def make_scatter_plots_pls(sig_name, bkg_name):
hname = sig_name
h = histograms[hname]
h.SetMinimum(h.ymin)
h.SetMaximum(h.ymax)
h.Draw()
n = len(h.data)
#
hname = bkg_name
h = histograms[hname]
g = Graph(n) # truncate
data = h.data[:n] # truncate
for i, (xx, yy) in enumerate(data):
g.SetPoint(i, xx, yy)
g.markerstyle = 4
g.markercolor = 'black'
g.Draw("p")
keepalive(gPad.func(), g)
#
hname = sig_name
h = histograms[hname]
g = Graph(n)
data = h.data
for i, (xx, yy) in enumerate(data):
g.SetPoint(i, xx, yy)
g.markerstyle = 4
g.markercolor = 'red'
g.Draw("p")
keepalive(gPad.func(), g)
gPad.Print(options.outdir + hname + ".png")
return
def spread_x( histograms, bin_edges ):
"""
Usually when plotting multiple histograms with same x-values and
similar y-values their markers will overlap. This function spreads
the data points across a bin. It creates a set of graphs with the
same y-values but different x.
@param histograms: list of histograms with same binning
@param bin_edges: the bin edges of the histograms
"""
# construct bins from the bin edges
bins = [( bin_lower, bin_upper ) for bin_lower, bin_upper in izip( bin_edges[:-1], bin_edges[1:] )]
# now get the bin widths
bin_widths = [abs( bin_i[1] - bin_i[0] ) for bin_i in bins]
# number of histograms
number_of_hists = len( histograms )
# and divide the bins into equidistant bits leaving some space to the bin edges
x_locations = []
add_locations = x_locations.append
for bin_lower, width in izip( bin_edges, bin_widths ):
x_step = width / ( 1.0 * number_of_hists + 1 ) # +1 due to spacing to bin edge
add_locations( [bin_lower + n * x_step for n in range( 1, number_of_hists + 1 )] )
# transpose
x_locations = map( list, zip( *x_locations ) )
graphs = []
for histogram, x_coordinates in zip( histograms, x_locations ):
g = Graph( histogram )
for i, ( x, y ) in enumerate( zip( x_coordinates, histogram.y() ) ):
g.SetPoint( i, x, y )
graphs.append( g )
return graphs
def tau_from_L_curve(unfoldingObject):
'''
Get best tau via l curve method
Not tested
'''
lCurve = TGraph()
logTauX = TSpline3()
logTauY = TSpline3()
iBest = unfoldingObject.ScanLcurve(500, 0., 0., lCurve, logTauX, logTauY)
# Additional info, plots
t = Double(0)
x = Double(0)
y = Double(0)
logTauX.GetKnot(iBest, t, x)
logTauY.GetKnot(iBest, t, y)
bestLcurve = Graph(1)
bestLcurve.SetPoint(1, x, y)
lCurve.SetMarkerColor(600)
lCurve.SetMarkerSize(1)
lCurve.SetMarkerStyle(5)
# lCurve.Draw("AP");
bestLcurve.markercolor = 'red'
# bestLcurve.Draw("*");
return unfoldingObject.GetTau()
def roc(ana, category, discr_var):
"""
Calculates the ROC curve
Returns the sorted list of wp and a TGraph
"""
h_template = Hist(1000, 0, 1)
h_sig = ana.tau.get_hist_array({discr_var: h_template}, category=category)
h_sig = h_sig[discr_var]
h_bkg = ana.jet.get_hist_array({discr_var: h_template}, category=category)
h_bkg = h_bkg[discr_var]
roc_gr = Graph(h_sig.GetNbinsX())
roc_list = []
for i in range(1, h_sig.GetNbinsX()):
eff_sig_i = (h_sig.Integral() -
h_sig.Integral(0, i)) / h_sig.Integral()
eff_bkg_i = (h_bkg.Integral() -
h_bkg.Integral(0, i)) / h_bkg.Integral()
rej_bkg_i = 1. / eff_bkg_i if eff_bkg_i != 0 else 0.
roc_list.append(
working_point(h_sig.GetBinLowEdge(i), eff_sig_i, eff_bkg_i))
roc_gr.SetPoint(i, eff_sig_i, rej_bkg_i)
return roc_gr, roc_list
def old_working_points(ana, category, wp_level):
log.info('create the workers')
names = ['loose', 'medium', 'tight']
cuts = [
wp_level + '_is_loose == 1', wp_level + '_is_medium == 1',
wp_level + '_is_tight == 1'
]
workers = [FuncWorker(get_sig_bkg, ana, category, cut) for cut in cuts]
run_pool(workers, n_jobs=-1)
yields = [w.output for w in workers]
log.info('--> Calculate the total yields')
sig_tot = ana.tau.events(category)[1].value
bkg_tot = ana.jet.events(category, weighted=True)[1].value
gr = Graph(len(cuts))
wps = []
for i, (val, yields, name) in enumerate(zip(cuts, yields, names)):
eff_sig = yields[0] / sig_tot
eff_bkg = yields[1] / bkg_tot
rej_bkg = 1. / eff_bkg if eff_bkg != 0 else 0
wps.append(working_point(val, eff_sig, eff_bkg, name=name))
gr.SetPoint(i, eff_sig, rej_bkg)
return gr, wps
def double_profile(tprofile_x, tprofile_y):
"""creates a graph with points whose x and y values and errors are taken from the bins of two profiles with identical binning"""
## Note: underflow and overflow bins are discarded
if len(tprofile_x) != len(tprofile_y):
raise ValueError(
"Cannot build double profile: x and y profiles "
"have different number or bins ({} and {})".format(
len(tprofile_x) - 2,
len(tprofile_y) - 2))
_dp_graph = Graph(len(tprofile_x) - 2,
type='errors') # symmetric errors
_i_point = 0
for _i_bin, (_bin_proxy_x,
_bin_proxy_y) in enumerate(zip(tprofile_x, tprofile_y)):
# disregard overflow/underflow bins
if _i_bin == 0 or _i_bin == len(tprofile_x) - 1:
continue
if _bin_proxy_y.value:
_dp_graph.SetPoint(_i_point, _bin_proxy_x.value,
_bin_proxy_y.value)
_dp_graph.SetPointError(_i_point, _bin_proxy_x.error,
_bin_proxy_y.error)
_i_point += 1
# remove "unfilled" points
while (_dp_graph.GetN() > _i_point):
_dp_graph.RemovePoint(_dp_graph.GetN() - 1)
return _dp_graph
def get_uncertainty_graph(hnom, curve_uncert):
"""
Convert an histogram and a RooCurve
into a TGraphAsymmError
Parameters
----------
hnom: TH1F, TH1D, ...
The histogram of nominal values
curve_uncert: RooCurve
The uncertainty band around the nominal value
TODO: Improve the handling of the underflow and overflow bins
"""
graph = Graph(hnom.GetNbinsX())
for ibin in xrange(1, hnom.GetNbinsX() + 1):
uncerts = []
for ip in xrange(3, curve_uncert.GetN() - 3):
x, y = ROOT.Double(0.), ROOT.Double(0.)
curve_uncert.GetPoint(ip, x, y)
if hnom.GetBinLowEdge(ibin) <= x < hnom.GetBinLowEdge(ibin + 1):
uncerts.append(y)
log.debug('{0}, bin {1}: {2}'.format(hnom.name, ibin, uncerts))
low, high = min(uncerts), max(uncerts)
bin_center = 0.5 * (hnom.GetBinLowEdge(ibin + 1) +
hnom.GetBinLowEdge(ibin))
e_x_low = bin_center - hnom.GetBinLowEdge(ibin)
e_x_high = hnom.GetBinLowEdge(ibin + 1) - bin_center
bin_content = hnom.GetBinContent(ibin)
e_y_low = hnom.GetBinContent(ibin) - low
e_y_high = high - hnom.GetBinContent(ibin)
graph.SetPoint(ibin - 1, bin_center, bin_content)
graph.SetPointError(ibin - 1, e_x_low, e_x_high, e_y_low, e_y_high)
return graph
def grrScale(gr1, scale):
x1 = Double()
x_ = Double()
x1e = Double()
y1 = Double()
y1e = Double()
y = []
ex = []
ey = []
NC = gr1.GetN()
x = [0 for i in range(NC)]
for ii in range(NC):
x1e = gr1.GetErrorX(ii)
y1e = gr1.GetErrorY(ii)
gr1.GetPoint(ii, x_, y1)
x1 = x_ * 1.0
x[ii] = x1
y.append(y1 * scale)
ex.append(x1e)
ey.append(y1e * scale)
gr = Graph(NC)
for x0, y0, x0e, y0e, i in zip(x, y, ex, ey, range(NC)):
gr.SetPoint(i, x0, y0)
gr.SetPointError(i, x0e, x0e, y0e, y0e)
return gr
def remap_x_values(hist, corr_hist):
"""
Map the x values of hist to the y values of map_hist.
In order to do so, it is necessary that the x values of hist are also present as x-values in map_hist.
Parameters
----------
hist : Hist1D
corr_hist : Hist2D
Correlations between the quantity on hist's x-axis (also corr_hist's xaxis) and the new
quantity to plot agains (on corr_hist's y-axis.
Returns
-------
Graph
Graph of the remapped hist. Errors are ??? TODO
"""
hist = asrootpy(hist)
corr_hist = asrootpy(corr_hist)
profx = asrootpy(corr_hist.ProfileX(gen_random_name()))
rt_graph = Graph()
for i, (nch_ref_bin,
counter_bin) in enumerate(zip(profx.bins(), hist.bins())):
rt_graph.SetPoint(i, nch_ref_bin.value, counter_bin.value)
xerr, yerr = nch_ref_bin.error / 2.0, counter_bin.error / 2.0
rt_graph.SetPointError(i, xerr, xerr, yerr, yerr)
return rt_graph
def get_mean_rms(category, var):
gr_mean = Graph(len(SIGNALS_14TEV))
gr_rms = Graph(len(SIGNALS_14TEV))
for ip, signal in enumerate(SIGNALS_14TEV):
with root_open('efficiencies/eff_presel_{0}_v{1}.root'.format(
signal, VERSION)) as fsig:
h_s = fsig[category].Get('h_' + category + '_' + var['name'])
gr_mean.SetPoint(ip, DATASETS[signal]['mu'], h_s.GetMean())
gr_mean.SetPointError(ip, 0, 0, h_s.GetMeanError(),
h_s.GetMeanError())
gr_rms.SetPoint(ip, DATASETS[signal]['mu'], h_s.GetRMS())
gr_rms.SetPointError(ip, 0, 0, h_s.GetRMSError(),
h_s.GetRMSError())
gr_mean.xaxis.title = 'Average Interactions Per Bunch Crossing'
gr_mean.yaxis.title = 'Mean of ' + get_label(var)
gr_rms.xaxis.title = 'Average Interactions Per Bunch Crossing'
gr_rms.yaxis.title = 'RMS of ' + get_label(var)
return gr_mean, gr_rms
def addConstantError(gr1, error, **kwargs):
x_ = Double()
x1e = Double()
y1_ = Double()
y1e = Double()
NC = gr1.GetN()
y2 = [0 for i in range(NC)]
ex = []
ey = []
x = [0 for i in range(NC)]
gr = Graph(NC)
for ii in range(NC):
x1e = gr1.GetErrorX(ii)
y1e = gr1.GetErrorY(ii)
gr1.GetPoint(ii, x_, y1_)
print("{} {} {}".format(i, x_, y1_))
x1 = x_ * 1.0
x[ii] = x1
y1 = y1_ * 1.0
y2[ii] = y1
print("Append y with {}".format(y1))
print(y2)
ex.append(x1e)
if (kwargs.get('rel'), False):
ey.append(math.sqrt(y1e**2 + (error * y1)**2))
print("Old error: {}, New Error: {}".format(
y1e, math.sqrt(y1e**2 + (error * y1)**2)))
else:
ey.append(math.sqrt(y1e**2 + error**2))
# gr.SetPoint(i,x1,y1)
# print("Set point {} {},{}".format(i,x1,y1))
#
# if(kwargs.get('rel'),False):
# gr.SetPointError(i,x1e,x1e,math.sqrt(y1e**2+(error*y1)**2),math.sqrt(y1e**2+(error*y1)**2))
# print("Set point Error {} {},{}".format(i,x1e,math.sqrt(y1e**2+(error*y1)**2)))
# else:
# gr.SetPointError(i,x1e,x1e,math.sqrt(y1e**2+error**2),math.sqrt(y1e**2+error**2))
gr = Graph(NC)
print(x)
print(y2)
print(ex)
print(ey)
for x0, y0, x0e, y0e, i in zip(x, y2, ex, ey, range(NC)):
gr.SetPoint(i, x0, y0)
print("Set point {} {},{}".format(i, x0, y0))
gr.SetPointError(i, x0e, x0e, y0e, y0e)
print("Set point Error {} {},{}".format(i, x0e, y0e))
print(gr)
return gr
def draw_curve_7(_func, name, title, ylow, yhigh):
""" Draw 7TeV trigger efficiency curves """
graphs = []
for (trigger, color) in triggers:
tool = ROOT.TauTriggerCorrections(
os.path.join(base, 'triggerSF_%s.root' % trigger))
func = getattr(tool, _func)
eff = map(lambda x: func(x, 0), pt)
eff_low = map(lambda x: func(x, -1), pt)
eff_high = map(lambda x: func(x, 1), pt)
graph = Graph(len(pt), name=trigger)
for i, (p, e, e_low,
e_high) in enumerate(zip(pt, eff, eff_low, eff_high)):
graph.SetPoint(i, p / 1000, e)
graph.SetPointError(i, 0.4, 0.4, e - e_low, e_high - e)
graph.linecolor = color
graph.linewidth = 2
graph.fillstyle = '/'
graph.fillcolor = color
graphs.append(graph)
c = Canvas()
leg = Legend(len(graphs),
pad=c,
topmargin=0.4,
leftmargin=0.3,
textsize=25,
margin=0.2)
for i, g in enumerate(graphs):
if i == 0:
g.Draw('3AC')
g.xaxis.title = '#font[52]{p}_{T} [GeV]'
g.xaxis.SetLimits(20, 100)
g.yaxis.SetLimits(ylow, yhigh)
g.yaxis.SetRangeUser(ylow, yhigh)
g.yaxis.title = title
else:
g.Draw('3C SAME')
leg.AddEntry(g, g.name, 'L')
leg.Draw()
lines = []
for thresh in (25, 35):
line = Line(thresh, ylow, thresh, yhigh)
line.linestyle = 'dashed'
line.linewidth = 2
line.Draw()
lines.append(line)
c.SaveAs('trigger_{0}.png'.format(name))
c.SaveAs('trigger_{0}.eps'.format(name))
def get_rebinned_graph(graph_origin, binning=None):
if binning is None:
return graph_origin
graph_rebin = Graph(len(binning) - 1)
if len(graph_origin) != len(graph_rebin):
log.warning('uniform: {0} bins != rebinned: {1} bins'.format(
len(graph_origin), len(graph_rebin)))
raise RuntimeError('wrong binning')
for ipoint, (y,
yerr) in enumerate(zip(graph_origin.y(),
graph_origin.yerr())):
x_rebin_err = 0.5 * (binning[ipoint + 1] - binning[ipoint])
x_rebin = binning[ipoint] + x_rebin_err
graph_rebin.SetPoint(ipoint, x_rebin, y)
graph_rebin.SetPointError(ipoint, x_rebin_err, x_rebin_err, yerr[0],
yerr[1])
return graph_rebin
def UncertGraph(hnom, curve_uncert):
"""
Convert an histogram and a RooCurve
into a TGraphAsymmError
Parameters
----------
hnom: TH1F, TH1D,...
The histogram of nominal values
curve_uncert: RooCurve
The uncertainty band around the nominal value
curve_uncert: RooCurve
TODO: Improve the handling of the underflow and overflow bins
"""
graph = Graph(hnom.GetNbinsX())
# ---------------------------------------------
for ibin in xrange(1, hnom.GetNbinsX() + 1):
uncerts = []
for ip in xrange(3, curve_uncert.GetN() - 3):
x, y = ROOT.Double(0.), ROOT.Double(0.)
curve_uncert.GetPoint(ip, x, y)
if int(x) == int(hnom.GetBinLowEdge(ibin)):
uncerts.append(y)
uncerts.sort()
log.info('{0}: {1}'.format(hnom.name, uncerts))
if len(uncerts) != 2:
for val in uncerts:
if val in uncerts:
uncerts.remove(val)
if len(uncerts) != 2:
raise RuntimeError(
'Need exactly two error values and got {0}'.format(uncerts))
bin_center = 0.5 * (hnom.GetBinLowEdge(ibin + 1) +
hnom.GetBinLowEdge(ibin))
e_x_low = bin_center - hnom.GetBinLowEdge(ibin)
e_x_high = hnom.GetBinLowEdge(ibin + 1) - bin_center
bin_content = hnom.GetBinContent(ibin)
e_y_low = hnom.GetBinContent(ibin) - uncerts[0]
e_y_high = uncerts[1] - hnom.GetBinContent(ibin)
graph.SetPoint(ibin - 1, bin_center, bin_content)
graph.SetPointError(ibin - 1, e_x_low, e_x_high, e_y_low, e_y_high)
# ---------------------------------------------
return graph
def scaleGraph(gr1, sc):
x1 = ROOT.Double()
x_ = ROOT.Double()
y1 = ROOT.Double()
test = []
y = []
NC = gr1.GetN()
x = [0 for i in range(NC)]
for ii in range(NC):
gr1.GetPoint(ii, x_, y1)
x1 = x_ * 1.0
x[ii] = x1
y.append(y1 * sc)
gr = Graph(NC)
for x0, y0, i in zip(x, y, range(NC)):
gr.SetPoint(i, x0, y0)
return gr
def makeSystError(gr1, gr2, **kwargs):
x_ = Double()
x1e = Double()
x2 = Double()
x2e = Double()
y1 = Double()
y1e = Double()
y2 = Double()
y2e = Double()
NC = gr1.GetN()
print("Number of points: {}".format(NC))
y = []
ex = []
ey = []
x = [0 for i in range(NC)]
for ii in range(NC):
x1e = gr1.GetErrorX(ii)
y1e = gr1.GetErrorY(ii)
gr1.GetPoint(ii, x_, y1)
x1 = x_ * 1.0
gr2.GetPoint(ii, x2, y2)
x2e = gr2.GetErrorX(ii)
y2e = gr2.GetErrorY(ii)
x[ii] = x1
if (kwargs.get('abs', False)):
y.append(math.fabs(y1 - y2))
elif (kwargs.get('rel', False)):
y.append((y1 - y2) / (y1 + y2))
else:
y.append(y1 - y2)
ex.append(x1e)
ey.append(math.sqrt(y1e**2 + y2e**2))
gr = Graph(NC)
for x0, y0, x0e, y0e, i in zip(x, y, ex, ey, range(NC)):
gr.SetPoint(i, x0, y0)
print("Set point {} {},{}".format(i, x0, y0))
gr.SetPointError(i, x0e, x0e, y0e, y0e)
return gr
def grrDivide(gr1, gr2):
x1 = Double()
x_ = Double()
x1e = Double()
x2 = Double()
x2e = Double()
y1 = Double()
y1e = Double()
y2 = Double()
y2e = Double()
test = []
y = []
ex = []
ey = []
NC = gr1.GetN()
x = [0 for i in range(NC)]
test = [0 for i in range(NC)]
for ii in range(NC):
x1e = gr1.GetErrorX(ii)
y1e = gr1.GetErrorY(ii)
gr1.GetPoint(ii, x_, y1)
x1 = x_ * 1.0
gr2.GetPoint(ii, x2, y2)
x2e = gr2.GetErrorX(ii)
y2e = gr2.GetErrorY(ii)
x[ii] = x1
y.append(y1 / y2 if y2 != 0 else 0)
ex.append(x2e)
ey.append(
math.sqrt(pow(y1e / y2, 2) + pow(y1 * y2e /
(y2 * y2), 2)) if y2 != 0 else 0)
gr = Graph(NC)
for x0, y0, x0e, y0e, i in zip(x, y, ex, ey, range(NC)):
gr.SetPoint(i, x0, y0)
gr.SetPointError(i, x0e, x0e, y0e, y0e)
return gr
def main():
print('Number of arguments: ', len(sys.argv), 'arguments.')
print('Argument list:',str(sys.argv))
filename = sys.argv[1]
separate = int(sys.argv[2])
if(len(sys.argv) > 3):
start = int(sys.argv[3])
end = int(sys.argv[4])
else:
start = 1
end = 6
n_figs = end-start
print("Number of figs: {}".format(n_figs))
print("Input file: ")
print(filename)
FullJets_R04 = dataset('Full jets R=0.4',NFIN=0,range=(start,end),filename=filename,directory='AliJJetJtTask/AliJJetJtHistManager',color=2,style=24,rebin=2)
#Mixed_FullJets_R04 = datasetMixed("Full jets R=0.4",NFIN=0,range=5,filename=filename,directory='AliJJetJtTask/AliJJetJtHistManager',directory2='AliJJetJtTask_kEMCEJE/AliJJetJtHistManager',color=2,style=24,rebin=2)
#signal,jetPt = FullJets_R04.getHist('JtWeightBin',jetpt = True)
#signal2 = FullJets_R04.getHist('JtWeightLeadingRefBin',jetpt=False)
compareHistsWithRatio(FullJets_R04,['JtWeightBin','JtWeightLeadingRefBin','JtWeightLeadingRefBin','JtWeightLeadingRefBin','JtWeightLeadingRefBin'],['Jet axis ref.','leading ref. (xlong 0.0-0.2)','leading ref. (xlong 0.2-0.4)','leading ref. (xlong 0.4-0.6)','leading ref. (xlong 0.6-1.0)'],step=1,extras=['','Xlong00','Xlong01','Xlong02','Xlong03'])
plt.savefig("PythonFigures/JetVsLeadingRefConst.pdf",format='pdf') #Save figure
plt.show()
sets = compareHistsWithRatio(FullJets_R04,['JetConeJtWeightBin','JetConeJtWeightLeadingRefBin','JetConeJtWeightLeadingRefBin','JetConeJtWeightLeadingRefBin','JetConeJtWeightLeadingRefBin'],['Jet axis ref.','leading ref.(xlong 0.0-0.2)','leading ref.(xlong 0.2-0.4)','leading ref.(xlong 0.4-0.6)','leading ref. (xlong 0.6-1.0)'],step=1,extras=['','Xlong00','Xlong01','Xlong02','Xlong03'])
plt.savefig("PythonFigures/JetVsLeadingRefJetCone.pdf",format='pdf') #Save figure
plt.show()
JtJet = sets[0][0]
JtLeadingxlong00 = sets[1][0]
JtLeadingxlong01 = sets[2][0]
JtLeadingxlong02 = sets[3][0]
JtLeadingxlong03 = sets[4][0]
JtLeading = [h.clone() for h in sets[1][0]]
for h,s,s2,s3 in zip(JtLeading,sets[2][0],sets[3][0],sets[4][0]):
h.Add(s,1)
h.Add(s2,1)
h.Add(s3,1)
# print(JtLeading)
# for set in sets[2:]:
# for h,s in zip(JtLeading,set[0]):
# print(s)
# h.Add(s,1)
jetPt = sets[0][1]
jetPtCenter = array('d',[(a+b)/2.0 for a,b in jetPt])
jetPtErrors = array('d',[(b-a)/2.0 for a,b in jetPt])
FullJets_fit = []
FullJets_parameters = []
FullJets_gausRMS = []
FullJets_gammaRMS = []
FullJets_gausYield = []
FullJets_gammaYield = []
for jT,title in zip((JtJet,JtLeading,JtLeadingxlong00,JtLeadingxlong01,JtLeadingxlong02),("Jet ref.","Leading ref","Leading ref.(xlong 0.0-0.2)","Leading ref.(xlong 0.2-0.4)","Leading ref.(xlong 0.4-0.6)","Leading ref.(xlong 0.6-1.0)")):
gausRMS = []
gammaRMS = []
gausRMSe = []
gammaRMSe = []
gausYield = []
gammaYield = []
gausYielde = []
gammaYielde = []
fits = []
parameters = []
for h,i in zip(jT,range(Njets)):
fit,d = defs.fitJtHisto(h,'',1,i,8,title,draw=False)
fits.append(fit)
parameters.append(d)
gausRMS.append(d['gausRMS'])
gausRMSe.append(d['gausRMSe'])
gammaRMS.append(d['gammaRMS'])
gammaRMSe.append(d['gammaRMSe'])
gausYield.append(d['gausYield'])
gausYielde.append(d['gausYielde'])
gammaYield.append(d['gammaYield'])
gammaYielde.append(d['gammaYielde'])
gausRMSg = Graph(len(gausRMS)-2)
gammaRMSg = Graph(len(gammaRMS)-2)
gausYieldg = Graph(len(gausYield) -2)
gammaYieldg = Graph(len(gammaYield)-2)
for h,he,g in zip((gausYield,gammaYield),(gausYielde,gammaYielde),(gausYieldg,gammaYieldg)):
for x,xe,a,e,i in zip(jetPtCenter[2:],jetPtErrors[2:],h[2:],he[2:],range(len(gausRMS)-2)):
g.SetPoint(i,x,a)
g.SetPointError(i,xe,xe,e,e)
for a,b,c,d,e,f,i in zip(gausRMS[2:],gammaRMS[2:],gausRMSe[2:],gammaRMSe[2:],jetPtCenter[2:],jetPtErrors[2:],range(len(gausRMS)-2)):
gausRMSg.SetPoint(i,e,a)
gausRMSg.SetPointError(i,f,f,c,c)
gammaRMSg.SetPoint(i,e,b)
gammaRMSg.SetPointError(i,f,f,d,d)
FullJets_gausRMS.append(gausRMSg)
FullJets_gammaRMS.append(gammaRMSg)
FullJets_gausYield.append(gausYieldg)
FullJets_gammaYield.append(gammaYieldg)
FullJets_fit.append(fits)
FullJets_parameters.append(parameters)
print(gausRMS[2:])
print(gammaRMS[2:])
print(jetPtCenter[2:])
drawWithErrors2Combined(FullJets_gausRMS,FullJets_gammaRMS,["Jet ref.","Leading ref.","Leading ref.(xlong 0.0-0.2)","Leading ref.(xlong 0.2-0.4)","Leading ref.(xlong 0.4-0.6)"],15,500,1,0,1.85,0,r'jet $p_T$',r'$\sqrt{\left<j_T^2\right>}$','Pythia','PythonFigures/JetVsLeadingRefJetConeFits')
return
if(separate > 0):
fig = plt.figure(1)
ax = fig.add_subplot(1,1,1)
ax.set_xscale('log')
ax.set_yscale('log')
ax.text(0.2,0.0005,d['system'] +'\n'+ d['jettype'] +'\n'+ d['jetalg'] + '\n Jet Cone',fontsize = 7)
rplt.errorbar(signal[separate],xerr=False,emptybins=False,axes=ax,label="Jet axis reference",fmt='o') #Plot jT histogram,
rplt.errorbar(signal2[separate],xerr=False,emptybins=False,axes=ax,label="Leading track reference",fmt='o')
ax.text(0.3,1e2,r'$p_{{T,\mathrm{{jet}}}}$:''\n'r' {:02d}-{:02d} GeV'.format(jetPt[separate][0],jetPt[separate][1]))
ax.set_xlim([0.1,12])
ax.set_ylim([5e-6,1.5e3])
ax.legend(loc = 'lower left')
plt.savefig("PythonFigures/MixedFullJetsR04JetConeJtLeadingRefJetPt{0}.pdf".format(separate),format='pdf') #Save figure
plt.show() #Draw figure on screen
else:
n_rows = n_figs//4
print(n_rows)
fig, axs = defs.makegrid(4,n_figs//4,xlog=True,ylog=True,d=d,shareY=True,figsize=(10,5))
axs = axs.reshape(n_figs)
axs[1].text(0.12,0.002,d['system'] +'\n'+ d['jettype'] +'\n'+ d['jetalg'] + '\n Jet Cone',fontsize = 7)
for jT,jT2,pT,ax,i in zip(signal[start:],signal2[start:],jetPt[start:],axs,range(0,9)):
jT.SetMarkerColor(1)
jT2.SetMarkerColor(2)
plot = rplt.errorbar(jT,xerr=False,emptybins=False,axes=ax,label="Jet axis reference",fmt='o',fillstyle='none',ecolor='black') #Plot jT histogram,
plot = rplt.errorbar(jT2,xerr=False,emptybins=False,axes=ax,label="Leading track reference",fmt='o',fillstyle='none',ecolor='red') #Plot jT histogram,
ax.text(0.3,1e2,r'$p_{{T,\mathrm{{jet}}}}$:''\n'r' {:02d}-{:02d} GeV'.format(pT[0],pT[1]))
ax.set_xlim([0.1,22]) #Set x-axis limits
ax.set_ylim([5e-4,2e3]) #Set y-axis limits
ax.set_xticklabels(ax.get_xticklabels(),horizontalalignment='left')
axs[0].legend(loc = 'lower left')
plt.savefig("PythonFigures/MixedFullJetsR04JetConeJtLeadingRefPtFrom{}To{}.pdf".format(start,end),format='pdf') #Save figure
plt.show() #Draw figure on screen
def main():
print('Number of arguments: ', len(sys.argv), 'arguments.')
print('Argument list:', str(sys.argv))
filename = sys.argv[1]
if len(sys.argv) > 2:
fileData = sys.argv[2]
else:
fileData = None
print("Input file: ")
print(filename)
Njets = 9
if fileData is not None:
fD = root_open(fileData, 'read')
iS = 0
gGausRMSData = fD.Get("gGausRMS{:02d}".format(iS))
gGausRMSerrData = fD.Get("gGausRMS{:02d}_Systematics".format(iS))
gGausYieldData = fD.Get("gGausYield{:02d}".format(iS))
gGausYielderrData = fD.Get("gGausYield{:02d}_Systematics".format(iS))
gGammaRMSData = fD.Get("gGammaRMS{:02d}".format(iS))
gGammaRMSerrData = fD.Get("gGammaRMS{:02d}_Systematics".format(iS))
gGammaYieldData = fD.Get("gGammaYield{:02d}".format(iS))
gGammaYielderrData = fD.Get("gGammaYield{:02d}_Systematics".format(iS))
with root_open(filename, 'read') as f:
FullJets_jT = []
colors = (1, 2, 3)
for iF, c in zip((8, 6, 7), colors):
jT = [
f.get(
'AliJJetJtTask/AliJJetJtHistManager/JetConeJtWeightBin/JetConeJtWeightBinNFin{:02d}JetPt{:02d}'
.format(iF, ij)) for ij in range(Njets)
]
bgJt = [
f.get(
'AliJJetJtTask/AliJJetJtHistManager/BgJtWeightBin/BgJtWeightBinNFin{:02d}JetPt{:02d}'
.format(iF, ij)) for ij in range(Njets)
]
jetPtBin = [
f.get(
'AliJJetJtTask/AliJJetJtHistManager/JetPtBin/JetPtBinNFin{:02d}JetPt{:02d}'
.format(iF, ij)) for ij in range(Njets)
]
nJets = [h.Integral() for h in jetPtBin]
nBgs = [
f.get(
'AliJJetJtTask/AliJJetJtHistManager/BgTrkNumberBin/BgTrkNumberBinNFin{:02d}JetPt{:02d}'
.format(iF, ij)).Integral() for ij in range(Njets)
]
FullJets_jT.append(jT)
#FullJets_bgJt.append(bgJt)
#FullJets_jetPtBin.append(jetPtBin)
for j, b, nj, nb in zip(jT, bgJt, nJets, nBgs):
j.Rebin(2)
b.Rebin(2)
j.Scale(1.0 / nj, "width")
b.Scale(1.0 / nb, "width")
j.SetMarkerColor(c)
b.SetMarkerColor(c)
j.Add(b, -1.0)
jetPt = [
(int(
re.search(r'p_{T,jet} : ([\d]*)\.[\d] - ([\d]*).[\d]*',
h.GetTitle(), re.M | re.I).group(1)),
int(
re.search(r'p_{T,jet} : ([\d]*)\.[\d] - ([\d]*).[\d]*',
h.GetTitle(), re.M | re.I).group(2)))
for h in FullJets_jT[0]
] #Use regular expressions to extract jet pT range from histogram titles
jetPtCenter = array('d', [(a + b) / 2.0 for a, b in jetPt])
jetPtErrors = array('d', [(b - a) / 2.0 for a, b in jetPt])
print(jetPt, type(jetPt))
print(jetPtCenter, type(jetPtCenter))
print(jetPtErrors, type(jetPtErrors))
FullJets_fit = []
FullJets_parameters = []
FullJets_gausRMS = []
FullJets_gammaRMS = []
FullJets_gausYield = []
FullJets_gammaYield = []
for jT in FullJets_jT:
gausRMS = []
gammaRMS = []
gausRMSe = []
gammaRMSe = []
gausYield = []
gammaYield = []
gausYielde = []
gammaYielde = []
fits = []
parameters = []
for h, i in zip(jT, range(Njets)):
fit, d = fitJtHisto(h, '', 1, i, 8)
fits.append(fit)
parameters.append(d)
gausRMS.append(d['gausRMS'])
gausRMSe.append(d['gausRMSe'])
gammaRMS.append(d['gammaRMS'])
gammaRMSe.append(d['gammaRMSe'])
gausYield.append(d['gausYield'])
gausYielde.append(d['gausYielde'])
gammaYield.append(d['gammaYield'])
gammaYielde.append(d['gammaYielde'])
gausRMSg = Graph(len(gausRMS) - 2)
gammaRMSg = Graph(len(gammaRMS) - 2)
gausYieldg = Graph(len(gausYield) - 2)
gammaYieldg = Graph(len(gammaYield) - 2)
for h, he, g in zip((gausYield, gammaYield),
(gausYielde, gammaYielde),
(gausYieldg, gammaYieldg)):
for x, xe, a, e, i in zip(jetPtCenter[2:],
jetPtErrors[2:], h[2:], he[2:],
range(len(gausRMS) - 2)):
g.SetPoint(i, x, a)
g.SetPointError(i, xe, xe, e, e)
for a, b, c, d, e, f, i in zip(gausRMS[2:], gammaRMS[2:],
gausRMSe[2:], gammaRMSe[2:],
jetPtCenter[2:], jetPtErrors[2:],
range(len(gausRMS) - 2)):
gausRMSg.SetPoint(i, e, a)
gausRMSg.SetPointError(i, f, f, c, c)
gammaRMSg.SetPoint(i, e, b)
gammaRMSg.SetPointError(i, f, f, d, d)
FullJets_gausRMS.append(gausRMSg)
FullJets_gammaRMS.append(gammaRMSg)
FullJets_gausYield.append(gausYieldg)
FullJets_gammaYield.append(gammaYieldg)
FullJets_fit.append(fits)
FullJets_parameters.append(parameters)
if fileData is not None:
FullJets_gausRMS.append(gGausRMSData)
FullJets_gammaRMS.append(gGammaRMSData)
FullJets_gausYield.append(gGausYieldData)
FullJets_gammaYield.append(gGammaYieldData)
fig, axs = plt.subplots(2, 1, figsize=(7, 7))
ax = axs[0]
ax.set_xlim([0.1, 15])
ax.set_ylim([5e-6, 2e3])
ax.set_xlabel(r'$j_{T}\left(GeV/c\right)$', fontsize=labelsize)
ax.set_ylabel(r'$\frac{1}{N_{jets}}\frac{dN}{j_{T}dj_{T}}$',
fontsize=labelsize)
ratios = []
ax.set_xscale('log')
ax.set_yscale('log')
for h, c, R in zip(FullJets_jT, (0, 1, 2, 3), Rs):
h[6].SetMarkerColor(colors[c])
h[6].SetMarkerStyle(styles[c])
h[6].SetLineColor(colors[c])
ratio = h[6].Clone()
ratio.Divide(FullJets_jT[1][6])
ratios.append(ratio)
plot = rplt.errorbar(h[6],
xerr=False,
emptybins=False,
label='R = {:.1f}'.format(R),
axes=ax,
fmt='+')
line = plot.get_children()[0]
line.set_markersize(mSize)
if (styles[c] > 23):
line.set_markerfacecolor('none')
#line.set_markeredgecolor(color)
line.set_color(colors[c])
ax.text(
0.15,
0.001,
'Pythia \n Full Jets\n' + r'Anti-$k_T$' + '\n' +
r'$p_{{T,\mathrm{{jet}}}}$: {:02d}-{:02d} GeV/c'.format(60, 80),
fontsize=10)
handles, labels = ax.get_legend_handles_labels()
handles = [
container.ErrorbarContainer(h, has_xerr=False, has_yerr=True)
if isinstance(h, container.ErrorbarContainer) else h
for h in handles
]
ax.legend(handles,
labels,
loc='upper right',
numpoints=1,
prop={'family': 'monospace'})
#ax.legend(loc = 'upper right')
ax.set_xlim([0.1, 15])
ax.set_ylim([5e-6, 2e3])
ax.grid(True)
ax = axs[1]
ax.grid(True)
ax.set_xlabel(r'$j_{T}\left[GeV\right]$', fontsize=labelsize)
ax.set_ylabel('Ratio',
fontsize=labelsize) #Add x-axis labels for bottom row
for ratio, c in zip(ratios, (0, 1, 2, 3)):
#ratio.SetMarkerColor(c)
#ratio.SetMarkerStyle(24)
plot = rplt.errorbar(ratio, xerr=False, emptybins=False, axes=ax)
line = plot.get_children()[0]
line.set_markersize(mSize)
if (styles[c] > 23):
line.set_markerfacecolor('none')
#line.set_markeredgecolor(color)
line.set_color(colors[c])
ax.set_xlim([0.1, 15])
ax.set_ylim([0.1, 3])
ax.set_xscale('log')
plt.tight_layout()
plt.subplots_adjust(wspace=0,
hspace=0) #Set space between subfigures to 0
plt.savefig("PythonFigures/RcomparisonSignalPt6080.pdf".format(file),
format='pdf') #Save figure
plt.show() #Draw figure on screen
drawWithErrors2Combined(FullJets_gausRMS,
FullJets_gammaRMS,
15,
500,
1,
0,
1.65,
0,
r'jet $p_T (GeV/c)$',
r'$\sqrt{\left<j_T^2\right>}$',
'Pythia',
'PythonFigures/RcomparisonRMS',
separate=True)
return
drawWithErrors2Combined(
FullJets_gausYield,
FullJets_gammaYield,
15,
500,
1,
0,
10,
0,
r'jet $p_T$',
r'Yield',
'Pythia',
'PythonFigures/RcomparisonYield',
)
ratios = []
for hists in FullJets_jT:
if hists is not None:
ratio = []
for h, true in zip(hists, FullJets_jT[1]):
h2 = h.Clone()
h2.Divide(true)
ratio.append(h2)
else:
ratio = None
ratios.append(ratio)
fig, axs = defs.makegrid(4,
2,
xlog=True,
ylog=False,
d=d,
shareY=False)
axs = axs.reshape(8)
axs[4].set_ylabel("Ratio to R = 0.4", fontsize=labelsize)
axs[7].set_ylabel("Ratio to R = 0.4", fontsize=labelsize)
axs[1].text(
0.02,
0.005, 'Pythia\n'
r'pPb $\sqrt{s_{NN}} = 5.02 \mathrm{TeV}$'
'\n Full jets \n'
r'Anti-$k_T$',
fontsize=7
) #Add text to second subfigure, first parameters are coordinates in the drawn scale/units
for hists, R in zip(FullJets_jT, Rs):
for jT, ax, i, pT in zip(hists[2:], axs[0:4], range(0, 9),
jetPt[2:]):
rplt.errorbar(jT,
emptybins=False,
xerr=False,
label="R = {:.1f}".format(R),
axes=ax,
fmt='o') #Plot jT histogram,
ax.text(
0.3, 1e2, r'$p_{{T,\mathrm{{jet}}}}$:'
'\n'
r' {:02d}-{:02d} GeV'.format(pT[0], pT[1]))
ax.set_xlim([0.01, 20]) #Set x-axis limits
ax.set_ylim([5e-4, 2e3]) #Set y-axis limits
ax.set_yscale('log')
ax.grid(True)
for ratio in ratios:
for r, ax in zip(ratio[2:], axs[4:8]):
rplt.errorbar(r, axes=ax, emptybins=False, xerr=False)
ax.set_xlim([0.01, 20])
ax.set_ylim([0.1, 3])
ax.grid(True)
axs[0].legend(loc='lower left')
plt.savefig("PythonFigures/RcomparisonSignal.pdf",
format='pdf') #Save figure
plt.show() #Draw figure on screen
# set the random seed
ROOT.gRandom.SetSeed(42)
np.random.seed(42)
# points
x = np.sort(np.random.random(10)) * 3500
y = np.random.random(10)
# set style for ROOT
set_style('ATLAS')
# create graph
graph = Graph(x.shape[0])
for i, (xx, yy) in enumerate(zip(x, y)):
graph.SetPoint(i, xx, yy)
# set visual attributes
graph.linecolor = 'blue'
graph.markercolor = 'blue'
graph.xaxis.SetTitle("E_{T} [GeV]")
graph.yaxis.SetTitle("d#sigma_{jet}/dE_{T,jet} [fb/GeV]")
graph.xaxis.SetRangeUser(0, 3500)
graph.yaxis.SetRangeUser(0, 1)
# plot with ROOT
canvas = Canvas()
graph.Draw("APL")
label = ROOT.TText(0.4, 0.8, "ROOT")
label.SetTextFont(43)
def pvalue_plot(poi,
pvalues,
pad=None,
xtitle='X',
ytitle='P_{0}',
linestyle=None,
linecolor=None,
yrange=None,
verbose=False):
"""
Draw a pvalue plot
Parameters
----------
poi : list
List of POI values tested
pvalues : list
List of p-values or list of lists of p-values to overlay
multiple p-value curves
pad : Canvas or Pad, optional (default=None)
Pad to draw onto. Create new pad if None.
xtitle : str, optional (default='X')
The x-axis label (POI name)
ytitle : str, optional (default='P_{0}')
The y-axis label
linestyle : str or list, optional (default=None)
Line style for the p-value graph or a list of linestyles for
multiple p-value graphs.
linecolor : str or list, optional (default=None)
Line color for the p-value graph or a list of linestyles for
multiple p-value graphs.
Returns
-------
pad : Canvas
The pad.
graphs : list of Graph
The p-value graphs
"""
if not pvalues:
raise ValueError("pvalues is empty")
if not poi:
raise ValueError("poi is empty")
# determine if pvalues is list or list of lists
if not isinstance(pvalues[0], (list, tuple)):
pvalues = [pvalues]
if linecolor is not None:
if not isinstance(linecolor, list):
linecolor = [linecolor]
linecolor = cycle(linecolor)
if linestyle is not None:
if not isinstance(linestyle, list):
linestyle = [linestyle]
linestyle = cycle(linestyle)
with preserve_current_canvas():
if pad is None:
pad = Canvas()
pad.cd()
pad.SetLogy()
# create the axis
min_poi, max_poi = min(poi), max(poi)
haxis = Hist(1000, min_poi, max_poi)
xaxis = haxis.xaxis
yaxis = haxis.yaxis
xaxis.SetRangeUser(min_poi, max_poi)
haxis.Draw('AXIS')
min_pvalue = float('inf')
graphs = []
for ipv, pv in enumerate(pvalues):
graph = Graph(len(poi),
linestyle='dashed',
drawstyle='L',
linewidth=2)
for idx, (point, pvalue) in enumerate(zip(poi, pv)):
graph.SetPoint(idx, point, pvalue)
if linestyle is not None:
graph.linestyle = linestyle.next()
if linecolor is not None:
graph.linecolor = linecolor.next()
graphs.append(graph)
curr_min_pvalue = min(pv)
if curr_min_pvalue < min_pvalue:
min_pvalue = curr_min_pvalue
if verbose:
for graph in graphs:
log.info(['{0:1.1f}'.format(xval) for xval in list(graph.x())])
log.info(['{0:0.3f}'.format(yval) for yval in list(graph.y())])
# automatically handles axis limits
axes, bounds = draw(graphs,
pad=pad,
same=True,
logy=True,
xtitle=xtitle,
ytitle=ytitle,
xaxis=xaxis,
yaxis=yaxis,
ypadding=(0.2, 0.1),
logy_crop_value=1E-300)
if yrange is not None:
xaxis, yaxis = axes
yaxis.SetLimits(*yrange)
yaxis.SetRangeUser(*yrange)
min_pvalue = yrange[0]
# draw sigma levels up to minimum of pvalues
line = Line()
line.SetLineStyle(2)
line.SetLineColor(2)
latex = ROOT.TLatex()
latex.SetNDC(False)
latex.SetTextSize(20)
latex.SetTextColor(2)
sigma = 0
while True:
pvalue = gaussian_cdf_c(sigma)
if pvalue < min_pvalue:
break
keepalive(
pad,
latex.DrawLatex(max_poi, pvalue, " {0}#sigma".format(sigma)))
keepalive(pad, line.DrawLine(min_poi, pvalue, max_poi, pvalue))
sigma += 1
pad.RedrawAxis()
pad.Update()
return pad, graphs
_, entry = j
print '[%d]' % i, entry
idx = raw_input('which one should I use? ')
idx = int(idx)
_, to_use = matches[idx]
print to_use.start.str, '-->', time.str
points.append((to_use.start.time, time.time))
#linear fit
from rootpy import ROOT
ROOT.gROOT.SetBatch()
from rootpy.plotting import Graph, F1, Canvas
fcn = F1(args.fitfunc)
graph = Graph(len(points))
for idx, point in enumerate(points):
x, y = point
graph.SetPoint(idx, x, y)
graph.fit(fcn)
canvas = Canvas()
graph.Draw()
canvas.SaveAs("shifts.png")
with open(args.out, 'w') as out:
for i, entry in enumerate(entries):
entry.remap(fcn)
out.write('%d\n' % i)
out.write('%s\n\n' % entry.string)
'/storage/TopQuarkGroup/unfolding/unfolding_merged_sub1.root', 'read')
h_truth_finebinned = inputFile.unfoldingAnalyserElectronChannel.truth
h_truth = asrootpy(
inputFile.unfoldingAnalyserElectronChannel.truth.Rebin(
nbins, 'truth_new', bins))
print 'old:', get_bin_centers(bins)
new_centers = barycenters(h_truth_finebinned, h_truth)
print 'centre of mass:', new_centers
new_centers = calculate_correct_x_coordinates(h_truth_finebinned, bins)
print 'correct:', new_centers
data = list(h_truth.y())
h_truth_new = Hist(new_centers)
bin_widths = [25, 20, 25, 30, 1000]
g_truth_new = Graph(len(new_centers))
for i, (x, y, width) in enumerate(zip(new_centers, data, bin_widths)):
g_truth_new.SetPoint(i, x, y / width)
error = h_truth.GetBinError(i + 1)
g_truth_new.SetPointError(i, 0, 0, error, error)
for bin_i in range(len(data)):
h_truth_new.SetBinContent(bin_i + 1, data[bin_i] / bin_widths[bin_i])
h_truth.SetBinContent(bin_i + 1, data[bin_i] / bin_widths[bin_i])
h_truth_finebinned.SetFillStyle(0)
h_truth_finebinned.Smooth(500)
x, y = list(h_truth_finebinned.x()), list(h_truth_finebinned.y())
bin_edges = np.array(list(h_truth_finebinned.xedges()))
bincenters = 0.5 * (bin_edges[1:] + bin_edges[:-1])
g_truth = Graph(h_truth)
# g_truth_new = Graph(len(h_truth), h_truth_new)
g_truth_new.SetLineColor('red')
def main():
JetPtBins = [5, 10, 20, 30, 40, 60, 80, 100, 150, 500]
jetPtBins2 = [(JetPtBins[i], JetPtBins[i + 1]) for i in range(8)]
#JetPtCenter = [7.5,15,25,35,50,70,90,125,325]
JetPtCenter = [
6.5, 12.45, 23.34, 33.83, 46.75, 67.73, 88.01, 116.11, 194.61
]
LeadPtMode = [2.0, 3.0, 5.6, 8.9, 9.9, 14.8, 20.7, 26.0, 34.6]
LeadPtMean = [2.35, 3.72, 6.66, 9.59, 13.58, 17.98, 23.27, 27.55, 31.68]
LeadPtError = [0.93, 1.69, 3.18, 4.43, 6.74, 8.34, 9.68, 10.27, 10.55]
JetPtError = [2.5, 5, 5, 5, 10, 10, 10, 25, 175]
JetPtLeadPtG = Graph(
len(JetPtCenter)) #Gives jet pT as a function of leading pT
JetPtLeadPtGerr = Graph(len(JetPtCenter))
LeadPtJetPtG = Graph(len(JetPtCenter))
LeadPtJetPtGerr = Graph(len(JetPtCenter))
for i, (x, y, e) in enumerate(zip(LeadPtMean, JetPtCenter, JetPtError)):
JetPtLeadPtG.SetPoint(i, x, y)
JetPtLeadPtGerr.SetPoint(i, x, e)
for i, (x, y, e) in enumerate(zip(JetPtCenter, LeadPtMean, LeadPtError)):
LeadPtJetPtG.SetPoint(i, x, y)
LeadPtJetPtGerr.SetPoint(i, x, e)
Njets = 8
topcomment = "_systematics_Triggered"
finderName = [
"Full jets, Anti-k_\mathrm{T} R = 0.4",
"Charged Jets, Anti-k_\mathrm{T} R = 0.4"
]
finderType = ["Full", "Charged"]
setTitle = ["0", "1", "2", "3", "4", "5"]
finderR = {4, 4}
iC = 0
logx = 1
doWeight = 1
mSize = 0.3
iS = 0
f = root_open("RootFiles/jtSystematics.root", 'read')
f2 = root_open("RootFiles/dihadronjTFinalGraphs.root", 'read')
gGausRMS = f.Get("gGausRMS{:02d}".format(iS))
gGausRMSerr = f.Get("gGausRMS{:02d}_Systematics".format(iS))
gGausYield = f.Get("gGausYield{:02d}".format(iS))
gGausYielderr = f.Get("gGausYield{:02d}_Systematics".format(iS))
gGammaRMS = f.Get("gGammaRMS{:02d}".format(iS))
gGammaRMSerr = f.Get("gGammaRMS{:02d}_Systematics".format(iS))
gGammaYield = f.Get("gGammaYield{:02d}".format(iS))
gGammaYielderr = f.Get("gGammaYield{:02d}_Systematics".format(iS))
gGausRMS.Print()
for g in (gGausRMS, gGausRMSerr, gGausYield, gGausYielderr, gGammaRMS,
gGammaRMSerr, gGammaYield, gGammaYielderr):
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
for i, x, y, jetpt in zip(range(n), xs, ys, JetPtCenter):
if (i < 3):
g.SetPoint(i, 0, 0)
else:
g.SetPoint(i, jetpt, y)
gGausRMS.Print()
g = gGausRMSerr
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
xerrs = g.GetEX()
yerrs = g.GetEY()
for i, x, y, xerr, yerr in zip(range(n), xs, ys, xerrs, yerrs):
if (y > 0 and yerr / y > 0.13):
yerr = 0.13 * y
if (y > 0 and yerr / y < 0.09):
yerr = 0.09 * y
g.SetPointError(i, xerr, yerr)
g = gGammaRMSerr
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
xerrs = g.GetEX()
yerrs = g.GetEY()
for i, x, y, xerr, yerr in zip(range(n), xs, ys, xerrs, yerrs):
if (y > 0 and yerr / y > 0.13):
yerr = 0.13 * y
if (y > 0 and yerr / y < 0.10):
yerr = 0.08 * y
g.SetPointError(i, xerr, yerr)
iSPythia = 3
gGausRMSPythia = f.Get("gGausRMS{:02d}".format(iSPythia))
gGausYieldPythia = f.Get("gGausYield{:02d}".format(iSPythia))
gGammaRMSPythia = f.Get("gGammaRMS{:02d}".format(iSPythia))
gGammaYieldPythia = f.Get("gGammaYield{:02d}".format(iSPythia))
gGausRMSPythia.Print()
for g in (gGausRMSPythia, gGausYieldPythia, gGammaRMSPythia,
gGammaYieldPythia):
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
for i, x, y, jetpt in zip(range(n), xs, ys, JetPtCenter):
if (i < 3):
g.SetPoint(i, 0, 0)
else:
g.SetPoint(i, jetpt, y)
gGausRMSPythia.Print()
gGausRMSJussi = f2.Get(
"systematicError_RMSNarrow_p-Pb_5.02TeV_0.2<xlong<0.4")
gGammaRMSJussi = f2.Get(
"systematicError_RMSWide_p-Pb_5.02TeV_0.2<xlong<0.4")
doWhat = False
n = gGausRMS.GetN()
xs = gGausRMSerr.GetX()
gGausRMS2 = gGausRMS.Clone()
gGausRMSerr2 = gGausRMSerr.Clone()
gGausYield2 = gGausYield.Clone()
gGausYielderr2 = gGausYielderr.Clone()
gGammaRMS2 = gGammaRMS.Clone()
gGammaRMSerr2 = gGammaRMSerr.Clone()
gGammaYield2 = gGammaYield.Clone()
gGammaYielderr2 = gGammaYielderr.Clone()
gGausRMSPythia2 = gGausRMSPythia.Clone()
gGausYieldPythia2 = gGausYieldPythia.Clone()
gGammaRMSPythia2 = gGammaRMSPythia.Clone()
gGammaYieldPythia2 = gGammaYieldPythia.Clone()
for g in (gGausRMS2, gGausRMSerr2, gGausYield2, gGausYielderr2, gGammaRMS2,
gGammaRMSerr2, gGammaYield2, gGammaYielderr2, gGausRMSPythia2,
gGausYieldPythia2, gGammaRMSPythia2, gGammaYieldPythia2):
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
xerrs = g.GetEX()
yerrs = g.GetEY()
for i, x, y, xerr, yerr in zip(range(n), xs, ys, xerrs, yerrs):
g.SetPoint(i, LeadPtMean[i], y)
g.SetPointError(i, LeadPtError[i], yerr)
gGausRMSJussi2 = gGausRMSJussi.Clone()
gGammaRMSJussi2 = gGammaRMSJussi.Clone()
for g in (gGausRMSJussi2, gGammaRMSJussi2):
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
xerrs = g.GetEX()
yerrs = g.GetEY()
for i, x, y, xerr, yerr in zip(range(n), xs, ys, xerrs, yerrs):
print("Trigger pT: {}".format(x))
x1 = JetPtLeadPtG.Eval(x)
x1e = JetPtLeadPtGerr.Eval(x)
print("Estimated jet pT: {}".format(x1))
g.SetPoint(i, x1, y)
g.SetPointError(i, x1e, yerr)
Pythia = dataset("Pythia8 4C",
NFIN=0,
range=(2, 8),
filename="RootFiles/Grid_Monash.root",
directory='/JCDijetBaseTask/jcdijet',
color=colors[1],
style=24,
rebin=Rebin)
Pythia2 = dataset("Pythia8 Monash",
NFIN=0,
range=(2, 8),
filename="RootFiles/Grid_Tune4c.root",
directory='/JCDijetBaseTask/jcdijet',
color=colors[2],
style=24,
rebin=Rebin)
#Herwig = dataset("Herwig 7.0",NFIN=0,range=(4,5),filename="RootFiles/Herwig7.root",directory='/JJetJt',color=colors[3],style=24,rebin=Rebin)
#Pythia_ALICE = dataset("ALICE Pythia6 Perugia2011",NFIN=0,range=(1,8),filename="CF_pPb_MC_legotrain/legotrain_610_20181010-1926_LHCb4_fix_CF_pPb_MC_ptHardMerged.root",directory='AliJJetJtTask/AliJJetJtHistManager',color=colors[4],style=24,rebin=Rebin)
#datasets = [Pythia]
#inclusive,jetPt = Pythia.getHist('JetConeJtWeightBin',jetpt = True)
#datasets.append(Mixed_FullJets_R04)
inclusive, jetPt = Pythia.getHist('JetConeJtWeightBin', jetpt=True)
datasets = [Pythia]
incs = [inclusive]
datasets.append(Pythia2)
#datasets.append(Herwig)
for data in datasets[1:]:
incs.append(data.getHist('JetConeJtWeightBin', jetpt=False))
names = [data.name() for data in datasets]
signals = [
data.getSubtracted('JetConeJtWeightBin', 'BgJtWeightBin', jetpt=False)
for data in datasets
]
graphs = [data.getGraphs() for data in datasets]
gausRMS = [x[0] for x in graphs]
gammaRMS = [x[1] for x in graphs]
gausYield = [x[2] for x in graphs]
gammaYield = [x[3] for x in graphs]
for graphs in (gausRMS, gammaRMS, gausYield, gammaYield):
for g in graphs:
n = g.GetN()
xs = g.GetX()
ys = g.GetY()
for i, x, y, jetpt in zip(range(n), xs, ys, JetPtCenter[4:]):
g.SetPoint(i, jetpt, y)
gausRMS[0].Print()
#pythiaN = [(gGausRMSPythia,"Pythia6"),(gausRMS[0],"Pythia8 4C"),(gausRMS[1],"Pythia8 Monash"),(gausRMS[2],"Herwig 7.0")]
#pythiaW = [(gGammaRMSPythia,"Pythia6"),(gammaRMS[0],"Pythia8 4C"),(gammaRMS[1],"Pythia8 Monash"),(gammaRMS[2],"Herwig 7.0")]
pythiaN = [(gausRMS[0], "Pythia8 4C"), (gausRMS[1], "Pythia8 Monash")]
pythiaW = [(gammaRMS[0], "Pythia8 4C"), (gammaRMS[1], "Pythia8 Monash")]
#Fig 3, NArrow and Wide RMS without Pythia
drawWithErrors2Combined(gGausRMS,
gGausRMSerr,
gGammaRMS,
gGammaRMSerr,
35,
135,
0,
0,
1.5,
0,
r'$p_\mathrm{T,jet}$ (GeV/c)',
r'$\sqrt{\left<j_\mathrm{T}^{2}\right>}$ (GeV/c)',
"RMS",
"_triggered",
"PythonFigures/RMSWithSystematics",
1,
-1,
wideE=0.041,
narrowE=0.051)
#Fig 3, NArrow and Wide RMS with Pythia Comparison
drawWithErrors2Combined(gGausRMS,
gGausRMSerr,
gGammaRMS,
gGammaRMSerr,
35,
135,
0,
0,
1.9,
0,
r'$p_\mathrm{T,jet}$ (GeV/c)',
r'$\sqrt{\left<j_\mathrm{T}^{2}\right>}$ (GeV/c)',
"",
"_triggered",
"PythonFigures/RMSWithSystematics_Pythia",
1,
-1,
pythiaN=pythiaN,
pythiaW=pythiaW,
wideE=0.041,
narrowE=0.051,
titleLoc=(95, 1.5))
#Fig 5 with pT,trigger on X-axis
drawWithErrors2Combined(
gGausRMS2,
gGausRMSerr2,
gGammaRMS2,
gGammaRMSerr2,
0,
50,
0,
0,
2.2,
0,
r'$p_\mathrm{T,trigger}$ (GeV/c)',
r'$\sqrt{\left<j_\mathrm{T}^{2}\right>}$ (GeV/c)',
"",
"_triggered",
"PythonFigures/RMSWithSystematics_DihadronTriggerPt",
1,
-1,
jussiN=gGausRMSJussi,
jussiW=gGammaRMSJussi,
wideE=0.041,
narrowE=0.051)
#Fig 5 with pT,jet on X-axis
drawWithErrors2Combined(gGausRMS,
gGausRMSerr,
gGammaRMS,
gGammaRMSerr,
1,
135,
0,
0,
2.2,
0,
r'$p_\mathrm{T,jet}$ (GeV/c)',
r'$\sqrt{\left<j_\mathrm{T}^{2}\right>}$ (GeV/c)',
"",
"_triggered",
"PythonFigures/RMSWithSystematics_DihadronJetPt",
1,
-1,
jussiN=gGausRMSJussi2,
jussiW=gGammaRMSJussi2,
wideE=0.041,
narrowE=0.051)
def main(args):
fileList = glob('/data/nawoods/lepsForSIP/*.root')
files = {int(f.split('_M')[1].split('.')[0]) : f for f in fileList}
checkers = {m : MuonSIPChecker('m={}'.format(m), [f]) for m,f in files.iteritems()}
sipRMS = Graph(len(fileList), type='errors')
sipHists = []
dxyRMS = Graph(len(fileList), type='errors')
dxyHists = []
dzRMS = Graph(len(fileList), type='errors')
dzHists = []
ipHists = []
ipErrHists = []
fracFailing = Graph(len(fileList), type='errors')
for i, m in enumerate(sorted(files.keys())):
checkers[m].processSample()
checkers[m].hists['sip'].Sumw2()
sipRMS.SetPoint(i, float(m), checkers[m].hists['sip'].GetRMS())
sipRMS.SetPointError(i, 0., checkers[m].hists['sip'].GetRMSError())
sipHists.append(checkers[m].hists['sip'])
sipHists[-1].color = getColor(m)
sipHists[-1].title = "m_{{H}} = {}".format(m)
sipHists[-1].drawstyle = 'hist'
sipHists[-1].legendstyle = 'L'
sipHists[-1].linewidth = 2
sipHists[-1].scale(1./sipHists[-1].integral())
ipHists.append(checkers[m].hists['ip'])
ipHists[-1].color = getColor(m)
ipHists[-1].title = "m_{{H}} = {}".format(m)
ipHists[-1].drawstyle = 'hist'
ipHists[-1].legendstyle = 'L'
ipHists[-1].linewidth = 2
ipHists[-1].scale(1./ipHists[-1].integral())
ipErrHists.append(checkers[m].hists['ipErr'])
ipErrHists[-1].color = getColor(m)
ipErrHists[-1].title = "m_{{H}} = {}".format(m)
ipErrHists[-1].drawstyle = 'hist'
ipErrHists[-1].legendstyle = 'L'
ipErrHists[-1].linewidth = 2
ipErrHists[-1].scale(1./ipErrHists[-1].integral())
checkers[m].hists['dxy'].Sumw2()
dxyRMS.SetPoint(i, float(m), checkers[m].hists['dxy'].GetRMS())
dxyRMS.SetPointError(i, 0., checkers[m].hists['dxy'].GetRMSError())
dxyHists.append(checkers[m].hists['dxy'])
dxyHists[-1].color = getColor(m)
dxyHists[-1].title = "m_{{H}} = {}".format(m)
dxyHists[-1].drawstyle = 'hist'
dxyHists[-1].legendstyle = 'L'
dxyHists[-1].linewidth = 2
dxyHists[-1].scale(1./dxyHists[-1].integral())
checkers[m].hists['dz'].Sumw2()
dzRMS.SetPoint(i, float(m), checkers[m].hists['dz'].GetRMS())
dzRMS.SetPointError(i, 0., checkers[m].hists['dz'].GetRMSError())
dzHists.append(checkers[m].hists['dz'])
dzHists[-1].color = getColor(m)
dzHists[-1].title = "m_{{H}} = {}".format(m)
dzHists[-1].drawstyle = 'hist'
dzHists[-1].legendstyle = 'L'
dzHists[-1].linewidth = 2
dzHists[-1].scale(1./dzHists[-1].integral())
fracFailing.SetPoint(i, float(m),
1. - float(checkers[m].nPassSIP) / checkers[m].nTot)
cSIP = Canvas(1000,1000)
draw(sipHists, cSIP, xtitle='#frac{IP_{3D}}{#sigma_{IP_{3D}}}',
ytitle='arb.')
legSIP = Legend(sipHists, cSIP, textsize=.03, entrysep=0.015, leftmargin=0.6, entryheight=0.04)
legSIP.Draw("same")
cSIP.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/sips.png')
cSIPLog = Canvas(1000,1000)
draw(sipHists, cSIPLog, xtitle='#frac{IP_{3D}}{#sigma_{IP_{3D}}}',
ytitle='arb.', logy=True)
legSIPLog = Legend(sipHists, cSIPLog, textsize=.027, entrysep=0.012, leftmargin=0.6, entryheight=0.03)
legSIPLog.Draw("same")
cSIPLog.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/sipsLog.png')
cSIPRMS = Canvas(1000, 1000)
sipRMS.color = 'b'
sipRMS.drawstyle = 'PE'
sipRMS.legendstyle = 'PE'
draw(sipRMS, cSIPRMS, xtitle="m_{H}", ytitle="RMS(SIP_{3D})", xlimits=(0.,2600.))
cSIPRMS.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/sipRMS.png')
cIP = Canvas(1000,1000)
draw(ipHists, cIP, xtitle='IP_{3D}',
ytitle='arb.')
legIP = Legend(ipHists, cIP, textsize=.03, entrysep=0.015, leftmargin=0.6, entryheight=0.04)
legIP.Draw("same")
cIP.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/ips.png')
cIPLog = Canvas(1000,1000)
draw(ipHists, cIPLog, xtitle='#frac{IP_{3D}}{#sigma_{IP_{3D}}}',
ytitle='arb.', logy=True)
legIPLog = Legend(ipHists, cIPLog, textsize=.027, entrysep=0.012, leftmargin=0.6, entryheight=0.03)
legIPLog.Draw("same")
cIPLog.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/ipsLog.png')
cIPErr = Canvas(1000,1000)
draw(ipErrHists, cIPErr, xtitle='#sigma_{IP_{3D}}',
ytitle='arb.')
legIPErr = Legend(ipErrHists, cIPErr, textsize=.03, entrysep=0.015, leftmargin=0.6, entryheight=0.04)
legIPErr.Draw("same")
cIPErr.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/ipErrs.png')
cIPErrLog = Canvas(1000,1000)
draw(ipErrHists, cIPErrLog, xtitle='#sigma_{IP_{3D}}',
ytitle='arb.', logy=True)
legIPErrLog = Legend(ipErrHists, cIPErrLog, textsize=.027, entrysep=0.012, leftmargin=0.6, entryheight=0.03)
legIPErrLog.Draw("same")
cIPErrLog.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/ipErrsLog.png')
cFail = Canvas(1000, 1000)
fracFailing.color = 'b'
fracFailing.drawstyle = 'PE'
fracFailing.legendstyle = 'PE'
draw(fracFailing, cSIPRMS, xtitle="m_{H}", ytitle="Fraction failing SIP", xlimits=(0.,2600.))
cSIPRMS.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/fracFailing.png')
cDXY = Canvas(1000,1000)
draw(dxyHists, cDXY, xtitle='#Delta_{xy}',
ytitle='arb.')
legDXY = Legend(dxyHists, cDXY, textsize=.03, entrysep=0.015, leftmargin=0.6, entryheight=0.04)
legDXY.Draw("same")
cDXY.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/dxys.png')
cDXYRMS = Canvas(1000, 1000)
dxyRMS.color = 'b'
dxyRMS.drawstyle = 'PE'
dxyRMS.legendstyle = 'PE'
draw(dxyRMS, cDXYRMS, xtitle="m_{H}", ytitle="RMS(#Delta_{xy})", xlimits=(0.,2600.))
cDXYRMS.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/dxyRMS.png')
cDZ = Canvas(1000,1000)
draw(dzHists, cDZ, xtitle='#Delta_{z}',
ytitle='arb.')
legDZ = Legend(dzHists, cDZ, textsize=.03, entrysep=0.015, leftmargin=0.6, entryheight=0.04)
legDZ.Draw("same")
cDZ.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/dzs.png')
cDZRMS = Canvas(1000, 1000)
dzRMS.color = 'b'
dzRMS.drawstyle = 'PE'
dzRMS.legendstyle = 'PE'
draw(dzRMS, cDZRMS, xtitle="m_{H}", ytitle="RMS(#Delta_{z})", xlimits=(0.,2600.))
cDZRMS.Print('/afs/cern.ch/user/n/nawoods/www/sipStudy/dzRMS.png')
def main():
print('Number of arguments: ', len(sys.argv), 'arguments.')
print('Argument list:', str(sys.argv))
filename = "rootFiles/legotrain_CF_pPb_2305_20190109_LHC13bcde_minimal.root"
separate = 0
start = 2
end = 6
n_figs = end - start
Mixed_FullJets_R04 = datasetMixed(
"Full jets R=0.4",
NFIN=0,
range=(1, 5),
filename=filename,
directory='AliJJetJtTask/AliJJetJtHistManager',
directory2='AliJJetJtTask_kEMCEJE/AliJJetJtHistManager',
color=2,
style=24,
rebin=2)
compareHistsWithRatio(
Mixed_FullJets_R04,
['JtWeightBin', 'JtWeightLeadingRefBin', 'JtWeightLeadingRefBin'], [
'Jet axis ref.', 'leading ref. (xlong 0.0-0.2)',
'leading ref. (xlong 0.2-0.4)'
],
step=1,
start=1,
extras=['', 'Xlong00', 'Xlong01'])
plt.savefig("PythonFigures/JetVsLeadingRefConst.pdf",
format='pdf') #Save figure
plt.show()
sets = compareHistsWithRatio(
Mixed_FullJets_R04, [
'JetConeJtWeightBin', 'JetConeJtWeightLeadingRefBin',
'JetConeJtWeightLeadingRefBin', 'JetConeJtWeightLeadingRefBin',
'JetConeJtWeightLeadingRefBin'
], [
'Jet axis ref.', 'leading ref.(xlong 0.0-0.2)',
'leading ref.(xlong 0.2-0.4)', 'leading ref.(xlong 0.4-0.6)',
'leading ref. (xlong 0.6-1.0)'
],
step=1,
extras=['', 'Xlong00', 'Xlong01', 'Xlong02', 'Xlong03'])
plt.savefig("PythonFigures/JetVsLeadingRefJetCone.pdf",
format='pdf') #Save figure
plt.show()
JtJet = sets[0][0]
JtLeadingxlong00 = sets[1][0]
JtLeadingxlong01 = sets[2][0]
JtLeadingxlong02 = sets[3][0]
JtLeadingxlong03 = sets[4][0]
JtLeading = [h.clone() for h in sets[1][0]]
for h, s, s2, s3 in zip(JtLeading, sets[2][0], sets[3][0], sets[4][0]):
h.Add(s, 1)
h.Add(s2, 1)
h.Add(s3, 1)
jetPt = sets[0][1]
jetPtCenter = array('d', [(a + b) / 2.0 for a, b in jetPt])
jetPtErrors = array('d', [(b - a) / 2.0 for a, b in jetPt])
FullJets_fit = []
FullJets_parameters = []
FullJets_gausRMS = []
FullJets_gammaRMS = []
FullJets_gausYield = []
FullJets_gammaYield = []
for jT, title in zip(
(JtJet, JtLeading, JtLeadingxlong00, JtLeadingxlong01,
JtLeadingxlong02),
("Jet ref.", "Leading ref", "Leading ref.(xlong 0.0-0.2)",
"Leading ref.(xlong 0.2-0.4)", "Leading ref.(xlong 0.4-0.6)",
"Leading ref.(xlong 0.6-1.0)")):
gausRMS = []
gammaRMS = []
gausRMSe = []
gammaRMSe = []
gausYield = []
gammaYield = []
gausYielde = []
gammaYielde = []
fits = []
parameters = []
for h, i in zip(jT, range(Njets)):
fit, d = defs.fitJtHisto(h, '', 1, i, 8, title, draw=False)
fits.append(fit)
parameters.append(d)
gausRMS.append(d['gausRMS'])
gausRMSe.append(d['gausRMSe'])
gammaRMS.append(d['gammaRMS'])
gammaRMSe.append(d['gammaRMSe'])
gausYield.append(d['gausYield'])
gausYielde.append(d['gausYielde'])
gammaYield.append(d['gammaYield'])
gammaYielde.append(d['gammaYielde'])
gausRMSg = Graph(len(gausRMS) - 2)
gammaRMSg = Graph(len(gammaRMS) - 2)
gausYieldg = Graph(len(gausYield) - 2)
gammaYieldg = Graph(len(gammaYield) - 2)
for h, he, g in zip((gausYield, gammaYield), (gausYielde, gammaYielde),
(gausYieldg, gammaYieldg)):
for x, xe, a, e, i in zip(jetPtCenter[2:], jetPtErrors[2:], h[2:],
he[2:], range(len(gausRMS) - 2)):
g.SetPoint(i, x, a)
g.SetPointError(i, xe, xe, e, e)
for a, b, c, d, e, f, i in zip(gausRMS[2:], gammaRMS[2:], gausRMSe[2:],
gammaRMSe[2:],
jetPtCenter[2:], jetPtErrors[2:],
range(len(gausRMS) - 2)):
gausRMSg.SetPoint(i, e, a)
gausRMSg.SetPointError(i, f, f, c, c)
gammaRMSg.SetPoint(i, e, b)
gammaRMSg.SetPointError(i, f, f, d, d)
FullJets_gausRMS.append(gausRMSg)
FullJets_gammaRMS.append(gammaRMSg)
FullJets_gausYield.append(gausYieldg)
FullJets_gammaYield.append(gammaYieldg)
FullJets_fit.append(fits)
FullJets_parameters.append(parameters)
print(gausRMS[2:])
print(gammaRMS[2:])
print(jetPtCenter[2:])
drawWithErrors2Combined(FullJets_gausRMS, FullJets_gammaRMS, [
"Jet ref.", "Leading ref.", "Leading ref.(xlong 0.0-0.2)",
"Leading ref.(xlong 0.2-0.4)", "Leading ref.(xlong 0.4-0.6)"
], 15, 500, 1, 0, 1.85, 0, r'jet $p_T$', r'$\sqrt{\left<j_T^2\right>}$',
'Pythia',
'PythonFigures/JetVsLeadingRefJetConeFits')
if (separate > 0):
fig = plt.figure(1)
ax = fig.add_subplot(1, 1, 1)
ax.set_xscale('log')
ax.set_yscale('log')
ax.text(0.2,
0.0005,
d['system'] + '\n' + d['jettype'] + '\n' + d['jetalg'] +
'\n Jet Cone',
fontsize=7)
rplt.errorbar(signal[separate],
xerr=False,
emptybins=False,
axes=ax,
label="Jet axis reference",
fmt='o') #Plot jT histogram,
rplt.errorbar(signal2[separate],
xerr=False,
emptybins=False,
axes=ax,
label="Leading track reference",
fmt='o')
ax.text(
0.3, 1e2, r'$p_{{T,\mathrm{{jet}}}}$:'
'\n'
r' {:02d}-{:02d} GeV'.format(jetPt[separate][0],
jetPt[separate][1]))
ax.set_xlim([0.1, 12])
ax.set_ylim([5e-6, 1.5e3])
ax.legend(loc='lower left')
plt.savefig(
"PythonFigures/MixedFullJetsR04JetConeJtLeadingRefJetPt{0}.pdf".
format(separate),
format='pdf') #Save figure
plt.show() #Draw figure on screen
else:
n_rows = n_figs // 4
print(n_rows)
fig, axs = defs.makegrid(4,
2,
xlog=True,
ylog=True,
d=d,
shareY=False,
figsize=(10, 5))
axs = axs.reshape(8)
#axs[1].text(0.12,0.002,d['system'] +'\n'+ d['jettype'] +'\n'+ d['jetalg'] + '\n Jet Cone',fontsize = 7)
ratios = []
for jT, jT2, pT, ax, i in zip(JtJet[start:], JtLeading[start:],
jetPt[start:], axs[0:4], range(0, 9)):
jT.SetMarkerColor(1)
jT.SetMarkerStyle(24)
jT.SetLineColor(1)
#jT.SetMarkerSize(mSize)
jT2.SetMarkerColor(2)
jT2.SetMarkerStyle(25)
#jT2.SetMarkerSize(mSize)
jT2.SetLineColor(2)
ratio = jT2.Clone()
ratio.Divide(jT)
ratios.append(ratio)
plot = rplt.errorbar(jT,
xerr=False,
emptybins=False,
axes=ax,
label="Jet axis reference",
fmt='o',
fillstyle='none',
ecolor='black') #Plot jT histogram,
line = plot.get_children()[0]
line.set_markersize(mSize)
line.set_markerfacecolor('none')
plot = rplt.errorbar(jT2,
xerr=False,
emptybins=False,
axes=ax,
label="Leading track reference",
fmt='o',
fillstyle='none',
ecolor='red') #Plot jT histogram,
line = plot.get_children()[0]
line.set_markersize(mSize)
line.set_markerfacecolor('none')
#line.set_color(color)
ax.text(
0.3, 1e2, r'$p_{{T,\mathrm{{jet}}}}$:'
'\n'
r' {:02d}-{:02d} GeV'.format(pT[0], pT[1]))
ax.set_xlim([0.1, 22]) #Set x-axis limits
ax.set_ylim([5e-5, 2e3]) #Set y-axis limits
ax.set_xticklabels(ax.get_xticklabels(),
horizontalalignment='left')
for ratio, ax, i in zip(ratios, axs[4:], range(0, 9)):
plot = rplt.errorbar(ratio,
xerr=False,
emptybins=False,
axes=ax,
fmt='o',
fillstyle='none',
ecolor='black') #Plot jT histogram,
line = plot.get_children()[0]
line.set_markersize(mSize)
line.set_markerfacecolor('none')
ax.set_yscale('linear')
ax.set_xlim([0.1, 22]) #Set x-axis limits
ax.set_ylim([0, 5]) #Set y-axis limits
handles, labels = axs[0].get_legend_handles_labels()
handles = [
container.ErrorbarContainer(h, has_xerr=False, has_yerr=True)
if isinstance(h, container.ErrorbarContainer) else h
for h in handles
]
axs[0].legend(handles, labels, loc='lower left', numpoints=1)
axs[4].set_ylabel('Ratio')
axs[7].set_ylabel('Ratio')
plt.savefig(
"PythonFigures/MixedFullJetsR04JetConeJtLeadingRefPtFrom{}To{}.pdf"
.format(start, end),
format='pdf') #Save figure
plt.show() #Draw figure on screen
def draw_to_canvas(self):
"""
Draw this figure to a canvas, which is then returned.
"""
if len(self._plottables) == 0:
raise IndexError("No plottables defined")
c = Canvas(width=self.style.canvasWidth,
height=self.style.canvasHeight,
size_includes_decorations=True)
if self.legend.position == 'seperate':
legend_width = .2
pad_legend = Pad(1 - legend_width, 0, 1., 1., name="legend")
pad_legend.SetLeftMargin(0.0)
pad_legend.SetFillStyle(0) # make this pad transparent
pad_legend.Draw()
else:
legend_width = 0
pad_plot = Pad(
0.,
0.,
1 - legend_width,
1.,
name="plot",
)
pad_plot.SetMargin(*self.style.plot_margins)
pad_plot.Draw()
pad_plot.cd()
# awkward hack around a bug in get limits where everything fails if one plottable is shitty...
xmin, xmax, ymin, ymax = None, None, None, None
for pdic in self._plottables:
try:
limits = get_limits(pdic['p'],
logx=self.plot.logx,
logy=self.plot.logy)
# Beware: Python 2 evaluates min/max of None in an undefined way with no error! Wow...
xmin = min([xmin, limits[0]
]) if xmin is not None else limits[0]
xmax = max([xmax, limits[1]
]) if xmax is not None else limits[1]
ymin = min([ymin, limits[2]
]) if ymin is not None else limits[2]
ymax = max([ymax, limits[3]
]) if ymax is not None else limits[3]
except (TypeError, ValueError):
# some plottables do not work with this rootpy function (eg. graph without points, tf1)
# TODO: should be fixed upstream
pass
# overwrite these ranges if defaults are given
if self.plot.xmin is not None:
xmin = self.plot.xmin
if self.plot.xmax is not None:
xmax = self.plot.xmax
if self.plot.ymax is not None:
ymax = self.plot.ymax
if self.plot.ymin is not None:
ymin = self.plot.ymin
if not all([val is not None for val in [xmin, xmax, ymin, ymax]]):
raise TypeError(
"unable to determine plot axes ranges from the given plottables"
)
colors = get_color_generator(self.plot.palette,
self.plot.palette_ncolors)
# draw an empty frame within the given ranges;
frame_from_plottable = [
p for p in self._plottables if p.get('use_as_frame')
]
if len(frame_from_plottable) > 0:
frame = frame_from_plottable[0]['p'].Clone('__frame')
frame.Reset()
frame.SetStats(0)
frame.xaxis.SetRangeUser(xmin, xmax)
frame.yaxis.SetRangeUser(ymin, ymax)
frame.GetXaxis().SetTitle(self.xtitle)
frame.GetYaxis().SetTitle(self.ytitle)
self._theme_plottable(frame)
frame.Draw()
else:
frame = Graph()
frame.SetName("__frame")
# add a silly point in order to have root draw this frame...
frame.SetPoint(0, 0, 0)
frame.GetXaxis().SetLimits(xmin, xmax)
frame.GetYaxis().SetLimits(ymin, ymax)
frame.SetMinimum(ymin)
frame.SetMaximum(ymax)
frame.GetXaxis().SetTitle(self.xtitle)
frame.GetYaxis().SetTitle(self.ytitle)
self._theme_plottable(frame)
# Draw this frame: 'A' should draw the axis, but does not work if nothing else is drawn.
# L would draw a line between the points but is seems to do nothing if only one point is present
# P would also draw that silly point but we don't want that!
frame.Draw("AL")
xtick_length = frame.GetXaxis().GetTickLength()
ytick_length = frame.GetYaxis().GetTickLength()
for i, pdic in enumerate(self._plottables):
obj = pdic['p']
if isinstance(obj, ROOT.TLegendEntry):
_root_color = Color(pdic['color'])
_root_markerstyle = MarkerStyle(pdic['markerstyle'])
obj.SetMarkerStyle(_root_markerstyle('root'))
obj.SetMarkerColor(_root_color('root'))
elif isinstance(obj, (ROOT.TH1, ROOT.TGraph, ROOT.TF1)):
self._theme_plottable(obj)
obj.SetMarkerStyle(pdic.get('markerstyle', 'circle'))
if pdic.get('color', None):
obj.color = pdic['color']
else:
try:
color = next(colors)
except StopIteration:
log.warning("Ran out of colors; defaulting to black")
color = 1
obj.color = color
xaxis = obj.GetXaxis()
yaxis = obj.GetYaxis()
# Set the title to the given title:
obj.title = self.title
# the xaxis depends on the type of the plottable :P
if isinstance(obj, ROOT.TGraph):
# SetLimit on a TH1 is simply messing up the
# lables of the axis to screw over the user, presumably...
xaxis.SetLimits(xmin, xmax)
yaxis.SetLimits(ymin, ymax) # for unbinned data
# 'P' plots the current marker, 'L' would connect the dots with a simple line
# see: https://root.cern.ch/doc/master/classTGraphPainter.html for more draw options
drawoption = 'Psame'
elif isinstance(obj, ROOT.TH1):
obj.SetStats(0)
xaxis.SetRangeUser(xmin, xmax)
yaxis.SetRangeUser(ymin, ymax)
drawoption = 'same'
elif isinstance(obj, ROOT.TF1):
# xaxis.SetLimits(xmin, xmax)
# yaxis.SetLimits(ymin, ymax) # for unbinned data
drawoption = 'same'
obj.Draw(drawoption)
# Its ok if obj is non; then we just add it to the legend.
else:
raise TypeError("Un-plottable type given.")
pad_plot.SetTicks()
pad_plot.SetLogx(self.plot.logx)
pad_plot.SetLogy(self.plot.logy)
pad_plot.SetGridx(self.plot.gridx)
pad_plot.SetGridy(self.plot.gridy)
# do we have legend titles?
if any([pdic.get('legend_title') for pdic in self._plottables]):
leg = self._create_legend()
longest_label = 0
for pdic in self._plottables:
if not pdic.get('legend_title', False):
continue
leg.AddEntry(pdic['p'], pdic['legend_title'])
if len(pdic['legend_title']) > longest_label:
longest_label = len(pdic['legend_title'])
# Set the legend position
# vertical:
if self.legend.position.startswith('t'):
leg_hight = leg.y2 - leg.y1
leg.y2 = 1 - pad_plot.GetTopMargin() - ytick_length
leg.y1 = leg.y2 - leg_hight
elif self.legend.position.startswith('b'):
leg_hight = leg.y2 - leg.y1
leg.y1 = pad_plot.GetBottomMargin() + ytick_length
leg.y2 = leg.y1 + leg_hight
# horizontal:
if self.legend.position[1:].startswith('l'):
leg_width = 0.3
leg.x1 = pad_plot.GetLeftMargin() + xtick_length
leg.x2 = leg.x1 + leg_width
elif self.legend.position[1:].startswith('r'):
leg_width = 0.3
leg.x2 = 1 - pad_plot.GetRightMargin() - xtick_length
leg.x1 = leg.x2 - leg_width
if self.legend.position == 'seperate':
with pad_legend:
leg.Draw()
else:
leg.Draw()
if self.plot.logx:
pad_plot.SetLogx(True)
if self.plot.logy:
pad_plot.SetLogy(True)
pad_plot.Update(
) # needed sometimes with import of canvas. maybe because other "plot" pads exist...
return c
# Find best fit point within axes
point_bf = Graph(
1,
drawstyle='p',
markerstyle=34,
markercolor='black',
markersize=2,
legendstyle='p',
title="Best fit",
)
best_fit = [
(getattr(p, xpoi), getattr(p, ypoi)) for p in scan.copy_tree(
'{}==0 & 0.8<{}<1.2 & 0.9<{}<1.3'.format(zparam, xpoi, ypoi), )
]
point_bf.SetPoint(1, *best_fit[0])
# Make contours: 68 and 95%
cont_1sig = prof.Clone()
cont_1sig.linewidth = 2
cont_1sig.linecolor = "black"
cont_1sig.legendstyle = 'l'
cont_1sig.title = "68% CL"
cont_2sig = cont_1sig.Clone()
cont_2sig.linestyle = 2
cont_2sig.legendstyle = 'l'
cont_2sig.title = "95% CL"
cont_1sig.SetContour(1, np.array([chi2_2df_one_sigma]))
cont_2sig.SetContour(1, np.array([chi2_2df_two_sigma]))
Hist(100, -5, 5, color='salmon',
drawstyle='hist').FillRandom(F1('TMath::Gaus(x, 2, 1)'), 500))
stack.Add(
Hist(100, -5, 5, color='powderblue',
drawstyle='hist').FillRandom(F1('TMath::Gaus(x, 2, 0.6)'), 300))
objects.append(stack)
# create some random histograms
for i, (mu, sigma, n, c,
s) in enumerate(zip(mus, sigmas, events, colors, styles)):
hist = Hist(100,
-5,
5,
color=c,
fillstyle=s,
drawstyle='hist' if i % 2 == 0 else '')
hist.FillRandom(F1('TMath::Gaus(x,{0},{1})'.format(mu, sigma)), n)
objects.append(hist)
# create a graph
graph = Graph(10, drawstyle='P')
for i in range(10):
x = -2 + i * 4 / 10.
graph.SetPoint(i, x, 40 + 10 * sin(x))
objects.append(graph)
draw(objects, xtitle='Some Variable [Units]', ytitle='Events', ypadding=0.05)
# see rootpy.plotting.utils.get_limits for details on what arguments are
# supported for setting the axes ranges.
wait()
#
ROOT.gStyle.SetOptStat(0)
fitfile = root_open('%s/MaxLikeFit.root' % basedir)
fit = fitfile.fit_s
pars = asrootpy(fit.floatParsFinal())
fitted = None
if args.conly:
fitted = ROOT.TArrow(pars['charmSF'].value, 2, pars['charmSF'].value, 1,
0.025, '|>')
fitted.SetLineWidth(3)
fitted.SetLineColor(ROOT.kBlue)
fitted.SetFillColor(ROOT.kBlue)
else:
fitted = Graph(1)
fitted.SetPoint(0, pars['charmSF'].value, pars['lightSF'].value)
fitted.markerstyle = 20
fitted.markersize = 3
fitted.markercolor = '#009600'
def addlabels(h):
h.xaxis.title = 'charm SF'
h.yaxis.title = 'light SF'
h.xaxis.SetTitleOffset(0.9)
h.yaxis.SetTitleOffset(1.2 if args.conly else 1.)
addlabels(cbias)
addlabels(failing)
addlabels(ccover)
