Metadata-Version: 2.1
Name: meshio
Version: 4.3.13
Summary: I/O for many mesh formats
Home-page: https://github.com/nschloe/meshio
Author: Nico Schlömer et al.
Author-email: nico.schloemer@gmail.com
License: MIT
Project-URL: Code, https://github.com/nschloe/meshio
Project-URL: Issues, https://github.com/nschloe/meshio/issues
Project-URL: Funding, https://github.com/sponsors/nschloe
Description: <p align="center">
          <a href="https://github.com/nschloe/meshio"><img alt="meshio" src="https://nschloe.github.io/meshio/logo-with-text.svg" width="60%"></a>
          <p align="center">I/O for mesh files.</p>
        </p>
        
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        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`),
         [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 tools
        ```bash
        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
        <!--exdown-skip-->
        ```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
        )
        # 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
        <!--exdown-skip-->
        ```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
        <!--exdown-skip-->
        ```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
        
        <img alt="gmsh paraview" src="https://nschloe.github.io/meshio/gmsh-paraview.png" width="60%">
        *A Gmsh file opened with ParaView.*
        
        If you have downloaded a binary version of ParaView, you may proceed as follows.
        
         * Make sure that ParaView uses a Python version that supports meshio. (That is at least
           Python 3.)
         * Install meshio
         * Open ParaView
         * Find the file `paraview-meshio-plugin.py` of your meshio installation (on Linux:
           `~/.local/share/paraview/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
        
        <img alt="file size" src="https://nschloe.github.io/meshio/filesizes.svg" width="60%">
        
        #### I/O speed
        
        <img alt="performance" src="https://nschloe.github.io/meshio/performance.svg" width="90%">
        
        #### Maximum memory usage
        
        <img alt="memory usage" src="https://nschloe.github.io/meshio/memory.svg" width="90%">
        
        
        ### Installation
        
        meshio is [available from the Python Package Index](https://pypi.org/project/meshio/),
        so simply do
        ```
        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
        ```
        pytest
        ```
        
        ### License
        
        meshio is published under the [MIT license](https://en.wikipedia.org/wiki/MIT_License).
        
Keywords: mesh,file formats,scientific,engineering,fem,finite elements
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: all
