double
Gaussian::Cdf(size_t dim_, double val_) const{
double nDevs = (val_ - GetMean(dim_))/GetStDev(dim_);
if (nDevs > fCdfCutOff)
return 1;
if(nDevs < -1 * fCdfCutOff)
return 0;
return gsl_cdf_gaussian_P(val_ - GetMean(dim_), GetStDev(dim_));
}
//circle equation |(x,y)-(a,b)|^2 = c^2
//f(a,b,c) = x^2+y^2-2ax-2yb+a^2+b^2-c^2 = 0
//let u=-2a, v=-2b, w = a^2+b^2-c^2
//f(u,v,w) = x^2+y^2+ux+vy+w
//min g(u,v,w) = 1/2 sum_(x,y) f(u,v,w)^2
//dg/du = sum_(x,y) df/du(u,v,w) f(u,v,w)
// = sum_(x,y) x f(u,v,w)
//dg/dv = sum_(x,y) y f(u,v,w)
//dg/dw = sum_(x,y) f(u,v,w)
//dg/dparams = [sum x^2, sum xy, sum x] *params + [sum x(x^2+y^2)] = 0
// [sum xy, sum y^2, sum y] [sum y(x^2+y^2)]
// [sum x, sum y, sum 1] [sum (x^2+y^2) ]
//least squares fit
//A = matrix of (x,y,1)
//b = matrix of (x^2+y^2)
bool FitCircle(const std::vector<Vector2>& pts,Circle2D& c)
{
Vector2 mean=GetMean(pts);
Matrix3 A(Zero);
Vector3 b(Zero);
for(size_t i=0;i<pts.size();i++) {
Vector3 v(pts[i].x-mean.x,pts[i].y-mean.x,1.0);
Rank1Update(A,v,v);
Real n = pts[i].distanceSquared(mean);
b.x += (pts[i].x-mean.x)*n;
b.y += (pts[i].y-mean.x)*n;
b.z += n;
}
Matrix3 Ainv;
if(!Ainv.setInverse(A)) return false;
Vector3 params = Ainv*b;
//recover circle from params
c.center.x = -params.x*0.5;
c.center.y = -params.y*0.5;
c.radius = c.center.normSquared()-params.z;
if(c.radius < 0) return false;
c.radius = Sqrt(c.radius);
c.center += mean;
return true;
}
void DataSignal :: WriteSmartPeakInfoToXML (RGTextOutput& text, const RGString& indent, const RGString& bracketTag, const RGString& locationTag) {
int peak;
Endl endLine;
RGString suffix;
// if (HasCrossChannelSignalLink ()) {
if (HasAlleleName () && (!mDoNotCall)) {
peak = (int) floor (Peak () + 0.5);
if (mOffGrid)
suffix = " OL";
text << indent << "<" << bracketTag << ">" << endLine;
text << indent << "\t<mean>" << GetMean () << "</mean>" << endLine;
text << indent << "\t<height>" << peak << "</height>" << endLine;
text << indent << "\t<BPS>" << GetBioID () << "</BPS>" << endLine;
// text << indent << "\t<" << locationTag << ">" << (int) floor (GetApproximateBioID () + 0.5) << "</" << locationTag << ">" << endLine;
text << indent << "\t<" << locationTag << ">" << GetApproximateBioID () << "</" << locationTag << ">" << endLine;
text << indent << "\t<PeakArea>" << TheoreticalArea () << "</PeakArea>" << endLine;
text << indent << "\t<allele>" << GetAlleleName () << suffix << "</allele>" << endLine;
text << indent << "\t<width>" << 4.0 * GetStandardDeviation () << "</width>" << endLine;
text << indent << "\t<fit>" << GetCurveFit () << "</fit>" << endLine;
text << indent << "</" + bracketTag << ">" << endLine;
}
// }
}
bool DataSignal :: ReportSmartNoticeObjects (RGTextOutput& text, const RGString& indent, const RGString& delim) {
if (NumberOfSmartNoticeObjects () > 0) {
int msgLevel = GetHighestMessageLevelWithRestrictionSM ();
RGDListIterator it (*mSmartMessageReporters);
SmartMessageReporter* nextNotice;
text.SetOutputLevel (msgLevel);
if (!text.TestCurrentLevel ()) {
text.ResetOutputLevel ();
return false;
}
Endl endLine;
text << endLine;
text << indent << "Notices for curve with (Mean, Sigma, Peak, 2Content, Fit) = " << delim << delim << delim << delim << delim << delim;
text << GetMean () << delim << GetStandardDeviation () << delim << Peak () << delim << GetScale (2) << delim << Fit << endLine;
while (nextNotice = (SmartMessageReporter*) it ())
text << indent << nextNotice->GetMessage () << nextNotice->GetMessageData () << endLine;
text.ResetOutputLevel ();
text.Write (1, "\n");
}
else
return false;
return true;
}
void GetCovariance(const vector<Vector3>& pts,Matrix3& C)
{
C.setZero();
Vector3 mean=GetMean(pts);
for(size_t i=0;i<pts.size();i++) {
Vector3 p = pts[i]-mean;
Rank1Update(C,p,p);
}
}
//******************************************************************************
// Main
//******************************************************************************
int main(int argc, char **argv) {
args::ArgumentParser parser("Checks if images are different within a tolerance.\n"
"Intended for use with library tests.\n"
"http://github.com/spinicist/QUIT");
args::HelpFlag help(parser, "HELP", "Show this help message", {'h', "help"});
args::Flag verbose(parser, "VERBOSE", "Print more information", {'v', "verbose"});
args::ValueFlag<std::string> input_path(parser, "INPUT", "Input file for difference",
{"input"});
args::ValueFlag<std::string> baseline_path(parser, "BASELINE", "Baseline file for difference",
{"baseline"});
args::ValueFlag<double> tolerance(parser, "TOLERANCE", "Tolerance (mean percent difference)",
{"tolerance"}, 0);
args::ValueFlag<double> noise(parser, "NOISE",
"Added noise level, tolerance is relative to this", {"noise"}, 0);
args::Flag absolute(parser, "ABSOLUTE",
"Use absolute difference, not relative (avoids 0/0 problems)",
{'a', "abs"});
QI::ParseArgs(parser, argc, argv, verbose);
auto input = QI::ReadImage(QI::CheckValue(input_path), verbose);
auto baseline = QI::ReadImage(QI::CheckValue(baseline_path), verbose);
auto diff = itk::SubtractImageFilter<QI::VolumeF>::New();
diff->SetInput1(input);
diff->SetInput2(baseline);
auto sqr_norm = itk::SquareImageFilter<QI::VolumeF, QI::VolumeF>::New();
if (absolute) {
sqr_norm->SetInput(diff->GetOutput());
} else {
auto diff_norm = itk::DivideImageFilter<QI::VolumeF, QI::VolumeF, QI::VolumeF>::New();
diff_norm->SetInput1(diff->GetOutput());
diff_norm->SetInput2(baseline);
diff_norm->Update();
sqr_norm->SetInput(diff_norm->GetOutput());
}
auto stats = itk::StatisticsImageFilter<QI::VolumeF>::New();
stats->SetInput(sqr_norm->GetOutput());
stats->Update();
const double mean_sqr_diff = stats->GetMean();
const double root_mean_sqr_diff = sqrt(mean_sqr_diff);
const double rel_diff =
(noise.Get() > 0) ? root_mean_sqr_diff / noise.Get() : root_mean_sqr_diff;
const bool passed = rel_diff <= tolerance.Get();
QI::Log(verbose, "Mean Square Diff: {}\nRelative noise: {}\nSquare-root mean square diff: {}\nRelative Diff: {}\nTolerance: {}\nResult: ", mean_sqr_diff
,noise.Get()
, root_mean_sqr_diff
, rel_diff
, tolerance.Get()
, (passed ? "Passed" : "Failed"));
if (passed) {
return EXIT_SUCCESS;
} else {
return EXIT_FAILURE;
}
}
float VarianceAccumulator<T>::GetNStdDev(T value)
{
T variance = GetVariance();
T mean = GetMean();
if (variance > 0) {
return std::fabs(value - mean) / (std::sqrt(variance));
} else {
return 0;
}
}
void CSamplePeak::FixAmel(int nStart, int nEnd)
{
int nMean = GetMean();
if( (nMean >= nStart) &&
(nMean <= nEnd) )
{
wxString s(m_sAllele);
s.Trim(true);
s.Trim(false);
if(s.Len() == 1)
{
m_sAllele.Replace("1","X");
m_sAllele.Replace("2","Y");
}
}
}
bool FitGaussian(const vector<Vector3>& pts,Vector3& mean,Matrix3& R,Vector3& axes)
{
mean = GetMean(pts);
Matrix A(pts.size(),3);
for(size_t i=0;i<pts.size();i++)
(pts[i]-mean).get(A(i,0),A(i,1),A(i,2));
SVDecomposition<Real> svd;
if(!svd.set(A)) {
return false;
}
svd.sortSVs();
axes.set(svd.W(0),svd.W(1),svd.W(2));
for(int i=0;i<3;i++)
for(int j=0;j<3;j++)
R(i,j) = svd.V(i,j);
return true;
}
bool FitLine(const vector<Vector3>& pts,Line3D& l)
{
Vector3 mean = GetMean(pts);
Matrix A(pts.size(),3);
for(size_t i=0;i<pts.size();i++)
(pts[i]-mean).get(A(i,0),A(i,1),A(i,2));
SVDecomposition<Real> svd;
if(!svd.set(A)) {
return false;
}
svd.sortSVs();
//take the first singular value
Vector sv;
svd.V.getColRef(0,sv);
l.direction.set(sv(0),sv(1),sv(2));
l.direction.inplaceNormalize();
l.source = mean;
return true;
}
bool FitPlane(const vector<Vector3>& pts,Plane3D& p)
{
Vector3 mean = GetMean(pts);
Matrix A(pts.size(),3);
for(size_t i=0;i<pts.size();i++)
(pts[i]-mean).get(A(i,0),A(i,1),A(i,2));
SVDecomposition<Real> svd;
if(!svd.set(A)) {
return false;
}
svd.sortSVs();
//take the last singular value
Vector sv;
svd.V.getColRef(2,sv);
p.normal.set(sv(0),sv(1),sv(2));
p.normal.inplaceNormalize();
p.offset = dot(p.normal,mean);
return true;
}
/* smooth and normalize the input pitch vector */
void SProcessQuery(float* fPitchArray,int& Len){
int i;
float MeanVal;
for (i=1;i<Len-1;i++){
if (fPitchArray[i-1]<2 && fPitchArray[i]>2 && fPitchArray[i+1]<2)
fPitchArray[i]=0;
}
int nCountFrm=0;
for (i=0;i<Len-5;i++){
if (i%5==0){
fPitchArray[i/5]=GetMean(fPitchArray+i,5);
nCountFrm++;
}
}
Len=nCountFrm;
float LastVal=0.0;
for (i=1;i<Len-1;i++){
if (fPitchArray[i-1]<2 && fabs(fPitchArray[i]-LastVal)>0.3*LastVal && fPitchArray[i+1]<2)
fPitchArray[i]=0;
if (fPitchArray[i]>2)
LastVal=fPitchArray[i];
}
/* remove the silence frame*/
float temppitch=0;
int vadCount=0;
int nStartTag=0;
int nStart=0;
for (i=0;i<Len;i++){
if(nStartTag==0){
if(fPitchArray[i]<2)
nStart=i;
else
nStartTag=1;
}
if (fPitchArray[i]>2){
fPitchArray[i]=(float)(log10(fPitchArray[i])/log10(2.0f));
if(i>3)
temppitch=GetMean(fPitchArray+i-3,3);
else
temppitch=fPitchArray[i];
vadCount=0;
}else{
vadCount++;
if (temppitch>0)
fPitchArray[i]=temppitch;
}
}
for(i=0;i<Len-nStart-1;i++){
fPitchArray[i]=fPitchArray[i+nStart+1];
}
Len-=(nStart+1);
MeanVal=0;
int VadSize=0;
for (i=0;i<Len;i++){
if (fPitchArray[i]>6.3){
MeanVal+=fPitchArray[i];
VadSize++;
}
}
float me=0.0f;
if(VadSize<1){
Len=0;
return ;
}
else
me=MeanVal/VadSize;
for (i=0; i<Len; i++){
fPitchArray[i]=fPitchArray[i]-me+PITCH_NORMALIZE_VALUE;
if (fPitchArray[i]>8)
fPitchArray[i]=fPitchArray[i]-1;
if (fPitchArray[i]<6.35)
fPitchArray[i]=fPitchArray[i]+1;
}
}
void findtruthPbPb(int binMin, int binMax)
{
TFile *fmc = new TFile(config.getFileName_djt("mcPbbfa"));
buildNamesuffix = TString::Format("_bin_%d_%d",binMin, binMax);
// buildTitlesuffix = TString::Format("%d-%d %%",binMin/2, binMax/2);
seth(10,0,1);
auto hmcPbPbxJTrue = geth("hmcPbPbxJTrue","PbPb true;x_{J};Event fractions");
auto hmcPbPbxJTrueTag = geth("hmcPbPbxJTrueTag","PbPb true tagged;x_{J};Event fractions");
auto hmcPbPbxJTrueTagCorr = geth("hmcPbPbxJTrueTagCorr","PbPb true tagged corrected;x_{J};Event fractions");
auto hmcPbPbxJTrueTagCorrPt = geth("hmcPbPbxJTrueTagCorrPt","PbPb true tagged corrected pt;x_{J};Event fractions");
auto hmcPbPbxJTrueTagCorrEta = geth("hmcPbPbxJTrueTagCorrEta","PbPb true tagged corrected eta;x_{J};Event fractions");
auto hmcPbPbxJTrueTagCorrBin = geth("hmcPbPbxJTrueTagCorrBin","PbPb true tagged corrected bin;x_{J};Event fractions");
seth(12,20,140);//10,40,100);
auto hpt2true = geth("hpt2true","true;p_{T,2} GeV");
auto hpt2truetag = geth("hpt2truetag","true tagged;p_{T,2} GeV");
auto hpt2truetagovertrue = geth("hpt2truetagovertrue","true tagged/true;p_{T,2} GeV");
auto hpt2truetagcorr = geth("hpt2truetagcorr","true tagged corrected;p_{T,2} GeV");
auto hpt2truetagcorrovertrue = geth("hpt2truetagcorrovertrue","true tagged corrected/true;p_{T,2} GeV");
seth(10,100,200);
auto hpt1true = geth("hpt1true","true;p_{T,1} GeV");
auto hpt1truetag = geth("hpt1truetag","true tagged;p_{T,1} GeV");
auto hpt1truetagovertrue = geth("hpt1truetagovertrue","true tagged/true;p_{T,1} GeV");
auto hpt1truetagcorr = geth("hpt1truetagcorr","true tagged corrected;p_{T,1} GeV");
auto hpt1truetagcorrovertrue = geth("hpt1truetagcorrovertrue","true tagged corrected/true;p_{T,1} GeV");
seth(10,0,200);
auto hbintrue = geth("hbintrue","true;bin");
auto hbintruetag = geth("hbintruetag","true tagged;bin");
auto hbintruetagovertrue = geth("hbintruetagovertrue","true tagged/true;bin");
auto hbintruetagcorr = geth("hbintruetagcorr","true tagged corrected;bin");
auto hbintruetagcorrovertrue = geth("hbintruetagcorrovertrue","true tagged corrected/true;bin");
seth(20,-2,2);
auto heta2true = geth("heta2true","true;#eta_{2}");
auto heta2truetag = geth("heta2truetag","true tagged;#eta_{2}");
auto heta2truetagovertrue = geth("heta2truetagovertrue","true tagged/true;#eta_{2}");
auto heta2truetagcorr = geth("heta2truetagcorr","true tagged corrected;#eta_{2}");
auto heta2truetagcorrovertrue = geth("heta2truetagcorrovertrue","true tagged corrected/true;#eta_{2}");
auto heta1true = geth("heta1true","true;#eta_{1}");
auto heta1truetag = geth("heta1truetag","true tagged;#eta_{1}");
auto heta1truetagovertrue = geth("heta1truetagovertrue","true tagged/true;#eta_{1}");
auto heta1truetagcorr = geth("heta1truetagcorr","true tagged corrected;#eta_{1}");
auto heta1truetagcorrovertrue = geth("heta1truetagcorrovertrue","true tagged corrected/true;#eta_{1}");
unordered_set<int> eventstodiscard = {1805770,1116573,1084397};//,
// 5755734,1599758,395810,
// 1363321,211625,3195128};
//
Fill(fmc,[&] (dict &m) {
if (m["bin"]<binMin || m["bin"]>=binMax) return;
if (m["pthat"]<pthatcut) return;
if (m[pairCodeSB1]!=0) return;
// if (m["bProdCode"]>1) return;
if (eventstodiscard.find(m["event"])!=eventstodiscard.end()) return; //kill large-weight GSP event
float w = m["weight"]*processweight((int)m["bProdCode"]); //because we have only b-dijets
float corr = tageffcorrectionPbPb(m["jtpt1"],m["jteta1"],m[jtptSB],m[jtetaSB],m["bin"]);
// float corrpt = getPbPbcorrectionPt(m["jtpt1"],m[jtptSB]);
// float correta = getPbPbcorrectionEta(m["jteta1"],m[jtetaSB]);
// float corrbin = getPbPbcorrectionBin(m["bin"]);
float wb = w*corr;
if (m["jtpt1"]>pt1cut && m["refpt1"]>50 && abs(m["refparton_flavorForB1"])==5 && m[jtptSB]>pt2cut && m[refptSB]>20 && m[dphiSB1]>PI23) {
hmcPbPbxJTrue->Fill(m[jtptSB]/m["jtpt1"],w);
hpt2true->Fill(m[jtptSB],w);
hpt1true->Fill(m["jtpt1"],w);
heta2true->Fill(m[jtetaSB],w);
heta1true->Fill(m["jteta1"],w);
hbintrue->Fill(m["bin"],w);
}
if (m["jtpt1"]>pt1cut && m["refpt1"]>50 && abs(m["refparton_flavorForB1"])==5 && m[jtptSB]>pt2cut && m[refptSB]>20 && m[dphiSB1]>PI23
&& m["discr_csvV1_1"]>0.9 && m[discr_csvV1_SB]>0.9) { //
//corrpt *= m[jtptSB] < 60 ? 1./0.7 : 1;
//wb *= m[jtptSB] < 60 ? 1./0.7 : 1;
hmcPbPbxJTrueTag->Fill(m[jtptSB]/m["jtpt1"],w);
hmcPbPbxJTrueTagCorr->Fill(m[jtptSB]/m["jtpt1"],wb);
// hmcPbPbxJTrueTagCorrPt->Fill(m[jtptSB]/m["jtpt1"],w*corrpt);
// hmcPbPbxJTrueTagCorrEta->Fill(m[jtptSB]/m["jtpt1"],w*corrpt*correta);
// hmcPbPbxJTrueTagCorrBin->Fill(m[jtptSB]/m["jtpt1"],w*corrpt*correta*corrbin);
hpt2truetag->Fill(m[jtptSB],w);
hpt1truetag->Fill(m["jtpt1"],w);
heta2truetag->Fill(m[jtetaSB],w);
heta1truetag->Fill(m["jteta1"],w);
hbintruetag->Fill(m["bin"],w);
hpt2truetagcorr->Fill(m[jtptSB],wb);
hpt1truetagcorr->Fill(m["jtpt1"],wb);
heta2truetagcorr->Fill(m[jtetaSB],wb);
heta1truetagcorr->Fill(m["jteta1"],wb);
hbintruetagcorr->Fill(m["bin"],wb);
}
});
NormalizeAllHists();
//plotymax = 9999;
aktstring = TString::Format("PbPb %d-%d %%",binMin/2, binMax/2);//TString::Format("PbPb#Delta#phi>2/3#pi %d-%d %%",binMin/2, binMax/2);
SetMC({hmcPbPbxJTrue,hmcPbPbxJTrueTag,hmcPbPbxJTrueTagCorr});
SetData({hmcPbPbxJTrue});
hmcPbPbxJTrue->SetMinimum(0);
hmcPbPbxJTrue->SetMaximum(0.3);
hmcPbPbxJTrue->SetLineWidth(2);
hmcPbPbxJTrue->SetMarkerStyle(kNone);
hmcPbPbxJTrue->SetFillStyle(0);
hmcPbPbxJTrueTag->SetMarkerStyle(kOpenCircle);
hmcPbPbxJTrueTagCorr->SetMarkerStyle(kOpenSquare);
plotymax = 0.3;
Draw({hmcPbPbxJTrue,hmcPbPbxJTrueTag,hmcPbPbxJTrueTagCorr});
SetB({hmcPbPbxJTrue,hmcPbPbxJTrueTag,hmcPbPbxJTrueTagCorr});
float xjtrue = hmcPbPbxJTrue->GetMean();
float xjtruetag = hmcPbPbxJTrueTag->GetMean();
float xjtruetagcorr = hmcPbPbxJTrueTagCorr->GetMean();
float exjtrue = hmcPbPbxJTrue->GetMeanError();
float exjtruetag = hmcPbPbxJTrueTag->GetMeanError();
float exjtruetagcorr = hmcPbPbxJTrueTagCorr->GetMeanError();
auto c = getc();
hmcPbPbxJTrue->Draw("hist");
hmcPbPbxJTrueTag->Draw("E1,same");
hmcPbPbxJTrueTagCorr->Draw("E1,same");
plotlegendpos = TopLeft;
auto l = getLegend();
l->AddEntry(hmcPbPbxJTrue,Form("b-dijets, #LTx_{J}#GT=%.3f#pm%.3f",xjtrue,exjtrue),"L");
l->AddEntry(hmcPbPbxJTrueTag,Form("uncorrected, #LTx_{J}#GT=%.3f#pm%.3f",xjtruetag,exjtruetag),"P");
l->AddEntry(hmcPbPbxJTrueTagCorr,Form("corrected, #LTx_{J}#GT=%.3f#pm%.3f",xjtruetagcorr,exjtruetagcorr),"P");
l->Draw();
TLatex *Tl = new TLatex();
Tl->DrawLatexNDC(0.2, 0.8, aktstring);
SavePlot(c,Form("closure%d%d",binMin,binMax));
// //if (binMin==0 && binMax==200) {
// Draw({hmcPbPbxJTrueTag,hmcPbPbxJTrueTagCorrPt,hmcPbPbxJTrueTagCorrEta,hmcPbPbxJTrueTagCorrBin});
// SetMC({hpt2truetag,hpt1truetag,heta2truetag,heta1truetag,hbintruetag});
// plotputmean = false;
// plotymax = 0.2;
// Draw({hpt2true,hpt2truetag,hpt2truetagcorr});
// plotymax = 0.3;
// Draw({hpt1true,hpt1truetag,hpt1truetagcorr});
// plotymax = 0.2;
// Draw({heta2true,heta2truetag,heta2truetagcorr});
// Draw({heta1true,heta1truetag,heta1truetagcorr});
// plotymax = 1;
// Draw({hbintrue,hbintruetag,hbintruetagcorr});
plotymin = 0;
plotymax = 0.2;
Draw({hpt2truetag,hpt2true});
Draw({hpt2truetagcorr,hpt2true});
hpt2truetagovertrue->Divide(hpt2truetag,hpt2true,1,1); //"B"
hpt1truetagovertrue->Divide(hpt1truetag,hpt1true,1,1); //"B"
heta2truetagovertrue->Divide(heta2truetag,heta2true,1,1); //"B"
heta1truetagovertrue->Divide(heta1truetag,heta1true,1,1); //"B"
hbintruetagovertrue->Divide(hbintruetag,hbintrue,1,1); //"B"
hpt2truetagcorrovertrue->Divide(hpt2truetagcorr,hpt2true,1,1); //"B"
hpt1truetagcorrovertrue->Divide(hpt1truetagcorr,hpt1true,1,1); //"B"
heta2truetagcorrovertrue->Divide(heta2truetagcorr,heta2true,1,1); //"B"
heta1truetagcorrovertrue->Divide(heta1truetagcorr,heta1true,1,1); //"B"
hbintruetagcorrovertrue->Divide(hbintruetagcorr,hbintrue,1,1); //"B"
NormalizeAllHists();
Draw({hpt2truetagovertrue,hpt2truetagcorrovertrue});
Draw({hpt1truetagovertrue,hpt1truetagcorrovertrue});
Draw({heta2truetagovertrue,heta2truetagcorrovertrue});
Draw({heta1truetagovertrue,heta1truetagcorrovertrue});
Draw({hbintruetagovertrue,hbintruetagcorrovertrue});
// }
}
mitk::Quaternion mitk::NavigationDataEvaluationFilter::GetQuaternionMean(int input)
{
return GetMean(m_LoggedQuaternions[input]);
}
T VarianceAccumulator<T>::
GetVariance() {
return (1.0*sumSqVal)/nSamples - GetMean()*GetMean();
}
void findtruthpp()
{
seth(10,0,1);
auto hmcppxJTrue = geth("hmcppxJTrue","true;x_{J};Event fractions");
auto hmcppxJTrueTag = geth("hmcppxJTrueTag","true tagged;x_{J};Event fractions");
auto hmcppxJTrueTagCorr = geth("hmcppxJTrueTagCorr","true tagged corrected;x_{J};Event fractions");
TFile *fmcpp = new TFile(config.getFileName_djt("mcppbfa"));
Fill(fmcpp,[&] (dict &m) {
if (m["pthat"]<pthatcut) return;
if (m[pairCodeSB1]!=0) return;
// if (m["pthat"]<80) return;
// if (m["bProdCode"]!=1) return;
float w = m["weight"]*processweight((int)m["bProdCode"]);
// float w = m["weight"];
// if (m["bProdCode"]==2) return;
float corr = tageffcorrectionpp(m["jtpt1"],m["jteta1"],m[jtptSB],m[jtetaSB]);
float wb = w*corr;
if (m["jtpt1"]>pt1cut && m["refpt1"]>50 && abs(m["refparton_flavorForB1"])==5 && m[jtptSB]>pt2cut && m[dphiSB1]>PI23)
hmcppxJTrue->Fill(m[jtptSB]/m["jtpt1"],w);
if (m["jtpt1"]>pt1cut && m["refpt1"]>50 && abs(m["refparton_flavorForB1"])==5 && m[jtptSB]>pt2cut && m[dphiSB1]>PI23
&& m["discr_csvV1_1"]>0.9 && m[discr_csvV1_SB]>0.9) {
hmcppxJTrueTag->Fill(m[jtptSB]/m["jtpt1"],w);
hmcppxJTrueTagCorr->Fill(m[jtptSB]/m["jtpt1"],wb);
}
});
NormalizeAllHists();
plotputmean = true;
plotytitle = "Event fractions";
plotdivide = false;
// aktstring += "R=0.4 |#eta|<2.0";
// plotsecondline = Form("p_{T,1}>%d GeV, p_{T,2}>%d GeV", (int)pt1cut, (int)pt2cut);
// plotthirdline = "#Delta#phi>2/3#pi";
plottextposy = 0.8;
plottextposx = 0.2;
plotmeanposy = 0.43;
plotymax = 0.2;
plotymin = 0;
plotlegendpos = BottomRight;//TopLeft;
aktstring = "pp";
SetMC({hmcppxJTrue,hmcppxJTrueTag,hmcppxJTrueTagCorr});
SetData({hmcppxJTrue});
Draw({hmcppxJTrue,hmcppxJTrueTag,hmcppxJTrueTagCorr});
hmcppxJTrue->SetMinimum(0);
hmcppxJTrue->SetMaximum(0.3);
hmcppxJTrue->SetLineWidth(2);
hmcppxJTrue->SetMarkerStyle(kNone);
hmcppxJTrue->SetFillStyle(0);
hmcppxJTrueTag->SetMarkerStyle(kOpenCircle);
hmcppxJTrueTagCorr->SetMarkerStyle(kOpenSquare);
plotymax = 0.3;
SetB({hmcppxJTrue,hmcppxJTrueTag,hmcppxJTrueTagCorr});
float xjtrue = hmcppxJTrue->GetMean();
float xjtruetag = hmcppxJTrueTag->GetMean();
float xjtruetagcorr = hmcppxJTrueTagCorr->GetMean();
float exjtrue = hmcppxJTrue->GetMeanError();
float exjtruetag = hmcppxJTrueTag->GetMeanError();
float exjtruetagcorr = hmcppxJTrueTagCorr->GetMeanError();
auto c = getc();
hmcppxJTrue->Draw("hist");
hmcppxJTrueTag->Draw("E1,same");
hmcppxJTrueTagCorr->Draw("E1,same");
plotlegendpos = TopLeft;
auto l = getLegend();
l->AddEntry(hmcppxJTrue,Form("b-dijets, #LTx_{J}#GT=%.3f#pm%.3f",xjtrue,exjtrue),"L");
l->AddEntry(hmcppxJTrueTag,Form("uncorrected, #LTx_{J}#GT=%.3f#pm%.3f",xjtruetag,exjtruetag),"P");
l->AddEntry(hmcppxJTrueTagCorr,Form("corrected, #LTx_{J}#GT=%.3f#pm%.3f",xjtruetagcorr,exjtruetagcorr),"P");
l->Draw();
TLatex *Tl = new TLatex();
Tl->DrawLatexNDC(0.2, 0.8, aktstring);
SavePlot(c,"closurepp");
}
// Transforms each nominal feature into one of more real features,
// imputes missing values, scales data.
static vector< vector<double> > PreprocessFeatures(const IDataSet *data) {
vector<int> offsets(1, 0);
for (int j = 0; j < data->GetFeatureCount(); j++) {
FeatureInfo info = data->GetMetaData().GetFeatureInfo(j);
assert(info.Type == Numeric || info.Type == Nominal);
int expansion = (info.Type == Nominal && info.NominalValues.size() >= 3) ? info.NominalValues.size() : 1;
offsets.push_back(offsets.back() + expansion);
}
vector< vector<double> > nonmissing_values(data->GetFeatureCount());
for (int i = 0; i < data->GetObjectCount(); i++) {
for (int j = 0; j < data->GetFeatureCount(); j++) {
if (data->HasFeature(i, j)) {
double feature = data->GetFeature(i, j);
nonmissing_values[j].push_back(feature);
}
}
}
vector<double> imputed_value(data->GetFeatureCount(), 0.0);
for (int j = 0; j < data->GetFeatureCount(); j++) {
FeatureInfo info = data->GetMetaData().GetFeatureInfo(j);
if (nonmissing_values[j].size() == 0) {
imputed_value[j] = 0;
continue;
}
sort(nonmissing_values[j].begin(), nonmissing_values[j].end());
if (info.Type == Nominal && info.NominalValues.size() >= 3) {
imputed_value[j] = GetMode(nonmissing_values[j]);
} else if (info.Type == Nominal) {
imputed_value[j] = 0;
} else {
imputed_value[j] = GetMean(nonmissing_values[j]);
}
}
vector< vector<double> > result(data->GetObjectCount(), vector<double>(offsets.back(), 0.0));
for (int i = 0; i < data->GetObjectCount(); ++i) {
for (int j = 0; j < data->GetFeatureCount(); ++j) {
FeatureInfo info = data->GetMetaData().GetFeatureInfo(j);
double feature = data->HasFeature(i, j) ? data->GetFeature(i, j) : imputed_value[j];
if (info.Type == Nominal && info.NominalValues.size() >= 3) {
int val = (int)feature;
assert(0 <= val && val < info.NominalValues.size());
result[i][offsets[j] + val] = 1;
} else if (info.Type == Nominal) {
// binary
if (!data->HasFeature(i, j))
result[i][offsets[j]] = 0;
else if (fabs(feature) < 0.5)
result[i][offsets[j]] = -1.0;
else
result[i][offsets[j]] = 1.0;
} else {
// real
if (nonmissing_values[j].size() != 0) {
// scale to [-1, 1]
double fmin = nonmissing_values[j][0];
double fmax = nonmissing_values[j].back();
if (fmax > fmin)
feature = (feature - fmin) / (fmax - fmin);
else
feature = 0;
}
result[i][offsets[j]] = feature;
}
}
}
return result;
}
void derivefromNS(bool data = false)
{
// float shift = mode == 2 ? -2 : mode*2; //mode = 0,1,2 shift = 0,2,-2
// cout<<"shift = "<<shift<<endl;
auto file = config.getfile_djt(data ? "dtPbjcl" : "mcPbqcd");
auto nt = (TTree *)file->Get("nt");
for (unsigned i=1;i<binbounds.size();i++) {
int b1 = binbounds[i-1];
int b2 = binbounds[i];
seth(71,38,180); //71,38
auto h = geth(Form("h%d%d",b1,b2)); //allowing one more bin for overflow
seth(b2-b1,b1,b2);
auto hb = geth(Form("hb%d%d",b1,b2));
TString mcappendix = data ? "" : "&& pthat>50";//"&& subid2!=0 && pthat>50"; //"&& pthat>50";//"&& !(subid2==0 && refpt2>20) && pthat>50"; //"&& pthat>80";//
//Form("jtpt2+%f",shift)
nt->Project(h->GetName(),"jtpt2", Form("weight*(jtpt1>100&&bin>=%d && bin<%d && dphi21<1.05 %s)",b1,b2,mcappendix.Data()));
nt->Project(hb->GetName(),"bin", Form("weight*(jtpt1>100&&bin>=%d && bin<%d && dphi21<1.05 %s)",b1,b2,mcappendix.Data()));
ScaleVisibleBins(h,NSfrac[i-1]);
h->SetBinContent(1,h->GetBinContent(0)+h->GetBinContent(1));
// auto p = new TProfile(Form("p%d%d",b1,b2),Form("prof"),71,38,180);
// nt->Project(p->GetName(),"(subid2 == 0 && refpt2 > 20):jtptSignal2",Form("weight*(jtpt1>100&&bin>=%d && bin<%d && dphiSignal21<1.05 && !(subid2==0 && refpt2>20) && pthat>80)",b1,b2));
auto g = getCDFgraph(h);
g->GetXaxis()->SetTitle("p_{T,2} threshold [GeV]");
g->GetYaxis()->SetTitle("found fraction");
auto gtemp = getCDFgraph(h);
meanb.push_back(hb->GetMean());
prob.push_back(gtemp->Eval(pt));
float c0=g->Eval(50);
cout<<"prob at 50: "<<c0<<endl;
auto gf = new TFile("graph.root","recreate");
gtemp->Write();
gf->Close();
// auto f = new TF1(Form("f%d%d",b1,b2),"1-[0]*exp(-[1]*(x-40))",40,180);
// f->SetParameters(0.1,0.1);
// // f->FixParameter(1,0.08);
// auto f = new TF1(Form("f%d%d",b1,b2),"TMath::Erf((x-[0])/[1])",40,180);
// f->SetParameters(40,10);
// f->FixParameter(1,25);
auto f = new TF1(Form("f%d%d",b1,b2),"exp(-[0]*exp(-[1]*x))",40,180);
f->SetParameters(100,0.1);
// f->FixParameter(1,0.11); //!!!!!!!!!!
f->SetLineColor(kRed);
f->SetLineWidth(2);
g->Fit(f,"RM");
fs.push_back(f);
binmean.push_back(hb->GetMean());
float median = -1/f->GetParameter(1)*log(-1/f->GetParameter(0)*log(0.5));
Draw({h});
// h->Rebin(2);
auto gcoarse = getCDFgraph(h);
auto c = getc();
TLatex *Tl = new TLatex();
gcoarse->SetMinimum(0);g->SetMaximum(1);
gcoarse->Draw("AP");
f->Draw("same");
Tl->DrawLatexNDC(0.6,0.55,"y=e^{-a e^{-b x} }");
Tl->DrawLatexNDC(0.6,0.50,Form("a = %.1f",f->GetParameter(0)));
Tl->DrawLatexNDC(0.6,0.45,Form("b = %.2f",f->GetParameter(1)));
Tl->DrawLatexNDC(0.6,0.4,Form("PbPb bin %d-%d",b1,b2));
Tl->DrawLatexNDC(0.6,0.35,Form("median = %.2f",median));
TLine *l1 = new TLine(median,0,median, f->Eval(median));
l1->Draw();
TLine *l2 = new TLine(0,0.5,median, f->Eval(median));
l2->Draw();
// p->SetMarkerColor(kRed);
// p->SetMarkerSize(1);
// p->Draw("same");
SavePlot(c,Form("fit%d%d",b1,b2));//return;
}
}
void drawMakeCorrelationSummariesTimePlots(){
gStyle->SetOptStat("mre");
// TFile* f = TFile::Open("makeCorrelationSummariesTimePlots_352_2016-02-26_18-02-20.root");
auto corTree = new TChain("corTree");
corTree->Add("makeCorrelationSummariesTimePlots/*.root");
// TTree* corTree = (TTree*) f->Get("corTree");
cout << corTree << endl;
auto cc = new CrossCorrelator();
auto h = new TH1D("h", "", 128, -2, 2);
// Book histogram and set x, y axis labels to antenna names
TString name = "h2";
TString polLetter = "H";
// TString polLetter = pol == AnitaPol::kHorizontal ? "H" : "V";
// name += polLetter;
// name += TString::Format("%u", eventNumber[pol]);
TString title = TString::Format("Mean #deltat_{measured} - #deltat_{expected} for all used antenna pairs; Antenna 1; Antenna 2; Mean #Delta#deltat (ns)");
int binShift = 0;
// title += pol==AnitaPol::kHorizontal ? "HPOL" : "VPOL";
// title += "; ; ; Correlation coefficient";
TH2D* h2 = new TH2D(name, title, NUM_SEAVEYS, 0, NUM_SEAVEYS, NUM_SEAVEYS, 0, NUM_SEAVEYS);
for(int ant=0; ant<NUM_SEAVEYS; ant++){
TString lab = TString::Format("%d", 1 + (ant/NUM_RING));
if(ant%NUM_RING==0){
lab += "T"+polLetter;
}
else if((ant%NUM_RING)==1){
lab += "M"+polLetter;
}
else{
lab += "B"+polLetter;
}
int binInd = ant + binShift;
// binInd = binInd < 0 ? binInd + NUM_SEAVEYS : binInd;
binInd = binInd >= NUM_SEAVEYS ? binInd - NUM_SEAVEYS : binInd;
h2->GetXaxis()->SetBinLabel(binInd+1, lab.Data());
h2->GetYaxis()->SetBinLabel(binInd+1, lab.Data());
}
std::vector<TH1D*> hs;
for(int combo=0; combo < NUM_COMBOS; combo++){
int ant1 = cc->comboToAnt1s.at(combo);
int ant2 = cc->comboToAnt2s.at(combo);
auto command = TString::Format("deltaTMeasured[%d]-deltaTExpected[%d]>>h", combo, combo);
auto cuts = TString::Format("deltaTMeasured[%d]>-999 && TMath::Abs(deltaTMeasured[%d]-deltaTExpected[%d]) < 0.7", combo, combo, combo);
// cout << command << "\t" << cuts << endl;
corTree->Draw(command, cuts, "goff");
std::cout << ant1 << "\t" << ant2<< "\t" << h->GetMean() << std::endl;
// auto h3 = ((TH1D*)h->Clone());
// h3->SetTitle(TString::Format("antennas %d and %d; #Delta#deltat (ns); Events / bin", ant1, ant2));
// hs.push_back(h3);
Int_t phi1 = ant1%NUM_PHI;
Int_t phi2 = ant2%NUM_PHI;
Int_t ring1 = ant1/NUM_PHI;
Int_t ring2 = ant2/NUM_PHI;
Int_t theBinX = phi1*NUM_RING + ring1 + 1;
Int_t theBinY = phi2*NUM_RING + ring2 + 1;
theBinX += binShift;
theBinY += binShift;
theBinX = theBinX >= NUM_SEAVEYS ? theBinX - NUM_SEAVEYS : theBinX;
theBinY = theBinY >= NUM_SEAVEYS ? theBinY - NUM_SEAVEYS : theBinY;
h2->SetBinContent(theBinX, theBinY, h->GetMean());
h2->SetBinContent(theBinY, theBinX, h->GetMean());
// if(combo >= 5){
// break;
// }
}
// TCanvas* c1 = RootTools::drawArrayOfHistosPrettily(&hs[0], (Int_t) hs.size());
// TCanvas* c2 = RootTools::drawHistsWithStatsBoxes((Int_t) hs.size(), &hs[0],
// "", "mre");
// TLegend* l = c2->BuildLegend();
// hs[0]->SetTitle("#deltat_{measured} - #deltat_{expected} for a selection of antenna pairs; #Delta#deltat (ns); Events / bin");
auto c3 = new TCanvas();
h2->Draw("colz");
}
void DataSignal :: WriteSmartArtifactInfoToXML (RGTextOutput& text, const RGString& indent, const RGString& bracketTag, const RGString& locationTag) {
int peak;
Endl endLine;
RGString suffix;
RGString label;
SmartMessageReporter* notice;
int i;
RGString virtualAllele;
int reportedMessageLevel;
reportedMessageLevel = GetHighestMessageLevelWithRestrictionSM ();
bool thisIsFirstNotice = true;
if ((!DontLook ()) && (NumberOfSmartNoticeObjects () != 0)) {
peak = (int) floor (Peak () + 0.5);
if (mOffGrid)
suffix = " OL";
virtualAllele = GetVirtualAlleleName ();
RGDListIterator it (*mSmartMessageReporters);
i = 0;
while (notice = (SmartMessageReporter*) it ()) {
if (!notice->GetDisplayOsirisInfo ())
continue;
if (thisIsFirstNotice) {
text << indent << "<" << bracketTag << ">" << endLine;
text << indent << "\t<level>" << reportedMessageLevel << "</level>" << endLine;
text << indent << "\t<mean>" << GetMean () << "</mean>" << endLine;
text << indent << "\t<height>" << peak << "</height>" << endLine;
// text << indent << "\t<" << locationTag << ">" << (int) floor (GetApproximateBioID () + 0.5) << "</" << locationTag << ">" << endLine;
text << indent << "\t<" << locationTag << ">" << GetApproximateBioID () << "</" << locationTag << ">" << endLine;
text << indent << "\t<PeakArea>" << TheoreticalArea () << "</PeakArea>" << endLine;
if (virtualAllele.Length () > 0)
text << indent << "\t<equivAllele>" << virtualAllele << suffix << "</equivAllele>" << endLine;
text << indent << "\t<width>" << 4.0 * GetStandardDeviation () << "</width>" << endLine;
text << indent << "\t<fit>" << GetCurveFit () << "</fit>" << endLine;
label = indent + "\t<label>";
thisIsFirstNotice = false;
}
if (i > 0)
label << " ";
label += notice->GetMessage ();
label += notice->GetMessageData ();
i++;
}
RGString temp = GetVirtualAlleleName () + suffix;
if (temp.Length () > 0) {
if (i > 0)
label << " ";
label += "Allele " + temp;
}
if (i > 0) {
label << "</label>";
text << label << endLine;
text << indent << "</" + bracketTag << ">" << endLine;
}
/*if ((signalLink != NULL) && (!signalLink->xmlArtifactInfoWritten)) {
signalLink->xmlArtifactInfoWritten = true;
peak = signalLink->height;
text << indent << "<" << bracketTag << ">" << endLine;
text << indent << "\t<mean>" << signalLink->mean << "</mean>" << endLine;
text << indent << "\t<height>" << peak << "</height>" << endLine;
text << indent << "\t<" << locationTag << ">" << signalLink->bioID << "</" << locationTag << ">" << endLine;
text << indent << "\t<fit>" << GetCurveFit () << "</fit>" << endLine;
label = indent + "\t<label>";
mNoticeObjectIterator.Reset ();
i = 0;
while (notice = (Notice*) mNoticeObjectIterator ()) {
if (i > 0)
label << " ";
label += notice->GetLabel ();
i++;
}
if (temp.Length () > 0) {
if (i > 0)
label << " ";
label += "Allele " + temp;
}
label << "</label>";
text << label << endLine;
text << indent << "</" + bracketTag << ">" << endLine;
}*/
}
}
void DataSignal :: WriteSmartTableArtifactInfoToXML (RGTextOutput& text, RGTextOutput& tempText, const RGString& indent, const RGString& bracketTag, const RGString& locationTag) {
int peak;
Endl endLine;
RGString suffix;
RGString label;
SmartMessageReporter* notice;
int i;
RGString virtualAllele;
SmartMessageReporter* nextNotice;
text.SetOutputLevel (1);
int msgNum;
smAcceptedOLLeft acceptedOLLeft;
smAcceptedOLRight acceptedOLRight;
int reportedMessageLevel = GetHighestMessageLevelWithRestrictionSM ();
//bool hasThreeLoci;
//bool needLocus0;
if ((!DontLook ()) && (NumberOfSmartNoticeObjects () != 0)) {
bool firstNotice = true;
peak = (int) floor (Peak () + 0.5);
virtualAllele = GetVirtualAlleleName ();
text << indent << "<" << bracketTag << ">" << endLine; // Should be <Artifact>
text << indent << "\t<Id>" << GetSignalID () << "</Id>" << endLine;
text << indent << "\t<Level>" << reportedMessageLevel << "</Level>" << endLine;
text << indent << "\t<RFU>" << peak << "</RFU>" << endLine;
text << indent << "\t<" << locationTag << ">" << GetApproximateBioID () << "</" << locationTag << ">" << endLine;
text << indent << "\t<PeakArea>" << TheoreticalArea () << "</PeakArea>" << endLine;
text << indent << "\t<Time>" << GetMean () << "</Time>" << endLine;
text << indent << "\t<Fit>" << GetCurveFit () << "</Fit>" << endLine;
if (!mAllowPeakEdit)
text << indent << "\t<AllowPeakEdit>false</AllowPeakEdit>" << endLine;
RGDListIterator it (*mSmartMessageReporters);
i = 0;
while (notice = (SmartMessageReporter*) it ()) {
if (!notice->GetDisplayOsirisInfo ())
continue;
if (firstNotice) {
label = indent + "\t<Label>";
firstNotice = false;
}
if (i > 0)
label << " ";
label += notice->GetMessage ();
label += notice->GetMessageData ();
i++;
}
if (i > 0) {
label << "</Label>";
text << label << endLine;
}
// Now add list of notices...
it.Reset ();
while (nextNotice = (SmartMessageReporter*) it ()) {
msgNum = Notice::GetNextMessageNumber ();
nextNotice->SetMessageCount (msgNum);
text << indent << "\t<MessageNumber>" << msgNum << "</MessageNumber>" << endLine;
tempText << "\t\t<Message>\n";
tempText << "\t\t\t<MessageNumber>" << msgNum << "</MessageNumber>\n";
tempText << "\t\t\t<Text>" << nextNotice->GetMessage () << nextNotice->GetMessageData () << "</Text>\n";
if (nextNotice->HasViableExportInfo ()) {
if (nextNotice->IsEnabled ())
tempText << "\t\t\t<Hidden>false</Hidden>\n";
else
tempText << "\t\t\t<Hidden>true</Hidden>\n";
if (!nextNotice->IsCritical ())
tempText << "\t\t\t<Critical>false</Critical>\n";
if (nextNotice->IsEnabled ())
tempText << "\t\t\t<Enabled>true</Enabled>\n";
else
tempText << "\t\t\t<Enabled>false</Enabled>\n";
if (!nextNotice->IsEditable ())
tempText << "\t\t\t<Editable>false</Editable>\n";
if (nextNotice->GetDisplayExportInfo ())
tempText << "\t\t\t<DisplayExportInfo>true</DisplayExportInfo>\n";
else
tempText << "\t\t\t<DisplayExportInfo>false</DisplayExportInfo>\n";
if (!nextNotice->GetDisplayOsirisInfo ())
tempText << "\t\t\t<DisplayOsirisInfo>false</DisplayOsirisInfo>\n";
tempText << "\t\t\t<MsgName>" << nextNotice->GetMessageName () << "</MsgName>\n";
//tempText << "\t\t\t<ExportProtocolList>";
//tempText << "\t\t\t" << nextNotice->GetExportProtocolInformation ();
//tempText << "\t\t\t</ExportProtocolList>\n";
}
tempText << "\t\t</Message>\n";
}
// Now add list of alleles
//hasThreeLoci = (mLocus != NULL) && (mLeftLocus != NULL) && (mRightLocus != NULL);
//if (mLocus != NULL) {
// if ((mLeftLocus == NULL) && (mRightLocus == NULL))
// needLocus0 = true;
// else
// needLocus0 = false;
//}
//else
// needLocus0 = false;
//needLocus0 = (!hasThreeLoci) && ((mLocus != mLeftLocus) || (mLocus != mRightLocus));
if (mLocus != NULL) {
//testing
RGString locusName = mLocus->GetLocusName ();
suffix = GetAlleleName (0);
if ((suffix.Length () > 0) || (virtualAllele.Length () > 0)) {
text << indent << "\t<Allele>" << endLine;
if (suffix.Length () > 0)
text << indent << "\t\t<Name>" << suffix << "</Name>" << endLine;
else
text << indent << "\t\t<Name>" << virtualAllele << "</Name>" << endLine;
if (mOffGrid)
suffix = "true";
else if (mAcceptedOffGrid)
suffix = "accepted";
else
suffix = "false";
text << indent << "\t\t<OffLadder>" << suffix << "</OffLadder>" << endLine;
text << indent << "\t\t<BPS>" << GetBioID (0) << "</BPS>" << endLine;
text << indent << "\t\t<Locus>" << mLocus->GetLocusName () << "</Locus>" << endLine;
text << indent << "\t\t<Location>0</Location>" << endLine;
text << indent << "\t</Allele>" << endLine;
}
}
if ((mLeftLocus != NULL) && (mLeftLocus != mLocus)) {
if (mAlleleNameLeft.Length () > 0) {
text << indent << "\t<Allele>" << endLine;
text << indent << "\t\t<Name>" << mAlleleNameLeft << "</Name>" << endLine;
if (mIsOffGridLeft)
suffix = "true";
else if (GetMessageValue (acceptedOLLeft))
suffix = "accepted";
else
suffix = "false";
text << indent << "\t\t<OffLadder>" << suffix << "</OffLadder>" << endLine;
text << indent << "\t\t<BPS>" << GetBioID (-1) << "</BPS>" << endLine;
text << indent << "\t\t<Locus>" << mLeftLocus->GetLocusName () << "</Locus>" << endLine;
text << indent << "\t\t<Location>-1</Location>" << endLine;
text << indent << "\t</Allele>" << endLine;
}
}
if ((mRightLocus != NULL) && (mRightLocus != mLocus)) {
if (mAlleleNameRight.Length () > 0) {
text << indent << "\t<Allele>" << endLine;
text << indent << "\t\t<Name>" << mAlleleNameRight << "</Name>" << endLine;
if (mIsOffGridRight)
suffix = "true";
else if (GetMessageValue (acceptedOLRight))
suffix = "accepted";
else
suffix = "false";
text << indent << "\t\t<OffLadder>" << suffix << "</OffLadder>" << endLine;
text << indent << "\t\t<BPS>" << GetBioID (1) << "</BPS>" << endLine;
text << indent << "\t\t<Locus>" << mRightLocus->GetLocusName () << "</Locus>" << endLine;
text << indent << "\t\t<Location>1</Location>" << endLine;
text << indent << "\t</Allele>" << endLine;
}
}
text << indent << "</" + bracketTag << ">" << endLine;
}
text.ResetOutputLevel ();
}
void zScan(){
double sf = 1.;
double ppm = 1E-6;
double ppb = 1E-9;
int units = 0; // 0 = ppm, 1 = ppb
TString Units = "ND";
if(units==0){
sf = ppm;
Units = Form("ppm");
}else if(units==1){
sf = ppb;
Units = Form("ppb");
}
TString prefix = Form("./probe/");
TString inpath = prefix + Form("probe-1.dat");
// double r = 5;
// TString inpath = Form("./probe/probe-1_r-%.0f-cm.dat",r);
vector<double> x,y,z,th,B,dB;
vector<double> z1,z2,z3,z4;
vector<double> b1,b2,b3,b4;
vector<double> db1,db2,db3,db4;
vector<double> BR,dBR;
ImportScanData(inpath,z,B,dB);
// ImportScanDataAlt(inpath,x,y,z,th,B,dB);
double mean_b = GetMean(B);
double arg=0,err=0;
cout << "B AVG = " << Form("%.15lf",mean_b) << endl;
int TH=0;
FieldData myData;
TTree *myTree = new TTree("T","Field Data");
myTree->Branch("field",&myData.x,"x/D:y/D:z/D:phi/D:B/D:dB/D:B_rel/D:dB_rel/D");
const int N = z.size();
for(int i=0;i<N;i++){
// TH = (int)th[i];
arg = (B[i]-mean_b)/mean_b/sf;
err = dB[i]/mean_b/sf;
// if(TH==0){
// z1.push_back(z[i]);
// b1.push_back(arg);
// db1.push_back(err);
// }else if(TH==90){
// z2.push_back(z[i]);
// b2.push_back(arg);
// db2.push_back(err);
// }else if(TH==180){
// z3.push_back(z[i]);
// b3.push_back(arg);
// db3.push_back(err);
// }else if(TH==270){
// z4.push_back(z[i]);
// b4.push_back(arg);
// db4.push_back(err);
// }
cout // << Form("%10.3f",x[i]) << "\t"
// << Form("%10.3f",y[i]) << "\t"
<< Form("%10.3f",z[i]) << "\t"
// << Form("%10.3f",th[i]) << "\t"
<< Form("%10.3f",arg ) << "\t"
<< Form("%10.3f",err ) << endl;
// myData.x = x[i];
// myData.y = y[i];
// myData.z = z[i];
// myData.B_rel = arg;
// myData.dB_rel = err;
// myTree->Fill();
BR.push_back(arg);
dBR.push_back(err);
}
TGraphErrors *g = GetTGraphErrors(z,BR,dBR);
SetGraphParameters(g,20,kBlack);
double MarkerSize = 1.5;
// TGraphErrors *g1 = GetTGraphErrors(z1,b1,db1);
// SetGraphParameters(g1,20,kBlack);
// g1->SetMarkerSize(MarkerSize);
// TGraphErrors *g2 = GetTGraphErrors(z2,b2,db2);
// SetGraphParameters(g2,21,kBlue);
// g2->SetMarkerSize(MarkerSize);
// TGraphErrors *g3 = GetTGraphErrors(z3,b3,db3);
// SetGraphParameters(g3,22,kRed);
// g3->SetMarkerSize(MarkerSize);
// TGraphErrors *g4 = GetTGraphErrors(z4,b4,db4);
// SetGraphParameters(g4,23,kMagenta);
// g4->SetMarkerSize(MarkerSize);
// TLegend *L = new TLegend(0.6,0.6,0.8,0.8);
// L->SetFillStyle(0);
// L->AddEntry(g1,"#theta = 0#circ" ,"p");
// L->AddEntry(g2,"#theta = 90#circ" ,"p");
// L->AddEntry(g3,"#theta = 180#circ","p");
// L->AddEntry(g4,"#theta = 270#circ","p");
// TMultiGraph *mg = new TMultiGraph();
// mg->Add(g1,"p");
// mg->Add(g2,"p");
// mg->Add(g3,"p");
// mg->Add(g4,"p");
double xMin = -350;
double xMax = 350;
// double yMin = -2;
// double yMax = 2;
TLine *xAxisLine = new TLine(xMin,0,xMax,0);
TLine *xAxisLine2 = new TLine(-150,0, 150,0);
TString Title = Form("Magnetic Field Map Along z Axis (x = 0, y = 0) ");
// TString Title2 = Form("Magnetic Field Map (r = %.0f cm)",r);
TString xAxisTitle = Form("z (mm)");
TString yAxisTitle = Form("B (%s)",Units.Data());
TCanvas *c1 = new TCanvas("c1","z Scan (1)",1200,800);
c1->SetFillColor(kWhite);
c1->cd();
gStyle->SetOptFit(111);
g->Draw("ap");
g->SetTitle(Title);
g->GetXaxis()->SetTitle(xAxisTitle);
g->GetXaxis()->CenterTitle();
g->GetYaxis()->SetTitle(yAxisTitle);
g->GetYaxis()->CenterTitle();
g->GetXaxis()->SetLimits(xMin,xMax);
g->Draw("ap");
xAxisLine->Draw("same");
c1->Update();
// TCanvas *c2 = new TCanvas("c2","z Scan (2)",1200,800);
// c2->SetFillColor(kWhite);
// c2->cd();
// gStyle->SetOptFit(111);
// mg->Draw("a");
// mg->SetTitle(Title2);
// mg->GetXaxis()->SetTitle("z (mm)");
// mg->GetXaxis()->CenterTitle();
// mg->GetYaxis()->SetTitle(yAxisTitle);
// mg->GetYaxis()->CenterTitle();
// mg->GetXaxis()->SetLimits(-150,150);
// mg->GetYaxis()->SetRangeUser(yMin,yMax);
// mg->Draw("a");
// xAxisLine2->Draw("same");
// L->Draw("same");
// c2->Update();
// myTree->SetMarkerStyle(20);
// myTree->SetMarkerSize(1.6);
// TCanvas *c3 = new TCanvas("c3","3D Field Map",1200,800);
// c3->SetFillColor(kWhite);
// c3->cd();
// myTree->Draw("y:x:z:B_rel","","colz");
// c3->Update();
}
