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# ComplexV

VTKEx/Python/Visualization/ComplexV

### Description

ComplexV from the VTK Textbook. The original example was written in TCL.

The example shows 167,000 3D vectors (using oriented and scaled lines) in the region of the human carotid artery. The larger vectors lie inside the arteries, the smaller vectors lie outside the arteries and are randomly oriented (measurement error) but small in magnitude. Clearly the details of the vector field are not discernible from this image.

Other languages

See (Cxx), (Java)

Question

If you have a simple question about this example contact us at VTKExProject If your question is more complex and may require extended discussion, please use the VTK Discourse Forum

### Code

ComplexV.py

    #!/usr/bin/env python

    import vtk

    def main():
        fileName = get_program_parameters()

        colors = vtk.vtkNamedColors()

        reader = vtk.vtkStructuredPointsReader()
        reader.SetFileName(fileName)

        hhog = vtk.vtkHedgeHog()
        hhog.SetInputConnection(reader.GetOutputPort())
        hhog.SetScaleFactor(0.3)

        lut = vtk.vtkLookupTable()
        # lut.SetHueRange(.667, 0.0)
        lut.Build()

        hhogMapper = vtk.vtkPolyDataMapper()
        hhogMapper.SetInputConnection(hhog.GetOutputPort())
        hhogMapper.SetScalarRange(50, 550)
        hhogMapper.SetLookupTable(lut)

        hhogActor = vtk.vtkActor()
        hhogActor.SetMapper(hhogMapper)

        outline = vtk.vtkOutlineFilter()
        outline.SetInputConnection(reader.GetOutputPort())

        outlineMapper = vtk.vtkPolyDataMapper()
        outlineMapper.SetInputConnection(outline.GetOutputPort())

        outlineActor = vtk.vtkActor()
        outlineActor.SetMapper(outlineMapper)
        outlineActor.GetProperty().SetColor(0, 0, 0)

        aRenderer = vtk.vtkRenderer()
        aRenderWindow = vtk.vtkRenderWindow()
        aRenderWindow.AddRenderer(aRenderer)
        anInteractor = vtk.vtkRenderWindowInteractor()
        anInteractor.SetRenderWindow(aRenderWindow)
        aRenderWindow.SetSize(640, 480)

        aRenderer.AddActor(outlineActor)
        aRenderer.AddActor(hhogActor)

        aRenderer.SetBackground(colors.GetColor3d("Gray"))

        # Generate an interesting view.

        aRenderer.GetActiveCamera().SetFocalPoint(0, 0, 0)
        aRenderer.GetActiveCamera().SetPosition(1, 0, 0)
        aRenderer.GetActiveCamera().SetViewUp(0, 0, 1)
        aRenderer.ResetCamera()

        aRenderer.GetActiveCamera().Azimuth(60)
        aRenderer.GetActiveCamera().Elevation(30)
        aRenderer.GetActiveCamera().Dolly(1.1)
        aRenderer.ResetCameraClippingRange()

        aRenderWindow.Render()

        # Interact with the data.
        anInteractor.Start()

    def get_program_parameters():
        import argparse
        description = 'Vector visualization techniques.'
        epilogue = '''
        '''
        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()