def gp_rapp():
inDir, outDir = getWorkDirs()<EOL>yields = {}<EOL>for infile in os.listdir(inDir):<EOL><INDENT>energy = re.compile('<STR_LIT>').search(infile).group()<EOL>medium = np.loadtxt(open(os.path.join(inDir, infile), '<STR_LIT:rb>'))<EOL>getMassRangesSums(energy, medium, yields)<EOL><DEDENT>data = dict( <EOL>(k, np.array(sorted(v)))<EOL>for k, v in yields.items()<EOL>)<EOL>for k in data: data[k][:,<NUM_LIT:1>] /= data[k][-<NUM_LIT:1>,<NUM_LIT:1>] <EOL>nSets = len(data)<EOL>make_plot(<EOL>data = [ data[k][:-<NUM_LIT:1>] for k in data ],<EOL>properties = [<EOL>'<STR_LIT>' % default_colors[i]<EOL>for i in range(nSets)<EOL>],<EOL>titles = list(data.keys()), <EOL>name = os.path.join(outDir, '<STR_LIT>'),<EOL>xlabel = '<STR_LIT>', ylabel = '<STR_LIT>',<EOL>lmargin = <NUM_LIT:0.1>, key = ['<STR_LIT:left>'], yr = [<NUM_LIT:0.1>, <NUM_LIT>]<EOL>)<EOL>return '<STR_LIT>'<EOL>
rho in-medium ratios by Rapp (based on protected data)