The classification map of kNN_SAM_Classifier is now sorted by ascending SA in the z-dimension.

Signed-off-by: Daniel Scheffler <danschef@gfz-potsdam.de>

gms_preprocessing/algorithms/classification.py

@@ -342,6 +342,13 @@ class kNN_SAM_Classifier(SAM_Classifier):
         if self.n_neighbors < angles.shape[2]:
             cmap = np.argpartition(angles, k, axis=2)[:, :, :k].astype(np.int16)
             angles_min_k = np.partition(angles, k, axis=2)[:, :, :k].astype(np.float32)
+
+            # sort cmap by ascending angles
+            idx_2D = np.argsort(angles_min_k, axis=2).reshape(-1, cmap.shape[2])
+            cmap = \
+                cmap.reshape(-1, cmap.shape[2])[np.arange(cmap.shape[0] * cmap.shape[1])[:, np.newaxis], idx_2D]\
+                .reshape(*cmap.shape)
+            angles_min_k = np.sort(angles_min_k, axis=2)
         else:
             cmap = np.tile(np.arange(angles.shape[2]).reshape(1, 1, -1), (*angles.shape[:2], 1))
             angles_min_k = angles

tests/test_image_classifier.py

@@ -141,9 +141,7 @@ class Test_kNN_SAM_Classifier(unittest.TestCase):
         SC = kNN_SAM_Classifier(cluster_centers, n_neighbors=self.n_neighbors, CPUs=None)
         cmap_mp = SC.classify(test_gA_pure_endmembers, in_nodataVal=-9999, cmap_nodataVal=-9999)
 
-        for i, cl in enumerate(cluster_labels):
-            self.assertTrue(cl in cmap_mp[0, i, :])
-        # self.assertTrue(np.array_equal(cmap_mp.flatten(), cluster_labels))  # TODO sort cmap by SC.angles_deg
+        self.assertTrue(np.array_equal(cmap_mp[:, :, 0].flatten(), cluster_labels))
 
     def test_label_unclassified_pixels_absolute_th(self):
         SC = kNN_SAM_Classifier(cluster_centers, n_neighbors=self.n_neighbors, CPUs=None)