“VTK for humans”: a high-level API to the Visualization Toolkit (VTK)
mesh data structures and filtering methods for spatial datasets
3D plotting made simple and built for large/complex data geometries
vtki) is a helper module for the Visualization Toolkit
(VTK) that takes a different approach on interfacing with VTK through NumPy and
direct array access.
This package provides a Pythonic, well-documented interface exposing
VTK’s powerful visualization backend to facilitate rapid prototyping, analysis,
and visual integration of spatially referenced datasets.
This module can be used for scientific plotting for presentations and research papers as well as a supporting module for other mesh dependent Python modules.
For general questions about the project, its applications, or about software usage, please create an issue in the pyvista/pyvista-support repository where the community can collectively address your questions. You are also welcome to join us on Slack or send one of the developers an email. The project support team can be reached at firstname.lastname@example.org.
PyVista is a powerful tool that researchers can harness to create compelling, integrated visualizations of large datasets in an intuitive, Pythonic manner. Here are a few open-source projects that leverage PyVista:
itkwidgets: Interactive Jupyter widgets to visualize images, point sets, and meshes in 2D and 3D. Supports all PyVista mesh types.
pyansys: Pythonic interface to ANSYS result, full, and archive files
PVGeo: Python package of VTK-based algorithms to analyze geoscientific data and models. PyVista is used to make the inputs and outputs of PVGeo’s algorithms more accessible.
omfvista: 3D visualization for the Open Mining Format (omf). PyVista provides the foundation for this library’s visualization.
pymeshfix: Python/Cython wrapper of Marco Attene’s wonderful, award-winning MeshFix software.
tetgen: Python Interface to Hang Si’s C++ TetGen Library
There is a paper about PyVista!
If you are using PyVista in your scientific research, please help our scientific visibility by citing our work! Head over to Citing PyVista to learn more about citing PyVista.
Here are some videos that you can watch to learn pyvista:
PyConJP2020 talk “How to plot unstructured mesh file on Jupyter Notebook” (15 minutes):
If there is any material that we can add, please report .
If you have a working copy of VTK, installation is simply:
$ pip install pyvista
See Installation for more details.
Be sure to head over to the examples gallery to explore different use cases of PyVista and to start visualizing 3D data in Python! Also, please explore the list of external projects leveraging PyVista for 3D visualization in our external examples list
Translating the documentation¶
The recommended way for new contributors to translate
pyvista’s documentation is to
join the translation team on Transifex.
There is a pyvista translation page for pyvista (master) documentation.
Login to transifex service.
Go to pyvista translation page.
Request languageand fill form.
Wait acceptance by transifex pyvista translation maintainers.
(After acceptance) Translate on transifex.
You can see the translated document in Read The Docs.
Details can be found here: https://docs.transifex.com/getting-started-1/translators
In this section, you can learn more about how PyVista wraps different VTK mesh types and how you can leverage powerful 3D plotting and mesh analysis tools. Highlights of the API include:
Pythonic interface to VTK’s Python-C++ bindings
Filtering/plotting tools built for interactivity (see Widgets)
Direct access to common VTK filters (see Filters)
Intuitive plotting routines with
matplotlibsimilar syntax (see Plotting)