def plotPerLumiSection(options):
"""Save profile histograms per lumisection to PDF files"""
name = options['name'] + '_perLS'
f = openRootFileR(name)
histname = plotName(options['title'] + '_perLS', timestamp=False)
filename = plotName(options['title'] + '_perLS', timestamp=True)
filepath = plotPath(options['title'] + '_perLS', timestamp=True)
print '<<< Save plot:', filepath
hist = f.Get(histname)
canvas = TCanvas()
canvas.SetLogy(options['logy'])
gStyle.SetOptStat(options['optstat'])
hist.Draw()
gPad.Update()
hist.GetXaxis().SetTitle('Lumisection')
hist.GetYaxis().SetTitle(options['ytitle'])
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
drawSignature(filename)
gPad.Modified()
gPad.Update()
#canvas.Print(filepath)
#canvas.Close()
#closeRootFile(f, name)
return [canvas, hist, f]
def plotPerTimeStamp(options):
"""Save profile histograms per timestamp to PDF files"""
name = options['name'] + '_' + options['scan'] + '_perTime'
if options['extra']:
name += '_' + options['extra']
f = openRootFileR(options['name'] + '_perTime')
histname = plotName(name, timestamp=False)
filename = plotName(name, timestamp=True)
filepath = plotPath(name, timestamp=True)
print '<<< Save plot:', filepath
hist = f.Get(histname)
hist.SetErrorOption(options['error'])
if options['big']:
canvas = TCanvas('c', '', 8000, 1200)
else:
canvas = TCanvas('c', '', 1400, 500)
canvas.SetLogy(options['logy'])
gStyle.SetOptStat(options['optstat'])
hist.Draw()
gPad.Update()
hist.GetXaxis().SetTimeDisplay(1)
hist.GetXaxis().SetTimeFormat('#splitline{%d.%m.%y}{%H:%M:%S}%F1969-12-31' \
+' 22:00:00')
hist.GetXaxis().SetLabelOffset(0.03)
hist.GetXaxis().SetTitle('')
if 'xmin' in options and 'xmax' in options:
hist.GetXaxis().SetRangeUser(options['xmin'], options['xmax'])
hist.GetYaxis().SetTitle(options['ytitle'])
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
if options['big']:
axis.SetTickLength(0.01)
if options['big']:
hist.GetYaxis().SetTitleOffset(0.25)
drawSignature(filename)
gPad.Modified()
gPad.Update()
if options['retrn']:
return [canvas, hist, f]
else:
canvas.Print(filepath)
canvas.Close()
closeRootFile(f, options['name'] + '_perTime')
def plotPerBxStep(options):
"""Save histograms (per BX and step) to PDF files"""
name = options['scan'] + '_' + options['name'] + options['extra']
if 'method' in options:
name += '_' + options['method']
f = openRootFileR(name)
for bx in options['crossings']:
for step in range(len(O['nominalPos'][options['scan']])):
histname = plotName(name+'_bx'+str(bx)+'_step'+str(step), \
timestamp=False)
filename = plotName(name+'_bx'+str(bx)+'_step'+str(step), \
timestamp=True)
filepath = plotPath(name+'_bx'+str(bx)+'_step'+str(step), \
timestamp=True)
print '<<< Save plot:', filepath
hist = f.Get(histname)
canvas = TCanvas()
canvas.SetLogx(options['logx'])
canvas.SetLogy(options['logy'])
gStyle.SetOptStat(options['optstat'])
gStyle.SetOptFit(options['optfit'])
hist.Draw()
gPad.Update()
hist.GetXaxis().SetTitle(options['xtitle'])
hist.GetXaxis().SetRangeUser(options['xmin'], options['xmax'])
hist.GetYaxis().SetTitle(options['ytitle'])
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
stats = hist.FindObject('stats')
stats.SetTextFont(133)
stats.SetTextSize(16)
drawSignature(filename)
gPad.Modified()
gPad.Update()
if 'custom' in options:
extragraphs = options['custom'](hist)
canvas.Print(filepath)
canvas.Close()
closeRootFile(f, name)
def extractPerDirectionBx(options):
"""Extract results from directional fits (per BX)"""
name = options['scan'] + '_'+ options['name'] + options['fitted'] \
+ '_collected'
f = openRootFileR(name)
crossings = O['crossings'][:]
if options['combine']:
crossings.append('all')
average = dict(zip(crossings, [[0, 0] for i in range(len(crossings))]))
averror = dict(zip(crossings, [[0, 0] for i in range(len(crossings))]))
def extract(graph):
func = graph.GetFunction(options['fit'])
return func.GetParameter(options['parameter']), \
func.GetParError(options['parameter'])
for bx in crossings:
plotname = plotName(name+'_bx'+str(bx), timestamp=False)
print '<<< Access plot:', plotname
graphs = f.Get(plotname)
for j, graph in enumerate(graphs.GetListOfGraphs()):
average[bx][j], averror[bx][j] = extract(graph)
return average, averror
def plotPerDirectionBx(options):
"""Save directional fit plots (per BX) to PDF files"""
name = options['scan'] + '_' + options['name'] + options['fitted']
if 'method' in options:
name += '_' + options['method']
name += '_collected'
f = openRootFileR(name)
for bx in options['crossings']:
plotname = plotName(name + '_bx' + str(bx), timestamp=False)
filename = plotName(name + '_bx' + str(bx), timestamp=True)
filepath = plotPath(name + '_bx' + str(bx), timestamp=True)
print '<<< Save plot:', filepath
graphs = f.Get(plotname)
residuals = f.Get(plotname + '_residuals')
if 'final' in options:
graphs.SetTitle('')
residuals.SetTitle('')
gStyle.SetOptFit(options['optfit'])
canvas = TCanvas(plotname + '_canvas', '', 700, 600)
canvas.cd()
canvas.SetMargin(0.13, 0.03, 0.33, 0.05)
graphs.Draw('AP')
gPad.Update()
text = TLatex()
text.SetNDC()
for j, graph in enumerate(graphs.GetListOfGraphs()):
graph.SetMarkerStyle(21)
graph.SetMarkerColor(2 + 2 * j)
graph.GetFunction(options['fit']).SetLineColor(2 + 2 * j)
stats = graph.GetListOfFunctions().FindObject('stats')
stats.SetTextColor(2 + 2 * j)
stats.SetBorderSize(0)
stats.SetTextSize(0.04)
inverted = graph.GetFunction(
options['fit']).GetParameter('p1') < 0.0
text.SetTextFont(42)
text.SetTextSize(0.04)
text.SetTextColor(2 + 2 * j)
if inverted and j == 0:
text.DrawLatex(0.18, 0.54, options['scan'] + ' scan forward')
stats.SetX1NDC(0.16)
stats.SetX2NDC(0.53)
stats.SetY1NDC(0.38)
stats.SetY2NDC(0.53)
elif inverted and j == 1:
text.DrawLatex(0.61, 0.9, options['scan'] + ' scan backward')
stats.SetX1NDC(0.59)
stats.SetX2NDC(0.96)
stats.SetY1NDC(0.74)
stats.SetY2NDC(0.89)
elif j == 0:
text.DrawLatex(0.18, 0.9, options['scan'] + ' scan forward')
stats.SetX1NDC(0.16)
stats.SetX2NDC(0.53)
stats.SetY1NDC(0.74)
stats.SetY2NDC(0.89)
else:
text.DrawLatex(0.61, 0.54, options['scan'] + ' scan backward')
stats.SetX1NDC(0.59)
stats.SetX2NDC(0.96)
stats.SetY1NDC(0.38)
stats.SetY2NDC(0.53)
graphs.GetXaxis().SetTitle('Nominal Position [#mum]')
graphs.GetYaxis().SetTitle(options['ytitle'])
graphs.GetYaxis().SetTitleOffset(1.3)
if ('final' in options):
text.SetTextColor(1)
text.SetTextFont(42)
text.SetTextSize(0.04)
text.SetTextAlign(31)
text.DrawLatex(0.97, 0.96, O['plotsig'])
text.SetTextAlign(11)
if options['final'] == 'wip':
text.SetTextFont(52)
text.SetTextSize(0.04)
text.DrawLatex(0.13, 0.96, 'Work in Progress')
else:
text.SetTextFont(62)
text.SetTextSize(0.05)
text.DrawLatex(0.13, 0.96, 'CMS')
text.SetTextFont(52)
text.SetTextSize(0.04)
text.DrawLatex(0.22, 0.96, 'Preliminary')
for axis in [graphs.GetYaxis(), graphs.GetXaxis()]:
axis.SetTitleSize(0.05)
axis.SetLabelSize(0.04)
axis.SetLabelOffset(0.01)
axis.CenterTitle()
pad = TPad('pad', 'pad', 0, 0, 1, 0.2)
pad.Draw()
pad.cd()
pad.SetMargin(0.13, 0.03, 0.01, 0.01)
for j, residual in enumerate(residuals.GetListOfGraphs()):
residual.SetMarkerStyle(21)
residual.SetMarkerColor(2 + 2 * j)
residuals.Draw("AP")
residuals.GetXaxis().SetTitle('')
residuals.GetXaxis().SetLabelSize(0.0)
residuals.GetXaxis().SetTickSize(0.151)
residuals.GetYaxis().SetNdivisions(305)
residuals.GetYaxis().SetTickSize(0.019)
residuals.GetYaxis().SetLabelSize(0.2)
residuals.GetYaxis().SetLabelOffset(0.01)
pad.Update()
line = TLine(pad.GetUxmin(), 0.0, pad.GetUxmax(), 0.0)
line.SetLineColor(14)
line.SetLineStyle(3)
line.Draw()
canvas.cd()
text.SetTextFont(42)
text.SetTextSize(0.05)
text.SetTextAngle(90.0)
text.DrawLatex(0.035, 0.0, 'Resid. ' + options['restitle'])
if not 'final' in options:
drawSignature(filename)
# canvas.Modified()
# canvas.Update()
canvas.Print(filepath)
canvas.Close()
closeRootFile(f, name)
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)