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diff --git a/data/T2K/CC0pi/T2K_CC0PI_2DPmuCosmu_Data.root b/data/T2K/CC0pi/T2K_CC0PI_2DPmuCosmu_Data.root
index e6d858f..d61ec36 100644
Binary files a/data/T2K/CC0pi/T2K_CC0PI_2DPmuCosmu_Data.root and b/data/T2K/CC0pi/T2K_CC0PI_2DPmuCosmu_Data.root differ
diff --git a/data/T2K/CC0pi/makedatafile_t2kcc0pi.py b/data/T2K/CC0pi/makedatafile_t2kcc0pi.py
index acc5297..e80c5ba 100644
--- a/data/T2K/CC0pi/makedatafile_t2kcc0pi.py
+++ b/data/T2K/CC0pi/makedatafile_t2kcc0pi.py
@@ -1,294 +1,296 @@
from ROOT import *
from array import *
def GetMiddle(mystr):
lims = mystr.strip().split(" - ")
val = (float(lims[0]) + float(lims[1]))/2.0
return val
def GetLowEdge(mystr):
lims = mystr.strip().split(" - ")
val = (float(lims[0]) + 0.00001)
return val
def GetHighEdge(mystr):
lims = mystr.strip().split(" - ")
val = (float(lims[1]) - 0.00001)
return val
def GetIndex(mystr):
lims = mystr.split("-")
return int(lims[0]), int(lims[1])
outfile = TFile("T2K_CC0PI_2DPmuCosmu_Data.root","RECREATE")
# ANALYSIS I
#______________________________
xedge = [0.0, 0.3, 0.4, 0.5, 0.65, 0.8, 0.95, 1.1, 1.25, 1.5, 2.0, 3.0, 5.0, 30.0]
yedge = [-1.0, 0.0, 0.6, 0.7, 0.8, 0.85, 0.9, 0.94, 0.98, 1.0]
datahist = TH2D("analysis1_data","analysis1_data",
len(xedge)-1, array('f',xedge),
len(yedge)-1, array('f',yedge))
maphist = datahist.Clone("analysis1_map")
maphist.SetTitle("analysis1_map")
counthist = datahist.Clone("analysis1_entrycount")
datapoly = TH2Poly("datapoly","datapoly", 0.0,30.0, -1.0, 1.0)
hist = None
binedges = []
histedgeslist = []
xsecvals = []
histxseclist = []
binlimits = [3,8,15,22,30,39,47,58,67]
with open("cross-section_analysisI.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
ibin = int( data[0] ) + 1
xval = round(float(GetLowEdge( data[2] )),4)
yval = round(float(GetLowEdge( data[1] )),4)
xhig = round(float(GetHighEdge( data[2] )),4)
yhig = round(float(GetHighEdge( data[1] )),4)
xsec = float( data[3] ) * 1E-38
datapoly.AddBin( xval, yval, xhig, yhig )
datapoly.SetBinContent( datapoly.GetNumberOfBins(), xsec)
binedges.append( xval )
xsecvals.append( xsec )
if ibin in binlimits:
binedges.append( xhig )
histedgeslist.append(binedges)
histxseclist.append(xsecvals)
binedges = []
xsecvals = []
datahist.Fill(xval, yval, xsec)
counthist.Fill(xval, yval, 1.0)
for i in range(maphist.GetNbinsX()):
for j in range(maphist.GetNbinsY()):
xcent = maphist.GetXaxis().GetBinCenter(i+1)
ycent = maphist.GetYaxis().GetBinCenter(j+1)
if (xcent > xval and xcent < xhig and
ycent > yval and ycent < yhig):
maphist.SetBinContent(i+1,j+1, ibin)
-data1D = TH1D("datahist","datahist", datapoly.GetNumberOfBins(), 0.0, float(datapoly.GetNumberOfBins()));
-for i in range(datapoly.GetNumberOfBins()):
- data1D.SetBinContent(i+1, datapoly.GetBinContent(i+1));
-
-outfile.cd()
-datahist.Write()
-counthist.Write()
-maphist.Write()
-datapoly.Write()
-data1D.Write()
-
-for i, obj in enumerate(histedgeslist):
- print obj
- hist = TH1D("dataslice_" + str(i), "dataslice_" + str(i), len(obj)-1, array('f',obj))
- for j in range(hist.GetNbinsX()):
- hist.SetBinContent(j+1, histxseclist[i][j])
-
- hist.GetXaxis().SetRangeUser(obj[0], obj[len(obj)-2])
- hist.Draw("HIST")
- gPad.Update()
-
- hist.SetNameTitle("dataslice_" + str(i),"dataslice_" + str(i))
- hist.Write()
-
-# Get N Bins
+# Get Covariances (keep in 1E-38 cm^2) \
nbins = 67
-print "NBins I = ", nbins
-# Get Covariances (keep in 1E-38 cm^2)
statcov = TH2D("analysis1_statcov","analysis1_statcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
systcov = TH2D("analysis1_systcov","analysis1_systcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
normcov = TH2D("analysis1_normcov","analysis1_normcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
totcov = TH2D("analysis1_totcov","analysis1_totcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
with open("covariance_statisticUncertainty_analysisI.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
xi, yi = GetIndex(data[0])
cov = float(data[1])
- statcov.SetBinContent(xi, yi, cov)
+ statcov.SetBinContent(xi + 1, yi + 1, cov)
with open("covariance_shapeSystematics_analysisI.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
xi, yi = GetIndex(data[0])
cov = float(data[1])
systcov.SetBinContent(xi + 1, yi + 1, cov)
with open("covariance_fluxNormalizationSystematics_analysisI.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
xi, yi = GetIndex(data[0])
cov = float(data[1])
normcov.SetBinContent(xi + 1, yi + 1, cov)
totcov.Add(systcov)
totcov.Add(statcov)
totcov.Add(normcov)
+
+data1D = TH1D("datahist","datahist", datapoly.GetNumberOfBins(), 0.0, float(datapoly.GetNumberOfBins()));
+for i in range(datapoly.GetNumberOfBins()):
+ data1D.SetBinContent(i+1, datapoly.GetBinContent(i+1));
+ data1D.SetBinError(i+1, sqrt(totcov.GetBinContent(i+1,i+1))*1E-38)
+
+outfile.cd()
+
+for i, obj in enumerate(histedgeslist):
+ print obj
+
+ hist = TH1D("dataslice_" + str(i), "dataslice_" + str(i), len(obj)-1, array('f',obj))
+ for j in range(hist.GetNbinsX()):
+ hist.SetBinContent(j+1, histxseclist[i][j])
+
+ hist.GetXaxis().SetRangeUser(obj[0], obj[len(obj)-2])
+ hist.Draw("HIST")
+ gPad.Update()
+
+ hist.SetNameTitle("dataslice_" + str(i),"dataslice_" + str(i))
+ hist.Write()
+
+
outfile.cd()
+datahist.Write()
+counthist.Write()
+maphist.Write()
+datapoly.Write()
+data1D.Write()
statcov.Write()
systcov.Write()
totcov.Write()
normcov.Write()
# ANALYSIS II
#______________________________
xedge = [0.2, 0.35, 0.5, 0.65, 0.8, 0.95, 1.1, 1.25, 1.5, 2.0, 3.0, 5.0, 30.0]
yedge = [0.6, 0.7, 0.8, 0.85, 0.9, 0.925, 0.95, 0.975, 1.0]
datahist = TH2D("analysis2_data","analysis2_data",
len(xedge)-1, array('f',xedge),
len(yedge)-1, array('f',yedge))
maphist = datahist.Clone("analysis2_map")
maphist.SetTitle("analysis2_map")
counthist = datahist.Clone("analysis2_entrycount")
# Get Data Entries
entries = []
count = 0
with open("rps_crossSection_analysis2.txt") as f:
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
ibin = int( data[0] ) + 1
xval = GetMiddle( data[2] )
yval = GetMiddle( data[1] )
xsec = float( data[3] ) * 1E-38
datahist.Fill(xval, yval, xsec)
maphist.Fill(xval, yval, ibin)
counthist.Fill(xval, yval, 1.0)
# print ibin, "Map Value"
# Get N Bins
nbins = int(maphist.GetMaximum())
print "NBins I = ", nbins
# Get Covariances (keep in 1E-38 cm^2)
statcov = TH2D("analysis2_statcov","analysis2_statcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
systcov = TH2D("analysis2_systcov","analysis2_systcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
normcov = TH2D("analysis2_normcov","analysis2_normcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
totcov = TH2D("analysis2_totcov","analysis2_totcov", nbins, 0.0, float(nbins), nbins, 0.0, float(nbins));
with open("rps_statsCov_analysis2.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
xi, yi = GetIndex(data[0])
cov = float(data[1])
- statcov.SetBinContent(xi, yi, cov)
+ statcov.SetBinContent(xi + 1, yi + 1, cov)
with open("rps_systCov_analysis2.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
xi, yi = GetIndex(data[0])
cov = float(data[1])
systcov.SetBinContent(xi + 1, yi + 1, cov)
with open("rps_fluxNormCov_analysis2.txt") as f:
count = 0
for line in f:
count += 1
if (count < 4): continue
data = line.strip().split("|")
if (len(data) < 1): continue
xi, yi = GetIndex(data[0])
cov = float(data[1])
normcov.SetBinContent(xi + 1, yi + 1, cov)
totcov.Add(systcov)
totcov.Add(statcov)
totcov.Add(normcov)
outfile.cd()
datahist.Write()
maphist.Write()
counthist.Write()
statcov.Write()
systcov.Write()
totcov.Write()
normcov.Write()
# LocalWords: xval
diff --git a/data/T2K/CC0pi/rps_systCov_analysis2.txt b/data/T2K/CC0pi/rps_systCov_analysis2.txt
index c5742a2..3c6d968 100644
--- a/data/T2K/CC0pi/rps_systCov_analysis2.txt
+++ b/data/T2K/CC0pi/rps_systCov_analysis2.txt
@@ -1,9219 +1,9219 @@
Units: cross-section (10^-38 cm2/(nucleon x GeV))
row (bin i) - column (bin j) | sigma_i x sigma_j x rho_ij
0 - 0 | 0.01032782641
0 - 1 | 0.0108180208299
0 - 2 | 0.00786964606803
0 - 3 | 0.00193139030968
0 - 4 | 0.00024987106812
0 - 5 | 0.000199263562451
0 - 6 | -5.61197638164e-05
0 - 7 | -1.04371850562e-05
0 - 8 | 0.0
0 - 9 | 0.0
0 - 10 | 0.0
0 - 11 | 0.0
0 - 12 | 0.00725724234117
0 - 13 | 0.00925039953685
0 - 14 | 0.00701414334472
0 - 15 | 0.00196275612097
0 - 16 | 0.00218592771666
0 - 17 | 0.000526274761454
0 - 18 | 0.000118864327899
0 - 19 | 0.000153699768568
0 - 20 | -1.06059542869e-05
0 - 21 | 0.0
0 - 22 | 0.0
0 - 23 | 0.0
0 - 24 | 0.00762330621865
0 - 25 | 0.00936702233237
0 - 26 | 0.00734724411651
0 - 27 | 0.0026991733176
0 - 28 | 0.00258441597314
0 - 29 | 0.00197362259173
0 - 30 | 0.000473234066476
0 - 31 | 0.000320513316156
0 - 32 | -0.000948168810462
0 - 33 | -0.000136434280686
0 - 34 | 0.0
0 - 35 | 0.0
0 - 36 | 0.00857885443639
0 - 37 | 0.0100386068366
0 - 38 | 0.00823549177393
0 - 39 | 0.00725690539939
0 - 40 | 0.00324561803762
0 - 41 | 0.00246960104105
0 - 42 | 0.00128498202076
0 - 43 | 0.00077631261023
0 - 44 | -0.000338015547979
0 - 45 | -0.000765836740289
0 - 46 | 0.0
0 - 47 | 0.0
0 - 48 | 0.00807993387852
0 - 49 | 0.00616382006363
0 - 50 | 0.00742085943667
0 - 51 | 0.00531037922662
0 - 52 | 0.00404220571018
0 - 53 | 0.00535248707498
0 - 54 | 0.00131424253197
0 - 55 | 0.0222488557125
0 - 56 | 0.000743196781925
0 - 57 | -4.39992678139e-05
0 - 58 | 1.67500068122e-07
0 - 59 | 0.0
0 - 60 | 0.00757011500512
0 - 61 | 0.00279485588595
0 - 62 | 0.000574069419969
0 - 63 | -0.00186754485194
0 - 64 | -0.0015099728354
0 - 65 | 0.00424116677819
0 - 66 | 0.00470429596863
0 - 67 | 0.00197113830862
0 - 68 | 0.00102743617456
0 - 69 | -8.9502972186e-05
0 - 70 | -3.87039978083e-05
0 - 71 | 0.0
0 - 72 | 0.00626571121633
0 - 73 | 0.0101652144923
0 - 74 | 0.0152565774931
0 - 75 | 0.0172984228592
0 - 76 | 0.0144494146074
0 - 77 | 0.00215971301558
0 - 78 | 0.00320018389697
0 - 79 | 0.00252287353601
0 - 80 | 0.00146432512511
0 - 81 | 0.00118290409502
0 - 82 | 0.000308989244786
0 - 83 | 3.13326041213e-07
0 - 84 | 0.00229149359019
0 - 85 | 0.00481620895723
0 - 86 | 0.00473625865517
0 - 87 | 0.006340450537
0 - 88 | 0.00447960875436
0 - 89 | 0.000906874287803
0 - 90 | 0.00230199524518
0 - 91 | 0.00254598026848
0 - 92 | 0.00172735378144
0 - 93 | 0.00125301107251
0 - 94 | 0.00104598311201
0 - 95 | 3.60236316688e-05
1 - 0 | 0.0108180208299
1 - 1 | 0.0145778273894
1 - 2 | 0.0090820202126
1 - 3 | 0.00248932537785
1 - 4 | 0.000543518499895
1 - 5 | 0.000345274800472
1 - 6 | 2.39035772153e-05
1 - 7 | 2.08810767598e-05
1 - 8 | 0.0
1 - 9 | 0.0
1 - 10 | 0.0
1 - 11 | 0.0
1 - 12 | 0.00830431957504
1 - 13 | 0.0114178972261
1 - 14 | 0.00820267464135
1 - 15 | 0.00278787478704
1 - 16 | 0.0025782770829
1 - 17 | 0.000860617988881
1 - 18 | 0.000324911663803
1 - 19 | 0.00024920507364
1 - 20 | 1.62389166501e-05
1 - 21 | 0.0
1 - 22 | 0.0
1 - 23 | 0.0
1 - 24 | 0.00880773826827
1 - 25 | 0.011494512972
1 - 26 | 0.00888362476058
1 - 27 | 0.00387500625896
1 - 28 | 0.00326007668979
1 - 29 | 0.00238345177095
1 - 30 | 0.00092106383001
1 - 31 | 0.000569742762073
1 - 32 | -0.000936303030456
1 - 33 | -0.00014345730992
1 - 34 | 0.0
1 - 35 | 0.0
1 - 36 | 0.00957049485976
1 - 37 | 0.0118402794482
1 - 38 | 0.00962235818452
1 - 39 | 0.00812396116569
1 - 40 | 0.0040870865094
1 - 41 | 0.00309052571364
1 - 42 | 0.0019290717455
1 - 43 | 0.00127901795903
1 - 44 | -0.000118396593961
1 - 45 | -0.000825387156266
1 - 46 | 0.0
1 - 47 | 0.0
1 - 48 | 0.00900812997902
1 - 49 | 0.00818637462594
1 - 50 | 0.00926080489665
1 - 51 | 0.00671978297538
1 - 52 | 0.00515235250991
1 - 53 | 0.00617448367916
1 - 54 | 0.00206233946089
1 - 55 | 0.021253284664
1 - 56 | 0.0011473662762
1 - 57 | 0.000102529425147
1 - 58 | 1.54693203685e-05
1 - 59 | 0.0
1 - 60 | 0.00864535454908
1 - 61 | 0.00491304299721
1 - 62 | 0.00334721030457
1 - 63 | 0.000647558077231
1 - 64 | 0.000368887789053
1 - 65 | 0.00514142752885
1 - 66 | 0.00546268144522
1 - 67 | 0.00274657032443
1 - 68 | 0.00167395868741
1 - 69 | 0.000224982899631
1 - 70 | 2.47553656086e-05
1 - 71 | 0.0
1 - 72 | 0.0072260698718
1 - 73 | 0.0117721993042
1 - 74 | 0.0159759563853
1 - 75 | 0.0172867507994
1 - 76 | 0.0145989538982
1 - 77 | 0.00359663809602
1 - 78 | 0.00414500797315
1 - 79 | 0.00357508857343
1 - 80 | 0.00235942944117
1 - 81 | 0.0017191806711
1 - 82 | 0.000490638824414
1 - 83 | 2.12561622041e-06
1 - 84 | 0.0030850025486
1 - 85 | 0.00612857737993
1 - 86 | 0.00601995008058
1 - 87 | 0.00723738364666
1 - 88 | 0.00515742562265
1 - 89 | 0.00203672925602
1 - 90 | 0.00321652691664
1 - 91 | 0.00343058166403
1 - 92 | 0.00265928243105
1 - 93 | 0.00203462625572
1 - 94 | 0.00152840995187
1 - 95 | 6.10118531234e-05
2 - 0 | 0.00786964606803
2 - 1 | 0.0090820202126
2 - 2 | 0.00797110120867
2 - 3 | 0.00203526682356
2 - 4 | 0.000475647333105
2 - 5 | 0.000277339726086
2 - 6 | 8.06402635155e-06
2 - 7 | 4.74473389075e-06
2 - 8 | 0.0
2 - 9 | 0.0
2 - 10 | 0.0
2 - 11 | 0.0
2 - 12 | 0.00599770253652
2 - 13 | 0.00721400229273
2 - 14 | 0.00628016178814
2 - 15 | 0.00211595635276
2 - 16 | 0.00192482772257
2 - 17 | 0.000673891083816
2 - 18 | 0.000264372487888
2 - 19 | 0.000198611516928
2 - 20 | 1.13431953358e-05
2 - 21 | 0.0
2 - 22 | 0.0
2 - 23 | 0.0
2 - 24 | 0.00637550053162
2 - 25 | 0.00727272495208
2 - 26 | 0.00644467632049
2 - 27 | 0.00271235453541
2 - 28 | 0.00236091168401
2 - 29 | 0.00184081754738
2 - 30 | 0.000690646784464
2 - 31 | 0.000464324733051
2 - 32 | -0.000712200603335
2 - 33 | -0.000114446249989
2 - 34 | 0.0
2 - 35 | 0.0
2 - 36 | 0.00715442083662
2 - 37 | 0.00772043448083
2 - 38 | 0.0070146157462
2 - 39 | 0.00589903669955
2 - 40 | 0.00299458976578
2 - 41 | 0.00224012088209
2 - 42 | 0.00134154280523
2 - 43 | 0.00100825719067
2 - 44 | -7.67605804839e-05
2 - 45 | -0.000665592533033
2 - 46 | 0.0
2 - 47 | 0.0
2 - 48 | 0.00675823989816
2 - 49 | 0.00500914823664
2 - 50 | 0.00628367329594
2 - 51 | 0.00462982918735
2 - 52 | 0.00367652404787
2 - 53 | 0.00434811509019
2 - 54 | 0.0014494710316
2 - 55 | 0.0176846269943
2 - 56 | 0.000926893691946
2 - 57 | 9.57296915295e-05
2 - 58 | 1.24033586313e-05
2 - 59 | 0.0
2 - 60 | 0.006444257335
2 - 61 | 0.00276724267823
2 - 62 | 0.00163662686412
2 - 63 | -0.000248290501065
2 - 64 | -0.000222544588559
2 - 65 | 0.00364362981625
2 - 66 | 0.00389739988712
2 - 67 | 0.00207876795473
2 - 68 | 0.00131082601607
2 - 69 | 0.000235969443513
2 - 70 | 2.02931363556e-05
2 - 71 | 0.0
2 - 72 | 0.00539105506912
2 - 73 | 0.0078430203291
2 - 74 | 0.011521647503
2 - 75 | 0.0130743357289
2 - 76 | 0.0106054649129
2 - 77 | 0.00220009254348
2 - 78 | 0.00289380096499
2 - 79 | 0.00241431422527
2 - 80 | 0.00177146812115
2 - 81 | 0.00148459386456
2 - 82 | 0.000490915534417
2 - 83 | 1.63135619153e-06
2 - 84 | 0.00225565245924
2 - 85 | 0.00392170889588
2 - 86 | 0.00392191373561
2 - 87 | 0.00523790953475
2 - 88 | 0.00362181112298
2 - 89 | 0.00120977448322
2 - 90 | 0.00212668159646
2 - 91 | 0.00228214810817
2 - 92 | 0.00183276394893
2 - 93 | 0.00162944691279
2 - 94 | 0.00162098262583
2 - 95 | 7.7193312075e-05
3 - 0 | 0.00193139030968
3 - 1 | 0.00248932537785
3 - 2 | 0.00203526682356
3 - 3 | 0.00100371305736
3 - 4 | 0.000411256262232
3 - 5 | 0.000170496065323
3 - 6 | 5.96100344844e-05
3 - 7 | 2.40094045965e-05
3 - 8 | 0.0
3 - 9 | 0.0
3 - 10 | 0.0
3 - 11 | 0.0
3 - 12 | 0.00151467240963
3 - 13 | 0.00195832478714
3 - 14 | 0.00194477108428
3 - 15 | 0.00100788193687
3 - 16 | 0.000605630862435
3 - 17 | 0.000372336829169
3 - 18 | 0.00019190419152
3 - 19 | 0.000103874301554
3 - 20 | 2.80038893394e-05
3 - 21 | 0.0
3 - 22 | 0.0
3 - 23 | 0.0
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