Collision#

Perform a collision detection between two meshes.

This example uses the collision filter to detect the faces from one sphere colliding with another sphere.

Note

Due to the nature of the vtk.vtkCollisionDetectionFilter, repeated uses of this method will be slower that using the vtk.vtkCollisionDetectionFilter directly. The first update of the filter creates two instances of vtkOBBTree, which can be subsequently updated by modifying the transform or matrix of the input meshes.

This method assumes no transform and is easier to use for single collision tests, but it is recommended to use a combination of pyvista and vtk for rapidly computing repeated collisions. See the Collision Detection Example

import numpy as np
import pyvista as pv

pv.set_plot_theme("document")

Create the main mesh and the secondary “moving” mesh.

Collision faces will be plotted on this sphere, and to do so we initialize an initial "collisions" mask.

sphere0 = pv.Sphere()
sphere0["collisions"] = np.zeros(sphere0.n_cells, dtype=bool)

# This mesh will be the moving mesh
sphere1 = pv.Sphere(radius=0.6, center=(-1, 0, 0))

Setup the plotter open a movie, and write a frame after moving the sphere.

pl = pv.Plotter()
pl.enable_hidden_line_removal()
pl.add_mesh(sphere0, show_scalar_bar=False, cmap="bwr")
pl.camera_position = "xz"
pl.add_mesh(sphere1, style="wireframe", color="green", line_width=5)

# for this example
pl.open_gif("collision_movie.gif")

# alternatively, to disable movie generation:
# pl.show(auto_close=False, interactive=False)

delta_x = 0.05
for i in range(int(2 / delta_x)):
    sphere1.translate([delta_x, 0, 0])
    col, n_contacts = sphere0.collision(sphere1)

    collision_mask = np.zeros(sphere0.n_cells, dtype=bool)
    if n_contacts:
        collision_mask[col["ContactCells"]] = True
    sphere0["collisions"] = collision_mask
    pl.write_frame()

    # alternatively, disable movie plotting and simply render the image
    # pl.render()

pl.close()
plot collisions

Total running time of the script: (0 minutes 9.034 seconds)

Estimated memory usage: 391 MB

Gallery generated by Sphinx-Gallery