def beautifyFVD(isStoringXMax=False, ylabel=True): """Formats the figure of the run length distribution. This function is to be used with :py:func:`plotFVDistr` :param bool isStoringMaxF: if set to True, the first call :py:func:`beautifyFVD` sets the global :py:data:`fmax` and all subsequent call will have the same maximum xlim :param bool ylabel: if True, y-axis will be labelled. """ a = plt.gca() a.set_xscale('log') if isStoringXMax: global fmax else: fmax = None if not fmax: xmin, fmax = plt.xlim() plt.xlim(1e-8, fmax) # 1e-8 was 1. # axisHandle.invert_xaxis() a.set_xlabel('log10 of Df') # / Dftarget if ylabel: a.set_ylabel('proportion of trials') logxticks(limits=plt.xlim()) beautifyECDF() if not ylabel: a.set_yticklabels(())
def beautify(): """Format the figure of the run length distribution. Used in conjunction with plot method (obsolete/outdated, see functions ``beautifyFVD`` and ``beautifyRLD``). """ # raise NotImplementedError('this implementation is obsolete') plt.subplot(121) axisHandle = plt.gca() axisHandle.set_xscale('log') axisHandle.set_xlabel('log10 of FEvals / DIM') axisHandle.set_ylabel('proportion of trials') # Grid options logxticks() beautifyECDF() plt.subplot(122) axisHandle = plt.gca() axisHandle.set_xscale('log') xmin, fmax = plt.xlim() plt.xlim(1., fmax) axisHandle.set_xlabel('log10 of Df / Dftarget') beautifyECDF() logxticks() axisHandle.set_yticklabels(()) plt.gcf().set_size_inches(16.35, 6.175)
def beautifyFVD(isStoringXMax = False, ylabel = True): """Formats the figure of the run length distribution. This function is to be used with :py:func:`plotFVDistr` :param bool isStoringMaxF: if set to True, the first call :py:func:`beautifyFVD` sets the global :py:data:`fmax` and all subsequent call will have the same maximum xlim :param bool ylabel: if True, y-axis will be labelled. """ a = plt.gca() a.set_xscale('log') if isStoringXMax: global fmax else: fmax = None if not fmax: xmin, fmax = plt.xlim() plt.xlim(1e-8, fmax) # 1e-8 was 1. # axisHandle.invert_xaxis() a.set_xlabel('log10 of Df') # / Dftarget if ylabel: a.set_ylabel('proportion of trials') logxticks(limits = plt.xlim()) beautifyECDF() if not ylabel: a.set_yticklabels(())
def beautify(): """Customize figure presentation.""" #plt.xscale('log') # Does not work with matplotlib 0.91.2 a = plt.gca() a.set_xscale('log') #Tick label handling plt.xlabel('log10 of (ERT / ERTref)') plt.ylabel('Proportion of functions') logxticks() beautifyECDF()
def beautify(): """Customize figure presentation.""" #plt.xscale('log') # Does not work with matplotlib 0.91.2 a = plt.gca() a.set_xscale('log') #Tick label handling plt.xlim(xmin=1e-0) plt.xlabel('log10 of (# f-evals / dimension)') plt.ylabel('Proportion of function+target pairs') ppfig.logxticks() pprldistr.beautifyECDF()
def beautifyRLD(xlimit_max = None): """Format and save the figure of the run length distribution. After calling this function, changing the boundaries of the figure will not update the ticks and tick labels. """ a = plt.gca() a.set_xscale('log') a.set_xlabel('log10 of FEvals / DIM') a.set_ylabel('proportion of trials') logxticks() if xlimit_max: plt.xlim(xmax = xlimit_max ** 1.0) # was 1.05 plt.xlim(xmin = runlen_xlimits_min) plt.text(plt.xlim()[0], plt.ylim()[0], single_target_values.short_info, fontsize = 14) beautifyECDF()
def beautify(): """Customize figure presentation.""" # plt.xscale('log') # Does not work with matplotlib 0.91.2 a = plt.gca() a.set_xscale("log") # Tick label handling plt.xlim(xmin=1e-0) global divide_by_dimension if divide_by_dimension: plt.xlabel("log10 of (# f-evals / dimension)", fontsize=label_fontsize) else: plt.xlabel("log10 of # f-evals", fontsize=label_fontsize) plt.ylabel("Proportion of function+target pairs", fontsize=label_fontsize) ppfig.logxticks() pprldistr.beautifyECDF()
def beautifyRLD(xlimit_max=None): """Format and save the figure of the run length distribution. After calling this function, changing the boundaries of the figure will not update the ticks and tick labels. """ a = plt.gca() a.set_xscale('log') a.set_xlabel('log10 of FEvals / DIM') a.set_ylabel('proportion of trials') logxticks() if xlimit_max: plt.xlim(xmax=xlimit_max ** 1.0) # was 1.05 plt.xlim(xmin=runlen_xlimits_min) plt.text(plt.xlim()[0], plt.ylim()[0], single_target_values.short_info, fontsize=14) beautifyECDF()