This is Python code for Delta-MOCK, including Adaptive Delta-MOCK, used in the paper "Towards an Adaptive Encoding for Evolutionary Data Clustering"1.
1Cameron Shand, Richard Allmendinger, Julia Handl, and John Keane. 2018. Towards an Adaptive Encoding for Evolutionary Data Clustering. In GECCO’18: Genetic and Evolutionary Computation Conference, July 15–19, 2018, Kyoto, Japan. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3205455.3205506
For the original Delta-MOCK in high performance C++, please see Mario Garza-Fabre's code here. This repo is intended for easy development, extensions, and, simple application of Delta-MOCK.
If you are having issues using this code, please raise an issue.
The key requirements are:
- Python 3.6+
- DEAP 1.2 (probably best to pip install from their github)
- python-igraph (best way is to install through conda-forge)
- Usual python stack (numpy, scipy etc.)
If you are on Linux, a conda environment has been provided. See the section below for install instructions.
If it is available, install the conda environment, run conda env create -f mock_env.yml.
To ensure that your setup works, run python run_mock.py -v. If no errors occur, success!
To then run experiments, you need to create a config file, save it in the configs sub-folder, and then run python run_mock.py -c configname.json.
The full user guide can be found here, which explains some aspects of the code and the different files.