meshio 3.3.1

I/O for various mesh formats

I/O for mesh files.

There are various mesh formats available for representing unstructured meshes. meshio can read and write all of the following and smoothly converts between them:

• Abaqus
• ANSYS msh
• CGNS
• DOLFIN XML
• Exodus
• FLAC3D
• H5M
• Kratos/MDPA
• Medit
• MED/Salome
• Nastran (bulk data)
• Neuroglancer precomputed format
• Gmsh (versions 2 and 4)
• OBJ
• OFF
• PERMAS
• PLY
• STL
• TetGen .node/.ele
• SVG (2D only, output only)
• UGRID
• VTK
• VTU (not raw binary data)
• WKT (TIN)
• XDMF

Install with

pip3 install meshio[all] --user

and simply call

meshio-convert input.msh output.vtu

with any of the supported formats.

In Python, simply do

import meshio

mesh = meshio.read(
    filename,  # string, os.PathLike, or a buffer/open file
    file_format="stl"  # optional if filename is a path; inferred from extension
)
# mesh.points, mesh.cells, ...

# mesh.vtk.read() is also possible

to read a mesh. To write, do

points = numpy.array([
    [0.0, 0.0, 0.0],
    [0.0, 1.0, 0.0],
    [0.0, 0.0, 1.0],
    ])
cells = {
    "triangle": numpy.array([
        [0, 1, 2]
        ])
    }
meshio.write_points_cells(
    "foo.vtk",
    points,
    cells,
    # Optionally provide extra data on points, cells, etc.
    # point_data=point_data,
    # cell_data=cell_data,
    # field_data=field_data
    )

or explicitly create a mesh object for writing

mesh = meshio.Mesh(points, cells)
meshio.write(
    "foo.vtk",  # str, os.PathLike, or buffer/ open file
    mesh,
    # file_format="vtk",  # optional if first argument is a path; inferred from extension
)

# mesh.vtk.write() is also possible

For both input and output, you can optionally specify the exact file_format (in case you would like to enforce ASCII over binary VTK, for example).

Reading and writing can also be handled directly by the Mesh object:

m = meshio.Mesh.read(filename, "vtk")  # same arguments as meshio.read
m.write("foo.vtk")  # same arguments as meshio.write, besides `mesh`

Time series

The XDMF format supports time series with a shared mesh. You can write times series data using meshio with

with meshio.xdmf.TimeSeriesWriter(filename) as writer:
    writer.write_points_cells(points, cells)
    for t in [0.0, 0.1, 0.21]:
        writer.write_data(t, point_data={"phi": data})

and read it with

with meshio.xdmf.TimeSeriesReader(filename) as reader:
    points, cells = reader.read_points_cells()
    for k in range(reader.num_steps):
        t, point_data, cell_data = reader.read_data(k)

Performance comparison

The comparisons here are for a tetrahedral mesh with about 400k points and 2M tetrahedra. The red lines mark the size of the mesh in memory.

File sizes

I/O speed

Maximum memory usage

Installation

meshio is available from the Python Package Index, so simply do

pip3 install meshio --user

to install.

Additional dependencies (netcdf4, h5py and lxml) are required for some of the output formats and can be pulled in by

pip install meshio[all] --user

You can also install meshio from anaconda:

conda install -c conda-forge meshio

Testing

To run the meshio unit tests, check out this repository and type

pytest

License

meshio is published under the MIT license.