|
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.
3 maintainers
Metadata
3 maintainers
Release files for coco-experiment 2.8.3
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Source distribution (sdist)
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Built distributions (wheels)
Total release size: 14.3 MB
Release files / coco_experiment-2.8.3.tar.gz
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