meshio 3.3.0

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)
• 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

Some mesh formats are more suitable for I/O than others. Here you find an overview of how fast the meshio routines are for a certain mesh with about 100k nodes.

File size comparison

Comparison of the file sizes for a tetrahedral mesh with about 100k points. The red line marks the size of the mesh in memory.

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.