def test_spike():
""" Test if a convolution with a delta spike is equal to the kernel
saved in the lookup table."""
# create kernel
D33 = 1.0
D44 = 0.04
t = 1
num_orientations = 5
k = EnhancementKernel(D33,
D44,
t,
orientations=num_orientations,
force_recompute=True)
# create a delta spike
numorientations = k.get_orientations().shape[0]
spike = np.zeros((7, 7, 7, numorientations), dtype=np.float64)
spike[3, 3, 3, 0] = 1
# convolve kernel with delta spike
csd_enh = convolve_sf(spike, k, test_mode=True, normalize=False)
# check if kernel matches with the convolved delta spike
totalsum = 0.0
for i in range(0, numorientations):
totalsum += np.sum(np.array(k.get_lookup_table())[i, 0, :, :, :] - \
np.array(csd_enh)[:, :, :, i])
npt.assert_equal(totalsum, 0.0)
def test_spike():
""" Test if a convolution with a delta spike is equal to the kernel
saved in the lookup table."""
# create kernel
D33 = 1.0
D44 = 0.04
t = 1
num_orientations = 5
k = EnhancementKernel(D33, D44, t, orientations=num_orientations, force_recompute=True)
# create a delta spike
numorientations = k.get_orientations().shape[0]
spike = np.zeros((7, 7, 7, numorientations), dtype=np.float64)
spike[3, 3, 3, 0] = 1
# convolve kernel with delta spike
csd_enh = convolve_sf(spike, k, test_mode=True, normalize=False)
# check if kernel matches with the convolved delta spike
totalsum = 0.0
for i in range(0, numorientations):
totalsum += np.sum(np.array(k.get_lookup_table())[i, 0, :, :, :] - \
np.array(csd_enh)[:, :, :, i])
npt.assert_equal(totalsum, 0.0)
def test_kernel_input():
""" Test the kernel for inputs of type Sphere, type int and for input None"""
sph = Sphere(1, 0, 0)
D33 = 1.0
D44 = 0.04
t = 1
k = EnhancementKernel(D33, D44, t, orientations=sph, force_recompute=True)
npt.assert_equal(k.get_lookup_table().shape, (1, 1, 7, 7, 7))
num_orientations = 2
k = EnhancementKernel(D33, D44, t, orientations=num_orientations, force_recompute=True)
npt.assert_equal(k.get_lookup_table().shape, (2, 2, 7, 7, 7))
k = EnhancementKernel(D33, D44, t, orientations=0, force_recompute=True)
npt.assert_equal(k.get_lookup_table().shape, (0, 0, 7, 7, 7))
def test_kernel_input():
""" Test the kernel for inputs of type Sphere, type int and for input None"""
sph = Sphere(1, 0, 0)
D33 = 1.0
D44 = 0.04
t = 1
k = EnhancementKernel(D33, D44, t, orientations=sph, force_recompute=True)
npt.assert_equal(k.get_lookup_table().shape, (1, 1, 7, 7, 7))
num_orientations = 2
k = EnhancementKernel(D33,
D44,
t,
orientations=num_orientations,
force_recompute=True)
npt.assert_equal(k.get_lookup_table().shape, (2, 2, 7, 7, 7))
k = EnhancementKernel(D33, D44, t, orientations=0, force_recompute=True)
npt.assert_equal(k.get_lookup_table().shape, (0, 0, 7, 7, 7))
