additional cleanup of stats_file name (Get_ObsFcstAna_stats.py, Plot_stats_maps.py, Plot_stats_timeseries.py)

Author: gmao-rreichle

GEOSldas_App/util/postproc/ObsFcstAna_stats/Get_ObsFcstAna_stats.py

@@ -72,11 +72,9 @@ def main():
     plot_maps       = False
     plot_timeseries = False
 
-    if plot_maps:
-        # Compute long-term temporal stats and plot maps
+    if plot_maps:            # Compute long-term temporal stats and plot maps
 
-        # Get output file name
-        stats_file  = out_path + 'tmp_stats_'+exp_list[0]['exptag']+ '_'+start_time.strftime('%Y%m%d')+'_'+ \
+        stats_file  = out_path + 'temporal_stats_'+exp_list[0]['exptag']+ '_'+start_time.strftime('%Y%m%d')+'_'+ \
             (end_time+timedelta(days=-1)).strftime('%Y%m%d')+'.nc4'
 
         # temporal_stats is a dictionary that contains all mean/variances fields for computing long-term O-F/O-A stats
@@ -88,9 +86,8 @@ def main():
         from Plot_stats_maps import plot_OmF_maps
         plot_OmF_maps(postproc, temporal_stats, fig_path=out_path )
 
+    if plot_timeseries:      # Compute spatially averaged stats and plot monthly time series of stats
 
-    if plot_timeseries:
-        # Compute spatially averaged stats and plot monthly time series of stats
         from Plot_stats_timeseries import Plot_monthly_OmF_bars
         Plot_monthly_OmF_bars(postproc, fig_path=out_path)
 

GEOSldas_App/util/postproc/ObsFcstAna_stats/Plot_stats_maps.py

@@ -184,13 +184,8 @@ def plot_OmF_maps(postproc_obj, stats, fig_path='./'):
     postproc = postproc_ObsFcstAna(exp_list, start_time, end_time, sum_path=sum_path)
 
     # Compute long-term temporal stats and plot maps
-    if len(exp_list) >1 :
-        stats_file  = out_path + 'tmp_stats_'+exp_list[0]['exptag']+'_obsfrom_'+ \
-                      exp_list[postproc.obs_from]['exptag']+'_'+start_time.strftime('%Y%m%d')+'_'+ \
-                      (end_time+timedelta(days=-1)).strftime('%Y%m%d')+'.nc4'
-    else:
-        stats_file  = out_path + 'tmp_stats_'+exp_list[0]['exptag']+'_'+ start_time.strftime('%Y%m%d')+'_'+ \
-                      (end_time+timedelta(days=-1)).strftime('%Y%m%d')+'.nc4'
+    stats_file  = out_path + 'temporal_stats_'+exp_list[0]['exptag']+'_'+ start_time.strftime('%Y%m%d')+'_'+ \
+        (end_time+timedelta(days=-1)).strftime('%Y%m%d')+'.nc4'
 
     # temporal_stats is a dictionary that contains all mean/variances fields for computing long-term O-F/O-A stats
     # each field has the dimension [N_tile, N_species]

GEOSldas_App/util/postproc/ObsFcstAna_stats/Plot_stats_timeseries.py

@@ -21,7 +21,7 @@ def Plot_monthly_OmF_bars(postproc_obj, fig_path='./'):
     start_month = postproc_obj.start_time
     end_month = postproc_obj.end_time
 
-    stats_file = fig_path + 'spa_stats_'+expid+'_'+start_month.strftime('%Y%m')+ \
+    stats_file = fig_path + 'spatial_stats_'+expid+'_'+start_month.strftime('%Y%m')+ \
             '_'+(end_month+timedelta(days=-1)).strftime('%Y%m')+'.pkl'
 
     if os.path.isfile(stats_file):