Change NREL to NLR (#492)

* initial pyproject.toml implementation

* changelog

* update URLs

* change NREL to NLR

* linting

* changelog

* update PVDAQ citation in notebooks

Author: martin-springer

CITATION.cff

@@ -43,4 +43,4 @@ authors:
   orcid: "https://orcid.org/0000-0002-9867-8930"
 title: "RdTools"
 doi: 10.5281/zenodo.1210316
-url: "https://github.com/NREL/rdtools"
+url: "https://github.com/NatLabRockies/rdtools"

CODE_OF_CONDUCT.md

@@ -55,7 +55,7 @@ further defined and clarified by project maintainers.
 ## Enforcement
 
 Instances of abusive, harassing, or otherwise unacceptable behavior may be
-reported by contacting the project team at RdTools@nrel.gov. All
+reported by contacting the project team at RdTools@nlr.gov. All
 complaints will be reviewed and investigated and will result in a response that
 is deemed necessary and appropriate to the circumstances. The project team is
 obligated to maintain confidentiality with regard to the reporter of an incident.

README.md

@@ -1,13 +1,13 @@
 <img src="./docs/sphinx/source/_images/logo_horizontal_highres.png" width="500" alt="RdTools logo"/>
 
 Master branch:
-[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NREL/rdtools/actions?query=branch%3Amaster)
+[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=master)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Amaster)
 
 Development branch:
-[![Build Status](https://github.com/NREL/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NREL/rdtools/actions?query=branch%3Adevelopment)
+[![Build Status](https://github.com/NatLabRockies/rdtools/workflows/pytest/badge.svg?branch=development)](https://github.com/NatLabRockies/rdtools/actions?query=branch%3Adevelopment)
 
 Code coverage:
-[![codecov](https://codecov.io/gh/NREL/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NREL/rdtools)
+[![codecov](https://codecov.io/gh/NatLabRockies/rdtools/graph/badge.svg?token=K2HDjFkBws)](https://codecov.io/gh/NatLabRockies/rdtools)
 
 RdTools is an open-source library to support reproducible technical analysis of
 time series data from photovoltaic energy systems. The library aims to provide
@@ -38,7 +38,7 @@ and the specific DOI coresponding to that version from [Zenodo](https://doi.org/
    Martin Springer, Jiyang Yan, Kirsten Perry, Sandra Villamar, Will Vining,
    Gregory Kimball, Daniel Ruth, Noah Moyer, Quyen Nguyen, Dirk Jordan,
    Matthew Muller, and Chris Deline, RdTools, version {insert version}, Computer Software,
-   https://github.com/NREL/rdtools. DOI:{insert DOI}
+   https://github.com/NatLabRockies/rdtools. DOI:{insert DOI}
 
 The underlying workflow of RdTools has been published in several places.
 If you use RdTools in a published work, you may also wish to cite the following as
@@ -76,5 +76,5 @@ Other useful references which may also be consulted for degradation rate methodo
 
 ## Further Instructions and Updates
 
-Check out the [wiki](https://github.com/NREL/rdtools/wiki) for additional usage documentation, and for information on development goals and framework.
+Check out the [wiki](https://github.com/NatLabRockies/rdtools/wiki) for additional usage documentation, and for information on development goals and framework.
 

docs/Multi-year_on_year_example.ipynb

@@ -18,7 +18,9 @@
     "\n",
     "For a consistent experience, we recommend installing the packages and versions documented in `docs/notebook_requirements.txt`. This can be achieved in your environment by running `pip install -r docs/notebook_requirements.txt` from the base directory. (RdTools must also be separately installed.) This notebook was tested in python 3.12.\n",
     "\n",
-    "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n"
+    "This notebook works with data from system 4 of the PVDAQ dataset [1]. This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n",
+    "\n",
+    "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)"
    ]
   },
   {
@@ -247,7 +249,7 @@
    ],
    "source": [
     "# Provide additional timestamp information for the YoY slopes including the left and right timestamps that were used to calculate the slope.\n",
-    "# The index is set to  equal dt_center because we passed label='center' in the yoy_kwargs. \n",
+    "# The index is set to  equal dt_center because we passed label='center' in the yoy_kwargs.\n",
     "print(calc_info['YoY_times'].head().to_markdown())"
    ]
   },

docs/TrendAnalysis_example.ipynb

@@ -14,9 +14,11 @@
     "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.**  \n",
     "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API to year on year (YOY) degradation and recovery (SRR) soiling calculations.\n",
     "\n",
-    "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system.  Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example.  This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n",
+    "This notebook works with data from system 4 of the PVDAQ dataset [1].  Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example.  This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n",
     "\n",
-    "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis."
+    "An older version of this notebook (RdTools<3) included emphasis on the clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we have de-emphasized the clear sky workflow in this version of the notebook. We also include a new notebook that illustrates the use of satellite irradiance data, which can serve as a check on the sensor-based analysis.\n",
+    "\n",
+    "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)"
    ]
   },
   {
@@ -61547,7 +61549,7 @@
             },
             "colorscale": [
              [
-              0.0,
+              0,
               "#0d0887"
              ],
              [
@@ -61583,7 +61585,7 @@
               "#fdca26"
              ],
              [
-              1.0,
+              1,
               "#f0f921"
              ]
             ],
@@ -61607,7 +61609,7 @@
             },
             "colorscale": [
              [
-              0.0,
+              0,
               "#0d0887"
              ],
              [
@@ -61643,7 +61645,7 @@
               "#fdca26"
              ],
              [
-              1.0,
+              1,
               "#f0f921"
              ]
             ],
@@ -61658,7 +61660,7 @@
             },
             "colorscale": [
              [
-              0.0,
+              0,
               "#0d0887"
              ],
              [
@@ -61694,7 +61696,7 @@
               "#fdca26"
              ],
              [
-              1.0,
+              1,
               "#f0f921"
              ]
             ],
@@ -61721,7 +61723,7 @@
             },
             "colorscale": [
              [
-              0.0,
+              0,
               "#0d0887"
              ],
              [
@@ -61757,7 +61759,7 @@
               "#fdca26"
              ],
              [
-              1.0,
+              1,
               "#f0f921"
              ]
             ],
@@ -61772,7 +61774,7 @@
             },
             "colorscale": [
              [
-              0.0,
+              0,
               "#0d0887"
              ],
              [
@@ -61808,7 +61810,7 @@
               "#fdca26"
              ],
              [
-              1.0,
+              1,
               "#f0f921"
              ]
             ],
@@ -61953,7 +61955,7 @@
             },
             "colorscale": [
              [
-              0.0,
+              0,
               "#0d0887"
              ],
              [
@@ -61989,7 +61991,7 @@
               "#fdca26"
              ],
              [
-              1.0,
+              1,
               "#f0f921"
              ]
             ],
@@ -62080,7 +62082,7 @@
            ],
            "sequential": [
             [
-             0.0,
+             0,
              "#0d0887"
             ],
             [
@@ -62116,13 +62118,13 @@
              "#fdca26"
             ],
             [
-             1.0,
+             1,
              "#f0f921"
             ]
            ],
            "sequentialminus": [
             [
-             0.0,
+             0,
              "#0d0887"
             ],
             [
@@ -62158,7 +62160,7 @@
              "#fdca26"
             ],
             [
-             1.0,
+             1,
              "#f0f921"
             ]
            ]
@@ -62290,8 +62292,8 @@
         "xaxis": {
          "anchor": "y",
          "domain": [
-          0.0,
-          1.0
+          0,
+          1
          ],
          "title": {
           "text": "datetime"
@@ -62300,8 +62302,8 @@
         "yaxis": {
          "anchor": "x",
          "domain": [
-          0.0,
-          1.0
+          0,
+          1
          ],
          "title": {
           "text": "energy_Wh"

docs/TrendAnalysis_example_NSRDB.ipynb

@@ -14,9 +14,11 @@
     "1. Import and preliminary calculations: In this step data is important and augmented to enable analysis with RdTools. **No RdTools functions are used in this step. It will vary depending on the particulars of your dataset. Be sure to understand the inputs RdTools requires and make appropriate adjustments.**  \n",
     "2. Analysis with RdTools: This notebook illustrates the use of the TrendAnalysis API for year on year (YOY) degradation calculations.\n",
     "\n",
-    "This notebook works with data from the NREL PVDAQ `[4] NREL x-Si #1` system.  Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example.  This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n",
+    "This notebook works with data from system 4 of the PVDAQ dataset [1].  Note that because this system does not experience significant soiling, the dataset contains a synthesized soiling signal for use in the soiling section of the example.  This notebook automatically downloads and locally caches the dataset used in this example. The data can also be found on the DuraMAT Datahub (https://datahub.duramat.org/dataset/pvdaq-time-series-with-soiling-signal).\n",
     "\n",
-    "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift."
+    "In prior versions of RdTools (RdTools<3) we emphasized a clear sky workflow which uses clear sky modeled irradiance rather than measured (sensor) irradiance for analysis. The clear sky analysis served to double check the sensor based result for things like sensor drift, but there was high uncertainty with this approach because aerosal optical depth (AOD), an input to the clear sky irradiance model, can change from year to year. Therefore we now recommend using satellite irradiance data to check that the results with ground measured irradiance are sensible. This can help catch problems with sensor drift.\n",
+    "\n",
+    "[1] Deline, C., Perry, K., Deceglie, M., Muller, M., Sekulic, W., and Jordan, D. \"Photovoltaic Data Acquisition (PVDAQ) Public Datasets,\" Open Energy Data Initiative (OEDI), NREL, 2021. DOI: [10.25984/1846021](https://doi.org/10.25984/1846021)"
    ]
   },
   {