Metadata-Version: 2.1
Name: pfevaluator
Version: 1.0.0
Summary: pfevaluator: A library for evaluating performance metrics of Pareto fronts in multiple/many objective optimization problems
Home-page: https://github.com/thieu1995/pfevaluator
Author: Thieu
Author-email: nguyenthieu2102@gmail.com
License: MIT
Download-URL: https://github.com/thieu1995/pfevaluator/archive/v1.0.0.zip
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: System :: Benchmark
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: numpy

# pfevaluator: A library for evaluating performance metrics of Pareto fronts in multiple/many objective optimization problems

[![GitHub release](https://img.shields.io/badge/release-1.0.0-yellow.svg)]()
[![Documentation Status](https://readthedocs.org/projects/permetrics/badge/?version=latest)](https://permetrics.readthedocs.io/en/latest/?badge=latest)
[![](https://img.shields.io/badge/python-3.7+-orange.svg)](https://www.python.org/downloads/release/python-370/)
[![Wheel](https://img.shields.io/pypi/wheel/gensim.svg)](https://pypi.python.org/pypi/permetrics) 
[![PyPI version](https://badge.fury.io/py/permetrics.svg)](https://badge.fury.io/py/permetrics)
[![DOI](https://zenodo.org/badge/280617738.svg)](https://zenodo.org/badge/latestdoi/280617738)
[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)


---
> "Knowledge is power, sharing it is the premise of progress in life. It seems like a burden to someone, but it is the only way to achieve immortality."
>  --- [Thieu Nguyen](https://www.researchgate.net/profile/Thieu_Nguyen6)
---

## Introduction


### Dependencies
* Python (>= 3.6)
* Numpy (>= 1.15.1)
* pygmo (>= 2.13.0) 

### User installation
Install the [current PyPI release](https://pypi.python.org/pypi/pfevaluator):

```bash
pip install pfevaluator
```

Or install the development version from GitHub:

```bash
pip install git+https://github.com/thieu1995/pfevaluator
```


### Example

* The more complicated tests in the folder: examples

The [documentation](https://pfevaluator.readthedocs.io/) includes more detailed installation instructions and explanations.

### Changelog
* See the [ChangeLog.md](https://github.com/thieu1995/pfevaluator/blob/master/ChangeLog.md) for a history of notable changes to permetrics.


### Important links

* Official source code repo: https://github.com/thieu1995/pfevaluator
* Official documentation: https://pfevaluator.readthedocs.io/
* Download releases: https://pypi.org/project/pfevaluator/
* Issue tracker: https://github.com/thieu1995/pfevaluator/issues

* This project also related to my another projects which are "meta-heuristics" and "neural-network", check it here
    * https://github.com/thieu1995/opfunu
    * https://github.com/thieu1995/metaheuristics
    * https://github.com/thieu1995/mealpy
    * https://github.com/thieu1995/permetrics
    * https://github.com/chasebk


## Contributions 

### Citation
+ If you use permetrics in your project, please cite my works: 
```code 
@article{nguyen2019efficient,
  title={Efficient Time-Series Forecasting Using Neural Network and Opposition-Based Coral Reefs Optimization},
  author={Nguyen, Thieu and Nguyen, Tu and Nguyen, Binh Minh and Nguyen, Giang},
  journal={International Journal of Computational Intelligence Systems},
  volume={12},
  number={2},
  pages={1144--1161},
  year={2019},
  publisher={Atlantis Press}
}
```

