Commit a80382ca by ulrich_y

 # vim: foldmethod=marker ## Init{{{ # We begin by loading pyMule from pymule import * # and point it to the correct folder setup(folder='ee2ee0504191/out.tar.bz2', obs='8') ##########################################################################}}} ## Load data{{{ # Load the LO with the correct factors of alpha and conv lo = scaleset(mergefks(sigma('ee2ee0')), alpha**2*conv) # Load the NLO, either with plot or without #nlo = scaleset(mergefks(sigma('ee2eeF'), sigma('ee2eeR')), alpha**3*conv) figxi, nlo = mergefkswithplot( [[sigma('ee2eeF')], [sigma('ee2eeR')]], scale=alpha**3*conv ) figxi.savefig("xicut.pdf") ##########################################################################}}} ## Make plots{{{ ### Simple plots{{{ # Let's start with a quick LO plot. Because we already have a figure # open (the $\xi_c$-study), we first need a new one figure() errorband(lo['thcms']) # Next, we look at the tK factor printnumber(dividenumbers(nlo['value'], lo['value'])) # Now we can make a K-plot figK, (ax1, ax2) = kplot( {'lo': mergebins(lo['thcms'], 4), 'nlo': mergebins(nlo['thcms'], 4)}, labelx='$\\theta_{CMS}$', labelsigma='$\\D\\sigma/\\D\\theta_{CMS}\ / \ {\\rm \upmu b}$', legend={ 'lo': '$\\sigma^{(0)}$', 'nlo': '$\\sigma^{(1)}$' }, legendopts={'what': 'u', 'loc': 'upper center', 'ncol': 2} ) ax1.set_yscale('log') figK.savefig("kfac.pdf") ###########################################################}}} ### bin-wise $\chi^2${{{ # Let's also look at the bin-wise $\chi^2$ of the FKS merge. For this # we have to do the FKS merge manually. Let's begin by loading the # relevant data. dataF = sigma('ee2eeF') dataR = sigma('ee2eeR') # Next, we need to know the FKS parameters used. These are the keys of # the sigma result. We will assume they are the same for R and F, # otherwise we would have to use an intersection routine such as # pymule.loader.multiintersect xicuts = dataF.keys() # Now we can add the thcms plot of ee2eeF and ee2eeF for each $\xi_c$ # and merge the results. pl, chi = mergeplots([ addplots( sigma('ee2eeF')[xic]['thcms'], sigma('ee2eeR')[xic]['thcms'] ) for xic in xicuts], True ) figure() scatter(chi[:, 0], chi[:, 1]) xlabel('$\\theta_{CMS}$') ylabel('$\\chi^2$') ###########################################################}}} ##########################################################################}}}