def rotate():
if rotate.do_360:
functions.adjust(0, numpy.pi/6)
rospy.sleep(2)
rotate.rotate_turn_counter += 1
if rotate.rotate_turn_counter == 12:
rotate.do_360 = False
rotate.rotate_turn_counter = 0
return rotate.do_360
def patrol():
if patrol.do_360:
functions.adjust(0, numpy.pi/6)
rospy.sleep(2)
patrol.patrol_turn_counter += 1
if patrol.patrol_turn_counter == 12:
patrol.do_360 = False
patrol.patrol_turn_counter = 0
else:
functions.patrol_movebase(patrol.patrol_positions_x[patrol.position_index], patrol.patrol_positions_y[patrol.position_index])
patrol.position_index +=1
if patrol.position_index == 7:
patrol.position_index = 0
patrol.do_360 = True
def runFit(evt, ip, vtrk, v, x, ktrkstr, kstr, param, img, hResoData, hResoMC):
ROOT.gROOT.Reset()
ROOT.gROOT.SetBatch()
pstyle = style.SetPlotStyle(1, 'FIT')
pstyle.SetOptFit(1111)
figs = []
if hResoData.GetEntries() < 10:
# print 'No stats in data: '+hResoData.GetName(), ktrkstr
return figs, x, ktrkstr, kstr, -1, -1, -1, -1, -1, -1, -1, -1
if hResoMC.GetEntries() < 10:
# print 'No stats in mc: '+hResoMC.GetName(), ktrkstr
return figs, x, ktrkstr, kstr, -1, -1, -1, -1, -1, -1, -1, -1
if param in ['pt', 'phi']:
if options.selection == '':
rResoData = fit.rebin(hResoData, 60, 30)
rResoMC = fit.rebin(hResoMC, 60, 30)
elif kstr == '_pt7p36to7p6':
rResoData = fit.rebin(hResoData, 80, 30)
rResoMC = fit.rebin(hResoMC, 80, 30)
else:
rResoData = fit.rebin(hResoData, 50, 30)
rResoMC = fit.rebin(hResoMC, 50, 30)
rmax = max(rResoData, rResoMC)
hResoData = hResoData.Rebin(rmax)
hResoMC = hResoMC.Rebin(rmax)
else:
if options.selection != '_pt3p0to10p0' and options.type == 'pv':
rResoData = fit.rebin(hResoData, 1000, 30)
rResoMC = fit.rebin(hResoMC, 1000, 30)
rmax = max(rResoData, rResoMC)
hResoData = hResoData.Rebin(rmax)
hResoMC = hResoMC.Rebin(rmax)
elif options.type == 'bs' and options.qcd:
rResoData = fit.rebin(hResoData, 500, 30)
rResoMC = fit.rebin(hResoMC, 500, 30)
rmax = max(rResoData, rResoMC)
hResoData = hResoData.Rebin(rmax)
hResoMC = hResoMC.Rebin(rmax)
elif options.type == 'bs' and options.selection == '_pt0p0to1p0':
rResoData = fit.rebin(hResoData, 1000, 30)
rResoMC = fit.rebin(hResoMC, 1000, 30)
rmax = max(rResoData, rResoMC)
hResoData = hResoData.Rebin(rmax)
hResoMC = hResoMC.Rebin(rmax)
else:
rResoData = fit.rebin(hResoData, 500, 30)
rResoMC = fit.rebin(hResoMC, 500, 30)
rmax = max(rResoData, rResoMC)
hResoData = hResoData.Rebin(rmax)
hResoMC = hResoMC.Rebin(rmax)
for h in [hResoData]:
h.SetMarkerStyle(c.datamrk)
h.SetMarkerSize(0.7)
h.SetMarkerColor(1)
h.SetLineColor(1)
for h in [hResoMC]:
h.SetMarkerSize(0)
h.SetMarkerColor(c.mccol)
h.SetLineColor(c.mccol)
h.SetFillColor(c.mccol)
h.SetLineStyle(1)
intResoMC = hResoMC.Integral()
intResoData = hResoData.Integral()
hResoMC.Scale(intResoData / intResoMC)
maxResoData = hResoData.GetMaximum()
maxResoMC = hResoMC.GetMaximum()
hResoMC.SetMaximum(1.2 * max(maxResoData, maxResoMC))
hResoMC.SetMinimum(0.)
selName = 'N_{trk}'
units = ''
if options.parampv == 'sumTrackPt':
selName = '#sump_{T}'
units = ' GeV'
elif options.parampv == 'sumTrackPtSq':
selName = '#sqrt{#sump^{2}_{T}}'
units = ' GeV'
# Resolution
c1 = ROOT.TCanvas()
hResoMC.Draw('hist')
hResoData.Draw('e1 sames')
fun.adjust(hResoMC, hResoData, nsig=2.0)
if options.fit:
if options.method == 'fwhm':
nsig = 2.0
else:
ffit = '3g'
nsig = 2.0
if x == 'dz': ffit = '3g'
resoChi2MC = 1e+10
resResoMC, resoMC, resoErrMC, resoChi2MC = fit.doFit('mcfit',
hResoMC,
x,
kstr,
c.mcfit,
ffit,
nsig=nsig,
nTries=3)
resoChi2Data = 1e+10
resResoData, resoData, resoErrData, resoChi2Data = fit.doFit('datafit',
hResoData,
x,
kstr,
1,
ffit,
nsig=nsig,
nTries=3)
sysErrData, sysErrMC = hResoData.GetXaxis().GetBinWidth(
2), hResoMC.GetXaxis().GetBinWidth(2)
resResoMC.Draw("same")
resResoData.Draw("same")
if options.method == 'fwhm':
# get resolution estimation from bins using the results of the maximum fit
resoData, resoErrData, sysErrData = fit.fwhm(hResoData,
resResoData,
nmin=10000)
resoMC, resoErrMC, sysErrMC = fit.fwhm(hResoMC,
resResoMC,
nmin=10000)
resResoData.SetLineStyle(2)
c1.Update()
finfoData = hResoData.GetListOfFunctions().FindObject("stats")
finfoData.__class__ = ROOT.TPaveStats
finfoData.SetX1NDC(0.7)
finfoData.SetX2NDC(0.95)
finfoData.SetY1NDC(0.20)
finfoData.SetY2NDC(0.40)
lData = ROOT.TText(0.81, 0.41, "Data (fit)")
lData.SetTextSize(0.035)
lData.SetNDC()
lData.Draw()
finfoMC = hResoMC.GetListOfFunctions().FindObject("stats")
finfoMC.__class__ = ROOT.TPaveStats
finfoMC.SetX1NDC(0.7)
finfoMC.SetX2NDC(0.95)
finfoMC.SetY1NDC(0.45)
finfoMC.SetY2NDC(0.65)
lMC = ROOT.TText(0.81, 0.66, "Simulation (fit)")
lMC.SetTextSize(0.035)
lMC.SetNDC()
lMC.Draw()
else:
resoData, resoErrData, sysErrData = fit.fwhm(hResoData, nmin=10000)
resoMC, resoErrMC, sysErrMC = fit.fwhm(hResoMC, nmin=10000)
if resoData * resoMC == 0.:
resoData, resoErrData, sysErrData = 0., 0., 0.
resoMC, resoErrMC, sysErrMC = 0., 0., 0.
xLabel = x
if x == 'd0': xLabel = 'd_{xy}'
elif x == 'dz': xLabel = 'd_{z}'
lDataReso = ROOT.TLatex(
0.20, 0.61, "#sigma^{Data}_{" + xLabel + "} = %.1f #mum" % (resoData))
lDataReso.SetNDC()
lDataReso.SetTextFont(43)
lDataReso.SetTextSize(20)
lDataReso.Draw()
lMCReso = ROOT.TLatex(
0.20, 0.70, "#sigma^{Sim.}_{" + xLabel + "} = %.1f #mum" % (resoMC))
lMCReso.SetNDC()
lMCReso.SetTextFont(43)
lMCReso.SetTextSize(20)
lMCReso.Draw()
lBin = ROOT.TLatex(0.43, 0.20, "Bin = %.1f #mum" % (sysErrData))
lBin.SetNDC()
lBin.SetTextFont(43)
lBin.SetTextSize(14)
lBin.Draw()
if ip != 'bs':
lSelPV = ROOT.TLatex(
0.20, 0.85,
str(vtrk['bins'][1]) + ' < ' + selName + ' < ' +
str(vtrk['bins'][2]) + units)
lSelPV.SetTextSize(0.035)
lSelPV.SetNDC()
lSelPV.Draw()
else:
lSelPVx = ROOT.TLatex(
0.20, 0.87,
'Beam width (x) = %.1f #mum' % (vtrk['beamwidthx'][int(ktrkstr)]))
lSelPVy = ROOT.TLatex(
0.20, 0.83,
'Beam width (y) = %.1f #mum' % (vtrk['beamwidthy'][int(ktrkstr)]))
lSelPVx.SetTextSize(0.032)
lSelPVy.SetTextSize(0.032)
lSelPVx.SetNDC()
lSelPVy.SetNDC()
lSelPVx.Draw()
lSelPVy.Draw()
pLabel = 'p_{T}'
pUnits = 'GeV'
pPrec = '%.2f'
if param == 'eta':
pLabel = '#eta'
pUnits = ''
elif param == 'phi':
pLabel = '#phi'
pUnits = ''
elif param == 'npv':
pLabel = 'N_{PV}'
pUnits = ''
pPrec = '%d'
elif param == 'dr':
pLabel = '#DeltaR'
pUnits = ''
lSel = ROOT.TLatex(
0.20, 0.78, (pPrec + ' < ' + pLabel + ' < ' + pPrec + ' ' + pUnits) %
(v['bins'][1], v['bins'][2]))
lSel.SetTextSize(0.035)
lSel.SetNDC()
lSel.Draw()
c1.Update()
leg = ROOT.TLegend(0.82, 0.92, 0.990, 0.75)
leg.SetFillColor(253)
leg.SetBorderSize(0)
leg.AddEntry(hResoData, "Data", "p")
leg.AddEntry(hResoMC, "Simulation", "f")
if options.fit:
leg.AddEntry(resResoData, "Data (fit)", "l")
leg.AddEntry(resResoMC, "Simulation (fit)", "l")
leg.Draw()
t1, t2, t3, t4 = style.cmslabel(1, c.year, evt)
t1.Draw()
t2.Draw()
t3.Draw()
t4.Draw()
# b = fun.isbadfit(resoChi2MC, resoChi2Data)
# b.Draw()
foutput = 'ip' + ip + 'Reso_' + x + ktrkstr + kstr
if ip == 'bs': foutput = 'ip' + ip + 'Reso_' + x + kstr + '_' + ktrkstr
figs.append(foutput)
c1.Print(options.output + '/' + foutput + '.' + img)
c1.Clear()
return figs, x, ktrkstr, kstr, resoData, resoErrData, intResoData, resoMC, resoErrMC, intResoMC, sysErrData, sysErrMC
def runFit(evt, v, x, kstr, img, hResoData, hResoMC, hPullData, hPullMC):
ROOT.gROOT.Reset()
ROOT.gROOT.SetBatch()
pstyle = style.SetPlotStyle(1, 'FIT')
pstyle.SetOptFit(1111)
figs = []
if hResoData.GetEntries() < 10:
print 'No stats in data: ' + hResoData.GetName()
sys.exit()
if hResoMC.GetEntries() < 10:
print 'No stats in mc: ' + hResoMC.GetName()
sys.exit()
for h in [hResoData, hPullData]:
h.SetMarkerStyle(c.datamrk)
h.SetMarkerSize(0.7)
h.SetMarkerColor(1)
h.SetLineColor(1)
for h in [hResoMC, hPullMC]:
h.SetMarkerSize(0)
h.SetMarkerColor(c.mccol)
h.SetLineColor(c.mccol)
h.SetFillColor(c.mccol)
h.SetLineStyle(1)
intResoMC = hResoMC.Integral()
intResoData = hResoData.Integral()
hResoMC.Scale(intResoData / intResoMC)
intPullMC = hPullMC.Integral()
intPullData = hPullData.Integral()
hPullMC.Scale(intPullData / intPullMC)
# Rebin in case of fine-bin measurement
# hResoData = hResoData.Rebin(2)
# hResoMC = hResoMC.Rebin(2)
# hPullData = hPullData.Rebin(5)
# hPullMC = hPullMC.Rebin(5)
maxResoData = hResoData.GetMaximum()
maxResoMC = hResoMC.GetMaximum()
hResoMC.SetMaximum(1.2 * max(maxResoData, maxResoMC))
hResoMC.SetMinimum(0.)
maxPullData = hPullData.GetMaximum()
maxPullMC = hPullMC.GetMaximum()
hPullMC.SetMaximum(1.2 * max(maxPullData, maxPullMC))
hPullMC.SetMinimum(0.)
selName = 'N_{trk}'
units = ''
if options.param == 'sumTrackPt':
selName = '#sump_{T}'
units = ' GeV'
elif options.param == 'sumTrackPtSq':
selName = '#sqrt{#sump^{2}_{T}}'
units = ' GeV'
# Resolution
c1 = ROOT.TCanvas()
fun.adjust(hResoMC, hResoData, nsig=5)
hResoMC.Draw('hist')
hResoData.Draw('e1 sames')
resResoMC, resoMC, resoErrMC, resoChi2MC = fit.doFit('mcfit_reso',
hResoMC,
x,
kstr,
c.mcfit,
'2g',
nsig=3,
nTries=3)
resResoMC.Draw("same")
resResoData, resoData, resoErrData, resoChi2Data = fit.doFit(
'datafit_reso', hResoData, x, kstr, 1, '2g', nsig=3, nTries=3)
resResoData.Draw("same")
resResoData.SetLineStyle(2)
sysResoData = hResoData.GetXaxis().GetBinWidth(2)
sysResoMC = hResoMC.GetXaxis().GetBinWidth(2)
c1.Update()
finfoData = hResoData.GetListOfFunctions().FindObject("stats")
finfoData.__class__ = ROOT.TPaveStats
finfoData.SetX1NDC(0.7)
finfoData.SetX2NDC(0.95)
finfoData.SetY1NDC(0.20)
finfoData.SetY2NDC(0.40)
lData = ROOT.TText(0.81, 0.41, "Data (fit)")
lData.SetTextSize(0.035)
lData.SetNDC()
lData.Draw()
finfoMC = hResoMC.GetListOfFunctions().FindObject("stats")
finfoMC.__class__ = ROOT.TPaveStats
finfoMC.SetX1NDC(0.7)
finfoMC.SetX2NDC(0.95)
finfoMC.SetY1NDC(0.45)
finfoMC.SetY2NDC(0.65)
lMC = ROOT.TText(0.81, 0.66, "Simulation (fit)")
lMC.SetTextSize(0.035)
lMC.SetNDC()
lMC.Draw()
lDataReso = ROOT.TLatex(
0.20, 0.63, "#sigma^{Data}_{" + x + "} = %.1f #mum" % (resoData))
lDataReso.SetNDC()
lDataReso.SetTextFont(43)
lDataReso.SetTextSize(20)
lDataReso.Draw()
lMCReso = ROOT.TLatex(0.20, 0.70,
"#sigma^{Sim.}_{" + x + "} = %.1f #mum" % (resoMC))
lMCReso.SetNDC()
lMCReso.SetTextFont(43)
lMCReso.SetTextSize(20)
lMCReso.Draw()
lSel = ROOT.TLatex(
0.20, 0.80,
str(v['bins'][1]) + ' < ' + selName + ' < ' + str(v['bins'][2]) +
units)
lSel.SetTextSize(0.035)
lSel.SetNDC()
lSel.Draw()
c1.Update()
leg = ROOT.TLegend(0.82, 0.92, 0.990, 0.75)
leg.SetFillColor(253)
leg.SetBorderSize(0)
leg.AddEntry(hResoData, "Data", "p")
leg.AddEntry(hResoMC, "Simulation", "f")
leg.AddEntry(resResoData, "Data (fit)", "l")
leg.AddEntry(resResoMC, "Simulation (fit)", "l")
leg.Draw()
t1, t2, t3, t4 = style.cmslabel(1, c.year, evt)
t1.Draw()
t2.Draw()
t3.Draw()
t4.Draw()
b = fun.isbadfit(resoChi2MC, resoChi2Data)
b.Draw()
foutput = 'pvReso_' + x + kstr
figs.append(foutput)
c1.Print(options.output + '/' + foutput + '.' + img)
c1.Clear()
# Pull
fun.adjust(hPullMC, hPullData, nsig=5)
hPullMC.Draw('hist')
hPullData.Draw('e1 sames')
resPullMC, pullMC, pullErrMC, pullChi2MC = fit.doFit('mcfit_pull',
hPullMC,
x,
kstr,
c.mcfit,
'1g',
nsig=2.5,
nTries=3)
resPullMC.Draw("same")
resPullData, pullData, pullErrData, pullChi2Data = fit.doFit(
'datafit_pull', hPullData, x, kstr, 1, '1g', nsig=2.5, nTries=3)
resPullData.Draw("same")
resPullData.SetLineStyle(2)
sysPullData = hPullData.GetXaxis().GetBinWidth(2)
sysPullMC = hPullMC.GetXaxis().GetBinWidth(2)
c1.Update()
finfoData = hPullData.GetListOfFunctions().FindObject("stats")
finfoData.__class__ = ROOT.TPaveStats
finfoData.SetX1NDC(0.7)
finfoData.SetX2NDC(0.95)
finfoData.SetY1NDC(0.20)
finfoData.SetY2NDC(0.40)
lData = ROOT.TText(0.81, 0.41, "Data (fit)")
lData.SetTextSize(0.035)
lData.SetNDC()
lData.Draw()
finfoMC = hPullMC.GetListOfFunctions().FindObject("stats")
finfoMC.__class__ = ROOT.TPaveStats
finfoMC.SetX1NDC(0.7)
finfoMC.SetX2NDC(0.95)
finfoMC.SetY1NDC(0.45)
finfoMC.SetY2NDC(0.65)
lMC = ROOT.TText(0.81, 0.66, "Simulation (fit)")
lMC.SetTextSize(0.035)
lMC.SetNDC()
lMC.Draw()
lDataPull = ROOT.TLatex(0.20, 0.63,
"#sigma^{Data}_{" + x + "} = %.2f" % (pullData))
lDataPull.SetNDC()
lDataPull.SetTextFont(43)
lDataPull.SetTextSize(20)
lDataPull.Draw()
lMCPull = ROOT.TLatex(0.20, 0.70,
"#sigma^{Sim.}_{" + x + "} = %.2f" % (pullMC))
lMCPull.SetNDC()
lMCPull.SetTextFont(43)
lMCPull.SetTextSize(20)
lMCPull.Draw()
lSel = ROOT.TLatex(
0.20, 0.80,
str(v['bins'][1]) + ' < ' + selName + ' < ' + str(v['bins'][2]) +
units)
lSel.SetTextSize(0.035)
lSel.SetNDC()
lSel.Draw()
c1.Update()
leg = ROOT.TLegend(0.82, 0.92, 0.990, 0.75)
leg.SetFillColor(253)
leg.SetBorderSize(0)
leg.AddEntry(hPullData, "Data", "p")
leg.AddEntry(hPullMC, "Simulation", "f")
leg.AddEntry(resPullData, "Data (fit)", "l")
leg.AddEntry(resPullMC, "Simulation (fit)", "l")
leg.Draw()
t1, t2, t3, t4 = style.cmslabel(1, c.year, evt)
t1.Draw()
t2.Draw()
t3.Draw()
t4.Draw()
b = fun.isbadfit(pullChi2MC, pullChi2Data)
b.Draw()
foutput = 'pvPull_' + x + kstr
figs.append(foutput)
c1.Print(options.output + '/' + foutput + '.' + img)
c1.Clear()
return figs, x, kstr, resoData, resoErrData, resoMC, resoErrMC, pullData, pullErrData, pullMC, pullErrMC, sysResoData, sysResoMC, sysPullData, sysPullMC
from functions import date
from functions import observations
from functions import setdata
from functions import getdata
from functions import deletedata
from functions import createtable
from texts import menu_text
from texts import invalidoption_text
#Menu inicial
menu_text()
option = input()
if option == '1':
total = dist()
totaltime = timerun()
adjusted = adjust(totaltime)
finalpace = calcpace(adjusted, total)
convertedpace = converttime(finalpace)
impress = toprint(convertedpace)
elif option == '2':
total = dist()
totaltime = timerun()
adjusted = adjust(totaltime)
calctemp = predictrun(adjusted, total)
convertedtemprun = converttime(calctemp)
impress = toprint(convertedtemprun)
elif option == '3':
createtable()
thedate = date()
total = dist()
totaltime = timerun()
img = cv2.imread(fn, 0)
height, width = img.shape
#use sobel operator to get x and y derivatives
sobelox = np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]])
sobeloy = np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]])
imgdx = ed.derivative(img, sobelox, height, width, 3, 3)
imgdy = ed.derivative(img, sobeloy, height, width, 3, 3)
#cv2.imwrite('dx.jpg', imgdx)
#cv2.imwrite('dy.jpg', imgdy)
#get image gradient magnitude
imgmagnitude = ed.magnitude(imgdx, imgdy, height, width)
imgmagnitudedisplay = ed.adjust(imgmagnitude, height, width)
cv2.imwrite('magnitudemap.jpg', imgmagnitudedisplay)
#get image gradient orientation
imgorientation, imgedgethin = ed.orientation(imgdx, imgdy, height, width,
imgmagnitude)
cv2.imwrite('orientation_map.jpg', imgorientation)
cv2.imwrite('edge_map_thin.jpg', imgedgethin)
#apply threshold and edgelink
threshold_low = 25
threshold_high = 50
imgedge = ed.doublethreshold(imgedgethin, height, width, threshold_low,
threshold_high)
cv2.imwrite('edge_map.jpg', imgedge)