def regionDailyTimeSeries(C, region): """" Returns a summed time series the length of axis 0 for C subet by the passed region name """ minLat, maxLat, minLon, maxLon, resolution = cnm.getRegionBounds(region) C_PNW, ynew, xnew = cnm.mask2dims(C, longitude, latitude, 0, minLon, maxLon, minLat, maxLat) C_PNW_daily = np.sum(C_PNW, axis=(1,2)) return C_PNW_daily
ValueError('Time dimensions of data array and time array do not match!')
if np.unique(np.diff(tBase)) != 24:
ValueError('Some time jump not equal to 24 hours present!')
print 'Final merged var size: ' + str(varBase.shape)
print 'Final merged time array: ' + str(len(tBase))
#######################################################################
# Handle making the spatial subset
#######################################################################
if region != '_':
# Get the chosen region bounds
minLat, maxLat, minLon, maxLon, resolution = cnm.getRegionBounds(region)
# Subset the data based on the bounds of this region.
varBase, latitude, longitude = cnm.mask2dims(varBase, longitude[:], latitude[:], 0,\
xmin=minLon, xmax=maxLon,\
ymin=minLat, ymax=maxLat)
print 'Data subset to region ' + region
#######################################################################
# Write the merged file
#######################################################################
if ncVARType == 'era_interim':
outputFile = outDir + ncVAR + region + \