wetterdienst_example.py

# The MIT License

# Copyright (c) 2017 - 2025 Tammo Ippen, tammo.ippen@posteo.de

# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
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# The above copyright notice and this permission notice shall be included in
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# THE SOFTWARE.

# Get data for your own: https://github.com/earthobservations/wetterdienst
# call
# wetterdienst values --provider=dwd --kind=observation \
#                     --parameter=kl --resolution=daily \
#                     --station 1048,4411 \
#                     --date=1970-01-01/2021-01-01 > wetter-data.json

import gzip
import json
import os
from collections import defaultdict
from datetime import datetime

import plotille as plt


def regression(x, y):
    # formula from here:
    # https://devarea.com/linear-regression-with-numpy/
    n = len(x)
    assert n > 0
    assert n == len(y)

    sum_x = sum(x)
    sum_xx = sum(x_ * x_ for x_ in x)
    sum_y = sum(y)
    sum_xy = sum(x_ * y_ for x_, y_ in zip(x, y, strict=True))

    m = (n * sum_xy - sum_x * sum_y) / (n * sum_xx - sum_x * sum_x)
    b = (sum_y - m * sum_x) / n

    return m, b


def main():
    current_dir = os.path.dirname(os.path.abspath(__file__))

    with gzip.open(current_dir + os.sep + "wetter-data.json.gz", "r") as f:
        data = json.load(f)

    # wetterdienst stations --station 1048,4411 \
    #                       --provider dwd \
    #                       --kind observation \
    #                       --parameter kl \
    #                       --resolution daily
    stations = [
        {
            "station_id": "01048",
            "from_date": "1934-01-01T00:00:00.000Z",
            "to_date": "2021-07-04T00:00:00.000Z",
            "height": 228.0,
            "latitude": 51.1278,
            "longitude": 13.7543,
            "name": "Dresden-Klotzsche",
            "state": "Sachsen",
        },
        {
            "station_id": "04411",
            "from_date": "1979-12-01T00:00:00.000Z",
            "to_date": "2021-07-04T00:00:00.000Z",
            "height": 155.0,
            "latitude": 49.9195,
            "longitude": 8.9671,
            "name": "Schaafheim-Schlierbach",
            "state": "Hessen",
        },
    ]
    station_by_id = {st["station_id"]: st for st in stations}

    Xs = defaultdict(list)
    Ys = defaultdict(list)
    for d in data:
        if d["temperature_air_200"] is not None:
            dt = datetime.strptime(d["date"], "%Y-%m-%dT%H:%M:%S.%fZ").date()
            name = station_by_id[d["station_id"]]["name"]
            if dt.month == 1 and dt.day == 1:
                Xs[name] += [dt.year]
                Ys[name] += [d["temperature_air_200"] - 273.15]

    fig = plt.Figure()
    fig.width = 120
    fig.height = 30
    fig.set_x_limits(1970, 2021)
    fig.set_y_limits(-18, 12)
    fig.y_label = "Celsius"
    fig.x_label = "Year"

    fig.x_ticks_fkt = lambda min_, max_: f"{int(min_):d}"
    fig.y_ticks_fkt = lambda min_, max_: f"{min_:.3f}"

    markers = ["x", "o"]
    for idx, station in enumerate(Xs.keys()):
        fig.plot(Xs[station], Ys[station], label=station, marker=markers[idx])
        m, b = regression(Xs[station], Ys[station])
        start = m * 1970 + b
        end = m * 2021 + b
        fig.plot([1970, 2021], [start, end], label=f"{station} - regression")

    print("\033[2J")  # clear screen
    print(" " * 50 + "Temperature of two stations in Germany at 1. Januar")
    print(fig.show(legend=True))


if __name__ == "__main__":
    main()