simplify

modules/util/viirs_l1b_l2.py

@@ -32,7 +32,7 @@ def run_all(directory, out_directory):
 
     cnt = 10
     total_num_train_samples = 0
-    total_num_test_samples = 0
+    total_num_valid_samples = 0
 
     for p in os.scandir(directory):
         if not p.is_dir():
@@ -105,8 +105,9 @@ def run_all(directory, out_directory):
                 [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)]
 
+                f_cnt += 1
                 if f_cnt == 10:
-                    cnt += 1
+                    f_cnt = 0
 
                     #label_valid = np.stack(label_valid_tiles)
                     #label_train = np.stack(label_train_tiles)
@@ -128,40 +129,11 @@ def run_all(directory, out_directory):
                     print('   file # done: ', cnt)
                     print('num_train_samples, num_valid_samples: ', num_train_samples, num_valid_samples)
                     total_num_train_samples += num_train_samples
-                    total_num_test_samples += num_valid_samples
-
-                    f_cnt = 0
-                else:
-                    f_cnt += 1
-
-        # if len(label_train_tiles) == 0 or len(data_train_tiles) == 0:
-        #     continue
-        # if len(label_train_tiles) != len(data_train_tiles):
-        #     print('weirdness')
-        #     continue
+                    total_num_valid_samples += num_valid_samples
 
-        if len(data_train_tiles) == 0:
-            continue
-
-        #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)
-
-        cnt += 1
-        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)
-
-        num_train_samples = data_train.shape[0]
-        num_valid_samples = data_valid.shape[0]
-
-        print('num_train_samples, num_valid_samples: ', num_train_samples, num_valid_samples)
-        total_num_train_samples += num_train_samples
-        total_num_test_samples += num_valid_samples
+                    cnt += 1
 
-    print('total_num_train_samples, total_num_valid_samples: ', num_train_samples, num_valid_samples)
+    print('total_num_train_samples, total_num_valid_samples: ', total_num_train_samples, total_num_valid_samples)
 
 
 def run(data_h5f, label_h5f, data_tiles, label_tiles, mod_tile_width=64, kernel_size=9):