Metadata-Version: 1.2
Name: cec2019comp100digit
Version: 0.4
Summary: Package for benchmark for the     100 digit competition on the IEEE     Congress on Evolutionary Computation CEC'2019
Home-page: https://github.com/dmolina/cec2019comp100digit
Author: Daniel Molina
Author-email: dmolina@decsai.ugr.es
Maintainer: Daniel Molina
License: GPL V3
Description: Introduction
        ============
        
        This is a Python wrapping using the C++ Implementation of the test suite for the
        Special Session on Large Scale Global Optimization at 2019 IEEE Congress on
        Evolutionary Computation http://cec2019.org/programs/competitions.html#cec-06.
        
        http://www.ntu.edu.sg/home/epnsugan/index_files/CEC2019/CEC2019.htm
        
        
        Note
        ----
        If you are to use any part of this code, please cite the following publications:
        
           K. V. Price, N. H. Awad, M. Z. Ali, P. N. Suganthan, "Problem Definitions and
           Evaluation Criteria for the 100-Digit Challenge Special Session and
           Competition on Single Objective Numerical Optimization,"  Technical Report,
           Nanyang Technological University, Singapore, November 2018.
        
        http://web.mysites.ntu.edu.sg/epnsugan/PublicSite/Shared%20Documents/Forms/AllItems.aspx?RootFolder=%2fepnsugan%2fPublicSite%2fShared%20Documents%2fCEC%2d2019&FolderCTID=&View=%7bDAF31868%2d97D8%2d4779%2dAE49%2d9CEC4DC3F310%7d
        
        Requirements
        ------------
        
        - GNU Make
        - GNU G++
        - Python
        - Cython
        
        Testing Environment
        -------------------
        
        - Debian GNU/Linux jessie/sid
        - GNU Make 3.81
        - g++ (Debian 4.7.3-4) 4.7.3
        - Python 2.7 and Python 3.2
        - numpy 1.8.1
        - cython 0.20.1
        
        Instalation
        -----------
        
        It is pending to submit to pip, when it is ready.
        
        Very easy, *pip install cec2019comp100digit* ;-). 
        
        You can also download from https://github.com/dmolina/cec2019comp100digit, and do *python setup.py install [--user]*.
        (the option *--user* is for installing the package locally, as a normal user (interesting when you want to 
        run the experiments in a cluster/server without administration permissions).
        
        To compile the source code in C++
        ----------------------------------
        
        The source code in C++ is also available. If you want to compile only the C++
        version type in 'make' in the root directory of source code. 
        
        There are two equivalents demo executables: demo and demo2. 
        
        **REMEMBER: To run the C++ version the directory input_data must be available in the working directory**. 
        In the python version, these files are included in the packages, so it is not
        needed.
        
        Quickstart
        ----------
        
        The package is very simple to use. There is a package cec2019comp100digit with
        three functions:
        
        - **init(fun_id, Dim)**
          Init the function for the dimension selected.
        
        - **eval(sol)**
          Eval the solution, when sol is a numpy (or array) of dimension *Dim*.
        
        - **end()**
          Free resources.
        
        Init function
        -------------
        >>> from cec2019comp100digit import cec2019comp100digit
        >>> bench = cec2019comp100digit
        >>> bench.init(3, 10) # Init function 3
        
        Create a random solution
        ~~~~~~~~~~~~~~~~~~~~~~~~
        >>> import numpy as np
        >>> sol = np.random.rand(10)
        
        Evaluate a solution
        ~~~~~~~~~~~~~~~~~~~
        >>> bench.eval(sol)
        18010038.104525752
        
        Freeing resources
        ~~~~~~~~~~~~~~~~~
        >>> bench.end()
        
        Contact
        -------
        
        Python package 
          Daniel Molina @ Computer Science Deparment, University of Granada
          Please feel free to contact me at <dmolina@decsai.ugr.es> for any enquiries or
          suggestions.
        
        
        Last Updated
        ~~~~~~~~~~~~
        - C++ version
          <2018-12-08>
        
        - Python wrapping
          <2018-12-08>
        
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
