZwTzTqPJKclBTCoauM9g5iKEbCKJAIhJLF46oiJKEmkpNyPuSFAVDN7DYbGiTwmGK3bYoHuqZQsa7HB41i5Myqr7ArIxRgihSVl9Oy84jEz73FeQwOjBCyD+WfW4LaYkrFg+ltS+nv/3PlFS/KKsaex7nBpZx/PJFlc856fGGrp/RIuzWPUcXtL1nGgnBTMJ888H4mo05UTueBNFgKwBHdv4fNmc58XR+tMNdS9MFX8CaLsxOxv2EA8dMCmVBwDB0krFBjh/4GrmFF1Kx9A1Z5eIMErEh4tE+kvEhkvFhUskxNDWa/i+GzVlKItqPf+DxCbljDncNifgwWiqEzVGKpLgY6n6IjiPfQ1JcbHrWn8gruZxVF3+Hwe77Ge59CH/ff5EUF3aHmSueX3ZVNr3qZMgt3IzNUUr74e9Rt+oDjA1tx+GupWHdbRPuKZM24M1fS83yd3Nsz2fw5q0z1Yxl54lickEgMLwXQ08iW1248jdOmYejoTZGBp7Ck7sSizUXAx1Z8RAONGdraAa7/43TU4/TU8tw739p2fdFNl7zOyTZQduh75CI9VNS/YJs8fxg9wMMdP2DyqVvIKfwgpnvt+gi1l7+Y4Ij+xno+if7t9xMXvGl2BylWO1F6aLytmxhb3BkP7quIooyeSUnmKtsjhJI66coFh81Te8ip9BUu1ZT4ZOmVzXvuhNNjbLm0nvw5a/H7WukqPJG9m+5GcMAXTfrFmtXvo9o8EQ03eldStOmz2MYGlvvfy5lta/A5WvAV7ABTYuz97E3Y7EVEgt3Ur3srbP/+OcxJ5xsLlasPoqrnoeuxRjoug8tFaF+zcfIL7mc4b5H6Dr2M+KRLgZ77s+mK4JZO1W7/N3ULn830XAHB568hdHBrSTjw1mjtqjyOfR3/JX+9j9PqC+b6zwa8O+l7eA3AJAVD7qeonHjx6hofAlaMkUiEsMwdBKxAVze2ZXoZ3IQPN2QmctOR818tufvzsvhRa+o4v6fznjIBAjGHOKiwWAQr9fLta/bipYU8RXmMtwzkC36LKouyzLOjM+tm0zxmBGiyxRGu/N8hEcD2VSrhcJi3cCMz6EfTwE6XY6gKEvTKpE3bl5O19HuKSrkCwlVjbL74dfhylnGsg13nbHrnMfJkUoGOfDkLYDG2st/fEavdSq5qiV1lfS1dM74/VzexdlqS55OWMh5R1KUU1ocpkMiNkjn0R+jWLzEIz3kFl8KhkbboW+TW3wpdas+QHfLL+k+9jN0PTHl/JzCzTRuuAtRTOcZq1F62/6Av++/RIInxCVFyYbFmoskO5FkO6JkJRpsQ1JclFQ9D2/+egRBJDh6gIGu+wiN7KNh3R2UNzyb0YFmdj30GgBsjjLWXfnTCUrEup4iNHoIf/9jDHT8DZevMatiPVeMDGzh6O5PZ2lZZcXJhqt/O+PxhmFw8KlbCfh3ZT/z5K6kvO41hIP76Tzy8+znheXLKKt/LxgO1FQImyvEzgduRzdSE4ysivo30Nf+BzZd+xcMQ2PHg69I036+gkRsgJH+JyisuB5JdhANdxLw76ak6vnZ80OjhzGAVGIESbbjy1930vs2dJXu479mbHgHidgAydgggiBhd1fjcFXjzVtDYcUN86K/DQeOse/xd7Dy4m/h9s28eTMMnVQyMMFpkkE03IWaHMOds2LKtTUtTnfLLymrfQX+vocZG96JriVZtvFTAIwN7yEW7iQVH8ZAo6rxLXPu+3mcPjLbRsNQObTtwwSGd6FYcnB5l5JbfDHFVc+b9ryWfV9moPNv5JdeRe2K92XpuAE6mn/AYOd9bHzW76c9d8a+6Cp7HnsbomShuOp5jA1to6rxrVNERkcGnuTw9o+y4sJv4M1bNWN7Vqd9gpbEeUyEbLWgpVSWbmikodHCh1/mIxAI4PF4Zj1vXsbGxc97gNpVyyd4NwtryhAFkf7WrpN2UrHbcHrdBIdHzEiH3YqaVE+ZQenpgukKXmfjWp8pN16UJcobqult6Zo3T/t8MdTzIEd330VN07sprX3JGb3WecyOvvY/03bwW1x4w78QFli4TxBFrA77GaP4+1/BqRpMM73rGW/UmfSw9bX/hdYDX83+u6z2FemUKwEw0gXXIhZbPsn4MKHRg0TDHQx23UcqMUJu8aXkFl+M012LxZaPJDvnvGFNxv0IgoTVmYfVYcfhcXFk2084uuuzrLvi59hd5TOem0oG08bC3IuWT5wboLf1d8SjPdic5RRXPR+LNW/Gfhu6SiI+hCDIREOttB++54SoZs2LKa15CanECG2Hv0Vo5PCEc/NKLqdu1YcIjR7k0LYPYXdVs+aye0nE+rE5yhAEIau8Pb64XVNjBEf24/YtyyqqT+iTYXBw663YHGUTNDbmihOsXKeeeqtpCYZ7/kNO0UXTGhLNu+7Al7+BosobT6n9aLiTA1veQ8P6O/DmrZ5RcLav7Y8ERw9S2fAmDCOF3Vm56IVpnwkwDIOxoW10NP+AaLCVpk2fSzsTZn/2Af9eDjz5XpZf8KUptMhdR39KX8ef2fSsP87ahq6rxKO9aKkwdnc1Q93303rg66y65G68+ctndND0d/yV4/u/xqZr/zTniOh5TIRstWTrs5/1orXEIkE++fqcORkb89q51K+to/3QCS+mOy+H0X7/rIusbLWkjQkDNZEk5B8DzBSiZCyBKEnIVsszwrM5EzIbhvEWs5ZSZ/Qkz2R4CYJI1+G2s2KY5ZdeRSTYQtuhbyFKVoqrZqZQPI8zC1lxYxgqyYT/lPLlZ4MgCiTj0797C+WpX6yRxoXCeHXw+WKm52KxW8+4d23yYp+IDzHc+zCaGsHmKMXlW4Zi8dJx5B56236PoadQLD7cOcupbvpylvryVGCx5WF12kklksTDUeLhKG7vSmSLl86jP6Jh3W0znjveGzpfKBYvVY1vBiA4so8d/3kJDncNOQUXoGlxZMWFzVGa9fSbeeWmh9RqL8BXsAHFHiQWlLA589BSKWyOElZu/iYjg9uIBFtIxAYZ7Po7/r5HcLiqqWy4iZyiiwj694IBducJQ8rcnE3coCXiQxza9iFWbP4q3mnUuAVBoHHDp5CkU6PYPR0jIwNJslJUeSN97X8hFm6ndsV7CY4eRBQtuLz12JwVTL6v+cDhqmT9Vb9Cku3pPk/fVknNiyipeRFth77DcO/DVDW+FdniIadg03mj4wyi9cBX6e/4K57clay48GszMjtNhid3FVZ7Ef7+x6adf2bS/smkUsYi3cSjveOihQKCIFJYcQNuX+OskeB4pBdBENC1M+uofaYi4xhbc9lyiosd/PXHj02opzoZ5mVsaJqBYrWYXMeaNqH+YDoodpuZNqUbIJpCLFkueT1lWkgWGUEQefpnyJ0cmc1DJqoxXwpgU8zm7GzaBEGgqvGt6FqS4/u/gsvXkC2yOo+zh2ionbZD38blW4bFevJC2JMhk85osVuRJIlENJZNaxREEUmRs1Gzk401Z653SjrfdIbFM9XQOPEen/79TY6MnI0wfmfzvSjWXNZc+n3GhnfQdug7jA1tQ5IdJGKDQJpBT5Apr38NJVUvyGpYnC5GBp5kpP9xlqy8JRutszlLsdoKkJXTo9WdKzIFxtFQ2xT2vWRihIr610w5RxAk1HgOimUioUJXy8/pOvrjKcdnPPuxUAeF5dcjSidfch2uSjZc/dtZIzey7EBVoxx86lYKK66fkGp1NhEONJOK+zEMneadd5BXfCkubz1VDW88rXbHhnYQi3RTUv2CKd9NFw0qr3s1up7i2J7PAvq0nvPzOHWMz84Y7v0v/R1/pXbFeymuesG8jDpdT5JMjGRJGZKJEQa77iM0eoiRgSepnDRuDMOgu+XndDb/AG/eWnKLLsLuLMfmrECWHURCrcQjPZTWvnT662lJRge3Mtj9b0YGHqd62dux2gtO8Sn87yGTzpupty6uLiEcTPDQ9pZ5tzUvY6PzcAfv/8il/OLX3fQ0t2c/b9y8nNBohN5jnRM5jmNxUukOZzjjYSIXvaZqqInYgnIbL3acSgrUQtBgzvuagkBN0zsY6PoHHUe+T37JldjdVXhylp/VfvyvwUjTcQ52/ZNYpAubo5RlGz+zIClUhq6TisVRE8kJaToZI2Q+HvrISABvUd4EWtf/lZQss4hw4fQUUrH4CU7zszAXjgw8yXDvw9Sv+SgWWx6F5ddRWH6CB19Vo0QCR+nv+CuRYAvlda/O1mwsBDQ1SioVzI5pQ1fpOHIvkWALJdUvPCvPoLT2ZfgKNhELd9J26DuIooyuJzF0FU/uzDnd02Gy7ohi8bF881ew2gvNFCDRwlDPA9SuuHnWdnQ9RSLaP6s+Rvaakh1P7ip8eSev2zhTMJW/4wiCyJrL7snqdZwODF1luO8RdD1JsfG8Kd7uVHKUnQ++kpyizXhyV1Fa82LikV4GOv/Ois1fRlKc5x1jC4zxhnUsYqbMD3T+A5ujjJzCmZW4J0PXYhh6ikjgGMf3f43BEWxI5gABAABJREFUbpNlzZ3TRGXDGylf8orssYHh3XQe/SHBkf1ULn0jpUtexujgVkIjBxjz70FLhZBkF43rbwdMtr3j+79GeOwwmpZA1xPoahzDUHF6l1K74pbzGRrzhK5pWOxWVl7cSHA0xiWXFPCvf3SgWCwodhsWx9wJbee1e1FTKmMRCVmRJ32uTTA+JiNDzSpKkrnJGbeQaGmF8We6obHYhcpmgiDKVDe9g66jP2EsTUvny9+AN38tZUteOWPY8zzmD8PQCI4coL/jbwz3Pkhh+XVUNb4VX8H6OYmonSxdaXwdgMked2I8ZoyQ+WKyfsRkQ2OxOBEWqh8LGc2YjEz/zvTzCgzv5vi+L+Mr2EhB2bXTHiPLDrx5a3CnHQsLaWgAFJRdTUHZ1YA5Nw73bqen9deULXklhRXPPitjRhBEnJ5anJ5a8kuvOK22SmtejGLxEh47Sk7hJnwFG7LpSkM9DxALt5Ffes1J22k98HUCw7tZd+XPTjq3GoZKzSkKD54KJs8vmpZAkqwoVieGbqBYfKd9jZ7jv8HmKKVu1a3ZQv4MDENnbGg7dmcFlY1vJhEbzM6LDncVKy/6ZrZYPR7tIx7tw5u35vwaNUfMNd21ov61eHJX09l8L4e2fYT1V/1iSjH2TFAsPpzepQz3/ReLNZfSmhdTWvvyKamRHc0/oDstaltUcSOJ2CBb//VcDOPEmiVKNnQtjq59lHi0h8PbP4GaClJUcSPuvAKsdhepFFgtS6ew6J3HzMhq4YkCFpuNgooCJEnE0A1+ee9OZEXBYreaTst5pFHNq0B88w33kVNchtPrYqC956QLQiYtI+MBnEl1+JmaZvFMg64lGe59iN62PxAJHsPpXUrdqg+cUS/SYtmsnmmkkmMc2flJgv49iKKV+jUfIb/0ygVrP1Mv9L/4vi3UPYuyhKQo0xpl49nlFiMMwyDg303P8V8xNrQdl28ZjevvyFJPngyaGsvmz58uOo7ci8vbQF7JpdnP1FSE7Q+8MCtcWTWL6NZixZor17Dn4T0TPtO1JDseejmS5GDJqvfjy18/4XtNTdDT+is8uavx5a8lFu7CMDQc7upZr5VKBti/5WYql77xtA2lU8W+J96NxZbD8s2fWzCSl8PbP47L10jFNOKlycQIO/7zUupWfZDCiutnbafn+G/oPPojNl9/3/najQVGhoFQU2Ns/89LKKl50bze15mK/REEwmNHGep5gN7WiSxxgqiAoafJDURyijYzmtZ78RVsJDhyAJujhMYNd2F3lpnZNJr2jK8HPhPIZCC583yoKRUtadYX/z975xkYx1W14WdmtnftqvdqybIs95riVEgIvQYChJJACKF3SIAUIAkQkhAIJaGE9oVeAundcdy71XvvWq22l5nvx2o3ktWllS0nfv/Y2p25987szL3n3HPO+5qSzPQ1d044NhzysOfxKxJfIC6pVbj6h3D1D8UHNZ0haLBZ8DpdhAPBGXf1X2uGz5kMUdKQmnMZKdmvj08Ix3Z9mpWbvjsnCsZp253hOXotOBrhkIfGo3fhcTVQvvlOrI61iNLChS6net9iNQCvxfctEdcc07zQGvQ4p1i8lrOjEQl7qd5/IyMDBzGYi1ix/pskZ1w4ZyOso/H/6Gn5Jxsu+lNCDLeRgYOTCp9VaiOrt/+YnrZH6Kj/PQFvN/a0c7ClbERRZFRq06ILm2OGSuwaEhVtjhVOnuxoAPR1PEYoMAxaidHh6gnOhrN/P3WHvoMgqlBrkrAlr5tT+hREtQQc6edjsJy+Hdu0nDdgspUl5B6Gw16ajv2IlOzXTStaqNHaWbfjt+jmQExgS9lER8MfGBk8tKi16bUIUSWh1moIBYLxXP1IKBRfi2NU55JKT0rWpfS0/IvM/HfMuZ5rujmks+FPtFT/DJXaTHbx+7HYV1N/+HvRlKiIj9Scy+nveAJFiTDcu4uk1O0kZ+6grfZX2NO2Ulz5pXiky2S3oNFpGe4ZWPwNeQ0hRuikNeiRwzKiIOLIS0cQBFqPz79OY0Lb8zk4HAiiGqesOJMh6HW6gLFdxflWQp/FmHKmsCyNbUEQSM1+HY7086ja+2Uajn6fgpXX48g4D0WJUL3/JjLy3jKj6NR4xK7xtbbrrigK/Z1P0VJ9P5GQh6LKz88r/3U6nInpessZokpCjkQwWEzojDrcwyNLTj2dKMhyiOp9N+IeqWHlpu+SlLpt3g5DUspGNFo7KBEQFl83VL75jjilqyyH4ilaJlsphZYi/J5OBrqeo7/zKWI0vKKki3L4p51DcuYF82JlG+x5ic6GP+BxNYAgojfmoDflkFX0XkzWkkVfz3RzlqLItNX9FlEyEA66MFoKUZQIfm8PemMWRksxBkshocDIvCliowQeUVatUHCEhiPfJ7/8uglMV4nCdJtBtpQNjDprMFoKF91HlMp49noPvSmboH+Qrua/klPygRnSSxXUWjsjg4fPOhvzhByOEAj7UOt1BLy+GdfknBUfZKDrGRqP3xOvnVgoTLZyADIK3kl28fsQRTWFFZ+l9uC3AZG+9kfjQpxDvbvIKHgnkqQlJet1k+a00UEnRqsFlVp9xszVpxOxFGtBFFGrJOwZyQx1Rx21zrq2uE0RCyKMP2+uWJJkxvEDiMq0K/Ma1FmANdWxLB2N8ZBUejIL303A201n08NAlK1FHDNIZDlM7cFbcDtr59Tea8rRkMM0Hb+b+sPfwWKvZP2FD00o0E0kYmHRs+/g/CGIItml+eSWF6Iz6uisbTmjFq/hvr2MDB6kbONt2NO2LygyMdizk4C3J2EaLyqNGUWRObH7ixx/+XOMz+QVRRV5Kz9G8Zovs+Gi/6O48ousWHcTuSs+hEptprX2AfY//R5O7PnSrBSWiqLQcPSH1Oz/BqJKT17ZteSu+DAmWyluZy1Ve79C04n7cA2fIDjGqJRIeFyNhAKDyBEvWmMWVscGulv+xYndn0eRw6i1Nso23ErJ2q8giipCASdyZLKo4mwI+gcIBgZRqeavOzITYvPFdOtQf+fTNB27e8rfITbnzBWSpKOw4lPTRjXGwz1SS1/7o4wMHp72mKHelwn4+ggFlk789tUKncmIwWZBDs+eGqfR2ims+AyD3c/S1TyzPsZssDoqySh4B+11v+bwC1FHeqDrGQzmQtZf+Duyi99P0erPYjAXkF18FZKkBaaOlGgNejR6Ldmlc4sULhSvhjVVVEnxumpJkrj6E5vjjobf7UVUSSRlpvLA3UVI0sT3Oqcsf879LHr1SMpMZbirb8LAT56cFFl+VfwoS4Hpdo2cPf2nYTTzhz11Gxpd2oSdxryVH6f5xI/xutvwjrYQMyWGenfh9/aQWfB2IPqivufj5/J/978woc2+9sdwDR+nuPKLp+oyTjlaqn9OT9t/KKr8Ium5b1zSvsazv53FzDiZMa9o3QpajjchRyLL3vmfCkM9L6AzZGJ1TNZrmA6hoIvWml+SW/phNFo7giAlvMhWEEQKV38Wv7c7Lm431LMTrSENs60sXuirG7fjn1V0JeGQh8GeF2g48n162x4hY2wumQrDfS/T2/afMRaaN08wSgL+AZqO3c1A59N0N0cViw2WEnJXfDBemGyyrUSrS57UrqIoBP39BP2DgIzelI9KbZx0XG/bfxAlHUmp28YUv7XojVnRDRpfHzpjJv2dT9Bc9RM2XPQn2mofxO2sZu35v56XU2i0FLHm3Puj1OjT5cMvALPNF+n5byUj/60IYvSdGb+WzfauKIpCODiCWmvD5+6gu/WfpGa/bk71f0mp29Cb8xnseRF72vYpxh2mr+NxclZcTVbBO2Zt77UMaSxTRWvUo9aqkcMyQb8fv9s/5/kuJeti3CO1NJ/4MTpDBva0bQseT+GqTxEOuRkdriIYGGKo9yXyyz+J3pgVj+TNBeGxOuHGQ3WzHLk4nKlraox9MuY8RCIRRFFAZzLw599XjUlcKKTlZ+EaGsHVP8w1n+2b1E5XY8ec+1yQszGeE368owHTTzJn6o+y1Jjufp0pKUWCqCK7+Eqajv+Y7OL3YrQU09v2CMN9uxnu2w1A84kfU7Lmq7idtYw6q8kseDuKInP4+Y8x0PVBHOnn4hw4QEvV/VRsvxfGCV0FfP201vyc3NJrMFiyzkiD72S4ho7R1fwXClZ9askdDVjeKXnLCYIootZqSC/Ior2mGVGSaDhQc7qHtWAE/YP0dz1DXulH52WAipKW0eHjuAaPkpx5wZTFuomA3piN3piNoigoikx36z9Ra6ysWHfTtONVqY2k5VyOa/AwrbUP4Bo+gSVpFUmpW9EZMyccG3UGRFIyL5rUnlaXzMpNtxGJBPC52xjoeobOpj9Ts3+imKDBXEBS6lbsadswJ63C526jpfoXDPe9PO4oYYzR6hKSUjdjTS5koOswPa3/RqWx4XO3kr/y4/Ex9bb9D0UOkVV0JcmZF2BL3ohWl0xmwbuQIwEEQSDoH6Sl5hfklX50zkX8w327aTj6A9ad/6uE6aHMBJXKgEqroav5j3Q1Ps6ac3+GIERFeiOh8IzrV1vdr4iEvBSs+iTe0WYCvl50hrmJRAqCwMqNtyKpJjt4EF2TDKZcnP370OocJGdefLZI/CTE0mZElYRGr0UURIK+AAaLiUgkMm+dn/yV1+Hs38dg93OLcjYA3M5aVGoT9Ye/hyBIpGTNzuJ2MkI+P1qDFkEU5q1n9lqAKEXrctRaNYqsoMgKSel2+tt7CfoCcT28mbT0DDYLXtfgtN+fjAU5G7E0gtcKU9DpwJngaMSQlvsmulv+QdPxH1Ox7W60uhQEQWLNeb8g4Oul4eid9LT9g4LyT41LmRAw28pQa6xAtODRnFQRVQMdx/kf9Pfh93QhqfSvmmfNOXAQldpMRv70u7KJgiM7ncGOnrMT7hygyPJY3qqAIiuEw2dOutRU8I42o8ghklK3zun4gH+A7ua/kV3yAdbt+PUSjy4Kv7ebIy9+nNINt4wZkHMT9Msv/wQqjZXR4RM0dz9P04l70ZvycaSfS3r+W9HqkscMbhn3SO20Am+SpMVkLWFk8DB5ZdeSmv06REGNLAcZGTyMs38vfe2P0tn4JyS1iUjIjVrroGTt1zBailAUhZaq+xkZPIjP3U5rzc/jbetNeaTlvpH2uofw+3oASM15Pfb0c1CpLYSCI6g1tjhl7PjaB7+3G+9oc5SFZ47QGTJJz3sLqrE5dakQy1JQZDlKACOmkl3yvrGoyvQ6UuGQB7+nA5OtFKO5EJ+nHUEQcWScN4GZbCZ4XE2MDBwkKXUrKrV52uOKKr9A0/H76Gz6MyODh6N0qEkr53+xi8By3jBUZBkZ0JkNqNQq1BoN4ZEQzt7Bedf8KYpCb9v/CPoHEJLmpiQew1T3KLv4KhqO3olKbaFs462TaHHnAlEloTNo0VtMk4RnX8uIbzxGIiSl2QEoKE2jubaXjjH5irnYWWq9jvLNJex5tHfufc+H+nbL6/87Zbj4LM5iuG8PVXu/QtmGW9Ea0jny4rVUnvNTzEnl1Oz/Jl53K+t2/HpCOsZ8J+Nw2EvA25OQgsSFwjV0lP7Opwn4+0GR0epTEQQ1QX8/4ZCbpLRtpOW8If6eTEUZ2nTiPoZ6drLx4v87HZdwFlNgKjX0Mx3BwDD7nnwbpeu/PSd6VL+3myM7r6N80+2nzDBTlAiNx+8lFBgip+SDCyrYDoe9jPTvZ6jvZQa7X0COBLClbMQ5cABz0irKN9+OJOkWMUYZt7Oaob7dGMwFONLPm6A7Eg6N4ho6hjV5A25nNaHAMJLKiC1l01iKWARZDsdzzAGq9n4Nn7uVDRf9cYZ+oylR4bCX9rrfklPywRnX31j611DfHvyeblRqI/b0cwj5h9CbEl84rtbrCPpcKDKIombWzceh3l3UHryFTRf/JU4QMF8MdD9PZ8OfWLX1BzMqrI/vs6Phj8gRPxZ7JTpjNq7Bw6xYd+OiGP+mg85kPGNETSW1Gp3ZgMFsxO/2EfT75x3RAAiH3Ox5/E0YrSWsWHcjhjF18MXA7+1BpTbHn/cYS9J8NhwFUaRkfSltNW2zFrq/2hHbINDotQiCiCXFhjhmi/W1dc3pvsY0psb/7XcPLw317XjEUqmWs/d+FqcOSalbsKVsprn6p6w5534EUU1P2yOYbCvJLHw3x3bdQH/n06RmXxo/Z77PTePRu/CONrH2/AfjYfFw2Et/+2PY08+ZF0PNyQgFR3ANHSfo70NvzMFiX00wMIQgiPF2FUXm+MufR1HCJKVuRRAkRodPIMthtPpURElDa/XP6Wv/H5mF76av/VFcQ0expWyidP234ouj1V5Jd/Nf8Xk60c+BxvEsFg+VVoNGryM5KwVREmk5Wj/h+1ebowGgVptRqc14XPWTnI2YYeodbaG56qesWHcjOkMGmy/9+6IpZucDQZBQq80M9by4YFE4lcqAI+N8HBnnU1D+yTFRzGfILnofWcXvm2DkT4fuln9iT9s+ZcqSIIiYk1bFBQ4n9a82ozNk0dv6bzIK3hmfm/zebnpa/0Ve6TVIkhY5EqC34zEy8t5CQfn1eEdbZhxTrB2vq4GBzqdJz3vzjM5G0/F7Geh6hnDINe7TaBuV594fr4NJFEI+PzV7b0ZWQqzacieKPP2+ZTjkwWwrZ+XG2xAXoNcSc7ySM3bgSD93zs+oPW07tpQtdDY+TGfjHyis+AyipIs7GgFfP1p9yrzHMx3OFEcDxtShdVrCoTCWZCtD3aEF2XMqtQlHxg6Gel+ir/3ReMrgYqAzpMf/b7RbUWRlAgvSXBCtFRbQ6LWEQyG0Rn1C5vkzMaNHEAUEQSQcDKM16gn6gowOOucVxYo5GrFnZL5EKQt2NmI1G2cdjbOIoWDVJzn8/EeoPXgzaTlX0NP6TwwWK5n515CceSFNx+/G6qhcsFOQW/ohRFGDIAhEwl4klYFIyE1z9f3oTblo9WnIkeC8dqx8nk4ajtyJa+gooIAgMiHnSBDJKf4AmQXvJBgYQFHC6E15lG++fcr2vKOtnNj9BRqO3IE5qYL88utpr3+I6n1fp3zL95EkLbaUTUgqA30dj5NX+pEF3YuzmB8MFhOiJNFe3fyamLMUOUzd4dsJhz2TisNrDnwLrT6NgvLrUanNKHKYUHAYtcZySh2NGGwpm9AZs9BMUYw9X6jUJrKL30t28XvndV5/51N4R5soWv35BfXb2fhH+joeR2fMwZ4WTVsLeHvpbPw/RofrWL39Lob799Je+2vSc65Ab8qZs6aGxV7Jhov+iChpkOUQvW3/Iy33CkRRhSyHARFRFHFknI+zfx/hkIuSNV9Fb8rFPVJHT+u/aKn6KRXb7klI7YKoksbyvGXCEQ+RsJfe9scY7t1F6YZvIwgi1ftuJCXrEpIzL6C97iF6Ox5lw4V/nDadbTY0HrsLrT6FnJIPzvsZFUWJrKJ3I0e8JKVuJTX7dUA0Sn385c+z7oLfLummT8DXh1pjG/v9wsiRwLLIEBFEgYDXj95kIOgPEgoEESWJyALmx5I1X6H+yO10N/+dvLKPJaxGRmvU43WOLnjOrj9YG8+msCbbMFpNk4Tp5oszz9EQEYSoBIUoSWgNOkb6Bhd8HfbMVIZ7+ud9/rycjbOMUkuDV0t0yGDKo2zjrbTW/BJX+3GSUrfSUvUwXpeTworPcfDZq+hsfJjCik8vqP0Yh7yiyBx6/sNk5L+NrKIr2f6GJ4Gowuyxl24gv/wTONJnzwEe7t9H3cFbUGmsFK/5Mrbk9Wh0KXhcjbidtWj1qbhHqmmr/S3t9b+Nnxf09xOJBKbcMTWY81h3wW8I+gcxmPMAMNvKObHnizQd+xEla7+KpNKTnHkxva3/IavwXTPmHp/F4mF2JBEKBPG7vcvqPZvqvU/EXOAeqaf5xL24hk9Quu6b2FI2Mty3Z0wsUovFvgadIVpMrdE5qNh216L6WyysjjVYHWuWtI/Z7mv55tvnlJYzHTIK3kFfx+NU7/sq2694FkEQ6Gl7BIBgIEojaU87B2m9aUEUwrENFNfgEZqO30Ny5g5EjW1so+QIelMeq7bcSVLaVvo6Hicl6xIEUYU5qRydIZOqvV9mqGfnnGsjZsJ4I6Ns4xfxe9wEfX1odCkIgojOZMRozUSljaaa2dO3ozflAjIwf2dWURR0hnTUmqQFjVdRZCIh9yQ2I5NtJXll16Ib2/xyj9SjN+XOKRI2G4KBIdQaK4Ig0XDkTgRJQ/mm71Jz4JsIgsTKjbcuuo+FQDXGMiSIAlqjHrPNgqxE5Qk0eh2hQHBBOk2SSo8oajBYChNajB9L6xpfJzQfRJ/V6PM6MuDElpJEVmk+XfVty2otSCRic934OU9RZPQWE4qs4HN5pnUUZoraJGWm4uofZrCjZ0Hjmtesp8jyQuaKs5gFr6aHPhq23kT94e8y0P08qdmvp6/9USJhL6k5l9PV9FfMSatIybp44Z0oMrml12C0FE34WK1JIjnrYozmomlOjC5cQ70v0dX0F1xDR6IpTuu+OSGH2GQtieeOJ6VuxpG+A7+vA1GU0OpzkCT9jAuSSm2aYLhY7BXkr7yOpuP3kLPianSGDHJKPsBA19O01jxI0erPLvBGnMVMEFUSoiThGXEty92oqd77xc4Fg90vUnfoNnTGTFZt+X5csbrp+L2k5lxOTsn749TTywWh4AhDvbtwpJ+7ZI73bPd1MY4GMIGydbhvD0mpWxjoegqAVVvuAKLpWLbkuVMQTwVbykbWX/hQXFMjLfeNWB1r44J4kbCPSMgdvZ8Z5wPROcyWsommE/dGj11AvYSkViOqpHhGQwxqdTaWXBORUJCh3l24R+qBEnJXXB9XaDdaijFaihd0vaGgC7XGQnbxVQs6H6Dh6A8Y7n2ZynN/is6QEf9cFNVkFb0HgN72R2k4cidrz38gXvg/m9EsRwIIonoSLXTAP8Ch566mYNUNpOVcTn759chyNOUkc4wUZLh/HwIikko3bXreUsFgMWG0mtDoNYQCISL+COFQaEIK2HxThRQlgrN/HylLpBWVCBvJMzSC1zmKKcmKKEnICWp3uUGR5Xj0MQaNTjenCNFUv7nZkYTeYkAOy4sSDF5wqCJa1S7OW7znLF79UBSZzIJ3gyJjsVeSlLadwe7nScu9gtTsS6k7dBst1T+fs9jfyRBEFanZl04qFBcEgbzSj6IzZhIOuVGUV16c0s3lrD6vgqbjd1Oz/0ZApnT9t6M7mjMsvjqTkdzybWQVX4YteRtmeyFaw/xzfKNGlBJfmLT6VFKyLplRmOosFo7oro5CJBROuEbEcoNz4BAn9nyZg89+gJoD3yQpbRuV5/4s7mgArFh34+Ic/CXE6HAVjUd/SDh0+vLdh3p3ceTF61Dk8ILbKN/yfQCq932VzsZXCr972/7LHHhY5gy9MTseHbE6KknLfQOOjHOBqAq7Vp9BZ9OfJ5xTXPlFImEvDccWdp8joRAhn39KgVCfy43b2YV3tAlFiSCqJKxpjgUZJqGgi66mvwDgHW3hwDPvxdm/f97tjEdRxWcoWftVdIYMFEWh8diPGBk8MuGY1OzLWHfBbzCYC1AUhao9X6Kl+hcAhIOjdDT8ieaqn9Fw5PtEIlGHq6v5rxzdeT0AciSIa+g44dAoWl0yhRWfxZEW/U2MlsJ4vYwtZSOipKFqz5c4sefLeEdbF3Vtc8UrkQEFvSXK+GZPNaM36dDoNBitJkxJVjQ6HYIozsvR6O98it2PvZFQ0ElyxgVLMfyEQZFlRgeHURSZlLyMV222jiIriFL0PYRoLVHM0VDro2QZZsfskUK1XodKq2awo4+B9u5FjWnBdzqqDC7P+aF8tf6oZzEZVXu+xNGXPoHWkEFS6lZK138TUdLTfOI+ilZ/gayiK+lu/jtHX7qegC/x4oWKInNiz5doOPr9+Ge1e6t4/KGb6WmNCumt3v5jkjMvmDb/V63XIanVBLw+fB4vfrcXQRQJB4IIojCnF3U8/J5OREk3IRXAYCnC524j4JsslnMWi0OUvlaOpg28inl/+zuf5sTuLxAOjWJL3ULxmi9Tuv6bEyJvoaCL1tpfEg77Z2jp9MGWvJ5tlz82oSj0VEOltmC0Fo9p/CwMSSmbsKVsBqC15pdANHWqo+H39LT9OyHjnA0ZeW+hYNUNjA4fp+HoDwmHvQBo9WkUVX6Bwe7n2fvEmzmx+4uzFqifDJVWM61AqEabTOW5P8doLiDoH2Wkd+78++PR0/JP+joeB0BvyiFnxdWY7fOjUz0ZoqQlKXULAJGID6+7lXBoFIgWiHtcTQiCgMGUN5bbHsaRsQNbStRZ9/t6aK35JZGwB60hnbbaX6EoMraUTSRnXQRAKOjk2K4bcA0dAyA1+9JpN7GM1pVkl3wQo6WQlKxLUOTwWERo6RCbCyOhEJ4R99i9UFCpJFRqCZ/bh3t4hHAoNK/dfr+3h8Zjd2FLXs/q7feecnrhhUIOR+hr7nxVRDZElRQXZ4Toe2pJidoZI72Dk64xFp2cSUMDoja7wWLEPexaVEQjPs5FtzAHqPW6V8WPulR4tUWH0vPeDIBaY8M32oIk6SjbeAvO/gO01PycvLJr2XTp30AQ6Wz806J2/aa6d4Igkld27SQdi/6OJ3BknD8nIb2Qz09kbOL1DI3EnWuITlSzvagnw5F5AbIcpKv5L/HPUjIvQZQ09Lb9F4BIxI93tAWfpxPnwKEJkZmzmB9iRlHI55+RJedMRijgpOn43SRn7qDynPsoHEvbiEVy/J4ugoEhwiEXIwOHOLrzY/g9Xad51JMhStoF1TEkEhZ7BcWVX1x0gXzR6s8BUeN+86X/ZOWm75Ce9xaaT9y35AZlDPa0beSVfZz+jidoOnY3kUgAgJTMi9hw0Z8oWPUpAv5+juy8jr6OJyacGw6N0t3yL2oP3krtwZsZHT7xynezsM8IgsBgz4vse/LteFyN8x63HAmSXXIVZRtvG2tPIqvw3YuiLT4ZKpWB1dvuxp52DgBttQ9Sdyjan6Io9Hc9gyCIpOe9KR4ZNFlL2H7F0xRWfBafux1n/34EIaprkpSyBTkSRK1NxpayGUGYWRels/Fh9j/1DrKKrmT19nsQJQ1tdb+hs3HpadCjG2XRuUFUiZy/3Yo91UR/ex+jg07kcGReDEOKotBw9E4klYmStV/DYq9cqqGfEZhuQ322jfbFbsTL4QiRUCjucIQDQUYWoJdyMiS1ClGS5s06NR0W7WzE0qlmwsl5nmfxCiwp9mWZT74YpGRdQtnGW4mEvRzf/Tl2P/YGUBQKyq+nu/nv1B26DZXaRF7pR+lu+TvV+76Gx9WwoL5OvnexZ9GWvB6LYyWKoiCqJDJX5CHLAbT6yYw3klodj2SMf5YltRqtcf40jVPBYMols+CdtNf/Dr83WmClUhtJztjBYM9OImEfex5/E4ee/xAHn72KE7s/x67/XozP05GQ/l+riIkYvdoQCrrGIncChas+EzeSW2sfxONqjNI07/4cXU1/RW/MZtXWH5JZ8C60YznrsR3v5QBn/36OvvRJZHnxu2cLRSTsI+DrW3S6k86QQWr2ZVFdjTGK14Ly6zGY8qk98O1Tct8FQSS7+L0UrPoUA93PcviFj8ZTp3SGdDLy38qac3+GI2MH9Ye/y4Fn3kfjsR/RXHU/+5++kuYT9+JxNeB21lG192vM1f/yjrbGdU30U2gtjN99PRmyHObYrk/T1fTXUxLhitVj5JdfT+mGbwPgcdVTd/A2/N5oushw3x6G+/aM/X83R1/6BCqNGWvyeiBKG33o+avH5mgZldqELE+2dQK+XoZ6o4rzqTmXkV3yAVQqQ1zA0pxUTlrO5Ut7wWOIzYVWh5mufmip6SHo9yNHIvG1b6bfaTz6O59gZOAgxZVfXHTN05kOSa2etKEe2widbaM9URvxMdXvRGKkb3JkZKFIgLPx6lvITyVc/UOnewhLAkf6eazb8RvyVl6HKOmo2vtl3K568ss/wUDXM/jcHWQVXUnZxlvxjDRQc+DmhPQ7/sXwjLRy+MWP0tX4T7rqWhFFPUH/5IhELB85FskQRBGVNipStRCRo+mQs+JDqNQmmk7cGzdqRCkqsiPLQZQpjK2F1rWcxSusHK82Z949Us+BZ9+Hc+AgRZVfGFPKjhZaD3Q+jc/Thd/bQ+m6b5Ke92YikQAmWxn5K6OUlG5nLfufeteyebb0pjxEUXta090Gup9j/9PvhgREE7OLryIUGKK3/X9A9B0v3fAtgv5+uhofXnT7c0V63htZteUH+D0djDqr6Gr+W7xWQVLpKVnzVco334EtZRPO/v30tP6b9Nw3UbHtR/g8nVFe/pCLwa5ds/blc7dz6Pmr8Y42R1nPplA+n2mnVRBEkrMuxrLErGQnQ62xxEXoTNYVrNr6A3T6qLPT1/E4Pa3R9DeLvQIlEqKg/AZyS69huG8PelMuFdvuRWfMQhRV5JV9DHvqtkl9DPfvo3r/N1AUGbXGSlbhuyZ8HyVVWRgl8GzIXVWENc2BShtlMxMEkUgwjCgKVB0bQFRF6zPkcCS+ds5lRzwUdNFc9VOSMy8mKXXzkoz9TMJU92yp1p3YBr/OZIzXTUdZxhY3f56cJaIeYy6b7bi5YlGx64XSkZ3FawOCIJBddCVZhe+hr/1Rmo7fg0ZrH9OYeJS8smtxpJ9HT+u/CfoHkOXQlIvUQqHVp5OR91Ysjmh4V5BUDHY/h6LcOCPTyEIEa+YClcpAwapPUXvgWzQeu4ui1Z8l4OtHrbWh1ljZdMnfECUdKrWRE3u+hLN/Hxb76oSP40xGjOFmJmiNegKeV6dirKIoNB2/G60uhVVbf4hGa49/5xo6xsrNtyMIEgeffR+rtv4QsyGdzsaHGex5kfzyT2BJWoXOmE1W0ZUYxtjcwiHPaeX91+pTKN9yZ0IpM+cLW/JGyjffEdXZWST0phxSs19Pa80D2NPOQatPRW/MJj3/rXQ2PYw1eR1Wx9rFD3ouGHPgOhv+xMjgQQRRzfoLHkJnyEAQBJJSt8TrGRRFwe/p5NhLN4ASRqtPB0Giuep+hvt2o9WnYbSuwGQtRa2ZqBasN+VQvvmOGa9LUeRoAfkUc7wgiHEjPMZAdTpgS14f/3/p+m8iR6LrQMA/hNfdzFDvSwS83fS2P0Ze2bVxTRVg2ohMcsYFYylZk59vj6uRntb/UFjxqSXRuOltiaZNxozSlJx0rroqjwNVEYwGif/+rgqYPK/OxkbVUvVTFDlMQfn1CR/zWUShMxkRVRJ+9ytUtePpbGPsYYqcOMdGZzLG2/W53FMes9C+FulsCK+KXcNXi87FcoUgCKTlvoGh3pdwj9SRnvcWOpv+TEr26zCY8nCkn0/jsR9y4Jn3kVd2bVx0abEQRVW8fgRADgfQmwtOq1HjSI+qHDdX/QRBkBju30N+2ceAqOZBJBKgq/lv5JdfjxIJTqlo/FrGVI7GyQtlIqNRyw3hkIvR4ROUrP3GBEejq+kvtFT/gvyVHyMt702s2vIDjJYofbM9bTtaQ3p8B1elNpJT8gEgWtdx6IVrKK78wmljq1KUCCf2fJHkjB1k5L/ttIxBq09JqJJ0QfknGe7fS0v1/ZSu/xYAOSVX43bWUnvwVjZc9IeE1iJMB5OtDI02mZHBg9jTzmGo9yV8no4JFLAxuJ01VO//elThO+TElrIRvSmPnrZ/MzpcRX/n00TCUUNEo0vFYM5Db8pFFLWotXYiYQ9DvS8RCfvGHAsZRQ4SDAwR9A8SCgwiiGrKNtwcd3BOht/bzZEXP0ZB+SdJzblsSe/NXBDTN9FobZRtvBVbyiZEQSIl+1LUGhuttQ+SknkxBnM+4ZAbORJAo3PEz4/qbSRNm2YU8PXidlYTDnkS4mDlrCygvboZIB7NCHh8aI16UotyOPfCXP74pxZWrs3ixceijsZ4AzOGmey63vZH6et4jOI1X0Gjc6AoCh31vyPg7yev7BrUGuuir+PVgKkctumcuJgNqjMZCXijG2VBvx+j1TIhurBUdmosWnHyc5BILMrZWI6OxkIch7OOxqmBIEhEQm6yi97HYPfztFT9jPLN3yM9701Y7BW01f2G+sPfQ62xTrsYLRRedxseVx2l67+d0HbnC0EQyCh4J+6ROnrb/4vRXEhqzhvi39ce+BbDfbtJStlC+Rg//1nMjEQwZZwp8IwVGZ+seDzqrCUj/22k570FUdJMSMuYTq1aURTUGhvmpJU0V91HStbFBHz9CTW65wJBkEhK3YrOkEnA14ta60A8xQXj3tEWnAMHyMh/W0KoklUaM3ll19Jw5A4c6TtIzrwAldpIXtk1HNv1KUYGDk/YFV8qSCo9pRtv5thLn2So9yUANFrHpOOGendRe+BmjNZiRFFLwN+Le6SGrKL3xMcZi3yMOqvxjjbjc7cy3LcXv6cDUFBrk9BoHUgqIwgCgiAiCmoM5gJsKRvRaJMZ7nuZ6v03snLjbVPO8Vp9GsWVX8Y4pnO0fCDQfOInZOR3klV0JWqNjUjYx0Dn0+iNuRjM+TRX/YTB7hfY8vpH4htaHfW/IxQcpXT9jVO2ak/bTlLqloRFNWKOBkQLhbNKihFEAZ1BQ26+jRefaUWtVbPnmSo8QyMAROaR6+8eqafp2I9IzXkDaTmXoygyTcfvpqf13wiimkjYS+n6mxJyLWc6RGmiY3GyozHeVlVpNYR8/gnG/kKIaOYDQRSjivGh0Cmx5U8vBcgCMZNDMRfH4Wwk4/TAbK9gsGonh1+8Fp0xi5GBg7TX/57s4vdiMBdQuv5bVO/7OjUHvkVx5ZcSutPqGjwMgrgs8ksFQWDFum9QsvargDgh0hLLox/u34Pf04XOmHmaRnkWyw3D/fuoO3QbRksJJluUYjIUcKLW2ihdf+OchMhiUBSZ3Y+9gYLy6ymq+CwBXy8eVwNHXryO8i13TkgnORXILroSgKq9X0UQ1adcYdk9Ukdr9S/IyHtLQlKpIKrd4OzfT/2R29GbsqPidtYSNNpkupr+jM6QjsGcn5C+ZoIlaRWOjAsZ7H4WgJGBg3hHm8dSmjSEgk6aT9xHUupWVqy/CUGQaDx6F30d/yM546K46rggCOhN2ehN2RPajxb2C3NyENNy30D1vq/TcPQHbLzoT0TCPhqO/ZDc0o9gMOXS2/Zfhvv3sjIBSueJhEptJm/lxzBZXnGCJJWeDRdF9VQiET/5Kz8e15kI+gdRa+2k5V6Bs//AlG02V/2U5IwdGCzFCIKSEAc7qzSfztoW3nT1efznty8S8AawpVowW3WsK4Pa42r62nompMjMhcBHURT6O5+k+cSP0ZvzKar4DBBl1+ppfYTCis/RUn0/BnPBoq/hTMZ4h2K6VOwYVW2MHUyRZUI+PyqtZsI5lhT7ktb0xqiQTxUEZQ70Gy6XC6vVypbX//e05vaexZkPn7udhqM/wDUUE1USSc97c1xFOxLx03j0h/R3PklGwTsoKP8koqRatHPYfOInDPftZv2Fv1vcBSwxRp01HN15HRAVCUtK2XSaR5Q4LMTJjymhvtY3B9wj9Rzb9Sks9tUUV34JrT4VZ/9+qvffyJpzo4t847G7saVswJE+N0Otp+0RLEkVcYNXkcP0dTxOavbrEUTVaYlyjDprUJQIllOsqrxUiET87H70MnSGTNZf+AcEQWCodxf1R+4gHBylYNUnySx4xykZy6izlqM7Pz7ld46MC1mx7ht0N/8NnTETe9q51Oy/kaHel0hK3YrJWootZQPmpFWL3oV3j9Rz5MVrsaediyNjB11ND1O24RZ0xkwGu1/ENXycgvJPLKqPpYBr6Ch+bw8pWZdOcOr7O5+Opgfnvgm9KZuAr4+6Q99BrbVTtuFbU7YlyyGOvPhxclZcjUptYahnJ4UVn1qSccfSqRZahxj0D9J47C6Gel8iOfMSCis+jVpjIeDr4+BzHyQ9902Yk1ZRe/DbrLvgoXi65qsZJ6eeqfW6aZ22mAMSY7acLc13fMRhqXCyY7NQhEMe9jx+BSMjI1gsM6cBnpGRDTgbnThToTflULHtR3TU/562ul8hqfT0tP4Ts62M1JzLkCQdJWu/jjmpnKbj9yIIUkKK0CJhL9JppueTI0H83m4UJYJKbUYQVajH/o3BbCsjPe8tDHQ/h1afdhpHm3jM532N1WG8WjUy5oOo6vFd6I3ZlG24JU6parFXklf2MeQx1etQYIhIeO71KifrzQiiirTcK4CoWNeh566meM2XT2kth9lWRiQSoOHoD+hte4TtVzyLx9WAzpiFaowqFCDg66O19kHScq7A6li+/P6SpMNoXYEgSHED1Z62nU2X/JWW6p/TfOLHmGxlp8S5MttKyV95PaPDJyhe80VEUYssB8Z0IuwIgoAgqulq/huO9PMo23grvW3/Y6D7Wbpb/kF7/W9JSt3Gyk3fWVSqmclaQmHFZ+lp/Rf1h79DSvblcUY1R8Z58UjKcsNgz0u4nTWTagrDYTddTQ8z3LuL9Rf+Dq0+lfyVH0ce0zeZCqKoZt2OXwHQUv3zeC3MXDC+Rs3n6USrS0YcJ+J5MhZqVCpKhJ7Wf9Na8wCiqKFsw60Tfpuu5r8iihpyVnyIukO3YrKtfE04GjC5tmGm6JAgiOgtevxu75RrYMyWjf2ryDLKErO8ZhRm0d/et6Q1GifjjHU2zjoaZy4EQSRnxQcBaKuLTrhuVz2pXDb2vRAtFFUUmk7ci1aXSmbhOxfenygSDnvjvOanEt7RZrpb/oWzfy9+72RBNbUmieSsi8jIfxt6YzQ9oWj15+LiYK9VxBbTs+85jA6fwO2spnzznXFHA6LFq/bUrVTt+xqrt91D2cZb5tWux9VI0D8wbe58UeUXsKdtB6LG/akiKxAQcA0eIW3MGara82VScy4nf+XH8LpbEUUNGq0dr6sxPibvaCtafeqE+zMfDPftoaPxT1Rs/WHCWYE0Wgc+dys+d0c8BUkU1RSUX8/IwAHaah6kYttdCe1zOkgqPZLagKQy4R1txONqJiXrEgRBQFEUMgveHi/MjorbvZH0vDeiKDKD3c9Te/AW2up+Q17pRxY1joz8t5Ke9xb6Oh6j6fg9jA4fZ+XG2zCY8xJxmUuCnBVXI0mvPF/hkIeBrmcQBTUr1t1EOBitgRh11mAw5895vclfGY02RcK+KZ9fRVEI+vvR6lOR5TB9zU9gtq1EZ8yket/XcGRcsOjfI4aArx+/t5uAr5eu5r/gGakjLfeN5JVdO6nwOyrGqUaO+Bnu30tRxWcTMoblAq1Rj9luY6C9e0Hnx9laFXlaZid4ZY0bv9YtdQ3FQGf/KXU04Ax2NmZCKOhEURQ02qTTPZSzmAEZBW+jv+spDKZ8cks/OsX3b8fv66W56qeY7RWYbWUL6keRZfzeToxjVJ+nCl3Nf6P5xI+n/K5swy0giLgGj9Df9RR9HY+TlLKFoL8fa/IGsouvOuVFsmexPOEdjRZ9ji/ybjp+D4KoJjljB6nZlyGq5s9s1NfxOEO9L7NhCmdDEIT4Dm44OMrhFz5KzooPLVnKj3e0hYYjd1K28VY0OgfrdvwaQVShKAqrz/kxoqiJslbt/hLhsJtVm+9k7fkPAFFjrO7QLehNeZSu/+aC+hclHVrdZMHPRCB/5XVU77+RIzs/Tsmar46rgRDJXfERag7chNtZi8lWuiT9j0d63ptIz3sTEHWwulv+QWr2pQAcf/kzpGRdij39HDjJUBYEkeTMC/F7u2it+SWekTrKN9++qLEIgkBazuWYk1ZRve8bVO//But3/Oa0q8lPh1hkTZHDCKKKkcHDNB77Yfz78s130NP2CF1Nf8Vgyp2X8+8dbeXIi9dSse0ezEnReqxI2EdP678Y6tsNCqzefjeCINJw9PsUrvo0elMOK9bdhCwHcQ0dRaW2LshZcw4cpLXmlxjNhfS2/zf+udG6gspzfoo5qXzK88y2cjrqf0ftwVsQRQ3JmRfOu+/lhJMLuAMe36KYDV9xIqZu/3RiJudnqbA83+pFIBRwsvfJtwICm1/3T1Rqy2mlOj2L6aFSm1l/wUMzHpNXdi3O/n101P+OlZu+s+C+RFFNOHRqXjBFUag//D36O5+If6bRpVBQfj21B6PihbUHb0GrT8WcVM7Kjd+hq/kvBP0DqDRWOuofYrhvN6XrbppQID5e1+bk0OtZvDoxMniY1ppfkpS6Nap7MAaLYy0+d1Sx2bzAFJycFR8ir/SaWY+T1CaKVn8hrqEQ8PWj0SUnZF4Nh72oVAY0OgdqbVI8DSxmcAqCEI/4AazceCt9nU+iGkcTKggCZRtviyuQu4aOM9y3m5ySD8yYXjIeFnslRksxMZ1b90g9Wl0Kaq2NcMiN39uFwVyIKKrwe3uQ5WA8ZcTjakCttaPR2gmHvfg9HRhMeYiSloCvD1BYc+7PaDhyBzUHbqK48kvxdDX9mHEYicxepJtoZBdfRUbBKxFji2MtQ70v0dP6r7gjdzKyit5HZ9Of8bpbEzYOAZGArwe9MRtFkadQozj9UBSFSMRH/aHvMDpcNTYvCwiCig0X/x8NR+6g/sgPECUVSSlbyFv5sXm1r9ZYyS39CEZLUZzowTV0jPb6P6DVp8YjeIIgsuX1jyCNPdemMdauE3u+jCCqKN/03bHxRlDkSJy6d6rrcTur6e98kp7W/yCqdHhG6sa0Q85Fo4uyis30jielbsWWvBHnwH6yi9+PSm2e8P1yMq6ngqiSolSzHt8pYWRKdPvL/f6ejFedsyGpDCRnXoxr6CiSpKf2wLcY7HmB1dvvxZy0+qzjcYZBFFVjAlm/YHS4atpdltmQnHkxzSfuwz1Sh8m6YsHjCfoHcQ0fx+2sIRL2jrG5DKMzZJGz4oMIgoQc8dPf+SQAao2N7OKrSM25DJXajD1tO86BgwR8PQS8vfR1PEZ/51No9emoNBas5rVkF72X2kO3cvjFayla/XmSMy/E5EgamxTDExyM8Y7GcnE8lss4Xg1orf4lokpPas7lRMI+Wmt+gcW+GoM5n+SMHchyiP6OJ0hK3TqB338uUM0xzUMQBJIzLwCidUfHdt1AStal5JXN7qjMhO7Wf9FR9zvWXfgQKrV5TpsJJlvplBGA8boRPncbI4OHyB1LLQmH3NPqHMTQ1/EYDUfuYPsbngJBxdGXrqeg/Hoy8t+Ga+gY1fu+xqZL/oZG56C9/iF8oy1UnvtTAI6//Dmyiq8iu+hKPM5aju/+HOsv/D16Yzadjf/HyOBh1u34FaUbbublR19HW91v485GzGiMhL1zu2kJhjTOGcsr/QhB/yAjg4emPX6472XCwREKV306YWNQ6+wYzAX4PZ24R2onCJkqioJ3tBGtLg2VxjxDK0uDjoY/Mty3B+9oM+GQK/55ODSKooTJLn4/Wl0yeaXXcGTnx8lfeT3mpLI5v1sxqLU2soquxO/t5uhL17Nqy11YHOvYetl/cA0dRz+uFkKawoEuXPVpNPpkZDlM9b6v43bWEgm7MVlLsdgrSc29HEFQMdD1ND5PJ6NDx/B7u9Bok8kqfh/ZxVcRDo3OK7onCAJFlV+gvf53ZJe8d9L3y9UQNtgs+Fxu1FoNXqdr9hOWKZbr/Z0Or3o2qur9NzHU8yIabTLBwADp+W8nJfPCs8rMpxgzKT/PZpzKcoj9T72L5MyLKKz49IKMWVkOc+j5D2FJqhijnJ0f3CP1tFTfz8jAQSAaqVBrbMgRP4oSTdOq2PojrMnrgOgiGQ65Zo2sRSJ+RgYO4xzYh9fVjGv4GOsviBpfjcd+xEDX04BIUsomitd+Ho12YtH4mWTY6y2mCeHbM21n5nRg39PvBlkmGBhgy2X/4/iuTyMIKjQ6Bys3fYdw2Muex95A+eY7503rHPD10nziJ+SVXTulDsd0GO7bg96Ui86QQcA/gEabNK86h0jEjyTpCPj6Gep5kbS8N88rZTCmop6W84ZpU49iu8NR0cKPsHLTd8ZUnKeGz92Oc2A/6XlvQRDEhEY2ImFvnPGruepndDX9X9xxURSFvU+8GUf6+RSv+dKc78HpwGDPS9Qe+BbW5HWUb06s4ns45BkzkmsoXvMlLPZKhvt209P6LzyuRtLz3hpnLDyV2PP4m9Hq03CknxePZliT16HR2omZTtF6lwi7/nspFscaVm/70YL783u76Wz8M/1dT6JEghSu/hxpOZcD0XskiKopnQ2I1oo0HLkT72gzablvxGguwDlwkKHenaTnvZnR4Wr83k4MpnwMlkKSMy/C6lizJMrlywkGmyW+Rga8vrNrTgLxmmCjmitK138Lz0gdrqFjtFTfT0/L3+lp+Tvbr3j6Vf+SLSdM5WjE6NdmM5YHup4hFHTGUw4WYlyLogp76jYGup+NGzvzQcOR24mEfRSv+Qq25I0TKEG7mv5Cc9VPkMY54oIgzElJVZJ02NO2Yk/bSijo4siLH+Pgsx9Aq08lPe/NpGa/Ho+rntaaX7LvyfdgTlpFbulHSErdFGeuWG4QRBFBFJDDEaxpDlz9wyjy5CK5s5P+7DCY8hkZOEzxmq8gSXrWnv8AQf9g/HtJ0rPx4ocXxFwmCCoiER+yPD1rzlSIFZQrikz13q+i1iZRvvmOOTEUdTX/jZ7Wf7HmvF+i1aeQUfD2eY9bkUM4+/eRmj29wnTMEFZpbeSWfiSeajbY/QJ6U84kPYCThQ9N40TlVGrThGiozpA+4dxo+tXYsSrDhGMnFdUr0WdeGftXEARyS6+h6fiPsKefd0qE/qbDqLOGga5nyF3xoQnFzZFIgMHu52mrfRBr8voxNqrEZgio1EbKt9xJ3cFbqDt029inIva0bUgqE6POqoT2NxeEg6OAQlLqljihyXiMvweCIGFOKsc1dISAvx+tbmGU0aKko6D8OqzJawn5h7AkVUTHEhrlwDNXkVHwDnJXXB1Pu4utY90t/6Tp+L0YLUWsOe/n8WcwOfMi9j75EoIg4XHVU7r+2/Eo5VJhuWyAxcZxqqMXZzfRpkZi1IuWMURRhTmpnKyi97Dt8idIz3srWn0aB5/7EP2dTzGHwM5ZLBHmSsnX2/YIAEnJi9OcSM25nHDITe3BW1DG6ELnAkWJ4BltJrPoPaTlXD7B0RgZPEpz1U/JLHz3otKzANQaC2vO/Rl5Kz+G39tFS/XPCAWHMdlWkrviIyRnXsTo8AlO7P4CvW2PEQ558LiaCAWdCKKIz9OJd7TllKdkxGpJok5G1NGIUdaO9A4ui4XnTEXZxluwJq+hrfZXKEr0mdXoHPGUKUEQFkyRrNE5WLXl+xOM5flAEESKVn+BFeu+gSCI8ZqJqRB732zJG0nPfTOiqF5QnxBl4Vpz3i/jhbQzQaUykFX4biRJh6IotNX9lt62/0XHNG7uH+rdRW/7oyjK0j6rKo0Vldo8wQlJz3szSSlbqNl/I/VH7pzxPi4lAt4eRgYOIZ60EdN84j7qD3+XUGCYglU3LOq3mwmSpKVs422s2/FryjbcysaL/8TKTd/Bnn4OPnfbkvQ5HVxDxzmx50uAQGr26+d0Tun6b6HW2KjZd9O8KKhj6G37L/ufehf7n34vgqAio+BtcQdYpTZTvvl2kjMvQI4EOfjM++lp+ScAA93P03T8HjLy38qac++fsA4JgoTBnE93yz8QBGnem2zzhdFuRZFl1PrF9xNbV+ZzvN5iQmeKbvq9FtcdUSXFdVWWG171kY3xECUNeWUfpaf1nwDUHbqNgK+P7OL3nd6BncWMyMh/B66hY7iGTyxKUdtoKaRsw81U7fsa3a3/mjOzjt/bDYo85W5VT+s/UGks5K+8bsHjGg+11oYyztioP/y9SceIkg69MZs9j18xZRuipCMpdRtpOZefEsV0UZKIjIuyLLG99pqCJOlIzX49dYduIxL2IGpsCW1fURRkOThtasZsiDPnRAIcfPYqbCmbKFnzlQnH9LY/Sm/bf1m9/R4M5ryE0Ju6ho4Q8PVGKbLnCEEQWHPez5Aj0U2Ovvb/0df5JKXrb8Y9Uk//mKDhUkJvzCIcGiUYGI6zJQqCQOmGb9HT+h9aax8gHByhdMO3l8yoH4+gf5CW6p+Ts+JqkjMvmLTrrSgRBrqeJqfkarKL3zfngvuFQhAEDOaCCZEnQVCdsklluG8vHQ2/xzV0FL0pj/LNd8w5xVCrT6F88+0c2/Vpdj92OVlF7yN/lkLx3vZHcTtrKVr9WVKyLgFBQpZD6AxpBHx9aHQp8QjK+HrF/PLrMNvK8bnbqTt0G8mZF1Cw6oYJ0cXu5r/TVHUfKDIqtRVBEKg9dCsbL/5zwtPh1XodkVAIz1CU/ncuquRTISZoJ6qkebVjdiQhKzJe5+isTkasbUh8dD2qyh1OmGjefCGHI8s2qrJkzsZcQ2njUy5OBQRBQhS1CKKKSDjKk33W2UgsZqrPWAgcGTtIyXodjUe/T9DfR0b+2xfMp5+UuoXkjB10Nf+V1JzLZy3kCwdHaan6GZLKiNWxbtL3AV8fKMqiRK5ORlrumzCYC1BrbGMMHwLBwCCipEWjS0ajdRAOudCb8vG5WzBaijFYijFbSzFai3D2H6Cj4fcMdj+LKOmo2Hb3gmmDZ0Oif+uzmIyocSwgiInfsTq++3NodamsWPf1xTWkyOSXX489dRt9HU/gdTWRlLYdq6MSjdaOPW1bYgY8hlFnDW5n9bycDYiy0sWMeLXWgd/TSW/rv8ldcTW5K65O6BingsUeFSB09u+d4NhIKgNZRe9Bb8qjet/X6Wt/nPS8N07XzIKgKBFCwRG8o60Efb1REVWVAa+7haB/EL0xa9I54ZAnSoQhaZfc0Tjd6G7+O00n7sVkW0nZxtuwp22f97xusq5gzbk/59DzVzM6fHxO58QilqKkJW1M48Tn6aBm/zcpWfu1Cc75YPcL9Hc9TUH5DWj1KbTV/hpR1FCy5qsTxjoyeISmE/eSkf92MgvfhaQycOj5j6DR2RDExKePL9S5iGE802JElue1pkhqNRq9lsGOnkltTdWPHI4sSaqX0W6NO1uJdDSWYqynQqX8ZCyZs3HyzZnuARBEAVGSUGTllIS9JJUBvTkPz0gdKVmXxhlLziJxSPQDHGO9UKlNtNX+mq7mv1Gy5qsL3rXPWfFhju68jqM7r8eeto2k1G1xFeJwyI3f08mos4qRwcM4+/cDUFT5hUkOjs/TQSg4ktDoQaywXGfMQqdPjy/wMTGwcMhDZ+Mf0ehSKFnzJWoP3oLH1UDphm+j1acjiios9krSct9I4/EfMdy7i6M7ryO75APklX6USNg3JoymRq1NQq1JWlT+9VlHY+lhtJZgMBfgHW3FMofUofkgu+i9iNLCHPfxkFR6UjIvAmBk4CD9Xc8SkQNYHZUkpW6ZUjhwMUiEiJk9bSujw6/HYCmY/eAEQaNzYLKtZLD7BVKyXjfp3bOnbcWWsoH+zicX7WwE/YO01/+WzMJ3ozdm0173ED1tj5CcsYNRZ82Ys6Fn7Xm/mHSuIodpq/sNnU0Px/8+XdBo7chykKB/cN6Ma3NFb/ujNJ24l8zCd5O/8hOLmhMN5jyKVn+exmN3Mdy3Z8pnX1EUImE3aTmXxwvAx0OOBNEa0tCeVB+kM2YR9A+iHqN+Dvj7ESUNciQ4wRkMBZ1AlN5apTbRWvNLwiEXa877eUJTqRRFwedpA0VBb8qZkW53xnbGbL/5GtaiSkJRZIa6+uK1EoosRz+XTzpOVpDUqqitqcjA4oz4k6MXXufogtuaDqJKiqaokti0sMySXDprWxLW3lxwytKoprtRcjiCKcmKxzmKDKckylGx9UdjHPULo1E9i1MPSdJSWPFpMgvfReOxu6jZfxNZRVdiTz8Xo6V4XouDwZRL+ebb6W75J30dj9PZ+CdSsi7FPVIbzw0WBBUmWxmZBe8kLfeNE+o0FCXCqLOGYy99EnhFATYRaKn6KV3Nfxn7SxgrCP8otjGWq4GuZ2it+eWk82r23YTOmIUgqhju24NG55hQSNzV9Beyi9/P8d2fx+2sjn+emn3Zgti5zuLUQWfIwDvaRMDXDQl2NhLtBAAUr/kyGn0qjvRzE942vMI0lQgslr53IUjNuYymYz+iZv+NFK3+/CQDOi3nDdQevJnhvr0LYBjrY3T4BMmZFyIIEqPDVVFla2M2yVkXYU5aRVvdb2YVvO3vepaOht+TXfJBbMnr44XKpwNme7Rv19CxJSlu7mt/jIYj3yct902LdjRiSMt9E4M9L9Jw5Pusu+A3k6iXu5v/RmfTw2y86E9TihjGUn6BMcNYQBAEBFGNLXlD/LcN+vuRIyEajn6f0g03v0KMoI46I0dfup6AtwdFCZNV9N6EC1cOdD1D3aFbAdAZMvF7uyjbcAuOjPNnPG98bd9423A+BrUlxc7ooDN+Xsy5kNRq5MgrNmTUgVHQ6LWEg+FxnwssxuE4OXqR6M1yrVFPKBBEa9QnvMi9p6kzoe3NBQl1NuabpxZ7KDzOUeRIZMIDA0vHaqBSG886GmcodIYMVm68jabj99LV/Ffa63+LIKpJStnMinXfmMCiMhMs9kos9koURaG15pf0dz6FLWUDOSUfRGfIxGApQpK0KHKY3vb/kZ735jH2na8x3L+XtNxXdh2TUhIX2YixjAiCCkUJMzp8nBO7P8fWyx9HkrRxjQXvaMuE87zuZrzuqNK0KOlQa2wkZ16IKGoY7n2ZnBVXI0laQoHhk85LnDjXWSwNohE1kXAo8Ttnfm8PI4OHSM2+LGEGvCCICYk8TAe3s4aa/TdRsf2eKVN/5oOgfxBBVMd3ik8FMvLeglpto/7wdzm88+NsvPCPE3aDHRkXYE3+D43HfsiqLT+YFy1xd/PfGezdiSNjB2qtbYI4n8GUh8GUh1pjRT1NhKCr+W/0tv13jOq3aEl/x7lCq0tGZ8jENZxYZyMavfk1HQ1/IC3nCopWfzaB74BA0eovcOCZKxnu2x2txxgHi6Mymj41TX8B/wCR0CgGcwHdzX+nu+XvbLjoj4SDTnrb/0tqzmVRTSc5REH59TQcvZPetkfi6vBWx1rKN99Bb/ujJKVsxpGxA6tjTUKubTz6Oh7DZFtJXulH6Wr6C35vF6Iq+izHCrX9bg9GuxX/qJdIKIQgimj02kWpc+stJkYHnRMiIpJaFWW3VGQuffc2JEmguXGYgc4hhnsG4o6GHIkgiAKCIGLPSkalVtHb0jknW1Ol1aDWavC7vUueiRO7P6ElqP04HRkJCXE2Yl7qfPPUYhccmeZHWy5sAsuFyu0sohAlLcVrvkTh6s/iGjqKZ6SetrrfcODZD5BXdg0pWZfMubhSEATyV35s2kK+YNBJb9t/0ZtysSRVEBkrLo0xPpVt/M6icplPfraKVn8eR+YmOur/Tsg/iMVeic6YiThG02ww57P2vAfwe3uikYyxxWqwZyc1+28kI/8dFFZ8akIfOSUfiP+/dP1NeN1tiKIGBIGklMUxfJ3F0iMaoZLR6hbGOjUTPCN1NBy5A3va9jlRNc8FiqLgGalDa0hDneCCdoiqLaflvSkh4z2x5wtYHRsmvTNLhVhUxpayHq0hHZ+7ld72R8nIf0v8GEEQKK78Eif2fInDL17L+gseQqtPpeHoD7DYV5Oa/XpGh0/Q2fgwRZVfRK2xjFHpiuSt/DiZhe+asdYgpk0yPkIUFc9rovnEj3Gkn48tZRPpeW9e0nsxH5hs5biHq2c/cI7wuJpoOHIH7pF68lZeR1bhexJO56szpKMzZDE6fGKSs2GyroizRkXCvkkpui1V9zPUs5Ntb3gco7WE7OKrgOgm2YYL/xBdcwwZVGz9EYIgMOqspvnEfVgclRhMeQiCsCTpi+MhyyGc/QcoXHUDtpSNmGwr2ffUO3CP1JCceR4AQX9088wzNBJNCRpzCiJj2Svzta0EUURnMkww9mNtjLc/n/rrbgDUWg0qrYa0gkxMFgMNh+vim9qCqGC0Gulq7Jh1DOP7SEQ9xnyue7H1MDGcrqL1eP+JaOTkiMRywkw/6mw/+Hi+5LMOx/KDOBZStiVvwJFxAa01P6fhyB201vyCtJwrcKSfh8GcvyhnQK2x4ci4gICvD8GhomLr9wn4+/GOtjHQ9fSid0Qn1TAJAknJ55OUPH0YWhBV8RqOGBzp57Lldf9BUs8c2TEnrYprDsTzQceiimexPDHcvxeIpv8pSgRZDi+YPepkJKVtY9vlTywoz3omHHv5MxSu+lRcKTuR0BkzE1bMXbT6i6dUmbru0G2k5VyOLWUj685/kLrDt9PR8HvSci6f8BvoDBlUnnMfe594O52ND5O38mPIkSCSKrpbLKmMBANDiKKaUNDJoec+TGHFZ0jOvGBOdQ3e0Raq9n2d7KL3MtD9HK7BIwiiGklloGj151FrbUt1CxYEc9JKBnueR5ZDi2bp8nu7ObLz4+gMmVSec9+SZjlIKt0kKnK/p4uWml+QXfw+Roer6Wr+C2vOvX+MDCSKgvLrySl5PwBWx5oJUQlR0jLUuwtFjuDIOA+fu4Ogrw+NLpm6g7dSec5PTkkxfzjoAuR4XYlKbSQ58yJ62x6n4pwvYLKZ43UBKXmZ9Ld2Rc8bZ/DO19GAqDDfVOdpjVGHTZYVkrNScQ2N4HO5eeeHNvP4v+uoq5scxW+raprTGMYfMx9bcDrNjdOx3oYDwRmL55cap01nY74cygvFTDd1pu9irAXRwqLlKZ52Fq9AZ0indP23WHv+r3Ck76C75e8c2flxdj/+RhqP/YiAr3fK88LBUTyuRuTI1MJmUWVjhY7630V3AkUVWn06o8PHANCbFk/jCYl5H1Qa85yFKmP0f4IoIKlVqPW6KEOF6qzQ5XJDb9ujJKVsQWvI4MjOT9B84scAyHJ42ud2rhBFNYKonlDfkwisPf8BTLbE1pcAhIIu6g/fnrDxWuwVGBL0Ds8FgqjC7+uJ/z+7+EqC/n5GBg9NOlatsZFXdg3dLX/j+K7PkFPywXgdjMGcT+U59yGp9KjUFrKK3ztZQHAa+DwdNB67m4C3i8ZjPyQUGCK37Bqyit7Duh2/WXaOBoDZthJFDuFxNS6qHe9oC601v0CRQ5RvvmNJHY2gfxCPqxHrmHK9oij0dTzB4RevZbD7OZpP/Bhb8gYy8t+GdBJJg0bnmCQ8OR79nc/Q1/kEEKX0D4fd5K+8Dq+7lSM7r1/0fZoNiiLTWvsgQLweRVEUvK4mjJZigr4Ag539QDTlaaC9Z/F9TmOHKbKMIIqotBpkWSESCtHb0kl2cTTFcs/uXlKyHZPW2IXadfM551SwrM7Hdjidtuxp09lY7sZ7bHzLlbP4LKaG0VJI0erPkl/+CbyuRpz9++lq/is9bf/BZC0lKWUzyZkXEQwM0d38V4Z6XwJAlPTY07aTV/rRuJaHc+AgdYduJX/l9eSt/DiCIOAdbaV6/zfwezqAmM6GDq0ul4C/F2f/LlTqZEKBIQzmQlKyLsFoKQRe2RGJ1SpNVRh3KkKdsYI5QRTGis9eqQWY6/N+NtJ36iAA4bAbQRDIK/1ovPhzsOcFmo7fQ+X2n0yKdM0HLVU/xe/rYeXGWxc91lgxq9648PHM3H4kSuTg6UwIM1F/1zOo1RZsKRsTMLrZsWLt1yb8bTAXodWnM9D17JQpL2l5V9Ba8wtMtrJpf2NBEMkqfPecx9Ba8yB+bwfFa76C1bEWrT4todTdSwGjpQhBUOEaOjpvGu9wyEN7/UOMDh9ndPgEak0SBas+PUkJPtEYGToCgM/dxnD/ProaH8Y5sJ/kzIuwp51D3aFbCQWH5qz3NB6l62+M/1+rT2X19vsQBIFKw0+pO/Qdjrz4cVZu/t6SpcmGAsP0tUfFMVVqC6Ggi6q9X8E9UkNZ8VVklWQz2D2E2WGNRzQWi1i6/lSfq7QaREGcsHbW7a9BpdXQeKgOSa2K60G9WhS+x9+PWGbR6U6VmgmvKVG/heDV8mC+1iBJWsxJ5ZiTysksfCf9Xc8wMnAwXlQOoDflUrT68+hN+biGjtLb9h8OPf9hVqz/JplFl2BV1lFY8dmoyJQpN9quRoc8Th22rfY3QEyJWMBoLcHvGURS6elte4TOpv8jp/gDZBa+E5XaHKfqmw6nYqIYL74X4wVfaBtw1vFYSnhcTYw6qylYFWU+G2+Qmq1lFJTfgG6sSDoc9tLT+m+sjrWYbWW4ho6h1iShN2XjdbfSWv0LCis+g1afSm/b/xh1VlNc+QVMtrK4/sNC0Nv+KEZzISZbKT1t/6Gl6n42XfKXCWkhi0UkEkAUVWi0Saw9/8FFG8fhkBuV2sTo8AnkSOCUOBsBXy9qTdKEdClBEMgoeActVT9BUpvIX/nxCWlCAU90RzgR9NrhkIf+jscZ7H6W7OKrpqRcXa4QJS2OjAvoqP89KVmXoNHa53xuT+s/6W75O0kpWyhd/23s6eecEsFES1IFjowL6Wx6mI6G36PVp7Fy0+3Y07aiKBHqD38Pz0gD3S3/JCl1K6nZr5t3H0O9L6MoYRzp5yHLIRqO3ElG/lsZ6t1F3aHbWHveL+cc8ZoPYs+wLWUzelMefe2P4nbWUHnuvZhtlTQcqEFUSZiSonVViUjfiUYwJttjiiwjSRLu4ZE4m6nWqEeWlXi9w/gUoljGyplu101VvjCd/bAc1uizzsYsONMfyOWK8ZOPLT0FZ0//kvUlqQyk576R9Nw3EokEGBk4hEZnH6PMjY7D6qgks+Dt1B++ndoD3yQUHEGStKRkXTyhLbXawcZL/kLA10vA14/RUoyk0hL0DyKpjHFl1oCvD1HS0dn4MO31v6Wn7b9suOgPgHbCix+7DzF2jOWqWxEb51RCQKd7Enu1IuDrp/7wdzGYc0nPnay5oDNmvhKF69+PLEfoano4LqDX2/4oAW8PZRtvBoWxIuIxx1gQ4il3Jz/jJ0ORw/i8nRhMedFUkPb/EQqNkpH3FiSVnraaB8koeBsmWylJKVuQSwMJdTQAelqiBuOGC/8wJVXofDDYs5OGI3ew5rxfRkUBldnPSQTqDn0XtcZK2cZbcI/U43O3kZx5EVmF70IUJJqrfoJr8Agr1n09nkLjHqkFmJT3P1cEfL0M9e1muG8PIwMHkeUgjowLych/e8Ku61ShcNUNHHr+QzQdu5uyjbfM+by+jidJzriAFeu+sYSjmwytPpWyDd8iEgkQ8HahNWTGa60EQYpSWns6kFTGSWlUc0XT8XtIz38rEE2JdGScj9FSRHLmBRx6/qO01z9EceUXE3VJcUgqA5LKiMm6AkWJ4HE1ojNmYbZFNy1ElRTXT5PUagwWE+7hhW1sjYciT3xZY2tpwOtDo9cS9AXQGvXRWsRwcFoj+7Vm1y2HNfqss3EG4lR6qfPdAYiJ58Q4tIFxoT5l3K76K+Mf72gs9Y6DJGmxp22d+juVgdL136T+6PdpPHonWkMmyZkXTWApGep9iabj97Bq851xIUBgwu6RHAlwYs+XySx4J/krr2W4bzfe0UaUSBBRa5hwfbH7IErLW4k7Ns7pmOPOIrGIRALsf/pdAFSe+7MZCz7lSJD6I3eSlLqZzZf+I/55waobCPmHkFQmDGYz5Ztvj383nZjYVGit/RV9HY+y8eI/4xlpoOnEfYiimpTMi5BUejZe8ue4064zpM8rpWeusKVsQqWxLNrRADBZS8gtu2YsfSixDEQzoaDiM7gGDhEKuhju201b7YM4Ms7HO9rOyOBhKs+9n7pD3+Hwix+joPx6MvLfhj39XBqP3YV7pG4So9FMiEQCNB2/m772R0EQsSStJqfkalKyLpmgGXQmQa21UVjxWWoPfpvBnpdwpJ8zp/NEUUJMoJDdfCFJ2inrL/SmXHyjzZRv+X5cRXwmyHJ4rIYQPK4GJJWRjRf/X/x7n7uD9Lw3xRngkjPOZ7hvb2Iu4iQIgkRa7hV0NPyejobfY7GvIejrJxzyEAo6saUVsWJ9KUaTht3/28fo4ETKdUm9sPUuale88vd4eyLoC0Q3w8IRFDmMHImQlp9FT1P7hGOXK5ZD9GEpsbwTNU8BzrSC2FP9QM7F8I8VFo+vBYgreUrR+zubQnyMk3u6/qL5iUv/uAqiipI1XyE9/20EvF3UHPgmA93P4xw4xEDXc4hilF1kcKzWIxx8pd7B7aylp/XfCKIKe9o2UrKjxkHymLLyVCHgGJazo7FQnCoSiFcjJElL7pjGwcjAwfjnihIhFJy4QyhKGjIL3kVv2yNxnRYAlcqA3pS9IINaUWS8YwKX6XlvpnzzHYiiGnPSSgorPk1W8fviDvZsKU1yZPGpgUZLIckZFyDLi3tPFEVBlPRk5L3llDoaAB11v6G56seMDh8np+QDbL38cURRjdfdQijkwmRdwZrzfoHekEXT8XvobHwYjdZOas7lOPv3oigzh2BkOUxv+6N0t/yTYy/dwEDnMxRWfI4tr/sXq7ffQ3bxe89YRyOG5MwLMFpXMND1zJzP0Zvy8C1DPSGrYx2u4eO01/2W47s+M+Oz3dP6b/Y8/sax6CQ0Hb+X1ppf4vd20936LxRFobnqPg49/1H62h8HwGJfg9/bScCXuKyBGOMTQF7ZK3TxRksxihJmz+NXcPDZq3jp32/lyT98i4MvHJiynYWud4qsxG0NmLjGKLJMJBSK1kMqMiXrS3nw6qYF9XM6MBf63TMZZ/boEwA5HJnXj3i6f/Dl4vmKKglJrZ6gBCpKUjwdSK3XobdEWSpijsd4jL+PklqN3+2ZMJGdjFN53YIgUlTxGVasuwmPq4HaA9/ixO7PUXvoVjoaHiK39BrScq9AjgQ4vvvzuMb4390jtTSfuA9Fkclf+XGksd20/o7HcGRcOGfBwTMVU7F9nMXCkVPyQdLz3kp7/UM0HLsLiDoBB555Lx5XY9zwALCnb6di2z1R/ZRFIFZP1FrzAMdeuoFI2IfOkB7XBIBoVCS76Mpp2wgHR6na+7W4cVy196s0n/jJosY0MnCYmgPfxO2sXXA7AMN9L3Pw2asILzAtaaFQFAVRZaCw4rNYHesA4ik1KZkXsXrb3bEjUZQIjvTzaam+n+7Wf+FIPx/vaAtuZ/WkNoOBIbzuNvo7n+bYrk/RcOQOmo7fg6JEWH3OfWTkvyXhKW2nG7bkDbgGj8z5eL0pF5+nfQlHtDDYUjaiyCFUGjNpuVcgimrCIQ+jzhpGnTUTnPTkjAvJXfEhFDn6zpeu/xZ5ZdfiGjxCV+PD+NytlKz5KnIkyGDfywBYxuhyXUNzv1czQa3XTRDii0Y3ovowI4MH4/NRavZlREJemo7+lJ3/eOusTvJ8Md6emC5FSg5H6G7u4b33JV6b6HThTF9Pz6ZRMb8f8VT/4POJZCw06jGf1CW9xYRKrcbn9sSLrkRJwpRsRRAFgv4APpebkC9E6CSB0NixkVAozgwB0V2OkyeyqXCq731K1sUkZ15IOOgiGBigq+kv9HU8yejwCXpa/o5aY8PjqufYS58gt/Sj5JR8gNTsyyYUH8qRID5PO1nF7zulY49hoeHqheBMnwyXI6yOtfS0/pOh7hc54qxl9Tn3kZZzBYdf+Cgr1t0YT63RG7PiatqKIi+ogNo1dJSW6l+wasv3ySl5P0mpWyaJjcWgyGGaTtyHI2MHtuR1E74bdVbjc7chywEkSUda7hVxAb6h3l0EfL1k5L8NRVHwudswmPMIh70c3fkJsoquJC3ncrzuNnrbHiG/7GOMDB6h5sBNWB0bUC1SyE9nyCCv7NpTUiA8HoIgsGLtV2c9TpJ0rNvxaxAkmk/cR9OxH5Fbeg0QLWqPwT1ST+3BW/CPM6JN1lIqz/kpJlvZsmeXWgxM1lI6G/9E0D84J0YytcZGODg6QcRwOUBvysOcVEFX05+jvznQcOQOBnteACCn5GpySz8MRGnNs8Y5+LHr1hkySErbhkptQhAk1px3P1pdNOKo0Sah1afjGWmYVwredDhZXC4S8dHb9i8AvKPN2NPOwefppK/jMQAsjrW4h6sIB0cSRqd8chrVVJDUahRFxuf2LKiPU7lmJhrLORXr1TsjTQFRJZ1xaVOnwhGaT41EOBQm6PePpUtF1Tz1JiNyJIJ3ZBT/qHdCEdf43e6Yo2FNc6DSTPRzxXGUdsvpNxIEEbXWhtFSTMnar7H9iidZvf1erMnrJ0QqnP37x1I0NCc3gCBICUklmQmKIhMJT3bWztRJ8yyikOWojkZR5RfGVJ7byC+/nszCK3GP1NPV9Dc8rmiqQCjoYv8zV9Hd8o+ZmpyhrzB6U25c3G28kNgkCAIjg4fjRo+zf3/8q6TUzWy46A/xyF5K1sVxtifvaDOD3S9GKWydVRx6/mq87jZUKgP5K6+DsV3QkH8QZ/8BfN4urI41ZBa+B3NSOUd2foLe1v8u6PoANLoUgoGhGRnhEg1FURju3zfnFDBBVCEIApLaiEpjo632AQA6G/+P1toHOf7y5zny4rXIER+l679FxbZ72XjxX1hz3s8xJ5W/qh0NeEUBfdQ5N0XxUGB4jAxheRlhgiBQsOoGgv4Bupv/QU/rfwj4+0lKiTLOjQweprX2VzQeu4vqfdMXt6s11jjZg96YPWENkuXAkkXUVSoDmfH6LAFZDrF6+z1k5L8DrSED1+BhZDlI4/G76e96Bp+nc9F9zmariCoJORIZcxjCC2J3PJPXzJNZIpcTltdolhCx3fvXGgtBIiCp1fGUqJDPT8DjIxIKodFr8bu9eEZceJyjBH0BFCVap6HW69Aa9ai0GiS1GpVWE1/gR3oHJ0Uxxv+9nH8jQZCw2Csprvwiq7b+gJWbokW3oeDolMKBocDwmOrz0jkboaCLIzuvY/djl9NS/XMAhnp34x6pW7I+T8Zym9heLTBZo5oCkbAPj6ueoL8fQRAwWgrpbv4rzVU/iTMVNZ+4F0UOxI3acHAU7xxz1RVFwZa8npI1X44Xoc4EQZAo23gzBlMuA90vUHvwZtwjdYRDbvzenmmN+eziq6jYdheCIGGyllK28TbUY7oh9rRtpOW+AQBr8jrW7XgQgykXQVSRu+Jq1BobAtBa+wDBwPCU7c8GUVTTXvcbRoeOLej86RAKOqd1JjyuBqr2fIXh3t3zatNkLcOWshFBiP4eI4MH6Wn5F4KoIj3vzay/4HckZ16I1VE5ay2G39OFx9WQ8JSW0wGtPh2jpYTOxj/NXscSCdDT+m9Scy6bs+DpqYQyti4oSoS+9kcJBobRGbMwWcuiWlAtf6enNVqLNdu1BgPDnNjzJfo6nhhrUyEcdKHSWJZs/LmlH8VoKQEUrI51aHRJFFZ8ivU7fkvOig8BMNj9HHUHb+HozusIh0ZnbG+xiKbFC1Ombi8Gy2kDdK5YbhGO14yFsJwN2OUOjV5LODSRLUOl1aA1RFMsFFmJi9TFOKzVY9+LohCv6Yh9F6v3UOtPH0NIomBP28ra8x9EjnioPXjzhFQHeKW4N2WsSDzRGOzZyZEXr8XvjokM/pv+zqep3vdVjr/8ORR5dpaTRGC5TWyvFuhNuRjMRTQc/QFrz38Ae9pWImEfjozzySh4J6Xrv4U5aRUAGQXvRJT0hMYM8ba639BS9TMikQCdjQ8zOnxiyj58nk6OvnT9lM7yTIhS4coMdD6FoijIET/9nU9z4JkrUeawiy+IKhzp5845xSIpdTNpOZdjTqqIG2nzhShp2fL6/yRUVyMSCbD3ibfS1fRn6g59l+6Wf0743mQtYd0Fv8GRcd6c2wz4eqk//B2SUjZjMBcBsGLdTWx5/b9ZteVOilZ/ftoUtxhkOYRz4CDNVT/lwLPv4/AL1+Bx1c/7+k41JLV60t/jjT1BEMgv/wSjwydmLRR3DVcRCg6TNgV19HJAzCm32CspqvwSQV8PFsca1pz3MzZc+Ds2Xfxncko+wMjAAYbHajEmnC+HGe7fB0TTxTS6FEzWaOQnEnKjKJF4CuNSQJK0rNz0HVKyLsE72sj+p65ksOcl3CO15JR8kE2X/guNNhmtPo1waJSe1keWbCwxyOFIwqMTgiDGn8FX08baqbyWRddsvBrEUc5iZvjd3ni0IgY5HGF00Dll4bdaq0Gj0yJHIoSD4aizobyiyC6IIrIcmvOEsNyfMaOliNL13+bEni9yZOcnSM99E6nZr0OttTHqrEYQVKjUpkX3I8thvK5Gelr/jYJCKDDMcN/L2FI24xxbcHSGLPrHdrYiYQ+7/ncpelMuZRtuwWDOW/QYzuLUQhAEyjd/l8MvXMPhFz6KI+MCRoeOs2L9TRSUf2LCsWZbGevHcr8BLI5KMgvfiSCIDPa8MMYmtWpSH0FfHyZrCZI0dbpFLNc9WmPRglrrQJS0CIKEKKpwj9RSUP5JLPZKhvv2IoiaGal6FwJFkZHUpri44WIgCBLOgYOIogaLvWLR7UmSloLyG0jJvpSOhj/GC7JDQSf9HU+Rnv+WuCjoXKHRJZNb+hH0xlw8rpjWxvQ56Iqi4HbW4B6po7/zSXzuDiJhD4oSQpT02NPOZah35ynbfJgLBFFEUqsmpbqMXxdElURKTjqiSqSr7pUonS15PY6MHTQe/xEWxxq0uuQp+4g5veol3N1fDCz21RjM+bTV/QajpRiV2ow9dVv8e0llIGfFhxgZPER73UMkpW6L151IajV97S9Rs/8brL/wD+iNWZSs+TIAAf8AtQe+jSCoMJgL5zSWueb7K4pMw5E7Scm6BFvKRrT6VFasu5GDz12N39tFzf5oylfluffTUf9HgoGBsfGaGBk4QHbxe+d1jxaCRNYuCKIYt19OpUL3qagdOZWbhIt2Nk6nEagzGfG7PcveGD2TMNVLKogCGr0WtVaDKEkEvD4UScI/VoB18jmRUAh00WiIIApjUY9XQsDzfcDPhN/WnLSSVVvu5OhLn6Sl+mfoTdnY07bj93YBApGIf1EGWNA/SM2Bb8Z3p1UaKxqtg/xVN5CR93aO7boBt7MKj6uOoDaJjIJ3RPv3dNLV/HeO7LyOynN+jNaQSTg4QjAwhN6YE1+Ew8FRRkdqkMM+IhEfihzGPVKPzpDByNARJEnPirVfm1XnYDkXqJ2p0OrTWHv+gwz2vEhL1c8RJc20KSHjf5/kjB3x/1dsuwe/p4NgYGiS+rI1eR3Wk4q8Y+hu+RfNVfex/Q1PAjLV+76BVp/O6PBxBFHNhov/zPoLfx8vuDbZykjPfROKEklo2krD0R8Q9PdTtvG7jA4fQ2/MWTCNa/3h2xkZOkJG/tsS4mzIkSDJWReh1lgnOIChoIvW2gdIzrpoXorXEHWIMgveQfX+mxAlPSq1meYT92F1rENvyiHg68c1dJSAr4eAr5fhvr0EfD2AgDV5PSBjTlpFYcUNGMyFDPXuYqh3J1pD+qKvN1GIKiBPTA06eS2XwxG0Bi2d9W2Tzi9a/QX2P/1uetv+S+6Kq2fpbfkUho+HIkcI+IeAATwjdaTmXDap7k8QBHJWfIgTuz9PZ+Mfych/e1RMs/aPDPe+zLoLHnqFHEIO09P2CG21v0KUNKzefs+cNpkEUUSj18bTmceTuZyMwe4X6Ot4DK+7dUKE0OpYRygwjEptxu/t5OjOiZshkZA7Tqe9FBi/9iRyDVJpNfHieEEQT9kaFwmFXlW27RnNRhUzdl8tP8bpwninzeyw4eqPpmHEXig5HMHncuOf5SWLpUclZ6fh7B9GkWWkMZE/RHlGnYlXA6K5q2CyrsCWvIlQ0EnA24OiROhs+BP55dctuO3GYz/C7+2mfPMdUUPLkEEk7ObAM1ehRIIkZ+zA7awiNedyiiu/+Iqhl7wBR/r57H3yrRx+4ZoJbaq1dopWfw6jpZiaA9/CM0uNR2HFp+KCUdPhrKOxNNDqU8kseAe2lI2cePkL9Lb/b16GciTs4chL11O8+oskZ16Aa+g4FvtqvKNNjAwewZK0Kl54C+AaPkE4OILVsYaiis8CUQO4YNWnCfh6UKktuIaOIEnaCTUejvRzcaSfm7DrhuiufUrWpUTCHkRRRfOJn2CyraBkzVfm3U7McJNrHkCrf4UWU44EGe7fu6CxN524l9Hhatae/wsEQaKn7REEBNJyr6Bi291otPYF71Kq1FYUOcyqrT+kZv83OLLzOtQa69gmBqjUFjS6FGwpG0nJvBizvWJMu6MNSWWI7/j73G2AeNrE7QRRRKXVRHUQxtYAQRQnGVQnrw+CKNJW1TTlvKLWWEjOvIi+9kfJKfnApML4oH8wzoy0XOEdbSYScpFVeCWdTf9HavbrpjzOlryezMJ301rzS1prHsDqWEt63lsxWkviUTOPq4Hag7fic7eRmnMZeWUfQ6NNmnUMar0umgItK5RuLqd2bxWCKMRZIsezUEUifppO/BiYrK+jKBHCIdcktXtB1KDIQUy2lZSu/+acjPXxCuSnu2B7wvWPjSV2DSfrfCQaryZ76Yx2Ns4iMQh4faj1umlTo2KLwXQvU+ylEyUpujviDaBSqwgDciSCSqNClpVJ1HmvNoiSBp0hk3DIxcuPXkpqzhtYf+HvaK//PW21D6DWJpFV9J4pz52JllFRFFxDR8nIfxvl299Fd0N0d0gUtaw5/4eEQyLHd30aANfgEeTIRAYStdbG6nN+QtDXh6LIqDVWJJWRluqfUbP/pnhbeSuvG1OVVjj0/IfH6CKjaReCoEJSGRN1q85igTCY8kjJfh2djf+HRmsnt/QjCIJIX8cTpGRdiiAIHNv1GbJL3k9Syqb4eZLKjCRqkFSGqD7My5+msOIzyJEA3S3/QFP+SbyjzTgyL0SStHQ1/YXR4RNsuuQvGMz58XbsaVuBqEaARmufVEzuHDiAHAnFj0sEBEGI0+s2HrsLR8b55BRfNa82PK4G6g/fTtnG2zBaClm56bYJxlJP67/paPg99rRz8Hu78Hu7SErZNJY+oSAIEooSwefpxGDKJeAfoKP+dxSs+hTZxe/H7+mIO/iekQa87lYs9krMtrEC/wUaTLkrPkBB+SdQqY2s3n4vXU1/QY4EMSeVY01eN63zf3LaVm/bI6Rmvw7VadL60Rr0mB1WXAPDBOXAhF3zmQyq2Qy41OzX09f+P0aHqyY434qi0HDkTlzDx7E41uIdbY2LUC4nqMfY3Hrb/4fOmIPJVj7tsfkrP0FK5sW4XfW01z1E47Efsnr7PQB4XE0cf/nzaPWprDnvF5isJbP2LanVpBdmEfAGGGjvBqB2b9WEY8av2YoSoWb/TYQCgwBx0dEYMvLfhqTS0938z/hnKrWF9Py30lH/EFpdKhpd8pyMcjkcQa3VEPQFJn2nNeon6n2MGf6nc6Nrur7PRvpfwVln4zWK2EsQ27mYyRGYzbuOCfsZLCZSc1PxjvqiqVc6LYbMFIa6Bwn6/a+qkOB0yC//JPWHvwNAX/v/EASJnBVXI0f8tNU/hCyHyC6+Ku5YBHx9tNY8QH9ntM4iLecKHJkXxA1FRVHobv4r4ZALo6U47mhANGVGqysmHKgjEvaQnHkJA11PEfAPTDI2LEmr4KR8/YptP8Lnacfv6cRoKZmQlrJy43dob/g9HmcdwcAApqTyU0oXehbTI7f0I1FWpfqHiIR92NO2UX/4uySlbkatsaE35SBHTn6fI6RmX4bBnIcoaag892eYrCtQlAiZBe+kv+sZGo/fjTVlIwICzv4DZE9j0Dv799PX8RjFa77KyMAhdMasuCHX3/EEoYCTpNQtCdE0CPoHaa19gPTcN2NOWoko6aJUn3NgzBqPaO56QZyqVxBEetv+h0ptwpFxPun5b8VkW4EgCHQ2/JFgYAhb8kZGh6voav479rQtmJMqOPTcB8kruxaTrZzBnp0UrPoUOkM6unHpSXll17Dn8TfS2/4o+Ss/Nt2Q5oRY9CUUcOIcOEBe2bWznqMoCh0Nf8BoKcaethW/twe/tytKLXyaEA6FGGjvQVKrokrPYwaYLT2FSCiM1+VekENmsa9GrXUw0P3cBGfDNXSE4f49FK/5Cr1t/6Vq75fILvkAuSs+jCiplo0BGPD2ANHnUaO1EfT3T+sUCYKAyVaKyVaKRmunet/XCQVdjAwepvbAt9Hq06jYehcqzdxEHDdesobW2l48I6NTpq+NRyQSoP7Qd+K1gWvP/xVGy8RaEKOlkKB/CEUJklX0XjobH2bV1h+iN+ViTV7HiZc/x6HnmyhZ+0Xs6ZuIhMLxjcqpfo/pdLfGf35y5GUpMVWa1lQ1q+M/m48T8ooqepRQZ7k8o4nCvGbsk1kiYjjrvZ0ZGJ+HqcgyOpMRtVbDqq1lHN9VFX/5p8JMjoIgCqi1GgRRoK+tj9TcVCSbEUVWUGtVDPcKaA16tAY97uGR6K7FKZwkTiUc6edgvuB3OAcOEPD20N3yd4Z7X+bC9/yLcNhDW+0DdLf8g9zSD+Ps28tgzwsIogadIYtI2INz8CC97f8lo+Cd5Jd9nJbqn9Ld8g8s9soJaS4A1fu+gd/bzbodv8actIqBrqfQGjLQG3PmNFZBEDGY8jCYJuf0mpPKKd/0XQAGup6j9uC3cfbtwZFx/uJv0lksCqKoIrf0w6i1STQdvxtzUgWV5/w0vstdXPnFKc5RT0jji+24x3b3U7Nfhz11W9xQ2XTJw0xHtCnLYULBEWQ5RN3h72B1rGPFumhRaPGaryBH/AkTTwv4+6PibfoUImEf3tEWbMkb5nSu39tN7YFvs3Lz7RjM+fExxjDQ/Rwm6wo0umRMtjIs9koACio+jc/dhiAI0X5DowT9A+iNWaw9/1cYzAUIgsCGC38/ZSVATEnZOE51fbHo63icrua/kJx5IYIgEg57p41SyBEfQ70vxTccoixGIhbH2oSNZzzmsv4bLCa8LveE4lpLih21Vo2zp3/hfQsijvTzGOx+noKV1yGIKpz9+2k6Ht3xd4/UMeqswuJYS0f979BoksgoePuC+0s0hnpfQq2xkZJ1KV3Nf2H/M1dSsfVurI7KGc9zO2sRRDUjAwdpr/8dVscaSjd8e86OBsC+Jw+RnJOO3+2d8feT5TCHnrt6rCaIeHRwKuSVfgRn/x46G/9ESvblmKwlOAcO0NX8NyBat1Gz/yY2v+4/8TlivMDvdJjuGVOpVSiyhrT8TDprW+Zy2QtGrP9E2LvjzxdVEhqdLl4WENvTO5XF6KcCgjIH4m2Xy4XVamXL6/+LSn02lWI5IxZijBnzSZmpDHf1TXu8qJIwJVmp3FbCwReq8Tpds/YR88BjL4ykVmMY0+EIh0KUbSrhou1GWntE2ju8NBzrQK1RI4gCQ939hINhRJX0qnQ2TkZv+6M0HLkDa/J6jJZi/N5uhnpeBECjSyU1+1IGe14kHPKgKFFnLyP/LXQ2PYwiRwCFotWfJz3vTZPadg0dJegfIjnzAryjzQz17sKWsnlOIfT5Yu+T7wAlgsW+mvzy69EZMhLex5mOU73poigKJ/Z8ARSo2HbXhO962/6HgkxazuVEwn5UaiO9bf/FPVJPet6bpzUWxqO15gH0pjxSsy+dYQzRQnC/txvvaCtJKRvnHXWYDnIkOFGgLBKk8dhdpOZchnUaw1lRFFqrf46iRMgoeDvtdb8hs/BdGC3FUx4/2PMiNftvYsW6b5KStXh66nDYixz2oShhVBobUoJYuRRFwedpx2DKJRwaZd9T76JkzVdJzrxgmuMjY6lfCoee/xAGUx5lG29JyFimwvjNKEmtjqbA+P3oTEZ8LjcpeRm4h0cJBYKEA8FoPd+Y0vNio92jzhqOvfRJ7OnnUVz5JQ4++360+lTS8t6EKGqoP/xdNlz0f3S3PExP66Osv+AhtPrUZbFJemzXp/F5Otlw4e/we7upO3QrWkNmfKNnOvg8HRx67kMoSoSckg+Ss+KDcyJkUGk1yJEIpiQrHufonO7/kZ2fwD0moFix7e5p370YRgaP0nTiHoK+PgpWfYr2ut+iKGGM1hUkZ55D3cHb2f7Gf6LWphIJhactRF/uOHnDdC7P08kpYNNBHKt1nS1yMhNOxfMdDnnY8/gVjIyMYLHMzPh22gmDT+bQPoupMT6qZHZEi75Ovm+CKMYf5NhLoDNMXxAYczQikQj7nj6KHI7ERfhmwnT5kZ4RF0FfgJbqTv7z6CDHjgzgGQ2SU5KOpJawJpuxptrJryhEFAXyKorZcMn6VxVv9cmwp23DaF3ByMBBupr+zFDvSxgtpaze/hMKym+go+EPyJEAq7bcydrzHyQSHmVk8BA6QyZWx1oqtt41paMBUW52R8YOfJ5OJJWJ7OKrlsTRAChY9UkM5iIGe17iwLMfoK3212fTqk7CqTZcBEHAnFSBZ7RxEqVpT9u/6aj/A7UHbqbu0G1AdKc9EvainkPRKERrkNzOqim/c4/UEwl7J9QpVO/76iSdmYVCkcNj2h+vbJSIkoaStV/F6liLIocnXbMihxEEAUFSYzAXoDNkULL2a9M6GgCSyojBXIQ9bfvix6wo1B24GefAQbT6tCkdjYXOdYIgxCMVgqCioPx6LPbVAHQ1/ZXW2gfxe3uo2vtVAr7e+O/iHNiPz91KRsE7FnhVs0NUSaTmZmJ2JKG3mLBnpuB3eyhcU8I7PrAOS0oSfc2dlKwpIOTzx9+T8cXiokpCZ5q4kTnXe2W2lVG64WaGenZy6LmrCYdclG74Num5b8TtrEZnyEJnSKew8oZoPVLzX9Aa9Wj02oTZHgv9XV1DRwkFBjm++wvojdlk5L+T4d5ds4pW6o3ZlG64mYpt95Bb+uE5M7/ZM1PQmYyEAsEJ938mxHR7trzuP9M6GrHrb6//PVV7v0zA240cCVB/+LsgCJRtvJWKbbeTteJiAGSimj6KLJ+RjgYQjzpYUuy89/od7HjbFnJXFc34TM3F0QCmrZGdzxpzuh3pk3FKajZmSsE5Ux+06WC0W/EMjSTUq9Qa9RMKpUYHoy9/NAXilfs6VX/jc/xPhhyO4OofmrGv2RCr1/C5PWMaGgqu/mF8Lg+KImO227Cn2QAY7B5GkiRGnW7Kt5ZxfFc17TUhdCYDWoM+Hk5fDjtOsyFWUD/b86vW2Fhz7s8Z7HkB19AxDKY82ut+y7Fdn4ynvVjsqzFailAUBbUmCZXazKot348Xec/EZBPw9XLw2aso3XAzWv2OKY9JBFIyL8KStJq+jseJRPy01z9EOOSmYNUNCUuZOYv5IznjfDrqH6K19kHyyj4W/y0qz/kpocAwoeAI3tFmDj73QdJz30zJ2q/N+ffKKfnglKrFihLh+O7PkVnwThQlghwJklf6ETa/7t8J0ZOBaI64Rpc8ZQ57MDDMoec+RHLmhRSuugEEkcMvXEtqzuvJKnw3eaUfnXM/tuT1rNvxYFTDZrQFldocr+uYPxRsKZtQqY1Ewj5ESTfpXqflZ9HT1D7l2XNlrJJUetLz3hz/W5S0hNzD1Oy/EbXWHlccB+hs+CNG64p4ilgioLeYEEQR/9ic78hKIz3PQe2BYVRqNaODI6j1OlqrWhjudSKHZfIrS+honFk0MhKJTJj7o7nrcxuTI/1cyjbeQlvtgxRVfiEeeRVFLaCg1uswJVnIW/Vemo7+lopzv4jRasfn8iKIAuFQGJ/LPVZTMncGpNh6v9D1Kil1K8N9u/GM1FN78Bbyx6iT3c7qWR1gR/o5c+5HpdVw7hs3cHxvC0Gff17pORsu+tO0c4YgivFn2udto632AUzWUqzJa+lsfBiNNpk1592PVm9HjkSQZDOSSk9vy1FySiribSyX9T7GzDkXKLKMJcWOKcnM0SND9LT2Ex5z4ARRxJ4ZnbcGO3oSMrYzveb1lDgbJ3Npj8d0N3A5PYBzhaiS8AyNAGB22KZkdloIxnvDRrsVg9mI3+3D7/URCYXYfsVmqg404xt1z9lznktfc4EgCoQDwQmpVZGx3Qq1XoezbxD3sItQIIjJbkFr0OFzeWk+0YEoChgcNgRBJOgPoNJq0JuMjA4On7IX6+SUsLliPilggiCQnLEjrntgspVx7KUbCAWdQDQ9JHZcdvFVtFT/nMZjd7Ni3deBmfm2VWoTa8//FXpTLj1tj6DRJieUCSgGWQ4R8PWSlnM5Gp0DrS6ZpuN340g/d1qNhrNYehgtxeSXX09L1U/xe3tIy7kcj6uR9Py3oNE50Ogc6Azp9LQ9QnPVT8goeBsw+y6oe6QerT5tGjE0kcrt9yGpDAz27ESRg4iSdlE6MrIcimt1KIqCpNJTvvn2KY8d6HoavTmPnrZHUGus5JZ+mLTcN8SVkxcCRQlzfPfnSc64gMKKTy+oDUEQySx8J7Ic4uhLnyQ1+/VkjosomB1J0zoasPCNt2jk802MDB6J/+YArqFjjAweomzDrQnbEBBEEZ8rGr3SW0zYUu1RmtSIgs/lJq+iGLVWRWtVC4WrCxnoGqKwIpfju6oo2bACv9eHHI4QGPt3PGLpVbF+5jv/29O2TzLQtYZ0Ar6+Mac4Qmbh+TQc+hl6Y4CLLitCEAR2PtuGLCuk5qYxOjQ6q3E4fi72j3pnPHY2lG74NqHAMD53G9X7vo7FXolWn05b7a8wJ1UsWowwthmoyArP/e3leUdgAr4+Ar4+zLayKdMjFVmOP9PdzX8HwD1Si3ukFou9AtfQcdpqf0PR6s8w0PMozcd+haTSEQkPIY85l8sJc3U0YnD1DzE66CToSyPoCzA6OExSZip6k57hnkGK1xYlzNmYyY4+E3BKfukZi4/CEfSWybthy9HRkNRqDLZXXn6VVoOokihaV4olxT5hcnT1D816DZYUO2q9DlEljU0K4pQhOIPNwoqNK/n8TedxzusqcA+74jzYklrNrv/uZaRvEJ0puhPuyE4/ZS9x7JqnutZwIEgkFI4zUYmShByWsSRbcfb0ozeb8Lo8OHv6o7tkkUg8ajPTQpOoa5PUahxZaai0GlRazSm7ZyZrCZsu/St5ZR+jdP23Kd1wc/y7zMJ3kln0Hvo7n8Ke5ceWHmWImu5+qNQmjJZCRFHFYNdzuIaOAOAcOERz1f1T7kwvBK6hoxzbdUO8SDA15zIAju/+HIPdLyakj7NYGLIK303J2q/jGjpK1d4v09Hw+wm0rpLKQOm6G1l3wW+Z65Rfs/9GOhp+P+V3giBgMOePaX+8nayiK3ENHaXu0HeRF6BQHfD1c+i5DzHctzfe91DPzmmPFxAx28rY/oYnyS39MACZBe9YlECfJOlYc+7PyCu7ZvaDZ4EoqknLuRzTWBF+DLG5LZGIhH10t/4LRVGwOtagN2YDUYetre43GMz52GfYAR+/ns0FOSsLMNqt6ExGBFHkqvfl4uwb5vjOY4gqibaqJlqONyGKAmqNio3nF9F0vA1Fkelt60cURPLK81h9TgWlm8vJXJGH1qiPjnkOLD7zhVafjqKE8Y62o8gKnpFoWp6kslKR62dr0RAbt+eg1qoZ6h5ksKNn1jTi8XPxTA7ibO1A9LnTGTJISt2CPf18upr/SmHFp/F7e9j35Ns49vJnZ02pmgmmJCs5ZQXxlNdYCvRc1jq/t5uDz32QY7tuoObgzcjyzM6wLbUIgPKtn2P7G58gqyjKZudI34HX00jN3tsJ+HoJ+oexZ5ROGM+ZivhmpaLgHh5BVEk4ewboaeog6Auwfp0Na9pCI6UT+zmT7xMsQYH4XHakx+8mx4rEtAZ9fMdkuUNSqymoLKL5aGN87EFfYJLgy3gIoogjKw1n3yAavQ5TkhmtToPP7Uej17BhWy67nq4n6AvgHbsPkVCIS9+znf4+L9V7a+OTlyAKbL90Fbufqkaj1+IadCKKAgGPD0mtRo5E0JkMs97PpXyAY85FbIdKZzag1mgIBYMEPD7kSARRkggHghhslikL0y0p9klpXokeoyCIE4rkosJT0aK1qPL5qX/BFSXCvqfeRVrOGxZs/PS1P0Zf5xOUb/oe7pE6BrqeobDiM1Mea0tPmZYRRhljHlKpTfg8nRMKi0cGD9Pd/HcGe3ZSuOoGUnMuR5R0+NytBP0DSCojJmtJwgqGX8t4w/vP5X+/n94AB4iEvfS0/puW6p/jyLiA4sovTpivvaPNOPv3k1HwjkmCXCfD7+1GEMQJwnfj4Ro+QXvdb0jJfD3D/bvxuVvxedrRGTKJqjXLpOW+ccLO/nSQ5TCtNb8gs+BdCKJEa/UvSM9/a5wx61TDOXCAgc5nKF7zpUW3FQ57iYRGp72Pi8VA9/M0HLmDtec9gM6YGf98sGcnNftvpGzjd2ZMtzE7kuJO0FzYbwRRZNvlGzm+t4FPf7qU799+mKDvFd0MUSWh1mqm1FUaz4aYkpfJ2q35uFxBqvc3xVkKE41I2MvBZz+I0VaENXkNva3/QZJUvP0ze7nzyk5q5JV8/+4W5Ei0b4PZSH97T0IK1+eLgK+P4y9/dmwObcORfj7Ogf2o1CZWrPsG5pOoy6dDTA1co9Oh0Wsn7KyLKglLsn1WBjBZDlO19yv43O3klV1L/ZHvUbjq02Tkv3XacwxJFgymCCq1nf72HnzuPvY/9U6yit9Fdsl72fv4u5AjQQRRzaZL/opaY53T9SxnxNLIwqEwQ9198ehDRnEOkiTSXt2M3mJakG17JqRNzadA/JSxUcUMu0gohN5iilbaK3I8bWd8rlysbuBM8uTG59tO9ZBIajVJ6ckM9wwgiAIXvW0TG1cqqCSFrmEN1XU+cnP0HNzfz2D3MIqiEAoEEUQBlVrNYEcPKq0GtVaDRq/F6/IQCYXQGqK7Qn63F0tKEiO9g1OOb2Iu7NI5GTFHUpQktEY9oUCQ1Nx0/B4/Q1196EwGNHotfreXgMc3aSzzyZlcClhS7AS8vrjjdrpqig4+9yH0phxWbrx1wW0oiowgiAz27KSj4Q8UV34JtcY6r5z0od5dVO/7OmvPfxCjpWjKPuoOfY+BrienPF8QtVjtlTgyd+BIOxe11rbQy3nNImYErtxWQfXLx2c9fqD7eeoPfw+V2kxx5RdJSt0S/7yl6qdUnvPTOT0DUwlNynIYZ/9eupv/gXNgP6Cg1qVgspaMqVWLCIJAMOBksPtZsks+MG0NhSyHcPbvIyl1W7Swe5Z5SVEUOhv/iD1tOwZzwazjXyiGenfR0/pvVm76zpwLb6fD8Zc/hyhqKN9yR4JGNxnBwBAarT3+txwJcPD5D6E35lC++Y45p1DpLaY4W1Qs0jveYYjNzbHoe+GaEirXpfL3B16Y0I5ar4s7LeMZC8eLu4oqCXtGKpe8sYSnHqmPi8otBfo7n6bu0K1IKiP29K28/gN3oTVmcs071KSrevnaL3S0VzeTXphDX1sXyTnpDHb0JXTuD4dGUeQIKrVpxs2Xvo7HqT/8Pco2fQ976laq930N19AxFCXCqi3fj5MCzIRYsb3P5Z7E9KTSakjOSqO3pXPady0S9lF78Gac/fupOOcHWGxrOfrSDXhcDaRkXUJq9usxJ1VM+VzFDOuYrVK7/27a6/6AzpiOHAmg1aeQWfDeaVnUzhQIooikViFHItgzUtHoNSiyQm9L5wTbL1a7kZLtoGb3idM44qXBsnQ2xkcwgr4A6rGH0etyR1Wmx4zoSDBMKBA8o6hRY3mRM3mheouJcCgcT32q2L6S2zc/xR31b0SrlfjUimfosKziH/vTOHG4m4HO6M6Dz+VGZzLgd3vRmQwEvFHnTJEVclYW0NfaQyQSWbb3SlKrMdrMhALBuHcviCIGmxlRENGZ9GQVptLR0LukC85cENsROt1q55FIgN2Pvp7s4vcnJK0jhpoD38Ln7mDdjgfnfI4cCdLf+SQp2ZcTCbuQI6EJ4n8Ag90v0nDsh+SVXoPP045G58CRdi6h4DC1B28jEnYTDkUdyOyS95O74kOz7qyfxSuIUSzOZ5PA7+2m8dhdOPv3k1d2LVlF70UQBCKRwASWJDkSxOdpx+duJ+DrQVSBSp2KSmWiueo+Vm+/D7XGgqJE6Gl7hPa63xAKDGO0FJGSfRmO9HOnpUFur/89bbUPUHnuz6aMUgx2v0jNgZtYd8FDk0Qop0Ik4mfvE2+ldP23sKdtm/FYRVEIh0amVdieeGzUKR8ZOIRz8BC5Kz5MJOxmsGcnQf8gWUXvideTzBejzhrUGivO/gPRNCfT3DRwph5nhGganELD0R9gdawlNft1k45rrf0VnQ1/YO2OX095X8dHM2KIRR2u+ex2du4aomZvDQaLCVmR8QyNxB2M8WtcLIo+0zMZa1elUZGcnYbepMPn9uPsH8brHMWa6sA9PLLkegKBQA8adTKCqEJSq7GkJFG+IZ815TraexSaGpw4Uoz097oZ7Bmmr7kzYX0riszuRy9DloMgiGh1qWgN6RgtxeSVXTvhfexq+ist1fez7Q1PIAgSzv79aPRpNB79Ad7RZtZf+NCsz/R4Z2O63yavophN2zK5bFUnDzxhp6fDSV9bL70te6g98G2CgWHKN30XW8pGIErK0NP6b3pa/kkoOExq9mWUrP3qlH0DpOZmct1Hs/jJL9robjpE07EHGOrZxer/Z++swxu5zrb/mxkxWzIzLjMl2TC3ScrwlflNGVJ625Qp7VumFNKUmblp0oazgWX27pqZbUkWSzPz/SHPrGSUYSnxfV25spZGZ85Ihx66753fmJUd7lwjlzVWNEhUr6sjGoqRjCdJJhKE/ePYPU4MRiPRUISIPzhtW2/73yv4zv89MkPLc2Opox1aHxfqgD7vjA2NGm+k73TozmA06BawttBIRiMWp42If1w/vGtpLedDlGMyl3guodbMH1Gj+S2pLSMWiWE0GUkmkpgtJmKRNAOUyWJibGCUWCiMxWHPSi8SRJGaDfW0Hjylt6cVaMPZVdNcSmhegqXYcOZb8K2lexnNphlDnUsd4cglPWz/g6/Gnb+Zhs0f0Pm2F9uPVGKceGwoJ40FgHd/5HK+8bl0PcbxPbeTSowTGW/lohv/nrOxEIv0I6cimMxehvr+SdvRu8krvIgVmz+CwZi7ANUzHQsReFJVhc5TP6G76Wf4iq+gYsXrUJUkosEKqsJA178Y7LqHVHIcSNd2iJKJZNyvt+H0rMXqrGJs8EmS8VEKy2+kpObFOVEsq6rM/gdfjdVeweodn9fHjKqqhAInGe1/HGfeWrxFF+X+TEoqp7S8tL7Nl9h+3e9njeKcOnAHBpOT2rXvpPPUTwgHmlm9PU0V/NS9zyGVDFG3/n0UV90CpCM7giDlxM6jITBymONPfYCGzR8hf4GimP7h/TTu/hCbr/oZZmsBLUe+htu3mYKyayddt49jT76fihWvpXLF63Juv7i2gqGufkrry7G7bfS29BEcGp3xcJNLBFpbi01Wc9qjXlqAwSgRGY9y0eVV3PfnQ8RCYVRFxepy6Ac0OLM1m1qUxZHnpnJlCeXlDgQBXrbhJINKMUd68/j7n5sZHwnklP4yuc/THeAe/9f1qIpM7bp3TRRd9zPavwtPwXZWbf2kPqbTtXHvonb9bZRUPU+/RyI+yv6HXkNB6TXUrX/vjH3R9jM5mcrq03SoWF3DDc+u5Dc/OUhoxE9Py6/oOHE3ksGKM28day/6Iu4in54tEY8Osvf+lwJQWPFsGjb+74x9cOS5cXpdjPQM6eQw/v7hC5K5MHMO+MqLcee72LqjmGRSxW4T+eNP92Jx2AiNpcmBMpXRASSjATmZQhCFib+N5/ycNtNZQjRI5FcUExgczYks6IwZG5fc/G8kyTZhAOTG0QynvRtGs4m6jbW0HGpN53WqCnIiXUCca1tLdfCbryXnLvJhtdtmDT/OBqPVgtFsmmBjCqeLpiUJb2kBo71DUwyqyUZKpmEzU03I+WCQzYb59PFM5itO7ocgiqzYtoqTu6fXFDgXOPLEe5Aky4yMPAvBXAfWzLQZVVUJjh7CZPZhdVQwNrSHeHQAVPSDF0DLka9jsuRT0fCqGdpUAEFvd2zwKU4e+Aw2RzVrdnxhyahSny6YaY4sZn4P9z5I2/HvkogNIhnsgICcCmEwuiiquAlv8aVYHRUYjG4EQSAeHSQUaCKZGGO0fxexSC95hRdRUHrtFBX7uZBOw/sI+aVXYbVXMtz7AKnkuM7EZnVUs/nKH84rXSkwchi7s2ZWtWRFjjPc+yCFFc9CVRWaD3+Zoopn4fJuYLD7PiSDFV/x5fR3/B3JaKegNC3oN3kODPX8h86TP2TLVT9DRWXvf1/Kmh2fnzF/XhBFRKNI+9Gf4C26FLurhqZDX2J87DibrriL8bHjDPX8h+o1b5tRAVxDPDrASN8jlNa+BEWO093yG0prXjyjwy8eHeLQo7dic9Wy9qIvzvqdTl4LtD1GMhrTdLblhVnefacvj2Q8QTwSxWA2zXhY0tJoBFHEYDZhc9kxGI0konHsbgdVK4vwj0QYGwrgcNtpO9w8RU15qes3J+8l2nlEEAWq19VSt9LHmzce5IS6mhLLMDY5yJ2PrsBqk+jtDtG0v3law2rVxWtpPtA0Ed1REUQBUUoftJOJdDqaFiUf7n2Qk/s/TXHVc6hddxuCIDA68ASNez9CUfmzqdvwPt0YP77nduRkmPU7v5F1v+bDXyHkP8GmK34w7TOqiorJas6ZUVI7DK/YtoqHf/95Wo58jeLqF1Kz5m0M99yPqqYoqrwZVVXoa/8LyfgY3c0/x+XdyOrtn53TWVRcW8En32njq78UaT546ryvP5gJmWfO/IoS1m6roq8rbVj4R4IMd/VTXFvOm19XzF/uT3Dg/gPA9Gu2Nu+W8rym9S9zTs+3/UzWsvl8bj7GxrwqN0VJwldWhLfIQzyWpPtkx5Qw6uTaAM2ak5NJVFXh2K4jQJpibCEKoosREsv0OMwXgYERAkxfD5ELlJRMLBkmHo7qi9+HP34Rv/7TMGP9I1N+4My/JxtXixV7gXNTfDSfPp7Jvk33XXcc78hpIThb31tw5CAOz2qdEnQpFqfetrtIxuyU1b5Ef017nsGufyPLcXpbf8vai76MxV5K08Ev4Cu5kpo1byWvYDsA4WAripJCFA0689BMXm5ZjtO4+0MUVjxbT/fIK7wIh3sVgeG9HHn8XWy64u4zllK1kGjAuYb2G2dGKSePubzSQoJDY6iqgrvQx1jv4LTRMm0Tqlr3fErrn0X3qb8zNvgEqipSUHoVeYUXZSl0azBbC3Vti+LKW6a8Px94i3ZSu+499LT8isDwQZx5a7A5a3D7NpFMBjm1/9O0Hfs2lSvfkFOkS5HjNO75EDVr3k5R5c1AOr0qOHIIu6ueVCpMOHCK/JKrdMa0ZHyMRGxIp5iORXpJxEbwFV8+RTAz0/MqCAIFZddjthaltSzifooqb8FoykNORfAP7cNXcjmCKGJ1JQgMRjCaXDTt+zoD3fcy1PMfNl/5Y6pXvzkdURKNSAYbocApBARUVSaZCGI0uYmFe2k69AVq1rwVZ95aTu7/LMn4KMGxI5TWvgRRMlO54rUzfi9yKkrj3o8giBIrNn8UQZBmdcxNnhfadVo2QWGZj2ueVcfe3YP0tvQiT5COPOcVW/nD3Y9ljc/M+2hGgqoounPNYDTg8KSdCsd3t2AwG3F5XXQca5uypikpeV46T3OhoKqUoY7erNc0enZBFBnpG8U/GOC2wyW84PlW9rdUoqhw8UaFzT96KYH33slfKzbzyD1HqFxZQWBknKGugXQ9wu7GSdEMlVQqkVV8rbFM5pdejZyK0Hz4S7ooo7foEho2fJCmQ/9HKhVixabbESUz+WWbaTvyM1LJcJZhKQgiipLUDTmt9sVksWD3OCmpLuT4RF1ALvuF9v6+//6O1qPfoqRmJ31tf6Ki4dUEx46QSo5TVHkz8egAbce+BUB+6bVUr741p7na39rFW25L/wYXMm1rZi2u0Wzk+P5ORnuH0tk3skzDlpW0Hmnlzh+kGOke1DNQ2g43621ov8fkWqal6t/krBZVUfR9QyMWmm4tyDwLTz7X5LJ/2vNyZ7Obl7Gx+cp1tJ8co6e1FzmRwuF1EfaPZ3XI6nIQC4XxlhQyPupHmRDImS5PdCERiswvJLPofDZo6UZpwyi7aE1joZjrx9fCxgs99J3uo6zXbdz7WJyuk51nPSJxmob2wvQ0nAlohY+CKOLIc89IU2l3u4gEQ4uKrs2V7pb2rhqIhbsn8rSNSzJGQmMhHO7s/HqTxcIVt2ziC295LVZ7BXmFF+sHzfU7v4HJkp/RL4WjT7yH4urnUbXyjYiigbr170mz9/Q+NKXoT5LMONwrMVkKMtpQsbtqsdhKGOj8+0SBcO5pNPPBhWZoZCKzRmPyRj3WO4jFYceR59LrnAorC5FlWdf5AXj5m3fy6+8/rr9WWH7DtDn+Zxol1c+jpPp5074XGW+jt/X3JOJ+Vm39xJxtiZKZVVs/jTt/i/6aIsdpOfJVSmvTtRU9rb8lv/R0epHJ4mPtRV/S//YWXTpjnclkCIKA27cRAKPZQ83at6S1BTr+Tuuxb7HO8k2cngYe+dPLKKt9JSXVL6C05sWYbcUTufVCllaCw93Axsu+hyCIREPd7H/oVazefgdu36aJaEna2IlH+4iEOthx3Z/n7KOqypw88BmioS7W7/wmpgmF+MlrVK5ptql4glAwytYaicK8An76wyFCo0ES0Rj79wxQsbqGzmMt6e9HFKdEQTRE/EE9HdjmtBMZD1NaV0pkPMpQ92C6Vmaa/XQpMhc0hr3hrqkaB9ohTFUU/P3DqIrCSI/IN0+0YbJYiIXCGK0WfCVf4p1xF5FIiuKqYkb6x6hfU4a30E1XUw+Z8YPpMg1MVjNyStbXoep1/w8ElebDXyUUOMWqbZ+msOJZSEY7p/Z/hiOPv4uVWz+J03UxqvoTTu7/FGt2fF6PUCViwxjNHlRFwe52EhUFBCHt0B3tHcQ/MDIrFf3k/gFEI+0cffx/cRds4qoX382hh/+ByZxH/Yb369cm4qOASvWat1FW+9L5/hRTjL0LGZdeXc3jD6ed7IIq4C0pJJWUKa0rR1VV6jc30HWqW0911zDX77Fyx5pFZVYYjAaSEwNSc/IbzSZSQmrWuqqZAgWiQZo2SmK0WvTPGYxGUsncI5DzTqOyOtLhVEgXAQ129k4Je9q9bkpqSgiOjhMLRc8ofelc0BbYwpoyAoOjaYYnQUSR5SkhR6vLgcVhY6x38Iz1R/NKGM0mlJRMMp542qmon884l3RykynwpqP8VVWZvva/0nbsm2y+9lvYrOuXpM+qqiKnQmmP5xzpGzO3oRAOtmA0ebKKxJsO/R/hYAsbL/v+lJzczpM/Jq9wx5S0E1VV2f/Qq3F7Ny4Jxei5wpmuk8rFuWHzuFBScpbxcaaxlGkAg13/punQF9h0xY9yridSVZXR/kex2Muwu+pIxMcQRQM9Lb9luPdBtl7zyyXp22z333v/y/CVXE7lyjcQHDmIy7dpztSoTKSSYfxDe/CVXDEluqfIcaLh7mkZ4DJhspk5sfuL9LX/ldXb75iXoOd064qWjqMpaTt9HoLDo7qHdHImQq5pzQazicrV1QBEQzGCowEi/vEz4mgzWi3pTIocU0ImZ2N4ivOJBMZJJdKRW7PdyorNtRx78gTAnCnkM9WdOH15hMYCBIYPc2LvR3F5N7Bq26cBCPlPcmL/J1HkOBsuvRNvCfznly9nzUVf0qPKnad+Sn/7n9lxw1+QjEY8RT7GJqIoZpuVWCgydwqmkCZmGO3fRSrVw9jgCWzOGtZd/DW2XreTw7v209P0V0qqX6Cv5W3H7qS3/Y9su+Y3uiPqmQZNcFgyGgiNBfSamHRUo+U0C6co6OdjSDsncxUpNlotqIqCIsvnhaCxthZM977V5SARjVO5uphf3FF3ZgrEzTbPlAXH6cvDZDUz1j+kv34uipW1QmNVUTGYDPpiUVhVgtFspLe5i9L6Ckb6homHo9MWURnMpjP6Y2sej0Q0rvcVlsabs4zccC4NDovDnkX5nIl4dIjDu95KIjZMcfVzadiUPoQvRV9TyXFO7f8ssWgfm674EeI0Rba9bX8EVaE0I80qF0xHkRoKNNHf8VeCo0fxFu2kevWtBEcPExnvpLDiWYiigfbG7zPQ9S92XP+nrPzyC4Ff/ExiPgf50hVVOD3286reaL5QaOOJf7yezVf9DFEwkIiP4fKmjdNoqItYpI+8wh0AJBN+jKb0HvTEPc/CaPKw6Yq7dIYeRUkSGDmoH9DOJCLjHUgG64wHsHh0gJ6W36QZh+ZhhMhyDEEwTDtHNQiiSCoRoungFxjpf4S69e+luOq5836GXGC2W3OuA4Ds+Zt5oLF5XDqhSSqROmd73nSp3tMdqlwFXhx5TnpPdeTc7lz6TJpxNtT7AKf2f5qGTbdTWH4DgigSj45wZNfb0zoUN/yQp+5Ji+LVb/gAnoJtjA48SeOeD1FW93KqV795Qc/d1/5XWg5/BburDkfeKhyeBlbteCV1a1ey77/7Gep9gOZDX2TLVT/Tx3UiPsahR/8Hs7WYdZd8fdZx+XTF5DGTeXb7w2ck3npXAf7BUYprS+lqTOu2lNRX0N/afUHsZXM5DWZ6fz41G/NKlhZEcVar3upy6Plh56LaXsuJM1nNFNeUUVRTiiLL9DV30nmsBUWW6TzWQng0MCX1S1sUU/HEvPILzXYrMyl/Q4buRMb7qUS6GFwzdpYNjbOLsz35tTFgdaXzlhPROAazSVfO1dDf8VdSyRDrLvkyL3jbj9IRuEX0VVFS+r0NRic1695Jw6bbp90sVFUhMHJwImQ+Mwa67qH9+Peyn08QCI4eoaf1D5zc/2n62v6EyZKPf3gfJTUvYqT/MVRVxj+8n6Ge/+iGia/4ClKJAEM990+ki6EXqD6TYbKaKa6toGpdPVXr0jSRBvPU2gqAvuauC9rQAOhp2oUoWbHay+hq/gUn9n6Ukf7HAWg5+nVajn6daDidprP/odfS0/IbBEGkoOxa7K46DMbT4mCiaDwrhgZAIj5CIj46Yw2gqqqM9O8iGu6eV7tP3fscBjr+Nus1IX8Th3e9Hf/wXlZt+xxl9XOLJ06HmfqeuV/NZWhMVsrOjNJoCtGiQSIRjaEqKt6SAhRZnkhvFvVo/0JqKWfqcy7Q1NNVRUWUsj8riCLBoVHd0NDSR2ZDek9Pzuoo0AuNS64mv/Q6mg7eQfOhL5FKhDGZ81iz4/9Ixsd44p8vRpQMpJJhjj31fpoPfwVf2UXUrPsfelt/Rzw6uyifBovTQMep7/LiW7pxeK3IqUO48zez5ZqfsOHyz1BW+xLKamvpOJmOiFaseA6vvL0Ri71Yb8NkzqN23bsZHztKyN+Y031zQSoZ4sjj78Q/tHfJ2szE5PGUi6L7TNB+U7vXrUcf0mmAAm+7u5DA8BiyLKPIE2lIksRgRx+OPDdmu5WVO9bobV31oktmXM+n6/fZwExnUK2fcjJJ9YYGDGbTvOeZhnk91UzhFCCtjSGkvfaiQVpwh2bDXG1qh7doMETH0WZ6T3XoCx2kD5mZbaiKonsiDGYTRqsl7XmeTzV+IqV7RmaC0WrJyqXUftjMfy/j6QttPEWDIVITm5GcTOlkAZD2gnY3/wJFjuH2bePwI0cXNTYGuu7hwMOv0++9+74XEPKfxOlZhSxPdQQERw6RiA5RXj89q5SGkP8kZns6332w69/6IXCg8x56W39DQdkNBMeOYTLnsfXqX2FzVFG9+s0IgkRFw2uzWHIcnlU4PKtpOngHHSfuBi5Mw3upN4dENE44ECKZSJNwFFSV4shzp1MniguwOE4XjZ4LBrqlft7RgV3kFWxHECQqV7weyegkHknneVfUvwZFTqAqSSKhTqrXvI28wrTGhiiasbvqdOO19di36Gr6+ZL2bTb0tvyWnuZfzfgbWGzFbLv2NzjcK+bVbsOmD+OZwWBSlCSdp37CoUdvBWDDpd/BV3zpgufN5Fxs/T7zMPgn33vaQlRBxOnzpOs4IrGsg7l2oFnIWNbGoiDm7pjR7pOZwjoXCct8nadzzRFBEFix+SPUbXg/Qz3/peNkev2zOipYd8nXKCx/NnmFl2I0eRBEE4Nd93DgwVtx5e1AVWUGu/855z0UOcHe+95J96nfc9tbXsW/f7Kd9uP/pWr1LSgpmb6WR2k7+j2OPHoAg0lCMPQRHQ/ReuB0JCevtFBvCyA4eojJyTCKkkCdIAuZDuFgK0cefzdDvQ9kvd7T8huCo0c49tT7aT32rSntLhZTyAfkxTuxNM0ZUUr/V7u+jkuuqqZyVSX5ZYX0nOrU76UqKlfetJayhgraj7UhiCIVq2tobxqetp7wbNA+zxeZ/Ww/3IScTC3YGbjoeFg0GJqo0k8vGPFw9IylUM31kKlEalr2iczPKSlZL1bXdD3K68sYHfATHB7TRfNyxVyLvKoo55xTeRnnFzJZHuRkilDgJB2N3wdAlCxEQ12LEv+yOOxY7eXkFZwuvK5e/WZEyUTjno8S9B9l/SXfwO6uIRxow+aowuldh9lWgmSwztIyVK95C5JkSdeWdPyVRHyE8vpXpusuVBlFlfFMFO+mi2s36J8VBAFPaanO2y4IAhsuvZPDu96es6fuXGC62hoNM4WXF1PToCoK4UBQJyIY6ujF7nVTVFOac0rHUmLysyzlZphM+An5G3HVrqe39Q+oKGy9+mf6++78jWy79teIopGOE3cTGDlI0aU3AlBS84Is5WyTpQBROHspHg2bb581PWps8CnyiraCOj/jTKPhnYxIqINT+z9NeLyN8vpXUdHw6gWLDU7Gmd6jVFXRayEn10TOh0Z/SrsTY3Excy2Tyc1st6IoKkpK1uf1fNPIcu2PwWSiuPIWEtEhelp+Q0X9qzGaPdhddXqtTkXDazi1/zP4h/eTjPs59Oj/AJBKhHVmzZk0mIZ67ycwcgibqxarvYy6TTdjNKYY7U87eyKhdgIjB6lc+Ub6mjvZ85+34vJtZtXWT+j9136r/NKrCY4eouPE3cSjPdSsuQ1RMjHS/yin9n8WyWgnv/RqrI5KzJYCxIk9IhJspb3xuwBIBmvW2PYP78NsTYsb9rX9kZKq5y9q35sLMxVDZyKXdVtJyTprW3W9l631UTraLXSe6NTZV9WkApLEw/86xrNftI7+9n6sRiNXXFPJL+98eNr7eorzz2i98GJwmqxk4Wv/olZmrQNKSiaeOj0ZzxULjLYx+8qL9fqRyYPHYDaRiMX066PBEC2HmpGTKZ17W1WeGXnjF4I2x9MF2maQKfijKgrdzb+k8+TdmG0l1G14P4nYMBZ7ma6ArGkfzAeCKODyrme490Faj36Dq1/2FSBNA2q25TPa/wQ2RxVjA3s59uR79cLcXNiAJCntARUEidp178bhXjnxtwCCAWmOJUUzNDQM9z1EyH8CX/Hl83rGXJFJ/7dQ7+9MhgbM7GxY7LxSUjIWh4WbX3kx9/x2D+HRQBbT1NmEKEnIEwcah9c15TdcDNK6H2kkE349nS7r/hMH6oKy67E5a/TXbY6qrOvK6162ZP2aDV2nfoY7fxMu74YZr0nG/ZzY9wmqV91KSc0L59X+UM/92N31Wc83OvAEpw58FpMln42XfW/e0ZJzjdn20un26TOBTCHCzPtp4oWCICKnZKwOO+HA6TmvKOoZ6Z+2dpTUvIDu5l8w1PsApZPGisHoYOXWT9K47x2k4hLl9a/AZCnA7dsEnF5nJnvtBVEkGurCbC1kzfbPYzC5sDjctB+/g+h4DG/hRazc9nrqNr6a8voyTu1t5NLn/QbJ4MVoMhOLRLMM0M5TP6F/IrWvv+MefCU3EAt303Lkq3pf+tr+OOOzipKF2nXvyXotlQjgLb4MX/EVjA48hizPz6BbDGYy0OaV1RJPsPuhUzxraxmBsRixUCRLnNhgMuD0unjkv+1ptktJYs9Tg9OyqKqKct4aGrA0DqZFGRu50GmdbVgcdka6T9PdZfNgp2s6UvF0UbuiKvoGLoiC/uPnoo76dMCyoXH2kJk6l/n/eLQfQZB48Xt2ExqLMNo3iJKS6W75DZ0n7uaiG/+GZLAx1PNf7K4GLLaSabURMiN6GuOVp2A7w30P0dnYqV+XV7SZS255GUceOYTdVcfai76cMwPQZDg9qxb0OQ2R8TZO7f80NmcdJdXPn/L+Ugh4aoecCzE9KxYK87efPHpW7zkbFamcTC6poQEQi6Rzxd2+TXiLdma9Z/O4MFnMlNeXcPSxw1gdldicVdM1k1Yl95/A4Vk1q3FesbqG0YHRnAy3mTzaY0O7ESXzrMaG0exh4+Xfx2ovn/M+k9F8+EtUrXyTbmyk2br+D2/RTho23T6jqN+FhsyxljnmcokkLCTakLmnaw4fTYgP0lFmp8ejp8hoa4dGQ61hqYSFQcuJ9+Ap2M5g1z0UV94yZX2XDFaqVryfY0+9n86TP6Z+wwemiKFO57VPkym4debAVDxB5coPIEkSqaSMKEnExgJEw+nnq1i5AVES6Wvry3q+RHyU3pbfUFT5HArLb8RsLUAQjRx78jYAAiMHZn1GQTCwZvvnsdiKs153eNbQ1/YH+tr+kP4uDGdX4HUpfsPA4Ag//UcpzfvSTGWZ4yQejtJzsl2vSQJQVHViXKXHVib724VM1Z4Lnna0AjMZCZM30Ewdhclel2eCoXEh4ukWiYlF+hjsvpf6TW/mRc8r4Ze/7NDHYmH5DdgcVUgGG9FwD82HvohkdLPpiu9jNubruc7aAjU5dTAW6ScUOMnKrR8m01mcjMZofCpd5Gc0ufEUbDs7DzsJZruVRNyN0ZRHZLyFJ/99E6JkwWT2Ur3mbXgLL0Ze4F5wIYr5nS+YbX4tJNqrpQdoegaTMdr/KKJkydLN0BDxB4kAobEAipKi6eDn8RRso6ji2VOujYa7OLzrray96MuzjumuxjYgzeIlCAI9J9unvc5d5MPldRGLxAmNBbMoqzdc+u05njoNzVio3tBA++GmnD4DcNENf9XrmkYHnqDp8BcpqrgpS2X66YCZxloiGie/ooTXvK6e737jwLRq4vM1NGa6vygZsbkc2Jx2kokkwRE/cDo7o7i2gv7WLlRFIb+ihOGuviV1XKTiCdxFPuo3/w/7/vNWGvfczqptn5mSzurMW83mK3/MvgdewdjQbvLLrpzT2estrmN0YFdWLYCcANFqxF3oITg0hpKS6Wpso3bTCirrfAz0jmOymLOM8XCwBUVJUFb3MmzOCgRRoPvUb4F0ZLJuw/vSwpeiCVEyISARDXcSCjRhthbiyd86LWOby7uO4d7/IkpWata8DfMM2jfx6BBDPfdhdVTh9m3EaHaftXPAXGcOVVFoOtSm/y2KUx0dWir91uu2sP+Bg3pa7uR0asg2ZJ9u2TXzXrlmq6JfxjLOJJ5Ohoaqqgx2/RtBkPAVP5c//nUAOSMUbjJ78RalC2Gt9jJq1r2LZHwIVQU5FddZoyYXdmoF58HRI/iH9hCLdKUPTgWnc9szD+JngshhNmjMHPFwFJPZy5arf8bai75Mw6aPULfhLchyhI4TP+CJfz+b/Q++mtZj38Y/vH/a9JqZsGxonBksZOPT0gOmm7upVITetj/hK74cg3Hm2odUPIEgSBhNHiRp+pois7WQDZfeiTNvzbTvT0YynsTqsMw4/gvKC/jw/1goqy2c9rALaY9vKhVJ9zE5TjjYCsD42HF2/eNqwsFWCmvK5mVoQFq4UGvn5L5P4i28hLr1tz2tDI3ZIEoSNpeNv/x9gFTydOHxYtiEpr2PIZ02bbZpqaHp7IbM9KH+1i6dKetMadj4SnxYrCu4+OYfEBw7xsn9n5q2WDowvB9VTZFXeHFOJA0CpaQSAfxDB7PmXzIaY6x3EDmZJK+0ELvXjc1hobNlBG++jUQsreButFrS95noi6po0XmV4b6HgHSal9u7EbOlkHCgif72v3HkiXfRuOd25GSI4qqbZ6SG9hZfBoAiRzFZfHpEUlVVRgeeoOPE3RzfczsHHn4tnSd/zIm9H+Wpe5/HgYffxOjAE+eEtWk6RPxB/btKROMzXrfvv/tRFYVoMMQr334lBqNRZxtUFQWz3Yqqnv6dnk6GBixAZ2O2EO7TzRJbxjLOFIb7Hubkvk9QWP4srn3lDxjuGZq9NkCOoyopDEY7jXs+Sjw2qIvoafzuJquZeCSq54Nm6l+U1FfS19w5pd3ZhHvOBQ4+8ibCwWYKK25CEETGBp8kERvGZMmnoOx6CstvxOasnrOdp1sU7HzAUq/v42PHOLzr7Tz79X/C5txIZDw8RQBWS5eZqUhfVWV6W/9Aae2Ls7RazhTajn+XoZ7/sHLTxzn61HtYueWT5JdexUDnv2g+/EV23nw/yUSQvrY/Ulr7EgTRmCX0l8u47O/8BwOd/0JORZAMVtZd8nWkCQPkmYDKtXVEQ1GCw2MkonFURUkzRdqshMbSHvelmNvuIl+6HimZQlXUrGwHDZm/l9luxWSxTHvdYqGN85G+Rzmx72Os2fFFXVtGQyjQxMl9nyAW6aW09v9Rs+ats7apqgqHHnsLgiBwzct+w2jvVBFFi8OOxWGjrC6d4iRKIk6nmYO7TmAwGmg/9meaDnwJyeBg+42/BMVIIj7E7ntfRHnDaxjs+heiaCaVDJJKpkVjVTVtIBZXPZe69e+dtY/9Hf+g5ciXs543ERthz3/TVM7OvHW487dQVvMSUslxAiMH6O/8B8n4KFuv+c286xkXglzT5oxWC6l4AsloyEmrTXPcT6fUfa6Ra1/mo7OxoDSqmTqybGgsYxm5QSu0Lm94FZ3HWrA47FmsKJlIxEdR5DiWiTBz7bp3E4/2nfYEKQqyohDVF8SJXOPEGEaTG0GQ6G/tzgrbZh4cz8QCt9CDaWHFTUhGM0XlNwNaLn4jg933MdD5T3pafk1p7UupWfO2WdtZqmc6F+Kk5wsm/4YLKeSd7Xqbqw6TpYB9//0WDRs/kUXpC+nDoNlmYbCtB1+Jjy2XFlDvOsSPfmnRtWJC/hN0nLwbd/4WHO6GBTxl7kilIgx2/xtZjtPb9jsQJCzW9CEtr+gSNlz6XUDAZM6jYsXrADj4yBsoKLuBioY0pXQu353VXgGqQjTUzrqLv3ZeGBoaffvZqH3qa+1BFIWsVKlkNLak89BgNuHwOOk52T6jkrqSOi3OJxok4uGo3qdc50HOh7YJAWJv8WW4vOvpOPF9PAXbsqJZDncDm678MU0Hv0Bv628prX0JZkv+zPcWRLZe9xke//vruefH17Llyp9iMDmzromFwgiigMEg0nq0E1mWdaNeMAzTuPsTlNXfTO3620A1IRolxjr2AFBW+xIKy2/g2JPvw2Ivx+lZw3DfA4iimbr1t+HMWz3n85fUPJfiqluyXjNZfFSt+h86TvyA8bFjCIJIWd3LsNhLsdhLMZhcnNj7MQQpgii6dGeZqqqMDT7BUM9/JxxzTgrKb8TlXb8oo2QmytzJRoicTGYYrwqe4gL8/TOzLE7OMFBSMlaXY0Yl+EzMJEa5VPXGZ+RMsOQtZjZ+llM0lrGMCwXCxGEpOHKIwe57QEiTFEwnbtV86Es0HbxDD61bncW4vBuQUxEGOv+JMhHeHul/TNe9ADj6xHtpO3YnoGm6nE5J0DbXNOvR0hecztfQ0NaK0poXUlR+s15UZ7SYceatoW79e9hxw5+oWvVmelt/x3DvQyRiI8Rjw0ve90ws1QHnfAn5Z2K6PmW+Nt1vON9NaLbrJclC9Zq3Mtj1IKMDjxMLhXEX+XAX+QDw9w8z0NrJQOc/8fhs9DTdz62vel5WSp3Lt56t1/z6jBsaAKgq9Rvfzaotn6Ks/hVsuernOPLSJAkmc176cDVxOBRFA4IgUl7/KrxFaRGvWLiXVHJ81lvEIn2c3P9pIuOt1Kx5O+78zWf8sTKhidRORjIam9PQWIp1xGA2pdktl6AmYyYIoojBaMRgNGD3uqekp2VqdmjfhWZoT75uLuQ6X7TvVhAEqla/hXCwhcGuf0+5TpLM1K17N6JkofPkj4iGO7NSbzQYzCYsDjve4s184s6HSMZHCY+3TbkOIBaKcPTx44TGAnpKGUBoLC1G2bD5NipWrsKV70UQRUKBU1jsZRiMTqz2crZc/UvyCnbQ1/5H3L4trL/0m+QVXoTR7Jnz+Wd6v2LFq9lyzc+o3/gBwsEmGvfcTsuRr9N8+MuMDe4GIDB8AsloRFUUxseOc+Txd9C453ai4W5kOUpg5ABHn3gXBx95E0M990/Rl8p1TZ6pj5Png5KSMZpNaNpusxkak6GNt8mGRjrVb2o/0zS06cLyTJzP9cYLimxMLk6dCcuRjmUsY3rIyXSud/PhLwFQsWoLBuNGBFFEMhoI+3tIJYPYXXWs2PoBVCWle2e0jW+4/z+0HP02pQ3PIxWP0nzo/yirexnl9a9EFUeo3/hWJCnt+ZqNveV8WKCmP9iq2FwOYqKI1WEjODRKSfXz6TjxfU7u/6R+ndVRRV7hdty+bTg8K1AVGVVJIohGnYllIZgpOrOQcLcjL61yPZlS8lxC2xQznzGX55otapULf31aOVpg7cWrObLLwFD3fTQd/DwbL/s+DKSjWY17P4LFWoy3+HKaD3+ZdZe/nCtveDWHd8d0T38ocAqbs3ZW726usDjsaQXglIzZbp02ZctgtOPJ38lI3yOc3P9JyhteRUX9K2dsUxBECstvIK+0EEWWOfTI11CVFOsu+dq0148OPE7z4S8hCBJbrv45ZmvRvJ9jsakYM60RM/3mWuqIKEkkYjE2Xb0Jr8/Kw3/dqx/GcklDEUQRs82K2W7BaDLprHxnAqqiIMsygeEA8XAUOZmckRlr8udm+3up4MpbS0HZDbQdvxNPwfYpa5jR7KFq5ZtoO/5tBrv+ha/4ClZu/VSW9z7NupkgFgpzT0f6nJaITU+tqkXGAcYnCuQBouPpdLFoIErH0WbMdithfycDXf+iatVLgTQRycjAvWnjw+RGToYoqFxJcHAsp+9HVWVCgSbkVARFTmCxl6QZ3BSw2ipx5tWTiHfTeeJXBEcOZn22pCpB+coaDj70b44++V6s9grWXPQlPPnbEAQBVVUIDO+np/W3nDrwGUDAbCsjr2AbheU34PCszvrOMg/18/ltR/of4sTeT1Kx4nWsv/xdJOPGBQsITmYVm20OaOyqFwqWtGZjGctYRu4YG3yK47v/F4BtN9zF+p3PY6BrkEgwzKGH3wOkWH/pN1BVhbKGSp1JR+PpBpCVMBUrVhIYDqAocQRRoufUIzTu+ShrLr6DosrLiPiDZy0fVHNCLEV+v8FsYtX2VaiqyrFdR4B07crxpz6I0eTGV3IlgiDiH9qLf3gv8ejAlDZ8JVdTvfpWPQXtbMPudacFoCYO2NOlyT1dkIsDaroNPZUY59Bjb0YQTay75GuYzHkMdt+HwejAW7STcLAFm6OKkvoa+lu79M8fevTNODyrqFt/GwazCbvHicvr0ufJfPpdWl/Bs28qZ/f+IIVFNu791a4p1/lHDtLX+gdWbv0knSd/xNjgU2y64q4ptSIzHa4TsRGSCT92Vx2xSB+CIGUVz57c/ylGB55kw6V3LpiOer7INR99NiNSEAUsDjvxcBRFlhFEYd5z3+pypGvOwjHsHieBodEzfpCye90YTSYSsTjJeGLGNDGnL49wIHjWnKeS0UgsPMKBh1+P2ZLP2ou/Ou25Kx4dxD+0h+bDX6Ju/fsornrOjG0+de9zUZGx2EpR5BjeossoqX4BgZHdREP9lNa+GKPJk/WZtuPfYbj3IbZd+1u9NrC39U+0Hv062679PaqaYv+Dr0ZVUxRXPQ9v0U6O7/5fqte8jbLatDGSOW4EUWSo537Gx06gyHHyS68hMt5K69GvZ93XYHThLb5sghTBwFP33YKcDOMp2E5B2fWIkpmBzn8SGN5HSc2LGB14AlE0sOHS78woShsZb2N8rJGu5p+TiI2gKglszlqKK28hv/QajGbPtJ/LBSf3f4rh3gf1v1dvv2MKjfd8MXm+zbWfnisGxvnUbJwzY2MpuaqXsYwLESN9j3Lq4OfIL72ajVd+jpKaEsqrPex5sJGxgVPkFVWQiAoYzSYUee7UAu1wLssp/vOLjyOKZkqqn6sfhs6E2vVscBV4iYYii/LkO3152N0OBtp7ZvWYq6pKPNZLONCGKBoRRAOxcB9dp35CMhmgtPpFVKx4bdZmJBmNGM2mMxrZ0Q4qdrfrjBSWngucCSKQSKiTo0+8B4PRxYpNt6MocVze9bN+JuQ/iWS0Z2lZbLthK3vv2zfv+xvMJsoaKult6cZT6J1CJQ3gH9pPd8uvqN/wPsyWAmQ5NkXvYKYaH195MWH/OLFQGFVVObLr7RRV3kJR5U0AREPdHHrsVoqrnkf16jfPu/8LRS6/pd3rJjYeQVWVKdcKoogjz40jz8lwT5p1zJHnJjoe0ou7c8EL33QFf/nJriUjq8h1TdOKvtfsqOOpe/bOeJ1kPO2tnjU1cAnPNaFAE0efeA92dwNrL/rSjGrxu//zQooqb6Jq5ZtwFXgZH/FPiVqOjx0jMHoIyRgmEQ3R3fRXIJ3uJxktyKkkJksBpTUvobjquYyPHeHI4++ioOwGVm79aIYu1BD7HngZZmsxZXUvo+XIVwAoq30Z1Wvewr4HX4XVXs6aHV/Q+6f9FoIosvu+F5KYSH2VDHZszhrGx45O+1y1626jpPp5RCPtnNz7WeLRQVZvv4PB7nspq30pw30P0d38SwRBYuNl38fqmFvTJjh6FEWOoaoy/Z3/YHRgF6hpGl5v0aX4Si7H7q6a12+oqgr+4X2c2PsxlIlUrbr176e46hZcBV7MNsu064mGTOFZRZZ1wUFBFHI2IM5VcfkFYWwsYxnPZPS0/Ib2xu8hiCaqVr+CFVvfTTwyxoEH38Kmq76Ew1OLIIhIBgmn10lPU9eUsKlkNGZtKLr4mhLmyGPvIR4b5qIb/jzt/UWDhMliOV0IqSqkEikUOS32NJ+FLhP1W1cRGgsz0N5DaUMl9WuKefjPT854/XSHHS2VzGg2EY9EMVksWQbBXIV3mZBTUXpaf0tP86+xOWtYveMOTGbv3B9cQjzdWPrO1PNEQp0ce+K9yHIEs7WYTVf8cNrCTlVVCQebl7xOI1cygLQ+zn1U1L9Sr72C017+XL6bjhN3U7HidXqhe9OhL+If2svmK3983u2xWv3UTN+N0Wohr9jHzqtqOXp4iJ6mblRFnZcRv3LHGjpPdM5IM3wmYLZbsThsBAZGpvx2ZrsVUZJw5+cRDUd0MUutpu5spUIGRg5z7MnbKK39f1SvvnXK+xpz0+arv0J+2dVceuM6ju7rpr+1G7PNSiIWQ0nJU1gHh/vvxWL3ULfh2fS3dxENP0ln40OM9j+OxV5ONNQBQM3ad+mq5lpUcqDz3zQdvIOCshsY6rlv4j0j9Rvez3Dvg4z7G9l85d2YzFNTWId6H6D1yNdIJcfxlVxFef2rCAVOoCoyRrOHVHKc4Mhhhnruw2QpZPt1v5vo74Oc3PspRNGEoiQQJQuVK15Hfuk1KEoSq71sQd9vIj7G2MDjjPQ/RmB4H4qSoKDsOmrXvzeLRS4X+If20dX0M4KjhwCo3/BBSmqfg2Q0zjletDk2Obp2PjFUTYf5GBvnX9XiMpZxgWMuYoREfIyOkz9k1Y5Xs/7Sr+IrupETT32dWGgMm6MWqyOPdTvqsLlsKIpCXkE6xcCR5+YdH75CX/QFUcDl86DIMuP+owz1PkBBVSnBkROEg02s2vqJGfugKiqpZBKrw4arwENhZTE2lyNdj2UyYJ0o9pxvYXPzvhO6CFbPyXZKS2Zn0pmpCNlst7JqewPbr99MPJId0ZlP4Z1ksFK54nWsv/RbxGODHN71diKhqRTACyn+zBVPJ0MDTj+PaJCWlFzA5qhk3SVfBwSMFi/RcFfW+x0TqUsDnf/k8K63EY+ezkE3Wi2svmTdou6fywFSURQCwwcZ6r4POZU9LlUl2/M/2zpQtepNiKKBcLCZo0+8l5G+R8gvvWpRhsZS61Bo0ETJNEx+LkmSqFpRzJpqmZVr8lFkeYqhMdt8Eg0SH3xFbMo8P9OQjEbdiLC6HDpZhs3jwuZ2Eg2GMFlNxEIRrK50BGuhufgLhdu3gcqVb6Cn5Vec3P9ZEvExjFaL/ltHwumUQauzDrPNgqJAX3MnqqIQC4UzGAdVBFFAMhqRjEZKap6Hw3kRA22jCKodm+1aVmz6GJ6Crdictaza9llK615EQdl1QPaht7D8BvKKdpKIp7+7uvXvxe3bRPOhL5JXdAmpRID9D70ehKnfVUHpNey44S9cdMPfWbnlEzjc9RRX3kJJ9fPIL7mS4spbWLH5drZe8+us6Ii38LI045xnNdtv+BlFlTfT3ngXx558H12nfkpX0y9IxEbm/D6Do0dIJE/of5vMeRRV3syaHZ9nxw1/pX7DBxjp38XhR99MLDI/XZVTBz87YWikx/pg9z0oKTmndUVzJGYaGhaHXY9QPR1wVoyN85GJZRnLOFOY63DpH3wKVUlid9yE072OVDJEd/NvScYi1K3/EKrq5OTBLtZuLqOyoYS1q9MeA3//EN/+/COnc93jCZxeJ97SQvpa/8Fg178Z6ujFlbeadTu/THHt5TP2QVvcNN56UZIoayjFVeBFTsmMj4zh9OUhSumFLr/idM3DfBa/X3/n4Zyv1WC2WwmPBjhw/wH2PXBYL65eDBzuFWy49E5E0cThx95Cy5GvMdz3MP6hvSAmESYpv57P3qRzhXRoP5utKk2dKS6Z2KvVUc7KLR8nMLSXAw+/gca9H2Og6x4ABrvuQRANFFU8i7U7vphV7+Ap9LJps29J+jATFEVh34MvI5kYY9OVP5pCI5oJs92qEzlkMspM3gsTcT/BsaOYbem0lMVAZzQ6Q/ut1eWgekPDlPUtEYsxOhii1OknFEphdTqmfHbyfJo8jt74ntZ0bdNZFA2O+INIRiNmu1VnYYqFwphtFqLBMEarBf/gGMl4gmgwlMVcNRNr12SkIya5/x7TXVu97g00bPow/qHdHHjotfS2/Ot0FDuZNurMNi+SJLHv0SZEgzRlropSOhqpyDJ2j3PaA7AomViz44us2voJfMWXUbP6nRhN6b1H0zqxuhys2LaaRHQAq6MQBBGjxYTLuxFVlWk98rWJfoUY6Z1a9wQgCBIGkxPJaJjxu7HYSrLqliSDmXUXf5X1O7+ByVRJ7dp3svHy72F3ryQW6aW7+Rfsvf//cerAHYT8J2f8fvs7/k7T/u9P+55ksFJUeTObLr8LVZU5vOsds7LHyXKMrqafEY8OMDb4FIocx2B0AemxbrFXAJBMBBjsvm9a1rBMTJ4jmsH+dHFWLadRLWMZZxmJ2Aj7Hng5ZfWvoHKCj19WgkhidhhSEEU2Xb2Rgw8empKDKxmNJKJBYtFerPZKVFXGU1RMJBBO833PQ6xPEEXyK4rJK3BTXu3JYpLRoPHsK7LMqovW0LT/1KIK0haS2zzfPNbpkEqM093ya4a67yMRT+cOW+zlbLvuB6jy9MWFyzj7aD32Hfra/khR5U3YXfWUVD+PVHIcg3HmA/7ZwEDnv7C763G4V8z7s9Nx4PuHD3DsydtYv/Nbc9aonK8orq1gbGAYd6GXNVsq+WjpL3nR77brUQOYvuDVXegjMDhyzkRFM3PlL7tlK3sfbgTSh7tUMoUkSaSSSX29KagqRVVUQmPBrN/R4rCTjCdQ1TQdKZw+OIoGCbPNmn5fUVFVBUEQMdvTa810bFiZ/VMVlco1tXQebyURHaX12DcY7n2Qlds+RH7xsxjsvo+mg3ew8zn/RZLS0e+GjdXcfJWZz3z8KV3sNZVM6et3QVUJsVB0wWQVycQwu+97MXUb/4e2oz/lre/7HP3x53Ho4e/TfPArmK1FxKMDrNzyCfJLr562DZvHhZxMoiiqnjo0V7oenB5H/uF9pBJBvf1UcpyBrnvoa/sj8egAbt9mVm377JTzqqKk6d9FcXYi1mi4h/0PvpLKFW+gtO7/6Qx4w30PMz56FKujipC/kYGuf+L0rGHcfwJQMJo8GM151G/8EA53A4Ig0nbsTnrbfk95/auoWvWmXL/macfEdPvmuUzTPeOifkuBXMVLlrGMpxtMFh+ewosY6r5PNzYk0ZW1aGgLzYH7D+if0zZGOZlETiYJh5o48ti72HzVT7E5qhgf9gPzVwVXFYXIeJiRngHC4xXTemC0DUA0SAx1jyAnUzoDhmQ04i0tmLUIbjIsThvh0UDO1wuiSEFFMalkimQikXWQmQ5OX960BdkGk5Pq1bdStepNpJLjxKODHHn8nXSd/DPl9a/IuT/LOLMorX4+fW2/Q1VlHJ6VQJrqtrf196za9llE0UB38y8JBZqoXftOqtZtnlCdTh+gBEE8IwQkWkH3fKCJdboKPHgKvVmMWkPd/8ZiK8OZt7gUsNlg97qz5tpSC1X2t3YhGiQCg6P0dbk59tO7SVVuRhDFiX0+rB/CNZhtVt765nr+77NjqMjnhDBGMhr1eoZH/74HQUhHoVw+D6lkktLaEpoPNuvf13BX/xT6ZpPVgq/Eh6KoRMYjONx2+lp7SMUTWBx2zHYLZpsFURCRZZlwIEQynsDqsLHz2gZ6e8IceOjQtIdF7bWOo81AmvJ2xeaPYzTlcXLvFxjI/6+eytR04CsYTXZMVh82561844gJQRSQk8kMsdc0Btt6WAwEwYrDs5qWQz9AECTufyBO+YogReXPIRYaoLv5F7jzt+Ip2DFjG9NRSzvy3Dh9LnpPdeivFdaUZfU3TVs8zrEn3weA3d2A1V6OweikrPallFa/kJGBXTQduIPu5l9MIVsQRQNWl4N4JDrrAd1qLyO/9Bo6T/2Intbfkl9yFUVVz0lrm4S0/qWjMpqhAenoUO2623BOrFkA7vyt9Lb9nu7mX+Bwr8RXMnPGQSa0ovrMfXy6OTJfQ+Nc1YGcM2MjGgwtp1ct4xkJRU4wNvA4ZmsRkVAHNkcVkPaQaYvwbEJC2rxxutezZscXceWvQEmlsoT65ovwaABBFOk52a6/lsmOofc9JTPc1YdokEjFE2kucFlmfCSgM7vkwroU8c8ubjYZJquZaDhCcVURJ3cfB2bXDpmrD4IgYjS5MZrcuH2b8A/vWzY2ziNY7KWYLIUMdd+LJ38rTs8qQEQQDGgJb6qqUFR5MyaLj8h4mMqV5RjWlmMySfR3+fVD2lIiMt7BuP84RRXPzul6yWhElmXKVlYTC8cYG8k2kmORfuzuhkUpHM+FTEMjl2LVhUBJycRTUU7uPs67HXfAaACbx6WvZ4YJRj3NCRKPRPnJL3t0Eoj5GhpLYTAlozHdk66RbaiKQmgsQFlDBWMDAURRQBBElIkaCXkiwqyqCihpg9bhsWMwStidVsaGAlgddhS7lZKaEipr8hgZitB6tJNIMKSvpwXlPh759/EsXYtcIAgCNWvficniY3ysEUFMp51Fx1sJKwnikX46Gn9EYcU1VK18G0bT6RTUkP8kifgILu/GRWWoGIx2Nuz8FuFgC1ZHBUaLUy/sr1r1Joqrn78g7ZvxkTHGR8ayDM/pDKPBrv/q/04lgpDxKIJoIL/kSiLBVrpbfkVpzYsxWU6nVw50/Y14dJDa9W+bc59cueXjVK58A4Pd9zHUfS8D3fdQu/bd9LX/kWioE6M5D6u9nHH/cQTBTN3691JYfv2Udtz5mzFZCkjEhjh18HM0qB8ir+gSPVoyG86EUXCuHPznzNgAsrwEyzS4y3imQJRMrNz6adqP38mhR9/Mik0fwVdy+bTensnQvIWdx/+G0ZJH1dpnAei1F/PBZA/HdIvQTAvT6cJDBZvHRTKeoHJVFS9+Xj7f/uZRJEkiODRK2crqLANmrnZnQjwcJR6OTolo5JUWMtY7OMV7Ox+487fSceIuZDme0wYwG0SDhChJF5TY0vkKX/Gl9LX/BcsE04wnfzOeDEXtioZXA2l2qsDgMO0pBbPNgsvnJDB8eixEQ11IBlvWoSMTWg1SLkZ6YOQAPa2/paD0GsQcxoqcTBIeDWSNzap19fQ0daZrrjyr6Wn9DacO3EHDpg9NUbNeCmTO87O5z2rrmcVhx1dWwEB7L6qgYp6Idgx1DSyY2nOxhkamo0Irtq5cVcVI3yjxSJShriFCY4Ep6VAJwO5xIssyRpOJZCJByB8mlZSpWlFEzQovh3d3ceX11TQeD+gpqQaziaKaUvqauxBEkRNPHltw3wVBoLz+lcSjg+x/6LWYLPlUrnwDeYUXkUqGGOj6G+3H72Kg4168RZciGaxIBjvDvQ+SSgZBEHG6V+HO30JR5c0L0iASRIMecZw8bxZiaGiRIskgzUnxLk4YWFZHFfYZGOmKq59PV9NPCYwcpKDsWv31FRvLOb53mLzifARRYMX6cvY9dGxGFjSrvRxVTpBMBEFVUJQIm6/8CeNjRxnufYhkwk/lyjdSXHnzjCmekmSmYdOHOPbk+1DkGKcOfBZVTZFXcBGrtn06p3Xk6YDzIrQwV+HM2cZCIy5PF9aAZZx5+IovZdOVPyKv8GJO7PtYlijQbFAVhYg/SG/b7xns/BfBoVGCQ6PY3S4sDvuMBZYGs2nK+MwUW5oOmXm0M0EQ0949m8tOb0sPj+1LcuVN65HldHrCdIbGUkFRVKwOK5LRyPar1yy4HU/+VlQlSXD0cE7XT/6+MlmAlJS8bGgsEapXvxWbs5auUz/Net1st6bpVksLkeUYhx69lf72fzA+MsZwVx+tB0/RfuQe2hvv0tXIB7vvnfE+SkpGENLjPPO31PLqM1Fc9dw00cA8DwiZ7Y72jehjpGr1rRRXPZ+hnvumFaVcCizGkymIIq4C74KZrkSDhN3jJOQfn4iECnr9Qrp9ITel6SX2xsbDUYxWC2svXo2cTOIqyKO3pYfoeAiLw4ZoSNNvQ3ocpGvk4hhMBpxeFxUryrE6rDg9LhrWFnPR5VWYzRJmk0g4EOLkqXHajnfp34GcTNHf2p2uvZOW5pygyAmsjgpUReb47v9lsOvfyKkIZbWvYOs1v6ag7HpUVSYeHWJ87DhmWzHrd36LunW3YbYV0d/xVxr33I6qpM55lok8URszl6EB4C2+lKpVb2b1ts/OqD0iSRaMZq9OQ6vB5LyFq1/6JcZHAkiSRMvxPgoqimZl1Usmg4DKyq0fp6jyeQiCiMu7gRVb38/KLR+nvO5lc9aSefK3snLLJ7E6KiirfyUAY0NP8cQ9NxIeb6Pr1M/mzX41E871bzkTzmlkQ8NSFrdoee82j4vSulKGe0aIhSLEQuGcc9kFUcBsO13Ml6s641LmzmnRnpkKx54uDAXPZEiShZVbPk7j7ihdTT/FV3JVzukUW675ASarBVVRSETjetqQ2W5FVbIjhWmDIDWxyZ0eN5LRiMlqJhaKzHifydoemeNRMhoxmAzEw2ktDIvDxuP/3Ku/X1xbQTgQYnxkbNoxW7aymt6mTkRJQk4mpy2gnQ1yMslAWy+ugjwe/VtakMtotWB12OZV/Gh1FAOQjPvnvHa6uprlqOyZgSiZKCy/gc6TP0RORdMeWqOReDiKIIoYzUaKa2vpad6Jw7MKRUkRC3dhc9YQDrYQDXchCAIO9ypKqp/PYPe9tDd+jx3XT9WeEUQBq8OO3e0gFokhiAKJWHzK4UcQRExmL9FQF8HRIxRV3pTTuM0cI3IGfaogiCQTfqyOSszWokV+Y4uD5l2Wkykko4H8siL6W7sWXEgsiCKiJBEaC5CcqO0CcPk8jPUPpSmubdY58+ena3cpjA8lJTM6GMRotTA+4kdOptI0vxP1Fuk6tL60o0YQScYTpJJJBtp76W1KYXU5KCgvpKczwJpr87nnd4cQBJG8Yh8n97Xoxd9aepbmU52PjsJsRdNWRzmbLr8LRY5z9InbaDqUpoo1WQqwu+qIhnswmfOwuxrwlVyJy7sWQZBweddTXPUcxv0nOPzYW9jz35dgthVjsRXj9m2msPzG89rbbjR5KK9/+YzvJxNBDj78BpJxP2ZriZ7Cp6RkBtt7iEejOH1uQmPjhAPB9BiMBelr/zvDvQ8iy1F8xZeTX3IVVkcFRRXPYrDr3/S1/QWnZx1GU5ptbb5OpfzSq8gvvQqAoopnceTxd5KIDTPYdQ+9rb+j89SPKK15CRUNr5mW6S7XcX++1kEvio3qfBcc0aAJmDnyXIz1DyMnk1MKjyAd7l178Ur2P3Aw67nO9nNqluls9zxX8vTLWHoEhg9w9MnbqFr1P5RPeD1mgyCKJBJ9mG0JjMYVGMwm5ERKP/DMZqhCRkpAND6tKnCu0MapZixIRiOl9eV0n+zAbLPqxbB1m1fS09StC0xlwmhNz8uCUh9tx9rwlRQw3JN7ekVmO+t2rubA/QewuhzzEgcb6d/Fib0fYes1v553SsFCDP8LZd08HxANdbP/oVexautn8JVcrqe/TP4OXQVeAsMHePzvr2XTFXdjd9WjqmqW8e4f2kss0kdR5S1ZrxvMJoxmEwajkbxiL0ZT2gfXeaIj65AXjw7qdLuNez+Of2gfm6/6MZaJ12YbC5pBYve6iYejOPLcul7MkcffjdHsYdXWT83ru8n8Dmb693xhdTmwu51YHRZcXgfHnzi24L0wM5KqfS+uAi/RUGSCFljQ6zjg3B6SMn87LRVSMz601zRM1lKZzoEpGiTsbldWKtZ0MNutuPLzJhiuInpRsEbF7fR5ADCaTIQD4/q6NnmsGcwmDOY4IX8jPc27CPlPYbVXkEoGCQwfIhEbwmjOw+lZg91Vj8niw2B04R/eR2DkACZzHiASHD2MyeyjrO5llNS8UDeGxwaepLf9T7jy1mGxlVJS8wISsWHGBp8iFumnsOJZmMw+/MN76Tz5Y3wll1O18o1Zz6qqKvFoP4nYMOFAEwaTm/zSa5a8Xqm98S56Wn5F7bp3Ew62Mj52DLu7AV/JTvyD+wgFTnLFi/5A2D+OZJAY6nmQxt2fR06GcOdvxWB0MDrwOIoc05XRg6OHObn/M6hqis1X/hijyZPTOS0XKEqK5kNf1AUSEUQ2X/kTAsP7cOdvxeao1K+dfO7LjGKc7wrii4psnI8bpnbQchV4CY0F0nRvKTnNBd6X3jjMdiujvUP6hHX68ogEQ7zubVu566u7JkK7p9vM9TmXYsGfXL+itTO5vVwOY8uHmgsD7vzNlNe/io4TP8BbtBObs2bW61VFoe3I3SRiw2y74S7gtLc0czGaziOmeRsT0fhEW3P6Gmbthx4dkdP0hd0nOxBEgXgkqrPutBw4qd97MlLxBPFIjJZDzSiynMXUkys0Rd/2xrTzYL4qxMHRw5gshZitxfO+92R181ywPCdzh8VehsmSj394D76Sy/VIg6ooaSN7wgu/ZnsdzUdU1l3ydWyOaoAphxhPwbZp75EW00ofLK0uG4Mdfl0/RIN/aC/Hdn+Qi274OwajHYu1CLuzmpbDX2LtRV9CVVVEgzjl4CmIIjaPE6PJRF6xT5+niVhcv0aRT/97Psjcp+aqvZoNmcXWiWicZDxBYFikr3Ui5WfCmQBpx4I4Bz0pTI0AQnrfTU4Il0lGI1aHjbB/HEU5t5FBzfOtQTszZGImI3K21yeTVEy3H8fDUXzra5EmUqsMRiMGs5FIYFyvUTPbrYQS2fV8qqJy5Qsu5tG/78HisGOymCmuLqSvLZ/iqnSNgmgQ8fhctB9vZWzwMENdDxMKnKS/828k4wE0BiWAWLgbp2cNDvdKQoETtB2/E3f+FmQ5ytEn3oM68RuFA6fSbUsmWo58Vf98T8uvsvoXCZ5W9FZVlfbG7zLU/R+SiezvxOasydLTWAqMDT4JQOvRbyAIEr6Sq4mMtzHUfS8FZddTXvcqXTUeoL/9PiSDjU2X343ZWpDOBJDjdDf9nK5TvyC/7Fpc3g1svOx77H/4tbQ33kXDxg9ispr1fXQxEEUDKzbfTkHZdRzf/UFQFbqbfsZQz3+xOqrYfOVP9LVs8rnvQtpLFq2zkcuBdqkswMlWXSa9pdOXRywSJRVP6Idzq8uhC/do/NYaF7YoSWy/fhMNdTZicZWUDMePDNPfMYDD41xQrrnRaklzR0/Q6Z3rVKdlY+PCgaIk2ffAK3D7NrNi8+1zXp9MBAABo8k1hTVqofPNbJ+IdswQDZlrXJvtVkRJ0hlmJrdlcdgprS9jqGsoayMWRJHShkoSscS86HMlo5HylVWU13h58t8HZk1n0taAKYcIOc6BR96Ew72SlVs+Ou1nM4vPZ2PAygXLEcn5YaTvUU7s+xirtn0GX/HMlJEz/S4aeYEjz8VobweDnQ/gLb4si6UnFyQTfoZ7HqCo6jl6nngiPkY8OoDTs4pQoImmg5+jYeOHsdjLECUzBpMFu9uF0+eiuqGIG3aKfPIj6YNQ9YYGQmMhRvsG6Tr1a9obv8fmK3+S5cU8U5iOyUkQ0zUKmd58DQazCU+hj+Gu7JzykvpK+po7p7QznZe/qLqM0Ng4kWDotOEyy1qS6d0/kzocWn8zU23OFGbaj7XvfiHrQmabhononCAKeAq9JONJRIPIUEef/j6ki+tVVUFOaU4SAf/QHga77yWZCOArvgxfyZVY7eUcefzdU+oeQKB+4wdpb/weqcRUUg53/haqVt2K3VVPf8df6Wv/K7Fw9jgRJSs1a942Jcq4FEglx0kmAoiiEclg0+spelp/R/vx7+DyrsdkKcBocmNz1tHb9nsUOca2a3+bLTappDjw0BsAWHfJVzGZvfR1/JXWI1/D4VnB9S/7CEO9NUs6NpMJP12nfoYzbx2nDnwagLUXfXlGR8m5xnwiG0tibEy3SGkHIEEUsibwfMOwqqIiGQ2oipqVGiIapDSPtc2S5ZVIJVPEw2mjI6+0kJe+cjWDoyqH9w/Q29KDyZrORaxZU4HbY2FlnZnf/PQIYf84d36xlnfe3oHFZs06DM12CJsJ880/P5NYZvu6MNDb9kfajt/J1qt/mVM6TzLuZ//Dr2XVtk9SWn8V9eurObLrKK58L4HBNGvTTJE2RY6TSoayGHqmSx+YjMntTDefzXYrNrcTq8NKX3MXJqtZPwhaXQ5WbW9ASSkceji9iRmtFmrX12K1mzj44MEZn1fbLDM3ZZvHRSwUnvaQYHU5SETjyMkkeaWF+PuHsz3Aqkrzof9juPcB1l96J45JzCaZh7Kl1CY4HxwRFwqGeu7n1IHPsOWqX2B1lM/rs4IoUlRdRlGFF/9ImNbDT7Dnvtey8bK79LaWyhEWDffQduzb+If3k19yFaHASbZe90M8hSVYHVZcXofOQLRi22pCwQhGkxGrw0xFpY3Pv7mKvMJLqd/4vnNHTTmNIZw5vyenJ+Y6JzRaWUB3xuUC0TDhuFiEcZ8r3EU+whN03EvtDMgcY/PVQJovZtvrtai22W4lGgylVcUnUZtPxujAk4yPHcFo9uFw12N1VNN08PMERg6gyDHsrgbK61+FweTEai/HZCnQjYe2Y3fS2/5H7BM1VCDgyd9KUeUteIsvm1NY70xguPdBBnv+gyLHiEcGiEV6cHrWULnqdaza8SI+/U4Ld93jord9mGQ8Sefxpzjy+HuQDFbWbP88Fnspnad+SnfTzzAYHRRV3ELlqjdNeZaFOqV6W/9A2/Fvp9uwFhKPDgKw8+b7EYTzj4DojKVRaQVemQd+JSXrkQI5I79REAXUZLooKnPBms8k0zypm69az/E9zRiMBkKjQZAkxAmKtILyQqwOM4lYkt7mHsx2C6LDTkwUcbjtRGJw4vgoiVgCu9tJODCOaJAoLLLzyD8O0nqikFQyhZxM8osHPSipVqKTjAQtR3g+0ArSl/pQMVNa1WxYNjQuDBRV3kxX08/oafktdevfA8zl/ZMorXkxFnspiizzjx++kpLqN/LkP/+XwornUFB2hT4nJ4+VpkNfIhEbZP3Ob+qvTZc+kH2/0/NeEER9o5p8YNNoauMeF+5CHy6fi85jLUA6xWlsKITJdHrpUVIykfEoLYfSugiTN0zRIJFXXIDRZMRoNtDV2Ka/NxtdsDs/T0/LGusdzHpPVRVaj36Twe5/07Dp9imGBmTTay6lNsGyoZE7vMWXYTC66Ov4C7Vr3zGvz4qSRH5pHv6RMP6hMSSpgA2XfjfLaMl1DR3ouodkfGxGLRarvYzV2z5DX/ufsbsbkNsiJGKDRIMuxnoH8Xtc1G1eSfepTvo7BrA57TgLbbjzLERjApfd/FYe+ftXqVn/GszWsjOihTEX5GRqymuZ34+mjaW9lmsqlZxMZq0VRqsFSZKIR6Kzfv+adseZhsY05Sn0ERoLLnmEY3LEOfOstNSYba9XFQVZUYj409fk0gdv0cV4iy4+3YYqYzA6UeT0bx8ONnHqwKfZccPfshzR4WArvW2/x+XdSCI2hNVRxbqLvzoj/fTZQn7p1Vmq5qnEuF6M3d/axa23pQ1PjWLdaq9g/c5v0rjnwxza9VbK616Ow72SiobX0tX0U3paf4OiJimve0XWsy3UQLZmRDbj0UGcnrWEAidz+uzZcGJNPnfOxlQ55bPziWxc/dJHsNg9BIdGde/lZG8hpD0ek1lsZupsLrB5XOn2JjyuWruCKGK2WUklk6iKiiLLSEaDztVscdhJxGK6UqiqpnPM88sKufTqavY80TuRXx7HV+xhsGeERDShF+49nTEfbvllnD10Nf2crqafsfXqX2G2FuT8OUVJcvyp/6Ww/Ab8I/soLLsxK/SqyHHajn8XX/FleAq2EQo0IacijI8dJ7/0Kj2SYnHY5zwETIY2DydH8rRUCKPZhGHCQ5lZT6L92+nLY8POBsxmSeel9xQX4O8f0tMhK1aU62J+ucBXXsxId/+076mqQsuRrzHQ+Q/qNryP4spbcm73bHpbl5FGe+Nd9LX/mU1X/ACrff7RjcnRrFzSNjKdOqIk0d/1G+LhAcrr3jZrKpzWvpa2m+n9z0zZURUVi9OGO99DQYmHg48+zFP/ehmqKrD9+j9iMNjm9ZxLCS0qP53Rr6RyU/ueLrVT+/dCMgXOBpZaWX0mLCZtKlec6YNnKHCKjhN34x/ajSia2X7dH7IYlEYHHqdxTzod2OqoYs2OLyxIz+NMIpWKEB1vw5m3dsp7227YSsvRLsZH/KTiCVLJEM2Hv8zY4JO6oZUJl28T6y/5+pL0Kx4dIhxsQRQNHN/zUVQlRn7pNVStfBMWe+mS3GO+KKmvJDDsz3LuWV0OxkcGznwa1WwTZvJ7k73x2kSYK39ZEEUsDhuKLJOIxhElCZvLoac4SUYjvvJC4pEYqqLqapzTLWJlK6tJJpJcfWMdL2g4xm3fteMtcvPmF6r89iEb8bjMyX2tSEYDweFRvCWFU3JUNZypiaxtbEsRiZjOqFuu4Tj/kUqG2ffAy/GVXEn9hvctuJ1x/wk6T/wQBIGate/Aaq+gcc+HyS+9Vlc5VZQUBx95A4Xlz1qUerbRasGdn8cl19Rz/18PZaU1aWkDopSOdmbOd9EgZSkaazVPrnyvbmho43XljjW0HGpekg265chX6e/4O/UbP5izEvQyzh1SyXEOPvI/uLzrWLF5+rqauaBRiLYd/RF9rX9i+/V/oK/9L3Q3/4rV2z6LyeJDlMwYza4sRiBHnhtviQ+LzYQkiUTDcTqOtc24Rve0/p54pJ+ate8gMt6C01eG01uuF6Rq2g2qoqIoSRLxPqz2KiRJ5NCj72Wk73FWb78Db9FOjFaLXoN4NmDzuHQjejF7kPbdTS4QX957nn5IJcZBEKek16uqQmDkEBZb8aKNjEiok+h4O27f5mkpYRcCRU5w4JE3EAt3s+HS7+DMy02nSVVVEvERYuFuQoFT9DT/ChCoWfs2CsqmqocvFloaKUBe4SWs2fH5BbWjGdILTe+a6TyZjI+feTaqmSIX2nsltWV0NbZNm0KlLUJzHRwEUdBzrtPCOEldKVk0SKiqwlBHH76yIhKx+BQDp7i2nKGutHezr6WL9Zeuo68/wcvvGkNVRvAPOviRqZ7I+Dgth5qRk0mMVgtmm5Wx/uEZ+7XQGpS5oIU5l6qtXF6bDstGybmDwWinvOHVtDd+l9Lalyy4YHSk70Ei4+3IchRBMCAIAmt2fEF/XxBFRAxsvvKnWZ5ezZDOlT5WcxiExoI8fn8TNWuraD3SRjQY0tMlJJNhWnXvyWlb2r9tLhvxyOn755UWkkrmJpZn97qJjUdmPCz5h/bS3/E36ta/d9nQuEBgMDpx5q0hHp1/xFk7+Dp9HkRJwuGuoaz+ZUC6kHWw+9+cPPAZLLYSBNHAmu136J8RJrQVBjr6UVIprE4Hqqrg9Hmyot9WlwOD0cj4yBgGo4OEKAEqRx5/N4UVzyIeHaR61a1YHRUMdj6EZDBRWHk5Y4PHOPDgrWy55mc43HXUrn0fI32PZ/V/IevwZCYog9mEr6RgTqY3jUwlswZyoVAVlfyKEvyDaSNLScnIE+x1y2m9Tx/MdPgXBBFP/uZFtz82+BTHd/+v/ndZ3cupWvlGhEXWe4z7jxMLdwPQ3/mPnI0NQRAwW/IxW/Jx+zZRVvvSRfVjLhSUXYvJ4iMeHcTuqp+9b7Oc25LRGIIoLjgiv5jzpIYlqdCZ7iG7GtswmE2Y7Vb9oKEt4laXAyUlz3mYSS+Ycsa/sx8wU9XUaDZhczkI+8eRk0lK6iswWUzklxUx0N5D3eYVtJ/o1nPxIJ2D2tM6iCRJVKyuRpJEisvdpFIKBx85RkFFMYOdvbMWdGW+/nQp/Fw2NM4tSqqeS1/bH+g8+cNZuffzSgun1CJoqF79VkqqX4woGTGaPEC2h1FPbxAEAqP7kEQHDs9KffzmSh+rGQCyLBMc8RP2j5NX7MNT6GWsf4Rt16zjyFPN+tyYjThBNEhIkolIMIIiy1SuraPzWAtjvYOMj/gpW1k9J0vcdEaNBlWVaTv+XZx56yiqfM6cz7Z8MDp/kIyPYTR75/05ba8RJQlJkiiuvk5PE7Q5Klmz/QtEw91IBisIKkarhd6WP5CMB6jf/FYgQSQ4zOP/eCH1G9/F5S/8IH1tvVkpN5lzRTNgZTmOIJowWYqIjLdhMLkQRJGR/kdIxEbxFl+C3VXJ5mvuxFO4gngohqJMpBia0srlyWhsQWNQSckoahL/4F58pZciJ5M5U0ovxXjXojf+wRFMVgvxcHSC9lZaVJrSfPfXzEwKSB+Al+fzhQNVSeHMW0NhxU0Mdv0LgJ7W3zLS9wh5hRchiAbyS64mHGwhFDhJMj5K3Yb3T2iGzI7R/l0YTXm4fBsY7n2AqlX/k9PnzhYyx7rbtymnz8x1bjvX57pF65qXrqjSH2Ky5HsqniA8GtAnu8bLH/GPE4+kLayFSqtnLjqR8TCKohAaCyAnk7iL0oU6ncdb6W/tQpQk2g636GwT2n3Ndiv+wVFikRgNqwtweqwIgkBpqY36TfUMtPdMFMDn9iMtRNxrPq8v45kBUTJTseJ1jPQ9THD0MEarZdrrZjI0YGJ8WwswmjzIchx5UqFl2vAXQRDoOvVLelp/h2Q0kpKDxCLTpw/OBjmZxO52UlBRSGDYT2DYj2iQ6GwZJjQaRBBEvd5htjaS8YTOpKUVlQMosozZauLKF5wuVrR5XFkOB7PdOmsfu5p+QWS8hZo1b8spb3/5YHJ+IOQ/SXD0CE7Pylmv09LyCmvKqFxbh2iQSERjaT78WJxELI7ZbskqajSaPbi867C76vAUrsNgNGBzFRCP9yKnxnj876+k+eB3qFlzK0WVz+bU/kd57C8vzzo0Z47BVDJEZLwNVUlRWvNCfMU7WXfxV7HY81EVhfr172fdJV9GkWVMljxKaq7AXeCbiMSvAiAWHsx6poWg5dBXaNzzYXpbfpvFBrVQzGdPSsUTSIZ0yrPZZsFkNePO9yzJYWc+z5FpaGiF6k93FFSdzun3FOde83e+Ybj3IfY+8DJ23/cChnsfAKCs7hVs2Hknbt8mRvofpb/jbxze9VZajnyFkb6HGB3YRePuDzNXZYAsxxjo+heF5TdS0fBqFDnG2MDjs37mbGO+Z0ltnBvMJvJKC2e8zmy34vTlzXimOJNYdGSj91SH/u+ZPJZOn4fg0BiqomB12AhGY7oY0WQBvflAS+VKxRO4vG7chT4SsTibL1tBX1eA3okfzGg2kYjFkOPZP2A8HE2nXYQinDo2yK2vymNw3MS3/m+XHs3IjNosNZ1tLtGSZTwzUVh+AwMdf6f50Jdw5v0Io8W+oHqF4OhRju/5EKu2fgpv8Y4pEUKLw87q7Z9HlAQMJgPj/oMc3XUHG6/4Be78qinjPbNINKsAdELDxmQxUbO2ivbGTuLhKAPtvVlMNFq91XTR0MxI5uRwr6qoBEfGefjgKf21iD+o13kAVK+tmbaIXJET9HX8ha5TP6Zy5RtyDpmfTTxdoqJLjXh0kMa9H8Huqqek5kUzXqdF0Z0eF1fdWIMkChwvdnFyXwtmmwX/4Gj6wCnHaT18JyU1t2B319O4+xO48tdQWp1Oh0hE45TW3URB+fXEQmFWbvkEqqJid9cQjwwzPnYcRU4imQ0IiBOCgBPsPnKMAw+9DodnJau3f46q1a/Tf1ONtl0QTafrlxIpQqNBIsEwktGAzeXBbM3XjX3JaFzQnFdVmcHuezFbi2k79j3c+duwOWYXCp2zzXnuSfHwaZ0d0SAx0N7DYgRENQiCiLZG5AKN0fKZQoiSqVN0oRLdjPQ/xsn9n8RbdBme/C3ISgKnZw3OvDWIogFn3mogHfkYG9qNxV6O1V7OsSffRzIRmNORJKciyKkwRosXu6seT8F2Ok7+CF/p1eeUmGG+yKx5zixNGOsdnDENOhGNo0zMQ60mbLI8xZnColzouXoZAgMjWYtV1brTuWcLfUij9bS+hqoo+AdHURUVT0Ee/T1Bupt7dA9WLBSeWKROQ+tPIhrHkefC6jDzje/38qc/dVOxqiZDUChDZXMWQ+N8jkboXuxlXDAQBIn6jR8gFumj8+RPs2qR9Gtm+V21cWuy+GjY+CHcvk3TzrV4JIokmRFFC4loHKNxE2su+hZmSz5h/zCdJ3+MIp8+8GQenkTp9PxXZBnDhIfX6bZgc9p11qbpaK9zObwIoqivMaUNlfgHR7K8yJBNvzkTW1V38y9pP/6diUL4V89533OBp/shaCFQVYUT+z6BIEis3v45XUxvOsjJFLHxCJHxMCdPjSOK0NM6SDwcZbirXzcKUokYgZH9qIQxWSx4CrYTCXRg8zixu53IySTBoTEi/mC6dsleic1ZRSwywL4HXoHB6GLT5XdjNJoxmk1Z41GSLGy55hc0bEqz8Iz0PUlwLK2toTEqplXPk+QV50/0O607YbJaEAQBo9mBI89KXmkhdo8zLdQ2H3pJUSQ4egxQqVp9KyZLPj0tv1/Atz+13fkis0ZzPhkCM93f6nJQtqJyyhowF7T7L8+x8x+qqnJi70cxW4tYte0zlNS8kPK6l+H2bZiiZSGIBrxFO1HkOEefeDeBkYNUr37znPcYn5iTrrx1AFSvfjPJ+AjhQPPSP9AZxGyOiExDI3O+qIqiZyHIyeRESvXinQC5YFEn0IVM3uDQKB1HZ/5RJx+gZjJoktEYrnwvvvJiIG0I+PuH6DnZTvvR9rQFl1HopnmfJrefjMYw28yoiorT4yAwHKDzeOu8n+18i0ZkPmNmjv4yLhzYnDV4CrbT3/E3/cBhMJuo37qKrddtAaYfd5m/vcVWgq/4shkFgTINAVVRMJpcONwN6SiEv5Hull+RSqUXruDo4azPZqZEqYqCf2CEtiPNPPmvPQx3ZdPOLjSNQ5uHo33DyBN6OPOBqioMdP0LX8lV1G/83yVXq13GmcNo/y5C/kZWbP7InPz82iYaHBpluNfPgQNjJONJ5GQy67BuMNjYcvVPsdnXEY9EKat/Hqt2fIRoMKR7gqdjXTFbCqhZ83ZMlrSREAuFMU4YDqcvFBjo/JeuzNx+/HsERw5htluJ+INYXQ7dOB7q6EVVFYxWC4IokIwniEfiSAYTyXiMeCRGWX0pnkIvRdWlWF2OOb8vRY6z74HXcPSJd+HybsBXfAUF5Tcw0vfwnKklc2Eh+4e212pRp8WkcqmKQjwcJTDsx+GdnfVmGecvVFUlHGylu/nX9Hf+A1XNPmdpgnb5pdfmvFaH/I0ER49Qv+H95BVepL8+03iLjLdjMDpxeNIREsNETWMqOT7t9WcTpSuqltwxrEX2tHatLgf+/iHdyJiPM2MxOPsSjnNAnBDs0xZlJSVnKV9qjBlpfYzTYntaXqokSZisaeMhNJaYkp4w3aLZ29SZxQE+34X1fGJvOp/6sozFw2IvJTC8j3gkiCSli1Kb953AYDYhiAImqxVFUbMoMjN/f//QXlLJEPmlV+V8T21OefK3cNENf0WUzARGDnJi78fYccPf9E1gukifIIhYHBaS8YTuXZGMRkxW85Swbl5pIbFQZMrrWnjYbLOSiKVprb0l+XMWhwPUb11F874T+t+KkiARG8JbtHPZ0LjAMNh9L3b3ClzeDfP6XG9zNyN9Vn1caXuJqsocevRWKle9EV/xZZis5rQWhtlEODC7GBpAcVU2qUBwaJRkIk1IYDS56Wv/C23HvkVw+CBrLvkcK7d+AkmykkqkSCb8MEFRr63Rmd52yWgkMDyGnAJFifPS122mvSvB9Vfn8fCuIFaHhZYDp7L6M6WfqERD7QCs3PIJRNGAw7UCORUmmRjDtIAC+8Ugcy+Xk6f3pYXuUYos6/T2y7jwkKm9IUoWFDlOf8ffWLXlk1jspYQCp+hr+xNVq99Ced3LcmpTVVVG+h/FbCuhoPzGrPdmchgbDHbkVBRVSSJIJgxGJwajk8Gue+jv+Asl1S/EW3TJop51PsicD33NXTnNjfko0WvrX/ozEBuPAOl1RKPCXWiJwHwcCOddbo2cTE5hrNC8Vqqi6OlTkkHiWS/Zoud2G82mtOJoJEpwaJRwIKgv6MCsodfMH2wh1GDn0+F+JqX25TSqCxOlNS9GVWU6TvwANaO4KRVP6GO7pLYMs82K1eWY8jv7h/Yy0PXPed0zMxJmtDiRjCYE0cjKbR9DNEwYIsUFWQuNaJAwTKiCx0JhPEU+vS9yMqmrD2uQjMZpDQ3t2bR2zDYrxbXlWGzmnMZw98ls1h1RTHttNKafZVwYSOdjP0VB6TXz/qycTBLxB6euy6qKM289RlMeFocNV34eyXgC0SBOITfJqY+qzL4HXkF/x98B8BZdyqqtn6V+84eJR8Y49uT7ScQG6Tz5Kw4+/CZ9/k63X2j7ntVezWDHk9z3r3a6Wkf5yQ+OMdA1SvfJLkxWc1pryuPC6cvD5jnt4VfkBG1HvwWIbLz8B3okSBMBi4V7p9zzTCNzL59vCuV0WKp0qHNRHPtMROZ63dPyG93QyC+9lotu+BsbLr0TORni6FPvY7j3IVoOfxVQKZ2lNmsyBrv+hX9oD7Vr3z0lzWomiJIZVU3pURVJMlNc/XxGBx5jfOw4pw58Bv/Q3twfdJEwWU/vbZmpyXNBlKSsc61/+ADHnvoA4WDrlGu19U0QxayMn3g47bBfaC3yfObiBXUCjQZDOPJcekj1zz98RA9jx0Jh3SCB7C+huLaCwqqpwjKzsUEtlr3jfMP5ZBAtI3dYbCVUrbqVvrY/cmLvx9Ie0gwkonF6m7vSxdlWM56JXHANVavfzIotCxNCg3RhttFsoqjqIiyWclQ5HXr19w9lzTGLw47T62HTletZe+l6xvqHMNvSqRPaQqeNwcKaMt0AyQVWhwVJmt0bqs3XKSrmgogomrPqTpZx/iM83oaqJLG7G5asTUE0ULf+Pbi8a1EVldHeIb1GI9exCGkxzJD/JIKUYtXWT+l0t2ZLPr6SSzEYrIiSmYKy6zCYbHgLL6Fq9ZuZiwnFV16MLIdRVZGRnkE6jrcRDUXIK3LTsKUei8Omj3OLw8rqbfVp7vzoEIcffweDPfdRt/69ODK+M5OlAIPRxWD3vxfwjT09cTZUwpdxer0fHXic9sbvU1hxE1uv+TUrt3wMUTLhzFvDuku+BsDJ/Z8kFEhHpOPRgZzvEZ3QyoDczzdmaxFAFutiRf2rWHvRl9l27W9xeFZxfPeHSCWXjgxoNqQSKSSjYV4016qiIifTaaKawTE+dgT/0B6OPfneLMcknK5bni6lfq6zodO3NJTA510a1WwwWi0Eh8bm/bmB9h7dYrS6HKSSqSlUeJnV+6qiUFBVxmBbz6x9WV60lnE2UFb3/7A6Kjh18A72P/gaqlbfSlHFTfrikWZkA7PNSigYxOZxEfEHGQ8cQ5IcODy1C/YGCqJAPBxlpP9RTuz9GNuu/a2+WGuQjEYkScJoTqc3Nh9s1u+npOQpBsBI98yUvZMRj0S5/MoSfvqNh/XXtNRIg9mEZJCoWV/LQOfQjFTAomRGkXOfq+ezvsYzJU1ysOvfGM15uL0bl6xNVZWJRwYwmvOyGFhURdHnTC5oOfwVRgd2Ub36rRRVTi8MKUlmqlffqv9tsZfNmcY32HWY0f4nqFv/HpLxhJ4m0fjEUf0apy+PSDBENBiiv/Uk8dgJGnd/A0VOsOHSO3G4V+jXppJh9t7/UhQ5RjjYMt0tzyomM9hN9/75Ou+WsTD4hw/QuPejeIsvo379e6eI8ZmtRWy96uekUhFSyXHkVBiLrSzn9svqXkZkvJ3GPbfjLbqMkpoX4PZtyZprk9fMcX8jomTJ2sdEyYynYBsAvuIrCQwfQJTObC2Dli682DGvfd5gcgOQTPiJhrunCAIv9D7jI2NLsu/MK7KhKDN39mxEAtK5n6d1NHKFqigosozRaiEaDOmy7euv2MjGKzfiLvLhyMsuOpvN0ND6soxlnC14i3ay5aqf4y26hJbDX+bIrncQCjRlXRMcGiUVTxAPR3EX+UjEujn4yJtIRAOL1rNx+7awevsdGE15+If2EgmlKa8FMS2UFQ2FGe4ZZP8DB/VUxJlCsyaredrXbR4XBVWlOH15OH15GMwmTBZLlqGR2SftWXtb+hjrHZwots1+TkVJIctRJCn31Inz+cDzTDA0AEYHHye/5OpFKwVnIpUMs+/BV+Af3quPIVeBF9Eg5ZRGIEjpseXMWwtAIj6CaJAIB5sIjByadK9xhnruJxbpo3HPR3VRssk4rUGVovGp/8NiK+bmN34Eq8uRNU+064a7T9F58hec2Ptpdt/3Yg48+AFAZf0lX8fhXpE1/uPRAd3IdnnXz/18ZyDVVitMncnQyLznuZ53y6nGSwetluLYk7dhMDhYtfWTCKJh2u9YEA0YTS6s9rL0GJ5HbZ3R5Gb19jto2PRhouFujj35Pk7s/SiJ+GmntEa7rmG490F8xZdjME6fOpk+pKtEQx3Tvr9UWAittYbp9oGCkmsoq3s5INLX/ud5tTdZo0r7vjKFgCcjHhumr+1POd9jfrNrljCwVsh9NjCZxjYXqIqSZSBEgyG6m/sYGw4R9o9n8VNPB6PVsqS5nhciHe2F1t+nG0zmPBo2fZh1l3wDWY5w6NFbOXXgs0RDp+sUtPomgPWXv55t1/4Wg9Gx6EOqwWjHW7QTUTLRfPhLDPX8F1VV9IVc07vJxExOgZlSViL+IMVVBYQDQcZHxkjFE1hd028I66847fEODo2SX1FCMhqjZkN91nWxcBeqksTmqpvP4y7jHEKWY8Qj/UuaQgVgMDpo2PghvEWX6a8Fh0YnaFnT6YGTqaW1uohTBz7Lscc/gGiMUVx1Cxff9CuKKp6NkpLp7/g7XU0/zbqXoqRoOfJVgqOHceatRjJOzyalpGRSyRAnD3yG4MhB1l/+cQ7vaiIRjZNKpNLRO6MRV74XQRTpafkVHY13EQ21UbX69Vz/6kfZceNv9dqMzHluc1YhShZszloqV7x+zu/nTBiyGuVtpiGR/R0L582+8kwx5M80+tr+xJP3PIsTez8GgDt/s86GeCa+Y0EQKCy/kc1X/phVWz/N+NgxDj/2FvxDe3UHuSZlEI8NExlvw52/Zcb20noeJsYG9yx5XxeC2Rz5mUaCweSkqOJmQKG//c8M9z44Z9uag06ZRH87U+0vgH94P4ceeyt7//tiOk/9MMenmGcalShN75Gc3MEzjaUQq1EVBV+JF3WCyWc6ZIaOMtl+5ovpBLsuxIXtQuzz0xFu30Y2Xn43A53/oLv5Fwz1PEBB+fVUNLwaq70cgEgwzEhPM5KU7bHQUhUWIyK38fLvI4gmDj36ZvJLr6K8/pWA5kE6vTAGBkb0f+dXlDDcla1Mnjm/nL48rC4bp/ad0vvl9OURj8SyxIsgXZx+5JFDWe0Md/Wx7Yat7H/gYFZKpFYsZ3fWLigU/ExJWzqfICfDgIrB6CQ4eoSmQ19k9bbPYHNWZ12XNnaTCKIRQRCR5TiqnEAyOqb1jgqCSGHFs4D0hulwN2AwOtNtTRjNBrNJT01UFUWPeNRvehsjvfuRE2YEAVTZgcmSNiCq17ydRHQofX8lgcHoxGTOY+vVv8Ro9sz4nOFgK33tf2ao5z+oqszKrZ/GZFw1bdQ8MDhC+coKDjy8n4Ly62nY+CEAImNT57Dd6yY8GkgLECoJSqpfiGSwTrnubENVlKxUKUEUdfrshRCzLOP8w9jgblqPfRuthqK46rlUr37LWbm3IAj4Sq7A4VlF496Pcuyp92Oy5FO3/r14i3YC4PYcRDJY8RVfPmM7omTGU3gRnSfvxlt0MTbn4gQxF4vZ9unJ88bqKKd+wwcZ7n0Ah2fVjJ/TDPxkNJYmXUrJOZcGDHb/h5C/ceIvkVzrZc4Pl8IsmK+Az1zI5BTuON7OcO/wnMJok/89EzKjFZkWZ+ZgORNenPPFM7SMswdRNFBS/Xy2Xv1Lata+A//QXvY/9BqCo0eA9CJy6sCXOL77g1ljXtvoF8PoYjR5MBhsFFXehHNCGEmDqqj62PcUF+hjc7KhAVC17nS0QTSIDHX0ZS2e4yPpwl3jJB7wyc4Gb2kh7iIfe+/bhyvfSzLDMImMt2KyFODML1mQ0TDdZ55u5BHnG4zmPETRTCzSh81Vh7foEt0o2Hv//6Pz1E8ACPlP8sQ9NxIZbwOg69RPOPDI65FTYVRVnVFbIpWKpg8jT76fxgnvq5yK0t30a6LjYySjaWrIZMJP04GvIKciiIKXgrLrpjViJMmM1VFOb+vv2P/gazKewzPt/YOjRzj6xG0cfOQNjA0+QVndy9l23W/xFV8643eiKgq77/kmkWA39ZteT+mKqhkj7eHRNB1vb9ufsNorKCi7dsZ254vp9uP57D+aoyPdlgGb2zmhqJ4mZZmczrGMCwutx76FJ38LJdVpRilRsiCdZVVus7WQDTu/zdqLv4bVXsmJfZ+g9di36Wv/Cw//7VsUV9+It7QSs906o/5Lw4YPIkoWBrvvO6t915BXWjhtv3KZa0WVN7H24i9jsZ0mRcpcKzSHCpBBTZ2cMfoI6fXx5P7PsOsf1zDc8x/cvk2s3n4H26/PPY3qjBWIL8ZzOhk2j4toMJQz/7AgiFPyQw1mE6u2ryIWTZCXb2ff/QdJRmMkjIYl81xOR6E72VqcSYRtMX1Y9rw+cyFKZkprXkhR5c3sf/DVtBz5KrXrbkMQRML+U9Sue7e+kS+1gm5J9QuAdH66aDAgClYEUSARjSOIIv7+oYkFM3t8S0YjRrOJjqOni1YzoyCZ12naOpDOrw8OjWY/v0FCURSUlELZyuoszRxVVQmOHsHmrJ4X29BcONNKxM/0aIogiBgtXpLxUQwGGzVr3qa/V7nyjVgnCh8t9hIaNt2O2VIIQEHZ9eSXXoPB6CAy3s7BR97E+p3fxJm3hoGuexgbeIq6De/FaHJhkGzEogM4PKuJRfo4+PAbEQ1WRvofIR4d4qJn/ZFEuB//8B6Sif+X04HJV3IFdlf9rNeM9O/i5P5PYnPWsGLLx/EVX5EzZWcyPorB5MFgKGewo4/K1dW0H22ZcTymEgFsztoljWpMV1cxn7EqiOJEGnS6z+JEdCMeiaaZ4yboPM91/cYyFoZkfJSiipsorX0xZXUvnUImcrYgSiY8+Zuxu+roOvVThnvuJ5kYw1d8BSu2voNoKIKmnj3d/DGYnHiLLiEwvP+s9lsb+1aHlcA0fCezzTXNEZA5d7RaqWQ0pv/bMHGdIst6+UOmTMR09+nv/AfDvQ9QVHETw30PEY8O4i3aOS/GrjPiEpeMxiXbkCdTZM5l2WksU5O/rFQ8QU9rP837TrDn3n0oKRnJaFzQIWQ+tRu5FpJnKjwuYxnzhSSZWb3js4iiiaNPvAv/8F6c3rVYHVUEh5v1nPSlRioZZvd9L2C451HgdI62qigzCg+Z7VY8hV49rWImaHoJGkJjgSnXKCmZSGAcRVXob80mdRjpe4jg6GGKq553QUUjnsmGhga7s5bB7vuIR7OjWIXlN+CcSA8wmjwUlt+AwZSOethdtTrtq9HsoWbt2zFPePcMBgeBkf10nkznGG+84i5ceWupWvUmRMlCWd3LKKq4BTkVo3rNW1FSMk73WjZf+dMsD+FssDmqZhUDG+q5nxP7Poa38BI2XHonBaXX5GxopJ8pj1TCTyoeJRVP0Ha4maLqsmnnkCzHGfc3Yl9ECkjmnFmqvUmr30gTS6QYnWCQE4S0QyQaDKGqygU1X5eRxkDnvybYpEoQReM5MzQyYTS5qF33TrZf93u2X/dHNl31FYqrV5CMxuZkgkolw0iG+evvLAZaf3pPdcz7DJ2eVwJmu1VfE7S6Su19LTVUTqb0M4HJak4LYs+yF1usxYDKQNc/kVNhvLOkoc0EQZ0p1pyBYDCI2+3mohv/OWMF/9nC+eL1W2g/ZvucZDSiqsoZ95wu4+kLVVU4uf9TxCJ9bLr8Lg4+8kYcntXUb3g/cDqfG057URYzpxQliX9oL3ZXHWZrYdZ7gihSu7GBzhMdi2Jvmy0qMxtbRnvjXQz33s+2a38LpCOk8XD0gplj58tady6QiI1w6LG3YDTnsX7nN+fFJjYTgqNHMBgdM+Zgp0W+xAUrzfe1/QlH3hrdGNIgyzFOHfgco/2PUlh+I/UbPrAglq3xsUYO73or6y75Om7fJoAZlX9H+h7lxL6Psfmqn02hwMwVJfWVDLT3TJkrSzkutflr86QNRm1tWsaFBU0dvLjqudSufdeSssidK/S0/IaOE3ezfue3cOatPtfdyQmakZ45Z2eKFM5L10NVCQdOER5vxWqvwJm3GkGQSCXDPHXvzQQCAVwu16xtnBFX+mK9Ermqfc92n6Wq9ci8h9FqoXpDA3avm9qNDdz4iplzbGfCTGlUkD4oTlaQzNWjtJzrugxIewgdntXEwt2oqsqKzR+jatX/6O9nbubaQjPbwSGZCGRx9DcfvoOUfFCP7omiEW/RJbqhkVkfoioKrYeaSEbTRd4Gs2lB41RVVCSjURcXkoxGvT6qqHpmTvZYpA+L/fT7EX9Qj7Ys4/yGyeJj9fY7iARbGOj856Laioa6OPrEbRhNebMWewqChCAIhPwnF5Sr3d3yG8bHjmW9JssxGvfcjn9oDw2bbqd+4/8u+CDm8KzEbC1ioOsf+r4wE2XvcN8D2F312ByVWXvhbPvJ5P3UW+TGZLFkfU67ZikjHaqiEB4NLBsaFyji0QHaj38Xl3djOoX3aWBoABRVPReLvZzDu97K8d0fIhQ4dUbv5ysvXnQbSkrWs3a0uTqTQTGfVEVBEHB4VlJU8Wxc3nU6u9h8sOTGRtrroS5qMcr1S5jNO7lUOZ+Z9zAYDXQeb0VOpGg/2spl65KLOuTroa4M1fNM1h3JaMzZg7TM5rEMDVZ7GXIqQtEr6g0AAJAWSURBVDI+is1ZTSI2hKqkFtRWT8tvaNxzu/63yeLhoovycPk8BEcPc+Tx9zDYfa/+/mRmt0w2N00XYzZMt26kmYIELA5rBv+3gMlqZtwfxOpyTDkoJRNBxkePTBGISkZjF0y04ELp55mCw92Ap2AHQ93/WVQ7gmjAaPZlMaXNhpH+R+lr++OsulLTYft1v6O05kX63/HoIAceei3jY8dZs+MLFJbfsCDadm3Me4oLyC+7ivHR47oGh8FsQjRIWeM/lQwz2r+L/NJrEUSRmg11+j6VWRg6GWablYKqUv3vY7uOIIgCTl8ekjF9gMxMk1wqLKcPX1iIhDoY7L6X/o6/cWLfJznw8BtQlAR169+74Kjg+QiDwcbmK+6mYdNHiEX6OPTYW+g4cTeKvHB9jNkw0t2f87WKkpx1fZKTyQWtNWcSS96bdB720lq2Fse5Td3SEA2GUFIy8Uj6wPSrv0e47oVbF6y/MZdBtFwkt4yFwGT2AumoRCoV4dBjb6Wv/S8Laquk+vmsueiL+t+VK97GsRNrGO0dpL/jnwTHDuuCZjMdGgzmqUqseaWF01w58wE7FU8w2juEzePEVZCXLh63pQ9QcjKpOwUEUURVFZoOfA5FSei0vJMhGY1LqpuzGCwftmZGUeUthAInpkQM5gOLrYSVWz46Y+3F5O+/cuUbWbfzG4iikVDgFPHo3Ir3qpIiOHo06zX/8D7i0QE2Xf4D3L5NC/6dNVrewOAowZGjWBxlxMNRfV4pKRmLw47FYUc0SIz0P4KiJCkouxZVUUjE0gcPjSjCYDbpBxHJaNTbSU7MMQ0Gs4lUMsUr37ieVDyBzePS21jKmopnulF9IUBVFUYHHqf58Jc58NDraTr4eVqOfJ14dIDSmhez8bLvY3NWnetuLjkE0UBh+fVsuuKHVDa8jp6WX3Pw0f/RKdWXGlbX9Ho8mVBVld33PZ8n/nU9rUe/RSoVmfa68+38eEbiXal4YiJdIVMhdWqhaK7IDBWfD3nMqqIgKwonnjrOSH8JtetrGeweBsDfP3zO+7eMZzbECW0NRY4iSVbW7/zWvIv1ErERAiMH8BbtnPJZbT5WNLya0YFdOjtQ5rh3FXiJR6IkonEkg4TN5WV8xK9fM9Y7+wFOEEUceW5CY4GsArfwaABtNUhGY3palGiQECUJOZmiq+nnjA3tZv2lX8HmKpsSAZWMRtZcsoajjx3BaLXoxsq5WluW14uZ4S26BIutlN62P7ByQrl7PjCYTSSjkbSKvME2bfhfO8xrv4MgCHqNSNPBzwOw+cofz3qf4b6HaTn6NXZc90ddj0pOhhEECXGCDUoQhdl0cefEQOe/GB87xtqLvzLRfgpVUbB5XDqRgsFsYrjnfly+jXpq40B7L1anA7vHycaLa2g5McRAex+eIh8j3f3YPC5K6ysY7OjP2mvdBWmnxfe++AiFNWWYLSZibgdj/cPIydR5sRcv48xAVVWCIwfpafs94cApVCVFMuHHYq+guOo5VK26FVE0zKm9dr5jtpq/TIiigYoVr8FbfCkHH3kjHY3fZ81F/7dk/dDqEnMhLBIEAaPJjZwK09f+R8aGdrN6+2exOc5vY++MuNQEUdRThLQcsjNBL3uuoSoKyXgSVVGx2Cy84jWr9PD2Ms4tnsneYo3qUpZjCIKA07MKkzlvWt2Bmbz7kVAHpw58Djl1Ou1J82pqsDrK2XHDnymtfiGiQaJ20wrdMxMcGk0XYysK8XCU4NDovOauqiiMj4xlfWbljjVZfQEwmk2IUnqhlgwSBpNAd9PPqVjxSipWXY/JYkEyGqfksB597AiiJGHLUChfzNryTB5vZxKCIFJa+/8Y7n2Icf+JeX8+FU8w7m/kqXufQzTUPeN1M/32Gy79Dpuu+NGc98kr2EH9hg9kHb4Kym/AYHTSfvxOYOa031zGTjjQRuvRb+DybiSvcDtGqwVfWRGe4gKUlIzd68Zd5ENVwvhH9pNfcrX+2Xg4SnB4FP/ACA/9ZTc9TZ2IBolENA5AYWURkWCERCymrwdGq4WR7n5ikegEu6RCUYWXeCSGnEzN+p0t48KGLMc5uf9THH3yNhLRAfJLriav6BLW7/wmW6/+OXXrb8NgtF/whgacrhnKFXZXHYUVNzE2vAf/LLS48438zZewZN0lX9edgInoAIcfeyujA4/Pq42zjTOyQ6qKoisTal/605Xadax3kKb9JwmOBjAbVTZfue6sPufT8TtdCjyzN8J03qxWpyHLcY48/i5GB3ZlXWVx2nF4pt8wPPlb2H7dHzBOpGSl25vK4iSKRmzuPJSUTOvBU0uqZzEZJ3cfz+oLpA9SWrg4Ho4Si/Sgqim8JTuJhdIHKIMpHcDNNDg0Cs7AwAhmW1rYKXO9mi8WOt6WKT7nRnHlzdhddbQc/jKyHM/5c4qSZHTgSUyWAlZu/RQmS/6cn8kUZoW04S4IAi1Hvk7jno+gTgpNqKpMZLwDg8lJfsmVWe8ZTS4qVr6e4d6HSMSm6sjobeQwdlqOfBmD0Ulp7UsxWc248/O4/IYGbnz+al7y+m1su3I1VruN8cBeUFV8xZdlfV4jHjFOkDSYbRZMVjOCKBIOhBnpGUinY02kJmqkDqqiIieT1KwpJZWUdafB8nh/eiEeHWSw+z90Nf2CAw+9hrGBJ1ix+WNsvPxuata+nYaN/4vLu+Fcd/O8QP369+L0rKFrQlx0OigpecnG+rT1VdZC1l78VSy2MlRVRk5FadxzO+2Nd01Zo84XnNGTajIa0w8nSxndON+gsWn86a/9BMbObaH28mK+jHg0XWhmtqXZLSTJjM1ZjWGCM1zL8QwMtvOPH2xmbHB3VtSj9di3aT32LYzmvDkL/k4d+CzHnvgskBYsazr0RRLxMf19yWjU88nPNMbHGjn+5OcQBAmzuZx4OIqSkklE47rIpyYaBuD05WUIhp5O8zybBvyFQMF7riGIBuo3fpBoqIvmQ1/I+XNjA0/QuOdDyKkI+SVX5kTbPtNB2pm3Bk/BNrqafk4y7geg48TdnDpwB4d3vY1kIjjlMwD5xVcCKk2HTqdczHd8KXKc8bFGyutfga/4UiwOGxUrinn2uj5ONAYo8Cg0Huxi3B+k6+S/cHnXY7YVZN1PTqaQk0kS0TgR/zhjvYPIKZnLn7sDZ54DQUzP8/GR03N33c41JCYoqw8+cozRwfF59T2zVkv73PJ4P/+gqip7738pTQc/R1fTT3Hnb2Xj5d+joOzap1XB91JBEA0UVz13giDl3UTG2yZos7Mx37GuObyma2e6eWe1l7Hxsu/hKdgBpPfvnpZf0Xz4y/O679nCslt8EZhMr9t+uInGJ47qm9X2G7ee8T5o+cYalhfzZcTCPYCAxXq6ILZu/XuxuWpob7yLvf99CcHRw0gGKyu3fgS7u4H+zr9xfM/tqKqM07OKVDJMJNiRZThMB4d7pe7xcnpWEQ6cxGBy8N6PXU7tphWY7VZUVdFJFTKxlIf6WLiXI4+/g1QyzOodX8BoOs35rR0gNUYsLRIyPjKm57pr76dpAw16Ia3d616yPi5j4XC4V1C1+laGex+esSByMnwlV3Dxs/61JIWraSYpicGue04fLASJcLCJ0poXZ423TBhM6fEjT/Q5HTmZ3wFOECRUFAQhHaELDIzQ3TzAF3+Rdiz98c99GIwGYiE/I31PUlh5LZLRkMXcJkrSRH3TaWMqHBjn0b/tpvXgKZSUjMFswlOcNlKqNzRw5LFjqIqaTtHKz8M/OIbT58nZoaUx05nt1jkFPLOed5Z1Ybr3lqP7i0Nw9Ij+78oVb6Bh4wdnpYheBviKL0MyOgiOHuLAw6+n5fBXF92mkpL1OsTJmMlRbzA5Wb39DlZu+YQuYCqnclf1Ppu4oAiRjVbLosTBlhpyMjmr4NiBh46clT6LkoT8NI0aLWP+iEV6MVsLEaVsFij/0D56Wn6FyZyP3b0SSTKTX3I9AKJowmT2IggSBWXXkV96LUcefwcGk5s12++Ycg+z3TqRT/8S/TWrs5hNV/wQQRT5+c9a2HZZLcM9w1kq4JlYaKQzHh0gMHKI4MghgmNHkVNhFDmOKFnYcNl3Fi0Al0nfm4onlsU2zxM43CsBhXikH4OrNqfPSAbbou450vcI0XA35fWvoLDiJgorno0opg/NVStfT3n9K5BmyV0XBAFv0aW6gZI+dKfrjCbTRM/YhmjAYisjOHaU4qrnADDc1U8ynmTMIKEoCqIoMtz9FKqS5KoXvh5ZKaL1SIt+j7SScHbNVua+ZLRakCSJcGCcvNJCRnqG9f3NaDIxPupHTsmoikpJXQWjfcPEQpGc5nAqkaJ6QwMD7X0kSO+bmuExHWPObG2KkoQy6ZrFFt4/0yFOUEIXVT6HsrqXnuPeXBiQDDa2Xfs75FSEvf99MaODTyxZ22mmuNz3GkEQyC+9Gm/x5URDneetoXhBGRvnG5UXpK3RlTvWEA3H6TyWFj/TDJBUPIHZbp3VIFkKLFYFehlPL0TDPVlidhryCi+mtOalBEYOTjkgFZRdx9X/7/0cfzxNMSoIAis2f1SnyFRVNSukHg9Huey5FzEyFKbxiaOs2JZWWD21t5G2Y99ldLCI0d6XYHHadG+uIIiLmsOJ+Bjtx7/DUE9ad8HmrMHt24TRnBb7c3pWL4nSNKTZtCLBEOUrKhnsHGR8ZAzRIGGyWEhmREeWcfagiYVNl7IwHcaG9tDd9AvWXvwVxAUKjUVC7RNpEsq0bUiSGVVVUZXEtAWzqqoy7j+Bw92AZDRSWFVCaGyccGB6A3wmFFXcROepH1G9+s2YzF5URcHfP4TFYScRSxsNqdQJbM5yRGMZkUAUySChKrmpBCejMVIT8zQ4lB7rK7atpqOxHavDisvnQpRELDYTnSe6iEei0+43okHC4rCjKgqxUDqaIyeTdB5vzUpVXOj8kZPJNCVvhqG27ARYHJKJtJhiac2LFyTWNl9YXY4zWtt3tmAw2DAYbNSuu422Y98kGu7Gai9fdLva3BBEkUuevY3H/7k7p8+JogF7jk6Yc4ELytg4XxcVrXBVEEVMVjOKoup9PVtie5kL/+TFeBnPLMTCXTg8a6a8Lkomata+DWWSwJ+2+GuGhgaLHpaNcvLA7eQVXElJ9fP19x/721P6v1MpmbbDzRP3MRMbVxDKBI4+9nmqVr0Oo9mtG8WQe1QjmQjQ2/ZHAkN7GQ+cwGBwULf+ffhKLsdo8uTUhgbJmNvBSzIaGR/xA9By4CSQnttKSkaWZYxm03Kk4xxAiygoSm5rmySZMVsLWEzWeXn9qwF1RoEsVVU5+Mgb8JVcSeWK12W9J4giqiyTTIyRiI+iqgp9zZ3TtjOXs6ig7Fo6TnyfkP8E3qKd+uuiQSKvuIBoOExv6/2UNVyNyWJg8Eg/3pL/395bx0mWVvf/72t1y6Xde1x31oVdHBa3GCFAQogHokT4EiEe4vxixBMSLHgSAgRfbFm3mR3Z8Zl2LZfrvz9uVU33TM+0TFXr8369+tXdVbfufarqPnKec87ntFPKF6kUSiiaRqVQrN+zl/eF2vU9F0LxEKqmcfrJk+jhEFND4/X5ZLF2urazoCezkX2lpoa1GPPkjMVm3FW5+Mz7iST21CXMm421ydYmrd3PZezcJzn87bez/44/uCKRfqmbzbV8jZrH0XPdJRsaGwER7NgAJFmuKnf4Mp9rGeolyTLKZTF/lyusCDYvnudSLgwTvmzieObx3+PMkf8P4Iod2nKugKwq/NDPPX/heGxJJtHyLFKdB1E0jez0E0wOfWFeUvm5w6eJt6eQZJmBPW9l+6EfQpIKTA59HsM4V49TX46Szcz4/Tzxjbcydu5TBEKd7LzhHdz6wg/Qvf11yzY0YOm7qY5l1YuTRloSaKEgejh0KfTD8SeOuZ+V6F/NJxjpBUmmtMSCWvGWG33v3DK9Gp7ncebIexk5+wkkSbpmJV5Jkujd8QZaOu++8kk5x7ljfwueS3vPi6+64JBVhR037b5mQa/a/W6Z2Xn3WimTY2Z4nNzMkxQyQ2y/4XtQVRlV04i3+OeLtSTrORNaKIiqB+ohUvX3XO2TwWgETQ+Qn0nXdf/nblythwX75XmKV2Nubsx6aPd6xHVMirnTdPS+ZNWSwWv3kxYKzskr2rjjZ0Bv4dCz30c4tp2nH/glpka+Mu/5peYqWeUKVrmyoT+La7GhPBvrlVpy6VpyaWfKvcKbEk0lKBeKy2qjFgpiG6YYpDcYRnkS1zWu2KVq6Xw28jVCjCRJ5oN/840Fn1MUnTtf+f+YvDiOaztkph8lnz5Ke9/L8DwPxyoQbelCVhRirUn0sH+d3LTLC9/wzSsWLIvheR7njv4NY+c/Tarjbnbd+CsEgq2Xnr/OehhXe/3lXpdaQrmiaXWpXMeyCMWjKFUpUT9e3CMQ0kl2pLh49IzYRW0SihIkEttBPnOsnrtwLSqlcQrZZ2jtes6ywkMkScLzXEILhCIuREf/ywF/zDRLZXKzRxg9+3FmJ+5HUcMM7vtJenf9ACxQ5wb8Xf9zR07Py6m4/B6SlQCR+G4mLvwvyfY7iKb6fLED2yA38xQXT/47oegAVqWbZFIn3pbgj7/nLF/J3MmREybjw1lmJzIYpQrlQtGvneFcMn5qng6zUsHzXGKtKUrVTYj1lCcJlz6bpXhZBNdGkjXiLTcyfvFzdG//vlVVn5p7X2308VILxDn4rD/nzOE/5+QT70GSVG576Y9z4enT9O8d4OyTJxc9R6w1RaW0tpvVl7PUaIClIIyNDcLlrriatex5vpyn53pXTRJv6W5l/FwF2/AnRM91CYSCdXf3QjdU7YYXC6eNRbngh2lcbmy09774mq9bbEDJTKWRZQkXGNz3E7iOgSRJ5NPHOHPkvdzxsg9RKZR404/fxhc+dwFVU5kaGqE4dhpNTxDQO5b8HoZPf4ix859mxw2/QNfgdzV0ArzWvXy15xzLItaaoug486q8zu0blUKRQjpbr2guaA6x1AGyM08u6djc7GFOPfke9t/5J0TiO9EXqLORnnwYSVZJtt2KbRWZGv0KrZ3PYeehdyzZQJke/TrBSA+6k+LEw79HbuYIoeggOw/9Mh39L0HTo1ftX7V76PKF8UL34vYbfpbjD/8aj331B2jvfTHh+E5Gz34SszJJINTBrhvfgeu4HH1ihNauJO/6dBhVS5OZzmNWTDzPm7fppGganiz54YHV9rm2g2GXsQyTYDSCJEs4lnVlfZ0m5yFeC0VTiSRjZCeuXrtEsDQkSaJr2+s4+fjvMT12H+09L1rrJm1YZFlj103vxPMcTj7x+4SifUTiu+rhxYtRyhXo3N5Da1eSU4+fplIoEm9vwXM9LMOkUlh9lalG5iZuTn/NKqFoGnrEL4Kk6oGm1rhYaGAPx6PEWpO4joMkSwSjkXmFy8CfFAqZQj1OsuaFqRkaic5WIsnYVV13wtDYWJSLw0iyhh66tLifGf8Wxx/5jes6b3E2O6+AXi0ZVlaChOM7MYpZLMPkwYdmcR2XcrHM8Yd+iyPfeQflwuiSrzMz/i0uPvOv9O95K93bvrupO23LcVfXwkpqr6slwc7Fc/3YftFnmkei9VbKhYuUiyOLHtvW/QJuv/cTnHryj5i4+Nn64+nJhxg+/WE81yYz/SijZz8B+Lkg54/+HYXsM8vyhJw58hdMjdzHk/e9DbOSZv8df8wtz38/XYOvRpb1a07Y81WVrn0/Jlpu4vYXf5zBfT9BduZJzh/7BxKtN3Hbvf/BHfd+gva+5+M6DuNnhzn2wDEunrhIZjqPYzmomoptWfMM4YWMiBqu7VApFKnkSwuGgayl18A2TIxi5YraPW393Zs2BKWZnHz89+q/XVcIX1wPkqSw+6Z3oQYSTAx9AVh4DVVbN4K/RqspHo6evMDT3z6CWanQs2cQWVEo5QqbIs9FeDauA8ey6tUaHcsmENIxXWNVFhuOZdULMEmyjIuD6Tj1kA7TNeohHrOjk/NCQ2oEoxE6+zsYOzeOoqm+WsgyEl+X6s4WrB5mZQo92D5vsSRJGrISuuLY/7v3M7zl1E+THp9ehgzn/O86Et/Bnpt/DfDvraP3H6Fjey+56QyZ6Ufp2/NK4i2Hltz+iaH/I5a6gf7dP7zk16yUld6zvtLOpV2mubu8dWNMVeja0cfoyQvX39B1yFr1+VTHXchKkNnxb9G78weueaysBNCVdm56zt+jh7rqjxvlSTJTj9K7801s2/82KsVhAAJ6ijtf+l9Lksv1XJtS4SLh2DZaOp8Nkoxl5lEUg1THHdfM87j6ORf/PFUtSu/ON9Cz/XtxXYNAKOnfc553WR92KFsWE4ZJIBRE0zVc213WTqV/TzsN3d1sFJVCEVUPzLsPp4fG/PAwxCbZUjHKk/P+t83cvJDV1WYziNtIskr39pcwPfIAu27bR09/ktnpEumpHBPnR7nlBYd4/GuHfVlpPeAXna0aeaF4lDf+2G2MTToce2qc/Exm3fS/6x3zxTbANVhKYk9tkVHLlViLQa7mhq+1xTLMuvEgK1ffoasUipx89Dj5mXS92Nlydqw8160XPxM7SusDy5itS8HWSHXcxd5bf/OKY1/xldcydWF0efkU1fvb8zxOP/VnZKYeveKYyXMjlHMFbn3BB+js+0Emh77A5PCXlnT+cv480eS+DVW5VtG0eQNxzfgYPzu8aYsCzn2vq4mihoglD8wrRHY1crOHOfnEH6AH2ykXznP26b8GoHPgVRy480+qyd8SoWj/nPMvrS5HpTzOU9/+KYrZU7R2PY/s1MPIcgDbLnOtaVWS5YZ8ZpKsoqiReYnec5NtZVVBkmVsw6ScK5CdmJlXHXwul3vCNwoLjVt+PRFhaCwVTW+p/9058Bo0Pbl2jYErxG02IrKqkGjrAyr86OujjA9nOfbgUfRQgEgyRltbiK4dvbR0d8xbMya72innCmTyHpMTJWzLnpdXtdZcb78SK8RrsJ6+6KXiJ4l7uI7j/13N6WiWMVCrJyIG+PWBaczOm0BsK8/RB3+J7PQTDb2O65QxKpO4rkmpcIF85oT/uGsxdPIDWGYaPdROQE9RzJ2hkDm+pPOGYtsoZk81tK2Xc3n4xfVilSvzFHL0cIiePX7V6uJstn7cZjTI1yKcJtZykNzsYRzn2omUjmNgVKZxPYfhMx+tS+ZKknxFwcvlEgx1sW3/24gk9mBbBUqF88iyQiJ16ApDee73vlB+xvUyd8PLv57kyzNX/w+EdFR9/vutbaQpmjavPa7toIWC11TGWk/UNrxquLZT3wATLI4sq+y55d0AxFtuWJU6G9ditUoFNBNJkpkZvUggmESWoKsvQTAaITeTJzeV5ksff4jM1HzDX1YVctOzbLtxN5/+l2/yxNefYuzM0KZaV22+2a+BNPuLbtbiY+6EVkv+a+Z72UwdYqNjlKcIzDE2ZCWIprcsWHDselDUMAfu/FNaOu9h6OS/c+7o3wL+QDty7uOMnPk406NfB2Db/p9i24Gfqb/2Wve9hIwkN3fCa1aiXa0fGKUykxfG8FwPPRKaJ/EouH46+1+JY5fruRZXI9V+B4fu/ksURWfPzb/Grht/pWFtkGSVnu3fgyRJJNtvY9eNv4plZmjve8kVx672+OjazrxFm7OAcVMLzVgoRMMqV65ZdG293ctXJtd7xFqTa9OYDUh774tJddzN+IX/XeumbAocyyIQ7CA7c5Z/+OAJZqdL9O3qpZQvEk7G6NrRy44btrH35n60ULCesyFJMkPHzwPwqjffw/ZDu5Ysm7sc1qr/rq9R4zpZb4PgYmzG3ZfLXfqC1SM3+zTlwnmSbbcBvoa6LGvsvfXdxFJXFvm7Xmo7uLtufCd7b/0tAGRF4457P4VZmWJ67BvVx/QlVXD2PI9i7jSR+K6Gt/VqNOM+rXn7Wno6UPXAvCJNgusnGO6me/v3cvHk+5ka/TonHv0thk9/eM3aEwi2Eor4oViRxC6/1lE1tG49UJNwbiTNWAQ1Cs91UTWRjrocYqmDlPLnMCtC4et6CSfjdA++lmC4g69/8rcZPj3G7ESG/j19tHa30daVYGp4lsxsmVe/6U5ufO4hDj5rH7tu2Q34c9LX/vcw06PT7L5tD7HWFMFohEhLAkmW6djeS6w1xa7b9tU3smpryaWMOXPnoVA8umrj1PoYDRvERpvMN+OAWFM78Vz3qsaUFgrWO856mZA3A8OnP0woOkhL13MoFS7y2H1vplxNfm0mihpCD3Xgujal3AUURWf3ze+qGyCXc7V+mpl+GKM8XjeWmsFcFZBrtaURzAyPU8rk6//PjdffbPf9ar+fbft/krbuF3Lqid8nFOnHdfzFtOteqi599ujf8NAXX4PnLq3i9NUwylNMjXz1msdMjX4FWQkSivTVa7Ksx/ko0dlKrDXFC7737iv6gqoH6lWMF0OSpXW9WTZ1wVfA22z9rFm097wIWdE59vD/W+umbHhKmRyheJKWrtvIzw6TGZ9iemiMC8cukGiNcvHUGNMjExy9/wj/9a/fZGo0g1GxyU77c4XnupQyebITM5x56gxmpYISUHFthz2376OcKzGwr49CuuiHESpKfTMh1ppE1QPokRB6JLTopkA5V1hwnGpG7pboiU1AkmW6dvTTv397/f+FBr1ruao3KrVKtbV6A5dPSMFohERbinAsQrKrbV1PWBsJ2yqQnnyA7u3f48ekSyqtXc9BD16SwG32Zz108v08/eA7cB0DWdaWleQ9fuEzHH/410m03Uay/c6mtXG1Y4I91523gKvJZa/HhehK8fv69b+f5SwMJUlhz82/RjS5n9nJB+nf8xYAnn7gFxk9+0kAerZ/H7tueteyK4hfztTIVzh39G+olMY4c+QvcR2j/pxjlzj55B8xdu5TDOx565ITzNeKWqL41z/1wLy+IMky0VSiXsTyWniui+s4qOvYuwHQv387kiwJg2MJBCM9bNv/0xRzpylknlnr5mx4jGKZYnYcVbuU+1QpFDnxyDOkRyfneRpHT13k+ANPM3lxtB7WWBtPrXLFP9dslnKuwDMPH6OQznL0/iOMnx2qC/vUyE3N4lg2RrE8T6r+chbrE83IxRO9sAmoeoAPvfCz3Hh7L1ooyJ7b9yHJ/sJrPbufG4VjWUiSXB/o5y62LMPEKFXITM5SyuY31aJrLVGUICAh4e9IBCM97LjhF+YlwjZbUrB3xw+w++ZfW3Z+SG72CGeOvJfOgVfXVYI2E7UEcs91scoVzLKxoVR/roUkyw2bmJY7FkiyyvYDb6OUP1NXO+sceFVdujMY7qa169krbo9tlwDo3fn93PrCD1MuDJFPH6FQFTBw7DJHHvhFZsa+we6bf31RKd71xtxx2XNdMuNTda/MUljv2v9Dx8+R6GglENKv8OIIrqS950WEYzs4f+If17opGx7bypOdeZJ4y43zHl+oOnht3KuNo4sJmCw2Ti5lHF2LddeKtny0UHBdlVRfb1jlCi95/y3Ad4i1Jjl75CzgT8zrRTO52TiWhSTLBEI6qc42HMchPT6NY9lXlWBsFOFkvF60cKsgySpaIIlp+DG3ufRRJEkhltzX1Ot6nsfpw39GLHWAroFXLzsEynUtTh/+C6LJ/ey44efXXA1lNfANj7VuRWNQNHVNdfFjqYO0dr+Qiyf+lbbu59PZ/4qGnNdzbR7/2pvpGnwt/XveSjF3hlTHnSTb76gfc/boX1MuXOTQPX9DNLG7IdddTaxyZcVjpWs7SLK3+IFrSDAaITM+XfcuinXLtZFklVjqIIWs8GxcL+nJh/Fci7aeFy77tZcLmCiatmrrxoX6SKNqKq3IsyE67OJIskSyqw3LMAlFw6S62lE0ta5/vhWo1R6ZHplgemh81SRy506el3tWNiu2VcSxi1UPBwyf+iBj5z7V9Otmpx/zKzKf+uCKXj9y5qOUixfZdeMvbwlDA6gnEG8GL+d6KMC1bf9PYls5hk59qGHnlGSV3l1vpHPg1eQzx3j6gZ/HsUv12hz59FEmh77Atv1v25CGRo3r2ZRZ717p2qJN0TSscoW4UKhaFC2QwChP4HkbT/Z/PZGZfpRwbCd6qGPxgxdhNTeor+V5uV62xqp3DXBtB6NUwbZsipk8lmHS0tOOrDQmvnkjcb1GxvUYZ7XQlc3O7MT9uHN2Uvbd/vv072l+Fe5wfAcDe3+M2170UQCmx77BI1/+Piwzs+j3VsydYejUB+jd8YZVVaBaa2qFNrVlJOQKrk4w3E3vrjczevbj9RCnRtC74/vRQ+3EkgfYfvDn6/kYpjHLicd+m1jqAJ0Dr2rY9QSNx69/I6FHQtiWJfrbIrR0PQfbzDIz9s21bsqGxnVM1EBsrZvRMHr2DNZzj1cqctJQY0OoC82npkiiBlSKmTzZydm1blJTaPb3vtWMs5XgOhWQJDQ9hefauI5JKNI375hGF7MDCOgtdA28sp5noShBBvf/JFogietYzE48sODrcrOHOfLALxCODq6KUbSe8Dw/wdYolbeEIbwa9O18I+HYICef+EOcOQncjUCSJHq2fw8ARnmSpx/4JTzPZe9tv7skSWfB2lCbkxRVwTZtSrnimhSh3EjEkvtItd/FhWf+bcUqbrKqIKsKoXi0LkqiaNqi80+lNM706NcZv/BZRs5+nIvPvJ/Rc5+q507Vzr0RKBfOzxNn2eiMnrxQzzv0Qyj9nNxwYukG1bJGSj0SxDEvdeKFFoFXWxg2Ku5rPRNrTdXzESRZxiiW/QRKx6kX19uMrNb3eq37bqsTivSD51IpjXLi0XfT0nEP2w789LxjGl3MrlwcZmr4y/Ts+D5UzR90Uh131Z9PTz7M8Ud+nVue/2+EY9uRVQXHshm/8D+cP/Z3RFMH2H/7H9RDv7YKYsHTeGQlwJ5bfpMnvvFjTI98lc6BVzb8GqXCBY4++KtIksShu/8KPdjW8GsIGkdtnrBNG89zUTUdU/S9Renf81YO3/82MjNPkJqTo7RUPNdDD4d8z60eqAtiqJqKpgdwPRfbMCnnMmRnniI9+RCZqYcpF4fq51DUMIoaxjKzDJ36AJ39rySgt5Bou41IfEcj327DKRUuUMydoXfnm9a6KU2jlndYNpau7rgsY8MoVlC1SNU1eWkne7mFRDYrc9U5au93MyWDrjWe61Z3Nja/4bpcQtEBAMqFIQb3/QTBcE/Tr1nKn2dy+Av07HzDgs+3dN7Nzc/7Z8IxXwLasWzOPv1XjF/4b7oGX8v2Az/T8MrmG41IS4LibHatm7Ep8O95F9tqvDhEduYpTjz6bgLBVg7c+afoofaGX0PQHBzLQlYVWrrbmB6e2LSbfo0imtyLLOuU8ueWbWz4+Wi13FQJVdP8OhCmxczYtzl75ENkp48iyzqWmcN1KgTDXSTa72Bg34/T2n0HeEEkyV9TGuVJhs98mMnhL+JYBVz3faQ676Fv15uJpw424+1fN8OnPkwg2EZr13MXfF7RNN+7vYEM34WcBZIsoyzDs7ssY2OuUTH3witd+G3ED/1qPOuVd3D0odMN3z0WzEdWFNSgJj7ny/C8qsvbc2ntft6qXLO16zm0dj3nmsdE4rvwXJtTT/0pWiDJ+MXPMLj/p+mbIxN68NmHOHr/kWY3d11SMzRUPVCvcXD5YijWmqK1t43zhxuXj7AZGapWEW9k/o/r2oye+yQXT/wL8ZYb2Xfb726qWOytgud6TF4cXxeCBusdxy7hugZaILXs13qu77VwHQezrGBUhhg79xmmR+6nmD1Pe/9d3PTct2AaKqFogm3772X8ooIeDlZf76GHg6iaSnp8mnj7PkKxX2HnDe/AdW2mR77Cqaf+mPTEd7jlBf9BODp4RRtK+XOUiyOLzk2NxrYKnDv2PqZGvnSF7PxcGmXsrqZK1dWimGxr6f1pWcaG57rQwJC5mjxqrQDcRtytVvUAgVCQbYMhHrtvfpEkWVFwHWdDvq/1imPZ8yaMrRCetxTSkw+BJJNouwXP85i4+L+YxiwDe97atGs6dglZCS1eF0OSAIlc+gialqB723fPe3qrGhpzqd3TC00e+Zk0hbTwfixGqv0Ohk99oCE5G6aRZnrkK4xf+Azl4gg927+Xwf0/JXI0Nhg1I15WFGRZQpIlEWmwCKX8OQAC+vKNDbhUe8fzXJ742s/heQ6t3fdw4/N+j7te+t1UyjayBK3tYaJRlexBi4e/+jS2ZdcVLF3HIZpKkJu6lOcqyyod/S9HDcQ5/sivc/KJP+SGZ713XuG8Yu4sT37zRwF49qu/vvIPYQWcfupPyUw/yq4bf5WO/saHcV7ORvPQrfnIuRHDjCRZRtUDWOUKtmFy+4tv4mtfOANcsjZVPYCqqZuySvhaIisKrYPdTJ4bAaiH9EmytCk8ZCslPfkQ8dTBeu6EY5ewjObWM3nsvh+io++lbNv/U9c8znNtjPI4xdxp9t762yhbPHRqJQiDenHiLYdQtTiF7ImrFvPzPJfszJMYpTFsu4RZmSYcHUQPd5GbeYpKaYzszBOYlRkkSaal8x723PpbG1reVgCBkI4ky5jlxooHbDYmhv6P00/9CYoWJRTbds1jy8URjPIEZmWKSmmcYLibcGwblpHGtgrk00cxypPc9Lx/IBrfBx48+uUngEvzdjgZo5S5VNy3rb+bzOQMg/t3XtWT29J5Dzc+5x84+tCv8Mxjv8P+O/8YWVbJTD3KySffUz/O85ymy6nXwmBL+fPMjH+TXTf+6rIV6moG8WZnzY2Ny9kIO9XBaBjLMIm0JIgl4zz61afqSeA19QWrXMFaeu6MYBlMD40D8xPGN5rBer3M7SeWmSMz9eg8VadmVzMOxkNYxgwjZz5Ka9fzkJUA4diOK7wcnudx/sQ/kc8c44ZnvZd4y6GmtmurIavKljayL8e2cgyf+iCJlptItN2CJCmYRprs9OMUs6eYHvs6RtkfP2Q5gKa3MFqeADwULYpjFQhG+th106/S0nkPWiCxtm9IcF3UFnGu46BUow2cdby+WOscrlL+HLKss/PQL11VAMEyc4xf+AwXn/mX+mNaIIllZi47UmZw30+SaD1U34X3XBdVDxCKRsjPpK94r9NDYwCLhozGkvvYe8tvcezhd5Kdfoxc+mmGT32QYLgXC0i234FlZAgEW5f1/pdLcTaL57mcOfJe9HA37b0vWfY5rhY+u1qYRhpVizXda7vujI31amjUFnd6JESlUKK1t5MDtw1y+tgYiqqgan4egWOtTC5OsDRqYWmyqvgTR/XzroWtbZYcoMWY208mhj6Ph0tH/8sBcJwKmanHaOm8Z/EQpxVSmJmutYTD978NgHBsJ12Dr8a2ioSjA4DE0OkPUsyeZPuBnxGGRhPYCvf6cjhw559w7OH/x9GHfoV4yyESbbcxevYTOHaRQLCdZPsddPa/gmhyHxISkqziOBUqxVFC0QE810KSlKvGW29FNsIG4GLUxFvUgLquw0/WWiwi1XEX6YkHOPn47zE18hV2HPw5guFuwM9JuPjMvzF2/r8Bl96dftHLgJ5CUcPYVp5y4SKa3kIgmAJUZFnFdeaPUbZhUqjO23okhFFc2a5sJOHnZg2f/giFzHF6d74RPdTF2af/P/KZ4xx/5De46bn/sNKPYsnkZo+Qmz3MgTv/dMXjxlrdkzVPVig6yKF7/gotkGzatSTP87zFDsrlciQSCe562edQtcZr9V9OKB5FkuXrqm7aSBKdrWQnZlA0DT0SwqoWqZNkGcey6rrDG31A3kjUQqckSUYNqNimjRpQ6y7JpQxgm+E781ybx+57M4nWm9l9868BMDn0BU4f+Qtue+GHG1LB9GqkJx/mxGO/hetUaOu5F9vKkZl6GEUN41S10eMtN9G/+4dItN3WNMNHIJiL4xikJx/k3NG/wTbztPe9lIE9b236LudWYKOOmbXNqVrNjfVscKw1nucxM/5Nzh39WyxjFlkNIUsqrmvheS59O99Iou2WdbF5NDP2LS6c+CcsM8OeW97NsYffOe/521/8MfRQZ1PbcPrwX5CZepjbXvSfdRWtjUIhe4qnvvUTAGh6K+09L6Jv95uXbHTYVpGHvvgqstks8Xj8mseuO88GUM9zkFUFSZLXbGCQZJloKoEkyWihoO/uUhQsIJpKYJTKVUNjYya3b2RqoVOy6u9a6eEQZtmYN5HUqsVerXBaOBlb852k62V24gGM8gTd27+3/lh738uIpQ7WDY14ewv5mUzD79FUx53cce8neOax32V24n7ufsX/1ZPGjfI4tlUQse6rxEZdBDYDRdFp634+rV3PEwZug5FkCUUL4FSTeTcKiqYRDPtVxCXZEeGH10CSJNq6n0+q/U6mRr5cVaey8Fybjv5XEAx3Let8zfysW7ufS0vn3ThOmYmh/wP8EKpy4SJGeYKxc/9Fx8ArFlStagSZ6ceZuPhZBvf9+IYzNACiid10b/tuxs7/F6oWY2Loc7iuwc5Dv9Twa61LY6OGf4M6hOLRNUm0DsWj7L1tB5mZIuV8oRpvqBEEctOzaHqAQEjHMswtkeCzHqkNYkapjKYHsE27vvCqeZ0uRwsF6RjoYnp4AlhdCblGMzH0OaKJfUQTewBfqtMsTxKK9tePmavo0WhULUYg2IaihjCNWQJ6C0Dd9b6abJVEu4XYSAu/RlHL2bqaOIQwNFbGtebbuZ+zFgpumGK1fiSCVJ0bPGFoLAFFDdE1+NrrPk+zP2tJVlHlGL07vp/eHd8PwMiZjzJy9hOMX/xfxi78N/tu+915BWcbxfDpDxNN7mt6jmQz2XbgZygXh8mnjxFJ7GFm/NvsuOEXGp5cvyFMMduy2XHznqadX1aVarG4+Qzs62f0/DRDJy7g2A6KppEenSQ/k653oHKusGUXOOsJ13YwimUcy5pTUNFb8HtVFIVKsYKs+M9thMlyIYzKNOnJh+kYeEX9sQsn/omnH3wHrrPwPbmUApzLpb3vpeC5HP722/G8tZvERT/cWvjeza2Ro7WaLLax59p+3pxVrtSVF6E5Y0sjkGTZzxNIZyllcht2vBcsnd6dP8CdL/kUd9z7SWKpg5w58l5ct7H5tJaZIzv9BJ39r2i66lUzkWWVvbf9LqHoALmZJ7GMWY585+cZOvkBHLtxKkfrc3S4DKtcYXY8veDCsRHUJis9EqpfQwsFOXfkLGOnh/zwHMO8YpBaKC9A0bSmtHG9EWm5pNKyXieZ2kLk8u/ErFQoZvLrtt1LwahMc/GZf0OWVdp7XlR/vHfHG9h986/NS1STZJlg1M+1asYOeLLtVrq2fRemMcMGGVIEAsEy8atCX9m/bcMkGI3Ux5baeLtexteaoIgkyVtmfhb4KGqIwX0/gVGeID97ZT2nROfK87iK2ZOAS6L1luto4fpAVcPc8Kz31o2mfPooF0/+G2ef/quGXWN9jAZLIDM+RSDox+ArmlZNEG5c8yVJxq26V7VQkGjqUrLLchZoW2XXpDibrRtm6zGEY161+8t0cV3boVIorhsBgpUwcvrDTA59no7+V9ZrawAEgq0kWm+ed6znuk2tuF7MnWb49Ifp7H/Vug9dUTStnssjEAiWzrU8SHPHl9ocKCtKfa5eD0iyhKYH1k17BKtDNLEHVYsxPXYfNT0kVQ/QPtiDHg6iR0LLPqfnuUyNfhUArRo6vNFR1BDbDrx93mOZ6ccwq/W6PM9leuwbpCcfxluBl2hd52xcjl2tOF4bzFS9cYlqjmXhWBapng4GdncTigR49KtPrcuF9HphPYcvzP3eUl3tzAz72vpaKIjnuhs+5EZWguihLnYe+sX6Y6X8OU4/9WfsOPSOVUvMtu0SJx77HcLRAbYfeNuqXPN6qPXzqyVUX48Uo0Cw2VnpxpuiaWh6AGuBCIHVwLWdumpkKB7FsSzRz7cIkiTTt+sHOX/87wGZ7u3fTSywC0VRKGYLdVlkz3OZGvkKM2PfYHDfTxKOXUoqt60CE0OfZ/z8/2BUJvFc/x5u63nBpipS2977Es4d/Rt23/zrBILtHHv4nTz6ldcTa7kBxy5VvTmw44ZfoHvbdy/r3BvL2DBMevYMMnryAgCJ9pb6IrIRqHoAWZaZGJolPTG94RekAp+594hVrtRzdDQ9sGEnHDWQwLZyeJ5X9yaEIv2EYtuWFT+6EqUQz/MoZI4zNfJlpka/huuY3Pzcf0beQINurWaOHvalrGtx6hv1fhAI1jM1I19WlTUVcnAsi+4dvZhlk9xsti7uomjqhlPYEiyd3p1vQJJVLhz/R8Yv/Dd6qJNQpJ94642kOu4mGOnl1BN/yOzE/QCEooP07/lhFEUnN3uEE4/+FraVp63nRfQkvxdJCRCK9JNovWmN31ljqRlRsqKTbLuFO+79JFPDXyKXPoYsB9h+4Gc5d+xvCUW3LfvcG8rYAEiPzwDNyY3wXI9COotjO8LQaADrVeWptsPVDFZLgjSa2OvvNORO1ZWoSoWL7L7pnYu8cj5XMzRKhYucP/Z3KGoUTU/gWAWMyjRmZQazMuUXSdPb6Oh7OV0DryYU7bvu97TatPV1IssSjuPiud6a7boKBFuFmocB1mZ+cG2H4WfOo2gakUTMFwvB38hcbNzWQkGsckXITG9QerZ/L50DryI7/TjZmacoF4cYOfOxau5jAElW2XHDO5ga+TwjZz7C1MiXaOm8h4mLnyOWuoE9t/wmeqi9qW1s7evCtiyyEzNNvc5C2Gae4dMfAiCW3A+AFkjQs+P1dHsujl1m6NR/oKhh4qmDyz7/hjM2rGoyWjQVZ3pobMGd2ZXqOtd2XwQrpzYQ18Ld1uvA7LluU3axa++92e853nIDshwgM/UI0cQeTCPNke/8HDc99x8JRRZf+MfbWwgEdaaHxhZ83jazpCcfJBjpQ5JUVC1CINhGOLaNgN5GNLmHROvNG1qFY+SZ8/VaOrKqoHpqPX7XKJbRI6ENnddzOevV+BdsTdbqXvRcD6tcoQiE4xFSXa24tsvs2OQ11w01r3hNdET0pY2HogRp6byHls57AHBdi9zMU2RnD9Pe8yLCsW10b3sd5cIQF0/+OxND/0fPjjcwsPdHkOXmiws0MlJnuRx54Ocp5c/Rt/stBIKXjCrXMXj6wV8mn34agL7db1lRpfQNZ2zYVbdnMBomFI9SKZSuOGY95xJsdi7Jzs7/vVTWq3GyHFaj/VPDX8Z1TSLxXQDIkuq7fdXIoq9t7etidnTymseEY9sA6Nv1Zjr7X3HNYzcynuuSn0nXKwxLkkxLTxszI/5CIpyMbxqDw3XEuCgQeK5bL9Kbnahw8wtvJj1VwPPar7rYq81LtbWFMDQ2B7KskWy/nWT77fMeD0X72Xvru+eFKa81zQ4/tIwMAOXCRYrZk0STewFfACaffpqBPT9KOLaNVNVQWy4bUpahrb+7rjAUjIbXuDWCpSDJ8jxlkoXCmGRV2fCGxmoxcuY/ae1+Yb1QkRrwixoF9NSir50ZHkcPh7j39c+ifbBnnqR07XvKVWUC4y2HmvMG1hluNXSyUihSSOcJBIOY5UpTVbxWm1rfarSSn0Cw0bDKlXp/ePK+J7nw9GkK6Wy9b9QSyYPRCMFohHAydlXpX8HmZSWGRrPukWYZGpbpb6bd/Px/Zdv+t1HMneHYI+/Ctvw8xvTUIwC0dj+P1u7nIcsr81FsOM8GwPTQWD1nY/DgdizDYuj4uTVu1fqn1gkasaBfyAPhGwvevMdrbmfPdXFcF0XTUEP6giFMwiO1NBy7TLk4TO/ON9YfG7/wWZJttxKM9CzpHJVCka9+6iE81yM3e4xS/hytnc9BDcRwXLdeFLBSHFlSWNZmYm7F9VqfibWmKGZzG/oerfXZWqjf3McEgvXASkOgG4FRLKNoGrtu2U0sGWLbYITHHxknENQYOjm8rvu+COtqDOnJh5gc/gLBcC8tnc8mmtyH65TJzT6NacygBnQSrc9CVedvcvubdCrheJT2vnaGT15c92IjlpnhzJG/YmbsPg4+671E4jvo7H8l4fgOjj30q6QnHyIY6WX41Afp2/WD9WiHlbIhjY255Gby2FZjK0NuVhq5qJh7rstdzHO5/LG5eTFiobMySvlzgEckvhPw1aHOHv0rth/8Wbojr1vyeVzbIZ85weFvvx1wOSO/l0h8F2Z5CtOYJhQdJBjpbc6b2CDU7s9SroBrO2y7cTeFdIHsdBqrXFnj1i2PuX1N9DvBeqImOb3WC3pND5CbLZBqizA0XKKUK6MFVEqZ/BXHNnLz7noRhkZjmB79GtOj96EFkgyf/hABvQ3TnIU5tbrmyr7G21vITc0Sb08RTcawTIvsdA5nHRumNU49+Sf1PIzTT/0JlplFD3VimVlkWSeWOsDRB3+FSHw3/Xt++Lqvt2GNDceyCEYjmBVj3k6kwKfZC/laRdZaHPi8InpLvK4kS3hrP05vOIq5MyDJ9Z0GSZK462WfXZHet21mAZcbn/0+crNHKObOkmy/g3B0kNbu56/YZbrZqE3m5w+fAnxlmrWU8GwUterKt734Zg5/+9i6340TbE7W6r6TZBlZ8aXQo6k4rd0tlAsVMrMlxs6Nk5/JMHlx4TltPRgZgsYSTe5ncviL7L31t/E8h/TUwwQjvSRabyYUGeCRr3wflpmtH19be+am0siKQjlXxCit/zF0Zvx+MtOPMrjvJ4gl93Ps4XfR1v0CJoe/gCRreK7FY197I2ogwYG7/qQhyfENCy5bi1hGo1TGtmw6tm/t3deFaPZA6Ll+JU5FU5FkCVmZH/cfb29Bj4Tm3RdzcwOAuqrHVqro3Ih+UsieRA92cP74PzA9+nUq5Uny6aMrOlfNczE99g0cu4znWQzsfgvtvS8WhsY1sMoVbMNE1QNNuX+1ULAp8t4L4doOh799jJd+3+0kOltX5ZqCxRH5AauDGlBRNRVZlhk7N0ZLZ4JitoQkyehhvxaPoml+baYNMFeJ+2bldA2+hljqBk4feS+JttvYfuDtdA++jnB0EM9zkCQZx7oyj89zXdKjk1QKxXqo6lqx2D1aKY7yzOO/Q7LtNjoHXk285RB3veyz9c3Lg3f9Ge2999K/563c9sIPNyyMumGriYXi913bmReD2ch4TD+JS2LvbTs5f3xEhOSsAeF4lHKhiKz4uRqyolS9FR5GqUwgGMStygyCX8kTrgyrkmRpTWN1V5NGeHMKmWPYdoGx8//F2Pn/ItZyI/nZw9zzqvuWndAWDPfSvf17GT37ScBvWLL9zk2tQNVIbMMk1ppC1dR6YcBGUNPzXy3MssHQxTy3P28v9/3XQ8iKsuG9NhudrTyfreZ8YBTL9QVae18HLa0hAgE/GTwHWKaJGlDXRZjXUrjafSPWSIsjSQp9u36Q44+8i0pplNCcMOLRsx/DMtIrVmNaLWrrrVpdmLk4dpnTh/8MLZBk762/jaL6Uu8z49/k/PF/pHfnm0i03kyi9eaGt6tpW5e1Tjm3czayo/qdRub88RFcxxGdaJWpGRaqpmEZJpFkjHKh5FeJVRS/QJrt+EZIdeK4Wt2N2qImnIwjyRKlTH7Tfp+e613XoG/bJYq5c8iySiDYgW1mSLbdxv7bfm9lyhmSRGf/K5ka/jK2lSMY6UMPdayobVuV/Eya1r4uXMdpaDjIavYBSZY48u2jeJ4v4iAMDcFaslqL+lofs8oVZobHyU7NMjMyjazKeK5HsZqrsRlyImrvtZYfI1iYWOoAshJk5PRH2HXTr+J5HsOnPsjFk/9GOLaTZNstSzqPrCoomtbw3L6ligFcft1S/hwnn/wjyoUh9t/xnjmGxrc4+cQf0NbzQgb3/XhD2zqXDR8nkZ2cIRSPrnUzthye51JIZ+vhVLmp2fpOrOP6CfsuTnXh4qBHQliGec0d01Imh6JpBEL6pq3ifr0LSLsaL+q6JrKi47omLZ33oOlJysWReTsxSyE7/QTHHn4XoWgfB+76U6KJvetGV3wjMTM8zrYbdzNyamjDJY6Dv7iTZI9gNIxZNpAVBTWkY5aNTWv4C9Yva7ULL8kypVyBSDKGUSojyZtvLJxraAhvx5VogTg7Dv4cpw//GR4eljFLevJBAFo6n7Xk87i20xSjebmGr23muXjqPxg//1/o4R4O3fPXRBO7AcjOPMWJR99NqvMedt/0rmr0SXPY0MZGzbvhmLboNKvMQp1oro6/H7fIpVA616t3Pi0UrHs6LsexLDzP9UOwHKduzIjv1kcPdbD94M8AUMqfxzLTROI7yKePcfj+t3Ponr8m3nLjks83Nfo1AqEODj3771aUYC64xMipIZIdLUxdGG3oeVdrbPNct14k1XNdXMdBD4cwSmXR/wSrSu1+W+3w2tpGQW5qFlUPoGpaPeG3Frq9EUKploro1wvT0f9KSoULpCcfwrGLbDvwdnp3fD+SIuM5G+Mzy80eYWrkq0yNfgXPdejf8yP07vh+ZCVApTTG2LlPM37hfwBQ1fCKqoIvh4YbG6u96PdcF89zUfXAhtxR3Iws9P07llWPIXRtp16UceHXe1QKxaobUq0aHc1s8dqwkr4yO/EA547+DQCyEiTZdhuSpBBLHWDvrb9NJLFnWecrF4eIJnYJQ6MBWOUKqfYExWyhoVXHV3s8Bf/e1MMhND2wIdRVBJuLmpdc0wMY9trcf7ZhzvOu1zbQBJsfSZLYfuDtbD/w9nmPN8PQWCi34nrwPIehkx9g6NR/oIe66Ox/Jb07f4CA3gJApTTOE19/K7Ki0zn4GlQtTqr9joZd/2o03NhYbGJsRrygUSwLBYZ1jB+icamI2LXcgLXjagUCbdtEVhVUPYDnepsqP2cl76OQOYGmt7Bt/0+RnnyQzv5XAVApjVHIPANAW88Lr3kOy8yRnnwQ1zHJp48yuLd5cZpbjbNHztTloBtJoyekpSDJEsVsjmA0TKVQ2jT9TnAlNQ9CbQNk7nyqaOqqh7R6rkuisxVV05AkGbNS2VQeBYGgxvWM65dvWNpmnpNP/AHpqYcZ2Ptj9O168xWhUeMXPoMkq9z2oo+gaquXgrDqYVTNSkySFQUUZVMkcm1GPNdFlqX6xHW1gkhetcq4n6iq1hPMZVlCkqpubMfBMsxNM/ksx8NRyD5DLLmfjr6X0dH3svrjZmUGDxdpEbnambFvcebIe7HMNABaIEmHUJ5qGM3yBFjlCsFohErhStnFZmFbNq7tUM4VaOvvJj+bwSiWkVUFPRxqqPqWYO2pjbue6xsYkWSM/EymGj60+mHKrd2thCI6o64rvGtrgAhNX//MK9TqORx/9Dco5c9z8Fl/RrLt9iuONyrTjJ3/NN2D37WqhgassrFxrZv3em9sPRJa1YlYsHxs008cr3kpfO+FO2/X7NKE5+FJ/jGaHsAyTMBBlVUkSSYQDGJbVn0X2XO9DTsw1orDLdZ+szJDPn2M3h1vuOK5eMsNxFtuuObry4UhTjz2W7R03sOOQ++oulUlkRDeQDQ90LRFuGWYq2Zw1LTia/fm9NAYQL32Ry23AyDWmiI/k256mwTNYa4XQ5JkQvEQtuWP1amudspVr9ZqejeC0QgAlmETioYwkzGKs9lFXiVoJBt1Pl0O66kK/PUycvYT5Gaf5oa7/5JE66W8zXoOLQ7nj/0dshygb/ebV719K449UvWlJ5Ms5QtdyZc9t5hfKZNraia94PqQZNn3UKgKgVAQPRJCrkrnzg2xAn/C81wXx7Lq3otIIkYoGq6fo2aEBILB6mulDRtKZ5Ur9bCBq1EpjnLkOz+HooZo73vJFc+nJx8inzlxzetMDn8RWdbYc+u70YNtvqdIGBorZqHiSTWpzGZQ8+hdXhyzWSiq4ieJR0L1azqWhRpQ5+V2KNqG1hnZ8khzvMbBWJienb1EEjFKuSKVqjhAM0IDr4VlmJRyZWRVRlFkZEneEAX1BGvLctcAa12Ar5EYpXFkRePCiX/i+CO/wdTIV/E8v+/OjN/PE1//YaZHv862A29D1WJL7k81z+Zy1vwLseJZYjm7HJd/mVfzYixXeWLy3MiSjxWsLZ7r1mMTHcvyK4frAZRaTY764sUPk6ppSTuWhWUoaLrmyxBWb4+59TzmXmMjk5tK13euazkrvgCCx9GH30mlNEpL57PJTj+B0hVGCyTqrx0+/SGCkT5iyX1XPb8e6sB1TU48+m523/xr9YQxwfKo5U8sFGvbzDBOz3VRQ/qqaeQbxTLBaATLMAkEg/X70jbtuofDsSwy41P116x2qJfg+pi7ONMjIWLJOLnZPIV0FtdxKM+5n1czrMZ1HIyKQWYyR3tfC/l0YdOEzW5Earm211qjrUVe2eWs9hpgqTUvVoP+PT+MrOhYRhqjPMbJJ36fU0/9MZKk4jplEm23sffW3yMS3wEsPVek9pler2dT8jzPW+ygXC5HIpHgrpd9DlWLXNcFoXmDlhYKXuHuFXGH64/aLqkkyeiRUP3xSrUaues4aHoA27SrhoeKoir13TdJlutGRqM6wnpjbqKm57pMDn+J9ORDzIx9A8+z6dv9Fgb3/mj9eM9zcOwSqhZb8Hy1SSI9+TCnnnwPlpUjEttBe9/L6N3x+tV6W5uW2i5RsyfbWgjiak1wbf3dSLJEZnL2qnLViqbVNwkWWxAqmlavxixYH9S8U7UxVgmo66Kwalt/Ny2dSQJBjexMnqmhyaYkios1gmAtaLahUqmcYXbsKTzPJhzdRrL9joZHMthWkYe++Cqy2SzxePyax66J//t6OnYtpn+hAaett4PpkcnraZpgFaipnkiKv3uqBlQUTSOSiGNWKjiWv3NaW8SYZQPHdlBU8BxwqoaF6zibNnROVhRcqCsBtffey+zE/XieTdfgd9G/y4+5dF0LszyFHu6+qqEBl+qipDru5Obnv5/Z8W9z4cQ/k554QBgbDWA1dvRkVcGxbF8MY5Wo5WrUquEC9ZCaWjFVSZauiKevudwdy5433te8lbVjapsES5l4a7vwiqZecd65zPW6CBantkFnG9WFd2HtF96x1hSO4+B6HpWyieteyt9rtBRuowwNYbQIlkMjxqdreZqCwZ30bN+5rPM18x5e0Uqtrb/7+i56HTHHjmWh6YF57l9ZVZBkmWR7/IodbtH51ye1OGDPc7FNG8swsS2LYDRMKB6tFwCshRK5joNZNvzjqj+1ndbNuKjw72l/tzjWmiQ99SAzY99gzy3vZuehX0Su1sVw7CJPfOOt9Qqn1zpfDS0QR1aC2FZ+wfwPwfph7jjn9wd31e/3UDxaD3lUAyqqHkBWFMKxCHo4SCCoE07G64t88D2NSvWe0yMhtFDwinjquWP13Pd0tfmhFl99LTGFmrT2ZhwTVoP1MF/6+X0ysVSMWDJEW2eMWMq/11x30UCMNWM9fHabkdrGo+BKGu3lW+49vJy1/IqMjez0ypRHapPNSj8gtWpk2Ob8XS3P9VA0lexMnt237t2wicJbDc916waDbZiUcwWMYjWvw3HqVntNa12St04ys7+g8nBdD8dxGDv3KeItN9DRP9840AJJbrj7LxcNb6z1uZnx+3n8vrdw6sk/JNVx16I1OQRrx0K7TGsx8dbUtWRVoX/fIP17B3Asi+mhMdKjk5RzRSqF4hWFOo2in1xslg1sw6x7Qhaj5vmcO5HN9axcC7Hg23jYVp7xC5/FmeOxCAR1ugdS7NoZQ1EkIlEdTdd8UZHrTFQVbCycOaqTsqqghYL18UCs9ZpDLSl8MZazll9RGNVKQwaudyKo7YRdfpbaznchnWdqaEJMOBuQ2ndWKRSRZJlASPdrc9SLTUloWnDL6K3XPg9/N9ejkHmGgX0/NK/A1uzEd4jEdxNLHVjSOY3yFCcf/z1iLTew59Z3XzOZXLD2XE1EYy2SMM2ygWzajJwark9C8fYWSrkCnucSjEauqJpel1ys9uPl5GlcXq3Zn9REgnCzWe1QIMcu89AXXwPAuaN/TTDSQ7zlBlp6/pxKyeL0mTzToxmMiolRqhBNJSiks9jGqjVRsA6o3ZO1iIdkVzvFbF54MJtEM8aADWkWLvRBeK5HIZ29ovqpYOPhuW49OdyxrPqOaaVQ3HKGpG2YGMUygWAS2ypWvXgahjHMmSPvZeLiZ5d8rosn/w1ZDbLvtt8VhsYGxSpX6h7e1aS2oVPOFdh/+y4iLQnyM5n6/Xm5oVF7TY2rJZevFDHGN4fVHl+LuVMA9O/+YRKtt1DKn2f8wmcxK0UyM0VmxnNkp7M4lkMoEsaxHQLBIMmudlQ9QCgerdfkEGwdMuNTa658JVgey/ZsrLckqLkJMn6ojZiENgMi7voSvsxvDLOSrn8mkfgO7n71/2CVF1fhKubOMnruk0wOfYEdN/z8qlcOFVw/clUpaK08G3BpIfrYVx5fk+vPZT3NQYKVo2q+fPfQqf+oP7br5rcRiScpF8sYpQr5mUxdLatWV8l1HBLtLciKTHp8uu4NFypngo3OcktAbBSWbWwsNMgvpwpjo5VCvGrCmOe6SJpaD7nxxFwk2ODMHXQ0LU4pdxHP85AkCceyQYLczJMk2m6pv0bRND/xvtoXp0e/zjOP/y6BYCuD+36CroHXrMl7EawcPRLyvVnVHIjVYr1tLAlWl9WorhyODXL7vR9BUSUgQDCWIhRuRZIlZFdGVhQCIV8MI5yI+fU3ihVfAS2T9xUJZQnPdTGK5XVV92CjU8uxmpuztRkXwesN13Y25X3cEDeA57pLriI7N9mnEUiyVDdgAqEgwVi4boAIBOuZpSg5qHoAWVXoGHgFudmnmBj6HOD3uYkLX+DpB98xL7HSsaxL+R6ex5kjf0FL57O57UUfpW/Xm5Dkxqhdu65FPn0Uz7Ubcj7BwmihIEaxTKVQJBDSV7WejDA0tjaXV1duZNRAbeyTVYVwbJBgZJBYyyChcCuRRJTte7vYsb+bRFuCWEuSeFuKeEvcVyf0XL8QbHWsm7sA3mwLtLWkUihtmRzJ9cZmvI8bVmdjuRXFG1Vtcm7iYK0onJgkBRuBxXaJaslwWihIR/+9nD/+D2SnH6dr4NUAtPe8iGC4C9e1wJFQlOC810uSRDDS54ffXKeRUcydYejkf5CZfox4600Y5QlKuTOEogPsPPRLJFpvvq7zL5X1UKW22dSqx8dakxQz+XrBwNoOY7MJRiM4jrPpP2fB0pib6N8ob1dNcaw2f8uqX8zVBnKzWU4fcwnHwmSns9iGhSRLVArl+uaitcmKuK43amPQ3I3b6/FqdGzvZXZ0atMV311rNpL3ec0SHBabyFayi+JX1hU7rYK1YSX3rKJpi3o4FEXBrExglMZJtt8x53oq8ZYbOfXEH/LkN38cz3OwzTz59FFcxx/UW7ueQ3rqYYq5s8tuW42Jof/jyW/+GDPj38Sxi6QnvoNRniDRdhvlwkUunvz3FZ97uWz2BXD//u310JHagsoqV5r6vucmnEuyjG1ZpLpaRf6bAJjv4WrkwuZyAQGzbFDOFShlcsyOTjF0/Dy5qTSlXIFSroBlmJhlg0qhKMJ5mozneg3duJ08N1IfT1Q9UN9AEVwfG8XQgBUYG+HktUuSL5Wlaq7XkGR50Rt0I33wgvXH3AXXSljJ/ed57qJhf5VCEUVpIZLYw+TQF0lPPoznXXrNzht/mf23/z6SpJBLH+Hw/T9DMXuKk0/8EUOnPozrVHjymz9KIXtq2e0DqBSH638rqq/84lgFsjNPEE3sY+ehd6zovEtlsy16r1YvonvXAJZh1wtYGqVy093pkiyjVAtIAujhEKqmkZ2cFeOpYFWZe7/Z1TCp2o9tmFQKRWForBLXKh660vG4tmFSK8oL/lgYb29B1QPokdDKGivYECw7tmIhicOVsFgs4OWxosmuNsyKsegOn5ggBStB1QPYhokWCtZlPldjUvNcD1UPLCoNKisKNz33r3nqWz/PsYffSTDcz7YDP0VL57PRQx314xQtSiSxj8Pf+Zl5r5ckDdeZL04vqwqyoizq2h7Y+6PISohAsJX23nvJzjyELEWIJvehqI2dIGpu4bnJiJutTy/0PQ8c3MnY2RFUTa2GL8yvM9Esaom1wWiESqGIWamg6QGh6iMQCBakEeNx7RyOZZGbmq3+7Rsx4WSccq6w6cb9rc6abRkupwqu57rkptIYxTJaKLjk6oYCwWLIquLHDjt+DLFVrqBUq5NqoSCKpqFHQk2731Q9gGNZaHrgmn3Cc10kgoSi3QBUSkOcePQ3Ofztt1EujNSPu3jinykXLiDLOn27fpCbnvOPBMO9eJ6FbeXnndO1nSXF0EqSQv/uH6Sz/xXIskaq/Tkk2m5puKEB1IUmlmLobRZXvBYKMjU0gWNZVAqlNZlkK4Ui4H/uwtAQCASrTW3cK2VyeK57haejNldvVZYScr2eWZc5G4qmzSvUU/uA9UgI13bqIVi1x7fyDSi4PlzbQVb8Hf6a8pNRLF+qVu841fsx3JTr+4oqHo6ztKJne2/7bTr6X17/v5A9weNffzOPfOX1nH7qzyhkTuI6FQb3/QSD+36caHIvt77wQ6Ta7+LM4b/AKE805X0sl6sZVstJINzo+RuyqtC1o9/3LpTKuLazrnbzxLgqEAjWCrNsEG9vYeDgzrqYQM0IWWrI1WYawxzL2tAhhOvym/B3+Ir1/z3XQ1YVHNPG89y65F0kEa/uOktIsryhrT7B2uJYNla5Mi90p1atea7yiaoHGnZNP2TII5pK1P9fFFdm722/we5bfhVJunS/m8YME0Ofw3UNosl9dA1eqqchSRI7b/xlPBwe+9qbOPXkH1HMnZ6X97HabDZpv6XkstU8srX8s0gizvTIBI5lr8tJZD0ZPgKBYOtQm2dzU7NMnB8lnIzRtaO/bmS4rrek+XIjj2ErWc+uZ29/w6RvL5fgarQkVy2mPZKIUymVkVWFQjpLS08HtmVhlv149LUKQxBsXOYufGu5ApIs13MpagOcFgriWFbD7u3aOSrVXe3l0Nn/GuKthzh35B+YnfgOwXAPsdRB4i2H6Oh7+Typ2we/8CoG9ryVW17wAYZO/gfjF/6XyeEvoqgRwrHtxFtu9PMyGlSDYytiliv079/O0PFzVz2m9n3XpGUL6awYqwQCgeAy5nq4jWKZeFuKfCZHIBish9qaFaNhOcRrjaJphONRitlcfS2wkg2o9eztl7wlbG/mcjkSiQR3vexzqFpkscMbTq0qsl8p1CMYDdetPrNsoOkBJFnyY9Cr0re1BWQt2VIguBbBaASz4nfUmrEhyRKRRLyu1FPKFaryyo3dlY+0JHBMG8fxcyiWer/W+kU+/TRDJz/C7MT9qIE4seR+guEeEm230NJxN5PDXyKa3Ise6uShL/o1OkLRASwjg23l0AIpnvWq/8a1NkYxzPVeyTYUj15REyOcjGNWJ4JaYbJmvIeNpLsuuJJanxbfoWCzs9QK9aoeQFEVHNuplzZQ9QCyLC07v2zuZqKs+GvIRm4gNpJLtU6ubJceCS363pvtAACwrSIPffFVZLNZ4vFre/c3xFamY1komuYbG9Il95ks+b/NcqVelbz25az3BYlgfWGUynVjFvzK9JLk1xwIhHRc2++ktfuskZhlA0VZvsu0ZvREEwfYf8cfUC4OM3Hx85QK50lPPcLY+U+j6SkisZ2kpx4hO/MEAIm228injyJJCqHoAHtvffc1DY311pfWU1sWYqHie6u1A7feJkyBQCBYiMXGKkXT6rLHnqtV8ydVHMte1qbcXCRJJpyMzKthVGvLYovx1TZIPNerpgjMn38VTVuSkdVsQ2O5bAhjA6qLPMe3aI1imVRXG5IsoYeD6GEdperpyE5nsAxr1artCjYHC0mNBkI6tmU3PTTPc12CiRjFbH7xg69BKNLHtv0/Wf+/kD3F9OjXqBRHsMw07b330tH3UqKJPUs+p6oH0PTAFf2pUYPXVqgILhAslc2WyyQQrJS5faH29/VWIHcsi1Jmvifjcg9CLVwa5kfGNGsNcLXNvKvJn69kjFhrQwM2kLFR+7CscgU9EiIzOYMeCbFt/wCu6zFyepSW7lbMsoHneiiaSjSVID+Tqd5M7nXfqILNz9zF9WoarM3wmEQTu4kmdl/XOfyK0nZ9l6lGowYvYWgINitXW0TMTWxdD4sAwepTq2vTTNbDbvbVuHyx3yxv9bUW8jUuf/7yOSkUj2KUyvWoh4U+U1lVkCR5RYbAevfUN4oNY2zMpVZvw3M9zh+/SCCok+xIMXlxArNs1MNhLNMkkoxVEzG9dRcOIlhfxFpT2JY1T31qNXAsG0mWUBQFax1NDpLsD56yoogdV4FgmVxtrlmvC0DB6tFsQwPW931WCw+C5i62a/kZK/0sJFmubzrKqkIwGkGSpfpjmh7AsR1UTcNxHNSAWl+D1q5/LbbSmrQhxsZaWNBWuVK3QItAenTyijbV6iWEk3Fc26knAK9HttJNtx6RZNlXOZuTt9FM5n7fiqZiW36C+HrDtVenkrpAsFo0a76qnXehxFcxvgsEl5jbF+ZKvC63jyylL19PX7/cA2IZZn3jTdMDuK6Hoip4nlvPu0x2tWGUKlfk6c1NTr8UmuWtaw9UI2lInY31+EHNbVMpk8OsVFZ9sF9OQRnXduqdrpG1HARLo1ZXwyiWmxLSdDlz70XP9XBMG1VbH47GWi2I9divBYLrpVn39dzYbs915xWuFIaGQHAlkiwjSfKKN7VWe47yE9M9XNvBKJaxyhUc20GSLtV5K+eK7LhhG8FoBFlVkFXFr/5dLRysaCqSLNcfq3lBNjvrsqhfo7ANsz7g1yzK1WS5HaHW2ebmllytsIusKvVFoaCxNHsAW8iYrCWjryW1wpiyoghDQyC4TpazaSE2mAQbgcXWG4s9X1t81/Bct6khunMLqTYC33MpoWgaWihYzWW0sS0Lo1jGcfxN4wvHh4im4ujhEJoeuLSRrGnokRCqHsDzXDzPRZK2xhpufWylNpFmJLWuJlcL6XFt54qk3aVwuTt/JecQXB+XCxU4lkV+JrNmOxy1miJQM3jFLqxAcL0sZ74R4iWCjcD1hiyt9qbv3LDGesmE68xBrM2RtfoctRzhmkHhGyMqRskP2w8Eg34eaNWLYRsmru3Ula4kuflh2+shUmFrmFSbhJo3o8ZKOkwoHq3/LckyO2/aRTC6+oUatxKSLKOFgtd8XtHUVckVWejanutu6NyMeHvLWjdBIBAIBEtgtRe9tbDG2k8jw6Rrc6djWfWfUiZPfibjh+47fp6H57l+0V7LvkKAZjU+j2tdY264ZzNZE8/GQtr6S60mudWoxf5qegAloNbjBSVZwrZsPNdFrd4stmXhOlcuGms60qF4tCoLrFWtcolCroTjXJ9ig+Da1PJBLqd2z6t6YM0++83wneemZte6CQKBQCDYADRrzqutuy733NhVD8jca6+naJLVasuaGBsLLbw2w6KnGcwNcdECAfr39GCUTMrFCpIsU8qV6BxoIzdbIDudxSwb2JaF53oEY2HMskEkEaOcL6AoCpFEFLkjhaqppMdnKRfKJDtamBmZWLCAzEZlIxivwWgYSZYxy/4OyHpuq0AgEAgEW4m564irbcjOfVzVAyiqgut6uPW6HB7g4lQ3h7cqmz5nY6NTu8klWUJRFWYnsmi6r2JQzBYxShVGz01Uj/UIRsOomoplmqiaRjAcQlZkgmG/4nprV5KZ8QzgJyUrmoJRqswL4dkMXg6piRK2jfh8aiFxtdjNjRrCJBAIBIKtRS0/YaPPW4vN5ZcXHlzoeEmWkBU/ukSrCj04tnmpCKDn4lrehl9TXS/C2GgCzdBU91yv7rVQNa1afM7CtR1irXHS4zPIqkI0GiKSCGMZvrJRKKojSRJmxSI3m+fM4bMEQjohNwxAOVeiXCjWO8KlhKeGNn/VmDsINisRrRGDhq9SoVGao9stEAgEAsF6pxHrm2tFH6zWhudSr7HYeqIWfWKUysiKgm2Y9fD1rW5k1BDGxhK5/OafW56+pqPs2o5f3KWqn7xQ/sRSr6VoKo5l15UTrHJlXtXRSEsCgK4dPcyOzdQftwyLcqFCvCWKqinYlkN2Jo9ru1QKZb8Qje1SzBawDHNe/RFJluvt3qjMfS+e615SiKh+V+sBRdOwDBPLMIUKjUAgEAi2HEvxKKw2l5SrLkVG1AyJ2v+KpuF5LrKioKgKtmnX10w1oRVhaFyJMDaWSE0H3anmQ9SKuMiqgixLdXmz2k1olg00PYAt2XW5s6WghYLzZNGcOR4HWVHmnV+WJcbPjqJHgujhEKFoiFA0SCCokZ7Iks/kkCXfU1FTQPBcz3frVTvOXNeg57q4rO88h+VQqxmhahqO46ybvAjXcfCstW+HQCAQCASbgeV6Q2rHz82L9Td37fqm5UJRKk71NS7+mqJWlHAuGz28rBkIY2OJOJaFJMmE4lFfJ9n16uXpa94FJaDWS9oD9d+utfTcAb9C5ZUdZq7hMfdGlmQZ27JQVAWjVGZ6xK9ELasKjmljey62adeLx9Q6Vc0iV/WA70GpegDWQn61WUiS7IefVSpoegA9HKobhGs5GKwHg0cgEAgEgq3K3Hm4th5YqtHgb87W/hOGxVIQxsYSqLnEZE2inCsQTSWQZIn8TAZND3Dh6TNIstSQBexyF6I148Ey/ISkWiVqK1e47DgZZBev2kTH8j0uuHJdenUjh09dTs04UzTNT8B2PWyjjKKp6KGIX+1znYRVbWRsq4AkayiKvtZNEQgEAsEW5cq806WFMa1086+2QStXN51FSPS1EcbGVfAX4F49bCqcjPnxeI5DfiYD+DepYZcXrcKt6oGm3Yhzi7FJsoxTbWONmqE09/i5lTRrHbLmDvQ2mZVeq/JZ8xh5rkc5V2i6d0FWFTQ9gKz4oXalTH7TeDRsq8Do2U8wfvGzWIafLzSw50fp3/OWNW6ZQCAQCLYyfmiUH0LtNHHOra2rHHe+pO1mUPNsBsLYWABZ9ZOko6kEsZY4ZsUkEAzgOi6WYWGZJmbZwCwbfmXIRXbIm2nx1oyJmmflUlLTJY+FJ1XzMxxnnjWuVhOdHNupV5HcTN6NGnM7fjO9GbKqEIpH0QIBIokIuekshXT2ijZsNCwzS3b6cYr5c+RmniKffhrPcwkE25GVIK5TIT31kDA2BAKBQNA0rqYIdfn86m/ANnctc7mBcbW2CHyEsbEANU9BIZ2lmMnXk7Jtw1zUS9EM2dtr4ble3Y2n6tW8C8c3JmRZAtlXzaohyVLdiwEQCAYp5Qp4rrPlwopqKmI1r8dKCwFKslytWaJRyuQByIxPNaSNa1Gc0DTSGKVRLDPHyJmPkpt9auHjKpOEIv2kOu+mf7cwNAQCgUDQPBo9D841EuYqUC33OsLAWBxhbCxCbQFeCz9azEux2onHnuviyVJdhs11PRRZRpYlXNfzDQ5ACaiomopru7hVb0ilUMRxHNSAim3aq24orTVzQ9CAulTuUmuMqHoATQ9QKZQwimWg3JB2zXXDruYgls+cYOT0R5iZ+DaXfwjh2E46+l+GHuzAKE9gGjN09r+CcGz7qrVPIBAIBIKlsJT1zNz5daPWFtsorJmxEYpHKV+WxLzeuPxGXa/W6yWpXM/PE1AVkh0pZkYm65K8gaCOHtSplCrInoseDvpVyRWlnoOylanVTamFkSmadkVIWc0Yqd0XdpPqZKzFfTZy5mOcP/73BCP97Dj4c5w7+j48z2b7gZ+lvfdeND256m0SCAQCAVhmBjzEODyHUv4cw6f/k/a+l5Bqv+OK57fSxulGYM2MjfVuaGwU5krWOpZVXyDXCsbZpo2mB1A1Fcu0iKWiTI9MUcoV60UIL+3obx7Z2+UyN8ZTCwWxypVrHLc81qvHyLHLTA5/kcmh/6OQfYbenW9icN+P4bkOZ5/+K7YdeDs9O76vfrweCeG63lU/G4FAsDEwjVlKubOUCxcxKlP+YhYJVYsR0FMEgu3EUgcJhrvWuqlbGscxGDnzn4yc/giuaxKK9NPW8yI6B16FHupY8Xk9z8PzbCwjTWbqERzHINF6E+HYDiRJauA7aB5To/cxNfIlpka+xN5bf4e2nhesdZME10CEUW1gJFmepy6laBqyqmCVK1jlyiVDxHOr8q8uM2MzuI6DbZhIslQtTnhl5e2tjG2YdeNL1QPXvbheyNBYqCL9ahkkrmsxdu5TDJ/+CLZdoKXjbvbt+kFaOu+mmDuLZaQBOH/s74gm9pJovQmgGiomEAg2Gp7nkJ1+gumxb5CdfoxKaRQASdbQg+2ogQQAtpnDNGZxHb+vx1tuZN/tv49WfX4r4nke54//PbIcoH/PW5Hl5i+bHKfC9Oh9DJ36AGZ5ip4drycS30Vm+lFGz32C4TMfoWvwtfTufCN6sG1J57TtErNj32Ts/H9TyJ4EavOPjCQreK5FvOVGth14O7HkvhW123NtTCONZWbQAgkCwfZ5xovnObiOHw0gK/q8fNLa80Z5kkpxBNNI4zoGnlstSIyHZaQxK9NYRppc+ggd/a/AKI1z8Zl/Jdl+B6oWWVG7Bc1H8jxv0e3sXC5HIpHgrpd9TnyZGxhVD/jF/6qLRmFYLJ+aUbAWiduNYHrsG1w4/o9UyuN0DbyG3p1vJBjuIjd7mLNP/zXF3Gn/QEkmEt/F/tv/ED3UvraNFggEK8a2Cpw/9vdMDH0OPdxNS8fdxFsOEYnvJhjuQlpg8WybeWYnH+TUk++hrecF9O16M5H4rjVo/driuTYjZz/GhRP/jCQpJDvuYs/Nv9G0dZDneUyNfJlzx96HbWZJdd7Dtv0/TTg6UD/GsUuMnvskI2c+huuadPS9nPaeFyErAZAUJCQcp4JZmcYoT2KUxygXR8jNHsZzLZLtd9DS+WwUNYSiRoi3HEJWgmSnH+P8sb+nXBwiHNuJLKu4rkUsdZD2nhcRTe5DUUMLtts0Zhm/8L+MnfsUtpWrPy4rQQLBdgJ6C45dpFy4iFs1HiRJJRBsq/60YpanKObO4LrGvHNLsq+UKSGhBpIEgq0E9Bb0UCf9e96CZeY4/O23oYc66Rp8HeHYdjzPxrFLeK6F5zl4rv+/bRfx6skZHp5r43kOkqwhywEURUfVYqiBOPGWm8R6dxFsq8hDX3wV2WyWeDx+zWOFsbGBWKyex0LUCxIqvpzv1RbHly+eJVn2daq3mELVSqgVEVrv3qGhUx/i4jP/QqrjWWzb/1OEY9sxKzOcOfL/MTvxbSKJPWzb95MEI30E9BSyKNQnEGwoXMdkZvxbjF/4HyrFUSRZwaxM43mOHxa5/fXLCpMZOfMxRs58FMtME285REvX8wgEW9FDncSS+5AkZcHXea5NqXCRUKTPXwSvI8qFITLTj1PMnkSSNQLBVlzHwKxMVRfnE3ieg6KGsYwMlpmmZ8cbSLbdyvFHfxPPdQjHtqOH2lG1KJaRwahMISs6mhZHVoJIsoplzGKZGVQ1SjDSR7LtVhzXoFIcxXNtwMMy05QLw0iSjB7uoVIcopg7TVvPixjc++MEIz1XfR+2VWT8wn8zevYT1TC4K1HUCHqoi2C4i3jLjbR2P/+aoXGe5zA7fj+zE9+pGqES6ckHMStT/gZUbDt6qBstkEDRIthWAbMyTXb6cSRJpnPgVSTb70QLJLDMDOXiMGZlGrMyi6IGCUe31fNObCuPUZ6sPj9DINhKJLGbcHTQn4OCrciyvqT7tZQ/x+nDf0EhcxzPWzhCQJI1VDU6756VZNXP1XRtPNfEcSq4TqV+/MCeH6Fv15sWvf5WRRgbW5DaAvdSSJV6qUo4IEmXqmqCX0+j9n8gpGOWjXnP1xbP63XhLFg+D33xtaQ67mL3zb+OJElUSmM89a2fQpIVth/4Wdp6XniFW1sgEKw/XNcmP3uE9NQj5NNHUNQIqhYnPfkgtpUj0XoL8ZYb8TyHQKidVPudBMPdK75WeuI7jJ77JIXMM/WdZz3USUffy2nreQGh6ACSpGCUJ5md+A4jZz+GURpDkjWi8d0EIz3ooU70UBd6uAstkEQLJPzFHnJ9AdqscFLPc8inj3Lu2N9TyBxHkpTqDriLacwgyzp6sA093Ike7ESSVRy7hKzotPW8iGhiNwCV0hjZ6cfJZ05gGbPYVg4t4Oe4uK6JbeVwHQPXtfz3qKdwrALF3GnfayzJBENd9Y0cVYsTivaD51EpjSErAXp3vrEeuroUXMegUh7Hc536QluWAwSCbQ1Zr3meQyl/jnz6OIXMCT+Mycxi20VUNYIWSJBsv4P2vpeiBa694Gw2jmNQKY4gKzqKGq6GavniL3LVQ7IYrmNiVKZ4/L43A3DrCz5EMNK7YXJZVhNhbGwBLjcual6IpRgHc70YwpjYOpx47Lcp5c9x6ws+AMDI2Y9z/tjfccsLPjDPTS8QCNYXtlWgVLhAMXuKzNSjZGcex7FLaIEU8dabcZ0KpjFDovVmOvtfRTg22JR2eJ6HYxco5S8wMfR5Zsa+gWMXAeoFPkGitfsFdPa/nHJxmELmBEZ5ovozxaVcgUt0Db6OnYfe0dC2lgoXSU88QHbmCXKzR3DsIpH4Tvp3v5Vk++1XDQlqFraZR1aDS170CtaWsXOf5sIz/1LvZ7HUAWKpg8RSNxBJ7EJVw2vdxDVnOcaGSBBvIitdyC/ldZfXYXBcd9GCg7VzL/R6webB3z9w57mLPc9DkjRsq1h/rLXruYyc/gjHHvpV+nb9IKnOu5ecbCgQCK7EdW3Gzv8Xk0NfIBBsJRzbRs/271uWcpDr2uRmnmRm/NuU8mcpF0ewjBkAJEkhljpI7843kuq4i0h816p6IyXJV6yKt9xAvOUGdt7wi2RnnsSsTGFbBYLhbuItN9Y9FSnuuuK9mZUpLCODbeXwPIdi7gwXn/lXIvFddA2+5rrbaJk5zh17H1PDX0KWA8RbDtG78weIp24g3nJowRyV1UANxNbkuoKV0b39e+jofwXZmSfIp4+Rzxxj6NQH6mFWWiBJMNyDHu6qeu06CEb6CEX6UbUYkqxSyJxg/ML/EIz00dr1HCLx3VvWQyI8G01kIaNB0bR6gtLl7uJYa4pCOntNA0B4IgRXY3biQYZPf4hS/hySpLDz0Dto63khrmtz7ujfMn7hv9l14zvpHHhl/TWV4ijnjr2P2YnvAB7xlhvp3vbdtHa/YMsOigLBSnAdg+OPvpvM1KO09Twf1zHJp4+CJNPZ/wqiyf04dhnXqdDSeQ+BYGv9tZ7nMHz6w2Snn6SQfQbHLvp5EalDhCK9BCN9hGPbCEUHUDZhLtXpw3/O5NAXuPWFH1xxuBf4ydPHHvl1SrkzDOz7cTr7XrHuckYEGxfPtSnmz1HKn6dSGqVSGvWL3JYnMSpTeO6VOa6hSD+mmcaxCkTiO+nofxWp9jsIRvo2/BwrwqjWmJr3oCYtWzMuPNer51L4/7vzXiOMCMFKmRr5Kief+APirTeRar+DQvYUM2Nf5+Bdf05u9gjDpz/Ejht+ga7B1y74esvMkp58iImLnyM3+xTd27+XHQd/bpXfhUCwcbCtAuXiMJYxSzF3lqnhL2KUJ9l/53tItt0GgFmZ4fzxfyQz9fC8JF5ZDtDR/3Jau1+AbeaYHruPmbFv0dL1bKKJPVWvxdbYBfUVmL7CqSf/kFue/37Cse3XPN4yM1hmDs81sa1iNal7nHJhiNzsYSwzy4E7/3hZeQ8CwfXieQ5GaYJycchXwvIc1ECCZNtteJ5Ldvoxxi98hvTkg1UBAj/fRQsk0YKtBPRWYqkDtPe+ZMP0e2FsrCPmGh615OvLjYqNKqMqWD+cfPKPKGZPc/Pz/rlq4HocfeiXKWRPEo5uQw3EOXDHe5Z0rrHz/8XZp/+K/Xe8h5bOe5rccsFWwjTSDJ38d4q5M7R03oOs6FRKo4Sjg3QOvOqy0D+XQuY4manHKGRPIisashIiEttBW++LmRz6PMXcGYzyJLaZxXVNX8NfkpAkFVWL+LKaeiuKFkHVYnT0vWxFO+eua2MZMxSyp5iduJ/szJMYpbH687Ks09L1HHp2vH7BGgV+IvIsqhbFcy1Gz32KiYuf81V+AD3cTf+uH5rnddzsmJUZRs5+nKmRr2AZM4Sig9zy/PdfNSwsM/04p554D6YxfcVztUTrUHSQ3h1vaFrOikBwvTh2iezMU5QKF7DNrF87xJjFrExRyp8j1fEsUh13EU3uJ5rYs65FW4SxsYEQHg1BIzj11J9Syp/jpuf8ff0x2yrw9AO/SKU0iud53Py8fyYU6Vv0XJ7ncfyRXyOfOc7+2/+AeMuhZjZdsEmxjAz5zDHKxWEqxREKmRMUsqdQ1BDxlhvJTj+Gh4ce6qRSHCaWOsjOQ79MODpAuTjCuWPvIzP1MIoaIZrcB56H45QpZE4AErKsEU3tRw92oOlJZDngh8x44Hq2X6CuMu2rBtml6sLeq6r93EK5OESlOFKVuzSg5oHGq2vzm5VpKqVRzMo04E+VoeggqfY76zKdgWBbXVlpOXieSzF3hoDeMi+kaitglKd47L434bkWibZb6Rx4NS2d96AowQWPz848ydGHfpV4y410DbwGrSrNrSgh9FA7ikjWFWwCpkfvY/jMf1LKncXzbEKRfrq2fTeR+C6C4W5kJVBXHFPUCLIcQJKkavSMtOoeEWFsCASbHM/zMCtTuI6JrAQ49vA7CUW3se+235l3XKU0xhPf+FFfxz3UzqF7/hZViy56fsvMcPyR3ySfOcbBO/+UZPvtTXongtXGtksMn/oQrlNB01OkOp5Vl/a8HNcxsMwskqzOm9zmnqtcuIhRGqNSnsAojWOUJ6oGxhDgqxQFw71E4jtItN5MS9ez0QJJXNeqy1LmZg9z+qk/o1waQZL8asaKGmH3zb9GS8ez5i3kZ8a/Rblwkc6BVy+rsrVtFbhw4l+YHPp8tbCYRCDY5r8vJTBff19SkGSVgJ4iGO71JVtD7YQi/desfSBYGo5j8NAXX12PcY8m98/bKKlhGRmGz3yE8QufIZrcx8G7/kyoOQk2Pa5jkE8fY/T8p5kd/za1jY4rkGTwvOrzMmrVgxsItqOHOglFB4inDl6zIOP1IIwNgWAT4rk26alHmRr5CtmZJ+oKNTVufPbfEUsduOJ1F595PyNnP4YkqUSTezh4558uaRfWc22efvCXcV1zwYWAYH2Smz3M2Pn/JjvzFIqiIyshWjrvpmfH9yPLKofv/1kqpVGC4W6M8iRIEu0996KoITzXvpT4WJnCsQrzzh1N7qd35w+QmXqEzPRj80KJFDVcr6UQDPcQS+0nljqIHupa0o6b65hMDH0ez3MJx7YTTexC1Rqv4GOZGYzyFKFo/1V30gXNp1wc4ezTf0lm6pEFc8TSkw/xzOO/B0D3tu+md+cbmnI/CATrGccx/M2c0iie6yDJCp7n4tglHLvs11CTFDzPxrYK9WKJRnmcUv58VZpaJhTtJ5rYTVvPvaQ67mxIeJaQvhVsKZ781k9ilCdQtRh6sB1Nb0XVIihqGFWL1mXpasV6guFuEq03r3Wzl83ZqqJUKDpIR99LibccQlHDfvEpOUA0uX/B11lmBlkOsOfW3+LYw+9kYujzV00Un4skq6Q67mL49Ier0rkbI2ltq+J5HhMXP8uZI+8lFB2gs//leJ6HZWYYOfsxhk9/qH7s/jv+mJbOZ2GZWU4/9afk00dw7DJISlW+9Cb0UAeBYGvVC2FjWzkunPgnnnnstwlG+mjpvIdofDfh2HaC4R4ULXpd94isBOje9l0N+CSujV9QLtn06wiuzdi5T5OZeoSeHd/Ptv0/VX/cdQymRr7C2af/mkTbLey+6V11KV2BYKuhKDrh2DbCsW3Lfq1fkPEC+cwxitnT5GYPMzXyLjr6Xs7um9/V+MZeA2FsCDY0tlWkmD3p/21mMSvTdR3sa9G/+4cZ2PsjK7xmYUmhSI2mdk091IlRnmL49EcwypOYlUkAurd9L6mOOykVLlDKn6NSHMWoTGKUxth+4GdItN5EQG+lkD215GtGE3tw7CLTo1+jvffFTXlfguvDtgqkJx9i9OwnKGRP0DX4Wnbc8Ivzdq76dr6JYu40rmsiSTKpjjsA0AIJ9t/xh0u+Vkvns7HNHKHo4rk/AsG1kGQFJJmxc59ievRraIEktl3EKI0DHh39r2DHDb+4KaV+BYLVQJIUIvEdROI7ABi/8BnOHHkv6jLCTxvWFhFGJdho5GaPcOyRXyMY7kYPduDYZUqF89hmDs+zl3yeu1/55WXF/3qey7lj72Ps3Kdo73sZ/bt+kGCkd9XUIlzHYHL4S0yNfAWqibV6qHPejjX4yjjh2Db0cC9aIIashFDUIFPDX8IoT3Do2e9bUDFnITzP4/jD78I009z0nH8U3o01xvM8jPIExewp8pnj5DPHyM8+jefZxFtupH/3W0i03Sa+J8GGwChPMTvxHSxjFstMoyhhQtF+IvFdRJN717p5AsGm4eIz72fo1H/QOfAath94W0NEFUQYlWBBsjNPMTtxP57rVCvA3rigCkpu9gjF3OlqMmQverC9HuPvh2WkffWVOQmVq4ke6sS1yzhWEU938HDRgx0Ew91Ikookq1hGGqM8jmOXkOQAqfY72H7w5wgE27CtfFV5RsIoT1ApjlIujVApjmCUp6rqNX4BnljyILKsYttFMtOPkZ54kK7B1zIz9k2mhr+ILOsEI924joVlZZGQ6Rp8Le29L0FRQ8hyAEWLLGjUFHOnOXP4vQSj/XT2vwo91I5t5f1KvKEu9HD3vEWjrOh0Db6mXmXXtgrk00fZtv9tVcWcGWwrh2OXMCszVQ+Gr7CjajESbbex7/Y/qO9yLAVJkuja9jqOP/LrwruxhlSKowyf+U9mxr7u379AQG8jmtrP9gNvp6Xr2eihzjVupUCwPPRQO93bXrfWzRAINi2e53Hx5L8xfOqDDO77Cfp2vXlN2iGMjS3E0w/8Qv3vsfOfqv8tK0EG9vwIvTvfgOd5HPnOZcXcJBk92I7rmFhmGoCBPT9K/563XPValdIYM2PfwDJzdA2+lmC4q2HvQw910NH3cmYmvs32gz97VTlXz/MoFy4wO/kgI2f+k8fvezOKGkZWgniejWVkuKTyIKGHOtBDnWh6K3q4k2L2JJNDXwA8ZDmApqfYd/vv0tr1XAb3/zS5mcOUi0MYpVFkJYgaSGBWphg998krvA2qFicQbCMcGyQS30W5OMLU8JcIRfvIzx5haviLV7Rf1eK0dD2H7m3fjSRJWGYeszxBPnOiHoMJLpKkEgi2oYfa0QIpQtFBND2FHmwnEGwjFOm7rmqloegASHI10Uyw2pTy53niG29FUSN0b/tuYqkDROK70UPta900gUAgEKwzCtlTpCceoFIep1y4QD59lMF9P0XfrjeuWZtEGNU6x7YKfvx9aQxFjRDQU2h6C45dwjJmMY00qhYlGO5BD3chSwqe51SLUKUxjWlsM4eihjGN2foufnb6CazLiiPd+dLPoAXiDJ36ABef+bertkmSA8RbbsSsTGFWpgkE2wnHthMItmCUxikVLlIpDvkymUoA1y6z66Z30tH3MoBqIqp8XbG4ZmWGI9/5OczKDNHkHhQ1iqan6Nv5pgXjyY3yJLMT9+PYZRyngiQp6ME2f5Ee7iIY8jWsL8dxDCRJXla4lWXmKOXO4LoWrmtgWwXMygxmZZJS/jzF3BlkJUjvjtfTNfg6ZEUnnz6K41TQtDiKGqFSGiGXfpqJi5+/QnUqFOknmtxHvPUmEi03E4z0NCWUy3EMJof+jwsn/hktkODGZ/+dSNRcA4ZOfoCLJ/3+2NL1XPbf/vtr3CKBQCAQrBdsq0hu9ilK+fMUsieZGfsGqhbzQ81DnbT1vpi27uc35bpC+naDUYvFLuXPUsydpZg9SSF7EqM83qQryihaGM918Fyrmusg12XUkGRqu/6e5/qFZKrFZNRAgljyAMFwD4FgK0Z5klL+HKYxSzDcTSjSR6zlBlo6ngX4KkqTQ58n2X4HnuuQmz2MJCkk22+npfMeguEeNL2FQLBlWdKGjl1m7PwnKeWHsO0CxexpbCtH38430bPj+9Ztoadal1uaHKhBLn0URQmhBmIE9JamvS9fzehzjJ3/NGZlGtvKARId/a9g+4G3r0lS/FbHdW3Skw9y8Zn3U8qfId5yE4fu+au1bpZAIBAI1gHF3FlOPPqbVEqjKGqYUHSQ9p4X07Xtu5CXWWh0uQhjYw1wHYNycYRKaRTLzNDa9Ty0QBzP87CtHKXcWfKZYxSyJ3Edo1qh1sG2C9hmDsvM1FWUFDVCJLGbaGIPkfguIvEdBMM9OHYZ05jFMmZRtSia3uIreFh5KqUxjPI4nudWC2UpaHqqWt02jmOVsKwctpnzr2nlcawSkqwgyxqSpAJe3bDwPBc8B89zqgWuAshygEh8O9HkvmXla3iex/TYfYye/QRaIEGy/U5c12R2/Nvk00eZW7AmGOkn3nKIQLAN16ngOhXMygyV0giV0jie5/jtlTVUNUog2EYg2Ioe6kQNJJi4+DkqxSF6d76Jbft/ssHf8ubEdW0KmWMMn/ow6amHaO1+AdHEbgLBNqKJPYRj29e6iVsGv1jjJLn0UXIzh5kZ+zqWmSEUHaC167n07HgDWuDag7pAIBAINjelwkVGz3yMiaH/IxwbYO+tv0MoOriq4iDC2FhlKqVxjtz/s5hzwpIULYoe7KgnKYNf9Cqa2IuiRpBk3yBQ1AhaIIEaiBOK9BOJ7yAQ7NgyajK2VawrkVRKE+TTR8nNHsa2Cn5BMjWEFkgSDPcQjPQgSyquZ+O5FpaZq4YnTfkSr+UJ8FyiiX3su+MP0INta/321hWe5/oJ8aUxjGq153z6KLn007hOhWC4h237f5rW7uetdVO3DJaZpZg9RSF7knzmOIX08fo4Egz30NL5bDr6X04kvnONWyoQCASCtcbzXM4+/deMX/hvtECK3l1vonvwdQuGgTcboUa1ykyPfg3TmGbb/rfR3nsvACNnP47rGATDL0UPdxOK9BOODa6ZgtN6RdUiqFqEEP3EW6Cj7yUrPpfn2pjGLIFg65b/nB27THbmCUqFi5QLFyjlz1PKn8d1yvVjND1FNLGX/j1vJdFyE9HE7iVVFhdcG89zMI00rl3B8yxc18K2CtUcqlmM0jjl4kVK+Qv1GimyEiSa2Et730uIpQ4QSx0koLes8TsRCAQCwXriwol/YfzCZ9h+8OfoGnjNmhgZK0GsLFaAr3J0kczUI5iV6fpOZKlwoS4lu/3A29ayiVsSSVbRQx1r3YyG4Lk2pcJ5LjkePVzHxLFLOE4Z1zGRZV/m1w+Bk/A8C8+1qZRGGT37Cb9yuBIiHB0kFBukrfv5frXnqpyxLIplrRjHLpGZfgKjNEqlNI5RnsA0ZqrjwUxVWvlKZCWIHmz342p77yUS30kksZtQpHfLG8gCgUAguDqmkWbkzEcZ2Psj9Gz/3rVuzrLY1MaG59ocf/Q3QZJp73kxLZ33ICtBXKeMbRWxrTyWmcYyMjhOmdau56ItUFnRdQxKhYsUqpKjuZmnqJRGkeUAgVAHqhol2XZ7PSFaILheJke+zOmn/mRFr5Ukhfa+l9G3843XJXkrmI/rGOQzJ5iduJ+Ji5/DsYvIcgA93IUe6iQc206y/Q4/hyjYjqKEkJQAsqyhqOGmJvcLBAKBYHNTyp8DXFq7Nl6o8+Y2NvBITz4IQHriO0iSiod71V3H88f+nvZeP4zHtgrYVo5KcYRKaQxwQZKJxHaSbL+TVMezSLTdcl3yrQLB1Wjtfj5nn/6rumhAjWhyPy2dd9PZ/ypkRcfzbFzXBs9DVrR6In+zVSg2O37xygzF3GlyM0+Rmz1MPnMcz7VQtThdg6+lc+DVBMM9wpgTCAQCQdMJhruRZI0Tj/02B+78I4Lh7rVu0pLZ9Anixx5+F45dZNeN/4/M1MMgK6hqFEWN+FKigRSansRxDIZPf5j0xHdQ1DCKFkVVIwTDPYSig/VibIoaWuu3JNgieJ5DIXOCSmkc2y5glMbJzjxJIXMcgIN3/TnJ9tvXuJWNpVIcpZA75SuQFYcpF4fBcwlG+wiGe4nEthNvvblhxlSt8GMxf5Zy/gKlwoXqBsNIXdhBCySJt9xIvPUm4i03EonvECFPAoFAIFh1irmzHH/k1wgE29l/x3vWVJ1wU6tROU6FoWf+ncmRL9WVnPxqyR2kOu4k0XrLvISZyeEvc+rJPyQY7qG976V+ImzqgPBICNYtw6c/QnryIYr5MzhWYd5zUrVoI8CeW95Ne++L16KJDceoTHPu6PuYGbsPAEnWfEM/0geS7BsAxRFc10DV4rT1vICe7a8nFO1f8TVtq8jxR95FbvYI4CfMh6KDhCL9BCO9hMK9hGIDhCIDwnshEAgEgnVBduYpTjz6m9hWHkWLomlx1ECCeMshtu3/qVXbDNvUalSOXWbk7EcBaOm4G9fzK2XPTn6HsfOfQlEjdA68ip7tr0cPtdPR9xJC0X5Gz36S0XOfZOjkvyPJGp39r6Bnx/ejaQkUNSRUeATrAtcxuHDin4m33EjvjjcQju1AVgI4VhHHLuK6JrHkASKJ3U2pGr7aeJ7H+IX/5vzxf0RWdHbf9C5SnfegapErBkzPcynmzjA9+jWmhr9MevIhbn7evyyrEORcstOPkZs9wt5bf4dE2y0L5msJBAKBQLBe8DyPYLiHHTf8AmPn/4ti9jQVaxRKoxQyx9ECCfp2vXmtm3kFG26FrShBene+ibHzn2Z28jt0DbyWroFXEU0eoFy4yMTFzzJ69uOMnv04d73sf1G1GLHkPvbe+pt4nkspf47ZiQcYOfOfjF/4TP28shxA0SKoWsL3lgQSKFoEWQ4gyRqyrCErQcLRQaLJveihLrHbKWg4pjELeFhmlmC4h0TrzWvuTWwWtlXg7NN/xdTIl+kafB2De38cNXB1w0GSZKKJ3UQTu+kafB1PfvPHGDr1oRUrv1VKY0iSgqwEKGROAP5A7joVLCtbLbaZxbEKuK6F59l4ro0kKey44RfqynMCgUAgEDSa3OwRzj79l/WCxp5r43n2nCMkAnormj6ApicBiVjywBq19tpsuDCqGkZ5kovP/CuzE9/BtvLIcgAPD8+16sfsvfW3aet54YKvt8wshcwzdSlRxy7hWMXqIiOLZebqiwzXtfBcX3bUMjMAqFqcaHIv0eQ+4qlDJNvvEMaH4LrxXJuLpz7A7Pj9lPJnCMd2cuDOP0YPta9Zm4zyJOeO/i2WmaGj7+W09bxwxblLtpWnUhxlZvybTAx9Htcx2HHDO1ZUX+XUU39CMXuam5/3zytqi1Ge4qlv/zSWMXPlk5Jcd02rWqxatV7FNvMUsicY3PcT63L3SCAQCAQbn5EzH+P88X8gljpAa9dzkaRLUveBYAvBSC/BUPea1tnY1Dkbl+Mn0Z4klz6CJKlogTiqFkMNJIgm9jbcADCNWQqZkxSyz1DInKCQOY5lZujb9YMM7vvxhl5LsLXJp4/x9APvwHUNIvGdxFtvIaCnqt63OGogjh7qRA91LDtGs1Ic5fij7ybVfkd1AFOQZAVZCaIoIf+3GqKYO83ImY+iqlHC8e1kph4lEt+15AV+uTjMhRP/4udclMfqOSiKGqG99yX07vwBguGuRc/jOgbl4oifzJ07TSHzDPnMcdRAnNtf9J/Leu9zcRwD28rPe0yRdRQtsmCYmud5nD78Z0wOfR6Am5/3r6K6t0AgEAgahlGe5PGvv4X23pew89AvrltBkk2ds3E5kqQQS+0nltq/KtcL6C0k225FDcRQlCCe55CZepjZifuFsSFoKLHUAW6/9xNkph4hPfkg6ckHsc1cdXF8aY9AkjVCkT5C0QGiiT1EkweIJfdes6bD5PAXKeXPUMqfWbQdrV3PY9uBtyFJCk98463EW25Y8nu4+Mz7mRn7ej1PKpa6gVCkj3B8Z12kwfM8HKuAacz6P5UpjPIERmmcSnmcSmkUozRef8+a3kosuY/eHW8g2XHnktuyEIqioyg6tlXArExjW7mq7HUe28xjWTlsM4NlZrGMDJaZoVIarb9+/ML/svPQL15XGwQCgUAgAMhMP8apJ/4IVYszsOet69bQWC4b3rOxHIZOfZCLz/wr4CvPxJIHUNQInudctsjIoahhYqkbiLfcQCDYRrlwkVLhAuX8eYr5s3iuhSzrRFP76eh9CW09LxKyuIJVwb9fC1hmFqM0RrkwRLk4RKlwgWL2ZFWyVSYU6SUc30E4tp1wdBuBYCuqFkWpSj/PjH+LmbH7yM48eUU9j6uh6S3c+vz/uGZuxVwmhv6PkTMfpVy4MOdRqRqW5IcmOXZpXvgjgBpIEAx1VQvmdRGODhCKDhCK9qMFktf4bFzKxWH/M/A8wK1WYfdw7LJvyFSmMMv+b6M8iVmZrMvczkWWddRAHC2QQA0k0AJJtECCYKSXcGwb4eg2NL1FhE8KBAKB4LoxylM8+tXXA5DqvIfO/lfQ0vmcdTvHbKkwquUwfPrDXDhxZfiHrASJpQ6ihzr9ECwthm1myaWfppg9iec5KGq4Wm9jO5H4TmKpg0Tiu0TxNMG6wvMcyoWL5NPHKObOUsqfpZg/i21mrzhWklTUQMKvdq2GUANxAnobeqidUHSQYKgH1634BnjVEI+33kQ4OrDsdllmhtzs09hW3k9ycy0c18I2Mzh2Gc9zUdSQX+NGqarDea4fzqWFUdUIihpBUcNoegotkKwPwI5jMHr242SnH6eQfWZBw2HOu0bTW9CDbQSC7eihDvRQB4FQB3qwDVVLoGpRP09jDWNhBQKBQLC18DyPmbFvkJ15nOzMYcqF87T13Mu2/T+JHupY6+ZdgTA2FsF1LUq5s0yPfZ3xC5/BsYsA6KFOYqmD7LrxV+teCsepYJt5AsG2dWtdCgSL4YcAZbHtAk7Ng2flsYxMdad/sr7T7zploBaeNUAkvp1wbCeR+A7C8Z0E9NYl9wXPtSkXhykXhjDKfliUUZrAKI9RLo7M96hIMhIySFL9t+sYzA0Zu3Sohh7sQA91+iFXlUlS7XcRS+0nmtiLGkhUcy4k/7ckoShBNL1VbBAIBAKBYN0zNfJVzhx5L45TprXzOaQ67ybZdvuaCsbMRRgby8BxDMr585QKFyhkTjB2/tPsuOEddG973Vo3TSBYdTzPwzazlPLnKOXPUcyf870jubN1IyQc20bvzjfT3vPCefVpTCNNKXeGYv6s/zt3llLhfD1ESpYDfkJ7NTQqFO0nFOknFB0gGOpcsNaN57k4TgXHKuDYJWy7iGWkMcqTvpFRngRcBvb+KOHo4Kp8RgKBQCAQrAa2VWRy+ItMDX+JQvYZwCMY6SeeOkgsdQOx1H7C0cE1qRW3pRLErxdF0Ykm9xKO72Bq5MvISpBoYs9aN0sgWBMkSULTkyT0W0i03VJ/3PNcjNI4xdxpJoY+z6kn/5CRMx+hd+cPkJs5THrqYczKFODnOoRj24kkdtPR/3Ii8Z2EogNogdSyvYOSJKOqYdRrJLsLBAKBQLAZUbUIPdu/h57t34NlZslMP0Zu5jD59FEmR75UDzeOJnYTie8iGO4lGOnxf4e7kKtCLGvNljc2aoyc+SiZqUfYd/sfEk3uW+vmCATrCkmS/QEs0kNr9/MoZJ7h5JPv4dSTf0QoOkBb9wuItdxAJLaTYKR70yhoCAQCgUCwHtACCdp7XkR7z4sAcOwShewpvwxD9gSZ6ScwSp/Ddc3qKyQSbbey77bfRdWia9dwlhlGdduLPwGejR7qnKdB7xe6esYvMhLurj/ueR6l/FkKmWf8GHG7iGMV63HjjlMhHNtGouVm4q03ogUSzXmXS+DpB36J7MzjgB/uUVef0ZO0db+Q9t57RcKoQDAH1zGxzOy6iR8VCAQCgWAr43kuZmWGSmmUcuEC50/8E7KkoYc6q8qKfo0uTUsQCLXT2vmcK9QlPc/BMrM4dhk92H7VtW/TcjYULY5j5ZCVoC+nGduGURonO/sUeC4AoUg/qY5nIckqM2PfpFIaAfBVZtRIVXrT/y3LAQrZkxjlcUAiFB0kljpALHWAcHTQV53RW3x1miYnZ1tGhmLutK+nb/p6+raZpVIcJTP9KKoWRw93+V+W5hcOrH9xWtTfya0muNYSUv3dXf//eMshIY0rEAgEAoFAIFgVSvnzTA5/0ReIMXPYVq7+t2VmkGWNZPsduK6JZcxiGmksIwO41TNI6KEOguEe/6cWohXpRdVTPPaV72u8sZHqfDZdA6+mXLhQTx4NBFKkOu8h0Xoz5cJFv/jY1EO4jklr13Np7X4+idabrhk3ZpQnyM48SW72aQqZYxRz5+a8UT8GXNOTVcnK9qoHpYdgpJdQpBdNb0GWtSV87D6e5/nJplYOWdHrFZOvZtCUCheYGvkKluEbIH6hrzy2lcU287iuseg1B/b+GP27f2jJbRQIBAKBQCAQCJqBWZlhcviLZKYe8TfQqxv8Ab0FTU+hKEGM8gTl4giV0qj/UxypK7jWWDM1qtopV+qNcOySX2zLSGMZs1hGGstMYxppzPIk5dIIRmmCyw0SRYv6GvlqpP63okaQJKVqsc36vyszCxgIkq/pr4ZQqr9lxdf910OdBMNd6OFuguEe9FAnrlOpFgSbolIc9SU9yxPV6sdTdeWeGre84D+EWo5AIBAIBAKBYEPieR62laNSHKFUuMjpp/54c0vfuq6FUZqgUhrBMtJ+0TG7UM8Jsa1Lf3uuQyBYs9aqv4OtaFoc1zVx7LL/45RxnXL9f9cpY1tFjMokldIojlVYsC2KFkUPdhAItvk/ekv1dyuBYAvBcC+anlzdD0ggEAgEAoFAIGgCW0L6VpY1QtE+QtG+VbumbeWplMYxSuMoaohAqL1afVnIcgoEAoFAIBAIBJezYY2NtUDVYkQTMaKJ3WvdFIFAIBAIBAKBYN0jL36IQCAQCAQCgUAgECwfYWwIBAKBQCAQCASCpiCMDYFAIBAIBAKBQNAUhLEhEAgEAoFAIBAImoIwNgQCgUAgEAgEAkFTEGpUAsECfPaDvfP+f/UPjSz5WMHCzP0M535m1/psBQKBQCAQbGyWVdTvDW/4LjRNW412CQQCgUAgEAgEdU5NvZXd7f++1s0QAF/96rcYGxtvXAXxSqXC9u3bGR8fb1gjBQKBQCAQCAQCwcakq6uLc+fOEQwGr3nckowN8A0O0zQb0jiBQCAQCAQCgUCwcQkEAosaGrAMY0MgEAgEAoFAIBAIloNQoxIIBAKBQCAQCARNQRgbAoFAIBAIBAKBoCkIY0MgEAgEAoFAIBA0BWFsCAQCgUAgEAgEgqYgjA2BQCAQCAQCgUDQFISxIRAIBAKBQCAQCJqCMDYEAoFAIBAIBAJBU/j/AQw495zromJtAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import os\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import xarray as xr\n", + "import imageio\n", + "\n", + "def create_imerg_animation(input_dir, output_file):\n", + " # Ensure the output directory exists\n", + " os.makedirs(os.path.dirname(output_file), exist_ok=True)\n", + "\n", + " # Get all NetCDF files in the input directory\n", + " files = sorted([os.path.join(input_dir, f) for f in os.listdir(input_dir) if f.endswith('.nc')])\n", + " if not files:\n", + " print(\"No IMERG NetCDF files found in the input directory.\")\n", + " return\n", + "\n", + " # List to store temporary frame files\n", + " frames = []\n", + "\n", + " # Create a figure for visualization\n", + " fig, ax = plt.subplots(subplot_kw={'projection': ccrs.PlateCarree()}, figsize=(10, 6))\n", + "\n", + " for file in files:\n", + " # Load data from NetCDF\n", + " print(f'Loading file {file}')\n", + " data = xr.open_dataset(file)\n", + " lats = data['lat'].values\n", + " lons = data['lon'].values\n", + " precipitation = data['precipitation'].values[0] # Assuming time is the first dimension\n", + " # print('precipitation.shape:', precipitation.shape)\n", + "\n", + " # Plot data\n", + " ax.clear()\n", + " ax.set_extent([lons.min(), lons.max(), lats.min(), lats.max()])\n", + " ax.add_feature(cfeature.COASTLINE)\n", + " ax.add_feature(cfeature.BORDERS, linestyle=':')\n", + " ax.add_feature(cfeature.LAND, edgecolor='black')\n", + "\n", + " print(lons.shape, lats.shape, precipitation.shape)\n", + " Y,X=np.meshgrid(lons, lats)\n", + " # print(Y.shape, X.shape, precipitation.shape)\n", + " im = ax.pcolormesh(Y, X, precipitation[:-1, :-1].T, transform=ccrs.PlateCarree(), cmap='coolwarm')\n", + "\n", + " # plt.colorbar(im, ax=ax, orientation='horizontal', pad=0.05, label=\"Precipitation (mm/h)\")\n", + " plt.title(f\"GPM IMERG: {data.time.values[0]}\") # Adjust as per dataset time format\n", + "\n", + " # Save the frame\n", + " frame_file = f\"frame_{len(frames):04d}.png\"\n", + " plt.savefig(frame_file)\n", + " frames.append(frame_file)\n", + "\n", + " # Close the dataset to save memory\n", + " data.close()\n", + "\n", + " # Create MP4 animation using imageio\n", + " with imageio.get_writer(output_file, fps=2) as writer:\n", + " for frame in frames:\n", + " writer.append_data(imageio.imread(frame))\n", + "\n", + " # Clean up temporary frames\n", + " for frame in frames:\n", + " os.remove(frame)\n", + "\n", + " print(f\"Animation saved as {output_file}\")\n", + "\n", + "\n", + "# Example usage\n", + "input_directory = \"../../data/GPM/2024\"\n", + "output_animation = \"./imerg_animation_2024_01_01.mp4\"\n", + "create_imerg_animation(input_directory, output_animation)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3599, 1799)" + ] + }, + "execution_count": 33, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "precipitation[:-1, :-1].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "precipitation.shape: (3600, 1800)\n", + "Frozen({'MWprecipitation': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: mm/hr\n", + " units: mm/hr\n", + " CodeMissingValue: -9999.9\n", + " LongName: Observed merged microwave precipitation estimate;\\n ...\n", + " origname: MWprecipitation\n", + " fullnamepath: /Grid/Intermediate/MWprecipitation\n", + " coordinates: Grid_Intermediate_time Grid_Intermediate_lon Grid_Inte..., 'MWobservationTime': \n", + "[6480000 values with dtype=timedelta64[ns]]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: minutes\n", + " CodeMissingValue: -9999\n", + " LongName: \\nObserved merged microwave observation time after\\n ...\n", + " origname: MWobservationTime\n", + " fullnamepath: /Grid/Intermediate/MWobservationTime\n", + " coordinates: Grid_Intermediate_time Grid_Intermediate_lon Grid_Inte..., 'IRprecipitation': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: mm/hr\n", + " units: mm/hr\n", + " CodeMissingValue: -9999.9\n", + " LongName: Infrared precipitation estimate\n", + " origname: IRprecipitation\n", + " fullnamepath: /Grid/Intermediate/IRprecipitation\n", + " coordinates: Grid_Intermediate_time Grid_Intermediate_lon Grid_Inte..., 'MWprecipSource': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " CodeMissingValue: -9999\n", + " LongName: Observed merged microwave satellite source;\\n ...\n", + " origname: MWprecipSource\n", + " fullnamepath: /Grid/Intermediate/MWprecipSource\n", + " coordinates: Grid_Intermediate_time Grid_Intermediate_lon Grid_Inte..., 'IRinfluence': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " CodeMissingValue: -9999\n", + " LongName: \\nRelative influence of infrared precipitation in the ...\n", + " origname: IRinfluence\n", + " fullnamepath: /Grid/Intermediate/IRinfluence\n", + " coordinates: Grid_Intermediate_time Grid_Intermediate_lon Grid_Inte..., 'precipitationUncal': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: mm/hr\n", + " units: mm/hr\n", + " CodeMissingValue: -9999.9\n", + " LongName: Merged microwave-infrared \\n pr...\n", + " origname: precipitationUncal\n", + " fullnamepath: /Grid/Intermediate/precipitationUncal\n", + " coordinates: Grid_Intermediate_time Grid_Intermediate_lon Grid_Inte..., 'precipitationQualityIndex': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " CodeMissingValue: -9999.9\n", + " LongName: \\nPrecipitation quality index; qualitative indicator\\n...\n", + " origname: precipitationQualityIndex\n", + " fullnamepath: /Grid/precipitationQualityIndex\n", + " coordinates: Grid_time Grid_lon Grid_lat, 'lat_bnds': \n", + "[3600 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: lat,latv\n", + " Units: degrees_north\n", + " units: degrees_north\n", + " origname: lat_bnds\n", + " fullnamepath: /Grid/lat_bnds\n", + " coordinates: Grid_lat Grid_latv, 'precipitation': \n", + "array([[[nan, nan, ..., 0., 0.],\n", + " [nan, nan, ..., 0., 0.],\n", + " ...,\n", + " [nan, nan, ..., 0., 0.],\n", + " [nan, nan, ..., 0., 0.]]], dtype=float32)\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: mm/hr\n", + " units: mm/hr\n", + " CodeMissingValue: -9999.9\n", + " LongName: \\nComplete merged microwave-infrared (gauge-adjusted)\\...\n", + " origname: precipitation\n", + " fullnamepath: /Grid/precipitation\n", + " coordinates: Grid_time Grid_lon Grid_lat, 'probabilityLiquidPrecipitation': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: percent\n", + " units: percent\n", + " CodeMissingValue: -9999\n", + " LongName: \\nProbability of liquid precipitation; estimated with...\n", + " origname: probabilityLiquidPrecipitation\n", + " fullnamepath: /Grid/probabilityLiquidPrecipitation\n", + " coordinates: Grid_time Grid_lon Grid_lat, 'randomError': \n", + "[6480000 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: time,lon,lat\n", + " Units: mm/hr\n", + " units: mm/hr\n", + " CodeMissingValue: -9999.9\n", + " LongName: \\nRoot-mean-square error estimate for \\n ...\n", + " origname: randomError\n", + " fullnamepath: /Grid/randomError\n", + " coordinates: Grid_time Grid_lon Grid_lat, 'time_bnds': \n", + "[2 values with dtype=object]\n", + "Attributes:\n", + " DimensionNames: time,nv\n", + " Units: seconds since 1980-01-06 00:00:00 UTC\n", + " origname: time_bnds\n", + " fullnamepath: /Grid/time_bnds\n", + " coordinates: Grid_time Grid_nv, 'lon_bnds': \n", + "[7200 values with dtype=float32]\n", + "Attributes:\n", + " DimensionNames: lon,lonv\n", + " Units: degrees_east\n", + " units: degrees_east\n", + " origname: lon_bnds\n", + " fullnamepath: /Grid/lon_bnds\n", + " coordinates: Grid_lon Grid_lonv, 'lat': \n", + "array([-89.95, -89.85, -89.75, ..., 89.75, 89.85, 89.95], dtype=float32)\n", + "Attributes:\n", + " DimensionNames: lat\n", + " Units: degrees_north\n", + " units: degrees_north\n", + " standard_name: latitude\n", + " LongName: Latitude at the center of\\n\\t\\t\\t0.10 degree grid interv...\n", + " bounds: lat_bnds\n", + " axis: Y\n", + " origname: lat\n", + " fullnamepath: /Grid/lat, 'latv': \n", + "array([0, 1], dtype=int32)\n", + "Attributes:\n", + " DimensionNames: latv\n", + " standard_name: numberlatbnds\n", + " LongName: Number of latitude bounds., 'lon': \n", + "array([-179.95 , -179.85 , -179.75 , ..., 179.75 , 179.84999,\n", + " 179.95 ], dtype=float32)\n", + "Attributes:\n", + " DimensionNames: lon\n", + " Units: degrees_east\n", + " units: degrees_east\n", + " standard_name: longitude\n", + " LongName: Longitude at the center of\\n\\t\\t\\t0.10 degree grid inter...\n", + " bounds: lon_bnds\n", + " axis: X\n", + " origname: lon\n", + " fullnamepath: /Grid/lon, 'lonv': \n", + "array([0, 1], dtype=int32)\n", + "Attributes:\n", + " DimensionNames: lonv\n", + " standard_name: numberlonbnds\n", + " LongName: Number of longitude bounds., 'nv': \n", + "array([0, 1], dtype=int32)\n", + "Attributes:\n", + " DimensionNames: nv\n", + " standard_name: numbertimebnds\n", + " LongName: Number of time bounds., 'time': \n", + "array([cftime.DatetimeJulian(2024, 1, 1, 0, 0, 0, 0, has_year_zero=False)],\n", + " dtype=object)\n", + "Attributes:\n", + " DimensionNames: time\n", + " Units: seconds since 1980-01-06 00:00:00 UTC\n", + " standard_name: time\n", + " LongName: \\nRepresentative time of data in \\n\\t\\t\\tseconds since 1...\n", + " bounds: time_bnds\n", + " axis: T\n", + " origname: time\n", + " fullnamepath: /Grid/time})\n" + ] + } + ], + "source": [ + "file = '../../data/GPM/2024/3B-HHR.MS.MRG.3IMERG.20240101-S000000-E002959.0000.V07B.nc'\n", + "\n", + "data = xr.open_dataset(file)\n", + "lats = data['lat'].values\n", + "lons = data['lon'].values\n", + "precipitation = data['precipitation'].values[0] # Assuming time is the first dimension\n", + "print('precipitation.shape:', precipitation.shape)\n", + "\n", + "print(data.variables)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(3600, 1800)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data.precipitation[0].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "((3599,), (3600,))" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "lons[:-1].shape, lons[:].shape" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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+       "    LongName:        Number of latitude bounds.
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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "times=np.linspace(0, 1, 251)\n", + "freqs=np.linspace(0, 22050, 287)\n", + "amplitudes = 1+np.sin(freqs[None,1:]*1e-4)+times[1:,None]\n", + "\n", + "print(freqs.shape, times.shape, amplitudes.shape)\n", + "\n", + "plt.figure(figsize=(10, 4))\n", + "# plt.pcolormesh(times, freqs, amplitudes, shading='auto')\n", + "\n", + "Y,X=np.meshgrid(freqs, times)\n", + "plt.pcolormesh(X, Y, amplitudes, shading='auto')\n", + "print(Y.shape, X.shape, amplitudes.shape)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# References\n", + "- [GPM Portal](https://gpm.nasa.gov/data/imerg)\n", + "- [pcolormesh (documentation)](https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.pcolormesh.html)\n", + "- [GPM IMERG (github repo)](https://github.com/aus-ref-clim-data-nci/GPM)\n", + "- [IMERG.ipynb](https://colab.research.google.com/drive/1FcN0dNlGiuguGZu-QMUTxqLunjR0UhZD?usp=sharing)\n", + "- [GPM_IMERG_30min_Rainfall.ipynb](https://colab.research.google.com/drive/1VIKun8K3RT8VvcPJ7DE5uDDC10i10k1T?usp=sharing#scrollTo=Mo8QqT84uqQU)\n", + "- [Interactive representation of IMERG Precipitation with Python over Germany](https://github.com/SaulMontoya/Interactive-representation-of-IMERG-Precipitation-with-Python-over-Germany)\n", + "- https://www.heywhale.com/mw/notebook/646e0ef8bf6378dc9094c10f\n", + "- [Download GPM IMERG 30-min Rainfall Data in netCDF format using Python (part 2)](https://www.youtube.com/watch?v=T_Us4hJxSeI) \n", + "- [How To Access Data With cURL And Wget](https://urs.earthdata.nasa.gov/documentation/for_users/data_access/curl_and_wget)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading file 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To keep the current behavior (and make this warning disappear) use `import imageio.v2 as imageio` or call `imageio.v2.imread` directly.\n", + " writer.append_data(imageio.imread(frame))\n", + "IMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (1000, 600) to (1008, 608) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Animation saved as ./imerg_rio_animation.mp4\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import os\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import cartopy.crs as ccrs\n", + "import cartopy.feature as cfeature\n", + "import xarray as xr\n", + "import imageio\n", + "\n", + "def create_imerg_animation(input_dir, output_file):\n", + " # Ensure the output directory exists\n", + " os.makedirs(os.path.dirname(output_file), exist_ok=True)\n", + "\n", + " # Get all NetCDF files in the input directory\n", + " files = sorted([os.path.join(input_dir, f) for f in os.listdir(input_dir) if f.endswith('.nc')])\n", + " if not files:\n", + " print(\"No IMERG NetCDF files found in the input directory.\")\n", + " return\n", + "\n", + " # List to store temporary frame files\n", + " frames = []\n", + "\n", + " # Define Rio de Janeiro bounding box\n", + " # rio_lon_min, rio_lon_max = -44.5, -42.5\n", + " # rio_lat_min, rio_lat_max = -23.5, -22.5\n", + " rio_lon_min, rio_lon_max = -45.05290312102409, -42.35676996062447\n", + " rio_lat_min, rio_lat_max = -23.801876626302175, -21.699774257353113\n", + "\n", + " # Create a figure for visualization\n", + " fig, ax = plt.subplots(subplot_kw={'projection': ccrs.PlateCarree()}, figsize=(10, 6))\n", + "\n", + " for file in files:\n", + " # Load data from NetCDF\n", + " print(f'Loading file {file}')\n", + " data = xr.open_dataset(file)\n", + " lats = data['lat'].values\n", + " lons = data['lon'].values\n", + " precipitation = data['precipitation'].values[0] # Assuming time is the first dimension\n", + "\n", + " # Filter data for the Rio de Janeiro region\n", + " lat_mask = (lats >= rio_lat_min) & (lats <= rio_lat_max)\n", + " lon_mask = (lons >= rio_lon_min) & (lons <= rio_lon_max)\n", + " lats_region = lats[lat_mask]\n", + " lons_region = lons[lon_mask]\n", + " precipitation_region = precipitation[np.ix_(lat_mask, lon_mask)]\n", + "\n", + " # Plot data\n", + " ax.clear()\n", + " ax.set_extent([rio_lon_min, rio_lon_max, rio_lat_min, rio_lat_max], crs=ccrs.PlateCarree())\n", + " ax.add_feature(cfeature.COASTLINE)\n", + " ax.add_feature(cfeature.BORDERS, linestyle=':')\n", + " ax.add_feature(cfeature.LAND, edgecolor='black')\n", + "\n", + " X, Y = np.meshgrid(lons_region, lats_region)\n", + " im = ax.pcolormesh(X, Y, precipitation_region, transform=ccrs.PlateCarree(), cmap='coolwarm')\n", + "\n", + " # plt.colorbar(im, ax=ax, orientation='horizontal', pad=0.05, label=\"Precipitation (mm/h)\")\n", + " plt.title(f\"GPM IMERG: {data.time.values[0]}\")\n", + "\n", + " # Save the frame\n", + " frame_file = f\"frame_{len(frames):04d}.png\"\n", + " plt.savefig(frame_file)\n", + " frames.append(frame_file)\n", + "\n", + " # Close the dataset to save memory\n", + " data.close()\n", + "\n", + " # Create MP4 animation using imageio\n", + " with imageio.get_writer(output_file, fps=2) as writer:\n", + " for frame in frames:\n", + " writer.append_data(imageio.imread(frame))\n", + "\n", + " # Clean up temporary frames\n", + " for frame in frames:\n", + " os.remove(frame)\n", + "\n", + " print(f\"Animation saved as {output_file}\")\n", + "\n", + "# Example usage\n", + "# input_directory = \"../../data/GPM/2024/01/13\"\n", + "# input_directory = \"../../data/GPM/2021/12/26\"\n", + "input_directory = \"../../data/GPM/2021/12/17\"\n", + "output_animation = \"./imerg_rio_animation.mp4\"\n", + "create_imerg_animation(input_directory, output_animation)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/MSWEP.ipynb b/notebooks/MSWEP.ipynb index e808e09e..245dc3c7 100644 --- a/notebooks/MSWEP.ipynb +++ b/notebooks/MSWEP.ipynb @@ -1,5 +1,15 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "0c587567", + "metadata": {}, + "source": [ + "See https://www.gloh2o.org/mswep/\n", + "\n", + "> MSWEP is a global precipitation product with a 3‑hourly 0.1° resolution available from 1979 to ~3 hours from real-time. The product is unique in that it merges gauge, satellite, and reanalysis data to obtain the highest quality precipitation estimates at every location." + ] + }, { "cell_type": "code", "execution_count": 2, diff --git a/notebooks/OR_ABI-L2-DSIF-M6_G16_s20220011800205_e20220011809513_c20220011811583.nc b/notebooks/OR_ABI-L2-DSIF-M6_G16_s20220011800205_e20220011809513_c20220011811583.nc deleted file mode 100644 index 4681024e..00000000 Binary files a/notebooks/OR_ABI-L2-DSIF-M6_G16_s20220011800205_e20220011809513_c20220011811583.nc and /dev/null differ diff --git a/notebooks/corrdiff.ipynb b/notebooks/corrdiff.ipynb new file mode 100644 index 00000000..7ce05243 --- /dev/null +++ b/notebooks/corrdiff.ipynb @@ -0,0 +1,169 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 5, + "id": "65219352", + "metadata": {}, + "outputs": [], + "source": [ + "import zarr\n", + "import numpy as np\n", + "\n", + "z = zarr.open(\n", + " \"/home/sangonvi/Cefet/repositories/atmoseer/datasets/corrdiff/train.zarr\",\n", + " mode=\"r\"\n", + ")\n", + "\n", + "y = z[\"target\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c65a8ea3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "global min 0.0\n", + "global max 3.8286414\n", + "global mean 0.092193365\n" + ] + } + ], + "source": [ + "print(\"global min\", np.min(y))\n", + "print(\"global max\", np.max(y))\n", + "print(\"global mean\", np.mean(y))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "8c9464c1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "patches > 5 dBZ : 6884\n", + "patches > 20 dBZ: 6819\n", + "total: 15924\n" + ] + } + ], + "source": [ + "count5 = 0\n", + "count20 = 0\n", + "\n", + "for i in range(len(y)):\n", + "\n", + " patch = np.expm1(y[i])\n", + "\n", + " if patch.max() > 5:\n", + " count5 += 1\n", + "\n", + " if patch.max() > 20:\n", + " count20 += 1\n", + "\n", + "print(\"patches > 5 dBZ :\", count5)\n", + "print(\"patches > 20 dBZ:\", count20)\n", + "print(\"total:\", len(y))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "3ed93926", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "global max: 3.8286414\n", + "global mean: 0.092193365\n", + "max expm1: 45.0\n" + ] + } + ], + "source": [ + "import zarr\n", + "import numpy as np\n", + "\n", + "z = zarr.open(\n", + " \"/home/sangonvi/Cefet/repositories/atmoseer/datasets/corrdiff/train.zarr\",\n", + " mode=\"r\"\n", + ")\n", + "\n", + "y = z[\"target\"]\n", + "\n", + "print(\"global max:\", np.max(y))\n", + "print(\"global mean:\", np.mean(y))\n", + "print(\n", + " \"max expm1:\",\n", + " np.expm1(np.max(y))\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "13167962", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "max dBZ: 45.0\n", + "mean dBZ: 0.7173415\n", + "fraction rainy: 0.02834643757064808\n", + "fraction strong: 0.027969586492872393\n" + ] + } + ], + "source": [ + "y_dbz = np.expm1(y)\n", + "\n", + "print(\"max dBZ:\", y_dbz.max())\n", + "print(\"mean dBZ:\", y_dbz.mean())\n", + "\n", + "print(\n", + " \"fraction rainy:\",\n", + " np.mean(y_dbz > 5)\n", + ")\n", + "\n", + "print(\n", + " \"fraction strong:\",\n", + " np.mean(y_dbz > 20)\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.15" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/corrdiffDataset.ipynb b/notebooks/corrdiffDataset.ipynb new file mode 100644 index 00000000..6f0b3355 --- /dev/null +++ b/notebooks/corrdiffDataset.ipynb @@ -0,0 +1,659 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "1ed48bce", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "import glob\n", + "from scipy.interpolate import griddata\n", + "from datetime import datetime\n", + "import math\n", + "import pandas as pd\n", + "import numpy as np\n", + "from pathlib import Path\n", + "import glob\n", + "from scipy.interpolate import griddata\n", + "import os\n", + "from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor, as_completed\n", + "from scipy.interpolate import griddata\n", + "from PIL import Image\n" + ] + }, + { + "cell_type": "markdown", + "id": "e9bd3459", + "metadata": {}, + "source": [ + "CONFIG\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "993f2194", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# CONFIG\n", + "ERA5_PATH = Path(\"/home/sangonvi/Cefet/repositories/atmoseer/data/reanalysis/cds/era5/pressure\")\n", + "RADAR_PATH = Path(\"/home/sangonvi/Cefet/repositories/atmoseer/data/radar_sumare\")\n", + "RADAR_CACHE = Path(\"radar_cache\")\n", + "\n", + "RADAR_RES_KM = 2\n", + "ERA5_RES_DEG = 0.25\n", + "ONE_DEG_LATLON_IN_KM = 111.32\n", + "\n", + "OUTPUT_DIR = Path(\"dataset\")\n", + "PATCH_SIZE = 32\n", + "STRIDE = 16\n", + "\n", + "TIME_START = \"2024-01-22\"\n", + "TIME_END = \"2024-01-23\"\n", + "\n", + "ERA5_VARS = [\"v\", \"u\"] # ajuste\n", + "\n", + "N_THREADS = 12 # I/O\n", + "N_PROCESSES = 6 # CPU (interpolação + patches)\n", + "\n", + "OUTPUT_DIR.mkdir(exist_ok=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "39ffab71", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/home/sangonvi/Cefet/repositories/atmoseer/data/radar_sumare\n", + "/home/sangonvi/Cefet/repositories/atmoseer/data/radar_sumare/2024/01/22/2024_01_22_00_00.png\n" + ] + } + ], + "source": [ + "print(str(RADAR_PATH))\n", + "print('/home/sangonvi/Cefet/repositories/atmoseer/data/radar_sumare/2024/01/22/2024_01_22_00_00.png')" + ] + }, + { + "cell_type": "markdown", + "id": "f6047223", + "metadata": {}, + "source": [ + "1. LOAD ERA5 (MULTI-MONTH)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "a4ff201f", + "metadata": {}, + "outputs": [], + "source": [ + "def load_era5_file(f):\n", + " df = pd.read_parquet(f)\n", + " if \"time\" not in df.columns:\n", + " df = df.reset_index()\n", + " \n", + " df[\"time\"] = pd.to_datetime(df[\"valid_time\"])\n", + " return df\n", + "\n", + "era5_files = list(ERA5_PATH.rglob(\"*.parquet\"))\n", + "with ThreadPoolExecutor(max_workers=N_THREADS) as ex:\n", + " dfs = list(ex.map(load_era5_file, era5_files))\n", + "\n", + "era5 = pd.concat(dfs, ignore_index=True)\n", + "era5 = era5.sort_values(\"time\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "160643af", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ERA5 loaded: (1050, 16)\n" + ] + } + ], + "source": [ + "era5[\"time\"] = pd.to_datetime(era5[\"valid_time\"])\n", + "\n", + "era5 = era5[\n", + " (era5[\"time\"] >= TIME_START) &\n", + " (era5[\"time\"] <= TIME_END)\n", + "]\n", + "\n", + "era5 = era5.sort_values(\"time\")\n", + "\n", + "print(\"ERA5 loaded:\", era5.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2e7a432c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['index', 'valid_time', 'pressure_level', 'latitude', 'longitude', 'u',\n", + " 'v', 'r', 'q', 't', 'w', 'crwc', 'number', 'expver', 'day', 'time'],\n", + " dtype='object')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "era5.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "5f6e3490", + "metadata": {}, + "outputs": [], + "source": [ + "def rgb_distance(c1, c2):\n", + " return math.sqrt((c1[0] - c2[0]) ** 2 + (c1[1] - c2[1]) ** 2 + (c1[2] - c2[2]) ** 2)\n", + "\n", + "\n", + "def interpolate_value(rgb, legend_colors, legend_values):\n", + " if rgb == (0, 0, 0):\n", + " return 0\n", + "\n", + " distances = [rgb_distance(rgb, lc) for lc in legend_colors]\n", + "\n", + " min_idx1 = distances.index(min(distances)) \n", + " distances[min_idx1] = float(\n", + " \"inf\"\n", + " ) \n", + " min_idx2 = distances.index(min(distances)) \n", + "\n", + " # Obter as cores e valores correspondentes\n", + " c1, c2 = legend_colors[min_idx1], legend_colors[min_idx2]\n", + " v1, v2 = legend_values[min_idx1], legend_values[min_idx2]\n", + "\n", + " # Calcular o peso de interpolação (t)\n", + " dist_c1_c2 = rgb_distance(c1, c2)\n", + " dist_c1_rgb = rgb_distance(c1, rgb)\n", + " t = dist_c1_rgb / dist_c1_c2 if dist_c1_c2 != 0 else 0\n", + "\n", + " # Interpolar o valor\n", + " interpolated_value = v1 + t * (v2 - v1)\n", + " return interpolated_value\n", + "\n", + "\n", + "def get_radar_data(inicio, fim, frequencia, latitude, longitude):\n", + " latitude = float(latitude)\n", + " longitude = float(longitude)\n", + "\n", + " pos_sumare = (-22.955139, -43.248278)\n", + " legend_values = [50, 45, 40, 35, 30, 25, 20, 0]\n", + " legend_colors = [\n", + " (197, 0, 197), # Magenta\n", + " (227, 6, 5), # Vermelho\n", + " (255, 112, 0), # Laranja\n", + " (195, 230, 0), # Amarelo\n", + " (4, 85, 4), # Amarelo\n", + " (19, 122, 19), # Verde escuro\n", + " (0, 167, 12), # Verde claro\n", + " (0, 0, 0), # Vazio\n", + " ]\n", + "\n", + " # Definir datas inicial e final\n", + " data_inicial = inicio + \" 00:00:00\"\n", + " data_final = fim + \" 00:00:00\"\n", + "\n", + " datas = pd.date_range(start=data_inicial, end=data_final, freq=frequencia)\n", + "\n", + " # Criar DataFrame com coluna \"datahora\"\n", + " radar_data = pd.DataFrame({\"time\": datas})\n", + " radar_data[\"reflect\"] = np.nan\n", + "\n", + " count = 0\n", + " while count < len(radar_data):\n", + " datetime_str = radar_data.iloc[count][\"time\"].strftime(\"%Y-%m-%d %H:%M:%S\")\n", + "\n", + " year = datetime_str[0:4]\n", + " month = datetime_str[5:7]\n", + " day = datetime_str[8:10]\n", + " hour = datetime_str[11:13]\n", + " minute = datetime_str[14:16]\n", + " file = year + \"_\" + month + \"_\" + day + \"_\" + hour + \"_\" + minute + \".png\"\n", + " file_path = str(RADAR_PATH) + \"/\" + year + \"/\" + month + \"/\" + day + \"/\" + file\n", + "\n", + " if os.path.exists(file_path):\n", + " try:\n", + " img = Image.open(file_path)\n", + " pos_sumare_img = (img.height / 2, img.width / 2)\n", + "\n", + " dify = pos_sumare_img[0] / pos_sumare[0]\n", + " difx = pos_sumare_img[1] / pos_sumare[1]\n", + "\n", + " posx = pos_sumare[1] - ((longitude - pos_sumare[1]) * 32.5)\n", + " valorx = posx * difx\n", + " posy = pos_sumare[0] + ((latitude - pos_sumare[0]) * 19.5)\n", + " valory = posy * dify\n", + "\n", + " rgb_im = img.convert(\"RGB\")\n", + " r, g, b = rgb_im.getpixel((valorx, valory))\n", + " radar_data.at[count, \"reflect\"] = interpolate_value((r, g, b), legend_colors, legend_values)\n", + " except Exception as e:\n", + " print(\"Mensagem de erro:\", str(e)) # como string\n", + "\n", + " count += 1\n", + "\n", + " return radar_data" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "e40b9c24", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Longitude points: [-44. -43.75 -43.5 -43.25 -43. -42.75 -42.5 ]\n", + "Latitude points: [-23.5 -23.25 -23. -22.75 -22.5 -22.25]\n", + "Radar lat/lon interval (degrees): 0.017966223499820338\n", + "Number of radar points - Latitude: 70 Longitude: 84\n" + ] + } + ], + "source": [ + "lon = np.sort(np.array(era5[\"longitude\"].unique()))\n", + "lat = np.sort(np.array(era5[\"latitude\"].unique()))\n", + "print(\"Longitude points:\", lon)\n", + "print(\"Latitude points:\", lat)\n", + "\n", + "Lon, Lat = np.meshgrid(lon, lat)\n", + "\n", + "radar_lat_lon_interval = RADAR_RES_KM / ONE_DEG_LATLON_IN_KM\n", + "print(\"Radar lat/lon interval (degrees):\", radar_lat_lon_interval)\n", + "number_lat_points = int((era5[\"latitude\"].max() - era5[\"latitude\"].min()) / radar_lat_lon_interval) + 1\n", + "number_lon_points = int((era5[\"longitude\"].max() - era5[\"longitude\"].min()) / radar_lat_lon_interval) + 1\n", + "print(\"Number of radar points - Latitude:\", number_lat_points, \"Longitude:\", number_lon_points)\n", + "\n", + "radar_lat = np.linspace(-23.5, -22.25, number_lat_points)\n", + "radar_lon = np.linspace(-44.0, -42.5, number_lon_points)\n", + "\n", + "RadarLon, RadarLat = np.meshgrid(radar_lon, radar_lat)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9b9596c5", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from pathlib import Path\n", + "from concurrent.futures import ThreadPoolExecutor, as_completed\n", + "import threading\n", + "\n", + "# =============================\n", + "# CONFIG\n", + "# =============================\n", + "CACHE_DIR = Path(\"radar_cache\")\n", + "CACHE_DIR.mkdir(exist_ok=True)\n", + "\n", + "MAX_WORKERS = 10 # ajuste (8–20 ideal)\n", + "\n", + "lock = threading.Lock()\n", + "counter = {\"done\": 0}\n", + "\n", + "# =============================\n", + "# CACHE PATH\n", + "# =============================\n", + "def get_cache_path(lat, lon):\n", + " return CACHE_DIR / f\"radar_lat_{lat:.4f}_lon_{lon:.4f}.parquet\"\n", + "\n", + "# =============================\n", + "# DOWNLOAD + CACHE\n", + "# =============================\n", + "def process_point(lat, lon):\n", + " path = get_cache_path(lat, lon)\n", + "\n", + " # -------------------------\n", + " # já existe → skip\n", + " # -------------------------\n", + " if path.exists():\n", + " with lock:\n", + " counter[\"done\"] += 1\n", + " print(f\"[{counter['done']}] CACHE OK ({lat:.3f}, {lon:.3f})\")\n", + " return (lat, lon, \"cached\")\n", + "\n", + " try:\n", + " # -------------------------\n", + " # download\n", + " # -------------------------\n", + " df = get_radar_data(inicio=TIME_START, fim=TIME_END, frequencia='2T',latitude=lat, longitude=lon)\n", + "\n", + " df[\"time\"] = pd.to_datetime(df[\"time\"])\n", + " df = df.set_index(\"time\")\n", + "\n", + " # agregação 2min → 1h\n", + " df = df.resample(\"1H\").max()\n", + "\n", + " # -------------------------\n", + " # salvar\n", + " # -------------------------\n", + " df.reset_index().to_parquet(path, compression=\"snappy\")\n", + "\n", + " with lock:\n", + " counter[\"done\"] += 1\n", + " print(f\"[{counter['done']}] DOWNLOADED ({lat:.3f}, {lon:.3f})\")\n", + "\n", + " return (lat, lon, \"downloaded\")\n", + "\n", + " except Exception as e:\n", + " with lock:\n", + " counter[\"done\"] += 1\n", + " print(f\"[{counter['done']}] ERROR ({lat:.3f}, {lon:.3f}) -> {e}\")\n", + " return (lat, lon, \"error\")\n", + "\n", + "# =============================\n", + "# PARALLEL EXECUTION\n", + "# =============================\n", + "print(\"🚀 Starting parallel radar download...\")\n", + "\n", + "tasks = [(lat, lon) for lat in radar_lat for lon in radar_lon]\n", + "total = len(tasks)\n", + "\n", + "print(f\"Total points: {total}\")\n", + "\n", + "results = []\n", + "\n", + "with ThreadPoolExecutor(max_workers=MAX_WORKERS) as executor:\n", + " futures = [executor.submit(process_point, lat, lon) for lat, lon in tasks]\n", + "\n", + " for future in as_completed(futures):\n", + " results.append(future.result())\n", + "\n", + "print(\"✅ Download finished\")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "aa90d21a", + "metadata": {}, + "outputs": [], + "source": [ + "def load_radar_cache_file(f):\n", + " df = pd.read_parquet(f)\n", + " df[\"time\"] = pd.to_datetime(df[\"time\"])\n", + " df = df.set_index(\"time\")\n", + " \n", + " # extrair lat/lon do nome\n", + " name = f.stem\n", + " parts = name.split(\"_\")\n", + " lat = float(parts[2])\n", + " lon = float(parts[4])\n", + " \n", + " return (lat, lon, df)\n", + "\n", + "files = list(RADAR_CACHE.glob(\"*.parquet\"))\n", + "\n", + "radar_data = {}\n", + "\n", + "with ThreadPoolExecutor(max_workers=N_THREADS) as ex:\n", + " for lat, lon, df in ex.map(load_radar_cache_file, files):\n", + " radar_data[(lat, lon)] = df" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "166127b2", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total de pontos no radar_data: 5880\n", + "Pontos válidos: 5880\n", + "Pontos inválidos: 0\n", + "Lat: -23.2464 Lon: -42.6627\n", + "Tipo: \n", + "Shape: (25, 1)\n", + "Colunas: Index(['reflect'], dtype='object')\n", + " reflect\n", + "time \n", + "2024-01-22 00:00:00 0.0\n", + "2024-01-22 01:00:00 0.0\n", + "2024-01-22 02:00:00 0.0\n", + "2024-01-22 03:00:00 0.0\n", + "2024-01-22 04:00:00 0.0\n" + ] + } + ], + "source": [ + "print(\"Total de pontos no radar_data:\", len(radar_data))\n", + "valid = sum(1 for v in radar_data.values() if v is not None)\n", + "invalid = sum(1 for v in radar_data.values() if v is None)\n", + "\n", + "print(\"Pontos válidos:\", valid)\n", + "print(\"Pontos inválidos:\", invalid)\n", + "\n", + "for (lat, lon), df in radar_data.items():\n", + " print(\"Lat:\", lat, \"Lon:\", lon)\n", + " print(\"Tipo:\", type(df))\n", + " \n", + " if df is not None:\n", + " print(\"Shape:\", df.shape)\n", + " print(\"Colunas:\", df.columns)\n", + " print(df.head())\n", + " else:\n", + " print(\"Sem dados\")\n", + " \n", + " break # só um exemplo\n", + "\n", + "values = []\n" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "6eff9a73", + "metadata": {}, + "outputs": [], + "source": [ + "def process_time_step(t):\n", + " era5_t = era5[era5[\"time\"] == t]\n", + " \n", + " if len(era5_t) == 0:\n", + " return None\n", + " \n", + " try:\n", + " points = era5_t[[\"latitude\", \"longitude\"]].values\n", + " \n", + " channels = []\n", + " for var in ERA5_VARS:\n", + " values = era5_t[var].values\n", + " \n", + " interp = griddata(\n", + " points,\n", + " values,\n", + " (RadarLat, RadarLon),\n", + " method=\"linear\"\n", + " )\n", + " channels.append(interp)\n", + " \n", + " X_t = np.stack(channels, axis=0)\n", + " \n", + " # radar grid\n", + " Y_t = np.full(RadarLat.shape, np.nan)\n", + " \n", + " for i, lat in enumerate(radar_lat):\n", + " for j, lon in enumerate(radar_lon):\n", + " df = radar_data.get((lat, lon))\n", + " \n", + " if df is not None and t in df.index:\n", + " Y_t[i, j] = df.loc[t].values[0]\n", + " \n", + " if np.isnan(Y_t).all():\n", + " return None\n", + " \n", + " return (t, X_t, Y_t)\n", + " \n", + " except:\n", + " return None" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "cf79c2b6", + "metadata": {}, + "outputs": [], + "source": [ + "times = sorted(era5[\"time\"].unique())\n", + "results = []\n", + "\n", + "with ProcessPoolExecutor(max_workers=N_PROCESSES) as ex:\n", + " futures = [ex.submit(process_time_step, t) for t in times]\n", + " \n", + " for f in as_completed(futures):\n", + " r = f.result()\n", + " if r is not None:\n", + " results.append(r)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b54bc714", + "metadata": {}, + "outputs": [], + "source": [ + "def create_patches(sample):\n", + " t, X_t, Y_t = sample\n", + " \n", + " patches = []\n", + " \n", + " H, W = Y_t.shape\n", + " \n", + " for i in range(0, H - PATCH_SIZE + 1, STRIDE):\n", + " for j in range(0, W - PATCH_SIZE + 1, STRIDE):\n", + " \n", + " xp = X_t[:, i:i+PATCH_SIZE, j:j+PATCH_SIZE]\n", + " yp = Y_t[i:i+PATCH_SIZE, j:j+PATCH_SIZE]\n", + " \n", + " valid_ratio = np.mean(~np.isnan(yp))\n", + "\n", + " if valid_ratio < 0.3:\n", + " continue\n", + "\n", + " mask = ~np.isnan(yp)\n", + " yp = np.nan_to_num(yp, nan=0.0)\n", + " \n", + " \n", + " patches.append((xp, yp))\n", + " \n", + " return patches" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "56b6d591", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"Building dataset...\")\n", + "\n", + "times = sorted(era5[\"time\"].unique())\n", + "\n", + "sample_id = 0\n", + "\n", + "for t in times:\n", + " print(\"Time:\", t)\n", + "\n", + " era5_t = era5[era5[\"time\"] == t]\n", + "\n", + " if len(era5_t) == 0:\n", + " continue\n", + "\n", + " X_t = interpolate_fast(era5_t)\n", + " Y_t = build_radar_grid(t)\n", + "\n", + " if np.isnan(Y_t).all():\n", + " continue\n", + "\n", + " H, W = Y_t.shape\n", + "\n", + " for i in range(0, H - PATCH_SIZE + 1, STRIDE):\n", + " for j in range(0, W - PATCH_SIZE + 1, STRIDE):\n", + "\n", + " xp = X_t[:, i:i+PATCH_SIZE, j:j+PATCH_SIZE]\n", + " yp = Y_t[i:i+PATCH_SIZE, j:j+PATCH_SIZE]\n", + "\n", + " valid_ratio = np.mean(~np.isnan(yp))\n", + "\n", + " if valid_ratio < 0.3:\n", + " continue\n", + "\n", + " mask = ~np.isnan(yp)\n", + " yp = np.nan_to_num(yp, nan=0.0)\n", + "\n", + " np.savez_compressed(\n", + " OUTPUT_DIR / \"train\" / f\"sample_{sample_id:06d}.npz\",\n", + " input=xp.astype(np.float32),\n", + " target=yp[None, ...].astype(np.float32),\n", + " mask=mask[None, ...].astype(np.float32)\n", + " )\n", + "\n", + " sample_id += 1\n", + "\n", + "print(\"Dataset ready:\", sample_id)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.15" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/elevation.ipynb b/notebooks/elevation.ipynb new file mode 100644 index 00000000..53602125 --- /dev/null +++ b/notebooks/elevation.ipynb @@ -0,0 +1,217 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Code adapted from [Visualizing elevation contours from raster digital elevation models in Python](https://www.earthdatascience.org/tutorials/visualize-digital-elevation-model-contours-matplotlib/)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Collecting elevation\n", + " Downloading elevation-1.1.3-py3-none-any.whl (16 kB)\n", + "Requirement already satisfied: click in /home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages (from elevation) (8.1.3)\n", + "Collecting fasteners\n", + " Downloading fasteners-0.19-py3-none-any.whl (18 kB)\n", + "Collecting appdirs\n", + " Downloading appdirs-1.4.4-py2.py3-none-any.whl (9.6 kB)\n", + "Installing collected packages: appdirs, fasteners, elevation\n", + "Successfully installed appdirs-1.4.4 elevation-1.1.3 fasteners-0.19\n", + "Note: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "#pip install elevation" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "About the --bounds option:\n", + "`--bounds `\n", + "\n", + "Where:\n", + "- min_longitude: The westernmost boundary (left).\n", + "- min_latitude: The southernmost boundary (bottom).\n", + "- max_longitude: The easternmost boundary (right).\n", + "- max_latitude: The northernmost boundary (top).\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Provided bounds for Rio de Janeiro's metropolitan area:\n", + "\n", + "- n_bound (north boundary) = -22.649724748272934\n", + "- s_bound (south boundary) = -23.1339033365138\n", + "- e_bound (east boundary) = -43.04835145732227\n", + "- w_bound (west boundary) = -43.8906028271505\n", + "\n", + "To call the command using the provided bounds, we should pass the coordinates in the correct order (min_longitude, min_latitude, max_longitude, max_latitude):" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "make: Entering directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "make: Nothing to be done for 'download'.\n", + "make: Leaving directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "make: Entering directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "make: Nothing to be done for 'all'.\n", + "make: Leaving directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "make: Entering directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "cp SRTM1.vrt SRTM1.f6ee03340caa4a90bde2f30e7b343b52.vrt\n", + "make: Leaving directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "make: Entering directory '/home/ebezerra/.cache/elevation/SRTM1'\n", + "gdal_translate -q -co TILED=YES -co COMPRESS=DEFLATE -co ZLEVEL=9 -co PREDICTOR=2 -projwin -43.8906028271505 -22.649724748272934 -43.04835145732227 -23.1339033365138 SRTM1.f6ee03340caa4a90bde2f30e7b343b52.vrt /home/ebezerra/ailab/atmoseer/notebooks/RJ-30m-DEM.tif\n", + "rm -f SRTM1.f6ee03340caa4a90bde2f30e7b343b52.vrt\n", + "make: Leaving directory '/home/ebezerra/.cache/elevation/SRTM1'\n" + ] + } + ], + "source": [ + "#eio clip -o RJ-30m-DEM.tif --bounds -43.8906028271505 -23.1339033365138 -43.04835145732227 -22.649724748272934" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "from osgeo import gdal\n", + "import numpy as np\n", + "import matplotlib \n", + "import matplotlib.pyplot as plt\n", + "import elevation " + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "filename = \"RJ-30m-DEM.tif\"\n", + "gdal_data = gdal.Open(filename)\n", + "gdal_band = gdal_data.GetRasterBand(1)\n", + "nodataval = gdal_band.GetNoDataValue()\n", + "\n", + "# convert to a numpy array\n", + "data_array = gdal_data.ReadAsArray().astype(float)\n", + "data_array\n", + "\n", + "# replace missing values if necessary\n", + "if np.any(data_array == nodataval):\n", + " data_array[data_array == nodataval] = np.nan" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "filename = \"RJ-30m-DEM.tif\"\n", + "gdal_data = gdal.Open(filename)\n", + "gdal_band = gdal_data.GetRasterBand(1)\n", + "nodataval = gdal_band.GetNoDataValue()\n", + "\n", + "# convert to a numpy array\n", + "data_array = gdal_data.ReadAsArray().astype(float)\n", + "\n", + "# replace missing values if necessary\n", + "if np.any(data_array == nodataval):\n", + " data_array[data_array == nodataval] = np.nan\n", + "\n", + "# Plot data with Matplotlib's 'contour'\n", + "fig = plt.figure(figsize=(12, 8))\n", + "ax = fig.add_subplot(111)\n", + "# Reverse the y-axis by using origin='upper'\n", + "plt.contour(data_array, cmap=\"viridis\", \n", + " levels=list(range(0, 2000, 50)), origin='upper')\n", + "plt.title(\"Elevation Contours of Rio de Janeiro\")\n", + "cbar = plt.colorbar()\n", + "plt.gca().set_aspect('equal', adjustable='box')\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Plot our data with Matplotlib's 'contourf'\n", + "fig = plt.figure(figsize = (12, 8))\n", + "ax = fig.add_subplot(111)\n", + "plt.contourf(data_array, cmap = \"viridis\", \n", + " levels = list(range(0, 2000, 50)), origin='upper')\n", + "plt.title(\"Elevation Contours of Rio de Janeiro\")\n", + "cbar = plt.colorbar()\n", + "plt.gca().set_aspect('equal', adjustable='box')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.19" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/exemplo.ipynb b/notebooks/exemplo.ipynb new file mode 100644 index 00000000..b30eb6e0 --- /dev/null +++ b/notebooks/exemplo.ipynb @@ -0,0 +1,1609 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "\n", + "import numpy as np\n", + "import pandas as pd\n", + "import xarray as xr" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Created Dataset:\n", + "10\n", + "10\n", + "(10, 5, 3, 4, 4)\n" + ] + }, + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
<xarray.DataArray 'y' (sample: 10, timestep: 5, lat: 3, lon: 4, channel: 4)> Size: 19kB\n",
+       "array([[[[[6.17795238e-01, 6.05669808e-01, 4.06707415e-01,\n",
+       "           2.95968217e-01],\n",
+       "          [6.42861067e-01, 3.65159698e-01, 9.15169225e-01,\n",
+       "           5.47648160e-01],\n",
+       "          [2.62961381e-01, 7.39297870e-01, 8.42019937e-01,\n",
+       "           6.80079018e-01],\n",
+       "          [4.93129346e-01, 3.83537189e-01, 7.24067927e-01,\n",
+       "           9.83109803e-01]],\n",
+       "\n",
+       "         [[6.45632827e-01, 3.87354429e-01, 3.75760372e-01,\n",
+       "           5.98634496e-02],\n",
+       "          [4.92354256e-01, 5.51777235e-02, 8.02497293e-01,\n",
+       "           2.26092441e-01],\n",
+       "          [2.12000698e-01, 1.78374240e-01, 5.72540290e-01,\n",
+       "           3.15224702e-01],\n",
+       "          [6.95656135e-01, 4.93868324e-01, 2.26080912e-01,\n",
+       "           7.68289127e-01]],\n",
+       "\n",
+       "         [[9.78097203e-02, 3.00242458e-01, 7.94940454e-02,\n",
+       "           7.21689648e-01],\n",
+       "...\n",
+       "          [7.98508500e-01, 5.44418693e-01, 3.33009094e-01,\n",
+       "           1.53365312e-01]],\n",
+       "\n",
+       "         [[5.63192085e-01, 2.00951978e-01, 6.55852894e-01,\n",
+       "           5.96269630e-01],\n",
+       "          [2.01135929e-01, 3.03287417e-02, 5.51503945e-01,\n",
+       "           4.69874328e-01],\n",
+       "          [1.22568823e-02, 7.85605355e-01, 4.82381509e-01,\n",
+       "           1.43895834e-01],\n",
+       "          [3.33124146e-01, 5.35878359e-01, 6.16718274e-01,\n",
+       "           9.27935681e-01]],\n",
+       "\n",
+       "         [[4.73561234e-01, 3.01044764e-01, 5.78551808e-01,\n",
+       "           3.82819929e-02],\n",
+       "          [7.84580031e-01, 8.22955743e-01, 2.08341661e-01,\n",
+       "           1.92762099e-01],\n",
+       "          [7.24726633e-01, 3.12273982e-01, 2.89708719e-01,\n",
+       "           1.02207054e-01],\n",
+       "          [9.19865111e-01, 2.74223920e-01, 7.41525514e-01,\n",
+       "           9.58186219e-01]]]]])\n",
+       "Coordinates:\n",
+       "  * sample    (sample) int64 80B 0 1 2 3 4 5 6 7 8 9\n",
+       "  * timestep  (timestep) int64 40B 0 1 2 3 4\n",
+       "  * lat       (lat) float64 24B -90.0 0.0 90.0\n",
+       "  * lon       (lon) float64 32B -180.0 -60.0 60.0 180.0\n",
+       "  * channel   (channel) int64 32B 0 1 2 3
" + ], + "text/plain": [ + " Size: 19kB\n", + "array([[[[[6.17795238e-01, 6.05669808e-01, 4.06707415e-01,\n", + " 2.95968217e-01],\n", + " [6.42861067e-01, 3.65159698e-01, 9.15169225e-01,\n", + " 5.47648160e-01],\n", + " [2.62961381e-01, 7.39297870e-01, 8.42019937e-01,\n", + " 6.80079018e-01],\n", + " [4.93129346e-01, 3.83537189e-01, 7.24067927e-01,\n", + " 9.83109803e-01]],\n", + "\n", + " [[6.45632827e-01, 3.87354429e-01, 3.75760372e-01,\n", + " 5.98634496e-02],\n", + " [4.92354256e-01, 5.51777235e-02, 8.02497293e-01,\n", + " 2.26092441e-01],\n", + " [2.12000698e-01, 1.78374240e-01, 5.72540290e-01,\n", + " 3.15224702e-01],\n", + " [6.95656135e-01, 4.93868324e-01, 2.26080912e-01,\n", + " 7.68289127e-01]],\n", + "\n", + " [[9.78097203e-02, 3.00242458e-01, 7.94940454e-02,\n", + " 7.21689648e-01],\n", + "...\n", + " [7.98508500e-01, 5.44418693e-01, 3.33009094e-01,\n", + " 1.53365312e-01]],\n", + "\n", + " [[5.63192085e-01, 2.00951978e-01, 6.55852894e-01,\n", + " 5.96269630e-01],\n", + " [2.01135929e-01, 3.03287417e-02, 5.51503945e-01,\n", + " 4.69874328e-01],\n", + " [1.22568823e-02, 7.85605355e-01, 4.82381509e-01,\n", + " 1.43895834e-01],\n", + " [3.33124146e-01, 5.35878359e-01, 6.16718274e-01,\n", + " 9.27935681e-01]],\n", + "\n", + " [[4.73561234e-01, 3.01044764e-01, 5.78551808e-01,\n", + " 3.82819929e-02],\n", + " [7.84580031e-01, 8.22955743e-01, 2.08341661e-01,\n", + " 1.92762099e-01],\n", + " [7.24726633e-01, 3.12273982e-01, 2.89708719e-01,\n", + " 1.02207054e-01],\n", + " [9.19865111e-01, 2.74223920e-01, 7.41525514e-01,\n", + " 9.58186219e-01]]]]])\n", + "Coordinates:\n", + " * sample (sample) int64 80B 0 1 2 3 4 5 6 7 8 9\n", + " * timestep (timestep) int64 40B 0 1 2 3 4\n", + " * lat (lat) float64 24B -90.0 0.0 90.0\n", + " * lon (lon) float64 32B -180.0 -60.0 60.0 180.0\n", + " * channel (channel) int64 32B 0 1 2 3" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "samples = 10\n", + "timesteps = 5 # or window length\n", + "latitudes = 3\n", + "longitudes = 4\n", + "channels = 4\n", + "\n", + "lat = np.linspace(-90, 90, latitudes)\n", + "lon = np.linspace(-180, 180, longitudes)\n", + "sample = np.arange(samples)\n", + "timestep = np.arange(timesteps)\n", + "channel = np.arange(channels)\n", + "\n", + "x_data = np.random.rand(samples, timesteps, latitudes, longitudes, channels)\n", + "y_data = np.random.rand(samples, timesteps, latitudes, longitudes, channels)\n", + "\n", + "ds = xr.Dataset(\n", + " {\n", + " \"x\": ([\"sample\", \"timestep\", \"lat\", \"lon\", \"channel\"], x_data),\n", + " \"y\": ([\"sample\", \"timestep\", \"lat\", \"lon\", \"channel\"], y_data),\n", + " },\n", + " coords={\"sample\": sample, \"timestep\": timestep, \"lat\": lat, \"lon\": lon, \"channel\": channel},\n", + ")\n", + "\n", + "print(\"Created Dataset:\")\n", + "# ds.to_netcdf(\"output_dataset.nc\")\n", + "# loaded_ds = xr.load_dataset(\"output_dataset.nc\")\n", + "# print(\"\\nLoaded Dataset from NetCDF:\\n\", loaded_ds)\n", + "# nparrayresult = ds.to_array()\n", + "# nparrayresult.shape\n", + "print(len(ds.y))\n", + "print(len(ds.x))\n", + "print(ds.y.values.shape)\n", + "ds.y" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Criando de forma dinamica, como ocorre no spatiotemporal_builder, código abaixo: " + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(2, 2, 1)" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.array([[[1], [2]], [[3], [4]]]).shape" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a.shape: (2, 2)\n", + "b.shape: (2, 2)\n", + "c.shape: (2, 2)\n", + "\n", + " data.shape: (3, 2, 2)\n", + " window length or timesteps: 3\n", + " lat: 2\n", + " lon: 2\n", + " No channel dimension yet\n", + "\n", + "np.array_equal(data_reshape, data_expand_dims): True\n", + "\n", + " data_reshape.shape: (3, 2, 2, 1)\n", + " window length or timesteps: 3\n", + " lat: 2\n", + " lon: 2\n", + " channel: 1, now we have the channel dimension\n", + "\n", + "\n", + " data.shape: (1, 3, 2, 2, 1)\n", + " Samples: 1\n", + " window length or timesteps: 3\n", + " lat: 2\n", + " lon: 2\n", + " channel: 1\n", + "\n" + ] + } + ], + "source": [ + "CHANNEL = 1\n", + "\n", + "a = np.array([[1, 2], [3, 4]])\n", + "b = np.array([[5, 6], [7, 8]])\n", + "c = np.array([[9, 10], [11, 12]])\n", + "data = np.stack([a, b, c], axis=0)\n", + "\n", + "print(f\"a.shape: {a.shape}\")\n", + "print(f\"b.shape: {b.shape}\")\n", + "print(f\"c.shape: {c.shape}\")\n", + "print(f\"\"\"\n", + " data.shape: {data.shape}\n", + " window length or timesteps: {data.shape[0]}\n", + " lat: {data.shape[1]}\n", + " lon: {data.shape[2]}\n", + " No channel dimension yet\n", + "\"\"\")\n", + "\n", + "# Como o channel é 1 precisamos dar um reshape pra transofmarr [[1, 2], [3, 4]] em [[[1], [2]], [[3], [4]]]\n", + "# podemos fazer com reshape ou expand_dims\n", + "data_reshape = data.reshape(data.shape[0], data.shape[1], data.shape[2], CHANNEL)\n", + "data_expand_dims = np.expand_dims(data, axis=-1)\n", + "print(\n", + " f\"np.array_equal(data_reshape, data_expand_dims): {np.array_equal(data_reshape, data_expand_dims)}\"\n", + ")\n", + "print(f\"\"\"\n", + " data_reshape.shape: {data_reshape.shape}\n", + " window length or timesteps: {data_reshape.shape[0]}\n", + " lat: {data_reshape.shape[1]}\n", + " lon: {data_reshape.shape[2]}\n", + " channel: {data_reshape.shape[3]}, now we have the channel dimension\n", + "\"\"\")\n", + "# A primeiras versão do WebsirenesDataset.py executas as linhas comentadas abaixo:\n", + "# data = np.stack(timesteps, axis=0)\n", + "# data = data.reshape(data.shape[0], data.shape[1], data.shape[2], channel)\n", + "# return data\n", + "\n", + "# o proximo passo é adicionar essa amostra de 3 timesteps 2x2x1 em um array de amostras\n", + "# nesse caso temos 1 amostra\n", + "data = np.stack([data_reshape], axis=0)\n", + "print(f\"\"\"\n", + " data.shape: {data.shape}\n", + " Samples: {data.shape[0]}\n", + " window length or timesteps: {data.shape[1]}\n", + " lat: {data.shape[2]}\n", + " lon: {data.shape[3]}\n", + " channel: {data.shape[4]}\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Agora vamos criar um exemplo com 2 amostras, 9 latitudes por 11 longitudes e channel 3, por exemplo, temperatura no indice 0, precipitação no indice 1 e umidade no indice 2 do channel" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(9,)\n", + "(11,)\n" + ] + } + ], + "source": [ + "lats = np.array([-21.8, -22.05, -22.3, -22.55, -22.8, -23.05, -23.3, -23.55, -23.8])\n", + "lons = np.array(\n", + " [\n", + " -45.053,\n", + " -44.8029,\n", + " -44.5528,\n", + " -44.3027,\n", + " -44.0526,\n", + " -43.8025,\n", + " -43.5524,\n", + " -43.3023,\n", + " -43.0522,\n", + " -42.8021,\n", + " -42.552,\n", + " ]\n", + ")\n", + "print(lats.shape)\n", + "print(lons.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sample1.shape: (5, 9, 11, 3)\n", + "sample2.shape: (5, 9, 11, 3)\n", + "data after stacking samples: (2, 5, 9, 11, 3)\n", + "Created Dataset:\n", + " Size: 24kB\n", + "Dimensions: (sample: 2, timestep: 5, lat: 9, lon: 11, channel: 3)\n", + "Coordinates:\n", + " * sample (sample) int64 16B 0 1\n", + " * timestep (timestep) int64 40B 0 1 2 3 4\n", + " * lat (lat) float64 72B -21.8 -22.05 -22.3 -22.55 ... -23.3 -23.55 -23.8\n", + " * lon (lon) float64 88B -45.05 -44.8 -44.55 ... -43.05 -42.8 -42.55\n", + " * channel (channel) int64 24B 0 1 2\n", + "Data variables:\n", + " data (sample, timestep, lat, lon, channel) float64 24kB 27.57 ... 64.43\n" + ] + } + ], + "source": [ + "lat_sorted_ascending = np.sort(lats)[::-1]\n", + "lon_sorted_ascending = np.sort(lons)\n", + "\n", + "sample = np.arange(2)\n", + "timestep = np.arange(5)\n", + "channel = np.arange(3)\n", + "\n", + "\n", + "def generate_sample(lat, lon, channels):\n", + " timestep = np.zeros((len(lat), len(lon), channels))\n", + " timestep[:, :, 0] = np.random.uniform(20, 30, (len(lat), len(lon))) # Temperature\n", + " timestep[:, :, 1] = np.random.uniform(0, 60, (len(lat), len(lon))) # Precipitation\n", + " timestep[:, :, 2] = np.random.uniform(0, 100, (len(lat), len(lon))) # Humidity\n", + " return timestep\n", + "\n", + "\n", + "# create a np array of shape len(lat) x len(lon) x len(channel), channel 0 should have temperature values, i.e. from 20 to 30, channel 1 precipitation values 0 to 60, channel 2 humidity values 0 to 100:\n", + "\n", + "\n", + "timestep0 = generate_sample(lats, lons, len(channel))\n", + "timestep1 = generate_sample(lats, lons, len(channel))\n", + "timestep2 = generate_sample(lats, lons, len(channel))\n", + "timestep3 = generate_sample(lats, lons, len(channel))\n", + "timestep4 = generate_sample(lats, lons, len(channel))\n", + "\n", + "sample1 = np.stack([timestep0, timestep1, timestep2, timestep3, timestep4], axis=0)\n", + "\n", + "timestep0 = generate_sample(lats, lons, len(channel))\n", + "timestep1 = generate_sample(lats, lons, len(channel))\n", + "timestep2 = generate_sample(lats, lons, len(channel))\n", + "timestep3 = generate_sample(lats, lons, len(channel))\n", + "timestep4 = generate_sample(lats, lons, len(channel))\n", + "\n", + "sample2 = np.stack([timestep0, timestep1, timestep2, timestep3, timestep4], axis=0)\n", + "\n", + "print(f\"sample1.shape: {sample1.shape}\")\n", + "print(f\"sample2.shape: {sample2.shape}\")\n", + "\n", + "data = np.stack([sample1, sample2], axis=0)\n", + "print(f\"data after stacking samples: {data.shape}\")\n", + "\n", + "ds = xr.Dataset(\n", + " {\"data\": ([\"sample\", \"timestep\", \"lat\", \"lon\", \"channel\"], data)},\n", + " coords={\n", + " \"sample\": sample,\n", + " \"timestep\": timestep,\n", + " \"lat\": lat_sorted_ascending,\n", + " \"lon\": lon_sorted_ascending,\n", + " \"channel\": channel,\n", + " },\n", + ")\n", + "\n", + "print(\"Created Dataset:\")\n", + "print(ds)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Ainda precisamos criar os data_vars \"x\" e \"y\", vamos utilizar 2 amostras no mesmo formato, vamos ter duas amostras em `ds.x` e duas amostras em `ds.y`. Para ter duas amostras vamos precisar de pelo menos 7 passos de tempo:\n", + "\n", + "T1 T2 T3 T4 T5 T6 T7\n", + "\n", + "```python\n", + "# amostra 1:\n", + "x = [T1, T2, T3, T4, T5]\n", + "y = [T2, T3, T4, T5, T6]\n", + "\n", + "# amostra 2:\n", + "x = [T2, T3, T4, T5, T6]\n", + "y = [T3, T4, T5, T6, T7]\n", + "```\n", + "\n", + "total_samples = (validated_total_timestamps - self.TIMESTEPS)\n", + "total_samples = 7 - 5 = 2\n", + "\n", + "A célula abaixo cria 7 timesteps dentro da pasta timesteps, as datas são ano-mes-dia-hora" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [], + "source": [ + "timesteps = [\n", + " generate_sample(lats, lons, len(channel)),\n", + " generate_sample(lats, lons, len(channel)),\n", + " generate_sample(lats, lons, len(channel)),\n", + " generate_sample(lats, lons, len(channel)),\n", + " generate_sample(lats, lons, len(channel)),\n", + " generate_sample(lats, lons, len(channel)),\n", + " generate_sample(lats, lons, len(channel)),\n", + "]\n", + "\n", + "timesteps_range = pd.date_range(start=\"2024-01-01T00:00:00\", end=\"2024-01-01T06:00:00\", freq=\"h\")\n", + "len(timesteps_range)\n", + "\n", + "for timestep in timesteps_range:\n", + " timestep_folder = Path(\"timesteps/\")\n", + " timestep_folder.mkdir(parents=True, exist_ok=True)\n", + " year = timestep.year\n", + " month = timestep.month\n", + " day = timestep.day\n", + " hour = timestep.hour\n", + " feature_file = timestep_folder / f\"{year:04}_{month:02}_{day:02}_{hour:02}.npy\"\n", + " np.save(feature_file, generate_sample(lats, lons, len(channel)))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "False\n", + "True\n" + ] + } + ], + "source": [ + "WINDOW_LENGTH = 5\n", + "\n", + "\n", + "def _has_timesteps(year: int, month: int, day: int, hour: int) -> bool:\n", + " # essa função ela faz o seguinte:\n", + " # dado um ano, mes dia e ano, ela verifica se existe os 5 timesteps anteriores a esse horario\n", + " # se existe a gente pode montar a amostra, se não a gente não pode montar a amostra\n", + " start_time = pd.Timestamp(year=year, month=month, day=day, hour=hour)\n", + " for timestep in reversed(range(WINDOW_LENGTH)):\n", + " current_time = start_time - pd.Timedelta(hours=timestep)\n", + " file = (\n", + " Path(\"timesteps/\")\n", + " / f\"{current_time.year:04}_{current_time.month:02}_{current_time.day:02}_{current_time.hour:02}.npy\"\n", + " )\n", + " if not Path(file).exists():\n", + " return False\n", + " return True\n", + "\n", + "\n", + "# por exemplo passando timesteps/2024_01_01_01 retorna False, mas passando 2024_01_01_04 retorna True:\n", + "print(_has_timesteps(2024, 1, 1, 1))\n", + "print(_has_timesteps(2024, 1, 1, 4))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Timestep adicionado: 2024-01-01 00:00:00\n", + "Timestep adicionado: 2024-01-01 01:00:00\n", + "Timestep adicionado: 2024-01-01 02:00:00\n", + "Timestep adicionado: 2024-01-01 03:00:00\n", + "Timestep adicionado: 2024-01-01 04:00:00\n", + "\n", + " data.shape: (5, 9, 11, 3)\n", + " window length or timesteps: 5\n", + " lat: 9\n", + " lon: 11\n", + " \n", + "(5, 9, 11, 3)\n" + ] + } + ], + "source": [ + "def _get_dataset_with_timesteps(year: int, month: int, day: int, hour: int, verbose=False):\n", + " start_time = pd.Timestamp(year=year, month=month, day=day, hour=hour)\n", + " timesteps = []\n", + " oldest_to_newest = reversed(range(WINDOW_LENGTH))\n", + " # processamos oldest to newest para garantir que a ordem do passado para o futuro, queremos a lista de timesteps seja na ordem abaixo:\n", + " # [2024_01_01_00, 2024_01_01_01, 2024_01_01_02, 2024_01_01_03, 2024_01_01_04]\n", + " # e não:\n", + " # [2024_01_01_04, 2024_01_01_03, 2024_01_01_02, 2024_01_01_01, 2024_01_01_00]\n", + " for timestep in oldest_to_newest:\n", + " current_time = start_time - pd.Timedelta(hours=timestep)\n", + " file = (\n", + " Path(\"timesteps/\")\n", + " / f\"{current_time.year:04}_{current_time.month:02}_{current_time.day:02}_{current_time.hour:02}.npy\"\n", + " )\n", + " data = np.load(file)\n", + " if verbose:\n", + " print(f\"Timestep adicionado: {current_time}\")\n", + " timesteps.append(data)\n", + " data = np.stack(timesteps, axis=0)\n", + " if verbose:\n", + " print(f\"\"\"\n", + " data.shape: {data.shape}\n", + " window length or timesteps: {data.shape[0]}\n", + " lat: {data.shape[1]}\n", + " lon: {data.shape[2]}\n", + " \"\"\")\n", + " return data\n", + "\n", + "\n", + "# exemplo\n", + "result = _get_dataset_with_timesteps(2024, 1, 1, 4, verbose=True)\n", + "print(result.shape)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Executando data X\n", + "Timestep adicionado: 2024-01-01 00:00:00\n", + "Timestep adicionado: 2024-01-01 01:00:00\n", + "Timestep adicionado: 2024-01-01 02:00:00\n", + "Timestep adicionado: 2024-01-01 03:00:00\n", + "Timestep adicionado: 2024-01-01 04:00:00\n", + "\n", + " data.shape: (5, 9, 11, 3)\n", + " window length or timesteps: 5\n", + " lat: 9\n", + " lon: 11\n", + " \n", + "Executando data Y\n", + "Timestep adicionado: 2024-01-01 01:00:00\n", + "Timestep adicionado: 2024-01-01 02:00:00\n", + "Timestep adicionado: 2024-01-01 03:00:00\n", + "Timestep adicionado: 2024-01-01 04:00:00\n", + "Timestep adicionado: 2024-01-01 05:00:00\n", + "\n", + " data.shape: (5, 9, 11, 3)\n", + " window length or timesteps: 5\n", + " lat: 9\n", + " lon: 11\n", + " \n", + "(5, 9, 11, 3)\n", + "(5, 9, 11, 3)\n" + ] + } + ], + "source": [ + "# agora vamos montar uma função que verifica se temos T1, T2, ..., até T7 suficientes para x e para y e retorna x e y caso seja possivel\n", + "\n", + "\n", + "def _process_timestamp(timestamp: pd.Timestamp, verbose=False):\n", + " year = timestamp.year\n", + " month = timestamp.month\n", + " day = timestamp.day\n", + " hour = timestamp.hour\n", + " if not _has_timesteps(year, month, day, hour):\n", + " return None, None\n", + "\n", + " next_timestamp = timestamp + pd.Timedelta(hours=1)\n", + " year_y = next_timestamp.year\n", + " month_y = next_timestamp.month\n", + " day_y = next_timestamp.day\n", + " hour_y = next_timestamp.hour\n", + "\n", + " if not _has_timesteps(year_y, month_y, day_y, hour_y):\n", + " return None, None\n", + " if verbose:\n", + " print(\"Executando data X\")\n", + " data_x = _get_dataset_with_timesteps(year, month, day, hour, verbose)\n", + " if verbose:\n", + " print(\"Executando data Y\")\n", + " data_y = _get_dataset_with_timesteps(year_y, month_y, day_y, hour_y, verbose)\n", + " return data_x, data_y\n", + "\n", + "\n", + "result_x, result_y = _process_timestamp(pd.Timestamp(\"2024-01-01T04:00:00\"), verbose=True)\n", + "print(result_x.shape)\n", + "print(result_y.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "data_x shape: (2, 5, 9, 11, 3)\n", + "data_y shape: (2, 5, 9, 11, 3)\n" + ] + }, + { + "data": { + "text/html": [ + "
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<xarray.Dataset> Size: 48kB\n",
+       "Dimensions:   (sample: 2, timestep: 5, lat: 9, lon: 11, channel: 3)\n",
+       "Coordinates:\n",
+       "  * sample    (sample) int64 16B 0 1\n",
+       "  * timestep  (timestep) int64 40B 0 1 2 3 4\n",
+       "  * lat       (lat) float64 72B -21.8 -22.05 -22.3 -22.55 ... -23.3 -23.55 -23.8\n",
+       "  * lon       (lon) float64 88B -45.05 -44.8 -44.55 ... -43.05 -42.8 -42.55\n",
+       "  * channel   (channel) int64 24B 0 1 2\n",
+       "Data variables:\n",
+       "    x         (sample, timestep, lat, lon, channel) float64 24kB 23.92 ... 24.56\n",
+       "    y         (sample, timestep, lat, lon, channel) float64 24kB 23.21 ... 93.13
" + ], + "text/plain": [ + " Size: 48kB\n", + "Dimensions: (sample: 2, timestep: 5, lat: 9, lon: 11, channel: 3)\n", + "Coordinates:\n", + " * sample (sample) int64 16B 0 1\n", + " * timestep (timestep) int64 40B 0 1 2 3 4\n", + " * lat (lat) float64 72B -21.8 -22.05 -22.3 -22.55 ... -23.3 -23.55 -23.8\n", + " * lon (lon) float64 88B -45.05 -44.8 -44.55 ... -43.05 -42.8 -42.55\n", + " * channel (channel) int64 24B 0 1 2\n", + "Data variables:\n", + " x (sample, timestep, lat, lon, channel) float64 24kB 23.92 ... 24.56\n", + " y (sample, timestep, lat, lon, channel) float64 24kB 23.21 ... 93.13" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# juntando tudo e montando o xr.Dataset\n", + "\n", + "\n", + "def build_netcdf(\n", + " min_timestamp: pd.Timestamp,\n", + " max_timestamp: pd.Timestamp,\n", + "):\n", + " timestamps = pd.date_range(start=min_timestamp, end=max_timestamp, freq=\"h\")\n", + "\n", + " data_x_list = []\n", + " data_y_list = []\n", + " for timestamp in timestamps:\n", + " data_x, data_y = _process_timestamp(timestamp)\n", + " if data_x is None and data_y is None:\n", + " continue\n", + " data_x_list.append(data_x)\n", + " data_y_list.append(data_y)\n", + "\n", + " assert len(data_x_list) == len(data_y_list), \"Mismatch between data_x and data_y lists\"\n", + " data_x = np.stack(data_x_list, axis=0)\n", + " data_y = np.stack(data_y_list, axis=0)\n", + " print(f\"data_x shape: {data_x.shape}\")\n", + " print(f\"data_y shape: {data_y.shape}\")\n", + "\n", + " assert data_x.shape == data_y.shape, f\"x shape {data_x.shape} != y shape {data_y.shape}\"\n", + "\n", + " sample = np.arange(data_x.shape[0])\n", + " timestep = np.arange(data_x.shape[1])\n", + " channel = np.arange(data_x.shape[4])\n", + "\n", + " ds = xr.Dataset(\n", + " {\n", + " \"x\": ([\"sample\", \"timestep\", \"lat\", \"lon\", \"channel\"], data_x),\n", + " \"y\": ([\"sample\", \"timestep\", \"lat\", \"lon\", \"channel\"], data_y),\n", + " },\n", + " coords={\n", + " \"sample\": sample,\n", + " \"timestep\": timestep,\n", + " \"lat\": lat_sorted_ascending,\n", + " \"lon\": lon_sorted_ascending,\n", + " \"channel\": channel,\n", + " },\n", + " )\n", + " return ds\n", + "\n", + "\n", + "ds = build_netcdf(pd.Timestamp(\"2024-01-01T00:00:00\"), pd.Timestamp(\"2024-01-01T06:00:00\"))\n", + "ds" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.19" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/geopy.ipynb b/notebooks/geopy.ipynb new file mode 100644 index 00000000..c61e03a6 --- /dev/null +++ b/notebooks/geopy.ipynb @@ -0,0 +1,349 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Rua Clóvis Bevilaqua 117, Tijuca, Rio de Janeiro, 20520-160\n", + "-22.929236894906\n", + "-43.235731526853\n", + "{'address': 'Rua Clóvis Bevilaqua 117, Tijuca, Rio de Janeiro, 20520-160', 'location': {'x': -43.235731526853, 'y': -22.929236894906}, 'score': 99.28, 'attributes': {}, 'extent': {'xmin': -43.236731526853, 'ymin': -22.930236894906, 'xmax': -43.234731526853, 'ymax': -22.928236894906}}\n", + "\n", + "Rua Clóvis Bevilaqua 117, Rio de Janeiro, Rio de Janeiro 20520-160, BRA\n" + ] + } + ], + "source": [ + "# pip install geopy\n", + "import pandas as pd\n", + "from geopy.geocoders import ArcGIS\n", + "from geopy.extra.rate_limiter import RateLimiter\n", + "geolocator = ArcGIS(user_agent='myGeoCoder')\n", + "geocode = RateLimiter(geolocator.geocode, min_delay_seconds=1)\n", + "location = geocode('Rua Clóvis Bevilaqua, 117 - Tijuca, Rio de Janeiro - RJ, 20520-060')\n", + "\n", + "print(type(location))\n", + "print(location.address)\n", + "print(location.latitude)\n", + "print(location.longitude)\n", + "print(location.raw)\n", + "\n", + "print()\n", + "\n", + "reverse_geocode = RateLimiter(geolocator.reverse, min_delay_seconds=1)\n", + "reverse_location = reverse_geocode('-22.929236894906, -43.235731526853')\n", + "print(reverse_location)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(21886, 21)\n" + ] + }, + { + "data": { + "text/html": [ + "
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Não foi possível encontrar o arquivo kml: {url_or_path}')\n", + " \n", + " root = tree.getroot()\n", + " namespaces = {'kml': 'http://www.opengis.net/kml/2.2'}\n", + " placemarks = root.findall('.//kml:Placemark', namespaces)\n", + "\n", + " data_list = []\n", + "\n", + " for placemark in placemarks:\n", + " data = {}\n", + "\n", + " for simple_data in placemark.findall('.//kml:SimpleData', namespaces):\n", + " name = simple_data.get('name')\n", + " if name:\n", + " data[name] = simple_data.text\n", + "\n", + " data_list.append(data)\n", + "\n", + " return data_list\n", + "\n", + "data_list = extract_kml_data('https://geoftp.ibge.gov.br/organizacao_do_territorio/estrutura_territorial/localidades/cadastro_de_localidades_selecionadas_2010/Google_KML/BR_Localidades_2010_v1.kml')\n", + "\n", + "df = pd.DataFrame(data_list)\n", + "\n", + "print(df.shape)\n", + "\n", + "df.head()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/ie01.ipynb b/notebooks/ie01.ipynb deleted file mode 100644 index f1390f5b..00000000 --- a/notebooks/ie01.ipynb +++ /dev/null @@ -1,871 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "id": "Qd5xVRuUJ8E2" - }, - "source": [ - "# Conceitos básicos da Inferência Estatística" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "W1G8GZXCKAWO" - }, - "source": [ - "\n", - "## População e amostra\n", - "\n", - "\n", - "* **População** (*population*) é a totalidade de elementos ou resultados (escores, pessoas, medidas, etc) que estão sob discussão e dos quais se deseja inferir alguma informação. Na Estatística, o termo \"população\" tem um significado ligeiramente diferente daquele que lhe é atribuído no discurso comum. Não precisa se referir apenas a pessoas ou a outros seres vivos - a população da Grã-Bretanha, por exemplo, ou a população de cães de Londres. Os estatísticos também usam o termo população para denotar coleções de objetos, eventos ou procedimentos ou observações, incluindo coisas como as quantidades de colesterol medidas no sangue de um grupo de indivíduos, visitas ao médico ou operações cirúrgicas.\n", - "\n", - "\n", - "* **Amostra** (*sample*) é qualquer subconjunto de uma população. Dado um inteiro positivo $n$, uma amostra corresponde aos resultados de $n$ experimentos nos quais a mesma quantidade é medida. Por exemplo, se queremos estimar a altura média dos membros de uma determinada população, inicialmente medimos a altura de $n$ indivíduos.\n", - "\n", - "

\n", - " \n", - "

\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "i25MHZRXKX3H" - }, - "source": [ - "População e amostra (exemplo 01) - Considere uma escola de 5.000 alunos. Se quisermos fazer um estudo das estaturas (e.g., qual a estatura média?), podemos colher uma amostra de, digamos, 40 alunos e estudar o comportamento da **varíavel estatura** apenas nesses alunos. A variável a ser estudada poderia ser inteligência, número de irmãos, número de cáries, notas em história ou renda familiar, dentre outras.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "cdp3rGP-PdnZ" - }, - "source": [ - "## Parâmetros versus estatísticas\n", - "\n", - "\n", - "* Um **parâmetro** é uma medida usada para descrever uma característica de uma população. É uma medida numérica, normalmente não observável, que descreve uma característica de uma população.\n", - "\n", - "\n", - "* Uma **estatística amostral** (ou simplesmente **estatística**) é alguma função computada a partir de uma amostra. Uma estatística é uma variável aleatória, pois seus valores são resultantes de alguma computação realizada sobre amostras aleatórias retiradas de uma população.\n", - "\n", - "Um parâmetro está para uma população assim como uma estatística está para uma amostra.\n", - "\n", - "Por exemplo, considere a porcentagem de eleitores de uma população que preferem um determinado candidato. Essa porcentagem é um exemplo de parâmetro populacional. Note que é (na maioria dos casos) impraticável perguntar a todos os eleitores da população quais são suas preferências de candidato. Sendo assim, uma amostra de eleitores pode ser consultada e uma estatística (nesse caso, a porcentagem dos eleitores que preferiram cada candidato) pode ser computada. Essa estatística pode então ser usada como um estimativa do parâmetro populacional.\n", - "\n", - "Da mesma forma, em algumas formas de teste de produtos fabricados, em vez de testar destrutivamente todos os produtos, apenas uma amostra de produtos é testada. Esses testes reúnem informações que permitem estimar qual a proporção de produtos fabricados que atende ou às especificações mínimas.\n", - "\n", - "> Repare que enquanto um parâmetro é um valor numérico, uma estatística é uma variável aleatória.\n", - "\n", - "Para entender isso, considere o experimento aleatório de produzir uma amostra aleatória de tamanho $n$ a partir de uma população. Podemos interpretar cada amostra (i.e., cada resultado da realização do experimento aleatório) como um elemento do espaço amostral correspondente a todas as possíveis amostras de tamanho $n$ dessa população. Se por definição cada valor de uma eatatística é uma função dos valores contidos na amostra aleatória correspondente, então faz sentido dizer que uma estatística é uma variável aleatória." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "yXXc0W14PfJM" - }, - "source": [ - "Alguns exemplos de parâmetros e suas notações:\n", - "\n", - "* $\\mu$: média populacional,\n", - "* $\\sigma^2$: variância populacional,\n", - "* $\\sigma$: desvio-padrão populacional,\n", - "* $p$: proporção populacional.\n", - "\n", - "\n", - "Seguem alguns exemplos de estatísticas com suas respectivas notações mais usuais (em todos os exemplos $n$ é o tamanho da amostra):\n", - "\n", - "* **média amostral** (*sample mean*, *empirical mean*):\n", - "$$\n", - "\t\t\\overline{x} = \\frac{1}{n}(x_1 + x_2 + \\ldots + x_n)\n", - "$$\n", - "* **variância amostral** (sample variance):\n", - "$$\n", - "\t\ts^2 = \\frac{1}{n-1} \\sum_{i}(x_i - \\overline{x})^2\n", - "$$\n", - "\n", - "* **desvio padrão amostral** (sample standard deviation):\n", - "$$\n", - "\t\ts = \\sqrt{s^2}\n", - "$$\n", - "\n", - "* Considere que $k$ é a quantidade de indivíduos na amostra que possuem uma dada característica de interesse (sendo assim, $n-k$ indivíduos dessa amostra não possuem essas caracterísica). A **proporção amostral** (sample proportion) é uma estatística dada por:\n", - "\n", - "$$\n", - "\t\t\\widehat{p} = \\frac{k}{n}\n", - "$$\n", - "\n", - "Repare que os valores de cada uma das estatísticas acima são computados sobre amostras aleatórias de tamanho fixo $n$. De fato, cada uma dessas estatísticas é uma função que mapeia elementos de $\\Re^n$ em $\\Re$.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "0p-MiOJkL45N" - }, - "source": [ - "## Objetivo da Inferência Estatística" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "e1nrVssHLVHF" - }, - "source": [ - "> O objetivo da Inferência Estatística é produzir afirmações sobre dada **característica** dos elementos de uma população, com base nos dados contidos em uma ou mais amostras dessa população.\n", - "\n", - "A característica sob estudo pode ser representada por uma variável aleatória, que possui uma determinada distribuição de probabilidades com determinado conjunto de parâmetros. Seguem alguns exemplos:\n", - "\n", - "1. A altura dos indivíduos de uma determinada população é uma característica que pode ser modelada por meio da [distribuição normal](https://en.wikipedia.org/wiki/Normal_distribution) com média $\\mu=1.65$ m e variância $\\sigma^2 = 0.2$ $m^2$.\n", - "\n", - "2. O tempo de atendimento em um quiosque pode ser modelado por uma [distribuição exponencial](https://en.wikipedia.org/wiki/Exponential_distribution) com média $\\lambda = 5$ minutos.\n", - "\n", - "3. A quantidade de defeitos em cada peça produzida em um processo industrial segue uma [distribuição de Poisson](https://en.wikipedia.org/wiki/Poisson_distribution), com média igual a $\\lambda = 0.8$.\n", - "\n", - "Repare que cada um dos exemplos acima presupõe que foi feito um estudo para (1) identificar a distribuição de probabilidades (normal, exponencial, Poisson, etc) mais adequada para o problema em questão e (2) identificar a combinação de parâmetros mais adequada para aquela distribuição.\n", - "\n", - "Quando a função de massa de probabilidade (no caso discreto) ou a função de densidade de probabilidade (no caso contínuo) da variável aleatória é conhecida, o problema de fazer afirmações sobre a população está resolvido. Ocorre que muitas vezes não sabemos nada sobre a variável ou essa informação é parcial. Por exemplo, no caso das alturas dos indivíduos de uma população, podemos presumir que elas sigam uma distribuição normal, mas em geral desconhecemos os parâmetros que a caracterizam (e.g., média e variância).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "YFLiNSCCM59t" - }, - "source": [ - "Em geral, pode acontecer de\n", - "\n", - "*\ttermos uma ideia de qual deve ser a distribuição de probabilidades adequada, mas desconhecermos os valores dos parâmetros dessa distribuição.\n", - "*\tconhecermos os valores dos parâmetros, mas desconhecermos a distribuição de probabilidades.\n", - "*\tnão conhecermos nem a distribuição de probabilidades nem os respectivos valores dos parâmetros.\n", - "\n", - "Em qualquer caso, o uso de uma amostra pode nos revelar informações sobre o comportamento da variável sob estudo na população." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "blSKWnohNBH0" - }, - "source": [ - "## Problemas alvos da Inferência Estatística" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "lRHRosMhNEgo" - }, - "source": [ - "As técnicas da Inferência Estatística podem ser divididas em duas grandes famílias:\n", - "\n", - "**Estimação de parâmetros**\n", - "> Conjunto de técnicas para **construir uma estimativa** para um parâmetro de uma população por meio de observações de uma amostra.\n", - "\n", - "**Teste de hipóteses**\n", - "> Conjunto de técnicas para **verificar alguma alegação** acerca do parâmetro de uma população por meio de observações de um ou mais amostras.\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bYxtW5OGNLdl" - }, - "source": [ - "## Planos Amostrais\n", - "\n", - "Dada uma população finita de tamanho $N$, a quantidade de amostras de tamanho $n$ que podem ser formadas a partir dessa população é\n", - "$$\n", - "\\binom{N}{n} = \\frac{N!}{n!(N-n)!}\n", - "$$\n", - "\n", - "Um **plano amostral** é uma forma de produzir amostras a partir de uma população. Existem inúmeros planos amostrais. Alguns planos amostrais são:\n", - "\n", - "* Amostragem aleatória sistemática\n", - "* Amostragem aleatória estratificada\n", - "* Amostragem aleatória simples" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "Uf0eMpxeNkK-" - }, - "source": [ - "### Amostragem aleatória sistemática\n", - "\n", - "Os itens ou indivíduos da população são ordenados de alguma forma - alfabeticamente ou por meio de algum outro método. Um ponto de partida aleatório é sorteado, e então cada $k$-ésimo membro da população é selecionado para a amostra. A varrecura sobre a lista ordenada é realizada de forma circular.\n", - "\n", - "

\n", - " \n", - "

\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ZyxieVkfNrgr" - }, - "source": [ - "### Amostragem aleatória estratificada\n", - "\n", - "A população é inicialmente dividida em subgrupos (estratos) e uma subamostra é selecionada a partir de cada estrato da população. O objetivo é fazer com a amostra resultante contenha proporções similares dos diferentes subgrupos da população.\n", - "\n", - "

\n", - " \n", - "

\n", - "\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "jWCoLscvNz_G" - }, - "source": [ - "### Amostragem aleatória simples (AAS)\n", - "\n", - "Na AAS, cada amostra é escolhida de tal forma que cada elemento da população tem a mesma probabilidade de ser selecionado. Dessa forma, se a população tem tamanho $N$, cada elemento dessa população tem a mesma probabilidade igual a $1/N$ de entrar na amostra.\n", - "\n", - "

\n", - " \n", - "

" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "bS2H8yH4O1SZ" - }, - "source": [ - "Uma AAS pode ser recolhida *com reposição* ou *sem reposição*.\n", - "\n", - "* Quando a amostra é recolhida com reposição, cada elemento eventualmente selecionado pode ser selecionado novamente.\n", - "\n", - "* Quando a amostra é recolhida sem reposição, não há independência entre os elementos, fato que tem impacto na fórmula do cálculo das estimativas feito a partir dessa amostra." - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "UxwX0zBaMMOT" - }, - "source": [ - "### Geração de amostras com Pandas\n", - "\n", - "Amostras podem ser geradas por meio da biblioteca Pandas no Python. Em particular a função [sample](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.sample.html) permite gerar amostras aleatórias de acordo com diferentes planos amostrais.\n", - "\n", - "Para ilustrar produção de amostras por meio de vários planos amostrais, vamos supor que a população corresponde aos elementos de um conjunto de dados que registra alegações de avistamentos de OVNIs. Esse conjunto de dados é publicamente disponível no portal [Kaggle](https://www.kaggle.com/NUFORC/ufo-sightings). Esse conjunto contém vários atributos, dentre os quais:\n", - "\n", - "- $\\texttt{datetime}$ - momento do avistamento, no formato MM/DD/AAAA HH:mm.\n", - "- $\\texttt{city}$ - A localização do avistamento do OVNI.\n", - "- $\\texttt{state}$ - o estado (unidade federativa) do avistamento.\n", - "- $\\texttt{country}$ - o país do avistamento.\n", - "- $\\texttt{shape}$ - a forma do OVNI visto.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 576 - }, - "id": "vgyVsIrXnu6s", - "outputId": "feb020a1-56c2-4969-cc02-84f253ca1504" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/lib/python3.7/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (5,9) have mixed types.Specify dtype option on import or set low_memory=False.\n", - " interactivity=interactivity, compiler=compiler, result=result)\n" - ] - }, - { - "data": { - "text/html": [ - "
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datetimecitystatecountryshapeduration (seconds)duration (hours/min)commentsdate postedlatitudelongitude
010/10/1949 20:30san marcostxuscylinder270045 minutesThis event took place in early fall around 194...4/27/200429.8830556-97.941111
110/10/1949 21:00lackland afbtxNaNlight72001-2 hrs1949 Lackland AFB&#44 TX. Lights racing acros...12/16/200529.38421-98.581082
210/10/1955 17:00chester (uk/england)NaNgbcircle2020 secondsGreen/Orange circular disc over Chester&#44 En...1/21/200853.2-2.916667
310/10/1956 21:00ednatxuscircle201/2 hourMy older brother and twin sister were leaving ...1/17/200428.9783333-96.645833
410/10/1960 20:00kaneohehiuslight90015 minutesAS a Marine 1st Lt. flying an FJ4B fighter/att...1/22/200421.4180556-157.803611
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" - ], - "text/plain": [ - " datetime city ... latitude longitude \n", - "0 10/10/1949 20:30 san marcos ... 29.8830556 -97.941111\n", - "1 10/10/1949 21:00 lackland afb ... 29.38421 -98.581082\n", - "2 10/10/1955 17:00 chester (uk/england) ... 53.2 -2.916667\n", - "3 10/10/1956 21:00 edna ... 28.9783333 -96.645833\n", - "4 10/10/1960 20:00 kaneohe ... 21.4180556 -157.803611\n", - "\n", - "[5 rows x 11 columns]" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "\n", - "link = 'scrubbed.csv'\n", - "ufo_df = pd.read_csv(link, encoding='utf8') # dataframe\n", - "\n", - "ufo_df.head(12)" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kDxNG1Ox6_Nc" - }, - "source": [ - "Podemos primeiro inspecionar os detalhes dos atributos desse conjunto de dados." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "YfNQLfSf7A4E", - "outputId": "08252021-910a-46ff-877c-6de68c3602bd" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 80332 entries, 0 to 80331\n", - "Data columns (total 11 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 datetime 80332 non-null object \n", - " 1 city 80332 non-null object \n", - " 2 state 74535 non-null object \n", - " 3 country 70662 non-null object \n", - " 4 shape 78400 non-null object \n", - " 5 duration (seconds) 80332 non-null object \n", - " 6 duration (hours/min) 80332 non-null object \n", - " 7 comments 80317 non-null object \n", - " 8 date posted 80332 non-null object \n", - " 9 latitude 80332 non-null object \n", - " 10 longitude 80332 non-null float64\n", - "dtypes: float64(1), object(10)\n", - "memory usage: 6.7+ MB\n" - ] - } - ], - "source": [ - "ufo_df.info()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "sLVgJzzKn5DN", - "outputId": "91ae872f-89aa-428c-8897-d4516b8ebba0" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(80332, 11)" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "ufo_df.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "ArEZtHuYl0jk" - }, - "source": [ - "#### Amostragem aleatória sistemática\n", - "\n", - "Agora podemos gerar uma amostra aleatória sistemática de tamanho $n=100$. Vamos realizar essa geração usando um deslocamento entre amostras igual a $5$." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "EeX4E6GKl05t", - "outputId": "ff69f4cb-499e-44f7-ac8a-f5ca39d37307" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(16067, 11)\n" - ] - }, - { - "data": { - "text/plain": [ - "(100, 11)" - ] - }, - "execution_count": 88, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "n = 100\n", - "deslocamento = 5\n", - "\n", - "sys_sample_df = ufo_df.iloc[::deslocamento]\n", - "\n", - "print(sys_sample_df.shape)\n", - "\n", - "amostra = sys_sample_df.head(n)\n", - "\n", - "amostra.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "sisqtA3f9IvY" - }, - "source": [ - "#### Amostragem aleatória simples\n", - "\n", - "Agora podemos retirar uma amostra aleatória simples de, digamos, tamanho igual a 100:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 610 - }, - "id": "ipUkWkWZoU8u", - "outputId": "567956a9-87f1-4f2f-8c74-a96a09f22ac4" - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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datetimecitystatecountryshapeduration (seconds)duration (hours/min)commentsdate postedlatitudelongitude
347473/5/1995 12:00anaheimcausother90015 minutesIn March of 1995 returning from St. Joseph Hos...10/31/200333.8352778-117.913611
2065612/26/1997 21:35bonhamtxusunknown1802 to 3 minutesRed object moving west to east&#44 person look...3/7/199833.5772222-96.178056
744259/14/2010 22:00fentonmousfireball36001 hour or morebright flickering red lights orbitting around ...4/3/201138.5131-90.435833
686878/2/2012 21:30oregon cityorusfireball1803 minutesSaw nine fireballs flying in the sky from the ...10/30/201245.3575-122.605556
378924/20/2000 21:00melbourne (vic&#44 australia)NaNaulight3005 minutesA drifting flashing glow of orange&#44 which w...4/26/2000-37.813938144.963425
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" - ], - "text/plain": [ - " datetime city ... latitude longitude \n", - "34747 3/5/1995 12:00 anaheim ... 33.8352778 -117.913611\n", - "20656 12/26/1997 21:35 bonham ... 33.5772222 -96.178056\n", - "74425 9/14/2010 22:00 fenton ... 38.5131 -90.435833\n", - "68687 8/2/2012 21:30 oregon city ... 45.3575 -122.605556\n", - "37892 4/20/2000 21:00 melbourne (vic, australia) ... -37.813938 144.963425\n", - "\n", - "[5 rows x 11 columns]" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "amostra = ufo_df.sample(n = 100)\n", - "amostra.head()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "bU5JbgIXBmqb", - "outputId": "cd364fb0-f23f-4da9-eb9e-efdf9d7efc39" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "(100, 11)" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "amostra.shape" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "kR7ixymoKpi8" - }, - "source": [ - "#### Amostragem aleatória estratificada\n", - "\n", - "Vamos usar o código acima para produzir uma amostra aleatória estratificada levando em consideração o atributo `country`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 282 - }, - "id": "5Pqpxwl5rJUm", - "outputId": "b15c8288-b6df-44f6-9764-df0af16ed624" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 86, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "ufo_df.country.hist()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "OIxv2nKCqXnT" - }, - "outputs": [], - "source": [ - "sample_df = ufo_df.groupby('country').apply(lambda x: x.sample(frac=0.1))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 282 - }, - "id": "FoY5wzatwcfO", - "outputId": "a8e9dc93-a918-474f-e2f3-3d07d31adf7a" - }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 85, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "sample_df.country.hist()" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2gSWVrOoLRpa" - }, - "source": [ - "Podemos nos certificar de que a amostra produzida realmente mantém as proporções de países existente na população." - ] - } - ], - "metadata": { - "colab": { - "provenance": [] - }, - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.9" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -} diff --git a/notebooks/inea_radar/9921GUA-PPIVol-20230323-170010-0000.hdf b/notebooks/inea_radar/9921GUA-PPIVol-20230323-170010-0000.hdf new file mode 100644 index 00000000..0b3fdb91 Binary files /dev/null and b/notebooks/inea_radar/9921GUA-PPIVol-20230323-170010-0000.hdf differ diff --git a/notebooks/inea_radar/anl_radar_inea.ipynb b/notebooks/inea_radar/anl_radar_inea.ipynb new file mode 100644 index 00000000..dde53b27 --- /dev/null +++ b/notebooks/inea_radar/anl_radar_inea.ipynb @@ -0,0 +1,31244 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Pré-análise\n", + "* O arquivo de dados do radar do INEA segue a estrutura de dados do [padrão OPERA do EUMET](https://www.eumetnet.eu/wp-content/uploads/2019/05/OPERA-ODIM_H5-v2.01.pdf)\n", + "* O modo como o radar realiza o escaneamento (PPI mode) é apresentado neste notebook (TODO: Inserir link para o notebook da Rafaela Castro)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "# import os, sys\n", + "\n", + "# ROOT_DIR = '../..'\n", + "# sys.path.append(ROOT_DIR)\n", + "# os.chdir(ROOT_DIR)\n", + "\n", + "# from dotenv import load_dotenv\n", + "# load_dotenv('config/.env')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "# pip install wradlib" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import wradlib.georef as georef\n", + "import wradlib.io as io\n", + "import wradlib.util as util\n", + "import warnings\n", + "# from src.utils.datalake import DataLakeWrapper\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Carregando o arquivo de dados" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "({'BBC': b'False',\n", + " 'RXloss': 2.0,\n", + " 'TXloss': 0.8999999761581421,\n", + " 'VPRCorr': b'False',\n", + " 'antgain': 45.0,\n", + " 'azmethod': b'AVERAGE',\n", + " 'beamwH': 1.0,\n", + " 'beamwV': 1.0,\n", + " 'binmethod': b'AVERAGE',\n", + " 'gasattn': 0.017000000923871994,\n", + " 'pointaccAZ': 0.20000000298023224,\n", + " 'pointaccEL': 0.20000000298023224,\n", + " 'radomeloss': 0.0,\n", + " 'software': b'EDGE',\n", + " 'sw_version': b'6.5.1-5',\n", + " 'system': b'EEC-DWSR-93C',\n", + " 'task': b'Padrao',\n", + " 'wavelength': 10.709933280944824},\n", + " {'date': b'20230323',\n", + " 'object': b'PVOL',\n", + " 'source': b'WMO:00000,RAD:,PLC:9921GUA,NOD:9921GUA,ORG:0,CTY:000,CMT:',\n", + " 'time': b'170010',\n", + " 'version': b'H5rad 2.1'},\n", + " {'height': 123.0, 'lat': -22.9932804107666, 'lon': -43.58795928955078})" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "filename = '9921GUA-PPIVol-20230323-170010-0000.hdf'\n", + "pvol = io.read_opera_hdf5(filename)\n", + "pvol['how'], pvol['what'], pvol['where']" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Contando a quantidade de datasets" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dataset1/what\n", + "dataset2/what\n", + "dataset3/what\n", + "dataset4/what\n", + "dataset5/what\n", + "dataset6/what\n", + "dataset7/what\n" + ] + }, + { + "data": { + "text/plain": [ + "'7 datasets found'" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ntilt = 1\n", + "for i in range(100):\n", + " try:\n", + " pvol[f\"dataset{ntilt}/what\"]\n", + " print(f\"dataset{ntilt}/what\")\n", + " ntilt += 1\n", + " except Exception:\n", + " ntilt -= 1\n", + " break\n", + "f\"{ntilt} datasets found\"" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "({'enddate': b'20230323',\n", + " 'endtime': b'170047',\n", + " 'product': b'SCAN',\n", + " 'startdate': b'20230323',\n", + " 'starttime': b'170011'},\n", + " {'CSR': 25.0,\n", + " 'Dclutter': b\"'14'\",\n", + " 'LOG': 2.0,\n", + " 'NEZ': 0.0,\n", + " 'NI': 48.194698333740234,\n", + " 'PAC': 0.0,\n", + " 'RAC': 0.0,\n", + " 'RXbandwidth': 1.0,\n", + " 'S2N': 2.0,\n", + " 'SQI': 30.0,\n", + " 'TXpower': array([777.50604358, 777.54975267, 777.08000874, 776.79065674,\n", + " 777.04315132, 776.66785121, 775.98186211, 777.4814583 ,\n", + " 777.47189757, 776.31182494, 776.98172617, 778.79375881,\n", + " 778.03071482, 778.39710138, 777.4568738 , 778.48188702,\n", + " 777.78609747, 777.80659317, 777.379028 , 777.10048584,\n", + " 777.85441859, 777.492385 , 777.67679615, 777.27797666,\n", + " 776.97763133, 776.4645825 , 777.63717821, 776.90392794,\n", + " 777.26978388, 777.66176842, 777.24657149, 775.71608501,\n", + " 778.17560828, 776.92303556, 776.13728167, 777.74374138,\n", + " 777.25749488, 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'nrays': 360,\n", + " 'rscale': 250.0,\n", + " 'rstart': 0.0})" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pvol['dataset1/what'], pvol['dataset1/how'], pvol['dataset1/where']" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'gain': 0.5,\n", + " 'nodata': 255.0,\n", + " 'offset': -32.0,\n", + " 'quantity': b'TH',\n", + " 'undetect': 0.0}" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pvol['dataset1/data1/what']\n", + "# pvol['dataset1/data1/how'] # not available\n", + "# pvol['dataset1/data1/where'] # not available" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(360, 1000)\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[146, 167, 123, ..., 0, 0, 0],\n", + " [148, 167, 115, ..., 0, 0, 0],\n", + " [147, 165, 127, ..., 0, 0, 0],\n", + " ...,\n", + " [125, 166, 124, ..., 0, 0, 0],\n", + " [138, 167, 123, ..., 0, 0, 0],\n", + " [144, 167, 128, ..., 0, 0, 0]], dtype=uint8)" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(pvol['dataset1/data1/data'].shape)\n", + "pvol['dataset1/data1/data']" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'a1gate': 352,\n", + " 'elangle': 6.199999809265137,\n", + " 'nbins': 600,\n", + " 'nrays': 360,\n", + " 'rscale': 250.0,\n", + " 'rstart': 0.0}" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# pvol['dataset14/where']\n", + "pvol['dataset7/where']" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(360, 600)\n" + ] + }, + { + "data": { + "text/plain": [ + "array([[102, 93, 66, ..., 0, 0, 0],\n", + " [ 92, 109, 77, ..., 0, 0, 0],\n", + " [ 96, 104, 69, ..., 0, 0, 0],\n", + " ...,\n", + " [107, 97, 82, ..., 0, 0, 0],\n", + " [103, 103, 73, ..., 0, 0, 0],\n", + " [ 96, 89, 68, ..., 0, 0, 0]], dtype=uint8)" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print(pvol['dataset7/data1/data'].shape)\n", + "pvol['dataset7/data1/data']" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Conclusão da análise da estrutura do arquivo de dados\n", + "\n", + "De acordo com os testes acima, o padrão empregado no arquivo de dados do radar do INEA segue a seguinte estrutura\n", + "\n", + "![pvol file structure](images/inea_radar_structure.png)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Informações mais relevantes\n", + "\n", + "### Datasets\n", + "* Cada arquivo contém 14 datasets {dataset1, dataset2, ..., dataset14}\n", + "* Cada dataset está relacionado a um ângulo de elevação que varia entre 0,5 e 19,5 graus aproximadamente\n", + "```python\n", + " pvol['dataset1/where']['elangle']\n", + "```\n", + "* Cada dataset contém 11 produtos {data1, data2, ..., data11}\n", + "* A identificação de cada produto pode ser encontrada em\n", + "```python\n", + " pvol['dataset1/data1/what']['quantity']\n", + "```\n", + "### Tabela de associação entre o nome do produto e a identificação\n", + "\n", + "|Param|Description|\n", + "|-----|------|\n", + "|`data1`|TH|\n", + "|`data2`|TV|\n", + "|`data3`|DBZH|\n", + "|`data4`|DBZV|\n", + "|`data5`|ZDR|\n", + "|`data6`|RHOHV|\n", + "|`data7`|PHIDP|\n", + "|`data8`|SQI|\n", + "|`data9`|SNR|\n", + "|`data10`|VRAD|\n", + "|`data11`|WRAD|\n", + "\n", + "### Coordenadas do radar\n", + "```python\n", + " pvol[\"where\"][\"lon\"]\n", + " pvol[\"where\"][\"lat\"]\n", + " pvol[\"where\"][\"height\"]\n", + "```\n", + "### Data e hora da aquisição (para cada dataset)\n", + "```python\n", + " pvol['dataset1/what']['starttime']\n", + " pvol['dataset1/what']['endtime']\n", + " pvol['dataset1/what']['startdate']\n", + " pvol['dataset1/what']['enddate']\n", + "```\n", + "### Modo da aquisição (para cada dataset)\n", + "```python\n", + " pvol['dataset1/where']['elangle']\n", + " pvol['dataset1/where']['nbins']\n", + " pvol['dataset1/where']['nrays']\n", + " pvol['dataset1/where']['rscale']\n", + " pvol['dataset1/where']['rstart']\n", + "```\n", + "### Especificação do modo de aquisição\n", + "|Param|Type|Description|\n", + "|-----|-------|------|\n", + "|`elangle`|double|Antenna elevation angle (degrees) above the horizon.|\n", + "|`nbins`|long|Number of range bins in each ray|\n", + "|`nrays`|long|Number of azimuth gates (rays) in the object|\n", + "|`rscale`|double|The distance in meters between two successive range bins|\n", + "|`rstart`|double|The range (km) of the start of the first range bin|" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Pré-análise DBZH (data3), transformação para coordenadas geográficas\n", + "Fonte: https://docs.wradlib.org/en/stable/notebooks/georeferencing/wradlib_coords_example.html" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# import os, sys\n", + "\n", + "# ROOT_DIR = '../..'\n", + "# sys.path.append(ROOT_DIR)\n", + "# os.chdir(ROOT_DIR)\n", + "\n", + "# from dotenv import load_dotenv\n", + "# load_dotenv('config/.env')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import wradlib.georef as georef\n", + "import wradlib.io as io\n", + "import wradlib.util as util\n", + "import warnings\n", + "# from src.utils.datalake import DataLakeWrapper\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Carregando os dados" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "filename = \"9921GUA-PPIVol-20160919-000015-0000.hdf\"\n", + "dlc = DataLakeWrapper().get_client()\n", + "dlc.fget_object(\n", + " bucket_name='landing',\n", + " object_name=f'radar/inea/guaratiba/2016-09-19/{filename}',\n", + " file_path=f'data/radar/{filename}'\n", + ")\n", + "pvol = io.read_opera_hdf5(f'data/radar/{filename}')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Contando a quantidade de datasets" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'14 datasets found'" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ntilt = 1\n", + "for i in range(100):\n", + " try:\n", + " pvol[f\"dataset{ntilt}/what\"]\n", + " ntilt += 1\n", + " except Exception:\n", + " ntilt -= 1\n", + " break\n", + "f\"{ntilt} datasets found\"" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Scan geometry de cada dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{1: (308, 250, 500),\n", + " 2: (308, 250, 500),\n", + " 3: (308, 250, 500),\n", + " 4: (308, 250, 500),\n", + " 5: (308, 250, 500),\n", + " 6: (258, 250, 500),\n", + " 7: (256, 250, 500),\n", + " 8: (257, 250, 500),\n", + " 9: (257, 250, 500),\n", + " 10: (257, 250, 500),\n", + " 11: (256, 250, 500),\n", + " 12: (257, 250, 500),\n", + " 13: (257, 250, 500),\n", + " 14: (257, 250, 500)}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scan_geometry = list()\n", + "for i in range(1,ntilt+1):\n", + " nrays = int(pvol[f\"dataset{i}/where\"][\"nrays\"])\n", + " nbins = int(pvol[f\"dataset{i}/where\"][\"nbins\"])\n", + " rscale = int(pvol[f\"dataset{i}/where\"][\"rscale\"])\n", + " scan_geometry.append(tuple([nrays, nbins, rscale]))\n", + "scan_geometry = dict(zip(range(1,ntilt+1), scan_geometry))\n", + "scan_geometry" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calculando as coordenadas geográficas (lat, lon)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(963000, 4)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sitecoords = (pvol[\"where\"][\"lon\"], pvol[\"where\"][\"lat\"], pvol[\"where\"][\"height\"])\n", + "ppi_data = np.ndarray((0,4))\n", + "for tilt in range(1,ntilt+1):\n", + " # scan_start_time = pvol[f\"dataset{tilt}/what\"][\"starttime\"]\n", + " # scan_start_date = pvol[f\"dataset{tilt}/what\"][\"startdate\"]\n", + " elangle = pvol[f\"dataset{tilt}/where\"][\"elangle\"]\n", + " nrays = int(pvol[f\"dataset{tilt}/where\"][\"nrays\"])\n", + " nbins = int(pvol[f\"dataset{tilt}/where\"][\"nbins\"])\n", + " rscale = int(pvol[f\"dataset{tilt}/where\"][\"rscale\"])\n", + " coord = np.empty((nrays, nbins, 3))\n", + " coord[...] = georef.sweep_centroids(nrays, rscale, nbins, elangle)\n", + " lon_lat_alt = georef.spherical_to_proj(\n", + " coord[..., 0], \n", + " coord[..., 1], \n", + " coord[..., 2], \n", + " sitecoords\n", + " )\n", + " dbzh = pvol[f'dataset{tilt}/data3/data'].reshape(-1)\n", + " data = np.column_stack((lon_lat_alt.reshape(-1, 3), dbzh))\n", + " ppi_data = np.row_stack((ppi_data, data))\n", + "# scan_start_time, scan_start_date\n", + "ppi_data.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "963000" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "total = 0\n", + "for x,y,_ in scan_geometry.values():\n", + " total += x*y\n", + "total" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[-43.587915130863095, -22.990992775084415, 122.18477745912969, 83.0],\n", + " [-43.587865395107585, -22.986478326804026, 126.57638954557478, 57.0],\n", + " [-43.58781566270931, -22.981963880617737, 130.99741114862263, 0.0]]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ppi_data[:3].tolist()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[-43.60167487854885, -21.945090454742587, 42226.62658525072, 0.0],\n", + " [-43.60172968420003, -21.940876283368034, 42399.969709496945, 0.0],\n", + " [-43.60178448439824, -21.93666228085649, 42573.33858192153, 0.0]]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ppi_data[-3:].tolist()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Min/Max longitude: (-44.80439032906937, -42.371489670930636)\n", + "Min/Max latitude: (-24.119298834573986, -21.867040208729073)\n", + "Min/Max altitude (km): (0.12, 42.57)\n" + ] + } + ], + "source": [ + "lon_min = np.min(ppi_data[:,0])\n", + "lon_max = np.max(ppi_data[:,0])\n", + "print(f'Min/Max longitude: {lon_min, lon_max}')\n", + "\n", + "lat_min = np.min(ppi_data[:,1])\n", + "lat_max = np.max(ppi_data[:,1])\n", + "print(f'Min/Max latitude: {lat_min, lat_max}')\n", + "\n", + "alt_min = np.round(np.min(ppi_data[:,2]) / 1000, 2)\n", + "alt_max = np.round(np.max(ppi_data[:,2]) / 1000, 2)\n", + "print(f'Min/Max altitude (km): {alt_min, alt_max}')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-23.1339033365138 -22.649724748272934\n", + "-43.8906028271505 -43.04835145732227\n" + ] + } + ], + "source": [ + "from src.data_classes.classes import RJCityArea as rj\n", + "\n", + "\n", + "print(rj.s_bound, rj.n_bound)\n", + "print(rj.w_bound, rj.e_bound)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> As coordenadas geográficas calculadas abrangem a cidade do Rio de Janeiro" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Elevation 0.5 degrees ALT: 1.0908169372967418 DIST: 124.99524038302141\n", + "Elevation 19.5 degrees ALT: 41.725857404221365 DIST: 117.8301863865223\n" + ] + } + ], + "source": [ + "# Math validation\n", + "def radar_beam_altitude(elevation_angle, radar_beam_range):\n", + " return radar_beam_range * np.sin(np.deg2rad(elevation_angle))\n", + "\n", + "\n", + "def radar_beam_horizontal_range(elevation_angle, radar_beam_range):\n", + " return radar_beam_range * np.cos(np.deg2rad(elevation_angle))\n", + "\n", + "\n", + "def print_radar_ranges(elevation_angle, radar_beam_range):\n", + " print(f'Elevation {elevation_angle} degrees', 'ALT:', radar_beam_altitude(elevation_angle, radar_beam_range), 'DIST:', radar_beam_horizontal_range(elevation_angle, radar_beam_range))\n", + "\n", + "print_radar_ranges(0.5, 125)\n", + "print_radar_ranges(19.5, 125)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> As altitudes calculadas parecem estar consistentes com a validação matemática realizada" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Staging file\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "np.save('data/radar/ppi_data.npy', ppi_data)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "pvol: 13056, \n", + "ppi_data: 30816128, \n" + ] + } + ], + "source": [ + "import sys\n", + "\n", + "print(f'pvol: {sys.getsizeof(pvol)}, {type(pvol)}')\n", + "print(f'ppi_data: {sys.getsizeof(ppi_data)}, {type(ppi_data)}')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> O armazenamento dos dados em formato numpy aumenta significativamente o tamanho do arquivo\n", + ">\n", + "> Considerar armazenar em formato Xarray" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Visualização dos dados" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os, sys\n", + "\n", + "ROOT_DIR = '../..'\n", + "sys.path.append(ROOT_DIR)\n", + "os.chdir(ROOT_DIR)\n", + "\n", + "from dotenv import load_dotenv\n", + "load_dotenv('config/.env')" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " lon lat alt dbzh\n", + "0 -43.587915 -22.990993 122.184777 83.0\n", + "250 -43.587865 -22.990994 122.184777 0.0\n", + "500 -43.587816 -22.990996 122.184777 0.0\n", + "750 -43.587766 -22.990998 122.184777 0.0\n", + "1000 -43.587716 -22.991002 122.184777 0.0\n", + "... ... ... ... ...\n", + "75750 -43.588164 -22.991002 122.184777 88.0\n", + "76000 -43.588114 -22.990998 122.184777 86.0\n", + "76250 -43.588064 -22.990996 122.184777 0.0\n", + "76500 -43.588015 -22.990994 122.184777 0.0\n", + "76750 -43.587965 -22.990993 122.184777 85.0\n", + "\n", + "[308 rows x 4 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "altitudes = sorted(ddf['alt'].unique())[:2] # [122.18477745912969, 126.5463136844337]\n", + "c1 = ddf['alt'] >= altitudes[0]\n", + "c2 = ddf['alt'] < altitudes[1]\n", + "ddf[c1 & c2]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlataltdbzh
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" + ], + "text/plain": [ + " lon lat alt dbzh\n", + "898998 -43.574150 -21.940876 42399.969709 0.0\n", + "899248 -43.546579 -21.941501 42399.969709 0.0\n", + "899498 -43.519032 -21.942749 42399.969709 0.0\n", + "899748 -43.491525 -21.944620 42399.969709 0.0\n", + "899998 -43.464074 -21.947113 42399.969709 0.0\n", + "... ... ... ... ...\n", + "961998 -43.711806 -21.947113 42399.969709 0.0\n", + "962248 -43.684355 -21.944620 42399.969709 0.0\n", + "962498 -43.656848 -21.942749 42399.969709 0.0\n", + "962748 -43.629301 -21.941501 42399.969709 0.0\n", + "962998 -43.601730 -21.940876 42399.969709 0.0\n", + "\n", + "[257 rows x 4 columns]" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "altitudes = sorted(ddf['alt'].unique())[-2:] # [42399.969709496945, 42573.33858192153]\n", + "c1 = ddf['alt'] >= altitudes[0]\n", + "c2 = ddf['alt'] < altitudes[1]\n", + "ddf[c1 & c2]" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> A quantidade de registros esperada para a maior altitude é consistente com a quantidade de bins do maior ângulo de elevação do radar." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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lonlataltdbzh
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" + ], + "text/plain": [ + " lon lat alt dbzh\n", + "0 -43.587915 -22.990993 122.184777 83.0\n", + "250 -43.587865 -22.990994 122.184777 0.0\n", + "500 -43.587816 -22.990996 122.184777 0.0\n", + "750 -43.587766 -22.990998 122.184777 0.0\n", + "1000 -43.587716 -22.991002 122.184777 0.0\n", + "... ... ... ... ...\n", + "75750 -43.588164 -22.991002 122.184777 88.0\n", + "76000 -43.588114 -22.990998 122.184777 86.0\n", + "76250 -43.588064 -22.990996 122.184777 0.0\n", + "76500 -43.588015 -22.990994 122.184777 0.0\n", + "76750 -43.587965 -22.990993 122.184777 85.0\n", + "\n", + "[308 rows x 4 columns]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "altitudes = sorted(ddf['alt'].unique())[:2] # [122.18477745912969, 126.5463136844337]\n", + "c1 = ddf['alt'] >= altitudes[0]\n", + "c2 = ddf['alt'] < altitudes[1]\n", + "ddf[c1 & c2]" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "import folium\n", + "from folium.plugins import HeatMap" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " lat lon dbzh\n", + "0 -22.990993 -43.587915 83.0\n", + "250 -22.990994 -43.587865 0.0\n", + "500 -22.990996 -43.587816 0.0\n", + "750 -22.990998 -43.587766 0.0\n", + "1000 -22.991002 -43.587716 0.0\n", + "... ... ... ...\n", + "75750 -22.991002 -43.588164 88.0\n", + "76000 -22.990998 -43.588114 86.0\n", + "76250 -22.990996 -43.588064 0.0\n", + "76500 -22.990994 -43.588015 0.0\n", + "76750 -22.990993 -43.587965 85.0\n", + "\n", + "[308 rows x 3 columns]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_ = ddf[c1 & c2].copy()\n", + "df_.drop('alt', inplace=True, axis=1)\n", + "df_ = df_[['lat', 'lon', 'dbzh']]\n", + "df_" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "count 308.000000\n", + "mean 87.464286\n", + "std 22.854347\n", + "min 0.000000\n", + "25% 83.000000\n", + "50% 96.000000\n", + "75% 100.000000\n", + "max 109.000000\n", + "Name: dbzh, dtype: float64" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_['dbzh'].describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "figure = folium.Figure(width=1200, height=700)\n", + "map = folium.Map(\n", + " [-22.925, -43.489], \n", + " zoom_start=10.5,\n", + " min_zoom=8, \n", + " tiles='cartodbpositron',\n", + ").add_to(figure)\n", + "folium.LatLngPopup().add_to(map)\n", + "HeatMap(df_).add_to(map)\n", + "map" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Demonstração de carga de dados otimizados com Dask\n", + "\n", + "https://docs.dask.org/en/stable/dataframe-best-practices.html" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os, sys, warnings\n", + "\n", + "ROOT_DIR = '../..'\n", + "sys.path.append(ROOT_DIR)\n", + "os.chdir(ROOT_DIR)\n", + "\n", + "from dotenv import load_dotenv\n", + "load_dotenv('config/.env')\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import sys\n", + "import pandas as pd\n", + "import dask.dataframe as dd\n", + "from src.utils.datalake import DataLakeWrapper" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Carregando e filtrando dados de forma _lazy_" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
Dask DataFrame Structure:
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longitudelatitudealtitudehorizontal_reflectivitydatetimeyearmonthday
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Dask Name: read-parquet, 1 graph layer
" + ], + "text/plain": [ + "Dask DataFrame Structure:\n", + " longitude latitude altitude horizontal_reflectivity datetime year month day\n", + "npartitions=5 \n", + " float64 float64 float64 float64 datetime64[ns] category[known] category[known] category[known]\n", + " ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ...\n", + " ... ... ... ... ... ... ... ...\n", + " ... ... ... ... ... ... ... ...\n", + "Dask Name: read-parquet, 1 graph layer" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ddf = dd.read_parquet(\n", + " path='s3://staged/radar/inea/guaratiba', \n", + " filesystem=DataLakeWrapper().get_filesystem(),\n", + " engine='pyarrow',\n", + ")\n", + "print(type(ddf))\n", + "ddf" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "56" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "sys.getsizeof(ddf)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of rows: 13500000\n" + ] + } + ], + "source": [ + "print('Number of rows: ', ddf.shape[0].compute())" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + ">\n", + "> O processamento dos dados com Dask é realizado de forma _lazy_, ou seja, os dados são carregados e processados de forma sequencial, mas não são armazenados em memória.\n", + ">\n", + "> A variável que representa o dask dataframe (`ddf`) ocupa apenas 56 bytes em memória RAM, apesar de fazer referência à 13,5 milhões de registros." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 2020-09-20\n", + "1 2020-09-21\n", + "2 2020-09-22\n", + "3 2020-10-29\n", + "4 2021-02-04\n", + "Name: datetime, dtype: object" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ddf['datetime'].dt.date.unique().compute()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Size: 56\n" + ] + } + ], + "source": [ + "ddf = ddf[\n", + " (ddf['year'] == 2020) & \n", + " (ddf['month'] == 9) & \n", + " (ddf['day'] == 20)\n", + "]\n", + "ddf = ddf[ddf['altitude'] <= 3000]\n", + "ddf = ddf[['latitude', 'longitude', 'altitude', 'horizontal_reflectivity', 'datetime']]\n", + "ddf[['latitude', 'longitude']] = ddf[['latitude', 'longitude']].round(3)\n", + "ddf['altitude'] = ddf['altitude'].round(0)\n", + "\n", + "print(type(ddf))\n", + "print('Size: ', sys.getsizeof(ddf))" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of rows: 1816560\n" + ] + } + ], + "source": [ + "print('Number of rows: ', ddf.shape[0].compute())" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + ">\n", + "> É uma boa prática filtrar os dados com Dask para depois operá-los com Pandas.\n", + ">\n", + "> O dataset foi reduzido de 13,5 milhões de registros para 1,8 milhão de registros em poucos segundos em 0.1s e sem _overhead_ de memória RAM." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/html": [ + "
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latitudelongitudealtitudehorizontal_reflectivitydatetime
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" + ], + "text/plain": [ + " latitude longitude altitude horizontal_reflectivity datetime\n", + "0 -22.992 -43.588 124 94.0 2020-09-20 00:00:15\n", + "1 -22.990 -43.588 126 80.0 2020-09-20 00:00:15\n", + "2 -22.988 -43.588 128 30.0 2020-09-20 00:00:15\n", + "3 -22.985 -43.588 131 0.0 2020-09-20 00:00:15\n", + "4 -22.983 -43.588 133 0.0 2020-09-20 00:00:15" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "result = ddf.head()\n", + "print(type(result))\n", + "result" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + ">\n", + "> Alguns comandos do Dask não permitem manter o processamento de forma _lazy_.\n", + ">\n", + "> No exemplo acima o comando `head()` retorna um pandas dataframe." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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horizontal_reflectivity
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horizontal_reflectivity
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datetimelatitudelongitudealtitudehorizontal_reflectivity_minhorizontal_reflectivity_maxhorizontal_reflectivity_sumhorizontal_reflectivity_meanhorizontal_reflectivity_stdhorizontal_reflectivity_countyearmonthday
02019-02-16 00:00:00-22.99-43.5900.0122.03062152.048.44870638.016906632042019216
12019-02-16 00:00:00-22.98-43.5900.0118.080832.05.70847515.291518141602019216
22019-02-16 00:00:00-22.97-43.5900.0110.072738.07.62452816.11744495402019216
32019-02-16 00:00:00-22.96-43.5900.0158.0111623.021.09278224.18853352922019216
42019-02-16 00:00:00-22.95-43.5900.0107.0152280.032.87564827.23885446322019216
..........................................
4092672019-02-16 23:00:00-22.65-43.6040.060.0978.022.22727327.129203442019216
4092682019-02-16 23:00:00-22.68-43.5940.057.0265.024.09090927.919364112019216
4092692019-02-16 23:00:00-22.67-43.5940.063.01248.028.36363627.787475442019216
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4092712019-02-16 23:00:00-22.65-43.5940.060.0331.015.04545525.253905222019216
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48.448706 \n", + "1 80832.0 5.708475 \n", + "2 72738.0 7.624528 \n", + "3 111623.0 21.092782 \n", + "4 152280.0 32.875648 \n", + "... ... ... \n", + "409267 978.0 22.227273 \n", + "409268 265.0 24.090909 \n", + "409269 1248.0 28.363636 \n", + "409270 1237.0 22.490909 \n", + "409271 331.0 15.045455 \n", + "\n", + " horizontal_reflectivity_std horizontal_reflectivity_count year \\\n", + "0 38.016906 63204 2019 \n", + "1 15.291518 14160 2019 \n", + "2 16.117444 9540 2019 \n", + "3 24.188533 5292 2019 \n", + "4 27.238854 4632 2019 \n", + "... ... ... ... \n", + "409267 27.129203 44 2019 \n", + "409268 27.919364 11 2019 \n", + "409269 27.787475 44 2019 \n", + "409270 26.963537 55 2019 \n", + "409271 25.253905 22 2019 \n", + "\n", + " month day \n", + "0 2 16 \n", + "1 2 16 \n", + "2 2 16 \n", + "3 2 16 \n", + "4 2 16 \n", + "... ... .. \n", + "409267 2 16 \n", + "409268 2 16 \n", + "409269 2 16 \n", + "409270 2 16 \n", + "409271 2 16 \n", + "\n", + "[409272 rows x 13 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = ddf.compute()\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['2019-02-16T00:00:00.000000000', '2019-02-16T01:00:00.000000000',\n", + " '2019-02-16T02:00:00.000000000', '2019-02-16T03:00:00.000000000',\n", + " '2019-02-16T04:00:00.000000000', '2019-02-16T05:00:00.000000000',\n", + " '2019-02-16T06:00:00.000000000', '2019-02-16T07:00:00.000000000',\n", + " '2019-02-16T08:00:00.000000000', '2019-02-16T09:00:00.000000000',\n", + " '2019-02-16T10:00:00.000000000', '2019-02-16T11:00:00.000000000',\n", + " '2019-02-16T12:00:00.000000000', '2019-02-16T13:00:00.000000000',\n", + " '2019-02-16T14:00:00.000000000', '2019-02-16T15:00:00.000000000',\n", + " '2019-02-16T16:00:00.000000000', '2019-02-16T17:00:00.000000000',\n", + " '2019-02-16T18:00:00.000000000', '2019-02-16T19:00:00.000000000',\n", + " '2019-02-16T20:00:00.000000000', '2019-02-16T21:00:00.000000000',\n", + " '2019-02-16T22:00:00.000000000', '2019-02-16T23:00:00.000000000'],\n", + " dtype='datetime64[ns]')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.datetime.unique()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Análise Exploratória" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import os, sys, warnings\n", + "\n", + "ROOT_DIR = '../..'\n", + "sys.path.append(ROOT_DIR)\n", + "os.chdir(ROOT_DIR)\n", + "\n", + "from dotenv import load_dotenv\n", + "load_dotenv('config/.env')\n", + "\n", + "warnings.filterwarnings(\"ignore\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import pyarrow as pa\n", + "import pyarrow.parquet as pq\n", + "import dask.dataframe as dd\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.image as mpimg\n", + "from matplotlib.colors import LinearSegmentedColormap\n", + "from shapely.geometry import Point\n", + "import geopandas as gpd\n", + "import folium\n", + "\n", + "from src.utils.datalake import DataLakeWrapper" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "datetime: timestamp[us]\n", + "latitude: double\n", + "longitude: double\n", + "altitude: int64\n", + "horizontal_reflectivity_min: double\n", + "horizontal_reflectivity_max: double\n", + "horizontal_reflectivity_sum: double\n", + "horizontal_reflectivity_mean: double\n", + "horizontal_reflectivity_std: double\n", + "horizontal_reflectivity_count: int64\n", + "year: dictionary\n", + "month: dictionary\n", + "day: dictionary\n", + "-- schema metadata --\n", + "naming_authority: 'INEA - Instituto Estadual do Ambiente'\n", + "timezone: 'UTC'\n", + "instrument: 'radar'\n", + "variable_1: 'longitude (degrees)'\n", + "variable_2: 'latitude (degrees)'\n", + "variable_3: 'altitude (metres)'\n", + "variable_4: 'horizontal reflectivity (dBZ)'" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "remote_path = 'staged/radar/inea/guaratiba_agg/'\n", + "filters = [\n", + " ('year', '==', 2016), \n", + " ('month', '==', 9),\n", + " ('day', '==', 19),\n", + "]\n", + "table = pq.read_table(\n", + " remote_path,\n", + " filters=filters,\n", + " filesystem=DataLakeWrapper().get_filesystem(),\n", + ")\n", + "table.schema" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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1001658 rows × 13 columns

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" + ], + "text/plain": [ + " datetime latitude longitude altitude \\\n", + "0 2016-09-19 00:00:00 -22.99 -43.59 0 \n", + "1 2016-09-19 00:00:00 -22.98 -43.59 0 \n", + "2 2016-09-19 00:00:00 -22.97 -43.59 0 \n", + "3 2016-09-19 00:00:00 -22.96 -43.59 0 \n", + "4 2016-09-19 00:00:00 -22.95 -43.59 0 \n", + "... ... ... ... ... \n", + "1001653 2016-09-19 23:00:00 -22.65 -43.88 0 \n", + "1001654 2016-09-19 23:00:00 -22.65 -43.18 0 \n", + "1001655 2016-09-19 23:00:00 -22.70 -43.05 0 \n", + "1001656 2016-09-19 23:00:00 -22.66 -43.12 0 \n", + "1001657 2016-09-19 23:00:00 -22.79 -43.05 0 \n", + "\n", + " horizontal_reflectivity_min horizontal_reflectivity_max \\\n", + "0 0.0 134.0 \n", + "1 0.0 132.0 \n", + "2 0.0 127.0 \n", + "3 0.0 120.0 \n", + "4 0.0 118.0 \n", + "... ... ... \n", + "1001653 0.0 0.0 \n", + "1001654 0.0 0.0 \n", + "1001655 0.0 0.0 \n", + "1001656 0.0 0.0 \n", + "1001657 0.0 0.0 \n", + "\n", + " horizontal_reflectivity_sum horizontal_reflectivity_mean \\\n", + "0 1931391.0 77.101437 \n", + "1 440124.0 80.682676 \n", + "2 257253.0 82.931335 \n", + "3 175927.0 77.535037 \n", + "4 101640.0 80.666667 \n", + "... ... ... \n", + "1001653 0.0 0.000000 \n", + "1001654 0.0 0.000000 \n", + "1001655 0.0 0.000000 \n", + "1001656 0.0 0.000000 \n", + "1001657 0.0 0.000000 \n", + "\n", + " horizontal_reflectivity_std horizontal_reflectivity_count year \\\n", + "0 26.677434 25050 2016 \n", + "1 34.804445 5455 2016 \n", + "2 31.305716 3102 2016 \n", + "3 36.385517 2269 2016 \n", + "4 30.069366 1260 2016 \n", + "... ... ... ... \n", + "1001653 NaN 1 2016 \n", + "1001654 NaN 1 2016 \n", + "1001655 NaN 1 2016 \n", + "1001656 NaN 1 2016 \n", + "1001657 NaN 1 2016 \n", + "\n", + " month day \n", + "0 9 19 \n", + "1 9 19 \n", + "2 9 19 \n", + "3 9 19 \n", + "4 9 19 \n", + "... ... .. \n", + "1001653 9 19 \n", + "1001654 9 19 \n", + "1001655 9 19 \n", + "1001656 9 19 \n", + "1001657 9 19 \n", + "\n", + "[1001658 rows x 13 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df = table.to_pandas()\n", + "df" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Geopoints" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 99751\n", + "1 99108\n", + "2 98240\n", + "3 95875\n", + "4 92427\n", + "5 87047\n", + "6 79743\n", + "7 70116\n", + "8 57522\n", + "9 48672\n", + "10 37512\n", + "11 32613\n", + "12 24271\n", + "13 20634\n", + "14 15596\n", + "15 10662\n", + "16 10171\n", + "17 7122\n", + "18 5370\n", + "19 4464\n", + "20 2485\n", + "21 1257\n", + "22 716\n", + "23 273\n", + "24 11\n", + "Name: altitude, dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['altitude'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " datetime latitude longitude altitude horizontal_reflectivity_min \\\n", + "0 2016-09-19 -22.99 -43.59 0 0.0 \n", + "1 2016-09-19 -22.98 -43.59 0 0.0 \n", + "2 2016-09-19 -22.97 -43.59 0 0.0 \n", + "3 2016-09-19 -22.96 -43.59 0 0.0 \n", + "4 2016-09-19 -22.95 -43.59 0 0.0 \n", + "... ... ... ... ... ... \n", + "41866 2016-09-19 -22.65 -43.18 0 0.0 \n", + "41867 2016-09-19 -22.66 -43.12 0 0.0 \n", + "41868 2016-09-19 -22.70 -43.05 0 0.0 \n", + "41869 2016-09-19 -22.79 -43.05 0 0.0 \n", + "41870 2016-09-19 -22.65 -43.88 0 54.0 \n", + "\n", + " horizontal_reflectivity_max horizontal_reflectivity_sum \\\n", + "0 134.0 1931391.0 \n", + "1 132.0 440124.0 \n", + "2 127.0 257253.0 \n", + "3 120.0 175927.0 \n", + "4 118.0 101640.0 \n", + "... ... ... \n", + "41866 0.0 0.0 \n", + "41867 0.0 0.0 \n", + "41868 0.0 0.0 \n", + "41869 0.0 0.0 \n", + "41870 54.0 54.0 \n", + "\n", + " horizontal_reflectivity_mean horizontal_reflectivity_std \\\n", + "0 77.101437 26.677434 \n", + "1 80.682676 34.804445 \n", + "2 82.931335 31.305716 \n", + "3 77.535037 36.385517 \n", + "4 80.666667 30.069366 \n", + "... ... ... \n", + "41866 0.000000 NaN \n", + "41867 0.000000 NaN \n", + "41868 0.000000 NaN \n", + "41869 0.000000 NaN \n", + "41870 54.000000 NaN \n", + "\n", + " horizontal_reflectivity_count year month day \n", + "0 25050 2016 9 19 \n", + "1 5455 2016 9 19 \n", + "2 3102 2016 9 19 \n", + "3 2269 2016 9 19 \n", + "4 1260 2016 9 19 \n", + "... ... ... ... .. \n", + "41866 1 2016 9 19 \n", + "41867 1 2016 9 19 \n", + "41868 1 2016 9 19 \n", + "41869 1 2016 9 19 \n", + "41870 1 2016 9 19 \n", + "\n", + "[4159 rows x 13 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.query('altitude == 0 & datetime == \"2016-09-19 00:00:00\"')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
datetimelatitudelongitudealtitudehorizontal_reflectivity_minhorizontal_reflectivity_maxhorizontal_reflectivity_sumhorizontal_reflectivity_meanhorizontal_reflectivity_stdhorizontal_reflectivity_countyearmonthday
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\n", + "
" + ], + "text/plain": [ + " datetime latitude longitude altitude horizontal_reflectivity_min \\\n", + "41767 2016-09-19 -22.65 -43.05 24 0.0 \n", + "\n", + " horizontal_reflectivity_max horizontal_reflectivity_sum \\\n", + "41767 0.0 0.0 \n", + "\n", + " horizontal_reflectivity_mean horizontal_reflectivity_std \\\n", + "41767 0.0 0.0 \n", + "\n", + " horizontal_reflectivity_count year month day \n", + "41767 2 2016 9 19 " + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.query('altitude == 24 & datetime == \"2016-09-19 00:00:00\"')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + ">\n", + "> Há mais pontos de observação em altitudes menores.\n", + ">\n", + "> Isso é consistente, já que as as regiões mais próximas do radar necessitam de um ângulo de elevação muito alto para ser capaz de observar altitudes maiores.\n", + ">\n", + "> * A imagem abaixo apresenta a relação entre a altitude e o ângulo de elevação do radar.\n", + "> \n", + "> ![radar elevation altitudes](images/radar_elevation_altitude.jpg)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Pontos observados em baixa altitude" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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latitudelongitudegeometry
0-22.99-43.59POINT (-43.59000 -22.99000)
1-22.98-43.59POINT (-43.59000 -22.98000)
2-22.97-43.59POINT (-43.59000 -22.97000)
3-22.96-43.59POINT (-43.59000 -22.96000)
4-22.95-43.59POINT (-43.59000 -22.95000)
............
41866-22.65-43.18POINT (-43.18000 -22.65000)
41867-22.66-43.12POINT (-43.12000 -22.66000)
41868-22.70-43.05POINT (-43.05000 -22.70000)
41869-22.79-43.05POINT (-43.05000 -22.79000)
41870-22.65-43.88POINT (-43.88000 -22.65000)
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4159 rows × 3 columns

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" + ], + "text/plain": [ + " latitude longitude geometry\n", + "0 -22.99 -43.59 POINT (-43.59000 -22.99000)\n", + "1 -22.98 -43.59 POINT (-43.59000 -22.98000)\n", + "2 -22.97 -43.59 POINT (-43.59000 -22.97000)\n", + "3 -22.96 -43.59 POINT (-43.59000 -22.96000)\n", + "4 -22.95 -43.59 POINT (-43.59000 -22.95000)\n", + "... ... ... ...\n", + "41866 -22.65 -43.18 POINT (-43.18000 -22.65000)\n", + "41867 -22.66 -43.12 POINT (-43.12000 -22.66000)\n", + "41868 -22.70 -43.05 POINT (-43.05000 -22.70000)\n", + "41869 -22.79 -43.05 POINT (-43.05000 -22.79000)\n", + "41870 -22.65 -43.88 POINT (-43.88000 -22.65000)\n", + "\n", + "[4159 rows x 3 columns]" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "unique_coords = df.query('altitude == 0 & datetime == \"2016-09-19 00:00:00\"')[['latitude', 'longitude']].drop_duplicates()\n", + "geometry = [Point(xy) for xy in zip(unique_coords['longitude'], unique_coords['latitude'])]\n", + "gdf = gpd.GeoDataFrame(unique_coords, geometry=geometry, crs='EPSG:4326')\n", + "gdf" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "map = folium.Map(\n", + " location=[-22.891814, -43.469477], \n", + " zoom_start=10,\n", + ")\n", + "# folium.GeoJson(gdf).add_to(map)\n", + "for i, row in gdf.iterrows():\n", + " folium.CircleMarker(\n", + " location=[row['latitude'], row['longitude']],\n", + " radius=1,\n", + " color='blue',\n", + " fill_color='blue'\n", + " ).add_to(map)\n", + "map" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Pontos observados a cada range de altitude" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.cpg',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.dbf',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.prj',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.shp',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.shx']" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "remote_path = os.path.join('landing', 'meshes', 'alertario', 'rainfall_zones', 'zonas_pluviometricas_rj_shapefile') \n", + "local_dir = os.path.join('data', 'radar')\n", + "objects = DataLakeWrapper().download_files_recursively(remote_path, local_dir)\n", + "objects" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "shapefile = [f for f in objects if f.endswith('.shp')][0]\n", + "rj_city = gpd.read_file(shapefile)\n", + "rj_city = rj_city.to_crs(epsg=4674)\n", + "\n", + "def plot_rj_city(plt_args={}):\n", + " fig, ax = plt.subplots()\n", + " rj_city.plot(\n", + " ax=ax,\n", + " alpha=1,\n", + " **plt_args\n", + " )\n", + " return fig, ax\n", + "\n", + "def get_gdf(df):\n", + " unique_coords = df[['latitude', 'longitude']].drop_duplicates()\n", + " geometry = [Point(xy) for xy in zip(unique_coords['longitude'], unique_coords['latitude'])]\n", + " gdf = gpd.GeoDataFrame(unique_coords, geometry=geometry, crs='EPSG:4674')\n", + " return gdf" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "figures_path = 'data/radar/figures/geopoints'\n", + "os.makedirs(figures_path, exist_ok=True)\n", + "plt_args = {\n", + " 'color': 'lightgrey',\n", + " 'edgecolor': 'blue',\n", + " 'linewidth': 0.5,\n", + "}\n", + "hour = '2016-09-19 00:00:00'\n", + "for altitude in list(range(25)):\n", + " fig, ax = plot_rj_city(plt_args)\n", + " gdf = get_gdf(df.query(f'altitude == {altitude} & datetime == \"{hour}\"'))\n", + " gdf.plot(\n", + " ax=ax, \n", + " markersize=5, \n", + " alpha=0.3,\n", + " color='blue'\n", + " )\n", + " ax.set_title(f'Datetime: {hour} / Altitude={altitude+1} km')\n", + " fig.tight_layout()\n", + " fig.savefig(f'{figures_path}/up_to_{str(altitude+1).zfill(2)}.png', dpi=300)\n", + " plt.close(fig)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "figures = sorted(os.listdir(figures_path))\n", + "figures = [figures[i] for i in [0,4,8,12]]\n", + "fig, axes = plt.subplots(2,2, figsize=(12,8))\n", + "for figure, ax in zip(figures, axes.flatten()):\n", + " ax.imshow(mpimg.imread(os.path.join(figures_path, figure)))\n", + " ax.set_axis_off()\n", + "fig.tight_layout()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> Cada ponto azul representa um par (latitude, longitude) observado pelo radar.\n", + "> \n", + "> As regiões mais próximas do radar não são observadas em altitudes maiores." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Refletividade" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "def get_gdf(df):\n", + " reflectivity = df[['latitude', 'longitude', 'horizontal_reflectivity_mean']].groupby(['latitude', 'longitude']).mean().reset_index()\n", + " geometry = [Point(xy) for xy in zip(reflectivity['longitude'], reflectivity['latitude'])]\n", + " gdf = gpd.GeoDataFrame(reflectivity, geometry=geometry, crs='EPSG:4674')\n", + " return gdf" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [], + "source": [ + "figures_path = 'data/radar/figures/reflectivity'\n", + "os.makedirs(figures_path, exist_ok=True)\n", + "hours = pd.date_range('2016-09-19 00:00:00', '2016-09-19 23:00:00', freq='1H')\n", + "altitude = 0\n", + "vmin, vmax = df['horizontal_reflectivity_mean'].min(), df['horizontal_reflectivity_mean'].max()\n", + "colors = [\"blue\", \"green\", \"yellow\", \"red\", \"purple\"]\n", + "cmap = LinearSegmentedColormap.from_list(\"custom_colormap\", colors)\n", + "for hour in hours:\n", + " fig, ax = plot_rj_city(plt_args)\n", + " df_tmp = df.query(f'altitude == {altitude} & datetime == \"{hour}\"')\n", + " gdf = get_gdf(df_tmp)\n", + " gdf.plot(\n", + " column='horizontal_reflectivity_mean',\n", + " cmap=cmap,\n", + " vmin=vmin,\n", + " vmax=vmax,\n", + " ax=ax,\n", + " alpha=0.2,\n", + " legend=True, \n", + " legend_kwds={'label': \"Refletividade (dBZ)\"}\n", + " )\n", + " # plt.colorbar(ax.get_children()[1], ax=ax, shrink=0.5, colors=colors, vmin=vmin, vmax=vmax)\n", + " fig.tight_layout()\n", + " ax.set_title(f'Datetime: {hour.strftime(\"%Y-%m-%d %H:%M:%S\")} / Altitude=1 km')\n", + " fig.savefig(f'{figures_path}/reflectivity_at_{hour.strftime(\"%H\")}h.png', dpi=300)\n", + " plt.close(fig)" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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datetimelatitudelongitudealtitudehorizontal_reflectivity_mean
02016-11-12 00:00:00-23.02-43.65011.836508
12016-11-12 00:00:00-23.02-43.6408.429251
22016-11-12 00:00:00-23.01-43.63010.506431
32016-11-12 00:00:00-23.00-43.59027.785027
42016-11-12 00:00:00-23.01-43.6206.814247
..................
1203031122023-01-03 23:00:00-22.65-43.6048.291667
1203031132023-01-03 23:00:00-22.68-43.59410.000000
1203031142023-01-03 23:00:00-22.67-43.5946.645833
1203031152023-01-03 23:00:00-22.66-43.5947.100000
1203031162023-01-03 23:00:00-22.65-43.5947.708333
\n", + "

120303117 rows × 5 columns

\n", + "
" + ], + "text/plain": [ + " datetime latitude longitude altitude \\\n", + "0 2016-11-12 00:00:00 -23.02 -43.65 0 \n", + "1 2016-11-12 00:00:00 -23.02 -43.64 0 \n", + "2 2016-11-12 00:00:00 -23.01 -43.63 0 \n", + "3 2016-11-12 00:00:00 -23.00 -43.59 0 \n", + "4 2016-11-12 00:00:00 -23.01 -43.62 0 \n", + "... ... ... ... ... \n", + "120303112 2023-01-03 23:00:00 -22.65 -43.60 4 \n", + "120303113 2023-01-03 23:00:00 -22.68 -43.59 4 \n", + "120303114 2023-01-03 23:00:00 -22.67 -43.59 4 \n", + "120303115 2023-01-03 23:00:00 -22.66 -43.59 4 \n", + "120303116 2023-01-03 23:00:00 -22.65 -43.59 4 \n", + "\n", + " horizontal_reflectivity_mean \n", + "0 11.836508 \n", + "1 8.429251 \n", + "2 10.506431 \n", + "3 27.785027 \n", + "4 6.814247 \n", + "... ... \n", + "120303112 8.291667 \n", + "120303113 10.000000 \n", + "120303114 6.645833 \n", + "120303115 7.100000 \n", + "120303116 7.708333 \n", + "\n", + "[120303117 rows x 5 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "path = 'staged/radar/inea/guaratiba_agg/'\n", + "columns = ['datetime', 'latitude', 'longitude', 'altitude', 'horizontal_reflectivity_mean']\n", + "df = pq.read_table(\n", + " path,\n", + " columns=columns,\n", + " filesystem=DataLakeWrapper().get_filesystem(),\n", + ").to_pandas()\n", + "df" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Duplicatas completas\n", + "\n", + "É a duplicata que possui todos os valores iguais em todas as colunas." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of duplicates dropped: 0\n", + "Percentage of duplicates dropped: 0.00%\n" + ] + } + ], + "source": [ + "n_rows = df.shape[0]\n", + "df.drop_duplicates(inplace=True)\n", + "current_n_rows = df.shape[0]\n", + "print(f'Number of duplicates dropped: {n_rows - current_n_rows}')\n", + "print(f'Percentage of duplicates dropped: {(n_rows - current_n_rows) / n_rows * 100:.2f}%')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Duplicatas temporais (inconsistência temporal)\n", + "\n", + "São registros que apresentam o mesmo timestamp (para uma mesma região no espaço) e valores diferentes em pelo menos uma coluna." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Number of temporal duplicates dropped: 0\n", + "Percentage of temporal duplicates dropped: 0.00%\n" + ] + } + ], + "source": [ + "n_rows = current_n_rows\n", + "df.drop_duplicates(subset=['datetime', 'latitude', 'longitude', 'altitude'], inplace=True)\n", + "current_n_rows = df.shape[0]\n", + "print(f'Number of temporal duplicates dropped: {n_rows - current_n_rows}')\n", + "print(f'Percentage of temporal duplicates dropped: {(n_rows - current_n_rows) / n_rows * 100:.2f}%')" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> Não há duplicatas de qualquer tipo." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Análise de operação do radar" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Altitude máxima observada" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df_altitude_max = df.groupby('datetime').agg({'altitude': 'max'}).resample('Y').max()\n", + "df_altitude_max.index = df_altitude_max.index.year\n", + "df_altitude_max.rename(columns={'altitude': 'max altitude'}, inplace=True)\n", + "df_altitude_max.plot(\n", + " kind='bar',\n", + " ylabel='Altitude (km)',\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df_altitude_max = df.query('datetime.dt.year == 2017')\n", + "df_altitude_max = df_altitude_max.groupby('datetime').agg({'altitude': 'max'}).resample('D').max().dropna()\n", + "df_altitude_max.rename(columns={'altitude': 'max altitude'}, inplace=True)\n", + "df_altitude_max.plot(\n", + " kind='bar',\n", + " figsize=(18,6),\n", + " ylabel='Altitude (km)',\n", + " rot=90,\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> A partir do mês de dezembro de 2017, a altitude máxima observada pelo radar foi reduzida de 24km para 7km." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Quantidade de registros por data e altitude" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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2016-09-201000011
2016-11-041001710
2016-11-051002241
2016-11-061002081
......
2023-01-02409632
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2023-01-12409632
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\n", + "
" + ], + "text/plain": [ + " count\n", + "datetime \n", + "2016-09-19 1001658\n", + "2016-09-20 1000011\n", + "2016-11-04 1001710\n", + "2016-11-05 1002241\n", + "2016-11-06 1002081\n", + "... ...\n", + "2023-01-02 409632\n", + "2023-01-03 409632\n", + "2023-01-12 409632\n", + "2023-01-13 409632\n", + "2023-01-19 409632\n", + "\n", + "[224 rows x 1 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_count = df['datetime'].to_frame().groupby(df['datetime'].dt.date).count().rename(columns={'datetime': 'count'})\n", + "df_count" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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1279 rows × 4 columns

\n", + "
" + ], + "text/plain": [ + " altitude datetime count mean\n", + "10 0 2016-12-03 24929 96051.285714\n", + "11 0 2016-12-11 87264 96051.285714\n", + "53 0 2017-11-20 70618 96051.285714\n", + "55 0 2017-11-30 74783 96051.285714\n", + "59 0 2017-12-23 58310 96051.285714\n", + "... ... ... ... ...\n", + "1787 7 2023-01-02 1080 17756.214286\n", + "1788 7 2023-01-03 1080 17756.214286\n", + "1789 7 2023-01-12 1080 17756.214286\n", + "1790 7 2023-01-13 1080 17756.214286\n", + "1791 7 2023-01-19 1080 17756.214286\n", + "\n", + "[1279 rows x 4 columns]" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "deviation = 5/100\n", + "df_count \\\n", + " .reset_index() \\\n", + " .merge(df_count_mean, on='altitude') \\\n", + " .query(f'count > mean * (1 + {deviation}) | count < mean * (1 - {deviation})') \\\n", + " .query('altitude <= 7')" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0, 1, 2, 3, 4, 5])" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_sample = df.query('datetime >= \"2016-12-03\" & datetime < \"2016-12-04\" & altitude == 0')\n", + "df_sample['datetime'].dt.hour.unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "99716.0" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "24929 / 6 * 24" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> Existem 1279 pares (data, altitude) com 5% à mais ou a menos de valores observados no espaço do que a média esperada.\n", + "> \n", + "> Um valor observado é um valor de refletividade medido para um ponto no espaço (lat/lon) e um ponto no tempo.\n", + "> \n", + "> Analisando os dados da data `2016-12-03` constata-se que apenas foram registradas as 6 primeiras horas do dia. Fazendo a proporção temos:\n", + "> \n", + "> 24929 observações em 6 horas = 4154 observações por hora = 99716 observações por dia que é o valor próximo da média esperada por dia (96051).\n", + "> \n", + "> ```python\n", + "> >>> 24929 / 6 * 24\n", + "> 99716.0\n", + "> ```" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.cpg',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.dbf',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.prj',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.shp',\n", + " 'data/radar/landing/meshes/alertario/rainfall_zones/zonas_pluviometricas_rj_shapefile/Zonas_Pluviometricas.shx']" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "remote_path = os.path.join('landing', 'meshes', 'alertario', 'rainfall_zones', 'zonas_pluviometricas_rj_shapefile') \n", + "local_dir = os.path.join('data', 'radar')\n", + "objects = DataLakeWrapper().download_files_recursively(remote_path, local_dir)\n", + "objects" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [], + "source": [ + "shapefile = [f for f in objects if f.endswith('.shp')][0]\n", + "rj_city = gpd.read_file(shapefile)\n", + "rj_city = rj_city.to_crs(epsg=4674)\n", + "\n", + "def get_gdf(df):\n", + " unique_coords = df[['latitude', 'longitude']].drop_duplicates()\n", + " geometry = [Point(xy) for xy in zip(unique_coords['longitude'], unique_coords['latitude'])]\n", + " gdf = gpd.GeoDataFrame(unique_coords, geometry=geometry, crs='EPSG:4674')\n", + " return gdf" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt_args = {\n", + " 'color': 'lightgrey',\n", + " 'edgecolor': 'blue',\n", + " 'linewidth': 0.5,\n", + "}\n", + "times = pd.date_range('2016-12-03', periods=6, freq='H')\n", + "fig, axes = plt.subplots(3,2, figsize=(12,12))\n", + "for time, ax in zip(times, axes.flatten()):\n", + " df_sample = df.query('datetime == @time')\n", + " rj_city.plot(\n", + " ax=ax,\n", + " alpha=1,\n", + " **plt_args\n", + " )\n", + " gdf = get_gdf(df_sample)\n", + " gdf.plot(\n", + " ax=ax, \n", + " markersize=5, \n", + " alpha=0.3,\n", + " color='blue'\n", + " )\n", + " ax.set_title(f'Datetime: {time.strftime(\"%Y-%m-%d %H:%M:%S\")}')\n", + "fig.tight_layout()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> O plot acima confirma que para os horários observados pelo radar na data `2016-12-03`, os pontos espaciais foram devidamente cobertos.\n", + ">\n", + "> É provável que a quantidade menor de observações para determinadas datas seja devido a falhas no equipamento em determinados horários." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Análise de dados faltantes" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['horizontal_reflectivity_mean'].isnull().sum()" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> Não há valores nulos para a refletividade média" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Análise de distribuição" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def trim_axes(axs, n):\n", + " \"\"\"\n", + " Reduce *axs* to *n* Axes. All further Axes are removed from the figure.\n", + " \"\"\"\n", + " axs = axs.flat\n", + " for ax in axs[n:]:\n", + " ax.remove()\n", + " return axs[:n]\n", + "\n", + "\n", + "def plot_variable(df, variable, unit):\n", + " altitudes = df['altitude'].unique()\n", + " n_cols = 2\n", + " n_rows = int(np.ceil(len(altitudes) / n_cols))\n", + " fig, axes = plt.subplots(n_rows, n_cols, figsize=(10, n_rows*2.5))\n", + " axes = trim_axes(axes, len(altitudes))\n", + " for altitude, ax in zip(altitudes, axes.flatten()):\n", + " df.query('altitude == @altitude').set_index('datetime')[variable].plot(\n", + " lw=0, \n", + " marker=\".\",\n", + " ax=ax,\n", + " xlabel='',\n", + " ylabel=unit,\n", + " title=f'Altitude: {altitude+1} km',\n", + " legend=False,\n", + " )\n", + " fig.suptitle(f'Distribuição da variável {variable}', fontsize=16)\n", + " fig.tight_layout()\n", + " # fig.savefig(f'data/{variable}_distribution.png')\n", + "\n", + "\n", + "def plot_hist_box(df, variable, unit):\n", + " fig, axes = plt.subplots(1, 2, figsize=(10, 4))\n", + " df[variable].plot(\n", + " kind='hist', \n", + " bins=100,\n", + " ax=axes[0],\n", + " )\n", + " df[variable].plot(\n", + " kind='box', \n", + " ax=axes[1],\n", + " ylabel=unit,\n", + " )\n", + " axes[0].set_xlabel(unit)\n", + " axes[0].set_ylabel('Frequência')\n", + " fig.suptitle(f'Distribuição da variável {variable}', fontsize=16)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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horizontal_reflectivity_mean
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mean6.83
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\n", + "
" + ], + "text/plain": [ + " horizontal_reflectivity_mean\n", + "count 120,303,117.00\n", + "mean 6.83\n", + "std 18.93\n", + "min 0.00\n", + "25% 0.00\n", + "50% 0.00\n", + "75% 0.34\n", + "max 157.09" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "variable = 'horizontal_reflectivity_mean'\n", + "unit='reflectivity (dBZ)'\n", + "\n", + "df[[variable]].describe().applymap('{:,.2f}'.format)" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_hist_box(df, variable, unit)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "df = df[['altitude', 'datetime', variable]].query(f'{variable} > 0.0')\n", + "plot_variable(df, variable, unit)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "> #### Nota\n", + "> \n", + "> Pelo menos 50% dos valores de refletividade média são iguais à 0 dBZ e valores acima de 0.34 dBZ estão presentes somente no último quartil, chegando à um máximo de 157.09 dBZ.\n", + "> \n", + "> Observa-se no intervalo de altitude [1,8] km refletividades máximas entre 100 dBZ e 150 dBZ. \n", + ">\n", + "> A partir de 9 km observa-se refletividades máximas entre 10 dBZ e 12.5 dBZ, com exceção para 9 km e 11 km que registram máximas de 80 dBZ e 40 dBZ, respectivamente.\n", + "> \n", + "> Como esperado, a quantidade de valores 0.0 é muito alta." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/mapa.html b/notebooks/mapa.html new file mode 100644 index 00000000..761df536 --- /dev/null +++ b/notebooks/mapa.html @@ -0,0 +1,1395 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + + + + + + + + jQuery UI Draggable - Default functionality + + + + + + + + + + +
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  • Sirenes
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  • INMET
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  • COR_Pluviométricas
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+
+ + + + + + + + + \ No newline at end of file diff --git a/notebooks/lafusion.ipynb b/notebooks/misc/2023_lafusion.ipynb similarity index 100% rename from notebooks/lafusion.ipynb rename to notebooks/misc/2023_lafusion.ipynb diff --git a/notebooks/misc/2024_monan.ipynb b/notebooks/misc/2024_monan.ipynb new file mode 100644 index 00000000..6d501d9a --- /dev/null +++ b/notebooks/misc/2024_monan.ipynb @@ -0,0 +1,452 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# XGBoost" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# %load ../src/globals.py\n", + "INMET_API_BASE_URL = \"https://apitempo.inmet.gov.br\"\n", + "\n", + "# Weather stations datasource directories\n", + "WS_INMET_DATA_DIR = \"./data/ws/inmet/\"\n", + "WS_ALERTARIO_DATA_DIR = \"./data/ws/alertario/ws/\"\n", + "GS_ALERTARIO_DATA_DIR = \"./data/ws/alertario/rain_gauge_era5_fused/\"\n", + "\n", + "# WS_GOES_DATA_DIR = \"atmoseer/data/ws/goes16\"\n", + "GOES_DATA_DIR = \"./data/goes16\"\n", + "\n", + "# Atmospheric sounding datasource directory\n", + "NWP_DATA_DIR = \"./data/NWP/\"\n", + "\n", + "# Atmospheric sounding datasource directory\n", + "AS_DATA_DIR = \"./data/as/\"\n", + "\n", + "#GOES16/DSI directory\n", + "DSI_DATA_DIR = \"./data/goes16/DSI\"\n", + "\n", + "# GOES16/TPW directory\n", + "TPW_DATA_DIR = \"./data/goes16/wsoi\"\n", + "\n", + "# Directory to store the train/val/test datasets for each weather station of interest\n", + "DATASETS_DIR = './data/datasets/'\n", + "\n", + "# Directory to store the generated models and their corresponding reports\n", + "MODELS_DIR = './models/'\n", + "\n", + "# see https://portal.inmet.gov.br/paginas/catalogoaut\n", + "INMET_WEATHER_STATION_IDS = (\n", + " 'A601', # Seropédica\n", + " 'A602', # Marambaia\n", + " 'A621', # Vila militar\n", + " 'A627', # Niteroi\n", + " 'A636', # Jacarepagua\n", + " 'A652' # Forte de Copacabana\n", + ")\n", + "\n", + "ALERTARIO_GAUGE_STATION_IDS = (\n", + " 'anchieta', \n", + " 'av_brasil_mendanha', \n", + " 'bangu', \n", + " 'barrinha', \n", + " 'campo_grande', \n", + " 'cidade_de_deus', \n", + " 'copacabana', \n", + " 'grajau_jacarepagua', \n", + " 'grajau', \n", + " 'grande_meier', \n", + " 'grota_funda', \n", + " 'ilha_do_governador', \n", + " 'laranjeiras', \n", + " 'madureira', \n", + " 'penha', \n", + " 'piedade', \n", + " 'recreio', \n", + " 'rocinha',\n", + " 'santa_teresa',\n", + " 'saude', \n", + " 'sepetiba', \n", + " 'tanque', \n", + " 'tijuca_muda', \n", + " 'tijuca', \n", + " 'urca',\n", + " 'alto_da_boa_vista', #**\n", + " 'iraja', #**\n", + " 'jardim_botanico', #**\n", + " 'riocentro', #**\n", + " 'santa_cruz', #**\n", + " 'vidigal' #**\n", + " )\n", + "\n", + "ALERTARIO_WEATHER_STATION_IDS = (\n", + " 'guaratiba', #**\n", + " 'sao_cristovao' #**\n", + " )\n", + "\n", + "# hyper_params_dict_bc = {\n", + "# \"N_EPOCHS\" : 3500,\n", + "# \"PATIENCE\" : 1000,\n", + "# \"BATCH_SIZE\" : 1024,\n", + "# \"WEIGHT_DECAY\" : 0,\n", + "# \"LEARNING_RATE\" : 0.0003,\n", + "# \"DROPOUT_RATE\" : 0.5,\n", + "# \"SLIDING_WINDOW_SIZE\" : 6\n", + "# }\n", + "\n", + "# hyper_params_dict_oc = {\n", + "# \"N_EPOCHS\" : 6000,\n", + "# \"PATIENCE\" : 1000,\n", + "# \"BATCH_SIZE\" : 1024,\n", + "# \"WEIGHT_DECAY\" : 0,\n", + "# \"LEARNING_RATE\" : 3e-6,\n", + "# \"DROPOUT_RATE\" : 0.5,\n", + "# \"SLIDING_WINDOW_SIZE\" : 6\n", + "# }\n", + "\n", + "\n", + "# Observed variables for INMET weather stations:\n", + "# ,DC_NOME,\n", + "# PRE_INS,\n", + "# TEM_SEN,\n", + "# VL_LATITUDE,\n", + "# PRE_MAX,UF,\n", + "# RAD_GLO,\n", + "# PTO_INS,\n", + "# TEM_MIN,\n", + "# VL_LONGITUDE,\n", + "# UMD_MIN,\n", + "# PTO_MAX,\n", + "# VEN_DIR,\n", + "# DT_MEDICAO,\n", + "# CHUVA,\n", + "# PRE_MIN,\n", + "# UMD_MAX,\n", + "# VEN_VEL,\n", + "# PTO_MIN,\n", + "# TEM_MAX,\n", + "# TEN_BAT,\n", + "# VEN_RAJ,\n", + "# TEM_CPU,\n", + "# TEM_INS,\n", + "# UMD_INS,\n", + "# CD_ESTACAO,\n", + "# HR_MEDICAO" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# %load ../src/train/xgboost.py\n", + "from sklearn.ensemble import GradientBoostingClassifier\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.metrics import confusion_matrix\n", + "import pickle\n", + "from sklearn.metrics import classification_report\n", + "\n", + "def _train_and_test_classifier(X_train, y_train, X_test, y_test):\n", + "\n", + " print(f\"Shapes before reshaping: \", X_train.shape, X_test.shape)\n", + " X_train = X_train.reshape(len(X_train), -1)\n", + " X_test = X_test.reshape(len(X_test), -1)\n", + " print(f\"Shapes after reshaping: \", X_train.shape, X_test.shape)\n", + "\n", + " y_train[y_train>0] = 1\n", + " y_test[y_test>0] = 1\n", + "\n", + " # Create a GradientBoostingClassifier object with default hyperparameters\n", + " clf = GradientBoostingClassifier()\n", + "\n", + " # Train the classifier\n", + " clf.fit(X_train, y_train)\n", + " \n", + " # Make predictions on the testing data\n", + " y_pred = clf.predict(X_test.reshape(len(X_test), -1))\n", + " \n", + " y_true = y_test\n", + " y_true[y_true>0] = 1\n", + "\n", + " # Calculate the confusion matrix\n", + " cm = confusion_matrix(y_true, y_pred)\n", + "\n", + " return cm, y_true, y_pred\n", + "\n", + "def report_results(cm, y_true, y_pred, title = None):\n", + " # Define the class labels\n", + " class_names = ['Negative', 'Positive']\n", + "\n", + " # Create a heatmap using Seaborn\n", + " sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=class_names, yticklabels=class_names)\n", + "\n", + " # Add labels and title\n", + " plt.xlabel('Predicted label')\n", + " plt.ylabel('True label')\n", + "\n", + " if title is not None:\n", + " plt.title('Confusion Matrix - ' + title)\n", + " else:\n", + " plt.title('Confusion Matrix')\n", + "\n", + " # Show the plot\n", + " plt.show()\n", + "\n", + " # Build the classification report\n", + " target_names = ['Negative', 'Positive']\n", + " report = classification_report(y_true, y_pred, target_names=target_names)\n", + "\n", + " # Print the classification report\n", + " print(report)\n", + "\n", + "def train_and_test_classifier(pipeline_id):\n", + " filename = f\"../data/datasets/{pipeline_id}.pickle\"\n", + " print(f\"Loading train/val/test datasets from {filename}.\")\n", + " file = open(filename, 'rb')\n", + " (X_train, y_train, X_val, y_val, X_test, y_test) = pickle.load(file)\n", + " print(f\"Shapes of train/val/test data matrices: {X_train.shape}/{X_val.shape}/{X_test.shape}\")\n", + " cm, y_true, y_pred = _train_and_test_classifier(X_train, y_train, X_test, y_test)\n", + " report_results(cm, y_true, y_pred, pipeline_id)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading train/val/test datasets from ../data/datasets/A602.pickle.\n" + ] + } + ], + "source": [ + "pipeline_id = 'A602'\n", + "filename = f\"../data/datasets/{pipeline_id}.pickle\"\n", + "print(f\"Loading train/val/test datasets from {filename}.\")\n", + "file = open(filename, 'rb')\n", + "(X_train, y_train, X_val, y_val, X_test, y_test) = pickle.load(file)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[0. ],\n", + " [0. ],\n", + " [0. ],\n", + " ...,\n", + " [2.2],\n", + " [0. ],\n", + " [0.6]]),\n", + " array([[0.2],\n", + " [0. ],\n", + " [1.6],\n", + " ...,\n", + " [0. ],\n", + " [0. ],\n", + " [0. ]]),\n", + " array([[0.],\n", + " [0.],\n", + " [0.],\n", + " ...,\n", + " [0.],\n", + " [0.],\n", + " [0.]]))" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "y_train, y_val, y_test" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading train/val/test datasets from ../data/datasets/A602.pickle.\n", + "Shapes of train/val/test data matrices: (13651, 3, 8)/(3436, 3, 8)/(11447, 3, 8)\n", + "Shapes before reshaping: (13651, 3, 8) (11447, 3, 8)\n", + "Shapes after reshaping: (13651, 24) (11447, 24)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages/sklearn/ensemble/_gb.py:570: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n", + " y = column_or_1d(y, warn=True)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Negative 0.96 0.98 0.97 10483\n", + " Positive 0.70 0.53 0.61 964\n", + "\n", + " accuracy 0.94 11447\n", + " macro avg 0.83 0.75 0.79 11447\n", + "weighted avg 0.94 0.94 0.94 11447\n", + "\n" + ] + } + ], + "source": [ + "station = 'A602'\n", + "train_and_test_classifier(station)\n", + "# train_and_test_classifier(station + '_DSI')" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading train/val/test datasets from ../data/datasets/A601.pickle.\n", + "Shapes of train/val/test data matrices: (12821, 3, 8)/(3202, 3, 8)/(13094, 3, 8)\n", + "Shapes before reshaping: (12821, 3, 8) (13094, 3, 8)\n", + "Shapes after reshaping: (12821, 24) (13094, 24)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages/sklearn/ensemble/_gb.py:570: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n", + " y = column_or_1d(y, warn=True)\n" + ] + }, + { + "data": { + "image/png": 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YP3++4OTkJOjr6wsODg7C7NmzlfoIQvG25u7du5c6z4vbaV+2rVkQBOHw4cNC06ZNBQMDA8HFxUX46aefSm1rPnr0qNCrVy/B3t5eMDAwEOzt7YVBgwYJt27dKnWOF7f+HjlyRPD09BSMjIwEc3Nz4eOPPxZu3Lih1KfkfC9um16/fr0AQEhMTHzpdyoIytuaX+Zl25qnTZsm1KxZUzAyMhI8PT2FmJiYMrcj//7774Krq6ugp6endJ3t27cXmjRpUuY5nx8nKytLcHR0FJo3by4UFBQo9ZsyZYqgo6MjxMTEvPIayuPChQsCAGHu3Lkv7XPv3j0BgDBlyhSx7Z9//hEmTZok2NnZCQYGBoKbm5vw008/lfn5nTt3Cu7u7oJcLhdq164tzJkzR8jPzy/VD8BLX0RUcTJBqMCKPiIiIiIN4BoWIiIi0npMWIiIiEjrMWEhIiIirceEhYiIiLQeExYiIiLSekxYiIiISOsxYSEiIiKtVynvdGvUbLymQyDSSunnvtN0CERax/AN/E2oqr+Xnl2quj/DrLAQERGR1quUFRYiIiKtImN9QComLEREROomk2k6grceExYiIiJ1Y4VFMn6DREREpPVYYSEiIlI3TglJxoSFiIhI3TglJBm/QSIiItJ6rLAQERGpG6eEJGPCQkREpG6cEpKM3yARERFpPVZYiIiI1I1TQpIxYSEiIlI3TglJxm+QiIiItB4rLEREROrGKSHJmLAQERGpG6eEJGPCQkREpG6ssEjGlI+IiIi0HissRERE6sYpIcmYsBAREakbExbJ+A0SERGR1mOFhYiISN10uOhWKiYsRERE6sYpIcn4DRIREZHWY4WFiIhI3XgfFsmYsBAREakbp4Qk4zdIREREWo8VFiIiInXjlJBkTFiIiIjUjVNCkjFhISIiUjdWWCRjykdERERajxUWIiIideOUkGRMWIiIiNSNU0KSMeUjIiIirccKCxERkbpxSkgyJixERETqxikhyZjyERERkdZjhYWIiEjdOCUkGRMWIiIidWPCIhm/QSIiItJ6rLAQERGpGxfdSsaEhYiISN04JSQZExYiIiJ1Y4VFMqZ8REREpPVYYSEiIlI3TglJxoSFiIhI3TglJBlTPiIiokrqxIkT+Pjjj2Fvbw+ZTIZdu3YpHRcEAfPmzUPNmjVhZGQELy8v3L59W6lPWloafH19YW5uDktLS/j7+yM7O1upz5UrV9C2bVsYGhrCwcEBoaGhpWL59ddf0ahRIxgaGsLNzQ379++v0LUwYSEiIlIzmUymkldFPX36FO+++y7+85//lHk8NDQUYWFhCA8Px5kzZ2BiYgJvb2/k5uaKfXx9fXH9+nVERkZi7969OHHiBEaPHi0ez8rKQufOneHo6IgLFy5g8eLFCAwMxNq1a8U+p0+fxqBBg+Dv749Lly6hd+/e6N27N65du1b+71AQBKHC34CWM2o2XtMhEGml9HPfaToEIq1j+AYWR5j0X6+ScZ5uH/7an5XJZNi5cyd69+4NoLi6Ym9vj2nTpiEgIAAAkJmZCVtbW2zYsAE+Pj6Ii4uDq6srzp07h5YtWwIADh48iG7duuGvv/6Cvb09Vq9ejS+//BLJyckwMDAAAMyaNQu7du3CzZs3AQADBw7E06dPsXfvXjGeDz74AO7u7ggPDy9X/KywEBERvSXy8vKQlZWl9MrLy3utsRITE5GcnAwvLy+xzcLCAq1atUJMTAwAICYmBpaWlmKyAgBeXl7Q0dHBmTNnxD7t2rUTkxUA8Pb2Rnx8PNLT08U+z5+npE/JecqDCQsREZG6yVTzCgkJgYWFhdIrJCTktUJKTk4GANja2iq129raiseSk5NhY2OjdFxPTw/W1tZKfcoa4/lzvKxPyfHy4C4hIiIiNXud9SdlmT17NqZOnarUJpfLVTK2tmPCQkRE9JaQy+UqS1Ds7OwAACkpKahZs6bYnpKSAnd3d7FPamqq0ucKCwuRlpYmft7Ozg4pKSlKfUre/1ufkuPlwSkhIiIiNdPULqFXcXJygp2dHY4ePSq2ZWVl4cyZM/Dw8AAAeHh4ICMjAxcuXBD7REVFQaFQoFWrVmKfEydOoKCgQOwTGRkJFxcXWFlZiX2eP09Jn5LzlAcTFiIiIjXTVMKSnZ2N2NhYxMbGAiheaBsbG4sHDx5AJpNh8uTJWLBgAXbv3o2rV6/i008/hb29vbiTqHHjxujSpQtGjRqFs2fP4tSpUxg/fjx8fHxgb28PABg8eDAMDAzg7++P69evY+vWrVixYoXS1NWkSZNw8OBBLFmyBDdv3kRgYCDOnz+P8ePLv6uXU0JERERqpurqSHmdP38eHTp0EN+XJBF+fn7YsGEDZsyYgadPn2L06NHIyMhAmzZtcPDgQRgaGoqfiYiIwPjx49GxY0fo6OigX79+CAsLE49bWFjg8OHDGDduHFq0aIHq1atj3rx5Svdqad26NbZs2YI5c+bgiy++QIMGDbBr1y40bdq03NfC+7AQVSG8DwtRaW/iPiwWgzarZJzMn4eqZJy3ESssRERE6sZHCUnGhIWIiEjNNDUlVJlw0S0RERFpPVZYiIiI1IwVFumYsBAREakZExbpOCVEREREWo8VFiIiIjVjhUU6ramwnDx5EkOGDIGHhwcePnwIANi8eTOio6M1HBkREZFEKnpac1WmFQnLjh074O3tDSMjI1y6dAl5eXkAgMzMTAQHB2s4OiIiItI0rUhYFixYgPDwcKxbtw76+vpiu6enJy5evKjByIiIiKTTxocfvm20Yg1LfHw82rVrV6rdwsICGRkZbz4gIiIiFarqyYYqaEWFxc7ODgkJCaXao6OjUa9ePQ1EREREpDqssEinFQnLqFGjMGnSJJw5cwYymQyPHj1CREQEAgICMHbsWE2HR0RERBqmFVNCs2bNgkKhQMeOHZGTk4N27dpBLpcjICAAEyZM0HR4RERE0lTt4ohKaEXCIpPJ8OWXX2L69OlISEhAdnY2XF1dYWpqqunQiIiIJKvq0zmqoBVTQj/99BNycnJgYGAAV1dXvP/++0xWiIiISKQVCcuUKVNgY2ODwYMHY//+/SgqKtJ0SERERCrDRbfSaUXCkpSUhF9++QUymQwDBgxAzZo1MW7cOJw+fVrToREREUnGhEU6rUhY9PT00KNHD0RERCA1NRXLli3DvXv30KFDB9SvX1/T4REREZGGacWi2+cZGxvD29sb6enpuH//PuLi4jQdEhERkSRVvTqiClpRYQGAnJwcREREoFu3bqhVqxaWL1+OPn364Pr165oOjYiISBo+/FAyraiw+Pj4YO/evTA2NsaAAQMwd+5ceHh4aDosIiIi0hJakbDo6upi27Zt8Pb2hq6urqbDISIiUilOCUmnFQlLRESEpkMgIiJSGyYs0mksYQkLC8Po0aNhaGiIsLCwV/adOHHiG4qKiIhI9ZiwSCcTBEHQxImdnJxw/vx5VKtWDU5OTi/tJ5PJcPfu3QqNbdRsvNTwiCql9HPfaToEIq1j+AZ+dXcY97tKxvnvf3qpZJy3kcYqLImJiWX+mYiIqNJhgUUyrdjWHBQUhJycnFLtz549Q1BQkAYiIiIiUh3e6VY6rUhY5s+fj+zs7FLtOTk5mD9/vgYiIiIiIm2iFbuEBEEoM3O8fPkyrK2tNRBR1eXZvD6mfOqF5q51ULOGBQZMWYs9x66Ix3t99C5G9m+DZo3roJqlCVoNDMGVWw+Vxji0bhLatWyg1LZuezQmLvxFqW3Ix60wcchHaOBog6ynufgt8hKmLNqm1Gfy0I4Y0c8TdWpa4UnGU6zZdhKhPxxS8VUTSffDujU4GnkYiYl3ITc0hLt7M0yeGoC6TvUAAJkZGVj1n5WIOR2N5KQkWFlZo0NHL4ybMAlmZmYAgPibN/Hj92tx6dIFZKSnw75WLXwywAe+Q/00eWmkAlW9OqIKGk1YrKysxDJXw4YNlf6FFhUVITs7G2PGjNFghFWPiZEcV289xKbfY7B16ehSx42NDHA69g52RF7E6nm+Lx3nhx2n8PXqveL7nNwCpeMTh3yESUM/whfLduHstXswMTKAo301pT5LZvRHxw8aYfaynbh2+xGsLYxhZW4i8QqJ1OP8ubMYOMgXTdzcUFRYhJUrlmLMKH/8tnsfjI2Nkfo4FY9TUzE1YCbq13fGo0cPsSAoEI9TU7FkefFOyRs3rsG6mjWCFy2GnV1NxMZexNeB86Cjo4tBvkM0e4EkCRMW6TSasCxfvhyCIGDEiBGYP38+LCwsxGMGBgaoW7cu73j7hh0+dQOHT9146fGf950DANSp+erK17PcfKQ8+afMY5ZmRvjq8x7oNzkcx87eEtuv3X4k/tnFyRaj+rdFi08W4vb9VADA/UdPyn0dRG/a6rU/KL0PWrgIHdp6IO7GdbRo+R4aNGiIpStWiscd6tTBhEmT8cXM6SgsLISenh769O2vNEZtBwdciY3F0SOHmbBQlafRhMXPr7jM6eTkhNatW0NfX1+T4ZAKDezWEj7d3kPKkyzsP3ENIesO4Nn/V1k6ftAIOjoy2NtY4tKOOTAzkePPy4mYtfQ3/JWSAQDo3s4NiQ//Rrd2TTFmYDvIZDJEnYnHl8t3IT2r9AJtIm2T/U9xwm7+3C9ipftkw9TUFHp6L/9f8T/Z/8DCwlLV4dEbxgqLdFqxhqV9+/bin3Nzc5Gfn6903Nzc/E2HRBJsPXAeD5LSkPQ4E24N7LFgUi80dLSBT8D3AACn2tWhoyPDjBGdEbB4B7Kyn+GrcT2wd/V4vDcgBAWFRahbuzrq1LRGX69mGDl3M3R0dBAa0BdbFvuj62cr/yUCIs1SKBQI/SYY7s2ao0GDhmX2SU9Pw9rwVej3ycCXjhN76SIOHzyAlavWqCtUelOYr0imFQlLTk4OZsyYgW3btuHJk9Jl/6Kiopd+Ni8vD3l5eUptgqIIMh0+k0hTfvztlPjn6wmPkPR3Fg6unQin2tWR+NffkMlkMNDXw7TQ7Tj6500AgN/sDbgXGYz27zXEkZg46MhkMJTrw3/uZiQ8KJ4SGjs/AjE/z0IDRxtxmohIGwUvmI87t29jw+YtZR7Pzs7G+LGfoV79+hjzedk3urx9+xYmT/gcn40dh9aebdQZLtFbQSu2NU+fPh1RUVFYvXo15HI5vv/+e8yfPx/29vbYtGnTKz8bEhICCwsLpVdhyoU3FDmVx7mr9wAA9R1qAACS/84CANy8myz2+Ts9G39nZMPBzur/+2SioKBITFYA4GZiCgDAwY47x0h7BS8Iwonjx7Bu/UbY2tmVOv70aTY+/2wkTExMsCzsP2VOhd9JSMBo/2Ho98lAjB7z+ZsIm9SM92GRTisSlj179mDVqlXo168f9PT00LZtW8yZMwfBwcH/+mDE2bNnIzMzU+mlZ9viDUVO5fGuS20AxUkIAMTEFj9qoUFdG7GPlbkxqlua4kFSmthHX18XTrWri30aOBb3L+lDpE0EQUDwgiBEHY3Euh83onZth1J9srOzMWaUP/T19bHiu+Jf0F6UkHAbI0d8ip49e2PCpClvInR6A5iwSKcVU0JpaWmoV6/4XgXm5uZISyv+C6lNmzYYO3bsKz8rl8tL/dBzOuj1mRgZiJUQAKhbqxreaVgL6Vk5+G9yOqzMjeFgZ4WaNsULCRvWtQUApDzJQsqTf+BUuzoGdm2JQ9HX8STjKdwa1kLotL44eeG2uAso4UEq9vxxGd9O74/xC35GVnYugib0RPy9FBw/X7xrKOpMPC7eeIA1gb6YvngHdHRkWD5rAI7ExClVXYi0RfDX83Fg/14sX7kKJsYm+PvxYwCAqZkZDA0N/z9ZGYHc3GcIXrQYT7Oz8fT/b5hpZW0NXV1d3L59C6NG+KG1ZxsM9RsujqGjq8t7Ur3lqniuoRJakbDUq1cPiYmJqFOnDho1aoRt27bh/fffx549e2Bpaanp8KqU5q6OOPz9JPF9aEA/AMDm3X9i9Fc/oXt7N6wLGioe3/zNCADAgvD9WLhmPwoKCvFRKxeMH9wBJkYG+CslHbuOxmLR98o3e/OfuxmhAX3xW9hYKBQCoi/cRq9x/0FhoQJA8W+r/SevwdKZnyDyh8l4+iwfh0/dwKylv6n7KyB6Ldu2/gwA8B82VKk9aEEIevXpi7gb13H1ymUAQI+unZT67D98FLVq1caRw4eQnpaGfXt2Y9+e3eJxe/taOBAZpeYrINJuGnta8/OWLVsGXV1dTJw4EUeOHMHHH38MQRBQUFCApUuXYtKkSf8+yHP4tGaisvFpzUSlvYmnNTeYflAl49xe3EUl47yNtKLCMmXK/+Zpvby8cPPmTVy4cAHOzs545513NBgZERGRdJwSkk4rEpYXOTo6wtHRUdNhEBERkZbQioQlLCyszHaZTAZDQ0M4OzujXbt20NXlYloiInr7VPUdPqqgFQnLsmXL8PjxY+Tk5MDKqvg+HOnp6TA2NoapqSlSU1NRr149/PHHH3BwKL1VkIiISJsxX5FOK+7DEhwcjPfeew+3b9/GkydP8OTJE9y6dQutWrXCihUr8ODBA9jZ2SmtdSEiIqKqQysqLHPmzMGOHTtQv359sc3Z2Rnffvst+vXrh7t37yI0NBT9+vXTYJRERESvR0eHJRaptCJhSUpKQmFhYan2wsJCJCcX377d3t4e//z/00+JiIjeJpwSkk4rpoQ6dOiAzz77DJcuXRLbLl26hLFjx+Kjjz4CAFy9ehVOTk6aCpGIiIg0SCsSlh9++AHW1tZo0aKFeKv9li1bwtraGj/88AMAwNTUFEuWLNFwpERERBXHZwlJpxVTQnZ2doiMjMTNmzdx61bxs2RcXFzg4uIi9unQoYOmwiMiIpKkiucaKqEVCUuJevXqQSaToX79+tDT06rQiIiIXltVr46oglZMCeXk5MDf3x/GxsZo0qQJHjx4AACYMGECFi1apOHoiIiISNO0ImGZPXs2Ll++jGPHjsHQ0FBs9/LywtatWzUYGRERkXRcwyKdVsy77Nq1C1u3bsUHH3yg9C+kSZMmuHPnjgYjIyIikq6K5xoqoRUVlsePH8PGxqZU+9OnT6t8RklERPQ6ioqKMHfuXDg5OcHIyAj169fH119/DUEQxD6CIGDevHmoWbMmjIyM4OXlhdu3byuNk5aWBl9fX5ibm8PS0hL+/v7Izs5W6nPlyhW0bdsWhoaGcHBwQGhoqMqvRysSlpYtW2Lfvn3i+5Ik5fvvv4eHh4emwiIiIlIJTUwJffPNN1i9ejW+++47xMXF4ZtvvkFoaChWrlwp9gkNDUVYWBjCw8Nx5swZmJiYwNvbG7m5uWIfX19fXL9+HZGRkdi7dy9OnDiB0aNHi8ezsrLQuXNnODo64sKFC1i8eDECAwOxdu1a6V/cc7RiSig4OBhdu3bFjRs3UFhYiBUrVuDGjRs4ffo0jh8/runwiIiIJNHEZMHp06fRq1cvdO/eHQBQt25d/Pzzzzh79iyA4urK8uXLMWfOHPTq1QsAsGnTJtja2mLXrl3w8fFBXFwcDh48iHPnzqFly5YAgJUrV6Jbt2749ttvYW9vj4iICOTn5+PHH3+EgYEBmjRpgtjYWCxdulQpsZFKKyosbdq0QWxsLAoLC+Hm5obDhw/DxsYGMTExaNGihabDIyIi0gp5eXnIyspSeuXl5ZXZt3Xr1jh69Kh4f7PLly8jOjoaXbt2BQAkJiYiOTkZXl5e4mcsLCzQqlUrxMTEAABiYmJgaWkpJitA8YYYHR0dnDlzRuzTrl07GBgYiH28vb0RHx+P9PR0lV27VlRYAKB+/fpYt26dpsMgIiJSOVWtxwwJCcH8+fOV2r766isEBgaW6jtr1ixkZWWhUaNG0NXVRVFRERYuXAhfX18AEJ/VZ2trq/Q5W1tb8VhycnKpNaZ6enqwtrZW6vPio3NKxkxOToaVldVrXq0yjSYsOjo6//ovUSaTlflgRCIioreFqqaEZs+ejalTpyq1yeXyMvtu27YNERER2LJlizhNM3nyZNjb28PPz081Ab1BGk1Ydu7c+dJjMTExCAsLg0KheIMRERERaa+S5+2Vx/Tp0zFr1iz4+PgAANzc3HD//n2EhITAz88PdnZ2AICUlBTUrFlT/FxKSgrc3d0BFD86JzU1VWncwsJCpKWliZ+3s7NDSkqKUp+S9yV9VEGjCUvJIp/nxcfHY9asWdizZw98fX0RFBSkgciIiIhURxO36MjJyYGOjvJSVV1dXbEQ4OTkBDs7Oxw9elRMULKysnDmzBmMHTsWAODh4YGMjAxcuHBBXFMaFRUFhUKBVq1aiX2+/PJLFBQUQF9fHwAQGRkJFxcXlU0HAVqy6BYAHj16hFGjRsHNzQ2FhYWIjY3Fxo0b4ejoqOnQiIiIJJHJVPOqiI8//hgLFy7Evn37cO/ePezcuRNLly5Fnz59/j8mGSZPnowFCxZg9+7duHr1Kj799FPY29ujd+/eAIDGjRujS5cuGDVqFM6ePYtTp05h/Pjx8PHxgb29PQBg8ODBMDAwgL+/P65fv46tW7dixYoVpaaupNL4otvMzEwEBwdj5cqVcHd3x9GjR9G2bVtNh0VERKQymqiwrFy5EnPnzsXnn3+O1NRU2Nvb47PPPsO8efPEPjNmzMDTp08xevRoZGRkoE2bNjh48KDSY3IiIiIwfvx4dOzYETo6OujXrx/CwsLE4xYWFjh8+DDGjRuHFi1aoHr16pg3b55KtzQDgEx4/pZ3b1hoaCi++eYb2NnZITg4uMwpotdh1Gy8SsYhqmzSz32n6RCItI7hG/jVvVWIau4pdmZ2e5WM8zbSaIVl1qxZMDIygrOzMzZu3IiNGzeW2e+33357w5ERERGpDp8yI51GE5ZPP/2UzwoiIqJKj3/XSafRhGXDhg2aPD0RERG9JTS+6JaIiKiyY4FFOiYsREREasYpIem05j4sRERERC/DCgsREZGascAiHRMWIiIiNeOUkHScEiIiIiKtxwoLERGRmrHCIh0TFiIiIjVjviIdExYiIiI1Y4VFOq5hISIiIq3HCgsREZGascAiHRMWIiIiNeOUkHScEiIiIiKtxwoLERGRmrHAIh0TFiIiIjXTYcYiGaeEiIiISOuxwkJERKRmLLBIx4SFiIhIzbhLSDomLERERGqmw3xFMq5hISIiIq3HCgsREZGacUpIOiYsREREasZ8RTpOCREREZHWY4WFiIhIzWRgiUUqJixERERqxl1C0nFKiIiIiLQeKyxERERqxl1C0pUrYdm9e3e5B+zZs+drB0NERFQZMV+RrlwJS+/evcs1mEwmQ1FRkZR4iIiIiEopV8KiUCjUHQcREVGlpcMSi2SS1rDk5ubC0NBQVbEQERFVSsxXpKvwLqGioiJ8/fXXqFWrFkxNTXH37l0AwNy5c/HDDz+oPEAiIqK3nUwmU8mrKqtwwrJw4UJs2LABoaGhMDAwENubNm2K77//XqXBEREREQGvkbBs2rQJa9euha+vL3R1dcX2d999Fzdv3lRpcERERJWBTKaaV1VW4TUsDx8+hLOzc6l2hUKBgoIClQRFRERUmXDRrXQVrrC4urri5MmTpdq3b9+OZs2aqSQoIiIioudVuMIyb948+Pn54eHDh1AoFPjtt98QHx+PTZs2Ye/eveqIkYiI6K3G+op0Fa6w9OrVC3v27MGRI0dgYmKCefPmIS4uDnv27EGnTp3UESMREdFbjbuEpHut+7C0bdsWkZGRqo6FiIiIqEyvfeO48+fPIy4uDkDxupYWLVqoLCgiIqLKRKdqF0dUosIJy19//YVBgwbh1KlTsLS0BABkZGSgdevW+OWXX1C7dm1Vx0hERPRWq+rTOapQ4TUsI0eOREFBAeLi4pCWloa0tDTExcVBoVBg5MiR6oiRiIiIqrgKV1iOHz+O06dPw8XFRWxzcXHBypUr0bZtW5UGR0REVBmwwCJdhRMWBweHMm8QV1RUBHt7e5UERUREVJlwSki6Ck8JLV68GBMmTMD58+fFtvPnz2PSpEn49ttvVRocERFRZaAjU82rKitXhcXKykopO3z69ClatWoFPb3ijxcWFkJPTw8jRoxA79691RIoERERVV3lSliWL1+u5jCIiIgqL04JSVeuhMXPz0/dcRAREVVaTFeke+0bxwFAbm4u8vPzldrMzc0lBURERET0ogonLE+fPsXMmTOxbds2PHnypNTxoqIilQRGRERUWehwSkiyCu8SmjFjBqKiorB69WrI5XJ8//33mD9/Puzt7bFp0yZ1xEhERPRWk8lU86rKKpyw7NmzB6tWrUK/fv2gp6eHtm3bYs6cOQgODkZERIQ6YiQiIqLX8PDhQwwZMgTVqlWDkZER3NzclG5LIggC5s2bh5o1a8LIyAheXl64ffu20hhpaWnw9fWFubk5LC0t4e/vj+zsbKU+V65cQdu2bWFoaAgHBweEhoaq/FoqnLCkpaWhXr16AIrXq6SlpQEA2rRpgxMnTqg2OiIiokpAJpOp5FUR6enp8PT0hL6+Pg4cOIAbN25gyZIlsLKyEvuEhoYiLCwM4eHhOHPmDExMTODt7Y3c3Fyxj6+vL65fv47IyEjs3bsXJ06cwOjRo8XjWVlZ6Ny5MxwdHXHhwgUsXrwYgYGBWLt2rfQv7jkVXsNSr149JCYmok6dOmjUqBG2bduG999/H3v27BEfhkhERET/o4npnG+++QYODg5Yv3692Obk5CT+WRAELF++HHPmzEGvXr0AAJs2bYKtrS127doFHx8fxMXF4eDBgzh37hxatmwJAFi5ciW6deuGb7/9Fvb29oiIiEB+fj5+/PFHGBgYoEmTJoiNjcXSpUuVEhupKlxhGT58OC5fvgwAmDVrFv7zn//A0NAQU6ZMwfTp01UWGBERESnLy8tDVlaW0isvL6/Mvrt370bLli3xySefwMbGBs2aNcO6devE44mJiUhOToaXl5fYZmFhgVatWiEmJgYAEBMTA0tLSzFZAQAvLy/o6OjgzJkzYp927drBwMBA7OPt7Y34+Hikp6er7NornLBMmTIFEydOBFAc9M2bN7FlyxZcunQJkyZNUllgRERElYWOTKaSV0hICCwsLJReISEhZZ7z7t27WL16NRo0aIBDhw5h7NixmDhxIjZu3AgASE5OBgDY2toqfc7W1lY8lpycDBsbG6Xjenp6sLa2VupT1hjPn0MVJN2HBQAcHR3h6OioiliIiIgqJVVNCc2ePRtTp05VapPL5WX2VSgUaNmyJYKDgwEAzZo1w7Vr1xAeHv5W3hC2XAlLWFhYuQcsqb4QERFRMVXdml8ul780QXlRzZo14erqqtTWuHFj7NixAwBgZ2cHAEhJSUHNmjXFPikpKXB3dxf7pKamKo1RWFiItLQ08fN2dnZISUlR6lPyvqSPKpQrYVm2bFm5BpPJZExYiIiItICnpyfi4+OV2m7duiXOijg5OcHOzg5Hjx4VE5SsrCycOXMGY8eOBQB4eHggIyMDFy5cQIsWLQAAUVFRUCgUaNWqldjnyy+/REFBAfT19QEAkZGRcHFxUdqRJJVMEARBZaNpicxnCk2HQEREbwkLowov56ywCTvjVDLOyj6Ny9333LlzaN26NebPn48BAwbg7NmzGDVqFNauXQtfX18AxTuJFi1ahI0bN8LJyQlz587FlStXcOPGDRgaGgIAunbtipSUFISHh6OgoADDhw9Hy5YtsWXLFgBAZmYmXFxc0LlzZ8ycORPXrl3DiBEjsGzZMpXuEpK8hoWIiIheTRNPa37vvfewc+dOzJ49G0FBQXBycsLy5cvFZAUovnv906dPMXr0aGRkZKBNmzY4ePCgmKwAQEREBMaPH4+OHTtCR0cH/fr1U1oqYmFhgcOHD2PcuHFo0aIFqlevjnnz5qk0WQFYYSEioiruTVRYJu66qZJxwno3Usk4byNWWIiIiNRMp4o/B0gVmLAQERGpGRMW6dRfByMiIiKS6LUSlpMnT2LIkCHw8PDAw4cPAQCbN29GdHS0SoMjIiKqDDTx8MPKpsIJy44dO+Dt7Q0jIyNcunRJfIZBZmameDc9IiIi+h8dmWpeVVmFE5YFCxYgPDwc69atE28QAxTfoObixYsqDY6IiIgIeI1Ft/Hx8WjXrl2pdgsLC2RkZKgiJiIiokqlis/mqESFKyx2dnZISEgo1R4dHY169eqpJCgiIqLKRFVPa67KKpywjBo1CpMmTcKZM2cgk8nw6NEjREREICAgQHz2ABEREf2PjopeVVmFp4RmzZoFhUKBjh07IicnB+3atYNcLkdAQAAmTJigjhiJiIioinvtW/Pn5+cjISEB2dnZcHV1hampqapje228NT8REZXXm7g1/5cHbqlknIVdG6pknLfRa9/p1sDAAK6urqqMhYiIqFKq6utPVKHCCUuHDh1eefOaqKgoSQERERERvajCCYu7u7vS+4KCAsTGxuLatWvw8/NTVVxERESVBgss0lU4YVm2bFmZ7YGBgcjOzpYcEBERUWVT1e9SqwoqW2k0ZMgQ/Pjjj6oajoiIiEj02otuXxQTEwNDQ0NVDUdERFRpcNGtdBVOWPr27av0XhAEJCUl4fz585g7d67KAiMiIqosmK9IV+GExcLCQum9jo4OXFxcEBQUhM6dO6ssMCIiIqISFUpYioqKMHz4cLi5ucHKykpdMREREVUqXHQrXYUW3erq6qJz5858KjMREVEFyFT0T1VW4V1CTZs2xd27d9URCxERUaWkI1PNqyqrcMKyYMECBAQEYO/evUhKSkJWVpbSi4iIiEjVyr2GJSgoCNOmTUO3bt0AAD179lS6Rb8gCJDJZCgqKlJ9lERERG+xql4dUYVyP61ZV1cXSUlJiIuLe2W/9u3bqyQwKfi0ZiIiKq838bTmxcdUs5Ri+of1VDLO26jcFZaSvEYbEhIiIiKqWiq0rflVT2kmIiKisnFKSLoKJSwNGzb816QlLS1NUkBERESVDX/fl65CCcv8+fNL3emWiIiISN0qlLD4+PjAxsZGXbEQERFVSnz4oXTlTli4foWIiOj1cA2LdOXey1XO3c9EREREKlfuCotCwXubEBERvQ5OUkhXoTUsREREVHE6VfzBharAhIWIiEjNWGGRTv33IyYiIiKSiBUWIiIiNeMuIemYsBAREakZ78MiHaeEiIiISOuxwkJERKRmLLBIx4SFiIhIzTglJB2nhIiIiEjrscJCRESkZiywSMeEhYiISM04nSEdv0MiIiLSeqywEBERqZmMc0KSMWEhIiJSM6Yr0jFhISIiUjNua5aOa1iIiIhI67HCQkREpGasr0jHhIWIiEjNOCMkHaeEiIiISOuxwkJERKRm3NYsHRMWIiIiNeN0hnT8DomIiKqARYsWQSaTYfLkyWJbbm4uxo0bh2rVqsHU1BT9+vVDSkqK0ucePHiA7t27w9jYGDY2Npg+fToKCwuV+hw7dgzNmzeHXC6Hs7MzNmzYoPL4mbAQERGpmUwmU8nrdZ07dw5r1qzBO++8o9Q+ZcoU7NmzB7/++iuOHz+OR48eoW/fvuLxoqIidO/eHfn5+Th9+jQ2btyIDRs2YN68eWKfxMREdO/eHR06dEBsbCwmT56MkSNH4tChQ68db1lkgiAIKh1RC2Q+U2g6BCIiektYGKn/d/dfYx+pZJxP3O0r/Jns7Gw0b94cq1atwoIFC+Du7o7ly5cjMzMTNWrUwJYtW9C/f38AwM2bN9G4cWPExMTggw8+wIEDB9CjRw88evQItra2AIDw8HDMnDkTjx8/hoGBAWbOnIl9+/bh2rVr4jl9fHyQkZGBgwcPquS6AVZYiIiIKrVx48ahe/fu8PLyUmq/cOECCgoKlNobNWqEOnXqICYmBgAQExMDNzc3MVkBAG9vb2RlZeH69etinxfH9vb2FsdQFS66JSIiUjNV7RLKy8tDXl6eUptcLodcLi+z/y+//IKLFy/i3LlzpY4lJyfDwMAAlpaWSu22trZITk4W+zyfrJQcLzn2qj5ZWVl49uwZjIyMyn+Br8AKCxERkZrpqOgVEhICCwsLpVdISEiZ5/zvf/+LSZMmISIiAoaGhmq9vjeBCQsREZGaqWrR7ezZs5GZman0mj17dpnnvHDhAlJTU9G8eXPo6elBT08Px48fR1hYGPT09GBra4v8/HxkZGQofS4lJQV2dnYAADs7u1K7hkre/1sfc3NzlVVXACYsREREbw25XA5zc3Ol18umgzp27IirV68iNjZWfLVs2RK+vr7in/X19XH06FHxM/Hx8Xjw4AE8PDwAAB4eHrh69SpSU1PFPpGRkTA3N4erq6vY5/kxSvqUjKEqXMNCRESkZpq4z62ZmRmaNm2q1GZiYoJq1aqJ7f7+/pg6dSqsra1hbm6OCRMmwMPDAx988AEAoHPnznB1dcXQoUMRGhqK5ORkzJkzB+PGjRMTpTFjxuC7777DjBkzMGLECERFRWHbtm3Yt2+fSq+HCQsREZGaaeud+ZctWwYdHR3069cPeXl58Pb2xqpVq8Tjurq62Lt3L8aOHQsPDw+YmJjAz88PQUFBYh8nJyfs27cPU6ZMwYoVK1C7dm18//338Pb2VmmsvA8LERFVaW/iPiy/X01WyTi93OxUMs7biBUWIiIiNdPRyKRQ5aI1i25PnjyJIUOGwMPDAw8fPgQAbN68GdHR0RqOjIiISBqZTDWvqkwrEpYdO3bA29sbRkZGuHTpknhTnMzMTAQHB2s4OiIiItI0rUhYFixYgPDwcKxbtw76+vpiu6enJy5evKjByIiIiKSTqeifqkwr1rDEx8ejXbt2pdotLCxK3dCGiIjobVPVp3NUQSsqLHZ2dkhISCjVHh0djXr16mkgIiIiItImWpGwjBo1CpMmTcKZM2cgk8nw6NEjREREICAgAGPHjtV0eERERJLoQKaSV1WmFVNCs2bNgkKhQMeOHZGTk4N27dpBLpcjICAAEyZM0HR4REREknBKSDqtunFcfn4+EhISkJ2dDVdXV5iamr7WOLxxHBERldebuHHc4bjHKhmnc+MaKhnnbaQVU0I//fQTcnJyYGBgAFdXV7z//vuvnawQERFR5aMVCcuUKVNgY2ODwYMHY//+/SgqKtJ0SERERCrDbc3SaUXCkpSUhF9++QUymQwDBgxAzZo1MW7cOJw+fVrToREREUmmI1PNqyrTqjUsAJCTk4OdO3diy5YtOHLkCGrXro07d+5UaAyuYSEiovJ6E2tYjt78WyXjdGxUXSXjvI20YpfQ84yNjeHt7Y309HTcv38fcXFxmg6JiIhIkqo+naMKWjElBBRXViIiItCtWzfUqlULy5cvR58+fXD9+nVNh0ZERCQJH34onVZUWHx8fLB3714YGxtjwIABmDt3Ljw8PDQdFhEREWkJrUhYdHV1sW3bNnh7e0NXV1fT4RAREakUp4Sk04qEJSIiQtMhEBERqU1V3+GjChpLWMLCwjB69GgYGhoiLCzslX0nTpz4hqIiIiIibaSxbc1OTk44f/48qlWrBicnp5f2k8lkuHv3boXG5rZmIiIqrzexrfnkrXSVjNO2oZVKxnkbaazCkpiYWOafiYiIKpuqvsNHFbRiW3NQUBBycnJKtT979gxBQUEaiIiIiEh1ZCp6VWVacadbXV1dJCUlwcbGRqn9yZMnsLGxqfCzhTglRERE5fUmpoRO3VbNlJBnA04JaZQgCJCVUS+7fPkyrK2tX/nZvLw85OXlKbcp9CGXy1UaIxER0evS4ZyQZBqdErKysoK1tTVkMhkaNmwIa2tr8WVhYYFOnTphwIABrxwjJCQEFhYWSq+lixe9oSsgIiL6d5wSkk6jU0IbN26EIAgYMWIEli9fDgsLC/GYgYEB6tat+693vC2rwpLLCgsREZXTm5gS+jMhQyXjfOBsqZJx3kYanRLy8/MDULzFuXXr1tDX16/wGHK5vFRyInANCxERaZOqXh5RAY0lLFlZWTA3NwcANGvWDM+ePcOzZ8/K7FvSj4iI6G3EW/NLp7GExcrKStwZZGlpWeai25LFuBXdJURERESVi8YSlqioKHEH0B9//KGpMIiIiNSOm4Sk04r7sKga78NCRETl9SYW3Z67m6mScd6rZ/HvnSoprbjT7cGDBxEdHS2+/89//gN3d3cMHjwY6emqudkOERERvb20ImGZPn06srKyAABXr17F1KlT0a1bNyQmJmLq1Kkajo6IiEgi3ohFMq24021iYiJcXV0BADt27MDHH3+M4OBgXLx4Ed26ddNwdERERNJwl5B0WlFhMTAwEB9+eOTIEXTu3BkAYG1tLVZeiIiI3lYymWpeVZlWVFjatGmDqVOnwtPTE2fPnsXWrVsBALdu3ULt2rU1HB0RERFpmlZUWL777jvo6elh+/btWL16NWrVqgUAOHDgALp06aLh6IiIiKThEhbpuK2ZiIiqtDexrfnifdUsb2juWHXv/K4VU0IAUFRUhF27diEuLg4A0KRJE/Ts2RO6uroajoyIiIg0TSsqLAkJCejWrRsePnwIFxcXAEB8fDwcHBywb98+1K9fv0LjscJCRETl9SYqLJfu/6OScZo5mqlknLeRViQs3bp1gyAIiIiIEG/X/+TJEwwZMgQ6OjrYt29fhcZjwkJEROX1JhKW2AeqSVjc6zBh0SgTExP8+eefcHNzU2q/fPkyPD09kZ2dXaHxmLAQEVF5MWF5O2jFGha5XI5//in9LzM7OxsGBgYaiIiIiEh1qvoOH1XQim3NPXr0wOjRo3HmzBkIggBBEPDnn39izJgx6Nmzp6bDIyIikob7miXTioQlLCwMzs7OaN26NQwNDWFoaAhPT084OztjxYoVmg6PiIiINEyjU0IKhQKLFy/G7t27kZ+fj969e8PPzw8ymQyNGzeGs7OzJsMjIiJSCT5LSDqNJiwLFy5EYGAgvLy8YGRkhP3798PCwgI//vijJsMiIiJSqar+HCBV0OguoQYNGiAgIACfffYZgOIHH3bv3h3Pnj2Djs7rz1ZxlxAREZXXm9gldO2viu12fZmmtU1VMs7bSKNrWB48eIBu3bqJ7728vCCTyfDo0SMNRkVERETaRqNTQoWFhTA0NFRq09fXR0FBgYYiIiIiUgNOCUmm0YRFEAQMGzYMcrlcbMvNzcWYMWNgYmIitv3222+aCI+IiEgluOhWOo0mLH5+fqXahgwZooFIiIiISJtpxa35VY2LbomIqLzexKLbG4+eqmQcV3uTf+9USWnFrfmJiIgqM04ISacVd7olIiIiehUmLEREROqmgWcJhYSE4L333oOZmRlsbGzQu3dvxMfHK/XJzc3FuHHjUK1aNZiamqJfv35ISUlR6vPgwQN0794dxsbGsLGxwfTp01FYWKjU59ixY2jevDnkcjmcnZ2xYcOGigVbDkxYiIiI1Eymon8q4vjx4xg3bhz+/PNPREZGoqCgAJ07d8bTp/9bTzNlyhTs2bMHv/76K44fP45Hjx6hb9++4vGioiJ0794d+fn5OH36NDZu3IgNGzZg3rx5Yp/ExER0794dHTp0QGxsLCZPnoyRI0fi0KFD0r+453DRLRERVWlvYtHtzaQclYzTqKbxa3/28ePHsLGxwfHjx9GuXTtkZmaiRo0a2LJlC/r3718c582baNy4MWJiYvDBBx/gwIED6NGjBx49egRbW1sAQHh4OGbOnInHjx/DwMAAM2fOxL59+3Dt2jXxXD4+PsjIyMDBgwelXfBzWGEhIiJSM5lMNa+8vDxkZWUpvfLy8soVQ2ZmJgDA2toaAHDhwgUUFBTAy8tL7NOoUSPUqVMHMTExAICYmBi4ubmJyQoAeHt7IysrC9evXxf7PD9GSZ+SMVSFCQsREZGaqWoJS0hICCwsLJReISEh/3p+hUKByZMnw9PTE02bNgUAJCcnw8DAAJaWlkp9bW1tkZycLPZ5PlkpOV5y7FV9srKy8OzZs3J8O+XDbc1ERETqpqJ9zbNnz8bUqVOV2p6/W/zLjBs3DteuXUN0dLRqAtEAJixERERvCblcXq4E5Xnjx4/H3r17ceLECdSuXVtst7OzQ35+PjIyMpSqLCkpKbCzsxP7nD17Vmm8kl1Ez/d5cWdRSkoKzM3NYWRkVKFYX4VTQkRERGqmiV1CgiBg/Pjx2LlzJ6KiouDk5KR0vEWLFtDX18fRo0fFtvj4eDx48AAeHh4AAA8PD1y9ehWpqalin8jISJibm8PV1VXs8/wYJX1KxlAV7hIiIqIq7U3sEkpIVc1aDmeb8lcsPv/8c2zZsgW///47XFxcxHYLCwux8jF27Fjs378fGzZsgLm5OSZMmAAAOH36NIDibc3u7u6wt7dHaGgokpOTMXToUIwcORLBwcEAirc1N23aFOPGjcOIESMQFRWFiRMnYt++ffD29lbJdQNMWIiIqIqrrAmLTFZ2RWb9+vUYNmwYgOIbx02bNg0///wz8vLy4O3tjVWrVonTPQBw//59jB07FseOHYOJiQn8/PywaNEi6On9b1XJsWPHMGXKFNy4cQO1a9fG3LlzxXOoChMWIiKq0t5EwnJHRQlL/QokLJUNF90SERGpG59+KBkX3RIREZHWY4WFiIhIzSq6w4dKY8JCRESkZi9Z/0oVwCkhIiIi0nqssBAREakZCyzSMWEhIiJSN2YskjFhISIiUjMuupWOa1iIiIhI67HCQkREpGbcJSQdExYiIiI1Y74iHaeEiIiISOuxwkJERKRmnBKSjgkLERGR2jFjkYpTQkRERKT1WGEhIiJSM04JSceEhYiISM2Yr0jHKSEiIiLSeqywEBERqRmnhKRjwkJERKRmfJaQdExYiIiI1I35imRcw0JERERajxUWIiIiNWOBRTomLERERGrGRbfScUqIiIiItB4rLERERGrGXULSMWEhIiJSN+YrknFKiIiIiLQeKyxERERqxgKLdExYiIiI1Iy7hKTjlBARERFpPVZYiIiI1Iy7hKRjwkJERKRmnBKSjlNCREREpPWYsBAREZHW45QQERGRmnFKSDomLERERGrGRbfScUqIiIiItB4rLERERGrGKSHpmLAQERGpGfMV6TglRERERFqPFRYiIiJ1Y4lFMiYsREREasZdQtJxSoiIiIi0HissREREasZdQtIxYSEiIlIz5ivSMWEhIiJSN2YsknENCxEREWk9VliIiIjUjLuEpGPCQkREpGZcdCsdp4SIiIhI68kEQRA0HQRVTnl5eQgJCcHs2bMhl8s1HQ6R1uDPBlHFMWEhtcnKyoKFhQUyMzNhbm6u6XCItAZ/NogqjlNCREREpPWYsBAREZHWY8JCREREWo8JC6mNXC7HV199xUWFRC/gzwZRxXHRLREREWk9VliIiIhI6zFhISIiIq3HhIWIiIi0HhMW0ip169bF8uXLNR0GkVocO3YMMpkMGRkZr+zHnwOi0piwVCHDhg2DTCbDokWLlNp37doF2Rt+MteGDRtgaWlZqv3cuXMYPXr0G42F6EUlPysymQwGBgZwdnZGUFAQCgsLJY3bunVrJCUlwcLCAgB/DogqgglLFWNoaIhvvvkG6enpmg6lTDVq1ICxsbGmwyBCly5dkJSUhNu3b2PatGkIDAzE4sWLJY1pYGAAOzu7f/0FgT8HRKUxYalivLy8YGdnh5CQkJf2iY6ORtu2bWFkZAQHBwdMnDgRT58+FY8nJSWhe/fuMDIygpOTE7Zs2VKqhL106VK4ubnBxMQEDg4O+Pzzz5GdnQ2guCw+fPhwZGZmir/FBgYGAlAuhQ8ePBgDBw5Uiq2goADVq1fHpk2bAAAKhQIhISFwcnKCkZER3n33XWzfvl0F3xRVdXK5HHZ2dnB0dMTYsWPh5eWF3bt3Iz09HZ9++imsrKxgbGyMrl274vbt2+Ln7t+/j48//hhWVlYwMTFBkyZNsH//fgDKU0L8OSCqGCYsVYyuri6Cg4OxcuVK/PXXX6WO37lzB126dEG/fv1w5coVbN26FdHR0Rg/frzY59NPP8WjR49w7Ngx7NixA2vXrkVqaqrSODo6OggLC8P169exceNGREVFYcaMGQCKy+LLly+Hubk5kpKSkJSUhICAgFKx+Pr6Ys+ePWKiAwCHDh1CTk4O+vTpAwAICQnBpk2bEB4ejuvXr2PKlCkYMmQIjh8/rpLvi6iEkZER8vPzMWzYMJw/fx67d+9GTEwMBEFAt27dUFBQAAAYN24c8vLycOLECVy9ehXffPMNTE1NS43HnwOiChKoyvDz8xN69eolCIIgfPDBB8KIESMEQRCEnTt3CiX/Kfj7+wujR49W+tzJkycFHR0d4dmzZ0JcXJwAQDh37px4/Pbt2wIAYdmyZS8996+//ipUq1ZNfL9+/XrBwsKiVD9HR0dxnIKCAqF69erCpk2bxOODBg0SBg4cKAiCIOTm5grGxsbC6dOnlcbw9/cXBg0a9Oovg+gVnv9ZUSgUQmRkpCCXy4XevXsLAIRTp06Jff/++2/ByMhI2LZtmyAIguDm5iYEBgaWOe4ff/whABDS09MFQeDPAVFF6Gk0WyKN+eabb/DRRx+V+o3u8uXLuHLlCiIiIsQ2QRCgUCiQmJiIW7duQU9PD82bNxePOzs7w8rKSmmcI0eOICQkBDdv3kRWVhYKCwuRm5uLnJyccs/N6+npYcCAAYiIiMDQoUPx9OlT/P777/jll18AAAkJCcjJyUGnTp2UPpefn49mzZpV6PsgetHevXthamqKgoICKBQKDB48GH379sXevXvRqlUrsV+1atXg4uKCuLg4AMDEiRMxduxYHD58GF5eXujXrx/eeeed146DPwdExZiwVFHt2rWDt7c3Zs+ejWHDhont2dnZ+OyzzzBx4sRSn6lTpw5u3br1r2Pfu3cPPXr0wNixY7Fw4UJYW1sjOjoa/v7+yM/Pr9BiQl9fX7Rv3x6pqamIjIyEkZERunTpIsYKAPv27UOtWrWUPsdntJBUHTp0wOrVq2FgYAB7e3vo6elh9+7d//q5kSNHwtvbG/v27cPhw4cREhKCJUuWYMKECa8dC38OiJiwVGmLFi2Cu7s7XFxcxLbmzZvjxo0bcHZ2LvMzLi4uKCwsxKVLl9CiRQsAxb/hPb/r6MKFC1AoFFiyZAl0dIqXSW3btk1pHAMDAxQVFf1rjK1bt4aDgwO2bt2KAwcO4JNPPoG+vj4AwNXVFXK5HA8ePED79u0rdvFE/8LExKTUz0Hjxo1RWFiIM2fOoHXr1gCAJ0+eID4+Hq6urmI/BwcHjBkzBmPGjMHs2bOxbt26MhMW/hwQlR8TlirMzc0Nvr6+CAsLE9tmzpyJDz74AOPHj8fIkSNhYmKCGzduIDIyEt999x0aNWoELy8vjB49GqtXr4a+vj6mTZsGIyMjcaums7MzCgoKsHLlSnz88cc4deoUwsPDlc5dt25dZGdn4+jRo3j33XdhbGz80srL4MGDER4ejlu3buGPP/4Q283MzBAQEIApU6ZAoVCgTZs2yMzMxKlTp2Bubg4/Pz81fGtUlTVo0AC9evXCqFGjsGbNGpiZmWHWrFmoVasWevXqBQCYPHkyunbtioYNGyI9PR1//PEHGjduXOZ4/DkgqgBNL6KhN+f5hYQlEhMTBQMDA+H5/xTOnj0rdOrUSTA1NRVMTEyEd955R1i4cKF4/NGjR0LXrl0FuVwuODo6Clu2bBFsbGyE8PBwsc/SpUuFmjVrCkZGRoK3t7ewadMmpcWGgiAIY8aMEapVqyYAEL766itBEJQXG5a4ceOGAEBwdHQUFAqF0jGFQiEsX75ccHFxEfT19YUaNWoI3t7ewvHjx6V9WVSllfWzUiItLU0YOnSoYGFhIf73fevWLfH4+PHjhfr16wtyuVyoUaOGMHToUOHvv/8WBKH0oltB4M8BUXnJBEEQNJgvUSXw119/wcHBAUeOHEHHjh01HQ4REVVCTFiowqKiopCdnQ03NzckJSVhxowZePjwIW7duiXOqxMREakS17BQhRUUFOCLL77A3bt3YWZmhtatWyMiIoLJChERqQ0rLERERKT1eGt+IiIi0npMWIiIiEjrMWEhIiIirceEhYiIiLQeExYiLTJs2DD07t1bfP/hhx9i8uTJbzyOY8eOQSaTISMj46V9ZDIZdu3aVe4xAwMD4e7uLimue/fuQSaTITY2VtI4RPT2YcJC9C+GDRsGmUwGmUwGAwMDODs7IygoCIWFhWo/92+//Yavv/66XH3Lk2QQEb2teB8WonLo0qUL1q9fj7y8POzfvx/jxo2Dvr4+Zs+eXapvfn4+DAwMVHJea2trlYxDRPS2Y4WFqBzkcjns7Ozg6OiIsWPHwsvLC7t37wbwv2mchQsXwt7eXnz69X//+18MGDAAlpaWsLa2Rq9evXDv3j1xzKKiIkydOhWWlpaoVq0aZsyYgRdvi/TilFBeXh5mzpwJBwcHyOVyODs744cffsC9e/fQoUMHAICVlRVkMhmGDRsGAFAoFAgJCYGTkxOMjIzw7rvvYvv27Urn2b9/Pxo2bAgjIyN06NBBKc7ymjlzJho2bAhjY2PUq1cPc+fORUFBQal+a9asgYODA4yNjTFgwABkZmYqHf/+++/RuHFjGBoaolGjRli1alWFYyGiyocJC9FrMDIyQn5+vvj+6NGjiI+PR2RkJPbu3YuCggJ4e3vDzMwMJ0+exKlTp2BqaoouXbqIn1uyZAk2bNiAH3/8EdHR0UhLS8POnTtfed5PP/0UP//8M8LCwhAXF4c1a9bA1NQUDg4O2LFjBwAgPj4eSUlJWLFiBQAgJCQEmzZtQnh4OK5fv44pU6ZgyJAhOH78OIDixKpv3774+OOPERsbi5EjR2LWrFkV/k7MzMywYcMG3LhxAytWrMC6deuwbNkypT4JCQnYtm0b9uzZg4MHD+LSpUv4/PPPxeMRERGYN28eFi5ciLi4OAQHB2Pu3LnYuHFjheMhokpGgw9eJHorPP/kXoVCIURGRgpyuVwICAgQj9va2gp5eXniZzZv3iy4uLgoPVU3Ly9PMDIyEg4dOiQIgiDUrFlTCA0NFY8XFBQItWvXVnpKcPv27YVJkyYJgiAI8fHxAgAhMjKyzDjLehJwbm6uYGxsLJw+fVqpr7+/vzBo0CBBEARh9uzZgqurq9LxmTNnlhrrRQCEnTt3vvT44sWLhRYtWojvv/rqK0FXV1f466+/xLYDBw4IOjo6QlJSkiAIglC/fn1hy5YtSuN8/fXXgoeHhyAIxU8XByBcunTppeclosqJa1iIymHv3r0wNTVFQUEBFAoFBg8ejMDAQPG4m5ub0rqVy5cvIyEhAWZmZkrj5Obm4s6dO8jMzERSUhJatWolHtPT00PLli1LTQuViI2Nha6uLtq3b1/uuBMSEpCTk4NOnToptefn56NZs2YAgLi4OKU4AMDDw6Pc5yixdetWhIWF4c6dO8jOzkZhYSHMzc2V+tSpUwe1atVSOo9CoUB8fDzMzMxw584d+Pv7Y9SoUWKfwsJCWFhYVDgeIqpcmLAQlUOHDh2wevVqGBgYwN7eHnp6yj86JiYmSu+zs7PRokULRERElBqrRo0arxWDkZFRhT+TnZ0NANi3b59SogAUr8tRlZiYGPj6+mL+/Pnw9vaGhYUFfvnlFyxZsqTCsa5bt65UAqWrq6uyWIno7cSEhagcTExM4OzsXO7+zZs3x9atW2FjY1OqylCiZs2aOHPmDNq1aweguJJw4cIFNG/evMz+bm5uUCgUOH78OLy8vEodL6nwFBUViW2urq6Qy+V48ODBSyszjRs3FhcQl/jzzz///SKfc/r0aTg6OuLLL78U2+7fv1+q34MHD/Do0SPY29uL59HR0YGLiwtsbW1hb2+Pu3fvwtfXt0LnJ6LKj4tuidTA19cX1atXR69evXDy5EkkJibi2LFjmDhxIv766y8AwKRJk7Bo0SLs2rULN2/exOeff/7Ke6jUrVsXfn5+GDFiBHbt2iWOuW3bNgCAo6MjZDIZ9u7di8ePHyM7OxtmZmYICAjAlClTsHHjRty5cwcXL17EypUrxYWsY8aMwe3btzF9+nTEx8djy5Yt2LBhQ4Wut0GDBnjw4AF++eUX3LlzB2FhYWUuIDY0NISfnx8uX76MkydPYuLEiRgwYADs7OwAAPPnz0dISAjCwsJw69YtXL16FevXr8fSpUsrFA8RVT5MWIjUwNjYGCdOnECdOnXQt29fNG7cGP7+/sjNzRUrLtOmTcPQoUPh5+cHDw8PmJmZoU+fPq8cd/Xq1ejfvz8+//xzNGrUCKNGjcLTp08BALVq1cL8+fMxa9Ys2NraYvz48QCAr7/+GnPnzkVISAgaN26MLl26YN++fXBycgJQvK5kx44d2LVrF959912Eh4cjODi4Qtfbs2dPTJkyBePHj4e7uztOnz6NuXPnlurn7OyMvn37olu3bujcuTPeeecdpW3LI0eOxPfff4/169fDzc0N7du3x4YNG8RYiajqkgkvW+FHREREpCVYYSEiIiKtx4SFiIiItB4TFiIiItJ6TFiIiIhI6zFhISIiIq3HhIWIiIi0HhMWIiIi0npMWIiIiEjrMWEhIiIirceEhYiIiLQeExYiIiLSekxYiIiISOv9H8Q/dARyzOafAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Negative 0.95 0.98 0.96 11788\n", + " Positive 0.74 0.50 0.60 1306\n", + "\n", + " accuracy 0.93 13094\n", + " macro avg 0.85 0.74 0.78 13094\n", + "weighted avg 0.93 0.93 0.93 13094\n", + "\n", + "Loading train/val/test datasets from ../data/datasets/A601_DSI.pickle.\n", + "Shapes of train/val/test data matrices: (12693, 3, 13)/(3160, 3, 13)/(12971, 3, 13)\n", + "Shapes before reshaping: (12693, 3, 13) (12971, 3, 13)\n", + "Shapes after reshaping: (12693, 39) (12971, 39)\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/ebezerra/anaconda3/envs/atmoseer/lib/python3.10/site-packages/sklearn/ensemble/_gb.py:570: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples, ), for example using ravel().\n", + " y = column_or_1d(y, warn=True)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precision recall f1-score support\n", + "\n", + " Negative 0.95 0.98 0.96 11684\n", + " Positive 0.72 0.50 0.59 1287\n", + "\n", + " accuracy 0.93 12971\n", + " macro avg 0.83 0.74 0.78 12971\n", + "weighted avg 0.92 0.93 0.93 12971\n", + "\n" + ] + } + ], + "source": [ + "for station in INMET_WEATHER_STATION_IDS:\n", + " train_and_test_classifier(station)\n", + " train_and_test_classifier(station + '_DSI')" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/.ipynb_checkpoints/CDS_api-checkpoint.ipynb b/notebooks/misc/CDS_api-checkpoint.ipynb similarity index 100% rename from notebooks/.ipynb_checkpoints/CDS_api-checkpoint.ipynb rename to notebooks/misc/CDS_api-checkpoint.ipynb diff --git a/notebooks/.ipynb_checkpoints/autoencoders-checkpoint.ipynb b/notebooks/misc/autoencoders-checkpoint.ipynb similarity index 100% rename from notebooks/.ipynb_checkpoints/autoencoders-checkpoint.ipynb rename to notebooks/misc/autoencoders-checkpoint.ipynb diff --git a/notebooks/autoencoders.ipynb b/notebooks/misc/autoencoders.ipynb similarity index 100% rename from notebooks/autoencoders.ipynb rename to notebooks/misc/autoencoders.ipynb diff --git a/notebooks/.ipynb_checkpoints/contiguous_blocks-checkpoint.ipynb b/notebooks/misc/contiguous_blocks-checkpoint.ipynb similarity index 100% rename from notebooks/.ipynb_checkpoints/contiguous_blocks-checkpoint.ipynb rename to notebooks/misc/contiguous_blocks-checkpoint.ipynb diff --git a/notebooks/contiguous_blocks.ipynb b/notebooks/misc/contiguous_blocks.ipynb similarity index 100% rename from notebooks/contiguous_blocks.ipynb rename to notebooks/misc/contiguous_blocks.ipynb diff --git a/notebooks/data_augmentation.ipynb b/notebooks/misc/data_augmentation.ipynb similarity index 100% rename from notebooks/data_augmentation.ipynb rename to notebooks/misc/data_augmentation.ipynb diff --git a/notebooks/.ipynb_checkpoints/data_fusion-checkpoint.ipynb b/notebooks/misc/data_fusion-checkpoint.ipynb similarity index 100% rename from notebooks/.ipynb_checkpoints/data_fusion-checkpoint.ipynb rename to notebooks/misc/data_fusion-checkpoint.ipynb diff --git a/notebooks/data_fusion.ipynb b/notebooks/misc/data_fusion.ipynb similarity index 100% rename from notebooks/data_fusion.ipynb rename to notebooks/misc/data_fusion.ipynb diff --git a/notebooks/.ipynb_checkpoints/data_imputation-checkpoint.ipynb b/notebooks/misc/data_imputation-checkpoint.ipynb similarity index 100% rename from notebooks/.ipynb_checkpoints/data_imputation-checkpoint.ipynb rename to notebooks/misc/data_imputation-checkpoint.ipynb diff --git a/notebooks/data_imputation.ipynb b/notebooks/misc/data_imputation.ipynb similarity index 100% rename from notebooks/data_imputation.ipynb rename to notebooks/misc/data_imputation.ipynb diff --git a/notebooks/misc/downscaling.ipynb b/notebooks/misc/downscaling.ipynb new file mode 100644 index 00000000..8f540224 --- /dev/null +++ b/notebooks/misc/downscaling.ipynb @@ -0,0 +1,181 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This notebook implements statistical downscaling of precipitation using the Mixed Bernoulli-Gamma model to synthetic data. It includes:\n", + "\n", + "- Fitting the Mixed Bernoulli-Gamma model to observed and climate model data.\n", + "- Bias correction for probability and intensity distributions.\n", + "- Generating high-resolution downscaled precipitation while preserving total rainfall." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import scipy.stats as stats\n", + "import matplotlib.pyplot as plt\n", + "\n", + "def fit_bernoulli_gamma(precip_data):\n", + " \"\"\"\n", + " Fit a Mixed Bernoulli-Gamma model to precipitation data.\n", + " \n", + " The model consists of two components:\n", + " 1. A Bernoulli distribution for the probability of precipitation (p).\n", + " 2. A Gamma distribution for the rainfall intensity (if precipitation occurs).\n", + "\n", + " Parameters:\n", + " - precip_data: Array of precipitation values (e.g., rainfall amounts).\n", + "\n", + " Returns:\n", + " - p: Probability of precipitation (Bernoulli component).\n", + " - shape: Shape parameter of the Gamma distribution (if precipitation occurs).\n", + " - scale: Scale parameter of the Gamma distribution (if precipitation occurs).\n", + " \"\"\"\n", + " p = np.mean(precip_data > 0) # Probability of precipitation (fraction of non-zero values)\n", + " if p > 0:\n", + " rain_values = precip_data[precip_data > 0] # Extract only non-zero precipitation values\n", + " shape, loc, scale = stats.gamma.fit(rain_values, floc=0) # Fit Gamma distribution to rain values\n", + " else:\n", + " shape, scale = 0, 0 # If no precipitation, set shape and scale to 0\n", + " return p, shape, scale\n", + "\n", + "def bias_correction(p_obs, shape_obs, scale_obs, p_climate, shape_climate, scale_climate):\n", + " \"\"\"\n", + " Compute bias correction factors between observed and climate model precipitation.\n", + "\n", + " Bias correction adjusts for differences in the probability and intensity of precipitation\n", + " between the observed data and the climate model data.\n", + "\n", + " Parameters:\n", + " - p_obs: Probability of precipitation from the observed data.\n", + " - shape_obs: Shape parameter of the Gamma distribution for the observed data.\n", + " - scale_obs: Scale parameter of the Gamma distribution for the observed data.\n", + " - p_climate: Probability of precipitation from the climate model data.\n", + " - shape_climate: Shape parameter of the Gamma distribution for the climate model data.\n", + " - scale_climate: Scale parameter of the Gamma distribution for the climate model data.\n", + "\n", + " Returns:\n", + " - p_bias: Bias correction factor for the probability of precipitation.\n", + " - shape_bias: Bias correction factor for the shape parameter of the Gamma distribution.\n", + " - scale_bias: Bias correction factor for the scale parameter of the Gamma distribution.\n", + " \"\"\"\n", + " p_bias = np.clip(p_obs / p_climate, 0, 2) if p_climate > 0 else 1 # Adjust probability of precipitation\n", + " shape_bias = np.clip(shape_obs / shape_climate, 0.5, 2) if shape_climate > 0 else 1 # Adjust Gamma shape\n", + " scale_bias = np.clip(scale_obs / scale_climate, 0.5, 2) if scale_climate > 0 else 1 # Adjust Gamma scale\n", + " return p_bias, shape_bias, scale_bias\n", + "\n", + "def downscale_precipitation(coarse_precip, p_bias, shape_bias, scale_bias, fine_grid_shape):\n", + " \"\"\"\n", + " Generate downscaled precipitation using the Mixed Bernoulli-Gamma model.\n", + "\n", + " The model downscales coarse precipitation data to a finer grid by adjusting the\n", + " probability of precipitation and intensity based on bias correction factors.\n", + "\n", + " Parameters:\n", + " - coarse_precip: Coarse-resolution precipitation data from the climate model.\n", + " - p_bias: Bias correction factor for the probability of precipitation.\n", + " - shape_bias: Bias correction factor for the shape parameter of the Gamma distribution.\n", + " - scale_bias: Bias correction factor for the scale parameter of the Gamma distribution.\n", + " - fine_grid_shape: Shape of the fine-resolution grid to which the precipitation will be downscaled.\n", + "\n", + " Returns:\n", + " - rain_intensity: Downscaled precipitation intensity for the fine grid.\n", + " \"\"\"\n", + " # Resize coarse precipitation to match the fine grid shape\n", + " coarse_precip_resized = np.resize(coarse_precip, fine_grid_shape)\n", + " \n", + " fine_p = np.clip(coarse_precip_resized * p_bias, 0, 1) # Adjusted probability of precipitation\n", + " rain_occurrence = np.random.rand(*fine_grid_shape) < fine_p # Simulate whether it rains in each grid cell\n", + " \n", + " rain_intensity = np.zeros(fine_grid_shape) # Initialize array for rain intensity\n", + " rain_intensity[rain_occurrence] = stats.gamma.rvs(\n", + " shape_bias, scale=scale_bias, size=np.sum(rain_occurrence)\n", + " ) # Generate rain intensity from Gamma distribution for rainy cells\n", + " \n", + " # Mass balance adjustment: scale intensity to match the total precipitation\n", + " coarse_total = np.sum(coarse_precip_resized) # Total precipitation in the coarse grid\n", + " fine_total = np.sum(rain_intensity) # Total precipitation in the fine grid\n", + " if fine_total > 0:\n", + " rain_intensity *= (coarse_total / fine_total) # Adjust intensity to match total precipitation\n", + " \n", + " return rain_intensity\n", + "\n", + "def plot_precipitation(coarse_precip, downscaled_precip):\n", + " \"\"\"\n", + " Plot coarse and downscaled precipitation side by side for comparison.\n", + "\n", + " Parameters:\n", + " - coarse_precip: Coarse-resolution precipitation data from the climate model.\n", + " - downscaled_precip: Downscaled precipitation data from the Mixed Bernoulli-Gamma model.\n", + " \"\"\"\n", + " fig, axes = plt.subplots(1, 2, figsize=(12, 5)) # Create a figure with two subplots\n", + " \n", + " axes[0].imshow(coarse_precip, cmap='Blues', origin='lower') # Display coarse precipitation\n", + " axes[0].set_title(\"Coarse Climate Model Precipitation\")\n", + " \n", + " axes[1].imshow(downscaled_precip, cmap='Blues', origin='lower') # Display downscaled precipitation\n", + " axes[1].set_title(\"Downscaled Precipitation\")\n", + " \n", + " plt.colorbar(axes[1].imshow(downscaled_precip, cmap='Blues', origin='lower'), ax=axes) # Add colorbar\n", + " plt.show() # Show the plots\n", + "\n", + "# Example usage:\n", + "np.random.seed(42) # Set random seed for reproducibility\n", + "coarse_precip = np.random.gamma(2, 2, size=(10, 10)) # Simulated coarse precipitation data\n", + "obs_precip = np.random.gamma(2.5, 1.5, size=(100, 100)) # Simulated observed precipitation data\n", + "\n", + "# Fit Mixed Bernoulli-Gamma model to observed and climate model precipitation\n", + "p_obs, shape_obs, scale_obs = fit_bernoulli_gamma(obs_precip.flatten())\n", + "p_climate, shape_climate, scale_climate = fit_bernoulli_gamma(coarse_precip.flatten())\n", + "\n", + "# Compute bias correction factors between observed and climate model data\n", + "p_bias, shape_bias, scale_bias = bias_correction(p_obs, shape_obs, scale_obs, p_climate, shape_climate, scale_climate)\n", + "\n", + "# Downscale precipitation from coarse grid to fine grid\n", + "fine_grid_shape = (100, 100) # Desired shape for the fine-resolution grid\n", + "downscaled_precip = downscale_precipitation(coarse_precip, p_bias, shape_bias, scale_bias, fine_grid_shape)\n", + "\n", + "# Plot the results for comparison\n", + "plot_precipitation(coarse_precip, downscaled_precip)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/error_analisys.ipynb b/notebooks/misc/error_analisys.ipynb similarity index 100% rename from notebooks/error_analisys.ipynb rename to notebooks/misc/error_analisys.ipynb diff --git a/notebooks/exploratory_analysis.ipynb b/notebooks/misc/exploratory_analysis.ipynb similarity index 99% rename from notebooks/exploratory_analysis.ipynb rename to notebooks/misc/exploratory_analysis.ipynb index bc988740..5bc892c3 100644 --- a/notebooks/exploratory_analysis.ipynb +++ b/notebooks/misc/exploratory_analysis.ipynb @@ -330,7 +330,7 @@ }, { "data": { - "image/png": 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\n", 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", 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\n", 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", 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" ] @@ -1777,7 +1777,8 @@ "\n", "df_estacoes_pluviometricas = df_estacoes[~df_estacoes['N'].isin([1,11,16,19,20,22,28,32])]\n", "df_estacoes_meteorologicas = df_estacoes[df_estacoes['N'].isin([1,11,16,19,20,22,28,32])]\n", - "df_estacoes.head()\n" + "df_estacoes.head()\n", + "\n" ] }, { @@ -2095,7 +2096,7 @@ }, { "data": { - "image/png": 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\n", 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", 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\n", 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", 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AAFgW/UEAMIx17bF1Z1XdVVW/UFVXJElVXZ7khUlu2XbeLUmuebonqKrXr5Y7PHrixIk1lQUAAAAwX20i691NpAwAYAEOGmzdn+S788RSgy9J8rwk718de+7qf09tO//U6pyLtNbe2Vq7trV27ZEjRw5YFgAAAMB8TXVf1anWBQDMx4GCrdba6dba0dba4621+5K8McnfqKrnJTm9Ou2ybQ+5LMlDB/mZczSV0VUAQzvx0Nl84cTp3U9kPVxg4En+Gvp3/nzLp+/4ythlALBuM75I9/DSeqgRAC60rqUIt2xdDw+11k4muTfJi7cdf3GSY2v+md0yiglYmr/6bz+ev/4fPjl2GXsmFwKYjht++478nXf8Tj5x231jlwIwKW1i0YQ2dCf9PT3UCAA72FOwVVWHq+o5SZ6V5FlV9ZzV915aVd9eVYeq6vlJ3p7kN1trW8sPvjfJdVV1eVVdneR1SW4Y4HUA0IFeb3K7uDF9Ot0WDnCx21czfu9+4MzIlQBMw2xaerN5IQDApux1xtZ1SR5J8i+S/N3Vv69L8i1JbswTywvemuRskldte9xbktye5M4kn0zyttbajWupHAA2pNdADriYv2cAGJaxVZ3QJgKgY4f3clJr7fok1+9w+APP8LizSV67+gKArrgpBwAA5swtDwBDGXJg6br32AIApsLUFHiSThsA5kqTb7paB2/O9CsEoDebuP8WbAHAzJQufAAANqyDDGeDOmiPd1AiAOxEsLUB2nYAAADAEljOGwAYmmALAAAAANbGEGcAlmsTV0HBFgAAAECnphahWJLwKWX6GgAz99VHH8+5809/8R/yMijYAgAAAOjM1DKT/dcjAQOA3v3ln/pY/tmv3rLxnyvYmgBNOQCG4PoCAMCmmKl1seaXAsACfOj37t74zxRsjWhig6sAuID7UAAApm5q4cneZ27NuVdkzq8NAMYn2AKAXUxtmZe96rRsAAD2oLT2AICFEmxtgKYmAAAAAADAwQm2AACYvV5nXgJAL5odXgGADRFsAcBM6VqAaTp+6kz+17HjY5cBwExMr81nNMmW6b03ADAPgi0A2MXE9uPelZkpMG0/8o7fzuvfd/PYZUzKrXefyq13nxdBtMIAACAASURBVBq7DICuTLfN11njeQDTfW8u1tu9DgAkyeGxCwCAqerphhTox10nHxm7hMn5Wz/3qSTJHW99+ciVAPRjaoFEmakFAGyIGVsAAAAAnZpKwGWPrT4ZzAfAUIZsowi2AACYval0+gHAukw3kNhrYfO9OGt3sCRfefjRHL3jK2OXAUzIJpoogi0AAAAARmEJQ+jbj7zjt/Mj7/idscsAFkawNQHNUB6ASer947n3+mHutAEBYJ5LGE53Nt3FNEc4qC+ceHjsEoAFEmyNqHpq6QAsmI9rAACmq9dkQiN7TH77APRMsLUBvTYxAeibQA4uZlQyAHMxtaaeaywAkGwmDxFsAQAwe4JeAAAA2Jwh78MFWwAAAAAciEEkF5vyLLYJlwYAuxJsAcBMTflGGvA3CsB6uJ5MT08Zn0ASgB4JtiZAGxSAdXJvCgAwfzWxRELA1ifvGwA9EmwBAAAAsBZ7z9skKmOaViwKAPsj2NoAjQWAvhnFCADAVPXeVC29JgDAPgm2AGAHE1vdBQAA6ErvsSMATJNgCwBmqrmRhknzFwrAnFzqdU2bFQDYL8HWBFjiCmCaev18NtMMAIDpW0KjdfqvUbAIQI8EWyOafvMGgKS/oKjXQA42QecNAHMzlbZfZ01mAGBgQ7ZRBFsAMFM24oan+HsAALiYNhIA67aJK4tgCwAAAIADmcjEsYnxWwGAIQi2AAAAADrVprIW4Yr5P/0tZQ4AvRFsAcBM2UsIpm1qHZEA9KX/8MR1EAC4NIKtKdCWA2CN+u/kAABgKezxNC6D4QBYt01cWQRbAADMnk4bAICnlNFwAAxsyEuNYGsDdKMAAAAAQ9DnAAAsjWALAAAAANZsyttp2usTgJ4JtgBgptyrwrT5EwWAeS4X3NO+YT3VCgBbBFsAMDPWy4edCXwBYCrm22adY1gHAFMi2JoADR4A1smyInAxo5EBmKvJNP0mU8h09DDeTJ8UAD0SbG3Aju2YDho4APSrhxtpAAAuzVTbelOti69llQcAeibYAgAAAGDD5j9TyCQ2ABiGYAsAAEagswuAdeh9Kbk5Lhc8x9cEAFMi2AKAmdJpDtNk5R8A1kF4AgBM2ZD9UoKtCdDxCMA6WS8fAAAAgDFsoldKsAUAAAAAAMCetRFn7Ai2AABgg8zWB2CtXFcmy1sDAMMQbAEAwAia7i4AmCUrgwPAsARbADBTuszhYlP4u9DZBcAcXeo11kAPAJiXTVzZBVsAsAO32DAfwiQA5mpqbdba85bxLs4AMGdD3ocLtiZgao1QAL6WW24AAKam/0Eb8+0N6Wo/zZ5qBYAVwdaIum+DAiyEez0AANib/S4tuPcZXgAATxBsbYAOUYA+9X6L3Xv9AADQo65m0/VUKwCsCLYAYKYMrIBp62qZIgAma2rXEzOwAIChCbYAAJi9KXX66e4DYB1cTwCApRJsTUCbUk8LAACD0vIDACZDwwSADgm2NsAoKgAAAGDOjNm92JR/J/qqADioMa9zgi0AAACATrWJTbkpiYnfAQAMTLAFAMBiWAKannzs2PGceezc2GUAE1XSEwBgwoa8/RZsAcBM6b+Hp0yp729CpTBht3zpgbzhfTfn+o8cG7sUYKKmOlhjomVd5CsPP5rf/cKXxy5jNJ28TQB0aBP3vIItANhBrzd7U+rAB+DSPHjmsSTJXScfGbkSYL9aa7nptj/L+fObaU32EiRNzSvf+Tt55Tt/d+wyxufeAYAOCbYmQBsUYNrc6wEAsFcfvfV4fuyGT+c9/+eLg/6cqS5FONGyLvJH951OMuzMt6ntf/a0OigRAC4k2BrRVBuhAPTNqF2A+eiiUxT4GsdPnUlixmUvltp21iMFQM8EWwAwU8ZPwLQttSONvSldjgAbcX7AC7LPcgCWaBO3uoItANhFr33POs0B+uezHNiNj4lLc2iVOW1oKzQAWJwhB1wLtgBgZszUAuifz3JgN1P7mBhyr6ohHFp90A45YwsAGIZgawK0oQCmaWqdBQAsh3sEoFe9tKEPHRJsAcBBjHkFFWwBAAAAdGpqM6WmVc3ONrEUYevmtwEAfRFsAQCwGFPqXtLZxTOxFCH0a2N/vxP7nKh9vvCx87jKcDO2ampvDgDMjGBrA3RZAACwZb8dfwD0ZezAZixTmzm2m60ZW+38uHUAAPsn2AKAmTIbBKB/nfUTA+x7rtJYbdZDZY8tAOiVYAsAdtDrLa6lTwD655Mc2Ktu26wjf9DVk3ts9fobhGnpbdYm0DfB1gQYUQ8wbToXAQBgXg6t1iI8N2BnfA/9/B2UCAAXEWxtwE4domOPTgJgngyYWKbWWh4/Z5OIHhjNyn74TAd60dun1bNWnTKDXJY76O/RJwXA0Ia89RVsAbAYZx47l5/7jT/OYwvp/Lck4bJc/5Fj+Uv/+qNCk454qwCYo+okMakh99hyjQdgwf4/e3ceZtl5F3b+d1uNbWLwJAEPZJgnEet4Yjx+CM7AEMhACGHAAyH4ISE4PEAwHg/wjMEEu/G+CGTwQmws2xgvWiwj2ZIsWW5r3yy11u6WutWbpO5Wt3rfu3qpverMH1W36tate+/Z3uX3e9/v53lAsqrqnPe8+3beE6InwMIWACAbn7p/j3zkrmfl2kf3xw5KEOzyz8tVj+SRr1NgZcIPOrBJAbAneDWvrMtnZZPNmqVvbPm7h+Ym30gyAQAwEAtbAIBsTMzMiYjI1Gzab2wxCQoA6WCTAoBhtPX4tIWnTHfRad7nypYB1tINAKBHzM0sLGxpkHcfCgAAAEA/ZhoBJC72G0NrfB5FuCj2MwIAkCoWtgAAKMF4FEgHE0wAAN9CtzVa3uzUEYrqvO4fMLQ5wVq6AQAgwsIWAABDGRqPAjCIiSRUwWIsgGG0frNRa7iwEskEAPAlxBCGhS0AAAAgIOaRUAXfSwQAAJawGQdAP5+bKFjYAgBgCPP9cvMPAAAAgORF7rMyGQ8AgD0sbAEAUMLannmOFckbkzP6kUQAkLbQfTEtbX/dcMTus4Y4MlFJ0gykJd8AANAEC1sK0JcAAAAAAABIg6V9ZpbCCgBAFwtbEdF5AAD4wO5LwIaCwooKyCUArIj9BlZdtMMLiAUAgEUsbAEAkCpjkwtALiiaqMLaBDGAeFifaSfX6KOdAQBYxsJWALl2kgAAkdEAAQAABBdqoUnbukTd5469IOfzG1t0wwEA8IuFLQAAEsPuSwBICLOjAGAWxx0CAFIWs5VjYUsB+jkAAACh0PGCDexRAOxikxHIAgAA+F33YGErADo0AAAAcfk8bqgpltgwCvkDQFXUF+3k/lZV7s8PAHAvxOibhS0AAAAAAABjtO3ZYHkEyBt1AICQWNgCAKCE1Q661XCjHdIdSIOy+WoAQKI0vtUOAEAZFrYAAEgMQ1MAAACENj073+jv2JQDAADqYmELAIASLBQBgCKZfQukYMoXQAkt30j6y9t31fp9LS8K+Yg93oICAMAvFrYUYLAKAADgl5ZJP6AqJkUB+3y3PR22XwEAAIVCjL5Z2IqIwSoAwAem7wEbWGtrKLM+NPkEwDDWN8lSv+nA5h8AgC8+h24sbAEAkKi8pn4BOzJblwGAbIXazKptWYJ2zgbSCQBgGQtbAAAkStskBwCgPiYeAQzDUYRu8MISAADNxGxDWdgCACAxTHEAw2mYvJqZWwjEQ8+djBwSWKAhzwJAikJsHNBch2sOGwAAZVjYUqBOZ+LSdevljVdv9BcYAABgGt9JsOOeXcdiBwGK8aYWACAEvv8OVxiHAAiJhS2D7tzBJAgAAEAdKidtGPs3w6QJAKxAtdgM8baAxQgAgEUsbAEAAACAUkw3Anb5XjDQuGfDpjxrWvIPAMAyFrYAAEgUuy8B5ZhQaiaTmbg8nhJIE+XXhkyaEwAAksTCVgBMKwKAUUYXhhikAwAAxGOzBxmP0S53JQW5AQCQMZ9tPAtbAACUUPltHgAAAKgWrg+pa/GkwztrxAAAIGsh2kEWtgIoS0hdXVAAQD+O9AMAAADSRFcfSM+6G7fKG656InYwAHjEwlZE7OABAOWMvqnF4BwwgrIKAEA0Rrv6ACq47okDcvfO47GDseRrWw7LT1x+j8zNMwAAXGFhCwCARHGEIoAkZbZ6z1vDgF2hyq+2aoLvSgHASu+46Wk5PDYpF6dnYwcFcCpmm8/CFgAAiWIyNE+kuiGsPWME9iYAdlF80UV3HDkhuwMIiYUtAAASw2QoMBwD7gRQyQGAah1jS3s++gY0VQCAnIUYd7OwpQA76gEAAPxifglWMVIAAHuY5gHQiyoBufK50YOFLQAAAAAAAKOYMAUAG9hsB7jDwhYAAAAQAzORAJCkUNV7h/Pu4ADdEQCARSxsAQCQKI5AAQDLmLAGrMt14anqY2vpqvrsM2vuj1v7FhqQAsVVAmAOC1sAAAyjeSQ6AoNUYDWVpZmi2ozRuhlAfkJ9T1tbtVg3PEWkVtpnn9nCmmaseAcAwAUWtgAAKJHrblsAnjGfhAq0TVgDKBeq52i9h2o9/KkgHYBwKG+AOyxsKcBgFQAAuEK/AsnLZLNBJo8JAMmZmy/k/ORs7GAAAJC0SgtbnU7nDzudzsZOpzPV6XSu7PvZz3Y6nV2dTme80+nc1+l0/lnPz17c6XQ+3+l0znU6naOdTuctjsNvGoNVAMD8fCHj024HvhwrAhhBXxAAkCBrcx2u+86Xf2On3LvruNNr+sTIAfAv1NG0QGhlWdtn1q/6xtZhEblMRD7f+x87nc53ishNIvIuEfnHIrJRRK7v+ZX3isgPisg/E5GfEZG3djqd/6tdkAEACMtnJ/Ty23bKP3/3HTIxPeftHgAAu5gGAVCGTU263LLl8NK/a04ZvssL11i7KcdnDpCLEDm90sJWURQ3FUVxs4ic6vvRr4rI9qIovlIUxaQsLGS9utPpvGLx578lIh8oiuJMURQ7ReTvROS3nYQcAIAE3Lj5kIiI07e2GKQCwzHgBgAAABADb24B7rT9xtYrRWRL938URXFRRPaIyCs7nc4/EpF/0vvzxX9/5aALdTqdNy4ed7jxxIkTLYMFAIADAXdT0b0F/GK5F1aRdwF76NcBAHrxphbgXtuFrW8TkbG+/zYmIt+++DPp+3n3Z6sURfGZoiheUxTFa17+8pe3DBYAADbQvQUyxsxnM5ntdM3raQGkwFr/NrNmZQlHWALh8KYW4F7bha0LIvKyvv/2MhE5v/gz6ft592cAAAAAgCGsTQwDWBa6/GqbL1UWnKF8vUBhrf62Fl7AMt7cAtxpu7C1XURe3f0fnU7npSLy/bLw3a0zInKk9+eL/7695T0BAEiOtgkJAAEwrm2GCQEAEBH71WEO3V8Lb2noDyEAIBVj4zNy6br18uUnDrS+VqWFrU6ns7bT6bxERC4RkUs6nc5LOp3OWhH5qoj8cKfTed3iz98tIluLoti1+KdXi8g7O53OP+p0Oq8Qkd8TkStbhxoAgET4nJBgkJonjpUBEmNgUhQAYE+HHTYAAE+GjWAOnBkXEZErH97X+h5V39h6p4hMiMg6Efkvi//+zqIoTojI60Tkz0XkjIj8mIj8es/fvUdE9ojIfhF5QEQ+VBTF7a1DDQBACEYnE63v3gUAcFQNgOps9liXxe5yx74/gPRRzSBXPoc0a6v8UlEU7xWR9w752d0i8oohP5sSkf+6+H8AAJjE5CIAAAC00dpFrRospcEHAAAGtP3GFhxgdxAAgOPjgAxR7AEgaVTzAHLCmHY4FvKBlVzUFixsRUW1BgBw3xawYQJA0qjkACjH2/55s5b8NKuAfxQzYIHLNpKFLQAAAGSj0DR7Y2ziC3EoyrEAKgrd1qhq2wzy+ZYJKQOgF91/5M5ll4WFLQAANHDYuFvbJQqEQLlISCaJmcdTxvdbn39cPvfQ87GDgURRjnXzlT7W1hkzaVYBAIlhYQsAkB1NY00GkgAAxPPAsyfkA1/fETsYAAAAQPI4ijAxfFwRAHTjeBcAXlC1oIJYTdDcfCFPHxyLc3MAWUi1GWTjGgAAC3yOZVjYAgBkp/JYk1EpDGIdFkhD7Cbok/ftll/6xEPy5Atn4gYEwFAdDjt0gr4TAABulfVQXGwgZ2ELAAAFGE8DfjFpBWti59nth8+JiMjRscm4AQEMy7Xpib0wr4qBTBC7vQEA5MPlphwWtgAAGCbAKM/nuJ9BKqAcE3/NULkBUK7Dyk7WrLxJRzYFAITm8pNMLGwBAFCCyQkAXrA+gxG0ND1kU0A/6+v9xoMPYJH1usgn4gZYycU8GwtbAAAoQEcXACrSsuKTOKIZaM7FdyOqsF5OjQd/KJe70X1i/AEAiIVvbCWCzgQA5Mv6hASAFij/qCDWBCljFKC9UNW8toUUK6cdWAmnb0QDEI6u2hpor2zM8PShsyv+N9/YSgSdBwCIg84kkC9V5V9VYKCNlW+0AIinW0toW4i+ZE3e9Vdv/a1t0REAgJDu3nnc27VZ2AIAAEDy2FAE1EOZAdrzvqShtKCuNbawpW1hMLTcnx8A4F6IpoWFLQBAdjQOtdnNCWRIY2UEAGgt9BF32hYm1lR8fmXBzo7SdVEAACphYQsAgIg4agoAatI2g5soohnQb+kowqihWC37owjzfnwAAIJgYUsBbZ1QAAAAAO79/eMvyIHT47X+hgUmANbkvrBFvQ2gHye0AO6xsAUAgAIMgAGgIqNb4cenZ+XPbnpafv0zj1b6/diPGfv+AKorlHUkzX1jy+OEs7KkAQAgGSxsAQBQwudkgc+JQ3aFAYAe84tV8tnx6bgBAeBdqIUmrQvQVt7YshFKACnRthEBCM1l34WFLQAAEhP6g+UAAH9iz3/Evj9gWagembZiuibzvmjmjw9gAL6tDbjHwhYAIDt1B/8sFAHwQttMJADAKd/V/FIPVVl78uJvqTfVxBsMAFLHaSqAeyxsAQCgAN1cpGrzC2dk9/HzsYMBoCH2dgD1hdoUpW3z1au+538QEZFLKoZLS+hZVwMAoJlhi7Yh2vi1Ae6BEuxOAoCwtAyiRXSFBWnQ1q341U8+LCIi+z742sghWaAqfqgAmlGViOkjugH9tLwJoCUcsfU278QIAAB+8MZWRMxlAAB8YMMEsJqyTe2AepQZQD/rxTTVHmuqzwUAgCsupq1Y2AIAOPPCqXH5/rd/g2PHGmAxCgAqYsUFAFagG4k2yD5AOJQ35K7KUO7gmXH5gbd/Q3YdPTfy91jYAgA4c+vWwzI3X8iNmw/FDooZPr6NoO17CwCA5pgAATBMt8unpZ6wusBmNNgAAJhTpa9w5/ZjMjtfyHWPHxj5eyxsAQCcszqoBYCgqCuzVDXZ2aMAoEzH/GGEkXmKPmupYi28AAD7XIx1WNhSgDkN5G7T/jPyix97UCZn5mIHBS0xCQdAKxbcAQCp0tbGKQtOVNrSBkAc1AXASqPKRNXiwsIWgOjed+t22XHknDxzlO8ypaJQPpzVGDo6ukCG2AyQpbrJzjcYAZTR0vdmkxuQN7osALqGVQd1+gplv2tyYWvPiQu82QEACnEcii4MLAAkicotKC0T5gAGUNb1tlo9576BIO+nBwBYZW5h68LUrPzsRx6QP71ha+ygAACMqjoHYHWQp2yOAwDQQodXIACUyHxdBgAAGONi85y5ha2J6YU3tR7ZczJySADb5ucLedsNW2X74bHYQQHUY0oRlvB2BZJnfKGnbgmN/SYBb2MDeqVSOlmYA5AL6jvAHXMLW11UBEA7h8cm5PqNB+SNV2+KHZQlFOuEJJaYPh/H+PwsYA4Lf0A9lBlAPy2llHma1ahDAQApa9r2u9g8Z3ZhKyV0/gCkIrVFmsQeB8haavUT7LKSFXlTC2jP91h/qW1jUqEV17HHEbIAAPjHwlZE9HWAlSgS6WBoHRfxDwAAEE+osT4L0O0QewuIBwBAaKPeaK56FLu5hS0Wg4B0MRmPnLHRFgDQRlEUcn5yJnYwAEj4fp22biT9WltILsA/yhmwoM6mnLLfNbewBQBAW5o6lT42bLAHBEDSjM+Y1g191cf922/ulVe99045OjZZO0wA/PC9Mbd7fePVogrTs/MyMzcfOxgAACTBRReo7DuVLGwBAJxhQaU5PiwNAOhVd6L6tm1HRUTkyNiEh9AA0IgTbdwoCpEfeudt8pN/eW/soACmMaatgCgCnDG7sJVWPZDW0wBA1fNwY9E0BxDy2wh3bj8qjz9/Otj9AMAL4zO5dUNv/HEBBKCl760jFNV1+irYY+emnN9DSdIAAGBO2XzZ2kDhAABkgMk33d54zSYREdn3wddGDgl80jSBcuqC+wkiIDeayjQApETLgiAAAKjP7BtbAAC9GCMCEBF583VPxQ4CAADRhOoT0/UGAAC5MbewxcsAQHoo19DK6iQBb85Bi7MT07GDoJvVSgateEt2dpUAaoTqi3WP6LFa/PW8MaUlHAAA5KFKF6CsP2VuYQsAgNBCzE2oGdcDqaOswZjYH2KnfQL00raZSc9CVTX939gCAG9sVY9AZXWzdp2mt6xbwcJWAPSVoJm1wQd0K/uwI1ajjQDCUFk/KQjSLU8dkotTs7GDUY/xvou3ZHfdoCjInwCq0VYrVl2Qz2FhSVvaAIgr9oYlIJRhOd3lUM7swpalyfiyoBp6FACoRHu1pjF8GsMEIG1bDpyVN1/3lLzjq0/HDgo0omECGst1jJ/DQhUANEL1CNTGUYSKqdw5jOxoGnxYWrDGYIqyk1M+c6aPKKMoAaji4vTCm1pHz01GDklNqTY2bSVc+W87NCZ7T1yIHQygtlDVlZZxlJZw1GU02AAAmOOyb7TW3aUAALCBKVEAQCy+50+dbVpS1Fj+33/zkIiI7PvgayOHBNBF0yZFi3zFnrVksbogCZhCMQMqq9osmXtji44bkC7KN7SxmiMpSnljzDSYyvPsYwcp9v0z07RqrjvfyAQloIfv4kiXr53ca0vG33CNLgiAqqpUF2WtlLmFLQDpYiImHSQlANjB8dhheG8aPU1Q0qQD9YVeL6DvrRiJAwDAkjpdpLIWlIUtBejmICYWkwAdKItAhpSsJ6l8my1h3pKddgTITncBjXq8nVxjj/EHEA71NLDAZUkwu7BFdQAAetFpq44jQABEY7X6yWwiru7Tum5XrGYTIAfWy2fshRXr8ecK4xEgnMy6scBQVVoejiIEMJKKTqyGMMAJFfnJKB/929iTBQCUo4qIgmgH4Jq2Lp+28ABAbBz9jdyU5XgXXQUWtgDEx8gHSoXImT66t3SZgeFocVYzN9DOZBNF0+6R600NvsvMC6fGZXx61vNdgLAY3sASNsMBAJqq24ZUGclVPQXK3MJWHsNYAIAmPtsehpFAGCoXb6gAsuJ94tDoEYT/+kP3ye9euTHQ3YA0WW9OYq+ruL5/b3WsOW04bQMIh881IDcucnxZM2VuYYtqAEgQHerkxB6cAtodHZuUyZm52MEAEIG3Xo+xN7V6PbL3VMC7Af6FGt50Fyas9r1jL6wwDAUAII4qm/7KfsXcwlaKrHZCkQaOHYBLjA3rI87y9OOX3yO/f+3m2MFAbFQA8CD2RDGAcLSVdmtDS2vhBQAAy1jYiogxJwCgi4F1ProbCu7dddzr9QHoVLeExirTDFUAOzjiCoAG1ETliCNgQZXNeOkdRchkDeAUu3qByCiC2bh7xzG5+clDMjdPXwZohfEAAIjI8oQP1WI7uc4z5frcAIA0mFvY6qL9BQCkhYYtdW+4eqP80fVPydxiJ2YNi5qIjFonLKvxzcQncnBxalY+8PUdBr9/qaszYe3NsRB7PKlCAQBYbdQYo2rbaXZhyxJeiAGQi1TrO5/j0USjDCN039i6hJUtoBnjjU3V0FubIG6CRTNo8an798jnHnpernlkf+ygNKLtbfCqoaEOiIvTWwAAvgxr4us0PWXtlLmFrZS6Pd0EzmHQClRBSUhHKoPUEEO9pjF1zaP7Zc+JC07DgjC6k09rmExAZORAVOFz4jOR7gISMDM/LyIis44XiHyP9bvF86N3Pev1PlV1aFlEhHgAsBp9HuTGRR+obG7R3MKWRVRe0CyVBQjowBAunHfdvE1+6W8eih0MNMAbW9CCHkAc1uKdviKAqqxu2rUZagBdR8cm5coNz8cOBoDA1sYOQM7YqA2sRJFIB4PD6trk+/Hp0d+BcJkOTGy6k9PClsZsoypMSsJCn1S3WNkkxBFVSooA4I3vN3eovtvxlT5WF/gAq373qidk++Fz8nOv/G75nn/4rbGDMxLjaqC69I4iTLD87zpyXu7ZeSx2MJApTedqJ1i8YVzIPOmyfdNUrrFaTgtbmlAsEJu1cUyIiRcmd6AGWTFLIRagLNRz+kMIjDY2MSMiIvPKvjfYi7EIUhWz1Jl9Y8tC56CqP7r+KRER2ffB10YOCQBgEJ99UBah8jO32IdZ62lhS1MPiexdgvhpxvg4oHayR35c2ikAvqX2hhPf2ALi0NxF1Bw2wIeyPD/qx1WLi7k3tgAAejH51Rz93HzMzi2kNuUFyJO1+t7nhkJrcYGEGW2StXUl6lYXWvpCuU8460gFoDklVQmASqoX2LLfNLewldpOHgB0pFOU++CwDvJ/vjiJEGiI2Ysggnxji/4CEsf8hW68WQW4Fet0LfoTgD4uhhJlRdvcwlZK6EJBAw3HesYPAVxhrrE+8j8QhoLmDqilbp4liwN6hOoSq12YybzRZUwEAMAw7voILGwBAKBA5uN/IE+Ryz31TmCB4tvSfCpvs0ANo1nR+gKKhk2WAOyzUBdS2wH1JXcUITUB4JaGc83jhwC50dSUkP8BxKagK5AV39GtqY0DckU5tMX1Invvep2FvGAhjEAVFjbM6A8h4MbwvSvuRkP2FrYWUREAgF4WOpTaEGf5YHMylihZUCJPhlU3uqv+vpLsVAt5D2p4KkC+jwrsbkz45Vf/T17vk6rcN3Zk/vhIiNpjvHKLRwAAIABJREFUWXvoDyGgR9UxgtmFrRQwjgOQGiudNU3hbDKg5tgWAC6YndCjDgSAFbTUilrCUZWv5sRs+woYZWGTqP4QAoFVKRQl7am5hS0qAsAtJsjhQ2rZKsTjpBZnVczPF/LEvtOxg4HMWBj4hpJjvZMy18kZcl6WSWBER32IDJHtAQCqlTRU5ha2UsL4DUByFmemGCRV5/PYBO2T1lc+vE9+7dOPyL27jsUOSlI0pbumsDBxPpy5uDEX4AVNF1XrbkJyFTts6gDaYzOFEZknk81WFTG955Zt8qn798QOxhILRxECqWrcn3dQbFnYAgAgIh8THj7mfH1MPu45cUFERA6dnXR/ccCCzCfSYrswNSvPn7wY/L5Vq+im2cNStuq2gUUhcvcONjkgHaGmWLv9M07haMbXPoney1pIGgNBFBGRD92xSz7zTT2LKTm76pH98pe374odjFUslDcgF06KY3JHEVJJAU51FO16pnwjZ+T/fPQuZv7Jl7fIA8+eiBgavxQ1McAqv/m5x+RnPnx/8PvWre6r9tVcF7fQxfcNV28MfEegB+2VU3XrudT6wVYex1q2v+K+PfIX39C3mIJlsfK+pTFHavUdMExpXndQFswtbC0xVBFYqmAB2HP7tiPyoTt0dPCp7uprcmwCneF03Lj5oPzW5x+PHQzEQqUZ1ZMvnF31305dmJKx8ZkIoRmu6psYFpsG2jMgb5o2WQKwi/4EYEeVpr/qyUZ2F7YAJIdxTTNv+uJmueI+XUcyaO9Yagwe32AAMkSxV+dHL7tbXv3+O2MHoxVL3SmKANQgM0ah5QhFHaEAAAC9yjaCm1vYsjjxN6yvxu4kaKBlMCGifzEktNMXp2VyZi52MGqhWquPOAPy873f+VIREfnJH/zOyCExymiHoWmwbT6tH6cuTMUOAhLnql8WutxqqSc0jS1jonsPhMWYGkhT2TqQuYUtAMjFv/jAXfL6zz4WOxhJ0tjvZR4gPzmkeQ7P2MR3vezFIiKy9pK4XXGLG8ZSoLENiqXuJPiPXna3nJ/UdVQkMEqTI6eRFlpaIBzN5Y2Ff6C6qv0nFrYAQLFN+8/EDgIAx7pjmnnGNkAzxrfl+i76lqqWJmF91XttHxUJ3VzPO7KBAAD8s90zBNAv2W9sscANuKXhSEwFQYBzVNY+Ebtp8LZrT1EGoX4fLfbOTd4ksCH2+Cf2/YEgHFeHwWtXJeVUSTBqc13PaRhjAzmxWvcAOatSbpP7xlZXCpVW7MkMQAuKQjqYJAWqm6fyy5aWupI3CXRrOlbQkbuqoRqEGory4uzcvMzOzccOBlpgrgfAMPS/AXfMLmwBAPRiLKcDnWbdOIowDuqn1bQstGGw2Bv/vd6f8ghlYpc3kYVvyf3IB+6KHYxWaGsBhKSg6gby5aHNr9qPMLewlVL/iNfToYGG3WQUhXSklpYhi4fLe1lJhvi1T1zd+ldzubnt6SOy9eDZ2MFwQnE0IxNN67zYXbXY9wdyMzYxI+cnZ2MHA45oGG8DoZDdAZRxWU+sdXcpAGiGzg9C05Tl2OSQn27+69Z9axTngf/32s0iIrLvg69t9PfU7zaYe7uTjBVEiKrJXN5D8qxWL5SldlzHH/17IA4WkgE92rStVZtRc29sAQAQWogOcp1GP0aH3ccdrQ/5L123Xt549cbGf9/9xtYa6xEBAA0x/wS0k0oZivUYLEAtSiQfAZpRzIDq0j2KMJWeG6CEhs68giDAMe1VddUsFyJvkv1tu3PHscZ/2/3GloZ62BdNj6a8WorK3De2NGWsAGK9iaG9LQd8yKx6yV7u80vkdwCAZmXtlLmFra7cOyAAoBFjo/r6j6VDPrpvbFFu0Gv38QuyYffJ2MEAgqDpA9xQ04/UEg5UoibfAC31bhScmZuX6594IWJoSlDuABFxs7bDN7YMYTEPgBWc848yx85NyrWPKR5wBODrG1uUP9v+7UcfEJHm3zWrg65lWHX78nWTx3V6BvnGFpkQSMq80TJtNNjusMsKCfn0/XvkI3c9GzsYq3SENS1kJkCGN/fGVvYdDsAxJhSAuHIdRz514GzsIETTrXe7C1ApHwNDE9Pc/Hy4yEs5D+aI9ARWOnF+Si5dt14efO5E6e/SbrUTsOlyIuXjoIEcFSJy6uJ07GAMZKx6BFobnufdlQZzC1sAAKSoTtOeQqc45KS9VvOe3thCGuYCzq4ykZsW1+np8y1Qsh5C2LK4mebKDfviBiQD3foi982T5np2eScXEsPYCrDBxeYSFrYCoE4FkAvqu/pyjTPWtfL4xlau+dsKs+njeMI0lQlYi+mZSNRDuTrZzGI5EtFTlrSEA9VYze/AKORrwAYXYzAWtgyhkwgfdB2/QCZPhfb6SmPwUplYrcrqNxhc6kaBqmo4A+S8ZRRDG2KnUyfp5XfkoNvHitHexi6/oVl9XqPBBrCoM+TfAdhWVp7NLmzR8YBFH/j6Dll349bYwQC8YfKrPp+TLJonF1jYWrZmDeUmBI2xPKoYhCwi5hZXHQc4VFz7vo2v5/B7FCFtAUIKWNmZq1jdsLZRK0QqGYsSoB3yeymiCKmJ2Z83u7BlCR0ZdH3uoefluicOxA6GYnkOAFOkvdqrmtNC1t9Ob2VgMiXntrH/0fWnFlwzUEShSN360lX+CpJNM24LoJOz/kngjo6WRWKOmrYl5/440kU/G7BhVBNUdaOMuYWtlBvejftOB7/nG656Qr7x9JHg94UeunbVaQoLoJeqYtsQb2wt03UkrFsk82A+4mX/qYvyCx97UM5cnHZ/8cSllk0pd8BKMYtEwk38QE37d7HGpDlWlzuPnJPJmbmV/zGzfIq0pTy2AlLgssk3t7CVsmPnpkb+3Een6+6dx+X3r93s4coAAAzHjl7ArU/dv0d2Hjknt28/GjsocCTWm1oh0RQgpCplxGI50sRq/07XZk9/zlycll/42IPypzf0fR4hj8dHBopC7zptJtUMUNmoslp1gdrcwpaWV+wBAANo7UUakFtHlze2/NEUtUwQNle3z6sp3RGHxTxgMcywJ+V8pm9+RFt4RvPWTVHa/7k4PSsiIpv3nxER+mlICHkZSEqyRxECcEvDa9rxQwDXUptA8Pk4HSMlwPVO1lx2xgKh2ahRWjJaH4Wq9hR07QCVUi4aWrpV3Te2lAQHQI5SruyBhFTpK5SNa8wubGnpuLXBoBNYkEBxxiKqtTbyKglWj6pxIYU+DPRpsmufrIjY9L1tglz5yom5tflsXFpNYz1HOiFlVjaOAmjP3MJWzu0vnQ8AcKNqbRpiA0KTe2gcINfFUYR5IJlH81GWs9g45fghyaaj+SzH1BEII0JGy6IyXs3qxiWjwQYwwBrl1S99H+SizTpG1T81t7AFwC0NC6bK+x1AEAqKYlBWJz4AF6rMd9atE5rUIbS/acqtPQHKdMvEqLqX+tANDWPLOjJdf1z1OYIUNs3l5OSFqdhBUKzItlwDVrhscVjYUoTKF0AqtA+OqG7jszbxgXSknvfqHL+SdkxUl3iWaM3nGIWoR9fkzJxMzsx5vUfQ46kCVyxayhL1qQ2p94VStuXAWXnNZXfLTZsPNvr785MzMudxh2GseQDG90Baqo4/zC1spdT89vcl6FsAsK5/9x8wzHzWr2zl8+yqqgRVgUGO6k/2NKsrXGd1v0cR5lMfYrRXvOt2+bG/uCd2MJzLremxdtT0UnBtBbuxYWM1vklkx66j50RE5NG9p2r/7fx8Ia96753y9puedh0sVcjPQFjDmv42XQKOIkxQJn0tBMZCBLygwqrNR5RpTgbNYQN88zHvR5lqTvtbxrHQR0zfV588KJv2n4kdjCVjEzNerlulhFMLuBFm+V6/3tpT01ofmwnyNreY/jc2fNvLCrovgA1VmqSyheq1jsISXAoDUCpbAKlJrVoLMfZrEmdl4UotHVCP/R4SWsmhAmBiLogQE6AkZVx/fP0WERHZ98HXRg6JX1W+seX73qncp4y1N7aYkwHSQ7EGdAjRIzD3xlbKO0zoVAFAvhJu3gbK7XlzpSqdVQXGvcQfzyvtcZfy+AcIadR42/lQPNPBffek6brVFrVcGLyJi9RZ6DKl8KIG4FvVUmJuYcsiV30HCxU07NE0WaIoKEA4DDCBbLls97qD5CxqFOrNIJgABVBbzXZNSy2T20Rz/9Pm9vxIz4o+C/0XQDWXY2AWtgAAzmkfGmkMn6ZF5q65+UKu3PC8TM3OOb92zuMNhUmNwHzmfxYjFEuo7E9Mz8lVD++T+fl2D0V9iBCYtA/HWlzn3mSWfbsEsIhcDdhXtRybW9iy1U0CgLzkPjjUpu2E4U2bD8p7b90hn7h3t5sA9WAyMw/UCc2FKCMaF9SxWuxUGpRN/uqOXfKer22XO3ccDR8goKFRk/ixy1lTy+VTxxPQrKymMUroniFljD8A+ziK0AAqW2igaWe3xk4/mtE+Waon1+t2cWpWRETOTcxQPgEkS3mTpdLZ8RkRERmfbvdGr7W3O2ATZRxYqVj6J4UD6eFNRCAdZVPWZhe2LHVOXYWVTgcApMtHDd923dpnq6NoTR1IQ4MCq2lzC1bTMt4ZlE20b2DBYNOz83Lzk4fyTb8RVZ7z2jDXODbKdXJpbV+HhYqFgDyEOQ3A/z1G3l8YZwJWuFjnWOsgHEHFriRTku2ABitoygeKggKs4DNvWuh3+xicU97zoDGdFQbJie5zWahTWtOYsTLVegMFSRnUX9/9rHzq/j3y0hevlZ/7598VOzjB5JDNtJQlJcHAEKQPUtUZ8u8A9KmyoFW1X2P2jS0Aq528MCWP7j1V6Xc17SLTFBa0k1pShnweLRMSvbqPr2kBPAW+Y5P0GkJRBVUliZruYKvzmNbyiq8kDH0qgrFoHxlea8+Su2PnJkVEZGxiJnJI4hhVhTjPyoraHM1SrUKsta+cDmSHsawVhfbqlzREappmaRdvC7OwFdAT+07LD73zNjl9cVpE4ldmse8P9/7jpx+RX//Mo5V+V1NnW1NY4AYpWp3mjjdHEaIt0nk0l81fk7Z0YvH7SFY2mFjvLjQNfqznDpErjCcpjKhTP9qoDfWjbC/T1Hb152+OIMxLLguYVvq1AIarWowNLmzZrYg/ff8emZ6dl837zwz8eVmaaeoQQae9Jy/GDkIrLHDZx+CouToDjapFxVWRcj04uDg1KxuHtIVADnyOt+tc+603bhURkYOnxz2FxpMRD3ng9LjsOXGh1uVCdz+svHlW5WrMHcGSKv0ZRiPtWK0ScvnGFuwjawGwoqxtHTV24ShCA/obpNCdaDrtENHR6dYQBrilfY2yavC0P8cw2ovUm697UtZvPRI7GED2zk/OiojIhanZyCFx56f+6j752Y88EDsYUVnaZMKmJsANLSVJSziqslRfAgAQw5uu2SSfvH93lHuXtdJOFrY6nc79nU5nstPpXFj8v2d6fvYbnU5nf6fTudjpdG7udDr/2MU9AaTH2kAIQDPbD5+LHQQEwpx1c3XjjqhuTnvc1X0Ty9WbW70DSRagkDqWN+KiigGqaVNWcihnRaF/kydgze3bj8pf3f5M+S9G4PKNrT8siuLbFv/vfxER6XQ6rxSRvxWR3xSR7xKRcRH5ZJub5FARD3J2fFr2n3J7TAwDVIiQD5AnlX3djIqiyvgPiGoXPrH7XL/Kx8nWvK72tL/ivt3y0TtXDoqpDhFCt8yNKiHkxTh011rNWXmuXL65hJVSXPjpfSbt/SEgd1XGQlXbJ99HEb5eRG4tiuKbRVFcEJF3icivdjqdb2974RSb31FV78//92/Kz//3bwYLC9LH8X/wgWxVn+Yoc7kA855btskNmw6KCPUP8PCeU86v2WoHr7tghOF4dTjUJp+mt4k9QTMo2E0e5UN3PCMfvzfOMSZAmX2L3yq22kNhs2I7PmNP4+IR2cUuF8Mo0j+uYdH/p1/ZIpeuWy97a34rFtAqRPvncmHr8k6nc7LT6WzodDo/vfjfXikiW7q/UBTFHhGZFpEf6v/jTqfzxk6ns7HT6Ww8ceKEw2DZMSq5j52bCno/pE/j4EdhkNAQSVlfnTir3kHQkxJXPbJf/ttXtpT/IpLCGmY43dKecpyn8mx1n6Nqna9x8rQMfT9oceeOY7GDkASNY8wYco2FA6fHZXJmLnYwkLk1RvuLX1ncBPqXt++KHBIgvqob+1wtbL1NRL5PRL5HRD4jIrd2Op3vF5FvE5Gxvt8dE5FVb2wVRfGZoiheUxTFa17+8pcPvZHlDkJ/2GPvvgQAxKf57SWtQdt9/IK85fqnZHZuPnZQgFZG9Wst93mtSS2ufYwx1t34tPNrAqF0F32r9Gus1QfWwgsdfPTxi6KQn/qr++T3r93s/uIKFEWx9GandT7HeBrqJK1jWCA3ZXtdRv086FGERVE8VhTF+aIopoqiuEpENojIL4rIBRF5Wd+vv0xEzru4b2pC171spoKIrkl1izuNAVf81MntyrfWduLN1z0pNz15SHYeoTsxiNJk04MIWkVrWR/GWHCDc92fOnlhSq7feGDgz9ovopGa8K/KN7bgVtU3t1KtAbTnNR/t/tz8wkXvf+a4+4srcPNTh+SnP3y/PPTcydhBac1av6+OQoqknw/ITsmcta9vbBWy0JZvF5FXL4el830i8mIRedbTfVXqpoH2zg3gyzWP7JN7d3G8B2CZywFC2/X0pQkqow1rTov4mgaWRrMLenQXUVznq9D5tO79qv6+8ze1AhQaTXUEYJmWoqRp02QduRyh6DN55hbjcO0aX9OMcW05sHAY1bPH7G6syySbA8hI6xan0+n8w06n8/OdTuclnU5nbafTeb2I/GsRuV1ErhWRX+p0Oj/V6XReKiLvF5GbiqJo3BJQEbuT08QahgvRiX/XLdvlv1650ft9oIf2waHu0KHrhVPjcvltO1flJ9IPWE17vetCd0LO6rP67ns7v77NaAZasbkso4e1+jnEOpymKOmG5ei5yYH/vY3uG1uJrmslxej6czb4bA2sqdv2u2wX1zq4xreIyGUi8goRmRORXSLyK0VRPCsi0ul03iQLC1zfISJ3i8jvOLhnEgMtFpaAPhQJ86zu0iznP3Pm1CZUzSb/zxc3yc4j5+R1/+J/lh/6rlWf52RQhqTVHiAs/rNZPWyj/kmlyFdNoqaDPtcTIj7j3UbOg3XLb3qHr0XI43nKsY+6tLCV48Mbo2mx1ZXevo/2LGhtAwDQVIiy2HphqyiKEyLyL0f8/Esi8qW294F71KV5I/3hk/bspamv22gKunIE60yJqpOus3PzA/87gwE7NA0sc8k1fusUHZwH19jzD7Pt0Dkv1x0UPT7yjKb6AmmqksVcZW2+nw2N+utZl/lmfrHbfgmVuVo5baQEEF+Ivom5l4RTqoh5vVSXmbl5JkuBlqjVmnP6DSvlKeFqvKv9OYEyTvsdGXRhum9b0F0LpEIV6+qbiUBqcs3aVp/bdbit1W0u+ubdb2ytWUP/XLuU1x6tlb1BUpr3Bnwzt7BlUQoVa+rGxmfkB99xm3zy/j2xgxKcpqPjKCrIkaIiaI7VuKNfALTjfAIycA+kbh2gucqgPoMFdbKp0a5FAqhMrOseRXgJC1tetWl3abMBaDKqTqpaX7GwhaTdtPmg7DlxofT3TlyYXPp9AA7Qaa5NY5T5ClPb4S6DMjtIq+aIuvRQHlZjVzKCijDfzhT/aKnGj5XNVy5rYL6xBQBwraxFMbewxYDQjsNnJ+SGTXEXit7y5S3ycx99IGoYYqhztJGm4xcVBQUNMY5Jk7Z07U6EaguXFtSlecqhXHSf7QNf3+H0uqHLTEpp5PJZEooWKKNpvONL+k8I7bpHEV5ibpaxnthteOz7l4lV32qPFwDLXG5sW+vsSoGxu6893+3Nr3/mUXnh9Li89lX/RL71RZf4vdkI82QV9eiDpIc62q+qsZvqPE73uVL5xlbKE24MMsNLpVxgWcJVRNLPBn2q1I9kybC0xHcudZHPPsJ8Jm9sWc4rhoMOIEEumovE91I0d+m69fKhO3Y5vWZ/I9KfgKm1/yfOT4kIE9woRw5Jh5UJVY15zuXihvb2RNO3/ZCfVPslbaqQecuzNA7k/fTlMs8eSEDMLEzx0c1Xj9TMmMhhBc9RhGHQJo9mIX4shBEIwUVZMLewFbICuOK+PeFuJuErt1QndmC3oSRPIkc+Br7a64DW39jqXsfouLk/fVjoC8NaLDctxylnJysThWWqpm3stzlDxLf29gppqVI/usr1oWqrbhmKXV9gJWvjWhf1fcj+ecz8nnI/CwCsMbewZRntn362up9uaJhQjR8C5EZjnvNR/ygo3oPVDFf/2LU7mNX6eFjGPNtoWqJHQ1+gCl/BDDVBpiW9qxo1MWvtWZC5kgzLohDQHuUojDZ9IdLIBpIJ1gzLsm3qnKp/ycKWIqHnFKgsoQ15Mh2kZQ025pO97jxtGgVG5uJLMciEC22yEXkwrFTqLhd62xYrC6ywixzmn93mxG3Ae9+Ayq2NpSoHALhS1qaYW9iy9kr3KJn1b0xIpQ9WJ2sdOjsh5yZnvIUFzVgdADGQaaFGklvNH1392aTsaXYdPVfr94GcpVwN+3o26pTBUjn6EYiBegW5ST3Paxl/KQkGUMuJ81Ny6br18vjzp2MHBQENf5PL3T3MLWx1UZm3RxSulmuc/MG1m2MHAYlJpY62vpmibTr4GsDV3ZX/5uueWvkfloKVxqRrym8pJPxo/tUsftbrqyryzU/ppm0q/QXoVlY/+syH2VZbMMFqHRwz3JbLtNHkriWH/rBFG/ctLGh9/qHnI4cEqTG7sJWCfAfn0KC3M7j7+IV4Aenx0O6TanZCoRmqteZcdsJdty9ad+1bbUcZcMGnJuUi9xwZuuvh+36u60bqLFjXLXMx+g25lh6GdMY4KBu5pHnsx7Q6/gFE6FPCPXMLW5YbS21BT2kB4XWfelhufvJQ6+vk2kfQ8tyf+eZeuWHTwdjBUCGh4pmE3NNDWwdUV2jac90ea0svhNHuG1vuwoHhQvW9SU8gPi3jq9C6k+51+yKx6y3X989z8WEhErVuiEMYdEEwSJ51IkIwt7BlEQXYv037z8gfXf9U+S+WSKURtrxoeeDMROwgIAOaSkiOTUT/M9eNg24dl2PcWWO4OTIs3ZKRyrGdVR9DS/EJNUmZRurCIp9lbWwizLeMaW8b8tSu9KaHprTpf1yrm6Fihjp2W8VGpsFS6SOmLuU8iNValcqKmYWFrYC0VbPUJ9DI8qIclmkdJGmrh3vVyfqhY9f1pGbbcUf3+VMZwKTyHGhgRGHWWo/G5KukENfx0O1DCEv9hgg9wfVbjwS/pwaU7WWaosJnupDmgBtpFiXGu2imrO/GwhbQg6o2PjrEC6xGg/b5eY3x6jPOUi9PyrMblEq1XLR5LDaVhFU3umMnz6CFP/IMLIn5ja3cEMULevMa1SVcalWPVcyLl9+2U/7+8Rda3CieouA4TECLEM3f2gD38MJi36A/zLGrWjpYq6USJZafg13TadBev1Stf0M+h8t7xW5fyvQPNuo+uvb8VaY//ClPEGuaRNQUFp9yeU6nEiuCrvJAiLxEvw9Ik7WS7TO8mus5l13QkE+50HfOs8MTYtjwtw/sFRGR//y//1P/N0NW9NaGsIo3tgZIeYIJw+TXKertYGs6BoviZxvpp4P2ZGh/FGHh5DpAStrUv+cmZ90FxCfjZT5UG+nqPqHbdOp0xOJj/B+u+BSL/19X748xgS0uq1/q8jB4KwmWdOsF2oY0xUxXcwtbFgvB0tEHcYOxmsG4rKPeACXxyDBknqRApnxk/dQHlqkM6DRtLnDNYr9Ni/pxt7jg6zwk6Qv+3cKaiaS5GLWtv5rWEWxERB1siAkn5T5NU5qqK58LoJqeMwdN0lLbAniuciwrtAwYxEV/3tzClmUZ1l3mpFLZWmsoV5xBTkkRESZstAiRDFUXZ8YmZmRyZk5E2EVP8UAT5Bv7UlnMruvs+HSU+7K7FukJV4fkWVstY0y3THNMUL9XpyWqtI3LtCBa/JicmZOxiZnYwUCGqta5LGwNEOyYkDC3GXH/2CHwq0k6ph0jevWmFZ3rNJCM7r36fXfKL37swVp/4/I4KqffAOsbkdUdiKT2EfjTF6fdLmZTAJEoX2U+dN+j7v3qvs3uOp581rVNo57+IlwiO8FrnZJJhRVyfimPGB0sk+zUGPHj1i987EF59fvudHjFPBLozMU4m9K0cVEey8Yh5ha20l6MSWSGDmhhnrMIEYDGXFZlYWPvyYuVrpVLa5LSwGXnkfOxg4AIfPRrOQYqHbHruBD3z+EN9c8+uFd2HD4XOxhZyyCbqXtGbeEZJkSLaSQqWlP7CQ5HUnguK+USejxfcf6hTE7jk/Vbj8iPfOAu2bT/dOygqFWlLjpf8RvQ5ha2unwOgnxdub8Yxy7W1j5gXfu+Df4mdpq4Ym0BeOVRhBCxHw9aO8213wzyEgp7nO/+d3u5JFirt6vKaAzjXN0cobXetSDV8ueTl+9C1mgdLKXYZet3yi9+vN4b1/CDNsm/pm/hp0zTM/aHRVHQ1NMSV9rrMU353aqU4zDlZ+t6dO8pERHZzqamxmOsTfvPyJUP76v0u2YXtlybny9kdm7e6z0yKL+qNFn8TCWNqjx67+/47Bzd98zxWr8/n0NLlzDtqac5fJrD5lv9CfycYwsYrFsqlM93tJLys7nkqoqs0j9smybNjyKkHUB1ZbmF7ORO03ElSRCXi7cpQpYjyiyGYbOSTvThUceWA2cr/665hS1fDdj/d92T8gPvuG3xHnlUhHk8ZZ5+9iMPxA7Ckg3Pnaz1+5kUP0SmqWPVaBxpvJy0HTtreHzXfYVU675Un0sz7Tt520jlG1sppRFFHJZUKXpWy6e29rZqP0lLfPucDGeiHS61Kesp50QtdUkV1AmAO+YWtnz5+tbeuAhhAAAgAElEQVQj3u9hqJ51KlaVnfNRhIfOTtT6fUudgFxoG5zmqjsoD5EcOaW5qzrH6qAgp7TWKNX4z2VjVgp8J5Xrfp3P8Da9NrkdtdTIaFSlYeUQ35qf0WXfwWq/vK4UvhVU5+hfazSXN9B/y01ZeXSRH1jYGiCXgpb6BEiTx0s7RmxIPV/mg3SsyufYqO0AU2txPDI2GTsIauMGw1mbh6A9XM3XRAwx3ZzTFKlxMYoHmrDWDlhGGV2mKSpChCXEwk8ui2iDuIjenOMPcXTzbU7jm4wetbY6dVBZlWduYctyvugPewo7PQDX5i0XciTHaj3tOtiuY6F/ctpmLKMKo0UIQI+B5dhZf63ZhcYmZuTSdevlS4+94CogSFjpN7ZMzzLo0u3jVY3RHCY5M3hEEcnnOS3LobwBCK9pP2rYVEGdq5lb2OryWR3nUteHesxYjScDlOo0vYpOui2wGg+p1Z9h6y+HR4EoTwdnRxFGfE7NUaw5bFjJZR7uXsrHYuK2Q2Ny6br1tT7ki9XqpreWvoDGNqV77PbVj+yLGg7Y0M3DmsY8rmmpL6zyeuSq4rTRGzIM4yKvtqkLz45Py6Xr1rcOw5uve1Je9d47Wl+nH3kaWrDBszwOOIrQiG5CkqfD0jgI10Rr9PDGFkKwns2qDpBTnsABEM69u46LiMjdO49FDYevAWLoTVghB7pHxyblvsX0q2tkMCNvUGDXOXyxNhGltShoDVc/X+m94tQHA3FhLNujIRdZ8fmTFx1cReSWpw7L+clZJ9cSWVmWrdXjqxmoNGpaOoowbjBgRJ0ibG5hK8QgxteOGm0F2Epns4ybPGG+5UtGKvkyd1rTUXNJ1xpnIeT26IP6GRrT30X7qvG5ypy6MCWXrlvfeDHAlbpR53W3uZJ01FyH1xEyPn/5Ew/J71z5hPsLK8kTgAu9ZVJLfWdWzYqa6A5rWN/ORTosvxnpX87lNPaijfaj+ouiUJ8/tIfPBzbc5ilEXje3sJWSXHYa2nhKG6H0RVPfZJ5XtkQkz85OCBqj1WcnT+vRJ66eOObTuW7DtaZVjrYdPiciIp/f8HzkkDRD+1FfynF2/PxU7CCM1Bv1ddqGhJMMHnTbbE1jHte01WP0a5apjgnVgdNFSxnTEo5hKPsuJNxYAY6xsDWA9obCFRocaMHujfRor1005jiXcaZ+4qYvgNqDm6tc+kP9uvnR6vOfHZ+JHQR/1FduCMVq+URcIWuQ3Ksra2XU7zfc9UeGi+zK/FJYTeZQDGRFJ6zXv9bDP0oueRCj1ckHZeXB3MKW5TLQnxbaX+G1YliBqFdhkhYA4qApcGdyZk427D4Z5F6W+yMhWczfFsMsIjI9Oy8iIn/ylS2RQ4JhmPRbLfUJDgsT2vAj16Sv3YRmEE+55oXUaOsfxupTKIuGVShuSmnPODDL3MJWl8vOwcT0nLuLjVAWZG0NpSuxOnL1GnqaP8CF1CbttA5EtYarKl/N3btv2Sav/+xjsvv4BU93QE5i12d1y/lcBkf5ptJV9t3nD9lGWB+/sPCUhzqp7CpP556zNH0nMjZNj9Yfzy77OimnoYie57Pe7vrS+wablrRqKuUkNp40UMjswpZLb7txq9frV61Ug1e+1ChZ0zqQjz2RCMSitEh64WzSqC/Sth4cExGRmbl5NzcYeW+3f6sx/V1+SFyT0o1GAYeTLqNnPkBkpzrQDp1PNZaLulz115r3R21EYgppnYJuOoQ8MSX0WEtLVlsKB5l/iYWocFo0Uu0sLIq9sNRqDKKmpvDHQnnLUeLVwkDkxfK+ydAT2Grcw9zClo+Msf3wmPd7iORZkEMYllwcRVhd3k9f34HT4/Lv/voBOaH8g+wxaV04RT2+Bj++6pyL07MiIvKt33KJpzvAsrr5zlo1Ziy4qEJJooZq0+tMFlorn7DDVd4ij9riup6zNr528fghszzli++UjxJ78bEt6+HPHekXlrmFLcu0HUWYel+g3vP5jY3th8dkPoMjglyw0En9woZ98uyxC3LLU4e83cNCPOQg5K42H/dylY+8H5vl6DqTMwtvaq29xH+D6jq9XF7N3aRcnhVRN79be/y2b2zlmt4iuexgbv6Mg95ycTWhlvb7WnbCmTsf1V/OdaqInbwfYgpGcxuTeTY1Ldo3tpi0by3nYpdD25jBI3pXp5phYWuAUA1ENu2B5+jUXjFuOXBWXvvxh+ST9++OHRQgGN2lUn/4UE1/OnabA+XNApTT0j+r2x/NId+vXbOQOpd+xz+IHJJmYqZRu+NTV/9x7InaHPI73Inxja3gjJYJo8GuxUJ95SLfa56X+fQDe+Qz39zT6hqx272uVmml4xE8y+IhzQl5FLAWWT3ysCMFHRw1WJZ3DC5spVtJcb6/W/U6Vv5qnMNnJ0REZNuhc97u0VaOjQz8SLVeCfFcde7R9KxiLfrrHIs1kPY4dsHFI2pqXuo+j5YJjKraTihZytM/8D9+W+2/efct22TD7pMDfxb62f2/BTtoIaq+EG8vWsp3TWie6M1RyDYp25Rnk1G2ukmuqOu35IO37ZK/+Mau2MFwInbZ0noEoqYxR1ta47iN9J4IWhhc2PKPb2ylQVtf2toEGeIiv/ilqT72ubCstYOvNFjBDCrdTH4qYjSDts1Bo/5eS5u0HIr6iXT1I/vl9Z99zGVwGotR3JvUMcEX/KwWPqhXlv81HwdtlY84fe7Yefmzm7bKnLEj/jX38fSGbDRf/ZJP3r9b7tpxbODPtLVR2sKzJHKmUlzcAHjAwlZA+r6xFabG930f7e2W1ollrfGmNVyoZ2xiJnYQ4ID2gYH28Fnn5EPihtNI25uaIa+lX1YPq1rbibWm44S235Rbur/vI9P9Xh41Vcmvzr5T6eYyau7jS51Fnzd9cZP8/eMHZO+JCx5D5J6FNHIxZZFCP+Svbn9Gfu/qjQN/pmWTT1eT8Oh6AgyjdQ7RhRTqCdThP8HNLWwFmWTwf4ug98mVtgrTd3i6Rx42kXC7iUiefOFs7CCY46OKcFXvuH6rzPsxXMrq/yoMBjlZanbA1swUTSb6f/snLl2+ncWC40gOT97qKEKnIQHyELpOVTfp7iE4Vo/P19S8uvjeSRmr6WRF7OiNff8UPHfsfOwgBBf0KOCikJMXpsLdsILZuXl5zy3b5MhY83nbJm5+8pCs33ok6D3rcNF3MbewBXc0dbDSFqYG/5MvbwlyH9/IlwuIBx1yT4fl76usjoi5+ULOTTZ7M8/XwkHYDnO4eyEsq5P5TU5metm3fsvSv1t7Xovqf+et599T/YZaw3CpfZ4+VsKZiyr9BCZt26k7SdXkq9gWipWVfOS2jgqXMjnXrW2ePYd4s/CIb7xm08ifW6k/mgixCePTD+yV11x2txw4Pe79XlU9uve0XPXIfnnrDVuD3vePrn9K/uBLm4Pec6VmmblOLmFha4BQu6sSrqtW8H7Ex7Drq2nR6gXkwtRso7vMtYno2Jkx9v0BBeq0PaHaqVG3eefN2+R/e++dMjM33/4+ra/Qfz01DYBpucfj48+fNvUWU7ILHz2Ww+i24xA6nZtMWLQNYpvybCFvAKOU5WEfedzVcZlW+Xj65Q1X7q/tM7ks9KcYjlenJa7UnDCgBLGhW8j8et+u4yIicqjFqVYu9LYr3XYg867BEpdjL3MLW77zgI+BrdbV9tTLk4UOZL97dx2TH37PHbJx3+nYQQnLXlJhCJKyPqVNxAqdTmdVJ+ymzQdFRJp9wNvZQ8fLce0miX1/e1JPSdTYByqL/94gP3/yot/AONQoW5kdXVkN94Im0V7nTwZd33VS+/gOUZ36QlM9N4qVcOZCQ5M0Mzcvsw42BfXTVp3XDU+dsuKyXPk6Nm/FhKaytPElm+eMHYBFtC+D5ZIPkbfJmbnYQXBi2IJnnZbZ3MKWb0Whp6HSZvfxC3LNo/tjB8Og6kXy4d2nRCTv7xPRQVtALPhVNX5zT4dQixKub2NxQKMxzC7CpOm5muSzmMGve++2bwfk3P7m++TttW0nNNURoT2295Tcvk3vdw9y5WzRdsh1fvg9d8iPX36vm5so9uBzJ5xfszsBZq3e0BTc/rbeattvM9TxWU3v3KT8Np61+rsJ33Mom/afkVe863a5/5njfm/kxOgEH1YncRShUmV5O3TVVXfH+C9/4iF5183b6t+n9l/Uvf6QgpBBhdlGb/xEbzajBwCIx2fHp2016KMe3XrwLEUeqvXu3rbUl2gU1LrPGvkVvOU+X361iNajJqOVEQ9vjPkwKn7+02celTd9MeZ3D/JRNpnrIx8Mu+bU7Ly6j9q71M3z2w+fc35tjW+BD9MbVkt9iTYyeUw1PZBYix+WyiH08HmU7NB7hrvVCr6fsXvC14bdJ/3eyAhzC1vev9fk8R5ll9XeERiftvWqo7b41BYeVYoh/w54Qn88nl/+xAZn1xrWXvuqRt5w1Ua5dN36kfc+dm5Srn1s4e3mJ/adloeeq9rhpPLTYuWA3c6xkfNNjgU1O9vmNtyhoqHN4lTctwf93b3pta3mXMTRLXpVJmRdTdqarV4Da3Q0q49vbHmtVfLIDEvlLG4wkDlL38cdikLkROycEHuDw/nJmWD3ihnX5ha2fHNVCc7NF/LgkMmspcwdubIKXbDu2nFMLl23XvY5+l7FNY/sk0vXrZdzE7NOrucLO1rs2338gty+7WjQeybRIUtAyHSocytNuaNJFPmuF1/3qYe9XPfuncdKf+cNV22Ud3x1mxwZm5Bf+/Qj8l8+91ila1Pk0VbbowgRTpM6sG3yNpm0rXLsF/1cYLDQR37l0AJ036jmODV36DrY1aQckN420LVCFWXfiHz/rTsChaQ5F3USC1t9iqX/V25sYkauf+KFgT/7ysYDw+8x5PpWKq+6E73d3//alsMiIrLloJvvR131yMKO+GPnJkfet5ZMG3pfH82tHoC4ty/zbz/6gLzpi5tiB8MEKwty1zy6X+aavN1ghOsnG1VE20yW+nL64rTX64sMj+PuvUflLys5z0Vxjt28NNEb5JhVWt17t63SRt1PS9W+HA7nX+ZzfL2SuwU4gcLFPUfV7z6+Q1QnVbXkSWAY8qg/FuI29k79YYbORTnosIXdEKgoUrFCKikzOzcvVz+yT2bm5mMHJQkxhoQGh6G1lNWDYxPh3tiqq6yeqJN25ha2fDdgdS7/thu2yttufFqePji26mcXpla/RZRKoWqaBK6fv2xnsrYGlb4XoMfBMxPy948P3pgQi4/dp67q3VEhi/nGluZqlTofobWtQ2ztgLcU1uZ665H26WvT2fHppSNge1nJrym1Bb/5ucfkZz9yf+xgNLL0db4hHRAfcwwv+ZZLnF/TgroxWacs+5xPuXXLEW/XTqkeqMLipiaLon1jS/nMpqvi9qXHX5B337JdPv/Q846uCJEw/TcrfcSmLNWxZe3fsGcpKvxO19paIcpE1ULQ/ejrxMzob091E9L6N7a62obTWceuxlnplXmoIAzVOSpYKQe+EQ/+natw5nA3HXxuqtBcR1R56lzzKjtFq7EYTSt2WccLRm0W4zqUsvJqIe5aH0XY4AJLRxEO+lmgDQrPOzrCHO0NO2bfghjf/vnul70k4N3y6Jf4nMy7d9dxb9fWPMnqMmR6nzJNjY4i9BAONRxXEOcW33apMmeACjRPeiCaKl2Xst8x98aWb7V2DC0WzMadyMitSuNg1z2KcPGfrjuiS9cdUkM2ej6vaaKtG6EtPEDe/HwI242RRxE2mSzNoGNb9xmdTiy4OiIs23bCZgadb3kWoYU5UQNBVMt13MXOL65OE/Z+Ggi5Fp7lsKDVz+Ujh2jxM0wi72JEqZZ0jD2Oin3/MiHS6bMP7pXvf/s3vF0/+qdCAEdCnPhm7o0t33VUUVSP+FG7GJuwUnUpac+XOvHU+WnJcXCGOKocoxCiemnScdVUTBQFJajSt7BzjRg4U3dCvPU3ttr9eVB1y1fZ74d6dktxvILHCq2338dEDmIxWzYTUKd6WdpYbCzFNIXWZ1jo+4ZBPIcxKp4vW7/T671T7g2FzL+x+5WU1ebqHEXIG1vSIrMvvbHV9MYN/86Rph3C1kehOOpOlb0J1ug+XtOk+sVDd9ZTbjitohHUgWQoFzOvdu995Ybn5V998F5n171h00H5kfffKXOuXgnoMyjONJZ5jWEKIeQH311ev+zbowPv7+72qqXwnHWSd9AmoTZ5LYX4iyXXelSbpbEVgx7v/B7fvbix2Fi5Uh1e1YHDKE2+dcUm4vq0f1PMCtcvhowSO5uzTyssFrYGqFoGunl10CJE7JVhn+ouuvg607y0suIoQgCGxO6ANdZoD4HbFuG9t+6QQ2cnnF3vXTdvkzPjMzI54huaZtMrMI3doVSTrvUbW2Rq1Vpvemrx5/3FeF/Pd6/aFvGmwSK/oomUJyitl4gqRXr5jS245qJkhNycG7UJUNK5bRXfLR5ByeMP5TofxnhDVHsca7f7xIXYQQji7PiMPPnCmSj3np8v5IFnT5R/x3hI+XFZh5tb2NK0c7azvLI14Dr6u1vNv7EV576rrrMY8doHKCkvcvqgv+QA6NWks6+9WtQevlCa1McXpmblJy6/RzbuO+08PG1VbY97f8vScUeNvnfX+/c1fz+KxWes+6Slgy4DyazlxAQRkZ/+8P3OrtWUgSQTETvhzJ2FOgA9G4sNJFjvHIWlvkQrSxuao/cW/Iqc/9qMUwwUncZc5zrGgytZqHe7zo7PRL1/qKj6yqaD8h8++XCYm/X5bzdskd/6/ONy27aj3u9V1qaYW9jyobeAFlJULrB1X6XMvV50vcAzP9+97uCfN6pLMv0QJ422Qnb6DY2MT8/GDkI1AdPBx61cdqo07lbzHaaRV0+8jDa19eBZOTw2KR++8xkRsTOAfui5k/ILH3tQpmfn1WxIqRt3TY4ibHM/S7Q82h9cu7nW7/fWcf3PUBSFPP786crjlibpO6qOdVb/akkcJC3l+k0br1GtpH2uYkUdqSj/9bcZioKGip4+NBb1/uoXLl11TyIWDg0xPDs3L5v2L78N1DY+Rr0YkipfTVaTMujydBsRkZs2HxIRkSNjkyIyPH+4qC/KxhwsbPVp9PHSin+jrfw2P/qj7n38PvmwYtKo4vUYVG0DKm3h6dIaLrj17LE8Xg+voklTr2HnZzcEPstsrPogxmBC4y44jWFqY9Tz/NlXt8rOI+fkyJjbTn9IP/hd3y4iIt/9spdU/hvrKfzCqXE5dWGq9PfKsnKoOnXX0fPOrnXDpoPyH//2EfnalsOVft9CWteqe42sq6VWj1pnaF2kNqtZTdmQ3Qtr4W0ql+eMWZGMjc/IFx99YSEYKpY/VrNaFzWRchv/4Tufldd9avltoLZPqjO35sPl98hd5nsXVzK3sOVj4LnnxMUV/7vyG1hLZzzXC1P37/oLtpYdwmXapoGzowiNNCKxU3V8elb2ZnLGbMrm5wvZcfjcyN+xUiZERF72krWxg6COpfQTkaXGskmozbR3I9KkXVu4+m+NpX4pa9m5q9M3TWDpOb73O14qIiK/8iPf0+wCI55VSzT0h+Nff+g++fHL7yn9u68+edBPgALqr4/2nVoYvxw4Pe7xnsN/5mpCrawuHfZTDRs8gFHIo+4tH0UYNRiVrDiK0EKAHQrSzY8QpRpScXxm+dQT6pgwRvV3Ui7aO4+snHtyVY+Rb+3r/a5ziPaNowhrqpMkaxZb7EHp2Dtp19+wD0v30B2epvdrGkzX/ZtuMIZNkFJhLvi9qzfKv/nIAyN/R+tun5z1598r7tstv/jxB+Xpg3GPHihjqXNXpY4I8Tg+Bn/O02FEGLttyb6TF2Vqdq7t5Wrxld+sLLz5Zqg4t2ap7hqm9cYjQyne24edmSsPd/8mttXXax0k7+oEcdDvuh5nWMovMWmOpdwm20VG9D/yi4pSM3Pz8sarN8q2yMee9fLRPQvR5WuSva59bL98/J7nnIeln9NjyylH3hHH5SxG0dTsnDx/crmvqmEsuuoI7JbX6z7TqYvTcuJ8+WkLLiiIxiCsrCXUUSfpWNjqUxRFg6P28lL7eYuR/7Oxtt+SCC1WaDfsPhXpztVl0t60suXgWRER08dk9bJVegd7bO8peefNT8cOxkhtO3NVqtlCRC5MzcpPf/h+eesNW9vdUJlRj6+5CdIUNGsDik5nZZh9p/PIPFb3WktvUVb/S6tvp+WobfpoTd6y53J65DiyleMiXlt7TlyQO3cck7d8+alaf1c7qmv8fs87UDVvYs87vrpNPnrXs+FuaKy/FoO2KIq1OVlr3z5GuFzVROtufFp+5sP3O7qaH66a0b0nLsq//PO73VwMIlI9bY4ufg+r9f1q/e7wsxdc3cPewlbECYZ+naU3ttwEKvSqfNNQN35eT483LDxNvpeWMs0DumLIv+ds6McXR2RWxUm8iqWwDvOfPvPo0hnnLliNkqIQmZheeFNrw+6TUcPiqiq3dNSNNv2DbCtxaCWcozR5BGuP3TSdyvpAKaR/mdSe0crzWAlnCiZn5uQt1z81cuIm5TGf67GexhM9OiNOzNFMU3h9BiXkm7wx3hrWkIxtw6ApL/pSFDreeKqjfwytMfS8qV/f4NPdwoej66N3PePkOr3PFaJOKYszewtbiixNfDX8e6vVQvvG1NHZrEs7k4f8vMG1fIrdOM2PeEZj7T4QjNoF4YrBChH8Jp1c9XVOjB1/CrNakzBZH/R0OmEn8x7b6+6t6qX0arr4M+Jn2oqs7VzWUOs3tppfYGTecPlmsLaMljiN7U4bd+04Jjc9eUg+sH7Hqp+VPav1tktEZG7xIU9dmJLp2Xln1/X/5nL9G1hIrRVvf8cLRimXY53U6hTtUqi3fAk1hnd1n7Vr9HeA2j6q+vG/Q76fddXnjvzebpXeuqesHjp6rv2xk2V5j4WtPkVRvYHotF3ZWnXv0Odihvm77q93J4rcHUXYLDwjeayAYnc7+vNX7PD0WnkUkqaQxZN+LKT/hLVZjZIh4X5kzyn5wobnB/7M1ze2nEfhiAu2uRfVnG4rJ6P8JtbXtx5xdq3W39gakTFTz7IWJof6w+jzuC8LXD2O9/o4sXi3TuNbSG11s9js4vcGf/Syu+WPrn+y9XW7baGmLGzpjfqVO9oNBBgmaMhLCoKQnDX9C1vpNVVR8k2C0TiQ1rWEu3Yck28+e6L1/TbtPz3y52tb3yEw78lV5/i6pT9pFiqrhWxUoXl4z0nZd3JcfuPH/mmIkIz+abOt5s5p2ZkQuh2ZnJmj09OChk4rlvlNDSWVREOFDH6C//x3j4qIyO/8q+8NFxZHCdW2fW9C5cR6gyBZmDQclE801rm1w6TvEdBS06M+BubxJvdvcO+m96j9dwrLrDXJxmDbXeUG2rFBZnuO5/jG00dbX09jLGgZV9eVbFnrE/I5YzYBMbNh73M3qatUjjccK6QIdhShq9i8ROEbW6s2xqefdVBR1bzw5AtnnFzr7p3HR/7c3MKWb4UUlWunpmc8D6tjrZwDO+p5f+PvHlv454CFLfdvuHUvN/iC9dLFfy0dewAe+vY/fvk9cnZ8Rt7wk+EmtXOnoa9RtbOcUseoKNx0njUONKqEqRi2sjWCv/bObRyOyqex63TtNMZOlXzX6XTM1k9F3z97XZyalX/woktGf6fRS6jc6tZJrtPIYpqHHDZobJ+sIO7CGVUm6qSC1TSbnXN3/GCvcEd6lf/O0gkwBirtFflRUXC9n3aQmYnpOXnR2jUqFyZ80VpHuk4Bl095cWpWXvri4dPvlxiYC9aa7hqFbqKq3s7Vxp0VRxEGOgluFI4i7FMncrtZYtS3i+rcI3wHrdn9ap98svgHvhoa7UcRammj5gPnr7PjM43+juZyQX88GBi/1ZLY47SipY4YZVQnqNE3tlZdY8jvlcRN66O5ht7X7dG5VrkYwFjI3yLLab0qbxrKBMP6kQdOj8sr33OHXPvYCyV/7yNUOqTwbG0fQetiYG++rVNdaEjS6dl5ma87EMQqT+w7Lbc8dcjrPZbGo0MymY86InS9MzNXOJ1PUNl+KzwesQoLE8IuJjwtLDi69r+++3Z56w1bo9zbQr6KwXU2HLlposK9bth0UF75njvkuWPnh/5O/8KoxjeH28ZrjvVDqHY0ZNTeuf1o5ftVeX4XcWRuYStEglVe7ex2rAYEauU3g1oHSZW2FZKrBri7UOM0fg2n1bD6oFploq/hzN2wfK0xpebm3Q6krXE3uefmOiuu2bJSq9KpbhLuqlVO7Y0j9YMy+nohvzmUaBGyUjWUTXpasLzhZ2WkHzg9LiIiX996uOTvjSRWAprEdYz+99LpCCP/1F2hsZQDi6KQH3rnbfLeW7eX/F6gADWgpe/2a59+RN583VPOrpdrXbbQH3d/Xd+x2WRjscvnDDmBfM0j+2TfyYvB7hdLbnMLN24+GDsIlbkoO2XXSK0OHnmCR4VnvXfXMREReabGwpZGaaVqWkKWuTdes2nFSxPLJ4asDkOV+sZFnWRuYcu3enFqe0d30yMUmz6v6/6Ny6MINS2Yert/7ABUZSWcgWmNlpMXpuT73/4NuerhfbX+zkp+rBLMGI9S+Z5td1ZVeM3cyfMPufju4xdqXsZNarRp76q0df4nidzcwUo5dU3LgLz2J7aG/P5LXnSJiIhMzqw+pspaGi/3/fLT9k3uNmk9+k/bLrg1/LvImaC78eKLj+6PGxAs0bjDPaTZ+XnHdWP9zpDvxdLl/pmtVqAoFo6KfNct2+VXP/Vw7OCs4DLJQqaKrRzgh5Y6b1S5n5mblyvu2y2TM3MBQ2TPmr4BpMa1YS2bYSzRFmWu8lXvY2l4Rha2+hRF9Z1Oy29s1btH9++s7mQZ9ryvueyuwb/vqdvRrVg1FKRRYnc4lj9ttjKitMdb7oaVm9GvwodP1ENnJkRE5KYn/R4hA7c2V/iQZ14YPs8AACAASURBVFW9+a56FnR0vnPf/VyVgOWjhke8sTVsoa9hIKiS47I2STbI8htbK//7S9Z2F7ZKJhXsR8FQ2h5t3s+ncFZZUT+HuWVtvfm1XsvgaAG/6dHsFSt7rfGem246D8tjvekUe+zW1Myc42Utm9GgRv8JPt3UOTfR7Lh+d6iVLGt9HJybYKy85oiLXv/EAfnQHc/IFfft9nDnIeFxdJ0qVWC9N06HX3H1UYT6tI3XHGuesr7iyQtTcs0j+xzcp/Ulgtzv/meOuw3IInMLW74nHupcfbmyqRcmLQsKjXdIDvnLkxemq/29o+cvu0wKk1QudBdQ+QSAMY4nzX3pBqfu0SAplU9nb8c4uUr3WqOv9qufdLdbVFOedB4WRc+GMDrSUZWn6xhWF71o7UINPT03ejWlymOnOtEZOs2bfPe03p+s/uU2bVWoowjriF1Ol/o/hguF0aqukWI5wcp/13DM+Njk5v0t8xq/22nwFlmFi3qxYkd7gDy17dCYXLpuvTyx77T3ew1lt+hUErvdEek7TcPzBvLhP+/73yN+t7upanza/xtbrtvjkMltoSuhIf/XFTtey6Lszdc9Ke+6Zbs8O+KYSpWK3n8d/pT98f/bX3jCS3DMLWyFULWB6L4uGmqhJralPFkhoPPzhUz07Qx2vvutexyNg4jTHvcu8OowfFjKVzV7DVayY5VwPnPsvFy6br08tvdUo3v47G+Fjuaq2aD/GHFX4XR3FGH5UcNlb1WGPCbMlyZB6s8DsQcUVbl+Ay+Gou+fS/+9W02HDIwny2+lGUqYAaoubLWdGC27zV/f9axcum79iPuPeGu1dmjKrzRoUkprSlfeyGM8r8KOonA7zd22zfi+l7/USTh6tf00wkABimiIauCBZ0+IiMi9u+rtiHcZtG7bFuJzQbnWrUE+oVF7DDOirxAhmVznDXfHtxnPs4XIxPScXLpuvXxhw/OxQ6NaN8+UvVxw5uLCG7zTs+2Ocqh76lxblccxI37NZWlgYatPrVdJfXSsAvJ5XNJt2462+vs64XDxja2ULR9FuPDq5wunxof+jgbmG3xHhsXCyKMIvYRkNFJLZMPukyIyut6rwssHv1tc9OLUrNy0ufyIyd5bVL3d2ks01TrDtfsmzfIfHzi9ut6FLknUZcMW56r+eRKR0Ezovkejt+j7/qbu4HRQ+n7snucWf1ayO1thCYkdou6g3kZrNliqZb7Jc6UwSe7rCerEzYpf9RilFpJrxVGE4j/Ms4tHUa5tuKrkYsKz27b1fy8oFf2PFbveaLJxvEqYy36jv08wqk9TdgxsDqweb7v6zbxCzowvnNL1tw/sbX29uQSPlJqfL+TSdevl6kcWvr9aVt7WLK7IWGjTeq1o6hWE3dzClu9IK8T/N7aW7qUhBzRQJdgXppbPjm74QkeFcJQNwpf9/rWb3N7ckN58+ttfeEL+zw/fFzdACGZ6dl6++uRBr3VN0zcBjFZ/A7V9liZ1Y/UjH5t7/607ZPfxCxXuUf8u/QNebW8+D/s24dJ9ej+WUEH/wtag51U5cewgYayU9RULtL3/XWG6DNN2o4+lZ0W1dK2aok3mFlx168ueQ/t0UFkbrrlUpVbmq2z+qpKfrE5CSuG2za3y9npJcKr9Xo1AL28stpV379pxTCZn/R7FNrf48cb+b/X08/mGesg3tmJYNdFvKxt6M/Ltbk9zgVpU64vVzyga46so3NbBMyVHpFs0V7NS6PY3mhxR3st1m1g2j6htLcPcwpZ3dd7Ykm5nT1eiVtX4Y8lKnrc7CK9Spr7xdLs3KVyIVfaX8uliAJTVQatoD18oqzvO9SPmY/c8K398/Ra5c8cxR6EaZHEXlsLOlwtV6jt3b6HqyvwnLkwt/fvIyaIGwS4bdDfmOArbDP57f+dFa8u7W8nVfaqfZ8QAvO9nltKlGNIvqlq3WHrWusqezcKztw1i9+2sgdceWtkNv3mIKLt921H5D0O+CRk7zWLfH82k2l/tctmXbBtVPia+lse1Ti8axJ9/fafX68/ON3tjy2U6NT2ivtG9vN+hnbGJGbl03Xq5Y7vbeagQz137G1sVAhXye5Ta80YVbTdY7DxyTi5dt16ec/jtpkLc1sEpLmz1p1pZPHWr67oLW/3lqfqfV8tXH7/nOfnj67cMrb/clrH2V2Nha4C60Vq603BI3mmeGeNY2rVVc0Kvzs/q6Hbch12u8bEJrnl8G6PNNXsHPrEHebHvr1HZ93uquOK+PSKy0LH2rfYbW0l0Od3wuTO4TV3SOy4uOx+5bhn2tbDl7I2tkqOGiyE/u+WpQ3LwzESjsGgsERrD1EaVXFcUK/sPluKgbCG21aSCkk6qkmDIlx57QX74PXfIfMBjVOo8+6DfvWHTwaG/X/YYg37sav5y1K0/ef/uEX/nJu6bH81uf8FYc9jaGPhcER421B2XNjWIrjSt/MZWjWuG+hTE9sNjzq959Nyk82v26r4pcMmaZlN8LsbjTU/ysGpUPtx9fGFB4dMP7HF7z9Zvdrj5HZf3c6Wb75456m4xp0yVvkCMt4C/vvWwiIjThdWiKFrVE3WOsHQnbNz3P9Kg/PHgcyeX/n3Nmu4bWz5DVd+xxfbq3MTswJ+v/BRF/MCbW9jyHWW1rt+wY+VyEv+K+3bLL3zswUZ/6/MbW4N+3/1RhN1/Dg5R/OK10qDwHD8/KU8dOBvt/looqAvVq9QJHfJLPpvzpkcypJTmbZ/F5yJfmytXnQQviupH+Hb17yZt2iFy8Wbj6OsPaV+G/PcP3rZr4O9U6ay63THr7FLNmZvVqJ7WE9Nz8tMfuk/ue6beB9prh6hmOi5v+OkfOC7877Ik0ZBtYqn77O++ZZtcmJqtfeRIG03aiqr1isXNJrHrOY741Kdps/PZB/fKz/31N5f+t6U0+9T9e+SBZ0+IiPs+UJPPLvT+atM2rIq2xzaVuXFT+Tdm6/Kdq+ZafmNrdm5efuT9d8rXthxuHIblb2w1voQJy2WjyqKGWxprp/7yOChaQmSJ7m17x2Pe7+kpQVzNnboMXzHk3xtfL3ZHzoO6c2NLnz8IsGDtUm94Q76NOYy5hS3f+nfqjjIqE7o+tmmYD93xjOw8cs7dBStoX+gc7bDs+6dF/+6vvym/csUG+ZUrNvi7SY2OlwZGgumdlXhYXriO36BV0fRbYKPfWIq7a3z0NZtd9KN3PiN39RxhWeW7FXU03U1axl0Ujn5Due6u6NUDvtV/rLHIt8qTjt7mcGnU4/TueC/7m2PnJmXfqXF52w1bHYXMjTZHZy78nsZcqFvMKHNZtsqPahz0C9UWTNveu6o//NJmed+t291crIKl/o+9VfwlORb5Qel12fqdcvritNf7+qpf//L2ng01jq/d9rMLVf+uUQnynHfPT7o/7aJOHpiYrv89ru5RhKXf2Bry3w+emZAz4zPyvq81r0eXNtJo6vx5VKVf6ff+fm5Se1F61Dh5ubHM1qB08nYs/yIffZOi6J0Db3+9QRs/v7Dhefn3n3io/cUjWXWkfcnvd7873jY6K69hVMwWZVcbOCoY8B9D1ZEsbPWp0zisqXE0n0aN39hq/LyuX9la/EfLiZyFS/lLxFFPfXZ8odPcfWvLRyewe8VRbwzE7nvGvr9G/cmlNYqsHTmhsbpu0vGsfARS7Ssv+Pi9K49/GhXCJm3CJX29D1fp4qo9LtulXOXtyDa7llNi5dmH7UIcFP5LlB4bsbThR0n/x4elt9IcvwlQd9I5Rr+lyRvSVZ+qfGFr+M9c9l3rXKo/SF/fekS+sGFfq/tfnBp85MrA+1d/ZQuBDSrvdZLBx4Tg1GyYb4mEOM7e9d/VSptOu8W2gdcc8N++MuLo1raqhPztX3269nXnKi5sDbNx/xkREZmYqb+o1tVd2Arxxpb2/qXWzZ/V+g71Infk5PXSJhj/8dAZ8u9Nuexn9bPwVuPqRZqela0mT76qH7v6Gu+7dYdsOej+KNhQar+x1f3GVstBpbfqcEg+1Vb/mlvY8r2bdOGNrWq/u3zGs7JU9WSuYWHrTzNXSbi8A37YBXWlS+yd0FbyqZVwhqY9VpT12Z2p8lyuirbmNB4dD8XyoKViPljr6I2tgR3uET774F55y5efanz9qvcRWZkvKtX/mjNARlan1ejhuia9b1n2yvGI2FBOXZySvScueLt+qO+9NTnWy13bpyfj/cGXNlf+3aVhkeH+j6a4921pI1ak9Bpv8AZOXUXhNk1HXet3r3xCrn/ihdLwuLa0YdPhOqG/CcHm31NvciJPN73aTpjPzjWPkeVyFqagveGqJ+TLTxwIcq9Bqryp5Pwowp571lksevC5E/LLn3hIZhcLT5tNi/0/H9WHGPYj72/JOrxW2zQclE5rLE6eFG4XKLVtEPShrE3u1pXa4qK0DvD5RnYD5ha2NGn6GmaoOmx8elb+/RUbhn78tPGxAg3n55x/Y6v7T2WVQL/Yu3SWbq88nrCwU/i5YwsfOx02ET6qMxFjgsLVt5FiqFSXBQin1yrCYfiHbiEoBv/7KP2deWcTpCXXuWz9Trlpc/l3E8ra97qTR5W+saWwkm4SJoPDtBX6NzgNPFYhUFK5O7pZX97SpmkM/R+X3yv/5iMPOA1Lr95w1WlvD52dWPybar8/NjH42K2yLWSuNak/XJbHWt+9TeCFLQ19MR80Hg9Z523AplzX9aOO475n13F5242r3yryvZFzeWOxXdpyZ51FijJVv+npyt07j8tbbwx/LPTy8dXlceV+nNcsfd56w1bZenBMjp2bchyeam1JNx5OX5yW1378waU5D5fivE3fLD3K3qzUuO61sk/q4HqpdkJ6lD1iNxvUPjmi5n2G/d0wy29aDlZ1IS5UCrOw1aeQ0Y359sNj8vrPPipTs3PLr8LXTC0XuzcOnhmXsfHRZz9v2n9Gthw4K5d/w+3HE7VMkHQLf5XJ1vJrtQ/P8GvHja/l89FXarrbx4dQx3No9ztXPrH08WqX2cbn4uryhuV65wNrqUdUcZjodQZcre+19P+G29P3RoOv4xdcP2279qX3TYt6b3ilwFoZH9ZWD/qv9p5t+M96238TeTBg3aZCw8d883XV30wVEfmlv6n/PQNXLyytWEiu9Xejf3tuvpBdR/19h7hs0G9BqqVoVP3g4xiuKmbm/I916pw88/+z997xdhz13f9nblfv7rZkjAu2wUBs2oPpkISS8uR5hbySJ4Q0nhTSSMGBQCj5OSF0QgfTwdiYYoxs2diWbEu2ZUlWsXqX7lW7ur2Xc878/jhn98zuzu7ObDlF/rxfL+mec3Z3Znb6zLdMLTBdAydJc73X10lolHErXhM/Oc5mZy025euTn5V+38ijRz7pK3nGTPM4qsdTmL8DANz7zKnAb4F4TQRblb/3bD+JXSdH8PX1R8wSYEFe3UJWwarpi7fYyqYRpUm733oz6Xwt7JlaWCnVWkAYdEUY/ZItWVls5bQJEraPqL5X2jzOot02nWAr77ovpYzM2Pf9dCc2HOzH7pMjVY3u7GI3vvOVH1uLV39ibbrYEiY8qSDP/Z4s2mC4GYVzruN0NEldSdaCeR1t9U5CQ/DUkQEA+gGwCddvzxrSLlzymHD5BY5pibQUjHn9qdkiXu+zaMhtkplROxEx2lMS0XOF8rPVz/7uVyssacQ23ohpygkbIab626GzYyjkvGFZKkn8ze1bsaVy/oUpUkocODNa7Q807c52Y6jeijDPNtTySbT5a1i+/TEugfTtwG5zLAk2WuB+PvfQAfzaZx7D7pPmwq08lOJq0bcnt54/tzr5qLpYb6FCrZZhWUbTaPtsgNnZ0UnDJGWS9AvfeeIovvLIIffZpnSzZkBVQd1cwT3reVPSbruqlO8oZZit7UzcYpakdC3Fg2F55wrO97acD5nKInQjAWbCsGt1xtZQjDFEFD2D3jL1zknTd8JprEMblcAxCTHCQKevTDtHyWuOE1ZNG63omk6wlTdSWjSwpGaDGXViaTqpNCStw3n5Fw51FZVxfM1OlGCr3nPPFQs63c+N1knWg8jFWtSivQ5558ZpWYeapZxrsyGVwzMZJzxusygqtoLB7kPS1AYVJ7J9bxthR9SzJvOKJmkSxjgL5nqPL6Z4iyh64eb80jc2g9d/8hF8/P591vHZ5Ev/+Azu2X4S/++7m43ud9J85+ZuvPHTj2LDwT6z5865WljFRhDdSNQ7XVFrnCiBqVUcymeboOLyZntP2a3g6RH9Zps+TPMMN72zbyx7t08kmrQuZLPaiPackadJQJz3Fev4Mg3NnkKx5HELl0f/VdUer/fb2lPv/jwM/9ifRGj4wbt34T/v21sV/DTJ3M8Wm/fLq7jV8krSV5mcT6fGYXI+oAQwaHhmllO/4lzxJSHzo08yLkQ1fXm7InSe/8aGI6nDcJCyWjeyyJoswiiWJI73T2QQUjbYGnU4eVwr5RfTelWL5GSpXEXBlgbT7DV1vRU0R7SLp9EwqYCRt2Q8QoRq1DdIBjdIMs5JjYhzFV1ZmZReWBHXYm3RjOuXrCa/WTWtRtKytYpLNlB/m1E64jQxJSzzuAHyZ6ZQwpmRKatn0iTbXfg0wLv7iUqTyYLEP+94smJtm1UabO6JYlfFUsX0HINGLCs/ThKbIa1xzBi4Yfa4HMpDCcI0nDp1YlHjdNy8NslZyDZvabogf2sCN4+2JPbCkW0yGoDwClPdPIp/6yP943j/T5/J1NuFLqgbPvJAZuEDAGS2G0Wu23/DMLd1D3nOMc2j38jDYqtWnAvjVhxO+6qJxVYd89Pk7ZIqfxqHa4m/DzQtosnZoGDLxt2a38rNiT8PwVZeRKU0aXk0g1Wjdk2Uot35wytl0JF/4oF9eNXH16JnsHGEWypx9cNR1ki7V5vX+BJWTdX0JlUGykpBDmhGwVYNBjAjwQ2UAngWTFJUkr5uXn13JtoC53AZOtluYjVRLzwajXVMRxy1ctlSLMW7OdM+V4eKnHTRWq9yzqMbSvsuubgizHgxlfWE3mZBZBVuJqGoZRKmOKH/XfVD7XVFaKIQkm+r+Oe7tuOltz5ktJl+rhJdj5VxKEaY4P9pe/cQHth1OlXassRJn7Nojhr/jd2ppUxT42P3hllYdPzLXdtj72kUV3F5JiPtO4Yq9SQ5CzmBEKwJ9qZC8fZ16Qu5WJL497t3onsg3QbTL3acTJ2WMEze8gcbj+P7G49j32kzpQATaqVgmIeSlGmYsxHnsWRF1Z1Z9mHnTd51QBp2SnkqKlTP2GrijjGCKDdjYffm5bVIl54o3LZjGYcJJi7X/VUijxpSF3fZNvMG5d4Wn2Av6+4hr+4mSwWzLMJYf6DslaJ/zMxiMG/8rxTXRlvcMS3lXDjV05rwYtKTRdlVx8T07bb5BFs5E6d5LjSfk04O6j3cJ9bu8z03MjVb142ycI36Bpnx1jkZzsQy0hVhjvE3SCk0FaqZt4NJGdXlHDV3AWP5WJ1WpI1cH7PMkszzN6KAZawzwvzwx5p1GwgLTsJgwqekziRZeefg/RXBS8HEB0mFZtw4Skp1A8+3aaEpmTs2dQd+e9d3t+SRrFQ42rAmbmSAxu4f09IoAiKV+3edib1Hej431jv4tbDrFX8YSfQPbRSEXK33uq/oUrTdjKvU9p4hfPuJY/i7H25NFc67f5Dued1ruR5TLMo4y735Wgi2TM7/zCSeUOUef3pyTEOGoeclg0kTbC0FQ1nWmWq/eG7id0VoUg8zd4+XeO/Re8ZWdBx216PS5N+6zlVRpsHmSVFcvmxe5PVGaEP+upL1XDqLcTHOAjDLJM8USvjg3TvRH+FiOphn0WHWol1448vI1bIaZtIgQ/YRf7ylx1phlIItHxLS2LQ9qcZQWMF3tbfaBVQ3vC/8gg89gD+8bWPCp7NIjT7ERtnDqPcA61Q3/4ZvrfKnUcohC/J+F6dv0G2smEQdtqmf68HuThwWk2UdB86M4gtrD2aUKjMapW7msSlWi1fzHiBbgwhrSNwk09aNnMkkN/f+xeKg62cz/vzRnU/11UcP1yg1Xoytqyr3OQdzP7y31/A5bwSlksTH1uzFyZADwetJs2i2RsZp0FPHWQ/mjZFmd+WuzUcH8N0njqaKz2YzN86dkv+gehOsvBucA31p1uO4KzxKH1TmOGmy2UjLcv5cG4FTPuH5w3Xc3GadHrP7HbdNdmE3Ak2YZGuc/raJvMwlwmhOnVOBq3HarCH9Z/lkWkQR7xpwP+eO3Y1fSYzmaZZWczdfuRwA8MLLFidOV5aMTM0auwRUjUCS7PkEz/PLQrBV/luL6rRm12l854lj+I/Ve0LvCQp9o/F7F/jqo4ew88RwbFqC559l2+G4e3wh+arGl9SRnXO/f7z4xx9tt1YYbTrBVlTHMTFTyCQO0wZmesaWnzwmtll0LOZxBX/b6DtfQrdQym1TLYuFWA2mmvXeTKyLNQ+87WlipqCtq+ov9c6nKPJOWtVvfLjGpUB4X1evMgYSWGz5vv/Olx7Hx+/fhymNH+9GJyst3CwPra9lO4qLK67NNzKhY4ME7t5m7irJrGnmmys2Lkgc6q2YUVOk9iO+sPZQzZPiT0fSxZrfzYlpfA7PnBjGl9YdSm19kSWNaHmVL1LzyeLpjLLLpB//P19+Ah+4e1c2EbrxRlyLfdr+LGSb8x7Sts8syaJdnEstK6pIbKbKWSoe1USw5f6XaYiBucDbPq8/Ny6YW9m/dBKBdRw1G1Zs5OZNOtbV0hVhPXIoSZxZKzAmrRrqPgMQXUbxbsh8CntR9/rMMnT3ZuX9KWlenx6ewqd+uT/3dhel9Bhw1ViDuUXf2DRe8KEH8HkL5WL3DOUM4s8kDFeYHpZh2ZfpbDG8vgaqUEyd8guFbr13r9HZrP5gM99i9+3hB65nEEeWng+aTrAVxv4zo7j2g/fjp1t7UoUT54pQpZF8POsm6XmlK2mweUxEgfD0NEK5AA2QDovDkvPm2g/ej+88cazeyTBiplCq+aLCPTyyFL6dvOvkCK794P2495lTgWv1EGxllUXTDXruT03qQB5nbGUcXlwSoxc0+ZFX+cSdzSIh8diBs5FhRC1e4u7Pg6oVWv3HgkbmXMgdZwTxy7V0C4eo93XmDTPF5s+VWOFGTVJhz7OhuSZ+x5jnkqzTbFwRngtlYztONQu6N3Fer14WW7U7Yyv7eAIbaGHKd74My+OVa+22KQ/ySrorbI+7L8cNUacfaQB5fy5IXybXY/2T2BWhs89QeTyqz7eNwaR/87ddtY687D8fsowxHpt3+Jvbn8bnHjoQsEY12XA36osMGkTWfZrJ+HV6eAoAcN9Ovds3nYzGTWcG6c1i3uHUvXDBVna0JNhXjdueS7pH3taabLyNyqZSSQaEdiYWW1FEKqg5fRGC8dpyzgi2dlc6obV7ozea4pCwsNhytQ7sKmEebS7JZDlpP5JWSyRrojYeG4EkC6kscfLdyr1KhhzuG/d8v29nUCCj0giaryNTs7jq3+7Dh37u1TzO3K9wSWrNePWC6vKPjmnyun1B11JhGzL5uiJ0tL4sn2uM5pkJqd8lh7zIuq5GlW+8xVZ8+I1aH0LHF4P0qn1+I7yef0GbdzzNhpotjVofbWm1LItz5b3PJbz1MsFcP8fep96CEFdrOGyTXbnTOEyLV2qUdYY1UvvxnCByrhJTX/KmJmdsRXh8SBZeyuezSYYHm7ONbMM8V6hnu66lxZYp39xwBD2DE5mGaaIs5gpwsj5jK+VenJPmKEWO2LWdxf3+fHD7QiVfBsZnoiM0RQnTxo32ZMVjTCN5PKnF+Z23/GRHJS4z1FO1k2SV/52zWJM6YYQ5qciyTFtcJfSImwKKA9EJqMoU7OhqS3aMUVR+vPNbm3Dl++8zSk8W+eoEcWZk2o03KU0n2IoTYqQdOJIcKNsIGwFRk+V6H1jpv//eZ05j18l4v6F5pUcbhistzo/HD/XnGHo8ke5Vcpx8PrrfK2zWaow3QBtS+dh9ewEA387Zuuw577sX/3jndve7OuEL64taIixJbFzoZEWcmXLEk5mnJU9MDsVNH0dyQs9XSxGmN5wIdxUIr6+VG5qW0DMcEd9vqW4ETDa0vrjuUGauOHQksdhqtL45T5x8qfdmfZbYuiJshsaqavflEa4xCTrXgNsZS03gepZOVNzpN7+TrWFiN4VyXqfptM7rhc0r/mTriepzDaaAkSuVF7TxbpDlOUG1mKI3WhnmMZ4283mhVbdL5y5V64n84zKpA31j0/jwPbvxR994Kps4LVqZIzjKfi8uIT7BUuTmvCWRc4TsoolHnTNlsvEeH4hRNA3aX+08UTYOMa2jWVt5Z3LGVslpZ/m5zHMwsdjy15m4V2xx56rSai+vvc1nsZXBm/r3baNQY0vax2Wp8NN0gq0wslpcSNicsVV9JuyaNo4Q7Y00xZqkTiSNL239e+roAN7yuXi/oaak0aivBbVysRbXodTLYstPXDobYbI/MaM/5ymPHFQ3GJzFWpQrwijXB3mW8UyhhK89ejhgJuzEmNUGUqO025qSQaW/8v33es7BqUU+uhvMMkZTT1Nbg25QGqvg4+qz7WTe3zR17/vMiWF854mjVuFa4U7G84viXKCRssfmDAMAWNDVVnmu/N1vsRU3/ppU6wZSwq4rSbIhSb+nO7M2TZxJn89zTFHDtsnXuCQlPQvZFJNzShqZf/rRdkwpa5Rzaf4V9S52GylZnrGVfwZLmW19l76/8fHbjVlJEE08l2nUJOdh5dco3aKzUTwypT+f2hr3/eLHlyzPj9GFa4vrGabS7ReiJFuWUURuyPvy4VxSIEtCmEJ9o7QZleC8VVEEzCD8LISrtRSmuxZb8dW9+j0mTHf/T9q5ww70Kxk3q/hz9rKIJIMwKpxzgq0sfGuaFpIbVQN0zo1kNht2TzMs/PJIoY0ZdB6o5zap1GsjOVaw1QDVpG7nkRksWUNV3wAAIABJREFU1g6cGQWgb2N5nrF12/oj+P/u3YPv+qzY/IPewISZK4GwQT/veplL9cqovli5QPLdXJLA3dtOVq9nnI9ChE9w/vaHW3Hzf68NfTbXDdHK3ytWzMs03FgBgOVzpou4qVm9UN0W7Rhc+WvTv9Va4aaeqMlttEW3cXJ895lYbDXYq9aNmmw6J3mmgcun3mlz4t9XmRf5qZXFViOQNC2jU7PZJqTORCqWOn8t8uo/792TJjkeaiWIybIvsxVsnxz2rnnzFYg3UAMMIXROmHe8MdfVrHvdJ9fhY2v2ZhZ3Lc+7MSGvvDbZBnT2Xnb0DGUad3or6TKRm/MxOZckDX6hdC6u9pQgk6yFQ61tIuqzUV+U4IytWu7VmVtspXN36380i3eMG1uzHCqqnpPCAw28Y0z86lzVbo2eUMBt2ezC9vCz2C/Nso43nWArLP90vlqThm9usZVME7BxztiqPjNo4dfW2hVh5fZvPX7U6jnj8Bs0LIe6CUkqOPUtypqnllNP28Pr60FYVuVdlM4eZDFi0rD/zFg5LZpcy1Ow5Wx+TMxEa7yNTKbbJMk7j22DN7k/bZLzaH9Z52NUGo/1R/utr0X7zktxIqz/tlWAaYT9F0fIUWuXpQ2yt+EhKgcaoaz8mM67nPrq3G27sdSArx4gyeZ0kvvzIMlGrLcPSrJJk44opZOwevnNDUew6pbVxoL6pGUTf26B2X2NZjFcL7LIh8YZ8zT1tZIom3XZQ3uD59kmpVbrwXpm/T/csd3zPRdXhBGeKxKHWaOVcCMK4w6fHY+/yYLqeTf552lD9N1Rgq3KtcysxUwijUAYbMq7MSSYY4V6uXDiTxh2Ukza9c4Tw9h4OP64EBOlCVsasDuIxXN+dAbpzyIMZ/+rFtnZUpGeZCmAUueqNhZstpZhtsSF5/W2kKy/z9IdatMJtsKodpjpnRGaVgpX68BykygPtx5pJ8tH+s0nNY3WCafdeMybeifDaRE2pq3Pduq18FBdEcaiuSVPwVZVYUnfx7qWgZoknBmZwoO7z2jDc5+v/I3ry2748AN47107YlLbnCSfGAefzHIzJi15LKD85LV8Dl+k2S2n663gAKhtzPyZLPrCBnh1F5Pzeu595lRNxu3l8zsBAM+/eFH8zYYJ8t/WajnLf+rIAPaHWL80UjnmQS1eL7WQqY5lEBW3/9qXHzkEABg0tODOKl4/eZ/FYxtunvu8STd41Xc4F9p4lJKL8371Go9rJtjKMJpqvUpYv7JLikszuzPzb/Cfi2SlbB5GoVibIx7CqK6H4+911uXtrdlmRtKqn8RzQ0QqPN/8YXrObwxswOfXdtWcNimjt/7Perz9q08qz/vPLcqWWvZaVq6dI9a7KmmPvQh6nMlinVkRbIW9Q4ZjhTPHKEbOTe0kTlWBc7r92syHxJiuPIt27A8hTVmdM4Ktqr/blMFI8wyNOmMrWeTJH52Nal0G1FqDu1Gpp+VE3gc4N0oZN6L2vh/TwT1rqib6EnG1QHc1bHKQhSaiDOljTQak//3Fx/Fn39msDS8QT0w6hidnccfm7pi7mou01ka6vHzqyEAmYWeBrkyzakth9TItsRbZhslvII/FivC5ARLTwHzql/txeniqZvHN62wNvWa7pehXnDLRmFbb4r/9bCfe9OlHDWNrLDYc7Iu8fuX582uUkmzxCB7ql4xcSazUEXdDDpYd3vilGk0s9R+Ng2Q9HNiG95tf2IA/980P08Ufn4B6LYdqNfTmsVZJnPZ8JFvloHMR4GXL9KzvXOJztRPXkFd/l/RcwKzTY2IR7PRHKyqKTFmRtBo5aTaRDdrGIRG+FnPHSr8rwhwqiZrubOR35UCi5tPW1m2VVPrrTmCPpYb9hWlchWLVq1DebgRN9+SrYeSfYa0GVo+BvbGYMFWBs5UlWEKBsW2zCz9mwTIgbRh+QWfysJpOsBX2rk5BZnFonLmLoXSagFl25nHuwXSoybax9DB5XxnyORcyFELkIlCquyvCimZBlCvCOq+21U6tVu4goqhXmakWFXFJ0A2oabVoIuMLb2gAorXATlicM9doiz41PePTBay6ZTVW7zjluSdtfUmrSVSLLEvTR9iOGY1EWNmYpjdUmFSHF050xlaCdNZ7PIki0vpDKZSZQi00gisLW5P24Qqs4hQevNfbfJPivaf11ljNiD8n/uDrGwP3fP2xw+7nRXPac05RPIFuwKhvrO/4Uk2HLuzoZ5LM5/otXKPHJaCqWBC8r3d0Cj/a3J0qf+wttvLrHJO+hlq/spx/mb7q9u4h/NJn0Z8XrqJAk1ls2aY3U4GPu4GZ8PnMUlIlifV5HHlViVmfBMFGWSXX/iLHSaijSJuXK8JpxcVtPVqyvz1G1Z28vOUkUVY+MTTpHmdgkq7Y+WZgPhMfpluna9QHJzqqxT+Prrg+mClmcwZypEvDBloM/95Xn8C7f/B04PdCqeqzJIv0RpWRafiuG/borapM8Cqhh8Rn2TbUvt6mbeddXWzO2RMCOD08ZeTWU8X/urTYQnaHEErYT5Q+8ovdVvfnMc5PzKTrbG0G3obwZ6wQlh6bdtEIA0leaXBdETaMxVZ0A6jVpuiBM6M4EOJyqV7uLZ1FwIfv2YX//cXHI+PWFWctyjhool+O02Su6nVL4FsYBD40Ho6A7tMP7s8lfJvBXL3VZOL++197Eu//6TNJkgUg3QK7Gd3FxJ3hEPZK/myqpd/vOFwhW329uDQsXsuY2pWYSUym6ZHN0JGmxKY7+Y/Ve4yfsxdS+J832ChKonAl9Z9rjS7utJve1XC8IRztM3OPHhdv1Lj1H7/Yg3++awcOnR0ziisu/t/+4gZ8NGY92IgyfzXrH9h9un4JyYiwMj89PIWnjw8CqN8YWKtlWB6CreTP5yeUU/vT/WdGseqW1TicsD3nVTS1VpTMy4uBDXla46jhA/VZX9jEWMpojEyTBodX//da93MeXnyiQqylbp9a7bLYF1nQ1QYAGIhQurGZ26l3xs5LjUPNnicPD+AXPkVeACiWSqnmfv5nMnF5X/lbizG2xWAt7a8PcelSvbukOS4gv71kfWfuV4x606cfwXvu3B55ny6U8G92nDOCrawGcinNG1jSuLKsdHPayy5sJjWCrbhoPBujKQ6qqzeZahhmF5SL6eQh72z1Cy/rVY55z7UfP9SHsel4C8Y3fvpRvDHE5VLdZICVzFm37yxGY95Bl8SwCVwmiwvDQVlNwnTB2y+ZHR3WYB2MQmuL/gy0tG0pa1eEujHs8UP9+P7G46niSYoue5JYLkSFbqvUYjrOh2t/2W7W1L9em2iZkTK1df9hIBAxTI+JAsTavb0NUR9rTd5ji9H45rvHpOs3Fbj2j027G/ee5+OjaDhUZb2oPNpzaiQynChXsM5ZcmlcuatnyWw9PoTb1h+JTk8jSrYUhidnje9t9D7klM+d7Gs/sQ5bjw8BqN+Zw8kttuzu331qOFE8eWD7xib99O5Ku1fz5WdbTwAA7tuZTDibV30OhFqJp1GUTfPAqef5nX3r3UyNY0dPPu0h1mU58jsGQn3vjUf6MTIV33erXl1M6p96xw8M1o82rtnyriP+eMLQpTlsPTk2nc6IoMGH/9B67K8qs0Wll86gekd70jCj5CqR6p/Isnt3BFv+ecR0oYifbz+p35OPib9FWZ+n8aJm+qTpvpOtQuDIVAIPcoF1a/LCajrBVrhboEoHmVawBWm8qR21kaZWmDynLi0ZbVTZWWzZkffiJ0uz0zxSahpmXvlU9accHr5Js1mz8xRu/u+HUx/aqmujMua6KYPjM/j9r23EX38/aDptQ70W7HaHfAbTWBOLrRj/z2pf1DsyHXrNn9JanUVkrT2qpNTxq5yny8ck2GoG1ZpG3P+KS1PcCC5l6CUtjVQmJSmx88QwXvzRX6J/bDr+gYQ4r9zom7kOtS4iV+MxalHn3GMaZqAvCD75x9/ahHufUTb/DAN3wsrC5XcmZFxgaQVfJvPwJH2h+kjU87/1xQ0BS+8siN6sClGmcTf8DBUI7JMFALj9qejzNk3OQAGSj1GKXMuIRjjzMopWi8bdiOO6yq6TXqHnpOK+rJbKHV6Ly9rE+yffyvDMMtflVG2EciZzpcNnxythV2+uatEnS2dec7RaWqpExZslvaNT2H0yXKnAKZe8+jvTMdEhyzP8dHFGtY04F2mJ06DkwtH+Cet9jyzmK/7LJu9YY0+EBoItkzDKf3UCi2pA8eHY1lub+7IgdI/d93vWe03ZnLEV3c7yOXfSG+bPt53E396+FT/cdDxQH+Lid8cvaXlcgN/aKeMK45R1a4jEyFOnI94xSmYSdEVomrogTSfYCqNqsZV+EDU+eC1hVHEHK9qFVW0IKjtPDGM0Vnuj+pCVP88GW82EpcbKrVcGHV73wAS6ByYCv5t2UBL5anOkHYje99Od6B6YNNLoTFNHjvQF89AUJ9ZH9p9NHAYQMTBmWPW1WkIWnYr6tHOOSp6L9fB2Vv5bPXOweqffYstsAlkfQbgJzqZP1pO6tO0+SrjYCNtotbDC0zWdqdnwRUhcPYs7Q7MkpdV7NcKwqVpVvv9nOzEwPoP1B/tyjzfJu9+z/SRe+4l1qfvyPNCN82kwyR5bC8M4odmZkSn9hQhKvr6+XiTtT/JugyZjl/8ekzSZln33gP4sy+zeu3admFrFjpw1c0uoDafyN054nPbsI9M2kWfLSVrO6nymNeEctJEweYN6jcdJXSDWM6+dvBqcMLfm8zyfo3W7c+ex/nF8fu1Bz2+25LW3UWhQ3882rzs+XcCOniH3++s/8Qje/LnHQu933e/llKdqf10PDwROjCbdZW4Kp75g46yX/ZhZbFm23ahrzvzRZ+WW93Qyrvnp0hwmLJicDbdGscmpms6gM8jgoMVWyc2TRPNx3yNR6xHT0Kt9jn1ybOkenPDE6dA3VnZVeXpkyl7oqxiq2PRpSbsX0/MPHUXutha9yMjUejaqnmS5R3TuCLYqf7PYIDStT42wYejgnzy89X/W490/2Br5zEyh+oyV2WNEvMoF4/DS0iiCtpv/ey1uVvwXO9RfK6NcU585EW6Kn/VGVVR1iovJdnKmkkVdeM8d2/DQ3t7U4cShS2pUMQQ6fuVrS0u0JZHjsjQN7gZOIF3w/K6mYGrWO6MsGQyAebfmNC5owqwfs1q3pNUad8hjoZemizDavM2h5N8XcaaYaZmF3WevhexbKNk9bo0uP6uakhLbu4cqn2PCqdPw+je3b8WRvnH80Teewqlh/YZ9lkzNFjFTMNuA+uGmcJcsf3jbRuu4o9rr8QFHM738Pa44/Nez7AucOhW1IPrwPbvwmZzOIMybtFmVl+KGd85t/bgVv9x9JjwdmrirAtS0mRd+Kc4tcxRxCgqAs5GQLHxnPmFq6NSIBltqnWyxsNgKq8u11shPQr3c8T4b3QAb76m4G3v2YX/vyWPW8QXCSvZYLP6N9fyrgCNszy7Ed//gafzG5ze4bv7j+uS867laR2ziyrr/NZmXVe/JNk/SrjtNnt/eHe3CMcna0+8S3daNvC1xa36vImjIOUKVW9K4LfaEl0kotcNfrsVStTZn0dT/5vbw/WrT8F2LrbDczTDT/+WuHZ44tdFZxucKfKWdK8IkynKAeV84W/HSFSLX8p53aBZkAH+an1UWW6Hv6mrNpQzfRrCV8oytLDpz3Way6QLzw/fscj9buSL0TCgM7jcOORlh4TfKwGGajrysGpx6+s0NRzMJzySVUZ29VoiW0atnIWD4ScVPuw5/GaURCOqSGhVaoONXQnC0bMMsL7PI3qpllv667vyead9GsfQMgPqN/rwXfbbhe9Jc+Zz1+Qy21Wi2GC4wBOq7oaSL2iQ5/71mX+TBvKHxufUymInbuocCvznEWmy54We0kGmADS2dX/BGPdNO3V/1C8jz4L0/3uH5HpUrrWEzfACPHbC3gIuqGrbjtqtFadFXGc9RYsaA2WIJ39xwFJ958IBhiOmwtwSIvp7WxayRa58kAUeMm7bPx6Fz2dSYPYQZujWSn/K6L9lbOpvWptqvpvclIWlfrlb79tbmd0VotkbJPRmR8cbVt9PDU4msahsR06xuEdWNvTgcZT2nz1U3nJMKVfKqE0FFuAZtOBFsrcylTZV/ct/38cxhbZ7LPv64cPM6zy9oVWT3fFw93Hd61NqF473PnDZ3BZdjJVGHWRtXhKHnM1V+9++xqK7cTfJfN7rG93e16y/CkuLvwwolaaxslzpNlRimC8VQxfeewQmMVs52qmX3GulCMcTqLwxVscPGyDfpuGU60yvECnOVvjhhWvxt9Fl1xlYYrouUlMIiCWlsNl5vdyzlRJT/qJ2taSXfe3q0+oxVy1Arcf0naFkkIc/XsHUh1KjY1PZ7nzmVWzrCKBRL+NNvb6ppnGnqv60rwijhRWuMxVYmbaTy19/H+t9DTcK0zxWcycZL3hvtiQdMWX02a9cStkk6OeS1YPE/novFVoqx1XR8uWf7ycRx6IiakJlmUdht1gJSu9tzwXVFqExx4t102Kc8i+rXpjj0zqM++4PcejxcCOqnPcaqwXjM9/3VsXBOeyVMoyAz9VXux3mvsNc/1u910Tg5U8SRvuRu5MLTkfC5mOvFlC6jjBS9EkQRZelcy35Fa7GV4BntfXm9iWKlGoatxdaWY4P4s29vRrFUdRljuhxsgFVjADVvzl/QZf5cQ4xqQTra4rc26iVc8CsehPGy/3wIL731ocBz9cY2HULAuJNSXSXH0eK26/JfdU6eOK9yyuNGO5M3Cbb9VtV6Ih90Coe1xB9lVF+Y2xlbKcOLW5eZnL/rb2ufe+iA77r6pfyn2s7txs6kxL2nbizwr3edIPz3qn20LQ3SpXsIFez5fo4XdiSLJyruD/18N379s48F9j8A4NO/jFemyyO7k7jNDUNtF1ZnbCWsSKbtzpGJhAqsDQTDtgT6V4t3PGcEW3ELbvNwqg22LSawpFGFnrGVoD44QR08O+Z23kk2XZNabNWrX/af3aOjUQaNeqfDpJ5mPa/4ux9uq1lcDqeGp7CjJ9ps3pbfuOEiz/ckZdk7MoWhiaAliq6ZWllsKd+driq87WdXCf39V3AjtfrDTMCyqPq5f2wGgzoLnZzbS5oNDd0iGshyMDcLx5/n/neaLWSfiUKYFY1eIy3r1Jjht2xTia0HMe6UJKT2Wtg5N0kPNM+S6pmc1bQc689D8JD+XVXhUZZ5Fzb/avXN96JeoTXGqsF6DhYR2ZuuPb98i611UoiGaRriFci8cf3F97bgtZ9Y1zCbsmE4ZW/rZia4+RH/fFpXhEnIdXyKCbokJc6MTGEk9sxfL1ltdrlWIBH3SNiVy199fwse3HMGvaNTStM1PGOrERQifXjdepk/NzXTmGcHOVy0KFxIV68+ybXYqkvsyVCzynZsK8u1zJ5RXSXHpqny12m3qvDIJLafPN2Dz/osi9MMldOFIo7368/e9CtM2FQ9m3o6NDGDP/nWJvSP2Xs+yBon2f48PXx2LBPFQK+yR3aby7aY1O285v5pQ43d98tgqPKUU+BaJZqch8S4aZ1eYcf7o6vU6hfwePqdZCUS91Qth6pw4YX3QlnYIbXX8uLpY4MAoJ1LmhxzkQdRfVnUnl1BszehWmwl3ZPXfQ/DdC7qrIvC90Ls4w6EEbGPaEvTCbbiMjbtokHKqnTSv9ERQLlsNbC6E9vsWt/7f7oTX3rkEIBkC+ekZ2yFxZVFRY9i89HBkNjCUlE/TMsjr844L5/SSdF7Isz+5adm44WfcWSRdy+59SG88CO/xOlhr1uRqDNwdPjzXa1XTl8V2h4zyN7wMNzeN3CfX6tHTd/f3L4VL/roL93vJi6DsiDNGiPUYiuHNmGSDjd6X/z/sXq3UTjvuXMb7t52Al999FDsvaZJ1GVFnprd3trnJWqj2rhfNtRgi6MB5Fouato/9/DByL7Sqxlbu5fwWmzlH5+/DUbV2daYBmuroR11e9U9Ezx/dejKJ8u8i9Ow9Uf/yP6zAHI8PF2bhqiFpv6aM36mTaeJNVaSs/aiyrxRxCShs3BZ1mp+/ScfiX4+kzmKb75RkuipHPIdldG2GrLOnkSrEO5zxmdsGcdiT9I8VOu9zYbK398RfY5zvXDqQVRzTmmcmZiq9YZdYdVz+qCOhbZdpBDCeqPNyPLVd48qPDJpy++5czs+7TsLMs089Z9+tAOv+vhaTM4E51K1Gv++v/E4Ht7biwcq5yTmcXaRab11hDmqUOdg7xhe98lH8NmH0rsqTnquS2ZTWH84keNL7C3JkpDyZeIEbib1J269p1XgrQSrVWzNgVhXhEp6487YagQFxTwJm9v75wWFYg1dERpEoCY7qzW7CdGuCP3fq7/8x+o9gfudtV6pJK3qWUCx2dTrnGH4rsVWWPwZKyqUv3uv28h2mk6wFUZWFfZ/Hj7gboa1t0Znj+orPVgI2aQnDvW9HWl2krywEmxJ/edaIjxCxezC1Zm4psU0eXm79YjSXrQhrQuPWmmsPlrZVEuDP6Vp3vxl/+k1Wddlo5UrQuVz3MZcFnOxuMmC7owtv8WMSdXJ20VMmsWAk49Bi61sME2aXxDhf6cNB6vn/EQF+ZOnT+DvfrgNt9671zSJidDVy1oISWYiLHvj2oTbEkPus019YJJbh7HTORrKv0gxHf9N0+zclqaMVcWiWriN8p99E5UlcUpPpoIt1y2ViRsbo/CCn43OfbJUvgk7JygsFNPNcuvNXs3tSca6NtdiK91ut5H2doL0qeEmaQqpm4+zgZEi7rOj8W6NVJJsyvrT9+VHD+HJwwPlaxFlI6Xe+jaMqoBXuHXb+OysRpFEKqjtzqav3XhkICS88t96Gae5409Emed17k0cebtoyxvbsbjF0NIfSHauqXNrwXPGVvj9o1OzeM+deo8iaarEI/t6AejPoApooyePpu6Yjl+6tZKj3Ln5qL7fsMFzxlYdMjTsjGgdeQk2bULtHZkKzG/i+sCk/bcarM5FqDO2R51nniXxrgiDv/WNTXvW2VVliah5hHma1h8469ahvOuvR+ijRLbl2CA+cf8+z71h8xi/rKRYkso6zz5NNs8Y7Y16zlRLEY4lNop06ledi3bVo4r6DmdGpvBn394c6vXA/76mFrume7EF12IrZA9Q/RypeRlxKbBBYpQ0LeeMYCsrX61PHu43tthSr/o7u6gK41zKQptGNzDlbrFVL2mWgpp3Yamx6zjLTBdKONg7ljhdadKRm8VWJa9uunwpAOAFlywK3mNQFXWCiyTEufhMSgN6eAmgmh9rBVsRz0ZtjOtcjKntNMtFvL9vq7qn8n4HgFm/AChqEuDekzKBMaQJ30m/Pz/T9om2Vffvf7jNWMGgEfpr0+ElTVp17T9Smyp2URftwkpKaT6hM7heC5yxIOlBrbV8g6j5VR74h6WoxXDcGKZzMxFF1OudGZmq3GMgoNL8lmXeuRsTlu60azkHitx4CPk9K4stM0sD31rBIFxPX1/HbVFdzGHpccqhln2LPy5HqAVE162StGsnTj0pSRnbJvyYCMDGpwv415/ssHbfmDQPPa4ILdpArFeTOtOI8yJXy90y+npOH9S4bccTAWGc167Gukk/Cm//4nEJFvH8z7efxE+e1m+o5yF/mJotYnS64PnNpu7ZKILmuQbWrTGjqLpuU8oF2ezTlcOvfo4bE/OwskmiCJF1Gw5snIfcN10o4iW3PoT3/niH5/e4aaouveO+uqx9LiSN4e+ffcVV9whjLbY0dfRPvrUZ7/ruFiWM8t+shJR3bu7xzE+i05dJlAC86f+dLz2Oz6896Lke1t/orIIaYEnr4tkTDklYHv27jaAzVplWdUWo3PzSWx/Cg3vO4OuPHnZ/GxyfcY/k8b+vSRtV44vDEYiHJX90qhpf0joRlGslL6wmFGxFv6yx1lxE6LOmZ2wpl4sliUKxhOHJ8kIkzlWNNu6QVxuIMNfVaQYn2cS2OqjO+rnsexMTi62ksZ7I2GpL18lqf8s01iBOR6mrmTYdftrBoUXTrrIYIP0Dchb56e9P0i6GJ1QNIMsUBtta9XuLCLunjE6L0Jbwdha+ST5bCD9jKzQe65TZYb2hoPlcbw28Az7he3jNSJafuolRuqE1v1KN0g6PGp9MLbZMx5e4elWvw+p1BF12Rdwb8Vx4+OW/Exq3PKao5VkLt1FBi63wd22LsebP0hXhrffuxV1beoxakC7NmQq2Kn/D5tmFkIIy7S+zSGtkGCGXnLl+2gOxzc7Ysg836pH6zMCVsGP6x1r2e0nzqVSSlnPg6ma6X7EnDpNx9DtPHMPtT3Xjy+viXQRngVpGVvUz5t66DXmVeCNdEdYwbWr/V7XYyjYB5y/sTPX8+HQBH/jZTu3cT02p9dzXwmIrbh3jSVPlFudOdeyJytsFXe2h10Ym7QTJ2nT54v7tLz4euKdR5oJJkqFL+/DkbECZx7Vw0dSXLJS6PVamMfND755YNnnf4juXM1pxonyxb2wa27uHMok/Lk4VJ4337zytTVcYfledAPDdJ4/FpiFMqdb5VGsl5Lj9j7AuTfX647yGmmd+xZOkNauWykq6d1XLK6xo/PvKthb4aTCp55494ZB78hBw242H0feqFsu6tqn+8qKP/hJ//p0tlfuTpUlX1lJKfOoBrxWfE15YOaiWjcNRY2hEu49zRWhDEwq29LibWxmE5Sxu2yIOCJfSLyEG/uHO7bjhww8AAHT7Hq7bGYsCu2tLD16snEPjR9dQTfz8B8KxSJOJpYCuYS2ZGz6htMXEn2oteSrEJQcQouUaM7hkidPhu4ItzazCpnNOOzjYWmxNzhTxkXt2YyxGCyGPQUsnhFOxdas4MV0dALQTjIhnA8c6Kd8dQbq6tlCv941N46O/2O1qeKTB/8aBA2CVeP0bnUZWBzkv+uwO5ZQYVSavoWe+/MxTAAAgAElEQVRspSSte86kFjhhXPfv9wd+S7MYta3rSdClL1qbKt1mu//nuNBqvZehxjc1W8TUbNGjEaZi7CrOMg2nR6bibwqltq4I/dYHUU083mLLLr1xdXHj4X6j+uO17CmT5LySMOI8I4S9t2n9su1WTedWcYvw1oqPTlPf9A7L5nd4vpsJthLUZSOt5/yIdOPn/A2Zn5gmN9if2r9owHNGRPjeuOzmj+r5MaWIebUOk7uSuqtLOndS22dSJUeVentPUJwkhd5TS+HCI8oGqVPNxqbC1zN6xce4TbF0mf7NDUfw3SeP4WuPHY68L3LjSoOAeZ8VZyXv8NCeM5iubFY7YatjT1R8YWP3xsP9iZVaiyWJ8YoSj39tsOfUSOD+qLNfg2Gbj0n+OpBHO/S/32yxhBs+/AD+7Wc7Pb87yj1qfcmyyXmsTGMC9rrDMws/ri/trGzyOUKTaHfS1c+/+YUNZgkwwHbe5iduHavb1zISOqv31+ksQ5W1+6KPpfAI4kLSq1v7v+BDD4SGk4bgUQfpwvWUh1b5rfq5JUQq4H/sMw8eSOXdyiar/LfqnjWZ6+WhkBwW1x2buvHE4X6jex1Ur1gm7cwRvPrvNV1v6RQUhyZm8bmHq1Z8UkplvJLubyrqPt/X1x8JjzAqWYH1Q/KyOncEWxmaODvnckSfsRWsSPdsP1m+ImWqjco7Nh13P68/EN0h18UVIcruNyZniokHzLSo+ZumExuZmsVMoZR6QPrdrzwRek23YI6TxifBX1+dQ2ydnHImms68Xk2CTZ1JuyC0dV/yg6eO4xsbjuBL6w5G3pfHOtWf1LAoJmYKRnVofEY12dXUgcjdF/9kp4ojgFPrmnr9Y2v24rb1R3DXlh7895q9ASvQQrGEj9+/N3ID0GlP/vLz+81W68eMbwGX5SZrUmzq79cfO4KpWeVQ6tBJb7o0pe1/wjYVy1/yEfraUC8N1Sw0tuO3dCvfKu/4klVLU8WXFVOKEPu6f78fL731IXcs8I+NUWNlkvNXnPlYVZki/N7pQlF7tpHHYqsG9cfGOjdO4cF/Bl4Ydm+lX1So6Moxbd55F8Xlv2Hz2zCLLdP+x7h+RdynC6NvrDyuhW0QtCV0RbjYp6xlJHyM+R73jP9+M1eG2bQfO4Ws8u9HzgbPEjAhyYZYlLJB3Dl2/mejlICcdVdRsdgyrTsmXkVq7SbPu7FnsRY0VPqoNU7diUqH7XicxuvBzyt7A+V4y8pSv/IfD4bebys8ygInr/RnRFUz65UfW4u//sHTxu6ObLzoVN2ZRxfOn357s/tZt+EcNd6ErT+39+gtaZ573vzItADAR3+x243fZFPRpi6p6w9bsmiHpZIsK0VVvo9Pe/tF51385yU5gsbNxwYxNFFebzrJyWKfzmazX62rYU9NzRY99SYu39v9gq2I5NTbw0dYe8hiXj05q7HwDNlbcj7654+6+jAxY9a/hGE3jlU/h+WV1PQzWeEvhqzXO9Oes8KC19V5+8HeMdwWJZxQONKX7bEtYejmGf49LG8d0uefrScNE8LKamhiFv9yl9f1Z1yxqq549eeSh6XB+93YYkvT7vx5JGX4us5htmAWX1T+B473MApRT9MJtuIKNq3mO2TVXdic9lbjdKiVu1CSWleETtrikvjeHz8TeMY0Hf60mGJ1JoQE7tzcjed9cA2O9U/ow8tdsOVJjpZ/vmt7bDj/678exl9+b0vsfWnQpU/7W8osW9DV5vn+vA+uQc9gtXyiNEvNOkJz/+dR6NpGtDynfDFuopnHYdBBIU75r7oRe2JoEtd+8H58b+NxxKFabOlTG97e/fmutnP3jBDPJDI4oVyz8zS+uO4QPnC3V7vugd1n8IW1hwIHiao4bTosT1RrEMc6M8w9hQ7bnnvU8vyJahrM0gMAa3bZuW5IS9LgA67l1HeEzKRtpBlajbUkDcMz3ig3FNjocN7XdPPO+XrJkjn6tAQmbvnWpV/7zGOexdjw5KwycfbXF1OBgmHklfuc/I967up/W4Nf+8yjkcE9ur/PMOLkBM7Yikh0nMXWGz71iFXcgbqhmeSb5L1qceTcn7bpe/vL8t+w1w/TRDddaGWyEacJI67vcrwz2GjSA1VLr2rc8c8nUTKwGbPyRNdnhaXGSebxAf0aIS7sJGNt0oPdpQw+e/W/rQmPp9LMiopmral1ap7WTEnn5uq+xWcfPGD8XERuJ0tIRnyi4kpnPGJz1LYdTaZwq+uNWC+4sj2XMWsc97omffXqHafwxQhFwxtXLnE/x82jPNjc68NzxlbEfbbHVZh4GLlrS4/72UQgr1PkCcNUSSYvPnb/XlzzgTWuhdyvfuZR3L2tKsRy3sWfS+o79o2FH6eRFDWfo/r9nSeGPUJkXd2aKZRwzQfW4NZ79wAop/15Hwzv/wGgo63cXozOnMppzDYNV23T6vo9yVxEfebMyBT+5FubA/ckVZRw+MnTPbj2g/fj0NnkgpO4zXgV7/6t/jnpXk82x3Aw2aPOWnimKr3r2ooa39RsCR/9xW6julGrqag/mo2H+/Hij/4SP1b6Xc/9oXKCPARb5veqc1yd62BVsSMq3E1HvZaUAYutFK4IZ/x7doh3t2rq6SIqXf75T9yaOIqmE2yF4d9cTRwOqgOVM3B545HufSpqJ1AsSSOrFL/Wb1ZNLskmpo0gSgL45e4zAID9Z0a193g0ZHLo/Lxmp9UI7t52wrWc6x7wuhUolWSgcYxOFfDQ3t7sE+hJX/A3XQc7UyhZb6yozO9sC/x2rH/CHUgL7iZj9MAWR60ttqrnX8QItgKaBvp06uqBDev29bp+pqWUrkbymp2nYp/1WGxpXicqa/wbP+ortChlHNZHAcB0RTg4POFdWDvaL1GWCE4fFxBsaTaknL7Tv4CLynXnmmn9SnoeilpPbAXweU3kkihkqPmuJqtcTlL5np/GoG6s0b1JVvE7dXvHieHAb7osjBoL01psSXj7mKqbtnSTkCzrWGA80VjrAjEWWynir4450fcd0lh1qLmo8/WfNf5y8w83NmNG2n4lynVnVMj+PnHXyWHPplsylH7GqeMhaghhfbJpdti6AtSVSRLhRtViyy5+/6ZnIotkg2c8rpQM0hWIM8EzxmHHbCLM7QhXEIyibEVll/LpCOWnqJBMXb84eC22bHM3H8nW2n29eHjvmUTPqu9w0eIu4+fCXj3LMcy2Dkgpsfd0eV0apQz32IE+q43dCY1lQhLC6svqZ6rrB9060C/c9qc97d6Hu87SaYpr7o+af1+xomrlVD03JD4NruKNRTfs5ENBo9ShIx+LC2X/x+BF8xJs2dYBE+WquzaX5w/qUQAP7qnumYRZn6kbpK5r1Qw7Bs9ZzhF18RllrQDo6/JkJY/v2NQNINqiTlbGJUdY8Mlf7g8N1yEvmXXweAJ9KkIFW74+xc+Fi4Jjgdo/9AzqXXd61qOqgq3jWct/vy/qB3ZV9hdP6/cXTYhq5/45sTe9+mf8lqFJ63K77ox53/fgXlaiqFwuXVpVttT1T7o+f9Kg30marLAzpMLv937/0D27AQBPKq7+PEcDhYRTC4st0/XH22+6LHDddcUrw7x6lX978pDfxaH33rC6H/hZM2BM+8q9JKW79xr2ZrOGFshRbTLQh6coqnNHsOV2mOkXDesPlLWDdZOE7T3lQVJK76RALa+wSYv/jK2OiDO80uBvD9EuFctYCbZkNcywhYNOSzOvxbXaIP7uh9vwN7dv1d73nPfdi1sUaziVPBf+2g5KE+Fvfn49vrHhCIBkh9jO74w+w8x1lZDSXVFat2bWgi3H5D9GkOHv3MMmu8953734y+89bRS3bhPqnd/c5PnJWVCZaAKq5vW6RUVUEP7Fnvq089wHfrYTn6lo3EYJVAO+fyt/o4rGmRAFzqIpedMgUVUKeMI3ANscCq2/pixmEjrvVt3CWJ+FE9JTZLVeS2rF47cY9grvSrlZ0OreWxfTX2isYpPk2Yd+vgtAcgsQte+Kq4vuXCJi8+6Vz10eiCusDZn2m85COQv8c5EwVz9ZW9Q4tznx2GhPOuRl2eCUq3+BFzxjy3vdu1GTTVqcKPzBBbXVqveaar1JKfGWz60PuOzQpiPimnfzo/w3rGzC+mTT+YXpAikqtKgzZsOec8re2mJL+MfC+OeTWEv6tShV8py7BuLS9ffuj746mzLs3/j8Bnzw7l1WYZwdizhLLWbDwaZNq5tctn2Bzaa2TRf4x9/chH+4I95LhQ71HVShhA41/aHzoUSp0PPlR6LPfPKjm2uE4d/0jsLU3Y6fnb44SlJfFVU34HHj8Rs+9Qhe9p8PeX4LqyvthvsMjtWqqQukSCU45QFnXWSSey3RUy4tzr3qXH4qwo2orSDa/kyh+Pttxhl1gzmpl4o0xO0fTYeM2Wo/4RcUpfasBG+dTOMmFAiWWdS68PJ/vRd/8PWNgTmQrXvkbDALV53rqnOWo/1VhTK/IjgAvP2mSwO/mayZ1dfVuyIs/3W8YuVh0Ra15v2nH3nHSTWNcUIBp+0mXQOY7Mdm7X3IoxShaSrFosSbn3+B57eJrCyUNbz64+vwru9aeMoyyI5WZZwLVbbK2Y3ksf5xfDzE69FFi7qMx4mibw/Hz2yM4DPs2TM+rwK6ftPfn0sZVFD1x2c6nkW6IvS/k++6zZjRdIKtsGyJW3DbsKCr3RNmNQ6p/Qx4C2W6UDLaoNRZhGWBfxA1mdjanrHldM5j0/qJlt8PszacFJ23ml6bSc0dm7u1YWSJekZaGLpXPzlc7XR6Yw4719HVHl2f1h8sC2yTbnI751Q8sDuZVqiD1hIyor20uwsuO1eEURsIfhdzYZhMSJ16ZCLYUtuFLugowXyUaa46Wf3W40fL1zV56kxWlsz1HnrvJCb6LJxSIK5yPN60F4old8LqP7TVSKM94ppXgSB9+7UVjoWlP61bubTnpKiXiiXp0a6cLpRyP/MwjjDNPlu+/UTZUlJnvWmSh2rfZ3telO73hXOCygRh/UBSP9hpCAi2FB/eKqZaZrb13MnvJG01CyUlHQvnlC2b/cojgfMUfXmiupHNeqPCRNjh5H3UuKbW7+mM1IR1mxRhrx+26WFa17Po05MIUdtazN1wqYS55Y3CX7Ym8zFV4BcWR1Rxq8+87przquEa1pGOynxfd+5U3JosSigXh2MZb8pYhFuo6HmFnXWYKmS27QtMXM7ltg8agvoOcZrao1Px3jiyTP/3LOvA/bvM1yc21jAzxWQbfRuPBN0GxQmP4trlobPjgTVi2MbPiy5dov3dT5sr3Ddrr1FKcJ7Xs3AvWJ2fRM1H9Jt6HleEEVHZ9vG2Vrgm4dv0ieqYODRhJ9jKwt11e1v0PCzsLEJ1X8ZpZ1l2a+q72SgL6PLQ//zOk9EC78cP9Vv1cbpjA7LANA3qvEy1Mn/sQNXFt67f19Vlk/mKWie0rqGd8KUjJMp+wEt6xlbYcxOVuYWzD2VT5/7ye1uw6pbVAPQKAXGCibS54xGoaPK6UJIBt9p+17s3X7kcfpKWm6l7ageTfmz5vOqeVli68lhzq+1518mR0PuEEN56pi2Hcp0qyaBFNqCMdQG3fd77wgSjN67yzgV0ihL+OZGEdPuPsHIwHc+i9nD9e3EN7YpQCLFUCPFTIcS4EOKYEOL3swz/WP84Vt2yGuv2lU2jSyWJVbesjvT/HMXYdMEt2F0nRzwuu1RJpoRvw0f58pqPr8M//8h7aBwQPGNLJ7lPI+xxnvRX8jYDDQGbTlrKqnaXushRUS1TnEof0J5P0cf84Teecj9HHfKswxlgbN7Zhvf++BnsPDGMVbesxkN7zmg72bgBIYk/9zChhP93XeduI2S995lTKBRLWHXLanxhrX0769DUR/9i1CO0qQy4d26Odqnkfy9d+eoWsiXPgki/aHLQnaPgxGsyYVVddOrqQJRgyT/xnJotYtUtq3Hb+iOeuKs+7YNhjFQGMt0ZLoB3M3lb9xBW3bIab/jUI9h5Yth18ekP1n0P4aSzhLkdQbeYunjj7nnPHduw6pbVWHXLahzrH/dcy+JMgh9sPI5Vt6x2DzeOI6zdOj9/6/GjODWcQIgTUWZhPKVsmKjp2nxswLMYfuxAH7Z16w/GtkqiEHj3D/TWsEkwtWTVMa4ZX3SNx+8qTO0jRqcKWHXL6tDN06h2pPvd+R6myeyfbCZ1pWnDTKWfdr9X5jBff8yrBZ+5xZb0/g0TNkRprdloxNrgCPUHA4cPeyN0FvDO4fEeN7IGabFqcyF1qXpZur9FCX/UOuV3KeHH/Fy16n1x1SSsTw6rX7/+2cfwm59f735Xx2y13obx9PEhvP6T6zy//dd9e9HrG6fdhVlI+p2it50Txln5AcDJoUncualbuccqCgB6t05+wubB/T4rpof39kJKiW9uOILnfWBNoB3oaIvw0BCWHqdtq1ZXV73/vtA4wrLlG4YHmQPR8+ao6i6lXbk4br9PD0/hvXcF13qrblkdal0xHpFGf53Py2q127expJbhOp8ykh9VISBcqFm+4swh//C2jckSinzPJJuyUIqcSWix5UdKqR0P1U0jW+XDUknixFA65aHoM7aCv/kVeJz2Pjo1ix8/XV2rua4IDdJQdVuov/v08BQu/9d7vfFW7lXz7IKF4e407QVbErtPjkS6+VTLbu2++KMNbJRxVVeud23pwfGQc8216VJedc3OU4nOLNJZ8qg4a3e/pr+6Xv0/X36ikqDynyyatImXJFP8G7N/8PX4/srTXoulyPFF7V9NzmwzxR/loLJfue/0qHtkyD8qFkph65MJzXmEun7oy48cik3XSaUv0grxUa6PTjvIQ8cvrg/1ejeo/h5Wl5y9TidcU8tWALhvZ1WR2qT4sxbA6JTT/PEFFPl8rndXLAieCZWlPPJFly0OvWamMOa9X5eHeQi2VMORqKIVonxUTs9guf9W175bjg1i1S2rseVYec34mQcP4NRwcK/RecL/HqYeWJb6FNrv3nYycI+/Hz/SN+7OV979g61un6Ky9bjZWlfXJp15sn8/JE3dqoXF1hcAzAA4H8AfAPiSEOK6uIccUzzdP/WeTUcHAcD96xzK+tkHD0SGoQvPQTVjf8+d29z71EVTyeeCQh0Yx6YLXs3wyvOq+4piSQYEW8WS1JgBmpeuownm31yYni1p31udMM0W9ffo8qlQKrmDc5jLPHXxNjJZ0HacM4X4OMP+ebWBggNRXAc2rggwAZ+LqgTp8eNYR/1oc49eQ6IYbWo6Ol2wToMuuHK+e3+bccraM9lqiQ3/4sVlP72vfO5ydwIV1s6i+Mqjh7H75Ii2XTl84O6d7nV1sIhKn79jnNLU+2OaRcGMUvf9HW/Rp13pF1pIWbWC6mzT56HK0ORsaF/mf1dPOkoyYEbsWH99ySfEd+qvrm06VndCBPMSqPYhxZLEb31hAwDgYO8YdiuaKP724bQdKZ3yLLgWW07aHXSb+W780vu9WJL4ydbqIcWbjw56ykdXvrZt1ZmsHh+YCGlTShnJYJk5qH3bzhMj1mlqrwhvR6ZmjdOunsmgXvvD256Cn/ueiT//La79Sinx6P6znvt1FJT2FIVucT85W4ztS4ol6VGoONQ7hmJJajfy21qFJyw1zhMVK7KvPHIoMq8LIb9PzBR895XfW124qO1gpNL2HXQHyAPA9RcvTFSvdfnlP3PGcUunamoCZWFJWHg6N5ex/6S3nahzHfU+VVgUV+7OPCLtP0cp5+zYtOd3/4JzZLKctldftQJAua9w7jXZeHxg1+nYtDj9htrvFksysLj250lYeKpwI87yQo0zbLGrlqWUEhsq85qi1MevzoPV9IbNL/ecGsH2nmH3u1/xxKRO+s9n+9GWHuzxnc3gjPF+lzP+fP2fhw8a53WxJAObRE4foP57xX89jH/58Q6cGp6s1B39fDXqn7ouODk0qc2LsPI+2DsWKN/xmSK+9uhhFEoS3YPBOVFYfuvmas6YXvSd5Tim2ShzykEXT9ha5yO/2K39XYdqseUPU9/+ytdmiyVtuYStUZbMK1vqnhqZCvWucGp4yvOMugEyXfCOcyoTMwVFkz2+bujCCHtf59/mYwOBex3mdrRGPjukjFuFsHWjrywfO9CHYknib2/fitd/cl1s2lWkRR7E5YOfyZmCcTqmCsG5ick/v/LGbDG4zge8Y6tubjSjmVc5/epQhOv68RmzcdPpyvR1Phhup08Z0pm7fsrnSrmzMgcaN1jTVhUM9Nd3nwpa0uj2PaL2M/xj61RlzqkqjCzoqirmlUoSb/7cY/iTb20Ore9q13Hn5h7PtWsvXBhaNkB83VbdwX32oQN4+1efCL03eOZjtT79xfeexls/t96q7YWhjiffrngIcd7F4cnD3j5mtljCaKV/7mqP32+I/6ffAwqUTcQemlOezvNh1pS6/FKDnZwteuaE/jSo11pbRAbvHt/f/dpnH8Wff2czZgolVwmyJMMVcIcmgmvPKEWlqPqj7hcUlLY8p7LnODpVwPc3Vj0b+ftId680ZJ5p8i9u71Rda6p9gl9Z37nHGeed99H10WHpdThwZhRrdga9BUnNc/78SFNH/OfR+eMYm54N7BOOTXnXtzolxLD5tG2dBcqKEmH3OWPjoE8BuaTMDdQ2NjQxgxd++AF87dHDnnBmNfPztO1O3TsNeTVcd9FCTMyU+4h3fOOpSp2r3uzsz+w5VW036mcHZ6zyr7MCXiAM52VjmjHZP8fffHTQY/hwx6buQDiRLsBRLSOdIcyJynombs2rRvmht10bGZ/Iw7epG7gQ8wAMArheSrm/8tt3AZyQUt4S9lznhVfKC//oM7mlixBCSH684XnneQ4YJuTZyMWL56TWpCb15R/feFWm554RkoTOthbMxGiGE5KGJXPbPVr/JFucTe1nEzdcssg9m7wZWNDVBgFgJMQbDTFn6bwOozM+CSHkXOVdr3oO7tzcbe1Klug5+l9vgRBii5TyRt11vb+o7LgKQMERalXYDuDV/huFEO8C8C4AWHrx5XjPG68KDXRgfAZL5na42j0P7+3Fa65egW3dQ3jxZUuw8Ug/rr9oEeZ1mr3e2dFpvOKKZTjcN45Tw5M4b0EXnnfhQtyxqRvXXrjA48rvycP96BubxltfcBGAsquF+Z1teO558zEyOYv9vWNYOrcdi+d24NDZMXS2teAFl5RNLIslifUH+1wNYCe85fM7ce1FC10NAIGyxc/KZXNx0eI5eGT/WbzmqvOw5fggOtta8Jzl89DR1oITg5MYmpzFwq42dA9O4pXPXe5qY2w6OoBrLliA3tHpyMOAF3a1YX/vWKTpvoNAWWvM0b5++vggXnzZEhRLEt0DE5gulNDV3goJiVXL5mHzsUEsm9eBy5fP8zw/MVOEALTnk5hSKJU19C9dOhcD4zPYfGwQV503H1OFIua0t7rnpF153nzsOTWCmaLE3tMjWDavE72jU7hp1VIAZTPLxXPbsWRuB471T2D/mVG88drzrdMjZTk/utpbMDJZwMuvWIa1+3rxqitXoLVFoH9sGjNFiTntrShJiaUVf7DThSL6RmfQPTiB5fM7sfvUCF5xxTIsnx80+zVhfLqA6y9ehAO9Y3j8YB9eddUKFEoSP992AjeuWoprLljgORTyFztOYtGcdtx85YqIUKscPjuG51TqU1Q7my4UcbRvAsOTs3jxyiVYNKcdkzMFnB2dxraeYbxeOecBADYfG8Tvv+QyFEolfOWRw7hp1VIsnlutH6t3nMJzVszD82K0304MTuLGVUvQIkTohvLhs2NYtXweBsZnMD5dxMplcz3XZ4slTFa0K5Yqfnv7x6axbH4npAQO943h+MAEXnt1+T22HBvEr6zU+7IfmZzFTLGEy5bODRzIefjsGJbM6/CceTUwPoOOthaMThUwr6MVczpa0d7aAimB29YfxkWL56CjrQVveN75eOJQP264dDHmdbRitljC5mODeP4lizCv4gqws60FS+Z14BP378NLn7MMV543330PP057dugemMCx/gm88LLFmN/ZhvMXdqJYqlp9+Z990aVL3D75ddech3/61avxQMVNxejULPaeHsVNq5aiJCV29AxjtljCeQu63Pwfny5g18kRvOTypW64vaNTOD08hf7xGTevZwolTBeKbhu3pXtgAmPTBUwXSrj2woV46sgAXqnxHw2U68JjB/qwfH4nXnDJIgBAz+AEzlvQVSmjWZwemcaV583Hg3vOoK1F4DVXn6cNK46wclFpbRF46sgArrtoIbraW/HNDUfw9psuc61vCxWtSGeM7GxvwQ+ePI4/f9VzICrvU5JlS6ZSSWL3qVGsWNCJYqmES5ZU20Hf2DTW7DyNX1m5BOcv7MLR/nG8+LIlOD0yhe3dQ3j1VSvKfb0EBidmsGxeB+Z2tmHz0QGsXDbPTc/4TAHH+iZwwaIu7D8ziqvOXwAhyv3l0nkdWDSnHVeeNx+bjw3igd2n8aZrLwi8c6EksXZvL5bM68BV5813x43zFnRi0Zx2HOituld5/FAfXnTZEvz1a5+Lj6/Zq83PFlE2t29vbcGGg334lZVL0KVYVjkUSxLPnBjGCy/1ukiQEhgYr5bVkb5xzBRKuPqCBe494zMF/N5Nl6F7YALPnBjGigWdOF1xLTAwPoPhyVlcvnweVizoxIaD5fr12mvOw5mRKZwZnkrlU310ahYHKlZsN61aiu3dQ+hsb8G8jjZcsmQuvrHhCN7x8pU4NTyFMyNTWNjV7km7jvHpAtpaBTrbgvkUxvGBCVy0qMudPz2y/yxuWrXUYykOlOdfnW0tgflAoVjCjhPDKBQlrrtoofF8zoRCsRRw0SxleT62cE4butpbccWK+VjQ1YbfvfFSzOloDfTdA+MzmNvRit2nRnD9RYtwbGAC7a0CW44NYny6iD982cpYN1oCwPMuXIjdGu28tlaBK1bMx9V0+f0AABUESURBVO1PHXf71r2nR3DZ0nmBPFRZ0NWGGy5djPUH+jA5W8Qdm7px629fj57BSVy2dC56R6ex6ehAYF54+fJ5ODMyhaePD2JhVzsuqlhoA8D6A3146XOWor21Jbafmi2W54HFUvmsv5NDk7jqfH39Onx2DC1CYFVljgiUtQg3HhlAR6uInJdcsLALTx8fxMRMEZcsmYN7dpzEqaEp/PH/WoUFXe14/FAfls7rwJmRac+cu1AsoaOtJaBd2T82jUJJ4vzKXPhA7xi62lpw6VLv/MDPkb5xLOxqw9zONo+FpoOUQP/4tGdOd2p4CnM7WtE7Oo2LFnUZ1e1rLliAmWIJh30WalKW3V+97przMDFTdMfxRXPacfe2E3jz8y8EUHZ9/ubnX4D7dp7GTKGEQkli14lh3HDpYpSkxJZjgxibLuCmVUtdV3sqA+MzWDqvAwd7x7B8frnvbWsVmC2WsKOn2k9OzBRxrH8cV1+wAFuPD2F4chbPWT4PP9l6Av/3ZZfhvAVdODE4ibZW4ea1w0yhhAsWdWFqtoizY9NoEQK7To7gxpVLcGp4EieHprB4bjsmZ4oQAlg+vxPThRImZgroamvFquXzPHP6QqlsZbigq80zt3Hw9/Fz2ltx7UUL8d4f78A1Fyxw1246nD5keHIWu04Oo6u9Fev2ncU7Xr4Se0+P4pXP9c4pWgRwyZK5uG/nKVx30SLPtZNDkzgxNAkhBG6szCM3Hxt0P5swPlPAyGQBnW0tnnlrGD/degLDk7N44/POx8VL5qCrvQWvuGI51u7tjR1/ZoslnB6ewoVK/+5n/YE+XLJkDnacGMaLL1uMS5bMxcmhSQxPzgbm8Qd6y2vlay5YgOlCCSNTs5jX0eaO57p2FcbZ0WkcH5jAsf5x/PaLLvH0wf1j0+gZnMRrrjkPO3uGcfGSOZ5nB8ZncKx/HDdcuhgHzozh6gsW4EWXLca+06OB/t+Gh/f24qO/eT1ODk9iX8Wa9PFDfbhx5VIMTsxge89QYO4zOjXrjrf++e7kbBH9Y9OeOduOnmG84JJFePPzL8Tf37EVXW2tWDa/I1DXovCvAVQO9I7hkiVzsOnIAOZ1tuFXVi7B5GwRa/f24uLFc3CDMk/afGwQL7xkEY4PTOAf3ngV1uw8rbVS8yMlcLR/3N0z0PHI/rN44aWLMae9FYvntrvlIiVwpG8MK5fNi3ULf/hsuQ87M1qeuzscOjuGP7/5OTg1PIW9p0bcsXlsuoATg5Oh86TxmQIO9Y7hwT29+Ic3XBUY95fP70ShVMJV5y/AnZu6sXLZPPxs2wm8+fkXGM2pnLH5iUP9uPaihdpjLBx+tu0EXnr5UpwanvKU5TMnhnHlefMDc93RqVn8YscpfOg3rsPy+R348iOHsXRuB15y+VI8c2IYUkocH5jAiy5bgkNnx9A9MIFXXbUCU7MlHOsfxzUXLMRnHtqPv3z1Fehqb8XYdAFbjw/i5itX4OVXLMOTh/qxtXvI7WOj6pgtxZJ0y7pncAIrFnRq83Ptvl5cff4CHK207Z7BSVy+bJ7HEmHjkX5cf3F57dw/No2H9vbi8uXzcNnSuZ5xqmdwAu2tLTh/YRd6BicgJdw5wvbuIVx30UJtnzi3oxWbjg7gqvMXRJafLVuPD2LhnHb0jkxjTkerm8/O2uvaixaib2waP916Ar//ksswt6MNR/rG0NnWiqHJGVy6ZC56Bidx7UX6vZWB8RlctnQuVi6bi8cP9eP0yBSuVuZzTj8vhMDY9CwOnx3H2264CEf6xtHZ1uKZRwLlNnbFivkolCQeP9iHV1yxDG2tLZjb0Yr5nW3Y3jOE8xZ04bEDZxOvpR1eccUy7Dk9iu6BCfx4Sw9eeOlidLa3YGq2FFjXbT0+iLmdbbh82Tw8dWQAczvLa4BFlXWJAHDT5Uux+eiAO3fcenwQczpaMTpV8Oz1+hmfLqBnaBIXL56DHT1DeP015+OB3afR1d6KF1+2ROvS+lj/BGYKJczpaMVlMXNQEzorc95Zn2XrnlOj7t7GwPgM+sdncLx/HK9/Xnkf9MzIFApFiYuXzMHZ0WnsOTWCN113Pu7fdQavvmoF9pwawarl86zG6KN94yhJiZuvXIGnjw/ihksXu+tjlYHxGRwfmHDLqlAqu9B+zdXnYXRqNtCPjFe8pS2a044dPUO45oKF6GhrQVurQIsQVi5g4xicmMGZkSlcc4G33azb14v5Xe04f0Enjg1M4MJFXfiHN1yFm69cjm+sP4LnX7LYtazdfGwQq5bNxbJ5nViz6zQuXjwHKxZ04lDvGF555XIMjM9gcqaI/b2jODM8hd97yWVuPF9YexDvePlKd16wctlc9I+V8ytq/nfV+fNxYqi8/hgYn9Eq2mzrHsLzLy6P385YXCiW8NjBPndPe/fJESyb34Fl8zvR1iJw4aIuXLCoC2t2lj2V7Dk1gkuWzMWFi7o8a/vHDpzFr153AaYLJUzPFj195dyOVtyz4xRufu5yt28+PTKFYqX+fXHdQXzgrdHWWkD+Fls3A/iRlPIC5bc/B/AHUsrXhD134403ys2bN+eWLkIIIYQQQgghhBBCCCGEENKYRFls5X3G1hgAvxrAQgCjmnsJIYQQQgghhBBCCCGEEEIICSVvwdZ+AG1CiCuV324AsCvneAkhhBBCCCGEEEIIIYQQQsg5Rq6CLSnlOICfAPiIEGKeEOJ/AfhNAN/NM15CCCGEEEIIIYQQQgghhBBy7pG3xRYA/BWAOQB6AdwO4C+llLTYIoQQQgghhBBCCCGEEEIIIVa05R2BlHIAwG/lHQ8hhBBCCCGEEEIIIYQQQgg5t6mFxRYhhBBCCCGEEEIIIYQQQgghqaFgixBCCCGEEEIIIYQQQgghhDQFFGwRQgghhBBCCCGEEEIIIYSQpoCCLUIIIYQQQgghhBBCCCGEENIUULBFCCGEEEIIIYQQQgghhBBCmgIKtgghhBBCCCGEEEIIIYQQQkhTQMEWIYQQQgghhBBCCCGEEEIIaQoo2CKEEEIIIYQQQgghhBBCCCFNAQVbhBBCCCGEEEIIIYQQQgghpCmgYIsQQgghhBBCCCGEEEIIIYQ0BRRsEUIIIYQQQgghhBBCCCGEkKaAgi1CCCGEEEIIIYQQQgghhBDSFFCwRQghhBBCCCGEEEIIIYQQQpoCCrYIIYQQQgghhBBCCCGEEEJIU0DBFiGEEEIIIYQQQgghhBBCCGkKKNgihBBCCCGEEEIIIYQQQgghTQEFW4QQQgghhBBCCCGEEEIIIaQpoGCLEEIIIYQQQgghhBBCCCGENAUUbBFCCCGEEEIIIYQQQgghhJCmgIItQgghhBBCCCGEEEIIIYQQ0hRQsEUIIYQQQgghhBBCCCGEEEKaAgq2CCGEEEIIIYQQQgghhBBCSFNAwRYhhBBCCCGEEEIIIYQQQghpCijYIoQQQgghhBBCCCGEEEIIIU0BBVuEEEIIIYQQQgghhBBCCCGkKaBgixBCCCGEEEIIIYQQQgghhDQFFGwRQgghhBBCCCGEEEIIIYSQpoCCLUIIIYQQQgghhBBCCCGEENIUULBFCCGEEEIIIYQQQgghhBBCmgIKtgghhBBCCCGEEEIIIYQQQkhTIKSU9U5DACHEKIB99U4H0bIIwHC9E0FCYfk0Byynxmc5gL56J4JoYftpbFg+zQHLqfHhONT4sB01Niyfxodl1BxwPGpc2IYaG5ZPc8ByanyullIu0F1oq3VKDNknpbyx3okgQYQQX5VSvqve6SB6WD7NAcup8RFCbOY41Jiw/TQ2LJ/mgOXU+HAcanzYjhoblk/jwzJqDjgeNS5sQ40Ny6c5YDk1PkKIzWHX6IqQ2HJPvRNAImH5NAcsJ0KSw/bT2LB8mgOWEyHpYTtqbFg+jQ/LiJB0sA01Niyf5oDl1MQ0qitCaoQQQgipGxyHCCGE1BOOQ4QQQhoBjkeEEELqSdQ41KgWW1+tdwIIIYQ8q+E4RAghpJ5wHCKEENIIcDwihBBST0LHoYa02CKEEEIIIYQQQgghhBBCCCHET6NabBFCCCGEEEIIIYQQQgghhBDigYItQgghhBBCCCGEEEIIIYQQ0hRQsEUIIYQQQgghhBBCCCGEEEKagtwEW0KITiHEbUKIY0KIUSHENiHEryvXXy+E2CuEmBBCrBVCrFSu/a4Q4vHKtXWasF8nhHhaCDEihDgshHhXXu9BCCGkecl5LHqbEGKnEGKsct+1NXotQgghTULKcegTQogDlef2CiHe4Qv7hUKILZVntwghXljLdyOEENIc5DwWfVUIsU8IURJCvLOGr0UIIeRZTp4WW20AugG8GsAiAP8G4E4hxCohxHIAPwHwAQBLAWwGcIfy7ACAzwD4L3+gQoh2AD8F8JVKuG8H8CkhxA35vQohhJAmJa+x6EoA3wfwFwAWA7gHwM+FEG35vQohhJAmJM04NA7gbZXn/gjAZ4UQrwAAIUQHgLsBfA/AEgDfBnB35XdCCCFEJZexqMJ2AH8F4Om8X4IQQghREVLK2kUmxA4AHwawDMA7pZTOwmwegD4AL5JS7lXu/zMA/1dK+Rrlt/MBnAYwT0o5UfltE4BPSSlvr9W7EEIIaU4yGoveDeDXpZRvqXxvQXnR91Yp5UO1ehdCCCHNh+04pDz3cwCPSCk/KYR4E4BvArhEVhZ0QojjAN4lpVxTo1chhBDSpGQxFvl+Xw/g61LKb+WddkIIIQSo4RlbFYHUVQB2AbgOZa0OAICUchzAocrvkUgpzwC4HcAfCyFahRAvB7ASwPo80k0IIeTcIauxyAnO91kAuD6blBJCCDkXSToOCSHmALip8hwq9+yQXi3FHbpnCSGEEJUMxyJCCCGkbtREsFVxH/h9AN+uaHzMBzDsu20YwALDIG8H8EEA0wAeA/B+KWV3RsklhBByDpLxWPQggFcLIV5Tcfv0PgAdAOZmmGRCCCHnECnHoS+jvPF4f+V72vUUIYSQZyEZj0WEEEJI3chdsFVxz/RdADMA3l35eQzAQt+tCwGMGoR3DYAfAngHypuI1wH4FyHEW7JKMyGEkHOLrMeiyiLwjwB8HsApAMsB7AbQk1GSCSGEnEOkGYeEEB9H2SL4dxULrcRjGCGEkGcnOYxFhBBCSN3IVbAlhBAAbgNwPoDfkVLOVi7tAnCDct88AFfAzJz5egD7pZT3SylLUsp9AFYD+PVME08IIeScIKexCFLKu6SU10splwH4dwCrAGzKMOmEEELOAdKMQ0KID6O8znmTlHJECXYXgBdUwnZ4AegeihBCiIacxiJCCCGkbuRtsfUlAM8D8DYp5aTy+08BXC+E+B0hRBfKbgV3OAdTVs7O6gLQBqBFCNFVMZcGgK0ArhRCvE6UuQLAW1H2KU8IIYT4yWMsghDiVyr3rADwVQA/1x2wTAgh5FlP0nHoXwH8PoA3SCn7fWGuA1AE8LdCiE4hhKN5/3CO70EIIaR5yWMsghCio/KcANBeWTPV5NgTQgghz25EXhbEQoiVAI6ifA5WQbn0/6SU3xdCvAFlF04rAWwE8E4p5dHKs+8E8E1fkN+WUr6zcv13UR5sV6Ls+/f7AP5VSlnK5WUIIYQ0JTmPRetR1m6cBfAjAO+pHLZMCCGEAEg9DkmU3UXNKs/dKqW8tXL9RQC+DuBaAHsA/KmUcmuuL0QIIaTpyHksWgfg1b4oXyulXJf5ixBCCCEKuQm2CCGEEEIIIYQQQgghhBBCCMkSmgcTQgghhBBCCCGEEEIIIYSQpoCCLUIIIYQQQgghhBBCCCGEENIUULBFCCGEEEIIIYQQQgghhBBCmgIKtgghhBBCCCGEEEIIIYQQQkhTQMEWIYQQQgghhBBCCCGEEEIIaQoo2CKEEEIIIYQQQgghhBBCCCFNAQVbhBBCCCGEENIECCFuFkLsq3c6CCGEEEIIIaSeULBFCCGEEEIIIQYIIY4KISaFEKNCiCEhxONCiL8QQsSuq4QQq4QQUgjRZhGfFEI81/kupXxMSnl10vQTQgghhBBCyLkABVuEEEIIIYQQYs7bpJQLAKwE8F8A3gvgtvomiRBCCCGEEEKePVCwRQghhBBCCCGWSCmHpZQ/B/B2AH8khLheCPEWIcRWIcSIEKJbCPEh5ZFHK3+HhBBjQoiXA4AQ4k+EEHuEEINCiPuFECsrvzv3b6/c/3YhxGuEED1OgBULsn8WQuwQQowLIW4TQpwvhLivYlX2oBBiiXL/yypWZkNCiO1CiNfkmEWEEEIIIYQQkgsUbBFCCCGEEEJIQqSUTwHoAXAzgHEA7wCwGMBb/v927t9VyzKMA/j3IgcHy5DOEApBQ4tDOvRjiGqJUBJD0UFaGgRzaKohg4hIoyUKG1olIwtCIbKhwSBDgiBQoT/gkHAQDv2Acgivhvc59BInOYe3zvGBz2d5fzzXfV/3+24P3+e+k7xQVc8OpY8Pr3d396buvlRVe5McS7IvyVySb5J8PMy7VP/gUP/Jvyxhf5KnkjyQZE+SL4c55zK533sxSapqa5IvkryZZEuSl5J8VlVzM/8JAAAAa0iwBQAAMJtrSbZ099fdfaW7b3b35UxCqiduMe5Ikre6+8fu/jPJiSQ7lnZtrdDJ7l7o7p8yCca+6+4fuvtGkrNJdg51zyU5393nh/V9leT7JLtX91MBAADWl2ALAABgNluTLFbVI1V1oaquV9UvmQRX99xi3H1J3huOBvw5yWKSGuZbqYWp938s83nTVK8DS72Gfo8luXcVvQAAANbdhvVeAAAAwFhV1UOZBFEXk5xL8n6SXd19o6rezd/BVi8zfD7J8e7+aA2WOp/kw+4+vAa9AAAA/jd2bAEAAKxSVd1VVc8kOZPkdHdfSXJnksUh1Ho4yaGpIdeT3Exy/9R3HyR5paq2D3NurqoDU9cX/lE/i9NJ9lTV01V1R1VtrKonq2rbfzQ/AADAmhBsAQAArNznVfVbJjugXk3yTpLnh2tHk7wxXH8tyadLg7r79yTHk3w7HAX4aHefTfJ2kjNV9WuSq0l2TfV6Pcmpof7gLIvu7vkke5McyyRkm0/yctwTAgAAI1Pdy52IAQAAAAAAALcXT+cBAAAAAAAwCoItAAAAAAAARkGwBQAAAAAAwCgItgAAAAAAABgFwRYAAAAAAACjINgCAAAAAABgFARbAAAAAAAAjIJgCwAAAAAAgFH4C0wa3iYTuVfgAAAAAElFTkSuQmCC", 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" ] diff --git a/notebooks/subsampling.ipynb b/notebooks/misc/negative_sampling.ipynb similarity index 100% rename from notebooks/subsampling.ipynb rename to notebooks/misc/negative_sampling.ipynb diff --git a/notebooks/misc/two_stage_undersampling.ipynb b/notebooks/misc/two_stage_undersampling.ipynb new file mode 100644 index 00000000..16a6bec9 --- /dev/null +++ b/notebooks/misc/two_stage_undersampling.ipynb @@ -0,0 +1,182 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a56070fc", + "metadata": {}, + "source": [ + "# Two-Stage Precipitation Modeling with Negative Sampling\n", + "\n", + "This notebook demonstrates how to handle a highly imbalanced precipitation dataset\n", + "(≈99% no-rain events) using structured undersampling and a two-stage modeling approach:\n", + "1. Classifier for rain vs. no-rain\n", + "2. Regressor for precipitation amount given rain\n", + "\n", + "Here is a summary of what the code does:\n", + "\n", + "- Undersample majority class (no-rain) to balance data.\n", + "- Train a classifier for event detection.\n", + "- Train a regressor for continuous rain amount prediction.\n", + "- Combine both for an end-to-end precipitation model." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a216e708", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "## 1. Setup\n", + "#\n", + "import pandas as pd\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor\n", + "from sklearn.metrics import classification_report, mean_squared_error\n", + "from imblearn.under_sampling import ClusterCentroids\n", + "\n", + "#\n", + "## 2. Load and Prepare Data\n", + "#\n", + "\n", + "# Replace the CSV path with your actual dataset path.\n", + "df = pd.read_csv(\"precipitation_dataset.csv\")\n", + "\n", + "# Separate predictors and target\n", + "X = df.drop(columns=[\"precipitation_mm\"])\n", + "y = df[\"precipitation_mm\"]\n", + "\n", + "# Create binary target (1 = rain, 0 = no rain)\n", + "y_binary = (y > 0.1).astype(int)\n", + "\n", + "print(\"Rain events:\", y_binary.sum(), \"of\", len(y_binary))\n", + "\n", + "#\n", + "## 3. Visualize Class Distribution\n", + "#\n", + "\n", + "plt.figure(figsize=(5,4))\n", + "sns.countplot(x=y_binary, palette=\"coolwarm\")\n", + "plt.title(\"Class Distribution (Rain vs. No Rain)\")\n", + "plt.xlabel(\"Rain (1) / No Rain (0)\")\n", + "plt.ylabel(\"Count\")\n", + "plt.show()\n", + "\n", + "#\n", + "## 4. Train/Test Split\n", + "#\n", + "\n", + "X_train, X_test, y_train_bin, y_test_bin = train_test_split(\n", + " X, y_binary, test_size=0.2, random_state=42, stratify=y_binary\n", + ")\n", + "\n", + "#\n", + "## 5. Structured Undersampling of the No-Rain Class\n", + "#\n", + "\n", + "# We'll use ClusterCentroids to retain diverse, representative no-rain samples.\n", + "cc = ClusterCentroids(random_state=42)\n", + "X_resampled, y_resampled = cc.fit_resample(X_train, y_train_bin)\n", + "\n", + "print(\"Before:\", np.bincount(y_train_bin))\n", + "print(\"After:\", np.bincount(y_resampled))\n", + "\n", + "# Visualize new balance\n", + "plt.figure(figsize=(5,4))\n", + "sns.countplot(x=y_resampled, palette=\"coolwarm\")\n", + "plt.title(\"After ClusterCentroids Undersampling\")\n", + "plt.xlabel(\"Rain (1) / No Rain (0)\")\n", + "plt.ylabel(\"Count\")\n", + "plt.show()\n", + "\n", + "#\n", + "## 6. Train Rain/No-Rain Classifier\n", + "#\n", + "clf = RandomForestClassifier(n_estimators=200, random_state=42)\n", + "clf.fit(X_resampled, y_resampled)\n", + "\n", + "# Evaluate\n", + "print(classification_report(y_test_bin, clf.predict(X_test)))\n", + "\n", + "# \n", + "# 7. Feature Importance Visualization (Classifier)\n", + "#\n", + "\n", + "importances = pd.Series(clf.feature_importances_, index=X.columns).sort_values(ascending=False)\n", + "plt.figure(figsize=(8,5))\n", + "sns.barplot(x=importances[:15], y=importances.index[:15], palette=\"viridis\")\n", + "plt.title(\"Top 15 Feature Importances (Rain Classifier)\")\n", + "plt.xlabel(\"Importance\")\n", + "plt.ylabel(\"Feature\")\n", + "plt.show()\n", + "\n", + "#\n", + "# 8. Train Regressor for Rain Amounts\n", + "#\n", + "\n", + "rain_mask = y > 0.1\n", + "X_rain = X[rain_mask]\n", + "y_rain = y[rain_mask]\n", + "\n", + "reg = RandomForestRegressor(n_estimators=300, random_state=42)\n", + "reg.fit(X_rain, y_rain)\n", + "\n", + "# Evaluate on training data (only for illustration)\n", + "y_pred_rain = reg.predict(X_rain)\n", + "rmse = np.sqrt(mean_squared_error(y_rain, y_pred_rain))\n", + "print(f\"RMSE on rain events: {rmse:.3f}\")\n", + "\n", + "# \n", + "# 9. Feature Importance Visualization (Regressor)\n", + "#\n", + "\n", + "reg_importances = pd.Series(reg.feature_importances_, index=X.columns).sort_values(ascending=False)\n", + "plt.figure(figsize=(8,5))\n", + "sns.barplot(x=reg_importances[:15], y=reg_importances.index[:15], palette=\"crest\")\n", + "plt.title(\"Top 15 Feature Importances (Rain Regressor)\")\n", + "plt.xlabel(\"Importance\")\n", + "plt.ylabel(\"Feature\")\n", + "plt.show()\n", + "\n", + "# \n", + "# 10. Combined Prediction Function\n", + "#\n", + "def predict_precipitation(x_new):\n", + " rain_prob = clf.predict_proba([x_new])[0, 1]\n", + " if rain_prob < 0.5:\n", + " return 0.0\n", + " else:\n", + " return reg.predict([x_new])[0]\n", + "\n", + "# Example usage:\n", + "example = X_test.iloc[0]\n", + "y_hat = predict_precipitation(example)\n", + "print(\"Predicted precipitation (mm):\", y_hat)" + ] + }, + { + "cell_type": "markdown", + "id": "cd5bef78", + "metadata": {}, + "source": [ + "Possible Refinements\n", + "\n", + "- Use **NearMiss** or **TomekLinks** instead of ClusterCentroids for undersampling.\n", + "- Apply **SMOTE** or **ADASYN** to oversample rare rain events.\n", + "- Calibrate classifier probabilities with `CalibratedClassifierCV`.\n", + "- Add temporal cross-validation to avoid data leakage." + ] + } + ], + "metadata": { + "language_info": { + "name": "python" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/.ipynb_checkpoints/eda_sounding-checkpoint.ipynb b/notebooks/sounding/eda_sounding-checkpoint.ipynb similarity index 100% rename from notebooks/.ipynb_checkpoints/eda_sounding-checkpoint.ipynb rename to notebooks/sounding/eda_sounding-checkpoint.ipynb diff --git a/notebooks/sounding_demo.py b/notebooks/sounding/sounding_demo.py similarity index 100% rename from notebooks/sounding_demo.py rename to notebooks/sounding/sounding_demo.py diff --git a/notebooks/eda_sounding.ipynb b/notebooks/sounding/sounding_eda.ipynb similarity index 97% rename from notebooks/eda_sounding.ipynb rename to notebooks/sounding/sounding_eda.ipynb index 241f8e8d..c6555c1a 100644 --- a/notebooks/eda_sounding.ipynb +++ b/notebooks/sounding/sounding_eda.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 122, + "execution_count": 7, "id": "9f8a5eab", "metadata": {}, "outputs": [], @@ -28,7 +28,7 @@ }, { "cell_type": "code", - "execution_count": 123, + "execution_count": 2, "id": "0c65fde1", "metadata": {}, "outputs": [], @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 124, + "execution_count": 3, "id": "2b2edb3a", "metadata": {}, "outputs": [ @@ -48,7 +48,7 @@ "292" ] }, - "execution_count": 124, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -59,7 +59,7 @@ }, { "cell_type": "code", - "execution_count": 125, + "execution_count": 4, "id": "a0d21fe0", "metadata": {}, "outputs": [ @@ -80,7 +80,7 @@ "Length: 292, dtype: datetime64[ns]" ] }, - "execution_count": 125, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -93,7 +93,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 9, "id": "d428d7b1", "metadata": {}, "outputs": [ @@ -203,19 +203,19 @@ "2010-06-15 9.162783 " ] }, - "execution_count": 22, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df_SBGL_indices = pd.read_parquet(\"../data/sounding/SBGL_indices_1997-01-01_2022-12-31_preprocessed.parquet.gzip\")\n", + "df_SBGL_indices = pd.read_parquet(\"../data/as/SBGL_indices_1997-01-01_2022-12-31_preprocessed.parquet.gzip\")\n", "df_SBGL_indices.head()" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 10, "id": "be63346e", "metadata": {}, "outputs": [ @@ -225,7 +225,7 @@ "(Timestamp('1997-01-01 00:00:00'), Timestamp('2022-12-31 12:00:00'))" ] }, - "execution_count": 23, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -236,7 +236,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 11, "id": "b4da29c4", "metadata": {}, "outputs": [ @@ -415,7 +415,7 @@ "[14890 rows x 6 columns]" ] }, - "execution_count": 24, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -426,7 +426,7 @@ }, { "cell_type": "code", - "execution_count": 127, + "execution_count": 12, "id": "a8fdd5d7", "metadata": {}, "outputs": [ @@ -447,7 +447,7 @@ " dtype='datetime64[ns]', name='Datetime', length=14890, freq=None)" ] }, - "execution_count": 127, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -458,7 +458,7 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": 13, "id": "fd4eee41", "metadata": {}, "outputs": [ @@ -15366,17 +15366,29 @@ }, { "cell_type": "code", - "execution_count": 129, + "execution_count": 14, "id": "ec4bf51c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df_SBGL' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m dates_with_sounding_data \u001b[38;5;241m=\u001b[39m \u001b[43mdf_SBGL\u001b[49m\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mto_series()\u001b[38;5;241m.\u001b[39mapply(\u001b[38;5;28;01mlambda\u001b[39;00m dt: dt\u001b[38;5;241m.\u001b[39mdate())\n", + "\u001b[0;31mNameError\u001b[0m: name 'df_SBGL' is not defined" + ] + } + ], "source": [ "dates_with_sounding_data = df_SBGL.index.to_series().apply(lambda dt: dt.date())" ] }, { "cell_type": "code", - "execution_count": 130, + "execution_count": null, "id": "067648ab", "metadata": {}, "outputs": [ @@ -15409,7 +15421,7 @@ }, { "cell_type": "code", - "execution_count": 131, + "execution_count": null, "id": "5863b119", "metadata": {}, "outputs": [], @@ -15419,7 +15431,7 @@ }, { "cell_type": "code", - "execution_count": 132, + "execution_count": null, "id": "8101b051", "metadata": {}, "outputs": [ @@ -15452,7 +15464,7 @@ }, { "cell_type": "code", - "execution_count": 133, + "execution_count": null, "id": "5f59580b", "metadata": {}, "outputs": [], @@ -15462,7 +15474,7 @@ }, { "cell_type": "code", - "execution_count": 134, + "execution_count": null, "id": "84ebcb0c", "metadata": {}, "outputs": [ @@ -15480,7 +15492,7 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": null, "id": "19755ab3", "metadata": {}, "outputs": [ @@ -15623,7 +15635,7 @@ }, { "cell_type": "code", - "execution_count": 136, + "execution_count": null, "id": "5581a87f", "metadata": {}, "outputs": [ @@ -15646,7 +15658,7 @@ }, { "cell_type": "code", - "execution_count": 137, + "execution_count": null, "id": "bccc6a26", "metadata": {}, "outputs": [ @@ -15836,7 +15848,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "5e2066c4", "metadata": {}, "outputs": [ @@ -15927,7 +15939,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "36c527e4", "metadata": {}, "outputs": [ @@ -15948,7 +15960,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "b4fca5e7", "metadata": {}, "outputs": [ @@ -15969,7 +15981,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "23cc1930", "metadata": {}, "outputs": [ @@ -16007,7 +16019,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "3bbe2580", "metadata": {}, "outputs": [ @@ -16242,7 +16254,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "6649361e", "metadata": {}, "outputs": [ @@ -17307,7 +17319,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "id": "5feed2d5", "metadata": {}, "outputs": [ @@ -17323,10 +17335,10 @@ ], "source": [ "import pandas as pd\n", - "df1 = pd.read_csv(\"../data/sounding/SBGL_1997_2022.csv\")\n", + "df1 = pd.read_csv(\"../data/as/SBGL_1997_2022.csv\")\n", "print(df1.shape)\n", "\n", - "df2 = pd.read_csv(\"../data/sounding/SBGL_2023_2023.csv\")\n", + "df2 = pd.read_csv(\"../data/as/SBGL_2023_2023.csv\")\n", "df2 = df2.drop(columns=[\"LaunchTime\"])\n", "print(df2.shape)\n", "\n", @@ -17336,17 +17348,17 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "73311d83", "metadata": {}, "outputs": [], "source": [ - "df3.to_parquet(\"../data/sounding/SBGL_1997_2023.parquet.gzip\", compression='gzip', index = False)" + "df3.to_parquet(\"../data/as/SBGL_1997_2023.parquet.gzip\", compression='gzip', index = False)" ] }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "id": "9b13f601", "metadata": {}, "outputs": [ @@ -17367,7 +17379,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "ddc7c59b", "metadata": {}, "outputs": [ @@ -17383,13 +17395,13 @@ } ], "source": [ - "df3 = pd.read_parquet(\"../data/sounding/SBGL_1997_2023.parquet.gzip\")\n", + "df3 = pd.read_parquet(\"../data/as/SBGL_1997_2023.parquet.gzip\")\n", "df3.shape" ] }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "id": "2f1e273d", "metadata": {}, "outputs": [ @@ -17472,7 +17484,7 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": null, "id": "70cdc76d", "metadata": {}, "outputs": [ @@ -17493,7 +17505,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": null, "id": "ef2e602e", "metadata": {}, "outputs": [ @@ -17517,7 +17529,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": null, "id": "be3276ee", "metadata": {}, "outputs": [ @@ -18612,7 +18624,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "id": "fd2de3c6", "metadata": {}, "outputs": [ @@ -19055,18 +19067,19 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": null, "id": "8d33536b", "metadata": {}, "outputs": [], "source": [ - "input_file = \"../data/sounding/SBGL_1997_2023.parquet.gzip\"\n", + "import pandas as pd\n", + "input_file = \"../data/as/SBGL_1997_2023.parquet.gzip\"\n", "df_s = pd.read_parquet(input_file)" ] }, { "cell_type": "code", - "execution_count": 112, + "execution_count": null, "id": "1319dbed", "metadata": {}, "outputs": [], @@ -19277,7 +19290,59 @@ "execution_count": null, "id": "56d2ee96", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(77, 15)\n", + "Shape before drop: (77, 15)\n", + "Shape after drop: (77, 15)\n", + "p.shape: (77,)\n", + "T.shape: (77,)\n", + "Td.shape: (77,)\n", + "The several versions of CAPE/CIN:\n", + "137.77700078291787 joule / kilogram -503.9640475863436 joule / kilogram\n", + "0.0 joule / kilogram -503.9640475863436 joule / kilogram\n", + "137.77700078291787 joule / kilogram -503.9640475863436 joule / kilogram\n", + "137.77700078291787 joule / kilogram -503.9640475863436 joule / kilogram\n", + "107.14012325529757 joule / kilogram -473.3271700587233 joule / kilogram\n", + "9.386084317651253 joule / kilogram -473.3271700587233 joule / kilogram\n", + "107.14012325529757 joule / kilogram -473.3271700587233 joule / kilogram\n", + "107.14012325529757 joule / kilogram -473.3271700587233 joule / kilogram\n", + "137.77700078291787 joule / kilogram -503.9640475863436 joule / kilogram\n", + "0.0 joule / kilogram -503.9640475863436 joule / kilogram\n", + "137.77700078291787 joule / kilogram -503.9640475863436 joule / kilogram\n", + "137.77700078291787 joule / kilogram -503.9640475863436 joule / kilogram\n", + "107.14012325529757 joule / kilogram -473.3271700587233 joule / kilogram\n", + "9.386084317651253 joule / kilogram -473.3271700587233 joule / kilogram\n", + "107.14012325529757 joule / kilogram -473.3271700587233 joule / kilogram\n", + "107.14012325529757 joule / kilogram -473.3271700587233 joule / kilogram\n", + "===\n" + ] + }, + { + "ename": "TypeError", + "evalue": "no implementation found for 'numpy.min' on types that implement __array_function__: []", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 6\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;66;03m# df_launch = df_launch.dropna()\u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28mprint\u001b[39m(df_launch\u001b[38;5;241m.\u001b[39mshape)\n\u001b[0;32m----> 6\u001b[0m \u001b[43mprint_indices\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdf_launch\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlaunch_time\u001b[49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[4], line 112\u001b[0m, in \u001b[0;36mprint_indices\u001b[0;34m(df, launch_time)\u001b[0m\n\u001b[1;32m 110\u001b[0m ml_t, ml_td \u001b[38;5;241m=\u001b[39m mpcalc\u001b[38;5;241m.\u001b[39mmixed_layer(p, T, Td, depth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m50\u001b[39m \u001b[38;5;241m*\u001b[39m units\u001b[38;5;241m.\u001b[39mhPa)\n\u001b[1;32m 111\u001b[0m ml_p, _, _ \u001b[38;5;241m=\u001b[39m mpcalc\u001b[38;5;241m.\u001b[39mmixed_parcel(p, T, Td, depth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m50\u001b[39m \u001b[38;5;241m*\u001b[39m units\u001b[38;5;241m.\u001b[39mhPa)\n\u001b[0;32m--> 112\u001b[0m mlcape, mlcin \u001b[38;5;241m=\u001b[39m \u001b[43mmpcalc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmixed_layer_cape_cin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mT\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprof\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdepth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m50\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43munits\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhPa\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 114\u001b[0m \u001b[38;5;66;03m# Compute the characteristics of the most unstable parcel (50-hPa depth)\u001b[39;00m\n\u001b[1;32m 115\u001b[0m mu_p, mu_t, mu_td, _ \u001b[38;5;241m=\u001b[39m mpcalc\u001b[38;5;241m.\u001b[39mmost_unstable_parcel(p, T, Td, depth\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m50\u001b[39m \u001b[38;5;241m*\u001b[39m units\u001b[38;5;241m.\u001b[39mhPa)\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/xarray.py:1330\u001b[0m, in \u001b[0;36mpreprocess_and_wrap..decorator..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 1327\u001b[0m _mutate_arguments(bound_args, units\u001b[38;5;241m.\u001b[39mQuantity, \u001b[38;5;28;01mlambda\u001b[39;00m arg, _: arg\u001b[38;5;241m.\u001b[39mm)\n\u001b[1;32m 1329\u001b[0m \u001b[38;5;66;03m# Evaluate inner calculation\u001b[39;00m\n\u001b[0;32m-> 1330\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# Wrap output based on match and match_unit\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m match \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/units.py:333\u001b[0m, in \u001b[0;36mcheck_units..dec..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 330\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m 331\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 332\u001b[0m _check_units_inner_helper(func, sig, defaults, dims, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/calc/thermo.py:3119\u001b[0m, in \u001b[0;36mmixed_layer_cape_cin\u001b[0;34m(pressure, temperature, dewpoint, **kwargs)\u001b[0m\n\u001b[1;32m 3116\u001b[0m dew_prof \u001b[38;5;241m=\u001b[39m concatenate([parcel_dewpoint, dew_prof])\n\u001b[1;32m 3118\u001b[0m p, t, td, ml_profile \u001b[38;5;241m=\u001b[39m parcel_profile_with_lcl(pressure_prof, temp_prof, dew_prof)\n\u001b[0;32m-> 3119\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcape_cin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mp\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mml_profile\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/xarray.py:1330\u001b[0m, in \u001b[0;36mpreprocess_and_wrap..decorator..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 1327\u001b[0m _mutate_arguments(bound_args, units\u001b[38;5;241m.\u001b[39mQuantity, \u001b[38;5;28;01mlambda\u001b[39;00m arg, _: arg\u001b[38;5;241m.\u001b[39mm)\n\u001b[1;32m 1329\u001b[0m \u001b[38;5;66;03m# Evaluate inner calculation\u001b[39;00m\n\u001b[0;32m-> 1330\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# Wrap output based on match and match_unit\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m match \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/units.py:333\u001b[0m, in \u001b[0;36mcheck_units..dec..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 330\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m 331\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 332\u001b[0m _check_units_inner_helper(func, sig, defaults, dims, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/calc/thermo.py:2430\u001b[0m, in \u001b[0;36mcape_cin\u001b[0;34m(pressure, temperature, dewpoint, parcel_profile, which_lfc, which_el)\u001b[0m\n\u001b[1;32m 2427\u001b[0m parcel_profile \u001b[38;5;241m=\u001b[39m virtual_temperature(parcel_profile, parcel_mixing_ratio)\n\u001b[1;32m 2429\u001b[0m \u001b[38;5;66;03m# Calculate LFC limit of integration\u001b[39;00m\n\u001b[0;32m-> 2430\u001b[0m lfc_pressure, _ \u001b[38;5;241m=\u001b[39m \u001b[43mlfc\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpressure\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdewpoint\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 2431\u001b[0m \u001b[43m \u001b[49m\u001b[43mparcel_temperature_profile\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mparcel_profile\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mwhich\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mwhich_lfc\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2433\u001b[0m \u001b[38;5;66;03m# If there is no LFC, no need to proceed.\u001b[39;00m\n\u001b[1;32m 2434\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m np\u001b[38;5;241m.\u001b[39misnan(lfc_pressure):\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/xarray.py:1330\u001b[0m, in \u001b[0;36mpreprocess_and_wrap..decorator..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 1327\u001b[0m _mutate_arguments(bound_args, units\u001b[38;5;241m.\u001b[39mQuantity, \u001b[38;5;28;01mlambda\u001b[39;00m arg, _: arg\u001b[38;5;241m.\u001b[39mm)\n\u001b[1;32m 1329\u001b[0m \u001b[38;5;66;03m# Evaluate inner calculation\u001b[39;00m\n\u001b[0;32m-> 1330\u001b[0m result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mbound_args\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1332\u001b[0m \u001b[38;5;66;03m# Wrap output based on match and match_unit\u001b[39;00m\n\u001b[1;32m 1333\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m match \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/units.py:333\u001b[0m, in \u001b[0;36mcheck_units..dec..wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 330\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m 331\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapper\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m 332\u001b[0m _check_units_inner_helper(func, sig, defaults, dims, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m--> 333\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/anaconda3/envs/atmoseer/lib/python3.10/site-packages/metpy/calc/thermo.py:724\u001b[0m, in \u001b[0;36mlfc\u001b[0;34m(pressure, temperature, dewpoint, parcel_temperature_profile, dewpoint_start, which)\u001b[0m\n\u001b[1;32m 720\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28many\u001b[39m(idx):\n\u001b[1;32m 721\u001b[0m el_pressure, _ \u001b[38;5;241m=\u001b[39m find_intersections(pressure[\u001b[38;5;241m1\u001b[39m:], parcel_temperature_profile[\u001b[38;5;241m1\u001b[39m:],\n\u001b[1;32m 722\u001b[0m temperature[\u001b[38;5;241m1\u001b[39m:], direction\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdecreasing\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m 723\u001b[0m log_x\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m--> 724\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mel_pressure\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;241m>\u001b[39m this_lcl[\u001b[38;5;241m0\u001b[39m]:\n\u001b[1;32m 725\u001b[0m x \u001b[38;5;241m=\u001b[39m units\u001b[38;5;241m.\u001b[39mQuantity(np\u001b[38;5;241m.\u001b[39mnan, pressure\u001b[38;5;241m.\u001b[39munits)\n\u001b[1;32m 726\u001b[0m y \u001b[38;5;241m=\u001b[39m units\u001b[38;5;241m.\u001b[39mQuantity(np\u001b[38;5;241m.\u001b[39mnan, temperature\u001b[38;5;241m.\u001b[39munits)\n", + "\u001b[0;31mTypeError\u001b[0m: no implementation found for 'numpy.min' on types that implement __array_function__: []" + ] + } + ], "source": [ "launch_time = datetime(2014, 2, 9, 0)\n", "df_launch = df_s[pd.to_datetime(df_s['time']) == launch_time]\n", @@ -19289,7 +19354,7 @@ }, { "cell_type": "code", - "execution_count": 118, + "execution_count": null, "id": "45a9b35c", "metadata": {}, "outputs": [ @@ -19371,7 +19436,7 @@ }, { "cell_type": "code", - "execution_count": 116, + "execution_count": null, "id": "df63ed4e", "metadata": {}, "outputs": [ @@ -19392,7 +19457,7 @@ }, { "cell_type": "code", - "execution_count": 117, + "execution_count": null, "id": "e4bff916", "metadata": {}, "outputs": [ @@ -19962,7 +20027,7 @@ }, { "cell_type": "code", - "execution_count": 109, + "execution_count": null, "id": "01863fde", "metadata": {}, "outputs": [ @@ -20029,7 +20094,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": null, "id": "9a3cba6f", "metadata": {}, "outputs": [ @@ -20091,7 +20156,7 @@ }, { "cell_type": "code", - "execution_count": 119, + "execution_count": null, "id": "453985b6", "metadata": {}, "outputs": [ @@ -20113,7 +20178,7 @@ }, { "cell_type": "code", - "execution_count": 120, + "execution_count": null, "id": "5b20b612", "metadata": {}, "outputs": [ @@ -20142,7 +20207,7 @@ }, { "cell_type": "code", - "execution_count": 121, + "execution_count": null, "id": "0a377146", "metadata": {}, "outputs": [ @@ -20195,7 +20260,7 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": null, "id": "36ed0d8a", "metadata": {}, "outputs": [ @@ -20268,7 +20333,7 @@ }, { "cell_type": "code", - "execution_count": 127, + "execution_count": null, "id": "dc61809d", "metadata": {}, "outputs": [], @@ -20278,7 +20343,7 @@ }, { "cell_type": "code", - "execution_count": 129, + "execution_count": null, "id": "62234ac2", "metadata": {}, "outputs": [ @@ -20589,7 +20654,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "981fb5f9", "metadata": {}, "outputs": [ @@ -20734,7 +20799,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "dbfed559", "metadata": {}, "outputs": [ @@ -20774,7 +20839,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "8173d57b", "metadata": {}, "outputs": [ @@ -21074,7 +21139,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "eae35a72", "metadata": {}, "outputs": [], @@ -21148,7 +21213,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "d3ec1c29", "metadata": {}, "outputs": [ @@ -21328,7 +21393,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "88cb994f", "metadata": {}, "outputs": [ @@ -21508,7 +21573,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "4ae86ac2", "metadata": {}, "outputs": [ @@ -21688,7 +21753,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "2f292cfb", "metadata": {}, "outputs": [ @@ -21881,7 +21946,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/notebooks/train_model_autoencode.ipynb b/notebooks/sounding/train_model_autoencode.ipynb similarity index 100% rename from notebooks/train_model_autoencode.ipynb rename to notebooks/sounding/train_model_autoencode.ipynb diff --git a/notebooks/stconvs2s.ipynb b/notebooks/stconvs2s.ipynb new file mode 100644 index 00000000..059b6e66 --- /dev/null +++ b/notebooks/stconvs2s.ipynb @@ -0,0 +1,3084 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import sys" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "import argparse\n", + "from datetime import datetime\n", + "import glob\n", + "import numpy as np\n", + "import xarray as xr\n", + "import re\n", + "\n", + "def process_single_day(files):\n", + " \"\"\"\n", + " Processa os arquivos de um único dia e retorna um dataset combinado.\n", + " \"\"\"\n", + " daily_datasets = []\n", + "\n", + " for file_path in files:\n", + " ds = xr.open_dataset(file_path)\n", + "\n", + " time_stamps = []\n", + " data_arrays = []\n", + "\n", + " for var_name in ds.variables:\n", + " match = re.search(r'CMI_(\\d{4}_\\d{2}_\\d{2}_\\d{2}_\\d{2})', var_name)\n", + " if match:\n", + " timestamp_str = match.group(1)\n", + " timestamp = np.datetime64(\n", + " f\"{timestamp_str[:4]}-{timestamp_str[5:7]}-{timestamp_str[8:10]}T{timestamp_str[11:13]}:{timestamp_str[14:]}\"\n", + " )\n", + " time_stamps.append(timestamp)\n", + "\n", + " var_data = ds[var_name].rename({\n", + " f'dim_0_{var_name}': 'lat',\n", + " f'dim_1_{var_name}': 'lon'\n", + " })\n", + " data_arrays.append(var_data)\n", + "\n", + " time_array = xr.DataArray(\n", + " np.array(time_stamps, dtype='datetime64[ns]'),\n", + " dims='time'\n", + " )\n", + " daily_data = xr.concat(data_arrays, dim=time_array)\n", + "\n", + " daily_data = daily_data.assign_coords(lat=np.arange(daily_data.sizes['lat']),\n", + " lon=np.arange(daily_data.sizes['lon']))\n", + "\n", + " daily_datasets.append(daily_data)\n", + "\n", + " # Concatenar todos os datasets do dia ao longo da dimensão 'time'\n", + " combined_day = xr.concat(daily_datasets, dim='time')\n", + " combined_day = combined_day.sortby('time') # Ordenar por timestamps\n", + "\n", + " return combined_day\n", + "\n", + "\n", + "def collect_samples(combined_data, TIMESTEP, max_gap):\n", + " \"\"\"\n", + " Coleta os samples de um dataset baseado em janelas de tempo e considera todas as bandas.\n", + " \n", + " Parâmetros:\n", + " combined_data: xarray.Dataset - Dataset combinado com as dimensões `time` e `channel`.\n", + " TIMESTEP: int - Número de timestamps por sample.\n", + " max_gap: int - Máximo intervalo permitido entre timestamps consecutivos (em minutos).\n", + " \n", + " Retorna:\n", + " xarray.Dataset - Dataset contendo os samples X e Y.\n", + " \"\"\"\n", + " total_time = combined_data.sizes['time']\n", + "\n", + " X_samples = []\n", + " Y_samples = []\n", + "\n", + " for i in range(total_time - TIMESTEP):\n", + " # Coleta do sample X\n", + " X_sample = combined_data.isel(time=slice(i, i + TIMESTEP)).assign_coords(\n", + " time=combined_data.time.isel(time=slice(i, i + TIMESTEP))\n", + " )\n", + " max_gap_X = check_max_gap(X_sample)\n", + "\n", + " # Coleta do sample Y\n", + " Y_sample = combined_data.isel(time=slice(i + 1, i + 1 + TIMESTEP)).assign_coords(\n", + " time=combined_data.time.isel(time=slice(i + 1, i + 1 + TIMESTEP))\n", + " )\n", + " max_gap_Y = check_max_gap(Y_sample)\n", + "\n", + " # Verificar gaps\n", + " if max_gap_X > max_gap:\n", + " print(f'Timestamp faltando no X_sample: {X_sample.time.values}')\n", + " continue\n", + " elif max_gap_Y > max_gap:\n", + " print(f'Timestamp faltando no Y_sample: {Y_sample.time.values}')\n", + " continue\n", + "\n", + " # Adicionar os samples válidos\n", + " X_samples.append(X_sample)\n", + " Y_samples.append(Y_sample)\n", + "\n", + " # Concatenar os samples ao longo da dimensão 'sample'\n", + " X_samples = xr.concat(X_samples, dim='sample')\n", + " Y_samples = xr.concat(Y_samples, dim='sample')\n", + "\n", + " # Dataset final contendo X e Y\n", + " combined_samples = xr.Dataset({'x': X_samples, 'y': Y_samples})\n", + "\n", + " return combined_samples\n", + "\n", + "def check_max_gap(sample):\n", + " \"\"\"\n", + " Calcula a maior diferença entre timestamps consecutivos dentro de um sample.\n", + " \n", + " Parâmetros:\n", + " sample: xarray.Dataset - Dataset contendo a dimensão `time`.\n", + " \n", + " Retorna:\n", + " int - O maior intervalo de tempo (em minutos) entre timestamps consecutivos.\n", + " \"\"\"\n", + " times = sample.time.values\n", + " gaps = np.diff(times).astype('timedelta64[m]').astype(int) # Diferenças em minutos\n", + " return np.max(gaps) if len(gaps) > 0 else 0\n", + "\n", + "def main(path, max_gap, features, output):\n", + " TIMESTEP = 5\n", + " files = glob.glob(path)\n", + " files.sort()\n", + " # print(files)\n", + "\n", + " # Organizar arquivos por dia\n", + " days = {}\n", + " for file in files:\n", + " # print(file)\n", + " day = re.search(r'(\\d{4}_\\d{2}_\\d{2})', file).group(1)\n", + " if day not in days:\n", + " days[day] = []\n", + " days[day].append(file)\n", + "\n", + " # print(days)\n", + " # sys.exit(1)\n", + "\n", + " # Processar cada dia\n", + " for day, day_files in days.items():\n", + " print(f\"Processando o dia: {day}...\")\n", + "\n", + " band_datasets = []\n", + " for feature in features:\n", + " band_files = [file for file in day_files if f\"{feature}\" in file]\n", + " if not band_files:\n", + " print(f\"Sem arquivos encontrados para a feature {feature} no dia {day}\")\n", + " continue\n", + "\n", + " daily_dataset = process_single_day(band_files)\n", + " band_datasets.append(daily_dataset)\n", + "\n", + " if band_datasets:\n", + " combined_day = xr.concat(band_datasets, dim='channel')\n", + " combined_day = combined_day.assign_coords(channel=('channel', features))\n", + "\n", + " # Coletar samples do dia\n", + " daily_samples = collect_samples(combined_day, TIMESTEP, max_gap)\n", + "\n", + " # Salvar os samples por dia\n", + " daily_output_path = f\"{output}/{day}_samples.nc\"\n", + " daily_samples.to_netcdf(daily_output_path)\n", + " print(f\"Samples do dia {day} salvos em {daily_output_path}\")\n", + " else:\n", + " print(f\"Nenhum dataset processado para o dia {day}.\")\n", + " \n", + " print(\"\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Processando o dia: 2023_10_31...\n", + "Samples do dia 2023_10_31 salvos em output/2023_10_31_samples.nc\n", + "\n", + "Processando o dia: 2024_01_13...\n", + "Samples do dia 2024_01_13 salvos em output/2024_01_13_samples.nc\n", + "\n", + "Processando o dia: 2024_07_07...\n", + "Samples do dia 2024_07_07 salvos em output/2024_07_07_samples.nc\n", + "\n" + ] + } + ], + "source": [ + "path = \"../features/CMI/*/*/*.nc\"\n", + "max_gap = 30\n", + "features = ['dF_dt']\n", + "output = \"output\"\n", + "main(path, max_gap, features, output)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "var name: time\n", + "[ 0 10 20 30 40 50 60 70 80 90 100 110 120 130\n", + " 140 150 160 170 180 190 200 210 220 230 240 250 260 270\n", + " 280 290 300 310 320 330 340 350 360 370 380 390 400 410\n", + " 420 430 440 450 460 470 480 490 500 510 520 530 540 550\n", + " 560 570 580 590 600 610 620 630 640 650 660 670 680 690\n", + " 700 710 720 730 740 750 760 770 780 790 800 810 820 830\n", + " 840 850 860 870 880 890 900 910 920 930 940 950 960 970\n", + " 980 990 1000 1010 1020 1030 1040 1050 1060 1070 1080 1090 1100 1110\n", + " 1120 1130 1140 1150 1160 1170 1180 1190 1200 1210 1220 1230 1240 1250\n", + " 1260 1270 1280 1290 1300 1310 1320 1330 1340 1350 1360 1370 1380 1390\n", + " 1400 1410 1420]\n", + "var name: lat\n", + "[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n", + " 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n", + " 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71\n", + " 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93]\n", + "var name: lon\n", + "[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17\n", + " 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35\n", + " 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53\n", + " 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71\n", + " 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89\n", + " 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107\n", + " 108 109 110 111 112 113 114 115 116 117 118 119 120]\n", + "var name: channel\n", + "['dF_dt']\n", + "var name: 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0.276541143655777 -0.165924072265625 0.0737457275390625]\n", + " ...\n", + " [0.5592254400253296 0.29497528076171875 0.33184814453125 ...\n", + " 0.09217987209558487 0.03687286376953125 0.03687133640050888]\n", + " [0.6944229006767273 0.497772216796875 0.4424636960029602 ...\n", + " 0.11676178127527237 0.04301757737994194 0.02458038367331028]\n", + " [0.7435836791992188 0.6329681277275085 0.5407882928848267 ...\n", + " 0.04916229099035263 0.0 0.0]]\n", + "\n", + " [[0.22737732529640198 0.497772216796875 0.497772216796875 ...\n", + " -1.0938689708709717 -1.4871704578399658 -1.2720855474472046]\n", + " [0.6944214105606079 0.26424866914749146 0.33184814453125 ...\n", + " -0.786602795124054 -0.786602795124054 0.27653807401657104]\n", + " [0.33184814453125 0.22737732529640198 0.3625732362270355 ... 0.0\n", + " -0.03072815015912056 -0.03687133640050888]\n", + " ...\n", + " [0.4977706968784332 0.22737732529640198 0.09217987209558487 ...\n", + " 0.08603362739086151 0.12905120849609375 0.06145324558019638]\n", + " [0.6022430658340454 0.3564300537109375 0.15363311767578125 ...\n", + " 0.08603362739086151 0.09217987209558487 0.12905272841453552]\n", + " [0.6145340204238892 0.4486099183559418 0.31341248750686646 ...\n", + " 0.10447082668542862 0.1351974457502365 0.1351974457502365]]]]]\n" + ] + } + ], + "source": [ + "import netCDF4 as nc\n", + "dataset = nc.Dataset('output/2024_01_13_samples.nc')\n", + "\n", + "for variable_name in dataset.variables.keys():\n", + " print(f'var name: {variable_name}')\n", + " data = dataset.variables[variable_name][:]\n", + " print(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['time', 'lat', 'lon', 'channel', 'x', 'y'])" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.variables.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "var name: CMI_2024_01_13_03_00\n", + "[[-0.23966828 -0.2949768 -0.2949768 ... -0.55922544 -0.03072815\n", + " -0.30726624]\n", + " [-0.05530853 -0.29497528 -0.48548126 ... -0.15363464 -0.15363464\n", + " -0.4486084 ]\n", + " [ 0.16592255 0.11676178 -0.3748657 ... -0.08603515 -0.0921814\n", + " 0.16592407]\n", + " ...\n", + " [ 0.06759949 0.06759796 -0.03072662 ... 0.06145325 0.12290649\n", + " 0.17821503]\n", + " [ 0.06145325 0.0737442 0.00614624 ... 0.06145325 0.10447083\n", + " 0.10447083]\n", + " [ 0.12290649 0.06759796 0.0737442 ... 0.11061554 0.12905273\n", + " 0.12905273]]\n", + "var name: CMI_2024_01_13_03_30\n", + "[[ 0.00614624 0.00614471 0.00614471 ... 0.12905273 0.3748657\n", + " 0.28883058]\n", + " [-0.00614471 0.14134216 0.09832611 ... 0.42402953 0.42402953\n", + " -0.16592407]\n", + " [ 0.13519745 0.21508637 0.11061706 ... -0.01843567 -0.06145325\n", + " -0.03072815]\n", + " ...\n", + " [ 0. 0.20894012 0.18435974 ... 0.19050446 0.1966507\n", + " 0.17207031]\n", + " [ 0.11676178 0.27653962 0.17821503 ... 0.20279694 0.15977784\n", + " 0.12905121]\n", + " [ 0.17821503 0.27653962 0.17206879 ... 0.16592407 0.16592407\n", + " 0.16592407]]\n", + "var name: CMI_2024_01_13_05_00\n", + "[[-0.3625763 -0.13519745 -0.13519745 ... 0.25810242 0.49777222\n", + " 0.8357666 ]\n", + " [-0.00614624 0.06145477 0.35642853 ... 0.5162079 0.5162079\n", + " 0.23352051]\n", + " [-0.06759949 0.00614624 0.01843567 ... 0.23352356 0.15363464\n", + " -0.24581298]\n", + " ...\n", + " [ 0.36257476 0.03072662 -0.21508637 ... 0.0307251 -0.23352356\n", + " -0.33799133]\n", + " [ 0.06145325 -0.58380586 -0.7620209 ... 0.10447083 -0.06759949\n", + " 0.12290649]\n", + " [-0.06759644 -0.35643005 -0.28883058 ... 0.27654114 0.2949768\n", + " 0.2949768 ]]\n", + "var name: CMI_2024_01_13_01_00\n", + "[[ 0.19050598 -0.12290649 -0.12290649 ... 0.38101044 0.33799285\n", + " 0.27653962]\n", + " [ 0.09217834 -0.02458191 -0.18435974 ... 0.55308074 0.55308074\n", + " 0.24581298]\n", + " [-0.11061402 0.07988892 0.1536316 ... 0.20279542 0.35642853\n", + " 0.11676178]\n", + " ...\n", + " [-0.18435974 0.09217987 0.11676178 ... 0.22737733 0.20279542\n", + " 0.20894012]\n", + " [-0.36257476 -0.06145325 0.04916229 ... 0.20279542 0.22737733\n", + " 0.18435974]\n", + " [-0.43017274 -0.1474884 -0.00614624 ... 0.24581298 0.15363312\n", + " 0.15363312]]\n", + "var name: CMI_2024_01_13_02_00\n", + "[[ 0.38715667 0.30112305 0.30112305 ... 0.30726928 0.56536865\n", + " 1.776001 ]\n", + " [ 0.17207031 0.2949768 0.20894165 ... 0.7558777 0.7558777\n", + " 1.4318634 ]\n", + " [-0.32570496 0.04916077 0.43017274 ... 0.87878263 1.1000137\n", + " 0.33799285]\n", + " ...\n", + " [ 0.08603515 0.0737442 0.00614624 ... 0.45475465 0.2642502\n", + " 0.32570344]\n", + " [ 0.0184372 0.06145325 0.14134216 ... 0.3748657 0.21508789\n", + " 0.25810394]\n", + " [ 0.07988892 0.11676178 0.20894165 ... 0.17207031 0.16592407\n", + " 0.16592407]]\n", + "var name: CMI_2024_01_13_00_00\n", + "[[ 0.5223541 0.41173553 0.41173553 ... -0.12290649 -0.57766116\n", + " -0.41173705]\n", + " [ 0.44860992 0.35028535 0.00614471 ... -0.31955567 -0.31955567\n", + " 0.1474884 ]\n", + " [ 0.368721 0.18435974 0.06145325 ... -0.02458191 0.2396698\n", + " -0.06145325]\n", + " ...\n", + " [ 0.46089935 0.368721 0.15363312 ... -0.02458038 -0.01229095\n", + " 0.22123261]\n", + " [ 0.1966507 0.11676178 -0.03072662 ... 0.09217987 0.02458191\n", + " 0.06759796]\n", + " [-0.03072662 -0.04301758 0. ... 0.13519745 0.12290649\n", + " 0.12290649]]\n", + "var name: CMI_2024_01_13_03_50\n", + "[[ 0.09832611 0.11676025 0.11676025 ... -0.16592407 -0.19665222\n", + " -0.35643005]\n", + " [ 0.03687134 0.0737442 0.21508637 ... -0.84190977 -0.84190977\n", + " -0.6759857 ]\n", + " [ 0. 0.04301758 0.1474884 ... -1.6715301 -0.9340881\n", + " -0.46704406]\n", + " ...\n", + " [-0.2703949 -0.01843567 0.22737733 ... 0.26424867 0.31341094\n", + " 0.3195572 ]\n", + " [-0.04916382 0.15363312 0.28883058 ... 0.30726776 0.35642853\n", + " 0.2949768 ]\n", + " [ 0.04301758 0.23966828 0.28268433 ... 0.32570344 0.2703949\n", + " 0.2703949 ]]\n", + "var name: CMI_2024_01_13_08_00\n", + "[[ 0.48548126 0.5346451 0.5346451 ... 0.09217834 0.71285707\n", + " 0.94023436]\n", + " [ 0.17206879 0.20279542 0.22737733 ... 0.70671386 0.70671386\n", + " 0.5162079 ]\n", + " [-0.08603515 0.01229095 0.1782135 ... 0.6268219 0.55307925\n", + " 0.3687195 ]\n", + " ...\n", + " [ 0.0737442 0.04916229 -0.19050598 ... 0.3625763 0.48547974\n", + " 0.2949768 ]\n", + " [-0.46089783 -1.1860473 -0.5653702 ... 0.41174012 0.2949768\n", + " 0.00614624]\n", + " [-0.17207031 -2.009523 -1.9173447 ... 0.04916382 0.00614319\n", + " 0.00614319]]\n", + "var name: CMI_2024_01_13_00_10\n", + "[[ 0.08603211 0.38715822 0.38715822 ... 0.5100616 0.33184814\n", + " 0.22123107]\n", + " [ 0.03072815 0.27653807 0.3748657 ... -0.41173705 -0.41173705\n", + " -0.2396698 ]\n", + " [ 0.11061402 0.3134125 0.33184814 ... -0.7681656 -0.21508789\n", + " 0.10447083]\n", + " ...\n", + " [ 0.49777222 0.22123107 0.16592407 ... 0.09832458 0.22123261\n", + " 0. ]\n", + " [ 0.5899521 0.43017274 0.38101044 ... 0.05530853 0.20894012\n", + " 0.08603515]\n", + " [ 0.36257324 0.17206879 0.04301605 ... 0.0737442 0.06145325\n", + " 0.06145325]]\n", + "var name: CMI_2024_01_13_03_20\n", + "[[-0.00614624 0. 0. ... -0.04916077 -0.48547974\n", + " -0.23966675]\n", + " [ 0.09217987 0.01229095 -0.23352356 ... -0.2703949 -0.2703949\n", + " 0.11676331]\n", + " [ 0.13519745 0. -0.30726776 ... 0.01228943 0.1536316\n", + " 0.19665222]\n", + " ...\n", + " [ 0.19050598 0.17821503 0.10447083 ... 0.21508789 0.23352356\n", + " 0.20894165]\n", + " [ 0.19664916 0.15977935 0.07374267 ... 0.18435974 0.21508789\n", + " 0.19050598]\n", + " [ 0.14748688 0.12290649 0.10447083 ... 0.15977935 0.12290649\n", + " 0.12290649]]\n", + "var name: CMI_2024_01_13_05_10\n", + "[[ 0.3257019 0.14134368 0.14134368 ... -1.450299 -0.25195923\n", + " 0.33184814]\n", + " [ 0.30112305 0.23966675 0.06759949 ... -0.3687195 -0.3687195\n", + " -0.09217834]\n", + " [ 0.06759949 -0.16592407 -0.23966828 ... 0.30726624 0.04916077\n", + " -0.15363464]\n", + " ...\n", + " [ 0.11061554 0.11061554 0.10447083 ... -0.02458191 -0.00614624\n", + " -0.02458191]\n", + " [ 0.12290649 -0.12905273 -0.23352203 ... 0.05530701 0.02458191\n", + " 0.23966675]\n", + " [-0.368721 -0.60838777 -0.8664917 ... 0.2703949 0.26424867\n", + " 0.26424867]]\n", + "var name: CMI_2024_01_13_02_10\n", + "[[-0.30726624 -0.35028535 -0.35028535 ... 0.48547974 0.50391847\n", + " 0.27654114]\n", + " [-0.11676025 -0.4178833 -0.21508789 ... 0.9771088 0.9771088\n", + " 0.78045654]\n", + " [ 0.18435974 -0.39329833 -0.54078674 ... 1.4072815 1.2966659\n", + " 1.6162231 ]\n", + " ...\n", + " [ 0.07988892 0.04301605 0.13519593 ... 0.18435974 0.22737733\n", + " 0.26424867]\n", + " [ 0.03072662 0.03072662 0.01229095 ... 0.15363312 0.17206879\n", + " 0.18435974]\n", + " [ 0.03072662 -0.15977935 -0.1966507 ... 0.07988892 0.22123107\n", + " 0.22123107]]\n", + "var name: CMI_2024_01_13_09_00\n", + "[[-0.1474884 -0.55922544 -0.55922544 ... -0.02458191 0.35642853\n", + " -1.2782272 ]\n", + " [ 0.25810242 -0.10447083 -0.28883058 ... -0.24581298 -0.24581298\n", + " -1.2106323 ]\n", + " [ 0.37486267 0.28883058 0.03072815 ... -0.28883058 -0.79274595\n", + " -0.99554443]\n", + " ...\n", + " [ 0.17821655 0.47933656 0.94023436 ... 0.11061706 0.5653702\n", + " 0.6391144 ]\n", + " [ 0.20279542 0.6759888 1.5793488 ... 0.26424712 0.38715667\n", + " 0.46090087]\n", + " [ 0.22123107 0.68213195 1.3704071 ... -0.14134216 0.06759796\n", + " 0.06759796]]\n", + "var name: CMI_2024_01_13_03_40\n", + "[[ 0.19050446 0.21508789 0.21508789 ... 0.356427 0.20894165\n", + " 0.22123107]\n", + " [ 0.21508637 0.25810394 0.26424867 ... -0.3134125 -0.3134125\n", + " -0.02458191]\n", + " [ 0.13519745 0.25810394 0.29497528 ... -0.38715515 -0.3379944\n", + " -0.34413758]\n", + " ...\n", + " [-0.10447083 0.05530853 0.25195923 ... 0.20279694 0.21508637\n", + " 0.24581298]\n", + " [-0.12905121 0.1474884 0.2703949 ... 0.20894012 0.25195923\n", + " 0.2703949 ]\n", + " [-0.0737442 0.15977784 0.30726776 ... 0.20279542 0.18435974\n", + " 0.18435974]]\n", + "var name: CMI_2024_01_13_07_00\n", + "[[-0.95867157 -0.32570344 -0.32570344 ... -0.41788024 -1.038559\n", + " -0.46090087]\n", + " [-1.1676133 -1.394989 -0.09832458 ... -1.4257171 -1.4257171\n", + " -0.8849274 ]\n", + " [-0.9955429 -1.4502976 -0.49162903 ... -0.95252687 -1.4441528\n", + " -0.8787842 ]\n", + " ...\n", + " [ 0.44860992 0.8111847 0.78045654 ... -0.1782135 -0.33184814\n", + " -0.46704406]\n", + " [ 0.6882782 0.9771072 0.8910736 ... -0.28268433 -0.23966675\n", + " -0.42402953]\n", + " [ 0.81118315 0.9095093 0.39944458 ... -0.22737733 -0.33184814\n", + " -0.33184814]]\n", + "var name: CMI_2024_01_13_01_30\n", + "[[ 0.03687134 0.54693604 0.54693604 ... 0.43631896 1.1245956\n", + " -0.12290649]\n", + " [ 0.03687134 0.3748657 0.38715822 ... 1.0447067 1.0447067\n", + " -0.38715515]\n", + " [-0.11676331 0.21508484 0.36257324 ... 1.2229202 -0.22737733\n", + " -0.2519577 ]\n", + " ...\n", + " [ 0.04301758 -0.03072662 -0.04916229 ... 0.06145325 0.0737442\n", + " 0.20894165]\n", + " [ 0.11676178 0.09832458 0.08603363 ... 0.03687286 0.05530853\n", + " 0.22123107]\n", + " [ 0.19050598 0.15363312 0.15363312 ... 0.11676178 0.18435974\n", + " 0.18435974]]\n", + "var name: CMI_2024_01_13_01_20\n", + "[[ 0.25195923 -0.54693604 -0.54693604 ... 0.77431184 -0.49777222\n", + " 0. ]\n", + " [ 0.24581298 -0.17206725 -0.16592407 ... -0.3134125 -0.3134125\n", + " 0.14748688]\n", + " [ 0.22123413 -0.15977784 -0.33184814 ... -0.7927475 0.27653962\n", + " 0.3748642 ]\n", + " ...\n", + " [-0.03687134 -0.01228943 0.04301758 ... 0.26424867 0.08603363\n", + " 0.09217987]\n", + " [-0.03072662 -0.00614471 0.0184372 ... 0.23352203 0.11061554\n", + " 0.13519745]\n", + " [-0.07989044 0.01229095 0.10447083 ... 0.15977784 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0.04916229 0.08603515\n", + " -0.03687286]\n", + " [ 0.19050598 0.09217987 0.03072662 ... 0.01229095 0.01229095\n", + " 0.01229095]]\n", + "var name: CMI_2024_01_13_21_30\n", + "[[-0.01228943 -0.04301758 -0.04301758 ... 0.1536316 0.34413758\n", + " 0.7620209 ]\n", + " [ 0.01843567 -0.01843567 0.03687134 ... 0.20279542 0.20279542\n", + " -0.03072815]\n", + " [ 0.06759644 0.05531006 0.06759644 ... 0.30726624 0.38100892\n", + " -0.10447083]\n", + " ...\n", + " [ 0.23966675 0.15977784 0.27654114 ... 0.22737733 0.13519745\n", + " 0.17207031]\n", + " [ 0.25810394 0.19050446 0.15977784 ... 0.25810394 0.22123261\n", + " 0.15977935]\n", + " [ 0.3257019 0.22737733 0.14134368 ... 0.20279542 0.20279542\n", + " 0.20279542]]\n", + "var name: CMI_2024_01_13_22_30\n", + "[[ 0.26424867 -0.18435974 -0.18435974 ... -0.28883058 -0.49162596\n", + " -0.2396698 ]\n", + " [ 0.2949768 0.20894165 0.10447083 ... -0.49162596 -0.49162596\n", + " -0.4731903 ]\n", + " [-0.19050598 -0.15977784 -0.01228943 ... -0.36872253 -0.3933014\n", + " -0.17821655]\n", + " ...\n", + " [-0.07988892 -0.09832458 0.03072662 ... -0.08603363 0.03687286\n", + " 0.16592407]\n", + " [-0.09832611 -0.07988892 0.08603515 ... 0. 0.05530853\n", + " 0.25195923]\n", + " [-0.11676178 0.03072662 0.15977784 ... 0.18435974 0.12290649\n", + " 0.12290649]]\n", + "var name: CMI_2024_01_13_22_40\n", + "[[-0.19050598 0.34413758 0.34413758 ... -0.12290649 0.1536316\n", + " 0.7497314 ]\n", + " [ 0.16592407 0.34413758 0.14134216 ... 0.11676025 0.11676025\n", + " 0.34413758]\n", + " [ 0.48548278 0.36257324 0.13519593 ... -0.19050293 0.3134125\n", + " 0.45475465]\n", + " ...\n", + " [ 0.06759796 0.09217987 0.10447083 ... 0. -0.03687286\n", + " 0.17821503]\n", + " [ 0. 0.02458038 0.04301758 ... 0.0737442 0.07988892\n", + " 0.28883058]\n", + " [-0.06145325 -0.11676178 0.01229095 ... 0. 0.15977784\n", + " 0.15977784]]\n", + "var name: CMI_2024_01_13_22_50\n", + "[[-0.25810546 -0.31955567 -0.31955567 ... -0.36257324 -0.5223541\n", + " -0.57766116]\n", + " [-0.11061706 -0.26424867 -0.4486084 ... -0.53464353 -0.53464353\n", + " -0.7190033 ]\n", + " [ 0.25195923 0.07374573 -0.23966675 ... -1.0508515 -0.82962036\n", + " -0.33184814]\n", + " ...\n", + " [ 0. 0.01843567 0.01229095 ... 0.06759796 0.06145325\n", + " -0.02458191]\n", + " [ 0.00614624 0.04301758 0. ... 0.09217987 0.\n", + " 0.01843567]\n", + " [-0.0737442 -0.00614471 -0.02458038 ... 0.22737733 0.33184814\n", + " 0.33184814]]\n", + "var name: CMI_2024_01_13_22_20\n", + "[[-0.38715515 -0.5100616 -0.5100616 ... -0.18435974 -0.20894165\n", + " 0.11061706]\n", + " [-0.11676025 -0.48548278 -0.20894165 ... -0.27654114 -0.27654114\n", + " 1.1000122 ]\n", + " [ 0.16592407 0.20279542 -0.04301758 ... 0.13519898 0.546933\n", + " 0.60838926]\n", + " ...\n", + " [ 0.04916229 0.12290649 0.07374267 ... 0.27039337 0.23966828\n", + " 0.02458038]\n", + " [ 0.09217987 0.16592407 0.15977784 ... 0.24581298 0.24581298\n", + " -0.08603515]\n", + " [ 0.18435974 0.1966507 0.22737733 ... 0.16592407 0.04916229\n", + " 0.04916229]]\n", + "var name: CMI_2024_01_13_23_10\n", + "[[ 0.11061402 0.19665222 0.19665222 ... 0.5960968 0.626825\n", + " 0.63297117]\n", + " [-0.01229248 0.02458191 0.30111998 ... 0.10447083 0.10447083\n", + " -0.24581298]\n", + " [-0.0921814 -0.14134216 0.10447083 ... -0.10447083 -0.00614624\n", + " -0.08603515]\n", + " ...\n", + " [ 0.21508637 0.21508637 0.17206879 ... 0.04301758 0.04301605\n", + " 0.03072662]\n", + " [ 0.23352356 0.19050446 0.17206879 ... 0.06145325 0.01229095\n", + " 0.09832458]\n", + " [ 0.33184814 0.23352356 0.19050446 ... 0.08603363 0.0737442\n", + " 0.0737442 ]]\n", + "var name: CMI_2024_01_13_22_10\n", + "[[-0.27653807 -0.04301758 -0.04301758 ... -0.04301758 0.19665222\n", + " -0.68213195]\n", + " [-0.53464353 -0.22737733 0.11061706 ... 0.60224307 0.60224307\n", + " -0.89107054]\n", + " [-0.3257019 -0.38100892 -0.03072815 ... 1.1368866 -0.16592407\n", + " -0.80503845]\n", + " ...\n", + " [ 0.10447083 0.22737733 0.23352356 ... -0.01843567 -0.11676178\n", + " -0.08603363]\n", + " [ 0.22123261 0.30112153 0.27654114 ... -0.04916229 -0.0737442\n", + " -0.03687134]\n", + " [ 0.28883058 0.28268585 0.19050598 ... 0.02458038 -0.04916229\n", + " -0.04916229]]\n", + "var name: CMI_2024_01_13_23_20\n", + "[[-0.5100616 -0.27654114 -0.27654114 ... -0.05530701 0.25810242\n", + " 0.7866028 ]\n", + " [-0.24581298 0.13519898 0.17207031 ... 0.22123107 0.22123107\n", + " 0.7866028 ]\n", + " [-0.06145325 0.15363464 0.15363464 ... -0.09832458 0.54693604\n", + " 0.24581298]\n", + " ...\n", + " [ 0.36257476 0.36257476 0.36257476 ... 0.09832611 0.08603515\n", + " 0.10447083]\n", + " [ 0.46704406 0.38101044 0.33799285 ... 0.03072662 0.05530701\n", + " -0.02458038]\n", + " [ 0.43631896 0.4424637 0.38715667 ... 0.01229095 0.01228943\n", + " 0.01228943]]\n", + "var name: CMI_2024_01_13_23_30\n", + "[[ 0.5285004 0. 0. ... -0.9095093 -0.09217834\n", + " 0.09832458]\n", + " [-0.09832458 -0.13519898 -0.15363464 ... 0.28268737 0.28268737\n", + " -0.10447083]\n", + " [-0.06145325 0. 0.06759949 ... 0.27654114 -0.16592407\n", + " 0.07374573]\n", + " ...\n", + " [ 0.55922544 0.29497528 0.33184814 ... 0.09217987 0.03687286\n", + " 0.03687134]\n", + " [ 0.6944229 0.49777222 0.4424637 ... 0.11676178 0.04301758\n", + " 0.02458038]\n", + " [ 0.7435837 0.6329681 0.5407883 ... 0.04916229 0.\n", + " 0. ]]\n", + "var name: CMI_2024_01_13_06_20\n", + "[[ 0.13519593 -0.08603515 -0.08603515 ... 0.15363464 1.0754334\n", + " 0.9709625 ]\n", + " [-0.04301758 -0.23352356 -0.21508789 ... 0.92180175 0.92180175\n", + " 1.0815766 ]\n", + " [ 0.07988892 -0.06145325 -0.03687134 ... 0.02458191 0.6145355\n", + " 0.6759888 ]\n", + " ...\n", + " [-0.33184966 -0.356427 -0.2949768 ... 0.10447083 0.45475465\n", + " 0.5715149 ]\n", + " [-0.25810242 -0.2949768 -0.05531006 ... 0.1474884 0.27654114\n", + " 0.44246215]\n", + " [-0.64526063 -0.33184814 0.25195923 ... 0.737442 0.52849734\n", + " 0.52849734]]\n", + "var name: CMI_2024_01_13_23_40\n", + "[[ 0.22737733 0.49777222 0.49777222 ... -1.093869 -1.4871705\n", + " -1.2720855 ]\n", + " [ 0.6944214 0.26424867 0.33184814 ... -0.7866028 -0.7866028\n", + " 0.27653807]\n", + " [ 0.33184814 0.22737733 0.36257324 ... 0. -0.03072815\n", + " -0.03687134]\n", + " ...\n", + " [ 0.4977707 0.22737733 0.09217987 ... 0.08603363 0.12905121\n", + " 0.06145325]\n", + " [ 0.60224307 0.35643005 0.15363312 ... 0.08603363 0.09217987\n", + " 0.12905273]\n", + " [ 0.614534 0.44860992 0.3134125 ... 0.10447083 0.13519745\n", + " 0.13519745]]\n", + "var name: CMI_2024_01_13_23_00\n", + "[[ 0.17821655 -0.04916382 -0.04916382 ... 0.09832458 -0.15977784\n", + " -0.79274905]\n", + " [-0.07374267 -0.02458191 -0.22123107 ... -0.09832458 -0.09832458\n", + " -0.546933 ]\n", + " [-0.16592407 -0.13519898 -0.15363464 ... 0.19050293 -0.6698395\n", + " -1.0262696 ]\n", + " ...\n", + " [ 0.11061706 0.08603515 0.12905273 ... 0.03072662 0.09832611\n", + " 0.14134368]\n", + " [ 0.09832458 0.05530853 0.0737442 ... -0.04301758 0.10447083\n", + " 0.11676178]\n", + " [ 0.12905273 0.09832458 0.03072662 ... -0.02458038 -0.02458038\n", + " -0.02458038]]\n" + ] + } + ], + "source": [ + "import netCDF4 as nc\n", + "dataset = nc.Dataset('../features/CMI/dF_dt/2024/FA_2024_01_13.nc')\n", + "\n", + "for variable_name in dataset.variables.keys():\n", + " print(f'var name: {variable_name}')\n", + " data = dataset.variables[variable_name][:]\n", + " print(data)" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['CMI_2024_01_13_03_00', 'CMI_2024_01_13_03_30', 'CMI_2024_01_13_05_00', 'CMI_2024_01_13_01_00', 'CMI_2024_01_13_02_00', 'CMI_2024_01_13_00_00', 'CMI_2024_01_13_03_50', 'CMI_2024_01_13_08_00', 'CMI_2024_01_13_00_10', 'CMI_2024_01_13_03_20', 'CMI_2024_01_13_05_10', 'CMI_2024_01_13_02_10', 'CMI_2024_01_13_09_00', 'CMI_2024_01_13_03_40', 'CMI_2024_01_13_07_00', 'CMI_2024_01_13_01_30', 'CMI_2024_01_13_01_20', 'CMI_2024_01_13_00_20', 'CMI_2024_01_13_00_30', 'CMI_2024_01_13_08_10', 'CMI_2024_01_13_05_20', 'CMI_2024_01_13_09_10', 'CMI_2024_01_13_07_10', 'CMI_2024_01_13_06_10', 'CMI_2024_01_13_08_20', 'CMI_2024_01_13_05_30', 'CMI_2024_01_13_00_40', 'CMI_2024_01_13_01_10', 'CMI_2024_01_13_03_10', 'CMI_2024_01_13_09_20', 'CMI_2024_01_13_04_00', 'CMI_2024_01_13_06_00', 'CMI_2024_01_13_04_10', 'CMI_2024_01_13_01_40', 'CMI_2024_01_13_07_20', 'CMI_2024_01_13_02_20', 'CMI_2024_01_13_05_40', 'CMI_2024_01_13_01_50', 'CMI_2024_01_13_02_40', 'CMI_2024_01_13_02_30', 'CMI_2024_01_13_06_30', 'CMI_2024_01_13_08_40', 'CMI_2024_01_13_06_40', 'CMI_2024_01_13_00_50', 'CMI_2024_01_13_04_20', 'CMI_2024_01_13_08_30', 'CMI_2024_01_13_09_30', 'CMI_2024_01_13_09_40', 'CMI_2024_01_13_02_50', 'CMI_2024_01_13_07_40', 'CMI_2024_01_13_04_30', 'CMI_2024_01_13_07_30', 'CMI_2024_01_13_07_50', 'CMI_2024_01_13_09_50', 'CMI_2024_01_13_04_50', 'CMI_2024_01_13_05_50', 'CMI_2024_01_13_04_40', 'CMI_2024_01_13_06_50', 'CMI_2024_01_13_10_30', 'CMI_2024_01_13_10_20', 'CMI_2024_01_13_08_50', 'CMI_2024_01_13_11_10', 'CMI_2024_01_13_10_40', 'CMI_2024_01_13_11_20', 'CMI_2024_01_13_10_50', 'CMI_2024_01_13_10_10', 'CMI_2024_01_13_11_00', 'CMI_2024_01_13_11_30', 'CMI_2024_01_13_11_50', 'CMI_2024_01_13_10_00', 'CMI_2024_01_13_12_30', 'CMI_2024_01_13_12_10', 'CMI_2024_01_13_13_00', 'CMI_2024_01_13_12_20', 'CMI_2024_01_13_13_20', 'CMI_2024_01_13_12_40', 'CMI_2024_01_13_12_00', 'CMI_2024_01_13_12_50', 'CMI_2024_01_13_11_40', 'CMI_2024_01_13_13_30', 'CMI_2024_01_13_13_40', 'CMI_2024_01_13_14_00', 'CMI_2024_01_13_14_50', 'CMI_2024_01_13_15_10', 'CMI_2024_01_13_14_30', 'CMI_2024_01_13_15_00', 'CMI_2024_01_13_13_50', 'CMI_2024_01_13_14_20', 'CMI_2024_01_13_14_10', 'CMI_2024_01_13_15_20', 'CMI_2024_01_13_14_40', 'CMI_2024_01_13_13_10', 'CMI_2024_01_13_15_30', 'CMI_2024_01_13_16_30', 'CMI_2024_01_13_15_50', 'CMI_2024_01_13_16_10', 'CMI_2024_01_13_17_00', 'CMI_2024_01_13_15_40', 'CMI_2024_01_13_16_00', 'CMI_2024_01_13_17_10', 'CMI_2024_01_13_16_20', 'CMI_2024_01_13_17_20', 'CMI_2024_01_13_18_10', 'CMI_2024_01_13_16_40', 'CMI_2024_01_13_18_00', 'CMI_2024_01_13_17_40', 'CMI_2024_01_13_18_20', 'CMI_2024_01_13_17_50', 'CMI_2024_01_13_18_40', 'CMI_2024_01_13_16_50', 'CMI_2024_01_13_17_30', 'CMI_2024_01_13_18_30', 'CMI_2024_01_13_19_20', 'CMI_2024_01_13_19_40', 'CMI_2024_01_13_19_10', 'CMI_2024_01_13_19_30', 'CMI_2024_01_13_19_00', 'CMI_2024_01_13_20_20', 'CMI_2024_01_13_20_00', 'CMI_2024_01_13_18_50', 'CMI_2024_01_13_20_10', 'CMI_2024_01_13_20_40', 'CMI_2024_01_13_20_30', 'CMI_2024_01_13_19_50', 'CMI_2024_01_13_20_50', 'CMI_2024_01_13_21_00', 'CMI_2024_01_13_21_10', 'CMI_2024_01_13_21_20', 'CMI_2024_01_13_21_50', 'CMI_2024_01_13_21_40', 'CMI_2024_01_13_22_00', 'CMI_2024_01_13_21_30', 'CMI_2024_01_13_22_30', 'CMI_2024_01_13_22_40', 'CMI_2024_01_13_22_50', 'CMI_2024_01_13_22_20', 'CMI_2024_01_13_23_10', 'CMI_2024_01_13_22_10', 'CMI_2024_01_13_23_20', 'CMI_2024_01_13_23_30', 'CMI_2024_01_13_06_20', 'CMI_2024_01_13_23_40', 'CMI_2024_01_13_23_00'])" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dataset.variables.keys()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/sumare_radar/RGB_Rainfall_Calibration.ipynb b/notebooks/sumare_radar/RGB_Rainfall_Calibration.ipynb new file mode 100644 index 00000000..d18c87dd --- /dev/null +++ b/notebooks/sumare_radar/RGB_Rainfall_Calibration.ipynb @@ -0,0 +1,1063 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# RGB–Rainfall Calibration Notebook\n", + "\n", + "This notebook provides a **generic pipeline** for calibrating radar RGB imagery against ground station precipitation data.\n", + "\n", + "**Main features:**\n", + "- Handles long historical archives (e.g., 2011–2024)\n", + "- Aggregates 2‑minute radar frames into hourly products\n", + "- Uses maximum‑intensity aggregation (suitable for extreme events)\n", + "- Builds an RGB→rainfall regression model using station data\n", + "- Produces estimated rainfall maps and saves results in `outputs/`" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "ab688f15", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: numpy in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (1.26.4)\n", + "Requirement already satisfied: pandas in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (2.3.3)\n", + "Requirement already satisfied: matplotlib in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (3.10.6)\n", + "Requirement already satisfied: scikit-learn in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (1.7.2)\n", + "Requirement already satisfied: pillow in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (10.4.0)\n", + "Requirement already satisfied: pyproj in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (3.6.1)\n", + "Requirement already satisfied: scipy in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (1.15.2)\n", + "Requirement already satisfied: joblib in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (1.5.2)\n", + "Requirement already satisfied: tqdm in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (4.67.1)\n", + "Requirement already satisfied: python-dateutil>=2.8.2 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from pandas) (2.9.0.post0)\n", + "Requirement already satisfied: pytz>=2020.1 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from pandas) (2025.2)\n", + "Requirement already satisfied: tzdata>=2022.7 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from pandas) (2025.2)\n", + "Requirement already satisfied: contourpy>=1.0.1 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from matplotlib) (1.3.2)\n", + "Requirement already satisfied: cycler>=0.10 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from matplotlib) (0.12.1)\n", + "Requirement already satisfied: fonttools>=4.22.0 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from matplotlib) (4.60.1)\n", + "Requirement already satisfied: kiwisolver>=1.3.1 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from matplotlib) (1.4.9)\n", + "Requirement already satisfied: packaging>=20.0 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from matplotlib) (25.0)\n", + "Requirement already satisfied: pyparsing>=2.3.1 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from matplotlib) (3.2.5)\n", + "Requirement already satisfied: threadpoolctl>=3.1.0 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from scikit-learn) (3.6.0)\n", + "Requirement already satisfied: certifi in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from pyproj) (2025.10.5)\n", + "Requirement already satisfied: six>=1.5 in /home/noemi/miniconda3/envs/atmoseer/lib/python3.10/site-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n", + "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager, possibly rendering your system unusable. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv. Use the --root-user-action option if you know what you are doing and want to suppress this warning.\u001b[0m\u001b[33m\n", + "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "pip install numpy pandas matplotlib scikit-learn pillow pyproj scipy joblib tqdm" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Imports and configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "0753f64c", + "metadata": {}, + "outputs": [], + "source": [ + "import os, glob\n", + "import numpy as np\n", + "import pandas as pd\n", + "from PIL import Image\n", + "from pyproj import Transformer, Geod\n", + "from sklearn.ensemble import RandomForestRegressor\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.metrics import r2_score, mean_absolute_error\n", + "import joblib\n", + "from tqdm import tqdm\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Directories\n", + "radar_dir = '../../data/radar_sumare'\n", + "stations_csv = '../../config/SurfaceStations.csv'\n", + "grid_file = 'sumare_radar_latlon_grid.npz'\n", + "outputs_dir = 'outputs'\n", + "os.makedirs(outputs_dir, exist_ok=True)\n", + "\n", + "# Radar parameters\n", + "SUMARE_RADAR_LAT = -22.955139\n", + "SUMARE_RADAR_LON = -43.248278\n", + "SUMARE_RADAR_RADIUS = 138_900 # meters\n", + "RADAR_INTERVAL_MIN = 2\n", + "STATION_INTERVAL_H = 1\n", + "IMG_WIDTH = 656 # pixels\n", + "IMG_HEIGHT = 654 # pixels" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "ca13a669", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image dimensions: 656 x 654 pixels\n" + ] + } + ], + "source": [ + "radar_dir_img = '../../data/radar_sumare/2011/01/17/2011_01_17_15_36__.png'\n", + "img = Image.open(radar_dir_img)\n", + "width, height = img.size\n", + "print(f\"Image dimensions: {width} x {height} pixels\")" + ] + }, + { + "cell_type": "markdown", + "id": "2eb9ac65", + "metadata": {}, + "source": [ + "## 2. Utility functions" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "a59c6882", + "metadata": {}, + "outputs": [], + "source": [ + "def load_radar_composite(radar_dir, dt_utc, window_minutes=60, frame_interval=2, method='max', min_coverage=0.5):\n", + "\n", + " import glob\n", + " from PIL import Image\n", + " import numpy as np\n", + " import os\n", + " from datetime import timedelta\n", + "\n", + " # compute number of expected frames\n", + " expected_frames = int(window_minutes / frame_interval)\n", + " min_frames = int(expected_frames * min_coverage)\n", + "\n", + " # collect all frames within the window\n", + " start_time = dt_utc\n", + " end_time = dt_utc + timedelta(minutes=window_minutes)\n", + "\n", + " pattern = f\"{radar_dir}/{dt_utc:%Y}/{dt_utc:%m}/{dt_utc:%d}/{dt_utc:%Y_%m_%d_}*.png\"\n", + " all_files = sorted(glob.glob(pattern))\n", + " files_in_window = [f for f in all_files if start_time.strftime(\"%H_\") <= os.path.basename(f)[11:14] <= end_time.strftime(\"%H_\")]\n", + "\n", + " if len(files_in_window) < min_frames:\n", + " return None\n", + "\n", + " imgs = []\n", + " for f in files_in_window:\n", + " try:\n", + " img = Image.open(f).convert('RGB')\n", + " imgs.append(np.array(img))\n", + " except Exception:\n", + " continue\n", + "\n", + " if not imgs:\n", + " return None\n", + "\n", + " agg_func = np.max if method == 'max' else np.mean\n", + " return agg_func(imgs, axis=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "cc6e9106", + "metadata": {}, + "outputs": [], + "source": [ + "def load_hourly_radar(radar_dir, dt_utc, method='max', min_frames=15):\n", + " \"\"\"Aggregate 2‑minute radar PNGs into a single hourly composite.\n", + " method='max' (default) preserves extreme intensity.\n", + " Returns np.ndarray (H×W×3) or None if no data.\"\"\"\n", + " \n", + " pattern = f\"{radar_dir}/{dt_utc:%Y}/{dt_utc:%m}/{dt_utc:%d}/{dt_utc:%Y_%m_%d_%H_}*.png\"\n", + " files = sorted(glob.glob(pattern))\n", + " if len(files) < min_frames:\n", + " return None\n", + " \n", + " imgs = []\n", + " for f in files:\n", + " try:\n", + " img = Image.open(f).convert('RGB')\n", + " imgs.append(np.array(img))\n", + " except Exception as e:\n", + " #print(f\"Skipping invalid radar frame: {os.path.basename(f)} ({e})\")\n", + " continue\n", + "\n", + " if len(imgs) == 0:\n", + " return None\n", + "\n", + " agg_func = np.max if method == 'max' else np.mean\n", + " return agg_func(imgs, axis=0)\n", + "\n", + "def latlon_to_pixel(lat, lon, lat_grid, lon_grid):\n", + " \"\"\"Return (row,col) of the closest pixel to (lat,lon).\"\"\"\n", + " dist = np.hypot(lat_grid - lat, lon_grid - lon)\n", + " return np.unravel_index(np.argmin(dist), dist.shape)\n", + "\n", + "def get_station_rain(df, timestamp):\n", + " \"\"\"Return precipitation (mm/h) for a given UTC hour if available.\"\"\"\n", + " try:\n", + " return df.loc[timestamp, 'precipitation']\n", + " except KeyError:\n", + " return np.nan\n", + "\n", + "def load_station_data(parquet_path):\n", + " df = pd.read_parquet(parquet_path)\n", + " df.index = pd.to_datetime(df.index, utc=True)\n", + " return df\n", + "\n", + "def extract_rgb_for_station(lat, lon, lat_grid, lon_grid, image):\n", + " row, col = latlon_to_pixel(lat, lon, lat_grid, lon_grid)\n", + " return tuple(image[row, col, :3])" + ] + }, + { + "cell_type": "markdown", + "id": "ee20f507", + "metadata": {}, + "source": [ + "## I) sumare_radar_latlon_grid.npz" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "34847ca3", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_981/3397030662.py:12: FutureWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1\n", + " lon_grid, lat_grid = transform(proj_aeqd, proj_wgs84, xx, yy)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "✅ Grid saved as sumare_radar_latlon_grid.npz\n", + "lat_grid shape: (654, 656)\n", + "lon_grid shape: (654, 656)\n", + "Latitude range: -24.209289508909624 → -21.695158782862908\n", + "Longitude range: -44.61543500513054 → -41.881120994869455\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "from pyproj import Proj, transform\n", + "\n", + "proj_aeqd = Proj(proj='aeqd', lat_0=SUMARE_RADAR_LAT, lon_0=SUMARE_RADAR_LON, datum='WGS84')\n", + "proj_wgs84 = Proj(proj='latlong', datum='WGS84')\n", + "\n", + "x = np.linspace(-SUMARE_RADAR_RADIUS, SUMARE_RADAR_RADIUS, IMG_WIDTH)\n", + "y = np.linspace(SUMARE_RADAR_RADIUS, -SUMARE_RADAR_RADIUS, IMG_HEIGHT) \n", + "\n", + "xx, yy = np.meshgrid(x, y)\n", + "\n", + "lon_grid, lat_grid = transform(proj_aeqd, proj_wgs84, xx, yy)\n", + "\n", + "np.savez(\"sumare_radar_latlon_grid.npz\", lat=lat_grid, lon=lon_grid)\n", + "\n", + "print(\"✅ Grid saved as sumare_radar_latlon_grid.npz\")\n", + "print(\"lat_grid shape:\", lat_grid.shape)\n", + "print(\"lon_grid shape:\", lon_grid.shape)\n", + "print(\"Latitude range:\", lat_grid.min(), \"→\", lat_grid.max())\n", + "print(\"Longitude range:\", lon_grid.min(), \"→\", lon_grid.max())" + ] + }, + { + "cell_type": "markdown", + "id": "0e9c3960", + "metadata": {}, + "source": [ + "## II) A652 (INMET) Station Data" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "65119852", + "metadata": {}, + "outputs": [], + "source": [ + "# Function \n", + "\n", + "import pandas as pd\n", + "\n", + "def read_station(station_file, id_station):\n", + " station = station_file[station_file['STATION_ID'] == id_station]\n", + " lat = station['VL_LATITUDE'].iloc[0]\n", + " lon = station['VL_LONGITUDE'].iloc[0]\n", + " return lat, lon\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "32adabda", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-22.98833333 -43.19055555\n" + ] + } + ], + "source": [ + "stations_file = pd.read_csv('../../config/SurfaceStations.csv')\n", + "A652_LAT, A652_LON = read_station(stations_file, 'A652')\n", + "print(A652_LAT, A652_LON)" + ] + }, + { + "cell_type": "markdown", + "id": "a183347c", + "metadata": {}, + "source": [ + "### Testing" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "e3b78651", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " precipitation\n", + "2011-01-01 00:00:00+00:00 0.0\n", + "2011-01-01 01:00:00+00:00 0.0\n", + "2011-01-01 02:00:00+00:00 0.0\n", + "2011-01-01 03:00:00+00:00 0.0\n", + "2011-01-01 04:00:00+00:00 0.0\n", + "... ...\n", + "2024-11-24 19:00:00+00:00 0.0\n", + "2024-11-24 20:00:00+00:00 0.0\n", + "2024-11-24 21:00:00+00:00 0.0\n", + "2024-11-24 22:00:00+00:00 0.0\n", + "2024-11-24 23:00:00+00:00 0.0\n", + "\n", + "[116866 rows x 1 columns]\n" + ] + } + ], + "source": [ + "df_rain = load_station_data('../../data/ws/inmet/A652_preprocessed.parquet.gzip')\n", + "print(df_rain)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "f34a841c", + "metadata": {}, + "outputs": [], + "source": [ + "def get_positive_precipitation(df):\n", + " return df[df['precipitation'] > 50]" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "0440213b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " precipitation\n", + "2016-03-12 23:00:00+00:00 60.8\n", + "2019-03-03 22:00:00+00:00 57.6\n", + "2019-03-17 00:00:00+00:00 54.4\n", + "2019-04-08 22:00:00+00:00 71.6\n", + "2019-04-09 01:00:00+00:00 52.6\n", + "2022-04-01 02:00:00+00:00 60.4\n", + "2023-02-07 23:00:00+00:00 64.4" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "get_positive_precipitation(df_rain)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "762c8e7a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(654, 656, 3) 0 255\n" + ] + } + ], + "source": [ + "from datetime import datetime\n", + "import pytz\n", + "\n", + "dt_utc = datetime(2019, 4, 9, 2, 0, 0, tzinfo=pytz.UTC)\n", + "radar_image = load_hourly_radar(radar_dir, dt_utc, min_frames=1)\n", + "print(radar_image.shape, radar_image.min(), radar_image.max())" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "69ec1c5f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "160482 pixels with reflectivity (>0) out of 429024 total\n" + ] + } + ], + "source": [ + "from datetime import datetime\n", + "import pytz\n", + "\n", + "dt_utc = datetime(2019, 4, 9, 1, 0, 0, tzinfo=pytz.UTC)\n", + "radar_image = load_hourly_radar(radar_dir, dt_utc)\n", + "#print(radar_image)\n", + "nonzero_pixels = np.count_nonzero(np.any(radar_image > 0, axis=-1))\n", + "total_pixels = radar_image.shape[0] * radar_image.shape[1]\n", + "print(f\"{nonzero_pixels} pixels with reflectivity (>0) out of {total_pixels} total\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "db5caa28", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(6, 6), facecolor='black') \n", + "plt.imshow(radar_image) \n", + "plt.title(\"Radar - 2019-04-09 02:00 UTC\") \n", + "plt.axis('off') \n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "b9ba12cd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Station A652 pixel: row=335, col=341\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "row, col = latlon_to_pixel(A652_LAT, A652_LON, lat_grid, lon_grid)\n", + "print(f\"Station A652 pixel: row={row}, col={col}\")\n", + "\n", + "# Radar image + A652 station \n", + "plt.figure(figsize=(6, 6), facecolor='black')\n", + "plt.imshow(radar_image)\n", + "plt.scatter(col, row, color='red', marker='o', s=80, label='A652 (Forte de Copacabana)')\n", + "plt.title(\"Radar - 2019-04-09 02:00 UTC (Station A652 marked)\")\n", + "plt.axis('off')\n", + "plt.legend(loc='lower right')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "ed3d07fa", + "metadata": {}, + "source": [ + "## 3. Build the calibration dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "be204104", + "metadata": {}, + "outputs": [], + "source": [ + "from datetime import timedelta\n", + "import pandas as pd\n", + "import numpy as np\n", + "import os\n", + "from tqdm import tqdm" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "6f6b1e1c", + "metadata": {}, + "outputs": [], + "source": [ + "def build_calibration_dataset_with_zeros(station_id, station_path, lat_s, lon_s, grid_file, radar_dir, outputs_dir):\n", + " \"\"\"\n", + " Generate a calibration dataset (RGB × precipitation) for a single station.\n", + " \"\"\"\n", + " os.makedirs(outputs_dir, exist_ok=True)\n", + "\n", + " latlon = np.load(grid_file)\n", + " lat, lon = latlon['lat'], latlon['lon']\n", + "\n", + " df = load_station_data(station_path)\n", + " df = df[df['precipitation'] >= 0] # include all precipitation values (including zeros)\n", + "\n", + " records = []\n", + " for ts, row in tqdm(df.iterrows(), total=len(df)):\n", + " rain = row['precipitation']\n", + " if np.isnan(rain):\n", + " continue\n", + "\n", + " # UTC-3\n", + " img = load_hourly_radar(radar_dir, ts - timedelta(hours=3), method='max', min_frames=1)\n", + " if img is None:\n", + " continue\n", + "\n", + " rgb = extract_rgb_for_station(lat_s, lon_s, lat, lon, img)\n", + " records.append((*rgb, rain))\n", + "\n", + " calib_df = pd.DataFrame(records, columns=['R', 'G', 'B', 'rain_mm_h'])\n", + " out_path = os.path.join(outputs_dir, f'calibration_data_{station_id}_with_zeros.csv')\n", + " calib_df.to_csv(out_path, index=False)\n", + " print(f'[{station_id}] Calibration dataset: {len(calib_df)} samples saved → {out_path}')\n", + " return calib_df\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "128e0ce1", + "metadata": {}, + "outputs": [], + "source": [ + "def build_calibration_dataset(station_id, station_path, lat_s, lon_s, grid_file, radar_dir, outputs_dir):\n", + " \"\"\"\n", + " Generate a calibration dataset (RGB × precipitation) for a single station.\n", + " \"\"\"\n", + " os.makedirs(outputs_dir, exist_ok=True)\n", + "\n", + " latlon = np.load(grid_file)\n", + " lat, lon = latlon['lat'], latlon['lon']\n", + "\n", + " df = load_station_data(station_path)\n", + " df = df[df['precipitation'] > 0] \n", + "\n", + " records = []\n", + " for ts, row in tqdm(df.iterrows(), total=len(df)):\n", + " rain = row['precipitation']\n", + " if np.isnan(rain):\n", + " continue\n", + "\n", + " # UTC-3\n", + " img = load_hourly_radar(radar_dir, ts - timedelta(hours=3), method='max', min_frames=1)\n", + " if img is None:\n", + " continue\n", + "\n", + " rgb = extract_rgb_for_station(lat_s, lon_s, lat, lon, img)\n", + " records.append((*rgb, rain))\n", + "\n", + " calib_df = pd.DataFrame(records, columns=['R', 'G', 'B', 'rain_mm_h'])\n", + " out_path = os.path.join(outputs_dir, f'calibration_data_{station_id}.csv')\n", + " calib_df.to_csv(out_path, index=False)\n", + " print(f'[{station_id}] Calibration dataset: {len(calib_df)} samples saved → {out_path}')\n", + " return calib_df\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "a586e076", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 116866/116866 [7:36:58<00:00, 4.26it/s] \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[A652] Calibration dataset: 101170 samples saved → outputs/calibration_data_A652_with_zeros.csv\n" + ] + } + ], + "source": [ + "# Testing\n", + "stations_df = pd.read_csv('../../config/SurfaceStations.csv')\n", + "lat, lon = read_station(stations_df, 'A652')\n", + "station_id = 'A652'\n", + "station_path = '../../data/ws/inmet/A652_preprocessed.parquet.gzip'\n", + "\n", + "# with zeros (NO precipitation events)\n", + "calib_df = build_calibration_dataset_with_zeros(\n", + " station_id,\n", + " station_path,\n", + " lat,\n", + " lon,\n", + " grid_file='sumare_radar_latlon_grid.npz',\n", + " radar_dir='../../data/radar_sumare',\n", + " outputs_dir='outputs'\n", + ") " + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "ee408c91", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " R G B rain_mm_h\n", + "0 0 0 0 0.0\n", + "1 0 0 0 0.0\n", + "2 0 0 0 0.0\n", + "3 0 0 0 0.0\n", + "4 0 0 0 0.0\n", + "101170 samples\n" + ] + } + ], + "source": [ + "#calib_df = pd.read_csv('/home/noemi/atmoseer/notebooks/sumare_radar/outputs/calibration_data_A652.csv')\n", + "print(calib_df.head())\n", + "print(len(calib_df), \"samples\")" + ] + }, + { + "cell_type": "markdown", + "id": "ec705a77", + "metadata": {}, + "source": [ + "## 4. Train and evaluate the RGB→rainfall model" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "e497b107", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "def train_and_evaluate_model(calib_df, outputs_dir='outputs', model_name='rgb2rain_model'):\n", + "\n", + " os.makedirs(outputs_dir, exist_ok=True)\n", + "\n", + " if len(calib_df) < 10:\n", + " print('Warning: too few samples for training.')\n", + " return None\n", + "\n", + " X = calib_df[['R','G','B']].values\n", + " y = np.log1p(calib_df['rain_mm_h'].values)\n", + "\n", + " X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\n", + "\n", + " model = RandomForestRegressor(n_estimators=200, random_state=42)\n", + " model.fit(X_train, y_train)\n", + "\n", + " y_pred_log = model.predict(X_test)\n", + " y_pred = np.expm1(y_pred_log)\n", + " y_true = np.expm1(y_test)\n", + "\n", + " # --- Overall metrics ---\n", + " r2 = r2_score(y_true, y_pred)\n", + " mae = mean_absolute_error(y_true, y_pred)\n", + " bias = np.mean(y_pred - y_true)\n", + "\n", + " print(f\"\\n=== Overall Performance ===\")\n", + " print(f\"R²: {r2:.3f}\")\n", + " print(f\"MAE: {mae:.2f} mm/h\")\n", + " print(f\"Bias (mean(pred) - mean(true)): {bias:.2f} mm/h\")\n", + "\n", + " # --- Stratified analysis by rainfall intensity ---\n", + " bins = [0, 5, 25, 50, np.inf]\n", + " labels = ['Weak (≤5 mm/h)', 'Moderate (5–25 mm/h)', 'Heavy (25-50 mm/h)', 'Extreme (>50 mm/h)']\n", + " groups = pd.cut(y_true, bins=bins, labels=labels, include_lowest=True)\n", + " print('----------------------------------------------------')\n", + " print(groups.value_counts())\n", + "\n", + " print(\"\\n=== Performance by Rainfall Intensity ===\")\n", + " for label in labels:\n", + " mask = (groups == label)\n", + " if mask.sum() == 0:\n", + " continue\n", + " r2_bin = r2_score(y_true[mask], y_pred[mask])\n", + " mae_bin = mean_absolute_error(y_true[mask], y_pred[mask])\n", + " bias_bin = np.mean(y_pred[mask] - y_true[mask])\n", + " print(f\"{label:20s} → R²={r2_bin:6.3f}, MAE={mae_bin:6.2f}, Bias={bias_bin:6.2f} mm/h\")\n", + "\n", + " model_path = os.path.join(outputs_dir, f'{model_name}.joblib')\n", + " joblib.dump(model, model_path)\n", + " print(f\"\\n Model saved → {model_path}\")\n", + "\n", + " return model, {'R2': r2, 'MAE': mae, 'Bias': bias}" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "6976373e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "=== Overall Performance ===\n", + "R²: 0.072\n", + "MAE: 0.16 mm/h\n", + "Bias (mean(pred) - mean(true)): -0.05 mm/h\n", + "----------------------------------------------------\n", + "Weak (≤5 mm/h) 30187\n", + "Moderate (5–25 mm/h) 155\n", + "Heavy (25-50 mm/h) 9\n", + "Extreme (>50 mm/h) 0\n", + "Name: count, dtype: int64\n", + "\n", + "=== Performance by Rainfall Intensity ===\n", + "Weak (≤5 mm/h) → R²=-0.060, MAE= 0.11, Bias= -0.00 mm/h\n", + "Moderate (5–25 mm/h) → R²=-3.975, MAE= 8.84, Bias= -8.81 mm/h\n", + "Heavy (25-50 mm/h) → R²=-46.433, MAE= 30.91, Bias=-30.91 mm/h\n", + "\n", + " Model saved → outputs/rgb2rain_model_A652_with_zeros.joblib\n" + ] + } + ], + "source": [ + "model, metrics = train_and_evaluate_model(calib_df, outputs_dir='outputs', model_name='rgb2rain_model_A652_with_zeros')" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "18a9a97a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "count 101170.000000\n", + "mean 0.134540\n", + "std 1.072216\n", + "min 0.000000\n", + "25% 0.000000\n", + "50% 0.000000\n", + "75% 0.000000\n", + "max 64.400000\n", + "Name: rain_mm_h, dtype: float64\n" + ] + } + ], + "source": [ + "print(calib_df['rain_mm_h'].describe())" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "dea100bb", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "plt.hist(calib_df['rain_mm_h'], bins=40, color='skyblue', edgecolor='k')\n", + "plt.xlabel('Rainfall (mm/h)')\n", + "plt.ylabel('Rainfall ')\n", + "plt.title('Rainfall Distribution - Station A652 ')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "149bf542", + "metadata": {}, + "source": [ + "## 5. Apply the model to a radar frame and generate rainfall map" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "3a051ef7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from datetime import datetime, timedelta\n", + "import joblib\n", + "\n", + "model = joblib.load('outputs/rgb2rain_model_A652_with_zeros.joblib')\n", + "\n", + "timestamp = datetime(2019, 3, 3, 19, 0)\n", + "\n", + "radar_dir = '../../data/radar_sumare'\n", + "outputs_dir = 'outputs'\n", + "os.makedirs(outputs_dir, exist_ok=True)\n", + "\n", + "img = load_radar_composite(\n", + " radar_dir,\n", + " timestamp - timedelta(hours=3), \n", + " window_minutes=60, \n", + " frame_interval=2,\n", + " method='max'\n", + ")\n", + "\n", + "if img is not None:\n", + " rgb_flat = img.reshape(-1, 3)\n", + "\n", + " rain_flat = np.expm1(model.predict(rgb_flat))\n", + "\n", + " rain_map = rain_flat.reshape(img.shape[:2])\n", + "\n", + " np.save(os.path.join(outputs_dir, 'rain_estimated.npy'), rain_map)\n", + " plt.figure(figsize=(7, 6))\n", + " plt.imshow(rain_map, cmap='turbo', vmin=0, vmax=rain_map.max())\n", + " plt.colorbar(label='Estimated rainfall (mm/h)')\n", + " plt.title('Estimated Rainfall Field - ' + timestamp.strftime('%Y-%m-%d %H:%M UTC'))\n", + " plt.axis('off')\n", + " plt.savefig(os.path.join(outputs_dir, 'rain_estimated_map.png'), dpi=150)\n", + " plt.show()\n", + "\n", + "else:\n", + " print('No radar data found for the selected timestamp.')\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "65da05ed", + "metadata": {}, + "source": [ + "## 6. Visualization and validation" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "74494d71", + "metadata": {}, + "outputs": [], + "source": [ + "def plot_validation(rgb_image, rain_map, stations_df, lat_grid, lon_grid):\n", + " fig, axes = plt.subplots(1, 2, figsize=(14,6))\n", + " ax1, ax2 = axes\n", + "\n", + " ax1.imshow(rgb_image.astype(np.uint8))\n", + " ax1.set_title('Radar RGB (max reflectivity)')\n", + " ax1.axis('off')\n", + "\n", + " im = ax2.imshow(rain_map, cmap='turbo')\n", + " ax2.set_title('Estimated rainfall (mm/h)')\n", + " ax2.axis('off')\n", + "\n", + " fig.colorbar(im, ax=ax2, fraction=0.046, pad=0.04)\n", + " for _, row in stations_df.iterrows():\n", + " r, c = latlon_to_pixel(row['VL_LATITUDE'], row['VL_LONGITUDE'], lat_grid, lon_grid)\n", + " ax2.plot(c, r, 'wo', markersize=5)\n", + " ax2.text(c+3, r, row['STATION_ID'], color='white', fontsize=8)\n", + " \n", + " plt.tight_layout()\n", + " plt.savefig(os.path.join(outputs_dir, 'validation_plot.png'), dpi=150)\n", + " plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "5647d04a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "stations_df = pd.DataFrame([{\n", + " 'STATION_ID': 'A652',\n", + " 'VL_LATITUDE': A652_LAT,\n", + " 'VL_LONGITUDE': A652_LON\n", + "}])\n", + "\n", + "latlon = np.load(grid_file)\n", + "lat_grid, lon_grid = latlon['lat'], latlon['lon']\n", + "\n", + "plot_validation(img, rain_map, stations_df, lat_grid, lon_grid)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.18" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sumare_radar/data_weather_systems_analysis.ipynb b/notebooks/sumare_radar/data_weather_systems_analysis.ipynb new file mode 100644 index 00000000..7e2b38ca --- /dev/null +++ b/notebooks/sumare_radar/data_weather_systems_analysis.ipynb @@ -0,0 +1,287564 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a55b2f89", + "metadata": {}, + "source": [ + "Append dos diretórios necessários no path, para uso de alguns scripts externos ao notebook:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f78398bb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['/home/sangonvi/miniconda3/envs/etl/lib/python311.zip', '/home/sangonvi/miniconda3/envs/etl/lib/python3.11', '/home/sangonvi/miniconda3/envs/etl/lib/python3.11/lib-dynload', '', '/home/sangonvi/miniconda3/envs/etl/lib/python3.11/site-packages', '/home/sangonvi/Cefet/repositories/atmoseer/notebooks', '/home/sangonvi/Cefet/repositories/atmoseer/notebooks/src', '/home/sangonvi/Cefet/repositories/atmoseer/notebooks/src/surface_stations', '/home/sangonvi/Cefet/repositories/atmoseer/notebooks/data', '/home/sangonvi/Cefet/repositories/atmoseer/notebooks/src/sumare_radar']\n" + ] + } + ], + "source": [ + "import os\n", + "import sys\n", + "path_list = ['..', '../src', '../src/surface_stations' , '../data', '../src/sumare_radar'] \n", + "for path in path_list:\n", + " module_path = os.path.abspath(path)\n", + " if module_path not in sys.path:\n", + " sys.path.append(module_path)\n", + "print(sys.path)" + ] + }, + { + "cell_type": "markdown", + "id": "09b34a2f", + "metadata": {}, + "source": [ + "Imports de Bibliotecas utilitárias e scripts:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "cf5e6fef", + "metadata": {}, + "outputs": [ + { + "ename": "ModuleNotFoundError", + "evalue": "No module named 'VAR'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mModuleNotFoundError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[2]\u001b[39m\u001b[32m, line 10\u001b[39m\n\u001b[32m 7\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mseaborn\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01msns\u001b[39;00m\n\u001b[32m 8\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mPIL\u001b[39;00m\u001b[34;01m.\u001b[39;00m\u001b[34;01mImage\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mImage\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m10\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mVAR\u001b[39;00m \u001b[38;5;66;03m#Credenciais Cemaden\u001b[39;00m\n\u001b[32m 11\u001b[39m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mretrieve_data_cemaden\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m get_token \u001b[38;5;66;03m#Obter token autenticação API Cemaden\u001b[39;00m\n\u001b[32m 13\u001b[39m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnumpy\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34;01mnp\u001b[39;00m\n", + "\u001b[31mModuleNotFoundError\u001b[39m: No module named 'VAR'" + ] + } + ], + "source": [ + "import folium\n", + "import leafmap.foliumap as leafmap\n", + "import requests\n", + "import datetime\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import PIL.Image as Image\n", + "\n", + "import VAR #Credenciais Cemaden\n", + "from retrieve_data_cemaden import get_token #Obter token autenticação API Cemaden\n", + "\n", + "import numpy as np\n", + "import math\n", + "from scipy import stats\n" + ] + }, + { + "cell_type": "markdown", + "id": "86b53480", + "metadata": {}, + "source": [ + "Folium: Utilitário para construção de mapas:\n", + "https://python-visualization.github.io/folium/latest/" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b1a6f25b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mapa = leafmap.Map(center= [-22.925778948753702, -43.489029909370046], zoom_start=8, tiles='cartodbpositron')\n", + "colormap = ['magenta', 'red', 'orange', 'yellow']\n", + "folium.LatLngPopup().add_to(mapa)" + ] + }, + { + "cell_type": "markdown", + "id": "164065a3", + "metadata": {}, + "source": [ + "### Posicionamento dos sistemas de dados e do radar

" + ] + }, + { + "cell_type": "markdown", + "id": "765303a9", + "metadata": {}, + "source": [ + "RADAR SUMARÉ" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "a5c29fc4", + "metadata": {}, + "outputs": [], + "source": [ + "lat = [-22.955139]\n", + "lon = [-43.248278]\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=100,\n", + " fill=True,\n", + " color='black',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=137100,\n", + " fill=True,\n", + " color='gray',\n", + " fill_opacity=0.1\n", + " ).add_to(mapa)\n" + ] + }, + { + "cell_type": "markdown", + "id": "4d3600cc", + "metadata": {}, + "source": [ + "CEMADEN" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6d3d08c8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Número de estações encontradas: 28\n", + "Dicionário de posições das estações:\n", + "330455734A: (-22.7613, -43.1084)\n", + "330455733A: (-22.875, -43.299)\n", + "330455732A: (-22.869, -43.265)\n", + "330455731A: (-22.948, -43.258)\n", + "330455730A: (-22.943, -43.241)\n", + "330455729A: (-22.9666, -43.2965)\n", + "330455728A: (-22.86086, -43.30756)\n", + "330455726A: (-22.894, -43.676)\n", + "330455725A: (-22.8131, -43.3101)\n", + "330455724A: (-22.8076, -43.3584)\n", + "330455722A: (-22.923, -43.176)\n", + "330455721A: (-22.995, -43.269)\n", + "330455720A: (-22.796, -43.203)\n", + "330455719A: (-22.9922, -43.367)\n", + "330455718A: (-22.989, -43.433)\n", + "330455716A: (-22.921, -43.227)\n", + "330455715A: (-22.93, -43.25)\n", + "330455714A: (-22.929, -43.228)\n", + "330455713A: (-22.8689, -43.4507)\n", + "330455712A: (-22.864, -43.425)\n", + "330455711A: (-22.8897, -43.7175)\n", + "330455710A: (-22.9592, -43.6082)\n", + "330455709A: (-22.977861, -43.277444)\n", + "330455706A: (-22.839, -43.279)\n", + "330455705A: (-22.918, -43.361)\n", + "330455704A: (-22.896, -43.352)\n", + "330455703A: (-22.885906, -43.297753)\n", + "330455701A: (-22.915, -43.176)\n", + "[{'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455734A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-04-17 13:23:58.932', 'dh_cadastro': '2015-04-17 13:23:58.932', 'dh_inicio_inativo': '2024-03-26 20:45:51.749', 'dh_ultima_remessa': '2024-03-26 18:40:24.000', 'id_estacao': 7615, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.7613, 'longitude': -43.1084, 'nome': 'Ilha de Paquetá', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455733A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-22 11:03:39.609', 'dh_cadastro': '2015-05-22 11:03:39.609', 'dh_inicio_inativo': '2025-05-24 03:35:26.360', 'dh_ultima_remessa': '2025-09-16 11:30:21.000', 'id_estacao': 7614, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.875, 'longitude': -43.299, 'nome': 'Pilares', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455732A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-26 13:12:55.735', 'dh_cadastro': '2015-05-26 13:12:55.735', 'dh_inicio_inativo': '2025-06-26 06:26:19.726', 'dh_ultima_remessa': '2025-09-16 11:20:25.000', 'id_estacao': 7613, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.869, 'longitude': -43.265, 'nome': 'Higienópolis', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455731A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-03-04 20:17:58.835', 'dh_cadastro': '2015-03-04 20:17:58.835', 'dh_inicio_inativo': '2025-06-26 07:16:09.334', 'dh_ultima_remessa': '2025-09-16 11:10:30.000', 'id_estacao': 7612, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.948, 'longitude': -43.258, 'nome': 'Usina', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455730A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-20 13:03:35.902', 'dh_cadastro': '2015-05-20 13:03:35.902', 'dh_inicio_inativo': '2025-09-03 13:04:55.200', 'dh_ultima_remessa': '2025-09-03 11:02:56.000', 'id_estacao': 7611, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.943, 'longitude': -43.241, 'nome': 'Tijuca', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455729A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-08-20 12:31:52.784', 'dh_cadastro': '2015-08-20 12:31:52.784', 'dh_inicio_inativo': '2025-08-05 15:14:16.114', 'dh_ultima_remessa': '2025-09-16 11:40:21.000', 'id_estacao': 7610, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.9666, 'longitude': -43.2965, 'nome': 'Alto da Boa Vista', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455728A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-15 12:53:15.827', 'dh_cadastro': '2015-05-15 12:53:15.827', 'dh_inicio_inativo': '2025-05-28 22:07:38.597', 'dh_ultima_remessa': '2025-09-16 11:00:30.000', 'id_estacao': 7609, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.86086, 'longitude': -43.30756, 'nome': 'Vicente de Carvalho', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455726A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-02-20 14:31:36.673', 'dh_cadastro': '2015-02-20 14:31:36.673', 'dh_inicio_inativo': '2023-06-27 18:52:25.122', 'dh_ultima_remessa': '2023-06-27 16:50:00.000', 'id_estacao': 7607, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.894, 'longitude': -43.676, 'nome': 'Defesa Civil Santa Cruz', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455725A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-04 13:35:59.398', 'dh_cadastro': '2015-05-04 13:35:59.398', 'dh_inicio_inativo': '2025-06-26 06:44:45.865', 'dh_ultima_remessa': '2025-09-16 11:40:26.000', 'id_estacao': 7606, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.8131, 'longitude': -43.3101, 'nome': 'Vigário Geral', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455724A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-04 14:11:06.152', 'dh_cadastro': '2015-05-04 14:11:06.152', 'dh_inicio_inativo': '2025-09-05 11:38:23.659', 'dh_ultima_remessa': '2025-09-16 11:30:00.000', 'id_estacao': 7605, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.8076, 'longitude': -43.3584, 'nome': 'Pavuna', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455722A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-26 14:20:15.064', 'dh_cadastro': '2015-05-26 14:20:15.064', 'dh_inicio_inativo': '2025-08-26 11:13:10.581', 'dh_ultima_remessa': '2025-09-16 11:10:34.000', 'id_estacao': 7603, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.923, 'longitude': -43.176, 'nome': 'Catete', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455721A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-26 13:34:42.170', 'dh_cadastro': '2015-05-26 13:34:42.170', 'dh_inicio_inativo': '2025-09-03 13:15:08.103', 'dh_ultima_remessa': '2025-09-03 11:05:30.000', 'id_estacao': 7602, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.995, 'longitude': -43.269, 'nome': 'São Conrado', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455720A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-14 12:57:54.207', 'dh_cadastro': '2015-05-14 12:57:54.207', 'dh_inicio_inativo': '2025-02-26 19:15:51.543', 'dh_ultima_remessa': '2025-02-26 17:10:25.000', 'id_estacao': 7601, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.796, 'longitude': -43.203, 'nome': 'CIEP Dr. João Ramos de Souza', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455719A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-06 13:19:01.353', 'dh_cadastro': '2015-05-06 13:19:01.353', 'dh_inicio_inativo': '2025-06-26 07:03:35.434', 'dh_ultima_remessa': '2025-09-16 12:00:33.000', 'id_estacao': 7600, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.9922, 'longitude': -43.367, 'nome': 'Jacarepaguá', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455718A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-14 14:45:28.982', 'dh_cadastro': '2015-05-14 14:45:28.982', 'dh_inicio_inativo': '2025-07-01 18:52:28.342', 'dh_ultima_remessa': '2025-09-16 11:50:25.000', 'id_estacao': 7599, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.989, 'longitude': -43.433, 'nome': 'Vargem Pequena', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455716A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-05-20 16:05:42.233', 'dh_cadastro': '2015-05-20 16:05:42.233', 'dh_inicio_inativo': '2025-09-15 20:45:36.457', 'dh_ultima_remessa': '2025-09-16 10:40:27.000', 'id_estacao': 7597, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.921, 'longitude': -43.227, 'nome': 'CIEP Samuel Wainer', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455715A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-08-04 12:58:24.170', 'dh_cadastro': '2015-08-04 12:58:24.170', 'dh_inicio_inativo': '2024-09-15 03:36:18.534', 'dh_ultima_remessa': '2024-09-15 01:30:24.000', 'id_estacao': 7596, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.93, 'longitude': -43.25, 'nome': 'Andaraí', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455714A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-07-22 13:24:23.687', 'dh_cadastro': '2015-07-22 13:24:23.687', 'dh_inicio_inativo': '2025-04-24 20:20:05.277', 'dh_ultima_remessa': '2025-04-24 18:20:20.000', 'id_estacao': 7595, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.929, 'longitude': -43.228, 'nome': 'Salgueiro', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455713A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-04-16 19:27:51.603', 'dh_cadastro': '2015-04-16 19:27:51.603', 'dh_inicio_inativo': '2025-06-26 07:16:15.456', 'dh_ultima_remessa': '2025-09-16 11:10:26.000', 'id_estacao': 7594, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.8689, 'longitude': -43.4507, 'nome': 'Padre Miguel', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455712A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-04-16 18:07:00.027', 'dh_cadastro': '2015-04-16 18:07:00.027', 'dh_inicio_inativo': '2025-09-02 18:21:09.815', 'dh_ultima_remessa': '2025-09-16 12:00:32.000', 'id_estacao': 7593, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.864, 'longitude': -43.425, 'nome': 'Realengo Batan', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455711A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-04-28 13:48:37.861', 'dh_cadastro': '2015-04-28 13:48:37.861', 'dh_inicio_inativo': '2025-05-24 03:11:57.786', 'dh_ultima_remessa': '2025-09-16 11:10:21.000', 'id_estacao': 7592, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.8897, 'longitude': -43.7175, 'nome': 'Santa Cruz', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455710A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2015-07-23 13:25:13.894', 'dh_cadastro': '2015-07-23 13:25:13.894', 'dh_inicio_inativo': '2025-05-21 18:53:37.848', 'dh_ultima_remessa': '2025-05-21 16:52:40.000', 'id_estacao': 7591, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.9592, 'longitude': -43.6082, 'nome': 'Jardim Maravilha', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455709A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2014-03-20 16:22:50.814', 'dh_cadastro': '2014-03-20 16:22:50.814', 'dh_inicio_inativo': '2025-09-03 12:53:48.571', 'dh_ultima_remessa': '2025-09-03 10:50:40.000', 'id_estacao': 3215, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.977861, 'longitude': -43.277444, 'nome': 'Est. Pedra Bonita', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455706A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2014-02-28 11:59:31.127', 'dh_cadastro': '2014-02-28 11:59:31.127', 'dh_inicio_inativo': '2025-09-15 03:30:06.097', 'dh_ultima_remessa': '2025-09-15 01:30:28.000', 'id_estacao': 3044, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.839, 'longitude': -43.279, 'nome': 'Penha', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455705A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2014-02-21 16:51:32.524', 'dh_cadastro': '2014-02-21 16:51:32.524', 'dh_inicio_inativo': '2025-07-18 04:56:25.882', 'dh_ultima_remessa': '2025-09-16 11:20:31.000', 'id_estacao': 3043, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.918, 'longitude': -43.361, 'nome': 'Tanque Jacarepagua', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455704A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2014-02-21 19:51:52.896', 'dh_cadastro': '2014-02-21 19:51:52.896', 'dh_inicio_inativo': '2025-07-15 19:07:56.094', 'dh_ultima_remessa': '2025-09-16 11:10:26.000', 'id_estacao': 3045, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.896, 'longitude': -43.352, 'nome': 'Praça Seca', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455703A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2014-07-31 20:39:13.358', 'dh_cadastro': '2014-07-31 20:39:13.358', 'dh_inicio_inativo': '2023-05-26 20:16:22.557', 'dh_ultima_remessa': '2023-05-26 18:09:53.000', 'id_estacao': 3042, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.885906, 'longitude': -43.297753, 'nome': 'Abolição', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}, {'altitude': 0.0, 'cidade': 'RIO DE JANEIRO', 'codestacao': '330455701A', 'codibge': 3304557, 'cota_alerta': None, 'cota_atencao': None, 'cota_transbordamento': None, 'data_instalacao': '2014-02-28 18:07:10.559', 'dh_cadastro': '2014-02-28 18:07:10.559', 'dh_inicio_inativo': '2025-09-03 14:35:49.411', 'dh_ultima_remessa': '2025-09-03 12:34:16.000', 'id_estacao': 3114, 'id_rede': 11, 'id_tipoestacao': 1, 'latitude': -22.915, 'longitude': -43.176, 'nome': 'Glória', 'offset': None, 'rede_sigla': 'CEMADEN', 'tipoestacao_descricao': 'Pluviométrica', 'uf': 'RJ'}]\n" + ] + } + ], + "source": [ + "url_cemaden = \"https://sws.cemaden.gov.br/PED/rest/pcds-cadastro/dados-cadastrais\"\n", + "\n", + "token = get_token(VAR.nome_secreto, VAR.senha_secreta)\n", + "codibge = \"3304557\" #Rio de janeiro\n", + "\n", + "headers = {\n", + " \"token\": token\n", + "}\n", + "\n", + "params = {\n", + " \"codibge\": codibge,\n", + " \"formato\": \"json\" \n", + "}\n", + "\n", + "response = requests.get(url_cemaden, headers=headers, params=params)\n", + "posicoes = {}\n", + "if response.status_code == 200:\n", + " estacoes = response.json()\n", + " print(\"Número de estações encontradas:\", len(estacoes))\n", + " for estacao in estacoes: \n", + " codigo = estacao.get(\"codestacao\")\n", + " lat = estacao.get(\"latitude\")\n", + " lon = estacao.get(\"longitude\")\n", + " if codigo and lat and lon:\n", + " posicoes[codigo] = (lat, lon)\n", + "\n", + " print(\"Dicionário de posições das estações:\")\n", + " for cod, coords in list(posicoes.items()): \n", + " print(f\"{cod}: {coords}\")\n", + "else:\n", + " print(\"Erro ao buscar estações:\", response.status_code)\n", + "\n", + "print(estacoes)\n", + "for codestacao, (lat, lon) in posicoes.items():\n", + " folium.Circle(\n", + " location=[lat,lon],\n", + " # popup=f\"Estação: {codestacao}\",\n", + " fill=True,\n", + " color='purple',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)" + ] + }, + { + "cell_type": "markdown", + "id": "b057628d", + "metadata": {}, + "source": [ + "ALERTA RIO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fb2830e7", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "df_estacoes = pd.read_csv('../../config/GaugeStations.csv')\n", + "\n", + "df_estacoes_pluviometricas = df_estacoes[~df_estacoes.index.isin([2,3,4,5,6,7,8,9,10,12,13,14,15,17,18,20,21,23,24,25,27,29,30,31,33])]\n", + "df_estacoes_meteorologicas = df_estacoes[df_estacoes.index.isin([1,11,16,19,20,22,28,32])]\n", + "df_estacoes.head()\n", + "\n", + "lat = list(df_estacoes_pluviometricas.VL_LATITUDE)\n", + "lon = list(df_estacoes_pluviometricas.VL_LONGITUDE)\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=10,\n", + " fill=True,\n", + " color='red',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)\n", + "\n", + "lat = list(df_estacoes_meteorologicas.VL_LATITUDE)\n", + "lon = list(df_estacoes_meteorologicas.VL_LONGITUDE)\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=10,\n", + " fill=True,\n", + " color='black',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)" + ] + }, + { + "cell_type": "markdown", + "id": "bda7ae7b", + "metadata": {}, + "source": [ + "INMET" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "d7b4940a", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "#Novo data set\n", + "dfnew = pd.read_json('https://apitempo.inmet.gov.br/estacoes/T')\n", + "dfnewrj = dfnew[dfnew['SG_ESTADO'] == 'RJ']\n", + "\n", + "dfnewrj.head()\n", + "\n", + "lat = list(dfnewrj.VL_LATITUDE)\n", + "lon = list(dfnewrj.VL_LONGITUDE)\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=10,\n", + " fill=True,\n", + " color='blue',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)\n" + ] + }, + { + "cell_type": "markdown", + "id": "baafcf8b", + "metadata": {}, + "source": [ + "SIRENES" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "0d849a0a", + "metadata": {}, + "outputs": [], + "source": [ + "sirenes = pd.read_parquet('../data/websirenes_defesa_civil/websirenes_stations.parquet')\n", + "sirenes.head()\n", + "\n", + "lat = list(sirenes.latitude)\n", + "lon = list(sirenes.longitude)\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=10,\n", + " fill=True,\n", + " color='green',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "1515cfbd", + "metadata": {}, + "outputs": [], + "source": [ + "# Define the legend\n", + "legend_dict = {\n", + " \"Sirenes\": \"green\",\n", + " \"INMET\": \"blue\",\n", + " \"COR_Pluviométricas\": \"red\",\n", + " \"COR_Meteorológicas\": \"black\",\n", + " \"CEMADEN\": \"purple\",\n", + " \"Radar_Sumaré\": \"grey\"\n", + "}\n", + "\n", + "mapa.add_legend(title=\"Legend Title\", legend_dict=legend_dict)\n", + "mapa.to_html(\"mapa.html\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "40cb75c3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mapa" + ] + }, + { + "cell_type": "markdown", + "id": "910d5dcb", + "metadata": {}, + "source": [ + "Resoluções temporais dos sistemas utilizados:\n", + "- CEMADEN : 1h\n", + "- INMET: 1h\n", + "- SUMARÉ: 2min\n", + "- COR: 15min\n", + "- SIRENES: 15min" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "ea940273", + "metadata": {}, + "outputs": [], + "source": [ + "cemaden_temp_resolution = \"1H\"\n", + "inmet_temp_resolution = \"1h\"\n", + "sumare_temp_resolution = \"2min\"\n", + "cor_temp_resolution = \"15min\"\n", + "sirenes_temp_resolution = \"15min\"" + ] + }, + { + "cell_type": "markdown", + "id": "465831ad", + "metadata": {}, + "source": [ + "Processamento dos dados do radar sumaré - Correspondência pixel/latitude-longitude:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "05db99fe", + "metadata": {}, + "outputs": [], + "source": [ + "def rgb_distance(c1, c2):\n", + " return math.sqrt((c1[0] - c2[0])**2 + (c1[1] - c2[1])**2 + (c1[2] - c2[2])**2)\n", + "\n", + "def interpolate_value(rgb, legend_colors, legend_values):\n", + " if rgb == (0,0,0):\n", + " return 0\n", + " # Calcular distâncias entre a cor fornecida e todas as cores da legenda\n", + " distances = [rgb_distance(rgb, lc) for lc in legend_colors]\n", + "\n", + " # Identificar as duas cores mais próximas na legenda\n", + " min_idx1 = distances.index(min(distances)) # Índice da cor mais próxima\n", + " distances[min_idx1] = float('inf') # Excluir a cor mais próxima para achar a segunda\n", + " min_idx2 = distances.index(min(distances)) # Índice da segunda cor mais próxima\n", + "\n", + " # Obter as cores e valores correspondentes\n", + " c1, c2 = legend_colors[min_idx1], legend_colors[min_idx2]\n", + " v1, v2 = legend_values[min_idx1], legend_values[min_idx2]\n", + "\n", + " # Calcular o peso de interpolação (t)\n", + " dist_c1_c2 = rgb_distance(c1, c2)\n", + " dist_c1_rgb = rgb_distance(c1, rgb)\n", + " t = dist_c1_rgb / dist_c1_c2 if dist_c1_c2 != 0 else 0\n", + "\n", + " # Interpolar o valor\n", + " interpolated_value = v1 + t * (v2 - v1)\n", + " return interpolated_value\n", + "\n", + "def get_radar_data(inicio, fim, frequencia, latitude, longitude):\n", + " latitude = float(latitude)\n", + " longitude = float(longitude)\n", + "\n", + " pos_sumare = (-22.955139,-43.248278)\n", + " legend_values = [50, 45, 40, 35, 30, 25, 20,0]\n", + " legend_colors = [\n", + " (197,0,197), # Magenta\n", + " (227,6,5), # Vermelho\n", + " (255,112,0), # Laranja\n", + " (195,230,0), # Amarelo\n", + " (4,85,4), # Amarelo\n", + " (19,122,19), # Verde escuro\n", + " (0,167,12), # Verde claro\n", + " (0,0,0) #Vazio\n", + " ]\n", + "\n", + " # Definir datas inicial e final\n", + " data_inicial = inicio + \" 00:00:00\"\n", + " data_final = fim + \" 23:58:00\"\n", + "\n", + " datas = pd.date_range(start=data_inicial, end=data_final, freq=frequencia)\n", + "\n", + " # Criar DataFrame com coluna \"datahora\"\n", + " radar_data = pd.DataFrame({\"datahora\": datas})\n", + " radar_data['reflect'] = np.nan\n", + "\n", + " count = 0\n", + " while count < len(radar_data):\n", + "\n", + " datetime_str = radar_data.iloc[count]['datahora'].strftime(\"%Y-%m-%d %H:%M:%S\")\n", + " \n", + " year = datetime_str[0:4]\n", + " month = datetime_str[5:7]\n", + " day = datetime_str[8:10]\n", + " hour = datetime_str[11:13]\n", + " minute = datetime_str[14:16]\n", + " file = year + '_'+ month + '_'+ day + '_' + hour + '_' + minute + '.png'\n", + " file_path = '../data/radar_sumare/' + year + \"/\" + month + \"/\" + day + \"/\" + file\n", + "\n", + " if os.path.exists(file_path):\n", + " try:\n", + " img = Image.open(file_path)\n", + " pos_sumare_img = (img.height/2, img.width/2)\n", + "\n", + " dify = (pos_sumare_img[0]/pos_sumare[0])\n", + " difx = (pos_sumare_img[1]/pos_sumare[1])\n", + "\n", + " posx = pos_sumare[1] - ((longitude - pos_sumare[1]) * 32.5)\n", + " valorx = posx * difx\n", + " posy = pos_sumare[0] + ((latitude - pos_sumare[0]) * 19.5)\n", + " valory = posy * dify\n", + " \n", + " rgb_im = img.convert('RGB')\n", + " r, g, b = rgb_im.getpixel((valorx, valory))\n", + " radar_data.at[count,'reflect'] = interpolate_value((r, g, b), legend_colors, legend_values)\n", + "\n", + " print(radar_data.iloc[count])\n", + " except Exception as e:\n", + " print(\"Mensagem de erro:\", str(e))\n", + " \n", + " count += 1\n", + "\n", + " return radar_data" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "488d8f0d", + "metadata": {}, + "outputs": [], + "source": [ + "def dispersao(data,x,y,titulo):# Gráfico de dispersão com seaborn\n", + " sns.scatterplot(x=x, y=y, data=data)\n", + " plt.title(titulo)\n", + " plt.savefig(titulo + \".png\", dpi=300, bbox_inches=\"tight\") # PNG em alta resolução\n", + " #plt.savefig(\"dispersao.pdf\", bbox_inches=\"tight\") # PDF vetorial\n", + " #plt.savefig(\"dispersao.svg\", bbox_inches=\"tight\") # SVG vetorial" + ] + }, + { + "cell_type": "markdown", + "id": "21ab117a", + "metadata": {}, + "source": [ + "CEMADEN - RADAR_SUMARE: CORRELAÇÃO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "61833eee", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(28, 21)\n" + ] + }, + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "altitude", + "rawType": "float64", + "type": "float" + }, + { + "name": "cidade", + "rawType": "object", + "type": "string" + }, + { + "name": "codestacao", + "rawType": "object", + "type": "string" + }, + { + "name": "codibge", + "rawType": "int64", + "type": "integer" + }, + { + "name": "cota_alerta", + "rawType": "object", + "type": "unknown" + }, + { + "name": "cota_atencao", + "rawType": "object", + "type": "unknown" + }, + { + "name": "cota_transbordamento", + "rawType": "object", + "type": "unknown" + }, + { + "name": "data_instalacao", + "rawType": "object", + "type": "string" + }, + { + "name": "dh_cadastro", + "rawType": "object", + "type": "string" + }, + { + "name": "dh_inicio_inativo", + "rawType": "object", + "type": "string" + }, + { + "name": "dh_ultima_remessa", 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altitudecidadecodestacaocodibgecota_alertacota_atencaocota_transbordamentodata_instalacaodh_cadastrodh_inicio_inativo...id_estacaoid_redeid_tipoestacaolatitudelongitudenomeoffsetrede_siglatipoestacao_descricaouf
00.0RIO DE JANEIRO330455734A3304557NoneNoneNone2015-04-17 13:23:58.9322015-04-17 13:23:58.9322024-03-26 20:45:51.749...7615111-22.761300-43.108400Ilha de PaquetáNoneCEMADENPluviométricaRJ
10.0RIO DE JANEIRO330455733A3304557NoneNoneNone2015-05-22 11:03:39.6092015-05-22 11:03:39.6092025-05-24 03:35:26.360...7614111-22.875000-43.299000PilaresNoneCEMADENPluviométricaRJ
20.0RIO DE JANEIRO330455732A3304557NoneNoneNone2015-05-26 13:12:55.7352015-05-26 13:12:55.7352025-06-26 06:26:19.726...7613111-22.869000-43.265000HigienópolisNoneCEMADENPluviométricaRJ
30.0RIO DE JANEIRO330455731A3304557NoneNoneNone2015-03-04 20:17:58.8352015-03-04 20:17:58.8352025-06-26 07:16:09.334...7612111-22.948000-43.258000UsinaNoneCEMADENPluviométricaRJ
40.0RIO DE JANEIRO330455730A3304557NoneNoneNone2015-05-20 13:03:35.9022015-05-20 13:03:35.9022025-09-03 13:04:55.200...7611111-22.943000-43.241000TijucaNoneCEMADENPluviométricaRJ
50.0RIO DE JANEIRO330455729A3304557NoneNoneNone2015-08-20 12:31:52.7842015-08-20 12:31:52.7842025-08-05 15:14:16.114...7610111-22.966600-43.296500Alto da Boa VistaNoneCEMADENPluviométricaRJ
60.0RIO DE JANEIRO330455728A3304557NoneNoneNone2015-05-15 12:53:15.8272015-05-15 12:53:15.8272025-05-28 22:07:38.597...7609111-22.860860-43.307560Vicente de CarvalhoNoneCEMADENPluviométricaRJ
70.0RIO DE JANEIRO330455726A3304557NoneNoneNone2015-02-20 14:31:36.6732015-02-20 14:31:36.6732023-06-27 18:52:25.122...7607111-22.894000-43.676000Defesa Civil Santa CruzNoneCEMADENPluviométricaRJ
80.0RIO DE JANEIRO330455725A3304557NoneNoneNone2015-05-04 13:35:59.3982015-05-04 13:35:59.3982025-06-26 06:44:45.865...7606111-22.813100-43.310100Vigário GeralNoneCEMADENPluviométricaRJ
90.0RIO DE JANEIRO330455724A3304557NoneNoneNone2015-05-04 14:11:06.1522015-05-04 14:11:06.1522025-09-05 11:38:23.659...7605111-22.807600-43.358400PavunaNoneCEMADENPluviométricaRJ
100.0RIO DE JANEIRO330455722A3304557NoneNoneNone2015-05-26 14:20:15.0642015-05-26 14:20:15.0642025-08-26 11:13:10.581...7603111-22.923000-43.176000CateteNoneCEMADENPluviométricaRJ
110.0RIO DE JANEIRO330455721A3304557NoneNoneNone2015-05-26 13:34:42.1702015-05-26 13:34:42.1702025-09-03 13:15:08.103...7602111-22.995000-43.269000São ConradoNoneCEMADENPluviométricaRJ
120.0RIO DE JANEIRO330455720A3304557NoneNoneNone2015-05-14 12:57:54.2072015-05-14 12:57:54.2072025-02-26 19:15:51.543...7601111-22.796000-43.203000CIEP Dr. João Ramos de SouzaNoneCEMADENPluviométricaRJ
130.0RIO DE JANEIRO330455719A3304557NoneNoneNone2015-05-06 13:19:01.3532015-05-06 13:19:01.3532025-06-26 07:03:35.434...7600111-22.992200-43.367000JacarepaguáNoneCEMADENPluviométricaRJ
140.0RIO DE JANEIRO330455718A3304557NoneNoneNone2015-05-14 14:45:28.9822015-05-14 14:45:28.9822025-07-01 18:52:28.342...7599111-22.989000-43.433000Vargem PequenaNoneCEMADENPluviométricaRJ
150.0RIO DE JANEIRO330455716A3304557NoneNoneNone2015-05-20 16:05:42.2332015-05-20 16:05:42.2332025-09-15 20:45:36.457...7597111-22.921000-43.227000CIEP Samuel WainerNoneCEMADENPluviométricaRJ
160.0RIO DE JANEIRO330455715A3304557NoneNoneNone2015-08-04 12:58:24.1702015-08-04 12:58:24.1702024-09-15 03:36:18.534...7596111-22.930000-43.250000AndaraíNoneCEMADENPluviométricaRJ
170.0RIO DE JANEIRO330455714A3304557NoneNoneNone2015-07-22 13:24:23.6872015-07-22 13:24:23.6872025-04-24 20:20:05.277...7595111-22.929000-43.228000SalgueiroNoneCEMADENPluviométricaRJ
180.0RIO DE JANEIRO330455713A3304557NoneNoneNone2015-04-16 19:27:51.6032015-04-16 19:27:51.6032025-06-26 07:16:15.456...7594111-22.868900-43.450700Padre MiguelNoneCEMADENPluviométricaRJ
190.0RIO DE JANEIRO330455712A3304557NoneNoneNone2015-04-16 18:07:00.0272015-04-16 18:07:00.0272025-09-02 18:21:09.815...7593111-22.864000-43.425000Realengo BatanNoneCEMADENPluviométricaRJ
200.0RIO DE JANEIRO330455711A3304557NoneNoneNone2015-04-28 13:48:37.8612015-04-28 13:48:37.8612025-05-24 03:11:57.786...7592111-22.889700-43.717500Santa CruzNoneCEMADENPluviométricaRJ
210.0RIO DE JANEIRO330455710A3304557NoneNoneNone2015-07-23 13:25:13.8942015-07-23 13:25:13.8942025-05-21 18:53:37.848...7591111-22.959200-43.608200Jardim MaravilhaNoneCEMADENPluviométricaRJ
220.0RIO DE JANEIRO330455709A3304557NoneNoneNone2014-03-20 16:22:50.8142014-03-20 16:22:50.8142025-09-03 12:53:48.571...3215111-22.977861-43.277444Est. Pedra BonitaNoneCEMADENPluviométricaRJ
230.0RIO DE JANEIRO330455706A3304557NoneNoneNone2014-02-28 11:59:31.1272014-02-28 11:59:31.1272025-09-15 03:30:06.097...3044111-22.839000-43.279000PenhaNoneCEMADENPluviométricaRJ
240.0RIO DE JANEIRO330455705A3304557NoneNoneNone2014-02-21 16:51:32.5242014-02-21 16:51:32.5242025-07-18 04:56:25.882...3043111-22.918000-43.361000Tanque JacarepaguaNoneCEMADENPluviométricaRJ
250.0RIO DE JANEIRO330455704A3304557NoneNoneNone2014-02-21 19:51:52.8962014-02-21 19:51:52.8962025-07-15 19:07:56.094...3045111-22.896000-43.352000Praça SecaNoneCEMADENPluviométricaRJ
260.0RIO DE JANEIRO330455703A3304557NoneNoneNone2014-07-31 20:39:13.3582014-07-31 20:39:13.3582023-05-26 20:16:22.557...3042111-22.885906-43.297753AboliçãoNoneCEMADENPluviométricaRJ
270.0RIO DE JANEIRO330455701A3304557NoneNoneNone2014-02-28 18:07:10.5592014-02-28 18:07:10.5592025-09-03 14:35:49.411...3114111-22.915000-43.176000GlóriaNoneCEMADENPluviométricaRJ
\n", + "

28 rows × 21 columns

\n", + "
" + ], + "text/plain": [ + " altitude cidade codestacao codibge cota_alerta cota_atencao \\\n", + "0 0.0 RIO DE JANEIRO 330455734A 3304557 None None \n", + "1 0.0 RIO DE JANEIRO 330455733A 3304557 None None \n", + "2 0.0 RIO DE JANEIRO 330455732A 3304557 None None \n", + "3 0.0 RIO DE JANEIRO 330455731A 3304557 None None \n", + "4 0.0 RIO DE JANEIRO 330455730A 3304557 None None \n", + "5 0.0 RIO DE JANEIRO 330455729A 3304557 None None \n", + "6 0.0 RIO DE JANEIRO 330455728A 3304557 None None \n", + "7 0.0 RIO DE JANEIRO 330455726A 3304557 None None \n", + "8 0.0 RIO DE JANEIRO 330455725A 3304557 None None \n", + "9 0.0 RIO DE JANEIRO 330455724A 3304557 None None \n", + "10 0.0 RIO DE JANEIRO 330455722A 3304557 None None \n", + "11 0.0 RIO DE JANEIRO 330455721A 3304557 None None \n", + "12 0.0 RIO DE JANEIRO 330455720A 3304557 None None \n", + "13 0.0 RIO DE JANEIRO 330455719A 3304557 None None \n", + "14 0.0 RIO DE JANEIRO 330455718A 3304557 None None \n", + "15 0.0 RIO DE JANEIRO 330455716A 3304557 None None \n", + "16 0.0 RIO DE JANEIRO 330455715A 3304557 None None \n", + "17 0.0 RIO DE JANEIRO 330455714A 3304557 None None \n", + "18 0.0 RIO DE JANEIRO 330455713A 3304557 None None \n", + "19 0.0 RIO DE JANEIRO 330455712A 3304557 None None \n", + "20 0.0 RIO DE JANEIRO 330455711A 3304557 None None \n", + "21 0.0 RIO DE JANEIRO 330455710A 3304557 None None \n", + "22 0.0 RIO DE JANEIRO 330455709A 3304557 None None \n", + "23 0.0 RIO DE JANEIRO 330455706A 3304557 None None \n", + "24 0.0 RIO DE JANEIRO 330455705A 3304557 None None \n", + "25 0.0 RIO DE JANEIRO 330455704A 3304557 None None \n", + "26 0.0 RIO DE JANEIRO 330455703A 3304557 None None \n", + "27 0.0 RIO DE JANEIRO 330455701A 3304557 None None \n", + "\n", + " cota_transbordamento data_instalacao dh_cadastro \\\n", + "0 None 2015-04-17 13:23:58.932 2015-04-17 13:23:58.932 \n", + "1 None 2015-05-22 11:03:39.609 2015-05-22 11:03:39.609 \n", + "2 None 2015-05-26 13:12:55.735 2015-05-26 13:12:55.735 \n", + "3 None 2015-03-04 20:17:58.835 2015-03-04 20:17:58.835 \n", + "4 None 2015-05-20 13:03:35.902 2015-05-20 13:03:35.902 \n", + "5 None 2015-08-20 12:31:52.784 2015-08-20 12:31:52.784 \n", + "6 None 2015-05-15 12:53:15.827 2015-05-15 12:53:15.827 \n", + "7 None 2015-02-20 14:31:36.673 2015-02-20 14:31:36.673 \n", + "8 None 2015-05-04 13:35:59.398 2015-05-04 13:35:59.398 \n", + "9 None 2015-05-04 14:11:06.152 2015-05-04 14:11:06.152 \n", + "10 None 2015-05-26 14:20:15.064 2015-05-26 14:20:15.064 \n", + "11 None 2015-05-26 13:34:42.170 2015-05-26 13:34:42.170 \n", + "12 None 2015-05-14 12:57:54.207 2015-05-14 12:57:54.207 \n", + "13 None 2015-05-06 13:19:01.353 2015-05-06 13:19:01.353 \n", + "14 None 2015-05-14 14:45:28.982 2015-05-14 14:45:28.982 \n", + "15 None 2015-05-20 16:05:42.233 2015-05-20 16:05:42.233 \n", + "16 None 2015-08-04 12:58:24.170 2015-08-04 12:58:24.170 \n", + "17 None 2015-07-22 13:24:23.687 2015-07-22 13:24:23.687 \n", + "18 None 2015-04-16 19:27:51.603 2015-04-16 19:27:51.603 \n", + "19 None 2015-04-16 18:07:00.027 2015-04-16 18:07:00.027 \n", + "20 None 2015-04-28 13:48:37.861 2015-04-28 13:48:37.861 \n", + "21 None 2015-07-23 13:25:13.894 2015-07-23 13:25:13.894 \n", + "22 None 2014-03-20 16:22:50.814 2014-03-20 16:22:50.814 \n", + "23 None 2014-02-28 11:59:31.127 2014-02-28 11:59:31.127 \n", + "24 None 2014-02-21 16:51:32.524 2014-02-21 16:51:32.524 \n", + "25 None 2014-02-21 19:51:52.896 2014-02-21 19:51:52.896 \n", + "26 None 2014-07-31 20:39:13.358 2014-07-31 20:39:13.358 \n", + "27 None 2014-02-28 18:07:10.559 2014-02-28 18:07:10.559 \n", + "\n", + " dh_inicio_inativo ... id_estacao id_rede id_tipoestacao \\\n", + "0 2024-03-26 20:45:51.749 ... 7615 11 1 \n", + "1 2025-05-24 03:35:26.360 ... 7614 11 1 \n", + "2 2025-06-26 06:26:19.726 ... 7613 11 1 \n", + "3 2025-06-26 07:16:09.334 ... 7612 11 1 \n", + "4 2025-09-03 13:04:55.200 ... 7611 11 1 \n", + "5 2025-08-05 15:14:16.114 ... 7610 11 1 \n", + "6 2025-05-28 22:07:38.597 ... 7609 11 1 \n", + "7 2023-06-27 18:52:25.122 ... 7607 11 1 \n", + "8 2025-06-26 06:44:45.865 ... 7606 11 1 \n", + "9 2025-09-05 11:38:23.659 ... 7605 11 1 \n", + "10 2025-08-26 11:13:10.581 ... 7603 11 1 \n", + "11 2025-09-03 13:15:08.103 ... 7602 11 1 \n", + "12 2025-02-26 19:15:51.543 ... 7601 11 1 \n", + "13 2025-06-26 07:03:35.434 ... 7600 11 1 \n", + "14 2025-07-01 18:52:28.342 ... 7599 11 1 \n", + "15 2025-09-15 20:45:36.457 ... 7597 11 1 \n", + "16 2024-09-15 03:36:18.534 ... 7596 11 1 \n", + "17 2025-04-24 20:20:05.277 ... 7595 11 1 \n", + "18 2025-06-26 07:16:15.456 ... 7594 11 1 \n", + "19 2025-09-02 18:21:09.815 ... 7593 11 1 \n", + "20 2025-05-24 03:11:57.786 ... 7592 11 1 \n", + "21 2025-05-21 18:53:37.848 ... 7591 11 1 \n", + "22 2025-09-03 12:53:48.571 ... 3215 11 1 \n", + "23 2025-09-15 03:30:06.097 ... 3044 11 1 \n", + "24 2025-07-18 04:56:25.882 ... 3043 11 1 \n", + "25 2025-07-15 19:07:56.094 ... 3045 11 1 \n", + "26 2023-05-26 20:16:22.557 ... 3042 11 1 \n", + "27 2025-09-03 14:35:49.411 ... 3114 11 1 \n", + "\n", + " latitude longitude nome offset rede_sigla \\\n", + "0 -22.761300 -43.108400 Ilha de Paquetá None CEMADEN \n", + "1 -22.875000 -43.299000 Pilares None CEMADEN \n", + "2 -22.869000 -43.265000 Higienópolis None CEMADEN \n", + "3 -22.948000 -43.258000 Usina None CEMADEN \n", + "4 -22.943000 -43.241000 Tijuca None CEMADEN \n", + "5 -22.966600 -43.296500 Alto da Boa Vista None CEMADEN \n", + "6 -22.860860 -43.307560 Vicente de Carvalho None CEMADEN \n", + "7 -22.894000 -43.676000 Defesa Civil Santa Cruz None CEMADEN \n", + "8 -22.813100 -43.310100 Vigário Geral None CEMADEN \n", + "9 -22.807600 -43.358400 Pavuna None CEMADEN \n", + "10 -22.923000 -43.176000 Catete None CEMADEN \n", + "11 -22.995000 -43.269000 São Conrado None CEMADEN \n", + "12 -22.796000 -43.203000 CIEP Dr. João Ramos de Souza None CEMADEN \n", + "13 -22.992200 -43.367000 Jacarepaguá None CEMADEN \n", + "14 -22.989000 -43.433000 Vargem Pequena None CEMADEN \n", + "15 -22.921000 -43.227000 CIEP Samuel Wainer None CEMADEN \n", + "16 -22.930000 -43.250000 Andaraí None CEMADEN \n", + "17 -22.929000 -43.228000 Salgueiro None CEMADEN \n", + "18 -22.868900 -43.450700 Padre Miguel None CEMADEN \n", + "19 -22.864000 -43.425000 Realengo Batan None CEMADEN \n", + "20 -22.889700 -43.717500 Santa Cruz None CEMADEN \n", + "21 -22.959200 -43.608200 Jardim Maravilha None CEMADEN \n", + "22 -22.977861 -43.277444 Est. Pedra Bonita None CEMADEN \n", + "23 -22.839000 -43.279000 Penha None CEMADEN \n", + "24 -22.918000 -43.361000 Tanque Jacarepagua None CEMADEN \n", + "25 -22.896000 -43.352000 Praça Seca None CEMADEN \n", + "26 -22.885906 -43.297753 Abolição None CEMADEN \n", + "27 -22.915000 -43.176000 Glória None CEMADEN \n", + "\n", + " tipoestacao_descricao uf \n", + "0 Pluviométrica RJ \n", + "1 Pluviométrica RJ \n", + "2 Pluviométrica RJ \n", + "3 Pluviométrica RJ \n", + "4 Pluviométrica RJ \n", + "5 Pluviométrica RJ \n", + "6 Pluviométrica RJ \n", + "7 Pluviométrica RJ \n", + "8 Pluviométrica RJ \n", + "9 Pluviométrica RJ \n", + "10 Pluviométrica RJ \n", + "11 Pluviométrica RJ \n", + "12 Pluviométrica RJ \n", + "13 Pluviométrica RJ \n", + "14 Pluviométrica RJ \n", + "15 Pluviométrica RJ \n", + "16 Pluviométrica RJ \n", + "17 Pluviométrica RJ \n", + "18 Pluviométrica RJ \n", + "19 Pluviométrica RJ \n", + "20 Pluviométrica RJ \n", + "21 Pluviométrica RJ \n", + "22 Pluviométrica RJ \n", + "23 Pluviométrica RJ \n", + "24 Pluviométrica RJ \n", + "25 Pluviométrica RJ \n", + "26 Pluviométrica RJ \n", + "27 Pluviométrica RJ \n", + "\n", + "[28 rows x 21 columns]" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cemaden_info_stations = pd.DataFrame(estacoes)\n", + "print(cemaden_info_stations.shape)\n", + "cemaden_info_stations.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "6adf0c48", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "datahora", + "rawType": "object", + "type": "string" + }, + { + "name": "chuva", + "rawType": "float64", + "type": "float" + }, + { + "name": "intensidade_precipitacao", + "rawType": "float64", + "type": "float" + }, + { + "name": "precipitacao_nao_registrada", + "rawType": "float64", + "type": "float" + } + ], + "ref": "a9233d7c-dbcd-4fe6-a786-1187f28c69f0", + "rows": [ + [ + "0", + "2015-06-25 18:40:00", + "0.2", + "1.0", + null + ], + [ + "1", + "2015-06-25 18:50:00", + "0.0", + "0.0", + null + ], + [ + "2", + "2015-06-25 19:00:00", + "0.0", + "0.0", + null + ], + [ + "3", + "2015-06-25 20:00:00", + "0.0", + "0.0", + null + ], + [ + "4", + "2015-06-25 21:00:00", + "0.0", + "0.0", + null + ] + ], + "shape": { + "columns": 4, + "rows": 5 + } + }, + "text/html": [ + "
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sensordatahorachuvaintensidade_precipitacaoprecipitacao_nao_registrada
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" + ], + "text/plain": [ + "sensor datahora chuva intensidade_precipitacao \\\n", + "0 2015-06-25 18:40:00 0.2 1.0 \n", + "1 2015-06-25 18:50:00 0.0 0.0 \n", + "2 2015-06-25 19:00:00 0.0 0.0 \n", + "3 2015-06-25 20:00:00 0.0 0.0 \n", + "4 2015-06-25 21:00:00 0.0 0.0 \n", + "\n", + "sensor precipitacao_nao_registrada \n", + "0 NaN \n", + "1 NaN \n", + "2 NaN \n", + "3 NaN \n", + "4 NaN " + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "cemaden_directory = \"../data/ws/cemaden/raw/\"\n", + "cemaden_data_station = pd.read_parquet(cemaden_directory + \"330455734A.parquet\") #Ilha de Paquetá\n", + "cemaden_data_station.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "0c14d455", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sensor\n", + "datahora object\n", + "chuva float64\n", + "intensidade_precipitacao float64\n", + "precipitacao_nao_registrada float64\n", + "dtype: object\n", + "[ 0.2 0. 0.4 0.8 1.2 0.6 2.6 1.6 1. 3. 1.4 4. 2.4 3.6\n", + " 3.4 6.2 5. 3.2 2.2 4.4 2. 4.8 6.4 15. 9.8 7.4 4.6 6.8\n", + " 8.8 1.8 6. 5.2 5.4 7.8 5.8 2.8 17.8 26.8 17.6 9.6 6.6 9.\n", + " 10.6 8.2 14.6 5.6 0.6 1.2 2.4 7. 5.6 3.8 11.4 10.4 2.8 8.4\n", + " 8. 6.8 5.8 7.6 6.6 4.2 12. nan 13.6 10. 4.8 4.6 7.8 3.4\n", + " 8.6 12.8 15.2 13.8 15.8 17.4 7.2 8.2 12.4 18.4 11.2 21.2 23. 14.8\n", + " 14.4 11. 11.8 9.4 19.6 13. 20. 16.8 17.2 16.2 13.2 18. 15.4 11.6\n", + " 18.2 30. 14. 17. 78.8]\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "print(cemaden_data_station.dtypes)\n", + "print(cemaden_data_station[\"chuva\"].unique())\n", + "cemaden_data_station[\"datahora\"] = pd.to_datetime(cemaden_data_station[\"datahora\"], errors=\"coerce\", dayfirst=True)\n", + "\n", + "# Gráfico de dispersão com seaborn\n", + "sns.scatterplot(x=\"datahora\", y=\"chuva\", data=cemaden_data_station)\n", + "plt.title(\"Chuva ao longo do tempo\")\n", + "\n", + "# Salvar em diferentes formatos\n", + "plt.savefig(\"dispersao.png\", dpi=300, bbox_inches=\"tight\") # PNG em alta resolução\n", + "#plt.savefig(\"dispersao.pdf\", bbox_inches=\"tight\") # PDF vetorial\n", + "#plt.savefig(\"dispersao.svg\", bbox_inches=\"tight\") # SVG vetorial\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "1265079c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Ilha de Paquetá -22.7613 -43.1084\n", + "datahora 2011-01-17 18:00:00\n", + "reflect 0.0\n", + "Name: 402, dtype: object\n", + "datahora 2011-01-17 19:00:00\n", + "reflect 0.0\n", + "Name: 403, dtype: object\n", + "datahora 2011-01-17 21:00:00\n", + "reflect 0.0\n", + "Name: 405, dtype: object\n", + "datahora 2011-01-17 22:00:00\n", + "reflect 0.0\n", + "Name: 406, dtype: object\n", + "datahora 2011-01-17 23:00:00\n", + "reflect 0.0\n", + "Name: 407, dtype: object\n", + "datahora 2011-01-18 00:00:00\n", + "reflect 0.0\n", + "Name: 408, dtype: object\n", + "datahora 2011-01-18 01:00:00\n", + "reflect 0.0\n", + "Name: 409, dtype: object\n", + "datahora 2011-01-18 02:00:00\n", + "reflect 0.0\n", + "Name: 410, dtype: object\n", + "datahora 2011-01-18 03:00:00\n", + "reflect 0.0\n", + "Name: 411, dtype: object\n", + "datahora 2011-01-18 04:00:00\n", + "reflect 0.0\n", + "Name: 412, dtype: object\n", + "datahora 2011-01-18 05:00:00\n", + "reflect 0.0\n", + "Name: 413, dtype: object\n", + "datahora 2011-01-18 06:00:00\n", + "reflect 0.0\n", + "Name: 414, dtype: object\n", + "datahora 2011-01-18 07:00:00\n", + "reflect 0.0\n", + "Name: 415, dtype: object\n", + "datahora 2011-01-18 08:00:00\n", + "reflect 0.0\n", + "Name: 416, dtype: object\n", + "datahora 2011-01-18 09:00:00\n", + "reflect 0.0\n", + "Name: 417, dtype: object\n", + "datahora 2011-01-18 10:00:00\n", + "reflect 0.0\n", + "Name: 418, dtype: object\n", + "datahora 2011-01-18 11:00:00\n", + "reflect 0.0\n", + "Name: 419, dtype: object\n", + "datahora 2011-01-18 12:00:00\n", + "reflect 0.0\n", + "Name: 420, dtype: object\n", + "datahora 2011-01-18 14:00:00\n", + "reflect 0.0\n", + "Name: 422, dtype: object\n", + "datahora 2011-01-20 15:00:00\n", + "reflect 0.0\n", + "Name: 471, dtype: object\n", + "datahora 2011-01-20 16:00:00\n", + "reflect 0.0\n", + "Name: 472, dtype: object\n", + "datahora 2011-01-20 17:00:00\n", + "reflect 0.0\n", + "Name: 473, dtype: object\n", + "datahora 2011-01-20 18:00:00\n", + "reflect 0.0\n", 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object\n", + "datahora 2019-08-03 23:00:00\n", + "reflect 0.0\n", + "Name: 75287, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/04/2019_08_04_00_00.png'\n", + "datahora 2019-08-04 02:00:00\n", + "reflect 0.0\n", + "Name: 75290, dtype: object\n", + "datahora 2019-08-04 03:00:00\n", + "reflect 0.0\n", + "Name: 75291, dtype: object\n", + "datahora 2019-08-04 04:00:00\n", + "reflect 0.0\n", + "Name: 75292, dtype: object\n", + "datahora 2019-08-04 05:00:00\n", + "reflect 0.0\n", + "Name: 75293, dtype: object\n", + "datahora 2019-08-04 06:00:00\n", + "reflect 0.0\n", + "Name: 75294, dtype: object\n", + "datahora 2019-08-04 07:00:00\n", + "reflect 0.0\n", + "Name: 75295, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/04/2019_08_04_08_00.png'\n", + "datahora 2019-08-04 09:00:00\n", + "reflect 0.0\n", + "Name: 75297, dtype: object\n", + "datahora 2019-08-04 10:00:00\n", + "reflect 0.0\n", + "Name: 75298, dtype: object\n", + "datahora 2019-08-04 11:00:00\n", + "reflect 0.0\n", + "Name: 75299, dtype: object\n", + "datahora 2019-08-04 12:00:00\n", + "reflect 0.0\n", + "Name: 75300, dtype: object\n", + "datahora 2019-08-04 13:00:00\n", + "reflect 0.0\n", + "Name: 75301, dtype: object\n", + "datahora 2019-08-04 14:00:00\n", + "reflect 0.0\n", + "Name: 75302, dtype: object\n", + "datahora 2019-08-04 15:00:00\n", + "reflect 0.0\n", + "Name: 75303, dtype: object\n", + "Mensagem de erro: image file is truncated\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/04/2019_08_04_18_00.png'\n", + "datahora 2019-08-04 19:00:00\n", + "reflect 0.0\n", + "Name: 75307, dtype: object\n", + "datahora 2019-08-04 20:00:00\n", + "reflect 0.0\n", + "Name: 75308, dtype: object\n", + "datahora 2019-08-04 21:00:00\n", + "reflect 0.0\n", + "Name: 75309, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/04/2019_08_04_22_00.png'\n", + "datahora 2019-08-04 23:00:00\n", + "reflect 0.0\n", + "Name: 75311, dtype: object\n", + "datahora 2019-08-05 00:00:00\n", + "reflect 0.0\n", + "Name: 75312, dtype: object\n", + "datahora 2019-08-05 01:00:00\n", + "reflect 0.0\n", + "Name: 75313, dtype: object\n", + "datahora 2019-08-05 02:00:00\n", + "reflect 0.0\n", + "Name: 75314, dtype: object\n", + "datahora 2019-08-05 03:00:00\n", + "reflect 0.0\n", + "Name: 75315, dtype: object\n", + "datahora 2019-08-05 04:00:00\n", + "reflect 0.0\n", + "Name: 75316, dtype: object\n", + "datahora 2019-08-05 05:00:00\n", + "reflect 0.0\n", + "Name: 75317, dtype: object\n", + "datahora 2019-08-05 07:00:00\n", + "reflect 0.0\n", + "Name: 75319, dtype: object\n", + "datahora 2019-08-05 08:00:00\n", + "reflect 0.0\n", + "Name: 75320, dtype: object\n", + "datahora 2019-08-05 09:00:00\n", + "reflect 0.0\n", + "Name: 75321, dtype: object\n", + "datahora 2019-08-05 10:00:00\n", + "reflect 0.0\n", + "Name: 75322, dtype: object\n", + "datahora 2019-08-05 11:00:00\n", + "reflect 0.0\n", + "Name: 75323, dtype: object\n", + "datahora 2019-08-05 12:00:00\n", + "reflect 0.0\n", + "Name: 75324, dtype: object\n", + "datahora 2019-08-05 13:00:00\n", + "reflect 0.0\n", + "Name: 75325, dtype: object\n", + "datahora 2019-08-05 14:00:00\n", + "reflect 0.0\n", + "Name: 75326, dtype: object\n", + "datahora 2019-08-05 15:00:00\n", + "reflect 0.0\n", + "Name: 75327, dtype: object\n", + "datahora 2019-08-05 16:00:00\n", + "reflect 0.0\n", + "Name: 75328, dtype: object\n", + "datahora 2019-08-05 17:00:00\n", + "reflect 0.0\n", + "Name: 75329, dtype: object\n", + "datahora 2019-08-05 18:00:00\n", + "reflect 0.0\n", + "Name: 75330, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/05/2019_08_05_19_00.png'\n", + "datahora 2019-08-05 20:00:00\n", + "reflect 0.0\n", + "Name: 75332, dtype: object\n", + "datahora 2019-08-05 21:00:00\n", + "reflect 0.0\n", + "Name: 75333, dtype: object\n", + "datahora 2019-08-05 22:00:00\n", + "reflect 0.0\n", + "Name: 75334, dtype: object\n", + "datahora 2019-08-05 23:00:00\n", + "reflect 0.0\n", + "Name: 75335, dtype: object\n", + "datahora 2019-08-06 00:00:00\n", + "reflect 0.0\n", + "Name: 75336, dtype: object\n", + "datahora 2019-08-06 01:00:00\n", + "reflect 0.0\n", + "Name: 75337, dtype: object\n", + "datahora 2019-08-06 02:00:00\n", + "reflect 0.0\n", + "Name: 75338, dtype: object\n", + "datahora 2019-08-06 03:00:00\n", + "reflect 0.0\n", + "Name: 75339, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/06/2019_08_06_04_00.png'\n", + "datahora 2019-08-06 05:00:00\n", + "reflect 0.0\n", + "Name: 75341, dtype: object\n", + "datahora 2019-08-06 06:00:00\n", + "reflect 0.0\n", + "Name: 75342, dtype: object\n", + "datahora 2019-08-06 07:00:00\n", + "reflect 0.0\n", + "Name: 75343, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/06/2019_08_06_08_00.png'\n", + "datahora 2019-08-06 09:00:00\n", + "reflect 0.0\n", + "Name: 75345, dtype: object\n", + "datahora 2019-08-06 10:00:00\n", + "reflect 0.0\n", + "Name: 75346, dtype: object\n", + "datahora 2019-08-06 12:00:00\n", + "reflect 0.0\n", + "Name: 75348, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/06/2019_08_06_21_00.png'\n", + "datahora 2019-08-06 22:00:00\n", + "reflect 0.0\n", + "Name: 75358, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/06/2019_08_06_23_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/07/2019_08_07_00_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/07/2019_08_07_01_00.png'\n", + "datahora 2019-08-07 02:00:00\n", + "reflect 0.0\n", + "Name: 75362, dtype: object\n", + "datahora 2019-08-07 03:00:00\n", + "reflect 0.0\n", + "Name: 75363, dtype: object\n", + "datahora 2019-08-07 04:00:00\n", + "reflect 0.0\n", + "Name: 75364, dtype: object\n", + "datahora 2019-08-07 05:00:00\n", + "reflect 0.0\n", + "Name: 75365, dtype: object\n", + "datahora 2019-08-07 06:00:00\n", + "reflect 0.0\n", + "Name: 75366, dtype: object\n", + "datahora 2019-08-07 07:00:00\n", + "reflect 0.0\n", + "Name: 75367, dtype: object\n", + "datahora 2019-08-07 08:00:00\n", + "reflect 0.0\n", + "Name: 75368, dtype: object\n", + "datahora 2019-08-07 20:00:00\n", + "reflect 0.0\n", + "Name: 75380, dtype: object\n", + "datahora 2019-08-07 21:00:00\n", + "reflect 0.0\n", + "Name: 75381, dtype: object\n", + "datahora 2019-08-07 22:00:00\n", + "reflect 0.0\n", + "Name: 75382, dtype: object\n", + "datahora 2019-08-07 23:00:00\n", + "reflect 0.0\n", + "Name: 75383, dtype: object\n", + "datahora 2019-08-08 00:00:00\n", + "reflect 0.0\n", + "Name: 75384, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/08/2019_08_08_01_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/08/2019_08_08_02_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/08/2019_08_08_03_00.png'\n", + "datahora 2019-08-08 04:00:00\n", + "reflect 0.0\n", + "Name: 75388, dtype: object\n", + "datahora 2019-08-08 05:00:00\n", + "reflect 0.0\n", + "Name: 75389, dtype: object\n", + "datahora 2019-08-08 06:00:00\n", + "reflect 0.0\n", + "Name: 75390, dtype: object\n", + "datahora 2019-08-08 07:00:00\n", + "reflect 0.0\n", + "Name: 75391, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/08/2019_08_08_08_00.png'\n", + "datahora 2019-08-08 09:00:00\n", + "reflect 0.0\n", + "Name: 75393, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/08/2019_08_08_10_00.png'\n", + "datahora 2019-08-08 20:00:00\n", + "reflect 0.0\n", + "Name: 75404, dtype: object\n", + "datahora 2019-08-08 21:00:00\n", + "reflect 0.0\n", + "Name: 75405, dtype: object\n", + "datahora 2019-08-08 22:00:00\n", + "reflect 0.0\n", + "Name: 75406, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/08/2019_08_08_23_00.png'\n", + "datahora 2019-08-09 00:00:00\n", + "reflect 0.0\n", + "Name: 75408, dtype: object\n", + "datahora 2019-08-09 01:00:00\n", + "reflect 0.0\n", + "Name: 75409, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/09/2019_08_09_02_00.png'\n", + "datahora 2019-08-09 03:00:00\n", + "reflect 0.0\n", + "Name: 75411, dtype: object\n", + "datahora 2019-08-09 04:00:00\n", + "reflect 0.0\n", + "Name: 75412, dtype: object\n", + "datahora 2019-08-09 05:00:00\n", + "reflect 0.0\n", + "Name: 75413, dtype: object\n", + "datahora 2019-08-09 06:00:00\n", + "reflect 0.0\n", + "Name: 75414, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/09/2019_08_09_07_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/09/2019_08_09_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/09/2019_08_09_22_00.png'\n", + "datahora 2019-08-09 23:00:00\n", + "reflect 0.0\n", + "Name: 75431, dtype: object\n", + "datahora 2019-08-10 00:00:00\n", + "reflect 0.0\n", + "Name: 75432, dtype: object\n", + "datahora 2019-08-10 01:00:00\n", + "reflect 0.0\n", + "Name: 75433, dtype: object\n", + "datahora 2019-08-10 02:00:00\n", + "reflect 0.0\n", + "Name: 75434, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/10/2019_08_10_04_00.png'\n", + "datahora 2019-08-10 05:00:00\n", + "reflect 0.0\n", + "Name: 75437, dtype: object\n", + "datahora 2019-08-10 06:00:00\n", + "reflect 0.0\n", + "Name: 75438, dtype: object\n", + "datahora 2019-08-10 07:00:00\n", + "reflect 0.0\n", + "Name: 75439, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/10/2019_08_10_08_00.png'\n", + "datahora 2019-08-10 21:00:00\n", + "reflect 0.0\n", + "Name: 75453, dtype: object\n", + "datahora 2019-08-10 22:00:00\n", + "reflect 0.0\n", + "Name: 75454, dtype: object\n", + "datahora 2019-08-10 23:00:00\n", + "reflect 0.0\n", + "Name: 75455, dtype: object\n", + "datahora 2019-08-11 00:00:00\n", + "reflect 0.0\n", + "Name: 75456, dtype: object\n", + "datahora 2019-08-11 01:00:00\n", + "reflect 0.0\n", + "Name: 75457, dtype: object\n", + "datahora 2019-08-11 02:00:00\n", + "reflect 0.0\n", + "Name: 75458, dtype: object\n", + "datahora 2019-08-11 03:00:00\n", + "reflect 0.0\n", + "Name: 75459, dtype: object\n", + "datahora 2019-08-11 04:00:00\n", + "reflect 0.0\n", + "Name: 75460, dtype: object\n", + "datahora 2019-08-11 05:00:00\n", + "reflect 0.0\n", + "Name: 75461, dtype: object\n", + "datahora 2019-08-11 06:00:00\n", + "reflect 0.0\n", + "Name: 75462, dtype: object\n", + "datahora 2019-08-11 07:00:00\n", + "reflect 0.0\n", + "Name: 75463, dtype: object\n", + "datahora 2019-08-11 08:00:00\n", + "reflect 0.0\n", + "Name: 75464, dtype: object\n", + "datahora 2019-08-11 10:00:00\n", + "reflect 0.0\n", + "Name: 75466, dtype: object\n", + "datahora 2019-08-11 11:00:00\n", + "reflect 0.0\n", + "Name: 75467, dtype: object\n", + "datahora 2019-08-11 12:00:00\n", + "reflect 0.0\n", + "Name: 75468, dtype: object\n", + "datahora 2019-08-11 13:00:00\n", + "reflect 0.0\n", + "Name: 75469, dtype: object\n", + "datahora 2019-08-11 14:00:00\n", + "reflect 0.0\n", + "Name: 75470, dtype: object\n", + "datahora 2019-08-11 15:00:00\n", + "reflect 0.0\n", + "Name: 75471, dtype: object\n", + "datahora 2019-08-11 16:00:00\n", + "reflect 0.0\n", + "Name: 75472, dtype: object\n", + "datahora 2019-08-11 17:00:00\n", + "reflect 0.0\n", + "Name: 75473, dtype: object\n", + "datahora 2019-08-11 18:00:00\n", + "reflect 0.0\n", + "Name: 75474, dtype: object\n", + "datahora 2019-08-11 19:00:00\n", + "reflect 0.0\n", + "Name: 75475, dtype: object\n", + "datahora 2019-08-11 20:00:00\n", + "reflect 0.0\n", + "Name: 75476, dtype: object\n", + "datahora 2019-08-11 21:00:00\n", + "reflect 0.0\n", + "Name: 75477, dtype: object\n", + "datahora 2019-08-11 22:00:00\n", + "reflect 0.0\n", + "Name: 75478, dtype: object\n", + "datahora 2019-08-11 23:00:00\n", + "reflect 0.0\n", + "Name: 75479, dtype: object\n", + "datahora 2019-08-12 00:00:00\n", + "reflect 0.0\n", + "Name: 75480, dtype: object\n", + "datahora 2019-08-12 01:00:00\n", + "reflect 0.0\n", + "Name: 75481, dtype: object\n", + "datahora 2019-08-12 02:00:00\n", + "reflect 0.0\n", + "Name: 75482, dtype: object\n", + "datahora 2019-08-12 03:00:00\n", + "reflect 0.0\n", + "Name: 75483, dtype: object\n", + "datahora 2019-08-12 04:00:00\n", + "reflect 0.0\n", + "Name: 75484, dtype: object\n", + "datahora 2019-08-12 05:00:00\n", + "reflect 0.0\n", + "Name: 75485, dtype: object\n", + "datahora 2019-08-12 06:00:00\n", + "reflect 0.0\n", + "Name: 75486, dtype: object\n", + "datahora 2019-08-12 07:00:00\n", + "reflect 0.0\n", + "Name: 75487, dtype: object\n", + "datahora 2019-08-12 08:00:00\n", + "reflect 0.0\n", + "Name: 75488, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/12/2019_08_12_09_00.png'\n", + "datahora 2019-08-12 10:00:00\n", + "reflect 0.0\n", + "Name: 75490, dtype: object\n", + "datahora 2019-08-12 21:00:00\n", + "reflect 0.0\n", + "Name: 75501, dtype: object\n", + "datahora 2019-08-12 22:00:00\n", + "reflect 0.0\n", + "Name: 75502, dtype: object\n", + "datahora 2019-08-12 23:00:00\n", + "reflect 0.0\n", + "Name: 75503, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_00_00.png'\n", + "datahora 2019-08-13 01:00:00\n", + "reflect 0.0\n", + "Name: 75505, dtype: object\n", + "datahora 2019-08-13 02:00:00\n", + "reflect 0.0\n", + "Name: 75506, dtype: object\n", + "datahora 2019-08-13 03:00:00\n", + "reflect 0.0\n", + "Name: 75507, dtype: object\n", + "datahora 2019-08-13 04:00:00\n", + "reflect 0.0\n", + "Name: 75508, dtype: object\n", + "datahora 2019-08-13 05:00:00\n", + "reflect 0.0\n", + "Name: 75509, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_06_00.png'\n", + "datahora 2019-08-13 07:00:00\n", + "reflect 0.0\n", + "Name: 75511, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_08_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_09_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_10_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_11_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_12_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_13_00.png'\n", + "datahora 2019-08-13 14:00:00\n", + "reflect 0.0\n", + "Name: 75518, dtype: object\n", + "datahora 2019-08-13 15:00:00\n", + "reflect 0.0\n", + "Name: 75519, dtype: object\n", + "datahora 2019-08-13 16:00:00\n", + "reflect 0.0\n", + "Name: 75520, dtype: object\n", + "datahora 2019-08-13 17:00:00\n", + "reflect 0.0\n", + "Name: 75521, dtype: object\n", + "datahora 2019-08-13 18:00:00\n", + "reflect 0.0\n", + "Name: 75522, dtype: object\n", + "datahora 2019-08-13 19:00:00\n", + "reflect 20.0\n", + "Name: 75523, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/13/2019_08_13_20_00.png'\n", + "datahora 2019-08-13 21:00:00\n", + "reflect 0.0\n", + "Name: 75525, dtype: object\n", + "datahora 2019-08-13 22:00:00\n", + "reflect 0.0\n", + "Name: 75526, dtype: object\n", + "datahora 2019-08-13 23:00:00\n", + "reflect 0.0\n", + "Name: 75527, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/14/2019_08_14_00_00.png'\n", + "datahora 2019-08-14 01:00:00\n", + "reflect 0.0\n", + "Name: 75529, dtype: object\n", + "datahora 2019-08-14 03:00:00\n", + "reflect 0.0\n", + "Name: 75531, dtype: object\n", + "datahora 2019-08-14 04:00:00\n", + "reflect 0.0\n", + "Name: 75532, dtype: object\n", + "datahora 2019-08-14 05:00:00\n", + "reflect 0.0\n", + "Name: 75533, dtype: object\n", + "datahora 2019-08-14 06:00:00\n", + "reflect 0.0\n", + "Name: 75534, dtype: object\n", + "datahora 2019-08-14 07:00:00\n", + "reflect 0.0\n", + "Name: 75535, dtype: object\n", + "datahora 2019-08-14 08:00:00\n", + "reflect 0.0\n", + "Name: 75536, dtype: object\n", + "datahora 2019-08-14 09:00:00\n", + "reflect 0.0\n", + "Name: 75537, dtype: object\n", + "datahora 2019-08-14 10:00:00\n", + "reflect 0.0\n", + "Name: 75538, dtype: object\n", + "datahora 2019-08-14 11:00:00\n", + "reflect 0.0\n", + "Name: 75539, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/14/2019_08_14_12_00.png'\n", + "datahora 2019-08-14 13:00:00\n", + "reflect 0.0\n", + "Name: 75541, dtype: object\n", + "datahora 2019-08-14 14:00:00\n", + "reflect 0.0\n", + "Name: 75542, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/14/2019_08_14_15_00.png'\n", + "datahora 2019-08-14 16:00:00\n", + "reflect 0.0\n", + "Name: 75544, dtype: object\n", + "datahora 2019-08-14 17:00:00\n", + "reflect 0.0\n", + "Name: 75545, dtype: object\n", + "datahora 2019-08-14 18:00:00\n", + "reflect 0.0\n", + "Name: 75546, dtype: object\n", + "datahora 2019-08-14 19:00:00\n", + "reflect 0.0\n", + "Name: 75547, dtype: object\n", + "datahora 2019-08-14 20:00:00\n", + "reflect 0.0\n", + "Name: 75548, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/14/2019_08_14_21_00.png'\n", + "datahora 2019-08-14 22:00:00\n", + "reflect 0.0\n", + "Name: 75550, dtype: object\n", + "datahora 2019-08-14 23:00:00\n", + "reflect 0.0\n", + "Name: 75551, dtype: object\n", + "datahora 2019-08-15 00:00:00\n", + "reflect 0.0\n", + "Name: 75552, dtype: object\n", + "datahora 2019-08-15 01:00:00\n", + "reflect 0.0\n", + "Name: 75553, dtype: object\n", + "datahora 2019-08-15 02:00:00\n", + "reflect 0.0\n", + "Name: 75554, dtype: object\n", + "datahora 2019-08-15 03:00:00\n", + "reflect 0.0\n", + "Name: 75555, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_04_00.png'\n", + "datahora 2019-08-15 05:00:00\n", + "reflect 0.0\n", + "Name: 75557, dtype: object\n", + "datahora 2019-08-15 06:00:00\n", + "reflect 0.0\n", + "Name: 75558, dtype: object\n", + "datahora 2019-08-15 07:00:00\n", + "reflect 0.0\n", + "Name: 75559, dtype: object\n", + "datahora 2019-08-15 08:00:00\n", + "reflect 0.0\n", + "Name: 75560, dtype: object\n", + "datahora 2019-08-15 09:00:00\n", + "reflect 0.0\n", + "Name: 75561, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_10_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_11_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_12_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_13_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_14_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_15_00.png'\n", + "datahora 2019-08-15 16:00:00\n", + "reflect 0.0\n", + "Name: 75568, dtype: object\n", + "datahora 2019-08-15 17:00:00\n", + "reflect 0.0\n", + "Name: 75569, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/15/2019_08_15_18_00.png'\n", + "datahora 2019-08-15 19:00:00\n", + "reflect 0.0\n", + "Name: 75571, dtype: object\n", + "datahora 2019-08-15 20:00:00\n", + "reflect 0.0\n", + "Name: 75572, dtype: object\n", + "datahora 2019-08-15 21:00:00\n", + "reflect 0.0\n", + "Name: 75573, dtype: object\n", + "datahora 2019-08-15 22:00:00\n", + "reflect 0.0\n", + "Name: 75574, dtype: object\n", + "datahora 2019-08-15 23:00:00\n", + "reflect 0.0\n", + "Name: 75575, dtype: object\n", + "datahora 2019-08-16 00:00:00\n", + "reflect 0.0\n", + "Name: 75576, dtype: object\n", + "datahora 2019-08-16 01:00:00\n", + "reflect 0.0\n", + "Name: 75577, dtype: object\n", + "datahora 2019-08-16 02:00:00\n", + "reflect 0.0\n", + "Name: 75578, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/16/2019_08_16_03_00.png'\n", + "datahora 2019-08-16 04:00:00\n", + "reflect 0.0\n", + "Name: 75580, dtype: object\n", + "datahora 2019-08-16 05:00:00\n", + "reflect 0.0\n", + "Name: 75581, dtype: object\n", + "datahora 2019-08-16 06:00:00\n", + "reflect 0.0\n", + "Name: 75582, dtype: object\n", + "datahora 2019-08-16 07:00:00\n", + "reflect 0.0\n", + "Name: 75583, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/16/2019_08_16_08_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/16/2019_08_16_09_00.png'\n", + "datahora 2019-08-16 10:00:00\n", + "reflect 0.0\n", + "Name: 75586, dtype: object\n", + "datahora 2019-08-16 21:00:00\n", + "reflect 0.0\n", + "Name: 75597, dtype: object\n", + "datahora 2019-08-16 22:00:00\n", + "reflect 0.0\n", + "Name: 75598, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/16/2019_08_16_23_00.png'\n", + "datahora 2019-08-17 00:00:00\n", + "reflect 0.0\n", + "Name: 75600, dtype: object\n", + "datahora 2019-08-17 01:00:00\n", + "reflect 0.0\n", + "Name: 75601, dtype: object\n", + "datahora 2019-08-17 02:00:00\n", + "reflect 0.0\n", + "Name: 75602, dtype: object\n", + "datahora 2019-08-17 03:00:00\n", + "reflect 0.0\n", + "Name: 75603, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/17/2019_08_17_04_00.png'\n", + "datahora 2019-08-17 05:00:00\n", + "reflect 0.0\n", + "Name: 75605, dtype: object\n", + "datahora 2019-08-17 20:00:00\n", + "reflect 0.0\n", + "Name: 75620, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/17/2019_08_17_21_00.png'\n", + "datahora 2019-08-17 22:00:00\n", + "reflect 0.0\n", + "Name: 75622, dtype: object\n", + "datahora 2019-08-17 23:00:00\n", + "reflect 0.0\n", + "Name: 75623, dtype: object\n", + "datahora 2019-08-18 00:00:00\n", + "reflect 0.0\n", + "Name: 75624, dtype: object\n", + "datahora 2019-08-18 01:00:00\n", + "reflect 0.0\n", + "Name: 75625, dtype: object\n", + "datahora 2019-08-18 02:00:00\n", + "reflect 0.0\n", + "Name: 75626, dtype: object\n", + "datahora 2019-08-18 03:00:00\n", + "reflect 0.0\n", + "Name: 75627, dtype: object\n", + "datahora 2019-08-18 04:00:00\n", + "reflect 0.0\n", + "Name: 75628, dtype: object\n", + "datahora 2019-08-18 05:00:00\n", + "reflect 0.0\n", + "Name: 75629, dtype: object\n", + "datahora 2019-08-18 06:00:00\n", + "reflect 0.0\n", + "Name: 75630, dtype: object\n", + "datahora 2019-08-18 07:00:00\n", + "reflect 0.0\n", + "Name: 75631, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/18/2019_08_18_21_00.png'\n", + "datahora 2019-08-18 22:00:00\n", + "reflect 0.0\n", + "Name: 75646, dtype: object\n", + "datahora 2019-08-18 23:00:00\n", + "reflect 0.0\n", + "Name: 75647, dtype: object\n", + "datahora 2019-08-19 00:00:00\n", + "reflect 0.0\n", + "Name: 75648, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/19/2019_08_19_01_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/19/2019_08_19_02_00.png'\n", + "datahora 2019-08-19 03:00:00\n", + "reflect 0.0\n", + "Name: 75651, dtype: object\n", + "datahora 2019-08-19 04:00:00\n", + "reflect 0.0\n", + "Name: 75652, dtype: object\n", + "datahora 2019-08-19 05:00:00\n", + "reflect 0.0\n", + "Name: 75653, dtype: object\n", + "datahora 2019-08-19 06:00:00\n", + "reflect 0.0\n", + "Name: 75654, dtype: object\n", + "datahora 2019-08-19 07:00:00\n", + "reflect 0.0\n", + "Name: 75655, dtype: object\n", + "datahora 2019-08-19 08:00:00\n", + "reflect 0.0\n", + "Name: 75656, dtype: object\n", + "datahora 2019-08-19 09:00:00\n", + "reflect 0.0\n", + "Name: 75657, dtype: object\n", + "datahora 2019-08-19 10:00:00\n", + "reflect 0.0\n", + "Name: 75658, dtype: object\n", + "datahora 2019-08-19 11:00:00\n", + "reflect 0.0\n", + "Name: 75659, dtype: object\n", + "datahora 2019-08-19 12:00:00\n", + "reflect 0.0\n", + "Name: 75660, dtype: object\n", + "datahora 2019-08-19 13:00:00\n", + "reflect 0.0\n", + "Name: 75661, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/19/2019_08_19_14_00.png'\n", + "datahora 2019-08-19 15:00:00\n", + "reflect 0.0\n", + "Name: 75663, dtype: object\n", + "datahora 2019-08-19 16:00:00\n", + "reflect 0.0\n", + "Name: 75664, dtype: object\n", + "datahora 2019-08-19 17:00:00\n", + "reflect 0.0\n", + "Name: 75665, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/19/2019_08_19_18_00.png'\n", + "datahora 2019-08-19 19:00:00\n", + "reflect 0.0\n", + "Name: 75667, dtype: object\n", + "datahora 2019-08-19 20:00:00\n", + "reflect 0.0\n", + "Name: 75668, dtype: object\n", + "datahora 2019-08-19 21:00:00\n", + "reflect 0.0\n", + "Name: 75669, dtype: object\n", + "datahora 2019-08-19 22:00:00\n", + "reflect 0.0\n", + "Name: 75670, dtype: object\n", + "datahora 2019-08-19 23:00:00\n", + "reflect 0.0\n", + "Name: 75671, dtype: object\n", + "datahora 2019-08-20 00:00:00\n", + "reflect 0.0\n", + "Name: 75672, dtype: object\n", + "datahora 2019-08-20 01:00:00\n", + "reflect 0.0\n", + "Name: 75673, dtype: object\n", + "datahora 2019-08-20 02:00:00\n", + "reflect 0.0\n", + "Name: 75674, dtype: object\n", + "datahora 2019-08-20 03:00:00\n", + "reflect 0.0\n", + "Name: 75675, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_04_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_06_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_07_00.png'\n", + "datahora 2019-08-20 08:00:00\n", + "reflect 0.0\n", + "Name: 75680, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_09_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_10_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_11_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_12_00.png'\n", + "datahora 2019-08-20 13:00:00\n", + "reflect 0.0\n", + "Name: 75685, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_14_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_15_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_16_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_17_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_18_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_19_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_20_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_22_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/20/2019_08_20_23_00.png'\n", + "datahora 2019-08-21 04:00:00\n", + "reflect 0.0\n", + "Name: 75700, dtype: object\n", + "datahora 2019-08-21 07:00:00\n", + "reflect 0.0\n", + "Name: 75703, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_08_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_09_00.png'\n", + "datahora 2019-08-21 10:00:00\n", + "reflect 0.0\n", + "Name: 75706, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_11_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_12_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_14_00.png'\n", + "datahora 2019-08-21 16:00:00\n", + "reflect 0.0\n", + "Name: 75712, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_17_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_18_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_20_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/21/2019_08_21_22_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/22/2019_08_22_01_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/22/2019_08_22_04_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/22/2019_08_22_05_00.png'\n", + "datahora 2019-08-22 11:00:00\n", + "reflect 0.0\n", + "Name: 75731, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/22/2019_08_22_15_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/22/2019_08_22_17_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/23/2019_08_23_16_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/23/2019_08_23_20_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/23/2019_08_23_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/23/2019_08_23_23_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_00_00.png'\n", + "datahora 2019-08-24 02:00:00\n", + "reflect 0.0\n", + "Name: 75770, dtype: object\n", + "datahora 2019-08-24 03:00:00\n", + "reflect 0.0\n", + "Name: 75771, dtype: object\n", + "datahora 2019-08-24 04:00:00\n", + "reflect 0.0\n", + "Name: 75772, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_05_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_06_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_07_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_08_00.png'\n", + "datahora 2019-08-24 09:00:00\n", + "reflect 0.0\n", + "Name: 75777, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_10_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_12_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_13_00.png'\n", + "datahora 2019-08-24 14:00:00\n", + "reflect 0.0\n", + "Name: 75782, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_15_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_16_00.png'\n", + "datahora 2019-08-24 17:00:00\n", + "reflect 0.0\n", + "Name: 75785, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_18_00.png'\n", + "datahora 2019-08-24 19:00:00\n", + "reflect 0.0\n", + "Name: 75787, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_20_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_22_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/24/2019_08_24_23_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_00_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_06_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_07_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_09_00.png'\n", + "datahora 2019-08-25 10:00:00\n", + "reflect 0.0\n", + "Name: 75802, dtype: object\n", + "datahora 2019-08-25 11:00:00\n", + "reflect 0.0\n", + "Name: 75803, dtype: object\n", + "datahora 2019-08-25 13:00:00\n", + "reflect 0.0\n", + "Name: 75805, dtype: object\n", + "datahora 2019-08-25 14:00:00\n", + "reflect 0.0\n", + "Name: 75806, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_15_00.png'\n", + "datahora 2019-08-25 16:00:00\n", + "reflect 0.0\n", + "Name: 75808, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_17_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_18_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_20_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_22_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/25/2019_08_25_23_00.png'\n", + "datahora 2019-08-26 01:00:00\n", + "reflect 0.0\n", + "Name: 75817, dtype: object\n", + "datahora 2019-08-26 12:00:00\n", + "reflect 0.0\n", + "Name: 75828, dtype: object\n", + "datahora 2019-08-26 13:00:00\n", + "reflect 0.0\n", + "Name: 75829, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/26/2019_08_26_15_00.png'\n", + "datahora 2019-08-26 16:00:00\n", + "reflect 0.0\n", + "Name: 75832, dtype: object\n", + "datahora 2019-08-26 17:00:00\n", + "reflect 0.0\n", + "Name: 75833, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/26/2019_08_26_20_00.png'\n", + "datahora 2019-08-26 21:00:00\n", + "reflect 0.0\n", + "Name: 75837, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/27/2019_08_27_13_00.png'\n", + "datahora 2019-08-27 16:00:00\n", + "reflect 0.0\n", + "Name: 75856, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/08/27/2019_08_27_22_00.png'\n", + "datahora 2019-08-29 00:00:00\n", + "reflect 0.0\n", + "Name: 75888, dtype: object\n", + "datahora 2019-08-29 02:00:00\n", + "reflect 0.0\n", + "Name: 75890, dtype: object\n", + "datahora 2019-08-29 05:00:00\n", + "reflect 0.0\n", + 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object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/09/01/2019_09_01_03_00.png'\n", + "datahora 2019-09-01 04:00:00\n", + "reflect 0.0\n", + "Name: 75964, dtype: object\n", + "datahora 2019-09-01 05:00:00\n", + "reflect 0.0\n", + "Name: 75965, dtype: object\n", + "datahora 2019-09-01 06:00:00\n", + "reflect 0.0\n", + "Name: 75966, dtype: object\n", + "datahora 2019-09-01 07:00:00\n", + "reflect 0.0\n", + "Name: 75967, dtype: object\n", + "datahora 2019-09-01 08:00:00\n", + "reflect 0.0\n", + "Name: 75968, dtype: object\n", + "datahora 2019-09-01 09:00:00\n", + "reflect 0.0\n", + "Name: 75969, dtype: object\n", + "datahora 2019-09-01 10:00:00\n", + "reflect 0.0\n", + "Name: 75970, dtype: object\n", + "datahora 2019-09-01 11:00:00\n", + "reflect 0.0\n", + "Name: 75971, dtype: object\n", + "datahora 2019-09-01 12:00:00\n", + "reflect 0.0\n", + "Name: 75972, dtype: object\n", + "datahora 2019-09-01 13:00:00\n", + "reflect 0.0\n", + "Name: 75973, dtype: object\n", + "datahora 2019-09-01 14:00:00\n", + "reflect 0.0\n", + "Name: 75974, dtype: object\n", + "datahora 2019-09-01 15:00:00\n", + "reflect 0.0\n", + "Name: 75975, dtype: object\n", + "datahora 2019-09-01 16:00:00\n", + "reflect 0.0\n", + "Name: 75976, dtype: object\n", + "datahora 2019-09-01 17:00:00\n", + "reflect 35.0\n", + "Name: 75977, dtype: object\n", + "datahora 2019-09-01 18:00:00\n", + "reflect 0.0\n", + "Name: 75978, dtype: object\n", + "datahora 2019-09-01 19:00:00\n", + "reflect 0.0\n", + "Name: 75979, dtype: object\n", + "datahora 2019-09-01 20:00:00\n", + "reflect 0.0\n", + "Name: 75980, dtype: object\n", + "datahora 2019-09-01 21:00:00\n", + "reflect 0.0\n", + "Name: 75981, dtype: object\n", + "datahora 2019-09-01 22:00:00\n", + "reflect 44.015479\n", + "Name: 75982, dtype: object\n", + "datahora 2019-09-01 23:00:00\n", + "reflect 0.0\n", + "Name: 75983, dtype: object\n", + "datahora 2019-09-02 00:00:00\n", + "reflect 0.0\n", + "Name: 75984, dtype: object\n", + "datahora 2019-09-02 01:00:00\n", + "reflect 0.0\n", + "Name: 75985, dtype: object\n", + "datahora 2019-09-02 02:00:00\n", + "reflect 27.876802\n", + "Name: 75986, dtype: object\n", + "datahora 2019-09-02 03:00:00\n", + "reflect 0.0\n", + "Name: 75987, dtype: object\n", + "datahora 2019-09-02 04:00:00\n", + "reflect 0.0\n", + "Name: 75988, dtype: object\n", + "datahora 2019-09-02 05:00:00\n", + "reflect 0.0\n", + "Name: 75989, dtype: object\n", + "datahora 2019-09-02 06:00:00\n", + "reflect 0.0\n", + "Name: 75990, dtype: object\n", + "datahora 2019-09-02 07:00:00\n", + "reflect 0.0\n", + "Name: 75991, dtype: object\n", + "datahora 2019-09-02 08:00:00\n", + "reflect 0.0\n", + "Name: 75992, dtype: object\n", + "datahora 2019-09-02 09:00:00\n", + "reflect 0.0\n", + "Name: 75993, dtype: object\n", + "datahora 2019-09-02 10:00:00\n", + "reflect 0.0\n", + "Name: 75994, dtype: object\n", + "datahora 2019-09-02 11:00:00\n", + "reflect 0.0\n", + "Name: 75995, dtype: object\n", + "datahora 2019-09-02 12:00:00\n", + "reflect 0.0\n", + "Name: 75996, dtype: object\n", + "datahora 2019-09-02 13:00:00\n", + "reflect 0.0\n", + "Name: 75997, dtype: object\n", + "datahora 2019-09-02 14:00:00\n", + "reflect 0.0\n", + "Name: 75998, dtype: object\n", + "datahora 2019-09-02 15:00:00\n", + "reflect 0.0\n", + "Name: 75999, dtype: object\n", + "datahora 2019-09-02 16:00:00\n", + "reflect 0.0\n", + "Name: 76000, dtype: object\n", + "datahora 2019-09-02 17:00:00\n", + "reflect 0.0\n", + "Name: 76001, dtype: object\n", + "datahora 2019-09-02 18:00:00\n", + "reflect 0.0\n", + "Name: 76002, dtype: object\n", + "datahora 2019-09-02 19:00:00\n", + "reflect 0.0\n", + "Name: 76003, dtype: object\n", + "datahora 2019-09-02 20:00:00\n", + "reflect 0.0\n", + "Name: 76004, dtype: object\n", + "datahora 2019-09-02 21:00:00\n", + "reflect 0.0\n", + "Name: 76005, dtype: object\n", + "datahora 2019-09-02 22:00:00\n", + "reflect 0.0\n", + "Name: 76006, dtype: object\n", + "datahora 2019-09-02 23:00:00\n", + "reflect 0.0\n", + "Name: 76007, dtype: object\n", + "datahora 2019-09-03 00:00:00\n", + "reflect 0.0\n", + "Name: 76008, dtype: object\n", + "datahora 2019-09-03 01:00:00\n", + "reflect 0.0\n", + "Name: 76009, dtype: object\n", + "datahora 2019-09-03 02:00:00\n", + "reflect 0.0\n", + "Name: 76010, dtype: object\n", + "datahora 2019-09-03 03:00:00\n", + "reflect 0.0\n", + "Name: 76011, dtype: object\n", + "datahora 2019-09-03 04:00:00\n", + "reflect 0.0\n", + "Name: 76012, dtype: object\n", + "datahora 2019-09-03 05:00:00\n", + "reflect 0.0\n", + "Name: 76013, dtype: object\n", + "datahora 2019-09-03 06:00:00\n", + "reflect 0.0\n", + "Name: 76014, dtype: object\n", + "datahora 2019-09-03 07:00:00\n", + "reflect 0.0\n", + "Name: 76015, dtype: object\n", + "datahora 2019-09-03 08:00:00\n", + "reflect 0.0\n", + "Name: 76016, dtype: object\n", + "datahora 2019-09-03 09:00:00\n", + "reflect 0.0\n", + "Name: 76017, dtype: object\n", + "datahora 2019-09-03 10:00:00\n", + "reflect 0.0\n", + "Name: 76018, dtype: object\n", + "datahora 2019-09-03 11:00:00\n", + "reflect 0.0\n", + "Name: 76019, dtype: object\n", + "datahora 2019-09-03 12:00:00\n", + "reflect 0.0\n", + "Name: 76020, dtype: object\n", + "datahora 2019-09-03 13:00:00\n", + "reflect 0.0\n", + "Name: 76021, dtype: object\n", + "datahora 2019-09-03 14:00:00\n", + "reflect 0.0\n", + "Name: 76022, dtype: object\n", + "datahora 2019-09-03 15:00:00\n", + "reflect 0.0\n", + "Name: 76023, dtype: object\n", + "datahora 2019-09-03 16:00:00\n", + "reflect 0.0\n", + "Name: 76024, dtype: object\n", + "datahora 2019-09-03 17:00:00\n", + "reflect 0.0\n", + "Name: 76025, dtype: object\n", + "datahora 2019-09-03 18:00:00\n", + "reflect 20.0\n", + "Name: 76026, dtype: object\n", + "datahora 2019-09-03 19:00:00\n", + "reflect 0.0\n", + "Name: 76027, dtype: object\n", + "datahora 2019-09-03 20:00:00\n", + "reflect 0.0\n", + "Name: 76028, dtype: object\n", + "datahora 2019-09-03 21:00:00\n", + "reflect 0.0\n", + 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object\n", + "datahora 2019-09-04 09:00:00\n", + "reflect 20.0\n", + "Name: 76041, dtype: object\n", + "datahora 2019-09-04 10:00:00\n", + "reflect 0.0\n", + "Name: 76042, dtype: object\n", + "datahora 2019-09-04 11:00:00\n", + "reflect 0.0\n", + "Name: 76043, dtype: object\n", + "datahora 2019-09-04 12:00:00\n", + "reflect 0.0\n", + "Name: 76044, dtype: object\n", + "datahora 2019-09-04 13:00:00\n", + "reflect 0.0\n", + "Name: 76045, dtype: object\n", + "datahora 2019-09-04 14:00:00\n", + "reflect 0.0\n", + "Name: 76046, dtype: object\n", + "datahora 2019-09-04 15:00:00\n", + "reflect 0.0\n", + "Name: 76047, dtype: object\n", + "datahora 2019-09-04 16:00:00\n", + "reflect 0.0\n", + "Name: 76048, dtype: object\n", + "datahora 2019-09-04 17:00:00\n", + "reflect 0.0\n", + "Name: 76049, dtype: object\n", + "datahora 2019-09-04 18:00:00\n", + "reflect 0.0\n", + "Name: 76050, dtype: object\n", + "datahora 2019-09-04 19:00:00\n", + "reflect 0.0\n", + "Name: 76051, dtype: object\n", + 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object\n", + "datahora 2019-12-21 07:00:00\n", + "reflect 0.0\n", + "Name: 78631, dtype: object\n", + "datahora 2019-12-21 09:00:00\n", + "reflect 0.0\n", + "Name: 78633, dtype: object\n", + "datahora 2019-12-21 10:00:00\n", + "reflect 0.0\n", + "Name: 78634, dtype: object\n", + "datahora 2019-12-21 11:00:00\n", + "reflect 0.0\n", + "Name: 78635, dtype: object\n", + "datahora 2019-12-21 12:00:00\n", + "reflect 0.0\n", + "Name: 78636, dtype: object\n", + "datahora 2019-12-21 13:00:00\n", + "reflect 0.0\n", + "Name: 78637, dtype: object\n", + "datahora 2019-12-21 14:00:00\n", + "reflect 0.0\n", + "Name: 78638, dtype: object\n", + "datahora 2019-12-21 15:00:00\n", + "reflect 0.0\n", + "Name: 78639, dtype: object\n", + "datahora 2019-12-21 16:00:00\n", + "reflect 0.0\n", + "Name: 78640, dtype: object\n", + "datahora 2019-12-21 17:00:00\n", + "reflect 0.0\n", + "Name: 78641, dtype: object\n", + "datahora 2019-12-21 18:00:00\n", + "reflect 0.0\n", + "Name: 78642, dtype: object\n", + 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07:00:00\n", + "reflect 0.0\n", + "Name: 78655, dtype: object\n", + "datahora 2019-12-22 08:00:00\n", + "reflect 0.0\n", + "Name: 78656, dtype: object\n", + "datahora 2019-12-22 09:00:00\n", + "reflect 0.0\n", + "Name: 78657, dtype: object\n", + "datahora 2019-12-22 10:00:00\n", + "reflect 0.0\n", + "Name: 78658, dtype: object\n", + "datahora 2019-12-22 11:00:00\n", + "reflect 0.0\n", + "Name: 78659, dtype: object\n", + "datahora 2019-12-22 12:00:00\n", + "reflect 0.0\n", + "Name: 78660, dtype: object\n", + "datahora 2019-12-22 13:00:00\n", + "reflect 0.0\n", + "Name: 78661, dtype: object\n", + "datahora 2019-12-22 14:00:00\n", + "reflect 0.0\n", + "Name: 78662, dtype: object\n", + "datahora 2019-12-22 15:00:00\n", + "reflect 0.0\n", + "Name: 78663, dtype: object\n", + "datahora 2019-12-22 16:00:00\n", + "reflect 0.0\n", + "Name: 78664, dtype: object\n", + "datahora 2019-12-22 17:00:00\n", + "reflect 0.0\n", + "Name: 78665, dtype: object\n", + "datahora 2019-12-22 18:00:00\n", + 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0.0\n", + "Name: 78677, dtype: object\n", + "datahora 2019-12-23 06:00:00\n", + "reflect 0.0\n", + "Name: 78678, dtype: object\n", + "datahora 2019-12-23 07:00:00\n", + "reflect 0.0\n", + "Name: 78679, dtype: object\n", + "datahora 2019-12-23 08:00:00\n", + "reflect 0.0\n", + "Name: 78680, dtype: object\n", + "datahora 2019-12-23 09:00:00\n", + "reflect 0.0\n", + "Name: 78681, dtype: object\n", + "datahora 2019-12-23 10:00:00\n", + "reflect 0.0\n", + "Name: 78682, dtype: object\n", + "datahora 2019-12-23 11:00:00\n", + "reflect 0.0\n", + "Name: 78683, dtype: object\n", + "datahora 2019-12-23 12:00:00\n", + "reflect 0.0\n", + "Name: 78684, dtype: object\n", + "datahora 2019-12-23 13:00:00\n", + "reflect 0.0\n", + "Name: 78685, dtype: object\n", + "datahora 2019-12-23 14:00:00\n", + "reflect 0.0\n", + "Name: 78686, dtype: object\n", + "datahora 2019-12-23 15:00:00\n", + "reflect 27.693735\n", + "Name: 78687, dtype: object\n", + "datahora 2019-12-23 16:00:00\n", + "reflect 0.0\n", + 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object\n", + "datahora 2019-12-24 04:00:00\n", + "reflect 0.0\n", + "Name: 78700, dtype: object\n", + "datahora 2019-12-24 05:00:00\n", + "reflect 0.0\n", + "Name: 78701, dtype: object\n", + "datahora 2019-12-24 06:00:00\n", + "reflect 0.0\n", + "Name: 78702, dtype: object\n", + "datahora 2019-12-24 07:00:00\n", + "reflect 0.0\n", + "Name: 78703, dtype: object\n", + "datahora 2019-12-24 08:00:00\n", + "reflect 0.0\n", + "Name: 78704, dtype: object\n", + "datahora 2019-12-24 09:00:00\n", + "reflect 0.0\n", + "Name: 78705, dtype: object\n", + "datahora 2019-12-24 10:00:00\n", + "reflect 0.0\n", + "Name: 78706, dtype: object\n", + "datahora 2019-12-24 11:00:00\n", + "reflect 0.0\n", + "Name: 78707, dtype: object\n", + "datahora 2019-12-24 12:00:00\n", + "reflect 0.0\n", + "Name: 78708, dtype: object\n", + "datahora 2019-12-24 13:00:00\n", + "reflect 0.0\n", + "Name: 78709, dtype: object\n", + "datahora 2019-12-24 14:00:00\n", + "reflect 0.0\n", + "Name: 78710, dtype: object\n", + 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02:00:00\n", + "reflect 0.0\n", + "Name: 78722, dtype: object\n", + "datahora 2019-12-25 03:00:00\n", + "reflect 0.0\n", + "Name: 78723, dtype: object\n", + "datahora 2019-12-25 04:00:00\n", + "reflect 0.0\n", + "Name: 78724, dtype: object\n", + "datahora 2019-12-25 05:00:00\n", + "reflect 0.0\n", + "Name: 78725, dtype: object\n", + "datahora 2019-12-25 06:00:00\n", + "reflect 0.0\n", + "Name: 78726, dtype: object\n", + "datahora 2019-12-25 07:00:00\n", + "reflect 0.0\n", + "Name: 78727, dtype: object\n", + "datahora 2019-12-25 08:00:00\n", + "reflect 0.0\n", + "Name: 78728, dtype: object\n", + "datahora 2019-12-25 09:00:00\n", + "reflect 0.0\n", + "Name: 78729, dtype: object\n", + "datahora 2019-12-25 10:00:00\n", + "reflect 0.0\n", + "Name: 78730, dtype: object\n", + "datahora 2019-12-25 11:00:00\n", + "reflect 0.0\n", + "Name: 78731, dtype: object\n", + "datahora 2019-12-25 12:00:00\n", + "reflect 0.0\n", + "Name: 78732, dtype: object\n", + "datahora 2019-12-25 13:00:00\n", + 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03:00:00\n", + "reflect 0.0\n", + "Name: 78795, dtype: object\n", + "datahora 2019-12-28 12:00:00\n", + "reflect 0.0\n", + "Name: 78804, dtype: object\n", + "datahora 2019-12-28 13:00:00\n", + "reflect 0.0\n", + "Name: 78805, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/12/28/2019_12_28_19_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/12/28/2019_12_28_21_00.png'\n", + "datahora 2019-12-29 00:00:00\n", + "reflect 0.0\n", + "Name: 78816, dtype: object\n", + "datahora 2019-12-29 02:00:00\n", + "reflect 0.0\n", + "Name: 78818, dtype: object\n", + "datahora 2019-12-29 04:00:00\n", + "reflect 0.0\n", + "Name: 78820, dtype: object\n", + "datahora 2019-12-30 00:00:00\n", + "reflect 0.0\n", + "Name: 78840, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/12/30/2019_12_30_01_00.png'\n", + "datahora 2019-12-30 03:00:00\n", + "reflect 0.0\n", + "Name: 78843, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/12/30/2019_12_30_20_00.png'\n", + "datahora 2019-12-31 00:00:00\n", + "reflect 0.0\n", + "Name: 78864, dtype: object\n", + "datahora 2019-12-31 01:00:00\n", + "reflect 0.0\n", + "Name: 78865, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2019/12/31/2019_12_31_04_00.png'\n", + "datahora 2019-12-31 05:00:00\n", + "reflect 0.0\n", + "Name: 78869, dtype: object\n", + "datahora 2019-12-31 06:00:00\n", + "reflect 0.0\n", + "Name: 78870, dtype: object\n", + "datahora 2019-12-31 18:00:00\n", + "reflect 0.0\n", + "Name: 78882, dtype: object\n", + "datahora 2019-12-31 23:00:00\n", + "reflect 0.0\n", + "Name: 78887, dtype: object\n", + "datahora 2020-01-01 00:00:00\n", + "reflect 0.0\n", + "Name: 78888, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_01_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_02_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_03_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_04_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_05_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_06_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_07_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_08_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_09_00.png'\n", + "datahora 2020-01-01 10:00:00\n", + "reflect 0.0\n", + "Name: 78898, dtype: object\n", + "datahora 2020-01-01 11:00:00\n", + "reflect 0.0\n", + "Name: 78899, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_12_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_18_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_19_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_20_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_21_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_22_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/01/2020_01_01_23_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_00_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_01_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_02_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_03_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_04_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_05_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_06_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_07_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_08_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_09_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/02/2020_01_02_10_00.png'\n", + "Mensagem de erro: cannot identify image file 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erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_07_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_08_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_09_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_10_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_11_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_12_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_13_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_14_00.png'\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/01/03/2020_01_03_15_00.png'\n", + "Mensagem de erro: cannot identify image file 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object\n", + "datahora 2020-02-02 15:00:00\n", + "reflect 0.0\n", + "Name: 79671, dtype: object\n", + "datahora 2020-02-02 16:00:00\n", + "reflect 0.0\n", + "Name: 79672, dtype: object\n", + "datahora 2020-02-02 17:00:00\n", + "reflect 0.0\n", + "Name: 79673, dtype: object\n", + "datahora 2020-02-02 18:00:00\n", + "reflect 0.0\n", + "Name: 79674, dtype: object\n", + "datahora 2020-02-02 19:00:00\n", + "reflect 20.0\n", + "Name: 79675, dtype: object\n", + "datahora 2020-02-02 20:00:00\n", + "reflect 0.0\n", + "Name: 79676, dtype: object\n", + "datahora 2020-02-02 21:00:00\n", + "reflect 20.0\n", + "Name: 79677, dtype: object\n", + "datahora 2020-02-02 22:00:00\n", + "reflect 0.0\n", + "Name: 79678, dtype: object\n", + "datahora 2020-02-02 23:00:00\n", + "reflect 0.0\n", + "Name: 79679, dtype: object\n", + "datahora 2020-02-03 00:00:00\n", + "reflect 0.0\n", + "Name: 79680, dtype: object\n", + "datahora 2020-02-03 01:00:00\n", + "reflect 0.0\n", + "Name: 79681, dtype: object\n", + 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07:00:00\n", + "reflect 0.0\n", + "Name: 80167, dtype: object\n", + "datahora 2020-02-23 08:00:00\n", + "reflect 0.0\n", + "Name: 80168, dtype: object\n", + "datahora 2020-02-23 09:00:00\n", + "reflect 0.0\n", + "Name: 80169, dtype: object\n", + "datahora 2020-02-23 10:00:00\n", + "reflect 0.0\n", + "Name: 80170, dtype: object\n", + "datahora 2020-02-23 11:00:00\n", + "reflect 0.0\n", + "Name: 80171, dtype: object\n", + "datahora 2020-02-23 12:00:00\n", + "reflect 0.0\n", + "Name: 80172, dtype: object\n", + "datahora 2020-02-23 13:00:00\n", + "reflect 0.0\n", + "Name: 80173, dtype: object\n", + "datahora 2020-02-23 14:00:00\n", + "reflect 0.0\n", + "Name: 80174, dtype: object\n", + "datahora 2020-02-23 15:00:00\n", + "reflect 0.0\n", + "Name: 80175, dtype: object\n", + "datahora 2020-02-23 16:00:00\n", + "reflect 0.0\n", + "Name: 80176, dtype: object\n", + "datahora 2020-02-23 17:00:00\n", + "reflect 0.0\n", + "Name: 80177, dtype: object\n", + "datahora 2020-02-23 18:00:00\n", + 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object\n", + "datahora 2020-02-24 18:00:00\n", + "reflect 0.0\n", + "Name: 80202, dtype: object\n", + "datahora 2020-02-24 19:00:00\n", + "reflect 0.0\n", + "Name: 80203, dtype: object\n", + "datahora 2020-02-24 20:00:00\n", + "reflect 0.0\n", + "Name: 80204, dtype: object\n", + "datahora 2020-02-24 21:00:00\n", + "reflect 0.0\n", + "Name: 80205, dtype: object\n", + "datahora 2020-02-24 22:00:00\n", + "reflect 0.0\n", + "Name: 80206, dtype: object\n", + "datahora 2020-02-24 23:00:00\n", + "reflect 0.0\n", + "Name: 80207, dtype: object\n", + "datahora 2020-02-25 00:00:00\n", + "reflect 0.0\n", + "Name: 80208, dtype: object\n", + "datahora 2020-02-25 01:00:00\n", + "reflect 0.0\n", + "Name: 80209, dtype: object\n", + "datahora 2020-02-25 02:00:00\n", + "reflect 0.0\n", + "Name: 80210, dtype: object\n", + "datahora 2020-02-25 03:00:00\n", + "reflect 0.0\n", + "Name: 80211, dtype: object\n", + "datahora 2020-02-25 04:00:00\n", + "reflect 0.0\n", + "Name: 80212, dtype: object\n", + 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16:00:00\n", + "reflect 0.0\n", + "Name: 80224, dtype: object\n", + "datahora 2020-02-25 17:00:00\n", + "reflect 0.0\n", + "Name: 80225, dtype: object\n", + "datahora 2020-02-25 18:00:00\n", + "reflect 0.0\n", + "Name: 80226, dtype: object\n", + "datahora 2020-02-25 19:00:00\n", + "reflect 0.0\n", + "Name: 80227, dtype: object\n", + "datahora 2020-02-25 20:00:00\n", + "reflect 22.427596\n", + "Name: 80228, dtype: object\n", + "datahora 2020-02-25 21:00:00\n", + "reflect 20.0\n", + "Name: 80229, dtype: object\n", + "datahora 2020-02-25 22:00:00\n", + "reflect 0.0\n", + "Name: 80230, dtype: object\n", + "datahora 2020-02-25 23:00:00\n", + "reflect 0.0\n", + "Name: 80231, dtype: object\n", + "datahora 2020-02-26 00:00:00\n", + "reflect 30.0\n", + "Name: 80232, dtype: object\n", + "Mensagem de erro: image file is truncated\n", + "datahora 2020-02-26 02:00:00\n", + "reflect 29.882766\n", + "Name: 80234, dtype: object\n", + "Mensagem de erro: cannot identify image file 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0.0\n", + "Name: 80259, dtype: object\n", + "datahora 2020-02-27 04:00:00\n", + "reflect 0.0\n", + "Name: 80260, dtype: object\n", + "datahora 2020-02-27 05:00:00\n", + "reflect 0.0\n", + "Name: 80261, dtype: object\n", + "datahora 2020-02-27 06:00:00\n", + "reflect 0.0\n", + "Name: 80262, dtype: object\n", + "datahora 2020-02-27 07:00:00\n", + "reflect 0.0\n", + "Name: 80263, dtype: object\n", + "Mensagem de erro: cannot identify image file '../data/radar_sumare/2020/02/27/2020_02_27_08_00.png'\n", + "datahora 2020-02-27 09:00:00\n", + "reflect 0.0\n", + "Name: 80265, dtype: object\n", + "datahora 2020-02-27 10:00:00\n", + "reflect 0.0\n", + "Name: 80266, dtype: object\n", + "datahora 2020-02-27 11:00:00\n", + "reflect 0.0\n", + "Name: 80267, dtype: object\n", + "datahora 2020-02-27 12:00:00\n", + "reflect 0.0\n", + "Name: 80268, dtype: object\n", + "datahora 2020-02-27 13:00:00\n", + "reflect 0.0\n", + "Name: 80269, dtype: object\n", + "datahora 2020-02-27 14:00:00\n", + "reflect 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00:00:00\n", + "reflect 25.165794\n", + "Name: 80328, dtype: object\n", + "datahora 2020-03-01 01:00:00\n", + "reflect 20.0\n", + "Name: 80329, dtype: object\n", + "datahora 2020-03-01 02:00:00\n", + "reflect 20.0\n", + "Name: 80330, dtype: object\n", + "datahora 2020-03-01 04:00:00\n", + "reflect 0.0\n", + "Name: 80332, dtype: object\n", + "datahora 2020-03-01 05:00:00\n", + "reflect 37.398653\n", + "Name: 80333, dtype: object\n", + "datahora 2020-03-01 06:00:00\n", + "reflect 0.0\n", + "Name: 80334, dtype: object\n", + "datahora 2020-03-01 07:00:00\n", + "reflect 0.0\n", + "Name: 80335, dtype: object\n", + "datahora 2020-03-01 08:00:00\n", + "reflect 0.0\n", + "Name: 80336, dtype: object\n", + "datahora 2020-03-01 09:00:00\n", + "reflect 0.0\n", + "Name: 80337, dtype: object\n", + "datahora 2020-03-01 10:00:00\n", + "reflect 0.0\n", + "Name: 80338, dtype: object\n", + "datahora 2020-03-01 11:00:00\n", + "reflect 0.0\n", + "Name: 80339, dtype: object\n", + "datahora 2020-03-01 12:00:00\n", + "reflect 0.0\n", + "Name: 80340, dtype: object\n", + "datahora 2020-03-01 13:00:00\n", + "reflect 0.0\n", + "Name: 80341, dtype: object\n", + "datahora 2020-03-01 14:00:00\n", + "reflect 0.0\n", + "Name: 80342, dtype: object\n", + "datahora 2020-03-01 15:00:00\n", + "reflect 0.0\n", + "Name: 80343, dtype: object\n", + "datahora 2020-03-01 16:00:00\n", + "reflect 0.0\n", + "Name: 80344, dtype: object\n", + "datahora 2020-03-01 17:00:00\n", + "reflect 0.0\n", + "Name: 80345, dtype: object\n", + "datahora 2020-03-01 18:00:00\n", + "reflect 0.0\n", + "Name: 80346, dtype: object\n", + "datahora 2020-03-01 19:00:00\n", + "reflect 0.0\n", + "Name: 80347, dtype: object\n", + "datahora 2020-03-01 20:00:00\n", + "reflect 0.0\n", + "Name: 80348, dtype: object\n", + "datahora 2020-03-01 21:00:00\n", + "reflect 0.0\n", + "Name: 80349, dtype: object\n", + "datahora 2020-03-01 22:00:00\n", + "reflect 0.0\n", + "Name: 80350, dtype: object\n", + "datahora 2020-03-01 23:00:00\n", + 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datahorareflect
02011-01-01 00:00:00NaN
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22011-01-01 02:00:00NaN
32011-01-01 03:00:00NaN
42011-01-01 04:00:00NaN
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" + ], + "text/plain": [ + " datahora reflect\n", + "0 2011-01-01 00:00:00 NaN\n", + "1 2011-01-01 01:00:00 NaN\n", + "2 2011-01-01 02:00:00 NaN\n", + "3 2011-01-01 03:00:00 NaN\n", + "4 2011-01-01 04:00:00 NaN" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "idx = cemaden_info_stations.index[cemaden_info_stations[\"codestacao\"] == \"330455734A\"][0]\n", + "latitude = cemaden_info_stations.iloc[idx][\"latitude\"]\n", + "longitude = cemaden_info_stations.iloc[idx][\"longitude\"]\n", + "nome = cemaden_info_stations.iloc[idx]['nome']\n", + "print(nome,latitude, longitude)\n", + "\n", + "\n", + "radar_data = get_radar_data(\"2011-01-01\",\"2025-01-01\", cemaden_temp_resolution,latitude, longitude)\n", + "radar_data[\"datahora\"] = pd.to_datetime(radar_data[\"datahora\"], errors=\"coerce\", dayfirst=True)\n", + "print(radar_data['reflect'].unique())\n", + "radar_data.head()\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "0a5acccf", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "reflect\n", + "0.000000 0.755596\n", + "NaN 0.231224\n", + "20.000000 0.003992\n", + "25.000000 0.002012\n", + "30.000000 0.001629\n", + " ... \n", + "21.519889 0.000008\n", + "28.753785 0.000008\n", + "40.995006 0.000008\n", + "22.541241 0.000008\n", + "28.607923 0.000008\n", + "Name: proportion, Length: 169, dtype: float64\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "print(radar_data[\"reflect\"].value_counts(normalize=True, dropna=False))\n", + "dispersao(radar_data,\"datahora\", \"reflect\",\"Refletividade ao longo do tempo\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "a4971f0e", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(19211, 5)\n", + "(16638, 5)\n", + "SignificanceResult(statistic=np.float64(0.1773521298898834), pvalue=np.float64(1.232695339293626e-117))\n", + "PearsonRResult(statistic=np.float64(0.09777106389384145), pvalue=np.float64(1.259658726165164e-36))\n" + ] + } + ], + "source": [ + "df_correlacao = pd.merge(cemaden_data_station, radar_data, on=\"datahora\", how=\"inner\")\n", + "print(df_correlacao.shape)\n", + "df_correlacao= df_correlacao.dropna(subset=[\"datahora\", \"reflect\", \"intensidade_precipitacao\"])\n", + "print(df_correlacao.shape)\n", + "\n", + "print(stats.spearmanr(df_correlacao['chuva'],df_correlacao['reflect']))\n", + "print(stats.pearsonr(df_correlacao['chuva'],df_correlacao['reflect']))\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.15" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sumare_radar/dataset.ipynb b/notebooks/sumare_radar/dataset.ipynb new file mode 100644 index 00000000..6cf7cc8a --- /dev/null +++ b/notebooks/sumare_radar/dataset.ipynb @@ -0,0 +1,671 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 52, + "id": "1bb9b6c8", + "metadata": {}, + "outputs": [], + "source": [ + "import folium\n", + "import leafmap.foliumap as leafmap\n", + "import requests\n", + "import datetime\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import PIL.Image as Image\n", + "import numpy as np\n", + "import math\n", + "from scipy import stats" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "id": "b6f72ed4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mapa = leafmap.Map(center= [-22.925778948753702, -43.489029909370046], zoom_start=8, tiles='OpenStreetMap')\n", + "colormap = ['magenta', 'red', 'orange', 'yellow']\n", + "folium.LatLngPopup().add_to(mapa)" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "id": "86886480", + "metadata": {}, + "outputs": [], + "source": [ + "lat = [-22.955139]\n", + "lon = [-43.248278]\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=100,\n", + " fill=True,\n", + " color='black',\n", + " fill_opacity=0.7\n", + " ).add_to(mapa)\n", + "\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=137100,\n", + " fill=True,\n", + " color='gray',\n", + " fill_opacity=0.1\n", + " ).add_to(mapa)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "id": "19ef9975", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[-22.19 -22.44 -22.69 -22.94 -23.19 -23.44 -23.69]\n", + "[-42.35 -42.6 -42.85 -43.1 -43.35 -43.6 -43.85 -44.1 ]\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "\n", + "step = 0.25\n", + "unique_lats = (-22.19 - np.arange(7) * step)\n", + "print(unique_lats)\n", + "\n", + "unique_lons = (-42.35 - np.arange(8) * step)\n", + "print(unique_lons)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "id": "36f40dc1", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "for lat in unique_lats:\n", + " for lon in unique_lons:\n", + " folium.CircleMarker(\n", + " location=[lat, lon],\n", + " radius=2,\n", + " color=\"blue\",\n", + " fill=True,\n", + " fill_color=\"blue\",\n", + " fill_opacity=0.7,\n", + " ).add_to(mapa)\n", + "\n", + "mapa.save(\"mapa.html\")" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "id": "68fb837a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mapa" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.15" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/sumare_radar/exibition_radar.ipynb b/notebooks/sumare_radar/exibition_radar.ipynb new file mode 100644 index 00000000..57423dcc --- /dev/null +++ b/notebooks/sumare_radar/exibition_radar.ipynb @@ -0,0 +1,7426 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "bGJ81u_Vm_fH" + }, + "source": [ + "## Overlay com Mapa\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "# pip install folium" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "v2jJbNqpVxBx", + "outputId": "593f9017-0347-44ca-c0c0-cca8c875d25f" + }, + "outputs": [], + "source": [ + "# pip install geopandas" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# Radar location and radius\n", + "SUMARE_RADAR_LAT = -22.955139\n", + "SUMARE_RADAR_LON = -43.248278\n", + "SUMARE_RADAR_RADIUS = 138900 # in meters\n", + "\n", + "RADAR_IMAGE_FILE = \"../../data/radar_sumare/2019/04/08/2019_04_08_12_52.png\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "id": "-idlCgTuV6xY" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import folium\n", + "from math import cos, asin, sqrt" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "iUNN__caV-Im", + "outputId": "e38b1404-9609-43cf-a3e0-db5c82722bf1" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "m = folium.Map([SUMARE_RADAR_LAT, SUMARE_RADAR_LON], zoom_start=8, tiles='cartodbpositron')\n", + "\n", + "colormap = ['magenta', 'red', 'orange', 'yellow']\n", + "folium.LatLngPopup().add_to(m)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 697 + }, + "id": "qa_hjvBoWDeY", + "outputId": "133dd918-08cf-4597-d35d-141b3139626c" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_surface_stations = pd.read_csv('../../config/SurfaceStations.csv')\n", + "\n", + "# Estações INMET\n", + "# df = pd.read_json('https://apitempo.inmet.gov.br/estacoes/T')\n", + "df_INMET_stations = df_surface_stations[(df_surface_stations['SYSTEM'] == 'INMET') & (df_surface_stations['SG_ESTADO'] == 'RJ')]\n", + "df_AlertaRio_stations = df_surface_stations[(df_surface_stations['SYSTEM'] == 'ALERTA_RIO') & (df_surface_stations['SG_ESTADO'] == 'RJ')]\n", + "\n", + "# INMET stations\n", + "lat = list(df_INMET_stations.VL_LATITUDE)\n", + "lon = list(df_INMET_stations.VL_LONGITUDE)\n", + "\n", + "# Plot INMET stations\n", + "for loc in zip(lat, lon):\n", + " folium.Circle(\n", + " location=loc,\n", + " radius=20,\n", + " fill=True,\n", + " color='purple',\n", + " fill_opacity=0.7\n", + " ).add_to(m)\n", + "\n", + "loc = (SUMARE_RADAR_LAT, SUMARE_RADAR_LON)\n", + "folium.Circle(\n", + " location=loc,\n", + " radius=100,\n", + " fill=True,\n", + " color='black',\n", + " fill_opacity=0.7\n", + ").add_to(m)\n", + "\n", + "# Plot radar coverage\n", + "folium.Circle(\n", + " size=20,\n", + " location=loc,\n", + " radius=SUMARE_RADAR_RADIUS,\n", + " fill=True,\n", + " color='gray',\n", + " fill_opacity=0.1\n", + " ).add_to(m)\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 🌍 Why do we use the value **111.32**?\n", + "\n", + "The value **111.32** represents the **average distance (in kilometers) corresponding to one degree of latitude on Earth**.\n", + "\n", + "---\n", + "\n", + "### 1️⃣ Explanation\n", + "\n", + "The Earth is approximately an oblate spheroid, with an average radius \n", + "$$ \n", + "R \\approx 6,371 \\, \\text{km} \n", + "$$. \n", + "The Earth's circumference is about:\n", + "\n", + "$$\n", + "C = 2 \\pi R \\approx 40,075 \\, \\text{km}\n", + "$$\n", + "\n", + "Since the full circle corresponds to 360°, each degree of **latitude** corresponds to:\n", + "\n", + "$$\n", + "\\frac{40,075}{360} \\approx 111.32 \\, \\text{km per degree}\n", + "$$\n", + "\n", + "That’s why we use:\n", + "\n", + "```python\n", + "deg_lat = radius_km / 111.32\n", + "````\n", + "\n", + "This converts a distance (in km) into degrees of latitude.\n", + "\n", + "---\n", + "\n", + "### 2️⃣ Longitude conversion\n", + "\n", + "For **longitude**, the distance per degree **depends on the latitude**,\n", + "because meridians converge toward the poles. The relationship is:\n", + "\n", + "$$\n", + "1°_\\text{lon} = 111.32 \\times \\cos(\\text{latitude})\n", + "$$\n", + "\n", + "So to convert a radius (in km) into degrees of longitude:\n", + "\n", + "```python\n", + "deg_lon = radius_km / (111.32 * math.cos(math.radians(latitude)))\n", + "```\n", + "\n", + "---\n", + "\n", + "### 3️⃣ Summary\n", + "\n", + "| Quantity | Approximation | Interpretation |\n", + "| --------------- | --------------------------- | ------------------------------------- |\n", + "| 1° latitude | ≈ 111.32 km | Almost constant everywhere |\n", + "| 1° longitude | ≈ 111.32 × cos(latitude) km | Decreases toward the poles |\n", + "| Source of value | ( 40,075 / 360 ) | Earth’s circumference divided by 360° |\n", + "\n", + "---\n", + "\n", + "### 4️⃣ Optional — more precise formulas\n", + "\n", + "If higher precision is needed (considering Earth’s flattening), we can use:\n", + "\n", + "$$\n", + "1°*\\text{lat} = 111.13295 - 0.55982 \\cos(2\\phi) + 0.00117 \\cos(4\\phi)\n", + "$$\n", + "$$\n", + "1°*\\text{lon} = 111.41288 \\cos(\\phi) - 0.09350 \\cos(3\\phi) + 0.00012 \\cos(5\\phi)\n", + "$$\n", + "\n", + "But for practical cases (such as overlaying a 140 km radar image) the simple **111.32 km per degree** approximation is more than accurate enough." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[[-24.20289322206252, -44.60333880587445],\n", + " [-21.707384777937477, -41.89321719412555]]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import math\n", + " \n", + "# Convert radius from meters to degrees\n", + "radius_km = SUMARE_RADAR_RADIUS / 1000\n", + "deg_lat = radius_km / 111.32\n", + "deg_lon = radius_km / (111.32 * math.cos(math.radians(SUMARE_RADAR_LAT)))\n", + "\n", + "lat_min = SUMARE_RADAR_LAT - deg_lat\n", + "lat_max = SUMARE_RADAR_LAT + deg_lat\n", + "lon_min = SUMARE_RADAR_LON - deg_lon\n", + "lon_max = SUMARE_RADAR_LON + deg_lon\n", + " \n", + "bounds = [[lat_min, lon_min], [lat_max, lon_max]]\n", + "\n", + "bounds" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 697 + }, + "id": "4ZKlIS0yUXOK", + "outputId": "ca2021ce-7263-4f74-b82f-d3d115a9dfa3" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "folium.raster_layers.ImageOverlay(\n", + " image=RADAR_IMAGE_FILE,\n", + " bounds=bounds,\n", + " colormap=lambda x: (1, 0, 0, x),\n", + " origin=\"lower\",\n", + " opacity=0.5,\n", + ").add_to(m)\n", + "\n", + "m" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IY_IE7FQnHWg" + }, + "source": [ + "## Overlay na imagem" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 673 + }, + "id": "ep7hogZwniRl", + "outputId": "4c3a5e2e-9567-40f2-ff55-7cb910b3726e" + }, + "outputs": [ + { + "data": { + "image/png": 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AAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCwTAL/P8Xkd4oegomBAAAAAElFTkSuQmCC", + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from PIL import Image, ImageDraw\n", + "import pandas as pd\n", + "\n", + "# See https://g1.globo.com/rj/rio-de-janeiro/noticia/2019/04/09/bombeiros-registram-deslizamento-no-morro-da-babilonia-rio.ghtml\n", + "RADAR_FRAME_FOR_TESTING = Image.open(\"../../data/radar_sumare/2019/04/08/2019_04_08_12_52.png\")\n", + "\n", + "draw = ImageDraw.Draw(RADAR_FRAME_FOR_TESTING)\n", + "draw.circle((RADAR_FRAME_FOR_TESTING.width/2,RADAR_FRAME_FOR_TESTING.height/2),2,\"black\")\n", + "RADAR_FRAME_FOR_TESTING" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 673 + }, + "id": "Auz6gV6Wp_cx", + "outputId": "b5238b71-5fda-49e9-bf16-22b183b85672" + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# pos_sumare = (-22.955139,-43.248278)\n", + "pos_sumare_img = (RADAR_FRAME_FOR_TESTING.height/2, RADAR_FRAME_FOR_TESTING.width/2)\n", + "\n", + "dify = (pos_sumare_img[0]/SUMARE_RADAR_LAT)\n", + "difx = (pos_sumare_img[1]/SUMARE_RADAR_LON)\n", + "\n", + "# Desenha as estações do AlertaRio em vermelho\n", + "lat = list(df_AlertaRio_stations.VL_LATITUDE)\n", + "lon = list(df_AlertaRio_stations.VL_LONGITUDE)\n", + "\n", + "for loc in zip(lat, lon):\n", + " posx = SUMARE_RADAR_LON - ((loc[1] - SUMARE_RADAR_LON) * 22)\n", + " valorx = posx * difx\n", + "\n", + " posy = SUMARE_RADAR_LAT + ((loc[0] - SUMARE_RADAR_LAT) * 22)\n", + " valory = posy * dify\n", + " draw.circle((valorx,valory),1.5,\"red\")\n", + "\n", + "\n", + "# Desenha as estações do INMET em roxo\n", + "lat = list(df_INMET_stations.VL_LATITUDE)\n", + "lon = list(df_INMET_stations.VL_LONGITUDE)\n", + "\n", + "for loc in zip(lat, lon):\n", + " posx = SUMARE_RADAR_LON - ((loc[1] - SUMARE_RADAR_LON) * 22)\n", + " valorx = posx * difx\n", + "\n", + " posy = SUMARE_RADAR_LAT + ((loc[0] - SUMARE_RADAR_LAT) * 22)\n", + " valory = posy * dify\n", + " draw.circle((valorx,valory),1.5,\"purple\")\n", + "\n", + "lat = [-22.81]\n", + "lon = [-43.25]\n", + "\n", + "for loc in zip(lat, lon):\n", + " posx = SUMARE_RADAR_LON - ((loc[1] - SUMARE_RADAR_LON) * 22)\n", + " valorx = posx * difx\n", + "\n", + " posy = SUMARE_RADAR_LAT + ((loc[0] - SUMARE_RADAR_LAT) * 22)\n", + " valory = posy * dify\n", + " draw.circle((valorx,valory),1.5,\"yellow\")\n", + "\n", + "RADAR_FRAME_FOR_TESTING" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 683 + }, + "id": "tZptP5juYUda", + "outputId": "f2e52dec-8275-45d2-f39b-153ca00be44b" + }, + "outputs": [ + { + "data": { + 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+ "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "width, height = RADAR_FRAME_FOR_TESTING.size # Get dimensions\n", + "new_width = new_height =666\n", + "left = (width - new_width)/2\n", + "top = (height - new_height)/2\n", + "right = (width + new_width)/2\n", + "bottom = (height + new_height)/2\n", + "\n", + "# Crop the center of the image\n", + "tst2 = RADAR_FRAME_FOR_TESTING.crop((left, top, right, bottom))\n", + "tst2" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pixel spacing (X, Y): 423.48 m × 424.77 m\n", + "Latitude grid shape: (654, 656) Longitude grid shape: (654, 656)\n" + ] + } + ], + "source": [ + "### 🌧️ Georeferencing the Sumaré radar PNG image\n", + "# (automatic pixel size from image dimensions and physical radius)\n", + "\n", + "import numpy as np\n", + "from pyproj import Transformer\n", + "import folium\n", + "\n", + "# --- Radar parameters\n", + "SUMARE_RADAR_LAT = -22.955139\n", + "SUMARE_RADAR_LON = -43.248278\n", + "SUMARE_RADAR_RADIUS = 138_900 # meters (physical radar coverage)\n", + "IMG_WIDTH = 656\n", + "IMG_HEIGHT = 654\n", + "\n", + "# --- 1. Compute pixel spacing from known physical radius\n", + "PIXEL_SIZE_X = (2 * SUMARE_RADAR_RADIUS) / IMG_WIDTH # ≈ 424.5 m\n", + "PIXEL_SIZE_Y = (2 * SUMARE_RADAR_RADIUS) / IMG_HEIGHT # ≈ 425.0 m\n", + "print(f\"Pixel spacing (X, Y): {PIXEL_SIZE_X:.2f} m × {PIXEL_SIZE_Y:.2f} m\")\n", + "\n", + "# --- 2. Define coordinate transforms\n", + "to_utm = Transformer.from_crs(\"EPSG:4326\", \"EPSG:31983\", always_xy=True)\n", + "to_geo = Transformer.from_crs(\"EPSG:31983\", \"EPSG:4326\", always_xy=True)\n", + "\n", + "# --- 3. Convert radar center to UTM\n", + "x0, y0 = to_utm.transform(SUMARE_RADAR_LON, SUMARE_RADAR_LAT)\n", + "\n", + "# --- 4. Define UTM bounds\n", + "R = SUMARE_RADAR_RADIUS\n", + "x_min, x_max = x0 - R, x0 + R\n", + "y_min, y_max = y0 - R, y0 + R\n", + "\n", + "# --- 5. Build UTM grid matching image dimensions\n", + "x = np.linspace(x_min, x_max, IMG_WIDTH)\n", + "y = np.linspace(y_min, y_max, IMG_HEIGHT)\n", + "xx, yy = np.meshgrid(x, y)\n", + "\n", + "# --- 6. Convert grid back to geographic coordinates\n", + "lon, lat = to_geo.transform(xx, yy)\n", + "\n", + "# These arrays now map each pixel center to a geographic coordinate\n", + "print(\"Latitude grid shape:\", lat.shape, \"Longitude grid shape:\", lon.shape)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Overlay on a Folium map" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import folium\n", + "\n", + "# --- Criação do mapa centrado no radar ---\n", + "m = folium.Map(location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON], zoom_start=8)\n", + "\n", + "# --- Overlay da imagem do radar ---\n", + "folium.raster_layers.ImageOverlay(\n", + " image=RADAR_IMAGE_FILE,\n", + " bounds=bounds, # calculado anteriormente\n", + " opacity=0.6\n", + ").add_to(m)\n", + "\n", + "# --- Marcador do centro do radar ---\n", + "folium.CircleMarker(\n", + " location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON],\n", + " radius=4,\n", + " color=\"red\",\n", + " fill=True,\n", + " fill_opacity=1,\n", + " popup=\"Radar Sumaré (centro)\"\n", + ").add_to(m)\n", + "\n", + "# --- Função auxiliar para deslocar o rótulo levemente para norte (em graus) ---\n", + "def offset_lat(lat, offset_m):\n", + " \"\"\"Aproxima deslocamento norte em metros → graus latitude\"\"\"\n", + " return lat + (offset_m / 111_320.0)\n", + "\n", + "# --- Círculos concêntricos + rótulos ---\n", + "range_km = [50, 100, 138.9]\n", + "colors = [\"#8888ff\", \"#4444ff\", \"#000000\"]\n", + "\n", + "for r_km, color in zip(range_km, colors):\n", + " radius_m = r_km * 1000\n", + "\n", + " # Círculo de alcance\n", + " folium.Circle(\n", + " location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON],\n", + " radius=radius_m,\n", + " color=color,\n", + " weight=1.2,\n", + " fill=True,\n", + " fill_opacity=0.08 if r_km < 138.9 else 0,\n", + " popup=f\"Alcance: {r_km:.1f} km\"\n", + " ).add_to(m)\n", + "\n", + " # Rótulo de texto sobre o mapa (ligeiramente acima do centro)\n", + " folium.map.Marker(\n", + " [offset_lat(SUMARE_RADAR_LAT, radius_m + 3000), SUMARE_RADAR_LON],\n", + " icon=folium.DivIcon(\n", + " html=f\"\"\"\n", + "
{r_km:.0f} km
\n", + " \"\"\"\n", + " )\n", + " ).add_to(m)\n", + "\n", + "m\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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SYSTEMSTATION_IDDC_NOMESG_ESTADOCD_SITUACAOVL_LATITUDEVL_LONGITUDEVL_ALTITUDEDT_INICIO_OPERACAO
0INMETA628ANGRA DOS REISRJOperante-22.975556-44.3033336.02017-08-24
1INMETA606ARRAIAL DO CABORJOperante-22.975278-42.0213895.02006-09-21
2INMETA604CAMBUCIRJOperante-21.587500-41.95833346.02002-11-19
3INMETA607CAMPOS DOS GOYTACAZESRJOperante-21.714722-41.34388917.02006-09-24
4INMETA620CAMPOS DOS GOYTACAZES - SAO TOMERJOperante-22.041667-41.0516677.02008-06-12
\n", + "
" + ], + "text/plain": [ + " SYSTEM STATION_ID DC_NOME SG_ESTADO CD_SITUACAO \\\n", + "0 INMET A628 ANGRA DOS REIS RJ Operante \n", + "1 INMET A606 ARRAIAL DO CABO RJ Operante \n", + "2 INMET A604 CAMBUCI RJ Operante \n", + "3 INMET A607 CAMPOS DOS GOYTACAZES RJ Operante \n", + "4 INMET A620 CAMPOS DOS GOYTACAZES - SAO TOME RJ Operante \n", + "\n", + " VL_LATITUDE VL_LONGITUDE VL_ALTITUDE DT_INICIO_OPERACAO \n", + "0 -22.975556 -44.303333 6.0 2017-08-24 \n", + "1 -22.975278 -42.021389 5.0 2006-09-21 \n", + "2 -21.587500 -41.958333 46.0 2002-11-19 \n", + "3 -21.714722 -41.343889 17.0 2006-09-24 \n", + "4 -22.041667 -41.051667 7.0 2008-06-12 " + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "\n", + "# Lê o arquivo CSV de estações\n", + "stations = pd.read_csv(\"../../config/SurfaceStations.csv\")\n", + "\n", + "# Mostra as primeiras linhas\n", + "stations.head()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Adiciona as estações como marcadores no mapa Folium\n", + "for _, row in stations.iterrows():\n", + " lat = row[\"VL_LATITUDE\"]\n", + " lon = row[\"VL_LONGITUDE\"]\n", + " name = row.get(\"DC_NOME\", \"Estação\")\n", + " system = row.get(\"SYSTEM\", \"\")\n", + " \n", + " folium.CircleMarker(\n", + " location=[lat, lon],\n", + " radius=3.5,\n", + " color=\"blue\" if system == \"INMET\" else \"green\",\n", + " fill=True,\n", + " fill_opacity=0.8,\n", + " popup=f\"{name}
Sistema: {system}
({lat:.4f}, {lon:.4f})\"\n", + " ).add_to(m)\n", + "\n", + "m\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "53 estações dentro do alcance do radar.\n" + ] + }, + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import folium\n", + "import pandas as pd\n", + "from math import radians, sin, cos, sqrt, atan2\n", + "\n", + "# --- Leitura do CSV de estações ---\n", + "stations = pd.read_csv(\"../../config/SurfaceStations.csv\")\n", + "\n", + "# --- Função para calcular distância haversine (em metros) ---\n", + "def haversine(lat1, lon1, lat2, lon2):\n", + " R = 6371e3 # raio médio da Terra\n", + " dlat, dlon = radians(lat2 - lat1), radians(lon2 - lon1)\n", + " a = sin(dlat/2)**2 + cos(radians(lat1))*cos(radians(lat2))*sin(dlon/2)**2\n", + " return R * 2 * atan2(sqrt(a), sqrt(1 - a))\n", + "\n", + "# --- Cálculo da distância de cada estação até o radar ---\n", + "stations[\"DIST_RADAR_M\"] = stations.apply(\n", + " lambda r: haversine(SUMARE_RADAR_LAT, SUMARE_RADAR_LON, r.VL_LATITUDE, r.VL_LONGITUDE),\n", + " axis=1\n", + ")\n", + "\n", + "# --- Filtra apenas estações dentro do alcance do radar ---\n", + "stations_in_range = stations[stations[\"DIST_RADAR_M\"] <= SUMARE_RADAR_RADIUS]\n", + "print(f\"{len(stations_in_range)} estações dentro do alcance do radar.\")\n", + "\n", + "# --- Criação do mapa ---\n", + "m = folium.Map(location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON], zoom_start=8)\n", + "\n", + "# --- Overlay da imagem de radar ---\n", + "folium.raster_layers.ImageOverlay(\n", + " image=RADAR_IMAGE_FILE,\n", + " bounds=bounds,\n", + " opacity=0.6\n", + ").add_to(m)\n", + "\n", + "# --- Marcador do centro do radar ---\n", + "folium.CircleMarker(\n", + " location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON],\n", + " radius=4,\n", + " color=\"red\",\n", + " fill=True,\n", + " fill_opacity=1,\n", + " popup=\"Radar Sumaré (centro)\"\n", + ").add_to(m)\n", + "\n", + "# --- Função auxiliar para deslocar rótulo (norte) ---\n", + "def offset_lat(lat, offset_m):\n", + " return lat + (offset_m / 111_320.0)\n", + "\n", + "# --- Círculos concêntricos + rótulos ---\n", + "range_km = [50, 100, 138.9]\n", + "colors = [\"#8888ff\", \"#4444ff\", \"#000000\"]\n", + "\n", + "for r_km, color in zip(range_km, colors):\n", + " radius_m = r_km * 1000\n", + " folium.Circle(\n", + " location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON],\n", + " radius=radius_m,\n", + " color=color,\n", + " weight=1.2,\n", + " fill=True,\n", + " fill_opacity=0.08 if r_km < 138.9 else 0,\n", + " popup=f\"Alcance: {r_km:.1f} km\"\n", + " ).add_to(m)\n", + "\n", + " # Rótulo de texto no anel\n", + " folium.map.Marker(\n", + " [offset_lat(SUMARE_RADAR_LAT, radius_m + 3000), SUMARE_RADAR_LON],\n", + " icon=folium.DivIcon(\n", + " html=f\"\"\"\n", + "
{r_km:.0f} km
\n", + " \"\"\"\n", + " )\n", + " ).add_to(m)\n", + "\n", + "# --- Plot das estações (cores e ícones por sistema) ---\n", + "for _, row in stations_in_range.iterrows():\n", + " lat, lon = row[\"VL_LATITUDE\"], row[\"VL_LONGITUDE\"]\n", + " name = row.get(\"DC_NOME\", \"Estação\")\n", + " system = row.get(\"SYSTEM\", \"\")\n", + "\n", + " if system.upper() == \"INMET\":\n", + " icon = folium.Icon(color=\"blue\", icon=\"triangle\", prefix=\"fa\")\n", + " else:\n", + " icon = folium.Icon(color=\"green\", icon=\"circle\", prefix=\"fa\")\n", + "\n", + " folium.Marker(\n", + " location=[lat, lon],\n", + " icon=icon,\n", + " popup=f\"{name}
Sistema: {system}
({lat:.4f}, {lon:.4f})\"\n", + " ).add_to(m)\n", + "\n", + "m\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import folium\n", + "import pandas as pd\n", + "from math import radians, sin, cos, sqrt, atan2\n", + "\n", + "# --- Leitura do CSV de estações ---\n", + "stations = pd.read_csv(\"../../config/SurfaceStations.csv\")\n", + "\n", + "# --- Função haversine para distância até o radar ---\n", + "def haversine(lat1, lon1, lat2, lon2):\n", + " R = 6371e3 # raio médio da Terra (m)\n", + " dlat, dlon = radians(lat2 - lat1), radians(lon2 - lon1)\n", + " a = sin(dlat/2)**2 + cos(radians(lat1))*cos(radians(lat2))*sin(dlon/2)**2\n", + " return R * 2 * atan2(sqrt(a), sqrt(1 - a))\n", + "\n", + "stations[\"DIST_RADAR_M\"] = stations.apply(\n", + " lambda r: haversine(SUMARE_RADAR_LAT, SUMARE_RADAR_LON, r.VL_LATITUDE, r.VL_LONGITUDE),\n", + " axis=1\n", + ")\n", + "\n", + "# --- Filtra apenas estações dentro do alcance do radar ---\n", + "stations_in_range = stations[stations[\"DIST_RADAR_M\"] <= SUMARE_RADAR_RADIUS]\n", + "\n", + "# --- Cria o mapa base ---\n", + "m = folium.Map(location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON], zoom_start=8)\n", + "\n", + "# --- Overlay da imagem do radar ---\n", + "folium.raster_layers.ImageOverlay(\n", + " image=RADAR_IMAGE_FILE,\n", + " bounds=bounds,\n", + " opacity=0.6\n", + ").add_to(m)\n", + "\n", + "# --- Marcador do radar ---\n", + "folium.CircleMarker(\n", + " location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON],\n", + " radius=4,\n", + " color=\"red\",\n", + " fill=True,\n", + " fill_opacity=1,\n", + " popup=\"Radar Sumaré (centro)\"\n", + ").add_to(m)\n", + "\n", + "# --- Função auxiliar para deslocar rótulo ---\n", + "def offset_lat(lat, offset_m):\n", + " return lat + (offset_m / 111_320.0)\n", + "\n", + "# --- Círculos concêntricos + rótulos ---\n", + "range_km = [50, 100, 138.9]\n", + "colors = [\"#8888ff\", \"#4444ff\", \"#000000\"]\n", + "\n", + "for r_km, color in zip(range_km, colors):\n", + " radius_m = r_km * 1000\n", + " folium.Circle(\n", + " location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON],\n", + " radius=radius_m,\n", + " color=color,\n", + " weight=1.2,\n", + " fill=True,\n", + " fill_opacity=0.08 if r_km < 138.9 else 0,\n", + " popup=f\"Alcance: {r_km:.1f} km\"\n", + " ).add_to(m)\n", + "\n", + " folium.map.Marker(\n", + " [offset_lat(SUMARE_RADAR_LAT, radius_m + 3000), SUMARE_RADAR_LON],\n", + " icon=folium.DivIcon(\n", + " html=f\"\"\"\n", + "
{r_km:.0f} km
\n", + " \"\"\"\n", + " )\n", + " ).add_to(m)\n", + "\n", + "# --- Cria grupos de camadas ---\n", + "layer_inmet = folium.FeatureGroup(name=\"Estações INMET\", show=True)\n", + "layer_alerta = folium.FeatureGroup(name=\"Estações AlertaRio\", show=True)\n", + "\n", + "# --- Adiciona estações de cada sistema ---\n", + "for _, row in stations_in_range.iterrows():\n", + " lat, lon = row[\"VL_LATITUDE\"], row[\"VL_LONGITUDE\"]\n", + " name = row.get(\"DC_NOME\", \"Estação\")\n", + " system = row.get(\"SYSTEM\", \"\")\n", + "\n", + " if system.upper() == \"INMET\":\n", + " folium.CircleMarker(\n", + " location=[lat, lon],\n", + " radius=2.5, # marcador menor\n", + " color=\"blue\",\n", + " fill=True,\n", + " fill_opacity=0.9,\n", + " popup=f\"{name}
Sistema: {system}
({lat:.4f}, {lon:.4f})\"\n", + " ).add_to(layer_inmet)\n", + " else:\n", + " folium.CircleMarker(\n", + " location=[lat, lon],\n", + " radius=2.5,\n", + " color=\"green\",\n", + " fill=True,\n", + " fill_opacity=0.9,\n", + " popup=f\"{name}
Sistema: {system}
({lat:.4f}, {lon:.4f})\"\n", + " ).add_to(layer_alerta)\n", + "\n", + "# --- Adiciona as camadas ao mapa ---\n", + "layer_inmet.add_to(m)\n", + "layer_alerta.add_to(m)\n", + "\n", + "# --- Controle de visibilidade das camadas ---\n", + "folium.LayerControl(collapsed=False).add_to(m)\n", + "\n", + "# --- Adiciona legenda fixa ---\n", + "legend_html = \"\"\"\n", + "
\n", + "🛰️ Legenda
\n", + "● Radar Sumaré
\n", + "● Estações INMET
\n", + "● Estações AlertaRio
\n", + "⬤ Círculo de alcance
\n", + "
\n", + "\"\"\"\n", + "m.get_root().html.add_child(folium.Element(legend_html))\n", + "\n", + "m\n" + ] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [ + "bGJ81u_Vm_fH" + ], + "provenance": [] + }, + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.19" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/notebooks/sumare_radar/mapa.html b/notebooks/sumare_radar/mapa.html new file mode 100644 index 00000000..8a237115 --- /dev/null +++ b/notebooks/sumare_radar/mapa.html @@ -0,0 +1,481 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + \ No newline at end of file diff --git a/notebooks/sumare_radar/overlay_radar_surface_elevation.ipynb b/notebooks/sumare_radar/overlay_radar_surface_elevation.ipynb new file mode 100644 index 00000000..c9befc73 --- /dev/null +++ b/notebooks/sumare_radar/overlay_radar_surface_elevation.ipynb @@ -0,0 +1,2001 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Overlay radar + estacoes de superficie + relevo (DEM)\n", + "\n", + "Notebook criado a partir de `notebooks/sumare_radar/exibition_radar.ipynb` e `notebooks/elevation.ipynb` para visualizar as tres fontes na mesma figura ou mapa interativo.\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Dependencias\n", + "\n", + "Descomente as linhas abaixo caso o ambiente nao tenha as bibliotecas instaladas.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "# !pip install folium pandas matplotlib pillow pyproj elevation\n", + "# !pip install rasterio # opcional se preferir rasterio em vez de GDAL\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Parametros e caminhos\n", + "Ajuste os caminhos se os dados estiverem em outra pasta. O arquivo DEM pode ser gerado com `eio clip` usando os limites do Rio listados abaixo.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "from pathlib import Path\n", + "\n", + "# Radar do Sumare\n", + "SUMARE_RADAR_LAT = -22.955139\n", + "SUMARE_RADAR_LON = -43.248278\n", + "SUMARE_RADAR_RADIUS_M = 138_900\n", + "RADAR_IMAGE_FILE = Path('../../data/radar_sumare/2019/04/08/2019_04_08_12_52.png')\n", + "\n", + "# Estacoes de superficie (arquivos JSON por sistema)\n", + "STATION_SYSTEMS_DIR = Path('../../config/station_systems')\n", + "\n", + "# DEM gerado com a biblioteca elevation (eio clip)\n", + "DEM_FILE = Path('../../data/RJ-30m-DEM.tif')\n", + "DEM_BOUNDS = (\n", + " -43.8906028271505, # min lon (oeste)\n", + " -23.1339033365138, # min lat (sul)\n", + " -43.04835145732227, # max lon (leste)\n", + " -22.649724748272934 # max lat (norte)\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "import numpy as np\n", + "import pandas as pd\n", + "import folium\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.cm as cm\n", + "from matplotlib.colors import LightSource\n", + "from math import radians, sin, cos, sqrt, atan2\n", + "from osgeo import gdal\n", + "\n", + "\n", + "def haversine(lat1, lon1, lat2, lon2):\n", + " 'Distancia em metros entre dois pares lat/lon.'\n", + " R = 6_371_000\n", + " dlat, dlon = radians(lat2 - lat1), radians(lon2 - lon1)\n", + " a = sin(dlat / 2) ** 2 + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) ** 2\n", + " return R * 2 * atan2(sqrt(a), sqrt(1 - a))\n", + "\n", + "\n", + "def compute_radar_bounds(lat, lon, radius_m):\n", + " radius_km = radius_m / 1000\n", + " deg_lat = radius_km / 111.32\n", + " deg_lon = radius_km / (111.32 * cos(radians(lat)))\n", + " return [[lat - deg_lat, lon - deg_lon], [lat + deg_lat, lon + deg_lon]]\n", + "\n", + "\n", + "def load_station_systems(directory: Path, state_filter=None) -> pd.DataFrame:\n", + " 'Carrega todas as estacoes a partir dos JSONs em config/station_systems.'\n", + " rows = []\n", + " for path in directory.glob(\"*.json\"):\n", + " data = json.loads(path.read_text())\n", + " system = path.stem.upper()\n", + " for sid, meta in data.get(\"stations\", {}).items():\n", + " lat = meta.get(\"latitude\") or meta.get(\"lat\")\n", + " lon = meta.get(\"longitude\") or meta.get(\"lon\")\n", + " if lat is None or lon is None:\n", + " continue\n", + " state = meta.get(\"state\")\n", + " if state_filter and state not in state_filter:\n", + " continue\n", + " rows.append(\n", + " {\n", + " \"station_id\": sid,\n", + " \"name\": meta.get(\"name\", sid),\n", + " \"system\": system,\n", + " \"state\": state,\n", + " \"latitude\": lat,\n", + " \"longitude\": lon,\n", + " }\n", + " )\n", + " return pd.DataFrame(rows)\n", + "\n", + "\n", + "def load_dem(path):\n", + " if not path.exists():\n", + " raise FileNotFoundError(f'DEM nao encontrado: {path}. Rode \"eio clip\" para gerar.')\n", + "\n", + " ds = gdal.Open(str(path))\n", + " band = ds.GetRasterBand(1)\n", + " arr = band.ReadAsArray().astype(float)\n", + " nodata = band.GetNoDataValue()\n", + " if nodata is not None:\n", + " arr[arr == nodata] = np.nan\n", + "\n", + " gt = ds.GetGeoTransform()\n", + " minx, pixel_w, _, maxy, _, pixel_h = gt\n", + " maxx = minx + pixel_w * ds.RasterXSize\n", + " miny = maxy + pixel_h * ds.RasterYSize\n", + " extent = (minx, maxx, miny, maxy)\n", + "\n", + " return arr, extent, abs(pixel_w), abs(pixel_h)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Radar + estacoes\n", + "Leitura dos arquivos JSON em `config/station_systems/` e calculo dos limites do radar para usar como `bounds` e `extent` nas visualizacoes.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Estacoes dentro do raio de cobertura: 54\n" + ] + }, + { + "data": { + "text/html": [ + "
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station_idnamesystemstatelatitudelongitudeDIST_RADAR_M
0alto_da_boa_vistaAlto da Boa VistaALERTARIORJ-22.9658-43.27833294.484617
1anchietaAnchietaALERTARIORJ-22.8269-43.403321342.738610
2av_brasil_mendanhaAv. Brasil/MendanhaALERTARIORJ-22.8569-43.541131920.085061
3banguBanguALERTARIORJ-22.8803-43.465823781.614807
4barrinhaBarra/BarrinhaALERTARIORJ-23.0085-43.29977931.968301
\n", + "
" + ], + "text/plain": [ + " station_id name system state latitude \\\n", + "0 alto_da_boa_vista Alto da Boa Vista ALERTARIO RJ -22.9658 \n", + "1 anchieta Anchieta ALERTARIO RJ -22.8269 \n", + "2 av_brasil_mendanha Av. Brasil/Mendanha ALERTARIO RJ -22.8569 \n", + "3 bangu Bangu ALERTARIO RJ -22.8803 \n", + "4 barrinha Barra/Barrinha ALERTARIO RJ -23.0085 \n", + "\n", + " longitude DIST_RADAR_M \n", + "0 -43.2783 3294.484617 \n", + "1 -43.4033 21342.738610 \n", + "2 -43.5411 31920.085061 \n", + "3 -43.4658 23781.614807 \n", + "4 -43.2997 7931.968301 " + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "if not RADAR_IMAGE_FILE.exists():\n", + " raise FileNotFoundError(f'Imagem do radar nao encontrada em {RADAR_IMAGE_FILE}')\n", + "if not STATION_SYSTEMS_DIR.exists():\n", + " raise FileNotFoundError(f'Diretorio de estacoes nao encontrado em {STATION_SYSTEMS_DIR}')\n", + "\n", + "radar_img = plt.imread(RADAR_IMAGE_FILE)\n", + "radar_bounds = compute_radar_bounds(SUMARE_RADAR_LAT, SUMARE_RADAR_LON, SUMARE_RADAR_RADIUS_M)\n", + "(lat_min, lon_min), (lat_max, lon_max) = radar_bounds\n", + "radar_extent = (lon_min, lon_max, lat_min, lat_max)\n", + "\n", + "stations = load_station_systems(STATION_SYSTEMS_DIR, state_filter={\"RJ\"})\n", + "if stations.empty:\n", + " raise ValueError(\"Nenhuma estacao carregada. Verifique os arquivos em config/station_systems.\")\n", + "\n", + "stations[\"DIST_RADAR_M\"] = stations.apply(\n", + " lambda r: haversine(SUMARE_RADAR_LAT, SUMARE_RADAR_LON, r.latitude, r.longitude), axis=1\n", + ")\n", + "\n", + "stations_in_range = stations[stations[\"DIST_RADAR_M\"] <= SUMARE_RADAR_RADIUS_M].copy()\n", + "print(f\"Estacoes dentro do raio de cobertura: {len(stations_in_range)}\")\n", + "stations_in_range.head()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## DEM e hillshade\n", + "Carrega o raster de relevo gerado via `elevation`, calcula o hillshade e guarda o `extent` para plot.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "DEM carregado: shape=(1743, 3032), extent=(-43.89069444444445, -43.04847222222223, -23.133750000000003, -22.649583333333336)\n" + ] + } + ], + "source": [ + "dem, dem_extent, pixel_w, pixel_h = load_dem(DEM_FILE)\n", + "\n", + "ls = LightSource(azdeg=315, altdeg=45)\n", + "dem_filled = np.where(np.isnan(dem), np.nanmean(dem), dem)\n", + "hillshade = ls.hillshade(dem_filled, vert_exag=1.5, dx=pixel_w, dy=pixel_h)\n", + "\n", + "print(f\"DEM carregado: shape={dem.shape}, extent={dem_extent}\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Figura estatica (matplotlib)\n", + "Sobrepoe hillshade + dem (cmap terrain) + imagem do radar + pontos das estacoes.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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XXCFLly6VfD4vzc3Ncu6558qNN95Ys5/7779fnv70p0tdXZ0A1fMslUry7ne/W+bPny+5XE7OPPNMuemmm0ZV+RPxr82HP/xhWb58uWQyGWlra5NLLrlE7rjjjppt3vve98qiRYskiiKZO3euvOUtb5Gurq5R53bTTTfJxRdfLE1NTZLNZmXRokXy0pe+VH7729+KiMjOnTvl9a9/vZxwwglSX18vDQ0Ncuqpp8pnPvOZ6s/GwVi0aNE+q2eOZ+hnraOjY8z1+3uNREZXTTyYxw55//vfL4AsXLhwzKqbaZrKv/7rv8pxxx0nURRJe3u7vPrVr5bNmzcf9DkrpdRTZUREJi8GKqWUUkoppdT0o2PElFJKKaWUUmqCaRBTSimllFJKqQmmQUwppZRSSimlJpgGMaWUUkoppZSaYBrElFJKKaWUUmqCaRBTSimllFJKqQmmEzofAs45tm3bRmNjI8aYyT4cpZRSSiml1CQREfr6+pg3bx7Wjt/upUHsENi2bRsLFy6c7MNQSimllFJKHSE2b97MggULxl2vQewQaGxsBPzFbmpqmuSjUUoppZRSSk2W3t5eFi5cWM0I49EgdggMdUdsamrSIKaUUkoppZTa75AlLdahlFJKKaWUUhNMg5hSSimllFJKTTANYkoppZRSSik1wTSIKaWUUkoppdQE0yCmlFJKKaWUUhNMg5hSSimllFJKTTANYkoppZRSSik1wTSIKaWUUkoppdQE0yCmlFJKKaWUUhNMg5hSSimllFJKTTANYkoppZRSSik1wTSIKaWUOmC/uu9mblr5k8k+DKWUUuqoF072ASillDoybd2xlR9uuqlmWZftxhnHxru2jPmY+cFcXnrWSybg6JRSSqmjmwYxpZRSo6x6fBV/7LydzdHWMdcP2rGX70m7SO5JeOXZLz+ch6eUUkod9TSIKaWUqnHX6ru4u+9eNkSbRq90e903lVvFQDDIA/Iw9ff+HIALlz2Lpqamw3asSiml1NFKg5hSSqmqe9bcwx/77mBHtKu6zDiwJYNxYMSADK0QpBLExIILBQkgNjF/4A4AgscDzlpwJrNnzp74k1FKKaWOYBrElFJqmovjmHWb1wHws4GbGYgG/QoHQWywCYQDAcYxIoTVfu8CIc0KLiukkVRLQd3KbczoaNUgppRSSu1Fg5hSSk1jxWKRDds28NWeb/oFFhAwKQRlQ9RXCWAV4irpSwADxvh+iTYx2MQgRSGudyT54TDWU+6lu6ebluaWiTotpZRS6oinQUwppaapUqnEfevv439KPxteKBCUDOGgJSgND/4SJ7jE4WKHJD6MmcBgI4sNrQ9l1mBSQ6YvwDhH3ODAwG/k9+xZ28UVZ79iok9x2ikWiyRJMu76IAjI5/MTeERKKaXGo0FMKaWmoTRN+fmqX3KnvXt4oUCmOyAom5pWsDROSfqS4dawoT6JsSEtpkAllGUsQdZiw4BowJLUOSTwmzpxpGlKEASH/+SmqTRN+Z+Hfsx94UPjbnNCvJw3nPVafR2UUuoIoBM6K6XUNPS5lV8cFcJyHQFhaTiEudhR6ioR98SVEOZvBvA9EoeXSepICylxf4KLfTjLdAeYSuPMfeFDfGrlZyfo7KanT9/77/sMYQBrorVcf98nJ+iIlFJK7Yu2iCml1DTzwZXXUoxK1fsmgWxXgHXDXRGTYkJaSJFUhrczMH8mLJsvLJgJ/QXYuNPw8AYox34bSYVkICUTBQSxwZdVHN6HOjzed+/VxGE82YehlFLqIGgQU0qpaUbMiHCVQFiw2LQSwgTScooruxEhTDj+GDh9udBYB9b4W30eZrUKZx0Hm3bCmk2waacZfpyAEZBKYQ91+IiGXaWUOupoEFNKqWmiWCzy6VX/QTkYar7y1Q7Dwoi5wQRcKcXFvn9iEAinLxNOPhZykW8VqxRK9NnKQGBh0Rzo6hM27/K7conDhhabgAvRIKaUUkrtRceIKaXUNCEidAXd1dYT48AmYEZ2SSwluFRAIJ8VTjgGTloC+QxY61u4bBkyfVC/HRq3gi1BaGBGE8xp8/tJS5UiHomvpKgOr7fNeROtSct+t1scL+SNC15z+A9IKaXUfmmLmFJKTQO7du/ilxv+t+a3vo0NtmxrhnC50nCXxIY8nHKsUJ+FaBCyPZAZ9MErSMDG4CJIQyi2QmsTLJgpbN9tqiXutcfcxFg4byHR1n3/ST8jOYWnzzuf+XPmT9BRKaWU2hcNYkopNQ0MFAdYFa4eXiA+SNkRU05JWglhAi2NwuI5QmuDbznL74G6DogKlcdUxn2lEWT7odwIdVlorq/sbGjIWVAZKKYOu4sansFgUmBjcTMPhY/UrDvfncM588/imHnHTNLRKaWU2psGMaWUmuK27dzGql0P14zTsmWDjW1Nt8S0lCLiQ9OsFlg6HxDIdkO+s9IalgznKhF/35Z9WAssRJXxYDbje75LRHUuMQWFQoH7N9w/5rpMkOGs48960vs+d8W5AGzYsoHGnQ016561+Bm0t7U/6X0rpZQ69DSIKaXUFLZ1x1Zu33IndwX3Di90EBYMNqkt0pEWna90aISGvNDaCCaFuj0+hJmRIWxoVyGkOXCBL+Jhjc97QeTTl1jAQFPayLHB4ok56SNUT28Pq7es5n9KPxtzfZ3L0/CED1BL5i0hk8k8qedZsmAJSxYsedLHqZRSamJoEFNKqSmqo7ODn276BY9HT9QsD0qGoGww6fAyl7rKpM0QBr51a0gaVYKXqZSir3zvLBSboXe+HytWLEHvoF9pAp/IhjZfzrG87Ky/PSzneaTb3bmbJE14aPsq/tfdOu52g7bAV7q+DsAb3auZ0TCDulwdTU1NE3WoSimlJpAGMaWUmoIGBgb44ob/ojfqG14ovoUr01fbJVGckAwODxYLAwgq3QnFQKnJjxHD+C6IQ+PDSk3Qt8C3isUpPPwErHzUYCqtYGlGx4cNDAzw1ce/TkfUWbtiRKAdy9d6vgU9cFZ6Gi9acXl1eX19/dgPUEopddTRIKaUUlNMuVzm2sc+jgvc8ELxVRKzXYHPRiPzkVCdNwzAOX8T8d0NS81QaIM044NZUIYghq7FgIVU4O7Vhse3gw0DosYIgFJLChYCAuw0nC0lSRI+8ui/kkQjK6L4WzRokUBwAbhQfCAbI5StDB5g5WMPVO9/eOk/awuZUkpNERrElFJqCunc08nHN366ZplxEBQNUV/gW7RqCOJcTTArJzBQhMGSr4RIAD2Lxn4+EfjdfbB5FxRLBpsBExg/V1klWPxN9gWcd+J5h+oUjwr9/f1cs/b6mnAVFiqvQTp6e7HgIqHc6JBo/FbE6x7/F97SdiVLj1l6GI5aKaXURJp+H1EqpdR0Ij6EhQN2zF6CkgppXJvORGBrh+Gh9T6UjSd18Ju7Yf02Q7EEYT4g05RBDJRb3Ljd7qYdgUx3QKZnOAiXukuk8XCVSiMQlA35zoC6HSF1O0LyuwKiXovZ6zX4UufXuPXB303wSSillDrUtEVMKaWmMJOCSQw2New9ubIguFRw5b2byQw9A8JDjxvWb4XjjhFOWuwrIpYTKJahvwAbtsOG7QYnYLMBJjP82V6am75jw9ZtWscNHd+qftSZ2xNgY4PEQlJKSIspCMS9cfUxxhpMaMg0+kqJLnUYa4gGLWHB4kKhNCOtFEARfp38ji13b+O157xqMk5RKaXUIaBBTCmlpjDjzBjdEStSkERgjPUihiQVegfhgXWGnn5hT5+hVPYtYSK+QIcTwBqCbEAQBYitFOmYxpxzlGwZwLeCJabS8piSFlMMwnHH+DBbKkMphmIsxGVDqavkdyJgQkOQC/y1jQ253QHFNj/uLjEJZSlP4lkqpZR6qjSIKaXUFCaBIMHYfQSd8yXrRcYLTgYRKMfCxh3GBy/nl4/YhKghwka2en9fY5ymurtW38Uf+m4HX6+EoOSDcFJMSEuOuqxw9vHCwlk+0KYC4nygTVJhawfcv874sBv7AOdKjqgxwqaGTHdA3OSQUNgYbOaGu7/BG8557eSetFJKqSdFg5hSSk1hYithzAomrQ1kplKpz1j/hn98hlI85mLCfICNLMaMKIe/Vx/Iv/SvZN3d62kKGnnRmS988idzFOgu97Az6qiOzTMO4oEYV3bMaXGccqwwrx1ymUqcHfGSOIHGPLQ1C87B2i2wbbcQlwX6IGqMCMsGV4bEQsEW2SxbJ+tUx3XfY/fxcM/qUcufOe/pLJo/TtUXpZSahjSIKaXUFFKXr+N59lL+191arVzoAj8pc7hXtT5jLCYQjB2RBiwYY3ywGlFSXVLxYa0S3IaCV5ANa0KYL5NvwaXVMVKbo61sZit1Lk/2/izPPf05h+8CHCkEwkHrpwYoO5bMdhx/jG8JCww07AAbV8bwUalqb6E5hKa5gIF8Vmhrhl17YEtHigkgrIsIihax7ogbh/fbB24hdjHr4g1sjDaPWp9sTZm9ayZNmSaeftIFk3CESil1ZNEgppRSU0g+n+eSUy7m1w/8rtoyJaHgsg6Ja0unm8AQUJm52YGIYEPrw5g1GMyIIOZwSSWIBQZrfbdFs1e3x6Hqf+GgwWUqc2RVAtmgLXCL+yPNjzRhjOGE+SfQ3NR8uC/JpAliUxlEB4vmCEtmQliATB80bYKwEsSGiPWTY+MgroNjmmBGI2xvEopl2N2T+PFiJUua8fEtNjF/Wf0Xzj3h3NpAPIGcc9z96N3cmtxG2Zar3TL3tipazSpW01poIVztf+7OPu5sgqHZw5VSaprRIKaUUlOcBL6Ahs0IYXEoWfkvJjCEQYg4ARFMMPasJsYG2L3eYI/5tr8yfVimPyDNCmnW4UIQK0gIzjh+WPopAM/fMMDpC0+jbUbbITnPI47gr2uFLUOuC1o2+kmxR10/B0EC7eug2AgDsyGYAcFMKCfC7+8zpKWUIGeqk3IXbJEfFn/K2W5yAk2pVOLxrY/zg+JPhifEcWBSgx05n7gZ6iILXUG33x6of6KeZfOXkcvlJvzYlVJqsuk8YkopNQ1IAHG9I438m+Fqt8OhcWKBwUS2MqascgvF3wJqH7O3vZdVQkJQNGR6ArLdgZ/HLDY1LUC/cr/l9xv+SFd312E55yPByEIoxvnuiMGIYoeCr0Ap4ntzutjfsj3Qug6aNkPOwvIFkM1AOpggqfgpCcqTO1FboVDgsc2P8bWeb1VPxiQQDhoyPZbsnmD41uV/BoJy7c/Ajb3fYcfuHZNzAkopNcm0RUwppaaDSjXDUmtKWDDYsvXjkyo5QQy+xSp0/msgwyEtgaBkKxUAjc9dI4cnjTVUSYaLdpjUz4cVFSCNhHJrilT2fae9mx2P7eQNJ7+Wurq6w3oJJpsRsHvNcy0JvltoAmkR0j4DFqJWweYhMwD1HdDXBisWCavWV8bmlQ1iDS47eePE7lt/Hz8q/7xyIv6Yol6LTfwxVierxhctiQYsMgguI5RahscQFuMiSZIQhvqWRCk1vWiLmFJKTTFpmo6/0kJS78NQqT2lONPfSu0p5ZaUpEFIc4JEPphJAC4LcZOj2J4SN6TDIW0v4oS0nFLuK1PuLVPu9rdkMEYSV32znt8Z+tacSobYEG3iX1f/2+G5GJPJgI1GdBcU3ypWaTAEIO6C0k4o7zIkXQZXAhnx8uV6YcZamL0Gzj8RwsrujMNP0j1JnHO4Ea19QdmQ7Q6wifE/B6WEUleJ0p4SpZ4SaTlFnPgxhCVDvmP4uvxX9ze47ZE/4dx4E94ppdTUpB8/KaXUFNK5p5OPb/z04dm5gSTv00TUF1Rb0wDSkp+s2MUj30z7DZJBRzKYYAJLpimDCQy5PQFxY0qS82PHpiIXiA9LBrr7DB2tAvMg3wlRwW8TZAEHrugDmCuC3U/3zzROaytdToL/Xvk97gsf8nccZLsCECj3lCs/A8M/HJIIcW8ZML7QS9YS1Ufkd4YUZiVg4Bfpr3li5SadE00pNa1M0T9/SimlDlR7MoP3nn3VmOsGBwe5+rGPDS8YGkNmBeMqXdCcjBnC9i7iJ6lQ6ioBkJ2RJeoPMM4RNzgG7CDvufeDfOyUq4miccruHU0sxM2O7J4AYwz3rzMUY7joNGHbObDoj36zoAmCRh9W0gGIOw0mAyYEM9RnxUBa+Ws9own2FKXSGjW5YQzAxIZ8ZyWEdZdxqf8ZyGVg/kzh/JNg1QZY/YSfi05SwZUdLuuwoSXqtyR1DtHCiUqpaUiDmFJKTREPrXuI7/b8zwF3On9R9HzOXXbO8LxhY7B29M5Gdq0DSCoFJLKR0NroS7UvngP1OapZYbAIW3YJt6/yZe9LXSWipoiQAJMaSq0pYiZvvNOhcslJFzNv41xu7P0OacafT6Y5Q9wXkyQJhRjyISR5CIuVMXoGCCFogLQoZGaCGdmj0UCa9d939YHLBdjQkExSDvvsXf+P7eFOcGBTQKDYWQSBOTOEkxYLi+aADSC0cM4JcNZxwr2Pwbqt0DcIcU/sw/iAJc0KEghrwrV88q7P8E/nvnNyTkwppSaYjhFTSqkpInUpJVve/4bAG5tfzdOWn0sulyObzR78k4346+EShzgfwo5bKJy0BFoaIBNBtnJrrofjj4ErLhXOOUGIAiHpS0gGE2xsCPstgvDJ+z/Lrt27Dv54jhBhGJIJMtX7pebUt/ZYeGKn4bf3+PRUbPSTbFcaFTHGt4INhbChjFVsgJ5F0DMfHlwPcQpgSDPgspMzpqpkSqQmJSj5qpgACLQ3C+esEJbM8699BmjaCpkEMiGcsVw463hhRpMgTogHYz/xdcFgYkPKgf/8KqXUVKBBTCmlpoDbVv2JX3ffesDbN9c1P7kABpUS9yNaryrf1uehrdkHL2sgKPnxUA3boa4LMgE01cOKxXDMbMiGrlrAIiz46LEn7Np3sZGjwMLZC3lD06sASLOCs0KYD5EoZLCIHzO2BHaeAjtOh10nQc8CSDM+hElQmUdsFvTNg6422NQNDzxuMHk/xs5lhCQ38S2IX7rrK3QHvZXWMAOpkBQSAE5bJrQ3QxT6lj6TQBBD/S5fsj8bwuK5cM4JQn1ecMVKAZeiJYgn/FSUUmrSaddEpZQ6yt18///yQLyKjqjzkO3zkfWPcH/ngySSwt5DtqzgIqBScAKB5QuEZfOF1gbAQd1uyHVDpt8HrTSCXI/vkmfmwJK5QlefoScWcDJu18ijUT6fZ9HsRdCLr1LZ6AitxTpLIQn57cqEupzQkIdFc3xrYbkBSk1QvxMw0DcH0hxs7oNVqw29AzCYBkQ5i8uCiwQs5F2OlzS+cMwupIeaiLAh3ERqKlMglAw4SIs+OM9p8y1hUT9k+/xrn+n3XSuNg1Iz2DqY1QrHzhUeWu9IiglB1ndPxQmDtsB/3/M9XnnWy6fUz4RSSo1Fg5hSSh3FfvvALdyV3Etv2HdQj7tjy585z53LwnkLa5b//qE/UEpLPFHexNpo/ZiPFQsSUVMrYsFMYW4b5AzkuiC/B+o6/QTGQ4/JDEKxCfrnwNwZvqBDd1FwicMEU6taQyaT4Xn2Un6d/o406wBHgMEMBGzYYwiTmFwW9vRCPgu5rDC7GRYv8I/fYWFbJ2zcYdi0C8RYosYQQkjzDhcKM5M2Lsg/jTOOO2PCz8/GliA2iAiSOqz13Q8tfu6zug4fwmxSmQwcSPMQ1/mJqZfNh4fW+xBnAoMtWsLAUK4rc1/wEK+Ql2kQU0pNeRrElFLqKPa75DZKwcGPq/lLsJJkW8Ky3mNrlt9S/gMFWxzdCjaSAWelpnLikCD2ISzT70OYqUw5JpXJo0NfNJH6vC/kgIBLhakVw3wQe/Zpl9Kzspf75SEK2aKfxNpajAuIO4U4hr6dfvtcRpjbInS1+dal3b2GLXsC+goGkwVrDSZrSPKVed4CaItn8MyTnzE5J7hXxZaoMq7Nxr5LalD2IcykvjXMpJAG4EIIje/C2t4Mnb1+fGFQBkJLUnd0d0tVSqmDoUFMKaWOQs451m9Zj3sKlQZXBg+wsvBA7cID7OEm1nc3DEuA8cFhRpNQn/Vjg6LB4RBWfYzxXRMB+gqQOP/YyZ4T63D627P+hvSelK64mx7Ty67m3dgYopF/fgXKqbChx/H4DuOvWWiwdRY7w1YvYpxxJPXC/GQudS7PvGjOZJzSKAbIZf03Qdn/bCR5//rb2K9PMz6EUTkdUwlje/rABn5+MWHix7wppdRk0iCmlFJHoVKpxJc6v3bYp5KyWNqTGQDsCbpJjC/MgIE05whLfp6sTTv9WKe5cxlzgmYxkOSge5G///AGP+7JhpYgG+Ds1H0T/vKzXwrAg2sf5Obu3/qw2wS7gz0448CBSQ1B2RCUI4z4yaDTjOCiFAnBYJiZtEEKf7vgxRwz75jJPSnDcGg3hmwkOAfluuHXOipUgpirBLFKK6sIJKkvZe/EgDGI8XPTKaXUdKJBTCmlpqq9J/w6yHoOAQEtSRPvOeddAHzxri+zMdziw5ipFIwATMbQW7AMFB0Yqb7pts6/6fbbQqkRkjq/78c2w2DJEOb9G/CkbnJKsU+kU5efyqmcWr3/r3d/mgE76O8EQL5yq9ytchBJVH0djgRpzoGrVDu0hl1dsLNLmDsDyPsgVkwrYwkrRCBNoRxDd7//3kYWY3wVSJfVIKaUml40iCml1FHIGEMgAakZf0zN0Ngc44xvwcrIQbWgLYoX8NZz/756/y3nvpkfrbyJO8xdgC+zDiCJnxcK/MTDfXMh2w0uGC7WkGZ9FcCRgmyAzVhcCEm9f3wgU2202Pjee85Vk30IBy0gwOFIs4JJfYtotjVLcXeRX/3ZcsmZjoWzfEEOAmBEvnYprNkMd68xlMr+BzHTlAELacaR5gSDmVY/A0qp6U2DmFJKHYVyuRz/euZH+MDKa8adBFcMWPElxjE+FLl9FeF4kkxgfPnxyigfF0LffN8CZlNfxj4q+DFlUGklA2zWYiNLWmm2Mxg+esqHiaLDcJDqKTPGcP2Z1/Cvd3+ajrCTJC+4MCXXGRBkA9JSyq33HmCzq4FcWw4MlFpS0kprWHPaxAfPfu/hOwmllDqCaBBTSqmpyoAzYCvVCU1qIJCD7qK4P1F9RDktc/9a2L7bcNnZAm1+nQP688Pbpg7+6+cGWxcRBJa43hE3TP1uiVPJe85+F9++57+5P1yFywiDcxLqiIgahwO0OMHFKfFA4id/zljCfICNan/4CjOTasvqicnxvP6s10zkqSil1KTSIKaUUlOVAULxpeOdgbTSVTDwrWUM3Q7CC099AfPXzeUHxZ+AgUJ7Qq4zJNOUIRlM2NkV86PbfBhrzPvKiDv3wKadhi0dldawKCDIBMQtjjTvu0vWpXned9K7tTXsKGCM4RWnv4yFaxbws+RmMDA4xxdxsWVDWDQEJUNgQ4JM5W1G5WdNKpOBp1lHkq/tKmswEzIxtVJKHSk0iCml1BQmQ9XtHFgBExuIR2xgKhM0BzKq2+LmcBv/ftfn+f/OfVt1WRRFZILM8P5DKDenRH2WIB9gAsNgf5nf3GMYqkqfpBCnBochqAuJQkt5piON/BvxRfFCXrX8FeTzedTRIYoinrb8XE4aOJE4ifn0ts8B4DJCORJMA5UfvpH86733hwCvrn85C9oWkIkyqCNfoQA7dsCcOaD/ZZV6ajSIKaXUVOaHbvk5vRKDTQxGhpcNvTEWC0mdL8JQnbfKxGyLdvDFu77Mm858I2E49p+MNCu4wPmWkEFLZLM1WY8IrAETCEkLSOh8xUUDZ6WncdGiZzGjdcZhvQzq0MvlcuRyOUSEt5b/rmbdE10b+WX6mzEfNzNp42Vz/qZ6f97MeeRyuTG3VUeONIWrr4bPfAYGB6GuDt75Trj2Wgi0vopST4oGMaWUOgrFccz/3P9jknD8qolAdWyYLfl5qkxqRvVGNEP/DFokcLhwOIylpDwePcH37/shgQk4e9aZLJq5iBcUn8Mv0l9XdyCRkBjBZQxmjCFfUtluKOi9OPor8mGOuS1zmTt77lO5FGqSGWM4duGxNcvamtto2tY45vb1mfpR26sj39VXw/XXDxfbGRz09wE++tHJOy6ljmZGZOi/lHqyent7aW5upqenh6ampsk+HKXUNFAoFPjQmo/sdzuT4FuqChabmtp5xaDaYjbUVSyucyR5N+akzOALKpzTeiZL5y3lT4/dXrNuQ3kja6P1Yz5uXjyHkzMrqvcvXPEsstnsfo9fKTX5CgVob/fha2/19dDRod0UlRrpQLOBtogppdRU5CCIDbYMtjxOCIPhZZXuikHJ4DKGNBh7zrFHwkcZ3DOINZbnnH5Z7br1j9C8Z+w/OIsbjuG8E897SqeklJocO3aMHcIABgb8+iVLJvaYlJoKNIgppdQUY1IfqIKixcZgZJwQNgabGkxsMIGM2yr2RLSZH3f9nPzmfE0XsxOPPZETjz3xEJyBUupIMmeOHxM2XovYnDkTf0xKTQVaJ1YppaYSB+GgJeoP/JgwN0YI21cocz7E2Xjf4a076OE/O25gd+dunNN5wJSayvJ5X5jD7NVKbgy84x3aLVGpJ0uDmFJKTRWV7ojhoPUFM8YJUmkpQdz4KSuIDUGxEsb2ITUp/7Lp39i9ZzeFQoEkSZ7CwSuljmTXXgvvf79vAQP/9f3v98uVUk+OFus4BLRYh1Jqoo1VrMMkhnDQEA2M8RnbUFEOIC2n2MBirBl/QmcLaSTE9Q6XGXu82N4u4Zk877Tn1u5GJ+hVakrRecSU2j8t1qGUUtOMTRm/FWvER27GGlzqMA6MtWB9CfIaDoKywZYtEkCaEz/pcwgSCjJGvrqV27j1gdtqlr1r3tuZN3veUzwzpdSRIp/XwhxKHSoaxJRSaiqoBK1Rc3iNaAkDEBFc2eGSoQ1TH8IMRHWhn3m55uEGk4IdGF4uBiQQkpwjzQuyj8lc/33bF2ErnOlO5RVnv+xJn55SSik11WgQU0qpqcJVKiSOJLV3XDElLadIKsPrjG8li4sJYS70XRZHPXbEtuK7QWb6A2RgeN8+oIHL+JAmkZ8QGgP32YfYeVcH//fctx7KM1ZKKaWOWtp5XymlpgDjfNl69lHAUBIhLbvaEAYgIKmQFlLivph4MPZhbayCHpX5xoa+N65yE4N1plosJNcVku8IyPRYbNmQmIRt0Q4+fde/H7qTVkoppY5i2iKmlFJTgRiMmHFraogTXOJ8uBqvRJOASxwmNTjrMMb41rGAamEPg0HE72Poa/Vm/XYmNARRABgCZ8AJqXMkuYQd0S6+dNdXeO3Jr6Kuru5wXIlpb/X61fxx9+2EhFx57usn+3CUUkqNQ4OYUkpNBSNbqva1yT7K1g9tJCLgQJBqt8VRCU/22h6qY82M9UEOA2FdSIDBOItJhaTesS7awI8f/gmXLrqYObN0Jtinolgs8tNVP69Ztst18ES0GSuW79/zw5p1c3NzeObJz5jIQ1RKKTUODWJKKTUFGPG3ccOYGT0Z6wGpdFscdyUQhRAGEARCUHmOnqHiHgaCbEDgLDb1C5J64b7wIYJNAecUz2LpMUufxIFNb49vepwNXU9QciXuCu6tXVkpnuKMG7VuZqENVqFhTCmljgAaxJRSatp4MklsmDVCJoJ8FupzkMuAsUI2GhnGfCDc3QP9RejoTkgdSFawoSXTFyA2Jc0J9wT3U9xZwolj+aLlh+gcp761G9dy+64/sypcXV1mEuOD7jiZ2YW+umVH2MmvS7fS8Fg9py8/ffS0BUoppSaMBjGllJoq9q6YWLNuxJiuMVaaSouZMb6CvbUQVG6Z0AesbASNdUJbE8yZAa2Nfrux3suLCNv3wIOPG3Z0JhQHrW8ZywZkuwNKrSlpRlgVrqZrZzd/G2U5Zt4xh+pKTFmbtm3i5ztvZmu0vVosxaaGoGgISgaTjq54KRaSvJ+Y24VQCIt8Z+CHNG1u4pi5xxBF0eScjFJKTXNHRdXEJ554giuvvJIlS5aQz+dZunQpV199NeVyubrNAw88wBVXXMHChQvJ5/OsWLGCf//3/VfnKpVK/OM//iPt7e3U19fzohe9iC1bthzO01FKqUNODIiRfTZ6je5iKFgr5DLQUAdtTTCrBea3w7Fz4YRFwhnLhQtPF15wvvBX5wsXng4nHwvtLT6kGfBl82OwZbAlfwvKMG8GXHqmcPwxkAscyWBCMpgAkO0KCEsGBLZG2/mv7V9nT9eew3Jtpoo9XXv4r+1fHw5hia9Qme0MCAcsJjHVrqTihm/GQTRgyXYHRH0Wk/rxf1/s/CpPbHui5m+pUkqpiXNUtIitWbMG5xz/+Z//ybJly1i1ahVvetObGBgY4FOf+hQAK1euZObMmXzrW99i4cKF3HHHHbz5zW8mCALe/va3j7vvd7zjHfzsZz/ju9/9Lm1tbVx11VVcfvnlrFy5kiDYxyylSil1JDGy74/WnODi2tr2xkBbMxy/QJjRBE31vtUrCHyr2Li91kZMHm0SyA5AtgfCAtgYrPPb7DrZd1k8/0ShvRn+cD/ExRQTGsJcSKYnwKSOuMExaAt8/IlPc33DNdpCM4Y4jvn4E59GrL/4YcEQDFqCeLgFTJyQxikSCy51PqxZQ5Cz2CjAWENYNARxSLE9QSz8554beNngizlr+VmE4VHxlkAppaYMI0Plro4yn/zkJ/niF7/I+vXrx93mbW97G6tXr+bWW28dc31PTw8zZ87km9/8Jq94xSsA2LZtGwsXLuSXv/wlz33ucw/oWHp7e2lubqanp4empqaDPxmllDpIxWKRDz/yUZyphCuBoGDI9ga13Q+NX5fGKXFvPGKdMKsVli8QTjgGMiOzjzB2y1rlsTaBaACatkCuG4K4dvOhp0hy0LUECq0QR7CnF/7n9wYBMq1ZbGBJs0JS50hzgsHwsZOuJpPJPMWrM/WUy2U+8PC1CEJQ8C1hQdlf9aSUkPQl+OQ1FMxGv4hBPvATdge+uuXg7KS6yfnuHF5y5l/rmDGllDoEDjQbHBVdE8fS09PDjBkzntI2K1euJI5jnvOc51SXzZs3j5NPPpk77rhj3MeVSiV6e3trbkopNZFyuRyfOPOjZF0ltBjAjjFMTMb+PgxhyVxh2XzfalVjnPfiYREat8LMR2D2g1Df4UPY3syI7Rt2QGbAt7A15OGM4/26cleZNE4Jyj5U+MMT3v/wNWzfuX3/F2Aa2bFrB+9/+Bo/nQAQFnxLmKRC3BeT9MVghCgE6wcDjvkapoWUUleJUlcJBOp2hr47I3CnvZvP3v3/JvK0lFJq2jsq+yE8/vjjfO5zn+PTn/70uNvceeedfP/73+cXv/jFuNvs2LGDTCZDa2trzfLZs2ezY8eOcR/38Y9/nGuvvfbgD1wppQ4nQ6WG/eh34Wbon0oYO3mJsGCmbwnbZxdEgaAIjTuhfieEJd8lsbrPfRwKQL4LBtuh2OKrLJ55nHDfo75VbGj/NoVw0JDUHZUdNCZUOGCwCUgipKWUtJQCcNFpwuK5e7Vsjkje2zvhofWGJ7b7AFfuLpNpyZDrDCg3+yqWSimlJtaktohdc801GGP2ebvnnntqHrNt2zae97zn8bKXvYy/+7u/G3O/Dz/8MC9+8Yv58Ic/zGWXXXbQxyUi++ye8b73vY+enp7qbfPmzQf9HEopdaiJBTfe8CpDTXIKrW8JC8b5K2BSyPZC+xqYvQqaN0NUrIwLY98hbO+nzQxApn+4ImNTAxgjpMWUtJxiUkM4MHwgX9jyFVY+uvIAn2F6CQctxhnSUkpSSIhC4dwVwrKFPugGFvID0PYEzHrUf23aBQsa4ZIzhWef7QgCwSXOX3sHQdFiS4bt4U4+ds8nJvsUlVJq2pjUFrG3v/3tvPKVr9znNosXL65+v23bNi6++GLOP/98vvzlL4+5/SOPPMIll1zCm970Jj74wQ/uc99z5syhXC7T1dVV0yq2a9cuLrjggnEfl81myWaz+9y3UkpNNDF+vqhgrBYxY7GBxTnfnNVXMJTi8Sadgkyf73qY3+PHhO2nIOM+hQWIClBu8mFsyVxh1QZDEjts5AOYccN7L9giiUue5LNNbcYZhpoTAyu0NMBJS3ywzgxC4zb/mgUx4AALaQDJCqAJFs2By88Xfno7JP0JttkSlAwSGOKsozvo4ZN3fYZ/PPUt5HK5ST1XpZSa6iY1iLW3t9Pe3n5A227dupWLL76Ys846ixtuuAFrR3+M+/DDD3PJJZfwute9jo997GP73edZZ51FFEX85je/4eUvfzkA27dvZ9WqVXziE/qpoFLqKGMEGa+fgwGbsdXKidt2w9w2X7K+ZoyY+LFd2Z5KIY5KCHsqgjIEpephMGcGrN4ISaW+RLU4yHhFQlSNtJTiYmFmMzzjFCEXQftqH3bDYqV4ytBrlvogPeNx6F0AzIRZM+AF5wu/vNMR98eEdSGh9YMM40bHzqijGtiVUkodPkdFsY5t27Zx0UUXsXDhQj71qU/R0dHBjh07asZxPfzww1x88cVcdtllvOtd76qu7+joqG6zdetWTjjhBO666y4AmpubufLKK7nqqqu45ZZbuO+++3j1q1/NKaecwrOf/ewJP0+llHoqxICEjNl30FiDDYd/5fcXoKcfBouj95Pph2xfZTzYIRg6FCT+NiQbjZ23TPrUn2uq2bBlA7/eeAvgpwoAcGWHJI5s5Od9s2Wo2+27koZlwIFLIOkHlwLiX8+mzdCyEer6YcFMmNEMpCkucRCDLQ+/Kj995Ofs7tw90aerlFLTylFRrOPXv/4169atY926dSxYsKBm3VD1/R/84Ad0dHTw7W9/m29/+9vV9YsWLeKJJ54A/Dwsjz76KIODg9X1n/nMZwjDkJe//OUUCgUuvfRSbrzxRp1DTCl19KkW6xhntTWYwBdrEDFs3Q11OeG4jB9fNCSNwIW1BRefshE7S7Wx5YDt6tvFg+HDAARl4xsOnTC3TVg2XzCpH783NHdbWgRXhLQAEkPQAGEjmAhyfX67JAulRl+w5S+PGEplVwnqAUHRkOaEe4L7OXfwbNrbDqzXilJKqYN3VLSIvf71r0dExrwNueaaa8ZcPxTCwI83ExEuuuii6rJcLsfnPvc5Ojs7GRwc5Gc/+xkLFy6cwLNTSqlDRxijhH2FCXz3xCG7uuDxrYbtnSM3gnIjlJr9PGCH7LhGHFOSjBPytFvi+ARs2VYv3IKZwgnzfSGU5s2Q9kPSA+XdhtI2Q3mHJd5jiDsNMtQFFMANV71cvtBXWXSxbxUzDqL+4Z+PdZ2Ps2v3rgk9TaWUmk6OihYxpZRSB0aGWsXGTGOGIBuQFtPKG3NDV7+wZrNhwUwhDHwxDQmhXA+lJt+l7SnnIzfcYgNQHhkM/GH4Yz8qPhqcPHav+iVBGeoqIbq8y5AOgiuAxJWCHsZgQvEfuQ5d48BX1jQGQrPX1AUCNhle8Gv5HdG2iFntsw7naSml1LSlf/aUUmqqqIwNc8GI+3uxocXY4RWlsqGjC3Z1+/tDHQ2SnA9i7hD8lTBQLcohQM8AuHEmmlbjM3t16bQxZLv895KAlECSoRBGpUALmLASsPE/G+UG/zoP3Ub9oOjroZRSE0KDmFJKTSFiIc04ZGis2FhhLLI1cyUWy3DPGlMzdstFENdBUvfUj8kFfswZ1r/xX7vFkIxVmKNySBmXITA6ThcgMAEZ5wfw7d3IGcSQ6/Xf26wQ1IGJBBMIJiMEzUJusWAqfV/E+Ne1XHlNB0uVIDa0XzPUonq4z0oppRRo10SllJpaDKQ5sE4IymBSM1wafmiToHZZmvoWsc4eaG+BoPJmPI2g2OyrKFZ2/aQUm/1tyEBxuOVtrB3/44K/Z+7suU/y2aaWs084mwW7FvCpLf9BmhFsYfhiuQDKecgUIHcMFDcLIQabhahNCJv8dkMzBMR1UGrwrZG9A/D9Ww1ODFFjRJALfGtqNPzCGE1kSil1WGkQU0qpqcSABEKSAxcIYcFiU7P3JqOkKezYAzOaIKj0lZBKN7ZDdVyjFgVmuF/GoaiTP5UZSOqFsDLdwM4uw6PNwrFnwIK/gE0htxDG6lcoFnaeCsUWGCjBxs3wh/t82s62ZjCBRQykWaHcMtxU+Zb2Kzl24bETcXZKKTUtaRBTSqmjULFY5JpHrifZu4JDhZFKa9gYZNR7dd88lomoCUwSQFzv38jvPT7pYNikttDE0FzBYT7EZi0SCOV6rWm/PxJWXjgLm3b5F2rJTKFnEbRsqLzmQ9saSANfdGXXyb5L4l1rDPet9SuN9SEM48vVJ3lHmhv+wbh62ftobGyc2BNUSqlpRoOYUkodhUSExIwRwsTPN2VLhqBksG50GJPRSQyA3kEQB1SGZ4n1c04lWYgKT/5YwyKEIx8/VCAiAGMMaSCkeW0ROxBihagxIhlIEEkQ4+cE27McokF/rUtN0Ffp2SkGvvcnw2AR4hQIA6KGyozaFoptKS4cvvYZyfCB4/+J+vr6STk/pZSaTjSIKaXUVCFgEkNQtH582FAI2yvjiJMxw1hvv8HttdyFvktbWHzyvQf3bhHzDXB77axyqO+Y81Zmts18ck80RbXPaOcd6Vv57I4vUGpNyfQEhC5kd8nwkzti/vp8odRYaRFzsH4X3HPncEGU7gFDUB8RBJbAgGSg1OpbICXwzWinJyfz7EWXYIzREKaUUhNEg5hSSk0RRnwlPRvvFcJGFusQGbM8uQjs7vEVFKOwMk7M+FaxwZlQ3+FLpD+Z8g1B7Oe8Gnrelkbo6Rvj+DHMbp9NGOqfppHCMGR2+2zMDoOEQtzkCAMLAwF7YsPP7yrXbD9QMvQULSbjC3AEDSD1hjgnSCiIGe7m+LLci2nONdPa0MrsmbMn4/SUUmra0r92Sik1VVTK441qCdurQqEJDCY2yF6JrL8AWztg8Vyozw1vX2r0t2yvLwoxXhgTAReDG4CodcRTOghLvvpiqQFOWSL8+REzxlg1NZ4gCHhJ9nJ+XvxfSlGZpN4hocEWLdv6opptjTWYvEHqwFXGfblQfBdEC3mX46+ylwFw2pLTyOVyo55PKaXU4adBTCmlpoqhILafgGOsH59FyoiQ5ruyPb4NGuuEKKBavMNF0D8bTAqZgX2HMVMZe1SzDD/GrH4XxHk4dh6s2gB9cUpqgKxOabk/1lrOP/F8+h8YoJSW2MAmNtZtJggNdq/rNzQEz0VCmvUv8OnJybSYZhDIhTnOP/H8iT8JpZRSNTSIKaXUlGF8pUSp3h3VDTEp+hRlI4sYwSWuZpvtndBU7wPV7NZKGAMG233Aq+uETB+E5dGBzxgwEdhmRgmKvntjuQFkFiyeI6zdklKIrd+PY1SAU6NddtqzAbj/sftp6WmG0I/zeih6pNrC2Za0soD5/gGVsXmXLb5Uux4qpdQRRoOYUkpNBVIpihGbmmXAcCATSAspYV2IzVlc2RdscPFw6XjnDGs3+7FiSSrMaoW6LEgI/XN9Ofu63ZDvhMyg3+eBjBuzAhR9mfWBmXD6MtjZBYUBsA7CkiHJC1t2bmHB7AVEUbTffU5npx93OqdzevX+5+/6Ein+dTw5t4JLTr14ko5MKaXUgdIgppRSR5k0Tenp66lZZmNDULIE8RixaEQgCxv8r31jDTY0SDJ6+yQ1bNwudPYYls6HkxcL+RxYA6VmiOug2Axt63w1RTnAMGbEjxWLBoF6XxBERCCGqM+S5FM+3/EVror+kbmz5x7cRZnm3nbuP0z2ISillDpI2hFEKaWOMpu3b+ZTW/9jeIFAUDQEhTHmDHNCGqek5RRxvmKipFK5jT+nmBND74Dh/rXw0zsMXf2QukpBjggKbbD9dEgy+OqKB3DcBh/GWjbC0BRoruxIBhM/4ZVSSik1jWgQU0qpo1xQMtjYjBiz5fshSiqkpZS04G/xQOy/L6bE/TFJIanpljgWEegdgHvWGPoGK3uulMRPs7DrFEhyB5GjBOo6fCXFuhxkAockWj5RKaXU9KNBTCmljnLh4HCXRBEhLiTEfQnl3jLJQIIrO1zscCX/VRLxt3TsOcXG0tUH9z5m2LQTyvHw8nIDdC3y3RUPlFQ6xS+bL8xrH7niwPehlFJKHe10jJhSSh1F/vjQbfwy/k11UJZJ/a1KQMqy35auA2GMkAmhtREa630FxT29EFpYMIvqMcQN4MLhuaMrh+G7PsZgQrAj/tqYysTQbc3QVDecvmziuz1OF4UC7NgBc+ZAPj/ZR6OUUmqiaRBTSqmjiMORDA2wwndLNDI8SEuce0ohLAiE+e0wt12Y2QzN9RCnvnIiwOqNvtrhglnDj8n2QDCilUwclHYM3w8bgTqwgb8/1IUynxkuj185uWkhTeHqq+Ezn4HBQairg3e+E669FoJgso9OKaXURNEgppRSR4Gv3PU1+uin3w74yZgrwkGLqQQYlziSwXTsHeyTEAQwvx1WLBZaGyCXhSjwlQ2d+IqJACcsYrgLoUBQhoYdvnriyNYw3PCgMd8Nkupxpxk/psyY4ccYAZsYXHbq90+8+mq4/vrKWDt8GLv+ev/9Rz86ecellFJqYmkQU0qpI1RfXx8/WPMjANaHG4nNyGYnCAsGm44IPG6oS6IQBjB/JmQjCKxgrQ895QQ6ew3lGNJKEMgEvgVsxSJobYAo9CFpSDDi+6GWMZwvQ9+80X81+2jNcmU/0TOVCouDbWMU9zAcWA38o1yh4FvC9i5WKQKf/Sx84APaTVEppaYLDWJKKXUE2rpjK3/c8iceCR8dvVL8uLBg0FYnapZUcImrtlYFAcxpFdpbfBdAG/ick6TQXxAKJR/KyonvSjhnBsxsrrRSmcr+SxAWfLfDoAwSVAJUZX2+G3J7wKa1GcoYCJoEY/2xJX2QDkLY4NenlUD28AbYuNMMnRJpNPVbw3bs8C1gYxkY8OuXLJnYY1JKKTU5NIgppdQRaHffblYGD4xeUenCFxQNwYjJmNM4xZVrm6WaG6G9GXKZStdC41te2pt9IItTiGMfxupywyEMfNAKS1C3BzL9PpC5ob8Yxh9HZmD4bg0DQcOIrodD849ZKNf7QIeBJ3YYdu4BWxknJtPgL9KcOX5M2FhhrL7er1dKKTU9aPl6pZQ6WgjY2E/cHI5sDXNSLUk/JAigqc4Xw7CW4SqLxt/PRFCfg+YGmNkCDfna7ohifeuXTSDq96EsO1C59fuv4/UmNPjnMJUNwmawM6HUDH3zodQAG3fBYAlMaLEZO226JubzvjCH2etcjYF3vEO7JSql1HQyDT5/VEqpKcL5KolhwdaMyUrL6ahJkRvzfjxXsJ+P21IHcQL5bO1yCfxEzUkWgmTsxw6VqDfB6AwllX24ENIQSk3QOws6Mn4eslvuM5RSS5APCOpC0ow//gXxPKJwatewv/Za//Wzn/XdEevrfQgbWq6UUmp60CCmlFJHiSA22NjUFsYQ8RM1p0MLBWOgud4X6NgXEegZgO274aTKuCRT6XaIARf4CZvHepy4yjb9EDT6FrSRVRPTDJQaoTADBluhkIHufvjzA4ZtnX7jqCHCZC1pVii3pBgMbzvj74miqR3EgsBXR/zAB3QeMaWUms40iCml1NFAfGuYjWsXp2WHOBkuKQ8YCwtmQhiO7gI3UjmGUtkHq4GibxUb0YsRCaHYUik1PzRPmYAr+AIcNgNJv8HkxY/zMkNFN2DbGZDmIXG+C+K6J+CuRwyCIduawQQGMRDXpyQNgsEQTafZnPHhSwtzKKXU9KVBTCmljgImBZNWJm+uEpJC4oNY5b610NYIC2dDuJ8Wse17oKPbB6/126BQhjOWjZhk2fn5wUZygxDvMZR3G1wBgkYhavbdEE2lO2PvfEjyPrT96I+Gzh6DjSxRU4DN+MnECm0JEoIxBoOhPq3jmrM/8NQvlFJKKXWU0CCmlFJHAeOnB6vcoVKkw5etH1pujK9+ePbxQj6z/33OaPRfBwpw7DxfXXGkoAQN24dbw8C3hMVd4Ir+OFwBkh5DlBGoBLGehdBfgO/eYkhSCBtCwlyIBMJgW1IzIfWl5lk87/TnPrmLopRSSh3FNIgppdRRwCamNowBrpTW3G+og6XzhIWz/P19dUsEKJZ998S63HAIG3pMUPSl6xu377uYoYihvEsImoB6cJEv/vGnh3whkExLFhtakrxQbh6ecOz9i99NY0MjQRDsY+9KKaXU1KVBTCmljgKjuyVCUkqr31srtDTA0nnst0jHkLZmmNFU2f+IXed3Q/1OqOusbQ0b2SJnrO96aDNQf7xgc1Cqg0IzOIHNu/ykZMYY4gZHXOf8/GIS8P5l76apsQmzv6SolFJKTWEaxJRS6ihgElPT+jU0d9iQbOQrJbY07L8lbEhNafvKrlo2QL4TogLYdHRrmM1B2AQuElwK2dk+hBkLURGyfSCzIU0NmZZKUY7AQQCtSQtvOObVNDc1P6lroJRSSk0lGsSUUuooMLJlSkRwiatZ35CH5nqInsxvdQGTQMtGqO+AoAzWjd7GObBZCFsEl/dFO8IWfKlFoNAKHbNg225/34a+NL2rHFMoAfNmz3sSB6iUUkpNPRrElFLqMHpo3UOs790wavm5889h7uy5B76j2mKJuLg2KeWzUJ878NawKueDV9NWaNgJQexDn0tBYpCk0g0xBayvjBjkfcuYjQQT+kMrVuYM25OBhx8dPogk73ChsDCezzOazzvIg1NKKaWmLg1iSil1mDyw9gHu6PoLj0dPjFpX3hJzdnwmSxYc2ERSUjPBFzXdEgHCwM8bdlAq5enrOqFxG9hkxFOUfYXEdMBUn9PmhLAJTN5PShxkK7sxUGiH/gbo7fdl8YN8gAsEFwEWZkk7Zx1/1kEeoFJKKTV1aRBTSqnDYM2GNdzc/Vs6os4x1//FrmRg2yDAmGGsOd/McV1LeSx6HAAJpJKSfDASqQ1iceIrIKZur7Ff+xAUIb8HGnZAkAwvF+fL0yfdhqTX+FaxsNISFgk2CwSVYWXGt4QNtsHOBLbsNpgwJGqIKNeliBXmxXNYUDf/wA5KKaWUmiYO8M+1Ukqpg/GtPd+jIxw7hA1ZFa3mF9tuHnPd4gWLeenyv6ned6FQLZpowEa1v767+mDnHiiWfDXDvXLamHJ9ULcbooHa5ZJCWoB0AKRswBmkbEj7DemAwZVHbGtg9/Gw28Jjmw2PbAqIGiNcKCT1wqy0nctmXMwzT37G/g9IKaWUmkY0iCml1FEgzQoSUCkdb7DZ2l/f/QXDjj2GLR1QKEPiDjyQ2b23GeqN6GoHnElqSPorAa2yzIV++zseNjyy0YDx3SiLbb7k4qsXvZJTlp3yZE5ZKaWUmtK0a6JSSh0GoYQYygjjJ6GAgPBAfw0b3/qEAQSCICAJEiQd3v+ePrjnUcOubpjZ7Cd2zmUruUpGzy+WRpBmxniuofFoow5dcEVD2g/SIpCF7Wf6SZzTFEwmIKyvVO8wEEmE2ed00EoppdT0pUFMKaUOg2vO/gD/cdcX2BRtGXO9wfBMzuPyc1+wz/0YTDXMxQ0pWEs46BNVpjlDqatUDUxpaugdgFXr/SPrcsJZxwlR6MeQnbSktqpikvM3obYoozG+EEdQJyRlatYaK0gCcRdEc3yYG36cgcAQ1/uJpq875YNE0YgNlFJKKVWlXROVUmoSvK7pCi4/Y98hbEbrDP7l1OuwlV/VEvouiknGJy9jDbm2LGF96MeM7dX4NFiE2x40/O4+w73rDHevqV2fZiHJj35eESCAoA6CxuFmMZPxy8JWITO7smyv+cZcICT5A+gPqZRSSk1z2iKmlFIT7L3HvJP2Ge0HtK3Za2KwNCu4IEUKlqjf9yEM8yGMDFQiJOWUZDCB1FdYHBiEBx43DJaEZ5wKofVjudLQt2qF8YjHx+AKkA6Ciyt9FC1k2gWbE4LMcOZr2A59C/Y+6IO7HkoppdR0pEFMKaUOkzee+FpSl45a3tTYNCpgHQwJIW5wJHlH1B8QlMCIGR7TZQxhNiSIAgDSYkIymJIkwtrNhiVzhLltkIkqw7lGNGC5BMp7IO70VRKH9wkmEMJGsHVDBwItG6F/zoiDGxrHppRSSql90iCmlFKHSUNDw5N+7NqNa/nlzl8jCBKN0dXPVAJZY0pcX5t8jEBQMkSDFhwEuRBjLXF/TJIK9z5muPhMIRP5AiAyopN6vBvSboMr+rL1nmAr84iZzPA4MzGw8xRfrKNKeyUqpZRSB0SDmFJKHWHuWn0Xf+67h83R1v1uKwEQ1KYfAcQKLiOEAxZbNtiMJawPSQZidvf44h0ALoA4D2FlbjBJ/YTOgE90AlhfuMNkGDWyuNSs2UsppZR6MjSIKaXUEWbb4PZxqy2O55TkRJbkFzEQD3ALf/SFPUIBHIGxhEVDkA1IBhKSFJwTRHzVxME2yPf4/RgLNgNUqiNKGYIGX7TDRCNaw4ae2PjS9TKiC6NSSiml9k+DmFJKHUEeXPsg29OdB1zT9jx3NgEBp805hWMXHsvAwACFNUXutHcjCGlGsLFA0dSEpELZt4rZDBRbIclAUIagHmzGF8wXB1IyhEMhLGJ4H8ZP5pzbA30N2iqmlFJKHSwNYkopdQT5XddttV0SBUyKHxM2NNHyCC865XIymeFZmTOZDMe3LOfO3rv9AjN2SNrVBU31kGn0rWL9s6GuE0IDVqpPjTgZNRG0AM5CuQEy/dARQyne+xmUUkoptS8axJRS6kglYBL8BM4BpBnBhVLTWra9YzuZcDiIdQ90c0Pvt4c3cLVVEYes32ZobRSa64EMdC2FuA4at0NUAJv4x5m9QpgzvjhHuR4GZvuKiXf8wbCnz2Cyh/b0lVJKqalMg5hSSh2pBDK9AUHsm7XCQEhyQlLnkMpv78/t+s99Pj4sGmw8euBWV59h5x6htRGa6yEMoG8u9M+D1nW+dSyotHLZpFJdMYAkCwPt0LPIL4sTGCiAM4Yw8M9jMDSk9Yf6aiillFJTigYxpZQ6ElW6JAYjQpRJDdGgISgb4iZHGsn4xTEEbNkQFCxBee8KG96qDYatu2HZAuGEYyBbKcaxZyl0L660iqUw62EoNUH/XN8S5gJwAi6F21cZygmEDSE2Z0kCoc7lufrs9x+Wy6KUUkpNFRrElFLqSCRg0zEGeAnY2JDdE+ACodTikLASyBzYxBAOWD/J88gBYiK4xNXuSgx7euGuRwx3PeKXLZojnH28MLPFBy6ArefUHkJnL6zeaFi1vhLwDERAkhfiRkem9mmUUkopNQYNYkopdYT44MprKUYlAIwz2HJtc5c4n6qM9cttash3BvvfsRPS2JEM7L+ixsYdsGmHYdlCOG2p0FQHqYP+Aqx8zLBzDxRLw/ku154D/MTSSU4TmFJKKXWgNIgppdQRQkY0fxlHzdguESEtp0jqW7+CTIANx6txL7jYkRQr2zv/+P3VmDeBAWOQVHh8i7Bh24iS9+IDmQgE2YCoYXhSsUJbilS6SS6Jj+FNp7/xKVwFpZRSanrQIKaUUkcgM9Q1sSIpJLjYQepDlSs5TGAwocFYgzhBEvHBC0AOLHyBb2ELG8JRwc4ljrjXt6KZYMQ2FiQwJHXOFw6plNV/unsal514aU05faWUUkqNTYOYUkodBYwxvmWr0j1RUkGcYJJKq9VBBK9RrG9h21sQBZgWU31+Yw1pVio3hwTDpfRfFD2f0445lYaGhid5hkoppdT0okFMKaUmWRzHfPf+H5CE6fBCAZwgjvHD1VD4GsFaPzfY8gVCQx4CC4US7O7xFRIHS5CmMF65RbGQ1DlcNEaVkMr6vecye2n2RZy08CQaGxsP4qyVUkqp6U2DmFJq0vT09vCnx28fd73B8PzTn+dbg6awNE15IFxVs8wFkGYhKEAaVwLaPi6DtX5OsEWzhRlNMK8NchmwFsoxzGkT5rZDqQwbths6eoQkGV3WPs36ucpkVBCrVZ/WcXH2mQCcuexM7Y6olFJKHSQNYkqpCbd241p2D+ymq9TN7/jTuNsZDC2PtAzVhGBu01wWL1g8MQc5ySQQXNYRFgPYV6tYxawWWDpfWL4A8tmRO/Lzg81sgfZmv6ghL6zZZNjVJRQrlRnFCcYaXKbS5bAilJBz5cxRz9cQ1XPRKRc+pXNUSimlpjMNYkqpCbVhywZ+u/N3PB49MbywMnmxET/vlRgfRMQKPyr/rLrZSdtO4IKkhDWW5YuWT/zBTzTjb8YaPweYUB0PNlI+Kz6ELYR8xq8PShDEYBKQANKMv2Fh6XwIAsEYw9bdQpoa0lJKmA8xqcE4QSzUuTzL3VJecs5fj3uIjz7xaPX7tsY22tvaD/11UEoppaYgDWJKqQmzs2Mn397+fbqjHr9AwKQGm0BQMtjYYFylW17O4TI+lGF8MHg4WsPDXWvISIb/m/8HANpa24iiaPJO6nAxkIY+cQW5ABkUX14ehisjViyY5Vu8hkIYDhq3Q64LogIkWSi2wuAMSHKQ5mDxHCjFQpwYtu0WksGEMB8SDVhcRkhDYUbaynOPffa4h5imKf/V9Y1q2f2n7T6LS+3FzGidcTiuiFJKKTWljDcJjVJKHTIiQl9fH/+2+f/RHVZCmPPhK787INsdEA5aTBmIwRYh6rHkdgfkOwIy3QFhwWAS/7iylPnU1v/gU1v/g3Wb1xHH+5+o+Khj8GXiKyEnzIdEdSE2Y0eNFZvVLNTn8CFMIDMATVsg1wNhGXJ90LwJ5jwIsx4GG/vtjl8IJy8RgsBXWxTnv5pKV8gt0Tb+38b/POBD/kuwku+t/eEhugBKKaXU1KZBTCl12PX29XLtuo+TGl90wqQQDViyXUE1PKRxSrmnTGlPidKeEuWuMvFADCIEZUOmJyDfEVK3KyS3J6h2z/tqzzf50+rbcc5N3gkeRm5EY58JLTbjbyPlshCFgAGb+NYwm9TuxwDWQbYPWjb5rosItDbCiYv9NqWuEuKEqCcgGjiwPw+hhJhKMrRiCRhdBl8ppZRSo2kQU0oddjUl1gWi3oCof/jXT6mrRNwTI4lvirFWCANHWkgodhYp7i5Q3F2gtKdE3BdjY0PdjtC33AC/SH/NN+759sSe1AQQAy5TuXaVVrAgCojqIkw03CwWBGANiPjy8uWG8Wt7GKB5M7Q/6rsuzmj0rWK+SQzSUgqpQIovErIPQRDw8TOvpSn1ZesvNs/gzede+VROWSmllJo2jOw9CY06aL29vTQ3N9PT00NTU9NkH45SR5RH1j/CDT3frnaxy3YGBHGlKEcqlHvL1TFP9XnhjOXCCYsgHPExUZL4TPDIE/Dnh33XvFxbDgwUZ6S4jHByvILXn/uaiT/BQ0RE+OC911Ky5doVDrJdw9dspHJfGVdy2EB4+snCSYsreU1g7krfRdGO8xveWdizDPrmQexgx274xZ0GwRA1RQSZgDQrlGakWCwfO/nqccfiDf0ZmerTDCillFIH4kCzgbaIKaUOu+o4pwGDrcxd5RJHUkyqIey4hcILzhdOXAwZICyBMf4WhpAJ4dSl8KJn+OqBxc4iOIj6LUHJsDp6jE/e9ZlJOsOnzhjDh09+HwviebUrLJRaU+KG1E+kPCLrZBozYMGl8OeHDX98gGqlxf45vlriuC1jDup3QcMOH3rntkN7i5+PLO6LSQYTbGzIdAc4HNc8+DG279w+7rFrCFNKKaUOjgYxpdRh87sHf88P9txUvR/1B5hKUQgXO9JiCgj5rHDOCUJLA9R3Q8sGmLEO5twHc+71RSbaHoOGPTC7FV52kQMRkmKCLYJJDCkpZXt0F+3IZrNcueJ1nJOeUbvCQlzvW6eKM1LixhSp/PbOtmSxmYAkNWztMPxltV/eP9e3diW5sZ/LANleyHX7sWOBheefJzTVgUVISylJf0xQmWesZMvVQK2UUkqpp06DmFLqsBlMB+kL+kEg7LeYocIchcSHMPHjmy46Q6jP+zAQxL5LXa7bB4Vsn/++frdvwanvhaZ6aKwDV0x9i1plv1NBY2Mjly29lOfZS2tXGN/C5SIhrhOKM1JKbSkmMET1ETYT0FeAjTsMA0U/BUDvfIjrwI3TWGUc5Lt86DUG6nNw2dnCglkQGAeJYFLfnRSB7278IavWrTr8F0EppZSaBjSIKaUOP4Gw4NNAUkxIyw5JhSgU5rbB/HZfbMKkEJQhLPpAZt3wLSj7cuz1uyGy8MzTBFup1hGUDUFx6nSNm9E6g7MXn8VfRy8YvXKorH0kpBmh3JhCxhDkA0wmpGcAbq9kpTQLhVaI68d+HoO/rnW7oXUd4KC9Gc4+Xrj0TOHMpSlxX0wQG4KyYVu4g75y32E6a6WUUmp60SCmlDos/vzIn1kfbwTACNi0Mjas5CrjwoR81lfsCwPfIiMGcD6Q7R2rDD6cRYN+20WzKpUCnWDLEJQtBVPg5vv/l6lQg6iluYWzl53F8+yl1fLwY0nygljBhhYbWZIEnthR2d5AudG3io3HiL+ujTugdT3k98DcBjh2LsxrE9JySlJICAcsJoWHB9bwwNoHDvHZKqWUUtOPBjGl1GFRTEvEjBizVclGQ5MG1+VgbptwzOwRDzJ+3qw0Uwll4xmxzpUcUhaMg6Itcau7bUoEMYBcLselp17Cee7s6u2YeEHtRrZyrYZuGMRBkvpy9i70XRr3ZSiMtWyGps1Q1wlB0b9Gxy0Q0kJKUPJJeU24loe7Vx+eE1ZKKaWmkXCyD0ApNTVddMqFDNw3wDZ2+AV7BauWBlg8x48Lq47vMhDnodTsxy9FBapzhYmBNIQkW7uvtJRiQoORAJMy5T5eMsbwt2f9TfX+7x/6A5uSLft4gP+SpBAGYGMwyfib762uy08GbVKQWfD0U4R1W/yLYFP/GiillFLqqdM/qUqpw04MuECwqS9zLsYnLxFIXWV8GID48Uz9IRSbfGn1oTDmQt/FrtQ49nPYBIKCwY0zHmraMPhJsytTftnEB6jxSOpv1ccaXyRFrG9JK7RBNgMudYSDFrFuyoVdpZRSajJoEFNKHTYZmyGXZCmaEuXmlNyeEJu1SEnYsUdIUsOMJl+2fqg3octAOQPlBhic6UOBcT4YGPGhTmSvIokCOD9OzNVPjW6J44lsRN7lKNhiddlQiGXE16AyB1uuBzL9o/cjACmkAxDvMUgMJgMmgKhNyPf47fa0w8wW2NoZE5gIm8NP9KaUUkqpp0Q/11RKHTaXnfZs/k/ry/zYr73evDtn2NMHf3jA0DsIhbJvHXMyImhZKLVAcUbla6v/CtDTPxzeMCARJHUODKTpPpqAjnJPP+kCrpz92tErhrprjsyh4itQ7j29mgCuCKWdUNhoKG03lDsMpW2G4haDK/ptjEAOX9LeiMOMVwdfKaWUUgdNg5hSasKkkRDWhdjA/+pJEsP23fDfvzV842bDD39vWPkodPaOCGRj3JzA2i0GNzJ0VKotOhzvW3U1e7r2TM5JToKawiYjv6/Mr2ZGXCcRcINQ3gXlXYa0b6hcpf9q7HB3xWwfzLsbopBRY/yUUkop9dRoEFNKHVYnHnsiH1jyTwCU2lIkgLA+JKwbLuU3FLC6+mDlGh/Ibvil4ae3GzbvgsGSby1LHfQNwqr1cO+jUNPwVZnw2IrlX0/9CDNaZ0zwmU6cxQsWc93xH6zejxtS0qxgrCHIDF/X5k0QlHy3zioD5U5Iug1SGiddWarVGJPs4TkHpZRSarrTMWJKqcPO2uEkUGhLyPYEhDYiyIZ+gufCcKISABHiBLZ3wq5ugzWQjSCf9YU9OnpAKk00JjSYwCDWt7hZfEGQqW7kOboMSAGC0GLqDOVywobtcIpAYSa4Hqgb0UBoAzCWarn7SkdEAMImwWb9+LJSA3ScNIEnpZRSSk0j2iKmlDrsGhsaed+iqwgIwIILBQkEExjCupBMSwYTmhHd33xXORFDkhjKMfQXYHcP7OqGNB0RtMyIr9PoN1oul+P9i99NRvzgu3JjSrnRj5EzQcAfHzDsngkuqHTZHHFtolkQtUsldAkEYCIhaHJk5wk2V4lnBlJtEVNKKaUOi2n0tkUpNVmstb6rYGWsUlLniOvEV0I0BhtaMo0ZMs0ZouaIsCHEZmr704kYnPO36tLAEOZDbGSHNps2jDHMaJ3B389+A7OSdrCQ5hxJkyNqiCiUDL++37A+gp5joH/OcLuXDSFqg+xCIb/MUX+8o/4ER/5YIaj3lRP7Z0HXMigncPNdBid2Wl1fpZRS6nDTIKaUmhDGGK5o+Fsa0wYkgDTviBtTkpz4VpzQB7IgCggyAWFdSNRYCVljBQDjx5rZyELkW9mmo0XzF/HimS/guHgpEkCSA7IQNUXs6DLcvs6wagB658PuFdA/27d02QiCOgibIGyGsBHCOh/C4jooNvs525zA5l2VSouh1I43U0oppdSTpmPElFIT5vTjTmfw4QJ3DtzF9mgnSV6wocNFYMRgY38zGIw1EFowKTaxuMQhTsABBmxgCCILxpBEQpqbnkEM4PjFxwOQ78jxQPgwcYPDRhbrQrZ3pQiOxAjHLYA4D+V6aNzuC3kYNzxKDPz6/jlQbIHeQVi1wZCmhiBvSXOCC8Y7CqWUUkodDA1iSqkJdcFJ52MfMdzdfx8bo824jPg5xkQIygZbNtjEfzUOgkyARIJNfRjDCRiDDSszFhtwkcNFQlYynO5O2W+xjtXrV9NfHmOWY2DZnGW0trQehjM/vI5ffDx1mTrYanigbhU2dASBxXZDx4Al3uRI0hRr4biFvpJiNFgJYgK27FvTyvUw2A67Yli3BR543BDkAoJcQDkvSCgwdadpU0oppSaMBjGl1IQ778TzaHy8kT913onD8Xj0hJ+IOSu+DHtsiAYroSyttJBVui7uLY0EqbTS1Lk6Xnb23475nCLC45sfB+Dnu29mZ9Qx5nbPeeJijp2xZNTyhbMXks0e2ZUrFs5byIsbLmdwzSAY2NC4yWfVoqGn7PjTIz6g1uUSdmQh3wz1WchZyAxCsdEXQ4n74fGthjWbDTayRI0RSVaQ0DErbWd2ZtbknqhSSik1BRgRmb79eQ6R3t5empub6enpoampabIPR6mjShzHfOb+zwHQZXuIbexXCAQlQ6bPYoaqJO7928pAqSUlzQhYaEobecuSv2Nm28zqJoVCgf7BfkrlEp/d8YXaxw9NeDx0d2QFxr28puEVzJsxj2yUPWr+n3/xri+zJdxGHMeEBUNQNpBCuasMAsfMchw7V5jV6k85SeHXdxsGShYnYENL2BwhVii2p8xIW/mr5ss4/bjTJ/vUlFL7USjAjh0wZw7k85N9NEpNLweaDTSIHQIaxJQ6NL56941stJtJSSnZsl/oINsVECSmGpyGglKSFeJG57vLVVgsH17+zwSBbya7c+2f+WX6m+EnqWxqUnwXyJJvdQNIsw6JwFkf7Kp7NcPPeVJyAlec8nJyudzhuASH3Hfu+S5rzFocjqIpEfVawqLFiBD3J7iiq2w5ci6x0HcJDcRf4yZHncvzlgV/x9zZcyftXNSTVyqVCIKAMNSOMFNdmsLVV8NnPgODg1BXB+98J1x7LQQ6xlOpCaFBbAJpEFPq0Hpk/SN8vee/SSuDkUwKUZ8PEEPE+ICQZOXA678KZLoDgsr4swMlgW95c5FvPmtNWnjfWe8GaierPpI9seUJvrjrqwCkJvWBrGRGtDb6sXdD4npH3OAreQQS8NFTPkwURZNx6OopcM7/oH/pnq9wXHYZl556ybSY8Hw6++AH4frr/X/pIcbA+98PH/3o5B2XUtOJBrEJpEFMqUOvu6ebj67/RPV+OGgIipahhjIJodTkkEjG7EpYJRCUDZmewIcvGVosuLIjGUyQpFKKcYgBYyvl9HMWGw1/jJzkhHLrcLWKDyz5p6OuuMcH7r2Gkhm6kGBjQ1AwSEaq0wkMqXN5rjvrQ5NzoOopieOY9626umbZivg4rjz39ZNzQOqwKxSgvd23hO2tvh46OrSbolITQYPYBNIgptSht3cQQyAoGsKCxaTgIt9qM9Qt0aQ+UISDFhuDGSudCZT7ykhZGPrVF4bC0vnw2EaQvR5jDNTlhMGiqX66bLMBUUtEYWbiy+iL5bVNr+TkZScflutwOAy1kvz43p9wZ3D3mNtczDN4/mnPAyau1U/HtBw623du5zNbP4/bq+nXYGhJm/nA2e+ZpCNTh9OGDXDsseOvX78eloyuRaSUOsQ0iE0gDWJKHXoiQqFQ4NpHP17toojz47qCskGMkGYAIwQl31oWxHuFLwFxgiunJIXUz0M2NEbMCE31sGy+cMZx4MYryW6gWIb/vcvQ2eP3b0JDZkbWd1fMCBnJ8KzgfJ53+nMPy7U4XOI4JkmSMddFUTRh44l0TMuhdc+ae7hp4BcUbQmTQnZPgBH/wUVSJxhjyLscV5/+/upYSjU1aIuYUkeGA80GOmpXKXVEMsaQz+drinNgwUV+LivBz4Fly4agVAlhleBV7inX7qyyHHwL1zknCDNbIJuBTAhR4MeBBSU/v9ZQOfyhsWdRCM9/mtA7IHT2wtbdho27SmRNhmJrSjksE7v48F+UQyyKoiNi3NfVV9eOaRkc9PdBx7Q8GYlLKJoStmzIdluM8/+Bov4Amwjl5pSCLU7yUarDIZ/3H2KMNUbsHe/QEKbUkUZbxA4BbRFT6tB6YssT/GrbrwFYH21ERtWtr6iUuA8HLUER0sSRDqR+4mcAI9TlYHYLHDtfqM9BYKGlATIRWOO7NNZ1QOMO/z1mr2qJFUkWemZBTyMUSrCjE25fHWJbI+IWR1PQxNLSCs6b9yLtWncQ9BP8Q+uWB2/lntJ97GYP2W6LLRvKfWVfdCUbYPMBSd6RNApL4mN41QmvpLmpebIPWx1CQy3Mn/0sDAz4/0fveIe2MCs1kbRFTCl1xOvq7uLX6347ernr9pM874/xLViYyqe/QjWEHbdQmNkiNOShPgetjT58DQmKkOuBfCdkBiDTX93lKAK4AIIEMrOgfzbUZWFzR8qOwYC0K+CX3z2Xe773dOKidq07GDt2jB3CwL+J3LFDx7QcqF/e9yseSFbR5bqJ+i0UHHHBkQ9SimWDhH58ZVA0xI2O9dFGynF5/ztWR5Ug8C3JH/iAjrlU6kinQUwpNSk2b9vMX7bfzd3BfaNXHkR4kUAQO7LyurBiMaw4Rnz4CquLsSXI9kFYhKgA2V5/Gxm+XAoSgyT4gFcGmwebhVyXD2VxHdDot09LKX/61mXc+YMLGdqT71rn+1Rq17p9mzPHB9fxWsTmzJn4YzparUpW0xl0EZYsQQHiwRRXdjTMgDgRktjhwhRjA4KSIc0Kt2+8g/PSpzFnll7oqSaf1w8xlDrSHR0T4CilppQNWzZw+7Y7+bO9xy9w/lP6oGAIK7egYAiKI/sJjk2sn1NMBCQVjIEzlgntLT6EBUXf6tWwE5q2QfMmaNkIjdsgVwlhArgSxN0Qd0J5p6G83d+K2wxxh8EVfdfFbD80bPePKcVQ7Df85acXsHdbmojhM58RCoVDfvmmlKExLXtPbaVjWg7OvY/eS9GUCMoGWzZQKVITBEJj3nfJlURIyw4jEA74P/9/Mn9he/f2ST56pZSanrRFTCk14W7ffif3h6v8HYGwYMj0BbWhy4AYiJtS0hBfpn4f84VJKqRFX/qwoc43qkWDUN8B9Tt8K5jZxy6SXijtNLhBkLTy5BWuX8AIURsEBup3w8AsWDZP2LOjkaSUGXOfg4OGx9b2ctqpOnZ0X6691n8da0yLOjDfH7iJJEjI9Pnxkk4Ea6C5AerzvrualARJpTq3Xk0hHKWUUhNOW8SUUpOnUmwj0xcgqdTeEoFYyHQHZHssQdH4YhpjtJAZ8eXuJR1eaVPfctWwHTIFsPvKcQLpgMENgCS1IQx8MCtusZQ7DK4MYRnmPgCnzoUXXtRLLj/2OJsoX2J3+eEnd22mkaExLR0dfp6jjg5/X8fXHbi2pJVAAsAgieBKKUEAS+cKgdWaXEopdSTSIKaUmjQmMWR6/bvtZCCh3F2m1FWk3D10K+HiFFOCbHdAtjsgHDQYx/B8YCmjghOAC30Ys2NPk1UlAM63iIkzjBvXnO+qWNpskMrzz34IZtcnXPm2PzI6IQpn/p87yObcGDtTYxka06LdEQ/eP537TtrSVjDgUkdadDiBtubR3T6VUkodGTSIKaUm1VArV1pOERFyGWisg4Y8tDcLYblM3F0kLafYsg9u+V0hme4AnJ/zS6yfpNaE/h2nCH5dpariPtsDxBfmcEX2Px4tNSS9htIOfz/T78eZvevd/8tbr7qFXL4EQJQrc/7rf88Ffz+6IqRSh1OSd6R5/4NsgGNm+2kaAIJcQFQfgYEku++uvkoppQ4/HSOmlJp0cV9cDUGnLhVOW+aLCwzp6oPbV5XZsstgI0vUFBGWDNJvwQo2NtjIkGnKUNpT5IZfGV5xiVDfAmHJVzsM0vGff6j0/YFwBSjvMGRmCSaEmQ+DO1l41wdv5iVv/C3fu7mZtmNjmFEm1i5haoK5jBA2WjLlgFJ3mS//1C8P6yPCfIAJDGKh3LyP/xBKKaUmhLaIKaUmXVgfgoGFs4T2Zh/CbOorHDZvgrY8nLdCOHGx4GJHubsMAtGgRTC4UHChYKwhNyNHkhhuvdewNoCOFbD1XNh6tp+UebxodDBT27uSoX/VcEVHI+AEwiihZWYXJiliywbjtMlBTZx3n/UOzkxO9Xeq/REN2Rk5wnyICXzJ+sLMpPrX/58W/H+ccdwZk3K8Sik13WmLmFJq0plK36kTFwtz24bfQxrx8301bwI7C2SREAbCg+sr7yJ9MUOSOiGtE8JBQzhoyc7IsrO7zO0POlYsFk5eDGkWtpzjS9g3bqtUUaw+v3/OA8tiBmOFsBEwlX0Y3/1rqBUvrAsptCSIFptQE8haizGGJC+49pQwDgmyQXVZmnekmdouidbq57HK+/bd/82jdt3wAoEPnfbPRFE0eQel1BSnQUwpNakkwBffGMGWfXfCbI+veFiuh/wAzG6EeC48tF5IiglhLsRFgoSCAOVGIa4T8p0BUWOG7sGYe9akPPQ4RCH87YVC3zzonwVNW/3cYkEZjC82d1BMUBvb4gQKpaGVfmyaUhPt8uP/ivb1bfw6+B1BzlKc6f9zyVDZUAMNaT1vW/JmAGa0zJjEo1WTzTnHp+/5d8QIPUEvJVNbAfbf7v8P3rDkNcxqnzVJR6jU1KZBTCk14S5bfCkNm+r5U/AXkrwjqkwu2zcIxTLUGcgMQhBDGvpbkgVyEJVBMEilL6FYRjRt+TecxRkpxkHQE5CWQvpTh+tL+NkdcMZyYXYrZJt8sY268oh9DM3uvD8GbK52USmGwdgQNQ5/evySzOWctPCkp3axlDoIjY2NPG3JuTRtaeJ/5Cd+/r2Kp7mzOKP9NEIbMrNt5iQepToS9Pb28p0132NXtBsZ5xdfR9hJku6n9KxS6knTIKaUmnCzZ85m1q5ZUIIkJ0QDYALDY1sMdTmheTYUWiEogoQ+KLmotpXJRrVNTvPjuTyj6TxEhB/yU1Jx0GJwiWDLhsBE7Oh33PtYwjNPE5r3arUKGyHpPsCxYhaCev9toRXSDHT0wNqtFhta0sqb34WtC2luan5qF0upg9TU1MSpS07Bbqxt5l3QuoC5s+dO0lGpI8nmbZv5/dbbWBdtmOxDUWpa0yCmlJo8huon9mE+pLMvYc0mP0nX8nmViZqt77qYZGBXN6yuvLm0oSXNSDVMtdLCOSecA0D3Az2ICA/ah9lZ14HNGILQEPaEbN/jeHiDw7YJ2UbI9fi5xjJzBFeEtAjsq8iGEYyVaotY/2yIc9DfAbu7DVELOjZMTbp8Pl/9/6DU3jr7O3kgXDXZh6HUtKdBTCk16dKMEBDgYsfW3VAqOwIrzGmDbKWn3849PoSt3WIJshaDIalPESssiOdxbH5xdX/POe0yAOpX1XPP4H1sibbhQsEmAbZkWbNZaKoTZsyCoARN2yFqgXSWQCe4QZAURg0cM4LNQNhMtepcsdm3iFHZ3BiDcT5cPtrxGLv7d9NS18KSBUuqu3n48Ycpp7VjMQBOW3aaFk9QSh12rfWtnNRzAg+Ha/a53enJyeSzOsO6UoeLBjGl1KRoyjUyf2AuW6PtlBscua6AIOdDyO5e+P19jnNWCC0N4Bzct9awo8tiM5aoIcJFQlqZlPaMzKk865RnjnqOZ5z8dJrWNnJL1x/88zSl5MsRcS909glbWwWOhWjQt4zl5oEJhaQbXMlP9MxQIREDxgpBo289M5VWL7G+UEec4MeXOSGIDSYx3MwtMADLupfwXJ5dPa4fdv2EvqB/1PHWb6onCiPamtpoamo6pNdbKaWGLJq/iBflX8DDG8cOYgEBi+IFvPLMlxOG+lZRqcNF/3cppSbFyUtPpqWuhc/u+AKS8fOABVIpX2igXIY/PTg8YMtYg81awroQCSoT0hpoTpvI53LjPs+py09l5s6Z3LDpW+wJu3CBENaHrNsJg4WEhtMFdwYs+Isfk5adBZmZgsSQDgppwR+SjXyJexOCzfp9D7WE9fRDf8EXEEnLKTYKyPRZ4gaHC4V14QbWdXxl+KAChouCDH018OWuGwF4TufFXLD0fBoaGg7BlVZKqVrlcpmuvq4x10USMTuZyVvP/fsJPiqlph/tA6OUmjTWWnLOp5pSW0qaEWxkieojMs0ZTGgqIcgSNUZEDRESQbkpxUWQc1leN+//cO6Kc/f5PHNnz+WqU/8veZej1O5wOTChYUun5ce3GUoJbH4axHXgAt/KZTO+u2JuLuTmQKYNohkQNvkwhoHO430RkUwEmUgwzhH3JcT9MbYAuc6AbHdAUKhMUjbiFpQN4aAhGrBEfZZw0PjWN4Ffp7/jf1bfRLFYpFgsHt4XQSk17TzyxCN8ac/XRi0PJWRpsph3nPv2STgqpaYfI3JANcLUPvT29tLc3ExPT492J1LqIJXLZT646jpcZTKxqM9Wy9kDSCp+wmcDSc4RNzkflMRy3YkfJLeP1rCxfGjldRQpEvVZTI+Q9CUgwt+90BEYyPb7CZ8btzN2KfuhTBXCpqf7+2kKmzvgkScMm3aCiK+DHzVlsJGfZPegrklTSlLvnzwg4PpTryEItAKIUuqpExHuX3s/3x74Qc1yg+ESnsnzz3jeJB2ZUlPHgWYDDWKHgAYxpZ66D628joKttP4I2NgQ9VlsDEm9kOSlWmEx6zJ87KxrntrzOAgLhkxPQFyMSQdSnnaiY9l8aKoDG0Pdbj/xM/j7g20wMBtKQxXpK/lKHMQpFMrQ1Qe/+rNhbhvs7oE48RsZawgbQoLMiEDlhDRxJIMJkgz/Kg4bQmxDQFLnqoHsQ0vfq6XwlVJP2Y9W3sQd9q5Ry69sfg0rjl0xCUek1NSjQWwCaRBT6qlL05QvrvwyT0Sba1cINcULF8bzeftZ//CkW4jSNOULK7/MxsrzmATyHSEglLvLkDqOPwbOPl5oyFPbKmZGfz9QhELRd09srPPLnMDsh2DPUt/dsasXVm8yrFp/4C1jQTYgavIlIwfnJAQS8LqWKzjx2BOf1HkrpRRoEFNqImgQm0AaxJQ6NIrFIs451mxew3cGfzhq/dPSs3jhyS846O6IYz3PLx++efjNiIO6XSHihLg/xiQpoYUggBMWCVt2GZxAWOkxWU6gHEPqIJ+FM48TFs6CXOTnJJv1EGQG/Fiz7mOgbzbEleqK37vVUIqHui9CEPjKkJefLwz1YNzTC49vMzyy0WICQ9SaoTAzIUeWZwUX8JzTL3tK56+Umr7GCmJXzftHZrXP0i7QSh0iGsQmkAYxpQ6tUqlEd2/3qOV1uToaGxsPyXP09/czUBigd7CX/9xzAyYxZLsspgyIH0chiSOIE8qx/zU51J4lUrkB1sDieXDCMcKiWRCUYcGf/STUAGkELvShzIWwZjk8uhma6yvrHSycNdyaZoDE+aDX2Qu/uNNAYAlnZIhbHfkwzwmynCvOfsUhuQ5Kqemlr6+PweJgzbKZbTN1DkOlDqEDzQZavl4pdcTJZrPMnjn7sD5HQ0MDDQ0NZLozsAckFMotDpNCUDSERYtYgwstQW78z6uSvoStHY62Rlg0ywcu4yDp9vOQJX0GG0F2geACaGmAkxbD0NQ8IpDP+Ja09jVg0sp+c9DSAi84X4CUWx+IEQkoNRV4JPcoX7/7W7zunFcf1muklJp6GhsbD9kHWkqpp0Y//lBKTWv1dfW8NPsiLLY6SXRcL5SbU+JWR9ImpO34Wxu45v+fvT8P0j3L7zq/9znnty/Pmuvdqm5tre7WNggEAnuklhAwkj14DBgBdjARSHg8EA4p4B+gTSNCiLCBUSuIMEGEbbCgHQ4gxsNMsISEGOwBCZBa6m51d1V11a275p757L/99zvHf/yee1vVXd3qpfqWSnVeFRlZ+eSTmb+8N28++c3v+X6+AhlIlKtQrsJJHGotOZ0L7p9/fqRN+qAfL4TettKEhvAKEh8Cr38K3X6h9OT1/nXhHKI5xBcwPYJvn8PNXXh2tyWsOsTc0BQ1L6vP8U8+/t/Stu0794dnWZZlWdbXzHbELMt6T/M8j9/1gd/F4hNLjDH8WvdZzt1LWvct7mxAdAbjCkQnkK1ACQUGZnnHG0cdz05Mf2QxBLHuCzLpG+hAqD4avxr0+8r6fWKQnEJ8BsL0NVtX9t00dwP+uu+OfeA6BF7Lo5liNuvru38f/zKDT6d81/O/y/6G23pXKQo4PYWDAwjDd/pqLMuy3hm2EHuPsg+ClvVmf+Dbfz8A8a/FPCgffsn7Lc2Ku9EDwCAbAUYihaLKDLN1R2Mg34XwctsV06afJ9sWYl7WF1yPqQaiC5C/7jZdQpeDCvqnyRvw7AdgmoBaaS7m4BiBUYKfDf5HnLsO33r9W9iZ7nyD/nQs6+3RdfCRj8BP/RTkOUQR/NiPwY//eB+OY1mW9V5iC7H3GPsgaFlf3n/6Lf/zL/v6Ow/u8C9OfxaA++4j2kjjbvqlzXUneHhlcL8JDn8VXNEXX6bpd40JoJj0c2SPGcB8wb89oQAJXQ1qW8AN78O4g8vOcCfWzFYNnvDobhj+efdzBKeBLcSs3/Q+8hH4yZ/sZyOhfxz6yZ/s//8nfuKduy7Lsqx3gp0Re495/CCYbwOTHj8IfuQj7+x1Wda7xfO3nufPfuf/gf/6t//vEUbQBX0Ih3Qlm1bx878iqAXMb/c7xGQKzhhkANqF2YvQKMhLKJv+tmK8Lci2H0NG4KQgBOiqv83P+vf3zEvwn35bH9lYL2tEw5t3nVnWb1JF0f8S8Auzmo2Bj360f71lWdZ7iS3E3kPsg6BlvX2EEATGRyAwyoArkJ7CaLh7DJsJbPahTvt5sNaH1SFoAZdL+NlfEnz8VUHjwvLGm2spqcCJwd8HJ+o7aVqAqsCp+wLNdQxCCcIrB9EKGt3Y4A7rN7XT08//EvALZVn/esuyrPcSW4i9h9gHQct6+wgh+Kvf8X9i1A5pEk0b94vD2k7w8x8XNC0sb8Lxb4MHvweOvwNmz8Eqh3/1y4KrFSw3cO+4L66aCBCf74y96UnA+hCKKTQh7I7gf/Mhg2k/X779D+2/5P/9q//oqf85/FZWFHD3rv0l1dvl4KA/Dv9W4rh/vWVZ1nuJLcTeQ+yDoGV9g8i+WJJK4A5dQPD3/rngM/dgtoarDXz6BP7uPxX8v35OsK4kdSu4fwafvCuoUzj+zr7Y6rZpjUZCncDpt8O974bZSzB/Dq5iePUBfOznJNKz38K/EboOPvxh2NmB557rn3/4w/3t1tcuDPuZZCHefLsQ8KM/aoOjLMt677FhHe8hjx8Ef/2gNNgHQct6+4g3/f+/+9Svu8kIhBT4E//JPdqi5WzW8Pf/peC//M8MVy/1xReif14ln3/7VsO/+rjgwRmgFP7EpZpVT+Wzeq+xgRLfOD/+4/3zj360P4kRx/3jz+PbLcuy3kuEMV84MWR9tVarFcPhkOVyyWAweKcv58t6nJr4Vg+CNjXRsr56f+2X/i/MnQWqELgbiWwE9apGN/rJfYQSKF+hQkUXgnEMqhSIFnSjaZc1gQ9/7PsMvqIvvgTkFfx/PyHYGxtevi/IKhCugxM5CCkw2qA9qMeaH/C/n9/9vu/C9/0vea3Wb6wo+g7YWx3jjmO4uLC/tHo72BUqlmX9VvaV1ga2EHsbvJsKscfsg6BlvT0uri74b+/8U15Tb6Aqgb9QGG1osgbT9emG0pM4iUMz0HS+wQgQGjACWYM7E9TLmlFiuH1o2BlAp+HBOdw7FXi+pHPdvn0twHjQpBrtABiMgv+1/7/kd3/wu97hP413v7t3++OIX8obb8Dt20/veizLsqx3n6+0NrBHE9+jwtD+MGFZb4fd6S7BGwHIPoq+8w2qEriRy+PfcxkH2tDQBgYk/LHoD/GLy//IPfchnQJ2wTUui1XDqw/gvgdaQ9EIROTSSoEJBF2kMU4/j6ZdAwL+y8Efx5EOBxM75Pl2eDxL+6U6YnaW1rIsy3q72ELMsizr6/Rdu9+JuBB8Sn2GJtZoJXAKiUTQuQbtG1rfIKXkf+X9AN9y+1tIjhNm+Yyrcsa/8f8dYiJwtENtoG7pu2kCXE/RJBrtajqvL+R22gnfHfweAD5w+wNIaUM73i52ltayLMt6WmwhZlmW9XV66dmXcB0X50TxK/6n+r1iCjB950o7BuOARPJdH/guhBC879n3ATBfzGnvtPzb+D/gGolTSGgMaIPG0HmGJtYg4VvaDzAVYybRhO/6gD2G+I1iAyUsy7Ksp8EWYpZlWW+D2zduk4Yp9Z2GT7sv0yT6Ta/3tMcH9Etf9Hbj0Zgf/NYfYP2JjE8nL9OiEe42rUMIuqAvwt7fvMT33fwebhzeeEqf0XuXUn064l/6S3aW1rIsy/rGeVecZ7l37x5/6k/9KW7fvk0Yhjz//PN85CMfoa7rJ/f55Cc/yR/7Y3+MmzdvEoYh73//+/npn/7p3/B9f8/3fA9CiDc9/dAP/dA38tOxLOu3qJ3pDn/82/8ot5obX/T0Uvc8/9vf8ccRX7hECXBdl//d7/jj3G5vIWKHetz1T6OOLujPx/3hb/ovbBH2lD2epbVFmGVZlvWN8K7oiL3yyitorfm7f/fv8sILL/DpT3+aH/mRHyHLMv7m3/ybAHz84x9nd3eXf/gP/yE3b97kF37hF/jTf/pPo5Tiz/7ZP/tl3/+P/MiP8Ff/6l998nJoH3Uty/oaeZ7H//E7/+uv6W3/q+/8Ef4f//H/yYk5+6LXCb64gLMsy7Is693rXRtf/zf+xt/g7/ydv8Mbb7zxJe/zZ/7Mn+Hll1/mX//rf/0l7/M93/M9fPu3fzsf/ehHv+ZreTfG11uWZVmWZVmW9fb7SmuDd8XRxLeyXC6ZTCZf930APvaxj7Gzs8MHP/hB/vyf//Os1+u36zIty7Isy7Isy7K+yLviaOIXunPnDn/7b/9t/tbf+ltf8j6/+Iu/yD/6R/+If/bP/tmXfV9/4k/8CW7fvs3BwQGf/vSn+Qt/4S/wyU9+kp/7uZ/7km9TVRVVVT15ebVaffWfhGVZlmVZlmVZ71nvaEfsr/yVv/JFQRlf+PTLv/zLb3qb4+Nj/sAf+AP8kT/yR/jhH/7ht3y/n/nMZ/iDf/AP8pf/8l/m+7//+7/sNfzIj/wIv/f3/l6++Zu/mR/6oR/in/yTf8K/+lf/il/5lV/5km/z1//6X2c4HD55unnz5lf/yVuWZVmWZVmW9Z71js6IXV5ecnl5+WXv8+yzzxIEAdAXYR/60If4nb/zd/L3//7ff8slpp/97Gf50Ic+xA//8A/z1/7aX/uqr8kYg+/7/IN/8A/4o3/0j77lfd6qI3bz5k07I2ZZlmVZlmVZ73Ff6YzYO3o0cWdnh52dna/ovkdHR3zoQx/iO77jO/h7f+/vvWUR9pnPfIbv/d7v5U/+yT/5NRVhj99H0zQcHh5+yfv4vo/v+1/T+7cs673ntfuv8T+c/Ys33faf7/8ALzzzwjt0RZZlWZZlvdPeFamJx8fHfPd3fze3bt3iZ37mZ1BKPXndwcEB0BdQH/rQh/h9v+/3PYm0B1BKsbu7C/TF3Pd93/fxMz/zM3znd34nd+7c4WMf+xg/8AM/wM7ODp/97Gf5c3/uzxGGIb/0S7/0po/z5djURMuyvpT/8PJ/4BfXv8Qj9/hNt99srvNd6e/gO9//ne/QlVmWZVmW9Y3wruiIfaV+9md/ltdff53XX3+dGzfevND0cR35j//xP+bi4oKPfexjfOxjH3vy+meeeYZ79+4B0DQNr776KnmeA/2+n5//+Z/np3/6p9lsNty8eZMf/MEf5CMf+chXXIRZlmV9OafFWV+EGVCVQNYCowyPgiP+3Vpz9PETXOHwv/htP/hOX6plWZZlWU/Ru6Ij9pud7YhZlvWl/NNf+e/5n8S/Bw3+XCEKA56gCwzaM2jX4EiX/8z7vfye9/9u+0sgy7Isy3qX+y2/R8yyLOvdRBhQtcB0BlGDXBjUElQpaGj475t/Qdu27/RlWpZlWZb1lNhCzLIs62kRoHxF13R0eYdZa9RaoGoBwNH5EU3TvMMXaVmWZVnW02ALMcuyrG+gUIXEOsII6NzPnwSXnsRoQ7dq8Zb9t+L/6+X/jdOL03fqUi3LsizLeopsIWZZlvUN9Pu+7fv5Q4P/HCRU0w4EOKGDUAIVKLzUAyPe6cu0LMuyLOspe1ekJlqWZb3bCQQGQ77f4s8VUiiEASOhDfU7fXmWZVmWZT1ltiNmWZb1DfatL34rf+HZP/fk5WrcUey35ActxV5Lk9pCzLIsy7Lea2xHzLIs6ymYjCf89eTHAfg/f/K/YaGWX3SfH3/pLxFF0dO+NMuyLMuy3gG2ELMsy3pKXNcF4Ee/6c+g9Rd3weI4ftqXZFmWZVnWO8QWYpZlWU9ZkiTv9CVYlmVZlvUOszNilmVZlmVZlmVZT5ktxCzLsizLsizLsp4yW4hZlmVZlmVZlmU9ZbYQsyzLsizLsizLespsIWZZlmVZlmVZlvWU2ULMsizLsizLsizrKbOFmGVZlmX9BooC7t7tn1uWZVnW28EWYpZlWZb1JXQdfPjDsLMDzz3XP//wh/vbLcuyLOvrYRc6W5ZlWdaX8JGPwE/+JBjTv5zn/csAP/ET79x1WZZlWe9+tiNmWZZlWW+hKOCnfurzRdhjxsBHP2qPKVqWZVlfH1uIWZZlWdZbOD3tO2BvJcv611uWZVnW18oWYpZlWZb1Fg4OIIre+nVx3L/esizLsr5WthCzLMuyrLcQhvBjPwZCvPl2IeBHf7R/vWVZlmV9rWxYh2VZlmV9CT/+4/3zj360P44Yx30R9vh2y7Isy/paCWO+cAzZ+mqtViuGwyHL5ZLBYPBOX45lWZb1NiuKfibs4MB2wizLsqwv7yutDWxHzLIsy7J+A2EIt2+/01dhWZZl/VZiZ8Qsy7Isy7Isy7KeMluIWZZlWZZlWZZlPWW2ELMsy7Isy7Isy3rKbCFmWZZlWZZlWZb1lNlCzLIsy7Isy7Is6ymzhZhlWZZlWZZlWdZTZgsxy7Isy7Is6z2rKODu3f65ZT1NthCzLMuyLMuy3nO6Dj78YdjZgeee659/+MP97Zb1NNiFzpZlWZZlWdZ7zkc+Aj/5k2BM/3Ke9y8D/MRPvHPXZb132I6YZf0WYI9VWJZlWdZXrijgp37q80XYY8bARz9qH0+tp8MWYpb1LmaPVViWZVnWV+/0tO+AvZUs619vWd9o9miiZb2LvVuPVfzzf/8PcRyH6zu7LOdzJBB6Lvlmg+96IAS+5zGfLXAdn+NHp9RtQRgFZLrlvK6ppEAGAbVUyCgkq2pKx8VTA/KrIUpGmNZlPJpyNbtgFE/JqwplDG1Z4AhJEkU0uqNtGkbTHUQieHTnBFVWeK6DHwRIx+X08pI2z/mml16k7DqypmWzWiGKnJ3JFKkk2SZDCvDDECEVSgqSNEUqh6NHD/GUwmiDkBLlOpRty+z8nPFwRBD45HlOFMXUdYXvetRNg5SSeJCi0pR103B5eYlXNwRhgFIKXI/s6oquaXj2uefA9/jsG3ehLBhGMboo2NvbY7lekxcFnlIEUYQBNBAPUvK2Y7HZsLm6YjIaMdzfw3gFebGhWigGacJivmB3d5d5voasxKlrojCkKUtc16VqGpCS4+Nj0jhmkMTorkMgEAJGwxEohef7LDcbQs+l1ZpVVVOtlhxev86DN+4yiCPSOMFxHLquo6pKHMelaRoGg5QiL6ibGkc5VG2DIxWu49B2HW4QsM4ypFK0dc3ezpT5YkGcpJxfXhCGIaHvo43B9Tw0gnK9ZhDHNHWNAZqmJvAD6qZGKQchBFprHN8j22xwHAdHKuqqwnNdtNYIKZDKoalrpJRo3f8WJPQDhOrvazB0naZrGvwgoO06giBgOBqRlwVFltM2DUkSs9lkFHmO53v4ng9C0LYtrusAgqKuiKKYqm1Z5jmhlMSHh3zu5ZeZBgFxHLExEA2HdLojPzriYG+f3Wef4fjRI3bSFB0ELIzmfH6H+mHOyPOJoog8z5lOJqw3Gxyl0LrD9XxwHbSULK9mTOKYpm34K//V979j3z8s6+1wcABR9NbFWBz3r7esbzTbEbOsd6l387GKOEk42NmhKXLqpsb1PcqmwYti3DDAYJivV1RopCdQkeDaC89y67lnOaoqjrqOE6lY+gGF1milkErx0s3r+HpJrReY1meY7PRF2GCPTtYUWYbWfYFgjKaqSnSnSUcj/KnLw7NPcXZ6ShxHDEYjqqpmsVoRO4pv+e3fwczA5eUli9MTRFlyeO060nVZbzZ4nkcyGGCEpNOayc1b+M/4zINzLjcbpJQUVYkUkGc5xWrN/u4uQRAQD4fsPvccFYa6bUEKlJKEUYQ7GHB8ecnp0TFulhH6Hl3dII0hm83QbcutW7fQrsOD0zPCpmbgeoi2ZTgYsFqtoOsYxjGj8Yg0TRnt7lC3Lav1hq6uCbqO63u7DJKEqqx4eOeK5UlFKCXSQOj7nD98iNoUqLZlMB7TCPCjCMdxSOKY0XDAi+97H/u3btEi8MOQNE3Zu3Yd5XkUZcl6+xOPVgoVRpTzGUkUcfLgIbvTCc62SCnrCsdxUI5L1dRIYDFfUDc1Qki00aANQgjarkVJSVUUhL5PV5YkUUiW50ghMMawt7MDQtLUNUpIlvMFXZEjBTR1DUJgtMZzPbQxOMrBGIPuOoyAuqqQUtI2LU3TkKQpRggAuk5TVyVSSozRSCFRStHp/usLQEmFUpIojhACAt8niCI2TUOpDcvNmrquWK/WAAwHA5IkQUgBxhBFEdFgiHYUvueTlQVhFBEKQRQGsFrx3N4u+5MJjpBMfY/s7JTNw4dcPzgkDAIeXlwyywsqx+GoekSnO8aHJWp3DzcK8TyP8WRCnmcoIQBDkqSkaYr0PMosJwwDOkAq9Q5817Cst1cYwo/9GGz/KT8hBPzoj/avt6xvNFuIWda71Lv5WIXpNNlyxdV8QZqm+EJi2o7Ac1ktV5wvFnSOy2R/Dz8Mef7FF3nxxk1Oz89wkxh/MKCSgrO5ofQmSMdlEvjkJ6d8+o03qDOPg+sD5vk9JuN9cDdcnF8xSBKkgTiOcfwALwjZv36dZG/Ig6PPcXUXXrxxg9oYlqs1eVUSCNg/PORyuWSTraiKgtj32d3ZYZVtmC0XaK1BCrRUBNMpkxefwT2Yscx+gV/91C+QhBFVp/Fcl6bTGN3hOYqu2XY6lOJ8c8XJ+Tm+0xd2xkBVFBzdvYtcrdgLg75rZ8ALA4q6hrYlTRK063Lntdcw63XfhepaXNkXBEmakAxSRjs7NAgqITi7uKRYrwiEIN9sMF3H5PAabRiwubok7loOkgTfUSxnM6hrbj93Gz+OiYIAx/coqprlcol0FEYIwnTAZVFwdO8ejhR4joMXBqyrkqwscZKE9WZN1zZkWc6je3dJwwhPKW7dvMHOtWssVyscz6XTmk1RUNYVZVHStA2u6yAAozswhsDzcBwHrTXGaHzPI0wTpOvSlBV10XfryjzD9TwcJenavrCajIbEozGeH1DUFcaYbTdL07Ytbdchtz+duY6LAbq2/7ie55FlmycdMKUkSio8z0NJRRCG/XVt36cUAuX03VBtDJ7rAlA1NcvZjPnFOUIbgiDE8z08x0EoiRD99cbDAXldcXl52Rd0YUDsBzRNjRMEACTTKWowIByPCEcjyrph6Adc29sjHI+5ms9x1ytuPPccd9+4y/z1JX7ZcHXkU1xesswLyrKkqEqiwQANKCkRUtJojXJc4uGApiwpsuyLf/tjWe9SP/7j8Bf/Yt8Bg/75X/yL/e2W9TTYo4mW9S71bj5WIY0mazuiOGa5WtHUDdJ1aJZLsrri2o2bpFGIaFpmmyuk5/PqK69R1A267RC+xzAaspmn1PMJmdPyuYtPUWUB1yf/Kc8/f5t7R5+Fbor0NpwdXTEIx+TZhjiKMa7D7OKC6XDI+eqKB599A7d2eXZ/n7bTDAcDlsslsecTJQlXyxVhmlLkJZHrsbu3z2wxRzcNkR/gui5+HBGMRgS7DSb4JIvzS37xl19HzV9E7DRkVcWtW7dYbDY02YZr12/gDFKIYh48uMf5nbsMgwDXdfC3R+GiOCaNE4QxBGnCxWJJKAVlnrNarZmkKcPJmIcPH+AZUMZgtCZNEpSj0MbQ1A0NsDw7JQhCGq0RbUMax3iey14wwYtjzq6uODs+ZuA6HN64QVUUGOVwcO2Qyc09LhavszyrORwOWVUVdbbh+uEhyWTCLMuZFQXlbMYLL75A5Th4dYPyfbLjI6aTKcfn5zhAW9XormUUhEynU9wgYL5e8/DOG0yHIwz9UbwgCDBdRxSGCCEQQuK5Csd1abZHB9umwXM9mqZBSs3y6grfczFtRxyGVF3HYDxmsd6g64ZkPKbcbIiHEQ8ePiR2XTzP6wsmKdFNA4+LMmMwQNs0CANhGNLUFXVdIRAgDFmeE26LobZpqOoKhEB3HVIpBH3HrulafM+naRuapkUoCU1LHIW0dYWrJI5SeFHEaj4nCkPKosDzfQyComnYH41wxhPOsoyg07iOQ5wOqNoW5fsM9kIePHhAd7ZGdZrY92nbluMHDxBdRzKdcO/+fZr1mtvXrlEaQ31SMXAcIinxPY91nlFXFYHbF7lGa7wo4nI+p9hsGCiHOI76otSyfgtQqj/G/5f+Uv/Ly4MD2wmzni7bEbOsd6l387EKYQwaQyOgBkQQ4McJlTG4QcBmuSCbz7lz53VWVU2uNdEwQngeThyRhhGBMQzHIX7ksDobEpS/i2+6+fu5dmPCg/Nfoioa9g6mzJeXhP6YxXxGHAQoKZldXqG6DtF1XL3xgD13yM5wSNf2nZCHDx8gjWb/2jWyokAZzeL0lIMo4sbt26yrkvVqheM4DAcD4uGAaDpFDJe4yV3qszP+/Sd+Fa/9Jq6Nx1y/foMbz9yiVorj4yNuPPc8ue5Yty2f/dx/5OHrd9hPU3anE7q2oyorvCBEeR5ojRGCVjnIMGRTVTRlySCOmEynzBdLJqMx0nFQRjMeDnA9D+V5VG2L5/vQtQxHY4Iooq1K2qYh8DyS4YjZes3po0e0iwXXh0OefeGFvoMVhBghEKOS107/GXfufhpHKRrHYX55yd7OLtFwxApBKwWPHj1kEAa0QnB2ckoTR8yMIRgMOJ/NSJMYLUB3Lb7rEacprVKcXFywmF2xMx4RRBFV02CkYjab4ShFOhpS1XXfpVKKrmsRQtI2DQhBUeQIAVIKIrefq8qbGq010hg6YxDGIIUgWy5pqorNcknieYRBgAAEhqqqaNsG13XBGLTWKClxXReDoSxLqqp+csxQSUUUhTiui3IUne4IwwgpJa7n9tcpBdpoXOUQRCGrPMcYgxAS1/PI1hukAc/3aNqGfLVCyv5hWTkOWVEwn82Io4hCa9azGVfHx1wtFmRA47m0g5BHxTGnV69z/GhO1zSk266cMRBIie+5VHmBt1iwNxqCkszv3eXGYMh4NGK4s8O6yEmjiDgICMMQISSO77FaLkmjENl1+L7PYr6wRxOt33LCEG7f/s39uGn91mQ7Ypb1Lvb4+MRHP9ofR4zjvgj7zX6som5b0iRlvlywO92hXq8pqgovDBkEAav1hsuyxCQpYRgSRxGUJZNBStk0HGUZ08GQO2dvsF6NcOvneObZWxj/lMXmhMtjg6ci5ssL6qpCdS23X3yRxWJBtlziaU00HGIw7EymhHFM23XUTU2ZF+yOxkwO9nl4fIzoOpRw2NvdRUvB1XrFcrki9HySdIAIfMKDhNZ7g4MdqB9e8Iu/9mny82/jRhpx+4UXuFytODt6xCCM+JYPfBC5O6SdLzl99JDqomDX94njmKZpUMrBDwPKpqHtOozWhGnCsq6Zn54QOi6xHyAFtAKM0VxeXuLSH6NTykEbTVU01FWF7jp02+IMBJu6Qnoesqpx45h7jx5SrtfcvH6DWndI5XB5ecnV1RWT8YTJwQFvvPwA5d9CNBtqWXN1dMQkTQjGY85WK8qiIB0MGI1GRJ5Ptlzx/EsvsermPLhzjFwsuLazQ+i6aM+HtiFOEhopELrDGMMgSTHA1XyOwtDUNZPhiINnnuHRo4ckaUoQhpRtgysV69kVgd93osIw7I9xVnV/DBBDoBzatqVqWyqlKLMNCoHvexgpUEoReB5KSYSAtm3RXYuSiq5tAeja5snXq5SSwPcxnocUgrqqcFwH13GfHGMUQj45Jtl1HUop6rJCdy14Ppv1BtN2uH4fwHFxdUnk+dSmD/IIAx+lHMqqoipLwjhGKUXbtjRVhTGwmM3YiSKGkzGV6zKrr7i6t8bVmvGtfa7dCHA2hmqzYbKzw2a9Io5T6rIEDOlgQBRFLBYL9sdjojTl/OycdtsFa5qGKIxopMAYaIuCbL3GaRpM15FlGwZpug0OsSzLsr5e9rupZb2LvZuPVVSbPphAGU222RBPxkSOQ1nVKCkYhClCKZQQNFlGmRfEgcfm5AQ/HfD6G3c4zwJ2kuuYzqHYVGxmNZeXsL/7QRAtxbyjaRQ3rk1YLpYoKfEDH9l2IEAg0Bjyuma1WaPajuvXryMCn7P5HCElVVlxsH9AJyWP3riDFJJACPYO9inqhhbI5sfcvrVh/soRv/Dqq6wun+WZwZj3f/M38/q9e5BnXJ/u4Ac+7s4Ody9/njc+UzMRCdM4wXNdjNYIBHEUkRtDtV5jDHhKIQwsz8+IlMMwSai23bw6L2jKClnXxEmC4zoIAbozKCH643l1xXRnyrquKTcZbVUyiBOKzYZIOVx/9jZV1+FsO12u6/LMjRtI12PVLPCAgZ+yMQ6+Noyu7bIocjarJVI5THZ36JQmPytolktuv/Q+sq7m0aNHjIRifOM6UTpgNZ9zcX7G/s4O4SBlnResjo4ZxDFeGJKt1ygMbP8M4sGAo4tz/CSh3GQsZlfouqYsKw7GY9quQ9DPbHVth1ISo02fdmhq2qYmDgI26zWxH2w7RBrH97ezYv0RSCklruP2HSDHoev625TsQ2M832edbfA9H7V9m+F4RFGUdFqjHIem6sNFpOq7ZUVeIBEo18VxnX6myhhGwyF1XeO6DsMkJUoTLs8vCIIAIWXfdasrBoMBQioa3X9eUkrKqmRvOkW5LmVRsrq4RIUhYdMQuy7t+ZLK8yk2a66PRyxXK+IgwEhB07X9kUmtWSyX+Nv5usV8wWAwoKorPNl39QDaokSLPtAmjWOMo2iUIopi9DYB0rIsy/r62ULMsn4LeHys4t3CU4q8qomjkPlmQ5jEmK6jrWvWTcu1yYSuaZBty8OzM06zjKJtqLXm0XrN5WKBlFMmg0PqjUekBLptqBbwTc9+G6vqisVVReL6PPv8M8xXC4yE5WJB5DgEcYz0PKrVGgE4TcONvb0+qCAIubg64uzhQ2Lfx3U9sizj5PycURgwHA7R2uCGIZ3ns5nNCCYTXj7+FK+/+ipe8zv5T168zeG1a5yuHpFt1tzcP2CzXJKORtx77XOcnrhMW8FkFD2ZxQnDgKwoaHTHfLHA6TpqnTPa22OxWeN1HW3XsVoscH2PMIopsgxlDIMkxnH6Do1yXGptyDYbBAaJIN9kbDZrBnFCkEyRQUi2WpKOxpzNZoTb+aA4CnE9n7KuSeKE2ckl0+mEcrUmkBKjG/I8o1ivGe4f9AVc6HPy8D5Ka0ajMZss43h2hd84BJ6Ll6Y8evCA2PO4ee0aUZIyKwry2YzdnR0GOzscP7hPEsVIE9DpjsFoRF03VOsNR5eXBNvQi+lkzM1bt5hdXpHGMbppUI7C9Tzatu/8lWW5TS3saKoaz3VQUj3pVPl+gBCSumno2pYwCPswEMfFGI3R5klBApDnOY5U/VFHx0FISd30hY10FOvVGkmfbFi3bZ9oqRTGGJq2xVEKIaBuaqRUBL6PGyecHB9jhKCsKiLfp9UahOjXAtQNnanRSlLlOYMoZpikVAI6Y2i6lsnOFD8IWTtOnxK53uBv1zrg+wwmU8quJTs9w1QVfhhhmqbv7AloPY8mLzB5vo3o7wvZuq6RApQQCOWyWq0QgOe5fUfRgGOPJlqWZb0tbCFmWdZTV2lDkiakYcjZ+QWN7+ECfhxzYAyPjo8JwpC7jx7y+mrNqeughaSsNZIpO8mzmC6g2HRMoxQJFOs17/vABzk6u0/TgCkrpvuHrDZrXN9hfjRjEMe0dYVyHDogbxpcKRmMRjSuSxfBovgUr7xyweFgF09IlJTUec6z16+h3H7/VTAake521Ku77O0fIp2Gk9MDJv4NksEYIsPL9z/BeqEZuB55niOUJMsy2k3GXpIQOA5RErNeLlGi/+HedV3auiYQEsdz8DyPPC9wpcB1HJQxjCcTWiFo6wYhxJMkPzcMmV/NCMOQumnwVD/D1DQtURSRpGlfKBjDYtbPy11eXtLVFVopuqrCiRM26xXj6Q6nR0fcvnmTRxfnhGFItlpxbTqhqGsO9vbI2xYjBZt8RldpwiRGG8NqsWAvDLncXOJ6LudHxwzCgNFkgpSK1XJJCwzjiHgy5s6dO0wGKXlZkI5GdEXBo0ePcMOQYrXk9vXrdF3HYDSkNXByesr169e53GS49M0m3/fQXQmy72opJXG00+/gqmscx6EoCqSS1HUNxuBICcqhqvtjf0J0NE2N7/l9VH3bz3j5qj9+2GlNURYIIQjjCNO0XJ2fo7u+i1oWRf/xug7XcdBdh+e6CCmoqhrHcfEch7ppqOdzTNNgmoZxmuI4CuG45FWFbhrCKMQVEi2gKUpq3eEqSbVc0W7/zpeLBd5As8lzdm/fJh9eUZ9nhEBbVhwdH9PUNYHjkCiH1WpJ4Lq4jtNH66/XDMcjVqs1URRSFwW67RgOBtRNQ1EWSCkJgwBH9SEpRvezc8IeTbQsy3pb2O+mlmU9dZM4Jokj3rh7lyBOWG02jEcjHp2eMV+viCZTXj16xMubDfPOJ9LP4qoRoQoIggDdNBitmQxHdEZTrSsS3+fi6op8VaG04aUXX0QkktXlGYvTksh1icKQVV2xXq/JsgzaltF0ihcGdLGh0Pd49bN3Cbsxpq6RQfikCyBdl8vVmv3DQ2ox52j2Crt+x+nsszy62iDr6+ztT7h8tKC47NBtQywlTV3h+H4fQiEEm+WScZIQRhFN11HWNWkY0ukOJRVt14HWuJ4HRtNnp4s+tn7b+VGOgwayomAyHOJ4Hpfn5yRxTLtdeKy7lrrTKClwfJ/Ti3OasiRN+7m72eUFk+kOwXBIUZbcuHadTZ6zs7fHxXxOEgZs8qyfUypykjhmVdU0ZcH01jM061OaNufBy6ccjsfopqWTgjgIuDo/Z5Qm0GlGUUQySHH9gKvZDN/3GAQh0c4On331VTxjKFYrAM6Oj2nLklEUY4qSmzdv4vg+m6om6zTzszOmkwmPLq8oFwtu3LjBfL0iq2vqzYaDyYSqqTFZ2e+8ato+PbLrnnRxJGw7W4K6afo5Mfrixvd8lKNomj7C3pX9rFmeZwRBSOj5DKZTVk1NU5bESYyrHi+frvodZI5D07Z0bYNSfSfN9/y+yybEk0XQSRxhjOmPyCpFmCQ0xuC4Ll4cUxRFXzw6iqooGY5GuHGM33U4nkcwHlFmGf5wQFVVHJ88ol5o9sIApywZBiHK6T+WEgIvCAjimLYs6Yym2GQIrTFdx6Zp6KqSOIxI0oS6romjqD8q2TQ4jkNVlSip8AO/X9dgWZZlfd1sIWZZ1lOXOg5UNYMwpHEdrh8ecnV1xb95+ACRpCRXlzTa0IYhh8kHkO0OaTyhbkvGwynL5ZKqaljM10SuQzwcoIuSdrVCVDWD4RCtFK+/8jlE67AzGlHlGVcnJ8RhiCMk0vOJxxNczyWvaqTr8OD+CWQTbt+6SRAE5EXOerVmZ2dK0TQc3LhOsLPEUw+oFxW/+MrrVJfPEMpbjEdjlmctTbEhdlx83ycMA9q6wQ986qqkWC4ZpymD0ZDFfN4v6/V9dKf7dERpMJjtzFA/0+NuF0R7rovuWoZpyrzI2eQZUmxTM7Um9IN+9kkbOt0f2XMwIBVXlxe4UjHe3aUsK9bLJdPpFIOhMZqqbWhWy75btlzhOy7SUbRVTZXliLYh9DwcqfDDiKMHDzi7OCcSgknQx6T72xmpk4cPGQ0HCGMYjkcI2e/Eqo2mBkaDIXlZcnzvHjvTKe1qRRJFnJ+fMQpD/OGoTy6UEi0EXpqiErh8+IDdmzfJ12uCMGCU3KDsWrpOI+qacRRRViVdUeL7fahGYwyi00glnxQPjuvQtA1C9LNXj4M1oiiiLCuM7hMWg20sfdPUTCYTlOMipGSZZZzPZySeT1M3uJHLfD7HUZIoCCmqCkG/F8xRirwo+kAPKVGOoihKPNftu59Ng+/4KMdl07WczGbsD1IWl5fgOHhBgGM0FbBarWikZDAY0rUNuZA045bixDAexbhnHp6s8D2fOs9xpUADrqP6AqxtuVqvcJq2/7oLAnzHZTgYkOcFuC470wmDJOmDOrqOqirZZDlV15JlWZ/OKcQXR7ValmVZXxNbiFmW9dS1tebs/IyszpneuIHfdZzOZmTKoVocctp0uJ4gHrislwXve2GKP1hR5prZ4tfwowmd9okch729Pc5mc0RZEAcB0vdp65rT+/fZjSd0VU1XlpiuY2c67cMPXA+/aeiModQaRwq6rqDLplzfDzECTs9OCYOQ6c4OLQbP83HGF9w//Y+cnMzZXA5I+O08s7fL+vwct+uos4wE8FwHDGhjKIqCuq7wHJcwCsmynCLLiLYx4Z4fcHV1RVdXKF9RFAVpmlLXNZ7nIYSgaRuMAY0g26xZz+cEng+OREjF1XxG6Af95+b18euO59G2LUb38elCSdarNa7nkkQhbdvhRRFt1xHGCXVZkHg+buCTFQV5liMdBVXFdDyiE5K8LFBCEijFtSSl6zrEdsGyMIbFfMb1w0OUo/Bcl7br57IGwxFFljEYpFyt1wgMkZQs1muK5YI865dKR3FCVpb4UUStNX4QcNW0PLx/j1Qq7j18iN5sGO/ssFivSAfDfjYu8FnNZkgEEhCmX8AcBj55luNJ70lhVTc1AtHPQbkOXSvoupaiKGmamjRNt1H2LbrrcD23L6ICn9Vmg+t6TEZj2qZmmO5weXLCjf19tDZkmzWDNKWsa8qqItjuKFOiP1qqtUYKgcH0wSxJAp5H02mujk8ItAZt2N3ZQSvF8dkpsq7xlCIeDmmkJO9aNkVJYAzHywvSYMjJ1cssT1Z88PZtlnmOiiKU1ijVYtqOoijINxlxGOIHAat1vxdPKgchZD9vp/t4emPAc91t+Egfpa9Xa/Z2dhkNBijX5eQ387Z4y7KsdxFbiFmW9dQ1bU2SRAz8IQjJo4sLGtclTmKGo33G4wFVAZuFJhyBE2bcefQfuXoUMI6fY6HneGLEwbVDzs7O6fKMW7dusVytCP2AaDBAeB6rbEHRtvgIIjfCDQPatqVs+oXGZ2enhI7LYDTmbHPJ7v6EJquYzebcvH6dcDhkVRSUiwXXXrjJ8fJ/4s4nYsaDF9DVguduH3J8coKua4rNBkcI9vb3KfKctmloipI0iZFSEscx6/UGx3H6JcBS4voei9WKtukDHnTXz4nVdY3RhrIoidMEYeg7S13XLzv2fOK47+DkWUawnWsKgn4+DAFd14EBI0EIwXRnh02WP/lYBkPbtsRJQl7XhIMBRZZRrhvKukYJQbHesDedgFJ9kbPd87Zer2jrCl8pwjjBcRRSSgaDAUVR0JQlXdcRRDFtWZBlG4Trsbi6Ikpiri6vCIQg8ly6bVdwfHDQH8eUfffscj5n6u5x/41XIM9pg4D9NCUYDcnznPG163QYZpdXVF1Lmg4osg2+69EZjTCCsixxXOfJbi5jDI5ycFynT1qUkrItcZRCSdEnNFY1Xdv23Uin71y5fsBitaLTmtms736VVY0rBOPxiNlqjdzOhG02axzH6Y/zNU1f8HkBGmiaFiUlRVEQhRF10zKb9UV0EkWYrmN0eEAXxdSmJtR7tOfnDIdDpB9gtKarKlwhcFyPQaMYDzzu3dn0SYl1TbZZE/k+eZYROS5sl2IHw2F/DW3DcDgEY6jLsl8WHgSEUYTn+Xieh1IKZ5uaSBASR3Ef6OEoqroherdEs1qWZf0mZwsxy7KeuigOOL84oxUwNwZHSDxgx3E54z67B7coZ3NKWdNVEQ/uO6Thf8L4GZcyF9R5TOR5PLh3n0AIXnjhBRpXYfKCwxevcXp5l6vTDUr0nSXRaYa7u1yu10wGQ3Z2hrxx91UcHFzXpWtqJuMJ9x+9gl4PeOHWM0STCcv8jMpUTG8NWHaf4NHdBbdvvJ9qtSRMYmYXl4ySFBNFdE1DHMdopVislkRBQOD5BGFEURYslivKImcymZA1LUkQcLVa4UqFkYK6qpmMR092h0lX4rgeRVkQRRGbbQqiNoY4ChGyD1Dw3H6OyXEcyroiDEIcz6NzFPlqDcbQdi2L9Yaj42MOdncpjAGtiYdDck/TOi2rRV+ApEohAYxmPB4TBCGt1hRNQ9s0FEUBxjAZTwjiiKwsaYWkWK/pmoZstWSUDmiblrquSUcjNmXFarUiHQ44v7jod7LVNU1VsXdwSOR5bLINzWqFRjC7vOT6tWu0QCAEg8GA6d4uxvPIqpp1McNRG2abDZPRCDcIWF5e9oVvEOIFEWyXOPcHEgV5nqGE7GfDqhoEaK3xnL77IxwHx3Wp225bdPQvGwTSdak7TV1VyLYFLRn6HnEU0wJtUzMdT9hsNk+6TM72OKSU/d4xhCDwfYqywHO9PvilbTnc26PaFtiO63B5ecWseEQF1HXNru/TScF8dkXTbee9XIfz2RV1XZNUFX6ekQwHVLojUorAcRns7NJWJXWeP1nVUJcF49FoGyjiEscxjnIIwxDXcYiifm7tceEaBAHbtWfkeU4QhLiu2/8iwbIsy/q6CWOMeacv4t1utVoxHA5ZLpcMBoN3+nIs6ze9f/Zv/u9oAUZrMq05qWvytqNUive9732o5YLX791jrhQqHBCHYwAuTyqK+Qi/c5lMxpRZxt7uHun1KRfrT+G5AfPNEZcPJZE6xHMUsVLsHhywWC4BcJKURX4PpRRpPCaUE1Soee3VuzRZzTPXr9NiyKuaRi7RuqGuOqLUIYoVV5dLsiPB/nBI17bIbSqe5zpEYcR8tcQR/TxQFEbUbUOe5YS+z3g8pq4rpOqT6zrdsVwucREkcdx3KZoGjCaOY+qmRWyPstV1TegHuJ5L12m6rqXRGu9xyl9T9wuJjUaqvhsThgHL1ZrJeERRlpRlhe+6dPTBFDgOpdasqpLYcajLitBxcH2PuijY2d+n6jRV01AWOYN0QNf2HzdwXXAdVOBx/+59xHpDXRRMhgMGgwFhGCGEoOr6z1E4DvlqxXg0otp2Y+rNhjiOkY5iMp5weXqKEn0oiZCSLM8J/IDdg31WqxXz5Yq2KknjBEcIHCVZbTJqIWiLnOlgyN7hIY/Oz0k9j51r1zi+uOD8+IhREDBIEqqqJggCqqpCCIGQAsd1qbZfm1mW0+UZ+/sHNIAwmk1RkmcZGEMS+PhhxHI+ZzwaYQA3jtBCsri8ZDqZULYNuiipyrJPcHQcXNcjL4o+PMVxMKbvTgmlkKrvNBkB0hiMEKw3GZ6SxOMJ2WqJBMIoYlUUxEqR5QWOlE86kS2gPZf11YwkTSmrEpqGQCnG4wlNVeE6DkkS47r9HjEhQGuDlIIwjJ4UYG9FbyP9heiXYP/B373/Dfv+YFmW9W73ldYGtiNmWdZTd/2ZWwzjhAcnxzw4OeGb3/8B6rIgLwpe/synOV8sWUuHWzeucXFR0mR9Kl25jNkJRriuA9pw+4UXwXVZLOacHwkEUJZTRNMRxYIbzzzDKi8gjDDNmtmDC6Isx/NHOImiFVe0Qc6v/spdDgfP8dxv/1YqveTo4QVOJ4gYEiYxg9sx6+oeR0dHzI48bo1H/WxNFLJZb4jCAEdKdNcRBUEf8Q00dY3RmmGaEscxfhRSVhVd2zwpBOg6/DihLPsQBykErucD9PubHIeiLAk870nynxb9D/Oe45CXFVEc4QcB89kVaZJgEBRFwezqCgwsFgvyPCeJYqbTCeFgyCLbkAxHXMxmpLojWy6Jo5iyKFBuf7RuOZ9TVBVBHPehIgL80YDN1YzrN69RiFd47bNnLE9L9pKU/WvX8H0fz/dpdUfgB+C5qLqiKApGoyFNVZKtN0hjGER9oEXTtlxcnBMFAVESA32BJF0XIQTz9ZqqbhgMBpg2ItuscaKIToi+2HY9wvGIIEk5WSzIViuuv/QSJ3nOYj5jkqbEYYSSEkcbqroCAQaDlA5Np+m07me7Nmt2xmPKsqAVks16zTBN+3TJLAOgLkvG4zHpcMhiuWC9XDFbrZiMhsxWK+Q2Qt91+4JLCfn5yHygqiriOMYLAqqmJkhSutWKtqr6I5JRTF1W7B8eMp/P8B0X03WYtkXWNTKMSMIQKSWOUmR5xmRvn1me40chm9WKOOr3kQ2nU6qqJstz9qcTRsMRQgoe/wq2L8i+fPiG1pqiKBHbItlx3G/AdwXLsqz3HluIWZb11NVlySzPWVxe8R3vfz+6KHl09y6vXl7yUEPqvMRQjlgvFhRXIcP9G6yXCyLt4m/jv8e7O8hRTSE+yTorGAyv48iI/BLSUcRwuoOKBZ67INeXPDp9QGR2CDwXJwhwgpBKXPLyq5/kYPodPP/STdb1a5yc32e1SDmYXOPg5jXW+Rmf+vSvUKwFUsdMfUXXaTxHcnF+jqsc4tEQ3fYdA1c5aNHP09R1TRj4aGOo6pq66TsgVZ4/2TP1eDbIdfsfbh2n3x/WtX3ketu1uK6D1gYNVFWNchz8MKRtG8I4wg8jHj58yMHuLp0xVGW/M8vbzqOVVc10NCIMI8qq5uroCDeOufuZzxDHEW4QII3BcxyiSX/ELnBdfD9gMBziT/qkynDUUbdn7D6jWehf4JWXX2N9ssdQOAwGA5LhkLoqCaII4zicXlywWS5p8owkimnKisl4hJSKQRKTFwWuUnjaQwiYTHdYliWu63A1m0Hb0eqOKAipsg3OaEzVNowmU/I8o1ytSZO4T6iME0ohWC0W3Lp5g+P5jCwvyPMCPwq5vLwk9H2kkn1hRD87J7Z/Xm3T4ijJMEkxBqqq7OfunP7vq+064ijCYDDaYIzm/OqKYrNhMB4zGQwwbcsgisnalrOTE/YnEyR9kSMAJSXi8a4z2ScqCtkXe0XRd/9001BlG/Z3dvq/Rynp2roPASlyAtfDc92+I7rtng6imDrLqNYrjIHE85iMxzSHAbPzc0zbMU5TXNfF2X6dPT4MY4xGiC+3oNlQFDlhGCKE7Gcf6/ob8n3BsizrvcYWYpZlPXWhUiyLkpu3bnJ5fs5/eOMNXtlkCGfAwLtBoHZxxAjTxuwOY1bnK3aiMcM0RQiJF/j4cQxySZUv2BRr6oWLrFN2hgP2bt6iVSVZe4/X736OYhERiDHj3QlN01Cv13RFQVZ43Nz53ezdVMybj3NxlnF10rGbTtm7sQPpK1xcvA71TfZCiSMlXduC1mAMgyTtl95GMflmg9Gapmn62aQOjO5jzIuioCpLXN9nk20YJGmfyOc6SATr9aovzDwXYwxN0/TzS54PHZTbosCRPl6S0GmNDHyarMNXilVVko6GLFYr5vM5h/v7dE2ftFhXNePtrrG6aajrmsBzuby4IFUKBygXC6Y7u2SbDWYbT+56Ll4YUGkD4hR/Z03dlfjjDafHRzy619KubjHAcP3aHsPpDmVVMdo/4Gqz4eS1z9FsMtI4JvQDptMpne7QUtI0DY7n40tJvlwy2d3j/OIcuV6zafqgkjBNqYuCcr6gVf0M1+byAkcqztdrurpmlKYMJlNm2/m0+eyKmzdvsqkrlmfnRNto/elwSNt2/TqBrkO3XT87KKBpGjzHRQnZH7/THW3doYRAConjKlzX6/e7bYsXz+tflroP/KDr2GQZO8MhbdeyurhgbzzG932qokBKDykFvt8nLwa+T57nGPoFyVVVEXouVVlgmpad3Z0+Mr4soW3x/ID5fE4Y+GAMXdvgKId0lFCUBU3b0LYte8MRWZGTTqYUUnF+dITMc0LXRYYB0TZ0Qyn5pAtmzG/cDROi76DleYbcHq20LMuyvn72u6llWU/d2aNHTK9do1yv0U3D4eE1yromjp+nq12WVw1SNOgmoalKDnd3EFKxKXJ2d3bpXId4t6WQD7l6cMHyPGQ/ucbBrX2U51GJNbPVa9z/3BpRT5mmgydJgXXbMEpTpnv7qMTHeJdcrD7L6dkjunzEdPACBzenBNMT7t3/LGcPHRKgaTuQGiUVnusgAeW6jMYjlmXJfL0iDULCMMBzPbLtD9xFnlOWJQDj8ZjD69couo5ytaJrGsqyot12x4QQfdoh/Q/AdV09SVAM0xA3Cqm7jryqUEoym12xMxpTAeVqjS5Lnr15Ey1gPpvhex7K6ZdE67pmk2UYtrvL6go/imirioHfH6cMo4jVcsn+/h7hYEhWVUCH9BrO5r9GU1VU5x3ZukKXt5gol2s3DtECNtmGaGeXz539GvWlRDYt+7u7REmMMLDKNuzuH7Cua2rHoe465lnGdDpllWdIqVCuQzmfIbQmyzaUecGNa4d95Pu6Jd3fp2lb1GJBmKZ4nkde5HhO39EZT3dYdS1nDx+ReB6i7Xj+uecIkoTTs1N8Kbm4uCTy3H6JM9vjiUJijEFtCwwpJVLI/rio8uh0t/170Pi+T9M22yCOPpRDGE3ie3RtS14UpHGEMNDWDVGS9sWT1nRthe+5BEHQF4JK0TYNWZahggBPabztbB1dhycljYE82+C7Do5U4PTFYF2VCOiPq4p+IfVqscDzPS6Pj8F16IqSNAzZ290h8gN833t8V2DbEfwNVoIJ8fg4ZUkUhUipaNvm7fpWYFmW9Z5mCzHLsp46GQQs1mukkGzyHM/1eP9wwOuzV3njtCR13o+vYqosYxTHeGFIrTWBSugchT/IkekZ5cNzLi5rJsm3Mj1ICSYbLhcPaNYRF2cNO8khvuviu30suhcGNMYwuXUDGV0ikyOO797jdL7m9jMvcnG+InEkTphzcvQp7j16ROr/HvxWIdsGow1aG6q2ZTgaIR2Homk4OzrG38bRd21H3uYgxJM9XgjRhySEIedFydXsCiklftuxmc2I/P64WV3XuK6LUs6TQszzPKIkwXFc3DTl8ugI03XETkqYpCjXIXAcqvUagLIsWK3WOEoymYxxHIe6rlmv13hhSJXnVOs1t2/epALmiwW66wijkIuLC/amU1pjeOPePRwpOXhpl8+9coc630MIB9/zaZc5+9GY3dGIqmtBG8IowkhBmbnQVgSuS7zdqRWFIbs7O5yenXJ6fIwvBJXvI8qKs+oChWG0t4eWCiEVptPsTcbMmpauaZllG6q8oMz7o3qx56GUQ9dpkALhOBTGcH7vLtOdHYZpgqhqJjs7yDDg/OKCTZaxWa1Jo4h0OKTYdp8w/TxaFEdUZT+3J4VEG/0kyh0pEaIGDIL+WJ/neTR1X5BUVdUfdxSCNE36ol1rHLcPxCirCtf18KMIrTWdlORNQ+i6BElMVFcIQT9TBxRFySbPCXwPYTS+VDhS0bYtruMQhv0OOtft95T1Xys1RVVS1zX7u7sslyv88RhHOcRxTBJGCCng8VHJ33Aps6HrPt89k1Jti09lZ8Qsy7LeJrYQsyzrqZOeT5rECCH47MkJnzk5oXNdNnXNZPB+qAX5smCw3cFVty3RMCCdtKxWl3iRQ71c8iuvvsqzu9/L/sEeuHPun77Ccl5gij1kN8KNfKq6wlEKP45xYo1sFJ06pxV38BcNy+WSWzevM3Qq7i/vUghF3aWs1hGs3s+mzJGB6fcx+T6e66CUQ12V6FqSZRuSMMRVql/ijKHZBmgIBNU2aKNtOy7OTsnLEqENXhRxtVwwSRMcBJtNRhJH/ZJk0ScxCiEI/IC20zhpyHlZcHF2zou3b7Nar3GEZLi7x0qXlEsfmWWUWY7vOgwHQwCqumGzyRDG0NU10+kUIyX+zi7nDx/SVjX7169zOZ+zt7ePVorZ5QU+At/zuPPZY0Q9YjQcopuaxAu5/sxNVBSi25ZxEPLw3j38OEJ4G6qiYz+JOTg4oG5alOOwWK+59+ABm8WcZ2/exI8ilsslbVUznUzwBgOurvp9YJM0pSkK5ldXKMehKwtCYH9/n2g44OHDh1RVX6A6roMXRRxfXtJUNa5U6KKgyAsiz8MPAy4v+5h333GJhxGhHyCiCOE6rE9PGQQh3rab5boubdeijaZtW6SUmNYglUIKgfL8vnMm+8XbruMQBME2YKX/Oy7LAtf1qLsWXTeUVUUYRnRd28/ZBQGd0QRxwmazocgzYs9HuX2ghzEG3baEvocAgihCCkng+/jbJ9d1MbrD2y7xbtuWtg0Im77TprUmHaQ4SuFtZ8pcz/uq/o1qrdFdh+46HMfFGL39RYT+Coo4y7Is6ythCzHLsp66w/GY9WKB8n2CMGAvvcm68pALn2odka9r9odjhsMhynFI9xz8yUOcekPmLkiiAz73ykO++YPfRppmFJtf4+zkkkevQ+o/y87kGkYbqqwgiWKSQcpwP6Lz73BZ3CcvX0KaAl9r2q4lW624f3FOR8reOKYpDdnCQ7UOkaJfoOt5jEYjjNYYo4mimE22IQz6gIV0MmG1WNBtFyo7jkNZlkRJTFWUSAE0LaMo7ueNhGA3HVA3dR/q4XkIIVEKHOVgvL4jUdQVuzdvcb5ec/TGHYZhQJb1YRrjW8/w6sPXmD04R7QNe4MBURTheR5GgO8H24JC4Ls+450pdafxk5hZcc4i33AwGTPfrHFdh0pJ1pcXKASj0agPttge1xNKoQYDrmYzOqDNc4Tb0CxaVlczZFWxvFugug5/d5d7xyd02QatDXs7O8SuSzyZEsUJKgwItaaROQLYrFbouiLyfDbLJUpKhmmK63l0TUMUJ2ghePm113Daluv7/fLnsq6hrHDajms3b7BYrZgMh5yenDIZpDT080xBGFBmGWVZkUymHJ2dUWYZgaNojaHOcqT4fKy8MRpHObRdSxAENHVDEIY0TYsx/doBJSRGGxyvD2+pq74AcpQDGDy3L+6EcqirCiEFaRwjpMA1UK7XVHmOI0W/y053JHFM12mCMMB1XByltru8+s6XMf3ModYdUsptlHzfrfJ9Qdv627m3tr8Gz9++/kvH0n85ddPgug6e69HUNcr5cqEelmVZ1lfLFmKWZT11q/mM0WTC5eUVAwR+WXFSrGiqHVw95XB3jBQSL47A3SCCBa+/8imCMOSbr9+gPD/jucND7h+f8Kuvzahqg8ch0+E1PDGlqirqqiVSCs/38BKf+eZ1svmjPkRDrnGV4vj0lMl0B9dxmB4coByPrplT5xJTTwipGA2HSCnxPI+qbRmkCXXTMlvMYTs/k6QDFleXdE2LkrKfCxKCdDCkyDOiJMYY0F1G17Zo3dE1ui/ItGE4HNJW1TbBTvS7xOi7EnEUcrlccH58wjMHh1RFgRICIQQnR0fM759ymA6QAq5fv4HBkJUlfhBQtS0XFxeMBwPAsFqv8QYDHi3PWS8K0qHPsm6hbYiDkE1e4CmHNE0pmgZhFHXToHVH2zSgDQYoqgrf93BVTFVscKWkLQqGTt+hunhwHwEcHhyiMazXG7TWmK4jW68JpaQuSsqiIPF9/CDg4mzDdNgfowvjiLIoqTpNWze4oWa+WiHqht3pFL2d53K0BkcRpSlSCBoD54sFWZZxuL/PKs+RrktrDMl0SrZccXp0hAKSMIS2xQgI05QyyzBSsMlzQs9DOv2Orqbu58HqqqKp6213yPRHFulnB9u2RW67RFJKXNejqkqqqsJ1+rAP5bqEYchms6FuagSGZ2/doq5rmrbB93yiMMB1XTzPx/e9J8W853l0ne5DYHSH4HH8vN4+7z/24yh6x3GfdK6+1u6VlIpwG5EP4Hrek11ilmVZ1tvDFmKWZT1148GEk9Mz/t2D+5wZQ60NWRsi8oTd3R2mBymbZU3ZrFjMHuJvDDv7L3A4dph6Pqnv8YlXP8f98zNc9QJJNECaAHSII1wcKZCtZjQaopViuVgSDH2k0ty8lSBlxvnlDJnE+K7DxWxOpzXpYIDoWh7eK3FKn/0kYTga0XYdru9zdnpCmWVs8ozQcYmTBOl5CMfBGMMgTRBK9d24qqZuWqToAxdW8xmecpBCIDDopsFRCjfwcR2Xtm4QUpFnG6IoBgyjyYRVU+NVFQejEflmw+7BAVenpzhdHxyxNxiC0YxGE8qmJi9LptM+STBfb/AchyAKaUV/hG05m5FtMgZJzOJsTbHulyx3ymF5dkri9wuiq7IAIemamvFkig5Crk5PCP2A/RvX6ZTTdwDrmjgISJKEbLWia1pGadqnRVZVH4nv+2R1X7xJoM4zsmyD57gUeU4+mzEIApI44mKzoWoa1osFh7duguOwWq+5Oj5iOhjiOA6OoyirCun1b++GEYv1msXlJVJrXnjuOTZF3nfxABUEHJ+fExgQukMKiXQUfppQZRlZfomSClcpkuGAKstwhdt3xdr2yXHEMIpomxaAruswRuO6Hq5SKMeh7TqUkjRNTdu0eK6L7/t9IAhQFAVlUWyPCQrCKEQpRSQj/O2SZcdxkPJxF0sQbPfSPS6IHoeMwK8P3TDbOHrxJJZe/rp5sK/VF3bSpLQdMcuyrLeTLcQsy3rq7j+4x/61Q95nDOvVknyZMBAH3PimF9i/4ZHpO2S6Yn014Nln3oeIHuK5BaosMXXDYrXk7tkpKIckSRBdSFVI6rwl9EriNCUdTzAC2qZFRR3CzQiUy/UkZn52ji5KhpMxy6tZ33lKRiznBacPW5ziGjtxxGg0QmNojeHs6AhdVQjXJQ1DfN9nPB6zLgrW6zV105KLPh2xyHIGaUpX12yqCoxmd2+Pum5oqwopIElS2rYlDAPqtsEP+kjzJE4QQDwckfs+F68dMwgCurYhDEJOT47RdY3jKNbLBQ6GwXCE63vMF0tG4zHz9Yb1fM7hjZussg0ijMiyjKNHDzkcDBjFEU3dMA4DQiE42N/n4vKKazs7NHVNmeckcdynLHYdUgjOTo4ZpSl7+/vkTcvFbEaW5cT0nbvlbEbbNEwnYzw/IMsy2qbGTxLW2Qa2gRJKSGhb9gdD6rbtC7U4gk5TlyWqqhFdx3SQYqqKxSajWiwYRjHD0Yg+XV/iOIpWG5TrIhzF+dEF0+GQQZLQCUG7DUvJ12uqsmQwHPTdJSlRGALlUNcN1XZOLVuvKDdrmrpmFCcopfpiSxsc18FoQ93WKKn6VEUlEYgnqZT1dm1B1+knSYSO52IwdG2HlprxdAcnipidnZHGEUb3xxyd7R6vIAi2++T6UBjgScdLiL7Q6pkv8S/rcRH29hVMZju39rgoM8Y8SQG1LMuyvj62ELMs66kb7O1y5/iIV05OuVMWPHf993PjxjW8dIlizvKNu5yt14Tm22jMjHyxoixPGYUR0XiMLEumkylt23B6cUrAbSJ3QJy6jMcjosGQy8sL8nVGMkgRomM5qwjHcHR2xtmjI/ydHcosJ0wSzk4vyTc5y+Mpu/6A8eGQye4uGuiamny5grbBd51tWp3DeDJltVmjhKCpKpq6wnMUSkieuf0sm/UGjEE5qg+BaBrW2QalTb/YV8jtst6Oru3A75c2N7rDcxxWyyXHF+dEnocnJU4c01QVjtYESYKjHJSQxIOUsuyPwQVhSF2VVE3D9Rs36cKA9dkZQgiOHzxkfzJBd5omz3E8D0cqosBnMV/0s1qbDUIbQt/v96UZTRRGzM/PGSUJo8mEeVGwms8pNhuUMRjXo61r0iSBIEBKSbEtwnTb0VQVnpAY5aCUxPVckiTpF1a7Do7r0TQNeVmihGSYJDiOQ1PXZPMFntYkwwFqW3wJqTBS0uqOfNMf+2yqmr39fVxHMVtv2JlMiIZDXn/tdZ45OCBbr3GlREuJ73nE6YBsuUQLmE4mnF9dYeqaJI7wfB/gSejF4yOIj4sR5fQdz8edqbZt+51igDYGtH5SnHnagBJPQkBOT44p6wYlBNPJpO+gSdWHgUiB6z5+SBaABrZFkPrShVXXdei2DxjRWtO2Xf/LiTcdSXwcsiG/iqOKhjzP0dogpdjOzv36bptlWZb19bKFmGVZT90nT064v1ywTmJuHTzHc++TZIuXOXnjgqurK1QwJJtH3HhuBP4jlCmI0gFpFCE9l1IpPndyjIkPOdh9Dl8cEIUJXtD/YHzvwct4bsz1Z3fxkoyrywXjZEwl1kRJyqLreHE0pCtK1psN2eWAafh+XrgWsrMzJUgSGpXz2usvU14apkmC7/mEgY8fhESBjwxDlNacPHyAB+zt7DKeTlnM+g5bWZZgDL7vow0s53OE0Wgh8cKwX2osJWx/yM5WK7zAp2hbdKdxlGRvNEI+7sBIhRsn1FXVzwmFLoNgAEqim5a2LFmtVuzt7bK3t4d/uMPLr/4K2jgIY7hx4wZlUaCUZDIY07YtXdf/0F5VFet1PzcnHUFRloRh2C+FVorA94i2S6vXmw3r+YIoDIijuL9v4BNHIW2nEcaQpAmb9YZGl5iuw3Od7bE7l/F4zHK1om0aDIb5ckVVlkxGo7571HUYrZFKkaZpXxBiSNIBQgiU67LMNgC4vocRguF4xNn5OV7gE49HGNflwd277A0G5HVFh8H3PEZxQl1XbIqCZZ6xMxqxWK3IVkt2RmNgG5RiDFp3T9YICMSbijLP82ja5smiZ1cqMAZHKZqupWs7XPX5Qjsdpfi+v53/6wu8x0WY4zq4jrN9358vcPr9XQKjuydfI49p03cP27ZDSoFSqo+VVw5BoN5UbPW76JonxZNSDr7v8RsdW3ycGhlF4Ztub+q6n220LMuyvm62ELMs66mTQnDz5k1ax2UynRA3FR9/9JDzXJD4HyD0Y9J9xWhfM1t2SAm3hgN2gpBuueCzjx4xOrxGhSGv7uLGJYvSpV7VZOuWZ268n+FuS979MmZTcrY840byIqvFiquzFaPdG6yuZtRNw7quufnsM2zODcPJhMHhkJK7vP7yHZr1Di+8cLPfweW5tE1LVRb4YcjnXvtcvz+q63j29m00cHF5SRgELJZL2q6F1mVxDkGUEQR9EaK1pms7hBQIBJ3uCw9HSpQxNFlOEEcY3e968lwXoSSbLOvDIpSDoyRVliMcl/n5FeN0QBjH7O7tEownLNqKz/7av6E4FVwbj6nrms1yhe+5ROmAqqn7fVxJQlGVaAyu289bAaA1bV0jdN/h0cBquUBvjw8mcQTaoLsOug4jBKvVCiEkXdvi1x7r9Zokip+ETkgp8YOQy8WCs+PjJyEojhSM9/eo6pqqqAiDALYhE1VVkqYpcTqg1ZrlfI5REiMkruPghwGL1YpuvabpOoSUiDjh5Vdf5fnDA8q8oNpkGAG66yhlR1U30LYEUuEqh3y1YncywdsGXIRhQNt21I3paxXTz0o9/hy6tqMsy77T6XkM4xiEYL1aUZUFwrCNjY9xXRc/8ImjGGP6IlNs/3uc0ug6DmEQYOiLv75r9fk9X0L2HVfh9OsRmrqm6zo8z8VxoG07tG6RsiMIgidvp7VmtVrhbTuQj2mtn+wD+3IeJ0j2CY3qydvWTUMYhl/2bS3LsqyvjC3ELMt66l7c3aF1PWoM9954g0d1zTLLMe0O02spbjRHKp8g0MRZyyAZUs5mHGnD4XjMB156iXlR8sZ6TasUm3XFaCJJBgnGZJTNjPm9GfFA0uqCGwcHnDx6ldHuNQ4O9ui6mqKUDFyPqK5YzgwvfEtCMlzS8jqf+NVfpbi4wSBUrJucxXpNPZ8zGaQkwxH3790j8jwCP8B1FF4UcXJ8QpqmVGWJQPErP/9t/I//nxFNrXDclt/7Xyz4vj98TN3lfbEhJUVVka83DIfDPordaNIk7ndWKYVA0HYtddkiDCgh2Ts8wPhB39lZrtjf28dJYmrPY5XnPDq/w4M3Log7wdBxaKsKuo5hkhDHMXXbooXECME622CAbJNhdEeaJIRx3Hd3HIflYo7p+iNywkDZVX03UErUdsFvmiY4Sm07OH3hYDqNOxrhuR4G0//gLhVXsxllnvcFYRgSRBGzq0vm8zlhEDIcDul0n0IYBz5REuN6fZfw8uyMwPeJ4oSyyCmahvlqSVc3JLduIeqaq/mC5b37XJ9OkUnC6cNHJFLiCMG6XaG7ljhJWeU5sVJkmzW+6yIB13WRUiCkQjkCTwow/RFEIQTa9KmF0n1coGi6rqUoS66WC64uLhFdR5rEDNIBvu8znUzwff9J9xFj8N1+bkzK/siq73lPdnw9Pvr367tVUiqMgrrqF0orpXCUoqrrbZEV8LhifDxX9vh9GaNRynnTbXVdsckyxsPRk9UEX4pSCqM1TdfH2EsptkXYl5pRsyzLsr4athCzLOupu72zR1EWfPzuXdLphDbLaDYZo1FKWeVkzZJxEHDv7FH/Bk3LS9cOuTUYsDw6pssLivkM07RkncOLzz9LFHWcnh8Tp0Mmuy5tlzDeVRRXHZ9+/Q6H117AcyqWp0cEccJBmuIqhXBdYlkwHV2SzRd88nOvMj89YEyKr1pO7z6iWq9JwxDTadbLJbHn4vsendaMx2PeeO110jShKAvapuXf/nfP8v/77yY8/oG6bRz+5T+asslzvvcPrVguznBdl+VqxcF02k8EdS1NVZOmKdJx+qN7WveLhpXEcV0WiyVXl5fUne67ZKs1bZ7RnBnWVY1pGnTXMkCwOxnTaU0YhHiBT920tFqzXq/6VMS672wEQcDe7g5eEKKbhlZAC8zOLxBty2QyYblY4CrVB5B0/Q6rpmmJwgClHLqufRKZXlUVBoO/PbYXhgFaSO4/eICrJGmSIEXfZVrMZzRNyyBJSdKE1XqNMBCGEUVdE7ou6yzj/OqKvZ2d/u2EYJ0XfaeubYiDgKvTE8rVmjRNSaSkKQrufOIT7IwndFVF4HvUdUMcJ2R5TiDA9zzatiFNEpSj8H0fZN+lWq03feqh56GUpCorwsAniGJ017FYLvvkxrJidXHJerWibVsGgwFJnKCUJI4ilJIopXBdh6IoAAfpuQgh+11ljvNlFy1rranrapvQ2O83a9sOx3GIougLUg3Fm2a3lFKMx2OKouzXD7QtnTGss4zZ1Yyqqrl+7ZAvdUTRmL7c0vQFXVM3OK6LlLKfhbMsy7K+brYQsyzrqTs9OyXbZFzf2+XReoOQig++8DyfOzlF1IdEacKmLRhNpuyPR1wPQoKq4vL1O1xs1tTa8ODsHLW/z3e8/wX2Yp/FyTFT12PvuYjQLahbzQDFv73/gL29PZQqWWUFw/GYriio8ozD8Zh8s+HR7IrF7IpPvHZB2H0LQxUTSgF1TaA148kEKfpuj5ISJSW+5xNEEccnJ5i2hU6TlxW0Dr/wzw/44h9wBf/h567znd//GsK0uErx/LPPUJUVVVODMQRBgHIUWZ7jOE6/L0spjICyrFBSELguSeTRCtBVzWgwQDku06ZBuX2BWDQNjpBURYHj++RZhhCCTmtGwyFV3ScFRmlKlue0ut8xls/nRFFE1XWEgY8jQo5PT/BdlygMkNuul9p2c4wBx3XRxiCkxPd9OqMRhn52ynORymGTbRimSd/VU4ogDPodW65L4Ac4SmHoP8ckivpADMD1fC5mc/Z3d9BKkeUFkZAEYcjs7JTID6jLAt1pkih6sndts94wDkKU7lCug0QQBQFd1xEFwXYGTOMHAUYbPN/vPwckVdexWi4ZDgd4QcBquSTwPLwwYp3nKCVZrddMxiOKIieNI0Lfw2hNHMeMx2OUVAyHwzcdEwTedETw19/e64ubpqm3+8AkRZH3i6E7vd0x14dtPC54f/1RxLfWH21dbjYsZjPiJOHiasZkOGR/b/ctvka3V2IMiL4jqI2h7Toc2RePnWFbVFqWZVlfL1uIWZb11KWjIa7nMhwM2I9j7i2WvHJ6SqoUwVTy3MEOYyW5urzErDecLxa4TcvucMC+7/FgueKlb/4gH3z2Ns16TST6H9q/eX8fpyq5nM14MJvx6sUll03NIE3ojMFVis1yyc5wRJtn/Nrrr/Pw/IJlF0FxwLPpt3G4s0NTVuTZhjrP2d3dxXQdzjbOXEmBHwQs8hxnG1rgOg5d06C6ltmFQ1u/9fxNUymqPOHgRowChHLA1TR1hQCkkhhtSJOYLC9o2xYlBa7nk+cFSRTjOE4f2b79IT6MIvKmYZ3nBEFA07VcrTd4UjBMUlzXpe46kiikqRuM59I0LY0xHJ2csLd/wHqxoCkLHEfRtS2OEFxeXGKamr2dXdI0pW5qmqbF2SZHxknKYrmkKHLC8PPdH4SgMxqDwfN8lOMwGo+pqppsvaZpG0xhCKO479K0DWxnzHzfJx0N6TqN4/scHx1RFAWe65KXBXE64PzigrZt0XXNYG+PxWxOsD0213UdTdMwGgy2UfItUinCIKTTfSevrmu6psUPfDy3LxSDOGa12eD7HsvZnMFoRJFneGGIF4Z0bUteVxitycqCKIr6ObFtYdppTRxGHOzvk6bpkyOCfY0kEKIvXLvtnrHHRwl/fSS8kNvZMPrY/T6iv99N1odrQFGUKKUIw4CvtCklpKBrWobDEXEUslqvicLwTTNi3fbrWCnVH2nsr+rzhWSnaQHalizLWSyXwHNf2QVYlmVZX5ItxCzLeup8x6HsBA/uP2KdrXmjyFn7AdPJkKarOH9wn9MsJ/Bcbu0fUGcNxnXZlBWxgBfHI8aTKVMhuGhqlABXKdzFnOVqxSv3H/BrqyXJzg6jyQRhDFm2YTAcEQf+dmZJoIOAnTTFOU7xg5s899LzFOYeR6+WzI+O2ElT6rJkZ28XIRXLxQIhJXlZIpqG5XyGhH7XlucSuB6H11xcX9NU8os+b9drcdwFVekRJwnHpyf9HFKniaIQow1N21DVFbrrY+zrpsZUJYHn9T+4C4FWitlijud75EWJUIog8PvjkVnOJI4xAvw04ejoGNG1FBiidEC+XhNHIV1dQ6fZrFZkywWOcmiqilL33Y/E99m7cZ2m6YsZZRzCsO86JcMRx6cnLGYz3v++b0ILqJoWN4oYJgl101AsV6R7e9QCqrygM4ZkMiFbrVBSsFqvKfIMJURf/CmH8XTK5eUVruexKQp8r499R2u6smRV1SznM8bpgCRJKTcbAs/F93yapiZJUuq6xvc9hBC0rWI4GlE2NVIr5qsVkVR4QUAcx6w3G3zlILYzV8L3KKsKL00py4rrgyH1Yk7XteRZThRHrK8u8aQiThIwBqMNk9GYQZqSpilfeETwscdHN/su2Jvv0zT1k31dbdsRRRGPI+ddty+YhJBEYdjP4D1Z5Pwb/1uTUrEznQKPgzckqyxDOQ5JHNO2/S61fgZM9t1CDMIIhOq/3sqyxBhNVTc0bUPdNF/lv3jLsizrrdhCzLKsp+7hw0cUukNLydxxGO3vEzh9WEKuNfFoxP4zz0BVoYxhMpngGs10MGAkFU1eUW0azrI18/kCN1CkgwQaw6v37/OgLLn5wguMk4Q7jx7hpSnPP/cckzhhaDRtXpCORhyfnXN6dkYQp9y6lqKGn+Fzv/rLrB/e5MZ0ymg0Js82LFcr5rMZXd0wmYwpioLRcEjbtNRFwWg4oiwLXFehTc3v+N77/MK/eJY3H/0yfPC7XiXwNHEYcnl2jhQwmUz6TpOU/XJf6dA2fXS4oQ/NeHwU0PE8PN/j3vkFoq4QjkvT1GSrgjCKOb24ZLIzJVuuSKKQB2/cRbctSini8Zirq0uUkAy8IWXVp++Vmw2+lH10vbfdCZamfXy9NoRRhNwmFDquS1GULLINynF57sWX0HHM8fkZk51dCu8cN2jQzZzOHGB2C4ryPsI7xBE1R3czqqxg4nrEUYTsB5/QrkZKwWI+QwpBXvSLrYssIwoD6rJEAp6URLt7eK6Ls30qi6IvFPEwjqLOGsKoX2A9SBOE6zKbz9jf26NdLpGOQxAEZGWJHwZEwxFV2xLv7LCcz3DDgNPzc67v7nJ+dsrVYkns9kVUsV6zO5n2RUlR4LoeURwxHAz6mcG2+7IBGG+e6eo93u/VdS1CQBSFT+7numB0fzzQ6A6DAc2TZMXHaw2+MoairPCiiMuz8z75EqiqmjAM33zE0dCnOHZ98mLddazXa9Capm2I0vQr/JiWZVnWl2MLMcuynrpOdyAVWkl2d6ZIqRhNJtw5OuLWtUNk1xEZ0G3Lar5AjUeMghAny1gUDZtVyWKxQDmKNE3I84LZ5Yq6KRgMR7z/2RF11/Hq/fuYOOaZ69fZEYLNo0dclAWe53NeFqzLkkGSkslzNm3N+WdOmR8NORwOufHCC7z6mc/gdLovTDwP5QeYTpOEEW3bkeUZuzu72yNvFeV2/9b3/+FHOErxiz97naZWuF7L7/jQff5nP/iQ6c4Ow/EIgDiOOT87x3ddNPTR6myTB7dtD0c5OIFPJwTnizmBEFAU/UyW65KkaX+sTUqm4zGX5+fkm4xy46ObhtD3iaKQfJMxHU9YbzYsZnOE6OfNlsslw+GQvMgZj8e425kv1/PJiwJfKRabDdeuXaNT/ccpsoz9l24howvu3fs4N55/AcJXOL845SAcIasFo+caUiUJqVirlzmdzdBqj9H4OjuDAXmek89njAcD1qsVSiqiIEQbjQfotkEpSdu0mK4jCkLMdo7Oc13i4ZB79+4S+z5KKcq6QhcapSROENCuVySjEQwGyKJg3jSsipLY93HCAC0EQRSxamoeHZ+wvrwgVg6T8QhXgOO5lHnL/nRCUZbIuiGMY7qu7WfjHJd0kDIeDvtZtyCg6/Sbvs617qiqerus2XtTIWaMoSj6hcnGaLTezgOaGt/3+46ZkBih++h7ozG675o1TYmh/7OQtLiu0x+VVArP87/E3Fg/W9ZVNc898wyD9PPzak+i8gVPOnNIQVkWlHmBFoLL+Yy96Q7TW7c4Pz97u74VWJZlvafZQsyyrKdumI7xPIe2azgrCsbjMQ9ee41lUyM9l66qGAUBVVEwimNoGmZFAU2DbDvQEEY+y9WCMPLIizVIzaYsOS0K2qrkaL3hrKmJqgmfyc9ZrE9o6g5JTNsuGQ6mrPNL2mzMNH2R5dmaopoydA/YOzjkc597jWqzYTCe4DoKJUUfMLFNvmvqhsloDEpxcXWFMholZH+k0PP47j94h9/23Z+hrQaMpxrPN3Sdj1KS8/ML6rbFC8O+iFL97JKjJG3b9juctHlyVKzMMqq6ocsziGMcKbl+/TrS/f+z9+fR1mVpXSb6zLnmXP1uT/918UVE9gmCokLSigKaUiqgiCKFYlOoo8pSB14dQ0c5dEjdxiEl994a5S0FZVgmhUIp5S2LolTMBBKKLiHb6L/29Gf3e/VrzXn/mPs7kUkGXMwMojRzP/9EfOfbsc86Z6+9Yr37fd/n5/Po+DG9JGGdZdjVmiLLUFK4wtG6IrKua0ajEcv1itVyye7OGCnc9zo82EcpRRRHaK3Rvk9VN0itGCS7VFXJwc2b2CTGC+ckwSWHQcZQXvHg/n36PcnhboqdLclMxZ7n8dLVJWkU0ZOSx2dn3Lu8YFY3VCXkNqGsK9bTKYmQSO1TNw07Q1cYCCNQWpFnOaEf4EmJ8X3sRqnvhwHrLGfy6BHSuoBiz5PEvR6r+YKd8ZjVaoXneRR1zeTxY44fP+apmzeJ0hQdJ6y7jqxpMALuf+x5IuDtTz9NZ4G2pSkr1ssVTV1Ts+k8eRLpeVgLXdOQ9lLiILze5XJ+i1cLIGM6iqIgDEIAurZF+ponXdK6rlBKUdfNRp2/EaFsdPOGzUMFlFV1fV4Ya2nalsvJhH4vJfQDAt8nityxtG2L1voT3m9u5LEliWN6v0wYopTa5IrJjSnR7a/ZzdhlZw110xEqje9rHr38MhcXF8BveV2vCVu2bNny2ci2ENuyZcsbzjRfUc1rGmvptMIsllRS8Js/7/OZTac8XmfkoSBMUo72dkkRPDo5xotjelFEmWXURclof8R4NKTpKn7i3iuctR0lMFk0UO9jlmP2Dg4IwyGzkx6jMCTupWTVGrUI8Nsb9Pop6WjE1eSKqEroHxxw//49dNvSixPSXkpd107f7Xl4yqMsStI0oWlbqiLHtA11VdFLU4QQ5Ks10vNIez4iLdC+xpOKtm2pipL1asV4Z4flcoWBjZLco9so059MNDpNfIOQgjDwCXxNkiSEUcwyW7M+v6CtSnpHN5hMZ/TiGJWmaE+hlCKNY6R2hcrF5QXWwng0Igrd+JvBdUE6oCxKkrRHB8jAxypFLgW1gp0Dg+5/iLAo2UkT3qETPvLcc7x9d5ej0RhfCF5YrXg6ihm0LYe9HmNf83Mf/jBniyWzriPynuWpW28hCBXnz6/pByG2bcmWS9IkwQ8DmsblcpmyJAxcXpkTcNRY40x+66sJSikU4Ich2veRnmK1mBMnMX4UkWhFmWWsZnOqsuT27p7bq2pbpmVBdjLl5uEhr7zwAl7Xkvb65GVFWRTEcQRCoDyJisLrAqmua8xGBjLo99Fa4ylF4PtI6SHEq11MgLIsCcPICUzAjWHiRhGttZvHg1IeQRBuIgAUxmz+DhDSA2upmobJ1RWj4ZDaGubzOV3d0FRul9CTkqqq8LXvjJP2VdGGtZY8z1DKxQxo7V8fE0AQ+K9+z483gFho25YwCJjOzkl6PYhi8ocPuXuw/+txWdiyZcuWzzq2hdiWLVvecPpRyM1nn2W2mDMvK6zy6Pf7mOmEfLlkfzRi1O+T5xmTyZRVXSOMxTQN67ZFIugNB3ieR1O3fODhQ+6XFVfWQyw+j8N0yDpfMRymDEcjXvzYi+wmCZ7yUG1LLD20FOgkZrCzw/HFObPLK0ZRxPzkGN22JFGErxS262jrGt/3adsW2xl8reg64/bClEZLSdLvo5WmaRtXKHgeYRRhhUAIWK9WFIV7fOBrfK2pqoqsLKg22VxpmuJJ13npTIcxLmsKwFhD13WucxaGBKMRk8tL+mnK9OKCfhzjK4XBopSm61ra1uIJwXqdEYXhRoXuDHlKKZru1e+R9Ho0bYMXJ1itaDB4wZqbTxtuDY55W9CjF0RYA688f8xRskezbnnlxQ9R1hleP2bFmnvn52TLBQ+vrjheLDDxHr/57c+iPEMgF3zk+ReIDz8fvY6QdQNtizGGtusoypIgDNB+wHI6cWp5ra6LB7NRxDdNQxLHNF3nRvXahp2dHfIsRycJtRC0UtJOpjz71rdwuVxxfnqC7gwyzxmkKRfHx+yFEbrXw/dcp61YrcjmC45u3MDTisvzC9IkcQVx3WCsQStFvNmvUsoV5k+KtY/viAkhNn9+tbjpjMWY7lpHbzf7YW3b4nnyWsLRdi1FUWKFU8VPZ3PaxokyrpYrl/fWtswXS+I4IgoCBoMBrxW0XNc1Wmt8P3DP3TZYKz/uWF8Vh9jNaGLd1JRlSVPX5GVJL02IxmNeevkVtHw1vHvLli1btnx6bAuxLVu2vOFIBCePT7haL3j6mWfJV0uWVUmgNeMopp8mDIVg6imS8Q6r+RyamlBp0jBC4LGYr8CXvHj/ZT62XnO86pM0b+Wol+Ih2D06IogiLs4v2I1jkjjiSatJ+q4QUUpzcvyYKss4GAwINmp3H0EYupGytusA4XaVTIeRkPZ7LBdLkjAiy3PspqPQmQ5PekjhgoGDKGQ+X5Ct12CdXa9rW6IwoigKVsslgVIIpUmiiG6jMW+a5rrw8KS32QtyI2xN09ACz334Ixz1nVSjrmpgk/9k7ebm2/18VkAQBMRx7Mb6VmvCKMQPQqrFgrTfo+0MnTHEvZS8aWnaEhnOiMcrDpXHrUKwfDzhwUVBmXVIIXm0ukL6LftHY46SQ4JQM1xN6eoaNRySNTVP37jJmw8P6Ps++XTKz738CmWRU9iPYrO3oLOScRQ5i+J84X4G03FxfkEahoRheF2IhnEEQL7OCAKX4XZ5esLB7i7RphO4KiuyPGeG5cHLr/DUeMzp+QWtMShg9+iIrMjxqppkf5/p5SW2awn7A05OThkkCQdHhwhPcXV5QRS7gmuZrVGehzTiWp7y5Pzp2g6hN+r5jyvEwjDa7H4BWOaLJVmWEUXRJxRvUmyKJ+shPBfa/PjkdBNcnROHAaPxmOlyQdW2BJ5HXtcM0hStPEzXIXhS9P2yrhauA+d/XGi064yZT+iKuQJOIBDUVU1VVjR1zWQ2c+OgcczDBw9os4zxeLxR8G/ZsmXLlk+XbSG2ZcuWN5zlckkYhhwdHFCvVkyvJqS7O4SeIkp9AgtFXhILj/piTigtcTqg7RrKsqZrYDFbcXL1gF/K1py1PknxLLdGPXytMdbgac3p+RnKWsIwoGu7zRiWcXsw1pKtVwRC4scxAuiaFtO68UCJcKHFAqqiwPOU+7r0aJuW4WjIxfk5woLWCjZhxaZrAbcrNp/NyNYZnelI4+S6G2W6jqqpGQ76bjbQWOquvc6lejKS+CSw98mukR8EdG3L8vyC2ztjPOFyx+Rmt0wgCMLAjdYpBULSdB1+EFBVJXXb4oUBjbVkywVN25AIiZWgfR+hfZIkxTM5JBf4umO5Lphpxe1hhG08TpZzLqYTVosFQhjmsyVSt6jAImKfVmu+4PN+A6Jp8XyfUGsGyuNnT8+YzGeU2R3qVQ+5uuBwMNgUJBbt+3Rti2k7xsMBoR+gPI+2bfGjEB0EnJycEvk+0SZnrb/R1Vvpka/XrJYrhJScPnzIQCuCIMBKyezqkl4Uc3b8GGGBriNOYqIoch0eKfClZLy7w+nFJUZKqjxn0O/RtC39fp8syyiqCoqC0WBwXdworT9hFPCXY3FdqbIqKaoKA3RdS9c0Lvx5sxOGFHhGsFyvscZQS+l+H4Qsi5zCGNZZzmI2ZZz2qNoGKSXaU66D2rV4nvqk41BPCvrrwus1jvNJh8taGmuZ5hnFYoG1EAQek4tLtDGMB32klNfF8ZYtW7Zs+fTYXk23bNnyhjMYDIh7KV3TUnUtTz11h8V8jtE+fmswQhJHPbAe88sLoiji8eUFB0d7KCkx1MxXl5wDKynRcsztWzeRdY0xTpZRFzmJH6A8iWk7hCcRQtI0Nb5WWMBXGqyl65wYQyoPjEHgiipPeazXGWojKgBB2zYEYcjkakKe5ezt7NBt1OJd22K6DiMNoQoJfZ+mqlEqxPcDTNdhASkESZKgtGY2X+ArD600Qgjqur6+mY6jiLws8AOfKE1ZL5YsV0v2dndd4HPXEgSBG3nUerMfBJ5SzJdLwiCgbhriJHFdIWlYzhdY6wqfKEloBHRKoXs9TCBQfk0vLBn1BYf0uHuYEhWG+VWOrQXGCl564Xn2Dgf0hzG9UYQfC8Y3jhj2+4RhSKR9ymXJ1fkFh7dvcnb/IWfn55i2ZTjsI/U+RX2Gp1xItvKky9eyliRJaLvWdejSBLsp6B4dH3Owt09R5GRZhhECoTzapiEUgkBKegf7nF1NiITgYGeXtqmp1mt2khQ/SVhOJwx6fZqqwvcUyyxDxwnZYkng+0zOL8jyHKk8+v2Bey0tHB8fE8cxVVkwGg5Z55uunO//siLHSTrKqqaqKzzpUdcV63UGm9e9yHM3Aio9yrIiCN0+mAVa2eF5HlJ5XFxdkfgBfhRyfH7Bej4jjWK8usHUlXu9sSRxTBi6fTpnPfzEzpzSmrZpPqFY/PiRyVczyQQWy9nZGau6JlAK2zSYzhBtnt8ZIOUnyUC2bNmyZcunxrYQ27JlyxuONYJskTEc9vG9gPViSZwkjHp9lOeTLTouj1e0bUNTelycnKMC2Bl6TK8WrNZzdBDyubeOsIs5iYlQNawftCSb0SutPLRSmM3+lZSStqnxlXLGwK4FQGuNwBViWOuMiE3rOkzCdRSEEFRVje06tK/Js4w8WzMeDelMt9nBcUVXY83191ut1yjloZTefP8G6XnEaYJUirppabvOhSDXNZ7nRt6cDr/GAlEYscrWTKYzZNcxHo5o25au6wgDn7wsXchyv4fnKSyW84sLwiAgCEP6wyHKDygvLvCUJk1c12QwHqF7PURf0YoJQj9E6IJA1ti2Y5+EdwYh85OMs/M1dWnx45i8qrh79ynCRCGVBSM42D0gCUJCIZk8vCJJYkwnyRYtL85f4eLqMcu2ZVqU3D0sObl6QCwCPCF4kmsscMr0JwVMlEQopSm7juXCFZ+tMfR3dlnNZyghiXsp89kMoRSTi3N8pSlWK0bDIdaTjAZDsrIkW6+pZzPoDGkUsagqzEa6UTftZi/PFYOjQR9rrAu+7qXMpjOktbRVRRxFaKWpKrdDNRwN6ermusDpjKGsSlarFVXduKKsLPF9H601+SoHIO33sQLmyyVJ1xIGIfPFnDzL6fVdoZj6AcPRiKquUcYw6vWpypKd4cD9vgTEcUKaJkRRfK3A/+Vh0kIItO9GKM3GPPmqyGNTjj1R1uPO9/07t3nw0kvIukZ76tUPB4zFk5KyrH59LxBbtmzZ8lnCthDbsmXLG858MeXw8AiB4uTRKbfuHKG1T5lZsBXTy4yTR1OU51FUFWmSIBB87IP3uP/wZdKBz1ve+TQs1uh1xrq45PS4YKfbxU9SfKXoOuFG24wLC/74LkHbNHjKFS11VaK1ZrCz63aGrEXiCgNrDF3ToH2NsJY4STCbUNt+2nOdEGPdzXldY41hNBo50QLuZlkKiRSCZlOEAWTrDBWFTGcz8tWScb9/3bHQWiM8SV5VFGWBQLBerem6liRO6KwhjmOazlCWJf1+nzDeBWC5XpFnOYPhiLTXIy8KVnnO4uycOArprOveJGlK2Ovj7QlE7zluCEiBsQ7ZIeDB5SUDITg/nvLSx06YTZY0jaE1Bj8I2D+6yWI6ZXd3TJxEXJ3M6HY9/P2YXjpkvSzIs4yXX7qH9Woa3ZF3HeP9G7RlgFlYenFE4AfXtsAnVko/8DGdQWlNZQzT2Zz93R2sp9DA1WKB7wc0XcfVbM5quSSME3qDIf1eSt02+FrR1jVFVZFXJRfHx9w4OmLQ72E3RXcSxyxXK6qyIAwClNTYzZhi1VQoKVBCkmwsnVEQ0pmOrmupyoosWyMQeL7b28vznK5tyYqSxWLhulMb02OWZcRRTBTHTorStdx/8JDdQZ+m7WjbjDCOoayQnkcQRvhhhPB9ylWJCALy2YxeFFHXDYGvCf3AmTSDcGM8fHVP7JMReEpRZmusNWjtuzPcGgxOU/+kQ7YzHnP/asJqtWaglOsgK2eIrOrKjd/++l0atmzZsuWzim0htmXLljecp+8+S6BDVquMW7du02SwzAvatnWdo1rSGw5o244gTZlOpzz/0Y+i/Jak77N/c8jV9JQFHY/ajkU+om/22d3ssEjYjAi6LpcnlSuwhNu7CcOQun7yqb7AGEtRFqzznDjwN90RixSWXr9HnuVu9wqoqgpPOhOi7QxBENDv9/F8nxeefx7f98mLgjSO8bWPkNLdvFYV1tprecJyOmM1nbK/t7fpvrkb6SzPwEISRWRZRq/XY293l/V6TRjHSM9jledMZ1Oeun2HpmupmoaryYTA99nb20Mqjw6YrVeYqub2nTus12uEJ10nTvvUcUscvcgzeLxF+awmay4vTpg3HcrTLC9PyNYNVV3x1N07TK7m7B0c4mmfsqoQSrMuKs4uTpleXHB4a4RpFIuZG5+sqgohYe9wxHOrBWF/h2cGQ37m5x8jqx0apShF6fKvgDiOaBu35+aHAVVn6KwbvfSU5vzqin4vZXl1RW84YLVcIo2hqxsm52esVmuulHJjhwi6rnNjmF3HOE2xtZO9LKYzwjDYGC8VMooIgwBrQUpBXVUE2kf4grapsV3rLIkCAj9AeYowhCAIsVhMZ1gsFiyWy+tAZ38zJurOLkHbdQjPIy8LkkGf5TJjNBzQHwwpiwKEIIhjhoFPqzRFWeAZy/Gjh0gEtutgUwT20pReLyWOE8IwwhjjCjApqMpyk6v2qgwEnLDDmI44Tliv16jNGKyUgq5uaa1xHTNj8IQg6Tr2kgQlBWEQvtotU4rBeMRsI1bZsmXLli2fHttCbMuWLW84ddnSFg3ShFS5oO0kyu9TlCuWiznT6YTjR48Ag5AS0xqkarj59BiZKk4pub9a0CUJrTW0XU0gheuuyI1EQXlI8WpgrTEGudFzl2UBgBASYS2+UpsuWkvbCJSn0L4mjmLKsnRBzkGwyWHSSNzujTGGum24uLrCCoEnBKZ1N+51VaO0vlbO682/K62ZLxd0Tcve7g79fo917kbW2q5FeW408Uk3DCCKIqrW7U3NlkuEtdy8cdMVYFdXRHHMerVi96k7dNZQ1oaLkxNMVbN/eMAr9+9BZ0j6PXaPjogPYpbN85y//DIkMUIpivMFTdNwsHuDD3/4YyRpyN07b6LOLJPJksViyXS+4PLyEtO2SM+jyNeEYUjT1LRyzWR2gfYVvg4xuMyt9SpjkKT0BkN+7KMfpZq+kx1ricOQJE3QnqKzFoTby7NSULctdB2ddUXN45NjpLHMm5oo8Mnmc5IoYjGbu7HOsmSYpkgB8c74OmC5bRrSXs8Vz8qj2nQQ26a5jhrQ2kdpTd24372xJToIaJoagSBNezRNTegH7rVsaqSQhGEAFlfAZ9lGb+/EME3T0DQtaa+HDkMWsxnWWtI0xUpJf2eXy7Mzsk1Q897hIcs84/Jqgt/rkVcl+WyG37bsj8fUTcPV2RlyJBiPRuyMx04k80S4aAxCeLRtt8kme/V/7VXlPnDoupYoUiRJ/HFFmgAhaKuatu1ACnzf587NG9y5fYvlcomwMF8s6EyHr3zqztDYbU9sy5YtW14PtoXYli1b3nishE4xucwYDEdE/YTj4xM+9Iu/QLacoHzBYD8kTfuEYURdGharCcOdhA/MF1wqj1Oj0bM9mkrhFT3iyMP3AxdQ3Blsa5C+60Y96WIZYzc36dblNhmDp3yklCymU/Z3dynWGYHWKN/HCOhMRxgENGWB8n2yPKO/Gftj0+EKggCk4O6zz3B2eka0yQITQlzndAnhyqrZbIZWit5g4MbFyupa1NFt9tme2BURruCbTKcUZUnT1PR7feJ+n4ePHlGXBVEQEmjNoN+jblpmFxc0tTPy2TAkX62Itc/wYIwIfGSS0AYvML96gTfdvcudMOAQwUtnl4x3B9RdifYFcRoymUyZzmZMriZkRUaShjzz5kMOdm9ycTYhbyck/YC6KRGeoRGC3eGArrRMphPCRHC/LpgWKx48fMhi9iz9tmM4HLrwZe1f56UBRJGLDJBao32frChI4pi6aWjLgv2bN8kWS3zfxzQtSgq3C5imBEGA8CRREBLGERdXE9I0wY8jjPKYnLu9ubquiTbRBNZYesMebdchcZldUZxQFsVGZumy6wI/oDUdfuBTrdeEgcLz3Njear2mKApn5QwD6qrGWEscRxRVyflsRlUW9NOU9XTC3STl/ssvkqQhM1b04x0aAauiwBcCWVVU8wVJHDMKw82HCBatNYEf4PsuU83zFMZarDVunLIsCXwf/XGqegDPkyilAdfRFcLjyRhi27bXhZqUzrQpNyO86/Watu0QUlI2DaZpiJOYLM+Je/1fv2vDli1btnwWsS3EtmzZ8oYjjGI2m5PlLY/Pzlkul5RFSbVeceuZHYJEEISauJeihcTXCatlRDSKeevBIeXlBao3hOIm9WVHFEp293bJsxzb1HRtSxxFxGnKcrnYZD9tNOlas15nhGFIVRYuFLptwFqKPGd3f4/lYkFVlNRNg2lblNZEUYQQgjAIXKaVENRViSc9fN+nqkpOT07xPQ9jrRtP09p1KzYq8nWW4W+ey+I6GU/EHEiBlh5sunZOHgJXVxPW6zVxFBFFEUprzk6OaYqcNI7ZGe/Qmo4ojOiamjiMCIdDOmvJshylFMPhED/wQfuouGSZnXG0u8sz/R43heDkuedZmZa33zjiYx9+iY6S3uCA2WSJDCsO7vQ4OHgTh/s3KdeGbN0xXz5kf3+P4TjGTw0vrJZMjeFBnkNVU8oW00leXi1ZVhF2/XZ2bMzOKGXQ7wFgN/tJ1hrSNCXt9bmcXEHbsq5qZpMr3vK2t1GWJb045vjhQ8osw5OSQa/HjYNDp73fKPqzqnLdxSCgMQY/Tak6w3S1oqhKJ24RgLW0XUccx3hKYTzJ+eMLbh8dUmx2ywb9PnVVEScxTdvRGcvJySk7Ozu0XUeWZ0hPspjNXfac77tdKymJgsAp5aucUb9P1++RLZeMR2NOT4/5oPgh3vf4+2lsiRYh79r5I3zZ+E8hoxCqmkjA7nCIH4RcTaeEYUCv3yeKIqSnuJrNONw/QEoXAm2t65q+Fq4IexW7Kd7qur4exxRCX3fRLFDVFXYTli2UQoUhJvBpmpZsndHOZsA7f70uD1u2bNnyWcO2ENuyZcsbzuRyhVY+wtZkiwWB59GYjjDxUZ7m8HCH++sF06ahrGsSv6KtCwaLljSKeCqOeVQseFzOUPJzGIUh08WC9WxGP042YcaKqm0oqwotPXQYUDUtVVXT1jUkCVJryqpEb6yGgaeouo6qafGMIQoCRBQ5cUfXYaVEeZIwCDk7v+Dm4SFNXVPXbrQrDHx8P0BpjVAei9WKfLlCK4XnSXxfb2JzLca6josvJdYaFIrOGHytIfAo8oxsvaaf9hj0ewSB64Y0TUtTO+Nfv9dH+T62rqmbBk95KC3czbfp6A/6+FoTpwneaIQ/Luj4CDsLQ9DUjLuO7OyC48WcZG+PR5eXhH2f3/qm30wYRjx1x6PMa4SQXJxPOTm+oFi1TKdL1ssFuztjnvvQQ5568y5fcPc2D+YTXlSahRScnq1Yr0qK7K2osk9cVxzsD0nihKauNrp1gZSuuxNvdgHX6/V1TpvU8Isvvp92ZqEZEQUBR0/ddblsSUrV1EitqbKMwJPoOGI1r10WXK/H5WzOycMHxGFEWS6Z65xbw6foTOeKc61pu5bFcoXCBWGfn5xyMB4jhGDv8JD1es1qNScMAm7durnpItU0dY01m4w6a2ma2nVbEcwWczCumG5Nx2h/n4f3H8DA8FP1e/g3s394/V5obMn7rr6Hpih4V/StRL0UqTX5ak1eVuSrFY0xBIFPEPgg2ISLGxe3gMSa7lfNMvvlVFWN3dg9hZB4nrruFHfG7YtleUHddTRlwapuWE0m7CQJ4eZxW7Zs2bLl02dbiG3ZsuUNJ/IHLLM1q3VGmqbXivj56pzW1EwnM9Jxn/tFzocvrxC+K5SiouAZtcdH79/ndLrHjnozYSqYr9dEWMZ9NzJlOoPF0lQ1crObUxYFpmkJwpAw8J0AAYEXhNRFgSclVVNS5Dk68Ek2kg6tNVWeufHBTQG1mM+JoxBPKc4uLwi1T6C1yymra8A9psgzIj9w3beqciHA1uIpjWmcJRAgDCPapqGzhrzI6Vp3Yx3Hidtx6zoCPyArcuqyIvDdmFpZleRFjvQUaZpS1RW9Xg8LaHyifp8uCJzuXk94fPZ+qtmMO0dHvO3GLarlikePH5HVFcMw4i2HB1SFASNdd7G1TK/W5HlOHEfEUcBqfsnp2QMGo5TT00cUZc4rL+c8PnmA1w+oPcm0rLi8Uvj5m+l3Hb6W9Ps9Au3T1C6LKgiCa90+QBBFzB8+QgtBS8e/fPx3+dnin9NSoUXAV4g/wu/qfzu90YjlaknreZRZQxgnLKsZtnOjkVXbIDzJ9PyMbLHEs5afad7Dz9T/nKau0HnAF8XfwLv3/owrXj0PvbEo5qs1h3t77nUSgsIYHpyc0AtcuHTdtE7y4SmqpqVtG4bDEV03Yb2uqI3Bk+75rHBKeGnh3osvIo2hbDLeO3/Pa74nfi77n/jq4R+jXK2pmoZ+EFIUBb1eSp1ljAYD4jghCAJ04n5vxhi6zlwXUb+WQkwIcR0U3nUdeVnQdZ0b6TWGLMuZLxfUdUPTtmAt9XpFrBXCk9cB1lu2bNmy5dNnW4ht2bLlDedyvuD0+JiD/T0mkwnruub4+D67NyOCvqQKPca+Jijg1u1bPHysyWY7+Hs9PjZ7jvPpU/TLAeOhQjU1nqd4klErhMDXzp63XK0JfJ91tqatasLABdOOD/a5ODnFEzBbrvGlwA8juq5zOzUIFvMFUgik8gij2HXREEgp8bVivVpxdXmJqRu8IKCqK8IwRPsBnTEIY+inKVJIqk3gslLKFVxtSxRFNHVNszFFAtdh0n7g07YtSnqbETJLnudUdQ1Y1wnTGs9zu2jKUwRRRF4UBGGI8TyUlES7u7xy9Yvce2FK2guJ+0eo/kaAkmW88uABJ13L53/ub+Bur8fkYsmLH3vA7s4By8WKssqZz+e0XeMChD3FKpszOvQZ74UIAWWX0hrDeVFwPJ9zZS1ro7GLNxHKjjQK6ScJpmlcp9Jz/9sRnmS5WqF9jSc9Pvrcc6wXC5Iw5Ge6H+Cniv/x+nxpbMW/nnwvTdfx9dFfYlUUxFqD1kzWaxaLBTu3btGVBf1ej4v5nGyxZBhFvL95Dz+5/sTn+vHs+1HK53ft/Wk832c5nZDGCU1Vu85jENAaw4OXXiLYnE9CCldkG0tLB11LlmXs7sYcHB4Qr2Kmkyme8hDSI8vWxHEMQD+OMb6P7ZU009fO4GooucpP2AtucrC7Q912pMpp+AfjMW3bMZ3P6bqO8Wi4eW6X4CyEE88Y0zkBza9SkDVN42IVpEdZV0wmE3Z2dliuM+aLOVhou44wCllPp+yOx/hh6KQndU25Ects2bJly5ZPn20htmXLljec1XJBGAT83M/8NFHPY7STcOdNe6QjjxeqikVZcaAUd/b2Yb3iatCii4T2dEkYP8szoUXHLp/LUx7WGNq2Qwch1hrAc9a6JEZYXG7UwAXhmq5jcnHJ1WxG4Eki7Tv5gzUbhby7EQ20EzK0xrBarVFKEWwKpLKwxFHk8sR6PTrTOYW9UkwmUwLfR0pBUzebYkmSbOx9T3Zx2ralaVu3r1N1eErha5+yKpGdcVlmQriioKndeKMQGOF2q5q6hiAgjAJUEOD3+3RpitAKGXRUXYZMXuH0+Y8R+m/mmWdv0Ykpy5XgorzkA9N7rCdTRJLQtg2v3LtHjEcQS66m5zx88BgrGnrDkH7qo33Xmev6MbO84OFySRUGjAYDLlcrzoUA7w6iuIOYrjiKY4b9Hk3lRvikUgjPc/tGXcd6tUJ5HhKQArqiYHc4pDdO+amP/bPXPG/eP/8Bfq/+DsIkRUgPlKVbLAiV4vLykrptafKcOAi4tbcHsuOnHv7Qaz7XTyx/gK/ofQtZXtBUFcFgSLK3y3q5ZL5cYIxhfzx22W/W4PsBm1gwus7lsRVVTZatCcKQ3Z1dlFLM5wuKyoU4e0pTFDkgODw6wsgWX0bUpvik41EElNOOU84wxtI7PGQ+mxIA9cbIOF8sGKQpYRBgOnfOKK15kh3WtR2e+sTMPGstbdOgtKZp6s2HDR5V03B+ecl4OGI6m2Ok4PTyknG/jzGu8A+1T9t2tG3L1eTKdTL9gChJPsV3/pYtW7Zs+Xi2hdiWLVvecFarFY8fvER/x2fnKKFNIp7a3+NkOsPXPus852wy53Fe0GQZZ5OYZDnh1u7edVdJSoEU0qnUpUR7zlBorcVXEl8prAAlPZTvo5Qir0rqukIKwWhzMxn6Pm3XUtcNypNI4W3Gr8zmJtrZ/Nq2dTbGzVRW0zYACCnoxT06a1ksFoSBj0AgPUUYOFOdNZayLGnbxu1vWRcW7bpfIZ3qEEKQF8XGwhhimpr1akUUR0SR66wYY5CbjCilFH7gkwyHyNGQLr5A6xPqZs1umsB6zS+++BLnpysG6hbS68jajzEv50TNHY6zc5Tv89Wf8056FhbAK/MraGrGg4SjOwOkZ3kpy3i8WtOPDXXTUFvrlP1ty2/5nHfyuTu7ZMslL8+mvHLRsVxadsOQUClM2xIEPnVZ4WuNrzXz+YyyKOn33N5bXrhOX+gHTmISN9SmfM3zpqHkdPGQvn+T+dUVTVOTTaf0/YAwjvG6jihNGY/HdMDp6mUa+ys8ly0xcUVYDzl405vBk9x76SWSMGR/dw8dR1xdXTGbzdgdjVGBTzafkYbRtSSjqkpWa++6uJbCZYa1m5HH9WoFWMbDEb7WBGGP333zT/AvHv23PDEXPuEL1O8hEe6c7KUp2XQKUjCdT9np9Z2FE8t4Z0wv7X2SlllOpwAA7kJJREFUHRH4pK85MYfFbIqxpnGvB8D88op+krCuSiaLOcPhiKauXcaY51F1LUma4mlFlKZUVcU6y0h2xjw8O3/tN/aWLVu2bPn3YluIbdmy5Q1nPjnjTW+/TX9HU0YBS2t5/2RC17TsDPqMsBSTA6aTMXVTk2Y5N0ZDQt+FLduuc2ODUuD5/kZW4LLD2ralM07/3lQ1RnlUdU1/OKRuGpI0JVuvadsGX2mKqkIrD+U5cYGxdpMn1qKVpts8txRiI9zwnVxDa4LAx1pLVdWUZeF2noxFKokxxnXAPLUZI/Scpn2jvHcdOOk6Fm0LgFZq8/zuOQeDAW3XUWxGG5+o7XUQEMUxvcEQMxpRpD/HW3qafRWQLwpCIXg8mdCtVkT6iNRTPHhpSlaNqEXOJJ9x58YXMrxzzseee45fmC+4Wi3RwyGJMawWc3phRLZcM61K1lWKWkUob4yQNUHg8863PUVPF7z/536WVVVzsVqxXt8lbSu09tHKI9h0+KIwRGtNnheYtqXfc9bEq6srfKUIwhDPkwx3dpgXCxQBLZ88wqcICW2P1WRCm+cEvk9vPAYEZZ5xsLNLaw1FnlPUFZE3QIvwNYsxX0Sk/j7r9Zr9OOL5F15AWIh7PYyAi+nMdYX8AE8pprM5dV3TxT6T/JhRcEiaptR1zWQ2o+sMcRxzuL/PcrmkqErqumZvZ5ckTQiDAKU0f+D2f4lWiv/5wX9PZXJ8EfFl/W/kK6JvwRhX2HdtQ+R5ZNMpgyTh8PCA9TojCgMG/QG/RicHQgjqunJWxyBgmudc3bvHzYN9+v0+i9WSyWzuxDFCkPT7NF2HEoK9/QPCJGFZlkxmM2xTE4Qhr9y7R1vVn9obf8uWLVu2fALbQmzLli1vOO94+2/g9OwR4WHKb3jTs3zw/os80JpHueDlywwhCrLliH3TsBdGWN9Ha1eg1HV9HdRc1xVhGFEWtct6alusBU96WKyTLuA08fPJBCEEl/PFRiEfYi1oKak2Gnohnzxv7XT3QqA8D19rDG5Useta17XyNV3bsVytsMagfd9lMAmBtW58Ldx0T4wx18WWlJLOGKTc5IxtNOFhGNJ1Hav1GmsMO7u7LJcL9GZ0Uvs+2XpFEITOvuh5tIHPvP4QN7yWNwU98seXnL/yMdRgwC+98jIPs4xifUjprUk9xah/k3W1Q+/mgNHTlov5Ix5cFKyvBgT+bQ7VkBcfv4jX3mWdwGpZ4tFDFx2RUoS+z2hvj8Y3PHpxymN/TZ6PseUuddYS1w27w9h1+jbH7X6H0v38wolJTNcipUcSRyjlClpPa1pjWS8rvnT4h/l383/0SefNbwp+L8V0jZQeGANtQ2sNq+WS/d1dWizLxZJ+mpLGCUYIvnLvP+VHL/7+Jz3XFw+/iTKr8aOQk7NziizjTXefZjKZYBNXMK+zjGdv3aaoKxCG/6P7AX764Q9da+e/MPp6vrL3xwiBy8mEfSlIkoS9YI/5fO72Eccj2q5z8oumBSv55mf/Cu/e+1PMm0tSOUJ23vWHB086rgbLaDhEb4LD9/b3XCdUev9e77UgCAkCF2WgceHl0+mMGzcikiShqiryosDWNaPRGAA/TTmbzbi6dw/ZNs7cOegjtc/hwQGd2co6tmzZsuX1YFuIbdmy5Q3n/e//SQ6OxiT+m/nIzz8k6sOR1sz6kJ/fJZsa/LKktxehlaKp3W6XJyXac10vY7rr8Fk/CDcdMkmwsbrZjT7cYgn8EH/ToUrj2O2VbcQeXbdRmXse1rhCz1faDY5ZC0JSb8YQn1jqtNYua8m4YGhPu6wmpZTb/Wrq63HCrmvp2g6D+35lVboCcHOcnlIo2Oy5NYRhSBRFZFmG7wcu56yuqZraBVBLSdu0VF2G2d1FBguO4j6iLHj55VeYFRkfu7rkpChZLPdJSsXBzSH7Tz/N47MzkijGi2NefP6DnJxdIOu7HMQDRNOQP5YE2R0CKWnOKvbjHZQnGd4YEKcpZnP8y9Mpo16PxUTS1z7rfMnNJCEYBVhrMG2L9jVt29K2LcJ6CClQUtG0DUEYYo3BWjdimfT7VAjyqkTFEV/h/Qn8MODHzr6PBlf0fPHgm/i9d/4CTdXQ1jUyTcnyHIHl7p07eEpzdXVJGAYgXKdUtC3vvvnnWKxW/ELxL2go8UXEb4q+jmeXX0MbN9RNgxSCZ59+mqvpDCkF2tcoKXn7m99MPByyfPiQH538/V8mECn5ifz70VrzO9S3IaRgMp1SV7XbHytLPKWYLRbkeU6WZQz6fZIkQRaCyE8IdYQx9lrq0W2K9bbr6DoXdG0FeLisOq01RZZdn1vWWpeNtrGOXn/NGDxP8mR3rKqcWn+Q9iiyDG8jTCmLEmMMSZygk4Tz1ZKr42OGvR5xFPG227cJopCm7bBBgIgjattx+fj01+vSsGXLli2fVWwLsS1btrzhjA8DDm4NefjgEY8eHXN4N+axaDlvarzlXfpSosLwupsUhZtdq81NppTSdUUA23V4yqMsK5SUtF2Lr518A1x3LExTTk9OCDwPPwhe1W+7eUaEtU4Hbg3aU1ghsNa4EbEkccXExpjoSY/WGMqycqOS0o0zKqWo6gpjjBN3eB55XuB5EiMNepPZFAQB1nQ0rdsLU55HkedYIEkSmrqmfWJSfLJLJqUr1sSmm4Z1HcAsh9Tj4viYPMs4zq54kGU8VxTU+Q2i+hZ3dsf0+j0ujh+jo4h0f4f7L9+nnFhG4g6jnTFZ11EtFqRRRBzFRFFIELhxwjCOKKuaKE3x4gjygjeNx85UKASB9ul5rkA2FjoDg/4ABNRdQ5okGGMQUmDaDuV5lFWFJwRBEJD0+pR1w8XFBTfv3OHq4oLAGN5948/xhckfZpqdcti/TdcI8tJltlV5BtYS+YErQITA8zV+FNHWNePRmOOzM5IopJ53fHn0rXzt4bdTsGAYHVKsKpqqYtDvUZQVo9GIs7MzsIb9w0MEgiBNaYKAD92/z9nLz/Oz/PPXPJd/YvlP+cr+tyJxVsmyaahXK4QAA0xPTpHCdUJNZ8iLEikkcRQhpdq0wCwgXP6cAM+4Dwqaxo0AGmNo65qmqgnDYPO+6Dbnl4fsuuvu75OxxbqunWDEdHRdSxwnWGu5fesWxkKWZVRNjfID5vMZoshpipK3PP00SX/AYrGg7FpWWY5oGpqiYDm5ZL66IOyCX4erwpYtW7Z89rEtxLZs2fKGs7s3olE5/YOUZ/s73CvXfHA6x6++kL41hFrj+xpPbLTumy6QJ8V1BlVRlJtMLo+2MwgswnO69zzLGY7HTuaQ5+gwJEkSfM+JO+rKCTu6tiWMIsI4Zj6ZXHe0hLU0TYMnJU3d0G5udJVWZHmOaTsCX4MQyM0oIk86coHLaMqyzI1IWnev3bUdSrlRRNN1iM3N92KxIIpChJBUZQFCsF6vCX0fz/fJ8xwp5fXoYtM0WGOo6oZgMODi+JSPzu6zFwZMs4zjvEBkbyds+gyUx43bt7iYL4g9RZz2eOnFV7Bti+9JRmnKZHLKrDzn1uhpdvo7rhjVPlEcUbUdLeAFPqLfx0sajHqJy3nAug5IhETjfjZhLVr7tG0DUjitvgXheazXa5R0qn3TtSilnDHR85yWv2sZj0as84x6vWK8v4+xFiFDRvoGWkU0ZUZe5IxGI4rlkvFg4AyTSMq8YLlas14tGQ2HNF2HH/gu00v7jAYDtK8ZRrv4cUyRnxImMWXtgo0vrq6o65r9vT2QEqRHYwyPz8+YP37E4a2E9vGvoJ23JWs749b4LSilWK/WlFVFFIU0dYXpOvww4OjgkDAMeenePbQnGfR71/IVh93INcQmzkAgZUjT1Gjt43mfOJJYFCVxHCGl54KYN+OeTdPQdebVSAQEWunNBxgCpOTk7IzJ5ZWze27y73aGI4IbERnwS88/z9HODkGSoAIfqzSqbakmV9wdHDnhzJYtW7Zs+bTZFmJbtmx5wxHK8LCsuVyvWRvDcVFgF5+L17aM9mM3gqgUWJCeK4ZC39+IM1yRBBaltbu5b1u07yOEcMVa4DtTXGfwfZ+iKMjKgmHao+k6rBRYITC4XZyTiwskQNU6lf2mWIrCEGMt0riCa71eOyvjxozYtA2edPs9TVMThRHWGpbLFXEUUTcNbdsSx7HbX8NiO+P2yDqDkIYkiTc3zlzbEIXletwxCALatqGpa4SURFGEHwQslgsW9+6RVbu0YpcH9pJifYvYasgz9gYx/Z0xDx8+4uDoiFrA2XRCeXnJII7BE/zo5X/HB+ofprEV+iLki6s/xFftfTvxYEA4HKB9RWvWVIXFH014cPIhTh8UzM8iEqAOQ0rfB2MIez0n3BgMXRem7fB9jbXQ66W0m9+FE5a44tQYQ380xmtbppcXREHI0089Rd0oHj+okLpmOIw5OT0j8X2ktayXK9q2JS9y1y1NUwBsVXG4f0C/3yerSqqioL+TEEYhOZa45+IFZvM5i/UKaQzj0YggDNF2o9A3Bj+MaKXEaE1eVbz57e+gtSX6+LWlH1qEeHXEYjan7DqmV5fsDkdUVU3b1MRxjJSSsiwBy7Dfo5f2rju7T8YHn1gUrbV0rcFTysUX+O71h49/LEgpEJsPKlzsgqTedGTttWbfqerFk3Fd60ZglRBIAVhL1zSMRiPKzf7lw/MLBklMMh7jhQGZbTg9v4f2ekRxQjIc8OjR49f9mrBly5Ytn41sC7EtW7a84bzQFZw0LWtP0pQjgvwL6HmGUT8hjuJNQK3YaOol0pd0WLrO4GtnMkzTHhbQccT64pK2qp38onXFVFWWlGWJ7Tp6vR62aaiKgrjXQ4Uhs+mErqqxWNRGPZ/GMVop8qZBbToQ1ljCKKKuquuRxrZtnY48CMnWazzluZHFzfdWSlGWJWYj4ajr2gXvSqfY19rf7PEoPE/SGSdy8DyPpnXShrquiKOYoijwN0WZvwkbvppOEOCEFGVFaixZEXPoa/wopgoDbty6zePjY24cHXH/8WPq9Zp+L2UnDBj0Uv7d+h/xM9U/vX5NGlvy3vk/Ain50u5P4BtDF77EdH5KEGouX1xTrwbYPOZGEmNNRxLFaM8jCAJ6aULbdrB5nTzPjY8qrZlMJlRlQeD7pEniRCZRRGsMs/mcVbZGKc1494D/6XsSfuJf7lJXEuW3/KavuMdX/L4pbdMQRxHGGIb9/ub5JVVV4XkeSZwglUfZNJyenJKEIW3XMpvNGe/uEg8GrK1h9vgxpmkZDYf4QeDMlabDWFC+T5atKRE0puPwxiHL9RXZpORdu9/C+y7/wSedy1/S/yZCFdFUFaZtGff6RGF4LZJx+345q2xNFEfs7e45AYfFBXgLeV2QXY+kCvFq1AFc73R9PGEY0bbunHkyxuo6pi3W2o3R0wASi/vAQSKQ0iMKnKJ/tV6TDAcYIeiKkqLrMHVN7+CAZVURJR4dF4SxYjSMaNqagglhHL0+F4ItW7Zs+SxnW4ht2bLlDeeVriMrxvjigKAZspMEJL5/LcnwPFfIKE86mYWnyIucYLMrFkcRnRB0XcvV5RWybeknMbYzdFrR1m63Jg7cjgzGEHiKwPfp2pZVnhP4AWG/T1WUIDqGgwE68FllGXQdnq+v98KqynVCnuRHuWLQgmnxA58oiq7lCkVZ0DQNaeoU7XVdo7VCCElZFijPBSM/ueEuqxrf95G+v5FbNIRRTLEZSVRKufbGJguqqio8IfE2Y5hBGKC6jtAfuB02z2PY6zGfTBjEEcvZlP00xUQRWiuSJGVVzHnv1f/wmq/N+2fv4atvfDuTBw9ohM9qvUMZBlRTj2GS4ieKNEmRwnXrvM2oqB+GaOkxn1xhrUUYi5CS0/NzpDXs7OxSFQVR4pTvQRRh6hopBIN+H98P+BffN+Df/uCIJ52ftlb8zP/+JrRS/PZvuI/WCj8IadoGu7FNPokG8LRGKo/Vek0UBvQHA9cxizTGGo6vrpg1KyxOjtEfDOisYbizS2Mtcj7Dk5L+7i6n5YI4anj08CVsG6GjgC8a/HFW9YpfWvwQhhYtQr5054/wZekfZTWdk8QRvSShM2bz+no0bUNZlHSd29M6Oz3jzlN3qNuWbL3GWIuvFUmcEIYh4PbCwjDCGOHOXVxMw8d3w8B9UKG1M3wqpciL4ro4FUK4zqqQdMbtVbZd62QfRUFVwumJIE5dfMPFao3oOnTgc/fuXRrPY2c3ZVL8Iudnl+yOb9F4x4Spx+nxhNHo7a/vBWHLli1bPkvZFmJbtmx5wylWt0nUDQIRsbOT0NWu2yG1Zj2fESUxOnAjgsJYhFIu36l28owwTVmsV0Q6Yfz0M9QYFpdXrB89wtYNw36fehOq63lub0b7rmBqjGGcJMwXcx49eswgTTf7N5auquna1nV3msYpxYWgrmon2djkiXXGvmpGtJayKFFaU1U1QjjpRl1VdKYjSVKMMSjljkVIgfZ9V1hubpgHwyFFXXP68AH9xI3xGWMoyxIhhNtX8zzqqtwUW04w4nauOqI4wQLtxtDYbBT/cRyTDoY8Pj5GC4jjhLIqmRTnr5nTBa4zdnr1CiN9BEKQ9nt40uPo9h38MGT3YJ8OyBZL4jB0kghPIv2Ax9MrLq4m7A8Gbl8qz/CVIo5jrIAgiuispek66vWaonBFqxACP5S8958P+eUFBwh+9t/e4bd/3SlKK6qqxPcD8DyqqqZpGyLpYbAsZnNm8zn7O2NnaVQ+VVmgg4B2tSZUitPlkrfeuUM0HtPUFTaOEeklF/MpcuEzLUtqrZgdH2OWHra+Im87jm4c8Z/c/MuMwyPG5R12/DczDHtURcl4d5euquisE77EUYz0PNarpcuFE67bhedxenpGVVe0net8RmEEu6C0+gTb5qs7Xr86nqeoqhrPc5l0/f6rHwCUdcXVfM5yNufoYJ8oSvn+f9DnX//wmLqSaL/jXV/9mC//PSuGoxG632faNRiWXJ6+gLUG7fWo65Ldmx6XJ6/QIhncuPz3fs9v+Y+booCzMzg8hGjbEN2y5XVjW4ht2bLlDeeZm1+I9jRJHGEQtHlOfzTk6uSEW888Q1ZVNFLiWRgdHGC9kqxYIKqIwWGfdf2AZF8QpmsS7zE/94EP8PjhLv1VxN5gsMkTs9RVhaec2lt7HnmWEfd7XF1dUtU1vShCAk1ZopRCa00ax0433xlUoMiKHK2UGytsOpT2qTfFQNs0TsfuB9RV5fT4aULXuo6X9vXGXudfd0a00htlvqYoC8Iw4mo6ocjdCOLO7i7r9ZpxmjKZTkmT5Foi4nmKNE3RYUiR58RxhAWU9rm4uiIKAqp6jWctvvZpO8NLL73ozJG9FBX4LLM1e8nRrxh0rEXI3RtvJ1/kTqUfJyyXC9Jen6JtKDzFsn2Rmh10HDNZLanbmvOzS4rLC27s7VN1LTQwGI2ZzWZ42mVXRUHAdDajaRrCyHWA2romjiKmpy1N9drFR115WDMiSg2i9Fgslm7HaaN+dzt9BqUVe7u7rgvpB7g9Qp/p/JJpdcFu/xY3R2OiXp8yKbmqH8HqBWYnj7i83ycqBHfvPMX0+AQBtNmSNIrwwwDfUxxfXVE/ymmtoenlyHHA7lN3mS+X1MsFvSjG024/cbFc4mFpO1cYK61pupYyz0HAznjMeDSmqiq3Q5YXBEFAXVcopT9JzvHLeRIErj8uOgFeVdUvliuatkFaSNMUIST/+O8F/MgP7fCk2G1qj/f9L3fwo4iv+Pp7UJZQ5CA9hLdDa+b0egNG+zC5fJmiqvG9fSaz7Y7YZwtdB3/9r8N/899AnkMcw1/4C/A3/gb8/zlFt2zZ8mtgW4ht2bLlDefu52eURY0p+5RFy8GdhPnyRUbP3EHGguK84ujmDjK8Igw/SIJltVqxMBaShDfvRrBYspgtePnxI1589BhvdoTyLJ5wHaeuLAmCwMkhpLgOVG47Q12WBNp13BbLJf0kJtiED1dVRds0REFA0zTOSreRbCjp0XUtgR9Q1RW+H6CVpm5qpJAM+n0AGuPMdXYjYDDG4CnvOtcsTXvMlwu0HzAYjzY7Z26vzQpouo5sMnHqeiHI8+w6INkKWC2XeFqTlxVWQFcU2K6jLEt0ECABT2lM17E7GtEbjzk7O3f2Qu0zGo951+U38b7F933Sa/PFwz9MtiwJ0xTpeSyKnCzP8fyABsvxCy9QNg1tdZ/H9+/RFQUK0Epz++BgEx3gCsHVcsl0OqVrG4LNbl8Uhpvi0u3UJVGMMR3jHYP2O5r6k+/udNCRjgxFXdNuJBdt4/Le6romCHyKqmIwHHJ2foaWbkRvtVryb5ffy/+x+kEXwnwR8jtu/nH+E/2XuLhY8uhBiWoMxrtDTzSkiaQpCnbShKZp6TyP3fEYKSXL+Yy+NYiVJekpRr2Urmk5u/cKi9WacRwT91KKvGC9XiOx+EFAnmcoT1FXrrsZJ07csl6t0UpTlgXD0QgjDE1T43nqOn/N3whoXgshQGv3v3AXiWDoTMdsNsMPAuI4JggClsslZdNwOV3zb/7lm3mtjuN7/+cxX/UHJ5hhj7wtGI920V1GUULga2bzY6TXsVqvoOuznqXwpZ/SW3/Lf2T89b8O//V//WrQeJ67PwP8rb/1f95xbdnymcKnXIi9/PLL/MN/+A95+eWX+e7v/m729/f5kR/5EW7fvs073/nO1/MYt2zZ8hnGU0HL84/vY5IElXr0ens8lUrOlx/lbL2id7SLHsyJhWTH97khJQLBvGmoOsPVw0e89PJLPF6tuLcyqNVvZUdY+r0enTFUVbkRFTgTnhTOcOj7PsvpFN9TCGPwlYff7xFFMUWRu4BlQGyKJu1r5Eae0W32uty4orv5vd4Zky7DqWkbF/IsJToI8JQbnwuCgLIsMMYQ+iEnJycIIej3+wghWaxWBNpHBT7T2ZwizxHWsre7i+dJylLRdi0GUFoThAFl0+AHIXESM50vCHupkzJ0Hfk6ww8sQRAym06p247A9/GUYtDvczWZ8qW9P4r2Ne+7+h9ckSJCfnPy+/ny3h9FWMPV1YSmbemahr3RCKyhzgt6SpFISWGN6/T0+igp2d3bpa0bl2PldVwWj0nliP29PSdcEU5z7ykPgYsOeDXnCjzV8SXvPuPf/fANPrFYsLzrd57SdGuW8zWrxYJQa0aj4ccVK5JAS1arFflqza1bN+mM4b2r7+Mnlq/uwjW25Ece/3c0yvKFR1/L7k2JWAzxmgZhfIbDIX4YUZUl68WCu297G1nTcPzgAW1VMez1+PJ3fqMzZXYddVXRTxIGoTNZ5uuMxnQIIE5SmroiiiJ0EJKtlhwdHiI9j0cPHxFHEUVVUpQlzOeMhyMnbumcgENrfa2u//hizFpLUeQb06ZAa43WPngerklomS+deMYCRVWx6lpeemX1mkUuQFMrLi4s6+lz7O3ucnz8CKUlvYFP0tNo0+fqwsNv76BESlYVr9OVYMt/yBSF64Q9KcKeYC383b8Lf/WvbscUt2z5dPmUCrH3vve9vPvd7+ZLvuRLeN/73sd3fud3sr+/zwc/+EH+wT/4B/zgD/7g632cW7Zs+QzCf/SYwySh9X329vbYiUKivKBdr+ilPaK+T+r7xEKSaEVa1Zw8OKZpKpZdw8+dnHA/y8jWI/TiJjdjn36a4AmJAIIgdNZC01FVLugZoKkq16OyXI8sKqVdrhgCIeX1bk7d1C6IeCMF8f0AqRRiY3LU2ndjZ1VFUZb4/mas0bhxtKIsiMII5XlUVUVZlsSx2//Z39ulrhv8KGS5XDCdTDg6OHRdmK5jOBwwHI+5OL8g8n03RpmmdG3LYrGgMx1hFHM2nVI1Lb04pk1i1nWN17bsjkb4myJsMBgQbjT8Fst8sUT7Psmgz29bfzufp34/Mq4RZUAv6JMkMb7v0zNu9E15HjIMefDwAeN+H4TrMvpKXe/W6Y0EpbMd7519D++fvue6uHvX4A/x5cNvQys3Kig2RZb2/Y3gxG4KEMPXfNMZUkp+/F/t01QeftDxW7/6mK/95gmejsiyjDiKGPT7CGvxfZ84iSnLit29Xc6vrhgMBrRdxzpf8v7lD7zG2Wd534N/yLP511I2hi57zDAMufvsmzBdSxcEnJyc4Lct55Mr7j0+Zi9JSPoDAPr9AcvVEqUVd+4+RVaWrJdLsrJAC0mcpkyuJsiyROKsm0VVsspz4vmczliiOMYPfOaLhRuBbFrAdRG1718Hl79q13y1gCoKJ3HpOnN9g9x1LUJ6WAGt6TZh3D7TyYS8KCjrmv0dfsWOox90qGDBfpCwns0RTc3u0RF+XzNbvczl4jnyqx0G8TNoP+D2/vDTvAJs+Y+BszPXAXstssz9/dNPv7HHtGXLZxqfUiH2V/7KX+Fv/a2/xV/8i3+RXq93/fWv/Mqv5Lu/+7tft4PbsmXLZyZDFXC4M8JLEvpRyFAqMs8Q7xwhQomOYqq2ZaAFL734Ij9x7x4ZglgrGmOoBRTLm6TrEXtpQugHmKZFKoWnFEWeuW6VgTSJqesaT3oYa/GsRamNbS5wnSyLpTfos15ngDPSxZETTFhjUVq5AquqXLCy6SgrJ7uw1hAGTlnfWSdJsFjCTcdstVqRJAn9ft+NC5oOqTV1UdBmOfP5nCQI6doWrTzCKKSqay4ur5jNZ9DvEyeugPN9Hyklxhg6a4iUJgkCojgmLyt021BkOXMLZV27sTqtWdUVXVUz3NujyC7xLJxfXbrOjR8SyzEiFSRJQhCGzBdLhNbU1lDMlwB4gLHga4+2hdHOjgvPznNXrEnJj539fd47+d7r17mxJe+b/yOk5/GVoz8FQiKVQmtFnrkcMIQAY/GUQvuKr/nDp3z1H7xiNdfs3fCJEklrRzy4f5+2rOhtxkiFFPQHQy4uLzFty+VkQlM3RInLoav0+jV34J4cV2MmDNghGI25dfMGk9n8Oti76VqUtcwvL0mFoD/oM59OabuC83zBQe8OSdhnvliyWC6pygIlJSpOyBZL2qame7JXaAzGbH55UqLDgPl06oqtrmM0GuFr/QmKerEJB3/yT3ee2U02mKHrnE3RCTpc19dai5Aew+EITwqKtkXEEV1V0jY1QaB51+94xPv+16f45R3H3/SVD+iqJcrv0VMKGUeEvT5ld06RV/j15zA6GNG1lr29EY8ePfq0rwFb/sPn8NDthL1WMZYk7u+3bNny6fEpFWIf+tCHeM973vNJX9/b22MymXzaB7Vly5bPbGSbsnq05M7TMc0i56defIWycmG0SRozGg1YLGcUzYrjbMVz6zXnXUfneQgbUy93CRYJR6M+oR9sAm0FWEMYhte6+bqpCaTLivKUhzQWT3nXMo22rvGU53LHamdJNJtsJwDhec5utzEUSiFYrVeYzpAkyeaH8UC4G25h3F6YVhohnV6+1+9fGxCNLcGTlNOZU6vHEb7WpIkLHm66jtXSday01uzu7OIrRZIkTBdzPOVR5jlhEBAFPoWQm5/b0tY1pm0YJAk6CPA38objx4+xxpCkKS8+9zFM19FPe6R+wGA0ot7kcyVpSu1JZosFpTFQlpydn3H31i38MKStGzxP0jQNg+EQYy1NUaB9n9ZYpDb8xORXUOJP38NXHf4pFAFqo91v2xalNWVZEvo+YRTiSQ/tBbRty503BazLiuPLNRfnZ4jGdfp6/T7C89C+z3y1pKorkijCkx69Xo9uMzLpt71fRUgScbN3B08EWGuwQrLKZyy7UyJvB/KCRsDu4SHZes1iOuF9q3/Ez5X/nMZW+NOQLx19M18afQt5ltFLYtramS61lIwHQ2azGcN+n6ZpUFoz7Pcp8oJ8MnUmTM8jCiOEtcRR7KQbwinrn5x/YF1Htm032WLtL5N0CFecGYMBpHX7hctlxoU1PD4+IaorDoYjoijkd/6BRwgpeP//fpOmVuig411f9Zjf+U0XSDmgMRbta5LRmHWW0UaKulD4Oma9yhkMRizXV8wm2et5OdjyHyhR5MQcH78jBu6zkz//57djiVu2vB58SoXYcDjk9PSUp39ZT/oDH/gAN2/efF0ObMuWLZ+5PLp3RZEX3HvlIUGkWGdzjm7tEQYRbdPy0isvsO4y7ncti7bjuGlQ7VuhGWDXLQdaM9iL0b7GtB1SCtqmRWlF2zS0TYuQAl9phAXPk7R1A7gxLmOtK8486fZ9Gvc103UIa+n1EoyxlLXrej0JXm67jtB3hYLpOrjuVhg86cFmpIxN96JuaqSUNF3rgqHDkHXh9r+0UlRZThiFCCmcdr5tEdZ1my6nUzwhscqjqGvKqnbB1GKF8jVWCMqqIgpDpIVhv4/SLk8q2IxNYgw7gz7a9ymrihv7+yAEcZwghCBMYoLhiFm95t7phDzPyC8vSeOEXprwtre8hXB3j/nVJTKOmF5ccrS/T9jvkbcdgZSsF3NMVbHOT3/FDlRtC5qgQjau2GzaFj8MqauKIPDxlCsqPO3GRP0wZJkXCLmRZ/R6+L5PFIYgJEJKyrqmqBuCMMIPQpRSTu0f+Jg8x67XvGvwTbxv/slCki/d/RaUF9I2DcPxiH9x/29fj1MqEfCbgq/jG9/0f6E1UFYVH+AH+anif3z15zEl/3byveRhxh9561+l6QwPX3mFKIqc8KUsiaOQtuvQvu+iB5qa2pTU4YpUDvG1ZjgcIIUgCAPkpnsmBNRdzqK9YujvEXgx7eb8stZgjLn+Z6D1RpnfuY6ttS67rKooLy859DyGRzeoypK8KJBC8o1/asUf+HNnTGYaI67wTU4YJBgs/SQlr0oa06HSlOVyiu+NkPj0ej7ZqqDNSw576et8RdjyHyp/42+4f/7dv+vGEZPEFWFPvr5ly5ZPj0+pEPvmb/5m/vJf/sv8s3/2zxCbT4J/8id/ku/4ju/gW7/1W1/vY9yyZctnGOeXJ5RVho4MN4Z7PHvzDoeHhxyfPOZkPWNKwcfyjLMOZDfEM7t46z4jKUj7fZIkoW0bPCGRWrgxL/vxhkKF2BgLhRDX4g6E03ybztBZizUWg+smmK7dhORq6qZxHTApsZ278S2L2skQjCGKIqTnkeXZpqBz8gYpJEp6SKVo6ub6+igsSE+6MUal6WRH27QEYUgYhhvVOkRaoZViNZ8zv7wijmM8r08wGBKajlVRkBeFC4sWEqQrSlpj8ISgaTviOCGIQupNqPV6tSYIQ4SnGAwGSKWwUmA9RWMtp1ev8NLLL5N2MZ6FuzdukqQJSI91VZEtHmCSU5aXivHeXfz9Po0642Mf+RkWx7sMfU0chuzt3vlVO1BtoTk9fcy43ycOQ7efpzW+r11hKAWmM+ggIBkOUJ7i+OIeyyzj6duuK1flBb1+j7ys8K1l9+4B82yN17kRx84Y1qsVjx49Yn8w5N03/nO09vmJ6T+h6nK0DPjc6PfzOXw9WZZzeHjIvzr97k8Yp2xtxc+UP0D3guErkj+GH0l+4vT7X/M8/vnyh3l3/p9z9vCUnf6AOE1YTGcbgQjX47BKe/yrq+/hp/MforEVmoDfvvstvDv8z1CeJuoMrYXlasH/cvX3+NGz76M2BYGM+N23/iTf9Mx3YDrhzlnrOra+74MUCOPO865raesO6SnSwQDTdbRNQ13XLkdPa0a7O4j+gDIomWc/y+RxwI00xXiKqmmoPI/a4kaAqwrfGyJ0zWKRUy1rYt/n4JlnWGfbjthnC57n7Ih/9a9uc8S2bPn14FMqxL7zO7+TP/bH/hg3b97EWss73vEOuq7jm7/5m/lrf+2vvd7HuGXLls8wrJdx6809WqU5un2T0PP46Q9/iJcXcybG0imP49JDrN6Jqi0D36cf+PhaE0URbeOKjKZrXH6SMcRRiNh0pSSuYLJmY05sO4QUWOM6CdKTNLVThT9R02vtXxcv3kbg0XUdSZJQlAVCCrzNfpa1lizPUNLDCoE1rsMmpQThbootTibRdcYVf9ZSlqXrnAFaa6IoxFMKFfjkWU7S61HVS8Iw5M7tW05FrzXTquL4/JyboxG7u3tujLF2NkatncK96zq0lCit6Yyh6QxVVVE1DTtRTCtXXFaP2E+fYdlKHty/Rz6doT2PpPXxRMvb3/4OvCCgBGxdc3R0RBtWFGJG0b6CCVo+/PKEyanF7/a5NezRT1OSJCHt9fnywz/Kvzn9/3zS6/356e8nUglP3+3RVBWelNRNS6/XQ2tFOhySlRVXx485PDigQVB6L3H/3iMOwzEIwWS5ZO/wkE77CKVcEb4P5y9+FC+7hTCGoirxjeVNTz+DVB4X5xd81d6f5rfd+rM8qH6e1WnE0BszGoyQUlKZgh+/+MeveY5+sPmXfMP+n2deXVD/SrtmlBxfvMDdo7fiKY/FconW+nrk0krLeH+PH3r0d/nx7D0f999V/G9X34MQgv/0rX+Vqqppu5YfPvtv+ZGLv3/9uMoU/POH/y/KsuT3Hf0XruMnBFJ6SCkQQiKECxk3xtA0LcY2dNYSRhGLqiTaFOZt29JauDg5xiYR2TRlP/S4+da3UZUFsiiwbUsQRtT+JdPJjGxlGKY3CGWIiCGOXG6c6cy/93t+y3/cRNFWzLFly68Hn1IhprXmn/yTf8Lf/Jt/kw984AMYY/iNv/E38uY3v/n1Pr4tW7Z8BtI/SvnR6RST9jh68JB8tWJSVSy6DiUHiGqAnI0YtC3jXo9+LwXLdZGjlaaqK5T08Dwn0lBaY40lLwt3ky5dB6pt3ZiiUmoj3tB0XUsUhK7D0Dk9fdu1xHGMlAIrJNJzu2NlVblOjVJYAcpzKnnlue/d1DXSk26HZ2Ov69oWgaCsSldobfbWPOld75pJz6PrDEGgWC6WhEnMsshZLObcvHGDqmmQQpCv1uzs7BB//m/k8uWXCIIQ4XkEcUyYJFyeXyCxeNLD04rJ1SVNZ5hOp/TShPHuDv/s5f8bPzn7/muT4TuC38dv6L6Oca9P17b0+n0ODg6IhwOapCUKzijyHLk34akIZGaYHhc8Or0kuxqyFybsjceEYUjbtQRRxKIo+LKd/wylND928r3UXY7vxXzx7T/A73nLXycMA1ZXNYvJhEhrDg+P0FGE5/us1Ypf+tAL3B3tE+/tUfr3eeW5jzDoP0s8GLPIMu6+7W1cZB+hKqfMZwVJsMdyNsXqBYVNaOaWNAzpDwc8ePgQYQ0g2B8NiXTIm/tfxaPyAXf2b7JarVBY6LXU5rVV7I0tWXVTUjX+VcOve94Y6Xl40nPSks1+l+/7pGlK4xneO3ntYu/fXv0TvvGZv0BR1EwWE/7N5Ws/7l9f/mPeFf4huqpjNBySxsm1SVEI3IcACIS1mw8YPOqqpN/r03YdZeNGQdfZmtQPeHj/IaEQ9HZ2eHR8TF5foL2E0XiAEWvW8w7PjBmmGrDE/R5VVREPh9h8hTHtv98bfsuWLVu2vCafVqDzs88+y7PPPvt6HcuWLVs+S/jFuuYsj4iWnwsjj6w6IZvFBLWlr31CX6NSSbgx7AEILFJ49Pt98qLYZIZZmqZGeB75OsPTmsD3icLIBTN3LXIjtAiDAOF5zGYz+v0+1liwlqbr3M5VZzDWUNeuMKuqCj9wevk0jjcSiIZhf0BRFmg/oKpKgiBECkFnOgROqOBJl+lUeR2FmEO9Q1d1KOUhhUL7mnWWE0URntZQFBgLRZah/YDOWoY7uzRdy3A4xPQDHr70k9RFSD9Jma0zri7OUUIisYyHI4y1FFlOFIaotuPoYJ8oTvj/nv4/+fHVJ2Zp/VL5A/gB/DbvjxP3+hweHSE8ybqsmFQfxFeXPDw54fPEW/A8xdXZGUPTcSKvuHn4DtIgJPR9N1aoffRIcXV8wfjWDX7bzp/l9/7WP8NKfoQ37+yTdoKyuc/zDx/w/LFgP3gb/eGIoNdjKc5YrE85ebDk9u13cPTUgEX3M3zwF55HVIfEgcQLPWTU53x6ytnVjDjYxWs6ylrSH+8zjpe8dH6fg4PfirWW3FiEJwmFx3i8g/QUUa+P6i2I1xnJoaUMcg72nmHRPYcSAa2tPukc9UXE3vApppcLvnT8zfzYx40vPuE3hV/H7nAf4UmsEORFwWgwxPNcCHjU73FWPX7N5we3O/fi8UdJxT6FWPyqlser/DE30mdpmie7joYnVvsnHzTItgFrybMMP/CpraE2HUG/x8V0RrteE2hNX0rSNEUZS2gttgiIE5+ukOh+iaedZTQIoCwaVqs1BzcGoKfMzs5Jot1f61t9y5YtW7b8KvyaC7G/+Bf/4q/5Sb/ru77rUzqYLVu2fHZw/+zt6GVBKFaQSXaTffrURKmmF8fODNc0JHFM27Zuv8pY4jTBWEtnOmQnXUGkNG3ndmCe7Gq5LlaHVtqNc2lFVpTUmy5a1xnM5oa13QQ9Yy2RFzk9fevsiU1VMRoOMZsizROSoiiwQFvX7nu3LRtxIabrMNagPI8fmfz3/NSTnSAR8MXpN/JV4bdhsVRVjfJc167c6O59rfG0pjdMQUrmVUXtC4riPi/90gNMpklEwyvzBaGvSaKIOIyuQ6a7ztDv92mamtBT4EnyYslPr1871/EX6x/md/f+DKPhmMVqSVHXCKXo33ozH7v/iJDfiBdZ3vdLv8jpOmOF5e7Nz+OpuyWL6ZKi1qyzEc88C5fz9xOMe0QHKw5Cw74fsOM9y57nsTo/5+eef56H0yk3jr6E23cGzCc5DFI8c0F+mfOWt92lE+e88OgXaZor4miEHw7Y2UmIR3POL4+5cXQLtVPRtRecPpoh8jdRLD1mTUZVaC7LU4JeS6J2yJdLDm7dZrQzpqwqGiAazXmH3yLih9wcgRQfozg95e29386Hlv/rJ/1+vmz3jyCtpiwLfvvOn6Kqa352/UM0tkCLkM/Xv4dvuP1f0h+MmM9mIOHg8IgoTVjM59imwwYhth2jCGj55GJMi5BEjhntH1BctL/q48bBIaPBwIk6NjuPpuuwWIS1SE+iPI9+LyUPQ7I8p6kr8qIkkpJmtSKNnKXRT3suIHwzumuahrppCJTHurhktlgSqD6GlCCMUEpStQtOHt/DVkMifzuauGXLli2vB7/mQuwDH/jAJ/z553/+5+m6jre+9a0AvPDCC3iexxd8wRe8vke4ZcuWzzh2GkE6HNHWFUEQopRH2OuTZRlXl5cIa+nqmvDgkOFwSJwk+L7PbLUiK3KUUm68zHMmOV/pzdiiQfsagK5taZqGKEmYXF25oOgwJAhDjLGsVyvKsiAOQ3yladvGdRuk62q1bYtWirZxhSDGjZvVm90sa63bBbNgrDMi1sagleZH59/D+z5+J8hWvHfTlXr3zp/G19qp+vt9rJR4QYBVivHNWxhPUmU5QeBTdi2nj1awkAx8jyQMKfOcQdpjOBwCbhdOK0XXtrSmQ/sBbdfRtQ2Vyn7VLsvl+jGRn4InWVxNOLp5g2LlQXHIwa2n+fDHfoJHxz6J/RyeuXOH3aMTmsUDUk9wajNG48+jah5xIwzZP+oxCjQ7WjOQEt0KPvrB53nl0Qs8spZ3vuWtHN7QeOYMWU1I4hl2NuPNdxXPP/55Tl8YMEpuMLg54uT8ZQbqFqHuaOUa6a944ZWf5eJ8gVndwJd7xGqNrkNa9VY+vPxePrz+IVoqZz2Mfz9f9uzfwYQJpq3QYcPk6gHBas1etGZa5FDXPPf4MW/x3k3S3+EX1j9EbQp8GfFFg2/id938L6jahiRJ0TrgD739v+LLz/84y+KEvd5tTNExGO9BkiCbFh8YHB4yyXMWdcMgCjl+8ICT6YR38rv4JX74k16DL4q/njju88orL6ON5V3JN/Dj2SeLQb6o9wfxVMQqzymLgsDXeFISx8l1zpgzcbrCsSxyOmsoLbRNTT6bMQgDhOce227ENB6COAzoRRFSa8qqoq72iOyIalmihWIxmxL6KW3ro+wOo70Dxrtba+KWLVu2vB78mguxH/uxH7v+9+/6ru+i1+vxfd/3fYxGIwBmsxnf9m3fxpd92Ze9/ke5ZcuWzygGYUgQBBitkEJQ1w2LLEMrTRqEVGXBeLzDrRs3GI6GSKXoEBRNTd22rJZLTNcRxDHS8647A08Cbpumvh4Pq+uaJHY5XdJTVHVNtlpRVyVpHKO1jxAC3w823SVDXdX4vkYgnMzD2OuA3SRJaLvOdRTaDqUVnhB0bYO1hto0/OTqn77mz/3+9Q/yO4Z/FN/X9EYjhOdxfH5OnmXcvH0bOZTce/gLdGVMmUFXtmTTOX2lSKIIrRVhMGI4GABuX05KSdu1aN8H4fbSjDGEQchY38SXIbV57f0m1SYURUFd19y8cYMwTujKEt0knN97TFUdMqoGvPOdb2J494hcP6YnIk4fPkK2LfTvMY4PeNoPuKM1vlAsLwoWDTx+dMbL915g7037/K63vJn9Xh9bFnzkwUOOwoDJ2Rknl5cu96oq2dl9hqTzKa8CbvZ/M6ODHtPLNRcX4AU7zM6H+O0RoZDs7A1ASLQQ/NTi+/jF9atFb2srfiZ7Dzv3bvC17/yTnK4/SPZY4vkdzz415uc+8hHC/oBUawaHh3T+AV/y1P+dr7d/k3l5THYluJmMsEKwzjOU1jTGUNQ11njsxXfJlxmjfp9aCE4nxxi55nDvLufd8zz/4hkDb8zVxQV+1zGOY37n+E8yqFN+KvshGlvii5Av6X0jv2Pwx8lWa0ZJCsbwtf6fxZtqfnL5T6/3+b64/wf5yvGfpCxrVoslvvLwpKCua6fLx2XouUBoZ+JMLZxdXNAUBZ4QzK4mKE9y9+lnyJuarnNym91bt+mSmHUzpWoappMV0/MJ416Pwxs3WDYlw+GQrmtJ0pheHdG0OW2rfz0uC1u2bNnyWYew9uNj+n5t3Lx5kx/90R/lne985yd8/cMf/jBf8zVfw8nJyet2gP8xsFwuGQwGLBYL+v3+/9mHs2XLf/D8V//vH8EPfKyxRHFEXRQc7B+QpilFWVDkuSvK0gQ/CKmamqKquLyaUJYFxliGwwH1JkS3Kks86ZTeUikC36ftWqqixA8CVusV1hisdfs0eZ4z6LncLU96NG2DNZa2bQCnsHc3ty7/yRhDvBmTrOsai8C0DVEUU28MjtYYtO+zllP+rw9//6/4s/+V2z/IXnibRilOHj8mDnxu3LqFt7/PLz33c1wdL0mlJPJ9TF0T+D7D4QCBE3wkceyKr7bFDwJ8ramaGmOhqUqCzbiiEIIoTfn+F76Tf/dxJr4nfGnvW/iK3h9n0O8zHI+ZLxZ0Aq6mM5q6gs5p+vvDAUGvz8yeMy9eJCuu6A/6DIcBX/jWt/L5aUpSNaznFfmy4/J0SVnXvPjiczz1pj3e/jlvBiO5upzw+OQBwSjgxcWS+2XBg2lA338TbVeC8Un1mEEQEO7t8srDX0IuFTuDIUYKRFWBsSgpCYKAxXpNmGi+6+T3veY4nxIhf/jw+1A2YTTaYXjQcpX9Itlc8vSbhpSrNaGUyGFKoFtuDI8wWclHT9YE7TtpM0uapIhAYRuDKXLy9RrRdoS+pt/rs1wtwfOY1jXT9RXZoiJsWnZ6KW3TMOoPsNaitaKpalQgmTcXDLxdPKvwlMJa67qwlcucS0YjlusJl+sTdsNDpHXZcNYa1Cb7LgxDfN9nf2eHKIqu7YldZ+i6lqpuyIr82vy5Xq/J1hm3bt/Cap/ZcklZlbQWss3fK2vxBdzY32fv1i2qJGA6P0ZKS1NDGIYMdjTT+Sl51vD/+D2/83W7HmzZsmXLZxq/1trgU5J1LJdLzs/PP6kQu7i4YLVafSpPuWXLls8ijLUoT2Gk26caHRziBwEGix8ESM+F8xrpMc9zWmNoyorB/j6R6ZhdXrLOcoosI+31XNByFNK0LVoIVlnGcjEnCAKnlQPiOKFpauqqZtDvXyu4q02HQEmJUnqTO2bpuo6mbVCewt/o5aUnSWLXRdKhG6lsO7e/JpXCU5qe+NUte14dkZkcY4wbZ+v1kVLyynPPsb4/4ShNSONkE07d4nkewkJ/2CcvStehEyA8z5kWV2uMMeTrNbt7uwRJSl2WpKMhnad4140/S5nn/Pz6h2go0YT8lvjr+J17306vNwStOTk9ZblY0Ov1oK5JggDf9wmjiLppmZ0co8KQcfyb+ZzPC4n7jzB5xm5Tc/HSSxTLjKaULCY5y3mF0gFVWfHo4THrbImQlqYrOGtL7s8aHncdsXgHoRlxkBwShBGdMSgpqLKc4viUcTsg6CuiwI1ayjhGey6wW2nFqN/jqnj0mkUYQGtLRr2U/f4z6CAgr085Gn0+/u0VRZFx48YR/+65H+CHf/IHqbqKwAt4943fwZc/8/Wc8gsc3fitJP2GxnuR5z54ydNHX8xoz0d7CYiW1TpnsbTkZ2eE2ifMDaMwJB0nWJy90JgOpTTWWoIwpGkbUrtL4MdUdY0nBEESo+OY9XIJVY0KA2Q34On+LsL3Wc1myE3sgSddALlpOxpbIzfW0CcI4WIYPE+5DxOkcJr+smKxWOApj7PLC2ZXE+7cue3ei8bQhiHa94nThPTmTarRy0zOPoL1bmCMT388JEk1RA85e/kVEnX3db0ebNmyZctnK59SIfb1X//1fNu3fRt/5+/8Hb7oi74IgJ/+6Z/mL/2lv8Q3fMM3vK4HuGXLls88wjBAKY+uE/Q3Y3aeVmjtY61F+Za267i4uED6Pr1nnmG1mhFGPrPlS2TAThSRjIYU6zXeZvclDENM2+FrTRiG7O/uUdaVU8u37SZcV+H7/vUemPKUk2wYc60Et1i0r5FC0jQNRZGjtY/WmvlygVaKUAcURYnneRhprrtUSmm+bPBN/Nv5933Sz/0lvW8kVBEC8IOAwNeYtuXq/Jx2vuD23p6ThXSdyybD0u/18IOAqqoYj4ZUTUtVVwTaZ7Va0bYdSZqS7oyxvs/Zckk/SVl4U66mjzg5W/L56g/zOcG7IazpqTG3D5+irCum0wll02A7QxLHKClJEzfGWRQlTdPQtC37u3sMbt0kOrzHOJgwMCF4Etm2yOGAt9+6w9mjKaM+lGtoEeTrFUe3hui447xecVwpznSEd3CLd/g3yCYpe7tH+HHF2cUx88sWW0V0yyU39vbYOTpCCIjSHsvZjP5gQJat8Y1B4qICdtUt9CSgeQ0roRYhvWCfeX2GVwyQcUW+PGV5dkI/jvjxF/41/9vL/+L68VVX8S8e/StWbcvvfssfZDS+zzCKmJ5O6Q8z/J179FVDsVrzofv3mR/fYdjF9JMUJSUiDNBK4YUBy9mMNIrcuey5UOfWGKqupNMZspV40sUhGCEplWZqKlbre7xlJ8VLUmrP4+TxY8qrS/bSHlprfK1Zr9bsjsfsHxwQRSHWgrVmMz7rkWVrkiTB83yquibPc7J1RhhHdG3L7cMjnr5zh16/T2Mss8sLFssV6aDP4OiIdtSynr1MsVzh+Scs54LOVNQ0nLzyEtrb4S2fO3rdrwlbtmzZ8tnIp1SI/b2/9/f4ju/4Dr7lW77lWqWrlOJP/Ik/wd/+23/7dT3ALVu2fOaxs7ND27akG3tb13YoP6BYLWnrmqIoUEoTxzGN1nzs3gc5eXzB0dER3uAxsy6lWnnQtvR9H9t1GL9D+T46DZlMp/ibwsn3NZeTCVVVXYcoB1FE83FmxMAPKEvXwQqCwHXDamdTFNLthTVNS1EWBL6Pr12+GOCKtw4QArUJa/5du9+O8DzeN3kPDSWKgC/t/0G+PP1Wsrxg2O8T///Y+/N4y7K7rht/r7X2eOY71q3qqurqIZ0BAghJJIGQNEPABzAYH8KQSEJQfFB+yqSvB/0hoP7Ul0HDQzSKImCUKQ/iEAElQCDMGSBjT+nuquqabtWtO55pT2ut3x9r7X3O7SEknbKRZH/y6tyqe/Y9Z5+997m1Pvvz+X4+3S7joyOqqqTT6ZKeSKiM26dQKYIgoF/bGaSk0+tio5hrFy9w26lT7O8fMOz36Q76TI1lv9jn2iO7zA7HhEKSVyWhlOQHc3o9SaBS1nq3Ya1hPB4zn8+I44REBXQHXSqjkULSSRKnkhhNL+kzSjsE3S7x6k2G9pC9By5iux1edPYs1y5s0xumnH/4Ege7E4SNmU8NUaeDVQGPfPQCz/3sc7zguc/lHmN5dDphFgTcd+Uiq6eew/aNP+La+w2x6dJRirVhTNS/ja3TpzFpytH0iPMHjzC9lrFRFtzY20dVFUJXDIcjgiDgRZ2/yO8sBaPUeNmJ1xHkhixX5OUBHTOkshGj9Axx5ya/dv4Xn/Ta/M3t3+C5G/eSW0PV7TI/PCIGlJmiSsl0f5/1lRGqTOnna4QC8tkc5XvlitmMJA2ZBwcEVZdQJlRlzm/N/gPv2v0pNyMmE148/Abu7b+O7LDgHRfeyLsnP09lM8LdlHvv+Mt84anXYaqKFX+tzKZORRVS0Ol2fGCM22djodIaWxZ0Ol2EkBhrMcBca8ZFTnc4JEpSl64YRlivSO/vH9BfWyW98y6y5FEqHuPa3h5Wxly/VNEJzjAuYW8Hut3ncfqumHJ+7Vb+OmjRokWLT1s8LSLW6XR4y1vewhvf+EYeeeQRrLXcfffddLvdW71/LVq0+BSEVIo0iphHEfs3Dtg6e4ar4wnb9z/A5sqIQCqKomQ6n2OtRUwn3NPfQIuU7asdDranxEqytbZGEsdcv3GDTpoSRhFJFHP61G2UVYmQbs5rbXWV2XxOnucknS7j8RjtAzeklBitSeIYqSRF4eyLSZKgjVOmZnMXkx+oAOGtjsYYojhmnmWuQBpFZTWBUuhS8wXRN/LS21/Do9fu5/TKHXSjnovStwIZBGR5To5lfW2d6WzqkhtzTSAVoSeAKlAgJAaLCkImVcnambMUSpFVJWtxTC4Vh8UuV69dZLqv6VtLHEhW44RAScSpDlXh+qXSNEUKAcrN0ymlQICQEqXd60VxTF4UDAYDpAqIBn3yQHNj9zznDx5BCUG6vsbO4RGTyZhut0un06WbDpmNS7LJHh/6wz9kPp9y7txZbm6P2ds9RIYFD5cZ25VmDFy6WCDmZ7lj7SQhgrWTWxDFhF2IVsZ85MHfZPLwCqIo6EYhejqlazS90YhsNkVYSxJHvDD8ekRP8AdL1suXrn4DXzR8A0dHY+IgIEwSTFVhpgXCdLkymVOZ8kmvzcoWDE6tcWb9du7q98n2dpkHIUEcMep0WS0L7r9yhZvRgxR6izgMCSoNxiCU4HfnP827bv7HRdjG8OsQAn5jf6GQFibjN/d/AikFURzzu8s9b2bOrzzyZvYmj/B88deQM003Tijnc4I0YT5zNynAhbXg5wHn2RyMJUmcEmeMZn9/n93xmNl8js4LOp2U1Y1NgjDEhCHzgwPW1tcJTmySxe/jxtUHKbMcW1Zs3ziC/eeycmqNm9evc/u5O9h81pCdyQf5w/c/wrc//3/d74cWLVq0+HTBJ1Xo3O12+azP+qxbtS8tWrT4NMGNw0PSKMYIyTyOuXRzl6sXznNqOKCTpIxGI6QU5HnBdDZjUw0ptebmYxcZCkmqFCdPnmR/b4+9/QNWhkPW1lYZjUZEUYS1UFUleV4gBCRRRBzFlFVJlmUoITBCOClBCspKI0UBBVhrXTJiVSEQrixXul+VUkoQNAEdutIIIZFKoXVFp9sFIRFBwHg2pZgW3LX+XHrdHmGaMJ1MEFLR6XW5fv0GQsBkOqUoS1bX1pltb5P2ugRBgFIBxkLSScl0hY4j0m6Xm+OPcvWxA050N4k3Nzl/5SNMDwUdM+TOu1ZRUeTS8rAoISmqipvXrrKxuurmzrR2atx4TBBFaGuJwoB0ZZUgTZnoDJuXqLwiTBOycEY4uI6pJJunTzMQgtPDIWc7XTpVzGS/4ObOPqur6yTJKqtbEemlC6ycCCmFqxvod7o8OJ3wqLVouYnJBty28jzOfd5Jtq/eZK23zvCMpQofQO7tcfH8LucfsJyJbqMqVzl1xwqT7MCRBGNctxygy4hIKu7tvp6X9r6RXI45e+LZHB7NCZDEYUSv20F2e+xev043TaAo6FSbT9nZFauYzxxsoouCyc0dznS79OOYME0xs5yL16/T6XapxhOiQUZ3Zch0L6E62Oe3Jj/Br+38WPNcpc34zYN/j3yKf2p/a++nEU/xGXn/9V/jnuTVnOidoCoLet0u0+kUIQRVVTKdTimLgqwsKAp3PfbSDmVZIAN3nqM4Yb3b5XCeUezeZDqZsrYl0VJSlCXZdEqUpsh+yv7BY2zv7ROFKTtXBWb7LKeHAcXuLnefOoXajHj/A7/K9QuSk3HLwlq0aNHiVuBpEbF77723uSv8ZPj1X//1p71DLVq0+NRHPpsjtcEWBfHKiCsXH2NoLKYsqYxuYuK73S5pmjKeTJhOJzz37mdRVSVaG4QQ7N286eZlNtbpdDouNVEqjDHEcezDN0BKRcdarLVYQGvNweEBRmsODp0d0oV6uBARrTVBEBAEgSNugbMclkXZBCAYY1y5blWCdOXMRZ6TpClZWTCbTFldWaHT7WKBo6MxOzs3OH3yFEdHY8IwoNvtEkQxsdFkVcXhdEIQBggpkaEAISgAtdnDBDtk+mEO59ucPnc7QXLAQzv/hdIIbNxlMDrNkZlw/sEdwvmMRCpWVlfY39unF0fu/cQxxWTK0XhCVWk6Kx3i0QgVB8zEI/SGgiC/xsULu4zSOxnPLSu9kFAdMhKGtcEQXRSoSnPh0YtMDgtMniBVl1lm2D28wfb161gRoKRh83SPS0eWy1gOgpAwTdjsn6SX3MbGxoD+6CIH1UXCtXWO9nbZ3dvjo9vb2KPnsf2ul/P2XzpBWSiCSPM5X/QIL/+qm5g8JxSSSCrms5lTgLQmFDHD3pDH9s6T6D5ZpohUgAwCrl+76ub9plOSOGEt6fFFp97Ar1/9V0+4Nr/2eX+RU5XhepExvO006ypk+9IB4/F1bu5d53M+404evLHN/sqItTum7O28m0t7gmfd9QJ+6x3/nq98EH7pWWDl4jkN1ZN+Dqqn6HgDqMh5W/atvCR6NS8NvglbGZSvKjg8PGTn+g0Oj47I8pyqqkjThJMnT5F2UkJvTTyqKqqVGdsHO0SFYK3bZefaNghBt9ejE0eI9XX2zW+xc/MmN89vEGYJcj5nq9+hE0Yu6GQ6Yft920ynfZ6zscHtjwvqatGiRYsWTw9Pi4h9zud8zrG/l2XJ+9//fj784Q/zute97lbsV4sWLT6FkYxG9OKIeLTCfRfOE0wn9FZW2d3dRZcVaZKSJDFxnLjurCiizEPm8znzPPe2wIhTp07RSVPStEMURj64wDYlt3X4Brjvg3UR9gKGwyFlUbrZLqXI/PMqpej2e8ymM8bTiSuLtiCEU8eMMWAhUC56PIpihBBIIdFGU5YVe3u7jIZDEp+saKQinzli1h8NORpPSDsuZl4piYxjHnn4YUKc6hZFMUGcEA0GVN2Qnew3eegjHya0p9jc6nPj4H7CYECZxVy/nLM6HPLw5YsUuxP6KmBzbRVrLKG1xFISKMV8NkeUJUEY0uv1ibsdolMduoMHIM+5unuTkVzjdz70ISZ6ldO3GfYOrjAtErZGA84FilWjyXTF6nBIv9Pn8sUbPPbodS4+eo2irJhMxvR7fYIwJMsLwnCF/sYms6LgjtGQ0ydPsXNwQBEdEEYz7GFBOJ0xszs8dOkSHfkcbhs8j/f92vP53f+yDl4vqgrFe3/1WcRByEv/jwcY9HpYILQWKwV5VfCuo7fy+9u/0FgCPzv4Kr5s7a9Q3SwZJTE39/cZ9PokUYiMYr44/VaKsuTdez9FoefEQcKff/bX8Hc+/1u5ce06L7n7bqr5HCUV81nO/u4R526/i8lBxcmkx22nT3Nhb5+j+ZxnP3+Fj5x/G694MOftPwNf9Q3wi8/+4z8HoUyw1lDZ4kkfryh419F/RErFl/bfgK5KsvmMnRs7TMZH5FlOELh/xgsgm8/Is5xCa7SQGCmZ7MYcXs05naas3HaKK5cuc+7MGTKlYGOdnfl7OX/+EcrJOifSDYY9RXF0RCdNUUEAxkBluK3TpYxjRidO8IEHH4Q/+5Kn/wugRYsWLVoAT5OIvelNb3rS7//AD/wAk8nkk9qhFi1afOqju7HBWBd8+APvZyQEncGQi489hrCWKAiYz2dkWZc4dn1JgCvWLV2vVhxHvjtJ0Ol0EEKgtW76s54MUgrKUkPdt1QHYwQhw+GQnq44PDzCApPxhNl8RjftYKxBG4Ou3DxZEASOjOFCiqrKRcxXVYU1ljyb008SlJJk8zkW2D88IEk7nDp7lqIs0dagZESpNWkacfXaNbL5nMHqCkmakpcl4eoK923fz40b28wnlhOjL+Cez76dhx97N4HYZH//iN3LgkFp6Sea2f6c9V6PNEkQCKIooNcfMB5PSJLER9GXrltKKuTWKt3hg3xGFBEUOYMw4g8/9CFMt8vz7riNlCPW+iGb6yuMwpBiMiWMImYHU4J4wHs/9ACT7IA07bF5JuFgd0aQKs6eXWf3xiG3n3sW6II7hzHrUcRo6wQn4pgdXTGRijBJSAcDntPpsDOfcyKKyAPLo9uP8dtveyk8wbQnePevn+GLX3mZWZFjq4owdLNS75r9B35rKbCjtBnvLX+eQTnki7e+ndneLoNul7W1NW7u7mLmc6yUfPltf5NXvvDboP8QLxhtcSbu0rOWKoyJ8woztxSVZdhfZ3pgef+7H2I83ef0HRtsmYrHLp5nz1huXr7E3m6Pr71PAoa/eP9xIqZkgDZPVMVecOKlVNWQ9+z8/Mf8vPzO4c/xfPvVdGxEWVZMDg8RQnLq3DkmB/voLKfb7SCFIM8yqszlx1RZxuzGDZ6zvk5/ZcT1yZTh6dOoOxRV+WHe//BFlN7kxOpzuJHNme3tYYxhY20VawzdNGE8ndLpdCmsRRrNhfvvxxRPThxbtGjRosUnhk9qRuzxeO1rX8uLXvQifuiHfuhWPm2LFi0+xXB5+odUkzXuuutu5pMx5f4BUkkG3S7D4ZDV1TXKqmJ/f5/RaESSpJ50ufLaWvGCuiZMeDJWNUEGj4e1oHwYh7YWo42LibcWi0WpgLW1NYqiYDafuyJn3wcVBCFSSsIwpKxKR/hw5C+MwoaY1UStKAqUkIhQUJUFq6MVBisjDiZjtre36SYph+MxgQq4fOUKaRLT63RIOx2KskIEAQ8/+CCTyZSR6vH8e86xeudZdufvQ1eC/WsW8ogTUiODgJVuFz0aEgWuO0ogCIOQw709VldcuqCQwhVkdzoQJxxO99h+4AH2q5LTUnFl5wZjpVhbW2MzDnn2aIXxwT4HR2NGa6uc29xETnPuv/ZhtneucjiZkPW6HJYT7EpEv9dhlKzxec/5DG5eKbh5Y99Fqfd6nB10ORF1mI0L2MnZ6EQMA8lkf8xjVx7lsaNDrhQlF6YT9q88n6p48nNYFgFVPkCE245wCoG2Bb8/fXIi89t7P81zzFex2VslCAK2r11FCcnJk1v01jfQvR43i7dzdzBi3SiKy/tcm1fEUY/pYQU64OGHrzLPLI89dondm1c4ffsJwiBmb2+Xm1rzWJ6jp6fZUGf4Px9UgOFV98O3fjVUXpD9xj/zGjaQvOWPforMFCQy4pVnXsFLbvs/uBIEhLHlPVd/kdI8uVWxtBnj+TZJehIGGc977vOpCsGVRx9hfuhKQ3tphySKQUAnjhFSkU+npFHEaH2d7aMjxtMJalTw4IX3cPnKFcz8DhIG7F3IUNbStZbPeN5zUT6UZnV1lel0yu7uLtOjI4wxDDsptz3rWR/X57xFixYtWnxs3FIi9nu/93skSXIrn7JFixafgrh6vmTFHnEgU7LxmEHkVKlBt8fm1hZXdm6QBgGb6xte4bKEYei6tYTrTaohhPRfBUJItNbHLIkAeZ5TlqXfBrCAtQhACoGSypOokE6aIJVEScFsPkeFISDAWrRxqps1lspUThErq+b1waUpGqMJo5SyKEnShChOyPOCvZs3ySYTYqUQ2jCbjeklCWVZsra64iLIhUBay6jT5dTmJt3RCrbfY2/2AR565MNMdgYM5xIpBIGQ9IZ9jNZUlSYQkjRKCX1YSLfbRSBI0g5GCkwQcmMyYXxjB8KA/sbnsNc9TxBUPHDxAlmccDYIuGO0wrlAsVsYYiE40+vRM5Lf+cMPcvVon2tCMC4rulGEzjPSNOX5d5/jc0+cIL+R8cBHHuXqtauknZCDvUNObG3y4IcukeczhqMhwgbc9/7zjLObHCQVj5UlR3HM6Ts+m+c8Z51f/oeaMj9+DgHCqGLtZECW9UnSlMPDA2Zm70l7xAAKO0fLIywrjA8P6XY7hHGCkZKpkly7/i766zGFNuznGatRhZ4W3NyusDbj4oXzqBAm00MMFesnu9x9zznmkwo5K3iuFhSTHJFLXjb/KJ3MJTEOc3jV/fBH52Je/eyv5O886xu5spvz8s/5sxyJA25b3YQgpur1OCcVpzp/gXvv+mL+8W/+zSedJwuIeST6bX7q6L+4+PujlJee/RZe/OzXsbGzx+pggFQKGYaIwJWha6MpioJsPufG1StEYUQwmzF+yDBXz8EebrFSafpJ4cJmjGDtzGk2N0/4z0ldhN6h0pW7NoF0NORIPvHctGjRokWLTxxPi4g9vrTZWsu1a9d473vfy/d93/fdkh1r0aLFpy7WdcKgk6AODumEAdOjMSc3N5FSsr+/jwpDjJQEYUjtNBRCIlQ96+W+CiHIsowkSQG8RbBEV9bNt2ApigJjDL1eD601Wleuj8k/b10GXVvh4jhhI4ophyPm8zlHR0dMp1MqfEqiV5xc4bJAW+3+ji91sqC8KhaogE7aIa8q5nlGFIakUYQpCsqyZGNtne5wwGw6o9NJkSqgMoZur0c0GnFzNuXRvW1mFzOSlSmxvhsCiRRHbAwHzGZzgiDgcG+fQAj63S5WCIqyYGU4QoahK6SezZjnOUJJ4ihmrdMh2Nigf+oq1Vzy8KOXuaFD7tx4NmsrMePr19lLEuYTQ2Rzxhev8sCVaxxNd7mkNZtnzrBz/QY7synDfp9nnTpFNj7isdmU8faYcX6N0XqAJqO/lhAmgus3b9AfdrCyoCxyVFLRTxLmacA96xvctnWCnlL8wX338QWvOclv/PhzOG5PtHzey84zn+yyf3REIARJFDFMNgjFU5c6x1WP+XRKoBTdbhdtQSLYu3aN1VO38ey1m6R5Rs/C6c1TbM+PED34g3e/m/n4iF6/Q5BCb9jj3J2niYKI+x+6j2/8rh/gC8uKb1x6PaMUUmusUvzcz2sgB34B+AXOhSHv//H/LxexpJsxn7uxxXg85qGdy9x38TG2d07zGfKr+ZD5z094HyfDu/mtyc82fy/MnF+78C/Y7e3ztYM3sLGxgbEWDZTWuNRQUxGFAb00RVSaTjdk5ezt5EoyFcLdgDg6YnV1xR0XYynyjMOjQ6IowmjjDr+F3f0D8rKkqEqysmA6nwP3fJyf9hYtWrRo8VR4WkRsMBgcm8OQUvLsZz+bv//3/z6veMUrbtnOtWjR4lMTw8GAh88/SqIU3Shm0O8hhCCOItI4YZzNuXLlKqfW1ppwDSFEQ76ElMxnM6IwpPLFzHmeIwSEYYTRmmw6xVpLECjCMGA6nSCEaMINwP3ucuEYUaOiudJcSSQlQRjQ63Ux1nL1ylXm8zllVWKNIYpitHEkTAjRzIlJr8oFYUCcJszznHmRc3Q0piwLjNZ00w4ntrbI8pzdvX2EtXQGA8JeFysVk0By6eJ7uPTImJEQnNg6wfYFTTbPkNOJ6/rKC6zRCCyj0QisJUpiZrM5/X4fbS1ZnlFVmlAp+t0uSbdLqRRSKbqbcwbxmF/9vQ8wPTrHuTMvQtopxuaUWCprGY8PubZziZkwXCoKRisjTKAwUiIF9MN7GAw0H37sMU71e4yFQIUFs/UQGQYIE7Bxz52Igwmrm32UEmxsjcimFXHYYV5MuGdrDRNFXLt8iUcPDomM5jO+4r9z/VLJQ7/5PHQREMSa5734Qe796ktE4YBeHBPHMVmeo3PNn01fxW/PfuYJ19kL4lfSCVKkhdFgiDGGTrdLaQwnNjcpwkM+9OADdKTkc28/x6XHLrN95RBTpuiqRIYameb0VzoMV3poqfnI9ftITka881u+mpf/u7cTlFVDF6XWAAj/FZz4qsOA93/bq7gcKC5hORNF/Nx7/4BLkyk3jSbbv40VvcpnrH0ro3mH36870UTCCzuv5D2z//qkn6P7pv+JlVPfhsESRBESsFWJNhatDaEKWFlZIY5jiqrCGsPB3i7jyRSd56RJQllWHBweMZ1MCALFbDYjCEIKXw4dxDE7+/skgaLX7ZFlGfl0dit+DbRo0aLFpz2eFhH7yZ/8yVu8Gy1atPh0wgMffQhblGhjCAZ90s0NQuXi4qWUpDrkWbffvjTvJbyK5UhYpSuM0RSlU8Hm87kL9bALBayeHauJWhRGVFpTFM4+JqXwcfcS7Yud6+9b60qObVX5TrKK0cqIOI45PDzEWIO1llzPmdlDBuEaCR1XCi0lFoEMFLN5RlkWTKcz9xyDAd1+nyCOuHzlKv1ejyrPGQwH3Lx5k2xnBxNF7B8dke3tMZKSfielPDwimUxJsYTdHr1Bn2w6IwwjkiTBaE0QRRTaYIRAKOUCO4KA/mBANpszGg4I+wMOxDadjiIMP8ofvu9DHExSVoPTRHKV9a2AorrCLEjQYUBhZhShpLN5gi0huHBwwGOTCd2TJ7k+HrMWD9m7Omb9xDnSUcVHPnIfN6YT1ldXObm2xu1r6wSdlJO9FdK0S6XnzKxlbb3PbFyxf/OI/f1dZCj51WtXuVgUrKytkSYxn/vlj/KKL7/GeFcwXNFoO6ff32Q8mVAVBUVZYrUm7aS8YvQtKCn53SUC8/npX+DewTdjKoMKA38VCY6OxogwoDOoyMrHMCsrnFhbw6qArdVVhE6ZT0OMeQChDGFiiYYJ/23yLv7du3+ezBTEMuKLPudl8Iv/ipd8xz+hc/+jCK/ULsMKOLzrDO/4zm/kd7ohF/b2ONF7Ce966CJ71wVMP4ueDFiJQtZXBgyHA14x+2u8rP9abE+zsX4Xj+2f53cf+Lkn/RwVNmMsDhnodazSBGFEKASmLDC6IggDOklKt9thMptxNJkgtebcyS3mWc6V7W1m0ynXr28z6PY4tbXF+vo6cRSTlwWHsznXLl8miUK6vb5T3Yyh3+ve6l8JLVq0aPFpiadFxO68807e8573sLa2duz7BwcHfO7nfi6PPvroLdm5Fi1afGpCaTfjpZRiZTCk1+kQxxGBCoiiiDSO6XbdYq9W34UQVGXpSZglCiOKssBaR56ybBF04NSzhX3RGEtZlYShS1ysLW9a++TEMPJzZ27OzBgNwvWFVVUJFjdj0w+QUnB95zrvnLyV35n8v5Q2JxQJL1/9Rl51+3cxHk85OjokjSIm0xm9bscpVsYgpKCoSnb39xikCdPphOFgiLCgsGz0e+wcHrGiJJ0zpzl58iSz+Zzp4SFRreQZw2w8odvtYK0rbU77HVQSM5lnVHlGaQxpt8tcBVw/GlNJkOmEaXY/W6cEQ2143x++nws3Q9TsOXT6juhefPQGo62KWWS5Op6weeYkjzwy49zqKienU65WFYG+i4sXLdnNu2EU0lu7m/HNA96/dz83b4y489wLWT095Vkrfc71etzR7XDloas8dv4apZly53PupNIasMyKAz6qS4Iw4jAIsLvPYrR5J9vXH8QeHmE6FavrEUkcE4UjsvmMqigQQtLppKRpymw6Q0nJl698K18yeh0Ts8dqcgKrvUIZutk/pGR/fIQCNk+dYjIuuXDjflbWhuzuH3BibY2be7tMZjMe+OAVDg92OHP3Kr21Lr9w8Ju89aH/1FxfuSl4x/Y7+MyzZ3nBr76V6C/8ddR7P4jUi9lFLQUP332an/un38GHr11jfmMTPV8nmxSo6jS3pylBR2KtZTRaYe2eexiLC2w/aHnW6TuQays8duUhDnZKQpFQPknnWCRS1oa3c3V3n9Vej15PIJWkLEqstSRRzGAwIAwDtLFMpjPy2ZzHjo7Ispzx2Km0SRyzsrLC6uoqHV8d0Vd9omTKqNfl6GhMMZ+7ouiyRMqn7hFt0aJFixYfP54WEbtw4QJ6yXpRI89zrly58knvVIsWAPM5bG/D1hak6Z/03rS4lUiUBCnodXusrq7S7XSJowilApQUxHGCfFwggBACqRSRlEilmHrrIYDWFusLloWQIJz60QyCWYPRUJjsGLGL4gQh8N1g1mdyOPKW5znWz9uAI3tBHBHFq/yXa2/mN8b/sdm30ma8Y/fHKY3hOeOvYGUwwIYRnTRBSIVSikxXqAoyTxyssaytrGKw5EWOEoLr12+QTaesnThBXhRUnQ73P/Io+to11odDsJY4iUmSmECpJrxEW8vh/gFxp0O0uoYNQ27mORce+CDDOGa0usbOTLFx1+0wf5D//u73INQIpnewJgVroxVk3GF94xxnN/cZzOfctbnJ+MIlZpMpv33hIsF8ztXDA8b76ygx4rZIEFUl+c4OpdbI4Fk8//ZTdFYFRX6Z/dmMM0rx0fPnOf/YRbrr6yS55dHtbaIo5mhvj8d0yaWyZKoN490enTxF71TEOwNGKyn9XhejNWmnyzQ7YmJ3GaRr9JI+syzz1wDY0ima1go20tMUZYXWlSvN7vXJM3feIyHp9LpEScr+7pw+LyBmTtjPGc9nrCcpp8+c4vrlIyZZj6QTEkQBP/uB//ak1/G/ft9P8WX68/ni+x8m9CTMABJQxnLi6gEPnj/Nh8e/zUfNm6nICeYxL0q+hi9Sr2XrxAm01iSdLpmu2Dm8gp112bmxw+7ly4jJlBPdLn8m/PO8u3jbE17/FVuvA6Nc3UMUoo80WBdAI2Bhl5USrKXMcyZHhxRFibGWSEnioMPp06c5d+4cSimstVQWAiyDbo8yLgmDACkVWmumSeJnxFq0aNHifw/8aV4vfkJE7L/9t8U/Rv/zf/5PhsNh83etNb/2a7/GuXPnbtnOtfj0hNbw/d8Pb3oTzGbQ6cB3fif84A+CasO6PiUw6vbo9Lqsra2zMhoR+yhyKQVJ8kQSVqOe45rPZ1hrFzeEnPzl/iiM7xMDweL7QDPPFQYhKgjQVQVKNfHzGEOeZxhjG5JXJ8hJqZAWMj3n13d/6kn373f2f4aXnPg/CQlI/AyTMYbecMDOxZt044TBYEClNVEQYIVgd+cmUeTUPWEsJzc3KXRFJ4756Ac+iDg85Nzp0/S6XeazmSMYQYgQgtK4Qurx0RGT2Yz9vT1yrUG5Gbo7NjfpDwYkaYfO2hrV+gE3r++TzTbplHfQLTM2TmyggoDtm9foFDDPL7NalfTncz70wP1cnGccliV5GTLfvZNBmTLqOeujCgKKLKenFIPhEJmkTKtHiJN9VnobXLh8mfsefZQjazlZlkRlwWQ6Zacouak1MkqYTvrI6V10xhPuOLkCVUXc7xOF7vzEScR/334zfzD/z5Q49fEL+6/my4bfjDXONhqEztIahaG3LBowBlNpsrJEnTnDtYceIjWGeDjielly88YNTt95J53VfYS9TKEC0jTh0sOXOZhd4cydGySdkMNgTmHKJz3fc51RfuB3iI8W/ZmTQZf+0RQBjCZjuhd+kvtXfrl5vCLnd7Ofo9vt8tfO/hNKrRlrTXTqGmfkmAemc+zhFifDiHIgmR4e8mWD19ErE3776G0UNiOSKa/Yej1fe+67wMDaaIXDo0PyuQuEGfR6BKErHNdGM5/PmE6nFHkGxlLlOYFSxGlCvz9gfW2VMAyJwhBtLdYajDFUuiLLc6RUzWz4cDBg/+jwj/+Qt2jRosX/YnwqrBc/ISL2NV/zNYBbmLzuda879lgYhpw7d45/9s/+2S3buRafnvj+74d/9I8W6+fZzP0d4B/+wz+5/Wpx6/C85z6XOE2Io5ggCpvo+Dr6/amImNaaLMswRqO1U8AwS0TLp8EJgVPFfMAHgPT9Y/Vd/yLPXQeY1hhrMcb1ilVV1ahiLsxDNKEeWMtBfoPCPLkiUJIz0btsde5ABQG9KCTPcrSxBFIhfY/ZdDYj7XaYHh4RRSGRUkQqJUoSoiQmMpb+YMD6qVMcHh6xsrbG+UceYSVJsNmcNE2YTmeEUYgUgjRNSJOEqJNS5AXT2ZRgtEKn12NSVdiqAimZji/x/geuIrLnIOZTTm9uEsURxXzOHSduQ3cKMqZk/Qm/dfUqW2fP8llRxLUs46EHQZk+G6tDImOI4sgFg3Q6KCXZ3DrJvGfopimmlPzR+z/AR7e3MQxJoiE7V3MIZkSR5NzZM6wFAdqcpHPXKvNxwPiRXdKakFoDFtI05e033sLvzheJgaXNeOfRW9FG82X9NxDFEVEYYi3kRUlZla7DTToCXWYZlz/8IcQ8Y/PECbYfu8gkz9k4dRudtYLOygHJkeHcaIULDz/MY9evY0/0OXPnHVw+f57DXBOKkNI+kYzFMuIz7tsGwErJH7zgz/OOD3wWn8/v8SX8KhLL8979DvjyJ14r79r/WV5X/F0OpxXnr15F7x1xefcRgvGfYZRWaCzzozGjbo/pfMbz86/iM+OvIFNjhsE6cZbw0Qc/6moVtEFXJdZYZJpgTAfpKxqKLCMvS/LZHAEM+n26aUIYhPT6PdJOBwnM53MMligMUUFEWZUU+YyqrIhC9zkJQmfxTOK2pqZFixZ/8vhUWC8Ka5duF3+cuOOOO3jPe97D+vr6/4p9+lOHoyNXqHl4eMhgMPiT3p0/1ZjPYX3dfZgej24Xdnb+9MnOLZ6IX/iNy1jhyBFNSIb7WpOgGsarVFobbyO0vojZYLR2zyFcvL1S0pMxuUg+t4Bwz6+kI2H4dMWyLACnlJVlSWUMVVW5jjHpEhaVUoRhRB3fmFcz3vC7n/2kZCwUCd93+u1EKgVrmRYFaI0MQ6TRxFEMws1jOfLpgkbC0IWGBGGAimKEkhipmCgJSlFWJfk8Q6iA8tJjrPX7SOFCSwIVUFQVCEGW52R5RhS4Xra40yHp9wlWVtDpjPs++nvcOB+RzGesdLqsr65S6orR6TM8drjN0UHGaENhoss89+4V7pSKD953H3944zqzw8/i7tUzmCwjkhJdliilXEgKYDsdim7ClA9z5bFdQrtFYFICY0j7PcaTCd3hiLA7YfPOMbcFks2VFaaHh7zv4kUEL6AvN9h55FFWOymBCjia7fPP977uKaPp/9Hd70BoRVYUCAFKBeR5RqicGuTsim4+sJOmyCBgMp25nrdej1k/Ij1xP4Msp5xMOL+7S2YMn33PPawVBTd3drhpDL++/05+5/qvPmEfvuEzv4F/848/SHL9Jr/y2a/lPb/Ybx47xRW+lrdxeQDP/64nV5D+xUt+n+m2YTqdIoKAeRQxPzjkcDKnLy0rvQ7jyYQb1284BcuHy9Sfi/qrMQYlBYNej5WVVUbDAUmSopREa/f5Kb1SKKSg1+nQSTugJJU2bmZPCFQYEIQRwqvEuirRlXZ22DBCKkVlNJN5xhu+4u6P9RFv0aJFi/+l+N99vfjxcoOnNSN2/vz5p71jLVp8LGxvP/mHCmA6dY/fccczu08tbj2EdIXEeAthU1gEx0iYrpw1Ko4jwhCybGlBbi1SSIQnNBj/dyEIwxDtwzHCIMTiFa9KN8mM1hjiKKasyqaUWQo3X4MQBKoueXa/JqVfnMYq5Stv+xb+86V/8YT39QX9ryUJuwRKMZvPGQz63Li2TVCWdDsdl+4YR25+zVqEVERpShxGVFVFt9dHhiHhcMhBWbJ78QKzw0NmkymRrrBC0lUS0+lihQVLo+T1el2qsuDE+gbDlRVKa4j6fS7f2CGJSkr7PnJ9RCe5k1EQkIYhla6IghCbZUwv73L75ibp6DZ0J2J+eIHfvHKF89OMQH02q+ka4/09lNYkgyFRmhIohbGus224usJMKnYfGLJZdEiiiEgJcmMod/c4kcSkxpDNB+ijEY+aD/Loxcd4cPcm5dEWcXGD1FxnJQgwUcTRdEYZTZ6yrLm0GWU4YyXZctbOoiD34S0W68q2fRqmkgqhFEVRuFlCY1hbXWNrc4O8YyiDR/jg+fMUs9MoFfGRyzn93pzpbEZ/fY3v+Nzv5I77tvj5D/88WZWRqIRv+jNfz//vZX8T89l7XDoqed9L/qC5hgGuchv/km+H2YSg/JdU4fGi5kimBEWHUyd7aGM5mM748V/7cS4NfxSiGRQdth58DV/Y+0ziQBEI11YnrEVXJWZZCbYWISSBVMRRSBTFLhFUCITQWBsRKncdK6VYGQ0JggBjLWWlKbWmMgYLGGugMggEcRSjlbvZYYVAG8PVnZscBU9r6dCiRYsWtwyfKuvFj/u36Y/8yI/wrd/6rSRJwo/8yI98zG3/xt/4G5/0jrX49MTWlvP4PtUdjq2tZ36fWtx6aGOQSiGs9ZYC28xi1bC+B6vT6aJ1RVEUKKUwRmM1GJfI4VQwa+l0uz463lKVFXHsSmnzPEf6IuMwCNHalTJbv5ANg5AwCJ3lsTJEkYvMbxbwPjLfWoNSkqqqePW578Zi+eUrP05u5sQy5d611/JlK99CUVROlQlC5pMpSkp6nY4jYIJGWdNGk4+P0MB+sc+pk6dcvL41HNy4wUMPf5RwMmGzPyCRAqVi0iShkySUWqOkIAqdGhUFAdPJhPWNTVCScHWFnd09Ln/4IwTzGav6NBcPe8x2A9biOaOtLfKjI8q8oJN2uL59jRO9LqsbG+wUhwRRztbJDebjMfYgIt9N6KiMVCm6vR7WQlkUhN0u/cGA9NQpdvKPsn1ll+LwiK3RCAuEQUBZFGyurtIfDomShLDbZawCHnh4TnVwwJq4gzLL2BimRFFIGASNEtkbrhHdTCieIjFwvm+wag9rIQgCwjBCVxpdaaI4JptNSeLYkWljKYsSpSRr6+t0NjfZlQ9w/cpDXLp4k1g8D71r6aQpQneIeh3GyUe57a5Nzqys8iMv/Zt8z11/kQ9cf5Sot8ELTp3hxiM7PPzRhzl4bB+TP9FcUhFCtcIrfuUV/PKf+2WsXGzzBYNXs7c7Zk+4+bJ//Ts/w6WtfwHCbxPN2L79x/jNR76ZV539QtIkIQgChLVUWrtOukrj7mcout0Og8GQfrdLmsSEYQAWAqWIgqCpdIhCF4ojpEJiUQBSIK2rJDf+2rfGzZdZpXhs+xor3S6D/oDAWuzuzU/q89+iRYsWnyw+VdaLHzcRe9Ob3sRrXvMakiThTW9601NuJ4S45UTswoUL/IN/8A/49V//dba3tzl16hSvfe1r+bt/9+82tpjd3V1e85rX8MEPfpDd3V02Nzd55StfyT/6R//oY0qCeZ7zPd/zPfzMz/wM8/mcL/mSL+Etb3kLp0+fvqXvocXHhzR1g5bLnl9w4Xff8R2tLfFTBn6OS9TzXIgnbJLnGVEUu76uvCBJErIsw3pbH8KpSkpIvxh1li2BK1fGWpRSpMqlvWmjG2JVb1ejfrzf61MUzq4Y+MWrxWKNRqqAsiyRQiCF4utu/x6+5ra/zm5+g55cwZYwmc6YTSYMhgMOj8bosnRR/L0uSirSNCUKQxdJP5sxHI2YzeaMBgOkknSGQw73dnn0Qx+iJwTDXp80igikII0ToihyczwyJM9zotDte5zErA02kd0OOkl46Po1bj70MGae0ev3KXZ3WakUPSU5ubFBZQyzLGPU7yOBNAhQUrG/u0u0ugJCYvOMC9ev0+FF3PWC5zG5foNid5fSJxT2ej1UFHKoKx76oz9iks0pjo44ESeEgUt0rMqSYb9PkiT01tawG6tM9IM8dvE8EatsrK4gipLO5ib5fO4KuYMQhGB9fY3VlVVefuMb+ZW9n2BZbQL4gv7/SYS3RVqDsS6EQkhBqEJPugJnNVXufKpAoVQAQnB1e5sPP3yTTjXgnjs+m2sHu8TlYwy7PTpBiN6RnD79QpLwGiekYu/GjN2rB5ztbfCLD5+HMGb94IAbeo/3J4cMw5CojJ70cn/he15IlmT8+pf8OgExL4y/hhdHX09ZFBhglpc8tvbvFiSs+ZxYds7+HN3en2PU6zoihvXZNAaBs/eGUUgcxyRphyRJCMIAQV2/UBFFTnFN09TZYv0Uu11S1VABe7MZe9vbnNrcRClFWZZcun4dKQWjtEOe54RhwKjb9oi1aNHiTxafKuvFj5uILdsRn2lr4gMPPIAxhh/90R/l7rvv5sMf/jB/5a/8FabTKT/0Qz8EuEXYK1/5Sv7hP/yHbGxs8PDDD/PX//pfZ29vj5/+6Z9+yuf+ju/4Dt7+9rfzsz/7s6ytrfHd3/3dfNVXfRXve9/7moS2Fs8sfvAH3dcf/mEnL3e77kNVf7/Fn34oH1rhypQN6ZP8xqwqTZK4UIo0dSQsiiLKPMdgkAiQAqEkEhbR9eBJnlx6PYV53PPbpYV9VVWNhbEoC+I49mRR+Bh8qMpiESiiXaBHKBM249NUVUkpK5IkJo42XPS9MYyGQ7qdDmnqSBRSNmmDAsFkOuPg8JBet0tPBexcu8r+9RvctrrGsN8ny+YoqVxYgjWUZdm8HykEVVW5njSt0dYwlooP/uEfYvYPWPcKYa/XI1CKjrUw6DOfzZjNpsRhhDWGaTZHCEFv0Cfo9pgKgYhg/2hMkHZQas4DH/1DAt1FTKecHDhiBTDeP+BoMiEREJQlg9VV0iT151UT+kV/lueMq5Ibe2/j4T9SDGcpG6MSFYTESUI6HLJ3eEg/icmLHKkUvW6PKI745s/8PtJHU/7HVac+RjLlSzf+Ei/v/CXCIHRR7NIl/IX+/NQdcKE1qCBECRgM+lSVJstz9m7uMM8LzgUBt911J7PBEB55hDPrG4xWVsjynBNbJ6i6I0pzzQV4XNvlYHqT+3ZmXMok2dWrDLQm05pr4YD7P/+dvPS3XnqM4NcQCD7/9z+fd33Ru/jc7lfypf1vZtAfsLd/wHw+5/LuAXSewmMTTcllwMpo5Gcgna1XSkkcxyjl6hFcUqj7PLibEfVnK0EIdz5UoFA4klwnI2r/3+7hEY9dv04MzGczpBRobeiGIVLAbDplOhmjtVmkjLZo0aLFnyA+FdaLTyus4+///b/P93zP99DpdI59fz6f88Y3vpG/9/f+3i3bwafCG9/4Rv7Vv/pXH7M8+kd+5Ed44xvfyKVLl5708cPDQzY2NvgP/+E/8HVf93UAXL16lTNnzvBLv/RLfPmXP0nU1ZOgDev4X4M/zb0QLT42fvodjxL6pDspJWEYHnu8qkrKsiSKYvI8o9PpMJlMSdOUIs/cnXwf9iGVRPmYROmT8pZJmLUG6xevAMZa5FJgBuCCDKwliiJnXfQL3XpRr3WFkk4hqHTV9JNZC8ZoqkpTVWUTKCKEdDHqxjAcDlFKNsERxs8wFUXB4cEhRVVR5Dnd4YC8rNDAfDLGVBWh8PNv4PqhlCQKIyw4wuLVvzCO6A6HXJtnPPThD7ORJHTShDB05djSB34Iqbi5c4PV1VWU8hH0oYvCjzodJkJQFDndU136G4+ye+Uyu5NVqmsj5HQKZcXa6gppklJVFfMsoypdEEYcx66w2hPsmpCowHVZGQQ74zFBVTLs9QnDkCCKmM9npKtr3Lxyhc21NVe8rQKEFHR9ZP98noHSjPUuo3iTbjJgOpkShAFH4zGDXg/t5+XG4zGroyFpp8PB4RFCQK/TZXNzA2MMWVEwm86wwGw+Jz15kuvmIfYuBmwZ28ySnX32szFrXTonHuCz4pjq0iX++0MP8vBkQjF+FqpcIQwCcp0RY/npg9fypb98L3/2PX/2Ka/7H/6bP8xkNOMby/+HTthzc45SMi8rfsL+NTcb9ngUXf75s9/BqNdFBcqLZhYpFb1eF60NoY+qt97qK6S7voP6c2Uts/m8+Te7JmLaB3VURpPlBfPc9dmVunLXelU1xEvryv2cMSDgB779z30iH/kWLVq0+F+G/x3Xix8vN5BP+cjHwA/+4A8ymUye8P3ZbMYPPkM09PDwkNXV1ad8/OrVq/zCL/wCL3vZy55ym/e9732UZckrXvGK5nunTp3iMz/zM/nd3/3dW7q/LT5xpKkbtPzf5UPV4tYhTTtEUUwcx08gYQBFURBFsf/qbFW1Qi1waYZhECL93X+LwArcV4SLo8fNuyAXJMximz83Zc/grFxSNCQM4Z5DSOGtiJJ5NnckDJwaZy3YhTIgpSRQzvoWhgG9bpfhcEgQKMIwdD1kUvpAEEkYhHS6HYqioNvvM1pbo7e2xqQo0NYSqsDH7QfNLJg1ljzPwcfyl56wHh0ccuPqNQ7Pn+d0v8/a6gphGBGHoZuHswZhnao37A/oe5VMSKemVVVFNpsRaM2ps7czGPYYj4+4dDjGqB3EwO1Lv9dDWMs8m1OWJQLLcDBoFM069CQMQrRxds8syxAIokBx2+YGcRgRhAFlVTKfTYmjmBvb1wi9claT36Is2T84YDrPCMOA1eE6J3p3kIQ9tDYknQ4qDImjGCsEs9mMqqoYDPqU2lDkBXEY0O10QAj29g+4ubvH3t5eox5JYL6/z7UHNWoyQSo3a7V+5xl20kPy8AGi+YxTWKoj2EhTtO2Qqi36ZcmKrjirYk7Hfb5g7et5xyveQREUT3rNF2HBpDehEgXRAFZXVjixucHJrS2e96y7ObvzzWAfp6ZZwV37f5mVfo8wConCiCiKCIKQJImb2Th3ObsbEO69uf8av44QJHHsCLFZ3CyQvhxdCkkcRfTSBGMNuqzQZYXRGozBGg3WkzCe6KBs0aJFiz9J/GleLz6t6KPHx0vX+MAHPvAxydGtwiOPPMKb3/zmJ+0s+4Zv+Ab+63/9r8znc776q7+aH/uxH3vK59ne3iaKIlZWVo59/8SJE2xvbz/lz+V57hZDHkdHR0/jXbRo0eKpYIz11ipNmibMZjPiOGkWlmHkoucDFbiUN78wXC5hlku/o0zzfUfGrOXY4wKXrmjqYmgfqNGoOkrR6XScQlA5goGtZ2ysm9XxVknnZBQEyiUuBkGANdYHfrh9M8ZC4IhZv9vBSMH5Rx7l8OiIQb/P4WTCXBtWRkPyLCMIfeJdoIijmEP/O0f4dEAERFHI+mjkXs+6dL0oitBGuy6oOEJqhYwE83mG1hWjlVWqqiTLcrq9HtXKiGrlQVY6BSvjLvfPobh+jvneDVasYbSeEieJtwQWFIU7nmVVkiQJs8MZ3U7XqY1CYqxLpqyVmsn+PioRHJrrrHa20Lk71idGI+azOaFSJGnKZDppZpuMMcjARfTneeGLhnWT2FhpTaCNKwL3wSp5UWB8KqcBZ2edz9HGEEUR8zyjLJxiKedzzsYRNgyREn7p5r/mXQ//DIWeE8iIP/fcV/HiL/r/cP3GDR49uM54d5Ph7CZba6vovEApgbCGL05fi103vPsl7+EL3vWSYxZFi+X3P//3qcKKSKT8mXteQKw6vnRcEEYR3/Xyv8T/81uK86v/DqIpFF3u3PsWvudlr3Xn2onAhGFIWZbEUYyxhif8U1zPX0pRX8aAS/1s7rxa22yjhASrMNZQVRqrNdYYBG7+EgXKK2xG2ebz0qJFixYtPnl8QkRsZWWlSTa75557jsdMa81kMuH/+r/+r4/7+X7gB37gj1XQ3vOe9/CCF7yg+fvVq1f5iq/4Cr72a7+Wv/yX//ITtn/Tm97E93//9/Pggw/yd/7O3+G7vuu7eMtb3vJx7xM8NdGs8Y//8T9+xpS/Fi0+FZFlczqdj3fgX3hipsjzvJmPahbpuKTE+n81Kauqqgn1WLYlCnGchNWoyVoNaw1lZQhCF/iQZZkvdXYR38uubimlU+T8wldJ5QNDOL5o9ml0SKcupEnqCE1Z0ksSQt9vphhgretLC5TvP8Ml+h0djQl8KXX9ZpVUTRG123frgk6whEHo4t3zAotFhSHSWBd+UhbMxmOSbpdZnmF29ziqJHZ0nY8+8EdMxmts5IbVNEEhnP0Qr7AJQZzEjmQKwXw2dz1pLMXH1+XYUpIVGb8xeyt/MP/PlDYjFAlfOHg1/8fGX0UKSX8woKwqDDDPcnpdl5YZhgHGWMbjCdorMkpKyqpqjv3MWyRDr57mee6IehhRFmNHwIVA4giFCgIXx24NJispC2ev/JWDH+M3jv5Dc14rU/D2j/wsK1pzTn8mD9zcZFid4uQgpRvFXLxwkdGgT2c4RFnLl8WvYf61GfPkUaJ37hGUiiIs+P3P/33eee87AXjF1jfRSwaNfdZozWw6IQwC/uZLvp7DyVezfTDm9MkRw+e6mw+6Kh3H99dtmqZ+xtHdLNBG++fz3xUSYZ191c0kKgKlFh12S6qwNa7aoSxKqrL0RenWK2a+WMJKkLYJr2nRokWLFrcGnxAR++Ef/mGstbzhDW/gB3/wBxkOh81jURRx7tw5XvziF3/cz/ft3/7tfP3Xf/3H3ObcuXPNn69evcq9997Li1/8Yv7Nv/k3T7r91tYWW1tbPOc5z2FtbY2XvvSlfN/3fR8nT5580m2LomB/f/+YKnbjxg1e8pKXPOU+fe/3fi/f9V3f1fz96OiIM2fOfMz30aJFiwWWO5CeDMs8afnGSFVVdHxQRJ0KV8+LCVx4BUCgXEJerXzVi8cnI2Buf1znGLhYfGsMWEvlQznyIicMnBJRV54JJ68h/FyatW5hraRaJC5aSxwnzYyZFbigEQNI9zPdbpeoLJnJOWGgkL6UOAgCAhkRRiFYizGWw8MjytKpT0I4KyV+gW4qQ6/nAjpKbcjncySSJI45Ohq7wBKtKUWF1hVlVVLkBaOVEVIFzLOMNE341Qs/zW9v/zilyVFEvHD49byQr2GUdrDGokLZzPapMHCJk9r4Y2AdAVZODQtjR8ykFPzW4U/x27OfaY55aTPeefhWpJS8vPt69x6t4eDAdX3NZlMCFVBap4RNJxPSjptFm0wmJIkjhUVVgoXhcMB8nhGFAUoKhsMR09nMzUop6dRTXREEbp8LY7C6IpSKTpqS6Rm/M/5/n/T6+OkH/xuvDF/JPf01t5+64uL589iqpKMUd5w6BSpgVpYcTCbsffkdXP+8AQ/M/ifv7f0S83BCJFNesflN/IVTf2NR2eCfv+6101qThoo710dEUeRVME+4hGiO8XQ6bX4uDEOUcvUKbj6MZv4xjmK0rqiqirIoiaLIfRa8jVFrjbEuoKYoCqqqdAmh7smP23itxWjdErEWLVq0uIX4hIjY6173OgDuuOMOXvKSlzzpbMcngvX1ddbX1z+uba9cucK9997L533e5/ETP/ETzZD9x0J9d3jZRriMz/u8zyMMQ97xjnfw6le/GoBr167x4Q9/mH/6T//pUz5vHLvZlhYtWjw9dDp/nJF7YauyXsUC3CLRf/ZNbR9U7q5+kWeNWgVQ5Y6URVHUKEpK+thuH5ZRlW5hHoQBVnuyFiiQiulk0pA76RetdUCIELVi4BfACNcTJiVauzmcMFpEqyupGnZZq2cY190EeLKgmoXvxvo6URgSetWvLApu7u4R+JkvYwxKqaacushd0qOxlul0RlkWJFFMJ02xQmC9glhWJQJIul2yLCcKncUw7QT0ej1+ee/f8s6r/6o5C5qC3z98KwVHvKr/N9xrFSVKKWd5NNr1uwlnw5TejukIW4D0x73QGe86/NknPdPv2v9Znpd9OSv9Vaw3va2sjJpode3T/YajEXEcEUcRcRgxGPQpyhJtLEWRU1aa2XzO+toqeV5weHjojqc1aO3Kvq11HXaFDwQhCP3+GibFPuWT9JUBVDbnzKqkzDVXrlwlKAoGUcTpM2c4vXWStNcjiGJS62bXBqMht526jRcmL+INyQ8wtfsMww0C4RQ74clMFEbkRY7WsrmundDpH/czlFEUoZQEBFHk5w3rmxNaN8SuVshqtVBXupl7DKOwmQ+zCIxx13WR5+iyAmOQQOCvz3qObOEOsVilsNYcv1PSokWLFi2eNp7WjNhyAMZ8Pm8ilWvc6uTAq1ev8vKXv5yzZ8/yQz/0Q+zs7DSPbfnGtl/6pV/i+vXrvPCFL6TX63Hffffxt//23+YLvuALGlXtypUrfMmXfAlvfetbedGLXsRwOORbvuVb+O7v/m7W1tZYXV3le77ne3j+85/Pl37pl97S99CiRYsFpPzjqyHcjZRaBYDH90gBVGXpupJ0BdYpZm4GzJMuAaaO27ZQ2KLZDt89Zoxpkv6klOTzEuMJX1lWLqRAWp8EeDwmX2tNksRIqVxJtRBIP2tWz/+YpUwk4dMdfR4I1koCqbBhRKACl6InBFKpJmlRKYWOE6eGVZUrLdaVf+2EqQ+8MMZgChdXrpRkNFphNpuyt7dPv98njGOyPCdNEzcLZDRhGNLt9kj6fUw34Nfu//EnPRcf4n/wNfKvYY0iCh05VNL1s6VxQhhHhGFINs9I0o6fgzNOuRGCneLqU5Kckox4CN24Q1bkJJ2UXreH1prpdNrkTSglMZUmNxlCSMaTCWEYYipNmiSkFhQQhaE7pnGMUtKXFy+i3utQDykleVmQZZmzkhYpoYgp7RNv3AXEpAy5dvMmQVkQScnm1gk2T2wRdjrk1l0LMlB0ej16atiotEjJ0DrHRZbNkVIQh7FLhwxDd6MBgdUGHblQDGGt33dFHMf0fG+XsZbS77O1bl4sjqNGkcRfn6EKKHVFGCiSOEYIqIzxwTa2IVPuedy1XZN6R9ZqJWz5A4mbHWtJWIsWLVrcMjwtIjabzfjbf/tv87a3vY3d3d0nPK61/qR3bBm/8iu/wsMPP8zDDz/8hKLlWvVK05R/+2//Ld/5nd9JnuecOXOGV73qVfzf//f/3WxbliUPPvggs6Ua7je96U0EQcCrX/3qptD5J3/yJ9sOsRYt/sRg/eJQ8Dhn1LFFoBSuK6nIC4xXTSrtFrIaTWl9jLp0AQ5OLbOelNnG8lgTsEaR8K9fNEoDSCvAGMIwcv1hYYhSypc9+yS5pZ+Xj9vP2g52HJIoin03mW6CKIQQfgEeecXNUdDTZ05z8+YuR+MjlApIk5DJxFkOtdZ0el2XZOj7xR577DGUEHQ7HaQQHBzsY60ly53NMopjkjhBhAE6SdiNL1DoJ++yKsmYc8BachorIJtkTgEUgjiOCCJHLFQQMPVEB2gCVbqMCIkpeSLJiUTKevckURBjccmLs/msUYKkECRJ7Mhjc85Ec5xEvJj/C4cDH9Ti0wOb8+qsndZoup0UpYLmd7zrxHLpj/fK1/Aru08koy9KvgYx16QC4m6Pc+du59SpUwjhiEtuDfM8QxWSKIqIhEAGwdI5t2jtrhPpbxDEcdyQIKkkYRxhjE8pxLpZQeX2vShLwjBACkEcxc0snjb1MVl8NrTWBIEkDo47VkKp0NbQyF04tTjPc/f6IvBq3CIJtA5ZsfX3VJ3I+KSXSYsWLVq0+ATxtIjY3/pbf4t3vvOdvOUtb+Gbvumb+Jf/8l9y5coVfvRHf5R/8k/+ya3eR17/+tfz+te//mNuc++99/6xkfPnzp07NmAPkCQJb37zm3nzm9/8ye5mixYtPklUVUnubXb4JMOqqud6qiatLc9zitLFhBvjZleMMU2YgPBhA8aHGAjhtzPG6Wr+94CUEiulS9jzhMkY09jihBAuIt+CxZcUh6FTP3x0PsJF50u/b7XqUKPehqXvuOem2YcsmxOFYdO5ZS2U3jYpBCAlnbTD1gmF8krO0ZEjZN1OSp4XLsgkCBmPx34+yEW7R0nMdDqj1+thjSXLMvI8c7a3OKZ/cguxVbIaa2IVk+snI0sJquhQUKCts10GSlFiMECWZe55i6I5D3EcuSAIaYlkwov7X8u7xv/xCc9979o3EoqYbD4nDkN6oyFJ5DrJLK7DTVe6+ddKLhOtmnxYgzAWWKiIQaB82XHg56dq8i3dvllHFLtd162Vph3+ysYPEt8f8T+2f5LSZgQ25rn5y3nu9GVMkn1Wej06/T69TtfZUZOYsig5Gh8xn81QUjHo9UAKwvr68iTMGHeD0tUGODJm3QXgFFBtUGFIoA3WB4qIOCHLM/AhI1EUOoulN3EuF5jXw4vK96CFYfTEmUjhyx6EbHrChBAI65RaKYV/HjcnaTgeSuPsuKK51lu0aNGixSeHp0XE3v72t/PWt76Vl7/85bzhDW/gpS99KXfffTe33347P/VTP8VrXvOaW72fLVq0+BRHls2x1pKmSWNdDKOQPM8Jw4iiyMF3fVVVRSftMJvP0FVFURaeQBm/QBWoZizLpQs2RM0u5l/skjJmrcUYjfaErVbcBAFISRgGBPVMkVcIapvi8u2dmoQ1M25Li2SeYgErhCQIQ/I8a4IwAqWccocAY0G6RMWNjXWsdSXFVVWxf3DAZDwmSVzvmiOLbi7OWEM+z4jCkDzLSTsdoiQhn89YX1+nu7lJsSIYdC5wj+rwVae/lP908RefsH9fvPGXWF87Sbfb4ejwCK01eZ6TJIkrWwY3a1RVaKPpdXsMhgPKsmI6m1EWBZ9b/Xls1/D7s1+gtBmRSHhx9y/yhfE3UBUlnTghSWLSJGkSJ7XRzrLnLadODVNIdXymShiaomPhQzBC5Wb/XLFx1ARNWOuIvCOL8dK5EigZ8qrbvoM/q/4iF248SJAlDAZ9Tp7YYm1tFRkElFVFXlUcHh6S7+xweHjou9Kg20n9ma4VLeVDNiBJ0uYGQE0ghXCBMEeTCcZY0ijCRpZ8NkMazXR3lySOkLjicGM0URQzn01JO92lWenalugsuaGf/auJW31d1jcFsixrPg/uQdOow/XzIAVo925qwieFO85SPa0K0hYtWrRo8Tg8LSK2t7fHHXfcAbh5sL29PQC+8Au/kG/7tm+7dXvXokWLTxsYY0j9fNECwilQfqZHCNnMd01nU7R2811FnlFVGrBIqQiDAEltF3TEShuNXlLCFAYpFMLb1rTWVLX6gvWL0hDnMJONDc0uWbdqNWwxe3P8PdXhE/V7qb/r7F6OIFpjieOIqiybcl6l3NdmG/djlGXBfJ45xScMyIqCOIkJgoAizxHSlV0bbw/XRtNNOwglKYoC4ojcGLZuv510a4uiWxKMHqSbF/zOB9/LqfIzeFZ8xPn8PVRkRDLlK27/q/yFz/x7HBUZmRbsbF9npBRxEtNdWUFPJxRHR6yurZFnGUmaYC1cv7FDICWT6YTVlRU21jb4KvlXecXo9ezn2yR2QECEKTVW+i42f4zrWaW6s622izYEBtEc60btYtFxJaVLbazKys1haY30qZFCuGTMJEm9PfG4etnpdLht6zSD7oj5dEKoFGmSIlVAGMUQRlTzGUobdm/eZG9vj7Is6KQdOmmCwCJxZdHC1nHyoikndwmH9b7DeDxm+8YNyqLg1NZJbhzsk09nnN3aIo1jtNHM5hmBt6sK4dIQa3pV77kUgqyoyI17nTiOKMuKMBR+VtFtX1c/NCFW1lDPYrprT3mlzMfXL92oaErVW29iixYtWtwSPC0iduedd3LhwgVuv/12nve85/G2t72NF73oRbz97W8/FmnfokWLFk8GXVVL8zsOSZI2Edy1miSlcsl7yi24HaFypKnICxfBnuVkWYau3HyUs2Th52scjVmeDXNWLItSAbJWnYxGVyW6rBYR+EGAUEGTjugCDdSiJNdarFiYtJrF9dL79JshxEIlqx+vaQNSOAvlUgFvvQ/GUznXaaY5ODzAWheSJL2yIaRwoSJAJFWT2GisRWpXaFxlOSoICMKIldNb7OvLHJiHiWcz7kxWubl9nftv7rAXx3zdC76X9a0Bh7MDumqL1dEaQe8+ent77GU54emTHF4uGSnF7viIq7t7rIcBB4cHFHnBdDql0ppOJ2U4GLC6MnJmN28RjU1MJ+5hPVmsgyLCMGzCVUpTNj1qpu61shaMxaCbQuLmmFrjzoNP+bPWYLQABWVVOlXIGoQ/PlEUeVImnkAqVBCgAQ30h0MEjhiXWLLZjIPJmFGvz+poxHw+czOARtPtdhkNR/T6PZIkcUEiPiQGKbwCazBmiZpLSb/fJwjCRrHqBCH9lRVKXZFXGl25RMMocjODUXQ8MKM+TkpJoihsKgSMcderI2PuxkSWF40d0R244/NgdciKlBLrO+zM0o0GIVykfaOktWjRokWLTwpPi4h98zd/Mx/4wAd42ctexvd+7/fylV/5lbz5zW+mqir++T//57d6H1u0aPEphms3rtPtdIniiEAq15m0lI4ohKAsS8LQkTGlFMa4mHprnQo2nU7JswxjNGVeUGmNkk4ZkD7kQUrpFtz1Qt7WIR9Bk0xojHGrbuuiwOs5s4DAKUxKESjZBIbA4mtt+HKFT+IJM6jLsAiscApYXTxdh3PURLEsSsqyJC8LDvYPyIu8CezQVdXYyQbDARoXtjDP5gRKoQKnVkgpKcrSKS9Yp7QpRVmV7N3cYf/yJUoh6KyP2HjWnN0bN9jeuYHudEmyEfNyHzO+CUdHbOcPMgzPMdjN+dAjj1AlCTuTjxLt3kMVxSRxTCfPmc7npHHEyc0N0m6PvcmERLoiauRSKAoc+1fnGAkyFl1WLkp96agtE1xrnbJZk1P8vFht/xMCtLVYIzDSICrRhGE4Mu3IWJ2aqKvKd2r582MtR0dH7OzeJI5jhivrjTJn/fXTiROEFOR5zmg4JIkTl1QYhqRJSpzEhIGPinfRiS5xEIMxdZiVrzJQjtjH3lZ64/oNIh/yURQFVVFidNXcDHCdbRVxp0NlNIEMPOmy5HneWG6VUkjpAqqklMznWUM6lRRePV5cy26WkqY/r7EoGtsQyIZILoV9tGjRokWLTw5Pi4h953d+Z/Pne++9lwceeID3vve9bGxs8BM/8RO3bOdatGjxqQlrLNeuXUMpRbfbZTgakiZpQ8aMdpUYZVkRxws7VF26XFYVk8mE2XSCxJElYS1KBi61Lo6IfeCDkf7n/NoxUE59qeO6tfZzSH6RarUrZQ4D5aLQlVoyGB6f83LBIN6CKAGeSMaEECzxNowxZFnmFtBekTg4PCSbzwnDiNl8TlW5rq4oCAnD0EWRe8tYHWRSVRUazTQr2ZsesdpN6MQhgQoaEgpuHioIu+jCEAvJHRsbDLdOIk8Zkk6F3t5m+2jMxUs9gkmH8GafDwYBUp5gtBkxlgdcvXGd+x4bsdV/FlWWsSGNCw3Jc/Z2b9LtdFhfGdHv9dBCsL+3SxoErK2suuPhya0RAolLspTUapafzfPF0LX1c6FELqQv6+f3TG0xFQuiJbx1dXHc3fkIAoUKQlQQIIUB4aoODI4UGaMbJdIIwY3dXWIVsDIcUeRFE/FeliWVrjCVi9VX3gYqrLNV6rJkWmmy+QylAoIodF+X0hmrpULkerbwcDp1SmdVOdtg2EdXpQ9tcQQokBLlw0cAqsrdMCjywpVnG/esRaUJpfWBMu44FkXpj/Hx4I36ODezk7V6hyspr8NQ6u49bUq378a2PKxFixYtbhGeFhF7PM6ePcvZs2f5wAc+wL//9/+eH//xJ++iadGiRQuAldEIFbjS5PFkTFkWKBWwtbXlrHk+oMHZC+MmorsmF0VRMJ1NGR+NUVIyGg7odbskcUy31yOOY8IoQkqB8UmBcRQvzWCpZlbHWOPmqoxBSYGJ3CxM5JUN4YmcpE6U8xA+lsFar3oct4vVkeLWzwlZazkaH1GWJePxmKqsyIrcL7gtSZKSZS74Qlh8cqBLSBTW9UBJ4cJKytIpgD/5/rdz+cS/h2gGkw5ndr6Zb3nBq7BGN11mVVFSBjmJnzeaTCaY+YyBusCl99/Pex+9gpg8l3QmOL0yYn1tjfl8TpikDE/dRdr5APdNpqyL53BbGJIb11N14dIlsumUOAw4ffIk/V6PMAwJgWedPUvpbZ6iPj7U80Zuhqq2Kmrt9tX48mGjtSdg7uescapXrRpqo12qpbsgmnJklmLWrTVYIZrgFik1xkiQ0qUBGjc/VpQFutIYT3gMFnRFoTVXr15lNpsxnU5duIW3MsZRSK/Xo9vtug610MW+m6pyP+/JX6g1URRifIy80f79GQPCzwEKgRKCThgRd3tEUch8OqMsS6w2BEq6qoEwJIqjpszZFXo7ghYEThUrcNUEiU+BjCKXOKo1nui6mP4nBMZYV8FgtGnskRKfzCj99esj/q0Pu2nRokWLFrcGt4SItWjRosUngl6vR5okZMMhOzd2qIxTEq5cuUwcJ67XKAyJCJu7+NYCQmKFQGtDWZaUZYERAmFhZWXEaDRazJd50mVMhVS+3ykIfK7eIkajXpS7+bKQKIoJwxDp49OFn++h7jXzHsVjSYneUimlQEiFtZbZdEoUR+R54WxmVcn+/gFlWRLHEUmaIoMAFagmnAIgzwuifh9tvN1NdNBGU2Q52rhExCiO+Be//TNcPv2v67hAiGZcOvUWfvy9gtf/ma/GVCXGWjqdDlEUMZ1O6XQ6jpweHnLx4YqPXp4RXn8O63HEbedOuRTELKPICzCW2eERD2xfpMi79Ho9bhwcsL+7i6g0pixRAvrdLoN+n8HAzQd3O12UUmT4uT1vSVSy7qBaqC3W+gJrBFZKAnAEym+jpHJzfIDQIFSdROneswqUUwB9X5ylPjd1rLsjKkoF7tzggjoWCZq2sRzif6oTxRRVRZbNKYuCqsjRpSsCl0r5IA6BqhU7bz80Ujaza0pKVH3d+NdxSp4nYVK5/QoC4jhm1O9hjGU6nVBWJbp0imgYRnQSlyYZJ4mf3TJ+DswRVnSFChSRsWwM+v5mg2huBGhPbJvr1AebCH+sjLd3ovCkeVEP4FIf62NGY5NtFbEWLVq0uDVoiViLFi3+RKCCgMhaRqMRewf7GGM5nEwRkwmBT6rr9/tIKUnTBGQdoe0XmX4xG4URaafjwh7ABWrU/VKVS0LEuqJggYukRyxSDg0ujjsgQPmUxgURw8+A+XmmelDMF0Q7W+IifsNYgdEV82zOdDZjcv26s6NZQxQnyCAgjWOqqmL7xo2FYuYTSsIooixcP1qWzRmNRq7I2NvxLCDlnKzUXFz/8QUJqyEsj238BMhXEcfOoigQrmxZuTh7XcEwjBDxc7FHU051LSc2N5nPZuzv7rqZK0BGIfraNVbKO1lTEhlaLk8mmPkcaSFUkjRNOXlii9FwRBAokiSh7mIz1jjlURivcClfxLwIODHGIJQEq1D16t6HQ9TR7+7IWqxSx45VHaCiAtVYEo/1twlvWfQBE/iOLGE0VipE4EigDepKA5eAabRBVSWhUiRxzLDf84qQQHkFKvLWVqVUY5etT4VSytkgfaG08cmXUuDnEp01VipHwGXgAmmKImdytLAPKimJ45hur0sUOjVMa4O2Tl2ru/OsktQCoRDOauuOmyNhaZpQ5DmBtxgaf/x8niO2cspXiPLHM3BKohTNPGMg1cLC+bgs0BYtWrRo8fTRErEWLVo846hDKlQY+DCBOWVZoXVFkiQYY8jLAn14wGw2I4xChoMhUgoyX1ycJDHYPt04Jk0TjLUUVUWAI2sWgbYG7e1sSoCoKiy+UJdFEqMTRJw6UGmNkBIlVKOAWOmVFp/oiHbKhvGzQwaYz+YuxVAp5vMZ83nm4vD9rM7R4VHz/qWUdNN0keIoRNOfFkYhAkHlgxOOjg4B6CQpYRgQRTEfeeyKsyM+GaIp1w4O2eqljqAqQRzFaKWbWar+6gr7xSH3nD7L5uoa071dZFkwCgYURU6UOLWuNJoiz7FaM5tOOdrdQwFJHLO6MuLEyZNsrK+TJCmBCiiKgrIs3ayX1i7DxJOwQMpFMIaflatTMqUQiCBAKqeC1aSivlaMMS7i3smijsAI4Z9bOKV0yTNXqzngiLZLuBRLjwsgwG/i4MMqKqERWAIpiaPIqav1a/r34C8e9348KVRq0W9Wx8VbXzRt633yJK62JbJktwUIorCZO4uj2KUv+jlB8LNb1qunPuTF6rrM2pFJ6WfjapKv/bxlGLkuOTcv6Qh6U1zuMvaJIneTYJmE0dxsEEjh6iE+VihNixYtWrT4+PEJEbFXvepVH/Pxg4ODT2ZfWrRo8WmCWn2oSmcB08aSxDFSdcjzjCRJfBnwHJNaJpMJR4dHKCVJOx0slq2Tp5hNJyghUVHkiJcx2Eo3hbN1sIOxbpEthAAjXWhD3UXl7YZWKm9ds44EaYERrodMa4v2pKoyrsy4KEuyeUZRFL7YeOa+zubEcUwShRgbYI310eJxMyMUhiFl4Yqq6+CQuii61Josy8iyHGuNCxcJFN1uh5WVVbCWz1ABXO88ORkrutx+ZtUZMK2hqAydJEEIiNIOo7NnyToV+xc+gOr3eGj/IuVuj1WpmB8duUJl6cJAJtMJN3d3mU2mCGMIA0W/0+Xuu+7ixOYmYRT5kAwfQpLn6LI8XhbsO7VqWGNdp5s2dVpHY1UM5UJNWtj5nJkUyyJAorYjetLREAMf6KLkQqmSdcKisRiv1tXkWKnjFQqVBRehKbxFT/gqhGBBxABrdDMTKNVCRQqCoCHWWmuqmsRYR/7CwJGwWl112y5IZBiELlpfKsI4ckEfwpE66cmVkE5NtkJ4lcrF1zchIP44IcBqp2IFSpJnroC7nkOst5detav7w7rdbrP/dXm6MQtSba0lCqOn8alv0aJFixaPxydExP64jrDhcMg3fdM3fVI71KJFi08DCGdu0rpChSHz6ZTO+hrT2dyn07muqCgIqUqX+ubmqCy7e3tEYUgn7RDGMdZYkl4PgHleEIQhkQixQiCVsxsKZZrFr5WCUmuXnGcNWmvCKAJrKYuS2WxGIFXTc5bnOXmeuR4uFYAnkEkckQ4HbmEaxcxmTsmLPbFyfUzK/1lTFAVGVxRFSZ5lBIFCysolNQpBhaX0xHTmCZ6Qgk6SEkUpYRhSlQUqCOh3Uu4ZfxsPrf7z4/ZEK7j76K9y1x3nyPKcyWTKdDJhnhdsbG6SnNziKP0oH/jI77H94BqrMmOl1yOYjsmx3HXuDtbW1sirkqwsWclHdNOU8XjM0f4+gZCc2NxkY2ODXr93LHo/z908VV2sXZcMy9rS6ZWkWsWpZ6fqNMzAE5rGfkidxyFxApD1VQaySVuskxWdwgogFkRncVAAR/yt1t5mCBKa+TRXPWBcGbMUTjHTws97uddU0pV/O2Ikm26tugctTdJFqmdRuph9b1+ti7YFiyAX/w4XypqUSKUIwgiN6z6riaOL6lc+zVCBcSEfaKis5WA8IQ4CN5cGCC18AIezKZogIAoCsixDKoXWi4oA6UNP6p48Ywzz+RzlbZ1Yw+KOhftalOWt/G3QokWLFp+2+ISIWBtN36JFi1sBi0VXFbP5nP39A+IkwWhDNp83Fq4g9AmHUiIi5ZICq8qpE0JSVKUv5405mkwoy8L1N2UZwlqiKCLtpC4Vz6cI6sotTMulhaSUkjgum1ks5bvDlJ/dCYOA0XBImqaL/beOZDnloGI6nRGGgev68hY3KQRYQ5FnrqS4DhfxHU7GBzzoOnK9cgSv9IRNYF3Uu1u9N/Ht1ke8f++X/xX+wS9WPLryYxBNoehyx9638Lde8Xq0saS9PnGvj9rdpSwKxGCA7lXs7D3AjUe73BYlbA2H3NzdYzYec/vp03T7fYIwJIgjIl+enaQpR7MZSRyDNgwGA0dGq4owipHCkYWqKptkvtrKVwed1EqS8GTHpVDWgRou+KImT3EcUfkExfpx2QRhCE9uFcYrjXWCYB0iIRoj3fGES4kLnVBKIZYi2JuZKevj2411c3LKPUfdf1bbJev5qaYM2quBs9msubbl40JJ3HbSv47FGOvslNKpfdIrYw1ZBbRXFY3A/axXuQQgVYCQFqkU2XSKDUP2ZzN6UQRGgydhAEq4YyTBW1OdLVFJ4ZM1/Ryedc+X5zndboc8y9ClC1tx71k2fWltoXOLFi1a3Bq0M2ItWrR4xjE+GlNqzWw2Iy9y0jRhNp8ThgFxFBHFMWVRelVJOnuYVMTdGGMW5ccAh/NDX0gr6HQ6TSx6NasWs2g+mVAEgigMWRmNjsXh14vjWgFp4GeaatIFUJUlRVmQpilZlrtSaa/g1XHpQDNjY7RpYtmxFuVVEyV84p412EW/rlPdIjDGqTNREPpiakNVOSWjTsr/W1/yenb3/wKXd/Y5e9sKJ160DtKRQ1tJCENsFCGUQqwl2N4DzM8f0hEn6YYhN3f3ODo44Pbbz3Lm9rPESYzFWfEUmrLI0Maws7dHEkXYsvSqlSMKoqoIAuXUME8w68S9ZStfEzHvCZGQys98LREcITFGk+e2sQzWC/4FkbOYqqKybhtduSAWGajjSX7GYJc7xVjMaWEFQiwSExfx7I6U1aQPX1xcP4s1tumjk8qFtSilHGlXixTIev5NW4NybM7PWXnS59UoIRVYg8SHYyiJEYKsKhHWkBdlc1MiiZNmts6de9uoWEmSsD8es7u3C/0BVBX4OH6BJQpcaEulJIFwSm3g0w+jMKQoy4aclYUr/55Nps5uWV+rgUJrTRAElEVBFLfWxBYtWrS4FWiJWIsWLZ5xHE0mrs/KaIqyZDKZMhwOUUpSFqUjYd6eNp1NCQNn95vP5z7BzXV/xXHMaDh0vV9R5LujvF1MBb7s1qlTSjnFKvAL07zIm3Q5wM/3uP2zFsqyII4TiqIgDN1CPMvzxja3v7e3CDSApqJJGPzi3s1BGeO7o7DHSR40RGOh5gjCwM2E1YELUrkI9KIsmsWwkAJdOWI36KTcc1vIoN8jjiLyOjCj0mgzJc9z4m6HeXWVw0cf4tL2dYLgDN0k4ca1a6yOVji5dZJef+DJhLOm7R0csL+/z3Q6daEmYUQUhhhryIrcq4IFQgjyPHOkiJo0eYKrte9ROx7uUBMwF7KxCE1xx8L4pENH6hqboicLxhhsVTbJikopTGGaVE2oQ1Uqx6WWyTHOjmqMI1/1rFpTIl3raLULD2f9q1/fkUxfIC4cETS6aqySNaETPrwjCJTvLqtTXnziobVYtCNTyt1sGM9m5IM+NwtFf79AlKW7+RCFVFUJhIBFe2XU4PrB5rM5oRBsDodk8zmm0k41E071Ki3uMxMEWGXBWGfTtJY8z5vr0BgXhlLgLJ9VVTXVAbUAVhQlUgiy+fxjfbxbtGjRosXHiZaItWjR4hnH9rVrTfIbQBwGGK0psmwxT2MsSRI7SxxuU2MDH+Xt0uwqHyZQFAWT6cQpTkFwTJHx+XDUq2ullAsw8AEZ4Gx2RmtXFmxr66FkNpsvzSm5wIeyKl04QjPH5AiBhOaVrHEKWxMxbt1UUd1FVs8XuWRzg9UW4Wd0lFIIVac6OsVGG40tSrQoMTpwj3uiUEftx7HrP8uLgiLPKSrNsNfDKMnBwQF7R4LLl4ak5fM5tdbDasPqcEiv26UsCg7396msYT6bcXh4yOHhEbPZDK01URhiu12ioOeqAIqFxdJ6ormw8Qms0It6AGscYa1DN5YSCIVYKFK10lmjVplqex/aH9faQihqUuXOFcbN/VX+eBtfPiy8ulbb/+ogkaqqmiCKOutDSh95z1Jsvkt6gSXi50igI3huv3XzeuD+YZVhSN2bZqUjkHjlVXvFDCGQ2tkOD/b32L++zVGWu3h8wOiKLM8BQZzEvtjaUJYV8/mc6XTKbD6n8lZbd73j1TODMQIr3TFz6qxGQ3PM6mOhq3JhmayPgxBIu7Bwivq6FkvhKC1atGjR4pNCS8RatGjxjGN9bRVjLVVZOWKEJYkTwihsrHzaz4CBW1gukvIEVVl6ApaTZzmVrpqCW6UWJb5KOXpUoyZV9WNKuV+BdUKcrkqMXtjh6tJdKetFt8Fo0yyqHQmTrmtMLWaenM5ml4IqVPPaTqFZnk1yaosKAqf8hWFjxasJgzUa7aPejTEoUXeqScJQYa1L2wsCF6Fezgoy30eWlwVmnqGmU84gqKRCFCVlWbK2tsag1ycOQ7I8ZzqdMB6Pmc1mFHmBMIagjkT35yvPM6zxJMMfV2c3rEmAOJZE6JnpQjEUwh9PlwRoar3MLlSjpptLLKlZtbLmVUiJcPNyXjWztVJktLuG/HNJaxHKYpQCqxfXl3azg1q7PWjUyno//T5ZH1RR74cQdZfdshey3lf3NQhDTyRpZsoAlLUY6SyYLsXRkdSyyojDiGGlGXY7ZJMpVikX2IKPz3cXJVVVMZvNODo6YjKbks/nTr2SrrQ8jRNUHLvL0daR/4CxID3594maxs+S1QmVDYxXGK1xrywW77ElYS1atGhx69ASsRYtWjzjCANnswqEbNIJlbfg1QTGxcm7wRjhk+ykXBQgWz93Za3xs0IWq11EufZpdRjZLIKhts3Vig1oUzaLUO0X8MYapJCN4iKNwUUd2IYsOFfdQrFxBFG6GabmdQKU0Fi76MWqt2/6mexCgVCBcvHmYeD20RrcWJkEW8eiSwJfBFz3YkmpCMPAz7FJQuWsl0WWOWvhbIYQgnue9SwmkzE712+wc+0at508yckTW/T7fay1zOdzjHbHMQ4jKl25dEP8LFQYNBZR5ZMOa7WxLmxWgWpSBmu1T7DY15p8NSEWUiCMs/wZYVwsvN9QLc3lue+BRWDVgqQt4udd8mR97qy0KCdiNd1edR/Wcim0sPikQdkokvWMIbhjX3eN1XOKQRAgvZLaxM6HkQ9YEUjlu+C87VU4n2BDnq3/f4tG1CEy2lAWOUZX6LJqZgmVXPSq1aSpKFyKZ1VVoGsbonT/1Z8XLEoGfuZRunlEf+PB3Qxw713iZs6kkEjlzkN9bN1nbqEOSh/WgVj0j7Vo0aJFi08OLRFr0aLFM44kjtG6IgxcAqJvoW3sUUpZpwAEqlFF6kWhtZZKV0AEdYhHFGONxoq66Nf/jCdUwvc41Ql+UrntaoXJFQlLN0PjoQLVqFcNhACpfIiDWLzWQjJolAvlZLxm/wU1QVtexNZhIBLlQznq+STtaY7yxCr0ZEwq1RTuGmxzbMIoxBpDGAYkSYw8BF3kWF1hjKXI5kzHY+azKbedPMnW1hajlZHvL8MpamFAmqZURdksumtFpSYoja3SLDrAlFJupssTUn8IsFYhZW1LxH+/VgW97ORJRlPqXKthTWeXba6NxWmorwlR+/CcwigcIVNKwVLqYR2zr41xc1y1mul7v6Qvhq63PfZa1ETFkaKaeFuv0rrgmJxut+u+789LgzpoREhU4K8nT9Iq7Y6mKt31pKSzKQqvjqZxQhiGhEHYKLLWODUwjkKkTYmjqLmk6vCQMAgIgtArlYIwdNULQRA04SN1MImPlEFKRRSGSKV8EqUi8FUAbp4sI4oSyqqk00n+mE94ixYtWrT4eNASsRYtWjzjEMIt/JdncYwvS65rsZrZnprU4LqgjDaEKCSCUElsTBO2UK+fHVGobY0L1apRruoEOh/cUG+3sM0trHWNhauen6mfTyxIQE1Mli2LzWs2HO1YrTH1rFTd19T0nFm7ZJ1z/Vii2XdHLq0A3djbKooCjJk4ZcZYQqXod7tudshYiqLg4qPniaKIrc0TrKyukKSJK1euNHNvb9NaY7Xx+x84YrB0YGs7pajZrRBLqYE14Vi4DBchGAuLXk3kBAtlpe7nqpXBen6pDkM5TsJoovFrGLtIp3S6mXvWmkRrP/9XzxRa415PCeESJevIefdkS6EbC/JekzCnzLnzXZRuprGTdo7bKVkijnUSi792UMopwf68llXZHDCJQAQKrCQKQz/3F4AQTq31CrBSklhEjoTV++wkyOZ1lPQzbZ5w1kqYsfhZtYUVsX5/dWFzHMcYY1z3nTEIKUiSlPl8TidNn2DLbNGiRYsWTw8tEWvRosUzjnpOq160151HQLNIl1ISLC1+8QvI2ra4IFV+ket/3hhDZeoUPtsk8LmF5oIIWGPRViKlV0dq1U16mQZ8sh6uW0ouLFpSLeLSHZmpsOZx6Xt+MSz97JHbT7u0LvedVvXrChdZb2oi5sMnwD+PWJCxJvjBL6itKcG6+TXhI89HoxH9fo+iKNDa+Hk5p+IEQQDGMptOm1mpqloOIPFqUk02/XEVxlk36/covT1QeZUQavJVWwAXJKv+mdqWaTBYbRriKwSEYUBV6ePzSn6eqZ7TEtalMbocd1/UbExDXOtj7a4ti9UV2oesVGXlLJfWzYQJb/OEJcurP6a18VKopZsFdciFDyB5/DXbHDxL8/qP36YO+oAAaytK6qRIdywF7rqOoshZTr1CVQeTuA4w5SyoSxUBRmuX4mjN4jxakEo1nXZVtZgztNZ4pVgifL+YlJLI21K11o2101rLbD4jiSJn49Vtj1iLFi1a3Aq0RKxFixbPPDypcv/hkgP9n+to83qWqLGfQZM6d2y2ypOUOu5eWoP0gRrGp741djhZazMuKEEaR9QQnlT4EmfwMzlYhJVIVS+WZbNPdVSFFtrPz7gCZgROhfAkrA4MsdYeU8XcvJsPd/A9Te49mkZ1ssJ6crggYcsQfh7I+v11BFa4RXocNERPa+3/7MhenRjoSJpG62qJxLh5Ixd4Ih3x8STCWOnahqEhYWJpzs8Yg7DCK2fuRNfko9n/msBYX7zsSZgKAiqtSdMU45Url2jo5pkQjtQJb/9zvV5gtSMGznLoZ5j8/F1NWrXRmMoRlTpKv368CbRYinVvjq//H4JFj9ixE+ASPrXW7hoERC3pekXOLp0zl/tR21T98fNWw0BJrHF1BUpIwjB0r20cYTWV9gTULl1b/voyFi38B6tysfZYHwaiNVosLJ4u/dMsbngoSUCAkYbSVx8oIZZI6UJpm06nx8hfixYtWrT45NASsRYtWjzjMFojmgWxv0PvgzoQ9TxXPTPmx2z8AruGBE/gJMYtgbFLakBNrmA5uW4xiwZ1AMGC57lFp26ei2VVSHhFzdKQsPq5pfKqnaltfUvBHNYpPcaTgXrfMBCETp0qy2pJQXELdPTiuWRtgfT2M2sXJceybneuZ678e62XykK416kVG6Xw8fvGz4c5QmJ9jHtjB1VOkXTzVQuFyM1BmaXtXHR/PY/k4jlkQwzr4yw9Uajtb4uUQWfRM8YQqoD5dOpCP5Yi/Os3U6tX7lzahpDVpN7WBB9HwI32qqG/LlzM/bL6tDj3wMIW617Z2VC9Cldfk8fKof05a+oNpMDapSfkuBVz6cnBQlm67rUgCBx59cdVKeWLv+2xWH8hJdLXPgg/v2d9bL61NTH3JN/H7lfak3RZNYmTxz4T1lB522OtmpbUh9Q2++CI2UINbdGiRYsWnzxaItaiRYtnHGVZovWCGB0PsKjJmcVajRICbRaKWI3aHLWY8VpssuSoaxaNNTGo+61q+x3CLtkVNVovLc7rmSjhF9SeKB23zrnnUUI2EfZuf2RjZauKgjAKiZKw/gGnVFWafJ4tvZ86Xlw0yYNuZmxp3mjpzbqwheOkENzcl5HG90B5m6QnNlVVkuU5gVIUXv0QUmKWGElN/PSSZdQ9v++V8kqY9GQAKdHGxYvUp7JRyPxzGbuwZzbnxv/dS3pUtkQFypVRV9onU/q+sWVCsmQvrZXPen7NNNeIt216AiusRXrSV1tD60NqrEVYszjvQhy7bqT09MuAxilj7j8fKGIt2mpE3Sbnzy/13NySbdEFkyyIen2swkBhzWImz5WBL1Ss+kZFE9Siq+YzgMX3uXmi7smpNhZM1exjfcxrsialdKEw/hpZXLv1uRHNHKXWuimvPnZHpEWLFi1aPG20RKxFixbPOMqyaBZzTaqgX9i7by4WxZolVgXNNs2C26sAi+dZLHBrJ9xyXHyTclhzBiFcYfKS5bGxrYlFuW2z8PfqivUR4I318XEBH9rPXNWLbm30IvABjsXl19HqDeFber916e7y/FYdF1//vTEoWoutcMl7AiD3RMM0z9MUHdtFQEad/gje6mePFyfX82DHkwUNxnEThK51ouOwS7NEtQIGS0qkV4p0TRaW5gMd8dEsx8lrbbzqiVND60TFpXPThHwsvYdlkcoRandlaWPQ/ppq4vi9cuqso9KTJ918r47pt8YipW0SP91lW6tV3koqzTFSVx+jyXTq57lcDYO1i5sERmuncuHsko+P8McuwkdMpZvZNaAJtXEjYW5msNlu2c5bJ0AuXdePP39NSik+SKeqqLyNteVhLVq0aHFr0BKxFi1aPOPQ1WIxV6cQqkC4ztlajWnCEPwC0s9yWUEzW3ZsnkcuuqecXWxpNmdpoekW0L4f6dj8Tq2ueBue8JZDy+MW/EvKA8vlxd7i5xWDhrT5OS9pJFZ4laZWrZaIA2IRk17PZVnrFuZNibS31LGkpPg31RwzYw3Wz0JZhAtxMHVhtW4UQSldJ5kKXEy5YlGMXOmqSemriZ8LVwn8LJxYOh7HV+WiZm/+dRornK2tfQJjtV/ku8cfr2Yt7HeeeNbWTB/I8aTkwZ8na6wjH8YshFZRXz+L68lt74LmjRBIU1s6PXHWIPx70zgFyShFAEgjoLYjusGwhkRaIXCR/QZJ3fnm3kM2zyh9GbnWy+Eoy4qvXRQt1zN2tUWyJsCeEOmqcsEZfhYS6WoEENJv57apn0941Vag3DUm3d2I+nhZLwc3dlh/Huu0yaqs3Dxhy8RatGjR4pagJWItWrR4xqGEIyWALwB281d1oaytF5b17ItXp/z9/mYe6vFETMhFgETTkWRsoxCAV2a8MlU/Xhf+NiEZlmNJhTWstW7RLnF70syDyWaeyGCwvlRYLG1TkywATG0RE34uyfrH1ZLi5AiF61mjUWyk8gRKKpA1eaq7uDxBrRUli1N0hETgE//qEmAcaar70GqyYoxZzMB5ZU1KF4MuhTt3oiYeVrgnMsvKVzOdBjWROGaLW1I3pQtZkfheq6UxKsFx8lSnNboT4X9+WYXELs3z+YqCWmUUbr+Eks0sWa2Y1ddUnRq4eA7RnIeaKAkfEFLfRWiIoHF/sn6GzIVa1tZERyqLqvKE+IkkzB0XVwbulEKaWbzlmcOa6EtpEBVNKTP+3EjhUjHdPkisdMEfCIsMAgT4uoHg+Ayetc7+qYJmn+rr3lqLwmCF8MRNoR5nzW3RokWLFk8PLRFr0aLFM44oihYKkF9k1kEBtYqyrHgsL7hrq5zb2AVqQB2mUCctqoagCCUxxikVTSmxWKT8WelUCG1xpc4+HRFoEg/rlb8Tahb7EiwnGXq1QiIxwiwFVCxi8aWUPvrbEiiFtaKZ0altb8KnRBpjEFqAwhdYexUreFxsuTFYFMZoH1NfC32L3jVngwyfQADUEvFrxEFrQakmhKMhgPL4XFNDci2u5NqjTpB0ASA1+WURBOJtgLX6FlCHf9Tn9LiN0S6RLiN9MqSfo2suiHqP/PmrwyUWgudiBsrWARdYZz3EXSPNtbi0H8fQKLcuWdPZ+habivqN+p221LUMCh4349YcIxZJmrZWEf1cXhgohAiXrKH48+0OpghBe6K4vE0Tx28MSgiMi/xsXtfVLyyuH6cyBk3dQ31t1CTUWosJFEGpMEH4pBbUFi1atGjx9NASsRYtWjzjiKLIBSc0RIxmLqpOgUMsSBYsZsOAhvQIEdZ/hSWysFiEuz+7u/8K/ML38UqH4x7q2PePLdzr+TIhqWvNhHDqyrFIcysaFUYKCKOoWfAqqSiKwisyXoVDkqSumykIgmbBbKw3pQlHOeMwcj/j1bDlGTIllV9EC0QQHFtEg0VLidQSLXWjgojmONRWQW8S9Met3v9gSTnxPwh+5qxWEJeJXJMlUm++NKt3PDXQkcA6Sr0J0PBPYuxyyuDC5gk+sXKZOC6uEP8eJErh7ZqL/a6JjqslkI2FcnmuUMrj83nunC6eQ8nF9dpcOMvk0jhVqz7HdQWCMYaqrJr5NvdWa92PxdxbTSCxCBG4tEu7eC0f+O+InDSIIKCeVQQ8mfVpil79C+pi9OY9LpEwCzaoZ+5qZWxx3ddddsYaCCPwNynaQucWLVq0uDVoiViLFi2ecSgpUL6QtiYNizvyj4uOh2ML78Viv/7e8cS3WnVY2BbdcztCcfxOf/0fzaKcJgSj3qfH75tyQ0sLRc0sFt1NufTSwrwyFYFS5HnWKCbLc2y60sRxjPHBFNbPe9VzP9ZYgkARRRHWz/Mcew9LSovyqmCdpGiMn6vy/x0nHYt+M6zxahl+/+u5MOVtob4awNQF0gulq06GrAlGTRiWY9st4hh5sdYHVAiBwTbEAGsJgtApgM3xd++ZpVm0mizWx7K+IhovKyD8P2/1rF3dieVUPOsV0vqci2Mkpj52tT2xhvWKlW32Fxc5rxT4xENhXZmCNQaDQBfah1zoYwS43l9dz//VZdmC2uPobYfuLbnybt+H5sNlsIuKAKAJR7FLZNqVNIcEQdioxsufo/qYHSfKi+u/Lg93NkmnyAZBu3Ro0aJFi1uB9rdpixYtnnG44AdvxbKLmRTjS3mbmZ5jN97rhTd4/xqPV8FqLPdtHRfSxLFtnrCdsajAk5h68e5LdOvXtrW6Y91Mkq5TFBsCYBEyaJSTNEmb91xWJZWpmm2VCglDp+oFgfJ9Yp6M4e1mgXQL+XlGkiSNAmbr91DbN/0cmrHG7Rd4m94iBr0movVc2/LjtepXL96lL2rGKzQuCMORsEX5sycwzfzWk6cnynp+iwWfqmfDFjZTi1SKSldEQUBZlrVP1Sc80rxPcCXYjc3Qk1YpFMY60l2XLNeJlTWplv49WU9X620EeMvkEolfuqbqy86JtY5k1YqoNcYPbC0qB7Cgq5KicuEc1hO7pgRbCB/8Ypr0TOGJvvCzXU3aovUlzGYp3MXfrKjnyxqLon8vUggIAqQQBEFIHEdEUURVlP74O8XQzem5PydpQpZl/r0vjoPxISmufDyg3+8/4Ry3aNGiRYtPHC0Ra9GixTOOOI4W6ous1RuD1i4QoCYO7g7+8bCMhaVQOFubn7cCFoqNaNapQD3nxIJQecJhlghWTdEqrZtY7xrL6svxfqm6JwpvtVwk2ykZEgQB83lGVVXHbWHCEZ+iKCjLslnghmFIVZVY7LHQkXpWrdJOXbM+ZMMK4ZiBXPR2SSUblcvt2yKKfWG5XFaRGlNfYyFsesc82Tw+b7U4HlK4Y9mcIyEWVjp/rFwv8UJdknah4DVKp3VFzxL3PoqiaMqm3Wsr7wL0JNK62bcwDAliV4Zc5DkWSxzHFEVBJ+2QZVljTa0J17EqAJaqDurrEAGYOpiyOU71NbJQ9nw0vvXlyVKANj7V06C1cemTlfaVAN7WZ13sva29nPXnYIkk18Ev7nj+/9u787CqqsX/45/N4TAroIhoouCYZU5pN7USU9O8+tWsn1pmUmZZqU1mOeTUnJlZPqWlZpo3tat2y9t1wLIwh4yiHHEI0gRyBpHpAPv3B3LyKCAqbETer+fZD56911lr7eNyP3xce69TMGMr52d+JjU6b3HMv01WzlsLXf7+zixg4+3trYz0dPn6+J59WsrIyJCH3cO5Mqenp6c8ztwKm5uXq+zMLOXq71t3CwIwAODyEcQAWC4nJ1fu7razZmXOXsjAJg8PmzIzs/5exKEgCEnOP9vc85/7ys7KVo5ynN/R5XxWxzBdZjQK/nz2MvYui3cYhrKzs/Pfb+R/z5Ij2+FcZKMgFOXm5C/t7lawAl9u/vNdOTn5z3B52O3KdjiUnZ0lR45DHh4e8vLyUkZGunJyHHJzszlv7zr7eaOcnFxlZmXK5maTl6enHI6c/JkUmfLw8JCH3S67YZfDkS13d7scDofcbW5y5OW6LKBhGIZycnJls7kpNyf/uTCbbPnLjp/5UuuC7+9yczOU6zgzg5SXK3ebe/6MkpvNOQtmuNucM2Znr6TnDLaG4QwxpinnFzK729xcwmpe3pngZHNXRmbGmdvdTGf4tBnGmcVG3OTh4amsrEx5enoqKytL7u526cwtjHm5ubK5u8vbI38mMTsrW44chzw9veTubtPptNPy9vFWZkamPDw95eZm6PTp03JT/oqP7u5/z1rlyZS7zf2cYJEnw8j/PPJMnfm7zZG7u7vz81PBLZeG6fw+toIFQJzP3Jn5T6IVLMzhdua2vuysbOd4NNwMKffMfyQUzETq74CYH5D/DsduksyCBWLO1Om8hbEgVJ/5N2AzCla8zB+7NjebPM7Mvp69Eqib4SZ3m7tyTIfs9vwFXQrO15GdP36zsjKdC8UUhFkAwOUjiAGwXP87G5V3FwAAAMqV24WLAAAAAABKE0EMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAi1WIIJaQkKAhQ4YoPDxc3t7eatCggSZOnKjs7GxnmWPHjql79+6qXbu2PD09FRoaquHDhys1NbXYuiMiImQYhss2YMCAsj4lAAAAAJWYe3l3oCR2796tvLw8zZ49Ww0bNtT27ds1dOhQnT59Wm+99ZYkyc3NTb1799bLL7+sGjVqaN++fXriiSd0/Phx/etf/yq2/qFDh2rKlCnO197e3mV6PgAAAAAqtwoRxLp3767u3bs7X9evX19xcXH64IMPnEEsMDBQjz32mLNMvXr19Pjjj2vq1KkXrN/Hx0chISGl33EAAAAAKESFuDWxMCkpKapWrVqRxxMTE7V8+XJ17NjxgnUtWrRIQUFBuv766zVq1CidOnWqNLsKAAAAAC4qxIzYufbv36/33ntP06ZNO+/Yvffeq//85z/KyMhQr169NGfOnGLrGjhwoMLDwxUSEqLt27drzJgx+vXXX7V27doi35OVlaWsrCzn6ws9hwYAAAAAZzNM0zTLq/FJkyZp8uTJxZbZunWr2rRp43ydmJiojh07qmPHjoWGrOTkZJ08eVJxcXEaO3asOnbsqPfff7/EfYqJiVGbNm0UExOj1q1bX1S/U1JSVLVq1RK3BQAAAODqkpqaKn9//wtmg3INYkePHtXRo0eLLRMWFiYvLy9J+SGsU6dO+sc//qH58+fLza34Oys3bNigW2+9VYmJiapVq1aJ+mSapjw9PbVw4UL179+/0DKFzYiFhoYSxAAAAIBKrqRBrFxvTQwKClJQUFCJyh46dEidOnXSjTfeqI8//viCIUzKD1WSXELThezYsUMOh6PY4Obp6SlPT88S1wkAAAAAZ6sQz4glJiYqIiJCdevW1VtvvaUjR444jxWsdvj111/rr7/+Utu2beXn56edO3dq9OjR6tChg8LCwiTlh7nOnTtrwYIFuummm7R//34tWrRIPXr0UFBQkHbu3Klnn31WrVq1UocOHcrjVAEAAABUAhUiiK1Zs0b79u3Tvn37VKdOHZdjBbNe3t7e+uijj/T0008rKytLoaGh6tu3r1544QVnWYfDobi4OKWnp0uSPDw8tG7dOs2YMUNpaWkKDQ3VP//5T02cOFE2m826EwQAAABQqZTrM2JXi5LeBwoAAADg6lbSbFBhv0cMAAAAACoqghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAAAAgMUIYgAAAABgMYIYAAAAAFiMIAYAAAAAFiOIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWcy/vDgAAAACXIjc3Vw6Ho7y7gUrGbrfLZrNddj0EMQAAAFQopmkqOTlZJ0+eLO+uoJIKCAhQSEiIDMO45DoIYgAAAKhQCkJYcHCwfHx8LuuXYeBimKap9PR0HT58WJJUq1atS66LIAYAAIAKIzc31xnCqlevXt7dQSXk7e0tSTp8+LCCg4Mv+TZFFusAAABAhVHwTJiPj0859wSVWcH4u5xnFAliAAAAqHC4HRHlqTTGH0EMAAAAACxGEAMAAAAAixHEAAAAAAtERkaqT58+zj8bhqHXX3/dpcwXX3zhctvb+vXrZRiGAgMDlZmZ6VL2xx9/lGEYhZYvbEtOTlZYWFiRxw3DUERERJmdP1wRxAAAAIBy4OXlpTfeeEMnTpy4YNkqVapoxYoVLvvmzZununXrFlo+Li5OSUlJLltwcLC2bt3qfL1s2bLzyi5fvvzyTwwlQhADAABApZSRIcXH5/8sD126dFFISIhee+21C5YdPHiw5s2b53ydkZGhxYsXa/DgwYWWDw4OVkhIiMvm5uamGjVqOF9Xq1btvLIF+1D2CGIAAACoVHJzpfHjpaAgqX79/J/jx+fvt5LNZtOrr76q9957T3/++WexZQcNGqTo6GgdOHBAkrRs2TKFhYWpdevWVnQVZYAgBgAAgEpl4kTp1Vel9PT81+np+a8nTrS+L3fddZdatmypiRdoPDg4WHfeeafmz58vKf+2xIceeqjI8nXq1JGfn59za9KkSWl2G6WAIAYAAIBKIyNDmj5dMk3X/aYpvfNO+dym+MYbb+iTTz7Rzp07iy330EMPaf78+fr999+1adMmDRw4sMiy0dHRio2NdW6rV68u7W7jMhHEAAAAUGkkJ/89E3au06fzj1vttttuU7du3TR27Nhiy/Xo0UOZmZkaMmSIevXqperVqxdZNjw8XA0bNnRuYWFhpdxrXC738u4AAAAAYJWQEMnHp/Aw5uubf7w8vP7662rZsqUaN25cZBmbzaZBgwbpzTff1P/+9z8Le4eywIwYAAAAKg1vb+npp6WzvnpLUv7rp57KP14ebrjhBg0cOFDvvfdeseVeeuklHTlyRN26dSu23OHDh5WcnOyyORyO0uwyLhNBDAAAAJXK5MnS2LH5M2BS/s+xY/P3l6eXXnpJ5rkPr53Dw8NDQUFBLl/iXJgmTZqoVq1aLltMTExpdheXyTAv9LeNC0pNTZW/v79SUlJUtWrV8u4OAADAVSszM1Px8fEKDw+Xl5fXZdWVkZH/TFhISPnNhKFiKm4cljQb8IwYAAAAKiVvbyk8vLx7gcqKWxMBAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAAixHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAIArwPr162UYhk6ePFneXSlWRennlY4gBgAAAFho48aNstls6t69e5nUn5CQIMMwFBsbe9HvDQsLk2EYMgxD3t7euvbaazV16lSZpuks0759eyUlJcnf378Ue135EMQAAAAAC82bN08jRozQhg0bdODAgVKtOzs7+7LrmDJlipKSkrRr1y6NGjVKY8eO1Ycffug87uHhoZCQEBmGcdltVWYEMQAAAFRKGY4MxZ+IV4Yjw7I2T58+raVLl+qxxx5Tz549NX/+/GLLb9y4Ubfddpu8vb0VGhqqkSNH6vTp087jYWFhevnllxUZGSl/f38NHTpU4eHhkqRWrVrJMAxFRERIkrZu3aquXbsqKChI/v7+6tixo37++efz2qxSpYpCQkIUFhamhx9+WM2bN9eaNWucxwu7NXHZsmW6/vrr5enpqbCwME2bNu3SP6RKgiAGAACASiU3L1fjvxmvoKlBqv9ufQVNDdL4b8YrNy+3zNtesmSJmjRpoiZNmuj+++/Xxx9/7HLb39m2bdumbt26qW/fvvrtt9+0ZMkSbdiwQcOHD3cpN3XqVDVr1kwxMTF68cUX9eOPP0qSoqKilJSUpOXLl0uSTp06pcGDBys6OlqbN29Wo0aN1KNHD506darQ9k3T1Pr167Vr1y7Z7fYizykmJkb9+vXTgAEDtG3bNk2aNEkvvvjiBUNmpWdWAPHx8eZDDz1khoWFmV5eXmb9+vXNCRMmmFlZWYWWP3r0qHnNNdeYkswTJ04UW3dmZqY5fPhws3r16qaPj4/Zq1cv8+DBgxfVv5SUFFOSmZKSclHvAwAAwMXJyMgwd+7caWZkZFxyHePWjTONSYapSXJuxiTDHLduXCn2tHDt27c333nnHdM0TdPhcJhBQUHm2rVrTdM0zW+//dbl99dBgwaZjzzyiMv7o6OjTTc3N+f516tXz+zTp49Lmfj4eFOS+csvvxTbl5ycHLNKlSrmV1995dxXr14908PDw/T19TXtdrspyfTy8jJ/+OEHZ5lz+3nfffeZXbt2dan7ueeeM6+77rqSfSgVUHHjsKTZoELMiO3evVt5eXmaPXu2duzYoenTp2vWrFkaO3ZsoeWHDBmi5s2bl6jup556SitWrNDixYu1YcMGpaWlqWfPnsrNLfv/EQEAAIC1MhwZmr55uky5zkKZMvXO5nfK9DbFuLg4/fjjjxowYIAkyd3dXf3799e8efMKLR8TE6P58+fLz8/PuXXr1k15eXmKj493lmvTpk2J2j98+LCGDRumxo0by9/fX/7+/kpLSzvvObXnnntOsbGx+u6779SpUyeNGzdO7du3L7LeXbt2qUOHDi77OnTooL179/I7dTHcy7sDJdG9e3eXVWXq16+vuLg4ffDBB3rrrbdcyn7wwQc6efKkJkyYoP/973/F1puSkqK5c+dq4cKF6tKliyTp008/VWhoqKKiotStW7fSPxkAAACUm+S0ZKU70gs9dtpxWslpyQoPDC+TtufOnaucnBxdc801zn2macput+vEiRPnlc/Ly9Ojjz6qkSNHnnesbt26zj/7+vqWqP3IyEgdOXJE77zzjurVqydPT0+1a9fuvAU+goKC1LBhQzVs2FDLli1Tw4YNdfPNNzt/Xz6XaZrnLdxhFnG7Jf5WIYJYYVJSUlStWjWXfTt37tSUKVO0ZcsW/f777xesIyYmRg6HQ3fccYdzX+3atdWsWTNt3LiRIAYAAHCVCfELkY/dp9Aw5mv3VYhfSJm0m5OTowULFmjatGkuv3tK0t13361FixapWbNmLvtbt26tHTt2qGHDhhfVloeHhySdNxsVHR2t999/Xz169JAkHTx4UEePHi22rsDAQI0YMUKjRo3SL7/8UuhKidddd502bNjgsm/jxo1q3LixbDbbRfW9MqkQtyaea//+/Xrvvfc0bNgw576srCzde++9mjp1qsv/EBQnOTlZHh4eCgwMdNlfs2ZNJScnF/m+rKwspaamumwAAAC48nnbvfX0zU/LkGugMGToqZufkrfdu0zaXblypU6cOKEhQ4aoWbNmLts999yjuXPnnvee559/Xps2bdITTzyh2NhY7d27V19++aVGjBhRbFvBwcHy9vbWqlWr9NdffyklJUWS1LBhQy1cuFC7du3Sli1bNHDgQHl7X/h8n3jiCcXFxWnZsmWFHn/22We1bt06vfTSS9qzZ48++eQTzZw5U6NGjSrBJ1N5lWsQmzRpkvML44rafvrpJ5f3JCYmqnv37vp//+//6eGHH3buHzNmjJo2bar777//svtV2PTq2V577TXnfbX+/v4KDQ297DYBAABgjckRkzX21rHyteff0udr99XYW8dqcsTkMmtz7ty56tKlS6Ffgnz33XcrNjb2vKXkmzdvru+++0579+7VrbfeqlatWunFF19UrVq1im3L3d1d7777rmbPnq3atWurd+/ekvK/v+zEiRNq1aqVBg0apJEjRyo4OPiCfa9Ro4YGDRqkSZMmKS8v77zjrVu31tKlS7V48WI1a9ZMEyZM0JQpUxQZGXnBuiszwyzHGziPHj16wenQsLAweXl5ScoPYZ06ddI//vEPzZ8/X25uf+fIli1batu2bc4AZZqm8vLyZLPZNG7cOE2efP4/rG+++UadO3fW8ePHXWbFWrRooT59+hT6Hil/RiwrK8v5OjU1VaGhoUpJSVHVqlVL/gEAAADgomRmZio+Pl7h4eHO3xEvVYYjQ8lpyQrxCymzmTBcnYobh6mpqfL3979gNijXZ8SCgoIUFBRUorKHDh1Sp06ddOONN+rjjz92CWFS/pfIZWT8vcrN1q1b9dBDDyk6OloNGjQotM4bb7xRdrtda9euVb9+/SRJSUlJ2r59u958880i++Lp6SlPT88S9RsAAABXJm+7d5ktzAFcSIVYrCMxMVERERGqW7eu3nrrLR05csR5LCQk/4HKc8NWwUxb06ZNFRAQICk/zHXu3FkLFizQTTfdJH9/fw0ZMkTPPvusqlevrmrVqmnUqFG64YYbilwVBgAAAAAuV4UIYmvWrNG+ffu0b98+1alTx+XYxdxZ6XA4FBcXp/T0v1fJmT59utzd3dWvXz9lZGSoc+fOmj9/Piu8AAAAACgz5fqM2NWipPeBAgAA4PKU5jNiwKUqjWfEKuTy9QAAAABQkRHEAAAAAMBiBDEAAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAACUCsMw9MUXX5R3NyoEghgAAABggYMHD2rIkCGqXbu2PDw8VK9ePT355JM6duzYRdWTkJAgwzAUGxtbNh29DElJSbrzzjtLVLayhzaCGAAAAFDGfv/9d7Vp00Z79uzRZ599pn379mnWrFlat26d2rVrp+PHj5d6m9nZ2aVe54WEhITI09PT8nYrIoIYAAAAKiVHhkMn4k/IkeEo87aeeOIJeXh4aM2aNerYsaPq1q2rO++8U1FRUTp06JDGjRvnLFvYTFFAQIDmz58vSQoPD5cktWrVSoZhKCIiQpIUGRmpPn366LXXXlPt2rXVuHFjSdK2bdt0++23y9vbW9WrV9cjjzyitLQ0Z93r16/XTTfdJF9fXwUEBKhDhw76448/Cj2P7OxsDR8+XLVq1ZKXl5fCwsL02muvFdr34sqGhYVJku666y4ZhuF8LUlfffWVbrzxRnl5eal+/fqaPHmycnJyXNqYPXu2evbsKR8fHzVt2lSbNm3Svn37FBERIV9fX7Vr10779+93vmf//v3q3bu3atasKT8/P7Vt21ZRUVEu5/b++++rUaNG8vLyUs2aNXXPPfcU+hmUFoIYAAAAKpW83Dx9M/4bTQ2aqnfrv6upQVP1zfhvlJebVybtHT9+XKtXr9bjjz8ub29vl2MhISEaOHCglixZItM0S1Tfjz/+KEmKiopSUlKSli9f7jy2bt067dq1S2vXrtXKlSuVnp6u7t27KzAwUFu3btXnn3+uqKgoDR8+XJKUk5OjPn36qGPHjvrtt9+0adMmPfLIIzIMo9C23333XX355ZdaunSp4uLi9Omnn7qEqJKW3bp1qyTp448/VlJSkvP16tWrdf/992vkyJHauXOnZs+erfnz5+uVV15xqfull17SAw88oNjYWF177bW677779Oijj2rMmDH66aefJMl5jpKUlpamHj16KCoqSr/88ou6deumXr166cCBA5Kkn376SSNHjtSUKVMUFxenVatW6bbbbivR38elci/T2gEAAIArzPqJ6xX9arR0Jvc40h35ryXd/vLtpd7e3r17ZZqmmjZtWujxpk2b6sSJEzpy5IiCg4MvWF+NGjUkSdWrV1dISIjLMV9fX82ZM0ceHh6SpI8++kgZGRlasGCBfH19JUkzZ85Ur1699MYbb8hutyslJUU9e/ZUgwYNnP0pyoEDB9SoUSPdcsstMgxD9erVu6SyBecQEBDgcg6vvPKKXnjhBQ0ePFiSVL9+fb300ksaPXq0Jk6c6Cz34IMPql+/fpKk559/Xu3atdOLL76obt26SZKefPJJPfjgg87yLVq0UIsWLZyvX375Za1YsUJffvmlhg8frgMHDsjX11c9e/ZUlSpVVK9ePbVq1arIcysNzIgBAACg0nBkOLR5+mZnCHMypc3vbLbkNsVzFcyEFTULdTFuuOEGZwiTpF27dqlFixbOECZJHTp0UF5enuLi4lStWjVFRkY6Z4hmzJihpKSkIuuPjIxUbGysmjRpopEjR2rNmjWlUrZATEyMpkyZIj8/P+c2dOhQJSUlKT093VmuefPmzj/XrFnTee5n78vMzFRqaqok6fTp0xo9erSuu+46BQQEyM/PT7t373bOiHXt2lX16tVT/fr1NWjQIC1atMilvbJAEAMAAEClkZacJkd64WHLcdqhtOS0Qo9djoYNG8owDO3cubPQ47t371ZgYKCCgoIk5Qeyc29TdDhKFhDPDlxSfsgrKuAV7P/444+1adMmtW/fXkuWLFHjxo21efPmQt/TunVrxcfH66WXXlJGRob69etX5LNUF1O2QF5eniZPnqzY2Fjntm3bNu3du1deXl7Ocna7/bzzKGxfXl7+7abPPfecli1bpldeeUXR0dGKjY3VDTfc4FzQpEqVKvr555/12WefqVatWpowYYJatGihkydPFtvfy0EQAwAAQKXhF+Inu4+90GN2X7v8QvxKvc3q1aura9euev/995WRkeFyLDk5WYsWLVL//v2d4aFGjRous1J79+51mZ0pmPHKzc29YNvXXXedYmNjdfr0aee+H374QW5ubs7FPKT8hT/GjBmjjRs3qlmzZvrXv/5VZJ1Vq1ZV//799dFHH2nJkiVatmxZkas+FlfWbrefdw6tW7dWXFycGjZseN7m5nbp0SU6OlqRkZG66667dMMNNygkJEQJCQkuZdzd3dWlSxe9+eab+u2335SQkKBvvvnmktu8EIIYAAAAKg27t103P32zdO4kkSHd/NTNsnsXHtIu18yZM5WVlaVu3brp+++/18GDB7Vq1Sp17dpV11xzjctiFLfffrtmzpypn3/+WT/99JOGDRvmMtsTHBwsb29vrVq1Sn/99ZdSUlKKbHfgwIHy8vLS4MGDtX37dn377bcaMWKEBg0apJo1ayo+Pl5jxozRpk2b9Mcff2jNmjXas2dPkc+JTZ8+XYsXL9bu3bu1Z88eff755woJCVFAQMBFlw0LC9O6deuUnJysEydOSJImTJigBQsWaNKkSdqxY4d27dqlJUuWaPz48Zfwqf+tYcOGWr58uWJjY/Xrr7/qvvvuc86WSdLKlSv17rvvKjY2Vn/88YcWLFigvLw8NWnS5LLaLQ5BDAAAAJVKxOQI3Tr2Vtl988ON3deuW8feqojJEWXWZqNGjfTTTz+pQYMG6t+/vxo0aKBHHnlEnTp10qZNm1StWjVn2WnTpik0NFS33Xab7rvvPo0aNUo+Pj7O4+7u7nr33Xc1e/Zs1a5dW7179y6yXR8fH61evVrHjx9X27Ztdc8996hz586aOXOm8/ju3bt19913q3HjxnrkkUc0fPhwPfroo4XW5+fnpzfeeENt2rRR27ZtlZCQoK+//rrQ2aoLlZ02bZrWrl2r0NBQ58IY3bp108qVK7V27Vq1bdtWN998s95+++1iFwUpienTpyswMFDt27dXr1691K1bN7Vu3dp5PCAgQMuXL9ftt9+upk2batasWfrss890/fXXX1a7xTHMkq6TiSKlpqbK399fKSkpqlq1anl3BwAA4KqVmZmp+Ph4hYeHuzwzdCkcGfnPhPmF+JXZTBiuTsWNw5JmA5avBwAAQKVk97YrMDywvLuBSopbEwEAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACwGEEMAAAAACxGEAMAAAAqsMjISPXp06e8u4GLRBADAABA5ZSXJ61cmf/TApGRkTIMQ4ZhyN3dXXXr1tVjjz2mEydOWNI+riwEMQAAAFRO//2v1KuX9PXXljXZvXt3JSUlKSEhQXPmzNFXX32lxx9/3LL2i+JwOMq7C5UOQQwAAACV07Jlrj8t4OnpqZCQENWpU0d33HGH+vfvrzVr1kiScnNzNWTIEIWHh8vb21tNmjTRjBkzXN6fm5urZ555RgEBAapevbpGjx4t0zRdyqxatUq33HKLs0zPnj21f/9+5/GEhAQZhqGlS5cqIiJCXl5e+vTTT8v+5OGCIAYAAIDKJztbWr48/8/Ll0vlMCP0+++/a9WqVbLb7ZKkvLw81alTR0uXLtXOnTs1YcIEjR07VkuXLnW+Z9q0aZo3b57mzp2rDRs26Pjx41qxYoVLvadPn9YzzzyjrVu3at26dXJzc9Ndd92lvHNuwXz++ec1cuRI7dq1S926dSv7E4YL9/LuAAAAAFDmTp6UTp36+/UPP/z9OjU1P4y1b//38SpVpICAUu/GypUr5efnp9zcXGVmZkqS3n77bUmS3W7X5MmTnWXDw8O1ceNGLV26VP369ZMkvfPOOxozZozuvvtuSdKsWbO0evVqlzYKjhWYO3eugoODtXPnTjVr1sy5/6mnnlLfvn1L/RxRMgQxAAAAXN2ys6XataWMDNf97u5STk7+zwEDXI/5+EgnTkgeHqXalU6dOumDDz5Qenq65syZoz179mjEiBHO47NmzdKcOXP0xx9/KCMjQ9nZ2WrZsqUkKSUlRUlJSWrXrt1Zp+CuNm3auNyeuH//fr344ovavHmzjh496pwJO3DggEsQa9OmTameGy4OtyYCAADg6ubhIc2eLXl5ue7PyXH9WcDLS5o1q9RDmCT5+vqqYcOGat68ud59911lZWU5Z8GWLl2qp59+Wg899JDWrFmj2NhYPfjgg8rOzr6oNnr16qVjx47po48+0pYtW7RlyxZJOq8eX1/f0jkpXBKCGAAAAK5+gwZJv/4q3XCDZBiFlzEMqXnz/HKDBlnSrYkTJ+qtt95SYmKioqOj1b59ez3++ONq1aqVGjZs6LLIhr+/v2rVqqXNmzc79+Xk5CgmJsb5+tixY9q1a5fGjx+vzp07q2nTpiyPf4Xi1kQAAABUDo0bS1u3Sl26SJs3u86EubtLN98sRUVJnp6WdSkiIkLXX3+9Xn31VTVq1EgLFizQ6tWrFR4eroULF2rr1q0KDw93ln/yySf1+uuvq1GjRmratKnefvttnTx50nk8MDBQ1atX14cffqhatWrpwIEDeuGFFyw7H5QcM2IAAACoPOx2KS7u7xBWMDuWkyPt2ZN/3GLPPPOMPvroI/Xp00d9+/ZV//799Y9//EPHjh077zvGnn32WT3wwAOKjIxUu3btVKVKFd11113O425ublq8eLFiYmLUrFkzPf3005o6darVp4QSMMxzv3gAFy01NVX+/v5KSUlR1apVy7s7AAAAV63MzEzFx8crPDxcXuc+81USGzdKHTr8/To4WDp82PX4WYthAIUpbhyWNBswIwYAAIDK49//zv9ps0lTp0qHDklvvpn/+uzjQBkjiAEAAKDy2LxZqldP2rRJGjUq/9mw557Lf12vnnRmhUGgrLFYBwAAACqP//xH8vOTvL1d97dtK+3aJaWllU+/UOkQxAAAAFB51KhR9DFv7/MDGlBGuDURAAAAACxGEAMAAECFw8LfKE+lMf4IYgAAAKgw7Ge+5ys9Pb2ce4LKrGD82S/je+d4RgwAAAAVhs1mU0BAgA6f+e4vHx8fGQVfygyUMdM0lZ6ersOHDysgIEC2gq89uAQEMQAAAFQoISEhkuQMY4DVAgICnOPwUhHEAAAAUKEYhqFatWopODhYDoejvLuDSsZut1/WTFgBghgAAAAqJJvNViq/EAPlgcU6AAAAAMBiBDEAAAAAsBhBDAAAAAAsxjNipaDgC91SU1PLuScAAAAAylNBJrjQlz4TxErBqVOnJEmhoaHl3BMAAAAAV4JTp07J39+/yOOGeaGohgvKy8tTYmKiqlSpYtkXCqampio0NFQHDx5U1apVLWkTVwfGDi4VYweXirGDS8XYwaUqz7FjmqZOnTql2rVry82t6CfBmBErBW5ubqpTp065tF21alUuTLgkjB1cKsYOLhVjB5eKsYNLVV5jp7iZsAIs1gEAAAAAFiOIAQAAAIDFCGIVlKenpyZOnChPT8/y7goqGMYOLhVjB5eKsYNLxdjBpaoIY4fFOgAAAADAYsyIAQAAAIDFCGIAAAAAYDGCGAAAAABYjCAGAAAAABYjiFUAWVlZatmypQzDUGxsbKFljh07pjp16sgwDJ08ebLY+iIiImQYhss2YMCA0u84yl1pj52srCyNGDFCQUFB8vX11f/93//pzz//LP2Oo9wVNXaOHTum7t27q3bt2vL09FRoaKiGDx+u1NTUYuvjulN5lPbY4bpTeRQ1dn799Vfde++9Cg0Nlbe3t5o2baoZM2ZcsD6uO5VHaY8dq647BLEKYPTo0apdu3axZYYMGaLmzZuXuM6hQ4cqKSnJuc2ePftyu4krUGmPnaeeekorVqzQ4sWLtWHDBqWlpalnz57Kzc0tje7iClLU2HFzc1Pv3r315Zdfas+ePZo/f76ioqI0bNiwC9bJdadyKO2xw3Wn8ihq7MTExKhGjRr69NNPtWPHDo0bN05jxozRzJkzL1gn153KobTHjmXXHRNXtK+//tq89tprzR07dpiSzF9++eW8Mu+//77ZsWNHc926daYk88SJE8XW2bFjR/PJJ58sk/7iylHaY+fkyZOm3W43Fy9e7Nx36NAh083NzVy1alUZnAHKS0nGztlmzJhh1qlTp9gyXHcqh9IeO1x3Ko+LHTuPP/642alTp2LLcN2pHEp77Fh53WFG7Ar2119/aejQoVq4cKF8fHwKLbNz505NmTJFCxYskJtbyf86Fy1apKCgIF1//fUaNWqUTp06VVrdxhWgLMZOTEyMHA6H7rjjDue+2rVrq1mzZtq4cWOp9R3lqyRj52yJiYlavny5OnbseMGyXHeubmUxdrjuVA4XO3YkKSUlRdWqVbtgOa47V7eyGDtWXncIYlco0zQVGRmpYcOGqU2bNoWWycrK0r333qupU6eqbt26Ja574MCB+uyzz7R+/Xq9+OKLWrZsmfr27VtaXUc5K6uxk5ycLA8PDwUGBrrsr1mzppKTky+73yh/JRk7Be699175+PjommuuUdWqVTVnzpxiy3PdubqV1djhunP1u5ixU2DTpk1aunSpHn300WLLcd25upXV2LHyukMQs9ikSZPOe3D03O2nn37Se++9p9TUVI0ZM6bIusaMGaOmTZvq/vvvv6g+DB06VF26dFGzZs00YMAA/fvf/1ZUVJR+/vnnyz09lKErYewUxjRNGYZx2fWg7JTm2Ckwffp0/fzzz/riiy+0f/9+PfPMM8WW57pTMV0JY6cwXHeufGUxdiRpx44d6t27tyZMmKCuXbsWW5brTsV0JYydwpTFdccwTdMs1RpRrKNHj+ro0aPFlgkLC9OAAQP01VdfufyF5+bmymazaeDAgfrkk0/UsmVLbdu2zVnGNE3l5eXJZrNp3Lhxmjx5con6ZJqmPD09tXDhQvXv3//STw5lqrzHzjfffKPOnTvr+PHjLv9L1KJFC/Xp06fE4w3WK82xU5gNGzbo1ltvVWJiomrVqlWiPnHdqRjKe+xw3am4ymLs7Ny5U506ddLDDz+sV1555aL7xHWnYijvsWPpdadUnzhDqfnjjz/Mbdu2ObfVq1ebksx///vf5sGDB03TNM19+/a5lJk3b54pydy4caP5119/lbitbdu2mZLM7777rqxOBxYqq7FT8PDqkiVLnPsSExN5aP4qUpKxU5jvv//elGTGx8eXuC2uO1eXsho7XHeufiUdO9u3bzeDg4PN55577pLb4rpzdSmrsWPldYcgVkHEx8dfcCWYb7/99ryV7/7880+zSZMm5pYtW0zTzP8FfPLkyebWrVvN+Ph487///a957bXXmq1atTJzcnLK+CxQHkpr7JimaQ4bNsysU6eOGRUVZf7888/m7bffbrZo0YKxc5UqbOz897//NefNm2du27bNeQ25/vrrzQ4dOjjLcN1BaY0d0+S6U9kUNna2b99u1qhRwxw4cKCZlJTk3A4fPuwsw3UHpTV2TNO664576c2t4UrkcDgUFxen9PR0SZKHh4fWrVunGTNmKC0tTaGhofrnP/+piRMnymazlXNvcSU5d+xI+c92uLu7q1+/fsrIyFDnzp01f/58xk4l4u3trY8++khPP/20srKyFBoaqr59++qFF15wluG6g8JcytiRuO5A+vzzz3XkyBEtWrRIixYtcu6vV6+eEhISJHHdQeEuZexI1l13eEYMAAAAACzGqokAAAAAYDGCGAAAAABYjCAGAAAAABYjiAEAAACAxQhiAAAAAGAxghgAAAAAWIwgBgAAAAAWI4gBAFAKEhISZBiGYmNjy6R+wzD0xRdflEndAADrEcQAAFeFyMhI9enTp9zaDw0NVVJSkpo1ayZJWr9+vQzD0MmTJ8utTwCAK5d7eXcAAICrgc1mU0hISHl3AwBQQTAjBgC46n333Xe66aab5OnpqVq1aumFF15QTk6O83hERIRGjhyp0aNHq1q1agoJCdGkSZNc6ti9e7duueUWeXl56brrrlNUVJTL7YJn35qYkJCgTp06SZICAwNlGIYiIyMlSWFhYXrnnXdc6m7ZsqVLe3v37tVtt93mbGvt2rXnndOhQ4fUv39/BQYGqnr16urdu7cSEhIu96MCAFiEIAYAuKodOnRIPXr0UNu2bfXrr7/qgw8+0Ny5c/Xyyy+7lPvkk0/k6+urLVu26M0339SUKVOcASgvL099+vSRj4+PtmzZog8//FDjxo0rss3Q0FAtW7ZMkhQXF6ekpCTNmDGjRP3Ny8tT3759ZbPZtHnzZs2aNUvPP/+8S5n09HR16tRJfn5++v7777Vhwwb5+fmpe/fuys7OvpiPBwBQTrg1EQBwVXv//fcVGhqqmTNnyjAMXXvttUpMTNTzzz+vCRMmyM0t//8kmzdvrokTJ0qSGjVqpJkzZ2rdunXq2rWr1qxZo/3792v9+vXO2w9feeUVde3atdA2bTabqlWrJkkKDg5WQEBAifsbFRWlXbt2KSEhQXXq1JEkvfrqq7rzzjudZRYvXiw3NzfNmTNHhmFIkj7++GMFBARo/fr1uuOOOy7uQwIAWI4gBgC4qu3atUvt2rVzBhZJ6tChg9LS0vTnn3+qbt26kvKD2Nlq1aqlw4cPS8qf1QoNDXV5Buymm24qs/7WrVvXGcIkqV27di5lYmJitG/fPlWpUsVlf2Zmpvbv318m/QIAlC6CGADgqmaapksIK9gnyWW/3W53KWMYhvLy8oqs41K5ubk52y/gcDjO69u5fTlbXl6ebrzxRi1atOi8sjVq1CiVfgIAyhZBDABwVbvuuuu0bNkylzC1ceNGValSRddcc02J6rj22mt14MAB/fXXX6pZs6YkaevWrcW+x8PDQ5KUm5vrsr9GjRpKSkpyvk5NTVV8fLxLfw8cOKDExETVrl1bkrRp0yaXOlq3bq0lS5YoODhYVatWLdE5AACuLCzWAQC4aqSkpCg2NtZle+SRR3Tw4EGNGDFCu3fv1n/+8x9NnDhRzzzzjPP5sAvp2rWrGjRooMGDB+u3337TDz/84Fyso6iZsnr16skwDK1cuVJHjhxRWlqaJOn222/XwoULFR0dre3bt2vw4MGy2WzO93Xp0kVNmjTRAw88oF9//VXR0dHnLQwycOBABQUFqXfv3oqOjlZ8fLy+++47Pfnkk/rzzz8v5aMDAFiMIAYAuGqsX79erVq1ctkmTpyor7/+Wj/++KNatGihYcOGaciQIRo/fnyJ67XZbPriiy+Ulpamtm3b6uGHH3a+38vLq9D3XHPNNZo8ebJeeOEF1axZU8OHD5ckjRkzRrfddpt69uypHj16qE+fPmrQoIHzfW5ublqxYoWysrJ000036eGHH9Yrr7ziUrePj4++//571a1bV3379lXTpk310EMPKSMjgxkyAKggDLOwm9EBAECxfvjhB91yyy3at2+fS5ACAKAkCGIAAJTAihUr5Ofnp0aNGmnfvn168sknFRgYqA0bNpR31wAAFRCLdQAAUAKnTp3S6NGjdfDgQQUFBalLly6aNm1aeXcLAFBBMSMGAAAAABZjsQ4AAAAAsBhBDAAAAAAsRhADAAAAAIsRxAAAAADAYgQxAAAAALAYQQwAAAAALEYQAwAAAACLEcQAAAAAwGIEMQAAAACw2P8Ho/TsEGdrkxMAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(10, 10))\n", + "\n", + "ax.imshow(hillshade, cmap=\"gray\", extent=dem_extent, origin=\"upper\", alpha=0.55)\n", + "ax.imshow(dem, cmap=\"terrain\", extent=dem_extent, origin=\"upper\", alpha=0.35)\n", + "ax.imshow(radar_img, extent=radar_extent, origin=\"upper\", alpha=0.55)\n", + "\n", + "inmet = stations_in_range[stations_in_range.system == \"INMET\"]\n", + "alr = stations_in_range[stations_in_range.system == \"ALERTARIO\"]\n", + "others = stations_in_range[~stations_in_range.system.isin([\"INMET\", \"ALERTARIO\"])]\n", + "\n", + "ax.scatter(inmet.longitude, inmet.latitude, s=18, c=\"blue\", label=\"INMET\")\n", + "ax.scatter(alr.longitude, alr.latitude, s=18, c=\"green\", label=\"AlertaRio\")\n", + "if not others.empty:\n", + " ax.scatter(others.longitude, others.latitude, s=18, c=\"purple\", label=\"Outros sistemas\")\n", + "ax.scatter(SUMARE_RADAR_LON, SUMARE_RADAR_LAT, marker=\"*\", c=\"red\", s=80, label=\"Radar\")\n", + "\n", + "ax.set_title(\"Radar + estacoes + relevo\")\n", + "ax.set_xlabel(\"Longitude\")\n", + "ax.set_ylabel(\"Latitude\")\n", + "ax.legend(loc=\"lower right\")\n", + "ax.set_xlim(radar_extent[0], radar_extent[1])\n", + "ax.set_ylim(radar_extent[2], radar_extent[3])\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Mapa interativo (folium)\n", + "Cria um mapa com controles de camada para DEM, radar e estacoes.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
Make this Notebook Trusted to load map: File -> Trust Notebook
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dem_norm = (dem - np.nanmin(dem)) / (np.nanmax(dem) - np.nanmin(dem))\n", + "dem_norm = np.clip(dem_norm, 0, 1)\n", + "dem_rgba = cm.gist_earth(dem_norm)\n", + "dem_rgba[..., 3] = 0.55\n", + "dem_rgba[np.isnan(dem_norm)] = (0, 0, 0, 0)\n", + "dem_overlay = (dem_rgba * 255).astype(np.uint8)\n", + "\n", + "dem_bounds_for_folium = [[dem_extent[2], dem_extent[0]], [dem_extent[3], dem_extent[1]]]\n", + "\n", + "m = folium.Map(location=[SUMARE_RADAR_LAT, SUMARE_RADAR_LON], zoom_start=9, tiles='cartodbpositron')\n", + "\n", + "folium.raster_layers.ImageOverlay(\n", + " image=dem_overlay,\n", + " bounds=dem_bounds_for_folium,\n", + " name=\"Relevo (DEM)\",\n", + " opacity=1,\n", + " origin=\"upper\",\n", + ").add_to(m)\n", + "\n", + "folium.raster_layers.ImageOverlay(\n", + " image=str(RADAR_IMAGE_FILE),\n", + " bounds=[[lat_min, lon_min], [lat_max, lon_max]],\n", + " name=\"Radar Sumare\",\n", + " opacity=0.6,\n", + ").add_to(m)\n", + "\n", + "layer_inmet = folium.FeatureGroup(name=\"Estacoes INMET\", show=True)\n", + "layer_alerta = folium.FeatureGroup(name=\"Estacoes AlertaRio\", show=True)\n", + "layer_others = folium.FeatureGroup(name=\"Outras estacoes\", show=True)\n", + "\n", + "color_by_system = {\n", + " \"INMET\": \"blue\",\n", + " \"ALERTARIO\": \"green\",\n", + "}\n", + "\n", + "for _, row in stations_in_range.iterrows():\n", + " lat, lon = row.latitude, row.longitude\n", + " name = row.get(\"name\", \"Estacao\")\n", + " system = row.get(\"system\", \"\")\n", + " color = color_by_system.get(system, \"purple\")\n", + "\n", + " marker = folium.CircleMarker(\n", + " location=[lat, lon],\n", + " radius=3,\n", + " color=color,\n", + " fill=True,\n", + " fill_opacity=0.9,\n", + " popup=f\"{name}
Sistema: {system}
({lat:.4f}, {lon:.4f})\",\n", + " )\n", + "\n", + " if system == \"INMET\":\n", + " marker.add_to(layer_inmet)\n", + " elif system == \"ALERTARIO\":\n", + " marker.add_to(layer_alerta)\n", + " else:\n", + " marker.add_to(layer_others)\n", + "\n", + "layer_inmet.add_to(m)\n", + "layer_alerta.add_to(m)\n", + "layer_others.add_to(m)\n", + "folium.LayerControl(collapsed=False).add_to(m)\n", + "\n", + "m\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Gerar o DEM com elevation\n", + "Use esta célula apenas se precisar baixar o DEM novamente. Altere o caminho de saída se necessário.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "# !eio clip -o ../../data/RJ-30m-DEM.tif --bounds\n", + "# -43.8906028271505 -23.1339033365138 -43.04835145732227 -22.649724748272934" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "b10eb996", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Altitude para alto_da_boa_vista (ALERTARIO): 354.00 m\n" + ] + } + ], + "source": [ + "# Funcao para obter altitude (m) no ponto de uma estacao\n", + "\n", + "def altitude_at(lat: float, lon: float, dem_array=dem, dem_extent=dem_extent, pixel_w=None, pixel_h=None):\n", + " \"Retorna a altitude estimada (em metros) para lat/lon usando o DEM carregado.\"\n", + " minx, maxx, miny, maxy = dem_extent\n", + " if not (miny <= lat <= maxy and minx <= lon <= maxx):\n", + " raise ValueError(\"Ponto fora da area do DEM\")\n", + "\n", + " # Pixel size (usa os valores retornados pelo load_dem, se disponiveis)\n", + " if pixel_w is None or pixel_h is None:\n", + " px_w = (maxx - minx) / dem_array.shape[1]\n", + " px_h = (maxy - miny) / dem_array.shape[0]\n", + " else:\n", + " px_w, px_h = pixel_w, pixel_h\n", + "\n", + " col = int((lon - minx) / px_w)\n", + " row = int((maxy - lat) / px_h) # origem superior\n", + "\n", + " if row < 0 or row >= dem_array.shape[0] or col < 0 or col >= dem_array.shape[1]:\n", + " raise ValueError(\"Indice fora dos limites do raster\")\n", + "\n", + " return float(dem_array[row, col])\n", + "\n", + "# Exemplo: usa a primeira estacao dentro do alcance\n", + "if not stations_in_range.empty:\n", + " sample_row = stations_in_range.iloc[0]\n", + " alt = altitude_at(sample_row.latitude, sample_row.longitude)\n", + " print(f\"Altitude para {sample_row.station_id} ({sample_row.system}): {alt:.2f} m\")\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.19" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/ws_alertario.ipynb b/notebooks/surface_stations/alertario.ipynb similarity index 100% rename from notebooks/ws_alertario.ipynb rename to notebooks/surface_stations/alertario.ipynb diff --git a/notebooks/surface_stations/inmet.ipynb b/notebooks/surface_stations/inmet.ipynb new file mode 100644 index 00000000..1b5a4d4b --- /dev/null +++ b/notebooks/surface_stations/inmet.ipynb @@ -0,0 +1,659 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 6, + "id": "b9dd9653", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " DC_NOME PRE_INS TEM_SEN VL_LATITUDE PRE_MAX UF \\\n", + "0 SEROPÉDICA-ECOLOGIA AGRÍCOLA 1006.6 24.7 -22.757778 1006.6 RJ \n", + "1 SEROPÉDICA-ECOLOGIA AGRÍCOLA 1007.0 24.8 -22.757778 1007.0 RJ \n", + "2 SEROPÉDICA-ECOLOGIA AGRÍCOLA 1007.0 24.8 -22.757778 1007.1 RJ \n", + "3 SEROPÉDICA-ECOLOGIA AGRÍCOLA 1006.3 24.6 -22.757778 1007.1 RJ \n", + "4 SEROPÉDICA-ECOLOGIA AGRÍCOLA 1005.7 24.5 -22.757778 1006.4 RJ \n", + "\n", + " RAD_GLO PTO_INS TEM_MIN VL_LONGITUDE ... VEN_VEL PTO_MIN TEM_MAX \\\n", + "0 1.1 21.0 22.1 -43.684722 ... 0.2 20.9 22.6 \n", + "1 -1.0 21.2 21.9 -43.684722 ... 0.1 20.9 22.2 \n", + "2 -0.7 21.3 22.0 -43.684722 ... 0.3 21.1 22.2 \n", + "3 -1.0 21.2 21.9 -43.684722 ... 0.0 21.1 22.1 \n", + "4 -1.6 21.1 21.7 -43.684722 ... 0.0 21.0 21.9 \n", + "\n", + " TEN_BAT VEN_RAJ TEM_CPU TEM_INS UMD_INS CD_ESTACAO HR_MEDICAO \n", + "0 12.1 1.4 23.0 22.2 93.0 A601 0 \n", + "1 12.1 0.7 23.0 22.1 95.0 A601 100 \n", + "2 12.1 0.6 23.0 22.1 96.0 A601 200 \n", + "3 12.0 0.9 23.0 21.9 96.0 A601 300 \n", + "4 12.0 0.1 23.0 21.8 96.0 A601 400 \n", + "\n", + "[5 rows x 27 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "df = pd.read_parquet(\"../../data/ws/inmet/A601.parquet\")\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "cb3b47b0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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temperaturebarometric_pressurerelative_humiditywind_direction_uwind_direction_vhour_sinhour_cosprecipitation
2011-01-01 00:00:000.3993990.3141990.9176470.4535230.4168690.5000001.0000000.0
2011-01-01 01:00:000.3873870.3262840.9411760.4654370.4185540.6294100.9829630.0
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2011-01-01 04:00:000.3783780.3081570.9529410.4625600.4230900.9330130.7500000.0
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" + ], + "text/plain": [ + " temperature barometric_pressure relative_humidity \\\n", + "2011-01-01 00:00:00 0.399399 0.314199 0.917647 \n", + "2011-01-01 01:00:00 0.387387 0.326284 0.941176 \n", + "2011-01-01 02:00:00 0.387387 0.329305 0.952941 \n", + "2011-01-01 03:00:00 0.384384 0.329305 0.952941 \n", + "2011-01-01 04:00:00 0.378378 0.308157 0.952941 \n", + "\n", + " wind_direction_u wind_direction_v hour_sin hour_cos \\\n", + "2011-01-01 00:00:00 0.453523 0.416869 0.500000 1.000000 \n", + "2011-01-01 01:00:00 0.465437 0.418554 0.629410 0.982963 \n", + "2011-01-01 02:00:00 0.455215 0.408821 0.750000 0.933013 \n", + "2011-01-01 03:00:00 0.462560 0.423090 0.853553 0.853553 \n", + "2011-01-01 04:00:00 0.462560 0.423090 0.933013 0.750000 \n", + "\n", + " precipitation \n", + "2011-01-01 00:00:00 0.0 \n", + "2011-01-01 01:00:00 0.0 \n", + "2011-01-01 02:00:00 0.0 \n", + "2011-01-01 03:00:00 0.2 \n", + "2011-01-01 04:00:00 0.0 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "df = pd.read_parquet(\"../../data/ws/inmet/A601_preprocessed.parquet.gzip\")\n", + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "a9a24913", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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temperaturebarometric_pressurerelative_humiditywind_direction_uwind_direction_vhour_sinhour_cosprecipitation
2024-11-24 19:00:000.4984980.5347430.5411760.5284840.5456810.0170370.6294100.2
2024-11-24 20:00:000.4954950.5347430.5647060.5577610.5472440.0669870.7500000.0
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" + ], + "text/plain": [ + " temperature barometric_pressure relative_humidity \\\n", + "2024-11-24 19:00:00 0.498498 0.534743 0.541176 \n", + "2024-11-24 20:00:00 0.495495 0.534743 0.564706 \n", + "2024-11-24 21:00:00 0.456456 0.552870 0.682353 \n", + "2024-11-24 22:00:00 0.405405 0.570997 0.717647 \n", + "2024-11-24 23:00:00 0.381381 0.586103 0.776471 \n", + "\n", + " wind_direction_u wind_direction_v hour_sin hour_cos \\\n", + "2024-11-24 19:00:00 0.528484 0.545681 0.017037 0.629410 \n", + "2024-11-24 20:00:00 0.557761 0.547244 0.066987 0.750000 \n", + "2024-11-24 21:00:00 0.555399 0.535681 0.146447 0.853553 \n", + "2024-11-24 22:00:00 0.553392 0.509153 0.250000 0.933013 \n", + "2024-11-24 23:00:00 0.556228 0.489969 0.370590 0.982963 \n", + "\n", + " precipitation \n", + "2024-11-24 19:00:00 0.2 \n", + "2024-11-24 20:00:00 0.0 \n", + "2024-11-24 21:00:00 0.2 \n", + "2024-11-24 22:00:00 0.0 \n", + "2024-11-24 23:00:00 0.2 " + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.tail()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "79ab5b3e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(118822, 1)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "43ad90fd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Index: 121848 entries, 0 to 7895\n", + "Data columns (total 27 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 DC_NOME 121848 non-null object \n", + " 1 PRE_INS 120509 non-null float64\n", + " 2 TEM_SEN 121624 non-null float64\n", + " 3 VL_LATITUDE 121848 non-null float64\n", + " 4 PRE_MAX 120492 non-null float64\n", + " 5 UF 121848 non-null object \n", + " 6 RAD_GLO 121677 non-null float64\n", + " 7 PTO_INS 121633 non-null float64\n", + " 8 TEM_MIN 121720 non-null float64\n", + " 9 VL_LONGITUDE 121848 non-null float64\n", + " 10 UMD_MIN 121606 non-null float64\n", + " 11 PTO_MAX 121605 non-null float64\n", + " 12 VEN_DIR 121744 non-null float64\n", + " 13 DT_MEDICAO 121848 non-null object \n", + " 14 CHUVA 118822 non-null float64\n", + " 15 PRE_MIN 120492 non-null float64\n", + " 16 UMD_MAX 121607 non-null float64\n", + " 17 VEN_VEL 121744 non-null float64\n", + " 18 PTO_MIN 121604 non-null float64\n", + " 19 TEM_MAX 121717 non-null float64\n", + " 20 TEN_BAT 121747 non-null float64\n", + " 21 VEN_RAJ 121724 non-null float64\n", + " 22 TEM_CPU 121747 non-null float64\n", + " 23 TEM_INS 121737 non-null float64\n", + " 24 UMD_INS 121633 non-null float64\n", + " 25 CD_ESTACAO 121848 non-null object \n", + " 26 HR_MEDICAO 121848 non-null int64 \n", + "dtypes: float64(22), int64(1), object(4)\n", + "memory usage: 26.0+ MB\n" + ] + } + ], + "source": [ + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "c282df46", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['DC_NOME', 'PRE_INS', 'TEM_SEN', 'VL_LATITUDE', 'PRE_MAX', 'UF',\n", + " 'RAD_GLO', 'PTO_INS', 'TEM_MIN', 'VL_LONGITUDE', 'UMD_MIN', 'PTO_MAX',\n", + " 'VEN_DIR', 'DT_MEDICAO', 'CHUVA', 'PRE_MIN', 'UMD_MAX', 'VEN_VEL',\n", + " 'PTO_MIN', 'TEM_MAX', 'TEN_BAT', 'VEN_RAJ', 'TEM_CPU', 'TEM_INS',\n", + " 'UMD_INS', 'CD_ESTACAO', 'HR_MEDICAO'],\n", + " dtype='object')" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "ed282c18", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 2011-01-01\n", + "1 2011-01-01\n", + "2 2011-01-01\n", + "3 2011-01-01\n", + "4 2011-01-01\n", + " ... \n", + "7891 2024-11-24\n", + "7892 2024-11-24\n", + "7893 2024-11-24\n", + "7894 2024-11-24\n", + "7895 2024-11-24\n", + "Name: DT_MEDICAO, Length: 121848, dtype: object" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.DT_MEDICAO" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "5addf156", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 0\n", + "1 100\n", + "2 200\n", + "3 300\n", + "4 400\n", + " ... \n", + "7891 1900\n", + "7892 2000\n", + "7893 2100\n", + "7894 2200\n", + "7895 2300\n", + "Name: HR_MEDICAO, Length: 121848, dtype: int64" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.HR_MEDICAO" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "atmoseer", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.18" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/ws_DEPRECATED.ipynb b/notebooks/surface_stations/ws_DEPRECATED.ipynb similarity index 100% rename from notebooks/ws_DEPRECATED.ipynb rename to notebooks/surface_stations/ws_DEPRECATED.ipynb diff --git a/notebooks/token_data.json b/notebooks/token_data.json new file mode 100644 index 00000000..4d274421 --- /dev/null +++ b/notebooks/token_data.json @@ -0,0 +1 @@ +{"timeToExp": "14399", "token": "eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJhdWQiOiIiLCJwYXNzd29yZCI6Ijd2REh2Z1RtSkp0OGJZaXNsMU04ME00YVFNTEVEdGVocWNnRXZpT1hBNVk9IiwiaXNzIjoiYnIuZ292LmNlbWFkZW4iLCJleHAiOjE3NTgwNDcwMzMsImlhdCI6MTc1ODAzMjYzMywianRpIjoiNDIwYzI2NDktMmZjMi00NTdmLTg2OTUtMzY2M2ZkYjJjNWQ1IiwidXNlcm5hbWUiOiJ1eHkvN3hodXN6MjUwV3lSWFVIdWlrK0ROQUR2Uy9BR1RLTmVjbS9JYmQ0PSJ9.MVr0WxMUwmBxAL5kRfXqPlPu5hYhr1hGbNtuSAnDAGw", "saved_at": 1758043433} \ No newline at end of file diff --git a/notebooks/tpw_2024-01-12 00:00:00_to_2024-01-12 00:00:00.parquet b/notebooks/tpw_2024-01-12 00:00:00_to_2024-01-12 00:00:00.parquet deleted file mode 100644 index 25b7093b..00000000 Binary files a/notebooks/tpw_2024-01-12 00:00:00_to_2024-01-12 00:00:00.parquet and /dev/null differ diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 00000000..ba40bdb5 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,21 @@ +[tool.black] +line-length = 88 +target-version = ["py310"] +extend-exclude = ''' +( + ^/data/ + | ^/downloads/ + | ^/notebooks/ +) +''' + +[tool.ruff] +line-length = 88 +target-version = "py310" + +[tool.ruff.lint] +exclude = ["data", "downloads", "notebooks"] +extend-select = ["I"] + +[tool.ruff.lint.per-file-ignores] +"tests/**" = ["T201"] diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 089beede..00000000 Binary files a/requirements.txt and /dev/null differ diff --git a/scripts/clean_weatherstations.py b/scripts/clean_weatherstations.py new file mode 100644 index 00000000..7264b1c7 --- /dev/null +++ b/scripts/clean_weatherstations.py @@ -0,0 +1,107 @@ +"""Clean config/WeatherStations.csv and save cleaned CSV and parquet. + +Cleans: +- Removes unnamed index column +- Normalizes decimal commas in VL_ALTITUDE to dot and coerces to float +- Coerces VL_LATITUDE / VL_LONGITUDE to float +- Normalizes DT_INICIO_OPERACAO from dd/mm/yyyy to ISO YYYY-MM-DD (when present) +- Strips whitespace and lowercases STATION_ID +- Saves cleaned CSV and parquet to config/ +""" + +import pandas as pd +from pathlib import Path +import sys + +ROOT = Path(__file__).resolve().parents[1] +INPUT = ROOT / "config" / "WeatherStations.csv" +OUT_CSV = ROOT / "config" / "WeatherStations.cleaned.csv" +OUT_PARQUET = ROOT / "config" / "WeatherStations.cleaned.parquet" + + +def parse_date(d): + if pd.isna(d): + return pd.NaT + d = str(d).strip() + if not d: + return pd.NaT + # expected dd/mm/yyyy + try: + return pd.to_datetime(d, dayfirst=True, errors="coerce").date() + except Exception: + return pd.NaT + + +def clean(): + if not INPUT.exists(): + print(f"Input not found: {INPUT}") + sys.exit(1) + + df = pd.read_csv(INPUT, dtype=str) + + # Drop unnamed index if present (first empty column) + if df.columns[0].startswith("Unnamed") or df.columns[0] == "": + df = df.drop(df.columns[0], axis=1) + + # Standardize column names + df.columns = [c.strip() for c in df.columns] + + # Clean station id + if "STATION_ID" in df.columns: + df["STATION_ID"] = df["STATION_ID"].astype(str).str.strip().str.lower() + + # Clean latitude/longitude + for col in ["VL_LATITUDE", "VL_LONGITUDE"]: + if col in df.columns: + # remove quotes and coerce + df[col] = df[col].astype(str).str.replace('"', "") + df[col] = df[col].str.replace(",", ".") + df[col] = pd.to_numeric(df[col], errors="coerce") + + # Clean altitude: replace comma decimal separators, remove quotes, coerce + if "VL_ALTITUDE" in df.columns: + df["VL_ALTITUDE"] = df["VL_ALTITUDE"].astype(str).str.replace('"', "") + df["VL_ALTITUDE"] = df["VL_ALTITUDE"].str.replace(",", ".") + df["VL_ALTITUDE"] = pd.to_numeric(df["VL_ALTITUDE"], errors="coerce") + + # Clean date + if "DT_INICIO_OPERACAO" in df.columns: + df["DT_INICIO_OPERACAO"] = df["DT_INICIO_OPERACAO"].apply(parse_date) + + # Strip station name and status + for col in ["DC_NOME", "SG_ESTADO", "CD_SITUACAO"]: + if col in df.columns: + df[col] = df[col].astype(str).str.strip() + + # Reorder columns to a sensible order if exists + desired = [ + "STATION_ID", + "DC_NOME", + "SG_ESTADO", + "CD_SITUACAO", + "VL_LATITUDE", + "VL_LONGITUDE", + "VL_ALTITUDE", + "DT_INICIO_OPERACAO", + ] + cols = [c for c in desired if c in df.columns] + rest = [c for c in df.columns if c not in cols] + df = df[cols + rest] + + # Save + df.to_csv(OUT_CSV, index=False) + try: + df.to_parquet(OUT_PARQUET, index=False) + except Exception as e: + print("Parquet save failed (pyarrow or fastparquet may be missing):", e) + + # Summary + print("Saved cleaned CSV to:", OUT_CSV) + if OUT_PARQUET.exists(): + print("Saved cleaned Parquet to:", OUT_PARQUET) + print("Rows:", len(df)) + print(df.dtypes) + + +if __name__ == "__main__": + clean() diff --git a/setup.sh b/setup.sh index 84a816f6..b70b17a8 100755 --- a/setup.sh +++ b/setup.sh @@ -1,15 +1,87 @@ #!/bin/bash -# conda environment -conda env create -f config/environment.yml - -mkdir -p ./data -mkdir -p ./data/ws -mkdir -p ./data/as -mkdir -p ./data/NWP -mkdir -p ./data/NWP/ERA5 -mkdir -p ./data/datasets -mkdir -p ./data/goes16 - -# docker image -#TODO docker build -t atmoseer . \ No newline at end of file +set -e # Exit on error + +# Path to environment file +ENV_FILE="config/environment.yml" + +# === Validate setup prerequisites === + +# Check if environment file exists +if [ ! -f "$ENV_FILE" ]; then + echo "Error: File '$ENV_FILE' not found." + exit 1 +fi + +# Check if conda is available +if ! command -v conda &> /dev/null; then + echo "Error: Conda is not installed or not in PATH." + exit 1 +fi + +# Extract environment name +ENV_NAME=$(grep '^name:' "$ENV_FILE" | cut -d ' ' -f2) + +if [ -z "$ENV_NAME" ]; then + echo "Error: Could not determine the environment name from $ENV_FILE." + exit 1 +fi + +# === Remove existing conda environment === + +if conda info --envs | awk '{print $1}' | grep -Fxq "$ENV_NAME"; then + echo "Removing existing environment: $ENV_NAME" + conda env remove -n "$ENV_NAME" || { + echo "Error: Failed to remove environment $ENV_NAME." + exit 1 + } +fi + +# === Create conda environment === + +echo "Creating new environment: $ENV_NAME" +conda env create -f "$ENV_FILE" || { + echo "Error: Failed to create environment $ENV_NAME." + exit 1 +} + +# === Create required data directories === + +echo "Creating data directories..." +mkdir -p ./data/ws \ + ./data/as \ + ./data/NWP/ERA5 \ + ./data/datasets \ + ./data/GPM \ + ./data/goes16 + +echo "Data directory setup complete." + +# === Setup NASA Earthdata authentication === + +echo "Setting up NASA Earthdata credentials..." + +if [[ -z "$EARTHDATA_USER" || -z "$EARTHDATA_PASS" ]]; then + echo "ERROR: EARTHDATA_USER and EARTHDATA_PASS environment variables must be set." + echo "Export them before running this script, e.g.:" + echo " export EARTHDATA_USER='your_username'" + echo " export EARTHDATA_PASS='your_password'" + exit 1 +fi + +NETRC_PATH="$HOME/.netrc" +echo "machine urs.earthdata.nasa.gov login $EARTHDATA_USER password $EARTHDATA_PASS" > "$NETRC_PATH" +chmod 600 "$NETRC_PATH" +echo ".netrc created at $NETRC_PATH" + +URS_COOKIES_PATH="$HOME/.urs_cookies" +touch "$URS_COOKIES_PATH" +chmod 600 "$URS_COOKIES_PATH" +echo ".urs_cookies created at $URS_COOKIES_PATH" + +echo "NASA Earthdata setup complete." + +# === Optional: Build docker image === +# TODO: docker build -t atmoseer . + +echo "Setup complete." diff --git a/src/__pycache__/__init__.cpython-310.pyc b/src/__pycache__/__init__.cpython-310.pyc deleted file mode 100644 index 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BaseDataSource(ABC): - @abstractmethod - def get_data(self, station_id, initial_datetime, final_datetime): - pass \ No newline at end of file diff --git a/src/build_datasets.py b/src/build_datasets.py deleted file mode 100644 index 6bcc1cc9..00000000 --- a/src/build_datasets.py +++ /dev/null @@ -1,675 +0,0 @@ -import pandas as pd -import numpy as np -import sys -import pickle -from utils.near_stations import prox - -from era5_data_source import Era5ReanalisysDataSource - -import globals - -from util import find_contiguous_observation_blocks, add_missing_indicator_column, split_dataframe_by_date -from utils.windowing import apply_windowing -import util as util -import argparse -from subsampling import apply_subsampling -import logging -import yaml -import datetime - -from statsmodels.stats.diagnostic import acorr_ljungbox -import matplotlib.pyplot as plt - -# def format_for_binary_classification(y_train, y_val, y_test): -# y_train_oc = map_to_binary_precipitation_levels(y_train) -# y_val_oc = map_to_binary_precipitation_levels(y_val) -# y_test_oc = map_to_binary_precipitation_levels(y_test) -# return y_train_oc, y_val_oc, y_test_oc - -# def format_for_ordinal_classification(y_train, y_val, y_test): -# y_train_oc = map_to_precipitation_levels(y_train) -# y_val_oc = map_to_precipitation_levels(y_val) -# y_test_oc = map_to_precipitation_levels(y_test) -# return y_train_oc, y_val_oc, y_test_oc - -def apply_sliding_window(df: pd.DataFrame, target_idx: int, window_size: int): - """ - This function applies the sliding window preprocessing technique to generate data and response - matrices (that is, X and y) from an input time series represented as a pandas DataFrame. This - DataFrame is supposed to have a datetime index that corresponds to the timestamps in the time series. - - @see: https://stackoverflow.com/questions/8269916/what-is-sliding-window-algorithm-examples - - Note that this function takes the eventual existence of gaps in the input time series - into account. In particular, the windowing operation is performed in each separate - contiguous block of observations. - """ - contiguous_observation_blocks = list( - find_contiguous_observation_blocks(df)) - - is_first_block = True - - for block in contiguous_observation_blocks: - start = block[0] - end = block[1] - - # logging.info(df[start:end].shape) - if df[start:end].shape[0] < window_size + 1: - continue - - arr = np.array(df[start:end]) - X_block, y_block = apply_windowing(arr, - initial_time_step=0, - max_time_step=len(arr)-window_size-1, - window_size=window_size, - target_idx=target_idx) - y_block = y_block.reshape(-1, 1) - if is_first_block: - X = X_block - y = y_block - is_first_block = False - else: - X = np.concatenate((X, X_block), axis=0) - y = np.concatenate((y, y_block), axis=0) - - return X, y - -def generate_windowed_split(train_df, val_df, test_df, target_name, window_size): - target_idx = train_df.columns.get_loc(target_name) - logging.info(f"Position (index) of target variable {target_name}: {target_idx}") - X_train, y_train = apply_sliding_window(train_df, target_idx, window_size) - X_val, y_val = apply_sliding_window(val_df, target_idx, window_size) - X_test, y_test = apply_sliding_window(test_df, target_idx, window_size) - return X_train, y_train, X_val, y_val, X_test, y_test - -def get_goes16_data_for_weather_station(df: pd.DataFrame, max_event: bool = False) -> pd.DataFrame: - """ - Filters lightning event data in a DataFrame based on latitude and longitude boundaries for a specific weather station - and calculates the maximum or median value of the 'event_energy' column on an hourly basis. - - Args: - df (pd.DataFrame): DataFrame containing lightning event data with columns 'event_energy', 'event_lat', and 'event_lon'. - station_id (str): Identifier for the weather station to filter coordinates. - max_event (bool, optional): Flag to determine whether to calculate the maximum event energy or the median event energy. - Defaults to True, calculating the maximum event energy. - - Returns: - pd.DataFrame: A new DataFrame with the same columns as the input DataFrame, but with lightning events outside of the - specified latitude and longitude boundaries removed, and the maximum or median value of 'event_energy' for each hour. - - """ - - filtered_df = util.min_max_normalize(df) - - result_df = filtered_df[["event_energy"]] - - if max_event: - result_df = result_df.resample('H').max() - else: - result_df = result_df.resample('H').mean() - - return result_df - -def gaussian_noise(df, column_name, mu=0, sigma=1): - - # Generate Gaussian noise - noise = np.random.normal(mu, sigma, size=df.shape[0]) - - # Add noise to the column - df[column_name] = df[column_name] + noise - - return df - - -def add_user_specified_data_sources( - station_id, - join_AS_datasource, - join_reanalisys_datasource, - join_goes16_glm_datasource, - join_goes16_tpw_datasource, - join_colorcord_datasource, - join_conv2d_datasource, - join_autoencoder_datasource, - df_ws, - min_datetime, - max_datetime): - joined_df = df_ws - - if join_reanalisys_datasource: - logging.info(f"Loading reanalisys (ERA5) data near the weather station {station_id}...") - data_source = Era5ReanalisysDataSource() - df_era5_reanalisys = data_source.get_data(station_id, min_datetime, max_datetime) - logging.info(f"Done! Shape = {df_era5_reanalisys.shape}.") - assert (not df_era5_reanalisys.isnull().values.any().any()) - - joined_df = pd.merge(joined_df, df_era5_reanalisys, how='left', left_index=True, right_index=True) - - logging.info(f"Reanalisys data successfully joined; resulting shape = {joined_df.shape}.") - logging.info(df_ws.index.difference(joined_df.index).shape) - logging.info(joined_df.index.difference(df_ws.index).shape) - - logging.info(df_era5_reanalisys.index.intersection(df_ws.index).shape) - logging.info(df_era5_reanalisys.index.difference(df_ws.index).shape) - logging.info(df_ws.index.difference(df_era5_reanalisys.index).shape) - logging.info(df_ws.index.difference(df_era5_reanalisys.index)) - - shape_before_dropna = joined_df.shape - joined_df = joined_df.dropna() - shape_after_dropna = joined_df.shape - logging.info(f"Removed NaN rows in merged dataset; Shapes before/after dropna: {shape_before_dropna}/{shape_after_dropna}.") - - assert (not joined_df.isnull().values.any().any()) - - if join_AS_datasource: - filename = globals.AS_DATA_DIR + 'SBGL_indices_1997_2023.parquet.gzip' - logging.info(f"Loading atmospheric sounding indices from {filename}...") - df_as = pd.read_parquet(filename) - logging.info(f"Done! Shape = {df_as.shape}.") - - format_string = '%Y-%m-%d %H:%M:%S' - - # - # Add index to dataframe using the observation's timestamps. - df_as['Datetime'] = pd.to_datetime(df_as['time'], format=format_string) - df_as = df_as.set_index(pd.DatetimeIndex(df_as['Datetime'])) - logging.info(f"Range of timestamps in the atmospheric sounding data source: [{min(df_as.index)}, {max(df_as.index)}]") - - # - # Remove time-related columns since now this information is in the index. - df_as = df_as.drop(['time', 'Datetime'], axis = 1) - - joined_df = pd.merge(joined_df, df_as, how='left', left_index=True, right_index=True) - - logging.info(f"Atmospheric sounding data successfully joined; resulting shape: {joined_df.shape}.") - - joined_df = add_missing_indicator_column(joined_df, "asi_idx_missing") - logging.info(f"Shape after adding missing indicator column: {joined_df.shape}.") - - logging.info(f"Doing interpolation to imput missing values on the sounding indices...") - joined_df['cape'] = joined_df['cape'].interpolate(method='linear') - joined_df['cin'] = joined_df['cin'].interpolate(method='linear') - joined_df['lift'] = joined_df['lift'].interpolate(method='linear') - joined_df['k'] = joined_df['k'].interpolate(method='linear') - joined_df['total_totals'] = joined_df['total_totals'].interpolate(method='linear') - joined_df['showalter'] = joined_df['showalter'].interpolate(method='linear') - logging.info("Done!") - - # At the beggining of the joined dataframe, a few entries may remain with NaN values. - # The code below gets rid of these entries. - # see https://stackoverflow.com/questions/27905295/how-to-replace-nans-by-preceding-or-next-values-in-pandas-dataframe - joined_df.fillna(method='bfill', inplace=True) - - # TODO: data normalization - # TODO: implement interpolation - # TODO: deal with missing values (see https://youtu.be/DKmDJJzayZw) - # TODO: Imputing with MICE (see https://towardsdatascience.com/imputing-missing-data-with-simple-and-advanced-techniques-f5c7b157fb87) - # TODO: use other sounding stations (?) (see tempo.inmet.gov.br/Sondagem/) - - if join_goes16_tpw_datasource: - logging.info(f"Loading GOES16 TPW product for weather station {station_id}...") - df_tpw = pd.read_parquet(f'{globals.TPW_DATA_DIR}/{station_id}.parquet') - logging.info(f"Done! Shape = {df_tpw.shape}.") - - logging.info(f"Range of timestamps in the TPW data: [{min(df_tpw.index)}, {max(df_tpw.index)}]") - - joined_df = joined_df.join(df_tpw, how='inner') - - logging.info(f"TPW data successfully joined; resulting shape: {joined_df.shape}.") - - # print(joined_df.columns) - - logging.info(f"Adding missing indicator column...") - joined_df = add_missing_indicator_column(joined_df, "tpw_idx_missing") - logging.info(f"Done! New shape: {joined_df.shape}.") - - logging.info(f"Doing interpolation to imput missing values on the TPW values...") - joined_df['tpw_value'] = joined_df['tpw_value'].interpolate(method='linear') - logging.info(f"Done!") - - # At the beggining of the joined dataframe, a few entries may remain with NaN values. - # The code below gets rid of these entries. - # see https://stackoverflow.com/questions/27905295/how-to-replace-nans-by-preceding-or-next-values-in-pandas-dataframe - joined_df.fillna(method='bfill', inplace=True) - - shape_before_dropna = joined_df.shape - joined_df = joined_df.dropna() - shape_after_dropna = joined_df.shape - assert shape_before_dropna == shape_after_dropna - - assert (not joined_df.isnull().values.any().any()) - - if join_goes16_glm_datasource: - print(f"Loading GLM (Goes 16) data near the weather station {station_id}...", end= "") - df_lightning = pd.read_parquet(f'data/parquet_files/glm_{station_id}_preprocessed_file.parquet') - df_lightning_filtered = get_goes16_data_for_weather_station(df_lightning) - print(df_lightning_filtered.isnull().sum()) - df_lightning_filtered.fillna(method="bfill", inplace=True) - assert (not df_lightning_filtered.isnull().values.any().any()) - joined_df = pd.merge(df_ws, df_lightning_filtered, how='left', left_index=True, right_index=True) - - joined_df['event_energy'].fillna(method="bfill", inplace=True) - - # Ruido branco - lb_test_stat = acorr_ljungbox(joined_df['event_energy'], lags=10) - print("Estatísticas do Teste:", lb_test_stat) - plt.axhline(y=0.05, color='r', linestyle='--') - plt.title('Valores p do Teste de Ljung-Box') - plt.xlabel('Lag') - plt.ylabel('Valor p') - plt.show() - - print(f"GLM data successfully joined; resulting shape = {joined_df.shape}.") - print(df_ws.index.difference(joined_df.index).shape) - print(joined_df.index.difference(df_ws.index).shape) - - print(df_lightning_filtered.index.intersection(df_ws.index).shape) - print(df_lightning_filtered.index.difference(df_ws.index).shape) - print(df_ws.index.difference(df_lightning_filtered.index).shape) - print(df_ws.index.difference(df_lightning_filtered.index)) - - shape_before_dropna = joined_df.shape - joined_df = joined_df.dropna() - shape_after_dropna = joined_df.shape - print(f"Removed NaN rows in merge data; Shapes before/after dropna: {shape_before_dropna}/{shape_after_dropna}.") - - assert (not joined_df.isnull().values.any().any()) - - if join_colorcord_datasource: - filename = f'FEATURE_{station_id}_COLORCORD.csv' - logging.info(f"Loading image features {filename}...") - df_new = pd.read_csv(filename) - logging.info(f"Done! Shape = {df_new.shape}.") - df_new['date'] = pd.to_datetime(df_new['date'], format="%Y-%m-%d--%H%M%S") - df_new['date'] = df_new['date'].dt.floor('H') - del df_new["Estação"] - df_new = df_new.groupby('date', as_index=False).mean() - - format_string = '%Y-%m-%d %H:%M:%S' - - df_new['Datetime'] = pd.to_datetime(df_new['date'], format=format_string) - df_new = df_new.set_index(pd.DatetimeIndex(df_new['Datetime'])) - logging.info(f"Range of timestamps in the image feature data source: [{min(df_new.index)}, {max(df_new.index)}]") - - df_new = df_new.drop(['date', 'Datetime', "Estação"], axis = 1) - joined_df = pd.merge(joined_df, df_new, how='left', left_index=True, right_index=True) - joined_df = joined_df.fillna(0) - - logging.info(f"Image features data successfully joined; resulting shape: {joined_df.shape}.") - - elif join_conv2d_datasource: - filename = f'FEATURE_{station_id}_CONV2D.csv' - logging.info(f"Loading image features {filename}...") - df_new = pd.read_csv(filename) - logging.info(f"Done! Shape = {df_new.shape}.") - df_new['date'] = pd.to_datetime(df_new['date'], format="%Y-%m-%d--%H%M%S") - df_new['date'] = df_new['date'].dt.floor('H') - del df_new["Estação"] - df_new = df_new.groupby('date', as_index=False).mean() - - format_string = '%Y-%m-%d %H:%M:%S' - - df_new['Datetime'] = pd.to_datetime(df_new['date'], format=format_string) - df_new = df_new.set_index(pd.DatetimeIndex(df_new['Datetime'])) - logging.info(f"Range of timestamps in the image feature data source: [{min(df_new.index)}, {max(df_new.index)}]") - - df_new = df_new.drop(['date', 'Datetime'], axis = 1) - joined_df = pd.merge(joined_df, df_new, how='left', left_index=True, right_index=True) - joined_df = joined_df.fillna(0) - - logging.info(f"Image features data successfully joined; resulting shape: {joined_df.shape}.") - - elif join_autoencoder_datasource: - filename = f'FEATURE_{station_id}_AUTOENCODER.csv' - logging.info(f"Loading image features {filename}...") - df_new = pd.read_csv(filename) - logging.info(f"Done! Shape = {df_new.shape}.") - df_new['date'] = pd.to_datetime(df_new['date'], format="%Y-%m-%d--%H%M%S") - df_new['date'] = df_new['date'].dt.ceil('H') - del df_new["Estação"] - df_new = df_new.groupby('date', as_index=False).mean() - - format_string = '%Y-%m-%d %H:%M:%S' - - df_new['Datetime'] = pd.to_datetime(df_new['date'], format=format_string) - df_new = df_new.set_index(pd.DatetimeIndex(df_new['Datetime'])) - logging.info(f"Range of timestamps in the image feature data source: [{min(df_new.index)}, {max(df_new.index)}]") - - df_new = df_new.drop(['date', 'Datetime'], axis = 1) - joined_df = pd.merge(joined_df, df_new, how='left', left_index=True, right_index=True) - joined_df = joined_df.fillna(0) - - logging.info(f"Image features data successfully joined; resulting shape: {joined_df.shape}.") - - assert (not joined_df.isnull().values.any().any()) - - return joined_df - -def build_datasets(station_id: str, - input_folder: str, - train_start_threshold: datetime.datetime, - train_test_threshold: datetime.datetime, - join_AS_data_source: bool, - join_reanalisys_datasource: bool, - join_goes16_glm_datasource: bool, - join_goes16_tpw_datasource: bool, - join_colorcord_datasource: bool, - join_conv2d_datasource: bool, - join_autoencoder_datasource: bool, - subsampling_procedure: str): - ''' - This function joins a set of datasources to build datasets. These resulting datasets are used to fit the - parameters of precipitation models down the AtmoSeer pipeline. Each datasource contributes with a group - of features to build the datasets that are going to be used for training and validating the prediction models. - - Notice that, when joining the user-specified data sources, there is always a station of interest, that is, - a weather station that will provide the values of the target variable (in our case, precipitation). - It can even be the case that the only user-specified data source is this weather station. - ''' - - pipeline_id = station_id - if join_reanalisys_datasource: - pipeline_id = pipeline_id + '_N' - if join_AS_data_source: - pipeline_id = pipeline_id + '_R' - if join_goes16_glm_datasource: - pipeline_id = pipeline_id + '_L' - if join_goes16_tpw_datasource: - pipeline_id = pipeline_id + '_T' - if join_colorcord_datasource: - pipeline_id = pipeline_id + '_I' - if join_conv2d_datasource: - pipeline_id = pipeline_id + '_C' - if join_autoencoder_datasource: - pipeline_id = pipeline_id + '_A' - - logging.info(f"Loading observations for weather station {station_id}...") - df_ws = pd.read_parquet(input_folder + station_id + "_preprocessed.parquet.gzip") - logging.info(f"Done! Shape = {df_ws.shape}.\n") - - #### - # Apply a filtering step, with the purpose of disregarding all observations - # before a user-specified timestamp. This is useful when doing training - # experiments with datasources whose start of operation was AFTER the one - # corresponding to the WSoI. - #### - if train_start_threshold is not None: - logging.info(f"Applying start threshold filtering...") - logging.info(f'Timestamp from which examples will be considered: {train_start_threshold}') - shape_before_month_filtering = df_ws.shape - df_ws = df_ws[df_ws.index >= train_start_threshold] - shape_after_month_filtering = df_ws.shape - logging.info(f"Done! Shapes before/after: {shape_before_month_filtering}/{shape_after_month_filtering}\n") - - #### - # Apply a filtering step, with the purpose of disregarding all observations made between - # what we consider to be the drought period of a year (months of June, July, and August). - #### - logging.info(f"Applying month filtering...") - shape_before_month_filtering = df_ws.shape - df_ws = df_ws[df_ws.index.month.isin([9, 10, 11, 12, 1, 2, 3, 4, 5])].sort_index(ascending=True) - shape_after_month_filtering = df_ws.shape - logging.info(f"Done! Shapes before/after: {shape_before_month_filtering}/{shape_after_month_filtering}\n") - - assert (not df_ws.isnull().values.any().any()) - - ##### - # Start with the mandatory data source (i.e., the one represented by the weather - # station of interest) and sequentially join the other user-specified datasources. - ##### - joined_df = df_ws - min_datetime = min(joined_df.index) - max_datetime = max(joined_df.index) - - ##### - # Now add user-specified data sources. - ##### - logging.info(f'Going to add features from the user-specified datasources...') - joined_df = add_user_specified_data_sources( - station_id, - join_AS_data_source, - join_reanalisys_datasource, - join_goes16_glm_datasource, - join_goes16_tpw_datasource, - join_colorcord_datasource, - join_conv2d_datasource, - join_autoencoder_datasource, - df_ws, - min_datetime, - max_datetime) - logging.info(f'Done!\n') - - # - # Save train/val/test DataFrames for future error analisys. - filename = globals.DATASETS_DIR + pipeline_id + '.parquet.gzip' - logging.info(f'Saving joined dataset for pipeline {pipeline_id} to file {filename}.') - joined_df.to_parquet(filename, compression='gzip') - logging.info(f'Done!\n') - - assert (not joined_df.isnull().values.any().any()) - - ##### - # Perform train/val/test split - ##### - logging.info(f'Going to split examples (train/val/test)...') - logging.info(f'Timestamp used to split train and test examples: {train_test_threshold}') - df_train_val, df_test = split_dataframe_by_date(joined_df, train_test_threshold) - - # TODO: parameterize with user-defined train/val splitting proportions. - n = len(df_train_val) - train_val_split = 0.8 - train_upper_limit = int(n*train_val_split) - df_train = df_train_val[0:train_upper_limit] - df_val = df_train_val[train_upper_limit:] - - assert (not df_train.isnull().values.any().any()) - assert (not df_val.isnull().values.any().any()) - assert (not df_test.isnull().values.any().any()) - - logging.info(f"Range of timestamps in the training dataset: [{min(df_train.index)}, {max(df_train.index)}]") - logging.info(f"Range of timestamps in the validation dataset: [{min(df_val.index)}, {max(df_val.index)}]") - logging.info(f"Range of timestamps in the test dataset: [{min(df_test.index)}, {max(df_test.index)}]") - logging.info(f'Number of examples in each dataset (train/val/test): {len(df_train)}/{len(df_val)}/{len(df_test)}.') - logging.info(f'Done!\n') - - # - # Save train/val/test DataFrames for future error analisys. - logging.info(f'Saving each train/val/test dataset for pipeline {pipeline_id} as a parquet file.') - df_train.to_parquet(globals.DATASETS_DIR + pipeline_id + '_train.parquet.gzip', compression='gzip') - df_val.to_parquet(globals.DATASETS_DIR + pipeline_id + '_val.parquet.gzip', compression='gzip') - df_test.to_parquet(globals.DATASETS_DIR + pipeline_id + '_test.parquet.gzip', compression='gzip') - logging.info(f'Done!\n') - - assert (not df_train.isnull().values.any().any()) - assert (not df_val.isnull().values.any().any()) - assert (not df_test.isnull().values.any().any()) - - if (station_id in globals.ALERTARIO_GAUGE_STATION_IDS): - df_train = gaussian_noise(df_train, "barometric_pressure", mu=1000) - df_val = gaussian_noise(df_val, "barometric_pressure", mu=1000) - df_test = gaussian_noise(df_test, "barometric_pressure", mu=1000) - - # - # Normalize the columns in train/val/test dataframes. This is done as a preparation step for applying - # the sliding window technique, since the target variable is going to be used as lag feature. - # (see, e.g., https://www.mikulskibartosz.name/forecasting-time-series-using-lag-features/) - # (see also https://datascience.stackexchange.com/questions/72480/what-is-lag-in-time-series-forecasting) - logging.info('Normalizing the features in train/val/test dataframes...') - _, target_name = util.get_relevant_variables(station_id) - min_target_value_in_train, max_target_value_in_train = min(df_train[target_name]), max(df_train[target_name]) - min_target_value_in_val, max_target_value_in_val = min(df_val[target_name]), max(df_val[target_name]) - min_target_value_in_test, max_target_value_in_test = min(df_test[target_name]), max(df_test[target_name]) - df_train = util.min_max_normalize(df_train) - df_val = util.min_max_normalize(df_val) - df_test = util.min_max_normalize(df_test) - logging.info(f'Done!\n') - - assert (not df_train.isnull().values.any().any()) - assert (not df_val.isnull().values.any().any()) - assert (not df_test.isnull().values.any().any()) - - # - # Apply sliding window method to build examples (instances) of train/val/test datasets - with open('./config/config.yaml', 'r') as file: - config = yaml.safe_load(file) - window_size = config["preproc"]["SLIDING_WINDOW_SIZE"] - logging.info('Applying sliding window to build train/val/test datasets...') - X_train, y_train, X_val, y_val, X_test, y_test = generate_windowed_split( - df_train, - df_val, - df_test, - target_name, - window_size) - logging.info("Resulting shapes:") - logging.info(f' - (X_train/X_val/X_test): ({X_train.shape}/{X_val.shape}/{X_test.shape})') - logging.info(f' - (y_train/y_val/y_test): ({y_train.shape}/{y_val.shape}/{y_test.shape})') - logging.info(f'Done!\n') - - assert not np.isnan(np.sum(X_train)) - assert not np.isnan(np.sum(X_val)) - assert not np.isnan(np.sum(X_test)) - assert not np.isnan(np.sum(y_train)) - assert not np.isnan(np.sum(y_val)) - assert not np.isnan(np.sum(y_test)) - - # - # Now, we restore the target variable to their original values. This is needed in case a multiclass - # classification task is defined down the pipeline. - logging.info('Restoring the target variable to their original values...') - y_train = (y_train + min_target_value_in_train) * (max_target_value_in_train - min_target_value_in_train) - y_val = (y_val + min_target_value_in_val) * (max_target_value_in_val - min_target_value_in_val) - y_test = (y_test + min_target_value_in_test) * (max_target_value_in_test - min_target_value_in_test) - logging.info('Min precipitation values (train/val/test): %.5f, %.5f, %.5f' % - (np.min(y_train), np.min(y_val), np.min(y_test))) - logging.info('Max precipitation values (train/val/test): %.5f, %.5f, %.5f' % - (np.max(y_train), np.max(y_val), np.max(y_test))) - logging.info(f'Done!\n') - - if subsampling_procedure != "NONE": - # - # Subsampling - logging.info('**********Subsampling************') - logging.info(f'- Shapes before subsampling (y_train/y_val/y_test): {y_train.shape}, {y_val.shape}, {y_test.shape}') - logging.info("Subsampling train data.") - X_train, y_train = apply_subsampling(X_train, y_train, subsampling_procedure) - logging.info("Subsampling val data...") - - X_val, y_val = apply_subsampling(X_val, y_val, "NEGATIVE") - logging.info('- Min precipitation values (train/val/test) after subsampling: %.5f, %.5f, %.5f' % - (np.min(y_train), np.min(y_val), np.min(y_test))) - - logging.info('- Max precipitation values (train/val/test) after subsampling: %.5f, %.5f, %.5f' % - (np.max(y_train), np.max(y_val), np.max(y_test))) - logging.info(f'- Shapes (y_train/y_val/y_test) after subsampling: {y_train.shape}, {y_val.shape}, {y_test.shape}') - logging.info(f'Done!\n') - - # - # Write numpy arrays for train/val/test dataset to a single pickle file - logging.info(f'Dumping train/val/test np arrays to pickle file {filename}...') - logging.info( - f'Number of examples (train/val/test): {len(X_train)}/{len(X_val)}/{len(X_test)}.') - filename = globals.DATASETS_DIR + pipeline_id + ".pickle" - file = open(filename, 'wb') - ndarrays = (X_train, y_train, - X_val, y_val, - X_test, y_test) - pickle.dump(ndarrays, file) - logging.info(f'Done!\n') - - logging.info('Done it all!') - -def main(argv): - parser = argparse.ArgumentParser( - description="""This script builds the train/val/test datasets for a given weather station, by using the user-specified data sources.""") - parser.add_argument('-s', '--station_id', type=str, required=True, help='station id') - parser.add_argument('-tt', '--train_test_threshold', type=str, required=True, help='The limiting date between train and test examples (format: YYYY-MM-DD).') - parser.add_argument('-ts', '--train_start_threshold', type=str, required=False, help='The limiting date from which to consider examples (format: YYYY-MM-DD).') - parser.add_argument('-d', '--datasources', type=str, help='data source spec') - parser.add_argument('-sp', '--subsampling_procedure', type=str, default='NONE', help='Subsampling procedure do be applied.') - args = parser.parse_args(argv[1:]) - - station_id = args.station_id - datasources = args.datasources - subsampling_procedure = args.subsampling_procedure - - try: - if (station_id in globals.ALERTARIO_WEATHER_STATION_IDS or station_id in globals.ALERTARIO_GAUGE_STATION_IDS): - train_test_threshold = pd.to_datetime(args.train_test_threshold, utc=True) # This UTC thing is really anonying! - else: - train_test_threshold = pd.to_datetime(args.train_test_threshold) - except ParserError: - print(f"Invalid date format: {args.train_test_threshold}.") - parser.print_help() - sys.exit(2) - - try: - train_start_threshold = args.train_start_threshold - if train_start_threshold is not None: - train_start_threshold = pd.to_datetime(args.train_start_threshold) - except pd.errors.ParserError: - print(f"Invalid date format: {args.train_start_threshold}.") - parser.print_help() - sys.exit(2) - - lst_subsampling_procedures = ["NONE", "NAIVE", "NEGATIVE"] - if not (subsampling_procedure in lst_subsampling_procedures): - print(f"Invalid subsampling procedure: {subsampling_procedure}. Valid values: {lst_subsampling_procedures}") - parser.print_help() - sys.exit(2) - - if not ((station_id in globals.INMET_WEATHER_STATION_IDS) or (station_id in globals.ALERTARIO_WEATHER_STATION_IDS) or (station_id in globals.ALERTARIO_GAUGE_STATION_IDS)): - print(f"Invalid station identifier: {station_id}") - parser.print_help() - sys.exit(2) - - if (station_id in globals.INMET_WEATHER_STATION_IDS): - input_folder = globals.WS_INMET_DATA_DIR - elif (station_id in globals.ALERTARIO_WEATHER_STATION_IDS): - input_folder = globals.WS_ALERTARIO_DATA_DIR - elif (station_id in globals.ALERTARIO_GAUGE_STATION_IDS): - # Its a gauge station. - input_folder = globals.GS_ALERTARIO_DATA_DIR - - fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" - logging.basicConfig(level=logging.DEBUG, format = fmt) - - join_goes16_tpw_data_source = False - join_as_data_source = False - join_nwp_data_source = False - join_lightning_data_source = False - join_colorcord_data_source = False - join_conv2d_data_source = False - join_autoencoder_data_source = False - - if datasources: - if 'R' in datasources: - join_as_data_source = True - if 'N' in datasources: - join_nwp_data_source = True - if 'L' in datasources: - join_lightning_data_source = True - if 'T' in datasources: - join_goes16_tpw_data_source = True - if "I" in datasources: - join_colorcord_data_source = True - if "C" in datasources: - join_conv2d_data_source = True - if "A" in datasources: - join_autoencoder_data_source = True - - assert(station_id is not None) and (station_id != "") - - build_datasets(station_id, - input_folder, - train_start_threshold, - train_test_threshold, - join_as_data_source, - join_nwp_data_source, - join_lightning_data_source, - join_goes16_tpw_data_source, - join_colorcord_data_source, - join_conv2d_data_source, - join_autoencoder_data_source, - subsampling_procedure) - -if __name__ == "__main__": - main(sys.argv) diff --git a/src/config/__init__.py b/src/config/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/config/__pycache__/__init__.cpython-311.pyc b/src/config/__pycache__/__init__.cpython-311.pyc new file mode 100644 index 00000000..b90bb9a6 Binary files /dev/null and b/src/config/__pycache__/__init__.cpython-311.pyc differ diff --git a/src/config/__pycache__/globals.cpython-311.pyc b/src/config/__pycache__/globals.cpython-311.pyc new file mode 100644 index 00000000..a4afe1b1 Binary files /dev/null and b/src/config/__pycache__/globals.cpython-311.pyc differ diff --git a/src/config/__pycache__/paths.cpython-311.pyc b/src/config/__pycache__/paths.cpython-311.pyc new file mode 100644 index 00000000..bf62f4b1 Binary files /dev/null and b/src/config/__pycache__/paths.cpython-311.pyc differ diff --git a/src/config/globals.py b/src/config/globals.py new file mode 100644 index 00000000..167e080c --- /dev/null +++ b/src/config/globals.py @@ -0,0 +1,120 @@ +import os + + +def _get_env(key: str, default: str) -> str: + return os.getenv(key, default) + + +def _get_env_float(key: str, default: float) -> float: + try: + return float(os.getenv(key, default)) + except (TypeError, ValueError): + return default + +INMET_API_BASE_URL = _get_env("INMET_API_BASE_URL", "https://apitempo.inmet.gov.br") + +# Weather stations datasource directories +WS_INMET_DATA_DIR = _get_env("WS_INMET_DATA_DIR", "./data/ws/inmet/") +WS_ALERTARIO_DATA_DIR = _get_env("WS_ALERTARIO_DATA_DIR", "./data/ws/alertario/ws/") +GS_ALERTARIO_DATA_DIR = _get_env("GS_ALERTARIO_DATA_DIR", "./data/ws/alertario/rain_gauge_era5_fused/") +CEMADEN_DATA_DIR = _get_env("CEMADEN_DATA_DIR", ".data/ws/cemaden/") + +SUMARE_DATA_DIR = _get_env("SUMARE_DATA_DIR", ".data/radar_sumare") +# WS_GOES_DATA_DIR = "atmoseer/data/ws/goes16" +GOES16_DATA_DIR = _get_env("GOES16_DATA_DIR", "./data/goes16/CMI/") + +# Directory to store the extracted features from GOES-16 data +GOES16_FEATURES_DIR = _get_env("GOES16_FEATURES_DIR", "./data/goes16/features/") + +# Atmospheric sounding datasource directory +NWP_DATA_DIR = _get_env("NWP_DATA_DIR", "./data/NWP/") + +# Atmospheric sounding datasource directory +AS_DATA_DIR = _get_env("AS_DATA_DIR", "./data/as/") + +# GOES16/DSI directory +DSI_DATA_DIR = _get_env("DSI_DATA_DIR", "./data/goes16/DSI") + +# GOES16/TPW directory +TPW_DATA_DIR = _get_env("TPW_DATA_DIR", "./data/goes16/wsoi") + +# Directory to store the train/val/test datasets for each weather station of interest +DATASETS_DIR = _get_env("DATASETS_DIR", "./data/datasets/") + +# Directory to store the generated models and their corresponding reports +MODELS_DIR = _get_env("MODELS_DIR", "./models/") + +# see https://portal.inmet.gov.br/paginas/catalogoaut +INMET_WEATHER_STATION_IDS = ( + "A601", # Seropédica + "A602", # Marambaia + "A621", # Vila militar + "A627", # Niteroi + "A636", # Jacarepagua + "A652", # Forte de Copacabana +) + +ALERTARIO_GAUGE_STATION_IDS = ( + "anchieta", + "av_brasil_mendanha", + "bangu", + "barrinha", + "campo_grande", + "cidade_de_deus", + "copacabana", + "grajau_jacarepagua", + "grajau", + "grande_meier", + "grota_funda", + "ilha_do_governador", + "laranjeiras", + "madureira", + "penha", + "piedade", + "recreio", + "rocinha", + "santa_teresa", + "saude", + "sepetiba", + "tanque", + "tijuca_muda", + "tijuca", + "urca", + "alto_da_boa_vista", # ** + "iraja", # ** + "jardim_botanico", # ** + "riocentro", # ** + "santa_cruz", # ** + "vidigal", # ** +) + +ALERTARIO_WEATHER_STATION_IDS = ( + "guaratiba", # ** + "sao_cristovao", # ** +) + +WEBSIRENE_DATA_DIR = _get_env("WEBSIRENE_DATA_DIR", "./data/ws/websirene/") + +WEBSIRENE_STATION_IDS = ( + "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", + "11", "12", "13", "14", "15", "16", "17", "18", "19", "20", + "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", + "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", + "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", + "51", "52", "53", "54", "55", "56", "57", "58", "59", "60", + "61", "62", "63", "64", "65", "66", "67", "68", "69", "70", + "71", "72", "73", "74", "75", "76", "77", "78", "79", "80", + "81", "82", "83" +) + +# lower left corner +lat_min = _get_env_float("REGION_LAT_MIN", -23.801876626302175) +lon_min = _get_env_float("REGION_LON_MIN", -45.05290312102409) + +# upper right corner +lat_max = _get_env_float("REGION_LAT_MAX", -21.699774257353113) +lon_max = _get_env_float("REGION_LON_MAX", -42.35676996062447) + +# Region of Interest +extent = [lon_min, lat_min, lon_max, lat_max] + diff --git a/src/config/paths.py b/src/config/paths.py new file mode 100644 index 00000000..c6dc764c --- /dev/null +++ b/src/config/paths.py @@ -0,0 +1,6 @@ +from pathlib import Path + + +ERA5_DIR = "data/reanalysis/cds/era5/pressure" +RADAR_CACHE_DIR = "data/radar_sumare/radar_cache" +RADAR_DIR = "data/radar_sumare" \ No newline at end of file diff --git a/src/corrdiff/CorrdiffDatasetBuilder.py b/src/corrdiff/CorrdiffDatasetBuilder.py new file mode 100644 index 00000000..3c2174d5 --- /dev/null +++ b/src/corrdiff/CorrdiffDatasetBuilder.py @@ -0,0 +1,997 @@ +""" +=============================================================================== +CorrDiffDatasetBuilder.py +=============================================================================== + +Author: + Vinicius / OpenAI Refactor + +Description: + This module builds a complete Zarr-based dataset pipeline compatible with + NVIDIA CorrDiff / PhysicsNeMo training workflows. + + The builder performs: + + 1. ERA5 loading from partitioned parquet datasets + 2. Temporal filtering + 3. Spatial interpolation of ERA5 variables into radar domain + 4. Radar image decoding into reflectivity fields + 5. Patch extraction + 6. NaN masking + 7. Train statistics computation + 8. Dataset normalization metadata export + 9. Zarr dataset generation optimized for ML training + +Dataset Structure: + datasets/corrdiff/ + ├── train.zarr/ + │ ├── input + │ ├── target + │ ├── mask + │ └── timestamps + │ + ├── stats/ + │ ├── input_mean.npy + │ ├── input_std.npy + │ ├── target_mean.npy + │ └── target_std.npy + │ + └── metadata.json + +Zarr Arrays: + input: + Shape: + (N, C, H, W) + + Example: + (500000, 8, 32, 32) + + Meaning: + N = samples + C = ERA5 variables + H/W = patch size + + target: + Shape: + (N, 1, H, W) + + Meaning: + Radar reflectivity patches + + mask: + Shape: + (N, 1, H, W) + + Meaning: + Valid radar pixels + + timestamps: + Shape: + (N,) + + Meaning: + Unix timestamp for each patch + +Compatible With: + - CorrDiff Regression Training + - CorrDiff Diffusion Training + - PhysicsNeMo + - Multi-GPU DDP + - Torch DataLoader + - Distributed training + +Recommended Workflow: + Step 1: + Generate dataset + + Step 2: + Compute statistics + + Step 3: + Train regression model + + Step 4: + Train diffusion model + +Requirements: + - zarr + - numcodecs + - pyarrow + - scipy + - pillow + - pandas + - numpy + +Example: + python3 -m src.corrdiff.CorrdiffDatasetBuilder \ + -b 2023-10-01 \ + -e 2024-01-31 \ + --era5_variables u,v \ + --radar_res 2 + +=============================================================================== +""" + +import argparse +import json +import logging +import sys +from pathlib import Path + +import numpy as np +import pandas as pd +import pyarrow.compute as pc +import pyarrow.dataset as ds +import zarr + +from numcodecs import Blosc +from PIL import Image +from scipy.interpolate import RegularGridInterpolator + +from src.config.paths import ( + ERA5_DIR, + RADAR_CACHE_DIR, + RADAR_DIR, +) + +# ============================================================================= +# LOGGER +# ============================================================================= + + +def setup_logger(): + + logger = logging.getLogger("corrdiff") + + if logger.handlers: + return logger + + logger.setLevel(logging.INFO) + + handler = logging.StreamHandler(sys.stdout) + + formatter = logging.Formatter( + "[%(asctime)s] [%(levelname)s] %(message)s" + ) + + handler.setFormatter(formatter) + + logger.addHandler(handler) + + return logger + + +# ============================================================================= +# ERA5 DATASET +# ============================================================================= + + +class ERA5Dataset: + + def __init__( + self, + path, + variables, + start_date, + end_date, + ): + + self.logger = setup_logger() + + self.path = Path(path) + + self.variables = variables + + self.start_date = pd.to_datetime(start_date) + self.end_date = pd.to_datetime(end_date) + + self.df = None + + self.lat = None + self.lon = None + + def load(self): + + self.logger.info(f"Loading ERA5 dataset from {self.path}") + + dataset = ds.dataset( + self.path, + format="parquet", + partitioning="hive", + ) + + time_col = None + + for col in dataset.schema.names: + + if col in ["time", "valid_time"]: + + time_col = col + break + + if time_col is None: + raise ValueError("No time column found") + + columns = [ + "latitude", + "longitude", + time_col, + ] + self.variables + + filter_expr = ( + (pc.field(time_col) >= pc.scalar(self.start_date)) + & + (pc.field(time_col) <= pc.scalar(self.end_date)) + ) + + table = dataset.to_table( + columns=columns, + filter=filter_expr, + ) + + df = table.to_pandas() + + df["time"] = pd.to_datetime(df[time_col]) + + df = df.sort_values( + ["time", "latitude", "longitude"] + ) + + self.df = df + + self.lat = np.sort(df["latitude"].unique()) + self.lon = np.sort(df["longitude"].unique()) + + self.logger.info(f"ERA5 loaded: {df.shape}") + + def interpolate( + self, + era5_t, + target_lat, + target_lon, + ): + + grids = [] + + for var in self.variables: + + grid = era5_t.pivot( + index="latitude", + columns="longitude", + values=var, + ).values + + interp = RegularGridInterpolator( + (self.lat, self.lon), + grid, + bounds_error=False, + fill_value=np.nan, + ) + + pts = np.stack( + [ + target_lat.ravel(), + target_lon.ravel(), + ], + axis=-1, + ) + + vals = interp(pts).reshape(target_lat.shape) + + grids.append(vals) + + return np.stack(grids, axis=0) + + +# ============================================================================= +# RADAR DATASET +# ============================================================================= + + +class RadarDataset: + + def __init__( + self, + radar_path, + cache_dir, + resolution_km, + lat_range, + lon_range, + start_date, + end_date, + ): + + self.logger = setup_logger() + + self.radar_path = Path(radar_path) + + self.cache_dir = Path(cache_dir) + + self.cache_dir.mkdir( + exist_ok=True, + parents=True, + ) + + self.res_km = resolution_km + + self.lat_range = lat_range + self.lon_range = lon_range + + self.start = pd.to_datetime(start_date) + self.end = pd.to_datetime(end_date) + + self.pos_sumare = ( + -22.955139, + -43.248278, + ) + + self.legend_values = np.array( + [50, 45, 40, 35, 30, 25, 20, 0] + ) + + self.legend_colors = np.array( + [ + (197, 0, 197), + (227, 6, 5), + (255, 112, 0), + (195, 230, 0), + (4, 85, 4), + (19, 122, 19), + (0, 167, 12), + (0, 0, 0), + ] + ) + + def build_grid(self): + + deg = self.res_km / 111.0 + + self.lat = np.arange( + self.lat_range[0], + self.lat_range[1], + deg, + ) + + self.lon = np.arange( + self.lon_range[0], + self.lon_range[1], + deg, + ) + + self.Lon, self.Lat = np.meshgrid( + self.lon, + self.lat, + ) + + def precompute_pixel_map(self): + + H = 654 + W = 656 + + lon_min = self.lon_range[0] + lon_max = self.lon_range[1] + + lat_min = self.lat_range[0] + lat_max = self.lat_range[1] + + self.px = ( + (self.Lon - lon_min) + / + (lon_max - lon_min) + * + (W - 1) + ).astype(np.int32) + + self.py = ( + (lat_max - self.Lat) + / + (lat_max - lat_min) + * + (H - 1) + ).astype(np.int32) + + print( + "PX MIN/MAX:", + self.px.min(), + self.px.max() + ) + + print( + "PY MIN/MAX:", + self.py.min(), + self.py.max() + ) + + def filepath(self, t): + + return self.radar_path / t.strftime( + "%Y/%m/%d/%Y_%m_%d_%H_%M.png" + ) + + def cache_path(self, t): + + return self.cache_dir / ( + f"{t.strftime('%Y%m%d_%H')}.npy" + ) + + def rgb_to_reflectivity(self, rgb): + + flat = rgb.reshape(-1, 3) + + dists = np.sqrt( + ( + ( + flat[:, None, :] + - self.legend_colors[None] + ) + ** 2 + ).sum(axis=2) + ) + + idx = np.argsort(dists, axis=1)[:, :2] + + c1 = self.legend_colors[idx[:, 0]] + c2 = self.legend_colors[idx[:, 1]] + + v1 = self.legend_values[idx[:, 0]] + v2 = self.legend_values[idx[:, 1]] + + dist = np.linalg.norm(c1 - c2, axis=1) + + t = np.divide( + np.linalg.norm(flat - c1, axis=1), + dist, + out=np.zeros_like(dist), + where=dist != 0, + ) + + val = v1 + t * (v2 - v1) + + return val.reshape(rgb.shape[:2]) + + def process_time(self, t): + + cache = self.cache_path(t) + + if cache.exists(): + return np.load(cache) + + path = self.filepath(t) + + if not path.exists(): + return None + + img = np.array( + Image.open(path).convert("RGB") + ) + + print("IMAGE SHAPE:", img.shape) + + reflect = self.rgb_to_reflectivity(img) + + H, W = reflect.shape + + px = np.clip(self.px, 0, W - 1) + py = np.clip(self.py, 0, H - 1) + + grid = reflect[py, px] + + print( + "REFLECT MIN/MAX:", + np.nanmin(reflect), + np.nanmax(reflect) + ) + + print( + "GRID MIN/MAX:", + np.nanmin(grid), + np.nanmax(grid) + ) + + print( + "GRID MEAN:", + np.nanmean(grid) + ) + + np.save( + cache, + grid.astype(np.float32), + ) + + return grid + + def get_grid(self, t): + + return self.process_time( + pd.to_datetime(t) + ) + + +# ============================================================================= +# CORRDIFF DATASET BUILDER +# ============================================================================= + + +class CorrDiffDatasetBuilder: + + def __init__( + self, + era5, + radar, + output_dir, + patch_size=32, + stride=16, + chunk_size=256, + ): + + self.logger = setup_logger() + + self.era5 = era5 + self.radar = radar + + self.output_dir = Path(output_dir) + + self.patch_size = patch_size + self.stride = stride + self.chunk_size = chunk_size + + self.output_dir.mkdir( + parents=True, + exist_ok=True, + ) + + self.sample_id = 0 + + self.zarr_path = ( + self.output_dir / "train.zarr" + ) + + compressor = Blosc( + cname="zstd", + clevel=3, + shuffle=2, + ) + + self.root = zarr.open( + str(self.zarr_path), + mode="w", + zarr_version=2, +) + + self.compressor = compressor + + self.input_ds = None + self.target_ds = None + self.mask_ds = None + self.timestamps_ds = None + + self.running_sum = None + self.running_sq_sum = None + self.running_count = 0 + + self.target_sum = 0.0 + self.target_sq_sum = 0.0 + self.target_count = 0 + + def initialize_zarr(self, input_channels): + + self.logger.info("Initializing Zarr arrays...") + + self.root = zarr.open( + str(self.zarr_path), + mode="w", + zarr_version=2, + ) + + self.input_ds = self.root.create_dataset( + name="input", + shape=(1, input_channels, + self.patch_size, + self.patch_size), + chunks=(self.chunk_size, + input_channels, + self.patch_size, + self.patch_size), + dtype="float32", + compressor=self.compressor, + ) + + self.target_ds = self.root.create_dataset( + name="target", + shape=(1, 1, + self.patch_size, + self.patch_size), + chunks=(self.chunk_size, + 1, + self.patch_size, + self.patch_size), + dtype="float32", + compressor=self.compressor, + ) + + self.mask_ds = self.root.create_dataset( + name="mask", + shape=(1, 1, + self.patch_size, + self.patch_size), + chunks=(self.chunk_size, + 1, + self.patch_size, + self.patch_size), + dtype="float32", + compressor=self.compressor, + ) + + self.timestamps_ds = self.root.create_dataset( + name="timestamps", + shape=(1,), + chunks=(self.chunk_size,), + dtype="int64", + compressor=self.compressor, + ) + + def append_sample( + self, + xp, + yp, + mask, + timestamp, + ): + + idx = self.sample_id + + new_shape_input = ( + idx + 1, + xp.shape[0], + self.patch_size, + self.patch_size, + ) + + new_shape_target = ( + idx + 1, + 1, + self.patch_size, + self.patch_size, + ) + + self.input_ds.resize(new_shape_input) + self.target_ds.resize(new_shape_target) + self.mask_ds.resize(new_shape_target) + + self.timestamps_ds.resize((idx + 1,)) + + self.input_ds[idx] = xp.astype(np.float32) + self.target_ds[idx] = yp.astype(np.float32) + self.mask_ds[idx] = mask.astype(np.float32) + + self.timestamps_ds[idx] = int( + pd.Timestamp(timestamp).timestamp() + ) + + if self.running_sum is None: + + self.running_sum = xp.sum( + axis=(1, 2) + ) + + self.running_sq_sum = ( + xp ** 2 + ).sum(axis=(1, 2)) + + else: + + self.running_sum += xp.sum( + axis=(1, 2) + ) + + self.running_sq_sum += ( + xp ** 2 + ).sum(axis=(1, 2)) + + self.running_count += ( + xp.shape[1] * xp.shape[2] + ) + + self.target_sum += yp.sum() + + self.target_sq_sum += ( + yp ** 2 + ).sum() + + self.target_count += yp.size + + self.sample_id += 1 + + def save_stats(self): + + stats_dir = self.output_dir / "stats" + + stats_dir.mkdir( + exist_ok=True, + parents=True, + ) + + input_mean = ( + self.running_sum + / self.running_count + ) + + input_std = np.sqrt( + ( + self.running_sq_sum + / self.running_count + ) + - input_mean**2 + ) + + target_mean = ( + self.target_sum + / self.target_count + ) + + target_std = np.sqrt( + ( + self.target_sq_sum + / self.target_count + ) + - target_mean**2 + ) + + np.save( + stats_dir / "input_mean.npy", + input_mean.astype(np.float32), + ) + + np.save( + stats_dir / "input_std.npy", + input_std.astype(np.float32), + ) + + np.save( + stats_dir / "target_mean.npy", + np.array( + [target_mean], + dtype=np.float32, + ), + ) + + np.save( + stats_dir / "target_std.npy", + np.array( + [target_std], + dtype=np.float32, + ), + ) + + metadata = { + "num_samples": int(self.sample_id), + "patch_size": self.patch_size, + "stride": self.stride, + "input_channels": int( + len(self.era5.variables) + ), + "variables": self.era5.variables, + } + + with open( + self.output_dir / "metadata.json", + "w", + ) as f: + + json.dump( + metadata, + f, + indent=4, + ) + + def build(self): + + times = sorted( + self.era5.df["time"].unique() + ) + + self.logger.info( + f"Total timesteps: {len(times)}" + ) + + for t in times: + + self.logger.info( + f"Processing timestep: {t}" + ) + + era5_t = self.era5.df[ + self.era5.df["time"] == t + ] + + if len(era5_t) == 0: + continue + + X = self.era5.interpolate( + era5_t, + self.radar.Lat, + self.radar.Lon, + ) + + Y = self.radar.get_grid(t) + + print( + "Y MIN/MAX:", + np.nanmin(Y), + np.nanmax(Y) + ) + + if Y is None: + continue + + if np.isnan(Y).all(): + continue + + if self.input_ds is None: + + self.initialize_zarr( + input_channels=X.shape[0] + ) + + H, W = Y.shape + + patches_created = 0 + + for i in range( + 0, + H - self.patch_size + 1, + self.stride, + ): + + for j in range( + 0, + W - self.patch_size + 1, + self.stride, + ): + + xp = X[ + :, + i:i+self.patch_size, + j:j+self.patch_size, + ] + + yp = Y[ + i:i+self.patch_size, + j:j+self.patch_size, + ] + + valid_ratio = np.mean( + ~np.isnan(yp) + ) + + if valid_ratio < 0.05: + continue + + mask = ~np.isnan(yp) + + yp = np.nan_to_num( + yp, + nan=0.0, + ) + yp = np.log1p(yp) + + yp = yp[None, ...] + mask = mask[None, ...] + + self.append_sample( + xp, + yp, + mask, + t, + ) + + patches_created += 1 + + self.logger.info( + f"Patches created: {patches_created}" + ) + + self.save_stats() + + self.logger.info( + f"Dataset size: {self.sample_id}" + ) + + +# ============================================================================= +# ARGUMENT PARSER +# ============================================================================= + + +def parameter_parser(): + + parser = argparse.ArgumentParser() + + parser.add_argument( + "-b", + "--begin", + required=True, + ) + + parser.add_argument( + "-e", + "--end", + required=True, + ) + + parser.add_argument( + "--era5_variables", + type=str, + default="u,v", + ) + + parser.add_argument( + "--lat_range", + nargs=2, + type=float, + default=[-23.5, -22.25], + ) + + parser.add_argument( + "--lon_range", + nargs=2, + type=float, + default=[-44.0, -42.5], + ) + + parser.add_argument( + "--radar_res", + type=int, + default=2, + ) + + return parser.parse_args() + + +# ============================================================================= +# MAIN +# ============================================================================= + + +def main(args): + + era5 = ERA5Dataset( + path=ERA5_DIR, + variables=args.era5_variables.split(","), + start_date=args.begin + " 00:00:00", + end_date=args.end + " 23:00:00", + ) + + era5.load() + + radar = RadarDataset( + radar_path=RADAR_DIR, + cache_dir=RADAR_CACHE_DIR, + resolution_km=args.radar_res, + lat_range=args.lat_range, + lon_range=args.lon_range, + start_date=args.begin + " 00:00:00", + end_date=args.end + " 23:59:00", + ) + + radar.build_grid() + + radar.precompute_pixel_map() + + builder = CorrDiffDatasetBuilder( + era5=era5, + radar=radar, + output_dir="datasets/corrdiff", + patch_size=32, + stride=16, + chunk_size=256, + ) + + builder.build() + + +if __name__ == "__main__": + + args = parameter_parser() + + main(args) \ No newline at end of file diff --git a/src/corrdiff/__pycache__/CorrdiffDatasetBuilder.cpython-311.pyc b/src/corrdiff/__pycache__/CorrdiffDatasetBuilder.cpython-311.pyc new file mode 100644 index 00000000..4d8e596e Binary files /dev/null and b/src/corrdiff/__pycache__/CorrdiffDatasetBuilder.cpython-311.pyc differ diff --git a/src/corrdiff/__pycache__/create_split.cpython-311.pyc b/src/corrdiff/__pycache__/create_split.cpython-311.pyc new file mode 100644 index 00000000..6004466f Binary files /dev/null and b/src/corrdiff/__pycache__/create_split.cpython-311.pyc differ diff --git a/src/corrdiff/__pycache__/evaluate_dataset.cpython-311.pyc b/src/corrdiff/__pycache__/evaluate_dataset.cpython-311.pyc new file mode 100644 index 00000000..31b3dbe8 Binary files /dev/null and b/src/corrdiff/__pycache__/evaluate_dataset.cpython-311.pyc differ diff --git a/src/corrdiff/__pycache__/evaluate_dataset.cpython-313.pyc b/src/corrdiff/__pycache__/evaluate_dataset.cpython-313.pyc new file mode 100644 index 00000000..ee48692f Binary files /dev/null and b/src/corrdiff/__pycache__/evaluate_dataset.cpython-313.pyc differ diff --git a/src/corrdiff/__pycache__/generate_normalization.cpython-311.pyc b/src/corrdiff/__pycache__/generate_normalization.cpython-311.pyc new file mode 100644 index 00000000..1ae6abde Binary files /dev/null and b/src/corrdiff/__pycache__/generate_normalization.cpython-311.pyc differ diff --git a/src/corrdiff/create_split.py b/src/corrdiff/create_split.py new file mode 100644 index 00000000..809bcb76 --- /dev/null +++ b/src/corrdiff/create_split.py @@ -0,0 +1,124 @@ +""" +create_split.py + +Create train/validation splits for CorrDiff datasets. + +This script generates: + + train_index.npy + valid_index.npy + +Expected dataset structure: + +datasets/ +└── corrdiff/ + ├── train.zarr/ + ├── train_index.npy + └── valid_index.npy + +Recommended split: + + train: 95% + valid: 5% + +Author: + Vinicius / CorrDiff adaptation + +""" + +from pathlib import Path +import numpy as np +import zarr + + +# ============================================================ +# CONFIG +# ============================================================ + +DATASET_PATH = "datasets/corrdiff/train.zarr" + +TRAIN_OUTPUT = "datasets/corrdiff/train_index.npy" +VALID_OUTPUT = "datasets/corrdiff/valid_index.npy" + +TRAIN_RATIO = 0.95 + +SEED = 42 + + +# ============================================================ +# MAIN +# ============================================================ + +def main(): + + print("=" * 80) + print("CorrDiff Train/Validation Split Generator") + print("=" * 80) + + dataset_path = Path(DATASET_PATH) + + if not dataset_path.exists(): + raise FileNotFoundError( + f"Dataset not found: {dataset_path}" + ) + + print(f"Opening dataset: {dataset_path}") + + z = zarr.open( + str(dataset_path), + mode="r", + ) + + n_samples = z["input"].shape[0] + + print(f"Total samples: {n_samples}") + + # ============================================================ + # SHUFFLE + # ============================================================ + + rng = np.random.default_rng(SEED) + + indices = np.arange(n_samples) + + rng.shuffle(indices) + + # ============================================================ + # SPLIT + # ============================================================ + + train_size = int(n_samples * TRAIN_RATIO) + + train_idx = indices[:train_size] + valid_idx = indices[train_size:] + + print(f"Train samples: {len(train_idx)}") + print(f"Valid samples: {len(valid_idx)}") + + # ============================================================ + # SAVE + # ============================================================ + + np.save( + TRAIN_OUTPUT, + train_idx, + ) + + np.save( + VALID_OUTPUT, + valid_idx, + ) + + print("\nSaved files:") + print(TRAIN_OUTPUT) + print(VALID_OUTPUT) + + print("\nDone.") + + +# ============================================================ +# ENTRYPOINT +# ============================================================ + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/src/corrdiff/evaluate_dataset.py b/src/corrdiff/evaluate_dataset.py new file mode 100644 index 00000000..7605077b --- /dev/null +++ b/src/corrdiff/evaluate_dataset.py @@ -0,0 +1,40 @@ +import zarr +import numpy as np + +dataset_dir = "./datasets/corrdiff/" +root = zarr.open(dataset_dir + "train.zarr", mode="r") + +target = root["target"] + +print("GLOBAL MIN:", target[:].min()) +print("GLOBAL MAX:", target[:].max()) +print("GLOBAL MEAN:", target[:].mean()) + +norm = np.load( + "datasets/corrdiff/normalization.npz" +) + +for k in norm.files: + print(k, norm[k]) + +import zarr +import numpy as np + +z = zarr.open( + "datasets/corrdiff/train.zarr", + mode="r" +) + +y = z["target"] + +print("mean =", np.mean(y)) +print("std =", np.std(y)) + +print("nonzero ratio =", + np.mean(y[:] > 0)) + +print("pixels > 5 dBZ =", + np.mean(y[:] > 5)) + +print("pixels > 20 dBZ =", + np.mean(y[:] > 20)) \ No newline at end of file diff --git a/src/corrdiff/generate_normalization.py b/src/corrdiff/generate_normalization.py new file mode 100644 index 00000000..89b02718 --- /dev/null +++ b/src/corrdiff/generate_normalization.py @@ -0,0 +1,51 @@ +import numpy as np +import zarr +from pathlib import Path + +DATASET_PATH = "datasets/corrdiff/train.zarr" +OUTPUT_PATH = "datasets/corrdiff/normalization.npz" + +print("Opening dataset...") + +z = zarr.open(DATASET_PATH, mode="r") + +x = z["input"] +y = z["target"] + +print("Computing input statistics...") + +# shape: +# input -> (N, C, H, W) +# target -> (N, 1, H, W) + +input_mean = np.mean(x, axis=(0, 2, 3)) +input_std = np.std(x, axis=(0, 2, 3)) + +#target = np.log1p(y[:]) +target = y[:] + +target_mean = np.mean( + target, + axis=(0,2,3) +) + +target_std = np.std( + target, + axis=(0,2,3) +) + +# avoid division by zero +input_std[input_std == 0] = 1.0 +target_std[target_std == 0] = 1.0 + +print("Saving normalization file...") + +np.savez( + OUTPUT_PATH, + input_mean=input_mean.astype(np.float32), + input_std=input_std.astype(np.float32), + target_mean=target_mean.astype(np.float32), + target_std=target_std.astype(np.float32), +) + +print("Done.") \ No newline at end of file diff --git a/src/csv2parquet.py b/src/csv2parquet.py deleted file mode 100644 index 63fbbfab..00000000 --- a/src/csv2parquet.py +++ /dev/null @@ -1,29 +0,0 @@ -import argparse -import os -import pyarrow.parquet as pq -import pandas as pd - -def convert_csv_to_parquet(input_folder, output_folder): - """ - Converts all CSV files in the input folder to Parquet files in the output folder. - - Args: - input_folder: The folder containing the CSV files. - output_folder: The folder where the Parquet files will be saved. - """ - - for file_name in os.listdir(input_folder): - if file_name.endswith(".csv"): - csv_file_path = os.path.join(input_folder, file_name) - parquet_file_path = os.path.join(output_folder, file_name.replace(".csv", ".parquet")) - df = pd.read_csv(csv_file_path) - df.to_parquet(parquet_file_path) - - -if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("input_folder", help="The folder containing the CSV files.") - parser.add_argument("output_folder", help="The folder where the Parquet files will be saved.") - args = parser.parse_args() - - convert_csv_to_parquet(args.input_folder, args.output_folder) diff --git a/src/era5_data_source.py b/src/era5/era5_data_source.py similarity index 65% rename from src/era5_data_source.py rename to src/era5/era5_data_source.py index d9e53d7a..f2af7758 100644 --- a/src/era5_data_source.py +++ b/src/era5/era5_data_source.py @@ -1,7 +1,9 @@ -from base_data_source import BaseDataSource import logging + import pandas as pd import xarray as xr +from base_data_source import BaseDataSource + class Era5ReanalisysDataSource(BaseDataSource): def get_data(self, station_id, initial_datetime, final_datetime): @@ -10,10 +12,14 @@ def get_data(self, station_id, initial_datetime, final_datetime): station_latitude = row["VL_LATITUDE"] station_longitude = row["VL_LONGITUDE"] - logging.info(f"Weather station {station_id} is located at lat/long = {station_latitude}/{station_longitude}") + logging.info( + f"Weather station {station_id} is located at lat/long = {station_latitude}/{station_longitude}" + ) + + logging.info( + f"Selecting NWP data between {initial_datetime} and {final_datetime}." + ) - logging.info(f"Selecting NWP data between {initial_datetime} and {final_datetime}.") - ds = xr.open_dataset(globals.NWP_DATA_DIR + "ERA5.nc") logging.info(f"Size.0: {ds.sizes['time']}") @@ -24,9 +30,11 @@ def get_data(self, station_id, initial_datetime, final_datetime): # logging.info(f"Range of timestamps in the original NWP data: [{time_min}, {time_max}]") time_min = ds.time.min().values time_max = ds.time.max().values - logging.info(f"Range of timestamps in the original NWP data: [{time_min}, {time_max}]") + logging.info( + f"Range of timestamps in the original NWP data: [{time_min}, {time_max}]" + ) - # If we want to properly merge the two data sources, then we have to consider + # If we want to properly merge the two data sources, then we have to consider # only the range of periods in which these data sources intersect. time_min = max(time_min, initial_datetime) time_max = min(time_max, final_datetime) @@ -35,13 +43,28 @@ def get_data(self, station_id, initial_datetime, final_datetime): ds = ds.sel(time=slice(time_min, time_max)) logging.info(f"Size.1: {ds.sizes['time']}") - era5_data_at_200hPa = ds.sel(level=200, longitude=station_longitude, latitude=station_latitude, method="nearest") + era5_data_at_200hPa = ds.sel( + level=200, + longitude=station_longitude, + latitude=station_latitude, + method="nearest", + ) logging.info(f"Size.2: {era5_data_at_200hPa.sizes['time']}") - era5_data_at_700hPa = ds.sel(level=700, longitude=station_longitude, latitude=station_latitude, method="nearest") + era5_data_at_700hPa = ds.sel( + level=700, + longitude=station_longitude, + latitude=station_latitude, + method="nearest", + ) logging.info(f"Size.3: {era5_data_at_700hPa.sizes['time']}") - era5_data_at_1000hPa = ds.sel(level=1000, longitude=station_longitude, latitude=station_latitude, method="nearest") + era5_data_at_1000hPa = ds.sel( + level=1000, + longitude=station_longitude, + latitude=station_latitude, + method="nearest", + ) logging.info(f"Size.4: {era5_data_at_1000hPa.sizes['time']}") logging.info(">>><<<") @@ -63,44 +86,53 @@ def get_data(self, station_id, initial_datetime, final_datetime): df_NWP_data_for_station = pd.DataFrame( { "time": era5_data_at_1000hPa.time.values, - "Geopotential_200": era5_data_at_200hPa.z, "Humidity_200": era5_data_at_200hPa.r, "Temperature_200": era5_data_at_200hPa.t, "WindU_200": era5_data_at_200hPa.u, "WindV_200": era5_data_at_200hPa.v, - "Geopotential_700": era5_data_at_700hPa.z, "Humidity_700": era5_data_at_700hPa.r, "Temperature_700": era5_data_at_700hPa.t, "WindU_700": era5_data_at_700hPa.u, "WindV_700": era5_data_at_700hPa.v, - "Geopotential_1000": era5_data_at_1000hPa.z, "Humidity_1000": era5_data_at_1000hPa.r, "Temperature_1000": era5_data_at_1000hPa.t, "WindU_1000": era5_data_at_1000hPa.u, - "WindV_1000": era5_data_at_1000hPa.v + "WindV_1000": era5_data_at_1000hPa.v, } ) # Drop rows with at least one NaN - logging.info(f"Shape before dropping NaN values is {df_NWP_data_for_station.shape}") - df_NWP_data_for_station = df_NWP_data_for_station.dropna(how='any') - logging.info(f"Shape before dropping NaN values is {df_NWP_data_for_station.shape}") + logging.info( + f"Shape before dropping NaN values is {df_NWP_data_for_station.shape}" + ) + df_NWP_data_for_station = df_NWP_data_for_station.dropna(how="any") + logging.info( + f"Shape before dropping NaN values is {df_NWP_data_for_station.shape}" + ) logging.info("Success!") # # Add index to dataframe using the timestamps. - format_string = '%Y-%m-%d %H:%M:%S' - df_NWP_data_for_station['Datetime'] = pd.to_datetime(df_NWP_data_for_station['time'], format=format_string) - df_NWP_data_for_station = df_NWP_data_for_station.set_index(pd.DatetimeIndex(df_NWP_data_for_station['Datetime'])) - df_NWP_data_for_station = df_NWP_data_for_station.drop(['time', 'Datetime'], axis = 1) - logging.info(f"Range of timestamps in the selected slice of NWP data: [{min(df_NWP_data_for_station.index)}, {max(df_NWP_data_for_station.index)}]") + format_string = "%Y-%m-%d %H:%M:%S" + df_NWP_data_for_station["Datetime"] = pd.to_datetime( + df_NWP_data_for_station["time"], format=format_string + ) + df_NWP_data_for_station = df_NWP_data_for_station.set_index( + pd.DatetimeIndex(df_NWP_data_for_station["Datetime"]) + ) + df_NWP_data_for_station = df_NWP_data_for_station.drop( + ["time", "Datetime"], axis=1 + ) + logging.info( + f"Range of timestamps in the selected slice of NWP data: [{min(df_NWP_data_for_station.index)}, {max(df_NWP_data_for_station.index)}]" + ) logging.info(df_NWP_data_for_station) - assert (not df_NWP_data_for_station.isnull().values.any().any()) + assert not df_NWP_data_for_station.isnull().values.any().any() return df_NWP_data_for_station diff --git a/src/era5/fuse_rain_gauge_and_era5.py b/src/era5/fuse_rain_gauge_and_era5.py new file mode 100644 index 00000000..9275ace3 --- /dev/null +++ b/src/era5/fuse_rain_gauge_and_era5.py @@ -0,0 +1,113 @@ +import pandas as pd +import xarray as xr + +from utils import util + + +def fuse_rain_gauge_and_era5( + df_station: pd.DataFrame, station_latitude: float, station_longitude: float, ds_era5 +): + df_station["datetime"] = df_station["datetime"].dt.tz_convert("UTC") + df_station["datetime"] = df_station["datetime"].dt.tz_localize(None) + df_station = df_station.set_index(pd.DatetimeIndex(df_station["datetime"])) + df_station = df_station.drop(["datetime"], axis=1) + assert not df_station.isnull().values.any().any() + + time_min = min(df_station.index) + time_max = max(df_station.index) + print(f"Range of timestamps: [{time_min}, {time_max}]") + print(f"Number of observations (gauge station): {df_station.shape[0]}") + + # Select ERA5 data near the station + era5_data_at_1000hPa = ds_era5.sel( + level=1000, + longitude=station_longitude, + latitude=station_latitude, + method="nearest", + ) + + df_era5_data_for_station = pd.DataFrame( + { + "time": era5_data_at_1000hPa.time.values, + "pressure_1000": 1000, + "Humidity_1000": era5_data_at_1000hPa.r, + "Temperature_1000": era5_data_at_1000hPa.t, + "WindU_1000": era5_data_at_1000hPa.u, + "WindV_1000": era5_data_at_1000hPa.v, + } + ) + + # Create a datetime index for the dataframe containing ERA5 simulated data. + format_string = "%Y-%m-%d %H:%M:%S" + df_era5_data_for_station["datetime"] = pd.to_datetime( + df_era5_data_for_station["time"], format=format_string + ) + df_era5_data_for_station = df_era5_data_for_station.set_index( + pd.DatetimeIndex(df_era5_data_for_station["datetime"]) + ) + df_era5_data_for_station = df_era5_data_for_station.drop( + ["time", "datetime"], axis=1 + ) + + # Temperature in ERA5 is provided in Kelvin; convert to Celsius. + df_era5_data_for_station["Temperature_1000_Celsius"] = df_era5_data_for_station[ + "Temperature_1000" + ].apply(util.convert_to_celsius) + + assert not df_era5_data_for_station.isnull().values.any().any() + + df_fusion = pd.merge( + df_station, + df_era5_data_for_station, + how="left", + left_index=True, + right_index=True, + ) + + column_name_mapping = { + "Temperature_1000_Celsius": "temperature", + "Humidity_1000": "relative_humidity", + "pressure_1000": "barometric_pressure", + "WindU_1000": "wind_direction_u", + "WindV_1000": "wind_direction_v", + "precipitation_sum": "precipitation", + } + column_names = column_name_mapping.keys() + + df_fusion = util.get_dataframe_with_selected_columns(df_fusion, column_names) + + df_fusion = util.rename_dataframe_column_names(df_fusion, column_name_mapping) + + print(f"Number of observations (fused gauge station): {df_fusion.shape[0]}") + + return df_fusion + + +def fuse_rain_gauges_and_era5(): + era5_filename = "./data/NWP/ERA5/RJ_1997_2023.nc" + ds_era5 = xr.open_dataset(era5_filename) + time_min = ds_era5.time.min().values + time_max = ds_era5.time.max().values + print(f"Range of timestamps in the ERA5 data: [{time_min}, {time_max}]") + + alertario_stations_filename = "./data/ws/alertario_stations.parquet" + df_alertario_stations = pd.read_parquet(alertario_stations_filename) + for index, row in df_alertario_stations.iterrows(): + station_id = row["estacao_desc"] + print(f"Fusing data for gauge station {station_id}") + station_latitude = row["latitude"] + station_longitude = row["longitude"] + df_station = pd.read_parquet( + "./data/ws/alertario/rain_gauge/" + station_id + ".parquet" + ) + df_fusion_result = fuse_rain_gauge_and_era5( + df_station, station_latitude, station_longitude, ds_era5 + ) + assert not df_fusion_result.isnull().values.any().any() + df_fusion_result.to_parquet( + "./data/ws/alertario/rain_gauge_era5_fused/" + station_id + ".parquet" + ) + + +if __name__ == "__main__": + fuse_rain_gauges_and_era5() diff --git a/src/era5/retrieve_ERA5.py b/src/era5/retrieve_ERA5.py new file mode 100644 index 00000000..7aa725ad --- /dev/null +++ b/src/era5/retrieve_ERA5.py @@ -0,0 +1,306 @@ +import argparse +import sys +from collections.abc import Generator +from datetime import datetime +from pathlib import Path + +import xarray as xr +from cdsapi.api import Client as ClientCDS +from xarray.core.dataset import Dataset + +from config import globals + +""" +For using the CDS API to download ERA-5 data consult: https://cds.climate.copernicus.eu/api-how-to +""" + +REGION_OF_INTEREST = {"north": -22, "west": -44, "south": -23, "east": -42} + + +class DatasetClient: + def __init__(self) -> None: + self.clientCDS = ClientCDS(timeout=30, retry_max=5, sleep_max=30) + + def _convert_grib_to_netcdf(self, target: str): + # please see, https://github.com/ecmwf/cfgrib + # also, https://docs.xarray.dev/en/stable/user-guide/io.html#grib-format-via-cfgrib + print("Converting grib data to netcdf...") + assert target.endswith(".grib"), "The target file must be a grib file" + data = xr.open_dataset(target, engine="cfgrib") + target = target.replace(".grib", ".nc") + data.to_netcdf(target) + print("Converted grib data to netcdf") + + def call_retrieve(self, name: str, request: dict, target: str): + try: + self.clientCDS.retrieve(name=name, request=request, target=target) + print(f"Downloaded ERA5 data - {request['format']} format") + if request["format"] == "grib": + self._convert_grib_to_netcdf(target) + except Exception as e: + if request["format"] == "grib": + print(f"Failed to download ERA5 data in grib format. Error {repr(e)}") + raise e + + print( + "Failed to download ERA5 data in netcdf format. Downloading in grib format" + ) + request["format"] = "grib" + target = target.replace(".nc", ".grib") + self.call_retrieve(name, request, target) + + +class CDSDatasetDownloader: + def __init__( + self, begin_year: int, begin_month: int, end_year: int, end_month: int + ) -> None: + self.begin_year = begin_year + self.begin_month = begin_month + self.end_year = min([end_year, datetime.today().year]) + self.end_month = end_month + self.dataset_client = DatasetClient() + + def _get_dates_generator(self) -> Generator[str, None, None]: + current_date = datetime.strptime( + f"{self.begin_year}-{self.begin_month}", "%Y-%m" + ) + end_date = datetime.strptime(f"{self.end_year}-{self.end_month + 1}", "%Y-%m") + while current_date < end_date: + year = int(current_date.year) + month = int(current_date.month) + + yield year, month + + if month == 12: + current_date = current_date.replace(year=current_date.year + 1, month=1) + else: + current_date = current_date.replace(month=current_date.month + 1) + + def _get_datasets_generator(self) -> Generator[Dataset, None, None]: + for year, month in self._get_dates_generator(): + yield xr.open_dataset( + f"{globals.NWP_DATA_DIR}ERA5/montly_data/RJ_{year}_{month}.nc" + ) + + def _download_dataset(self, month: str, year: str): + target_path_nc = Path( + f"{globals.NWP_DATA_DIR}ERA5/montly_data/RJ_{year}_{month}.nc" + ) + if target_path_nc.is_file(): + print(f"ERA5 data already downloaded for the month {month} of year {year}") + return + + target_path_grib = Path( + f"{globals.NWP_DATA_DIR}ERA5/montly_data/RJ_{year}_{month}.grib" + ) + if target_path_grib.is_file(): + print( + f"ERA5 data already downloaded for the month {month} of year {year} with GRIB format" + ) + self.dataset_client._convert_grib_to_netcdf(str(target_path_grib.resolve())) + return + + request = { + "product_type": "reanalysis", + "format": "netcdf", + "variable": [ + "10m_u_component_of_wind", + "10m_v_component_of_wind", + "2m_dewpoint_temperature", + "2m_temperature", + "convective_available_potential_energy", + "convective_inhibition", + "geopotential", + "k_index", + "total_totals_index", + ], + "year": year, + "month": [month], + "day": [f"{day:02d}" for day in range(1, 32)], + "time": [f"{hour:02d}:00" for hour in range(24)], + "area": [ + REGION_OF_INTEREST[key] for key in ["north", "west", "south", "east"] + ], + } + + print(f"Downloading ERA5 data at month {month} of year {year}...") + self.dataset_client.call_retrieve( + name="reanalysis-era5-single-levels", + request=request, + target=str(target_path_nc.resolve()), + ) + print(f"Downloaded ERA5 data at month {month} of year {year}") + + def download_datasets(self): + print( + f"Downloading ERA5 data for the period {self.begin_year} to {self.end_year}..." + ) + for year, month in self._get_dates_generator(): + self._download_dataset(month, year) + print( + f"Downloaded ERA5 data for the period {self.begin_year} to {self.end_year}" + ) + + def prepend_dataset(self, prepend_dataset: str): + if not Path(prepend_dataset).is_file(): + raise FileNotFoundError(f"Dataset to prepend not found: {prepend_dataset}") + + # filename follows this pattern: RJ_YYYY_YYYY.nc + prepend_dataset_name = Path(prepend_dataset).name + prepend_begin_year = int(prepend_dataset_name.split("_")[1]) + prepend_end_year = int(prepend_dataset_name.split("_")[-1].split(".")[0]) + + target_path = Path( + f"{globals.NWP_DATA_DIR}ERA5/RJ_{prepend_begin_year}_{self.end_year}.nc" + ) + if target_path.is_file(): + print( + f"ERA5 data already prepended for the period {prepend_begin_year} to {self.end_year}" + ) + return + + print( + f""" + Last dataset info: + Begin year: {prepend_begin_year} + End year: {prepend_end_year} + """ + ) + + print( + f""" + Current CDSDatasetDownloader info: + Begin year: {self.begin_year} + End year: {self.end_year} + """ + ) + + assert ( + self.end_year >= prepend_end_year + ), "The end year must be greater than the last year of the dataset to prepend" + + print( + f"Prepending ERA5 data {prepend_begin_year}-{prepend_end_year} to {self.begin_year}-{self.end_year}..." + ) + + prepend_ds = xr.open_dataset(prepend_dataset) + append_ds = xr.open_dataset( + f"{globals.NWP_DATA_DIR}ERA5/RJ_{self.begin_year}_{self.end_year}.nc" + ) + + ds = prepend_ds.merge(append_ds) + ds.to_netcdf(str(target_path.resolve())) + print( + f"ERA5 data prepended for the period {prepend_begin_year} to {self.end_year}" + ) + + def merge_datasets(self): + target_path = Path( + f"{globals.NWP_DATA_DIR}ERA5/RJ_{self.begin_year}_{self.end_year}.nc" + ) + if target_path.is_file(): + print( + f"ERA5 data already merged for the period {self.begin_year} to {self.end_year}" + ) + return + + print( + f"Merging ERA5 data for the period {self.begin_year} to {self.end_year}..." + ) + datasets_generator = self._get_datasets_generator() + ds = next(datasets_generator) + for dataset in datasets_generator: + ds = ds.merge(dataset) + ds.to_netcdf(str(target_path.resolve())) + print(f"ERA5 data merged for the period {self.begin_year} to {self.end_year}") + + +def valid_date(arg: str): + try: + year_str, month_str = arg.split("-") + if len(month_str) != 2 or len(year_str) != 4: + raise ValueError + year = int(year_str) + month = int(month_str) + return year, month + except ValueError: + raise argparse.ArgumentTypeError("Invalid date format. Please use YYYY-MM") + + +def main(argv): + parser = argparse.ArgumentParser( + description="Retrieve ERA5 data between two given years." + ) + parser.add_argument( + "-b", "--begin", type=valid_date, required=True, help="Begin date (YYYY-MM)" + ) + parser.add_argument( + "-e", "--end", type=valid_date, required=True, help="End date (YYYY-MM)" + ) + parser.add_argument( + "-pd", + "--prepend_dataset", + type=str, + default=None, + help="Dataset to merge datasets", + ) + parser.add_argument( + "-north", + "--north", + type=float, + default=REGION_OF_INTEREST["north"], + help="Northernmost latitude", + ) + parser.add_argument( + "-west", + "--west", + type=float, + default=REGION_OF_INTEREST["west"], + help="Westernmost longitude", + ) + parser.add_argument( + "-south", + "--south", + type=float, + default=REGION_OF_INTEREST["south"], + help="Southernmost latitude", + ) + parser.add_argument( + "-east", + "--east", + type=float, + default=REGION_OF_INTEREST["east"], + help="Easternmost longitude", + ) + + args = parser.parse_args(argv[1:]) + + begin_year, begin_month = args.begin + end_year, end_month = args.end + prepend_dataset = args.prepend_dataset + REGION_OF_INTEREST["north"] = args.north + REGION_OF_INTEREST["west"] = args.west + REGION_OF_INTEREST["south"] = args.south + REGION_OF_INTEREST["east"] = args.east + + # ERA5 data goes back to the year 1940. + # see https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=form + assert begin_year >= 1940, "ERA5 start year must be greater than or equal to 1940" + assert ( + begin_year <= end_year + ), "ERA5 start year must be less than or equal to end year" + + dataset_downloader = CDSDatasetDownloader( + begin_year=begin_year, + begin_month=begin_month, + end_year=end_year, + end_month=end_month, + ) + dataset_downloader.download_datasets() + dataset_downloader.merge_datasets() + if prepend_dataset: + dataset_downloader.prepend_dataset(prepend_dataset) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/era5/retrieve_ERA5Land.py b/src/era5/retrieve_ERA5Land.py new file mode 100644 index 00000000..f3bb2dac --- /dev/null +++ b/src/era5/retrieve_ERA5Land.py @@ -0,0 +1,294 @@ +import argparse +import sys +from collections.abc import Generator +from datetime import datetime +from pathlib import Path + +import xarray as xr +from cdsapi.api import Client as ClientCDS +from xarray.core.dataset import Dataset + +from config import globals + +""" +For using the CDS API to download ERA-5 data consult: https://cds.climate.copernicus.eu/api-how-to +""" + +REGION_OF_INTEREST = {"north": -22, "west": -44, "south": -23, "east": -42} + + +class DatasetClient: + def __init__(self) -> None: + self.clientCDS = ClientCDS(timeout=30, retry_max=5, sleep_max=30) + self.target = "ERA5Land" + + def _convert_grib_to_netcdf(self, target: str): + # please see, https://github.com/ecmwf/cfgrib + # also, https://docs.xarray.dev/en/stable/user-guide/io.html#grib-format-via-cfgrib + print("Converting grib data to netcdf...") + assert target.endswith(".grib"), "The target file must be a grib file" + data = xr.open_dataset(target, engine="cfgrib") + target = target.replace(".grib", ".nc") + data.to_netcdf(target) + print("Converted grib data to netcdf") + + def call_retrieve(self, name: str, request: dict, target: str): + try: + self.clientCDS.retrieve(name=name, request=request, target=target) + print(f"Downloaded {self.target} data - {request['format']} format") + if request["format"] == "grib": + self._convert_grib_to_netcdf(target) + except Exception as e: + if request["format"] == "grib": + print( + f"Failed to download {self.target} data in grib format. Error {repr(e)}" + ) + raise e + + print( + f"Failed to download {self.target} data in netcdf format. Downloading in grib format" + ) + request["format"] = "grib" + target = target.replace(".nc", ".grib") + self.call_retrieve(name, request, target) + + +class CDSDatasetDownloader: + def __init__( + self, begin_year: int, begin_month: int, end_year: int, end_month: int + ) -> None: + self.begin_year = begin_year + self.begin_month = begin_month + self.end_year = min([end_year, datetime.today().year]) + self.end_month = end_month + self.dataset_client = DatasetClient() + self.target = "ERA5Land" + + def _get_dates_generator(self) -> Generator[str, None, None]: + current_date = datetime.strptime( + f"{self.begin_year}-{self.begin_month}", "%Y-%m" + ) + end_date = datetime.strptime(f"{self.end_year}-{self.end_month}", "%Y-%m") + + while current_date <= end_date: + year = int(current_date.year) + month = int(current_date.month) + + yield year, month + + if month == 12: + current_date = current_date.replace(year=current_date.year + 1, month=1) + else: + current_date = current_date.replace(month=current_date.month + 1) + + def _get_datasets_generator(self) -> Generator[Dataset, None, None]: + for year, month in self._get_dates_generator(): + yield xr.open_dataset( + f"{globals.NWP_DATA_DIR}{self.target}/montly_data/RJ_{year}_{month}.nc" + ) + + def _download_dataset(self, month: str, year: str): + self.dataset_client = DatasetClient() + target_path_nc = Path( + f"{globals.NWP_DATA_DIR}{self.target}/montly_data/RJ_{year}_{month}.nc" + ) + if target_path_nc.is_file(): + print( + f"{self.target} data already downloaded for the month {month} of year {year}" + ) + return + + target_path_grib = Path( + f"{globals.NWP_DATA_DIR}{self.target}/montly_data/RJ_{year}_{month}.grib" + ) + if target_path_grib.is_file(): + print( + f"{self.target} data already downloaded for the month {month} of year {year} with GRIB format" + ) + self.dataset_client._convert_grib_to_netcdf(str(target_path_grib.resolve())) + return + + request = { + "variable": [ + "10m_u_component_of_wind", + "10m_v_component_of_wind", + "2m_dewpoint_temperature", + "2m_temperature", + "skin_temperature", + "soil_temperature_level_1", + "soil_temperature_level_2", + "soil_temperature_level_3", + "soil_temperature_level_4", + "surface_pressure", + "total_precipitation", + ], + "year": year, + "month": month, + "day": [f"{day:02d}" for day in range(1, 32)], + "time": [f"{hour:02d}:00" for hour in range(24)], + "area": [ + REGION_OF_INTEREST[key] for key in ["north", "west", "south", "east"] + ], + "format": "netcdf", + } + + print(f"Downloading {self.target} data at month {month} of year {year}...") + self.dataset_client.call_retrieve( + name="reanalysis-era5-land", + request=request, + target=str(target_path_nc.resolve()), + ) + print(f"Downloaded {self.target} data at month {month} of year {year}") + + def _download_datasets_wrapper(args): + self, month, year = args + self._download_dataset(month, year) + + def download_datasets(self): + target_folder = Path(f"{globals.NWP_DATA_DIR}{self.target}/montly_data") + if not target_folder.exists(): + target_folder.mkdir(parents=True, exist_ok=True) + print( + f"Downloading {self.target} data for the period {self.begin_year}-{self.begin_month} to {self.end_year}-{self.end_month}..." + ) + for year, month in self._get_dates_generator(): + self._download_dataset(month, year) + print( + f"Downloaded {self.target} data for the period {self.begin_year}-{self.begin_month} to {self.end_year}-{self.end_month}" + ) + + def prepend_dataset(self, prepend_dataset: str): + if not Path(prepend_dataset).is_file(): + raise FileNotFoundError(f"Dataset to prepend not found: {prepend_dataset}") + + # filename follows this pattern: RJ_YYYY_YYYY.nc + prepend_dataset_name = Path(prepend_dataset).name + prepend_begin_year = int(prepend_dataset_name.split("_")[1]) + prepend_end_year = int(prepend_dataset_name.split("_")[-1].split(".")[0]) + + target_path = Path( + f"{globals.NWP_DATA_DIR}{self.target}/RJ_{prepend_begin_year}_{self.end_year}.nc" + ) + if target_path.is_file(): + print( + f"{self.target} data already prepended for the period {prepend_begin_year} to {self.end_year}" + ) + return + + print( + f""" + Last dataset info: + Begin year: {prepend_begin_year} + End year: {prepend_end_year} + """ + ) + + print( + f""" + Current CDSDatasetDownloader info: + Begin year: {self.begin_year} + End year: {self.end_year} + """ + ) + + assert ( + self.end_year >= prepend_end_year + ), "The end year must be greater than the last year of the dataset to prepend" + + print( + f"Prepending {self.target} data {prepend_begin_year}-{prepend_end_year} to {self.begin_year}-{self.end_year}..." + ) + + prepend_ds = xr.open_dataset(prepend_dataset) + append_ds = xr.open_dataset( + f"{globals.NWP_DATA_DIR}{self.target}/RJ_{self.begin_year}_{self.end_year}.nc" + ) + + ds = prepend_ds.merge(append_ds) + ds.to_netcdf(str(target_path.resolve())) + print( + f"{self.target} data prepended for the period {prepend_begin_year} to {self.end_year}" + ) + + def merge_datasets(self): + target_path = Path( + f"{globals.NWP_DATA_DIR}{self.target}/RJ_{self.begin_year}_{self.end_year}.nc" + ) + if target_path.is_file(): + print( + f"{self.target} data already merged for the period {self.begin_year}-{self.begin_month} to {self.end_year}-{self.end_month}" + ) + return + + print( + f"Merging {self.target} data for the period {self.begin_year}-{self.begin_month} to {self.end_year}-{self.end_month}..." + ) + datasets_generator = self._get_datasets_generator() + ds = next(datasets_generator) + for dataset in datasets_generator: + ds = ds.merge(dataset) + ds.to_netcdf(str(target_path.resolve())) + print( + f"{self.target} data merged for the period {self.begin_year}-{self.begin_month} to {self.end_year}-{self.end_month}" + ) + + +def valid_date(arg: str): + try: + year_str, month_str = arg.split("-") + if len(month_str) != 2 or len(year_str) != 4: + raise ValueError + year = int(year_str) + month = int(month_str) + return year, month + except ValueError: + raise argparse.ArgumentTypeError("Invalid date format. Please use YYYY-MM") + + +def main(argv): + parser = argparse.ArgumentParser( + description="Retrieve ERA5Land data between two given years." + ) + parser.add_argument( + "-b", "--begin", type=valid_date, required=True, help="Begin date (YYYY-MM)" + ) + parser.add_argument( + "-e", "--end", type=valid_date, required=True, help="End date (YYYY-MM)" + ) + parser.add_argument( + "-pd", + "--prepend_dataset", + type=str, + default=None, + help="Dataset to merge datasets", + ) + + args = parser.parse_args(argv[1:]) + + begin_year, begin_month = args.begin + end_year, end_month = args.end + prepend_dataset = args.prepend_dataset + + # ERA5Land data goes back to the year 1940. + # see https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-land?tab=overview + assert ( + begin_year >= 1950 + ), "ERA5Land start year must be greater than or equal to 1950" + assert ( + begin_year <= end_year + ), "ERA5Land start year must be less than or equal to end year" + + dataset_downloader = CDSDatasetDownloader( + begin_year=begin_year, + begin_month=begin_month, + end_year=end_year, + end_month=end_month, + ) + dataset_downloader.download_datasets() + dataset_downloader.merge_datasets() + if prepend_dataset: + dataset_downloader.prepend_dataset(prepend_dataset) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/fuse_rain_gauge_and_era5.py b/src/fuse_rain_gauge_and_era5.py deleted file mode 100644 index ec6c7884..00000000 --- a/src/fuse_rain_gauge_and_era5.py +++ /dev/null @@ -1,82 +0,0 @@ -import pandas as pd -import xarray as xr -import util - -def fuse_rain_gauge_and_era5(df_station: pd.DataFrame, station_latitude: float, station_longitude: float, ds_era5): - df_station['datetime'] = df_station['datetime'].dt.tz_convert('UTC') - df_station['datetime'] = df_station['datetime'].dt.tz_localize(None) - df_station = df_station.set_index(pd.DatetimeIndex(df_station['datetime'])) - df_station = df_station.drop(['datetime'], axis = 1) - assert (not df_station.isnull().values.any().any()) - - time_min = min(df_station.index) - time_max = max(df_station.index) - print(f"Range of timestamps: [{time_min}, {time_max}]") - print(f"Number of observations (gauge station): {df_station.shape[0]}") - - # Select ERA5 data near the station - era5_data_at_1000hPa = ds_era5.sel(level=1000, longitude=station_longitude, latitude=station_latitude, method="nearest") - - df_era5_data_for_station = pd.DataFrame( - { - "time": era5_data_at_1000hPa.time.values, - "pressure_1000": 1000, - "Humidity_1000": era5_data_at_1000hPa.r, - "Temperature_1000": era5_data_at_1000hPa.t, - "WindU_1000": era5_data_at_1000hPa.u, - "WindV_1000": era5_data_at_1000hPa.v - } - ) - - # Create a datetime index for the dataframe containing ERA5 simulated data. - format_string = '%Y-%m-%d %H:%M:%S' - df_era5_data_for_station['datetime'] = pd.to_datetime(df_era5_data_for_station['time'], format=format_string) - df_era5_data_for_station = df_era5_data_for_station.set_index(pd.DatetimeIndex(df_era5_data_for_station['datetime'])) - df_era5_data_for_station = df_era5_data_for_station.drop(['time', 'datetime'], axis = 1) - - # Temperature in ERA5 is provided in Kelvin; convert to Celsius. - df_era5_data_for_station["Temperature_1000_Celsius"] = df_era5_data_for_station["Temperature_1000"].apply(util.convert_to_celsius) - - assert (not df_era5_data_for_station.isnull().values.any().any()) - - df_fusion = pd.merge(df_station, df_era5_data_for_station, how='left', left_index=True, right_index=True) - - column_name_mapping = { - "Temperature_1000_Celsius": "temperature", - "Humidity_1000": "relative_humidity", - "pressure_1000": "barometric_pressure", - "WindU_1000": "wind_direction_u", - "WindV_1000": "wind_direction_v", - "precipitation_sum": "precipitation" - } - column_names = column_name_mapping.keys() - - df_fusion = util.get_dataframe_with_selected_columns(df_fusion, column_names) - - df_fusion = util.rename_dataframe_column_names(df_fusion, column_name_mapping) - - print(f"Number of observations (fused gauge station): {df_fusion.shape[0]}") - - return df_fusion - -def fuse_rain_gauges_and_era5(): - era5_filename = "./data/NWP/ERA5/RJ_1997_2023.nc" - ds_era5 = xr.open_dataset(era5_filename) - time_min = ds_era5.time.min().values - time_max = ds_era5.time.max().values - print(f"Range of timestamps in the ERA5 data: [{time_min}, {time_max}]") - - alertario_stations_filename = "./data/ws/alertario_stations.parquet" - df_alertario_stations = pd.read_parquet(alertario_stations_filename) - for index, row in df_alertario_stations.iterrows(): - station_id = row["estacao_desc"] - print(f"Fusing data for gauge station {station_id}") - station_latitude = row["latitude"] - station_longitude = row["longitude"] - df_station = pd.read_parquet("./data/ws/alertario/rain_gauge/" + station_id + ".parquet") - df_fusion_result = fuse_rain_gauge_and_era5(df_station, station_latitude, station_longitude, ds_era5) - assert (not df_fusion_result.isnull().values.any().any()) - df_fusion_result.to_parquet("./data/ws/alertario/rain_gauge_era5_fused/" + station_id + ".parquet") - -if __name__ == "__main__": - fuse_rain_gauges_and_era5() diff --git a/src/gen_dsif_images.py b/src/gen_dsif_images.py deleted file mode 100644 index 1a4faaea..00000000 --- a/src/gen_dsif_images.py +++ /dev/null @@ -1,170 +0,0 @@ -import os -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -from osgeo import osr # Python bindings for GDAL -from osgeo import gdal # Python bindings for GDAL -import numpy as np # Scientific computing with Python - -"""Builds a reprojected netCDF file from a full disk netCDF file. - -Args: -in_filename (str): Path to the full disk netCDF file. -out_filename (str): Path to write the reprojected netCDF file. -var (str): Name of the variable to reproject within the input file. -extent (tuple): A tuple of four floats defining the output bounding box in -geographic coordinates (lon_min, lat_max, lon_max, lat_min). - -Returns: -str: The starting time of the data coverage extracted from the metadata -of the input file. - -Raises: -RuntimeError: If there is an error opening the input file or writing -the reprojected file. -""" -def build_projection_from_full_disk(in_filename, out_filename, var, extent): - - # Open the file - img = gdal.Open(f'NETCDF:{in_filename}:' + var) - - # Read the header metadata - metadata = img.GetMetadata() - scale = float(metadata.get(var + '#scale_factor')) - offset = float(metadata.get(var + '#add_offset')) - undef = float(metadata.get(var + '#_FillValue')) - dtime = metadata.get('NC_GLOBAL#time_coverage_start') - - # print(f'scale/offset/undef/dtime: {scale}/{offset}/{undef}/{dtime}') - - # Load the data - ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) - - # Apply the scale and offset - ds = (ds * scale + offset) - - # Read the original file projection and configure the output projection - source_prj = osr.SpatialReference() - source_prj.ImportFromProj4(img.GetProjectionRef()) - - target_prj = osr.SpatialReference() - target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") - - # Reproject the data - GeoT = img.GetGeoTransform() - driver = gdal.GetDriverByName('MEM') - raw = driver.Create('raw', ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32) - raw.SetGeoTransform(GeoT) - raw.GetRasterBand(1).WriteArray(ds) - - # Define the parameters of the output file - options = gdal.WarpOptions(format = 'netCDF', - srcSRS = source_prj, - dstSRS = target_prj, - outputBounds = (extent[0], extent[3], extent[2], extent[1]), - outputBoundsSRS = target_prj, - outputType = gdal.GDT_Float32, - srcNodata = undef, - dstNodata = 'nan', - xRes = 0.02, - yRes = 0.02, - resampleAlg = gdal.GRA_NearestNeighbour) - - # print(options) - - # Write the reprojected file on disk - gdal.Warp(f'{out_filename}', raw, options=options) - print(f'Projection saved to file {out_filename}.') - - return dtime - -def build_image_from_projection(projection_filename, var, dtime): - #----------------------------------------------------------------------------------------------------------- - # Open the reprojected GOES-R image - file = Dataset(f'{projection_filename}') - - # print(f'file.variables = {file.variables}') - - # Get the pixel values - data = file.variables['Band1'][:] - - #----------------------------------------------------------------------------------------------------------- - # Choose the plot size (width x height, in inches) - plt.figure(figsize=(10,10)) - - # Use the Geostationary projection in cartopy - ax = plt.axes(projection=ccrs.PlateCarree()) - - # Define the image extent - img_extent = [extent[0], extent[2], extent[1], extent[3]] - - # Define the color scale based on the channel - colormap = "jet" # White to black for IR channels - # colormap = "gray_r" # White to black for IR channels - - # Plot the image - img = ax.imshow(data, origin='upper', extent=img_extent, cmap=colormap) - - # Add coastlines, borders and gridlines - ax.coastlines(resolution='10m', color='black', linewidth=0.8) - ax.add_feature(cartopy.feature.BORDERS, edgecolor='white', linewidth=0.5) - gl = ax.gridlines(crs=ccrs.PlateCarree(), - color='gray', - alpha=1.0, - linestyle='--', - linewidth=0.25, - xlocs=np.arange(-180, 180, 5), - ylocs=np.arange(-90, 90, 5), - draw_labels=True) - gl.top_labels = False - gl.right_labels = False - - # Add a colorbar - plt.colorbar(img, label=var, extend='both', orientation='horizontal', pad=0.05, fraction=0.05) - - # Extract date - date = (datetime.strptime(dtime, '%Y-%m-%dT%H:%M:%S.%fZ')) - - # Add a title - plt.title('GOES-16 ' + var + ' ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC', fontweight='bold', fontsize=10, loc='left') - plt.title('Reg.: ' + str(extent) , fontsize=10, loc='right') - - - #----------------------------------------------------------------------------------------------------------- - # Save the image - temp = file_name[0:-3] - plt.savefig(f'{output_folder}{temp}_{var}.png', bbox_inches='tight', pad_inches=0, dpi=300) - - -if __name__ == "__main__": - input_folder = './data/goes16/goes16_dsif/' - output_folder = './data/goes16/goes16_dsif_imgs/' - - # Get the list of file names in the folder - file_names = [f for f in os.listdir(input_folder) if os.path.isfile(os.path.join(input_folder, f))] - - # Coordinates of rectangle for region of interest (Rio de Janeiro municipality) - extent = [-64.0, -35.0, -35.0, -15.0] # Min lon, Min lat, Max lon, Max lat - - # Options: - # - Convective Available Potential Energy (CAPE) - # - Lifted Index (LI) - # - Total Totals (TT) - # - Showalter Index (SI) - # - K-index (KI) - - vars = ['CAPE', 'LI', 'TT', 'SI', 'KI'] - - file_names.sort() - - for file_name in file_names: - print(f'Generating images for {file_name}') - for var in vars: - in_filename = f'{input_folder}{file_name}' - out_filename = file_name[0:-3] - out_filename = f'{output_folder}{out_filename}_reprojected.nc' - print(out_filename) - dtime = build_projection_from_full_disk(in_filename, out_filename, var, extent) - build_image_from_projection(out_filename, var, dtime) \ No newline at end of file diff --git a/src/gen_sounding_indices.py b/src/gen_sounding_indices.py deleted file mode 100644 index fae56a0f..00000000 --- a/src/gen_sounding_indices.py +++ /dev/null @@ -1,74 +0,0 @@ -import pandas as pd -from metpy.units import units -import metpy.calc as mpcalc -import argparse - -def compute_indices(df_launch): - df_launch_cleaned = df_launch.drop_duplicates(subset='pressure', ignore_index=True) - - df_launch_cleaned = df_launch_cleaned.dropna(subset=('temperature', 'dewpoint', 'pressure'), how='any').reset_index(drop=True) - - df_launch_cleaned = df_launch_cleaned.sort_values('pressure', ascending=False) - - pressure_values = df_launch_cleaned['pressure'].to_list() * units.hPa - temperature_values = df_launch_cleaned['temperature'].to_list() * units.degC - dewpoint_values = df_launch_cleaned['dewpoint'].to_list() * units.degC - - parcel_profile = mpcalc.parcel_profile(pressure_values, - temperature_values[0], - dewpoint_values[0]).to('degC') - - indices = dict() - - CAPE = mpcalc.cape_cin(pressure_values, temperature_values, dewpoint_values, parcel_profile)#, which_lfc = "top", which_el = "top") - indices['cape'] = CAPE[0].magnitude - indices['cin'] = CAPE[1].magnitude - - lift = mpcalc.lifted_index(pressure_values, temperature_values, parcel_profile) - indices['lift'] = lift[0].magnitude - - k = mpcalc.k_index(pressure_values, temperature_values, dewpoint_values) - indices['k'] = k.magnitude - - total_totals = mpcalc.total_totals_index(pressure_values, temperature_values, dewpoint_values) - indices['total_totals'] = total_totals.magnitude - - showalter = mpcalc.showalter_index(pressure_values, temperature_values, dewpoint_values) - indices['showalter'] = showalter.magnitude[0] - - return indices - -def main(): - parser = argparse.ArgumentParser(description='Generate instability indices from sounding measurements.') - parser.add_argument('--input_file', help='input Parquet file name containing the sounding measurements', required=True) - parser.add_argument('--output_file', help='output Parquet file name where the indices are going to be saved', required=True) - args = parser.parse_args() - - df_s = pd.read_parquet(args.input_file) - - df_indices = pd.DataFrame(columns = ['time', 'cape', 'cin', 'lift', 'k', 'total_totals', 'showalter']) - - for launch_timestamp in pd.to_datetime(df_s.time).unique(): - print(f"Generating instability indices for launch made at {launch_timestamp}...", end="") - try: - df_launch = df_s[pd.to_datetime(df_s['time']) == launch_timestamp] - indices_dict = compute_indices(df_launch) - indices_dict['time'] = launch_timestamp - df_indices = pd.concat([df_indices, pd.DataFrame.from_records([indices_dict])]) - print("Success!") - except ValueError as e: - print(f'Error processing measurements made by launch at {launch_timestamp}') - print(f'{repr(e)}') - except IndexError as e: - print(f'Error processing measurements made by launch at {launch_timestamp}') - print(f'{repr(e)}') - except KeyError as e: - print(f'Error processing measurements made by launch at {launch_timestamp}') - print(f'{repr(e)}') - - df_indices.to_parquet(args.output_file, compression='gzip', index = False) - - print("Done!") - -if __name__ == "__main__": - main() diff --git a/src/gen_tpw_datasets_per_wsois.py b/src/gen_tpw_datasets_per_wsois.py deleted file mode 100644 index 842fd34f..00000000 --- a/src/gen_tpw_datasets_per_wsois.py +++ /dev/null @@ -1,108 +0,0 @@ -import pandas as pd -from globals import INMET_WEATHER_STATION_IDS - -import os -import pandas as pd - -def hourly_average_with_nan_handling(df): - # Resample the DataFrame to hourly frequency and compute the mean - df_resampled = df['tpw_value'].resample('H').mean() - - # Drop rows with NaN values in 'tpw' - # df_resampled = df_resampled.dropna() - - return pd.DataFrame({'tpw_value': df_resampled.values}, - index=df_resampled.index + pd.DateOffset(hours=1)) - -# def hourly_average_with_nan_handling(df): -# # First, make sure the DataFrame is sorted by the datetime index -# df = df.sort_index() - -# # Use resample to group the data by hour and calculate the mean -# hourly_avg_df = df.resample('H').mean() - -# return hourly_avg_df - -# hourly_avg_df = hourly_average_with_nan_handling(df) -# print(hourly_avg_df) - -# Set the folder containing the Parquet files -folder_path = './data/goes16/tpw' # Replace with the path to your folder - -# Initialize an empty list to store DataFrames -dataframes = [] - -# List all Parquet files in the folder -parquet_files = [file for file in os.listdir(folder_path) if file.endswith('.parquet')] - -# Loop through the Parquet files, read them, and append to the list -for file in parquet_files: - file_path = os.path.join(folder_path, file) - df = pd.read_parquet(file_path) - print(f'Merging dataframe {file_path} of shape {df.shape}') - dataframes.append(df) - -# Concatenate all DataFrames into a single DataFrame, so that -# merged_df contains the combined data from all Parquet files -merged_df = pd.concat(dataframes) - -# print(f'merged_df.columns (1): {merged_df.columns}') - -# # Reset the index to 'timestamp' and drop the old index -# merged_df.set_index('timestamp', inplace=True) -# merged_df.index = pd.to_datetime(merged_df.index[0]) - -# print(f'merged_df.columns (2): {merged_df.columns}') - -# If you want to sort the DataFrame by the 'timestamp' column -# merged_df.sort_index(inplace=True) - - -# Print the first few rows to verify -print('MERGED DATAFRAME:') -print(merged_df.head()) -print(merged_df.shape) - -for wsoi_id in INMET_WEATHER_STATION_IDS: - print(f'Processing data for station {wsoi_id}') - - # Create a boolean mask to filter rows with 'station_id' equal to 'wsoi_id' - mask = merged_df['station_id'] == wsoi_id - - # Use the mask to select rows from the DataFrame - df_wsoi = merged_df[mask] - print(df_wsoi) - - print('columns (1):', df_wsoi.columns) - df_wsoi.reset_index(inplace=True) - print('columns (2):', df_wsoi.columns) - - # Now, the `df_wsoi` DataFrame contains rows where 'station_id' matches 'wsoi_id' - print(f'df_wsoi.shape: {df_wsoi.shape}') - print('Number of NaN values:', df_wsoi['tpw_value'].isna().sum()) - - print(f'df_wsoi.index (1): {df_wsoi.index}') - - print(f'---(1):') - print(df_wsoi.head()) - - df_wsoi = df_wsoi[['timestamp', 'tpw_value']] - - df_wsoi.index = pd.to_datetime(df_wsoi.timestamp) - df_wsoi = df_wsoi.drop(columns=['timestamp']) - - df_wsoi = df_wsoi.sort_index() - - print(f'---(2):') - print(df_wsoi.head(80)) - - df_wsoi = hourly_average_with_nan_handling(df_wsoi) - - print(f'df_wsoi.index (2): {df_wsoi.index}') - - print(f'---(3):') - print(df_wsoi.head(30)) - - print(df_wsoi['tpw_value'].isna().sum()) - df_wsoi.to_parquet(f'./data/goes16/wsoi/{wsoi_id}.parquet') - print('~~~') diff --git a/src/globals.py b/src/globals.py deleted file mode 100644 index c0539877..00000000 --- a/src/globals.py +++ /dev/null @@ -1,121 +0,0 @@ -INMET_API_BASE_URL = "https://apitempo.inmet.gov.br" - -# Weather stations datasource directories -WS_INMET_DATA_DIR = "./data/ws/inmet/" -WS_ALERTARIO_DATA_DIR = "./data/ws/alertario/ws/" -GS_ALERTARIO_DATA_DIR = "./data/ws/alertario/rain_gauge_era5_fused/" - -# WS_GOES_DATA_DIR = "atmoseer/data/ws/goes16" -GOES_DATA_DIR = "./data/goes16" - -# Atmospheric sounding datasource directory -NWP_DATA_DIR = "./data/NWP/" - -# Atmospheric sounding datasource directory -AS_DATA_DIR = "./data/as/" - -# TPW GOES16 datasource directory -TPW_DATA_DIR = "./data/goes16/wsoi" - -# Directory to store the train/val/test datasets for each weather station of interest -DATASETS_DIR = './data/datasets/' - -# Directory to store the generated models and their corresponding reports -MODELS_DIR = './models/' - -# see https://portal.inmet.gov.br/paginas/catalogoaut -INMET_WEATHER_STATION_IDS = ( - 'A636', # Jacarepagua - 'A621', # Vila militar - 'A602', # Marambaia - 'A652', # Forte de Copacabana - 'A627' # Niteroi -) - -ALERTARIO_GAUGE_STATION_IDS = ( - 'anchieta', - 'av_brasil_mendanha', - 'bangu', - 'barrinha', - 'campo_grande', - 'cidade_de_deus', - 'copacabana', - 'grajau_jacarepagua', - 'grajau', - 'grande_meier', - 'grota_funda', - 'ilha_do_governador', - 'laranjeiras', - 'madureira', - 'penha', - 'piedade', - 'recreio', - 'rocinha', - 'santa_teresa', - 'saude', - 'sepetiba', - 'tanque', - 'tijuca_muda', - 'tijuca', - 'urca', - 'alto_da_boa_vista', #** - 'iraja', #** - 'jardim_botanico', #** - 'riocentro', #** - 'santa_cruz', #** - 'vidigal' #** - ) - -ALERTARIO_WEATHER_STATION_IDS = ( - 'guaratiba', #** - 'sao_cristovao' #** - ) - -# hyper_params_dict_bc = { -# "N_EPOCHS" : 3500, -# "PATIENCE" : 1000, -# "BATCH_SIZE" : 1024, -# "WEIGHT_DECAY" : 0, -# "LEARNING_RATE" : 0.0003, -# "DROPOUT_RATE" : 0.5, -# "SLIDING_WINDOW_SIZE" : 6 -# } - -# hyper_params_dict_oc = { -# "N_EPOCHS" : 6000, -# "PATIENCE" : 1000, -# "BATCH_SIZE" : 1024, -# "WEIGHT_DECAY" : 0, -# "LEARNING_RATE" : 3e-6, -# "DROPOUT_RATE" : 0.5, -# "SLIDING_WINDOW_SIZE" : 6 -# } - - -# Observed variables for INMET weather stations: -# ,DC_NOME, -# PRE_INS, -# TEM_SEN, -# VL_LATITUDE, -# PRE_MAX,UF, -# RAD_GLO, -# PTO_INS, -# TEM_MIN, -# VL_LONGITUDE, -# UMD_MIN, -# PTO_MAX, -# VEN_DIR, -# DT_MEDICAO, -# CHUVA, -# PRE_MIN, -# UMD_MAX, -# VEN_VEL, -# PTO_MIN, -# TEM_MAX, -# TEN_BAT, -# VEN_RAJ, -# TEM_CPU, -# TEM_INS, -# UMD_INS, -# CD_ESTACAO, -# HR_MEDICAO \ No newline at end of file diff --git a/src/goes16/README.md b/src/goes16/README.md new file mode 100644 index 00000000..cc964d5f --- /dev/null +++ b/src/goes16/README.md @@ -0,0 +1,114 @@ +## 📥 GOES-16 ABI Downloader and Cropper + +The script `goes16_download_crop.py` allows you to: + +- Download GOES-16 ABI data from AWS (`noaa-goes16` S3 bucket) +- Select a specific ABI channel (e.g., C08) +- Define a date range for download +- Crop and resample data to a specific geographic bounding box +- Save one NetCDF file per day of imagery + +### ⚙️ Usage with Makefile + +You can execute the downloader/cropper using the provided `Makefile`. An example: + +```bash +make goes16-download-crop START=2024-01-01 END=2024-01-01 CHANNEL=08 DIR=./data/goes16/CMI/2024/C08 +``` + +This will create daily NetCDF files (reprojected and cropped) in: + +``` +data/goes16/CMI/2024/C08/ +``` + +Make sure to set up AWS CLI credentials and install dependencies like `s3fs`, `xarray`, and `pyproj`. + +--- + +## 📦 GOES-16 Feature Extractor + +This module provides feature engineering routines to extract physically meaningful variables from GOES-16 ABI satellite imagery. These features can be used to support precipitation nowcasting models. + +### 📁 Location + +All scripts are contained in: + +``` +src/goes16/ +├── features.py # All feature extraction functions +├── main_goes16_features.py # Command-line script for feature generation +``` + +### ⚙️ Available Features + +| Flag | Description | +|--------------|------------------------------------------------------------| +| `--pn` | Cloud depth: difference between channels C09 and C13 | +| `--gtn` | Glaciation top of clouds: tri-spectral difference (C11,C14,C15) | +| `--fa` | Temporal derivative of upward flux (based on C13) | +| `--wv_grad` | Water vapor gradient: difference C09 - C08 | +| `--li_proxy` | Stability proxy: difference C14 - C13 | +| `--toct` | Cloud Top Temperature (C13 raw) | +| `--pn_std` | Spatial texture (std) of cloud depth (PN) | +| `--verbose` | Print progress messages by year and file count | + +### 🚀 How to Run + +Use the Makefile to extract selected features. An example: + +```bash +make goes16-features FEATS="--pn --gtn --fa --wv_grad --li_proxy --toct --pn_std --verbose" +``` + + +### 📂 Expected Input Structure + +GOES-16 ABI data must be organized as follows: + +``` +data/ +├── goes16/ +│ ├── CMI/ +│ │ └── / +│ │ ├── C09/ +│ │ ├── C13/ +│ │ └── ... +│ └── features/ +│ └── / +│ └── / +``` + +Each channel directory contains files named like: + +``` +C13_2020_01_01_00_00.nc +C13_2020_01_01_00_10.nc +... +``` + +### 💾 Output + +Features are saved to: + +``` +features/CMI/{feature_name}/{year}/FEATURE_TIMESTAMP.nc +``` + +Where `feature_name` is one of the extracted variables (e.g., `temperatura_topo_nuvem`, `proxy_estabilidade`, etc.). + +## Feature Validation and Logging + +### Validating Generated Features + +You can validate whether the generated features are consistent with the source channels: + +make validate-feature FEAT=pn CANAIS="C09 C13" + +### Log Analysis + +Each feature module generates a `.log` file (e.g. pn.log, gtn.log, ...) in `src/goes16/features/`. + +To summarize warnings and errors across all logs: + +make analyze-logs \ No newline at end of file diff --git a/src/goes16/__init__.py b/src/goes16/__init__.py new file mode 100644 index 00000000..8b5acb04 --- /dev/null +++ b/src/goes16/__init__.py @@ -0,0 +1 @@ +# GOES-16 CMI feature extractor package diff --git a/src/goes16/__pycache__/processing_data.cpython-310.pyc b/src/goes16/__pycache__/processing_data.cpython-310.pyc deleted file mode 100644 index 9b580552..00000000 Binary files a/src/goes16/__pycache__/processing_data.cpython-310.pyc and /dev/null differ diff --git a/src/goes16/analyze_logs.py b/src/goes16/analyze_logs.py new file mode 100644 index 00000000..14696bca --- /dev/null +++ b/src/goes16/analyze_logs.py @@ -0,0 +1,43 @@ +# This script analyzes the logs generated by the GOES-16 feature extraction scripts. +# It summarizes warnings, errors, and exceptions found in the log files. +# The logs are expected to be in the "src/goes16/features" directory, and +# the script will parse each log file to extract relevant information. +import os +import re + +LOG_DIR = "src/goes16/features" +LOG_PATTERNS = { + "warnings": re.compile(r"\[WARNING\] (.+)"), + "errors": re.compile(r"\[ERROR\] (.+)"), + "exceptions": re.compile(r"\[ERROR\] (.+?)(?=\n|$)"), +} + + +def parse_log(file_path): + summary = {"warnings": [], "errors": [], "exceptions": []} + with open(file_path, encoding="utf-8") as f: + content = f.read() + for key, pattern in LOG_PATTERNS.items(): + summary[key] = pattern.findall(content) + return summary + + +def summarize_logs(): + print("\n📋 Análise de logs de features GOES-16:\n") + for file in sorted(os.listdir(LOG_DIR)): + if not file.endswith(".log"): + continue + path = os.path.join(LOG_DIR, file) + print(f"🔍 {file}") + result = parse_log(path) + for kind in ["warnings", "errors", "exceptions"]: + items = result[kind] + if items: + print( + f" {kind.capitalize()}: {len(items)} ocorrências. Ex: {items[0]}" + ) + print() + + +if __name__ == "__main__": + summarize_logs() diff --git a/src/goes16/download_data.py b/src/goes16/download_data.py index 5d116021..0afc48c1 100644 --- a/src/goes16/download_data.py +++ b/src/goes16/download_data.py @@ -1,48 +1,60 @@ # -*- coding: utf-8 -*- -#----------------------------------------------------------------------------------------------------------------------------------- -''' +# ----------------------------------------------------------------------------------------------------------------------------------- +""" Description: Downloads GOES-16/17 data from amazon Author: Joao Henry Huaman Chinchay E-mail: joaohenry23@gmail.com Created date: Mar 23, 2020 Modification date: Jul 23, 2023 -''' -#----------------------------------------------------------------------------------------------------------------------------------- -import numpy as np -import s3fs -from datetime import * -import requests +""" + +# ----------------------------------------------------------------------------------------------------------------------------------- import os +from datetime import datetime, timedelta -from urllib3.util.retry import Retry +import numpy as np +import requests +import s3fs from requests.adapters import HTTPAdapter +from urllib3.util.retry import Retry -#----------------------------------------------------------------------------------------------------------------------------------- -def show_products(): - ''' +# ----------------------------------------------------------------------------------------------------------------------------------- +def show_products(): + """ Lists the products available from GOES-16, GOES-17 and GOES-18. - ''' + """ - Satellite = ['goes16','goes17','goes18'] - print(' ') + Satellite = ["goes16", "goes17", "goes18"] + print(" ") for sat in Satellite: - print('Products for '+sat+':') + print("Products for " + sat + ":") fs = s3fs.S3FileSystem(anon=True) - for item in fs.ls('s3://noaa-'+sat+'/'): - if item.split('/')[-1] == 'index.html': - print(' ') + for item in fs.ls("s3://noaa-" + sat + "/"): + if item.split("/")[-1] == "index.html": + print(" ") else: - print('\t'+item.split('/')[-1]) - - print('Descriptions of each product is shown in https://docs.opendata.aws/noaa-goes16/cics-readme.html#about-the-data \n') - -#----------------------------------------------------------------------------------------------------------------------------------- -def download_file(URL, name_file, path_out, retries=10, backoff=0.2, size_format='Decimal', show_download_progress=True, overwrite_file=False): - - ''' + print("\t" + item.split("/")[-1]) + + print( + "Descriptions of each product is shown in https://docs.opendata.aws/noaa-goes16/cics-readme.html#about-the-data \n" + ) + + +# ----------------------------------------------------------------------------------------------------------------------------------- +def download_file( + URL, + name_file, + path_out, + retries=10, + backoff=0.2, + size_format="Decimal", + show_download_progress=True, + overwrite_file=False, +): + """ Save data in file. @@ -51,7 +63,7 @@ def download_file(URL, name_file, path_out, retries=10, backoff=0.2, size_format URL : str Link of file. - name_file : str + name_file : str Name of output file. path_out : str, optional, default '' @@ -69,7 +81,7 @@ def download_file(URL, name_file, path_out, retries=10, backoff=0.2, size_format size_format: str, optional, default 'Decimal' Defines how is print the size of file. Options are: - 'Decimal' : divide file size (in bytes) by (1000*1000) + 'Decimal' : divide file size (in bytes) by (1000*1000) 'Binary' : divide file size (in bytes) by (1024*1024) show_download_progress : boolean, optional, default True @@ -81,58 +93,110 @@ def download_file(URL, name_file, path_out, retries=10, backoff=0.2, size_format If overwrite_file=True the downloaded file is overwrite (the file is downloaded again). - ''' + """ StartTime = datetime.now() - retries_config = Retry(total=retries, backoff_factor=backoff, status_forcelist=[500, 502, 503, 504]) + retries_config = Retry( + total=retries, backoff_factor=backoff, status_forcelist=[500, 502, 503, 504] + ) session = requests.Session() - session.mount('http://', HTTPAdapter(max_retries=retries_config)) - session.mount('https://', HTTPAdapter(max_retries=retries_config)) + session.mount("http://", HTTPAdapter(max_retries=retries_config)) + session.mount("https://", HTTPAdapter(max_retries=retries_config)) req = session.get(URL, stream=True) - #req = requests.get(URL, stream=True) - total_size = int(req.headers['content-length']) + # req = requests.get(URL, stream=True) + total_size = int(req.headers["content-length"]) size = 0 - if size_format == 'Binary': - dsize = 1024*1024 + if size_format == "Binary": + dsize = 1024 * 1024 else: - dsize = 1000*1000 - + dsize = 1000 * 1000 make_download = True - if os.path.isfile(path_out+name_file)==True: - if os.path.getsize(path_out+name_file)==total_size: - if overwrite_file==False: - print(' {} already exists.'.format(name_file)) + if os.path.isfile(path_out + name_file): + if os.path.getsize(path_out + name_file) == total_size: + if not overwrite_file: + print(" {} already exists.".format(name_file)) make_download = False else: - print(' {} will be overwritten.'.format(name_file)) + print(" {} will be overwritten.".format(name_file)) make_download = True else: make_download = True - - if make_download == True: - with open(path_out+name_file,'wb') as output_file: + if make_download: + with open(path_out + name_file, "wb") as output_file: for chunk in req.iter_content(chunk_size=1024): if chunk: rec_size = output_file.write(chunk) size = rec_size + size - if show_download_progress==True: - print(' {} {:3.0f}% {:.1f}MB {}'.format(name_file,100.0*size/total_size, size/dsize, '{}m{}s'.format(round((datetime.now()-StartTime).seconds/60.0),(datetime.now()-StartTime).seconds%60) if (datetime.now()-StartTime).seconds>60 else '{}s'.format((datetime.now()-StartTime).seconds) ), end="\r") #, flush=True) - #print('\t{}\t{:3.0f}%\t{:.2f} min'.format(name_file,100.0*size/total_size, (datetime.now()-StartTime).seconds/60.0), end="\r") #, flush=True) + if show_download_progress: + print( + " {} {:3.0f}% {:.1f}MB {}".format( + name_file, + 100.0 * size / total_size, + size / dsize, + ( + "{}m{}s".format( + round( + (datetime.now() - StartTime).seconds / 60.0 + ), + (datetime.now() - StartTime).seconds % 60, + ) + if (datetime.now() - StartTime).seconds > 60 + else "{}s".format( + (datetime.now() - StartTime).seconds + ) + ), + ), + end="\r", + ) # , flush=True) + # print('\t{}\t{:3.0f}%\t{:.2f} min'.format(name_file,100.0*size/total_size, (datetime.now()-StartTime).seconds/60.0), end="\r") #, flush=True) if size == total_size: - #print('\n') - print(' {} {:3.0f}% {:.1f}MB {}'.format(name_file,100.0*size/total_size, size/dsize, '{}m{}s'.format(round((datetime.now()-StartTime).seconds/60.0),(datetime.now()-StartTime).seconds%60) if (datetime.now()-StartTime).seconds>60 else '{}s'.format((datetime.now()-StartTime).seconds) )) - - #print('\b') - -#----------------------------------------------------------------------------------------------------------------------------------- -def download(Satellite, Product, DateTimeIni=None, DateTimeFin=None, domain=None, channel=None, rename_fmt=False, path_out='', retries=10, backoff=10, size_format='Decimal', show_download_progress=True, overwrite_file=False): - - ''' + # print('\n') + print( + " {} {:3.0f}% {:.1f}MB {}".format( + name_file, + 100.0 * size / total_size, + size / dsize, + ( + "{}m{}s".format( + round( + (datetime.now() - StartTime).seconds + / 60.0 + ), + (datetime.now() - StartTime).seconds % 60, + ) + if (datetime.now() - StartTime).seconds > 60 + else "{}s".format( + (datetime.now() - StartTime).seconds + ) + ), + ) + ) + + # print('\b') + + +# ----------------------------------------------------------------------------------------------------------------------------------- +def download( + Satellite, + Product, + DateTimeIni=None, + DateTimeFin=None, + domain=None, + channel=None, + rename_fmt=False, + path_out="", + retries=10, + backoff=10, + size_format="Decimal", + show_download_progress=True, + overwrite_file=False, +): + """ Download data of GOES-16, GOES-17 and GOES-18 from Amazon server. This function is based on the code of @@ -210,7 +274,7 @@ def download(Satellite, Product, DateTimeIni=None, DateTimeFin=None, domain=None size_format: str, optional, default 'Decimal' It defines how is print the size of file. Options are: - 'Decimal' : divide file size (in bytes) by (1000*1000) + 'Decimal' : divide file size (in bytes) by (1000*1000) 'Binary' : divide file size (in bytes) by (1024*1024) show_download_progress : boolean, optional, default True @@ -228,150 +292,188 @@ def download(Satellite, Product, DateTimeIni=None, DateTimeFin=None, domain=None Download_files : list List with the downloaded files (path+filename). - ''' + """ # ---------- Satellite ------------------- try: - assert Satellite == 'goes16' or Satellite == 'goes17' or Satellite == 'goes18' + assert Satellite == "goes16" or Satellite == "goes17" or Satellite == "goes18" except AssertionError: - print('\nSatellite should be goes16, goes17 or goes18\n') + print("\nSatellite should be goes16, goes17 or goes18\n") return else: - if Satellite == 'goes16': - Sat = 'G16' - elif Satellite == 'goes17': - Sat = 'G17' - elif Satellite == 'goes18': - Sat = 'G18' + if Satellite == "goes16": + pass + elif Satellite == "goes17": + pass + elif Satellite == "goes18": + pass # ---------- Product and Domain ------------------- - if Product[-1] == 'M': + if Product[-1] == "M": try: - assert domain == 'M1' or domain == 'M2' + assert domain == "M1" or domain == "M2" except AssertionError: - print("\nProduct domain is mesoscale so you need define domain='M1' or domain='M2'\n") + print( + "\nProduct domain is mesoscale so you need define domain='M1' or domain='M2'\n" + ) return else: - if domain == 'M1': - Product2 = Product+'1' - elif domain == 'M2': - Product2 = Product+'2' + if domain == "M1": + Product2 = Product + "1" + elif domain == "M2": + Product2 = Product + "2" else: Product2 = Product # ---------- DateTimeIni ------------------- try: - assert DateTimeIni != None + assert DateTimeIni is not None except AssertionError: - print('\nYou must define initial DateTimeIni\n') + print("\nYou must define initial DateTimeIni\n") return else: - DateTimeIni = datetime.strptime(DateTimeIni, '%Y%m%d-%H%M%S') + DateTimeIni = datetime.strptime(DateTimeIni, "%Y%m%d-%H%M%S") # ---------- DateTimeFin ------------------- - if DateTimeFin == None : + if DateTimeFin is None: DateTimeFin = DateTimeIni else: - DateTimeFin = datetime.strptime(DateTimeFin, '%Y%m%d-%H%M%S') + DateTimeFin = datetime.strptime(DateTimeFin, "%Y%m%d-%H%M%S") # ---------- channel ------------------- - if Product[:-1] in ['ABI-L1b-Rad','ABI-L2-CMIP']: - + if Product[:-1] in ["ABI-L1b-Rad", "ABI-L2-CMIP"]: try: - assert channel != None + assert channel is not None except AssertionError: - print('\nYou must define channel or channels\n') + print("\nYou must define channel or channels\n") return else: - try: - assert isinstance(channel, list) == True + assert isinstance(channel, list) except AssertionError: - print('\nChannel must be a list\n') + print("\nChannel must be a list\n") return else: ChannelList = [] for item in channel: - try: - assert isinstance(item, str) == True + assert isinstance(item, str) except AssertionError: - print('\nEach elements of channel must have string format\n') + print("\nEach elements of channel must have string format\n") return else: - try: assert len(item) == 2 or len(item) == 5 except AssertionError: - print('\nElement of channel must be string with two or five characters\n') + print( + "\nElement of channel must be string with two or five characters\n" + ) return else: - if len(item) == 2 : + if len(item) == 2: ChannelList.append(item) - elif len(item) == 5 : - ChIni, ChEnd = item.split('-') - for Chn in range(int(ChIni),int(ChEnd)+1): - ChannelList.append('{:02d}'.format(Chn)) + elif len(item) == 5: + ChIni, ChEnd = item.split("-") + for Chn in range(int(ChIni), int(ChEnd) + 1): + ChannelList.append("{:02d}".format(Chn)) - #if download_info == 'minimal' or download_info == 'full': + # if download_info == 'minimal' or download_info == 'full': # print('channel list: {}'.format(ChannelList)) - - #""" + # """ Downloaded_files = [] - if show_download_progress == True: - print('Files:') + if show_download_progress: + print("Files:") # ---------- Loop ------------------- DateTimeIniLoop = DateTimeIni.replace(minute=0) - DateTimeFinLoop = DateTimeFin.replace(minute=0)+timedelta(minutes=60) - while DateTimeIniLoop < DateTimeFinLoop : + DateTimeFinLoop = DateTimeFin.replace(minute=0) + timedelta(minutes=60) + while DateTimeIniLoop < DateTimeFinLoop: + DateTimeFolder = DateTimeIniLoop.strftime("%Y/%j/%H/") - DateTimeFolder = DateTimeIniLoop.strftime('%Y/%j/%H/') - - server = 's3://noaa-'+Satellite+'/'+Product+'/' + server = "s3://noaa-" + Satellite + "/" + Product + "/" fs = s3fs.S3FileSystem(anon=True) - ListFiles = np.array(fs.ls(server+DateTimeFolder)) + ListFiles = np.array(fs.ls(server + DateTimeFolder)) for line in ListFiles: - if Product[:-1] in ['ABI-L1b-Rad','ABI-L2-CMIP']: - NameFile = line.split('/')[-1] - ChannelFile = NameFile.split('_')[1][-2:] - DateTimeFile = datetime.strptime(NameFile[NameFile.find('_s')+2:NameFile.find('_e')-1], '%Y%j%H%M%S') - - if Product2 in NameFile and ChannelFile in ChannelList and DateTimeIni <= DateTimeFile <= DateTimeFin: - - if rename_fmt == False: + if Product[:-1] in ["ABI-L1b-Rad", "ABI-L2-CMIP"]: + NameFile = line.split("/")[-1] + ChannelFile = NameFile.split("_")[1][-2:] + DateTimeFile = datetime.strptime( + NameFile[NameFile.find("_s") + 2 : NameFile.find("_e") - 1], + "%Y%j%H%M%S", + ) + + if ( + Product2 in NameFile + and ChannelFile in ChannelList + and DateTimeIni <= DateTimeFile <= DateTimeFin + ): + if not rename_fmt: NameOut = NameFile else: - NameOut = NameFile[:NameFile.find('_s')+2] + DateTimeFile.strftime(rename_fmt) + '.nc' - - #print(ChannelFile, DateTimeFile, NameOut) - download_file('https://noaa-'+Satellite+'.s3.amazonaws.com'+line[len('noaa-'+Satellite):], NameOut, path_out, retries=retries, backoff=backoff, size_format=size_format, show_download_progress=show_download_progress, overwrite_file=overwrite_file) - Downloaded_files.append(path_out+NameOut) + NameOut = ( + NameFile[: NameFile.find("_s") + 2] + + DateTimeFile.strftime(rename_fmt) + + ".nc" + ) + + # print(ChannelFile, DateTimeFile, NameOut) + download_file( + "https://noaa-" + + Satellite + + ".s3.amazonaws.com" + + line[len("noaa-" + Satellite) :], + NameOut, + path_out, + retries=retries, + backoff=backoff, + size_format=size_format, + show_download_progress=show_download_progress, + overwrite_file=overwrite_file, + ) + Downloaded_files.append(path_out + NameOut) else: - NameFile = line.split('/')[-1] - DateTimeFile = datetime.strptime(NameFile[NameFile.find('_s')+2:NameFile.find('_e')-1], '%Y%j%H%M%S') - - if Product2 in NameFile and DateTimeIni <= DateTimeFile <= DateTimeFin: - - if rename_fmt == False: + NameFile = line.split("/")[-1] + DateTimeFile = datetime.strptime( + NameFile[NameFile.find("_s") + 2 : NameFile.find("_e") - 1], + "%Y%j%H%M%S", + ) + + if Product2 in NameFile and DateTimeIni <= DateTimeFile <= DateTimeFin: + if not rename_fmt: NameOut = NameFile else: - NameOut = NameFile[:NameFile.find('_s')+2] + DateTimeFile.strftime(rename_fmt) + '.nc' - - #print(DateTimeFile, NameOut) - download_file('https://noaa-'+Satellite+'.s3.amazonaws.com'+line[len('noaa-'+Satellite):], NameOut, path_out, retries=retries, backoff=backoff, size_format=size_format, show_download_progress=show_download_progress, overwrite_file=overwrite_file) - Downloaded_files.append(path_out+NameOut) + NameOut = ( + NameFile[: NameFile.find("_s") + 2] + + DateTimeFile.strftime(rename_fmt) + + ".nc" + ) + + # print(DateTimeFile, NameOut) + download_file( + "https://noaa-" + + Satellite + + ".s3.amazonaws.com" + + line[len("noaa-" + Satellite) :], + NameOut, + path_out, + retries=retries, + backoff=backoff, + size_format=size_format, + show_download_progress=show_download_progress, + overwrite_file=overwrite_file, + ) + Downloaded_files.append(path_out + NameOut) DateTimeIniLoop = DateTimeIniLoop + timedelta(minutes=60) Downloaded_files.sort() - return Downloaded_files; + return Downloaded_files -#----------------------------------------------------------------------------------------------------------------------------------- +# ----------------------------------------------------------------------------------------------------------------------------------- diff --git a/src/goes16/features.py b/src/goes16/features.py new file mode 100644 index 00000000..47fa4a9d --- /dev/null +++ b/src/goes16/features.py @@ -0,0 +1,280 @@ +# GOES-16 Feature Extraction (corrigido) +# Este módulo contém funções para extrair várias features dos dados do satélite GOES-16. + +import os +from datetime import datetime, timedelta + +import netCDF4 as nc +import numpy as np +from scipy.ndimage import generic_filter + + +# PN: Profundidade da Nuvem +def profundidade_nuvens(pasta_entrada_canal9, pasta_entrada_canal13, pasta_saida): + arquivos_canal9 = sorted(os.listdir(pasta_entrada_canal9)) + arquivos_canal13 = sorted(os.listdir(pasta_entrada_canal13)) + prefix_canal9 = arquivos_canal9[0].split("_", 1)[0] + prefix_canal13 = arquivos_canal13[0].split("_", 1)[0] + prefix_feature = "PN" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos_canal9 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + arq_entrada1 = os.path.join( + pasta_entrada_canal9, f"{prefix_canal9}_{timestamp}" + ) + arq_entrada2 = os.path.join( + pasta_entrada_canal13, f"{prefix_canal13}_{timestamp}" + ) + arq_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + if not os.path.exists(arq_saida) and os.path.exists(arq_entrada2): + with ( + nc.Dataset(arq_entrada1, "r") as nc1, + nc.Dataset(arq_entrada2, "r") as nc2, + nc.Dataset(arq_saida, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in nc1.variables: + if nome_var in nc2.variables: + dados = nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = "PN: profundidade da nuvem (C09 - C13)" + out.description = "Diferença entre canais para profundidade da nuvem" + + +# GTN: Glaciação do Topo da Nuvem +def glaciacao_topo_nuvem( + pasta_entrada_canal11, pasta_entrada_canal14, pasta_entrada_canal15, pasta_saida +): + arquivos_c11 = sorted(os.listdir(pasta_entrada_canal11)) + arquivos_c14 = sorted(os.listdir(pasta_entrada_canal14)) + arquivos_c15 = sorted(os.listdir(pasta_entrada_canal15)) + pfx11 = arquivos_c11[0].split("_", 1)[0] + pfx14 = arquivos_c14[0].split("_", 1)[0] + pfx15 = arquivos_c15[0].split("_", 1)[0] + pfx_feat = "GTN" + timestamps = [f.split("_", 1)[1] for f in arquivos_c11 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in timestamps: + arq11 = os.path.join(pasta_entrada_canal11, f"{pfx11}_{timestamp}") + arq14 = os.path.join(pasta_entrada_canal14, f"{pfx14}_{timestamp}") + arq15 = os.path.join(pasta_entrada_canal15, f"{pfx15}_{timestamp}") + saida = os.path.join(pasta_saida, f"{pfx_feat}_{timestamp}") + if ( + not os.path.exists(saida) + and os.path.exists(arq14) + and os.path.exists(arq15) + ): + with ( + nc.Dataset(arq11, "r") as nc1, + nc.Dataset(arq14, "r") as nc2, + nc.Dataset(arq15, "r") as nc3, + nc.Dataset(saida, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in nc1.variables: + if nome_var in nc2.variables and nome_var in nc3.variables: + dados = ( + nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + ) - (nc2.variables[nome_var][:] - nc3.variables[nome_var][:]) + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = ( + "GTN: glaciação topo da nuvem (tri-espectral)" + ) + out.description = "Glaciação topo da nuvem" + + +# FA: Derivada Temporal do Fluxo Ascendente +def derivada_temporal_fluxo_ascendente( + pasta_entrada_canal, pasta_saida, intervalo_temporal=10 +): + arquivos = sorted(os.listdir(pasta_entrada_canal)) + pfx = arquivos[0].split("_", 1)[0] + timestamps = [f.split("_", 1)[1] for f in arquivos if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for ts in timestamps: + atual = os.path.join(pasta_entrada_canal, f"{pfx}_{ts}") + saida = os.path.join(pasta_saida, f"FA_{ts}") + if not os.path.exists(saida): + with nc.Dataset(atual, "r") as src, nc.Dataset(saida, "w") as dst: + for nome_dim, dim in src.dimensions.items(): + dst.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in src.variables: + partes = nome_var.split("_")[1:] + try: + year, mes, dia, hora, minuto = map(int, partes) + hora_adiante = datetime( + year, mes, dia, hora, minuto + ) + timedelta(minutes=intervalo_temporal) + nome_adiante = f"CMI_{hora_adiante.year:04}_{hora_adiante.month:02}_{hora_adiante.day:02}_{hora_adiante.hour:02}_{hora_adiante.minute:02}" + if nome_adiante in src.variables: + delta_t = intervalo_temporal + derivada = ( + src.variables[nome_adiante][:] + - src.variables[nome_var][:] + ) / delta_t + var_out = dst.createVariable( + nome_var, "f4", src.variables[nome_var].dimensions + ) + var_out[:] = derivada + var_out.description = f"Derivada temporal de {nome_var}" + except ValueError: + continue + dst.description = "Derivada temporal do fluxo ascendente" + + +# WV_grad: Gradiente de Vapor d'Água +def gradiente_vapor_agua(pasta_c09, pasta_c08, pasta_saida): + arquivos_c09 = sorted(os.listdir(pasta_c09)) + arquivos_c08 = sorted(os.listdir(pasta_c08)) + prefix_c09 = arquivos_c09[0].split("_", 1)[0] + prefix_c08 = arquivos_c08[0].split("_", 1)[0] + prefix_feature = "WV_grad" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos_c09 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_c09 = os.path.join(pasta_c09, f"{prefix_c09}_{timestamp}") + path_c08 = os.path.join(pasta_c08, f"{prefix_c08}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_saida) and os.path.exists(path_c08): + with ( + nc.Dataset(path_c09, "r") as nc1, + nc.Dataset(path_c08, "r") as nc2, + nc.Dataset(path_saida, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in nc1.variables: + if nome_var in nc2.variables: + dados = nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = "Diferença C09 - C08 (vapor d’água)" + out.description = "Gradiente espectral do vapor d’água" + + +# LI_proxy: Proxy de Estabilidade Atmosférica +def proxy_estabilidade(pasta_c14, pasta_c13, pasta_saida): + arquivos_c14 = sorted(os.listdir(pasta_c14)) + arquivos_c13 = sorted(os.listdir(pasta_c13)) + prefix_c14 = arquivos_c14[0].split("_", 1)[0] + prefix_c13 = arquivos_c13[0].split("_", 1)[0] + prefix_feature = "LI_proxy" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos_c14 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_c14 = os.path.join(pasta_c14, f"{prefix_c14}_{timestamp}") + path_c13 = os.path.join(pasta_c13, f"{prefix_c13}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_saida) and os.path.exists(path_c13): + with ( + nc.Dataset(path_c14, "r") as nc1, + nc.Dataset(path_c13, "r") as nc2, + nc.Dataset(path_saida, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in nc1.variables: + if nome_var in nc2.variables: + dados = nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = "C14 - C13 como proxy de estabilidade" + out.description = ( + "Proxy de estabilidade atmosférica com canais C14 e C13" + ) + + +# TOCT: Temperatura do Topo da Nuvem +def temperatura_topo_nuvem(pasta_c13, pasta_saida): + arquivos = sorted(os.listdir(pasta_c13)) + prefix = arquivos[0].split("_", 1)[0] + prefix_feature = "TOCT" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_entrada = os.path.join(pasta_c13, f"{prefix}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_saida): + with ( + nc.Dataset(path_entrada, "r") as src, + nc.Dataset(path_saida, "w") as dst, + ): + for nome_dim, dim in src.dimensions.items(): + dst.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in src.variables: + dados = src.variables[nome_var][:] + var_out = dst.createVariable( + nome_var, "f4", src.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = ( + "Temperatura do topo da nuvem (TOCT) diretamente do canal 13" + ) + dst.description = "TOCT a partir do canal C13" + + +# PNstd: Textura Local da Profundidade da Nuvem +def textura_local_profundidade(pasta_pn, pasta_saida, tamanho_janela=3): + arquivos = sorted(os.listdir(pasta_pn)) + prefix = arquivos[0].split("_", 1)[0] + prefix_feature = "PNstd" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_entrada = os.path.join(pasta_pn, f"{prefix}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_saida): + with ( + nc.Dataset(path_entrada, "r") as src, + nc.Dataset(path_saida, "w") as dst, + ): + for nome_dim, dim in src.dimensions.items(): + dst.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in src.variables: + dados = src.variables[nome_var][:] + std_local = generic_filter( + dados, np.std, size=tamanho_janela, mode="nearest" + ) + var_out = dst.createVariable( + nome_var, "f4", src.variables[nome_var].dimensions + ) + var_out[:] = std_local + var_out.description = "Desvio padrão espacial local (textura) da profundidade da nuvem" + dst.description = "Textura espacial (desvio padrão local) da feature PN" diff --git a/src/goes16/features/__init__.py b/src/goes16/features/__init__.py new file mode 100644 index 00000000..c4a2b9f4 --- /dev/null +++ b/src/goes16/features/__init__.py @@ -0,0 +1,18 @@ +# src/goes16/features/__init__.py +from .fa import derivada_temporal_fluxo_ascendente +from .gtn import glaciacao_topo_nuvem +from .li_proxy import proxy_estabilidade +from .pn import profundidade_nuvens +from .pn_std import textura_local_profundidade +from .toct import temperatura_topo_nuvem +from .wv_grad import gradiente_vapor_agua + +__all__ = [ + "derivada_temporal_fluxo_ascendente", + "glaciacao_topo_nuvem", + "proxy_estabilidade", + "profundidade_nuvens", + "textura_local_profundidade", + "temperatura_topo_nuvem", + "gradiente_vapor_agua", +] diff --git a/src/goes16/features/fa.py b/src/goes16/features/fa.py new file mode 100644 index 00000000..3eccd477 --- /dev/null +++ b/src/goes16/features/fa.py @@ -0,0 +1,82 @@ +import logging +import os +from datetime import datetime, timedelta + +import netCDF4 as nc + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("fa.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def derivada_temporal_fluxo_ascendente( + pasta_entrada_canal: str, pasta_saida: str, intervalo_temporal: int = 10 +): + """ + Calcula a derivada temporal do fluxo ascendente com base no canal fornecido. + + Args: + pasta_entrada_canal (str): Caminho para os arquivos do canal. + pasta_saida (str): Caminho de saída para os arquivos FA gerados. + intervalo_temporal (int): Intervalo em minutos entre frames (default: 10). + """ + arquivos = sorted(os.listdir(pasta_entrada_canal)) + if not arquivos: + logger.warning(f"Nenhum arquivo encontrado em {pasta_entrada_canal}") + return + + pfx = arquivos[0].split("_", 1)[0] + timestamps = [f.split("_", 1)[1] for f in arquivos if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for ts in timestamps: + arq_atual = os.path.join(pasta_entrada_canal, f"{pfx}_{ts}") + arq_saida = os.path.join(pasta_saida, f"FA_{ts}") + + if not os.path.exists(arq_atual): + logger.warning(f"Arquivo ausente: {arq_atual}") + continue + if os.path.exists(arq_saida): + continue + + try: + with nc.Dataset(arq_atual, "r") as src, nc.Dataset(arq_saida, "w") as dst: + for nome_dim, dim in src.dimensions.items(): + dst.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + vars_salvas = 0 + for nome_var in src.variables: + partes = nome_var.split("_")[1:] + try: + year, mes, dia, hora, minuto = map(int, partes) + hora_adiante = datetime( + year, mes, dia, hora, minuto + ) + timedelta(minutes=intervalo_temporal) + nome_adiante = f"CMI_{hora_adiante.year:04}_{hora_adiante.month:02}_{hora_adiante.day:02}_{hora_adiante.hour:02}_{hora_adiante.minute:02}" + if nome_adiante in src.variables: + delta_t = intervalo_temporal + derivada = ( + src.variables[nome_adiante][:] + - src.variables[nome_var][:] + ) / delta_t + var_out = dst.createVariable( + nome_var, "f4", src.variables[nome_var].dimensions + ) + var_out[:] = derivada + var_out.description = f"Derivada temporal de {nome_var}" + vars_salvas += 1 + except ValueError: + continue + if vars_salvas == 0: + logger.warning( + f"Nenhuma variável derivada para {ts}, possível falha de naming" + ) + dst.description = "Derivada temporal do fluxo ascendente" + except Exception: + logger.exception(f"Erro ao processar {ts}") diff --git a/src/goes16/features/gtn.py b/src/goes16/features/gtn.py new file mode 100644 index 00000000..18c5ee1b --- /dev/null +++ b/src/goes16/features/gtn.py @@ -0,0 +1,89 @@ +import logging +import os + +import netCDF4 as nc + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("gtn.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def glaciacao_topo_nuvem( + pasta_c11: str, pasta_c14: str, pasta_c15: str, pasta_saida: str +): + """ + Calcula a glaciação do topo da nuvem como uma combinação tri-espectral (C11, C14, C15). + + Args: + pasta_c11 (str): Caminho para os arquivos do canal C11. + pasta_c14 (str): Caminho para os arquivos do canal C14. + pasta_c15 (str): Caminho para os arquivos do canal C15. + pasta_saida (str): Caminho de saída para os arquivos GTN gerados. + """ + arquivos_c11 = sorted(os.listdir(pasta_c11)) + arquivos_c14 = sorted(os.listdir(pasta_c14)) + arquivos_c15 = sorted(os.listdir(pasta_c15)) + + pfx11 = arquivos_c11[0].split("_", 1)[0] + pfx14 = arquivos_c14[0].split("_", 1)[0] + pfx15 = arquivos_c15[0].split("_", 1)[0] + pfx_feat = "GTN" + + timestamps = [f.split("_", 1)[1] for f in arquivos_c11 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for ts in timestamps: + arq11 = os.path.join(pasta_c11, f"{pfx11}_{ts}") + arq14 = os.path.join(pasta_c14, f"{pfx14}_{ts}") + arq15 = os.path.join(pasta_c15, f"{pfx15}_{ts}") + arq_out = os.path.join(pasta_saida, f"{pfx_feat}_{ts}") + + if not os.path.exists(arq11): + logger.warning(f"Arquivo ausente: {arq11}") + continue + if not os.path.exists(arq14): + logger.warning(f"Arquivo ausente: {arq14}") + continue + if not os.path.exists(arq15): + logger.warning(f"Arquivo ausente: {arq15}") + continue + if os.path.exists(arq_out): + continue + + try: + with ( + nc.Dataset(arq11, "r") as nc1, + nc.Dataset(arq14, "r") as nc2, + nc.Dataset(arq15, "r") as nc3, + nc.Dataset(arq_out, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + vars_salvas = 0 + for nome_var in nc1.variables: + if nome_var in nc2.variables and nome_var in nc3.variables: + dados = ( + nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + ) - (nc2.variables[nome_var][:] - nc3.variables[nome_var][:]) + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = ( + "GTN: glaciação topo da nuvem (tri-espectral)" + ) + vars_salvas += 1 + if vars_salvas == 0: + logger.warning( + f"Nenhuma variável processada para {ts}, possível incompatibilidade" + ) + out.description = "Glaciação topo da nuvem (GTN)" + except Exception: + logger.exception(f"Erro ao processar {ts}") diff --git a/src/goes16/features/li_proxy.py b/src/goes16/features/li_proxy.py new file mode 100644 index 00000000..3506527e --- /dev/null +++ b/src/goes16/features/li_proxy.py @@ -0,0 +1,73 @@ +import logging +import os + +import netCDF4 as nc + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("li_proxy.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def proxy_estabilidade(pasta_c14: str, pasta_c13: str, pasta_saida: str): + """ + Computes a stability proxy as the difference between channels C14 and C13. + + Args: + pasta_c14 (str): Path to input files for channel C14. + pasta_c13 (str): Path to input files for channel C13. + pasta_saida (str): Path to output directory for LI_proxy feature. + """ + arquivos_c14 = sorted(os.listdir(pasta_c14)) + arquivos_c13 = sorted(os.listdir(pasta_c13)) + prefix_c14 = arquivos_c14[0].split("_", 1)[0] + prefix_c13 = arquivos_c13[0].split("_", 1)[0] + prefix_feature = "LI_proxy" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos_c14 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_c14 = os.path.join(pasta_c14, f"{prefix_c14}_{timestamp}") + path_c13 = os.path.join(pasta_c13, f"{prefix_c13}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_c14): + logger.warning(f"Missing file: {path_c14}") + continue + if not os.path.exists(path_c13): + logger.warning(f"Missing file: {path_c13}") + continue + if os.path.exists(path_saida): + continue + + try: + with ( + nc.Dataset(path_c14, "r") as nc1, + nc.Dataset(path_c13, "r") as nc2, + nc.Dataset(path_saida, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + vars_saved = 0 + for nome_var in nc1.variables: + if nome_var in nc2.variables: + dados = nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = "C14 - C13 as a proxy for stability" + vars_saved += 1 + if vars_saved == 0: + logger.warning( + f"No variables saved for {timestamp}, possible mismatch." + ) + out.description = "Atmospheric stability proxy from C14 and C13" + except Exception: + logger.exception(f"Error processing {timestamp}") diff --git a/src/goes16/features/pn.py b/src/goes16/features/pn.py new file mode 100644 index 00000000..cd75f7a4 --- /dev/null +++ b/src/goes16/features/pn.py @@ -0,0 +1,77 @@ +import logging +import os + +import netCDF4 as nc + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("pn.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def profundidade_nuvens( + pasta_entrada_canal9: str, pasta_entrada_canal13: str, pasta_saida: str +): + """ + Calcula a profundidade da nuvem como a diferença entre os canais C09 e C13. + + Args: + pasta_entrada_canal9 (str): Caminho para os arquivos do canal C09 (por ano). + pasta_entrada_canal13 (str): Caminho para os arquivos do canal C13 (por ano). + pasta_saida (str): Caminho de saída para os arquivos PN gerados. + """ + arquivos_c9 = sorted(os.listdir(pasta_entrada_canal9)) + arquivos_c13 = sorted(os.listdir(pasta_entrada_canal13)) + + prefix_c9 = arquivos_c9[0].split("_", 1)[0] + prefix_c13 = arquivos_c13[0].split("_", 1)[0] + prefix_feat = "PN" + + timestamps = [f.split("_", 1)[1] for f in arquivos_c9 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for ts in timestamps: + arq_c9 = os.path.join(pasta_entrada_canal9, f"{prefix_c9}_{ts}") + arq_c13 = os.path.join(pasta_entrada_canal13, f"{prefix_c13}_{ts}") + arq_out = os.path.join(pasta_saida, f"{prefix_feat}_{ts}") + + if not os.path.exists(arq_c9): + logger.warning(f"Arquivo ausente: {arq_c9}") + continue + if not os.path.exists(arq_c13): + logger.warning(f"Arquivo ausente: {arq_c13}") + continue + if os.path.exists(arq_out): + continue + + try: + with ( + nc.Dataset(arq_c9, "r") as nc1, + nc.Dataset(arq_c13, "r") as nc2, + nc.Dataset(arq_out, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + vars_salvas = 0 + for nome_var in nc1.variables: + if nome_var in nc2.variables: + dados = nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = "PN: profundidade da nuvem (C09 - C13)" + vars_salvas += 1 + if vars_salvas == 0: + logger.warning( + f"Nenhuma variável processada para {ts}, possível incompatibilidade" + ) + out.description = "Diferença entre canais para profundidade da nuvem" + except Exception: + logger.exception(f"Erro ao processar {ts}") diff --git a/src/goes16/features/pn_std.py b/src/goes16/features/pn_std.py new file mode 100644 index 00000000..409c85ce --- /dev/null +++ b/src/goes16/features/pn_std.py @@ -0,0 +1,76 @@ +import logging +import os + +import netCDF4 as nc +import numpy as np +from scipy.ndimage import generic_filter + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("pn_std.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def textura_local_profundidade( + pasta_pn: str, pasta_saida: str, tamanho_janela: int = 3 +): + """ + Calcula o desvio padrão local (textura) da profundidade da nuvem (PN). + + Args: + pasta_pn (str): Caminho para os arquivos da feature PN. + pasta_saida (str): Caminho de saída para os arquivos PNstd gerados. + tamanho_janela (int): Tamanho da janela para o filtro de desvio padrão. + """ + arquivos = sorted(os.listdir(pasta_pn)) + if not arquivos: + logger.warning(f"Nenhum arquivo encontrado em {pasta_pn}") + return + + prefix = arquivos[0].split("_", 1)[0] + prefix_feature = "PNstd" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_entrada = os.path.join(pasta_pn, f"{prefix}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_entrada): + logger.warning(f"Arquivo ausente: {path_entrada}") + continue + if os.path.exists(path_saida): + continue + + try: + with ( + nc.Dataset(path_entrada, "r") as src, + nc.Dataset(path_saida, "w") as dst, + ): + for nome_dim, dim in src.dimensions.items(): + dst.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + vars_salvas = 0 + for nome_var in src.variables: + dados = src.variables[nome_var][:] + std_local = generic_filter( + dados, np.std, size=tamanho_janela, mode="nearest" + ) + var_out = dst.createVariable( + nome_var, "f4", src.variables[nome_var].dimensions + ) + var_out[:] = std_local + var_out.description = "Desvio padrão espacial local (textura) da profundidade da nuvem" + vars_salvas += 1 + if vars_salvas == 0: + logger.warning( + f"Nenhuma variável de textura gerada para {timestamp}" + ) + dst.description = "Textura espacial (desvio padrão local) da feature PN" + except Exception: + logger.exception(f"Erro ao processar {timestamp}") diff --git a/src/goes16/features/toct.py b/src/goes16/features/toct.py new file mode 100644 index 00000000..25297516 --- /dev/null +++ b/src/goes16/features/toct.py @@ -0,0 +1,42 @@ +import os + +import netCDF4 as nc + + +def temperatura_topo_nuvem(pasta_c13: str, pasta_saida: str): + """ + Extrai a temperatura do topo da nuvem diretamente do canal C13. + + Args: + pasta_c13 (str): Caminho para os arquivos do canal C13. + pasta_saida (str): Caminho de saída para os arquivos TOCT gerados. + """ + arquivos = sorted(os.listdir(pasta_c13)) + prefix = arquivos[0].split("_", 1)[0] + prefix_feature = "TOCT" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_entrada = os.path.join(pasta_c13, f"{prefix}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_saida): + with ( + nc.Dataset(path_entrada, "r") as src, + nc.Dataset(path_saida, "w") as dst, + ): + for nome_dim, dim in src.dimensions.items(): + dst.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + for nome_var in src.variables: + dados = src.variables[nome_var][:] + var_out = dst.createVariable( + nome_var, "f4", src.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = ( + "Temperatura do topo da nuvem (TOCT) diretamente do canal 13" + ) + dst.description = "TOCT a partir do canal C13" diff --git a/src/goes16/features/tp.py b/src/goes16/features/tp.py new file mode 100644 index 00000000..96cec56c --- /dev/null +++ b/src/goes16/features/tp.py @@ -0,0 +1,60 @@ +import logging +import os + +import netCDF4 as nc + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("tp.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def tamanho_particulas(pasta_entrada_canal7: str, pasta_saida: str): + """ + Mapeia o tamanho das partículas (TP) diretamente a partir dos arquivos do canal C07. + + Args: + pasta_entrada_canal7 (str): Caminho para os arquivos do canal C07 (por ano). + pasta_saida (str): Caminho de saída para os arquivos TP gerados. + """ + arquivos_c7 = sorted(os.listdir(pasta_entrada_canal7)) + prefix_c7 = arquivos_c7[0].split("_", 1)[0] + prefix_feat = "TP" + + timestamps = [f.split("_", 1)[1] for f in arquivos_c7 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for ts in timestamps: + arq_c7 = os.path.join(pasta_entrada_canal7, f"{prefix_c7}_{ts}") + arq_out = os.path.join(pasta_saida, f"{prefix_feat}_{ts}") + + if not os.path.exists(arq_c7): + logger.warning(f"Arquivo ausente: {arq_c7}") + continue + if os.path.exists(arq_out): + continue + + try: + with nc.Dataset(arq_c7, "r") as nc_in, nc.Dataset(arq_out, "w") as out: + for nome_dim, dim in nc_in.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + + for nome_var in nc_in.variables: + var_in = nc_in.variables[nome_var] + var_out = out.createVariable( + nome_var, var_in.datatype, var_in.dimensions + ) + var_out.setncatts( + {k: var_in.getncattr(k) for k in var_in.ncattrs()} + ) + var_out[:] = var_in[:] + + out.description = "TP: tamanho das partículas a partir do canal C07" + except Exception: + logger.exception(f"Erro ao processar {ts}") diff --git a/src/goes16/features/wv_grad.py b/src/goes16/features/wv_grad.py new file mode 100644 index 00000000..19b4a975 --- /dev/null +++ b/src/goes16/features/wv_grad.py @@ -0,0 +1,73 @@ +import logging +import os + +import netCDF4 as nc + +logger = logging.getLogger(__name__) +logger.setLevel(logging.INFO) + +if not logger.handlers: + file_handler = logging.FileHandler("wv_grad.log") + formatter = logging.Formatter("%(asctime)s [%(levelname)s] %(message)s") + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + +def gradiente_vapor_agua(pasta_c09: str, pasta_c08: str, pasta_saida: str): + """ + Calcula o gradiente espectral de vapor d'água como a diferença entre os canais C09 e C08. + + Args: + pasta_c09 (str): Caminho para os arquivos do canal C09. + pasta_c08 (str): Caminho para os arquivos do canal C08. + pasta_saida (str): Caminho de saída para os arquivos WV_grad gerados. + """ + arquivos_c09 = sorted(os.listdir(pasta_c09)) + arquivos_c08 = sorted(os.listdir(pasta_c08)) + prefix_c09 = arquivos_c09[0].split("_", 1)[0] + prefix_c08 = arquivos_c08[0].split("_", 1)[0] + prefix_feature = "WV_grad" + arquivos_timestamp = [f.split("_", 1)[1] for f in arquivos_c09 if "_" in f] + os.makedirs(pasta_saida, exist_ok=True) + + for timestamp in arquivos_timestamp: + path_c09 = os.path.join(pasta_c09, f"{prefix_c09}_{timestamp}") + path_c08 = os.path.join(pasta_c08, f"{prefix_c08}_{timestamp}") + path_saida = os.path.join(pasta_saida, f"{prefix_feature}_{timestamp}") + + if not os.path.exists(path_c09): + logger.warning(f"Arquivo ausente: {path_c09}") + continue + if not os.path.exists(path_c08): + logger.warning(f"Arquivo ausente: {path_c08}") + continue + if os.path.exists(path_saida): + continue + + try: + with ( + nc.Dataset(path_c09, "r") as nc1, + nc.Dataset(path_c08, "r") as nc2, + nc.Dataset(path_saida, "w") as out, + ): + for nome_dim, dim in nc1.dimensions.items(): + out.createDimension( + nome_dim, len(dim) if not dim.isunlimited() else None + ) + vars_salvas = 0 + for nome_var in nc1.variables: + if nome_var in nc2.variables: + dados = nc1.variables[nome_var][:] - nc2.variables[nome_var][:] + var_out = out.createVariable( + nome_var, "f4", nc1.variables[nome_var].dimensions + ) + var_out[:] = dados + var_out.description = "Diferença C09 - C08 (vapor d’água)" + vars_salvas += 1 + if vars_salvas == 0: + logger.warning( + f"Nenhuma variável processada para {timestamp}, possível incompatibilidade" + ) + out.description = "Gradiente espectral do vapor d’água" + except Exception: + logger.exception(f"Erro ao processar {timestamp}") diff --git a/src/goes16/goes16_create_animation_from_snapshots.py b/src/goes16/goes16_create_animation_from_snapshots.py new file mode 100644 index 00000000..9b50acea --- /dev/null +++ b/src/goes16/goes16_create_animation_from_snapshots.py @@ -0,0 +1,292 @@ +import argparse +import math +import os + +import cartopy.crs as ccrs +import matplotlib.pyplot as plt +import netCDF4 as nc +import numpy as np +from matplotlib.animation import FuncAnimation +from PIL import Image + +from config import globals + + +def create_animation(output_directory, output_file, global_min, global_max, fps=5): + """ + Generates an animation (MP4 file) from PNG images in the given directory, + with a single global scale and colorbar. + + Args: + image_directory (str): Directory containing the PNG images. + output_file (str): Path to save the MP4 animation. + fps (int): Frames per second for the animation. + """ + # Collect all image files in the directory + image_files = sorted( + [ + os.path.join(output_directory, file) + for file in os.listdir(output_directory) + if file.endswith(".png") + ] + ) + + if not image_files: + print("No PNG images found in the directory!") + return + + # Verify the order of images + print(f"Found {len(image_files)} images: {image_files}") + + # Load the first image to set up the figure + first_image = np.array(Image.open(image_files[0])) + fig, ax = plt.subplots() + img_plot = ax.imshow(first_image, cmap="viridis", vmin=global_min, vmax=global_max) + ax.axis("off") # Remove axes for better visualization + + # Add a single global colorbar + cbar = fig.colorbar(img_plot, ax=ax, label="Intensity") + cbar.ax.tick_params(labelsize=10) # Adjust colorbar tick size if necessary + + def update(frame): + """Update the image data for each frame.""" + image = np.array(Image.open(image_files[frame])) + img_plot.set_array(image) + return [img_plot] + + # Create the animation + anim = FuncAnimation( + fig, update, frames=len(image_files), interval=1000 / fps, blit=True + ) + + # Save the animation as an MP4 file + output_file = os.path.join(output_directory, output_file) + anim.save(output_file, fps=fps, extra_args=["-vcodec", "libx264"]) + print(f"Animation saved to {output_file}") + + +def create_snapshots(netcdf_file, output_directory, title_prefix=""): + """ + Plots all snapshots (numpy arrays) inside the provided netCDF file and saves the results as PNG images. + + Args: + netcdf_file (str): Path to the netCDF file containing several snapshots. + output_directory (str): Directory where the output image files will be saved. + """ + try: + # Open the netCDF file + with nc.Dataset(netcdf_file, "r") as dataset: + # print(f"Variables in the netCDF file: {list(dataset.variables.keys())}") + + global_min = float("inf") + global_max = float("-inf") + + # Iterate through all variables in the dataset + for variable_name in dataset.variables.keys(): + # Retrieve the data array for the variable + data = dataset.variables[variable_name][:] + + # Compute the global min and max values for scaling + global_min = min(global_min, data.min()) + global_max = max(global_max, data.max()) + + # Generate a sanitized output file name + sanitized_name = variable_name.replace(":", "_").replace(" ", "_") + output_image_file = os.path.join( + output_directory, f"{sanitized_name}.png" + ) + + # Plot the data array and save it + create_snapshot( + data, f"{title_prefix} {variable_name}", output_image_file + ) + print(f"Saved snapshot for {variable_name} to {output_image_file}") + + print(f"Global scale: min={global_min}, max={global_max}") + + return global_min, global_max + except Exception as e: + print(f"Error while processing netCDF file: {e}") + + +def latlon2xy(lat, lon): + # goes_imagery_projection:semi_major_axis + req = 6378137 # meters + # goes_imagery_projection:inverse_flattening + # goes_imagery_projection:semi_minor_axis + rpol = 6356752.31414 # meters + e = 0.0818191910435 + # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis + H = 42164160 # meters + # goes_imagery_projection: longitude_of_projection_origin + lambda0 = -1.308996939 + + # Convert to radians + latRad = lat * (math.pi / 180) + lonRad = lon * (math.pi / 180) + + # (1) geocentric latitude + Phi_c = math.atan(((rpol * rpol) / (req * req)) * math.tan(latRad)) + # (2) geocentric distance to the point on the ellipsoid + rc = rpol / (math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) + # (3) sx + sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0)) + # (4) sy + sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0) + # (5) + sz = rc * math.sin(Phi_c) + + # x,y + x = math.asin((-sy) / math.sqrt((sx * sx) + (sy * sy) + (sz * sz))) + y = math.atan(sz / sx) + + return x, y + + +# Function to convert lat / lon extent to GOES-16 extents +def convertExtent2GOESProjection(extent): + # GOES-16 viewing point (satellite position) height above the earth + GOES16_HEIGHT = 35786023.0 + # GOES-16 longitude position + + a, b = latlon2xy(extent[1], extent[0]) + c, d = latlon2xy(extent[3], extent[2]) + return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT) + + +def create_snapshot(data, title, output_image_file): + """ + Plots a data array with coastlines, borders, and gridlines, and saves it as an image. + + Args: + data_array (numpy.ndarray): The data array to plot. + title (str): Title of the plot. + output_image_file (str): Path to save the plot. + """ + # Define the projection for the plot + # projection = ccrs.PlateCarree() + + plt.figure(figsize=(10, 10)) + + # Use the Geostationary projection in cartopy + # ax = plt.axes(projection=ccrs.PlateCarree()) + ax = plt.axes( + projection=ccrs.Geostationary( + central_longitude=-75.0, satellite_height=35786023.0 + ) + ) + + img_extent = convertExtent2GOESProjection(globals.extent) + + # Create the plot + # fig, ax = plt.subplots(subplot_kw={'projection': projection}, figsize=(10, 8)) + _ = ax.imshow( + data, + origin="upper", + extent=img_extent, + cmap="viridis", + # transform=ccrs.PlateCarree(), + ) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=1) + # ax.add_feature(cfeature.BORDERS, edgecolor='black') + # gl = ax.gridlines(crs=ccrs.PlateCarree(), + # color='gray', + # alpha=1.0, + # linestyle='--', + # linewidth=0.5, + # xlocs=np.arange(-180, 180, 5), + # ylocs=np.arange(-90, 90, 5), + # draw_labels=True) + # gl.top_labels = False + # gl.right_labels = False + + # Add title and colorbar + plt.title(title, fontsize=14) + # cbar = fig.colorbar(img, ax=ax, orientation='horizontal', pad=0.05) + # cbar.set_label('Intensity') + + # Save the plot + plt.savefig(output_image_file, bbox_inches="tight") + plt.close() + + +# def create_snapshot(data_array, title, output_image_file): +# """ +# A placeholder function to plot a data array and save it as an image. +# Replace this with your actual plotting logic. + +# Args: +# data_array (numpy.ndarray): The data array to plot. +# title (str): Title of the plot. +# output_image_file (str): Path to save the plot. +# """ +# import matplotlib.pyplot as plt + +# plt.figure() +# plt.imshow(data_array, cmap='viridis') +# plt.title(title) +# # plt.colorbar(label='Intensity') +# plt.savefig(output_image_file) +# plt.close() + +######################################################################## +### MAIN +######################################################################## + +if __name__ == "__main__": + """ + python src/goes16_create_animation_from_snapshots.py --netcdf_file ./data/goes16/CMI/C07/2023/C07_2023_10_31.nc --output_dir ./C07_2023_10_31 --title_prefix Channel 07 + """ + parser = argparse.ArgumentParser(description="Plot data from a NetCDF file.") + parser.add_argument( + "--netcdf_file", + type=str, + help="Path to the NetCDF file containing the snapshots.", + ) + parser.add_argument( + "--title_prefix", + default="", + type=str, + help="Path of directory to save the resulting PNG images and animation.", + ) + parser.add_argument( + "--output_dir", + type=str, + help="Path of directory to save the resulting PNG images and animation.", + ) + parser.add_argument( + "--keep_snapshots", + action="store_true", + help="Keep the individual PNG snapshots after creating the animation.", + ) + parser.add_argument( + "--min_max", + nargs=2, + metavar=("min_value", "max_value"), + help="Minimum and maximum values to be used to control color pallete", + ) + + args = parser.parse_args() + + output_file = "animation.mp4" # Name of the output MP4 file + fps = 5 # Frames per second + + global_min, global_max = create_snapshots( + args.netcdf_file, args.output_dir, args.title_prefix + ) + if args.min_max is not None: + global_min, global_max = args.min_max[0], args.min_max[1] + + create_animation(args.output_dir, output_file, global_min, global_max, fps) + + # Delete snapshots if --keep_snapshots is not set + if not args.keep_snapshots: + import glob + import os + + snapshots = glob.glob(f"{args.output_dir}/*.png") + for snapshot in snapshots: + os.remove(snapshot) + print(f"Deleted {len(snapshots)} snapshots from {args.output_dir}.") diff --git a/src/goes16/goes16_create_animation_from_snapshots_overlay_glm.py b/src/goes16/goes16_create_animation_from_snapshots_overlay_glm.py new file mode 100644 index 00000000..bc94409f --- /dev/null +++ b/src/goes16/goes16_create_animation_from_snapshots_overlay_glm.py @@ -0,0 +1,293 @@ +import argparse +import math +import os + +import cartopy.crs as ccrs +import matplotlib.pyplot as plt +import netCDF4 as nc +import numpy as np +from matplotlib.animation import FuncAnimation +from matplotlib.patches import Circle +from PIL import Image + +from config import globals + + +def create_animation(output_directory, output_file, global_min, global_max, fps=5): + """ + Generates an animation (MP4 file) from PNG images in the given directory, + with a single global scale and colorbar. + + Args: + image_directory (str): Directory containing the PNG images. + output_file (str): Path to save the MP4 animation. + fps (int): Frames per second for the animation. + """ + # Collect all image files in the directory + image_files = sorted( + [ + os.path.join(output_directory, file) + for file in os.listdir(output_directory) + if file.endswith(".png") + ] + ) + + if not image_files: + print("No PNG images found in the directory!") + return + + # Verify the order of images + print(f"Found {len(image_files)} images: {image_files}") + + # Load the first image to set up the figure + first_image = np.array(Image.open(image_files[0])) + fig, ax = plt.subplots() + img_plot = ax.imshow(first_image, cmap="viridis", vmin=global_min, vmax=global_max) + ax.axis("off") # Remove axes for better visualization + + # Add a single global colorbar + cbar = fig.colorbar(img_plot, ax=ax, label="Intensity") + cbar.ax.tick_params(labelsize=10) # Adjust colorbar tick size if necessary + + def update(frame): + """Update the image data for each frame.""" + image = np.array(Image.open(image_files[frame])) + img_plot.set_array(image) + return [img_plot] + + # Create the animation + anim = FuncAnimation( + fig, update, frames=len(image_files), interval=1000 / fps, blit=True + ) + + # Save the animation as an MP4 file + output_file = os.path.join(output_directory, output_file) + anim.save(output_file, fps=fps, extra_args=["-vcodec", "libx264"]) + print(f"Animation saved to {output_file}") + + +def create_snapshots(netcdf_file, glm_netcdf_file, output_directory, title_prefix=""): + """ + Plots all snapshots (numpy arrays) inside the provided netCDF file and saves the results as PNG images. + + Args: + netcdf_file (str): Path to the netCDF file containing several snapshots. + output_directory (str): Directory where the output image files will be saved. + """ + try: + # Open the netCDF file + print(f"Opening file {netcdf_file}") + with ( + nc.Dataset(netcdf_file, "r") as dataset, + nc.Dataset(glm_netcdf_file, "r") as glm_dataset, + ): + # print(f"Variables in the netCDF file: {list(dataset.variables.keys())}") + + global_min = float("inf") + global_max = float("-inf") + + # Iterate through all variables in the dataset + for variable_name in dataset.variables.keys(): + # Retrieve the data array for the variable + data = dataset.variables[variable_name][:] + if variable_name[4:] in glm_dataset.variables: + overlay_data = glm_dataset.variables[variable_name[4:]][:] + else: + print( + f"Variable {variable_name} not found in GLM dataset, skipping." + ) + continue + + # Compute the global min and max values for scaling + global_min = min(global_min, data.min()) + global_max = max(global_max, data.max()) + + # Generate a sanitized output file name + sanitized_name = variable_name.replace(":", "_").replace(" ", "_") + output_image_file = os.path.join( + output_directory, f"{sanitized_name}.png" + ) + + # Plot the data array and save it + print(f"data.shape for variable {variable_name}: {data.shape}") + create_snapshot_with_overlay( + data, + overlay_data, + f"{title_prefix} {variable_name}", + output_image_file, + ) + print(f"Saved snapshot for {variable_name} to {output_image_file}") + + print(f"Global scale: min={global_min}, max={global_max}") + return global_min, global_max + except Exception as e: + print(f"Error while processing netCDF file: {e}") + + +def latlon2xy(lat, lon): + # goes_imagery_projection:semi_major_axis + req = 6378137 # meters + # goes_imagery_projection:inverse_flattening + # goes_imagery_projection:semi_minor_axis + rpol = 6356752.31414 # meters + e = 0.0818191910435 + # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis + H = 42164160 # meters + # goes_imagery_projection: longitude_of_projection_origin + lambda0 = -1.308996939 + + # Convert to radians + latRad = lat * (math.pi / 180) + lonRad = lon * (math.pi / 180) + + # (1) geocentric latitude + Phi_c = math.atan(((rpol * rpol) / (req * req)) * math.tan(latRad)) + # (2) geocentric distance to the point on the ellipsoid + rc = rpol / (math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) + # (3) sx + sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0)) + # (4) sy + sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0) + # (5) + sz = rc * math.sin(Phi_c) + + # x,y + x = math.asin((-sy) / math.sqrt((sx * sx) + (sy * sy) + (sz * sz))) + y = math.atan(sz / sx) + + return x, y + + +# Function to convert lat / lon extent to GOES-16 extents +def convertExtent2GOESProjection(extent): + # GOES-16 viewing point (satellite position) height above the earth + GOES16_HEIGHT = 35786023.0 + # GOES-16 longitude position + + a, b = latlon2xy(extent[1], extent[0]) + c, d = latlon2xy(extent[3], extent[2]) + return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT) + + +def create_snapshot_with_overlay(data, overlay_data, title, output_image_file): + """ + Plots a data array with coastlines, borders, gridlines, and overlay points, and saves it as an image. + + Args: + data (numpy.ndarray): The main data array to plot. + overlay_data (numpy.ndarray): The overlay data array for plotting red circles. + title (str): Title of the plot. + output_image_file (str): Path to save the plot. + """ + + if data.shape != overlay_data.shape: + raise ValueError( + f"The overlay shape {overlay_data.shape} must be the same as the GLM array shape {data.shape}." + ) + + # Define the projection for the plot + fig, ax = plt.subplots( + subplot_kw={ + "projection": ccrs.Geostationary( + central_longitude=-75.0, satellite_height=35786023.0 + ) + } + ) + + # Define the extent of the plot (use actual geographical extents for your data) + img_extent = convertExtent2GOESProjection(globals.extent) + + # Plot the main data array + ax.imshow(data, origin="upper", extent=img_extent, cmap="viridis") + + # Add coastlines + ax.coastlines(resolution="10m", color="black", linewidth=1) + + # Overlay points (draw circles for non-zero values) + rows, cols = overlay_data.shape + for row in range(rows): + for col in range(cols): + value = overlay_data[row, col] + if value > 0: # Only draw circles for non-zero values + # Convert array indices to geographic coordinates (adjust to your projection) + x = img_extent[0] + (img_extent[1] - img_extent[0]) * col / cols + y = img_extent[2] + (img_extent[3] - img_extent[2]) * row / rows + # Scale circle size by value (adjust multiplier as needed) + circle_size = value * 250 + circle = Circle( + (x, y), radius=circle_size, color="red", transform=ax.transData + ) + ax.add_patch(circle) + + # Add title and save the plot + plt.title(title, fontsize=14) + plt.savefig(output_image_file, bbox_inches="tight") + plt.close() + + +######################################################################## +### MAIN +######################################################################## + +if __name__ == "__main__": + """ + python src/goes16_create_animation_from_snapshots_overlay_glm.py --netcdf_file ./features/CMI/profundidade_nuvens/2020/PN_2020_03_02.nc + --glm_netcdf_file ./data/goes16/GLM/aggregated_data/2020/03/2020-03-02.nc + --output_dir ./anim/PN_GLM --title_prefix PN_GLM + """ + parser = argparse.ArgumentParser(description="Plot data from a NetCDF file.") + parser.add_argument( + "--netcdf_file", + type=str, + help="Path to the NetCDF file containing the snapshots.", + ) + parser.add_argument( + "--glm_netcdf_file", + type=str, + help="Path to the GLM NetCDF file containing the snapshots.", + ) + parser.add_argument( + "--title_prefix", + default="", + type=str, + help="Path of directory to save the resulting PNG images and animation.", + ) + parser.add_argument( + "--output_dir", + type=str, + help="Path of directory to save the resulting PNG images and animation.", + ) + parser.add_argument( + "--keep_snapshots", + action="store_true", + help="Keep the individual PNG snapshots after creating the animation.", + ) + parser.add_argument( + "--min_max", + nargs=2, + metavar=("min_value", "max_value"), + help="Minimum and maximum values to be used to control color pallete", + ) + + args = parser.parse_args() + + output_file = "animation.mp4" # Name of the output MP4 file + fps = 5 # Frames per second + + global_min, global_max = create_snapshots( + args.netcdf_file, args.glm_netcdf_file, args.output_dir, args.title_prefix + ) + if args.min_max is not None: + global_min, global_max = args.min_max[0], args.min_max[1] + + create_animation(args.output_dir, output_file, global_min, global_max, fps) + + # Delete snapshots if --keep_snapshots is not set + if not args.keep_snapshots: + import glob + import os + + snapshots = glob.glob(f"{args.output_dir}/*.png") + for snapshot in snapshots: + os.remove(snapshot) + print(f"Deleted {len(snapshots)} snapshots from {args.output_dir}.") diff --git a/src/goes16/goes16_download_crop.py b/src/goes16/goes16_download_crop.py new file mode 100644 index 00000000..8799ad46 --- /dev/null +++ b/src/goes16/goes16_download_crop.py @@ -0,0 +1,390 @@ +import argparse +import logging +import os +import threading +import time +from concurrent.futures import ThreadPoolExecutor +from datetime import datetime, timedelta + +import netCDF4 as nc +import s3fs +from osgeo import gdal, osr + +from config import globals + +# Lock to synchronize access to shared resources +download_lock = threading.Lock() + +# Thread-safe dict to keep track of cropped content +cropped_dict = {} +cropped_dict_lock = threading.Lock() # Initialize the lock + +######################################################################## +### DOWNLOADER +######################################################################## + + +# Full disk download and crop function +def download_and_crop_full_disk( + fs, + remote_path: str, + local_path: str, + spatial_resolution: float, + variable_names: str, +): + try: + fs.get(remote_path, local_path) + # print(f"Processing {remote_path}") + lat_max, lon_max = ( + globals.lat_max, + globals.lon_max, + ) # canto superior direito + lat_min, lon_min = ( + globals.lat_min, + globals.lon_min, + ) # canto inferior esquerdo + extent = [lon_min, lat_min, lon_max, lat_max] + cropped_content = crop_full_disk( + full_disk_filename=local_path, + spatial_resolution=spatial_resolution, + variable_names=variable_names, + extent=extent, + ) + + # Lock to ensure thread-safe access + with cropped_dict_lock: + # print('Updating cropped_dict') + cropped_dict.update( + cropped_content + ) # Add the cropped content in a thread-safe way + + os.remove(local_path) # Delete the local copy of the FD file after processing + except Exception as e: + print(f"Error downloading {os.path.basename(remote_path)}: {e}") + + +# Function to convert a regular date to the Julian day of the year +def get_julian_day(date): + return date.strftime("%j") + + +# Function to download files from GOES-16 for a specific hour +def process_goes16_data_for_hour( + fs, s3_path, channel, download_dir, spatial_resolution, variable_names +): + # List all files in the given hour directory + try: + files = fs.ls(s3_path) + except Exception as e: + print(f"Error accessing S3 path {s3_path}: {e}") + return + + # Filter files for the specific channel (e.g., C01 for channel 1) + channel_files = [file for file in files if f"C{channel:02d}" in file] + + # print(f'# files in {s3_path}: {len(channel_files)}') + + # Download each file using threads + with ThreadPoolExecutor() as executor: + for remote_path in channel_files: + file_name = os.path.basename(remote_path) + local_path = os.path.join(download_dir, file_name) + if not os.path.exists(local_path): + executor.submit( + download_and_crop_full_disk, + fs, + remote_path, + local_path, + spatial_resolution, + variable_names, + ) + + +# Function to download all files for a given day +def process_goes16_data_for_day( + date, channel, download_dir, spatial_resolution, variable_names +): + # Set up S3 access + fs = s3fs.S3FileSystem(anon=True) + bucket = "noaa-goes16" + product = "ABI-L2-CMIPF" + + # Format the date + year = date.strftime("%Y") + julian_day = get_julian_day(date) + + # Download data for each hour concurrently + with download_lock: + with ThreadPoolExecutor() as executor: + for hour in range(24): + hour_str = f"{hour:02d}" + s3_path = f"{bucket}/{product}/{year}/{julian_day}/{hour_str}/" + # Submit each hour's download process to the thread pool + executor.submit( + process_goes16_data_for_hour, + fs, + s3_path, + channel, + download_dir, + spatial_resolution, + variable_names, + ) + + +# Main function to process files for a range of dates +def process_goes16_data_for_period( + start_date, + end_date, + ignored_months, + channel, + download_dir, + crop_dir, + spatial_resolution, + variable_names, +): + current_date = start_date + while current_date <= end_date: + day = current_date.strftime("%Y_%m_%d") + if (current_date.month in ignored_months) or any( + day in filename for filename in os.listdir(crop_dir) + ): + print(f"Ignoring data for {day}") + current_date += timedelta(days=1) + continue + + print(f"Processing data for {day}") + process_goes16_data_for_day( + current_date, channel, download_dir, spatial_resolution, variable_names + ) + + netcdf_filename = f"{crop_dir}/C{channel:02d}_{day}.nc" + global cropped_dict + save_to_netcdf(cropped_dict, netcdf_filename) + cropped_dict = {} + + current_date += timedelta(days=1) + + +######################################################################## +### CROPPER +######################################################################## + + +def extract_middle_part(file_path): + # Split the file path by '/' and get the last part (the filename) + filename = file_path.split("/")[-1] + + # The middle part ends right before the '_s' section + middle_part = filename.split("_s")[0] + + return middle_part + + +def crop_full_disk(full_disk_filename, spatial_resolution, variable_names, extent): + # Explicitly choose to use exceptions + # gdal.UseExceptions() + + cropped_content_dict = dict() + + for var in variable_names: + # Open the file + fd_dataset = gdal.Open(f"NETCDF:{full_disk_filename}:" + var) + if fd_dataset is None: + print("Unable to open the input file.") + exit(1) + + # Read the header metadata + metadata = fd_dataset.GetMetadata() + scale = float(metadata.get(var + "#scale_factor")) + offset = float(metadata.get(var + "#add_offset")) + undef = float(metadata.get(var + "#_FillValue")) + + dtime = metadata.get("NC_GLOBAL#time_coverage_start") + dtime = datetime.strptime(dtime, "%Y-%m-%dT%H:%M:%S.%fZ") + yyyymmddhhmn = dtime.strftime("%Y_%m_%d_%H_%M") + + # Read the full disk data into a NumPy array + ds = fd_dataset.ReadAsArray( + 0, 0, fd_dataset.RasterXSize, fd_dataset.RasterYSize + ).astype(float) + + # Apply the scale and offset + ds = ds * scale + offset + # print(f'offset={offset}, scale={scale}') + + # Read the original file projection and configure the output projection + source_prj = osr.SpatialReference() + source_prj.ImportFromProj4(fd_dataset.GetProjectionRef()) + + target_prj = osr.SpatialReference() + target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") + + # Reproject the data + GeoT = fd_dataset.GetGeoTransform() + mem_driver = gdal.GetDriverByName("MEM") + raw = mem_driver.Create("raw", ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32) + raw.SetGeoTransform(GeoT) + raw.GetRasterBand(1).WriteArray(ds) + + # Define the parameters for the reprojection + warp_options = gdal.WarpOptions( + format="MEM", + srcSRS=source_prj, + dstSRS=target_prj, + outputBounds=(extent[0], extent[3], extent[2], extent[1]), + outputBoundsSRS=target_prj, + outputType=gdal.GDT_Float32, + xRes=spatial_resolution, + yRes=spatial_resolution, + srcNodata=undef, + dstNodata="nan", + resampleAlg=gdal.GRA_Max, + ) + + # Apply the transformation and write to the virtual dataset + mem_dataset = gdal.Warp("", raw, options=warp_options) + + # Check if the warp operation succeeded + if mem_dataset is None: + print("Warping failed.") + exit(1) + + # Now access the warped data from the virtual memory + mem_band = mem_dataset.GetRasterBand(1) + warped_data = mem_band.ReadAsArray() + + key = f"{var}_{yyyymmddhhmn}" + cropped_content_dict[key] = warped_data + + # Clean up + fd_dataset = None + mem_dataset = None + + return cropped_content_dict + + +def save_to_netcdf(cropped_dict, filename): + """ + Creates a netCDF file from a dictionary where the keys are date strings + and the values are numpy arrays. + + Args: + cropped_dict (dict): Dictionary with keys in the format '%Y_%m_%d_%H_%M' + and numpy arrays as values. + filename (str): Path and name of the netCDF file to be created. + """ + print(f"# cropped files: {len(cropped_dict)}") + + # Create a new netCDF file + with nc.Dataset(filename, "w", format="NETCDF4") as dataset: + # Loop through the dictionary and add data to the netCDF file + for timestamp, data_array in cropped_dict.items(): + # Replace ':' and spaces with underscores in timestamp to create valid variable names + sanitized_name = timestamp.replace(":", "_").replace(" ", "_") + + # Create dimensions based on the shape of the numpy array + for i, dim_size in enumerate(data_array.shape): + dim_name = f"dim_{i}_{sanitized_name}" + if dim_name not in dataset.dimensions: + dataset.createDimension(dim_name, dim_size) + + # Create a variable with the timestamp as its name + var = dataset.createVariable( + sanitized_name, + data_array.dtype, + tuple(f"dim_{i}_{sanitized_name}" for i in range(data_array.ndim)), + ) + + # Assign the data from the numpy array to the variable + var[:] = data_array + + print(f"netCDF file '{filename}' created successfully.") + + +######################################################################## +### MAIN +######################################################################## + +if __name__ == "__main__": + """ + Example usage: + one-day test + python src/goes16_sync_downloader_cropper.py --start_date "2024-02-08" --end_date "2024-02-08" --channel 7 --download_dir "./downloads" --crop_dir "./cropped" --spatial_resolution 0.1 --vars "CMI" + """ + + # Create an argument parser to accept start and end dates, and channel number from the command line + parser = argparse.ArgumentParser( + description="Download GOES-16 data for a specific date range." + ) + parser.add_argument( + "--start_date", type=str, required=True, help="Start date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--end_date", type=str, required=True, help="End date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--channel", type=int, required=True, help="GOES-16 channel number (1-16)" + ) + parser.add_argument( + "--download_dir", + type=str, + default="./downloads", + help="Directory to (temporarily) save downloaded FD files", + ) + parser.add_argument( + "--crop_dir", type=str, required=True, help="Directory to save cropped files" + ) + parser.add_argument( + "--spatial_resolution", + type=float, + required=True, + help="Spatial resolution in degrees (e.g., 0.1 for 0.1 degrees of latitude/longitude)", + ) + parser.add_argument( + "--ignored_months", + nargs="+", + type=int, + required=False, + default=[6, 7, 8], + help="Months to ignore (e.g., --ignored_months 6 7 8)", + ) + parser.add_argument( + "--vars", + nargs="+", + type=str, + required=True, + help="At least one variable name (CMI, ...)", + ) + + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.INFO, format=fmt) + + args = parser.parse_args() + + # Parse the start and end dates + start_date = datetime.strptime(args.start_date, "%Y-%m-%d") + end_date = datetime.strptime(args.end_date, "%Y-%m-%d") + channel = args.channel + download_dir = args.download_dir + crop_dir = args.crop_dir + spatial_resolution = args.spatial_resolution + ignored_months = args.ignored_months + variable_names = args.vars + + start_time = time.time() # Record the start time + download_dir = "./downloads" + if not os.path.exists(download_dir): + os.makedirs(download_dir) + process_goes16_data_for_period( + start_date, + end_date, + ignored_months, + channel=channel, + download_dir=download_dir, + crop_dir=crop_dir, + spatial_resolution=spatial_resolution, + variable_names=variable_names, + ) + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + print(f"Script execution time: {duration:.2f} minutes.") diff --git a/src/goes16/goes16_gen_dsi_dataframes.py b/src/goes16/goes16_gen_dsi_dataframes.py new file mode 100644 index 00000000..5d448156 --- /dev/null +++ b/src/goes16/goes16_gen_dsi_dataframes.py @@ -0,0 +1,91 @@ +import logging +import os +import sys +import time + +import pandas as pd +from netCDF4 import Dataset + +from utils.util import split_filename + + +def main(argv): + # Set the folder containing the DSI files + input_folder_path = "./data/goes16/DSI" + + dsi_variable_names = ["CAPE", "LI", "TT", "SI", "KI"] + + for variable_name in dsi_variable_names: + df = None + + # Create a list to store all the variable's timestamped files in the folder and subfolders + filenames = [] + for root, dirs, files in os.walk(input_folder_path): + for file in files: + if file.endswith(f"_{variable_name}.nc"): + # if file.startswith('2019') and file.endswith(f'_{variable_name}.nc'): + filenames.append(os.path.join(root, file)) + + logging.info(f"Total number of files: {len(filenames)}") + + # Loop through the selected timestamped files + counter = 0 + for filename in filenames: + if (counter > 0) and (counter % 5000 == 0): + logging.info(f"Number of processed files: {counter}") + counter += 1 + + file = Dataset(f"{filename}") + + # The timestamp is a substring of the filename! + dir_path, base_name, file_ext = split_filename(filename) + yyyymmddhhmn = base_name.partition("_")[0] + + # Get the pixel values + data = file.variables["Band1"][:] + + if df is None: + feature_names = [] + for y in range(data.shape[0]): + for x in range(data.shape[1]): + feature_names += [f"{variable_name}{y}{x}"] + df = pd.DataFrame(columns=["timestamp", *feature_names]) + + feature_values = [] + for y in range(data.shape[0]): + for x in range(data.shape[1]): + feature_values += [data[y, x]] + + # See https://stackoverflow.com/questions/70837397/good-alternative-to-pandas-append-method-now-that-it-is-being-deprecated + df.loc[len(df), df.columns] = [yyyymmddhhmn] + feature_values + + logging.info("Creating index in dataframe...") + + # Set the index to 'timestamp' + timestamp = pd.to_datetime(df.timestamp) + df = df.set_index(pd.DatetimeIndex(timestamp)) + + # Sort the DataFrame by the 'timestamp' column + df.sort_index(inplace=True) + + logging.info("Done!") + + df_filename = f"{variable_name}.parquet" + df.to_parquet(df_filename) + logging.info( + f"A Pandas dataframe with shape {df.shape} was created and saved in the file {df_filename}." + ) + + +if __name__ == "__main__": + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.DEBUG, format=fmt) + + start_time = time.time() # Record the start time + + main(sys.argv) + + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + + logging.info(f"Script duration: {duration:.2f} minutes") diff --git a/src/goes16/goes16_gen_dsif_images.py b/src/goes16/goes16_gen_dsif_images.py new file mode 100644 index 00000000..b7d34724 --- /dev/null +++ b/src/goes16/goes16_gen_dsif_images.py @@ -0,0 +1,193 @@ +import os +from datetime import datetime # Basic Dates and time types + +import cartopy # Plot maps +import cartopy.crs as ccrs +import matplotlib.pyplot as plt # Plotting library +import numpy as np # Scientific computing with Python +from netCDF4 import Dataset # Read / Write NetCDF4 files +from osgeo import ( + gdal, # Python bindings for GDAL + osr, # Python bindings for GDAL +) + +"""Builds a reprojected netCDF file from a full disk netCDF file. + +Args: +in_filename (str): Path to the full disk netCDF file. +out_filename (str): Path to write the reprojected netCDF file. +var (str): Name of the variable to reproject within the input file. +extent (tuple): A tuple of four floats defining the output bounding box in +geographic coordinates (lon_min, lat_max, lon_max, lat_min). + +Returns: +str: The starting time of the data coverage extracted from the metadata +of the input file. + +Raises: +RuntimeError: If there is an error opening the input file or writing +the reprojected file. +""" + + +def build_projection_from_full_disk(in_filename, out_filename, var, extent): + # Open the file + img = gdal.Open(f"NETCDF:{in_filename}:" + var) + + # Read the header metadata + metadata = img.GetMetadata() + scale = float(metadata.get(var + "#scale_factor")) + offset = float(metadata.get(var + "#add_offset")) + undef = float(metadata.get(var + "#_FillValue")) + dtime = metadata.get("NC_GLOBAL#time_coverage_start") + + # print(f'scale/offset/undef/dtime: {scale}/{offset}/{undef}/{dtime}') + + # Load the data + ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) + + # Apply the scale and offset + ds = ds * scale + offset + + # Read the original file projection and configure the output projection + source_prj = osr.SpatialReference() + source_prj.ImportFromProj4(img.GetProjectionRef()) + + target_prj = osr.SpatialReference() + target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") + + # Reproject the data + GeoT = img.GetGeoTransform() + driver = gdal.GetDriverByName("MEM") + raw = driver.Create("raw", ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32) + raw.SetGeoTransform(GeoT) + raw.GetRasterBand(1).WriteArray(ds) + + # Define the parameters of the output file + options = gdal.WarpOptions( + format="netCDF", + srcSRS=source_prj, + dstSRS=target_prj, + outputBounds=(extent[0], extent[3], extent[2], extent[1]), + outputBoundsSRS=target_prj, + outputType=gdal.GDT_Float32, + srcNodata=undef, + dstNodata="nan", + xRes=0.02, + yRes=0.02, + resampleAlg=gdal.GRA_NearestNeighbour, + ) + + # print(options) + + # Write the reprojected file on disk + gdal.Warp(f"{out_filename}", raw, options=options) + print(f"Projection saved to file {out_filename}.") + + return dtime + + +def build_image_from_projection(projection_filename, var, dtime): + # ----------------------------------------------------------------------------------------------------------- + # Open the reprojected GOES-R image + file = Dataset(f"{projection_filename}") + + # print(f'file.variables = {file.variables}') + + # Get the pixel values + data = file.variables["Band1"][:] + + # ----------------------------------------------------------------------------------------------------------- + # Choose the plot size (width x height, in inches) + plt.figure(figsize=(10, 10)) + + # Use the Geostationary projection in cartopy + ax = plt.axes(projection=ccrs.PlateCarree()) + + # Define the image extent + img_extent = [extent[0], extent[2], extent[1], extent[3]] + + # Define the color scale based on the channel + colormap = "jet" # White to black for IR channels + # colormap = "gray_r" # White to black for IR channels + + # Plot the image + img = ax.imshow(data, origin="upper", extent=img_extent, cmap=colormap) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=0.8) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="white", linewidth=0.5) + gl = ax.gridlines( + crs=ccrs.PlateCarree(), + color="gray", + alpha=1.0, + linestyle="--", + linewidth=0.25, + xlocs=np.arange(-180, 180, 5), + ylocs=np.arange(-90, 90, 5), + draw_labels=True, + ) + gl.top_labels = False + gl.right_labels = False + + # Add a colorbar + plt.colorbar( + img, label=var, extend="both", orientation="horizontal", pad=0.05, fraction=0.05 + ) + + # Extract date + date = datetime.strptime(dtime, "%Y-%m-%dT%H:%M:%S.%fZ") + + # Add a title + plt.title( + "GOES-16 " + var + " " + date.strftime("%Y-%m-%d %H:%M") + " UTC", + fontweight="bold", + fontsize=10, + loc="left", + ) + plt.title("Reg.: " + str(extent), fontsize=10, loc="right") + + # ----------------------------------------------------------------------------------------------------------- + # Save the image + temp = file_name[0:-3] + plt.savefig( + f"{output_folder}{temp}_{var}.png", bbox_inches="tight", pad_inches=0, dpi=300 + ) + + +if __name__ == "__main__": + input_folder = "./data/goes16/goes16_dsif/" + output_folder = "./data/goes16/goes16_dsif_imgs/" + + # Get the list of file names in the folder + file_names = [ + f + for f in os.listdir(input_folder) + if os.path.isfile(os.path.join(input_folder, f)) + ] + + # Coordinates of rectangle for region of interest (Rio de Janeiro municipality) + extent = [-64.0, -35.0, -35.0, -15.0] # Min lon, Min lat, Max lon, Max lat + + # Options: + # - Convective Available Potential Energy (CAPE) + # - Lifted Index (LI) + # - Total Totals (TT) + # - Showalter Index (SI) + # - K-index (KI) + + vars = ["CAPE", "LI", "TT", "SI", "KI"] + + file_names.sort() + + for file_name in file_names: + print(f"Generating images for {file_name}") + for var in vars: + in_filename = f"{input_folder}{file_name}" + out_filename = file_name[0:-3] + out_filename = f"{output_folder}{out_filename}_reprojected.nc" + print(out_filename) + dtime = build_projection_from_full_disk( + in_filename, out_filename, var, extent + ) + build_image_from_projection(out_filename, var, dtime) diff --git a/src/goes16/goes16_generate_samples_to_stconvs2s.py b/src/goes16/goes16_generate_samples_to_stconvs2s.py new file mode 100644 index 00000000..cd5c4e31 --- /dev/null +++ b/src/goes16/goes16_generate_samples_to_stconvs2s.py @@ -0,0 +1,168 @@ +import glob +import re + +import numpy as np +import xarray as xr + + +def process_single_day(files): + """ + Processa os arquivos de um único dia e retorna um dataset combinado. + """ + daily_datasets = [] + + for file_path in files: + ds = xr.open_dataset(file_path) + + time_stamps = [] + data_arrays = [] + + for var_name in ds.variables: + match = re.search(r"CMI_(\d{4}_\d{2}_\d{2}_\d{2}_\d{2})", var_name) + if match: + timestamp_str = match.group(1) + timestamp = np.datetime64( + f"{timestamp_str[:4]}-{timestamp_str[5:7]}-{timestamp_str[8:10]}T{timestamp_str[11:13]}:{timestamp_str[14:]}" + ) + time_stamps.append(timestamp) + + var_data = ds[var_name].rename( + {f"dim_0_{var_name}": "lat", f"dim_1_{var_name}": "lon"} + ) + data_arrays.append(var_data) + + time_array = xr.DataArray( + np.array(time_stamps, dtype="datetime64[ns]"), dims="time" + ) + daily_data = xr.concat(data_arrays, dim=time_array) + + daily_data = daily_data.assign_coords( + lat=np.arange(daily_data.sizes["lat"]), + lon=np.arange(daily_data.sizes["lon"]), + ) + + daily_datasets.append(daily_data) + + # Concatenar todos os datasets do dia ao longo da dimensão 'time' + combined_day = xr.concat(daily_datasets, dim="time") + combined_day = combined_day.sortby("time") # Ordenar por timestamps + + return combined_day + + +def collect_samples(combined_data, TIMESTEP, max_gap): + """ + Coleta os samples de um dataset baseado em janelas de tempo e considera todas as bandas. + + Parâmetros: + combined_data: xarray.Dataset - Dataset combinado com as dimensões `time` e `channel`. + TIMESTEP: int - Número de timestamps por sample. + max_gap: int - Máximo intervalo permitido entre timestamps consecutivos (em minutos). + + Retorna: + xarray.Dataset - Dataset contendo os samples X e Y. + """ + total_time = combined_data.sizes["time"] + + X_samples = [] + Y_samples = [] + + for i in range(total_time - TIMESTEP): + # Coleta do sample X + X_sample = combined_data.isel(time=slice(i, i + TIMESTEP)).assign_coords( + time=combined_data.time.isel(time=slice(i, i + TIMESTEP)) + ) + max_gap_X = check_max_gap(X_sample) + + # Coleta do sample Y + Y_sample = combined_data.isel( + time=slice(i + 1, i + 1 + TIMESTEP) + ).assign_coords( + time=combined_data.time.isel(time=slice(i + 1, i + 1 + TIMESTEP)) + ) + max_gap_Y = check_max_gap(Y_sample) + + # Verificar gaps + if max_gap_X > max_gap: + print(f"Timestamp faltando no X_sample: {X_sample.time.values}") + continue + elif max_gap_Y > max_gap: + print(f"Timestamp faltando no Y_sample: {Y_sample.time.values}") + continue + + # Adicionar os samples válidos + X_samples.append(X_sample) + Y_samples.append(Y_sample) + + # Concatenar os samples ao longo da dimensão 'sample' + X_samples = xr.concat(X_samples, dim="sample") + Y_samples = xr.concat(Y_samples, dim="sample") + + # Dataset final contendo X e Y + combined_samples = xr.Dataset({"x": X_samples, "y": Y_samples}) + + return combined_samples + + +def check_max_gap(sample): + """ + Calcula a maior diferença entre timestamps consecutivos dentro de um sample. + + Parâmetros: + sample: xarray.Dataset - Dataset contendo a dimensão `time`. + + Retorna: + int - O maior intervalo de tempo (em minutos) entre timestamps consecutivos. + """ + times = sample.time.values + gaps = np.diff(times).astype("timedelta64[m]").astype(int) # Diferenças em minutos + return np.max(gaps) if len(gaps) > 0 else 0 + + +def main(path, max_gap, bands, output): + TIMESTEP = 5 + files = glob.glob(path) + files.sort() + + # Organizar arquivos por dia + days = {} + for file in files: + day = re.search(r"(\d{4}_\d{2}_\d{2})", file).group(1) + if day not in days: + days[day] = [] + days[day].append(file) + + # Processar cada dia + for day, day_files in days.items(): + print(f"Processando o dia: {day}") + + band_datasets = [] + for band in bands: + band_files = [file for file in day_files if f"band{band}" in file] + if not band_files: + print(f"Sem arquivos encontrados para a banda {band} no dia {day}") + continue + + daily_dataset = process_single_day(band_files) + band_datasets.append(daily_dataset) + + if band_datasets: + combined_day = xr.concat(band_datasets, dim="channel") + combined_day = combined_day.assign_coords(channel=("channel", bands)) + + # Coletar samples do dia + daily_samples = collect_samples(combined_day, TIMESTEP, max_gap) + + # Salvar os samples por dia + daily_output_path = f"{output}/{day}_samples.nc" + daily_samples.to_netcdf(daily_output_path) + print(f"Samples do dia {day} salvos em {daily_output_path}") + else: + print(f"Nenhum dataset processado para o dia {day}.") + + +path = "./features/CMI/" +max_gap = 30 +features = ["dF_dt"] +output = "output" +main(path, max_gap, features, output) diff --git a/src/goes16/goes16_plot_CAPE.py b/src/goes16/goes16_plot_CAPE.py new file mode 100644 index 00000000..1b56fe87 --- /dev/null +++ b/src/goes16/goes16_plot_CAPE.py @@ -0,0 +1,254 @@ +# Training: Python and GOES-R Imagery: Script 17 - Level 2 Products (RRQPE) and Data Accumulation +# ----------------------------------------------------------------------------------------------------------- +# Required modules +from datetime import datetime, timedelta # Basic Dates and time types + +import cartopy # Plot maps +import cartopy.crs as ccrs +import matplotlib.pyplot as plt # Plotting library +import numpy as np # Scientific computing with Python +from goes16_utils import ( + download_PROD, # Our function for download + reproject, # Our function for reproject +) +from matplotlib import cm # Colormap handling utilities +from netCDF4 import Dataset # Read / Write NetCDF4 files +from osgeo import gdal # Python bindings for GDAL + +gdal.PushErrorHandler("CPLQuietErrorHandler") # Ignore GDAL warnings + + +def plot_data_for_this_timestamp( + filename_reprojected, extent, variable_name, yyyymmddhhmn +): + print(f"extent: {extent}") + # ----------------------------------------------------------------------------------------------------------- + # Open the reprojected GOES-R image + Dataset(filename_reprojected) + + # Read file netcdf with estimated rain from GOES-16 + sat_data = gdal.Open(f"{filename_reprojected}") + # Read number of cols and rows + ncol = sat_data.RasterXSize + nrow = sat_data.RasterYSize + # Load the data + sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) + # print(type(sat_array)) + # print(f'sat_array.shape = {sat_array.shape}') + + # Get geotransform + transform = sat_data.GetGeoTransform() + # print(f'ncol, nrow = {(ncol, nrow)}') + # lat, lon = -22.98833333,-43.19055555 + # x_float = (lon - transform[0]) / transform[1] + # y_float = (transform[3] - lat) / -transform[5] + # x = int(x_float) + # y = int(y_float) + # print(f'(x_float,y_float) = {(x,y)}') + # print(f'(x,y) = {(x,y)}') + # sat = sat_array[y,x] + # print(f'*VALUE = {sat}') + + # ----------------------------------------------------------------------------------------------------------- + # Choose the plot size (width x height, in inches) + plt.figure(figsize=(10, 10)) + + # Use the Geostationary projection in cartopy + ax = plt.axes(projection=ccrs.PlateCarree()) + + # Define the image extent + img_extent = [extent[0], extent[2], extent[1], extent[3]] + + # Modify the colormap to zero values are white + colormap = plt.get_cmap("rainbow").resampled(240) + + newcolormap = colormap(np.linspace(0, 1, 240)) + newcolormap[:1, :] = np.array([1, 1, 1, 1]) + cmap = cm.colors.ListedColormap(newcolormap) + + # #- Plot WSoI location ---------------------------------------------------------------------------------------- + # Define the coordinates to extract the data (lat,lon) <- pairs + coordinates = [("A652", -22.98833333, -43.19055555)] + + for label, lat, lon in coordinates: + # Reading coordinate of a WSoI + lat_point = lat + lon_point = lon + + x = int((lon - transform[0]) / transform[1]) + y = int((transform[3] - lat) / -transform[5]) + variable_point = sat_array[y, x] + print(f"**VALUE = {variable_point}") + + # Adding WSoI as an annotation + ax.plot( + lon_point, + lat_point, + "x", + color="black", + markersize=2, + transform=ccrs.Geodetic(), + markeredgewidth=1.0, + markeredgecolor=(0, 0, 0, 1), + zorder=8, + ) + + # Add a text + txt_offset_x = 0.4 + txt_offset_y = 0.4 + + plt.annotate( + label + + "\n" + + "Lat: " + + str(lat_point) + + "\n" + + "Lon: " + + str(lon_point) + + "\n" + + variable_name + + ": " + + str(variable_point) + + "", + xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), + xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), + fontsize=10, + fontweight="bold", + color="gold", + bbox=dict(boxstyle="round", fc=(0.0, 0.0, 0.0, 0.5), ec=(1.0, 1.0, 1.0)), + alpha=1.0, + zorder=9, + ) + + # ----------------------------------------------------------------------------------------------------------- + + # - Plot product image ---------------------------------------------------------------------------------------- + img = ax.imshow( + sat_array, vmin=0, vmax=2500, cmap=cmap, origin="upper", extent=img_extent + ) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=0.8) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="black", linewidth=0.5) + ax.gridlines( + crs=ccrs.PlateCarree(), + color="gray", + alpha=1.0, + linestyle="--", + linewidth=0.25, + xlocs=np.arange(-180, 180, 5), + ylocs=np.arange(-90, 90, 5), + draw_labels=True, + ) + plt.xlim(extent[0], extent[2]) + plt.ylim(extent[1], extent[3]) + + # Add a colorbar + plt.colorbar( + img, + label=variable_name, + extend="max", + orientation="horizontal", + pad=0.05, + fraction=0.05, + ) + + # Extract date + datetime.strptime(dtime, "%Y-%m-%dT%H:%M:%S.%fZ") + + # Add a title + plt.title(f"G-16-DSIF {variable_name}", fontweight="bold", fontsize=10, loc="left") + plt.title(f"Timestamp: {yyyymmddhhmn}", fontsize=10, loc="right") + # ----------------------------------------------------------------------------------------------------------- + # Save the image + filename = f"{output}/{variable_name}_{yyyymmddhhmn}.png" + plt.savefig(filename, bbox_inches="tight", pad_inches=0, dpi=300) + print(f"Plot saved in file {filename}.") + + plt.close() + + +if __name__ == "__main__": + temp_dir = "./data/goes16/temp" + output = "./data/goes16/Animation" + + # Desired extent + # extent = [-74.0, -34.1, -34.8, 5.5] # Min lon, Max lon, Min lat, Max lat + # extent = [-64.0, -35.0, -35.0, -15.0] # Min lon, Min lat, Max lon, Max lat + # extent = [-45, -25, -40, -20] + # extent = [-44, -24, -42, -20] + + # Region of Interest - Rio de Janeiro municipality + extent = [ + -43.890602827150, + -23.1339033365138, + -43.0483514573222, + -22.64972474827293, + ] + + # Parameters to process + yyyymmdd = "20240113" + product_name = "ABI-L2-DSIF" + + # Initial time and date + yyyy = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%Y") + mm = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%m") + dd = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%d") + + date_ini = str(datetime(int(yyyy), int(mm), int(dd), 12, 0) - timedelta(hours=23)) + date_end = str(datetime(int(yyyy), int(mm), int(dd), 12, 0)) + + # ----------------------------------------------------------------------------------------------------------- + # Loop to produce sequence of images (animation) + while date_ini <= date_end: + # Date structure + yyyymmddhhmn = datetime.strptime(date_ini, "%Y-%m-%d %H:%M:%S").strftime( + "%Y%m%d%H%M" + ) + + # Download file for current timestamp + filename_downloaded = download_PROD(yyyymmddhhmn, product_name, temp_dir) + # ----------------------------------------------------------------------------------------------------------- + # Variable + variable_name = "CAPE" + + # Open the file + img = gdal.Open(f"NETCDF:{temp_dir}/{filename_downloaded}.nc:" + variable_name) + dqf = gdal.Open(f"NETCDF:{temp_dir}/{filename_downloaded}.nc:DQF_Overall") + + # Read the header metadata + metadata = img.GetMetadata() + scale = float(metadata.get(variable_name + "#scale_factor")) + offset = float(metadata.get(variable_name + "#add_offset")) + undef = float(metadata.get(variable_name + "#_FillValue")) + dtime = metadata.get("NC_GLOBAL#time_coverage_start") + + print(metadata) + + # Load the data + ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) + ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float) + + # Remove undef + ds[ds == undef] = np.nan + + # Apply the scale and offset + ds = ds * scale + offset + + # Apply NaN's where the quality flag is greater than 0 + ds[ds_dqf > 0] = np.nan + + # Reproject the data to the region (extent) of interest. + filename_reprojected = f"{output}/{variable_name}_{yyyymmddhhmn}.nc" + reproject(filename_reprojected, img, ds, extent, undef) + + # Now plot the region of interest and save it to a file. + plot_data_for_this_timestamp( + filename_reprojected, extent, variable_name, yyyymmddhhmn + ) + + # Increment 1 hour + date_ini = str( + datetime.strptime(date_ini, "%Y-%m-%d %H:%M:%S") + timedelta(minutes=10) + ) + # ----------------------------------------------------------------------------------------------------------- diff --git a/src/goes16/goes16_plot_CMI.py b/src/goes16/goes16_plot_CMI.py new file mode 100644 index 00000000..e0d0448e --- /dev/null +++ b/src/goes16/goes16_plot_CMI.py @@ -0,0 +1,349 @@ +# ----------------------------------------------------------------------------------------------------------- +# Agrometeorology Course - Demonstration: Normalized Difference Vegetation Index (NDVI) - Extract Values +# Author: Diego Souza +# ----------------------------------------------------------------------------------------------------------- +# Required modules +import os # Miscellaneous operating system interfaces +from datetime import ( # Basic Dates and time types + # date, + datetime, # Basic Dates and time types + timedelta, +) + +import cartopy +import cartopy.crs as ccrs # Plot maps +import cartopy.feature as cfeature # Cartopy features +import cartopy.io.shapereader as shpreader # Import shapefiles +import matplotlib +import matplotlib.pyplot as plt # Plotting library +import numpy as np # Scientific computing with Python +from goes16_utils import ( + convertExtent2GOESProjection, + download_CMI, # Our own utilities + geo2grid, +) # Our own utilities +from netCDF4 import Dataset # Read / Write NetCDF4 files + +# ----------------------------------------------------------------------------------------------------------- +# Input and output directories +input = "./data/goes16/Samples" +output = "./data/goes16/Animation" + +# Desired extent +extent = [-93.0, -60.00, -25.00, 15.00] # Min lon, Min lat, Max lon, Max lat + +# Initial date and time to process +date_ini = "202201011800" + +# Number of days to accumulate +ndays = 1 + +# Convert to datetime +date_ini = datetime( + int(date_ini[0:4]), + int(date_ini[4:6]), + int(date_ini[6:8]), + int(date_ini[8:10]), + int(date_ini[10:12]), +) +date_end = date_ini + timedelta(days=ndays) + +# Create our references for the loop +date_loop = date_ini + +# ----------------------------------------------------------------------------------------------------------- +# NDVI colormap creation + +colors = [ + "#8f2723", + "#8f2723", + "#8f2723", + "#8f2723", + "#af201b", + "#af201b", + "#af201b", + "#af201b", + "#ce4a2e", + "#ce4a2e", + "#ce4a2e", + "#ce4a2e", + "#df744a", + "#df744a", + "#df744a", + "#df744a", + "#f0a875", + "#f0a875", + "#f0a875", + "#f0a875", + "#fad398", + "#fad398", + "#fad398", + "#fad398", + "#fff8ba", + "#d8eda0", + "#d8eda0", + "#d8eda0", + "#d8eda0", + "#bddd8a", + "#bddd8a", + "#bddd8a", + "#bddd8a", + "#93c669", + "#93c669", + "#93c669", + "#93c669", + "#5da73e", + "#5da73e", + "#5da73e", + "#5da73e", + "#3c9427", + "#3c9427", + "#3c9427", + "#3c9427", + "#235117", + "#235117", + "#235117", + "#235117", +] +cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", colors) +cmap.set_over("#235117") +cmap.set_under("#8f2723") +vmin = 0.1 +vmax = 0.8 +# ----------------------------------------------------------------------------------------------------------- + +# Variable to check if is the first iteration +first = True + +# Create our references for the loop +date_loop = date_ini + +while date_loop <= date_end: + # Date structure + yyyymmddhhmn = date_loop.strftime("%Y%m%d%H%M") + print(yyyymmddhhmn) + + # Download the file for Band 02 + file_name_ch02 = download_CMI(yyyymmddhhmn, "2", input) + + # Download the file for Band 03 + file_name_ch03 = download_CMI(yyyymmddhhmn, "3", input) + + # ----------------------------------------------------------------------------------------------------------- + + # If one the files hasn't been downloaded for some reason, skip the current iteration + if not (os.path.exists(f"{input}/{file_name_ch02}.nc")) or not ( + os.path.exists(f"{input}/{file_name_ch03}.nc") + ): + # Increment the date_loop + date_loop = date_loop + timedelta(days=1) + print("The file is not available, skipping this iteration.") + continue + + # Open the GOES-R image (Band 02) + file = Dataset(f"{input}/{file_name_ch02}.nc") + print(f"file.dimensions for file_name_ch02: {file.dimensions}") + + # Convert lat/lon to grid-coordinates + lly, llx = geo2grid(extent[1], extent[0], file) + ury, urx = geo2grid(extent[3], extent[2], file) + print(f"file_name_ch02 --> lly, llx, ury, urx: {(lly, llx, ury, urx)}") + + # Get the pixel values + data_ch02 = file.variables["CMI"][ury:lly, llx:urx][::2, ::2] + print(type(data_ch02)) + print(f"data_ch02.shape: {data_ch02.shape}") + + # ----------------------------------------------------------------------------------------------------------- + + # Open the GOES-R image (Band 03) + file = Dataset(f"{input}/{file_name_ch03}.nc") + print(f"file.dimensions for file_name_ch03: {file.dimensions}") + + # Convert lat/lon to grid-coordinates + lly, llx = geo2grid(extent[1], extent[0], file) + ury, urx = geo2grid(extent[3], extent[2], file) + print(f"file_name_ch03 --> lly, llx, ury, urx: {(lly, llx, ury, urx)}") + + # Get the pixel values + data_ch03 = file.variables["CMI"][ury:lly, llx:urx] + print(type(data_ch03)) + print(f"data_ch03.shape: {data_ch03.shape}") + + # ----------------------------------------------------------------------------------------------------------- + + # Make the arrays equal size + cordX = np.shape(data_ch02)[0], np.shape(data_ch03)[0] + cordY = np.shape(data_ch02)[1], np.shape(data_ch03)[1] + + minvalX = np.array(cordX).min() + minvalY = np.array(cordY).min() + + data_ch02 = data_ch02[0:minvalX, 0:minvalY] + data_ch03 = data_ch03[0:minvalX, 0:minvalY] + + # ----------------------------------------------------------------------------------------------------------- + + # Calculate the NDVI + data = (data_ch03 - data_ch02) / (data_ch03 + data_ch02) + + # ----------------------------------------------------------------------------------------------------------- + + # Compute data-extent in GOES projection-coordinates + img_extent = convertExtent2GOESProjection(extent) + + # ----------------------------------------------------------------------------------------------------------- + + # If it's the first iteration, create the array that will store the max values + if first: + first = False + ndvi_max = np.full((data_ch02.shape[0], data_ch02.shape[1]), -9999) + + # Keep the maximuns, ignoring the nans + ndvi_max = np.fmax(data, ndvi_max) + # Remove low values from the accumulation + ndvi_max[ndvi_max < 0.1] = np.nan + + # Choose the plot size (width x height, in inches) + plt.figure(figsize=(15, 15)) + + # Use the Geostationary projection in cartopy + ax = plt.axes( + projection=ccrs.Geostationary( + central_longitude=-75.0, satellite_height=35786023.0 + ) + ) + + # Add a land mask + ax.stock_img() + land = ax.add_feature(cfeature.LAND, facecolor="gray", zorder=1) + + # ----------------------------------------------------------------------------------------------------------- + # Define the coordinates to extract the data (lat,lon) <- pairs + coordinates = [("P1", 0, -60), ("P2", -5, -70), ("P3", -10, -55), ("P4", -20, -50)] + + for label, lat, lon in coordinates: + # Reading the data from a coordinate + lat_point = lat + lon_point = lon + + # Convert lat/lon to grid-coordinates + lat_ind, lon_ind = geo2grid(lat_point, lon_point, file) + NDVI_point = (ndvi_max[lat_ind - ury, lon_ind - llx]).round(2) + + # Adding the data as an annotation + # Add a circle + ax.plot( + lon_point, + lat_point, + "o", + color="red", + markersize=5, + transform=ccrs.Geodetic(), + markeredgewidth=1.0, + markeredgecolor=(0, 0, 0, 1), + zorder=8, + ) + + # Add a text + txt_offset_x = 0.8 + txt_offset_y = 0.8 + + plt.annotate( + label + + "\n" + + "Lat: " + + str(lat_point) + + "\n" + + "Lon: " + + str(lon_point) + + "\n" + + "NDVI: " + + str(NDVI_point) + + "", + xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), + xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), + fontsize=10, + fontweight="bold", + color="gold", + bbox=dict(boxstyle="round", fc=(0.0, 0.0, 0.0, 0.5), ec=(1.0, 1.0, 1.0)), + alpha=1.0, + zorder=9, + ) + + # ----------------------------------------------------------------------------------------------------------- + + # Plot the image + img = ax.imshow( + ndvi_max, + origin="upper", + vmin=vmin, + vmax=vmax, + extent=img_extent, + cmap=cmap, + zorder=2, + ) + + # Add a shapefile + shapefile = list( + shpreader.Reader( + "./data/natural_earth/ne_10m_admin_1_states_provinces.shp" + ).geometries() + ) + ax.add_geometries( + shapefile, + ccrs.PlateCarree(), + edgecolor="dimgray", + facecolor="none", + linewidth=0.3, + zorder=4, + ) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=0.8, zorder=5) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="black", linewidth=0.5, zorder=6) + ax.gridlines( + color="gray", + alpha=0.5, + linestyle="--", + linewidth=0.5, + xlocs=np.arange(-180, 180, 5), + ylocs=np.arange(-90, 90, 5), + zorder=7, + ) + + # Add a colorbar + plt.colorbar( + img, + label="Normalized Difference Vegetation Index", + extend="both", + orientation="vertical", + pad=0.05, + fraction=0.05, + ) + + # Extract date + date = datetime.strptime(file.time_coverage_start, "%Y-%m-%dT%H:%M:%S.%fZ") + + # Add a title + plt.title( + "GOES-16 NDVI " + date.strftime("%Y-%m-%d %H:%M") + " UTC", + fontweight="bold", + fontsize=10, + loc="left", + ) + plt.title("Reg.: " + str(extent), fontsize=10, loc="right") + + # Save the image + plt.savefig( + f"{output}/G16_NDVI_{yyyymmddhhmn}.png", + bbox_inches="tight", + pad_inches=0, + dpi=300, + ) + + # Show the image + plt.show() + + # Increment the date_loop + date_loop = date_loop + timedelta(days=1) diff --git a/src/goes16/goes16_plot_DSIF.py b/src/goes16/goes16_plot_DSIF.py new file mode 100644 index 00000000..79fd4f5c --- /dev/null +++ b/src/goes16/goes16_plot_DSIF.py @@ -0,0 +1,309 @@ +# Training: Python and GOES-R Imagery: Script 17 - Level 2 Products (RRQPE) and Data Accumulation +# ----------------------------------------------------------------------------------------------------------- +# Required modules +import argparse +import sys +from datetime import datetime, timedelta # Basic Dates and time types + +import cartopy # Plot maps +import cartopy.crs as ccrs +import matplotlib.pyplot as plt # Plotting library +import numpy as np # Scientific computing with Python +import pandas as pd # Miscellaneous operating system interfaces +from goes16_utils import ( + download_PROD, # Our function for download + reproject, # Our function for reproject +) +from matplotlib import cm # Colormap handling utilities +from netCDF4 import Dataset # Read / Write NetCDF4 files +from osgeo import gdal # Python bindings for GDAL + +gdal.PushErrorHandler("CPLQuietErrorHandler") # Ignore GDAL warnings + + +def fill_pixel_values(sat_array, x, y, resolution): + list_pixel_values = [] + for i in range(x - resolution, x + resolution + 1): + for j in range(y - resolution, y + resolution + 1): + list_pixel_values = np.append(list_pixel_values, sat_array[j, i]) + print(list_pixel_values) + return np.array(list_pixel_values) + + +def plot_data_for_this_timestamp( + filename_reprojected, extent, index_name, yyyymmddhhmn, ws_id, dtime +): + # ----------------------------------------------------------------------------------------------------------- + # Open the reprojected GOES-R image + Dataset(filename_reprojected) + + # Read file netcdf with estimated rain from GOES-16 + sat_data = gdal.Open(f"{filename_reprojected}") + # Read number of cols and rows + ncol = sat_data.RasterXSize + nrow = sat_data.RasterYSize + # Load the data + sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) + # print(type(sat_array)) + # print(f'sat_array.shape = {sat_array.shape}') + + # Get geotransform + transform = sat_data.GetGeoTransform() + # print(f'ncol, nrow = {(ncol, nrow)}') + # lat, lon = -22.98833333,-43.19055555 + # x_float = (lon - transform[0]) / transform[1] + # y_float = (transform[3] - lat) / -transform[5] + # x = int(x_float) + # y = int(y_float) + # print(f'(x_float,y_float) = {(x,y)}') + # print(f'(x,y) = {(x,y)}') + # sat = sat_array[y,x] + # print(f'*VALUE = {sat}') + + # ----------------------------------------------------------------------------------------------------------- + # Choose the plot size (width x height, in inches) + plt.figure(figsize=(10, 10)) + + # Use the Geostationary projection in cartopy + ax = plt.axes(projection=ccrs.PlateCarree()) + + # Define the image extent + img_extent = [extent[0], extent[2], extent[1], extent[3]] + + # Modify the colormap to zero values are white + colormap = plt.get_cmap("rainbow").resampled(240) + + newcolormap = colormap(np.linspace(0, 1, 240)) + newcolormap[:1, :] = np.array([1, 1, 1, 1]) + cmap = cm.colors.ListedColormap(newcolormap) + + # #- Plot WSoI location ---------------------------------------------------------------------------------------- + # Define the coordinates to extract the data (lat,lon) <- pairs + coordinates = [(ws_id, -22.98833333, -43.19055555)] + + for label, lat, lon in coordinates: + # Reading coordinate of a WSoI + lat_point = lat + lon_point = lon + + x = int((lon - transform[0]) / transform[1]) + y = int((transform[3] - lat) / -transform[5]) + variable_list_values = fill_pixel_values(sat_array, x, y, 1) + # print(f'**VALUE = {variable_point}') + + # Adding WSoI as an annotation + ax.plot( + lon_point, + lat_point, + "x", + color="black", + markersize=2, + transform=ccrs.Geodetic(), + markeredgewidth=1.0, + markeredgecolor=(0, 0, 0, 1), + zorder=8, + ) + + # Add a text + txt_offset_x = 0.4 + txt_offset_y = 0.4 + + plt.annotate( + label + + "\n" + + "Lat: " + + str(lat_point) + + "\n" + + "Lon: " + + str(lon_point) + + "\n" + + index_name + + ": " + + str(index_name) + + "", + xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), + xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), + fontsize=10, + fontweight="bold", + color="gold", + bbox=dict(boxstyle="round", fc=(0.0, 0.0, 0.0, 0.5), ec=(1.0, 1.0, 1.0)), + alpha=1.0, + zorder=9, + ) + + # ----------------------------------------------------------------------------------------------------------- + + # - Plot product image ---------------------------------------------------------------------------------------- + img = ax.imshow( + sat_array, vmin=0, vmax=150, cmap=cmap, origin="upper", extent=img_extent + ) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=0.8) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="black", linewidth=0.5) + ax.gridlines( + crs=ccrs.PlateCarree(), + color="gray", + alpha=1.0, + linestyle="--", + linewidth=0.25, + xlocs=np.arange(-180, 180, 5), + ylocs=np.arange(-90, 90, 5), + draw_labels=True, + ) + plt.xlim(extent[0], extent[2]) + plt.ylim(extent[1], extent[3]) + + # Add a colorbar + plt.colorbar( + img, + label=index_name, + extend="max", + orientation="horizontal", + pad=0.05, + fraction=0.05, + ) + + # Extract date + datetime.strptime(dtime, "%Y-%m-%dT%H:%M:%S.%fZ") + + # Add a title + plt.title(f"G-16-DSIF {index_name}", fontweight="bold", fontsize=10, loc="left") + plt.title(f"Timestamp: {yyyymmddhhmn}", fontsize=10, loc="right") + # ----------------------------------------------------------------------------------------------------------- + # Save the image + plt.savefig( + f"{output}/{index_name}_{yyyymmddhhmn}.png", + bbox_inches="tight", + pad_inches=0, + dpi=300, + ) + + plt.close() + return variable_list_values + + +def main(argv): + parser = argparse.ArgumentParser( + prog=argv[0], + description="""This script provides a simple interface for retrieving observations values + of DSIT indexes.""", + ) + parser.add_argument("-i", "--index", required=True, help="DSIF index", metavar="") + parser.add_argument( + "-s", "--ws_id", required=True, help="Weather station ID", metavar="" + ) + parser.add_argument( + "-l", + "--latlonlist", + nargs="+", + help=" Set min and max latitude and longitude values", + required=True, + ) + parser.add_argument( + "-d", + "--day_of_retrieve_data", + help=" Set day to retrieve data", + required=True, + ) + + args = parser.parse_args(argv[1:]) + + index_name = args.index + station_id = args.ws_id + date_to_retrieve_data = args.day_of_retrieve_data + extent = [float(x) for x in args.latlonlist] + + # Desired extent + # extent = [-74.0, -34.1, -34.8, 5.5] -74.0, -34.1 -34.8 5.5 # Min lon, Max lon, Min lat, Max lat + # extent = [-64.0, -35.0, -35.0, -15.0] -64.0 -35.0 -35.0 -15.0 # Min lon, Min lat, Max lon, Max lat + # extent = [-45, -25, -40, -20] -45 -25 -40 -20 + # extent = [-44, -24, -42, -20] + + # Initial time and date + yyyy = datetime.strptime(date_to_retrieve_data, "%Y%m%d").strftime("%Y") + mm = datetime.strptime(date_to_retrieve_data, "%Y%m%d").strftime("%m") + dd = datetime.strptime(date_to_retrieve_data, "%Y%m%d").strftime("%d") + + date_ini = str(datetime(int(yyyy), int(mm), int(dd), 12, 0) - timedelta(hours=12)) + date_end = str(datetime(int(yyyy), int(mm), int(dd), 12, 0) + timedelta(hours=12)) + + np.zeros((1086, 1086)) + + columns = [ + "datetime", + "x-1,y-1", + "x-1,y", + "x-1,y+1", + "x,y-1", + "x,y", + "x,y+1", + "x+1,y-1", + "x+1,y", + "x+1,y+1", + ] + df = pd.DataFrame(columns=columns) + # ----------------------------------------------------------------------------------------------------------- + # Loop to produce sequence of images (animation) + while date_ini <= date_end: + # Date structure + yyyymmddhhmn = datetime.strptime(date_ini, "%Y-%m-%d %H:%M:%S").strftime( + "%Y%m%d%H%M" + ) + + # Download file for current timestamp + filename_downloaded = download_PROD(yyyymmddhhmn, product_name, temp_dir) + # ----------------------------------------------------------------------------------------------------------- + + # Open the file + img = gdal.Open(f"NETCDF:{temp_dir}/{filename_downloaded}.nc:" + index_name) + dqf = gdal.Open(f"NETCDF:{temp_dir}/{filename_downloaded}.nc:DQF_Overall") + + # Read the header metadata + metadata = img.GetMetadata() + scale = float(metadata.get(index_name + "#scale_factor")) + offset = float(metadata.get(index_name + "#add_offset")) + undef = float(metadata.get(index_name + "#_FillValue")) + dtime = metadata.get("NC_GLOBAL#time_coverage_start") + + # Load the data + ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) + ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float) + + # Remove undef + ds[ds == undef] = np.nan + + # Apply the scale and offset + ds = ds * scale + offset + + # Apply NaN's where the quality flag is greater than 0 + ds[ds_dqf > 0] = np.nan + + # Reproject the file + filename_reprojected = f"{output}/{index_name}_{yyyymmddhhmn}.nc" + reproject(filename_reprojected, img, ds, extent, undef) + + variable_values = plot_data_for_this_timestamp( + filename_reprojected, extent, index_name, yyyymmddhhmn, station_id, dtime + ) + variable_values = np.append(date_ini, variable_values) + + df.loc[len(df)] = variable_values + + date_ini = str( + datetime.strptime(date_ini, "%Y-%m-%d %H:%M:%S") + timedelta(minutes=10) + ) + + df.to_csv( + "./data/goes16/data_" + index_name + "_" + date_to_retrieve_data + ".csv", + index=False, + ) + + +if __name__ == "__main__": + temp_dir = "./data/goes16/temp" + output = "./data/goes16/Animation" + # yyyymmdd = '20201217' + product_name = "ABI-L2-DSIF" + + main(sys.argv) diff --git a/src/goes16/goes16_plot_cmi_features.py b/src/goes16/goes16_plot_cmi_features.py new file mode 100644 index 00000000..55af4443 --- /dev/null +++ b/src/goes16/goes16_plot_cmi_features.py @@ -0,0 +1,238 @@ +import math +import pickle +from datetime import datetime, timedelta + +import cartopy +import cartopy.crs as ccrs +import matplotlib.animation as animation +import matplotlib.pyplot as plt +import numpy as np + + +def min_max_normalize_masked_array(masked_array: np.ma.MaskedArray): + # Ensure the input is a MaskedArray + if not isinstance(masked_array, np.ma.MaskedArray): + raise ValueError("Input must be a numpy.ma.MaskedArray") + + # Calculate the min and max values ignoring the masked elements + min_val = masked_array.min() + max_val = masked_array.max() + + # Avoid division by zero in case max_val equals min_val + if max_val == min_val: + return np.ma.masked_array(np.zeros_like(masked_array), mask=masked_array.mask) + + # Apply the min-max normalization + normalized_array = (masked_array - min_val) / (max_val - min_val) + + return normalized_array + + +def latlon2xy(lat, lon): + # goes_imagery_projection:semi_major_axis + req = 6378137 # meters + # goes_imagery_projection:inverse_flattening + # goes_imagery_projection:semi_minor_axis + rpol = 6356752.31414 # meters + e = 0.0818191910435 + # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis + H = 42164160 # meters + # goes_imagery_projection: longitude_of_projection_origin + lambda0 = -1.308996939 + + # Convert to radians + latRad = lat * (math.pi / 180) + lonRad = lon * (math.pi / 180) + + # (1) geocentric latitude + Phi_c = math.atan(((rpol * rpol) / (req * req)) * math.tan(latRad)) + # (2) geocentric distance to the point on the ellipsoid + rc = rpol / (math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) + # (3) sx + sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0)) + # (4) sy + sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0) + # (5) + sz = rc * math.sin(Phi_c) + + # x,y + x = math.asin((-sy) / math.sqrt((sx * sx) + (sy * sy) + (sz * sz))) + y = math.atan(sz / sx) + + return x, y + + +# Function to convert lat / lon extent to GOES-16 extents +def convertExtent2GOESProjection(extent): + # GOES-16 viewing point (satellite position) height above the earth + GOES16_HEIGHT = 35786023.0 + # GOES-16 longitude position + + a, b = latlon2xy(extent[1], extent[0]) + c, d = latlon2xy(extent[3], extent[2]) + return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT) + + +def generate_timestamps(initial_timestamp, final_timestamp, interval_in_minutes=10): + # Parse the input timestamps to datetime objects + initial_dt = datetime.strptime(initial_timestamp, "%Y%m%d%H%M") + final_dt = datetime.strptime(final_timestamp, "%Y%m%d%H%M") + + # Generate timestamps in 10-minute intervals + timestamps = [] + current_dt = initial_dt + + while current_dt <= final_dt: + timestamps.append(current_dt.strftime("%Y%m%d%H%M")) + current_dt += timedelta(minutes=interval_in_minutes) + + return timestamps + + +def get_frame(data, extent): + # ----------------------------------------------------------------------------------------------------------- + # Compute data-extent in GOES projection-coordinates + img_extent = convertExtent2GOESProjection(extent) + # ----------------------------------------------------------------------------------------------------------- + # Choose the plot size (width x height, in inches) + # plt.figure(figsize=(10,10)) + + # Use the Geostationary projection in cartopy + ax = plt.axes( + projection=ccrs.Geostationary( + central_longitude=-75.0, satellite_height=35786023.0 + ) + ) + + # Define the color scale based on the channel + colormap = "jet" # White to black for IR channels + + # Plot the image + img = ax.imshow( + data, origin="upper", extent=img_extent, cmap=colormap, animated=True + ) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=0.8) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="black", linewidth=0.5) + ax.gridlines(color="black", alpha=0.5, linestyle="--", linewidth=0.5) + + # Add a colorbar + # plt.colorbar(img, label='CAPE', extend='both', orientation='horizontal', pad=0.05, fraction=0.05) + + # plt.close() + + return img + return plt.imgshow() + + +def gen_animation( + initial_timestamp: str, + final_timestamp: str, + input_folder: str, + product_name: str, + extent: list, + out_file_name: str, +): + def update_frame(frame_number, img, images): + """Update the image for each frame of the animation.""" + img.set_array(images[frame_number]) + return (img,) + + # fig = plt.figure() + + i_timestamp = int(initial_timestamp) + f_timestamp = int(final_timestamp) + + assert i_timestamp <= f_timestamp + + timestamps = generate_timestamps( + initial_timestamp, final_timestamp, interval_in_minutes=10 + ) + + # images is a list of artists to draw at each frame + images = [] + for timestamp in timestamps: + # print(f'Current timestamp: {timestamp}') + + filename = f"{input_folder}/diff_{timestamp}.pkl" + + # open a file containing the pickled data + file = open(filename, "rb") + + pickled_data = pickle.load(file) + + # close the file + file.close() + + data = pickled_data[product_name] + + data = min_max_normalize_masked_array(data) + + images += [data] + + num_images = len(images) + print(num_images) + + # Create a figure and axis + fig, ax = plt.subplots() + + # Use the Geostationary projection in cartopy + ax = plt.axes( + projection=ccrs.Geostationary( + central_longitude=-75.0, satellite_height=35786023.0 + ) + ) + ax.set_axis_off() + + # See https://stackoverflow.com/questions/67855367/remove-axis-from-animation-artistanimation-python + # ax = fig.add_subplot(111) + ax.get_xaxis().set_visible(False) + ax.get_yaxis().set_visible(False) + # ax.axis('off') + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="black", linewidth=0.8) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="black", linewidth=0.5) + # ax.gridlines(color='black', alpha=0.5, linestyle='--', linewidth=0.5) + + img_extent = convertExtent2GOESProjection(extent) + + img = ax.imshow( + images[0], interpolation="none", extent=img_extent, cmap="gray", origin="upper" + ) + ax.coastlines(resolution="10m", color="yellow", linewidth=0.8) + plt.axis("off") + + # Configurar o writer + Writer = animation.writers["ffmpeg"] + writer = Writer(fps=15, metadata=dict(artist="Me"), bitrate=1800) + plt.colorbar( + img, + label=f"Profundidade das nuvens - {initial_timestamp[:4]}-{initial_timestamp[4:6]}-{initial_timestamp[6:8]}", + extend="both", + orientation="vertical", + pad=0.05, + fraction=0.05, + ) + + # Create the animation + ani = animation.FuncAnimation( + fig, update_frame, frames=num_images, fargs=(img, images), blit=True + ) + + # Save the animation + ani.save(out_file_name, writer=writer) + print(f"Created MP4 file: {out_file_name}") + + +extent = [-43.890602827150, -23.1339033365138, -43.0483514573222, -22.64972474827293] + +gen_animation( + initial_timestamp="202310310000", + final_timestamp="202310312300", + input_folder="animation_input/20231031", + product_name="Band1", + extent=extent, + out_file_name="profundidade_nuvens_2023_10_31.mp4", +) diff --git a/src/goes16/goes16_plot_crop.py b/src/goes16/goes16_plot_crop.py new file mode 100644 index 00000000..7dec9c63 --- /dev/null +++ b/src/goes16/goes16_plot_crop.py @@ -0,0 +1,143 @@ +# %load ../../src/goes16_plot_crop.py +import os # Miscellaneous operating system interfaces +import re +from datetime import datetime + +import cartopy # Plot maps +import cartopy.crs as ccrs +import matplotlib.pyplot as plt # Plotting library +import numpy as np # Scientific computing with Python +from netCDF4 import Dataset # Read / Write NetCDF4 files + + +def change_extension_to_jpg(filepath: str) -> str: + # Use os.path.splitext to separate the file root and extension + file_root, _ = os.path.splitext(filepath) + # Append the new '.jpg' extension + return f"{file_root}.jpg" + + +def extract_timestamp(file_path: str) -> str: + # Use regular expressions to capture the date and time in the file path + match = re.search(r"(\d{4})_(\d{2})_(\d{2})_(\d{2})_(\d{2})", file_path) + + if match: + # Extract the date and time components + year, month, day, hour, minute = match.groups() + + # Create a datetime object + dt = datetime( + year=int(year), + month=int(month), + day=int(day), + hour=int(hour), + minute=int(minute), + ) + + # Format the datetime object into the desired output format + return dt.strftime("%d/%m/%Y %H:%M") + else: + raise ValueError("No valid timestamp found in the file path.") + + +def extract_band_number(file_path): + # Use regular expression to find the 'band' followed by digits + match = re.search(r"band(\d+)", file_path) + + if match: + # Return the band number as an integer + return int(match.group(1)) + else: + # Return None if no match is found + return None + + +def convert_timestamp(timestamp: str) -> str: + # Convert the timestamp to a datetime object + dt = datetime.strptime(timestamp, "%Y%m%d%H%M") + # Return the date and time in the format YYYY-MM-DD HH:MM:SS + return dt.strftime("%Y-%m-%d %H:%M:%S") + + +def plot_crop(filename: str, save_fig: bool = False): + # Open the reprojected GOES-R image + file = Dataset(filename) + + lat_max, lon_max = ( + -21.699774257353113, + -42.35676996062447, + ) # canto superior direito + lat_min, lon_min = ( + -23.801876626302175, + -45.05290312102409, + ) # canto inferior esquerdo + + extent = [lon_min, lat_min, lon_max, lat_max] + + # Get the pixel values + data = file.variables["Band1"][:] + + # ----------------------------------------------------------------------------------------------------------- + # Choose the plot size (width x height, in inches) + plt.figure(figsize=(10, 10)) + + # Use the Geostationary projection in cartopy + ax = plt.axes(projection=ccrs.PlateCarree()) + + # Define the image extent + img_extent = [extent[0], extent[2], extent[1], extent[3]] + + # Define the color scale based on the channel + colormap = "gray_r" # White to black for IR channels + + # Plot the image + img = ax.imshow(data, origin="upper", extent=img_extent, cmap=colormap) + + # Add coastlines, borders and gridlines + ax.coastlines(resolution="10m", color="white", linewidth=0.8) + ax.add_feature(cartopy.feature.BORDERS, edgecolor="white", linewidth=0.5) + gl = ax.gridlines( + crs=ccrs.PlateCarree(), + color="gray", + alpha=1.0, + linestyle="--", + linewidth=0.25, + xlocs=np.arange(-180, 180, 5), + ylocs=np.arange(-90, 90, 5), + draw_labels=True, + ) + gl.top_labels = False + gl.right_labels = False + + # Add a colorbar + plt.colorbar( + img, + label="Brightness Temperatures (°C)", + extend="both", + orientation="horizontal", + pad=0.05, + fraction=0.05, + ) + + # Extract date + dtime = extract_timestamp(filename) + + band_number = extract_band_number(filename) + + # Add a title + plt.title( + "GOES-16 Band " + str(band_number) + " at " + dtime + " UTC\n", + fontweight="bold", + fontsize=10, + loc="left", + ) + plt.title("Reg.: " + str(extent), fontsize=10, loc="right") + + if save_fig: + # ----------------------------------------------------------------------------------------------------------- + # Save the image + fig_filename = change_extension_to_jpg(filename) + plt.savefig(fig_filename, bbox_inches="tight", pad_inches=0, dpi=300) + + # Show the image + plt.show() diff --git a/src/plot_dsif_series.py b/src/goes16/goes16_plot_dsif_series.py similarity index 50% rename from src/plot_dsif_series.py rename to src/goes16/goes16_plot_dsif_series.py index 76bc87c2..9c5ae6de 100644 --- a/src/plot_dsif_series.py +++ b/src/goes16/goes16_plot_dsif_series.py @@ -1,14 +1,14 @@ -from datetime import datetime # Basic Dates and time types +import argparse import os import sys -import argparse -import xarray as xr # type: ignore -import pandas as pd # type: ignore +from datetime import datetime # Basic Dates and time types + import matplotlib.pyplot as plt # type: ignore +import pandas as pd # type: ignore +import xarray as xr # type: ignore def goes16_data_retrieve(begin_date, end_date, lat_point, lon_point, agg_function): - extent = [-74.0, -34.1, -34.8, 5.5] # Min lon, Min lat, Max lon, Max lat min_lon = extent[0] @@ -17,10 +17,19 @@ def goes16_data_retrieve(begin_date, end_date, lat_point, lon_point, agg_functio max_lat = extent[3] dir_list = os.listdir(path_goes16) - goes16_data = pd.DataFrame(columns=['time', 'goes16_cape', 'goes16_ki', 'goes16_si', 'goes16_li', 'goes16_tt']) + goes16_data = pd.DataFrame( + columns=[ + "time", + "goes16_cape", + "goes16_ki", + "goes16_si", + "goes16_li", + "goes16_tt", + ] + ) for file in dir_list: - current_date = datetime.strptime(file[0:12], '%Y%m%d%H%M') + current_date = datetime.strptime(file[0:12], "%Y%m%d%H%M") if begin_date <= current_date <= end_date: data = pd.read_pickle(path_goes16 + file) cape = pd.DataFrame(data["CAPE"]) @@ -37,18 +46,24 @@ def goes16_data_retrieve(begin_date, end_date, lat_point, lon_point, agg_functio y = int((float(lat_point) - max_lat) / axis_y) x = int((float(lon_point) - min_lon) / axis_x) - goes16_data.loc[len(goes16_data.index)] = [current_date, cape.iat[x, y], ki.iat[x, y], si.iat[x, y], - li.iat[x, y], tt.iat[x, y]] + goes16_data.loc[len(goes16_data.index)] = [ + current_date, + cape.iat[x, y], + ki.iat[x, y], + si.iat[x, y], + li.iat[x, y], + tt.iat[x, y], + ] - goes16_data = goes16_data.sort_values('time') + goes16_data = goes16_data.sort_values("time") print(f"Aggregating GOES16 Data, using {agg_function}...") - if (agg_function == 'max'): - goes16_data_agg = goes16_data.resample('2h', on='time').max() - elif (agg_function == 'min'): - goes16_data_agg = goes16_data.resample('2h', on='time').min() - elif (agg_function == 'mean'): - goes16_data_agg = goes16_data.resample('2h', on='time').mean() + if agg_function == "max": + goes16_data_agg = goes16_data.resample("2h", on="time").max() + elif agg_function == "min": + goes16_data_agg = goes16_data.resample("2h", on="time").min() + elif agg_function == "mean": + goes16_data_agg = goes16_data.resample("2h", on="time").mean() goes16_data_agg = goes16_data_agg.reset_index() return goes16_data_agg @@ -65,21 +80,30 @@ def eras5_data_retrieve(lat, lon): # Put the selected variables in a Pandas DataFrame df_era5_data_nearest_to_SBGL = pd.DataFrame( - { - "time": ds_era5_data_nearest_to_SBGL.time.values, - "ERA5_cape": ds_era5_data_nearest_to_SBGL.cape, - "ERA5_ki": ds_era5_data_nearest_to_SBGL.kx, - "ERA5_tt": ds_era5_data_nearest_to_SBGL.totalx - } - ) + { + "time": ds_era5_data_nearest_to_SBGL.time.values, + "ERA5_cape": ds_era5_data_nearest_to_SBGL.cape, + "ERA5_ki": ds_era5_data_nearest_to_SBGL.kx, + "ERA5_tt": ds_era5_data_nearest_to_SBGL.totalx, + } + ) return df_era5_data_nearest_to_SBGL def sbgl_data_retrieve(): - sbgl_data = pd.read_parquet(path_sbgl, engine='pyarrow') - sbgl_data.rename(columns={'cape': 'sbgl_cape', 'cin': 'sbgl_cin', 'k': 'sbgl_ki', 'lift': 'sbgl_li', - 'total_totals': 'sbgl_tt', 'showalter': 'sbgl_si'}, inplace=True) + sbgl_data = pd.read_parquet(path_sbgl, engine="pyarrow") + sbgl_data.rename( + columns={ + "cape": "sbgl_cape", + "cin": "sbgl_cin", + "k": "sbgl_ki", + "lift": "sbgl_li", + "total_totals": "sbgl_tt", + "showalter": "sbgl_si", + }, + inplace=True, + ) return sbgl_data @@ -87,33 +111,63 @@ def sbgl_data_retrieve(): def plot_dsif_index_values(df, start_date, end_date, index): # Filter the DataFrame to include only the data within the specified date range filtered_df = df[start_date:end_date] - filtered_df = filtered_df.dropna(subset=['goes16_' + index]) + filtered_df = filtered_df.dropna(subset=["goes16_" + index]) # Plot the data plt.figure(figsize=(10, 5)) - plt.plot(filtered_df.index, filtered_df['goes16_' + index].astype(dtype='Float64'), label='GOES16') - plt.plot(filtered_df.index, filtered_df['sbgl_' + index].astype(dtype='Float64'), label='SBGL') - if index in ('cape', 'ki', 'tt'): - plt.plot(filtered_df.index, filtered_df['ERA5_' + index].astype(dtype='Float64'), label='ERA5') + plt.plot( + filtered_df.index, + filtered_df["goes16_" + index].astype(dtype="Float64"), + label="GOES16", + ) + plt.plot( + filtered_df.index, + filtered_df["sbgl_" + index].astype(dtype="Float64"), + label="SBGL", + ) + if index in ("cape", "ki", "tt"): + plt.plot( + filtered_df.index, + filtered_df["ERA5_" + index].astype(dtype="Float64"), + label="ERA5", + ) # Adding title and labels - plt.title(f'{index} values from {start_date} to {end_date}') - plt.xlabel('Date') + plt.title(f"{index} values from {start_date} to {end_date}") + plt.xlabel("Date") plt.ylabel(index) # Adding a legend plt.legend() - plt.savefig(root_path + index + "_" + datetime.strptime(str(start_date), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') - + "_" + str(datetime.strptime(str(end_date), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M')) + ".png") - - print("plot saved at " + root_path + index + "_" + datetime.strptime(str(start_date), '%Y-%m-%d %H:%M:%S').strftime( - '%Y%m%d%H%M') + "_" + str(datetime.strptime(str(end_date), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M')) + ".png" + plt.savefig( + root_path + + index + + "_" + + datetime.strptime(str(start_date), "%Y-%m-%d %H:%M:%S").strftime("%Y%m%d%H%M") + + "_" + + str( + datetime.strptime(str(end_date), "%Y-%m-%d %H:%M:%S").strftime("%Y%m%d%H%M") + ) + + ".png" + ) + + print( + "plot saved at " + + root_path + + index + + "_" + + datetime.strptime(str(start_date), "%Y-%m-%d %H:%M:%S").strftime("%Y%m%d%H%M") + + "_" + + str( + datetime.strptime(str(end_date), "%Y-%m-%d %H:%M:%S").strftime("%Y%m%d%H%M") ) + + ".png" + ) # Display the plot plt.show() -def join_dataframes_on_datetime(df1, df2, datetime_col='datetime'): +def join_dataframes_on_datetime(df1, df2, datetime_col="datetime"): """ Joins two Pandas DataFrames on a datetime column. @@ -128,9 +182,12 @@ def join_dataframes_on_datetime(df1, df2, datetime_col='datetime'): if datetime_col not in df1.columns or datetime_col not in df2.columns: raise ValueError(f"Both dataframes must contain the column '{datetime_col}'") - if not pd.api.types.is_datetime64_any_dtype(df1[datetime_col]) or not pd.api.types.is_datetime64_any_dtype( - df2[datetime_col]): - raise TypeError(f"The column '{datetime_col}' must be of type datetime64 in both dataframes") + if not pd.api.types.is_datetime64_any_dtype( + df1[datetime_col] + ) or not pd.api.types.is_datetime64_any_dtype(df2[datetime_col]): + raise TypeError( + f"The column '{datetime_col}' must be of type datetime64 in both dataframes" + ) joined_df = pd.merge(df1, df2, on=datetime_col) @@ -138,14 +195,27 @@ def join_dataframes_on_datetime(df1, df2, datetime_col='datetime'): def main(argv): - parser = argparse.ArgumentParser(prog=argv[0], - description="""This script provides a simple interface to build and plot - a time series for indexes """) - parser.add_argument("-b", "--begin_date", required=True, help="Begin date", metavar='') - parser.add_argument("-e", "--end_date", required=False, help="End date", metavar='') - parser.add_argument('-lat', "--point_latitude", help='Latitude of the current point', required=False) - parser.add_argument('-lon', "--point_longitude", help='Longitude of the current point', required=False) - parser.add_argument('-i', "--dsif_index", help='DSIF index to be plotted', required=False) + parser = argparse.ArgumentParser( + prog=argv[0], + description="""This script provides a simple interface to build and plot + a time series for indexes """, + ) + parser.add_argument( + "-b", "--begin_date", required=True, help="Begin date", metavar="" + ) + parser.add_argument("-e", "--end_date", required=False, help="End date", metavar="") + parser.add_argument( + "-lat", "--point_latitude", help="Latitude of the current point", required=False + ) + parser.add_argument( + "-lon", + "--point_longitude", + help="Longitude of the current point", + required=False, + ) + parser.add_argument( + "-i", "--dsif_index", help="DSIF index to be plotted", required=False + ) args = parser.parse_args(argv[1:]) begin_date_string = args.begin_date @@ -154,26 +224,28 @@ def main(argv): lon_point = args.point_longitude dsif_index = args.dsif_index - print('-' * 100) - times_of_day = ['0000', '1200'] + print("-" * 100) + times_of_day = ["0000", "1200"] - begin_date = datetime.strptime(begin_date_string + times_of_day[0], '%Y%m%d%H%M') - end_date = datetime.strptime(end_date_string + times_of_day[1], '%Y%m%d%H%M') + begin_date = datetime.strptime(begin_date_string + times_of_day[0], "%Y%m%d%H%M") + end_date = datetime.strptime(end_date_string + times_of_day[1], "%Y%m%d%H%M") print("Retriveving GOES16 Data...") - goes16_data = goes16_data_retrieve(begin_date, end_date, lat_point, lon_point, agg_function='mean') + goes16_data = goes16_data_retrieve( + begin_date, end_date, lat_point, lon_point, agg_function="mean" + ) print("Retriveving ERA5 Data...") era5_data = eras5_data_retrieve(lat_point, lon_point) print("Retriveving SBGL Data...") sbgl_data = sbgl_data_retrieve() print("Joining datasets...") - joined_df = join_dataframes_on_datetime(goes16_data, sbgl_data, datetime_col='time') - joined_df = join_dataframes_on_datetime(joined_df, era5_data, datetime_col='time') - joined_df.set_index('time', inplace=True) + joined_df = join_dataframes_on_datetime(goes16_data, sbgl_data, datetime_col="time") + joined_df = join_dataframes_on_datetime(joined_df, era5_data, datetime_col="time") + joined_df.set_index("time", inplace=True) plot_dsif_index_values(joined_df, begin_date, end_date, dsif_index) - print('-' * 100) + print("-" * 100) if __name__ == "__main__": diff --git a/src/goes16/goes16_retrieve_cmi_for_extent.py b/src/goes16/goes16_retrieve_cmi_for_extent.py new file mode 100644 index 00000000..4bb5371a --- /dev/null +++ b/src/goes16/goes16_retrieve_cmi_for_extent.py @@ -0,0 +1,270 @@ +# Download data from aws +# ----------------------------------------------------------------------------------------------------------- +# Required modules +import argparse +import logging +import os # Miscellaneous operating system interfaces +import sys +import time +from datetime import datetime, timedelta # Basic Dates and time types +from typing import List + +from goes16_utils import download_CMI +from netCDF4 import Dataset +from osgeo import ( + gdal, # Python bindings for GDAL + osr, # Python bindings for GDAL +) + + +def crop_full_disk_and_save( + full_disk_filename, variable_names, extent, dest_path, band +): + file = Dataset(full_disk_filename) + date = datetime.strptime(file.time_coverage_start, "%Y-%m-%dT%H:%M:%S.%fZ") + # print('date1: ', date.strftime('%Y_%m_%d_%H_%M')) + # print('date2: ', yyyymmddhhmn) + + yyyymmddhhmn = date.strftime("%Y_%m_%d_%H_%M") + + for var in variable_names: + # Open the file + img = gdal.Open(f"NETCDF:{full_disk_filename}:" + var) + + # Read the header metadata + metadata = img.GetMetadata() + scale = float(metadata.get(var + "#scale_factor")) + offset = float(metadata.get(var + "#add_offset")) + undef = float(metadata.get(var + "#_FillValue")) + # dtime = metadata.get('NC_GLOBAL#time_coverage_start') + + # Load the data + ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) + + # Apply the scale and offset + ds = ds * scale + offset + + # Read the original file projection and configure the output projection + source_prj = osr.SpatialReference() + source_prj.ImportFromProj4(img.GetProjectionRef()) + + target_prj = osr.SpatialReference() + target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") + + # Reproject the data + GeoT = img.GetGeoTransform() + driver = gdal.GetDriverByName("MEM") + raw = driver.Create("raw", ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32) + raw.SetGeoTransform(GeoT) + raw.GetRasterBand(1).WriteArray(ds) + + # Define the parameters of the output file + options = gdal.WarpOptions( + format="netCDF", + srcSRS=source_prj, + dstSRS=target_prj, + outputBounds=(extent[0], extent[3], extent[2], extent[1]), + outputBoundsSRS=target_prj, + outputType=gdal.GDT_Float32, + srcNodata=undef, + dstNodata="nan", + resampleAlg=gdal.GRA_NearestNeighbour, + ) + + img = None # Close file + + # Write the reprojected file on disk + filename_reprojected = f"{dest_path}/{var}_band{band}_{yyyymmddhhmn}.nc" + gdal.Warp(filename_reprojected, raw, options=options) + + +def download_data_for_a_day( + extent: List[float], + dest_path: str, + yyyymmdd: str, + variable_names: List[str], + bands: List[str], + temporal_resolution: int, + remove_full_disk_file: bool = True, +): + """ + Downloads values of a specific variable from a specific product and for a specific day from GOES-16 satellite. + These values are downloaded only for the locations (lat/lon) of a list of stations of interest. + These downloaded values are appended (as new rows) to the provided DataFrame. + Each row will have the following columns: (timestamp, station_id, variable names's value) + + Args: + - df (pandas.DataFrame): DataFrame to which downloaded values for stations of interest will be appended as a new column. + - yyyymmdd (str): Date in 'YYYYMMDD' format specifying the day for which data will be downloaded. + - stations_of_interest (dict): Dictionary containing stations of interest with their IDs as keys + and their corresponding latitude and longitude coordinates as values. + - product_name (str): The name of the GOES-16 product from which data will be downloaded. + - variable_name (str): The specific variable to be retrieved from the product. + """ + + # Directory to temporarily store each downloaded full disk file. + TEMP_DIR = "data/goes16" + + # Initial time and date + yyyy = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%Y") + mm = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%m") + dd = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%d") + + hour_ini = 0 + date_ini = datetime(int(yyyy), int(mm), int(dd), hour_ini, 0) + date_end = datetime(int(yyyy), int(mm), int(dd), hour_ini, 0) + timedelta(hours=23) + + time_step = date_ini + + while time_step <= date_end: + # Date structure + yyyymmddhhmn = datetime.strptime(str(time_step), "%Y-%m-%d %H:%M:%S").strftime( + "%Y%m%d%H%M" + ) + + logging.info(f"-Getting data for {yyyymmddhhmn}...") + + for band in bands: + # Download the full disk file from the Amazon cloud. + file_name = download_CMI(yyyymmddhhmn, band, TEMP_DIR) + + if file_name != -1: + try: + full_disk_filename = f"{TEMP_DIR}/{file_name}.nc" + + crop_full_disk_and_save( + full_disk_filename, + yyyymmddhhmn, + variable_names, + extent, + dest_path, + band, + ) + + if remove_full_disk_file: + try: + os.remove( + full_disk_filename + ) # Use os.remove() to delete the file + except FileNotFoundError: + logging.info( + f"Error: File '{full_disk_filename}' not found." + ) + except PermissionError: + logging.info( + f"Error: Permission denied to remove file '{full_disk_filename}'." + ) + except Exception as e: + logging.info(f"An error occurred: {e}") + except Exception as e: + logging.info(f"An error occurred: {e}") + + # Increment to get the next full disk observation. + time_step = time_step + timedelta(minutes=temporal_resolution) + + +def main(argv): + # Create an argument parser + parser = argparse.ArgumentParser( + description="Retrieve GOES16's data for (user-provided) band, variable, and date range." + ) + + # Add command line arguments for date_ini and date_end + parser.add_argument( + "--date_ini", type=str, required=True, help="Start date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--date_end", type=str, required=True, help="End date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--vars", + nargs="+", + type=str, + required=True, + help="At least one variable name (CMI, ...)", + ) + parser.add_argument( + "--bands", + nargs="+", + type=str, + required=True, + help="At least one channel from goes 16", + ) + parser.add_argument( + "--temporal_resolution", + type=int, + default=10, + help="Temporal resolution of the observations, in minutes (default: 10)", + ) + + # TODO - change to cmd line args + lat_max, lon_max = ( + -21.699774257353113, + -42.35676996062447, + ) # canto superior direito + lat_min, lon_min = ( + -23.801876626302175, + -45.05290312102409, + ) # canto inferior esquerdo + + extent = [lon_min, lat_min, lon_max, lat_max] + + dest_path = "data/goes16" + + args = parser.parse_args() + start_date = args.date_ini + end_date = args.date_end + variable_names = args.vars + temporal_resolution = args.temporal_resolution + bands = args.bands + + # Convert start_date and end_date to datetime objects + from datetime import datetime + + start_datetime = datetime.strptime(start_date, "%Y-%m-%d") + end_datetime = datetime.strptime(end_date, "%Y-%m-%d") + + folder_path = "data/goes16" + + # Verifica se a pasta existe + if not os.path.exists(folder_path): + # Se não existir, cria a pasta + os.makedirs(folder_path) + print(f"Pasta criada: {folder_path}") + else: + print(f"A pasta já existe: {folder_path}") + + # Iterate through the range of user-provided days, + # one day at a time, to retrieve corresponding data. + current_datetime = start_datetime + while current_datetime <= end_datetime: + # Ignore winter months + if current_datetime.month not in [6, 7, 8]: + yyyymmdd = current_datetime.strftime("%Y%m%d") + download_data_for_a_day( + extent, + dest_path, + yyyymmdd, + variable_names, + bands, + temporal_resolution=temporal_resolution, + ) + # Increment the current date by one day + current_datetime += timedelta(days=1) + + +if __name__ == "__main__": + ### Examples: + # python src/retrieve_goes16_cmi_for_extent.py --date_ini "2024-02-08" --date_end "2024-02-08" --vars CMI --bands 7 9 11 13 14 15 + + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.INFO, format=fmt) + + start_time = time.time() # Record the start time + + main(sys.argv) + + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + + print(f"Script execution time: {duration:.2f} minutes.") diff --git a/src/retrieve_goes16_data.py b/src/goes16/goes16_retrieve_data.py similarity index 50% rename from src/retrieve_goes16_data.py rename to src/goes16/goes16_retrieve_data.py index 3755a3af..0b66523b 100644 --- a/src/retrieve_goes16_data.py +++ b/src/goes16/goes16_retrieve_data.py @@ -1,4 +1,4 @@ -''' +""" Retrieve GOES16 Data Script Command line inputs: -p: Product Name @@ -8,100 +8,105 @@ Example: python src/retrieve_goes16_data.py -p ABI-L2-DSIF -di 20200201 -df 20200201 -l -74.0 34.1 -34.8 5.5 -''' +""" # Required modules -from datetime import timedelta, datetime # Basic Dates and time types +import argparse +import math import os +import pickle import sys -import argparse +from datetime import datetime, timedelta # Basic Dates and time types + import boto3 # type: ignore from botocore import UNSIGNED # type: ignore # boto3 config from botocore.config import Config # type: ignore -from osgeo import gdal # Python bindings for GDAL + # from goes16_utils import reproject from netCDF4 import Dataset # type: ignore -import math -import pickle +from osgeo import gdal # Python bindings for GDAL -gdal.PushErrorHandler('CPLQuietErrorHandler') # Ignore GDAL warnings +gdal.PushErrorHandler("CPLQuietErrorHandler") # Ignore GDAL warnings def get_sub_folder_list(prefix): - - s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter="/") + s3_result = s3_client.list_objects_v2( + Bucket=bucket_name, Prefix=prefix, Delimiter="/" + ) list_of_subfolders = [] - for result in s3_result['CommonPrefixes']: - list_of_subfolders.append(result['Prefix'].replace(prefix, '').replace('/', '')) + for result in s3_result["CommonPrefixes"]: + list_of_subfolders.append(result["Prefix"].replace(prefix, "").replace("/", "")) return list_of_subfolders def download_full_disk(product_name, year, day_of_year, hour, minute, path_dest): + prefix = f"{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6_G16_s{year}{day_of_year}{hour}{minute}" - prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6_G16_s{year}{day_of_year}{hour}{minute}' - - s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter="/") + s3_result = s3_client.list_objects_v2( + Bucket=bucket_name, Prefix=prefix, Delimiter="/" + ) # Check if there are files available - if 'Contents' not in s3_result: + if "Contents" not in s3_result: # There are no files - print(f'No files found for the date. Product: {product_name}') + print(f"No files found for the date. Product: {product_name}") return None else: # There are files - for obj in s3_result['Contents']: - key = obj['Key'] + for obj in s3_result["Contents"]: + key = obj["Key"] # Print the file name - file_name = key.split('/')[-1].split('.')[0] + file_name = key.split("/")[-1].split(".")[0] # Download the file - if os.path.exists(f'{path_dest}/{file_name}.nc'): - print(f'File {path_dest}/{file_name}.nc exists') + if os.path.exists(f"{path_dest}/{file_name}.nc"): + print(f"File {path_dest}/{file_name}.nc exists") return None else: - print(f'Downloading file {path_dest}/{file_name}.nc') - s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc') - return f'{file_name}' + print(f"Downloading file {path_dest}/{file_name}.nc") + s3_client.download_file(bucket_name, key, f"{path_dest}/{file_name}.nc") + return f"{file_name}" def evaluate_year_limits(list_to_filter, initial_date, final_date): - if initial_date is not None: - year_initial_date = datetime.strptime(initial_date, '%Y%m%d').strftime('%Y') + year_initial_date = datetime.strptime(initial_date, "%Y%m%d").strftime("%Y") list_to_filter = list(filter(lambda x: x >= year_initial_date, list_to_filter)) if final_date is not None: - year_final_date = datetime.strptime(final_date, '%Y%m%d').strftime('%Y') + year_final_date = datetime.strptime(final_date, "%Y%m%d").strftime("%Y") list_to_filter = list(filter(lambda x: x <= year_final_date, list_to_filter)) return list_to_filter def evaluate_day_of_year_limits(year, list_to_filter, initial_date, final_date): - if initial_date is not None: - day_of_initial_date = datetime.strptime(initial_date, '%Y%m%d').strftime('%j') - year_initial_date = datetime.strptime(initial_date, '%Y%m%d').strftime('%Y') + day_of_initial_date = datetime.strptime(initial_date, "%Y%m%d").strftime("%j") + year_initial_date = datetime.strptime(initial_date, "%Y%m%d").strftime("%Y") if year == year_initial_date: - list_to_filter = list(filter(lambda x: x >= day_of_initial_date, list_to_filter)) + list_to_filter = list( + filter(lambda x: x >= day_of_initial_date, list_to_filter) + ) if final_date is not None: - day_of_final_date = datetime.strptime(final_date, '%Y%m%d').strftime('%j') - year_final_date = datetime.strptime(final_date, '%Y%m%d').strftime('%Y') + day_of_final_date = datetime.strptime(final_date, "%Y%m%d").strftime("%j") + year_final_date = datetime.strptime(final_date, "%Y%m%d").strftime("%Y") if year == year_final_date: - list_to_filter = list(filter(lambda x: x <= day_of_final_date, list_to_filter)) + list_to_filter = list( + filter(lambda x: x <= day_of_final_date, list_to_filter) + ) return list_to_filter def geo2grid(lat, lon, nc): - # Apply scale and offset - xscale, xoffset = nc.variables['x'].scale_factor, nc.variables['x'].add_offset - yscale, yoffset = nc.variables['y'].scale_factor, nc.variables['y'].add_offset + xscale, xoffset = nc.variables["x"].scale_factor, nc.variables["x"].add_offset + yscale, yoffset = nc.variables["y"].scale_factor, nc.variables["y"].add_offset x, y = latlon2xy(lat, lon) - col = (x - xoffset)/xscale - lin = (y - yoffset)/yscale + col = (x - xoffset) / xscale + lin = (y - yoffset) / yscale return int(lin), int(col) @@ -119,13 +124,13 @@ def latlon2xy(lat, lon): lambda0 = -1.308996939 # Convert to radians - latRad = lat * (math.pi/180) - lonRad = lon * (math.pi/180) + latRad = lat * (math.pi / 180) + lonRad = lon * (math.pi / 180) # (1) geocentric latitude - Phi_c = math.atan(((rpol * rpol)/(req * req)) * math.tan(latRad)) + Phi_c = math.atan(((rpol * rpol) / (req * req)) * math.tan(latRad)) # (2) geocentric distance to the point on the ellipsoid - rc = rpol/(math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) + rc = rpol / (math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) # (3) sx sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0)) # (4) sy @@ -134,14 +139,13 @@ def latlon2xy(lat, lon): sz = rc * math.sin(Phi_c) # x,y - x = math.asin((-sy)/math.sqrt((sx*sx) + (sy*sy) + (sz*sz))) - y = math.atan(sz/sx) + x = math.asin((-sy) / math.sqrt((sx * sx) + (sy * sy) + (sz * sz))) + y = math.atan(sz / sx) return x, y def obtain_index_values(path, file_name, date, extent): - file = Dataset(path + file_name) print(file) @@ -152,17 +156,17 @@ def obtain_index_values(path, file_name, date, extent): print(lly, llx, ury, urx) dict_indices = {} - for instability_index_name in ['CAPE', 'LI', 'TT', 'SI', 'KI']: + for instability_index_name in ["CAPE", "LI", "TT", "SI", "KI"]: # Get the pixel values data = file.variables[instability_index_name][ury:lly, llx:urx] dict_indices[instability_index_name] = data - data = file.variables['DQF_Overall'][ury:lly, llx:urx] - dict_indices['DQF_Overall'] = data + data = file.variables["DQF_Overall"][ury:lly, llx:urx] + dict_indices["DQF_Overall"] = data # open a file, where you want to store the data # temp = os.path.splitext(file_name) # given '/home/user/somefile.nc', returns ('/home/user/somefile', '.nc') - pkl_file = open(f'{path + date}.pkl', 'wb') + pkl_file = open(f"{path + date}.pkl", "wb") # dump information to that file pickle.dump(dict_indices, pkl_file) @@ -174,15 +178,27 @@ def obtain_index_values(path, file_name, date, extent): def main(argv): # --------------------------------------------------------------------------------------------------------------- # Command line argument section - parser = argparse.ArgumentParser(prog=argv[0], - description="""This script provides a simple interface for retrieve the partial - or complete temporal series of a GOES16 Product.""") - parser.add_argument("-p", "--product_name", required=True, help="product name", metavar='') - # parser.add_argument("-i", "--index_name", required=False, help="index name", metavar='') - parser.add_argument('-di', "--initial_date", help='Initial date to retrieve data', required=False) - parser.add_argument('-df', "--final_date", help='Final date to retrieve data', required=False) - parser.add_argument('-l', "--latlonlist", nargs='+', help=' Set min and max latitude and' + - 'longitude values', required=True) + parser = argparse.ArgumentParser( + prog=argv[0], + description="""This script provides a simple interface for retrieve the partial + or complete temporal series of a GOES16 Product.""", + ) + parser.add_argument( + "-p", "--product_name", required=True, help="product name", metavar="" + ) + parser.add_argument( + "-di", "--initial_date", help="Initial date to retrieve data", required=False + ) + parser.add_argument( + "-df", "--final_date", help="Final date to retrieve data", required=False + ) + parser.add_argument( + "-l", + "--latlonlist", + nargs="+", + help=" Set min and max latitude and" + "longitude values", + required=True, + ) args = parser.parse_args(argv[1:]) product_name = args.product_name @@ -198,30 +214,41 @@ def main(argv): days = evaluate_day_of_year_limits(year, days, initial_date, final_date) for day_of_year in days: - hours = get_sub_folder_list(product_name + "/" + year + "/" + day_of_year + "/") + hours = get_sub_folder_list( + product_name + "/" + year + "/" + day_of_year + "/" + ) for hour in hours: for minute in minutes: - yyyy_mm_dd = datetime(int(year), 1, 1, int(hour), minute) + timedelta(int(day_of_year) - 1) - current_date_string = datetime.strptime(str(yyyy_mm_dd), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') - - if not os.path.exists(data_dir + current_date_string + '.pkl'): - full_disk_downloaded = download_full_disk(product_name, year, day_of_year, - hour, minute, data_dir) + yyyy_mm_dd = datetime( + int(year), 1, 1, int(hour), minute + ) + timedelta(int(day_of_year) - 1) + current_date_string = datetime.strptime( + str(yyyy_mm_dd), "%Y-%m-%d %H:%M:%S" + ).strftime("%Y%m%d%H%M") + + if not os.path.exists(data_dir + current_date_string + ".pkl"): + full_disk_downloaded = download_full_disk( + product_name, year, day_of_year, hour, minute, data_dir + ) if full_disk_downloaded is not None: print("Retrieving data for " + str(yyyy_mm_dd)) - current_date_string = datetime.strptime(str(yyyy_mm_dd), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') + current_date_string = datetime.strptime( + str(yyyy_mm_dd), "%Y-%m-%d %H:%M:%S" + ).strftime("%Y%m%d%H%M") - obtain_index_values(data_dir, full_disk_downloaded + '.nc', current_date_string, extent) - os.remove(data_dir + "/" + full_disk_downloaded + '.nc') + obtain_index_values( + data_dir, + full_disk_downloaded + ".nc", + current_date_string, + extent, + ) + os.remove(data_dir + "/" + full_disk_downloaded + ".nc") if __name__ == "__main__": data_dir = "./data/goes16/dsif/" - # output = "./data/goes16/Animation" - # product_name = 'ABI-L2-DSIF' - bucket_name = 'noaa-goes16' - # extent = [-74.0, -34.1, -34.8, 5.5] - s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) + bucket_name = "noaa-goes16" + s3_client = boto3.client("s3", config=Config(signature_version=UNSIGNED)) main(sys.argv) diff --git a/src/goes16/goes16_retrieve_glm.py b/src/goes16/goes16_retrieve_glm.py new file mode 100644 index 00000000..b142c6c6 --- /dev/null +++ b/src/goes16/goes16_retrieve_glm.py @@ -0,0 +1,305 @@ +import argparse +import logging +import os +import shutil +import sys +import time +from concurrent.futures import ThreadPoolExecutor +from datetime import datetime, timedelta + +import netCDF4 as nc +import numpy.ma as ma +import s3fs +from netCDF4 import Dataset + +from config import globals + +# Define coordinate limits of interest +lon_min, lon_max = globals.lon_min, globals.lon_max +lat_min, lat_max = globals.lat_min, globals.lat_max + +# Directories +output_directory = "data/goes16/GLM/" +temp_directory = os.path.join(output_directory, "temp") +final_directory = os.path.join(output_directory, "aggregated_data") + + +def create_directory(directory): + os.makedirs(directory, exist_ok=True) + logging.info(f"Directory {directory} created (or already exists).") + + +def clear_directory(directory): + if os.path.exists(directory): + shutil.rmtree(directory) + logging.info(f"Directory {directory} cleared.") + create_directory(directory) + + +def create_grid_spatial_resolution( + lon_min, lon_max, lat_min, lat_max, flash_lat, flash_lon, spatial_resolution +): + n_lat = round((lat_max - lat_min) / spatial_resolution) + n_lon = round((lon_max - lon_min) / spatial_resolution) + + shape = (n_lat, n_lon) + + # Interval size + intervalo_lat = (lat_max - lat_min) / n_lat + intervalo_lon = (lon_max - lon_min) / n_lon + # Initialize grid with zeroes + grid = ma.zeros(shape, dtype=int) + # Iterating over (lat, lon) list + for lat, lon in zip(flash_lat, flash_lon): + if not (lat_min <= lat <= lat_max and lon_min <= lon <= lon_max): + continue # Skipping (lat, lon) out of the bound + # Intervals idx + idx_lat = int((lat - lat_min) / intervalo_lat) + idx_lon = int((lon - lon_min) / intervalo_lon) + # Idx on range + idx_lat = max(0, min(idx_lat, n_lat - 1)) + idx_lon = max(0, min(idx_lon, n_lon - 1)) + # Adding one to the corresponding pair matched on the grid + grid[idx_lat, idx_lon] += 1 + + return grid + + +def generate_structure(year, month, day): + # Define the fixed start of the day. + base_date = datetime(year, month, day, 0, 0) # yyyy-mm-dd hh:mm + + # Creating an empty dictionary + data = {} + + # Generating 48 timestamps starting from 00:00, with intervals of 30 minutes + for i in range(48): + timestamp = base_date + timedelta(minutes=30 * i) + timestamp_key = timestamp.strftime("%Y_%m_%d_%H_%M") # Format: yyyy_mm_dd_hh_mm + data[timestamp_key] = {"latitude": [], "longitude": []} + + return data + + +def adjust_to_previous_interval(dt, interval_minutes=30): + # Calculate the number of intervals that have passed since the start of the day + total_minutes = dt.hour * 60 + dt.minute + previous_interval_minutes = (total_minutes // interval_minutes) * interval_minutes + adjusted_time = datetime(dt.year, dt.month, dt.day) + timedelta( + minutes=previous_interval_minutes + ) + + return adjusted_time.strftime("%Y_%m_%d_%H_%M") + + +# Função para download +def download_and_process_file(file, fs, temp_directory): + local_file_path = os.path.join(temp_directory, os.path.basename(file)) + logging.info(f"Downloading {file} to {local_file_path}") + fs.get(file, local_file_path) + logging.info(f"Downloaded: {file}") + return local_file_path + + +# Processamento paralelo com threading +def process_hourly_files(fs, hour_path, temp_directory): + try: + hourly_files = fs.ls(hour_path) + except FileNotFoundError: + logging.warning(f"Hour path {hour_path} not found.") + return + + with ThreadPoolExecutor(max_workers=4) as executor: + futures = [ + executor.submit(download_and_process_file, file, fs, temp_directory) + for file in hourly_files + ] + for future in futures: + try: + file_path = future.result() + logging.info(f"Processing completed for {file_path}") + except Exception as e: + logging.error(f"Error processing file: {e}") + + +def aggregate_daily_files( + day_directory, output_file, year, month, day, spatial_resolution +): + """Aggregate all filtered files from a day into a single NetCDF file.""" + files = [ + os.path.join(day_directory, f) + for f in os.listdir(day_directory) + if f.endswith(".nc") + ] + if not files: + logging.warning(f"No files found in directory {day_directory}.") + return + + logging.info( + f"Aggregating {len(files)} files from {day_directory} into {output_file}." + ) + + # Initialization of a structure to store the latitudes and longitudes for the 48 timestamps + data = generate_structure(year, month, day) + + for file in files: + try: + with Dataset(file, "r") as ds: + longitudes = ds.variables["flash_lon"][:] + latitudes = ds.variables["flash_lat"][:] + time_coverage_start = ds.getncattr("time_coverage_start") + dt = datetime.strptime(time_coverage_start, "%Y-%m-%dT%H:%M:%S.%fZ") + + # Adjusting timestamp with the expected format + formatted_time = adjust_to_previous_interval(dt, interval_minutes=30) + + # Update lat lon + data[formatted_time]["latitude"].extend(latitudes) + data[formatted_time]["longitude"].extend(longitudes) + + except Exception as e: + logging.error(f"Error reading file {file}: {e}") + + # Create a new netCDF file + with nc.Dataset(output_file, "w", format="NETCDF4") as dataset: + # Loop through the dictionary and add data to the netCDF file + for key in data: + latitude = data[key]["latitude"] + longitude = data[key]["longitude"] + grid = create_grid_spatial_resolution( + lon_min, + lon_max, + lat_min, + lat_max, + latitude, + longitude, + spatial_resolution, + ) + + # Create dimensions based on the shape of the numpy array + for i, dim_size in enumerate(grid.shape): + dim_name = f"dim_{i}_{key}" + if dim_name not in dataset.dimensions: + dataset.createDimension(dim_name, dim_size) + + # Create a variable with the timestamp as its name + var = dataset.createVariable( + key, grid.dtype, tuple(f"dim_{i}_{key}" for i in range(grid.ndim)) + ) + + # Assign the data from the numpy array to the variable + var[:] = grid + + logging.info(f"netCDF file '{output_file}' created successfully.") + + +def download_files(start_date, end_date, ignored_months, spatial_resolution): + """Download and process GLM files for a specified date range, saving daily files in monthly directories.""" + current_date = start_date + fs = s3fs.S3FileSystem(anon=True) + + clear_directory(temp_directory) # Ensure temp_directory is empty + create_directory(final_directory) + + while current_date <= end_date: + if current_date.month in ignored_months: + logging.info(f"Ignoring data for {current_date.strftime('%Y-%m-%d')}.") + current_date += timedelta(days=1) + continue + + year = current_date.year + month = current_date.month + day = current_date.day + day_str = current_date.strftime("%Y-%m-%d") + + year_dir = os.path.join(final_directory, f"{year}") + month_dir = os.path.join(year_dir, f"{month:02d}") + create_directory(month_dir) + + logging.info(f"Processing files for {day_str}.") + + # Path in the S3 bucket for the day + day_of_year = current_date.timetuple().tm_yday + bucket_path = f"noaa-goes16/GLM-L2-LCFA/{year}/{day_of_year:03d}/" + + with ThreadPoolExecutor(max_workers=4) as executor: + for hour in range(24): + hour_path = bucket_path + f"{hour:02d}/" + executor.submit(process_hourly_files, fs, hour_path, temp_directory) + + # Path for the aggregated file of the day + aggregated_file = os.path.join(month_dir, f"{day_str}.nc") + aggregate_daily_files( + temp_directory, aggregated_file, year, month, day, spatial_resolution + ) + + # Limpeza de diretório temporário + clear_directory(temp_directory) + current_date += timedelta(days=1) + + +def main(argv): + """ + Example usage (download data for one specific day): + python src/goes16_retrieve_glm.py --start_date 2019-01-01 --end_date 2019-01-01 --spatial_resolution 0.1 --ignored_months 6 7 8 + """ + + parser = argparse.ArgumentParser( + description="Download and filter GLM files by coordinates." + ) + parser.add_argument( + "-b", "--start_date", required=True, help="Start date in YYYY-MM-DD format" + ) + parser.add_argument( + "-e", "--end_date", required=True, help="End date in YYYY-MM-DD format" + ) + parser.add_argument( + "-s", + "--spatial_resolution", + type=float, + required=True, + help="Spatial resolution in degrees (e.g., 0.1 for 0.1 degrees of latitude/longitude)", + ) + parser.add_argument( + "-i", + "--ignored_months", + nargs="*", + type=int, + default=[], + help="Months to ignore (e.g., 1 2 12 to ignore January, February, and December)", + ) + args = parser.parse_args(argv[1:]) + + start_date = datetime.strptime(args.start_date, "%Y-%m-%d") + end_date = datetime.strptime(args.end_date, "%Y-%m-%d") + spatial_resolution = args.spatial_resolution + + assert ( + start_date <= end_date + ), "Start date must be earlier than or equal to end date." + + ignored_months = set(args.ignored_months) + for month in ignored_months: + assert ( + 1 <= month <= 12 + ), f"Invalid month: {month}. Months should be between 1 and 12." + + logging.info( + f"Starting download from {start_date.strftime('%Y-%m-%d')} to {end_date.strftime('%Y-%m-%d')}" + ) + logging.info( + f"Ignored months: {', '.join(map(str, ignored_months)) if ignored_months else 'None'}" + ) + + start_time = time.time() # Record the start time + download_files(start_date, end_date, ignored_months, spatial_resolution) + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + print(f"Script execution time: {duration:.2f} minutes.") + + +if __name__ == "__main__": + logging.basicConfig( + level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s" + ) + main(sys.argv) diff --git a/src/goes16/goes16_retrieve_product_for_wsois.py b/src/goes16/goes16_retrieve_product_for_wsois.py new file mode 100644 index 00000000..cdcb9121 --- /dev/null +++ b/src/goes16/goes16_retrieve_product_for_wsois.py @@ -0,0 +1,221 @@ +import argparse +import os # Miscellaneous operating system interfaces +import sys +import time +from collections import OrderedDict +from datetime import datetime, timedelta # Basic Dates and time types +from typing import List + +import pandas as pd +from goes16_utils import download_PROD # Our function for download + +from config.globals import INMET_WEATHER_STATION_IDS +from goes16.processing_data import find_pixel_of_coordinate, open_dataset + + +# ------------------------------------------------------------------------------ +def download_data_for_a_day( + df: pd.DataFrame, + yyyymmdd: str, + stations_of_interest: dict, + product_name: str, + variable_names: List[str], + temporal_resolution: int, + remove_full_disk_file: bool = True, +): + """ + Downloads values of a specific variable from a specific product and for a specific day from GOES-16 satellite. + These values are downloaded only for the locations (lat/lon) of a list of stations of interest. + These downloaded values are appended (as new rows) to the provided DataFrame. + Each row will have the following columns: (timestamp, station_id, variable names's value) + + Args: + - df (pandas.DataFrame): DataFrame to which downloaded values for stations of interest will be appended as a new column. + - yyyymmdd (str): Date in 'YYYYMMDD' format specifying the day for which data will be downloaded. + - stations_of_interest (dict): Dictionary containing stations of interest with their IDs as keys + and their corresponding latitude and longitude coordinates as values. + - product_name (str): The name of the GOES-16 product from which data will be downloaded. + - variable_name (str): The specific variable to be retrieved from the product. + + Returns: + - pandas.DataFrame: Updated DataFrame with appended TPW values for stations of interest. + """ + + # Directory to temporarily store each downloaded full disk file. + temp_dir = "./data/goes16/temp" + + # Initial time and date + yyyy = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%Y") + mm = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%m") + dd = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%d") + + hour_ini = 0 + date_ini = datetime(int(yyyy), int(mm), int(dd), hour_ini, 0) + date_end = datetime(int(yyyy), int(mm), int(dd), hour_ini, 0) + timedelta(hours=23) + + time_step = date_ini + + # ----------------------------------------------------------------------------------------------------------- + # Accumulation loop. Scans all of the files for the given day. + # For each file, gets the TPW values for the locations where + # the stations of interested are located. + while time_step <= date_end: + # Date structure + yyyymmddhhmn = datetime.strptime(str(time_step), "%Y-%m-%d %H:%M:%S").strftime( + "%Y%m%d%H%M" + ) + + print(f"-Getting data for {yyyymmddhhmn}...") + + # Download the full disk file from the Amazon cloud. + file_name = download_PROD(yyyymmddhhmn, product_name, temp_dir) + + try: + full_disk_filename = f"{temp_dir}/{file_name}.nc" + ds = open_dataset(full_disk_filename) + + if ds is not None: + for wsoi_id in stations_of_interest: + values_dict = OrderedDict() + for variable_name in variable_names: + field, LonCen, LatCen = ds.image(variable_name, lonlat="center") + lon = stations_of_interest[wsoi_id][1] + lat = stations_of_interest[wsoi_id][0] + x, y = find_pixel_of_coordinate(LonCen, LatCen, lon, lat) + value = field.data[y, x] + values_dict[variable_name] = value + new_row = {"timestamp": yyyymmddhhmn, "station_id": wsoi_id} + new_row.update(values_dict) + df = df.append(new_row, ignore_index=True) + + if remove_full_disk_file: + try: + os.remove( + full_disk_filename + ) # Use os.remove() to delete the file + except FileNotFoundError: + print(f"Error: File '{full_disk_filename}' not found.") + except PermissionError: + print( + f"Error: Permission denied to remove file '{full_disk_filename}'." + ) + except Exception as e: + print(f"An error occurred: {e}") + except FileNotFoundError: + print(f"Error: File '{full_disk_filename}' not found.") + + # Increment to get the next full disk observation. + time_step = time_step + timedelta(minutes=temporal_resolution) + + return df + + +def main(argv): + # Create an argument parser + parser = argparse.ArgumentParser( + description="Retrieve GOES16's data for (user-provided) product, variable, and date range." + ) + + # Add command line arguments for date_ini and date_end + parser.add_argument( + "--date_ini", type=str, required=True, help="Start date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--date_end", type=str, required=True, help="End date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--prod", + type=str, + required=True, + help="GOES16 product name (e.g., 'ABI-L2-TPWF', 'ABI-L2-DSIF')", + ) + parser.add_argument( + "--vars", + nargs="+", + type=str, + required=True, + help="Variable names (e.g., CAPE, CIN, ...)", + ) + parser.add_argument( + "--temporal_resolution", + type=int, + default=10, + help="Temporal resolution of the observations, in minutes (default: 10)", + ) + + args = parser.parse_args() + start_date = args.date_ini + end_date = args.date_end + product_name = args.prod + variable_names = args.vars + temporal_resolution = args.temporal_resolution + + # try: + # if (station_id in globals.ALERTARIO_WEATHER_STATION_IDS or station_id in globals.ALERTARIO_GAUGE_STATION_IDS): + # # This UTC thing is really anonying! + # start_date = pd.to_datetime(args.date_ini, utc=True) + # end_date = pd.to_datetime(args.date_end, utc=True) + # else: + # start_date = pd.to_datetime(args.date_ini) + # end_date = pd.to_datetime(args.date_end) + # except ParserError: + # print(f"Invalid date format: {args.date_ini}, {args.date_end}.") + # parser.print_help() + # sys.exit(2) + + # Load Station Data + stations_of_interest = dict() + stations_filename = "./data/ws/WeatherStations.csv" + df_stations = pd.read_csv(stations_filename) + for wsoi_id in INMET_WEATHER_STATION_IDS: + row = df_stations[df_stations["STATION_ID"] == wsoi_id].iloc[0] + wsoi_lat_lon = (row["VL_LATITUDE"], row["VL_LONGITUDE"]) + stations_of_interest[row["STATION_ID"]] = wsoi_lat_lon + + # Create an empty DataFrame to store historical product values for each station of interest. + df = pd.DataFrame(columns=["timestamp", "station_id", *variable_names]) + + # Convert start_date and end_date to datetime objects + from datetime import datetime + + start_datetime = datetime.strptime(start_date, "%Y-%m-%d") + end_datetime = datetime.strptime(end_date, "%Y-%m-%d") + + # Iterate through the range of user-provided days, + # one day at a time, to retrieve corresponding data. + current_datetime = start_datetime + while current_datetime <= end_datetime: + yyyymmdd = current_datetime.strftime("%Y%m%d") + df = download_data_for_a_day( + df, + yyyymmdd, + stations_of_interest, + product_name, + variable_names, + temporal_resolution=temporal_resolution, + ) + # Increment the current date by one day + current_datetime += timedelta(days=1) + + filename = f"{product_name}_{start_datetime}_to_{end_datetime}.parquet" + filename = filename.replace(" 00:00:00", "") + df.to_parquet(filename) + print( + f"A Pandas dataframe with shape {df.shape} was created and saved in the file {filename}." + ) + + +if __name__ == "__main__": + ### Examples: + # python src/retrieve_goes16_product_for_wsois.py --date_ini "2024-03-09" --date_end "2024-03-09" --prod ABI-L2-DSIF --vars CAPE TT CIN + # python src/retrieve_goes16_product_for_wsois.py --date_ini "2024-01-12" --date_end "2024-01-12" --prod ABI-L2-DSIF --vars CAPE K + # python src/retrieve_goes16_product_for_wsois.py --date_ini "2024-01-12" --date_end "2024-01-12" --prod ABI-L2-TPWF --vars TPW + + start_time = time.time() # Record the start time + + main(sys.argv) + + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + + print(f"Script duration: {duration:.2f} minutes") diff --git a/src/goes16/goes16_retrieve_rrqpe.py b/src/goes16/goes16_retrieve_rrqpe.py new file mode 100644 index 00000000..a2d4f5b0 --- /dev/null +++ b/src/goes16/goes16_retrieve_rrqpe.py @@ -0,0 +1,192 @@ +import os # Miscellaneous operating system interfaces +import sys +from datetime import datetime, timedelta # Basic Dates and time types + +import numpy as np # Scientific computing with Python +from goes16_utils import ( + download_PROD, # Our function for download + reproject, # Our function for reproject +) +from osgeo import gdal # Python bindings for GDAL + +from goes16.processing_data import find_pixel_of_coordinate, open_dataset + + +# ------------------------------------------------------------------------------ +def get_rrqpe_value(sat_data): + # Read number of cols and rows + ncol = sat_data.RasterXSize + nrow = sat_data.RasterYSize + print(f"ncol, nrow = {ncol}, {nrow}") + + # Load the data + sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) + + # Get geotransform + transform = sat_data.GetGeoTransform() + + # Coordenadas da estação do Forte de Copacabana + lat = -22.98833333 + lon = -43.19055555 + + x = int((lon - transform[0]) / transform[1]) + y = int((transform[3] - lat) / -transform[5]) + + # print(f'Value at ({x},{y}): {sat_array[x,y]}') + + return sat_array[x, y] + + +gdal.PushErrorHandler("CPLQuietErrorHandler") # Ignore GDAL warnings + + +# ------------------------------------------------------------------------------ +def store_file(product_name, yyyymmddhhmn, output, img, acum, extent, undef): + # Reproject the file + filename_acum = f"{output}/{product_name}_{yyyymmddhhmn}.nc" + reproject(filename_acum, img, acum, extent, undef) + + +# ------------------------------------------------------------------------------ +def download_data_for_a_day(yyyymmdd): + # Input and output directories + input = "./data/goes16/Samples" + os.makedirs(input, exist_ok=True) + output = "./data/goes16/Output" + os.makedirs(output, exist_ok=True) + + # Initial time and date + yyyy = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%Y") + mm = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%m") + dd = datetime.strptime(yyyymmdd, "%Y%m%d").strftime("%d") + + hour_ini = 0 + date_ini = datetime(int(yyyy), int(mm), int(dd), hour_ini, 0) + date_end = datetime(int(yyyy), int(mm), int(dd), hour_ini, 0) + timedelta(hours=23) + + temp = date_ini + + # ----------------------------------------------------------------------------------------------------------- + # Accumulation loop + while temp <= date_end: + # Date structure + yyyymmddhhmn = datetime.strptime(str(temp), "%Y-%m-%d %H:%M:%S").strftime( + "%Y%m%d%H%M" + ) + + product_name = "ABI-L2-TPWF" + # product_name = 'ABI-L2-RRQPEF' + + print(f"Getting {product_name} data for {yyyymmddhhmn}...") + + # Download the file + file_name = download_PROD(yyyymmddhhmn, product_name, input) + + # ----------------------------------------------------------------------------------------------------------- + # Variable + var = "TPW" + + # Open the file + img = gdal.Open(f"NETCDF:{input}/{file_name}.nc:" + var) + gdal.Open(f"NETCDF:{input}/{file_name}.nc:DQF") + + if img is not None: + ds = open_dataset(f"{input}/{file_name}.nc") + RRQPE, LonCen, LatCen = ds.image(var, lonlat="center") + + print("@@@@@@-RRQPE") + print(RRQPE) + print("@@@@@@") + + print("@@@@@@-LonCen") + print(LonCen) + print("@@@@@@") + + print("@@@@@@-LatCen") + print(LatCen) + print("@@@@@@") + + lat = -22.98833333 + lon = -43.19055555 + x, y = find_pixel_of_coordinate(LonCen, LatCen, lon, lat) + value1 = RRQPE.data[y, x] + + np.zeros((5424, 5424)) + + # Read the header metadata + metadata = img.GetMetadata() + scale = float(metadata.get(var + "#scale_factor")) + offset = float(metadata.get(var + "#add_offset")) + undef = float(metadata.get(var + "#_FillValue")) + metadata.get("NC_GLOBAL#time_coverage_start") + + # Load the data + ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) + # ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float) + + # Remove undef + ds[ds == undef] = np.nan + + # Apply the scale and offset + ds = ds * scale + offset + + # Apply NaN's where the quality flag is greater than 1 + ds[ds > 0] = np.nan + + value2 = ds[y, x] # get_rrqpe_value(img) + print(f"***Values for PoI at {yyyymmddhhmn}: {value1}/{value2}") + + # Sum the instantaneous value in the accumulation + # acum = np.nansum(np.dstack((acum, ds)),2) + + # store_file(product_name, yyyymmddhhmn, output, img, acum, extent, undef) + + # Increment 1 hour + temp = temp + timedelta(hours=1) + + try: + file_path = f"{input}/{file_name}.nc" + print(f"Removing file {file_path}") + os.remove(file_path) # Use os.remove() to delete the file + print(f"File '{file_path}' has been successfully removed.") + except FileNotFoundError: + print(f"Error: File '{file_path}' not found.") + except PermissionError: + print(f"Error: Permission denied to remove file '{file_path}'.") + except Exception as e: + print(f"An error occurred: {e}") + # ----------------------------------------------------------------------------------------------------------- + + +def main(argv): + periods = [ + # ('20191204', '20200531'), + # ('20200901', '20210531'), + # ('20210901', '20220531'), + # ('20220901', '20230531') + # ('20220401', '20220531') + ] + + periods = [("20220331", "20220331")] + + for period in periods: + start_date = period[0] + end_date = period[1] + + # Convert start_date and end_date to datetime objects + from datetime import datetime + + start_datetime = datetime.strptime(start_date, "%Y%m%d") + end_datetime = datetime.strptime(end_date, "%Y%m%d") + + # Iterate through the range of dates + current_datetime = start_datetime + while current_datetime <= end_datetime: + yyyymmdd = current_datetime.strftime("%Y%m%d") + download_data_for_a_day(yyyymmdd) + # Increment the current date by one day + current_datetime += timedelta(days=1) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/goes16/goes16_sync_downloader_cropper_for_glm.py b/src/goes16/goes16_sync_downloader_cropper_for_glm.py new file mode 100644 index 00000000..5133c325 --- /dev/null +++ b/src/goes16/goes16_sync_downloader_cropper_for_glm.py @@ -0,0 +1,340 @@ +import argparse +import logging +import os +import threading +import time +from concurrent.futures import ThreadPoolExecutor +from datetime import datetime, timedelta + +import netCDF4 as nc + +# import netCDF4 as nc +import numpy as np +import s3fs +from netCDF4 import Dataset + +# Lock to synchronize access to shared resources +download_lock = threading.Lock() + +# Thread-safe dict to keep track of cropped content +cropped_dict = {} +cropped_dict_lock = threading.Lock() # Initialize the lock + +######################################################################## +### DOWNLOADER +######################################################################## + +# Output directories +output_directory = "data/goes16/glm_files/" +temp_directory = "data/goes16/temp_glm_files/" +final_directory = "data/goes16/aggregated_glm_files/" + +# print(f"Processing {remote_path}") +lat_max, lon_max = ( + -21.699774257353113, + -42.35676996062447, +) # canto superior direito +lat_min, lon_min = ( + -23.801876626302175, + -45.05290312102409, +) # canto inferior esquerdo +extent = [lon_min, lat_min, lon_max, lat_max] + + +# Full disk download and crop function +def download_and_crop_full_disk(fs, remote_path: str, local_path: str): + try: + print(f"Downloading {remote_path} to {local_path}") + fs.get(remote_path, local_path) + # print(f"Processing {remote_path}") + cropped_content = crop_full_disk(file_path=local_path, extent=extent) + + # Lock to ensure thread-safe access + with cropped_dict_lock: + # print('Updating cropped_dict') + cropped_dict.update( + cropped_content + ) # Add the cropped content in a thread-safe way + + os.remove(local_path) # Delete the local copy of the FD file after processing + except Exception as e: + print(f"Error downloading {os.path.basename(remote_path)}: {e}") + + +# Function to convert a regular date to the Julian day of the year +def get_julian_day(date): + return date.strftime("%j") + + +# Function to download files from GOES-16 for a specific hour +def process_goes16_data_for_hour(fs, s3_path, download_dir): + # List all files in the given hour directory + try: + files = fs.ls(s3_path) + except Exception as e: + print(f"Error accessing S3 path {s3_path}: {e}") + return + + # print(f'# files in {s3_path}: {len(files)}') + + # Download each file using threads + with ThreadPoolExecutor() as executor: + for remote_path in files: + file_name = os.path.basename(remote_path) + local_path = os.path.join(download_dir, file_name) + if not os.path.exists(local_path): + executor.submit( + download_and_crop_full_disk, fs, remote_path, local_path + ) + + +# Function to download all files for a given day +def process_goes16_data_for_day(date, download_dir): + # Set up S3 access + fs = s3fs.S3FileSystem(anon=True) + bucket = "noaa-goes16" + product = "GLM-L2-LCFA" + + # Format the date + year = date.strftime("%Y") + julian_day = get_julian_day(date) + + # Download data for each hour concurrently + with download_lock: + with ThreadPoolExecutor() as executor: + for hour in range(24): + hour_str = f"{hour:02d}" + s3_path = f"{bucket}/{product}/{year}/{julian_day}/{hour_str}/" + # Submit each hour's download process to the thread pool + executor.submit(process_goes16_data_for_hour, fs, s3_path, download_dir) + + +# Main function to process files for a range of dates +def process_goes16_data_for_period( + start_date, end_date, ignored_months, download_dir, crop_dir +): + current_date = start_date + while current_date <= end_date: + day = current_date.strftime("%Y_%m_%d") + if (current_date.month in ignored_months) or any( + day in filename for filename in os.listdir(crop_dir) + ): + print(f"Ignoring data for {day}") + current_date += timedelta(days=1) + continue + + print(f"Processing data for {day}") + process_goes16_data_for_day(current_date, download_dir) + + netcdf_filename = f"{crop_dir}/GLM_{day}.nc" + global cropped_dict + save_to_netcdf(cropped_dict, netcdf_filename) + cropped_dict = {} + + current_date += timedelta(days=1) + + +######################################################################## +### CROPPER +######################################################################## + + +def extract_middle_part(file_path): + # Split the file path by '/' and get the last part (the filename) + filename = file_path.split("/")[-1] + + # The middle part ends right before the '_s' section + middle_part = filename.split("_s")[0] + + return middle_part + + +def crop_full_disk(file_path, extent): + """ + Filter GLM events in a NetCDF file based on the provided coordinate bounds. + + Parameters: + file_path (str): Path to the input NetCDF file. + lon_min (float): Minimum longitude of the bounding box. + lon_max (float): Maximum longitude of the bounding box. + lat_min (float): Minimum latitude of the bounding box. + lat_max (float): Maximum latitude of the bounding box. + + Returns: + Dataset: A new in-memory NetCDF Dataset object containing filtered data. + """ + try: + print("0 --> ", file_path) + + lon_min, lat_min, lon_max, lat_max = extent + + # sys.exit(0) + + # Open the original NetCDF file in read mode + dataset = Dataset(file_path, "r") + + print("1 --> Opened successfully!") + + # Get the longitude and latitude variables + longitudes = dataset.variables["flash_lon"][:] + latitudes = dataset.variables["flash_lat"][:] + + # Create a mask for the bounding box + mask = ( + (longitudes >= lon_min) + & (longitudes <= lon_max) + & (latitudes >= lat_min) + & (latitudes <= lat_max) + ) + + # Create an in-memory NetCDF dataset for filtered data + filtered_dataset = Dataset( + "filtered_data.nc", "w", format="NETCDF4", memory=True + ) + + # Copy global attributes + filtered_dataset.setncatts( + {attr: dataset.getncattr(attr) for attr in dataset.ncattrs()} + ) + + # Copy dimensions + for dim_name, dim in dataset.dimensions.items(): + filtered_dataset.createDimension( + dim_name, len(dim) if not dim.isunlimited() else None + ) + + # Copy variables and apply the mask + for var_name, var in dataset.variables.items(): + # Create the new variable in the filtered dataset + filtered_var = filtered_dataset.createVariable( + var_name, var.datatype, var.dimensions + ) + + # Copy variable attributes + filtered_var.setncatts( + {attr: var.getncattr(attr) for attr in var.ncattrs()} + ) + + # Apply the mask if the variable is related to flash events + if var_name in ["flash_lon", "flash_lat"]: + filtered_var[:] = var[:][mask] + elif "event_id" in var.dimensions or "flash_id" in var.dimensions: + filtered_var[:] = np.compress(mask, var[:], axis=0) + else: + filtered_var[:] = var[:] + + # Close the original dataset + dataset.close() + + # Return the filtered dataset + return filtered_dataset + + except Exception as e: + print(f"An error occurred: {e}") + return None + + +def save_to_netcdf(cropped_dict, filename): + """ + Creates a netCDF file from a dictionary where the keys are date strings + and the values are numpy arrays. + + Args: + cropped_dict (dict): Dictionary with keys in the format '%Y_%m_%d_%H_%M' + and numpy arrays as values. + filename (str): Path and name of the netCDF file to be created. + """ + + print(f"# cropped files: {len(cropped_dict)}") + + # Create a new netCDF file + with nc.Dataset(filename, "w", format="NETCDF4") as dataset: + # Loop through the dictionary and add data to the netCDF file + for timestamp, data_array in cropped_dict.items(): + # Replace ':' and spaces with underscores in timestamp to create valid variable names + sanitized_name = timestamp.replace(":", "_").replace(" ", "_") + + # Create dimensions based on the shape of the numpy array + for i, dim_size in enumerate(data_array.shape): + dim_name = f"dim_{i}_{sanitized_name}" + if dim_name not in dataset.dimensions: + dataset.createDimension(dim_name, dim_size) + + # Create a variable with the timestamp as its name + var = dataset.createVariable( + sanitized_name, + data_array.dtype, + tuple(f"dim_{i}_{sanitized_name}" for i in range(data_array.ndim)), + ) + + # Assign the data from the numpy array to the variable + var[:] = data_array + + print(f"netCDF file '{filename}' created successfully.") + + +######################################################################## +### MAIN +######################################################################## + +if __name__ == "__main__": + """ + Example usage (download data for one specific day): + python src/goes16_sync_downloader_cropper_for_glm.py --start_date "2024-02-08" --end_date "2024-02-08" --download_dir "./downloads" --crop_dir "./cropped" + """ + + # Create an argument parser to accept start and end dates, and channel number from the command line + parser = argparse.ArgumentParser( + description="Download GOES-16 data for a specific date range." + ) + parser.add_argument( + "--start_date", type=str, required=True, help="Start date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--end_date", type=str, required=True, help="End date (format: YYYY-MM-DD)" + ) + parser.add_argument( + "--download_dir", + type=str, + default="./downloads", + help="Directory to (temporarily) save downloaded FD files", + ) + parser.add_argument( + "--crop_dir", type=str, required=True, help="Directory to save cropped files" + ) + parser.add_argument( + "--ignored_months", + nargs="+", + type=int, + required=False, + default=[6, 7, 8], + help="Months to ignore (e.g., --ignored_months 6 7 8)", + ) + # parser.add_argument("--vars", nargs='+', type=str, required=True, help="At least one variable name (CMI, ...)") + + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.INFO, format=fmt) + + args = parser.parse_args() + + # Parse the start and end dates + start_date = datetime.strptime(args.start_date, "%Y-%m-%d") + end_date = datetime.strptime(args.end_date, "%Y-%m-%d") + download_dir = args.download_dir + crop_dir = args.crop_dir + ignored_months = args.ignored_months + + start_time = time.time() # Record the start time + download_dir = "./downloads" + if not os.path.exists(download_dir): + os.makedirs(download_dir) + process_goes16_data_for_period( + start_date, + end_date, + ignored_months, + download_dir=download_dir, + crop_dir=crop_dir, + ) + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + print(f"Script execution time: {duration:.2f} minutes.") diff --git a/src/goes16/goes16_tpw_fuse_with_wsois.py b/src/goes16/goes16_tpw_fuse_with_wsois.py new file mode 100644 index 00000000..e85fedc4 --- /dev/null +++ b/src/goes16/goes16_tpw_fuse_with_wsois.py @@ -0,0 +1,148 @@ +import os + +import pandas as pd + +from config.globals import INMET_WEATHER_STATION_IDS + + +def hourly_average_with_nan_handling(df: pd.DataFrame): + """ + Resamples a DataFrame containing time series data to an hourly frequency and computes the mean of + the 'tpw_value' column. + + Parameters: + df (pd.DataFrame): A pandas DataFrame with a DateTime index and a column named 'tpw_value' containing + the time series data. + + Returns: + pd.DataFrame: A DataFrame with the hourly resampled mean values of the 'tpw_value' column. + The index of the returned DataFrame is shifted by one hour. + + Notes: + - The function resamples the input DataFrame to an hourly frequency and calculates the mean of the 'tpw_value' column for each hour. + - NaN values are ignored in the mean calculation. + - The index of the resulting DataFrame is shifted by one hour using `pd.DateOffset(hours=1)` to correctly represent the aggregated value in the previous hour. + - If all the values in a hour are NaN, the the corresponding entry in the resulting dataframe will also be NaN. + + Example: + df = pd.DataFrame({'tpw_value': [2, 2, 2, np.NaN, 2, 2, 3, 3, 3, 3, 3, 3, np.NaN, 4, 4, 4, np.NaN]}, + index=pd.date_range('2023-01-01', periods=17, freq='10T')) + print(df) + print(30*'~') + print(hourly_average_with_nan_handling(df)) + + tpw_value + 2023-01-01 00:00:00 2.0 + 2023-01-01 00:10:00 2.0 + 2023-01-01 00:20:00 2.0 + 2023-01-01 00:30:00 NaN + 2023-01-01 00:40:00 2.0 + 2023-01-01 00:50:00 2.0 + 2023-01-01 01:00:00 3.0 + 2023-01-01 01:10:00 3.0 + 2023-01-01 01:20:00 3.0 + 2023-01-01 01:30:00 3.0 + 2023-01-01 01:40:00 3.0 + 2023-01-01 01:50:00 3.0 + 2023-01-01 02:00:00 NaN + 2023-01-01 02:10:00 4.0 + 2023-01-01 02:20:00 4.0 + 2023-01-01 02:30:00 4.0 + 2023-01-01 02:40:00 NaN + ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + tpw_value + 2023-01-01 01:00:00 2.0 + 2023-01-01 02:00:00 3.0 + 2023-01-01 03:00:00 4.0 + """ + # Resample the DataFrame to hourly frequency and compute the mean + df_resampled = df["tpw_value"].resample("H").mean() + + return pd.DataFrame( + {"tpw_value": df_resampled.values}, + index=df_resampled.index + pd.DateOffset(hours=1), + ) + + +if __name__ == "__main__": + # Set the folder containing the TPW parquet files + folder_path = "./data/goes16/tpw" + + # Initialize an empty list to store DataFrames + dataframes = [] + + # Create list with all Parquet files in the folder + parquet_files = [ + file for file in os.listdir(folder_path) if file.endswith(".parquet") + ] + + # Loop through the Parquet files, read them, and append to the list of Dataframes + for file in parquet_files: + file_path = os.path.join(folder_path, file) + df = pd.read_parquet(file_path) + print(f"Merging dataframe {file_path} of shape {df.shape}") + dataframes.append(df) + + # Concatenate all DataFrames into a single DataFrame, so that + # merged_df contains the combined data from all Parquet files + merged_df = pd.concat(dataframes) + + # print(f'merged_df.columns (1): {merged_df.columns}') + + # # Reset the index to 'timestamp' and drop the old index + # merged_df.set_index('timestamp', inplace=True) + # merged_df.index = pd.to_datetime(merged_df.index[0]) + + # print(f'merged_df.columns (2): {merged_df.columns}') + + # If you want to sort the DataFrame by the 'timestamp' column + # merged_df.sort_index(inplace=True) + + # Print the first few rows to verify + print("MERGED DATAFRAME:") + print(merged_df.head()) + print(merged_df.shape) + + for wsoi_id in INMET_WEATHER_STATION_IDS: + print(f"Processing data for station {wsoi_id}") + + # Create a boolean mask to filter rows with 'station_id' equal to 'wsoi_id' + mask = merged_df["station_id"] == wsoi_id + + # Use the mask to select rows from the DataFrame + df_wsoi = merged_df[mask] + print(df_wsoi) + + print("columns (1):", df_wsoi.columns) + df_wsoi.reset_index(inplace=True) + print("columns (2):", df_wsoi.columns) + + # Now, the `df_wsoi` DataFrame contains rows where 'station_id' matches 'wsoi_id' + print(f"df_wsoi.shape: {df_wsoi.shape}") + print("Number of NaN values:", df_wsoi["tpw_value"].isna().sum()) + + print(f"df_wsoi.index (1): {df_wsoi.index}") + + print("---(1):") + print(df_wsoi.head()) + + df_wsoi = df_wsoi[["timestamp", "tpw_value"]] + + df_wsoi.index = pd.to_datetime(df_wsoi.timestamp) + df_wsoi = df_wsoi.drop(columns=["timestamp"]) + + df_wsoi = df_wsoi.sort_index() + + print("---(2):") + print(df_wsoi.head(80)) + + df_wsoi = hourly_average_with_nan_handling(df_wsoi) + + print(f"df_wsoi.index (2): {df_wsoi.index}") + + print("---(3):") + print(df_wsoi.head(30)) + + print(df_wsoi["tpw_value"].isna().sum()) + df_wsoi.to_parquet(f"./data/goes16/wsoi/{wsoi_id}.parquet") + print("~~~") diff --git a/src/goes16/goes16_utils.py b/src/goes16/goes16_utils.py new file mode 100644 index 00000000..187df5ff --- /dev/null +++ b/src/goes16/goes16_utils.py @@ -0,0 +1,333 @@ +# Training: Python and GOES-R Imagery: Script 8 - Functions for download data from AWS +# ----------------------------------------------------------------------------------------------------------- +# Required modules +import colorsys # To make convertion of colormaps +import math # Mathematical functions +import os # Miscellaneous operating system interfaces +from datetime import datetime # Basic Dates and time types + +import boto3 # Amazon Web Services (AWS) SDK for Python +import numpy as np # Import the Numpy package +from botocore import UNSIGNED # boto3 config +from botocore.config import Config # boto3 config +from osgeo import ( + gdal, # Python bindings for GDAL + osr, # Python bindings for GDAL +) + +# from netCDF4 import Dataset # Read / Write NetCDF4 files +# import matplotlib.pyplot as plt # Plotting library +# import cartopy, cartopy.crs as ccrs # Plot maps +##import sys +# from datetime import timedelta, date, datetime # Manipulate dates + + +# ----------------------------------------------------------------------------------------------------------- +def loadCPT(path): + try: + f = open(path) + except FileNotFoundError as e: + print(f"File {path} not found: {e}") + return None + + lines = f.readlines() + + f.close() + + x = np.array([]) + r = np.array([]) + g = np.array([]) + b = np.array([]) + + colorModel = "RGB" + + for line in lines: + ls = line.split() + if line[0] == "#": + if ls[-1] == "HSV": + colorModel = "HSV" + continue + else: + continue + if ls[0] == "B" or ls[0] == "F" or ls[0] == "N": + pass + else: + x = np.append(x, float(ls[0])) + r = np.append(r, float(ls[1])) + g = np.append(g, float(ls[2])) + b = np.append(b, float(ls[3])) + xtemp = float(ls[4]) + rtemp = float(ls[5]) + gtemp = float(ls[6]) + btemp = float(ls[7]) + + x = np.append(x, xtemp) + r = np.append(r, rtemp) + g = np.append(g, gtemp) + b = np.append(b, btemp) + + if colorModel == "HSV": + for i in range(r.shape[0]): + rr, gg, bb = colorsys.hsv_to_rgb(r[i] / 360.0, g[i], b[i]) + r[i] = rr + g[i] = gg + b[i] = bb + + if colorModel == "RGB": + r = r / 255.0 + g = g / 255.0 + b = b / 255.0 + + xNorm = (x - x[0]) / (x[-1] - x[0]) + + red = [] + blue = [] + green = [] + + for i in range(len(x)): + red.append([xNorm[i], r[i], r[i]]) + green.append([xNorm[i], g[i], g[i]]) + blue.append([xNorm[i], b[i], b[i]]) + + colorDict = {"red": red, "green": green, "blue": blue} + + return colorDict + + +# ----------------------------------------------------------------------------------------------------------- +def download_CMI(yyyymmddhhmn, band, path_dest): + os.makedirs(path_dest, exist_ok=True) + + year = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%Y") + day_of_year = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%j") + hour = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%H") + min = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%M") + + # AMAZON repository information + # https://noaa-goes16.s3.amazonaws.com/index.html + bucket_name = "noaa-goes16" + product_name = "ABI-L2-CMIPF" + + # Initializes the S3 client + s3_client = boto3.client("s3", config=Config(signature_version=UNSIGNED)) + # ----------------------------------------------------------------------------------------------------------- + # File structure + prefix = f"{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6C{int(band):02.0f}_G16_s{year}{day_of_year}{hour}{min}" + + # Seach for the file on the server + s3_result = s3_client.list_objects_v2( + Bucket=bucket_name, Prefix=prefix, Delimiter="/" + ) + + # ----------------------------------------------------------------------------------------------------------- + # Check if there are files available + if "Contents" not in s3_result: + # There are no files + print(f"No files found for the date: {yyyymmddhhmn}, Band-{band}") + return -1 + else: + # There are files + for obj in s3_result["Contents"]: + key = obj["Key"] + # Print the file name + file_name = key.split("/")[-1].split(".")[0] + + # Download the file + if os.path.exists(f"{path_dest}/{file_name}.nc"): + print(f"File {path_dest}/{file_name}.nc exists") + else: + print(f"Downloading file {path_dest}/{file_name}.nc") + s3_client.download_file(bucket_name, key, f"{path_dest}/{file_name}.nc") + return f"{file_name}" + + +s3_client = boto3.client("s3", config=Config(signature_version=UNSIGNED)) + + +# ----------------------------------------------------------------------------------------------------------- +def download_PROD(yyyymmddhhmn, product_name, path_dest): + # os.makedirs(path_dest, exist_ok=True) + + year = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%Y") + day_of_year = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%j") + hour = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%H") + min = datetime.strptime(yyyymmddhhmn, "%Y%m%d%H%M").strftime("%M") + + # AMAZON repository information + # https://noaa-goes16.s3.amazonaws.com/index.html + bucket_name = "noaa-goes16" + + # Initializes the S3 client + # s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) + + # ----------------------------------------------------------------------------------------------------------- + # File structure + prefix = f"{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6_G16_s{year}{day_of_year}{hour}{min}" + + # Seach for the file on the server + s3_result = s3_client.list_objects_v2( + Bucket=bucket_name, Prefix=prefix, Delimiter="/" + ) + + # ----------------------------------------------------------------------------------------------------------- + # Check if there are files available + if "Contents" not in s3_result: + # There are no files + print(f"No files found for the date: {yyyymmddhhmn}, Product: {product_name}") + return -1 + else: + # There are files + for obj in s3_result["Contents"]: + key = obj["Key"] + # Print the file name + file_name = key.split("/")[-1].split(".")[0] + + # print(f'File name: {file_name}') + + # Download the file + if os.path.exists(f"{path_dest}/{file_name}.nc"): + print(f"File {path_dest}/{file_name}.nc exists") + else: + # print(f'Downloading file {path_dest}/{file_name}.nc') + s3_client.download_file(bucket_name, key, f"{path_dest}/{file_name}.nc") + return f"{file_name}" + + +# ----------------------------------------------------------------------------------------------------------- +def download_GLM(yyyymmddhhmnss, path_dest): + os.makedirs(path_dest, exist_ok=True) + + year = datetime.strptime(yyyymmddhhmnss, "%Y%m%d%H%M%S").strftime("%Y") + day_of_year = datetime.strptime(yyyymmddhhmnss, "%Y%m%d%H%M%S").strftime("%j") + hour = datetime.strptime(yyyymmddhhmnss, "%Y%m%d%H%M%S").strftime("%H") + min = datetime.strptime(yyyymmddhhmnss, "%Y%m%d%H%M%S").strftime("%M") + seg = datetime.strptime(yyyymmddhhmnss, "%Y%m%d%H%M%S").strftime("%S") + + # AMAZON repository information + # https://noaa-goes16.s3.amazonaws.com/index.html + bucket_name = "noaa-goes16" + + # Initializes the S3 client + s3_client = boto3.client("s3", config=Config(signature_version=UNSIGNED)) + # ----------------------------------------------------------------------------------------------------------- + # File structure + product_name = "GLM-L2-LCFA" + prefix = f"{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}_G16_s{year}{day_of_year}{hour}{min}{seg}" + + # Seach for the file on the server + s3_result = s3_client.list_objects_v2( + Bucket=bucket_name, Prefix=prefix, Delimiter="/" + ) + + # ----------------------------------------------------------------------------------------------------------- + # Check if there are files available + if "Contents" not in s3_result: + # There are no files + print(f"No files found for the date: {yyyymmddhhmnss}, Product-{product_name}") + return -1 + else: + # There are files + for obj in s3_result["Contents"]: + key = obj["Key"] + # Print the file name + file_name = key.split("/")[-1].split(".")[0] + + # Download the file + if os.path.exists(f"{path_dest}/{file_name}.nc"): + print(f"File {path_dest}/{file_name}.nc exists") + else: + print(f"Downloading file {path_dest}/{file_name}.nc") + s3_client.download_file(bucket_name, key, f"{path_dest}/{file_name}.nc") + return f"{file_name}" + + +# ----------------------------------------------------------------------------------------------------------- +# Functions to convert lat / lon extent to array indices +def geo2grid(lat, lon, nc): + # Apply scale and offset + xscale, xoffset = nc.variables["x"].scale_factor, nc.variables["x"].add_offset + yscale, yoffset = nc.variables["y"].scale_factor, nc.variables["y"].add_offset + + x, y = latlon2xy(lat, lon) + col = (x - xoffset) / xscale + lin = (y - yoffset) / yscale + return int(lin), int(col) + + +def latlon2xy(lat, lon): + # goes_imagery_projection:semi_major_axis + req = 6378137 # meters + # goes_imagery_projection:inverse_flattening + # goes_imagery_projection:semi_minor_axis + rpol = 6356752.31414 # meters + e = 0.0818191910435 + # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis + H = 42164160 # meters + # goes_imagery_projection: longitude_of_projection_origin + lambda0 = -1.308996939 + + # Convert to radians + latRad = lat * (math.pi / 180) + lonRad = lon * (math.pi / 180) + + # (1) geocentric latitude + Phi_c = math.atan(((rpol * rpol) / (req * req)) * math.tan(latRad)) + # (2) geocentric distance to the point on the ellipsoid + rc = rpol / (math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) + # (3) sx + sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0)) + # (4) sy + sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0) + # (5) + sz = rc * math.sin(Phi_c) + + # x,y + x = math.asin((-sy) / math.sqrt((sx * sx) + (sy * sy) + (sz * sz))) + y = math.atan(sz / sx) + + return x, y + + +# Function to convert lat / lon extent to GOES-16 extents +def convertExtent2GOESProjection(extent): + # GOES-16 viewing point (satellite position) height above the earth + GOES16_HEIGHT = 35786023.0 + # GOES-16 longitude position + + a, b = latlon2xy(extent[1], extent[0]) + c, d = latlon2xy(extent[3], extent[2]) + return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT) + + +# ----------------------------------------------------------------------------------------------------------- +# Function to reproject the data +def reproject(file_name, ncfile, array, extent, undef): + # Read the original file projection and configure the output projection + source_prj = osr.SpatialReference() + source_prj.ImportFromProj4(ncfile.GetProjectionRef()) + + target_prj = osr.SpatialReference() + target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") + + # Reproject the data + GeoT = ncfile.GetGeoTransform() + driver = gdal.GetDriverByName("MEM") + raw = driver.Create("raw", array.shape[0], array.shape[1], 1, gdal.GDT_Float32) + raw.SetGeoTransform(GeoT) + raw.GetRasterBand(1).WriteArray(array) + + # Define the parameters of the output file + kwargs = { + "format": "netCDF", + "srcSRS": source_prj, + "dstSRS": target_prj, + "outputBounds": (extent[0], extent[3], extent[2], extent[1]), + "outputBoundsSRS": target_prj, + "outputType": gdal.GDT_Float32, + "srcNodata": undef, + "dstNodata": "nan", + "resampleAlg": gdal.GRA_NearestNeighbour, + } + + # Write the reprojected file on disk + gdal.Warp(file_name, raw, **kwargs) diff --git a/src/goes16/goes16_visualize_data.py b/src/goes16/goes16_visualize_data.py new file mode 100644 index 00000000..70fc4492 --- /dev/null +++ b/src/goes16/goes16_visualize_data.py @@ -0,0 +1,87 @@ +import cartopy.crs as ccrs +import cartopy.feature as cfeature +import matplotlib.pyplot as plt +import netCDF4 as nc +import numpy as np + + +# Function to visualize the GOES-16 full-disk data +def visualize_goes16_file(file_path, save_path=None): + # Open the NetCDF file + dataset = nc.Dataset(file_path) + + # Extract data: we assume the variable of interest is 'Rad' (radiance), adjust if needed + radiance = dataset.variables["Rad"][:] + + # Retrieve GOES-16 projection info and coordinates + dataset.variables["goes_imager_projection"].perspective_point_height + scale_x = dataset.variables["x"].scale_factor + offset_x = dataset.variables["x"].add_offset + scale_y = dataset.variables["y"].scale_factor + offset_y = dataset.variables["y"].add_offset + + # Create coordinate arrays + x = dataset.variables["x"][:] * scale_x + offset_x + y = dataset.variables["y"][:] * scale_y + offset_y + X, Y = np.meshgrid(x, y) + + # GOES-16 parameters for the satellite projection + sat_height = dataset.variables["goes_imager_projection"].perspective_point_height + central_lon = dataset.variables[ + "goes_imager_projection" + ].longitude_of_projection_origin + dataset.variables["goes_imager_projection"].latitude_of_projection_origin + + # Close the NetCDF file + dataset.close() + + # Create a figure for plotting + plt.figure(figsize=(12, 8)) + + # Set up Cartopy projection + ax = plt.axes( + projection=ccrs.Geostationary( + central_longitude=central_lon, satellite_height=sat_height + ) + ) + + # Plot the radiance data + plt.pcolormesh( + X, + Y, + radiance, + transform=ccrs.Geostationary(), + cmap="gray", + vmin=np.nanmin(radiance), + vmax=np.nanmax(radiance), + ) + + # Add features such as coastlines and borders for reference + ax.add_feature(cfeature.COASTLINE, linewidth=0.5) + ax.add_feature(cfeature.BORDERS, linewidth=0.5) + + # Add a colorbar for the radiance data + plt.colorbar(label="Radiance") + + # Set title + plt.title("GOES-16 Full Disk Radiance Visualization") + + # Show the plot + plt.show() + + # Save the figure as an image file (if a save_path is provided) + if save_path: + plt.savefig(save_path, dpi=300, bbox_inches="tight") + print(f"Image saved as {save_path}") + + +if __name__ == "__main__": + # Example file path to a downloaded GOES-16 full disk file (replace with the correct file path) + file_path = "./goes16_data/OR_ABI-L1b-RadF-M6C10_G16_s20233222350206_e20233222359526_c20233222359549.nc" + # file_path = input("Enter the GOES16 full disk filename: ") + + # Provide the save path for the image (adjust the filename and extension as needed) + save_image_path = "goes16_full_disk_image.png" + + # Call the visualization function + visualize_goes16_file(file_path, save_path=save_image_path) diff --git a/src/goes16/main_goes16_features.py b/src/goes16/main_goes16_features.py new file mode 100644 index 00000000..a1f156cb --- /dev/null +++ b/src/goes16/main_goes16_features.py @@ -0,0 +1,102 @@ +import argparse +from pathlib import Path + +from config import globals +from goes16.features import ( + derivada_temporal_fluxo_ascendente, + glaciacao_topo_nuvem, + gradiente_vapor_agua, + profundidade_nuvens, + proxy_estabilidade, + temperatura_topo_nuvem, + textura_local_profundidade, +) +from goes16.utils import build_channel_paths_by_year, build_feature_paths_by_year + +FEATURES_ROOT = Path(globals.GOES16_FEATURES_DIR) + + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--pn", action="store_true") + parser.add_argument("--gtn", action="store_true") + parser.add_argument("--fa", action="store_true") + parser.add_argument("--wv_grad", action="store_true") + parser.add_argument("--li_proxy", action="store_true") + parser.add_argument("--toct", action="store_true") + parser.add_argument("--pn_std", action="store_true") + parser.add_argument("--verbose", action="store_true") + args = parser.parse_args() + + if args.pn: + if args.verbose: + print("Feature: pn") + for c09, c13 in zip( + build_channel_paths_by_year("C09"), build_channel_paths_by_year("C13") + ): + if args.verbose: + print(f"Processing C09: {c09}, C13: {c13}") + year = c09.parent.name + profundidade_nuvens(str(c09), str(c13), str(FEATURES_ROOT / "pn" / year)) + + if args.gtn: + if args.verbose: + print("Feature: gtn") + for c11, c14, c15 in zip( + build_channel_paths_by_year("C11"), + build_channel_paths_by_year("C14"), + build_channel_paths_by_year("C15"), + ): + year = c11.parent.name + glaciacao_topo_nuvem( + str(c11), str(c14), str(c15), str(FEATURES_ROOT / "gtn" / year) + ) + + if args.fa: + if args.verbose: + print("Feature: fa") + for c13 in build_channel_paths_by_year("C13"): + year = c13.parent.name + derivada_temporal_fluxo_ascendente( + str(c13), str(FEATURES_ROOT / "fa" / year) + ) + + if args.wv_grad: + if args.verbose: + print("Feature: wv_grad") + for c09, c08 in zip( + build_channel_paths_by_year("C09"), build_channel_paths_by_year("C08") + ): + year = c09.parent.name + gradiente_vapor_agua( + str(c09), str(c08), str(FEATURES_ROOT / "wv_grad" / year) + ) + + if args.li_proxy: + if args.verbose: + print("Feature: li_proxy") + for c14, c13 in zip( + build_channel_paths_by_year("C14"), build_channel_paths_by_year("C13") + ): + year = c14.parent.name + proxy_estabilidade( + str(c14), str(c13), str(FEATURES_ROOT / "li_proxy" / year) + ) + + if args.toct: + if args.verbose: + print("Feature: toct") + for c13 in build_channel_paths_by_year("C13"): + year = c13.parent.name + temperatura_topo_nuvem(str(c13), str(FEATURES_ROOT / "toct" / year)) + + if args.pn_std: + if args.verbose: + print("Feature: pn_std") + for pn in build_feature_paths_by_year("profundidade_nuvens"): + year = pn.parent.name + textura_local_profundidade(str(pn), str(FEATURES_ROOT / "pn_std" / year)) + + +if __name__ == "__main__": + main() diff --git a/src/goes16/processing_data.py b/src/goes16/processing_data.py index 2f9f4341..81cf22f0 100644 --- a/src/goes16/processing_data.py +++ b/src/goes16/processing_data.py @@ -1,92 +1,101 @@ # -*- coding: utf-8 -*- -#----------------------------------------------------------------------------------------------------------------------------------- -''' +# ----------------------------------------------------------------------------------------------------------------------------------- +""" Description: Process the GOES-16/17 data Author: Joao Henry Huaman Chinchay E-mail: joaohenry23@gmail.com Created date: Mar 23, 2020 Modification date: Jul 23, 2023 -''' -#----------------------------------------------------------------------------------------------------------------------------------- -import numpy as np -from netCDF4 import Dataset, num2date -from pyproj import Proj +""" + +# ----------------------------------------------------------------------------------------------------------------------------------- import datetime import glob -import os -import warnings import re -warnings.filterwarnings('ignore') +import warnings -#----------------------------------------------------------------------------------------------------------------------------------- +import numpy as np +from netCDF4 import Dataset, num2date +from pyproj import Proj -class GOES(): +warnings.filterwarnings("ignore") +# ----------------------------------------------------------------------------------------------------------------------------------- + +class GOES: def __init__(self, attrs): for key in attrs.keys(): setattr(self, key, attrs[key]) - def __str__(self): attr = [] classes = [] var = [] for key in list(self.__dict__.keys()): - - if isinstance(self.__dict__[key],np.ndarray): - var.append(' {:29} ({}) {}'.format(key, ', '.join(np.array(self.__dict__[key].shape).astype('str')), str(self.__dict__[key].dtype))) - - elif isinstance(self.__dict__[key],GOES): - classes.append(' {:29} {}'.format(key, self.__dict__[key].__class__)) - - elif isinstance(self.__dict__[key],str): - if len(self.__dict__[key])>50 : - attrib = '{:.48}...'.format(self.__dict__[key]) + if isinstance(self.__dict__[key], np.ndarray): + var.append( + " {:29} ({}) {}".format( + key, + ", ".join(np.array(self.__dict__[key].shape).astype("str")), + str(self.__dict__[key].dtype), + ) + ) + + elif isinstance(self.__dict__[key], GOES): + classes.append(" {:29} {}".format(key, self.__dict__[key].__class__)) + + elif isinstance(self.__dict__[key], str): + if len(self.__dict__[key]) > 50: + attrib = "{:.48}...".format(self.__dict__[key]) else: - attrib = '{}'.format(self.__dict__[key]) - attr.append(' {:30}: {}'.format(key, attrib)) + attrib = "{}".format(self.__dict__[key]) + attr.append(" {:30}: {}".format(key, attrib)) - elif isinstance(self.__dict__[key],tuple): - attr.append(' {:30}: ({})'.format(key, ', '.join(self.__dict__[key]))) + elif isinstance(self.__dict__[key], tuple): + attr.append(" {:30}: ({})".format(key, ", ".join(self.__dict__[key]))) else: - attr.append(' {:30}: {}'.format(key, self.__dict__[key])) - - return '\n'.join([str(self.__class__)]+['']+['Keys:']+attr+classes+var+['']) - + attr.append(" {:30}: {}".format(key, self.__dict__[key])) + return "\n".join( + [str(self.__class__)] + [""] + ["Keys:"] + attr + classes + var + [""] + ) def __repr__(self): attr = [] classes = [] var = [] for key in list(self.__dict__.keys()): - - if isinstance(self.__dict__[key],np.ndarray): - var.append(' {:29} ({}) {}'.format(key, ', '.join(np.array(self.__dict__[key].shape).astype('str')), str(self.__dict__[key].dtype))) - - elif isinstance(self.__dict__[key],GOES): - classes.append(' {:29} {}'.format(key, self.__dict__[key].__class__)) - - elif isinstance(self.__dict__[key],str): - if len(self.__dict__[key])>50 : - attrib = '{:.48}...'.format(self.__dict__[key]) + if isinstance(self.__dict__[key], np.ndarray): + var.append( + " {:29} ({}) {}".format( + key, + ", ".join(np.array(self.__dict__[key].shape).astype("str")), + str(self.__dict__[key].dtype), + ) + ) + + elif isinstance(self.__dict__[key], GOES): + classes.append(" {:29} {}".format(key, self.__dict__[key].__class__)) + + elif isinstance(self.__dict__[key], str): + if len(self.__dict__[key]) > 50: + attrib = "{:.48}...".format(self.__dict__[key]) else: - attrib = '{}'.format(self.__dict__[key]) - attr.append(' {:30}: {}'.format(key, attrib)) + attrib = "{}".format(self.__dict__[key]) + attr.append(" {:30}: {}".format(key, attrib)) - elif isinstance(self.__dict__[key],tuple): - attr.append(' {:30}: ({})'.format(key, ', '.join(self.__dict__[key]))) + elif isinstance(self.__dict__[key], tuple): + attr.append(" {:30}: ({})".format(key, ", ".join(self.__dict__[key]))) else: - attr.append(' {:30}: {}'.format(key, self.__dict__[key])) - - return '\n'.join([str(self.__class__)]+['']+['Keys:']+attr+classes+var+['']) - + attr.append(" {:30}: {}".format(key, self.__dict__[key])) + return "\n".join( + [str(self.__class__)] + [""] + ["Keys:"] + attr + classes + var + [""] + ) def refl_fact_to_refl(self, Lons, Lats, MinCosTheta=0.0, fmt=np.float32): - - ''' + """ It converts reflectance factor to reflectance. @@ -109,41 +118,53 @@ def refl_fact_to_refl(self, Lons, Lats, MinCosTheta=0.0, fmt=np.float32): reflectance : object reflectance. - ''' - - if self.long_name == 'ABI L2+ Cloud and Moisture Imagery reflectance factor': + """ + if self.long_name == "ABI L2+ Cloud and Moisture Imagery reflectance factor": try: assert self.data.shape == Lons.data.shape == Lats.data.shape except AssertionError: - print('\n\tShape of Lon, Lat and data do not match.\n') + print("\n\tShape of Lon, Lat and data do not match.\n") return else: - dict_Field = {'long_name':'ABI L2+ Cloud and Moisture Imagery reflectance', 'standard_name':'toa_lambertian_equivalent_albedo', - 'units':1, 'undef':np.nan, 'axis':'YX', 't':self.t, 'time_bounds':self.time_bounds, 'pixels_limits':self.pixels_limits, 'dimensions':('y','x'), - 'data':self.data/cosine_of_solar_zenith_angle(Lons.data, Lats.data, self.t.data, MinCosTheta=MinCosTheta, fmt=fmt).data} - return GOES(dict_Field); - + dict_Field = { + "long_name": "ABI L2+ Cloud and Moisture Imagery reflectance", + "standard_name": "toa_lambertian_equivalent_albedo", + "units": 1, + "undef": np.nan, + "axis": "YX", + "t": self.t, + "time_bounds": self.time_bounds, + "pixels_limits": self.pixels_limits, + "dimensions": ("y", "x"), + "data": self.data + / cosine_of_solar_zenith_angle( + Lons.data, + Lats.data, + self.t.data, + MinCosTheta=MinCosTheta, + fmt=fmt, + ).data, + } + return GOES(dict_Field) else: - print('\n\tIt is not possible convert Data because is not ABI L2+ Cloud and Moisture Imagery reflectance factor\n') - - + print( + "\n\tIt is not possible convert Data because is not ABI L2+ Cloud and Moisture Imagery reflectance factor\n" + ) def keys(self): return list(self.__dict__.keys()) -#----------------------------------------------------------------------------------------------------------------------------------- +# ----------------------------------------------------------------------------------------------------------------------------------- -class open_dataset(): +class open_dataset: def __init__(self, File): self.ds = Dataset(File) - def attribute(self, parameter): - - ''' + """ It gets attribute from file. @@ -157,22 +178,19 @@ def attribute(self, parameter): ------- Value of attribute - ''' + """ ds = self.ds try: assert parameter in ds.ncattrs() except AssertionError: - print('\n\tParameter not found, check if it is an attribute\n') + print("\n\tParameter not found, check if it is an attribute\n") return else: - return getattr(ds,parameter); - - + return getattr(ds, parameter) def dimension(self, parameter): - - ''' + """ It gets dimension from file. @@ -187,24 +205,20 @@ def dimension(self, parameter): parameter: str Value of dimension - ''' + """ ds = self.ds try: assert parameter in ds.dimensions.keys() except AssertionError: - print('\n\tParameter not found, check if it is a dimension\n') + print("\n\tParameter not found, check if it is a dimension\n") return else: parameter = ds.dimensions[parameter] - return GOES({'name':parameter.name, 'size':parameter.size}); - - - + return GOES({"name": parameter.name, "size": parameter.size}) def group(self, parameter): - - ''' + """ It gets group from file. @@ -219,24 +233,19 @@ def group(self, parameter): parameter: str Value of group - ''' + """ ds = self.ds try: assert parameter in ds.groups.keys() except AssertionError: - print('\n\tParameter not found, check if it is a group\n') + print("\n\tParameter not found, check if it is a group\n") return else: - return ds.groups[parameter]; - - - - + return ds.groups[parameter] def variable(self, parameter): - - ''' + """ It gets variable from file. @@ -251,80 +260,109 @@ def variable(self, parameter): parameter: str Value of variable - ''' + """ ds = self.ds try: assert parameter in ds.variables.keys() except AssertionError: - print('\n\tParameter not found, check if it is a variable\n') + print("\n\tParameter not found, check if it is a variable\n") return else: try: - assert ds.variables[parameter].dimensions != ('y','x') #(ds.variables[parameter].ndim == 0) or (ds.variables[parameter].ndim == 1) + assert ds.variables[parameter].dimensions != ( + "y", + "x", + ) # (ds.variables[parameter].ndim == 0) or (ds.variables[parameter].ndim == 1) except AssertionError: - print('\n\tParameter is not a variable\n') + print("\n\tParameter is not a variable\n") return else: parameter = ds.variables[parameter] fmt = parameter[:].dtype - data = np.where(parameter[:].mask==True, np.nan, parameter[:].data) + data = np.where(parameter[:].mask, np.nan, parameter[:].data) IsDateTime = False - if 'units' in parameter.ncattrs(): - if 'seconds since' in parameter.units: - data = num2date(data, parameter.units, 'standard', only_use_cftime_datetimes=False, only_use_python_datetimes=True) + if "units" in parameter.ncattrs(): + if "seconds since" in parameter.units: + data = num2date( + data, + parameter.units, + "standard", + only_use_cftime_datetimes=False, + only_use_python_datetimes=True, + ) fmt = object data = np.array(data) IsDateTime = True - #if isinstance(data, np.ma.core.MaskedArray): + # if isinstance(data, np.ma.core.MaskedArray): # data = np.array(data) - #if isinstance(data, datetime.datetime): + # if isinstance(data, datetime.datetime): # data = np.array(data) else: - if 'long_name' in parameter.ncattrs(): - if 'seconds since' in parameter.long_name or 'time' in parameter.long_name: - if '(' and ')' in parameter.long_name: - units = 'seconds since '+re.findall(r'\(.+?\)',parameter.long_name)[0][1:-1] + if "long_name" in parameter.ncattrs(): + if ( + "seconds since" in parameter.long_name + or "time" in parameter.long_name + ): + if "(" and ")" in parameter.long_name: + units = ( + "seconds since " + + re.findall(r"\(.+?\)", parameter.long_name)[0][ + 1:-1 + ] + ) else: - units = 'seconds since 2000-01-01 12:00:00' - data = num2date(data, units, 'standard', only_use_cftime_datetimes=False, only_use_python_datetimes=True) + units = "seconds since 2000-01-01 12:00:00" + data = num2date( + data, + units, + "standard", + only_use_cftime_datetimes=False, + only_use_python_datetimes=True, + ) fmt = object data = np.array(data) IsDateTime = True - #if isinstance(data, np.ma.core.MaskedArray): + # if isinstance(data, np.ma.core.MaskedArray): # data = np.array(data) - #if isinstance(data, datetime.datetime): + # if isinstance(data, datetime.datetime): # data = np.array(data) dict = {} for key in parameter.__dict__.keys(): - dict.update({key: getattr(parameter,key)}) + dict.update({key: getattr(parameter, key)}) - if IsDateTime == True: - if 'units' in dict: - del dict['units'] + if IsDateTime: + if "units" in dict: + del dict["units"] - for item in ['_Unsigned','scale_factor','add_offset','_FillValue']: + for item in ["_Unsigned", "scale_factor", "add_offset", "_FillValue"]: if item in dict: del dict[item] - dict.update({'dimensions': getattr(parameter,'dimensions')}) + dict.update({"dimensions": getattr(parameter, "dimensions")}) if data.ndim == 0: data = data.reshape([1]) - dict.update({'data':data[0]}) + dict.update({"data": data[0]}) else: - dict.update({'data':data.astype(fmt)}) - - return GOES(dict); - - - - - def image(self, parameter, lonlat='center', domain=None, domain_in_pixels=None, up_level=False, nan_mask=None, delta_index=4, fmt=np.float32): - - ''' + dict.update({"data": data.astype(fmt)}) + + return GOES(dict) + + def image( + self, + parameter, + lonlat="center", + domain=None, + domain_in_pixels=None, + up_level=False, + nan_mask=None, + delta_index=4, + fmt=np.float32, + ): + """ It gets image from dataset with its longitude and latitude information. @@ -343,7 +381,7 @@ def image(self, parameter, lonlat='center', domain=None, domain_in_pixels=None, List with coordinates of domain that you want to select. Example: domain = [LLLon, URLon, LLLat, URLat] - + Where: LLLon : float @@ -364,7 +402,7 @@ def image(self, parameter, lonlat='center', domain=None, domain_in_pixels=None, you want to select. Example: domain_in_pixels = [XMIN, XMAX, YMIN, YMAX] - + Where: XMIN : int @@ -414,329 +452,484 @@ def image(self, parameter, lonlat='center', domain=None, domain_in_pixels=None, Lats : object A scalar 2-D array with latitude of Field. - ''' + """ ds = self.ds try: assert parameter in ds.variables.keys() except AssertionError: - print('\n\tParameter not found, check if it is an image\n') + print("\n\tParameter not found, check if it is an image\n") return else: - try: - assert ('y','x') == ds.variables[parameter].dimensions + assert ("y", "x") == ds.variables[parameter].dimensions except AssertionError: - print("\n\t{} is not a valid product because have not ('y','x') dimensions\n".format(parameter)) + print( + "\n\t{} is not a valid product because have not ('y','x') dimensions\n".format( + parameter + ) + ) return else: - ProcessingLevel = ds.processing_level.split(' ')[-1] + ProcessingLevel = ds.processing_level.split(" ")[-1] PlatformID = ds.platform_ID - SatHeight = ds.variables['goes_imager_projection'].perspective_point_height - SatLon = ds.variables['goes_imager_projection'].longitude_of_projection_origin - SatSweep = ds.variables['goes_imager_projection'].sweep_angle_axis - - X = ds.variables['x'] - Y = ds.variables['y'] + SatHeight = ds.variables[ + "goes_imager_projection" + ].perspective_point_height + SatLon = ds.variables[ + "goes_imager_projection" + ].longitude_of_projection_origin + SatSweep = ds.variables["goes_imager_projection"].sweep_angle_axis + + X = ds.variables["x"] + Y = ds.variables["y"] xsize = X.shape[0] ysize = Y.shape[0] - #------------------------------------------------------------------ + # ------------------------------------------------------------------ # gets attributes of Field - dict_Field = {'long_name':None, 'standard_name':None, - 'units':None, 'undef':np.nan, 'pixels_limits':None, 'axis':'YX', - 't':None, 'time_bounds':None, 'dimensions':('y','x'), 'data':None} - - dict_Field['t'] = self.variable('t') - dict_Field['time_bounds'] = self.variable('time_bounds') - - #------------------------------------------------------------------ + dict_Field = { + "long_name": None, + "standard_name": None, + "units": None, + "undef": np.nan, + "pixels_limits": None, + "axis": "YX", + "t": None, + "time_bounds": None, + "dimensions": ("y", "x"), + "data": None, + } + + dict_Field["t"] = self.variable("t") + dict_Field["time_bounds"] = self.variable("time_bounds") + + # ------------------------------------------------------------------ for item in ds.variables[parameter].ncattrs(): if item in dict_Field.keys(): - dict_Field[item] = getattr(ds.variables[parameter],item) + dict_Field[item] = getattr(ds.variables[parameter], item) - #------------------------------------------------------------------ + # ------------------------------------------------------------------ if isinstance(domain, list) or isinstance(domain, np.ndarray): - LLLon, URLon, LLLat, URLat = domain - Lons, Lats = get_lonlat(X[::delta_index].astype(fmt), Y[::delta_index].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) - - xpixmin, xpixmax, ypixmin, ypixmax = find_pixels_of_region(Lons, Lats, LLLon, URLon, LLLat, URLat) + Lons, Lats = get_lonlat( + X[::delta_index].astype(fmt), + Y[::delta_index].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) + + xpixmin, xpixmax, ypixmin, ypixmax = find_pixels_of_region( + Lons, Lats, LLLon, URLon, LLLat, URLat + ) del Lons, Lats - xini = xpixmin*delta_index - xfin = (xpixmax+1)*delta_index -1 - yini = ypixmin*delta_index - yfin = (ypixmax+1)*delta_index -1 + xini = xpixmin * delta_index + xfin = (xpixmax + 1) * delta_index - 1 + yini = ypixmin * delta_index + yfin = (ypixmax + 1) * delta_index - 1 - #- - - - - - - - - - - - - - - - - - - + # - - - - - - - - - - - - - - - - - - - # add and decrease pixels to improve the search of pixels of interest region if xini - delta_index < 0: xini = 0 else: xini = xini - delta_index - - if xfin + delta_index > xsize-1: - xfin = xsize-1 + if xfin + delta_index > xsize - 1: + xfin = xsize - 1 else: xfin = xfin + delta_index - - if yini - delta_index < 0: yini = 0 else: yini = yini - delta_index - - if yfin + delta_index > ysize-1: - yfin = ysize-1 + if yfin + delta_index > ysize - 1: + yfin = ysize - 1 else: yfin = yfin + delta_index - #- - - - - - - - - - - - - - - - - - - - - Lons, Lats = get_lonlat(X[xini:xfin+1].astype(fmt), Y[yini:yfin+1].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) - - xpixmin, xpixmax, ypixmin, ypixmax = find_pixels_of_region(Lons, Lats, LLLon, URLon, LLLat, URLat) - Limits = np.array([xini+xpixmin, xini+xpixmax, yini+ypixmin, yini+ypixmax]) - dict_Field['pixels_limits'] = Limits - - - if lonlat == 'center': + # - - - - - - - - - - - - - - - - - - - + + Lons, Lats = get_lonlat( + X[xini : xfin + 1].astype(fmt), + Y[yini : yfin + 1].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) + + xpixmin, xpixmax, ypixmin, ypixmax = find_pixels_of_region( + Lons, Lats, LLLon, URLon, LLLat, URLat + ) + Limits = np.array( + [xini + xpixmin, xini + xpixmax, yini + ypixmin, yini + ypixmax] + ) + dict_Field["pixels_limits"] = Limits + + if lonlat == "center": del X, Y dict_Lons = Lons dict_Lats = Lats - dict_Lons.data = np.ascontiguousarray(Lons.data[ypixmin:ypixmax+1,xpixmin:xpixmax+1], dtype=fmt) - dict_Lats.data = np.ascontiguousarray(Lats.data[ypixmin:ypixmax+1,xpixmin:xpixmax+1], dtype=fmt) - - elif lonlat == 'corner': - Lons, Lats = get_lonlatcorner(X[xini+xpixmin:xini+xpixmax+1].astype(fmt), Y[yini+ypixmin:yini+ypixmax+1].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) + dict_Lons.data = np.ascontiguousarray( + Lons.data[ypixmin : ypixmax + 1, xpixmin : xpixmax + 1], + dtype=fmt, + ) + dict_Lats.data = np.ascontiguousarray( + Lats.data[ypixmin : ypixmax + 1, xpixmin : xpixmax + 1], + dtype=fmt, + ) + + elif lonlat == "corner": + Lons, Lats = get_lonlatcorner( + X[xini + xpixmin : xini + xpixmax + 1].astype(fmt), + Y[yini + ypixmin : yini + ypixmax + 1].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) del X, Y dict_Lons = Lons dict_Lats = Lats - - elif isinstance(domain_in_pixels, list) or isinstance(domain_in_pixels, np.ndarray): - + elif isinstance(domain_in_pixels, list) or isinstance( + domain_in_pixels, np.ndarray + ): xpixmin, xpixmax, ypixmin, ypixmax = domain_in_pixels Limits = np.array([xpixmin, xpixmax, ypixmin, ypixmax]) - dict_Field['pixels_limits'] = Limits - - if lonlat == 'center': - Lons, Lats = get_lonlat(X[xpixmin:xpixmax+1].astype(fmt), Y[ypixmin:ypixmax+1].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) + dict_Field["pixels_limits"] = Limits + + if lonlat == "center": + Lons, Lats = get_lonlat( + X[xpixmin : xpixmax + 1].astype(fmt), + Y[ypixmin : ypixmax + 1].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) del X, Y dict_Lons = Lons dict_Lats = Lats - elif lonlat == 'corner': - Lons, Lats = get_lonlatcorner(X[xpixmin:xpixmax+1].astype(fmt), Y[ypixmin:ypixmax+1].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) + elif lonlat == "corner": + Lons, Lats = get_lonlatcorner( + X[xpixmin : xpixmax + 1].astype(fmt), + Y[ypixmin : ypixmax + 1].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) del X, Y dict_Lons = Lons dict_Lats = Lats else: - - xpixmin, xpixmax, ypixmin, ypixmax = 0, xsize-1, 0, ysize-1 + xpixmin, xpixmax, ypixmin, ypixmax = 0, xsize - 1, 0, ysize - 1 Limits = np.array([xpixmin, xpixmax, ypixmin, ypixmax]) - dict_Field['pixels_limits'] = Limits - - if lonlat == 'center': - Lons, Lats = get_lonlat(X[:].astype(fmt), Y[:].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) + dict_Field["pixels_limits"] = Limits + + if lonlat == "center": + Lons, Lats = get_lonlat( + X[:].astype(fmt), + Y[:].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) del X, Y dict_Lons = Lons dict_Lats = Lats - elif lonlat == 'corner': - Lons, Lats = get_lonlatcorner(X[:].astype(fmt), Y[:].astype(fmt), PlatformID, SatLon, SatHeight, SatSweep, fmt=fmt) + elif lonlat == "corner": + Lons, Lats = get_lonlatcorner( + X[:].astype(fmt), + Y[:].astype(fmt), + PlatformID, + SatLon, + SatHeight, + SatSweep, + fmt=fmt, + ) del X, Y dict_Lons = Lons dict_Lats = Lats - #------------------------------------------------------------------ - - if up_level == True: + # ------------------------------------------------------------------ + if up_level: try: - assert ProcessingLevel == 'L1b' + assert ProcessingLevel == "L1b" except AssertionError: - print('\n\tWas not possible increase level of {} because is not L1b.\n'.format(parameter)) + print( + "\n\tWas not possible increase level of {} because is not L1b.\n".format( + parameter + ) + ) return else: - if ds.variables['band_id'][0].data < 7: - dict_Field['long_name'] = 'ABI L2+ Cloud and Moisture Imagery reflectance factor' - dict_Field['standard_name'] = 'toa_lambertian_equivalent_albedo_multiplied_by_cosine_solar_zenith_angle' - dict_Field['units'] = '1' - kappa = ds.variables['kappa0'][:] - Field = kappa*ds.variables[parameter][Limits[2]:Limits[3]+1,Limits[0]:Limits[1]+1].astype(dtype=fmt) + if ds.variables["band_id"][0].data < 7: + dict_Field["long_name"] = ( + "ABI L2+ Cloud and Moisture Imagery reflectance factor" + ) + dict_Field["standard_name"] = ( + "toa_lambertian_equivalent_albedo_multiplied_by_cosine_solar_zenith_angle" + ) + dict_Field["units"] = "1" + kappa = ds.variables["kappa0"][:] + Field = kappa * ds.variables[parameter][ + Limits[2] : Limits[3] + 1, Limits[0] : Limits[1] + 1 + ].astype(dtype=fmt) else: - dict_Field['long_name'] = 'ABI L2+ Cloud and Moisture Imagery brightness temperature' - dict_Field['standard_name'] = 'toa_brightness_temperature' - dict_Field['units'] = 'K' - planck_fk1 = ds.variables['planck_fk1'][:] - planck_fk2 = ds.variables['planck_fk2'][:] - planck_bc1 = ds.variables['planck_bc1'][:] - planck_bc2 = ds.variables['planck_bc2'][:] - Field = (planck_fk2/(np.log( (planck_fk1/ds.variables[parameter][Limits[2]:Limits[3]+1,Limits[0]:Limits[1]+1].astype(dtype=fmt)) +1 )) - planck_bc1)/planck_bc2 + dict_Field["long_name"] = ( + "ABI L2+ Cloud and Moisture Imagery brightness temperature" + ) + dict_Field["standard_name"] = "toa_brightness_temperature" + dict_Field["units"] = "K" + planck_fk1 = ds.variables["planck_fk1"][:] + planck_fk2 = ds.variables["planck_fk2"][:] + planck_bc1 = ds.variables["planck_bc1"][:] + planck_bc2 = ds.variables["planck_bc2"][:] + Field = ( + planck_fk2 + / ( + np.log( + ( + planck_fk1 + / ds.variables[parameter][ + Limits[2] : Limits[3] + 1, + Limits[0] : Limits[1] + 1, + ].astype(dtype=fmt) + ) + + 1 + ) + ) + - planck_bc1 + ) / planck_bc2 else: - dict_Field['long_name'] = ds.variables[parameter].long_name - dict_Field['standard_name'] = ds.variables[parameter].standard_name - dict_Field['units'] = ds.variables[parameter].units - Field = ds.variables[parameter][Limits[2]:Limits[3]+1,Limits[0]:Limits[1]+1].astype(dtype=fmt) - - #------------------------------------------------------------------ - - if lonlat == 'center': - Field = np.where((Field[:].mask==True)|(Lons.data==-999.99), np.nan, Field[:]) + dict_Field["long_name"] = ds.variables[parameter].long_name + dict_Field["standard_name"] = ds.variables[parameter].standard_name + dict_Field["units"] = ds.variables[parameter].units + Field = ds.variables[parameter][ + Limits[2] : Limits[3] + 1, Limits[0] : Limits[1] + 1 + ].astype(dtype=fmt) + + # ------------------------------------------------------------------ + + if lonlat == "center": + Field = np.where( + (Field[:].mask) | (Lons.data == -999.99), + np.nan, + Field[:], + ) Field = np.ascontiguousarray(Field, dtype=fmt) - dict_Field['data'] = Field - return GOES(dict_Field), dict_Lons, dict_Lats; - - elif lonlat == 'corner': - mask = np.where(Lons.data<-990.0, True, False) + dict_Field["data"] = Field + return GOES(dict_Field), dict_Lons, dict_Lats + elif lonlat == "corner": + mask = np.where(Lons.data < -990.0, True, False) mask = corner_size_to_center_size(mask) - Field = np.where((Field[:].mask==True)|(mask==True), np.nan, Field[:]) + Field = np.where((Field[:].mask) | (mask), np.nan, Field[:]) Field = np.ascontiguousarray(Field, dtype=fmt) - dict_Field['data'] = Field - return GOES(dict_Field), dict_Lons, dict_Lats; - + dict_Field["data"] = Field + return GOES(dict_Field), dict_Lons, dict_Lats else: - - if isinstance(nan_mask,np.ndarray): + if isinstance(nan_mask, np.ndarray): if Field[:].size == nan_mask.size: - Field = np.where((Field[:].mask==True)|(nan_mask==True), np.nan, Field[:]) + Field = np.where( + (Field[:].mask) | (nan_mask), + np.nan, + Field[:], + ) else: - print('The size of the nan_mask does not match the size of the returned image. Masking will not be done.') - Field = np.where((Field[:].mask==True), np.nan, Field[:]) + print( + "The size of the nan_mask does not match the size of the returned image. Masking will not be done." + ) + Field = np.where((Field[:].mask), np.nan, Field[:]) else: - Field = np.where((Field[:].mask==True), np.nan, Field[:]) + Field = np.where((Field[:].mask), np.nan, Field[:]) Field = np.ascontiguousarray(Field, dtype=fmt) - dict_Field['data'] = Field + dict_Field["data"] = Field dict_Lons = None dict_Lats = None - return GOES(dict_Field), None, None; - - - + return GOES(dict_Field), None, None def __str__(self): - ds = self.ds - attr = ['attribute:'] - dims = ['dimension:'] - var0D = ['variable:'] + attr = ["attribute:"] + dims = ["dimension:"] + var0D = ["variable:"] var1D = [] var2D = [] varMD = [] - image = ['image:'] - group = ['group:'] + image = ["image:"] + group = ["group:"] for item in ds.ncattrs(): - attrib = getattr(ds,item) - if len(attrib)>50 : - attrib = '{:.48}...'.format(attrib) - attr.append(' {:30}: {}'.format(item, attrib)) + attrib = getattr(ds, item) + if len(attrib) > 50: + attrib = "{:.48}...".format(attrib) + attr.append(" {:30}: {}".format(item, attrib)) for item in ds.dimensions.keys(): - dims.append(' {:50} ({})'.format(item, ds.dimensions[item].size)) + dims.append(" {:50} ({})".format(item, ds.dimensions[item].size)) for item in ds.variables.keys(): if ds.variables[item].ndim == 0: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var0D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var0D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 1: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var1D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var1D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 2: - if ds.variables[item].dimensions == ('y','x') : - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - image.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + if ds.variables[item].dimensions == ("y", "x"): + size = "({})".format(", ".join(ds.variables[item].dimensions)) + image.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) else: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var2D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var2D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim > 2: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - varMD.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + varMD.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) for item in ds.groups.keys(): - groups.append(' {:50}'.format(item)) - - return '\n'.join([str(self.__class__)]+['']+attr+['']+dims+['']+var0D+var1D+var2D+varMD+['']+image+['']+group+['']) - - + group.append(" {:50}".format(item)) + + return "\n".join( + [str(self.__class__)] + + [""] + + attr + + [""] + + dims + + [""] + + var0D + + var1D + + var2D + + varMD + + [""] + + image + + [""] + + group + + [""] + ) def __repr__(self): - ds = self.ds - attr = ['attribute:'] - dims = ['dimension:'] - var0D = ['variable:'] + attr = ["attribute:"] + dims = ["dimension:"] + var0D = ["variable:"] var1D = [] var2D = [] varMD = [] - image = ['image:'] - group = ['group:'] + image = ["image:"] + group = ["group:"] for item in ds.ncattrs(): - attrib = getattr(ds,item) - if len(attrib)>50 : - attrib = '{:.48}...'.format(attrib) - attr.append(' {:30}: {}'.format(item, attrib)) + attrib = getattr(ds, item) + if len(attrib) > 50: + attrib = "{:.48}...".format(attrib) + attr.append(" {:30}: {}".format(item, attrib)) for item in ds.dimensions.keys(): - dims.append(' {:50} ({})'.format(item, ds.dimensions[item].size)) + dims.append(" {:50} ({})".format(item, ds.dimensions[item].size)) for item in ds.variables.keys(): if ds.variables[item].ndim == 0: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var0D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var0D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 1: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var1D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var1D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 2: - if ds.variables[item].dimensions == ('y','x') : - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - image.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + if ds.variables[item].dimensions == ("y", "x"): + size = "({})".format(", ".join(ds.variables[item].dimensions)) + image.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) else: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var2D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var2D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim > 2: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - varMD.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + varMD.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) for item in ds.groups.keys(): - groups.append(' {:50}'.format(item)) - - return '\n'.join([str(self.__class__)]+['']+attr+['']+dims+['']+var0D+var1D+var2D+varMD+['']+image+['']+group+['']) - - + group.append(" {:50}".format(item)) + + return "\n".join( + [str(self.__class__)] + + [""] + + attr + + [""] + + dims + + [""] + + var0D + + var1D + + var2D + + varMD + + [""] + + image + + [""] + + group + + [""] + ) def keys(self): return list(self.__dict__.keys()) -#----------------------------------------------------------------------------------------------------------------------------------- +# ----------------------------------------------------------------------------------------------------------------------------------- -class open_mfdataset(): +class open_mfdataset: def __init__(self, FList): try: - assert isinstance(FList,list) + assert isinstance(FList, list) except AssertionError: - print('\n\tFList must be a list\n') + print("\n\tFList must be a list\n") return else: ds = [] for File in FList: try: - assert 'GLM' in File + assert "GLM" in File except AssertionError: - print('\n\topen_mfdataset just work with GLM files\n') + print("\n\topen_mfdataset just work with GLM files\n") return else: ds.append(Dataset(File)) @@ -744,12 +937,8 @@ def __init__(self, FList): self.ds = ds self.files = FList - - - def attribute(self, parameter): - - ''' + """ It gets attribute from file. @@ -763,25 +952,22 @@ def attribute(self, parameter): ------- Value of attribute - ''' + """ mfparameter = [] for idx in range(len(self.ds)): ds = self.ds[idx] try: assert parameter in ds.ncattrs() - except AssertionError: - print('\n\tParameter not found, check if it is an attribute\n') + except AssertionError as Error: + print(f"\n\tParameter not found, check if it is an attribute\n{Error}") return else: - mfparameter.append(getattr(ds,parameter)) - return mfparameter; - - + mfparameter.append(getattr(ds, parameter)) + return mfparameter def dimension(self, parameter): - - ''' + """ It gets dimension from file. @@ -796,7 +982,7 @@ def dimension(self, parameter): parameter: str Value of dimension - ''' + """ mfparameter_name = [] mfparameter_size = [] @@ -805,19 +991,18 @@ def dimension(self, parameter): try: assert parameter in ds.dimensions.keys() except AssertionError: - print('\n\tParameter not found, check if it is a dimension\n') + print("\n\tParameter not found, check if it is a dimension\n") print(list(ds.dimensions.keys())) return else: mfparameter_name.append(ds.dimensions[parameter].name) mfparameter_size.append(ds.dimensions[parameter].size) - return GOES({'name':np.array(mfparameter_name), 'size':np.array(mfparameter_size)}); - - + return GOES( + {"name": np.array(mfparameter_name), "size": np.array(mfparameter_size)} + ) def group(self, parameter): - - ''' + """ It gets group from file. @@ -832,7 +1017,7 @@ def group(self, parameter): parameter: str Value of group - ''' + """ mfparameter = [] for idx in range(len(self.ds)): @@ -840,18 +1025,14 @@ def group(self, parameter): try: assert parameter in ds.groups.keys() except AssertionError: - print('\n\tParameter not found, check if it is a group\n') + print("\n\tParameter not found, check if it is a group\n") return else: mfparameter.append(ds.groups[parameter]) - return mfparameter; - - - + return mfparameter def variable(self, parameter): - - ''' + """ It gets variable from file. @@ -866,205 +1047,282 @@ def variable(self, parameter): parameter: str Value of variable - ''' + """ for idx in range(len(self.ds)): ds = self.ds[idx] try: assert parameter in ds.variables.keys() except AssertionError: - print('\n\tParameter not found, check if it is a variable\n') + print("\n\tParameter not found, check if it is a variable\n") return else: try: - assert ds.variables[parameter].dimensions != ('y','x') - #assert (ds.variables[parameter].ndim == 0) or (ds.variables[parameter].ndim == 1) + assert ds.variables[parameter].dimensions != ("y", "x") + # assert (ds.variables[parameter].ndim == 0) or (ds.variables[parameter].ndim == 1) except AssertionError: - print('\n\tParameter is not a variable\n') + print("\n\tParameter is not a variable\n") return else: mfparameter = ds.variables[parameter] fmt = mfparameter[:].dtype - data = np.where(mfparameter[:].mask==True, np.nan, mfparameter[:].data) + data = np.where(mfparameter[:].mask, np.nan, mfparameter[:].data) IsDateTime = False - if 'units' in mfparameter.ncattrs(): - if 'seconds since' in mfparameter.units: - data = num2date(data, mfparameter.units, 'standard', only_use_cftime_datetimes=False, only_use_python_datetimes=True) + if "units" in mfparameter.ncattrs(): + if "seconds since" in mfparameter.units: + data = num2date( + data, + mfparameter.units, + "standard", + only_use_cftime_datetimes=False, + only_use_python_datetimes=True, + ) fmt = object data = np.array(data) IsDateTime = True - #if isinstance(data, np.ma.core.MaskedArray): + # if isinstance(data, np.ma.core.MaskedArray): # data = np.array(data) - #if isinstance(data, datetime.datetime): + # if isinstance(data, datetime.datetime): # data = np.array(data)#([data]) else: - if 'long_name' in mfparameter.ncattrs(): - if 'seconds since' in mfparameter.long_name or 'time' in mfparameter.long_name: - if '(' and ')' in mfparameter.long_name: - units = 'seconds since '+re.findall(r'\(.+?\)',mfparameter.long_name)[0][1:-1] + if "long_name" in mfparameter.ncattrs(): + if ( + "seconds since" in mfparameter.long_name + or "time" in mfparameter.long_name + ): + if "(" and ")" in mfparameter.long_name: + units = ( + "seconds since " + + re.findall(r"\(.+?\)", mfparameter.long_name)[ + 0 + ][1:-1] + ) else: - units = 'seconds since 2000-01-01 12:00:00' - data = num2date(data, units, 'standard', only_use_cftime_datetimes=False, only_use_python_datetimes=True) + units = "seconds since 2000-01-01 12:00:00" + data = num2date( + data, + units, + "standard", + only_use_cftime_datetimes=False, + only_use_python_datetimes=True, + ) fmt = object data = np.array(data) IsDateTime = True - #if isinstance(data, np.ma.core.MaskedArray): + # if isinstance(data, np.ma.core.MaskedArray): # data = np.array(data) - #if isinstance(data, datetime.datetime): + # if isinstance(data, datetime.datetime): # data = np.array(data)#([data]) if data.ndim == 0: - data = data.reshape([1]) #np.array([data]) + data = data.reshape([1]) # np.array([data]) elif data.ndim == 1: - if 'bounds' in mfparameter.dimensions[0]: - data = data.reshape([1,2]) + if "bounds" in mfparameter.dimensions[0]: + data = data.reshape([1, 2]) - if idx == 0 : + if idx == 0: mfdata = data else: - mfdata = np.concatenate((mfdata,data)) + mfdata = np.concatenate((mfdata, data)) dict = {} for key in mfparameter.__dict__.keys(): - dict.update({key: getattr(mfparameter,key)}) + dict.update({key: getattr(mfparameter, key)}) - if IsDateTime == True: - if 'units' in dict: - del dict['units'] + if IsDateTime: + if "units" in dict: + del dict["units"] - for item in ['_Unsigned','scale_factor','add_offset','_FillValue']: + for item in ["_Unsigned", "scale_factor", "add_offset", "_FillValue"]: if item in dict: del dict[item] - if len(getattr(mfparameter,'dimensions')) == 0: - dict.update({'dimensions': ('number_of_files',)}) - elif len(getattr(mfparameter,'dimensions')) == 1: - if 'bounds' in mfparameter.dimensions[0]: - dict.update({'dimensions': ('number_of_files',getattr(mfparameter,'dimensions')[0])}) + if len(getattr(mfparameter, "dimensions")) == 0: + dict.update({"dimensions": ("number_of_files",)}) + elif len(getattr(mfparameter, "dimensions")) == 1: + if "bounds" in mfparameter.dimensions[0]: + dict.update( + { + "dimensions": ( + "number_of_files", + getattr(mfparameter, "dimensions")[0], + ) + } + ) else: - dict.update({'dimensions': getattr(mfparameter,'dimensions')}) + dict.update({"dimensions": getattr(mfparameter, "dimensions")}) else: - dict.update({'dimensions': getattr(mfparameter,'dimensions')}) - - dict.update({'data':mfdata.astype(fmt)}) - - return GOES(dict); + dict.update({"dimensions": getattr(mfparameter, "dimensions")}) + dict.update({"data": mfdata.astype(fmt)}) + return GOES(dict) def image(self, parameter): - - ''' + """ It gets image from file, however, in this case, this method is disable because the files was open with open_mfdataset(). - ''' - print('\nThe image() method is disable for open_mfdataset(). Open the file with open_dataset() if you wan to use the image() method.\n') - return None, None, None; - - + """ + print( + "\nThe image() method is disable for open_mfdataset(). Open the file with open_dataset() if you wan to use the image() method.\n" + ) + return None, None, None def __str__(self): - - nfiles = len(self.ds) #for idx in range(len(self.ds)): + nfiles = len(self.ds) # for idx in range(len(self.ds)): ds = self.ds[0] - nf = ['number files: '+str(nfiles)] + nf = ["number files: " + str(nfiles)] files = self.files - attr = ['attribute:'] - dims = ['dimension:'] - var0D = ['variable:'] + attr = ["attribute:"] + dims = ["dimension:"] + var0D = ["variable:"] var1D = [] var2D = [] varMD = [] - image = ['image:'] - group = ['group:'] + image = ["image:"] + group = ["group:"] for item in ds.ncattrs(): - attr.append(' {:30}'.format(item)) + attr.append(" {:30}".format(item)) for item in ds.dimensions.keys(): - dims.append(' {:50}'.format(item)) + dims.append(" {:50}".format(item)) for item in ds.variables.keys(): if ds.variables[item].ndim == 0: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var0D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var0D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 1: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var1D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var1D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 2: - if ds.variables[item].dimensions == ('y','x'): - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - image.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + if ds.variables[item].dimensions == ("y", "x"): + size = "({})".format(", ".join(ds.variables[item].dimensions)) + image.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) else: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var2D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var2D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim > 2: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - varMD.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + varMD.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) for item in ds.groups.keys(): - groups.append(' {:50}'.format(item)) - - return '\n'.join([str(self.__class__)]+['']+nf+files+['']+attr+['']+dims+['']+var0D+var1D+var2D+varMD+['']+image+['']+group+['']) - - + group.append(" {:50}".format(item)) + + return "\n".join( + [str(self.__class__)] + + [""] + + nf + + files + + [""] + + attr + + [""] + + dims + + [""] + + var0D + + var1D + + var2D + + varMD + + [""] + + image + + [""] + + group + + [""] + ) def __repr__(self): - - nfiles = len(self.ds) #for idx in range(len(self.ds)): + nfiles = len(self.ds) # for idx in range(len(self.ds)): ds = self.ds[0] - nf = ['number files: '+str(nfiles)] + nf = ["number files: " + str(nfiles)] files = self.files - attr = ['attribute:'] - dims = ['dimension:'] - var0D = ['variable:'] + attr = ["attribute:"] + dims = ["dimension:"] + var0D = ["variable:"] var1D = [] var2D = [] varMD = [] - image = ['image:'] - group = ['group:'] + image = ["image:"] + group = ["group:"] for item in ds.ncattrs(): - attr.append(' {:30}'.format(item)) + attr.append(" {:30}".format(item)) for item in ds.dimensions.keys(): - dims.append(' {:50}'.format(item)) + dims.append(" {:50}".format(item)) for item in ds.variables.keys(): if ds.variables[item].ndim == 0: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var0D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var0D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 1: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var1D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var1D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim == 2: - if ds.variables[item].dimensions == ('y','x'): - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - image.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + if ds.variables[item].dimensions == ("y", "x"): + size = "({})".format(", ".join(ds.variables[item].dimensions)) + image.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) else: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - var2D.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + var2D.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) elif ds.variables[item].ndim > 2: - size = '({})'.format(', '.join(ds.variables[item].dimensions)) - varMD.append(' {:50} {} {}'.format(item, size, ds.variables[item].dtype)) + size = "({})".format(", ".join(ds.variables[item].dimensions)) + varMD.append( + " {:50} {} {}".format(item, size, ds.variables[item].dtype) + ) for item in ds.groups.keys(): - groups.append(' {:50}'.format(item)) - - return '\n'.join([str(self.__class__)]+['']+nf+files+['']+attr+['']+dims+['']+var0D+var1D+var2D+varMD+['']+image+['']+group+['']) - - + group.append(" {:50}".format(item)) + + return "\n".join( + [str(self.__class__)] + + [""] + + nf + + files + + [""] + + attr + + [""] + + dims + + [""] + + var0D + + var1D + + var2D + + varMD + + [""] + + image + + [""] + + group + + [""] + ) def keys(self): return list(self.__dict__.keys()) -#----------------------------------------------------------------------------------------------------------------------------------- -def get_lonlat(X, Y, PlatformID, SatLon, SatHeight, SatSweep, fmt=np.float32): +# ----------------------------------------------------------------------------------------------------------------------------------- - ''' + +def get_lonlat(X, Y, PlatformID, SatLon, SatHeight, SatSweep, fmt=np.float32): + """ Calculates the longitude and latitude of the center of the pixels, corresponding to the satellite image, using the fixed grid East/West and @@ -1107,33 +1365,56 @@ def get_lonlat(X, Y, PlatformID, SatLon, SatHeight, SatSweep, fmt=np.float32): Scalar 2-D array with the center latitude of the pixels. Undefined data are set as -999.99. - ''' + """ - X = X[:]*SatHeight - Y = Y[:]*SatHeight + X = X[:] * SatHeight + Y = Y[:] * SatHeight X, Y = np.meshgrid(X, Y) - proj = Proj(proj='geos', h=SatHeight, lon_0=SatLon, sweep=SatSweep) + proj = Proj(proj="geos", h=SatHeight, lon_0=SatLon, sweep=SatSweep) Lons, Lats = proj(X, Y, inverse=True) - if PlatformID == 'G17' or PlatformID == 'G18': - Lons = np.where(Lons>0,Lons-360,Lons) - - Lons = np.where((Lons>=-360.0)&(Lons<=360.0)&(Lats>=-90.0)&(Lats<=90.0),Lons,-999.99).astype(fmt) - Lats = np.where((Lons>=-360.0)&(Lons<=360.0)&(Lats>=-90.0)&(Lats<=90.0),Lats,-999.99).astype(fmt) - - dict_Lons = {'long_name':'Longitude of center of pixels', 'standard_name':'pixels center longitude', - 'units':'degrees_east', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':Lons} - - dict_Lats = {'long_name':'Latitude of center of pixels', 'standard_name':'pixels center latitude', - 'units':'degrees_north', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':Lats} - - return GOES(dict_Lons), GOES(dict_Lats); + if PlatformID == "G17" or PlatformID == "G18": + Lons = np.where(Lons > 0, Lons - 360, Lons) + + Lons = np.where( + (Lons >= -360.0) & (Lons <= 360.0) & (Lats >= -90.0) & (Lats <= 90.0), + Lons, + -999.99, + ).astype(fmt) + Lats = np.where( + (Lons >= -360.0) & (Lons <= 360.0) & (Lats >= -90.0) & (Lats <= 90.0), + Lats, + -999.99, + ).astype(fmt) + + dict_Lons = { + "long_name": "Longitude of center of pixels", + "standard_name": "pixels center longitude", + "units": "degrees_east", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": Lons, + } + + dict_Lats = { + "long_name": "Latitude of center of pixels", + "standard_name": "pixels center latitude", + "units": "degrees_north", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": Lats, + } + + return GOES(dict_Lons), GOES(dict_Lats) + + +# ----------------------------------------------------------------------------------------------------------------------------------- -#----------------------------------------------------------------------------------------------------------------------------------- def get_lonlatcorner(X, Y, PlatformID, SatLon, SatHeight, SatSweep, fmt=np.float32): - - ''' + """ Calculates the longitude and latitude of the corners of the pixels, corresponding to the satellite image, using the fixed grid East/West and @@ -1176,37 +1457,60 @@ def get_lonlatcorner(X, Y, PlatformID, SatLon, SatHeight, SatSweep, fmt=np.float Scalar 2-D array with the center latitude of the pixels. Undefined data are set as -999.99. - ''' + """ - X = X[:]*SatHeight - Y = Y[:]*SatHeight - dx = X[1]-X[0] - dy = Y[1]-Y[0] - XCor = np.concatenate([X, [X[-1]+dx]])-dx/2 - YCor = np.concatenate([Y, [Y[-1]+dy]])-dy/2 + X = X[:] * SatHeight + Y = Y[:] * SatHeight + dx = X[1] - X[0] + dy = Y[1] - Y[0] + XCor = np.concatenate([X, [X[-1] + dx]]) - dx / 2 + YCor = np.concatenate([Y, [Y[-1] + dy]]) - dy / 2 XCor, YCor = np.meshgrid(XCor, YCor) - proj = Proj(proj='geos', h=SatHeight, lon_0=SatLon, sweep=SatSweep) + proj = Proj(proj="geos", h=SatHeight, lon_0=SatLon, sweep=SatSweep) Lons, Lats = proj(XCor, YCor, inverse=True) - if PlatformID == 'G17' or PlatformID == 'G18': - Lons = np.where(Lons>0,Lons-360,Lons) - - Lons = np.where((Lons>=-360.0)&(Lons<=360.0)&(Lats>=-90.0)&(Lats<=90.0),Lons,-999.99).astype(fmt) - Lats = np.where((Lons>=-360.0)&(Lons<=360.0)&(Lats>=-90.0)&(Lats<=90.0),Lats,-999.99).astype(fmt) - - dict_Lons = {'long_name':'Longitude of corners of pixels', 'standard_name':'pixels corners longitude', - 'units':'degrees_east', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':Lons} + if PlatformID == "G17" or PlatformID == "G18": + Lons = np.where(Lons > 0, Lons - 360, Lons) + + Lons = np.where( + (Lons >= -360.0) & (Lons <= 360.0) & (Lats >= -90.0) & (Lats <= 90.0), + Lons, + -999.99, + ).astype(fmt) + Lats = np.where( + (Lons >= -360.0) & (Lons <= 360.0) & (Lats >= -90.0) & (Lats <= 90.0), + Lats, + -999.99, + ).astype(fmt) + + dict_Lons = { + "long_name": "Longitude of corners of pixels", + "standard_name": "pixels corners longitude", + "units": "degrees_east", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": Lons, + } + + dict_Lats = { + "long_name": "Latitude of corners of pixels", + "standard_name": "pixels corners latitude", + "units": "degrees_north", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": Lats, + } + + return GOES(dict_Lons), GOES(dict_Lats) + + +# ----------------------------------------------------------------------------------------------------------------------------------- - dict_Lats = {'long_name':'Latitude of corners of pixels', 'standard_name':'pixels corners latitude', - 'units':'degrees_north', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':Lats} - - return GOES(dict_Lons), GOES(dict_Lats); - -#----------------------------------------------------------------------------------------------------------------------------------- def corner_size_to_center_size(Field): - - ''' + """ Reduce dimension of array from [m,n] to [m-1,n-1]. Where m and n are odd numbers. @@ -1218,20 +1522,25 @@ def corner_size_to_center_size(Field): Returns ---------- Field with size [m-1,n-1] - ''' + """ ny, nx = Field.shape ny = ny - 1 nx = nx - 1 - Field = np.concatenate((Field[:,0:int(nx/2.0)], Field[:,int(nx/2.0)+1:]),axis=1) - Field = np.concatenate((Field[0:int(ny/2.0),:], Field[int(ny/2.0)+1:,:]),axis=0) - return Field; + Field = np.concatenate( + (Field[:, 0 : int(nx / 2.0)], Field[:, int(nx / 2.0) + 1 :]), axis=1 + ) + Field = np.concatenate( + (Field[0 : int(ny / 2.0), :], Field[int(ny / 2.0) + 1 :, :]), axis=0 + ) + return Field -#----------------------------------------------------------------------------------------------------------------------------------- -def midpoint_in_x(Field, fmt=np.float32): +# ----------------------------------------------------------------------------------------------------------------------------------- + - ''' +def midpoint_in_x(Field, fmt=np.float32): + """ Calculates the middle value between pixels in X axis. @@ -1250,23 +1559,34 @@ def midpoint_in_x(Field, fmt=np.float32): A scalar 2-D array with dimension [m,n+1]. Undefined data are set as -999.99. - ''' - - Field = np.array(Field,dtype=fmt) - Field = np.column_stack((Field, np.full([Field.shape[0],1],-999.99,dtype=fmt))) - right = np.column_stack((Field[:,1:], np.full([Field.shape[0],1],-999.99,dtype=fmt))) - left = np.column_stack((np.full([Field.shape[0],1],-999.99,dtype=fmt), Field[:,:-1])) - left2 = np.column_stack((np.full([Field.shape[0],2],-999.99,dtype=fmt), Field[:,:-2])) - - midpoint = np.where((Field>-400.0)&(left<-400.0),Field-(right-Field)/2.0,-999.99) - midpoint = np.where((Field>-400.0)&(left>-400.0),(left+Field)/2.0,midpoint) - midpoint = np.where((Field<-400.0)&(left>-400.0),left+(left-left2)/2.0,midpoint) - return midpoint; + """ + + Field = np.array(Field, dtype=fmt) + Field = np.column_stack((Field, np.full([Field.shape[0], 1], -999.99, dtype=fmt))) + right = np.column_stack( + (Field[:, 1:], np.full([Field.shape[0], 1], -999.99, dtype=fmt)) + ) + left = np.column_stack( + (np.full([Field.shape[0], 1], -999.99, dtype=fmt), Field[:, :-1]) + ) + left2 = np.column_stack( + (np.full([Field.shape[0], 2], -999.99, dtype=fmt), Field[:, :-2]) + ) + + midpoint = np.where( + (Field > -400.0) & (left < -400.0), Field - (right - Field) / 2.0, -999.99 + ) + midpoint = np.where( + (Field > -400.0) & (left > -400.0), (left + Field) / 2.0, midpoint + ) + midpoint = np.where( + (Field < -400.0) & (left > -400.0), left + (left - left2) / 2.0, midpoint + ) + return midpoint def midpoint_in_y(Field, fmt=np.float32): - - ''' + """ Calculates the middle value between pixels in Y axis. @@ -1285,24 +1605,33 @@ def midpoint_in_y(Field, fmt=np.float32): A scalar 2-D array with dimension [m+1,n]. Undefined data are set as -999.99. - ''' + """ - Field = np.array(Field,dtype=fmt) - Field = np.vstack((Field, np.full([1,Field.shape[1]],-999.99,dtype=fmt))) - lower = np.vstack((Field[1:,:], np.full([1,Field.shape[1]],-999.99,dtype=fmt))) - upper = np.vstack((np.full([1,Field.shape[1]],-999.99,dtype=fmt), Field[:-1,:])) - upper2 = np.vstack((np.full([2,Field.shape[1]],-999.99,dtype=fmt), Field[:-2,:])) + Field = np.array(Field, dtype=fmt) + Field = np.vstack((Field, np.full([1, Field.shape[1]], -999.99, dtype=fmt))) + lower = np.vstack((Field[1:, :], np.full([1, Field.shape[1]], -999.99, dtype=fmt))) + upper = np.vstack((np.full([1, Field.shape[1]], -999.99, dtype=fmt), Field[:-1, :])) + upper2 = np.vstack( + (np.full([2, Field.shape[1]], -999.99, dtype=fmt), Field[:-2, :]) + ) - midpoint = np.where((Field>-400.0)&(upper<-400.0),Field-(lower-Field)/2.0,-999.99) - midpoint = np.where((Field>-400.0)&(upper>-400.0),(upper+Field)/2.0,midpoint) - midpoint = np.where((Field<-400.0)&(upper>-400.0),upper+(upper-upper2)/2.0,midpoint) - return midpoint; + midpoint = np.where( + (Field > -400.0) & (upper < -400.0), Field - (lower - Field) / 2.0, -999.99 + ) + midpoint = np.where( + (Field > -400.0) & (upper > -400.0), (upper + Field) / 2.0, midpoint + ) + midpoint = np.where( + (Field < -400.0) & (upper > -400.0), upper + (upper - upper2) / 2.0, midpoint + ) + return midpoint -#----------------------------------------------------------------------------------------------------------------------------------- -def calculate_corners(Lons, Lats, fmt=np.float32): +# ----------------------------------------------------------------------------------------------------------------------------------- + - ''' +def calculate_corners(Lons, Lats, fmt=np.float32): + """ Calculates corners of pixels of the satellite image, from the longitude and latitude of the center of the pixels. @@ -1332,16 +1661,17 @@ def calculate_corners(Lons, Lats, fmt=np.float32): A scalar 2-D array with the latitude of the corners of the pixels of the satellite image. - ''' - + """ try: - assert (isinstance(Lons,GOES)==isinstance(Lats,GOES)==True) or (isinstance(Lons,np.ndarray)==isinstance(Lats,np.ndarray)==True) + assert (isinstance(Lons, GOES) == isinstance(Lats, GOES) is True) or ( + isinstance(Lons, np.ndarray) == isinstance(Lats, np.ndarray) is True + ) except AssertionError: - print('\nLons and Lats must be GOES class or numpy.ndarray\n') + print("\nLons and Lats must be GOES class or numpy.ndarray\n") return else: - if isinstance(Lons,GOES) and isinstance(Lats,GOES): + if isinstance(Lons, GOES) and isinstance(Lats, GOES): Lons = Lons.data Lats = Lats.data @@ -1351,19 +1681,34 @@ def calculate_corners(Lons, Lats, fmt=np.float32): Lons = midpoint_in_y(Lons, fmt=fmt) Lats = midpoint_in_x(Lats, fmt=fmt) - dict_Lons = {'long_name':'Longitude of corners of pixels', 'standard_name':'pixels corners longitude', - 'units':'degrees_east', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':Lons} + dict_Lons = { + "long_name": "Longitude of corners of pixels", + "standard_name": "pixels corners longitude", + "units": "degrees_east", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": Lons, + } - dict_Lats = {'long_name':'Latitude of corners of pixels', 'standard_name':'pixels corners latitude', - 'units':'degrees_north', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':Lats} + dict_Lats = { + "long_name": "Latitude of corners of pixels", + "standard_name": "pixels corners latitude", + "units": "degrees_north", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": Lats, + } - return GOES(dict_Lons), GOES(dict_Lats); + return GOES(dict_Lons), GOES(dict_Lats) -#----------------------------------------------------------------------------------------------------------------------------------- -def find_pixel_of_coordinate(Lons, Lats, LonCoord, LatCoord): +# ----------------------------------------------------------------------------------------------------------------------------------- - ''' + +def find_pixel_of_coordinate(Lons, Lats, LonCoord, LatCoord): + """ Finds the X and Y index of the pixel closest to the required coordinate. @@ -1392,29 +1737,31 @@ def find_pixel_of_coordinate(Lons, Lats, LonCoord, LatCoord): ypix : int Index on the Y axis of the pixel closest to the required coordinate. - ''' - + """ try: - assert (isinstance(Lons,GOES)==isinstance(Lats,GOES)==True) or (isinstance(Lons,np.ndarray)==isinstance(Lats,np.ndarray)==True) + assert (isinstance(Lons, GOES) == isinstance(Lats, GOES) is True) or ( + isinstance(Lons, np.ndarray) == isinstance(Lats, np.ndarray) is True + ) except AssertionError: - print('\nLons and Lats must be GOES class or numpy.ndarray\n') + print("\nLons and Lats must be GOES class or numpy.ndarray\n") return else: - if isinstance(Lons,GOES) and isinstance(Lats,GOES): + if isinstance(Lons, GOES) and isinstance(Lats, GOES): Lons = Lons.data Lats = Lats.data - Dist = np.sqrt( (Lons-LonCoord)**2 + (Lats-LatCoord)**2 ) - ypix, xpix = np.unravel_index( np.argmin(Dist, axis=None ), Dist.shape) + Dist = np.sqrt((Lons - LonCoord) ** 2 + (Lats - LatCoord) ** 2) + ypix, xpix = np.unravel_index(np.argmin(Dist, axis=None), Dist.shape) - return xpix, ypix; + return xpix, ypix -#----------------------------------------------------------------------------------------------------------------------------------- -def cosine_of_solar_zenith_angle(Lons, Lats, DateTime, MinCosTheta=0.0, fmt=np.float32): +# ----------------------------------------------------------------------------------------------------------------------------------- + - ''' +def cosine_of_solar_zenith_angle(Lons, Lats, DateTime, MinCosTheta=0.0, fmt=np.float32): + """ It calculates the cosine of solar zenith angle (cosine of theta). @@ -1440,50 +1787,90 @@ def cosine_of_solar_zenith_angle(Lons, Lats, DateTime, MinCosTheta=0.0, fmt=np.f CosTheta : object Cosine of solar zenith angle (cosine of theta). - ''' + """ try: - assert (isinstance(Lons,GOES)==isinstance(Lats,GOES)==True) or (isinstance(Lons,np.ndarray)==isinstance(Lats,np.ndarray)==True) + assert (isinstance(Lons, GOES) == isinstance(Lats, GOES) is True) or ( + isinstance(Lons, np.ndarray) == isinstance(Lats, np.ndarray) is True + ) except AssertionError: - print('\nLons and Lats must be GOES class or numpy.ndarray\n') + print("\nLons and Lats must be GOES class or numpy.ndarray\n") return else: if isinstance(Lons, GOES) and isinstance(Lats, GOES): Lons = Lons.data Lats = Lats.data + JulDay = DateTime.strftime("%j") + Hour = DateTime.strftime("%H") + Minute = DateTime.strftime("%M") - JulDay = DateTime.strftime('%j') - Hour = DateTime.strftime('%H') - Minute = DateTime.strftime('%M') - - HourDiff = np.where(Lons>-400.0,0.0,np.nan) - CenMer = -165.0+15.0*(np.arange(24)) - HourVar = np.arange(-11,13,1) + HourDiff = np.where(Lons > -400.0, 0.0, np.nan) + CenMer = -165.0 + 15.0 * (np.arange(24)) + HourVar = np.arange(-11, 13, 1) for idx in range(CenMer.shape[0]): - HourDiff = np.where( (Lons>= CenMer[idx]-7.5)&(Lons= CenMer[idx] - 7.5) & (Lons < CenMer[idx] + 7.5), + HourVar[idx], + 0.0, + ) + + HourDiff + ) + + Gamma = 2.0 * np.pi * (float(JulDay) - 1.0) / 365.0 # Gamma is in radians + Delta = ( + 0.006918 + - 0.399912 * np.cos(Gamma) + + 0.070257 * np.sin(Gamma) + - 0.006758 * np.cos(2 * Gamma) + + 0.000907 * np.sin(2 * Gamma) + - 0.002697 * np.cos(3 * Gamma) + + 0.00148 * np.sin(3 * Gamma) + ) # Solar decline, is in radians. + EqTime = 229.18 * ( + 0.0000075 + + 0.001868 * np.cos(Gamma) + - 0.032077 * np.sin(Gamma) + - 0.014615 * np.cos(2 * Gamma) + - 0.04089 * np.sin(2 * Gamma) + ) # Equation of time, is in minutes. + + Omega = (np.pi / 12.0) * ( + float(Hour) + + (float(Minute) / 60.0) + + HourDiff + - 12.0 + + ((Lons - HourDiff * 15.0) / 15.0) + + EqTime / 60.0 + ) # Hour angle, is in radians. + CosTheta = np.sin(Delta) * np.sin(Lats * np.pi / 180.0) + np.cos( + Delta + ) * np.cos(Lats * np.pi / 180.0) * np.cos( + Omega + ) # Cosine of theta (zenith angle) + CosTheta[np.where(CosTheta < MinCosTheta)] = np.nan CosTheta = np.array(CosTheta, dtype=fmt) - dict_CosTheta = {'long_name':'cosine of solar zenith angle', 'standard_name':'cosine of solar zenith angle', - 'units':None, 'undef':np.nan, 'axis':'YX', 'dimensions':('y','x'), 'data':CosTheta} + dict_CosTheta = { + "long_name": "cosine of solar zenith angle", + "standard_name": "cosine of solar zenith angle", + "units": None, + "undef": np.nan, + "axis": "YX", + "dimensions": ("y", "x"), + "data": CosTheta, + } - return GOES(dict_CosTheta); + return GOES(dict_CosTheta) -#----------------------------------------------------------------------------------------------------------------------------------- +# ----------------------------------------------------------------------------------------------------------------------------------- -def find_pixels_of_region(Lons, Lats, LLLon, URLon, LLLat, URLat): - ''' +def find_pixels_of_region(Lons, Lats, LLLon, URLon, LLLat, URLat): + """ It finds the corners (pixels index) of the region. @@ -1526,33 +1913,39 @@ def find_pixels_of_region(Lons, Lats, LLLon, URLon, LLLat, URLat): ymax: pixel index more close to URLat. - ''' - + """ try: - assert (isinstance(Lons,GOES)==isinstance(Lats,GOES)==True) or (isinstance(Lons,np.ndarray)==isinstance(Lats,np.ndarray)==True) + assert (isinstance(Lons, GOES) == isinstance(Lats, GOES) is True) or ( + isinstance(Lons, np.ndarray) == isinstance(Lats, np.ndarray) is True + ) except AssertionError: - print('\nLons and Lats must be GOES class or numpy.ndarray\n') + print("\nLons and Lats must be GOES class or numpy.ndarray\n") return else: if isinstance(Lons, GOES) and isinstance(Lats, GOES): Lons = Lons.data Lats = Lats.data - Mask = np.where((Lons>=LLLon)&(Lons<=URLon)&(Lats>=LLLat)&(Lats<=URLat),True,False) - yx = np.argwhere(Mask==True) - ypixmin, ypixmax = np.min(yx[:,0]), np.max(yx[:,0]) - xpixmin, xpixmax = np.min(yx[:,1]), np.max(yx[:,1]) + Mask = np.where( + (Lons >= LLLon) & (Lons <= URLon) & (Lats >= LLLat) & (Lats <= URLat), + True, + False, + ) + yx = np.argwhere(Mask) + ypixmin, ypixmax = np.min(yx[:, 0]), np.max(yx[:, 0]) + xpixmin, xpixmax = np.min(yx[:, 1]), np.max(yx[:, 1]) Limits = np.array([xpixmin, xpixmax, ypixmin, ypixmax]) - return Limits; + return Limits -#----------------------------------------------------------------------------------------------------------------------------------- -def create_gridmap(Domain, PixResol=2.0, fmt=np.float32): +# ----------------------------------------------------------------------------------------------------------------------------------- + - ''' +def create_gridmap(Domain, PixResol=2.0, fmt=np.float32): + """ It creates a equirectangular gridmap and return its longitudes and latitudes. @@ -1576,34 +1969,51 @@ def create_gridmap(Domain, PixResol=2.0, fmt=np.float32): Lats : object GOES class with the latitude of gridmap. - ''' - - dict_Lons = {'long_name':'Longitude of gridmap', 'standard_name':'longitude', - 'units':'degrees_east', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':None} - dict_Lats = {'long_name':'Latitude of gridmap', 'standard_name':'latitude', - 'units':'degrees_north', 'undef':-999.99, 'axis':'YX', 'dimensions':('y','x'), 'data':None} - nx = int( np.ceil( (Domain[1] - Domain[0])*111.0/float(PixResol) ) ) - ny = int( np.ceil( (Domain[3] - Domain[2])*111.0/float(PixResol) ) ) - Lons = np.arange(nx+1,dtype=fmt)*(float(PixResol)/111.0)+Domain[0] - Lats = np.arange(ny+1,dtype=fmt)*(float(PixResol)/111.0)*(-1.0)+Domain[3] + """ + + dict_Lons = { + "long_name": "Longitude of gridmap", + "standard_name": "longitude", + "units": "degrees_east", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": None, + } + dict_Lats = { + "long_name": "Latitude of gridmap", + "standard_name": "latitude", + "units": "degrees_north", + "undef": -999.99, + "axis": "YX", + "dimensions": ("y", "x"), + "data": None, + } + nx = int(np.ceil((Domain[1] - Domain[0]) * 111.0 / float(PixResol))) + ny = int(np.ceil((Domain[3] - Domain[2]) * 111.0 / float(PixResol))) + Lons = np.arange(nx + 1, dtype=fmt) * (float(PixResol) / 111.0) + Domain[0] + Lats = np.arange(ny + 1, dtype=fmt) * (float(PixResol) / 111.0) * (-1.0) + Domain[3] Lons, Lats = np.meshgrid(Lons, Lats) - dict_Lons['data'] = Lons - dict_Lats['data'] = Lats + dict_Lons["data"] = Lons + dict_Lats["data"] = Lats + + return GOES(dict_Lons), GOES(dict_Lats) - return GOES(dict_Lons), GOES(dict_Lats); -#----------------------------------------------------------------------------------------------------------------------------------- +# ----------------------------------------------------------------------------------------------------------------------------------- -def locate_files(path, prefix, datetime_ini, datetime_fin, use_parameter='scan_start_time'): - ''' +def locate_files( + path, prefix, datetime_ini, datetime_fin, use_parameter="scan_start_time" +): + """ It locates GOES-16/17 files between initial and final date time. Parameters ---------- path : str - path of files + path of files prefix : str Prefix name used to search files @@ -1629,74 +2039,104 @@ def locate_files(path, prefix, datetime_ini, datetime_fin, use_parameter='scan_s ------- return list with name of files. - ''' - + """ try: - assert (isinstance(datetime_ini,datetime.datetime) or ( isinstance(datetime_ini,str) and len(datetime_ini)==15 )) and (isinstance(datetime_fin,datetime.datetime) or ( isinstance(datetime_fin,str) and len(datetime_fin)==15 ) ) + assert ( + isinstance(datetime_ini, datetime.datetime) + or (isinstance(datetime_ini, str) and len(datetime_ini) == 15) + ) and ( + isinstance(datetime_fin, datetime.datetime) + or (isinstance(datetime_fin, str) and len(datetime_fin) == 15) + ) except AssertionError: - print('\n\tdatetime_ini and datetime_fin must be datetime.datetime or str with format YYYYmmdd-HHMMSS\n') + print( + "\n\tdatetime_ini and datetime_fin must be datetime.datetime or str with format YYYYmmdd-HHMMSS\n" + ) return else: - if isinstance(datetime_ini,str) and len(datetime_ini)==15: - datetime_ini = datetime.datetime.strptime(datetime_ini,'%Y%m%d-%H%M%S') - - if isinstance(datetime_fin,str) and len(datetime_fin)==15: - datetime_fin = datetime.datetime.strptime(datetime_fin,'%Y%m%d-%H%M%S') - + if isinstance(datetime_ini, str) and len(datetime_ini) == 15: + datetime_ini = datetime.datetime.strptime(datetime_ini, "%Y%m%d-%H%M%S") - l = sorted(glob.glob(path+prefix)) + if isinstance(datetime_fin, str) and len(datetime_fin) == 15: + datetime_fin = datetime.datetime.strptime(datetime_fin, "%Y%m%d-%H%M%S") - if use_parameter=='scan_start_time': + files = sorted(glob.glob(path + prefix)) + if use_parameter == "scan_start_time": ini_datetime = [] - for file in l: - datetimestr = file[file.find('_s')+2:file.find('_e')] - ini_datetime.append(datetime.datetime.strptime(datetimestr,'%Y%j%H%M%S%f')) - + for file in files: + datetimestr = file[file.find("_s") + 2 : file.find("_e")] + ini_datetime.append( + datetime.datetime.strptime(datetimestr, "%Y%j%H%M%S%f") + ) ini_datetime = np.array(ini_datetime) - mask = np.where((ini_datetime>=datetime_ini)&(ini_datetime= datetime_ini) & (ini_datetime < datetime_fin), + True, + False, + ) + files = np.array(files) + + elif use_parameter == "scan_end_time": fin_datetime = [] - for file in l: - datetimestr = file[file.find('_e')+2:file.find('_c')] - fin_datetime.append(datetime.datetime.strptime(datetimestr,'%Y%j%H%M%S%f')) + for file in files: + datetimestr = file[file.find("_e") + 2 : file.find("_c")] + fin_datetime.append( + datetime.datetime.strptime(datetimestr, "%Y%j%H%M%S%f") + ) fin_datetime = np.array(fin_datetime) - mask = np.where((fin_datetime>=datetime_ini)&(fin_datetime= datetime_ini) & (fin_datetime < datetime_fin), + True, + False, + ) + files = np.array(files) + + elif use_parameter == "both": ini_datetime = [] fin_datetime = [] - for file in l: - datetimestr = file[file.find('_s')+2:file.find('_e')] - ini_datetime.append(datetime.datetime.strptime(datetimestr,'%Y%j%H%M%S%f')) - - datetimestr = file[file.find('_e')+2:file.find('_c')] - fin_datetime.append(datetime.datetime.strptime(datetimestr,'%Y%j%H%M%S%f')) + for file in files: + datetimestr = file[file.find("_s") + 2 : file.find("_e")] + ini_datetime.append( + datetime.datetime.strptime(datetimestr, "%Y%j%H%M%S%f") + ) + datetimestr = file[file.find("_e") + 2 : file.find("_c")] + fin_datetime.append( + datetime.datetime.strptime(datetimestr, "%Y%j%H%M%S%f") + ) ini_datetime = np.array(ini_datetime) fin_datetime = np.array(fin_datetime) - mask = np.where((ini_datetime>=datetime_ini)&(fin_datetime= datetime_ini) & (fin_datetime < datetime_fin), + True, + False, + ) + files = np.array(files) + + return list(files[mask]) + + +# ----------------------------------------------------------------------------------------------------------------------------------- + + +def accumulate_in_gridmap( + Lons, + Lats, + parameter_lon, + parameter_lat, + parameter_value=None, + dx=200, + dy=200, + dz=200, + show_progress=True, + fmt=np.float32, +): + """ It accumulates the occurrence or the value of one parameter in equirectangular gridmap. Parameters @@ -1742,22 +2182,27 @@ def accumulate_in_gridmap(Lons, Lats, parameter_lon, parameter_lat, parameter_va accum: object Parameter accumulated in the gridmap. - ''' + """ try: - assert (isinstance(parameter_lon,GOES) and isinstance(parameter_lat,GOES)) or (isinstance(parameter_lon,np.ndarray) and isinstance(parameter_lat,np.ndarray)) + assert ( + isinstance(parameter_lon, GOES) and isinstance(parameter_lat, GOES) + ) or ( + isinstance(parameter_lon, np.ndarray) + and isinstance(parameter_lat, np.ndarray) + ) except AssertionError: - print('\n\tparameter_lon and parameter_lat must be GOES class or np.ndarray\n') + print("\n\tparameter_lon and parameter_lat must be GOES class or np.ndarray\n") return else: - try: - assert (isinstance(Lons,GOES) and isinstance(Lats,GOES)) or (isinstance(Lons,np.ndarray) and isinstance(Lats,np.ndarray)) + assert (isinstance(Lons, GOES) and isinstance(Lats, GOES)) or ( + isinstance(Lons, np.ndarray) and isinstance(Lats, np.ndarray) + ) except AssertionError: - print('\nLons and Lats must be GOES class or numpy.ndarray\n') + print("\nLons and Lats must be GOES class or numpy.ndarray\n") return else: - if isinstance(parameter_lon, GOES): Ltng_Lon = parameter_lon.data Ltng_Lat = parameter_lat.data @@ -1765,109 +2210,160 @@ def accumulate_in_gridmap(Lons, Lats, parameter_lon, parameter_lat, parameter_va Ltng_Lon = parameter_lon Ltng_Lat = parameter_lat - try: - assert isinstance(parameter_value,GOES) or isinstance(parameter_value,np.ndarray) or isinstance(parameter_value,type(None)) + assert ( + isinstance(parameter_value, GOES) + or isinstance(parameter_value, np.ndarray) + or isinstance(parameter_value, type(None)) + ) except AssertionError: - print('\nparameter_value must be GOES class, numpy.ndarray or None\n') + print("\nparameter_value must be GOES class, numpy.ndarray or None\n") return else: - - - LongName = 'Parameter accumulated in the gridmap' - StandardName = 'Parameter accumulated' + LongName = "Parameter accumulated in the gridmap" + StandardName = "Parameter accumulated" Units = None TimeBounds = None - if isinstance(parameter_value, GOES): Ltng_Par = parameter_value.data - elif isinstance(parameter_value,np.ndarray): + elif isinstance(parameter_value, np.ndarray): Ltng_Par = parameter_value else: - Ltng_Par = np.full(Ltng_Lon.shape[0],1.0,dtype=fmt) - LongName = 'Accumulated occurrences in the gridmap' - StandardName = 'Accumulated occurrences' - + Ltng_Par = np.full(Ltng_Lon.shape[0], 1.0, dtype=fmt) + LongName = "Accumulated occurrences in the gridmap" + StandardName = "Accumulated occurrences" - if isinstance(Lons, GOES)==True and isinstance(Lats, GOES)==True: + if isinstance(Lons, GOES) and isinstance(Lats, GOES): Lons = Lons.data Lats = Lats.data - - dict_Field = {'long_name':LongName, 'standard_name':StandardName, - 'units':Units, 'undef':np.nan, 'axis':'YX', - 'time_bounds':TimeBounds, 'dimensions':('y','x'), 'data':None} - - - LonsCen = Lons[0,:-1]+(Lons[0,1]-Lons[0,0])/2.0 - LatsCen = Lats[:-1,0]+(Lats[1,0]-Lats[0,0])/2.0 + dict_Field = { + "long_name": LongName, + "standard_name": StandardName, + "units": Units, + "undef": np.nan, + "axis": "YX", + "time_bounds": TimeBounds, + "dimensions": ("y", "x"), + "data": None, + } + + LonsCen = Lons[0, :-1] + (Lons[0, 1] - Lons[0, 0]) / 2.0 + LatsCen = Lats[:-1, 0] + (Lats[1, 0] - Lats[0, 0]) / 2.0 LonsCen, LatsCen = np.meshgrid(LonsCen, LatsCen) - Mask = np.where((Ltng_Lon>=Lons[0,0])&(Ltng_Lon<=Lons[0,-1])&(Ltng_Lat>=Lats[-1,0])&(Ltng_Lat<=Lats[0,0]),True,False) - Ltng_Lon = np.delete(Ltng_Lon, np.where(Mask==False)) - Ltng_Lat = np.delete(Ltng_Lat, np.where(Mask==False)) - Ltng_Par = np.delete(Ltng_Par, np.where(Mask==False)) - if show_progress == True: - print(' There are {:.0f} occurrences inside gridmap'.format(Ltng_Lon.shape[0])) - - - accum = np.full(LonsCen.shape,0,dtype=fmt) + Mask = np.where( + (Ltng_Lon >= Lons[0, 0]) + & (Ltng_Lon <= Lons[0, -1]) + & (Ltng_Lat >= Lats[-1, 0]) + & (Ltng_Lat <= Lats[0, 0]), + True, + False, + ) + Ltng_Lon = np.delete(Ltng_Lon, np.where(not Mask)) + Ltng_Lat = np.delete(Ltng_Lat, np.where(not Mask)) + Ltng_Par = np.delete(Ltng_Par, np.where(not Mask)) + if show_progress: + print( + " There are {:.0f} occurrences inside gridmap".format( + Ltng_Lon.shape[0] + ) + ) + + accum = np.full(LonsCen.shape, 0, dtype=fmt) if Ltng_Lon.shape[0] == 0: - - dict_Field['data'] = accum - return GOES(dict_Field); - + dict_Field["data"] = accum + return GOES(dict_Field) else: - ysize, xsize = Lons.shape - xidx = np.arange(0,xsize+dx-1,dx-1) - yidx = np.arange(0,ysize+dy-1,dy-1) - NSlides = (xidx.shape[0]-1)*(yidx.shape[0]-1) + xidx = np.arange(0, xsize + dx - 1, dx - 1) + yidx = np.arange(0, ysize + dy - 1, dy - 1) + NSlides = (xidx.shape[0] - 1) * (yidx.shape[0] - 1) Slide = 0 - - for j in range(len(yidx)-1): - for i in range(len(xidx)-1): - LonsCut = Lons[yidx[j]:yidx[j+1]+1,xidx[i]:xidx[i+1]+1] + for j in range(len(yidx) - 1): + for i in range(len(xidx) - 1): + LonsCut = Lons[ + yidx[j] : yidx[j + 1] + 1, xidx[i] : xidx[i + 1] + 1 + ] LonsCutMin, LonsCutMax = LonsCut.min(), LonsCut.max() - LonsCutCen = LonsCen[yidx[j]:yidx[j+1],xidx[i]:xidx[i+1]] + LonsCutCen = LonsCen[ + yidx[j] : yidx[j + 1], xidx[i] : xidx[i + 1] + ] - LatsCut = Lats[yidx[j]:yidx[j+1]+1,xidx[i]:xidx[i+1]+1] + LatsCut = Lats[ + yidx[j] : yidx[j + 1] + 1, xidx[i] : xidx[i + 1] + 1 + ] LatsCutMin, LatsCutMax = LatsCut.min(), LatsCut.max() - LatsCutCen = LatsCen[yidx[j]:yidx[j+1],xidx[i]:xidx[i+1]] + LatsCutCen = LatsCen[ + yidx[j] : yidx[j + 1], xidx[i] : xidx[i + 1] + ] # delete occurrences out of Sub-Area - Mask = np.where((Ltng_Lon>=LonsCutMin)&(Ltng_Lon<=LonsCutMax)&(Ltng_Lat>=LatsCutMin)&(Ltng_Lat<=LatsCutMax),True,False) - Ltng_Lon2 = np.delete(Ltng_Lon, np.where(Mask==False)) - Ltng_Lat2 = np.delete(Ltng_Lat, np.where(Mask==False)) - Ltng_Par2 = np.delete(Ltng_Par, np.where(Mask==False)) - - - if Ltng_Lon2.shape[0]>0: + Mask = np.where( + (Ltng_Lon >= LonsCutMin) + & (Ltng_Lon <= LonsCutMax) + & (Ltng_Lat >= LatsCutMin) + & (Ltng_Lat <= LatsCutMax), + True, + False, + ) + Ltng_Lon2 = np.delete(Ltng_Lon, np.where(not Mask)) + Ltng_Lat2 = np.delete(Ltng_Lat, np.where(not Mask)) + Ltng_Par2 = np.delete(Ltng_Par, np.where(not Mask)) + + if Ltng_Lon2.shape[0] > 0: zsize = Ltng_Lon2.shape[0] - zidx = np.arange(0,zsize+dz,dz) - for k in range(len(zidx)-1): - Ltng_Lon3 = Ltng_Lon2[zidx[k]:zidx[k+1]] - Ltng_Lat3 = Ltng_Lat2[zidx[k]:zidx[k+1]] - Ltng_Par3 = Ltng_Par2[zidx[k]:zidx[k+1]] - - Dist = np.sqrt( (LonsCutCen-Ltng_Lon3[:,None,None])**2 + (LatsCutCen-Ltng_Lat3[:,None,None])**2 ) - Mins = np.min(Dist.reshape((Dist.shape[0],Dist.shape[1]*Dist.shape[2])), axis=1)[:,None,None] - accum[yidx[j]:yidx[j+1],xidx[i]:xidx[i+1]] = np.sum(np.where(Dist==Mins, 1, 0)*Ltng_Par3[:,None,None], axis=0) + accum[yidx[j]:yidx[j+1],xidx[i]:xidx[i+1]] + zidx = np.arange(0, zsize + dz, dz) + for k in range(len(zidx) - 1): + Ltng_Lon3 = Ltng_Lon2[zidx[k] : zidx[k + 1]] + Ltng_Lat3 = Ltng_Lat2[zidx[k] : zidx[k + 1]] + Ltng_Par3 = Ltng_Par2[zidx[k] : zidx[k + 1]] + + Dist = np.sqrt( + (LonsCutCen - Ltng_Lon3[:, None, None]) ** 2 + + (LatsCutCen - Ltng_Lat3[:, None, None]) ** 2 + ) + Mins = np.min( + Dist.reshape( + ( + Dist.shape[0], + Dist.shape[1] * Dist.shape[2], + ) + ), + axis=1, + )[:, None, None] + accum[ + yidx[j] : yidx[j + 1], xidx[i] : xidx[i + 1] + ] = ( + np.sum( + np.where(Dist == Mins, 1, 0) + * Ltng_Par3[:, None, None], + axis=0, + ) + + accum[ + yidx[j] : yidx[j + 1], xidx[i] : xidx[i + 1] + ] + ) Slide = Slide + 1 - if show_progress == True: - print(' processing {:3.0f}%'.format(100.0*(Slide)/NSlides), end='\r', flush=True) - if Slide == NSlides: - print('\b') + if show_progress: + print( + " processing {:3.0f}%".format( + 100.0 * (Slide) / NSlides + ), + end="\r", + flush=True, + ) + if Slide == NSlides: + print("\b") accum = np.array(accum, dtype=fmt) - dict_Field['data'] = accum - - return GOES(dict_Field); + dict_Field["data"] = accum -#----------------------------------------------------------------------------------------------------------------------------------- + return GOES(dict_Field) +# ----------------------------------------------------------------------------------------------------------------------------------- diff --git a/src/goes16/utils.py b/src/goes16/utils.py new file mode 100644 index 00000000..a5291a3a --- /dev/null +++ b/src/goes16/utils.py @@ -0,0 +1,30 @@ +from pathlib import Path + +from config import globals + +DATA_ROOT = Path(globals.GOES16_DATA_DIR) +FEATURES_ROOT = Path(globals.GOES16_FEATURES_DIR) + + +def build_channel_paths_by_year(channel: str): + """ + Retorna uma lista de caminhos para cada ano contendo dados do canal especificado. + """ + temp = [ + DATA_ROOT / year.name / channel + for year in sorted(DATA_ROOT.iterdir()) + if (DATA_ROOT / year.name / channel).is_dir() + ] + print(f"Found {len(temp)} directories for channel {channel} in {DATA_ROOT}") + return temp + + +def build_feature_paths_by_year(feature: str): + """ + Retorna uma lista de caminhos para cada ano contendo features já extraídas. + """ + return [ + FEATURES_ROOT / feature / year.name + for year in sorted((FEATURES_ROOT / feature).iterdir()) + if (FEATURES_ROOT / feature / year.name).is_dir() + ] diff --git a/src/goes16/validate_features.py b/src/goes16/validate_features.py new file mode 100644 index 00000000..10472082 --- /dev/null +++ b/src/goes16/validate_features.py @@ -0,0 +1,88 @@ +# validate_features.py +import argparse +import os +from collections import defaultdict +from pathlib import Path + +import netCDF4 as nc + + +def list_timestamps_from_dir(path): + arquivos = sorted(os.listdir(path)) + return set(f.split("_", 1)[1] for f in arquivos if "_" in f) + + +def validate_presence(feature_dir, canais, base_raw_dir="data/goes16/CMI"): + print(f"\n📁 Validando presença de arquivos em: {feature_dir}") + for year_dir in sorted(Path(feature_dir).iterdir()): + if not year_dir.is_dir(): + continue + ano = year_dir.name + feature_files = list_timestamps_from_dir(year_dir) + + expected = None + for canal in canais: + path = Path(base_raw_dir) / ano / canal + if not path.exists(): + print(f" ⚠ Referência ausente: {path}") + continue + ref_files = list_timestamps_from_dir(path) + if expected is None: + expected = ref_files + else: + expected &= ref_files + + if expected is None: + print(f" ⚠ Nenhum diretório de referência disponível para {ano}") + continue + + diff = expected - feature_files + if not diff: + print(f" ✓ {ano}: {len(feature_files)} arquivos gerados corretamente") + else: + print(f" ✗ {ano}: {len(diff)} arquivos ausentes. Ex: {list(diff)[:3]}") + + +def validate_netcdf_structure(feature_dir): + print(f"\n🔍 Validando estrutura NetCDF em: {feature_dir}") + problemas = defaultdict(list) + for year_dir in sorted(Path(feature_dir).iterdir()): + if not year_dir.is_dir(): + continue + for f in sorted(year_dir.glob("*.nc")): + try: + with nc.Dataset(f, "r") as ds: + if not ds.variables: + problemas["sem_variaveis"].append(f.name) + for v in ds.variables.values(): + if not hasattr(v, "description"): + problemas["sem_descricao"].append(f.name) + except Exception: + problemas["erro_abertura"].append(f.name) + if not problemas: + print(" ✓ Todos os arquivos têm estrutura válida.") + else: + for tipo, arqs in problemas.items(): + print(f" ✗ {tipo}: {len(arqs)} arquivos. Ex: {arqs[:3]}") + + +def run_all(feature: str, canais: list): + feature_path = Path("data/goes16/features") / feature + validate_presence(str(feature_path), canais) + validate_netcdf_structure(str(feature_path)) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Valida arquivos de features GOES-16") + parser.add_argument( + "--feature", required=True, help="Nome da feature (ex: pn, gtn, wv_grad)" + ) + parser.add_argument( + "--canais", + nargs="+", + required=True, + help="Lista de canais de referência (ex: C09 C13)", + ) + args = parser.parse_args() + + run_all(args.feature, args.canais) diff --git a/src/goes16_utils.py b/src/goes16_utils.py deleted file mode 100644 index 9fc31f3f..00000000 --- a/src/goes16_utils.py +++ /dev/null @@ -1,318 +0,0 @@ -# Training: Python and GOES-R Imagery: Script 8 - Functions for download data from AWS -#----------------------------------------------------------------------------------------------------------- -# Required modules -import os # Miscellaneous operating system interfaces -import numpy as np # Import the Numpy package -import colorsys # To make convertion of colormaps -import boto3 # Amazon Web Services (AWS) SDK for Python -from botocore import UNSIGNED # boto3 config -from botocore.config import Config # boto3 config -import math # Mathematical functions -from datetime import datetime # Basic Dates and time types -from osgeo import osr # Python bindings for GDAL -from osgeo import gdal # Python bindings for GDAL - -#from netCDF4 import Dataset # Read / Write NetCDF4 files -#import matplotlib.pyplot as plt # Plotting library -#import cartopy, cartopy.crs as ccrs # Plot maps -##import sys -#from datetime import timedelta, date, datetime # Manipulate dates - -#----------------------------------------------------------------------------------------------------------- -def loadCPT(path): - - try: - f = open(path) - except: - print ("File ", path, "not found") - return None - - lines = f.readlines() - - f.close() - - x = np.array([]) - r = np.array([]) - g = np.array([]) - b = np.array([]) - - colorModel = 'RGB' - - for l in lines: - ls = l.split() - if l[0] == '#': - if ls[-1] == 'HSV': - colorModel = 'HSV' - continue - else: - continue - if ls[0] == 'B' or ls[0] == 'F' or ls[0] == 'N': - pass - else: - x=np.append(x,float(ls[0])) - r=np.append(r,float(ls[1])) - g=np.append(g,float(ls[2])) - b=np.append(b,float(ls[3])) - xtemp = float(ls[4]) - rtemp = float(ls[5]) - gtemp = float(ls[6]) - btemp = float(ls[7]) - - x=np.append(x,xtemp) - r=np.append(r,rtemp) - g=np.append(g,gtemp) - b=np.append(b,btemp) - - if colorModel == 'HSV': - for i in range(r.shape[0]): - rr, gg, bb = colorsys.hsv_to_rgb(r[i]/360.,g[i],b[i]) - r[i] = rr ; g[i] = gg ; b[i] = bb - - if colorModel == 'RGB': - r = r/255.0 - g = g/255.0 - b = b/255.0 - - xNorm = (x - x[0])/(x[-1] - x[0]) - - red = [] - blue = [] - green = [] - - for i in range(len(x)): - red.append([xNorm[i],r[i],r[i]]) - green.append([xNorm[i],g[i],g[i]]) - blue.append([xNorm[i],b[i],b[i]]) - - colorDict = {'red': red, 'green': green, 'blue': blue} - - return colorDict -#----------------------------------------------------------------------------------------------------------- -def download_CMI(yyyymmddhhmn, band, path_dest): - - os.makedirs(path_dest, exist_ok=True) - - year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%Y') - day_of_year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%j') - hour = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%H') - min = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%M') - - # AMAZON repository information - # https://noaa-goes16.s3.amazonaws.com/index.html - bucket_name = 'noaa-goes16' - product_name = 'ABI-L2-CMIPF' - - # Initializes the S3 client - s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) - #----------------------------------------------------------------------------------------------------------- - # File structure - prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6C{int(band):02.0f}_G16_s{year}{day_of_year}{hour}{min}' - - # Seach for the file on the server - s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = "/") - - #----------------------------------------------------------------------------------------------------------- - # Check if there are files available - if 'Contents' not in s3_result: - # There are no files - print(f'No files found for the date: {yyyymmddhhmn}, Band-{band}') - return -1 - else: - # There are files - for obj in s3_result['Contents']: - key = obj['Key'] - # Print the file name - file_name = key.split('/')[-1].split('.')[0] - - # Download the file - if os.path.exists(f'{path_dest}/{file_name}.nc'): - print(f'File {path_dest}/{file_name}.nc exists') - else: - print(f'Downloading file {path_dest}/{file_name}.nc') - s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc') - return f'{file_name}' - -s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) - -#----------------------------------------------------------------------------------------------------------- -def download_PROD(yyyymmddhhmn, product_name, path_dest): - - # os.makedirs(path_dest, exist_ok=True) - - year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%Y') - day_of_year = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%j') - hour = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%H') - min = datetime.strptime(yyyymmddhhmn, '%Y%m%d%H%M').strftime('%M') - - # AMAZON repository information - # https://noaa-goes16.s3.amazonaws.com/index.html - bucket_name = 'noaa-goes16' - - # Initializes the S3 client - # s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) - - #----------------------------------------------------------------------------------------------------------- - # File structure - prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}-M6_G16_s{year}{day_of_year}{hour}{min}' - - # Seach for the file on the server - s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = "/") - - #----------------------------------------------------------------------------------------------------------- - # Check if there are files available - if 'Contents' not in s3_result: - # There are no files - print(f'No files found for the date: {yyyymmddhhmn}, Product: {product_name}') - return -1 - else: - # There are files - for obj in s3_result['Contents']: - key = obj['Key'] - # Print the file name - file_name = key.split('/')[-1].split('.')[0] - - # print(f'File name: {file_name}') - - # Download the file - if os.path.exists(f'{path_dest}/{file_name}.nc'): - print(f'File {path_dest}/{file_name}.nc exists') - else: - # print(f'Downloading file {path_dest}/{file_name}.nc') - s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc') - return f'{file_name}' - -#----------------------------------------------------------------------------------------------------------- -def download_GLM(yyyymmddhhmnss, path_dest): - - os.makedirs(path_dest, exist_ok=True) - - year = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%Y') - day_of_year = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%j') - hour = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%H') - min = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%M') - seg = datetime.strptime(yyyymmddhhmnss, '%Y%m%d%H%M%S').strftime('%S') - - # AMAZON repository information - # https://noaa-goes16.s3.amazonaws.com/index.html - bucket_name = 'noaa-goes16' - - # Initializes the S3 client - s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) - #----------------------------------------------------------------------------------------------------------- - # File structure - product_name = "GLM-L2-LCFA" - prefix = f'{product_name}/{year}/{day_of_year}/{hour}/OR_{product_name}_G16_s{year}{day_of_year}{hour}{min}{seg}' - - # Seach for the file on the server - s3_result = s3_client.list_objects_v2(Bucket=bucket_name, Prefix=prefix, Delimiter = "/") - - #----------------------------------------------------------------------------------------------------------- - # Check if there are files available - if 'Contents' not in s3_result: - # There are no files - print(f'No files found for the date: {yyyymmddhhmnss}, Product-{product_name}') - return -1 - else: - # There are files - for obj in s3_result['Contents']: - key = obj['Key'] - # Print the file name - file_name = key.split('/')[-1].split('.')[0] - - # Download the file - if os.path.exists(f'{path_dest}/{file_name}.nc'): - print(f'File {path_dest}/{file_name}.nc exists') - else: - print(f'Downloading file {path_dest}/{file_name}.nc') - s3_client.download_file(bucket_name, key, f'{path_dest}/{file_name}.nc') - return f'{file_name}' - -#----------------------------------------------------------------------------------------------------------- -# Functions to convert lat / lon extent to array indices -def geo2grid(lat, lon, nc): - - # Apply scale and offset - xscale, xoffset = nc.variables['x'].scale_factor, nc.variables['x'].add_offset - yscale, yoffset = nc.variables['y'].scale_factor, nc.variables['y'].add_offset - - x, y = latlon2xy(lat, lon) - col = (x - xoffset)/xscale - lin = (y - yoffset)/yscale - return int(lin), int(col) - -def latlon2xy(lat, lon): - # goes_imagery_projection:semi_major_axis - req = 6378137 # meters - # goes_imagery_projection:inverse_flattening - invf = 298.257222096 - # goes_imagery_projection:semi_minor_axis - rpol = 6356752.31414 # meters - e = 0.0818191910435 - # goes_imagery_projection:perspective_point_height + goes_imagery_projection:semi_major_axis - H = 42164160 # meters - # goes_imagery_projection: longitude_of_projection_origin - lambda0 = -1.308996939 - - # Convert to radians - latRad = lat * (math.pi/180) - lonRad = lon * (math.pi/180) - - # (1) geocentric latitude - Phi_c = math.atan(((rpol * rpol)/(req * req)) * math.tan(latRad)) - # (2) geocentric distance to the point on the ellipsoid - rc = rpol/(math.sqrt(1 - ((e * e) * (math.cos(Phi_c) * math.cos(Phi_c))))) - # (3) sx - sx = H - (rc * math.cos(Phi_c) * math.cos(lonRad - lambda0)) - # (4) sy - sy = -rc * math.cos(Phi_c) * math.sin(lonRad - lambda0) - # (5) - sz = rc * math.sin(Phi_c) - - # x,y - x = math.asin((-sy)/math.sqrt((sx*sx) + (sy*sy) + (sz*sz))) - y = math.atan(sz/sx) - - return x, y - -# Function to convert lat / lon extent to GOES-16 extents -def convertExtent2GOESProjection(extent): - # GOES-16 viewing point (satellite position) height above the earth - GOES16_HEIGHT = 35786023.0 - # GOES-16 longitude position - GOES16_LONGITUDE = -75.0 - - a, b = latlon2xy(extent[1], extent[0]) - c, d = latlon2xy(extent[3], extent[2]) - return (a * GOES16_HEIGHT, c * GOES16_HEIGHT, b * GOES16_HEIGHT, d * GOES16_HEIGHT) - -#----------------------------------------------------------------------------------------------------------- -# Function to reproject the data -def reproject(file_name, ncfile, array, extent, undef): - - # Read the original file projection and configure the output projection - source_prj = osr.SpatialReference() - source_prj.ImportFromProj4(ncfile.GetProjectionRef()) - - target_prj = osr.SpatialReference() - target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") - - # Reproject the data - GeoT = ncfile.GetGeoTransform() - driver = gdal.GetDriverByName('MEM') - raw = driver.Create('raw', array.shape[0], array.shape[1], 1, gdal.GDT_Float32) - raw.SetGeoTransform(GeoT) - raw.GetRasterBand(1).WriteArray(array) - - # Define the parameters of the output file - kwargs = {'format': 'netCDF', \ - 'srcSRS': source_prj, \ - 'dstSRS': target_prj, \ - 'outputBounds': (extent[0], extent[3], extent[2], extent[1]), \ - 'outputBoundsSRS': target_prj, \ - 'outputType': gdal.GDT_Float32, \ - 'srcNodata': undef, \ - 'dstNodata': 'nan', \ - 'resampleAlg': gdal.GRA_NearestNeighbour} - - # Write the reprojected file on disk - gdal.Warp(file_name, raw, **kwargs) \ No newline at end of file diff --git a/src/gpm/README.md b/src/gpm/README.md new file mode 100644 index 00000000..dba4f0f5 --- /dev/null +++ b/src/gpm/README.md @@ -0,0 +1,33 @@ +## 🌧️ GPM Preprocessing Scripts + +This module contains scripts to process GPM (IMERG) precipitation data: + +- `gpm_download_crop.py`: Download and spatially crop GPM data to a given bounding box +- `gpm_plot.py`: Visualize GPM precipitation fields + +--- + +## 🛠️ Usage via Makefile + +You can call the GPM downloader with cropping directly from the root of the repository using: + +make gpm-download-crop BEGIN=2024/01/01 END=2024/01/03 USER=your_username PWD=your_password + +### 📌 Optional Flags + +You can pass optional arguments like: + +- DEBUG=--debug → Enables verbose mode. +- IGNORED="--ignored_months 6 7" → Skips specified months. + +### 🧩 Example with All Options + +make gpm-download-crop \ + BEGIN=2024/01/01 \ + END=2024/01/31 \ + USER=your_username \ + PWD=your_password \ + DEBUG=--debug \ + IGNORED="--ignored_months 6 7" + +> Make sure your NASA Earthdata credentials are valid and authorized to access IMERG files. diff --git a/src/gpm/__init__.py b/src/gpm/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/gpm/gpm_download_crop.py b/src/gpm/gpm_download_crop.py new file mode 100644 index 00000000..d5bf5237 --- /dev/null +++ b/src/gpm/gpm_download_crop.py @@ -0,0 +1,563 @@ +""" +Copyright 2022 ARC Centre of Excellence for Climate Systems Science + +author: Paola Petrelli + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. + + This script is used to download and/or update the GPM-IMERG V06 dataset on + the NCI server from https://disc.gsfc.nasa.gov/datasets/GPM_3IMERGHH_06/summary + Last change: + 2022-07-19 + + Usage: + Inputs are: + y - year to check/download/update the only one required + f - this forces local chksum to be re-calculated even if local file exists + The script will look for the local and remote checksum files: + trmm__cksum_.txt + If the local file does not exists calls calculate_cksum() to create one + If the remote cksum file does not exist calls retrieve_cksum() to create one + The remote checksum are retrieved directly from the cksum field in + the filename.xml available online. + The checksums are compared for each files and if they are not matching + the local file is deleted and download it again using the requests module + The requests module also handle the website cookies by opening a session + at the start of the script + + Uses the following modules: + import requests to download files and html via http + import beautifulsoup4 to parse html + import xml.etree.cElementTree to read a single xml field + import time and calendar to convert timestamp in filename + to day number from 1-366 for each year + import subprocess to run cksum as a shell command + import argparse to manage inputs + should work with both python 2 and 3 + +""" + +import argparse + +# try: +# import xml.etree.cElementTree as ET +# except ImportError as e: +# print(f"Pass a password as input or set the GPMPWD variable: {e}") +# from util import set_log, check_mdt, print_summary +import logging +import os +import re +import sys +import time +from datetime import datetime, timedelta + +import dateutil.parser +import numpy as np +import pytz +import requests +from bs4 import BeautifulSoup +from netCDF4 import Dataset + +from config import globals + + +def set_log(name, fname, level): + """Set up logging with a file handler + + Parameters + ---------- + name: str + Name of logger object + fname: str + Log output filename + level: str + Base logging level + """ + + # First disable default root logger + for handler in logging.root.handlers[:]: + logging.root.removeHandler(handler) + # start a logger + logger = logging.getLogger(name) + # set a formatter to manage the output format of our handler + logging.Formatter("%(asctime)s | %(message)s", "%H:%M:%S") + minimal = logging.Formatter("%(message)s") + if level == "debug": + minimal = logging.Formatter("%(levelname)s: %(message)s") + # set the level passed as input, has to be logging.LEVEL not a string + log_level = logging.getLevelName(level.upper()) + logger.setLevel(log_level) + # add a handler for console this will have the chosen level + console_handler = logging.StreamHandler() + console_handler.setLevel(log_level) + console_handler.setFormatter(minimal) + logger.addHandler(console_handler) + # add a handler for the log file, this is set to INFO level + file_handler = logging.FileHandler(fname) + file_handler.setLevel(logging.INFO) + file_handler.setFormatter(minimal) + logger.addHandler(file_handler) + # return the logger object + logger.propagate = False + return logger + + +def check_mdt( + req, fpath, logger, remoteModDate=None, furl=None, head_key="Last-modified" +): + """Check local and remote modified time and return comparison + You have to pass either the remote last modified date or + the file url to try to retrieve it + """ + if not remoteModDate: + response = req.head(furl) + remoteModDate = response.headers[head_key] + remoteModDate = dateutil.parser.parse(remoteModDate) + localModDate = datetime.fromtimestamp(os.path.getmtime(fpath)) + localModDate = localModDate.replace(tzinfo=pytz.UTC) + to_update = localModDate < remoteModDate + logger.debug(f"File: {fpath}") + logger.debug(f"Local mod_date: {localModDate}") + logger.debug(f"ftp mod_date: {remoteModDate}") + logger.debug(f"to update: {to_update}") + return to_update + + +def print_summary(updated, new, error, logger): + """Print a summary of new, updated and error files to log file""" + + logger.info("==========================================") + logger.info("Summary") + logger.info("==========================================") + logger.info("These files were updated: ") + for f in updated: + logger.info(f"{f}") + logger.info("==========================================") + logger.info("These are new files: ") + for f in new: + logger.info(f"{f}") + logger.info("==========================================") + logger.info("These files and problems: ") + for f in error: + logger.info(f"{f}") + logger.info("\n\n") + + +def parse_input(): + """Parse input arguments""" + parser = argparse.ArgumentParser( + description="""Retrieve GPM-IMERG data from NASA server for a given date range.""", + formatter_class=argparse.RawTextHelpFormatter, + ) + + parser.add_argument( + "--ignored_months", + type=int, + nargs="*", + default=[], + help="List of month numbers (1-12) to ignore in the download process. Example: --ignored_months 6 7", + ) + + parser.add_argument( + "--begin_date", type=str, required=True, help="Start date in format YYYY/MM/DD" + ) + parser.add_argument( + "--end_date", type=str, required=True, help="End date in format YYYY/MM/DD" + ) + parser.add_argument("-u", "--user", type=str, required=True, help="User account") + parser.add_argument( + "-p", + "--pwd", + type=str, + default=None, + required=False, + help="Account password (optional if GPMPWD env variable is set)", + ) + parser.add_argument( + "-d", + "--debug", + action="store_true", + required=False, + help="Print out debug information (default is False)", + ) + + return vars(parser.parse_args()) + + +def delete_file(file_path): + try: + os.remove(file_path) + print(f"File '{file_path}' successfully removed.") + except FileNotFoundError: + print(f"File '{file_path}' not found.") + except PermissionError: + print(f"No permission to delete the file '{file_path}'.") + except Exception as e: + print(f"Error deleting file: {e}") + + +def robust_download(session, url, retries=5, backoff_factor=2, **kwargs): + """ + Download a file with retries and exponential backoff. + Args: + session (requests.Session): The requests session to use for the download. + url (str): The URL of the file to download. + retries (int): Number of retry attempts. + backoff_factor (int): Factor by which to increase wait time between retries. + **kwargs: Additional keyword arguments to pass to requests.get(). + Returns: + requests.Response: The response object if the download is successful. + None: If the download fails after all retries. + """ + for attempt in range(retries): + try: + response = session.get(url, timeout=600, **kwargs) + response.raise_for_status() + return response + except (requests.exceptions.Timeout, requests.exceptions.ConnectionError) as e: + wait_time = backoff_factor**attempt + print( + f"Attempt {attempt + 1} failed: {e}. Retrying in {wait_time} seconds..." + ) + time.sleep(wait_time) + except requests.exceptions.RequestException as e: + print(f"Permanent failure: {e}") + break + return None + + +def download_file(session, url, fname, local_dir, size, data_log): + """Download file using requests""" + status = "fine" + data_log.debug(url) + try: + # Optionally, set a timeout for the request to prevent hanging. + r = robust_download(session, url) + if r is None: + print(f"Failed to download {url} after multiple retries.") + sys.exit(1) + r.raise_for_status() # Optionally raise HTTPError for bad responses (4xx, 5xx) + except requests.exceptions.Timeout as e: + print("The request timed out:", e) + # Handle timeout, e.g., retry or log the error + sys.exit(1) + except requests.exceptions.ConnectionError as e: + print("A connection error occurred:", e) + # Handle connection error + sys.exit(1) + except requests.exceptions.HTTPError as e: + print("An HTTP error occurred:", e) + # Handle HTTP errors + sys.exit(1) + except requests.exceptions.RequestException as e: + print("An error occurred while making the request:", e) + # Handle any other type of request exception + sys.exit(1) + + with open(fname, "wb") as f: + f.write(r.content) + del r + + local_size = int(os.stat(fname).st_size) + if local_size < size: + status = "error" + + try: + timestamp, precipitation = crop_precipitation(fname) + + var_name = timestamp.strftime("%Y_%m_%d_%H_%M") + day_str = timestamp.strftime("%Y-%m-%d") + + file_path = f"{local_dir}/{day_str}.nc" + + update_or_create_netcdf(file_path, var_name, precipitation) + delete_file(fname) + + except Exception as e: + status = "error" + print(f"Error cropping file: {e}") + + return status + + +def update_or_create_netcdf(file_path, var_name, var_value): + """ + Atualiza ou cria um arquivo NetCDF. + + Args: + - file_path: Caminho do arquivo NetCDF. + - var_name: Nome da variável a ser adicionada. + - var_value: Valor da nova variável. + - dimensions: Dimensões para a variável (default: ('time',)). + """ + + # Verifica se o arquivo já existe + if os.path.exists(file_path): + print("Arquivo existe. Atualizando...") + # Abrir no modo append + with Dataset(file_path, mode="a") as dataset: + if var_name not in dataset.variables: + # Create dimensions based on the shape of the numpy array + for i, dim_size in enumerate(var_value.shape): + dim_name = f"dim_{i}_{var_name}" + if dim_name not in dataset.dimensions: + dataset.createDimension(dim_name, dim_size) + + # Create a variable with the timestamp as its name + var = dataset.createVariable( + var_name, + var_value.dtype, + tuple(f"dim_{i}_{var_name}" for i in range(var_value.ndim)), + ) + + # Assign the data from the numpy array to the variable + var[:] = var_value + + else: + print(f"A variável '{var_name}' já existe.") + else: + print("Arquivo não existe. Criando...") + # Criar novo arquivo NetCDF + with Dataset(file_path, mode="w") as nc: + # Create dimensions based on the shape of the numpy array + for i, dim_size in enumerate(var_value.shape): + dim_name = f"dim_{i}_{var_name}" + if dim_name not in nc.dimensions: + nc.createDimension(dim_name, dim_size) + + # Create a variable with the timestamp as its name + var = nc.createVariable( + var_name, + var_value.dtype, + tuple(f"dim_{i}_{var_name}" for i in range(var_value.ndim)), + ) + + # Assign the data from the numpy array to the variable + var[:] = var_value + + +def crop_precipitation(fname): + dataset = Dataset(fname, "r", format="NETCDF4") + + header = dataset.getncattr("FileHeader").split(";") + + for elem in header: + if "StartGranuleDateTime" in elem: + timestamp_str = elem.split("=")[1] + timestamp = datetime.fromisoformat(timestamp_str.replace("Z", "+00:00")) + + # Abrindo o arquivo + lat = dataset.variables["lat"][:] + lon = dataset.variables["lon"][:] + precipitation = dataset.variables["precipitation"] + + # Define the latitude bounds + lower_latitude_bound = globals.lat_min + upper_latitude_bound = globals.lat_max + + # Define the longitude bounds + lower_longitude_bound = globals.lon_min + upper_longitude_bound = globals.lon_max + + # Find latitude indices of elements within the bounds + indices_in_range_latitude = np.where( + (lat >= lower_latitude_bound) & (lat <= upper_latitude_bound) + )[0] + indices_in_range_longitude = np.where( + (lon >= lower_longitude_bound) & (lon <= upper_longitude_bound) + )[0] + precipitation_data = precipitation[0, indices_in_range_longitude, :][ + :, indices_in_range_latitude + ].T + + dataset.close() # Feche o arquivo para liberar o bloqueio + + return timestamp, precipitation_data + + +def download_yr(session, http_url, yr, data_dir, days, data_log): + """Download the whole year directory""" + r = session.get(f"{http_url}/{yr}/contents.html") + soup = BeautifulSoup(r.content, "html.parser") + status = {"new": [], "updated": [], "error": []} + # find all links with 3 digits indicating day of year folders + for link in soup.find_all("a", string=re.compile("^\d{3}/")): + subdir = link.get("href").rstrip() + if days != [] and subdir[:3] not in days: + data_log.debug(f"skipping {subdir[:3]}") + continue + r2 = session.get(f"{http_url}/{yr}/{subdir}") + soup2 = BeautifulSoup(r2.content, "html.parser") + # the same href file link is repeated in the html, + # so we need to keep track of what we already checked + done_list = [] + for sub in soup2.find_all("a", href=re.compile("^3B-HHR.*\.HDF5\..*\.html$")): + href = sub.get("href") + if sub.find_next("time"): + sub_next = sub.find_next("time") + last_mod = sub_next.text.strip() + size = sub_next.find_next("td").text.strip() + data_log.debug(f"{href}: {last_mod}, {size}") + if href in done_list: + continue + else: + done_list.append(href) + status = process_file( + session, + data_dir, + yr, + http_url, + subdir, + href, + last_mod, + int(size), + status, + data_log, + ) + if status == "error": + print(f"Downloading failed: {http_url}/{subdir}/{href}") + data_log.info(f"Download for year {yr} is complete") + return status + + +def process_file( + session, data_dir, yr, http_url, subdir, href, last_mod, size, status, data_log +): + """Check if file exists and/or needs updating, if new or to update, + download file + """ + fname = href.replace("HDF5.dmr.html", "nc") + local_name = f"{data_dir}/{yr}/{fname}" + local_dir = f"{data_dir}/{yr}" + if not os.path.exists(local_name): + data_log.debug(f"New file: {local_name}") + furl = ( + f"{http_url}/{yr}/" + + f"{subdir.replace('contents.html', '')}" + + f"{href.replace('.dmr.html', '.dap.nc4')}" + ) + data_log.debug(furl) + st = download_file(session, furl, local_name, local_dir, size, data_log) + if st == "error": + status["error"].append(local_name) + else: + status["new"].append(local_name) + else: + update = check_mdt(session, local_name, data_log, remoteModDate=last_mod) + if update: + os.remove(local_name) + st = download_file(session, furl, local_name, local_dir, size, data_log) + if st == "error": + status["error"].append(local_name) + else: + status["updated"].append(local_name) + return status + + +def open_session(usr, pwd): + """Open a requests session to manage connection to server""" + session = requests.session() + p = session.post("http://urs.earthdata.nasa.gov", {"user": usr, "password": pwd}) + print(f"session.post: {p}") + requests.utils.dict_from_cookiejar(session.cookies) + return session + + +def main(): + """ + Before running this script, perform the three steps described below. + + 1) Create an user account in the Earthdata Portal (https://urs.earthdata.nasa.gov/users/new) + + 2) Configure your username and password for authentication using a .netrc file + > cd ~ + > touch .netrc + > echo "machine urs.earthdata.nasa.gov login uid_goes_here password password_goes_here" > .netrc + > chmod 0600 .netrc + where uid_goes_here is your Earthdata Login username and password_goes_here is your Earthdata Login password. + Note that some password characters can cause problems. A backslash or space anywhere in your password will need to be escaped with an additional backslash. + Similarly, if you use a '#' as the first character of your password, it will also need to be escaped with a preceding backslash. + Depending on your environment, the use of double-quotes " may be turned into "smart-quotes" automatically. We recommend turning this feature off. + Some users have found that the double quotes are not supported by their systems. + Some users have found that the > is aliased to >> on some machines. + This will append the text instead of overwrite the text. + We recommend checking your ~/.netrc file to ensure it only has one line. + + 3) Create a cookie file. + This will be used to persist sessions across individual cURL/Wget calls, making it more efficient. + > cd ~ + > touch .urs_cookies + """ + args = parse_input() + + begin_date = datetime.strptime(args["begin_date"], "%Y/%m/%d") + end_date = datetime.strptime(args["end_date"], "%Y/%m/%d") + user = args["user"] + + if begin_date > end_date: + raise ValueError("begin_date must be earlier than or equal to end_date") + + if begin_date.year != end_date.year: + raise ValueError("Date range must be within the same year") + + yr = str(begin_date.year) + ignored_months = args.get("ignored_months", []) + + # Gerar lista de dias julianos válidos + delta = end_date - begin_date + days = [] + for i in range(delta.days + 1): + current_date = begin_date + timedelta(days=i) + if current_date.month not in ignored_months: + julian_day = str(current_date.timetuple().tm_yday).zfill(3) + days.append(julian_day) + + try: + pwd = args["pwd"] + if pwd is None: + pwd = os.getenv("GPMPWD") + except KeyError as e: + print(f"Pass a password as input or set the GPMPWD variable: {e}") + + today = datetime.today().strftime("%Y-%m-%d") + sys_user = os.getenv("USER") + root_dir = os.getenv("AUSREFDIR", ".") + run_dir = f"{root_dir}" + + http_url = ( + "https://gpm1.gesdisc.eosdis.nasa.gov/opendap/hyrax/GPM_L3/GPM_3IMERGHH.07" + ) + data_dir = f"{root_dir}/data/GPM" + flog = f"{run_dir}/gpm_update_log.txt" + + level = "info" + if args.get("debug", False): + level = "debug" + data_log = set_log("gpmlog", flog, level) + + directory = f"{data_dir}/{yr}" + if not os.path.exists(directory): + os.mkdir(directory) + print(f"Directory '{directory}' created.") + else: + print(f"Directory '{directory}' already exists.") + + session = open_session(user, pwd) + status = download_yr(session, http_url, yr, data_dir, days, data_log) + + data_log.info(f"Updated on {today} by {sys_user}") + print_summary(status["updated"], status["new"], status["error"], data_log) + + +if __name__ == "__main__": + main() diff --git a/src/gpm/gpm_plot.py b/src/gpm/gpm_plot.py new file mode 100644 index 00000000..a5cc8171 --- /dev/null +++ b/src/gpm/gpm_plot.py @@ -0,0 +1,80 @@ +import os + +import cartopy.crs as ccrs +import cartopy.feature as cfeature +import imageio +import matplotlib.pyplot as plt +import xarray as xr + + +def create_imerg_animation(input_dir, output_file): + # Ensure the output directory exists + print(f"Output file: {output_file}") + os.makedirs(os.path.dirname(output_file), exist_ok=True) + + # Get all NetCDF files in the input directory + files = sorted( + [os.path.join(input_dir, f) for f in os.listdir(input_dir) if f.endswith(".nc")] + ) + if not files: + print("No IMERG NetCDF files found in the input directory.") + return + + # List to store temporary frame files + frames = [] + + # Create a figure for visualization + fig, ax = plt.subplots( + subplot_kw={"projection": ccrs.PlateCarree()}, figsize=(10, 6) + ) + + for file in files: + # Load data from NetCDF + print(f"Opening file {file}") + data = xr.open_dataset(file) + lats = data["lat"].values + lons = data["lon"].values + precipitation = data["precipitationCal"].values[ + 0 + ] # Assuming time is the first dimension + + # Plot data + ax.clear() + ax.set_extent([lons.min(), lons.max(), lats.min(), lats.max()]) + ax.add_feature(cfeature.COASTLINE) + ax.add_feature(cfeature.BORDERS, linestyle=":") + ax.add_feature(cfeature.LAND, edgecolor="black") + im = ax.pcolormesh( + lons, lats, precipitation, transform=ccrs.PlateCarree(), cmap="coolwarm" + ) + plt.colorbar( + im, ax=ax, orientation="horizontal", pad=0.05, label="Precipitation (mm/h)" + ) + plt.title( + f"GPM IMERG: {data.time.values[0]}" + ) # Adjust as per dataset time format + + # Save the frame + frame_file = f"frame_{len(frames):04d}.png" + plt.savefig(frame_file) + frames.append(frame_file) + + # Close the dataset to save memory + data.close() + + # Create MP4 animation using imageio + with imageio.get_writer(output_file, fps=2) as writer: + for frame in frames: + writer.append_data(imageio.imread(frame)) + + # Clean up temporary frames + for frame in frames: + os.remove(frame) + + print(f"Animation saved as {output_file}") + + +# Example usage +input_directory = "./data/GPM/2024" +output_animation = "./imerg_animation.mp4" +create_imerg_animation(input_directory, output_animation) diff --git a/src/plot_CAPE.py b/src/plot_CAPE.py deleted file mode 100644 index 9c7c94e4..00000000 --- a/src/plot_CAPE.py +++ /dev/null @@ -1,186 +0,0 @@ -# Training: Python and GOES-R Imagery: Script 17 - Level 2 Products (RRQPE) and Data Accumulation -#----------------------------------------------------------------------------------------------------------- -# Required modules -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import timedelta, date, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -from osgeo import gdal # Python bindings for GDAL -import numpy as np # Scientific computing with Python -from matplotlib import cm # Colormap handling utilities -from goes16_utils import download_PROD # Our function for download -from goes16_utils import reproject # Our function for reproject -from goes16_utils import geo2grid -gdal.PushErrorHandler('CPLQuietErrorHandler') # Ignore GDAL warnings -import sys - -def plot_data_for_this_timestamp(filename_reprojected, extent, variable_name, yyyymmddhhmn): - print(f'extent: {extent}') - #----------------------------------------------------------------------------------------------------------- - # Open the reprojected GOES-R image - file_reprojected = Dataset(filename_reprojected) - - # Read file netcdf with estimated rain from GOES-16 - sat_data = gdal.Open(f'{filename_reprojected}') - # Read number of cols and rows - ncol = sat_data.RasterXSize - nrow = sat_data.RasterYSize - # Load the data - sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) - # print(type(sat_array)) - # print(f'sat_array.shape = {sat_array.shape}') - - # Get geotransform - transform = sat_data.GetGeoTransform() - # print(f'ncol, nrow = {(ncol, nrow)}') - # lat, lon = -22.98833333,-43.19055555 - # x_float = (lon - transform[0]) / transform[1] - # y_float = (transform[3] - lat) / -transform[5] - # x = int(x_float) - # y = int(y_float) - # print(f'(x_float,y_float) = {(x,y)}') - # print(f'(x,y) = {(x,y)}') - # sat = sat_array[y,x] - # print(f'*VALUE = {sat}') - - #----------------------------------------------------------------------------------------------------------- - # Choose the plot size (width x height, in inches) - plt.figure(figsize=(10,10)) - - # Use the Geostationary projection in cartopy - ax = plt.axes(projection=ccrs.PlateCarree()) - - # Define the image extent - img_extent = [extent[0], extent[2], extent[1], extent[3]] - - # Modify the colormap to zero values are white - colormap = plt.get_cmap('rainbow').resampled(240) - - newcolormap = colormap(np.linspace(0, 1, 240)) - newcolormap[:1, :] = np.array([1, 1, 1, 1]) - cmap = cm.colors.ListedColormap(newcolormap) - - # #- Plot WSoI location ---------------------------------------------------------------------------------------- - # Define the coordinates to extract the data (lat,lon) <- pairs - coordinates = [('A652', -22.98833333,-43.19055555)] - - for label, lat, lon in coordinates: - # Reading coordinate of a WSoI - lat_point = lat - lon_point = lon - - x = int((lon - transform[0]) / transform[1]) - y = int((transform[3] - lat) / -transform[5]) - variable_point = sat_array[y,x] - print(f'**VALUE = {variable_point}') - - # Adding WSoI as an annotation - ax.plot(lon_point, lat_point, 'x', color='black', markersize=2, transform=ccrs.Geodetic(), markeredgewidth=1.0, markeredgecolor=(0, 0, 0, 1), zorder=8) - - # Add a text - txt_offset_x = 0.4 - txt_offset_y = 0.4 - - plt.annotate(label + "\n" + "Lat: " + str(lat_point) + "\n" + "Lon: " + str(lon_point) + "\n" + variable_name + ": " + str(variable_point) + '', - xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), - fontsize=10, fontweight='bold', color='gold', bbox=dict(boxstyle="round",fc=(0.0, 0.0, 0.0, 0.5), ec=(1., 1., 1.)), alpha = 1.0, zorder=9) - - #----------------------------------------------------------------------------------------------------------- - - #- Plot product image ---------------------------------------------------------------------------------------- - img = ax.imshow(sat_array, vmin=0, vmax=150, cmap=cmap, origin='upper', extent=img_extent) - - # Add coastlines, borders and gridlines - ax.coastlines(resolution='10m', color='black', linewidth=0.8) - ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5) - gl = ax.gridlines(crs=ccrs.PlateCarree(), color='gray', alpha=1.0, linestyle='--', linewidth=0.25, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), draw_labels=True) - plt.xlim(extent[0], extent[2]) - plt.ylim(extent[1], extent[3]) - - # Add a colorbar - plt.colorbar(img, label=variable_name, extend='max', orientation='horizontal', pad=0.05, fraction=0.05) - - # Extract date - date = (datetime.strptime(dtime, '%Y-%m-%dT%H:%M:%S.%fZ')) - - # Add a title - plt.title(f'G-16-DSIF {variable_name}', fontweight='bold', fontsize=10, loc='left') - plt.title(f'Timestamp: {yyyymmddhhmn}', fontsize=10, loc='right') - #----------------------------------------------------------------------------------------------------------- - # Save the image - plt.savefig(f'{output}/{variable_name}_{yyyymmddhhmn}.png', bbox_inches='tight', pad_inches=0, dpi=300) - - plt.close() - -if __name__ == "__main__": - temp_dir = "./data/goes16/temp" - output = "./data/goes16/Animation" - - # Desired extent - extent = [-74.0, -34.1, -34.8, 5.5] # Min lon, Max lon, Min lat, Max lat - # extent = [-64.0, -35.0, -35.0, -15.0] # Min lon, Min lat, Max lon, Max lat - # extent = [-45, -25, -40, -20] - # extent = [-44, -24, -42, -20] - - # Parameters to process - yyyymmdd = '20201217' - product_name = 'ABI-L2-DSIF' - - # Initial time and date - yyyy = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%Y') - mm = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%m') - dd = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%d') - - date_ini = str(datetime(int(yyyy),int(mm),int(dd),12,0) - timedelta(hours=23)) - date_end = str(datetime(int(yyyy),int(mm),int(dd),12,0)) - - acum = np.zeros((1086,1086)) - - #----------------------------------------------------------------------------------------------------------- - # Loop to produce sequence of images (animation) - while (date_ini <= date_end): - - # Date structure - yyyymmddhhmn = datetime.strptime(date_ini, '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') - - # Download file for current timestamp - filename_downloaded = download_PROD(yyyymmddhhmn, product_name, temp_dir) - #----------------------------------------------------------------------------------------------------------- - # Variable - variable_name = 'CAPE' - - # Open the file - img = gdal.Open(f'NETCDF:{temp_dir}/{filename_downloaded}.nc:' + variable_name) - dqf = gdal.Open(f'NETCDF:{temp_dir}/{filename_downloaded}.nc:DQF_Overall') - - # Read the header metadata - metadata = img.GetMetadata() - scale = float(metadata.get(variable_name + '#scale_factor')) - offset = float(metadata.get(variable_name + '#add_offset')) - undef = float(metadata.get(variable_name + '#_FillValue')) - dtime = metadata.get('NC_GLOBAL#time_coverage_start') - - # Load the data - ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) - ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float) - - # Remove undef - ds[ds == undef] = np.nan - - # Apply the scale and offset - ds = (ds * scale + offset) - - # Apply NaN's where the quality flag is greater than 0 - ds[ds_dqf > 0] = np.nan - - # Reproject the file - filename_reprojected = f'{output}/{variable_name}_{yyyymmddhhmn}.nc' - reproject(filename_reprojected, img, ds, extent, undef) - plot_data_for_this_timestamp(filename_reprojected, extent, variable_name, yyyymmddhhmn) - - sys.exit(1) - - # Increment 1 hour - date_ini = str(datetime.strptime(date_ini, '%Y-%m-%d %H:%M:%S') + timedelta(minutes=10)) - #----------------------------------------------------------------------------------------------------------- diff --git a/src/plot_CAPE_OLD.py b/src/plot_CAPE_OLD.py deleted file mode 100644 index 61d5f458..00000000 --- a/src/plot_CAPE_OLD.py +++ /dev/null @@ -1,211 +0,0 @@ -#----------------------------------------------------------------------------------------------------------- -# Agrometeorology Course - Demonstration: Normalized Difference Vegetation Index (NDVI) - Extract Values -# Author: Diego Souza -#----------------------------------------------------------------------------------------------------------- -# Required modules -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import datetime # Basic Dates and time types -from datetime import timedelta, date, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import cartopy.io.shapereader as shpreader # Import shapefiles -import cartopy.feature as cfeature # Cartopy features -from osgeo import gdal # Python bindings for GDAL -import numpy as np # Scientific computing with Python -import os # Miscellaneous operating system interfaces -from goes16_utils import download_PROD # Our own utilities -from goes16_utils import geo2grid, latlon2xy, convertExtent2GOESProjection # Our own utilities -#----------------------------------------------------------------------------------------------------------- -# Input and output directories -temp_dir = "./data/goes16/temp" -output = "./data/goes16/Animation" - -# # Desired extent -# extent = [-93.0, -60.00, -25.00, 15.00] # Min lon, Min lat, Max lon, Max lat -extent = [-74.0, -34.1, -34.8, 5.5] # Min lon, Max lon, Min lat, Max lat - -# Coordinates of rectangle for region of interest (Rio de Janeiro municipality) -# extent = [-64.0, -35.0, -35.0, -15.0] # Min lon, Min lat, Max lon, Max lat - -# Initial date and time to process -date_ini = '202201011800' - -# Number of days to accumulate -ndays = 1 - -prod_name = 'ABI-L2-DSIF' -variable_name = 'CAPE' - -# prod_name = 'ABI-L2-SSTF' -# variable_name = 'SST' - -# product_name = 'ABI-L2-RRQPEF' -# variable_name = 'RRQPE' - - -# Convert to datetime -date_ini = datetime(int(date_ini[0:4]), int(date_ini[4:6]), int(date_ini[6:8]), int(date_ini[8:10]), int(date_ini[10:12])) -date_end = date_ini + timedelta(days=ndays) - -# Create our references for the loop -date_loop = date_ini - -#----------------------------------------------------------------------------------------------------------- -# NDVI colormap creation -import matplotlib -colors = ["#8f2723", "#8f2723", "#8f2723", "#8f2723", "#af201b", "#af201b", "#af201b", "#af201b", "#ce4a2e", "#ce4a2e", "#ce4a2e", "#ce4a2e", - "#df744a", "#df744a", "#df744a", "#df744a", "#f0a875", "#f0a875", "#f0a875", "#f0a875", "#fad398", "#fad398", "#fad398", "#fad398", - "#fff8ba", - "#d8eda0", "#d8eda0", "#d8eda0", "#d8eda0", "#bddd8a", "#bddd8a", "#bddd8a", "#bddd8a", "#93c669", "#93c669", "#93c669", "#93c669", - "#5da73e", "#5da73e", "#5da73e", "#5da73e", "#3c9427", "#3c9427", "#3c9427", "#3c9427", "#235117", "#235117", "#235117", "#235117"] -cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", colors) -cmap.set_over('#235117') -cmap.set_under('#8f2723') -vmin = 0.1 -vmax = 0.8 -#----------------------------------------------------------------------------------------------------------- - -# Variable to check if is the first iteration -first = True - -# Create our references for the loop -date_loop = date_ini - -while (date_loop <= date_end): - - # Date structure - yyyymmddhhmn = date_loop.strftime('%Y%m%d%H%M') - print(yyyymmddhhmn) - - # Download the Full Disk file - file_name = download_PROD(yyyymmddhhmn, prod_name, temp_dir) - - #----------------------------------------------------------------------------------------------------------- - - # Open the file - img = gdal.Open(f'NETCDF:{temp_dir}/{file_name}.nc:' + variable_name) - dqf = gdal.Open(f'NETCDF:{temp_dir}/{file_name}.nc:DQF_Overall') - - # Read the header metadata - metadata = img.GetMetadata() - scale = float(metadata.get(variable_name + '#scale_factor')) - offset = float(metadata.get(variable_name + '#add_offset')) - undef = float(metadata.get(variable_name + '#_FillValue')) - dtime = metadata.get('NC_GLOBAL#time_coverage_start') - print(f'scale, offset, undef, dtime = {(scale, offset, undef, dtime)}') - - #----------------------------------------------------------------------------------------------------------- - - # If file hasn't been downloaded for some reason, skip the current iteration - if not (os.path.exists(f'{temp_dir}/{file_name}.nc')): - # Increment the date_loop - date_loop = date_loop + timedelta(days=1) - print("The file is not available, skipping this iteration.") - continue - - # Open the Full Disk file - file = Dataset(f'{temp_dir}/{file_name}.nc') - print(f'file.dimensions from Dataset instantiation: {file.dimensions}') - - ############################## - lat_point, lon_point = -22.98833333,-43.19055555 - lat_ind, lon_ind = geo2grid(lat_point, lon_point, file) - print(f'lat_ind, lon_ind: {(lat_ind, lon_ind)}\n') - ############################## - - - # Convert lat/lon to grid-coordinates - lly, llx = geo2grid(extent[1], extent[0], file) - ury, urx = geo2grid(extent[3], extent[2], file) - print(f'lly, llx, ury, urx: {(lly, llx, ury, urx)}\n') - - # print(f'file.variables: {file.variables}\n') - - # Get the pixel values - data = file.variables[variable_name][ury:lly, llx:urx] - # data = file.variables[variable_name][ury:lly, llx:urx][::2 ,::2] - print(type(data)) - print(f'data.shape: {data.shape}') - - #----------------------------------------------------------------------------------------------------------- - - # Calculate the NDVI - # TODO, TODO - # data = (data_ch03 - data_ch02) / (data_ch03 + data_ch02) - - #----------------------------------------------------------------------------------------------------------- - - # Compute data-extent in GOES projection-coordinates - img_extent = convertExtent2GOESProjection(extent) - - #----------------------------------------------------------------------------------------------------------- - - # Choose the plot size (width x height, in inches) - plt.figure(figsize=(15,15)) - - # Use the Geostationary projection in cartopy - ax = plt.axes(projection=ccrs.Geostationary(central_longitude=-75.0, satellite_height=35786023.0)) - - # Add a land mask - ax.stock_img() - land = ax.add_feature(cfeature.LAND, facecolor='gray', zorder=1) - - #----------------------------------------------------------------------------------------------------------- - # Define the coordinates to extract the data (lat,lon) <- pairs - coordinates = [('A652', -22.98833333,-43.19055555)] - - for label, lat, lon in coordinates: - # Reading the data from a coordinate - lat_point = lat - lon_point = lon - - # Convert lat/lon to grid-coordinates - lat_ind, lon_ind = geo2grid(lat_point, lon_point, file) - print(f'Current (x,y)={(lat_ind, lon_ind)}') - print(f'lat_ind - ury, lon_ind - llx = {(lat_ind - ury, lon_ind - llx)}') - variable_point = (data[lat_ind - ury, lon_ind - llx]).round(2) - - # Adding the data as an annotation - # Add a circle - ax.plot(lon_point, lat_point, 'o', color='black', markersize=3, transform=ccrs.Geodetic(), markeredgewidth=1.0, markeredgecolor=(0, 0, 0, 1), zorder=8) - - # Add a text - txt_offset_x = 0.8 - txt_offset_y = 0.8 - - plt.annotate(label + "\n" + "Lat: " + str(lat_point) + "\n" + "Lon: " + str(lon_point) + "\n" + variable_name + ": " + str(variable_point) + '', - xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), - fontsize=10, fontweight='bold', color='gold', bbox=dict(boxstyle="round",fc=(0.0, 0.0, 0.0, 0.5), ec=(1., 1., 1.)), alpha = 1.0, zorder=9) - - #----------------------------------------------------------------------------------------------------------- - - # Plot the image - img = ax.imshow(data, origin='upper', vmin=vmin, vmax=vmax, extent=img_extent, cmap=cmap, zorder=2) - - # Add a shapefile - shapefile = list(shpreader.Reader('./data/natural_earth/ne_10m_admin_1_states_provinces.shp').geometries()) - ax.add_geometries(shapefile, ccrs.PlateCarree(), edgecolor='dimgray',facecolor='none', linewidth=0.3, zorder=4) - - # Add coastlines, borders and gridlines - ax.coastlines(resolution='10m', color='black', linewidth=0.8, zorder=5) - ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5, zorder=6) - ax.gridlines(color='gray', alpha=0.5, linestyle='--', linewidth=0.5, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), zorder=7) - - # Add a colorbar - plt.colorbar(img, label=variable_name, extend='both', orientation='vertical', pad=0.05, fraction=0.05) - - # Extract date - date = (datetime.strptime(file.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ')) - - # Add a title - plt.title('GOES-16 CAPE ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC', fontweight='bold', fontsize=10, loc='left') - plt.title('ROI: ' + str(extent) , fontsize=10, loc='right') - - # Save the image - plt.savefig(f'{output}/G16_{variable_name}_{yyyymmddhhmn}.png', bbox_inches='tight', pad_inches=0, dpi=300) - - # Show the image - plt.show() - - # Increment the date_loop - date_loop = date_loop + timedelta(days=1) \ No newline at end of file diff --git a/src/plot_CMI.py b/src/plot_CMI.py deleted file mode 100644 index 18ae9a38..00000000 --- a/src/plot_CMI.py +++ /dev/null @@ -1,210 +0,0 @@ -#----------------------------------------------------------------------------------------------------------- -# Agrometeorology Course - Demonstration: Normalized Difference Vegetation Index (NDVI) - Extract Values -# Author: Diego Souza -#----------------------------------------------------------------------------------------------------------- -# Required modules -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import datetime # Basic Dates and time types -from datetime import timedelta, date, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import cartopy.io.shapereader as shpreader # Import shapefiles -import cartopy.feature as cfeature # Cartopy features -import numpy as np # Scientific computing with Python -import os # Miscellaneous operating system interfaces -from goes16_utils import download_CMI # Our own utilities -from goes16_utils import geo2grid, latlon2xy, convertExtent2GOESProjection # Our own utilities -#----------------------------------------------------------------------------------------------------------- -# Input and output directories -input = "./data/goes16/Samples" -output = "./data/goes16/Animation" - -# Desired extent -extent = [-93.0, -60.00, -25.00, 15.00] # Min lon, Min lat, Max lon, Max lat - -# Initial date and time to process -date_ini = '202201011800' - -# Number of days to accumulate -ndays = 1 - -# Convert to datetime -date_ini = datetime(int(date_ini[0:4]), int(date_ini[4:6]), int(date_ini[6:8]), int(date_ini[8:10]), int(date_ini[10:12])) -date_end = date_ini + timedelta(days=ndays) - -# Create our references for the loop -date_loop = date_ini - -#----------------------------------------------------------------------------------------------------------- -# NDVI colormap creation -import matplotlib -colors = ["#8f2723", "#8f2723", "#8f2723", "#8f2723", "#af201b", "#af201b", "#af201b", "#af201b", "#ce4a2e", "#ce4a2e", "#ce4a2e", "#ce4a2e", - "#df744a", "#df744a", "#df744a", "#df744a", "#f0a875", "#f0a875", "#f0a875", "#f0a875", "#fad398", "#fad398", "#fad398", "#fad398", - "#fff8ba", - "#d8eda0", "#d8eda0", "#d8eda0", "#d8eda0", "#bddd8a", "#bddd8a", "#bddd8a", "#bddd8a", "#93c669", "#93c669", "#93c669", "#93c669", - "#5da73e", "#5da73e", "#5da73e", "#5da73e", "#3c9427", "#3c9427", "#3c9427", "#3c9427", "#235117", "#235117", "#235117", "#235117"] -cmap = matplotlib.colors.LinearSegmentedColormap.from_list("", colors) -cmap.set_over('#235117') -cmap.set_under('#8f2723') -vmin = 0.1 -vmax = 0.8 -#----------------------------------------------------------------------------------------------------------- - -# Variable to check if is the first iteration -first = True - -# Create our references for the loop -date_loop = date_ini - -while (date_loop <= date_end): - - # Date structure - yyyymmddhhmn = date_loop.strftime('%Y%m%d%H%M') - print(yyyymmddhhmn) - - # Download the file for Band 02 - file_name_ch02 = download_CMI(yyyymmddhhmn, '2', input) - - # Download the file for Band 03 - file_name_ch03 = download_CMI(yyyymmddhhmn, '3', input) - - #----------------------------------------------------------------------------------------------------------- - - # If one the files hasn't been downloaded for some reason, skip the current iteration - if not (os.path.exists(f'{input}/{file_name_ch02}.nc')) or not (os.path.exists(f'{input}/{file_name_ch03}.nc')): - # Increment the date_loop - date_loop = date_loop + timedelta(days=1) - print("The file is not available, skipping this iteration.") - continue - - # Open the GOES-R image (Band 02) - file = Dataset(f'{input}/{file_name_ch02}.nc') - print(f'file.dimensions for file_name_ch02: {file.dimensions}') - - # Convert lat/lon to grid-coordinates - lly, llx = geo2grid(extent[1], extent[0], file) - ury, urx = geo2grid(extent[3], extent[2], file) - print(f'file_name_ch02 --> lly, llx, ury, urx: {(lly, llx, ury, urx)}') - - # Get the pixel values - data_ch02 = file.variables['CMI'][ury:lly, llx:urx][::2 ,::2] - print(type(data_ch02)) - print(f'data_ch02.shape: {data_ch02.shape}') - - #----------------------------------------------------------------------------------------------------------- - - # Open the GOES-R image (Band 03) - file = Dataset(f'{input}/{file_name_ch03}.nc') - print(f'file.dimensions for file_name_ch03: {file.dimensions}') - - # Convert lat/lon to grid-coordinates - lly, llx = geo2grid(extent[1], extent[0], file) - ury, urx = geo2grid(extent[3], extent[2], file) - print(f'file_name_ch03 --> lly, llx, ury, urx: {(lly, llx, ury, urx)}') - - # Get the pixel values - data_ch03 = file.variables['CMI'][ury:lly, llx:urx] - print(type(data_ch03)) - print(f'data_ch03.shape: {data_ch03.shape}') - - #----------------------------------------------------------------------------------------------------------- - - # Make the arrays equal size - cordX = np.shape(data_ch02)[0], np.shape(data_ch03)[0] - cordY = np.shape(data_ch02)[1], np.shape(data_ch03)[1] - - minvalX = np.array(cordX).min() - minvalY = np.array(cordY).min() - - data_ch02 = data_ch02[0:minvalX, 0:minvalY] - data_ch03 = data_ch03[0:minvalX, 0:minvalY] - - #----------------------------------------------------------------------------------------------------------- - - # Calculate the NDVI - data = (data_ch03 - data_ch02) / (data_ch03 + data_ch02) - - #----------------------------------------------------------------------------------------------------------- - - # Compute data-extent in GOES projection-coordinates - img_extent = convertExtent2GOESProjection(extent) - - #----------------------------------------------------------------------------------------------------------- - - # If it's the first iteration, create the array that will store the max values - if (first == True): - first = False - ndvi_max = np.full((data_ch02.shape[0],data_ch02.shape[1]),-9999) - - # Keep the maximuns, ignoring the nans - ndvi_max = np.fmax(data,ndvi_max) - # Remove low values from the accumulation - ndvi_max[ndvi_max < 0.1] = np.nan - - # Choose the plot size (width x height, in inches) - plt.figure(figsize=(15,15)) - - # Use the Geostationary projection in cartopy - ax = plt.axes(projection=ccrs.Geostationary(central_longitude=-75.0, satellite_height=35786023.0)) - - # Add a land mask - ax.stock_img() - land = ax.add_feature(cfeature.LAND, facecolor='gray', zorder=1) - - #----------------------------------------------------------------------------------------------------------- - # Define the coordinates to extract the data (lat,lon) <- pairs - coordinates = [('P1', 0,-60), ('P2', -5,-70), ('P3', -10,-55), ('P4', -20,-50)] - - for label, lat, lon in coordinates: - # Reading the data from a coordinate - lat_point = lat - lon_point = lon - - # Convert lat/lon to grid-coordinates - lat_ind, lon_ind = geo2grid(lat_point, lon_point, file) - NDVI_point = (ndvi_max[lat_ind - ury, lon_ind - llx]).round(2) - - # Adding the data as an annotation - # Add a circle - ax.plot(lon_point, lat_point, 'o', color='red', markersize=5, transform=ccrs.Geodetic(), markeredgewidth=1.0, markeredgecolor=(0, 0, 0, 1), zorder=8) - - # Add a text - txt_offset_x = 0.8 - txt_offset_y = 0.8 - - plt.annotate(label + "\n" + "Lat: " + str(lat_point) + "\n" + "Lon: " + str(lon_point) + "\n" + "NDVI: " + str(NDVI_point) + '', - xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), - fontsize=10, fontweight='bold', color='gold', bbox=dict(boxstyle="round",fc=(0.0, 0.0, 0.0, 0.5), ec=(1., 1., 1.)), alpha = 1.0, zorder=9) - - #----------------------------------------------------------------------------------------------------------- - - # Plot the image - img = ax.imshow(ndvi_max, origin='upper', vmin=vmin, vmax=vmax, extent=img_extent, cmap=cmap, zorder=2) - - # Add a shapefile - shapefile = list(shpreader.Reader('./data/natural_earth/ne_10m_admin_1_states_provinces.shp').geometries()) - ax.add_geometries(shapefile, ccrs.PlateCarree(), edgecolor='dimgray',facecolor='none', linewidth=0.3, zorder=4) - - # Add coastlines, borders and gridlines - ax.coastlines(resolution='10m', color='black', linewidth=0.8, zorder=5) - ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5, zorder=6) - ax.gridlines(color='gray', alpha=0.5, linestyle='--', linewidth=0.5, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), zorder=7) - - # Add a colorbar - plt.colorbar(img, label='Normalized Difference Vegetation Index', extend='both', orientation='vertical', pad=0.05, fraction=0.05) - - # Extract date - date = (datetime.strptime(file.time_coverage_start, '%Y-%m-%dT%H:%M:%S.%fZ')) - - # Add a title - plt.title('GOES-16 NDVI ' + date.strftime('%Y-%m-%d %H:%M') + ' UTC', fontweight='bold', fontsize=10, loc='left') - plt.title('Reg.: ' + str(extent) , fontsize=10, loc='right') - - # Save the image - plt.savefig(f'{output}/G16_NDVI_{yyyymmddhhmn}.png', bbox_inches='tight', pad_inches=0, dpi=300) - - # Show the image - plt.show() - - # Increment the date_loop - date_loop = date_loop + timedelta(days=1) \ No newline at end of file diff --git a/src/plot_DSIF.py b/src/plot_DSIF.py deleted file mode 100644 index f8ab759b..00000000 --- a/src/plot_DSIF.py +++ /dev/null @@ -1,220 +0,0 @@ -# Training: Python and GOES-R Imagery: Script 17 - Level 2 Products (RRQPE) and Data Accumulation -#----------------------------------------------------------------------------------------------------------- -# Required modules -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import timedelta, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os -import sys -import argparse -import pandas as pd # Miscellaneous operating system interfaces -from osgeo import gdal # Python bindings for GDAL -import numpy as np # Scientific computing with Python -from matplotlib import cm # Colormap handling utilities -from goes16_utils import download_PROD # Our function for download -from goes16_utils import reproject # Our function for reproject -from goes16_utils import geo2grid -gdal.PushErrorHandler('CPLQuietErrorHandler') # Ignore GDAL warnings - - -def fill_pixel_values(sat_array, x, y, resolution): - list_pixel_values = [] - for i in range(x-resolution, x+resolution+1): - for j in range(y-resolution, y+resolution+1): - list_pixel_values = np.append(list_pixel_values, sat_array[j, i]) - print(list_pixel_values) - return np.array(list_pixel_values) - - -def plot_data_for_this_timestamp(filename_reprojected, extent, index_name, yyyymmddhhmn, ws_id, dtime): - #----------------------------------------------------------------------------------------------------------- - # Open the reprojected GOES-R image - file_reprojected = Dataset(filename_reprojected) - - # Read file netcdf with estimated rain from GOES-16 - sat_data = gdal.Open(f'{filename_reprojected}') - # Read number of cols and rows - ncol = sat_data.RasterXSize - nrow = sat_data.RasterYSize - # Load the data - sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) - # print(type(sat_array)) - # print(f'sat_array.shape = {sat_array.shape}') - - # Get geotransform - transform = sat_data.GetGeoTransform() - # print(f'ncol, nrow = {(ncol, nrow)}') - # lat, lon = -22.98833333,-43.19055555 - # x_float = (lon - transform[0]) / transform[1] - # y_float = (transform[3] - lat) / -transform[5] - # x = int(x_float) - # y = int(y_float) - # print(f'(x_float,y_float) = {(x,y)}') - # print(f'(x,y) = {(x,y)}') - # sat = sat_array[y,x] - # print(f'*VALUE = {sat}') - - # ----------------------------------------------------------------------------------------------------------- - # Choose the plot size (width x height, in inches) - plt.figure(figsize=(10,10)) - - # Use the Geostationary projection in cartopy - ax = plt.axes(projection=ccrs.PlateCarree()) - - # Define the image extent - img_extent = [extent[0], extent[2], extent[1], extent[3]] - - # Modify the colormap to zero values are white - colormap = plt.get_cmap('rainbow').resampled(240) - - newcolormap = colormap(np.linspace(0, 1, 240)) - newcolormap[:1, :] = np.array([1, 1, 1, 1]) - cmap = cm.colors.ListedColormap(newcolormap) - - # #- Plot WSoI location ---------------------------------------------------------------------------------------- - # Define the coordinates to extract the data (lat,lon) <- pairs - coordinates = [(ws_id, -22.98833333, -43.19055555)] - - for label, lat, lon in coordinates: - # Reading coordinate of a WSoI - lat_point = lat - lon_point = lon - - x = int((lon - transform[0]) / transform[1]) - y = int((transform[3] - lat) / -transform[5]) - variable_list_values = fill_pixel_values(sat_array, x, y, 1) - # print(f'**VALUE = {variable_point}') - - # Adding WSoI as an annotation - ax.plot(lon_point, lat_point, 'x', color='black', markersize=2, transform = ccrs.Geodetic(), markeredgewidth=1.0, markeredgecolor=(0, 0, 0, 1), zorder=8) - - # Add a text - txt_offset_x = 0.4 - txt_offset_y = 0.4 - - plt.annotate(label + "\n" + "Lat: " + str(lat_point) + "\n" + "Lon: " + str(lon_point) + "\n" + index_name + ": " + str(index_name) + '', - xy=(lon_point + txt_offset_x, lat_point + txt_offset_y), xycoords=ccrs.PlateCarree()._as_mpl_transform(ax), - fontsize=10, fontweight='bold', color='gold', bbox=dict(boxstyle="round",fc=(0.0, 0.0, 0.0, 0.5), ec=(1., 1., 1.)), alpha = 1.0, zorder=9) - - #----------------------------------------------------------------------------------------------------------- - - #- Plot product image ---------------------------------------------------------------------------------------- - img = ax.imshow(sat_array, vmin=0, vmax=150, cmap=cmap, origin='upper', extent=img_extent) - - # Add coastlines, borders and gridlines - ax.coastlines(resolution='10m', color='black', linewidth=0.8) - ax.add_feature(cartopy.feature.BORDERS, edgecolor='black', linewidth=0.5) - gl = ax.gridlines(crs=ccrs.PlateCarree(), color='gray', alpha=1.0, linestyle='--', linewidth=0.25, xlocs=np.arange(-180, 180, 5), ylocs=np.arange(-90, 90, 5), draw_labels=True) - plt.xlim(extent[0], extent[2]) - plt.ylim(extent[1], extent[3]) - - # Add a colorbar - plt.colorbar(img, label=index_name, extend='max', orientation='horizontal', pad=0.05, fraction=0.05) - - # Extract date - date = (datetime.strptime(dtime, '%Y-%m-%dT%H:%M:%S.%fZ')) - - # Add a title - plt.title(f'G-16-DSIF {index_name}', fontweight='bold', fontsize=10, loc='left') - plt.title(f'Timestamp: {yyyymmddhhmn}', fontsize=10, loc='right') - #----------------------------------------------------------------------------------------------------------- - # Save the image - plt.savefig(f'{output}/{index_name}_{yyyymmddhhmn}.png', bbox_inches='tight', pad_inches=0, dpi=300) - - plt.close() - return variable_list_values - - -def main(argv): - parser = argparse.ArgumentParser(prog=argv[0], - description="""This script provides a simple interface for retrieving observations values - of DSIT indexes.""") - parser.add_argument("-i", "--index", required=True, help="DSIT index", metavar='') - parser.add_argument("-s", "--ws_id", required=True, help="Weather station ID", metavar='') - parser.add_argument('-l', "--latlonlist", nargs='+', help=' Set min and max latitude and longitude values', required=True) - parser.add_argument('-d', "--day_of_retrieve_data", help=' Set day to retrieve data', required=True ) - - args = parser.parse_args(argv[1:]) - - index_name = args.index - station_id = args.ws_id - date_to_retrieve_data = args.day_of_retrieve_data - extent = [float(x) for x in args.latlonlist] - - # Desired extent - # extent = [-74.0, -34.1, -34.8, 5.5] -74.0, -34.1 -34.8 5.5 # Min lon, Max lon, Min lat, Max lat - # extent = [-64.0, -35.0, -35.0, -15.0] -64.0 -35.0 -35.0 -15.0 # Min lon, Min lat, Max lon, Max lat - # extent = [-45, -25, -40, -20] -45 -25 -40 -20 - # extent = [-44, -24, -42, -20] - - # Initial time and date - yyyy = datetime.strptime(date_to_retrieve_data, '%Y%m%d').strftime('%Y') - mm = datetime.strptime(date_to_retrieve_data, '%Y%m%d').strftime('%m') - dd = datetime.strptime(date_to_retrieve_data, '%Y%m%d').strftime('%d') - - date_ini = str(datetime(int(yyyy), int(mm), int(dd), 12, 0) - timedelta(hours=12)) - date_end = str(datetime(int(yyyy), int(mm), int(dd), 12, 0) + timedelta(hours=12)) - - acum = np.zeros((1086,1086)) - - columns = ['datetime', 'x-1,y-1', 'x-1,y', 'x-1,y+1', 'x,y-1', 'x,y', 'x,y+1', 'x+1,y-1', 'x+1,y', 'x+1,y+1'] - df = pd.DataFrame(columns=columns) - #----------------------------------------------------------------------------------------------------------- - # Loop to produce sequence of images (animation) - while (date_ini <= date_end): - - # Date structure - yyyymmddhhmn = datetime.strptime(date_ini, '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') - - # Download file for current timestamp - filename_downloaded = download_PROD(yyyymmddhhmn, product_name, temp_dir) - #----------------------------------------------------------------------------------------------------------- - - - # Open the file - img = gdal.Open(f'NETCDF:{temp_dir}/{filename_downloaded}.nc:' + index_name) - dqf = gdal.Open(f'NETCDF:{temp_dir}/{filename_downloaded}.nc:DQF_Overall') - - # Read the header metadata - metadata = img.GetMetadata() - scale = float(metadata.get(index_name + '#scale_factor')) - offset = float(metadata.get(index_name + '#add_offset')) - undef = float(metadata.get(index_name + '#_FillValue')) - dtime = metadata.get('NC_GLOBAL#time_coverage_start') - - # Load the data - ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) - ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float) - - # Remove undef - ds[ds == undef] = np.nan - - # Apply the scale and offset - ds = (ds * scale + offset) - - # Apply NaN's where the quality flag is greater than 0 - ds[ds_dqf > 0] = np.nan - - # Reproject the file - filename_reprojected = f'{output}/{index_name}_{yyyymmddhhmn}.nc' - reproject(filename_reprojected, img, ds, extent, undef) - - variable_values = plot_data_for_this_timestamp(filename_reprojected, extent, index_name, yyyymmddhhmn, station_id, dtime) - variable_values = np.append(date_ini, variable_values) - - df.loc[len(df)] = variable_values - - date_ini = str(datetime.strptime(date_ini, '%Y-%m-%d %H:%M:%S') + timedelta(minutes=10)) - - df.to_csv('./data/goes16/data_' + index_name + '_' + - date_to_retrieve_data + '.csv', index=False) - - -if __name__ == "__main__": - temp_dir = "./data/goes16/temp" - output = "./data/goes16/Animation" - # yyyymmdd = '20201217' - product_name = 'ABI-L2-DSIF' - - main(sys.argv) diff --git a/src/preprocess/preprocess_cemaden.py b/src/preprocess/preprocess_cemaden.py new file mode 100644 index 00000000..f5c67199 --- /dev/null +++ b/src/preprocess/preprocess_cemaden.py @@ -0,0 +1,161 @@ +import argparse +import logging +from pathlib import Path + +import numpy as np +import pandas as pd +from metpy.calc import wind_components +from metpy.units import units +from sklearn.impute import KNNImputer + +from config import globals + + +def add_hour_related_features(df): + dt = df.index + hourfloat = dt.hour + dt.minute / 60.0 + df["hour_sin"] = np.sin(2.0 * np.pi * hourfloat / 24.0) + df["hour_cos"] = np.cos(2.0 * np.pi * hourfloat / 24.0) + return df + + +def transform_wind(wind_speed, wind_direction, comp_idx): + assert comp_idx in [0, 1] + return wind_components(wind_speed * units("m/s"), wind_direction * units.deg)[ + comp_idx + ].magnitude + + +def add_wind_related_features(df): + df["wind_direction_u"] = df.apply( + lambda x: transform_wind(x.wind_speed, x.wind_dir, 0), axis=1 + ) + df["wind_direction_v"] = df.apply( + lambda x: transform_wind(x.wind_speed, x.wind_dir, 1), axis=1 + ) + return df + + +def min_max_normalize(df): + return (df - df.min()) / (df.max() - df.min()) + + +def preprocess(filename, output_folder): + logging.info(f"Loading datasource file {filename}.") + df = pd.read_parquet(filename) + logging.info(df.head()) + + # 1. Converter para datetime (sem UTC ainda) + df["datahora"] = pd.to_datetime(df["datahora"]) + + # 2. Arredondar para hora cheia + df["hora_cheia"] = df["datahora"].dt.floor("H") + + # 3. Agregar por hora cheia: pegar máximo de 'chuva' e 'intensidade_precipitacao' + colunas_para_agregar = [] + if "intensidade_precipitacao" in df.columns: + colunas_para_agregar.append("intensidade_precipitacao") + if "chuva" in df.columns: + colunas_para_agregar.append("chuva") + + if colunas_para_agregar: + max_por_hora = ( + df.groupby("hora_cheia")[colunas_para_agregar].max().reset_index() + ) + if "intensidade_precipitacao" in max_por_hora.columns: + max_por_hora = max_por_hora.rename( + columns={"intensidade_precipitacao": "intensidade_max"} + ) + if "chuva" in max_por_hora.columns: + max_por_hora = max_por_hora.rename(columns={"chuva": "chuva_max"}) + + df = df.merge(max_por_hora, on="hora_cheia", how="left") + + if "intensidade_max" in df.columns: + df["intensidade_precipitacao"] = df["intensidade_max"] + df = df.drop(columns=["intensidade_max"]) + if "chuva_max" in df.columns: + df["chuva"] = df["chuva_max"] + df = df.drop(columns=["chuva_max"]) + + # 4. Substituir datahora pela hora cheia com UTC + df["datahora"] = df["hora_cheia"].dt.tz_localize("UTC") + df = df.drop(columns=["hora_cheia"]) + + df = df.set_index(pd.DatetimeIndex(df["datahora"])) + logging.info("Datetime index added.") + + # Define mapeamento de colunas baseado em sensores típicos do CEMADEN tipo 1 + column_name_mapping = { + "datahora": "datetime", + "chuva": "precipitation", + "intensidade da Precipitação": "precipitation_intensity", + "temperatura do Ar": "temperature", + "umidade Relativa do Ar": "relative_humidity", + "velocidade do Vento": "wind_speed", + "direção do Vento": "wind_dir", + } + + df = df.rename(columns=column_name_mapping) + logging.info("Column names standardized.") + + # Definir variáveis preditoras e alvo + predictors = [ + "temperature", + "relative_humidity", + "wind_speed", + "wind_dir", + "hour_sin", + "hour_cos", + ] + target = "precipitation" + + # Filtrar apenas colunas relevantes disponíveis + available_predictors = [c for c in predictors if c in df.columns] + if target not in df.columns: + logging.warning("Target variable 'precipitation' not found. Skipping file.") + return + + df = df[available_predictors + [target]].copy() + df = df[df[target].notna()] + logging.info(f"Remaining observations after dropping NaN in target: {len(df)}") + + if "wind_speed" in df.columns and "wind_dir" in df.columns: + df = add_wind_related_features(df) + + df = add_hour_related_features(df) + df = df.drop(columns=["wind_speed", "wind_dir"], errors="ignore") + + predictors_final = [col for col in df.columns if col != target] + target_column = df[target] + df = df[predictors_final] + df = min_max_normalize(df) + + logging.info("Applying KNN imputation...") + imputer = KNNImputer(n_neighbors=2) + df[:] = imputer.fit_transform(df) + + df[target] = target_column + filename_new = Path(filename).stem + "_preprocessed.parquet.gzip" + output_path = Path(output_folder) / filename_new + print(df) + df.to_parquet(output_path, compression="gzip") + logging.info(f"Saved preprocessed file to {output_path}") + + +def main(): + parser = argparse.ArgumentParser( + description="Preprocess CEMADEN weather station data." + ) + parser.add_argument( + "-f", "--file", required=True, help="Path to the raw .parquet file" + ) + args = parser.parse_args() + file = globals.CEMADEN_DATA_DIR + "raw/" + args.file + ".parquet" + output = globals.CEMADEN_DATA_DIR + "preprocessed/" + logging.basicConfig(level=logging.INFO, format="[%(levelname)s] %(message)s") + preprocess(file, output) + + +if __name__ == "__main__": + main() diff --git a/src/preprocess_glm.py b/src/preprocess/preprocess_glm.py similarity index 63% rename from src/preprocess_glm.py rename to src/preprocess/preprocess_glm.py index c010424d..8ce55a93 100644 --- a/src/preprocess_glm.py +++ b/src/preprocess/preprocess_glm.py @@ -1,45 +1,27 @@ -from netCDF4 import Dataset +import argparse +import glob import os +import sys + import numpy as np -import glob import pandas as pd import pyarrow.parquet as pq import xarray as xr -import argparse -import sys - -from globals import * -from util import * - station_ids_for_goes16 = { - "A652": { - "latitude": -22.98833333, - "longitude": -43.19055555 - }, - "A636": { - "latitude": -22.93999999, - "longitude": -43.40277777 - }, - "A621": { - "latitude": -22.86138888, - "longitude": -43.41138888 - }, - "A602": { - "latitude": -23.05027777, - "longitude": -43.59555555 - }, - "A627": { - "latitude": -22.86749999, - "longitude": -43.10194444 - } - } + "A652": {"latitude": -22.98833333, "longitude": -43.19055555}, + "A636": {"latitude": -22.93999999, "longitude": -43.40277777}, + "A621": {"latitude": -22.86138888, "longitude": -43.41138888}, + "A602": {"latitude": -23.05027777, "longitude": -43.59555555}, + "A627": {"latitude": -22.86749999, "longitude": -43.10194444}, +} + def haversine(lat1, lon1, lat2, lon2): """ Calculate the great circle distance between two points on the earth. - This function computes the distance using the Haversine formula, which is an equation giving the shortest distance between any two points on the surface of a sphere. + This function computes the distance using the Haversine formula, which is an equation giving the shortest distance between any two points on the surface of a sphere. Parameters: lat1 (float): Latitude of the first point in decimal degrees. @@ -56,8 +38,10 @@ def haversine(lat1, lon1, lat2, lon2): R = 6371 # Earth radius in kilometers dLat = np.radians(lat2 - lat1) dLon = np.radians(lon2 - lon1) - a = np.sin(dLat/2) * np.sin(dLat/2) + np.cos(np.radians(lat1)) * np.cos(np.radians(lat2)) * np.sin(dLon/2) * np.sin(dLon/2) - c = 2 * np.arctan2(np.sqrt(a), np.sqrt(1-a)) + a = np.sin(dLat / 2) * np.sin(dLat / 2) + np.cos(np.radians(lat1)) * np.cos( + np.radians(lat2) + ) * np.sin(dLon / 2) * np.sin(dLon / 2) + c = 2 * np.arctan2(np.sqrt(a), np.sqrt(1 - a)) distance = R * c return distance @@ -83,18 +67,30 @@ def read_and_process_files(files, station_id, g16_pre_process_data_file): nc_indx = i g16_data = files[nc_indx] g16_data_file.append(g16_data) - ds = xr.open_dataset(g16_data_file[i], cache=False, ) + ds = xr.open_dataset( + g16_data_file[i], + cache=False, + ) df = ds.to_dataframe() - df = df[df.apply(lambda row: haversine(station_lat, station_lon, row['event_lat'], row['event_lon']) <= radius_km, axis=1)] - df['event_time_offset'] = df['event_time_offset'].astype('datetime64[us]') - g16_pre_process_data_file['Datetime'].extend(df['event_time_offset']) - g16_pre_process_data_file['event_energy'].extend(df['event_energy']) + df = df[ + df.apply( + lambda row: haversine( + station_lat, station_lon, row["event_lat"], row["event_lon"] + ) + <= radius_km, + axis=1, + ) + ] + df["event_time_offset"] = df["event_time_offset"].astype("datetime64[us]") + g16_pre_process_data_file["Datetime"].extend(df["event_time_offset"]) + g16_pre_process_data_file["event_energy"].extend(df["event_energy"]) ds.close() - except: - pass + except Exception as e: + print(f"Error processing file {g16_data}: {e}") return g16_pre_process_data_file + def pre_process_tpw_product(path, station_id): """ Preprocess Total Precipitable Water (TPW) data from NetCDF files and save it to a Parquet file. @@ -114,25 +110,25 @@ def pre_process_tpw_product(path, station_id): """ # navigate to directory with .nc data files os.chdir(str(path)) - nc_files = glob.glob('*GLM-L2-LCFA*') + nc_files = glob.glob("*GLM-L2-LCFA*") nc_files = sorted(nc_files) - parquet_dir = 'data/parquet_files' + parquet_dir = "data/parquet_files" if not os.path.exists(parquet_dir): os.makedirs(parquet_dir) - parquet_path = f'data/parquet_files/glm_{station_id}_preprocessed_file.parquet' + parquet_path = f"data/parquet_files/glm_{station_id}_preprocessed_file.parquet" batch_size = 1000 total_files = len(nc_files) - g16_pre_process_data_file = {'Datetime': [], 'event_energy': []} + g16_pre_process_data_file = {"Datetime": [], "event_energy": []} print(f"You have {total_files} to be processed") for i in range(0, total_files, batch_size): - batch_files = nc_files[i:i+batch_size] + batch_files = nc_files[i : i + batch_size] read_and_process_files(batch_files, station_id, g16_pre_process_data_file) print(f"{len(g16_pre_process_data_file)} Files was pre processed") @@ -140,11 +136,11 @@ def pre_process_tpw_product(path, station_id): df = pd.DataFrame(g16_pre_process_data_file) # Set the 'Datetime' column as the DatetimeIndex - df['Datetime'] = pd.to_datetime(df['Datetime']) - df = df.set_index(pd.DatetimeIndex(df['Datetime'])) + df["Datetime"] = pd.to_datetime(df["Datetime"]) + df = df.set_index(pd.DatetimeIndex(df["Datetime"])) # Remove time-related columns since now this information is in the index. - df = df.drop(['Datetime'], axis=1) + df = df.drop(["Datetime"], axis=1) # Append to the existing Parquet file or create a new one if os.path.exists(parquet_path): @@ -155,22 +151,31 @@ def pre_process_tpw_product(path, station_id): df_combined = df # Save the combined DataFrame to a Parquet file - df_combined.to_parquet(parquet_path, compression='gzip') + df_combined.to_parquet(parquet_path, compression="gzip") return + def main(argv): - parser = argparse.ArgumentParser(description='Preprocess ABI products station data.') - parser.add_argument('-s', '--station_id', required=True, help='ID of the weather station to preprocess data for.') + parser = argparse.ArgumentParser( + description="Preprocess ABI products station data." + ) + parser.add_argument( + "-s", + "--station_id", + required=True, + help="ID of the weather station to preprocess data for.", + ) args = parser.parse_args(argv[1:]) - directory = 'data/goes16/glm_files' + directory = "data/goes16/glm_files" station_id = args.station_id - print('\n***Preprocessing GLM Files***') + print("\n***Preprocessing GLM Files***") pre_process_tpw_product(directory, station_id) - print('Done!') + print("Done!") + -if __name__ == '__main__': - main(sys.argv) \ No newline at end of file +if __name__ == "__main__": + main(sys.argv) diff --git a/src/preprocess_gs.py b/src/preprocess/preprocess_gs.py similarity index 66% rename from src/preprocess_gs.py rename to src/preprocess/preprocess_gs.py index cb005d5c..77cc37c7 100644 --- a/src/preprocess_gs.py +++ b/src/preprocess/preprocess_gs.py @@ -1,28 +1,41 @@ -import pandas as pd -from pathlib import Path import argparse import sys -import globals -import util -from sklearn.impute import KNNImputer + +import pandas as pd + +import src.utils.util as util +from config import globals + def get_relevant_variables(): - return ['temperature', 'relative_humidity', 'barometric_pressure', 'wind_direction_u', 'wind_direction_v', 'hour_sin', 'hour_cos'], 'precipitation' + return [ + "temperature", + "relative_humidity", + "barometric_pressure", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos", + ], "precipitation" -def preprocess_gauge_station(station_id, df, output_folder): +def preprocess_gauge_station(station_id, df, output_folder): predictor_names, target_name = get_relevant_variables() print(f"Chosen predictors: {predictor_names}") print(f"Chosen target: {target_name}") # # Drop observations in which the target variable is not defined. - print(f"Dropping entries with null target.") + print("Dropping entries with null target.") n_obser_before_drop = len(df) df = df[df[target_name].notna()] n_obser_after_drop = len(df) - print(f"Number of observations before/after dropping entries with undefined target value: {n_obser_before_drop}/{n_obser_after_drop}.") - print(f"Range of timestamps after dropping entries with undefined target value: [{min(df.index)}, {max(df.index)}]") + print( + f"Number of observations before/after dropping entries with undefined target value: {n_obser_before_drop}/{n_obser_after_drop}." + ) + print( + f"Range of timestamps after dropping entries with undefined target value: [{min(df.index)}, {max(df.index)}]" + ) # # Create hour-related features (sin and cos components) @@ -32,20 +45,20 @@ def preprocess_gauge_station(station_id, df, output_folder): # print(df.head()) - assert (not df.isnull().values.any().any()) + assert not df.isnull().values.any().any() # # Normalize the weather station data. This step is necessary here due to the next step, which deals with missing values. # Notice that we drop the target column before normalizing, to avoid some kind of data leakage. # (see https://stats.stackexchange.com/questions/214728/should-data-be-normalized-before-or-after-imputation-of-missing-data) - print("Min-max normalizing data...", end='') + print("Min-max normalizing data...", end="") target_column = df[target_name] barometric_pressure_column = df["barometric_pressure"] df = df.drop(columns=[target_name, "barometric_pressure"], axis=1) df = util.min_max_normalize(df) print("Done!") - assert (not df.isnull().values.any().any()) + assert not df.isnull().values.any().any() # # Add the target column back to the DataFrame. @@ -54,9 +67,10 @@ def preprocess_gauge_station(station_id, df, output_folder): # # Save preprocessed data to a parquet file. - filename = output_folder + station_id + '_preprocessed.parquet.gzip' + filename = output_folder + station_id + "_preprocessed.parquet.gzip" print(f"Saving preprocessed data to {filename}") - df.to_parquet(filename, compression='gzip') + df.to_parquet(filename, compression="gzip") + def preprocess_all_gauge_stations(output_folder): alertario_stations_filename = "./data/ws/alertario_stations.parquet" @@ -66,14 +80,23 @@ def preprocess_all_gauge_stations(output_folder): if station_id in globals.ALERTARIO_WEATHER_STATION_IDS: continue print(f"Fusing data for gauge station {station_id}") - df_station = pd.read_parquet("./data/ws/alertario/rain_gauge_era5_fused/" + station_id + ".parquet") + df_station = pd.read_parquet( + "./data/ws/alertario/rain_gauge_era5_fused/" + station_id + ".parquet" + ) preprocess_gauge_station(station_id, df_station, output_folder=output_folder) + def main(argv): - parser = argparse.ArgumentParser(description='Preprocess gauge station data.') - parser.add_argument('-s', '--station_id', required=True, choices=globals.ALERTARIO_GAUGE_STATION_IDS + ("all",), help='ID of the weather station to preprocess data for.') + parser = argparse.ArgumentParser(description="Preprocess gauge station data.") + parser.add_argument( + "-s", + "--station_id", + required=True, + choices=globals.ALERTARIO_GAUGE_STATION_IDS + ("all",), + help="ID of the weather station to preprocess data for.", + ) args = parser.parse_args(argv[1:]) - + station_id = args.station_id if not (station_id == "all" or station_id in globals.ALERTARIO_GAUGE_STATION_IDS): @@ -87,13 +110,14 @@ def main(argv): if station_id == "all": preprocess_all_gauge_stations(output_folder) else: - print(f'Preprocessing data coming from weather station {station_id}') + print(f"Preprocessing data coming from weather station {station_id}") station_filename = input_folder + args.station_id + ".parquet" df = pd.read_parquet(station_filename) print(f"Fusing data for gauge station {station_id}") preprocess_gauge_station(station_id, df, output_folder=output_folder) - print('Done!') + print("Done!") + -if __name__ == '__main__': +if __name__ == "__main__": main(sys.argv) diff --git a/src/preprocess/preprocess_websirene_inmet_alertario.py b/src/preprocess/preprocess_websirene_inmet_alertario.py new file mode 100644 index 00000000..49230a90 --- /dev/null +++ b/src/preprocess/preprocess_websirene_inmet_alertario.py @@ -0,0 +1,742 @@ +import argparse +import json +import logging +import math +import sys +from functools import lru_cache +from pathlib import Path + +import numpy as np +import pandas as pd +from sklearn.impute import KNNImputer +from sklearn.preprocessing import MinMaxScaler, StandardScaler + +from config import globals +from utils import utils + +PROJECT_ROOT = Path(__file__).resolve().parents[2] +SRC_DIR = PROJECT_ROOT / "src" +if str(SRC_DIR) not in sys.path: + sys.path.insert(0, str(SRC_DIR)) + +def _safe_get(dct: dict, key: str, default=None): + try: + return dct.get(key, default) + except AttributeError: + return default + + +def _is_truthy(value) -> bool: + if isinstance(value, str): + return value.lower() in {"1", "true", "yes", "on"} + return bool(value) + + +def _nan_to_none(value): + if value is None: + return None + if isinstance(value, float) and math.isnan(value): + return None + return value + + +def _ensure_list(value, default=None): + if value is None: + return default or [] + if isinstance(value, (list, tuple)): + return list(value) + return [value] + + +STATION_SYSTEM_CONFIG_DIR = PROJECT_ROOT / "config" / "station_systems" + +STATION_SYSTEM_CONFIG = { + "inmet": { + "ids": set(globals.INMET_WEATHER_STATION_IDS), + "data_dir": globals.WS_INMET_DATA_DIR, + "config_path": STATION_SYSTEM_CONFIG_DIR / "inmet.json", + "raw_format": "parquet", + }, + "alertario": { + "ids": set(globals.ALERTARIO_WEATHER_STATION_IDS), + "data_dir": globals.WS_ALERTARIO_DATA_DIR, + "config_path": STATION_SYSTEM_CONFIG_DIR / "alertario.json", + "raw_format": "parquet", + }, + "websirene": { + "ids": set(globals.WEBSIRENE_STATION_IDS), + "data_dir": globals.WEBSIRENE_DATA_DIR, + "config_path": STATION_SYSTEM_CONFIG_DIR / "websirene.json", + "raw_format": "csv", + }, +} + + +@lru_cache(maxsize=None) +def load_station_system_settings(system_name: str) -> dict: + system_name = system_name.lower() + if system_name not in STATION_SYSTEM_CONFIG: + raise KeyError(f"Unknown station system '{system_name}'.") + config_path = STATION_SYSTEM_CONFIG[system_name]["config_path"] + if not config_path.exists(): + raise FileNotFoundError( + f"Configuration file not found for system '{system_name}' at '{config_path}'." + ) + with config_path.open("r", encoding="utf-8") as config_file: + return json.load(config_file) + + +def apply_scaling(df: pd.DataFrame, scaler_config: dict) -> pd.DataFrame: + if df.empty: + return df + scaler_config = scaler_config or {} + scaler_type = scaler_config.get("type", "minmax") + if not isinstance(scaler_type, str): + logging.warning(f"Invalid scaler type '{scaler_type}'. Skipping normalization.") + return df + scaler_type = scaler_type.lower() + params = scaler_config.get("params", {}) or {} + + if scaler_type == "minmax": + feature_range = params.get("feature_range", [0.0, 1.0]) + if feature_range == [0.0, 1.0] or tuple(feature_range) == (0.0, 1.0): + return utils.min_max_normalize(df) + scaler = MinMaxScaler(feature_range=tuple(feature_range)) + scaled = scaler.fit_transform(df) + elif scaler_type == "standard": + scaler = StandardScaler(**params) + scaled = scaler.fit_transform(df) + elif scaler_type in {"none", "identity"}: + return df + else: + logging.warning(f"Unknown scaler type '{scaler_type}'. Skipping normalization.") + return df + + scaled_df = pd.DataFrame(scaled, columns=df.columns, index=df.index) + return scaled_df + + +def apply_imputation(df: pd.DataFrame, imputation_config: dict) -> pd.DataFrame: + if df.empty: + return df + imputation_config = imputation_config or {} + strategy = imputation_config.get("strategy", "knn") + if not isinstance(strategy, str): + logging.warning( + f"Invalid imputation strategy '{strategy}'. Skipping imputation." + ) + return df + strategy = strategy.lower() + params = imputation_config.get("params", {}) or {} + + if strategy == "knn": + n_neighbors = params.get("n_neighbors", 2) + weights = params.get("weights", "uniform") + imputer = KNNImputer(n_neighbors=n_neighbors, weights=weights) + imputed = imputer.fit_transform(df) + return pd.DataFrame(imputed, columns=df.columns, index=df.index) + if strategy in {"ffill_then_zero", "forward_then_zero"}: + return df.ffill().fillna(0.0) + if strategy in {"ffill", "forward"}: + return df.ffill() + if strategy in {"bfill", "backward"}: + return df.bfill() + if strategy in {"zero", "zeros"}: + return df.fillna(0.0) + if strategy in {"none", "skip"}: + return df + + logging.warning(f"Unknown imputation strategy '{strategy}'. Skipping imputation.") + return df + + +def apply_quality_checks( + df: pd.DataFrame, + quality_config: dict, + predictor_columns, + flag_suffix: str = "_flag", + include_flag_columns: bool = True, +): + if df.empty: + return df, {"checks": [], "flag_columns": [], "new_columns": []} + + checks = _ensure_list(_safe_get(quality_config, "checks"), default=[]) + records = [] + created_flag_columns = [] + new_predictor_columns = [] + row_count = len(df.index) + + for idx, raw_check in enumerate(checks): + check = raw_check or {} + check_type = str(check.get("type", "")).lower() + if not check_type: + continue + columns = _ensure_list(check.get("columns"), default=predictor_columns) + actions = _ensure_list( + check.get("actions") or check.get("strategy"), default=["flag"] + ) + actions = [action.lower() for action in actions] + if not actions: + continue + + # compute parameters common across columns depending on check type + for column in columns: + if column not in df.columns: + logging.debug( + f"Quality check '{check_type}' skipped for missing column '{column}'." + ) + continue + series = df[column] + if not pd.api.types.is_numeric_dtype(series): + logging.debug( + f"Quality check '{check_type}' skipped for non-numeric column '{column}'." + ) + continue + + mask = pd.Series(False, index=df.index) + params_summary = {} + + if check_type == "bounds": + min_value = check.get("min") + max_value = check.get("max") + if min_value is not None: + mask |= series < min_value + if max_value is not None: + mask |= series > max_value + params_summary = {"min": min_value, "max": max_value} + elif check_type == "iqr": + k = float(check.get("k", 1.5)) + q1 = series.quantile(0.25) + q3 = series.quantile(0.75) + iqr = q3 - q1 + if pd.isna(iqr) or iqr == 0: + continue + lower = q1 - k * iqr + upper = q3 + k * iqr + mask = (series < lower) | (series > upper) + params_summary = {"k": k, "lower": lower, "upper": upper} + elif check_type == "zscore": + threshold = float(check.get("threshold", 3.0)) + mean = series.mean() + std = series.std() + if pd.isna(std) or std == 0: + continue + zscores = (series - mean) / std + mask = zscores.abs() > threshold + params_summary = {"threshold": threshold} + else: + logging.warning( + f"Unknown quality check type '{check_type}' for column '{column}'. Skipping." + ) + continue + + if not mask.any(): + records.append( + { + "check": check.get("name") or f"{check_type}_{idx}", + "type": check_type, + "column": column, + "flags": 0, + "fraction": 0.0, + "actions": actions, + "params": params_summary, + } + ) + continue + + if "clip" in actions and check_type in {"bounds", "iqr"}: + if "min" in params_summary and params_summary["min"] is not None: + df.loc[series < params_summary["min"], column] = params_summary[ + "min" + ] + if "max" in params_summary and params_summary["max"] is not None: + df.loc[series > params_summary["max"], column] = params_summary[ + "max" + ] + if "lower" in params_summary and params_summary["lower"] is not None: + df.loc[series < params_summary["lower"], column] = params_summary[ + "lower" + ] + if "upper" in params_summary and params_summary["upper"] is not None: + df.loc[series > params_summary["upper"], column] = params_summary[ + "upper" + ] + + if "set_nan" in actions: + df.loc[mask, column] = np.nan + + flag_column = None + if "flag" in actions: + flag_column = check.get("flag_column") or f"{column}{flag_suffix}" + if flag_column not in df.columns: + df[flag_column] = False + df[flag_column] = df[flag_column].fillna(False).astype(bool) + df.loc[mask, flag_column] = True + df[flag_column] = df[flag_column].astype(bool) + created_flag_columns.append(flag_column) + if include_flag_columns: + if flag_column not in new_predictor_columns: + new_predictor_columns.append(flag_column) + + records.append( + { + "check": check.get("name") or f"{check_type}_{idx}", + "type": check_type, + "column": column, + "flags": int(mask.sum()), + "fraction": float(mask.sum()) / row_count if row_count else 0.0, + "actions": actions, + "flag_column": flag_column, + "params": params_summary, + } + ) + + quality_output = { + "checks": records, + "flag_columns": list(dict.fromkeys(created_flag_columns)), + "new_columns": list(dict.fromkeys(new_predictor_columns)), + } + return df, quality_output + + +def build_quality_report( + station_id: str, + station_system: str, + report_df: pd.DataFrame, + report_config: dict, + station_metadata: dict, + scaler_config: dict, + imputation_config: dict, + missing_counts_before: pd.Series, + imputation_applied: bool, + source_file: str, + output_file: str, + target_column: str, + quality_checks=None, +) -> dict: + report_fields = _ensure_list( + _safe_get(report_config, "fields"), default=["missing_fraction", "min", "max"] + ) + summary_keys = _ensure_list( + _safe_get(report_config, "summary"), + default=["rows", "columns", "missing_fraction"], + ) + + num_rows = int(report_df.shape[0]) + num_columns = int(report_df.shape[1]) + total_cells = num_rows * num_columns if num_rows and num_columns else 0 + missing_fraction = ( + (missing_counts_before.sum() / total_cells) if total_cells else 0.0 + ) + + per_column_metrics = {} + for column in report_df.columns: + column_metrics = {} + for field in report_fields: + if field == "missing_fraction": + column_metrics[field] = ( + float(missing_counts_before[column]) / num_rows if num_rows else 0.0 + ) + elif field == "missing_count": + column_metrics[field] = int(missing_counts_before[column]) + elif field == "imputed_fraction": + column_metrics[field] = ( + float(missing_counts_before[column]) / num_rows + if (num_rows and imputation_applied) + else 0.0 + ) + elif field == "imputed_count": + column_metrics[field] = ( + int(missing_counts_before[column]) if imputation_applied else 0 + ) + elif field == "min": + column_metrics[field] = _nan_to_none(report_df[column].min(skipna=True)) + elif field == "max": + column_metrics[field] = _nan_to_none(report_df[column].max(skipna=True)) + elif field == "mean": + column_metrics[field] = _nan_to_none( + report_df[column].mean(skipna=True) + ) + elif field == "median": + column_metrics[field] = _nan_to_none( + report_df[column].median(skipna=True) + ) + elif field == "std": + column_metrics[field] = _nan_to_none(report_df[column].std(skipna=True)) + per_column_metrics[column] = column_metrics + + summary = {} + for key in summary_keys: + if key == "rows": + summary[key] = num_rows + elif key == "columns": + summary[key] = num_columns + elif key == "missing_fraction": + summary[key] = missing_fraction + elif key == "imputed_fraction": + summary[key] = missing_fraction if imputation_applied else 0.0 + elif key == "min": + summary[key] = _nan_to_none(report_df.min(skipna=True).min()) + elif key == "max": + summary[key] = _nan_to_none(report_df.max(skipna=True).max()) + elif key == "mean": + summary[key] = _nan_to_none(report_df.mean(skipna=True).mean()) + + report_payload = { + "station_id": station_id, + "station_system": station_system, + "target_column": target_column, + "columns": list(report_df.columns), + "rows": num_rows, + "metadata": station_metadata or {}, + "scaler": scaler_config or {}, + "imputation": imputation_config or {}, + "imputation_applied": imputation_applied, + "source_file": source_file, + "output_file": output_file, + "column_metrics": per_column_metrics, + "summary": summary, + "quality_checks": quality_checks or [], + } + return report_payload + + +def preprocess_ws(ws_id, ws_filename, output_folder, station_system, raw_format="parquet"): + system_settings = load_station_system_settings(station_system) + feature_toggles = system_settings.get("features", {}) + add_wind_features = feature_toggles.get("add_wind_related_features", True) + add_hour_features = feature_toggles.get("add_hour_related_features", True) + normalize_predictors = feature_toggles.get("normalize_predictors", True) + impute_missing_values = feature_toggles.get("impute_missing_values", True) + preprocessing_settings = system_settings.get("preprocessing", {}) + scaler_config = preprocessing_settings.get("scaler", {}) + imputation_config = preprocessing_settings.get("imputation", {}) + quality_config = system_settings.get("quality", {}) + quality_enabled = _is_truthy(_safe_get(quality_config, "enabled", False)) + include_flag_columns = _is_truthy( + _safe_get(quality_config, "include_flag_columns", True) + ) + flag_suffix = quality_config.get("flag_column_suffix", "_flag") + report_config = system_settings.get("report", {}) + report_enabled = _is_truthy(_safe_get(report_config, "enabled", False)) + station_metadata = _safe_get(_safe_get(system_settings, "stations", {}), ws_id, {}) + + logging.info(f"Loading datasource file {ws_filename}).") + # + # Read CSV or Parquet + if raw_format == "csv": + try: + df = pd.read_csv(ws_filename, parse_dates=["datetime"]) + except (FileNotFoundError, pd.errors.EmptyDataError) as e: + logging.error(f"Failed to read CSV {ws_filename}: {e}") + return + elif raw_format == "parquet": + df = pd.read_parquet(ws_filename) + else: + logging.error(f"Unknown raw file format '{raw_format}'. Aborting.") + return + + logging.info(df.head()) + logging.info("Done!\n") + + # + # Add index to dataframe using the timestamps. + logging.info("Adding index to dataframe using the timestamps...") + df = utils.add_datetime_index(ws_id, df) + logging.info(df.head()) + logging.info("Done!\n") + + # + # Standardize column names. + logging.info("Standardizing column names...") + column_name_mapping = system_settings.get("column_mapping", {}) + if not column_name_mapping: + raise ValueError( + f"No column mapping provided for station system '{station_system}'." + ) + missing_columns = [col for col in column_name_mapping if col not in df.columns] + if missing_columns: + logging.warning( + f"The following columns from the mapping are missing in the datasource: {missing_columns}" + ) + column_names = column_name_mapping.keys() + df = utils.get_dataframe_with_selected_columns(df, column_names) + df = utils.rename_dataframe_column_names(df, column_name_mapping) + logging.info(df.head()) + logging.info("Done!\n") + + logging.info("Getting relevant variables...") + predictor_names = system_settings.get("predictor_columns") + target_name = system_settings.get("target_column") + if not (predictor_names and target_name): + variables = utils.get_relevant_variables(ws_id) + if not variables: + raise ValueError( + f"Could not determine predictors/target for station '{ws_id}'." + ) + predictor_names, target_name = variables + logging.info(f"Predictors: {predictor_names}") + logging.info(f"Target: {target_name}") + logging.info("Done!\n") + + # + # Drop observations in which the target variable is not defined. + logging.info("Dropping entries with null target...") + n_obser_before_drop = len(df) + df = df[df[target_name].notna()] + n_obser_after_drop = len(df) + + if df.empty: + logging.warning(f"No observations remaining for {ws_id} after dropping null target '{target_name}'. Aborting.") + return + + logging.info( + f"Number of observations before/after dropping entries with undefined target value: {n_obser_before_drop}/{n_obser_after_drop}." + ) + logging.info( + f"Range of timestamps after dropping entries with undefined target value: [{min(df.index)}, {max(df.index)}]" + ) + logging.info(df.head()) + logging.info("Done!\n") + + quality_summary = [] + quality_added_predictors = [] + if quality_enabled: + logging.info("Applying quality checks before feature engineering...") + pre_quality_columns = [ + column for column in predictor_names if column in df.columns + ] + df, quality_output = apply_quality_checks( + df=df, + quality_config=quality_config, + predictor_columns=pre_quality_columns, + flag_suffix=flag_suffix, + include_flag_columns=include_flag_columns, + ) + quality_summary = quality_output.get("checks", []) + if include_flag_columns: + quality_added_predictors = [ + column + for column in quality_output.get("new_columns", []) + if column in df.columns + ] + logging.info("Quality checks completed.\n") + + # + # Create wind-related features (U and V components of wind observations). + if add_wind_features: + logging.info("Creating wind-related features...") + df = utils.add_wind_related_features(ws_id, df) + logging.info(df.head()) + logging.info("Done!\n") + else: + logging.info("Skipping wind-related feature generation as configured.\n") + + # + # Create time-related features (sin and cos components) + if add_hour_features: + logging.info("Creating time-related features...") + df = utils.add_hour_related_features(df) + logging.info(df.head()) + logging.info("Done!\n") + else: + logging.info("Skipping time-related feature generation as configured.\n") + + available_predictors = [ + column for column in predictor_names if column in df.columns + ] + if include_flag_columns and quality_added_predictors: + for column in quality_added_predictors: + if column not in available_predictors: + available_predictors.append(column) + missing_predictors = sorted(set(predictor_names) - set(available_predictors)) + if missing_predictors: + logging.warning( + f"The following predictors are missing and will be ignored: {missing_predictors}" + ) + if not available_predictors: + raise ValueError( + f"No predictor columns were found after preprocessing for station '{ws_id}'." + ) + if target_name not in df.columns: + raise KeyError( + f"Target column '{target_name}' not found after preprocessing for station '{ws_id}'." + ) + df = df[available_predictors + [target_name]] + report_reference_df = df[available_predictors].copy() if report_enabled else None + missing_counts_before = ( + report_reference_df.isna().sum() if report_reference_df is not None else None + ) + + # + # Scale the data. This step is necessary here due to the next step, which deals with missing values. + # Notice that we drop the target column before scaling, to avoid some kind of data leakage. + # (see https://stats.stackexchange.com/questions/214728/should-data-be-normalized-before-or-after-imputation-of-missing-data) + target_column = df[target_name] + predictors_df = df.drop(columns=[target_name], axis=1).copy() + if normalize_predictors: + scaler_type = ( + (scaler_config.get("type") or "minmax") + if isinstance(scaler_config, dict) + else "minmax" + ) + logging.info(f"Applying '{scaler_type}' scaling...") + predictors_df = apply_scaling(predictors_df, scaler_config) + logging.info("Done!\n") + else: + logging.info("Skipping normalization as configured.\n") + + # + # Imput missing values on some features. + if impute_missing_values: + strategy = ( + (imputation_config.get("strategy") or "knn") + if isinstance(imputation_config, dict) + else "knn" + ) + logging.info(f"Applying '{strategy}' imputation...") + percentage_missing = ( + predictors_df.isna().mean() * 100 + ).mean() # Compute the percentage of missing values + logging.info( + f"There are {predictors_df.isnull().sum().sum()} missing values ({percentage_missing:.2f}%). Going to fill them..." + ) + predictors_df = apply_imputation(predictors_df, imputation_config) + assert not predictors_df.isnull().values.any().any() + logging.info("Done!\n") + else: + logging.info("Skipping missing-value imputation as configured.\n") + strategy_value = None + strategy_flag = True + if isinstance(imputation_config, dict): + strategy_value = imputation_config.get("strategy", "knn") + if isinstance(strategy_value, str): + strategy_flag = strategy_value.lower() not in {"none", "skip"} + imputation_applied = bool(impute_missing_values and strategy_flag) + + # + # Add the target column back to the DataFrame. + predictors_df[target_name] = target_column + df = predictors_df + + # + # Save preprocessed data to a parquet file. + filename_and_extension = utils.get_filename_and_extension(ws_filename) + filename = output_folder + filename_and_extension[0] + "_preprocessed.parquet.gzip" + logging.info(f"Saving preprocessed data to {filename}...") + df.to_parquet(filename, compression="gzip") + logging.info("Done!\n") + + if ( + report_enabled + and report_reference_df is not None + and missing_counts_before is not None + ): + report_payload = build_quality_report( + station_id=ws_id, + station_system=station_system, + report_df=report_reference_df, + report_config=report_config, + station_metadata=station_metadata, + scaler_config=scaler_config, + imputation_config=imputation_config, + missing_counts_before=missing_counts_before, + imputation_applied=imputation_applied, + source_file=ws_filename, + output_file=filename, + target_column=target_name, + quality_checks=quality_summary, + ) + report_filename = ( + output_folder + filename_and_extension[0] + "_preprocess_report.json" + ) + with open(report_filename, "w", encoding="utf-8") as report_file: + json.dump(report_payload, report_file, indent=2, ensure_ascii=False) + logging.info(f"Quality report saved to {report_filename}\n") + + logging.info("Done it all!\n") + + +def main(argv): + parser = argparse.ArgumentParser(description="Preprocess weather station data.") + parser.add_argument( + "-s", + "--station_id", + required=True, + #Add STATION_IDS + choices=globals.INMET_WEATHER_STATION_IDS + + globals.ALERTARIO_WEATHER_STATION_IDS + + globals.WEBSIRENE_STATION_IDS, + + help="ID of the weather station to preprocess data for.", + ) + parser.add_argument( + "-y", + "--station_system", + choices=sorted(STATION_SYSTEM_CONFIG.keys()), + type=str.lower, + help="System of the weather station (e.g., INMET, AlertaRio).", + ) + args = parser.parse_args(argv[1:]) + + station_id = args.station_id + station_system = args.station_system + + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.DEBUG, format=fmt) + + if station_system: + #Added ID type check + if station_system == 'websirene': + try: + # Ensure the websirene ID is treated as a string + station_id = str(int(station_id)) + except ValueError: + parser.error(f"Station ID '{station_id}' for websirene must be numeric.") + + system_config = STATION_SYSTEM_CONFIG[station_system] + + # Compare IDs as strings for consistency + if str(station_id) not in {str(sid) for sid in system_config["ids"]}: + parser.error( + f"Station {station_id} does not belong to the {station_system.upper()} system." + ) + ws_data_dir = system_config["data_dir"] + else: + ws_data_dir = None + # Infer system + for system_name, system_config in STATION_SYSTEM_CONFIG.items(): + # Compare IDs as strings for consistency + if str(station_id) in {str(sid) for sid in system_config["ids"]}: + station_system = system_name + ws_data_dir = system_config["data_dir"] + break + if ws_data_dir is None: + parser.error(f"Invalid station identifier: {station_id}") + + print( + f"Preprocessing data coming from weather station {station_id} (system: {station_system.upper()})" + ) + + system_config_full = STATION_SYSTEM_CONFIG[station_system] + raw_format = system_config_full.get("raw_format", "parquet") # Default is parquet + + # Build the file name with the correct extension + ws_filename = str(ws_data_dir) + str(station_id) + f".{raw_format}" + + # Check if the input file exists + if not Path(ws_filename).exists(): + logging.error(f"Input file not found: {ws_filename}") + parser.error(f"Input file not found: {ws_filename}") + + preprocess_ws( + ws_id=station_id, + ws_filename=ws_filename, + output_folder=str(ws_data_dir), + station_system=station_system, + raw_format=raw_format + ) + + +if __name__ == "__main__": + main(sys.argv) \ No newline at end of file diff --git a/src/preprocess_rd_colorcord.py b/src/preprocess_rd_colorcord.py deleted file mode 100644 index b677fbad..00000000 --- a/src/preprocess_rd_colorcord.py +++ /dev/null @@ -1,183 +0,0 @@ -import os, argparse -import pandas as pd -import cv2 -import math - -coords = "..\\data\\nova_base\\estacoes_pluviometricas.csv" -coords = pd.read_csv(coords) - -latitude_pc = 4.4997 -longitude_pc = 4.9321 - - -def gera_df_est(): - - df_est = pd.DataFrame() - - for n in coords['N']: - - e = coords.iloc[(n-1),1] - lat = coords.iloc[(n-1),2] - long =coords.iloc[(n-1),3] - - ya, xa = pontos(long,lat) - xa, ya = round(xa), round(ya) - - d1 = {"Estação": [e], "X": [xa], "Y": [ya]} - df = pd.DataFrame(d1) - df_est = pd.concat([df_est,df]) - - return df_est - -def pontos(x,y): - - lat_pc, long_pc = -22.464278, -43.297476 - - dist_x = (x - long_pc) - dist_y = (y - lat_pc) - - x1 = 125 + (dist_x * 250 / longitude_pc) - y1 = 125 - (dist_y * 250 / latitude_pc) - - return y1,x1 - -def parameter(image,raio,df_est, df_estacoes): - - i = 5 #COPACABANA - - x = int(df_est.iloc[i, 1]) - y = int(df_est.iloc[i, 2]) - - pixel_est = f'({str(df_est.iloc[i, 1])},{str(df_est.iloc[i, 2])})' - dic1= {'Estação': df_est.iloc[i, 0], 'Pixel': [pixel_est]} - df_head = pd.DataFrame(dic1) - - dataframe1 = gera_dataframe(image,x,y,raio, df_head, df_estacoes) - return dataframe1 - - - -def gera_dataframe(image,x,y,raio,df_head, df_estacoes): - - df_data = pd.DataFrame() - - for ix in range (x-raio, x+raio+1): - for iy in range (y-raio, y+raio+1): - - dist_x = ix - x - if dist_x > 0: - coord_x = f"p{dist_x}" - elif dist_x < 0: - dist_x = abs(dist_x) - coord_x = f"m{dist_x}" - else: - coord_x = "e0" - - dist_y = iy - y - - if dist_y < 0: - dist_y = abs(dist_y) - coord_y = f"p{dist_y}" - elif dist_y > 0: - dist_y = (dist_y) - coord_y = f"m{dist_y}" - else: - coord_y = "e0" - - pixel = image[iy, ix] - B = pixel[0] - G = pixel[1] - R = pixel[2] - - hsv_img = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) - - pixel = hsv_img[iy, ix] - H = pixel[0] - S = pixel[1] - V = pixel[2] - - - - dic = {f"{coord_x}{coord_y}R": [R], f"{coord_x}{coord_y}G": [G],f"{coord_x}{coord_y}B": [B], - f"{coord_x}{coord_y}H": [H], f"{coord_x}{coord_y}S":[S], f"{coord_x}{coord_y}V":[V]} - - d_colors = pd.DataFrame(dic) - d_colors[f"{coord_x}{coord_y}R"] = R - d_colors[f"{coord_x}{coord_y}G"] = G - d_colors[f"{coord_x}{coord_y}B"] = B - d_colors[f"{coord_x}{coord_y}H"] = H - d_colors[f"{coord_x}{coord_y}S"] = S - d_colors[f"{coord_x}{coord_y}V"] = V - - df_data = pd.concat([df_data,d_colors], axis=1) - dataframe1 = pd.concat([df_head, df_data], axis=1) - - dataframe1 = dataframe1.loc[~dataframe1.index.duplicated(keep='first')] - - return dataframe1 - - - -path = "..\\data\\nova_base\\img\\" - -print("Iniciando extração de cores") - -def processing(raio): - - df_estacoes = pd.DataFrame() - - for year_folder in os.listdir(path): - year_path = os.path.join(path, year_folder) - if os.path.isdir(year_path): - - for month_folder in os.listdir(year_path): - month_path = os.path.join(year_path, month_folder) - if os.path.isdir(month_path): - - for day_folder in os.listdir(month_path): - day_path = os.path.join(month_path, day_folder) - if os.path.isdir(day_path): - - for filename in os.listdir(day_path): - if filename.endswith(".png"): - - file = os.path.join(day_path, filename) - - image = cv2.imread(file) - if image is None: - continue - image = cv2.resize(image, (250, 250)) - if image is None: - continue - - df_est = gera_df_est() - - dataframe1 = parameter(image,raio, df_est, df_estacoes) - dataframe1.insert(0, "date", filename.split(".")[0]) - df_estacoes = pd.concat([df_estacoes, dataframe1], ignore_index=True) - - - df_estacoes.sort_values("date") - df_estacoes.to_csv(f"..\\data\\nova_base\\FEATURE_A652_COLORCORD.csv") - -def parameter_parser(): - description ="Script to parametrize one region around a station, represented by a pixel. Analyzes in RGB and HSV colors. \n \ - acepts [-r, -f] to radius of region and wich feature will be used. \n " - - parser = argparse.ArgumentParser(description=description) - - parser.add_argument('-r',"--radius", required=False) - - - return parser.parse_args() - -if __name__ == '__main__': - - args = parameter_parser() - - raio = args.radius if args.radius != None else 1 - raio = int(raio) - processing(raio) - - - diff --git a/src/preprocess_ws.py b/src/preprocess_ws.py deleted file mode 100644 index 3ea9557c..00000000 --- a/src/preprocess_ws.py +++ /dev/null @@ -1,195 +0,0 @@ -import pandas as pd -from pathlib import Path -import argparse -import sys -import globals -import util -from sklearn.impute import KNNImputer -import logging - -# list_valid_datasource_combinations = ("R", "N", "R+N") - -# def preprocess_sounding_data(sounding_data_source): -# print(f"Loading datasource file ({sounding_data_source}).") -# df = pd.read_parquet(sounding_data_source) -# format_string = '%Y-%m-%d %H:%M:%S' - -# # -# # Add index to dataframe using the observation's timestamps. -# df['Datetime'] = pd.to_datetime(df['time'], format=format_string) -# df = df.set_index(pd.DatetimeIndex(df['Datetime'])) -# print(f"Range of timestamps after preprocessing {sounding_data_source}: [{min(df.index)}, {max(df.index)}]") - -# # -# # Remove time-related columns since now this information is in the index. -# df = df.drop(['time', 'Datetime'], axis = 1) - -# # -# # Save preprocessed data. -# filename_and_extension = get_filename_and_extension(sounding_data_source) -# filename = WS_DATA_DIR + filename_and_extension[0] + '_preprocessed.parquet.gzip' -# print(f"Saving preprocessed data to {filename}") -# df.to_parquet(filename, compression='gzip') - -# def preprocess_numerical_model_data(numerical_model_data_source): -# print(f"Loading NWP datasource file ({numerical_model_data_source}).") -# df = pd.read_csv(numerical_model_data_source) - -# # -# # Add index to dataframe using the timestamps. -# format_string = '%Y-%m-%d %H:%M:%S' -# df['Datetime'] = pd.to_datetime(df['time'], format=format_string) -# df = df.set_index(pd.DatetimeIndex(df['Datetime'])) -# df = df.drop(['time', 'Datetime', 'Unnamed: 0'], axis = 1) -# print(f"Range of timestamps after preprocessing {numerical_model_data_source}: [{min(df.index)}, {max(df.index)}]") - -# df = util.min_max_normalize(df) - -# # -# # Save preprocessed data. -# filename_and_extension = get_filename_and_extension(numerical_model_data_source) -# filename = filename_and_extension[0] + '_preprocessed.parquet.gzip' -# print(f"Saving preprocessed data to {filename}") -# df.to_parquet(filename, compression='gzip') - -def preprocess_ws(ws_id, ws_filename, output_folder): - - logging.info(f"Loading datasource file {ws_filename}).") - df = pd.read_parquet(ws_filename) - logging.info(df.head()) - logging.info("Done!\n") - - # - # Add index to dataframe using the timestamps. - logging.info(f"Adding index to dataframe using the timestamps...") - df = util.add_datetime_index(ws_id, df) - logging.info(df.head()) - logging.info("Done!\n") - - # - # Standardize column names. - logging.info(f"Standardizing column names...") - if ws_id in globals.ALERTARIO_WEATHER_STATION_IDS: - column_name_mapping = { - "datetime": "datetime", - "temperature_mean": "temperature", - "humidity_mean": "relative_humidity", - "pressure_mean": "barometric_pressure", - "wind_speed_mean": "wind_speed", - "wind_dir_mean": "wind_dir", - "precipitation_sum": "precipitation" - } - elif ws_id in globals.INMET_WEATHER_STATION_IDS: - column_name_mapping = { - "datetime": "datetime", - "TEM_MAX": "temperature", - "UMD_MAX": "relative_humidity", - "PRE_MAX": "barometric_pressure", - "VEN_VEL": "wind_speed", - "VEN_DIR": "wind_dir", - "CHUVA": "precipitation" - } - column_names = column_name_mapping.keys() - df = util.get_dataframe_with_selected_columns(df, column_names) - df = util.rename_dataframe_column_names(df, column_name_mapping) - logging.info(df.head()) - logging.info("Done!\n") - - logging.info("Getting relevant variables...") - predictor_names, target_name = util.get_relevant_variables(ws_id) - logging.info(f"Predictors: {predictor_names}") - logging.info(f"Target: {target_name}") - logging.info("Done!\n") - - # - # Drop observations in which the target variable is not defined. - logging.info(f"Dropping entries with null target...") - n_obser_before_drop = len(df) - df = df[df[target_name].notna()] - n_obser_after_drop = len(df) - logging.info(f"Number of observations before/after dropping entries with undefined target value: {n_obser_before_drop}/{n_obser_after_drop}.") - logging.info(f"Range of timestamps after dropping entries with undefined target value: [{min(df.index)}, {max(df.index)}]") - logging.info(df.head()) - logging.info("Done!\n") - - # - # Create wind-related features (U and V components of wind observations). - logging.info(f"Creating wind-related features...") - df = util.add_wind_related_features(ws_id, df) - logging.info(df.head()) - logging.info("Done!\n") - - # - # Create time-related features (sin and cos components) - logging.info(f"Creating time-related features...") - df = util.add_hour_related_features(df) - logging.info(df.head()) - logging.info("Done!\n") - - df = df[predictor_names + [target_name]] - - # - # Normalize the weather station data. This step is necessary here due to the next step, which deals with missing values. - # Notice that we drop the target column before normalizing, to avoid some kind of data leakage. - # (see https://stats.stackexchange.com/questions/214728/should-data-be-normalized-before-or-after-imputation-of-missing-data) - logging.info("Min-max normalizing data...") - target_column = df[target_name] - df = df.drop(columns=[target_name], axis=1) - df = util.min_max_normalize(df) - logging.info("Done!\n") - - # - # Imput missing values on some features. - logging.info("Applying KNNImputer...") - percentage_missing = (df.isna().mean() * 100).mean() # Compute the percentage of missing values - logging.info(f"There are {df.isnull().sum().sum()} missing values ({percentage_missing:.2f}%). Going to fill them...") - imputer = KNNImputer(n_neighbors=2) - df[:] = imputer.fit_transform(df) - assert (not df.isnull().values.any().any()) - logging.info("Done!\n") - - # - # Add the target column back to the DataFrame. - df[target_name] = target_column - - # - # Save preprocessed data to a parquet file. - filename_and_extension = util.get_filename_and_extension(ws_filename) - filename = output_folder + filename_and_extension[0] + '_preprocessed.parquet.gzip' - logging.info(f"Saving preprocessed data to {filename}...") - df.to_parquet(filename, compression='gzip') - logging.info("Done!\n") - - logging.info("Done it all!\n") - -def main(argv): - parser = argparse.ArgumentParser(description='Preprocess weather station data.') - parser.add_argument('-s', '--station_id', - required=True, - choices=globals.INMET_WEATHER_STATION_IDS + globals.ALERTARIO_WEATHER_STATION_IDS, - help='ID of the weather station to preprocess data for.') - args = parser.parse_args(argv[1:]) - - station_id = args.station_id - - fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" - logging.basicConfig(level=logging.DEBUG, format = fmt) - - if not ((station_id in globals.INMET_WEATHER_STATION_IDS) or (station_id in globals.ALERTARIO_WEATHER_STATION_IDS)): - print(f"Invalid station identifier: {station_id}") - parser.print_help() - sys.exit(2) - - if (station_id in globals.INMET_WEATHER_STATION_IDS): - ws_data_dir = globals.WS_INMET_DATA_DIR - elif (station_id in globals.ALERTARIO_WEATHER_STATION_IDS): - ws_data_dir = globals.WS_ALERTARIO_DATA_DIR - - print(f'Preprocessing data coming from weather station {station_id}') - ws_filename = ws_data_dir + args.station_id + ".parquet" - preprocess_ws(ws_id=station_id, ws_filename=ws_filename, output_folder=ws_data_dir) - - print('Done!') - -if __name__ == '__main__': - main(sys.argv) diff --git a/src/qcheck/check_acc_15min_vs_1h.py b/src/qcheck/check_acc_15min_vs_1h.py new file mode 100644 index 00000000..80c513e9 --- /dev/null +++ b/src/qcheck/check_acc_15min_vs_1h.py @@ -0,0 +1,147 @@ +import argparse +from datetime import timedelta +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +from tqdm import tqdm + + +class Websirene1h15mQualityCheck: + def _check_websirenes_keys_exists( + self, websirene_key: str, fn_disabled=True + ) -> str: + if fn_disabled: + return websirene_key + + try: + current_dir = Path.cwd() + websirenes_keys_dir = current_dir / "websirenes_keys" + if not websirenes_keys_dir.exists(): + raise FileNotFoundError( + "websirenes_keys folder not found in the current directory" + ) + + parquet_files = list(websirenes_keys_dir.glob("*.parquet")) + if not parquet_files or not len(parquet_files) > 0: + raise FileNotFoundError( + "No .parquet files found in websirenes_keys folder" + ) + + websirene_key_path = websirenes_keys_dir / websirene_key + if not websirene_key_path.exists(): + raise FileNotFoundError( + f"{websirene_key} not found in websirenes_keys folder" + ) + + filename = websirene_key_path.stem + return filename + except FileNotFoundError as e: + print(f"Error: {e}") + exit(1) + + def _show_info(self, df: pd.DataFrame): + print("head:") + print(df.head()) + + print("describe:") + print(df.describe()) + + print("min index:") + print(df.index.min()) + + print("max index:") + print(df.index.max()) + + def compare_15min_1h(self, parquet: str): + filename = self._check_websirenes_keys_exists(parquet) + + df = pd.read_parquet(parquet) + self._show_info(df) + + minimum_date = df.index.min().replace(minute=0, second=0, microsecond=0) + minimum_date = ( + minimum_date + if minimum_date >= df.index.min() + else minimum_date + timedelta(hours=1) + ) + + print(f"Using minimum date: {minimum_date}") + + maximum_date = df.index.max().replace(minute=0, second=0, microsecond=0) + maximum_date = ( + maximum_date + if maximum_date <= df.index.max() + else maximum_date - timedelta(hours=1) + ) + print(f"Using maximum date: {maximum_date}") + + hourly_range = pd.date_range(start=minimum_date, end=maximum_date, freq="H") + + total_processed = 0 + + diff_series = [] + + for hour in tqdm(hourly_range): + time_upper_bound = hour + time_lower_bound = hour - timedelta(minutes=45) + + df_filtered = df[ + (df.index >= time_lower_bound) & (df.index <= time_upper_bound) + ] + + h01 = df[df.index == time_upper_bound]["h01"] + m15 = df_filtered["m15"] + + if not np.isclose(m15.sum(), h01.sum(), rtol=1e-05): + m15_value = m15.sum() + h1_value = h01.sum() + diff_series.append(np.abs(m15_value - h1_value)) + total_processed += 1 + + fig, ax = plt.subplots(figsize=(12, 6)) + + ax.boxplot(diff_series, labels=["Absolute Difference"]) + plt.title( + f"Absolute Difference between h01 and m15 {len(diff_series)}/{total_processed} are different" + ) + plt.ylabel("Diff Value") + output_file = Path.cwd() / f"{filename}_boxplot_1h_15minAggregated.png" + green = "\033[92m" + reset = "\033[0m" + print(f"{green}Saving boxplot to {output_file}{reset}") + plt.savefig(output_file) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description=( + "Check if the 15min sum is equal to the 1h sum.\n\n" + "Usage example:\n" + 'python check_acc_15min_vs_1h.py --station-type websirenes --parquet="-22.8652_-43.2805.parquet"' + ), + formatter_class=argparse.RawTextHelpFormatter, # Ensures proper formatting for multiline help text + ) + parser.add_argument( + "--station-type", + dest="station_type", + type=str, + required=True, + help="Station name", + choices=["websirenes", "inmet", "alertario"], + ) + parser.add_argument( + "--parquet", + type=str, + required=True, + help='Name of the parquet file, for example: "-22.8652_-43.2805.parquet"', + ) + + args = parser.parse_args() + + if args.station_type == "websirenes": + station_check = Websirene1h15mQualityCheck() + # TODO: alertario and inmet + + station_check.compare_15min_1h(args.parquet) diff --git a/src/radar/pico_couto/preprocess_rd_colorcord.py b/src/radar/pico_couto/preprocess_rd_colorcord.py new file mode 100644 index 00000000..a7ff5598 --- /dev/null +++ b/src/radar/pico_couto/preprocess_rd_colorcord.py @@ -0,0 +1,178 @@ +import argparse +import os + +import cv2 +import pandas as pd + +coords = "..\\data\\nova_base\\estacoes_pluviometricas.csv" +coords = pd.read_csv(coords) + +latitude_pc = 4.4997 +longitude_pc = 4.9321 + + +def gera_df_est(): + df_est = pd.DataFrame() + + for n in coords["N"]: + e = coords.iloc[(n - 1), 1] + lat = coords.iloc[(n - 1), 2] + long = coords.iloc[(n - 1), 3] + + ya, xa = pontos(long, lat) + xa, ya = round(xa), round(ya) + + d1 = {"Estação": [e], "X": [xa], "Y": [ya]} + df = pd.DataFrame(d1) + df_est = pd.concat([df_est, df]) + + return df_est + + +def pontos(x, y): + lat_pc, long_pc = -22.464278, -43.297476 + + dist_x = x - long_pc + dist_y = y - lat_pc + + x1 = 125 + (dist_x * 250 / longitude_pc) + y1 = 125 - (dist_y * 250 / latitude_pc) + + return y1, x1 + + +def parameter(image, raio, df_est, df_estacoes): + i = 5 # COPACABANA + + x = int(df_est.iloc[i, 1]) + y = int(df_est.iloc[i, 2]) + + pixel_est = f"({str(df_est.iloc[i, 1])},{str(df_est.iloc[i, 2])})" + dic1 = {"Estação": df_est.iloc[i, 0], "Pixel": [pixel_est]} + df_head = pd.DataFrame(dic1) + + dataframe1 = gera_dataframe(image, x, y, raio, df_head, df_estacoes) + return dataframe1 + + +def gera_dataframe(image, x, y, raio, df_head, df_estacoes): + df_data = pd.DataFrame() + + for ix in range(x - raio, x + raio + 1): + for iy in range(y - raio, y + raio + 1): + dist_x = ix - x + if dist_x > 0: + coord_x = f"p{dist_x}" + elif dist_x < 0: + dist_x = abs(dist_x) + coord_x = f"m{dist_x}" + else: + coord_x = "e0" + + dist_y = iy - y + + if dist_y < 0: + dist_y = abs(dist_y) + coord_y = f"p{dist_y}" + elif dist_y > 0: + dist_y = dist_y + coord_y = f"m{dist_y}" + else: + coord_y = "e0" + + pixel = image[iy, ix] + B = pixel[0] + G = pixel[1] + R = pixel[2] + + hsv_img = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) + + pixel = hsv_img[iy, ix] + H = pixel[0] + S = pixel[1] + V = pixel[2] + + dic = { + f"{coord_x}{coord_y}R": [R], + f"{coord_x}{coord_y}G": [G], + f"{coord_x}{coord_y}B": [B], + f"{coord_x}{coord_y}H": [H], + f"{coord_x}{coord_y}S": [S], + f"{coord_x}{coord_y}V": [V], + } + + d_colors = pd.DataFrame(dic) + d_colors[f"{coord_x}{coord_y}R"] = R + d_colors[f"{coord_x}{coord_y}G"] = G + d_colors[f"{coord_x}{coord_y}B"] = B + d_colors[f"{coord_x}{coord_y}H"] = H + d_colors[f"{coord_x}{coord_y}S"] = S + d_colors[f"{coord_x}{coord_y}V"] = V + + df_data = pd.concat([df_data, d_colors], axis=1) + dataframe1 = pd.concat([df_head, df_data], axis=1) + + dataframe1 = dataframe1.loc[~dataframe1.index.duplicated(keep="first")] + + return dataframe1 + + +path = "..\\data\\nova_base\\img\\" + +print("Iniciando extração de cores") + + +def processing(raio): + df_estacoes = pd.DataFrame() + + for year_folder in os.listdir(path): + year_path = os.path.join(path, year_folder) + if os.path.isdir(year_path): + for month_folder in os.listdir(year_path): + month_path = os.path.join(year_path, month_folder) + if os.path.isdir(month_path): + for day_folder in os.listdir(month_path): + day_path = os.path.join(month_path, day_folder) + if os.path.isdir(day_path): + for filename in os.listdir(day_path): + if filename.endswith(".png"): + file = os.path.join(day_path, filename) + + image = cv2.imread(file) + if image is None: + continue + image = cv2.resize(image, (250, 250)) + if image is None: + continue + + df_est = gera_df_est() + + dataframe1 = parameter( + image, raio, df_est, df_estacoes + ) + dataframe1.insert(0, "date", filename.split(".")[0]) + df_estacoes = pd.concat( + [df_estacoes, dataframe1], ignore_index=True + ) + + df_estacoes.sort_values("date") + df_estacoes.to_csv("..\\data\\nova_base\\FEATURE_A652_COLORCORD.csv") + + +def parameter_parser(): + description = "Script to parametrize one region around a station, represented by a pixel. Analyzes in RGB and HSV colors. \n \ + acepts [-r, -f] to radius of region and wich feature will be used. \n " + + parser = argparse.ArgumentParser(description=description) + + parser.add_argument("-r", "--radius", required=False) + + return parser.parse_args() + + +if __name__ == "__main__": + args = parameter_parser() + + raio = args.radius if args.radius is not None else 1 + raio = int(raio) + processing(raio) diff --git a/src/preprocess_rd_conv2d.py b/src/radar/pico_couto/preprocess_rd_conv2d.py similarity index 63% rename from src/preprocess_rd_conv2d.py rename to src/radar/pico_couto/preprocess_rd_conv2d.py index 11722031..5e712f1f 100644 --- a/src/preprocess_rd_conv2d.py +++ b/src/radar/pico_couto/preprocess_rd_conv2d.py @@ -1,8 +1,8 @@ import os -import pandas as pd -import numpy as np + import cv2 -import tensorflow as tf +import numpy as np +import pandas as pd from tensorflow.keras import layers, models PATH = "..\\data\\nova_base\\img\\" @@ -10,17 +10,23 @@ OUTPUT_FILE = "..\\data\\nova_base\\FEATURE_A652_CONV2D.csv" IMAGE_SIZE = (250, 250) + def create_conv_model(): model = models.Sequential() - model.add(layers.Conv2D(16, (3, 3), activation='relu', padding='same', input_shape=(*IMAGE_SIZE, 3))) + model.add( + layers.Conv2D( + 16, (3, 3), activation="relu", padding="same", input_shape=(*IMAGE_SIZE, 3) + ) + ) model.add(layers.MaxPooling2D((3, 3))) model.add(layers.Dropout(0.25)) - model.add(layers.Conv2D(32, (3, 3), activation='relu', padding='same')) + model.add(layers.Conv2D(32, (3, 3), activation="relu", padding="same")) model.add(layers.MaxPooling2D((3, 3))) model.add(layers.Dropout(0.25)) model.add(layers.GlobalAveragePooling2D()) return model + def processing(model): df_estacoes = pd.DataFrame() @@ -47,13 +53,29 @@ def processing(model): feature_maps = model.predict(image) feature_means = np.mean(feature_maps, axis=(1, 2)) feature_vars = np.var(feature_maps, axis=(1, 2)) - df_row = pd.DataFrame([np.concatenate((feature_means.flatten(), feature_vars.flatten()))], - columns=[f"Mean_{i}" for i in range(feature_means.shape[1])] + - [f"Var_{i}" for i in range(feature_vars.shape[1])]) + df_row = pd.DataFrame( + [ + np.concatenate( + ( + feature_means.flatten(), + feature_vars.flatten(), + ) + ) + ], + columns=[ + f"Mean_{i}" + for i in range(feature_means.shape[1]) + ] + + [ + f"Var_{i}" + for i in range(feature_vars.shape[1]) + ], + ) df_estacoes = pd.concat([df_estacoes, df_row]) df_estacoes.to_csv(OUTPUT_FILE) -if __name__ == '__main__': + +if __name__ == "__main__": model = create_conv_model() - processing(model) \ No newline at end of file + processing(model) diff --git a/src/radar/pico_couto/retrieve_rd.py b/src/radar/pico_couto/retrieve_rd.py new file mode 100644 index 00000000..6e34dd41 --- /dev/null +++ b/src/radar/pico_couto/retrieve_rd.py @@ -0,0 +1,145 @@ +import argparse +import os +import shutil +import time +from datetime import datetime, timedelta + +import requests + +api_key = "aOrV6N5DtQen69uEDlYwbUTo3CTTCcAZ50r7WEW4" + + +def extract(datas_str): + dados_faltantes = [] + sem_dados = [] + + for data in datas: + print(f"\n{data}") + + date_h = [] + for hora in range(0, 24): + date_h.append(data.replace(hour=hora)) + datas_str = [data.strftime("%Y%m%d%H") for data in date_h] + + print("iniciando requisição") + + true = [] + + for i in datas_str: + requisicao = requests.get( + f"https://api-redemet.decea.mil.br/produtos/radar/03km?api_key={api_key}&radar=pc&anima=3&data={i}" + ) + # time.sleep(0.2) + + print(f"Requisição concluida da hora {i}") + + if "Server Error" not in requisicao.text: + json = requisicao.json() + if "status" in json: + if json["status"]: + true.append(json) + + elif "error" in json: + print("OVER_RATE LIMIT") + break + else: + print("Sem status") + else: + print("ERRO DE SERVIDOR") + + radares = [i["data"]["radar"] for i in true] + rad1 = [i[0] for i in radares] + rad2 = [i[1] for i in radares] + rad3 = [i[2] for i in radares] + radares_1 = rad1 + rad2 + rad3 + + date1 = [i[11]["data"] for i in radares_1] + date_t = [x for x in date1 if x is not None] + date_true = [datetime.strptime(i, "%Y-%m-%d %H:%M:%S") for i in date_t] + date_days = [i.strftime("%Y%m%d%H") for i in date_true] + date_days = list(set(date_days)) + hora_sem_retorno = list(set(datas_str) - set(date_days)) + + if len(hora_sem_retorno) == 24: + sem_dados.append(list(i for i in hora_sem_retorno)) + print("Atenção: DATA SEM DADOS!") + time.sleep(0.2) + + elif len(hora_sem_retorno) < 24 and len(hora_sem_retorno) > 0: + dados_faltantes.append(list(i for i in hora_sem_retorno)) + print(f"Atenção: data com horas faltantes. ({len(hora_sem_retorno)})") + + elif len(hora_sem_retorno) == 0: + print("Data com todos os dados") + + pc = [i[11]["path"] for i in radares_1] + path_pc = list(set(pc)) + path_pc = [i for i in path_pc if type(i) is str] + + for i in path_pc: + filename = i.split("/")[-1] + response = requests.get(i) + with open( + "..\\data\\nova_base\\img\\" + + filename.split(".")[0].replace(":", "") + + ".png", + "wb", + ) as f: + f.write(response.content) + + print("\nDados Baixados\n") + + +def parameter_parser(): + description = "Script to perform ETL on PICODOCOUTO data. Format: DD/MM/YYYY" + + parser = argparse.ArgumentParser(description=description) + + parser.add_argument("-b", "--dt_begin", required=True) + + parser.add_argument("-e", "--dt_end", required=True) + + return parser.parse_args() + + +args = parameter_parser() + +db = args.dt_begin[:2] +mb = args.dt_begin[3:5] +yb = args.dt_begin[6:10] + +de = args.dt_end[:2] +me = args.dt_end[3:5] +ye = args.dt_end[6:10] + +print(db, mb, yb) + +data_inicial = datetime(int(yb), int(mb), int(db)) +data_final = datetime(int(ye), int(me), int(de)) + +datas = [] +data_atual = data_inicial +while data_atual <= data_final: + datas.append(data_atual) + data_atual += timedelta(days=1) + +extract(datas) + +dir_path = "..\\data\\nova_base\\img" + +for filename in os.listdir(dir_path): + if filename.endswith(".png"): + datetime_str = filename.split("--")[0] + datetime_obj = datetime.strptime(datetime_str, "%Y-%m-%d") + year_dir = os.path.join(dir_path, datetime_obj.strftime("%Y")) + if not os.path.exists(year_dir): + os.mkdir(year_dir) + month_dir = os.path.join(year_dir, datetime_obj.strftime("%m")) + if not os.path.exists(month_dir): + os.mkdir(month_dir) + day_dir = os.path.join(month_dir, datetime_obj.strftime("%d")) + if not os.path.exists(day_dir): + os.mkdir(day_dir) + src_path = os.path.join(dir_path, filename) + dst_path = os.path.join(day_dir, filename) + shutil.move(src_path, dst_path) diff --git a/src/radar/sumare/__pycache__/crop_image.cpython-311.pyc b/src/radar/sumare/__pycache__/crop_image.cpython-311.pyc new file mode 100644 index 00000000..43d812f3 Binary files /dev/null and b/src/radar/sumare/__pycache__/crop_image.cpython-311.pyc differ diff --git a/src/radar/sumare/__pycache__/radar_data.cpython-311.pyc b/src/radar/sumare/__pycache__/radar_data.cpython-311.pyc new file mode 100644 index 00000000..c1f7f53d Binary files /dev/null and b/src/radar/sumare/__pycache__/radar_data.cpython-311.pyc differ diff --git a/src/radar/sumare/correlation.py b/src/radar/sumare/correlation.py new file mode 100644 index 00000000..64728e97 --- /dev/null +++ b/src/radar/sumare/correlation.py @@ -0,0 +1,254 @@ +import math +import os + +import numpy as np +import pandas as pd +from PIL import Image +from scipy import stats + + +def rgb_distance(c1, c2): + return math.sqrt((c1[0] - c2[0]) ** 2 + (c1[1] - c2[1]) ** 2 + (c1[2] - c2[2]) ** 2) + + +def interpolate_value(rgb, legend_colors, legend_values): + if rgb == (0, 0, 0): + return 0 + # Calcular distâncias entre a cor fornecida e todas as cores da legenda + distances = [rgb_distance(rgb, lc) for lc in legend_colors] + + # Identificar as duas cores mais próximas na legenda + min_idx1 = distances.index(min(distances)) # Índice da cor mais próxima + distances[min_idx1] = float( + "inf" + ) # Excluir a cor mais próxima para achar a segunda + min_idx2 = distances.index(min(distances)) # Índice da segunda cor mais próxima + + # Obter as cores e valores correspondentes + c1, c2 = legend_colors[min_idx1], legend_colors[min_idx2] + v1, v2 = legend_values[min_idx1], legend_values[min_idx2] + + # Calcular o peso de interpolação (t) + dist_c1_c2 = rgb_distance(c1, c2) + dist_c1_rgb = rgb_distance(c1, rgb) + t = dist_c1_rgb / dist_c1_c2 if dist_c1_c2 != 0 else 0 + + # Interpolar o valor + interpolated_value = v1 + t * (v2 - v1) + return interpolated_value + + +def get_radar_data(station_name, met): + df_local = pd.read_csv("./WeatherStations.csv") + df_local = df_local[df_local["STATION_ID"] == station_name] + + if station_name in STATION_NAMES_FOR_RJ: + if met: + df = pd.read_csv("./data/landing/" + station_name + ".csv") # COR + else: + df = pd.read_csv("./data/landing/plv/" + station_name + ".csv") + else: + df = pd.read_parquet("./data/inmet-data/" + station_name + ".parquet") + df["reflect"] = np.nan + vlat = df_local["VL_LATITUDE"].iloc[0] + vlon = df_local["VL_LONGITUDE"].iloc[0] + print(station_name) + i = 0 + + while i < len(df): + df1 = df[df.index == i] + if station_name in STATION_NAMES_FOR_RJ: + arquivo = ( + df1["Dia"].iloc[0][:4] + + "_" + + df1["Dia"].iloc[0][5:7] + + "_" + + df1["Dia"].iloc[0][8:10] + + "_" + + df1["Hora"].iloc[0][:2] + + "_" + + df1["Hora"].iloc[0][3:5] + ) + caminho = ( + "./data/radar_sumare/" + + df1["Dia"].iloc[0][:4] + + "/" + + df1["Dia"].iloc[0][5:7] + + "/" + + df1["Dia"].iloc[0][8:10] + + "/" + + arquivo + + ".png" + ) + else: + arquivo = ( + df1["DT_MEDICAO"].iloc[0][:4] + + "_" + + df1["DT_MEDICAO"].iloc[0][5:7] + + "_" + + df1["DT_MEDICAO"].iloc[0][8:10] + + "_" + + str(df1["HR_MEDICAO"].iloc[0]).zfill(4)[:2] + + "_" + + str(df1["HR_MEDICAO"].iloc[0]).zfill(4)[2:4] + ) + caminho = ( + "./data/radar_sumare/" + + df1["DT_MEDICAO"].iloc[0][:4] + + "/" + + df1["DT_MEDICAO"].iloc[0][5:7] + + "/" + + df1["DT_MEDICAO"].iloc[0][8:10] + + "/" + + arquivo + + ".png" + ) + if os.path.exists(caminho): + img = Image.open(caminho) + pos_sumare = (-22.955139, -43.248278) + pos_sumare_img = (img.height / 2, img.width / 2) + + dify = pos_sumare_img[0] / pos_sumare[0] + difx = pos_sumare_img[1] / pos_sumare[1] + + posx = pos_sumare[1] - ((vlon - pos_sumare[1]) * 32.5) + valorx = posx * difx + posy = pos_sumare[0] + ((vlat - pos_sumare[0]) * 19.5) + valory = posy * dify + + rgb_im = img.convert("RGB") + r, g, b = rgb_im.getpixel((valorx, valory)) + # print(r, g, b) + df.at[i, "reflect"] = interpolate_value( + (r, g, b), legend_colors, legend_values + ) + else: + arquivo = ( + df1["Dia"].iloc[0][:4] + + "_" + + df1["Dia"].iloc[0][5:7] + + "_" + + df1["Dia"].iloc[0][8:10] + + "_" + + df1["Hora"].iloc[0][:2] + + "_" + + str(int(df1["Hora"].iloc[0][3:5]) + 1).zfill(2) + ) + caminho = ( + "./data/radar_sumare/" + + df1["Dia"].iloc[0][:4] + + "/" + + df1["Dia"].iloc[0][5:7] + + "/" + + df1["Dia"].iloc[0][8:10] + + "/" + + arquivo + + ".png" + ) + if os.path.exists(caminho): + img = Image.open(caminho) + pos_sumare = (-22.955139, -43.248278) + pos_sumare_img = (img.height / 2, img.width / 2 - 1) + + dify = pos_sumare_img[0] / pos_sumare[0] + difx = pos_sumare_img[1] / pos_sumare[1] + + posx = pos_sumare[1] - ((vlon - pos_sumare[1]) * 32.5) + valorx = posx * difx + posy = pos_sumare[0] + ((vlat - pos_sumare[0]) * 19.5) + valory = posy * dify + + rgb_im = img.convert("RGB") + r, g, b = rgb_im.getpixel((valorx, valory)) + # print(r, g, b) + df.at[i, "reflect"] = interpolate_value( + (r, g, b), legend_colors, legend_values + ) + i = i + 1 + # print(df['reflect'].unique()) + df_correlacao = df[df["reflect"].notnull()] + + if station_name in STATION_NAMES_FOR_RJ: + if met: + df_correlacao.loc[df_correlacao.index.values, "Chuva"] = df_correlacao[ + "Chuva" + ].fillna(0) + if df["reflect"].unique().size == 1 or df["reflect"].unique().size == 2: + print("Não possui nenhum registro de reflectividade") + else: + print(stats.spearmanr(df_correlacao["Chuva"], df_correlacao["reflect"])) + print(stats.pearsonr(df_correlacao["Chuva"], df_correlacao["reflect"])) + else: + df_correlacao.loc[df_correlacao.index.values, "15 min"] = df_correlacao[ + "15 min" + ].fillna(0) + if df["reflect"].unique().size == 1 or df["reflect"].unique().size == 2: + print("Não possui nenhum registro de reflectividade") + else: + print( + stats.spearmanr(df_correlacao["15 min"], df_correlacao["reflect"]) + ) + print(stats.pearsonr(df_correlacao["15 min"], df_correlacao["reflect"])) + else: + df_correlacao.loc[df_correlacao.index.values, "CHUVA"] = df_correlacao[ + "CHUVA" + ].fillna(0) + if df["reflect"].unique().size == 1 or df["reflect"].unique().size == 2: + print("Não possui nenhum registro de reflectividade") + else: + print(stats.spearmanr(df_correlacao["CHUVA"], df_correlacao["reflect"])) + print(stats.pearsonr(df_correlacao["CHUVA"], df_correlacao["reflect"])) + + +legend_colors = [ + (197, 0, 197), # Magenta + (227, 6, 5), # Red + (255, 112, 0), # Orange + (195, 230, 0), # Yellow + (4, 85, 4), # Yellow + (19, 122, 19), # Dark Green + (0, 167, 12), # Light Green + (0, 0, 0), # Black +] +legend_values = [50, 45, 40, 35, 30, 25, 20, 0] + +STATION_NAMES_FOR_RJ = ( + "alto_da_boa_vista", + "guaratiba", + "iraja", + "jardim_botanico", + "riocentro", + "santa_cruz", + "sao_cristovao", + "vidigal", + "urca", + "rocinha", + "tijuca", + "santa_teresa", + "copacabana", + "grajau", + "ilha_do_governador", + "penha", + "madureira", + "bangu", + "piedade", + "tanque", + "saude", + "barrinha", + "cidade_de_deus", + "grajau", + "grande_meier", + "anchieta", + "grota_funda", + "campo_grande", + "sepetiba", + "av_brasil_mendanha", + "recreio", + "laranjeiras", + "tijuca_muda", +) + +for station in STATION_NAMES_FOR_RJ: + get_radar_data(station, False) + +# get_radar_data('tijuca_muda',False) diff --git a/src/radar/sumare/crop_image.py b/src/radar/sumare/crop_image.py new file mode 100644 index 00000000..797fe9f1 --- /dev/null +++ b/src/radar/sumare/crop_image.py @@ -0,0 +1,52 @@ +from pathlib import Path + +from PIL import Image + + +def list_files_pathlib(path=Path("."), arq=[]): + for entry in path.iterdir(): + if entry.is_file(): + try: + tst = Image.open(str(entry)) + + width, height = tst.size # Get dimensions + new_width = new_height = 656 + left = (width - new_width) / 2 - 4 + top = (height - new_height) / 2 + 1 + right = (width + new_width) / 2 - 4 + bottom = (height + new_height) / 2 - 1 + + # Crop the center of the image + tst2 = tst.crop((left, top, right, bottom)) + + tst2.save(str(entry)) + print("Cropped file " + str(entry) + " saved") + except Exception: + print("File not Cropped: " + str(entry)) + + elif entry.is_dir(): + list_files_pathlib(entry, arq) + + +# Specify the directory path you want to start from + +arq1 = [] +directory_path = Path("./data/radar_sumare") +list_files_pathlib(directory_path, arq1) + +print(arq1) +# print(glob.glob("./data/radar_sumare/*")) + +""" +tst = Image.open("2024_01_13_16_37.png") + +width, height = tst.size # Get dimensions +new_width = new_height =656 +left = (width - new_width)/2 +top = (height - new_height)/2 +right = (width + new_width)/2 +bottom = (height + new_height)/2 + +# Crop the center of the image +tst2 = tst.crop((left, top, right, bottom)) +tst2""" diff --git a/src/radar/sumare/radar_data.py b/src/radar/sumare/radar_data.py new file mode 100644 index 00000000..c09c5be5 --- /dev/null +++ b/src/radar/sumare/radar_data.py @@ -0,0 +1,134 @@ +import argparse +import math +import os + +import numpy as np +import pandas as pd +from PIL import Image + + +def rgb_distance(c1, c2): + return math.sqrt((c1[0] - c2[0]) ** 2 + (c1[1] - c2[1]) ** 2 + (c1[2] - c2[2]) ** 2) + + +def interpolate_value(rgb, legend_colors, legend_values): + if rgb == (0, 0, 0): + return 0 + # Calcular distâncias entre a cor fornecida e todas as cores da legenda + distances = [rgb_distance(rgb, lc) for lc in legend_colors] + + # Identificar as duas cores mais próximas na legenda + min_idx1 = distances.index(min(distances)) # Índice da cor mais próxima + distances[min_idx1] = float( + "inf" + ) # Excluir a cor mais próxima para achar a segunda + min_idx2 = distances.index(min(distances)) # Índice da segunda cor mais próxima + + # Obter as cores e valores correspondentes + c1, c2 = legend_colors[min_idx1], legend_colors[min_idx2] + v1, v2 = legend_values[min_idx1], legend_values[min_idx2] + + # Calcular o peso de interpolação (t) + dist_c1_c2 = rgb_distance(c1, c2) + dist_c1_rgb = rgb_distance(c1, rgb) + t = dist_c1_rgb / dist_c1_c2 if dist_c1_c2 != 0 else 0 + + # Interpolar o valor + interpolated_value = v1 + t * (v2 - v1) + return interpolated_value + + +def get_radar_data(inicio, fim, frequencia, latitude, longitude): + latitude = float(latitude) + longitude = float(longitude) + + pos_sumare = (-22.955139, -43.248278) + legend_values = [50, 45, 40, 35, 30, 25, 20, 0] + legend_colors = [ + (197, 0, 197), # Magenta + (227, 6, 5), # Vermelho + (255, 112, 0), # Laranja + (195, 230, 0), # Amarelo + (4, 85, 4), # Amarelo + (19, 122, 19), # Verde escuro + (0, 167, 12), # Verde claro + (0, 0, 0), # Vazio + ] + + # Definir datas inicial e final + data_inicial = inicio + " 00:00:00" + data_final = fim + " 23:58:00" + + datas = pd.date_range(start=data_inicial, end=data_final, freq=frequencia) + + # Criar DataFrame com coluna "datahora" + radar_data = pd.DataFrame({"datahora": datas}) + radar_data["reflect"] = np.nan + + count = 0 + while count < len(radar_data): + datetime_str = radar_data.iloc[count]["datahora"].strftime("%Y-%m-%d %H:%M:%S") + + year = datetime_str[0:4] + month = datetime_str[5:7] + day = datetime_str[8:10] + hour = datetime_str[11:13] + minute = datetime_str[14:16] + file = year + "_" + month + "_" + day + "_" + hour + "_" + minute + ".png" + file_path = "./data/radar_sumare/" + year + "/" + month + "/" + day + "/" + file + + if os.path.exists(file_path): + print(file_path) + try: + img = Image.open(file_path) + print(type(img)) + pos_sumare_img = (img.height / 2, img.width / 2) + + dify = pos_sumare_img[0] / pos_sumare[0] + difx = pos_sumare_img[1] / pos_sumare[1] + + posx = pos_sumare[1] - ((longitude - pos_sumare[1]) * 32.5) + valorx = posx * difx + posy = pos_sumare[0] + ((latitude - pos_sumare[0]) * 19.5) + valory = posy * dify + + rgb_im = img.convert("RGB") + r, g, b = rgb_im.getpixel((valorx, valory)) + radar_data.at[count, "reflect"] = interpolate_value( + (r, g, b), legend_colors, legend_values + ) + except Exception as e: + print("Mensagem de erro:", str(e)) # como string + + count += 1 + + return radar_data + + +def parse_arguments(): + parser = argparse.ArgumentParser( + description="Baixa dados meteorológicos de refletividade do Radar Sumaré" + ) + parser.add_argument( + "--inicio", help="Data inicial no formato YYYY-MM-DD", default=None + ) + parser.add_argument("--fim", help="Data final no formato YYYY-MM-DD", default=None) + parser.add_argument( + "--frequencia", help="Escala Temporal a ser demandada", default="2min" + ) + parser.add_argument( + "--latitude", required=True, help="Latitude do ponto solicitado" + ) + parser.add_argument( + "--longitude", required=True, help="Longitude do ponto solicitado" + ) + + return parser.parse_args() + + +if __name__ == "__main__": + args = parse_arguments() + radar_data = get_radar_data( + args.inicio, args.fim, args.frequencia, args.latitude, args.longitude + ) + radar_data.to_parquet("./data/radar_sumare/radar_data.parquet") diff --git a/src/retrieve_ERA5.py b/src/retrieve_ERA5.py deleted file mode 100644 index c5ed58b6..00000000 --- a/src/retrieve_ERA5.py +++ /dev/null @@ -1,175 +0,0 @@ -import sys -from datetime import datetime -import time -import cdsapi -from pathlib import Path -import xarray as xr -import argparse -import sys -from enum import Enum -import globals - -""" - For using the CDS API to download ERA-5 data consult: https://cds.climate.copernicus.eu/api-how-to -""" - -# North -22°, West -44°, South -23°, East -42° -REGION_OF_INTEREST = [-22, -44, -23, -42] - -class Months(Enum): - JANUARY = 1 - FEBRUARY = 2 - MARCH = 3 - APRIL = 4 - MAY = 5 - JUNE = 6 - JULY = 7 - AUGUST = 8 - SEPTEMBER = 9 - OCTOBER = 10 - NOVEMBER = 11 - DECEMBER = 12 - -def get_data(start_year, end_year): - - end_year = min([end_year, datetime.today().year]) - - file = "RJ_" + str(start_year) + "_" + str(end_year) - - file_exist = Path(globals.NWP_DATA_DIR + "ERA5/" + file + ".nc") - - months = range(Months.JANUARY.value, Months.DECEMBER.value+1) - - if file_exist.is_file(): - ds = xr.open_dataset(globals.NWP_DATA_DIR + "ERA5/" + file + ".nc") - else: - c = cdsapi.Client() - years = list(map(str, range(int(start_year), int(end_year) + 1))) - for year in years: - for month in months: - print(f"Downloading ERA5 data at month {month} of year {year}...", end="") - try: - c.retrieve( - "reanalysis-era5-pressure-levels", - { - "product_type": "reanalysis", - "format": "netcdf", - "variable": [ - "geopotential", - "relative_humidity", - "temperature", - "u_component_of_wind", - "v_component_of_wind" - ], - "pressure_level": [ - '200', '700', '1000' - ], - "year": [ - year, - ], - "month": [ - str(month) - ], - "day": [ - "01", - "02", - "03", - "04", - "05", - "06", - "07", - "08", - "09", - "10", - "11", - "12", - "13", - "14", - "15", - "16", - "17", - "18", - "19", - "20", - "21", - "22", - "23", - "24", - "25", - "26", - "27", - "28", - "29", - "30", - "31", - ], - "time": [ - "00:00", - "01:00", - "02:00", - "03:00", - "04:00", - "05:00", - "06:00", - "07:00", - "08:00", - "09:00", - "10:00", - "11:00", - "12:00", - "13:00", - "14:00", - "15:00", - "16:00", - "17:00", - "18:00", - "19:00", - "20:00", - "21:00", - "22:00", - "23:00", - ], - "area": REGION_OF_INTEREST, - }, - globals.NWP_DATA_DIR + "ERA5/montly_data/RJ_" + year + "_" + str(month) + ".nc", - ) - print("Done!") - except Exception as e: - print(f"Unexpected error! {repr(e)}") - sys.exit(2) - - ds = None - for year in years: - for month in months: - if ds is None: - ds = xr.open_dataset(globals.NWP_DATA_DIR + "ERA5/montly_data/RJ_" + year + "_" + str(month) + ".nc") - else: - ds_aux = xr.open_dataset(globals.NWP_DATA_DIR + "ERA5/montly_data/RJ_" + year + "_" + str(month) + ".nc") - ds = ds.merge(ds_aux) - - print(f"Done!", end="") - filename = globals.NWP_DATA_DIR + "ERA5/" + file + ".nc" - print(f"Saving dowloaded data to {filename}") - ds.to_netcdf(filename) - -def main(argv): - parser = argparse.ArgumentParser(description='Retrieve ERA5 data between two given years.') - parser.add_argument('-b', '--start_year', type=int, required=True, help='Start year') - parser.add_argument('-e', '--end_year', type=int, required=True, help='End year') - - args = parser.parse_args(argv[1:]) - - start_year = args.start_year - end_year = args.end_year - - # ERA5 data goes back to the year 1940. - # see https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview - assert start_year >= 1940 - - assert start_year <= end_year - - get_data(start_year, end_year) - -if __name__ == "__main__": - main(sys.argv) - diff --git a/src/retrieve_glm.py b/src/retrieve_glm.py deleted file mode 100644 index 3cf31859..00000000 --- a/src/retrieve_glm.py +++ /dev/null @@ -1,98 +0,0 @@ -import pandas as pd -import sys -import argparse -import globals -import s3fs -import xarray as xr -import os -import tenacity -from botocore.exceptions import ConnectTimeoutError -import concurrent.futures - -# Use the anonymous credentials to access public data -fs = s3fs.S3FileSystem(anon=True) - -# Download all files in parallel, and rename them the same name (without the directory structure) -@tenacity.retry( - retry=tenacity.retry_if_exception_type(ConnectTimeoutError), - wait=tenacity.wait_exponential(), - stop=tenacity.stop_after_attempt(5) -) -def download_file(files): - """ - Downloads GOES-16 netCDF files from an S3 bucket, filters them for events that fall within specified coordinates, - and saves the filtered data to disk as a Parquet file. - - Args: - files (list): A list of strings representing the names of files to be downloaded from an S3 bucket. - """ - - def process_file(file): - print(f"Reading file: {file}") - filename = f"data/goes16/glm_files/{file.split('/')[-1]}" - try: - fs.get(file, filename) - except Exception as e: - print(f"Error processing file {file}: {str(e)}") - - with concurrent.futures.ThreadPoolExecutor(max_workers=5) as executor: - executor.map(process_file, files) - - -def import_data(initial_year, final_year): - """ - Downloads and saves GOES-16 (Geostationary Operational Environmental Satellite) data files from the Amazon S3 bucket for a specified time period. - - This function targets the 'noaa-goes16' S3 bucket, specifically accessing the GLM-L2-LCFA (Geostationary Lightning Mapper - Level 2 Lightning Detection) dataset. - It downloads data for every day between the initial and final years specified, covering all hours of each day. - - The data is organized in a multiband format and follows the structure: ////. - - Args: - initial_year (int): The initial year of the time period for which data is to be downloaded. The data for this year starts from January 1st. - final_year (int): The final year of the time period for which data is to be downloaded. The data for this year includes up to December 31st. - - Returns: - None. The function saves the downloaded files to a specified location (not defined in this docstring). - - Note: - - This function requires a pre-established connection to Amazon S3 and appropriate permissions to access the 'noaa-goes16' bucket. - - It assumes the GOES-16 data is in the correct format and available for the entire range from the initial_year to the final_year. - - Ensure sufficient storage space and network bandwidth as the dataset might be large, especially for longer time periods. - - The function handles data for 24 hours each day, using a 0-23 hour format. - """ - # Get files of GOES-16 data (multiband format) on multiple dates - # format: //// - hours = [f'{h:02d}' for h in range(25)] # Download all 24 hours of data - - start_date = pd.to_datetime(f'{initial_year}-01-01') - end_date = pd.to_datetime(f'{final_year}-12-31') - dates = pd.date_range(start=start_date, end=end_date, freq='D') - - files = [] - for date in dates: - year = str(date.year) - day_of_year = f'{date.dayofyear:03d}' - print(f'noaa-goes16/GLM-L2-LCFA/{year}/{day_of_year}') - for hour in hours: - target = f'noaa-goes16/GLM-L2-LCFA/{year}/{day_of_year}/{hour}' - files.extend(fs.ls(target)) - - download_file(files) - -def main(argv): - parser = argparse.ArgumentParser(description='Downlaod GLM files') - parser.add_argument('-b', '--start', required=True, help='Start year to get data') - parser.add_argument('-e', '--end', required=True, help='End year to get data') - args = parser.parse_args(argv[1:]) - - start_year = args.start - end_year = args.end - - assert (start_year <= end_year) - - import_data(start_year, end_year) - - -if __name__ == "__main__": - main(sys.argv) \ No newline at end of file diff --git a/src/retrieve_goes16_dsif.py b/src/retrieve_goes16_dsif.py deleted file mode 100644 index 3fdecd5e..00000000 --- a/src/retrieve_goes16_dsif.py +++ /dev/null @@ -1,157 +0,0 @@ -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -from goes16_utils import download_CMI # Our own utilities -from goes16_utils import geo2grid, convertExtent2GOESProjection # Our own utilities -from globals import GOES_DATA_DIR -import argparse - -import boto3 -import botocore -from botocore import UNSIGNED # boto3 config -from botocore.config import Config # boto3 config - -from datetime import datetime, timedelta -import logging - -from osgeo import osr # Python bindings for GDAL -from osgeo import gdal # Python bindings for GDAL - -"""Builds a reprojected netCDF file from a full disk netCDF file. - -Args: -in_filename (str): Path to the full disk netCDF file. -out_filename (str): Path to write the reprojected netCDF file. -var (str): Name of the variable to reproject within the input file. -extent (tuple): A tuple of four floats defining the output bounding box in -geographic coordinates (lon_min, lat_max, lon_max, lat_min). - -Returns: -str: The starting time of the data coverage extracted from the metadata -of the input file. - -Raises: -RuntimeError: If there is an error opening the input file or writing -the reprojected file. -""" -def build_projection_from_full_disk(in_filename, out_filename, var, extent): - - # Open the file - img = gdal.Open(f'NETCDF:{in_filename}:' + var) - - # Read the header metadata - metadata = img.GetMetadata() - scale = float(metadata.get(var + '#scale_factor')) - offset = float(metadata.get(var + '#add_offset')) - undef = float(metadata.get(var + '#_FillValue')) - dtime = metadata.get('NC_GLOBAL#time_coverage_start') - - # print(f'scale/offset/undef/dtime: {scale}/{offset}/{undef}/{dtime}') - - # Load the data - ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) - - # Apply the scale and offset - ds = (ds * scale + offset) - - # Read the original file projection and configure the output projection - source_prj = osr.SpatialReference() - source_prj.ImportFromProj4(img.GetProjectionRef()) - - target_prj = osr.SpatialReference() - target_prj.ImportFromProj4("+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs") - - # Reproject the data - GeoT = img.GetGeoTransform() - driver = gdal.GetDriverByName('MEM') - raw = driver.Create('raw', ds.shape[0], ds.shape[1], 1, gdal.GDT_Float32) - raw.SetGeoTransform(GeoT) - raw.GetRasterBand(1).WriteArray(ds) - - # Define the parameters of the output file - options = gdal.WarpOptions(format = 'netCDF', - srcSRS = source_prj, - dstSRS = target_prj, - outputBounds = (extent[0], extent[3], extent[2], extent[1]), - outputBoundsSRS = target_prj, - outputType = gdal.GDT_Float32, - srcNodata = undef, - dstNodata = 'nan', - xRes = 0.02, - yRes = 0.02, - resampleAlg = gdal.GRA_NearestNeighbour) - - # print(options) - - # Write the reprojected file on disk - gdal.Warp(f'{out_filename}', raw, options=options) - - return dtime - -def download_goes16_product(product_name, date_str, save_path="."): - # Convert date string to datetime object - date_obj = datetime.strptime(date_str, "%Y%m%d") - - yyyymmddhh = date_str - year = datetime.strptime(yyyymmddhh, '%Y%m%d').strftime('%Y') - day_of_year = datetime.strptime(yyyymmddhh, '%Y%m%d').strftime('%j') - - satellite = "noaa-goes16" - - # Create an S3 client - s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) - - # Generate the prefix based on the date - prefix = f'{product_name}/{year}/{day_of_year}' - print(f'prefix: {prefix}') - - # List objects in the specified S3 bucket and prefix - try: - response = s3_client.list_objects_v2(Bucket="noaa-goes16", Prefix=prefix, ) - - if 'Contents' not in response: - # There are no files - print(f'No files found for the date: {date_str}, Product: {product_name}') - return -1 - else: - # print(f'Contents: {response.get("Contents", [])}') - # Download each file - for content in response.get("Contents", []): - filename = content["Key"] - - # Find the index (within the key) in which the date information begins, and extract the date part - s_index = filename.find('s') - temp = filename[s_index+1: -1] - underline_index = temp.find('_') - date_string = temp[0: underline_index-3] - - # Parse the date string - parsed_date = datetime.strptime(date_string, '%Y%j%H%M') - - # Format the parsed date as YYYYMMDDHM - formatted_date = parsed_date.strftime('%Y_%m_%d_%H_%M') - - print(f'formatted data: {formatted_date}') - - full_disk_filename = f"{save_path}/{product_name}_{formatted_date}.nc" - - print(f"Downloading {filename} to {full_disk_filename}") - s3_client.download_file("noaa-goes16", filename, full_disk_filename) - - print("Download complete!") - - except botocore.exceptions.NoCredentialsError: - print("Credentials not available. Please configure AWS credentials.") - -if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Download GOES-16 data for a specified product, date, and save path.") - - parser.add_argument("--product_name", type=str, default="ABI-L2-DSIF", help="Specify the product name") - parser.add_argument("--target_date", type=str, default="20220911", help="Specify the target date in YYYYMMDD format") - parser.add_argument("--local_save_path", type=str, default="./data/goes16/goes16_dsif", help="Specify the local path to save the downloaded files") - - args = parser.parse_args() - - download_goes16_product(args.product_name, args.target_date, args.local_save_path) diff --git a/src/retrieve_goes16_prod_for_wsois.py b/src/retrieve_goes16_prod_for_wsois.py deleted file mode 100644 index 1aace929..00000000 --- a/src/retrieve_goes16_prod_for_wsois.py +++ /dev/null @@ -1,165 +0,0 @@ -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import timedelta, date, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -import numpy as np # Scientific computing with Python -from matplotlib import cm # Colormap handling utilities -from goes16_utils import download_PROD # Our function for download -from goes16_utils import reproject # Our function for reproject -from goes16.processing_data import find_pixel_of_coordinate -from goes16.processing_data import open_dataset - -import pandas as pd - -import sys - -import argparse -from globals import INMET_WEATHER_STATION_IDS - -# gdal.PushErrorHandler('CPLQuietErrorHandler') # Ignore GDAL warnings - -#------------------------------------------------------------------------------ -# def store_file(product_name, yyyymmddhhmn, output, img, acum, extent, undef): -# # Reproject the file -# filename_acum = f'{output}/{product_name}_{yyyymmddhhmn}.nc' -# reproject(filename_acum, img, acum, extent, undef) - - -#------------------------------------------------------------------------------ -def download_data_for_a_day(df: pd.DataFrame, yyyymmdd: str, stations_of_interest: dict, product_name: str, variable_name: str): - """ - Downloads TPW (Total Precipitable Water) data for a specific day from GOES-16 satellite, - extracts TPW values for stations of interest, and appends them to a DataFrame. - - Args: - - df (pandas.DataFrame): DataFrame to which TPW values for stations of interest will be appended. - - yyyymmdd (str): Date in 'YYYYMMDD' format specifying the day for which data will be downloaded. - - stations_of_interest (dict): Dictionary containing stations of interest with their IDs as keys - and their corresponding latitude and longitude coordinates as values. - - Returns: - - pandas.DataFrame: Updated DataFrame with appended TPW values for stations of interest. - """ - - # Directory to temporarily store each downloaded full disk file. - temp_dir = "./data/goes16/temp" - - # Initial time and date - yyyy = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%Y') - mm = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%m') - dd = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%d') - - hour_ini = 0 - date_ini = datetime(int(yyyy),int(mm),int(dd),hour_ini,0) - date_end = datetime(int(yyyy),int(mm),int(dd),hour_ini,0) + timedelta(hours=23) - - time_step = date_ini - - #----------------------------------------------------------------------------------------------------------- - # Accumulation loop. Scans all of the files for the given day. - # For each file, gets the TPW values for the locations where - # the stations of interested are located. - while (time_step <= date_end): - # Date structure - yyyymmddhhmn = datetime.strptime(str(time_step), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') - - print(f'-Getting data for {yyyymmddhhmn}...') - - # Download the full disk file from the Amazon cloud. - file_name = download_PROD(yyyymmddhhmn, product_name, temp_dir) - - try: - filename = f'{temp_dir}/{file_name}.nc' - ds = open_dataset(filename) - - if ds is not None: - field, LonCen, LatCen = ds.image(variable_name, lonlat='center') - - for wsoi_id in stations_of_interest: - lon = stations_of_interest[wsoi_id][1] - lat = stations_of_interest[wsoi_id][0] - x, y = find_pixel_of_coordinate(LonCen, LatCen, lon, lat) - value1 = field.data[y,x] - new_row = {'timestamp': yyyymmddhhmn, 'station_id': wsoi_id, variable_name: value1} - df = df.append(new_row, ignore_index=True) - - # try: - # os.remove(filename) # Use os.remove() to delete the file - # except FileNotFoundError: - # print(f"Error: File '{filename}' not found.") - # except PermissionError: - # print(f"Error: Permission denied to remove file '{filename}'.") - # except Exception as e: - # print(f"An error occurred: {e}") - except FileNotFoundError: - print(f"Error: File '{filename}' not found.") - - # Increment 10 minutes - time_step = time_step + timedelta(minutes=10) - return df - -### -# python src/retrieve_goes16_prod_for_wsois.py --date_ini "2024-03-09" --date_end "2024-03-09" --prod ABI-L2-DSIF --var CAPE -# python src/retrieve_goes16_prod_for_wsois.py --date_ini "2024-01-12" --date_end "2024-01-12" --prod ABI-L2-DSIF --var CAPE -# python src/retrieve_goes16_prod_for_wsois.py --date_ini "2024-01-12" --date_end "2024-01-12" --prod ABI-L2-TPWF --var TPW -def main(argv): - # Create an argument parser - parser = argparse.ArgumentParser(description="Retrieve GOES16's data for (user-provided) product, variable, and date range.") - - # Add command line arguments for date_ini and date_end - parser.add_argument("--date_ini", type=str, required=True, help="Start date (format: YYYY-MM-DD)") - parser.add_argument("--date_end", type=str, required=True, help="End date (format: YYYY-MM-DD)") - parser.add_argument("--prod", type=str, required=True, help="GOES16 product name (e.g., 'ABI-L2-TPWF', 'ABI-L2-DSIF')") - parser.add_argument("--var", type=str, required=True, help="Variable name (e.g., CAPE, TPW, ...)") - - args = parser.parse_args() - start_date = args.date_ini - end_date = args.date_end - - product_name = args.prod - variable_name = args.var - - # try: - # if (station_id in globals.ALERTARIO_WEATHER_STATION_IDS or station_id in globals.ALERTARIO_GAUGE_STATION_IDS): - # # This UTC thing is really anonying! - # start_date = pd.to_datetime(args.date_ini, utc=True) - # end_date = pd.to_datetime(args.date_end, utc=True) - # else: - # start_date = pd.to_datetime(args.date_ini) - # end_date = pd.to_datetime(args.date_end) - # except ParserError: - # print(f"Invalid date format: {args.date_ini}, {args.date_end}.") - # parser.print_help() - # sys.exit(2) - - stations_of_interest = dict() - stations_filename = "./data/ws/WeatherStations.csv" - df_stations = pd.read_csv(stations_filename) - for wsoi_id in INMET_WEATHER_STATION_IDS: - row = df_stations[df_stations["STATION_ID"] == wsoi_id].iloc[0] - wsoi_lat_lon = (row["VL_LATITUDE"], row["VL_LONGITUDE"]) - stations_of_interest[row["STATION_ID"]] = wsoi_lat_lon - - # Create an empty DataFrame to store historical product values for each station of interest. - df = pd.DataFrame(columns=['timestamp', 'station_id', variable_name]) - - # Convert start_date and end_date to datetime objects - from datetime import datetime - start_datetime = datetime.strptime(start_date, '%Y-%m-%d') - end_datetime = datetime.strptime(end_date, '%Y-%m-%d') - - # Iterate through the range of user-provided days, - # one day at a time, to retrieve corresponding TPW data. - current_datetime = start_datetime - while current_datetime <= end_datetime: - yyyymmdd = current_datetime.strftime('%Y%m%d') - df = download_data_for_a_day(df, yyyymmdd, stations_of_interest, product_name, variable_name) - # Increment the current date by one day - current_datetime += timedelta(days=1) - - print(f'Shape in the end: {df.shape}') - df.to_parquet(f'tpw_{start_datetime}_to_{end_datetime}.parquet') - -if __name__ == "__main__": - main(sys.argv) diff --git a/src/retrieve_goes16_product.py b/src/retrieve_goes16_product.py deleted file mode 100644 index f12c38d5..00000000 --- a/src/retrieve_goes16_product.py +++ /dev/null @@ -1,85 +0,0 @@ -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -from goes16_utils import download_CMI # Our own utilities -from goes16_utils import geo2grid, convertExtent2GOESProjection # Our own utilities -from globals import GOES_DATA_DIR -import argparse - -import boto3 -import botocore -from botocore import UNSIGNED # boto3 config -from botocore.config import Config # boto3 config - -from datetime import datetime, timedelta - -def download_goes16_product(product_name, date_str, save_path="."): - # Convert date string to datetime object - date_obj = datetime.strptime(date_str, "%Y%m%d") - - yyyymmddhh = date_str - year = datetime.strptime(yyyymmddhh, '%Y%m%d').strftime('%Y') - day_of_year = datetime.strptime(yyyymmddhh, '%Y%m%d').strftime('%j') - - satellite = "noaa-goes16" - - # Create an S3 client - s3_client = boto3.client('s3', config=Config(signature_version=UNSIGNED)) - - # Generate the prefix based on the date - prefix = f'{product_name}/{year}/{day_of_year}' - print(f'prefix: {prefix}') - - # List objects in the specified S3 bucket and prefix - try: - response = s3_client.list_objects_v2(Bucket="noaa-goes16", Prefix=prefix, ) - - if 'Contents' not in response: - # There are no files - print(f'No files found for the date: {date_str}, Product: {product_name}') - return -1 - else: - # print(f'Contents: {response.get("Contents", [])}') - # Download each file - for content in response.get("Contents", []): - key = content["Key"] - print(f'key: {key}') - - # Find the index (within the key) in which the date information begins, and extract the date part - s_index = key.find('s') - temp = key[s_index+1: -1] - underline_index = temp.find('_') - date_string = temp[0: underline_index-3] - - print(f'date: {date_string}') - - # Parse the date string - parsed_date = datetime.strptime(date_string, '%Y%j%H%M') - - # Format the parsed date as YYYYMMDDHM - formatted_date = parsed_date.strftime('%Y_%m_%d_%H_%M') - - print(f'formatted data: {formatted_date}') - - local_path = f"{save_path}/{product_name}_{formatted_date}.nc" - - print(f"Downloading {key} to {local_path}") - s3_client.download_file("noaa-goes16", key, local_path) - - print("Download complete!") - - except botocore.exceptions.NoCredentialsError: - print("Credentials not available. Please configure AWS credentials.") - -if __name__ == "__main__": - parser = argparse.ArgumentParser(description="Download GOES-16 data for a specified product, date, and save path.") - - parser.add_argument("--product_name", type=str, default="ABI-L2-DSIF", help="Specify the product name") - parser.add_argument("--target_date", type=str, default="20220911", help="Specify the target date in YYYYMMDD format") - parser.add_argument("--local_save_path", type=str, default="./data/goes16/goes16_dsif", help="Specify the local path to save the downloaded files") - - args = parser.parse_args() - - download_goes16_product(args.product_name, args.target_date, args.local_save_path) diff --git a/src/retrieve_goes16_rrqpe.py b/src/retrieve_goes16_rrqpe.py deleted file mode 100644 index 6aca72cc..00000000 --- a/src/retrieve_goes16_rrqpe.py +++ /dev/null @@ -1,197 +0,0 @@ -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import timedelta, date, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -from osgeo import gdal # Python bindings for GDAL -import numpy as np # Scientific computing with Python -from matplotlib import cm # Colormap handling utilities -from goes16_utils import download_PROD # Our function for download -from goes16_utils import reproject # Our function for reproject -from goes16.processing_data import find_pixel_of_coordinate -from goes16.processing_data import open_dataset - -#------------------------------------------------------------------------------ -def get_rrqpe_value(sat_data): - - # Read number of cols and rows - ncol = sat_data.RasterXSize - nrow = sat_data.RasterYSize - print(f'ncol, nrow = {ncol}, {nrow}') - - # Load the data - sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) - - # Get geotransform - transform = sat_data.GetGeoTransform() - - # Coordenadas da estação do Forte de Copacabana - lat = -22.98833333 - lon = -43.19055555 - - x = int((lon - transform[0]) / transform[1]) - y = int((transform[3] - lat) / -transform[5]) - - # print(f'Value at ({x},{y}): {sat_array[x,y]}') - - return sat_array[x,y] - - -import sys - -gdal.PushErrorHandler('CPLQuietErrorHandler') # Ignore GDAL warnings - -#------------------------------------------------------------------------------ -def store_file(product_name, yyyymmddhhmn, output, img, acum, extent, undef): - # Reproject the file - filename_acum = f'{output}/{product_name}_{yyyymmddhhmn}.nc' - reproject(filename_acum, img, acum, extent, undef) - - -#------------------------------------------------------------------------------ -def download_data_for_a_day(yyyymmdd): - # Input and output directories - input = "./data/goes16/Samples"; os.makedirs(input, exist_ok=True) - output = "./data/goes16/Output"; os.makedirs(output, exist_ok=True) - - extent = [-44.0, -23.0, -43.0, -22.0] # Min lon, Min lat, Max lon, Max lat - - # Initial time and date - yyyy = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%Y') - mm = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%m') - dd = datetime.strptime(yyyymmdd, '%Y%m%d').strftime('%d') - - hour_ini = 0 - date_ini = datetime(int(yyyy),int(mm),int(dd),hour_ini,0) - date_end = datetime(int(yyyy),int(mm),int(dd),hour_ini,0) + timedelta(hours=23) - - temp = date_ini - - #----------------------------------------------------------------------------------------------------------- - # Accumulation loop - while (temp <= date_end): - # Date structure - yyyymmddhhmn = datetime.strptime(str(temp), '%Y-%m-%d %H:%M:%S').strftime('%Y%m%d%H%M') - - product_name = 'ABI-L2-TPWF' - # product_name = 'ABI-L2-RRQPEF' - - print(f'Getting {product_name} data for {yyyymmddhhmn}...') - - # Download the file - file_name = download_PROD(yyyymmddhhmn, product_name, input) - - #----------------------------------------------------------------------------------------------------------- - # Variable - var = 'TPW' - - # Open the file - img = gdal.Open(f'NETCDF:{input}/{file_name}.nc:' + var) - dqf = gdal.Open(f'NETCDF:{input}/{file_name}.nc:DQF') - - if img is not None: - - ds = open_dataset(f'{input}/{file_name}.nc') - RRQPE, LonCen, LatCen = ds.image(var, lonlat='center') - - print('@@@@@@-RRQPE') - print(RRQPE) - print('@@@@@@') - - print('@@@@@@-LonCen') - print(LonCen) - print('@@@@@@') - - print('@@@@@@-LatCen') - print(LatCen) - print('@@@@@@') - - lat = -22.98833333 - lon = -43.19055555 - x, y = find_pixel_of_coordinate(LonCen, LatCen, lon, lat) - value1 = RRQPE.data[y,x] - - acum = np.zeros((5424,5424)) - - # Read the header metadata - metadata = img.GetMetadata() - scale = float(metadata.get(var + '#scale_factor')) - offset = float(metadata.get(var + '#add_offset')) - undef = float(metadata.get(var + '#_FillValue')) - dtime = metadata.get('NC_GLOBAL#time_coverage_start') - - # Load the data - ds = img.ReadAsArray(0, 0, img.RasterXSize, img.RasterYSize).astype(float) - # ds_dqf = dqf.ReadAsArray(0, 0, dqf.RasterXSize, dqf.RasterYSize).astype(float) - - # Remove undef - ds[ds == undef] = np.nan - - # Apply the scale and offset - ds = (ds * scale + offset) - - # Apply NaN's where the quality flag is greater than 1 - # ds[ds_dqf > 0] = np.nan - - print('@@@@@@-ds.shape') - print(ds[y,x]) - print(ds.shape) - print('@@@@@@') - value2 = ds[y,x]#get_rrqpe_value(img) - print(f'***Values for PoI at {yyyymmddhhmn}: {value1}/{value2}') - - # Sum the instantaneous value in the accumulation - # acum = np.nansum(np.dstack((acum, ds)),2) - - # store_file(product_name, yyyymmddhhmn, output, img, acum, extent, undef) - - # Increment 1 hour - temp = temp + timedelta(hours=1) - - try: - file_path = f'{input}/{file_name}.nc' - print(f'Removing file {file_path}') - os.remove(file_path) # Use os.remove() to delete the file - print(f"File '{file_path}' has been successfully removed.") - except FileNotFoundError: - print(f"Error: File '{file_path}' not found.") - except PermissionError: - print(f"Error: Permission denied to remove file '{file_path}'.") - except Exception as e: - print(f"An error occurred: {e}") - #----------------------------------------------------------------------------------------------------------- - - -def main(argv): - - periods = [ - # ('20191204', '20200531'), - # ('20200901', '20210531'), - # ('20210901', '20220531'), - # ('20220901', '20230531') - # ('20220401', '20220531') - ] - - periods = [ - ('20220331', '20220331') - ] - - for period in periods: - start_date = period[0] - end_date = period[1] - - # Convert start_date and end_date to datetime objects - from datetime import datetime - start_datetime = datetime.strptime(start_date, '%Y%m%d') - end_datetime = datetime.strptime(end_date, '%Y%m%d') - - # Iterate through the range of dates - current_datetime = start_datetime - while current_datetime <= end_datetime: - yyyymmdd = current_datetime.strftime('%Y%m%d') - download_data_for_a_day(yyyymmdd) - # Increment the current date by one day - current_datetime += timedelta(days=1) - -if __name__ == "__main__": - main(sys.argv) diff --git a/src/retrieve_rd.py b/src/retrieve_rd.py deleted file mode 100644 index 4abfe331..00000000 --- a/src/retrieve_rd.py +++ /dev/null @@ -1,142 +0,0 @@ -import requests, os, time -import datetime -from datetime import datetime, timedelta -import argparse -import shutil -import pandas as pd -import urllib.request - -api_key = "aOrV6N5DtQen69uEDlYwbUTo3CTTCcAZ50r7WEW4" - -def extract(datas_str): - - dados_faltantes = [] - sem_dados = [] - - for data in datas: - - print(f"\n{data}") - - date_h = [] - for hora in range(0, 24): - date_h.append(data.replace(hour=hora)) - datas_str = [data.strftime("%Y%m%d%H") for data in date_h] - - print('iniciando requisição') - - true = [] - - for i in datas_str: - - requisicao = requests.get(f'https://api-redemet.decea.mil.br/produtos/radar/03km?api_key={api_key}&radar=pc&anima=3&data={i}') - #time.sleep(0.2) - - print(f"Requisição concluida da hora {i}") - - if "Server Error" not in requisicao.text: - json = requisicao.json() - if "status" in json: - if json["status"] == True: - true.append(json) - - elif "error" in json: - print("OVER_RATE LIMIT") - break - else: - print("Sem status") - else: - print("ERRO DE SERVIDOR") - - radares = [i["data"]["radar"] for i in true] - rad1 = [i[0] for i in radares] - rad2 = [i[1] for i in radares] - rad3 = [i[2] for i in radares] - radares_1 = rad1 + rad2 + rad3 - - - date1 = [i[11]["data"] for i in radares_1] - date_t = [x for x in date1 if x is not None] - date_true = [datetime.strptime(i, '%Y-%m-%d %H:%M:%S') for i in date_t] - date_days = [i.strftime('%Y%m%d%H') for i in date_true] - date_days = list(set(date_days)) - hora_sem_retorno = list(set(datas_str) - set(date_days)) - - if len(hora_sem_retorno) == 24: - - sem_dados.append(list(i for i in hora_sem_retorno)) - print("Atenção: DATA SEM DADOS!") - time.sleep(0.2) - - elif len(hora_sem_retorno) < 24 and len(hora_sem_retorno) > 0: - - dados_faltantes.append(list(i for i in hora_sem_retorno)) - print(f"Atenção: data com horas faltantes. ({len(hora_sem_retorno)})") - - elif len(hora_sem_retorno) == 0: - print("Data com todos os dados") - - pc = [i[11]["path"] for i in radares_1] - path_pc = list(set(pc)) - path_pc = [i for i in path_pc if type(i) is str] - - - for i in path_pc: - filename = i.split("/")[-1] - response = requests.get(i) - with open("..\\data\\nova_base\\img\\"+filename.split(".")[0].replace(":","")+".png", 'wb') as f: - f.write(response.content) - - print("\nDados Baixados\n") - -def parameter_parser(): - description = 'Script to perform ETL on PICODOCOUTO data. Format: DD/MM/YYYY' - - parser = argparse.ArgumentParser(description=description) - - parser.add_argument('-b',"--dt_begin", required=True) - - parser.add_argument('-e', "--dt_end", required=True) - - return parser.parse_args() - -args = parameter_parser() - -db = args.dt_begin[:2] -mb = args.dt_begin[3:5] -yb = args.dt_begin[6:10] - -de = args.dt_end[:2] -me = args.dt_end[3:5] -ye = args.dt_end[6:10] - -print(db,mb,yb) - -data_inicial = datetime(int(yb), int(mb), int(db)) -data_final = datetime(int(ye), int(me), int(de)) - -datas = [] -data_atual = data_inicial -while data_atual <= data_final: - datas.append(data_atual) - data_atual += timedelta(days=1) - -extract(datas) - -dir_path = "..\\data\\nova_base\\img" - -for filename in os.listdir(dir_path): - if filename.endswith(".png"): - datetime_str = filename.split("--")[0] - datetime_obj = datetime.strptime(datetime_str, "%Y-%m-%d") - year_dir = os.path.join(dir_path, datetime_obj.strftime("%Y")) - if not os.path.exists(year_dir): - os.mkdir(year_dir) - month_dir = os.path.join(year_dir, datetime_obj.strftime("%m")) - if not os.path.exists(month_dir): - os.mkdir(month_dir) - day_dir = os.path.join(month_dir, datetime_obj.strftime("%d")) - if not os.path.exists(day_dir): - os.mkdir(day_dir) - src_path = os.path.join(dir_path, filename) - dst_path = os.path.join(day_dir, filename) - shutil.move(src_path, dst_path) \ No newline at end of file diff --git a/src/retrieve_ws_cor.py b/src/retrieve_ws_cor.py deleted file mode 100644 index e966922f..00000000 --- a/src/retrieve_ws_cor.py +++ /dev/null @@ -1,163 +0,0 @@ -import pandas as pd -import numpy as np -import sys, getopt, os, re -import datetime - -STATION_NAMES_FOR_RJ = ('alto_da_boa_vista', - 'guaratiba', - 'iraja', - 'jardim_botanico', - 'riocentro', - 'santa_cruz', - 'sao_cristovao', - 'vidigal') - -def corrige_txt(station_name, years, months): - for year in years: - for month in months: - file = "../data/RAW_data/COR/meteorologica/" + station_name + "_" + year + month + "_Met.txt" - if os.path.exists(file): - fin = open(file, "rt") - if not os.path.exists("../data/RAW_data/COR/meteorologica/aux_"+ station_name): - os.mkdir("../data/RAW_data/COR/meteorologica/aux_"+ station_name) - fout = open("../data/RAW_data/COR/meteorologica/aux_" + station_name + "/" + station_name + "_" + year + month + "_Met2.txt", "wt") - count = 0 - for line in fin: - count += 1 - if station_name == 'guaratiba': - fout.write(re.sub('\s+', ' ', line.replace(':40 ', ':00 nHBV'))) - else: - fout.write(re.sub('\s+', ' ', line.replace(':00 ', ':00 nHBV'))) - fout.write('\n') - if count == 6: - fout.write('01/' + month + '/'+ year + ' 00:00:00 nHBV ND ND ND ND ND ND') - fin.close() - fout.close() - else: - pass - -def import_data(station_name, years, months, arg_end): - df = pd.DataFrame() - - for year in years: - check = 0 - for month in months: - texto = '../data/RAW_data/COR/meteorologica/aux_' + station_name + '/' + station_name + '_' + year + month + '_Met2.txt' - if os.path.exists(texto): - df = pd.read_csv(texto, sep=' ', skiprows=[0, 1, 2, 3, 4, 5], header=None) - if len(df.columns) == 10: - df.columns = ['Dia', 'Hora', 'HBV', 'Chuva', 'DirVento','VelVento', 'Temperatura', 'Pressao', 'Umidade', 'teste'] - del df["teste"] - else: - df.columns = ['Dia', 'Hora', 'HBV', 'Chuva', 'DirVento','VelVento', 'Temperatura', 'Pressao', 'Umidade'] - df['Chuva'] = df['Chuva'][~df['Chuva'].isin(['-', 'ND'])].astype(float) - df['Umidade'] = df['Umidade'][df['Umidade'] != 'ND'].astype(float) - df['Temperatura'] = df['Temperatura'][df['Temperatura'] != 'ND'].astype(float) - df['DirVento'] = df['DirVento'][~df['DirVento'].isin(['-', 'ND'])].astype(float) - df['VelVento'] = df['VelVento'][df['VelVento'] != 'ND'].astype(float) - df['Pressao'] = df['Pressao'][df['Pressao'] != 'ND'].astype(float) - df['Dia'] = pd.to_datetime(df['Dia'], format='%d/%m/%Y') - ano_aux = year - mes_aux = month - print(year + '/' + month) - check = 1 - break - else: - pass - if check == 1: - break - - ano1 = list(map(str,range(int(ano_aux),arg_end))) - mes1 = list(range(int(mes_aux),13)) - mes1 = [str(i).rjust(2, '0') for i in mes1] - - for year in ano1: - for month in mes1: - texto = '../data/RAW_data/COR/meteorologica/aux_' + station_name + '/' + station_name + '_' + year + month + '_Met2.txt' - if os.path.exists(texto): - data2 = pd.read_csv(texto, sep=' ', skiprows=[0, 1, 2, 3, 4, 5], header=None, on_bad_lines='skip') - if len(data2.columns) == 10: - data2.columns = ['Dia', 'Hora', 'HBV', 'Chuva', 'DirVento','VelVento', 'Temperatura', 'Pressao', 'Umidade', 'teste'] - del data2["teste"] - else: - data2.columns = ['Dia', 'Hora', 'HBV', 'Chuva', 'DirVento','VelVento', 'Temperatura', 'Pressao', 'Umidade'] - data2['Chuva'] = data2['Chuva'][~data2['Chuva'].isin(['-', 'ND'])].astype(float) - data2['Umidade'] = data2['Umidade'][data2['Umidade'] != 'ND'].astype(float) - data2['Temperatura'] = data2['Temperatura'][~data2['Temperatura'].isin(['-', 'ND'])].astype(float) - data2['DirVento'] = data2['DirVento'][~data2['DirVento'].isin(['-', 'ND'])].astype(float) - data2['VelVento'] = data2['VelVento'][data2['VelVento'] != 'ND'].astype(float) - data2['Pressao'] = data2['Pressao'][data2['Pressao'] != 'ND'].astype(float) - data2['Dia'] = pd.to_datetime(data2['Dia'], format='%d/%m/%Y') - saida = pd.concat([df, data2]) - df = saida - del saida - else: - pass - if year == ano_aux: - mes1 = list(range(1,13)) - mes1 = [str(i).rjust(2, '0') for i in mes1] - df = df.replace('ND', np.NaN) - df = df.replace('-', np.NaN) - df = df[df['Hora'].str[2:6] == ':00:'] - df['Hora'] = np.where(df['HBV'] == 'HBV', df['Hora'].str[0:2].astype(int) - 1, df['Hora'].str[0:2].astype(int)) - df['Hora'] = np.where(df['Hora'] == -1, 23, df['Hora']) - df['Hora'] = df['Hora'].astype(str).str.zfill(2) + ':00:00' - - df['estacao'] = station_name - df.to_csv('../data/landing/' + station_name + '.csv') - data_aux = df - del df, data2 - return data_aux - - -def import_data(station_name, initial_year, final_year): - years = list(map(str,range(initial_year, final_year))) - months = list(range(1,13)) - months = [str(i).rjust(2, '0') for i in months] - - if station_name == "all": - station_names = STATION_NAMES_FOR_RJ - else: - station_names = [station_name] - - for station_name in station_names: - corrige_txt(station_name, years, months) - data = import_data(station_name, years, months, final_year) - del data - -def main(argv): - station_name = "" - default_initial_year = 1997 - - today = datetime.date.today() - default_final_year = today.year - - arg_help = "{0} -s -b -e ".format(argv[0]) - - try: - opts, args = getopt.getopt(argv[1:], "hs:a:b:e:", ["help", "station=", "begin=", "end="]) - except: - print(arg_help) - sys.exit(2) - - for opt, arg in opts: - if opt in ("-h", "--help"): - print(arg_help) # print the help message - sys.exit(2) - elif opt in ("-s", "--station"): - station_name = arg - if not ((station_name == "all") or (station_name in STATION_NAMES_FOR_RJ)): - print(arg_help) # print the help message - sys.exit(2) - elif opt in ("-b", "--begin"): - default_initial_year = arg - elif opt in ("-e", "--end"): - default_final_year = arg - - import_data(station_name, default_initial_year, default_final_year) - - -if __name__ == "__main__": - main(sys.argv) - - diff --git a/src/retrieve_ws_inmet.py b/src/retrieve_ws_inmet.py deleted file mode 100644 index 17612f9b..00000000 --- a/src/retrieve_ws_inmet.py +++ /dev/null @@ -1,85 +0,0 @@ -import pandas as pd -import sys -from datetime import datetime -from util import is_posintstring -import globals - -def retrieve_from_station(station_id, beginning_year, end_year, api_token): - - current_date = datetime.now() - current_year = current_date.year - end_year = min(end_year, current_year) - - years = list(range(beginning_year, end_year + 1)) - df_inmet_stations = pd.read_json(globals.INMET_API_BASE_URL + '/estacoes/T') - station_row = df_inmet_stations[df_inmet_stations['CD_ESTACAO'] == station_id] - df_observations_for_all_years = None - print(f"Downloading observations from weather station {station_id}...") - for year in years: - print(f"Downloading observations for year {year}...") - - if year == end_year: - datetime_str = str(end_year) + '-12-31' - last_date_of_the_end_year = datetime.strptime(datetime_str, '%Y-%m-%d') - end_date = min(last_date_of_the_end_year, current_date) - end_date_str = end_date.strftime("%Y-%m-%d") - query_str = globals.INMET_API_BASE_URL + '/token/estacao/' + str(year) + '-01-01/' + end_date_str + '/' + station_id + "/" + api_token - else: - query_str = globals.INMET_API_BASE_URL + '/token/estacao/' + str(year) + '-01-01/' + str(year) + '-12-31/' + station_id + "/" + api_token - - print(f"Query to be sent to server: {query_str}") - - df_observations_for_a_year = pd.read_json(query_str) - if df_observations_for_all_years is None: - temp = [df_observations_for_a_year] - else: - temp = [df_observations_for_all_years, df_observations_for_a_year] - df_observations_for_all_years = pd.concat(temp) - filename = globals.WS_INMET_DATA_DIR + station_row['CD_ESTACAO'].iloc[0] + '.parquet' - print(f"Done! Saving dowloaded content to '{filename}'.") - df_observations_for_all_years.to_parquet(filename) - -def retrieve_data(station_id, initial_year, final_year, api_token): - if station_id == "all": - df_inmet_stations = pd.read_json(globals.INMET_API_BASE_URL + '/estacoes/T') - station_row = df_inmet_stations[df_inmet_stations['CD_ESTACAO'].isin(globals.INMET_WEATHER_STATION_IDS)] - for j in list(range(0, len(station_row))): - station_id = station_row['CD_ESTACAO'].iloc[j] - retrieve_from_station(station_id, initial_year, final_year, api_token) - else: - retrieve_from_station(station_id, initial_year, final_year, api_token) - -import argparse - -def main(argv): - station_id = "" - - parser = argparse.ArgumentParser(prog=argv[0], - usage='{0} -s -b -e -t '.format(argv[0]), - description="""This script provides a simple interface for retrieving observations - made by a user-provided weather station from the INMET archive.""") - parser.add_argument("-t", "--api_token", required=True, help="INMET API token", metavar='') - parser.add_argument("-s", "--ws_id", required=True, help="Weather station ID", metavar='') - parser.add_argument("-b", "--begin_year", type=int, required=True, help="Start year", metavar='') - parser.add_argument("-e", "--end_year", type=int, required=True, help="End year", metavar='') - - args = parser.parse_args(argv[1:]) - - api_token = args.api_token - station_id = args.station_id - start_year = args.begin - end_year = args.end - - if not (station_id in globals.INMET_WEATHER_STATION_IDS): - parser.error(f'Invalid station ID: {station_id}') - - assert (api_token is not None) and (api_token != '') - assert (station_id is not None) and (station_id != '') - assert (start_year <= end_year) - - retrieve_data(station_id, start_year, end_year, api_token) - -if __name__ == "__main__": - main(sys.argv) - - diff --git a/src/sounding/README.md b/src/sounding/README.md new file mode 100644 index 00000000..23bd6d85 --- /dev/null +++ b/src/sounding/README.md @@ -0,0 +1,90 @@ +# AtmoSeer – Radiosonde Retrieval & Atmospheric Instability Indices + +Este conjunto de scripts permite: + +✔️ Baixar radiossondas de **duas fontes oficiais** +✔️ Padronizar os dados em formato Parquet +✔️ Calcular índices de instabilidade com MetPy +✔️ Incorporar metadados das estações +✔️ Servir como base para previsão, análise e visualização + +--- + +## Funcionalidades + +### **1. Coleta de radiossondas – Wyoming Upper Air Archive (Siphon)** +- Baixa sondagens atmosféricas dos horários **00Z e 12Z** +- Usa a biblioteca **Siphon / WyomingUpperAir** +- Retorna perfil vertical completo (pressão, vento, temperatura, etc.) + +### **2. Cálculo de índices de instabilidade – MetPy** +Gera índices clássicos de tempo severo: + +- CAPE +- CIN +- Lifted Index +- K Index +- Total Totals +- Showalter Index + +### **3. Coleta de radiossondas – NOAA IGRA v2 (igra library)** +- Baixa arquivo completo da estação em formato ZIP +- Converte para DataFrame +- Incorpora **metadados da estação**: + - latitude + - longitude + - altitude + - número de níveis + - tipo de sensor +--- + +# 📁 Estrutura do Projeto + +1️⃣ Instale as dependências + +pip install pandas siphon metpy igra pyarrow requests + + +🎈 1. Baixar dados radiossondas – Wyoming (Siphon) +Script: +src/sounding/retrieve_uow.py + +Usando datas: +python -m src.sounding.retrieve_uow -s SBGL --start_date 2021-01-01 --end_date 2021-01-31 + +Usando anos inteiros: +python -m src.sounding.retrieve_uow -s SBGL -b 2020 -e 2023 + +Saída: +data/as/SBGL_2021-01-01_2021-01-31.parquet.gzip + +Visualizar tabela: +df = pd.read_parquet("data/as/SBGL_2021-01-01_2021-01-31.parquet.gzip", engine="pyarrow") +print(df.head()) + +🌩️ 2. Gerar índices de instabilidade – MetPy +Script: +src/sounding/gen_indices.py +Exemplo: +python -m src.sounding.gen_indices \ + --input_file data/as/SBGL_2021-01-01_2021-01-31.parquet.gzip \ + --output_file data/as/SBGL_indices.parquet.gzip + +Visualizar tabela: +df = pd.read_parquet("data/as/SBGL_2021-01-01_2021-01-31_indices.parquet.gzip") +print(df.head()) + +🎈 3. Baixar radiossondas – IGRA v2 (NOAA) +Script: +src/sounding/retrieve_igra.py + +Exemplo: +python -m src.sounding.retrieve_igra -s BRM00083746 --start_date 2018-01-01 --end_date 2020-12-31 + +Saída: +data/as/BRM00083746_2018-01-01_2020-12-31_igra.parquet.gzip + +Visualizar tabela: +df_indices = pd.read_parquet("data/as/BRM00083746_2018-01-01_2018-01-31_igra.parquet.gzip") +print(df_indices.head()) + diff --git a/src/sounding/gen_indices.py b/src/sounding/gen_indices.py new file mode 100644 index 00000000..be2e1b10 --- /dev/null +++ b/src/sounding/gen_indices.py @@ -0,0 +1,96 @@ +#Esse código lê os perfis das radiossondas (arquivo Parquet) e calcula índices de instabilidade atmosférica (CAPE, CIN, Lifted Index, K-Index, etc.) com a biblioteca MetPy, salvando os resultados em outro arquivo Parquet. + +import pandas as pd +from metpy.units import units # Adiciona unidades físicas (°C, hPa etc.) +import metpy.calc as mpcalc # Funções meteorológicas prontas (CAPE, CIN, índices de instabilidade) +import argparse # Para criar interface de linha de comando (CLI) + +def compute_indices(df_launch): # Função que calcula índices de instabilidade de UM lançamento + # Remove linhas duplicadas pela coluna 'pressure' + df_launch_cleaned = df_launch.drop_duplicates(subset='pressure', ignore_index=True) + + # Remove linhas com valores nulos em temperatura, ponto de orvalho ou pressão + df_launch_cleaned = df_launch_cleaned.dropna(subset=('temperature', 'dewpoint', 'pressure'), how='any').reset_index(drop=True) + + # Ordena os dados por pressão (do nível mais alto de pressão → superfície, até menor pressão → altitudes maiores) + df_launch_cleaned = df_launch_cleaned.sort_values('pressure', ascending=False) + + # Converte as colunas em listas e atribui as unidades corretas + pressure_values = df_launch_cleaned['pressure'].to_list() * units.hPa + temperature_values = df_launch_cleaned['temperature'].to_list() * units.degC + dewpoint_values = df_launch_cleaned['dewpoint'].to_list() * units.degC + + # Calcula o perfil da parcela de ar que sobe na atmosfera (parcel profile) + parcel_profile = mpcalc.parcel_profile(pressure_values, + temperature_values[0], # temp da superfície + dewpoint_values[0] # ponto de orvalho da superfície + ).to('degC') + + indices = dict() # Dicionário para armazenar os índices calculados + + # CAPE (energia de convecção) e CIN (energia de inibição) + CAPE = mpcalc.cape_cin(pressure_values, temperature_values, dewpoint_values, parcel_profile) + indices['cape'] = CAPE[0].magnitude # CAPE em J/kg + indices['cin'] = CAPE[1].magnitude # CIN em J/kg + + # Lifted Index (LI): diferença de temp em 500 hPa (instabilidade) + lift = mpcalc.lifted_index(pressure_values, temperature_values, parcel_profile) + indices['lift'] = lift[0].magnitude + + # K-Index: usado para prever tempestades + k = mpcalc.k_index(pressure_values, temperature_values, dewpoint_values) + indices['k'] = k.magnitude + + # Total Totals Index: combina temp e ponto de orvalho → instabilidade + total_totals = mpcalc.total_totals_index(pressure_values, temperature_values, dewpoint_values) + indices['total_totals'] = total_totals.magnitude + + # Showalter Index: outro índice clássico de instabilidade (comparação em 500 hPa) + showalter = mpcalc.showalter_index(pressure_values, temperature_values, dewpoint_values) + indices['showalter'] = showalter.magnitude[0] + + return indices # Retorna todos os índices em formato de dicionário + +def main(): + # Define argumentos de linha de comando + parser = argparse.ArgumentParser(description='Generate instability indices from sounding measurements.') + parser.add_argument('--input_file', help='Parquet file name containing the sounding measurements', required=True) + parser.add_argument('--output_file', help='Parquet file name where the indices are going to be saved', required=True) + args = parser.parse_args() + + # Lê o arquivo Parquet com todos os lançamentos da radiossonda + df_s = pd.read_parquet(args.input_file) + + # Cria DataFrame vazio com as colunas dos índices + df_indices = pd.DataFrame(columns=['time', 'cape', 'cin', 'lift', 'k', 'total_totals', 'showalter']) + + # Loop em cada lançamento único (cada horário/time diferente) + for launch_timestamp in pd.to_datetime(df_s.time).unique(): + print(f"Generating instability indices for launch made at {launch_timestamp}...", end="") + try: + # Filtra só os dados desse lançamento + df_launch = df_s[pd.to_datetime(df_s['time']) == launch_timestamp] + # Calcula os índices com a função compute_indices + indices_dict = compute_indices(df_launch) + # Adiciona a data/hora do lançamento ao dicionário + indices_dict['time'] = launch_timestamp + # Concatena no DataFrame de saída + df_indices = pd.concat([df_indices, pd.DataFrame.from_records([indices_dict])]) + print("Success!") # Log se deu certo + except ValueError as e: # Erros de valor (dados ruins) + print(f'Error processing measurements made by launch at {launch_timestamp}') + print(f'{repr(e)}') + except IndexError as e: # Erros de índice (dados faltando) + print(f'Error processing measurements made by launch at {launch_timestamp}') + print(f'{repr(e)}') + except KeyError as e: # Erros de chave (colunas faltando) + print(f'Error processing measurements made by launch at {launch_timestamp}') + print(f'{repr(e)}') + + # Salva os índices em um novo arquivo Parquet comprimido + df_indices.to_parquet(args.output_file, compression='gzip', index=False) + + print("Done!") # Finaliza o programa + +if __name__ == "__main__": + main() # Ponto de entrada do programa: só roda se for executado pelo terminal diff --git a/src/sounding/retrieve_igra.py b/src/sounding/retrieve_igra.py new file mode 100644 index 00000000..7730a2bf --- /dev/null +++ b/src/sounding/retrieve_igra.py @@ -0,0 +1,145 @@ +# -*- coding: utf-8 -*- +""" +retrieve_data_igra.py +---------------------- + +This script provides a simple interface for retrieving upper air sounding +observations from the NOAA/NCDC Integrated Global Radiosonde Archive (IGRA v2). + +It uses the `igra` Python library to: + - Download radiosonde data for a given station ID (e.g., BRM00083746), + - Read and convert them into a pandas DataFrame, + - Filter by a specified time range, + - Compute dew point temperature, + - Save data to a compressed Parquet file. + +For an overview of weather balloons, see: +https://www.weather.gov/media/key/Weather-Balloons.pdf +""" + +import os +import sys +import argparse +import pandas as pd +from datetime import datetime, timedelta +import time +import requests +import igra +from src.config import globals +import urllib.request + + + +def get_data_for_period(station_id, start_date, end_date): + """ + Downloads and processes IGRA radiosonde data for the specified station and date range. + """ + + print(f"Downloading IGRA v2 data for {station_id} between {start_date.date()} and {end_date.date()}...") + + # Garante que a pasta de saída exista + os.makedirs(globals.AS_DATA_DIR, exist_ok=True) + + try: + # Faz download do arquivo ZIP da estação + igra.download.station(station_id, globals.AS_DATA_DIR) + zip_path = os.path.join(globals.AS_DATA_DIR, f"{station_id}-data.txt.zip") + + # Lê os dados baixados + print("Reading downloaded file...") + data, station_info = igra.read.igra(station_id, zip_path) + df = data.to_dataframe().reset_index() + station_df = station_info.to_dataframe().reset_index() + + # Filtra pelo intervalo de datas informado + df["date"] = pd.to_datetime(df["date"]) + station_df["date"] = pd.to_datetime(station_df["date"]) + + df_filtered = df[(df["date"] >= start_date) & (df["date"] <= end_date)] + + df_final = df_filtered.merge(station_df, on="date", how="left") + + print(f"Loaded {df_final.shape[0]} records (with metadata) from IGRA for {station_id}.") + return df_final + + except requests.HTTPError as e: + print(f"HTTP error while downloading IGRA data: {e}") + time.sleep(10) + print("Retrying...") + return get_data_for_period(station_id, start_date, end_date) + + except Exception as e: + print(f"Unexpected error: {repr(e)}") + sys.exit(2) + + +def get_data(station_id, start_date, end_date): + """ + Orchestrates download, processing, and saving of IGRA radiosonde data. + """ + + # Executa o download e a leitura dos dados + df_igra = get_data_for_period(station_id, start_date, end_date) + + # Renomeia colunas para compatibilidade + df_igra = df_igra.rename(columns={ + "pres": "pressure", + "temp": "temperature", + "dpd": "dewpoint_depression", + "date": "time" + }) + + # Converte temperatura para Celsius + if df_igra["temperature"].max() > 200: + df_igra["temperature"] = df_igra["temperature"] - 273.15 + + # Calcula o ponto de orvalho: T - DPD + df_igra["dewpoint"] = df_igra["temperature"] - df_igra["dewpoint_depression"] + + # Define o nome do arquivo de saída + filename = os.path.join( + globals.AS_DATA_DIR, + f"{station_id}_{start_date.date()}_{end_date.date()}_igra.parquet.gzip" + ) + + # Salva os dados em formato Parquet comprimido (.gzip) + print(f"Saving {df_igra.shape[0]} observations to {filename}...", end=" ") + df_igra.to_parquet(filename, compression='gzip', index=False) + print("Done!") + + return df_igra + + +def main(argv): + """ + Entry point for command-line execution. + """ + # Configura os argumentos que podem ser passados pelo terminal + parser = argparse.ArgumentParser( + description="""This script retrieves upper-air sounding data from NOAA's IGRA v2 archive + for a specified station ID and time period.""", + prog=sys.argv[0] + ) + parser.add_argument('-s', '--station_id', help='IGRA station ID (e.g., BRM00083746)', required=True) + parser.add_argument('--start_date', help='Start date (YYYY-MM-DD)', required=True) + parser.add_argument('--end_date', help='End date (YYYY-MM-DD)', required=True) + args = parser.parse_args() + + # Converte as strings das datas em datetime + try: + start_date = datetime.strptime(args.start_date, "%Y-%m-%d") + end_date = datetime.strptime(args.end_date, "%Y-%m-%d") + except ValueError: + print("Invalid date format. Use YYYY-MM-DD.") + sys.exit(2) + + assert end_date >= start_date, "End date must be greater than or equal to start date." + + # Executa todo o processo completo + get_data(args.station_id, start_date, end_date) + print("✅ Process completed successfully!") + + +if __name__ == "__main__": + # Executa a função principal quando o script é chamado diretamente + main(sys.argv) diff --git a/src/sounding/retrieve_uow.py b/src/sounding/retrieve_uow.py new file mode 100644 index 00000000..fd6d0bd4 --- /dev/null +++ b/src/sounding/retrieve_uow.py @@ -0,0 +1,111 @@ +#Esse script baixa automaticamente dados de radiossondas (00Z e 12Z) da Universidade de Wyoming para um período e uma estação escolhidos, e salva tudo em um arquivo único no formato Parquet. + + +# -*- coding: utf-8 -*- # Declara a codificação do arquivo (útil p/ acentos). +""" +This script provides a simple interface for retrieving upper air sounding +observations from the University of Wyoming Upper Air Archive. + +It uses the WyomingUpperAir class in the siphon library. In particular, +the request_data method of the WyomingUpperAir class takes two arguments: + - the date of the sounding launch as a datetime object, + - the atmospheric sounding station ID (as a string). + +For an overview of weather balloons, see: +https://www.weather.gov/media/key/Weather-Balloons.pdf +""" # Docstring: descreve o propósito do script e a fonte dos dados. + +import pandas as pd # Importa pandas para manipular DataFrames e salvar Parquet. +import sys # Acessa argv e permite sair com sys.exit. +import argparse # Faz o parsing dos argumentos de linha de comando (CLI). +from datetime import datetime, timedelta # Trabalha com datas e somas de tempo (horas, dias). +from siphon.simplewebservice.wyoming import WyomingUpperAir # Cliente Siphon para baixar as sondagens. +import time # Fornece sleep para pausar entre tentativas. +import requests # Para capturar exceções HTTP (usado dentro do Siphon). +from src.config import globals # Configurações do projeto (ex.: AS_DATA_DIR). + +def get_data_for_period(station_id, first_day, last_day): # Função que coleta dados 00Z e 12Z entre duas datas. + #00Z → 00:00 UTC + #12Z → 12:00 UTC + unsuccesfull_launchs = 0 # Contador de lançamentos sem sucesso (sem dados ou erro). + next_day = first_day # Cursor do dia atual a ser processado. + df_all_launchs = pd.DataFrame() # Acumulador de todas as sondagens do período (DataFrame). + + while next_day <= last_day: # Loop dia a dia do intervalo [first_day, last_day]. + for hour_of_day in [0, 12]: # Para cada dia, tenta nos horários padrão: 00Z e 12Z. + + current_launch_time = next_day + timedelta(hours=hour_of_day) # Timestamp da sondagem desejada. + + try: # Bloco de tentativa para baixar a sondagem desse timestamp. + print(f"Downloading {current_launch_time}...", end="") # Log sem quebrar linha. + df_launch = WyomingUpperAir.request_data(current_launch_time, station_id) + # Chama a API do Wyoming via Siphon; retorna DataFrame da sondagem. + print(f" OK ({len(df_launch)} obs).") # Loga sucesso + número de níveis/linhas retornados. + df_all_launchs = pd.concat([df_all_launchs, df_launch]) # Concatena no acumulador (custo alto se muitas iterações). + except IndexError as e: # Sem dados para esse horário (comum em alguns dias/estações). + print(f"IndexError: {repr(e)}") # Loga o erro específico. + unsuccesfull_launchs += 1 # Incrementa contador de falhas. + except ValueError as e: # Erros de valor/formato vindos do provedor/biblioteca. + print(f"ValueError: {str(e)}") # Loga mensagem do erro. + unsuccesfull_launchs += 1 # Conta como falha. + except requests.HTTPError as e: # Falha HTTP (servidor ocupado/instável, timeouts etc.). + print(f"HTTPError: {repr(e)}") # Loga a exceção HTTP. + print(f"Server busy at {current_launch_time}, retrying in 10s...") + # Informa que vai tentar novamente. + time.sleep(10) # Dorme 10 segundos antes de prosseguir. + continue # Volta para o próximo passo do for (não incrementa o dia aqui). + except Exception as e: # Qualquer outra exceção não prevista. + print(f"Unexpected error: {repr(e)}") # Loga erro inesperado. + sys.exit(2) # Encerra o programa com código de saída 2. + + next_day += timedelta(days=1) # Após tentar 00Z e 12Z, avança para o dia seguinte. + + return df_all_launchs, unsuccesfull_launchs # Retorna o DataFrame acumulado e o total de falhas no período. + +def get_data(station_id, start_date, end_date): # Função “orquestradora”: baixa e salva do período informado. + print(f"Downloading observations from {station_id} between {start_date.date()} and {end_date.date()}...") + # Log inicial informando estação e intervalo de datas. + df_all_launchs, unsuccesfull_launchs = get_data_for_period(station_id, start_date, end_date) + # Chama a função que percorre dia a dia e horários 00/12Z. + + print(f"Done! {unsuccesfull_launchs} failed launches.") # Log final de falhas (sem dados/erros). + filename = globals.AS_DATA_DIR + f"{station_id}_{start_date.date()}_{end_date.date()}.parquet.gzip" + # Monta o caminho do arquivo de saída (usa diretório de config). + df_all_launchs.to_parquet(filename, compression='gzip', index=False) + # Salva o DataFrame completo em Parquet comprimido (precisa pyarrow/fastparquet). + print(f"Saved {df_all_launchs.shape[0]} observations to {filename}") + # Loga quantas linhas (níveis de sondagem) foram salvas. + +def main(argv): # Função principal para rodar como CLI. + parser = argparse.ArgumentParser( # Cria o parser de argumentos do terminal. + description="Retrieve upper air sounding observations from University of Wyoming Upper Air Archive.", + prog=sys.argv[0] # Nome do programa (usado em mensagens de help). + ) + parser.add_argument('-s', '--station_id', help='Atmospheric sounding station ID', default='SBGL') + # Estação upper-air (default SBGL = Galeão/Rio). + parser.add_argument('-b', '--start_year', help='Start year', required=False) + # Alternativa 1: informar anos (início). + parser.add_argument('-e', '--end_year', help='End year', required=False) + # Alternativa 1: informar anos (fim). + parser.add_argument('--start_date', help='Start date (YYYY-MM-DD)', required=False) + # Alternativa 2: informar datas completas (início). + parser.add_argument('--end_date', help='End date (YYYY-MM-DD)', required=False) + # Alternativa 2: informar datas completas (fim). + args = parser.parse_args() # Faz o parsing real dos argumentos passados no terminal. + + # Decide se usa ano inteiro ou intervalo de datas + if args.start_date and args.end_date: # Se o usuário passou datas (string no formato YYYY-MM-DD)... + start_date = datetime.strptime(args.start_date, "%Y-%m-%d") # Converte início p/ datetime. + end_date = datetime.strptime(args.end_date, "%Y-%m-%d") # Converte fim p/ datetime. + elif args.start_year and args.end_year: # Caso contrário, se passou anos... + start_date = datetime(int(args.start_year), 1, 1) # Usa 1º de jan do ano inicial. + end_date = datetime(int(args.end_year), 12, 31) # Usa 31 de dez do ano final. + else: # Se não passou nenhuma combinação válida... + print("Error: provide either --start_date and --end_date OR --start_year and --end_year") + # Mensagem de uso incorreto. + sys.exit(1) # Sai com erro. + + get_data(args.station_id, start_date, end_date) # Dispara a coleta + salvamento com os parâmetros decididos. + +if __name__ == "__main__": # Garante execução deste bloco só quando o arquivo é rodado direto. + main(sys.argv) # Chama a função principal, repassando argumentos da linha de comando. diff --git a/src/sounding/sounding_gen_indices.py b/src/sounding/sounding_gen_indices.py new file mode 100644 index 00000000..a3fb350e --- /dev/null +++ b/src/sounding/sounding_gen_indices.py @@ -0,0 +1,103 @@ +import argparse + +import metpy.calc as mpcalc +import pandas as pd +from metpy.units import units + + +def compute_indices(df_launch): + df_launch_cleaned = df_launch.drop_duplicates(subset="pressure", ignore_index=True) + + df_launch_cleaned = df_launch_cleaned.dropna( + subset=("temperature", "dewpoint", "pressure"), how="any" + ).reset_index(drop=True) + + df_launch_cleaned = df_launch_cleaned.sort_values("pressure", ascending=False) + + pressure_values = df_launch_cleaned["pressure"].to_list() * units.hPa + temperature_values = df_launch_cleaned["temperature"].to_list() * units.degC + dewpoint_values = df_launch_cleaned["dewpoint"].to_list() * units.degC + + parcel_profile = mpcalc.parcel_profile( + pressure_values, temperature_values[0], dewpoint_values[0] + ).to("degC") + + indices = dict() + + CAPE = mpcalc.cape_cin( + pressure_values, temperature_values, dewpoint_values, parcel_profile + ) # , which_lfc = "top", which_el = "top") + indices["cape"] = CAPE[0].magnitude + indices["cin"] = CAPE[1].magnitude + + lift = mpcalc.lifted_index(pressure_values, temperature_values, parcel_profile) + indices["lift"] = lift[0].magnitude + + k = mpcalc.k_index(pressure_values, temperature_values, dewpoint_values) + indices["k"] = k.magnitude + + total_totals = mpcalc.total_totals_index( + pressure_values, temperature_values, dewpoint_values + ) + indices["total_totals"] = total_totals.magnitude + + showalter = mpcalc.showalter_index( + pressure_values, temperature_values, dewpoint_values + ) + indices["showalter"] = showalter.magnitude[0] + + return indices + + +def main(): + parser = argparse.ArgumentParser( + description="Generate instability indices from sounding measurements." + ) + parser.add_argument( + "--input_file", + help="Parquet file name containing the sounding measurements", + required=True, + ) + parser.add_argument( + "--output_file", + help="Parquet file name where the indices are going to be saved", + required=True, + ) + args = parser.parse_args() + + df_s = pd.read_parquet(args.input_file) + + df_indices = pd.DataFrame( + columns=["time", "cape", "cin", "lift", "k", "total_totals", "showalter"] + ) + + for launch_timestamp in pd.to_datetime(df_s.time).unique(): + print( + f"Generating instability indices for launch made at {launch_timestamp}...", + end="", + ) + try: + df_launch = df_s[pd.to_datetime(df_s["time"]) == launch_timestamp] + indices_dict = compute_indices(df_launch) + indices_dict["time"] = launch_timestamp + df_indices = pd.concat( + [df_indices, pd.DataFrame.from_records([indices_dict])] + ) + print("Success!") + except ValueError as e: + print(f"Error processing measurements made by launch at {launch_timestamp}") + print(f"{repr(e)}") + except IndexError as e: + print(f"Error processing measurements made by launch at {launch_timestamp}") + print(f"{repr(e)}") + except KeyError as e: + print(f"Error processing measurements made by launch at {launch_timestamp}") + print(f"{repr(e)}") + + df_indices.to_parquet(args.output_file, compression="gzip", index=False) + + print("Done!") + + +if __name__ == "__main__": + main() diff --git a/src/retrieve_as.py b/src/sounding/sounding_retrieve_data.py similarity index 58% rename from src/retrieve_as.py rename to src/sounding/sounding_retrieve_data.py index 4d6bb7e3..32bb46f5 100644 --- a/src/retrieve_as.py +++ b/src/sounding/sounding_retrieve_data.py @@ -1,52 +1,57 @@ -''' - This script provides a simple interface for retrieving upper air sounding - observations from the University of Wyoming Upper Air Archive. - - Its code uses the WyomingUpperAir class in the siphon library. In particular, - the request_data method of the WyomingUpperAir class takes two arguments: - - the date of the sounding launch as a datetime object, - - the atmospheric sounding station ID (as a string). - - For an overview of weather baloons, see https://www.weather.gov/media/key/Weather-Balloons.pdf -''' -import pandas as pd -import sys +""" +This script provides a simple interface for retrieving upper air sounding +observations from the University of Wyoming Upper Air Archive. + +Its code uses the WyomingUpperAir class in the siphon library. In particular, +the request_data method of the WyomingUpperAir class takes two arguments: + - the date of the sounding launch as a datetime object, + - the atmospheric sounding station ID (as a string). + +For an overview of weather baloons, see https://www.weather.gov/media/key/Weather-Balloons.pdf +""" + import argparse -from datetime import datetime, timedelta -from siphon.simplewebservice.wyoming import WyomingUpperAir -import util as util +import sys import time +from datetime import datetime, timedelta + +import pandas as pd import requests -import globals +from siphon.simplewebservice.wyoming import WyomingUpperAir + +import src.utils.util as util +from config import globals + def get_data_for_year_and_hour_of_day(station_id, first_day, last_day, hour_of_day): unsuccesfull_launchs = 0 next_day = first_day - nb_launchs = 0 df_all_launchs = pd.DataFrame() while next_day <= last_day: - current_launch_time = next_day + timedelta(hours=hour_of_day) try: - print(f"Downloading observations made on {current_launch_time}...", end = "") + print(f"Downloading observations made on {current_launch_time}...", end="") df_launch = WyomingUpperAir.request_data(current_launch_time, station_id) print(f"Success! ({len(df_launch)} observations).") df_all_launchs = pd.concat(([df_all_launchs, df_launch])) except IndexError as e: - print(f'{repr(e)}') + print(f"{repr(e)}") unsuccesfull_launchs += 1 except ValueError as e: - print(f'{str(e)}') + print(f"{str(e)}") unsuccesfull_launchs += 1 except requests.HTTPError as e: - print(f'{repr(e)}') - print(f"Server seems to be busy while trying to download data for {current_launch_time}. Going to sleep for a while...", end="") + print(f"{repr(e)}") + print( + f"Server seems to be busy while trying to download data for {current_launch_time}. Going to sleep for a while...", + end="", + ) time.sleep(10) # Sleep for a moment print("Back to work!") continue except Exception as e: - print(f'Unexpected error! {repr(e)}') + print(f"Unexpected error! {repr(e)}") sys.exit(2) # Now, go to next day next_day = next_day + timedelta(days=1) @@ -57,44 +62,65 @@ def get_data_for_year_and_hour_of_day(station_id, first_day, last_day, hour_of_d return df_all_launchs, unsuccesfull_launchs + def get_data(station_id, start_year, end_year): print(f"Downloading observations from sounding station {station_id}...") df_all_launchs = pd.DataFrame() unsuccesfull_launchs = 0 end_year = min([end_year, datetime.now().year]) - assert(end_year >= start_year) + assert end_year >= start_year - for year in range(start_year, end_year+1): + for year in range(start_year, end_year + 1): first_day, last_day = util.get_first_and_last_days_of_year(year) - + # Download data at 00Z - df_launchs, nb_unsuccessful_launchs_of_year = get_data_for_year_and_hour_of_day(station_id, first_day, last_day, 0) + df_launchs, nb_unsuccessful_launchs_of_year = get_data_for_year_and_hour_of_day( + station_id, first_day, last_day, 0 + ) df_all_launchs = pd.concat(([df_all_launchs, df_launchs])) unsuccesfull_launchs += nb_unsuccessful_launchs_of_year # Download data at 12Z - df_launchs, nb_unsuccessful_launchs_of_year = get_data_for_year_and_hour_of_day(station_id, first_day, last_day, 12) + df_launchs, nb_unsuccessful_launchs_of_year = get_data_for_year_and_hour_of_day( + station_id, first_day, last_day, 12 + ) df_all_launchs = pd.concat(([df_all_launchs, df_launchs])) unsuccesfull_launchs += nb_unsuccessful_launchs_of_year - print(f"Done! There were {unsuccesfull_launchs} unsuccessful launchs in the specified period.") - filename = globals.AS_DATA_DIR + station_id + '_'+ str(start_year) + '_' + str(end_year) + '.parquet.gzip' - print(f"Saving data on {df_all_launchs.shape[0]} observations to file {filename}.", end=" ") - df_all_launchs.to_parquet(filename, compression='gzip', index = False) + print( + f"Done! There were {unsuccesfull_launchs} unsuccessful launchs in the specified period." + ) + filename = ( + globals.AS_DATA_DIR + + station_id + + "_" + + str(start_year) + + "_" + + str(end_year) + + ".parquet.gzip" + ) + print( + f"Saving data on {df_all_launchs.shape[0]} observations to file {filename}.", + end=" ", + ) + df_all_launchs.to_parquet(filename, compression="gzip", index=False) print("Done!") -def main(argv): - sounding_station_id = 'SBGL' +def main(argv): + sounding_station_id = "SBGL" parser = argparse.ArgumentParser( description="""This script provides a simple interface for retrieving upper air sounding observations made by a user-provided station from the University of Wyoming Upper Air Archive.""", - prog=sys.argv[0]) - parser.add_argument('-s', '--station_id', help='Atmospheric sounding station ID', default='SBGL') - parser.add_argument('-b', '--start_year', help='Start year', required=True) - parser.add_argument('-e', '--end_year', help='End year', required=True) + prog=sys.argv[0], + ) + parser.add_argument( + "-s", "--station_id", help="Atmospheric sounding station ID", default="SBGL" + ) + parser.add_argument("-b", "--start_year", help="Start year", required=True) + parser.add_argument("-e", "--end_year", help="End year", required=True) args = parser.parse_args() sounding_station_id = args.station_id @@ -105,10 +131,11 @@ def main(argv): print("Invalid date format. Use -h or --help for more information.") sys.exit(2) - assert (sounding_station_id is not None) and (sounding_station_id != '') - assert (start_year <= end_year) + assert (sounding_station_id is not None) and (sounding_station_id != "") + assert start_year <= end_year get_data(sounding_station_id, start_year, end_year) + if __name__ == "__main__": main(sys.argv) diff --git a/src/spatiotemporal_builder/AlertarioCoords.py b/src/spatiotemporal_builder/AlertarioCoords.py new file mode 100644 index 00000000..2e1f433c --- /dev/null +++ b/src/spatiotemporal_builder/AlertarioCoords.py @@ -0,0 +1,33 @@ +from pathlib import Path + +import pandas as pd +import pandera as pa + + +class AlertarioCoordsSchema(pa.DataFrameModel): + estacao_desc: str + latitude: float = pa.Field(ge=-90, le=90) + longitude: float = pa.Field(ge=-180, le=180) + + +class AlertarioCoordsSchemaLatLongStr(AlertarioCoordsSchema): + latitude: str + longitude: str + + +def get_alertario_coords(): + alertario_coords_path = Path(__file__).parent / "alertario_stations.parquet" + + alertario_coords = pd.read_parquet(alertario_coords_path) + alertario_coords = alertario_coords[["estacao_desc", "latitude", "longitude"]] + AlertarioCoordsSchema.validate(alertario_coords) + + alertario_coords["latitude"] = alertario_coords["latitude"].apply(lambda x: str(x)) + alertario_coords["longitude"] = alertario_coords["longitude"].apply( + lambda x: str(x) + ) + alertario_coords["estacao_desc"] = alertario_coords["estacao_desc"].str.strip() + + AlertarioCoordsSchemaLatLongStr.validate(alertario_coords) + + return alertario_coords diff --git a/src/spatiotemporal_builder/AlertarioKeys.py b/src/spatiotemporal_builder/AlertarioKeys.py new file mode 100644 index 00000000..15e4aba9 --- /dev/null +++ b/src/spatiotemporal_builder/AlertarioKeys.py @@ -0,0 +1,138 @@ +import json +from pathlib import Path + +import pandas as pd +from tqdm import tqdm + +from .AlertarioCoords import AlertarioCoordsSchemaLatLongStr +from .AlertarioParser import AlertarioParser, AlertarioSchema +from .Logger import logger + + +class AlertarioKeySchema(AlertarioSchema, AlertarioCoordsSchemaLatLongStr): + pass + + +log = logger.get_logger(__name__) + + +class AlertarioKeys: + def __init__( + self, alertario_parser: AlertarioParser, alertario_coords: pd.DataFrame + ) -> None: + self.alertario_keys_path = Path(__file__).parent / "alertario_keys" + if not self.alertario_keys_path.exists(): + self.alertario_keys_path.mkdir() + self.alertario_describe_path = self.alertario_keys_path / "describe" + if not self.alertario_describe_path.exists(): + self.alertario_describe_path.mkdir() + self.alertario_parser = alertario_parser + self.alertario_coords = alertario_coords + + def _serialize_describe(self, df: pd.DataFrame, describe_path: Path): + describe = df.describe() + estacao_Desc = df["estacao_desc"].iloc[0] + lattiude = df["latitude"].iloc[0] + longitude = df["longitude"].iloc[0] + filename = f"{estacao_Desc}_{lattiude}_{longitude}.json" + describe.to_json(describe_path / filename) + + def _write_key(self, df: pd.DataFrame): + row = df.iloc[0] + assert isinstance(row["latitude"], str), f"{type(row['latitude'])}" + assert isinstance(row["longitude"], str), f"{type(row['longitude'])}" + key = f"{row['latitude']}_{row['longitude']}" + df.to_parquet(self.alertario_keys_path / f"{key}.parquet") + + def load_key(self, key: str) -> pd.DataFrame: + return pd.read_parquet(f"{self.alertario_keys_path}/{key}.parquet") + + def _merge_coords_by_estacao_desc( + self, df: pd.DataFrame, estacao_desc: str + ) -> pd.DataFrame: + station = self.alertario_coords[ + self.alertario_coords["estacao_desc"] == estacao_desc + ] + lat = station["latitude"].values[0] + lon = station["longitude"].values[0] + df["estacao_desc"] = estacao_desc + df["latitude"] = lat + df["longitude"] = lon + AlertarioKeySchema.validate(df) + return df + + def build_keys(self, use_cache: bool = True) -> None: + total_files = len(list(self.alertario_keys_path.glob("*.parquet"))) + if use_cache and total_files > 0: + log.warning( + f"Using cached keys, {total_files} files found. To clear cache delete the {self.alertario_keys_path} folder" + ) + return + + minimum_date = pd.Timestamp.max + maximum_date = pd.Timestamp.min + stations = self.alertario_parser.list_rain_gauge_stations() + log.info(f"Processing {len(stations)} files to build keys") + region_of_interest = self.alertario_parser.get_region_of_interest() + for station in tqdm(stations): + data = self.alertario_parser.process_station(station) + data = self._merge_coords_by_estacao_desc(data, station) + + lat = float(data["latitude"].iloc[0]) + lon = float(data["longitude"].iloc[0]) + if not ( + lat <= region_of_interest["north"] + and lat >= region_of_interest["south"] + and lon <= region_of_interest["east"] + and lon >= region_of_interest["west"] + ): + log.error( + f""" + Station {station} is not in the region of interest: + Station lat: {lat} + Station lon: {lon} + Region of interest: {region_of_interest} + """ + ) + exit(1) + + if data["datetime"].min() < minimum_date: + minimum_date = data["datetime"].min() + if data["datetime"].max() > maximum_date: + maximum_date = data["datetime"].max() + + self._write_key(data) + + self._serialize_describe(data, self.alertario_describe_path) + + minimum_maximum_dates_path = ( + self.alertario_keys_path / "minimum_maximum_dates_alertario.json" + ) + with open(minimum_maximum_dates_path, "w") as f: + json.dump( + { + "minimum_date": minimum_date.isoformat(), + "maximum_date": maximum_date.isoformat(), + }, + f, + indent=4, + ) + + log.success( + f""" + Alertario keys built successfully: + Keys path: {self.alertario_keys_path} + Describe path: {self.alertario_describe_path} + Minimum date: {minimum_date} + Maximum date: {maximum_date} + Minimum and maximum path: {minimum_maximum_dates_path} + """ + ) + + +if __name__ == "__main__": + # python -m src.spatiotemporal_builder.AlertarioKeys + from .AlertarioCoords import get_alertario_coords + + alertario_keys = AlertarioKeys(AlertarioParser(), get_alertario_coords()) + alertario_keys.build_keys() diff --git a/src/spatiotemporal_builder/AlertarioParser.py b/src/spatiotemporal_builder/AlertarioParser.py new file mode 100644 index 00000000..d087894e --- /dev/null +++ b/src/spatiotemporal_builder/AlertarioParser.py @@ -0,0 +1,125 @@ +import re +from pathlib import Path + +import pandas as pd +import pandera as pa +import xarray as xr +from sklearn.impute import KNNImputer + +from .Logger import logger + +log = logger.get_logger(__name__) + + +class AlertarioSchema(pa.DataFrameModel): + datetime: pd.Timestamp + m15: float = pa.Field(nullable=False, ge=0) + h01: float = pa.Field(nullable=False, ge=0) + + +class AlertarioParser: + rain_gauge_path = Path(__file__).parent / "alertario-from-source" + + def get_region_of_interest(self) -> dict: + ds = xr.open_dataset( + "./data/reanalysis/ERA5-single-levels/monthly_data/RJ_2018_1.nc" + ) + lats = ds.latitude.values + lons = ds.longitude.values + region_of_interest = { + "north": lats.max(), + "south": lats.min(), + "east": lons.max(), + "west": lons.min(), + } + return region_of_interest + + def _impute_missing_values(self, df: pd.DataFrame, column: str) -> pd.DataFrame: + total_values = df.shape[0] + missing_values = df[column].isna().sum() + percentage_missing = (missing_values / total_values) * 100 + + if percentage_missing == 0: + return df + + if percentage_missing > 10: + log.error( + f"Percentage of missing values for {column} in the region of interest: {percentage_missing:.2f}% ({missing_values}/{total_values}) greater than 10% - exiting" + ) + exit(1) + elif percentage_missing > 5: + log.warning( + f"Missing values for {column}: {percentage_missing:.2f}% ({missing_values}/{total_values})" + ) + + imputer = KNNImputer(n_neighbors=2) + df[column] = imputer.fit_transform(df[[column]]) + assert ( + df[column].isna().sum() == 0 + ), "Missing values after imputation should be zero" + return df + + def _get_df(self, file_path: Path) -> pd.DataFrame: + df = pd.read_csv( + file_path, + sep=r"\s{2,}", + engine="python", + skiprows=5, + names=["Dia", "Hora", "HBV", "m15", "h01", "h04", "h24", "h96"], + ) + df["datetime"] = pd.to_datetime( + df["Dia"] + " " + df["Hora"], format="%d/%m/%Y %H:%M:%S" + ) + + df["m15"] = pd.to_numeric(df["m15"], errors="coerce") + df["h01"] = pd.to_numeric(df["h01"], errors="coerce") + df = df.drop(columns=["Dia", "Hora", "HBV", "h04", "h24", "h96"]) + return df + + def process_station(self, station: str): + station_dfs = [] + months = pd.date_range( + pd.Timestamp("2013-01-01"), pd.Timestamp("2024-10-01"), freq="MS" + ) + for month in months: + current_year = month.year + current_month = month.month + try: + file_name = f"{station}_{current_year:04d}{current_month:02d}_Plv.txt" + file_path = self.rain_gauge_path / file_name + if not file_path.exists(): + raise FileNotFoundError(f"File {file_path} not found") + df = self._get_df(file_path) + station_dfs.append(df) + except Exception as e: + print( + f"Error processing station {station} at {current_year}-{current_month}: {e}" + ) + raise e + assert len(station_dfs) == len(months) + df = pd.concat(station_dfs).sort_values(by="datetime").reset_index(drop=True) + df = self._impute_missing_values(df, AlertarioSchema.m15) + df = self._impute_missing_values(df, AlertarioSchema.h01) + AlertarioSchema.validate(df) + return df + + def list_rain_gauge_stations(self) -> list[str]: + unique_names = set() + pattern = re.compile(r"^(.*?)_\d{6}_Plv\.txt$") + for file in self.rain_gauge_path.iterdir(): + filename = file.name + match = pattern.match(filename) + if not match: + raise ValueError(f"Filename {filename} does not match the pattern") + unique_names.add(match.group(1)) + return sorted(unique_names) + + +if __name__ == "__main__": + # python -m src.spatiotemporal_builder.AlertarioParser + alertario_parser = AlertarioParser() + for station in alertario_parser.list_rain_gauge_stations(): + print(f"station: {station}") + data = alertario_parser.process_station(station) + print(data) + break diff --git a/src/spatiotemporal_builder/AlertarioSquare.py b/src/spatiotemporal_builder/AlertarioSquare.py new file mode 100644 index 00000000..12407ead --- /dev/null +++ b/src/spatiotemporal_builder/AlertarioSquare.py @@ -0,0 +1,156 @@ +from datetime import timedelta +from pathlib import Path + +import numpy as np +import pandas as pd +import xarray as xr + +from .AlertarioKeys import AlertarioKeys +from .ERA5Square import ERA5Square +from .Logger import logger +from .square import Square + +log = logger.get_logger(__name__) + + +class AlertarioSquare(ERA5Square): + def __init__(self, alertario_keys: AlertarioKeys) -> None: + self.alertario_keys = alertario_keys + + def get_keys_in_square( + self, square: Square, stations_alertario: set, verbose: bool = False + ) -> list[str]: + keys = [ + x.stem + for x in Path(self.alertario_keys.alertario_keys_path).glob("*.parquet") + ] + alertario_keys = [] + for key in keys: + key_lat, key_lon = map(float, key.split("_")) + + if ( + verbose + and not ( + key_lat < square.bottom_left[0] or key_lat > square.top_left[0] + ) + and not (key_lon < square.top_left[1] or key_lon > square.top_right[1]) + ): + log.success( + f""" + Lat and Lon Square: + {square.top_left[0]}{square.top_left[1]} - {square.top_right[0]}{square.top_right[1]} + | {key_lat} {key_lon} | + {square.bottom_left[0]}{square.bottom_left[1]} - {square.bottom_right[0]}{square.bottom_right[1]} + """ + ) + + if key_lat < square.bottom_left[0] or key_lat > square.top_left[0]: + continue + if key_lon < square.top_left[1] or key_lon > square.top_right[1]: + continue + + alertario_keys.append(key) + + if len(alertario_keys) > 0: + stations_alertario.update(alertario_keys) + + return alertario_keys + + def get_precipitation_in_square( + self, + square: Square, + alertario_keys: list[str], + timestamp: pd.Timestamp, + ds_time: xr.Dataset, + ) -> float: + if len(alertario_keys) == 0: + return super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + + precipitations_15_min_aggregated: list[float] = [] + for key in alertario_keys: + df_alertario = self.alertario_keys.load_key(key) + + time_upper_bound = timestamp + time_lower_bound = timestamp - timedelta(minutes=45) + + df_alertario_filtered = df_alertario[ + (df_alertario.datetime >= time_lower_bound) + & (df_alertario.datetime <= time_upper_bound) + ] + + m15 = df_alertario_filtered["m15"] + h01 = df_alertario[df_alertario.datetime == time_upper_bound]["h01"] + + if m15.size < 4 or m15.isnull().any(): + # Please see WebSirenesSquare:get_precipitation_in_square for more information + m15_era5 = super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + m15 = np.array([m15.sum(), m15_era5]).max() + + max_between_m15_and_h01 = np.array( + [m15.sum().item(), h01.sum().item()] + ).max() + precipitations_15_min_aggregated.append(max_between_m15_and_h01.item()) + + return max(precipitations_15_min_aggregated) + + +if __name__ == "__main__": + # python -m src.spatiotemporal_builder.AlertarioSquare + # https://g1.globo.com/rj/rio-de-janeiro/noticia/2022/10/31/rio-entra-em-estagio-de-mobilizacao-por-previsao-de-chuva.ghtml + from .AlertarioCoords import get_alertario_coords + from .AlertarioParser import AlertarioParser + from .square import get_square + + alertario_square = AlertarioSquare( + AlertarioKeys(AlertarioParser(), get_alertario_coords()) + ) + timestamp = pd.Timestamp("2022-10-31T18:00:00") + year = timestamp.year + month = timestamp.month + ds = xr.open_dataset( + f"./data/reanalysis/ERA5-single-levels/monthly_data/RJ_{year}_{month}.nc" + ) + print("xr.Dataset:") + print(ds) + + ds = ds.sel(valid_time=timestamp) + lats = ds.latitude.values + lons = ds.longitude.values + print(f"Grid: {lats.shape[0]}x{lons.shape[0]}") + lat = lats[4] + lon = lons[7] + + square = get_square(lat, lon, sorted(lats), sorted(lons)) + print( + f""" + square: + top_left={square.top_left} + bottom_left={square.bottom_left} + bottom_right={square.bottom_right} + top_right={square.top_right} + {square.top_left} --- {square.top_right} + | {" " * 48} | + {square.bottom_left} --- {square.bottom_right} + """ + ) + + keys = alertario_square.get_keys_in_square(square, set()) + print(f"keys: {keys}") + + precipitation = alertario_square.get_precipitation_in_square( + square, keys, timestamp, ds + ) + print(f"precipitation: {precipitation}") + + print( + f""" + Precipitation in square: + {square.top_left} --- {square.top_right} + | {" " * 20} {precipitation:.2f} mm {" " * 20} | + {square.bottom_left} --- {square.bottom_right} + """ + ) diff --git a/src/spatiotemporal_builder/ERA5Square.py b/src/spatiotemporal_builder/ERA5Square.py new file mode 100644 index 00000000..aad6b6de --- /dev/null +++ b/src/spatiotemporal_builder/ERA5Square.py @@ -0,0 +1,430 @@ +from typing import Optional + +import numpy as np +import numpy.typing as npt +import xarray as xr +from pydantic import BaseModel + +from .get_neighbors import get_bottom_neighbor, get_right_neighbor, get_upper_neighbor +from .Logger import logger + +log = logger.get_logger(__name__) + + +class Square(BaseModel): + top_left: tuple[float, float] + bottom_left: tuple[float, float] + bottom_right: tuple[float, float] + top_right: tuple[float, float] + + +class ERA5Square: + def _find_nearest_non_null( + self, + ds_time: xr.Dataset, + lat: float, + lon: float, + data_var: str, + max_radius=1.0, + step=0.1, + ) -> float: + # This function is useful for ERA5Land where we don't have ocean data + log.warning(f"Finding nearest non-null value called for lat={lat}, lon={lon}") + radius = 0.0 + while radius <= max_radius: + ds_lat_lon = ds_time.sel(latitude=lat, longitude=lon, method="nearest") + value = ds_lat_lon[data_var].values + if not np.isnan(value): + return float(value) + lat_range = np.arange(lat - radius, lat + radius, step) + lon_range = np.arange(lon - radius, lon + radius, step) + for new_lat in lat_range: + for new_lon in lon_range: + ds_lat_lon = ds_time.sel( + latitude=new_lat, longitude=new_lon, method="nearest" + ) + value = ds_lat_lon[data_var].values + if not np.isnan(value): + return float(value) + radius += step + log.warning( + f"Could not find a non-null value for lat={lat}, lon={lon}, returning median of the ds_time to avoid bias" + ) + median_ds_time = ds_time[data_var].median().item() + if np.isnan(median_ds_time): + log.error("median_ds_time is NaN") + exit(1) + return median_ds_time + + def get_relative_humidity_in_square(self, square: Square, ds_time: xr.Dataset): + # all these functions violate the dry principle, but I decided to repeat them to leave the code "open to change" + corners = ["top_left", "bottom_left", "bottom_right", "top_right"] + coords = [ + square.top_left, + square.bottom_left, + square.bottom_right, + square.top_right, + ] + corner_data = { + corner: ds_time.sel(latitude=lat, longitude=lon) + for corner, (lat, lon) in zip(corners, coords) + } + + pressure_levels_length = len([1000, 700, 200]) + assert ( + corner_data["top_left"]["r"].size == pressure_levels_length + ), f"top_left['r'].size: {corner_data['top_left']['r'].size}" + + results = [] + for corner in corner_data: + value = corner_data[corner]["r"].values + if np.isnan(value).any(): + lat, lon = dict(square)[corner] + value = self._find_nearest_non_null(ds_time, lat, lon, "r") + results.append(value) + + assert len(results) == len(corners), f"len(results)={len(results)} != 4" + assert ( + len(results[0]) == pressure_levels_length + ), f"len(results[0])={len(results[0])} != 3" + corner_sums = [np.sum(values) for values in results] + best_corner = corners[np.argmax(corner_sums)] + return corner_data[best_corner]["r"].values + + def get_temperature_in_square( + self, square: Square, ds_time: xr.Dataset, verbose=False + ): + # all these functions violate the dry principle, but I decided to repeat them to leave the code "open to change" + corners = ["top_left", "bottom_left", "bottom_right", "top_right"] + coords = [ + square.top_left, + square.bottom_left, + square.bottom_right, + square.top_right, + ] + corner_data = { + corner: ds_time.sel(latitude=lat, longitude=lon) + for corner, (lat, lon) in zip(corners, coords) + } + + pressure_levels_length = len([1000, 700, 200]) + assert ( + corner_data["top_left"]["t"].size == pressure_levels_length + ), f"top_left['t'].size: {corner_data['top_left']['t'].size}" + + results = [] + for corner in corner_data: + value = corner_data[corner]["t"].values + if np.isnan(value).any(): + lat, lon = dict(square)[corner] + value = self._find_nearest_non_null(ds_time, lat, lon, "t") + results.append(value) + assert len(results) == len(corners), f"len(results)={len(results)} != 4" + assert ( + len(results[0]) == pressure_levels_length + ), f"len(results[0])={len(results[0])} != 3" + + corner_sums = [np.sum(values) for values in results] + best_corner = corners[np.argmax(corner_sums)] + + if verbose: + log.debug( + f""" + corner_data: + Top left lat lon: ({corner_data["top_left"].latitude.values}, {corner_data["top_left"].longitude.values}) + Top left temperature: {corner_data["top_left"]["t"].values} + Top left pressure levels: {corner_data["top_left"]["pressure_level"].values} + + Bottom left lat lon: ({corner_data["bottom_left"].latitude.values}, {corner_data["bottom_left"].longitude.values}) + Bottom left temperature: {corner_data["bottom_left"]["t"].values} + Bottom left pressure levels: {corner_data["bottom_left"]["pressure_level"].values} + + Bottom right lat lon: ({corner_data["bottom_right"].latitude.values}, {corner_data["bottom_right"].longitude.values}) + Bottom right temperature: {corner_data["bottom_right"]["t"].values} + Bottom right pressure levels: {corner_data["bottom_right"]["pressure_level"].values} + + Top right lat lon: ({corner_data["top_right"].latitude.values}, {corner_data["top_right"].longitude.values}) + Top right temperature: {corner_data["top_right"]["t"].values} + Top right pressure levels: {corner_data["top_right"]["pressure_level"].values} + + best_corner (most significant): {best_corner} + return: {corner_data[best_corner]["t"].values} + """ + ) + + return corner_data[best_corner]["t"].values + + def get_u_component_in_square(self, square: Square, ds_time: xr.Dataset): + # all these functions violate the dry principle, but I decided to repeat them to leave the code "open to change" + corners = ["top_left", "bottom_left", "bottom_right", "top_right"] + coords = [ + square.top_left, + square.bottom_left, + square.bottom_right, + square.top_right, + ] + corner_data = { + corner: ds_time.sel(latitude=lat, longitude=lon) + for corner, (lat, lon) in zip(corners, coords) + } + assert ( + corner_data["top_left"]["u"].size == 3 + ), f"top_left['u'].size: {corner_data['top_left']['u'].size}" + + results = [] + for corner in corner_data: + value = corner_data[corner]["u"].values + if np.isnan(value).any(): + lat, lon = dict(square)[corner] + value = self._find_nearest_non_null(ds_time, lat, lon, "u") + results.append(value) + assert len(results) == 4, f"len(results)={len(results)} != 4" + assert len(results[0]) == 3, f"len(results[0])={len(results[0])} != 3" + corner_sums = [np.sum(values) for values in results] + best_corner = corners[np.argmax(corner_sums)] + datazada = corner_data[best_corner]["u"].values + return datazada + + def get_v_component_in_square(self, square: Square, ds_time: xr.Dataset): + # all these functions violate the dry principle, but I decided to repeat them to leave the code "open to change" + corners = ["top_left", "bottom_left", "bottom_right", "top_right"] + coords = [ + square.top_left, + square.bottom_left, + square.bottom_right, + square.top_right, + ] + corner_data = { + corner: ds_time.sel(latitude=lat, longitude=lon) + for corner, (lat, lon) in zip(corners, coords) + } + assert ( + corner_data["top_left"]["v"].size == 3 + ), f"top_left['v'].size: {corner_data['top_left']['v'].size}" + + results = [] + for corner in corner_data: + value = corner_data[corner]["v"].values + if np.isnan(value).any(): + lat, lon = dict(square)[corner] + value = self._find_nearest_non_null(ds_time, lat, lon, "v") + results.append(value) + assert len(results) == 4, f"len(results)={len(results)} != 4" + assert len(results[0]) == 3, f"len(results[0])={len(results[0])} != 3" + corner_sums = [np.sum(values) for values in results] + best_corner = corners[np.argmax(corner_sums)] + return corner_data[best_corner]["v"].values + + def get_w_component_in_square(self, square: Square, ds_time: xr.Dataset): + # all these functions violate the dry principle, but I decided to repeat them to leave the code "open to change" + corners = ["top_left", "bottom_left", "bottom_right", "top_right"] + coords = [ + square.top_left, + square.bottom_left, + square.bottom_right, + square.top_right, + ] + corner_data = { + corner: ds_time.sel(latitude=lat, longitude=lon) + for corner, (lat, lon) in zip(corners, coords) + } + assert ( + corner_data["top_left"]["w"].size == 3 + ), f"top_left['w'].size: {corner_data['top_left']['w'].size}" + + results = [] + for corner in corner_data: + value = corner_data[corner]["w"].values + if np.isnan(value).any(): + lat, lon = dict(square)[corner] + value = self._find_nearest_non_null(ds_time, lat, lon, "w") + results.append(value) + assert len(results) == 4, f"len(results)={len(results)} != 4" + assert len(results[0]) == 3, f"len(results[0])={len(results[0])} != 3" + corner_sums = [np.sum(values) for values in results] + best_corner = corners[np.argmax(corner_sums)] + return corner_data[best_corner]["w"].values + + def get_era5_single_levels_precipitation_in_square( + self, square: Square, era5_at_time: xr.Dataset, data_var="tp", verbose=False + ) -> float: + corners = ["top_left", "bottom_left", "bottom_right", "top_right"] + coords = [ + square.top_left, + square.bottom_left, + square.bottom_right, + square.top_right, + ] + + corner_data = { + corner: era5_at_time.sel(latitude=lat, longitude=lon) + for corner, (lat, lon) in zip(corners, coords) + } + + single_levels_length = 1 + for corner in corners: + assert ( + corner_data[corner][data_var].size == single_levels_length + ), f"{corner}['{data_var}'].size: {corner_data[corner][{data_var}].size}" + + tp_values = [corner_data[corner][data_var].item() for corner in corners] + max_tp = max(tp_values) + + if verbose: + log.debug( + f""" + corner_data: + Top left lat lon: ({corner_data["top_left"].latitude.values}, {corner_data["top_left"].longitude.values}) + Top left precipitation: {corner_data["top_left"][data_var].values} + + Bottom left lat lon: ({corner_data["bottom_left"].latitude.values}, {corner_data["bottom_left"].longitude.values}) + Bottom left precipitation: {corner_data["bottom_left"][data_var].values} + + Bottom right lat lon: ({corner_data["bottom_right"].latitude.values}, {corner_data["bottom_right"].longitude.values}) + Bottom right precipitation: {corner_data["bottom_right"][data_var].values} + + Top right lat lon: ({corner_data["top_right"].latitude.values}, {corner_data["top_right"].longitude.values}) + Top right precipitation: {corner_data["top_right"][data_var].values} + + max_tp: {max_tp} + """ + ) + + if np.isnan(max_tp): + lat_mean, lon_mean = np.mean(coords, axis=0) + max_tp = self._find_nearest_non_null( + era5_at_time, lat_mean, lon_mean, data_var + ) + m_to_mm = 1000 + return max_tp * m_to_mm + + def get_precipitation_in_square( + self, + square: Square, + ds_time: xr.Dataset, + ) -> float: + return self.get_era5_single_levels_precipitation_in_square( + square, ds_time, verbose=True + ) + + def get_square( + self, + lat: float, + lon: float, + sorted_latitudes_ascending: npt.NDArray[np.float32], + sorted_longitudes_ascending: npt.NDArray[np.float32], + ) -> Optional[Square]: + """ + Get the square that contains the point (lat, lon) + Example, given this grid: + 0 1 2 3 + 0 * * * * + 1 * * * * + 2 * * * * + Given that lat long "*" is the top_left = (0,0): + top_left's bottom_left neighbor = (1,0) + bottom_left's bottom_right neighbor = (1,1) + bottom_right's top_right neighbor = (0,1) + + With top_left, bottom_left, bottom_right, top_right we can create a square + + Note we can get out of bounds, that's when we return None. + For example, there's no bottom neighbor or right neighbor for (2,3) + """ + bottom_neighbor = get_bottom_neighbor(lat, lon, sorted_latitudes_ascending) + if bottom_neighbor is None: + return None + lat_bottom, lon_bottom = bottom_neighbor + + right_neighbor = get_right_neighbor( + lat_bottom, lon_bottom, sorted_longitudes_ascending + ) + if right_neighbor is None: + return None + lat_right, lon_right = right_neighbor + + upper_neighbor = get_upper_neighbor( + lat_right, lon_right, sorted_latitudes_ascending + ) + if upper_neighbor is None: + return None + lat_upper, lon_upper = upper_neighbor + + return Square( + top_left=(lat, lon), + bottom_left=(lat_bottom, lon_bottom), + bottom_right=(lat_right, lon_right), + top_right=(lat_upper, lon_upper), + ) + + +if __name__ == "__main__": + # python -m src.spatiotemporal_builder.ERA5Square + import pandas as pd + + timestamp = pd.Timestamp("2022-10-31T18:00:00") + year = timestamp.year + month = timestamp.month + + era5_square = ERA5Square() + ds = xr.open_dataset( + f"./data/reanalysis/ERA5-single-levels/monthly_data/RJ_{year}_{month}.nc" + ) + ds = ds.sel(valid_time=timestamp) + lats = ds.latitude.values + lons = ds.longitude.values + log.debug("single levels dataset:") + log.debug(ds) + + log.debug("lats:") + log.debug(lats) + + log.debug("lons:") + log.debug(lons) + + log.info(f"Spatial resolution: {sorted(lats)[1] - sorted(lats)[0]:.2f} degrees") + log.debug(f"Grid: {lats.shape[0]}x{lons.shape[0]}") + + lat = sorted(lats)[4] + lon = sorted(lons)[7] + + square = era5_square.get_square(lat, lon, sorted(lats), sorted(lons)) + + precipitation = era5_square.get_precipitation_in_square(square, ds) + + log.success( + f""" + Precipitation in square: + top_left={square.top_left} + bottom_left={square.bottom_left} + bottom_right={square.bottom_right} + top_right={square.top_right} + {square.top_left} --- {square.top_right} + | {" " * 20} {precipitation:.2f} mm {" " * 20} | + {square.bottom_left} --- {square.bottom_right} + """ + ) + ds.close() + + ds = xr.open_dataset( + f"./data/reanalysis/ERA5-pressure-levels/monthly_data/RJ_{year}_{month}.nc" + ) + ds = ds.sel(valid_time=timestamp) + log.debug("pressure levels dataset:") + log.debug(ds) + + temperature = era5_square.get_temperature_in_square(square, ds, verbose=True) + log.success( + f""" + Temperature in square: + top_left={square.top_left} + bottom_left={square.bottom_left} + bottom_right={square.bottom_right} + top_right={square.top_right} + {square.top_left} --- {square.top_right} + | {" " * 10} {temperature} {" " * 10} | + {square.bottom_left} --- {square.bottom_right} + """ + ) + + ds.close() diff --git a/src/spatiotemporal_builder/INMETCoords.py b/src/spatiotemporal_builder/INMETCoords.py new file mode 100644 index 00000000..9f6576db --- /dev/null +++ b/src/spatiotemporal_builder/INMETCoords.py @@ -0,0 +1,45 @@ +from pathlib import Path + +import pandas as pd +import pandera as pa + + +class INMETCoordsSchema(pa.DataFrameModel): + id_estacao: str + estacao: str + estacao_desc: str + latitude: float = pa.Field(ge=-90, le=90) + longitude: float = pa.Field(ge=-180, le=180) + + +class INMETCoordsSchemaLatLongStr(INMETCoordsSchema): + latitude: str + longitude: str + + +def get_inmet_coords(): + inmet_coords_path = Path(__file__).parent / "../../WeatherStations.csv" + + inmet_coords = pd.read_csv(inmet_coords_path) + inmet_coords = inmet_coords.rename( + columns={ + "DC_NOME": "estacao", + "VL_LATITUDE": "latitude", + "VL_LONGITUDE": "longitude", + "STATION_ID": "id_estacao", + "CD_SITUACAO": "estacao_desc", + } + ) + inmet_coords = inmet_coords[ + ["id_estacao", "estacao", "estacao_desc", "latitude", "longitude"] + ] + INMETCoordsSchema.validate(inmet_coords) + + inmet_coords["latitude"] = inmet_coords["latitude"].apply(lambda x: str(x)) + inmet_coords["longitude"] = inmet_coords["longitude"].apply(lambda x: str(x)) + inmet_coords["estacao"] = inmet_coords["estacao"].str.strip() + inmet_coords["id_estacao"] = inmet_coords["id_estacao"].str.strip() + + INMETCoordsSchemaLatLongStr.validate(inmet_coords) + + return inmet_coords diff --git a/src/spatiotemporal_builder/INMETKeys.py b/src/spatiotemporal_builder/INMETKeys.py new file mode 100644 index 00000000..fe94be70 --- /dev/null +++ b/src/spatiotemporal_builder/INMETKeys.py @@ -0,0 +1,118 @@ +import json +from pathlib import Path +from typing import TypedDict + +import pandas as pd +from tqdm import tqdm + +from .INMETParser import INMETParser, INMETSchema +from .Logger import logger + +log = logger.get_logger(__name__) + + +class INMETKeySchema(INMETSchema): + latitude: str + longitude: str + + +class StationNameId(TypedDict): + name: str + station_id: int + + +class INMETKeys: + def __init__(self, inmet_parser: INMETParser, inmet_coords: pd.DataFrame) -> None: + self.inmet_keys_path = Path(__file__).parent / "inmet_keys" + if not self.inmet_keys_path.exists(): + self.inmet_keys_path.mkdir() + self.inmet_parser = inmet_parser + self.inmet_coords = inmet_coords + + def _not_founds_in_coords(self) -> list[StationNameId]: + not_founds_in_coords: list[StationNameId] = [] + existing_station_ids = set(self.inmet_coords["id_estacao"].values) + for file in self.inmet_parser.list_files(): + file_path = str(self.inmet_parser.inmet_path / file) + station_id = self.inmet_parser.read_station_id(file_path) + if station_id not in existing_station_ids: + not_founds_in_coords.append({"name": file, "station_id": station_id}) + if not_founds_in_coords: + log.warning( + f"Stations not found in websirenes coordinates: {not_founds_in_coords}" + ) + return not_founds_in_coords + + def _merge_by_id( + self, inmet_coords: pd.DataFrame, inmet_df: pd.DataFrame, station_id: str + ) -> pd.DataFrame: + station = inmet_coords[inmet_coords["id_estacao"] == station_id] + lat = station["latitude"].values[0] + lon = station["longitude"].values[0] + inmet_df["latitude"] = lat + inmet_df["longitude"] = lon + INMETKeySchema.validate(inmet_df) + return inmet_df + + def _write_key(self, df: pd.DataFrame): + row = df.iloc[0] + assert isinstance(row["latitude"], str), f"{type(row['latitude'])}" + assert isinstance(row["longitude"], str), f"{type(row['longitude'])}" + key = f"{row['latitude']}_{row['longitude']}" + df.to_parquet(self.inmet_keys_path / f"{key}.parquet") + + def load_key(self, key: str) -> pd.DataFrame: + return pd.read_parquet(f"{self.inmet_keys_path}/{key}.parquet") + + def build_keys(self, use_cache: bool = True): + total_files = len(list(self.inmet_keys_path.glob("*.parquet"))) + if use_cache and total_files > 0: + log.warning( + f"Using cached keys, {total_files} files found. To clear cache delete the {self.inmet_keys_path} folder" + ) + return + + files = self.inmet_parser.list_files() + not_found_in_coords = self._not_founds_in_coords() + log.info(f"Found {len(not_found_in_coords)} stations not found in coordinates") + log.info(f"Processing {len(files)} files to build keys") + minimum_date = pd.Timestamp.max + maximum_date = pd.Timestamp.min + for file in tqdm(files): + station_id = file.split("_")[0] + + df = self.inmet_parser.get_dataframe( + str(self.inmet_parser.inmet_path / file) + ) + + if df.index.min() < minimum_date: + minimum_date = df.index.min() + if df.index.max() > maximum_date: + maximum_date = df.index.max() + + df = self._merge_by_id(self.inmet_coords, df, station_id) + self._write_key(df) + log.info( + f""" + Minimum date: {minimum_date} + Maximum date: {maximum_date} + """ + ) + log.success(f"INMET keys built successfully in {self.inmet_keys_path}") + + minimum_maximum_dates_path = ( + self.inmet_keys_path / "minimum_maximum_dates_inmet.json" + ) + with open(minimum_maximum_dates_path, "w") as f: + json.dump( + { + "minimum_date": minimum_date.isoformat(), + "maximum_date": maximum_date.isoformat(), + }, + f, + indent=4, + ) + + log.success( + f"Minimum and maximum dates written to {minimum_maximum_dates_path}" + ) diff --git a/src/spatiotemporal_builder/INMETParser.py b/src/spatiotemporal_builder/INMETParser.py new file mode 100644 index 00000000..5b6cf66a --- /dev/null +++ b/src/spatiotemporal_builder/INMETParser.py @@ -0,0 +1,31 @@ +from pathlib import Path + +import pandas as pd +import pandera as pa + +from .Logger import logger + +log = logger.get_logger(__name__) + + +class INMETSchema(pa.DataFrameModel): + precipitation: float = pa.Field(nullable=False, ge=0) + + +class INMETParser: + inmet_path = Path(__file__).parent.parent.parent / "data/ws/inmet" + + def list_files(self) -> list[str]: + return [x.name for x in self.inmet_path.glob("*.gzip")] + + def read_station_id(self, file_path: str) -> str: + station_id = file_path.split("/")[-1].split("_")[0] + return station_id + + def get_dataframe(self, file_path: str) -> pd.DataFrame: + df = pd.read_parquet(file_path) + # df["horaLeitura"] = pd.to_datetime( + # df["horaLeitura"], format="%Y-%m-%d %H:%M:%S%z" + # ).dt.tz_convert(None) + INMETSchema.validate(df) + return df diff --git a/src/spatiotemporal_builder/INMETSquare.py b/src/spatiotemporal_builder/INMETSquare.py new file mode 100644 index 00000000..898fe782 --- /dev/null +++ b/src/spatiotemporal_builder/INMETSquare.py @@ -0,0 +1,78 @@ +from pathlib import Path + +import numpy as np +import pandas as pd +import xarray as xr + +from .ERA5Square import ERA5Square +from .INMETKeys import INMETKeys +from .Logger import logger +from .square import Square + +log = logger.get_logger(__name__) + + +class INMETSquare(ERA5Square): + def __init__(self, inmet_keys: INMETKeys) -> None: + self.inmet_keys = inmet_keys + + def get_keys_in_square( + self, square: Square, stations_inmet: set, verbose: bool = False + ) -> list[str]: + keys = [x.stem for x in Path(self.inmet_keys.inmet_keys_path).glob("*.parquet")] + inmet_keys = [] + for key in keys: + key_lat, key_lon = map(float, key.split("_")) + + if ( + verbose + and not ( + key_lat < square.bottom_left[0] or key_lat > square.top_left[0] + ) + and not (key_lon < square.top_left[1] or key_lon > square.top_right[1]) + ): + log.success( + f""" + Lat and Lon Square: + {square.top_left[0]}{square.top_left[1]} - {square.top_right[0]}{square.top_right[1]} + | {key_lat} {key_lon} | + {square.bottom_left[0]}{square.bottom_left[1]} - {square.bottom_right[0]}{square.bottom_right[1]} + """ + ) + + if key_lat < square.bottom_left[0] or key_lat > square.top_left[0]: + continue + if key_lon < square.top_left[1] or key_lon > square.top_right[1]: + continue + + inmet_keys.append(key) + + if len(inmet_keys) > 0: + stations_inmet.update(inmet_keys) + + return inmet_keys + + def get_precipitation_in_square( + self, + square: Square, + inmet_keys: list[str], + timestamp: pd.Timestamp, + ds_time: xr.Dataset, + ) -> float: + if len(inmet_keys) == 0: + return super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + precipitations: list[float] = [] + for key in inmet_keys: + df_web = self.inmet_keys.load_key(key) + df_web_filtered = df_web[df_web.index == timestamp] + h1 = df_web_filtered["precipitation"] + if h1.isnull().all(): + h1 = np.array( + super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + ) + precipitations.append(h1.item()) + return max(precipitations) diff --git a/src/spatiotemporal_builder/Logger.py b/src/spatiotemporal_builder/Logger.py new file mode 100644 index 00000000..9e0093c2 --- /dev/null +++ b/src/spatiotemporal_builder/Logger.py @@ -0,0 +1,75 @@ +import io +import logging +from typing import cast + +SUCCESS = logging.INFO - 5 +logging.addLevelName(SUCCESS, "SUCCESS") + + +class MyLogger(logging.Logger): + def success(self, msg, *args, **kwargs): + if self.isEnabledFor(SUCCESS): + self._log(SUCCESS, msg, args, **kwargs) + + +logging.setLoggerClass(MyLogger) + + +class ColorFormatter(logging.Formatter): + error_color = "\033[91m" + warning_color = "\033[93m" + info_color = "\033[96m" + success_color = "\033[92m" + reset_color = "\033[0m" + log_format = "%(asctime)s - %(name)s - %(levelname)s - %(message)s" + + FORMATS = { + SUCCESS: f"{success_color}{log_format}{reset_color}", + logging.DEBUG: f"{log_format}", + logging.INFO: f"{info_color}{log_format}{reset_color}", + logging.WARNING: f"{warning_color}{log_format}{reset_color}", + logging.ERROR: f"{error_color}{log_format}{reset_color}", + } + + def format(self, record): + formatter = logging.Formatter( + self.FORMATS.get(record.levelno), datefmt="%Y-%m-%d %H:%M:%S" + ) + return formatter.format(record) + + +class Logger: + def __init__(self): + self.logger = cast(MyLogger, logging.getLogger("log")) + self.logger.setLevel(logging.DEBUG) + + stream_handler = logging.StreamHandler() + file_handler = logging.FileHandler("websirenes_spatiotemporal_log.log") + stream_handler.setFormatter(ColorFormatter()) + file_handler.setFormatter( + logging.Formatter( + "%(asctime)s - %(name)s - %(levelname)s - %(message)s", + datefmt="%Y-%m-%d %H:%M:%S", + ) + ) + self.logger.addHandler(stream_handler) + self.logger.addHandler(file_handler) + + def get_logger(self, name: str) -> MyLogger: + return self.logger.getChild(name) + + +# https://stackoverflow.com/questions/14897756/python-progress-bar-through-logging-module +class TqdmLogger(io.StringIO): + def __init__(self, logger: logging.Logger): + self.logger = logger + self.level = logging.DEBUG + + def write(self, buf: str) -> None: + self.buf = buf.strip("\r\n\t ") + + def flush(self) -> None: + self.logger.log(self.level, self.buf) + + +logger = Logger() diff --git a/src/spatiotemporal_builder/README.md b/src/spatiotemporal_builder/README.md new file mode 100644 index 00000000..b0935f08 --- /dev/null +++ b/src/spatiotemporal_builder/README.md @@ -0,0 +1,119 @@ +# Spatiotemporal dataset builder + +This package build the dataset illustrated in the image below. Currently only integrates WebSirenes data with ERA5Land reanalysis model. A target grid corresponds to a 11x21 matrix of precipitation data, where each cell is a square of 0.1x0.1 degrees. The precipitation data is in mm/hour. The dataset is built hourly, so for each hour we have a grid of precipitation data. The dataset is built from 2011-04-12 20:30:00 to 2022-06-02 21:30:00. The dataset is built for the region of Rio de Janeiro, Brazil. + +Spatiotemporal dataset + +1- Place the WebSirenes dataset in the `atmoseer/data/ws/websirenes_defesa_civil` folder. In this folder should exist a list of `.txt` files with the stations' precipitation data. + +2- Place the WebSirenes coordinates in the `atmoseer/src/spatiotemporal_builder/websirenes_coords.parquet` folder. In this folder should exist a `websirenes_coords.parquet` file with the stations' coordinates. + +3- Place the ERA5Land reanalysis data in the `atmoseer/data/reanalysis/ERA5Land` folder. In this folder should exist a `monthly_data` folder with a list of `RJ_YEAR_MONTH.nc` files with the reanalysis data. + +Usage for production (integreates Websirenes spatiotemporal data from `2011-04-12 20:30:00` to `2022-06-02 21:30:00`): +```sh +python -m src.spatiotemporal_builder.main +``` + +The command above is equivalent of running: +```sh +python -m src.spatiotemporal_builder.main --start_date 2011-04-12T20:30:00 --end_date 2022-06-02T21:30:00 +``` +Passing the `--start_date` and `--end_date` arguments, has the advantage of not having to process keys again to find minimum and maximum dates of the dataset. + +For example, usage for building a small dataset. The command below will process 14 hours (i.e. 14 grids of precipitation data) from 2011-04-12-21 to 2011-04-13-00: +```sh +python -m src.spatiotemporal_builder.main --start_date 2011-04-12T21:00:00 --end_date 2011-04-13T10:00:00 +``` + +The diagram below presents the classes and their methods + +```mermaid +--- +title: Websirenes spatiotemporal data +--- +classDiagram + class WebSirenesParser { + +get_dataframe() + +read_station_name_id_txt_file() + +list_files() + -_parse_txt_file() + -_extract_features() + -_get_complete_pattern() + -_get_timeframe_pattern() + -_get_date_pattern() + -_get_name_pattern() + } + + class WebSirenesCoords { + +int id_estacao + +str estacao + +str estacao_desc + +str latitude + +str longitude + } + + class WebSirenesKeys { + +build_keys() + +load_key() + -_merge_by_name() + -_write_key() + -_not_founds_in_coords() + -_set_minimum_date() + -_set_maximum_date() + + } + + class WebSirenesSquare { + +get_keys_in_square() + +get_precipitation_in_square() + +get_square() + +get_features_in_square() + -_get_era5land_precipitation_in_square() + } + + class WebSirenesTarget { + +build_timestamps_hourly() + -_process_timestamp() + -_process_grid() + -_get_era5land_dataset() + -_write_target() + -_write_features() + -_get_grid_lats_lons() + -_get_relative_humidity() + } + + class WebsirenesDataset { + +build_netcdf() + -_process_timestamp() + -_get_dataset_with_timesteps() + -_has_timesteps() + -_process_timestamps_in_target() + } + + WebSirenesKeys --> WebSirenesParser + WebSirenesKeys --> WebSirenesCoords + + WebSirenesSquare --> WebSirenesKeys + + WebSirenesTarget --> WebSirenesParser: minimum_date, maximum_date + WebSirenesTarget --> WebSirenesSquare + + WebsirenesDataset --> WebSirenesTarget +``` + +TODO, improve the text and add WebsirenesDataset text + +The `WebSirenesParser` class is responsible for ETL, by reading the WebSirenes dataset in the `websirenes_defesa_civil` folder and extracting the features from the `.txt` files, it returns the data as a pandas Dataframe, the main function of this class is `get_dataframe`. + +The `WebSirenesCoords` is responsible for reading and validating the coordinates of the stations from the `websirenes_coords.parquet` file. The coordinates of the stations `websirenes_coords.parquet` came separated from the precipitation measurements `websirenes_defesa_civil` folder. The main attribute + +The `WebSirenesKeys` is responsible for building the keys in the `websirenes_keys` folder. Since the keys need to know the precipitation data and also the station coordinates, it depends on the `WebSirenesParser` and `WebSirenesCoords`. The keys are stored in the `websirenes_keys` folder, this folder contain a list of `lat_lon.parquet` files, each file is a WebSirenes station with the precipitation data. In total we have 83 stations, so we'll have 83 key files. + +The `WebSirenesSquare` is responsible for getting the precipitation data in the square. A square is a ``gridpoint`` which has top left, bottom left, top right and bottom right coordinates. A square can include one or more WebSirenes stations or not, the logic for getting the precipitation data is performed in the `get_precipitation_in_square` function. + +The `WebSirenesTarget` is responsible for building the target dataset. The target dataset is a grid with the precipitation data. Its main function is `build_timestamps_hourly` where it will build a grid per hour for each day in the dataset. Foe each hour, it will call `_process_grid`, this function processes the grid latitudes top to bottom and longitudes left to right, to build the `Squares` or gridpoints in the grid. It depends on the `WebSirenesSquare` class to get the precipitation data in the square and on the `WebSirenesKeys` to get the minimum and maximum date of the dataset, that was set in the `WebSirenesKeys` when building the keys. + +The target dataset will be written in `.npy` files under the `src/spatiotemporal_builder/target` folder. The features dataset will be written in `.npy` files under the `src/spatiotemporal_builder/features` folder. + +TODO integrate AlertaRio and INMET data diff --git a/src/spatiotemporal_builder/WebSirenesCoords.py b/src/spatiotemporal_builder/WebSirenesCoords.py new file mode 100644 index 00000000..3b1d1777 --- /dev/null +++ b/src/spatiotemporal_builder/WebSirenesCoords.py @@ -0,0 +1,36 @@ +from pathlib import Path + +import pandas as pd +import pandera as pa + + +class WebSireneCoordsSchema(pa.DataFrameModel): + id_estacao: int + estacao: str + estacao_desc: str + latitude: float = pa.Field(ge=-90, le=90) + longitude: float = pa.Field(ge=-180, le=180) + + +class WebSireneCoordsSchemaLatLongStr(WebSireneCoordsSchema): + latitude: str + longitude: str + + +def get_websirenes_coords() -> pd.DataFrame: + websirenes_coords_path = Path(__file__).parent / "websirenes_coords.parquet" + + websirenes_coords = pd.read_parquet(websirenes_coords_path) + WebSireneCoordsSchema.validate(websirenes_coords) + + websirenes_coords["latitude"] = websirenes_coords["latitude"].apply( + lambda x: str(x) + ) + websirenes_coords["longitude"] = websirenes_coords["longitude"].apply( + lambda x: str(x) + ) + websirenes_coords["estacao"] = websirenes_coords["estacao"].str.strip() + + WebSireneCoordsSchemaLatLongStr.validate(websirenes_coords) + + return websirenes_coords diff --git a/src/spatiotemporal_builder/WebSirenesKeys.py b/src/spatiotemporal_builder/WebSirenesKeys.py new file mode 100644 index 00000000..1be2e0cb --- /dev/null +++ b/src/spatiotemporal_builder/WebSirenesKeys.py @@ -0,0 +1,151 @@ +import json +from pathlib import Path +from typing import TypedDict + +import pandas as pd +from pandera.typing import Index +from tqdm import tqdm + +from .Logger import logger +from .WebSirenesParser import WebSireneSchema, WebSirenesParser + +log = logger.get_logger(__name__) + + +class StationNameId(TypedDict): + name: str + station_id: str + + +class WebsirenesKeySchema(WebSireneSchema): + horaLeitura: Index[pd.Timestamp] + latitude: str + longitude: str + + +class WebSirenesKeys: + def __init__( + self, websirenes_parser: WebSirenesParser, websirenes_coords: pd.DataFrame + ) -> None: + self.websirenes_keys_path = Path(__file__).parent / "websirenes_keys" + if not self.websirenes_keys_path.exists(): + self.websirenes_keys_path.mkdir() + self.websirenes_parser = websirenes_parser + self.websirenes_coords = websirenes_coords + + def _not_founds_in_coords(self) -> list[StationNameId]: + not_founds_in_coords: list[StationNameId] = [] + existing_station_names = set(self.websirenes_coords["estacao"].values) + for file in self.websirenes_parser.list_files(): + file_path = str(self.websirenes_parser.websirenes_defesa_civil_path / file) + name, station_id = self.websirenes_parser.read_station_name_id_txt_file( + file_path + ) + if name not in existing_station_names: + not_founds_in_coords.append({"name": name, "station_id": station_id}) + log.warning( + f"Stations not found in websirenes coordinates: {not_founds_in_coords}" + ) + return not_founds_in_coords + + def _merge_by_name( + self, websirenes_coords: pd.DataFrame, websirenes_defesa_civil: pd.DataFrame + ) -> pd.DataFrame: + websirenes_defesa_civil.reset_index(inplace=True) + df = pd.merge( + websirenes_coords, + websirenes_defesa_civil, + left_on="estacao", + right_on="nome", + how="inner", + ) + df.drop(columns=["estacao", "id_estacao"], inplace=True) + df.set_index("horaLeitura", inplace=True) + return df + + def _write_key(self, df: pd.DataFrame): + row = df.iloc[0] + assert isinstance(row["latitude"], str), f"{type(row['latitude'])}" + assert isinstance(row["longitude"], str), f"{type(row['longitude'])}" + key = f"{row['latitude']}_{row['longitude']}" + df.to_parquet(self.websirenes_keys_path / f"{key}.parquet") + + def load_key(self, key: str) -> pd.DataFrame: + return pd.read_parquet(f"{self.websirenes_keys_path}/{key}.parquet") + + def build_keys(self, use_cache: bool = True): + """ + Builds datasets by key (latitude and longitude) for each station + + Each station is mapped to a "lat_lon.parquet" file in the "websirenes_keys" folder + The keys generated are used to identify whether there are stations in an ERA5land gridpoint + + As a side effect, this function updates the minimum and maximum dates of the dataset as the files are processed + + The function performs the following steps: + 1. Lists all files to process + 2. Reads each file into a DataFrame + 3. Filters out files based on whether the station name is found in the coordinates list + 4. Updates the minimum and maximum dates of the dataset + 5. Merges the DataFrame with existing coordinates + 6. Writes the resulting each DataFrame to a key file + + Returns: + None + """ + total_files = len(list(self.websirenes_keys_path.glob("*.parquet"))) + if use_cache and total_files > 0: + log.warning( + f"Using cached keys, {total_files} files found. To clear cache delete the {self.websirenes_keys_path} folder" + ) + return + + files = self.websirenes_parser.list_files() + not_found_in_coords = self._not_founds_in_coords() + log.info(f"Found {len(not_found_in_coords)} stations not found in coordinates") + log.info( + f"Processing {len(files) - len(not_found_in_coords)} files to build keys" + ) + minimum_date = pd.Timestamp.max + maximum_date = pd.Timestamp.min + for file in tqdm(files): + df = self.websirenes_parser.get_dataframe( + str(self.websirenes_parser.websirenes_defesa_civil_path / file) + ) + station_name = df.nome.iloc[0] + if station_name in [x["name"] for x in not_found_in_coords]: + continue + + if df.index.min() < minimum_date: + minimum_date = df.index.min() + if df.index.max() > maximum_date: + maximum_date = df.index.max() + + df = self._merge_by_name(self.websirenes_coords, df) + self._write_key(df) + log.info( + f""" + Minimum date: {minimum_date} + Maximum date: {maximum_date} + """ + ) + log.success( + f"Websirenes keys built successfully in {self.websirenes_keys_path}" + ) + + minimum_maximum_dates_path = ( + self.websirenes_keys_path / "minimum_maximum_dates_websirenes.json" + ) + with open(minimum_maximum_dates_path, "w") as f: + json.dump( + { + "minimum_date": minimum_date.isoformat(), + "maximum_date": maximum_date.isoformat(), + }, + f, + indent=4, + ) + + log.success( + f"Minimum and maximum dates written to {minimum_maximum_dates_path}" + ) diff --git a/src/spatiotemporal_builder/WebSirenesParser.py b/src/spatiotemporal_builder/WebSirenesParser.py new file mode 100644 index 00000000..225cf22a --- /dev/null +++ b/src/spatiotemporal_builder/WebSirenesParser.py @@ -0,0 +1,173 @@ +import os +import re +from pathlib import Path + +import numpy as np +import pandas as pd +import pandera as pa + +from .Logger import logger + +log = logger.get_logger(__name__) + + +class WebSireneSchema(pa.DataFrameModel): + horaLeitura: pd.Timestamp + nome: str + m15: float = pa.Field(nullable=True) # ge=0, but txt has -99.99 values + m30: float = pa.Field(nullable=True) + h01: float = pa.Field(nullable=True) + h02: float = pa.Field(nullable=True) + h03: float = pa.Field(nullable=True) + h04: float = pa.Field(nullable=True) + h24: float = pa.Field(nullable=True) + h96: float = pa.Field(nullable=True) + station_id: int + + +class WebSirenesParser: + websirenes_defesa_civil_path = ( + Path(__file__).parent.parent.parent / "data/ws" / "websirenes_defesa_civil" + ) + + def list_files(self) -> list[str]: + return os.listdir(self.websirenes_defesa_civil_path) + + def _get_name_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 ... matches BARRA DA TIJUCA 3 + Returns: + str: regex pattern to extract name from line + """ + return r"^(?P.+?)(?=\s+\d{4}-\d{2}-\d{2})" + + def _get_date_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 ... matches 2021-08-01 00:00:00-03 + Returns: + str: regex pattern to extract date from line + """ + return r"(?P\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2}-\d{2})" + + def _get_timeframe_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 3 4 5 6 7 8 ... matches null 2 3 4 5 6 7 8 ... + Returns: + str: regex pattern to extract timeframe from line + """ + return r"(?P.+)$" + + def _get_complete_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 3 4 5 6 7 8 ... + matches: + BARRA DA TIJUCA 3 at group 'name' + 2021-08-01 00:00:00-03 at group 'date' + null 2 3 4 5 6 7 8 at group 'timeframe' + Returns: + str: regex pattern to extract name, date and timeframe from line + """ + return rf"{self._get_name_pattern()}\s+{self._get_date_pattern()}\s+{self._get_timeframe_pattern()}" + + def _extract_features(self, line: str) -> tuple: + """ + Extract features from line, the line comes from a txt file with the following format: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 3 4 5 6 7 8 ... + Where: + BARRA DA TIJUCA 3 is the name + 2021-08-01 00:00:00-03 is the date + null 2 3 4 5 6 7 8 is the timeframe + ... is the station_id + Returns: + tuple: (name, date, m15, m30, h01, h02, h03, h04, h24, h96, station_id) + """ + complete_pattern = self._get_complete_pattern() + + match = re.search(complete_pattern, line) + + if match is None: + raise ValueError(f"Could not extract features from line: {line}") + + name = match.group("name") + date = match.group("date") + "00" + timeframe = match.group("timeframe") + + m15, m30, h01, h02, h03, h04, h24, h96, station_id = [ + ( + np.nan + if x == "null" + else float(x.replace(",", ".")) if "," in x else float(x) + ) + for x in timeframe.strip().split() + ] + + return ( + name, + date, + m15, + m30, + h01, + h02, + h03, + h04, + h24, + h96, + int(station_id), + ) + + def _parse_txt_file(self, file_path: str) -> tuple[list[str], list[tuple]]: + """ + Given a file path, parse the file and return the header and the data + Returns: + tuple: (header, data) + Where: + header: list of strings with the header of the file + data: list of tuples with the data of the file + """ + try: + file_data: list[tuple] = [] + with open(file_path, "r", encoding="utf-8-sig") as file: + header = file.readline().strip().split() + for line in file: + file_data.append(self._extract_features(line)) + return header, file_data + except Exception as e: + log.error(f"Error parsing file {file_path}: {e}") + raise e + + def read_station_name_id_txt_file(self, file_path: str) -> tuple[str, int]: + try: + with open(file_path, "r", encoding="utf-8-sig") as file: + _header = file.readline().strip().split() + ( + nome, + horaLeitura, + m15, + m30, + h01, + h02, + h03, + h04, + h24, + h96, + station_id, + ) = self._extract_features(file.readline()) + return nome, station_id + except Exception as e: + log.error(f"Error parsing file {file_path}: {e}") + raise e + + def get_dataframe(self, file_path: str) -> pd.DataFrame: + header, file_data = self._parse_txt_file(file_path) + df = pd.DataFrame(file_data, columns=header) + df["horaLeitura"] = pd.to_datetime( + df["horaLeitura"], format="%Y-%m-%d %H:%M:%S%z" + ).dt.tz_convert(None) + df.rename(columns={"id": "station_id"}, inplace=True) + WebSireneSchema.validate(df) + df.set_index("horaLeitura", inplace=True) + return df diff --git a/src/spatiotemporal_builder/WebSirenesSquare.py b/src/spatiotemporal_builder/WebSirenesSquare.py new file mode 100644 index 00000000..9ebf781b --- /dev/null +++ b/src/spatiotemporal_builder/WebSirenesSquare.py @@ -0,0 +1,121 @@ +from datetime import timedelta +from pathlib import Path + +import numpy as np +import pandas as pd +import xarray as xr + +from .ERA5Square import ERA5Square +from .Logger import logger +from .square import Square +from .WebSirenesKeys import WebSirenesKeys + +log = logger.get_logger(__name__) + + +class WebSirenesSquare(ERA5Square): + def __init__(self, websirenes_keys: WebSirenesKeys) -> None: + self.websirenes_keys = websirenes_keys + + def get_keys_in_square( + self, square: Square, stations_websirenes: set, verbose: bool = False + ) -> list[str]: + """ + Get the keys of the websirenes datasets that are inside the square + Args: + square (Square): The square to check for keys + """ + keys = [ + x.stem + for x in Path(self.websirenes_keys.websirenes_keys_path).glob("*.parquet") + ] + websirenes_keys = [] + for key in keys: + key_lat, key_lon = map(float, key.split("_")) + + if ( + verbose + and not ( + key_lat < square.bottom_left[0] or key_lat > square.top_left[0] + ) + and not (key_lon < square.top_left[1] or key_lon > square.top_right[1]) + ): + log.success( + f""" + Lat and Lon Square: + {square.top_left[0]}{square.top_left[1]} - {square.top_right[0]}{square.top_right[1]} + | {key_lat} {key_lon} | + {square.bottom_left[0]}{square.bottom_left[1]} - {square.bottom_right[0]}{square.bottom_right[1]} + """ + ) + + if key_lat < square.bottom_left[0] or key_lat > square.top_left[0]: + continue + if key_lon < square.top_left[1] or key_lon > square.top_right[1]: + continue + + websirenes_keys.append(key) + + if len(websirenes_keys) > 0: + stations_websirenes.update(websirenes_keys) + + return websirenes_keys + + def get_precipitation_in_square( + self, + square: Square, + websirenes_keys: list[str], + timestamp: pd.Timestamp, + ds_time: xr.Dataset, + ) -> float: + if len(websirenes_keys) == 0: + return super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + + precipitations_15_min_aggregated: list[float] = [] + for key in websirenes_keys: + df_web = self.websirenes_keys.load_key(key) + + time_upper_bound = timestamp + time_lower_bound = timestamp - timedelta(minutes=45) + + df_web_filtered = df_web[ + (df_web.index >= time_lower_bound) & (df_web.index <= time_upper_bound) + ] + + m15 = df_web_filtered["m15"] + h01 = df_web[df_web.index == time_upper_bound]["h01"] + + if m15.size < 4 or m15.isnull().any(): + # Websirenes (and also Alertario) have a time resolution of 15 minutes + # for 16h for example, we'll get four m15 values: 16h, 15h45, 15h30, 15h15 + # to get this data we have two situations: + # situation 1, the timestamp or the DF index doesn't have all the values: + # 16h00 = 0.15 mm precipitation + # 15h45 = 0.05 mm precipitation + # 15h15 = 0.00 mm precipitation + # Notice the 15h30 is missing + # situation 2, the timestamp has all the values, but one of them is NaN: + # 16h00 = 0.15 mm precipitation + # 15h45 = 0.05 mm precipitation + # 15h30 = NaN + # 15h15 = 0.00 mm precipitation + # If either of these situations happen: + # Compare the aggregated sum with the ERA5 data, we use the most significant value + m15_era5 = super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + m15 = np.array([m15.sum(), m15_era5]).max() + max_between_m15_and_h01 = np.array( + [m15.sum().item(), h01.sum().item()] + ).max() + precipitations_15_min_aggregated.append(max_between_m15_and_h01.item()) + + max_precipitation = max(precipitations_15_min_aggregated) + # see "ge=0, but txt has -99.99 values" comment in WebSirenesParser.py + if max_precipitation < 0: + return super().get_era5_single_levels_precipitation_in_square( + square, ds_time + ) + return max_precipitation diff --git a/src/spatiotemporal_builder/WebsirenesDataset.py b/src/spatiotemporal_builder/WebsirenesDataset.py new file mode 100644 index 00000000..c0827f5c --- /dev/null +++ b/src/spatiotemporal_builder/WebsirenesDataset.py @@ -0,0 +1,187 @@ +import os +from pathlib import Path +from typing import Optional + +import numpy as np +import numpy.typing as npt +import pandas as pd +import xarray as xr +from tqdm import tqdm + +from .Logger import TqdmLogger, logger +from .WebsirenesTarget import SpatioTemporalFeatures + +log = logger.get_logger(__name__) + +os.environ["HDF5_USE_FILE_LOCKING"] = "FALSE" + + +class WebsirenesDataset: + dataset_path = Path(__file__).parent / "output_dataset.nc" + + def __init__(self, websirenes_target: SpatioTemporalFeatures) -> None: + self.websirenes_target = websirenes_target + self.TIMESTEPS = 5 + + def _has_timesteps(self, year: int, month: int, day: int, hour: int) -> bool: + start_time = pd.Timestamp(year=year, month=month, day=day, hour=hour) + for timestep in reversed(range(self.TIMESTEPS)): + current_time = start_time - pd.Timedelta(hours=timestep) + file = ( + self.websirenes_target.features_path + / f"{current_time.year:04}_{current_time.month:02}_{current_time.day:02}_{current_time.hour:02}_features.npy" + ) + if not Path(file).exists(): + return False + return True + + def _get_dataset_with_timesteps( + self, year: int, month: int, day: int, hour: int, time_step: int = 5 + ) -> npt.NDArray[np.float64]: + start_time = pd.Timestamp(year=year, month=month, day=day, hour=hour) + timesteps = [] + oldest_to_newest = reversed(range(time_step)) + for timestep in oldest_to_newest: + current_time = start_time - pd.Timedelta(hours=timestep) + file = f"{current_time.year:04}_{current_time.month:02}_{current_time.day:02}_{current_time.hour:02}_features.npy" + try: + data = np.load(self.websirenes_target.features_path / file) + except Exception as e: + print(f"Error loading file {file}: {e}") + exit(1) + timesteps.append(data) + data = np.stack(timesteps, axis=0) + return data + + def _process_timestamp( + self, timestamp: pd.Timestamp, overlapping: bool = True + ) -> tuple[Optional[npt.NDArray[np.float64]], Optional[npt.NDArray[np.float64]]]: + year = timestamp.year + month = timestamp.month + day = timestamp.day + hour = timestamp.hour + if not self._has_timesteps(year, month, day, hour): + return None, None + + next_timestamp = ( + timestamp + pd.Timedelta(hours=1) + if overlapping + else timestamp + pd.Timedelta(hours=self.TIMESTEPS) + ) + year_y = next_timestamp.year + month_y = next_timestamp.month + day_y = next_timestamp.day + hour_y = next_timestamp.hour + + if not self._has_timesteps(year_y, month_y, day_y, hour_y): + return None, None + + # log.debug(f"Loading data_x for {year:02}-{month:02}-{day:02} {hour}:00") + data_x = self._get_dataset_with_timesteps(year, month, day, hour) + + # log.debug(f"Loading data_y for {year:02}-{month:02}-{day:02} {hour + self.TIMESTEPS}:00") + data_y = self._get_dataset_with_timesteps(year_y, month_y, day_y, hour_y) + + return data_x, data_y + + def build_netcdf( + self, + min_timestamp: pd.Timestamp, + max_timestamp: pd.Timestamp, + ignored_months: list[int], + use_cache: bool = True, + overlapping: bool = True, + ) -> None: + if use_cache and self.dataset_path.exists(): + log.warning( + f"Using cached output_dataset.nc. To clear cache delete the {self.dataset_path} file" + ) + return + + log.info(f"Building dataset in {self.dataset_path}") + + validated_total_timestamps = self.websirenes_target.validate_timestamps( + min_timestamp, max_timestamp, ignored_months + ) + + has_last_timestamp_plus_one_hour = self._has_timesteps( + max_timestamp.year, + max_timestamp.month, + max_timestamp.day, + max_timestamp.hour + 1, + ) + added_extra_hour = 1 if has_last_timestamp_plus_one_hour else 0 + + total_samples = ( + validated_total_timestamps - self.TIMESTEPS + added_extra_hour + if overlapping + else validated_total_timestamps + - (2 * self.TIMESTEPS) + + 1 + + added_extra_hour + ) + + timestamps = pd.date_range(start=min_timestamp, end=max_timestamp, freq="h") + + log.info( + f""" + Total timestamps: {validated_total_timestamps} + Min timestamp: {min_timestamp} + Max timestamp: {max_timestamp} + Total samples: {total_samples} (overlapping: {overlapping}) + """ + ) + + data_x_list = [] + data_y_list = [] + for timestamp in tqdm(timestamps, mininterval=60, file=TqdmLogger(log)): + if timestamp.month in ignored_months: + continue + + data_x, data_y = self._process_timestamp(timestamp, overlapping) + if data_x is None and data_y is None: + continue + data_x_list.append(data_x) + data_y_list.append(data_y) + # high space complexity, may need to investigate another approach + + assert len(data_x_list) == len( + data_y_list + ), "Mismatch between data_x and data_y lists" + + data_x = np.stack(data_x_list, axis=0) + data_y = np.stack(data_y_list, axis=0) + + print(f"data_x shape: {data_x.shape}") + print(f"data_y shape: {data_y.shape}") + + # assert len(data_x) == total_samples, f"Expected {total_samples} samples, got {len(data_x)}" + # this assertion is not valid when ignoring months + + assert ( + data_x.shape == data_y.shape + ), f"x shape {data_x.shape} != y shape {data_y.shape}" + + log.debug(f"data_x shape: {data_x.shape}") + log.debug(f"data_y shape: {data_y.shape}") + + sample = np.arange(data_x.shape[0]) + timestep = np.arange(data_x.shape[1]) + channel = np.arange(data_x.shape[4]) + + ds = xr.Dataset( + { + "x": (["sample", "timestep", "lat", "lon", "channel"], data_x), + "y": (["sample", "timestep", "lat", "lon", "channel"], data_y), + }, + coords={ + "sample": sample, + "timestep": timestep, + "lat": self.websirenes_target.sorted_latitudes_ascending[::-1], + "lon": self.websirenes_target.sorted_longitudes_ascending, + "channel": channel, + }, + ) + + ds.to_netcdf(self.dataset_path) + log.success(f"Dataset saved to {self.dataset_path}") diff --git a/src/spatiotemporal_builder/WebsirenesTarget.py b/src/spatiotemporal_builder/WebsirenesTarget.py new file mode 100644 index 00000000..733151c5 --- /dev/null +++ b/src/spatiotemporal_builder/WebsirenesTarget.py @@ -0,0 +1,633 @@ +import os +import time +from concurrent.futures import ProcessPoolExecutor, as_completed +from multiprocessing.managers import BaseManager +from pathlib import Path +from typing import Optional + +import numpy as np +import numpy.typing as npt +import pandas as pd +import xarray as xr +from tqdm import tqdm + +from .AlertarioSquare import AlertarioSquare +from .INMETSquare import INMETSquare +from .Logger import TqdmLogger, logger +from .settings import settings +from .square import Square, get_square +from .WebSirenesSquare import WebSirenesSquare + +log = logger.get_logger(__name__) + + +class StationsManager(BaseManager): + pass + + +StationsManager.register("Set", set) +StationsManager.register("Dict", dict) + + +class SpatioTemporalFeatures: + manager = StationsManager() + manager.start() + stations_cells = manager.Set() + stations_inmet = manager.Set() + stations_websirenes = manager.Set() + stations_alertario = manager.Set() + dataset_era5_year_month = manager.Dict() + + def __init__( + self, + websirenes_square: WebSirenesSquare, + inmet_square: INMETSquare, + alertario_square: AlertarioSquare, + ): + self.features_path = Path(__file__).parent / "features" + if not self.features_path.exists(): + self.features_path.mkdir() + + self.era5_single_levels_path = ( + Path(__file__).parent.parent.parent / "data/reanalysis/ERA5-single-levels" + ) + self.era5_pressure_levels_path = ( + Path(__file__).parent.parent.parent / "data/reanalysis/ERA5-pressure-levels" + ) + + self.websirenes_square = websirenes_square + self.inmet_square = inmet_square + self.alertario_square = alertario_square + + lats, lons = self._get_grid_lats_lons() + + self.sorted_latitudes_ascending = np.sort(lats) + self.sorted_longitudes_ascending = np.sort(lons) + + self.features_tuple = { + "tp": "Total precipitation", + "r200": "Relative humidity at 200 hPa", + "r700": "Relative humidity at 700 hPa", + "r1000": "Relative humidity at 1000 hPa", + "t200": "Temperature at 200 hPa", + "t700": "Temperature at 700 hPa", + "t1000": "Temperature at 1000 hPa", + "u200": "U component of wind", + "u700": "U component of wind", + "u1000": "U component of wind", + "v200": "V component of wind", + "v700": "V component of wind", + "v1000": "V component of wind", + "speed200": "Speed of wind at 200 hPa", + "speed700": "Speed of wind at 700 hPa", + "speed1000": "Speed of wind at 1000 hPa", + "w200": "Vertical velocity at 200 hPa", + "w700": "Vertical velocity at 700 hPa", + "w1000": "Vertical velocity at 1000 hPa", + } + + log.debug("SpatioTemporalFeatures initialized") + log.debug( + f"Grid: {len(self.sorted_latitudes_ascending)}x{len(self.sorted_longitudes_ascending)}" + ) + log.debug(f"sorted_latitudes_ascending: {self.sorted_latitudes_ascending}") + log.debug(f"sorted_longitudes_ascending: {self.sorted_longitudes_ascending}") + log.info( + f"Spatial resolution: {self.sorted_latitudes_ascending[1] - self.sorted_latitudes_ascending[0]:.2f} degrees" + ) + + def _write_features( + self, features: npt.NDArray[np.float64], timestamp: pd.Timestamp + ): + features_filename = ( + self.features_path / f"{timestamp.strftime('%Y_%m_%d_%H')}_features.npy" + ) + np.save(features_filename, features) + + def _get_grid_lats_lons( + self, + ) -> tuple[npt.NDArray[np.float32], npt.NDArray[np.float32]]: + ds = self._get_era5_single_levels_dataset(2009, 6) + lats = ds.coords["latitude"].values + lons = ds.coords["longitude"].values + return lats, lons + + def _get_era5_single_levels_dataset(self, year: int, month: int) -> xr.Dataset: + if ( + self.dataset_era5_year_month.get((year, month)) == (year, month) + and self.dataset_era5_year_month.get("single_levels") is not None + ): + return self.dataset_era5_year_month.get("single_levels") + + era5_year_month_path = ( + self.era5_single_levels_path / "monthly_data" / f"RJ_{year}_{month}.nc" + ) + + if not os.path.exists(era5_year_month_path): + raise FileNotFoundError(f"File {era5_year_month_path} not found") + + if self.dataset_era5_year_month.get("single_levels") is not None: + self.dataset_era5_year_month.get("single_levels").close() + + ds = xr.open_dataset(era5_year_month_path) + ds = ds[["tp"]] + self.dataset_era5_year_month.update({(year, month): (year, month)}) + self.dataset_era5_year_month.update({"single_levels": ds}) + return ds + + def _get_era5_pressure_levels_dataset(self, year: int, month: int) -> xr.Dataset: + if ( + self.dataset_era5_year_month.get((year, month)) == (year, month) + and self.dataset_era5_year_month.get("pressure_levels") is not None + ): + return self.dataset_era5_year_month.get("pressure_levels") + + era5_year_month_path = ( + self.era5_pressure_levels_path / "monthly_data" / f"RJ_{year}_{month}.nc" + ) + + if not era5_year_month_path.exists(): + raise FileNotFoundError(f"File {era5_year_month_path} not found") + + if self.dataset_era5_year_month.get("pressure_levels") is not None: + self.dataset_era5_year_month.get("pressure_levels").close() + + ds = xr.open_dataset(era5_year_month_path) + ds = ds[["r", "t", "u", "v", "w"]] + self.dataset_era5_year_month.update({(year, month): (year, month)}) + self.dataset_era5_year_month.update({"pressure_levels": ds}) + return ds + + def _get_precipitation_in_square( + self, + square: Square, + timestamp: pd.Timestamp, + ds: xr.Dataset, + keys: list[tuple], + lat_index: int, + lon_index: int, + ): + if settings.only_ERA5: + return ( + self.websirenes_square.get_era5_single_levels_precipitation_in_square( + square, ds + ) + ) + + websirenes_keys = self.websirenes_square.get_keys_in_square(square, keys) + + inmet_keys = self.inmet_square.get_keys_in_square(square, keys) + + alertario_keys = self.alertario_square.get_keys_in_square(square, keys) + + if inmet_keys or websirenes_keys or alertario_keys: + keys.append((lat_index, lon_index)) + + tp_sirenes = self.websirenes_square.get_precipitation_in_square( + square, websirenes_keys, timestamp, ds + ) + + tp_inmet = self.inmet_square.get_precipitation_in_square( + square, inmet_keys, timestamp, ds + ) + + tp_alertario = self.alertario_square.get_precipitation_in_square( + square, alertario_keys, timestamp, ds + ) + + return max(tp_sirenes, tp_inmet, tp_alertario) + + def _process_grid( + self, + features: npt.NDArray[np.float64], + ds_single_levels: xr.Dataset, + ds_pressure_levels: xr.Dataset, + timestamp: pd.Timestamp, + ): + top_down_lats = self.sorted_latitudes_ascending[::-1] + left_right_lons = self.sorted_longitudes_ascending + + processed = 0 + keys = [] + # O(len(top_down_lats) * len(left_right_lons)) + # O(top_down_lats * left_right_lons * logn) + for i, lat in enumerate(top_down_lats): + for j, lon in enumerate(left_right_lons): + # O(logn), uses bisect + square = get_square( + lat, + lon, + self.sorted_latitudes_ascending, + self.sorted_longitudes_ascending, + ) + + if square is None: + continue + + tp = self._get_precipitation_in_square( + square, timestamp, ds_single_levels, keys, i, j + ) + + # O(4) ~ O(1) + r1000, r700, r200 = ( + self.websirenes_square.get_relative_humidity_in_square( + square, ds_pressure_levels + ) + ) + + # O(4) ~ O(1), all these below are the O(square) + t1000, t700, t200 = self.websirenes_square.get_temperature_in_square( + square, ds_pressure_levels + ) + u1000, u700, u200 = self.websirenes_square.get_u_component_in_square( + square, ds_pressure_levels + ) + + v1000, v700, v200 = self.websirenes_square.get_v_component_in_square( + square, ds_pressure_levels + ) + w1000, w700, w200 = self.websirenes_square.get_w_component_in_square( + square, ds_pressure_levels + ) + + speed200 = np.sqrt(u200**2 + v200**2) + speed700 = np.sqrt(u700**2 + v700**2) + speed1000 = np.sqrt(u1000**2 + v1000**2) + + features[i, j] = [ + tp, + r200, + r700, + r1000, + t200, + t700, + t1000, + u200, + u700, + u1000, + v200, + v700, + v1000, + speed200, + speed700, + speed1000, + w200, + w700, + w1000, + ] + processed += 1 + + self.stations_cells.update(keys) + + total_squares = (len(top_down_lats) - 1) * (len(left_right_lons) - 1) + assert processed == total_squares, "Not all squares processed" + + bottom_row_pressure_levels = ds_pressure_levels.sel(latitude=min(top_down_lats)) + bottom_row_single_levels = ds_single_levels.sel(latitude=min(top_down_lats)) + + right_column_pressure_levels = ds_pressure_levels.sel( + longitude=max(left_right_lons) + ) + right_column_single_levels = ds_single_levels.sel( + longitude=max(left_right_lons) + ) + + for j, lon in enumerate(left_right_lons): + features[-1, j] = [ + bottom_row_single_levels["tp"].values[j] * 1000, + bottom_row_pressure_levels["r"].sel(pressure_level=200).values[j], + bottom_row_pressure_levels["r"].sel(pressure_level=700).values[j], + bottom_row_pressure_levels["r"].sel(pressure_level=1000).values[j], + bottom_row_pressure_levels["t"].sel(pressure_level=200).values[j], + bottom_row_pressure_levels["t"].sel(pressure_level=700).values[j], + bottom_row_pressure_levels["t"].sel(pressure_level=1000).values[j], + bottom_row_pressure_levels["u"].sel(pressure_level=200).values[j], + bottom_row_pressure_levels["u"].sel(pressure_level=700).values[j], + bottom_row_pressure_levels["u"].sel(pressure_level=1000).values[j], + bottom_row_pressure_levels["v"].sel(pressure_level=200).values[j], + bottom_row_pressure_levels["v"].sel(pressure_level=700).values[j], + bottom_row_pressure_levels["v"].sel(pressure_level=1000).values[j], + np.sqrt( + bottom_row_pressure_levels["u"].sel(pressure_level=200).values[j] + ** 2 + + bottom_row_pressure_levels["v"].sel(pressure_level=200).values[j] + ** 2 + ), + np.sqrt( + bottom_row_pressure_levels["u"].sel(pressure_level=700).values[j] + ** 2 + + bottom_row_pressure_levels["v"].sel(pressure_level=700).values[j] + ** 2 + ), + np.sqrt( + bottom_row_pressure_levels["u"].sel(pressure_level=1000).values[j] + ** 2 + + bottom_row_pressure_levels["v"].sel(pressure_level=1000).values[j] + ** 2 + ), + bottom_row_pressure_levels["w"].sel(pressure_level=200).values[j], + bottom_row_pressure_levels["w"].sel(pressure_level=700).values[j], + bottom_row_pressure_levels["w"].sel(pressure_level=1000).values[j], + ] + processed += 1 + + for i, lat in enumerate(top_down_lats): + features[i, -1] = [ + right_column_single_levels["tp"].values[i] * 1000, + right_column_pressure_levels["r"].sel(pressure_level=200).values[i], + right_column_pressure_levels["r"].sel(pressure_level=700).values[i], + right_column_pressure_levels["r"].sel(pressure_level=1000).values[i], + right_column_pressure_levels["t"].sel(pressure_level=200).values[i], + right_column_pressure_levels["t"].sel(pressure_level=700).values[i], + right_column_pressure_levels["t"].sel(pressure_level=1000).values[i], + right_column_pressure_levels["u"].sel(pressure_level=200).values[i], + right_column_pressure_levels["u"].sel(pressure_level=700).values[i], + right_column_pressure_levels["u"].sel(pressure_level=1000).values[i], + right_column_pressure_levels["v"].sel(pressure_level=200).values[i], + right_column_pressure_levels["v"].sel(pressure_level=700).values[i], + right_column_pressure_levels["v"].sel(pressure_level=1000).values[i], + np.sqrt( + right_column_pressure_levels["u"].sel(pressure_level=200).values[i] + ** 2 + + right_column_pressure_levels["v"] + .sel(pressure_level=200) + .values[i] + ** 2 + ), + np.sqrt( + right_column_pressure_levels["u"].sel(pressure_level=700).values[i] + ** 2 + + right_column_pressure_levels["v"] + .sel(pressure_level=700) + .values[i] + ** 2 + ), + np.sqrt( + right_column_pressure_levels["u"].sel(pressure_level=1000).values[i] + ** 2 + + right_column_pressure_levels["v"] + .sel(pressure_level=1000) + .values[i] + ** 2 + ), + right_column_pressure_levels["w"].sel(pressure_level=200).values[i], + right_column_pressure_levels["w"].sel(pressure_level=700).values[i], + right_column_pressure_levels["w"].sel(pressure_level=1000).values[i], + ] + processed += 1 + # the corner cell is processed twice, is the common point between the last row and the last column + processed -= 1 + total_squares = len(top_down_lats) * len(left_right_lons) + assert ( + processed == total_squares + ), "Not all cells processed failed to include last row and last column" + + def _process_timestamp(self, timestamp: pd.Timestamp): + year = timestamp.year + month = timestamp.month + day = timestamp.day + hour = timestamp.hour + + time = f"{year}-{month}-{day}T{hour}:00:00.000000000" + + ds_single_levels_month = self._get_era5_single_levels_dataset(year, month) + ds_pressure_levels_month = self._get_era5_pressure_levels_dataset(year, month) + + ds_single_levels_time = ds_single_levels_month.sel( + valid_time=time, method="nearest" + ) + ds_pressure_levels_time = ds_pressure_levels_month.sel( + valid_time=time, method="nearest" + ) + + features = np.zeros( + ( + self.sorted_latitudes_ascending.size, + self.sorted_longitudes_ascending.size, + len(self.features_tuple), + ), + dtype=np.float64, + ) + + self._process_grid( + features, ds_single_levels_time, ds_pressure_levels_time, timestamp + ) + self._write_features(features, timestamp) + ds_single_levels_time.close() + ds_pressure_levels_time.close() + + def build_timestamps_hourly( + self, + start_date: Optional[pd.Timestamp], + end_date: Optional[pd.Timestamp], + ignored_months: list[int], + use_cache: bool = True, + ): + minimum_date = start_date + maximum_date = end_date + + timestamps = pd.date_range(start=minimum_date, end=maximum_date, freq="h") + + log.info(f"Building websirenes target from {timestamps[0]} to {timestamps[-1]}") + start_time = time.time() + ONE_MINUTE = 60 * 1 + all_cached = True + + with ProcessPoolExecutor() as executor: + futures = [] + + for timestamp in timestamps: + if ( + use_cache + and self.features_path.joinpath( + f"{timestamp.strftime('%Y_%m_%d_%H')}_features.npy" + ).exists() + ): + continue + + if timestamp.month in ignored_months: + continue + + all_cached = False + futures.append(executor.submit(self._process_timestamp, timestamp)) + log.info(f"Tasks submitted - {len(futures)}") + + with tqdm( + total=len(timestamps), + desc="Processing timestamps", + file=TqdmLogger(log), + dynamic_ncols=True, + mininterval=ONE_MINUTE, + ) as pbar: + for future in as_completed(futures): + try: + future.result() + pbar.update() + except Exception as e: + log.error(f"Error processing timestamp: {e}") + raise SystemExit(e) + + self.found_stations = self.stations_websirenes._getvalue() + self.found_stations_inmet = self.stations_inmet._getvalue() + self.found_stations_alertario = self.stations_alertario._getvalue() + self.stations_cells = self.stations_cells._getvalue() + self.manager.shutdown() + + end_time = time.time() + log.info(f"Target built in {end_time - start_time:.2f} seconds - parallel") + + # start_time = time.time() + # os.environ["IS_SEQUENTIAL"] = "True" + # for i in tqdm( + # range(len(timestamps)), + # desc="Processing timestamps", + # file=TqdmLogger(log), + # dynamic_ncols=True, + # mininterval=ONE_MINUTE, + # ): + # if self.features_path.joinpath( + # f"{timestamps[i].strftime('%Y_%m_%d_%H')}_features.npy" + # ).exists(): + # continue + + # if timestamps[i].month in ignored_months: + # continue + + # self._process_timestamp(timestamps[i]) + # self.found_stations = self.stations_websirenes._getvalue() + # self.found_stations_inmet = self.stations_inmet._getvalue() + # self.found_stations_alertario = self.stations_alertario._getvalue() + # self.stations_cells = self.stations_cells._getvalue() + # self.manager.shutdown() + # end_time = time.time() + # log.info(f"Target built in {end_time - start_time:.2f} seconds - sequential") + + validated_total_timestamps = self.validate_timestamps( + minimum_date, maximum_date, ignored_months + ) + + log.success( + f"Websirenes features hourly built successfully in {self.features_path} - {validated_total_timestamps} files" + ) + + assert ( + settings.only_ERA5 + or all_cached + or len(self.found_stations) + == len( + list( + self.websirenes_square.websirenes_keys.websirenes_keys_path.glob( + "*.parquet" + ) + ) + ) + ), "Expected all websirenes stations to be found and processed" + + assert ( + settings.only_ERA5 + or all_cached + or len(list(self.inmet_square.inmet_keys.inmet_keys_path.glob("*.parquet"))) + ), "Expected all inmet stations to be found and processed" + + assert ( + settings.only_ERA5 + or all_cached + or len( + list( + self.alertario_square.alertario_keys.alertario_keys_path.glob( + "*.parquet" + ) + ) + ) + ), "Expected all alertario stations to be found and processed" + + if not all_cached and not settings.only_ERA5: + log.success( + f""" + All stations processed: + Websirenes: {len(self.found_stations)} files + INMET: {len(self.found_stations_inmet)} files + Alertario: {len(self.found_stations_alertario)} files + Total cells with station: {len(self.stations_cells)} + """ + ) + + if len(self.stations_cells) > 0: + np.save( + self.features_path / "stations_cells.npy", list(self.stations_cells) + ) + log.success( + f"set {self.stations_cells} file created in {self.features_path / 'stations_cells.npy'}" + ) + + def validate_timestamps( + self, + min_timestamp: pd.Timestamp, + max_timestamp: pd.Timestamp, + ignored_months: list[int], + ) -> int: + timestamps = pd.date_range(start=min_timestamp, end=max_timestamp, freq="h") + not_found = [] + total_timestamps = 0 + total_files = 0 + + for timestamp in timestamps: + if timestamp.month in ignored_months: + continue + + total_timestamps += 1 + year = timestamp.year + month = timestamp.month + day = timestamp.day + hour = timestamp.hour + file = ( + self.features_path + / f"{year:04}_{month:02}_{day:02}_{hour:02}_features.npy" + ) + + if not Path(file).exists(): + not_found.append(timestamp) + continue + + features = np.load(file) + assert features.shape[0] == len( + self.sorted_latitudes_ascending + ), f"shape[0] should be {len(self.sorted_latitudes_ascending)} but is {features.shape[0]}" + assert features.shape[1] == len( + self.sorted_longitudes_ascending + ), f"shape[1] should be {len(self.sorted_longitudes_ascending)} but is {features.shape[1]}" + assert features.shape[2] == len( + self.features_tuple + ), f"shape[2] should be {len(self.features_tuple)} but is {features.shape[2]}" + + assert np.all( + np.any(features != 0, axis=(1, 2)) + ), f"Should not have one row with all values as zero for {file}" + + total_files += 1 + + if not_found: + log.error(f"Missing timestamps: {not_found}") + exit(1) + + assert ( + total_files == total_timestamps + ), "Mismatch between timestamps and files (ignoring specific months)" + + log.success( + f"""All timestamps found in target directory: + From={min_timestamp} + To={max_timestamp} + Ignoring months={ignored_months} + Total timestamps={total_timestamps} + Shape: {features.shape} + All rows have at least one non-zero value: { + np.all(np.any(features != 0, axis=(1, 2))) + } + """ + ) + return total_timestamps + + +if __name__ == "__main__": + """""" diff --git a/src/spatiotemporal_builder/__init__.py b/src/spatiotemporal_builder/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/spatiotemporal_builder/get_neighbors.py b/src/spatiotemporal_builder/get_neighbors.py new file mode 100644 index 00000000..5c937408 --- /dev/null +++ b/src/spatiotemporal_builder/get_neighbors.py @@ -0,0 +1,40 @@ +import bisect + +import numpy as np +import numpy.typing as npt + + +def get_upper_neighbor( + lat: float, lon: float, sorted_latitudes_ascending: npt.NDArray[np.float32] +): + lat_idx = bisect.bisect_right(sorted_latitudes_ascending, lat) + if lat_idx < len(sorted_latitudes_ascending): + return sorted_latitudes_ascending[lat_idx], lon + return None + + +def get_bottom_neighbor( + lat: float, lon: float, sorted_latitudes_ascending: npt.NDArray[np.float32] +): + lat_idx = bisect.bisect_left(sorted_latitudes_ascending, lat) + if lat_idx > 0: + return sorted_latitudes_ascending[lat_idx - 1], lon + return None + + +def get_left_neighbor( + lat: float, lon: float, sorted_longitudes_ascending: npt.NDArray[np.float32] +): + lon_idx = bisect.bisect_left(sorted_longitudes_ascending, lon) + if lon_idx > 0: + return lat, sorted_longitudes_ascending[lon_idx - 1] + return None + + +def get_right_neighbor( + lat: float, lon: float, sorted_longitudes_ascending: npt.NDArray[np.float32] +): + lon_idx = bisect.bisect_right(sorted_longitudes_ascending, lon) + if lon_idx < len(sorted_longitudes_ascending): + return lat, sorted_longitudes_ascending[lon_idx] + return None diff --git a/src/spatiotemporal_builder/main.py b/src/spatiotemporal_builder/main.py new file mode 100644 index 00000000..d981d619 --- /dev/null +++ b/src/spatiotemporal_builder/main.py @@ -0,0 +1,198 @@ +import argparse +from typing import Optional + +import pandas as pd + +from .AlertarioCoords import get_alertario_coords +from .AlertarioKeys import AlertarioKeys +from .AlertarioParser import AlertarioParser +from .AlertarioSquare import AlertarioSquare +from .INMETCoords import get_inmet_coords +from .INMETKeys import INMETKeys +from .INMETParser import INMETParser +from .INMETSquare import INMETSquare +from .Logger import logger +from .settings import settings +from .WebSirenesCoords import get_websirenes_coords +from .WebsirenesDataset import WebsirenesDataset +from .WebSirenesKeys import WebSirenesKeys +from .WebSirenesParser import WebSirenesParser +from .WebSirenesSquare import WebSirenesSquare +from .WebsirenesTarget import SpatioTemporalFeatures + +log = logger.get_logger(__name__) + + +def validate_dates( + start_date: Optional[str], end_date: Optional[str] +) -> tuple[Optional[pd.Timestamp], Optional[pd.Timestamp]]: + if not start_date or not end_date: + return None, None + + s_date = pd.Timestamp(start_date) + e_date = pd.Timestamp(end_date) + + # TODO FIX THIS + # MIN_START_DATE = pd.Timestamp("2011-04-12 20:30:00") + # MAX_END_DATE = pd.Timestamp("2022-06-02 21:30:00") + + # if not (MIN_START_DATE <= s_date <= e_date <= MAX_END_DATE): + # raise ValueError( + # f"start_date and end_date must be between {MIN_START_DATE} and {MAX_END_DATE}" + # ) + + log.info(f"Building spatiotemporal data from {s_date} to {e_date}") + return s_date, e_date + + +def check_data_requirements(): + pass + # try: + # websirenes_defesa_civil_path = WebSirenesParser.websirenes_defesa_civil_path + # if not websirenes_defesa_civil_path.exists(): + # raise FileNotFoundError( + # f"websirenes_defesa_civil folder not found in {websirenes_defesa_civil_path}. Please place the websirenes dataset in the expected folder" + # ) + # if not any(websirenes_defesa_civil_path.glob("*.txt")): + # raise FileNotFoundError(f"No txt files found in {websirenes_defesa_civil_path}") + + # if not websirenes_coords_path.exists(): + # raise FileNotFoundError( + # f"websirenes_coords.parquet not found in {websirenes_coords_path}. Please place the websirenes coordinates dataset in the expected folder" + # ) + + # if not websirenes_target.era5_pressure_levels_path.exists(): + # raise FileNotFoundError( + # f"ERA5 pressure levels folder not found in {websirenes_target.era5_pressure_levels_path}. Please place the ERA5 pressure levels dataset in the expected folder" + # ) + + # if not websirenes_target.era5_single_levels_path.exists(): + # raise FileNotFoundError( + # f"ERA5 single levels folder not found in {websirenes_target.era5_single_levels_path}. Please place the ERA5 single levels dataset in the expected folder" + # ) + + # if not (websirenes_target.era5_single_levels_path / "monthly_data").exists(): + # raise FileNotFoundError( + # f"ERA5 single levels monthly_data folder not found in {websirenes_target.era5_single_levels_path}. Please place the ERA5 single levels monthly data in the expected folder" + # ) + + # if not any((websirenes_target.era5_single_levels_path / "monthly_data").glob("*.nc")): + # raise FileNotFoundError( + # f"No nc files found in {websirenes_target.era5_single_levels_path / 'monthly_data'}. Please place the ERA5 single levels monthly data in the expected folder" + # ) + + # if not (websirenes_target.era5_pressure_levels_path / "monthly_data").exists(): + # raise FileNotFoundError( + # f"ERA5 pressure levels monthly_data folder not found in {websirenes_target.era5_pressure_levels_path}. Please place the ERA5 pressure levels monthly data in the expected folder" + # ) + + # if not any((websirenes_target.era5_pressure_levels_path / "monthly_data").glob("*.nc")): + # raise FileNotFoundError( + # f"No nc files found in {websirenes_target.era5_pressure_levels_path / 'monthly_data'}. Please place the ERA5 pressure levels monthly data in the expected folder" + # ) + # except Exception as e: + # log.error(f"Error while checking data requirements: {e}") + # exit(1) + + +def get_instances(): + sirenes_coords = get_websirenes_coords() if not settings.only_ERA5 else None + websirenes_keys = WebSirenesKeys(WebSirenesParser(), sirenes_coords) + websirenes_square = WebSirenesSquare(websirenes_keys) + + inmet_coords = get_inmet_coords() if not settings.only_ERA5 else None + inmet_keys = INMETKeys(INMETParser(), inmet_coords) + inmet_square = INMETSquare(inmet_keys) + + alertario_coords = get_alertario_coords() if not settings.only_ERA5 else None + alertario_keys = AlertarioKeys(AlertarioParser(), alertario_coords) + alertario_square = AlertarioSquare(alertario_keys) + + spatio_temporal_features = SpatioTemporalFeatures( + websirenes_square, inmet_square, alertario_square + ) + dataset_builder = WebsirenesDataset(spatio_temporal_features) + + return ( + websirenes_keys, + inmet_keys, + alertario_keys, + spatio_temporal_features, + dataset_builder, + ) + + +def build_features( + start_date: pd.Timestamp, end_date: pd.Timestamp, ignored_months: list[int] +): + try: + ( + websirenes_keys, + inmet_keys, + alertario_keys, + spatio_temporal_features, + dataset_builder, + ) = get_instances() + + if not settings.only_ERA5: + websirenes_keys.build_keys() + inmet_keys.build_keys() + alertario_keys.build_keys() + + spatio_temporal_features.build_timestamps_hourly( + start_date, end_date, ignored_months + ) + + dataset_builder.build_netcdf(start_date, end_date, ignored_months) + except Exception as e: + log.error(f"Error while building features: {e}") + + +def build_test(start_date: pd.Timestamp, end_date: pd.Timestamp): + try: + pass + # websirenes_target.build_timestamps_hourly(start_date, end_date, []) + # websirenes_dataset.build_netcdf(start_date, end_date, []) + except Exception as e: + log.error(f"Error while building test: {e}") + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(description="Build spatiotemporal data") + parser.add_argument( + "--start-date", + type=str, + required=False, + help="Start date in the format YYYY-MM-DDTHH:MM:SS", + ) + parser.add_argument( + "--end-date", + type=str, + required=False, + help="End date in the format YYYY-MM-DDTHH:MM:SS", + ) + parser.add_argument( + "--ignored_months", + nargs="+", + type=int, + required=False, + default=[6, 7, 8], + help="Months to ignore (e.g., --ignored_months 6 7 8)", + ) + parser.add_argument( + "--only-ERA5", + action="store_true", + help="Build features only using ERA5 data", + ) + + # check_data_requirements() + + args = parser.parse_args() + + settings.set_settings(args) + + start_date, end_date = validate_dates(args.start_date, args.end_date) + + build_features(start_date, end_date, args.ignored_months) + + # build_test(start_date, end_date) diff --git a/src/spatiotemporal_builder/settings.py b/src/spatiotemporal_builder/settings.py new file mode 100644 index 00000000..fc3a9b22 --- /dev/null +++ b/src/spatiotemporal_builder/settings.py @@ -0,0 +1,26 @@ +import json +from argparse import Namespace + +import pandas as pd + +from .Logger import logger + +log = logger.get_logger(__name__) + + +class Settings: + def __init__(self) -> None: + self.only_ERA5 = False + self.start_date: pd.Timestamp = pd.Timestamp.min + self.end_date: pd.Timestamp = pd.Timestamp.max + self.ignored_months = [] + + def set_settings(self, args: Namespace): + for key, value in vars(args).items(): + if not hasattr(self, key): + log.error(f"Unknown setting: {key}") + setattr(self, key, value) + log.info(f"Settings: {json.dumps((vars(self)), indent=4)}") + + +settings = Settings() diff --git a/src/spatiotemporal_builder/square.py b/src/spatiotemporal_builder/square.py new file mode 100644 index 00000000..0221f5b6 --- /dev/null +++ b/src/spatiotemporal_builder/square.py @@ -0,0 +1,64 @@ +from typing import Optional + +import numpy as np +import numpy.typing as npt +from pydantic import BaseModel + +from .get_neighbors import get_bottom_neighbor, get_right_neighbor, get_upper_neighbor + + +class Square(BaseModel): + top_left: tuple[float, float] + bottom_left: tuple[float, float] + bottom_right: tuple[float, float] + top_right: tuple[float, float] + + +def get_square( + lat: float, + lon: float, + sorted_latitudes_ascending: npt.NDArray[np.float32], + sorted_longitudes_ascending: npt.NDArray[np.float32], +) -> Optional[Square]: + """ + Get the square that contains the point (lat, lon) + Example, given this grid: + 0 1 2 3 + 0 * * * * + 1 * * * * + 2 * * * * + Given that lat long "*" is the top_left = (0,0): + top_left's bottom_left neighbor = (1,0) + bottom_left's bottom_right neighbor = (1,1) + bottom_right's top_right neighbor = (0,1) + + With top_left, bottom_left, bottom_right, top_right we can create a square + + Note we can get out of bounds, that's when we return None. + For example, there's no bottom neighbor for (3,3) + """ + bottom_neighbor = get_bottom_neighbor(lat, lon, sorted_latitudes_ascending) + if bottom_neighbor is None: + return None + lat_bottom, lon_bottom = bottom_neighbor + + right_neighbor = get_right_neighbor( + lat_bottom, lon_bottom, sorted_longitudes_ascending + ) + if right_neighbor is None: + return None + lat_right, lon_right = right_neighbor + + upper_neighbor = get_upper_neighbor( + lat_right, lon_right, sorted_latitudes_ascending + ) + if upper_neighbor is None: + return None + lat_upper, lon_upper = upper_neighbor + + return Square( + top_left=(lat, lon), + bottom_left=(lat_bottom, lon_bottom), + bottom_right=(lat_right, lon_right), + top_right=(lat_upper, lon_upper), + ) diff --git a/src/surface_stations/README_preprocess.md b/src/surface_stations/README_preprocess.md new file mode 100644 index 00000000..1448c873 --- /dev/null +++ b/src/surface_stations/README_preprocess.md @@ -0,0 +1,212 @@ +# Surface Station Preprocessing + +This guide explains how to configure and execute `src/surface_stations/preprocess.py`, the script that standardises and engineers features from the raw weather-station datasets. + +## 1. Prerequisites +- Execute commands from the project root (`~/ailab/atmoseer`). +- Activate the Conda environment that contains the project dependencies (e.g. `conda activate atmoseer`). +- Ensure `PYTHONPATH` includes the `src` directory when calling the script directly. The examples below set it inline; the `make surface_stations_preprocess` target also takes care of this. +- The raw station files must exist under the paths defined in `config/globals.py` (for example `data/ws/inmet/`). + +## 2. Station System Configuration + +Preprocessing behaviour is controlled by JSON files under `config/station_systems/`. Each file corresponds to a station system (INMET, AlertaRio, etc.) and provides: + +| Key | Description | +| --- | --- | +| `column_mapping` | Maps raw column names to the canonical names expected by the pipeline. | +| `features` | Toggles that enable or skip feature engineering steps (`add_wind_related_features`, `add_hour_related_features`, `normalize_predictors`, `impute_missing_values`). | +| `predictor_columns` | Ordered list of predictor columns to retain after feature engineering. | +| `stations` | Metadata indexed by station id (name, state, status, coordinates, altitude, start date). | +| `quality` | Optional quality-control checks (bounds, IQR/z-score detection, flag generation). | +| `preprocessing` | Optional scaling/imputation configuration (`scaler`, `imputation`). | +| `target_column` | Name of the target variable to keep with the predictors. | + +Example (`config/station_systems/inmet.json`): +```json +{ + "column_mapping": { + "datetime": "datetime", + "TEM_MAX": "temperature", + "UMD_MAX": "relative_humidity", + "PRE_MAX": "barometric_pressure", + "VEN_VEL": "wind_speed", + "VEN_DIR": "wind_dir", + "CHUVA": "precipitation" + }, + "features": { + "add_wind_related_features": true, + "add_hour_related_features": true, + "normalize_predictors": true, + "impute_missing_values": true + }, + "predictor_columns": [ + "temperature", + "barometric_pressure", + "relative_humidity", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos" + ], + "stations": { + "A601": { + "name": "SEROPEDICA-ECOLOGIA AGRICOLA", + "state": "RJ", + "status": "Operante", + "latitude": -22.75777777, + "longitude": -43.68472221, + "altitude_m": 35.0, + "operation_start": "2000-05-23" + } + }, + "target_column": "precipitation", + "quality": { + "enabled": true, + "flag_column_suffix": "_flag", + "include_flag_columns": true, + "checks": [ + { + "type": "bounds", + "name": "temperature_physical_limits", + "columns": ["temperature"], + "min": -60, + "max": 60, + "actions": ["clip", "flag"] + }, + { + "type": "bounds", + "name": "humidity_range", + "columns": ["relative_humidity"], + "min": 0, + "max": 100, + "actions": ["clip", "flag"] + } + ] + }, + "preprocessing": { + "scaler": { + "type": "minmax", + "params": { + "feature_range": [0, 1] + } + }, + "imputation": { + "strategy": "knn", + "params": { + "n_neighbors": 2, + "weights": "uniform" + } + } + }, + "report": { + "enabled": true, + "fields": ["missing_fraction", "imputed_fraction", "min", "max"], + "summary": ["rows", "columns", "missing_fraction", "imputed_fraction"] + } +} +``` + +To add a new system, duplicate one of the existing JSON files, adjust the mapping and toggles, then reference the new system from the command line (see Section 3). + +## 3. Command-Line Interface + +`preprocess.py` expects at least the station identifier. You can optionally specify the station system; otherwise the script infers it from `config/globals.py`. + +```text +usage: preprocess.py -s STATION_ID [-y STATION_SYSTEM] + +options: + -s, --station_id Station code to preprocess (required). + -y, --station_system Station system name (optional). Accepted values are the keys defined in `STATION_SYSTEM_CONFIG` inside `preprocess.py` (currently `INMET`, `ALERTARIO`). +``` + +### Example (direct invocation) +```bash +PYTHONPATH=src python3 src/surface_stations/preprocess.py \ + --station_id A601 \ + --station_system INMET +``` + +### Example (Make target) +```bash +make surface_stations_preprocess \ + STATION_ID=A601 \ + SYSTEM=INMET +``` + +## 4. Processing Steps + +For stations whose system is configured via JSON, the script performs: +1. **Timestamp index creation** using `utils.util.add_datetime_index`. +2. **Column standardisation** according to the system's `column_mapping`. +3. **Feature selection** using `predictor_columns` and `target_column`. +4. **Quality checks** (optional) defined in `quality.checks` to clip, flag or nullify outliers before feature creation. +5. **Feature engineering** toggled per system: + - Wind vector components (`add_wind_related_features`). + - Time-of-day sine/cosine (`add_hour_related_features`). + - Min-max normalisation (`normalize_predictors`). + - KNN-based gap filling (`impute_missing_values`). +6. **Persistence** to `/_preprocessed.parquet.gzip`, where `output_dir` comes from the system definition in `config/globals.py`. +7. **Optional report** (when `report.enabled` is true) saved as `/_preprocess_report.json` with missing-data stats, quality flags and the preprocessing settings applied. + +## 5. Quality Filters (`quality`) + +Each station system may declare hygiene rules in the `quality` section of its JSON. The structure is: + +```json +"quality": { + "enabled": true, + "flag_column_suffix": "_flag", + "include_flag_columns": true, + "checks": [ + { + "type": "bounds", + "name": "temperature_physical_limits", + "columns": ["temperature"], + "min": -60, + "max": 60, + "actions": ["clip", "flag"] + } + ] +} +``` + +- `enabled`: toggles the entire block on/off. When false, the checks are skipped. +- `flag_column_suffix`: suffix used when creating boolean flag columns via the `flag` action. +- `include_flag_columns`: if true, the generated flag columns are appended to the predictor list. +- `checks`: list of rules applied before feature engineering. Common keys: + - `type`: supported values: + - `bounds`: compares against physical limits (`min`, `max`). + - `iqr`: applies the interquartile range rule with optional factor `k` (default 1.5). + - `zscore`: flags absolute z-scores above `threshold` (default 3.0). + - `columns`: explicit list of target columns; defaults to the predictor set. + - `actions`: ordered actions applied to the flagged rows: + - `clip`: truncate values to the computed bounds (`bounds`/`iqr` only). + - `set_nan`: replace flagged values with `NaN` so the imputer can handle them. + - `flag`: create/update a boolean column (``) marking suspect readings. + - `name`: optional label surfaced in the report for readability. + +### Report interpretation + +With `report.enabled` set to true, the generated JSON report contains: + +- `quality_checks`: one entry per rule with `flags` (count), `fraction` (share of rows affected), `flag_column` (if any) and the actions applied. +- `column_metrics.missing_fraction`: share of missing values before imputation; `imputed_fraction` repeats it when an imputation strategy ran. +- Flag columns (`*_flag`) appear in the Parquet output when `include_flag_columns` is enabled, allowing downstream filtering or robust modelling. + +### Quick tips +- Adjust physical limits (e.g., temperature, humidity, wind) per network reality. +- Combine `clip` + `flag` to keep a truncated value while still marking the observation. +- Use `set_nan` together with imputation when you prefer to discard the raw measurement. +- Checks run before normalisation and imputation, so values turned into `NaN` are handled by the configured imputer. + +Warnings are logged if mapped columns or predictors are missing, and the run aborts when the target column cannot be found. + +## 5. Tips and Troubleshooting +- Run with `--station_system` whenever you introduce a new JSON so that the script does not rely solely on inference. +- If you encounter `ModuleNotFoundError: No module named 'config'`, verify that `PYTHONPATH` includes `src` or call the Make target. +- To disable a processing step (for example, wind features on gauge-only stations), set the corresponding flag to `false` in the system JSON. +- After editing JSON files, keep them valid by running a quick lint (`python -m json.tool config/station_systems/.json`). +- Customise the generated report by editing `report.fields` (per-column metrics) and `report.summary` (dataset-level metrics) in each system JSON. +- Combine `quality.checks` and the `actions` list (`flag`, `clip`, `set_nan`) to enforce physical limits or highlight suspect readings before feature engineering. diff --git a/src/surface_stations/README_retrieve.md b/src/surface_stations/README_retrieve.md new file mode 100644 index 00000000..1b7ed450 --- /dev/null +++ b/src/surface_stations/README_retrieve.md @@ -0,0 +1,120 @@ +# Surface Station Data Retrieval + +This directory concentrates the scripts that download ("retrieve") raw observations from the different weather-station systems supported by AtmoSeer. Use this document as a quick reference for the available collectors, their required credentials and typical command lines. + +## Before You Start +- Execute the commands from the project root with the Conda environment activated (e.g. `conda activate atmoseer`). +- Most scripts expect `PYTHONPATH=src`. The examples below set this explicitly; alternatively, use the Make targets that already export it for you. +- Sensitive credentials (API tokens, email/password) are passed through the command line. Prefer exporting them as environment variables and referencing those variables in the examples. + +## Summary of Retrieval Scripts + +| Script | System | Output | Notes | +| --- | --- | --- | --- | +| `retrieve_ws_inmet.py` | INMET automatic stations | `data/ws/inmet/.parquet` | Requires an INMET API token; pulls one or more full years per request. | +| `retrieve_ws_cemaden.py` | Cemaden PCD network | `data/ws/cemaden/raw/.parquet` | Requires credentials; handles token caching (`config/token_demaden.json`). | +| `retrieve_ws_alertario.py` | AlertaRio (COR/RJ) meteorological stations | `data/landing/.csv` | Works on previously downloaded text files under `data/RAW_data/COR/meteorologica`. | +| `retrieve_ws_redemet.py` | REDEMET aerodrome reports | `.csv` + `log.csv` | Requires a DECEA API key; runs hourly requests for the selected time span. | +| `retrieve_ws_websirene.py` | COR/RJ WebSirene pluviometers | `data/ws/websirene/.csv` | Pulls 10-minute rainfall totals for a single numeric station ID via the public XML feed. | + +Each section below details CLI options, expected inputs and a runnable example. + +## INMET - `retrieve_ws_inmet.py` +Downloads hourly observations from the INMET API for one of the stations listed in `config/globals.py`. + +**Requirements** +- INMET API token (`-t/--api_token`). +- Station id (`-s/--station_id`) present in `globals.INMET_WEATHER_STATION_IDS`. +- Begin and end years (`-b/--begin_year`, `-e/--end_year`). The script automatically clamps the end date to "today" to avoid future requests. + +**Usage** +```bash +PYTHONPATH=src python3 src/surface_stations/retrieve_ws_inmet.py \ + --api_token "$INMET_TOKEN" \ + --station_id A601 \ + --begin_year 2019 \ + --end_year 2023 +``` +The resulting Parquet file is written to `data/ws/inmet/A601.parquet`. + +**Make shortcut** +```bash +make inmet_retrieve_ws API_TOKEN="$INMET_TOKEN" STATION_ID=A601 BEGIN_YEAR=2019 END_YEAR=2023 +``` + +## Cemaden - `retrieve_ws_cemaden.py` +Calls the Cemaden REST API to fetch data either by municipality (IBGE code) or by explicit station code. The script manages authentication tokens and persists them in `config/token_demaden.json` to reduce login calls. + +**Requirements** +- Cemaden API credentials (`--email`, `--senha`). +- Either a list of IBGE municipality codes (`--ibge 3304557 3301702`) or a specific station (`--estacao `). +- Optional time bounds (`--inicio YYYY-MM-DD`, `--fim YYYY-MM-DD`). Defaults span from 2015-01-01 to "today". + +**Usage** +```bash +PYTHONPATH=src python3 src/surface_stations/retrieve_ws_cemaden.py \ + --ibge 3304557 \ + --inicio 2023-01-01 \ + --fim 2023-12-31 \ + --email "$CEMADEN_EMAIL" \ + --senha "$CEMADEN_PASSWORD" +``` +When multiple municipalities or stations are requested, one Parquet file per station is created under `data/ws/cemaden/raw/`. + +## AlertaRio - `retrieve_ws_alertario.py` +Processes the monthly text files provided by COR/AlertaRio for the Rio de Janeiro stations. It standardises the fixed-width format, cleans sentinel values and exports hourly CSVs. + +**Requirements** +- Local files organised at `data/RAW_data/COR/meteorologica/` following the naming convention `__Met.txt`. +- Station name via `-s/--station` (use `all` to process the predefined list in `STATION_NAMES_FOR_RJ`). +- Optional year bounds (`-b/--begin`, `-e/--end`). Defaults cover 1997 up to the current year. + +**Usage** +```bash +PYTHONPATH=src python3 src/surface_stations/retrieve_ws_alertario.py \ + --station guaratiba \ + --begin 2018 \ + --end 2024 +``` +Outputs are CSV files in `data/landing/.csv`. Intermediate corrected files are stored under `data/RAW_data/COR/meteorologica/aux_/`. + +## REDEMET - `retrieve_ws_redemet.py` +Retrieves METAR-like observations from the DECEA/REDEMET API for aerodrome stations (e.g. SBGL, SBRJ). The script walks hour-by-hour across the requested time span, logging the status of each request. + +**Requirements** +- Valid REDEMET API key (`-k/--key`). +- ICAO station code (`-s/--station`). +- Start and end datetimes formatted as `AAAAMMDDHH` (`-start/--start_date`, `-end/--end_date`). +- Desired output name (`-o/--output_file`). The script saves `.csv` plus a `log.csv` with the HTTP status per hour. + +**Usage** +```bash +python3 src/surface_stations/retrieve_ws_redemet.py \ + --key "$REDEMET_KEY" \ + --station SBGL \ + --start_date 2023010100 \ + --end_date 2023010723 \ + --output_file data/ws/redemet/SBGL_202301 +``` +If the API returns HTTP 429 (rate limit), the script waits and retries automatically. Large ranges may take considerable time because one request is issued per hour. + +## WebSirene - `retrieve_ws_websirene.py` +Downloads rainfall totals from the COR/RJ WebSirene XML feed for a single station ID, iterating every 10 minutes between the requested timestamps. Useful when you know the numeric identifier exposed in ``. The exported CSV contains the station metadata (`id`, `nome`, `type`, `latitude`, `longitude`) plus the five-minute rainfall total (`rains`, pulled from the XML `m5` field) and the timestamp of the slot. + +**Requirements** +- Start/end datetimes (`--start-date`, `--end-date`) in `DD/MM/YYYY HH:MM` (or `DD-MM-YYYY HH:MM`) format. Each 10-minute slot within the window is requested individually. +- A numeric station identifier (`--station-id`) as listed by WebSirene. +- Optional custom output directory (`--output-dir`, defaults to `data/ws/websirene`). + +**Usage** +```bash +PYTHONPATH=src python3 src/surface_stations/retrieve_ws_websirene.py \ + --start-date "01/01/2024 00:00" \ + --end-date "02/01/2024 23:50" \ + --station-id 22 \ + --output-dir data/ws/websirene +``` +The script caches all successful responses in memory and exports a single chronologically sorted CSV: `data/ws/websirene/22.csv` in the example above. Missing timestamps simply log warnings and are skipped. + +--- +Need to support another station system? Create a new retrieval script beside the ones above and add its documentation to this file so the team can discover it easily. diff --git a/src/surface_stations/README_websirene.md b/src/surface_stations/README_websirene.md new file mode 100644 index 00000000..64a0b535 --- /dev/null +++ b/src/surface_stations/README_websirene.md @@ -0,0 +1,76 @@ +# WebSirene Tools + +Scripts to fetch, export, and visualize WebSirene station data. + +## 1. Historical fetch (`retrieve_ws_websirene.py`) +Downloads historical data (partitioned by station/year) to Parquet or CSV, with rate limiting, optional resume, and ambiguous-date filtering. + +Example: +```bash +PYTHONPATH=src python3 src/surface_stations/retrieve_ws_websirene.py \ + --start-date "01/01/2019 00:00" \ + --end-date "31/12/2019 23:59" \ + --stations all \ + --output-dir data/ws/full \ + --format parquet \ + --rate-per-second 2.5 \ + --block-size-days 3 \ + --ignore-months "6,7,8" \ + --resume +``` +Key flags: +- `--start-date/--end-date` (DD/MM/YYYY HH:MM) +- `--stations` (`all` or comma-separated IDs) +- `--output-dir` for partitioned files +- `--format` (`parquet` or `csv`) +- `--rate-per-second`, `--max-workers`, `--block-size-days`, `--resume` +- `--ignore-months` to skip specific months + +Note: for ambiguous dates (day ≤ 12), the script tries both formats (MM/DD and DD/MM) and keeps only rows whose `observation_datetime.date()` matches the requested date, avoiding swapped month/day. + +## 2. Export a station series (`export_station_series.py`) +Extracts a single station series over a time window and writes Parquet or CSV. + +Example: +```bash +PYTHONPATH=src python3 src/surface_stations/export_station_series.py \ + --station-id 1 \ + --start-date "01/01/2019 00:00" \ + --end-date "31/12/2019 23:59" \ + --format csv \ + --output data/ws/export/station_15_20190101_20191231.csv +``` +Key flags: +- `--station-id` (required) +- `--start-date/--end-date` (DD/MM/YYYY HH:MM) +- `--data-dir` (default `data/ws/full`) +- `--format` (`csv` or `parquet`) +- `--output` (optional; if omitted, writes to `data/ws/export/…`) + +## 3. Interactive animation (`animate_ws_websirene.py`) +Builds a Folium map with a temporal animation of rainfall over a bounding box using `TimestampedGeoJson`. + +Example: +```bash +PYTHONPATH=src python3 src/surface_stations/animate_ws_websirene.py \ + --start-date "08/04/2019 00:00" \ + --end-date "09/04/2019 00:00" \ + --bbox -23.0 -44.5 -22.0 -42.5 \ + --accum-field m15 \ + --frame-duration-ms 1000 \ + --hide-zeros \ + --output-html websirene_animation.html +``` +Key flags: +- `--start-date/--end-date` (DD/MM/YYYY HH:MM) +- `--bbox` (lat_min lon_min lat_max lon_max) +- `--accum-field` (`m5`, `m15`, `h01`, `h04`, `h24`, `h96`) +- `--data-dir` (default `data/ws/full`) +- `--output-html` HTML output path +- `--transition-ms`, `--frame-duration-ms`, `--zoom-start`, `--tiles` +- `--hide-zeros` to omit zero/negative accumulations + +Visual details: +- Categorical colormap based on AlertaRio levels (mm/h): light/none (≤5), moderate (>5–25), strong (>25–50), extreme (>50). +- Small neutral markers show all station locations in the ROI; larger colored markers show rainfall per frame. +- Fixed legend in the lower-left corner. diff --git a/src/surface_stations/__init__.py b/src/surface_stations/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/surface_stations/animate_ws_websirene.py b/src/surface_stations/animate_ws_websirene.py new file mode 100644 index 00000000..eb95b6db --- /dev/null +++ b/src/surface_stations/animate_ws_websirene.py @@ -0,0 +1,382 @@ +""" +Create an animated Folium map for WebSirene precipitation. + +Usage example: +PYTHONPATH=src python3 src/surface_stations/animate_ws_websirene.py \ + --start-date "01/01/2013 00:00" \ + --end-date "03/01/2013 00:00" \ + --bbox "-23.0,-44.5,-22.0,-42.5" \ + --accum-field m15 \ + --output-html websirene_animation.html +""" + +import argparse +import sys +from datetime import datetime +from pathlib import Path +from typing import Iterable + +import folium +import pandas as pd +from branca.colormap import LinearColormap, linear +from folium.plugins import TimestampedGeoJson +# PYTHONPATH is typically set to "src", so we import config directly. +from config.globals import extent + +# Mapping from accumulation field to pandas frequency and ISO8601 period +FIELD_FREQ = { + "m5": ("5min", "PT5M"), + "m15": ("15min", "PT15M"), + "h01": ("1h", "PT1H"), + "h04": ("4h", "PT4H"), + "h24": ("24h", "PT24H"), + "h96": ("96h", "PT96H"), +} +# Window length in minutes for each accumulation field (used to derive mm/h intensity) +FIELD_MINUTES = { + "m5": 5, + "m15": 15, + "h01": 60, + "h04": 240, + "h24": 1440, + "h96": 5760, +} + +# Rain rate categories in mm/h +PRECIPITATION_LEVELS = [ + (0, 5, "Chuva fraca / sem chuva", "#c7e9ff"), + (5, 25, "Chuva moderada", "#fdd49e"), + (25, 50, "Chuva forte", "#f46d43"), + (50, float("inf"), "Chuva extrema", "#b2172b"), +] + + +def add_precipitation_legend(fmap: folium.Map) -> None: + rows = [] + for lower, upper, label, color in PRECIPITATION_LEVELS: + upper_str = "∞" if upper == float("inf") else f"{upper:g}" + rows.append( + f'
' + f'' + f'{label} ({lower:g}–{upper_str} mm/h)' + f"
" + ) + legend_html = ( + '
' + '
Níveis de precipitação (mm/h)
' + + "".join(rows) + + "
" + ) + fmap.get_root().html.add_child(folium.Element(legend_html)) + + +def parse_cli_datetime(raw_datetime: str) -> datetime: + supported_formats = ("%d/%m/%Y %H:%M", "%d-%m-%Y %H:%M") + for fmt in supported_formats: + try: + return datetime.strptime(raw_datetime, fmt) + except ValueError: + continue + raise ValueError( + f"'{raw_datetime}' is not in a supported format (expected DD/MM/YYYY HH:MM or DD-MM-YYYY HH:MM)." + ) + + +def parse_bbox(raw_bbox: list[str]) -> tuple[float, float, float, float]: + # Supports either one token with commas or four separate tokens. + if len(raw_bbox) == 1: + parts = raw_bbox[0].split(",") + else: + parts = raw_bbox + try: + floats = [float(x.strip()) for x in parts] + except ValueError: + raise ValueError("Bounding box must be four numbers: lat_min,lon_min,lat_max,lon_max") + if len(floats) != 4: + raise ValueError("Bounding box must have four values: lat_min,lon_min,lat_max,lon_max") + lat_min, lon_min, lat_max, lon_max = floats + if lat_min >= lat_max or lon_min >= lon_max: + raise ValueError("Invalid bbox: ensure lat_min < lat_max and lon_min < lon_max") + return lat_min, lon_min, lat_max, lon_max + + +def _read_station_file(path: Path, field: str) -> pd.DataFrame: + usecols = ["id", "nome", "latitude", "longitude", "observation_datetime", field] + parse_dates = ["observation_datetime"] + if path.suffix == ".parquet": + return pd.read_parquet(path, columns=usecols) + return pd.read_csv(path, usecols=usecols, parse_dates=parse_dates) + + +def _iter_data_files(base_dir: Path, years: Iterable[int]) -> Iterable[Path]: + for station_dir in base_dir.glob("station_id=*"): + for year in years: + parquet_path = station_dir / f"year={year}" / "data.parquet" + csv_path = station_dir / f"year={year}" / "data.csv" + if parquet_path.exists(): + yield parquet_path + elif csv_path.exists(): + yield csv_path + + +def load_filtered_data( + data_dir: Path, + start_dt: pd.Timestamp, + end_dt: pd.Timestamp, + bbox: tuple[float, float, float, float], + field: str, +) -> pd.DataFrame: + lat_min, lon_min, lat_max, lon_max = bbox + years = range(start_dt.year, end_dt.year + 1) + frames = [] + for path in _iter_data_files(data_dir, years): + try: + df = _read_station_file(path, field) + except Exception: + continue + if df.empty or field not in df.columns: + continue + df["observation_datetime"] = pd.to_datetime(df["observation_datetime"], utc=True, errors="coerce") + df = df.dropna(subset=["latitude", "longitude", field, "observation_datetime"]) + df = df[ + (df["latitude"] >= lat_min) + & (df["latitude"] <= lat_max) + & (df["longitude"] >= lon_min) + & (df["longitude"] <= lon_max) + & (df["observation_datetime"] >= start_dt) + & (df["observation_datetime"] <= end_dt) + ] + if df.empty: + continue + frames.append(df) + if not frames: + return pd.DataFrame(columns=["id", "nome", "latitude", "longitude", "observation_datetime", field]) + return pd.concat(frames, ignore_index=True) + + +def build_features(df: pd.DataFrame, field: str, colormap, freq: str) -> list[dict]: + df = df.copy() + df["frame_time"] = pd.to_datetime(df["observation_datetime"], utc=True).dt.floor(freq) + minutes = FIELD_MINUTES.get(field, 60) + df["rate_mm_h"] = df[field] * 60.0 / minutes + df.sort_values(by="frame_time", inplace=True) + features: list[dict] = [] + for _, row in df.iterrows(): + value = float(row[field]) + rate = float(row["rate_mm_h"]) + color = colormap(rate) + popup = ( + f"{row.get('nome', 'Estacao')}
" + f"{row['frame_time']}
" + f"{field}: {value:.2f} mm
" + f"Intensidade: {rate:.2f} mm/h" + ) + naive_time = row["frame_time"].tz_convert(None) + iso_time = naive_time.isoformat() + hex_color = color if isinstance(color, str) else "#000000" + features.append( + { + "type": "Feature", + "geometry": { + "type": "Point", + "coordinates": [float(row["longitude"]), float(row["latitude"])], + }, + "properties": { + "times": [iso_time], + "popup": popup, + "style": {"color": hex_color, "fillColor": hex_color}, + "icon": "circle", + "iconstyle": { + "fillColor": hex_color, + "fillOpacity": 0.85, + "stroke": True, + "color": hex_color, + "radius": 2.1, # ~30% of original size + }, + }, + } + ) + return features + + +def create_map( + features: list[dict], + bbox: tuple[float, float, float, float], + colormap, + stations_df: pd.DataFrame, + period: str, + transition_ms: int, + duration_ms: int, + tiles: str, + zoom_start: int, +) -> folium.Map: + lat_min, lon_min, lat_max, lon_max = bbox + center_lat = (lat_min + lat_max) / 2 + center_lon = (lon_min + lon_max) / 2 + fmap = folium.Map(location=[center_lat, center_lon], zoom_start=zoom_start - 1 if zoom_start > 1 else zoom_start, tiles=tiles) + duration_js = "undefined" + if duration_ms is not None and duration_ms > 0: + seconds = max(1, round(duration_ms / 1000)) + duration_js = f"\"PT{seconds}S\"" + layer = TimestampedGeoJson( + {"type": "FeatureCollection", "features": features}, + period=period, + transition_time=transition_ms, + duration=None, # overridden below + add_last_point=False, + auto_play=True, + loop=True, + loop_button=True, + time_slider_drag_update=True, + ) + layer.duration = duration_js + layer.add_to(fmap) + # Static location markers for station positions (small, neutral color). + if not stations_df.empty: + loc_group = folium.FeatureGroup(name="Estações (referência)", overlay=True, control=False) + for _, row in stations_df.iterrows(): + folium.CircleMarker( + location=[float(row["latitude"]), float(row["longitude"])], + radius=2, + color="#555", + weight=1, + fill=True, + fill_color="#cccccc", + fill_opacity=0.7, + opacity=0.8, + tooltip=row.get("nome", f"Estação {row.get('id','')}"), + ).add_to(loc_group) + loc_group.add_to(fmap) + folium.Rectangle(bounds=[[lat_min, lon_min], [lat_max, lon_max]], color="#2c7bb6", fill=False).add_to(fmap) + colormap.add_to(fmap) + add_precipitation_legend(fmap) + return fmap + + +def build_arg_parser() -> argparse.ArgumentParser: + parser = argparse.ArgumentParser( + description="Animate WebSirene precipitation using Folium TimestampedGeoJson." + ) + parser.add_argument("--start-date", required=True, help="Start date/time (DD/MM/YYYY HH:MM)") + parser.add_argument("--end-date", required=True, help="End date/time (DD/MM/YYYY HH:MM)") + parser.add_argument( + "--bbox", + nargs="+", + help="Bounding box as lat_min,lon_min,lat_max,lon_max (e.g., '-23.0,-44.5,-22.0,-42.5' or '-23.0 -44.5 -22.0 -42.5'). Defaults to extent in src/config/globals.py when omitted.", + ) + parser.add_argument( + "--accum-field", + choices=list(FIELD_FREQ.keys()), + default="m5", + help="Accumulation field to visualise (controls frame interval).", + ) + parser.add_argument("--data-dir", default="data/ws/full", help="Directory containing partitioned WebSirene data.") + parser.add_argument("--output-html", default="websirene_animation.html", help="Output HTML path for the map.") + parser.add_argument( + "--transition-ms", + type=int, + default=300, + help="Animation transition time between frames (milliseconds).", + ) + parser.add_argument( + "--frame-duration-ms", + type=int, + default=800, + help="How long each frame persists (milliseconds).", + ) + parser.add_argument( + "--hide-zeros", + action="store_true", + help="Hide observations with zero (or negative) accumulation.", + ) + parser.add_argument("--zoom-start", type=int, default=10, help="Initial zoom level for the map.") + parser.add_argument("--tiles", default="cartodbpositron", help="Folium tileset.") + parser.add_argument( + "--max-scale", + type=float, + default=None, + help="Optional fixed upper bound for the color scale; defaults to dataset max.", + ) + return parser + + +def main(): + args = build_arg_parser().parse_args() + try: + start_dt = parse_cli_datetime(args.start_date) + end_dt = parse_cli_datetime(args.end_date) + except ValueError as err: + print(f"Invalid datetime: {err}") + sys.exit(1) + if end_dt < start_dt: + print("End date/time must be greater than or equal to the start date/time.") + sys.exit(1) + if args.bbox: + try: + bbox = parse_bbox(args.bbox) + except ValueError as err: + print(f"Invalid bbox: {err}") + sys.exit(1) + else: + # extent is [lon_min, lat_min, lon_max, lat_max] + lon_min_ext, lat_min_ext, lon_max_ext, lat_max_ext = extent + bbox = (lat_min_ext, lon_min_ext, lat_max_ext, lon_max_ext) + + freq, period = FIELD_FREQ[args.accum_field] + data_dir = Path(args.data_dir) + if not data_dir.exists(): + print(f"Data directory not found: {data_dir}") + sys.exit(1) + + start_ts = pd.to_datetime(start_dt, utc=True) + end_ts = pd.to_datetime(end_dt, utc=True) + df = load_filtered_data(data_dir, start_ts, end_ts, bbox, args.accum_field) + stations_df = df[["id", "nome", "latitude", "longitude"]].drop_duplicates() + if args.hide_zeros: + df = df[df[args.accum_field] > 0] + if df.empty: + print("No data found for the given filters (dates, bbox, accumulation field).") + sys.exit(1) + + # Build a discrete colormap based on AlertaRio thresholds (rates in mm/h). + def alertario_color(rate: float) -> str: + for lower, upper, _, hex_color in PRECIPITATION_LEVELS: + if lower <= rate < upper: + return hex_color + return PRECIPITATION_LEVELS[-1][3] + + # For legend rendering we also keep a discrete colormap for the caption. + # Discrete colormap for legend; last bin covers 50+ mm/h. + colormap = LinearColormap( + colors=[lvl[3] for lvl in PRECIPITATION_LEVELS], + vmin=0, + vmax=50, + index=[0, 5, 25, 50], + ) + colormap.caption = "Intensidade (mm/h) - níveis AlertaRio" + + features = build_features(df, args.accum_field, alertario_color, freq) + if not features: + print("No features to render after filtering. Check date range, bbox, and accumulation field.") + sys.exit(1) + fmap = create_map( + features=features, + bbox=bbox, + colormap=colormap, + stations_df=stations_df, + period=period, + transition_ms=args.transition_ms, + duration_ms=args.frame_duration_ms, + tiles=args.tiles, + zoom_start=args.zoom_start, + ) + output_path = Path(args.output_html) + output_path.parent.mkdir(parents=True, exist_ok=True) + fmap.save(output_path) + print(f"Animation saved to {output_path}") + + +if __name__ == "__main__": + main() diff --git a/src/augment_datasets.py b/src/surface_stations/augment_datasets.py similarity index 55% rename from src/augment_datasets.py rename to src/surface_stations/augment_datasets.py index 0407d46e..2021a6a1 100644 --- a/src/augment_datasets.py +++ b/src/surface_stations/augment_datasets.py @@ -1,36 +1,70 @@ -''' +""" This script merges the train/val/test datasets from two or more user-specified weather stations -''' +""" import argparse -from globals import * -import sys import pickle +import sys + import numpy as np import pandas as pd -from util import haversine_distance -from rainfall import get_events_per_level, OrdinalPrecipitationLevel +from globals import ( + ALERTARIO_WEATHER_STATION_IDS, + DATASETS_DIR, + INMET_WEATHER_STATION_IDS, +) + +from src.utils.util import haversine_distance +from utils.rainfall import OrdinalPrecipitationLevel, get_events_per_level # def get_pos_class_ratio(y): # pos_examples_idxs = np.where(y > 0)[0] # return len(pos_examples_idxs)/len(y) + def print_events_by_level(suffix, y): none_idx, weak_idx, moderate_idx, strong_idx, extreme_idx = get_events_per_level(y) - print(f'{suffix} \t {OrdinalPrecipitationLevel.NONE.name}, {OrdinalPrecipitationLevel.WEAK.name}, {OrdinalPrecipitationLevel.STRONG.name}, {OrdinalPrecipitationLevel.MODERATE.name}, {OrdinalPrecipitationLevel.EXTREME.name}:', end = ' ') - print(f'{y[none_idx].shape[0]}, {y[weak_idx].shape[0]}, {y[moderate_idx].shape[0]}, {y[strong_idx].shape[0]}, {y[extreme_idx].shape[0]}') + print( + f"{suffix} \t {OrdinalPrecipitationLevel.NONE.name}, {OrdinalPrecipitationLevel.WEAK.name}, {OrdinalPrecipitationLevel.STRONG.name}, {OrdinalPrecipitationLevel.MODERATE.name}, {OrdinalPrecipitationLevel.EXTREME.name}:", + end=" ", + ) + print( + f"{y[none_idx].shape[0]}, {y[weak_idx].shape[0]}, {y[moderate_idx].shape[0]}, {y[strong_idx].shape[0]}, {y[extreme_idx].shape[0]}" + ) + def main(argv): parser = argparse.ArgumentParser( description="""This script builds the train/val/test datasets for a given weather station, - by using the user-specified data sources.""", prog=sys.argv[0]) + by using the user-specified data sources.""", + prog=sys.argv[0], + ) # Add an argument to accept the station of interest - parser.add_argument('-s', '--station_id', type=str, required=True, help='id of the station of interest') + parser.add_argument( + "-s", + "--station_id", + type=str, + required=True, + help="id of the station of interest", + ) # Add an argument to accept the pipeline identifier - parser.add_argument('-p', '--pipeline_id', type=str, required=True, help='id of the pipeline') + parser.add_argument( + "-p", "--pipeline_id", type=str, required=True, help="id of the pipeline" + ) # Add an argument to accept one or more identifiers - parser.add_argument('-i', '--identifiers', type=str, nargs='+', help='IDs of one or more weather stations to merge.') - parser.add_argument('-o', '--only_pos', action="store_true", help="Boolean argument. If provided, only positive events (i.e., events with target (rainfall) greater than zero) are used in the augmentation.") + parser.add_argument( + "-i", + "--identifiers", + type=str, + nargs="+", + help="IDs of one or more weather stations to merge.", + ) + parser.add_argument( + "-o", + "--only_pos", + action="store_true", + help="Boolean argument. If provided, only positive events (i.e., events with target (rainfall) greater than zero) are used in the augmentation.", + ) # Parse the arguments args = parser.parse_args() @@ -42,7 +76,10 @@ def main(argv): wsoi_id = args.station_id identifiers = args.identifiers - if not ((wsoi_id in INMET_WEATHER_STATION_IDS) or (wsoi_id in ALERTARIO_WEATHER_STATION_IDS)): + if not ( + (wsoi_id in INMET_WEATHER_STATION_IDS) + or (wsoi_id in ALERTARIO_WEATHER_STATION_IDS) + ): print(f"Invalid station identifier: {wsoi_id}") parser.print_help() sys.exit(2) @@ -51,21 +88,29 @@ def main(argv): # Load numpy arrays (stored in a pickle file) for the WSoI (weather station of interest). filename = DATASETS_DIR + soi_pipeline_id + ".pickle" print(f"Loading train/val/test datasets from {filename} for WSoI.") - file = open(filename, 'rb') - (wsoi_X_train, wsoi_y_train, wsoi_X_val, wsoi_y_val, wsoi_X_test, wsoi_y_test) = pickle.load(file) - print(f'Number of examples (train/val/test): {len(wsoi_X_train)}/{len(wsoi_X_val)}/{len(wsoi_X_test)}.') - print(f"Min values of train/val/test data matrices: {min(wsoi_X_train.reshape(-1,1))}/{min(wsoi_X_val.reshape(-1,1))}/{min(wsoi_X_test.reshape(-1,1))}") - print(f"Max values in the train/val/test data matrices: {max(wsoi_X_train.reshape(-1,1))}/{max(wsoi_X_val.reshape(-1,1))}/{max(wsoi_X_test.reshape(-1,1))}") - print_events_by_level(str(wsoi_id)+"/train", wsoi_y_train) - print_events_by_level(str(wsoi_id)+"/val", wsoi_y_val) - print_events_by_level(str(wsoi_id)+"/test", wsoi_y_test) + file = open(filename, "rb") + (wsoi_X_train, wsoi_y_train, wsoi_X_val, wsoi_y_val, wsoi_X_test, wsoi_y_test) = ( + pickle.load(file) + ) + print( + f"Number of examples (train/val/test): {len(wsoi_X_train)}/{len(wsoi_X_val)}/{len(wsoi_X_test)}." + ) + print( + f"Min values of train/val/test data matrices: {min(wsoi_X_train.reshape(-1, 1))}/{min(wsoi_X_val.reshape(-1, 1))}/{min(wsoi_X_test.reshape(-1, 1))}" + ) + print( + f"Max values in the train/val/test data matrices: {max(wsoi_X_train.reshape(-1, 1))}/{max(wsoi_X_val.reshape(-1, 1))}/{max(wsoi_X_test.reshape(-1, 1))}" + ) + print_events_by_level(str(wsoi_id) + "/train", wsoi_y_train) + print_events_by_level(str(wsoi_id) + "/val", wsoi_y_val) + print_events_by_level(str(wsoi_id) + "/test", wsoi_y_test) print() - + augmented_X_train = wsoi_X_train augmented_y_train = wsoi_y_train augmented_X_val = wsoi_X_val augmented_y_val = wsoi_y_val - + if wsoi_id in INMET_WEATHER_STATION_IDS: stations_filename = "./data/ws/WeatherStations.csv" df_stations = pd.read_csv(stations_filename) @@ -93,22 +138,26 @@ def main(argv): pipeline_id = soi_pipeline_id.replace(wsoi_id, ws_id) filename = DATASETS_DIR + pipeline_id + ".pickle" print(f"Loading train/val/test datasets from {filename}.") - file = open(filename, 'rb') + file = open(filename, "rb") (X_train, y_train, X_val, y_val, _, y_test) = pickle.load(file) - print(f'Number of examples (train/val): {len(X_train)}/{len(X_val)}.') - print(f"Min values of train/val data matrices: {min(X_train.reshape(-1,1))}/{min(X_val.reshape(-1,1))})") - print(f"Max values of train/val data matrices: {max(X_train.reshape(-1,1))}/{max(X_val.reshape(-1,1))}") - print_events_by_level(str(ws_id)+"/train", y_train) - print_events_by_level(str(ws_id)+"/val", y_val) - print_events_by_level(str(ws_id)+"/test", y_test) + print(f"Number of examples (train/val): {len(X_train)}/{len(X_val)}.") + print( + f"Min values of train/val data matrices: {min(X_train.reshape(-1, 1))}/{min(X_val.reshape(-1, 1))})" + ) + print( + f"Max values of train/val data matrices: {max(X_train.reshape(-1, 1))}/{max(X_val.reshape(-1, 1))}" + ) + print_events_by_level(str(ws_id) + "/train", y_train) + print_events_by_level(str(ws_id) + "/val", y_val) + print_events_by_level(str(ws_id) + "/test", y_test) if use_only_pos_examples: temp = len(X_train) y_train_gt_zero_idxs = np.where(y_train > 0)[0] X_train = X_train[y_train_gt_zero_idxs] y_train = y_train[y_train_gt_zero_idxs] - + # y_val_gt_zero_idxs = np.where(y_val > 0)[0] # X_val = X_val[y_val_gt_zero_idxs] # y_val = y_val[y_val_gt_zero_idxs] @@ -118,7 +167,7 @@ def main(argv): # augmented_X_val = np.concatenate((augmented_X_val, X_val)) # augmented_y_val = np.concatenate((augmented_y_val, y_val)) - print(f'Ratio of positive examples: {len(X_train)} of {temp}.') + print(f"Ratio of positive examples: {len(X_train)} of {temp}.") augmented_X_train = np.concatenate((augmented_X_train, X_train)) augmented_y_train = np.concatenate((augmented_y_train, y_train)) @@ -127,20 +176,30 @@ def main(argv): # # Write resulting merged numpy arrays for train/val/test datasets to a single pickle file - print(f'Number of examples in the merged datasets (train/val/test): {len(augmented_X_train)}/{len(augmented_X_val)}/{len(wsoi_X_test)}.') + print( + f"Number of examples in the merged datasets (train/val/test): {len(augmented_X_train)}/{len(augmented_X_val)}/{len(wsoi_X_test)}." + ) print_events_by_level("aug/train", augmented_y_train) print_events_by_level("aug/val", augmented_y_val) print_events_by_level("aug/test", wsoi_y_test) merge_list = "_".join(identifiers) filename = DATASETS_DIR + soi_pipeline_id + "_" + merge_list + ".pickle" - print(f'Dumping merged train/val/test np arrays to pickle file {filename}.', end = " ") - file = open(filename, 'wb') - ndarrays = (augmented_X_train, augmented_y_train, - augmented_X_val, augmented_y_val, - wsoi_X_test, wsoi_y_test) + print( + f"Dumping merged train/val/test np arrays to pickle file {filename}.", end=" " + ) + file = open(filename, "wb") + ndarrays = ( + augmented_X_train, + augmented_y_train, + augmented_X_val, + augmented_y_val, + wsoi_X_test, + wsoi_y_test, + ) pickle.dump(ndarrays, file) - print('Done!') + print("Done!") + if __name__ == "__main__": main(sys.argv) diff --git a/src/surface_stations/build_datasets.py b/src/surface_stations/build_datasets.py new file mode 100644 index 00000000..bc4ab337 --- /dev/null +++ b/src/surface_stations/build_datasets.py @@ -0,0 +1,984 @@ +import argparse +import datetime +import logging +import pickle +import sys +from typing import List + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +import yaml +from era5_data_source import Era5ReanalisysDataSource +from statsmodels.stats.diagnostic import acorr_ljungbox + +import src.utils.util as util +from config import globals +from src.surface_stations.subsampling import apply_subsampling +from src.utils.util import ( + add_missing_indicator_column, + find_contiguous_observation_blocks, + split_dataframe_by_date, +) +from utils.windowing import apply_windowing + +# def format_for_binary_classification(y_train, y_val, y_test): +# y_train_oc = map_to_binary_precipitation_levels(y_train) +# y_val_oc = map_to_binary_precipitation_levels(y_val) +# y_test_oc = map_to_binary_precipitation_levels(y_test) +# return y_train_oc, y_val_oc, y_test_oc + +# def format_for_ordinal_classification(y_train, y_val, y_test): +# y_train_oc = map_to_precipitation_levels(y_train) +# y_val_oc = map_to_precipitation_levels(y_val) +# y_test_oc = map_to_precipitation_levels(y_test) +# return y_train_oc, y_val_oc, y_test_oc + + +def apply_sliding_window(df: pd.DataFrame, target_idx: int, window_size: int): + """ + This function applies the sliding window preprocessing technique to generate data and response + matrices (that is, X and y) from an input time series represented as a pandas DataFrame. This + DataFrame is supposed to have a datetime index that corresponds to the timestamps in the time series. + + @see: https://stackoverflow.com/questions/8269916/what-is-sliding-window-algorithm-examples + + Note that this function takes the eventual existence of gaps in the input time series + into account. In particular, the windowing operation is performed in each separate + contiguous block of observations. + """ + contiguous_observation_blocks = list(find_contiguous_observation_blocks(df)) + + is_first_block = True + + for block in contiguous_observation_blocks: + start = block[0] + end = block[1] + + # logging.info(df[start:end].shape) + if df[start:end].shape[0] < window_size + 1: + continue + + arr = np.array(df[start:end]) + X_block, y_block = apply_windowing( + arr, + initial_time_step=0, + max_time_step=len(arr) - window_size - 1, + window_size=window_size, + target_idx=target_idx, + ) + y_block = y_block.reshape(-1, 1) + if is_first_block: + X = X_block + y = y_block + is_first_block = False + else: + X = np.concatenate((X, X_block), axis=0) + y = np.concatenate((y, y_block), axis=0) + + return X, y + + +def generate_windowed_split(train_df, val_df, test_df, target_name, window_size): + target_idx = train_df.columns.get_loc(target_name) + logging.info(f"Position (index) of target variable {target_name}: {target_idx}") + X_train, y_train = apply_sliding_window(train_df, target_idx, window_size) + X_val, y_val = apply_sliding_window(val_df, target_idx, window_size) + X_test, y_test = apply_sliding_window(test_df, target_idx, window_size) + return X_train, y_train, X_val, y_val, X_test, y_test + + +def get_goes16_data_for_weather_station( + df: pd.DataFrame, max_event: bool = False +) -> pd.DataFrame: + """ + Filters lightning event data in a DataFrame based on latitude and longitude boundaries for a specific weather station + and calculates the maximum or median value of the 'event_energy' column on an hourly basis. + + Args: + df (pd.DataFrame): DataFrame containing lightning event data with columns 'event_energy', 'event_lat', and 'event_lon'. + station_id (str): Identifier for the weather station to filter coordinates. + max_event (bool, optional): Flag to determine whether to calculate the maximum event energy or the median event energy. + Defaults to True, calculating the maximum event energy. + + Returns: + pd.DataFrame: A new DataFrame with the same columns as the input DataFrame, but with lightning events outside of the + specified latitude and longitude boundaries removed, and the maximum or median value of 'event_energy' for each hour. + + """ + + filtered_df = util.min_max_normalize(df) + + result_df = filtered_df[["event_energy"]] + + if max_event: + result_df = result_df.resample("H").max() + else: + result_df = result_df.resample("H").mean() + + return result_df + + +def gaussian_noise(df, column_name, mu=0, sigma=1): + # Generate Gaussian noise + noise = np.random.normal(mu, sigma, size=df.shape[0]) + + # Add noise to the column + df[column_name] = df[column_name] + noise + + return df + + +def add_features_from_user_specified_data_sources( + station_id, fusion_sources: List[str], df_wsoi, min_datetime, max_datetime +): + join_radiosonde_features = "R" in fusion_sources + join_reanalisys_features = "ERA5" in fusion_sources + join_goes16_glm_features = "L" in fusion_sources + join_goes16_tpw_features = "TPW" in fusion_sources + join_goes16_dsi_features = "DSI" in fusion_sources + join_colorcord_features = "I" in fusion_sources + join_conv2d_features = "C" in fusion_sources + join_autoencoder_features = "A" in fusion_sources + + joined_df = df_wsoi + + ############################################################################################ + # ERA5 features + ############################################################################################ + if join_reanalisys_features: + logging.info( + f"Loading reanalisys (ERA5) data near the weather station {station_id}..." + ) + data_source = Era5ReanalisysDataSource() + df_era5_reanalisys = data_source.get_data( + station_id, min_datetime, max_datetime + ) + logging.info(f"Done! Shape = {df_era5_reanalisys.shape}.") + assert not df_era5_reanalisys.isnull().values.any().any() + + joined_df = pd.merge( + joined_df, df_era5_reanalisys, how="left", left_index=True, right_index=True + ) + + logging.info( + f"Reanalisys data successfully joined; resulting shape: {joined_df.shape}." + ) + logging.info(df_wsoi.index.difference(joined_df.index).shape) + logging.info(df_wsoi.index.difference(df_era5_reanalisys.index).shape) + logging.info(df_wsoi.index.difference(df_era5_reanalisys.index)) + logging.info(joined_df.index.difference(df_wsoi.index).shape) + logging.info(df_era5_reanalisys.index.intersection(df_wsoi.index).shape) + logging.info(df_era5_reanalisys.index.difference(df_wsoi.index).shape) + + shape_before_dropna = joined_df.shape + joined_df = joined_df.dropna() + shape_after_dropna = joined_df.shape + logging.info( + f"Removed NaN rows in merged dataset; Shapes before/after dropna: {shape_before_dropna}/{shape_after_dropna}." + ) + + assert not joined_df.isnull().values.any().any() + + ############################################################################################ + # SBGL features + ############################################################################################ + if join_radiosonde_features: + filename = globals.AS_DATA_DIR + "SBGL_indices_1997_2023.parquet.gzip" + logging.info(f"Loading atmospheric sounding indices from {filename}...") + df_as = pd.read_parquet(filename) + logging.info(f"Done! Shape = {df_as.shape}.") + + format_string = "%Y-%m-%d %H:%M:%S" + + # + # Add index to dataframe using the observation's timestamps. + df_as["Datetime"] = pd.to_datetime(df_as["time"], format=format_string) + df_as = df_as.set_index(pd.DatetimeIndex(df_as["Datetime"])) + logging.info( + f"Range of timestamps in the atmospheric sounding data source: [{min(df_as.index)}, {max(df_as.index)}]" + ) + + # + # Remove time-related columns since now this information is in the index. + df_as = df_as.drop(["time", "Datetime"], axis=1) + + joined_df = pd.merge( + joined_df, df_as, how="left", left_index=True, right_index=True + ) + + logging.info( + f"Atmospheric sounding data successfully joined; resulting shape: {joined_df.shape}." + ) + + joined_df = add_missing_indicator_column(joined_df, "asi_idx_missing") + logging.info(f"Shape after adding missing indicator column: {joined_df.shape}.") + + logging.info( + "Doing interpolation to imput missing values on the sounding indices..." + ) + joined_df["cape"] = joined_df["cape"].interpolate(method="linear") + joined_df["cin"] = joined_df["cin"].interpolate(method="linear") + joined_df["lift"] = joined_df["lift"].interpolate(method="linear") + joined_df["k"] = joined_df["k"].interpolate(method="linear") + joined_df["total_totals"] = joined_df["total_totals"].interpolate( + method="linear" + ) + joined_df["showalter"] = joined_df["showalter"].interpolate(method="linear") + logging.info("Done!") + + # At the beggining of the joined dataframe, a few entries may remain with NaN values. + # The code below gets rid of these entries. + # see https://stackoverflow.com/questions/27905295/how-to-replace-nans-by-preceding-or-next-values-in-pandas-dataframe + joined_df.fillna(method="bfill", inplace=True) + + # TODO: data normalization + # TODO: implement interpolation + # TODO: deal with missing values (see https://youtu.be/DKmDJJzayZw) + # TODO: test data imputing with MICE (see https://towardsdatascience.com/imputing-missing-data-with-simple-and-advanced-techniques-f5c7b157fb87) + # TODO: use other sounding stations (?) (see tempo.inmet.gov.br/Sondagem/) + + ############################################################################################ + # TPW features + ############################################################################################ + if join_goes16_tpw_features: + logging.info(f"Loading GOES16 TPW data for WSoI {station_id}...") + df_tpw = pd.read_parquet(f"{globals.TPW_DATA_DIR}/{station_id}.parquet") + logging.info(f"Done! Shape = {df_tpw.shape}.") + + logging.info( + f"Range of timestamps in the TPW data: [{min(df_tpw.index)}, {max(df_tpw.index)}]" + ) + + joined_df = joined_df.join(df_tpw, how="inner") + + logging.info( + f"TPW data successfully joined; resulting shape: {joined_df.shape}." + ) + + # print(joined_df.columns) + + logging.info("Adding missing indicator column...") + joined_df = add_missing_indicator_column(joined_df, "tpw_idx_missing") + logging.info(f"Done! New shape: {joined_df.shape}.") + + logging.info("Doing interpolation to imput missing values on the TPW values...") + joined_df["tpw_value"] = joined_df["tpw_value"].interpolate(method="linear") + logging.info("Done!") + + # At the beggining of the joined dataframe, a few entries may remain with NaN values. + # The code below gets rid of these entries. + # see https://stackoverflow.com/questions/27905295/how-to-replace-nans-by-preceding-or-next-values-in-pandas-dataframe + joined_df.fillna(method="bfill", inplace=True) + + shape_before_dropna = joined_df.shape + joined_df = joined_df.dropna() + shape_after_dropna = joined_df.shape + assert shape_before_dropna == shape_after_dropna + + ############################################################################################ + # DSI features + ############################################################################################ + if join_goes16_dsi_features: + # Remember: (y, x) + wsoi2cell_dict = dict() + wsoi2cell_dict["A627"] = (1, 6) + wsoi2cell_dict["A652"] = (2, 5) + wsoi2cell_dict["A636"] = (2, 4) + wsoi2cell_dict["A621"] = (1, 3) + wsoi2cell_dict["A602"] = (3, 2) + wsoi2cell_dict["A601"] = (0, 1) + + associated_cell = wsoi2cell_dict[station_id] + + logging.info(f"Loading GOES16 DSI data for WSoI {station_id}...") + dsi_variable_names = ["CAPE", "LI", "TT", "SI", "KI"] + features_dict = dict() + for variable_name in dsi_variable_names: + logging.info(f"Adding feature - {variable_name}...") + df_dsi = pd.read_parquet( + f"{globals.DSI_DATA_DIR}/DSI_{variable_name}_1H.parquet" + ) + logging.info(f"Done! Shape = {df_dsi.shape}.") + + logging.info( + f"Range of timestamps in the DSI data: [{min(df_dsi.index)}, {max(df_dsi.index)}]" + ) + + column_name = f"{variable_name}{associated_cell[0]}{associated_cell[1]}" + + features_dict[variable_name] = df_dsi[column_name] + + # Transform the dictionary into a DataFrame + df_dsi_features = pd.DataFrame(features_dict) + logging.info( + f"Dataframe of features create with shape {df_dsi_features.shape}." + ) + + df_dsi_features.to_parquet("dsi_features.parquet") + # assert (not df_dsi_features.isnull().values.any().any()) + + # joined_df = joined_df.join(df_dsi_features, how='inner') + joined_df = joined_df.merge( + df_dsi_features, how="left", left_index=True, right_index=True + ) + + logging.info( + f"DSI features successfully joined; resulting shape: {joined_df.shape}." + ) + logging.info( + f"|wsoi - dsi_features|: {df_wsoi.index.difference(df_dsi_features.index).shape}" + ) + logging.info( + f"|dsi_features - wsoi|: {df_dsi_features.index.difference(df_wsoi.index).shape}" + ) + logging.info(df_wsoi.index.difference(joined_df.index).shape) + logging.info(joined_df.index.difference(df_wsoi.index).shape) + logging.info(df_dsi_features.index.intersection(df_wsoi.index).shape) + logging.info("") + logging.info( + f"wsoi - dsi_features:\n {df_wsoi.index.difference(df_dsi_features.index)}" + ) + # assert(False) + + assert not joined_df.isnull().values.any().any() + + if join_goes16_glm_features: + print( + f"Loading GLM (Goes 16) data near the weather station {station_id}...", + end="", + ) + df_lightning = pd.read_parquet( + f"data/parquet_files/glm_{station_id}_preprocessed_file.parquet" + ) + df_lightning_filtered = get_goes16_data_for_weather_station(df_lightning) + print(df_lightning_filtered.isnull().sum()) + df_lightning_filtered.fillna(method="bfill", inplace=True) + assert not df_lightning_filtered.isnull().values.any().any() + joined_df = pd.merge( + df_wsoi, + df_lightning_filtered, + how="left", + left_index=True, + right_index=True, + ) + + joined_df["event_energy"].fillna(method="bfill", inplace=True) + + # Ruido branco + lb_test_stat = acorr_ljungbox(joined_df["event_energy"], lags=10) + print("Estatísticas do Teste:", lb_test_stat) + plt.axhline(y=0.05, color="r", linestyle="--") + plt.title("Valores p do Teste de Ljung-Box") + plt.xlabel("Lag") + plt.ylabel("Valor p") + plt.show() + + print(f"GLM data successfully joined; resulting shape = {joined_df.shape}.") + print(df_wsoi.index.difference(joined_df.index).shape) + print(joined_df.index.difference(df_wsoi.index).shape) + + print(df_lightning_filtered.index.intersection(df_wsoi.index).shape) + print(df_lightning_filtered.index.difference(df_wsoi.index).shape) + print(df_wsoi.index.difference(df_lightning_filtered.index).shape) + print(df_wsoi.index.difference(df_lightning_filtered.index)) + + shape_before_dropna = joined_df.shape + joined_df = joined_df.dropna() + shape_after_dropna = joined_df.shape + print( + f"Removed NaN rows in merge data; Shapes before/after dropna: {shape_before_dropna}/{shape_after_dropna}." + ) + + assert not joined_df.isnull().values.any().any() + + if join_colorcord_features: + filename = f"FEATURE_{station_id}_COLORCORD.csv" + logging.info(f"Loading image features {filename}...") + df_new = pd.read_csv(filename) + logging.info(f"Done! Shape = {df_new.shape}.") + df_new["date"] = pd.to_datetime(df_new["date"], format="%Y-%m-%d--%H%M%S") + df_new["date"] = df_new["date"].dt.floor("H") + del df_new["Estação"] + df_new = df_new.groupby("date", as_index=False).mean() + + format_string = "%Y-%m-%d %H:%M:%S" + + df_new["Datetime"] = pd.to_datetime(df_new["date"], format=format_string) + df_new = df_new.set_index(pd.DatetimeIndex(df_new["Datetime"])) + logging.info( + f"Range of timestamps in the image feature data source: [{min(df_new.index)}, {max(df_new.index)}]" + ) + + df_new = df_new.drop(["date", "Datetime", "Estação"], axis=1) + joined_df = pd.merge( + joined_df, df_new, how="left", left_index=True, right_index=True + ) + joined_df = joined_df.fillna(0) + + logging.info( + f"Image features data successfully joined; resulting shape: {joined_df.shape}." + ) + + elif join_conv2d_features: + filename = f"FEATURE_{station_id}_CONV2D.csv" + logging.info(f"Loading image features {filename}...") + df_new = pd.read_csv(filename) + logging.info(f"Done! Shape = {df_new.shape}.") + df_new["date"] = pd.to_datetime(df_new["date"], format="%Y-%m-%d--%H%M%S") + df_new["date"] = df_new["date"].dt.floor("H") + del df_new["Estação"] + df_new = df_new.groupby("date", as_index=False).mean() + + format_string = "%Y-%m-%d %H:%M:%S" + + df_new["Datetime"] = pd.to_datetime(df_new["date"], format=format_string) + df_new = df_new.set_index(pd.DatetimeIndex(df_new["Datetime"])) + logging.info( + f"Range of timestamps in the image feature data source: [{min(df_new.index)}, {max(df_new.index)}]" + ) + + df_new = df_new.drop(["date", "Datetime"], axis=1) + joined_df = pd.merge( + joined_df, df_new, how="left", left_index=True, right_index=True + ) + joined_df = joined_df.fillna(0) + + logging.info( + f"Image features data successfully joined; resulting shape: {joined_df.shape}." + ) + + elif join_autoencoder_features: + filename = f"FEATURE_{station_id}_AUTOENCODER.csv" + logging.info(f"Loading image features {filename}...") + df_new = pd.read_csv(filename) + logging.info(f"Done! Shape = {df_new.shape}.") + df_new["date"] = pd.to_datetime(df_new["date"], format="%Y-%m-%d--%H%M%S") + df_new["date"] = df_new["date"].dt.ceil("H") + del df_new["Estação"] + df_new = df_new.groupby("date", as_index=False).mean() + + format_string = "%Y-%m-%d %H:%M:%S" + + df_new["Datetime"] = pd.to_datetime(df_new["date"], format=format_string) + df_new = df_new.set_index(pd.DatetimeIndex(df_new["Datetime"])) + logging.info( + f"Range of timestamps in the image feature data source: [{min(df_new.index)}, {max(df_new.index)}]" + ) + + df_new = df_new.drop(["date", "Datetime"], axis=1) + joined_df = pd.merge( + joined_df, df_new, how="left", left_index=True, right_index=True + ) + joined_df = joined_df.fillna(0) + + logging.info( + f"Image features data successfully joined; resulting shape: {joined_df.shape}." + ) + + assert not joined_df.isnull().values.any().any() + + return joined_df + + +def build_datasets( + station_id: str, + input_folder: str, + train_start_threshold: datetime.datetime, + train_test_threshold: datetime.datetime, + test_end_threshold: datetime.datetime, + fusion_sources: List[str], + # join_AS_data_source: bool, + # join_reanalisys_datasource: bool, + # join_goes16_glm_datasource: bool, + # join_goes16_tpw_datasource: bool, + # join_colorcord_datasource: bool, + # join_conv2d_datasource: bool, + # join_autoencoder_datasource: bool, + subsampling_procedure: str, +): + """ + This function builds the train, validation and test datasets. These resulting datasets will used to fit the parameters + of precipitation models down the AtmoSeer pipeline. Notice that there is always a Weather Station of Interest (WSoI), + that is, a weather station that will provide the values of the target variable (in our case, precipitation) and + also some features (predictors). + + This function can *optionally* use a set of extra data sources to build the datasets. Each data source contributes + with a group of additional features. Notice that these extra data sources are not mandatory. Indeed, it can be the + case that the only features used are the ones extracted from the WSoI. + """ + + pipeline_id = station_id + if fusion_sources is not None: + if "ERA5" in fusion_sources: + pipeline_id = pipeline_id + "_ERA5" + if "R" in fusion_sources: + pipeline_id = pipeline_id + "_R" + if "L" in fusion_sources: + pipeline_id = pipeline_id + "_L" + if "DSI" in fusion_sources: + pipeline_id = pipeline_id + "_DSI" + if "TPW" in fusion_sources: + pipeline_id = pipeline_id + "_TPW" + if "I" in fusion_sources: + pipeline_id = pipeline_id + "_I" + if "C" in fusion_sources: + pipeline_id = pipeline_id + "_C" + if "A" in fusion_sources: + pipeline_id = pipeline_id + "_A" + # if join_reanalisys_datasource: + # pipeline_id = pipeline_id + '_N' + # if join_AS_data_source: + # pipeline_id = pipeline_id + '_R' + # if join_goes16_glm_datasource: + # pipeline_id = pipeline_id + '_L' + # if join_goes16_tpw_datasource: + # pipeline_id = pipeline_id + '_T' + # if join_colorcord_datasource: + # pipeline_id = pipeline_id + '_I' + # if join_conv2d_datasource: + # pipeline_id = pipeline_id + '_C' + # if join_autoencoder_datasource: + # pipeline_id = pipeline_id + '_A' + + logging.info(f"Loading observations for weather station {station_id}...") + df_wsoi = pd.read_parquet(input_folder + station_id + "_preprocessed.parquet.gzip") + logging.info(f"Done! Shape = {df_wsoi.shape}.\n") + + #### + # Apply a filtering step to disregard all observations before a user-specified timestamp. + # This is useful when doing training experiments with datasources whose start of operation + # was AFTER the one corresponding to the WSoI. + #### + if train_start_threshold is not None: + logging.info("Applying start threshold filtering...") + logging.info( + f"Timestamp from which examples will be considered: {train_start_threshold}" + ) + shape_before_filtering = df_wsoi.shape + df_wsoi = df_wsoi[df_wsoi.index >= train_start_threshold] + shape_after_filtering = df_wsoi.shape + logging.info( + f"Done! Shapes before/after: {shape_before_filtering}/{shape_after_filtering}\n" + ) + + #### + # Apply a filtering step to disregard all observations after a user-specified timestamp. + #### + if test_end_threshold is not None: + logging.info("Applying end threshold filtering...") + logging.info( + f"Timestamp up until which examples will be considered: {test_end_threshold}" + ) + shape_before_filtering = df_wsoi.shape + df_wsoi = df_wsoi[df_wsoi.index <= test_end_threshold] + shape_after_filtering = df_wsoi.shape + logging.info( + f"Done! Shapes before/after: {shape_before_filtering}/{shape_after_filtering}\n" + ) + + #### + # Apply a filtering step, with the purpose of disregarding all observations made between + # what we consider to be the drought period of a year (months of June, July, and August). + #### + # TODO: parameterize with user-defined months. + logging.info("Applying month filtering...") + shape_before_month_filtering = df_wsoi.shape + df_wsoi = df_wsoi[ + df_wsoi.index.month.isin([9, 10, 11, 12, 1, 2, 3, 4, 5]) + ].sort_index(ascending=True) + shape_after_month_filtering = df_wsoi.shape + logging.info( + f"Done! Shapes before/after: {shape_before_month_filtering}/{shape_after_month_filtering}\n" + ) + + assert not df_wsoi.isnull().values.any().any() + + ##### + # Start with the mandatory data source (i.e., the one represented by the weather + # station of interest) and sequentially join the other user-specified datasources. + ##### + joined_df = df_wsoi + min_timestamp = min(joined_df.index) + max_timestamp = max(joined_df.index) + logging.info( + f"Range of timestamps after applying temporal filtering: ({min_timestamp}, {max_timestamp})\n" + ) + + ##### + # Now add features from the user-specified data sources, if any. + ##### + if fusion_sources is not None: + logging.info( + "Going to add features from the user-specified data sources (if any)..." + ) + joined_df = add_features_from_user_specified_data_sources( + station_id, + fusion_sources, + # join_AS_data_source, + # join_reanalisys_datasource, + # join_goes16_glm_datasource, + # join_goes16_tpw_datasource, + # join_colorcord_datasource, + # join_conv2d_datasource, + # join_autoencoder_datasource, + df_wsoi, + min_timestamp, + max_timestamp, + ) + min_timestamp = min(joined_df.index) + max_timestamp = max(joined_df.index) + logging.info( + f"Done! New range of timestamps: ({min_timestamp}, {max_timestamp})\n" + ) + + # + # Save train/val/test dataFrames for future error analisys. + filename = globals.DATASETS_DIR + pipeline_id + ".parquet.gzip" + logging.info( + f"Saving joined dataframe for pipeline {pipeline_id} to file {filename}." + ) + joined_df.to_parquet(filename, compression="gzip") + logging.info("Done!\n") + + assert not joined_df.isnull().values.any().any() + + ##### + # Perform train/val/test split + ##### + logging.info("Going to split examples (train/val/test)...") + logging.info( + f"Timestamp used to split train and test examples: {train_test_threshold}" + ) + df_train_val, df_test = split_dataframe_by_date(joined_df, train_test_threshold) + + # TODO: parameterize with user-defined train/val splitting proportion. + n = len(df_train_val) + train_val_splitting_proportion = 0.8 + train_upper_limit = int(n * train_val_splitting_proportion) + df_train = df_train_val[0:train_upper_limit] + df_val = df_train_val[train_upper_limit:] + + assert not df_train.isnull().values.any().any() + assert not df_val.isnull().values.any().any() + assert not df_test.isnull().values.any().any() + + logging.info( + f"Range of timestamps in the training dataset: [{min(df_train.index)}, {max(df_train.index)}]" + ) + logging.info( + f"Range of timestamps in the validation dataset: [{min(df_val.index)}, {max(df_val.index)}]" + ) + logging.info( + f"Range of timestamps in the test dataset: [{min(df_test.index)}, {max(df_test.index)}]" + ) + logging.info( + f"Number of examples in each dataset (train/val/test): {len(df_train)}/{len(df_val)}/{len(df_test)}." + ) + logging.info("Done!\n") + + # + # Save train/val/test observations for future error analisys. + logging.info( + f"Saving each train/val/test dataset for pipeline {pipeline_id} as a parquet file." + ) + df_train.to_parquet( + globals.DATASETS_DIR + pipeline_id + "_train.parquet.gzip", compression="gzip" + ) + df_val.to_parquet( + globals.DATASETS_DIR + pipeline_id + "_val.parquet.gzip", compression="gzip" + ) + df_test.to_parquet( + globals.DATASETS_DIR + pipeline_id + "_test.parquet.gzip", compression="gzip" + ) + logging.info("Done!\n") + + assert not df_train.isnull().values.any().any() + assert not df_val.isnull().values.any().any() + assert not df_test.isnull().values.any().any() + + if station_id in globals.ALERTARIO_GAUGE_STATION_IDS: + df_train = gaussian_noise(df_train, "barometric_pressure", mu=1000) + df_val = gaussian_noise(df_val, "barometric_pressure", mu=1000) + df_test = gaussian_noise(df_test, "barometric_pressure", mu=1000) + + # + # Normalize the columns in train/val/test dataframes. This is done as a preparation step for applying + # the sliding window technique, since the target variable is going to be used as lag feature. + # (see, e.g., https://www.mikulskibartosz.name/forecasting-time-series-using-lag-features/) + # (see also https://datascience.stackexchange.com/questions/72480/what-is-lag-in-time-series-forecasting) + logging.info("Normalizing the features in train/val/test dataframes...") + _, target_name = util.get_relevant_variables(station_id) + min_target_value_in_train, max_target_value_in_train = ( + min(df_train[target_name]), + max(df_train[target_name]), + ) + min_target_value_in_val, max_target_value_in_val = ( + min(df_val[target_name]), + max(df_val[target_name]), + ) + min_target_value_in_test, max_target_value_in_test = ( + min(df_test[target_name]), + max(df_test[target_name]), + ) + df_train = util.min_max_normalize(df_train) + df_val = util.min_max_normalize(df_val) + df_test = util.min_max_normalize(df_test) + logging.info("Done!\n") + + assert not df_train.isnull().values.any().any() + assert not df_val.isnull().values.any().any() + assert not df_test.isnull().values.any().any() + + # + # Apply sliding window method to build examples (instances) of train/val/test datasets + with open("./config/config.yaml", "r") as file: + config = yaml.safe_load(file) + window_size = config["preproc"]["SLIDING_WINDOW_SIZE"] + logging.info("Applying sliding window to build train/val/test datasets...") + X_train, y_train, X_val, y_val, X_test, y_test = generate_windowed_split( + df_train, df_val, df_test, target_name, window_size + ) + logging.info("Resulting shapes:") + logging.info( + f" - (X_train/X_val/X_test): ({X_train.shape}/{X_val.shape}/{X_test.shape})" + ) + logging.info( + f" - (y_train/y_val/y_test): ({y_train.shape}/{y_val.shape}/{y_test.shape})" + ) + logging.info("Done!\n") + + assert not np.isnan(np.sum(X_train)) + assert not np.isnan(np.sum(X_val)) + assert not np.isnan(np.sum(X_test)) + assert not np.isnan(np.sum(y_train)) + assert not np.isnan(np.sum(y_val)) + assert not np.isnan(np.sum(y_test)) + + # + # Now, we restore the target variable to its original values. This is needed in case a multiclass + # classification task is defined down the pipeline. + logging.info("Restoring the target variable to its original values...") + y_train = (y_train + min_target_value_in_train) * ( + max_target_value_in_train - min_target_value_in_train + ) + y_val = (y_val + min_target_value_in_val) * ( + max_target_value_in_val - min_target_value_in_val + ) + y_test = (y_test + min_target_value_in_test) * ( + max_target_value_in_test - min_target_value_in_test + ) + logging.info( + "Min precipitation values (train/val/test): %.5f, %.5f, %.5f" + % (np.min(y_train), np.min(y_val), np.min(y_test)) + ) + logging.info( + "Max precipitation values (train/val/test): %.5f, %.5f, %.5f" + % (np.max(y_train), np.max(y_val), np.max(y_test)) + ) + logging.info("Done!\n") + + if subsampling_procedure != "NONE": + # + # Subsampling + logging.info("**********Subsampling************") + logging.info( + f"- Shapes before subsampling (y_train/y_val/y_test): {y_train.shape}, {y_val.shape}, {y_test.shape}" + ) + logging.info("Subsampling train data.") + X_train, y_train = apply_subsampling(X_train, y_train, subsampling_procedure) + logging.info("Subsampling val data...") + + X_val, y_val = apply_subsampling(X_val, y_val, "NEGATIVE") + logging.info( + "- Min precipitation values (train/val/test) after subsampling: %.5f, %.5f, %.5f" + % (np.min(y_train), np.min(y_val), np.min(y_test)) + ) + + logging.info( + "- Max precipitation values (train/val/test) after subsampling: %.5f, %.5f, %.5f" + % (np.max(y_train), np.max(y_val), np.max(y_test)) + ) + logging.info( + f"- Shapes (y_train/y_val/y_test) after subsampling: {y_train.shape}, {y_val.shape}, {y_test.shape}" + ) + logging.info("Done!\n") + + # + # Write numpy arrays for train/val/test dataset to a single pickle file + logging.info(f"Dumping train/val/test np arrays to pickle file {filename}...") + logging.info( + f"Number of examples (train/val/test): {len(X_train)}/{len(X_val)}/{len(X_test)}." + ) + filename = globals.DATASETS_DIR + pipeline_id + ".pickle" + file = open(filename, "wb") + ndarrays = (X_train, y_train, X_val, y_val, X_test, y_test) + pickle.dump(ndarrays, file) + logging.info("Done!\n") + + logging.info("Done it all!") + + +def main(argv): + parser = argparse.ArgumentParser( + description="""This script builds the train/val/test datasets for a given weather station, by using the user-specified data sources.""" + ) + parser.add_argument( + "-s", "--station_id", type=str, required=True, help="station id" + ) + parser.add_argument( + "-tt", + "--train_test_threshold", + type=str, + required=True, + help="The limiting date between train and test examples (format: YYYY-MM-DD).", + ) + parser.add_argument( + "-b", + "--train_start_threshold", + type=str, + required=False, + help="The lower limiting date from which to consider examples (format: YYYY-MM-DD).", + ) + parser.add_argument( + "-e", + "--test_end_threshold", + type=str, + required=False, + help="The upper limiting date from which to consider examples (format: YYYY-MM-DD).", + ) + parser.add_argument( + "-d", + "--datasources", + nargs="+", + type=str, + help="List of data sources to fuse with", + ) + parser.add_argument( + "-sp", + "--subsampling_procedure", + type=str, + default="NONE", + help="Subsampling procedure do be applied.", + ) + args = parser.parse_args(argv[1:]) + + station_id = args.station_id + fusion_sources = args.datasources + subsampling_procedure = args.subsampling_procedure + + try: + train_start_threshold = args.train_start_threshold + if train_start_threshold is not None: + train_start_threshold = pd.to_datetime(args.train_start_threshold) + except pd.errors.ParserError: + print(f"Invalid date format: {args.train_start_threshold}.") + parser.print_help() + sys.exit(2) + + try: + if ( + station_id in globals.ALERTARIO_WEATHER_STATION_IDS + or station_id in globals.ALERTARIO_GAUGE_STATION_IDS + ): + train_test_threshold = pd.to_datetime( + args.train_test_threshold, utc=True + ) # This UTC thing is really anonying! + else: + train_test_threshold = pd.to_datetime(args.train_test_threshold) + except pd.errors.ParserError: + print(f"Invalid date format: {args.train_test_threshold}.") + parser.print_help() + sys.exit(2) + + try: + test_end_threshold = args.test_end_threshold + if test_end_threshold is not None: + test_end_threshold = pd.to_datetime(args.test_end_threshold) + except pd.errors.ParserError: + print(f"Invalid date format: {args.train_start_threshold}.") + parser.print_help() + sys.exit(2) + + assert (train_start_threshold <= train_test_threshold) and ( + train_test_threshold <= test_end_threshold + ) + + lst_subsampling_procedures = ["NONE", "NAIVE", "NEGATIVE"] + if subsampling_procedure not in lst_subsampling_procedures: + print( + f"Invalid subsampling procedure: {subsampling_procedure}. Valid values: {lst_subsampling_procedures}" + ) + parser.print_help() + sys.exit(2) + + if not ( + (station_id in globals.INMET_WEATHER_STATION_IDS) + or (station_id in globals.ALERTARIO_WEATHER_STATION_IDS) + or (station_id in globals.ALERTARIO_GAUGE_STATION_IDS) + ): + print(f"Invalid station identifier: {station_id}") + parser.print_help() + sys.exit(2) + + if station_id in globals.INMET_WEATHER_STATION_IDS: + input_folder = globals.WS_INMET_DATA_DIR + elif station_id in globals.ALERTARIO_WEATHER_STATION_IDS: + input_folder = globals.WS_ALERTARIO_DATA_DIR + elif station_id in globals.ALERTARIO_GAUGE_STATION_IDS: + # Its a gauge station. + input_folder = globals.GS_ALERTARIO_DATA_DIR + + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.DEBUG, format=fmt) + + # join_goes16_tpw_data_source = False + # join_goes16_dsi_data_source = False + # join_as_data_source = False + # join_nwp_data_source = False + # join_lightning_data_source = False + # join_colorcord_data_source = False + # join_conv2d_data_source = False + # join_autoencoder_data_source = False + + # fusion_list = list() + # if datasources: + # if 'R' in datasources: + # join_as_data_source = True + # if 'ERA5' in datasources: + # join_nwp_data_source = True + # if 'L' in datasources: + # join_lightning_data_source = True + # if 'TPW' in datasources: + # join_goes16_tpw_data_source = True + # if 'DSI' in datasources: + # join_goes16_dsi_data_source = True + # if "I" in datasources: + # join_colorcord_data_source = True + # if "C" in datasources: + # join_conv2d_data_source = True + # if "A" in datasources: + # join_autoencoder_data_source = True + + assert (station_id is not None) and (station_id != "") + + build_datasets( + station_id, + input_folder, + train_start_threshold, + train_test_threshold, + test_end_threshold, + fusion_sources, + # join_as_data_source, + # join_nwp_data_source, + # join_lightning_data_source, + # join_goes16_tpw_data_source, + # join_colorcord_data_source, + # join_conv2d_data_source, + # join_autoencoder_data_source, + subsampling_procedure, + ) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/surface_stations/build_datasets_cemaden.py b/src/surface_stations/build_datasets_cemaden.py new file mode 100644 index 00000000..c474ec49 --- /dev/null +++ b/src/surface_stations/build_datasets_cemaden.py @@ -0,0 +1,160 @@ +import argparse +import datetime +import logging +import os +import pickle +import sys + +import numpy as np +import pandas as pd +import yaml + +from config import globals + + +def split_dataframe_by_date(df, threshold_date): + threshold_date = pd.to_datetime(threshold_date).tz_localize("UTC") + df_train_val = df[df.index < threshold_date] + df_test = df[df.index >= threshold_date] + return df_train_val, df_test + + +def min_max_normalize(df): + return (df - df.min()) / (df.max() - df.min()) + + +def restore_target(y, df_ref, target_col): + min_y = df_ref[target_col].min() + max_y = df_ref[target_col].max() + return (y * (max_y - min_y)) + min_y + + +def apply_subsampling(X, y, method): + if method == "NAIVE": + # Exemplo: mantém apenas 50% dos exemplos com chuva < 1 + mask = y >= 1 + non_rain_idx = y < 1 + sampled_non_rain_idx = np.random.choice( + np.where(non_rain_idx)[0], size=int(len(non_rain_idx) * 0.5), replace=False + ) + selected_idx = np.concatenate([np.where(mask)[0], sampled_non_rain_idx]) + return X[selected_idx], y[selected_idx] + elif method == "NEGATIVE": + return X[y > 0], y[y > 0] + return X, y + + +def generate_windowed_split(df_train, df_val, df_test, target_name, window_size): + def create_X_y(df): + X, y = [], [] + for i in range(window_size, len(df)): + X.append(df.iloc[i - window_size : i].values) + y.append(df.iloc[i][target_name]) + return np.array(X), np.array(y) + + return (*create_X_y(df_train), *create_X_y(df_val), *create_X_y(df_test)) + + +def build_datasets( + station_id: str, + input_folder: str, + train_start_threshold: datetime.datetime, + train_test_threshold: datetime.datetime, + test_end_threshold: datetime.datetime, + subsampling_procedure: str, +): + df = pd.read_parquet( + os.path.join(input_folder, f"{station_id}_preprocessed.parquet.gzip") + ) + + train_start_threshold = pd.to_datetime(train_start_threshold).tz_localize("UTC") + test_end_threshold = pd.to_datetime(test_end_threshold).tz_localize("UTC") + if train_start_threshold: + df = df[df.index >= train_start_threshold] + if test_end_threshold: + df = df[df.index <= test_end_threshold] + + df = df[df.index.month.isin([9, 10, 11, 12, 1, 2, 3, 4, 5])] + + _min_timestamp, _max_timestamp = df.index.min(), df.index.max() + + os.makedirs(globals.DATASETS_DIR, exist_ok=True) + filename_base = globals.DATASETS_DIR + f"{station_id}" + df.to_parquet(f"{filename_base}.parquet.gzip", compression="gzip") + + df_train_val, df_test = split_dataframe_by_date(df, train_test_threshold) + n = len(df_train_val) + train_cut = int(n * 0.8) + df_train = df_train_val[:train_cut] + df_val = df_train_val[train_cut:] + + df_train.to_parquet(f"{filename_base}_train.parquet.gzip") + df_val.to_parquet(f"{filename_base}_val.parquet.gzip") + df_test.to_parquet(f"{filename_base}_test.parquet.gzip") + + target_name = "precipitation" + df_train = min_max_normalize(df_train) + df_val = min_max_normalize(df_val) + df_test = min_max_normalize(df_test) + + with open("config/config.yaml", "r") as f: + window_size = yaml.safe_load(f)["preproc"]["SLIDING_WINDOW_SIZE"] + + X_train, y_train, X_val, y_val, X_test, y_test = generate_windowed_split( + df_train, df_val, df_test, target_name, window_size + ) + + y_train = restore_target(y_train, df_train, target_name) + y_val = restore_target(y_val, df_val, target_name) + y_test = restore_target(y_test, df_test, target_name) + + if subsampling_procedure != "NONE": + X_train, y_train = apply_subsampling(X_train, y_train, subsampling_procedure) + X_val, y_val = apply_subsampling(X_val, y_val, "NEGATIVE") + + with open(f"{filename_base}.pickle", "wb") as f: + pickle.dump((X_train, y_train, X_val, y_val, X_test, y_test), f) + + logging.info("Processamento concluído com sucesso.") + + +def main(argv): + parser = argparse.ArgumentParser() + parser.add_argument("-s", "--station_id", required=True) + parser.add_argument("-tt", "--train_test_threshold", required=True) + parser.add_argument("-b", "--train_start_threshold") + parser.add_argument("-e", "--test_end_threshold") + parser.add_argument("-sp", "--subsampling_procedure", default="NONE") + + args = parser.parse_args(argv[1:]) + input_folder = globals.CEMADEN_DATA_DIR + "/preprocessed/" + + try: + ttt = pd.to_datetime(args.train_test_threshold) + tst = ( + pd.to_datetime(args.train_start_threshold) + if args.train_start_threshold + else None + ) + tet = ( + pd.to_datetime(args.test_end_threshold) if args.test_end_threshold else None + ) + except Exception as e: + print("Erro ao converter datas:", str(e)) + parser.print_help() + sys.exit(1) + + build_datasets( + station_id=args.station_id, + input_folder=input_folder, + train_start_threshold=tst, + train_test_threshold=ttt, + test_end_threshold=tet, + subsampling_procedure=args.subsampling_procedure, + ) + + +if __name__ == "__main__": + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.INFO, format=fmt) + main(sys.argv) diff --git a/src/surface_stations/cemaden_mapa.py b/src/surface_stations/cemaden_mapa.py new file mode 100644 index 00000000..047b3582 --- /dev/null +++ b/src/surface_stations/cemaden_mapa.py @@ -0,0 +1,45 @@ +import folium +import requests + +from src.surface_stations.retrieve_ws_cemaden import get_token +from src.utils.env_loader import get_cemaden_credentials + +url = "https://sws.cemaden.gov.br/PED/rest/pcds-cadastro/dados-cadastrais" + +nome_secreto, senha_secreta = get_cemaden_credentials() +token = get_token(nome_secreto, senha_secreta) +codibge = "3304557" + +headers = {"token": token} + +params = {"codibge": codibge, "formato": "json"} + +response = requests.get(url, headers=headers, params=params) +posicoes = {} +if response.status_code == 200: + estacoes = response.json() + print("Número de estações encontradas:", len(estacoes)) + for estacao in estacoes: + codigo = estacao.get("codestacao") + lat = estacao.get("latitude") + lon = estacao.get("longitude") + if codigo and lat and lon: + posicoes[codigo] = (lat, lon) + + print("Dicionário de posições das estações:") + for cod, coords in list(posicoes.items()): + print(f"{cod}: {coords}") +else: + print("Erro ao buscar estações:", response.status_code) + +mapa = folium.Map(location=[-22.9068, -43.1729], zoom_start=10) + +for codestacao, (lat, lon) in posicoes.items(): + folium.Marker( + location=[lat, lon], + popup=f"Estação: {codestacao}", + icon=folium.Icon(color="blue", icon="info-sign"), + ).add_to(mapa) + +mapa.save("mapa_estacoes_rj.html") +print("Mapa gerado: mapa_estacoes_rj.html") diff --git a/src/surface_stations/cemaden_mapa_chuva.py b/src/surface_stations/cemaden_mapa_chuva.py new file mode 100644 index 00000000..8e81af26 --- /dev/null +++ b/src/surface_stations/cemaden_mapa_chuva.py @@ -0,0 +1,109 @@ +import os +from pathlib import Path + +import folium +import matplotlib.pyplot as plt +import pandas as pd +import requests + +from src.surface_stations.retrieve_ws_cemaden import get_token +from src.utils.env_loader import get_cemaden_credentials + +NOME_SECRETO, SENHA_SECRETA = get_cemaden_credentials() + + +def get_estacao_posicoes(codibge="3304557"): + url = "https://sws.cemaden.gov.br/PED/rest/pcds-cadastro/dados-cadastrais" + token = get_token(NOME_SECRETO, SENHA_SECRETA) + headers = {"token": token} + params = {"codibge": codibge, "formato": "json"} + response = requests.get(url, headers=headers, params=params) + + posicoes = {} + if response.status_code == 200: + estacoes = response.json() + for est in estacoes: + cod = est.get("codestacao") + lat = est.get("latitude") + lon = est.get("longitude") + if cod and lat and lon: + posicoes[cod] = (lat, lon) + return posicoes + + +def calcular_chuva_por_estacao(raw_folder="data/ws/cemaden/raw/"): + chuva_total = {} + for file in os.listdir(raw_folder): + if file.endswith(".parquet"): + cod = Path(file).stem + caminho = os.path.join(raw_folder, file) + try: + df = pd.read_parquet(caminho) + if "chuva" in df.columns and not df["chuva"].isna().all(): + total = df["chuva"].sum(skipna=True) + chuva_total[cod] = total + except Exception as e: + print(f"Erro ao ler {file}: {e}") + return chuva_total + + +def plotar_mapa_matplotlib(chuva_total, posicoes): + lats, lons, intensidades = [], [], [] + for cod, total in chuva_total.items(): + if cod in posicoes: + lat, lon = posicoes[cod] + lats.append(lat) + lons.append(lon) + intensidades.append(total) + + if not lats: + print("Nenhuma estação com dados e coordenadas disponíveis.") + return + + plt.figure(figsize=(10, 8)) + scatter = plt.scatter( + lons, lats, c=intensidades, cmap="viridis", s=100, edgecolor="k" + ) + plt.colorbar(scatter, label="Chuva acumulada (mm)") + plt.title("Estações e precipitação acumulada") + plt.xlabel("Longitude") + plt.ylabel("Latitude") + plt.grid(True) + plt.tight_layout() + plt.show() + + +def gerar_mapa_com_folium(chuva_total, posicoes, saida_html="mapa_chuva.html"): + mapa = folium.Map(location=[-22.9, -43.2], zoom_start=8) + + if not chuva_total: + print("Nenhuma estação com chuva registrada encontrada.") + return + + max_chuva = max(chuva_total.values()) + + for cod, total in chuva_total.items(): + if cod in posicoes: + lat, lon = posicoes[cod] + cor = "green" if total < 10 else "orange" if total < 50 else "red" + raio = 2000 + (total / max_chuva) * 3000 + + folium.Circle( + location=[lat, lon], + radius=raio, + color=cor, + fill=True, + fill_color=cor, + fill_opacity=0.6, + popup=f"Estação: {cod}
Chuva: {total:.1f} mm", + ).add_to(mapa) + + mapa.save(saida_html) + print(f"Mapa interativo salvo em: {saida_html}") + + +posicoes = get_estacao_posicoes() +chuva_total = calcular_chuva_por_estacao() + +plotar_mapa_matplotlib(chuva_total, posicoes) +gerar_mapa_com_folium(chuva_total, posicoes) diff --git a/src/evaluate_model.py b/src/surface_stations/evaluate_model.py similarity index 70% rename from src/evaluate_model.py rename to src/surface_stations/evaluate_model.py index a02550b7..40927a05 100644 --- a/src/evaluate_model.py +++ b/src/surface_stations/evaluate_model.py @@ -1,35 +1,42 @@ +import argparse +import logging +import sys +import time + import torch -import torch.nn as nn -import torch.nn.functional as F import yaml -import time -import numpy as np -import sys -import argparse -import time +import src.utils.rainfall as rp import train.pipeline as pipeline - -from train.ordinal_classifier import OrdinalClassifier +from config import globals from train.binary_classifier import BinaryClassifier +from train.ordinal_classifier import OrdinalClassifier from train.regression_net import Regressor -from train.training_utils import DeviceDataLoader, to_device, gen_learning_curve, seed_everything -from train.conv1d_neural_net import Conv1DNeuralNet -from train.lstm_neural_net import LstmNeuralNet -import rainfall as rp +from train.training_utils import ( + DeviceDataLoader, + seed_everything, + to_device, +) -from globals import MODELS_DIR - -import logging def main(argv): parser = argparse.ArgumentParser(description="Train a rainfall forecasting model.") - parser.add_argument("-t", "--task", choices=["ORDINAL_CLASSIFICATION", "BINARY_CLASSIFICATION"], - default="REGRESSION", help="Prediction task") - parser.add_argument("-l", "--learner", choices=["Conv1DNeuralNet", "LstmNeuralNet"], - default="LstmNeuralNet", help="Learning algorithm to be used.") + parser.add_argument( + "-t", + "--task", + choices=["ORDINAL_CLASSIFICATION", "BINARY_CLASSIFICATION"], + default="REGRESSION", + help="Prediction task", + ) + parser.add_argument( + "-l", + "--learner", + choices=["Conv1DNeuralNet", "LstmNeuralNet"], + default="LstmNeuralNet", + help="Learning algorithm to be used.", + ) parser.add_argument("-p", "--pipeline_id", required=True, help="Pipeline ID") - + args = parser.parse_args(argv[1:]) forecasting_task_id = None @@ -44,9 +51,10 @@ def main(argv): seed_everything() X_train, y_train, X_val, y_val, X_test, y_test = pipeline.load_datasets( - args.pipeline_id) + args.pipeline_id + ) - with open('./config/config.yaml', 'r') as file: + with open("./config/config.yaml", "r") as file: config = yaml.safe_load(file) SEQ_LENGTH = config["preproc"]["SLIDING_WINDOW_SIZE"] @@ -78,23 +86,25 @@ def main(argv): print(f"Number of features: {NUM_FEATURES}") # Instantiate the learner class - learner = class_obj(seq_length = SEQ_LENGTH, - input_size = NUM_FEATURES, - output_size = OUTPUT_SIZE, - dropout_rate = DROPOUT_RATE) - print(f'Learner: {learner}') + learner = class_obj( + seq_length=SEQ_LENGTH, + input_size=NUM_FEATURES, + output_size=OUTPUT_SIZE, + dropout_rate=DROPOUT_RATE, + ) + print(f"Learner: {learner}") if prediction_task_sufix == "oc": forecaster = OrdinalClassifier(learner) elif prediction_task_sufix == "bc": forecaster = BinaryClassifier(learner) elif prediction_task_sufix == "reg": - forecaster = Regressor(in_channels=NUM_FEATURES, y_mean_value=y_mean_value) + forecaster = Regressor(in_channels=NUM_FEATURES) # , y_mean_value=y_mean_value) # # Load model. # - filename = MODELS_DIR + '/best_' + args.pipeline_id + '.pt' + filename = globals.MODELS_DIR + "/best_" + args.pipeline_id + ".pt" logging.info(f"Loading model from file {filename}") forecaster.learner.load_state_dict(torch.load(filename)) @@ -104,7 +114,10 @@ def main(argv): test_loader = learner.create_dataloader(X_test, y_test, batch_size=BATCH_SIZE) test_loader = DeviceDataLoader(test_loader, device) to_device(forecaster.learner, device) - forecaster.print_evaluation_report(args.pipeline_id, test_loader, forecasting_task_id) + forecaster.print_evaluation_report( + args.pipeline_id, test_loader, forecasting_task_id + ) + if __name__ == "__main__": start_time = time.time() diff --git a/src/surface_stations/export_station_series.py b/src/surface_stations/export_station_series.py new file mode 100644 index 00000000..f51fb465 --- /dev/null +++ b/src/surface_stations/export_station_series.py @@ -0,0 +1,136 @@ +""" +Export a single WebSirene station time series to CSV or Parquet for a given date range. + +Example: +PYTHONPATH=src python3 src/surface_stations/export_station_series.py \ + --station-id 15 \ + --start-date "01/01/2013 00:00" \ + --end-date "03/01/2013 00:00" \ + --format parquet \ + --output data/ws/export/station_15_20130101_20130103.parquet +""" + +import argparse +import sys +from datetime import datetime +from pathlib import Path +from typing import Iterable + +import pandas as pd + + +def parse_cli_datetime(raw_datetime: str) -> datetime: + supported_formats = ("%d/%m/%Y %H:%M", "%d-%m-%Y %H:%M") + for fmt in supported_formats: + try: + return datetime.strptime(raw_datetime, fmt) + except ValueError: + continue + raise ValueError( + f"'{raw_datetime}' is not in a supported format (expected DD/MM/YYYY HH:MM or DD-MM-YYYY HH:MM)." + ) + + +def _iter_station_files(base_dir: Path, station_id: int, years: Iterable[int]) -> list[Path]: + paths: list[Path] = [] + for year in years: + parquet_path = base_dir / f"station_id={station_id}" / f"year={year}" / "data.parquet" + csv_path = base_dir / f"station_id={station_id}" / f"year={year}" / "data.csv" + if parquet_path.exists(): + paths.append(parquet_path) + elif csv_path.exists(): + paths.append(csv_path) + return paths + + +def _read_file(path: Path) -> pd.DataFrame: + if path.suffix == ".parquet": + df = pd.read_parquet(path) + else: + df = pd.read_csv(path, parse_dates=["observation_datetime", "request_datetime"], infer_datetime_format=True) + df["observation_datetime"] = pd.to_datetime(df["observation_datetime"], utc=True, errors="coerce") + return df + + +def main(): + parser = argparse.ArgumentParser( + description="Export a single WebSirene station series to CSV or Parquet for a given date range." + ) + parser.add_argument("--station-id", required=True, type=int, help="Station identifier (integer).") + parser.add_argument("--start-date", required=True, help="Start date/time (DD/MM/YYYY HH:MM)") + parser.add_argument("--end-date", required=True, help="End date/time (DD/MM/YYYY HH:MM)") + parser.add_argument("--data-dir", default="data/ws/full", help="Base directory containing partitioned WebSirene data.") + parser.add_argument("--format", choices=["csv", "parquet"], default="parquet", help="Output format.") + parser.add_argument( + "--output", + default=None, + help="Output file path. Defaults to data/ws/export/station___.", + ) + args = parser.parse_args() + + try: + start_dt = parse_cli_datetime(args.start_date) + end_dt = parse_cli_datetime(args.end_date) + except ValueError as err: + print(f"Invalid datetime: {err}") + sys.exit(1) + + if end_dt < start_dt: + print("End date/time must be greater than or equal to the start date/time.") + sys.exit(1) + + start_ts = pd.to_datetime(start_dt, utc=True) + end_ts = pd.to_datetime(end_dt, utc=True) + + data_dir = Path(args.data_dir) + if not data_dir.exists(): + print(f"Data directory not found: {data_dir}") + sys.exit(1) + + years = range(start_ts.year, end_ts.year + 1) + files = _iter_station_files(data_dir, args.station_id, years) + if not files: + print(f"No files found for station {args.station_id} in {data_dir} for years {start_ts.year}-{end_ts.year}.") + sys.exit(1) + + frames = [] + for path in files: + try: + frames.append(_read_file(path)) + except Exception as exc: + print(f"Skipping {path} due to error: {exc}") + if not frames: + print("No data could be loaded from available files.") + sys.exit(1) + + df = pd.concat(frames, ignore_index=True) + df = df.dropna(subset=["observation_datetime"]) + df = df[ + (df["observation_datetime"] >= start_ts) + & (df["observation_datetime"] <= end_ts) + ].sort_values("observation_datetime") + + if df.empty: + print("No observations in the requested period for this station.") + sys.exit(1) + + out_path = Path(args.output) if args.output else None + if out_path is None: + out_dir = Path("data/ws/export") + out_dir.mkdir(parents=True, exist_ok=True) + start_tag = start_ts.strftime("%Y%m%d%H%M") + end_tag = end_ts.strftime("%Y%m%d%H%M") + out_path = out_dir / f"station_{args.station_id}_{start_tag}_{end_tag}.{args.format}" + else: + out_path.parent.mkdir(parents=True, exist_ok=True) + + if args.format == "parquet": + df.to_parquet(out_path, index=False) + else: + df.to_csv(out_path, index=False) + + print(f"Saved {len(df)} rows to {out_path}") + + +if __name__ == "__main__": + main() diff --git a/src/surface_stations/plot_map_cemaden_redemet.py b/src/surface_stations/plot_map_cemaden_redemet.py new file mode 100644 index 00000000..7c92e5ec --- /dev/null +++ b/src/surface_stations/plot_map_cemaden_redemet.py @@ -0,0 +1,134 @@ +import folium +import pandas as pd + + +def parse_coordinates(coord_str): + degrees = float(coord_str.split("º")[0]) + minutes = float(coord_str.split("º")[1].split("'")[0]) + seconds = float(coord_str.split("'")[1].split("''")[0]) + direction = coord_str.split("'' ")[1] + + decimal_degrees = degrees + minutes / 60 + seconds / 3600 + if direction in ["S", "W"]: + decimal_degrees = -decimal_degrees + + return decimal_degrees + + +def add_points_to_map( + map_obj: folium.Map, df: pd.DataFrame, radius=5, color="blue", fill_opacity=0.6 +): + for _, row in df.iterrows(): + folium.CircleMarker( + location=[row["lat"], row["long"]], + radius=radius, + color=color, + fill_color=color, + fill_opacity=fill_opacity, + popup=f"{row['nome']}: {row['lat']}, {row['long']}", + ).add_to(map_obj) + return map_obj + + +redemet_df = pd.DataFrame( + { + "nome": ["SBGL", "SBJR", "SBRJ", "SBSC", "SBAF"], + "lat": [ + "22º48'32'' S", + "22º59'12'' S", + "22º54'37'' S", + "22º55'56'' S", + "22º52'30'' S", + ], + "long": [ + "43º14'37'' W", + "43º22'19'' W", + "43º9'47'' W", + "43º43'8'' W", + "43º 23'4'' W", + ], + } +) + + +redemet_df["lat"] = redemet_df["lat"].apply(parse_coordinates) +redemet_df["long"] = redemet_df["long"].apply(parse_coordinates) + +centroid = [-22.89181404239337, -43.269477142236386] +zoom_start = 11 +tiles = "cartodbpositron" + +_map = folium.Map( + location=centroid, + zoom_start=zoom_start, + tiles=tiles, +) + +_map = add_points_to_map( + _map, + redemet_df, + color="darkgreen", +) + +_map.save("mapa.html") + +_map + +cemaden_df = pd.read_csv("cemaden2.csv") +cemaden_df.tail() +print(cemaden_df) + +cemaden_df = pd.read_csv("cemaden2.csv", usecols=["nome", "lat", "long"]) +cemaden_df.columns = ["nome", "lat", "long"] + +cemaden_df.head() + + +required_columns = ["lat", "long"] +dataframes = [redemet_df, cemaden_df] + +for df in dataframes: + for column in required_columns: + assert column in df.columns, f"Column '{column}' not found in DataFrame '{df}'" + + +_map = folium.Map( + location=centroid, + zoom_start=zoom_start, + tiles=tiles, +) + +_map = add_points_to_map( + _map, + redemet_df, + color="darkred", +) + +_map = add_points_to_map( + _map, + cemaden_df, + color="darkblue", +) + +colors = ["red", "blue"] +labels = ["Redemet", "Cemaden"] + +legend_html = """ +
+""" + +for i, label in enumerate(labels): + legend_html += f""" +     {label}
+""" +legend_html += "
" + +_map.get_root().html.add_child(folium.Element(legend_html)) +_map + +_map.save("mapaoficial.html") +_map diff --git a/src/predict_oc.py b/src/surface_stations/predict_oc.py similarity index 63% rename from src/predict_oc.py rename to src/surface_stations/predict_oc.py index d9e1ecdd..41cf9db8 100644 --- a/src/predict_oc.py +++ b/src/surface_stations/predict_oc.py @@ -1,17 +1,18 @@ -import torch -import torch.nn as nn -from src.train.ordinal_classifier import OrdinalClassifier -import globals as globals import pickle + +import torch import yaml +import config.globals as globals +from src.train.ordinal_classifier import OrdinalClassifier + if __name__ == "__main__": pipeline_id = "A652_N" # # Load numpy arrays (stored in a pickle file) from disk filename = globals.DATASETS_DIR + pipeline_id + ".pickle" - file = open(filename, 'rb') + file = open(filename, "rb") (_, _, _, _, X_test, _) = pickle.load(file) print(f"Shape of test data matrix: {X_test.shape}") @@ -24,20 +25,23 @@ NUM_FEATURES = X_test.shape[2] NUM_CLASSES = 5 - with open('./config/config.yaml', 'r') as file: + with open("./config/config.yaml", "r") as file: config = yaml.safe_load(file) - #Create an instance of the model + # Create an instance of the model input_dim = (NUM_FEATURES, config["preproc"]["SLIDING_WINDOW_SIZE"]) - model = OrdinalClassifier(in_channels=NUM_FEATURES, - num_classes=NUM_CLASSES, - input_dim = input_dim, - target_average = None) + model = OrdinalClassifier( + in_channels=NUM_FEATURES, + num_classes=NUM_CLASSES, + input_dim=input_dim, + target_average=None, + ) # Load the pretrained model weights from the file - model_path = globals.MODELS_DIR + "best_" + pipeline_id + "_OC.pt" # Path to the pretrained model file - model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu'))) - + model_path = ( + globals.MODELS_DIR + "best_" + pipeline_id + "_OC.pt" + ) # Path to the pretrained model file + model.load_state_dict(torch.load(model_path, map_location=torch.device("cpu"))) # Set the model in evaluation (inference) mode. model.eval() @@ -45,4 +49,4 @@ # Make prediction using the loaded model with torch.no_grad(): output = model.predict(x) - print(f"Predicted level: {output[0][0]}") \ No newline at end of file + print(f"Predicted level: {output[0][0]}") diff --git a/src/surface_stations/preprocess.py b/src/surface_stations/preprocess.py new file mode 100644 index 00000000..310251e1 --- /dev/null +++ b/src/surface_stations/preprocess.py @@ -0,0 +1,690 @@ +import argparse +import json +import logging +import math +import sys +from functools import lru_cache +from pathlib import Path + +import numpy as np +import pandas as pd +from sklearn.impute import KNNImputer +from sklearn.preprocessing import MinMaxScaler, StandardScaler + +from config import globals +from utils import util as util + +PROJECT_ROOT = Path(__file__).resolve().parents[2] +SRC_DIR = PROJECT_ROOT / "src" +if str(SRC_DIR) not in sys.path: + sys.path.insert(0, str(SRC_DIR)) + + +def _safe_get(dct: dict, key: str, default=None): + try: + return dct.get(key, default) + except AttributeError: + return default + + +def _is_truthy(value) -> bool: + if isinstance(value, str): + return value.lower() in {"1", "true", "yes", "on"} + return bool(value) + + +def _nan_to_none(value): + if value is None: + return None + if isinstance(value, float) and math.isnan(value): + return None + return value + + +def _ensure_list(value, default=None): + if value is None: + return default or [] + if isinstance(value, (list, tuple)): + return list(value) + return [value] + + +STATION_SYSTEM_CONFIG_DIR = PROJECT_ROOT / "config" / "station_systems" + +STATION_SYSTEM_CONFIG = { + "inmet": { + "ids": set(globals.INMET_WEATHER_STATION_IDS), + "data_dir": globals.WS_INMET_DATA_DIR, + "config_path": STATION_SYSTEM_CONFIG_DIR / "inmet.json", + }, + "alertario": { + "ids": set(globals.ALERTARIO_WEATHER_STATION_IDS), + "data_dir": globals.WS_ALERTARIO_DATA_DIR, + "config_path": STATION_SYSTEM_CONFIG_DIR / "alertario.json", + }, +} + + +@lru_cache(maxsize=None) +def load_station_system_settings(system_name: str) -> dict: + system_name = system_name.lower() + if system_name not in STATION_SYSTEM_CONFIG: + raise KeyError(f"Unknown station system '{system_name}'.") + config_path = STATION_SYSTEM_CONFIG[system_name]["config_path"] + if not config_path.exists(): + raise FileNotFoundError( + f"Configuration file not found for system '{system_name}' at '{config_path}'." + ) + with config_path.open("r", encoding="utf-8") as config_file: + return json.load(config_file) + + +def apply_scaling(df: pd.DataFrame, scaler_config: dict) -> pd.DataFrame: + if df.empty: + return df + scaler_config = scaler_config or {} + scaler_type = scaler_config.get("type", "minmax") + if not isinstance(scaler_type, str): + logging.warning(f"Invalid scaler type '{scaler_type}'. Skipping normalization.") + return df + scaler_type = scaler_type.lower() + params = scaler_config.get("params", {}) or {} + + if scaler_type == "minmax": + feature_range = params.get("feature_range", [0.0, 1.0]) + if feature_range == [0.0, 1.0] or tuple(feature_range) == (0.0, 1.0): + return util.min_max_normalize(df) + scaler = MinMaxScaler(feature_range=tuple(feature_range)) + scaled = scaler.fit_transform(df) + elif scaler_type == "standard": + scaler = StandardScaler(**params) + scaled = scaler.fit_transform(df) + elif scaler_type in {"none", "identity"}: + return df + else: + logging.warning(f"Unknown scaler type '{scaler_type}'. Skipping normalization.") + return df + + scaled_df = pd.DataFrame(scaled, columns=df.columns, index=df.index) + return scaled_df + + +def apply_imputation(df: pd.DataFrame, imputation_config: dict) -> pd.DataFrame: + if df.empty: + return df + imputation_config = imputation_config or {} + strategy = imputation_config.get("strategy", "knn") + if not isinstance(strategy, str): + logging.warning( + f"Invalid imputation strategy '{strategy}'. Skipping imputation." + ) + return df + strategy = strategy.lower() + params = imputation_config.get("params", {}) or {} + + if strategy == "knn": + n_neighbors = params.get("n_neighbors", 2) + weights = params.get("weights", "uniform") + imputer = KNNImputer(n_neighbors=n_neighbors, weights=weights) + imputed = imputer.fit_transform(df) + return pd.DataFrame(imputed, columns=df.columns, index=df.index) + if strategy in {"ffill_then_zero", "forward_then_zero"}: + return df.ffill().fillna(0.0) + if strategy in {"ffill", "forward"}: + return df.ffill() + if strategy in {"bfill", "backward"}: + return df.bfill() + if strategy in {"zero", "zeros"}: + return df.fillna(0.0) + if strategy in {"none", "skip"}: + return df + + logging.warning(f"Unknown imputation strategy '{strategy}'. Skipping imputation.") + return df + + +def apply_quality_checks( + df: pd.DataFrame, + quality_config: dict, + predictor_columns, + flag_suffix: str = "_flag", + include_flag_columns: bool = True, +): + if df.empty: + return df, {"checks": [], "flag_columns": [], "new_columns": []} + + checks = _ensure_list(_safe_get(quality_config, "checks"), default=[]) + records = [] + created_flag_columns = [] + new_predictor_columns = [] + row_count = len(df.index) + + for idx, raw_check in enumerate(checks): + check = raw_check or {} + check_type = str(check.get("type", "")).lower() + if not check_type: + continue + columns = _ensure_list(check.get("columns"), default=predictor_columns) + actions = _ensure_list( + check.get("actions") or check.get("strategy"), default=["flag"] + ) + actions = [action.lower() for action in actions] + if not actions: + continue + + # compute parameters common across columns depending on check type + for column in columns: + if column not in df.columns: + logging.debug( + f"Quality check '{check_type}' skipped for missing column '{column}'." + ) + continue + series = df[column] + if not pd.api.types.is_numeric_dtype(series): + logging.debug( + f"Quality check '{check_type}' skipped for non-numeric column '{column}'." + ) + continue + + mask = pd.Series(False, index=df.index) + params_summary = {} + + if check_type == "bounds": + min_value = check.get("min") + max_value = check.get("max") + if min_value is not None: + mask |= series < min_value + if max_value is not None: + mask |= series > max_value + params_summary = {"min": min_value, "max": max_value} + elif check_type == "iqr": + k = float(check.get("k", 1.5)) + q1 = series.quantile(0.25) + q3 = series.quantile(0.75) + iqr = q3 - q1 + if pd.isna(iqr) or iqr == 0: + continue + lower = q1 - k * iqr + upper = q3 + k * iqr + mask = (series < lower) | (series > upper) + params_summary = {"k": k, "lower": lower, "upper": upper} + elif check_type == "zscore": + threshold = float(check.get("threshold", 3.0)) + mean = series.mean() + std = series.std() + if pd.isna(std) or std == 0: + continue + zscores = (series - mean) / std + mask = zscores.abs() > threshold + params_summary = {"threshold": threshold} + else: + logging.warning( + f"Unknown quality check type '{check_type}' for column '{column}'. Skipping." + ) + continue + + if not mask.any(): + records.append( + { + "check": check.get("name") or f"{check_type}_{idx}", + "type": check_type, + "column": column, + "flags": 0, + "fraction": 0.0, + "actions": actions, + "params": params_summary, + } + ) + continue + + if "clip" in actions and check_type in {"bounds", "iqr"}: + if "min" in params_summary and params_summary["min"] is not None: + df.loc[series < params_summary["min"], column] = params_summary[ + "min" + ] + if "max" in params_summary and params_summary["max"] is not None: + df.loc[series > params_summary["max"], column] = params_summary[ + "max" + ] + if "lower" in params_summary and params_summary["lower"] is not None: + df.loc[series < params_summary["lower"], column] = params_summary[ + "lower" + ] + if "upper" in params_summary and params_summary["upper"] is not None: + df.loc[series > params_summary["upper"], column] = params_summary[ + "upper" + ] + + if "set_nan" in actions: + df.loc[mask, column] = np.nan + + flag_column = None + if "flag" in actions: + flag_column = check.get("flag_column") or f"{column}{flag_suffix}" + if flag_column not in df.columns: + df[flag_column] = False + df[flag_column] = df[flag_column].fillna(False).astype(bool) + df.loc[mask, flag_column] = True + df[flag_column] = df[flag_column].astype(bool) + created_flag_columns.append(flag_column) + if include_flag_columns: + if flag_column not in new_predictor_columns: + new_predictor_columns.append(flag_column) + + records.append( + { + "check": check.get("name") or f"{check_type}_{idx}", + "type": check_type, + "column": column, + "flags": int(mask.sum()), + "fraction": float(mask.sum()) / row_count if row_count else 0.0, + "actions": actions, + "flag_column": flag_column, + "params": params_summary, + } + ) + + quality_output = { + "checks": records, + "flag_columns": list(dict.fromkeys(created_flag_columns)), + "new_columns": list(dict.fromkeys(new_predictor_columns)), + } + return df, quality_output + + +def build_quality_report( + station_id: str, + station_system: str, + report_df: pd.DataFrame, + report_config: dict, + station_metadata: dict, + scaler_config: dict, + imputation_config: dict, + missing_counts_before: pd.Series, + imputation_applied: bool, + source_file: str, + output_file: str, + target_column: str, + quality_checks=None, +) -> dict: + report_fields = _ensure_list( + _safe_get(report_config, "fields"), default=["missing_fraction", "min", "max"] + ) + summary_keys = _ensure_list( + _safe_get(report_config, "summary"), + default=["rows", "columns", "missing_fraction"], + ) + + num_rows = int(report_df.shape[0]) + num_columns = int(report_df.shape[1]) + total_cells = num_rows * num_columns if num_rows and num_columns else 0 + missing_fraction = ( + (missing_counts_before.sum() / total_cells) if total_cells else 0.0 + ) + + per_column_metrics = {} + for column in report_df.columns: + column_metrics = {} + for field in report_fields: + if field == "missing_fraction": + column_metrics[field] = ( + float(missing_counts_before[column]) / num_rows if num_rows else 0.0 + ) + elif field == "missing_count": + column_metrics[field] = int(missing_counts_before[column]) + elif field == "imputed_fraction": + column_metrics[field] = ( + float(missing_counts_before[column]) / num_rows + if (num_rows and imputation_applied) + else 0.0 + ) + elif field == "imputed_count": + column_metrics[field] = ( + int(missing_counts_before[column]) if imputation_applied else 0 + ) + elif field == "min": + column_metrics[field] = _nan_to_none(report_df[column].min(skipna=True)) + elif field == "max": + column_metrics[field] = _nan_to_none(report_df[column].max(skipna=True)) + elif field == "mean": + column_metrics[field] = _nan_to_none( + report_df[column].mean(skipna=True) + ) + elif field == "median": + column_metrics[field] = _nan_to_none( + report_df[column].median(skipna=True) + ) + elif field == "std": + column_metrics[field] = _nan_to_none(report_df[column].std(skipna=True)) + per_column_metrics[column] = column_metrics + + summary = {} + for key in summary_keys: + if key == "rows": + summary[key] = num_rows + elif key == "columns": + summary[key] = num_columns + elif key == "missing_fraction": + summary[key] = missing_fraction + elif key == "imputed_fraction": + summary[key] = missing_fraction if imputation_applied else 0.0 + elif key == "min": + summary[key] = _nan_to_none(report_df.min(skipna=True).min()) + elif key == "max": + summary[key] = _nan_to_none(report_df.max(skipna=True).max()) + elif key == "mean": + summary[key] = _nan_to_none(report_df.mean(skipna=True).mean()) + + report_payload = { + "station_id": station_id, + "station_system": station_system, + "target_column": target_column, + "columns": list(report_df.columns), + "rows": num_rows, + "metadata": station_metadata or {}, + "scaler": scaler_config or {}, + "imputation": imputation_config or {}, + "imputation_applied": imputation_applied, + "source_file": source_file, + "output_file": output_file, + "column_metrics": per_column_metrics, + "summary": summary, + "quality_checks": quality_checks or [], + } + return report_payload + + +def preprocess_ws(ws_id, ws_filename, output_folder, station_system): + system_settings = load_station_system_settings(station_system) + feature_toggles = system_settings.get("features", {}) + add_wind_features = feature_toggles.get("add_wind_related_features", True) + add_hour_features = feature_toggles.get("add_hour_related_features", True) + normalize_predictors = feature_toggles.get("normalize_predictors", True) + impute_missing_values = feature_toggles.get("impute_missing_values", True) + preprocessing_settings = system_settings.get("preprocessing", {}) + scaler_config = preprocessing_settings.get("scaler", {}) + imputation_config = preprocessing_settings.get("imputation", {}) + quality_config = system_settings.get("quality", {}) + quality_enabled = _is_truthy(_safe_get(quality_config, "enabled", False)) + include_flag_columns = _is_truthy( + _safe_get(quality_config, "include_flag_columns", True) + ) + flag_suffix = quality_config.get("flag_column_suffix", "_flag") + report_config = system_settings.get("report", {}) + report_enabled = _is_truthy(_safe_get(report_config, "enabled", False)) + station_metadata = _safe_get(_safe_get(system_settings, "stations", {}), ws_id, {}) + + logging.info(f"Loading datasource file {ws_filename}).") + df = pd.read_parquet(ws_filename) + logging.info(df.head()) + logging.info("Done!\n") + + # + # Add index to dataframe using the timestamps. + logging.info("Adding index to dataframe using the timestamps...") + df = util.add_datetime_index(ws_id, df) + logging.info(df.head()) + logging.info("Done!\n") + + # + # Standardize column names. + logging.info("Standardizing column names...") + column_name_mapping = system_settings.get("column_mapping", {}) + if not column_name_mapping: + raise ValueError( + f"No column mapping provided for station system '{station_system}'." + ) + missing_columns = [col for col in column_name_mapping if col not in df.columns] + if missing_columns: + logging.warning( + f"The following columns from the mapping are missing in the datasource: {missing_columns}" + ) + column_names = column_name_mapping.keys() + df = util.get_dataframe_with_selected_columns(df, column_names) + df = util.rename_dataframe_column_names(df, column_name_mapping) + logging.info(df.head()) + logging.info("Done!\n") + + logging.info("Getting relevant variables...") + predictor_names = system_settings.get("predictor_columns") + target_name = system_settings.get("target_column") + if not (predictor_names and target_name): + variables = util.get_relevant_variables(ws_id) + if not variables: + raise ValueError( + f"Could not determine predictors/target for station '{ws_id}'." + ) + predictor_names, target_name = variables + logging.info(f"Predictors: {predictor_names}") + logging.info(f"Target: {target_name}") + logging.info("Done!\n") + + # + # Drop observations in which the target variable is not defined. + logging.info("Dropping entries with null target...") + n_obser_before_drop = len(df) + df = df[df[target_name].notna()] + n_obser_after_drop = len(df) + logging.info( + f"Number of observations before/after dropping entries with undefined target value: {n_obser_before_drop}/{n_obser_after_drop}." + ) + logging.info( + f"Range of timestamps after dropping entries with undefined target value: [{min(df.index)}, {max(df.index)}]" + ) + logging.info(df.head()) + logging.info("Done!\n") + + quality_summary = [] + quality_added_predictors = [] + if quality_enabled: + logging.info("Applying quality checks before feature engineering...") + pre_quality_columns = [ + column for column in predictor_names if column in df.columns + ] + df, quality_output = apply_quality_checks( + df=df, + quality_config=quality_config, + predictor_columns=pre_quality_columns, + flag_suffix=flag_suffix, + include_flag_columns=include_flag_columns, + ) + quality_summary = quality_output.get("checks", []) + if include_flag_columns: + quality_added_predictors = [ + column + for column in quality_output.get("new_columns", []) + if column in df.columns + ] + logging.info("Quality checks completed.\n") + + # + # Create wind-related features (U and V components of wind observations). + if add_wind_features: + logging.info("Creating wind-related features...") + df = util.add_wind_related_features(ws_id, df) + logging.info(df.head()) + logging.info("Done!\n") + else: + logging.info("Skipping wind-related feature generation as configured.\n") + + # + # Create time-related features (sin and cos components) + if add_hour_features: + logging.info("Creating time-related features...") + df = util.add_hour_related_features(df) + logging.info(df.head()) + logging.info("Done!\n") + else: + logging.info("Skipping time-related feature generation as configured.\n") + + available_predictors = [ + column for column in predictor_names if column in df.columns + ] + if include_flag_columns and quality_added_predictors: + for column in quality_added_predictors: + if column not in available_predictors: + available_predictors.append(column) + missing_predictors = sorted(set(predictor_names) - set(available_predictors)) + if missing_predictors: + logging.warning( + f"The following predictors are missing and will be ignored: {missing_predictors}" + ) + if not available_predictors: + raise ValueError( + f"No predictor columns were found after preprocessing for station '{ws_id}'." + ) + if target_name not in df.columns: + raise KeyError( + f"Target column '{target_name}' not found after preprocessing for station '{ws_id}'." + ) + df = df[available_predictors + [target_name]] + report_reference_df = df[available_predictors].copy() if report_enabled else None + missing_counts_before = ( + report_reference_df.isna().sum() if report_reference_df is not None else None + ) + + # + # Scale the data. This step is necessary here due to the next step, which deals with missing values. + # Notice that we drop the target column before scaling, to avoid some kind of data leakage. + # (see https://stats.stackexchange.com/questions/214728/should-data-be-normalized-before-or-after-imputation-of-missing-data) + target_column = df[target_name] + predictors_df = df.drop(columns=[target_name], axis=1).copy() + if normalize_predictors: + scaler_type = ( + (scaler_config.get("type") or "minmax") + if isinstance(scaler_config, dict) + else "minmax" + ) + logging.info(f"Applying '{scaler_type}' scaling...") + predictors_df = apply_scaling(predictors_df, scaler_config) + logging.info("Done!\n") + else: + logging.info("Skipping normalization as configured.\n") + + # + # Imput missing values on some features. + if impute_missing_values: + strategy = ( + (imputation_config.get("strategy") or "knn") + if isinstance(imputation_config, dict) + else "knn" + ) + logging.info(f"Applying '{strategy}' imputation...") + percentage_missing = ( + predictors_df.isna().mean() * 100 + ).mean() # Compute the percentage of missing values + logging.info( + f"There are {predictors_df.isnull().sum().sum()} missing values ({percentage_missing:.2f}%). Going to fill them..." + ) + predictors_df = apply_imputation(predictors_df, imputation_config) + assert not predictors_df.isnull().values.any().any() + logging.info("Done!\n") + else: + logging.info("Skipping missing-value imputation as configured.\n") + strategy_value = None + strategy_flag = True + if isinstance(imputation_config, dict): + strategy_value = imputation_config.get("strategy", "knn") + if isinstance(strategy_value, str): + strategy_flag = strategy_value.lower() not in {"none", "skip"} + imputation_applied = bool(impute_missing_values and strategy_flag) + + # + # Add the target column back to the DataFrame. + predictors_df[target_name] = target_column + df = predictors_df + + # + # Save preprocessed data to a parquet file. + filename_and_extension = util.get_filename_and_extension(ws_filename) + filename = output_folder + filename_and_extension[0] + "_preprocessed.parquet.gzip" + logging.info(f"Saving preprocessed data to {filename}...") + df.to_parquet(filename, compression="gzip") + logging.info("Done!\n") + + if ( + report_enabled + and report_reference_df is not None + and missing_counts_before is not None + ): + report_payload = build_quality_report( + station_id=ws_id, + station_system=station_system, + report_df=report_reference_df, + report_config=report_config, + station_metadata=station_metadata, + scaler_config=scaler_config, + imputation_config=imputation_config, + missing_counts_before=missing_counts_before, + imputation_applied=imputation_applied, + source_file=ws_filename, + output_file=filename, + target_column=target_name, + quality_checks=quality_summary, + ) + report_filename = ( + output_folder + filename_and_extension[0] + "_preprocess_report.json" + ) + with open(report_filename, "w", encoding="utf-8") as report_file: + json.dump(report_payload, report_file, indent=2, ensure_ascii=False) + logging.info(f"Quality report saved to {report_filename}\n") + + logging.info("Done it all!\n") + + +def main(argv): + parser = argparse.ArgumentParser(description="Preprocess weather station data.") + parser.add_argument( + "-s", + "--station_id", + required=True, + choices=globals.INMET_WEATHER_STATION_IDS + + globals.ALERTARIO_WEATHER_STATION_IDS, + help="ID of the weather station to preprocess data for.", + ) + parser.add_argument( + "-y", + "--station_system", + choices=sorted(STATION_SYSTEM_CONFIG.keys()), + type=str.lower, + help="System of the weather station (e.g., INMET, AlertaRio).", + ) + args = parser.parse_args(argv[1:]) + + station_id = args.station_id + station_system = args.station_system + + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.DEBUG, format=fmt) + + if station_system: + system_config = STATION_SYSTEM_CONFIG[station_system] + if station_id not in system_config["ids"]: + parser.error( + f"Station {station_id} does not belong to the {station_system.upper()} system." + ) + ws_data_dir = system_config["data_dir"] + else: + ws_data_dir = None + for system_name, system_config in STATION_SYSTEM_CONFIG.items(): + if station_id in system_config["ids"]: + station_system = system_name + ws_data_dir = system_config["data_dir"] + break + if ws_data_dir is None: + parser.error(f"Invalid station identifier: {station_id}") + + print( + f"Preprocessing data coming from weather station {station_id} (system: {station_system.upper()})" + ) + ws_filename = ws_data_dir + args.station_id + ".parquet" + preprocess_ws( + ws_id=station_id, + ws_filename=ws_filename, + output_folder=ws_data_dir, + station_system=station_system, + ) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/surface_stations/retrieve_rgs_cor.py b/src/surface_stations/retrieve_rgs_cor.py new file mode 100644 index 00000000..3903f8a0 --- /dev/null +++ b/src/surface_stations/retrieve_rgs_cor.py @@ -0,0 +1,369 @@ +import datetime +import getopt +import os +import re +import sys + +import numpy as np +import pandas as pd + +STATION_NAMES_FOR_RJ = ( + "alto_da_boa_vista", + "guaratiba", + "iraja", + "jardim_botanico", + "riocentro", + "santa_cruz", + "sao_cristovao", + "vidigal", + "urca", + "rocinha", + "tijuca", + "santa_teresa", + "copacabana", + "grajau", + "ilha_do_governador", + "penha", + "madureira", + "bangu", + "piedade", + "tanque", + "saude", + "barrinha", + "cidade_de_deus", + "grajau", + "grande_meier", + "anchieta", + "grota_funda", + "campo_grande", + "sepetiba", + "av_brasil_mendanha", + "recreio", + "laranjeiras", + "tijuca_muda", +) + + +def corrige_txt(station_name, years, months): + for year in years: + for month in months: + file = ( + "./data/RAW_data/COR/pluviometrica/" + + station_name + + "_" + + year + + month + + "_Plv.txt" + ) + if os.path.exists(file): + fin = open(file, "rt") + if not os.path.exists( + "./data/RAW_data/COR/pluviometrica/aux_" + station_name + ): + os.mkdir("./data/RAW_data/COR/pluviometrica/aux_" + station_name) + fout = open( + "./data/RAW_data/COR/pluviometrica/aux_" + + station_name + + "/" + + station_name + + "_" + + year + + month + + "_Plv2.txt", + "wt", + ) + count = 0 + for line in fin: + count += 1 + # fout.write(re.sub('\s+', ' ', line.replace(':00 ', ':00 HBV'))) + text_to_write = re.sub( + "\s+", + " ", + line.replace("HBV", "") + .replace("05 min", "05_min") + .replace("10 min", "10_min") + .replace("15 min", "15_min") + .replace("01 h", "01_h") + .replace("04 h", "04_h") + .replace("24 h", "24_h") + .replace("96 h", "96_h"), + ) + while len(text_to_write) < 34: + text_to_write = text_to_write + "ND " + fout.write(text_to_write) + fout.write("\n") + if count == 5: + fout.write("01/" + month + "/" + year + " 00:00:00 ND ND ND ND ND") + + fin.close() + fout.close() + else: + pass + + +def import_data(station_name, years, months, arg_end): + df = pd.DataFrame() + + for year in years: + check = 0 + for month in months: + texto = ( + "./data/RAW_data/COR/pluviometrica/aux_" + + station_name + + "/" + + station_name + + "_" + + year + + month + + "_Plv2.txt" + ) + if os.path.exists(texto): + df = pd.read_csv(texto, sep=" ", skiprows=[0, 1, 2, 3, 4], header=None) + if len(df.columns) == 9 or len(df.columns) == 10: + if len(df.columns) == 10: + df.columns = [ + "Dia", + "Hora", + "05 min", + "10 min", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + "teste", + ] + del df["05 min"] + del df["10 min"] + del df["teste"] + else: + df.columns = [ + "Dia", + "Hora", + "05 min", + "10 min", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + ] + del df["05 min"] + del df["10 min"] + else: + if len(df.columns) == 8: + df.columns = [ + "Dia", + "Hora", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + "teste", + ] + del df["teste"] + else: + df.columns = [ + "Dia", + "Hora", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + ] + df["15 min"] = df["15 min"][~df["15 min"].isin(["-", "ND"])].astype( + float + ) + df["01 h"] = df["01 h"][~df["01 h"].isin(["-", "ND"])].astype(float) + df["04 h"] = df["04 h"][~df["04 h"].isin(["-", "ND"])].astype(float) + df["24 h"] = df["24 h"][~df["24 h"].isin(["-", "ND"])].astype(float) + df["96 h"] = df["96 h"][~df["96 h"].isin(["-", "ND"])].astype(float) + df["Dia"] = pd.to_datetime(df["Dia"], format="%d/%m/%Y") + + ano_aux = year + mes_aux = month + print(year + "/" + month) + check = 1 + break + else: + pass + if check == 1: + break + + ano1 = list(map(str, range(int(ano_aux), arg_end))) + mes1 = list(range(int(mes_aux), 13)) + mes1 = [str(i).rjust(2, "0") for i in mes1] + + for year in ano1: + for month in mes1: + texto = ( + "./data/RAW_data/COR/pluviometrica/aux_" + + station_name + + "/" + + station_name + + "_" + + year + + month + + "_Plv2.txt" + ) + if os.path.exists(texto): + print(texto) + data2 = pd.read_csv( + texto, + sep=" ", + skiprows=[0, 1, 2, 3, 4], + header=None, + on_bad_lines="skip", + ) + if len(data2.columns) == 9 or len(data2.columns) == 10: + if len(data2.columns) == 10: + data2.columns = [ + "Dia", + "Hora", + "05 min", + "10 min", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + "teste", + ] + del data2["05 min"] + del data2["10 min"] + del data2["teste"] + else: + data2.columns = [ + "Dia", + "Hora", + "05 min", + "10 min", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + ] + del data2["05 min"] + del data2["10 min"] + else: + if len(data2.columns) == 8: + data2.columns = [ + "Dia", + "Hora", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + "teste", + ] + del data2["teste"] + else: + data2.columns = [ + "Dia", + "Hora", + "15 min", + "01 h", + "04 h", + "24 h", + "96 h", + ] + data2["15 min"] = data2["15 min"][ + ~data2["15 min"].isin(["-", "ND"]) + ].astype(float) + data2["01 h"] = data2["01 h"][~data2["01 h"].isin(["-", "ND"])].astype( + float + ) + data2["04 h"] = data2["04 h"][~data2["04 h"].isin(["-", "ND"])].astype( + float + ) + data2["24 h"] = data2["24 h"][~data2["24 h"].isin(["-", "ND"])].astype( + float + ) + data2["96 h"] = data2["96 h"][~data2["96 h"].isin(["-", "ND"])].astype( + float + ) + data2["Dia"] = pd.to_datetime(data2["Dia"], format="%d/%m/%Y") + saida = pd.concat([df, data2]) + df = saida + del saida + else: + pass + if year == ano_aux: + mes1 = list(range(1, 13)) + mes1 = [str(i).rjust(2, "0") for i in mes1] + df = df.replace("ND", np.NaN) + df = df.replace("-", np.NaN) + print(df) + # df = df[df['Hora'].str[2:6] == ':00:'] + + # df['Hora'] = np.where(df['HBV'] == 'HBV', df['Hora'].str[0:2].astype(int) - 1, df['Hora'].str[0:2].astype(int)) + # df['Hora'] = np.where(df['Hora'] == -1, 23, df['Hora']) + # df['Hora'] = df['Hora'].astype(str).str.zfill(2) + ':00:00' + + df["estacao"] = station_name + if not os.path.exists("./data/landing/plv"): + os.mkdir("./data/landing/plv") + df.to_csv("./data/landing/plv/" + station_name + ".csv") + data_aux = df + del df, data2 + return data_aux + + +def import_data_cor(station_name, initial_year, final_year): + years = list(map(str, range(int(initial_year), int(final_year)))) + months = list(range(1, 13)) + months = [str(i).rjust(2, "0") for i in months] + + if station_name == "all": + station_names = STATION_NAMES_FOR_RJ + else: + station_names = [station_name] + + for station_name in station_names: + print(station_name) + corrige_txt(station_name, years, months) + data = import_data(station_name, years, months, int(final_year)) + del data + + +def main(argv): + station_name = "" + default_initial_year = 1997 + + today = datetime.date.today() + default_final_year = today.year + + arg_help = "{0} -s -b -e ".format(argv[0]) + + try: + opts, args = getopt.getopt( + argv[1:], "hs:a:b:e:", ["help", "station=", "begin=", "end="] + ) + except getopt.GetoptError as err: + print(err) + print(arg_help) + sys.exit(2) + + for opt, arg in opts: + if opt in ("-h", "--help"): + print(arg_help) # print the help message + sys.exit(2) + elif opt in ("-s", "--station"): + station_name = arg + if not ((station_name == "all") or (station_name in STATION_NAMES_FOR_RJ)): + print(arg_help) # print the help message + sys.exit(2) + elif opt in ("-b", "--begin"): + default_initial_year = arg + elif opt in ("-e", "--end"): + default_final_year = arg + + import_data_cor(station_name, default_initial_year, default_final_year) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/surface_stations/retrieve_ws_alertario.py b/src/surface_stations/retrieve_ws_alertario.py new file mode 100644 index 00000000..5f1819c4 --- /dev/null +++ b/src/surface_stations/retrieve_ws_alertario.py @@ -0,0 +1,270 @@ +import datetime +import getopt +import os +import re +import sys + +import numpy as np +import pandas as pd + +STATION_NAMES_FOR_RJ = ( + "alto_da_boa_vista", + "guaratiba", + "iraja", + "jardim_botanico", + "riocentro", + "santa_cruz", + "sao_cristovao", + "vidigal", +) + + +def corrige_txt(station_name, years, months): + for year in years: + for month in months: + file = ( + "../data/RAW_data/COR/meteorologica/" + + station_name + + "_" + + year + + month + + "_Met.txt" + ) + if os.path.exists(file): + fin = open(file, "rt") + if not os.path.exists( + "../data/RAW_data/COR/meteorologica/aux_" + station_name + ): + os.mkdir("../data/RAW_data/COR/meteorologica/aux_" + station_name) + fout = open( + "../data/RAW_data/COR/meteorologica/aux_" + + station_name + + "/" + + station_name + + "_" + + year + + month + + "_Met2.txt", + "wt", + ) + count = 0 + for line in fin: + count += 1 + if station_name == "guaratiba": + fout.write( + re.sub("\s+", " ", line.replace(":40 ", ":00 nHBV")) + ) + else: + fout.write( + re.sub("\s+", " ", line.replace(":00 ", ":00 nHBV")) + ) + fout.write("\n") + if count == 6: + fout.write( + "01/" + month + "/" + year + " 00:00:00 nHBV ND ND ND ND ND ND" + ) + fin.close() + fout.close() + else: + pass + + +def import_data(station_name, years, months, arg_end): + df = pd.DataFrame() + + for year in years: + check = 0 + for month in months: + texto = ( + "../data/RAW_data/COR/meteorologica/aux_" + + station_name + + "/" + + station_name + + "_" + + year + + month + + "_Met2.txt" + ) + if os.path.exists(texto): + df = pd.read_csv( + texto, sep=" ", skiprows=[0, 1, 2, 3, 4, 5], header=None + ) + if len(df.columns) == 10: + df.columns = [ + "Dia", + "Hora", + "HBV", + "Chuva", + "DirVento", + "VelVento", + "Temperatura", + "Pressao", + "Umidade", + "teste", + ] + del df["teste"] + else: + df.columns = [ + "Dia", + "Hora", + "HBV", + "Chuva", + "DirVento", + "VelVento", + "Temperatura", + "Pressao", + "Umidade", + ] + df["Chuva"] = df["Chuva"][~df["Chuva"].isin(["-", "ND"])].astype(float) + df["Umidade"] = df["Umidade"][df["Umidade"] != "ND"].astype(float) + df["Temperatura"] = df["Temperatura"][df["Temperatura"] != "ND"].astype( + float + ) + df["DirVento"] = df["DirVento"][ + ~df["DirVento"].isin(["-", "ND"]) + ].astype(float) + df["VelVento"] = df["VelVento"][df["VelVento"] != "ND"].astype(float) + df["Pressao"] = df["Pressao"][df["Pressao"] != "ND"].astype(float) + df["Dia"] = pd.to_datetime(df["Dia"], format="%d/%m/%Y") + ano_aux = year + mes_aux = month + print(year + "/" + month) + check = 1 + break + else: + pass + if check == 1: + break + + ano1 = list(map(str, range(int(ano_aux), arg_end))) + mes1 = list(range(int(mes_aux), 13)) + mes1 = [str(i).rjust(2, "0") for i in mes1] + + for year in ano1: + for month in mes1: + texto = ( + "../data/RAW_data/COR/meteorologica/aux_" + + station_name + + "/" + + station_name + + "_" + + year + + month + + "_Met2.txt" + ) + if os.path.exists(texto): + data2 = pd.read_csv( + texto, + sep=" ", + skiprows=[0, 1, 2, 3, 4, 5], + header=None, + on_bad_lines="skip", + ) + if len(data2.columns) == 10: + data2.columns = [ + "Dia", + "Hora", + "HBV", + "Chuva", + "DirVento", + "VelVento", + "Temperatura", + "Pressao", + "Umidade", + "teste", + ] + del data2["teste"] + else: + data2.columns = [ + "Dia", + "Hora", + "HBV", + "Chuva", + "DirVento", + "VelVento", + "Temperatura", + "Pressao", + "Umidade", + ] + data2["Chuva"] = data2["Chuva"][ + ~data2["Chuva"].isin(["-", "ND"]) + ].astype(float) + data2["Umidade"] = data2["Umidade"][data2["Umidade"] != "ND"].astype( + float + ) + data2["Temperatura"] = data2["Temperatura"][ + ~data2["Temperatura"].isin(["-", "ND"]) + ].astype(float) + data2["DirVento"] = data2["DirVento"][ + ~data2["DirVento"].isin(["-", "ND"]) + ].astype(float) + data2["VelVento"] = data2["VelVento"][data2["VelVento"] != "ND"].astype( + float + ) + data2["Pressao"] = data2["Pressao"][data2["Pressao"] != "ND"].astype( + float + ) + data2["Dia"] = pd.to_datetime(data2["Dia"], format="%d/%m/%Y") + saida = pd.concat([df, data2]) + df = saida + del saida + else: + pass + if year == ano_aux: + mes1 = list(range(1, 13)) + mes1 = [str(i).rjust(2, "0") for i in mes1] + df = df.replace("ND", np.NaN) + df = df.replace("-", np.NaN) + df = df[df["Hora"].str[2:6] == ":00:"] + df["Hora"] = np.where( + df["HBV"] == "HBV", + df["Hora"].str[0:2].astype(int) - 1, + df["Hora"].str[0:2].astype(int), + ) + df["Hora"] = np.where(df["Hora"] == -1, 23, df["Hora"]) + df["Hora"] = df["Hora"].astype(str).str.zfill(2) + ":00:00" + + df["estacao"] = station_name + df.to_csv("../data/landing/" + station_name + ".csv") + data_aux = df + del df, data2 + return data_aux + + +def main(argv): + station_name = "" + default_initial_year = 1997 + + today = datetime.date.today() + default_final_year = today.year + + arg_help = "{0} -s -b -e ".format(argv[0]) + + try: + opts, args = getopt.getopt( + argv[1:], "hs:a:b:e:", ["help", "station=", "begin=", "end="] + ) + except getopt.GetoptError as err: + print(err) + print(arg_help) + sys.exit(2) + + for opt, arg in opts: + if opt in ("-h", "--help"): + print(arg_help) # print the help message + sys.exit(2) + elif opt in ("-s", "--station"): + station_name = arg + if not ((station_name == "all") or (station_name in STATION_NAMES_FOR_RJ)): + print(arg_help) # print the help message + sys.exit(2) + elif opt in ("-b", "--begin"): + default_initial_year = arg + elif opt in ("-e", "--end"): + default_final_year = arg + + import_data(station_name, default_initial_year, default_final_year) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/surface_stations/retrieve_ws_cemaden.py b/src/surface_stations/retrieve_ws_cemaden.py new file mode 100644 index 00000000..9a478a9e --- /dev/null +++ b/src/surface_stations/retrieve_ws_cemaden.py @@ -0,0 +1,160 @@ +import argparse +import io +import json +import os +import time +from datetime import datetime + +import pandas as pd +import requests +from dateutil.relativedelta import relativedelta + +from config import globals + +TOKEN_FILE = "./config/token_demaden.json" +rota = "https://sws.cemaden.gov.br/PED/rest" +rota_token = "https://sgaa.cemaden.gov.br/SGAA/rest" + + +def get_token(email, senha): + url = rota_token + "/controle-token/tokens" + if os.path.exists(TOKEN_FILE): + with open(TOKEN_FILE, "r") as f: + token_data = json.load(f) + saved_at = token_data.get("saved_at", 0) + time_to_exp = int(token_data.get("timeToExp", 0)) + if int(time.time()) - saved_at <= time_to_exp: + return token_data.get("token", 0) + + payload = {"email": email, "password": senha} + response = requests.post(url, json=payload) + token_data = response.json() + token_data["saved_at"] = int(time.time()) + + with open(TOKEN_FILE, "w") as f: + json.dump(token_data, f) + + return token_data.get("token", 0) + + +def get_estacoes(codibge, email, senha): + url = rota + "/pcds-cadastro/estacoes" + token = get_token(email, senha) + headers = {"token": token} + tipos_est = requests.get( + rota + "/pcds-tipo-estacao/sensores", headers=headers + ).json() + estacoes_tipo = {e["tipoestacao"]: e for e in tipos_est} + + estacoes = [] + for cod in codibge: + time.sleep(5) + params = {"codibge": cod} + response = requests.get(url, params=params, headers=headers).json() + for est in response: + cod_estacao = est.get("codestacao", 0) + tipo_id = est.get("id_tipoestacao", None) + sensores = [ + s["sensordescricao"] + for s in estacoes_tipo.get(tipo_id, {}).get("sensor", []) + ] + estacoes.append((cod_estacao, sensores)) + return estacoes + + +def get_dados_estacoes(codibge, email, senha, inicio=None, fim=None, codestacao=None): + url = rota + "/pcds/dados_pcd" + + if codestacao: + estacoes = [(codestacao, [])] # Lista com uma estação só + else: + estacoes = get_estacoes(codibge, email, senha) + + print("estações ", estacoes) + start_date = ( + datetime.strptime(inicio, "%Y-%m-%d") if inicio else datetime(2015, 1, 1) + ) + end_date = datetime.strptime(fim, "%Y-%m-%d") if fim else datetime.today() + + for est in estacoes: + token = get_token(email, senha) + current = start_date + todos_dados = [] + headers = {"token": token} + + while current < end_date: + data_inicio = current.strftime("%Y%m010000") + proximo_mes = current + relativedelta(months=1) + data_fim = proximo_mes.strftime("%Y%m010000") + + params = { + "inicio": data_inicio, + "fim": data_fim, + "rede": "11", + "codigo": est[0], + } + + print(f"Baixando: {data_inicio} até {data_fim} para estação {est[0]}") + response = requests.get(url, params=params, headers=headers) + + if response.status_code == 200: + try: + df = pd.read_csv(io.StringIO(response.text), sep=";", skiprows=1) + if df.empty: + continue + df_pivot = df.pivot( + index="datahora", columns="sensor", values="valor" + ).reset_index() + todos_dados.append(df_pivot) + except Exception as e: + print(f"Erro ao processar: {e}") + else: + print(f"Erro HTTP {response.status_code}: {response.text}") + current = proximo_mes + time.sleep(5) + + if todos_dados: + df_final = pd.concat(todos_dados, ignore_index=True) + filename = f"{est[0]}.parquet" + output_path = os.path.join(globals.CEMADEN_DATA_DIR, "raw", filename) + df_final.to_parquet(output_path, index=False) + print(f"Dados salvos em: {output_path}") + else: + print(f"Nenhum dado encontrado para estação {est[0]}.") + + +def main(): + parser = argparse.ArgumentParser( + description="Baixa dados meteorológicos por código IBGE ou estação usando API do Cemaden." + ) + parser.add_argument( + "--ibge", nargs="+", help="Código(s) IBGE do município (ex: 3304557)" + ) + parser.add_argument( + "--inicio", help="Data inicial no formato YYYY-MM-DD", default=None + ) + parser.add_argument("--fim", help="Data final no formato YYYY-MM-DD", default=None) + parser.add_argument("--email", required=True, help="E-mail de autenticação na API") + parser.add_argument("--senha", required=True, help="Senha de autenticação na API") + parser.add_argument( + "--estacao", required=False, help="Código de uma estação específica (ex: A627)" + ) + + args = parser.parse_args() + + # Validação básica: se não passou estação, precisa passar pelo menos 1 código IBGE + if not args.estacao and not args.ibge: + parser.error("Você deve fornecer --ibge ou --estacao.") + + get_dados_estacoes( + codibge=args.ibge, + email=args.email, + senha=args.senha, + inicio=args.inicio, + fim=args.fim, + codestacao=args.estacao, + ) + + +if __name__ == "__main__": + main() diff --git a/src/surface_stations/retrieve_ws_cemaden_DEPRECATED.py b/src/surface_stations/retrieve_ws_cemaden_DEPRECATED.py new file mode 100644 index 00000000..dfa6f69a --- /dev/null +++ b/src/surface_stations/retrieve_ws_cemaden_DEPRECATED.py @@ -0,0 +1,108 @@ +import argparse +import datetime as dt +import time + +import pandas as pd +import requests + +# Constant for retry delay +RETRY_DELAY = 1800 # 30 minutes in seconds + + +def download_weather_data(uf, id_station, start_date, end_date, output_file, log_file): + start_datetime = dt.datetime.strptime(start_date, "%Y%m%d%H%M") + end_datetime = dt.datetime.strptime(end_date, "%Y%m%d%H%M") + + current_datetime = start_datetime + dataframes = [] + log_data = [] + start_time = time.time() + contador = 0 + + while current_datetime <= end_datetime: + try: + formatted_date = current_datetime.strftime("%d/%m/%Y %H:%M") + print(f"Downloading data for: {formatted_date}") + + url = f"http://sjc.salvar.cemaden.gov.br/resources/graficos/interativo/getJson2.php?uf={uf}&idestacao={id_station}&datahoraUltimovalor={formatted_date}" + response = requests.get(url) + response.raise_for_status() + + clima = response.json() + + if clima: + df = pd.DataFrame(clima) + dataframes.append(df) + log_entry = create_log_entry(formatted_date, "Success") + log_data.append(log_entry) + else: + log_entry = create_log_entry(formatted_date, "Error: No data") + log_data.append(log_entry) + contador += 1 + + except requests.exceptions.RequestException as e: + print(f"Request error: {e}") + log_entry = create_log_entry(formatted_date, f"Request error: {e}") + log_data.append(log_entry) + time.sleep(RETRY_DELAY) # Retry after delay + + current_datetime += dt.timedelta(hours=1) + + end_time = time.time() + end_time - start_time + + final_df = pd.concat(dataframes, ignore_index=True) + final_df.to_csv(output_file, index=False) + + log_df = pd.DataFrame(log_data) + log_df.to_csv(log_file, index=False) + + +def create_log_entry(timestamp, status): + """Helper function to create a log entry.""" + return { + "datahoraUltimovalor": timestamp, + "Status": status, + } + + +def parse_arguments(): + """Parse command-line arguments.""" + description = "Choose the State, station, and the start and end dates." + parser = argparse.ArgumentParser(description=description) + parser.add_argument("-e", "--estado", required=True, help="State") + parser.add_argument("-c", "--idestacao", required=True, help="Station ID") + parser.add_argument( + "-start", + "--start_date", + required=True, + help="Start date in format YYYYMMDDHHMM", + ) + parser.add_argument( + "-end", "--end_date", required=True, help="End date in format YYYYMMDDHHMM" + ) + parser.add_argument( + "-o", "--output_file", required=True, help="Output CSV file name" + ) + return parser.parse_args() + + +""" +CEMADEN (National Center for Monitoring and Early Warning of Natural Disasters) is a Brazilian agency responsible for monitoring natural hazards. +This programa downloads weather station data from the CEMADEN website, given a state, station ID, and a date range. +The data is saved in a CSV file and a log file is created to keep track of the download status. + +# Example usage: +# python retrieve_ws_cemaden.py -e "RJ" -c "330455718A" -start "202303010600" -end "202303031200" -o "output_data.csv" +""" +if __name__ == "__main__": + args = parse_arguments() + log_file = "log.csv" + download_weather_data( + args.estado, + args.idestacao, + args.start_date, + args.end_date, + args.output_file, + log_file, + ) diff --git a/src/surface_stations/retrieve_ws_inmet.py b/src/surface_stations/retrieve_ws_inmet.py new file mode 100644 index 00000000..1abd2a4d --- /dev/null +++ b/src/surface_stations/retrieve_ws_inmet.py @@ -0,0 +1,122 @@ +import argparse +import sys +from datetime import datetime + +import pandas as pd + +from config import globals + + +def retrieve_from_station(station_id, beginning_year, end_year, api_token): + current_date = datetime.now() + current_year = current_date.year + end_year = min(end_year, current_year) + + years = list(range(beginning_year, end_year + 1)) + df_inmet_stations = pd.read_json(globals.INMET_API_BASE_URL + "/estacoes/T") + station_row = df_inmet_stations[df_inmet_stations["CD_ESTACAO"] == station_id] + df_observations_for_all_years = None + print(f"Downloading observations from weather station {station_id}...") + for year in years: + print(f"Downloading observations for year {year}...") + + if year == end_year: + datetime_str = str(end_year) + "-12-31" + last_date_of_the_end_year = datetime.strptime(datetime_str, "%Y-%m-%d") + end_date = min(last_date_of_the_end_year, current_date) + end_date_str = end_date.strftime("%Y-%m-%d") + query_str = ( + globals.INMET_API_BASE_URL + + "/token/estacao/" + + str(year) + + "-01-01/" + + end_date_str + + "/" + + station_id + + "/" + + api_token + ) + else: + query_str = ( + globals.INMET_API_BASE_URL + + "/token/estacao/" + + str(year) + + "-01-01/" + + str(year) + + "-12-31/" + + station_id + + "/" + + api_token + ) + + print(f"Query to be sent to server: {query_str}") + + df_observations_for_a_year = pd.read_json(query_str) + if df_observations_for_all_years is None: + temp = [df_observations_for_a_year] + else: + temp = [df_observations_for_all_years, df_observations_for_a_year] + df_observations_for_all_years = pd.concat(temp) + filename = ( + globals.WS_INMET_DATA_DIR + station_row["CD_ESTACAO"].iloc[0] + ".parquet" + ) + print(f"Done! Saving dowloaded content to '{filename}'.") + df_observations_for_all_years.to_parquet(filename) + + +def retrieve_data(station_id, initial_year, final_year, api_token): + if station_id == "all": + df_inmet_stations = pd.read_json(globals.INMET_API_BASE_URL + "/estacoes/T") + station_row = df_inmet_stations[ + df_inmet_stations["CD_ESTACAO"].isin(globals.INMET_WEATHER_STATION_IDS) + ] + for j in list(range(0, len(station_row))): + station_id = station_row["CD_ESTACAO"].iloc[j] + retrieve_from_station(station_id, initial_year, final_year, api_token) + else: + retrieve_from_station(station_id, initial_year, final_year, api_token) + + +def main(argv): + station_id = "" + + parser = argparse.ArgumentParser( + prog=argv[0], + usage="{0} -s -b -e -t ".format( + argv[0] + ), + description="""This script provides a simple interface for retrieving observations + made by a user-provided weather station from the INMET archive.""", + ) + parser.add_argument( + "-t", "--api_token", required=True, help="INMET API token", metavar="" + ) + parser.add_argument( + "-s", "--station_id", required=True, help="Weather station ID", metavar="" + ) + parser.add_argument( + "-b", "--begin_year", type=int, required=True, help="Start year", metavar="" + ) + parser.add_argument( + "-e", "--end_year", type=int, required=True, help="End year", metavar="" + ) + + args = parser.parse_args(argv[1:]) + + api_token = args.api_token + station_id = args.station_id + start_year = args.begin_year + end_year = args.end_year + + if station_id not in globals.INMET_WEATHER_STATION_IDS: + parser.error(f"Invalid station ID: {station_id}") + + assert (api_token is not None) and (api_token != "") + assert (station_id is not None) and (station_id != "") + assert start_year <= end_year + + retrieve_data(station_id, start_year, end_year, api_token) + + +if __name__ == "__main__": + main(sys.argv) diff --git a/src/surface_stations/retrieve_ws_redemet.py b/src/surface_stations/retrieve_ws_redemet.py new file mode 100644 index 00000000..b428c6bc --- /dev/null +++ b/src/surface_stations/retrieve_ws_redemet.py @@ -0,0 +1,184 @@ +import argparse +import datetime as dt +import json +import time + +import pandas as pd +import requests + + +def qtd_stations(): + stations_rj = ["SBGL", "SBAF", "SBRJ", "SBJR", "SBSC"] + print( + "Na cidade do Rio de Janeiro temos o total de:", + len(stations_rj), + "estações meteorológicas", + (stations_rj), + ) + print("Iniciando") + + +def start_data(api_key, station, start_date, end_date, output_file, log_file): + current_date = start_date + dataframes = [] + log_data = [] + error_log = [] + start_time = time.time() + contador = 0 + + while current_date <= end_date: + try: + url = requests.get( + f"https://api-redemet.decea.mil.br/aerodromos/info?api_key={api_key}&localidade={station}&datahora={current_date}" + ) + url.raise_for_status() + clima = json.loads(url.text) + + if clima: + df = pd.DataFrame(clima) + + if "message" in clima: + df = df.drop("message", axis=1) + + if "status" in clima: + df = df.drop("status", axis=1) + + dataset = df.T + + dataset.rename(columns={"ur": "relative_humidity"}, inplace=True) + dataset.rename(columns={"data": "datatime"}, inplace=True) + dataset["barometric_pressure"] = None + dataset["wind_speed"] = None + dataset["wind_dir"] = None + + if "barometric_pressure" in dataset: + dataset["barometric_pressure"] = dataset["metar"].str.extract( + r"(Q\d{4})" + ) + dataset["barometric_pressure"] = dataset[ + "barometric_pressure" + ].str.replace("Q", "", regex=True) + + if "vento" in dataset: + dataset["wind_speed"] = dataset["vento"].str.extract( + r"(\d{1,2}km/h)" + ) + dataset["wind_dir"] = dataset["vento"].str.extract(r"(\d{2,3}º)") + dataset["wind_dir"] = dataset["wind_dir"].str.replace("º", "") + + if "nome" in dataset: + dataset = dataset.drop("nome", axis=1) + + if "ceu" in dataset: + dataset = dataset.drop("ceu", axis=1) + + if "cidade" in dataset: + dataset = dataset.drop("cidade", axis=1) + + if "condicoes_tempo" in dataset: + dataset = dataset.drop("condicoes_tempo", axis=1) + + if "localizacao" in dataset: + dataset = dataset.drop("localizacao", axis=1) + + if "metar" in dataset: + dataset = dataset.drop("metar", axis=1) + + if "tempoImagem" in dataset: + dataset = dataset.drop("tempoImagem", axis=1) + + if "teto" in dataset: + dataset = dataset.drop("teto", axis=1) + + if "visibilidade" in dataset: + dataset = dataset.drop("visibilidade", axis=1) + + if "vento" in dataset: + dataset = dataset.drop("vento", axis=1) + + if "lat" in dataset: + dataset = dataset.drop("lat", axis=1) + + if "lon" in dataset: + dataset = dataset.drop("lon", axis=1) + + dataframes.append(dataset) + log_entry = { + "Data": current_date, + "Status": "Sucesso", + } + log_data.append(log_entry) + else: + log_entry = { + "Data": current_date, + "Status": "Erro: Sem dados", + } + + log_data.append(log_entry) + contador += 1 + except requests.exceptions.RequestException as e: + if "429" and "443" in str(e): + print("Erro 429: Muitas solicitações. Primeiro looping") + log_entry = { + "Data": current_date, + "Status": "Erro 429: Muitas solicitações", + } + error_log.append(log_entry) + # retry_data.append(current_date) + time.sleep(1800) + else: + print(f"Erro na solicitação HTTP: {e}") + break + current_date = ( + dt.datetime.strptime(current_date, "%Y%m%d%H") + dt.timedelta(hours=1) + ).strftime("%Y%m%d%H") + + end_time = time.time() + total_time = end_time - start_time + log_df = pd.DataFrame(log_data) + log_df.to_csv(log_file, index=False) + + if dataframes: + combined_df = pd.concat(dataframes, ignore_index=True) + combined_df.to_csv(f"{output_file}.csv", index=False) + print(f"Dados salvos em {output_file}.csv") + print(f"Tempo total: {total_time} segundos") + print( + f"O máximo de requisições é de {contador}, após isso precisa fazer uma nova com uma chave nova" + ) + + +def argumentos(): + description = "Escolha a estação meteorológica, sua chave de API e as datas de início e fim no formato AAAAMMDDHH." + parser = argparse.ArgumentParser(description=description) + parser.add_argument("-k", "--key", required=True, help="Chave de API") + parser.add_argument( + "-s", "--station", required=True, help="Estação meteorológica (exemplo: SBBR)" + ) + parser.add_argument( + "-start", + "--start_date", + required=True, + help="Data de início no formato AAAAMMDDHH", + ) + parser.add_argument( + "-end", "--end_date", required=True, help="Data de fim no formato AAAAMMDDHH" + ) + parser.add_argument( + "-o", "--output_file", required=True, help="Nome do arquivo de saída CSV" + ) + return parser.parse_args() + + +if __name__ == "__main__": + qtd_stations() + args = argumentos() + log_file = "log.csv" + start_data( + args.key, + args.station, + args.start_date, + args.end_date, + args.output_file, + log_file, + ) diff --git a/src/surface_stations/retrieve_ws_websirene.py b/src/surface_stations/retrieve_ws_websirene.py new file mode 100644 index 00000000..e69e27b4 --- /dev/null +++ b/src/surface_stations/retrieve_ws_websirene.py @@ -0,0 +1,486 @@ +import argparse +import os +import sys +import time +from collections import defaultdict +from concurrent.futures import ThreadPoolExecutor, as_completed +from dataclasses import dataclass, field +from datetime import datetime +from threading import Lock +from typing import Iterable, Iterator, Sequence +from xml.etree import ElementTree as ET + +import pandas as pd +import requests + +REQUEST_INTERVAL_SECONDS = 0.1 +MAX_FETCH_ATTEMPTS = 3 +BACKOFF_SECONDS = 5 +DEFAULT_RATE_PER_SECOND = 2.5 +DEFAULT_MAX_WORKERS = 8 +REQUEST_TIMEOUT = 30 +# The WebSirene API appears to interpret the date as MM/DD/YYYY despite accepting DD/MM/YYYY. +# We try both formats to handle ambiguous days (1-12). +PRIMARY_TIMESTAMP_FORMAT = "%m/%d/%Y %H:%M" +FALLBACK_TIMESTAMP_FORMAT = "%d/%m/%Y %H:%M" + + +def parse_cli_datetime(raw_datetime: str) -> datetime: + supported_formats = ("%d/%m/%Y %H:%M", "%d-%m-%Y %H:%M") + for fmt in supported_formats: + try: + return datetime.strptime(raw_datetime, fmt) + except ValueError: + continue + raise ValueError( + f"'{raw_datetime}' is not in a supported format (expected DD/MM/YYYY HH:MM or DD-MM-YYYY HH:MM)." + ) + + +def make_time_blocks(start: pd.Timestamp, end: pd.Timestamp, block_days: int) -> Iterator[tuple[pd.Timestamp, pd.Timestamp]]: + cursor = start + delta = pd.Timedelta(days=block_days) + while cursor < end: + block_end = min(cursor + delta, end) + yield cursor, block_end + cursor = block_end + + +def _clean_text(value: str | None) -> str: + if value is None: + return "" + return value.strip() + + +def _parse_numeric(value: str | None) -> float | None: + if value is None: + return None + cleaned = value.strip() + if not cleaned or cleaned.lower() == "null": + return None + cleaned = cleaned.replace(",", ".") + try: + return float(cleaned) + except ValueError: + return None + + +def _extract_rain_value(chuvas_elem: ET.Element) -> float | None: + """Prefer chuvas@m5; fallback to other possible numeric fields.""" + if chuvas_elem is None: + return None + primary = _parse_numeric(chuvas_elem.get("m5")) + if primary is not None: + return primary + fallback_sources = [ + chuvas_elem.get("chuva"), + chuvas_elem.get("h01"), + chuvas_elem.get("h04"), + chuvas_elem.get("h24"), + chuvas_elem.get("h96"), + ] + for candidate in chuvas_elem.findall(".//chuva"): + fallback_sources.append(_clean_text(candidate.text)) + for source in fallback_sources: + parsed = _parse_numeric(source) + if parsed is not None: + return parsed + return None + + +def _extract_rain_fields(chuvas_elem: ET.Element) -> dict: + """Return a dict with all rain accumulation windows present in the chuvas element.""" + fields = { + "m5": _parse_numeric(chuvas_elem.get("m5")) if chuvas_elem is not None else None, + "m15": _parse_numeric(chuvas_elem.get("m15")) if chuvas_elem is not None else None, + "h01": _parse_numeric(chuvas_elem.get("h01")) if chuvas_elem is not None else None, + "h04": _parse_numeric(chuvas_elem.get("h04")) if chuvas_elem is not None else None, + "h24": _parse_numeric(chuvas_elem.get("h24")) if chuvas_elem is not None else None, + "h96": _parse_numeric(chuvas_elem.get("h96")) if chuvas_elem is not None else None, + "mes": _parse_numeric(chuvas_elem.get("mes")) if chuvas_elem is not None else None, + } + # Keep backward compatibility: "rains" mirrors m5 when available, otherwise fallback. + fields["rains"] = fields.get("m5") if fields.get("m5") is not None else _extract_rain_value(chuvas_elem) + return fields + + +def _format_duration(seconds: float) -> str: + seconds = int(seconds) + mins, sec = divmod(seconds, 60) + hrs, mins = divmod(mins, 60) + return f"{hrs:02d}:{mins:02d}:{sec:02d}" + + +def parse_month_list(raw: str | None) -> set[int]: + if not raw: + return set() + months: set[int] = set() + for part in raw.split(','): + part = part.strip() + if not part: + continue + try: + month = int(part) + except ValueError: + raise ValueError(f"Invalid month '{part}'. Use numbers 1-12 separated by commas.") + if month < 1 or month > 12: + raise ValueError(f"Invalid month '{part}'. Use numbers 1-12.") + months.add(month) + return months + + +def _extract_station_catalog(xml_content: str) -> list[dict]: + root = ET.fromstring(xml_content) + stations: list[dict] = [] + for station_elem in root.findall(".//estacao"): + raw_id = station_elem.get("id") + try: + station_id = int(raw_id) if raw_id is not None else None + except ValueError: + station_id = None + loc_elem = station_elem.find("localizacao") + latitude = _parse_numeric(loc_elem.get("latitude")) if loc_elem is not None else None + longitude = _parse_numeric(loc_elem.get("longitude")) if loc_elem is not None else None + stations.append( + { + "id": station_id, + "nome": _clean_text(station_elem.get("nome")), + "type": _clean_text(station_elem.get("type")), + "latitude": latitude, + "longitude": longitude, + } + ) + return [s for s in stations if s.get("id") is not None] + + +def fetch_station_catalog() -> list[dict]: + url = "http://websirene.rio.rj.gov.br/xml/chuvas.xml" + response = requests.get(url, timeout=30) + response.raise_for_status() + encoding = response.encoding or response.apparent_encoding or "latin-1" + response.encoding = encoding + return _extract_station_catalog(response.text) + + +def _extract_all_station_payloads(xml_content: str, station_ids_filter: set[int]) -> list[dict]: + root = ET.fromstring(xml_content) + payloads: list[dict] = [] + for station_elem in root.findall(".//estacao"): + raw_id = station_elem.get("id") + if raw_id is None: + continue + try: + current_id = int(raw_id) + except ValueError: + continue + if station_ids_filter and current_id not in station_ids_filter: + continue + + chuvas_elem = station_elem.find("chuvas") + observation_dt = None + rain_value = None + if chuvas_elem is not None: + hora_attr = chuvas_elem.get("hora") + if hora_attr: + observation_dt = pd.to_datetime(hora_attr, utc=True, errors="coerce") + rain_value = _extract_rain_value(chuvas_elem) + rain_fields = _extract_rain_fields(chuvas_elem) if chuvas_elem is not None else {k: None for k in ["m5","m15","h01","h04","h24","h96","mes","rains"]} + + loc_elem = station_elem.find("localizacao") + latitude = _parse_numeric(loc_elem.get("latitude")) if loc_elem is not None else None + longitude = _parse_numeric(loc_elem.get("longitude")) if loc_elem is not None else None + + payloads.append( + { + "id": current_id, + "nome": _clean_text(station_elem.get("nome")), + "type": _clean_text(station_elem.get("type")), + "latitude": latitude, + "longitude": longitude, + "rains": rain_value, + "m5": rain_fields.get("m5"), + "m15": rain_fields.get("m15"), + "h01": rain_fields.get("h01"), + "h04": rain_fields.get("h04"), + "h24": rain_fields.get("h24"), + "h96": rain_fields.get("h96"), + "mes": rain_fields.get("mes"), + "observation_datetime": observation_dt, + } + ) + return payloads + + +@dataclass +class RateLimiter: + rate_per_second: float + allowance: float = 0.0 + last_check: float = time.monotonic() + _lock: Lock = field(default_factory=Lock, init=False, repr=False) + + def acquire(self) -> None: + if self.rate_per_second <= 0: + return + with self._lock: + current = time.monotonic() + time_passed = current - self.last_check + self.last_check = current + self.allowance += time_passed * self.rate_per_second + if self.allowance > self.rate_per_second: + self.allowance = self.rate_per_second + if self.allowance < 1.0: + sleep_time = (1.0 - self.allowance) / self.rate_per_second + time.sleep(sleep_time) + self.allowance = 0.0 + else: + self.allowance -= 1.0 + + +def _fetch_with_format(ts: pd.Timestamp, ts_format: str, station_ids_filter: set[int], session: requests.Session, rate_limiter: RateLimiter) -> list[dict]: + rate_limiter.acquire() + timestamp_str = ts.strftime(ts_format) + url = f"http://websirene.rio.rj.gov.br/xml/chuvas.xml?time={timestamp_str}" + for attempt in range(1, MAX_FETCH_ATTEMPTS + 1): + try: + response = session.get(url, timeout=REQUEST_TIMEOUT) + response.raise_for_status() + encoding = response.encoding or response.apparent_encoding or "latin-1" + response.encoding = encoding + payloads = _extract_all_station_payloads(response.text, station_ids_filter) + if not payloads: + return [] + df = pd.DataFrame(payloads) + df["request_datetime"] = ts + df["observation_datetime"] = pd.to_datetime(df["observation_datetime"], utc=True, errors="coerce") + # Keep only rows matching the requested calendar date to avoid swapped month/day. + df = df[df["observation_datetime"].dt.date == ts.date()] + if df.empty: + return [] + return df.to_dict(orient="records") + except (requests.exceptions.RequestException, ET.ParseError): + if attempt < MAX_FETCH_ATTEMPTS: + time.sleep(BACKOFF_SECONDS * attempt) + continue + return [] + + +def fetch_timestamp(ts: pd.Timestamp, station_ids_filter: set[int], session: requests.Session, rate_limiter: RateLimiter) -> list[dict]: + # Try primary (MM/DD) first, fallback to DD/MM if observation months clearly mismatch. + recs_primary = _fetch_with_format(ts, PRIMARY_TIMESTAMP_FORMAT, station_ids_filter, session, rate_limiter) + if recs_primary: + obs_months = pd.DataFrame(recs_primary)["observation_datetime"].dt.month.dropna() + if not obs_months.empty and obs_months.mode().iloc[0] == ts.month: + return recs_primary + recs_fallback = _fetch_with_format(ts, FALLBACK_TIMESTAMP_FORMAT, station_ids_filter, session, rate_limiter) + return recs_fallback or recs_primary + + +def group_and_dedup(records: Iterable[dict]) -> dict[int, pd.DataFrame]: + per_station: dict[int, list[dict]] = defaultdict(list) + for rec in records: + if rec is None: + continue + station_id = rec.get("id") + if station_id is None: + continue + per_station[int(station_id)].append(rec) + result: dict[int, pd.DataFrame] = {} + for station_id, recs in per_station.items(): + df = pd.DataFrame(recs) + if df.empty: + continue + df = df.dropna(subset=["observation_datetime"]) + if df.empty: + continue + df = df.drop_duplicates(subset=["observation_datetime"]) + df = df.sort_values(by="observation_datetime") + result[station_id] = df + return result + + +def write_partitioned(df: pd.DataFrame, output_dir: str, station_id: int, fmt: str = "parquet") -> None: + if df.empty: + return + df = df.copy() + df["year"] = df["observation_datetime"].dt.year + for year, chunk in df.groupby("year"): + base_dir = os.path.join(output_dir, f"station_id={station_id}", f"year={int(year)}") + os.makedirs(base_dir, exist_ok=True) + if fmt == "parquet": + path = os.path.join(base_dir, "data.parquet") + try: + if os.path.exists(path): + existing = pd.read_parquet(path) + chunk = pd.concat([existing, chunk], ignore_index=True) + chunk = chunk.drop_duplicates(subset=["observation_datetime"]) + chunk.sort_values(by="observation_datetime", inplace=True) + chunk.to_parquet(path, index=False) + continue + except Exception: + # fallback to CSV on parquet errors + fmt = "csv" + path = os.path.join(base_dir, "data.csv") + if os.path.exists(path): + existing = pd.read_csv(path, parse_dates=["observation_datetime", "request_datetime"]) + chunk = pd.concat([existing, chunk], ignore_index=True) + chunk = chunk.drop_duplicates(subset=["observation_datetime"]) + chunk.sort_values(by="observation_datetime", inplace=True) + chunk.to_csv(path, index=False) + + +def load_index(index_path: str) -> pd.DataFrame: + if not os.path.exists(index_path): + return pd.DataFrame(columns=["station_id", "first_obs", "last_obs", "last_request_dt", "row_count"]) + return pd.read_csv(index_path, parse_dates=["first_obs", "last_obs", "last_request_dt"]) + + +def update_index(index_df: pd.DataFrame, station_id: int, df: pd.DataFrame, request_dt: pd.Timestamp) -> pd.DataFrame: + if df.empty: + return index_df + first_obs = df["observation_datetime"].min() + last_obs = df["observation_datetime"].max() + row_count = len(df) + existing = index_df[index_df["station_id"] == station_id] + if existing.empty: + new_row = pd.DataFrame( + { + "station_id": [station_id], + "first_obs": [first_obs], + "last_obs": [last_obs], + "last_request_dt": [request_dt], + "row_count": [row_count], + } + ) + # Avoid FutureWarning when concatenating with an empty/all-NA frame. + return new_row if index_df.empty else pd.concat([index_df, new_row], ignore_index=True) + idx = existing.index[0] + index_df.loc[idx, "first_obs"] = min(first_obs, existing.iloc[0]["first_obs"]) + index_df.loc[idx, "last_obs"] = max(last_obs, existing.iloc[0]["last_obs"]) + index_df.loc[idx, "last_request_dt"] = request_dt + index_df.loc[idx, "row_count"] = existing.iloc[0]["row_count"] + row_count + return index_df + + +def should_skip(index_df: pd.DataFrame, station_id: int, ts: pd.Timestamp) -> bool: + row = index_df[index_df["station_id"] == station_id] + if row.empty: + return False + last_obs = row.iloc[0]["last_obs"] + if pd.isna(last_obs): + return False + return ts <= last_obs + + +def collect_block( + start_ts: pd.Timestamp, + end_ts: pd.Timestamp, + station_ids: Sequence[int], + rate_limiter: RateLimiter, + args, + index_df: pd.DataFrame, +) -> tuple[list[dict], pd.Timestamp]: + records: list[dict] = [] + session = requests.Session() + station_filter_set = set(station_ids) + timestamps = pd.date_range(start=start_ts, end=end_ts, freq="10min", inclusive="both") + with ThreadPoolExecutor(max_workers=args.max_workers) as pool: + futures = [] + for ts in timestamps: + if args.ignore_months and ts.month in args.ignore_months: + continue + if args.resume: + # If all stations already beyond last_obs, skip the timestamp entirely. + if all(should_skip(index_df, station_id, ts) for station_id in station_ids): + continue + futures.append(pool.submit(fetch_timestamp, ts, station_filter_set, session, rate_limiter)) + + for future in as_completed(futures): + recs = future.result() + if not recs: + continue + for rec in recs: + obs_dt = rec.get("observation_datetime") + if pd.isna(obs_dt): + continue + if obs_dt < start_ts or obs_dt > end_ts: + continue + records.append(rec) + last_request_dt = end_ts + return records, last_request_dt + + +def run_pipeline(args): + overall_start = time.monotonic() + try: + start_dt = parse_cli_datetime(args.start_date) + end_dt = parse_cli_datetime(args.end_date) + except ValueError as err: + print(f"Invalid datetime: {err}") + sys.exit(1) + + if end_dt < start_dt: + print("End date/time must be greater than or equal to the start date/time.") + sys.exit(1) + + start_dt_utc = pd.to_datetime(start_dt).tz_localize("UTC") + end_dt_utc = pd.to_datetime(end_dt).tz_localize("UTC") + + try: + ignore_months = parse_month_list(args.ignore_months) + except ValueError as err: + print(f"Invalid --ignore-months: {err}") + sys.exit(1) + args.ignore_months = ignore_months + + print(f"Period: {start_dt.strftime('%d/%m/%Y %H:%M')} to {end_dt.strftime('%d/%m/%Y %H:%M')}") + + # Catalog + if args.stations == "all": + try: + catalog = fetch_station_catalog() + station_ids = sorted(int(s["id"]) for s in catalog) + except Exception as e: + print(f"Failed to load station catalog: {e}") + sys.exit(1) + else: + station_ids = sorted(int(s) for s in args.stations.split(",") if s.strip()) + + os.makedirs(args.output_dir, exist_ok=True) + index_path = os.path.join(args.output_dir, "index.csv") + index_df = load_index(index_path) if args.resume else pd.DataFrame(columns=["station_id", "first_obs", "last_obs", "last_request_dt", "row_count"]) + + rate_limiter = RateLimiter(rate_per_second=args.rate_per_second) + + for block_start, block_end in make_time_blocks(start_dt_utc, end_dt_utc, args.block_size_days): + print(f"Processing block {block_start} -> {block_end} ({len(station_ids)} stations)") + records, last_request_dt = collect_block(block_start, block_end, station_ids, rate_limiter, args, index_df) + grouped = group_and_dedup(records) + if not grouped: + continue + for station_id, df in grouped.items(): + write_partitioned(df, args.output_dir, station_id, fmt=args.format) + index_df = update_index(index_df, station_id, df, last_request_dt) + index_df.to_csv(index_path, index=False) + + elapsed = time.monotonic() - overall_start + print(f"Done in {_format_duration(elapsed)}. Index saved at {index_path}") + + +def build_arg_parser(): + parser = argparse.ArgumentParser(description="Download full historical rain data for WebSirene stations.") + parser.add_argument("--start-date", required=True, help="Start date/time (DD/MM/YYYY HH:MM)") + parser.add_argument("--end-date", required=True, help="End date/time (DD/MM/YYYY HH:MM)") + parser.add_argument("--stations", default="all", help="Comma-separated station IDs or 'all'") + parser.add_argument("--output-dir", default="data/ws/full", help="Output directory for partitioned data") + parser.add_argument("--max-workers", type=int, default=DEFAULT_MAX_WORKERS, help="Concurrent workers (threads)") + parser.add_argument("--rate-per-second", type=float, default=DEFAULT_RATE_PER_SECOND, help="Max requests per second") + parser.add_argument("--block-size-days", type=int, default=1, help="Block size in days for processing") + parser.add_argument("--format", choices=["parquet", "csv"], default="parquet", help="Output format") + parser.add_argument("--resume", action="store_true", help="Resume using existing index to skip completed timestamps") + parser.add_argument("--ignore-months", default=None, help="Comma-separated list of months (1-12) to skip entirely, e.g., '6,7,8'") + return parser + + +if __name__ == "__main__": + args = build_arg_parser().parse_args() + run_pipeline(args) diff --git a/src/subsampling.py b/src/surface_stations/subsampling.py similarity index 63% rename from src/subsampling.py rename to src/surface_stations/subsampling.py index cd6d28ff..f9177dde 100644 --- a/src/subsampling.py +++ b/src/surface_stations/subsampling.py @@ -1,34 +1,42 @@ -from sklearn.ensemble import GradientBoostingClassifier -import numpy as np import logging +import numpy as np +from sklearn.ensemble import GradientBoostingClassifier + NAIVE_SUBSAMPLING_KEEP_RATIO = 0.05 # With negative subsampling (train/val/test): 13934/3142/10219. + def apply_subsampling(X, y, subsampling_strategy): - assert subsampling_strategy in ("NAIVE", "NEGATIVE") + assert subsampling_strategy in ("NAIVE", "NEGATIVE") if subsampling_strategy == "NAIVE": return apply_naive_subsampling(X, y) else: return apply_negative_subsampling(X, y) + def apply_naive_subsampling(X, y): """ Naive subsampling: keep all the positive instances and subsample the negative instances completely at random. """ y_eq_zero_idxs = np.where(y == 0)[0] y_gt_zero_idxs = np.where(y > 0)[0] - logging.info(f' - Original sizes (target=0)/(target>0): ({y_eq_zero_idxs.shape[0]})/({y_gt_zero_idxs.shape[0]})') + logging.info( + f" - Original sizes (target=0)/(target>0): ({y_eq_zero_idxs.shape[0]})/({y_gt_zero_idxs.shape[0]})" + ) logging.info(f" - Using keep ratio = {NAIVE_SUBSAMPLING_KEEP_RATIO}.") # Setting numpy seed value np.random.seed(0) - mask = np.random.choice([True, False], size=y.shape[0], p=[ - NAIVE_SUBSAMPLING_KEEP_RATIO, 1.0-NAIVE_SUBSAMPLING_KEEP_RATIO]) - y_train_subsample_idxs = np.where(mask == True)[0] + mask = np.random.choice( + [True, False], + size=y.shape[0], + p=[NAIVE_SUBSAMPLING_KEEP_RATIO, 1.0 - NAIVE_SUBSAMPLING_KEEP_RATIO], + ) + y_train_subsample_idxs = np.where(mask)[0] logging.info(f" - Subsample (total) size: {y_train_subsample_idxs.shape[0]}") idxs = np.intersect1d(y_eq_zero_idxs, y_train_subsample_idxs) @@ -38,17 +46,20 @@ def apply_naive_subsampling(X, y): X, y = X[idxs], y[idxs] y_eq_zero_idxs = np.where(y == 0)[0] y_gt_zero_idxs = np.where(y > 0)[0] - logging.info(f' - Resulting sizes (target=0)/(target>0): ({y_eq_zero_idxs.shape[0]})/({y_gt_zero_idxs.shape[0]})') + logging.info( + f" - Resulting sizes (target=0)/(target>0): ({y_eq_zero_idxs.shape[0]})/({y_gt_zero_idxs.shape[0]})" + ) return X, y + def apply_negative_subsampling(X_train, y_train): original_shape_X_train = X_train.shape - + X_train = X_train.reshape(len(X_train), -1) y_train_binarized = np.copy(y_train) - y_train_binarized[y_train_binarized>0] = 1 - + y_train_binarized[y_train_binarized > 0] = 1 + positive_indices = np.where(y_train_binarized == 1)[0] print("num examples in X_train:", len(X_train)) @@ -65,27 +76,38 @@ def apply_negative_subsampling(X_train, y_train): y_proba_normalized = score_negative_examples(clf, X_train, y_train_binarized) # Step 3: Sample the negative examples proportionally to their scores - negative_indices = sample_from_negative_examples(X_train, y_train_binarized, y_proba_normalized) - - X_train_sampled = np.concatenate((X_train[positive_indices], X_train[negative_indices])) - y_train_sampled = np.concatenate((y_train[positive_indices], y_train[negative_indices])) - - X_train_sampled = X_train_sampled.reshape((len(X_train_sampled), original_shape_X_train[1], original_shape_X_train[2])) + negative_indices = sample_from_negative_examples( + X_train, y_train_binarized, y_proba_normalized + ) + + X_train_sampled = np.concatenate( + (X_train[positive_indices], X_train[negative_indices]) + ) + y_train_sampled = np.concatenate( + (y_train[positive_indices], y_train[negative_indices]) + ) + + X_train_sampled = X_train_sampled.reshape( + (len(X_train_sampled), original_shape_X_train[1], original_shape_X_train[2]) + ) y_train_sampled = y_train_sampled.reshape(-1, 1) return X_train_sampled, y_train_sampled + def train_pilot_model(X_train, y_train): - ''' - Train the pilot model on a balanced dataset. This balanced dataset is built in - such a way that it has equal amounts of positive and negative examples. If there + """ + Train the pilot model on a balanced dataset. This balanced dataset is built in + such a way that it has equal amounts of positive and negative examples. If there are P positive examples in the original training set, then P negative - examples will be uniformly sampled from it to put into the balanced dataset. All + examples will be uniformly sampled from it to put into the balanced dataset. All the positive examples in the original dataset are put in the balanced dataset. - ''' + """ y_eq_zero_idxs = np.where(y_train == 0)[0] y_gt_zero_idxs = np.where(y_train > 0)[0] - logging.info(f"Amounts of neg/pos examples: {len(y_eq_zero_idxs)}/{len(y_gt_zero_idxs)}") + logging.info( + f"Amounts of neg/pos examples: {len(y_eq_zero_idxs)}/{len(y_gt_zero_idxs)}" + ) X_train_positives = X_train[y_gt_zero_idxs] X_train_negatives = X_train[y_eq_zero_idxs] @@ -97,22 +119,34 @@ def train_pilot_model(X_train, y_train): num_negative_examples_to_sample = min(num_positive_examples, num_negative_examples) - positive_indices = np.random.choice(num_positive_examples, size=num_negative_examples_to_sample, replace=False) - negative_indices = np.random.choice(num_negative_examples, size=num_negative_examples_to_sample, replace=False) - - X_train_balanced = np.concatenate((X_train_positives[positive_indices], X_train_negatives[negative_indices])) - y_train_balanced = np.concatenate((np.ones(num_negative_examples_to_sample), np.zeros(num_negative_examples_to_sample))) - - assert len(y_train_balanced) == 2*num_negative_examples_to_sample + positive_indices = np.random.choice( + num_positive_examples, size=num_negative_examples_to_sample, replace=False + ) + negative_indices = np.random.choice( + num_negative_examples, size=num_negative_examples_to_sample, replace=False + ) + + X_train_balanced = np.concatenate( + (X_train_positives[positive_indices], X_train_negatives[negative_indices]) + ) + y_train_balanced = np.concatenate( + ( + np.ones(num_negative_examples_to_sample), + np.zeros(num_negative_examples_to_sample), + ) + ) + + assert len(y_train_balanced) == 2 * num_negative_examples_to_sample # Create a GradientBoostingClassifier object with default hyperparameters clf = GradientBoostingClassifier() # Train the classifier on the balanced training dataset clf.fit(X_train_balanced, y_train_balanced) - + return clf + def score_negative_examples(clf, X_train, y_train): y_eq_zero_idxs = np.where(y_train == 0)[0] X_train_negatives = X_train[y_eq_zero_idxs] @@ -128,19 +162,26 @@ def score_negative_examples(clf, X_train, y_train): y_proba_normalized = y_proba_negative / np.sum(y_proba_negative) N = 5 - logging.info(f"Normalized scores for the first {N} negative examples: {y_proba_normalized[:N]}") - logging.info(f"Correct labels for the first {N} negative examples: {y_train_negatives[:N]}") - + logging.info( + f"Normalized scores for the first {N} negative examples: {y_proba_normalized[:N]}" + ) + logging.info( + f"Correct labels for the first {N} negative examples: {y_train_negatives[:N]}" + ) + return y_proba_normalized + def sample_from_negative_examples(X_train, y_train, y_proba_normalized): y_eq_zero_idxs = np.where(y_train == 0)[0] y_gt_zero_idxs = np.where(y_train > 0)[0] - + positive_examples = X_train[y_gt_zero_idxs] num_positive_examples = len(positive_examples) # Sample the indices using the normalized probabilities - negative_sampled_idxs = np.random.choice(y_eq_zero_idxs, size=num_positive_examples, replace=False, p=y_proba_normalized) + negative_sampled_idxs = np.random.choice( + y_eq_zero_idxs, size=num_positive_examples, replace=False, p=y_proba_normalized + ) return negative_sampled_idxs diff --git a/src/train_model.py b/src/surface_stations/train_model.py similarity index 76% rename from src/train_model.py rename to src/surface_stations/train_model.py index 70e36cdd..47931b65 100644 --- a/src/train_model.py +++ b/src/surface_stations/train_model.py @@ -1,31 +1,32 @@ +import argparse +import logging +import sys +import time + +import numpy as np import torch import torch.nn as nn import torch.nn.functional as F import yaml -import time -import numpy as np -import sys -import argparse -import time +import src.utils.rainfall as rp import train.pipeline as pipeline - -from train.ordinal_classifier import OrdinalClassifier +from config.globals import MODELS_DIR from train.binary_classifier import BinaryClassifier +from train.ordinal_classifier import OrdinalClassifier from train.regression_net import Regressor -from train.training_utils import DeviceDataLoader, to_device, gen_learning_curve, seed_everything -from train.conv1d_neural_net import Conv1DNeuralNet -from train.lstm_neural_net import LstmNeuralNet -import rainfall as rp +from train.training_utils import ( + DeviceDataLoader, + gen_learning_curve, + seed_everything, + to_device, +) -from globals import MODELS_DIR - -import logging def compute_weights_for_binary_classification(y): - ''' - TODO: really compute the weights! - ''' + """ + TODO: really compute the weights! + """ print(y.shape) weights = np.zeros_like(y) @@ -72,24 +73,35 @@ def __init__(self, pos_weight=None, neg_weight=None): self.neg_weight = neg_weight def forward(self, inputs, targets): - inputs = torch.clamp(inputs, min=1e-7, max=1-1e-7) + inputs = torch.clamp(inputs, min=1e-7, max=1 - 1e-7) # Apply class weights to positive and negative examples if self.pos_weight is not None and self.neg_weight is not None: - loss = self.neg_weight * \ - (1 - targets) * torch.log(1 - inputs) + \ - self.pos_weight * targets * torch.log(inputs) + loss = self.neg_weight * (1 - targets) * torch.log( + 1 - inputs + ) + self.pos_weight * targets * torch.log(inputs) elif self.pos_weight is not None: loss = self.pos_weight * targets * torch.log(inputs) elif self.neg_weight is not None: loss = self.neg_weight * (1 - targets) * torch.log(1 - inputs) else: - loss = F.binary_cross_entropy(inputs, targets, reduction='mean') + loss = F.binary_cross_entropy(inputs, targets, reduction="mean") return -torch.mean(loss) -def train(forecaster, X_train, y_train, X_val, y_val, forecasting_task_sufix, pipeline_id, learner, config, resume_training: bool = False): +def train( + forecaster, + X_train, + y_train, + X_val, + y_val, + forecasting_task_sufix, + pipeline_id, + learner, + config, + resume_training: bool = False, +): NUM_FEATURES = X_train.shape[2] print(f"Number of features: {NUM_FEATURES}") @@ -105,7 +117,7 @@ def train(forecaster, X_train, y_train, X_val, y_val, forecasting_task_sufix, pi loss = nn.MSELoss() y_train = rp.value_to_ordinal_encoding(y_train) y_val = rp.value_to_ordinal_encoding(y_val) - target_average = torch.mean(torch.tensor(y_train, dtype=torch.float32), dim=0, keepdim=True) + torch.mean(torch.tensor(y_train, dtype=torch.float32), dim=0, keepdim=True) elif forecasting_task_sufix == "bc": print("- Forecasting task: binary classification.") train_weights = compute_weights_for_binary_classification(y_train) @@ -133,15 +145,18 @@ def train(forecaster, X_train, y_train, X_val, y_val, forecasting_task_sufix, pi WEIGHT_DECAY = config["training"][forecasting_task_sufix]["WEIGHT_DECAY"] optimizer = torch.optim.Adam( - forecaster.learner.parameters(), lr=LEARNING_RATE, weight_decay=WEIGHT_DECAY) + forecaster.learner.parameters(), lr=LEARNING_RATE, weight_decay=WEIGHT_DECAY + ) print(f" - Setting up optimizer: {optimizer}") # optimizer = torch.optim.SGD(model.parameters(), lr=1e-5, momentum=0.9) - print(f" - Creating data loaders.") + print(" - Creating data loaders.") train_loader = learner.create_dataloader( - X_train, y_train, batch_size=BATCH_SIZE, weights=train_weights) + X_train, y_train, batch_size=BATCH_SIZE, weights=train_weights + ) val_loader = learner.create_dataloader( - X_val, y_val, batch_size=BATCH_SIZE, weights=val_weights) + X_val, y_val, batch_size=BATCH_SIZE, weights=val_weights + ) device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") print(f" - Moving data and parameters to {device}.") @@ -154,14 +169,16 @@ def train(forecaster, X_train, y_train, X_val, y_val, forecasting_task_sufix, pi # model_path = globals.MODELS_DIR + "best_" + pipeline_id + ".pt" # Path to the pretrained model file # model.load_state_dict(torch.load(model_path)) - print(f" - Fitting model...", end=" ") - train_loss, val_loss = forecaster.learner.fit(n_epochs=N_EPOCHS, - optimizer=optimizer, - train_loader=train_loader, - val_loader=val_loader, - patience=PATIENCE, - criterion=loss, - pipeline_id=pipeline_id) + print(" - Fitting model...", end=" ") + train_loss, val_loss = forecaster.learner.fit( + n_epochs=N_EPOCHS, + optimizer=optimizer, + train_loader=train_loader, + val_loader=val_loader, + patience=PATIENCE, + criterion=loss, + pipeline_id=pipeline_id, + ) print("Done!") gen_learning_curve(train_loss, val_loss, pipeline_id) @@ -169,17 +186,29 @@ def train(forecaster, X_train, y_train, X_val, y_val, forecasting_task_sufix, pi # # Load the best model obtainined throughout the training epochs. # - forecaster.learner.load_state_dict(torch.load(MODELS_DIR + '/best_' + pipeline_id + '.pt')) + forecaster.learner.load_state_dict( + torch.load(MODELS_DIR + "/best_" + pipeline_id + ".pt") + ) def main(argv): parser = argparse.ArgumentParser(description="Train a rainfall forecasting model.") - parser.add_argument("-t", "--task", choices=["ORDINAL_CLASSIFICATION", "BINARY_CLASSIFICATION"], - default="REGRESSION", help="Prediction task") - parser.add_argument("-l", "--learner", choices=["Conv1DNeuralNet", "LstmNeuralNet"], - default="LstmNeuralNet", help="Learning algorithm to be used.") + parser.add_argument( + "-t", + "--task", + choices=["ORDINAL_CLASSIFICATION", "BINARY_CLASSIFICATION"], + default="REGRESSION", + help="Prediction task", + ) + parser.add_argument( + "-l", + "--learner", + choices=["Conv1DNeuralNet", "LstmNeuralNet"], + default="LstmNeuralNet", + help="Learning algorithm to be used.", + ) parser.add_argument("-p", "--pipeline_id", required=True, help="Pipeline ID") - + args = parser.parse_args(argv[1:]) forecasting_task_id = None @@ -194,9 +223,10 @@ def main(argv): seed_everything() X_train, y_train, X_val, y_val, X_test, y_test = pipeline.load_datasets( - args.pipeline_id) + args.pipeline_id + ) - with open('./config/config.yaml', 'r') as file: + with open("./config/config.yaml", "r") as file: config = yaml.safe_load(file) SEQ_LENGTH = config["preproc"]["SLIDING_WINDOW_SIZE"] @@ -228,11 +258,13 @@ def main(argv): print(f"Number of features: {NUM_FEATURES}") # Instantiate the class - learner = class_obj(seq_length = SEQ_LENGTH, - input_size = NUM_FEATURES, - output_size = OUTPUT_SIZE, - dropout_rate = DROPOUT_RATE) - print(f'Learner: {learner}') + learner = class_obj( + seq_length=SEQ_LENGTH, + input_size=NUM_FEATURES, + output_size=OUTPUT_SIZE, + dropout_rate=DROPOUT_RATE, + ) + print(f"Learner: {learner}") if prediction_task_sufix == "oc": forecaster = OrdinalClassifier(learner) @@ -243,12 +275,25 @@ def main(argv): # Build model start_time = time.time() - train(forecaster, X_train, y_train, X_val, y_val, prediction_task_sufix, args.pipeline_id, learner, config) + train( + forecaster, + X_train, + y_train, + X_val, + y_val, + prediction_task_sufix, + args.pipeline_id, + learner, + config, + ) logging.info("Model training took %s seconds." % (time.time() - start_time)) # Evaluate using the best model produced test_loader = learner.create_dataloader(X_test, y_test, batch_size=BATCH_SIZE) - forecaster.print_evaluation_report(args.pipeline_id, test_loader, forecasting_task_id) + forecaster.print_evaluation_report( + args.pipeline_id, test_loader, forecasting_task_id + ) + if __name__ == "__main__": start_time = time.time() diff --git a/src/train/base_classifier.py b/src/train/base_classifier.py index 3bfc5552..eb27285d 100644 --- a/src/train/base_classifier.py +++ b/src/train/base_classifier.py @@ -1,11 +1,11 @@ -from train.base_forecaster import BaseForecaster import yaml -from train.evaluate import export_confusion_matrix_to_latex from sklearn.metrics import classification_report -import globals as globals -class BaseClassifier(BaseForecaster): +from train.base_forecaster import BaseForecaster +from train.evaluate import export_confusion_matrix_to_latex + +class BaseClassifier(BaseForecaster): def print_evaluation_report(self, pipeline_id, test_loader, forecasting_task): print("\\begin{verbatim}") print(f"***Evaluation report for pipeline {pipeline_id}***") @@ -13,9 +13,9 @@ def print_evaluation_report(self, pipeline_id, test_loader, forecasting_task): print("\\begin{verbatim}") print("***Hyperparameters***") - with open('./config/config.yaml', 'r') as file: + with open("./config/config.yaml", "r") as file: config = yaml.safe_load(file) - model_config = config['training']['oc'] + model_config = config["training"]["oc"] pretty_model_config = yaml.dump(model_config, indent=4) print(pretty_model_config) print("\\end{verbatim}") @@ -26,13 +26,13 @@ def print_evaluation_report(self, pipeline_id, test_loader, forecasting_task): print("\\end{verbatim}") print("\\begin{verbatim}") - print('***Confusion matrix***') + print("***Confusion matrix***") print("\\end{verbatim}") y_true, y_pred = self.evaluate(test_loader) - assert(y_true.shape == y_pred.shape) + assert y_true.shape == y_pred.shape export_confusion_matrix_to_latex(y_true, y_pred, forecasting_task) print("\\begin{verbatim}") - print('***Classification report***') + print("***Classification report***") print(classification_report(y_true, y_pred)) print("\\end{verbatim}") diff --git a/src/train/base_forecaster.py b/src/train/base_forecaster.py index 72359f65..ced61710 100644 --- a/src/train/base_forecaster.py +++ b/src/train/base_forecaster.py @@ -2,4 +2,4 @@ class BaseForecaster(ABC): - pass \ No newline at end of file + pass diff --git a/src/train/base_learner.py b/src/train/base_learner.py index f7609abe..32c14239 100644 --- a/src/train/base_learner.py +++ b/src/train/base_learner.py @@ -1,4 +1,5 @@ from abc import ABC + class BaseLearner(ABC): - pass \ No newline at end of file + pass diff --git a/src/train/base_neural_net.py b/src/train/base_neural_net.py index 6511979a..39d6c842 100644 --- a/src/train/base_neural_net.py +++ b/src/train/base_neural_net.py @@ -1,10 +1,21 @@ -from train.base_learner import BaseLearner +import numpy as np import torch.nn as nn + +from train.base_learner import BaseLearner from train.early_stopping import EarlyStopping -import numpy as np + class BaseNeuralNet(nn.Module, BaseLearner): - def fit(self, n_epochs, optimizer, train_loader, val_loader, patience, criterion, pipeline_id): + def fit( + self, + n_epochs, + optimizer, + train_loader, + val_loader, + patience, + criterion, + pipeline_id, + ): # to track the training loss as the model trains train_losses = [] # to track the validation loss as the model trains @@ -18,7 +29,6 @@ def fit(self, n_epochs, optimizer, train_loader, val_loader, patience, criterion early_stopping = EarlyStopping(patience=patience, verbose=True) for epoch in range(n_epochs): - ################### # train the model # ################### @@ -33,8 +43,9 @@ def fit(self, n_epochs, optimizer, train_loader, val_loader, patience, criterion # calculate the loss loss = criterion(output, target.float()) - assert not (np.isnan(loss.item()) or loss.item() > - 1e6), f"Loss explosion: {loss.item()}" + assert not ( + np.isnan(loss.item()) or loss.item() > 1e6 + ), f"Loss explosion: {loss.item()}" # see https://discuss.pytorch.org/t/per-class-and-per-sample-weighting/25530 loss = loss * sample_weights @@ -70,9 +81,11 @@ def fit(self, n_epochs, optimizer, train_loader, val_loader, patience, criterion epoch_len = len(str(n_epochs)) - print_msg = (f'[{(epoch+1):>{epoch_len}}/{n_epochs:>{epoch_len}}] ' + - f'train_loss: {train_loss:.5f} ' + - f'valid_loss: {valid_loss:.5f}') + print_msg = ( + f"[{(epoch + 1):>{epoch_len}}/{n_epochs:>{epoch_len}}] " + + f"train_loss: {train_loss:.5f} " + + f"valid_loss: {valid_loss:.5f}" + ) print(print_msg) @@ -95,25 +108,28 @@ def forward(self, x): return out # def training_step(self, batch): - # images, labels = batch + # images, labels = batch # out = self(images) # Generate predictions # loss = F.cross_entropy(out, labels) # Calculate loss # return loss - + # def validation_step(self, batch): - # images, labels = batch + # images, labels = batch # out = self(images) # Generate predictions # loss = F.cross_entropy(out, labels) # Calculate loss # acc = accuracy(out, labels) # Calculate accuracy # return {'val_loss': loss.detach(), 'val_acc': acc} - + # def validation_epoch_end(self, outputs): # batch_losses = [x['val_loss'] for x in outputs] # epoch_loss = torch.stack(batch_losses).mean() # Combine losses # batch_accs = [x['val_acc'] for x in outputs] # epoch_acc = torch.stack(batch_accs).mean() # Combine accuracies # return {'val_loss': epoch_loss.item(), 'val_acc': epoch_acc.item()} - + def epoch_end(self, epoch, result): - print("Epoch [{}], train_loss: {:.4f}, val_loss: {:.4f}, val_acc: {:.4f}".format( - epoch, result['train_loss'], result['val_loss'], result['val_acc'])) \ No newline at end of file + print( + "Epoch [{}], train_loss: {:.4f}, val_loss: {:.4f}, val_acc: {:.4f}".format( + epoch, result["train_loss"], result["val_loss"], result["val_acc"] + ) + ) diff --git a/src/train/binary_classifier.py b/src/train/binary_classifier.py index 7c7fa23c..4b2d47cb 100644 --- a/src/train/binary_classifier.py +++ b/src/train/binary_classifier.py @@ -1,8 +1,10 @@ -import torch import numpy as np -import rainfall as rp -from train.training_utils import DeviceDataLoader +import torch + from train.base_classifier import BaseClassifier +from train.training_utils import DeviceDataLoader +from utils import rainfall as rp + class BinaryClassifier(BaseClassifier): def __init__(self, learner): @@ -10,7 +12,7 @@ def __init__(self, learner): self.learner = learner def evaluate(self, test_loader): - print('Evaluating binary classifier...') + print("Evaluating binary classifier...") self.learner.eval() device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") @@ -22,10 +24,10 @@ def evaluate(self, test_loader): yb_pred = self.learner(xb_test.float()) yb_pred = yb_pred.detach().cpu().numpy() - yb_pred = yb_pred.reshape(-1,1) + yb_pred = yb_pred.reshape(-1, 1) yb_test = yb_test.detach().cpu().numpy() - yb_test = yb_test.reshape(-1,1) + yb_test = yb_test.reshape(-1, 1) if y_pred is None: y_pred = yb_pred @@ -41,4 +43,4 @@ def evaluate(self, test_loader): assert np.all(np.logical_or(y_true == 0, y_true == 1)) y_true = y_true.ravel() - return y_true, y_pred \ No newline at end of file + return y_true, y_pred diff --git a/src/train/conv1d_neural_net.py b/src/train/conv1d_neural_net.py index d53f02ac..f81ca98c 100644 --- a/src/train/conv1d_neural_net.py +++ b/src/train/conv1d_neural_net.py @@ -1,9 +1,12 @@ +import functools +import operator + import torch import torch.nn as nn from torch.utils.data import TensorDataset + from train.base_neural_net import BaseNeuralNet -import functools -import operator + class Conv1DNeuralNet(BaseNeuralNet): def __init__(self, seq_length, input_size, output_size, dropout_rate=0.5): @@ -14,16 +17,20 @@ def __init__(self, seq_length, input_size, output_size, dropout_rate=0.5): self.dropout_rate = dropout_rate self.feature_extractor = self._get_feature_extractor() self.classifier = self._get_classifier() - + def _get_feature_extractor(self): fe = nn.Sequential( - nn.Conv1d(in_channels=self.input_size, out_channels=16, kernel_size=3, padding=3), + nn.Conv1d( + in_channels=self.input_size, out_channels=16, kernel_size=3, padding=3 + ), nn.ReLU(inplace=True), - nn.Dropout1d(p=self.dropout_rate) + nn.Dropout1d(p=self.dropout_rate), ) # https://datascience.stackexchange.com/questions/40906/determining-size-of-fc-layer-after-conv-layer-in-pytorch input_dim = (self.input_size, self.seq_length) - self.num_features_before_fcnn = functools.reduce(operator.mul, list(fe(torch.rand(1, *input_dim)).shape)) + self.num_features_before_fcnn = functools.reduce( + operator.mul, list(fe(torch.rand(1, *input_dim)).shape) + ) print(f"num_features_before_fcnn = {self.num_features_before_fcnn}") return fe @@ -32,21 +39,21 @@ def _get_classifier(self): nn.Linear(in_features=self.num_features_before_fcnn, out_features=50), nn.ReLU(inplace=True), nn.Linear(50, self.output_size), - nn.Sigmoid() + nn.Sigmoid(), ) - def create_dataloader(self, X, y, batch_size, weights = None): - ''' + def create_dataloader(self, X, y, batch_size, weights=None): + """ The X parameter is a numpy array having the following shape: - [batch_size, input_size, sequence_len] + [batch_size, input_size, sequence_len] - The nn.Conv1D module expects inputs having the following shape: - [batch_size, sequence_len, input_size] + The nn.Conv1D module expects inputs having the following shape: + [batch_size, sequence_len, input_size] See https://stackoverflow.com/questions/62372938/understanding-input-shape-to-pytorch-conv1d - ''' - X = torch.from_numpy(X.astype('float64')) + """ + X = torch.from_numpy(X.astype("float64")) X = torch.permute(X, (0, 2, 1)) - y = torch.from_numpy(y.astype('float64')) + y = torch.from_numpy(y.astype("float64")) if weights is None: ds = TensorDataset(X, y) diff --git a/src/train/early_stopping.py b/src/train/early_stopping.py index 96dce253..831d6a18 100644 --- a/src/train/early_stopping.py +++ b/src/train/early_stopping.py @@ -1,6 +1,8 @@ -import torch import numpy as np -import globals as globals +import torch + +from config import globals + class EarlyStopping: """Early stops the training if validation loss doesn't improve after a given patience.""" @@ -10,7 +12,7 @@ def __init__(self, patience=7, verbose=False, delta=0): Args: patience (int): How long to wait after last time validation loss improved. Default: 7 - verbose (bool): If True, prints a message for each validation loss improvement. + verbose (bool): If True, prints a message for each validation loss improvement. Default: False delta (float): Minimum change in the monitored quantity to qualify as an improvement. Default: 0 @@ -24,7 +26,6 @@ def __init__(self, patience=7, verbose=False, delta=0): self.delta = delta def __call__(self, val_loss, model, pipeline_id): - score = -val_loss if self.best_score is None: @@ -32,8 +33,7 @@ def __call__(self, val_loss, model, pipeline_id): self.save_checkpoint(val_loss, model, pipeline_id) elif score < self.best_score + self.delta: self.counter += 1 - print( - f'EarlyStopping counter: {self.counter} out of {self.patience}') + print(f"EarlyStopping counter: {self.counter} out of {self.patience}") if self.counter >= self.patience: self.early_stop = True else: @@ -42,9 +42,12 @@ def __call__(self, val_loss, model, pipeline_id): self.counter = 0 def save_checkpoint(self, val_loss, model, pipeline_id): - '''Saves model when validation loss decrease.''' + """Saves model when validation loss decrease.""" if self.verbose: print( - f'Validation loss decreased ({self.val_loss_min:.6f} --> {val_loss:.6f}). Saving model ...') - torch.save(model.state_dict(), globals.MODELS_DIR + 'best_' + pipeline_id + '.pt') + f"Validation loss decreased ({self.val_loss_min:.6f} --> {val_loss:.6f}). Saving model ..." + ) + torch.save( + model.state_dict(), globals.MODELS_DIR + "best_" + pipeline_id + ".pt" + ) self.val_loss_min = val_loss diff --git a/src/train/evaluate.py b/src/train/evaluate.py index a9ed0a97..3889a6c5 100644 --- a/src/train/evaluate.py +++ b/src/train/evaluate.py @@ -1,99 +1,143 @@ -import torch import numpy as np -from sklearn.metrics import confusion_matrix import pandas as pd import sklearn.metrics as skl -from rainfall import get_events_per_level, value_to_level -import rainfall as rp +import torch +from sklearn.metrics import confusion_matrix + +from src.utils.rainfall import get_events_per_level +from utils import rainfall as rp + def accuracy(outputs, labels): _, preds = torch.max(outputs, dim=1) return torch.tensor(torch.sum(preds == labels).item() / len(preds)) -''' + +""" https://stackoverflow.com/questions/59935155/how-to-calculate-mean-bias-errormbe-in-python -''' +""" + + def mean_bias_error(y_true, y_pred): MBE = np.mean(y_pred - y_true) return MBE + def export_confusion_matrix_to_latex(y_true, y_pred, prediction_task): if prediction_task == rp.ForecastingTask.BINARY_CLASSIFICATION: df = pd.DataFrame( confusion_matrix(y_true, y_pred, labels=[0, 1]), - index=['NORAIN', 'RAIN'], - columns=['NORAIN', 'RAIN'], + index=["NORAIN", "RAIN"], + columns=["NORAIN", "RAIN"], ) elif prediction_task == rp.ForecastingTask.ORDINAL_CLASSIFICATION: df = pd.DataFrame( confusion_matrix(y_true, y_pred, labels=[0, 1, 2, 3, 4]), - index=['None', 'Weak', 'Moderate', 'Strong', 'Extreme'], - columns=['None', 'Weak', 'Moderate', 'Strong', 'Extreme'], + index=["None", "Weak", "Moderate", "Strong", "Extreme"], + columns=["None", "Weak", "Moderate", "Strong", "Extreme"], ) - df.index.name = 'true($\\downarrow$)/pred($\\rightarrow$)' + df.index.name = "true($\\downarrow$)/pred($\\rightarrow$)" print(df.style.to_latex(hrules=True)) def export_results_to_latex(y_true, y_pred): - ''' - MAE (mean absolute error) and MBE (mean bias error) values are computed for each precipitation level. - ''' + """ + MAE (mean absolute error) and MBE (mean bias error) values are computed for each precipitation level. + """ export_confusion_matrix_to_latex(y_true, y_pred) print(y_true.shape) print(y_true) - no_rain_true, weak_rain_true, moderate_rain_true, strong_rain_true, extreme_rain_true = get_events_per_level(y_true) - no_rain_pred, weak_rain_pred, moderate_rain_pred, strong_rain_pred, extreme_rain_pred = get_events_per_level(y_pred) + ( + no_rain_true, + weak_rain_true, + moderate_rain_true, + strong_rain_true, + extreme_rain_true, + ) = get_events_per_level(y_true) + ( + no_rain_pred, + weak_rain_pred, + moderate_rain_pred, + strong_rain_pred, + extreme_rain_pred, + ) = get_events_per_level(y_pred) if no_rain_pred[0].size > 0: mse_no_rain = skl.mean_absolute_error( - y_true[no_rain_true], y_pred[no_rain_true]) - mbe_no_rain = mean_bias_error( - y_true[no_rain_true], y_pred[no_rain_true]) + y_true[no_rain_true], y_pred[no_rain_true] + ) + mbe_no_rain = mean_bias_error(y_true[no_rain_true], y_pred[no_rain_true]) else: - mse_no_rain = mbe_no_rain = 'n/a' + mse_no_rain = mbe_no_rain = "n/a" if weak_rain_pred[0].size > 0: mse_weak_rain = skl.mean_absolute_error( - y_true[weak_rain_true], y_pred[weak_rain_true]) - mbe_weak_rain = mean_bias_error( - y_true[weak_rain_true], y_pred[weak_rain_true]) + y_true[weak_rain_true], y_pred[weak_rain_true] + ) + mbe_weak_rain = mean_bias_error(y_true[weak_rain_true], y_pred[weak_rain_true]) else: - mse_weak_rain = mbe_weak_rain = 'n/a' + mse_weak_rain = mbe_weak_rain = "n/a" if moderate_rain_pred[0].size > 0: mse_moderate_rain = skl.mean_absolute_error( - y_true[moderate_rain_true], y_pred[moderate_rain_true]) + y_true[moderate_rain_true], y_pred[moderate_rain_true] + ) mbe_moderate_rain = mean_bias_error( - y_true[moderate_rain_true], y_pred[moderate_rain_true]) + y_true[moderate_rain_true], y_pred[moderate_rain_true] + ) else: - mse_moderate_rain = mbe_moderate_rain = 'n/a' + mse_moderate_rain = mbe_moderate_rain = "n/a" if strong_rain_pred[0].size > 0: mse_strong_rain = skl.mean_absolute_error( - y_true[strong_rain_true], y_pred[strong_rain_true]) + y_true[strong_rain_true], y_pred[strong_rain_true] + ) mbe_strong_rain = mean_bias_error( - y_true[strong_rain_true], y_pred[strong_rain_true]) + y_true[strong_rain_true], y_pred[strong_rain_true] + ) else: - mse_strong_rain = mbe_strong_rain = 'n/a' + mse_strong_rain = mbe_strong_rain = "n/a" if extreme_rain_pred[0].size > 0: mse_extreme_rain = skl.mean_absolute_error( - y_true[extreme_rain_true], y_pred[extreme_rain_true]) + y_true[extreme_rain_true], y_pred[extreme_rain_true] + ) mbe_extreme_rain = mean_bias_error( - y_true[extreme_rain_true], y_pred[extreme_rain_true]) + y_true[extreme_rain_true], y_pred[extreme_rain_true] + ) else: - mse_extreme_rain = mbe_extreme_rain = 'n/a' + mse_extreme_rain = mbe_extreme_rain = "n/a" df = pd.DataFrame() - df['level'] = ['No rain', 'Weak', 'Moderate', 'Strong', 'Extreme'] - df['qty_true'] = [no_rain_true[0].shape[0], weak_rain_true[0].shape[0], - moderate_rain_true[0].shape[0], strong_rain_true[0].shape[0], extreme_rain_true[0].shape[0]] - df['qty_pred'] = [no_rain_pred[0].shape[0], weak_rain_pred[0].shape[0], - moderate_rain_pred[0].shape[0], strong_rain_pred[0].shape[0], extreme_rain_pred[0].shape[0]] - df['mae'] = [mse_no_rain, mse_weak_rain, - mse_moderate_rain, mse_strong_rain, mse_extreme_rain] - df['mbe'] = [mbe_no_rain, mbe_weak_rain, - mbe_moderate_rain, mbe_strong_rain, mbe_extreme_rain] + df["level"] = ["No rain", "Weak", "Moderate", "Strong", "Extreme"] + df["qty_true"] = [ + no_rain_true[0].shape[0], + weak_rain_true[0].shape[0], + moderate_rain_true[0].shape[0], + strong_rain_true[0].shape[0], + extreme_rain_true[0].shape[0], + ] + df["qty_pred"] = [ + no_rain_pred[0].shape[0], + weak_rain_pred[0].shape[0], + moderate_rain_pred[0].shape[0], + strong_rain_pred[0].shape[0], + extreme_rain_pred[0].shape[0], + ] + df["mae"] = [ + mse_no_rain, + mse_weak_rain, + mse_moderate_rain, + mse_strong_rain, + mse_extreme_rain, + ] + df["mbe"] = [ + mbe_no_rain, + mbe_weak_rain, + mbe_moderate_rain, + mbe_strong_rain, + mbe_extreme_rain, + ] print(df.style.to_latex(hrules=True)) diff --git a/src/train/lstm_neural_net.py b/src/train/lstm_neural_net.py index 06f424f0..b7abcb76 100644 --- a/src/train/lstm_neural_net.py +++ b/src/train/lstm_neural_net.py @@ -1,15 +1,18 @@ import torch import torch.nn as nn from torch.utils.data import TensorDataset + from train.base_neural_net import BaseNeuralNet + # Needed because nn.LSTM() returns tuple of (tensor, (recurrent state)) # See https://discuss.pytorch.org/t/lstm-network-inside-a-sequential-container/19304/4 class extract_tensor(nn.Module): - def forward(self,x): + def forward(self, x): out, _ = x return out + class LstmNeuralNet(BaseNeuralNet): def __init__(self, seq_length, input_size, output_size, dropout_rate=0.5): super(BaseNeuralNet, self).__init__() @@ -23,7 +26,12 @@ def __init__(self, seq_length, input_size, output_size, dropout_rate=0.5): def _get_feature_extractor(self): hidden_size = 32 fe = nn.Sequential( - nn.LSTM(input_size = self.input_size, hidden_size = hidden_size, num_layers = 2, batch_first = True), + nn.LSTM( + input_size=self.input_size, + hidden_size=hidden_size, + num_layers=2, + batch_first=True, + ), extract_tensor(), nn.ReLU(), nn.Dropout(p=self.dropout_rate), @@ -36,16 +44,16 @@ def _get_classifier(self): nn.Linear(in_features=self.num_features_before_fcnn, out_features=50), nn.ReLU(), nn.Linear(in_features=50, out_features=self.output_size), - nn.Sigmoid() - ) + nn.Sigmoid(), + ) - def create_dataloader(self, X, y, batch_size, weights = None): - ''' + def create_dataloader(self, X, y, batch_size, weights=None): + """ The X parameter is a numpy array having the following shape: - [batch_size, sequence_len, input_size] + [batch_size, sequence_len, input_size] - The nn.LSTM module (with 'batch_first = True') expects inputs having the following shape: - [batch_size, sequence_len, input_size] + The nn.LSTM module (with 'batch_first = True') expects inputs having the following shape: + [batch_size, sequence_len, input_size] where: - sequence_length = number of timestamps @@ -53,16 +61,16 @@ def create_dataloader(self, X, y, batch_size, weights = None): - input_size = the length of the vector describing each feature observed at each timestamp. See https://discuss.pytorch.org/t/using-lstm-after-conv1d-for-time-series-data/111140 - ''' - X = torch.from_numpy(X.astype('float64')) - y = torch.from_numpy(y.astype('float64')) + """ + X = torch.from_numpy(X.astype("float64")) + y = torch.from_numpy(y.astype("float64")) if weights is None: ds = TensorDataset(X, y) else: print(X.shape) print(y.shape) - print(weights.shape) + print(weights.shape) ds = TensorDataset(X, y, weights) loader = torch.utils.data.DataLoader(ds, batch_size=batch_size, shuffle=True) diff --git a/src/train/ordinal_classifier.py b/src/train/ordinal_classifier.py index 412bc885..6f04beed 100644 --- a/src/train/ordinal_classifier.py +++ b/src/train/ordinal_classifier.py @@ -1,98 +1,42 @@ """ - https://stats.stackexchange.com/questions/209290/deep-learning-for-ordinal-classification +https://stats.stackexchange.com/questions/209290/deep-learning-for-ordinal-classification - https://towardsdatascience.com/simple-trick-to-train-an-ordinal-regression-with-any-classifier-6911183d2a3c +https://towardsdatascience.com/simple-trick-to-train-an-ordinal-regression-with-any-classifier-6911183d2a3c - https://towardsdatascience.com/how-to-perform-ordinal-regression-classification-in-pytorch-361a2a095a99 +https://towardsdatascience.com/how-to-perform-ordinal-regression-classification-in-pytorch-361a2a095a99 - https://arxiv.org/pdf/0704.1028.pdf +https://arxiv.org/pdf/0704.1028.pdf - https://datascience.stackexchange.com/questions/44354/ordinal-classification-with-xgboost +https://datascience.stackexchange.com/questions/44354/ordinal-classification-with-xgboost - https://towardsdatascience.com/building-rnn-lstm-and-gru-for-time-series-using-pytorch-a46e5b094e7b +https://towardsdatascience.com/building-rnn-lstm-and-gru-for-time-series-using-pytorch-a46e5b094e7b - https://neptune.ai/blog/how-to-deal-with-imbalanced-classification-and-regression-data +https://neptune.ai/blog/how-to-deal-with-imbalanced-classification-and-regression-data - https://colab.research.google.com/github/YyzHarry/imbalanced-regression/blob/master/tutorial/tutorial.ipynb#scrollTo=tSrzhog1gxyY +https://colab.research.google.com/github/YyzHarry/imbalanced-regression/blob/master/tutorial/tutorial.ipynb#scrollTo=tSrzhog1gxyY """ -from train.base_classifier import BaseClassifier +import numpy as np import torch -import torch.nn as nn -from torch.utils.data import TensorDataset -import torch.nn.functional as F -from train.training_utils import * -from train.evaluate import * -from rainfall import ordinal_encoding_to_level -from train.early_stopping import * -import rainfall as rp -import globals as globals + +from src.utils.rainfall import ordinal_encoding_to_level, value_to_level +from train.base_classifier import BaseClassifier + +# from train.early_stopping import * +# from train.evaluate import * +from train.training_utils import DeviceDataLoader + class OrdinalClassifier(BaseClassifier): def __init__(self, learner): super(OrdinalClassifier, self).__init__() self.learner = learner - # self.feature_extractor = nn.Sequential( - # nn.Conv1d(in_channels=in_channels, out_channels=16, kernel_size=3, padding=3), - # nn.ReLU(inplace=True), - # nn.Dropout1d(p=dropout_rate)) - - # # https://datascience.stackexchange.com/questions/40906/determining-size-of-fc-layer-after-conv-layer-in-pytorch - # num_features_before_fcnn = functools.reduce(operator.mul, list(self.feature_extractor(torch.rand(1, *input_dim)).shape)) - - # self.classifier = nn.Sequential( - # nn.Linear(in_features=num_features_before_fcnn, out_features=50), - # nn.ReLU(inplace=True), - # nn.Linear(50, num_classes), - # nn.Sigmoid() - # ) - - # # Initialize the bias of the last layer with the average target value - # # see https://discuss.pytorch.org/t/how-to-initialize-weight-with-arbitrary-tensor/3432 - # if target_average is not None: - # # Get the last layer - # last_layer = self.classifier[-2] - # print(f"last_layer.bias = {last_layer.bias}") - # print(f"target_average = {target_average[0]}") - # last_layer.bias = torch.nn.Parameter(target_average[0]) - # print(f"last_layer.bias = {last_layer.bias}") - - # def forward(self, x): - # out = self.feature_extractor(x) - # out = out.view(out.shape[0], -1) - # out = self.classifier(out) - # return out - - # def training_step(self, batch): - # X_train, y_train = batch - # out = self(X_train) # Generate predictions - # loss = F.cross_entropy(out, y_train) # Calculate loss - # return loss - - # def validation_step(self, batch): - # X_train, y_train = batch - # out = self(X_train) # Generate predictions - # loss = F.cross_entropy(out, y_train) # Calculate loss - # acc = accuracy(out, y_train) # Calculate accuracy - # return {'val_loss': loss, 'val_acc': acc} - - # def validation_epoch_end(self, outputs): - # batch_losses = [x['val_loss'] for x in outputs] - # epoch_loss = torch.stack(batch_losses).mean() # Combine losses - # batch_accs = [x['val_acc'] for x in outputs] - # epoch_acc = torch.stack(batch_accs).mean() # Combine accuracies - # return {'val_loss': epoch_loss.item(), 'val_acc': epoch_acc.item()} - - # def epoch_end(self, epoch, result): - # print("Epoch [{}], val_loss: {:.4f}, val_acc: {:.4f}".format( - # epoch, result['val_loss'], result['val_acc'])) - def predict(self, X): - print('Making predictions with ordinal classification model...') + print("Making predictions with ordinal classification model...") self.eval() - X_as_tensor = torch.from_numpy(X.astype('float64')) + X_as_tensor = torch.from_numpy(X.astype("float64")) X_as_tensor = torch.permute(X_as_tensor, (0, 2, 1)) outputs = [] @@ -107,7 +51,7 @@ def predict(self, X): return y_pred def evaluate(self, test_loader): - print('Evaluating ordinal classifier...') + print("Evaluating ordinal classifier...") self.learner.eval() device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") @@ -120,10 +64,10 @@ def evaluate(self, test_loader): yb_pred = yb_pred.detach().cpu().numpy() yb_pred = ordinal_encoding_to_level(yb_pred) - yb_pred = yb_pred.reshape(-1,1) + yb_pred = yb_pred.reshape(-1, 1) yb_test = yb_test.detach().cpu().numpy() - yb_test = yb_test.reshape(-1,1) + yb_test = yb_test.reshape(-1, 1) if y_pred is None: y_pred = yb_pred @@ -132,8 +76,8 @@ def evaluate(self, test_loader): y_pred = np.vstack([y_pred, yb_pred]) y_true = np.vstack([y_true, yb_test]) - y_true = rp.value_to_level(y_true) - print(f'Shapes: {y_true.shape}, {y_pred.shape}') + y_true = value_to_level(y_true) + print(f"Shapes: {y_true.shape}, {y_pred.shape}") return y_true, y_pred diff --git a/src/train/pipeline.py b/src/train/pipeline.py index 82bee6bc..68b9a430 100644 --- a/src/train/pipeline.py +++ b/src/train/pipeline.py @@ -1,19 +1,31 @@ -import pickle import logging -import globals as globals +import pickle + +from config import globals + def load_datasets(pipeline_id: str): - ''' + """ Load numpy arrays (stored in a pickle file) from disk - ''' + """ filename = globals.DATASETS_DIR + pipeline_id + ".pickle" logging.info(f"Loading train/val/test datasets from {filename}.") - file = open(filename, 'rb') + file = open(filename, "rb") (X_train, y_train, X_val, y_val, X_test, y_test) = pickle.load(file) - logging.info(f"Shapes of train/val/test data matrices: {X_train.shape}/{X_val.shape}/{X_test.shape}") - logging.info(f"Min values of train/val/test data matrices: {min(X_train.reshape(-1,1))}/{min(X_val.reshape(-1,1))}/{min(X_test.reshape(-1,1))}") - logging.info(f"Max values of train/val/test data matrices: {max(X_train.reshape(-1,1))}/{max(X_val.reshape(-1,1))}/{max(X_test.reshape(-1,1))}") - logging.info(f"Min values of train/val/test target: {min(y_train)}/{min(y_val)}/{min(y_test)}") - logging.info(f"Max values of train/val/test target: {max(y_train)}/{max(y_val)}/{max(y_test)}") + logging.info( + f"Shapes of train/val/test data matrices: {X_train.shape}/{X_val.shape}/{X_test.shape}" + ) + logging.info( + f"Min values of train/val/test data matrices: {min(X_train.reshape(-1, 1))}/{min(X_val.reshape(-1, 1))}/{min(X_test.reshape(-1, 1))}" + ) + logging.info( + f"Max values of train/val/test data matrices: {max(X_train.reshape(-1, 1))}/{max(X_val.reshape(-1, 1))}/{max(X_test.reshape(-1, 1))}" + ) + logging.info( + f"Min values of train/val/test target: {min(y_train)}/{min(y_val)}/{min(y_test)}" + ) + logging.info( + f"Max values of train/val/test target: {max(y_train)}/{max(y_val)}/{max(y_test)}" + ) return X_train, y_train, X_val, y_val, X_test, y_test diff --git a/src/train/regression_net.py b/src/train/regression_net.py index 15d68215..cceb9eae 100644 --- a/src/train/regression_net.py +++ b/src/train/regression_net.py @@ -1,28 +1,35 @@ +import sklearn.metrics as skl import torch import torch.nn as nn -from torch.utils.data import TensorDataset import torch.nn.functional as F -from train.training_utils import * -from train.evaluate import * +from torch.utils.data import TensorDataset + +from train.evaluate import accuracy, export_results_to_latex, mean_bias_error +from train.training_utils import DeviceDataLoader, get_default_device + class Regressor(nn.Module): def __init__(self, in_channels, y_mean_value): super(Regressor, self).__init__() self.conv1d_1 = nn.Conv1d( - in_channels=in_channels, out_channels=32, kernel_size=3, padding=2) + in_channels=in_channels, out_channels=32, kernel_size=3, padding=2 + ) self.gn_1 = nn.GroupNorm(1, 32) self.conv1d_2 = nn.Conv1d( - in_channels=32, out_channels=64, kernel_size=3, padding=2) + in_channels=32, out_channels=64, kernel_size=3, padding=2 + ) self.gn_2 = nn.GroupNorm(1, 64) self.conv1d_3 = nn.Conv1d( - in_channels=64, out_channels=64, kernel_size=3, padding=2) + in_channels=64, out_channels=64, kernel_size=3, padding=2 + ) self.gn_3 = nn.GroupNorm(1, 64) self.conv1d_4 = nn.Conv1d( - in_channels=64, out_channels=128, kernel_size=3, padding=2) + in_channels=64, out_channels=128, kernel_size=3, padding=2 + ) self.gn_4 = nn.GroupNorm(1, 128) # self.conv1d_5 = nn.Conv1d(in_channels = 64, out_channels = 64, kernel_size = 3, padding=2) @@ -102,31 +109,29 @@ def forward(self, x): def validation_step(self, batch): X_train, y_train = batch - out = self(X_train) # Generate predictions - loss = F.cross_entropy(out, y_train) # Calculate loss - acc = accuracy(out, y_train) # Calculate accuracy - return {'val_loss': loss, 'val_acc': acc} + out = self(X_train) # Generate predictions + loss = F.cross_entropy(out, y_train) # Calculate loss + acc = accuracy(out, y_train) # Calculate accuracy + return {"val_loss": loss, "val_acc": acc} def validation_epoch_end(self, outputs): - batch_losses = [x['val_loss'] for x in outputs] - epoch_loss = torch.stack(batch_losses).mean() # Combine losses - batch_accs = [x['val_acc'] for x in outputs] - epoch_acc = torch.stack(batch_accs).mean() # Combine accuracies - return {'val_loss': epoch_loss.item(), 'val_acc': epoch_acc.item()} + batch_losses = [x["val_loss"] for x in outputs] + epoch_loss = torch.stack(batch_losses).mean() # Combine losses + batch_accs = [x["val_acc"] for x in outputs] + epoch_acc = torch.stack(batch_accs).mean() # Combine accuracies + return {"val_loss": epoch_loss.item(), "val_acc": epoch_acc.item()} def evaluate(self, X_test, y_test): self.eval() - test_x_tensor = torch.from_numpy(X_test.astype('float64')) + test_x_tensor = torch.from_numpy(X_test.astype("float64")) test_x_tensor = torch.permute(test_x_tensor, (0, 2, 1)) - test_y_tensor = torch.from_numpy(y_test.astype('float64')) + test_y_tensor = torch.from_numpy(y_test.astype("float64")) test_ds = TensorDataset(test_x_tensor, test_y_tensor) - test_loader = torch.utils.data.DataLoader( - test_ds, batch_size=32, shuffle=False) + test_loader = torch.utils.data.DataLoader(test_ds, batch_size=32, shuffle=False) test_loader = DeviceDataLoader(test_loader, get_default_device()) - test_losses = [] outputs = [] with torch.no_grad(): for xb, yb in test_loader: @@ -136,10 +141,10 @@ def evaluate(self, X_test, y_test): y_pred = torch.vstack(outputs).squeeze(1) y_pred = y_pred.cpu().numpy().reshape(-1, 1) test_error = skl.mean_squared_error(y_test, y_pred) - print('MSE on the entire test set: %f' % test_error) + print("MSE on the entire test set: %f" % test_error) test_error2 = skl.mean_absolute_error(y_test, y_pred) - print('MAE on the entire test set: %f' % test_error2) + print("MAE on the entire test set: %f" % test_error2) test_error3 = mean_bias_error(y_test, y_pred) - print('MBE on the entire test set: %f' % test_error3) + print("MBE on the entire test set: %f" % test_error3) export_results_to_latex(y_test, y_pred) diff --git a/src/train/training_utils.py b/src/train/training_utils.py index c2d704b1..af3eae0c 100644 --- a/src/train/training_utils.py +++ b/src/train/training_utils.py @@ -1,15 +1,18 @@ -import torch -import torch.nn as nn -from torch.utils.data import TensorDataset -import numpy as np import os import random + import matplotlib.pyplot as plt -import globals as globals +import numpy as np +import torch +import torch.nn as nn +from torch.utils.data import TensorDataset + +from config import globals + def initialize_weights(m): if isinstance(m, nn.Conv1d): - nn.init.kaiming_uniform_(m.weight.data, nonlinearity='relu') + nn.init.kaiming_uniform_(m.weight.data, nonlinearity="relu") if m.bias is not None: nn.init.constant_(m.bias.data, 0) elif isinstance(m, nn.BatchNorm2d): @@ -19,9 +22,10 @@ def initialize_weights(m): nn.init.kaiming_uniform_(m.weight.data) nn.init.constant_(m.bias.data, 0) + def seed_everything(seed=1234): random.seed(seed) - os.environ['PYTHONHASHSEED'] = str(seed) + os.environ["PYTHONHASHSEED"] = str(seed) np.random.seed(seed) torch.manual_seed(seed) torch.cuda.manual_seed(seed) @@ -31,9 +35,9 @@ def seed_everything(seed=1234): def get_default_device(): """Pick GPU if available, else CPU""" if torch.cuda.is_available(): - return torch.device('cuda') + return torch.device("cuda") else: - return torch.device('cpu') + return torch.device("cpu") def to_device(data, device): @@ -43,7 +47,7 @@ def to_device(data, device): return data.to(device, non_blocking=True) -class DeviceDataLoader(): +class DeviceDataLoader: """Wrap a dataloader to move data to a device""" def __init__(self, dl, device): @@ -60,14 +64,16 @@ def __len__(self): return len(self.dl) -def DEPRECATED_create_train_and_val_loaders(X_train, y_train, X_val, y_val, batch_size, train_weights, val_weights): - X_train = torch.from_numpy(X_train.astype('float64')) +def DEPRECATED_create_train_and_val_loaders( + X_train, y_train, X_val, y_val, batch_size, train_weights, val_weights +): + X_train = torch.from_numpy(X_train.astype("float64")) X_train = torch.permute(X_train, (0, 2, 1)) - y_train = torch.from_numpy(y_train.astype('float64')) + y_train = torch.from_numpy(y_train.astype("float64")) - X_val = torch.from_numpy(X_val.astype('float64')) + X_val = torch.from_numpy(X_val.astype("float64")) X_val = torch.permute(X_val, (0, 2, 1)) - y_val = torch.from_numpy(y_val.astype('float64')) + y_val = torch.from_numpy(y_val.astype("float64")) if (train_weights is None) and (val_weights is None): train_ds = TensorDataset(X_train, y_train) @@ -77,21 +83,25 @@ def DEPRECATED_create_train_and_val_loaders(X_train, y_train, X_val, y_val, batc val_ds = TensorDataset(X_val, y_val, val_weights) train_loader = torch.utils.data.DataLoader( - train_ds, batch_size=batch_size, shuffle=True) + train_ds, batch_size=batch_size, shuffle=True + ) val_loader = torch.utils.data.DataLoader( - val_ds, batch_size=batch_size, shuffle=True) + val_ds, batch_size=batch_size, shuffle=True + ) return train_loader, val_loader + def gen_learning_curve(train_loss, val_loss, pipeline_id): fig = plt.figure(figsize=(10, 8)) - plt.plot(range(1, len(train_loss)+1), train_loss, label='Training Loss') - plt.plot(range(1, len(val_loss)+1), val_loss, label='Validation Loss') - plt.xlabel('epochs') - plt.ylabel('loss') - plt.xlim(0, len(train_loss)+1) + plt.plot(range(1, len(train_loss) + 1), train_loss, label="Training Loss") + plt.plot(range(1, len(val_loss) + 1), val_loss, label="Validation Loss") + plt.xlabel("epochs") + plt.ylabel("loss") + plt.xlim(0, len(train_loss) + 1) plt.grid(True) plt.legend() plt.tight_layout() - fig.savefig(globals.MODELS_DIR + '/loss_plot_' + pipeline_id + - '.png', bbox_inches='tight') + fig.savefig( + globals.MODELS_DIR + "/loss_plot_" + pipeline_id + ".png", bbox_inches="tight" + ) diff --git a/src/train/xgboost.py b/src/train/xgboost.py index 40f07a54..a40b984d 100644 --- a/src/train/xgboost.py +++ b/src/train/xgboost.py @@ -1,69 +1,79 @@ -from sklearn.ensemble import GradientBoostingClassifier -import numpy as np +import pickle + import matplotlib.pyplot as plt import seaborn as sns -from sklearn.metrics import confusion_matrix -import pickle -from sklearn.metrics import classification_report +from sklearn.ensemble import GradientBoostingClassifier +from sklearn.metrics import classification_report, confusion_matrix -def _train_and_test_classifier(X_train, y_train, X_test, y_test): - print(f"Shapes before reshaping: ", X_train.shape, X_test.shape) +def _train_and_test_classifier(X_train, y_train, X_test, y_test): + print("Shapes before reshaping: ", X_train.shape, X_test.shape) X_train = X_train.reshape(len(X_train), -1) X_test = X_test.reshape(len(X_test), -1) - print(f"Shapes after reshaping: ", X_train.shape, X_test.shape) + print("Shapes after reshaping: ", X_train.shape, X_test.shape) - y_train[y_train>0] = 1 - y_test[y_test>0] = 1 + y_train[y_train > 0] = 1 + y_test[y_test > 0] = 1 # Create a GradientBoostingClassifier object with default hyperparameters clf = GradientBoostingClassifier() # Train the classifier clf.fit(X_train, y_train) - + # Make predictions on the testing data y_pred = clf.predict(X_test.reshape(len(X_test), -1)) - + y_true = y_test - y_true[y_true>0] = 1 + y_true[y_true > 0] = 1 # Calculate the confusion matrix cm = confusion_matrix(y_true, y_pred) return cm, y_true, y_pred -def report_results(cm, y_true, y_pred, title = None): + +def report_results(cm, y_true, y_pred, title=None): # Define the class labels - class_names = ['Negative', 'Positive'] + class_names = ["Negative", "Positive"] # Create a heatmap using Seaborn - sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=class_names, yticklabels=class_names) + sns.heatmap( + cm, + annot=True, + fmt="d", + cmap="Blues", + xticklabels=class_names, + yticklabels=class_names, + ) # Add labels and title - plt.xlabel('Predicted label') - plt.ylabel('True label') + plt.xlabel("Predicted label") + plt.ylabel("True label") if title is not None: - plt.title('Confusion Matrix - ' + title) + plt.title("Confusion Matrix - " + title) else: - plt.title('Confusion Matrix') + plt.title("Confusion Matrix") # Show the plot plt.show() # Build the classification report - target_names = ['Negative', 'Positive'] + target_names = ["Negative", "Positive"] report = classification_report(y_true, y_pred, target_names=target_names) # Print the classification report print(report) + def train_and_test_classifier(pipeline_id): filename = f"../data/datasets/{pipeline_id}.pickle" print(f"Loading train/val/test datasets from {filename}.") - file = open(filename, 'rb') + file = open(filename, "rb") (X_train, y_train, X_val, y_val, X_test, y_test) = pickle.load(file) - print(f"Shapes of train/val/test data matrices: {X_train.shape}/{X_val.shape}/{X_test.shape}") + print( + f"Shapes of train/val/test data matrices: {X_train.shape}/{X_val.shape}/{X_test.shape}" + ) cm, y_true, y_pred = _train_and_test_classifier(X_train, y_train, X_test, y_test) - report_results(cm, y_true, y_pred, pipeline_id) \ No newline at end of file + report_results(cm, y_true, y_pred, pipeline_id) diff --git a/src/utils/__init__.py b/src/utils/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/utils/__pycache__/evaluation.cpython-310.pyc b/src/utils/__pycache__/evaluation.cpython-310.pyc deleted file mode 100644 index cf691da8..00000000 Binary files a/src/utils/__pycache__/evaluation.cpython-310.pyc and /dev/null differ diff --git a/src/utils/__pycache__/model.cpython-310.pyc b/src/utils/__pycache__/model.cpython-310.pyc deleted file mode 100644 index b3fa6158..00000000 Binary files a/src/utils/__pycache__/model.cpython-310.pyc and /dev/null differ diff --git a/src/utils/__pycache__/near_stations.cpython-310.pyc b/src/utils/__pycache__/near_stations.cpython-310.pyc deleted file mode 100644 index a41a4010..00000000 Binary files a/src/utils/__pycache__/near_stations.cpython-310.pyc and /dev/null differ diff --git a/src/utils/__pycache__/training.cpython-310.pyc b/src/utils/__pycache__/training.cpython-310.pyc deleted file mode 100644 index 21cf67c3..00000000 Binary files a/src/utils/__pycache__/training.cpython-310.pyc and /dev/null differ diff --git a/src/utils/__pycache__/windowing.cpython-310.pyc b/src/utils/__pycache__/windowing.cpython-310.pyc deleted file mode 100644 index 3ac53955..00000000 Binary files a/src/utils/__pycache__/windowing.cpython-310.pyc and /dev/null differ diff --git a/src/utils/aggregate_through_time.py b/src/utils/aggregate_through_time.py new file mode 100644 index 00000000..de76b0e9 --- /dev/null +++ b/src/utils/aggregate_through_time.py @@ -0,0 +1,58 @@ +import argparse +import logging +import sys +import time + +import pandas as pd + + +def aggregate_to_hourly_resolution(df: pd.DataFrame): + assert not df.isnull().values.any().any() + + # Resample the DataFrame to hourly frequency and compute the mean + hourly_df = df.resample("H").mean() + + hourly_df.set_index(hourly_df.index + pd.DateOffset(hours=1), inplace=True) + + hourly_df = hourly_df.dropna() + + return hourly_df + + +def main(argv): + parser = argparse.ArgumentParser( + description="Aggregate observations of a Pandas dataframe with a datetime as index to hourly temporal resolution. Results are saved as another Pandas dataframe." + ) + parser.add_argument( + "--input_file", type=str, required=True, help="Path to the input Parquet file" + ) + parser.add_argument( + "--output_file", type=str, required=True, help="Path to the output Parquet file" + ) + + args = parser.parse_args() + + input_file = args.input_file + output_file = args.output_file + + df = pd.read_parquet(input_file) + logging.info(f"The input dataframe has shape {df.shape}.") + + agg_df = aggregate_to_hourly_resolution(df) + agg_df.to_parquet(output_file) + logging.info(f"The output dataframe with shape {agg_df.shape} was created.") + + +# python src/aggregate_through_time.py --input_file ./data/goes16/DSI/DSI_CAPE.parquet --output_file ./data/goes16/DSI/DSI_CAPE_1H.parquet +if __name__ == "__main__": + fmt = "[%(levelname)s] %(funcName)s():%(lineno)i: %(message)s" + logging.basicConfig(level=logging.DEBUG, format=fmt) + + start_time = time.time() # Record the start time + + main(sys.argv) + + end_time = time.time() # Record the end time + duration = (end_time - start_time) / 60 # Calculate duration in minutes + + logging.info(f"Script duration: {duration:.2f} minutes") diff --git a/src/utils/concatenate_csv.py b/src/utils/concatenate_csv.py index ff164f5f..275c259f 100644 --- a/src/utils/concatenate_csv.py +++ b/src/utils/concatenate_csv.py @@ -1,9 +1,9 @@ -import sys -import os import csv +import os +import sys # Define usage message -usage_msg = 'Usage: python concat_csv.py ' +usage_msg = "Usage: python concat_csv.py " # Get command line arguments if len(sys.argv) != 3: @@ -20,22 +20,24 @@ # Loop through input files and append rows to list for filename in os.listdir(input_dir): - if filename.endswith('.csv'): - with open(os.path.join(input_dir, filename), newline='') as csvfile: + if filename.endswith(".csv"): + with open(os.path.join(input_dir, filename), newline="") as csvfile: reader = csv.reader(csvfile) if is_first_file: is_first_file = False else: - next(reader) # This skips the first row of the CSV file (because it is the header) + next( + reader + ) # This skips the first row of the CSV file (because it is the header) for row in reader: rows.append(row) # Write rows to output file -with open(output_file, 'w', newline='') as csvfile: +with open(output_file, "w", newline="") as csvfile: writer = csv.writer(csvfile) for row in rows: writer.writerow(row) -print(f'{len(rows)} rows written to {output_file}.') +print(f"{len(rows)} rows written to {output_file}.") # python concatenate_csv.py input_dir SBGL_1997-01-01_2022-12-31.csv diff --git a/src/utils/csv2parquet.py b/src/utils/csv2parquet.py new file mode 100644 index 00000000..fd40ce8b --- /dev/null +++ b/src/utils/csv2parquet.py @@ -0,0 +1,34 @@ +import argparse +import os + +import pandas as pd + + +def convert_csv_to_parquet(input_folder, output_folder): + """ + Converts all CSV files in the input folder to Parquet files in the output folder. + + Args: + input_folder: The folder containing the CSV files. + output_folder: The folder where the Parquet files will be saved. + """ + + for file_name in os.listdir(input_folder): + if file_name.endswith(".csv"): + csv_file_path = os.path.join(input_folder, file_name) + parquet_file_path = os.path.join( + output_folder, file_name.replace(".csv", ".parquet") + ) + df = pd.read_csv(csv_file_path) + df.to_parquet(parquet_file_path) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("input_folder", help="The folder containing the CSV files.") + parser.add_argument( + "output_folder", help="The folder where the Parquet files will be saved." + ) + args = parser.parse_args() + + convert_csv_to_parquet(args.input_folder, args.output_folder) diff --git a/src/utils/env_loader.py b/src/utils/env_loader.py new file mode 100644 index 00000000..61eeb5b8 --- /dev/null +++ b/src/utils/env_loader.py @@ -0,0 +1,69 @@ +from __future__ import annotations + +import os +from pathlib import Path +from typing import Iterable, Tuple + + +def _load_env_file(env_path: Path) -> bool: + if not env_path.exists(): + return False + + loaded = False + try: + with env_path.open("r", encoding="utf-8") as env_file: + for raw_line in env_file: + line = raw_line.strip() + if not line or line.startswith("#") or "=" not in line: + continue + key, value = line.split("=", 1) + key = key.strip() + value = value.strip().strip('"').strip("'") + if key and value and key not in os.environ: + os.environ[key] = value + loaded = True + except OSError: + return False + + return loaded + + +def load_env_files(candidates: Iterable[Path]) -> None: + for env_path in candidates: + _load_env_file(env_path) + + +def get_project_root(reference: Path) -> Path: + return reference.resolve().parent.parent.parent + + +def get_cemaden_credentials(reference_file: Path | None = None) -> Tuple[str, str]: + if reference_file is None: + reference_file = Path(__file__) + + project_root = get_project_root(reference_file) + env_candidates = [ + project_root / ".env", + project_root / "config" / ".env", + ] + + load_env_files(env_candidates) + + username = os.getenv("CEMADEN_USERNAME") + password = os.getenv("CEMADEN_PASSWORD") + + missing = [ + name + for name, value in ( + ("CEMADEN_USERNAME", username), + ("CEMADEN_PASSWORD", password), + ) + if not value + ] + if missing: + raise RuntimeError( + f"Missing environment variable(s): {', '.join(missing)}. " + "Ensure they are set or defined in a .env file." + ) + + return username, password diff --git a/src/extract_rrqpe_series.py b/src/utils/main_extract_rrqpe_series.py similarity index 70% rename from src/extract_rrqpe_series.py rename to src/utils/main_extract_rrqpe_series.py index c2ced880..c44c6bf9 100644 --- a/src/extract_rrqpe_series.py +++ b/src/utils/main_extract_rrqpe_series.py @@ -1,34 +1,30 @@ -from netCDF4 import Dataset # Read / Write NetCDF4 files -import matplotlib.pyplot as plt # Plotting library -from datetime import timedelta, date, datetime # Basic Dates and time types -import cartopy, cartopy.crs as ccrs # Plot maps -import os # Miscellaneous operating system interfaces -from osgeo import gdal # Python bindings for GDAL -import numpy as np # Scientific computing with Python - -from datetime import datetime +import os # Miscellaneous operating system interfaces +from datetime import datetime # Basic Dates and time types import pandas as pd +from osgeo import gdal # Python bindings for GDAL + def dictionary_to_dataframe(input_dict): # Create a DataFrame from the dictionary - df = pd.DataFrame(list(input_dict.items()), columns=['Datetime', 'Value']) - + df = pd.DataFrame(list(input_dict.items()), columns=["Datetime", "Value"]) + # If you want to set the 'Datetime' column as the index - df.set_index('Datetime', inplace=True) - + df.set_index("Datetime", inplace=True) + # Sort the DataFrame by the 'Datetime' index in ascending order df.sort_index(inplace=True) return df + def extract_datetime_from_string(input_string): try: # Split the string by the underscore character to get the date part - date_str = input_string.split('_')[-1] + date_str = input_string.split("_")[-1] # Remove the file extension (if any) by splitting at the last dot ('.') and taking the first part - date_str = date_str.split('.')[0] + date_str = date_str.split(".")[0] # Use strptime to parse the date string into a datetime object # Adjust the format to match the date format in your string (YYYYMMDDHHMM) @@ -47,7 +43,7 @@ def get_rrqpe_value(filename): # Read number of cols and rows ncol = sat_data.RasterXSize nrow = sat_data.RasterYSize - print(f'ncol, nrow = {ncol}, {nrow}') + print(f"ncol, nrow = {ncol}, {nrow}") # Load the data sat_array = sat_data.ReadAsArray(0, 0, ncol, nrow).astype(float) @@ -64,8 +60,7 @@ def get_rrqpe_value(filename): # print(f'Value at ({x},{y}): {sat_array[x,y]}') - return sat_array[x,y] - + return sat_array[x, y] def get_rrqpe_series(folder_path): @@ -82,7 +77,7 @@ def get_rrqpe_series(folder_path): assert timestamp is not None full_filename = os.path.join(folder_path, file) observations[timestamp] = get_rrqpe_value(full_filename) - + return observations except FileNotFoundError: @@ -90,11 +85,14 @@ def get_rrqpe_series(folder_path): except PermissionError: print(f"Permission denied to access folder '{folder_path}'.") + if __name__ == "__main__": - folder_path = './data/goes16/Output' + folder_path = "./data/goes16/Output" print(folder_path) series = get_rrqpe_series(folder_path) df = dictionary_to_dataframe(series) - print(f'Extracted series has {df.shape[0]} points, from {min(df.index)} to {max(df.index)}.') + print( + f"Extracted series has {df.shape[0]} points, from {min(df.index)} to {max(df.index)}." + ) print(df.head()) - df.to_csv('./data/goes16/rrqpe.csv') \ No newline at end of file + df.to_csv("./data/goes16/rrqpe.csv") diff --git a/src/utils/main_plot_bboxes.py b/src/utils/main_plot_bboxes.py new file mode 100644 index 00000000..839a887c --- /dev/null +++ b/src/utils/main_plot_bboxes.py @@ -0,0 +1,90 @@ +import argparse + +import folium +from geopy.distance import geodesic + +""" + Each bounding box is placed in a separate folium.FeatureGroup, ensuring that overlapping or nested bounding boxes are displayed correctly. + Additionally, a layer control is added so users can toggle bounding boxes on and off. +""" + + +def plot_map(bboxes, colors): + # Compute center of the first bounding box + first_bbox = bboxes[0] + center_lat = (first_bbox[0] + first_bbox[2]) / 2 + center_lon = (first_bbox[1] + first_bbox[3]) / 2 + + # Create a Folium map centered at the computed location + m = folium.Map(location=[center_lat, center_lon], zoom_start=8) + + # Create separate feature groups for each bounding box + for i, (lat_min, lon_min, lat_max, lon_max) in enumerate(bboxes): + color = colors[i % len(colors)] # Cycle through colors if fewer than bboxes + bbox_coords = [ + [lat_min, lon_min], + [lat_min, lon_max], + [lat_max, lon_max], + [lat_max, lon_min], + [lat_min, lon_min], # Close the polygon + ] + + # Calculate distances of the sides + width_km = geodesic((lat_min, lon_min), (lat_min, lon_max)).km + height_km = geodesic((lat_min, lon_min), (lat_max, lon_min)).km + popup_text = f"Width: {width_km:.2f} km\nHeight: {height_km:.2f} km" + + # Create a feature group for the bounding box + feature_group = folium.FeatureGroup(name=f"Bounding Box {i + 1}") + folium.Polygon( + bbox_coords, + color=color, + weight=3, + fill=True, + fill_opacity=0.2, + popup=popup_text, + ).add_to(feature_group) + feature_group.add_to(m) + + # Add layer control to toggle visibility + folium.LayerControl().add_to(m) + + # Save map to an HTML file + map_filename = "map.html" + m.save(map_filename) + print(f"Map saved to {map_filename}") + + +def main(): + parser = argparse.ArgumentParser( + description="Plot a map with multiple bounding boxes using Folium." + ) + parser.add_argument( + "bboxes", + type=float, + nargs="+", + help="Bounding box coordinates (lat_min lon_min lat_max lon_max) repeated.", + ) + parser.add_argument( + "--colors", + type=str, + nargs="+", + default=["red"], + help="List of colors for bounding boxes.", + ) + args = parser.parse_args() + + if len(args.bboxes) % 4 != 0: + raise ValueError( + "Each bounding box must have exactly four values: lat_min lon_min lat_max lon_max" + ) + + # Convert list to tuples of bounding boxes + bboxes = [tuple(args.bboxes[i : i + 4]) for i in range(0, len(args.bboxes), 4)] + plot_map(bboxes, args.colors) + + +if __name__ == "__main__": + main() +# Example usage: +# python src/plot_bboxes.py -23.1339033365138 -43.8906028271505 -22.649724748272934 -43.04835145732227 -23.801876626302175 -45.05290312102409 -21.699774257353113 -42.35676996062447 --colors blue green diff --git a/src/utils/near_stations.py b/src/utils/near_stations.py index 9cd3b69d..be270b02 100644 --- a/src/utils/near_stations.py +++ b/src/utils/near_stations.py @@ -1,26 +1,36 @@ -from math import cos, asin, sqrt +from math import asin, cos, sqrt + import pandas as pd + def myFunc2(e): - return e[:][1] + return e[:][1] + def prox(nome, num): - lugar = [] - result = [] - aux1 = pd.read_csv('../data/estacoes_local.csv') - aux = aux1[~aux1['files'].isin([nome])] - del aux['Unnamed: 0'] - for loc in aux['DC_NOME']: - p = 0.017453292519943295 - alvo = aux1[aux1['files'] == nome] - est = aux[aux['DC_NOME'] == loc] + lugar = [] + result = [] + aux1 = pd.read_csv("../data/estacoes_local.csv") + aux = aux1[~aux1["files"].isin([nome])] + del aux["Unnamed: 0"] + for loc in aux["DC_NOME"]: + p = 0.017453292519943295 + alvo = aux1[aux1["files"] == nome] + est = aux[aux["DC_NOME"] == loc] + + hav = ( + 0.5 + - cos((est.VL_LATITUDE.iloc[0] - alvo.VL_LATITUDE.iloc[0]) * p) / 2 + + cos(alvo.VL_LATITUDE.iloc[0] * p) + * cos(est.VL_LATITUDE.iloc[0] * p) + * (1 - cos((est.VL_LONGITUDE.iloc[0] - alvo.VL_LONGITUDE.iloc[0]) * p)) + / 2 + ) - hav = 0.5 - cos((est.VL_LATITUDE.iloc[0]-alvo.VL_LATITUDE.iloc[0])*p)/2 + cos(alvo.VL_LATITUDE.iloc[0]*p)*cos(est.VL_LATITUDE.iloc[0]*p) * (1-cos((est.VL_LONGITUDE.iloc[0]-alvo.VL_LONGITUDE.iloc[0])*p)) / 2 - - dist = 12742 * asin(sqrt(hav)) - lugar = lugar + [(est.files.iloc[0],dist)] - lugar.sort(key=myFunc2) - lugar = lugar[0:num] - result = [i[0] for i in lugar] - print(result) - return result \ No newline at end of file + dist = 12742 * asin(sqrt(hav)) + lugar = lugar + [(est.files.iloc[0], dist)] + lugar.sort(key=myFunc2) + lugar = lugar[0:num] + result = [i[0] for i in lugar] + print(result) + return result diff --git a/src/rainfall.py b/src/utils/rainfall.py similarity index 75% rename from src/rainfall.py rename to src/utils/rainfall.py index 37250f9a..f85addec 100644 --- a/src/rainfall.py +++ b/src/utils/rainfall.py @@ -1,36 +1,37 @@ -import numpy as np -from enum import Enum -from sklearn.preprocessing import OneHotEncoder import math +from enum import Enum -binary_classification_thresholds_dict = { - "NO_RAIN": (0.0, 0.0), - "RAIN": (0.4, math.inf) -} +import numpy as np + +binary_classification_thresholds_dict = {"NO_RAIN": (0.0, 0.0), "RAIN": (0.4, math.inf)} # see http://alertario.rio.rj.gov.br/previsao-do-tempo/termosmet/ multiclass_classification_thresholds_dict = { - "NO_RAIN": (0.0, 0.0), - "WEAK_RAIN": (0.0, 5.0), - "MODERATE_RAIN": (5.0, 25.0), - "STRONG_RAIN": (25.0, 50.0), - "EXTREME_RAIN": (50.0, math.inf) + "NO_RAIN": (0.0, 0.0), + "WEAK_RAIN": (0.0, 5.0), + "MODERATE_RAIN": (5.0, 25.0), + "STRONG_RAIN": (25.0, 50.0), + "EXTREME_RAIN": (50.0, math.inf), } + class ExtendedEnum(Enum): @classmethod def list(cls): return list(map(lambda c: c.value, cls)) + class ForecastingTask(ExtendedEnum): - REGRESSION = 'REGRESSION' - ORDINAL_CLASSIFICATION = 'ORDINAL_CLASSIFICATION' - BINARY_CLASSIFICATION = 'BINARY_CLASSIFICATION' + REGRESSION = "REGRESSION" + ORDINAL_CLASSIFICATION = "ORDINAL_CLASSIFICATION" + BINARY_CLASSIFICATION = "BINARY_CLASSIFICATION" + class BinaryPrecipitationLevel(Enum): NO_RAIN = 0 RAIN = 1 + class OrdinalPrecipitationLevel(Enum): NONE = 0 WEAK = 1 @@ -57,11 +58,13 @@ def level_to_ordinal_encoding(y_level): elif y_level == OrdinalPrecipitationLevel.EXTREME.value: return np.array([1, 1, 1, 1, 1]) + def value_to_ordinal_encoding(y_values): y_levels = value_to_level(y_values) y_encoded = np.array(list(map(level_to_ordinal_encoding, y_levels))) return y_encoded + def ordinal_encoding_to_level(y_encoded: np.ndarray): """ Convert ordinal predictions to class labels, e.g. @@ -71,8 +74,11 @@ def ordinal_encoding_to_level(y_encoded: np.ndarray): """ return (y_encoded > 0.5).cumprod(axis=1).sum(axis=1) - 1 + def value_to_level(y_values): - none_idx, weak_idx, moderate_idx, strong_idx, extreme_idx = get_events_per_level(y_values) + none_idx, weak_idx, moderate_idx, strong_idx, extreme_idx = get_events_per_level( + y_values + ) y_ordinal_levels = np.zeros_like(y_values) y_ordinal_levels[none_idx] = OrdinalPrecipitationLevel.NONE.value y_ordinal_levels[weak_idx] = OrdinalPrecipitationLevel.WEAK.value @@ -81,13 +87,17 @@ def value_to_level(y_values): y_ordinal_levels[extreme_idx] = OrdinalPrecipitationLevel.EXTREME.value return y_ordinal_levels + def value_to_binary_level(y): none_idx, weak_idx, moderate_idx, strong_idx, extreme_idx = get_events_per_level(y) y_levels = np.zeros_like(y) y_levels[none_idx] = BinaryPrecipitationLevel.NO_RAIN.value - y_levels[weak_idx] = y_levels[strong_idx] = y_levels[moderate_idx] = y_levels[extreme_idx] = BinaryPrecipitationLevel.RAIN.value + y_levels[weak_idx] = y_levels[strong_idx] = y_levels[moderate_idx] = y_levels[ + extreme_idx + ] = BinaryPrecipitationLevel.RAIN.value return y_levels + def binary_encoding_to_level(y_encoded): """ Converts a numpy array of binary one-hot-encoded values to their corresponding labels. @@ -105,12 +115,24 @@ def binary_encoding_to_level(y_encoded): binary_labels.append(np.argmax(row)) return binary_labels + def get_events_per_level(y_values): - assert np.all((y_values >= 0)) # We can't have negative precipitation values...right!? + assert np.all( + (y_values >= 0) + ) # We can't have negative precipitation values...right!? thresholds = multiclass_classification_thresholds_dict no_rain = np.where(y_values <= thresholds["NO_RAIN"][1]) - weak_rain = np.where((y_values > thresholds["WEAK_RAIN"][0]) & (y_values <= thresholds["WEAK_RAIN"][1])) - moderate_rain = np.where((y_values > thresholds["MODERATE_RAIN"][0]) & (y_values <= thresholds["MODERATE_RAIN"][1])) - strong_rain = np.where((y_values > thresholds["STRONG_RAIN"][0]) & (y_values <= thresholds["STRONG_RAIN"][1])) - extreme_rain = np.where((y_values > thresholds["EXTREME_RAIN"][0])) + weak_rain = np.where( + (y_values > thresholds["WEAK_RAIN"][0]) + & (y_values <= thresholds["WEAK_RAIN"][1]) + ) + moderate_rain = np.where( + (y_values > thresholds["MODERATE_RAIN"][0]) + & (y_values <= thresholds["MODERATE_RAIN"][1]) + ) + strong_rain = np.where( + (y_values > thresholds["STRONG_RAIN"][0]) + & (y_values <= thresholds["STRONG_RAIN"][1]) + ) + extreme_rain = np.where((y_values > thresholds["EXTREME_RAIN"][0])) return no_rain, weak_rain, moderate_rain, strong_rain, extreme_rain diff --git a/src/util.py b/src/utils/util.py similarity index 64% rename from src/util.py rename to src/utils/util.py index 6f1f7b63..94a22a59 100644 --- a/src/util.py +++ b/src/utils/util.py @@ -1,45 +1,78 @@ -import pytz -from datetime import datetime, timedelta import os -from metpy.calc import wind_components -from metpy.units import units +from datetime import datetime, timedelta +from math import atan2, cos, radians, sin, sqrt + import numpy as np import pandas as pd -import globals -from math import radians, sin, cos, sqrt, atan2 -import logging +import pytz +from metpy.calc import wind_components +from metpy.units import units -import pandas as pd +from config import globals + + +def split_filename(full_filename): + """ + Splits a full filename into its directory path, base name, and file extension. + + Parameters: + full_filename (str): The full path of the file, including directory, base name, and extension. + + Returns: + tuple: A tuple containing: + - dir_path (str): The directory path. + - base_name (str): The base name of the file without the extension. + - file_ext (str): The file extension. + + Examples: + >>> split_filename('/home/user/docs/report.pdf') + ('/home/user/docs', 'report', '.pdf') + + >>> split_filename('C:\\Users\\user\\Desktop\\image.png') + ('C:\\Users\\user\\Desktop', 'image', '.png') + + >>> split_filename('archive.tar.gz') + ('', 'archive.tar', '.gz') + + >>> split_filename('README') + ('', 'README', '') + """ + # Extract the directory path and the filename with extension + dir_path, filename_with_ext = os.path.split(full_filename) + + # Extract the base name and the extension + base_name, file_ext = os.path.splitext(filename_with_ext) + + return (dir_path, base_name, file_ext) -import pandas as pd def add_missing_indicator_column(df: pd.DataFrame, indicator_col_name: str): """ - Add a new column to the given Pandas dataframe with value 1 for rows that have null values + Add a new column to the given Pandas dataframe with value 1 for rows that have null values and 0 for rows that do not have null values. - + Parameters: ----------- df : pandas.DataFrame The dataframe to which the new indicator column is to be added. indicator_col_name : str The name of the new indicator column to be added. - + Returns: -------- pandas.DataFrame The modified dataframe with the new indicator column. """ - + # Create a new column with default value 0 df[indicator_col_name] = 0 - + # Check if any null value is present in each row has_null = df.isnull().any(axis=1) - + # Set the value of the missing indicator column to 1 for the rows that have null values df.loc[has_null, indicator_col_name] = 1 - + return df @@ -71,16 +104,20 @@ def haversine_distance(point1, point2): lat2, lon2 = point2 dlat = radians(lat2 - lat1) dlon = radians(lon2 - lon1) - a = sin(dlat / 2) ** 2 + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) ** 2 + a = ( + sin(dlat / 2) ** 2 + + cos(radians(lat1)) * cos(radians(lat2)) * sin(dlon / 2) ** 2 + ) c = 2 * atan2(sqrt(a), sqrt(1 - a)) distance = R * c return distance + def get_first_and_last_days_of_year(year: int): - ''' + """ This function takes a year as input and returns the first and last days of that year as datetime objects - ''' - assert(year <= datetime.now().year) + """ + assert year <= datetime.now().year # Create datetime object for January 1 of the year first_day = datetime(year, 1, 1) @@ -93,10 +130,12 @@ def get_first_and_last_days_of_year(year: int): return first_day, last_day + def min_max_normalize(df: pd.DataFrame): df = (df - df.min()) / (df.max() - df.min()) return df + def is_posintstring(s): try: temp = int(s) @@ -107,54 +146,57 @@ def is_posintstring(s): except ValueError: return False + def format_time(input_str): - ''' - This function first converts the input string to an integer using the int function. - It then extracts the hours and minutes from the input integer using integer division and modulus operations. + """ + This function first converts the input string to an integer using the int function. + It then extracts the hours and minutes from the input integer using integer division and modulus operations. Finally, it formats the output string using f-strings to ensure that both hours and minutes are represented with two digits. Usage examples: print(format_time("100")) # Output: "01:00" print(format_time("1200")) # Output: "12:00" print(format_time("2300")) # Output: "23:00" - ''' + """ # Convert input string to integer input_int = int(input_str) - + # Extract hours and minutes from the input integer hours = input_int // 100 minutes = input_int % 100 - + # Format the output string output_str = f"{hours:02}:{minutes:02}" - + return output_str + def utc_to_local_DEPRECATED(utc_string, local_tz, format_string): - ''' - This function first converts the UTC string to a datetime object with timezone information - using strptime() and replace(). Then it converts the datetime object to the local timezone + """ + This function first converts the UTC string to a datetime object with timezone information + using strptime() and replace(). Then it converts the datetime object to the local timezone using astimezone(). Finally, it formats the resulting datetime as a string in the same format as the input string. Here's an example usage of the function: - + utc_string = '1972-09-13 12:00:00' local_tz = 'America/Sao_Paulo' format_string = '%Y-%m-%d %H:%M' local_string = utc_to_local(utc_string, local_tz, format_string) print(local_string) - ''' + """ # convert utc string to datetime object utc_dt = datetime.strptime(utc_string, format_string).replace(tzinfo=pytz.UTC) - + # convert to local timezone local_tz = pytz.timezone(local_tz) local_dt = utc_dt.astimezone(local_tz) - + # format as string and return return local_dt.strftime(format_string) + def transform_wind(wind_speed, wind_direction, comp_idx): """ This function calculates either the U or V wind vector component from the speed and direction. @@ -162,26 +204,35 @@ def transform_wind(wind_speed, wind_direction, comp_idx): comp_idx = 1 --> computes the V component (see https://unidata.github.io/MetPy/latest/api/generated/metpy.calc.wind_components.html) """ - assert(comp_idx == 0 or comp_idx == 1) - return wind_components(wind_speed * units('m/s'), wind_direction * units.deg)[comp_idx].magnitude + assert comp_idx == 0 or comp_idx == 1 + return wind_components(wind_speed * units("m/s"), wind_direction * units.deg)[ + comp_idx + ].magnitude + def add_datetime_index(station_id, df): timestamp = None if station_id in globals.INMET_WEATHER_STATION_IDS: - df.HR_MEDICAO = df.HR_MEDICAO.apply(format_time) # e.g., 1800 --> 18:00 - timestamp = pd.to_datetime(df.DT_MEDICAO + ' ' + df.HR_MEDICAO) + df.HR_MEDICAO = df.HR_MEDICAO.apply(format_time) # e.g., 1800 --> 18:00 + timestamp = pd.to_datetime(df.DT_MEDICAO + " " + df.HR_MEDICAO) elif station_id in globals.ALERTARIO_WEATHER_STATION_IDS: - timestamp = pd.to_datetime(df['datetime']) - timestamp = timestamp.dt.tz_convert('UTC') + timestamp = pd.to_datetime(df["datetime"]) + timestamp = timestamp.dt.tz_convert("UTC") assert timestamp is not None df = df.set_index(pd.DatetimeIndex(timestamp)) return df + def add_wind_related_features(station_id, df): - df['wind_direction_u'] = df.apply(lambda x: transform_wind(x.wind_speed, x.wind_dir, 0),axis=1) - df['wind_direction_v'] = df.apply(lambda x: transform_wind(x.wind_speed, x.wind_dir, 1),axis=1) + df["wind_direction_u"] = df.apply( + lambda x: transform_wind(x.wind_speed, x.wind_dir, 0), axis=1 + ) + df["wind_direction_v"] = df.apply( + lambda x: transform_wind(x.wind_speed, x.wind_dir, 1), axis=1 + ) return df + def add_hour_related_features(df): """ Transforms a DataFrame's datetime index into two new columns representing the hour in sin and cosine form. @@ -194,11 +245,12 @@ def add_hour_related_features(df): - The input pandas DataFrame with two new columns named 'hour_sin' and 'hour_cos' representing the hour in sin and cosine form. """ dt = df.index - hourfloat = dt.hour + dt.minute/60.0 - df['hour_sin'] = np.sin(2. * np.pi * hourfloat/24.) - df['hour_cos'] = np.cos(2. * np.pi * hourfloat/24.) + hourfloat = dt.hour + dt.minute / 60.0 + df["hour_sin"] = np.sin(2.0 * np.pi * hourfloat / 24.0) + df["hour_cos"] = np.cos(2.0 * np.pi * hourfloat / 24.0) return df + def get_filename_and_extension(filename): """ Given a filename, returns a tuple with the base filename and extension. @@ -207,6 +259,7 @@ def get_filename_and_extension(filename): filename_parts = os.path.splitext(basename) return filename_parts + def find_contiguous_observation_blocks(df: pd.DataFrame): """ Given a list of timestamps, finds contiguous blocks of timestamps that are exactly one hour apart of each other. @@ -223,10 +276,10 @@ def find_contiguous_observation_blocks(df: pd.DataFrame): >>> print(len(contiguous_observations)) >>> print(contiguous_observations) 5 - [(Timestamp('2007-05-18 18:00:00'), Timestamp('2007-05-18 19:00:00')), - (Timestamp('2007-05-19 11:00:00'), Timestamp('2007-05-19 13:00:00')), - (Timestamp('2007-05-20 12:00:00'), Timestamp('2007-05-21 00:00:00')), - (Timestamp('2007-05-21 02:00:00'), Timestamp('2007-05-21 08:00:00')), + [(Timestamp('2007-05-18 18:00:00'), Timestamp('2007-05-18 19:00:00')), + (Timestamp('2007-05-19 11:00:00'), Timestamp('2007-05-19 13:00:00')), + (Timestamp('2007-05-20 12:00:00'), Timestamp('2007-05-21 00:00:00')), + (Timestamp('2007-05-21 02:00:00'), Timestamp('2007-05-21 08:00:00')), (Timestamp('2007-05-21 10:00:00'), Timestamp('2007-05-31 23:00:00'))] In this example, `timestamp_range` is a list of pandas Timestamps extracted from a DataFrame's 'Datetime' index. @@ -237,80 +290,108 @@ def find_contiguous_observation_blocks(df: pd.DataFrame): - None """ timestamp_range = df.index - assert (len(timestamp_range) > 1) + assert len(timestamp_range) > 1 first = last = timestamp_range[0] for n in timestamp_range[1:]: previous = n - timedelta(hours=1, minutes=0) - if previous == last: # Part of the current block, bump the end + if previous == last: # Part of the current block, bump the end last = n - else: # Not part of the current block; yield current block and start a new one + else: # Not part of the current block; yield current block and start a new one yield first, last first = last = n - yield first, last # Yield the last block + yield first, last # Yield the last block + def get_relevant_variables(station_id): if station_id in globals.INMET_WEATHER_STATION_IDS: - return ['temperature', 'barometric_pressure', 'relative_humidity', 'wind_direction_u', 'wind_direction_v', 'hour_sin', 'hour_cos'], 'precipitation' + return [ + "temperature", + "barometric_pressure", + "relative_humidity", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos", + ], "precipitation" elif station_id in globals.ALERTARIO_WEATHER_STATION_IDS: - return ['temperature', 'barometric_pressure', 'relative_humidity', 'wind_direction_u', 'wind_direction_v', 'hour_sin', 'hour_cos'], 'precipitation' + return [ + "temperature", + "barometric_pressure", + "relative_humidity", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos", + ], "precipitation" elif station_id in globals.ALERTARIO_GAUGE_STATION_IDS: - return ['temperature', 'barometric_pressure', 'relative_humidity', 'wind_direction_u', 'wind_direction_v', 'hour_sin', 'hour_cos'], 'precipitation' + return [ + "temperature", + "barometric_pressure", + "relative_humidity", + "wind_direction_u", + "wind_direction_v", + "hour_sin", + "hour_cos", + ], "precipitation" return None + def convert_to_celsius(temperature_kelvin): - """Converts a temperature from Kelvin to Celsius. + """Converts a temperature from Kelvin to Celsius. + + Args: + temperature_kelvin: The temperature in Kelvin. - Args: - temperature_kelvin: The temperature in Kelvin. + Returns: + The temperature in Celsius. + """ - Returns: - The temperature in Celsius. - """ + return temperature_kelvin - 273.15 - return temperature_kelvin - 273.15 def rename_dataframe_column_names(df: pd.DataFrame, column_name_mapping: dict): - """ - Renames the column names in the DataFrame according to the specified dictionary. + """ + Renames the column names in the DataFrame according to the specified dictionary. + + Args: + df: The DataFrame to rename. + column_name_mapping: The dictionary that maps old column names to new column names. - Args: - df: The DataFrame to rename. - column_name_mapping: The dictionary that maps old column names to new column names. + Returns: + The renamed DataFrame. + """ - Returns: - The renamed DataFrame. - """ + new_column_names = [] + for old_column_name, new_column_name in column_name_mapping.items(): + if old_column_name in df.columns: + new_column_names.append(new_column_name) + else: + print(f"The column name {old_column_name} does not exist in the DataFrame.") - new_column_names = [] - for old_column_name, new_column_name in column_name_mapping.items(): - if old_column_name in df.columns: - new_column_names.append(new_column_name) - else: - print(f"The column name {old_column_name} does not exist in the DataFrame.") + df.columns = new_column_names + return df - df.columns = new_column_names - return df def get_dataframe_with_selected_columns(df, column_names): - """ - Returns a DataFrame containing only the columns whose names are passed in the list. + """ + Returns a DataFrame containing only the columns whose names are passed in the list. - Args: - df: The DataFrame to select columns from. - column_names: The list of column names to select. + Args: + df: The DataFrame to select columns from. + column_names: The list of column names to select. - Returns: - A DataFrame containing only the selected columns. - """ + Returns: + A DataFrame containing only the selected columns. + """ - selected_columns = [] - for column_name in column_names: - if column_name in df.columns: - selected_columns.append(column_name) - else: - print(f"The column name {column_name} does not exist in the DataFrame.") + selected_columns = [] + for column_name in column_names: + if column_name in df.columns: + selected_columns.append(column_name) + else: + print(f"The column name {column_name} does not exist in the DataFrame.") - return df[selected_columns] + return df[selected_columns] def split_dataframe_by_date(df, split_date): @@ -337,8 +418,8 @@ def split_dataframe_by_date(df, split_date): # print(type(df.index[0])) # print(type(df.index)) # print(type(df.index.to_pydatetime())) - + df_before = df[df.index < split_date] df_after = df[df.index >= split_date] - return df_before, df_after \ No newline at end of file + return df_before, df_after diff --git a/src/utils/windowing.py b/src/utils/windowing.py index d119ef94..112ef667 100644 --- a/src/utils/windowing.py +++ b/src/utils/windowing.py @@ -1,13 +1,7 @@ - -import pandas as pd import numpy as np -def apply_windowing(X, - initial_time_step, - max_time_step, - window_size, - target_idx): +def apply_windowing(X, initial_time_step, max_time_step, window_size, target_idx): assert target_idx >= 0 and target_idx < X.shape[1] assert initial_time_step >= 0 assert max_time_step >= initial_time_step @@ -15,26 +9,29 @@ def apply_windowing(X, start = initial_time_step sub_windows = ( - start + + start + + # expand_dims converts a 1D array to 2D array. - np.expand_dims(np.arange(window_size), 0) + - np.expand_dims(np.arange(max_time_step + 1), 0).T + np.expand_dims(np.arange(window_size), 0) + + np.expand_dims(np.arange(max_time_step + 1), 0).T ) - X_temp, y_temp = X[sub_windows], X[window_size:( - max_time_step+window_size+1):1, target_idx] + X_temp, y_temp = ( + X[sub_windows], + X[window_size : (max_time_step + window_size + 1) : 1, target_idx], + ) idx_y_train_not_nan = np.where(~np.isnan(y_temp))[0] assert len(idx_y_train_not_nan) == len(y_temp) - x_train_is_nan_idx = np.unique(np.where(np.isnan(X_temp))) + np.unique(np.where(np.isnan(X_temp))) # assert len(x_train_is_nan_idx) == len(y_temp) # print(f'X.shape: {X.shape}') # print(f'Shapes before filtering: {X_temp.shape}, {y_temp.shape}') - idx_y_train_gt_zero = np.where(y_temp > 0)[0] - + np.where(y_temp > 0)[0] + # if only_y_gt_zero: # y_train_gt_zero_idx = np.where(y_temp > 0)[0] # idxs = np.intersect1d(y_train_not_nan_idx, y_train_gt_zero_idx) diff --git a/src/websirenes/.gitignore b/src/websirenes/.gitignore new file mode 100644 index 00000000..f5484bf7 --- /dev/null +++ b/src/websirenes/.gitignore @@ -0,0 +1,3 @@ +websirenes_coords.parquet +websirenes_coords.csv +*.png \ No newline at end of file diff --git a/src/websirenes/ERA5Land/.gitignore b/src/websirenes/ERA5Land/.gitignore new file mode 100644 index 00000000..c96a04f0 --- /dev/null +++ b/src/websirenes/ERA5Land/.gitignore @@ -0,0 +1,2 @@ +* +!.gitignore \ No newline at end of file diff --git a/src/websirenes/GreatCircleDistance.py b/src/websirenes/GreatCircleDistance.py new file mode 100644 index 00000000..5a70fa68 --- /dev/null +++ b/src/websirenes/GreatCircleDistance.py @@ -0,0 +1,33 @@ +from math import atan2, cos, radians, sin, sqrt + + +class GreatCircleDistance: + EARTH_RADIUS_KM = 6371.0 + + def _degrees_to_radians(self, *degrees: float) -> list[float]: + return [radians(degree) for degree in degrees] + + def _haversine_function(self, theta: float) -> float: + return sin(theta / 2) ** 2 + + def _haversine_formula( + self, lat1: float, lon1: float, lat2: float, lon2: float + ) -> float: + delta_lat = lat2 - lat1 + delta_lon = lon2 - lon1 + return self._haversine_function(delta_lat) + cos(lat1) * cos( + lat2 + ) * self._haversine_function(delta_lon) + + def _inverse_haversine_function(self, y: float) -> float: + return 2 * atan2(sqrt(y), sqrt(1 - y)) + + def get_distance(self, lat1: float, lon1: float, lat2: float, lon2: float) -> float: + lat1, lon1, lat2, lon2 = self._degrees_to_radians(lat1, lon1, lat2, lon2) + haversine_theta = self._haversine_formula(lat1, lon1, lat2, lon2) + theta_angle = self._inverse_haversine_function(haversine_theta) + arc_length = self.EARTH_RADIUS_KM * theta_angle + return arc_length + + +great_circle_distance = GreatCircleDistance() diff --git a/src/websirenes/Logger.py b/src/websirenes/Logger.py new file mode 100644 index 00000000..7e065ac4 --- /dev/null +++ b/src/websirenes/Logger.py @@ -0,0 +1,21 @@ +import logging + + +class Logger: + def __init__(self): + self.logger = logging.getLogger("log") + self.logger.setLevel(logging.DEBUG) + handler = logging.StreamHandler() + handler.setFormatter( + logging.Formatter( + "%(asctime)s - %(name)s - %(levelname)s - %(message)s", + datefmt="%Y-%m-%d %H:%M:%S", + ) + ) + self.logger.addHandler(handler) + + def get_logger(self, name: str) -> logging.Logger: + return self.logger.getChild(name) + + +logger = Logger() diff --git a/src/websirenes/WebSirenesBuilder.py b/src/websirenes/WebSirenesBuilder.py new file mode 100644 index 00000000..2f0ed4c9 --- /dev/null +++ b/src/websirenes/WebSirenesBuilder.py @@ -0,0 +1,106 @@ +from pathlib import Path +from typing import Annotated + +import pandas as pd +import pandera as pa + +from .Logger import logger +from .WebSirenesParser import WebSirenesParser, websirenes_parser + +log = logger.get_logger(__name__) + + +class WebSirenesBuilder: + def __init__( + self, websirenes_parser: WebSirenesParser, websirenes_coords: pd.DataFrame + ) -> None: + self.websirenes_datasets_path = Path(__file__).parent / "websirenes_datasets" + self.websirenes_parser = websirenes_parser + self.websirenes_coords = websirenes_coords + + @property + def _not_founds_in_coords( + self, + ) -> list[dict[Annotated[str, "name"], Annotated[int, "station_id"]]]: + stations_name_id = [] + + for file in self.websirenes_parser.list_files(): + name, station_id = self.websirenes_parser.read_station_name_id_txt_file( + self.websirenes_parser.websirenes_defesa_civil_path / file + ) + stations_name_id.append({"name": name, "station_id": station_id}) + + not_founds_in_parquet = [] + for station_name_id in stations_name_id: + name = station_name_id["name"] + if name not in self.websirenes_coords["estacao"].values: + not_founds_in_parquet.append(station_name_id) + return not_founds_in_parquet + + def merge_by_name( + self, websirenes_coords: pd.DataFrame, websirenes_defesa_civil: pd.DataFrame + ) -> pd.DataFrame: + websirenes_defesa_civil.reset_index(inplace=True) + df = pd.merge( + websirenes_coords, + websirenes_defesa_civil, + left_on="estacao", + right_on="nome", + how="inner", + ) + df.drop(columns=["estacao", "id_estacao"], inplace=True) + df.set_index("horaLeitura", inplace=True) + return df + + def _create_key(self, df: pd.DataFrame) -> Annotated[str, "lat_long"]: + row = df.iloc[0] + return f"{row['latitude']}_{row['longitude']}" + + def _write_dataset_key(self, df: pd.DataFrame, key: str): + if not self.websirenes_datasets_path.exists(): + self.websirenes_datasets_path.mkdir() + if (self.websirenes_datasets_path / f"{key}.parquet").exists(): + print(f"Dataset {key}.parquet already exists") + return + df.to_parquet(self.websirenes_datasets_path / f"{key}.parquet") + + def build_dataset_keys(self): + if not self.websirenes_datasets_path.exists(): + self.websirenes_datasets_path.mkdir() + for i, file in enumerate(self.websirenes_parser.list_files()): + log.info( + f"Processing file {i + 1} of {len(self.websirenes_parser.list_files())}" + ) + df = self.websirenes_parser.get_dataframe( + self.websirenes_parser.websirenes_defesa_civil_path / file + ) + station_name = df.nome.iloc[0] + if station_name in [x["name"] for x in self._not_founds_in_coords]: + log.info(f"Station {station_name} not found in parquet") + continue + + df = self.merge_by_name(self.websirenes_coords, df) + key = self._create_key(df) + self._write_dataset_key(df, key) + log.info( + f""" + Station name: {station_name} + Station key: {key} + Initial operation date: {df.index.min()} + Last operation date: {df.index.max()} + """ + ) + + +class WebSireneCoordsSchema(pa.DataFrameModel): + id_estacao: int + estacao: str + estacao_desc: str + latitude: float = pa.Field(ge=-90, le=90, nullable=False) + longitude: float = pa.Field(ge=-180, le=180, nullable=False) + + +websirenes_coords = pd.read_parquet(Path(__file__).parent / "websirenes_coords.parquet") +WebSireneCoordsSchema.validate(websirenes_coords) + +websirenes_builder = WebSirenesBuilder(websirenes_parser, websirenes_coords) diff --git a/src/websirenes/WebSirenesParser.py b/src/websirenes/WebSirenesParser.py new file mode 100644 index 00000000..1a03cf94 --- /dev/null +++ b/src/websirenes/WebSirenesParser.py @@ -0,0 +1,159 @@ +import os +import re +from collections import Counter +from datetime import datetime +from pathlib import Path +from typing import Annotated +from zoneinfo import ZoneInfo + +import numpy as np +import pandas as pd +import pandera as pa + + +def get_UTC_offset_from_timezone_name(timezone_name: str) -> str: + now = datetime.now(ZoneInfo(timezone_name)) + return now.strftime("%z") + + +class WebSireneSchema(pa.DataFrameModel): + # horaLeitura: pa.typing.Index[datetime] = pa.Field(coerce=True) # tz naive + horaLeitura: pa.typing.Index[ + Annotated[ + pd.DatetimeTZDtype, + "ns", + f"UTC{get_UTC_offset_from_timezone_name('America/Sao_Paulo')}", + ] + ] # tz aware + nome: str + m15: float = pa.Field(nullable=True) + m30: float = pa.Field(nullable=True) + h01: float = pa.Field(nullable=True) + h02: float = pa.Field(nullable=True) + h03: float = pa.Field(nullable=True) + h04: float = pa.Field(nullable=True) + h24: float = pa.Field(nullable=True) + h96: float = pa.Field(nullable=True) + station_id: int + + +class WebSirenesParser: + def list_files(self) -> list[str]: + files = os.listdir(Path(__file__).parent / "websirenes_defesa_civil") + return [file for file in files if file != ".gitignore"] + + def _get_name_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 ... matches BARRA DA TIJUCA 3 + Returns: + str: regex pattern to extract name from line + """ + return r"^(?P.+?)(?=\s+\d{4}-\d{2}-\d{2})" + + def _get_date_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 ... matches 2021-08-01 00:00:00-03 + Returns: + str: regex pattern to extract date from line + """ + return r"(?P\d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2}-\d{2})" + + def _get_timeframe_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 3 4 5 6 7 8 ... matches null 2 3 4 5 6 7 8 + Returns: + str: regex pattern to extract timeframe from line + """ + return r"(?P.+)$" + + def _get_complete_pattern(self) -> str: + """ + Example: + BARRA DA TIJUCA 3 2021-08-01 00:00:00-03 null 2 3 4 5 6 7 8 ... + matches: + BARRA DA TIJUCA 3 at group 'name' + 2021-08-01 00:00:00-03 at group 'date' + null 2 3 4 5 6 7 8 at group 'timeframe' + Returns: + str: regex pattern to extract name, date and timeframe from line + """ + return rf"{self._get_name_pattern()}\s+{self._get_date_pattern()}\s+{self._get_timeframe_pattern()}" + + def _extract_features(self, line: str) -> tuple: + complete_pattern = self._get_complete_pattern() + + match = re.search(complete_pattern, line) + + name = match.group("name") + date = match.group("date") + "00" + timeframe = match.group("timeframe") + + m15, m30, h01, h02, h03, h04, h24, h96, station_id = [ + ( + np.nan + if x == "null" + else float(x.replace(",", ".")) if "," in x else float(x) + ) + for x in timeframe.strip().split() + ] + + return ( + name, + datetime.strptime(date, "%Y-%m-%d %H:%M:%S%z"), + m15, + m30, + h01, + h02, + h03, + h04, + h24, + h96, + int(station_id), + ) + + def _parse_txt_file(self, file_path: str) -> tuple[list[str], list[tuple]]: + file_data: list[tuple] = [] + with open(file_path, "r", encoding="utf-8-sig") as file: + header = file.readline().strip().split() + for line in file: + file_data.append(self._extract_features(line)) + return header, file_data + + def read_station_name_id_txt_file(self, file_path: str) -> tuple[str, int]: + with open(file_path, "r", encoding="utf-8-sig") as file: + _ = file.readline().strip().split() + nome, horaLeitura, m15, m30, h01, h02, h03, h04, h24, h96, station_id = ( + self._extract_features(file.readline()) + ) + return nome, station_id + + def get_dataframe_by_name(self, name: str) -> pd.DataFrame: + for file in self.list_files(): + nome, _ = self.read_station_name_id_txt_file( + Path(__file__).parent / "websirenes_defesa_civil" / file + ) + if nome == name: + return self.get_dataframe( + Path(__file__).parent / "websirenes_defesa_civil" / file + ) + print(f"Station {name} not found") + exit(1) + + def get_time_resolution(self, dates: pd.Series) -> dict: + return dict(Counter([dates[i] - dates[i - 1] for i in range(1, len(dates))])) + + def get_dataframe(self, file_path: str) -> pd.DataFrame: + header, file_data = self._parse_txt_file(file_path) + df = pd.DataFrame(file_data, columns=header) + df.rename(columns={"id": "station_id"}, inplace=True) + df.set_index("horaLeitura", inplace=True) + return WebSireneSchema.validate(df) + + def assert_is_sorted_by_date(self, df: pd.DataFrame) -> bool: + assert df.index.is_monotonic_increasing, "DataFrame index is not sorted by date" + + +websirenes_parser = WebSirenesParser() diff --git a/src/websirenes/__init__.py b/src/websirenes/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/src/websirenes/check_requirements.py b/src/websirenes/check_requirements.py new file mode 100644 index 00000000..3447246a --- /dev/null +++ b/src/websirenes/check_requirements.py @@ -0,0 +1,40 @@ +from pathlib import Path + + +def check_requirements(): + websirenes_defesa_civil_path = Path(__file__).parent / "websirenes_defesa_civil" + if not websirenes_defesa_civil_path.exists(): + print( + f"Expected websirenes_defesa_civil folder in {websirenes_defesa_civil_path}" + ) + exit(1) + + if not list(websirenes_defesa_civil_path.glob("*.txt")): + print( + f"websirenes_defesa_civil folder does not contain any txt files at {websirenes_defesa_civil_path}" + ) + exit(1) + + websirenes_coords_path = Path(__file__).parent / "websirenes_coords.parquet" + if not websirenes_coords_path.exists(): + print(f"Expected websirenes_coords.parquet file in {websirenes_coords_path}") + exit(1) + + era5_land_path = Path(__file__).parent / "ERA5Land" + if not era5_land_path.exists(): + print(f"Expected ERA5Land folder in {era5_land_path}") + exit(1) + + monthly_data_path = era5_land_path / "monthly_data" + montly_data_path = era5_land_path / "montly_data" + if not monthly_data_path.exists() and not montly_data_path.exists(): + print(f"Expected monthly_data folder in {monthly_data_path}") + exit(1) + + if not list(monthly_data_path.glob("*.nc")) and not list( + montly_data_path.glob("*.nc") + ): + print( + f"monthly_data folder does not contain any .nc files at {monthly_data_path}" + ) + exit(1) diff --git a/src/websirenes/get_nearest_ERA5Land.py b/src/websirenes/get_nearest_ERA5Land.py new file mode 100644 index 00000000..397e6887 --- /dev/null +++ b/src/websirenes/get_nearest_ERA5Land.py @@ -0,0 +1,38 @@ +from pathlib import Path + +import xarray as xr + +from .GreatCircleDistance import great_circle_distance +from .Logger import logger + +log = logger.get_logger(__name__) + + +def _get_lats_lons() -> tuple[list[float], list[float]]: + era5_land_path = Path(__file__).parent / "ERA5Land" / "montly_data" + if not era5_land_path.exists(): + log.error(f"ERA5Land path {era5_land_path} does not exist.") + era5_land_path = Path(__file__).parent / "ERA5Land" / "monthly_data" + if not era5_land_path.exists(): + log.error(f"ERA5Land path {era5_land_path} does not exist.") + exit(1) + + era5land_nc_ds = xr.open_dataset(next(era5_land_path.iterdir())) + latitudes = era5land_nc_ds.coords["latitude"].values + longitudes = era5land_nc_ds.coords["longitude"].values + log.info(f"latitudes: {latitudes}") + log.info(f"longitudes: {longitudes}") + return latitudes, longitudes + + +def get_nearest_ERA5Land(latitude: float, longitude: float) -> tuple[float, float]: + min_distance = float("inf") + nearest_station = None + era5land_lats, era5land_lons = _get_lats_lons() + for lat in era5land_lats: + for lon in era5land_lons: + distance = great_circle_distance.get_distance(latitude, longitude, lat, lon) + if distance < min_distance: + min_distance = distance + nearest_station = (lat, lon) + return nearest_station diff --git a/src/websirenes/plot_values.py b/src/websirenes/plot_values.py new file mode 100644 index 00000000..2b3ad82a --- /dev/null +++ b/src/websirenes/plot_values.py @@ -0,0 +1,29 @@ +from pathlib import Path + +import matplotlib.pyplot as plt +import pandas as pd + + +def plot_tp_values( + websirenes_df: pd.DataFrame, + era5land_df: pd.DataFrame, + start_date: pd.Timestamp, + end_date: pd.Timestamp, + station_name: str, +): + plt.figure(figsize=(10, 5)) + plt.plot(era5land_df.index, era5land_df["tp"], label="ERA5Land") + plt.plot(websirenes_df.index, websirenes_df["m15"], label="WebSirenes") + + plt.title("Total Precipitation values") + plt.xlabel("Date") + plt.ylabel("Total Precipitation") + + plt.legend() + + plt.savefig( + Path(__file__).parent + / f"Total_Precipitation_values_{station_name}_{start_date}_{end_date}.png" + ) + + plt.show() diff --git a/src/websirenes/total_precipitation.py b/src/websirenes/total_precipitation.py new file mode 100644 index 00000000..a4c7ceab --- /dev/null +++ b/src/websirenes/total_precipitation.py @@ -0,0 +1,224 @@ +import argparse +from collections.abc import Generator +from datetime import datetime +from pathlib import Path +from zoneinfo import ZoneInfo + +import pandas as pd +import xarray as xr + +from .check_requirements import check_requirements +from .get_nearest_ERA5Land import get_nearest_ERA5Land +from .Logger import logger +from .plot_values import plot_tp_values +from .WebSirenesBuilder import websirenes_builder, websirenes_coords +from .WebSirenesParser import websirenes_parser + +log = logger.get_logger(__name__) + + +def _get_datasets_generator( + era5land_nc_files: list[str], +) -> Generator[xr.Dataset, None, None]: + for nc_file in era5land_nc_files: + yield xr.open_dataset( + Path(__file__).parent / "ERA5Land" / "montly_data" / nc_file + ) + + +def _get_era5land_data( + nearest_era5land: tuple[float, float], + start_date: pd.Timestamp, + end_date: pd.Timestamp, +) -> pd.DataFrame: + start_year, start_month = start_date.year, start_date.month + end_year, end_month = end_date.year, end_date.month + + era5land_monthly_data_path = Path(__file__).parent / "ERA5Land" / "montly_data" + if not era5land_monthly_data_path.exists(): + era5land_monthly_data_path = Path(__file__).parent / "ERA5Land" / "monthly_data" + if not era5land_monthly_data_path.exists(): + log.error( + f"ERA5Land monthly data path {era5land_monthly_data_path} does not exist." + ) + exit(1) + + era5land_nc_files = [ + f"RJ_{year}_{month}.nc" + for year in range(start_year, end_year + 1) + for month in range(start_month, end_month + 1) + ] + + datasets_generator = _get_datasets_generator(era5land_nc_files) + ds = next(datasets_generator) + for dataset in datasets_generator: + if "expver" in list(ds.coords.keys()): + log.warning("expver dimension found. Going to remove it.") + ds_combine = ds.sel(expver=1).combine_first(ds.sel(expver=5)) + ds_combine.load() + ds = ds_combine + ds = ds.merge(dataset) + + nearest_era5land_lat, nearest_era5land_lon = nearest_era5land + + ds = ds.sel( + latitude=nearest_era5land_lat, longitude=nearest_era5land_lon, method="nearest" + ) + log.info("ERA5Land ds data:") + print(ds) + + era5land_df = ds.to_dataframe() + log.info("ERA5Land df data:") + print(era5land_df) + log.info("ERA5Land data summary:") + print(era5land_df.describe()) + log.info("ERA5Land data time range:") + print(era5land_df.index.min(), era5land_df.index.max()) + log.info("NaN values in ERA5Land data per column:") + print(era5land_df.isna().sum()) + return era5land_df + + +def main( + start_date: str, + end_date: str, + station_name: str, +): + df = get_websinere(station_name) + log.info(f"Filtering Websirene data between {start_date} and {end_date}") + + start_date = pd.to_datetime( + datetime.strptime(start_date, "%Y-%m-%d").replace( + tzinfo=ZoneInfo("America/Sao_Paulo") + ) + ) + end_date = pd.to_datetime( + datetime.strptime(end_date, "%Y-%m-%d").replace( + tzinfo=ZoneInfo("America/Sao_Paulo") + ) + ) + + if start_date < df.index.min() or start_date > df.index.max(): + log.error(f"Invalid start date {start_date} for WebSirene {station_name} data") + log.error(f"Data range is {df.index.min()} to {df.index.max()}") + exit(1) + + if end_date > df.index.max() or end_date < df.index.min(): + log.error(f"Invalid end date {end_date} for WebSirene {station_name} data") + log.error(f"Data range is {df.index.min()} to {df.index.max()}") + exit(1) + + df = df.loc[start_date:end_date] + log.info(f"WebSirene {station_name} data between {start_date} and {end_date}:") + print(df) + log.info(f"WebSirene {station_name} data summary:") + print(df.describe()) + # log.info("WebSirene data time resolution:") + # print(websirenes_parser.get_time_resolution(df.index)) + log.info("WebSirene data time range:") + print(df.index.min(), df.index.max()) + log.info("NaN values in WebSirene data per column:") + print(df.isna().sum()) + log.info("Merging WebSirene data with WebSirene coords") + df = websirenes_builder.merge_by_name(websirenes_coords, df) + log.info("WebSirene data after merge:") + print(df) + lat, long = df["latitude"].values[0], df["longitude"].values[0] + log.info(f"Getting nearest ERA5Land station to WebSirene {station_name} station") + nearest_era5land = get_nearest_ERA5Land(lat, long) + log.info(f"Nearest ERA5Land station to WebSirene {station_name} station coords:") + print(nearest_era5land) + log.info("Getting ERA5Land data...") + era5land_df = _get_era5land_data(nearest_era5land, start_date, end_date) + + df_m15_values = df[["m15"]] + log.info("WebSirene m15 and horaLeitura data:") + print(df_m15_values) + era5land_df_total_precipitation = era5land_df[["tp"]] + log.info("ERA5Land total precipitation and time data:") + print(era5land_df_total_precipitation) + plot_tp_values( + df_m15_values, + era5land_df_total_precipitation, + start_date, + end_date, + station_name, + ) + + +def show_websirenes_coords_and_names(): + websirenes_coords.to_csv( + Path(__file__).parent / "websirenes_coords.csv", index=False + ) + log.info("Websirenes coords stored into csv 'websirenes_coords.csv' file") + log.info("Websirenes coords data:") + print(websirenes_coords) + log.info("Websirenes coords and names:") + coords_data = [ + { + "name": row["estacao"], + "latitude": row["latitude"], + "longitude": row["longitude"], + } + for name, row in websirenes_coords.iterrows() + ] + print(coords_data) + + +def get_websinere(station_name: str) -> pd.DataFrame: + websirene = websirenes_coords[websirenes_coords["estacao"] == station_name] + log.info(f"Websirene {station_name} station coords data:") + print(websirene) + log.info(f"Getting WebSirene {station_name} data...") + df = websirenes_parser.get_dataframe_by_name(station_name) + log.info(f"WebSirene {station_name} data:") + print(df) + log.info(f"WebSirene {station_name} data summary:") + print(df.describe()) + # log.info("WebSirene data time resolution:") + # print(websirenes_parser.get_time_resolution(df.index)) + log.info("WebSirene data time range:") + print(df.index.min(), df.index.max()) + log.info("NaN values in WebSirene data per column:") + print(df.isna().sum()) + return df + + +if __name__ == "__main__": + parser = argparse.ArgumentParser( + description="Plot ERA5Land total precipitation and websirenes precipitation data between two dates" + ) + parser.add_argument( + "--start_date", type=str, help="Start date of the period to be analyzed" + ) + parser.add_argument( + "--end_date", type=str, help="End date of the period to be analyzed" + ) + parser.add_argument("--station_name", type=str, help="Region of interest") + + parser.add_argument( + "--show_websirenes", action="store_true", help="Show websirenes data" + ) + parser.add_argument("--get_websirene", type=str, help="Get websirene data") + + args = parser.parse_args() + + check_requirements() + + if args.show_websirenes: + show_websirenes_coords_and_names() + exit(0) + + if args.get_websirene: + get_websinere(args.get_websirene) + exit(0) + + if not args.start_date or not args.end_date or not args.station_name: + log.error("Please provide --start_date, --end_date and --station_name") + exit(1) + + main( + start_date=args.start_date, + end_date=args.end_date, + station_name=args.station_name, + ) diff --git a/test.txt b/test.txt new file mode 100644 index 00000000..6f16acbb --- /dev/null +++ b/test.txt @@ -0,0 +1 @@ +teste diff --git a/tests/test_rainfall.py b/tests/test_rainfall.py index 7a6b3b71..aeb4c680 100644 --- a/tests/test_rainfall.py +++ b/tests/test_rainfall.py @@ -1,57 +1,90 @@ # import sys # sys.path.insert(0, '../src') import unittest + import numpy as np -from src.rainfall import * + +from utils import rainfall + class TestRainfallFunctions(unittest.TestCase): def test_level_to_ordinal_encoding(self): - self.assertTrue(np.array_equal(level_to_ordinal_encoding(0), np.array([1, 0, 0, 0, 0]))) - self.assertTrue(np.array_equal(level_to_ordinal_encoding(1), np.array([1, 1, 0, 0, 0]))) - self.assertTrue(np.array_equal(level_to_ordinal_encoding(2), np.array([1, 1, 1, 0, 0]))) - self.assertTrue(np.array_equal(level_to_ordinal_encoding(3), np.array([1, 1, 1, 1, 0]))) - self.assertTrue(np.array_equal(level_to_ordinal_encoding(4), np.array([1, 1, 1, 1, 1]))) + self.assertTrue( + np.array_equal( + rainfall.level_to_ordinal_encoding(0), np.array([1, 0, 0, 0, 0]) + ) + ) + self.assertTrue( + np.array_equal( + rainfall.level_to_ordinal_encoding(1), np.array([1, 1, 0, 0, 0]) + ) + ) + self.assertTrue( + np.array_equal( + rainfall.level_to_ordinal_encoding(2), np.array([1, 1, 1, 0, 0]) + ) + ) + self.assertTrue( + np.array_equal( + rainfall.level_to_ordinal_encoding(3), np.array([1, 1, 1, 1, 0]) + ) + ) + self.assertTrue( + np.array_equal( + rainfall.level_to_ordinal_encoding(4), np.array([1, 1, 1, 1, 1]) + ) + ) def test_binary_encoding_to_level(self): one_hot_array = np.array([[1, 0], [0, 1], [0, 1]]) expected_levels = [0, 1, 1] - self.assertEqual(binary_encoding_to_level(one_hot_array), expected_levels) + self.assertEqual( + rainfall.binary_encoding_to_level(one_hot_array), expected_levels + ) def test_ordinal_encoding_to_level(self): - pred = np.array([[0.9, 0.1, 0.1, 0.1], [0.9, 0.9, 0.1, 0.1], [0.9, 0.9, 0.9, 0.1]]) + pred = np.array( + [[0.9, 0.1, 0.1, 0.1], [0.9, 0.9, 0.1, 0.1], [0.9, 0.9, 0.9, 0.1]] + ) expected_levels = np.array([0, 1, 2]) - self.assertTrue(np.array_equal(ordinal_encoding_to_level(pred), expected_levels)) + self.assertTrue( + np.array_equal(rainfall.ordinal_encoding_to_level(pred), expected_levels) + ) def test_value_to_level(self): - y_value = np.array([0., 0.2, 0.4, 1., 1.2, 20.2, 42.2, 54.8, 60.8]) + y_value = np.array([0.0, 0.2, 0.4, 1.0, 1.2, 20.2, 42.2, 54.8, 60.8]) expected_levels = np.array([0, 1, 1, 1, 1, 2, 3, 4, 4]) - self.assertTrue(np.array_equal(value_to_level(y_value), expected_levels)) + self.assertTrue( + np.array_equal(rainfall.value_to_level(y_value), expected_levels) + ) def test_value_to_ordinal_encoding(self): - y_values = np.array([0., 0.2, 0.4, 1., 1.2, 20.2, 42.2, 54.8, 60.8]) - expected_encoding = np.array([ - [1, 0, 0, 0, 0], - - [1, 1, 0, 0, 0], - [1, 1, 0, 0, 0], - [1, 1, 0, 0, 0], - [1, 1, 0, 0, 0], - - [1, 1, 1, 0, 0], - - [1, 1, 1, 1, 0], - - [1, 1, 1, 1, 1], - [1, 1, 1, 1, 1] - ]) + y_values = np.array([0.0, 0.2, 0.4, 1.0, 1.2, 20.2, 42.2, 54.8, 60.8]) + expected_encoding = np.array( + [ + [1, 0, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 0, 0, 0], + [1, 1, 1, 0, 0], + [1, 1, 1, 1, 0], + [1, 1, 1, 1, 1], + [1, 1, 1, 1, 1], + ] + ) # print("*-*") # print(value_to_ordinal_encoding(y_values)) # print(expected_encoding) # print("*-*") - self.assertTrue(np.array_equal(value_to_ordinal_encoding(y_values), expected_encoding)) + self.assertTrue( + np.array_equal( + rainfall.value_to_ordinal_encoding(y_values), expected_encoding + ) + ) -if __name__ == '__main__': +if __name__ == "__main__": unittest.main() diff --git a/websirene_animation.html b/websirene_animation.html new file mode 100644 index 00000000..39b9e15b --- /dev/null +++ b/websirene_animation.html @@ -0,0 +1,1531 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
Níveis de precipitação (mm/h)
Chuva fraca / sem chuva (0–5 mm/h)
Chuva moderada (5–25 mm/h)
Chuva forte (25–50 mm/h)
Chuva extrema (50–∞ mm/h)
+ +
+ + + + \ No newline at end of file