Metadata-Version: 2.1
Name: opfunu
Version: 1.0.0
Summary: A framework of Optimization Functions using Numpy (OpFuNu) for optimization problems
Home-page: https://github.com/thieu1995/opfunu
Author: Thieu
Author-email: nguyenthieu2102@gmail.com
License: MIT
Download-URL: https://github.com/thieu1995/opfunu/archive/v1.0.0.zip
Description: # Optimization Function using Numpy (OpFuNu)
        [![GitHub release](https://img.shields.io/badge/release-1.0.0-yellow.svg)]()
        [![Wheel](https://img.shields.io/pypi/wheel/gensim.svg)](https://pypi.python.org/pypi/opfunu) 
        [![PyPI version](https://badge.fury.io/py/opfunu.svg)](https://badge.fury.io/py/opfunu)
        [![DOI version](https://zenodo.org/badge/DOI/10.5281/zenodo.3620960.svg)](https://badge.fury.io/py/opfunu)
        [![Downloads](https://pepy.tech/badge/opfunu)](https://pepy.tech/project/opfunu)
        [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
        
        ## Quick Notification
        
        * The structure of version 1.0.0 is based on Object-Oriented Programming, which is entirely different from the previous version (<= 0.8.0). 
        * All CEC functions from 2005, 2008, 2010, 2013, 2014, 2015, 2017, 2019, 2020, 2021, 2022 are implemented. This version is well-organized, faster and has no more bugs.
        * All old code-based functions from previous version <= 0.8.0 will be removed in version 1.0.1
        
        
        
        ## Installation
        
        Install the [current PyPI release](https://pypi.python.org/pypi/opfunu):
        
        ```bash
        pip install opfunu==1.0.0
        ```
        
        Or install the development version from GitHub:
        
        ```bash
        pip install git+https://github.com/thieu1995/opfunu
        ```
        
        ## Lib's structure
        
        ```code 
        
        docs
        examples
        opfunu
            cec_based
                cec.py
                cec2005.py
                cec2008.py
                ...
                cec2021.py
                cec2022.py
            name_based
                a_func.py
                b_func.py
                ...
                y_func.py
                z_func.py
            utils
                operator.py
                validator.py
                visualize.py
            __init__.py
            benchmark.py
        README.md
        setup.py
        ```
        
        ## Examples
        
        ### How to get the function and use it
        
        * 1st way
        
        ```python 
        from opfunu.cec_based.cec2014 import F12014
        
        func = F12014(ndim=30)
        func.evaluate(func.create_solution())
        
        ## or
        
        from opfunu.cec_based import F12014
        
        func = F102014(ndim=50)
        func.evaluate(func.create_solution())
        ```
        
        
        * 2nd way
        
        ```python
        
        import opfunu
        
        funcs = opfunu.get_functions_by_classname("F12014")
        func = funcs[0](ndim=10)
        func.evaluate(func.create_solution())
        
        ## or
        
        all_funcs_2014 = opfunu.get_functions_based_classname("2014")
        print(all_funcs_2014)
        
        ```
        
        
        ## References
        
        #### Publications
        
        + If you see my code and data useful and use it, please cite my works here
        
        ```code 
        @software{thieu_nguyen_2020_3711682,
          author       = {Thieu Nguyen},
          title        = {A framework of Optimization Functions using Numpy (OpFuNu) for optimization problems},
          year         = 2020,
          publisher    = {Zenodo},
          doi          = {10.5281/zenodo.3620960},
          url          = {https://doi.org/10.5281/zenodo.3620960.}
        }
        
        ```
        
        #### Documentation 
        ```code 
        1. dimension_based references
            1. http://benchmarkfcns.xyz/fcns
            2. https://en.wikipedia.org/wiki/Test_functions_for_optimization
            3. https://www.cs.unm.edu/~neal.holts/dga/benchmarkFunction/
            4. http://www.sfu.ca/~ssurjano/optimization.html
        
        2. type_based
            A Literature Survey of Benchmark Functions For Global Optimization Problems (2013)
        
        3. cec
            Problem Definitions and Evaluation Criteria for the CEC 2014 
        Special Session and Competition on Single Objective Real-Parameter Numerical Optimization 
        
        ```
        
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 :: GNU General Public License v3 (GPLv3)
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: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: System :: Benchmark
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Build Tools
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Utilities
Requires-Python: >=3.6
Description-Content-Type: text/markdown
