py_forecasyting_3.py

# convert temperature
df['temp_air'] = kelvin_to_celsius(df['temp_air'])
# covert wind component to wind speed
df['wind_speed'] = uv_to_speed(df)

# resampling to 5min temporal resolution
df_interpol = df.resample('5min').interpolate(method='time')
# cloud types: total_clouds, low_clouds,mid_clouds,high_clouds,boundary_clouds,convect_clouds
resampled_irrads = cloud_cover_to_irradiance(df_interpol, clouds_type='total_clouds', how='clearsky_scaling')

# calculate irradiance estimates from cloud cover
# uses a cloud_cover to ghi model or
# uses a cloud_cover to transmittance to irradiance model
# irrads = cloud_cover_to_irradiance(df, how='clearsky_scaling')

df = df_interpol.join(resampled_irrads, how='outer')