Fast tools for simplex meshes.
Compute all sorts of interesting points, areas, and volumes in triangular and tetrahedral meshes, with a focus on efficiency. Useful in many contexts, e.g., finite-element and finite-volume computations.
meshplex is used in optimesh and pyfvm.
For triangular and tetrahedral meshes, meshplex can compute the following data:
import numpy
import meshplex
# create a simple MeshTri instance
points = numpy.array([[0.0, 0.0, 0.0], [1.0, 0.0, 0.0], [0.0, 1.0, 0.0]])
cells = numpy.array([[0, 1, 2]])
mesh = meshplex.MeshTri(points, cells)
# or read it from a file
# mesh = meshplex.read("pacman.vtk")
# triangle volumes
print(mesh.cell_volumes)
# circumcenters, centroids, incenters
print(mesh.cell_circumcenters)
print(mesh.cell_centroids)
print(mesh.cell_incenters)
# circumradius, inradius, cell quality, angles
print(mesh.cell_circumradius)
print(mesh.cell_inradius)
print(mesh.q_radius_ratio) # d * inradius / circumradius (min 0, max 1)
print(mesh.angles)
# control volumes, centroids
print(mesh.control_volumes)
print(mesh.control_volume_centroids)
# covolume/edge length ratios
print(mesh.ce_ratios)
# flip edges until the mesh is Delaunay
mesh.flip_until_delaunay()
# show the mesh
mesh.show()
For triangular meshes, meshplex also has some mesh manipulation routines:
mesh.flip_until_delaunay() # flips edges until the mesh is Delaunay
mesh.remove_cells([0, 2, ...]) # removes some cells
For a documentation of all classes and functions, see readthedocs.
(For mesh creation, check out this list).
import meshplex
mesh = meshplex.read("pacman-optimized.vtk")
mesh.show(
# show_coedges=True,
# control_volume_centroid_color=None,
# mesh_color="k",
# nondelaunay_edge_color=None,
# boundary_edge_color=None,
# comesh_color=(0.8, 0.8, 0.8),
show_axes=False,
)
import numpy
import meshplex
# Generate tetrahedron
points = (
numpy.array(
[
[1.0, 0.0, -1.0 / numpy.sqrt(8)],
[-0.5, +numpy.sqrt(3.0) / 2.0, -1.0 / numpy.sqrt(8)],
[-0.5, -numpy.sqrt(3.0) / 2.0, -1.0 / numpy.sqrt(8)],
[0.0, 0.0, numpy.sqrt(2.0) - 1.0 / numpy.sqrt(8)],
]
)
/ numpy.sqrt(3.0)
)
cells = [[0, 1, 2, 3]]
# Create mesh object
mesh = meshplex.MeshTetra(points, cells)
# Plot cell 0 with control volume boundaries
mesh.show_cell(
0,
# barycenter_rgba=(1, 0, 0, 1.0),
# circumcenter_rgba=(0.1, 0.1, 0.1, 1.0),
# circumsphere_rgba=(0, 1, 0, 1.0),
# incenter_rgba=(1, 0, 1, 1.0),
# insphere_rgba=(1, 0, 1, 1.0),
# face_circumcenter_rgba=(0, 0, 1, 1.0),
control_volume_boundaries_rgba=(1.0, 0.0, 0.0, 1.0),
line_width=3.0,
)
meshplex is available from the Python Package Index, so simply type
pip install meshplex
to install.
To run the meshplex unit tests, check out this repository and type
pytest
This software is published under the GPLv3 license.