snaphot...

modules/util/viirs_l1b_l2.py

@@ -49,15 +49,15 @@ emis_params = ['temp_10_4um_nom', 'temp_11_0um_nom', 'temp_12_0um_nom', 'temp_13
 #refl_params = ['refl_0_47um_nom', 'refl_0_65um_nom', 'refl_0_86um_nom', 'refl_1_38um_nom', 'refl_1_60um_nom']
 
 # data_params = refl_params + emis_params
-data_params = emis_params
+# data_params = emis_params
 
-l2_params = ['cld_temp_acha', 'cld_press_acha', 'cloud_fraction']
+l2_params = ['cld_temp_acha', 'cld_press_acha', 'cld_emiss_acha', 'cloud_fraction']
 
 label_params = l2_params
-#data_params = l2_params
+data_params = l2_params
 
 
-def run_all(directory, out_directory):
+def run_all(directory, out_directory, day_night='ANY'):
 
     cnt = 10
     total_num_train_samples = 0
@@ -105,8 +105,8 @@ def run_all(directory, out_directory):
                 label_tiles = []
 
                 try:
-                    run(data_h5f, data_params, data_tiles, tile_width=128, kernel_size=7)
-                    run(data_h5f, label_params, label_tiles, tile_width=128, kernel_size=7)
+                    run(data_h5f, data_params, data_tiles, tile_width=128, kernel_size=7, day_night=day_night)
+                    # run(data_h5f, label_params, label_tiles, tile_width=128, kernel_size=7, day_night=day_night)
                 except Exception as e:
                     print(e)
                     data_h5f.close()
@@ -116,21 +116,20 @@ def run_all(directory, out_directory):
                 data_h5f.close()
                 #label_h5f.close()
 
-                if len(data_tiles) == 0 or len(label_tiles) == 0:
-                    continue
+                # if len(data_tiles) == 0 or len(label_tiles) == 0:
+                #     continue
+                # if len(data_tiles) != len(label_tiles):
+                #     print('weirdness: ', data_f)
+                #     continue
 
-                if len(data_tiles) != len(label_tiles):
-                    print('weirdness: ', data_f)
+                if len(data_tiles) == 0:
                     continue
 
-                # if len(data_tiles) == 0:
-                #     continue
-
                 num = len(data_tiles)
                 n_vld = int(num * 0.1)
 
-                [label_valid_tiles.append(label_tiles[k]) for k in range(n_vld)]
-                [label_train_tiles.append(label_tiles[k]) for k in range(n_vld, num)]
+                # [label_valid_tiles.append(label_tiles[k]) for k in range(n_vld)]
+                # [label_train_tiles.append(label_tiles[k]) for k in range(n_vld, num)]
                 [data_valid_tiles.append(data_tiles[k]) for k in range(n_vld)]
                 [data_train_tiles.append(data_tiles[k]) for k in range(n_vld, num)]
 
@@ -138,15 +137,15 @@ def run_all(directory, out_directory):
                 if f_cnt == 10:
                     f_cnt = 0
 
-                    label_valid = np.stack(label_valid_tiles)
-                    label_train = np.stack(label_train_tiles)
+                    # label_valid = np.stack(label_valid_tiles)
+                    # label_train = np.stack(label_train_tiles)
                     data_valid = np.stack(data_valid_tiles)
                     data_train = np.stack(data_train_tiles)
 
                     np.save(out_directory+'data_train_' + str(cnt), data_train)
                     np.save(out_directory+'data_valid_' + str(cnt), data_valid)
-                    np.save(out_directory+'label_train_' + str(cnt), label_train)
-                    np.save(out_directory+'label_valid_' + str(cnt), label_valid)
+                    # np.save(out_directory+'label_train_' + str(cnt), label_train)
+                    # np.save(out_directory+'label_valid_' + str(cnt), label_valid)
 
                     label_valid_tiles = []
                     label_train_tiles = []