snapshot...

modules/deeplearning/cloud_opd_fcn_abi.py

@@ -333,17 +333,35 @@ class SRCNN:
         tmp = tmp[:, slc_y, slc_x]
         data_norm.append(tmp)
 
-        for param in sub_fields:
-            idx = params.index(param)
-            tmp = input_data[:, idx, :, :]
-            tmp = tmp[:, slc_y, slc_x]
-            if param != 'refl_substddev_ch01':
-                # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
-                tmp = scale(tmp, 'refl_0_65um_nom', mean_std_dct)
-            else:
-                # tmp = np.where(np.isnan(tmp), 0, tmp)
-                tmp = scale2(tmp, 0.0, 20.0)
-            data_norm.append(tmp)
+        # for param in sub_fields:
+        #     idx = params.index(param)
+        #     tmp = input_data[:, idx, :, :]
+        #     tmp = tmp[:, slc_y, slc_x]
+        #     if param != 'refl_substddev_ch01':
+        #         # tmp = normalize(tmp, 'refl_0_65um_nom', mean_std_dct)
+        #         tmp = scale(tmp, 'refl_0_65um_nom', mean_std_dct)
+        #     else:
+        #         # tmp = np.where(np.isnan(tmp), 0, tmp)
+        #         tmp = scale2(tmp, 0.0, 20.0)
+        #     data_norm.append(tmp)
+
+        idx = params.index(sub_fields[0])
+        tmp = input_data[:, idx, :, :]
+        tmp = tmp[:, slc_y, slc_x]
+        rlo = scale(tmp, 'refl_0_65um_nom', mean_std_dct)
+        data_norm.append(rlo)
+
+        idx = params.index(sub_fields[1])
+        tmp = input_data[:, idx, :, :]
+        tmp = tmp[:, slc_y, slc_x]
+        tmp = scale(tmp, 'refl_0_65um_nom', mean_std_dct)
+        data_norm.append(tmp - rlo)
+
+        idx = params.index(sub_fields[2])
+        tmp = input_data[:, idx, :, :]
+        tmp = tmp[:, slc_y, slc_x]
+        tmp = scale2(tmp, 0.0, 20.0)
+        data_norm.append(tmp)
 
         tmp = input_label[:, label_idx_i, :, :]
         tmp = get_grid_cell_mean(tmp)