Welcome to PVGeo’s code docs!

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The PVGeo python package contains VTK powered tools for data visualization in geophysics which are wrapped for direct use within the application ParaView by Kitware. These tools are tailored to data visualization in the geosciences with a heavy focus on structured data sets like 2D or 3D time-varying grids.

This website hosts the code documentation for the PVGeo python package found on GitHub and PyPI. This website strictly documents the code so that users have a convenient and familiar means of searching through the library to understand how to use PVGeo in a Python environment outside of ParaView. If you are searching for examples and demonstrations on how to use the PVGeo library, then head over to the full website where you can find tutorials with sample data sets and links to many other helpful resources.

For a quick overview of how PVGeo can be used in a Python environment or directly within ParaView, please checkout the code snippets and videos on the About Examples Page.


This package provides many VTK-like algorithms designed for geoscientific data formats and types to perform data integration and analysis. To ensure our users have powerful and easy to use tools that can visualize the results of PVGeo algorithms, we are actively involved in the development of vtki: a toolset for easy access to VTK data objects and 3D visualization in Python. To learn more about pairing PVGeo with vtki, please check out the example Jupyter notebooks.

Requesting Features, Reporting Issues, and Contributing

Please feel free to post features you would like to see from this package on the issues page as a feature request. If you stumble across any bugs or crashes while using code distributed here, please report it in the issues page so we can promptly address it. For other questions please join the PVGeo community on Slack.

About the Authors

The PVGeo code library was created and is managed by Bane Sullivan, graduate student in the Hydrological Science and Engineering interdisciplinary program at the Colorado School of Mines under Whitney Trainor-Guitton. If you would like to contact us, please inquire with info@pvgeo.org.

It is important to note the project is open source and that many features in this repository were made possible by contributors volunteering their time. Please take a look at the Contributors Page to learn more about the developers of PVGeo.

Getting Started

To begin using the PVGeo Python package, create/activate your Python virtual environment (we highly recommend using anaconda) and install PVGeo through pip:

pip install PVGeo


Windows users: Please see installation instructions on GitHub README.

Now PVGeo is ready for use in your standard python environment. To use the PVGeo library as plugins in ParaView, please see the detailed explanation here.

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