CarotidFlowGlyphs
vtk-examples/Python/VisualizationAlgorithms/CarotidFlowGlyphs
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Code¶
CarotidFlowGlyphs.py
#!/usr/bin/env python
import vtk
def main():
fileName = get_program_parameters()
colors = vtk.vtkNamedColors()
ren1 = vtk.vtkRenderer()
renWin = vtk.vtkRenderWindow()
renWin.AddRenderer(ren1)
iren = vtk.vtkRenderWindowInteractor()
iren.SetRenderWindow(renWin)
# Create the pipeline.
#
reader = vtk.vtkStructuredPointsReader()
reader.SetFileName(fileName)
threshold = vtk.vtkThresholdPoints()
threshold.SetInputConnection(reader.GetOutputPort())
threshold.ThresholdByUpper(200)
mask = vtk.vtkMaskPoints()
mask.SetInputConnection(threshold.GetOutputPort())
mask.SetOnRatio(5)
cone = vtk.vtkConeSource()
cone.SetResolution(11)
cone.SetHeight(1)
cone.SetRadius(0.25)
cones = vtk.vtkGlyph3D()
cones.SetInputConnection(mask.GetOutputPort())
cones.SetSourceConnection(cone.GetOutputPort())
cones.SetScaleFactor(0.4)
cones.SetScaleModeToScaleByVector()
lut = vtk.vtkLookupTable()
lut.SetHueRange(.667, 0.0)
lut.Build()
scalarRange = [0] * 2
cones.Update()
scalarRange[0] = cones.GetOutput().GetPointData().GetScalars().GetRange()[0]
scalarRange[1] = cones.GetOutput().GetPointData().GetScalars().GetRange()[1]
print("range: ", scalarRange[0], ", ", scalarRange[1])
vectorMapper = vtk.vtkPolyDataMapper()
vectorMapper.SetInputConnection(cones.GetOutputPort())
vectorMapper.SetScalarRange(scalarRange[0], scalarRange[1])
vectorMapper.SetLookupTable(lut)
vectorActor = vtk.vtkActor()
vectorActor.SetMapper(vectorMapper)
# Speed contours.
iso = vtk.vtkContourFilter()
iso.SetInputConnection(reader.GetOutputPort())
iso.SetValue(0, 175)
isoMapper = vtk.vtkPolyDataMapper()
isoMapper.SetInputConnection(iso.GetOutputPort())
isoMapper.ScalarVisibilityOff()
isoActor = vtk.vtkActor()
isoActor.SetMapper(isoMapper)
isoActor.GetProperty().SetRepresentationToWireframe()
isoActor.GetProperty().SetOpacity(0.25)
# Outline
outline = vtk.vtkOutlineFilter()
outline.SetInputConnection(reader.GetOutputPort())
outlineMapper = vtk.vtkPolyDataMapper()
outlineMapper.SetInputConnection(outline.GetOutputPort())
outlineActor = vtk.vtkActor()
outlineActor.SetMapper(outlineMapper)
outlineActor.GetProperty().SetColor(colors.GetColor3d("Black"))
# Add the actors to the renderer, set the background and size.
#
ren1.AddActor(outlineActor)
ren1.AddActor(vectorActor)
ren1.AddActor(isoActor)
ren1.SetBackground(colors.GetColor3d("Wheat"))
renWin.SetSize(640, 480)
renWin.SetWindowName('CarotidFlowGlyphs')
cam1 = vtk.vtkCamera()
cam1.SetClippingRange(17.4043, 870.216)
cam1.SetFocalPoint(136.71, 104.025, 23)
cam1.SetPosition(204.747, 258.939, 63.7925)
cam1.SetViewUp(-0.102647, -0.210897, 0.972104)
cam1.Zoom(1.2)
ren1.SetActiveCamera(cam1)
# Render the image.
#
renWin.Render()
iren.Start()
def get_program_parameters():
import argparse
description = 'Visualizing blood flow in human carotid arteries.'
epilogue = '''
Cone glyphs indicate flow direction and magnitude.
'''
parser = argparse.ArgumentParser(description=description, epilog=epilogue,
formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('filename', help='carotid.vtk.')
args = parser.parse_args()
return args.filename
if __name__ == '__main__':
main()