Consider moving LAT testcase from hatyan to this repos

[veenstrajelmer]

• https://github.com/Deltares/hatyan/issues/221
• consider moving hatyan.calc_HWLWtidalrange() to kwk (incl testcase)
• there might be more kwk-only functions in hatyan, which would be not publicly exposed anymore since https://github.com/Deltares/hatyan/pull/232

An alternative (pragmatic) method to compute LAT is to retrieve a long astro timeseries from the DDL and to compute its minimum. A faster method would be to retrieve only the astro extremes, if they are all available. It is also not sure if all astro timeseries values are available for this entire period, which is why the nvalues column is added to the dataframe:

import ddlpy # available via pip install rws-ddlpy
import pandas as pd

# retrieve astro timeseries for >=19 years and derive minimum from it
start_date = "2000-01-01"
end_date = "2020-01-01"

locations = ddlpy.locations()

# station list from n:\Projects\11206500\11206799\C. Report - advise\3. Natuurmonitoring\2. Showcase Friesche Zeegat - Digitale Systeemrapportage\getijanalyse\TA_wadden_filtersurge.py
station_list = ['WIERMGDN','WESTTSLG','TEXNZE','TERSLNZE','SCHIERMNOG','NES','LAUWOG','HUIBGT','HOLWD','HARLGN','EEMSHVN','DENHDR','DELFZL']
station_list = ['DENHDR','WESTTSLG']

lat_list = []
nvalues_list = []
for current_station in station_list:

    bool_grootheid = locations['Grootheid.Code'].isin(['WATHTBRKD']) # measured waterlevels (not astro)
    bool_groepering = locations['Groepering.Code'].isin(['NVT']) # timeseries (not extremes)
    bool_hoedanigheid = locations['Hoedanigheid.Code'].isin(['NAP']) # vertical reference
    bool_station = locations.index.isin([current_station])
    locs_wathte = locations.loc[bool_grootheid & bool_groepering & bool_hoedanigheid & bool_station]

    # no support for multiple rows, so pass one at a time
    if len(locs_wathte) != 1:
        raise Exception(f"no or duplicate stations for wathte for {current_station}:\n{locs_wathte}")

    # get the measurements
    meas_wathte = ddlpy.measurements(locs_wathte.iloc[0], start_date=start_date, end_date=end_date)
    ts_astro = meas_wathte["Meetwaarde.Waarde_Numeriek"]
    lat_list.append(ts_astro.min())
    nvalues_list.append(len(ts_astro.dropna()))

lat_df = pd.DataFrame({"LAT":lat_list, "nvalues":nvalues_list}, index=station_list)
print(lat_df)