I/O for mesh files.
[](https://pypi.org/project/meshio) [](https://anaconda.org/conda-forge/meshio/) [](https://repology.org/project/python:meshio/versions) [](https://pypi.org/project/meshio/) [](https://doi.org/10.5281/zenodo.1173115) [](https://github.com/nschloe/meshio) [](https://pypistats.org/packages/meshio) [](https://discord.gg/Z6DMsJh4Hr) [](https://github.com/nschloe/meshio/actions?query=workflow%3Aci) [](https://app.codecov.io/gh/nschloe/meshio) [](https://lgtm.com/projects/g/nschloe/meshio) [](https://github.com/psf/black) 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](http://abaqus.software.polimi.it/v6.14/index.html) (`.inp`), ANSYS msh (`.msh`), [AVS-UCD](https://lanl.github.io/LaGriT/pages/docs/read_avs.html) (`.avs`), [CGNS](https://cgns.github.io/) (`.cgns`), [DOLFIN XML](https://manpages.ubuntu.com/manpages/disco/man1/dolfin-convert.1.html) (`.xml`), [Exodus](https://nschloe.github.io/meshio/exodus.pdf) (`.e`, `.exo`), [FLAC3D](https://www.itascacg.com/software/flac3d) (`.f3grid`), [H5M](https://www.mcs.anl.gov/~fathom/moab-docs/h5mmain.html) (`.h5m`), [Kratos/MDPA](https://github.com/KratosMultiphysics/Kratos/wiki/Input-data) (`.mdpa`), [Medit](https://people.sc.fsu.edu/~jburkardt/data/medit/medit.html) (`.mesh`, `.meshb`), [MED/Salome](https://docs.salome-platform.org/latest/dev/MEDCoupling/developer/med-file.html) (`.med`), [Nastran](https://help.autodesk.com/view/NSTRN/2019/ENU/?guid=GUID-42B54ACB-FBE3-47CA-B8FE-475E7AD91A00) (bulk data, `.bdf`, `.fem`, `.nas`), [Netgen](https://github.com/ngsolve/netgen) (`.vol`, `.vol.gz`), [Neuroglancer precomputed format](https://github.com/google/neuroglancer/tree/master/src/neuroglancer/datasource/precomputed#mesh-representation-of-segmented-object-surfaces), [Gmsh](https://gmsh.info/doc/texinfo/gmsh.html#File-formats) (format versions 2.2, 4.0, and 4.1, `.msh`), [OBJ](https://en.wikipedia.org/wiki/Wavefront_.obj_file) (`.obj`), [OFF](https://segeval.cs.princeton.edu/public/off_format.html) (`.off`), [PERMAS](https://www.intes.de) (`.post`, `.post.gz`, `.dato`, `.dato.gz`), [PLY](https://en.wikipedia.org/wiki/PLY_(file_format)) (`.ply`), [STL](https://en.wikipedia.org/wiki/STL_(file_format)) (`.stl`), [Tecplot .dat](http://paulbourke.net/dataformats/tp/), [TetGen .node/.ele](https://wias-berlin.de/software/tetgen/fformats.html), [SVG](https://www.w3.org/TR/SVG/) (2D output only) (`.svg`), [SU2](https://su2code.github.io/docs_v7/Mesh-File/) (`.su2`), [UGRID](https://www.simcenter.msstate.edu/software/documentation/ug_io/3d_grid_file_type_ugrid.html) (`.ugrid`), [VTK](https://vtk.org/wp-content/uploads/2015/04/file-formats.pdf) (`.vtk`), [VTU](https://vtk.org/Wiki/VTK_XML_Formats) (`.vtu`), [WKT](https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry) ([TIN](https://en.wikipedia.org/wiki/Triangulated_irregular_network)) (`.wkt`), [XDMF](https://www.xdmf.org/index.php/XDMF_Model_and_Format) (`.xdmf`, `.xmf`). Install with ``` pip install meshio[all] ``` (`[all]` pulls in all optional dependencies. By default, meshio only uses numpy.) You can then use the command-line tool ```sh meshio convert input.msh output.vtk # convert between two formats meshio info input.xdmf # show some info about the mesh meshio compress input.vtu # compress the mesh file meshio decompress input.vtu # decompress the mesh file meshio binary input.msh # convert to binary format meshio ascii input.msh # convert to ASCII format ``` with any of the supported formats. In Python, simply do ```python 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 # see meshio-convert -h for all possible formats ) # mesh.points, mesh.cells, mesh.cells_dict, ... # mesh.vtk.read() is also possible ``` to read a mesh. To write, do ```python import meshio # two triangles and one quad points = [ [0.0, 0.0], [1.0, 0.0], [0.0, 1.0], [1.0, 1.0], [2.0, 0.0], [2.0, 1.0], ] cells = [ ("triangle", [[0, 1, 2], [1, 3, 2]]), ("quad", [[1, 4, 5, 3]]), ] mesh = meshio.Mesh( points, cells, # Optionally provide extra data on points, cells, etc. point_data={"T": [0.3, -1.2, 0.5, 0.7, 0.0, -3.0]}, # Each item in cell data must match the cells array cell_data={"a": [[0.1, 0.2], [0.4]]}, ) mesh.write( "foo.vtk", # str, os.PathLike, or buffer/open file # file_format="vtk", # optional if first argument is a path; inferred from extension ) # Alternative with the same options meshio.write_points_cells("foo.vtk", points, cells) ``` 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). #### Time series The [XDMF format](https://www.xdmf.org/index.php/XDMF_Model_and_Format) supports time series with a shared mesh. You can write times series data using meshio with ```python 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 ```python 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) ``` ### ParaView plugin
*A Gmsh file opened with ParaView.*
If you have downloaded a binary version of ParaView, you may proceed as follows.
* Install meshio for the Python major version that ParaView uses (check `pvpython --version`)
* Open ParaView
* Find the file `paraview-meshio-plugin.py` of your meshio installation (on Linux:
`~/.local/share/paraview-5.9/plugins/`) and load it under _Tools / Manage Plugins / Load New_
* _Optional:_ Activate _Auto Load_
You can now open all meshio-supported files in ParaView.
### Performance comparison
The comparisons here are for a triangular mesh with about 900k points and 1.8M
triangles. 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](https://pypi.org/project/meshio/),
so simply run
```
pip install meshio
```
to install.
Additional dependencies (`netcdf4`, `h5py`) are required for some of the output formats
and can be pulled in by
```
pip install meshio[all]
```
You can also install meshio from [Anaconda](https://anaconda.org/conda-forge/meshio):
```
conda install -c conda-forge meshio
```
### Testing
To run the meshio unit tests, check out this repository and type
```
tox
```
### License
meshio is published under the [MIT license](https://en.wikipedia.org/wiki/MIT_License).