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Fix cupy pytest errors (#368)
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* Fix cupy pytest errors, matches cpu threshold tests from PR 366
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@GenevieveBuckley
GenevieveBuckley authored May 15, 2024
1 parent 56e307f commit 382e203
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2 changes: 2 additions & 0 deletions tests/test_dask_image/test_ndfilters/test__threshold.py
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Original file line number Diff line number Diff line change
Expand Up @@ -98,6 +98,7 @@ def test_threshold_local_generic(simple_test_image):
assert np.allclose(unchanged.compute(), simple_test_image.compute())
assert np.allclose(out.compute(), ref)


def test_threshold_local_generic_invalid(simple_test_image):
expected_error_message = "Must include a valid function to use as "
"the 'param' keyword argument."
Expand All @@ -117,6 +118,7 @@ def test_nan_blocksize(simple_test_image, method, block_size, error_type):
with pytest.raises(error_type):
threshold_local(simple_test_image, block_size, method=method)


def test_invalid_threshold_method(simple_test_image):
with pytest.raises(ValueError):
threshold_local(simple_test_image, 3, method='invalid')
211 changes: 113 additions & 98 deletions tests/test_dask_image/test_ndfilters/test_cupy_threshold.py
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Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,20 @@

cupy = pytest.importorskip("cupy", minversion="5.0.0")

@pytest.fixture
def simple_test_image():
image = da.from_array(cupy.array(
[[0, 0, 1, 3, 5],
[0, 1, 4, 3, 4],
[1, 2, 5, 4, 1],
[2, 4, 5, 2, 1],
[4, 5, 1, 0, 0]], dtype=int), chunks=(5, 5))
return image


# ==================================================
# Test Threshold Filters
# ==================================================

@pytest.mark.cupy
@pytest.mark.parametrize('block_size', [
Expand All @@ -18,101 +32,102 @@
da.from_array(np.array([3, 3]), chunks=1),
da.from_array(np.array([3, 3]), chunks=2),
])
class TestSimpleImage:
def setup(self):
self.image = da.from_array(cupy.array(
[[0, 0, 1, 3, 5],
[0, 1, 4, 3, 4],
[1, 2, 5, 4, 1],
[2, 4, 5, 2, 1],
[4, 5, 1, 0, 0]], dtype=int), chunks=(5, 5))

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_mean(self, block_size):
ref = cupy.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')
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())


class TestGenericFilter:
def setup(self):
self.image = da.from_array(cupy.array(
[[0, 0, 1, 3, 5],
[0, 1, 4, 3, 4],
[1, 2, 5, 4, 1],
[2, 4, 5, 2, 1],
[4, 5, 1, 0, 0]], dtype=int), chunks=(5, 5))

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_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


class TestInvalidArguments:
def setup(self):
self.image = da.from_array(cupy.array(
[[0, 0, 1, 3, 5],
[0, 1, 4, 3, 4],
[1, 2, 5, 4, 1],
[2, 4, 5, 2, 1],
[4, 5, 1, 0, 0]], dtype=int), chunks=(5, 5))

@pytest.mark.parametrize("method, block_size, error_type", [
('median', cupy.nan, TypeError),
])
def test_nan_blocksize(self, method, block_size, error_type):
with pytest.raises(error_type):
threshold_local(self.image, block_size, method=method)

def test_invalid_threshold_method(self):
with pytest.raises(ValueError):
threshold_local(self.image, 3, method='invalid')
def test_threshold_local_gaussian(simple_test_image, 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(simple_test_image, block_size, method='gaussian')
cupy.testing.assert_array_equal(ref, (simple_test_image > out).compute())

out = threshold_local(simple_test_image, block_size, method='gaussian',
param=1./3.)
cupy.testing.assert_array_equal(ref, (simple_test_image > out).compute())


@pytest.mark.cupy
@pytest.mark.parametrize('block_size', [
3,
[3, 3],
np.array([3, 3]),
da.from_array(np.array([3, 3]), chunks=1),
da.from_array(np.array([3, 3]), chunks=2),
])
def test_threshold_local_mean(simple_test_image, block_size):
ref = cupy.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(simple_test_image, block_size, method='mean')
cupy.testing.assert_array_equal(ref, (simple_test_image > out).compute())


@pytest.mark.cupy
@pytest.mark.parametrize('block_size', [
3,
[3, 3],
np.array([3, 3]),
da.from_array(np.array([3, 3]), chunks=1),
da.from_array(np.array([3, 3]), chunks=2),
])
def test_threshold_local_median(simple_test_image, 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(simple_test_image, block_size, method='median')
cupy.testing.assert_array_equal(ref, (simple_test_image > out).compute())


# ==================================================
# Test Generic Filters
# ==================================================

def test_threshold_local_generic(simple_test_image):
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(simple_test_image, 1, method='generic', param=my_sum) # noqa: E501
out = threshold_local(simple_test_image, 3, method='generic', param=my_sum)
assert cupy.allclose(unchanged.compute(), simple_test_image.compute())
assert cupy.allclose(out.compute(), ref)


def test_threshold_local_generic_invalid(simple_test_image):
expected_error_message = "Must include a valid function to use as "
"the 'param' keyword argument."
with pytest.raises(ValueError) as e:
threshold_local(simple_test_image, 3, method='generic', param='sum')
assert e == expected_error_message


# ==================================================
# Test Invalid Arguments
# ==================================================

@pytest.mark.parametrize("method, block_size, error_type", [
('median', cupy.nan, TypeError),
])
def test_nan_blocksize(simple_test_image, method, block_size, error_type):
with pytest.raises(error_type):
threshold_local(simple_test_image, block_size, method=method)


def test_invalid_threshold_method(simple_test_image):
with pytest.raises(ValueError):
threshold_local(simple_test_image, 3, method='invalid')

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