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# CarotidFlowGlyphs

VTKEx/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)

        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(1.6)
        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()