Merge pull request haesleinhuepf#24 from haesleinhuepf/more_shape_des…

…criptors

added circularity, roundness and aspect ratio + docs + test

README.md

@@ -60,6 +60,9 @@ The user can select categories of features for feature extraction in the user in
   * extent
   * feret_diameter_max
   * local_centroid
+  * roundness as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html)
+  * circularity as defined for 2D labels  [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html)
+  * aspect_ratio as defined for 2D labels [by ImageJ](https://imagej.nih.gov/ij/docs/menus/analyze.html)
 * position:
   * centroid
   * bbox

napari_skimage_regionprops/_parametric_images.py

@@ -1,3 +1,4 @@
+import numpy as np
 from napari_tools_menu import register_function
 import numpy
 
@@ -15,15 +16,16 @@ def visualize_measurement_on_labels(labels_layer:"napari.layers.Labels", column:
         if "frame" in table.keys():
             table = table[table['frame'] == current_timepoint]
 
-    measurements = table[column]
+    measurements = np.asarray(table[column]).tolist()
 
-    if isinstance(measurements, numpy.ndarray):
-        measurements = measurements.tolist()
+    import importlib
+    loader = importlib.find_loader("pyclesperanto_prototype")
+    found = loader is not None
 
-    try:
+    if found:
         import pyclesperanto_prototype as cle
         return cle.pull(cle.replace_intensities(labels, numpy.asarray([0] + measurements)))
-    except ImportError:
+    else:
         return relabel_numpy(labels, measurements)
 
 

napari_skimage_regionprops/_regionprops.py

@@ -71,6 +71,9 @@ def standard_deviation_intensity(region, intensities):
         properties = properties + ['solidity', 'extent', 'feret_diameter_max', 'local_centroid']
         if len(labels.shape) == 2:
             properties = properties + ['major_axis_length', 'minor_axis_length', 'orientation', 'eccentricity']
+            if not size:
+                # we need these two to compute some shape descriptors
+                properties = properties + ['area', 'perimeter']
         else:
             properties = properties + ['moments_central']
         # euler_number,
@@ -98,6 +101,13 @@ def standard_deviation_intensity(region, intensities):
                               properties=properties, extra_properties=extra_properties)
 
     if shape:
+        if len(labels.shape) == 2:
+            # See https://imagej.nih.gov/ij/docs/menus/analyze.html
+            table['aspect_ratio'] = table['major_axis_length'] / table['minor_axis_length']
+            table['roundness'] = 4 * table['area'] / np.pi / pow(table['major_axis_length'], 2)
+            table['circularity'] = 4 * np.pi * table['area'] / pow(table['perimeter'], 2)
+
+        # 3D image
         if len(labels.shape) == 3:
             axis_lengths_0 = []
             axis_lengths_1 = []
@@ -125,6 +135,11 @@ def standard_deviation_intensity(region, intensities):
                 # remove moment from table as we didn't ask for them
                 table = {k: v for k, v in table.items() if not 'moments_central' in k}
 
+        if not size:
+            table = {k: v for k, v in table.items() if k != 'area'}
+        if not perimeter:
+            table = {k: v for k, v in table.items() if k != 'perimeter'}
+
     if napari_viewer is not None:
         # Store results in the properties dictionary:
         labels_layer.properties = table

napari_skimage_regionprops/_tests/test_function.py

@@ -55,8 +55,8 @@ def test_regionprops(make_napari_viewer):
 
     # generate a parametric image
     from napari_skimage_regionprops import visualize_measurement_on_labels
-    layer = visualize_measurement_on_labels(labels_layer, "area", viewer)
-    assert layer is not None
+    result = visualize_measurement_on_labels(labels_layer, "area", viewer)
+    assert result is not None
 
     reference = np.asarray([
         [0, 0, 0, 0, 0, 0, 0],
@@ -67,9 +67,9 @@ def test_regionprops(make_napari_viewer):
         [0, 0, 6, 6, 6, 0, 0],
         [0, 0, 6, 6, 6, 0, 1],
     ])
-    print("layer.data: ", layer.data)
+    print("result: ", result)
     print("reference: ", np.asarray(reference))
-    assert np.array_equal(layer.data, reference)
+    assert np.array_equal(result, reference)
 
     # replace table
     from napari_skimage_regionprops import add_table
@@ -350,3 +350,37 @@ def test_napari_api():
 def test_napari_api2():
     from napari_skimage_regionprops._utilities import napari_experimental_provide_function
     napari_experimental_provide_function()
+
+def test_shape_descriptors():
+    import numpy as np
+    labels = np.asarray([
+        [0, 0, 0, 0, 0, 0, 0, 0],
+        [1, 1, 0, 2, 2, 2, 3, 3],
+        [1, 1, 0, 2, 2, 2, 3, 3],
+        [0, 0, 0, 2, 2, 2, 3, 3],
+        [0, 0, 0, 0, 0, 0, 3, 3],
+        [0, 4, 4, 4, 4, 4, 0, 0],
+        [0, 4, 4, 4, 4, 4, 0, 0],
+        [0, 0, 0, 0, 0, 0, 0, 0],
+        [5, 5, 5, 5, 5, 0, 6, 6],
+        [5, 5, 5, 5, 5, 0, 6, 6],
+        [5, 5, 5, 5, 5, 0, 6, 6],
+        [0, 0, 0, 0, 0, 0, 0, 0]
+    ])
+
+    from napari_skimage_regionprops import regionprops_table
+    table = regionprops_table(labels, labels, None, False, False, False, True)
+
+    print(table.keys())
+    assert "area" not in table.keys()
+    assert "perimeter" not in table.keys()
+
+    print("aspect_ratio", table['aspect_ratio'])
+    assert np.allclose(table['aspect_ratio'], [1., 1., 2.23606798, 2.82842712, 1.73205081, 1.63299316])
+
+    print("circularity", table['circularity'])
+    assert np.allclose(table['circularity'], [3.14159265, 1.76714587, 1.57079633, 1.25663706, 1.30899694, 2.0943951 ])
+
+    print("roundness", table['roundness'])
+    # Values > 1 should actually not appear, but do so in case of very small objects apparently
+    assert np.allclose(table['roundness'], [1.27323954, 1.07429587, 0.50929582, 0.39788736, 0.59683104, 0.71619724])