def test_output_shape(self, class_args, img_shape):
key = "img"
bias_field = RandBiasFieldd(keys=[key], **class_args)
img = np.random.rand(*img_shape)
output = bias_field({key: img})
np.testing.assert_equal(output[key].shape, img_shape)
np.testing.assert_equal(output[key].dtype, bias_field.rand_bias_field.dtype)
def test_one_range_input(self, class_args, expected):
key = "img"
bias_field = RandBiasFieldd(keys=[key], **class_args)
img = np.ones([1, 2, 2])
output = bias_field({key: img})
np.testing.assert_allclose(output[key],
expected.astype(
bias_field.rand_bias_field.dtype),
rtol=1e-3)
def test_zero_prob(self):
key = "img"
bias_field = RandBiasFieldd(keys=[key], prob=0.0)
img = np.random.rand(3, 32, 32)
output = bias_field({key: img})
np.testing.assert_equal(output[key], img)
def test_zero_range(self, class_args, img_shape):
key = "img"
bias_field = RandBiasFieldd(keys=[key], **class_args)
img = np.ones(img_shape)
output = bias_field({key: img})
np.testing.assert_allclose(output[key], np.ones(img_shape))