def display(self):
""" Display Electrode in Mayavi """
f = mlab.figure(figure=mlab.gcf(),
bgcolor=(0,0,0),
size=(800,600))
# Call Super Class
Electrode.display(self)
# Build electrode contacts
c0 = find_new_point(self.sphere_center, self.direction, self.contact_height * 3 / 2)
c1 = find_new_point(self.sphere_center, self.direction, self.contact_height * 7 / 2)
c2 = find_new_point(self.sphere_center, self.direction, self.contact_height * 11 / 2)
c3 = find_new_point(self.sphere_center, self.direction, self.contact_height * 15 / 2)
contactCenters = array([c0, c1, c2, c3])
contact = []
for ii in xrange(4):
topContact = find_new_point(contactCenters[ii,:], self.direction, self.contact_height / 2)
bottomContact = find_new_point(contactCenters[ii,:], [-1 * ii for ii in self.direction], self.contact_height / 2)
contact.append([bottomContact, topContact])
contact_array = array(contact)
x, y, z = contact_array.T
activity_array = array([
[self.contact0, self.contact0],
[self.contact1, self.contact1],
[self.contact2, self.contact2],
[self.contact3, self.contact3]])
src = pipeline.scalar_scatter(x.T, y.T, z.T, activity_array)
src.mlab_source.dataset.lines = array([[0, 1], [2, 3], [4, 5], [6, 7]])
src.name = 'Contacts'
self.mlab_contacts = pipeline.tube(src,
tube_radius=self.diameter * 1.03 / 2,
tube_sides=40,
name='DBS Contacts',)
stripper = pipeline.stripper(self.mlab_contacts)
surface = pipeline.surface(stripper)
self.mlab_contacts.filter.capping = True
surface.module_manager.scalar_lut_manager.lut_mode = 'RdBu'
surface.module_manager.scalar_lut_manager.reverse_lut = True
#surface.module_manager.scalar_lut_manager.use_default_range = False
surface.module_manager.scalar_lut_manager.use_default_range = True
surface.module_manager.scalar_lut_manager.data_range = array([-1., 1.])
def display(self,
func,
segfunc=False,
scaling=1,
replace=True,
clim=None,
colormap='jet'):
''' Display current cell in mayavi
'''
#from neuron import h
from numpy import array, vstack, float_
from enthought.mayavi import mlab
from enthought.mayavi.mlab import pipeline
if replace:
try:
self.mlab_cell.parent.parent.parent.parent.parent.parent.remove(
)
except AttributeError:
pass
### Turn off vtk warnings # # # # # # # # # # # # # # # # # # # # # # #
from vtk import vtkObject
o = vtkObject
o.GetGlobalWarningDisplay()
o.SetGlobalWarningDisplay(0) # Turn it off.
f = mlab.figure(figure=mlab.gcf(), bgcolor=(1, 1, 1), size=(800, 600))
self.build_tree(func, segfunc)
## xs = self.xyzdv[:,0]
## ys = self.xyzdv[:,1]
## zs = self.xyzdv[:,2]
xs = float_(self.xyzdv[:, 0])
ys = float_(self.xyzdv[:, 1])
zs = float_(self.xyzdv[:, 2])
# don't want scaling for soma segments
## diams = self.xyzdv[:,3]
diams = float_(self.xyzdv[:, 3])
#nonsoma = (diams < 15) # non-somatic
nonsoma = ones(shape(diams))
diams += diams * nonsoma * (scaling - 1)
#diams = self.xyzdv[:,3] * scaling # larger scaling makes neurons more visible
## data = self.xyzdv[:,4]
data = float_(self.xyzdv[:, 4])
edges = self.connections
# Display in mayavi
pts = pipeline.scalar_scatter(xs, ys, zs, diams / 2.0, name=str(self))
dataset = pts.mlab_source.dataset
dataset.point_data.get_array(0).name = 'diameter'
dataset.lines = vstack(edges)
array_id = dataset.point_data.add_array(data.T.ravel())
dataset.point_data.get_array(array_id).name = 'data'
dataset.point_data.update()
#### Create tube with diameter data
src = pipeline.set_active_attribute(pts, point_scalars='diameter')
stripper = pipeline.stripper(src)
tube = pipeline.tube(stripper, tube_sides=8, tube_radius=1)
tube.filter.capping = True
tube.filter.use_default_normal = False
tube.filter.vary_radius = 'vary_radius_by_absolute_scalar'
#tube.filter.radius_factor = 90.0 # just for making movies
src2 = pipeline.set_active_attribute(tube, point_scalars='data')
lines = pipeline.surface(src2, colormap=colormap)
if clim:
from numpy import array
lines.parent.scalar_lut_manager.use_default_range = False
lines.parent.scalar_lut_manager.data_range = array(clim)
self.mlab_cell = lines
def display(self, var='v', scaling=1):
''' Display current cell in mayavi'''
from neuron import h
from numpy import array, vstack
from enthought.mayavi import mlab
from enthought.mayavi.mlab import pipeline
try:
self.mlab_cell.parent.parent.parent.parent.parent.parent.remove()
except:
pass
f = mlab.figure(figure=mlab.gcf(),
bgcolor=(0,0,0),
size=(800,600))
### Turn off vtk warnings # # # # # # # # # # # # # # # # # # # # # # #
from vtk import vtkObject
o = vtkObject
o.GetGlobalWarningDisplay()
o.SetGlobalWarningDisplay(0) # Turn it off.
self.var = var
self.build_tree()
xs = self.xyzdv[:,0]
ys = self.xyzdv[:,1]
zs = self.xyzdv[:,2]
diams = self.xyzdv[:,3] * scaling # larger scaling makes neurons more visible
data = self.xyzdv[:,4]
edges = self.connections
# Display in mayavi
#Create Scalar scatter with diameter data and edges
#pts = pipeline.scalar_scatter(xs, ys, zs, diams)
# Display in mayavi
pts = pipeline.scalar_scatter(xs, ys, zs, diams/2.0,
name=self.name)
dataset = pts.mlab_source.dataset
dataset.point_data.get_array(0).name = 'diameter'
dataset.lines = vstack(edges)
array_id = dataset.point_data.add_array(data.T.ravel())
dataset.point_data.get_array(array_id).name = 'data'
dataset.point_data.update()
#### Create tube with diameter data
src = pipeline.set_active_attribute(pts,
point_scalars='diameter')
stripper = pipeline.stripper(src)
tube = pipeline.tube(stripper,
tube_sides = 8,
tube_radius = 1)
tube.filter.capping = True
tube.filter.use_default_normal = False
tube.filter.vary_radius = 'vary_radius_by_absolute_scalar'
#tube.filter.radius_factor = 90.0 # just for making movies
src2 = pipeline.set_active_attribute(tube, point_scalars='data')
lines = pipeline.surface(src2)
self.mlab_cell = lines
if self.var is 'v':
self.mlab_cell.module_manager.scalar_lut_manager.use_default_range=False
self.mlab_cell.module_manager.scalar_lut_manager.data_range = array([-70, 0])
mlab.view(azimuth = 133.48567814586244,
elevation = 72.824281412546014,
distance = 409.81131636077509,
focalpoint = array([-4502.1515611 , 5031.21983918, -2293.53156414]))