def test_greater_than_validator_creator():
"""Check the greater_than_validator creator raises
errors when start is not a number type"""
with pytest.raises(TypeError):
greater_than_validator("str")
with pytest.raises(TypeError):
greater_than_validator([])
def test_greater_than_validator():
""" Test the greater_than_validator with some values """
validator = greater_than_validator(100)
assert str(validator) == "Value(s) must be greater than 100"
assert validator(101)
assert validator(1000)
assert validator(float("inf"))
assert not validator(99)
assert not validator(100)
assert not validator(float("-inf"))
assert not validator("not a number")
def test_for_each_validator():
""" Test the for each validator """
validator = for_each_validator(greater_than_validator(0.5))
assert (
str(validator) == "Must be a list or tuple and for each value in the "
"list: Value(s) must be greater than 0.5")
assert validator([0.6, 0.7, 0.8])
assert validator((0.7, 0.51, 0.6))
assert not validator([0.5, 0.6, 0.7])
assert not validator([0.1, 100, 0.9])
assert not validator((0.7, 0.1, 0.6))
assert not validator("not a list or tuple")
def test_greater_than_validator_image_container():
""" Test the greater than validator with an image container """
validator = greater_than_validator(1.5)
assert str(validator) == "Value(s) must be greater than 1.5"
image_container = NumpyImageContainer(
image=np.array([[-0.5, 0.2], [0.1, -0.9]]))
assert not validator(image_container)
image_container = NumpyImageContainer(
image=np.array([[1.5, 2.2], [1.7, 90]]))
assert not validator(image_container)
image_container = NumpyImageContainer(
image=np.array([[1.51, 2.2], [1.7, 90]]))
assert validator(image_container)
default_value=0.0),
TRANSL_X:
Parameter(validators=range_inclusive_validator(-1000.0, 1000.0),
default_value=0.0),
TRANSL_Y:
Parameter(validators=range_inclusive_validator(-1000.0, 1000.0),
default_value=0.0),
TRANSL_Z:
Parameter(validators=range_inclusive_validator(-1000.0, 1000.0),
default_value=0.0),
ACQ_MATRIX:
Parameter(
validators=[
list_of_type_validator(int),
of_length_validator(3),
for_each_validator(greater_than_validator(0)),
],
default_value=[64, 64, 12],
),
}),
STRUCTURAL:
ParameterValidator(
parameters={
ECHO_TIME:
Parameter(validators=greater_than_validator(0),
default_value=0.005),
REPETITION_TIME:
Parameter(validators=greater_than_validator(0), default_value=0.3),
ROT_X:
Parameter(validators=range_inclusive_validator(-180.0, 180.0),
default_value=0.0),
def _validate_inputs(self):
"""Checks that the inputs meet their validation criteria
`'object'` must be derived from BaseImageContainer
`'target_shape'` (optional)must be a Tuple of ints of length 3, values > 0
`'rotation'` (optional) must be a Tuple of floats of length 3, each value -180 to 180
inclusive, default (optional) = (0.0, 0.0, 0.0)
`'rotation_origin'` (optional) must be a Tuple of floats of length 3,
default = (0.0, 0.0, 0.0)
`'translation'` (optional) must be a Tuple of floats of length 3, default = (0.0, 0.0, 0.0)
"""
input_validator = ParameterValidator(
parameters={
self.KEY_IMAGE:
Parameter(validators=isinstance_validator(BaseImageContainer)),
self.KEY_ROTATION:
Parameter(
validators=[
isinstance_validator(tuple),
for_each_validator(isinstance_validator(float)),
for_each_validator(range_inclusive_validator(
-180, 180)),
],
optional=True,
default_value=(0.0, 0.0, 0.0),
),
self.KEY_ROTATION_ORIGIN:
Parameter(
validators=[
isinstance_validator(tuple),
for_each_validator(isinstance_validator(float)),
],
optional=True,
default_value=(0.0, 0.0, 0.0),
),
self.KEY_TRANSLATION:
Parameter(
validators=[
isinstance_validator(tuple),
for_each_validator(isinstance_validator(float)),
],
optional=True,
default_value=(0.0, 0.0, 0.0),
),
self.KEY_TARGET_SHAPE:
Parameter(
validators=[
isinstance_validator(tuple),
for_each_validator(isinstance_validator(int)),
for_each_validator(greater_than_validator(0)),
],
optional=True,
default_value=(9999, 9999, 9999),
),
})
# validate, returning a dictionary which also includes default parameters
new_params = input_validator.validate(
self.inputs, error_type=FilterInputValidationError)
# Further validation that can't be handled by the parameter validator
if new_params[self.KEY_TARGET_SHAPE] == (9999, 9999, 9999):
new_params[self.KEY_TARGET_SHAPE] = self.inputs[
self.KEY_IMAGE].shape
# Check that the tuple self.KEY_ROTATION's length is 3
if len(new_params[self.KEY_ROTATION]) != 3:
raise FilterInputValidationError
# Check that the tuple self.KEY_ROTATION_ORIGIN's length is 3
if len(new_params[self.KEY_ROTATION_ORIGIN]) != 3:
raise FilterInputValidationError
# Check that the tuple self.KEY_TRANSLATION's length is 3
if len(new_params[self.KEY_TRANSLATION]) != 3:
raise FilterInputValidationError
# Check that the tuple self.KEY_SCALE's length is 3
if len(new_params[self.KEY_TARGET_SHAPE]) != 3:
raise FilterInputValidationError
# merge the updated parameters from the output with the input parameters
self.inputs = {**self._i, **new_params}