Python module to do inference with Gaussian processes. Features:
See this report for the theory behind lsqfitgp.
Python >= 3.9 required. Then:
$ pip install lsqfitgp
The complete manual is available online at gattocrucco.github.io/lsqfitgp/docs. All the code is documented with docstrings, so you can also use the Python help system directly from the shell:
>>> import lsqfitgp as lgp
>>> help(lgp)
>>> help(lgp.something)
or, in an IPython shell/Jupyter notebook/Spyder IDE, use the question mark shortcut:
In [1]: lgp?
In [2]: lgp.something?
See also Comparison of Gaussian process Software on Wikipedia.
This software is released under the GPL. Amongst other things, it implies that, if you release an adaptation of this software, or even a program just importing it as external library, you have to release its code as open source with a license at least as strong as the GPL.
FAQs
A general purpose Gaussian process regression module
We found that lsqfitgp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.