snapshot...

modules/icing/pirep_goes.py

@@ -1126,7 +1126,7 @@ def box_extract(outfile='/home/rink/box_out.h5', train_params=train_params_day):
     h5f_expl.close()
 
 
-def run_mean_std():
+def run_mean_std(check_cloudy=False):
     ds_list = ['cld_height_acha', 'cld_geo_thick', 'cld_press_acha',
                'supercooled_cloud_fraction', 'cld_temp_acha', 'cld_opd_acha',
                'cld_reff_acha', 'cld_reff_dcomp', 'cld_reff_dcomp_1', 'cld_reff_dcomp_2', 'cld_reff_dcomp_3',
@@ -1142,6 +1142,16 @@ def run_mean_std():
     ice_h5f_lst = [h5py.File(f, 'r') for f in ice_flist]
     no_ice_h5f_lst = [h5py.File(f, 'r') for f in no_ice_flist]
 
+    if check_cloudy:
+        cld_msk_i = []
+        cld_msk_ni = []
+        for idx, ice_h5f in enumerate(ice_h5f_lst):
+            no_ice_h5f = no_ice_h5f_lst[idx]
+            cld_msk_i.append(ice_h5f['cloud_mask'][:,].flatten())
+            cld_msk_ni.append(no_ice_h5f['cloud_mask'][:,].flatten())
+        cld_msk_i = np.concatenate(cld_msk_i)
+        cld_msk_ni = np.concatenate(cld_msk_ni)
+
     for dname in ds_list:
         data = []
         data_i = []
@@ -1160,11 +1170,19 @@ def run_mean_std():
         std = np.nanstd(data)
 
         data_i = np.concatenate(data_i)
+        if check_cloudy:
+            keep = np.logical_or(cld_msk_i == 2, cld_msk_i == 3)
+            data_i = data_i[keep]
+        print('ice: ', data_i.shape)
         mean_i = np.nanmean(data_i)
         data_i -= mean_i
         std_i = np.nanstd(data_i)
 
         data_ni = np.concatenate(data_ni)
+        if check_cloudy:
+            keep = np.logical_or(cld_msk_ni == 2, cld_msk_ni == 3)
+            data_ni = data_ni[keep]
+        print('no ice: ', data_ni.shape)
         mean_ni = np.nanmean(data_ni)
         data_ni -= mean_ni
         std_ni = np.nanstd(data_ni)