purGraph = TGraphErrors(len(_NumberOfProtons), _NumberOfProtons, _Purity,
_NumberOfProtonsErr, _PurityErr)
purGraph.SetMarkerStyle(5)
purGraph.SetLineColor(2)
purGraph.SetMarkerColor(2)
purGraph.SetMarkerSize(2)
purGraph.GetXaxis().SetTitle("Mean N Proton")
purGraph.GetYaxis().SetTitle("Purity")
purGraph.SetTitle("Purity")
MyFile = TFile(
"effVsPurity_bs" + (str)(beamSpread) + "mrad_geo" + geoName +
"_RestrictTracks" + (str)(restrictNTracks) + "_pitch" + (str)(pitch) +
".root", "RECREATE")
mg = TMultiGraph()
mg.SetTitle("Efficiency and Purity vs nProtons;Mean N Protons; (%)")
mg.Add(effGraph, "lp")
mg.Add(purGraph, "lp")
mg.Draw("a")
effGraph.Write()
purGraph.Write()
mg.Write()
legend = TLegend(0.1, 0.7, 0.48, 0.9)
legend.AddEntry(effGraph, "Efficiency", "lp")
legend.AddEntry(purGraph, "Purity", "lp")
legend.Draw("SAME")
canvas1.Write("EffVsPurity")
def collectPerDirectionBx(options):
"""Fit data in both directions of a scan"""
nSteps = len(O['nominalPos'][options['scan']])
for i in range(nSteps - 1):
if O['nominalPos'][options['scan']][i+1] == \
O['nominalPos'][options['scan']][i]:
break
else:
for i in range(nSteps - 1):
if abs(O['nominalPos'][options['scan']][i+1] - \
O['nominalPos'][options['scan']][i]) < 10.0:
break
else:
raise RuntimeError('Could not find change of direction.')
if 'nominalPos' in options:
nominalPos = options['nominalPos']
else:
nominalPos = O['nominalPos'][options['scan']]
oldname = options['scan'] + '_' + options['name'] + options['fitted']
if options.get('newname', False):
newname = options['scan'] + '_' + options['newname'] + \
options['fitted']
else:
newname = oldname
if options.get('method', False):
oldname += '_' + options['method']
newname += '_' + options['method']
newname += '_collected'
f = openRootFileR(oldname)
g = openRootFileW(newname)
for bx in options['crossings']:
average = [0 for j in range(nSteps)]
averror = [0 for j in range(nSteps)]
for step in range(nSteps):
print '<<< Access data from:', options['scan'], bx, 'step', step
histname = plotName(oldname+'_bx'+str(bx)+'_step'+str(step), \
timestamp=False)
hist = f.Get(histname)
if options['custom']:
average[step], averror[step] = options['custom'](hist, step)
else:
average[step] = hist.GetMean()
averror[step] = hist.GetMeanError()
plotname = plotName(newname + '_bx' + str(bx), timestamp=False)
plottitl = plotTitle(options['scan'] + ' BX ' + str(bx))
print '<<< Create plot:', plotname
graphs = TMultiGraph(plotname, plottitl)
residuals = TMultiGraph(plotname + '_residuals', '')
for n, rnge in zip([i+1, nSteps-i-1], [lambda l: l[:i+1], \
lambda l: l[i+1:]]):
graph = TGraphErrors(n, \
array('d', [options['x'](a) for a in rnge(nominalPos)]), \
array('d', [options['y'](a) for a in rnge(average)]), \
array('d', [0]*n), \
array('d', [options['e'](a) for a in rnge(averror)]))
graph.Fit(options['fit'])
residual = TGraphErrors(n, \
array('d', [options['x'](a) for a in rnge(nominalPos)]), \
array('d', [options['y'](a) - graph.GetFunction( \
options['fit']).Eval(options['x'](b)) for a, b \
in zip(rnge(average), rnge(nominalPos))]),
array('d', [0]*n), \
array('d', [options['e'](a) for a in rnge(averror)]))
graphs.Add(graph)
residuals.Add(residual)
graphs.Write('', TObject.kOverwrite)
residuals.Write('', TObject.kOverwrite)
closeRootFile(g, newname)
closeRootFile(f, oldname)
def plotDistributionComparisonPlot(cfg):
multiGraph = TMultiGraph()
multiGraph.SetName("triggerRateMultiGraph")
tfiles = []
histograms = []
canvas = TCanvas("canvas", "canvas", 800, 800)
'''Contains the legend'''
legend = TLegend(0.3, 0.7, 0.90, 0.9)
'''Maximum value container, used to scale histograms'''
maximumY = float("-inf")
pad1 = TPad("pad1", "pad1", 0, 0.3, 1, 1.0)
pad1.SetBottomMargin(0.05) # Upper and lower plot are joined
#pad1.SetBottomMargin(0) # Upper and lower plot are joined
pad1.SetGridx() # Vertical grid
pad1.Draw() # Draw the upper pad: pad1
pad1.cd() # pad1 becomes the current pad
for histogramFileNameAndTitle in cfg.plots:
tfile = TFile(histogramFileNameAndTitle[0])
tfiles.append(tfile)
histogram = tfile.Get(histogramFileNameAndTitle[1])
histograms.append(histogram)
if histogram.ClassName() == "TH1F":
histogram.SetStats(0) # No statistics on upper plot
maximumY = histogram.GetMaximum(
) if histogram.GetMaximum() > maximumY else maximumY
legend.AddEntry(histogram, histogramFileNameAndTitle[2], "l")
# histograms[0] settings
histograms[0].SetMarkerColor(4)
histograms[0].SetLineColor(4)
histograms[0].SetLineWidth(1)
# Y axis histograms[0] plot settings
histograms[0].GetYaxis().SetTitleSize(20)
histograms[0].GetYaxis().SetTitleFont(43)
histograms[0].GetYaxis().SetTitleOffset(1.55)
#histograms[0].Scale(1./histograms[0].GetEntries())
if histograms[0].ClassName() == "TH1F":
histograms[0].Draw(
"SAME HIST") # Draw histograms[1] on top of histograms[0]
else:
histograms[0].Draw(
"SAME APE") # Draw histograms[1] on top of histograms[0]
#multiGraph.Add(histograms[0])
if getattr(cfg, "xRange", None) is not None:
histograms[0].GetXaxis().SetRangeUser(cfg.xRange[0], cfg.xRange[1])
gPad.RedrawAxis()
if getattr(cfg, "xAxisLabel", None) is not None:
histograms[0].GetXaxis().SetTitle(cfg.xAxisLabel)
gPad.RedrawAxis()
if getattr(cfg, "yAxisLabel", None) is not None:
histograms[0].GetYaxis().SetTitle(cfg.yAxisLabel)
gPad.RedrawAxis()
if getattr(cfg, "yRange", None) is not None:
histograms[0].GetYaxis().SetRangeUser(cfg.yRange[0], cfg.yRange[1])
gPad.RedrawAxis()
else:
maximumY *= 1.1
histograms[0].GetYaxis().SetRangeUser(1e-6, maximumY)
if getattr(cfg, "logY", False):
canvas.SetLogy()
# histograms[1] settings
histograms[1].SetMarkerColor(2)
histograms[1].SetLineColor(2)
histograms[1].SetLineWidth(1)
#histograms[1].Scale(1./histograms[1].GetEntries())
if histograms[1].ClassName() == "TH1F":
histograms[1].Draw(
"SAME HIST") # Draw histograms[1] on top of histograms[0]
else:
histograms[1].Draw(
"SAME PE") # Draw histograms[1] on top of histograms[0]
#multiGraph.Add(histograms[1])
#if multiGraph.GetListOfGraphs() != None:
# multiGraph.Draw("SAME PE")
# Do not draw the Y axis label on the upper plot and redraw a small
# axis instead, in order to avoid the first label (0) to be clipped.
#histograms[0].GetYaxis().SetLabelSize(0.)
#axis = TGaxis( 0, 20, 0, maximumY, 20, maximumY, 510,"")
#axis.SetLabelFont(43) # Absolute font size in pixel (precision 3)
#axis.SetLabelSize(15)
#axis.Draw()
# Adding a small text with the chi-squared
chiSquared = 0
if (histograms[0].ClassName() == "TGraph") or (histograms[0].ClassName()
== "TGraphErrors"):
numberOfBins = histograms[0].GetN()
numberOfDegreesOfFreedom = numberOfBins
else:
numberOfBins = histograms[0].GetNbinsX()
numberOfDegreesOfFreedom = numberOfBins
for x in xrange(
1, numberOfBins + 1
): # numberOfBins contains last bin, numberOfBins+1 contains the overflow (latter excluded), underflow also excluded
if (histograms[0].ClassName()
== "TGraph") or (histograms[0].ClassName() == "TGraphErrors"):
binContent0 = histograms[0].GetY()[x - 1]
else:
binContent0 = histograms[0].GetBinContent(x)
if (histograms[1].ClassName()
== "TGraph") or (histograms[1].ClassName() == "TGraphErrors"):
binContent1 = histograms[1].GetY()[x - 1]
else:
binContent1 = histograms[1].GetBinContent(x)
bin0ErrorSquared = binContent0
bin1ErrorSquared = binContent1
#bin1ErrorSquared = 0
if (binContent0 == 0) and (binContent1 == 0):
numberOfDegreesOfFreedom -= 1 #No data means one less degree of freedom
else:
binDifferenceSquared = (binContent0 - binContent1)**2
chiSquaredTerm = binDifferenceSquared / (bin0ErrorSquared +
bin1ErrorSquared)
chiSquared += chiSquaredTerm
if chiSquaredTerm > chiSquaredWarningThreshold:
if (histograms[0].ClassName()
== "TGraph") or (histograms[0].ClassName()
== "TGraphErrors"):
print "Bin", x, "-", histograms[0].GetX()[
x - 1], "has a CS=", chiSquaredTerm
else:
print "Bin", x, "-", histograms[0].GetBinCenter(
x), "has a CS=", chiSquaredTerm
chiSquareLabel = TPaveText(0.7, 0.6, 0.9, 0.4)
chiSquareLabel.AddText("#chi^{2}/ndf = " + str(chiSquared) + "/" +
str(numberOfDegreesOfFreedom) + " = " +
str(chiSquared / numberOfDegreesOfFreedom))
chiSquareLabel.Draw()
print "FINAL CS IS", format(
chiSquared,
".2f") + "/" + str(numberOfDegreesOfFreedom) + " = " + format(
chiSquared / numberOfDegreesOfFreedom, ".2f")
legend.SetHeader(
"#chi^{2}/ndf = " + format(chiSquared, ".2f") + "/" +
str(numberOfDegreesOfFreedom) + " = " +
format(chiSquared / numberOfDegreesOfFreedom, ".2f"), "C")
legend.Draw()
# lower plot will be in pad
canvas.cd() # Go back to the main canvas before defining pad2
pad2 = TPad("pad2", "pad2", 0, 0.05, 1, 0.3)
pad2.SetTopMargin(0)
pad2.SetBottomMargin(0.2)
pad2.SetGridx() # vertical grid
pad2.Draw()
pad2.cd() # pad2 becomes the current pad
pad2.SetGridy()
# Define the ratio plot
ratioPlot = TGraphErrors(histograms[0])
ratioPlot.SetName("ratioPlot")
graph_histo0 = TGraphErrors(histograms[0])
graph_histo1 = TGraphErrors(histograms[1])
ratioPlot.SetLineColor(1)
ratioPlot.SetMinimum(0.6) # Define Y ..
ratioPlot.SetMaximum(1.5) # .. range
#ratioPlot.Sumw2()
#ratioPlot.SetStats(0) # No statistics on lower plot
#Dividing point by point
for index in xrange(0, ratioPlot.GetN()):
if graph_histo1.GetY()[index] == 0:
ratioPlot.GetY()[index] = 0
ratioPlot.GetEY()[index] = 0
else:
ratioPlot.GetY()[index] /= graph_histo1.GetY()[index]
ratioPlot.GetEY()[index] = sqrt(
((graph_histo1.GetY()[index])**2 *
(graph_histo0.GetEY()[index])**2 +
(graph_histo0.GetY()[index])**2 *
(graph_histo1.GetEY()[index])**2) /
(graph_histo1.GetY()[index])**4)
ratioPlot.SetMarkerStyle(21)
if getattr(cfg, "xRange", None) is not None:
ratioPlot.GetXaxis().SetRangeUser(cfg.xRange[0], cfg.xRange[1])
gPad.RedrawAxis()
if getattr(cfg, "yRangeRatio", None) is not None:
ratioPlot.GetYaxis().SetRangeUser(cfg.yRangeRatio[0],
cfg.yRangeRatio[1])
gPad.RedrawAxis()
ratioPlot.Draw("APE") # Draw the ratio plot
line0 = TLine(ratioPlot.GetXaxis().GetXmin(), 1,
ratioPlot.GetXaxis().GetXmax(), 1)
line0.SetLineColor(2)
line0.SetLineWidth(2)
line0.SetLineStyle(2)
line0.Draw()
# Ratio plot (ratioPlot) settings
ratioPlot.SetTitle("") # Remove the ratio title
# Y axis ratio plot settings
ratioPlot.GetYaxis().SetTitle("Ratio #frac{blue}{red}")
ratioPlot.GetYaxis().SetNdivisions(505)
ratioPlot.GetYaxis().SetTitleSize(20)
ratioPlot.GetYaxis().SetTitleFont(43)
ratioPlot.GetYaxis().SetTitleOffset(1.55)
ratioPlot.GetYaxis().SetLabelFont(
43) # Absolute font size in pixel (precision 3)
ratioPlot.GetYaxis().SetLabelSize(15)
# X axis ratio plot settings
ratioPlot.GetXaxis().SetTitleSize(20)
ratioPlot.GetXaxis().SetTitleFont(43)
ratioPlot.GetXaxis().SetTitleOffset(4.)
ratioPlot.GetXaxis().SetLabelFont(
43) # Absolute font size in pixel (precision 3)
ratioPlot.GetXaxis().SetLabelSize(15)
xRangeBinning = getattr(cfg, "simplifiedRatioPlotXRangeBinning", None)
if xRangeBinning is not None:
simplifiedRatioPlot = TGraphErrors(len(xRangeBinning) - 1)
simplifiedRatioPlot.SetName("simplifiedRatioPlot")
ratioPlotIndex = 0
for idx in xrange(0, simplifiedRatioPlot.GetN()):
yAverage = 0.
yMax = float("-inf")
yMin = float("+inf")
nPoints = 0.
simplifiedRatioPlot.GetX()[idx] = (xRangeBinning[idx] +
xRangeBinning[idx + 1]) / 2.
simplifiedRatioPlot.GetEX()[idx] = (xRangeBinning[idx + 1] -
xRangeBinning[idx]) / 2.
while (ratioPlot.GetX()[ratioPlotIndex] < xRangeBinning[idx]):
ratioPlotIndex += 1
while ((ratioPlotIndex < ratioPlot.GetN()) and
(ratioPlot.GetX()[ratioPlotIndex] < xRangeBinning[idx + 1])
and
(ratioPlot.GetX()[ratioPlotIndex] >= xRangeBinning[idx])):
yAverage += ratioPlot.GetY()[ratioPlotIndex]
if (yMax < ratioPlot.GetY()[ratioPlotIndex] +
ratioPlot.GetEY()[ratioPlotIndex]):
yMax = ratioPlot.GetY()[ratioPlotIndex] + ratioPlot.GetEY(
)[ratioPlotIndex]
if (yMin > ratioPlot.GetY()[ratioPlotIndex] -
ratioPlot.GetEY()[ratioPlotIndex]):
yMin = ratioPlot.GetY()[ratioPlotIndex] - ratioPlot.GetEY(
)[ratioPlotIndex]
nPoints += 1.
ratioPlotIndex += 1
simplifiedRatioPlot.GetY()[idx] = yAverage / nPoints
simplifiedRatioPlot.GetEY()[idx] = (yMax - yMin) / 2.
saveFile = TFile(cfg.saveFileName, "RECREATE")
saveFile.cd()
canvas.Write()
histograms[0].Write()
histograms[1].Write()
if multiGraph.GetListOfGraphs() != None:
multiGraph.Write()
ratioPlot.Write()
if xRangeBinning is not None:
simplifiedRatioPlot.Write()
saveFile.Close()
for tfile in tfiles:
tfile.Close()
kk1.append(TGraph(int(len(bias1)), bias1, heigth_b_g[i]))
for i in gain1:
kk2.append(TGraph(int(len(bias1)), bias1, widht_b_g[i]))
k = 0
for i in kk1:
k = k + 1
i.SetLineColor(k + 1)
l5.AddEntry(i, "gain " + str(k - 1), "alp")
mm1.Add(i)
k = 0
for i in kk2:
k = k + 1
i.SetLineColor(k + 1)
l5.AddEntry(i, "gain " + str(k - 1), "alp")
mm2.Add(i)
c5.cd()
mm1.Draw("APL")
l5.Draw("")
c5.Modified()
c5.Update()
mm1.Write()
c5.Write()
c6.cd()
mm2.Draw("APL")
l6.Draw("")
mm2.Write()
c6.Modified()
c6.Update()
c6.Write()
def isobar_analysis_0pp():
"""Does the 2D isobar analysis, based on 'print2DtoRoot', with all cuts, argands and what not"""
root_name='isobar_analysis.root'
outROOT=root_open('./ROOT/'+root_name,mode="RECREATE")
isobar = 'f0_'
jpcs = ['0-+','1++','2-+']
# jpcs = ['0-+']
M='0'
iso_slices = { # do not use bin borders in definitions, a bin will be used, if any part of the defined interval overlaps with the bin #hence the *.**1 and *.**9 at the end of each definition
'0-+':[[1.661,1.699,'below_resonance'],[1.781,1.819,'on_resonance'],[1.901,1.939,'above_resonance']],
'1++':[[1.261,1.299,'below_resonance'],[1.381,1.419,'on_resonance'],[1.501,1.539,'above_resonance']],
'2-+':[[1.781,1.819,'below_resonance'],[1.901,1.939,'on_resonance'],[2.021,2.059,'above_resonance']]
}
all_slices = True # Set True, if all 3pi slices shall be written out
if all_slices:
for i in range(50):
mmin = 0.5 +i*0.04 + 0.001
mmax = 0.5 + (i+1)*0.04 - 0.001
name = "slice_"+str(i)
iso_slices["0-+"].append([mmin,mmax,name])
iso_slices["1++"].append([mmin,mmax,name])
iso_slices["2-+"].append([mmin,mmax,name])
prefixes = {'0-+':'1-(0-+)0+ f0_','1++':'1-(1++)0+ f0_','2-+':'1-(2-+)0+ f0_'}
suffixes = {'0-+':' pi S','1++':' pi P','2-+':' pi D'}
X_slices = [[0.961,0.999,'f_0(980)'],[1.401,1.559,'f_0(1500)'],[0.2781,2.279,'Incoherent_sum']]
suppressSigma=0
tbins=['0.10000-0.14077','0.14077-0.19435','0.19435-0.32617','0.32617-1.00000']
sumintens={}
for tbin in tbins:
dataSet = get2D('/nfs/mds/user/fkrinner/massIndepententFits/fits/4tbin_deisobarred/fit/'+tbin, '/nfs/mds/user/fkrinner/massIndepententFits/fits/4tbin_deisobarred/integrals/'+tbin ,normalizeToIntegrals = False, divide_key_intens = True)
for jpc in jpcs:
addString = '_'+isobar
bins2Pi=[]
bins3Pi=[]
for i in range(0,len(dataSet[0])):
if dataSet[0][i][4]==jpc and dataSet[0][i][13] == M and isobar in dataSet[0][i][14]:
bins3Pi.append(dataSet[0][i][0])
bins3Pi.append(dataSet[0][i][1])
bins2Pi.append(dataSet[0][i][2])
bins2Pi.append(dataSet[0][i][3])
bins3Pi.sort()
bins2Pi.sort()
if not len(bins3Pi) + len(bins2Pi) == 0:
binning2Pi=[bins2Pi[0]]
binning3Pi=[bins3Pi[0]]
for i in range(1,len(bins3Pi)-1):
if binning3Pi[-1] != bins3Pi[i]:
binning3Pi.append(bins3Pi[i])
if bins3Pi[i] != bins3Pi[i+1]:
print "Warning: Binning in m(3Pi) is wrong."
binning3Pi.append(bins3Pi[-1])
for i in range(1,len(bins2Pi)-1):
if binning2Pi[-1] != bins2Pi[i]:
binning2Pi.append(bins2Pi[i])
if bins2Pi[i] != bins2Pi[i+1]:
print "Warning: Binning in m(2Pi) is wrong."
binning2Pi.append(bins2Pi[-1])
binning2Pi= numpy.asarray(binning2Pi,dtype=numpy.float64)
binning3Pi= numpy.asarray(binning3Pi,dtype=numpy.float64)
histIn = TH2D("Intensity of "+jpc+'_'+M+addString+"_"+tbin,"Intensity of "+jpc+addString,len(binning3Pi)-1,binning3Pi,len(binning2Pi)-1,binning2Pi)
histIn.SetDrawOption('col')
histIn.GetXaxis().SetTitle("Mass of the #pi^{#font[122]{-}}#pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histIn.GetYaxis().SetTitle("Mass of the #pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histIn.GetZaxis().SetTitle("Intensity of "+jpc+addString)
histRe = TH2D("Real part of "+jpc+'_'+M+addString+"_"+tbin,"Real part of "+jpc+addString,len(binning3Pi)-1,binning3Pi,len(binning2Pi)-1,binning2Pi)
histRe.SetDrawOption('col')
histRe.GetXaxis().SetTitle("Mass of the #pi^{#font[122]{-}}#pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histRe.GetYaxis().SetTitle("Mass of the #pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histRe.GetZaxis().SetTitle("Real part of "+jpc+addString)
histIm = TH2D("Imag part of "+jpc+'_'+M+addString+"_"+tbin,"Imag part of "+jpc+addString,len(binning3Pi)-1,binning3Pi,len(binning2Pi)-1,binning2Pi)
histIm.SetDrawOption('col')
histIm.GetXaxis().SetTitle("Mass of the #pi^{#font[122]{-}}#pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histIm.GetYaxis().SetTitle("Mass of the #pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histIm.GetZaxis().SetTitle("Imag part of "+jpc+addString)
histPh = TH2D("Phase of "+jpc+'_'+M+addString+"_"+tbin,"Phase of "+jpc+addString,len(binning3Pi)-1,binning3Pi,len(binning2Pi)-1,binning2Pi)
histPh.SetDrawOption('col')
histPh.GetXaxis().SetTitle("Mass of the #pi^{#font[122]{-}}#pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histPh.GetYaxis().SetTitle("Mass of the #pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histPh.GetZaxis().SetTitle("Phase of "+'_'+M+jpc+addString)
for i in range(0,len(dataSet[0])):
if dataSet[0][i][4] == jpc and dataSet[0][i][13] == M and isobar in dataSet[0][i][14]:
m2Center = (dataSet[0][i][3] + dataSet[0][i][2])/2
m3Center = (dataSet[0][i][0] + dataSet[0][i][1])/2
n2 = histIn.GetYaxis().FindBin(m2Center)
n3 = histIn.GetXaxis().FindBin(m3Center)
histIn.SetBinContent(n3,n2,dataSet[0][i][5])
histRe.SetBinContent(n3,n2,dataSet[0][i][7])
histIm.SetBinContent(n3,n2,dataSet[0][i][9])
histPh.SetBinContent(n3,n2,dataSet[0][i][11])
histIn.SetBinError(n3,n2,dataSet[0][i][6])
histRe.SetBinError(n3,n2,dataSet[0][i][8])
histIm.SetBinError(n3,n2,dataSet[0][i][10])
histPh.SetBinError(n3,n2,dataSet[0][i][12])
if histIn.GetBinContent(n3,n2) < suppressSigma * histIn.GetBinError(n3,n2):
histIn.SetBinContent(n3,n2,0.)
histIn.SetBinError(n3,n2,0.)
histPh=removePhaseAmbiguities(histPh)
histIn.Write()
histRe.Write()
histIm.Write()
histPh.Write()
histIn.Draw("col")
# canv.Print('./pdfs/'+histIn.GetName()+".pdf")
for slic in iso_slices[jpc]:
minm = slic[0]
maxm = slic[1]
name = slic[2]
for i in range(len(binning3Pi)-1):
bul = binning3Pi[i+1]
bll = binning3Pi[i]
if bul > maxm and bll < maxm:
maxb = i+1
if bul > minm and bll < minm:
minb = i+1
massstring = 'm3Pi='+str(binning3Pi[minb-1])+'-'+str(binning3Pi[maxb])
slcInt=histIn.ProjectionY('slice_of_'+jpc+'_intens_'+name+"_"+tbin ,minb,maxb)
slcRe =histRe.ProjectionY('slice_of_'+jpc+'_real_part_'+name+"_"+tbin,minb,maxb)
slcIm =histIm.ProjectionY('slice_of_'+jpc+'_imag_part_'+name+"_"+tbin,minb,maxb)
slcPha=histPh.ProjectionY('slice_of_'+jpc+'_phase_'+name+"_"+tbin ,minb,maxb)
adjust_phase_range(slcPha)
slcInt.Draw()
# canv.Print('./pdfs/'+slcInt.GetName()+".pdf")
re = []
im = []
ree= []
ime= []
for i in range(1,slcRe.GetNbinsX()+1):
e = slcRe.GetBinError(i)+ slcIm.GetBinError(i)
if not e==0.:
re.append(slcRe.GetBinContent(i))
im.append(slcIm.GetBinContent(i))
ree.append(slcRe.GetBinError(i))
ime.append(slcIm.GetBinError(i))
if len(re)>0 and len(re) == len(im) and len(re) == len(ree) and len(re) == len(ime):
while re[-1] ==0. and im[-1]==0.: # Kill the last (zero) point
re = re[:-1]
im = im[:-1]
ree=ree[:-1]
ime=ime[:-1]
re= numpy.asarray(re,dtype=numpy.float64)
im= numpy.asarray(im,dtype=numpy.float64)
ree= numpy.asarray(ree,dtype=numpy.float64)
ime= numpy.asarray(ime,dtype=numpy.float64)
argand = TGraphErrors(len(re),re,im,ree,ime)
argand.SetName('slice_of_'+jpc+'_argand_'+name+"_"+tbin)
# argand.Write()
argand.Draw('apl')
# canv.Print('./pdfs/'+argand.GetName()+".pdf")
argand_wrapper = TMultiGraph()
argand_wrapper.SetName(argand.GetName())
argand_wrapper.Add(argand)
argand_wrapper.Write()
slcInt.SetTitle(massstring)
slcRe.SetTitle(massstring)
slcIm.SetTitle(massstring)
slcPha.SetTitle(massstring)
slcInt.Write()
slcRe.Write()
slcIm.Write()
slcPha.Write()
for slic in X_slices:
minm = slic[0]
maxm = slic[1]
name = slic[2]
total_list = make_f0_wavelist(minm,maxm,prefixes[jpc],suffixes[jpc])
# if name == 'f_0(1500)':
# print total_list
# raise Exception
total_data = getTotal('/nfs/mds/user/fkrinner/massIndepententFits/fits/4tbin_deisobarred/fit/'+tbin,total_list, '/nfs/mds/user/fkrinner/massIndepententFits/fits/4tbin_deisobarred/integrals/'+tbin,normalizeToDiag=True)
total_binning = [total_data[0][0]]
for total_point in total_data:
total_binning.append(total_point[1])
total_binning= numpy.asarray(total_binning,dtype=numpy.float64)
total_mmin = total_binning[0]
total_mmax = total_binning[-1]
total_hist = TH1D('coherent_sum_of_'+jpc+'_'+name+'_'+tbin,'coherent_sum_of_'+jpc+'_'+name+'_'+tbin,len(total_binning)-1,total_binning)
total_hist.GetXaxis().SetTitle("Mass of the #pi^{#font[122]{-}}#pi^{#font[122]{+}}#pi^{#font[122]{-}} System (GeV/#it{c}^{2})")
histIn.GetZaxis().SetTitle("Intensity of "+jpc+addString)
for i in range(len(total_data)):
total_hist.SetBinContent(i+1,total_data[i][2])
total_hist.SetBinError(i+1,total_data[i][3])
for i in range(len(binning2Pi)-1):
bul = binning2Pi[i+1]
bll = binning2Pi[i]
if bul > maxm and bll < maxm:
maxb = i+1
if bul > minm and bll < minm:
minb = i+1
massstring = 'm2Pi='+str(binning2Pi[minb-1])+'-'+str(binning2Pi[maxb])
slcInt=histIn.ProjectionX('slice_of_'+jpc+'_intens_'+name+"_"+tbin ,minb,maxb)
slcRe =histRe.ProjectionX('slice_of_'+jpc+'_real_part_'+name+"_"+tbin,minb,maxb)
slcIm =histIm.ProjectionX('slice_of_'+jpc+'_imag_part_'+name+"_"+tbin,minb,maxb)
slcPha=histPh.ProjectionX('slice_of_'+jpc+'_phase_'+name+"_"+tbin ,minb,maxb)
slcInt.SetTitle(massstring)
slcRe.SetTitle(massstring)
slcIm.SetTitle(massstring)
slcPha.SetTitle(massstring)
total_hist.SetTitle(massstring)
slcInt.Write()
slcRe.Write()
slcIm.Write()
slcPha.Write()
total_hist.Write()
slcInt.Draw()
# canv.Print('./pdfs/'+slcInt.GetName()+".pdf")
if not sumintens.has_key(name+"_"+jpc):
sumintens[name+"_"+jpc] = slcInt
sumintens[name+"_"+jpc].SetName('incoherent_sum_'+jpc+'_'+name)
else:
sumintens[name+"_"+jpc].Add(slcInt)
for key in sumintens.iterkeys():
sumintens[key].Write()
sumintens[key].Draw()
# canv.Print('./pdfs/'+sumintens[key].GetName()+".pdf")
outROOT.close()
print "ran with no exceptions"
def energylinearity():
outputfile = "EMLinearityEnergyRes"
displayfile = TFile(outputfile + ".root", "RECREATE")
MeanEnergyScin = array('d')
MeanEnergyCher = array('d')
MeanEnergy = array('d')
resolutionscin = array('d')
resolutioncher = array('d')
resolution = array('d')
towers = array('d')
##inputfiles = sorted(glob.glob(datapath+"*"), key=os.path.getmtime) #get files from tower 1 to 75 ordered by creation time
inputfiles = [
"/home/software/Calo/results/newresults/barrel2/Barrel_" + str(i) +
".root" for i in range(1, 76)
]
#inputfiles = ["/home/software/Calo/results/NewTowerScan4/Barrel_"+str(i)+".root" for i in range(1,76)]
#inputfiles = ["/home/lorenzo/Desktop/Calo/results/NewTowerScan4/Barrel_"+str(i)+".root" for i in range(1,76)]
for counter, inputfile in enumerate(inputfiles):
inputfile = TFile(inputfile)
print "Analyzing: " + str(inputfile) + " \n"
tree = TTree()
inputfile.GetObject("B4", tree)
ScinEnergyHist = TH1F("scinenergy_",
str(counter + 1) + "_scin", 200, 0., 100.)
CherEnergyHist = TH1F("cherenergy_",
str(counter + 1) + "_cher", 200, 0., 100.)
RecEnergyHist = TH1F("RecEnergy_",
str(counter + 1) + "_Energy", 200, 0., 100.)
Energytot = 0.0
energy = 40.0
sqrtenergy = 1 / (40.0**0.5)
towers.append(counter + 1.)
#loop over events
for Event in range(int(tree.GetEntries())):
tree.GetEntry(Event)
#Set values of the tree
PrimaryParticleName = tree.PrimaryParticleName # MC truth: primary particle Geant4 name
PrimaryParticleEnergy = tree.PrimaryParticleEnergy
EnergyTot = tree.EnergyTot # Total energy deposited in calorimeter
Energyem = tree.Energyem # Energy deposited by the em component
EnergyScin = tree.EnergyScin # Energy deposited in Scin fibers (not Birk corrected)
EnergyCher = tree.EnergyCher # Energy deposited in Cher fibers (not Birk corrected)
NofCherenkovDetected = tree.NofCherenkovDetected # Total Cher p.e. detected
BarrelR_VectorSignals = tree.VectorSignalsR # Vector of energy deposited in Scin fibers (Birk corrected)
BarrelL_VectorSignals = tree.VectorSignalsL # Vector of energy deposited in Scin fibers (Birk corrected)
BarrelR_VectorSignalsCher = tree.VectorSignalsCherR # Vector of Cher p.e. detected in Cher fibers
BarrelL_VectorSignalsCher = tree.VectorSignalsCherL
VectorR = tree.VectorR
VectorL = tree.VectorL
#apply calibrations
Calib_BarrelL_VectorSignals = calibration2.calibscin(
BarrelL_VectorSignals)
Calib_BarrelR_VectorSignals = calibration2.calibscin(
BarrelR_VectorSignals)
Calib_BarrelL_VectorSignalsCher = calibration2.calibcher(
BarrelL_VectorSignalsCher)
Calib_BarrelR_VectorSignalsCher = calibration2.calibcher(
BarrelR_VectorSignalsCher)
#end of calibrations
energyscin = sum(Calib_BarrelR_VectorSignals) + sum(
Calib_BarrelL_VectorSignals)
energycher = sum(Calib_BarrelR_VectorSignalsCher) + sum(
Calib_BarrelL_VectorSignalsCher)
ScinEnergyHist.Fill(energyscin)
CherEnergyHist.Fill(energycher)
#sigmascin = 0.15*(energyscin**0.5)+0.012*energyscin #old value
#sigmacher = 0.18*(energycher**0.5)+0.0045*energycher #old value
sigmascin = 0.177 * (energyscin**0.5) + 0.006 * energyscin
sigmacher = 0.194 * (energycher**0.5) + 0.001 * energycher
RecEnergyHist.Fill(
(energyscin / (sigmascin**2) + energycher /
(sigmacher**2)) / (1 / sigmascin**2 + 1 / sigmacher**2))
#RecEnergyHist.Fill((energyscin+energycher)/2)
Energytot += (sum(VectorL) + sum(VectorR)) / 1000
Energytot = Energytot / int(tree.GetEntries())
print Energytot, ScinEnergyHist.GetMean(), CherEnergyHist.GetMean()
displayfile.cd()
gStyle.SetOptStat(111)
ScinEnergyHist.Fit("gaus")
CherEnergyHist.Fit("gaus")
RecEnergyHist.Fit("gaus")
RecEnergyHist.Write()
ScinEnergyHist.Write()
CherEnergyHist.Write()
#MeanEnergyScin.append(ScinEnergyHist.GetFunction("gaus").GetParameter(1)/Energytot)
MeanEnergyScin.append(ScinEnergyHist.GetMean() / energy)
#MeanEnergyCher.append(CherEnergyHist.GetFunction("gaus").GetParameter(1)/Energytot)
MeanEnergyCher.append(CherEnergyHist.GetMean() / energy)
MeanEnergy.append(
RecEnergyHist.GetFunction("gaus").GetParameter(1) / energy)
resolution.append(
RecEnergyHist.GetFunction("gaus").GetParameter(2) /
RecEnergyHist.GetFunction("gaus").GetParameter(1))
resolutionscin.append(
ScinEnergyHist.GetFunction("gaus").GetParameter(2) /
ScinEnergyHist.GetFunction("gaus").GetParameter(1))
resolutioncher.append(
CherEnergyHist.GetFunction("gaus").GetParameter(2) /
CherEnergyHist.GetFunction("gaus").GetParameter(1))
print MeanEnergyScin, MeanEnergyCher
LinearityGraph = TGraph(len(towers), towers, MeanEnergy)
LinearityGraph.SetName("LinearityGraph")
LinearityGraph.Write()
LinearityGraphScin = TGraph(len(towers), towers, MeanEnergyScin)
LinearityGraphCher = TGraph(len(towers), towers, MeanEnergyCher)
LinearityGraphCher.SetName("LinearityGraphCher")
LinearityGraphCher.Write()
LinearityGraphScin.SetName("LinearityGraphScin")
LinearityGraphScin.Write()
ResolutionGraphScin = TGraph(len(towers), towers, resolutionscin)
ResolutionGraphCher = TGraph(len(towers), towers, resolutioncher)
ResolutionGraphScin.SetName("ResolutionGraphScin")
ResolutionGraphScin.Write()
ResolutionGraphCher.SetName("ResolutionGraphCher")
ResolutionGraphCher.Write()
ResolutionGraph = TGraph(len(towers), towers, resolution)
ResolutionGraph.SetName("ResolutionGraph")
ResolutionGraph.Write()
x2 = array('d', (0., 90., 90., 0.))
y2 = array('d', (0.024, 0.024, 0.034, 0.034))
Fillgraph2 = TGraph(4, x2, y2)
Fillgraph2.SetName("ban")
Fillgraph2.Write()
linefill1 = TF1("1", str(1.0), 0., 90.)
linefill1.Write()
EMResolutions = TMultiGraph()
EMResolutions.Add(ResolutionGraphScin)
EMResolutions.Add(ResolutionGraphCher)
EMResolutions.Add(ResolutionGraph)
EMResolutions.SetName("EMResolutions")
EMResolutions.Write()
Linearities = TMultiGraph()
Linearities.Add(LinearityGraph)
Linearities.Add(LinearityGraphScin)
Linearities.Add(LinearityGraphCher)
Linearities.SetName("Linearities")
Linearities.Write()
MGElastic.Draw("al*")
canvas.SetLogy()
MGElastic.Draw()
#if MGElastic.GetListOfGraphs().GetEntries() < 10:
legendElastic.Draw()
canvas.SaveAs("aa_ElasticBatch.png")
MGInElastic.Draw("al*")
#canvas.SetLogy()
MGInElastic.Draw()
#if MGInElastic.GetListOfGraphs().GetEntries() < 10:
legendInElastic.Draw()
canvas.SaveAs("aa_InElasticBatch.png")
outFile = TFile("Batch.root","recreate")
MGElastic.Write()
MGInElastic.Write()
couOnlyFile = TFile("../coulombOnly.root","read")
if couOnlyFile:
couOnlyGraph = couOnlyFile.Get("G1")
if couOnlyGraph:
couOnlyGraph.SetMarkerColor(ROOT.kWhite)
couOnlyGraph.SetLineColor(ROOT.kMagenta)
couOnlyGraph.SetFillColor(ROOT.kWhite)
couOnlyGraph.SetLineWidth(5)
couOnlyGraph.SetLineStyle(5)
MGElastic.Add(couOnlyGraph,"L")
legendElastic.AddEntry(couOnlyGraph,"Coulomb Only")
MGElastic.Draw("al*")
def MakePlot(PlotList, name):
canvas = TCanvas('canvas', 'shouldnotseethis', 0, 0, 1280, 720)
colors = [ROOT.kRed, ROOT.kBlue, ROOT.kGreen, ROOT.kCyan,
ROOT.kMagenta] # ROOT.kOrange+1,
MG = TMultiGraph()
MG.SetTitle(
"Best Fits per Chi Square;Center of Mass Angle in Degrees;Cross Section in mb/sr"
)
MG.SetTitle("MG")
MG.SetName(name)
legend = ROOT.TLegend(0.3, .65, .9, .9)
# if len(PlotList) >6:
# PlotList = PlotList[:6]
# print "Cutting PlotList length for {}".format(name)
#
Zipper = zip(PlotList, colors)
#
# MG.Add(dataG,"P")
# legend.AddEntry(dataG,"Data")
i = 2
for bigInfo, color in Zipper:
if len(Zipper) == 1:
color = ROOT.kBlack
plot = bigInfo[-1]
plot.SetMarkerColor(ROOT.kWhite)
plot.SetLineColor(color)
plot.SetFillColor(ROOT.kWhite)
plot.SetLineWidth(2)
if len(Zipper) > 1:
plot.SetLineStyle(i)
i += 1
MG.Add(plot, "L")
legend.AddEntry(
plot, "chiSquare(" + str(int(bigInfo[0])) + ")_" + plot.GetName())
dataPlot = bigInfo[-2]
dataPlot.SetMarkerColor(ROOT.TColor.GetColorDark(color))
dataPlot.SetLineColor(ROOT.TColor.GetColorDark(color))
dataPlot.SetFillColor(ROOT.kWhite)
MG.Add(dataPlot, "P")
legend.AddEntry(
dataPlot,
"data_chiSquare(" + str(int(bigInfo[0])) + ")_" + plot.GetName())
if len(PlotList) < 4:
blurPlot = bigInfo[-3]
blurPlot.SetMarkerColor(color)
blurPlot.SetLineColor(color)
blurPlot.SetLineStyle(2)
blurPlot.SetLineWidth(2)
blurPlot.SetFillColor(ROOT.kWhite) # print blurPlot.GetName()
# blurPlot.Print()
MG.Add(blurPlot, "L")
legend.AddEntry(blurPlot, "Blurred Fresco Output")
MG.Draw("AL")
canvas.SetLogy()
MG.GetXaxis().SetTitle("Center of Mass Angle in Degrees")
MG.GetYaxis().SetTitle("Cross Section in mb/sr")
MG.Draw()
legend.Draw()
outF.cd()
MG.Write()
canvas.SaveAs("pngs/{}.png".format(name))
def recenergy():
outputfile = "EMEnergyRes"
displayfile = TFile(outputfile + ".root", "RECREATE")
MeanEnergyScin = array('d')
MeanEnergyCher = array('d')
Energy = array('d')
energyfractionscin = array('d')
energyfractioncher = array('d')
energyfraction = array('d')
resolutionscin = array('d')
resolutioncher = array('d')
resolution = array('d')
energies = array(
'd',
[10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150])
energies = array('d', [40, 50, 60, 70, 80, 90, 100])
energies = array('d', [5, 10, 40, 60, 80, 100, 150])
sqrtenergies = array('d', [1 / (x**0.5) for x in energies])
scin_sqrtenergies = array('d')
cher_sqrtenergies = array('d')
#inputfiles = sorted(glob.glob(datapath+"*"), key=os.path.getmtime) #get files from tower 1 to 75 ordered by creation time
t = [5, 10, 40, 60, 80, 100, 150]
inputfiles = [
"/home/software/Calo/results/newenergyscan3_noangsmearing/Electron_" +
str(i) + ".root" for i in t
]
for counter, inputfile in enumerate(inputfiles):
inputfile = TFile(inputfile)
print "Analyzing: " + str(inputfile) + " \n"
tree = TTree()
inputfile.GetObject("B4", tree)
ScinEnergyHist = TH1F("scinenergy_",
str(counter + 1) + "_scin", 500, 0., 200.)
CherEnergyHist = TH1F("cherenergy_",
str(counter + 1) + "_cher", 500, 0., 200.)
RecEnergyHist = TH1F("RecEnergy_",
str(counter + 1) + "_Energy", 500, 0., 200.)
Signalscinhist = TH1F("scintot_",
str(counter + 1) + "_scin", 3000, 0., 30000)
EnergyHist = TH1F("Energy_",
str(counter + 1) + "_Energy", 500, 0., 200.)
#loop over events
for Event in range(int(tree.GetEntries())):
tree.GetEntry(Event)
#Set values of the tree
PrimaryParticleName = tree.PrimaryParticleName # MC truth: primary particle Geant4 name
PrimaryParticleEnergy = tree.PrimaryParticleEnergy
EnergyTot = tree.EnergyTot # Total energy deposited in calorimeter
Energyem = tree.Energyem # Energy deposited by the em component
EnergyScin = tree.EnergyScin # Energy deposited in Scin fibers (not Birk corrected)
EnergyCher = tree.EnergyCher # Energy deposited in Cher fibers (not Birk corrected)
NofCherenkovDetected = tree.NofCherenkovDetected # Total Cher p.e. detected
BarrelR_VectorSignals = tree.VectorSignalsR # Vector of energy deposited in Scin fibers (Birk corrected)
BarrelL_VectorSignals = tree.VectorSignalsL # Vector of energy deposited in Scin fibers (Birk corrected)
BarrelR_VectorSignalsCher = tree.VectorSignalsCherR # Vector of Cher p.e. detected in Cher fibers
BarrelL_VectorSignalsCher = tree.VectorSignalsCherL
VectorR = tree.VectorR
VectorL = tree.VectorL
totalsignalscin = sum(BarrelR_VectorSignals) + sum(
BarrelL_VectorSignals)
Signalscinhist.Fill(totalsignalscin)
energytot = (sum(VectorR) + sum(VectorL)) / 1000
EnergyHist.Fill(energytot)
#apply calibrations
Calib_BarrelL_VectorSignals = calibration.calibscin(
BarrelL_VectorSignals)
Calib_BarrelR_VectorSignals = calibration.calibscin(
BarrelR_VectorSignals)
Calib_BarrelL_VectorSignalsCher = calibration.calibcher(
BarrelL_VectorSignalsCher)
Calib_BarrelR_VectorSignalsCher = calibration.calibcher(
BarrelR_VectorSignalsCher)
#end of calibrations
energyscin = sum(Calib_BarrelR_VectorSignals) + sum(
Calib_BarrelL_VectorSignals)
energycher = sum(Calib_BarrelR_VectorSignalsCher) + sum(
Calib_BarrelL_VectorSignalsCher)
ScinEnergyHist.Fill(energyscin)
sigmascin = 0.15 * (energyscin**0.5) + 0.012 * energyscin
CherEnergyHist.Fill(energycher)
sigmacher = 0.18 * (energycher**0.5) + 0.0045 * energycher
RecEnergyHist.Fill(
(energyscin / (sigmascin**2) + energycher /
(sigmacher**2)) / (1 / sigmascin**2 + 1 / sigmacher**2))
print energies[counter], ScinEnergyHist.GetMean(
), CherEnergyHist.GetMean()
displayfile.cd()
gStyle.SetOptStat(111)
ScinEnergyHist.Fit("gaus")
CherEnergyHist.Fit("gaus")
RecEnergyHist.Fit("gaus")
RecEnergyHist.Write()
ScinEnergyHist.Write()
CherEnergyHist.Write()
Signalscinhist.Write()
EnergyHist.Write()
scin_sqrtenergies.append(
1. / (ScinEnergyHist.GetFunction("gaus").GetParameter(1)**0.5))
cher_sqrtenergies.append(
1. / (CherEnergyHist.GetFunction("gaus").GetParameter(1)**0.5))
MeanEnergyScin.append(
ScinEnergyHist.GetFunction("gaus").GetParameter(1))
MeanEnergyCher.append(
CherEnergyHist.GetFunction("gaus").GetParameter(1))
resolution.append(
RecEnergyHist.GetFunction("gaus").GetParameter(2) /
RecEnergyHist.GetFunction("gaus").GetParameter(1))
energyfractionscin.append(
ScinEnergyHist.GetFunction("gaus").GetParameter(1))
energyfractioncher.append(
CherEnergyHist.GetFunction("gaus").GetParameter(1))
energyfraction.append(
RecEnergyHist.GetFunction("gaus").GetParameter(1))
resolutionscin.append(
ScinEnergyHist.GetFunction("gaus").GetParameter(2) /
ScinEnergyHist.GetFunction("gaus").GetParameter(1))
resolutioncher.append(
CherEnergyHist.GetFunction("gaus").GetParameter(2) /
CherEnergyHist.GetFunction("gaus").GetParameter(1))
LinearityGraph = TGraph(len(energies), energies, energyfraction)
LinearityGraph.SetName("LinearityGraph")
LinearityGraph.Write()
LinearityGraphScin = TGraph(len(energies), energies, energyfractionscin)
LinearityGraphCher = TGraph(len(energies), energies, energyfractioncher)
LinearityGraphCher.SetName("LinearityGraphCher")
LinearityGraphCher.Write()
LinearityGraphScin.SetName("LinearityGraphScin")
LinearityGraphScin.Write()
ResolutionGraphScin = TGraph(len(energies), scin_sqrtenergies,
resolutionscin)
func = TF1("func", "[0]*x+[1]", 0.1, 0.45)
ResolutionGraphCher = TGraph(len(energies), cher_sqrtenergies,
resolutioncher)
ResolutionGraphScin.Fit("func", "R")
ResolutionGraphCher.Fit("func", "R")
ResolutionGraphScin.SetName("ResolutionGraphScin")
ResolutionGraphScin.Write()
ResolutionGraphCher.SetName("ResolutionGraphCher")
ResolutionGraphCher.Write()
ResolutionGraph = TGraph(len(energies), sqrtenergies, resolution)
ResolutionGraph.Fit("func", "R")
ResolutionGraph.SetName("ResolutionGraph")
ResolutionGraph.Write()
rd52copper = array('d', [
0.04478505426185217, 0.027392527130926082, 0.02420093893609386,
0.02229837387624884, 0.020999999999999998
])
rd52graph = TGraph(len(energies), sqrtenergies, rd52copper)
rd52graph.SetName("rd52resolution")
rd52graph.Write()
EMResolutions = TMultiGraph()
EMResolutions.Add(ResolutionGraphScin)
EMResolutions.Add(ResolutionGraphCher)
EMResolutions.Add(ResolutionGraph)
EMResolutions.Add(rd52graph)
EMResolutions.SetName("EMResolutions")
EMResolutions.Write()
Linearities = TMultiGraph()
Linearities.Add(LinearityGraph)
Linearities.Add(LinearityGraphScin)
Linearities.Add(LinearityGraphCher)
Linearities.SetName("Linearities")
Linearities.Write()
def combinedDraw(frescoGraph, goodPID, badPID, goodCORR, badCORR):
#print "combinedDraw start"
canvas = TCanvas('canvas', 'shouldnotseethis', 0, 0, 1280, 720)
MG = TMultiGraph()
legend = ROOT.TLegend(0.55, .55, .9, .9)
##legend.SetBorderSize(0)
#underHisto.SetLineColor(ROOT.kBlack)
#underHisto.SetMinimum(0)
##underHisto.SetMaximum(underHisto.GetMaximum() * 1.5)
#underHisto.GetXaxis().SetRangeUser(0,180)
#underHisto.SetTitle(title)
#underHisto.SetLineColor(ROOT.kBlack)
#underHisto.SetTitle(title)
#underHisto.GetYaxis().SetTitle("Counts in Arb. Units")
#legend.AddEntry(underHisto,"Simulated Angular Distribution")
#underHisto.SetStats(ROOT.kFALSE)
#underHisto.Draw()
if frescoGraph:
#print "frescoGraph"
frescoGraph.SetMarkerColor(ROOT.kBlack)
frescoGraph.SetLineColor(ROOT.kBlack)
frescoGraph.SetFillColor(ROOT.kBlack)
#frescoGraph.SetMarkerStyle(33)
MG.Add(frescoGraph, "L")
legend.AddEntry(frescoGraph, "Fresco Output")
else:
print "No FrescoGraph!!!"
return
if goodPID:
#print "goodPID"
goodPID.SetMarkerColor(ROOT.kGreen)
goodPID.SetLineColor(ROOT.kGreen)
goodPID.SetFillColor(ROOT.kGreen)
#goodPID.SetMarkerStyle(33)
MG.Add(goodPID, "P")
legend.AddEntry(goodPID, "ScaledPID")
else:
print "No goodPID in Draw()"
if goodCORR:
#print "goodCORR"
goodCORR.SetMarkerColor(TColor.GetColorDark(ROOT.kGreen))
goodCORR.SetLineColor(TColor.GetColorDark(ROOT.kGreen))
goodCORR.SetFillColor(TColor.GetColorDark(ROOT.kGreen))
goodCORR.SetMarkerStyle(21)
#afterHisto.Draw("PLsame")
MG.Add(goodCORR, "P")
legend.AddEntry(goodCORR, "Good Dual Det")
else:
print "No goodCORR in Draw()"
if badPID:
#print "badPID"
badPID.SetMarkerColor(ROOT.kRed)
badPID.SetLineColor(ROOT.kRed)
badPID.SetFillColor(ROOT.kRed)
badPID.SetMarkerStyle(33)
MG.Add(badPID, "P")
legend.AddEntry(badPID, "Discard PID")
else:
print "No badPID in Draw()"
if badCORR:
#print "badCORR"
badCORR.SetMarkerColor(TColor.GetColorDark(ROOT.kRed))
badCORR.SetLineColor(TColor.GetColorDark(ROOT.kRed))
badCORR.SetFillColor(TColor.GetColorDark(ROOT.kRed))
badCORR.SetMarkerStyle(21)
MG.Add(badCORR, "P")
legend.AddEntry(badCORR, "Discard Dual Det")
else:
print "No badCORR in Draw()"
MG.SetTitle(
"Scaled Elastic Distribution for detector {};Center of Mass Angle in Degrees;Cross section in mb/sr"
.format(det))
MG.SetName("MG_d{}".format(det))
MG.Draw("AP")
legend.Draw()
MG.Write()
MG.SetMaximum(500)
MG.SetMinimum(0)
canvas.SetLogy()
#MG.GetYaxis().SetRangeUser(0,500)
MG.Draw()
canvas.SaveAs(MG.GetName() + '.png')
