import numpy import numpy as np from numpy.testing import (assert_, assert_equal, assert_array_equal, assert_array_almost_equal) import pytest from pytest import raises as assert_raises from scipy import ndimage from . import types class TestNdimageMorphology: @pytest.mark.parametrize('dtype', types) def test_distance_transform_bf01(self, dtype): # brute force (bf) distance transform data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_bf(data, 'euclidean', return_indices=True) expected = [[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 2, 4, 2, 1, 0, 0], [0, 0, 1, 4, 8, 4, 1, 0, 0], [0, 0, 1, 2, 4, 2, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]] assert_array_almost_equal(out * out, expected) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 1, 2, 2, 2, 2], [3, 3, 3, 2, 1, 2, 3, 3, 3], [4, 4, 4, 4, 6, 4, 4, 4, 4], [5, 5, 6, 6, 7, 6, 6, 5, 5], [6, 6, 6, 7, 7, 7, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 2, 4, 6, 6, 7, 8], [0, 1, 1, 2, 4, 6, 7, 7, 8], [0, 1, 1, 1, 6, 7, 7, 7, 8], [0, 1, 2, 2, 4, 6, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(ft, expected) @pytest.mark.parametrize('dtype', types) def test_distance_transform_bf02(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_bf(data, 'cityblock', return_indices=True) expected = [[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 2, 2, 2, 1, 0, 0], [0, 0, 1, 2, 3, 2, 1, 0, 0], [0, 0, 1, 2, 2, 2, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]] assert_array_almost_equal(out, expected) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 1, 2, 2, 2, 2], [3, 3, 3, 3, 1, 3, 3, 3, 3], [4, 4, 4, 4, 7, 4, 4, 4, 4], [5, 5, 6, 7, 7, 7, 6, 5, 5], [6, 6, 6, 7, 7, 7, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 2, 4, 6, 6, 7, 8], [0, 1, 1, 1, 4, 7, 7, 7, 8], [0, 1, 1, 1, 4, 7, 7, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(expected, ft) @pytest.mark.parametrize('dtype', types) def test_distance_transform_bf03(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_bf(data, 'chessboard', return_indices=True) expected = [[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 2, 1, 1, 0, 0], [0, 0, 1, 2, 2, 2, 1, 0, 0], [0, 0, 1, 1, 2, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]] assert_array_almost_equal(out, expected) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 1, 2, 2, 2, 2], [3, 3, 4, 2, 2, 2, 4, 3, 3], [4, 4, 5, 6, 6, 6, 5, 4, 4], [5, 5, 6, 6, 7, 6, 6, 5, 5], [6, 6, 6, 7, 7, 7, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 2, 5, 6, 6, 7, 8], [0, 1, 1, 2, 6, 6, 7, 7, 8], [0, 1, 1, 2, 6, 7, 7, 7, 8], [0, 1, 2, 2, 6, 6, 7, 7, 8], [0, 1, 2, 4, 5, 6, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(ft, expected) @pytest.mark.parametrize('dtype', types) def test_distance_transform_bf04(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) tdt, tft = ndimage.distance_transform_bf(data, return_indices=1) dts = [] fts = [] dt = numpy.zeros(data.shape, dtype=numpy.float64) ndimage.distance_transform_bf(data, distances=dt) dts.append(dt) ft = ndimage.distance_transform_bf( data, return_distances=False, return_indices=1) fts.append(ft) ft = numpy.indices(data.shape, dtype=numpy.int32) ndimage.distance_transform_bf( data, return_distances=False, return_indices=True, indices=ft) fts.append(ft) dt, ft = ndimage.distance_transform_bf( data, return_indices=1) dts.append(dt) fts.append(ft) dt = numpy.zeros(data.shape, dtype=numpy.float64) ft = ndimage.distance_transform_bf( data, distances=dt, return_indices=True) dts.append(dt) fts.append(ft) ft = numpy.indices(data.shape, dtype=numpy.int32) dt = ndimage.distance_transform_bf( data, return_indices=True, indices=ft) dts.append(dt) fts.append(ft) dt = numpy.zeros(data.shape, dtype=numpy.float64) ft = numpy.indices(data.shape, dtype=numpy.int32) ndimage.distance_transform_bf( data, distances=dt, return_indices=True, indices=ft) dts.append(dt) fts.append(ft) for dt in dts: assert_array_almost_equal(tdt, dt) for ft in fts: assert_array_almost_equal(tft, ft) @pytest.mark.parametrize('dtype', types) def test_distance_transform_bf05(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_bf( data, 'euclidean', return_indices=True, sampling=[2, 2]) expected = [[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 4, 4, 4, 0, 0, 0], [0, 0, 4, 8, 16, 8, 4, 0, 0], [0, 0, 4, 16, 32, 16, 4, 0, 0], [0, 0, 4, 8, 16, 8, 4, 0, 0], [0, 0, 0, 4, 4, 4, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]] assert_array_almost_equal(out * out, expected) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 1, 2, 2, 2, 2], [3, 3, 3, 2, 1, 2, 3, 3, 3], [4, 4, 4, 4, 6, 4, 4, 4, 4], [5, 5, 6, 6, 7, 6, 6, 5, 5], [6, 6, 6, 7, 7, 7, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 2, 4, 6, 6, 7, 8], [0, 1, 1, 2, 4, 6, 7, 7, 8], [0, 1, 1, 1, 6, 7, 7, 7, 8], [0, 1, 2, 2, 4, 6, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(ft, expected) @pytest.mark.parametrize('dtype', types) def test_distance_transform_bf06(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_bf( data, 'euclidean', return_indices=True, sampling=[2, 1]) expected = [[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 4, 1, 0, 0, 0], [0, 0, 1, 4, 8, 4, 1, 0, 0], [0, 0, 1, 4, 9, 4, 1, 0, 0], [0, 0, 1, 4, 8, 4, 1, 0, 0], [0, 0, 0, 1, 4, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]] assert_array_almost_equal(out * out, expected) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 2, 2, 2, 2, 2, 2], [3, 3, 3, 3, 2, 3, 3, 3, 3], [4, 4, 4, 4, 4, 4, 4, 4, 4], [5, 5, 5, 5, 6, 5, 5, 5, 5], [6, 6, 6, 6, 7, 6, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 2, 6, 6, 6, 7, 8], [0, 1, 1, 1, 6, 7, 7, 7, 8], [0, 1, 1, 1, 7, 7, 7, 7, 8], [0, 1, 1, 1, 6, 7, 7, 7, 8], [0, 1, 2, 2, 4, 6, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(ft, expected) def test_distance_transform_bf07(self): # test input validation per discussion on PR #13302 data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]]) with assert_raises(RuntimeError): ndimage.distance_transform_bf( data, return_distances=False, return_indices=False ) @pytest.mark.parametrize('dtype', types) def test_distance_transform_cdt01(self, dtype): # chamfer type distance (cdt) transform data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_cdt( data, 'cityblock', return_indices=True) bf = ndimage.distance_transform_bf(data, 'cityblock') assert_array_almost_equal(bf, out) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 1, 1, 1, 2, 2, 2], [3, 3, 2, 1, 1, 1, 2, 3, 3], [4, 4, 4, 4, 1, 4, 4, 4, 4], [5, 5, 5, 5, 7, 7, 6, 5, 5], [6, 6, 6, 6, 7, 7, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 1, 1, 4, 7, 7, 7, 8], [0, 1, 1, 1, 4, 5, 6, 7, 8], [0, 1, 2, 2, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(ft, expected) @pytest.mark.parametrize('dtype', types) def test_distance_transform_cdt02(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_cdt(data, 'chessboard', return_indices=True) bf = ndimage.distance_transform_bf(data, 'chessboard') assert_array_almost_equal(bf, out) expected = [[[0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1], [2, 2, 2, 1, 1, 1, 2, 2, 2], [3, 3, 2, 2, 1, 2, 2, 3, 3], [4, 4, 3, 2, 2, 2, 3, 4, 4], [5, 5, 4, 6, 7, 6, 4, 5, 5], [6, 6, 6, 6, 7, 7, 6, 6, 6], [7, 7, 7, 7, 7, 7, 7, 7, 7], [8, 8, 8, 8, 8, 8, 8, 8, 8]], [[0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 2, 3, 4, 6, 7, 8], [0, 1, 1, 2, 2, 6, 6, 7, 8], [0, 1, 1, 1, 2, 6, 7, 7, 8], [0, 1, 1, 2, 6, 6, 7, 7, 8], [0, 1, 2, 2, 5, 6, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8], [0, 1, 2, 3, 4, 5, 6, 7, 8]]] assert_array_almost_equal(ft, expected) @pytest.mark.parametrize('dtype', types) def test_distance_transform_cdt03(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) tdt, tft = ndimage.distance_transform_cdt(data, return_indices=True) dts = [] fts = [] dt = numpy.zeros(data.shape, dtype=numpy.int32) ndimage.distance_transform_cdt(data, distances=dt) dts.append(dt) ft = ndimage.distance_transform_cdt( data, return_distances=False, return_indices=True) fts.append(ft) ft = numpy.indices(data.shape, dtype=numpy.int32) ndimage.distance_transform_cdt( data, return_distances=False, return_indices=True, indices=ft) fts.append(ft) dt, ft = ndimage.distance_transform_cdt( data, return_indices=True) dts.append(dt) fts.append(ft) dt = numpy.zeros(data.shape, dtype=numpy.int32) ft = ndimage.distance_transform_cdt( data, distances=dt, return_indices=True) dts.append(dt) fts.append(ft) ft = numpy.indices(data.shape, dtype=numpy.int32) dt = ndimage.distance_transform_cdt( data, return_indices=True, indices=ft) dts.append(dt) fts.append(ft) dt = numpy.zeros(data.shape, dtype=numpy.int32) ft = numpy.indices(data.shape, dtype=numpy.int32) ndimage.distance_transform_cdt(data, distances=dt, return_indices=True, indices=ft) dts.append(dt) fts.append(ft) for dt in dts: assert_array_almost_equal(tdt, dt) for ft in fts: assert_array_almost_equal(tft, ft) def test_distance_transform_cdt04(self): # test input validation per discussion on PR #13302 data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]]) indices_out = numpy.zeros((data.ndim,) + data.shape, dtype=numpy.int32) with assert_raises(RuntimeError): ndimage.distance_transform_bf( data, return_distances=True, return_indices=False, indices=indices_out ) @pytest.mark.parametrize('dtype', types) def test_distance_transform_cdt05(self, dtype): # test custom metric type per discussion on issue #17381 data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) metric_arg = np.ones((3, 3)) actual = ndimage.distance_transform_cdt(data, metric=metric_arg) assert actual.sum() == -21 @pytest.mark.parametrize('dtype', types) def test_distance_transform_edt01(self, dtype): # euclidean distance transform (edt) data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) out, ft = ndimage.distance_transform_edt(data, return_indices=True) bf = ndimage.distance_transform_bf(data, 'euclidean') assert_array_almost_equal(bf, out) dt = ft - numpy.indices(ft.shape[1:], dtype=ft.dtype) dt = dt.astype(numpy.float64) numpy.multiply(dt, dt, dt) dt = numpy.add.reduce(dt, axis=0) numpy.sqrt(dt, dt) assert_array_almost_equal(bf, dt) @pytest.mark.parametrize('dtype', types) def test_distance_transform_edt02(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) tdt, tft = ndimage.distance_transform_edt(data, return_indices=True) dts = [] fts = [] dt = numpy.zeros(data.shape, dtype=numpy.float64) ndimage.distance_transform_edt(data, distances=dt) dts.append(dt) ft = ndimage.distance_transform_edt( data, return_distances=0, return_indices=True) fts.append(ft) ft = numpy.indices(data.shape, dtype=numpy.int32) ndimage.distance_transform_edt( data, return_distances=False, return_indices=True, indices=ft) fts.append(ft) dt, ft = ndimage.distance_transform_edt( data, return_indices=True) dts.append(dt) fts.append(ft) dt = numpy.zeros(data.shape, dtype=numpy.float64) ft = ndimage.distance_transform_edt( data, distances=dt, return_indices=True) dts.append(dt) fts.append(ft) ft = numpy.indices(data.shape, dtype=numpy.int32) dt = ndimage.distance_transform_edt( data, return_indices=True, indices=ft) dts.append(dt) fts.append(ft) dt = numpy.zeros(data.shape, dtype=numpy.float64) ft = numpy.indices(data.shape, dtype=numpy.int32) ndimage.distance_transform_edt( data, distances=dt, return_indices=True, indices=ft) dts.append(dt) fts.append(ft) for dt in dts: assert_array_almost_equal(tdt, dt) for ft in fts: assert_array_almost_equal(tft, ft) @pytest.mark.parametrize('dtype', types) def test_distance_transform_edt03(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) ref = ndimage.distance_transform_bf(data, 'euclidean', sampling=[2, 2]) out = ndimage.distance_transform_edt(data, sampling=[2, 2]) assert_array_almost_equal(ref, out) @pytest.mark.parametrize('dtype', types) def test_distance_transform_edt4(self, dtype): data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype) ref = ndimage.distance_transform_bf(data, 'euclidean', sampling=[2, 1]) out = ndimage.distance_transform_edt(data, sampling=[2, 1]) assert_array_almost_equal(ref, out) def test_distance_transform_edt5(self): # Ticket #954 regression test out = ndimage.distance_transform_edt(False) assert_array_almost_equal(out, [0.]) def test_distance_transform_edt6(self): # test input validation per discussion on PR #13302 data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0]]) distances_out = numpy.zeros(data.shape, dtype=numpy.float64) with assert_raises(RuntimeError): ndimage.distance_transform_bf( data, return_indices=True, return_distances=False, distances=distances_out ) def test_generate_structure01(self): struct = ndimage.generate_binary_structure(0, 1) assert_array_almost_equal(struct, 1) def test_generate_structure02(self): struct = ndimage.generate_binary_structure(1, 1) assert_array_almost_equal(struct, [1, 1, 1]) def test_generate_structure03(self): struct = ndimage.generate_binary_structure(2, 1) assert_array_almost_equal(struct, [[0, 1, 0], [1, 1, 1], [0, 1, 0]]) def test_generate_structure04(self): struct = ndimage.generate_binary_structure(2, 2) assert_array_almost_equal(struct, [[1, 1, 1], [1, 1, 1], [1, 1, 1]]) def test_iterate_structure01(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] out = ndimage.iterate_structure(struct, 2) assert_array_almost_equal(out, [[0, 0, 1, 0, 0], [0, 1, 1, 1, 0], [1, 1, 1, 1, 1], [0, 1, 1, 1, 0], [0, 0, 1, 0, 0]]) def test_iterate_structure02(self): struct = [[0, 1], [1, 1], [0, 1]] out = ndimage.iterate_structure(struct, 2) assert_array_almost_equal(out, [[0, 0, 1], [0, 1, 1], [1, 1, 1], [0, 1, 1], [0, 0, 1]]) def test_iterate_structure03(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] out = ndimage.iterate_structure(struct, 2, 1) expected = [[0, 0, 1, 0, 0], [0, 1, 1, 1, 0], [1, 1, 1, 1, 1], [0, 1, 1, 1, 0], [0, 0, 1, 0, 0]] assert_array_almost_equal(out[0], expected) assert_equal(out[1], [2, 2]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion01(self, dtype): data = numpy.ones([], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, 1) @pytest.mark.parametrize('dtype', types) def test_binary_erosion02(self, dtype): data = numpy.ones([], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, 1) @pytest.mark.parametrize('dtype', types) def test_binary_erosion03(self, dtype): data = numpy.ones([1], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [0]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion04(self, dtype): data = numpy.ones([1], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion05(self, dtype): data = numpy.ones([3], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [0, 1, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion06(self, dtype): data = numpy.ones([3], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [1, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion07(self, dtype): data = numpy.ones([5], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [0, 1, 1, 1, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion08(self, dtype): data = numpy.ones([5], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [1, 1, 1, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion09(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [0, 0, 0, 0, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion10(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [1, 0, 0, 0, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion11(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 struct = [1, 0, 1] out = ndimage.binary_erosion(data, struct, border_value=1) assert_array_almost_equal(out, [1, 0, 1, 0, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion12(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 struct = [1, 0, 1] out = ndimage.binary_erosion(data, struct, border_value=1, origin=-1) assert_array_almost_equal(out, [0, 1, 0, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion13(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 struct = [1, 0, 1] out = ndimage.binary_erosion(data, struct, border_value=1, origin=1) assert_array_almost_equal(out, [1, 1, 0, 1, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion14(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 struct = [1, 1] out = ndimage.binary_erosion(data, struct, border_value=1) assert_array_almost_equal(out, [1, 1, 0, 0, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion15(self, dtype): data = numpy.ones([5], dtype) data[2] = 0 struct = [1, 1] out = ndimage.binary_erosion(data, struct, border_value=1, origin=-1) assert_array_almost_equal(out, [1, 0, 0, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion16(self, dtype): data = numpy.ones([1, 1], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [[1]]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion17(self, dtype): data = numpy.ones([1, 1], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [[0]]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion18(self, dtype): data = numpy.ones([1, 3], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [[0, 0, 0]]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion19(self, dtype): data = numpy.ones([1, 3], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [[1, 1, 1]]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion20(self, dtype): data = numpy.ones([3, 3], dtype) out = ndimage.binary_erosion(data) assert_array_almost_equal(out, [[0, 0, 0], [0, 1, 0], [0, 0, 0]]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion21(self, dtype): data = numpy.ones([3, 3], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, [[1, 1, 1], [1, 1, 1], [1, 1, 1]]) @pytest.mark.parametrize('dtype', types) def test_binary_erosion22(self, dtype): expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_erosion(data, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_erosion23(self, dtype): struct = ndimage.generate_binary_structure(2, 2) expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_erosion(data, struct, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_erosion24(self, dtype): struct = [[0, 1], [1, 1]] expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 1, 1, 1, 1], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_erosion(data, struct, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_erosion25(self, dtype): struct = [[0, 1, 0], [1, 0, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 1, 0, 1, 1], [0, 0, 1, 0, 1, 1, 0, 0], [0, 1, 0, 1, 1, 1, 1, 0], [0, 1, 1, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_erosion(data, struct, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_erosion26(self, dtype): struct = [[0, 1, 0], [1, 0, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0, 0, 1], [0, 0, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 1, 0, 1, 1], [0, 0, 1, 0, 1, 1, 0, 0], [0, 1, 0, 1, 1, 1, 1, 0], [0, 1, 1, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_erosion(data, struct, border_value=1, origin=(-1, -1)) assert_array_almost_equal(out, expected) def test_binary_erosion27(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_erosion(data, struct, border_value=1, iterations=2) assert_array_almost_equal(out, expected) def test_binary_erosion28(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_erosion(data, struct, border_value=1, iterations=2, output=out) assert_array_almost_equal(out, expected) def test_binary_erosion29(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0]], bool) out = ndimage.binary_erosion(data, struct, border_value=1, iterations=3) assert_array_almost_equal(out, expected) def test_binary_erosion30(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_erosion(data, struct, border_value=1, iterations=3, output=out) assert_array_almost_equal(out, expected) # test with output memory overlap ndimage.binary_erosion(data, struct, border_value=1, iterations=3, output=data) assert_array_almost_equal(data, expected) def test_binary_erosion31(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 1, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0, 1], [0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 1]] data = numpy.array([[0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_erosion(data, struct, border_value=1, iterations=1, output=out, origin=(-1, -1)) assert_array_almost_equal(out, expected) def test_binary_erosion32(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_erosion(data, struct, border_value=1, iterations=2) assert_array_almost_equal(out, expected) def test_binary_erosion33(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 1, 1], [0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] mask = [[1, 1, 1, 1, 1, 0, 0], [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]] data = numpy.array([[0, 0, 0, 0, 0, 1, 1], [0, 0, 0, 1, 0, 0, 1], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_erosion(data, struct, border_value=1, mask=mask, iterations=-1) assert_array_almost_equal(out, expected) def test_binary_erosion34(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] mask = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 0, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_erosion(data, struct, border_value=1, mask=mask) assert_array_almost_equal(out, expected) def test_binary_erosion35(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] mask = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 0, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0]], bool) tmp = [[0, 0, 1, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 0, 1], [0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 1]] expected = numpy.logical_and(tmp, mask) tmp = numpy.logical_and(data, numpy.logical_not(mask)) expected = numpy.logical_or(expected, tmp) out = numpy.zeros(data.shape, bool) ndimage.binary_erosion(data, struct, border_value=1, iterations=1, output=out, origin=(-1, -1), mask=mask) assert_array_almost_equal(out, expected) def test_binary_erosion36(self): struct = [[0, 1, 0], [1, 0, 1], [0, 1, 0]] mask = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] tmp = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1], [0, 0, 0, 0, 1, 0, 0, 1], [0, 0, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 1]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 1, 1, 1, 0, 1, 1], [0, 0, 1, 0, 1, 1, 0, 0], [0, 1, 0, 1, 1, 1, 1, 0], [0, 1, 1, 0, 0, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]]) expected = numpy.logical_and(tmp, mask) tmp = numpy.logical_and(data, numpy.logical_not(mask)) expected = numpy.logical_or(expected, tmp) out = ndimage.binary_erosion(data, struct, mask=mask, border_value=1, origin=(-1, -1)) assert_array_almost_equal(out, expected) def test_binary_erosion37(self): a = numpy.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]], dtype=bool) b = numpy.zeros_like(a) out = ndimage.binary_erosion(a, structure=a, output=b, iterations=0, border_value=True, brute_force=True) assert_(out is b) assert_array_equal( ndimage.binary_erosion(a, structure=a, iterations=0, border_value=True), b) def test_binary_erosion38(self): data = numpy.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]], dtype=bool) iterations = 2.0 with assert_raises(TypeError): _ = ndimage.binary_erosion(data, iterations=iterations) def test_binary_erosion39(self): iterations = numpy.int32(3) struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_erosion(data, struct, border_value=1, iterations=iterations, output=out) assert_array_almost_equal(out, expected) def test_binary_erosion40(self): iterations = numpy.int64(3) struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 0], [1, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 0, 0], [0, 0, 0, 1, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_erosion(data, struct, border_value=1, iterations=iterations, output=out) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation01(self, dtype): data = numpy.ones([], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, 1) @pytest.mark.parametrize('dtype', types) def test_binary_dilation02(self, dtype): data = numpy.zeros([], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, 0) @pytest.mark.parametrize('dtype', types) def test_binary_dilation03(self, dtype): data = numpy.ones([1], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [1]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation04(self, dtype): data = numpy.zeros([1], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation05(self, dtype): data = numpy.ones([3], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [1, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation06(self, dtype): data = numpy.zeros([3], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [0, 0, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation07(self, dtype): data = numpy.zeros([3], dtype) data[1] = 1 out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [1, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation08(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 data[3] = 1 out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [1, 1, 1, 1, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation09(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [1, 1, 1, 0, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation10(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 out = ndimage.binary_dilation(data, origin=-1) assert_array_almost_equal(out, [0, 1, 1, 1, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation11(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 out = ndimage.binary_dilation(data, origin=1) assert_array_almost_equal(out, [1, 1, 0, 0, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation12(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 struct = [1, 0, 1] out = ndimage.binary_dilation(data, struct) assert_array_almost_equal(out, [1, 0, 1, 0, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation13(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 struct = [1, 0, 1] out = ndimage.binary_dilation(data, struct, border_value=1) assert_array_almost_equal(out, [1, 0, 1, 0, 1]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation14(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 struct = [1, 0, 1] out = ndimage.binary_dilation(data, struct, origin=-1) assert_array_almost_equal(out, [0, 1, 0, 1, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation15(self, dtype): data = numpy.zeros([5], dtype) data[1] = 1 struct = [1, 0, 1] out = ndimage.binary_dilation(data, struct, origin=-1, border_value=1) assert_array_almost_equal(out, [1, 1, 0, 1, 0]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation16(self, dtype): data = numpy.ones([1, 1], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [[1]]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation17(self, dtype): data = numpy.zeros([1, 1], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [[0]]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation18(self, dtype): data = numpy.ones([1, 3], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [[1, 1, 1]]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation19(self, dtype): data = numpy.ones([3, 3], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [[1, 1, 1], [1, 1, 1], [1, 1, 1]]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation20(self, dtype): data = numpy.zeros([3, 3], dtype) data[1, 1] = 1 out = ndimage.binary_dilation(data) assert_array_almost_equal(out, [[0, 1, 0], [1, 1, 1], [0, 1, 0]]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation21(self, dtype): struct = ndimage.generate_binary_structure(2, 2) data = numpy.zeros([3, 3], dtype) data[1, 1] = 1 out = ndimage.binary_dilation(data, struct) assert_array_almost_equal(out, [[1, 1, 1], [1, 1, 1], [1, 1, 1]]) @pytest.mark.parametrize('dtype', types) def test_binary_dilation22(self, dtype): expected = [[0, 1, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation23(self, dtype): expected = [[1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0, 0, 1], [1, 1, 0, 0, 0, 1, 0, 1], [1, 0, 0, 1, 1, 1, 1, 1], [1, 0, 1, 1, 1, 1, 0, 1], [1, 1, 1, 1, 1, 1, 1, 1], [1, 0, 1, 0, 0, 1, 0, 1], [1, 1, 1, 1, 1, 1, 1, 1]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation24(self, dtype): expected = [[1, 1, 0, 0, 0, 0, 0, 0], [1, 0, 0, 0, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 0, 0, 0], [1, 1, 1, 1, 1, 1, 0, 0], [0, 1, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, origin=(1, 1)) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation25(self, dtype): expected = [[1, 1, 0, 0, 0, 0, 1, 1], [1, 0, 0, 0, 1, 0, 1, 1], [0, 0, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 0, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 0, 0, 1, 0, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, origin=(1, 1), border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation26(self, dtype): struct = ndimage.generate_binary_structure(2, 2) expected = [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, struct) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation27(self, dtype): struct = [[0, 1], [1, 1]] expected = [[0, 1, 0, 0, 0, 0, 0, 0], [1, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 0, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, struct) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation28(self, dtype): expected = [[1, 1, 1, 1], [1, 0, 0, 1], [1, 0, 0, 1], [1, 1, 1, 1]] data = numpy.array([[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, border_value=1) assert_array_almost_equal(out, expected) def test_binary_dilation29(self): struct = [[0, 1], [1, 1]] expected = [[0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 1, 1, 0], [0, 1, 1, 1, 0], [0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 0]], bool) out = ndimage.binary_dilation(data, struct, iterations=2) assert_array_almost_equal(out, expected) def test_binary_dilation30(self): struct = [[0, 1], [1, 1]] expected = [[0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 1, 1, 0], [0, 1, 1, 1, 0], [0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_dilation(data, struct, iterations=2, output=out) assert_array_almost_equal(out, expected) def test_binary_dilation31(self): struct = [[0, 1], [1, 1]] expected = [[0, 0, 0, 1, 0], [0, 0, 1, 1, 0], [0, 1, 1, 1, 0], [1, 1, 1, 1, 0], [0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 0]], bool) out = ndimage.binary_dilation(data, struct, iterations=3) assert_array_almost_equal(out, expected) def test_binary_dilation32(self): struct = [[0, 1], [1, 1]] expected = [[0, 0, 0, 1, 0], [0, 0, 1, 1, 0], [0, 1, 1, 1, 0], [1, 1, 1, 1, 0], [0, 0, 0, 0, 0]] data = numpy.array([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 0, 0, 0]], bool) out = numpy.zeros(data.shape, bool) ndimage.binary_dilation(data, struct, iterations=3, output=out) assert_array_almost_equal(out, expected) def test_binary_dilation33(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 1, 1, 0, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) mask = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 1, 1, 0, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_dilation(data, struct, iterations=-1, mask=mask, border_value=0) assert_array_almost_equal(out, expected) def test_binary_dilation34(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] mask = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.zeros(mask.shape, bool) out = ndimage.binary_dilation(data, struct, iterations=-1, mask=mask, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_dilation35(self, dtype): tmp = [[1, 1, 0, 0, 0, 0, 1, 1], [1, 0, 0, 0, 1, 0, 1, 1], [0, 0, 1, 1, 1, 1, 1, 1], [0, 1, 1, 1, 1, 0, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1], [0, 1, 0, 0, 1, 0, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1]] data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]]) mask = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] expected = numpy.logical_and(tmp, mask) tmp = numpy.logical_and(data, numpy.logical_not(mask)) expected = numpy.logical_or(expected, tmp) data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_dilation(data, mask=mask, origin=(1, 1), border_value=1) assert_array_almost_equal(out, expected) def test_binary_propagation01(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 1, 1, 0, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) mask = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 1, 1, 0, 0], [0, 0, 1, 1, 1, 0, 0, 0], [0, 1, 1, 0, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_propagation(data, struct, mask=mask, border_value=0) assert_array_almost_equal(out, expected) def test_binary_propagation02(self): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] mask = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.zeros(mask.shape, bool) out = ndimage.binary_propagation(data, struct, mask=mask, border_value=1) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_opening01(self, dtype): expected = [[0, 1, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 0], [0, 0, 1, 1, 0, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_opening(data) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_opening02(self, dtype): struct = ndimage.generate_binary_structure(2, 2) expected = [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [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, 1, 1, 1, 0, 0, 0, 0], [0, 1, 1, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 0, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_opening(data, struct) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_closing01(self, dtype): expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 1, 1, 1, 0, 1, 0, 0], [0, 0, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 1, 0, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 1, 1, 0], [0, 0, 1, 1, 0, 1, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_closing(data) assert_array_almost_equal(out, expected) @pytest.mark.parametrize('dtype', types) def test_binary_closing02(self, dtype): struct = ndimage.generate_binary_structure(2, 2) expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 1, 0, 0, 0, 0, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 0, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_closing(data, struct) assert_array_almost_equal(out, expected) def test_binary_fill_holes01(self): expected = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_fill_holes(data) assert_array_almost_equal(out, expected) def test_binary_fill_holes02(self): expected = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 1, 1, 1, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 1, 0, 0, 1, 0, 0], [0, 0, 0, 1, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_fill_holes(data) assert_array_almost_equal(out, expected) def test_binary_fill_holes03(self): expected = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 1, 1, 1, 0, 1, 1, 1], [0, 1, 1, 1, 0, 1, 1, 1], [0, 1, 1, 1, 0, 1, 1, 1], [0, 0, 1, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0]], bool) data = numpy.array([[0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 1, 0, 1, 0, 1, 1, 1], [0, 1, 0, 1, 0, 1, 0, 1], [0, 1, 0, 1, 0, 1, 0, 1], [0, 0, 1, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0]], bool) out = ndimage.binary_fill_holes(data) assert_array_almost_equal(out, expected) def test_grey_erosion01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] output = ndimage.grey_erosion(array, footprint=footprint) assert_array_almost_equal([[2, 2, 1, 1, 1], [2, 3, 1, 3, 1], [5, 5, 3, 3, 1]], output) def test_grey_erosion01_overlap(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] ndimage.grey_erosion(array, footprint=footprint, output=array) assert_array_almost_equal([[2, 2, 1, 1, 1], [2, 3, 1, 3, 1], [5, 5, 3, 3, 1]], array) def test_grey_erosion02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] output = ndimage.grey_erosion(array, footprint=footprint, structure=structure) assert_array_almost_equal([[2, 2, 1, 1, 1], [2, 3, 1, 3, 1], [5, 5, 3, 3, 1]], output) def test_grey_erosion03(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[1, 1, 1], [1, 1, 1]] output = ndimage.grey_erosion(array, footprint=footprint, structure=structure) assert_array_almost_equal([[1, 1, 0, 0, 0], [1, 2, 0, 2, 0], [4, 4, 2, 2, 0]], output) def test_grey_dilation01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[0, 1, 1], [1, 0, 1]] output = ndimage.grey_dilation(array, footprint=footprint) assert_array_almost_equal([[7, 7, 9, 9, 5], [7, 9, 8, 9, 7], [8, 8, 8, 7, 7]], output) def test_grey_dilation02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[0, 1, 1], [1, 0, 1]] structure = [[0, 0, 0], [0, 0, 0]] output = ndimage.grey_dilation(array, footprint=footprint, structure=structure) assert_array_almost_equal([[7, 7, 9, 9, 5], [7, 9, 8, 9, 7], [8, 8, 8, 7, 7]], output) def test_grey_dilation03(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[0, 1, 1], [1, 0, 1]] structure = [[1, 1, 1], [1, 1, 1]] output = ndimage.grey_dilation(array, footprint=footprint, structure=structure) assert_array_almost_equal([[8, 8, 10, 10, 6], [8, 10, 9, 10, 8], [9, 9, 9, 8, 8]], output) def test_grey_opening01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] tmp = ndimage.grey_erosion(array, footprint=footprint) expected = ndimage.grey_dilation(tmp, footprint=footprint) output = ndimage.grey_opening(array, footprint=footprint) assert_array_almost_equal(expected, output) def test_grey_opening02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp = ndimage.grey_erosion(array, footprint=footprint, structure=structure) expected = ndimage.grey_dilation(tmp, footprint=footprint, structure=structure) output = ndimage.grey_opening(array, footprint=footprint, structure=structure) assert_array_almost_equal(expected, output) def test_grey_closing01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] tmp = ndimage.grey_dilation(array, footprint=footprint) expected = ndimage.grey_erosion(tmp, footprint=footprint) output = ndimage.grey_closing(array, footprint=footprint) assert_array_almost_equal(expected, output) def test_grey_closing02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp = ndimage.grey_dilation(array, footprint=footprint, structure=structure) expected = ndimage.grey_erosion(tmp, footprint=footprint, structure=structure) output = ndimage.grey_closing(array, footprint=footprint, structure=structure) assert_array_almost_equal(expected, output) def test_morphological_gradient01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp1 = ndimage.grey_dilation(array, footprint=footprint, structure=structure) tmp2 = ndimage.grey_erosion(array, footprint=footprint, structure=structure) expected = tmp1 - tmp2 output = numpy.zeros(array.shape, array.dtype) ndimage.morphological_gradient(array, footprint=footprint, structure=structure, output=output) assert_array_almost_equal(expected, output) def test_morphological_gradient02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp1 = ndimage.grey_dilation(array, footprint=footprint, structure=structure) tmp2 = ndimage.grey_erosion(array, footprint=footprint, structure=structure) expected = tmp1 - tmp2 output = ndimage.morphological_gradient(array, footprint=footprint, structure=structure) assert_array_almost_equal(expected, output) def test_morphological_laplace01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp1 = ndimage.grey_dilation(array, footprint=footprint, structure=structure) tmp2 = ndimage.grey_erosion(array, footprint=footprint, structure=structure) expected = tmp1 + tmp2 - 2 * array output = numpy.zeros(array.shape, array.dtype) ndimage.morphological_laplace(array, footprint=footprint, structure=structure, output=output) assert_array_almost_equal(expected, output) def test_morphological_laplace02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp1 = ndimage.grey_dilation(array, footprint=footprint, structure=structure) tmp2 = ndimage.grey_erosion(array, footprint=footprint, structure=structure) expected = tmp1 + tmp2 - 2 * array output = ndimage.morphological_laplace(array, footprint=footprint, structure=structure) assert_array_almost_equal(expected, output) def test_white_tophat01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp = ndimage.grey_opening(array, footprint=footprint, structure=structure) expected = array - tmp output = numpy.zeros(array.shape, array.dtype) ndimage.white_tophat(array, footprint=footprint, structure=structure, output=output) assert_array_almost_equal(expected, output) def test_white_tophat02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp = ndimage.grey_opening(array, footprint=footprint, structure=structure) expected = array - tmp output = ndimage.white_tophat(array, footprint=footprint, structure=structure) assert_array_almost_equal(expected, output) def test_white_tophat03(self): array = numpy.array([[1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 0, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 1]], dtype=numpy.bool_) structure = numpy.ones((3, 3), dtype=numpy.bool_) expected = numpy.array([[0, 1, 1, 0, 0, 0, 0], [1, 0, 0, 1, 1, 1, 0], [1, 0, 0, 1, 1, 1, 0], [0, 1, 1, 0, 0, 0, 1], [0, 1, 1, 0, 1, 0, 1], [0, 1, 1, 0, 0, 0, 1], [0, 0, 0, 1, 1, 1, 1]], dtype=numpy.bool_) output = ndimage.white_tophat(array, structure=structure) assert_array_equal(expected, output) def test_white_tophat04(self): array = numpy.eye(5, dtype=numpy.bool_) structure = numpy.ones((3, 3), dtype=numpy.bool_) # Check that type mismatch is properly handled output = numpy.empty_like(array, dtype=numpy.float64) ndimage.white_tophat(array, structure=structure, output=output) def test_black_tophat01(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp = ndimage.grey_closing(array, footprint=footprint, structure=structure) expected = tmp - array output = numpy.zeros(array.shape, array.dtype) ndimage.black_tophat(array, footprint=footprint, structure=structure, output=output) assert_array_almost_equal(expected, output) def test_black_tophat02(self): array = numpy.array([[3, 2, 5, 1, 4], [7, 6, 9, 3, 5], [5, 8, 3, 7, 1]]) footprint = [[1, 0, 1], [1, 1, 0]] structure = [[0, 0, 0], [0, 0, 0]] tmp = ndimage.grey_closing(array, footprint=footprint, structure=structure) expected = tmp - array output = ndimage.black_tophat(array, footprint=footprint, structure=structure) assert_array_almost_equal(expected, output) def test_black_tophat03(self): array = numpy.array([[1, 0, 0, 0, 0, 0, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 0, 1, 0], [0, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 1]], dtype=numpy.bool_) structure = numpy.ones((3, 3), dtype=numpy.bool_) expected = numpy.array([[0, 1, 1, 1, 1, 1, 1], [1, 0, 0, 0, 0, 0, 1], [1, 0, 0, 0, 0, 0, 1], [1, 0, 0, 0, 0, 0, 1], [1, 0, 0, 0, 1, 0, 1], [1, 0, 0, 0, 0, 0, 1], [1, 1, 1, 1, 1, 1, 0]], dtype=numpy.bool_) output = ndimage.black_tophat(array, structure=structure) assert_array_equal(expected, output) def test_black_tophat04(self): array = numpy.eye(5, dtype=numpy.bool_) structure = numpy.ones((3, 3), dtype=numpy.bool_) # Check that type mismatch is properly handled output = numpy.empty_like(array, dtype=numpy.float64) ndimage.black_tophat(array, structure=structure, output=output) @pytest.mark.parametrize('dtype', types) def test_hit_or_miss01(self, dtype): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0], [0, 1, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0]] data = numpy.array([[0, 1, 0, 0, 0], [1, 1, 1, 0, 0], [0, 1, 0, 1, 1], [0, 0, 1, 1, 1], [0, 1, 1, 1, 0], [0, 1, 1, 1, 1], [0, 1, 1, 1, 1], [0, 0, 0, 0, 0]], dtype) out = numpy.zeros(data.shape, bool) ndimage.binary_hit_or_miss(data, struct, output=out) assert_array_almost_equal(expected, out) @pytest.mark.parametrize('dtype', types) def test_hit_or_miss02(self, dtype): struct = [[0, 1, 0], [1, 1, 1], [0, 1, 0]] expected = [[0, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 1, 0, 0, 1, 1, 1, 0], [1, 1, 1, 0, 0, 1, 0, 0], [0, 1, 0, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_hit_or_miss(data, struct) assert_array_almost_equal(expected, out) @pytest.mark.parametrize('dtype', types) def test_hit_or_miss03(self, dtype): struct1 = [[0, 0, 0], [1, 1, 1], [0, 0, 0]] struct2 = [[1, 1, 1], [0, 0, 0], [1, 1, 1]] expected = [[0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0]] data = numpy.array([[0, 1, 0, 0, 1, 1, 1, 0], [1, 1, 1, 0, 0, 0, 0, 0], [0, 1, 0, 1, 1, 1, 1, 0], [0, 0, 1, 1, 1, 1, 1, 0], [0, 1, 1, 1, 0, 1, 1, 0], [0, 0, 0, 0, 1, 1, 1, 0], [0, 1, 1, 1, 1, 1, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0]], dtype) out = ndimage.binary_hit_or_miss(data, struct1, struct2) assert_array_almost_equal(expected, out) class TestDilateFix: def setup_method(self): # dilation related setup self.array = numpy.array([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 1, 0], [0, 0, 1, 1, 0], [0, 0, 0, 0, 0]], dtype=numpy.uint8) self.sq3x3 = numpy.ones((3, 3)) dilated3x3 = ndimage.binary_dilation(self.array, structure=self.sq3x3) self.dilated3x3 = dilated3x3.view(numpy.uint8) def test_dilation_square_structure(self): result = ndimage.grey_dilation(self.array, structure=self.sq3x3) # +1 accounts for difference between grey and binary dilation assert_array_almost_equal(result, self.dilated3x3 + 1) def test_dilation_scalar_size(self): result = ndimage.grey_dilation(self.array, size=3) assert_array_almost_equal(result, self.dilated3x3) class TestBinaryOpeningClosing: def setup_method(self): a = numpy.zeros((5, 5), dtype=bool) a[1:4, 1:4] = True a[4, 4] = True self.array = a self.sq3x3 = numpy.ones((3, 3)) self.opened_old = ndimage.binary_opening(self.array, self.sq3x3, 1, None, 0) self.closed_old = ndimage.binary_closing(self.array, self.sq3x3, 1, None, 0) def test_opening_new_arguments(self): opened_new = ndimage.binary_opening(self.array, self.sq3x3, 1, None, 0, None, 0, False) assert_array_equal(opened_new, self.opened_old) def test_closing_new_arguments(self): closed_new = ndimage.binary_closing(self.array, self.sq3x3, 1, None, 0, None, 0, False) assert_array_equal(closed_new, self.closed_old) def test_binary_erosion_noninteger_iterations(): # regression test for gh-9905, gh-9909: ValueError for # non integer iterations data = numpy.ones([1]) assert_raises(TypeError, ndimage.binary_erosion, data, iterations=0.5) assert_raises(TypeError, ndimage.binary_erosion, data, iterations=1.5) def test_binary_dilation_noninteger_iterations(): # regression test for gh-9905, gh-9909: ValueError for # non integer iterations data = numpy.ones([1]) assert_raises(TypeError, ndimage.binary_dilation, data, iterations=0.5) assert_raises(TypeError, ndimage.binary_dilation, data, iterations=1.5) def test_binary_opening_noninteger_iterations(): # regression test for gh-9905, gh-9909: ValueError for # non integer iterations data = numpy.ones([1]) assert_raises(TypeError, ndimage.binary_opening, data, iterations=0.5) assert_raises(TypeError, ndimage.binary_opening, data, iterations=1.5) def test_binary_closing_noninteger_iterations(): # regression test for gh-9905, gh-9909: ValueError for # non integer iterations data = numpy.ones([1]) assert_raises(TypeError, ndimage.binary_closing, data, iterations=0.5) assert_raises(TypeError, ndimage.binary_closing, data, iterations=1.5) def test_binary_closing_noninteger_brute_force_passes_when_true(): # regression test for gh-9905, gh-9909: ValueError for # non integer iterations data = numpy.ones([1]) assert ndimage.binary_erosion( data, iterations=2, brute_force=1.5 ) == ndimage.binary_erosion(data, iterations=2, brute_force=bool(1.5)) assert ndimage.binary_erosion( data, iterations=2, brute_force=0.0 ) == ndimage.binary_erosion(data, iterations=2, brute_force=bool(0.0)) @pytest.mark.parametrize( 'function', ['binary_erosion', 'binary_dilation', 'binary_opening', 'binary_closing'], ) @pytest.mark.parametrize('iterations', [1, 5]) @pytest.mark.parametrize('brute_force', [False, True]) def test_binary_input_as_output(function, iterations, brute_force): rstate = numpy.random.RandomState(123) data = rstate.randint(low=0, high=2, size=100).astype(bool) ndi_func = getattr(ndimage, function) # input data is not modified data_orig = data.copy() expected = ndi_func(data, brute_force=brute_force, iterations=iterations) assert_array_equal(data, data_orig) # data should now contain the expected result ndi_func(data, brute_force=brute_force, iterations=iterations, output=data) assert_array_equal(expected, data) def test_binary_hit_or_miss_input_as_output(): rstate = numpy.random.RandomState(123) data = rstate.randint(low=0, high=2, size=100).astype(bool) # input data is not modified data_orig = data.copy() expected = ndimage.binary_hit_or_miss(data) assert_array_equal(data, data_orig) # data should now contain the expected result ndimage.binary_hit_or_miss(data, output=data) assert_array_equal(expected, data) def test_distance_transform_cdt_invalid_metric(): msg = 'invalid metric provided' with pytest.raises(ValueError, match=msg): ndimage.distance_transform_cdt(np.ones((5, 5)), metric="garbage")