diff --git a/modules/util/abi_surfrad.py b/modules/util/abi_surfrad.py index d1c3b5accabb101021e39a33a69c4cd82a0a7b9e..3cb05ad66ed515f640139466abc294893495bd5b 100644 --- a/modules/util/abi_surfrad.py +++ b/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