def clear_namespace(self, interpreter, project):
if project is None:
return
sys.path = self.old_syspath
for k in project.ns.keys() + ['world', 'data', 'project']:
if k in interpreter.user_ns:
del interpreter.user_ns[k]
from openalea.core.world import World
world = World()
world.clear()
def add_objects_then_attributes():
world = World()
world["obj1"] = 1
world["obj2"] = 2
obj1 = world["obj1"]
obj2 = world["obj2"]
obj1.set_attribute('a1', 1, 'IInt', constraints=c1)
obj1.set_attribute('a2', True, 'IBool')
obj2.set_attribute('b1', 2.34, 'IFloat', constraints=c2)
def add_objects_with_attributes_set():
"""
Attributes are defined before adding object to world.
Results is less signals sent by world
"""
world = World()
world.clear()
obj1 = WorldObject("obj1", 1)
obj2 = WorldObject("obj2", 2)
obj1.set_attribute('a1', 1, 'IInt', constraints=c1)
obj1.set_attribute('a2', True, 'IBool')
obj2.set_attribute('b1', 2.34, 'IFloat', constraints=c2)
world["obj1"] = obj1
world["obj2"] = obj2
def update_namespace(self, interpreter):
"""
Definition: Update namespace
"""
if self._cproject:
if self._cproject.path.exists():
os.chdir(self._cproject.path)
sys.path.insert(0, str(self._cproject.path / 'lib'))
else:
os.chdir(self.tmpdir)
sys.path.insert(0, str(self.tmpdir / 'lib'))
interpreter.user_ns.update(self._cproject.ns)
interpreter.user_ns['project'] = self._cproject
interpreter.user_ns['data'] = self._cproject.path / 'data'
from openalea.core.world import World
world = World()
world.update_namespace(interpreter)
def setUp(self):
ev.events
self.world = World()
self.world.register_listener(ev)
def nuclei_active_region_segmentation(input_img,
positions,
omega_energies=dict(intensity=1.0,
gradient=1.5,
smoothness=10000.0),
intensity_min=20000.,
iterations=10,
display=False):
"""
3D extension of the multiple region extension of the binary level set implementation
"""
segmentation_start_time = time()
print "--> Active region segmentation (", len(positions), " regions )"
from copy import deepcopy
reference_img = deepcopy(input_img)
size = np.array(reference_img.shape)
voxelsize = np.array(reference_img.voxelsize)
if display:
from openalea.core.world import World
world = World()
if omega_energies.has_key('gradient'):
from scipy.ndimage.filters import gaussian_gradient_magnitude
start_time = time()
print " --> Computing image gradient"
gradient = gaussian_gradient_magnitude(
np.array(reference_img, np.float64),
sigma=0.5 / np.array(reference_img.voxelsize))
gradient_img = SpatialImage(np.array(gradient, np.uint16),
voxelsize=reference_img.voxelsize)
end_time = time()
print " <-- Computing image gradient [", end_time - start_time, " s]"
start_time = time()
print " --> Creating seed image"
print positions.keys()
seed_img = seed_image_from_points(size,
voxelsize,
positions,
point_radius=1.0)
regions_img = np.copy(seed_img)
end_time = time()
print " <-- Creating seed image (", len(np.unique(
regions_img)) - 1, " regions ) [", end_time - start_time, " s]"
if display:
world.add(seed_img,
'active_regions_seeds',
colormap='glasbey',
voxelsize=voxelsize,
alphamap='constant',
volume=False,
cut_planes=True)
raw_input()
for iteration in xrange(iterations):
start_time = time()
print " --> Active region energy gradient descent : iteration", iteration, " (", len(
np.unique(regions_img)) - 1, " regions )"
previous_regions_img = np.copy(regions_img)
regions_img = active_regions_energy_gradient_descent(
regions_img,
reference_img,
omega_energies=omega_energies,
intensity_min=intensity_min,
gradient_img=gradient)
change = ((regions_img - previous_regions_img) != 0.).sum() / float(
(regions_img > 1.).sum())
end_time = time()
print " --> Active region energy gradient descent : iteration", iteration, " (Evolution : ", int(
100 * change), " %) ", "[", end_time - start_time, " s]"
if display:
world.add(regions_img,
'active_regions',
colormap='invert_grey',
voxelsize=voxelsize,
intensity_range=(1, 2))
segmented_img = SpatialImage(regions_img,
voxelsize=reference_img.voxelsize)
if display:
world.add(segmented_img,
'active_regions',
colormap='glasbey',
voxelsize=voxelsize,
alphamap='constant')
raw_input()
segmentation_end_time = time()
print "<-- Active region segmentation (", len(
np.unique(segmented_img)
) - 1, " regions ) [", segmentation_end_time - segmentation_start_time, " s]"
return segmented_img
def initialize(self):
self.world = World()
self.world.register_listener(self)
