def value(self, value):
a = vv.gca()
view = a.GetView()
a.Clear()
vv.volshow3(value, renderStyle='mip')
if not self._first:
a = vv.gca()
a.SetView(view)
self._first=False
def refresh(self):
if len(self._value)>1:
a = vv.gca()
view = a.GetView()
a.Clear()
vv.volshow3(self._value, renderStyle='mip', cm=self._colorMap )
if not self._first:
a = vv.gca()
a.SetView(view)
self._first=False
def refresh(self):
if len(self._value)>1:
vv.figure(self._fig.nr)
a = vv.gca()
view = a.GetView()
a.Clear()
vv.volshow3(self._value, renderStyle='mip', cm=self._colorMap, clim=self._colors_limits )
if not self._first:
a = vv.gca()
a.SetView(view)
self._first=False
def refresh(self):
if len(self._value) > 1:
vv.figure(self._fig.nr)
a = vv.gca()
view = a.GetView()
a.Clear()
vv.volshow3(self._value, renderStyle='mip', cm=self._colorMap)
if not self._first:
a = vv.gca()
a.SetView(view)
self._first = False
def volshow(*args, **kwargs):
""" volshow(vol, clim=None, cm=CM_GRAY, axesAdjust=True, axes=None)
Display a 3D image (a volume).
This is a convenience function that calls either volshow3() or
volshow2(). If the current system supports it (OpenGL version >= 2.0),
displays a 3D rendering (volshow3). Otherwise shows three slices
that can be moved interactively (volshow2).
Parameters
----------
vol : numpy array
The 3D image to visualize. Can be grayscale, RGB, or RGBA.
If the volume is an anisotropic array (vv.Aaray), the appropriate
scale and translate transformations are applied.
clim : 2-element tuple
The color limits to scale the intensities of the image. If not given,
the im.min() and im.max() are used (neglecting nan and inf).
cm : Colormap
Set the colormap to apply in case the volume is grayscale.
axesAdjust : bool
If axesAdjust==True, this function will call axes.SetLimits(), and set
the camera type to 3D. If daspectAuto has not been set yet, it is
set to False.
axes : Axes instance
Display the image in this axes, or the current axes if not given.
Any other keyword arguments are passed to either volshow2() or volshow3().
"""
# Make sure that a figure exists
vv.gcf()
# Test and run
if vv.settings.volshowPreference == 3 and vv.misc.getOpenGlCapable(2.0):
return vv.volshow3(*args, **kwargs)
else:
return vv.volshow2(*args, **kwargs)
def volshow(*args, **kwargs):
""" volshow(vol, clim=None, cm=CM_GRAY, axesAdjust=True, axes=None)
Display a 3D image (a volume).
This is a convenience function that calls either volshow3() or
volshow2(). If the current system supports it (OpenGL version >= 2.0),
displays a 3D rendering (volshow3). Otherwise shows three slices
that can be moved interactively (volshow2).
Parameters
----------
vol : numpy array
The 3D image to visualize. Can be grayscale, RGB, or RGBA.
If the volume is an anisotropic array (vv.Aaray), the appropriate
scale and translate transformations are applied.
clim : 2-element tuple
The color limits to scale the intensities of the image. If not given,
the im.min() and im.max() are used (neglecting nan and inf).
cm : Colormap
Set the colormap to apply in case the volume is grayscale.
axesAdjust : bool
If axesAdjust==True, this function will call axes.SetLimits(), and set
the camera type to 3D. If daspectAuto has not been set yet, it is
set to False.
axes : Axes instance
Display the image in this axes, or the current axes if not given.
Any other keyword arguments are passed to either volshow2() or volshow3().
"""
# Make sure that a figure exists
vv.gcf()
# Test and run
if vv.settings.volshowPreference==3 and vv.misc.getOpenGlCapable(2.0):
return vv.volshow3(*args, **kwargs)
else:
return vv.volshow2(*args, **kwargs)
t_end = 3600
epsilon = 1E-10
diff = epsilon * 2
zeros = np.zeros(Ci.shape)
while(t <= t_end and diff >= epsilon):
#solve for the gradients in each direction
l_xyz = ndimage.convolve(Ci, l, mode = "constant",
cval = c_out)
# l_y = ndimage.convolve(Ci, ly, mode = "constant",
# cval = c_out)
# l_z = ndimage.convolve(Ci, lz, mode = "constant",
# cval = c_out)
#first diffusion
C = Ci + (l_xyz)*D*dt
#MUST BE normalized by unit VOLUME
temp_sink = (-sink*dt) / grid_vol
temp_source = source*dt / grid_vol
C += temp_sink + temp_source
#get the summed difference
diff = np.sum(np.abs(Ci - C))
#make sure its positive
C = C * (C > 0.0)
#update the old
Ci = C
#update the time step
t += dt
vv.use('qt4')
vv.volshow3(C)
app = vv.use()
app.Run()
# create texture
t = vv.Texture3D(axes, vol, renderStyle)
# set clim
if isinstance(clim, list):
clim = tuple(clim)
if isinstance(clim, tuple):
t.SetClim(clim)
# set colormap
if cm is not None:
t.colormap = cm
# adjust axes
if axesAdjust:
if axes.daspectAuto is None:
axes.daspectAuto = False
axes.cameraType = '3d'
axes.SetLimits()
# done
axes.Draw()
return t
if __name__ == "__main__":
vol = vv.aVolume()
t = vv.volshow3(vol)
t.renderStyle = 'iso' # Isosurface rendering instead of MIP
t.isoThreshold = 0.1
# create texture
t = vv.Texture3D(axes, vol, renderStyle)
# set clim
if isinstance(clim,list):
clim = tuple(clim)
if isinstance(clim, tuple):
t.SetClim(clim)
# set colormap
if cm is not None:
t.colormap = cm
# adjust axes
if axesAdjust:
if axes.daspectAuto is None:
axes.daspectAuto = False
axes.cameraType = '3d'
axes.SetLimits()
# done
axes.Draw()
return t
if __name__ == "__main__":
vol = vv.aVolume()
t = vv.volshow3(vol)
t.renderStyle = 'iso' # Isosurface rendering instead of MIP
t.isoThreshold = 0.1
