def test_threshold_local_generic(self):
ref = np.array([[1., 7., 16., 29., 37.], [5., 14., 23., 30., 30.],
[13., 24., 30., 29., 21.], [25., 29., 28., 19., 10.],
[34., 31., 23., 10., 4.]])
unchanged = threshold_local(self.image, 1, method='generic', param=sum)
out = threshold_local(self.image, 3, method='generic', param=sum)
assert np.allclose(unchanged.compute(), self.image.compute())
assert np.allclose(out.compute(), ref)
def test_threshold_local_generic(self):
ref = cupy.array([[1., 7., 16., 29., 37.], [5., 14., 23., 30., 30.],
[13., 24., 30., 29., 21.], [25., 29., 28., 19., 10.],
[34., 31., 23., 10., 4.]])
my_sum = cupy.ReductionKernel('T x', 'T out', 'x', 'a + b', 'out = a',
'0', 'my_sum')
unchanged = threshold_local(self.image,
1,
method='generic',
param=my_sum) # noqa: E501
out = threshold_local(self.image, 3, method='generic', param=my_sum)
assert cupy.allclose(unchanged.compute(), self.image.compute())
assert cupy.allclose(out.compute(), ref)
def test_threshold_local_gaussian(self, block_size):
ref = np.array([[False, False, False, False, True],
[False, False, True, False, True],
[False, False, True, True, False],
[False, True, True, False, False],
[True, True, False, False, False]])
out = threshold_local(self.image, block_size, method='gaussian')
cupy.testing.assert_array_equal(ref, (self.image > out).compute())
out = threshold_local(self.image,
block_size,
method='gaussian',
param=1. / 3.)
cupy.testing.assert_array_equal(ref, (self.image > out).compute())
def test_threshold_local_median(self, block_size):
ref = cupy.array([[False, False, False, False, True],
[False, False, True, False, False],
[False, False, True, False, False],
[False, False, True, True, False],
[False, True, False, False, False]])
out = threshold_local(self.image, block_size, method='median')
cupy.testing.assert_array_equal(ref, (self.image > out).compute())
def test_threshold_local_mean(self, block_size):
ref = np.array([[False, False, False, False, True],
[False, False, True, False, True],
[False, False, True, True, False],
[False, True, True, False, False],
[True, True, False, False, False]])
out = threshold_local(self.image, block_size, method='mean')
assert_equal(ref, (self.image > out).compute())
def test_threshold_local_generic_invalid(self):
expected_error_message = "Must include a valid function to use as "
"the 'param' keyword argument."
with pytest.raises(ValueError) as e:
threshold_local(self.image, 3, method='generic', param='sum')
assert e == expected_error_message
def test_invalid_threshold_method(self):
with pytest.raises(ValueError):
threshold_local(self.image, 3, method='invalid')
def test_nan_blocksize(self, method, block_size, error_type):
with pytest.raises(error_type):
threshold_local(self.image, block_size, method=method)