def tst_with_no_points(self):
from dials.model.data import PixelList, PixelListLabeller
from scitbx.array_family import flex
size = (500, 500)
sf = 0
labeller = PixelListLabeller()
count = 0
mask_list = []
for i in range(3):
image = flex.random_int_gaussian_distribution(
size[0] * size[1], 100, 5)
mask = flex.bool(size[0] * size[0], False)
image.reshape(flex.grid(size))
mask.reshape(flex.grid(size))
pl = PixelList(sf + i, image, mask)
count += len(mask.as_1d().select(mask.as_1d()))
labeller.add(pl)
mask_list.append(mask)
coords = labeller.coords()
labels1 = labeller.labels_2d()
labels2 = labeller.labels_2d()
assert len(coords) == 0
assert len(labels1) == 0
assert len(labels2) == 0
print 'OK'
def setup_class(self):
from dials.algorithms.image.connected_components import LabelImageStack3d
self.size = (500, 500)
self.label_images = LabelImageStack3d(self.size)
from scitbx.array_family import flex
self.data_list = []
self.mask_list = []
for i in range(10):
data = flex.random_int_gaussian_distribution(
self.size[0] * self.size[1], 100, 10
)
data.reshape(flex.grid(self.size))
mask = flex.random_bool(self.size[0] * self.size[1], 0.1)
mask.reshape(flex.grid(self.size))
self.data_list.append(data)
self.mask_list.append(mask)
for i in range(10):
self.label_images.add_image(self.data_list[i], self.mask_list[i])
self.labels = self.label_images.labels()
self.coords = self.label_images.coords()
self.values = list(self.label_images.values())
assert len(self.labels) > 0
assert len(self.labels) == len(self.coords)
assert len(self.labels) == len(self.values)
def create_random_data_with_gaussian_distribution(mu=0.0, sigma=1.0):
slow = 2048
fast = 2048
total_sz = slow * fast
random_data = flex.random_int_gaussian_distribution(total_sz, mu, sigma)
random_data.reshape(flex.grid(slow, fast))
return random_data
def run(self):
from scitbx.array_family import flex
data_list = []
mask_list = []
for i in range(10):
data = flex.random_int_gaussian_distribution(
self.size[0] * self.size[1], 100, 10)
data.reshape(flex.grid(self.size))
mask = flex.random_bool(self.size[0] * self.size[1], 0.1)
mask.reshape(flex.grid(self.size))
data_list.append(data)
mask_list.append(mask)
for i in range(10):
self.label_images.add_image(data_list[i], mask_list[i])
labels = self.label_images.labels()
coords = self.label_images.coords()
values = self.label_images.values()
assert(len(labels) > 0)
assert(len(labels) == len(coords))
assert(len(labels) == len(values))
self.tst_coords_are_valid(mask_list, coords)
self.tst_values_are_valid(data_list, mask_list, values)
self.tst_labels_are_valid(data_list, mask_list, coords, labels)
def create_random_data_with_gaussian_distribution(mu=0.0,sigma=1.0): slow=2048 fast=2048 total_sz = slow*fast random_data = flex.random_int_gaussian_distribution(total_sz,mu,sigma) random_data.reshape(flex.grid(slow,fast)) return random_data
def tst_labels_3d(self):
from dials.model.data import PixelList, PixelListLabeller
from scitbx.array_family import flex
size = (500, 500)
sf = 0
labeller = PixelListLabeller()
count = 0
mask_list = []
for i in range(3):
image = flex.random_int_gaussian_distribution(
size[0] * size[1], 100, 5)
mask = flex.random_bool(size[0] * size[1], 0.5)
image.reshape(flex.grid(size))
mask.reshape(flex.grid(size))
pl = PixelList(sf + i, image, mask)
count += len(mask.as_1d().select(mask.as_1d()))
labeller.add(pl)
mask_list.append(mask)
coords = labeller.coords()
labels = labeller.labels_3d()
# Create a map of labels
label_map = flex.int(flex.grid(3, size[0], size[1]))
for c, l in zip(coords, labels):
label_map[c] = l
# Ensure all labels are correct
vi = 0
for k in range(3):
for j in range(size[0]):
for i in range(size[1]):
if mask_list[k][j, i]:
l1 = labels[vi]
if k > 0 and mask_list[k - 1][j, i]:
l2 = label_map[k - 1, j, i]
assert (l2 == l1)
if j > 0 and mask_list[k][j - 1, i]:
l2 = label_map[k, j - 1, i]
assert (l2 == l1)
if i > 0 and mask_list[k][j, i - 1]:
l2 = label_map[k, j, i - 1]
assert (l2 == l1)
vi += 1
# Test passed
print 'OK'
def test_add_image():
from dials.model.data import PixelList, PixelListLabeller
from scitbx.array_family import flex
size = (2000, 2000)
sf = 10
labeller = PixelListLabeller()
count = 0
for i in range(3):
image = flex.random_int_gaussian_distribution(size[0] * size[1], 100,
5)
mask = flex.random_bool(size[0] * size[1], 0.5)
image.reshape(flex.grid(size))
mask.reshape(flex.grid(size))
pl = PixelList(sf + i, image, mask)
count += len(mask.as_1d().select(mask.as_1d()))
labeller.add(pl)
assert len(labeller.values()) == count
