diff --git a/src/FitBase/Measurement1D.cxx b/src/FitBase/Measurement1D.cxx
index 5140ffd..4772c92 100644
--- a/src/FitBase/Measurement1D.cxx
+++ b/src/FitBase/Measurement1D.cxx
@@ -1,1904 +1,1900 @@
// Copyright 2016 L. Pickering, P. Stowell, R. Terri, C. Wilkinson, C. Wret
/*******************************************************************************
* This ile is part of NUISANCE.
*
* NUISANCE is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* NUISANCE is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with NUISANCE. If not, see <http://www.gnu.org/licenses/>.
*******************************************************************************/
#include "Measurement1D.h"
//********************************************************************
Measurement1D::Measurement1D(void) {
//********************************************************************
// XSec Scalings
fScaleFactor = -1.0;
fCurrentNorm = 1.0;
// Histograms
fDataHist = NULL;
fDataTrue = NULL;
fMCHist = NULL;
fMCFine = NULL;
fMCWeighted = NULL;
fMaskHist = NULL;
// Covar
covar = NULL;
fFullCovar = NULL;
fShapeCovar = NULL;
fCovar = NULL;
fInvert = NULL;
fDecomp = NULL;
// Fake Data
fFakeDataInput = "";
fFakeDataFile = NULL;
// Options
fDefaultTypes = "FIX/FULL/CHI2";
fAllowedTypes =
"FIX,FREE,SHAPE/FULL,DIAG/CHI2/NORM/ENUCORR/Q2CORR/ENU1D/MASK/NOWIDTH";
fIsFix = false;
fIsShape = false;
fIsFree = false;
fIsDiag = false;
fIsFull = false;
fAddNormPen = false;
fIsMask = false;
fIsChi2SVD = false;
fIsRawEvents = false;
fIsNoWidth = false;
fIsDifXSec = false;
fIsEnu1D = false;
// Inputs
fInput = NULL;
fRW = NULL;
// Extra Histograms
fMCHist_Modes = NULL;
}
//********************************************************************
Measurement1D::~Measurement1D(void) {
//********************************************************************
if (fDataHist) delete fDataHist;
if (fDataTrue) delete fDataTrue;
if (fMCHist) delete fMCHist;
if (fMCFine) delete fMCFine;
if (fMCWeighted) delete fMCWeighted;
if (fMaskHist) delete fMaskHist;
if (covar) delete covar;
if (fFullCovar) delete fFullCovar;
if (fShapeCovar) delete fShapeCovar;
if (fCovar) delete fCovar;
if (fInvert) delete fInvert;
if (fDecomp) delete fDecomp;
}
//********************************************************************
void Measurement1D::FinaliseSampleSettings() {
//********************************************************************
MeasurementBase::FinaliseSampleSettings();
// Setup naming + renaming
fName = fSettings.GetName();
fSettings.SetS("originalname", fName);
if (fSettings.Has("rename")) {
fName = fSettings.GetS("rename");
fSettings.SetS("name", fName);
}
// Setup all other options
LOG(SAM) << "Finalising Sample Settings: " << fName << std::endl;
if ((fSettings.GetS("originalname").find("Evt") != std::string::npos)) {
fIsRawEvents = true;
LOG(SAM) << "Found event rate measurement but using poisson likelihoods."
<< std::endl;
}
if (fSettings.GetS("originalname").find("XSec_1DEnu") != std::string::npos) {
fIsEnu1D = true;
LOG(SAM) << "::" << fName << "::" << std::endl;
LOG(SAM) << "Found XSec Enu measurement, applying flux integrated scaling, "
<< "not flux averaged!" << std::endl;
}
if (fIsEnu1D && fIsRawEvents) {
LOG(SAM) << "Found 1D Enu XSec distribution AND fIsRawEvents, is this "
"really correct?!"
<< std::endl;
LOG(SAM) << "Check experiment constructor for " << fName
<< " and correct this!" << std::endl;
LOG(SAM) << "I live in " << __FILE__ << ":" << __LINE__ << std::endl;
exit(-1);
}
if (!fRW) fRW = FitBase::GetRW();
if (!fInput and !fIsJoint) SetupInputs(fSettings.GetS("input"));
// Setup options
SetFitOptions(fDefaultTypes); // defaults
SetFitOptions(fSettings.GetS("type")); // user specified
EnuMin = GeneralUtils::StrToDbl(fSettings.GetS("enu_min"));
EnuMax = GeneralUtils::StrToDbl(fSettings.GetS("enu_max"));
if (fAddNormPen) {
if (fNormError <= 0.0) {
ERR(WRN) << "Norm error for class " << fName << " is 0.0!" << std::endl;
ERR(WRN) << "If you want to use it please add fNormError=VAL" << std::endl;
throw;
}
}
}
//********************************************************************
void Measurement1D::CreateDataHistogram(int dimx, double* binx) {
//********************************************************************
if (fDataHist) delete fDataHist;
fDataHist = new TH1D( (fSettings.GetName() + "_data").c_str(), (fSettings.GetFullTitles()).c_str(),
dimx, binx) ;
}
//********************************************************************
void Measurement1D::SetDataFromTextFile(std::string datafile) {
//********************************************************************
LOG(SAM) << "Reading data from text file: " << datafile << std::endl;
fDataHist = PlotUtils::GetTH1DFromFile(datafile,
fSettings.GetName() + "_data",
fSettings.GetFullTitles());
}
//********************************************************************
void Measurement1D::SetDataFromRootFile(std::string datafile,
std::string histname) {
//********************************************************************
LOG(SAM) << "Reading data from root file: " << datafile << ";" << histname << std::endl;
fDataHist = PlotUtils::GetTH1DFromRootFile(datafile, histname);
fDataHist->SetNameTitle((fSettings.GetName() + "_data").c_str(),
(fSettings.GetFullTitles()).c_str());
return;
};
//********************************************************************
void Measurement1D::SetEmptyData(){
//********************************************************************
fDataHist = new TH1D("EMPTY_DATA","EMPTY_DATA",1,0.0,1.0);
}
//********************************************************************
void Measurement1D::SetPoissonErrors() {
//********************************************************************
if (!fDataHist) {
ERR(FTL) << "Need a data hist to setup possion errors! " << std::endl;
ERR(FTL) << "Setup Data First!" << std::endl;
throw;
}
for (int i = 0; i < fDataHist->GetNbinsX() + 1; i++) {
fDataHist->SetBinError(i + 1, sqrt(fDataHist->GetBinContent(i + 1)));
}
}
//********************************************************************
void Measurement1D::SetCovarFromDiagonal(TH1D* data) {
//********************************************************************
if (!data and fDataHist) {
data = fDataHist;
}
if (data) {
LOG(SAM) << "Setting diagonal covariance for: " << data->GetName() << std::endl;
fFullCovar = StatUtils::MakeDiagonalCovarMatrix(data);
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
} else {
ERR(FTL) << "No data input provided to set diagonal covar from!" << std::endl;
}
// if (!fIsDiag) {
// ERR(FTL) << "SetCovarMatrixFromDiag called for measurement "
// << "that is not set as diagonal." << std::endl;
// throw;
// }
}
//********************************************************************
void Measurement1D::SetCovarFromTextFile(std::string covfile, int dim) {
//********************************************************************
if (dim == -1) {
dim = fDataHist->GetNbinsX();
}
LOG(SAM) << "Reading covariance from text file: " << covfile << std::endl;
fFullCovar = StatUtils::GetCovarFromTextFile(covfile, dim);
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void Measurement1D::SetCovarFromMultipleTextFiles(std::string covfiles, int dim) {
//********************************************************************
if (dim == -1) {
dim = fDataHist->GetNbinsX();
}
std::vector<std::string> covList = GeneralUtils::ParseToStr(covfiles, ";");
fFullCovar = new TMatrixDSym(dim);
for (uint i = 0; i < covList.size(); ++i){
LOG(SAM) << "Reading covariance from text file: " << covList[i] << std::endl;
TMatrixDSym* temp_cov = StatUtils::GetCovarFromTextFile(covList[i], dim);
(*fFullCovar) += (*temp_cov);
delete temp_cov;
}
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void Measurement1D::SetCovarFromRootFile(std::string covfile, std::string histname) {
//********************************************************************
LOG(SAM) << "Reading covariance from text file: " << covfile << ";" << histname << std::endl;
fFullCovar = StatUtils::GetCovarFromRootFile(covfile, histname);
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void Measurement1D::SetCovarInvertFromTextFile(std::string covfile, int dim) {
//********************************************************************
if (dim == -1) {
dim = fDataHist->GetNbinsX();
}
LOG(SAM) << "Reading inverted covariance from text file: " << covfile << std::endl;
covar = StatUtils::GetCovarFromTextFile(covfile, dim);
fFullCovar = StatUtils::GetInvert(covar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void Measurement1D::SetCovarInvertFromRootFile(std::string covfile, std::string histname) {
//********************************************************************
LOG(SAM) << "Reading inverted covariance from text file: " << covfile << ";" << histname << std::endl;
covar = StatUtils::GetCovarFromRootFile(covfile, histname);
fFullCovar = StatUtils::GetInvert(covar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void Measurement1D::SetCorrelationFromTextFile(std::string covfile, int dim) {
//********************************************************************
if (dim == -1) dim = fDataHist->GetNbinsX();
LOG(SAM) << "Reading data correlations from text file: " << covfile << ";" << dim << std::endl;
TMatrixDSym* correlation = StatUtils::GetCovarFromTextFile(covfile, dim);
if (!fDataHist) {
ERR(FTL) << "Trying to set correlations from text file but there is no data to build it from. \n"
<< "In constructor make sure data is set before SetCorrelationFromTextFile is called. \n" << std::endl;
throw;
}
// Fill covar from data errors and correlations
fFullCovar = new TMatrixDSym(dim);
for (int i = 0; i < fDataHist->GetNbinsX(); i++) {
for (int j = 0; j < fDataHist->GetNbinsX(); j++) {
(*fFullCovar)(i, j) = (*correlation)(i, j) * fDataHist->GetBinError(i + 1) * fDataHist->GetBinError(j + 1) * 1.E76;
}
}
// Fill other covars.
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete correlation;
}
//********************************************************************
void Measurement1D::SetCorrelationFromMultipleTextFiles(std::string corrfiles, int dim) {
//********************************************************************
if (dim == -1) {
dim = fDataHist->GetNbinsX();
}
std::vector<std::string> corrList = GeneralUtils::ParseToStr(corrfiles, ";");
fFullCovar = new TMatrixDSym(dim);
for (uint i = 0; i < corrList.size(); ++i){
LOG(SAM) << "Reading covariance from text file: " << corrList[i] << std::endl;
TMatrixDSym* temp_cov = StatUtils::GetCovarFromTextFile(corrList[i], dim);
for (int i = 0; i < fDataHist->GetNbinsX(); i++) {
for (int j = 0; j < fDataHist->GetNbinsX(); j++) {
(*temp_cov)(i, j) = (*temp_cov)(i, j) * fDataHist->GetBinError(i + 1) * fDataHist->GetBinError(j + 1) * 1.E76;
}
}
(*fFullCovar) += (*temp_cov);
delete temp_cov;
}
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void Measurement1D::SetCorrelationFromRootFile(std::string covfile, std::string histname) {
//********************************************************************
LOG(SAM) << "Reading data correlations from text file: " << covfile << ";" << histname << std::endl;
TMatrixDSym* correlation = StatUtils::GetCovarFromRootFile(covfile, histname);
if (!fDataHist) {
ERR(FTL) << "Trying to set correlations from text file but there is no data to build it from. \n"
<< "In constructor make sure data is set before SetCorrelationFromTextFile is called. \n" << std::endl;
throw;
}
// Fill covar from data errors and correlations
fFullCovar = new TMatrixDSym(fDataHist->GetNbinsX());
for (int i = 0; i < fDataHist->GetNbinsX(); i++) {
for (int j = 0; j < fDataHist->GetNbinsX(); j++) {
(*fFullCovar)(i, j) = (*correlation)(i, j) * fDataHist->GetBinError(i + 1) * fDataHist->GetBinError(j + 1) * 1.E76;
}
}
// Fill other covars.
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete correlation;
}
//********************************************************************
void Measurement1D::SetCholDecompFromTextFile(std::string covfile, int dim) {
//********************************************************************
if (dim == -1) {
dim = fDataHist->GetNbinsX();
}
LOG(SAM) << "Reading cholesky from text file: " << covfile << std::endl;
TMatrixD* temp = StatUtils::GetMatrixFromTextFile(covfile, dim, dim);
TMatrixD* trans = (TMatrixD*)temp->Clone();
trans->T();
(*trans) *= (*temp);
fFullCovar = new TMatrixDSym(dim, trans->GetMatrixArray(), "");
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete temp;
delete trans;
}
//********************************************************************
void Measurement1D::SetCholDecompFromRootFile(std::string covfile, std::string histname) {
//********************************************************************
LOG(SAM) << "Reading cholesky decomp from root file: " << covfile << ";" << histname << std::endl;
TMatrixD* temp = StatUtils::GetMatrixFromRootFile(covfile, histname);
TMatrixD* trans = (TMatrixD*)temp->Clone();
trans->T();
(*trans) *= (*temp);
fFullCovar = new TMatrixDSym(temp->GetNrows(), trans->GetMatrixArray(), "");
covar = StatUtils::GetInvert(fFullCovar);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete temp;
delete trans;
}
void Measurement1D::SetShapeCovar(){
// Return if this is missing any pre-requisites
if (!fFullCovar) return;
if (!fDataHist) return;
// Also return if it's bloody stupid under the circumstances
if (fIsDiag) return;
fShapeCovar = StatUtils::ExtractShapeOnlyCovar(fFullCovar, fDataHist);
return;
}
//********************************************************************
void Measurement1D::ScaleData(double scale) {
//********************************************************************
fDataHist->Scale(scale);
}
//********************************************************************
void Measurement1D::ScaleDataErrors(double scale) {
//********************************************************************
for (int i = 0; i < fDataHist->GetNbinsX(); i++) {
fDataHist->SetBinError(i + 1, fDataHist->GetBinError(i + 1) * scale);
}
}
//********************************************************************
void Measurement1D::ScaleCovar(double scale) {
//********************************************************************
(*fFullCovar) *= scale;
(*covar) *= 1.0 / scale;
(*fDecomp) *= sqrt(scale);
}
//********************************************************************
void Measurement1D::SetBinMask(std::string maskfile) {
//********************************************************************
if (!fIsMask) return;
LOG(SAM) << "Reading bin mask from file: " << maskfile << std::endl;
// Create a mask histogram with dim of data
int nbins = fDataHist->GetNbinsX();
fMaskHist =
new TH1I((fSettings.GetName() + "_BINMASK").c_str(),
(fSettings.GetName() + "_BINMASK; Bin; Mask?").c_str(), nbins, 0, nbins);
std::string line;
std::ifstream mask(maskfile.c_str(), std::ifstream::in);
if (!mask.is_open()) {
LOG(FTL) << " Cannot find mask file." << std::endl;
throw;
}
while (std::getline(mask >> std::ws, line, '\n')) {
std::vector<int> entries = GeneralUtils::ParseToInt(line, " ");
// Skip lines with poorly formatted lines
if (entries.size() < 2) {
LOG(WRN) << "Measurement1D::SetBinMask(), couldn't parse line: " << line
<< std::endl;
continue;
}
// The first index should be the bin number, the second should be the mask
// value.
int val = 0;
if (entries[1] > 0) val = 1;
fMaskHist->SetBinContent(entries[0], val);
}
// Apply masking by setting masked data bins to zero
PlotUtils::MaskBins(fDataHist, fMaskHist);
return;
}
//********************************************************************
void Measurement1D::FinaliseMeasurement() {
//********************************************************************
LOG(SAM) << "Finalising Measurement: " << fName << std::endl;
if (fSettings.GetB("onlymc")){
if (fDataHist) delete fDataHist;
fDataHist = new TH1D("empty_data","empty_data",1,0.0,1.0);
}
// Make sure data is setup
if (!fDataHist) {
ERR(FTL) << "No data has been setup inside " << fName << " constructor!" << std::endl;
throw;
}
// Make sure covariances are setup
if (!fFullCovar) {
fIsDiag = true;
SetCovarFromDiagonal(fDataHist);
}
if (!covar) {
covar = StatUtils::GetInvert(fFullCovar);
}
if (!fDecomp) {
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
// Push the diagonals of fFullCovar onto the data histogram
// Comment this out until the covariance/data scaling is consistent!
StatUtils::SetDataErrorFromCov(fDataHist, fFullCovar, 1E-38);
// If shape only, set covar and fDecomp using the shape-only matrix (if set)
if (fIsShape && fShapeCovar and FitPar::Config().GetParB("UseShapeCovar")){
if (covar) delete covar;
covar = StatUtils::GetInvert(fShapeCovar);
if (fDecomp) delete fDecomp;
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
// Setup fMCHist from data
fMCHist = (TH1D*)fDataHist->Clone();
fMCHist->SetNameTitle((fSettings.GetName() + "_MC").c_str(),
(fSettings.GetFullTitles()).c_str());
fMCHist->Reset();
// Setup fMCFine
fMCFine = new TH1D("mcfine", "mcfine", fDataHist->GetNbinsX() * 8,
fMCHist->GetBinLowEdge(1),
fMCHist->GetBinLowEdge(fDataHist->GetNbinsX() + 1));
fMCFine->SetNameTitle((fSettings.GetName() + "_MC_FINE").c_str(),
(fSettings.GetFullTitles()).c_str());
fMCFine->Reset();
// Setup MC Stat
fMCStat = (TH1D*)fMCHist->Clone();
fMCStat->Reset();
// Search drawopts for possible types to include by default
std::string drawopts = FitPar::Config().GetParS("drawopts");
if (drawopts.find("MODES") != std::string::npos) {
fMCHist_Modes = new TrueModeStack( (fSettings.GetName() + "_MODES").c_str(),
("True Channels"), fMCHist);
SetAutoProcessTH1(fMCHist_Modes, kCMD_Reset, kCMD_Norm, kCMD_Write);
}
// Setup bin masks using sample name
if (fIsMask) {
std::string curname = fName;
std::string origname = fSettings.GetS("originalname");
// Check rename.mask
std::string maskloc = FitPar::Config().GetParDIR(curname + ".mask");
// Check origname.mask
if (maskloc.empty()) maskloc = FitPar::Config().GetParDIR(origname + ".mask");
// Check database
if (maskloc.empty()) {
maskloc = FitPar::GetDataBase() + "/masks/" + origname + ".mask";
}
// Setup Bin Mask
SetBinMask(maskloc);
}
if (fScaleFactor < 0) {
ERR(FTL) << "I found a negative fScaleFactor in " << __FILE__ << ":" << __LINE__ << std::endl;
ERR(FTL) << "fScaleFactor = " << fScaleFactor << std::endl;
ERR(FTL) << "EXITING" << std::endl;
throw;
}
// Create and fill Weighted Histogram
if (!fMCWeighted) {
fMCWeighted = (TH1D*)fMCHist->Clone();
fMCWeighted->SetNameTitle((fName + "_MCWGHTS").c_str(),
(fName + "_MCWGHTS" + fPlotTitles).c_str());
fMCWeighted->GetYaxis()->SetTitle("Weighted Events");
}
}
//********************************************************************
void Measurement1D::SetFitOptions(std::string opt) {
//********************************************************************
// Do nothing if default given
if (opt == "DEFAULT") return;
// CHECK Conflicting Fit Options
std::vector<std::string> fit_option_allow =
GeneralUtils::ParseToStr(fAllowedTypes, "/");
for (UInt_t i = 0; i < fit_option_allow.size(); i++) {
std::vector<std::string> fit_option_section =
GeneralUtils::ParseToStr(fit_option_allow.at(i), ",");
bool found_option = false;
for (UInt_t j = 0; j < fit_option_section.size(); j++) {
std::string av_opt = fit_option_section.at(j);
if (!found_option and opt.find(av_opt) != std::string::npos) {
found_option = true;
} else if (found_option and opt.find(av_opt) != std::string::npos) {
ERR(FTL) << "ERROR: Conflicting fit options provided: "
<< opt << std::endl
<< "Conflicting group = " << fit_option_section.at(i) << std::endl
<< "You should only supply one of these options in card file." << std::endl;
throw;
}
}
}
// Check all options are allowed
std::vector<std::string> fit_options_input =
GeneralUtils::ParseToStr(opt, "/");
for (UInt_t i = 0; i < fit_options_input.size(); i++) {
if (fAllowedTypes.find(fit_options_input.at(i)) == std::string::npos) {
ERR(FTL) << "ERROR: Fit Option '" << fit_options_input.at(i)
<< "' Provided is not allowed for this measurement."
<< std::endl;
ERR(FTL) << "Fit Options should be provided as a '/' seperated list "
"(e.g. FREE/DIAG/NORM)"
<< std::endl;
ERR(FTL) << "Available options for " << fName << " are '" << fAllowedTypes
<< "'" << std::endl;
throw;
}
}
// Set TYPE
fFitType = opt;
// FIX,SHAPE,FREE
if (opt.find("FIX") != std::string::npos) {
fIsFree = fIsShape = false;
fIsFix = true;
} else if (opt.find("SHAPE") != std::string::npos) {
fIsFree = fIsFix = false;
fIsShape = true;
} else if (opt.find("FREE") != std::string::npos) {
fIsFix = fIsShape = false;
fIsFree = true;
}
// DIAG,FULL (or default to full)
if (opt.find("DIAG") != std::string::npos) {
fIsDiag = true;
fIsFull = false;
} else if (opt.find("FULL") != std::string::npos) {
fIsDiag = false;
fIsFull = true;
}
// CHI2/LL (OTHERS?)
if (opt.find("LOG") != std::string::npos) {
fIsChi2 = false;
ERR(FTL) << "No other LIKELIHOODS properly supported!" << std::endl;
ERR(FTL) << "Try to use a chi2!" << std::endl;
throw;
} else {
fIsChi2 = true;
}
// EXTRAS
if (opt.find("RAW") != std::string::npos) fIsRawEvents = true;
if (opt.find("NOWIDTH") != std::string::npos) fIsNoWidth = true;
if (opt.find("DIF") != std::string::npos) fIsDifXSec = true;
if (opt.find("ENU1D") != std::string::npos) fIsEnu1D = true;
if (opt.find("NORM") != std::string::npos) fAddNormPen = true;
if (opt.find("MASK") != std::string::npos) fIsMask = true;
return;
};
//********************************************************************
void Measurement1D::SetSmearingMatrix(std::string smearfile, int truedim,
int recodim) {
//********************************************************************
// The smearing matrix describes the migration from true bins (rows) to reco
// bins (columns)
// Counter over the true bins!
int row = 0;
std::string line;
std::ifstream smear(smearfile.c_str(), std::ifstream::in);
// Note that the smearing matrix may be rectangular.
fSmearMatrix = new TMatrixD(truedim, recodim);
if (smear.is_open())
LOG(SAM) << "Reading smearing matrix from file: " << smearfile << std::endl;
else
ERR(FTL) << "Smearing matrix provided is incorrect: " << smearfile
<< std::endl;
while (std::getline(smear >> std::ws, line, '\n')) {
int column = 0;
std::vector<double> entries = GeneralUtils::ParseToDbl(line, " ");
for (std::vector<double>::iterator iter = entries.begin();
iter != entries.end(); iter++) {
(*fSmearMatrix)(row, column) =
(*iter) / 100.; // Convert to fraction from
// percentage (this may not be
// general enough)
column++;
}
row++;
}
return;
}
//********************************************************************
void Measurement1D::ApplySmearingMatrix() {
//********************************************************************
if (!fSmearMatrix) {
ERR(WRN) << fName
<< ": attempted to apply smearing matrix, but none was set"
<< std::endl;
return;
}
TH1D* unsmeared = (TH1D*)fMCHist->Clone();
TH1D* smeared = (TH1D*)fMCHist->Clone();
smeared->Reset();
// Loop over reconstructed bins
// true = row; reco = column
for (int rbin = 0; rbin < fSmearMatrix->GetNcols(); ++rbin) {
// Sum up the constributions from all true bins
double rBinVal = 0;
// Loop over true bins
for (int tbin = 0; tbin < fSmearMatrix->GetNrows(); ++tbin) {
rBinVal +=
(*fSmearMatrix)(tbin, rbin) * unsmeared->GetBinContent(tbin + 1);
}
smeared->SetBinContent(rbin + 1, rBinVal);
}
fMCHist = (TH1D*)smeared->Clone();
return;
}
/*
Reconfigure LOOP
*/
//********************************************************************
void Measurement1D::ResetAll() {
//********************************************************************
fMCHist->Reset();
fMCFine->Reset();
fMCStat->Reset();
return;
};
//********************************************************************
void Measurement1D::FillHistograms() {
//********************************************************************
if (Signal) {
QLOG(DEB, "Fill MCHist: " << fXVar << ", " << Weight);
fMCHist->Fill(fXVar, Weight);
fMCFine->Fill(fXVar, Weight);
fMCStat->Fill(fXVar, 1.0);
if (fMCHist_Modes) fMCHist_Modes->Fill(Mode, fXVar, Weight);
}
return;
};
//********************************************************************
void Measurement1D::ScaleEvents() {
//********************************************************************
// Fill MCWeighted;
// for (int i = 0; i < fMCHist->GetNbinsX(); i++) {
// fMCWeighted->SetBinContent(i + 1, fMCHist->GetBinContent(i + 1));
// fMCWeighted->SetBinError(i + 1, fMCHist->GetBinError(i + 1));
// }
// Setup Stat ratios for MC and MC Fine
double* statratio = new double[fMCHist->GetNbinsX()];
for (int i = 0; i < fMCHist->GetNbinsX(); i++) {
if (fMCHist->GetBinContent(i + 1) != 0) {
statratio[i] = fMCHist->GetBinError(i + 1) / fMCHist->GetBinContent(i + 1);
} else {
statratio[i] = 0.0;
}
}
double* statratiofine = new double[fMCFine->GetNbinsX()];
for (int i = 0; i < fMCFine->GetNbinsX(); i++) {
if (fMCFine->GetBinContent(i + 1) != 0) {
statratiofine[i] = fMCFine->GetBinError(i + 1) / fMCFine->GetBinContent(i + 1);
} else {
statratiofine[i] = 0.0;
}
}
// Scaling for raw event rates
if (fIsRawEvents) {
double datamcratio = fDataHist->Integral() / fMCHist->Integral();
fMCHist->Scale(datamcratio);
fMCFine->Scale(datamcratio);
if (fMCHist_Modes) fMCHist_Modes->Scale(datamcratio);
// Scaling for XSec as function of Enu
} else if (fIsEnu1D) {
PlotUtils::FluxUnfoldedScaling(fMCHist, GetFluxHistogram(),
GetEventHistogram(), fScaleFactor,
fNEvents);
PlotUtils::FluxUnfoldedScaling(fMCFine, GetFluxHistogram(),
GetEventHistogram(), fScaleFactor,
fNEvents);
// if (fMCHist_Modes) {
// PlotUtils::FluxUnfoldedScaling(fMCHist_Modes, GetFluxHistogram(),
// GetEventHistogram(), fScaleFactor,
// fNEvents);
// }
} else if (fIsNoWidth) {
fMCHist->Scale(fScaleFactor);
fMCFine->Scale(fScaleFactor);
if (fMCHist_Modes) fMCHist_Modes->Scale(fScaleFactor);
// Any other differential scaling
} else {
fMCHist->Scale(fScaleFactor, "width");
fMCFine->Scale(fScaleFactor, "width");
if (fMCHist_Modes) fMCHist_Modes->Scale(fScaleFactor, "width");
}
// Proper error scaling - ROOT Freaks out with xsec weights sometimes
for (int i = 0; i < fMCStat->GetNbinsX(); i++) {
fMCHist->SetBinError(i + 1, fMCHist->GetBinContent(i + 1) * statratio[i]);
}
for (int i = 0; i < fMCFine->GetNbinsX(); i++) {
fMCFine->SetBinError(i + 1, fMCFine->GetBinContent(i + 1) * statratiofine[i]);
}
// Clean up
delete statratio;
delete statratiofine;
return;
};
//********************************************************************
void Measurement1D::ApplyNormScale(double norm) {
//********************************************************************
fCurrentNorm = norm;
fMCHist->Scale(1.0 / norm);
fMCFine->Scale(1.0 / norm);
return;
};
/*
Statistic Functions - Outsources to StatUtils
*/
//********************************************************************
int Measurement1D::GetNDOF() {
//********************************************************************
int ndof = fDataHist->GetNbinsX();
if (fMaskHist and fIsMask) ndof -= fMaskHist->Integral();
return ndof;
}
//********************************************************************
double Measurement1D::GetLikelihood() {
//********************************************************************
// If this is for a ratio, there is no data histogram to compare to!
if (fNoData || !fDataHist) return 0.;
// Apply Masking to MC if Required.
if (fIsMask and fMaskHist) {
PlotUtils::MaskBins(fMCHist, fMaskHist);
}
// Sort Shape Scaling
double scaleF = 0.0;
// TODO Include !fIsRawEvents
if (fIsShape) {
if (fMCHist->Integral(1, fMCHist->GetNbinsX(), "width")) {
scaleF = fDataHist->Integral(1, fDataHist->GetNbinsX(), "width") /
fMCHist->Integral(1, fMCHist->GetNbinsX(), "width");
fMCHist->Scale(scaleF);
fMCFine->Scale(scaleF);
}
}
// Likelihood Calculation
double stat = 0.;
if (fIsChi2) {
if (fIsRawEvents) {
stat = StatUtils::GetChi2FromEventRate(fDataHist, fMCHist, fMaskHist);
} else if (fIsDiag) {
stat = StatUtils::GetChi2FromDiag(fDataHist, fMCHist, fMaskHist);
} else if (!fIsDiag and !fIsRawEvents) {
stat = StatUtils::GetChi2FromCov(fDataHist, fMCHist, covar, fMaskHist);
}
}
// Sort Penalty Terms
if (fAddNormPen) {
double penalty =
(1. - fCurrentNorm) * (1. - fCurrentNorm) / (fNormError * fNormError);
stat += penalty;
}
// Return to normal scaling
if (fIsShape) { // and !FitPar::Config().GetParB("saveshapescaling")) {
fMCHist->Scale(1. / scaleF);
fMCFine->Scale(1. / scaleF);
}
fLikelihood = stat;
return stat;
}
/*
Fake Data Functions
*/
//********************************************************************
void Measurement1D::SetFakeDataValues(std::string fakeOption) {
//********************************************************************
// Setup original/datatrue
TH1D* tempdata = (TH1D*) fDataHist->Clone();
if (!fIsFakeData) {
fIsFakeData = true;
// Make a copy of the original data histogram.
if (!fDataOrig) fDataOrig = (TH1D*)fDataHist->Clone((fName + "_data_original").c_str());
} else {
ResetFakeData();
}
// Setup Inputs
fFakeDataInput = fakeOption;
LOG(SAM) << "Setting fake data from : " << fFakeDataInput << std::endl;
// From MC
if (fFakeDataInput.compare("MC") == 0) {
fDataHist = (TH1D*)fMCHist->Clone((fName + "_MC").c_str());
// Fake File
} else {
if (!fFakeDataFile) fFakeDataFile = new TFile(fFakeDataInput.c_str(), "READ");
fDataHist = (TH1D*)fFakeDataFile->Get((fName + "_MC").c_str());
}
// Setup Data Hist
fDataHist->SetNameTitle((fName + "_FAKE").c_str(),
(fName + fPlotTitles).c_str());
// Replace Data True
if (fDataTrue) delete fDataTrue;
fDataTrue = (TH1D*)fDataHist->Clone();
fDataTrue->SetNameTitle((fName + "_FAKE_TRUE").c_str(),
(fName + fPlotTitles).c_str());
// Make a new covariance for fake data hist.
int nbins = fDataHist->GetNbinsX();
double alpha_i = 0.0;
double alpha_j = 0.0;
for (int i = 0; i < nbins; i++) {
for (int j = 0; j < nbins; j++) {
alpha_i = fDataHist->GetBinContent(i + 1) / tempdata->GetBinContent(i + 1);
alpha_j = fDataHist->GetBinContent(j + 1) / tempdata->GetBinContent(j + 1);
(*fFullCovar)(i, j) = alpha_i * alpha_j * (*fFullCovar)(i, j);
}
}
// Setup Covariances
if (covar) delete covar;
covar = StatUtils::GetInvert(fFullCovar);
if (fDecomp) delete fDecomp;
fDecomp = StatUtils::GetInvert(fFullCovar);
delete tempdata;
return;
};
//********************************************************************
void Measurement1D::ResetFakeData() {
//********************************************************************
if (fIsFakeData) {
if (fDataHist) delete fDataHist;
fDataHist = (TH1D*)fDataTrue->Clone((fSettings.GetName() + "_FKDAT").c_str());
}
}
//********************************************************************
void Measurement1D::ResetData() {
//********************************************************************
if (fIsFakeData) {
if (fDataHist) delete fDataHist;
fDataHist = (TH1D*)fDataOrig->Clone((fSettings.GetName() + "_data").c_str());
}
fIsFakeData = false;
}
//********************************************************************
void Measurement1D::ThrowCovariance() {
//********************************************************************
// Take a fDecomposition and use it to throw the current dataset.
// Requires fDataTrue also be set incase used repeatedly.
if (!fDataTrue) fDataTrue = (TH1D*) fDataHist->Clone();
if (fDataHist) delete fDataHist;
fDataHist = StatUtils::ThrowHistogram(fDataTrue, fFullCovar);
return;
};
//********************************************************************
void Measurement1D::ThrowDataToy(){
//********************************************************************
if (!fDataTrue) fDataTrue = (TH1D*) fDataHist->Clone();
if (fMCHist) delete fMCHist;
fMCHist = StatUtils::ThrowHistogram(fDataTrue, fFullCovar);
}
/*
Access Functions
*/
//********************************************************************
TH1D* Measurement1D::GetMCHistogram() {
//********************************************************************
if (!fMCHist) return fMCHist;
std::ostringstream chi2;
chi2 << std::setprecision(5) << this->GetLikelihood();
int linecolor = kRed;
int linestyle = 1;
int linewidth = 1;
int fillcolor = 0;
int fillstyle = 1001;
// if (fSettings.Has("linecolor")) linecolor = fSettings.GetI("linecolor");
// if (fSettings.Has("linestyle")) linestyle = fSettings.GetI("linestyle");
// if (fSettings.Has("linewidth")) linewidth = fSettings.GetI("linewidth");
// if (fSettings.Has("fillcolor")) fillcolor = fSettings.GetI("fillcolor");
// if (fSettings.Has("fillstyle")) fillstyle = fSettings.GetI("fillstyle");
fMCHist->SetTitle(chi2.str().c_str());
fMCHist->SetLineColor(linecolor);
fMCHist->SetLineStyle(linestyle);
fMCHist->SetLineWidth(linewidth);
fMCHist->SetFillColor(fillcolor);
fMCHist->SetFillStyle(fillstyle);
return fMCHist;
};
//********************************************************************
TH1D* Measurement1D::GetDataHistogram() {
//********************************************************************
if (!fDataHist) return fDataHist;
int datacolor = kBlack;
int datastyle = 1;
int datawidth = 1;
// if (fSettings.Has("datacolor")) datacolor = fSettings.GetI("datacolor");
// if (fSettings.Has("datastyle")) datastyle = fSettings.GetI("datastyle");
// if (fSettings.Has("datawidth")) datawidth = fSettings.GetI("datawidth");
fDataHist->SetLineColor(datacolor);
fDataHist->SetLineWidth(datawidth);
fDataHist->SetMarkerStyle(datastyle);
return fDataHist;
};
/*
Write Functions
*/
// Save all the histograms at once
//********************************************************************
void Measurement1D::Write(std::string drawOpt) {
//********************************************************************
// Get Draw Options
drawOpt = FitPar::Config().GetParS("drawopts");
// Write Settigns
if (drawOpt.find("SETTINGS") != std::string::npos){
fSettings.Set("#chi^{2}",fLikelihood);
fSettings.Set("NDOF", this->GetNDOF() );
fSettings.Set("#chi^{2}/NDOF", fLikelihood / this->GetNDOF() );
fSettings.Write();
}
// Write Data/MC
- GetDataList().at(0)->Write();
- GetMCList().at(0)->Write();
-
- if((fEvtRateScaleFactor != 0xdeadbeef) && GetMCList().at(0)){
- TH1D * PredictedEvtRate = static_cast<TH1D *>(GetMCList().at(0)->Clone());
- PredictedEvtRate->Scale(fEvtRateScaleFactor);
- PredictedEvtRate->GetYaxis()->SetTitle("Predicted event rate");
- PredictedEvtRate->Write();
+ if (drawOpt.find("DATA") != std::string::npos) GetDataList().at(0)->Write();
+ if (drawOpt.find("MC") != std::string::npos) {
+ GetMCList().at(0)->Write();
+ if((fEvtRateScaleFactor != 0xdeadbeef) && GetMCList().at(0)){
+ TH1D * PredictedEvtRate = static_cast<TH1D *>(GetMCList().at(0)->Clone());
+ PredictedEvtRate->Scale(fEvtRateScaleFactor);
+ PredictedEvtRate->GetYaxis()->SetTitle("Predicted event rate");
+ PredictedEvtRate->Write();
+ }
}
-
// Write Fine Histogram
if (drawOpt.find("FINE") != std::string::npos)
GetFineList().at(0)->Write();
// Write Weighted Histogram
if (drawOpt.find("WEIGHTS") != std::string::npos && fMCWeighted)
fMCWeighted->Write();
// Save Flux/Evt if no event manager
if (!FitPar::Config().GetParB("EventManager")) {
-
if (drawOpt.find("FLUX") != std::string::npos && GetFluxHistogram())
GetFluxHistogram()->Write();
if (drawOpt.find("EVT") != std::string::npos && GetEventHistogram())
GetEventHistogram()->Write();
if (drawOpt.find("XSEC") != std::string::npos && GetEventHistogram())
GetXSecHistogram()->Write();
-
}
// Write Mask
if (fIsMask && (drawOpt.find("MASK") != std::string::npos)) {
fMaskHist->Write();
}
-
// Write Covariances
if (drawOpt.find("COV") != std::string::npos && fFullCovar) {
PlotUtils::GetFullCovarPlot(fFullCovar, fSettings.GetName());
}
if (drawOpt.find("INVCOV") != std::string::npos && covar) {
PlotUtils::GetInvCovarPlot(covar, fSettings.GetName());
}
if (drawOpt.find("DECOMP") != std::string::npos && fDecomp) {
PlotUtils::GetDecompCovarPlot(fDecomp, fSettings.GetName());
}
// // Likelihood residual plots
// if (drawOpt.find("RESIDUAL") != std::string::npos) {
// WriteResidualPlots();
// }
// Ratio and Shape Plots
if (drawOpt.find("RATIO") != std::string::npos) {
WriteRatioPlot();
}
if (drawOpt.find("SHAPE") != std::string::npos) {
WriteShapePlot();
if (drawOpt.find("RATIO") != std::string::npos)
WriteShapeRatioPlot();
}
// // RATIO
// if (drawOpt.find("CANVMC") != std::string::npos) {
// TCanvas* c1 = WriteMCCanvas(fDataHist, fMCHist);
// c1->Write();
// delete c1;
// }
// // PDG
// if (drawOpt.find("CANVPDG") != std::string::npos && fMCHist_Modes) {
// TCanvas* c2 = WritePDGCanvas(fDataHist, fMCHist, fMCHist_Modes);
// c2->Write();
// delete c2;
// }
// Write Extra Histograms
AutoWriteExtraTH1();
WriteExtraHistograms();
// Returning
LOG(SAM) << "Written Histograms: " << fName << std::endl;
return;
}
//********************************************************************
void Measurement1D::WriteRatioPlot() {
-//********************************************************************
+ //********************************************************************
// Setup mc data ratios
TH1D* dataRatio = (TH1D*)fDataHist->Clone((fName + "_data_RATIO").c_str());
TH1D* mcRatio = (TH1D*)fMCHist->Clone((fName + "_MC_RATIO").c_str());
// Extra MC Data Ratios
for (int i = 0; i < mcRatio->GetNbinsX(); i++) {
dataRatio->SetBinContent(i + 1, fDataHist->GetBinContent(i + 1) / fMCHist->GetBinContent(i + 1));
dataRatio->SetBinError(i + 1, fDataHist->GetBinError(i + 1) / fMCHist->GetBinContent(i + 1));
mcRatio->SetBinContent(i + 1, fMCHist->GetBinContent(i + 1) / fMCHist->GetBinContent(i + 1));
mcRatio->SetBinError(i + 1, fMCHist->GetBinError(i + 1) / fMCHist->GetBinContent(i + 1));
}
// Write ratios
mcRatio->Write();
dataRatio->Write();
delete mcRatio;
delete dataRatio;
}
//********************************************************************
void Measurement1D::WriteShapePlot() {
-//********************************************************************
+ //********************************************************************
TH1D* mcShape = (TH1D*)fMCHist->Clone((fName + "_MC_SHAPE").c_str());
TH1D* dataShape = (TH1D*)fDataHist->Clone((fName + "_data_SHAPE").c_str());
if (fShapeCovar) StatUtils::SetDataErrorFromCov(dataShape, fShapeCovar, 1E-38);
double shapeScale = 1.0;
if (fIsRawEvents) {
shapeScale = fDataHist->Integral() / fMCHist->Integral();
} else {
shapeScale = fDataHist->Integral("width") / fMCHist->Integral("width");
}
mcShape->Scale(shapeScale);
std::stringstream ss;
ss << shapeScale;
mcShape->SetTitle(ss.str().c_str());
mcShape->SetLineWidth(3);
mcShape->SetLineStyle(7);
mcShape->Write();
dataShape->Write();
delete mcShape;
}
//********************************************************************
void Measurement1D::WriteShapeRatioPlot() {
-//********************************************************************
+ //********************************************************************
// Get a mcshape histogram
TH1D* mcShape = (TH1D*)fMCHist->Clone((fName + "_MC_SHAPE").c_str());
double shapeScale = 1.0;
if (fIsRawEvents) {
shapeScale = fDataHist->Integral() / fMCHist->Integral();
} else {
shapeScale = fDataHist->Integral("width") / fMCHist->Integral("width");
}
mcShape->Scale(shapeScale);
// Create shape ratio histograms
TH1D* mcShapeRatio = (TH1D*)mcShape->Clone((fName + "_MC_SHAPE_RATIO").c_str());
TH1D* dataShapeRatio = (TH1D*)fDataHist->Clone((fName + "_data_SHAPE_RATIO").c_str());
// Divide the histograms
mcShapeRatio->Divide(mcShape);
dataShapeRatio->Divide(mcShape);
// Colour the shape ratio plots
mcShapeRatio->SetLineWidth(3);
mcShapeRatio->SetLineStyle(7);
mcShapeRatio->Write();
dataShapeRatio->Write();
delete mcShapeRatio;
delete dataShapeRatio;
-
}
//// CRAP TO BE REMOVED
//********************************************************************
void Measurement1D::SetupMeasurement(std::string inputfile, std::string type,
- FitWeight * rw, std::string fkdt) {
+ FitWeight * rw, std::string fkdt) {
//********************************************************************
nuiskey samplekey = Config::CreateKey("sample");
samplekey.Set("name", fName);
samplekey.Set("type",type);
samplekey.Set("input",inputfile);
fSettings = LoadSampleSettings(samplekey);
// Reset everything to NULL
// Init();
// Check if name contains Evt, indicating that it is a raw number of events
// measurements and should thus be treated as once
fIsRawEvents = false;
if ((fName.find("Evt") != std::string::npos) && fIsRawEvents == false) {
fIsRawEvents = true;
LOG(SAM) << "Found event rate measurement but fIsRawEvents == false!"
- << std::endl;
+ << std::endl;
LOG(SAM) << "Overriding this and setting fIsRawEvents == true!"
- << std::endl;
+ << std::endl;
}
fIsEnu1D = false;
if (fName.find("XSec_1DEnu") != std::string::npos) {
fIsEnu1D = true;
LOG(SAM) << "::" << fName << "::" << std::endl;
LOG(SAM) << "Found XSec Enu measurement, applying flux integrated scaling, "
- "not flux averaged!"
- << std::endl;
+ "not flux averaged!"
+ << std::endl;
}
if (fIsEnu1D && fIsRawEvents) {
LOG(SAM) << "Found 1D Enu XSec distribution AND fIsRawEvents, is this "
- "really correct?!"
- << std::endl;
+ "really correct?!"
+ << std::endl;
LOG(SAM) << "Check experiment constructor for " << fName
- << " and correct this!" << std::endl;
+ << " and correct this!" << std::endl;
LOG(SAM) << "I live in " << __FILE__ << ":" << __LINE__ << std::endl;
exit(-1);
}
fRW = rw;
if (!fInput and !fIsJoint) SetupInputs(inputfile);
// Set Default Options
SetFitOptions(fDefaultTypes);
// Set Passed Options
SetFitOptions(type);
// Still adding support for flat flux inputs
// // Set Enu Flux Scaling
// if (isFlatFluxFolding) this->Input()->ApplyFluxFolding(
// this->defaultFluxHist );
// FinaliseMeasurement();
}
//********************************************************************
void Measurement1D::SetupDefaultHist() {
//********************************************************************
// Setup fMCHist
fMCHist = (TH1D*)fDataHist->Clone();
fMCHist->SetNameTitle((fName + "_MC").c_str(),
- (fName + "_MC" + fPlotTitles).c_str());
+ (fName + "_MC" + fPlotTitles).c_str());
// Setup fMCFine
Int_t nBins = fMCHist->GetNbinsX();
fMCFine = new TH1D(
- (fName + "_MC_FINE").c_str(), (fName + "_MC_FINE" + fPlotTitles).c_str(),
- nBins * 6, fMCHist->GetBinLowEdge(1), fMCHist->GetBinLowEdge(nBins + 1));
+ (fName + "_MC_FINE").c_str(), (fName + "_MC_FINE" + fPlotTitles).c_str(),
+ nBins * 6, fMCHist->GetBinLowEdge(1), fMCHist->GetBinLowEdge(nBins + 1));
fMCStat = (TH1D*)fMCHist->Clone();
fMCStat->Reset();
fMCHist->Reset();
fMCFine->Reset();
// Setup the NEUT Mode Array
PlotUtils::CreateNeutModeArray((TH1D*)fMCHist, (TH1**)fMCHist_PDG);
PlotUtils::ResetNeutModeArray((TH1**)fMCHist_PDG);
// Setup bin masks using sample name
if (fIsMask) {
std::string maskloc = FitPar::Config().GetParDIR(fName + ".mask");
if (maskloc.empty()) {
maskloc = FitPar::GetDataBase() + "/masks/" + fName + ".mask";
}
SetBinMask(maskloc);
}
fMCHist_Modes = new TrueModeStack( (fName + "_MODES").c_str(), ("True Channels"), fMCHist);
SetAutoProcessTH1(fMCHist_Modes, kCMD_Reset, kCMD_Norm, kCMD_Write);
return;
}
//********************************************************************
void Measurement1D::SetDataValues(std::string dataFile) {
//********************************************************************
// Override this function if the input file isn't in a suitable format
LOG(SAM) << "Reading data from: " << dataFile.c_str() << std::endl;
fDataHist =
PlotUtils::GetTH1DFromFile(dataFile, (fName + "_data"), fPlotTitles);
fDataTrue = (TH1D*)fDataHist->Clone();
// Number of data points is number of bins
fNDataPointsX = fDataHist->GetXaxis()->GetNbins();
return;
};
//********************************************************************
void Measurement1D::SetDataFromDatabase(std::string inhistfile,
- std::string histname) {
+ std::string histname) {
//********************************************************************
LOG(SAM) << "Filling histogram from " << inhistfile << "->" << histname
- << std::endl;
+ << std::endl;
fDataHist = PlotUtils::GetTH1DFromRootFile(
- (GeneralUtils::GetTopLevelDir() + "/data/" + inhistfile), histname);
+ (GeneralUtils::GetTopLevelDir() + "/data/" + inhistfile), histname);
fDataHist->SetNameTitle((fName + "_data").c_str(), (fName + "_data").c_str());
return;
};
//********************************************************************
void Measurement1D::SetDataFromFile(std::string inhistfile,
- std::string histname) {
+ std::string histname) {
//********************************************************************
LOG(SAM) << "Filling histogram from " << inhistfile << "->" << histname
- << std::endl;
+ << std::endl;
fDataHist = PlotUtils::GetTH1DFromRootFile((inhistfile), histname);
fDataHist->SetNameTitle((fName + "_data").c_str(), (fName + "_data").c_str());
return;
};
//********************************************************************
void Measurement1D::SetCovarMatrix(std::string covarFile) {
//********************************************************************
// Covariance function, only really used when reading in the MB Covariances.
TFile* tempFile = new TFile(covarFile.c_str(), "READ");
TH2D* covarPlot = new TH2D();
// TH2D* decmpPlot = new TH2D();
TH2D* covarInvPlot = new TH2D();
TH2D* fFullCovarPlot = new TH2D();
std::string covName = "";
std::string covOption = FitPar::Config().GetParS("thrown_covariance");
if (fIsShape || fIsFree) covName = "shp_";
if (fIsDiag)
covName += "diag";
else
covName += "full";
covarPlot = (TH2D*)tempFile->Get((covName + "cov").c_str());
covarInvPlot = (TH2D*)tempFile->Get((covName + "covinv").c_str());
if (!covOption.compare("SUB"))
fFullCovarPlot = (TH2D*)tempFile->Get((covName + "cov").c_str());
else if (!covOption.compare("FULL"))
fFullCovarPlot = (TH2D*)tempFile->Get("fullcov");
else
ERR(WRN) << "Incorrect thrown_covariance option in parameters."
- << std::endl;
+ << std::endl;
int dim = int(fDataHist->GetNbinsX()); //-this->masked->Integral());
int covdim = int(fDataHist->GetNbinsX());
this->covar = new TMatrixDSym(dim);
fFullCovar = new TMatrixDSym(dim);
fDecomp = new TMatrixDSym(dim);
int row, column = 0;
row = 0;
column = 0;
for (Int_t i = 0; i < covdim; i++) {
// if (this->masked->GetBinContent(i+1) > 0) continue;
for (Int_t j = 0; j < covdim; j++) {
// if (this->masked->GetBinContent(j+1) > 0) continue;
(*this->covar)(row, column) = covarPlot->GetBinContent(i + 1, j + 1);
(*fFullCovar)(row, column) = fFullCovarPlot->GetBinContent(i + 1, j + 1);
column++;
}
column = 0;
row++;
}
// Set bin errors on data
if (!fIsDiag) {
StatUtils::SetDataErrorFromCov(fDataHist, fFullCovar);
}
// Get Deteriminant and inverse matrix
// fCovDet = this->covar->Determinant();
TDecompSVD LU = TDecompSVD(*this->covar);
this->covar = new TMatrixDSym(dim, LU.Invert().GetMatrixArray(), "");
return;
};
//********************************************************************
// Sets the covariance matrix from a provided file in a text format
// scale is a multiplicative pre-factor to apply in the case where the
// covariance is given in some unit (e.g. 1E-38)
void Measurement1D::SetCovarMatrixFromText(std::string covarFile, int dim,
double scale) {
//********************************************************************
// Make a counter to track the line number
int row = 0;
std::string line;
std::ifstream covarread(covarFile.c_str(), std::ifstream::in);
this->covar = new TMatrixDSym(dim);
fFullCovar = new TMatrixDSym(dim);
if (covarread.is_open())
LOG(SAM) << "Reading covariance matrix from file: " << covarFile
- << std::endl;
+ << std::endl;
else
ERR(FTL) << "Covariance matrix provided is incorrect: " << covarFile
- << std::endl;
+ << std::endl;
// Loop over the lines in the file
while (std::getline(covarread >> std::ws, line, '\n')) {
int column = 0;
// Loop over entries and insert them into matrix
std::vector<double> entries = GeneralUtils::ParseToDbl(line, " ");
if (entries.size() <= 1) {
ERR(WRN) << "SetCovarMatrixFromText -> Covariance matrix only has <= 1 "
- "entries on this line: "
- << row << std::endl;
+ "entries on this line: "
+ << row << std::endl;
}
for (std::vector<double>::iterator iter = entries.begin();
- iter != entries.end(); iter++) {
+ iter != entries.end(); iter++) {
(*covar)(row, column) = *iter;
(*fFullCovar)(row, column) = *iter;
column++;
}
row++;
}
covarread.close();
// Scale the actualy covariance matrix by some multiplicative factor
(*fFullCovar) *= scale;
// Robust matrix inversion method
TDecompSVD LU = TDecompSVD(*this->covar);
// THIS IS ACTUALLY THE INVERSE COVARIANCE MATRIXA AAAAARGH
delete this->covar;
this->covar = new TMatrixDSym(dim, LU.Invert().GetMatrixArray(), "");
// Now need to multiply by the scaling factor
// If the covariance
(*this->covar) *= 1. / (scale);
return;
};
//********************************************************************
void Measurement1D::SetCovarMatrixFromCorrText(std::string corrFile, int dim) {
//********************************************************************
// Make a counter to track the line number
int row = 0;
std::string line;
std::ifstream corr(corrFile.c_str(), std::ifstream::in);
this->covar = new TMatrixDSym(dim);
this->fFullCovar = new TMatrixDSym(dim);
if (corr.is_open())
LOG(SAM) << "Reading and converting correlation matrix from file: "
- << corrFile << std::endl;
+ << corrFile << std::endl;
else {
ERR(FTL) << "Correlation matrix provided is incorrect: " << corrFile
- << std::endl;
+ << std::endl;
exit(-1);
}
while (std::getline(corr >> std::ws, line, '\n')) {
int column = 0;
// Loop over entries and insert them into matrix
// Multiply by the errors to get the covariance, rather than the correlation
// matrix
std::vector<double> entries = GeneralUtils::ParseToDbl(line, " ");
for (std::vector<double>::iterator iter = entries.begin();
- iter != entries.end(); iter++) {
+ iter != entries.end(); iter++) {
double val = (*iter) * this->fDataHist->GetBinError(row + 1) * 1E38 *
- this->fDataHist->GetBinError(column + 1) * 1E38;
+ this->fDataHist->GetBinError(column + 1) * 1E38;
if (val == 0) {
ERR(FTL) << "Found a zero value in the covariance matrix, assuming "
- "this is an error!"
- << std::endl;
+ "this is an error!"
+ << std::endl;
exit(-1);
}
(*this->covar)(row, column) = val;
(*this->fFullCovar)(row, column) = val;
column++;
}
row++;
}
// Robust matrix inversion method
TDecompSVD LU = TDecompSVD(*this->covar);
delete this->covar;
this->covar = new TMatrixDSym(dim, LU.Invert().GetMatrixArray(), "");
return;
};
//********************************************************************
// FullUnits refers to if we have "real" unscaled units in the covariance matrix, e.g. 1E-76.
// If this is the case we need to scale it so that the chi2 contribution is correct
// NUISANCE internally assumes the covariance matrix has units of 1E76
void Measurement1D::SetCovarFromDataFile(std::string covarFile,
std::string covName, bool FullUnits) {
//********************************************************************
LOG(SAM) << "Getting covariance from " << covarFile << "->" << covName
- << std::endl;
+ << std::endl;
TFile* tempFile = new TFile(covarFile.c_str(), "READ");
TH2D* covPlot = (TH2D*)tempFile->Get(covName.c_str());
covPlot->SetDirectory(0);
// Scale the covariance matrix if it comes in normal units
if (FullUnits) {
covPlot->Scale(1.E76);
}
int dim = covPlot->GetNbinsX();
fFullCovar = new TMatrixDSym(dim);
for (int i = 0; i < dim; i++) {
for (int j = 0; j < dim; j++) {
(*fFullCovar)(i, j) = covPlot->GetBinContent(i + 1, j + 1);
}
}
this->covar = (TMatrixDSym*)fFullCovar->Clone();
fDecomp = (TMatrixDSym*)fFullCovar->Clone();
TDecompSVD LU = TDecompSVD(*this->covar);
this->covar = new TMatrixDSym(dim, LU.Invert().GetMatrixArray(), "");
TDecompChol LUChol = TDecompChol(*fDecomp);
LUChol.Decompose();
fDecomp = new TMatrixDSym(dim, LU.GetU().GetMatrixArray(), "");
return;
};
// //********************************************************************
// void Measurement1D::SetBinMask(std::string maskFile) {
// //********************************************************************
// // Create a mask histogram.
// int nbins = fDataHist->GetNbinsX();
// fMaskHist =
// new TH1I((fName + "_fMaskHist").c_str(),
// (fName + "_fMaskHist; Bin; Mask?").c_str(), nbins, 0, nbins);
// std::string line;
// std::ifstream mask(maskFile.c_str(), std::ifstream::in);
// if (mask.is_open())
// LOG(SAM) << "Reading bin mask from file: " << maskFile << std::endl;
// else
// LOG(FTL) << " Cannot find mask file." << std::endl;
// while (std::getline(mask >> std::ws, line, '\n')) {
// std::vector<int> entries = GeneralUtils::ParseToInt(line, " ");
// // Skip lines with poorly formatted lines
// if (entries.size() < 2) {
// LOG(WRN) << "Measurement1D::SetBinMask(), couldn't parse line: " << line
// << std::endl;
// continue;
// }
// // The first index should be the bin number, the second should be the mask
// // value.
// fMaskHist->SetBinContent(entries[0], entries[1]);
// }
// // Set masked data bins to zero
// PlotUtils::MaskBins(fDataHist, fMaskHist);
// return;
// }
// //********************************************************************
// void Measurement1D::GetBinContents(std::vector<double>& cont,
// std::vector<double>& err) {
// //********************************************************************
// // Return a vector of the main bin contents
// for (int i = 0; i < fMCHist->GetNbinsX(); i++) {
// cont.push_back(fMCHist->GetBinContent(i + 1));
// err.push_back(fMCHist->GetBinError(i + 1));
// }
// return;
// };
/*
XSec Functions
*/
// //********************************************************************
// void Measurement1D::SetFluxHistogram(std::string fluxFile, int minE, int
// maxE,
// double fluxNorm) {
// //********************************************************************
// // Note this expects the flux bins to be given in terms of MeV
// LOG(SAM) << "Reading flux from file: " << fluxFile << std::endl;
// TGraph f(fluxFile.c_str(), "%lg %lg");
// fFluxHist =
// new TH1D((fName + "_flux").c_str(), (fName + "; E_{#nu} (GeV)").c_str(),
// f.GetN() - 1, minE, maxE);
// Double_t* yVal = f.GetY();
// for (int i = 0; i < fFluxHist->GetNbinsX(); ++i)
// fFluxHist->SetBinContent(i + 1, yVal[i] * fluxNorm);
// };
// //********************************************************************
// double Measurement1D::TotalIntegratedFlux(std::string intOpt, double low,
// double high) {
// //********************************************************************
// if (fInput->GetType() == kGiBUU) {
// return 1.0;
// }
// // The default case of low = -9999.9 and high = -9999.9
// if (low == -9999.9) low = this->EnuMin;
// if (high == -9999.9) high = this->EnuMax;
// int minBin = fFluxHist->GetXaxis()->FindBin(low);
// int maxBin = fFluxHist->GetXaxis()->FindBin(high);
// // Get integral over custom range
// double integral = fFluxHist->Integral(minBin, maxBin + 1, intOpt.c_str());
// return integral;
// };