if directional wspd are missing, then they are recalculated

This is necessary because historical data doesn't have directional wind speeds.

src/pypromice/process/resample.py

@@ -8,6 +8,7 @@
 import logging
 import numpy as np
 import xarray as xr
+from pypromice.process.L1toL2 import calcDirWindSpeeds
 logger = logging.getLogger(__name__)
 
 def resample_dataset(ds_h, t):
@@ -35,12 +36,15 @@ def resample_dataset(ds_h, t):
 
     # recalculating wind direction from averaged directional wind speeds
     for var in ['wdir_u','wdir_l']:
+        boom = var.split('_')[1]
         if var in df_d.columns:
-            if ('wspd_x_'+var.split('_')[1] in df_d.columns) & ('wspd_y_'+var.split('_')[1] in df_d.columns):
-                df_d[var] = _calcWindDir(df_d['wspd_x_'+var.split('_')[1]],
-                                   df_d['wspd_y_'+var.split('_')[1]])
+            if ('wspd_x_'+boom in df_d.columns) & ('wspd_y_'+boom in df_d.columns):
+                df_d[var] = _calcWindDir(df_d['wspd_x_'+boom], df_d['wspd_y_'+boom])
             else:
-                logger.info(var+' in dataframe but not wspd_x_'+var.split('_')[1]+' nor wspd_y_'+var.split('_')[1])
+                logger.info(var+' in dataframe but not wspd_x_'+boom+' nor wspd_y_'+boom+', recalculating them')
+                ds_h['wspd_x_'+boom], ds_h['wspd_y_'+boom] = calcDirWindSpeeds(ds_h['wspd_'+boom], ds_h['wdir_'+boom])
+                df_d[['wspd_x_'+boom, 'wspd_y_'+boom]] = ds_h[['wspd_x_'+boom, 'wspd_y_'+boom]].to_dataframe().resample(t).mean()
+                df_d[var] = _calcWindDir(df_d['wspd_x_'+boom], df_d['wspd_y_'+boom])
 
     # recalculating relative humidity from average vapour pressure and average
     # saturation vapor pressure