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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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 |
work_keys_str_mv |
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