class TestOpArrayPiper7(object):
def setUp(self):
self.graph = Graph()
self.operator_identity_1 = OpArrayPiper(graph=self.graph)
self.operator_identity_2 = OpArrayPiper(graph=self.graph)
self.operator_identity_1.Input.meta.axistags = vigra.AxisTags("txyzc")
self.operator_identity_2.Input.meta.axistags = vigra.AxisTags("txyzc")
def test1(self):
# Explicitly set has_mask for the input
self.operator_identity_1.Input.meta.has_mask = True
self.operator_identity_1.Output.meta.has_mask = True
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(
data,
mask=numpy.zeros(data.shape, dtype=bool),
shrink=False
)
# Try to connect the compatible operators.
self.operator_identity_2.Input.connect(self.operator_identity_1.Output)
self.operator_identity_1.Input.setValue(data)
output = self.operator_identity_2.Output[None].wait()
assert((data == output).all())
assert(data.mask.shape == output.mask.shape)
assert((data.mask == output.mask).all())
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(
data,
mask=numpy.zeros(data.shape, dtype=bool),
shrink=False
)
# Try to connect the compatible operators.
self.operator_identity_1.Input.setValue(data)
self.operator_identity_2.Input.connect(self.operator_identity_1.Output)
output = self.operator_identity_2.Output[None].wait()
assert((data == output).all())
assert(data.mask.shape == output.mask.shape)
assert((data.mask == output.mask).all())
def tearDown(self):
# Take down operators
self.operator_identity_2.Input.disconnect()
self.operator_identity_2.Output.disconnect()
self.operator_identity_2.cleanUp()
self.operator_identity_1.Input.disconnect()
self.operator_identity_1.Output.disconnect()
self.operator_identity_1.cleanUp()
class TestOpArrayPiper4(object):
def setup_method(self, method):
self.graph = Graph()
self.operator_identity = OpArrayPiper(graph=self.graph)
self.operator_identity.Input.allow_mask = False
self.operator_identity.Output.allow_mask = False
self.operator_identity.Input.meta.has_mask = False
self.operator_identity.Output.meta.has_mask = False
self.operator_identity.Input.meta.axistags = vigra.AxisTags("txyzc")
@nose.tools.raises(AllowMaskException)
def test1(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data, mask=numpy.zeros(data.shape, dtype=bool), shrink=False)
# Provide input read all output.
try:
self.operator_identity.Input.setValue(data)
except AssertionError as e:
raise AllowMaskException(str(e))
@nose.tools.raises(AllowMaskException)
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data, mask=numpy.zeros(data.shape, dtype=bool), shrink=False)
# Create array to store results. Don't keep original data.
output = data.copy()
output[:] = 0
output[:] = numpy.ma.nomask
# Provide input and grab chunks.
try:
self.operator_identity.Input.setValue(data)
except AssertionError as e:
raise AllowMaskException(str(e))
@nose.tools.raises(AllowMaskException)
def test3(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data, mask=numpy.zeros(data.shape, dtype=bool), shrink=False)
# Provide input read all output.
try:
self.operator_identity.Input.setValue(numpy.zeros_like(data))
except AssertionError as e:
raise AllowMaskException(str(e))
def teardown_method(self, method):
# Take down operators
self.operator_identity.Input.disconnect()
self.operator_identity.Output.disconnect()
self.operator_identity.cleanUp()
class TestOpArrayPiper4(object):
def setup_method(self, method):
self.graph = Graph()
self.operator_identity = OpArrayPiper(graph=self.graph)
self.operator_identity.Input.allow_mask = False
self.operator_identity.Output.allow_mask = False
self.operator_identity.Input.meta.has_mask = False
self.operator_identity.Output.meta.has_mask = False
self.operator_identity.Input.meta.axistags = vigra.AxisTags("txyzc")
def test1(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data, mask=numpy.zeros(data.shape, dtype=bool), shrink=False)
# Provide input read all output.
with pytest.raises(AllowMaskException):
try:
self.operator_identity.Input.setValue(data)
except AssertionError as e:
raise AllowMaskException(str(e))
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data, mask=numpy.zeros(data.shape, dtype=bool), shrink=False)
# Create array to store results. Don't keep original data.
output = data.copy()
output[:] = 0
output[:] = numpy.ma.nomask
# Provide input and grab chunks.
with pytest.raises(AllowMaskException):
try:
self.operator_identity.Input.setValue(data)
except AssertionError as e:
raise AllowMaskException(str(e))
def test3(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data, mask=numpy.zeros(data.shape, dtype=bool), shrink=False)
# Provide input read all output.
with pytest.raises(AllowMaskException):
try:
self.operator_identity.Input.setValue(numpy.zeros_like(data))
except AssertionError as e:
raise AllowMaskException(str(e))
def teardown_method(self, method):
# Take down operators
self.operator_identity.Input.disconnect()
self.operator_identity.Output.disconnect()
self.operator_identity.cleanUp()
class TestOpArrayPiper(object):
def setup_method(self, method):
self.graph = Graph()
self.operator_identity = OpArrayPiper(graph=self.graph)
self.operator_identity.Input.meta.axistags = vigra.AxisTags("txyzc")
def test1(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
# Provide input read all output.
self.operator_identity.Input.setValue(data)
output = self.operator_identity.Output[None].wait()
assert (data == output).all()
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
# Create array to store results. Don't keep original data.
output = data.copy()
output[:] = 0
# Provide input and grab chunks.
self.operator_identity.Input.setValue(data)
output[:2] = self.operator_identity.Output[:2].wait()
output[2:] = self.operator_identity.Output[2:].wait()
assert (data == output).all()
def test3(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
# Provide input read all output.
self.operator_identity.Input.setValue(numpy.zeros_like(data))
output = self.operator_identity.Output[None].wait()
assert (output == 0).all()
# Try setInSlot
data_shape_roi = roiFromShape(data.shape)
data_shape_slice = roiToSlice(*data_shape_roi)
self.operator_identity.Input[data_shape_slice] = data
output = self.operator_identity.Output[None].wait()
assert (data == output).all()
def teardown_method(self, method):
# Take down operators
self.operator_identity.Input.disconnect()
self.operator_identity.Output.disconnect()
self.operator_identity.cleanUp()
class TestOpArrayPiper(object):
def setUp(self):
self.graph = Graph()
self.operator_identity = OpArrayPiper(graph=self.graph)
self.operator_identity.Input.meta.axistags = vigra.AxisTags("txyzc")
def test1(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
# Provide input read all output.
self.operator_identity.Input.setValue(data)
output = self.operator_identity.Output[None].wait()
assert((data == output).all())
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
# Create array to store results. Don't keep original data.
output = data.copy()
output[:] = 0
# Provide input and grab chunks.
self.operator_identity.Input.setValue(data)
output[:2] = self.operator_identity.Output[:2].wait()
output[2:] = self.operator_identity.Output[2:].wait()
assert((data == output).all())
def test3(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
# Provide input read all output.
self.operator_identity.Input.setValue(numpy.zeros_like(data))
output = self.operator_identity.Output[None].wait()
assert((output == 0).all())
# Try setInSlot
data_shape_roi = roiFromShape(data.shape)
data_shape_slice = roiToSlice(*data_shape_roi)
self.operator_identity.Input[data_shape_slice] = data
output = self.operator_identity.Output[None].wait()
assert((data == output).all())
def tearDown(self):
# Take down operators
self.operator_identity.Input.disconnect()
self.operator_identity.Output.disconnect()
self.operator_identity.cleanUp()
class TestOpArrayPiper7(object):
def setup_method(self, method):
self.graph = Graph()
self.operator_identity_1 = OpArrayPiper(graph=self.graph)
self.operator_identity_2 = OpArrayPiper(graph=self.graph)
self.operator_identity_1.Input.meta.axistags = vigra.AxisTags("txyzc")
self.operator_identity_2.Input.meta.axistags = vigra.AxisTags("txyzc")
def test1(self):
# Explicitly set has_mask for the input
self.operator_identity_1.Input.meta.has_mask = True
self.operator_identity_1.Output.meta.has_mask = True
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data,
mask=numpy.zeros(data.shape, dtype=bool),
shrink=False)
# Try to connect the compatible operators.
self.operator_identity_2.Input.connect(self.operator_identity_1.Output)
self.operator_identity_1.Input.setValue(data)
output = self.operator_identity_2.Output[None].wait()
assert (data == output).all()
assert data.mask.shape == output.mask.shape
assert (data.mask == output.mask).all()
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data,
mask=numpy.zeros(data.shape, dtype=bool),
shrink=False)
# Try to connect the compatible operators.
self.operator_identity_1.Input.setValue(data)
self.operator_identity_2.Input.connect(self.operator_identity_1.Output)
output = self.operator_identity_2.Output[None].wait()
assert (data == output).all()
assert data.mask.shape == output.mask.shape
assert (data.mask == output.mask).all()
def teardown_method(self, method):
# Take down operators
self.operator_identity_2.Input.disconnect()
self.operator_identity_2.Output.disconnect()
self.operator_identity_2.cleanUp()
self.operator_identity_1.Input.disconnect()
self.operator_identity_1.Output.disconnect()
self.operator_identity_1.cleanUp()
class TestOpArrayPiper6(object):
def setup_method(self, method):
self.graph = Graph()
self.operator_identity_1 = OpArrayPiper(graph=self.graph)
self.operator_identity_2 = OpArrayPiper(graph=self.graph)
self.operator_identity_2.Input.allow_mask = False
self.operator_identity_2.Output.allow_mask = False
self.operator_identity_1.Input.meta.axistags = vigra.AxisTags("txyzc")
self.operator_identity_2.Input.meta.axistags = vigra.AxisTags("txyzc")
@nose.tools.raises(AllowMaskException)
def test1(self):
# Explicitly set has_mask for the input
self.operator_identity_1.Input.meta.has_mask = True
self.operator_identity_1.Output.meta.has_mask = True
# Try to connect the incompatible operators.
try:
self.operator_identity_2.Input.connect(
self.operator_identity_1.Output)
except AssertionError as e:
raise AllowMaskException(str(e))
@nose.tools.raises(AllowMaskException)
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(data,
mask=numpy.zeros(data.shape, dtype=bool),
shrink=False)
# Implicitly set has_mask for the input by setting the value.
self.operator_identity_1.Input.setValue(data)
# Try to connect the incompatible operators.
try:
self.operator_identity_2.Input.connect(
self.operator_identity_1.Output)
except AssertionError as e:
raise AllowMaskException(str(e))
def teardown_method(self, method):
# Take down operators
self.operator_identity_2.Input.disconnect()
self.operator_identity_2.Output.disconnect()
self.operator_identity_2.cleanUp()
self.operator_identity_1.Input.disconnect()
self.operator_identity_1.Output.disconnect()
self.operator_identity_1.cleanUp()
class TestOpArrayPiper6(object):
def setUp(self):
self.graph = Graph()
self.operator_identity_1 = OpArrayPiper(graph=self.graph)
self.operator_identity_2 = OpArrayPiper(graph=self.graph)
self.operator_identity_2.Input.allow_mask = False
self.operator_identity_2.Output.allow_mask = False
self.operator_identity_1.Input.meta.axistags = vigra.AxisTags("txyzc")
self.operator_identity_2.Input.meta.axistags = vigra.AxisTags("txyzc")
@nose.tools.raises(AllowMaskException)
def test1(self):
# Explicitly set has_mask for the input
self.operator_identity_1.Input.meta.has_mask = True
self.operator_identity_1.Output.meta.has_mask = True
# Try to connect the incompatible operators.
try:
self.operator_identity_2.Input.connect(self.operator_identity_1.Output)
except AssertionError as e:
raise AllowMaskException(str(e))
@nose.tools.raises(AllowMaskException)
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
data = numpy.ma.masked_array(
data,
mask=numpy.zeros(data.shape, dtype=bool),
shrink=False
)
# Implicitly set has_mask for the input by setting the value.
self.operator_identity_1.Input.setValue(data)
# Try to connect the incompatible operators.
try:
self.operator_identity_2.Input.connect(self.operator_identity_1.Output)
except AssertionError as e:
raise AllowMaskException(str(e))
def tearDown(self):
# Take down operators
self.operator_identity_2.Input.disconnect()
self.operator_identity_2.Output.disconnect()
self.operator_identity_2.cleanUp()
self.operator_identity_1.Input.disconnect()
self.operator_identity_1.Output.disconnect()
self.operator_identity_1.cleanUp()
class TestOpMaskArray3(object):
def setUp(self):
self.graph = Graph()
self.operator_border = OpMaskArray(graph=self.graph)
self.operator_identity = OpArrayPiper(graph=self.graph)
self.operator_border.InputArray.meta.axistags = vigra.AxisTags("txyzc")
self.operator_identity.Input.connect(self.operator_border.Output)
def test1(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
mask = numpy.zeros(data.shape, dtype=bool)
# Mask borders of the expected output.
left_slicing = (mask.ndim - 1) * (slice(None),) + (slice(None, 1),)
right_slicing = (mask.ndim - 1) * (slice(None),) + (slice(-1, None),)
for i in xrange(mask.ndim):
left_slicing = left_slicing[-1:] + left_slicing[:-1]
right_slicing = right_slicing[-1:] + right_slicing[:-1]
mask[left_slicing] = True
mask[right_slicing] = True
expected_output = numpy.ma.masked_array(data,
mask=mask,
shrink=False
)
# Provide input read all output.
self.operator_border.InputArray.setValue(data)
self.operator_border.InputMask.setValue(mask)
output = self.operator_identity.Output[None].wait()
assert((expected_output == output).all())
assert(expected_output.mask.shape == output.mask.shape)
assert((expected_output.mask == output.mask).all())
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
mask = numpy.zeros(data.shape, dtype=bool)
# Mask borders of the expected output.
left_slicing = (mask.ndim - 1) * (slice(None),) + (slice(None, 1),)
right_slicing = (mask.ndim - 1) * (slice(None),) + (slice(-1, None),)
for i in xrange(mask.ndim):
left_slicing = left_slicing[-1:] + left_slicing[:-1]
right_slicing = right_slicing[-1:] + right_slicing[:-1]
mask[left_slicing] = True
mask[right_slicing] = True
expected_output = numpy.ma.masked_array(data,
mask=mask,
shrink=False
)
# Create array to store results. Don't keep original data.
output = expected_output.copy()
output[:] = 0
output[:] = numpy.ma.nomask
# Provide input and grab chunks.
self.operator_border.InputArray.setValue(data)
self.operator_border.InputMask.setValue(mask)
output[:2] = self.operator_identity.Output[:2].wait()
output[2:] = self.operator_identity.Output[2:].wait()
assert((expected_output == output).all())
assert(expected_output.mask.shape == output.mask.shape)
assert((expected_output.mask == output.mask).all())
def tearDown(self):
# Take down operators
self.operator_identity.Input.disconnect()
self.operator_identity.Output.disconnect()
self.operator_identity.cleanUp()
self.operator_border.InputArray.disconnect()
self.operator_border.InputMask.disconnect()
self.operator_border.Output.disconnect()
self.operator_border.cleanUp()
class TestOpMaskArray3(object):
def setUp(self):
self.graph = Graph()
self.operator_border = OpMaskArray(graph=self.graph)
self.operator_identity = OpArrayPiper(graph=self.graph)
self.operator_border.InputArray.meta.axistags = vigra.AxisTags("txyzc")
self.operator_identity.Input.connect(self.operator_border.Output)
def test1(self):
# Generate a random dataset and see if it we get the right masking from the operator.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
mask = numpy.zeros(data.shape, dtype=bool)
# Mask borders of the expected output.
left_slicing = (mask.ndim - 1) * (slice(None), ) + (slice(None, 1), )
right_slicing = (mask.ndim - 1) * (slice(None), ) + (slice(-1, None), )
for i in xrange(mask.ndim):
left_slicing = left_slicing[-1:] + left_slicing[:-1]
right_slicing = right_slicing[-1:] + right_slicing[:-1]
mask[left_slicing] = True
mask[right_slicing] = True
expected_output = numpy.ma.masked_array(data, mask=mask, shrink=False)
# Provide input read all output.
self.operator_border.InputArray.setValue(data)
self.operator_border.InputMask.setValue(mask)
output = self.operator_identity.Output[None].wait()
assert ((expected_output == output).all())
assert (expected_output.mask.shape == output.mask.shape)
assert ((expected_output.mask == output.mask).all())
def test2(self):
# Generate a dataset and grab chunks of it from the operator. The result should be the same as above.
data = numpy.random.random((4, 5, 6, 7, 3)).astype(numpy.float32)
mask = numpy.zeros(data.shape, dtype=bool)
# Mask borders of the expected output.
left_slicing = (mask.ndim - 1) * (slice(None), ) + (slice(None, 1), )
right_slicing = (mask.ndim - 1) * (slice(None), ) + (slice(-1, None), )
for i in xrange(mask.ndim):
left_slicing = left_slicing[-1:] + left_slicing[:-1]
right_slicing = right_slicing[-1:] + right_slicing[:-1]
mask[left_slicing] = True
mask[right_slicing] = True
expected_output = numpy.ma.masked_array(data, mask=mask, shrink=False)
# Create array to store results. Don't keep original data.
output = expected_output.copy()
output[:] = 0
output[:] = numpy.ma.nomask
# Provide input and grab chunks.
self.operator_border.InputArray.setValue(data)
self.operator_border.InputMask.setValue(mask)
output[:2] = self.operator_identity.Output[:2].wait()
output[2:] = self.operator_identity.Output[2:].wait()
assert ((expected_output == output).all())
assert (expected_output.mask.shape == output.mask.shape)
assert ((expected_output.mask == output.mask).all())
def tearDown(self):
# Take down operators
self.operator_identity.Input.disconnect()
self.operator_identity.Output.disconnect()
self.operator_identity.cleanUp()
self.operator_border.InputArray.disconnect()
self.operator_border.InputMask.disconnect()
self.operator_border.Output.disconnect()
self.operator_border.cleanUp()