def opyfBuildLocatorandStuff2D(X):
# Create points array which are positions to probe data with
# FindClosestPoint(), We also create an array to hold the results of this
# probe operation and
# This array is the same array since we want to find the closest neighbor
# The strategy will be to find the 2 closest point since one of them will be the same point
# And we consider the second one, the farthest
npPoints = X
points = vtk.vtkPoints()
points.SetDataTypeToDouble()
probePoints = vtk.vtkPoints()
probePoints.SetDataTypeToDouble()
for [x, y] in npPoints:
points.InsertNextPoint(x, y, 0.)
probePoints.InsertNextPoint(x, y, 0.)
polydata = vtk.vtkPolyData()
polydata.SetPoints(points)
points.ComputeBounds()
staticLocator = vtk.vtkStaticPointLocator()
staticLocator.SetDataSet(polydata)
staticLocator.SetNumberOfPointsPerBucket(5)
staticLocator.AutomaticOn()
staticLocator.BuildLocator()
return staticLocator, points, probePoints
def get_data_vtk(self, points_interpol, interpolation_method="linear"):
"""
Get interpolated data for points_interpol using vtks built-in interpolation methods
"""
kernels = {
"voronoi": vtk.vtkVoronoiKernel(),
"gaussian": vtk.vtkGaussianKernel(),
"shepard": vtk.vtkShepardKernel(),
"linear": vtk.vtkLinearKernel()
}
pointnumpyarray = np.array(
[points_interpol[pt] for pt in points_interpol])
out_u_grid = vtk.vtkUnstructuredGrid()
r = vtk.vtkPoints()
r.SetData(numpy_to_vtk(pointnumpyarray))
out_u_grid.SetPoints(r)
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(self.output)
locator.BuildLocator()
interpolator = vtk.vtkPointInterpolator()
interpolator.SetInputData(out_u_grid)
interpolator.SetSourceData(self.output)
interpolator.SetKernel(kernels[interpolation_method])
interpolator.SetLocator(locator)
interpolator.Update()
return interpolator.GetOutput().GetPointData()
def get_vtk_point_locator(centerline):
"""Wrapper for vtkStaticPointLocator.
Args:
centerline (vtkPolyData): Input vtkPolyData.
Returns:
locator (vtkStaticPointLocator): Point locator of the input surface.
"""
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(centerline)
locator.BuildLocator()
return locator
def showPointCloud(modelNodeID):
model = slicer.mrmlScene.GetNodeByID(modelNodeID)
polydata = model.GetPolyData()
# Reuse the locator
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(polydata)
locator.BuildLocator()
# Remove isolated points
removal = vtk.vtkRadiusOutlierRemoval()
removal.SetInputData(polydata)
removal.SetLocator(locator)
removal.SetRadius(10)
removal.SetNumberOfNeighbors(2)
removal.GenerateOutliersOn()
# Time execution
timer = vtk.vtkTimerLog()
timer.StartTimer()
removal.Update()
timer.StopTimer()
time = timer.GetElapsedTime()
print("Time to remove points: {0}".format(time))
print(" Number removed: {0}".format(removal.GetNumberOfPointsRemoved()),
" (out of: {}".format(polydata.GetNumberOfPoints()))
# First output are the non-outliers
remMapper = vtk.vtkPointGaussianMapper()
remMapper.SetInputConnection(removal.GetOutputPort())
remMapper.EmissiveOff()
remMapper.SetScaleFactor(0.0)
remActor = vtk.vtkActor()
remActor.SetMapper(remMapper)
lm = slicer.app.layoutManager()
tdWidget = lm.threeDWidget(0)
tdView = tdWidget.threeDView()
rWin = tdView.renderWindow()
rCollection = rWin.GetRenderers()
renderer = rCollection.GetItemAsObject(0)
# Add the actors to the renderer, set the background and size
#
renderer.AddActor(remActor)
def showPointCloud(modelNodeID):
model = slicer.mrmlScene.GetNodeByID(modelNodeID)
polydata = model.GetPolyData()
# Reuse the locator
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(polydata)
locator.BuildLocator()
# Remove isolated points
removal = vtk.vtkRadiusOutlierRemoval()
removal.SetInputData(polydata)
removal.SetLocator(locator)
removal.SetRadius(10)
removal.SetNumberOfNeighbors(2)
removal.GenerateOutliersOn()
# Time execution
timer = vtk.vtkTimerLog()
timer.StartTimer()
removal.Update()
timer.StopTimer()
time = timer.GetElapsedTime()
print("Time to remove points: {0}".format(time))
print(" Number removed: {0}".format(removal.GetNumberOfPointsRemoved()),
" (out of: {}".format(polydata.GetNumberOfPoints()))
# First output are the non-outliers
remMapper = vtk.vtkPointGaussianMapper()
remMapper.SetInputConnection(removal.GetOutputPort())
remMapper.EmissiveOff()
remMapper.SetScaleFactor(0.0)
remActor = vtk.vtkActor()
remActor.SetMapper(remMapper)
lm = slicer.app.layoutManager()
tdWidget = lm.threeDWidget(0)
tdView = tdWidget.threeDView()
rWin = tdView.renderWindow()
rCollection = rWin.GetRenderers()
renderer = rCollection.GetItemAsObject(0)
# Add the actors to the renderer, set the background and size
#
renderer.AddActor(remActor)
def findClosestPointsTwoLists(X_source, X_target):
'''return the closest points indexes in X_source from the X_target points,
indexes output has the same length than X_target'''
listPoints = X_source
points = vtk.vtkPoints()
points.SetDataTypeToDouble()
listProbePoints = X_target
probePoints = vtk.vtkPoints()
probePoints.SetDataTypeToDouble()
for [x, y] in listPoints:
points.InsertNextPoint(x, y, 0.)
for [x, y] in listProbePoints:
probePoints.InsertNextPoint(x, y, 0.)
polydata = vtk.vtkPolyData()
polydata.SetPoints(points)
points.ComputeBounds()
staticLocator = vtk.vtkStaticPointLocator()
staticLocator.SetDataSet(polydata)
staticLocator.SetNumberOfPointsPerBucket(5)
staticLocator.AutomaticOn()
staticLocator.BuildLocator()
staticClosestN = vtk.vtkIdList()
ind = np.zeros(len(X_target), dtype=np.int)
D = np.zeros(len(X_target))
math = vtk.vtkMath()
x = [0, 0, 0]
p = [0, 0, 0]
staticClosestN = vtk.vtkIdList()
for i in range(len(X_target)):
staticLocator.FindClosestNPoints(1, probePoints.GetPoint(i),
staticClosestN)
ind[i] = staticClosestN.GetId(0) # we then select the closest point
points.GetPoint(ind[i], x)
probePoints.GetPoint(i, p)
D[i] = math.Distance2BetweenPoints(x, p)**0.5
return ind, D
def opyfBuildLocatorandStuff3D(X):
npPoints = X
points = vtk.vtkPoints()
points.SetDataTypeToDouble()
probePoints = vtk.vtkPoints()
probePoints.SetDataTypeToDouble()
for [x, y, z] in npPoints:
points.InsertNextPoint(x, y, z)
probePoints.InsertNextPoint(x, y, z)
polydata = vtk.vtkPolyData()
polydata.SetPoints(points)
points.ComputeBounds()
staticLocator = vtk.vtkStaticPointLocator()
staticLocator.SetDataSet(polydata)
staticLocator.SetNumberOfPointsPerBucket(5)
staticLocator.AutomaticOn()
staticLocator.BuildLocator()
return staticLocator, points, probePoints
locator.FindClosestNPoints(10, probePoints.GetPoint(0), closestN)
# Time the deletion of the locator. The incremental locator is quite slow due
# to fragmented memory.
timer.StartTimer()
del locator
timer.StopTimer()
time2 = timer.GetElapsedTime()
totalTime = time + opTime + time2
print(" Delete Point Locator: {0}".format(time2))
print(" Point Locator (Total): {0}".format(totalTime))
print("\n")
# StaticPointLocator
# Time the creation of static point locator
staticLocator = vtk.vtkStaticPointLocator()
staticLocator.SetDataSet(polydata)
staticLocator.SetNumberOfPointsPerBucket(5)
staticLocator.AutomaticOn()
staticTimer = vtk.vtkTimerLog()
staticTimer.StartTimer()
staticLocator.BuildLocator()
staticTimer.StopTimer()
StaticTime = staticTimer.GetElapsedTime()
print("Build Static Point Locator: {0}".format(StaticTime))
# Now probe the dataset with FindClosestPoint()
math.RandomSeed(314159)
staticTimer.StartTimer()
for i in range (0,numProbes):
output = pl3d.GetOutput().GetBlock(0)
# Create a probe volume
center = output.GetCenter()
bounds = output.GetBounds()
length = output.GetLength()
probe = vtk.vtkImageData()
probe.SetDimensions(res,res,res)
probe.SetOrigin(bounds[0],bounds[2],bounds[4])
probe.SetSpacing((bounds[1]-bounds[0])/(res-1),
(bounds[3]-bounds[2])/(res-1),
(bounds[5]-bounds[4])/(res-1))
# Reuse the locator
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(output)
locator.BuildLocator()
# Use a gaussian kernel------------------------------------------------
gaussianKernel = vtk.vtkGaussianKernel()
gaussianKernel.SetRadius(0.5)
gaussianKernel.SetSharpness(4)
print ("Radius: {0}".format(gaussianKernel.GetRadius()))
interpolator = vtk.vtkPointInterpolator()
interpolator.SetInputData(probe)
interpolator.SetSourceData(output)
interpolator.SetKernel(gaussianKernel)
interpolator.SetLocator(locator)
interpolator.SetNullPointsStrategyToClosestPoint()
def opyfFindBlobs3D(scalars,
th1,
th2=None,
R=1.,
minArea=None,
CenterType='barycenter'):
if th2 is None:
th2 = np.max(scalars)
[h, w, p] = scalars.shape
scalars = scalars.T.copy()
scalars = scalars.ravel()
# (scalars>=th1)*(scalars<=th2)
# indth=np.where((scalars>=th1)*(scalars<=th2))
# Points XYZ
x, y, z = np.mgrid[0:h, 0:w, 0:p]
pts = np.empty(z.shape + (3, ), dtype=float)
pts[..., 0] = x
pts[..., 1] = y
pts[..., 2] = z
pts = pts.transpose(2, 1, 0, 3).copy()
pts.shape = pts.size / 3, 3
# VTK
points = vtk.vtkPoints()
points.SetDataTypeToDouble()
for [x, y, z] in pts:
points.InsertNextPoint(x, y, z)
Scalarsvtk = vtk.vtkFloatArray()
for s in scalars:
Scalarsvtk.InsertNextValue(s)
Ids = vtk.vtkIdList()
polydata = vtk.vtkPolyData()
# polydata=vtk.vtkUnstructuredGrid()
polydata.SetPoints(points)
polydata.GetPointData().SetScalars(Scalarsvtk)
ThresholdIn = vtk.vtkThresholdPoints()
ThresholdIn.SetInputData(polydata)
# ThresholdIn.ThresholdByLower(230.)
ThresholdIn.ThresholdBetween(th1, th2)
ThresholdIn.Update()
PointsThresh = ThresholdIn.GetOutput().GetPoints()
staticLocator = vtk.vtkStaticPointLocator()
staticLocator.SetDataSet(ThresholdIn.GetOutput())
staticLocator.SetNumberOfPointsPerBucket(5)
staticLocator.AutomaticOn()
staticLocator.BuildLocator()
S = ThresholdIn.GetOutput().GetPointData().GetArray(0)
nppointsArr = vtk_to_numpy(S)
idspointsThresh = np.arange(0, PointsThresh.GetNumberOfPoints())
entitiy = 0
i = idspointsThresh[0]
idsStored = np.array([])
ids1 = [0]
C = 1
blob3D = []
indstore = 0
while len(idspointsThresh) > 0:
C = 1
while C == 1:
ids2 = []
l = len(idsStored)
for i in ids1:
PointswhithinRadius = vtk.vtkIdList()
staticLocator.FindPointsWithinRadius(R,
PointsThresh.GetPoint(i),
PointswhithinRadius)
for j in range(PointswhithinRadius.GetNumberOfIds()):
tempid = PointswhithinRadius.GetId(j)
if len(np.where(idsStored == tempid)[0]) == 0:
idsStored = np.append(idsStored, np.int(tempid))
ids2.append(tempid)
indDel = np.where(idspointsThresh == tempid)
idspointsThresh = np.delete(idspointsThresh, indDel, 0)
if len(idsStored) == l:
C = 0
blob3D.append(idsStored[indstore:].astype(int))
indstore = len(idsStored)
entitiy += 1
if len(idspointsThresh) > 0:
ids1 = [idspointsThresh[0]]
else:
ids1 = ids2
C = np.zeros((len(blob3D), 3))
AreaBlob = []
X = vtk_to_numpy(PointsThresh.GetData())
blob3Dout = []
for i in range(len(blob3D)):
ind = blob3D[i]
Xblob = X[ind]
blob3Dout.append(Xblob)
pxInts = nppointsArr[ind]
if CenterType == 'barycenter':
C[i, :] = np.sum(Xblob * np.array([pxInts, pxInts, pxInts]).T,
axis=0) / (np.sum(pxInts))
elif CenterType == 'geometric':
C[i, :] = np.sum(Xblob, axis=0) / (np.float(len(pxInts)))
AreaBlob.append(len(Xblob))
AreaBlob = np.array(AreaBlob)
blob3Dout = np.array(blob3Dout)
if minArea is not None:
C = C[np.where(AreaBlob > minArea)]
blob3Dout = blob3Dout[np.where(AreaBlob > minArea)]
AreaBlob = AreaBlob[np.where(AreaBlob > minArea)]
return blob3Dout, C, AreaBlob
# Create an initial set of points and associated dataset
rpts = vtk.vtkPointSource()
rpts.SetNumberOfPoints(numPts)
rpts.SetDistributionToUniform()
rpts.SetRadius(1)
rpts.Update()
polydata = rpts.GetOutput()
# Print initial statistics
print("Processing NumPts: {0}".format(numPts))
timer = vtk.vtkTimerLog()
# Create the locator.
sclean = vtk.vtkStaticPointLocator()
sclean.SetDataSet(polydata)
timer.StartTimer()
sclean.BuildLocator()
timer.StopTimer()
time = timer.GetElapsedTime()
print("Build Static Point Locator (threaded): {0}".format(time))
print("Number of Divisions: ", sclean.GetDivisions())
# Create a comparison point locator.
clean = vtk.vtkPointLocator()
clean.SetDataSet(polydata)
timer.StartTimer()
clean.BuildLocator()
def npInterpolateVTK3D(npPoints,
npValues,
npTargetPoints,
ParametreInterpolatorVTK=None):
if ParametreInterpolatorVTK == None:
ParametreInterpolatorVTK = {
'kernel': 'Gaussian',
'Radius': 10.,
'Sharpness': 2.
}
print('[' + ParametreInterpolatorVTK['kernel'] +
' Interpolation - Radius =' +
str(ParametreInterpolatorVTK['Radius']) + ' - Sharpness =' +
str(ParametreInterpolatorVTK['Sharpness']) + '] processing... ')
#
# Set Source Points
UnGrid = vtk.vtkUnstructuredGrid()
vtkP = vtk.vtkPoints()
for [x, y, z] in npPoints:
vtkP.InsertNextPoint(x, y, z)
UnGrid.SetPoints(vtkP)
# Set source Point Values
l, c = npValues.shape
for i in range(0, c):
vtkFA = vtk.vtkFloatArray()
vtkFA.SetName('Values' + str(i))
for v in npValues:
vtkFA.InsertNextValue(v[i])
UnGrid.GetPointData().AddArray(vtkFA)
# Set Target Points
vtkTP = vtk.vtkPoints()
for [x, y, z] in npTargetPoints:
vtkTP.InsertNextPoint(x, y, z)
vtkTargetPointsPolyData = vtk.vtkPolyData()
vtkTargetPointsPolyData.SetPoints(vtkTP)
if ParametreInterpolatorVTK['kernel'] == 'Gaussian':
Kernel = vtk.vtkGaussianKernel()
Kernel.SetSharpness(ParametreInterpolatorVTK['Sharpness'])
Kernel.SetRadius(ParametreInterpolatorVTK['Radius'])
if ParametreInterpolatorVTK['kernel'] == 'Voronoi':
Kernel = vtk.vtkVoronoiKernel()
if ParametreInterpolatorVTK['kernel'] == 'Shepard':
Kernel = vtk.vtkShepardKernel()
Kernel.SetRadius(ParametreInterpolatorVTK['Radius'])
# Build locator
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(UnGrid)
locator.BuildLocator()
# build interpolator
interp = vtk.vtkPointInterpolator()
interp.SetInputData(vtkTargetPointsPolyData)
interp.SetSourceData(UnGrid)
interp.SetKernel(Kernel)
interp.SetLocator(locator)
interp.GetLocator().SetNumberOfPointsPerBucket(5)
interp.SetNullPointsStrategyToMaskPoints()
interp.Update()
outputInterp = interp.GetOutput()
pointsArr = outputInterp.GetPoints().GetData()
nppointsArr = vtk_to_numpy(pointsArr)
pdata = outputInterp.GetPointData()
# Convert volocities into Numpy Array
npOutputValues = np.zeros((len(npTargetPoints), c))
for i in range(0, c):
vtkOutputValues = pdata.GetArray('Values' + str(i))
npOutputValues[:, i] = vtk_to_numpy(vtkOutputValues)
return npOutputValues
# serve as starting points that shoot rays towards the # center of the fist sphere. # sphere = vtk.vtkSphereSource() sphere.SetThetaResolution(2 * res) sphere.SetPhiResolution(res) sphere.Update() mapper = vtk.vtkPolyDataMapper() mapper.SetInputConnection(sphere.GetOutputPort()) actor = vtk.vtkActor() actor.SetMapper(mapper) # Now the locator loc = vtk.vtkStaticPointLocator() loc.SetDataSet(sphere.GetOutput()) loc.SetNumberOfPointsPerBucket(5) loc.BuildLocator() locPD = vtk.vtkPolyData() loc.GenerateRepresentation(4, locPD) locMapper = vtk.vtkPolyDataMapper() locMapper.SetInputData(locPD) locActor = vtk.vtkActor() locActor.SetMapper(locMapper) locActor.GetProperty().SetRepresentationToWireframe() # Now the outer sphere sphere2 = vtk.vtkSphereSource() sphere2.SetThetaResolution(res)
def interpolate_data(self, points, disp, stretch=None, shear=None, on_deformed=True, kernel_radius=3.0,
kernel_sharpness=1.0, remove_null=True, return_deformed=True):
"""
Interpolate data on the mesh. This can be used for comparing experimental and simulation data together.
on_deform selects whether to interpolate the data on the original or on the deformed configuration
"""
if stretch is None:
stretch = np.array([])
if shear is None:
shear = np.array([])
# We need nPts*3 data for vtk
if points.shape[1] == 2:
points_ = np.zeros([points.shape[0], 3])
points_[:,0:2] = points
# Deform data if needed
if on_deformed:
points_[:,0:2] = points + disp
# Generate vtk points structure with all data
vtkpoints = vtk.vtkPoints()
vtkpoints.SetData(numpy_support.numpy_to_vtk(points_))
vtkdisp = vtk.vtkDoubleArray()
vtkdisp.SetName("disp")
vtkdisp.SetNumberOfComponents(disp.shape[1])
vtkdisp.SetNumberOfTuples(disp.shape[0])
vtkdisp.SetVoidArray(disp.flatten(), disp.size, 1)
vtkstretch = vtk.vtkDoubleArray()
vtkstretch.SetName("stretch")
vtkstretch.SetNumberOfComponents(1)
vtkstretch.SetNumberOfTuples(stretch.size)
vtkstretch.SetVoidArray(stretch, stretch.size, 1)
shear = shear.reshape([-1, 4])
vtkshear = vtk.vtkDoubleArray()
vtkshear.SetName("shear")
vtkshear.SetNumberOfComponents(shear.shape[1])
vtkshear.SetNumberOfTuples(shear.shape[0])
vtkshear.SetVoidArray(shear, shear.size, 1)
vtkpointset = vtk.vtkPolyData()
vtkpointset.SetPoints(vtkpoints)
vtkpointset.GetPointData().AddArray(vtkdisp)
vtkpointset.GetPointData().AddArray(vtkstretch)
vtkpointset.GetPointData().AddArray(vtkshear)
# Build the locator for the interpolation
locator = vtk.vtkStaticPointLocator()
locator.SetDataSet(vtkpointset)
locator.BuildLocator()
# Build the Gaussian kernel
kernel = vtk.vtkGaussianKernel()
kernel.SetKernelFootprint(0)
kernel.SetRadius(kernel_radius)
kernel.SetSharpness(kernel_sharpness)
# If the interpolation is performed on the deformed configuration, warp the data
if on_deformed:
disp_ = np.zeros(self.x_nodes.shape)
disp_[:,0:2] = self.disp
warpData = vtk.vtkDoubleArray()
warpData.SetName("warp")
warpData.SetNumberOfComponents(3)
warpData.SetNumberOfTuples(self.x_nodes.shape[0])
warpData.SetVoidArray(disp_, self.x_nodes.shape[0], 1)
self.vtkmesh.GetPointData().AddArray(warpData)
self.vtkmesh.GetPointData().SetActiveVectors(warpData.GetName())
warpVector = vtk.vtkWarpVector()
warpVector.SetInputData(self.vtkmesh)
warpVector.Update()
self.vtkmesh = warpVector.GetOutput()
coarseInterpolator = vtk.vtkPointInterpolator()
coarseInterpolator.SetSourceData(vtkpointset)
coarseInterpolator.SetInputData(self.vtkmesh)
coarseInterpolator.SetKernel(kernel)
coarseInterpolator.SetLocator(locator)
coarseInterpolator.PassPointArraysOff()
coarseInterpolator.SetNullPointsStrategyToMaskPoints() # Get points with an invalid interpolation
coarseInterpolator.Update()
vtkmesh = coarseInterpolator.GetOutput()
if return_deformed:
self.x_nodes[:,0:2] += self.disp
self.disp = numpy_support.vtk_to_numpy(vtkmesh.GetPointData().GetArray("disp"))
self.stretch = numpy_support.vtk_to_numpy(vtkmesh.GetPointData().GetArray("stretch"))
self.shear = numpy_support.vtk_to_numpy(vtkmesh.GetPointData().GetArray("shear"))
if remove_null:
not_null = (numpy_support.vtk_to_numpy(vtkmesh.GetPointData().GetArray(
coarseInterpolator.GetValidPointsMaskArrayName()))).astype(bool)
idlist_old = np.arange(self.x_nodes.shape[0])[not_null]
self.x_nodes = self.x_nodes[not_null]
self.disp = self.disp[not_null]
self.stretch = self.stretch[not_null]
self.shear = self.shear[not_null]
idlist_new = np.arange(self.x_nodes.shape[0])
c1 = np.in1d(self.connec[:, 0], idlist_old)
c2 = np.in1d(self.connec[:, 1], idlist_old)
c3 = np.in1d(self.connec[:, 2], idlist_old)
self.connec = self.connec[np.logical_and(np.logical_and(c1,c2),c3)]
for i in idlist_new:
self.connec[self.connec == idlist_old[i]] = i
points = vtk.vtkPoints()
points.SetData(numpy_support.numpy_to_vtk(self.x_nodes))
vtkmesh.SetPoints(points)
cells = vtk.vtkCellArray()
cells.SetCells(self.connec.shape[0], numpy_support.numpy_to_vtkIdTypeArray(self.connec))
vtkmesh.SetPolys(cells)
self.shear = self.shear.reshape([-1, 2, 2])
