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ClipUnstructuredGridWithPlane

vtk-examples/PythonicAPI/UnstructuredGrid/ClipUnstructuredGridWithPlane

Description

The example uses vtkTableBasedClipDataSet to clip a vtkUnstructuredGrid. The resulting output and clipped output are presented in yellow and red respectively. To illustrate the clipped interfaces, the example uses a vtkTransform to rotate each output about their centers.

Note that unlike other clipping filters (except for vtkClipPolyData), vtkTableBasedClipDataSet retains the original cells if they are not clipped.

After exiting, the example reports the number of each cell type for each output:

------------------------
The inside dataset contains a vtkUnstructuredGrid that has 26116 cells
 Cell type vtkTetra occurs 3751 times.
 Cell type vtkHexahedron occurs 17361 times.
 Cell type vtkWedge occurs 628 times.
 Cell type vtkPyramid occurs 4376 times.
------------------------
The clipped dataset contains a vtkUnstructuredGrid that has 25655 cells
 Cell type vtkTetra occurs 3715 times.
 Cell type vtkHexahedron occurs 16984 times.
 Cell type vtkWedge occurs 616 times.
 Cell type vtkPyramid occurs 4340 times.

Compare these results with ClipUnstructuredGridWithPlane2. Also, the resulting vtkUnstructuredGrid's have a quarter of the number of cells.

usage

ClipUnstructuredGridWithPlane treemesh.vtk

thanks

Thanks to Bane Sullivan for sharing the treemesh.vtk unstructured grid dataset.

Other languages

See (Cxx), (Python)

Question

If you have a question about this example, please use the VTK Discourse Forum

Code

ClipUnstructuredGridWithPlane.py

#!/usr/bin/env python3

import collections

# noinspection PyUnresolvedReferences
import vtkmodules.vtkInteractionStyle
# noinspection PyUnresolvedReferences
import vtkmodules.vtkRenderingOpenGL2
from vtkmodules.vtkCommonColor import vtkNamedColors
from vtkmodules.vtkCommonDataModel import (
    vtkCellTypes,
    vtkPlane
)
from vtkmodules.vtkCommonTransforms import vtkTransform
from vtkmodules.vtkFiltersGeneral import vtkTableBasedClipDataSet
from vtkmodules.vtkIOLegacy import vtkUnstructuredGridReader
from vtkmodules.vtkRenderingCore import (
    vtkActor,
    vtkDataSetMapper,
    vtkRenderWindow,
    vtkRenderWindowInteractor,
    vtkRenderer
)


def get_program_parameters():
    import argparse
    description = 'Use a vtkTableBasedClipDataSet to clip a vtkUnstructuredGrid.'
    epilogue = '''
 Use a vtkTableBasedClipDataSet to clip a vtkUnstructuredGrid.
 The resulting output and clipped output are presented in yellow and red respectively.
 To illustrate the clipped interfaces, the example uses a vtkTransform to rotate each
    output about their centers.
 Note: This clipping filter does retain the original cells if they are not clipped.

   '''
    parser = argparse.ArgumentParser(description=description, epilog=epilogue,
                                     formatter_class=argparse.RawDescriptionHelpFormatter)
    parser.add_argument('filename', help='treemesh.vtk')
    args = parser.parse_args()
    return args.filename


def main():
    filename = get_program_parameters()

    # Create the reader for the data.
    reader = vtkUnstructuredGridReader(file_name=filename)
    reader.update()

    bounds = reader.output.bounds
    center = reader.output.center

    colors = vtkNamedColors()

    renderer = vtkRenderer(background=colors.GetColor3d('Wheat'))
    renderer.UseHiddenLineRemovalOn()
    render_window = vtkRenderWindow(size=(640, 480), window_name='ClipUnstructuredGridWithPlane')
    render_window.AddRenderer(renderer)
    interactor = vtkRenderWindowInteractor()
    interactor.render_window = render_window

    x_norm = [-1.0, -1.0, 1.0]

    clip_plane = vtkPlane(origin=center, normal=x_norm)
    clipper = vtkTableBasedClipDataSet(clip_function=clip_plane, input_data=reader.output,
                                       value=0.0, generate_clipped_output=True)
    clipper.update()

    inside_mapper = vtkDataSetMapper(scalar_visibility=False, input_data=clipper.output)
    inside_actor = vtkActor(mapper=inside_mapper)
    inside_actor.property.diffuse_color = colors.GetColor3d('Banana')
    inside_actor.property.ambient = 0.3
    inside_actor.property.edge_visibility = True

    clipped_mapper = vtkDataSetMapper(scalar_visibility=False, input_data=clipper.clipped_output)
    clipped_actor = vtkActor(mapper=clipped_mapper)
    clipped_actor.property.diffuse_color = colors.GetColor3d('Tomato')
    clipped_actor.property.ambient = 0.3
    clipped_actor.property.edge_visibility = True

    # Create transforms to make a better visualization
    # Reverse the sign of each element in center.
    rev_center = tuple(-i for i in center)

    inside_transform = vtkTransform()
    inside_transform.Translate(-(bounds[1] - bounds[0]) * 0.75, 0, 0)
    inside_transform.Translate(*center)
    inside_transform.RotateY(-120.0)
    inside_transform.Translate(*rev_center)
    inside_actor.user_transform = inside_transform

    clipped_transform = vtkTransform()
    clipped_transform.Translate((bounds[1] - bounds[0]) * 0.75, 0, 0)
    clipped_transform.Translate(*center)
    clipped_transform.RotateY(60.0)
    clipped_transform.Translate(*rev_center)
    clipped_actor.user_transform = clipped_transform

    renderer.AddViewProp(clipped_actor)
    renderer.AddViewProp(inside_actor)

    renderer.ResetCamera()
    renderer.active_camera.Dolly(1.4)
    renderer.ResetCameraClippingRange()
    render_window.Render()

    interactor.Start()

    # Generate a report.
    number_of_cells = clipper.output.number_of_cells
    print('------------------------')
    print(f'The inside dataset contains a {clipper.output.class_name} that has {number_of_cells} cells')
    cell_map = dict()
    for i in range(0, number_of_cells):
        cell_map.setdefault(clipper.output.GetCellType(i), 0)
        cell_map[clipper.output.GetCellType(i)] += 1
    # Sort by key and put into an OrderedDict.
    # An OrderedDict remembers the order in which the keys have been inserted.
    for k, v in collections.OrderedDict(sorted(cell_map.items())).items():
        print(f' Cell type {vtkCellTypes.GetClassNameFromTypeId(k)} occurs {v} times.')

    number_of_cells = clipper.clipped_output.number_of_cells
    print('------------------------')
    print(f'The clipped dataset contains a {clipper.clipped_output.class_name} that has {number_of_cells} cells')
    outside_cell_map = dict()
    for i in range(0, number_of_cells):
        outside_cell_map.setdefault(clipper.clipped_output.GetCellType(i), 0)
        outside_cell_map[clipper.clipped_output.GetCellType(i)] += 1
    for k, v in collections.OrderedDict(sorted(outside_cell_map.items())).items():
        print(f' Cell type {vtkCellTypes.GetClassNameFromTypeId(k)} occurs {v} times.')


if __name__ == '__main__':
    main()