Fix netcdf creation of dewpoint when it isn't in the input files

aosstower/level_b1/calc.py

@@ -3,9 +3,11 @@ import math
 import numpy as np
 
 try:
+    import pandas as pd
     from pandas import Series
 except ImportError:
     # expected to use for isinstance
+    pd = None
     Series = np.ndarray
 
 NaN = float('nan')
@@ -33,7 +35,9 @@ def dewpoint(tempC, relhum):
     dp = 1.0 / (1.0 / (273.15 + tempC) - gasconst * np.log((0.0 + relhum) / 100) /
                 (latheat - tempC * 2397.5))
 
-    return min(dp - 273.15, tempC)
+    if pd is not None and isinstance(dp, pd.Series):
+        return pd.concat([dp - 273.15, tempC], axis=1).min(axis=1)
+    return np.min(dp - 273.15, tempC)
 
 
 def relhum(airTempK, dewpointTempK):

aosstower/level_b1/nc.py

@@ -402,6 +402,11 @@ def create_giant_netcdf(input_files, output_fn, zlib, chunk_size,
 
     # Add wind direction components so we can average wind direction properly
     frame['wind_east'], frame['wind_north'], _ = calc.wind_vector_components(frame['wind_speed'], frame['wind_dir'])
+
+    if 'air_temp' in frame and 'rh' in frame and 'dewpoint' in database:
+        LOG.info("'dewpoint' is missing from the input file, will calculate it from air temp and relative humidity")
+        frame['dewpoint'] = calc.dewpoint(frame['air_temp'], frame['rh'])
+
     # round up each 1 minute group so data at time T is the average of data
     # from T - 1 (exclusive) to T (inclusive).
     new_frame = frame.resample('5S', closed='right', loffset='5S').mean()