Merge pull request #24 from BiAPoL/unique_layer_names

Give cropped layers unique names.
Merging this because it seems to have fixed #20  while keeping backwards compatibility.

Author: zoccoler

.github/workflows/test_and_deploy.yml

@@ -3,7 +3,7 @@
 
 name: tests
 
-on: 
+on:
   push:
     branches:
       - master
@@ -46,7 +46,7 @@ jobs:
       - name: Install Windows OpenGL
         if: runner.os == 'Windows'
         run: |
-          git clone --depth 1 git://github.com/pyvista/gl-ci-helpers.git
+          git clone --depth 1 https://github.com/pyvista/gl-ci-helpers.git
           powershell gl-ci-helpers/appveyor/install_opengl.ps1
 
       # note: if you need dependencies from conda, considering using
@@ -69,7 +69,7 @@ jobs:
 
   deploy:
     # this will run when you have tagged a commit, starting with "v*"
-    # and requires that you have put your twine API key in your 
+    # and requires that you have put your twine API key in your
     # github secrets (see readme for details)
     needs: [test]
     runs-on: ubuntu-latest

napari_crop/_function.py

@@ -7,6 +7,7 @@
 from napari.types import LayerDataTuple
 from typing import List
 
+
 # This is the actual plugin function, where we export our function
 # (The functions themselves are defined below)
 @napari_hook_implementation
@@ -18,6 +19,7 @@ def napari_experimental_provide_function():
 def crop_region(
     layer: napari.layers.Layer,
     shapes_layer: napari.layers.Shapes,
+    viewer: 'napari.viewer.Viewer' = None, 
 ) -> List[LayerDataTuple]:
     """Crop regions in napari defined by shapes."""
     if shapes_layer is None:
@@ -42,7 +44,14 @@ def crop_region(
     shape_types = shapes_layer.shape_type
     shapes = shapes_layer.data
     cropped_list = []
-    for count, [shape, shape_type] in enumerate(zip(shapes, shape_types)):
+    new_layer_index = 0
+    new_name = layer_props["name"] + " cropped [0]"
+    names_list = []
+    if viewer is not None:
+        # Get existing layer names in viewer
+        names_list = [layer.name for layer in viewer.layers]
+    for shape_count, [shape, shape_type] in enumerate(zip(shapes,
+                                                          shape_types)):
         # move shape vertices to within image coordinate limits
         layer_shape = np.array(layer_data.shape)
         if rgb:
@@ -101,6 +110,16 @@ def crop_region(
             cropped_data = cropped_data[tuple(indices)]
 
         new_layer_props = layer_props.copy()
-        new_layer_props["name"] = layer_props["name"] + f" (cropped {count+1})"
+        # If layer name is in viewer or is about to be added,
+        # give it a different name
+        while True:
+            new_name = layer_props["name"] \
+                + f" cropped [{shape_count+new_layer_index}]"
+            if new_name not in names_list:
+                break
+            else:
+                new_layer_index += 1
+        new_layer_props["name"] = new_name
+        names_list.append(new_name)
         cropped_list.append((cropped_data, new_layer_props, layer_type))
     return cropped_list

napari_crop/_tests/test_function.py

@@ -68,7 +68,7 @@ def test_crop_multiple_shapes(make_napari_viewer):
     viewer = make_napari_viewer()
     img_layer = viewer.add_image(arr_2d)
     shapes_layer = viewer.add_shapes(shapes, shape_type=shape_types)
-    cropped_actual = crop_region(img_layer, shapes_layer)
+    cropped_actual = crop_region(img_layer, shapes_layer, viewer=viewer)
 
     assert len(shapes) == len(cropped_actual)