def rebin(histogram, binning):
''' Rebin a histogram
[binning] can be either an integer, or a list/tuple for variable bin
sizes.
'''
# Just merging bins
if isinstance(binning, int):
if binning == 1 or isinstance(histogram, ROOT.TH2):
return histogram
histogram.Rebin(binning)
return histogram
# Fancy variable size bins
if isinstance(histogram, ROOT.TH2):
if not isinstance(binning[0], (list, tuple)):
return histogram
#print binning[0], ' ' , binning[1]
bin_arrayx = binning[0] #array.array('d',binning[0])
bin_arrayy = binning[1] #array.array('d',binning[1])
if len(binning[0]) ==1 and len(binning[1])==1 :
return asrootpy(histogram.Rebin2D(int(binning[0][0]),int(binning[1][0]), histogram.GetName() + 'rebin'))
else:
return RebinView.newRebin2D(histogram, bin_arrayx, bin_arrayy)
elif isinstance(histogram, ROOT.TH1):
if isinstance(binning[0], (list, tuple)):
raise ValueError(
"You are providing a binning scheme (%s) "
"not compatible with 1D hists!" % (binning.__repr__()))
bin_array = array.array('d', binning)
ret = asrootpy( histogram.Rebin(len(binning)-1, histogram.GetName() + 'rebin', bin_array) )
if hasattr(histogram, 'decorators'):
ret.decorate( **histogram.decorators )
return ret
else:
raise ValueError('ERROR in RebinView: not a TH1 or TH2 histo. Rebin not done')
return histogram
def Get(self, path):
hist = self.input.Get(path)
if not isinstance(hist, (ROOT.TH2, ROOT.TH3)):
return hist #nothin to do
projection_axis = 'X' if self.axis.upper() == 'Y' else 'Y'
axis = getattr(hist, 'Get%saxis' % projection_axis)()
min_bin = axis.FindFixBin(self.range[0])
max_bin = axis.FindFixBin(self.range[1])
if axis.GetBinLowEdge(max_bin) == self.range[1]:
max_bin -= 1
output = getattr(hist, 'Projection%s' % self.axis.upper())(hist.GetName() + '_projection', min_bin, max_bin)
output = asrootpy( output )
#print "ProjectionView: path %s, minimum:%.2f --> %i, maximum:%.2f --> %i, integral: %.3f entries: %i" % (path, self.range[0], min_bin, self.range[1], max_bin, output.Integral(), output.GetEntries())
output.decorate( **hist.decorators )
output.SetTitle( hist.GetTitle() )
#print hist.GetTitle(), output.GetTitle()
return output
def Get(self, path):
hist = self.input.Get(path)
if not isinstance(hist, (ROOT.TH2, ROOT.TH3)):
return hist #nothin to do
projection_axis = 'X' if self.axis.upper() == 'Y' else 'Y'
axis = getattr(hist, 'Get%saxis' % projection_axis)()
min_bin = axis.FindFixBin(self.range[0])
max_bin = axis.FindFixBin(self.range[1])
if axis.GetBinLowEdge(max_bin) == self.range[1]:
max_bin -= 1
output = getattr(hist, 'Projection%s' % self.axis.upper())(
hist.GetName() + '_projection', min_bin, max_bin)
output = asrootpy(output)
#print "ProjectionView: path %s, minimum:%.2f --> %i, maximum:%.2f --> %i, integral: %.3f entries: %i" % (path, self.range[0], min_bin, self.range[1], max_bin, output.Integral(), output.GetEntries())
output.decorate(**hist.decorators)
output.SetTitle(hist.GetTitle())
#print hist.GetTitle(), output.GetTitle()
return output
def rebin(self, histogram, binning):
''' Rebin a histogram
[binning] can be either an integer, or a list/tuple for variable bin
sizes.
'''
# Just merging bins
if isinstance(binning, int):
if binning == 1 or isinstance(histogram, ROOT.TH2):
return histogram
histogram.Rebin(binning)
return histogram
# Fancy variable size bins
if isinstance(histogram, ROOT.TH2):
if not isinstance(binning[0], (list, tuple)):
return histogram
#print binning[0], ' ' , binning[1]
bin_arrayx = binning[0] #array.array('d',binning[0])
bin_arrayy = binning[1] #array.array('d',binning[1])
if len(binning[0]) == 1 and len(binning[1]) == 1:
return histogram.Rebin2D(int(binning[0][0]),
int(binning[1][0]),
histogram.GetName() + 'rebin')
else:
return self.newRebin2D(histogram, bin_arrayx, bin_arrayy)
elif isinstance(histogram, ROOT.TH1):
if isinstance(binning[0], (list, tuple)):
return histogram
bin_array = array.array('d', binning)
ret = asrootpy(
histogram.Rebin(
len(binning) - 1,
histogram.GetName() + 'rebin', bin_array))
if hasattr(histogram, 'decorators'):
ret.decorate(**histogram.decorators)
return ret
else:
print 'ERROR in RebinView: not a TH1 or TH2 histo. Rebin not done'
return histogram
def rebin(self, histogram, binning):
''' Rebin a histogram
[binning] can be either an integer, or a list/tuple for variable bin
sizes.
'''
# Just merging bins
if isinstance(binning, int):
if binning == 1 or isinstance(histogram, ROOT.TH2):
return histogram
histogram.Rebin(binning)
return histogram
# Fancy variable size bins
if isinstance(histogram, ROOT.TH2):
if not isinstance(binning[0], (list, tuple)):
return histogram
#print binning[0], ' ' , binning[1]
bin_arrayx = binning[0] #array.array('d',binning[0])
bin_arrayy = binning[1] #array.array('d',binning[1])
if len(binning[0]) ==1 and len(binning[1])==1 :
return histogram.Rebin2D(int(binning[0][0]),int(binning[1][0]), histogram.GetName() + 'rebin')
else:
return self.newRebin2D(histogram, bin_arrayx, bin_arrayy)
elif isinstance(histogram, ROOT.TH1):
if isinstance(binning[0], (list, tuple)):
return histogram
bin_array = array.array('d', binning)
ret = asrootpy( histogram.Rebin(len(binning)-1, histogram.GetName() + 'rebin', bin_array) )
if hasattr(histogram, 'decorators'):
ret.decorate( **histogram.decorators )
return ret
else:
print 'ERROR in RebinView: not a TH1 or TH2 histo. Rebin not done'
return histogram
from rootpy.plotting import Canvas, Legend, HistStack
from FinalStateAnalysis.Utilities.AnalysisPlotter import styling,samplestyles
import rootpy.io as io
import FinalStateAnalysis.StatTools.poisson as poisson
# This stuff is just so we can get matching styles as analysis.py
import FinalStateAnalysis.PatTools.data as data_tool
int_lumi = 5000
skips = ['DoubleEl', 'EM']
samples, plotter = data_tool.build_data(
'VH', '2012-04-14-v1-WHAnalyze', 'scratch_results',
int_lumi, skips, count='emt/skimCounter')
# Get stupid templates to build the styles automatically
signal = asrootpy(plotter.get_histogram(
'VH120',
'emt/skimCounter',
).th1)
wz = asrootpy(plotter.get_histogram(
'WZ',
'emt/skimCounter',
).th1)
zz = asrootpy(plotter.get_histogram(
'ZZ',
'emt/skimCounter',
).th1)
fakes_myhist = asrootpy(plotter.get_histogram(
'Zjets',
'emt/skimCounter',
if args.plot:
canvas = ROOT.TCanvas("asdf", "asdf", 800, 600)
canvas.SetLogz(True)
myeff.Draw("LEGO")
efficiency.Draw("SURFSAME")
# import pdb; pdb.set_trace()
canvas.SaveAs(args.output)
plot_name = args.output.replace('.root', '.png')
# log.info("Saving fit plot in %s", plot_name)
canvas.SaveAs(plot_name)
canvas.SaveAs(plot_name.replace('.png', '.pdf'))
canvas.SetLogz(False)
canvas.SetLogy(True)
graph_proj_x = asrootpy( myeff.Projection(ROOT.TEfficiencyBugFixed.xaxis) )
graph_proj_x.SetMarkerStyle(20)
graph_proj_x.title = 'data'
fcn_proj_x = asrootpy( myeff.ProjectFunction(ROOT.TEfficiencyBugFixed.xaxis, all_histo_finebin) ) \
if all_histo_finebin else \
asrootpy( myeff.ProjectFunction(ROOT.TEfficiencyBugFixed.xaxis) )
print graph_proj_x, fcn_proj_x
fcn_proj_x.SetName('fcn_proj_x')
fcn_proj_x.SetFillStyle(0)
fcn_proj_x.Draw('AL')
graph_proj_x.Draw('P SAME')
plot_name = plot_name.replace('.png', '_projX.png')
canvas.SaveAs(plot_name)
canvas.SaveAs(plot_name.replace('.png', '.pdf'))
graph_proj_y = asrootpy( myeff.Projection(ROOT.TEfficiencyBugFixed.yaxis) )
def apply_view(self, histo):
graph = poisson.convert(histo, self.x_err, self.set_zero_bins, self.is_scaled)
graph.SetMarkerSize(self.marker_size)
return asrootpy(graph)
value = var_d[var]
hist_maps[var]['estimate'].Fill(value, mva*weight)
hist_maps[var]['all'].Fill(value, weight)
hist_maps[var]['estimate_all'].Fill(value, weight)
if cut:
hist_maps[var]['pass'].Fill(value, weight)
canvas = plotting.Canvas(name='adsf', title='asdf')
canvas.SetLogy(True)
for var in args.variables:
for key in hist_maps[var].iterkeys():
hist_maps[var][key] = round_to_ints(hist_maps[var][key])
eff = asrootpy( ROOT.TGraphAsymmErrors( hist_maps[var]['pass'], hist_maps[var]['all']) )
eff.markerstyle = 20
estimate = hist_maps[var]['estimate'].Clone() #avoid getting divided
estimate.Divide(hist_maps[var]['estimate_all'])
estimate.linecolor = ROOT.kBlue
estimate.linewidth = 2
estimate.fillstyle = 0
estimate.drawstyle = 'hist'
estimate.Draw()
eff.Draw('P same')
canvas.Update()
canvas.SetLogy(True)
canvas.SaveAs( output_file.replace('.root', '.%s.png' % var ) )
for key, obj in hist_maps[var].iteritems():
def apply_view(self, histo):
graph = poisson.convert(histo, self.x_err, self.set_zero_bins,
self.is_scaled)
graph.SetMarkerSize(self.marker_size)
return asrootpy(graph)
# write some histograms
h1 = Hist(100, 0, 100, name='h1', type='I')
# variable bin widths
h2 = Hist2D((0, 3, 5, 20, 50), (10, 20, 30, 40, 1000), name='h2')
h1.Write()
h2.Write()
# file is automatically closed after with statement
# retrieve the histograms previously saved
with open('data.root') as f:
h1 = f.h1
# or h1 = f.Get('h1')
h2 = f.h2
# or h2 = f.Get('h2')
# ROOT classes are automatically converted into
# rootpy form when retrieved from a ROOT file as
# long as their module was previously imported
print h1.__class__.__name__
print h2.__class__.__name__
# you may also do this to convert an object into
# rootpy form (again, assuming the relevant module
# was previously imported)
h1 = asrootpy(h1)
# if it is already in rootpy form or if no rootpy form
# exists then asrootpy does nothing
print h1.__class__.__name__
binning = int(args.rebin)
input_view = RebinView(input_view, binning)
log.info("Getting histograms")
pass_histo = input_view.Get(args.num)
all_histo = input_view.Get(args.denom)
#canvas = ROOT.TCanvas("asdf", "asdf", 800, 600)
#pass_histo.Draw()
#canvas.SaveAs( args.output.replace(".root", "numerator.root"))
#all_histo.Draw()
#canvas.SaveAs(args.output.replace(".root", "denominator.root"))
##make slice if necessary
if args.slice: #maybe a check if is 2d would be a good thing
log.info("Slicing! Slice #%s" % args.slice)
#project
pass_histo_px = asrootpy( pass_histo.ProjectionX('pass_histo_px', args.slice, args.slice, "e") )
all_histo_px = asrootpy( all_histo.ProjectionX('all_histo_px', args.slice, args.slice, "e") )
#get rootpy plotting stuff
pass_histo_px.decorate( **pass_histo.decorators )
all_histo_px.decorate( **all_histo.decorators )
#reassign variables
pass_histo = pass_histo_px
all_histo = all_histo_px
if not all_histo.Integral():
log.info("no entries in denominator!")
else:
log.info("pass/all = %0.0f/%0.0f = %0.2f%%",
if weight > 0: #fill only data-like events
hist_maps[var]['estimate'].Fill(value, weight*mva)
hist_maps[var]['estimate_all'].Fill(value, weight)
hist_maps[var]['all'].Fill(value, weight)
if cut:
hist_maps[var]['pass'].Fill(value, weight)
canvas = plotting.Canvas(name='adsf', title='asdf')
canvas.SetLogy(True)
for var in args.variables:
for key in ['pass', 'all']: #hist_maps[var].iterkeys():
hist_maps[var][key] = round_to_ints(hist_maps[var][key])
eff = asrootpy( ROOT.TGraphAsymmErrors( hist_maps[var]['pass'], hist_maps[var]['all']) )
eff.markerstyle = 20
eff.SetName('efficiency_%s' % var)
estimate = hist_maps[var]['estimate'].Clone() #avoid getting divided
estimate.Divide(hist_maps[var]['estimate_all'])
estimate.SetName('estimate_%s' % var)
estimate.linecolor = ROOT.kBlue
estimate.linewidth = 2
estimate.fillstyle = 0
estimate.drawstyle = 'hist'
estimate.Draw()
eff.Draw('P same')
canvas.Update()
canvas.SetLogy(True)
canvas.SaveAs( output_file.replace('.root', '.%s.png' % var ) )
import FinalStateAnalysis.StatTools.limitplot as limitplot
import FinalStateAnalysis.Utilities.styling as styling
print args.plot1, args.plot4
plots_to_comp = []
key = (args.method, args.label)
xmin = 1e9
xmax = -1e9
for plot in [args.plot1, args.plot2, args.plot3, args.plot4]:
if plot:
the_glob, title, type, color = tuple(plot)
limit_data = limitplot.get_limit_info(glob.glob(the_glob))
tgraph = asrootpy(limitplot.build_line(limit_data, key, type))
print tgraph
tgraph.SetLineColor(color)
plots_to_comp.append((tgraph, title))
xmin = min(min(limit_data[key].keys()), xmin)
xmax = max(max(limit_data[key].keys()), xmax)
canvas = ROOT.TCanvas("c", "c", args.cx, args.cy)
if args.maxx > 0:
xmax = args.maxx
frame = ROOT.TH1F("frame", "frame", 1, xmin, xmax)
frame.Draw()
#frame.SetTitle("WH(#tau#tau) limits [4.6 fb^{-1}]")
if args.plot:
canvas = ROOT.TCanvas("asdf", "asdf", 800, 600)
canvas.SetLogz(True)
myeff.Draw("LEGO")
efficiency.Draw("SURFSAME")
# import pdb; pdb.set_trace()
canvas.SaveAs(args.output)
plot_name = args.output.replace('.root', '.png')
# log.info("Saving fit plot in %s", plot_name)
canvas.SaveAs(plot_name)
canvas.SaveAs(plot_name.replace('.png', '.pdf'))
canvas.SetLogz(False)
canvas.SetLogy(True)
graph_proj_x = asrootpy(
myeff.Projection(ROOT.TEfficiencyBugFixed.xaxis))
graph_proj_x.SetMarkerStyle(20)
graph_proj_x.title = 'data'
fcn_proj_x = asrootpy( myeff.ProjectFunction(ROOT.TEfficiencyBugFixed.xaxis, all_histo_finebin) ) \
if all_histo_finebin else \
asrootpy( myeff.ProjectFunction(ROOT.TEfficiencyBugFixed.xaxis) )
print graph_proj_x, fcn_proj_x
fcn_proj_x.SetName('fcn_proj_x')
fcn_proj_x.SetFillStyle(0)
fcn_proj_x.Draw('AL')
graph_proj_x.Draw('P SAME')
plot_name = plot_name.replace('.png', '_projX.png')
canvas.SaveAs(plot_name)
canvas.SaveAs(plot_name.replace('.png', '.pdf'))
graph_proj_y = asrootpy(
# write some histograms
h1 = Hist(100, 0, 100, name='h1', type='I')
# variable bin widths
h2 = Hist2D((0,3,5,20,50), (10,20,30,40,1000), name='h2')
h1.Write()
h2.Write()
# file is automatically closed after with statement
# retrieve the histograms previously saved
with open('data.root') as f:
h1 = f.h1
# or h1 = f.Get('h1')
h2 = f.h2
# or h2 = f.Get('h2')
# ROOT classes are automatically converted into
# rootpy form when retrieved from a ROOT file as
# long as their module was previously imported
print h1.__class__.__name__
print h2.__class__.__name__
# you may also do this to convert an object into
# rootpy form (again, assuming the relevant module
# was previously imported)
h1 = asrootpy(h1)
# if it is already in rootpy form or if no rootpy form
# exists then asrootpy does nothing
print h1.__class__.__name__
if ',' in args.rebin:
binning = tuple(int(x) for x in args.rebin.split(','))
else:
binning = int(args.rebin)
input_view = RebinView(input_view, binning)
log.info("Getting histograms")
pass_histo = input_view.Get(args.num)
all_histo = input_view.Get(args.denom)
#make slice if necessary
if args.slice: #maybe a check if is 2d would be a good thing
log.info("Slicing! Slice #%s" % args.slice)
#project
pass_histo_px = asrootpy(
pass_histo.ProjectionX('pass_histo_px', args.slice, args.slice,
"e"))
all_histo_px = asrootpy(
all_histo.ProjectionX('all_histo_px', args.slice, args.slice, "e"))
#get rootpy plotting stuff
pass_histo_px.decorate(**pass_histo.decorators)
all_histo_px.decorate(**all_histo.decorators)
#reassign variables
pass_histo = pass_histo_px
all_histo = all_histo_px
if not all_histo.Integral():
log.info("no entries in denominator!")
else: