"""
Finnish daily snow depth (FMI)
==============================

The Finnish Meteorological Institute (FMI) publishes daily snow depth from its
automatic weather stations and its manual precipitation and climate stations
through its open-data WFS (CC BY 4.0), from 1895 at Helsinki Kaisaniemi and
from 1959 at most stations. It publishes no SWE; Finnish snow-course SWE is Syke's.

``FMIClient`` reads the service, with no account. It lists open and closed
stations; some closed ones are unknown to the observation service and are
skipped when data is asked for. Station codes in ``esd.stations`` are
``FMI-<fmisid>``.

The figures show the stations by network and status, and two winters of daily
snow depth at four stations from south to north.
"""

import geopandas as gpd
import pandas as pd

import easysnowdata as esd
from easysnowdata.stations.clients import FMIClient

client = FMIClient()

# %%
# Every station of the networks that report snow depth. ``network_code`` is
# the station's main network: AWS (automatic weather station), AIRP
# (airport), CLIM (climate), WS (manned weather station) or PRCP
# (precipitation).
stations = client.get_all_stations()
stations_gdf = gpd.GeoDataFrame(
    pd.DataFrame(stations).set_index("station_id"),
    geometry=gpd.points_from_xy(
        [s["longitude"] for s in stations], [s["latitude"] for s in stations]
    ),
    crs="EPSG:4326",
)
print(pd.crosstab(stations_gdf["network_code"], stations_gdf["status"]).to_string())

ax = esd.plotting.points(
    stations_gdf[stations_gdf["status"] == "Active"],
    column="network_code",
    legend_label="network",
    title="Active FMI snow-depth stations",
)

# %%
# Daily snow depth at Helsinki Kaisaniemi, Jyväskylä airport, Oulu airport
# and Sodankylä Tähtelä. At automatic stations a value is the 06:00 UTC
# reading of its day; ``-1`` (snow-free ground) arrives as 0 cm.
ids = ["100971", "137208", "101786", "101932"]
records = client.get_data(ids, begin_date="2022-10-01", end_date="2024-06-30")
depth_df = (
    pd.DataFrame(records)
    .assign(date=lambda df: pd.to_datetime(df["date"]))
    .pivot_table(index="date", columns="station_id", values="value")
)
depth_df.columns = [stations_gdf.loc[c, "name"] for c in depth_df.columns]
ax = depth_df.plot(figsize=(10, 4))
ax.set(ylabel="snow depth (cm)", title="Daily snow depth, FMI")