Benchmarking framework for all types of black-box optimization algorithms, postprocessing.
Project description
COmparing Continuous Optimisers (COCO) post-processing
The (cocopp
) package takes data generated with the COCO framework to compare continuous opitmizers and produces output figures and tables in html format and for including into LaTeX-documents.
Installation
pip install cocopp
Usage
The main method of the cocopp
package is main
(currently aliased to cocopp.rungeneric.main
). The main
method also allows basic use of the post-processing through a shell command-line interface. The recommended use is however from an IPython/Jupyter shell or notebook:
>>> import cocopp >>> cocopp.main('exdata/my_output another_folder yet_another_or_not')
postprocesses data from one or several folders, for example data generated with the help from the cocoex
module. Each folder should contain data of a full experiment with a single algorithm. (Within the folder the data can be distributed over subfolders). Results can be explored from the ppdata/index.html file, unless a a different output folder is specified with the -o option. Comparative data from over 200 full experiments are archived online and can be listed, filtered, and retrieved from cocopp.archives
(of type OfficialArchives
) and processed alone or together with local data. For example
>>> cocopp.archives.bbob('bfgs') ['2009/BFGS_...
lists all data sets run on the bbob
testbed containing 'bfgs' in their name. The first in the list can be postprocessed by
>>> cocopp.main('bfgs!')
All of them can be processed like
>>> cocopp.main('bfgs*')
Only a trailing *
is accepted and any string containing the substring is matched. The postprocessing result of
>>> cocopp.main('bbob/2009/*')
can be browsed at https://numbbo.github.io/ppdata-archive/bbob/2009. To display algorithms in the background, the genericsettings.background variable needs to be set:
>>> cocopp.genericsettings.background = {None: cocopp.archives.bbob.get_all('bfgs')}
where None
invokes the default color (grey) and line style (solid) genericsettings.background_default_style. Now we could compare our own data with the first 'bfgs'-matching archived algorithm where all other archived BFGS data are shown in the background with the command
>>> cocopp.main('exdata/my_output bfgs!')
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