Fixed missing cmap sorting.

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

gms_preprocessing/algorithms/classification.py

@@ -278,17 +278,17 @@ class kNN_MinimumDistance_Classifier(MinimumDistance_Classifier):
         if self.n_neighbors < dists.shape[2]:
             cmap = np.argpartition(dists, k, axis=2)[:, :, :k].astype(np.int16)
             dists_min_k = np.partition(dists, k, axis=2)[:, :, :k].astype(np.float32)
-
-            # sort cmap by ascending spectral distances
-            idx_2D = np.argsort(dists_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)
-            dists_min_k = np.sort(dists_min_k, axis=2)
         else:
             cmap = np.tile(np.arange(dists.shape[2]).reshape(1, 1, -1), (*dists.shape[:2], 1))
             dists_min_k = dists
 
+        # sort cmap by ascending spectral distances
+        idx_2D = np.argsort(dists_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)
+        dists_min_k = np.sort(dists_min_k, axis=2)
+
         if global_shared_im2classify.nodata is not None and self._cmap_nodataVal is not None:
             cmap = self.overwrite_cmap_at_nodata_positions(cmap, tileimdata,
                                                            self._cmap_nodataVal, global_shared_im2classify.nodata)
@@ -402,17 +402,17 @@ 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
 
+        # 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)
+
         if global_shared_im2classify.nodata is not None and self._cmap_nodataVal is not None:
             cmap = self.overwrite_cmap_at_nodata_positions(cmap, tileimdata,
                                                            self._cmap_nodataVal, global_shared_im2classify.nodata)
@@ -519,17 +519,17 @@ class kNN_FEDSA_Classifier(FEDSA_Classifier):
         if self.n_neighbors < fedsa.shape[2]:
             cmap = np.argpartition(fedsa, k, axis=2)[:, :, :k].astype(np.int16)
             fedsa_min_k = np.partition(fedsa, k, axis=2)[:, :, :k].astype(np.float32)
-
-            # sort cmap by ascending angles
-            idx_2D = np.argsort(fedsa_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)
-            fedsa_min_k = np.sort(fedsa_min_k, axis=2)
         else:
             cmap = np.tile(np.arange(fedsa.shape[2]).reshape(1, 1, -1), (*fedsa.shape[:2], 1))
             fedsa_min_k = fedsa
 
+        # sort cmap by ascending angles
+        idx_2D = np.argsort(fedsa_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)
+        fedsa_min_k = np.sort(fedsa_min_k, axis=2)
+
         if global_shared_im2classify.nodata is not None and self._cmap_nodataVal is not None:
             cmap = self.overwrite_cmap_at_nodata_positions(cmap, tileimdata,
                                                            self._cmap_nodataVal, global_shared_im2classify.nodata)