def test_with_zero_intensity(self):
transform = RandomGhosting(intensity=0)
transformed = transform(self.sample_subject)
self.assertTensorAlmostEqual(
self.sample_subject.t1.data,
transformed.t1.data,
)
def test_with_ghosting(self):
transform = RandomGhosting()
transformed = transform(self.sample_subject)
self.assertTensorNotEqual(
self.sample_subject.t1.data,
transformed.t1.data,
)
def simulate_artefacts(sample, artefacts=(0, 0, 0, 0)):
transforms = []
if artefacts[0] == 1:
if random.random() < 0.5:
degrees = (5, random.random() * 10 + 5)
else:
degrees = (-(random.random() * 10 + 5), -5)
if random.random() < 0.5:
translation = (5, random.random() * 10 + 5)
else:
translation = (-(random.random() * 10 + 5), -5)
transforms.append(
RandomMotion(degrees=degrees,
translation=translation,
num_transforms=random.randint(2, 15)))
elif artefacts[1] == 1:
transforms.append(
RandomGhosting(num_ghosts=(2, 10), intensity=(0.5, 0.75)))
elif artefacts[2] == 1:
transforms.append(RandomBlur(std=(0.5, 2.)))
elif artefacts[3] == 1:
transforms.append(RandomNoise(std=(0.01, 0.05)))
transforms = Compose(transforms)
return transforms(sample)
def test_out_of_range_restore(self):
with self.assertRaises(ValueError):
RandomGhosting(restore=-1.)
def test_wrong_axes_type(self):
with self.assertRaises(ValueError):
RandomGhosting(axes=None)
def test_out_of_range_axis_in_tuple(self):
with self.assertRaises(ValueError):
RandomGhosting(axes=(0, -1, 2))
def test_out_of_range_axis(self):
with self.assertRaises(ValueError):
RandomGhosting(axes=3)
def test_wrong_num_ghosts_type(self):
with self.assertRaises(ValueError):
RandomGhosting(num_ghosts='wrong')
def test_not_integer_num_ghosts(self):
with self.assertRaises(ValueError):
RandomGhosting(num_ghosts=(0.7, 4))
def test_negative_num_ghosts(self):
with self.assertRaises(ValueError):
RandomGhosting(num_ghosts=-1)
def test_wrong_intensity_type(self):
with self.assertRaises(ValueError):
RandomGhosting(intensity='wrong')
def test_intensity_range_with_negative_min(self):
with self.assertRaises(ValueError):
RandomGhosting(intensity=(-0.5, 4))
def test_with_ghosting(self):
transform = RandomGhosting()
transformed = transform(self.sample)
with self.assertRaises(AssertionError):
assert_array_equal(self.sample.t1.data, transformed.t1.data)
def test_with_zero_ghost(self):
transform = RandomGhosting(num_ghosts=0)
transformed = transform(self.sample)
assert_array_equal(self.sample.t1.data, transformed.t1.data)
def test_with_zero_ghost(self):
transform = RandomGhosting(num_ghosts=0)
transformed = transform(self.sample)
self.assertTensorAlmostEqual(self.sample.t1.data, transformed.t1.data)
def test_wrong_restore_type(self):
with self.assertRaises(TypeError):
RandomGhosting(restore='wrong')
def test_with_zero_intensity(self):
transform = RandomGhosting(intensity=0)
transformed = transform(self.sample)
assert_array_equal(self.sample.t1.data, transformed.t1.data)
def test_num_ghosts_range_with_negative_min(self):
with self.assertRaises(ValueError):
RandomGhosting(num_ghosts=(-1, 4))