def add_dataset(dataset, name='', **kwargs):
"""Add a dataset object to the Mayavi pipeline.
**Parameters**
:dataset: a tvtk/vtk dataset/tvtk/VTK Algorithm, or a Mayavi source. The
dataset added to the Mayavi pipeline
:figure: a figure identifier number or string, None or False, optional.
If no `figure` keyword argument is given, the data
is added to the current figure (a new figure if created if
necessary).
If a `figure` keyword argument is given, it should either the name
the number of the figure the dataset should be added to, or None,
in which case the data is not added to the pipeline.
If figure is False, a null engine is created. This null
engine does not create figures, and is mainly usefull for
tensting, or using the VTK algorithms without visualization.
**Returns**
The corresponding Mayavi source is returned.
"""
if isinstance(dataset, (tvtk.DataSet, vtk.vtkDataSet)):
d = VTKDataSource()
d.data = tvtk.to_tvtk(dataset)
elif isinstance(dataset, (tvtk.DataObject, vtk.vtkDataObject)):
d = VTKObjectSource()
tp = tvtk.TrivialProducer()
tp.set_output(tvtk.to_tvtk(dataset))
d.object = tp
elif isinstance(dataset, (tvtk.Object, vtk.vtkObject)):
d = VTKObjectSource()
d.object = tvtk.to_tvtk(dataset)
elif isinstance(dataset, Source):
d = dataset
else:
raise TypeError(
"first argument should be either a TVTK object"
" or a mayavi source")
if len(name) > 0:
d.name = name
engine = _get_engine_from_kwarg(kwargs)
if engine is None:
# Return early, as we don't want to add the source to an engine.
return d
engine.add_source(d)
return d
def add_dataset(dataset, name='', **kwargs):
"""Add a dataset object to the Mayavi pipeline.
**Parameters**
:dataset: a tvtk/vtk dataset/tvtk/VTK Algorithm, or a Mayavi source. The
dataset added to the Mayavi pipeline
:figure: a figure identifier number or string, None or False, optionnal.
If no `figure` keyword argument is given, the data
is added to the current figure (a new figure if created if
necessary).
If a `figure` keyword argument is given, it should either the name
the number of the figure the dataset should be added to, or None,
in which case the data is not added to the pipeline.
If figure is False, a null engine is created. This null
engine does not create figures, and is mainly usefull for
tensting, or using the VTK algorithms without visualization.
**Returns**
The corresponding Mayavi source is returned.
"""
if isinstance(dataset, (tvtk.DataSet, vtk.vtkDataSet)):
d = VTKDataSource()
d.data = tvtk.to_tvtk(dataset)
elif isinstance(dataset, (tvtk.DataObject, vtk.vtkDataObject)):
d = VTKObjectSource()
tp = tvtk.TrivialProducer()
tp.set_output(tvtk.to_tvtk(dataset))
d.object = tp
elif isinstance(dataset, (tvtk.Object, vtk.vtkObject)):
d = VTKObjectSource()
d.object = tvtk.to_tvtk(dataset)
elif isinstance(dataset, Source):
d = dataset
else:
raise TypeError(
"first argument should be either a TVTK object"
" or a mayavi source")
if len(name) > 0:
d.name = name
engine = _get_engine_from_kwarg(kwargs)
if engine is None:
# Return early, as we don't want to add the source to an engine.
return d
engine.add_source(d)
return d
def add_attribute(self, array, name, category='point'):
"""Add an attribute to the dataset to specified category ('point' or
'cell').
One may add a scalar, vector (3/4 components) or a tensor (9
components).
Note that it is the user's responsibility to set the correct size of
the arrays. Also no automatic transposing of the data is done.
Parameters
----------
array: numpy array/list : array data to add.
name: str: name of the array.
category: 'point'/'cell': the category of the attribute data.
"""
array = np.asarray(array)
assert len(array.shape) <= 2, "Only 2D arrays can be added."
data = getattr(self.image_data, '%s_data' % category)
if len(array.shape) == 2:
assert array.shape[1] in [1, 3, 4, 9], \
"Only N x m arrays where (m in [1,3,4,9]) are supported"
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
def add_attribute(self, array, name, category='point'):
"""Add an attribute to the dataset to specified category ('point' or
'cell').
One may add a scalar, vector (3/4 components) or a tensor (9
components).
Note that it is the user's responsibility to set the correct size of
the arrays. Also no automatic transposing of the data is done.
Parameters
----------
array: numpy array/list : array data to add.
name: str: name of the array.
category: 'point'/'cell': the category of the attribute data.
"""
array = np.asarray(array)
assert len(array.shape) <= 2, "Only 2D arrays can be added."
data = getattr(self.image_data, '%s_data' % category)
if len(array.shape) == 2:
assert array.shape[1] in [1, 3, 4, 9], \
"Only N x m arrays where (m in [1,3,4,9]) are supported"
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
def test_to_tvtk_returns_tvtk_object(self):
# Given
v = vtk.vtkContourFilter()
# When
x = tvtk.to_tvtk(v)
# Then
self.assertEqual(x.class_name, 'vtkContourFilter')
self.assertTrue(isinstance(x, tvtk_base.TVTKBase))
self.assertTrue(isinstance(x, tvtk.ContourFilter))
self.assertTrue(v is x._vtk_obj)
def set_arrays(dataset, particle_array):
""" Code to add all the arrays to a dataset given a particle array."""
props = set(particle_array.properties.keys())
# Add the vector data.
vec = numpy.empty((len(particle_array.x), 3), dtype=float)
vec[:,0] = particle_array.u
vec[:,1] = particle_array.v
vec[:,2] = particle_array.w
va = tvtk.to_tvtk(array2vtk(vec))
va.name = 'velocity'
dataset.data.point_data.add_array(vec)
# Now add the scalar data.
scalars = props - set(('u', 'v', 'w'))
for sc in scalars:
arr = particle_array.get(sc)
va = tvtk.to_tvtk(array2vtk(arr))
va.name = sc
dataset.data.point_data.add_array(va)
dataset._update_data()
def set_arrays(dataset, particle_array):
""" Code to add all the arrays to a dataset given a particle array."""
props = set(particle_array.properties.keys())
# Add the vector data.
vec = numpy.empty((len(particle_array.x), 3), dtype=float)
vec[:, 0] = particle_array.u
vec[:, 1] = particle_array.v
vec[:, 2] = particle_array.w
va = tvtk.to_tvtk(array2vtk(vec))
va.name = 'velocity'
dataset.data.point_data.add_array(vec)
# Now add the scalar data.
scalars = props - set(('u', 'v', 'w'))
for sc in scalars:
arr = particle_array.get(sc)
va = tvtk.to_tvtk(array2vtk(arr))
va.name = sc
dataset.data.point_data.add_array(va)
dataset._update_data()
def intersect_line(self, lineP0, lineP1):
''' 计算与线段相交的交点，这里调用了tvtk的方法
lineP0: 线段的第一个点，长度3的数组
lineP1: 线段的第二个点
return
points: 所有的交点坐标
cell_ids: 每个交点所属的面片ID '''
intersectPoints = tvtk.to_vtk(tvtk.Points())
intersectCells = tvtk.to_vtk(tvtk.IdList())
self._obb_tree.intersect_with_line(lineP0, lineP1, intersectPoints,
intersectCells)
intersectPoints = tvtk.to_tvtk(intersectPoints)
intersectCells = tvtk.to_tvtk(intersectCells)
points = intersectPoints.to_array()
cell_ids = [
intersectCells.get_id(i)
for i in range(intersectCells.number_of_ids)
]
return points, cell_ids
def test_to_tvtk_returns_tvtk_object(self):
# Given
v = vtk.vtkContourFilter()
# When
x = tvtk.to_tvtk(v)
# Then
self.assertEqual(x.class_name, 'vtkContourFilter')
self.assertTrue(isinstance(x, tvtk_base.TVTKBase))
self.assertTrue(isinstance(x, tvtk.ContourFilter))
self.assertTrue(v is x._vtk_obj)
def on_pick(self, vtk_picker, event):
""" Dispatch the pick to the callback associated with the
corresponding mouse button.
"""
picker = tvtk.to_tvtk(vtk_picker)
for event_type, event_picker in self._active_pickers.items():
if picker is event_picker:
for callback, type, button in self.callbacks:
if (type == event_type and button == self._current_button):
callback(picker)
break
def on_pick(self, vtk_picker, event):
""" Dispatch the pick to the callback associated with the
corresponding mouse button.
"""
picker = tvtk.to_tvtk(vtk_picker)
for event_type, event_picker in self._active_pickers.iteritems():
if picker is event_picker:
for callback, type, button in self.callbacks:
if ( type == event_type
and button == self._current_button):
callback(picker)
break
def _create_control(self, parent):
""" Create the toolkit-specific control that represents the widget. """
# Create the VTK widget.
self._vtk_control = window = FlatInteractor(self,
parent,
stereo=self.stereo)
# Switch the default interaction style to the trackball one.
window.GetInteractorStyle().SetCurrentStyleToTrackballCamera()
# Grab the renderwindow.
renwin = self._renwin = tvtk.to_tvtk(window.GetRenderWindow())
renwin.set(point_smoothing=self.point_smoothing,
line_smoothing=self.line_smoothing,
polygon_smoothing=self.polygon_smoothing)
# Create a renderer and add it to the renderwindow
self._renderer = tvtk.Renderer()
renwin.add_renderer(self._renderer)
# Save a reference to our camera so it is not GC'd -- needed for
# the sync_traits to work.
self._camera = self.camera
# Sync various traits.
self._renderer.background = self.background
self.sync_trait('background', self._renderer)
self.renderer.on_trait_change(self.render, 'background')
renwin.off_screen_rendering = self.off_screen_rendering
self._camera.parallel_projection = self.parallel_projection
self.sync_trait('parallel_projection', self._camera)
self.sync_trait('off_screen_rendering', self._renwin)
self.render_window.on_trait_change(self.render,
'off_screen_rendering')
self.render_window.on_trait_change(self.render, 'stereo_render')
self.render_window.on_trait_change(self.render, 'stereo_type')
self.camera.on_trait_change(self.render, 'parallel_projection')
self._interactor = tvtk.to_tvtk(window._Iren)
return window
def test_to_tvtk_wraps_subclass_of_vtk(self):
# Given
class MyAlgorithm(vtk.vtkPythonAlgorithm):
pass
a = MyAlgorithm()
# When
ta = tvtk.to_tvtk(a)
# Then
self.assertTrue(isinstance(ta, tvtk.PythonAlgorithm))
# Given
class B(MyAlgorithm):
pass
b = B()
# When
tb = tvtk.to_tvtk(b)
# Then
self.assertTrue(isinstance(tb, tvtk.PythonAlgorithm))
def add_array(self, array, name, category='point'):
"""
Add an array to the dataset to specified category ('point' or
'cell').
"""
assert len(array.shape) <= 2, "Only 2D arrays can be added."
data = getattr(self.dataset, '%s_data' % category)
if len(array.shape) == 2:
assert array.shape[1] in [1, 3, 4, 9], \
"Only Nxm arrays where (m in [1,3,4,9]) are supported"
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
mapping = {1: 'scalars', 3: 'vectors', 4: 'scalars', 9: 'tensors'}
dict = getattr(self, '%s_%s' % (category, mapping[array.shape[1]]))
dict[name] = array
else:
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
dict = getattr(self, '%s_scalars' % (category))
dict[name] = array
def test_to_tvtk_wraps_subclass_of_vtk(self):
# Given
class MyAlgorithm(vtk.vtkPythonAlgorithm):
pass
a = MyAlgorithm()
# When
ta = tvtk.to_tvtk(a)
# Then
self.assertTrue(isinstance(ta, tvtk.PythonAlgorithm))
# Given
class B(MyAlgorithm):
pass
b = B()
# When
tb = tvtk.to_tvtk(b)
# Then
self.assertTrue(isinstance(tb, tvtk.PythonAlgorithm))
def add_attribute(self, array, name, category='point'):
"""Add an attribute to the dataset to specified category ('point' or
'cell').
One may add a scalar, vector (3/4 components) or a tensor (9 components).
Note that it is the user's responsibility to set the correct size of
the arrays.
Parameters
----------
array: numpy array/list : array data to add.
name: str: name of the array.
category: 'point'/'cell': the category of the attribute data.
"""
array = np.asarray(array)
assert len(array.shape) <= 2, "Only 2D arrays can be added."
data = getattr(self.data, '%s_data' % category)
if len(array.shape) == 2:
assert array.shape[1] in [1, 3, 4, 9], \
"Only Nxm arrays where (m in [1,3,4,9]) are supported"
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
mapping = {1: 'scalars', 3: 'vectors', 4: 'scalars',
9: 'tensors'}
attribute = '_%s_%s_list' % (category, mapping[array.shape[1]])
else:
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
attribute = '_%s_scalars_list' % category
names = set(getattr(self, attribute) + [name])
setattr(self, attribute, sorted(names))
def _create_control(self, parent):
""" Create the toolkit-specific control that represents the widget. """
# Create the VTK widget.
self._vtk_control = window = _VTKRenderWindowInteractor(
self, parent, stereo=self.stereo)
# Switch the default interaction style to the trackball one.
window.GetInteractorStyle().SetCurrentStyleToTrackballCamera()
# Grab the renderwindow.
renwin = self._renwin = tvtk.to_tvtk(window.GetRenderWindow())
renwin.set(point_smoothing=self.point_smoothing,
line_smoothing=self.line_smoothing,
polygon_smoothing=self.polygon_smoothing)
# Create a renderer and add it to the renderwindow
self._renderer = tvtk.Renderer()
renwin.add_renderer(self._renderer)
# Save a reference to our camera so it is not GC'd -- needed for
# the sync_traits to work.
self._camera = self.camera
# Sync various traits.
self._renderer.background = self.background
self.sync_trait('background', self._renderer)
self.renderer.on_trait_change(self.render, 'background')
renwin.off_screen_rendering = self.off_screen_rendering
self._camera.parallel_projection = self.parallel_projection
self.sync_trait('parallel_projection', self._camera)
self.sync_trait('off_screen_rendering', self._renwin)
self.render_window.on_trait_change(self.render, 'off_screen_rendering')
self.render_window.on_trait_change(self.render, 'stereo_render')
self.render_window.on_trait_change(self.render, 'stereo_type')
self.camera.on_trait_change(self.render, 'parallel_projection')
self._interactor = tvtk.to_tvtk(window._Iren)
return window
def on_key_down(iren_style, key):
rendrr = iren_style.GetCurrentRenderer()
rendrr = tvtk.to_tvtk(rendrr)
if key == '+':
for act in rendrr.actors:
act.property.point_size *= 1.1
elif key == '-':
for act in rendrr.actors:
act.property.point_size /= 1.1
elif key == 's':
ren_win = rendrr.render_window
w2if = tvtk.WindowToImageFilter(input=ren_win)
w2if.update()
writer = tvtk.PNGWriter(file_name=snapshot_file, input=w2if.output)
writer.write()
def add_array(self, array, name, category='point'):
"""
Add an array to the dataset to specified category ('point' or
'cell').
"""
assert len(array.shape) <= 2, "Only 2D arrays can be added."
data = getattr(self.dataset, '%s_data'%category)
if len(array.shape) == 2:
assert array.shape[1] in [1, 3, 4, 9], \
"Only Nxm arrays where (m in [1,3,4,9]) are supported"
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
mapping = {1:'scalars', 3: 'vectors', 4: 'scalars',
9: 'tensors'}
dict = getattr(self, '%s_%s'%(category,
mapping[array.shape[1]]))
dict[name] = array
else:
va = tvtk.to_tvtk(array2vtk(array))
va.name = name
data.add_array(va)
dict = getattr(self, '%s_scalars'%(category))
dict[name] = array
def display_3d_array(array_3d, color_map, figure):
'''
Method displays 3d array.
Param:
array_3d - np.array
attenmap - np.array
'''
cm = color_map
# Dislay 3D Array Rendering
v = figure
for j in range(len(array_3d)):
c = tuple(cm[j])
# Coordinate Information
xx, yy, zz = np.where(array_3d[j] > 0.0)
xx *= 100
yy *= 100
zz *= 100
# Generate Voxels For Protein
append_filter = vtk.vtkAppendPolyData()
for i in range(len(xx)):
input1 = vtk.vtkPolyData()
voxel_source = vtk.vtkCubeSource()
voxel_source.SetCenter(xx[i], yy[i], zz[i])
voxel_source.SetXLength(100)
voxel_source.SetYLength(100)
voxel_source.SetZLength(100)
voxel_source.Update()
input1.ShallowCopy(voxel_source.GetOutput())
append_filter.AddInputData(input1)
append_filter.Update()
# Remove Any Duplicate Points.
clean_filter = vtk.vtkCleanPolyData()
clean_filter.SetInputConnection(append_filter.GetOutputPort())
clean_filter.Update()
# Render Voxels
pd = tvtk.to_tvtk(clean_filter.GetOutput())
cube_mapper = tvtk.PolyDataMapper()
configure_input_data(cube_mapper, pd)
p = tvtk.Property(opacity=1.0, color=c)
cube_actor = tvtk.Actor(mapper=cube_mapper, property=p)
v.scene.add_actor(cube_actor)
def _picker_callback(self, picker_obj, evt):
# test
print 'come in the picker callback'
picker_obj = tvtk.to_tvtk(picker_obj)
tmp_pos = picker_obj.picked_positions.to_array()
# test
print tmp_pos
if len(tmp_pos):
distance = np.sum(np.abs(self.coords - tmp_pos[0]), axis=1)
picked_id = np.argmin(distance)
tmp_lut = self.rgba_lut.copy()
self._toggle_color(tmp_lut[picked_id])
self.surf.module_manager.scalar_lut_manager.lut.table = tmp_lut
image.origin=nii.affine[0:3,3] vImage=tvtk.to_vtk(image) vPD=vImage.GetPointData() vSC=vPD.GetScalars() data=numpy_support.vtk_to_numpy(vSC) indxs=np.unique(data) for ind in indxs[1:]: print ind tmp=data.copy() tmp[tmp!=ind]=0 tmp[tmp==ind]=1 vPD.SetScalars(numpy_support.numpy_to_vtk(tmp)) image=tvtk.to_tvtk(vImage) iso=tvtk.MarchingCubes() iso.set_input_data(image) iso.set_value(0,0.5) iso.update() smoother = tvtk.SmoothPolyDataFilter() smoother.convergence=0 smoother.number_of_iterations=30 smoother.relaxation_factor=0.1 smoother.feature_angle=60 smoother.feature_edge_smoothing=True smoother.boundary_smoothing=True smoother.set_input_data_object(iso.get_output_data_object(0)) smoother.update()
def display_3d_model(array_3d, pointcloud=None, centroids=None):
'''
Method renders space-filling atomic model of PDB data.
Param:
pdb_data - np.array ; mulitchanneled pdb atom coordinates
skeletal - boolean ; if true shows model without radial information
attenmap - np.array
'''
# Dislay 3D Mesh Rendering
v = mlab.figure(bgcolor=(1.0,1.0,1.0))
if array_3d is not None:
# Color Mapping
n = len(array_3d)
cm = [winter(float(i)/n)[:3] for i in range(n)]
for j in range(len(array_3d)):
c = tuple(cm[j])
# Coordinate Information
xx, yy, zz = np.where(array_3d[j] > 0.0)
xx = xx.astype('float') - ((resolution * array_3d.shape[1])/2.0)
yy = yy.astype('float') - ((resolution * array_3d.shape[1])/2.0)
zz = zz.astype('float') - ((resolution * array_3d.shape[1])/2.0)
# Generate Voxels For Protein
append_filter = vtk.vtkAppendPolyData()
for i in range(len(xx)):
input1 = vtk.vtkPolyData()
voxel_source = vtk.vtkCubeSource()
voxel_source.SetCenter(xx[i],yy[i],zz[i])
voxel_source.SetXLength(1)
voxel_source.SetYLength(1)
voxel_source.SetZLength(1)
voxel_source.Update()
input1.ShallowCopy(voxel_source.GetOutput())
append_filter.AddInputData(input1)
append_filter.Update()
# Remove Any Duplicate Points.
clean_filter = vtk.vtkCleanPolyData()
clean_filter.SetInputConnection(append_filter.GetOutputPort())
clean_filter.Update()
# Render Voxels
pd = tvtk.to_tvtk(clean_filter.GetOutput())
cube_mapper = tvtk.PolyDataMapper()
configure_input_data(cube_mapper, pd)
p = tvtk.Property(opacity=1.0, color=c)
cube_actor = tvtk.Actor(mapper=cube_mapper, property=p)
v.scene.add_actor(cube_actor)
if pointcloud is not None:
# Generate Voxels For Pointcloud
append_filter = vtk.vtkAppendPolyData()
for i in range(len(pointcloud)):
input1 = vtk.vtkPolyData()
voxel_source = vtk.vtkCubeSource()
voxel_source.SetCenter(pointcloud[i][0],pointcloud[i][1], pointcloud[i][2])
voxel_source.SetXLength(1)
voxel_source.SetYLength(1)
voxel_source.SetZLength(1)
voxel_source.Update()
input1.ShallowCopy(voxel_source.GetOutput())
append_filter.AddInputData(input1)
append_filter.Update()
# Remove Any Duplicate Points.
clean_filter = vtk.vtkCleanPolyData()
clean_filter.SetInputConnection(append_filter.GetOutputPort())
clean_filter.Update()
# Render Voxels
pd = tvtk.to_tvtk(clean_filter.GetOutput())
cube_mapper = tvtk.PolyDataMapper()
configure_input_data(cube_mapper, pd)
p = tvtk.Property(opacity=1.0, color=(1.0,0.5,0.5))
cube_actor = tvtk.Actor(mapper=cube_mapper, property=p)
v.scene.add_actor(cube_actor)
if centroids is not None:
# Generate Mesh For Centroids
append_filter = vtk.vtkAppendPolyData()
for i in range(len(centroids)):
input1 = vtk.vtkPolyData()
sphere_source = vtk.vtkSphereSource()
sphere_source.SetCenter(centroids[i][0],centroids[i][1],centroids[i][2])
sphere_source.SetRadius(4.0)
sphere_source.Update()
input1.ShallowCopy(sphere_source.GetOutput())
append_filter.AddInputData(input1)
append_filter.Update()
# Remove Any Duplicate Points.
clean_filter = vtk.vtkCleanPolyData()
clean_filter.SetInputConnection(append_filter.GetOutputPort())
clean_filter.Update()
# Render Mesh
pd = tvtk.to_tvtk(clean_filter.GetOutput())
sphere_mapper = tvtk.PolyDataMapper()
configure_input_data(sphere_mapper, pd)
p = tvtk.Property(opacity=1.0, color=(1.0,0.0,1.0))
sphere_actor = tvtk.Actor(mapper=sphere_mapper, property=p)
v.scene.add_actor(sphere_actor)
mlab.show()
def experiment(num_particles):
L = 1
#L = 50e-9
D = 1
#D = 1e-10
timesteps = 100000
#timesteps = 10000
max_t = 4.0/(2.0*num_particles**0.5);
mol_dt = max_t/timesteps
#mol_dt = 0.025*1e-8
#max_t = mol_dt * timesteps
A = tyche.new_species(D)
B = tyche.new_species(D)
C = tyche.new_species(D)
bd = tyche.new_diffusion()
bd.add_species(A)
bd.add_species(B)
bd.add_species(C)
xlow = tyche.new_xplane(0,1)
xhigh = tyche.new_xplane(L,-1)
ylow = tyche.new_yplane(0,1)
yhigh = tyche.new_yplane(L,-1)
zlow = tyche.new_zplane(0,1)
zhigh = tyche.new_zplane(L,-1)
xminboundary = tyche.new_jump_boundary(xlow,[L,0,0])
xmaxboundary = tyche.new_jump_boundary(xhigh,[-L,0,0])
yminboundary = tyche.new_jump_boundary(ylow,[0,L,0])
ymaxboundary = tyche.new_jump_boundary(yhigh,[0,-L,0])
zminboundary = tyche.new_jump_boundary(zlow,[0,0,L])
zmaxboundary = tyche.new_jump_boundary(zhigh,[0,0,-L])
boundaries = tyche.group([xminboundary, xmaxboundary, yminboundary, ymaxboundary, zminboundary, zmaxboundary])
boundaries.add_species(A)
boundaries.add_species(B)
boundaries.add_species(C)
algorithm = tyche.group([bd,boundaries])
A.fill_uniform([0,0,0],[L,L,L],int(num_particles*L**3))
B.fill_uniform([0,0,0],[L,L,L],int(num_particles*L**3))
C.fill_uniform([0,0,0],[L,L,L],int(num_particles*L**3))
output_dt = max_t/100.0
time = 0;
print algorithm
for i in range(100):
print A,B,C
print 'time = ',time,' ',i,' percent done'
time = algorithm.integrate_for_time(output_dt,mol_dt)
grid = tvtk.to_tvtk(A.get_vtk())
g = init_vis(grid)
print algorithm
def display_3d_model(pdb_data, centroids=None):
'''
Method renders space-filling atomic model of PDB data.
Param:
pdb_data - np.array ; mulitchanneled pdb atom coordinates
skeletal - boolean ; if true shows model without radial information
attenmap - np.array
'''
# Dislay 3D Mesh Rendering
v = mlab.figure(bgcolor=(1.0, 1.0, 1.0))
if pdb_data is not None:
# Color Mapping
n = len(pdb_data)
cm = [jet(float(i) / n)[:3] for i in range(n)]
for j in range(len(pdb_data)):
c = cm[j]
# Coordinate, Radius Information
r = pdb_data[j][:, 0].astype('float')
x = pdb_data[j][:, 1].astype('float')
y = pdb_data[j][:, 2].astype('float')
z = pdb_data[j][:, 3].astype('float')
# Generate Mesh For Protein
append_filter = vtk.vtkAppendPolyData()
for i in range(len(pdb_data[j])):
input1 = vtk.vtkPolyData()
sphere_source = vtk.vtkSphereSource()
sphere_source.SetCenter(x[i], y[i], z[i])
sphere_source.SetRadius(r[i])
sphere_source.Update()
input1.ShallowCopy(sphere_source.GetOutput())
append_filter.AddInputData(input1)
append_filter.Update()
# Remove Any Duplicate Points.
clean_filter = vtk.vtkCleanPolyData()
clean_filter.SetInputConnection(append_filter.GetOutputPort())
clean_filter.Update()
# Render Mesh
pd = tvtk.to_tvtk(clean_filter.GetOutput())
sphere_mapper = tvtk.PolyDataMapper()
configure_input_data(sphere_mapper, pd)
p = tvtk.Property(opacity=1.0, color=(0.0, 0.4, 0.8))
sphere_actor = tvtk.Actor(mapper=sphere_mapper, property=p)
v.scene.add_actor(sphere_actor)
if centroids is not None:
# Generate Mesh For Protein
append_filter = vtk.vtkAppendPolyData()
for i in range(len(centroids)):
input1 = vtk.vtkPolyData()
sphere_source = vtk.vtkSphereSource()
sphere_source.SetCenter(centroids[i][0], centroids[i][1],
centroids[i][2])
sphere_source.SetRadius(2.0)
sphere_source.Update()
input1.ShallowCopy(sphere_source.GetOutput())
append_filter.AddInputData(input1)
append_filter.Update()
# Remove Any Duplicate Points.
clean_filter = vtk.vtkCleanPolyData()
clean_filter.SetInputConnection(append_filter.GetOutputPort())
clean_filter.Update()
# Render Mesh
pd = tvtk.to_tvtk(clean_filter.GetOutput())
sphere_mapper = tvtk.PolyDataMapper()
configure_input_data(sphere_mapper, pd)
p = tvtk.Property(opacity=1.0, color=(1.0, 0.0, 0.0))
sphere_actor = tvtk.Actor(mapper=sphere_mapper, property=p)
v.scene.add_actor(sphere_actor)
mlab.show()
def _create_control(self, parent):
""" Create the toolkit-specific control that represents the widget. """
# Create the VTK widget.
self._vtk_control = window = wxVTKRenderWindowInteractor(parent, -1,
stereo=self.stereo)
# Override these handlers.
wx.EVT_CHAR(window, None) # Remove the default handler.
wx.EVT_CHAR(window, self.OnKeyDown)
wx.EVT_KEY_UP(window, None) # Remove the default handler.
wx.EVT_KEY_UP(window, self.OnKeyUp)
wx.EVT_PAINT(window, None) # Remove the default handler.
wx.EVT_PAINT(window, self.OnPaint)
wx.EVT_SIZE(window, None) # Remove the default handler.
wx.EVT_SIZE(window, self.OnSize)
# Override the button down and up handlers as well to note the
# interaction. This is to toggle the busy status nicely.
for evt in (wx.EVT_LEFT_DOWN, wx.EVT_RIGHT_DOWN,
wx.EVT_MIDDLE_DOWN):
evt(window, None)
evt(window, self.OnButtonDown)
for evt in (wx.EVT_LEFT_UP, wx.EVT_RIGHT_UP,
wx.EVT_MIDDLE_UP):
evt(window, None)
evt(window, self.OnButtonUp)
# Enable the widget.
window.Enable(1)
# Switch the default interaction style to the trackball one.
window.GetInteractorStyle().SetCurrentStyleToTrackballCamera()
# Grab the renderwindow.
renwin = self._renwin = tvtk.to_tvtk(window.GetRenderWindow())
renwin.set(point_smoothing=self.point_smoothing,
line_smoothing=self.line_smoothing,
polygon_smoothing=self.polygon_smoothing)
# Create a renderer and add it to the renderwindow
self._renderer = tvtk.Renderer()
renwin.add_renderer(self._renderer)
# Save a reference to our camera so it is not GC'd -- needed for
# the sync_traits to work.
self._camera = self.camera
# Sync various traits.
self._renderer.background = self.background
self.sync_trait('background', self._renderer)
self.renderer.on_trait_change(self.render, 'background')
self._camera.parallel_projection = self.parallel_projection
self.sync_trait('parallel_projection', self._camera)
renwin.off_screen_rendering = self.off_screen_rendering
self.sync_trait('off_screen_rendering', self._renwin)
self.render_window.on_trait_change(self.render, 'off_screen_rendering')
self.render_window.on_trait_change(self.render, 'stereo_render')
self.render_window.on_trait_change(self.render, 'stereo_type')
self.camera.on_trait_change(self.render, 'parallel_projection')
def _show_parent_hack(window, parent):
"""A hack to get the VTK scene properly setup for use."""
# Force the parent to show itself.
parent.Show(1)
# on some platforms, this SetSize() is necessary to cause
# an OnPaint() when the event loop begins; else we get an
# empty window until we force a redraw.
window.SetSize(parent.GetSize())
# This is necessary on slow machines in order to force the
# wx events to be handled.
wx.GetApp().Yield(True)
window.Render()
if wx.Platform == '__WXMSW__':
_show_parent_hack(window, parent)
else:
if (wx.VERSION[0] == 2) and (wx.VERSION[1] < 5):
_show_parent_hack(window, parent)
window.Update()
# Because of the way the VTK widget is setup, and because we
# set the size above, the window sizing is usually completely
# messed up when the application window is shown. To work
# around this a dynamic IDLE event handler is added and
# immediately removed once it executes. This event handler
# simply forces a resize to occur. The _idle_count allows us
# to execute the idle function a few times (this seems to work
# better).
def _do_idle(event, window=window):
w = wx.GetTopLevelParent(window)
# Force a resize
sz = w.GetSize()
w.SetSize((sz[0]-1, sz[1]-1))
w.SetSize(sz)
window._idle_count -= 1
if window._idle_count < 1:
wx.EVT_IDLE(window, None)
del window._idle_count
window._idle_count = 2
wx.EVT_IDLE(window, _do_idle)
self._interactor = tvtk.to_tvtk(window._Iren)
return window
b = float(j)/N
v = 0.5 + 0.5*cos(13*a)*cos(8*b+3*a*a)
v = v**2
method(i,j,0,0,v)
geometry_filter = vtk.vtkImageDataGeometryFilter()
geometry_filter.SetInput(image_data)
warp = vtk.vtkWarpScalar()
warp.SetInput(geometry_filter.GetOutput())
warp.SetScaleFactor(8.1)
normal_filter = vtk.vtkPolyDataNormals()
normal_filter.SetInput(warp.GetOutput())
data_mapper = vtk.vtkDataSetMapper()
data_mapper.SetInput(normal_filter.GetOutput())
data_actor = vtk.vtkActor()
data_actor.SetMapper(data_mapper)
renderer.AddActor(data_actor)
table = vtk.vtkLookupTable()
data_mapper.SetLookupTable(table)
# the actual gradient editor code.
def on_color_table_changed():
render_window.Render()
# Gradient editor only works with tvtk objects, so convert the lut
# to a tvtk version.
tvtk_table = tvtk.to_tvtk(table)
editor = GradientEditor(root, tvtk_table, on_color_table_changed)
root.mainloop()
b = float(j) / N
v = 0.5 + 0.5 * cos(13 * a) * cos(8 * b + 3 * a * a)
v = v**2
method(i, j, 0, 0, v)
geometry_filter = vtk.vtkImageDataGeometryFilter()
geometry_filter.SetInput(image_data)
warp = vtk.vtkWarpScalar()
warp.SetInput(geometry_filter.GetOutput())
warp.SetScaleFactor(8.1)
normal_filter = vtk.vtkPolyDataNormals()
normal_filter.SetInput(warp.GetOutput())
data_mapper = vtk.vtkDataSetMapper()
data_mapper.SetInput(normal_filter.GetOutput())
data_actor = vtk.vtkActor()
data_actor.SetMapper(data_mapper)
renderer.AddActor(data_actor)
table = vtk.vtkLookupTable()
data_mapper.SetLookupTable(table)
# the actual gradient editor code.
def on_color_table_changed():
render_window.Render()
# Gradient editor only works with tvtk objects, so convert the lut
# to a tvtk version.
tvtk_table = tvtk.to_tvtk(table)
editor = GradientEditor(root, tvtk_table, on_color_table_changed)
root.mainloop()
def experiment(num_particles,timesteps):
L = 1
D = 1
k2 = 1000.0
k1 = k2/num_particles**3
max_t = 1.0
DAB = D+D;
DABC = D + D*D/DAB;
Rsq = ( k1 / (4*3.14**3*(DAB*DABC)**(3.0/2.0) ) )**0.5;
mol_dt = Rsq/10000;
A = tyche.new_species(D)
B = tyche.new_species(D)
C = tyche.new_species(D)
bd = tyche.new_diffusion()
bd.add_species(A)
bd.add_species(B)
bd.add_species(C)
xlow = tyche.new_xplane(0,1)
xhigh = tyche.new_xplane(L,-1)
ylow = tyche.new_yplane(0,1)
yhigh = tyche.new_yplane(L,-1)
zlow = tyche.new_zplane(0,1)
zhigh = tyche.new_zplane(L,-1)
xminboundary = tyche.new_jump_boundary(xlow,[L,0,0])
xmaxboundary = tyche.new_jump_boundary(xhigh,[-L,0,0])
yminboundary = tyche.new_jump_boundary(ylow,[0,L,0])
ymaxboundary = tyche.new_jump_boundary(yhigh,[0,-L,0])
zminboundary = tyche.new_jump_boundary(zlow,[0,0,L])
zmaxboundary = tyche.new_jump_boundary(zhigh,[0,0,-L])
boundaries = tyche.group([xminboundary, xmaxboundary, yminboundary, ymaxboundary, zminboundary, zmaxboundary])
boundaries.add_species(A)
boundaries.add_species(B)
boundaries.add_species(C)
dr3 = tyche.new_tri_reaction(k1, A, B, C, [B,C], mol_dt,
[0,0,0], [L,L,L], [True, True, True])
dr = tyche.new_zero_reaction(k2,[0,0,0],[L,L,L])
dr.add_species(A)
algorithm = tyche.group([bd,boundaries,dr,dr3])
A.fill_uniform([0,0,0],[L,L,L],int(num_particles))
B.fill_uniform([0,0,0],[L,L,L],int(num_particles))
C.fill_uniform([0,0,0],[L,L,L],int(num_particles))
N = 1000
output_dt = max_t/N
time = 0;
print algorithm
grid = tvtk.to_tvtk(A.get_vtk())
numA = np.zeros(N)
for i in range(N):
print A,B,C
numA[i] = A.get_concentration([0,0,0],[L,L,L],[1,1,1])[0]
print 'time = ',time,' ',i*100.0/N,' percent done'
time = algorithm.integrate_for_time(output_dt,mol_dt)
# grid = tvtk.to_tvtk(A.get_vtk())
# g = init_vis(grid)
print algorithm
return numA
