def show_surface_and_vol(vol,
pp_isosurface,
showVol='MIP',
clim=(-200, 1000),
isoTh=300,
climEditor=True):
""" Show the generated isosurface in original volume
"""
f = vv.figure()
ax = vv.gca()
ax.daspect = 1, 1, -1
ax.axis.axisColor = 1, 1, 1
ax.bgcolor = 0, 0, 0
# show vol and iso vertices
show_ctvolume(vol,
showVol=showVol,
isoTh=isoTh,
clim=clim,
climEditor=climEditor)
label = pick3d(vv.gca(), vol)
vv.plot(pp_isosurface, ms='.', ls='', mc='r', alpha=0.2, mw=4)
a = vv.gca()
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [a]))
print('------------------------')
print('Use keys 1, 2, 3, 4 and 5 for preset anatomic views')
print('Use v for a default zoomed view')
print('Use x to show and hide axis')
print('------------------------')
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
return label
def DoAction(self):
"""
This method is affiliated to the method <self.SartAction>
"""
####################################################
#
# Zak add you code here
# e.g., in what follows we just acquire spectra
#
####################################################
# If you want to apply some radom phase maske then uncomment the following:
#amplitude_mask = self.PulseShaper.GetZeroMask() + 1
#phase_mask = np.random.rand(max_amplitude_mask.size)
#self.PulseShaper.SetMasks(amplitude_mask, phase_mask)
# Getting spectrum
spectrum = self.Spectrometer.AcquiredData()
# Plot the spectra
visvis.gca().Clear()
visvis.plot(self.wavelengths, spectrum)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
visvis.title("Spectrum from radom pulse shape")
self.fig.DrawNow()
# Going to the next iteration
if self._continue_action:
wx.CallAfter(self.DoAction)
def Draw(self, nodesNr=0, drawTex=True, fignr=101, **kwargs):
# Init visualization
if fignr is not None:
f = vv.figure(fignr)
vv.clf()
a = vv.gca()
else:
a = vv.gca()
a.cameraType = '3d'
a.daspect = 1, 1, -1
a.daspectAuto = False
# f.position = -769.00, 342.00, 571.00, 798.00
#f.position = 269.00, 342.00, 571.00, 798.00
# Draw texture?
if drawTex:
self._tex1 = vv.volshow(self._vol)
# Draw nodes?
nodes = {
0: None,
1: self._nodes1,
2: self._nodes2,
3: self._nodes3
}[nodesNr]
if nodes is not None:
nodes.draw(**kwargs)
a.SetLimits()
def visualize(im, vol, sz=0.25, thr=0.99):
im, vol = im.numpy(), vol.numpy()
print("Image shape:", im.shape)
print("Volume shape:", vol.shape)
# overlap with 3d representation + BGR->RGB
im = im.transpose(1, 2, 0) # H,W,C
im = im[:, :, ::-1]
im = cv2.resize(im, (128, 128))
t = vv.imshow(im)
t.interpolate = True # interpolate pixels
# volshow will use volshow3 and rendering the isosurface if OpenGL version is >= 2.0
# Otherwise, it will show slices with bars that you can move (much less useful).
im = (im * 128 + 128).astype(np.uint8)
# im = np.ones_like(im)
volRGB = np.stack(((vol >= thr) * im[:, :, 0], (vol >= thr) * im[:, :, 1],
(vol >= thr) * im[:, :, 2]),
axis=3)
v = vv.volshow(volRGB, renderStyle='iso')
v.transformations[1].sz = sz # Z rescaling
l0 = vv.gca()
l0.light0.ambient = 0.9 # 0.2 is default for light 0
l0.light0.diffuse = 1.0 # 1.0 is default
a = vv.gca()
a.axis.visible = 0
a.camera.fov = 0 # orthographic
vv.use().Run()
def _createWindow(self, name, im, axis):
vv.figure()
vv.gca()
vv.clf()
fig = vv.imshow(im)
dims = im.shape
''' Change color bounds '''
if im.dtype == np.uint8:
fig.clim.Set(0, 255)
else:
fig.clim.Set(0., 1.)
fig.GetFigure().title = name
''' Show ticks on axes? '''
if not axis:
fig.GetAxes().axis.visible = False
bgcolor = (0.,0.,0.)
else:
fig.GetAxes().axis.showBox = False
bgcolor = (1.,1.,1.)
''' Set background color '''
fig.GetFigure().bgcolor = bgcolor
fig.GetAxes().bgcolor = bgcolor
''' Setup keyboard event handler '''
fig.eventKeyDown.Bind(self._keyHandler)
win = {'name':name, 'canvas':fig, 'shape':dims, 'keyEvent':None, 'text':[]}
self.open_windows.append(win)
return win
def on_key(event):
"""KEY commands for user interaction
UP/DOWN = show/hide nodes
ENTER = show edge and attribute values [select 2 nodes]
DELETE = remove edge [select 2 nodes]
CTRL = replace intially created ringparts
ESCAPE = FINISH: refine, smooth
"""
if event.key == vv.KEY_DOWN:
# hide nodes
t1.visible = False
t2.visible = False
t3.visible = False
for node_point in node_points:
node_point.visible = False
if event.key == vv.KEY_UP:
# show nodes
for node_point in node_points:
node_point.visible = True
if event.key == vv.KEY_ENTER:
select1 = selected_nodes[0].node
select2 = selected_nodes[1].node
c, ct, p, l = _utils_GUI.get_edge_attributes(model, select1, select2)
# visualize edge and deselect nodes
selected_nodes[1].faceColor = 'b'
selected_nodes[0].faceColor = 'b'
selected_nodes.clear()
_utils_GUI.set_edge_labels(t1,t2,t3,ct,c,l)
a = vv.gca()
view = a.GetView()
pp = Pointset(p) # visvis meshes do not work with PointSet
line = vv.solidLine(pp, radius = 0.2)
line.faceColor = 'y'
a.SetView(view)
if event.key == vv.KEY_DELETE:
# remove edge
assert len(selected_nodes) == 2
select1 = selected_nodes[0].node
select2 = selected_nodes[1].node
c, ct, p, l = _utils_GUI.get_edge_attributes(model, select1, select2)
model.remove_edge(select1, select2)
# visualize removed edge, show keys and deselect nodes
selected_nodes[1].faceColor = 'b'
selected_nodes[0].faceColor = 'b'
selected_nodes.clear()
_utils_GUI.set_edge_labels(t1,t2,t3,ct,c,l)
a = vv.gca()
view = a.GetView()
pp = Pointset(p)
line = vv.solidLine(pp, radius = 0.2)
line.faceColor = 'r'
a.SetView(view)
if event.key == vv.KEY_CONTROL:
# replace intially created ringparts
ringparts(ringpart=ringpart)
figparts()
def ScanVoltage(self):
"""
Using the iterator <self.scan_pixel_voltage_pair> record the spectral response
by applying the voltages
"""
# Pause calibration, if user requested
try:
if self.pause_calibration: return
except AttributeError:
return
try:
param = self.scan_pixel_voltage_pair.next()
self.PulseShaper.SetUniformMasks(*param)
# Getting spectrum
spectrum = self.Spectrometer.AcquiredData()
# Save the spectrum
try:
self.SpectraGroup["voltages_%d_%d" % param] = spectrum
except RuntimeError:
print "There was RuntimeError while saving scan voltages_%d_%d" % param
# Plot the spectra
visvis.gca().Clear()
visvis.plot(self.wavelengths, spectrum)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
# Scanning progress info
self.scanned += 1.
percentage_completed = 100. * self.scanned / self.scan_length
seconds_left = (time.clock() - self.initial_time) * (
100. / percentage_completed - 1.)
# convert to hours:min:sec
m, s = divmod(seconds_left, 60)
h, m = divmod(m, 60)
title_info = param + (percentage_completed, h, m, s)
visvis.title(
"Scanning spectrum by applying voltages %d/%d. Progress: %.1f%% completed. Time left: %d:%02d:%02d."
% title_info)
self.fig.DrawNow()
# Measure the next pair
wx.CallAfter(self.ScanVoltage)
except StopIteration:
# Perform processing of the measured data
wx.CallAfter(self.ExtractPhaseFunc,
filename=self.calibration_file.filename)
# All voltages are scanned
self.StopAllJobs()
# Sop using the shaper
self.PulseShaper.StopDevice()
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 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 DrawSpectrum(self, event):
"""
Draw spectrum interactively
"""
spectrum = self.Spectrometer.AcquiredData()
if spectrum == RETURN_FAIL: return
# Display the spectrum
if len(spectrum.shape) > 1:
try:
self.__interact_2d_spectrum__.SetData(spectrum)
except AttributeError:
visvis.cla()
visvis.clf()
# Spectrum is a 2D image
visvis.subplot(211)
self.__interact_2d_spectrum__ = visvis.imshow(spectrum,
cm=visvis.CM_JET)
visvis.subplot(212)
# Plot a vertical binning
spectrum = spectrum.sum(axis=0)
# Linear spectrum
try:
self.__interact_1d_spectrum__.SetYdata(spectrum)
except AttributeError:
if self.wavelengths is None:
self.__interact_1d_spectrum__ = visvis.plot(spectrum, lw=3)
visvis.xlabel("pixels")
else:
self.__interact_1d_spectrum__ = visvis.plot(self.wavelengths,
spectrum,
lw=3)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
if self.is_autoscaled_spectrum:
# Smart auto-scale linear plot
try:
self.spectrum_plot_limits = GetSmartAutoScaleRange(
spectrum, self.spectrum_plot_limits)
except AttributeError:
self.spectrum_plot_limits = GetSmartAutoScaleRange(spectrum)
visvis.gca().SetLimits(rangeY=self.spectrum_plot_limits)
# Display the current temperature
try:
visvis.title("Temperature %d (C)" %
self.Spectrometer.GetTemperature())
except AttributeError:
pass
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 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 DrawModelAxes(vol,
graph=None,
ax=None,
axVis=False,
meshColor=None,
getLabel=False,
mc='b',
lc='g',
mw=7,
lw=0.6,
**kwargs):
""" Draw model with volume with axes set
ax = axes to draw (a1 or a2 or a3); graph = sd._nodes1 or 2 or 3
meshColor = None or faceColor e.g. 'g'
"""
#todo: prevent TypeError: draw() got an unexpected keyword argument mc/lc when not given as required variable
#todo: *args voor vol in drawModelAxes of **kwargs[key] in functies hieronder
if ax is None:
ax = vv.gca()
ax.MakeCurrent()
ax.daspect = 1, 1, -1
ax.axis.axisColor = 1, 1, 1
ax.bgcolor = 0, 0, 0
ax.axis.visible = axVis
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
if graph is None:
show_ctvolume(vol, graph, axis=ax, removeStent=False, **kwargs)
label = pick3d(vv.gca(), vol)
return label
if hasattr(graph, 'number_of_edges'):
if graph.number_of_edges(
) == 0: # get label from picked seeds sd._nodes1
show_ctvolume(vol, graph, axis=ax, **kwargs)
label = pick3d(vv.gca(), vol)
graph.Draw(mc=mc, lc=lc)
return label
if not meshColor is None:
bm = create_mesh(graph, 0.5) # (argument is strut tickness)
m = vv.mesh(bm)
m.faceColor = meshColor # 'g'
show_ctvolume(vol, graph, axis=ax, **kwargs)
graph.Draw(mc=mc, lc=lc)
if getLabel == True:
label = pick3d(vv.gca(), vol)
return label
else:
pick3d(vv.gca(), vol)
return
def ScanVoltage (self) :
"""
Using the iterator <self.scan_pixel_voltage_pair> record the spectral response
by applying the voltages
"""
# Pause calibration, if user requested
try :
if self.pause_calibration : return
except AttributeError : return
try :
param = self.scan_pixel_voltage_pair.next()
self.PulseShaper.SetUniformMasks(*param)
# Getting spectrum
spectrum = self.Spectrometer.AcquiredData()
# Save the spectrum
try : self.SpectraGroup["voltages_%d_%d" % param] = spectrum
except RuntimeError : print "There was RuntimeError while saving scan voltages_%d_%d" % param
# Plot the spectra
visvis.gca().Clear()
visvis.plot (self.wavelengths, spectrum)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
# Scanning progress info
self.scanned += 1.
percentage_completed = 100.*self.scanned/self.scan_length
seconds_left = ( time.clock() - self.initial_time )*(100./percentage_completed - 1.)
# convert to hours:min:sec
m, s = divmod(seconds_left, 60)
h, m = divmod(m, 60)
title_info = param + (percentage_completed, h, m, s)
visvis.title ("Scanning spectrum by applying voltages %d/%d. Progress: %.1f%% completed. Time left: %d:%02d:%02d." % title_info)
self.fig.DrawNow()
# Measure the next pair
wx.CallAfter(self.ScanVoltage)
except StopIteration :
# Perform processing of the measured data
wx.CallAfter(self.ExtractPhaseFunc, filename=self.calibration_file.filename)
# All voltages are scanned
self.StopAllJobs()
# Sop using the shaper
self.PulseShaper.StopDevice()
def __init__(self):
# Create figure and axes
vv.figure()
self._a = a = vv.gca()
vv.title("Hold mouse to draw lines. Use 'rgbcmyk' and '1-9' keys.")
# Set axes
a.SetLimits((0, 1), (0, 1))
a.cameraType = "2d"
a.daspectAuto = False
a.axis.showGrid = True
# Init variables needed during drawing
self._active = None
self._pp = Pointset(2)
# Create null and empty line objects
self._line1 = None
self._line2 = vv.plot(vv.Pointset(2), ls="+", lc="c", lw="2", axes=a)
# Bind to events
a.eventMouseDown.Bind(self.OnDown)
a.eventMouseUp.Bind(self.OnUp)
a.eventMotion.Bind(self.OnMotion)
a.eventKeyDown.Bind(self.OnKey)
def show(items, normals=None):
"""Function that shows a mesh object.
"""
for item in items:
vv.clf()
# convert to visvis.Mesh class
new_normals = []
new_vertices = []
for k, v in item.vertices.iteritems():
new_normals.append(item.normal(k))
new_vertices.append(v)
mesh = item.to_visvis_mesh()
mesh.SetVertices(new_vertices)
mesh.SetNormals(new_normals)
mesh.faceColor = 'y'
mesh.edgeShading = 'plain'
mesh.edgeColor = (0, 0, 1)
axes = vv.gca()
if axes.daspectAuto is None:
axes.daspectAuto = False
axes.SetLimits()
if normals is not None:
for normal in normals:
sl = solidLine(normal, 0.15)
sl.faceColor = 'r'
# Show title and enter main loop
vv.title('Show')
app = vv.use()
app.Run()
def __init__(self):
# Init visualization
fig = vv.figure(102); vv.clf()
a = vv.gca()
# Init points
pp = Pointset(2)
pp.append(14,12)
pp.append(12,16)
pp.append(16,16)
self._pp = vv.plot(pp, ls='', ms='.', mw=10, mc='g')
# Init line representing the circle
self._cc = vv.plot(pp, lc='r', lw=2, ms='.', mw=5, mew=0, mc='r')
# Set limits
a.SetLimits((0,32), (0,32))
a.daspectAuto = False
# Init object being moved
self._movedPoint = None
# Enable callbacks
self._pp.hitTest = True
self._pp.eventMouseDown.Bind(self.OnDown)
self._pp.eventMouseUp.Bind(self.OnUp)
a.eventMotion.Bind(self.OnMotion)
a.eventDoubleClick.Bind(self.OnDD)
# Start
self.Apply()
def showModel3d(basedir,ptcode, ctcode, cropname='ring', showVol='MIP',
showmodel=True, graphname='model', **kwargs):
""" show model and vol in 3d by mip iso or 2D
graphname 'all' draws all graph models stored in s, if multiple
"""
s = loadmodel(basedir, ptcode, ctcode, cropname, modelname='modelavgreg')
vol = loadvol(basedir, ptcode, ctcode, cropname, what='avgreg').vol
# figure
f = vv.figure(); vv.clf()
f.position = 0.00, 22.00, 1920.00, 1018.00
a = vv.gca()
a.axis.axisColor = 1,1,1
a.axis.visible = False
a.bgcolor = 0,0,0
a.daspect = 1, 1, -1
t = show_ctvolume(vol, axis=a, showVol=showVol, removeStent=False,
climEditor=True, **kwargs)
label = pick3d(a, vol)
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
if showmodel:
if graphname == 'all':
for key in dir(s):
if key.startswith('model'):
s[key].Draw(mc='b', mw = 5, lc='g', alpha = 0.5)
else:
s[graphname].Draw(mc='b', mw = 5, lc='g', alpha = 0.5)
vv.title('Model for LSPEAS %s - %s' % (ptcode[8:], ctcode))
# f.eventKeyDown.Bind(lambda event: _utils_GUI.RotateView(event, [a], axishandling=False ))
f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [a]) )
return f, a, label, s
def ShowImg (self) :
"""
Draw image
"""
if self._abort_img :
# Exit
return
# Get image
img = self.dev.StopImgAqusition()
# Display image
try :
if img <> RETURN_FAIL :
self._img_plot.SetData(img)
except AttributeError :
visvis.cla()
visvis.clf()
self._img_plot = visvis.imshow(img)
visvis.title ('Camera view')
ax = visvis.gca()
ax.axis.xTicks = []
ax.axis.yTicks = []
# Start acquisition of histogram
self.dev.StartImgAqusition()
wx.CallAfter(self.ShowImg)
def compareGraphsVisually(graph1, graph2, fig=None):
""" compareGraphsVisually(graph1, graph2, fig=None)
Show the two graphs together in a figure. Matched nodes are
indicated by lines between them.
"""
# Get figure
if isinstance(fig,int):
fig = vv.figure(fig)
elif fig is None:
fig = vv.figure()
# Prepare figure and axes
fig.Clear()
a = vv.gca()
a.cameraType = '3d'; a.daspectAuto = False
# Draw both graphs
graph1.Draw(lc='b', mc='b')
graph2.Draw(lc='r', mc='r')
# Set the limits
a.SetLimits()
# Make a line from the edges
pp = Pointset(3)
for node in graph1:
if hasattr(node, 'match') and node.match is not None:
pp.append(node); pp.append(node.match)
# Plot edges
vv.plot(pp, lc='g', ls='+')
def add_text(text,
pos,
angle=0,
fontName=None,
fontSize=9,
color='k',
bgcolor=None,
axes=None):
'''
Adds a text in the world space. Returns the Text object.
Parameters:
text - String. The text of the label
pos - Tuple with two or three numbers. The (x,y,z) position of the text in
world space.
angle - Float or int. The rotation of the label in degrees.
fontname- String. Either 'mono', 'sans' or 'serif'.
fontSize- Int. Size of the text. Default 9.
color - A 3-tuple or a character in 'rgbycmkw', etc that defines text color.
Default 'k' (black).
bgcolor - Background color. See color. Default None.
axes - Axes wherein the label is placed. If None then the current axes is
chosen.
'''
if axes is None:
axes = vv.gca()
text = vv.Text(axes,
text,
*pos,
fontName=fontName,
fontSize=fontSize,
color=color)
text.bgcolor = bgcolor
text.textAngle = angle
return text
def title(text, axes=None):
""" title(text, axes=None)
Show title above axes. Remove title by suplying an empty string.
Parameters
----------
text : string
The text to display.
axes : Axes instance
Display the image in this axes, or the current axes if not given.
"""
if axes is None:
axes = vv.gca()
# seek Title object
for child in axes.children:
if isinstance(child, vv.Title):
ob = child
ob.text = text
break
else:
ob = vv.Title(axes, text)
# destroy if no text, return object otherwise
if not text:
ob.Destroy()
return None
else:
return ob
def __init__(self):
# Create figure and axes
vv.figure()
self._a = a = vv.gca()
vv.title("Hold mouse to draw lines. Use 'rgbcmyk' and '1-9' keys.")
# Set axes
a.SetLimits((0,1), (0,1))
a.cameraType = '2d'
a.daspectAuto = False
a.axis.showGrid = True
# Init variables needed during drawing
self._active = None
self._pp = Pointset(2)
# Create null and empty line objects
self._line1 = None
self._line2 = vv.plot(vv.Pointset(2), ls='+', lc='c', lw='2', axes=a)
# Bind to events
a.eventMouseDown.Bind(self.OnDown)
a.eventMouseUp.Bind(self.OnUp)
a.eventMotion.Bind(self.OnMotion)
a.eventKeyDown.Bind(self.OnKey)
def plot_points(pp, mc='g', ms='o', mw=8, alpha=0.5, ls='', ax=None, **kwargs):
""" Plot a point or set of points in current axis and restore current view
alpha 0.9 = solid; 0.1 transparant
"""
if ax is None:
ax = vv.gca()
# check if pp is 1 point and not a PointSet
if not isinstance(pp, PointSet):
pp = np.asarray(pp)
if pp.ndim == 1:
p = PointSet(3)
p.append(pp)
pp = p
# get view and plot
view = ax.GetView()
point = vv.plot(PointSet(pp),
mc=mc,
ms=ms,
mw=mw,
ls=ls,
alpha=alpha,
axes=ax,
**kwargs)
ax.SetView(view)
return point
def ShowImg(self):
"""
Draw image
"""
if self._abort_img:
# Exit
return
# Get image
img = self.dev.StopImgAqusition()
# Display image
try:
if img <> RETURN_FAIL:
self._img_plot.SetData(img)
except AttributeError:
visvis.cla()
visvis.clf()
self._img_plot = visvis.imshow(img)
visvis.title('Camera view')
ax = visvis.gca()
ax.axis.xTicks = []
ax.axis.yTicks = []
# Start acquisition of histogram
self.dev.StartImgAqusition()
wx.CallAfter(self.ShowImg)
def compareGraphsVisually(graph1, graph2, fig=None):
""" compareGraphsVisually(graph1, graph2, fig=None)
Show the two graphs together in a figure. Matched nodes are
indicated by lines between them.
"""
# Get figure
if isinstance(fig,int):
fig = vv.figure(fig)
elif fig is None:
fig = vv.figure()
# Prepare figure and axes
fig.Clear()
a = vv.gca()
a.cameraType = '3d'; a.daspectAuto = False
# Draw both graphs
graph1.Draw(lc='b', mc='b')
graph2.Draw(lc='r', mc='r')
# Set the limits
a.SetLimits()
# Make a line from the edges
pp = Pointset(3)
for node in graph1:
if hasattr(node, 'match') and node.match is not None:
pp.append(node); pp.append(node.match)
# Plot edges
vv.plot(pp, lc='g', ls='+')
def ViewPresets(event, axis=None, keyboard=['1', '2', '3', '4', '5']):
""" View presets for anatomic views: anterior, posterior, left, right, top,
bottom. 1, 2.. keys or provide keyboard keys
Can be used with f.eventKeyDown.Bind(lambda event: _utils_GUI.ViewPresets(event, [a1, a2]) )
"""
if axis is None:
ax = vv.gca()
axis = [ax]
for ax in axis:
view = ax.GetView()
view['roll'] = 0
# sagital LR
if event.text == keyboard[0]:
view['azimuth'] = 90
view['elevation'] = 0
# posterior
elif event.text == keyboard[1]:
view['azimuth'] = 0
view['elevation'] = 0
# sagital RL
elif event.text == keyboard[2]:
view['azimuth'] = -90
view['elevation'] = 0
elif event.text == keyboard[3]:
view['azimuth'] = -180
view['elevation'] = 90
elif event.text == keyboard[4]:
view['azimuth'] = 0
view['elevation'] = -90
elif event.text == 'z':
view['zoom'] = 0.0198
ax.SetView(view)
if event.text == 'x':
# axes visible or hide
AxesVis(axis)
def vis3Dfit(fitted, vol, model, ptcode, ctcode, showAxis, **kwargs):
"""Visualize ellipse fit in 3D with CT volume in current axis
input: fitted = _fit3D output = (pp3, plane, pp3_2, e3)
"""
from stentseg.utils import fitting
import numpy as np
pp3,plane,pp3_2,e3 = fitted[0],fitted[1],fitted[2],fitted[3]
a = vv.gca()
# show_ctvolume(vol, model, showVol=showVol, clim=clim0, isoTh=isoTh)
show_ctvolume(vol, model, **kwargs)
vv.xlabel('x (mm)');vv.ylabel('y (mm)');vv.zlabel('z (mm)')
vv.title('Ellipse fit for model %s - %s' % (ptcode[7:], ctcode))
a.axis.axisColor= 1,1,1
a.bgcolor= 0,0,0
a.daspect= 1, 1, -1 # z-axis flipped
a.axis.visible = showAxis
# For visualization, calculate 4 points on rectangle that lies on the plane
x1, x2 = pp3.min(0)[0]-0.3, pp3.max(0)[0]+0.3
y1, y2 = pp3.min(0)[1]-0.3, pp3.max(0)[1]+0.3
p1 = x1, y1, -(x1*plane[0] + y1*plane[1] + plane[3]) / plane[2]
p2 = x2, y1, -(x2*plane[0] + y1*plane[1] + plane[3]) / plane[2]
p3 = x2, y2, -(x2*plane[0] + y2*plane[1] + plane[3]) / plane[2]
p4 = x1, y2, -(x1*plane[0] + y2*plane[1] + plane[3]) / plane[2]
vv.plot(pp3, ls='', ms='.', mc='y', mw = 10)
vv.plot(fitting.project_from_plane(pp3_2, plane), lc='r', ls='', ms='.', mc='r', mw=9)
# vv.plot(fitting.project_from_plane(fitting.sample_circle(c3), plane), lc='r', lw=2)
vv.plot(fitting.project_from_plane(fitting.sample_ellipse(e3), plane), lc='b', lw=2)
vv.plot(np.array([p1, p2, p3, p4, p1]), lc='g', lw=2)
# vv.legend('3D points', 'Projected points', 'Circle fit', 'Ellipse fit', 'Plane fit')
vv.legend('3D points', 'Projected points', 'Ellipse fit', 'Plane fit')
def view(viewparams=None, axes=None, **kw):
""" view(viewparams=None, axes=None, **kw)
Get or set the view parameters for the given axes.
Parameters
----------
viewparams : dict
View parameters to set.
axes : Axes instance
The axes the view parameters are for. Uses the current axes by default.
keyword pairs
View parameters to set. These take precidence.
If neither viewparams or any keyword pairs are given, returns the current
view parameters (as a dict). Otherwise, sets the view parameters given.
"""
if axes is None:
axes = vv.gca()
if viewparams or kw:
axes.SetView(viewparams, **kw)
else:
return axes.GetView()
def vis2Dfit(fitted, ptcode, ctcode, showAxis):
"""Visualize ellipse fit in 2D in current axis
input: fitted = _fit3D output = (pp3, plane, pp3_2, e3)
"""
from stentseg.utils import fitting
import numpy as np
plane,pp3_2,e3 = fitted[1],fitted[2],fitted[3]
# endpoints axis
x0,y0,res1,res2,phi = e3[0], e3[1], e3[2], e3[3], e3[4]
dxax1 = np.cos(phi)*res1
dyax1 = np.sin(phi)*res1
dxax2 = np.cos(phi+0.5*np.pi)*res2
dyax2 = np.sin(phi+0.5*np.pi)*res2
p1ax1, p2ax1 = (x0+dxax1, y0+dyax1), (x0-dxax1, y0-dyax1)
p1ax2, p2ax2 = (x0+dxax2, y0+dyax2), (x0-dxax2, y0-dyax2)
a = vv.gca()
vv.xlabel('x (mm)');vv.ylabel('y (mm)')
vv.title('Ellipse fit for model %s - %s' % (ptcode[7:], ctcode))
a.axis.axisColor= 0,0,0
a.bgcolor= 0,0,0
a.axis.visible = showAxis
a.daspectAuto = False
a.axis.showGrid = True
vv.plot(pp3_2, ls='', ms='.', mc='r', mw=9)
vv.plot(fitting.sample_ellipse(e3), lc='b', lw=2)
vv.plot(np.array([p1ax1, p2ax1]), lc='w', lw=2) # major axis
vv.plot(np.array([p1ax2, p2ax2]), lc='w', lw=2) # minor axis
vv.legend('3D points projected to plane', 'Ellipse fit on projected points')
def __init__(self, audiofile=None, fs=22050, bandwidth=300,freqRange= 5000, dynamicRange=48, noiseFloor =-72, parent = None):
super(Spec, self).__init__()
backend = 'pyqt4'
app = vv.use(backend)
Figure = app.GetFigureClass()
self.fig= Figure(self)
self.fig.enableUserInteraction = True
self.fig._widget.setMinimumSize(700,350)
self.axes = vv.gca()
self.audiofilename = audiofile
self.freqRange = freqRange
self.fs = fs
self.NFFT = int(1.2982804/bandwidth*self.fs)
self.overlap = int(self.NFFT/2)
self.noiseFloor = noiseFloor
self.dynamicRange = dynamicRange
self.timeLength = 60
self.resize(700,250)
layout = QtGui.QVBoxLayout()
layout.addWidget(self.fig._widget)
self.setLayout(layout)
self.win = gaussian(self.NFFT,self.NFFT/6)
self.show()
def solidTeapot(translation=None, scaling=None, direction=None, rotation=None,
axesAdjust=True, axes=None):
""" solidTeapot(
translation=None, scaling=None, direction=None, rotation=None,
axesAdjust=True, axes=None)
Create a model of a teapot (a teapotahedron) with its bottom at the
origin. Returns an OrientableMesh instance.
Parameters
----------
Note that translation, scaling, and direction can also be given
using a Point instance.
translation : (dx, dy, dz), optional
The translation in world units of the created world object.
scaling: (sx, sy, sz), optional
The scaling in world units of the created world object.
direction: (nx, ny, nz), optional
Normal vector that indicates the direction of the created world object.
rotation: scalar, optional
The anle (in degrees) to rotate the created world object around its
direction vector.
axesAdjust : bool
If 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 bars in the given axes, or the current axes if not given.
"""
# Load mesh data
bm = vv.meshRead('teapot.ssdf')
# Use current axes?
if axes is None:
axes = vv.gca()
# Create Mesh object
m = vv.OrientableMesh(axes, bm)
#
if translation is not None:
m.translation = translation
if scaling is not None:
m.scaling = scaling
if direction is not None:
m.direction = direction
if rotation is not None:
m.rotation = rotation
# Adjust axes
if axesAdjust:
if axes.daspectAuto is None:
axes.daspectAuto = False
axes.cameraType = '3d'
axes.SetLimits()
# Done
axes.Draw()
return m
def add_label(text,
pos,
angle=0,
fontName=None,
fontSize=9,
color='k',
bgcolor=None,
axes=None):
'''
Adds a label inside the axes. Returns the Label object.
Parameters:
text - String. The text of the label
pos - Tuple with two numbers. The (x,y) position of the label with origin
at the upper left corner.
angle - Float or int. The rotation of the label in degrees.
fontname- String. Either 'mono', 'sans' or 'serif'.
fontSize- Int. Size of the text. Default 9.
color - A 3-tuple or a character in 'rgbycmkw', etc that defines text color.
Default 'k' (black).
bgcolor - Background color. See color. Default None.
axes - Axes wherein the label is placed. If None then the current axes is
chosen.
'''
if axes is None:
axes = vv.gca()
label = vv.Label(axes, text, fontName, fontSize, color)
label.position = pos
label.bgcolor = bgcolor
label.textAngle = angle
return label
def view(viewparams=None, axes=None, **kw):
""" view(viewparams=None, axes=None, **kw)
Get or set the view parameters for the given axes.
Parameters
----------
viewparams : dict
View parameters to set.
axes : Axes instance
The axes the view parameters are for. Uses the current axes by default.
keyword pairs
View parameters to set. These take precidence.
If neither viewparams or any keyword pairs are given, returns the current
view parameters (as a dict). Otherwise, sets the view parameters given.
"""
if axes is None:
axes = vv.gca()
if viewparams or kw:
axes.SetView(viewparams, **kw)
else:
return axes.GetView()
def _visualise_world_visvis(X, Y, Z, format="surf"):
"""
Legacy function to produce a surface render using visvis
:param X:
:param Y:
:param Z:
:param format:
"""
import visvis as vv
# m2 = vv.surf(worldx[::detail], worldy[::detail], worldz[::detail])
app = vv.use()
# prepare axes
a = vv.gca()
a.cameraType = '3d'
a.daspectAuto = False
# print("view", a.camera.GetViewParams())
# a.SetView(loc=(-1000,0,0))
# a.camera.SetView(None, loc=(-1000,0,0))
if format == "surf":
l = vv.surf(X, Y, Z)
a.SetLimits(rangeX=(-0.2, 0.2),
rangeY=(-0.5, 0.5),
rangeZ=(-0.5, 0),
margin=0.02)
else:
# draw points
pp = vv.Pointset(
np.concatenate([X.flatten(), Y.flatten(),
Z.flatten()], axis=0).reshape((-1, 3)))
l = vv.plot(pp, ms='.', mc='r', mw='5', ls='', mew=0)
l.alpha = 0.2
app.Run()
def __init__(self, mvertices, mverticesDeltas, mangleChanges):
""" Allows measureing on the motions of a stent by placing a ring
around it. The z-position of the ring can be changed using a slider.
The ring is oriented purely in the xy plane; it is not orthogonal to
the stent's centerline!
"""
# For interacting
self._interact_over = False
self._interact_down = False
self._screenVec = None
self._refPos = (0,0)
self._screenVec = None
self._refZ = 0
# Get axes
axes = vv.gca()
# Get vertices etc.
vertices, indices, normals, texcords = self._CalculateDonut()
# Initialize
vv.OrientableMesh.__init__(self, axes,
vertices, indices, normals, values=texcords, verticesPerFace=4)
self.faceColor = 'c'
# Make hittable
self.hitTest = True
# Bind events
self.eventEnter.Bind(self._OnMouseEnter)
self.eventLeave.Bind(self._OnMouseLeave)
self.eventMouseDown.Bind(self._OnMouseDown)
self.eventMouseUp.Bind(self._OnMouseUp)
self.eventMotion.Bind(self._OnMouseMotion)
# Variables for "child" objects
self._slider = None
self._line = None
# Store data per vertex
self._mvertices = mvertices
self._mverticesDeltas = mverticesDeltas
self._mangleChanges = mangleChanges
# Get limits and halfway position
limits = self._getVertexLimits(mvertices)[2]
halfway = limits.min+limits.range*0.5
# Create slider
if True:
self._slider = vv.Slider(self.GetFigure(), limits, halfway)
self._slider.eventSliderChanged.Bind(self.onSliderChanged)
self._slider.eventSliding.Bind(self.onSliderSliding)
# Init
self.performMeasurements(halfway)
def drawmodelphasescycles(vol1,
model1,
modelori1,
showVol,
isoTh=300,
removeStent=False,
showmodelavgreg=False,
showvol=True,
phases=range(10),
colors='cgmrcgywmb',
meshWithColors=False,
stripSizeZ=None,
ax=None):
""" draw model and volume (show optional) at different phases cycle
"""
if ax is None:
ax = vv.gca()
ax.daspect = 1, 1, -1
ax.axis.axisColor = 0, 0, 0
ax.bgcolor = 1, 1, 1
vv.xlabel('x (mm)')
vv.ylabel('y (mm)')
vv.zlabel('z (mm)')
# draw
t = show_ctvolume(vol1,
modelori1,
showVol=showVol,
removeStent=removeStent,
climEditor=True,
isoTh=isoTh,
clim=clim0,
stripSizeZ=stripSizeZ)
if showmodelavgreg:
# show model and CT mid cycle
mw = 5
for model in model1:
model.Draw(mc='b', mw=mw, lc='b', alpha=0.5)
label = pick3d(ax, vol1)
if not showvol:
t.visible = False
# get models in different phases
for model in model1:
for phasenr in phases:
model_phase = get_graph_in_phase(model, phasenr=phasenr)
if meshWithColors:
modelmesh1 = create_mesh_with_abs_displacement(model_phase,
radius=radius,
dim=dimensions)
m = vv.mesh(modelmesh1, colormap=vv.CM_JET, clim=clim2)
#todo: use colormap Viridis or Magma as JET is not linear (https://bids.github.io/colormap/)
else:
model_phase.Draw(mc=colors[phasenr], mw=10, lc=colors[phasenr])
# modelmesh1 = create_mesh(model_phase, radius = radius)
# m = vv.mesh(modelmesh1); m.faceColor = colors[phasenr]
if meshWithColors:
vv.colorbar()
return ax
def cla():
""" cla()
Clear the current axes.
"""
a = vv.gca()
a.Clear()
return a
def DrawSpectrum (self, event) :
"""
Draw spectrum interactively
"""
spectrum = self.Spectrometer.AcquiredData()
if spectrum == RETURN_FAIL : return
# Display the spectrum
if len(spectrum.shape) > 1:
try :
self.__interact_2d_spectrum__.SetData(spectrum)
except AttributeError :
visvis.cla(); visvis.clf();
# Spectrum is a 2D image
visvis.subplot(211)
self.__interact_2d_spectrum__ = visvis.imshow(spectrum, cm=visvis.CM_JET)
visvis.subplot(212)
# Plot a vertical binning
spectrum = spectrum.sum(axis=0)
# Linear spectrum
try :
self.__interact_1d_spectrum__.SetYdata(spectrum)
except AttributeError :
if self.wavelengths is None :
self.__interact_1d_spectrum__ = visvis.plot (spectrum, lw=3)
visvis.xlabel ("pixels")
else :
self.__interact_1d_spectrum__ = visvis.plot (self.wavelengths, spectrum, lw=3)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
if self.is_autoscaled_spectrum :
# Smart auto-scale linear plot
try :
self.spectrum_plot_limits = GetSmartAutoScaleRange(spectrum, self.spectrum_plot_limits)
except AttributeError :
self.spectrum_plot_limits = GetSmartAutoScaleRange(spectrum)
visvis.gca().SetLimits ( rangeY=self.spectrum_plot_limits )
# Display the current temperature
try : visvis.title ("Temperature %d (C)" % self.Spectrometer.GetTemperature() )
except AttributeError : pass
def paint(self, visvis):
vv.clf()
colors = ['r','g','b','c','m','y','k']
for index, dataset in enumerate(self._value):
l = visvis.plot(dataset, ms='o', mc=colors[ index % len(colors) ], mw='3', ls='', mew=0 )
l.alpha = 0.3
self._a = vv.gca()
self._a.daspectAuto = True
def paint(self, visvis): vv.clf() colors = ['r','g','b','c','m','y','k'] for index, dataset in enumerate(self._value): l = visvis.plot(dataset, ms='o', mc=colors[ index % len(colors) ], mw='3', ls='', mew=0 ) l.alpha = 0.3 self._a = vv.gca() self._a.daspectAuto = True
def ShowSpectra_by_VaryingPixelBundle(self):
"""
This method is affiliated to the method <self.VaryPixelBundle>
"""
# Exit if the iterator is not defined
try:
self.pixel_bundel_value_iter
except AttributeError:
return
try:
voltage = self.pixel_bundel_value_iter.next()
# Set the mask for pixel bundle
width = self.SettingsNotebook.CalibrateShaper.pixel_bundle_width.GetValue(
) / 2
start_pixel_bundle = self.pixel_to_vary.GetValue()
mask = np.copy(self.fixed_mask)
if width:
mask[max(start_pixel_bundle -
width, 0):min(mask.size, start_pixel_bundle +
width)] = voltage
else:
# Enforce single pixel width
mask[min(max(start_pixel_bundle, 0), mask.size)] = voltage
self.PulseShaper.SetMasks(mask, self.fixed_mask)
# Getting spectrum
spectrum = self.Spectrometer.AcquiredData()
# Plot the spectra
visvis.gca().Clear()
visvis.plot(self.wavelengths, spectrum)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
visvis.title("Voltage %d / %d " % (voltage, self.fixed_mask[0]))
self.fig.DrawNow()
# Going to the next iteration
wx.CallAfter(self.ShowSpectra_by_VaryingPixelBundle)
except StopIteration:
# Finish the job
self.StopAllJobs()
def paint(self, visvis):
vv.clf()
colors = ["r", "g", "b", "c", "m", "y", "k"]
for index, dataset in enumerate(self._value):
l = visvis.plot(dataset, ms="o", mc=colors[index % len(colors)], mw="3", ls="", mew=0)
l.alpha = 0.3
self._a = vv.gca()
self._a.daspectAuto = True
def solidLine(pp, radius=1.0, N=16, axesAdjust=True, axes=None):
""" solidLine(pp, radius=1.0, N=16, axesAdjust=True, axes=None)
Creates a solid line in 3D space.
Parameters
----------
Note that translation, scaling, and direction can also be given
using a Point instance.
pp : Pointset
The sequence of points of which the line consists.
radius : scalar or sequence
The radius of the line to create. If a sequence if given, it
specifies the radius for each point in pp.
N : int
The number of subdivisions around its centerline. If smaller
than 8, flat shading is used instead of smooth shading.
axesAdjust : bool
If 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 bars in the given axes, or the current axes if not given.
"""
# Check first argument
if is_Pointset(pp):
pass
else:
raise ValueError('solidLine() needs a Pointset or list of pointsets.')
# Obtain mesh and make a visualization mesh
baseMesh = lineToMesh(pp, radius, N)
## Visualize
# Get axes
if axes is None:
axes = vv.gca()
# Create mesh object
m = vv.Mesh(axes, baseMesh)
# Adjust axes
if axesAdjust:
if axes.daspectAuto is None:
axes.daspectAuto = False
axes.cameraType = '3d'
axes.SetLimits()
# Return
axes.Draw()
return m
def solidLine(pp, radius=1.0, N=16, axesAdjust=True, axes=None):
""" solidLine(pp, radius=1.0, N=16, axesAdjust=True, axes=None)
Creates a solid line in 3D space.
Parameters
----------
Note that translation, scaling, and direction can also be given
using a Point instance.
pp : Pointset
The sequence of points of which the line consists.
radius : scalar or sequence
The radius of the line to create. If a sequence if given, it
specifies the radius for each point in pp.
N : int
The number of subdivisions around its centerline. If smaller
than 8, flat shading is used instead of smooth shading.
axesAdjust : bool
If 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 bars in the given axes, or the current axes if not given.
"""
# Check first argument
if is_Pointset(pp):
pass
else:
raise ValueError('solidLine() needs a Pointset or list of pointsets.')
# Obtain mesh and make a visualization mesh
baseMesh = lineToMesh(pp, radius, N)
## Visualize
# Get axes
if axes is None:
axes = vv.gca()
# Create mesh object
m = vv.Mesh(axes, baseMesh)
# Adjust axes
if axesAdjust:
if axes.daspectAuto is None:
axes.daspectAuto = False
axes.cameraType = '3d'
axes.SetLimits()
# Return
axes.Draw()
return m
def remove_nodes_by_selected_point(graph,
vol,
axes,
label,
clim,
location='posterior',
**kwargs):
""" removes nodes and edges in graph. Graph is separated by coord of selected point
use location to define what to remove, e.g. posterior to remove nodes in spine
Input : graph, axes, label of selected point,
dimension how to separate graph
Output: graph is modified locally and visualized in current view
"""
from stentseg.utils.picker import pick3d, label2worldcoordinates
from stentseg.utils.visualization import DrawModelAxes
if graph is None:
print('No nodes removed, graph is NoneType')
return
coord1 = np.asarray(label2worldcoordinates(label),
dtype=np.float32) # x,y,z
if location == 'posterior':
seeds = np.asarray(sorted(
graph.nodes(), key=lambda x: x[1])) # sort dim small to large
falseindices = np.where(
seeds[:, 1] > coord1[1]
) # tuple wih array of indices with values higher than coord y = 1
if location == 'anterior':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[1]))
falseindices = np.where(seeds[:, 1] < coord1[1])
elif location == 'proximal':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[2]))
falseindices = np.where(
seeds[:, 2] < coord1[2]) # dim z = 2; origin proximal
elif location == 'distal':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[2]))
falseindices = np.where(seeds[:, 2] > coord1[2]) # dim z = 2
elif location == 'left':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[0]))
falseindices = np.where(seeds[:, 0] > coord1[0])
elif location == 'right':
seeds = np.asarray(sorted(graph.nodes(), key=lambda x: x[0]))
falseindices = np.where(seeds[:, 0] < coord1[0])
# get seeds for removal by indices
falseseeds = seeds[falseindices[0]]
# remove from graph
graph.remove_nodes_from(tuple(map(
tuple, falseseeds))) # use map to convert to tuples
view = axes.GetView()
axes.Clear()
DrawModelAxes(vol, graph, ax=axes, clim=clim, **kwargs)
axes.SetView(view)
if graph.number_of_edges() == 0: # get label from picked seeds sd._nodes1
label = pick3d(vv.gca(), vol)
return label
def __plot(self, spectrum):
vv.clf()
axes = vv.gca()
axes.axis.showGrid = True
axes.axis.xLabel = 'Frequency (MHz)'
axes.axis.yLabel = 'Level (dB)'
total = len(spectrum)
count = 0.
for _time, sweep in spectrum.items():
alpha = (total - count) / total
vv.plot(sweep.keys(), sweep.values(), lw=1, alpha=alpha)
count += 1
def __init__(self, parent):
super(VisPolar, self).__init__(parent)
self.lines = dict()
self.polar = None
vv.polarplot([0], [0], lc='w', axesAdjust=True)
self.axes = vv.gca()
self.params = self.axes.camera.GetViewParams()
self.axes.axisType = 'polar'
self.axes.axis.angularRefPos = 0 # 0 deg points up
self.axes.axis.isCW = True # changes angular sense (azimuth instead of phi)
self.axes.axis.showGrid = True
fig = self.axes.GetFigure()
def colorbar(axes=None):
""" colorbar(axes=None)
Attach a colorbar to the given axes (or the current axes if
not given). The reference to the colorbar instance is returned.
Also see the vv.ColormapEditor wibject.
"""
if axes is None:
axes = vv.gca()
return vv.Colorbar(axes)
def ShowSpectra_by_VaryingPixelBundle (self) :
"""
This method is affiliated to the method <self.VaryPixelBundle>
"""
# Exit if the iterator is not defined
try : self.pixel_bundel_value_iter
except AttributeError : return
try :
voltage = self.pixel_bundel_value_iter.next()
# Set the mask for pixel bundle
width = self.SettingsNotebook.CalibrateShaper.pixel_bundle_width.GetValue() / 2
start_pixel_bundle = self.pixel_to_vary.GetValue()
mask = np.copy(self.fixed_mask)
if width:
mask[max(start_pixel_bundle-width, 0):min(mask.size, start_pixel_bundle+width)] = voltage
else:
# Enforce single pixel width
mask[min(max(start_pixel_bundle,0),mask.size)] = voltage
self.PulseShaper.SetMasks( mask, self.fixed_mask)
# Getting spectrum
spectrum = self.Spectrometer.AcquiredData()
# Plot the spectra
visvis.gca().Clear()
visvis.plot (self.wavelengths, spectrum)
visvis.xlabel("wavelength (nm)")
visvis.ylabel("counts")
visvis.title ("Voltage %d / %d " % (voltage, self.fixed_mask[0]) )
self.fig.DrawNow()
# Going to the next iteration
wx.CallAfter (self.ShowSpectra_by_VaryingPixelBundle)
except StopIteration :
# Finish the job
self.StopAllJobs()
def _makeColorBar(text, axes=None):
'''
Convenience function that finds the current colorbar in the axes
or creates a new one if one does not exist.
The reason is that colorbars can not be deleted without clearing
the whole figure, and several colorbars can exist simultaneously.
This should be avoided.
'''
if axes is None:
axes = vv.gca()
colBar = getColorbar(axes)
if colBar is None:
vv.colorbar(axes).SetLabel(text) #Creates a colorbar and sets the label.
else:
colBar.SetLabel(text)# A colorbar already exists, Change label.
def getColorbar(axes=None):
'''
Returns the Colorbar.
If axes is None the colorbar in the current axes will be found.
If several colorbars exists in the axes the first found will be returned
If no colorbar is found None is returned.
'''
#An ugly solution, but visvis seems to have no other way of getting the colorbar,
#or most other entities that exist in the axes.
if axes is None:
axes = vv.gca()
for obj in axes.children:
if type(obj) == Colorbar:
return obj
return None
def createWindow(self, name, im, axis):
vv.figure()
vv.gca()
vv.clf()
fig = vv.imshow(im)
dims = im.shape
''' Change color bounds '''
if im.dtype == np.uint8:
fig.clim.Set(0, 255)
else:
fig.clim.Set(im.min(), im.max())
fig.GetFigure().title = name
''' Show ticks on axes? '''
if not axis:
fig.GetAxes().axis.visible = False
bgcolor = (0.,0.,0.)
else:
fig.GetAxes().axis.showBox = False
bgcolor = (1.,1.,1.)
fig.GetFigure().bgcolor = bgcolor
fig.GetAxes().bgcolor = bgcolor
fig.eventKeyUp.Bind(self.keyHandler)
win = {'name':name, 'figure':fig, 'shape':dims, 'keyEvent':None}
self.open_windows.append(win)
return win
def axis(command, axes=None):
""" axis(command, axes=None)
Convenience function to set axis properties. Note that all functionality
can also be applied via the properties of the Axis object.
Parameters
----------
command : string
The setting command to apply. See below.
axes : Axes instance
The axes to apply the setting to. Uses the current axes by default.
Possible string commands
------------------------
* off: hide the axis (Axes.axis.visible = False)
* on: show the axis (Axes.axis.visible = True)
* equal: make a circle be displayed circular (Axes.daspectAuto = False)
* auto: change the range for each dimension indepdently (Axes.daspectAuto = True)
* tight: show all data (Axes.SetLimits())
* ij: flip the y-axis (make second element of Axes.daspect negative)
* xy: (make all elements of Axes.daspect positive)
If you want to set an Axes' limits, use Axes.SetLimits(xlim, ylim, zlim).
"""
# Get axes
if axes is None:
axes = vv.gca()
if command == 'off':
axes.axis.visible = 0
elif command == 'on':
axes.axis.visible = 1
elif command == 'equal':
axes.daspectAuto = 0
elif command == 'auto':
axes.daspectAuto = 1
elif command == 'tight':
axes.SetLimits()
elif command == 'ij':
da = [abs(tmp) for tmp in axes.daspect]
axes.daspect = da[0], -abs(da[1]), da[2]
elif command == 'xy':
da = [abs(tmp) for tmp in axes.daspect]
axes.daspect = da[0], abs(da[1]), da[2]
else:
raise ValueError('Unknown command in vv.axis().')
def ginput(N=0, axes=None, ms='+', **kwargs):
""" ginput(N=0, axes=None, ms='+', **kwargs)
Graphical input: select N number of points with the mouse.
Returns a 2D pointset.
Parameters
----------
N : int
The maximum number of points to capture. If N=0, will keep capturing
until the user stops it. The capturing always stops when enter is
pressed or the mouse is double clicked. In the latter case a final
point is added.
axes : Axes instance
The axes to capture the points in, or the current axes if not given.
ms : markerStyle
The marker style to use for the points. See plot.
Any other keyword arguments are passed to plot to show the selected
points and the lines between them.
"""
# Get axes
if not axes:
axes = vv.gca()
# Get figure
fig = axes.GetFigure()
if not fig:
return
# Init pointset, helper, and line object
line = vv.plot(Pointset(2), axes=axes, ms=ms, **kwargs)
pp = line._points
ginputHelper.Start(axes, pp, N)
# Enter a loop
while ginputHelper.axes:
fig._ProcessGuiEvents()
time.sleep(0.1)
# Remove line object and return points
pp = Pointset(pp[:,:2])
line.Destroy()
return pp
def setupAxes(self):
"""
Sets up the axes initially. Shows a 2d view with a range based
on the sensor positions. Might want to give the user the option to set the range
in future releases.
The if statement is for when the sensors got switched.. which only
happens on 2 subjects, but totally messes up the axes view then.
"""
vv.clf()
self.axes = vv.gca()
self.axisLabeler = self.axes.axis
self.axes.cameraType = 3
self.axes.daspectAuto= False
#.SetLimits(#rangeX = (xmin,xmax),rangeY = (ymin,ymax), rangeZ = (zmin,zmax))
self.axisLabeler.showGrid = True
def ylabel(text, axes=None):
""" ylabel(text, axes=None)
Set the ylabel of an axes.
Note that you can also use "axes.axis.yLabel = text".
Parameters
----------
text : string
The text to display.
axes : Axes instance
Display the image in this axes, or the current axes if not given.
"""
if axes is None:
axes = vv.gca()
axes.axis.yLabel = text
def __init__(self, sampleinterval=0.1, timewindow=10.0, size=(600, 350)):
# Data stuff
self._interval = int(sampleinterval * 1000)
self._bufsize = int(timewindow / sampleinterval)
self.databuffer = collections.deque([0.0] * self._bufsize, self._bufsize)
self.x = np.linspace(-timewindow, 0.0, self._bufsize)
self.y = np.zeros(self._bufsize, dtype=np.float)
# Visvis stuff
self.app = vv.use("qt4")
vv.title("Dynamic Plotting with VisVis")
self.line = vv.plot(self.x, self.y, lc="b", lw=3, ms="+")
vv.xlabel("time")
vv.ylabel("amplitude")
self.ax = vv.gca()
self.timer = vv.Timer(self.app, 50, oneshot=False)
self.timer.Bind(self.updateplot)
self.timer.Start()
