Added option to plot specific layer of gridded averages. Adhoc fix to trap nans in some files. (d2dfcc5c) · Commits · CAMS / CSO

py/cso_catalogue.py

+59 −18

Original line number	Diff line number	Diff line
		@@ -9,6 +9,12 @@
		# Support steps over year when plotting series of gridded observations.
		# Define full output filename in settings instead of path only.
		#
		# 2022-02, Arjo Segers, Met-Norway
		# Added option to specify which layer of gridded fields should be plotted.
		#
		# 2022-10, Arjo Segers, Met-Norway
		# Adhoc fix to trap nans in lon/lat arrays in S5p/glyoxal data.
		#

		########################################################################
		###
		@@ -446,6 +452,13 @@ class CSO_Catalogue( CSO_CatalogueBase ) :
		# extract corner grids and values:
		xx,yy,values,attrs = orb.GetTrack( vname )

		# adhoc, some chocho files have nans in lon/lat bound arrays,
		# these are still present because the scan line has some valid values ...
		if numpy.any( numpy.isnan(xx) ) :
		logging.warning( ' found nans in track corners, skip ...' )
		break # leave loop over variables
		#endif

		# squeeze
		if len(values.shape) > 2 :
		# remove lenth-1 dim "retr" from dims: (scan,pixel,retr)
		@@ -790,6 +803,13 @@ class CSO_SimCatalogue( CSO_CatalogueBase ) :
		raise Exception
		#endif

		# adhoc, some chocho files have nans in lon/lat bound arrays,
		# these are still present because the scan line has some valid values ...
		if numpy.any( numpy.isnan(xx) ) :
		logging.warning( ' found nans in track corners, skip ...' )
		break # leave loop over variables
		#endif

		# squeeze
		shp = values.shape
		if len(shp) != 2 :
		@@ -895,6 +915,10 @@ class CSO_GriddedCatalogue( CSO_CatalogueBase ) :
		<rcbase>.var.yr.source : yr
		<rcbase>.var.yr.source : ys

		Optionally specify a source layer for profiles, default is first layer::

		<rcbase>.var.yr.source_layer : 0

		Optionally specify target units that are different from the input::

		! convert units:
		@@ -1060,6 +1084,8 @@ class CSO_GriddedCatalogue( CSO_CatalogueBase ) :
		vkey = 'var.%s' % varname
		# originating variable:
		vsource = self.GetSetting( vkey+'.source' )
		# optional layer selection:
		vsource_layer = self.GetSetting( vkey+'.source_layer', totype='int', default=0 )
		# target units:
		vunits = self.GetSetting( vkey+'.units' , default='None' )
		# plot type:
		@@ -1090,6 +1116,21 @@ class CSO_GriddedCatalogue( CSO_CatalogueBase ) :

		# data:
		values = vda.values.squeeze()
		# select layer if needed ..
		if len(values.shape) == 3 :
		# check ..
		if (vsource_layer < 0) or (values.shape[2] < vsource_layer+1) :
		logging.error( 'could not extract source layer %i from values with shape (%s)' % (vsource_layer,str(vvalues.shape)) )
		raise Exception
		#endif
		# extract:
		values = values[:,:,vsource_layer]
		#
		elif len(values.shape) != 2 :
		logging.error( 'could not plot map of array with shape (%s)' % (str(values.shape)) )
		raise Exception
		#endif

		# adhoc fix, convert to masked array ...
		values = numpy.ma.array( data=values, mask=numpy.isnan(values) )