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https://github.com/nschloe/meshio

:spider_web: input/output for many mesh formats
https://github.com/nschloe/meshio

engineering mathematics mesh meshing pypi python vtk

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:spider_web: input/output for many mesh formats

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meshio

I/O for mesh files.

[![PyPi Version](https://img.shields.io/pypi/v/meshio.svg?style=flat-square)](https://pypi.org/project/meshio/)
[![Anaconda Cloud](https://anaconda.org/conda-forge/meshio/badges/version.svg?=style=flat-square)](https://anaconda.org/conda-forge/meshio/)
[![Packaging status](https://repology.org/badge/tiny-repos/python:meshio.svg)](https://repology.org/project/python:meshio/versions)
[![PyPI pyversions](https://img.shields.io/pypi/pyversions/meshio.svg?style=flat-square)](https://pypi.org/project/meshio/)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1173115.svg?style=flat-square)](https://doi.org/10.5281/zenodo.1173115)
[![GitHub stars](https://img.shields.io/github/stars/nschloe/meshio.svg?style=flat-square&logo=github&label=Stars&logoColor=white)](https://github.com/nschloe/meshio)
[![Downloads](https://pepy.tech/badge/meshio/month?style=flat-square)](https://pepy.tech/project/meshio)

[![Discord](https://img.shields.io/static/v1?logo=discord&logoColor=white&label=chat&message=on%20discord&color=7289da&style=flat-square)](https://discord.gg/Z6DMsJh4Hr)

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[![codecov](https://img.shields.io/codecov/c/github/nschloe/meshio.svg?style=flat-square)](https://app.codecov.io/gh/nschloe/meshio)
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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg?style=flat-square)](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/jammy/en/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]() (`.ply`),
> [STL]() (`.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://xdmf.org/index.php/XDMF_Model_and_Format) (`.xdmf`, `.xmf`).

([Here's a little survey](https://forms.gle/PSeNb3N3gv3wbEus8) on which formats are actually
used.)

Install with one of

```
pip install meshio[all]
conda install -c conda-forge meshio
```

(`[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://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

gmsh paraview
*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

file size

#### I/O speed

performance

#### Maximum memory usage

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).