import math import functools import numpy as np from skimage.measure._regionprops import (regionprops as regionprops_default, PROPS, perimeter, _parse_docs) from skimage._shared import testing from skimage._shared.testing import (assert_array_equal, assert_almost_equal, assert_array_almost_equal, assert_equal) regionprops = functools.partial(regionprops_default, coordinates='rc') SAMPLE = np.array( [[0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [1, 0, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 1, 1, 1, 1], [0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1]] ) INTENSITY_SAMPLE = SAMPLE.copy() INTENSITY_SAMPLE[1, 9:11] = 2 SAMPLE_3D = np.zeros((6, 6, 6), dtype=np.uint8) SAMPLE_3D[1:3, 1:3, 1:3] = 1 SAMPLE_3D[3, 2, 2] = 1 INTENSITY_SAMPLE_3D = SAMPLE_3D.copy() def test_all_props(): region = regionprops(SAMPLE, INTENSITY_SAMPLE)[0] for prop in PROPS: assert_almost_equal(region[prop], getattr(region, PROPS[prop])) def test_all_props_3d(): region = regionprops(SAMPLE_3D, INTENSITY_SAMPLE_3D)[0] for prop in PROPS: try: assert_almost_equal(region[prop], getattr(region, PROPS[prop])) except NotImplementedError: pass def test_dtype(): regionprops(np.zeros((10, 10), dtype=np.int)) regionprops(np.zeros((10, 10), dtype=np.uint)) with testing.raises(TypeError): regionprops(np.zeros((10, 10), dtype=np.float)) with testing.raises(TypeError): regionprops(np.zeros((10, 10), dtype=np.double)) def test_ndim(): regionprops(np.zeros((10, 10), dtype=np.int)) regionprops(np.zeros((10, 10, 1), dtype=np.int)) regionprops(np.zeros((10, 10, 10), dtype=np.int)) regionprops(np.zeros((1, 1), dtype=np.int)) regionprops(np.zeros((1, 1, 1), dtype=np.int)) with testing.raises(TypeError): regionprops(np.zeros((10, 10, 10, 2), dtype=np.int)) def test_area(): area = regionprops(SAMPLE)[0].area assert area == np.sum(SAMPLE) area = regionprops(SAMPLE_3D)[0].area assert area == np.sum(SAMPLE_3D) def test_bbox(): bbox = regionprops(SAMPLE)[0].bbox assert_array_almost_equal(bbox, (0, 0, SAMPLE.shape[0], SAMPLE.shape[1])) SAMPLE_mod = SAMPLE.copy() SAMPLE_mod[:, -1] = 0 bbox = regionprops(SAMPLE_mod)[0].bbox assert_array_almost_equal(bbox, (0, 0, SAMPLE.shape[0], SAMPLE.shape[1]-1)) bbox = regionprops(SAMPLE_3D)[0].bbox assert_array_almost_equal(bbox, (1, 1, 1, 4, 3, 3)) def test_bbox_area(): padded = np.pad(SAMPLE, 5, mode='constant') bbox_area = regionprops(padded)[0].bbox_area assert_array_almost_equal(bbox_area, SAMPLE.size) def test_moments_central(): mu = regionprops(SAMPLE)[0].moments_central # determined with OpenCV assert_almost_equal(mu[2, 0], 436.00000000000045) # different from OpenCV results, bug in OpenCV assert_almost_equal(mu[3, 0], -737.333333333333) assert_almost_equal(mu[1, 1], -87.33333333333303) assert_almost_equal(mu[2, 1], -127.5555555555593) assert_almost_equal(mu[0, 2], 1259.7777777777774) assert_almost_equal(mu[1, 2], 2000.296296296291) assert_almost_equal(mu[0, 3], -760.0246913580195) def test_centroid(): centroid = regionprops(SAMPLE)[0].centroid # determined with MATLAB assert_array_almost_equal(centroid, (5.66666666666666, 9.444444444444444)) def test_centroid_3d(): centroid = regionprops(SAMPLE_3D)[0].centroid # determined by mean along axis 1 of SAMPLE_3D.nonzero() assert_array_almost_equal(centroid, (1.66666667, 1.55555556, 1.55555556)) def test_convex_area(): area = regionprops(SAMPLE)[0].convex_area # determined with MATLAB assert area == 124 def test_convex_image(): img = regionprops(SAMPLE)[0].convex_image # determined with MATLAB ref = np.array( [[0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]] ) assert_array_equal(img, ref) def test_coordinates(): sample = np.zeros((10, 10), dtype=np.int8) coords = np.array([[3, 2], [3, 3], [3, 4]]) sample[coords[:, 0], coords[:, 1]] = 1 prop_coords = regionprops(sample)[0].coords assert_array_equal(prop_coords, coords) sample = np.zeros((6, 6, 6), dtype=np.int8) coords = np.array([[1, 1, 1], [1, 2, 1], [1, 3, 1]]) sample[coords[:, 0], coords[:, 1], coords[:, 2]] = 1 prop_coords = regionprops(sample)[0].coords assert_array_equal(prop_coords, coords) def test_eccentricity(): eps = regionprops(SAMPLE)[0].eccentricity assert_almost_equal(eps, 0.814629313427) img = np.zeros((5, 5), dtype=np.int) img[2, 2] = 1 eps = regionprops(img)[0].eccentricity assert_almost_equal(eps, 0) def test_equiv_diameter(): diameter = regionprops(SAMPLE)[0].equivalent_diameter # determined with MATLAB assert_almost_equal(diameter, 9.57461472963) def test_euler_number(): en = regionprops(SAMPLE)[0].euler_number assert en == 1 SAMPLE_mod = SAMPLE.copy() SAMPLE_mod[7, -3] = 0 en = regionprops(SAMPLE_mod)[0].euler_number assert en == 0 def test_extent(): extent = regionprops(SAMPLE)[0].extent assert_almost_equal(extent, 0.4) 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, -2.72586158e-05, -6.48350653e-06 ]) # bug in OpenCV caused in Central Moments calculation? assert_array_almost_equal(hu, ref) def test_image(): img = regionprops(SAMPLE)[0].image assert_array_equal(img, SAMPLE) img = regionprops(SAMPLE_3D)[0].image assert_array_equal(img, SAMPLE_3D[1:4, 1:3, 1:3]) def test_label(): label = regionprops(SAMPLE)[0].label assert_array_equal(label, 1) label = regionprops(SAMPLE_3D)[0].label assert_array_equal(label, 1) def test_filled_area(): area = regionprops(SAMPLE)[0].filled_area assert area == np.sum(SAMPLE) SAMPLE_mod = SAMPLE.copy() SAMPLE_mod[7, -3] = 0 area = regionprops(SAMPLE_mod)[0].filled_area assert area == np.sum(SAMPLE) def test_filled_image(): img = regionprops(SAMPLE)[0].filled_image assert_array_equal(img, SAMPLE) def test_major_axis_length(): length = regionprops(SAMPLE)[0].major_axis_length # MATLAB has different interpretation of ellipse than found in literature, # here implemented as found in literature assert_almost_equal(length, 16.7924234999) def test_max_intensity(): intensity = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].max_intensity assert_almost_equal(intensity, 2) def test_mean_intensity(): intensity = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].mean_intensity assert_almost_equal(intensity, 1.02777777777777) def test_min_intensity(): intensity = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].min_intensity assert_almost_equal(intensity, 1) def test_minor_axis_length(): length = regionprops(SAMPLE)[0].minor_axis_length # MATLAB has different interpretation of ellipse than found in literature, # here implemented as found in literature assert_almost_equal(length, 9.739302807263) def test_moments(): m = regionprops(SAMPLE)[0].moments.T # test was written with x/y coords # 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) def test_moments_normalized(): # test was written with x/y coords nu = regionprops(SAMPLE)[0].moments_normalized.T # 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) def test_orientation(): orientation = regionprops(SAMPLE, coordinates='xy')[0].orientation # determined with MATLAB assert_almost_equal(orientation, 0.10446844651921) # test correct quadrant determination orientation2 = regionprops(SAMPLE, coordinates='rc')[0].orientation assert_almost_equal(orientation2, -math.pi / 2 + orientation) # test diagonal regions diag = np.eye(10, dtype=int) orientation_diag = regionprops(diag, coordinates='xy')[0].orientation assert_almost_equal(orientation_diag, -math.pi / 4) orientation_diag = regionprops(np.flipud(diag))[0].orientation assert_almost_equal(orientation_diag, math.pi / 4) orientation_diag = regionprops(np.fliplr(diag))[0].orientation assert_almost_equal(orientation_diag, math.pi / 4) orientation_diag = regionprops(np.fliplr(np.flipud(diag)))[0].orientation assert_almost_equal(orientation_diag, -math.pi / 4) def test_perimeter(): per = regionprops(SAMPLE)[0].perimeter assert_almost_equal(per, 55.2487373415) per = perimeter(SAMPLE.astype('double'), neighbourhood=8) assert_almost_equal(per, 46.8284271247) def test_solidity(): solidity = regionprops(SAMPLE)[0].solidity # determined with MATLAB assert_almost_equal(solidity, 0.580645161290323) def test_weighted_moments_central(): wmu = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_moments_central.T # test used x/y coords 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]] ) np.set_printoptions(precision=10) assert_array_almost_equal(wmu, ref) def test_weighted_centroid(): centroid = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_centroid assert_array_almost_equal(centroid, (5.540540540540, 9.445945945945)) def test_weighted_moments_hu(): whu = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_moments_hu ref = np.array([ 3.1750587329e-01, 2.1417517159e-02, 2.3609322038e-02, 1.2565683360e-03, 8.3014209421e-07, -3.5073773473e-05, -6.7936409056e-06 ]) assert_array_almost_equal(whu, ref) def test_weighted_moments(): wm = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_moments.T # test used x/y coords 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]] ) assert_array_almost_equal(wm, ref) def test_weighted_moments_normalized(): wnu = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE )[0].weighted_moments_normalized.T # test used x/y coord ref = np.array( [[ np.nan, np.nan, 0.0873590903, -0.0161217406], [ np.nan, -0.0160405109, -0.0031421072, -0.0031376984], [ 0.230146783, 0.0457932622, 0.0165315478, 0.0043903193], [-0.0162529732, -0.0104598869, -0.0028544152, -0.0011057191]] ) assert_array_almost_equal(wnu, ref) def test_label_sequence(): a = np.empty((2, 2), dtype=np.int) a[:, :] = 2 ps = regionprops(a) assert len(ps) == 1 assert ps[0].label == 2 def test_pure_background(): a = np.zeros((2, 2), dtype=np.int) ps = regionprops(a) assert len(ps) == 0 def test_invalid(): ps = regionprops(SAMPLE) def get_intensity_image(): ps[0].intensity_image with testing.raises(AttributeError): get_intensity_image() def test_invalid_size(): wrong_intensity_sample = np.array([[1], [1]]) with testing.raises(ValueError): regionprops(SAMPLE, wrong_intensity_sample) def test_equals(): arr = np.zeros((100, 100), dtype=np.int) arr[0:25, 0:25] = 1 arr[50:99, 50:99] = 2 regions = regionprops(arr) r1 = regions[0] regions = regionprops(arr) r2 = regions[0] r3 = regions[1] assert_equal(r1 == r2, True, "Same regionprops are not equal") assert_equal(r1 != r3, True, "Different regionprops are equal") def test_iterate_all_props(): region = regionprops(SAMPLE)[0] p0 = dict((p, region[p]) for p in region) region = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE)[0] p1 = dict((p, region[p]) for p in region) assert len(p0) < len(p1) def test_cache(): region = regionprops(SAMPLE)[0] f0 = region.filled_image region._label_image[:10] = 1 f1 = region.filled_image # Changed underlying image, but cache keeps result the same assert_array_equal(f0, f1) # Now invalidate cache region._cache_active = False f1 = region.filled_image assert np.any(f0 != f1) def test_docstrings_and_props(): region = regionprops(SAMPLE)[0] docs = _parse_docs() props = [m for m in dir(region) if not m.startswith('_')] nr_docs_parsed = len(docs) nr_props = len(props) assert_equal(nr_docs_parsed, nr_props) ds = docs['weighted_moments_normalized'] assert 'iteration' not in ds assert len(ds.split('\n')) > 3 def test_incorrect_coordinate_convention(): with testing.raises(ValueError): regionprops_default(SAMPLE, coordinates='xyz')[0]