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| Current File : //proc/thread-self/root/usr/local/lib/python3.8/dist-packages/skimage/morphology/tests/test_misc.py |
import numpy as np
import pytest
from skimage.morphology import remove_small_objects, remove_small_holes
from skimage._shared import testing
from skimage._shared.testing import assert_array_equal, assert_equal
from skimage._shared._warnings import expected_warnings
test_image = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 1]], bool)
def test_one_connectivity():
expected = np.array([[0, 0, 0, 0, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], bool)
observed = remove_small_objects(test_image, min_size=6)
assert_array_equal(observed, expected)
def test_two_connectivity():
expected = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], bool)
observed = remove_small_objects(test_image, min_size=7, connectivity=2)
assert_array_equal(observed, expected)
def test_in_place():
image = test_image.copy()
with expected_warnings(["in_place argument is deprecated"]):
observed = remove_small_objects(image, min_size=6, in_place=True)
assert_equal(observed is image, True,
"remove_small_objects in_place argument failed.")
@pytest.mark.parametrize("in_dtype", [bool, int, np.int32])
@pytest.mark.parametrize("out_dtype", [bool, int, np.int32])
def test_out(in_dtype, out_dtype):
image = test_image.astype(in_dtype, copy=True)
expected_out = np.empty_like(test_image, dtype=out_dtype)
if out_dtype != bool:
# object with only 1 label will warn on non-bool output dtype
exp_warn = ["Only one label was provided"]
else:
exp_warn = []
with expected_warnings(exp_warn):
out = remove_small_objects(image, min_size=6, out=expected_out)
assert out is expected_out
def test_labeled_image():
labeled_image = np.array([[2, 2, 2, 0, 1],
[2, 2, 2, 0, 1],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=int)
expected = np.array([[2, 2, 2, 0, 0],
[2, 2, 2, 0, 0],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=int)
observed = remove_small_objects(labeled_image, min_size=3)
assert_array_equal(observed, expected)
def test_uint_image():
labeled_image = np.array([[2, 2, 2, 0, 1],
[2, 2, 2, 0, 1],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=np.uint8)
expected = np.array([[2, 2, 2, 0, 0],
[2, 2, 2, 0, 0],
[2, 0, 0, 0, 0],
[0, 0, 3, 3, 3]], dtype=np.uint8)
observed = remove_small_objects(labeled_image, min_size=3)
assert_array_equal(observed, expected)
def test_single_label_warning():
image = np.array([[0, 0, 0, 1, 0],
[1, 1, 1, 0, 0],
[1, 1, 1, 0, 0]], int)
with expected_warnings(['use a boolean array?']):
remove_small_objects(image, min_size=6)
def test_float_input():
float_test = np.random.rand(5, 5)
with testing.raises(TypeError):
remove_small_objects(float_test)
def test_negative_input():
negative_int = np.random.randint(-4, -1, size=(5, 5))
with testing.raises(ValueError):
remove_small_objects(negative_int)
test_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], bool)
def test_one_connectivity_holes():
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], bool)
observed = remove_small_holes(test_holes_image, area_threshold=3)
assert_array_equal(observed, expected)
def test_two_connectivity_holes():
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], bool)
observed = remove_small_holes(test_holes_image, area_threshold=3,
connectivity=2)
assert_array_equal(observed, expected)
def test_in_place_holes():
image = test_holes_image.copy()
with expected_warnings(["in_place argument is deprecated"]):
observed = remove_small_holes(image, area_threshold=3, in_place=True)
assert_equal(observed is image, True,
"remove_small_holes in_place argument failed.")
def test_out_remove_small_holes():
image = test_holes_image.copy()
expected_out = np.empty_like(image)
out = remove_small_holes(image, area_threshold=3, out=expected_out)
assert out is expected_out
def test_non_bool_out():
image = test_holes_image.copy()
expected_out = np.empty_like(image, dtype=int)
with testing.raises(TypeError):
remove_small_holes(image, area_threshold=3, out=expected_out)
def test_labeled_image_holes():
labeled_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]],
dtype=int)
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], dtype=bool)
with expected_warnings(['returned as a boolean array']):
observed = remove_small_holes(labeled_holes_image, area_threshold=3)
assert_array_equal(observed, expected)
def test_uint_image_holes():
labeled_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]],
dtype=np.uint8)
expected = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1],
[0, 0, 0, 0, 0, 0, 0, 1, 1, 1]], dtype=bool)
with expected_warnings(['returned as a boolean array']):
observed = remove_small_holes(labeled_holes_image, area_threshold=3)
assert_array_equal(observed, expected)
def test_label_warning_holes():
labeled_holes_image = np.array([[0, 0, 0, 0, 0, 0, 1, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 1, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 1, 0, 0, 0, 0],
[0, 1, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 0, 2],
[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]],
dtype=int)
with expected_warnings(['use a boolean array?']):
remove_small_holes(labeled_holes_image, area_threshold=3)
remove_small_holes(labeled_holes_image.astype(bool), area_threshold=3)
def test_float_input_holes():
float_test = np.random.rand(5, 5)
with testing.raises(TypeError):
remove_small_holes(float_test)