vtk_poly_data#

k3d.factory.vtk_poly_data(poly_data: Any, color: int = 255, color_attribute: Tuple[str, float, float] | None = None, color_map: List[List[float]] | Dict[str, Any] | ndarray | None = None, side: str = 'front', slice_planes: List | ndarray | Tuple = None, wireframe: bool = False, opacity: float = 1.0, volume: List | ndarray | Tuple = None, volume_bounds: List | ndarray | Tuple = None, opacity_function: List[float] = None, color_range: List[float] = None, cell_color_attribute: Tuple[str, float, float] | None = None, flat_shading: bool = True, name: str | None = None, group: str | None = None, custom_data: Dict[str, Any] | None = None, compression_level: int = 0, **kwargs: Any) → Mesh[source]#

Examples#

Basic#

cow.vtp

# VTP model from https://github.com/naucoin/VTKData/blob/master/Data/cow.vtp

import k3d
import numpy as np
import pyvista as pv

data = pv.raed('cow.vtp')

plt_vtk = k3d.vtk_poly_data(data,
                            color=0xc6884b,
                            model_matrix = (1.0, 0.0, 0.0, 0.0,
                                            0.0, 0.0, 1.0, 0.0,
                                            0.0, 1.0, 0.0, 0.0,
                                            0.0, 0.0, 0.0, 1.0))

plot = k3d.plot()
plot += plt_vtk
plot.display()

Colormap#

bunny.vtp

Attention

color_map must be used along with color_attribute in order to work correctly.

# VTP model from https://github.com/pyvista/vtk-data/blob/master/Data/Bunny.vtp

import k3d
import pyvista as pv
from k3d.colormaps import matplotlib_color_maps

data = pv.read('bunny.vtp')

plt_vtk = k3d.vtk_poly_data(data,
                            color_attribute=('Normals', 0, 1),
                            color_map=matplotlib_color_maps.Rainbow,
                            model_matrix = (1.0, 0.0, 0.0, 0.0,
                                            0.0, 0.0, 1.0, 0.0,
                                            0.0, 1.0, 0.0, 0.0,
                                            0.0, 0.0, 0.0, 1.0))

plot = k3d.plot()
plot += plt_vtk
plot.display()