Пример #1
0
 if isConv:
     ppconverrorbars.main(dictAlg,outputdir,verbose)
 # Performance profiles
 if isPer:
     config.config()
     # ECDFs per noise groups
     dictNoi = pproc.dictAlgByNoi(dictAlg)
     for ng, tmpdictAlg in dictNoi.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             # pprldmany.main(entries, inset.summarized_target_function_values,
             # from . import config
             # config.config()
             pprldmany.main(entries, # pass expensive flag here? 
                            order=sortedAlgs,
                            outputdir=outputdir,
                            info=('%02dD_%s' % (d, ng)),
                            verbose=verbose)
     # ECDFs per function groups
     dictFG = pproc.dictAlgByFuncGroup(dictAlg)
     for fg, tmpdictAlg in dictFG.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             pprldmany.main(entries,
                            order=sortedAlgs,
                            outputdir=outputdir,
                            info=('%02dD_%s' % (d, fg)),
                            verbose=verbose)
     if isRldOnSingleFcts: # copy-paste from above, here for each function instead of function groups
         # ECDFs for each function
         dictFG = pproc.dictAlgByFun(dictAlg)
Пример #2
0
        #convergence plots
        if isConv:
            ppconverrorbars.main(dictAlg, outputdir, verbose)
        # Performance profiles
        if isPer:
            # ECDFs per noise groups
            dictNoi = pproc.dictAlgByNoi(dictAlg)
            for ng, tmpdictAlg in dictNoi.iteritems():
                dictDim = pproc.dictAlgByDim(tmpdictAlg)
                for d, entries in dictDim.iteritems():
                    # pprldmany.main(entries, inset.summarized_target_function_values,
                    # from . import config
                    # config.config()
                    pprldmany.main(
                        entries,  # pass expensive flag here? 
                        order=sortedAlgs,
                        outputdir=outputdir,
                        info=('%02dD_%s' % (d, ng)),
                        verbose=verbose)
            # ECDFs per function groups
            dictFG = pproc.dictAlgByFuncGroup(dictAlg)
            for fg, tmpdictAlg in dictFG.iteritems():
                dictDim = pproc.dictAlgByDim(tmpdictAlg)
                for d, entries in dictDim.iteritems():
                    pprldmany.main(entries,
                                   order=sortedAlgs,
                                   outputdir=outputdir,
                                   info=('%02dD_%s' % (d, fg)),
                                   verbose=verbose)
            print "ECDFs of run lengths figures done."

        if isTab:
Пример #3
0
 if isConv:
     ppconverrorbars.main(dictAlg,outputdir,verbose)
 # Performance profiles
 if isPer:
     config.config()
     # ECDFs per noise groups
     dictNoi = pproc.dictAlgByNoi(dictAlg)
     for ng, tmpdictAlg in dictNoi.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             # pprldmany.main(entries, inset.summarized_target_function_values,
             # from . import config
             # config.config()
             pprldmany.main(entries, # pass expensive flag here? 
                            order=sortedAlgs,
                            outputdir=outputdir,
                            info=('%02dD_%s' % (d, ng)),
                            verbose=verbose)
     # ECDFs per function groups
     dictFG = pproc.dictAlgByFuncGroup(dictAlg)
     for fg, tmpdictAlg in dictFG.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             pprldmany.main(entries,
                            order=sortedAlgs,
                            outputdir=outputdir,
                            info=('%02dD_%s' % (d, fg)),
                            verbose=verbose)
     if isRldOnSingleFcts: # copy-paste from above, here for each function instead of function groups
         # ECDFs for each function
         dictFG = pproc.dictAlgByFun(dictAlg)
Пример #4
0
     ppconverrorbars.main(dictAlg, outputdir, genericsettings.verbose)
 # empirical cumulative distribution functions (ECDFs) aka Data profiles
 if genericsettings.isRLDistr:
     config.config()
     # ECDFs per noise groups
     dictNoi = pproc.dictAlgByNoi(dictAlg)
     for ng, tmpdictAlg in dictNoi.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             # pprldmany.main(entries, inset.summarized_target_function_values,
             # from . import config
             # config.config()
             pprldmany.main(
                 entries,  # pass expensive flag here?
                 order=sortedAlgs,
                 outputdir=outputdir,
                 info=("%02dD_%s" % (d, ng)),
                 verbose=genericsettings.verbose,
             )
     # ECDFs per function groups
     dictFG = pproc.dictAlgByFuncGroup(dictAlg)
     for fg, tmpdictAlg in dictFG.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             pprldmany.main(
                 entries,
                 order=sortedAlgs,
                 outputdir=outputdir,
                 info=("%02dD_%s" % (d, fg)),
                 verbose=genericsettings.verbose,
             )
Пример #5
0
        #convergence plots
        if isConv:
            ppconverrorbars.main(dictAlg,outputdir,verbose)
        # Performance profiles
        if isPer:
            # ECDFs per noise groups
            dictNoi = pproc.dictAlgByNoi(dictAlg)
            for ng, tmpdictAlg in dictNoi.iteritems():
                dictDim = pproc.dictAlgByDim(tmpdictAlg)
                for d, entries in dictDim.iteritems():
                    # pprldmany.main(entries, inset.summarized_target_function_values,
                    # from . import config
                    # config.config()
                    pprldmany.main(entries, # pass expensive flag here? 
                                   order=sortedAlgs,
                                   outputdir=outputdir,
                                   info=('%02dD_%s' % (d, ng)),
                                   verbose=verbose)
            # ECDFs per function groups
            dictFG = pproc.dictAlgByFuncGroup(dictAlg)
            for fg, tmpdictAlg in dictFG.iteritems():
                dictDim = pproc.dictAlgByDim(tmpdictAlg)
                for d, entries in dictDim.iteritems():
                    pprldmany.main(entries,
                                   order=sortedAlgs,
                                   outputdir=outputdir,
                                   info=('%02dD_%s' % (d, fg)),
                                   verbose=verbose)
            print "ECDFs of run lengths figures done."

        if isTab:
Пример #6
0
 if genericsettings.isConv:
     ppconverrorbars.main(dictAlg, outputdir, genericsettings.verbose)
 # empirical cumulative distribution functions (ECDFs) aka Data profiles
 if genericsettings.isRLDistr:
     config.config(dsList[0].isBiobjective())
     # ECDFs per noise groups
     dictNoi = pproc.dictAlgByNoi(dictAlg)
     for ng, tmpdictAlg in dictNoi.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             # pprldmany.main(entries, inset.summarized_target_function_values,
             # from . import config
             # config.config()
             pprldmany.main(entries, # pass expensive flag here? 
                            dsList[0].isBiobjective(),
                            order=sortedAlgs,
                            outputdir=outputdir,
                            info=('%02dD_%s' % (d, ng)),
                            verbose=genericsettings.verbose)
     # ECDFs per function groups
     dictFG = pproc.dictAlgByFuncGroup(dictAlg)
     for fg, tmpdictAlg in dictFG.iteritems():
         dictDim = pproc.dictAlgByDim(tmpdictAlg)
         for d, entries in dictDim.iteritems():
             pprldmany.main(entries,
                            dsList[0].isBiobjective(),
                            order=sortedAlgs,
                            outputdir=outputdir,
                            info=('%02dD_%s' % (d, fg)),
                            verbose=genericsettings.verbose)
     if genericsettings.isRldOnSingleFcts: # copy-paste from above, here for each function instead of function groups
         # ECDFs for each function