https://github.com/darcamo/gpr_complex

A Gaussian Process Regression (GPR) library that can work with complex numbers.
https://github.com/darcamo/gpr_complex

gaussian-process-regression gpr machine-learning

Last synced: 5 months ago
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A Gaussian Process Regression (GPR) library that can work with complex numbers.

• Host: GitHub
• URL: https://github.com/darcamo/gpr_complex
• Owner: darcamo
• License: mit
• Created: 2020-01-29T21:16:20.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-06-12T19:59:58.000Z (about 6 years ago)
• Last Synced: 2025-08-17T00:58:23.055Z (11 months ago)
• Topics: gaussian-process-regression, gpr, machine-learning
• Language: Python
• Size: 140 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          

[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)

A Gaussian Process Regression (GPR) library that can work with complex numbers.

# Development

For dependency management and publishing to [Pypi](https://pypi.org/) we use

[poetry](https://python-poetry.org/).

If you want to extend `gpr_complex`, clone it from the

[git repository](https://github.com/darcamo/gpr_complex), run

`poetry install` to create the virtual environment with the required

dependencies and run `pre-commit install` to install the commit hooks.