Skip to main content

pyGIMLi CI Anaconda-Server Badge release Github commits (since latest release) Slack

pyGIMLi is an open-source library for modelling and inversion and in geophysics. The object-oriented library provides management for structured and unstructured meshes in 2D and 3D, finite-element and finite-volume solvers, various geophysical forward operators, as well as Gauss-Newton based frameworks for constrained, joint and fully-coupled inversions with flexible regularization.

What is pyGIMLi suited for?

  • analyze, visualize and invert geophysical data in a reproducible manner
  • forward modelling of (geo)physical problems on complex 2D and 3D geometries
  • inversion with flexible controls on a-priori information and regularization
  • combination of different methods in constrained, joint and fully-coupled inversions
  • teaching applied geophysics (e.g. in combination with Jupyter notebooks)

What is pyGIMLi NOT suited for?

  • for people that expect a ready-made GUI for interpreting their data
Installation

Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge Anaconda-Server Badge

pyGIMLi can be installed with many different package managers (e.g., pip, conda, uv, etc.). Please refer to these instructions for more details.

Import convention
import pygimli as pg
print(pg.__version__)

Check www.pygimli.org for additional information, detailed installation instructions and many examples.

Citing pyGIMLi

More information can be found in this paper. If you use pyGIMLi for your work, please cite as:

Rücker, C., Günther, T., Wagner, F.M., 2017. pyGIMLi: An open-source library for modelling and inversion in geophysics, Computers and Geosciences, 109, 106-123, doi: 10.1016/j.cageo.2017.07.011.

BibTeX code:

@article{Ruecker2017,
  title = {{pyGIMLi}: An open-source library for modelling and inversion in geophysics},
  journal = {Computers and Geosciences},
  volume = {109},
  pages = {106--123},
  year = {2017},
  doi = {10.1016/j.cageo.2017.07.011},
  url = {https://www.sciencedirect.com/science/article/pii/S0098300417300584},
  author = {R\"ucker, C. and G\"unther, T. and Wagner, F. M.}
}
License

pyGIMLi is distributed under the terms of the Apache 2.0 license. Details on the license agreement can be found here.

Credits

We use or link some third-party software (beside the usual tool stack: cmake, gcc, boost, python, numpy, scipy, matplotlib) and are grateful for all the work made by the authors of these awesome open-source tools:

Metadata

Release files for pygimli 1.6.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for pygimli 1.6.1
File Interpreter ABI Platform Actions
pygimli-1.6.1-py3-none-any.whl Python 3 none any Details for pygimli-1.6.1-py3-none-any.whl

Release files / pygimli-1.6.1-py3-none-any.whl

Download URL pygimli-1.6.1-py3-none-any.whl
Size 546.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
3c404356fe4a9782e4492badf5a049b15ce7010d41ff01e6254a1a17d75901e0
BLAKE2b-256 checksum
How to use checksums
476455dd05de3cb440ab35f4df327bce20fd361792e67037c35bd091a710e088
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.14.7

Security for pygimli 1.6.1

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page