snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -784,6 +784,7 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
 
     grd_c = get_grid_values_all(h5f, label_param)
     grd_c = grd_c[y_0:y_0+sub_y, x_0:x_0+sub_x]
+    hr_grd_c = grd_c.copy()
     grd_c = grd_c[slc_y_2, slc_x_2]
     if label_param != 'cloud_probability':
         grd_c = normalize(grd_c, label_param, mean_std_dct)
@@ -798,7 +799,7 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
     if label_param != 'cloud_probability':
         out_sr = denormalize(out_sr, label_param, mean_std_dct)
     if out_file is not None:
-        np.save(out_file, out_sr)
+        np.save(out_file, [out_sr, hr_grd_c])
     else:
         return out_sr, bt, refl