def test_correlation_invalid_normalization(normalization):
reference_image = fft.fftn(camera())
shift = (-7, 12)
shifted_image = fourier_shift(reference_image, shift)
# pixel precision
with pytest.raises(ValueError):
phase_cross_correlation(reference_image,
shifted_image,
space="fourier",
normalization=normalization)
def test_wrong_input():
# Dimensionality mismatch
image = np.ones((5, 5, 1))
template = np.ones((5, 5))
with testing.raises(ValueError):
phase_cross_correlation(template, image)
# Size mismatch
image = np.ones((5, 5))
template = np.ones((4, 4))
with testing.raises(ValueError):
phase_cross_correlation(template, image)
def test_4d_input_pixel():
phantom = img_as_float(binary_blobs(length=32, n_dim=4))
reference_image = fft.fftn(phantom)
shift = (-2., 1., 5., -3)
shifted_image = fourier_shift(reference_image, shift)
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image,
space="fourier")
assert_allclose(result, -np.array(shift), atol=0.05)
def test_correlation():
reference_image = fft.fftn(camera())
shift = (-7, 12)
shifted_image = fourier_shift(reference_image, shift)
# pixel precision
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image,
space="fourier")
assert_allclose(result[:2], -np.array(shift))
def test_real_input():
reference_image = camera()
subpixel_shift = (-2.4, 1.32)
shifted_image = fourier_shift(fft.fftn(reference_image), subpixel_shift)
shifted_image = fft.ifftn(shifted_image)
# subpixel precision
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image, 100)
assert_allclose(result[:2], -np.array(subpixel_shift), atol=0.05)
def test_subpixel_precision():
reference_image = fft.fftn(camera())
subpixel_shift = (-2.4, 1.32)
shifted_image = fourier_shift(reference_image, subpixel_shift)
# subpixel precision
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image, 100,
space="fourier")
assert_allclose(result[:2], -np.array(subpixel_shift), atol=0.05)
def test_3d_input():
phantom = img_as_float(binary_blobs(length=32, n_dim=3))
reference_image = fft.fftn(phantom)
shift = (-2., 1., 5.)
shifted_image = fourier_shift(reference_image, shift)
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image,
space="fourier")
assert_allclose(result, -np.array(shift), atol=0.05)
# subpixel precision now available for 3-D data
subpixel_shift = (-2.3, 1.7, 5.4)
shifted_image = fourier_shift(reference_image, subpixel_shift)
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image,
upsample_factor=100,
space="fourier")
assert_allclose(result, -np.array(subpixel_shift), atol=0.05)
def test_correlation(normalization):
reference_image = fft.fftn(camera())
shift = (-7, 12)
shifted_image = fourier_shift(reference_image, shift)
# pixel precision
result, _, _ = phase_cross_correlation(reference_image,
shifted_image,
space="fourier",
normalization=normalization)
assert_allclose(result[:2], -np.array(shift))
def test_size_one_dimension_input():
# take a strip of the input image
reference_image = fft.fftn(camera()[:, 15]).reshape((-1, 1))
subpixel_shift = (-2.4, 4)
shifted_image = fourier_shift(reference_image, subpixel_shift)
# subpixel precision
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image, 20,
space="fourier")
assert_allclose(result[:2], -np.array((-2.4, 0)), atol=0.05)
def test_real_input(dtype):
reference_image = camera().astype(dtype, copy=False)
subpixel_shift = (-2.4, 1.32)
shifted_image = fourier_shift(fft.fftn(reference_image), subpixel_shift)
shifted_image = fft.ifftn(shifted_image).real.astype(dtype, copy=False)
# subpixel precision
result, error, diffphase = phase_cross_correlation(reference_image,
shifted_image,
upsample_factor=100)
assert result.dtype == _supported_float_type(dtype)
assert_allclose(result[:2], -np.array(subpixel_shift), atol=0.05)
def test_subpixel_precision(normalization):
reference_image = fft.fftn(camera())
subpixel_shift = (-2.4, 1.32)
shifted_image = fourier_shift(reference_image, subpixel_shift)
# subpixel precision
result, _, _ = phase_cross_correlation(reference_image,
shifted_image,
upsample_factor=100,
space="fourier",
normalization=normalization)
assert_allclose(result[:2], -np.array(subpixel_shift), atol=0.05)
def test_wrong_input():
# Dimensionality mismatch
image = np.ones((5, 5, 1))
template = np.ones((5, 5))
with pytest.raises(ValueError):
phase_cross_correlation(template, image)
# Size mismatch
image = np.ones((5, 5))
template = np.ones((4, 4))
with pytest.raises(ValueError):
phase_cross_correlation(template, image)
# NaN values in data
image = np.ones((5, 5))
image[0][0] = np.nan
template = np.ones((5, 5))
with pytest.raises(ValueError):
phase_cross_correlation(template, image, return_error=True)
def test_wrong_input():
# Dimensionality mismatch
image = np.ones((5, 5, 1))
template = np.ones((5, 5))
with pytest.raises(ValueError):
phase_cross_correlation(template, image)
# Size mismatch
image = np.ones((5, 5))
template = np.ones((4, 4))
with pytest.raises(ValueError):
phase_cross_correlation(template, image)
# NaN values in data
image = np.ones((5, 5))
image[0][0] = np.nan
template = np.ones((5, 5))
with expected_warnings([r'invalid value encountered in true_divide|\A\Z']):
with pytest.raises(ValueError):
phase_cross_correlation(template, image, return_error=True)
def test_unknown_space_input():
image = np.ones((5, 5))
with testing.raises(ValueError):
phase_cross_correlation(image, image, space="frank")
