Merge pull request #284 from NOAA-CSL/hotfix/satplots_and_aircraft

Satellite plotting fix, OMPS pairing fix, and some additional time interval looping

melodies_monet/driver.py

@@ -271,18 +271,21 @@ def open_sat_obs(self, time_interval=None, control_dict=None):
                 else: flst = self.file
 
                 self.obj = mio.sat._omps_nadir_mm.read_OMPS_nm(flst)
-                
+
                 # couple of changes to move to reader
                 self.obj = self.obj.swap_dims({'x':'time'}) # indexing needs
                 self.obj = self.obj.sortby('time') # enforce time in order. 
                 # restrict observation data to time_interval if using
                 # additional development to deal with files crossing intervals needed (eg situtations where orbit start at 23hrs, ends next day).
                 if time_interval is not None:
                     self.obj = self.obj.sel(time=slice(time_interval[0],time_interval[-1]))
-                    
+
             elif self.sat_type == 'mopitt_l3':
                 print('Reading MOPITT')
-                self.obj = mio.sat._mopitt_l3_mm.open_dataset(self.file, ['column','pressure_surf','apriori_col',
+                if time_interval is not None:
+                    flst = tsub.subset_mopitt_l3(self.file,time_interval)
+                else: flst = self.file
+                self.obj = mio.sat._mopitt_l3_mm.open_dataset(flst, ['column','pressure_surf','apriori_col',
                                                                           'apriori_surf','apriori_prof','ak_col'])
             elif self.sat_type == 'modis_l2':
                 # from monetio import modis_l2
@@ -599,12 +602,22 @@ def open_model_files(self, time_interval=None, control_dict=None):
                 #self.obj.monet.scrip = self.obj_scrip      
             elif "camx" in self.model.lower():
                 self.mod_kwargs.update({"var_list": list_input_var})
+                self.mod_kwargs.update({"surf_only": control_dict['model'][self.label].get('surf_only', False)})
+                self.mod_kwargs.update({"fname_met_3D": control_dict['model'][self.label].get('files_vert', None)})
+                self.mod_kwargs.update({"fname_met_2D": control_dict['model'][self.label].get('files_met_surf', None)})
                 self.obj = mio.models._camx_mm.open_mfdataset(self.files, **self.mod_kwargs)
             elif 'raqms' in self.model.lower():
-                if len(self.files) > 1:
-                    self.obj = mio.raqms.open_mfdataset(self.files,**self.mod_kwargs)
+                if time_interval is not None:
+                    # fill filelist with subset
+                    print('subsetting model files to interval')
+                    file_list = tsub.subset_model_filelist(self.files,'%m_%d_%Y_%HZ','6H',time_interval)
+                else:
+                    file_list = self.files
+                if len(file_list) > 1:
+                    self.obj = mio.models.raqms.open_mfdataset(file_list,**self.mod_kwargs)
                 else:
-                    self.obj = mio.raqms.open_dataset(self.files,**self.mod_kwargs)
+                    self.obj = mio.models.raqms.open_dataset(file_list)
+
             else:
                 print('**** Reading Unspecified model output. Take Caution...')
                 if len(self.files) > 1:
@@ -1779,7 +1792,7 @@ def plotting(self):
                             if filter_criteria and 'altitude' in filter_criteria:
                                 vmin_y2, vmax_y2 = filter_criteria['altitude']['value']
                             elif filter_criteria is None:
-                                #if 'altitude' in pairdf.columns: # pairdf is dataset object, don't have columns
+
                                 if 'altitude' in pairdf:
                                     vmin_y2 = pairdf['altitude'].min()
                                     vmax_y2 = pairdf['altitude'].max()

melodies_monet/plots/satplots.py

@@ -524,7 +524,7 @@ def make_spatial_overlay(df, vmodel, column_o=None, label_o=None, column_m=None,
     cax.tick_params(labelsize=text_kwargs['fontsize']*0.8,length=10.0,width=2.0,grid_linewidth=2.0)    
 
     #plt.tight_layout(pad=0)
-    savefig(outname + '.png',loc=4, height=100, decorate=True, bbox_inches='tight', dpi=150)
+    savefig(outname + '.png',loc=4, logo_height=100, decorate=True, bbox_inches='tight', dpi=150)
     return ax
 
 def calculate_boxplot(df, df_reg=None,column=None, label=None, plot_dict=None, comb_bx = None, label_bx = None):
@@ -671,7 +671,7 @@ def make_boxplot(comb_bx, label_bx, ylabel = None, vmin = None, vmax = None, out
         ax.set_ylim(ymin = vmin, ymax = vmax)
 
     plt.tight_layout()
-    savefig(outname + '.png',loc=4, height=100, decorate=True, bbox_inches='tight', dpi=200)
+    savefig(outname + '.png',loc=4, logo_height=100, decorate=True, bbox_inches='tight', dpi=200)
 
 def make_spatial_bias_gridded(df, column_o=None, label_o=None, column_m=None, 
                       label_m=None, ylabel = None, vmin=None,
@@ -777,5 +777,5 @@ def make_spatial_bias_gridded(df, column_o=None, label_o=None, column_m=None,
     cax.tick_params(labelsize=text_kwargs['fontsize']*0.8,length=10.0,width=2.0,grid_linewidth=2.0)    
 
     #plt.tight_layout(pad=0)
-    savefig(outname + '.png',loc=4, height=100, decorate=True, bbox_inches='tight', dpi=150)
+    savefig(outname + '.png',loc=4, logo_height=100, decorate=True, bbox_inches='tight', dpi=150)
     return ax    

melodies_monet/util/satellite_utilities.py

@@ -140,11 +140,10 @@ def omps_l3_daily_o3_pairing(model_data,obs_data,ozone_ppbv_varname):
     grid_adjust = xe.Regridder(model_data[['latitude','longitude']],obs_data[['latitude','longitude']],'bilinear')
     mod_col_obsgrid = grid_adjust(column)
     # Aggregate time-step to daily means
-    daily_mean = mod_col_obsgrid.groupby('time.date').mean(numeric_only=True).compute()
-
+    daily_mean = mod_col_obsgrid.resample(time='1D').mean()
     # change dimension name for date to time
-    daily_mean = daily_mean.rename({'date':'time'})
     daily_mean = daily_mean.rename(ozone_ppbv_varname)
+
     return xr.merge([daily_mean,obs_data])
 
 def space_and_time_pairing(model_data,obs_data,pair_variables):

melodies_monet/util/time_interval_subset.py

@@ -20,6 +20,7 @@ def subset_model_filelist(all_files,timeformat,timestep,timeinterval):
 
 def subset_OMPS_l2(file_path,timeinterval):
     '''Dependent on filenaming convention
+     OMPS-satelliteid_NMTO3-L2_version_startingtimestamp_orbitnumber_endingtimestamp.h5
     '''
     import pandas as pd
     from glob import glob
@@ -29,7 +30,30 @@ def subset_OMPS_l2(file_path,timeinterval):
     subset_interval = pd.date_range(start=timeinterval[0],end=timeinterval[-1],freq='D',inclusive='left')
 
     for i in subset_interval:
-        fst = fnmatch.filter(all_files,'*OMPS-NPP_NMTO3-L2_v*_{}*_o*'.format(i.strftime('%Ym%m%d')))
+        fst = fnmatch.filter(all_files,'*OMPS-*_NMTO3-L2_v*_{}*_o*'.format(i.strftime('%Ym%m%d')))
+        fst.sort()
+        for j in fst:
+            interval_files.append(j)
+    return interval_files
+
+def subset_mopitt_l3(file_path,timeinterval):
+    '''Dependent on filenaming conventions
+    MOP03J-YYYYMMDD-
+    MOP03JM-201909-
+    '''
+    import pandas as pd
+    from glob import glob
+    import fnmatch
+    all_files = glob(file_path)
+    interval_files = []
+    if 'MOP03JM-' in all_files[0]:
+        subset_interval = pd.date_range(start=timeinterval[0],end=timeinterval[-1],freq='M')
+        strfmt = '%Y%m'
+    else:
+        subset_interval = pd.date_range(start=timeinterval[0],end=timeinterval[-1],freq='D')
+        strfmt = '%Y%m%d'
+    for i in subset_interval:
+        fst = fnmatch.filter(all_files,'*MOP*-{}*'.format(i.strftime(strfmt)))
         fst.sort()
         for j in fst:
             interval_files.append(j)