def test_surface_area_on_checkerboard():
"""Run surface area on checkerboard block"""
l = 50
img = generate_checkerboard(l)
sa = surface_area(img, phases=[0, 1])
assert sa == 1
def test_surface_area_interfactial_3ph():
l = 3
img = np.zeros([l, l, l])
img[1] = 1
img[2] = 2
sa = surface_area(img, phases=[1, 2])
assert sa == 1 / 6
def test_surface_area_on_empty_block():
"""Run surface area on empty block"""
l = 20
img = np.zeros([l, l, l])
sa = surface_area(img, phases=0)
assert sa == 0
def test_surface_area_on_uniform_block():
"""Run surface area on uniform block"""
l = 20
img = np.ones([l, l, l])
sa = surface_area(img, phases=1)
assert sa == 0
def test_surface_area_on_strip_of_ones():
"""Run surface area on single one in small 2x2z2 cube"""
l = 2
img = np.zeros([l, l, l])
t = 1
img[0, 0, 0] = 1
sa = surface_area(img, phases=[0, 1])
assert sa == 0.25
def vf_sa_metrics(batch_images):
"""
:param batch_images: a 4-dim or 3-dim array of images (batch_size x H x
W or batch_size x D x H x W)
:return: a list of the mean volume fractions of the different phases and
the interfacial surface area between every pair of phases.
"""
batch_size = batch_images.shape[0]
phases = np.unique(batch_images)
vf = np.mean([[(batch_images[j] == p).mean() for p in phases]
for j in range(batch_size)],
axis=0)
sa = np.mean([[
metrics.surface_area(batch_images[j], [ph1, ph2]).item()
for ph1, ph2 in combinations(phases, 2)
] for j in range(batch_size)],
axis=0)
return list(vf), list(sa)
def test_surface_area_on_periodic_2d():
"""Run surface area on a pair of one in small 3x3 square"""
img = np.array([[0, 0, 0], [1, 1, 0], [0, 0, 0]])
sa = surface_area(img, phases=[0, 1], periodic=[0, 1])
assert sa == 6 / 18