new test on dual data handler normalization that should pass but is not

tests/data_handling/test_dual_data_handling.py

@@ -427,6 +427,11 @@ def test_normalization(log=False,
                                    t_enhance=t_enhance,
                                    val_split=0.1)
 
+    hr_means0 = np.mean(hr_handler.data, axis=(0, 1, 2))
+    lr_means0 = np.mean(lr_handler.data, axis=(0, 1, 2))
+    ddh_hr_means0 = np.mean(dual_handler.hr_data, axis=(0, 1, 2))
+    ddh_lr_means0 = np.mean(dual_handler.lr_data, axis=(0, 1, 2))
+
     means = copy.deepcopy(lr_handler.means)
     stdevs = copy.deepcopy(lr_handler.stds)
 
@@ -436,6 +441,11 @@ def test_normalization(log=False,
                                      t_enhance=t_enhance,
                                      n_batches=10)
 
+    hr_means1 = np.mean(hr_handler.data, axis=(0, 1, 2))
+    lr_means1 = np.mean(lr_handler.data, axis=(0, 1, 2))
+    ddh_hr_means1 = np.mean(dual_handler.hr_data, axis=(0, 1, 2))
+    ddh_lr_means1 = np.mean(dual_handler.lr_data, axis=(0, 1, 2))
+
     assert all(means[k] == v for k, v in batch_handler.means.items())
     assert all(stdevs[k] == v for k, v in batch_handler.stds.items())
 
@@ -446,6 +456,12 @@ def test_normalization(log=False,
         assert np.allclose(std, 1, atol=1e-3), str(std)
         assert np.allclose(mean, 0, atol=1e-3), str(mean)
 
+        fn = FEATURES[idf]
+        assert np.allclose(hr_means0[idf] - means[fn], hr_means1[idf])
+        assert np.allclose(lr_means0[idf] - means[fn], lr_means1[idf])
+        assert np.allclose(ddh_hr_means0[idf] - means[fn], ddh_hr_means1[idf])
+        assert np.allclose(ddh_lr_means0[idf] - means[fn], ddh_lr_means1[idf])
+
 
 @pytest.mark.parametrize(['lr_features', 'hr_features', 'hr_exo_features'],
                          [(['U_100m'], ['U_100m', 'V_100m'], ['V_100m']),