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Gap filling with NaN values added to Level 2 #326

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Gap filling with NaN values added to Level 2 #326

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32 changes: 31 additions & 1 deletion src/pypromice/process/L1toL2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -205,9 +205,10 @@ def toL2(
ds['precip_l_cor'], ds['precip_l_rate']= correctPrecip(ds['precip_l'],
ds['wspd_l'])

get_directional_wind_speed(ds) # Get directional wind speed
get_directional_wind_speed(ds) # Get directional wind speed

ds = clip_values(ds, vars_df)
ds = fill_gaps(ds)
return ds

def get_directional_wind_speed(ds: xr.Dataset) -> xr.Dataset:
Expand Down Expand Up @@ -782,6 +783,35 @@ def calcCorrectionFactor(Declination_rad, phi_sensor_rad, theta_sensor_rad,

return CorFac_all

def fill_gaps(ds):
'''Fill data gaps with nan values

Parameters
----------
ds : xarray.Dataset
Data set to gap fill

Returns
-------
ds_filled : xarray.Dataset
Gap-filled dataset
'''
# Determine time range of dataset
min_date = ds.to_dataframe().index.min()
max_date = ds.to_dataframe().index.max()

# Determine common time interval
time_diffs = np.diff(ds['time'].values)
common_diff = pd.Timedelta(pd.Series(time_diffs).mode()[0])

# Determine gap filled index
full_time_range = pd.date_range(start=min_date,
end=max_date,
freq=common_diff)

# Apply gap-fille index to dataset
ds_filled = ds.reindex({'time': full_time_range}, fill_value=np.nan)
return ds_filled

def _checkSunPos(ds, OKalbedos, sundown, sunonlowerdome, TOA_crit_nopass):
'''Check sun position
Expand Down