snapshot...

modules/util/abi_surfrad.py

@@ -178,8 +178,8 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
                     valid_i = np.stack(data_tiles_i)
                     valid_m = np.stack(data_tiles_m)
                     if DO_WRITE_OUTFILE:
-                        np.save(out_directory + 'valid_mres_' + str(cnt), valid_m)
-                        np.save(out_directory + 'valid_ires_' + str(cnt), valid_i)
+                        np.save(out_directory + 'valid_mres_' + f'{cnt:04d}', valid_m)
+                        np.save(out_directory + 'valid_ires_' + f'{cnt:04d}', valid_i)
                     num_valid_samples = valid_m.shape[0]
 
                     param_valid_hist += np.histogram(valid_m[param_idx_m, ], bins=16, range=hist_range)[0]
@@ -200,8 +200,8 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
         valid_i = np.stack(data_tiles_i)
         valid_m = np.stack(data_tiles_m)
         if DO_WRITE_OUTFILE:
-            np.save(out_directory + 'valid_mres_' + str(cnt), valid_m)
-            np.save(out_directory + 'valid_ires_' + str(cnt), valid_i)
+            np.save(out_directory + 'valid_mres_' + f'{cnt:04d}', valid_m)
+            np.save(out_directory + 'valid_ires_' + f'{cnt:04d}', valid_i)
         num_valid_samples = valid_m.shape[0]
         param_valid_hist += np.histogram(valid_m[param_idx_m, ], bins=16, range=hist_range)[0]
     total_num_valid_samples += num_valid_samples
@@ -249,8 +249,8 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
                     train_i = np.stack(data_tiles_i)
                     train_m = np.stack(data_tiles_m)
                     if DO_WRITE_OUTFILE:
-                        np.save(out_directory + 'train_ires_' + str(cnt), train_i)
-                        np.save(out_directory + 'train_mres_' + str(cnt), train_m)
+                        np.save(out_directory + 'train_ires_' + f'{cnt:04d}', train_i)
+                        np.save(out_directory + 'train_mres_' + f'{cnt:04d}', train_m)
                     num_train_samples = train_m.shape[0]
 
                     param_train_hist += np.histogram(train_m[param_idx_m, ], bins=16, range=hist_range)[0]
@@ -271,8 +271,8 @@ def run_all(directory, out_directory, day_night='ANY', pattern='clavrx_*.nc', st
         train_i = np.stack(data_tiles_i)
         train_m = np.stack(data_tiles_m)
         if DO_WRITE_OUTFILE:
-            np.save(out_directory + 'train_ires_' + str(cnt), train_i)
-            np.save(out_directory + 'train_mres_' + str(cnt), train_m)
+            np.save(out_directory + 'train_ires_' + f'{cnt:04d}', train_i)
+            np.save(out_directory + 'train_mres_' + f'{cnt:04d}', train_m)
         num_train_samples = train_m.shape[0]
         param_train_hist += np.histogram(train_m[param_idx_m, ], bins=16, range=hist_range)[0]
     total_num_train_samples += num_train_samples