Merge pull request #26 from BiAPoL/fix_axes_swap

I am merging this to have bug fixed. Fixed one of the tests as well. If errors arise, please file new issues.
BiAPoL · Jul 25, 2022 · c87f01a · c87f01a
2 parents 814f583 + a7811a9
commit c87f01a
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Showing 2 changed files with 14 additions and 8 deletions.
diff --git a/napari_crop/_function.py b/napari_crop/_function.py
@@ -83,11 +83,17 @@ def crop_region(
                 .squeeze()
             )
             # match cropped_data (x,y) shape with mask_2D shape
+            cropped_data_shape = cropped_data.shape
+            # Adjust cropped_data axes order in case axes were swapped in napari
+            if viewer is not None:
+                cropped_data_shape = np.moveaxis(cropped_data,
+                                                  viewer.dims.order,
+                                                  np.arange(len(cropped_data_shape))).shape
             if rgb:
-                shape_dif_2D = np.array(cropped_data.shape[-3:-1]) \
+                shape_dif_2D = np.array(cropped_data_shape[-3:-1]) \
                     - np.array(mask_2D.shape)
             else:
-                shape_dif_2D = np.array(cropped_data.shape[-2:]) \
+                shape_dif_2D = np.array(cropped_data_shape[-2:]) \
                     - np.array(mask_2D.shape)
             shape_dif_2D = [None if i == 0 else i
                             for i in shape_dif_2D.tolist()]
@@ -111,7 +117,7 @@ def crop_region(
 
         new_layer_props = layer_props.copy()
         # If layer name is in viewer or is about to be added,
-        # give it a different name
+        # increment layer name until it has a different name
         while True:
             new_name = layer_props["name"] \
                 + f" cropped [{shape_count+new_layer_index}]"

diff --git a/napari_crop/_tests/test_function.py b/napari_crop/_tests/test_function.py
@@ -13,16 +13,16 @@
 shapes = [
     np.array([[1, 1], [1, 3], [4, 3], [4, 1]]),
     np.array([[0.5, 0.5], [0.5, 3.5], [4.51, 3.5], [4.51, 0.5]]),
-    np.array([[0, 2], [4, 4], [4, 2], [2, 0]]),
+    np.array([[0, 2], [2, 0], [3, 2], [2, 4]]),
 ]
 shape_types = ["rectangle", "ellipse", "polygon"]
 crop_expected = [
     np.array([[6, 7, 8], [11, 12, 13], [16, 17, 18], [21, 22, 23]]),
     np.array([[0, 7, 0], [11, 12, 13], [16, 17, 18], [0, 22, 0]]),
-    np.array([[0, 2, 0],
-              [6, 7, 0],
-              [11, 12, 13],
-              [0, 17, 18]]),  # fmt: skip
+    np.array([[ 0,  0,  2,  0,  0],
+              [ 0,  6,  7,  8,  0],
+              [10, 11, 12, 13, 14],
+              [ 0,  0, 17,  0,  0]]),  # fmt: skip
 
 ]