"""
Swiss long-term SWE (SLF)
=========================

The WSL Institute for Snow and Avalanche Research SLF has measured SWE by hand
every two weeks at 11 sites between 1,200 and 2,540 m, some since 1936 (the
GCOS SWE series). It also publishes daily snow depth from its manual study
plots and its automated IMIS stations. Switzerland has no open **daily** SWE.

``SLFClient(dataset=...)`` reads one dataset at a time: ``"gcos"`` (default,
SWE every ~15 days), ``"new_snow"`` (2016–2022 new-snow SWE study),
``"study_plot"`` and ``"imis"`` (daily snow depth). Each uses its own station
ids. Data are free with attribution to SLF (CC BY 4.0; GCOS: ODbL). It is not
part of ``esd.stations.inventory()`` or ``load()``.

The figures show the GCOS SWE series at Weissfluhjoch since 1936, and one
winter of IMIS daily snow depth next to the biweekly SWE.
"""

import matplotlib.pyplot as plt
import pandas as pd

from easysnowdata.stations.clients import SLFClient

gcos = SLFClient(dataset="gcos")

# %%
# The eleven GCOS sites.
sites_df = pd.DataFrame(gcos.get_all_stations()).set_index("station_id")
print(sites_df[["name", "elevation_m", "period_of_record"]].to_string())

# %%
# Weissfluhjoch above Davos (2,540 m): every manual SWE measurement since
# 1936. Records are ``"periodic"``.
records = gcos.get_data("5WJ", variables="swe")
wfj_df = pd.DataFrame(records).assign(date=lambda df: pd.to_datetime(df["date"]))
print(wfj_df["interval"].unique(), len(wfj_df), "measurements")
fig, ax = plt.subplots(figsize=(10, 4))
ax.plot(wfj_df["date"], wfj_df["value"], ".")
ax.set(ylabel="SWE (cm)", title="GCOS SWE at Weissfluhjoch, 1936 onward")

# %%
# Peak SWE by water year shows the long-term record that only the manual
# series can give.
wfj_df["water_year"] = wfj_df["date"].dt.year + (wfj_df["date"].dt.month >= 10)
peak = wfj_df.groupby("water_year")["value"].max()
fig, ax = plt.subplots(figsize=(10, 3.5))
ax.plot(peak.index, peak.values, marker="o")
ax.set(
    xlabel="water year",
    ylabel="peak SWE (cm)",
    title="Annual peak SWE at Weissfluhjoch",
)

# %%
# The automated IMIS station at the same site (``WFJ2``) gives daily snow
# depth for the same winter as the biweekly SWE.
imis = SLFClient(dataset="imis")
depth_df = pd.DataFrame(
    imis.get_data(
        "WFJ2",
        variables="snwd",
        interval="daily",
        begin_date="2023-10-01",
        end_date="2024-07-31",
    )
).assign(date=lambda df: pd.to_datetime(df["date"]))
winter_df = wfj_df[(wfj_df["date"] >= "2023-10-01") & (wfj_df["date"] <= "2024-07-31")]
fig, ax = plt.subplots(figsize=(9, 4))
ax.plot(depth_df["date"], depth_df["value"], label="IMIS snow depth (daily)")
ax.plot(winter_df["date"], winter_df["value"], "o", label="GCOS SWE (biweekly)")
ax.set(ylabel="cm", title="Weissfluhjoch, winter 2023–24")
ax.legend()