Allow mean pixel value inference from int arrays, not just float (#220)

1. Now only passes None to self.pixel_values i ncsr.py if subdtype is
np.bool_ rather than only collecting pixel_values when subdtype is
np.float_ allowing for pixel_values to be obtained from int and uint
images.
2. add skeletonlabel to _testdata.py to have an example int array
3. add test_skeletonlabel to test_csr.py to confirm int array behaves as
expected with csr.summarize

---------

Co-authored-by: Juan Nunez-Iglesias <[email protected]>

pyproject.toml

@@ -61,15 +61,15 @@ all = [
 testing = [
     'coverage',
     'hypothesis',
-    'napari[pyqt5]!=0.4.18',
+    'napari[pyqt5]>=0.4.19rc1',
     'pytest',
     'pytest-cov',
     'pytest-qt',
     'seaborn<1.0',
     'tifffile',
 ]
 docs = [
-    'napari[all]<0.4.18',
+    'napari[all]>=0.4.19rc1',
     'sphinx',
     'jupyter',
     'notebook',

src/skan/_testdata.py

@@ -64,3 +64,10 @@
                            [1, 0, 1, 0, 0],
                            [1, 0, 0, 1, 0],
                            [1, 0, 0, 0, 1]], dtype=bool)
+
+skeletonlabel = np.array([[1, 1, 0, 0, 2, 2, 0],
+                          [0, 0, 1, 0, 0, 0, 2],
+                          [3, 0, 0, 1, 0, 0, 2],
+                          [3, 0, 0, 1, 0, 0, 0],
+                          [3, 0, 0, 0, 1, 1, 1],
+                          [0, 3, 0, 0, 0, 1, 0]], dtype=int)

src/skan/csr.py

@@ -506,7 +506,9 @@ def __init__(
                 )
         if np.issubdtype(skeleton_image.dtype, np.float_):
             self.pixel_values = skeleton_image[coords]
-        else:
+        elif np.issubdtype(skeleton_image.dtype, np.int_):
+            self.pixel_values = skeleton_image.astype(float)[coords]
+        elif np.issubdtype(skeleton_image.dtype, np.bool_):
             self.pixel_values = None
         self.graph = graph
         self.nbgraph = csr_to_nbgraph(graph, self.pixel_values)

src/skan/test/test_csr.py

@@ -8,7 +8,7 @@
 from skan import csr, summarize
 from skan._testdata import (
         tinycycle, tinyline, skeleton0, skeleton1, skeleton2, skeleton3d,
-        topograph1d, skeleton4
+        topograph1d, skeleton4, skeletonlabel
         )
 
 
@@ -311,3 +311,8 @@ def test_skeleton_path_image_no_keep_image():
     s = csr.Skeleton(skeleton2, keep_images=False)
     pli = s.path_label_image()
     assert np.max(pli) == s.n_paths
+
+def test_skeletonlabel():
+    stats = csr.summarize(csr.Skeleton(skeletonlabel))
+    assert stats['mean-pixel-value'].max() == skeletonlabel.max()
+    assert stats['mean-pixel-value'].max() > 1