Contouring

Contouring#

Download Python source code | Download Jupyter notebook

Generate iso-lines or -surfaces for the scalars of a surface or volume.

3D meshes can have 2D iso-surfaces of a scalar field extracted and 2D surface meshes can have 1D iso-lines of a scalar field extracted.

import numpy as np
import pyvista as pv
from pyvista import examples

Iso-Lines#

Let’s extract 1D iso-lines of a scalar field from a 2D surface mesh.

mesh = examples.load_random_hills()

contours = mesh.contour()

pl = pv.Plotter()
pl.add_mesh(mesh, opacity=0.85)
pl.add_mesh(contours, color='white', line_width=5)
pl.show()

Static Scene

Interactive Scene

Iso-Surfaces#

Let’s extract 2D iso-surfaces of a scalar field from a 3D mesh.

mesh = examples.download_embryo().resample(0.5, anti_aliasing=True)

contours = mesh.contour(np.linspace(50, 200, 5))

pl = pv.Plotter()
pl.add_mesh(mesh.outline(), color='k')
pl.add_mesh(contours, opacity=0.25, clim=[0, 200])
pl.camera_position = pv.CameraPosition(
    position=(-131.0, 644.5, 163.8),
    focal_point=(125.2, 123.9, 108.8),
    viewup=(0.278, 0.03548, 0.9599),
)
pl.show()

Static Scene

Interactive Scene

Banded Contours#

Create banded contours for surface meshes using contour_banded().

mesh = examples.load_random_hills()

Set number of contours and produce mesh and lines

n_contours = 8
contours, edges = mesh.contour_banded(n_contours)

Also make normal vectors

arrows = mesh.glyph(scale='Normals', orient='Normals', tolerance=0.05)

# Common display arguments
dargs = dict(scalars='Elevation', n_colors=n_contours - 1, cmap='Set3')

pl = pv.Plotter()
pl.add_mesh(edges, line_width=5, render_lines_as_tubes=True, color='k')
pl.add_mesh(contours, **dargs)
pl.add_mesh(arrows, **dargs)
pl.show()

Static Scene

Interactive Scene

Contours From a Label Map#

Create labeled surfaces from 3D label maps (e.f. multi-label image segmentation) using contour_labels().

label_map = pv.examples.load_frog_tissues().resample(0.5, interpolation='nearest')
mesh = label_map.contour_labels()
mesh.plot(cmap='glasbey', cpos='yx', categories=True)