cocopp
package documentationCOmparing Continuous Optimisers (COCO) post-processing package
This package (cocopp
) generates output figures and tables in html format
and for including into LaTeX-documents.
The cocopp.Interface
class contains the most basic commands and data of
the package, sufficient for most use cases.
>>> import cocopp >>> sorted(cocopp.Interface.dir()) ['archives', 'config', 'genericsettings', 'load', 'main'] >>> all(hasattr(cocopp, name) for name in cocopp.Interface.dir()) True
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 command-line interface. The recommended use
is however from an IPython/Jupyter shell:
>>> import cocopp >>> cocopp.main('exdata/my_output another_folder yet_another_or_not') # doctest:+SKIP
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') # doctest:+ELLIPSIS,+SKIP, ['2009/BFGS_...
lists all data sets containing 'bfgs' in their name. The first in the list can be postprocessed by
>>> cocopp.main('bfgs!') # doctest:+SKIP
All of them can be processed like
>>> cocopp.main('bfgs*') # doctest:+SKIP
Only a trailing *
is accepted and any string containing the
substring is matched. The postprocessing result of
>>> cocopp.main('bbob/2009/*') # doctest:+SKIP
can be browsed at http://coco.gforge.inria.fr/ppdata-archive/bbob/2009-all.
To display algorithms in the background, the genericsettings.background variable needs to be set:
>>> cocopp.genericsettings.background = {None: cocopp.archives.bbob.get_all('bfgs')} # doctest:+SKIP
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
>>> cocopp.main('exdata/my_output bfgs!') # doctest:+SKIP
Module | __main__ | Calls rungeneric.py. |
Module | algportfolio | Algorithm portfolio data set module. |
Module | archives | Undocumented |
Module | archives2 | Undocumented |
Module | archiving | Online and offline archiving of COCO data. |
Module | bestalg | Best algorithm dataset module |
Module | bwsettings | This module contains settings for outputting black and white figures. |
Module | captions | Provides basic functionality for creating figure and table captions. |
Module | cococommands | Depreciated (cocopp itself is to be used from Jupyter or IPython): Module for using COCO from the (i)Python interpreter. |
Package | comp2 | COmparing Continuous Optimisers (COCO) post-processing tool for comparing two algorithms: |
Package | compall | COmparing Continuous Optimisers (COCO) post-processing tool for comparing multiple algorithms: |
Module | config | This module is an attempt for a global configuration file for various parameters. |
Module | dataformatsettings | No module docstring; 2/4 classes documented |
Module | findfiles | Recursively find :file:`info` and zipped files within a directory and administer archives. |
Module | firstsession | First session script. |
Module | genericsettings | This module contains some global variables settings for COCO. |
Module | grayscalesettings | This module contains settings for outputting grayscale figures. |
Module | htmldesc | Prepares the descriptions of images and tables which will be converted to html. |
Module | old_ranksumtest | Stats including rank-sum test for small sample and correct tied ranks. Author: Sturla Molden http://mail.scipy.org/pipermail/scipy-user/2009-February/019759.html |
Module | ppconverrorbars | Process data and generates some comparison results. |
Module | ppfig | Generic routines for figure generation. |
Module | ppfigdim | Generate performance scaling figures. |
Module | ppfigparam | Generate aRT vs param. figures. |
Module | pplogloss | Module for computing aRT loss ratio |
Module | pprldistr | For generating empirical cumulative distribution function figures. |
Module | pprldistr2009_hardestRLB | Generates "pprldistr2009_RLB.pickle.gz" that is used to plot, in the background, the results of the 2009 algorithms |
Module | pproc | Raw post-processing routines. |
Module | pprocold | Helper routines for read index files. |
Module | ppsingle | Single data set results output module. |
Module | pptable | Module for generating tables used by rungeneric1.py. |
Module | pptex | Routines for writing TeX for tables. |
Module | preparehtml | Prepares the figure and table descriptions in html. |
Module | preparetexforhtml | Prepares the descriptions of images and tables which will be converted to html. |
Module | readalign | Helper routines to read in data files. |
Module | rungeneric | Process data to be included in a latex template. Called via |
Module | rungeneric1 | Module for post-processing the data of one algorithm. |
Module | rungenericmany | Process data to be included in a generic template. |
Module | sanitycheck | Module for checking data sets. |
Module | test | Tests the cocopp module. |
Module | testbedsettings | No module docstring; 10/10 classes, 1/9 functions documented |
Module | toolsdivers | Various tools. |
Module | toolsstats | Bootstrapping and statistics routines. |
From the __init__.py
module:
Class | Interface | collection of the most user-relevant modules, methods and data. |