Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software

A very important area of research in the field of Mathematical Optimization is the benchmarking of optimization packages to compare solvers. During benchmarking, one usually collects a large amount of information like CPU time, number of functions evaluations, number of iterations, and much more. Th...

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Main Authors: Abel Soares Siqueira, Raniere Gaia Costa da Silva, Luiz-Rafael Santos
Format: Article
Language:English
Published: Ubiquity Press 2016-04-01
Series:Journal of Open Research Software
Subjects:
Online Access:http://openresearchsoftware.metajnl.com/articles/81
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spelling doaj-4058ff664f8a417e8f6a9098aa4cfde12020-11-24T22:22:38ZengUbiquity PressJournal of Open Research Software2049-96472016-04-0141e12e1210.5334/jors.8172Perprof-py: A Python Package for Performance Profile of Mathematical Optimization SoftwareAbel Soares Siqueira0Raniere Gaia Costa da Silva1Luiz-Rafael Santos2Federal University of ParanáUniversity of CampinasFederal University of Santa CatarinaA very important area of research in the field of Mathematical Optimization is the benchmarking of optimization packages to compare solvers. During benchmarking, one usually collects a large amount of information like CPU time, number of functions evaluations, number of iterations, and much more. This information, if presented as tables, can be difficult to analyze and compare due to large amount of data. Therefore tools to better process and understand optimization benchmark data have been developed. One of the most widespread tools is the Performance Profile graphics proposed by Dolan and Moré [2]. In this context, this paper describes perprof-py, a free/open source software that creates 'Performance Profile' graphics. This software produces graphics in PDF using LaTeX with PGF/TikZ [22] and PGFPLOTS [4] packages, in PNG using matplotlib [9], and in HTML using Bokeh [1]. Perprof-py can also be easily extended to be used with other plot libraries. It is implemented in Python 3 with support for internationalization, and is under the General Public License Version 3 (GPLv3).http://openresearchsoftware.metajnl.com/articles/81software benchmarkingmathematical optimizationperformance profilePython 3
collection DOAJ
language English
format Article
sources DOAJ
author Abel Soares Siqueira
Raniere Gaia Costa da Silva
Luiz-Rafael Santos
spellingShingle Abel Soares Siqueira
Raniere Gaia Costa da Silva
Luiz-Rafael Santos
Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
Journal of Open Research Software
software benchmarking
mathematical optimization
performance profile
Python 3
author_facet Abel Soares Siqueira
Raniere Gaia Costa da Silva
Luiz-Rafael Santos
author_sort Abel Soares Siqueira
title Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
title_short Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
title_full Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
title_fullStr Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
title_full_unstemmed Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software
title_sort perprof-py: a python package for performance profile of mathematical optimization software
publisher Ubiquity Press
series Journal of Open Research Software
issn 2049-9647
publishDate 2016-04-01
description A very important area of research in the field of Mathematical Optimization is the benchmarking of optimization packages to compare solvers. During benchmarking, one usually collects a large amount of information like CPU time, number of functions evaluations, number of iterations, and much more. This information, if presented as tables, can be difficult to analyze and compare due to large amount of data. Therefore tools to better process and understand optimization benchmark data have been developed. One of the most widespread tools is the Performance Profile graphics proposed by Dolan and Moré [2]. In this context, this paper describes perprof-py, a free/open source software that creates 'Performance Profile' graphics. This software produces graphics in PDF using LaTeX with PGF/TikZ [22] and PGFPLOTS [4] packages, in PNG using matplotlib [9], and in HTML using Bokeh [1]. Perprof-py can also be easily extended to be used with other plot libraries. It is implemented in Python 3 with support for internationalization, and is under the General Public License Version 3 (GPLv3).
topic software benchmarking
mathematical optimization
performance profile
Python 3
url http://openresearchsoftware.metajnl.com/articles/81
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AT luizrafaelsantos perprofpyapythonpackageforperformanceprofileofmathematicaloptimizationsoftware
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