https://github.com/acj/python-gp
Simple genetic programming algorithm in Python that can interface with C++ (via Boost) for better performance.
https://github.com/acj/python-gp
Last synced: over 1 year ago
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Simple genetic programming algorithm in Python that can interface with C++ (via Boost) for better performance.
- Host: GitHub
- URL: https://github.com/acj/python-gp
- Owner: acj
- Created: 2012-01-07T20:15:36.000Z (over 14 years ago)
- Default Branch: master
- Last Pushed: 2012-01-07T20:29:12.000Z (over 14 years ago)
- Last Synced: 2025-01-04T09:08:47.490Z (over 1 year ago)
- Language: Python
- Homepage:
- Size: 152 KB
- Stars: 1
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
Requirements
============
* Python 2.3 (or higher)
* Boost's [bjam](http://sourceforge.net/projects/boost/files/latest/download?source=files) (run `bjam` from the `pycpp` directory and copy hybridgp.so to the main directory)
Usage
=====
To run the multiplexer example:
1. Edit multiplexer.py to choose an implementation (Native Python or C++)
2. Run `python multiplexer.py`
To run the regression example:
1. Edit regression.py to choose an implementation (Native Python or C++)
2. Run `python regression.py`
Miscellany
==========
This was a project for a graduate-level CS course. If you use it or improve it, let me know. Pull requests are welcome.