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CurvaturesNormalsElevations

Repository source: CurvaturesNormalsElevations

Description

In this example we are coloring the surface by partitioning the Gaussian and Mean curvatures into bands with arrows colored by elevation to display the normals.

Rather beautiful surfaces are generated.

The banded contour filter and an indexed/categorical lookup table is used to generate the curvature bands on the surface. To further enhance the surface, the surface normals are glyphed and colored by elevation using an ordinal lookup table.

Note that:

  • If the regions on a surface have zero Gaussian curvature, then they can be flattened into a plane with no distortion, and the geometry of the region is Euclidean geometry.

  • If the regions on a surface have positive Gaussian curvature, then the geometry of the surface is spherical geometry.

  • If the regions on the surface have a negative Gaussian curvature, then the geometry of the surface is hyperbolic geometry.

In the above image you can see that the random hills incorporate all of these geometries.

The surface selected is the parametric random hills surface. The problem with the random hills surface is:

  • Most of the gaussian curvatures will lie in the range -1 to 0.2 (say) with a few large values say 20 to 40 at the peaks of the hills.
  • The edges of the random hills surface also have large irregular values so we need to handle these also. In order to fix this, a function is provided to adjust the edges.

So we need to manually generate custom bands to group the curvatures. The bands selected in the examples show that the surface is mostly planar with some hyperbolic regions (saddle points) and some spherical regions.

Feel free to experiment with different color schemes and/or the other sources from the parametric function group or the torus etc.

A histogram of the frequencies can be output to the console. This is useful if you want to get an idea of the distribution of the scalars in each band.

Question

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

Code

CurvaturesNormalsElevations.py

#!/usr/bin/env python

import math
from collections import namedtuple, OrderedDict
from dataclasses import dataclass

import numpy as np
from vtk.util import numpy_support
from vtkmodules.numpy_interface import dataset_adapter as dsa
from vtkmodules.vtkCommonColor import (
    vtkColorSeries,
    vtkNamedColors
)
from vtkmodules.vtkCommonComputationalGeometry import (
    vtkParametricRandomHills,
    vtkParametricTorus
)
from vtkmodules.vtkCommonCore import (
    VTK_DOUBLE,
    vtkDoubleArray,
    vtkFloatArray,
    vtkIdList,
    vtkLookupTable,
    vtkPoints,
    vtkVariant,
    vtkVariantArray
)
from vtkmodules.vtkCommonDataModel import vtkPolyData
from vtkmodules.vtkCommonTransforms import vtkTransform
from vtkmodules.vtkFiltersCore import (
    vtkCleanPolyData,
    vtkDelaunay2D,
    vtkElevationFilter,
    vtkFeatureEdges,
    vtkGlyph3D,
    vtkGenerateIds,
    vtkMaskPoints,
    vtkPolyDataNormals,
    vtkReverseSense,
    vtkTriangleFilter
)
from vtkmodules.vtkFiltersGeneral import (
    vtkCurvatures,
    vtkTransformPolyDataFilter
)
from vtkmodules.vtkFiltersModeling import vtkBandedPolyDataContourFilter
from vtkmodules.vtkFiltersSources import (
    vtkArrowSource,
    vtkParametricFunctionSource,
    vtkPlaneSource,
    vtkSphereSource,
    vtkSuperquadricSource
)
from vtkmodules.vtkInteractionStyle import vtkInteractorStyleTrackballCamera
from vtkmodules.vtkInteractionWidgets import (
    vtkCameraOrientationWidget,
    vtkOrientationMarkerWidget,
    vtkScalarBarRepresentation,
    vtkScalarBarWidget,
    vtkTextRepresentation,
    vtkTextWidget
)
from vtkmodules.vtkRenderingAnnotation import vtkAxesActor, vtkScalarBarActor
from vtkmodules.vtkRenderingCore import (
    vtkActor,
    vtkColorTransferFunction,
    vtkPolyDataMapper,
    vtkRenderWindow,
    vtkRenderWindowInteractor,
    vtkRenderer,
    vtkTextActor,
    vtkTextProperty
)


def get_program_parameters():
    import argparse
    description = 'Demonstrates Gaussian and Mean curvatures on a surface, along with normals colored by elevation.'
    epilogue = '''
    For example: -s"Random Hills" -f
                 Will display the curvatures along with normals on the surface colored by elevation.
    '''
    parser = argparse.ArgumentParser(description=description, epilog=epilogue,
                                     formatter_class=argparse.RawDescriptionHelpFormatter)
    parser.add_argument('-s', '--surface_name', default='random hills', help='The name of the surface.')
    parser.add_argument('-f', '--frequency_table', action='store_true', help='Display the frequency table.')
    parser.add_argument('-omw', action='store_false',
                        help='Use an OrientationMarkerWidget instead of a CameraOrientationWidget.')

    args = parser.parse_args()
    return args.surface_name, args.frequency_table, args.omw


def main(argv):
    surface_name, frequency_table, use_camera_omw = get_program_parameters()

    available_surfaces = ['hills', 'parametric torus', 'plane', 'random hills', 'sphere', 'torus']
    # Surfaces whose curvatures need to be adjusted along the edges of the surface or constrained.
    needs_adjusting = ['hills', 'parametric torus', 'plane', 'random hills']

    surface_name = ' '.join(surface_name.lower().replace('_', ' ').split())
    if surface_name.lower() not in available_surfaces:
        print('Nonexistent surface:', surface_name)
        print('Available surfaces are:')
        asl = sorted(available_surfaces)
        asl = [asl[i].title() for i in range(0, len(asl))]
        asl = [asl[i:i + 5] for i in range(0, len(asl), 5)]
        for i in range(0, len(asl)):
            s = ', '.join(asl[i])
            if i < len(asl) - 1:
                s += ','
            print(f'   {s}')
        print('If a name has spaces in it, delineate the name with quotes e.g. "random hills"')
        return

    Surface = namedtuple('Surface', 'name source')
    surface = Surface(surface_name, get_source(surface_name, available_surfaces))

    # --------------------------------------------------------------------------------------
    # Get the filters, scalar range of curvatures and elevation along with the lookup tables.
    # --------------------------------------------------------------------------------------
    # Use an ordered dictionary as we want the keys in a specific order.
    curvatures = OrderedDict()
    curvatures['Gauss_Curvature'] = generate_gaussian_curvatures(surface, needs_adjusting,
                                                                 frequency_table=frequency_table)
    curvatures['Mean_Curvature'] = generate_mean_curvatures(surface, needs_adjusting, frequency_table=frequency_table)

    colors = vtkNamedColors()

    # Set the background color.
    colors.SetColor('BkgColor', [179, 204, 255, 255])
    colors.SetColor("ParaViewBkg", [82, 87, 110, 255])

    # Define viewport ranges [x_min, y_min, x_max, y_max]
    viewports = dict()
    viewports['Gauss_Curvature'] = [0.0, 0.0, 0.5, 1.0]
    viewports['Mean_Curvature'] = [0.5, 0.0, 1.0, 1.0]

    window_height = 800
    window_width = 2 * window_height

    # --------------------------------------------------
    # Create the RenderWindow, Renderers and Interactor.
    # --------------------------------------------------
    ren_win = vtkRenderWindow(size=(window_width, window_height), window_name='CurvaturesNormalsElevations')
    iren = vtkRenderWindowInteractor()
    iren.render_window = ren_win
    style = vtkInteractorStyleTrackballCamera()
    iren.interactor_style = style

    renderers = list()
    contour_widgets = dict()
    elevation_widgets = dict()
    # Set up the scalar bar properties.
    scalar_bar_properties = ScalarBarProperties()

    # Position the source name according to its length.
    text_positions = get_text_positions(available_surfaces,
                                        justification=TextProperty.Justification.VTK_TEXT_LEFT,
                                        vertical_justification=TextProperty.VerticalJustification.VTK_TEXT_TOP,
                                        width=0.45)

    text_property = vtkTextProperty(color=colors.GetColor3d('AliceBlue'), bold=True, italic=True, shadow=True,
                                    font_size=16,
                                    justification=TextProperty.Justification.VTK_TEXT_LEFT)
    text_actor = vtkTextActor(input=surface_name.title(), text_scale_mode=vtkTextActor.TEXT_SCALE_MODE_NONE,
                              text_property=text_property)
    # Create the text representation. Used for positioning the text actor.
    text_representation = vtkTextRepresentation(enforce_normalized_viewport_bounds=True)
    text_representation.position_coordinate.value = text_positions[surface.name]['p']
    text_representation.position2_coordinate.value = text_positions[surface.name]['p2']
    text_widget = vtkTextWidget(representation=text_representation, text_actor=text_actor, interactor=iren,
                                selectable=False)

    first = True
    for k, v in curvatures.items():
        src_mapper = vtkPolyDataMapper(scalar_range=v['scalar_range_curvatures'],
                                       lookup_table=v['lut'],
                                       scalar_mode=Mapper.ScalarMode().VTK_SCALAR_MODE_USE_CELL_DATA)

        src_actor = vtkActor(mapper=src_mapper)
        v['bcf'] >> src_mapper

        # Create contour edges
        edge_mapper = vtkPolyDataMapper(
            resolve_coincident_topology=Mapper.ResolveCoincidentTopology.VTK_RESOLVE_POLYGON_OFFSET)

        edge_actor = vtkActor(mapper=edge_mapper)
        edge_actor.property.color = colors.GetColor3d('Black')
        v['bcf'].GetContourEdgesOutput() >> edge_mapper

        glyph_mapper = vtkPolyDataMapper(scalar_range=v['scalar_range_elevation'],
                                         lookup_table=v['lut1'],
                                         scalar_mode=Mapper.ScalarMode.VTK_SCALAR_MODE_USE_POINT_FIELD_DATA,
                                         scalar_visibility=True,
                                         color_mode=Mapper.ColorMode.VTK_COLOR_MODE_MAP_SCALARS)
        glyph_mapper.SelectColorArray('Elevation')

        glyph_actor = vtkActor(mapper=glyph_mapper)
        v['glyph'] >> glyph_mapper

        # This LUT puts the lowest value at the top of the scalar bar.
        scalar_bar_properties.lut = curvatures[k]['lut']
        # Use this LUT if you want the highest value at the top.
        # scalar_bar_properties.lut = curvatures[k]['lutr']
        scalar_bar_properties.orientation = False
        scalar_bar_properties.title_text = k.replace('_', '\n')
        contour_widgets[k] = make_scalar_bar_widget(scalar_bar_properties, text_property, iren)

        # Now for the elevation, it is the same for both surface actors.
        # This LUT puts the lowest value at the top of the scalar bar.
        # scalar_bar_properties.lut = curvatures[k]['lutr']
        # Use this LUT if you want the highest value at the top.
        scalar_bar_properties.lut = curvatures[k]['lut1']
        scalar_bar_properties.orientation = True
        scalar_bar_properties.title_text = 'Elevation\n'
        scalar_bar_properties.number_of_labels = 13
        if surface_name == 'plane':
            scalar_bar_properties.number_of_labels = 1
        elevation_widgets[k] = make_scalar_bar_widget(scalar_bar_properties, text_property, iren)

        renderer = vtkRenderer(background=colors.GetColor3d('ParaViewBkg'))
        if first:
            text_widget.default_renderer = renderer
            first = False
        renderer.SetViewport(*viewports[k])
        renderer.AddActor(src_actor)
        renderer.AddActor(edge_actor)
        renderer.AddActor(glyph_actor)
        contour_widgets[k].default_renderer = renderer
        elevation_widgets[k].default_renderer = renderer

        renderers.append(renderer)

    for renderer in renderers:
        ren_win.AddRenderer(renderer)

    for k in curvatures.keys():
        if k == 'Gauss_Curvature':
            contour_widgets[k].On()
        else:
            contour_widgets[k].On()
            elevation_widgets[k].On()
    text_widget.On()

    if use_camera_omw:
        cam_orient_manipulator = vtkCameraOrientationWidget(parent_renderer=renderers[0])
        # Enable the widget.
        cam_orient_manipulator.On()
    else:
        rgb = [0.0] * 4
        colors.GetColor("Carrot", rgb)
        rgb = tuple(rgb[:3])
        widget = vtkOrientationMarkerWidget(orientation_marker=vtkAxesActor(),
                                            interactor=iren, default_renderer=renderers[1],
                                            outline_color=rgb, viewport=(0.7, 0.8, 0.9, 1.0), zoom=1.5, enabled=True,
                                            interactive=True)

    camera = None
    for i in range(0, len(renderers)):
        if i == 0:
            camera = renderers[0].active_camera
            camera.Elevation(60)
            # This moves the window center slightly to ensure that
            # the whole surface is not obscured by the scalar bars.
            camera.window_center = (0.0, -0.15)
        else:
            renderers[i].active_camera = camera
        renderers[i].ResetCamera()

    if surface_name == 'plane':
        renderers[0].active_camera.Zoom(0.8)
    ren_win.Render()

    iren.Start()


def adjust_edge_curvatures(source, curvature_name, epsilon=1.0e-08):
    """
    This function adjusts curvatures along the edges of the surface by replacing
     the value with the average value of the curvatures of points in the neighborhood.

    :param source: The vtkCurvatures object.
    :param curvature_name: The name of the curvature, 'Gauss_Curvature' or 'Mean_Curvature'.
    :param epsilon: Absolute curvature values less than this will be set to zero.
    :return:
    """

    def point_neighbourhood(pt_id):
        """
        Extract the topological neighbors for point.

        :param pt_id: The point id.
        :return: The neighbour ids.
        """
        cell_ids = vtkIdList()
        source.GetPointCells(pt_id, cell_ids)
        neighbour = set()
        for cell_idx in range(0, cell_ids.GetNumberOfIds()):
            cell_id = cell_ids.GetId(cell_idx)
            cell_point_ids = vtkIdList()
            source.GetCellPoints(cell_id, cell_point_ids)
            for cell_pt_idx in range(0, cell_point_ids.GetNumberOfIds()):
                neighbour.add(cell_point_ids.GetId(cell_pt_idx))
        return neighbour

    def compute_distance(pt_id_a, pt_id_b):
        """
        Compute the distance between two points given their ids.

        :param pt_id_a: First point.
        :param pt_id_b: Second point.
        :return: The distance.
        """
        pt_a = np.array(source.GetPoint(pt_id_a))
        pt_b = np.array(source.GetPoint(pt_id_b))
        return np.linalg.norm(pt_a - pt_b)

    # Get the active scalars
    source.point_data.SetActiveScalars(curvature_name)
    np_source = dsa.WrapDataObject(source)
    curvatures = np_source.PointData[curvature_name]

    #  Get the boundary point IDs.
    array_name = 'ids'
    id_filter = vtkGenerateIds(point_ids=True, cell_ids=False,
                               point_ids_array_name=array_name,
                               cell_ids_array_name=array_name)

    edges = vtkFeatureEdges(boundary_edges=True, manifold_edges=False,
                            non_manifold_edges=False, feature_edges=False)

    (source >> id_filter >> edges).update()

    edge_array = edges.output.GetPointData().GetArray(array_name)
    boundary_ids = []
    for i in range(edges.output.GetNumberOfPoints()):
        boundary_ids.append(edge_array.GetValue(i))
    # Remove duplicate Ids.
    p_ids_set = set(boundary_ids)

    # Iterate over the edge points and compute the curvature as the weighted
    # average of the neighbours.
    count_invalid = 0
    for p_id in boundary_ids:
        p_ids_neighbors = point_neighbourhood(p_id)
        # Keep only interior points.
        p_ids_neighbors -= p_ids_set
        # Compute distances and extract curvature values.
        curvs = [curvatures[p_id_n] for p_id_n in p_ids_neighbors]
        dists = [compute_distance(p_id_n, p_id) for p_id_n in p_ids_neighbors]
        curvs = np.array(curvs)
        dists = np.array(dists)
        curvs = curvs[dists > 0]
        dists = dists[dists > 0]
        if len(curvs) > 0:
            weights = 1 / np.array(dists)
            weights /= weights.sum()
            new_curv = np.dot(curvs, weights)
        else:
            # Corner case.
            count_invalid += 1
            # Assuming the curvature of the point is planar.
            new_curv = 0.0
        # Set the new curvature value.
        curvatures[p_id] = new_curv

    #  Set small values to zero.
    if epsilon != 0.0:
        curvatures = np.where(abs(curvatures) < epsilon, 0, curvatures)
        curv = numpy_support.numpy_to_vtk(num_array=curvatures.ravel(),
                                          deep=True,
                                          array_type=VTK_DOUBLE)
        curv.name = curvature_name
        source.point_data.RemoveArray(curvature_name)
        source.point_data.AddArray(curv)
        source.point_data.active_scalars = curvature_name


def constrain_curvatures(source, curvature_name, lower_bound=0.0, upper_bound=0.0):
    """
    This function constrains curvatures to the range [lower_bound ... upper_bound].

    Remember to update the vtkCurvatures object before calling this.

    :param source: A vtkPolyData object corresponding to the vtkCurvatures object.
    :param curvature_name: The name of the curvature, 'Gauss_Curvature' or 'Mean_Curvature'.
    :param lower_bound: The lower bound.
    :param upper_bound: The upper bound.
    :return:
    """

    bounds = list()
    if lower_bound < upper_bound:
        bounds.append(lower_bound)
        bounds.append(upper_bound)
    else:
        bounds.append(upper_bound)
        bounds.append(lower_bound)

    # Get the active scalars
    source.point_data.SetActiveScalars(curvature_name)
    np_source = dsa.WrapDataObject(source)
    curvatures = np_source.PointData[curvature_name]

    # Set upper and lower bounds.
    curvatures = np.where(curvatures < bounds[0], bounds[0], curvatures)
    curvatures = np.where(curvatures > bounds[1], bounds[1], curvatures)
    curv = numpy_support.numpy_to_vtk(num_array=curvatures.ravel(),
                                      deep=True,
                                      array_type=VTK_DOUBLE)
    curv.name = curvature_name
    source.point_data.RemoveArray(curvature_name)
    source.point_data.AddArray(curv)
    source.point_data.active_scalars = curvature_name


def get_source(source, available_surfaces):
    """

    :param source: The name of the source.
    :param available_surfaces: The surfaces
    :return:
    """
    surface = source.lower()
    if surface not in available_surfaces:
        return None
    elif surface == 'hills':
        return get_hills()
    elif surface == 'parametric torus':
        return get_parametric_torus()
    elif surface == 'plane':
        return get_plane()
    elif surface == 'random hills':
        return get_parametric_hills()
    elif surface == 'sphere':
        return get_sphere()
    elif surface == 'torus':
        return get_torus()
    return None


def get_hills():
    """
    Create four hills on a plane.
    This will have regions of negative, zero and positive Gaussian curvatures.

    :return:
    """

    x_res = 50
    y_res = 50
    x_min = -5.0
    x_max = 5.0
    dx = (x_max - x_min) / (x_res - 1)
    y_min = -5.0
    y_max = 5.0
    dy = (y_max - y_min) / (x_res - 1)

    # Make a grid.
    points = vtkPoints()
    for i in range(0, x_res):
        x = x_min + i * dx
        for j in range(0, y_res):
            y = y_min + j * dy
            points.InsertNextPoint(x, y, 0)

    # Add the grid points to a polydata object.
    plane = vtkPolyData(points=points)

    # Triangulate the grid.
    delaunay = vtkDelaunay2D()
    polydata = (plane >> delaunay).update().output

    elevation = vtkDoubleArray(number_of_tuples=points.number_of_points)

    #  We define the parameters for the hills here.
    # [[0: x0, 1: y0, 2: x variance, 3: y variance, 4: amplitude]...]
    hd = [[-2.5, -2.5, 2.5, 6.5, 3.5], [2.5, 2.5, 2.5, 2.5, 2],
          [5.0, -2.5, 1.5, 1.5, 2.5], [-5.0, 5, 2.5, 3.0, 3]]
    xx = [0.0] * 2
    for i in range(0, points.number_of_points):
        x = list(polydata.GetPoint(i))
        for j in range(0, len(hd)):
            xx[0] = (x[0] - hd[j][0] / hd[j][2]) ** 2.0
            xx[1] = (x[1] - hd[j][1] / hd[j][3]) ** 2.0
            x[2] += hd[j][4] * math.exp(-(xx[0] + xx[1]) / 2.0)
            polydata.points.SetPoint(i, x)
            elevation.SetValue(i, x[2])

    textures = vtkFloatArray(name='Textures', number_of_components=2, number_of_tuples=2 * polydata.number_of_points)

    for i in range(0, x_res):
        tc = [i / (x_res - 1.0), 0.0]
        for j in range(0, y_res):
            # tc[1] = 1.0 - j / (y_res - 1.0)
            tc[1] = j / (y_res - 1.0)
            textures.SetTuple(i * y_res + j, tc)

    polydata.GetPointData().SetScalars(elevation)
    polydata.GetPointData().scalars.name = 'Elevation'
    polydata.GetPointData().SetTCoords(textures)

    normals = vtkPolyDataNormals(feature_angle=30, splitting=False)

    transform = vtkTransform()
    # transform.Translate(0.0, 5.0, 15.0)
    transform.RotateX(-90.0)
    transform_filter = vtkTransformPolyDataFilter(transform=transform)

    return polydata >> normals >> transform_filter


def get_parametric_hills():
    fn = vtkParametricRandomHills(random_seed=1, number_of_hills=30)
    fn.AllowRandomGenerationOn()

    source = vtkParametricFunctionSource(parametric_function=fn, u_resolution=51, v_resolution=51,
                                         scalar_mode=vtkParametricFunctionSource.SCALAR_Z)
    source.SetScalarModeToZ()
    src = source.update().output

    # Rename the scalars to 'Elevation' since we are using the Z-scalars as elevations.
    src.point_data.scalars.SetName('Elevation')

    transform = vtkTransform()
    transform.Translate(0.0, 5.0, 15.0)
    transform.RotateX(-90.0)
    transform_filter = vtkTransformPolyDataFilter(transform=transform)

    return src >> transform_filter


def get_parametric_torus():
    fn = vtkParametricTorus(ring_radius=5, cross_section_radius=2)

    source = vtkParametricFunctionSource(parametric_function=fn, u_resolution=51, v_resolution=51,
                                         scalar_mode=vtkParametricFunctionSource.SCALAR_Z)
    src = source.update().output

    # Rename the scalars to 'Elevation' since we are using the Z-scalars as elevations.
    src.point_data.scalars.SetName('Elevation')

    transform = vtkTransform()
    transform.Translate(0.0, 0.0, 0.0)
    transform.RotateX(-90.0)
    transform_filter = vtkTransformPolyDataFilter(transform=transform)

    return src >> transform_filter


def get_plane():
    source = vtkPlaneSource(origin=(-10.0, -10.0, 0.0), point1=(10.0, -10.0, 0.0), point2=(-10.0, 10.0, 0.0),
                            x_resolution=5, y_resolution=5)
    src = source.update().output

    transform = vtkTransform()
    transform.Translate(0.0, 0.0, 0.0)
    transform.RotateX(-90.0)

    transform_filter = vtkTransformPolyDataFilter(transform=transform)

    # We have an m x n array of quadrilaterals arranged as a regular tiling in a
    # plane. So pass it through a triangle filter since the curvature filter only
    # operates on polys.
    tri = vtkTriangleFilter()

    # Pass it though a CleanPolyDataFilter and merge any points which
    # are coincident, or very close
    cleaner = vtkCleanPolyData(tolerance=0.005)

    elev_filter = vtkElevationFilter(low_point=(0, 0, 0), high_point=(0, 0, 1), scalar_range=(0, 0))

    return src >> transform_filter >> tri >> cleaner >> elev_filter


def get_sphere():
    source = vtkSphereSource(center=(0.0, 0.0, 0.0), radius=10.0, theta_resolution=32, phi_resolution=32)
    src = source.update().output

    elev_filter = vtkElevationFilter(low_point=(0, src.bounds[2], 0), high_point=(0, src.bounds[3], 0),
                                     scalar_range=(src.bounds[2], src.bounds[3]))

    return src >> elev_filter


def get_torus():
    source = vtkSuperquadricSource(center=(0.0, 0.0, 0.0), scale=(1.0, 1.0, 1.0), phi_resolution=64,
                                   theta_resolution=64, theta_roundness=1, thickness=0.5, size=10, toroidal=True)
    src = source.update().output

    # The quadric is made of strips, so pass it through a triangle filter as
    # the curvature filter only operates on polys
    tri = vtkTriangleFilter()

    # The quadric has nasty discontinuities from the way the edges are generated
    # so let's pass it though a CleanPolyDataFilter and merge any points which
    # are coincident, or very close
    cleaner = vtkCleanPolyData(tolerance=0.005)

    elev_filter = vtkElevationFilter(low_point=(0, src.bounds[2], 0), high_point=(0, src.bounds[3], 0),
                                     scalar_range=(src.bounds[2], src.bounds[3]))

    return src >> tri >> cleaner >> elev_filter


def get_categorical_lut():
    """
    Make a lookup table using vtkColorSeries.
    :return: An indexed (categorical) lookup table.
    """
    color_series = vtkColorSeries(color_scheme=vtkColorSeries.BREWER_QUALITATIVE_SET3)
    # Make the lookup table.
    lut = vtkLookupTable()
    color_series.BuildLookupTable(lut, color_series.CATEGORICAL)
    lut.nan_color = (0, 1, 0, 1)
    return lut


def get_ordinal_lut():
    """
    Make a lookup table using vtkColorSeries.
    :return: An ordinal (not indexed) lookup table.
    """
    color_series = vtkColorSeries(color_scheme=vtkColorSeries.BREWER_DIVERGING_BROWN_BLUE_GREEN_11)
    # Make the lookup table.
    lut = vtkLookupTable()
    color_series.BuildLookupTable(lut, color_series.ORDINAL)
    lut.nan_color = (0, 1, 0, 1)
    return lut


def get_diverging_lut():
    """
    See: [Diverging Color Maps for Scientific Visualization](https://www.kennethmoreland.com/color-maps/)
                       start point         midPoint            end point
     cool to warm:     0.230, 0.299, 0.754 0.865, 0.865, 0.865 0.706, 0.016, 0.150
     purple to orange: 0.436, 0.308, 0.631 0.865, 0.865, 0.865 0.759, 0.334, 0.046
     green to purple:  0.085, 0.532, 0.201 0.865, 0.865, 0.865 0.436, 0.308, 0.631
     blue to brown:    0.217, 0.525, 0.910 0.865, 0.865, 0.865 0.677, 0.492, 0.093
     green to red:     0.085, 0.532, 0.201 0.865, 0.865, 0.865 0.758, 0.214, 0.233

    :return: The lookup table.
    """
    ctf = vtkColorTransferFunction(color_space=ColorTransferFunction.ColorSpace.VTK_CTF_DIVERGING)
    # Cool to warm.
    ctf.AddRGBPoint(0.0, 0.085, 0.532, 0.201)
    ctf.AddRGBPoint(0.5, 0.865, 0.865, 0.865)
    ctf.AddRGBPoint(1.0, 0.758, 0.214, 0.233)

    table_size = 256
    lut = vtkLookupTable()
    lut.SetNumberOfTableValues(table_size)
    lut.Build()

    for i in range(0, table_size):
        rgba = list(ctf.GetColor(float(i) / table_size))
        rgba.append(1)
        lut.SetTableValue(i, rgba)

    return lut


def reverse_lut(lut):
    """
    Create a lookup table with the colors reversed.
    :param: lut - An indexed lookup table.
    :return: The reversed indexed lookup table.
    """
    lutr = vtkLookupTable()
    lutr.DeepCopy(lut)
    t = lut.GetNumberOfTableValues() - 1
    rev_range = reversed(list(range(t + 1)))
    for i in rev_range:
        rgba = [0.0] * 3
        v = float(i)
        lut.GetColor(v, rgba)
        rgba.append(lut.GetOpacity(v))
        lutr.SetTableValue(t - i, rgba)
    t = lut.number_of_annotated_values - 1
    rev_range = reversed(list(range(t + 1)))
    for i in rev_range:
        lutr.annotation = (t - i, lut.GetAnnotation(i))
    return lutr


def get_glyphs(surface, arrow_scale=None, scale_factor=None, reverse_normals=False):
    """
    Glyph the surface.

    :param surface: The surface to glyph.
    :param arrow_scale: Scaling for the arrows, default is [1, 1, 1].
    :param scale_factor: The scaling factor for the arrow, default is 1.0.
    :param reverse_normals: If True the normals on the surface are reversed.
    :return: The glyph filter.
    """
    name = surface.name
    source = surface.source

    if arrow_scale is None:
        arrow_scale = [1, 1, 1]
    # The length of the arrow glyph.
    if scale_factor is None:
        scale_factor = 1.0

    # Choose a random subset of points.
    if name == 'plane':
        mask_pts = vtkMaskPoints(on_ratio=1, random_mode=True)
    else:
        mask_pts = vtkMaskPoints(on_ratio=5, random_mode=True)

    # Sometimes the contouring algorithm can create a volume whose gradient
    # vector and ordering of the polygon (using the right hand rule) are
    # inconsistent. vtkReverseSense cures this problem.
    if reverse_normals:
        reverse = vtkReverseSense(reverse_cells=True, reverse_normals=True)
        source >> reverse >> mask_pts
    else:
        source >> mask_pts

    # Source for the glyph filter.
    arrow = vtkArrowSource(shaft_resolution=16, shaft_radius=0.03, tip_resolution=16, tip_length=0.3, tip_radius=0.1)
    # Scale the arrow.
    transform = vtkTransform()
    transform.Scale(arrow_scale)
    transform_filter = vtkTransformPolyDataFilter(transform=transform)

    p = (arrow >> transform_filter).update().output

    glyph = vtkGlyph3D(source_data=p, scale_factor=scale_factor,
                       vector_mode=Glyph3D.VectorMode.VTK_USE_NORMAL,
                       color_mode=Glyph3D.ColorMode.VTK_COLOR_BY_VECTOR,
                       scale_mode=Glyph3D.ScaleMode.VTK_SCALE_BY_VECTOR
                       )
    glyph.OrientOn()

    return mask_pts >> glyph


def get_bands(d_r, number_of_bands, precision=2, nearest_integer=False):
    """
    Divide a range into bands.

    :param: d_r - [min, max] the range that is to be covered by the bands.
    :param: number_of_bands - The number of bands, a positive integer.
    :param: precision - The decimal precision of the bounds.
    :param: nearest_integer - If True then [floor(min), ceil(max)] is used.
    :return: A dictionary consisting of the band number and [min, midpoint, max] for each band.
    """
    prec = abs(precision)
    if prec > 14:
        prec = 14

    bands = dict()
    if (d_r[1] < d_r[0]) or (number_of_bands <= 0):
        return bands
    x = list(d_r)
    if nearest_integer:
        x[0] = math.floor(x[0])
        x[1] = math.ceil(x[1])
    dx = (x[1] - x[0]) / float(number_of_bands)
    b = [x[0], x[0] + dx / 2.0, x[0] + dx]
    i = 0
    while i < number_of_bands:
        b = list(map(lambda ele_b: round(ele_b, prec), b))
        if i == 0:
            b[0] = x[0]
        bands[i] = b
        b = [b[0] + dx, b[1] + dx, b[2] + dx]
        i += 1
    return bands


def get_custom_bands(d_r, number_of_bands, my_bands):
    """
    Divide a range into custom bands.

    You need to specify each band as a list [r1, r2] where r1 < r2 and
    append these to a list.
    The list should ultimately look
    like this: [[r1, r2], [r2, r3], [r3, r4]...]

    :param: d_r - [min, max] the range that is to be covered by the bands.
    :param: number_of_bands - the number of bands, a positive integer.
    :return: A dictionary consisting of band number and [min, midpoint, max] for each band.
    """
    bands = dict()
    if (d_r[1] < d_r[0]) or (number_of_bands <= 0):
        return bands
    x = my_bands
    # Determine the index of the range minimum and range maximum.
    idx_min = 0
    for idx in range(0, len(my_bands)):
        if my_bands[idx][1] > d_r[0] >= my_bands[idx][0]:
            idx_min = idx
            break

    idx_max = len(my_bands) - 1
    for idx in range(len(my_bands) - 1, -1, -1):
        if my_bands[idx][1] > d_r[1] >= my_bands[idx][0]:
            idx_max = idx
            break

    # Set the minimum to match the range minimum.
    x[idx_min][0] = d_r[0]
    x[idx_max][1] = d_r[1]
    x = x[idx_min: idx_max + 1]
    for idx, e in enumerate(x):
        bands[idx] = [e[0], e[0] + (e[1] - e[0]) / 2, e[1]]
    return bands


def get_frequencies(bands, src):
    """
    Count the number of scalars in each band.
    The scalars used are the active scalars in the polydata.

    :param: bands - The bands.
    :param: src - The vtkPolyData source.
    :return: The frequencies of the scalars in each band.
    """
    freq = dict()
    for i in range(len(bands)):
        freq[i] = 0
    tuples = src.GetPointData().GetScalars().GetNumberOfTuples()
    for i in range(tuples):
        x = src.GetPointData().GetScalars().GetTuple1(i)
        for j in range(len(bands)):
            if x <= bands[j][2]:
                freq[j] += 1
                break
    return freq


def adjust_ranges(bands, freq):
    """
    The bands and frequencies are adjusted so that the first and last
     frequencies in the range are non-zero.

    :param bands: The bands dictionary.
    :param freq: The frequency dictionary.
    :return: Adjusted bands and frequencies.
    """
    # Get the indices of the first and last non-zero elements.
    first = 0
    for k, v in freq.items():
        if v != 0:
            first = k
            break
    rev_keys = list(freq.keys())[::-1]
    last = rev_keys[0]
    for idx in list(freq.keys())[::-1]:
        if freq[idx] != 0:
            last = idx
            break
    # Now adjust the ranges.
    min_key = min(freq.keys())
    max_key = max(freq.keys())
    for idx in range(min_key, first):
        freq.pop(idx)
        bands.pop(idx)
    for idx in range(last + 1, max_key + 1):
        freq.popitem()
        bands.popitem()
    old_keys = freq.keys()
    adj_freq = dict()
    adj_bands = dict()

    for idx, k in enumerate(old_keys):
        adj_freq[idx] = freq[k]
        adj_bands[idx] = bands[k]

    return adj_bands, adj_freq


def print_bands_frequencies(curvature, bands, freq, precision=2):
    prec = abs(precision)
    if prec > 14:
        prec = 14

    if len(bands) != len(freq):
        print('Bands and Frequencies must be the same size.')
        return
    s = f'Bands & Frequencies:\n{" ".join(curvature.lower().replace("_", " ").split()).title()}\n'
    total = 0
    width = prec + 6
    for k, v in bands.items():
        total += freq[k]
        for j, q in enumerate(v):
            if j == 0:
                s += f'{k:4d} ['
            if j == len(v) - 1:
                s += f'{q:{width}.{prec}f}]: {freq[k]:8d}\n'
            else:
                s += f'{q:{width}.{prec}f}, '
    width = 3 * width + 13
    s += f'{"Total":{width}s}{total:8d}\n'
    print(s)


def generate_gaussian_curvatures(surface, needs_adjusting, frequency_table=False):
    """
    Generate the filters for the surface.

    :param surface: The surface.
    :param needs_adjusting: Surfaces whose curvatures need to be adjusted along the edges of the surface or constrained.
    :param frequency_table: True if a frequency table is to be displayed.
    :return: Return the filters, scalar ranges of curvatures and elevation along with the lookup tables.
    """
    name = surface.name
    source = surface.source
    curvature = 'Gauss_Curvature'

    curvatures = vtkCurvatures(curvature_type=Curvatures.CurvatureType().VTK_CURVATURE_GAUSS)
    p = (source >> curvatures).update().output

    if name in needs_adjusting:
        adjust_edge_curvatures(p, curvature)
    if name == 'plane':
        constrain_curvatures(p, curvature, 0.0, 0.0)
    if name == 'sphere':
        # Gaussian curvature is 1/r^2
        radius = 10
        gauss_curvature = 1.0 / radius ** 2
        constrain_curvatures(p, curvature, gauss_curvature, gauss_curvature)

    p.GetPointData().SetActiveScalars(curvature)
    scalar_range_curvatures = curvatures.update().output.GetPointData().GetScalars(curvature).range
    scalar_range_elevation = p.GetPointData().GetScalars('Elevation').range

    lut = get_categorical_lut()
    lut.SetTableRange(scalar_range_curvatures)
    number_of_bands = lut.GetNumberOfTableValues()
    bands = get_bands(scalar_range_curvatures, number_of_bands=number_of_bands, precision=10, nearest_integer=False)

    # lut1 = get_diverging_lut()
    lut1 = get_ordinal_lut()
    lut1.SetTableRange(scalar_range_elevation)

    if name == 'random hills':
        # These are my custom bands.
        # Generated by first running:
        # bands = get_bands(scalar_range_curvatures, number_of_bands=number_of_bands,
        #                   precision=2, nearest_integer=False)
        # then:
        #  freq = frequencies(bands, curvatures_output)
        #  print_bands_frequencies(curvature, bands, freq)
        # Finally using the output to create this table:
        # my_bands = [
        #     [-0.630, -0.190], [-0.190, -0.043], [-0.043, -0.0136],
        #     [-0.0136, 0.0158], [0.0158, 0.0452], [0.0452, 0.0746],
        #     [0.0746, 0.104], [0.104, 0.251], [0.251, 1.131]]
        #  This demonstrates that the gaussian curvature of the surface
        #   is mostly planar with some hyperbolic regions (saddle points)
        #   and some spherical regions.
        my_bands = [
            [-0.630, -0.190], [-0.190, -0.043], [-0.043, 0.0452], [0.0452, 0.0746],
            [0.0746, 0.104], [0.104, 0.251], [0.251, 1.131]]
        # Comment this out if you want to see how allocating
        # equally spaced bands works.
        bands = get_custom_bands(scalar_range_curvatures, number_of_bands=number_of_bands, my_bands=my_bands)
        # Adjust the number of table values
        lut.SetNumberOfTableValues(len(bands))
    if name == 'hills':
        my_bands = [
            [-2.104, -0.15], [-0.15, -0.1], [-0.1, -0.05],
            [-0.05, -0.02], [-0.02, -0.005], [-0.005, -0.0005],
            [-0.0005, 0.0005], [0.0005, 0.09], [0.09, 4.972]]
        # Comment this out if you want to see how allocating
        # equally spaced bands works.
        bands = get_custom_bands(scalar_range_curvatures, number_of_bands=number_of_bands, my_bands=my_bands)
        # Adjust the number of table values
        lut.SetNumberOfTableValues(len(bands))

    freq = get_frequencies(bands, p)
    bands, freq = adjust_ranges(bands, freq)
    if frequency_table:
        # Let's do a frequency table with the number of scalars in each band.
        print_bands_frequencies(curvature, bands, freq)

    lut.SetTableRange(scalar_range_curvatures)
    lut.SetNumberOfTableValues(len(bands))

    # We will use the midpoint of the band as the label.
    labels = []
    for k in bands:
        labels.append(f'{bands[k][1]:4.2f}')

    # Annotate
    values = vtkVariantArray()
    for i in range(len(labels)):
        values.InsertNextValue(vtkVariant(labels[i]))
    for i in range(values.GetNumberOfTuples()):
        lut.SetAnnotation(i, values.GetValue(i).ToString())

    # Create a lookup table with the colors reversed.
    lutr = reverse_lut(lut)

    # Create the contour bands.
    # We will use an indexed lookup table.
    bcf = vtkBandedPolyDataContourFilter(input_data=p,
                                         scalar_mode=BandedPolyDataContourFilter.ScalarMode.VTK_SCALAR_MODE_INDEX,
                                         generate_contour_edges=True)

    # Use either the minimum or maximum value for each band.
    for k in bands:
        bcf.SetValue(k, bands[k][2])

    # Generate the glyphs on the original surface.
    arrow_scale = [2, 1, 1]
    scale_factor = 1.0
    if name == 'plane':
        arrow_scale = [5, 2, 2]
    if name == 'hills':
        scale_factor = 0.5
    if name == 'sphere':
        scale_factor = 2.0

    glyph = get_glyphs(surface, arrow_scale=arrow_scale, scale_factor=scale_factor, reverse_normals=False)

    return {'bcf': bcf, 'glyph': glyph, 'scalar_range_curvatures': scalar_range_curvatures,
            'scalar_range_elevation': scalar_range_elevation, 'lut': lut,
            'lut1': lut1, 'lutr': lutr}


def generate_mean_curvatures(surface, needs_adjusting, frequency_table=False):
    """
    Generate the filters for the surface.

    :param surface: The surface.
    :param needs_adjusting: Surfaces whose curvatures need to be adjusted along the edges of the surface or constrained.
    :param frequency_table: True if a frequency table is to be displayed.
    :return: Return the filters, scalar ranges of curvatures and elevation along with the lookup tables.
    """
    name = surface.name
    source = surface.source
    curvature = 'Mean_Curvature'

    curvatures = vtkCurvatures(curvature_type=Curvatures.CurvatureType().VTK_CURVATURE_MEAN)
    p = (source >> curvatures).update().output

    if name in needs_adjusting:
        adjust_edge_curvatures(p, curvature)
    if name == 'plane':
        constrain_curvatures(p, curvature, 0.0, 0.0)
    if name == 'sphere':
        # Mean curvature is 1/r
        radius = 10
        mean_curvature = 1.0 / radius
        constrain_curvatures(p, curvature, mean_curvature, mean_curvature)

    p.GetPointData().SetActiveScalars(curvature)
    scalar_range_curvatures = p.GetPointData().GetScalars(curvature).range
    scalar_range_elevation = p.GetPointData().GetScalars('Elevation').range

    lut = get_categorical_lut()
    lut.SetTableRange(scalar_range_curvatures)
    number_of_bands = lut.GetNumberOfTableValues()
    bands = get_bands(scalar_range_curvatures, number_of_bands=number_of_bands, precision=10, nearest_integer=False)

    # lut1 = get_diverging_lut()
    lut1 = get_ordinal_lut()
    lut1.SetTableRange(scalar_range_elevation)

    # If any bands need adjusting, we would do it here.

    freq = get_frequencies(bands, p)
    bands, freq = adjust_ranges(bands, freq)
    if frequency_table:
        # Let's do a frequency table with the number of scalars in each band.
        print_bands_frequencies(curvature, bands, freq)

    lut.SetTableRange(scalar_range_curvatures)
    lut.SetNumberOfTableValues(len(bands))

    # We will use the midpoint of the band as the label.
    labels = []
    for k in bands:
        labels.append(f'{bands[k][1]:4.2f}')

    # Annotate
    values = vtkVariantArray()
    for i in range(len(labels)):
        values.InsertNextValue(vtkVariant(labels[i]))
    for i in range(values.GetNumberOfTuples()):
        lut.SetAnnotation(i, values.GetValue(i).ToString())

    # Create a lookup table with the colors reversed.
    lutr = reverse_lut(lut)

    # Create the contour bands.
    # We will use an indexed lookup table.
    bcf = vtkBandedPolyDataContourFilter(input_data=p,
                                         scalar_mode=BandedPolyDataContourFilter.ScalarMode.VTK_SCALAR_MODE_INDEX,
                                         generate_contour_edges=True)

    # Use either the minimum or maximum value for each band.
    for k in bands:
        bcf.SetValue(k, bands[k][2])

    # Generate the glyphs on the original surface.
    arrow_scale = (2, 1, 1)
    scale_factor = 1.0
    if name == 'plane':
        arrow_scale = (5, 2, 2)
    if name == 'hills':
        scale_factor = 0.5
    if name == 'sphere':
        scale_factor = 2.0

    glyph = get_glyphs(surface, arrow_scale=arrow_scale, scale_factor=scale_factor, reverse_normals=False)

    return {'bcf': bcf, 'glyph': glyph, 'scalar_range_curvatures': scalar_range_curvatures,
            'scalar_range_elevation': scalar_range_elevation, 'lut': lut,
            'lut1': lut1, 'lutr': lutr}


class ScalarBarProperties:
    """
    The properties needed for scalar bars.
    """
    named_colors = vtkNamedColors()

    lut = None
    # These are in pixels
    maximum_dimensions = {'width': 100, 'height': 260}
    title_text = '',
    number_of_labels: int = 5
    # Orientation vertical=True, horizontal=False
    orientation: bool = True
    # Horizontal and vertical positioning
    position_v = {'point1': (0.85, 0.1), 'point2': (0.1, 0.7)}
    position_h = {'point1': (0.10, 0.1), 'point2': (0.7, 0.1)}


def make_scalar_bar_widget(scalar_bar_properties, text_property, interactor):
    """
    Make a scalar bar widget.

    :param scalar_bar_properties: The lookup table, title name, maximum dimensions in pixels and position.
    :param text_property: The properties for the title.
    :param interactor: The vtkInteractor.
    :return: The scalar bar widget.
    """
    sb_actor = vtkScalarBarActor(lookup_table=scalar_bar_properties.lut, title=scalar_bar_properties.title_text,
                                 unconstrained_font_size=True, number_of_labels=scalar_bar_properties.number_of_labels,
                                 title_text_property=text_property
                                 )

    sb_rep = vtkScalarBarRepresentation(enforce_normalized_viewport_bounds=True,
                                        orientation=scalar_bar_properties.orientation)

    # Set the position
    sb_rep.position_coordinate.SetCoordinateSystemToNormalizedViewport()
    sb_rep.position2_coordinate.SetCoordinateSystemToNormalizedViewport()
    if scalar_bar_properties.orientation:
        sb_rep.position_coordinate.value = scalar_bar_properties.position_v['point1']
        sb_rep.position2_coordinate.value = scalar_bar_properties.position_v['point2']
    else:
        sb_rep.position_coordinate.value = scalar_bar_properties.position_h['point1']
        sb_rep.position2_coordinate.value = scalar_bar_properties.position_h['point2']

    widget = vtkScalarBarWidget(representation=sb_rep, scalar_bar_actor=sb_actor, interactor=interactor, enabled=True)

    return widget


def get_text_positions(names, justification=0, vertical_justification=0, width=0.96, height=0.1):
    """
    Get viewport positioning information for a list of names.

    :param names: The list of names.
    :param justification: Horizontal justification of the text, default is left.
    :param vertical_justification: Vertical justification of the text, default is bottom.
    :param width: Width of the bounding_box of the text in screen coordinates.
    :param height: Height of the bounding_box of the text in screen coordinates.
    :return: A list of positioning information.
    """
    # The gap between the left or right edge of the screen and the text.
    dx = 0.02
    width = abs(width)
    if width > 0.96:
        width = 0.96

    y0 = 0.01
    height = abs(height)
    if height > 0.9:
        height = 0.9
    dy = height
    if vertical_justification == TextProperty.VerticalJustification.VTK_TEXT_TOP:
        y0 = 1.0 - (dy + y0)
        dy = height
    if vertical_justification == TextProperty.VerticalJustification.VTK_TEXT_CENTERED:
        y0 = 0.5 - (dy / 2.0 + y0)
        dy = height

    name_len_min = 0
    name_len_max = 0
    first = True
    for k in names:
        sz = len(k)
        if first:
            name_len_min = name_len_max = sz
            first = False
        else:
            name_len_min = min(name_len_min, sz)
            name_len_max = max(name_len_max, sz)
    text_positions = dict()
    for k in names:
        sz = len(k)
        delta_sz = width * sz / name_len_max
        if delta_sz > width:
            delta_sz = width

        if justification == TextProperty.Justification.VTK_TEXT_CENTERED:
            x0 = 0.5 - delta_sz / 2.0
        elif justification == TextProperty.Justification.VTK_TEXT_RIGHT:
            x0 = 1.0 - dx - delta_sz
        else:
            # Default is left justification.
            x0 = dx

        # For debugging!
        # print(
        #     f'{k:16s}: (x0, y0) = ({x0:3.2f}, {y0:3.2f}), (x1, y1) = ({x0 + delta_sz:3.2f}, {y0 + dy:3.2f})'
        #     f', width={delta_sz:3.2f}, height={dy:3.2f}')
        text_positions[k] = {'p': [x0, y0, 0], 'p2': [delta_sz, dy, 0]}

    return text_positions


@dataclass(frozen=True)
class BandedPolyDataContourFilter:
    @dataclass(frozen=True)
    class ScalarMode:
        VTK_SCALAR_MODE_INDEX: int = 0
        VTK_SCALAR_MODE_VALUE: int = 1


@dataclass(frozen=True)
class ColorTransferFunction:
    @dataclass(frozen=True)
    class ColorSpace:
        VTK_CTF_RGB: int = 0
        VTK_CTF_HSV: int = 1
        VTK_CTF_LAB: int = 2
        VTK_CTF_DIVERGING: int = 3
        VTK_CTF_LAB_CIEDE2000: int = 4
        VTK_CTF_STEP: int = 5

    @dataclass(frozen=True)
    class Scale:
        VTK_CTF_LINEAR: int = 0
        VTK_CTF_LOG10: int = 1


@dataclass(frozen=True)
class Curvatures:
    @dataclass(frozen=True)
    class CurvatureType:
        VTK_CURVATURE_GAUSS: int = 0
        VTK_CURVATURE_MEAN: int = 1
        VTK_CURVATURE_MAXIMUM: int = 2
        VTK_CURVATURE_MINIMUM: int = 3


@dataclass(frozen=True)
class Glyph3D:
    @dataclass(frozen=True)
    class ColorMode:
        VTK_COLOR_BY_SCALE: int = 0
        VTK_COLOR_BY_SCALAR: int = 1
        VTK_COLOR_BY_VECTOR: int = 2

    @dataclass(frozen=True)
    class IndexMode:
        VTK_INDEXING_OFF: int = 0
        VTK_INDEXING_BY_SCALAR: int = 1
        VTK_INDEXING_BY_VECTOR: int = 2

    @dataclass(frozen=True)
    class ScaleMode:
        VTK_SCALE_BY_SCALAR: int = 0
        VTK_SCALE_BY_VECTOR: int = 1
        VTK_SCALE_BY_VECTORCOMPONENTS: int = 2
        VTK_DATA_SCALING_OFF: int = 3

    @dataclass(frozen=True)
    class VectorMode:
        VTK_USE_VECTOR: int = 0
        VTK_USE_NORMAL: int = 1
        VTK_VECTOR_ROTATION_OFF: int = 2
        VTK_FOLLOW_CAMERA_DIRECTION: int = 3


@dataclass(frozen=True)
class Mapper:
    @dataclass(frozen=True)
    class ColorMode:
        VTK_COLOR_MODE_DEFAULT: int = 0
        VTK_COLOR_MODE_MAP_SCALARS: int = 1
        VTK_COLOR_MODE_DIRECT_SCALARS: int = 2

    @dataclass(frozen=True)
    class ResolveCoincidentTopology:
        VTK_RESOLVE_OFF: int = 0
        VTK_RESOLVE_POLYGON_OFFSET: int = 1
        VTK_RESOLVE_SHIFT_ZBUFFER: int = 2

    @dataclass(frozen=True)
    class ScalarMode:
        VTK_SCALAR_MODE_DEFAULT: int = 0
        VTK_SCALAR_MODE_USE_POINT_DATA: int = 1
        VTK_SCALAR_MODE_USE_CELL_DATA: int = 2
        VTK_SCALAR_MODE_USE_POINT_FIELD_DATA: int = 3
        VTK_SCALAR_MODE_USE_CELL_FIELD_DATA: int = 4
        VTK_SCALAR_MODE_USE_FIELD_DATA: int = 5


@dataclass(frozen=True)
class TextProperty:
    @dataclass(frozen=True)
    class Justification:
        VTK_TEXT_LEFT: int = 0
        VTK_TEXT_CENTERED: int = 1
        VTK_TEXT_RIGHT: int = 2

    @dataclass(frozen=True)
    class VerticalJustification:
        VTK_TEXT_BOTTOM: int = 0
        VTK_TEXT_CENTERED: int = 1
        VTK_TEXT_TOP: int = 2


if __name__ == '__main__':
    import sys

    main(sys.argv)