The below code raises "ValueError: Can only compare identically-labeled Series objects" because compute_actual_counts() only returns years for which there are no nans, so will have different length than expected counts if there is an all-nan year.
import kenmerkendewaarden as kw
import numpy as np
import hatyan
file_dia_ts = r"c:\DATA\kenmerkendewaarden\tests\testdata\HOEK_KW.dia"
df_meas = hatyan.read_dia(file_dia_ts)
df_meas_2010_2014 = df_meas.loc["2010":"2014"]
# create dataset with a gap
df_meas_withgap = df_meas_2010_2014.copy() # copy to prevent altering the original dataset
df_meas_withgap.loc["2012", "values"] = np.nan
df_meas_withgap.loc["2012", "qualitycode"] = 99
slotgemiddelden_dict_nogap = kw.calc_wltidalindicators(df_meas_2010_2014, min_coverage=1)
slotgemiddelden_dict_withgap = kw.calc_wltidalindicators(df_meas_withgap, min_coverage=1)
Todo:
[x] fix this issue, also goes for months (with "2012-01")
The below code raises
"ValueError: Can only compare identically-labeled Series objects"becausecompute_actual_counts()only returns years for which there are no nans, so will have different length than expected counts if there is an all-nan year.Todo:
"2012-01")