diff --git a/skimage/measure/_regionprops.py b/skimage/measure/_regionprops.py index f0e75fae..4d267a4f 100644 --- a/skimage/measure/_regionprops.py +++ b/skimage/measure/_regionprops.py @@ -7,7 +7,6 @@ from ._label import label from . import _moments -import sys from functools import wraps from collections import defaultdict @@ -24,14 +23,14 @@ PROPS = { 'CentralMoments': 'moments_central', 'Centroid': 'centroid', 'ConvexArea': 'convex_area', -# 'ConvexHull', + # 'ConvexHull', 'ConvexImage': 'convex_image', 'Coordinates': 'coords', 'Eccentricity': 'eccentricity', 'EquivDiameter': 'equivalent_diameter', 'EulerNumber': 'euler_number', 'Extent': 'extent', -# 'Extrema', + # 'Extrema', 'FilledArea': 'filled_area', 'FilledImage': 'filled_image', 'HuMoments': 'moments_hu', @@ -46,10 +45,10 @@ PROPS = { 'NormalizedMoments': 'moments_normalized', 'Orientation': 'orientation', 'Perimeter': 'perimeter', -# 'PixelIdxList', -# 'PixelList', + # 'PixelIdxList', + # 'PixelList', 'Solidity': 'solidity', -# 'SubarrayIdx' + # 'SubarrayIdx' 'WeightedCentralMoments': 'weighted_moments_central', 'WeightedCentroid': 'weighted_centroid', 'WeightedHuMoments': 'weighted_moments_hu', @@ -125,7 +124,8 @@ class _RegionProperties(object): def euler_number(self): euler_array = self.filled_image != self.image - _, num = label(euler_array, neighbors=8, return_num=True, background=-1) + _, num = label(euler_array, neighbors=8, return_num=True, + background=-1) return -num + 1 def extent(self): @@ -237,7 +237,8 @@ class _RegionProperties(object): @_cached def weighted_moments(self): - return _moments.moments_central(self._intensity_image_double(), 0, 0, 3) + return _moments.moments_central(self._intensity_image_double(), + 0, 0, 3) @_cached def weighted_moments_central(self): @@ -284,7 +285,7 @@ class _RegionProperties(object): for key in PROP_VALS: try: - #so that NaNs are equal + # so that NaNs are equal np.testing.assert_equal(getattr(self, key, None), getattr(other, key, None)) except AssertionError: @@ -526,7 +527,6 @@ def perimeter(image, neighbourhood=4): perimeter_weights[[21, 33]] = sqrt(2) perimeter_weights[[13, 23]] = (1 + sqrt(2)) / 2 - perimeter_image = ndi.convolve(border_image, np.array([[10, 2, 10], [ 2, 1, 2], [10, 2, 10]]), @@ -541,13 +541,13 @@ def perimeter(image, neighbourhood=4): return total_perimeter - def _parse_docs(): import re import textwrap doc = regionprops.__doc__ - matches = re.finditer('\*\*(\w+)\*\* \:.*?\n(.*?)(?=\n [\*\S]+)', doc, flags=re.DOTALL) + matches = re.finditer('\*\*(\w+)\*\* \:.*?\n(.*?)(?=\n [\*\S]+)', + doc, flags=re.DOTALL) prop_doc = dict((m.group(1), textwrap.dedent(m.group(2))) for m in matches) return prop_doc diff --git a/skimage/measure/tests/test_regionprops.py b/skimage/measure/tests/test_regionprops.py index 0fc140ad..259967ea 100644 --- a/skimage/measure/tests/test_regionprops.py +++ b/skimage/measure/tests/test_regionprops.py @@ -4,8 +4,7 @@ import numpy as np import math from skimage.measure._regionprops import (regionprops, PROPS, perimeter, - _parse_docs, _RegionProperties) -from skimage._shared._warnings import expected_warnings + _parse_docs) SAMPLE = np.array( @@ -64,14 +63,14 @@ def test_bbox(): def test_moments_central(): mu = regionprops(SAMPLE)[0].moments_central # determined with OpenCV - assert_almost_equal(mu[0,2], 436.00000000000045) + assert_almost_equal(mu[0, 2], 436.00000000000045) # different from OpenCV results, bug in OpenCV - assert_almost_equal(mu[0,3], -737.333333333333) - assert_almost_equal(mu[1,1], -87.33333333333303) - assert_almost_equal(mu[1,2], -127.5555555555593) - assert_almost_equal(mu[2,0], 1259.7777777777774) - assert_almost_equal(mu[2,1], 2000.296296296291) - assert_almost_equal(mu[3,0], -760.0246913580195) + assert_almost_equal(mu[0, 3], -737.333333333333) + assert_almost_equal(mu[1, 1], -87.33333333333303) + assert_almost_equal(mu[1, 2], -127.5555555555593) + assert_almost_equal(mu[2, 0], 1259.7777777777774) + assert_almost_equal(mu[2, 1], 2000.296296296291) + assert_almost_equal(mu[3, 0], -760.0246913580195) def test_centroid(): @@ -146,13 +145,13 @@ def test_extent(): def test_moments_hu(): hu = regionprops(SAMPLE)[0].moments_hu ref = np.array([ - 3.27117627e-01, - 2.63869194e-02, - 2.35390060e-02, - 1.23151193e-03, - 1.38882330e-06, + 3.27117627e-01, + 2.63869194e-02, + 2.35390060e-02, + 1.23151193e-03, + 1.38882330e-06, -2.72586158e-05, - 6.48350653e-06 + 6.48350653e-06 ]) # bug in OpenCV caused in Central Moments calculation? assert_array_almost_equal(hu, ref) @@ -218,27 +217,27 @@ def test_minor_axis_length(): def test_moments(): m = regionprops(SAMPLE)[0].moments # determined with OpenCV - assert_almost_equal(m[0,0], 72.0) - assert_almost_equal(m[0,1], 408.0) - assert_almost_equal(m[0,2], 2748.0) - assert_almost_equal(m[0,3], 19776.0) - assert_almost_equal(m[1,0], 680.0) - assert_almost_equal(m[1,1], 3766.0) - assert_almost_equal(m[1,2], 24836.0) - assert_almost_equal(m[2,0], 7682.0) - assert_almost_equal(m[2,1], 43882.0) - assert_almost_equal(m[3,0], 95588.0) + assert_almost_equal(m[0, 0], 72.0) + assert_almost_equal(m[0, 1], 408.0) + assert_almost_equal(m[0, 2], 2748.0) + assert_almost_equal(m[0, 3], 19776.0) + assert_almost_equal(m[1, 0], 680.0) + assert_almost_equal(m[1, 1], 3766.0) + assert_almost_equal(m[1, 2], 24836.0) + assert_almost_equal(m[2, 0], 7682.0) + assert_almost_equal(m[2, 1], 43882.0) + assert_almost_equal(m[3, 0], 95588.0) def test_moments_normalized(): nu = regionprops(SAMPLE)[0].moments_normalized # determined with OpenCV - assert_almost_equal(nu[0,2], 0.08410493827160502) - assert_almost_equal(nu[1,1], -0.016846707818929982) - assert_almost_equal(nu[1,2], -0.002899800614433943) - assert_almost_equal(nu[2,0], 0.24301268861454037) - assert_almost_equal(nu[2,1], 0.045473992910668816) - assert_almost_equal(nu[3,0], -0.017278118992041805) + assert_almost_equal(nu[0, 2], 0.08410493827160502) + assert_almost_equal(nu[1, 1], -0.016846707818929982) + assert_almost_equal(nu[1, 2], -0.002899800614433943) + assert_almost_equal(nu[2, 0], 0.24301268861454037) + assert_almost_equal(nu[2, 1], 0.045473992910668816) + assert_almost_equal(nu[3, 0], -0.017278118992041805) def test_orientation(): @@ -278,14 +277,14 @@ def test_weighted_moments_central(): wmu = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_moments_central ref = np.array( - [[ 7.4000000000e+01, -2.1316282073e-13, 4.7837837838e+02, - -7.5943608473e+02], - [ 3.7303493627e-14, -8.7837837838e+01, -1.4801314828e+02, - -1.2714707125e+03], - [ 1.2602837838e+03, 2.1571526662e+03, 6.6989799420e+03, - 1.5304076361e+04], - [ -7.6561796932e+02, -4.2385971907e+03, -9.9501164076e+03, - -3.3156729271e+04]] + [[ 7.4000000000e+01, -2.1316282073e-13, + 4.7837837838e+02, -7.5943608473e+02], + [ 3.7303493627e-14, -8.7837837838e+01, + -1.4801314828e+02, -1.2714707125e+03], + [ 1.2602837838e+03, 2.1571526662e+03, + 6.6989799420e+03, 1.5304076361e+04], + [-7.6561796932e+02, -4.2385971907e+03, + -9.9501164076e+03, -3.3156729271e+04]] ) np.set_printoptions(precision=10) assert_array_almost_equal(wmu, ref) @@ -316,14 +315,10 @@ def test_weighted_moments(): wm = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_moments ref = np.array( - [[ 7.4000000000e+01, 4.1000000000e+02, 2.7500000000e+03, - 1.9778000000e+04], - [ 6.9900000000e+02, 3.7850000000e+03, 2.4855000000e+04, - 1.7500100000e+05], - [ 7.8630000000e+03, 4.4063000000e+04, 2.9347700000e+05, - 2.0810510000e+06], - [ 9.7317000000e+04, 5.7256700000e+05, 3.9007170000e+06, - 2.8078871000e+07]] + [[7.4000000e+01, 4.1000000e+02, 2.7500000e+03, 1.9778000e+04], + [6.9900000e+02, 3.7850000e+03, 2.4855000e+04, 1.7500100e+05], + [7.8630000e+03, 4.4063000e+04, 2.9347700e+05, 2.0810510e+06], + [9.7317000e+04, 5.7256700e+05, 3.9007170e+06, 2.8078871e+07]] ) assert_array_almost_equal(wm, ref) @@ -356,6 +351,7 @@ def test_pure_background(): def test_invalid(): ps = regionprops(SAMPLE) + def get_intensity_image(): ps[0].intensity_image