Development Status
- 4 - Beta
License
- OSI Approved :: BSD License
Programming Language
- Python
- Python :: 3.8
- Python :: 3.9
- Python :: 3.10
- Python :: 3.11
- Python :: 3.12
- Python :: Implementation :: CPython
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COmparing Continuous Optimisers COCO Experiment |
The coco-experiment Python module implements the experimental part of COCO: A Platform for Comparing Continuous Optimizers in a Black-Box Setting.
It provides several benchmark function suites and the data logging.
Documentation
The main documentation pages for the coco-experiment package cocoex can be found at
- getting-started
- API documentation
- issue tracker and bug reports
- source code page on GitHub
- COCO home page
Below are installation instruction and some usage hints.
Installation
The easiest way to install coco-experiment is using pip (preferably in a virtual environment):
pip install -U coco-experiment
For the difficult way look at this page and start with git clone https://github.com/numbbo/coco-experiment.git.
Usage
Similar to scikit-learn, the module name (coco-experiment) is not the import name, hence usage starts with
import cocoex
To get started, take a look at the getting-started page and at this simple example experiment. To run an experiment in practice, take a look at the complete example experiment.
Wheel compatibility matrix
| Platform | CPython 3.9 | CPython 3.10 | CPython 3.11 | CPython 3.12 | PyPy 3.9 (pp73) |
|---|---|---|---|---|---|
| macosx_11_0_arm64 | |||||
| manylinux2014_x86_64 | |||||
| manylinux_2_17_x86_64 | |||||
| manylinux_2_28_x86_64 | |||||
| musllinux_1_1_x86_64 | |||||
| win_amd64 |
Files in release
numpy
(>=1.24.0)