示例#1
0
def main(argv=None):
    r"""Routine for post-processing COCO data from two algorithms.

    Provided with some data, this routine outputs figure and TeX files
    in a folder needed for the compilation of the provided LaTeX templates
    for comparing two algorithms (``*cmp.tex`` or ``*2*.tex``).
    
    The used template file needs to be edited so that the command
    ``\bbobdatapath`` points to the output folder created by this routine.

    The output files will contain performance tables, performance
    scaling figures and empirical cumulative distribution figures. On
    subsequent executions, new files will be added to the output folder,
    overwriting existing older files in the process.

    Keyword arguments:

    *argv* -- list of strings containing options and arguments. If not
    given, sys.argv is accessed.

    *argv* must list folders containing BBOB data files. Each of these
    folders should correspond to the data of ONE algorithm.

    Furthermore, argv can begin with, in any order, facultative option
    flags listed below.

        -h, --help
            displays this message.
        -v, --verbose
            verbose mode, prints out operations.
        -o OUTPUTDIR, --output-dir=OUTPUTDIR
            changes the default output directory (:file:`ppdata`) to
            :file:`OUTPUTDIR`
        --noise-free, --noisy
            processes only part of the data.
        --settings=SETTING
            changes the style of the output figures and tables. At the
            moment only the only differences are in the colors of the
            output figures. SETTING can be either "grayscale", "color"
            or "black-white". The default setting is "color".
        --fig-only, --rld-only, --tab-only, --sca-only
            these options can be used to output respectively the ERT
            graphs figures, run length distribution figures or the
            comparison tables scatter plot figures only. Any combination
            of these options results in no output.
        --conv 
            if this option is chosen, additionally convergence
            plots for each function and algorithm are generated.
        --rld-single-fcts
            generate also runlength distribution figures for each
            single function.
        --expensive
            runlength-based f-target values and fixed display limits,
            useful with comparatively small budgets. By default the
            setting is based on the budget used in the data.
        --not-expensive
            expensive setting off. 
        --svg
            generate also the svg figures which are used in html files 

    Exceptions raised:

    *Usage* -- Gives back a usage message.

    Examples:

    * Calling the rungeneric2.py interface from the command line::

        $ python bbob_pproc/rungeneric2.py -v Alg0-baseline Alg1-of-interest

      will post-process the data from folders :file:`Alg0-baseline` and
      :file:`Alg1-of-interest`, the former containing data for the
      reference algorithm (zero-th) and the latter data for the
      algorithm of concern (first). The results will be output in the
      default output folder. The ``-v`` option adds verbosity.

    * From the python interpreter (requires that the path to this
      package is in python search path)::

        >> import bbob_pproc as bb
        >> bb.rungeneric2.main('-o outputfolder PSO DEPSO'.split())

    This will execute the post-processing on the data found in folder
    :file:`PSO` and :file:`DEPSO`. The ``-o`` option changes the output
    folder from the default to :file:`outputfolder`.

    """

    if argv is None:
        argv = sys.argv[1:]
        # The zero-th input argument which is the name of the calling script is
        # disregarded.

    global ftarget
    try:

        try:
            opts, args = getopt.getopt(argv, genericsettings.shortoptlist, genericsettings.longoptlist)
        except getopt.error, msg:
             raise Usage(msg)

        if not (args):
            usage()
            sys.exit()

        #Process options
        outputdir = genericsettings.outputdir
        for o, a in opts:
            if o in ("-v", "--verbose"):
                genericsettings.verbose = True
            elif o in ("-h", "--help"):
                usage()
                sys.exit()
            elif o in ("-o", "--output-dir"):
                outputdir = a
            elif o == "--fig-only":
                genericsettings.isRLDistr = False
                genericsettings.isTab = False
                genericsettings.isScatter = False
            elif o == "--rld-only":
                genericsettings.isFig = False
                genericsettings.isTab = False
                genericsettings.isScatter = False
            elif o == "--tab-only":
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
                genericsettings.isScatter = False
            elif o == "--sca-only":
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
                genericsettings.isTab = False
            elif o == "--noisy":
                genericsettings.isNoisy = True
            elif o == "--noise-free":
                genericsettings.isNoiseFree = True
            elif o == "--settings":
                genericsettings.inputsettings = a
            elif o == "--conv":
                genericsettings.isConv = True
            elif o == "--rld-single-fcts":
                genericsettings.isRldOnSingleFcts = True
            elif o == "--runlength-based":
                genericsettings.runlength_based_targets = True
            elif o == "--expensive":
                genericsettings.isExpensive = True  # comprises runlength-based
            elif o == "--not-expensive":
                genericsettings.isExpensive = False  
            elif o == "--svg":
                genericsettings.generate_svg_files = True
            elif o == "--los-only":
                warnings.warn("option --los-only will have no effect with rungeneric2.py")
            elif o == "--crafting-effort=":
                warnings.warn("option --crafting-effort will have no effect with rungeneric2.py")
            elif o in ("-p", "--pickle"):
                warnings.warn("option --pickle will have no effect with rungeneric2.py")
            else:
                assert False, "unhandled option"

        # from bbob_pproc import bbob2010 as inset # input settings
        if genericsettings.inputsettings == "color":
            from bbob_pproc import genericsettings as inset # input settings
            config.config()
        elif genericsettings.inputsettings == "grayscale": # probably very much obsolete
            from bbob_pproc import grayscalesettings as inset # input settings
        elif genericsettings.inputsettings == "black-white": # probably very much obsolete
            from bbob_pproc import bwsettings as inset # input settings
        else:
            txt = ('Settings: %s is not an appropriate ' % genericsettings.inputsettings
                   + 'argument for input flag "--settings".')
            raise Usage(txt)

        if (not genericsettings.verbose):
            warnings.simplefilter('module')
            warnings.simplefilter('ignore')            

        print ("Post-processing will generate comparison " +
               "data in folder %s" % outputdir)
        print "  this might take several minutes."

        dsList, sortedAlgs, dictAlg = processInputArgs(args, verbose=genericsettings.verbose)

        if 1 < 3 and len(sortedAlgs) != 2:
            raise ValueError('rungeneric2.py needs exactly two algorithms to compare, found: ' 
                             + str(sortedAlgs)
                             + '\n use rungeneric.py (or rungenericmany.py) to compare more algorithms. ')
 
        if not dsList:
            sys.exit()

        for i in dictAlg:
            if genericsettings.isNoisy and not genericsettings.isNoiseFree:
                dictAlg[i] = dictAlg[i].dictByNoise().get('nzall', DataSetList())
            if genericsettings.isNoiseFree and not genericsettings.isNoisy:
                dictAlg[i] = dictAlg[i].dictByNoise().get('noiselessall', DataSetList())

        for i in dsList:
            if i.dim not in genericsettings.dimensions_to_display:
                continue

            if (dict((j, i.instancenumbers.count(j)) for j in set(i.instancenumbers)) <
                inset.instancesOfInterest):
                warnings.warn('The data of %s do not list ' %(i) +
                              'the correct instances ' +
                              'of function F%d.' %(i.funcId))

        if len(sortedAlgs) < 2:
            raise Usage('Expect data from two different algorithms, could ' +
                        'only find one.')
        elif len(sortedAlgs) > 2:
            warnings.warn('Data from folders: %s ' % (sortedAlgs) +
                          'were found, the first two will be processed.')

        # Group by algorithm
        dsList0 = dictAlg[sortedAlgs[0]]
        if not dsList0:
            raise Usage('Could not find data for algorithm %s.' % (sortedAlgs[0]))

        dsList1 = dictAlg[sortedAlgs[1]]
        if not dsList1:
            raise Usage('Could not find data for algorithm %s.' % (sortedAlgs[0]))

        # get the name of each algorithm from the input arguments
        tmppath0, alg0name = os.path.split(sortedAlgs[0].rstrip(os.sep))
        tmppath1, alg1name = os.path.split(sortedAlgs[1].rstrip(os.sep))

        for i in dsList0:
            i.algId = alg0name
        for i in dsList1:
            i.algId = alg1name

        # compute maxfuneval values
        dict_max_fun_evals1 = {}
        dict_max_fun_evals2 = {}
        for ds in dsList0:
            dict_max_fun_evals1[ds.dim] = np.max((dict_max_fun_evals1.setdefault(ds.dim, 0), float(np.max(ds.maxevals))))
        for ds in dsList1:
            dict_max_fun_evals2[ds.dim] = np.max((dict_max_fun_evals2.setdefault(ds.dim, 0), float(np.max(ds.maxevals))))
        config.target_values(genericsettings.isExpensive, {1: min([max([val/dim for dim, val in dict_max_fun_evals1.iteritems()]), 
                                                   max([val/dim for dim, val in dict_max_fun_evals2.iteritems()])]
                                                  )})
        config.config()
        
        ######################### Post-processing #############################
        if genericsettings.isFig or genericsettings.isRLDistr or genericsettings.isTab or genericsettings.isScatter:
            if not os.path.exists(outputdir):
                os.mkdir(outputdir)
                if genericsettings.verbose:
                    print 'Folder %s was created.' % (outputdir)
            
            # prepend the algorithm name command to the tex-command file
            abc = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
            lines = []
            for i, alg in enumerate(args):
                lines.append('\\providecommand{\\algorithm' + abc[i] + '}{' + 
                        str_to_latex(strip_pathname1(alg)) + '}')
            prepend_to_file(os.path.join(outputdir,
                         'bbob_pproc_commands.tex'), lines, 1000, 
                         'bbob_proc_commands.tex truncated, consider removing the file before the text run'
                         )

        # Check whether both input arguments list noisy and noise-free data
        dictFN0 = dsList0.dictByNoise()
        dictFN1 = dsList1.dictByNoise()
        k0 = set(dictFN0.keys())
        k1 = set(dictFN1.keys())
        symdiff = k1 ^ k0 # symmetric difference
        if symdiff:
            tmpdict = {}
            for i, noisegrp in enumerate(symdiff):
                if noisegrp == 'nzall':
                    tmp = 'noisy'
                elif noisegrp == 'noiselessall':
                    tmp = 'noiseless'

                if dictFN0.has_key(noisegrp):
                    tmp2 = sortedAlgs[0]
                elif dictFN1.has_key(noisegrp):
                    tmp2 = sortedAlgs[1]

                tmpdict.setdefault(tmp2, []).append(tmp)

            txt = []
            for i, j in tmpdict.iteritems():
                txt.append('Only input folder %s lists %s data.'
                            % (i, ' and '.join(j)))
            raise Usage('Data Mismatch: \n  ' + ' '.join(txt)
                        + '\nTry using --noise-free or --noisy flags.')

        if genericsettings.isFig:
            plt.rc("axes", **inset.rcaxeslarger)
            plt.rc("xtick", **inset.rcticklarger)
            plt.rc("ytick", **inset.rcticklarger)
            plt.rc("font", **inset.rcfontlarger)
            plt.rc("legend", **inset.rclegendlarger)
            plt.rc('pdf', fonttype = 42)
            ppfig2.main(dsList0, dsList1, ppfig2_ftarget,
                        outputdir, genericsettings.verbose)
            print "log ERT1/ERT0 vs target function values done."

        plt.rc("axes", **inset.rcaxes)
        plt.rc("xtick", **inset.rctick)
        plt.rc("ytick", **inset.rctick)
        plt.rc("font", **inset.rcfont)
        plt.rc("legend", **inset.rclegend)
        plt.rc('pdf', fonttype = 42)

        if genericsettings.isRLDistr:
            if len(dictFN0) > 1 or len(dictFN1) > 1:
                warnings.warn('Data for functions from both the noisy and ' +
                              'non-noisy testbeds have been found. Their ' +
                              'results will be mixed in the "all functions" ' +
                              'ECDF figures.')
            dictDim0 = dsList0.dictByDim()
            dictDim1 = dsList1.dictByDim()

            # ECDFs of ERT ratios
            for dim in set(dictDim0.keys()) & set(dictDim1.keys()):
                if dim in inset.rldDimsOfInterest:
                    # ECDF for all functions altogether
                    try:
                        pprldistr2.main(dictDim0[dim], dictDim1[dim], dim,
                                        inset.rldValsOfInterest,
                                        outputdir,
                                        '%02dD_all' % dim,
                                        genericsettings.verbose)
                    except KeyError:
                        warnings.warn('Could not find some data in %d-D.'
                                      % (dim))
                        continue

                    # ECDFs per function groups
                    dictFG0 = dictDim0[dim].dictByFuncGroup()
                    dictFG1 = dictDim1[dim].dictByFuncGroup()

                    for fGroup in set(dictFG0.keys()) & set(dictFG1.keys()):
                        pprldistr2.main(dictFG1[fGroup], dictFG0[fGroup], dim,
                                        inset.rldValsOfInterest,
                                        outputdir,
                                        '%02dD_%s' % (dim, fGroup),
                                        genericsettings.verbose)

                    # ECDFs per noise groups
                    dictFN0 = dictDim0[dim].dictByNoise()
                    dictFN1 = dictDim1[dim].dictByNoise()

                    for fGroup in set(dictFN0.keys()) & set(dictFN1.keys()):
                        pprldistr2.main(dictFN1[fGroup], dictFN0[fGroup], dim,
                                        inset.rldValsOfInterest,
                                        outputdir,
                                        '%02dD_%s' % (dim, fGroup),
                                        genericsettings.verbose)
                                                
            prepend_to_file(os.path.join(outputdir,
                            'bbob_pproc_commands.tex'),
                            ['\\providecommand{\\bbobpprldistrlegendtwo}[1]{',
                             pprldistr.caption_two(),  # depends on the config setting, should depend on maxfevals
                             '}'
                            ])
            
            
            print "ECDF runlength ratio graphs done."

            for dim in set(dictDim0.keys()) & set(dictDim1.keys()):
                pprldistr.fmax = None #Resetting the max final value
                pprldistr.evalfmax = None #Resetting the max #fevalsfactor
                # ECDFs of all functions altogether
                if dim in inset.rldDimsOfInterest:
                    try:
                        pprldistr.comp(dictDim1[dim], dictDim0[dim],
                                       inset.rldValsOfInterest, # TODO: let rldVals... possibly be RL-based targets
                                       True,
                                       outputdir, 'all', genericsettings.verbose)
                    except KeyError:
                        warnings.warn('Could not find some data in %d-D.'
                                      % (dim))
                        continue

                    # ECDFs per function groups
                    dictFG0 = dictDim0[dim].dictByFuncGroup()
                    dictFG1 = dictDim1[dim].dictByFuncGroup()

                    for fGroup in set(dictFG0.keys()) & set(dictFG1.keys()):
                        pprldistr.comp(dictFG1[fGroup], dictFG0[fGroup],
                                       inset.rldValsOfInterest, True,
                                       outputdir,
                                       '%s' % fGroup, genericsettings.verbose)

                    # ECDFs per noise groups
                    dictFN0 = dictDim0[dim].dictByNoise()
                    dictFN1 = dictDim1[dim].dictByNoise()
                    for fGroup in set(dictFN0.keys()) & set(dictFN1.keys()):
                        pprldistr.comp(dictFN1[fGroup], dictFN0[fGroup],
                                       inset.rldValsOfInterest, True,
                                       outputdir,
                                       '%s' % fGroup, genericsettings.verbose)

            if genericsettings.isRldOnSingleFcts: # copy-paste from above, here for each function instead of function groups
                # ECDFs for each function
                pprldmany.all_single_functions(dictAlg, sortedAlgs,
                        outputdir, genericsettings.verbose)
            print "ECDF runlength graphs done."

        if genericsettings.isConv:
            ppconverrorbars.main(dictAlg, outputdir, genericsettings.verbose)

        if genericsettings.isScatter:
            if genericsettings.runlength_based_targets:
                ppscatter.targets = ppscatter.runlength_based_targets
            ppscatter.main(dsList1, dsList0, outputdir,
                           verbose=genericsettings.verbose)
            prepend_to_file(os.path.join(outputdir,
                            'bbob_pproc_commands.tex'), 
                            ['\\providecommand{\\bbobppscatterlegend}[1]{', 
                             ppscatter.figure_caption(), 
                             '}'
                            ])
            
            replace_in_file(os.path.join(outputdir, genericsettings.two_algorithm_file_name + '.html'), '##bbobppscatterlegend##', ppscatter.figure_caption_html())
                            
            print "Scatter plots done."

        if genericsettings.isTab:
            dictNG0 = dsList0.dictByNoise()
            dictNG1 = dsList1.dictByNoise()

            for nGroup in set(dictNG0.keys()) & set(dictNG1.keys()):
                # split table in as many as necessary
                dictFunc0 = dictNG0[nGroup].dictByFunc()
                dictFunc1 = dictNG1[nGroup].dictByFunc()
                funcs = list(set(dictFunc0.keys()) & set(dictFunc1.keys()))
                if len(funcs) > 24:
                    funcs.sort()
                    nbgroups = int(numpy.ceil(len(funcs)/24.))
                    def split_seq(seq, nbgroups):
                        newseq = []
                        splitsize = 1.0/nbgroups*len(seq)
                        for i in range(nbgroups):
                            newseq.append(seq[int(round(i*splitsize)):int(round((i+1)*splitsize))])
                        return newseq

                    groups = split_seq(funcs, nbgroups)
                    # merge
                    group0 = []
                    group1 = []
                    for i, g in enumerate(groups):
                        tmp0 = DataSetList()
                        tmp1 = DataSetList()
                        for f in g:
                            tmp0.extend(dictFunc0[f])
                            tmp1.extend(dictFunc1[f])
                        group0.append(tmp0)
                        group1.append(tmp1)
                    for i, g in enumerate(zip(group0, group1)):
                        pptable2.main(g[0], g[1], inset.tabDimsOfInterest,
                                      outputdir,
                                      '%s%d' % (nGroup, i), genericsettings.verbose)
                else:
                    if 11 < 3:  # future handling: 
                        dictFunc0 = dsList0.dictByFunc()
                        dictFunc1 = dsList1.dictByFunc()
                        funcs = list(set(dictFunc0.keys()) & set(dictFunc1.keys()))
                        funcs.sort()
#                        nbgroups = int(numpy.ceil(len(funcs)/testbedsettings.numberOfFunctions))
#                        pptable2.main(dsList0, dsList1,
#                                      testbedsettings.tabDimsOfInterest, outputdir,
#                                      '%s' % (testbedsettings.testbedshortname), genericsettings.verbose)
                    else:
                        pptable2.main(dictNG0[nGroup], dictNG1[nGroup],
                                      inset.tabDimsOfInterest,
                                      outputdir,
                                      '%s' % (nGroup), genericsettings.verbose)

            if isinstance(pptable2.targetsOfInterest, pproc.RunlengthBasedTargetValues):
                prepend_to_file(os.path.join(outputdir,
                            'bbob_pproc_commands.tex'), 
                            ['\\providecommand{\\bbobpptablestwolegend}[1]{', 
                             pptable2.table_caption_expensive, 
                             '}'
                            ])
            else:
                prepend_to_file(os.path.join(outputdir,
                            'bbob_pproc_commands.tex'), 
                            ['\\providecommand{\\bbobpptablestwolegend}[1]{', 
                             pptable2.table_caption, 
                             '}'
                            ])
                            
            htmlFileName = os.path.join(outputdir, genericsettings.two_algorithm_file_name + '.html')            
            key =  '##bbobpptablestwolegendexpensive##' if isinstance(pptable2.targetsOfInterest, pproc.RunlengthBasedTargetValues) else '##bbobpptablestwolegend##'
            replace_in_file(htmlFileName, '##bbobpptablestwolegend##', htmldesc.getValue(key))
                        
            alg0 = set(i[0] for i in dsList0.dictByAlg().keys()).pop().replace(genericsettings.extraction_folder_prefix, '')[0:3]
            alg1 = set(i[0] for i in dsList1.dictByAlg().keys()).pop().replace(genericsettings.extraction_folder_prefix, '')[0:3]
            replace_in_file(htmlFileName, 'algorithmAshort', alg0)
            replace_in_file(htmlFileName, 'algorithmBshort', alg1)
            
            for i, alg in enumerate(args):
                replace_in_file(htmlFileName, 'algorithm' + abc[i], str_to_latex(strip_pathname1(alg)))

            print "Tables done."

        if genericsettings.isScaleUp:
            plt.rc("axes", labelsize=20, titlesize=24)
            plt.rc("xtick", labelsize=20)
            plt.rc("ytick", labelsize=20)
            plt.rc("font", size=20)
            plt.rc("legend", fontsize=20)
            plt.rc('pdf', fonttype = 42)
            if genericsettings.runlength_based_targets:
                ftarget = RunlengthBasedTargetValues([target_runlength])  # TODO: make this more variable but also consistent
            ppfigs.main(dictAlg, genericsettings.two_algorithm_file_name, sortedAlgs, ftarget,
                        outputdir, genericsettings.verbose)
            plt.rcdefaults()
            print "Scaling figures done."

        if genericsettings.isFig or genericsettings.isRLDistr or genericsettings.isTab or genericsettings.isScatter or genericsettings.isScaleUp:
            print "Output data written to folder %s" % outputdir

        plt.rcdefaults()
示例#2
0
def main(argv=None):
    r"""Post-processing COCO data of a single algorithm.

    Provided with some data, this routine outputs figure and TeX files
    in a folder needed for the compilation of the provided LaTeX templates
    for one algorithm (``*article.tex`` or ``*1*.tex``).
    The used template file needs to be edited so that the commands
    ``\bbobdatapath`` and ``\algfolder`` point to the output folder created
    by this routine.

    These output files will contain performance tables, performance
    scaling figures and empirical cumulative distribution figures. On
    subsequent executions, new files will be added to the output folder,
    overwriting existing older files in the process.

    Keyword arguments:

    *argv* -- list of strings containing options and arguments. If not
    given, sys.argv is accessed.

    *argv* should list either names of :file:`info` files or folders
    containing :file:`info` files. argv can also contain post-processed
    :file:`pickle` files generated by this routine. Furthermore, *argv*
    can begin with, in any order, facultative option flags listed below.

        -h, --help
            displays this message.
        -v, --verbose
            verbose mode, prints out all operations.
        -p, --pickle
            generates pickle post processed data files.
        -o OUTPUTDIR, --output-dir=OUTPUTDIR
            changes the default output directory (:file:`ppdata`) to
            :file:`OUTPUTDIR`.
        --crafting-effort=VALUE
            sets the crafting effort to VALUE (float). Otherwise the
            default value of 0. will be used.
        --noise-free, --noisy
            processes only part of the data.
        --settings=SETTINGS
            changes the style of the output figures and tables. At the
            moment the only differences are  in the colors of the output
            figures. SETTINGS can be either "grayscale", "color" or
            "black-white". The default setting is "color".
        --tab-only, --fig-only, --rld-only, --los-only
            these options can be used to output respectively the TeX
            tables, convergence and ERTs graphs figures, run length
            distribution figures, ERT loss ratio figures only. A
            combination of any two of these options results in no
            output.
        --conv
            if this option is chosen, additionally convergence plots
            for each function and algorithm are generated.
        --rld-single-fcts
            generate also runlength distribution figures for each
            single function.
        --expensive
            runlength-based f-target values and fixed display limits,
            useful with comparatively small budgets. By default the
            setting is based on the budget used in the data.
        --not-expensive
            expensive setting off. 
        --svg
            generate also the svg figures which are used in html files 
        --runlength-based
            runlength-based f-target values, such that the
            "level of difficulty" is similar for all functions. 

    Exceptions raised:

    *Usage* -- Gives back a usage message.

    Examples:

    * Calling the rungeneric1.py interface from the command line::

        $ python bbob_pproc/rungeneric1.py -v experiment1

      will post-process the folder experiment1 and all its containing
      data, base on the .info files found in the folder. The result will
      appear in the default output folder. The -v option adds verbosity. ::

        $ python bbob_pproc/rungeneric1.py -o exp2 experiment2/*.info

      This will execute the post-processing on the info files found in
      :file:`experiment2`. The result will be located in the alternative
      location :file:`exp2`.

    * Loading this package and calling the main from the command line
      (requires that the path to this package is in python search path)::

        $ python -m bbob_pproc.rungeneric1 -h

      This will print out this help message.

    * From the python interpreter (requires that the path to this
      package is in python search path)::

        >> import bbob_pproc as bb
        >> bb.rungeneric1.main('-o outputfolder folder1'.split())

      This will execute the post-processing on the index files found in
      :file:`folder1`. The ``-o`` option changes the output folder from
      the default to :file:`outputfolder`.

    """

    if argv is None:
        argv = sys.argv[1:]
        # The zero-th input argument which is the name of the calling script is
        # disregarded.

    if 1 < 3:
        opts, args = getopt.getopt(argv, genericsettings.shortoptlist, genericsettings.longoptlist)
        if 11 < 3:
            try:
                opts, args = getopt.getopt(argv, genericsettings.shortoptlist, genericsettings.longoptlist)
            except getopt.error, msg:
                raise Usage(msg)

        if not (args) and not "--help" in argv and not "h" in argv:
            print "not enough input arguments given"
            print "cave: the following options also need an argument:"
            print [o for o in genericsettings.longoptlist if o[-1] == "="]
            print "options given:"
            print opts
            print "try --help for help"
            sys.exit()

        # Process options
        outputdir = genericsettings.outputdir
        for o, a in opts:
            if o in ("-v", "--verbose"):
                genericsettings.verbose = True
            elif o in ("-h", "--help"):
                usage()
                sys.exit()
            elif o in ("-p", "--pickle"):
                genericsettings.isPickled = True
            elif o in ("-o", "--output-dir"):
                outputdir = a
            elif o == "--noisy":
                genericsettings.isNoisy = True
            elif o == "--noise-free":
                genericsettings.isNoiseFree = True
            # The next 4 are for testing purpose
            elif o == "--tab-only":
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
                genericsettings.isLogLoss = False
            elif o == "--fig-only":
                genericsettings.isTab = False
                genericsettings.isRLDistr = False
                genericsettings.isLogLoss = False
            elif o == "--rld-only":
                genericsettings.isTab = False
                genericsettings.isFig = False
                genericsettings.isLogLoss = False
            elif o == "--los-only":
                genericsettings.isTab = False
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
            elif o == "--crafting-effort":
                try:
                    genericsettings.inputCrE = float(a)
                except ValueError:
                    raise Usage("Expect a valid float for flag crafting-effort.")
            elif o == "--settings":
                genericsettings.inputsettings = a
            elif o == "--conv":
                genericsettings.isConv = True
            elif o == "--rld-single-fcts":
                genericsettings.isRldOnSingleFcts = True
            elif o == "--runlength-based":
                genericsettings.runlength_based_targets = True
            elif o == "--expensive":
                genericsettings.isExpensive = True  # comprises runlength-based
            elif o == "--not-expensive":
                genericsettings.isExpensive = False
            elif o == "--svg":
                genericsettings.generate_svg_files = True
            elif o == "--sca-only":
                warnings.warn("option --sca-only will have no effect with rungeneric1.py")
            else:
                assert False, "unhandled option"

        # from bbob_pproc import bbob2010 as inset # input settings
        if genericsettings.inputsettings == "color":
            from bbob_pproc import genericsettings as inset  # input settings
        elif genericsettings.inputsettings == "grayscale":
            from bbob_pproc import grayscalesettings as inset  # input settings
        elif genericsettings.inputsettings == "black-white":
            from bbob_pproc import bwsettings as inset  # input settings
        else:
            txt = (
                "Settings: %s is not an appropriate " % genericsettings.inputsettings
                + 'argument for input flag "--settings".'
            )
            raise Usage(txt)

        if 11 < 3:
            from bbob_pproc import config  # input settings

            config.config(False)
            import imp

            # import testbedsettings as testbedsettings # input settings
            try:
                fp, pathname, description = imp.find_module("testbedsettings")
                testbedsettings = imp.load_module("testbedsettings", fp, pathname, description)
            finally:
                fp.close()

        if not genericsettings.verbose:
            warnings.simplefilter("module")
            # warnings.simplefilter('ignore')

        # get directory name if outputdir is a archive file
        algfolder = findfiles.get_output_directory_subfolder(args[0])
        outputdir = os.path.join(outputdir, algfolder)

        print ("Post-processing (1): will generate output " + "data in folder %s" % outputdir)
        print "  this might take several minutes."

        filelist = list()
        for i in args:
            i = i.strip()
            if os.path.isdir(i):
                filelist.extend(findfiles.main(i, genericsettings.verbose))
            elif os.path.isfile(i):
                filelist.append(i)
            else:
                txt = "Input file or folder %s could not be found." % i
                print txt
                raise Usage(txt)
        dsList = DataSetList(filelist, genericsettings.verbose)

        if not dsList:
            raise Usage("Nothing to do: post-processing stopped.")

        if genericsettings.isNoisy and not genericsettings.isNoiseFree:
            dsList = dsList.dictByNoise().get("nzall", DataSetList())
        if genericsettings.isNoiseFree and not genericsettings.isNoisy:
            dsList = dsList.dictByNoise().get("noiselessall", DataSetList())

        # compute maxfuneval values
        dict_max_fun_evals = {}
        for ds in dsList:
            dict_max_fun_evals[ds.dim] = np.max((dict_max_fun_evals.setdefault(ds.dim, 0), float(np.max(ds.maxevals))))

        from bbob_pproc import config

        config.target_values(genericsettings.isExpensive, dict_max_fun_evals)
        config.config(dsList.isBiobjective())

        if genericsettings.verbose:
            for i in dsList:
                if dict((j, i.instancenumbers.count(j)) for j in set(i.instancenumbers)) != inset.instancesOfInterest:
                    warnings.warn(
                        "The data of %s do not list " % (i) + "the correct instances " + "of function F%d." % (i.funcId)
                    )

        dictAlg = dsList.dictByAlg()

        if len(dictAlg) > 1:
            warnings.warn("Data with multiple algId %s " % str(dictAlg.keys()) + "will be processed together.")
            # TODO: in this case, all is well as long as for a given problem
            # (given dimension and function) there is a single instance of
            # DataSet associated. If there are more than one, the first one only
            # will be considered... which is probably not what one would expect.
            # TODO: put some errors where this case would be a problem.
            # raise Usage?

        if genericsettings.isFig or genericsettings.isTab or genericsettings.isRLDistr or genericsettings.isLogLoss:
            if not os.path.exists(outputdir):
                os.makedirs(outputdir)
                if genericsettings.verbose:
                    print "Folder %s was created." % (outputdir)

        if genericsettings.isPickled:
            dsList.pickle(verbose=genericsettings.verbose)

        if genericsettings.isConv:
            ppconverrorbars.main(dictAlg, outputdir, genericsettings.verbose)

        if genericsettings.isFig:
            print "Scaling figures...",
            sys.stdout.flush()
            # ERT/dim vs dim.
            plt.rc("axes", **inset.rcaxeslarger)
            plt.rc("xtick", **inset.rcticklarger)
            plt.rc("ytick", **inset.rcticklarger)
            plt.rc("font", **inset.rcfontlarger)
            plt.rc("legend", **inset.rclegendlarger)
            plt.rc("pdf", fonttype=42)
            ppfigdim.main(dsList, ppfigdim.values_of_interest, outputdir, genericsettings.verbose)
            plt.rcdefaults()
            print_done()

        plt.rc("axes", **inset.rcaxes)
        plt.rc("xtick", **inset.rctick)
        plt.rc("ytick", **inset.rctick)
        plt.rc("font", **inset.rcfont)
        plt.rc("legend", **inset.rclegend)
        plt.rc("pdf", fonttype=42)

        if genericsettings.isTab:
            print "TeX tables...",
            sys.stdout.flush()
            dictNoise = dsList.dictByNoise()
            for noise, sliceNoise in dictNoise.iteritems():
                pptable.main(sliceNoise, inset.tabDimsOfInterest, outputdir, noise, genericsettings.verbose)
            print_done()

        if genericsettings.isRLDistr:
            print "ECDF graphs...",
            sys.stdout.flush()
            dictNoise = dsList.dictByNoise()
            if len(dictNoise) > 1:
                warnings.warn(
                    "Data for functions from both the noisy and "
                    "non-noisy testbeds have been found. Their "
                    'results will be mixed in the "all functions" '
                    "ECDF figures."
                )
            dictDim = dsList.dictByDim()
            for dim in inset.rldDimsOfInterest:
                try:
                    sliceDim = dictDim[dim]
                except KeyError:
                    continue

                pprldistr.main(sliceDim, True, outputdir, "all", genericsettings.verbose)
                dictNoise = sliceDim.dictByNoise()
                for noise, sliceNoise in dictNoise.iteritems():
                    pprldistr.main(sliceNoise, True, outputdir, "%s" % noise, genericsettings.verbose)
                dictFG = sliceDim.dictByFuncGroup()
                for fGroup, sliceFuncGroup in dictFG.items():
                    pprldistr.main(sliceFuncGroup, True, outputdir, "%s" % fGroup, genericsettings.verbose)

                pprldistr.fmax = None  # Resetting the max final value
                pprldistr.evalfmax = None  # Resetting the max #fevalsfactor

            if (
                genericsettings.isRldOnSingleFcts
            ):  # copy-paste from above, here for each function instead of function groups
                # ECDFs for each function
                pprldmany.all_single_functions(dictAlg, None, outputdir, genericsettings.verbose)
            print_done()

        if genericsettings.isLogLoss:
            print "ERT loss ratio figures and tables...",
            sys.stdout.flush()
            for ng, sliceNoise in dsList.dictByNoise().iteritems():
                if ng == "noiselessall":
                    testbed = "noiseless"
                elif ng == "nzall":
                    testbed = "noisy"
                txt = "Please input crafting effort value " + "for %s testbed:\n  CrE = " % testbed
                CrE = genericsettings.inputCrE
                while CrE is None:
                    try:
                        CrE = float(raw_input(txt))
                    except (SyntaxError, NameError, ValueError):
                        print "Float value required."
                dictDim = sliceNoise.dictByDim()
                for d in inset.rldDimsOfInterest:
                    try:
                        sliceDim = dictDim[d]
                    except KeyError:
                        continue
                    info = "%s" % ng
                    pplogloss.main(sliceDim, CrE, True, outputdir, info, verbose=genericsettings.verbose)
                    pplogloss.generateTable(sliceDim, CrE, outputdir, info, verbose=genericsettings.verbose)
                    for fGroup, sliceFuncGroup in sliceDim.dictByFuncGroup().iteritems():
                        info = "%s" % fGroup
                        pplogloss.main(sliceFuncGroup, CrE, True, outputdir, info, verbose=genericsettings.verbose)
                    pplogloss.evalfmax = None  # Resetting the max #fevalsfactor

            print_done()

        latex_commands_file = os.path.join(outputdir.split(os.sep)[0], "bbob_pproc_commands.tex")
        html_file = os.path.join(outputdir, genericsettings.single_algorithm_file_name + ".html")
        prepend_to_file(
            latex_commands_file, ["\\providecommand{\\bbobloglosstablecaption}[1]{", pplogloss.table_caption, "}"]
        )
        prepend_to_file(
            latex_commands_file, ["\\providecommand{\\bbobloglossfigurecaption}[1]{", pplogloss.figure_caption, "}"]
        )
        prepend_to_file(
            latex_commands_file,
            [
                "\\providecommand{\\bbobpprldistrlegend}[1]{",
                pprldistr.caption_single(
                    np.max([val / dim for dim, val in dict_max_fun_evals.iteritems()])
                ),  # depends on the config setting, should depend on maxfevals
                "}",
            ],
        )
        replace_in_file(
            html_file,
            r"TOBEREPLACED",
            "D, ".join([str(i) for i in pprldistr.single_runlength_factors[:6]]) + "D,&hellip;",
        )
        prepend_to_file(
            latex_commands_file, ["\\providecommand{\\bbobppfigdimlegend}[1]{", ppfigdim.scaling_figure_caption(), "}"]
        )
        prepend_to_file(latex_commands_file, ["\\providecommand{\\bbobpptablecaption}[1]{", pptable.table_caption, "}"])
        prepend_to_file(latex_commands_file, ["\\providecommand{\\algfolder}{" + algfolder + "/}"])
        prepend_to_file(
            latex_commands_file,
            [
                "\\providecommand{\\algname}{"
                + (str_to_latex(strip_pathname1(args[0])) if len(args) == 1 else str_to_latex(dsList[0].algId))
                + "{}}"
            ],
        )
        if genericsettings.isFig or genericsettings.isTab or genericsettings.isRLDistr or genericsettings.isLogLoss:
            print "Output data written to folder %s" % outputdir

        plt.rcdefaults()
示例#3
0
def main(argv=None):
    r"""Routine for post-processing COCO data from two algorithms.

    Provided with some data, this routine outputs figure and TeX files
    in a folder needed for the compilation of the provided LaTeX templates
    for comparing two algorithms (``*cmp.tex`` or ``*2*.tex``).
    
    The used template file needs to be edited so that the command
    ``\bbobdatapath`` points to the output folder created by this routine.

    The output files will contain performance tables, performance
    scaling figures and empirical cumulative distribution figures. On
    subsequent executions, new files will be added to the output folder,
    overwriting existing older files in the process.

    Keyword arguments:

    *argv* -- list of strings containing options and arguments. If not
    given, sys.argv is accessed.

    *argv* must list folders containing BBOB data files. Each of these
    folders should correspond to the data of ONE algorithm.

    Furthermore, argv can begin with, in any order, facultative option
    flags listed below.

        -h, --help
            displays this message.
        -v, --verbose
            verbose mode, prints out operations.
        -o OUTPUTDIR, --output-dir=OUTPUTDIR
            changes the default output directory (:file:`ppdata`) to
            :file:`OUTPUTDIR`
        --noise-free, --noisy
            processes only part of the data.
        --settings=SETTING
            changes the style of the output figures and tables. At the
            moment only the only differences are in the colors of the
            output figures. SETTING can be either "grayscale", "color"
            or "black-white". The default setting is "color".
        --fig-only, --rld-only, --tab-only, --sca-only
            these options can be used to output respectively the ERT
            graphs figures, run length distribution figures or the
            comparison tables scatter plot figures only. Any combination
            of these options results in no output.
        --conv 
            if this option is chosen, additionally convergence
            plots for each function and algorithm are generated.
        --rld-single-fcts
            generate also runlength distribution figures for each
            single function.
        --expensive
            runlength-based f-target values and fixed display limits,
            useful with comparatively small budgets. By default the
            setting is based on the budget used in the data.
        --not-expensive
            expensive setting off. 
        --svg
            generate also the svg figures which are used in html files 

    Exceptions raised:

    *Usage* -- Gives back a usage message.

    Examples:

    * Calling the rungeneric2.py interface from the command line::

        $ python bbob_pproc/rungeneric2.py -v Alg0-baseline Alg1-of-interest

      will post-process the data from folders :file:`Alg0-baseline` and
      :file:`Alg1-of-interest`, the former containing data for the
      reference algorithm (zero-th) and the latter data for the
      algorithm of concern (first). The results will be output in the
      default output folder. The ``-v`` option adds verbosity.

    * From the python interpreter (requires that the path to this
      package is in python search path)::

        >> import bbob_pproc as bb
        >> bb.rungeneric2.main('-o outputfolder PSO DEPSO'.split())

    This will execute the post-processing on the data found in folder
    :file:`PSO` and :file:`DEPSO`. The ``-o`` option changes the output
    folder from the default to :file:`outputfolder`.

    """

    if argv is None:
        argv = sys.argv[1:]
        # The zero-th input argument which is the name of the calling script is
        # disregarded.

    global ftarget
    try:

        try:
            opts, args = getopt.getopt(argv, genericsettings.shortoptlist,
                                       genericsettings.longoptlist)
        except getopt.error, msg:
            raise Usage(msg)

        if not (args):
            usage()
            sys.exit()

        #Process options
        outputdir = genericsettings.outputdir
        for o, a in opts:
            if o in ("-v", "--verbose"):
                genericsettings.verbose = True
            elif o in ("-h", "--help"):
                usage()
                sys.exit()
            elif o in ("-o", "--output-dir"):
                outputdir = a
            elif o == "--fig-only":
                genericsettings.isRLDistr = False
                genericsettings.isTab = False
                genericsettings.isScatter = False
            elif o == "--rld-only":
                genericsettings.isFig = False
                genericsettings.isTab = False
                genericsettings.isScatter = False
            elif o == "--tab-only":
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
                genericsettings.isScatter = False
            elif o == "--sca-only":
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
                genericsettings.isTab = False
            elif o == "--noisy":
                genericsettings.isNoisy = True
            elif o == "--noise-free":
                genericsettings.isNoiseFree = True
            elif o == "--settings":
                genericsettings.inputsettings = a
            elif o == "--conv":
                genericsettings.isConv = True
            elif o == "--rld-single-fcts":
                genericsettings.isRldOnSingleFcts = True
            elif o == "--runlength-based":
                genericsettings.runlength_based_targets = True
            elif o == "--expensive":
                genericsettings.isExpensive = True  # comprises runlength-based
            elif o == "--not-expensive":
                genericsettings.isExpensive = False
            elif o == "--svg":
                genericsettings.generate_svg_files = True
            elif o == "--los-only":
                warnings.warn(
                    "option --los-only will have no effect with rungeneric2.py"
                )
            elif o == "--crafting-effort=":
                warnings.warn(
                    "option --crafting-effort will have no effect with rungeneric2.py"
                )
            elif o in ("-p", "--pickle"):
                warnings.warn(
                    "option --pickle will have no effect with rungeneric2.py")
            else:
                assert False, "unhandled option"

        # from bbob_pproc import bbob2010 as inset # input settings
        if genericsettings.inputsettings == "color":
            from bbob_pproc import genericsettings as inset  # input settings
            config.config()
        elif genericsettings.inputsettings == "grayscale":  # probably very much obsolete
            from bbob_pproc import grayscalesettings as inset  # input settings
        elif genericsettings.inputsettings == "black-white":  # probably very much obsolete
            from bbob_pproc import bwsettings as inset  # input settings
        else:
            txt = ('Settings: %s is not an appropriate ' %
                   genericsettings.inputsettings +
                   'argument for input flag "--settings".')
            raise Usage(txt)

        if (not genericsettings.verbose):
            warnings.simplefilter('module')
            warnings.simplefilter('ignore')

        print("Post-processing will generate comparison " +
              "data in folder %s" % outputdir)
        print "  this might take several minutes."

        dsList, sortedAlgs, dictAlg = processInputArgs(
            args, verbose=genericsettings.verbose)

        if 1 < 3 and len(sortedAlgs) != 2:
            raise ValueError(
                'rungeneric2.py needs exactly two algorithms to compare, found: '
                + str(sortedAlgs) +
                '\n use rungeneric.py (or rungenericmany.py) to compare more algorithms. '
            )

        if not dsList:
            sys.exit()

        for i in dictAlg:
            if genericsettings.isNoisy and not genericsettings.isNoiseFree:
                dictAlg[i] = dictAlg[i].dictByNoise().get(
                    'nzall', DataSetList())
            if genericsettings.isNoiseFree and not genericsettings.isNoisy:
                dictAlg[i] = dictAlg[i].dictByNoise().get(
                    'noiselessall', DataSetList())

        for i in dsList:
            if i.dim not in genericsettings.dimensions_to_display:
                continue

            if (dict((j, i.instancenumbers.count(j))
                     for j in set(i.instancenumbers)) <
                    inset.instancesOfInterest):
                warnings.warn('The data of %s do not list ' % (i) +
                              'the correct instances ' + 'of function F%d.' %
                              (i.funcId))

        if len(sortedAlgs) < 2:
            raise Usage('Expect data from two different algorithms, could ' +
                        'only find one.')
        elif len(sortedAlgs) > 2:
            warnings.warn('Data from folders: %s ' % (sortedAlgs) +
                          'were found, the first two will be processed.')

        # Group by algorithm
        dsList0 = dictAlg[sortedAlgs[0]]
        if not dsList0:
            raise Usage('Could not find data for algorithm %s.' %
                        (sortedAlgs[0]))

        dsList1 = dictAlg[sortedAlgs[1]]
        if not dsList1:
            raise Usage('Could not find data for algorithm %s.' %
                        (sortedAlgs[0]))

        # get the name of each algorithm from the input arguments
        tmppath0, alg0name = os.path.split(sortedAlgs[0].rstrip(os.sep))
        tmppath1, alg1name = os.path.split(sortedAlgs[1].rstrip(os.sep))

        for i in dsList0:
            i.algId = alg0name
        for i in dsList1:
            i.algId = alg1name

        # compute maxfuneval values
        dict_max_fun_evals1 = {}
        dict_max_fun_evals2 = {}
        for ds in dsList0:
            dict_max_fun_evals1[ds.dim] = np.max(
                (dict_max_fun_evals1.setdefault(ds.dim, 0),
                 float(np.max(ds.maxevals))))
        for ds in dsList1:
            dict_max_fun_evals2[ds.dim] = np.max(
                (dict_max_fun_evals2.setdefault(ds.dim, 0),
                 float(np.max(ds.maxevals))))
        config.target_values(
            genericsettings.isExpensive, {
                1:
                min([
                    max([
                        val / dim
                        for dim, val in dict_max_fun_evals1.iteritems()
                    ]),
                    max([
                        val / dim
                        for dim, val in dict_max_fun_evals2.iteritems()
                    ])
                ])
            })
        config.config()

        ######################### Post-processing #############################
        if genericsettings.isFig or genericsettings.isRLDistr or genericsettings.isTab or genericsettings.isScatter:
            if not os.path.exists(outputdir):
                os.mkdir(outputdir)
                if genericsettings.verbose:
                    print 'Folder %s was created.' % (outputdir)

            # prepend the algorithm name command to the tex-command file
            abc = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
            lines = []
            for i, alg in enumerate(args):
                lines.append('\\providecommand{\\algorithm' + abc[i] + '}{' +
                             str_to_latex(strip_pathname1(alg)) + '}')
            prepend_to_file(
                os.path.join(outputdir,
                             'bbob_pproc_commands.tex'), lines, 1000,
                'bbob_proc_commands.tex truncated, consider removing the file before the text run'
            )

        # Check whether both input arguments list noisy and noise-free data
        dictFN0 = dsList0.dictByNoise()
        dictFN1 = dsList1.dictByNoise()
        k0 = set(dictFN0.keys())
        k1 = set(dictFN1.keys())
        symdiff = k1 ^ k0  # symmetric difference
        if symdiff:
            tmpdict = {}
            for i, noisegrp in enumerate(symdiff):
                if noisegrp == 'nzall':
                    tmp = 'noisy'
                elif noisegrp == 'noiselessall':
                    tmp = 'noiseless'

                if dictFN0.has_key(noisegrp):
                    tmp2 = sortedAlgs[0]
                elif dictFN1.has_key(noisegrp):
                    tmp2 = sortedAlgs[1]

                tmpdict.setdefault(tmp2, []).append(tmp)

            txt = []
            for i, j in tmpdict.iteritems():
                txt.append('Only input folder %s lists %s data.' %
                           (i, ' and '.join(j)))
            raise Usage('Data Mismatch: \n  ' + ' '.join(txt) +
                        '\nTry using --noise-free or --noisy flags.')

        if genericsettings.isFig:
            plt.rc("axes", **inset.rcaxeslarger)
            plt.rc("xtick", **inset.rcticklarger)
            plt.rc("ytick", **inset.rcticklarger)
            plt.rc("font", **inset.rcfontlarger)
            plt.rc("legend", **inset.rclegendlarger)
            plt.rc('pdf', fonttype=42)
            ppfig2.main(dsList0, dsList1, ppfig2_ftarget, outputdir,
                        genericsettings.verbose)
            print "log ERT1/ERT0 vs target function values done."

        plt.rc("axes", **inset.rcaxes)
        plt.rc("xtick", **inset.rctick)
        plt.rc("ytick", **inset.rctick)
        plt.rc("font", **inset.rcfont)
        plt.rc("legend", **inset.rclegend)
        plt.rc('pdf', fonttype=42)

        if genericsettings.isRLDistr:
            if len(dictFN0) > 1 or len(dictFN1) > 1:
                warnings.warn('Data for functions from both the noisy and ' +
                              'non-noisy testbeds have been found. Their ' +
                              'results will be mixed in the "all functions" ' +
                              'ECDF figures.')
            dictDim0 = dsList0.dictByDim()
            dictDim1 = dsList1.dictByDim()

            # ECDFs of ERT ratios
            for dim in set(dictDim0.keys()) & set(dictDim1.keys()):
                if dim in inset.rldDimsOfInterest:
                    # ECDF for all functions altogether
                    try:
                        pprldistr2.main(dictDim0[dim], dictDim1[dim], dim,
                                        inset.rldValsOfInterest, outputdir,
                                        '%02dD_all' % dim,
                                        genericsettings.verbose)
                    except KeyError:
                        warnings.warn('Could not find some data in %d-D.' %
                                      (dim))
                        continue

                    # ECDFs per function groups
                    dictFG0 = dictDim0[dim].dictByFuncGroup()
                    dictFG1 = dictDim1[dim].dictByFuncGroup()

                    for fGroup in set(dictFG0.keys()) & set(dictFG1.keys()):
                        pprldistr2.main(dictFG1[fGroup], dictFG0[fGroup], dim,
                                        inset.rldValsOfInterest, outputdir,
                                        '%02dD_%s' % (dim, fGroup),
                                        genericsettings.verbose)

                    # ECDFs per noise groups
                    dictFN0 = dictDim0[dim].dictByNoise()
                    dictFN1 = dictDim1[dim].dictByNoise()

                    for fGroup in set(dictFN0.keys()) & set(dictFN1.keys()):
                        pprldistr2.main(dictFN1[fGroup], dictFN0[fGroup], dim,
                                        inset.rldValsOfInterest, outputdir,
                                        '%02dD_%s' % (dim, fGroup),
                                        genericsettings.verbose)

            prepend_to_file(
                os.path.join(outputdir, 'bbob_pproc_commands.tex'),
                [
                    '\\providecommand{\\bbobpprldistrlegendtwo}[1]{',
                    pprldistr.caption_two(
                    ),  # depends on the config setting, should depend on maxfevals
                    '}'
                ])

            print "ECDF runlength ratio graphs done."

            for dim in set(dictDim0.keys()) & set(dictDim1.keys()):
                pprldistr.fmax = None  #Resetting the max final value
                pprldistr.evalfmax = None  #Resetting the max #fevalsfactor
                # ECDFs of all functions altogether
                if dim in inset.rldDimsOfInterest:
                    try:
                        pprldistr.comp(
                            dictDim1[dim],
                            dictDim0[dim],
                            inset.
                            rldValsOfInterest,  # TODO: let rldVals... possibly be RL-based targets
                            True,
                            outputdir,
                            'all',
                            genericsettings.verbose)
                    except KeyError:
                        warnings.warn('Could not find some data in %d-D.' %
                                      (dim))
                        continue

                    # ECDFs per function groups
                    dictFG0 = dictDim0[dim].dictByFuncGroup()
                    dictFG1 = dictDim1[dim].dictByFuncGroup()

                    for fGroup in set(dictFG0.keys()) & set(dictFG1.keys()):
                        pprldistr.comp(dictFG1[fGroup], dictFG0[fGroup],
                                       inset.rldValsOfInterest, True,
                                       outputdir, '%s' % fGroup,
                                       genericsettings.verbose)

                    # ECDFs per noise groups
                    dictFN0 = dictDim0[dim].dictByNoise()
                    dictFN1 = dictDim1[dim].dictByNoise()
                    for fGroup in set(dictFN0.keys()) & set(dictFN1.keys()):
                        pprldistr.comp(dictFN1[fGroup], dictFN0[fGroup],
                                       inset.rldValsOfInterest, True,
                                       outputdir, '%s' % fGroup,
                                       genericsettings.verbose)

            if genericsettings.isRldOnSingleFcts:  # copy-paste from above, here for each function instead of function groups
                # ECDFs for each function
                pprldmany.all_single_functions(dictAlg, sortedAlgs, outputdir,
                                               genericsettings.verbose)
            print "ECDF runlength graphs done."

        if genericsettings.isConv:
            ppconverrorbars.main(dictAlg, outputdir, genericsettings.verbose)

        if genericsettings.isScatter:
            if genericsettings.runlength_based_targets:
                ppscatter.targets = ppscatter.runlength_based_targets
            ppscatter.main(dsList1,
                           dsList0,
                           outputdir,
                           verbose=genericsettings.verbose)
            prepend_to_file(os.path.join(outputdir, 'bbob_pproc_commands.tex'),
                            [
                                '\\providecommand{\\bbobppscatterlegend}[1]{',
                                ppscatter.figure_caption(), '}'
                            ])

            replace_in_file(
                os.path.join(outputdir,
                             genericsettings.two_algorithm_file_name +
                             '.html'), '##bbobppscatterlegend##',
                ppscatter.figure_caption_html())

            print "Scatter plots done."

        if genericsettings.isTab:
            dictNG0 = dsList0.dictByNoise()
            dictNG1 = dsList1.dictByNoise()

            for nGroup in set(dictNG0.keys()) & set(dictNG1.keys()):
                # split table in as many as necessary
                dictFunc0 = dictNG0[nGroup].dictByFunc()
                dictFunc1 = dictNG1[nGroup].dictByFunc()
                funcs = list(set(dictFunc0.keys()) & set(dictFunc1.keys()))
                if len(funcs) > 24:
                    funcs.sort()
                    nbgroups = int(numpy.ceil(len(funcs) / 24.))

                    def split_seq(seq, nbgroups):
                        newseq = []
                        splitsize = 1.0 / nbgroups * len(seq)
                        for i in range(nbgroups):
                            newseq.append(
                                seq[int(round(i * splitsize)
                                        ):int(round((i + 1) * splitsize))])
                        return newseq

                    groups = split_seq(funcs, nbgroups)
                    # merge
                    group0 = []
                    group1 = []
                    for i, g in enumerate(groups):
                        tmp0 = DataSetList()
                        tmp1 = DataSetList()
                        for f in g:
                            tmp0.extend(dictFunc0[f])
                            tmp1.extend(dictFunc1[f])
                        group0.append(tmp0)
                        group1.append(tmp1)
                    for i, g in enumerate(zip(group0, group1)):
                        pptable2.main(g[0], g[1], inset.tabDimsOfInterest,
                                      outputdir, '%s%d' % (nGroup, i),
                                      genericsettings.verbose)
                else:
                    if 11 < 3:  # future handling:
                        dictFunc0 = dsList0.dictByFunc()
                        dictFunc1 = dsList1.dictByFunc()
                        funcs = list(
                            set(dictFunc0.keys()) & set(dictFunc1.keys()))
                        funcs.sort()


#                        nbgroups = int(numpy.ceil(len(funcs)/testbedsettings.numberOfFunctions))
#                        pptable2.main(dsList0, dsList1,
#                                      testbedsettings.tabDimsOfInterest, outputdir,
#                                      '%s' % (testbedsettings.testbedshortname), genericsettings.verbose)
                    else:
                        pptable2.main(dictNG0[nGroup], dictNG1[nGroup],
                                      inset.tabDimsOfInterest, outputdir,
                                      '%s' % (nGroup), genericsettings.verbose)

            if isinstance(pptable2.targetsOfInterest,
                          pproc.RunlengthBasedTargetValues):
                prepend_to_file(
                    os.path.join(outputdir, 'bbob_pproc_commands.tex'), [
                        '\\providecommand{\\bbobpptablestwolegend}[1]{',
                        pptable2.table_caption_expensive, '}'
                    ])
            else:
                prepend_to_file(
                    os.path.join(outputdir, 'bbob_pproc_commands.tex'), [
                        '\\providecommand{\\bbobpptablestwolegend}[1]{',
                        pptable2.table_caption, '}'
                    ])

            htmlFileName = os.path.join(
                outputdir, genericsettings.two_algorithm_file_name + '.html')
            key = '##bbobpptablestwolegendexpensive##' if isinstance(
                pptable2.targetsOfInterest, pproc.RunlengthBasedTargetValues
            ) else '##bbobpptablestwolegend##'
            replace_in_file(htmlFileName, '##bbobpptablestwolegend##',
                            htmldesc.getValue(key))

            alg0 = set(i[0] for i in dsList0.dictByAlg().keys()).pop().replace(
                genericsettings.extraction_folder_prefix, '')[0:3]
            alg1 = set(i[0] for i in dsList1.dictByAlg().keys()).pop().replace(
                genericsettings.extraction_folder_prefix, '')[0:3]
            replace_in_file(htmlFileName, 'algorithmAshort', alg0)
            replace_in_file(htmlFileName, 'algorithmBshort', alg1)

            for i, alg in enumerate(args):
                replace_in_file(htmlFileName, 'algorithm' + abc[i],
                                str_to_latex(strip_pathname1(alg)))

            print "Tables done."

        if genericsettings.isScaleUp:
            plt.rc("axes", labelsize=20, titlesize=24)
            plt.rc("xtick", labelsize=20)
            plt.rc("ytick", labelsize=20)
            plt.rc("font", size=20)
            plt.rc("legend", fontsize=20)
            plt.rc('pdf', fonttype=42)
            if genericsettings.runlength_based_targets:
                ftarget = RunlengthBasedTargetValues([
                    target_runlength
                ])  # TODO: make this more variable but also consistent
            ppfigs.main(dictAlg, genericsettings.two_algorithm_file_name,
                        sortedAlgs, ftarget, outputdir,
                        genericsettings.verbose)
            plt.rcdefaults()
            print "Scaling figures done."

        if genericsettings.isFig or genericsettings.isRLDistr or genericsettings.isTab or genericsettings.isScatter or genericsettings.isScaleUp:
            print "Output data written to folder %s" % outputdir

        plt.rcdefaults()
示例#4
0
def main(argv=None):
    r"""Post-processing COCO data of a single algorithm.

    Provided with some data, this routine outputs figure and TeX files
    in a folder needed for the compilation of the provided LaTeX templates
    for one algorithm (``*article.tex`` or ``*1*.tex``).
    The used template file needs to be edited so that the commands
    ``\bbobdatapath`` and ``\algfolder`` point to the output folder created
    by this routine.

    These output files will contain performance tables, performance
    scaling figures and empirical cumulative distribution figures. On
    subsequent executions, new files will be added to the output folder,
    overwriting existing older files in the process.

    Keyword arguments:

    *argv* -- list of strings containing options and arguments. If not
    given, sys.argv is accessed.

    *argv* should list either names of :file:`info` files or folders
    containing :file:`info` files. argv can also contain post-processed
    :file:`pickle` files generated by this routine. Furthermore, *argv*
    can begin with, in any order, facultative option flags listed below.

        -h, --help
            displays this message.
        -v, --verbose
            verbose mode, prints out all operations.
        -p, --pickle
            generates pickle post processed data files.
        -o OUTPUTDIR, --output-dir=OUTPUTDIR
            changes the default output directory (:file:`ppdata`) to
            :file:`OUTPUTDIR`.
        --crafting-effort=VALUE
            sets the crafting effort to VALUE (float). Otherwise the
            default value of 0. will be used.
        --noise-free, --noisy
            processes only part of the data.
        --settings=SETTINGS
            changes the style of the output figures and tables. At the
            moment the only differences are  in the colors of the output
            figures. SETTINGS can be either "grayscale", "color" or
            "black-white". The default setting is "color".
        --tab-only, --fig-only, --rld-only, --los-only
            these options can be used to output respectively the TeX
            tables, convergence and ERTs graphs figures, run length
            distribution figures, ERT loss ratio figures only. A
            combination of any two of these options results in no
            output.
        --conv
            if this option is chosen, additionally convergence plots
            for each function and algorithm are generated.
        --rld-single-fcts
            generate also runlength distribution figures for each
            single function.
        --expensive
            runlength-based f-target values and fixed display limits,
            useful with comparatively small budgets. By default the
            setting is based on the budget used in the data.
        --not-expensive
            expensive setting off. 
        --svg
            generate also the svg figures which are used in html files 
        --runlength-based
            runlength-based f-target values, such that the
            "level of difficulty" is similar for all functions. 

    Exceptions raised:

    *Usage* -- Gives back a usage message.

    Examples:

    * Calling the rungeneric1.py interface from the command line::

        $ python bbob_pproc/rungeneric1.py -v experiment1

      will post-process the folder experiment1 and all its containing
      data, base on the .info files found in the folder. The result will
      appear in the default output folder. The -v option adds verbosity. ::

        $ python bbob_pproc/rungeneric1.py -o exp2 experiment2/*.info

      This will execute the post-processing on the info files found in
      :file:`experiment2`. The result will be located in the alternative
      location :file:`exp2`.

    * Loading this package and calling the main from the command line
      (requires that the path to this package is in python search path)::

        $ python -m bbob_pproc.rungeneric1 -h

      This will print out this help message.

    * From the python interpreter (requires that the path to this
      package is in python search path)::

        >> import bbob_pproc as bb
        >> bb.rungeneric1.main('-o outputfolder folder1'.split())

      This will execute the post-processing on the index files found in
      :file:`folder1`. The ``-o`` option changes the output folder from
      the default to :file:`outputfolder`.

    """

    if argv is None:
        argv = sys.argv[1:]
        # The zero-th input argument which is the name of the calling script is
        # disregarded.

    if 1 < 3:
        opts, args = getopt.getopt(argv, genericsettings.shortoptlist, genericsettings.longoptlist)
        if 11 < 3:
            try:
                opts, args = getopt.getopt(argv, genericsettings.shortoptlist, genericsettings.longoptlist)
            except getopt.error, msg:
                raise Usage(msg)

        if not (args) and not '--help' in argv and not 'h' in argv:
            print 'not enough input arguments given'
            print 'cave: the following options also need an argument:'
            print [o for o in genericsettings.longoptlist if o[-1] == '=']
            print 'options given:'
            print opts
            print 'try --help for help'
            sys.exit()

        # Process options
        outputdir = genericsettings.outputdir
        for o, a in opts:
            if o in ("-v", "--verbose"):
                genericsettings.verbose = True
            elif o in ("-h", "--help"):
                usage()
                sys.exit()
            elif o in ("-p", "--pickle"):
                genericsettings.isPickled = True
            elif o in ("-o", "--output-dir"):
                outputdir = a
            elif o == "--noisy":
                genericsettings.isNoisy = True
            elif o == "--noise-free":
                genericsettings.isNoiseFree = True
            # The next 4 are for testing purpose
            elif o == "--tab-only":
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
                genericsettings.isLogLoss = False
            elif o == "--fig-only":
                genericsettings.isTab = False
                genericsettings.isRLDistr = False
                genericsettings.isLogLoss = False
            elif o == "--rld-only":
                genericsettings.isTab = False
                genericsettings.isFig = False
                genericsettings.isLogLoss = False
            elif o == "--los-only":
                genericsettings.isTab = False
                genericsettings.isFig = False
                genericsettings.isRLDistr = False
            elif o == "--crafting-effort":
                try:
                    genericsettings.inputCrE = float(a)
                except ValueError:
                    raise Usage('Expect a valid float for flag crafting-effort.')
            elif o == "--settings":
                genericsettings.inputsettings = a
            elif o == "--conv":
                genericsettings.isConv = True
            elif o == "--rld-single-fcts":
                genericsettings.isRldOnSingleFcts = True
            elif o == "--runlength-based":
                genericsettings.runlength_based_targets = True
            elif o == "--expensive":
                genericsettings.isExpensive = True  # comprises runlength-based
            elif o == "--not-expensive":
                genericsettings.isExpensive = False
            elif o == "--svg":
                genericsettings.generate_svg_files = True
            elif o == "--sca-only":
                warnings.warn("option --sca-only will have no effect with rungeneric1.py")
            else:
                assert False, "unhandled option"

        # from bbob_pproc import bbob2010 as inset # input settings
        if genericsettings.inputsettings == "color":
            from bbob_pproc import genericsettings as inset  # input settings
        elif genericsettings.inputsettings == "grayscale":
            from bbob_pproc import grayscalesettings as inset  # input settings
        elif genericsettings.inputsettings == "black-white":
            from bbob_pproc import bwsettings as inset  # input settings
        else:
            txt = ('Settings: %s is not an appropriate ' % genericsettings.inputsettings
                   + 'argument for input flag "--settings".')
            raise Usage(txt)
        
        if 11 < 3:
            from bbob_pproc import config  # input settings
            config.config()
            import imp
            # import testbedsettings as testbedsettings # input settings
            try:
                fp, pathname, description = imp.find_module("testbedsettings")
                testbedsettings = imp.load_module("testbedsettings", fp, pathname, description)
            finally:
                fp.close()

        if (not genericsettings.verbose):
            warnings.simplefilter('module')
            # warnings.simplefilter('ignore')            

        #get directory name if outputdir is a archive file
        algfolder = findfiles.get_output_directory_subfolder(args[0])
        outputdir = os.path.join(outputdir, algfolder)
        
        print ("Post-processing (1): will generate output " + 
               "data in folder %s" % outputdir)
        print "  this might take several minutes."

        filelist = list()
        for i in args:
            i = i.strip()
            if os.path.isdir(i):
                filelist.extend(findfiles.main(i, genericsettings.verbose))
            elif os.path.isfile(i):
                filelist.append(i)
            else:
                txt = 'Input file or folder %s could not be found.' % i
                print txt
                raise Usage(txt)
        dsList = DataSetList(filelist, genericsettings.verbose)
        
        if not dsList:
            raise Usage("Nothing to do: post-processing stopped.")

        if genericsettings.isNoisy and not genericsettings.isNoiseFree:
            dsList = dsList.dictByNoise().get('nzall', DataSetList())
        if genericsettings.isNoiseFree and not genericsettings.isNoisy:
            dsList = dsList.dictByNoise().get('noiselessall', DataSetList())

        # compute maxfuneval values
        dict_max_fun_evals = {}
        for ds in dsList:
            dict_max_fun_evals[ds.dim] = np.max((dict_max_fun_evals.setdefault(ds.dim, 0), float(np.max(ds.maxevals))))
        
        from bbob_pproc import config
        config.target_values(genericsettings.isExpensive, dict_max_fun_evals)
        config.config()

        if (genericsettings.verbose):
            for i in dsList:
                if (dict((j, i.instancenumbers.count(j)) for j in set(i.instancenumbers)) != 
                    inset.instancesOfInterest):
                    warnings.warn('The data of %s do not list ' % (i) + 
                                  'the correct instances ' + 
                                  'of function F%d.' % (i.funcId))

        dictAlg = dsList.dictByAlg()

        if len(dictAlg) > 1:
            warnings.warn('Data with multiple algId %s ' % str(dictAlg.keys()) +
                          'will be processed together.')
            # TODO: in this case, all is well as long as for a given problem
            # (given dimension and function) there is a single instance of
            # DataSet associated. If there are more than one, the first one only
            # will be considered... which is probably not what one would expect.
            # TODO: put some errors where this case would be a problem.
            # raise Usage?

        if genericsettings.isFig or genericsettings.isTab or genericsettings.isRLDistr or genericsettings.isLogLoss:
            if not os.path.exists(outputdir):
                os.makedirs(outputdir)
                if genericsettings.verbose:
                    print 'Folder %s was created.' % (outputdir)

        if genericsettings.isPickled:
            dsList.pickle(verbose=genericsettings.verbose)

        if genericsettings.isConv:
            ppconverrorbars.main(dictAlg, outputdir, genericsettings.verbose)

        if genericsettings.isFig:
            print "Scaling figures...",
            sys.stdout.flush()
            # ERT/dim vs dim.
            plt.rc("axes", **inset.rcaxeslarger)
            plt.rc("xtick", **inset.rcticklarger)
            plt.rc("ytick", **inset.rcticklarger)
            plt.rc("font", **inset.rcfontlarger)
            plt.rc("legend", **inset.rclegendlarger)
            plt.rc('pdf', fonttype = 42)
            ppfigdim.main(dsList, ppfigdim.values_of_interest,
                          outputdir, genericsettings.verbose)
            plt.rcdefaults()
            print_done()

        plt.rc("axes", **inset.rcaxes)
        plt.rc("xtick", **inset.rctick)
        plt.rc("ytick", **inset.rctick)
        plt.rc("font", **inset.rcfont)
        plt.rc("legend", **inset.rclegend)
        plt.rc('pdf', fonttype = 42)

        if genericsettings.isTab:
            print "TeX tables...",
            sys.stdout.flush()
            dictNoise = dsList.dictByNoise()
            for noise, sliceNoise in dictNoise.iteritems():
                pptable.main(sliceNoise, inset.tabDimsOfInterest,
                             outputdir, noise, genericsettings.verbose)
            print_done()

        if genericsettings.isRLDistr:
            print "ECDF graphs...",
            sys.stdout.flush()
            dictNoise = dsList.dictByNoise()
            if len(dictNoise) > 1:
                warnings.warn('Data for functions from both the noisy and '
                              'non-noisy testbeds have been found. Their '
                              'results will be mixed in the "all functions" '
                              'ECDF figures.')
            dictDim = dsList.dictByDim()
            for dim in inset.rldDimsOfInterest:
                try:
                    sliceDim = dictDim[dim]
                except KeyError:
                    continue

                pprldistr.main(sliceDim, True,
                               outputdir, 'all', genericsettings.verbose)
                dictNoise = sliceDim.dictByNoise()
                for noise, sliceNoise in dictNoise.iteritems():
                    pprldistr.main(sliceNoise, True,
                                   outputdir,
                                   '%s' % noise, genericsettings.verbose)
                dictFG = sliceDim.dictByFuncGroup()
                for fGroup, sliceFuncGroup in dictFG.items():
                    pprldistr.main(sliceFuncGroup, True,
                                   outputdir,
                                   '%s' % fGroup, genericsettings.verbose)

                pprldistr.fmax = None  # Resetting the max final value
                pprldistr.evalfmax = None  # Resetting the max #fevalsfactor

            if genericsettings.isRldOnSingleFcts: # copy-paste from above, here for each function instead of function groups
                # ECDFs for each function
                pprldmany.all_single_functions(dictAlg, None,
                                               outputdir,
                                               genericsettings.verbose)
            print_done()

        if genericsettings.isLogLoss:
            print "ERT loss ratio figures and tables...",
            sys.stdout.flush()
            for ng, sliceNoise in dsList.dictByNoise().iteritems():
                if ng == 'noiselessall':
                    testbed = 'noiseless'
                elif ng == 'nzall':
                    testbed = 'noisy'
                txt = ("Please input crafting effort value "
                       + "for %s testbed:\n  CrE = " % testbed)
                CrE = genericsettings.inputCrE
                while CrE is None:
                    try:
                        CrE = float(raw_input(txt))
                    except (SyntaxError, NameError, ValueError):
                        print "Float value required."
                dictDim = sliceNoise.dictByDim()
                for d in inset.rldDimsOfInterest:
                    try:
                        sliceDim = dictDim[d]
                    except KeyError:
                        continue
                    info = '%s' % ng
                    pplogloss.main(sliceDim, CrE, True,
                                   outputdir, info,
                                   verbose=genericsettings.verbose)
                    pplogloss.generateTable(sliceDim, CrE,
                                            outputdir, info,
                                            verbose=genericsettings.verbose)
                    for fGroup, sliceFuncGroup in sliceDim.dictByFuncGroup().iteritems():
                        info = '%s' % fGroup
                        pplogloss.main(sliceFuncGroup, CrE, True,
                                       outputdir, info,
                                       verbose=genericsettings.verbose)
                    pplogloss.evalfmax = None  # Resetting the max #fevalsfactor

            print_done()

        latex_commands_file = os.path.join(outputdir.split(os.sep)[0], 'bbob_pproc_commands.tex')
        html_file = os.path.join(outputdir, genericsettings.single_algorithm_file_name + '.html')
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\bbobloglosstablecaption}[1]{', 
                         pplogloss.table_caption, '}'])
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\bbobloglossfigurecaption}[1]{', 
                         pplogloss.figure_caption, '}'])
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\bbobpprldistrlegend}[1]{',
                         pprldistr.caption_single(np.max([ val / dim for dim, val in dict_max_fun_evals.iteritems()])),  # depends on the config setting, should depend on maxfevals
                         '}'])
        replace_in_file(html_file, r'TOBEREPLACED', 'D, '.join([str(i) for i in pprldistr.single_runlength_factors[:6]]) + 'D,&hellip;')
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\bbobppfigdimlegend}[1]{',
                         ppfigdim.scaling_figure_caption(),
                         '}'])
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\bbobpptablecaption}[1]{',
                         pptable.table_caption,
                         '}'])
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\algfolder}{' + algfolder + '/}'])
        prepend_to_file(latex_commands_file,
                        ['\\providecommand{\\algname}{' + 
                         (str_to_latex(strip_pathname1(args[0])) if len(args) == 1 else str_to_latex(dsList[0].algId)) + '{}}'])
        if genericsettings.isFig or genericsettings.isTab or genericsettings.isRLDistr or genericsettings.isLogLoss:
            print "Output data written to folder %s" % outputdir

        plt.rcdefaults()