Metadata-Version: 2.1
Name: modcma
Version: 0.0.2.8
Summary: Package Containing Modular CMA-ES optimizer
Home-page: UNKNOWN
Author: Jacob de Nobel
Author-email: jacobdenobel@gmail.com
License: UNKNOWN
Description: # ModularCMAES ![Unittest](https://github.com/IOHprofiler/ModularCMAES/workflows/Unittest/badge.svg) [![Codacy Badge](https://api.codacy.com/project/badge/Grade/e25b2d338c194d67954fc9e138ca69cc)](https://app.codacy.com/gh/IOHprofiler/ModularCMAES?utm_source=github.com&utm_medium=referral&utm_content=IOHprofiler/ModularCMAES&utm_campaign=Badge_Grade) [![Codacy Badge](https://app.codacy.com/project/badge/Coverage/73720e228a89480585bdde05d3806661)](https://www.codacy.com/gh/IOHprofiler/ModularCMAES/dashboard?utm_source=github.com&utm_medium=referral&utm_content=IOHprofiler/ModularCMAES&utm_campaign=Badge_Coverage)
        
        This is a restructured version of the Modular CMA-ES framework, first introduced in ...
        Its modular design allows for the creation of thousands of variants of the CMA-ES algorithm.
        
        ## Installation
        Installation can be done via pip, using:
        `$ pip install modcma`
        
        ## Usage
        To optimize a single function, we provide a basic fmin interface, which can be used as follows:
        ```python
        from modcma import modularcmaes
        modularcmaes.fmin(func=sum, dim=5, maxfun=100)
        ```
        
        [Documentation](https://modularcmaes.readthedocs.io/)
        
        Running tests
        `$ python3 -m unittest discover`
        
        Running optimizer
        `$ python3 -m modcma  [-h] [-f FID] [-d DIM] [-i ITERATIONS] [-l] [-c] [-L LABEL] [-s SEED] [-a ARGUMENTS [ARGUMENTS ...]]`
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
