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.
1 maintainer
Release files for meshio 3.3.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| meshio-3.3.1.tar.gz | 86.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| meshio-3.3.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 193.7 kB
Release files / meshio-3.3.1.tar.gz
| Download URL | meshio-3.3.1.tar.gz |
|---|---|
| Size | 86.8 kB |
| Tags | Source |
|
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Release files / meshio-3.3.1-py3-none-any.whl
| Download URL | meshio-3.3.1-py3-none-any.whl |
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| Size | 106.9 kB |
| Tags | Python 3 |
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