def test_euler_number(): en = regionprops(SAMPLE)[0].euler_number assert en == 0 SAMPLE_mod = SAMPLE.copy() SAMPLE_mod[7, -3] = 0 en = regionprops(SAMPLE_mod)[0].euler_number assert en == -1 en = euler_number(SAMPLE, 1) assert en == 2 en = euler_number(SAMPLE_mod, 1) assert en == 1 en = euler_number(SAMPLE_3D, 1) assert en == 1 en = euler_number(SAMPLE_3D, 3) assert en == 1 # for convex body, Euler number is 1 SAMPLE_3D_2 = cp.zeros((100, 100, 100)) SAMPLE_3D_2[40:60, 40:60, 40:60] = 1 en = euler_number(SAMPLE_3D_2, 3) assert en == 1 SAMPLE_3D_2[45:55, 45:55, 45:55] = 0 en = euler_number(SAMPLE_3D_2, 3) assert en == 2
def test_extra_properties_nr_args(): with pytest.raises(AttributeError): region = regionprops(SAMPLE, extra_properties=(too_few_args, ))[0] _ = region.too_few_args with pytest.raises(AttributeError): region = regionprops(SAMPLE, extra_properties=(too_many_args, ))[0] _ = region.too_many_args
def test_multichannel(): """Test that computing multichannel properties works.""" astro = data.astronaut()[::4, ::4] labels = slic(astro.astype(float), start_label=1) astro = cp.asarray(astro) astro_green = astro[..., 1] labels = cp.asarray(labels) segment_idx = int(cp.max(labels) // 2) region = regionprops(labels, astro_green)[segment_idx] region_multi = regionprops(labels, astro)[segment_idx] for prop in PROPS: p = region[prop] p_multi = region_multi[prop] if isinstance(p, (list, tuple)): p = tuple([cp.asnumpy(p_) for p_ in p]) p = np.stack(p) if isinstance(p_multi, (list, tuple)): p_multi = tuple([cp.asnumpy(p_) for p_ in p_multi]) p_multi = np.stack(p_multi) if np.shape(p) == np.shape(p_multi): # property does not depend on multiple channels assert_array_equal(p, p_multi) else: # property uses multiple channels, returns props stacked along # final axis assert_array_equal(p, p_multi[..., 1])
def test_iterate_all_props(): region = regionprops(SAMPLE)[0] p0 = {p: region[p] for p in region} region = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE)[0] p1 = {p: region[p] for p in region} assert len(p0) < len(p1)
def test_filled_area(): area = regionprops(SAMPLE)[0].filled_area assert area == cp.sum(SAMPLE) SAMPLE_mod = SAMPLE.copy() SAMPLE_mod[7, -3] = 0 area = regionprops(SAMPLE_mod)[0].filled_area assert area == cp.sum(SAMPLE)
def test_eccentricity(): eps = regionprops(SAMPLE)[0].eccentricity assert_almost_equal(eps, 0.814629313427) img = cp.zeros((5, 5), dtype=cp.int) img[2, 2] = 1 eps = regionprops(img)[0].eccentricity assert_almost_equal(eps, 0)
def test_dtype(): regionprops(cp.zeros((10, 10), dtype=cp.int)) regionprops(cp.zeros((10, 10), dtype=cp.uint)) with pytest.raises(TypeError): regionprops(cp.zeros((10, 10), dtype=cp.float)) with pytest.raises(TypeError): regionprops(cp.zeros((10, 10), dtype=cp.double)) with pytest.raises(TypeError): regionprops(cp.zeros((10, 10), dtype=bool))
def test_feret_diameter_max(): # comparator result is based on SAMPLE from manually-inspected computations comparator_result = 18 test_result = regionprops(SAMPLE)[0].feret_diameter_max assert cp.abs(test_result - comparator_result) < 1 # square, test that Feret diameter is sqrt(2) * square side img = cp.zeros((20, 20), dtype=cp.uint8) img[2:-2, 2:-2] = 1 feret_diameter_max = regionprops(img)[0].feret_diameter_max assert cp.abs(feret_diameter_max - 16 * math.sqrt(2)) < 1
def test_coordinates(): sample = cp.zeros((10, 10), dtype=cp.int8) coords = cp.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 = cp.zeros((6, 6, 6), dtype=cp.int8) coords = cp.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_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_equals(): arr = cp.zeros((100, 100), dtype=cp.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_orientation(): orient = regionprops(SAMPLE)[0].orientation # determined with MATLAB assert_almost_equal(orient, -1.4663278802756865) # test diagonal regions diag = cp.eye(10, dtype=int) orient_diag = regionprops(diag)[0].orientation assert_almost_equal(orient_diag, -math.pi / 4) orient_diag = regionprops(cp.flipud(diag))[0].orientation assert_almost_equal(orient_diag, math.pi / 4) orient_diag = regionprops(cp.fliplr(diag))[0].orientation assert_almost_equal(orient_diag, math.pi / 4) orient_diag = regionprops(cp.fliplr(cp.flipud(diag)))[0].orientation assert_almost_equal(orient_diag, -math.pi / 4)
def test_extra_properties_mixed(): # mixed properties, with and without intensity region = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE, extra_properties=(median_intensity, pixelcount))[0] assert region.median_intensity == cp.median(INTENSITY_SAMPLE[SAMPLE == 1]) assert region.pixelcount == cp.sum(SAMPLE == 1)
def test_column_dtypes_correct(): msg = 'mismatch with expected type,' region = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE)[0] for col in COL_DTYPES: r = region[col] if col in OBJECT_COLUMNS: assert COL_DTYPES[col] == object continue # TODO: grlee77: check desired types for returned. # e.g. currently inertia_tensor_eigvals returns a list of 0-dim # arrays if isinstance(r, (tuple, list)): r0 = r[0] if isinstance(r0, cp.ndarray) and r0.ndim == 0: r0 = r0.item() t = type(r0) elif cp.isscalar(r): t = type(r) else: t = type(r.ravel()[0].item()) if cp.issubdtype(t, cp.floating): assert COL_DTYPES[col] == float, ( f'{col} dtype {t} {msg} {COL_DTYPES[col]}') elif cp.issubdtype(t, cp.integer): assert COL_DTYPES[col] == int, ( f'{col} dtype {t} {msg} {COL_DTYPES[col]}') else: assert False, (f'{col} dtype {t} {msg} {COL_DTYPES[col]}')
def test_all_props(): region = regionprops(SAMPLE, INTENSITY_SAMPLE)[0] for prop in PROPS: try: assert_array_almost_equal(region[prop], getattr(region, PROPS[prop])) except TypeError: # the `slice` property causes this pass
def test_all_props_3d(): region = regionprops(SAMPLE_3D, INTENSITY_SAMPLE_3D)[0] for prop in PROPS: try: assert_array_almost_equal(region[prop], getattr(region, PROPS[prop])) except (NotImplementedError, TypeError): pass
def test_invalid(): ps = regionprops(SAMPLE) def get_intensity_image(): ps[0].intensity_image with pytest.raises(AttributeError): get_intensity_image()
def test_moments_hu(): hu = regionprops(SAMPLE)[0].moments_hu # fmt: off ref = cp.array([ 3.27117627e-01, 2.63869194e-02, 2.35390060e-02, 1.23151193e-03, 1.38882330e-06, -2.72586158e-05, -6.48350653e-06 ]) # fmt: on # bug in OpenCV caused in Central Moments calculation? assert_array_almost_equal(hu, ref)
def test_weighted_moments_hu(): whu = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE)[0].weighted_moments_hu # fmt: off ref = cp.array([ 3.1750587329e-01, 2.1417517159e-02, 2.3609322038e-02, 1.2565683360e-03, 8.3014209421e-07, -3.5073773473e-05, -6.7936409056e-06 ]) # fmt: on assert_array_almost_equal(whu, ref)
def test_moments_normalized(): nu = regionprops(SAMPLE)[0].moments_normalized # determined with OpenCV assert_almost_equal(nu[0, 2], 0.24301268861454037) assert_almost_equal(nu[0, 3], -0.017278118992041805) assert_almost_equal(nu[1, 1], -0.016846707818929982) assert_almost_equal(nu[1, 2], 0.045473992910668816) assert_almost_equal(nu[2, 0], 0.08410493827160502) assert_almost_equal(nu[2, 1], -0.002899800614433943)
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_weighted_moments(): wm = regionprops(SAMPLE, intensity_image=INTENSITY_SAMPLE)[0].weighted_moments # fmt: off ref = cp.array( [[7.4000000e+01, 6.9900000e+02, 7.8630000e+03, 9.7317000e+04], [4.1000000e+02, 3.7850000e+03, 4.4063000e+04, 5.7256700e+05], [2.7500000e+03, 2.4855000e+04, 2.9347700e+05, 3.9007170e+06], [1.9778000e+04, 1.7500100e+05, 2.0810510e+06, 2.8078871e+07]]) # fmt: on assert_array_almost_equal(wm, ref)
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], 680.0) assert_almost_equal(m[0, 2], 7682.0) assert_almost_equal(m[0, 3], 95588.0) assert_almost_equal(m[1, 0], 408.0) assert_almost_equal(m[1, 1], 3766.0) assert_almost_equal(m[1, 2], 43882.0) assert_almost_equal(m[2, 0], 2748.0) assert_almost_equal(m[2, 1], 24836.0) assert_almost_equal(m[3, 0], 19776.0)
def test_props_to_dict(): regions = regionprops(SAMPLE) out = _props_to_dict(regions) assert out == { 'label': cp.array([1]), 'bbox-0': cp.array([0]), 'bbox-1': cp.array([0]), 'bbox-2': cp.array([10]), 'bbox-3': cp.array([18]) } regions = regionprops(SAMPLE) out = _props_to_dict(regions, properties=('label', 'area', 'bbox'), separator='+') assert out == { 'label': cp.array([1]), 'area': cp.array([72]), 'bbox+0': cp.array([0]), 'bbox+1': cp.array([0]), 'bbox+2': cp.array([10]), 'bbox+3': cp.array([18]) }
def test_weighted_moments_normalized(): wnu = regionprops( SAMPLE, intensity_image=INTENSITY_SAMPLE)[0].weighted_moments_normalized # fmt: off ref = np.array([ [np.nan, np.nan, 0.2301467830, -0.0162529732], # noqa [np.nan, -0.0160405109, 0.0457932622, -0.0104598869], # noqa [0.0873590903, -0.0031421072, 0.0165315478, -0.0028544152], # noqa [-0.0161217406, -0.0031376984, 0.0043903193, -0.0011057191] ] # noqa ) # fmt: on assert_array_almost_equal(wnu, ref)
def test_convex_image(): img = regionprops(SAMPLE)[0].convex_image # fmt: off ref = cp.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], [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]]) # fmt: on assert_array_equal(img, ref)
def test_cache(): SAMPLE_mod = SAMPLE.copy() region = regionprops(SAMPLE_mod)[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 cp.any(f0 != f1)
def test_docstrings_and_props(): def foo(): """foo""" has_docstrings = bool(foo.__doc__) 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) if has_docstrings: assert_equal(nr_docs_parsed, nr_props) ds = docs['weighted_moments_normalized'] assert 'iteration' not in ds assert len(ds.split('\n')) > 3 else: assert_equal(nr_docs_parsed, 0)
def test_weighted_moments_central(): wmu = regionprops( SAMPLE, intensity_image=INTENSITY_SAMPLE)[0].weighted_moments_central # fmt: off ref = cp.array([[ 7.4000000000e+01, 3.7303493627e-14, 1.2602837838e+03, -7.6561796932e+02 ], [ -2.1316282073e-13, -8.7837837838e+01, 2.1571526662e+03, -4.2385971907e+03 ], [ 4.7837837838e+02, -1.4801314828e+02, 6.6989799420e+03, -9.9501164076e+03 ], [ -7.5943608473e+02, -1.2714707125e+03, 1.5304076361e+04, -3.3156729271e+04 ]]) # fmt: on np.set_printoptions(precision=10) assert_array_almost_equal(wmu, ref)
def test_feret_diameter_max_3d(): img = cp.zeros((20, 20), dtype=cp.uint8) img[2:-2, 2:-2] = 1 img_3d = cp.dstack((img, ) * 3) feret_diameter_max = regionprops(img_3d)[0].feret_diameter_max assert cp.abs(feret_diameter_max - 16 * math.sqrt(2)) < 1