def plot_crosssection_ratio(args=None,
obs='zpt',
pdf='NNPDF31_nnlo_as_0118',
mc='NNLO'):
plots = []
invert_3Dhists(args, obs + '_17Jul2018_total.root',
PLOTSFOLDER + '/uncertainty', BUFFERFOLDER + '/uncertainty')
data_source = [
BUFFERFOLDER + '/uncertainty/' + obs + '_17Jul2018_total_binned.root'
]
if 'LO' in mc:
invert_3Dhists(args, obs + '_' + mc + '_' + pdf + '.root',
PLOTSFOLDER + '/theory', BUFFERFOLDER + '/theory')
mc_source = [
BUFFERFOLDER + '/theory/' + obs + '_' + mc + '_' + pdf +
'_binned.root'
]
else:
invert_3Dhists(args, obs + '_' + mc + '.root', PLOTSFOLDER,
BUFFERFOLDER)
mc_source = [BUFFERFOLDER + '/' + obs + '_' + mc + '_binned.root']
invert_3Dhists(args, obs + '_17Jul2018_systematic.root',
PLOTSFOLDER + '/uncertainty', BUFFERFOLDER + '/uncertainty')
unc_source = [
BUFFERFOLDER + '/uncertainty/' + obs +
'_17Jul2018_systematic_binned.root'
]
filelist_binned = data_source + mc_source + unc_source
ybins = [0.0, 0.5, 1.0, 1.5, 2.0, 2.5]
ylist = [((xb, yb), (xs, ys)) for (xs, ys) in zip(ybins[:-1], ybins[1:])
for (xb, yb) in zip(ybins[:-1], ybins[1:]) if xb + xs < 2.5]
markerlist = [
'^', '1', 'd', '+', '*', '<', '2', 'o', 'x', '>', '3', 's', 'v', '4',
'p'
]
colorlist = [
'red', 'salmon', 'crimson', 'violet', 'brown', 'blue', 'cyan',
'royalblue', 'teal', 'orange', 'gold', 'yellow', 'green', 'lime',
'purple'
]
namelist = [
'_yb{}_ys{}'.format(int(2 * yboost[0]), int(2 * ystar[0]))
for (yboost, ystar) in ylist
]
d = ({
'www':
'crosssections_vs_' + mc,
'files': [filelist_binned],
'folders': [''],
'x_expressions': [(obs + '_total' + name, 'gen' + obs + '_asym' + name,
obs + '_systematic' + name) for name in namelist],
'nicks':
[('unf' + name, 'gen' + name, 'unc' + name) for name in namelist],
'x_errors': [0],
'y_errors': [0],
'x_log':
True,
'title':
LABELDICT[mc] if mc in ['amc', 'hpp', 'mad'] else mc,
'marker_fill_styles': ['none'],
'markeredgewidth':
2.5,
'markersize':
12,
'labelsize':
40,
'labels': [('bin' + x, 'bin' + x) for x in namelist],
'filename':
obs,
'x_label':
obs,
'x_ticks': [30, 60, 100, 200, 400, 1000]
if obs == 'zpt' else [0.5, 1.0, 2.0, 4.0, 10, 30],
'x_lims': [25, 1000] if obs == 'zpt' else [0.4, 50],
'legend':
None,
'figsize': [10, 16],
'lumis': [35.9],
'texts': [
r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$" if CMSLABEL else "",
r"$35.9\\mathrm{\\,fb}^{-1} \\hspace{0.2}$(13TeV)"
],
'texts_size': [30, 25],
'texts_y': [1.03, 1.035],
'filename':
obs + '_ratio',
'analysis_modules': ['Ratio', 'AddHistograms'],
'ratio_numerator_nicks':
[('unf' + name, 'gen' + name, 'unf' + name, 'unc' + name)
for name in namelist],
'ratio_denominator_nicks':
[('unf' + name, 'gen' + name, 'gen' + name, 'gen' + name)
for name in namelist],
'ratio_result_nicks':
[('unity' + name, 'scale' + name, 'ratio' + name, 'syst' + name)
for name in namelist],
'add_nicks':
[('unity' + name + ' ratio' + name, 'unity' + name + ' scale' + name,
'unity' + name + ' ratio' + name, 'unity' + name + ' syst' + name)
for name in namelist],
'add_result_nicks': [('stacked1' + name, 'stacked2' + name,
'stacked3' + name, 'stacked4' + name)
for name in namelist],
'add_no_error_scale': [True],
'zorder':
len(namelist) * [2] + len(namelist) * [1] + len(namelist) * [3] +
len(namelist) * [4],
'step':
3 * len(namelist) * [1] + len(namelist) * [0],
'line_styles': [''],
'line_widths': [1.5],
'labels': ['bin' + x for x in namelist],
'markers':
len(namelist) * ['fill'] + 2 * len(namelist) * ['errorband'] +
markerlist[:len(namelist)],
'hatch':
len(namelist) * ['//'] + len(namelist) * [''] + len(namelist) * [''] +
len(namelist) * [''],
'colors':
len(namelist) * ['gray'] + len(namelist) * ['grey'] +
colorlist[:len(namelist)] + len(namelist) * ['black'],
'nicks_whitelist': ['stacked4', 'stacked3', 'stacked2', 'stacked1'],
'alphas':
len(namelist) * [1] + 3 * len(namelist) * [0.707],
'subplot_nicks': ['dummy'],
'lines_styles': ['-', ':', ':'],
'y_label':
'Ratio to theory',
'y_lims': [0.5, 15.5],
'add_scale_factors': [
(str(len(ylist) - x - 1) + ' 1', str(len(ylist) - x - 1) + ' 1',
str(len(ylist) - x - 1) + ' 1', str(len(ylist) - x - 1) + ' 1')
for x in xrange(len(ylist))
],
'lines': [(0.5 + x, 0.75 + x, 1.25 + x)
for x in xrange(len(namelist))],
'y_ticks': [(0.75 + x, 1.0 + x, 1.25 + x)
for x in xrange(len(namelist))],
'texts_x': [0.03, (0.65 if obs == 'zpt' else 0.66)],
})
plots.append(d)
return plots
def plot_crosssection_overview(args=None,
obs='zpt',
pdf='NNPDF31_nnlo_as_0118',
mc='NNLO'):
plots = []
invert_3Dhists(args, obs + '_17Jul2018_by_toy0.root',
PLOTSFOLDER + '/unfolded', BUFFERFOLDER + '/unfolded')
data_source = [
BUFFERFOLDER + '/unfolded/' + obs + '_17Jul2018_by_toy0_binned.root'
]
if 'LO' in mc:
invert_3Dhists(args, obs + '_' + mc + '_' + pdf + '.root',
PLOTSFOLDER + '/theory', BUFFERFOLDER + '/theory')
mc_source = [
BUFFERFOLDER + '/theory/' + obs + '_' + mc + '_' + pdf +
'_binned.root'
]
else:
invert_3Dhists(args, obs + '_' + mc + '.root', PLOTSFOLDER,
BUFFERFOLDER)
mc_source = [BUFFERFOLDER + '/' + obs + '_' + mc + '_binned.root']
filelist_binned = data_source + mc_source
ybins = [0.0, 0.5, 1.0, 1.5, 2.0, 2.5]
ylist = [((xb, yb), (xs, ys)) for (xs, ys) in zip(ybins[:-1], ybins[1:])
for (xb, yb) in zip(ybins[:-1], ybins[1:]) if xb + xs < 2.5]
markerlist = [
'^', '1', 'd', '+', '*', '<', '2', 'o', 'x', '>', '3', 's', 'v', '4',
'p'
]
colorlist = [
'red', 'salmon', 'crimson', 'violet', 'brown', 'blue', 'cyan',
'royalblue', 'teal', 'orange', 'gold', 'yellow', 'green', 'lime',
'purple'
]
scalelist = [
1e20, 1e19, 1e18, 1e17, 1e16, 1e13, 1e12, 1e11, 1e10, 1e7, 1e6, 1e5,
1e2, 1e1, 1e0
]
namelist = [
'_yb{}_ys{}'.format(int(2 * yboost[0]), int(2 * ystar[0]))
for (yboost, ystar) in ylist
]
d = ({
'www':
'crosssections_vs_' + mc,
'files': [filelist_binned],
'folders': [''],
'x_expressions':
[('unfolded' + obs + name, 'gen' + obs + name) for name in namelist],
'nicks': [('unf' + name, 'gen' + name) for name in namelist],
'analysis_modules': ['ScaleHistograms', 'NormalizeByBinWidth'],
'scale_nicks': [('unf' + name, 'gen' + name) for name in namelist],
'scales':
[(1e0 / 35.9 / 1000 * x, 1e0 / 35.9 / 1000 * x) for x in scalelist],
'x_errors': [0],
'x_log':
True,
'y_log':
True,
'title':
LABELDICT[mc] if mc in ['amc', 'hpp', 'mad'] else mc,
'y_errors': [0],
'step': [0, 1],
'line_styles': ['', '-'],
'line_widths': [3],
'zorder': ['unf', 'gen'],
'y_lims': [1e-5, 1e20] if obs == 'zpt' else [1e-4, 1e22],
'marker_fill_styles': ['none'],
'markeredgewidth':
2.5,
'markersize':
12,
'labelsize':
40,
'markers': [(x, '') for x in markerlist],
'colors': [('black', x) for x in colorlist],
'labels': [('bin' + x, 'bin' + x) for x in namelist],
'filename':
obs,
'x_label':
obs,
'x_ticks': [30, 60, 100, 200, 400, 1000]
if obs == 'zpt' else [0.5, 1.0, 2.0, 4.0, 10, 30],
'legend':
None,
'figsize': [10, 16],
'lumis': [35.9],
'texts': [
r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$" if CMSLABEL else "",
r"$35.9\\mathrm{\\,fb}^{-1} \\hspace{0.2}$(13TeV)"
],
'texts_size': [30, 25],
'texts_x': [0.03, (0.64 if obs == 'zpt' else 0.65)],
'texts_y': [1.03, 1.035],
})
if obs == 'zpt':
d['y_label'] = r'$ \\frac{d^3\\mathit{\\sigma}}{d\\mathit{p}_T^Z dy_b dy^*}/(\\frac{pb}{GeV})$'
elif obs == 'phistareta':
d['y_label'] = r'$ \\frac{d^3\\mathit{\\sigma}}{d\\phi^{*}_{\\eta} dy_b dy^*}/pb$'
plots.append(d)
return plots
def plot_datamc(args=None, obs='zpt', data='17Jul2018', mc='mad'):
plots = []
data_source = obs + '_' + data + '.root'
mc_source = obs + '_' + mc + '.root'
bkg_list = ['TT', 'WZ', 'ZZ', 'TW', 'WW']
bkg_source = [obs + '_' + bkg + '.root' for bkg in bkg_list]
filelist = [data_source, mc_source] + bkg_source
filelist_binned = []
for x in filelist:
invert_3Dhists(args, x, PLOTSFOLDER, BUFFERFOLDER)
filelist_binned.append(BUFFERFOLDER + '/' +
x.replace('.root', '_binned.root'))
d0 = ({
'files':
filelist_binned,
'folders': [''],
'nicks': ['Data', 'DY'] + bkg_list,
'sum_nicks': ['DY ' + ' '.join(bkg_list)],
'analysis_modules':
['SumOfHistograms', 'NormalizeByBinWidth', 'Ratio'],
'sum_result_nicks': ['sim'],
'ratio_numerator_nicks': ['Data'],
'ratio_denominator_nicks': ['sim'],
'ratio_result_nicks': ['ratio'],
'ratio_denominator_no_errors':
False,
'stacks': ['data', 'mc'] + len(bkg_list) * ['mc'] + ['ratio'],
'filename':
obs,
'x_errors': [1],
'x_ticks': [30, 60, 100, 200, 400, 1000]
if obs == 'zpt' else [0.5, 1.0, 2.0, 4.0, 10, 30],
'x_log':
True,
'x_label':
obs,
'y_log':
True,
'y_lims': [1e-2, 1e5] if obs == 'zpt' else [1e0, 1e7],
'y_label':
'Events per binsize',
'nicks_blacklist': ['sim'],
'y_subplot_label':
'Data/Sim',
'y_subplot_lims': [0.75, 1.25],
'texts_size': [20],
'texts_y': [1.07, 0.97],
'labelsize':
25,
'lumis': [35.9],
'energies': [13],
})
for ybmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
for ysmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
if not ybmin + ysmin > 2:
namestring = '_yb{}_ys{}'.format(int(2 * ybmin),
int(2 * ysmin))
d = deepcopy(d0)
d.update({
'x_expressions': [obs + namestring],
'www':
'datamc_' + data + '_vs_' + mc + '/datamc' + namestring,
'texts': [
r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$"
if CMSLABEL else "", r"${}<y_b<{}$,${}<y*<{}$".format(
ybmin, ybmin + 0.5, ysmin, ysmin + 0.5)
],
})
if ysmin > 1.0:
d['y_subplot_lims'] = [0.9, 2.3]
elif ysmin > 0.5:
d['y_subplot_lims'] = [0.8, 1.8]
elif ybmin > 1.0:
d['y_subplot_lims'] = [0.5, 1.5]
plots.append(d)
return plots
def plot_crosssections(args=None, obs='zpt', pdf='', mclist=['mad', 'amc']):
plots = []
invert_3Dhists(args, obs + '_17Jul2018_total.root',
PLOTSFOLDER + '/uncertainty', BUFFERFOLDER + '/uncertainty')
data_source = [
BUFFERFOLDER + '/uncertainty/' + obs + '_17Jul2018_total_binned.root'
]
mc_source = []
for mc in mclist:
if 'LO' in mc:
invert_3Dhists(args, obs + '_' + mc + '_' + pdf + '.root',
PLOTSFOLDER + '/theory', BUFFERFOLDER + '/theory')
mc_source.append(BUFFERFOLDER + '/theory/' + obs + '_' + mc + '_' +
pdf + '_binned.root')
else:
invert_3Dhists(args, obs + '_' + mc + '.root', PLOTSFOLDER,
BUFFERFOLDER)
mc_source.append(BUFFERFOLDER + '/' + obs + '_' + mc +
'_binned.root')
invert_3Dhists(args, obs + '_17Jul2018_systematic.root',
PLOTSFOLDER + '/uncertainty', BUFFERFOLDER + '/uncertainty')
unc_source = [
BUFFERFOLDER + '/uncertainty/' + obs +
'_17Jul2018_systematic_binned.root'
]
filelist_binned = data_source + mc_source + unc_source
for ybmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
for ysmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
if not ybmin + ysmin > 2:
namestring = '_yb{}_ys{}'.format(int(2 * ybmin),
int(2 * ysmin))
d = ({
'www':
'crosssections_' + '_'.join(mclist) +
('_' + pdf if not pdf == '' else pdf) + '/xsec' +
namestring,
'files':
filelist_binned,
'folders': [''],
'x_expressions': [obs + '_total' + namestring] +
len(mclist) * ['gen' + obs + '_asym' + namestring] +
[obs + '_systematic' + namestring],
'x_label':
obs,
'x_log':
True,
'x_ticks': [30, 60, 100, 200, 400, 1000]
if obs == 'zpt' else [0.5, 1.0, 2.0, 4.0, 10, 30],
'x_lims': [25, 1000] if obs == 'zpt' else [0.4, 50],
'x_errors': [1],
'lumis': [35.9],
'energies': [13],
'nicks': ['data'] + mclist + ['uncertainty'],
'analysis_modules':
['ScaleHistograms', 'NormalizeByBinWidth', 'Ratio'],
'scale_nicks': ['data', 'uncertainty'] + mclist,
'scales': [
1e0 / 35.9 / 1000 *
(5941.0 / 6225.42 if x == 'amc' else 1)
for x in ['data', 'uncertainty'] + mclist
],
'ratio_numerator_nicks':
['uncertainty', 'data'] + 2 * mclist,
'ratio_denominator_nicks':
(2 + 2 * len(mclist)) * ['data'],
'ratio_result_nicks':
['ratio' + x for x in ['syst', 'total'] + mclist] +
['unc' + x for x in mclist],
'nicks_blacklist': ['uncertainty'],
'filename':
obs,
'markers':
['.'] + [MARKERDICT[x]
for x in mclist] + ['fill', 'errorband'] +
[MARKERDICT[x]
for x in mclist] + len(mclist) * ['errorband'],
'colors': ['black'] + [COLORDICT[x] for x in mclist] +
['gray', 'grey'] + 2 * [COLORDICT[x] for x in mclist],
'hatch': (1 + len(mclist)) * [None] + ['//', None] +
2 * len(mclist) * [None],
'alphas': (1 + len(mclist)) * [1] + [1, 0.707] +
2 * len(mclist) * [0.3],
'zorder':
[5] + len(mclist) * [1] + [3, 2] + 2 * len(mclist) * [4],
'step': [True],
'line_styles': [''],
'y_log':
True,
'y_lims': [1e-6, 1e1] if obs == 'zpt' else [1e-5, 1e3],
'y_errors':
False,
'y_subplot_lims': [0.75, 1.25],
'y_label':
'Events per binwidth',
'y_subplot_label':
'Ratio to Data', #'Sim/Data' if 'amc' in mclist else 'Theory/Data',
'subplot_legend':
'lower left',
'subplot_nicks': ['ratio', 'unc'],
'subplot_fraction':
50,
'labels': ['Data'] + [LABELDICT[x] for x in mclist] +
['Syst. Unc', 'Syst.+Stat. Unc'] + 2 * len(mclist) * [''],
'labelsize':
25,
'texts_size': [20],
'texts_x': [0.02],
'texts': [
r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$"
if CMSLABEL else "", r"${}<y_b<{}$,${}<y*<{}$".format(
ybmin, ybmin + 0.5, ysmin, ysmin + 0.5)
],
'texts_y': [1.10, 0.97],
})
if obs == 'zpt':
d['y_label'] = r'$ \\frac{d^3\\mathit{\\sigma}}{d\\mathit{p}_T^Z dy_b dy^*}/(\\frac{pb}{GeV})$'
elif obs == 'phistareta':
d['y_label'] = r'$ \\frac{d^3\\mathit{\\sigma}}{d\\phi^{*}_{\\eta} dy_b dy^*}/pb$'
if ysmin > 1.5:
d['y_subplot_lims'] = [0.0, 1.5]
d['vertical_lines'] = [250 if obs == 'zpt' else 5]
elif ysmin + ybmin > 1.0:
d['y_subplot_lims'] = [0.5, 1.5]
plots.append(d)
return plots
def plot_uncertainties(args=None, obs='zpt'):
plots = []
l_var = ['stat', 'systematic', 'lumi', 'bkg', 'eff', 'unf', 'jec', 'jer']
varlist = l_var
invert_3Dhists(args, obs + '_17Jul2018_systematic.root',
PLOTSFOLDER + '/uncertainty', BUFFERFOLDER + '/uncertainty')
filelist_binned = [
BUFFERFOLDER + '/uncertainty/' + obs +
'_17Jul2018_systematic_binned.root'
]
for ybmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
for ysmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
if not ybmin + ysmin > 2:
namestring = '_yb{}_ys{}'.format(int(2 * ybmin),
int(2 * ysmin))
d = ({
'files':
filelist_binned,
'folders': [''],
'nicks':
varlist,
'x_expressions':
['uncertainty_' + var + namestring for var in varlist],
'filename':
obs,
'labels': [
'Statistical', 'Total systematic', 'Luminosity',
'Background', 'Efficiency', 'Unfolding', 'JEC', 'JER'
],
'alphas': [0.5],
'x_log':
True,
'x_label':
obs,
'x_ticks': [30, 60, 100, 200, 400, 1000]
if obs == 'zpt' else [0.5, 1.0, 2.0, 4.0, 10, 30],
'x_lims': [25, 1000] if obs == 'zpt' else [0.4, 50],
'y_errors':
False,
'y_lims': [0.0, 0.1],
'y_label':
"Relative Uncertainty",
'www':
'uncertainties/uncertainties' + namestring,
'step': [True],
'legend':
None,
'line_styles': ['-'],
'markers': ['fill', 'o', 'v', '^', '>', '<', 's', 'D'],
'colors': [
'grey', 'black', 'red', 'blue', 'green', 'purple',
'orange', 'turquoise'
],
'texts': [
r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$"
if CMSLABEL else "", r"${}<y_b<{}$,${}<y*<{}$".format(
ybmin, ybmin + 0.5, ysmin, ysmin + 0.5)
],
'texts_size': [20],
'texts_y': [1.05, 0.97],
'labelsize':
25,
})
if ysmin > 1.5:
d['y_lims'] = [0, 0.29]
d['vertical_lines'] = [250 if obs == 'zpt' else 5]
elif ysmin > 1.0:
d['y_lims'] = [0, 0.2]
elif ysmin > 0.5:
d['y_lims'] = [0, 0.15]
elif ybmin + ysmin > 1:
d['y_lims'] = [0, 0.17]
plots.append(d)
return plots
def plot_unfolding_closure(args=None, obs='zpt', mc='mad'):
varlist = 2 * ['stats_' + mc]
plots = []
px, py = ROOT.Double(0), ROOT.Double(0)
ybinedges = [0, 5, 9, 12, 14, 0]
if 'toy' in mc:
varlist = [
'stats_toy', 'model_toy', 'Robs', 'Ryj', 'Ryz', 'switch', 'F', 'A'
]
filelist_binned = []
filelist_chi2 = []
for sample in MCLIST:
f = ROOT.TFile(
PLOTSFOLDER + '/chi2/' + obs + '_' + sample + '_by_' + mc +
'.root', 'READ')
h = f.Get('chi2_' + sample + '_by_' + mc)
filelist_chi2.append(deepcopy(h))
f.Close()
invert_3Dhists(args, obs + '_' + sample + '.root', PLOTSFOLDER,
BUFFERFOLDER)
filelist_binned.append(BUFFERFOLDER + '/' + obs + '_' + sample +
'_binned.root')
invert_3Dhists(args, obs + '_' + sample + '_by_' + mc + '.root',
PLOTSFOLDER + '/unfolded', BUFFERFOLDER + '/unfolded')
filelist_binned.append(BUFFERFOLDER + '/unfolded/' + obs + '_' +
sample + '_by_' + mc + '_binned.root')
for var in varlist:
invert_3Dhists(args, obs + '_17Jul2018_' + var + '.root',
PLOTSFOLDER + '/uncertainty',
BUFFERFOLDER + '/uncertainty')
filelist_binned.append(BUFFERFOLDER + '/uncertainty/' + obs +
'_17Jul2018_' + var + '_binned.root')
for ybmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
for ysmin in [0.0, 0.5, 1.0, 1.5, 2.0]:
if not ybmin + ysmin > 2:
namestring = '_yb{}_ys{}'.format(int(2 * ybmin),
int(2 * ysmin))
chi2 = []
for i in xrange(len(MCLIST)):
filelist_chi2[i].GetPoint(
ybinedges[int(2 * ysmin)] + int(2 * ybmin), px, py)
chi2.append(1.0 * py)
#calculate_closure_chi2(args,obs,cut,x,mc,match,postfix,int(2*ybmin),int(2*ysmin)))
d = ({
'www':
'unfolding_MC_by_' + mc + '/unfolded' + namestring,
'files':
filelist_binned,
'x_expressions':
len(MCLIST) *
['gen' + obs + namestring, 'unfolded' + obs + namestring] +
['uncertainty_' + x + namestring for x in varlist],
'folders': [''],
'nicks': [(x + 'gen', x + 'unf')
for x in MCLIST] + ['unc_' + x for x in varlist],
'analysis_modules':
['QuadraticSumOfHistograms', 'Ratio', 'SumOfHistograms'],
'quad_sum_nicks': ['unc_' + ' unc_'.join(varlist[1:])],
'quad_sum_result_nicks': ['unc_model'],
'ratio_numerator_nicks':
['unc_model'] + [x + 'unf' for x in MCLIST],
'ratio_denominator_nicks':
['unc_model'] + [x + 'gen' for x in MCLIST],
'ratio_result_nicks':
['unity'] + [x + 'ratio' for x in MCLIST],
'sum_nicks': [
'unity unc_' + varlist[0], 'unity unc_' + varlist[0],
'unity unc_model', 'unity unc_model'
],
'sum_scale_factors': ['1 1', '1 -1', '1 1', '1 -1'],
'sum_result_nicks':
['stats_up', 'stats_down', 'model_up', 'model_down'],
'labels': ["Toy Stat. Unc.", "", "Toy Syst. Unc.", ""] +
[(LABELDICT[x] + ' (chi2/ndf={:.3f})').format(chi2[i])
for (i, x) in list(enumerate(MCLIST))],
'subplot_legend':
'upper left',
'subplot_fraction':
45,
'subplot_nicks': ['up', 'down', 'ratio'],
'y_subplot_label':
'Unfolded/Gen',
'filename':
obs,
'x_label':
obs,
'x_errors':
4 * [0] + len(MCLIST) * [1],
'x_log':
True,
'x_ticks': [30, 60, 100, 200, 400, 1000]
if obs == 'zpt' else [0.5, 1.0, 2.0, 4.0, 10, 30],
'y_label':
'Unfolded/Gen',
'y_lims': [0.9, 1.1],
'y_errors':
4 * [False] + len(MCLIST) * [True],
'y_log':
False,
'step':
2 * [True] + 2 * [True] + len(MCLIST) * [False],
'line_styles':
len(MCLIST) * 3 * [''] + 2 * ['-'] + 2 * ['-'],
'markers':
2 * ['fill'] + 2 * [''] + [MARKERDICT[x] for x in MCLIST],
'colors': ['yellow', 'white', 'black', 'black'] +
[COLORDICT[x] for x in MCLIST],
'nicks_whitelist': ['stats', 'model', 'ratio'],
'nicks_blacklist': ['unity', 'unc'],
'y_subplot_lims': [0.9, 1.1],
'texts': [
r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$"
if CMSLABEL else "", r"${}<y_b<{}$,${}<y*<{}$".format(
ybmin, ybmin + 0.5, ysmin, ysmin + 0.5)
],
'texts_x': [0.03],
'texts_y': [1.07, 0.97],
'texts_size': [20],
'labelsize':
25,
'line_styles':
2 * [''] + 2 * ['-'] + len(MCLIST) * [''],
'subplot_nicks': ['dummy'],
'legend':
'lower left',
})
if not 'toy' in mc:
d['labels'][len(MCLIST)] = LABELDICT[mc] + " Stat. Unc."
#d0['labels'][len(MCLIST)+2] = LABELDICT[mc]+" Syst. Unc."
d['labels'][len(MCLIST) + 1] = " "
d['nicks_blacklist'] += ['model']
d.update({
'nicks_whitelist': ['stats', 'ratio'],
'x_errors':
2 * [0] + len(MCLIST) * [1],
'labels': [LABELDICT[x] + " Stat. Unc.", ""] +
[(LABELDICT[x] + ' (chi2/ndf={:.3f})').format(chi2[i])
for (i, x) in list(enumerate(MCLIST))],
'y_errors':
2 * [False] + len(MCLIST) * [True],
'step':
2 * [True] + len(MCLIST) * [False],
'line_styles':
2 * [''] + len(MCLIST) * [''],
'markers':
2 * ['fill'] + [MARKERDICT[x] for x in MCLIST],
'colors':
['yellow', 'white'] + [COLORDICT[x] for x in MCLIST],
})
if ysmin == 2.0:
d['y_lims'] = [0.5, 1.5]
elif ybmin == 2.0:
d['y_lims'] = [0.75, 1.25]
elif ysmin + ybmin > 1.0:
d['y_lims'] = [0.65, 1.35]
plots.append(d)
return plots