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ai-content-maker/.venv/Lib/site-packages/scipy/ndimage/tests/test_morphology.py

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first commit
2024-05-03 04:18:51 +03:00
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")