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diff --git a/src/FitBase/JointMeas1D.cxx b/src/FitBase/JointMeas1D.cxx
index 3b6978f..30d4037 100644
--- a/src/FitBase/JointMeas1D.cxx
+++ b/src/FitBase/JointMeas1D.cxx
@@ -1,2222 +1,2223 @@
// Copyright 2016-2021 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 "JointMeas1D.h"
//********************************************************************
JointMeas1D::JointMeas1D(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;
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";
fIsFix = false;
fIsShape = false;
fIsFree = false;
fIsDiag = false;
fIsFull = false;
fAddNormPen = false;
fIsMask = false;
fIsChi2SVD = false;
fIsRawEvents = false;
fIsDifXSec = false;
fIsEnu1D = false;
+ fSaveFine = true;
// Inputs
fInput = NULL;
fRW = NULL;
// Extra Histograms
fMCHist_Modes = NULL;
for (std::vector<MeasurementBase *>::const_iterator iter = fSubChain.begin();
iter != fSubChain.end(); iter++) {
MeasurementBase *exp = *iter;
if (exp)
delete exp;
}
fSubChain.clear();
// Flags for Joint Measurements
fIsRatio = false;
fIsSummed = false;
fSaveSubMeas = false;
fIsJoint = true;
}
//********************************************************************
void JointMeas1D::SetupDefaultHist() {
//********************************************************************
// Setup fMCHist
fMCHist = (TH1D *)fDataHist->Clone();
fMCHist->SetNameTitle((fName + "_MC").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));
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);
return;
}
//********************************************************************
JointMeas1D::~JointMeas1D(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 (fCovar)
delete fCovar;
if (fInvert)
delete fInvert;
if (fDecomp)
delete fDecomp;
for (std::vector<MeasurementBase *>::const_iterator iter = fSubChain.begin();
iter != fSubChain.end(); iter++) {
MeasurementBase *exp = *iter;
if (exp)
delete exp;
}
fSubChain.clear();
}
//********************************************************************
SampleSettings JointMeas1D::LoadSampleSettings(nuiskey samplekey) {
//********************************************************************
SampleSettings s = MeasurementBase::LoadSampleSettings(samplekey);
// Parse Inputs
fSubInFiles.clear();
std::vector<std::string> entries =
GeneralUtils::ParseToStr(s.GetS("input"), ";");
if (entries.size() < 2) {
NUIS_ABORT("Joint measurement expected to recieve at least two semi-colon "
"separated input files, but recieved: \""
<< s.GetS("input") << "\"");
}
std::vector<std::string> first_file_descriptor =
GeneralUtils::ParseToStr(entries.front(), ":");
if (first_file_descriptor.size() != 2) {
NUIS_ABORT("Found Joint measurement where the input file had no type: \""
<< s.GetS("input")
<< "\", expected \"INPUTTYPE:File.root;File2.root\".");
}
std::string inpType = first_file_descriptor[0];
for (std::vector<std::string>::iterator iter = entries.begin();
iter != entries.end(); iter++) {
if (GeneralUtils::ParseToStr(*iter, ":").size() != 2) {
std::stringstream ss("");
ss << inpType << ":" << (*iter);
fSubInFiles.push_back(ss.str());
} else {
fSubInFiles.push_back(*iter);
}
}
return s;
}
//********************************************************************
void JointMeas1D::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
NUIS_LOG(SAM, "Finalising Sample Settings: " << fName);
if ((fSettings.GetS("originalname").find("Evt") != std::string::npos)) {
fIsRawEvents = true;
NUIS_LOG(SAM, "Found event rate measurement but using poisson likelihoods.");
}
if (fSettings.GetS("originalname").find("XSec_1DEnu") != std::string::npos) {
fIsEnu1D = true;
NUIS_LOG(SAM, "::" << fName << "::");
NUIS_LOG(SAM, "Found XSec Enu measurement, applying flux integrated scaling, "
<< "not flux averaged!");
}
if (fIsEnu1D && fIsRawEvents) {
NUIS_LOG(SAM, "Found 1D Enu XSec distribution AND fIsRawEvents, is this "
"really correct?!");
NUIS_LOG(SAM,
"Check experiment constructor for " << fName << " and correct this!");
NUIS_LOG(SAM, "I live in " << __FILE__ << ":" << __LINE__);
exit(-1);
}
// Parse Inputs
fSubInFiles.clear();
std::vector<std::string> entries =
GeneralUtils::ParseToStr(fSettings.GetS("input"), ";");
if (entries.size() < 2) {
NUIS_ABORT("Joint measurement expected to recieve at least two semi-colon "
"separated input files, but recieved: \""
<< fSettings.GetS("input") << "\"");
}
std::vector<std::string> first_file_descriptor =
GeneralUtils::ParseToStr(entries.front(), ":");
if (first_file_descriptor.size() != 2) {
NUIS_ABORT("Found Joint measurement where the input file had no type: \""
<< fSettings.GetS("input")
<< "\", expected \"INPUTTYPE:File.root;File2.root\".");
}
std::string inpType = first_file_descriptor[0];
for (std::vector<std::string>::iterator iter = entries.begin();
iter != entries.end(); iter++) {
if (GeneralUtils::ParseToStr(*iter, ":").size() != 2) {
std::stringstream ss("");
ss << inpType << ":" << (*iter);
fSubInFiles.push_back(ss.str());
} else {
fSubInFiles.push_back(*iter);
}
}
// 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) {
NUIS_ERR(FTL, "Norm error for class " << fName << " is 0.0!");
NUIS_ERR(FTL, "If you want to use it please add fNormError=VAL");
throw;
}
}
if (!fRW)
fRW = FitBase::GetRW();
NUIS_LOG(SAM, "Finalised Sample Settings");
}
//********************************************************************
void JointMeas1D::SetDataFromTextFile(std::string datafile) {
//********************************************************************
NUIS_LOG(SAM, "Reading data from text file: " << datafile);
fDataHist = PlotUtils::GetTH1DFromFile(
datafile, fSettings.GetName() + "_data", fSettings.GetFullTitles());
}
//********************************************************************
void JointMeas1D::SetDataFromRootFile(std::string datafile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM, "Reading data from root file: " << datafile << ";" << histname);
fDataHist = PlotUtils::GetTH1DFromRootFile(datafile, histname);
fDataHist->SetNameTitle((fSettings.GetName() + "_data").c_str(),
(fSettings.GetFullTitles()).c_str());
return;
};
//********************************************************************
void JointMeas1D::SetPoissonErrors() {
//********************************************************************
if (!fDataHist) {
NUIS_ERR(FTL, "Need a data hist to setup possion errors! ");
NUIS_ABORT("Setup Data First!");
}
for (int i = 0; i < fDataHist->GetNbinsX() + 1; i++) {
fDataHist->SetBinError(i + 1, sqrt(fDataHist->GetBinContent(i + 1)));
}
}
//********************************************************************
void JointMeas1D::SetCovarFromDiagonal(TH1D *data) {
//********************************************************************
if (!data and fDataHist) {
data = fDataHist;
}
if (data) {
NUIS_LOG(SAM, "Setting diagonal covariance for: " << data->GetName());
fFullCovar = StatUtils::MakeDiagonalCovarMatrix(data);
covar = StatUtils::GetInvert(fFullCovar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
} else {
NUIS_ERR(FTL, "No data input provided to set diagonal covar from!");
}
if (!fIsDiag) {
NUIS_ERR(FTL, "SetCovarMatrixFromDiag called for measurement "
<< "that is not set as diagonal.");
throw;
}
}
//********************************************************************
void JointMeas1D::SetCovarFromTextFile(std::string covfile, int dim) {
//********************************************************************
NUIS_LOG(SAM, "Reading covariance from text file: " << covfile);
fFullCovar = StatUtils::GetCovarFromTextFile(covfile, dim);
covar = StatUtils::GetInvert(fFullCovar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void JointMeas1D::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) {
NUIS_LOG(SAM, "Reading covariance from text file: " << covList[i]);
TMatrixDSym *temp_cov = StatUtils::GetCovarFromTextFile(covList[i], dim);
(*fFullCovar) += (*temp_cov);
delete temp_cov;
}
covar = StatUtils::GetInvert(fFullCovar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void JointMeas1D::SetCovarFromRootFile(std::string covfile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM,
"Reading covariance from text file: " << covfile << ";" << histname);
fFullCovar = StatUtils::GetCovarFromRootFile(covfile, histname);
covar = StatUtils::GetInvert(fFullCovar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void JointMeas1D::SetCovarInvertFromTextFile(std::string covfile, int dim) {
//********************************************************************
NUIS_LOG(SAM, "Reading inverted covariance from text file: " << covfile);
covar = StatUtils::GetCovarFromTextFile(covfile, dim);
fFullCovar = StatUtils::GetInvert(covar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void JointMeas1D::SetCovarInvertFromRootFile(std::string covfile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM, "Reading inverted covariance from text file: " << covfile << ";"
<< histname);
covar = StatUtils::GetCovarFromRootFile(covfile, histname);
fFullCovar = StatUtils::GetInvert(covar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void JointMeas1D::SetCorrelationFromTextFile(std::string covfile, int dim) {
//********************************************************************
if (dim == -1)
dim = fDataHist->GetNbinsX();
NUIS_LOG(SAM,
"Reading data correlations from text file: " << covfile << ";" << dim);
TMatrixDSym *correlation = StatUtils::GetCovarFromTextFile(covfile, dim);
if (!fDataHist) {
NUIS_ABORT("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");
}
// 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,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete correlation;
}
//********************************************************************
void JointMeas1D::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) {
NUIS_LOG(SAM, "Reading covariance from text file: " << corrList[i]);
TMatrixDSym *temp_cov = StatUtils::GetCovarFromTextFile(corrList[i], dim);
for (int i = 0; i < fDataHist->GetNbinsX(); i++) {
for (int j = 0; j < fDataHist->GetNbinsX(); j++) {
// Note that there is a factor of 1E76 here. It is very silly indeed.
// However, if you remove it, you also need to fix the factors of 1E38
// added to the chi2 calculations!
(*temp_cov)(i, j) = (*temp_cov)(i, j) * fDataHist->GetBinError(i + 1) *
fDataHist->GetBinError(j + 1) * 1E76;
}
}
(*fFullCovar) += (*temp_cov);
delete temp_cov;
}
covar = StatUtils::GetInvert(fFullCovar,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
//********************************************************************
void JointMeas1D::SetCorrelationFromRootFile(std::string covfile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM, "Reading data correlations from text file: " << covfile << ";"
<< histname);
TMatrixDSym *correlation = StatUtils::GetCovarFromRootFile(covfile, histname);
if (!fDataHist) {
NUIS_ABORT("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");
}
// 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,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete correlation;
}
void JointMeas1D::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 JointMeas1D::SetCholDecompFromTextFile(std::string covfile, int dim) {
//********************************************************************
NUIS_LOG(SAM, "Reading cholesky from text file: " << covfile);
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,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete temp;
delete trans;
}
//********************************************************************
void JointMeas1D::SetCholDecompFromRootFile(std::string covfile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM, "Reading cholesky decomp from root file: " << covfile << ";"
<< histname);
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,true);
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete temp;
delete trans;
}
//********************************************************************
void JointMeas1D::ScaleData(double scale) {
//********************************************************************
fDataHist->Scale(scale);
}
//********************************************************************
void JointMeas1D::ScaleCovar(double scale) {
//********************************************************************
(*fFullCovar) *= scale;
(*covar) *= 1.0 / scale;
(*fDecomp) *= sqrt(scale);
}
//********************************************************************
void JointMeas1D::SetBinMask(std::string maskfile) {
//********************************************************************
if (!fIsMask)
return;
NUIS_LOG(SAM, "Reading bin mask from file: " << maskfile);
// 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()) {
NUIS_ABORT(" Cannot find mask file: " << maskfile);
}
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) {
NUIS_LOG(WRN, "JointMeas1D::SetBinMask(), couldn't parse line: " << line);
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 JointMeas1D::FinaliseMeasurement() {
//********************************************************************
NUIS_LOG(SAM, "Finalising Measurement: " << fName);
// Make sure data is setup
if (!fDataHist) {
NUIS_ABORT("No data has been setup inside " << fName << " constructor!");
}
// Make sure covariances are setup
if (!fFullCovar) {
fIsDiag = true;
SetCovarFromDiagonal(fDataHist);
}
if (!covar) {
covar = StatUtils::GetInvert(fFullCovar,true);
}
if (!fDecomp) {
fDecomp = StatUtils::GetDecomp(fFullCovar);
}
// Push the diagonals of fFullCovar onto the data histogram
// Comment out until scaling is used consistently...
StatUtils::SetDataErrorFromCov(fDataHist, fFullCovar, 1E-38);
// 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(),
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);
}
// 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 JointMeas1D::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) {
NUIS_ABORT("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.");
}
}
}
// 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) {
NUIS_ERR(FTL, "ERROR: Fit Option '"
<< fit_options_input.at(i)
<< "' Provided is not allowed for this measurement.");
NUIS_ERR(FTL, "Fit Options should be provided as a '/' separated list "
"(e.g. FREE/DIAG/NORM)");
NUIS_ERR(FTL, "Available options for " << fName << " are '" << fAllowedTypes
<< "'");
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;
NUIS_ERR(FTL, "No other LIKELIHOODS properly supported!");
NUIS_ERR(FTL, "Try to use a chi2!");
throw;
} else {
fIsChi2 = true;
}
// EXTRAS
if (opt.find("RAW") != std::string::npos)
fIsRawEvents = 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 JointMeas1D::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()) {
NUIS_LOG(SAM, "Reading smearing matrix from file: " << smearfile);
} else {
NUIS_ABORT("Smearing matrix provided is incorrect: " << smearfile);
}
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 JointMeas1D::ApplySmearingMatrix() {
//********************************************************************
if (!fSmearMatrix) {
NUIS_ERR(WRN,
fName << ": attempted to apply smearing matrix, but none was set");
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 JointMeas1D::ResetAll() {
//********************************************************************
fMCHist->Reset();
fMCFine->Reset();
fMCStat->Reset();
return;
};
//********************************************************************
void JointMeas1D::FillHistograms() {
//********************************************************************
if (Signal) {
fMCHist->Fill(fXVar, Weight);
fMCFine->Fill(fXVar, Weight);
fMCStat->Fill(fXVar, 1.0);
if (fMCHist_Modes)
fMCHist_Modes->Fill(Mode, fXVar, Weight);
}
return;
};
//********************************************************************
void JointMeas1D::ScaleEvents() {
//********************************************************************
NUIS_LOG(FIT, "Scaling JointMeas1D");
// 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);
// }
// 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 JointMeas1D::ApplyNormScale(double norm) {
//********************************************************************
fCurrentNorm = norm;
fMCHist->Scale(1.0 / norm);
fMCFine->Scale(1.0 / norm);
return;
};
/*
Statistic Functions - Outsources to StatUtils
*/
//********************************************************************
int JointMeas1D::GetNDOF() {
//********************************************************************
int ndof = fDataHist->GetNbinsX();
if (fMaskHist)
ndof -= fMaskHist->Integral();
return ndof;
}
//********************************************************************
double JointMeas1D::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;
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 JointMeas1D::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;
NUIS_LOG(SAM, "Setting fake data from : " << fFakeDataInput);
// 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,true);
if (fDecomp)
delete fDecomp;
fDecomp = StatUtils::GetDecomp(fFullCovar);
delete tempdata;
return;
};
//********************************************************************
void JointMeas1D::ResetFakeData() {
//********************************************************************
if (fIsFakeData) {
if (fDataHist)
delete fDataHist;
fDataHist =
(TH1D *)fDataTrue->Clone((fSettings.GetName() + "_FKDAT").c_str());
}
}
//********************************************************************
void JointMeas1D::ResetData() {
//********************************************************************
if (fIsFakeData) {
if (fDataHist)
delete fDataHist;
fDataHist =
(TH1D *)fDataOrig->Clone((fSettings.GetName() + "_data").c_str());
}
fIsFakeData = false;
}
//********************************************************************
void JointMeas1D::ThrowCovariance() {
//********************************************************************
// Take a fDecomposition and use it to throw the current dataset.
// Requires fDataTrue also be set incase used repeatedly.
if (fDataHist)
delete fDataHist;
fDataHist = StatUtils::ThrowHistogram(fDataTrue, fFullCovar);
return;
};
//********************************************************************
void JointMeas1D::ThrowDataToy() {
//********************************************************************
if (!fDataTrue)
fDataTrue = (TH1D *)fDataHist->Clone();
if (fMCHist)
delete fMCHist;
fMCHist = StatUtils::ThrowHistogram(fDataTrue, fFullCovar);
}
/*
Access Functions
*/
//********************************************************************
TH1D *JointMeas1D::GetMCHistogram() {
//********************************************************************
if (!fMCHist)
return fMCHist;
std::ostringstream chi2;
chi2 << "#chi^{2}=" << 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 *JointMeas1D::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 JointMeas1D::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
GetDataHistogram()->Write();
GetMCHistogram()->Write();
// Write Fine Histogram
- if (drawOpt.find("FINE") != std::string::npos)
+ if (fSaveFine && 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())
GetEventHistogram()->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())->Write();
}
if (drawOpt.find("INVCOV") != std::string::npos && covar) {
PlotUtils::GetInvCovarPlot(covar, fSettings.GetName())->Write();
}
if (drawOpt.find("DECOMP") != std::string::npos && fDecomp) {
PlotUtils::GetDecompCovarPlot(fDecomp, fSettings.GetName())->Write();
}
// // 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();
if (fSaveSubMeas) {
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
exp->Write(drawOpt);
}
}
// Returning
NUIS_LOG(SAM, "Written Histograms: " << fName);
return;
}
//********************************************************************
void JointMeas1D::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 JointMeas1D::WriteShapePlot() {
//********************************************************************
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);
std::stringstream ss;
ss << "Scale=" << shapeScale;
mcShape->SetTitle(ss.str().c_str());
mcShape->SetLineWidth(3);
mcShape->SetLineStyle(7);
mcShape->Write();
delete mcShape;
}
//********************************************************************
void JointMeas1D::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;
}
/*
Setup Functions
*/
//********************************************************************
void JointMeas1D::SetupMeasurement(std::string input, std::string type,
FitWeight *rw, std::string fkdt) {
//********************************************************************
// For joint samples, input files are given as a semi-colon separated list.
// Parse this list and save it for later, and set up the types etc.
if (FitPar::Config().GetParB("EventManager")) {
NUIS_ERR(FTL, "Event Manager does not yet work with JointMeas1D Samples");
NUIS_ERR(FTL, "If you want good predictions for "
<< fName
<< " then run with it turned off! (-q EventManager=0)");
}
fSubInFiles.clear();
std::vector<std::string> entries = GeneralUtils::ParseToStr(input, ";");
if (entries.size() < 2) {
NUIS_ABORT("Joint measurement expected to recieve at least two semi-colon "
"separated input files, but recieved: \""
<< input << "\"");
}
std::vector<std::string> first_file_descriptor =
GeneralUtils::ParseToStr(entries.front(), ":");
if (first_file_descriptor.size() != 2) {
NUIS_ABORT("Found Joint measurement where the input file had no type: \""
<< input << "\", expected \"INPUTTYPE:File.root;File2.root\".");
}
std::string inpType = first_file_descriptor[0];
for (std::vector<std::string>::iterator iter = entries.begin();
iter != entries.end(); iter++) {
if (GeneralUtils::ParseToStr(*iter, ":").size() != 2) {
std::stringstream ss("");
ss << inpType << ":" << (*iter);
fSubInFiles.push_back(ss.str());
} else {
fSubInFiles.push_back(*iter);
}
}
// Set Engine and Fake Data
fRW = rw;
fFakeDataInput = fkdt;
// Set Fit Options
SetFitOptions(type);
return;
}
/*
XSec Functions
*/
//********************************************************************
double JointMeas1D::TotalIntegratedFlux(std::string intOpt, double low,
double high) {
//********************************************************************
double totalflux = 0.0;
// Destroy the job for sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
double expflux = exp->TotalIntegratedFlux(intOpt, low, high);
// Fill flux options
if (fIsRatio) {
totalflux = expflux;
break;
}
if (fIsSummed) {
totalflux += expflux;
}
}
return totalflux;
}
/*
Reconfigure Functions
*/
//********************************************************************
void JointMeas1D::Reconfigure() {
//********************************************************************
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
exp->Reconfigure();
}
ConvertEventRates();
return;
}
//********************************************************************
void JointMeas1D::ConvertEventRates() {
//********************************************************************
// Apply Event Scaling
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = static_cast<MeasurementBase *>(*expIter);
exp->ScaleEvents();
}
// Joint function called by top level class
MakePlots();
// Do Final Normalisation
ApplyNormScale(fRW->GetSampleNorm(this->fName));
}
//********************************************************************
void JointMeas1D::MakePlots() {
//********************************************************************
// Reset the 1D histograms but not the subClasses
ResetAll();
// If Summed
if (fIsSummed) {
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = static_cast<MeasurementBase *>(*expIter);
this->fMCHist->Add(exp->GetMCList().at(0));
this->fMCFine->Add(exp->GetFineList().at(0));
}
return;
}
// If Ratio
if (fIsRatio) {
int sample = 0;
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
if (sample == 0) {
this->fMCHist->Add(exp->GetMCList().at(0));
this->fMCFine->Add(exp->GetFineList().at(0));
} else if (sample == 1) {
this->fMCHist->Divide(exp->GetMCList().at(0));
this->fMCFine->Divide(exp->GetFineList().at(0));
} else {
break;
}
sample++;
}
return;
}
return;
}
/*
Access Functions
*/
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetMCList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(this->fMCHist);
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetMCList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetDataList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(this->fDataHist);
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetDataList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetFineList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(this->fMCFine);
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetFineList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetMaskList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(this->fMaskHist);
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetMaskList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetFluxList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(MeasurementBase::GetFluxHistogram());
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetFluxList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetEventRateList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(MeasurementBase::GetEventHistogram());
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetEventRateList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
std::vector<TH1 *> JointMeas1D::GetXSecList() {
//********************************************************************
// Make Default Vector
std::vector<TH1 *> tempVect;
tempVect.push_back(MeasurementBase::GetXSecHistogram());
// Return vector from all sub samples
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
std::vector<TH1 *> subTempVect = exp->GetXSecList();
for (UInt_t i = 0; i < subTempVect.size(); i++) {
tempVect.push_back(subTempVect.at(i));
}
}
return tempVect;
}
//********************************************************************
TH1D *JointMeas1D::GetCombinedFlux() {
//********************************************************************
TH1D *newflux = NULL;
int sample = 0;
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
// Get flux from experiment
std::vector<TH1 *> fluxVect = exp->GetFluxList();
// Setup newflux
if (sample == 0) {
newflux = (TH1D *)fluxVect.at(0);
newflux->Reset();
}
// Add all fluxes
for (UInt_t i = 0; i < fluxVect.size(); i++) {
newflux->Add((TH1D *)fluxVect.at(i));
sample++;
}
}
if (!newflux) {
NUIS_ABORT("No combined flux setup in JointMeas1D");
}
return newflux;
}
//********************************************************************
TH1D *JointMeas1D::GetCombinedEventRate() {
//********************************************************************
TH1D *newflux = NULL;
int sample = 0;
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
MeasurementBase *exp = *expIter;
// Get flux from experiment
std::vector<TH1 *> fluxVect = exp->GetFluxList();
// Setup newflux
if (sample == 0) {
newflux = (TH1D *)fluxVect.at(0);
newflux->Reset();
}
// Add all fluxes
for (UInt_t i = 0; i < fluxVect.size(); i++) {
newflux->Add(fluxVect.at(i));
sample++;
}
}
if (!newflux) {
NUIS_ABORT("No combined event rate setup in JointMeas1D");
}
return newflux;
}
//********************************************************************
std::vector<MeasurementBase *> JointMeas1D::GetSubSamples() {
//********************************************************************
std::vector<MeasurementBase *> exps;
for (std::vector<MeasurementBase *>::const_iterator expIter =
fSubChain.begin();
expIter != fSubChain.end(); expIter++) {
exps.push_back(*expIter);
}
return exps;
}
//// CRAP TO BE REMOVED
//********************************************************************
void JointMeas1D::SetDataValues(std::string dataFile) {
//********************************************************************
// Override this function if the input file isn't in a suitable format
NUIS_LOG(SAM, "Reading data from: " << dataFile.c_str());
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 JointMeas1D::SetDataFromDatabase(std::string inhistfile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM, "Filling histogram from " << inhistfile << "->" << histname);
fDataHist = PlotUtils::GetTH1DFromRootFile(
(GeneralUtils::GetTopLevelDir() + "/data/" + inhistfile), histname);
fDataHist->SetNameTitle((fName + "_data").c_str(), (fName + "_data").c_str());
return;
};
//********************************************************************
void JointMeas1D::SetDataFromFile(std::string inhistfile,
std::string histname) {
//********************************************************************
NUIS_LOG(SAM, "Filling histogram from " << inhistfile << "->" << histname);
fDataHist = PlotUtils::GetTH1DFromRootFile((inhistfile), histname);
fDataHist->SetNameTitle((fName + "_data").c_str(), (fName + "_data").c_str());
return;
};
//********************************************************************
void JointMeas1D::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 *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());
if (!covOption.compare("SUB"))
fFullCovarPlot = (TH2D *)tempFile->Get((covName + "cov").c_str());
else if (!covOption.compare("FULL"))
fFullCovarPlot = (TH2D *)tempFile->Get("fullcov");
else {
NUIS_ERR(WRN, "Incorrect thrown_covariance option in parameters.");
}
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 JointMeas1D::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()) {
NUIS_LOG(SAM, "Reading covariance matrix from file: " << covarFile);
} else {
NUIS_ERR(FTL, "Covariance matrix provided is incorrect: " << covarFile);
}
// 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) {
NUIS_ERR(WRN, "SetCovarMatrixFromText -> Covariance matrix only has <= 1 "
"entries on this line: "
<< row);
}
for (std::vector<double>::iterator iter = entries.begin();
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 JointMeas1D::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()) {
NUIS_LOG(SAM,
"Reading and converting correlation matrix from file: " << corrFile);
} else {
NUIS_ERR(FTL, "Correlation matrix provided is incorrect: " << corrFile);
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++) {
double val = (*iter) * this->fDataHist->GetBinError(row + 1) * 1E38 *
this->fDataHist->GetBinError(column + 1) * 1E38;
if (val == 0) {
NUIS_ERR(FTL, "Found a zero value in the covariance matrix, assuming "
"this is an error!");
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 JointMeas1D::SetCovarFromDataFile(std::string covarFile,
std::string covName, bool FullUnits) {
//********************************************************************
NUIS_LOG(SAM, "Getting covariance from " << covarFile << "->" << covName);
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;
};
// std::vector<TH1*> JointMeas1D::GetMCList(void){
// std::vector<TH1*> temp;
// return temp;
// }
// std::vector<TH1*> JointMeas1D::GetDataList(void){
// std::vector<TH1*> temp;
// return temp;
// }
// std::vector<TH1*> JointMeas1D::GetMaskList(void){
// std::vector<TH1*> temp;
// return temp;
// }
// std::vector<TH1*> JointMeas1D::GetFineList(void){
// std::vector<TH1*> temp;
// return temp;
// }
diff --git a/src/FitBase/JointMeas1D.h b/src/FitBase/JointMeas1D.h
index 4ba5fa4..a175832 100644
--- a/src/FitBase/JointMeas1D.h
+++ b/src/FitBase/JointMeas1D.h
@@ -1,650 +1,651 @@
// Copyright 2016-2021 L. Pickering, P Stowell, R. Terri, C. Wilkinson, C. Wret
/*******************************************************************************
* This file 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/>.
*******************************************************************************/
#ifndef JOINTMEASUREMENT_1D_H_SEEN
#define JOINTMEASUREMENT_1D_H_SEEN
/*!
* \addtogroup FitBase
* @{
*/
#include <deque>
#include <iomanip>
#include <iostream>
#include <list>
#include <math.h>
#include <numeric>
#include <sstream>
#include <stdlib.h>
#include <string>
// ROOT includes
#include "Measurement1D.h"
#include <TArrayF.h>
#include <TCanvas.h>
#include <TCut.h>
#include <TDecompChol.h>
#include <TDecompSVD.h>
#include <TGraph.h>
#include <TGraphErrors.h>
#include <TH1D.h>
#include <TH2D.h>
#include <TMatrixDSym.h>
#include <TROOT.h>
#include <TSystem.h>
// External data fit includes
#include "FitEvent.h"
#include "FitUtils.h"
#include "MeasurementBase.h"
#include "PlotUtils.h"
#include "StatUtils.h"
//********************************************************************
/// 1D Measurement base class. Histogram handling is done in this base layer.
class JointMeas1D : public MeasurementBase {
//********************************************************************
public:
/*
Constructor/Deconstuctor
*/
JointMeas1D(void);
virtual ~JointMeas1D(void);
/*
Setup Functions
*/
SampleSettings LoadSampleSettings(nuiskey samplekey);
/// \brief Setup all configs once initialised
///
/// Should be called after all configs have been setup inside fSettings
/// container. Handles the processing of inputs and setting up of types.
/// Replaces the old 'SetupMeasurement' function.
void FinaliseSampleSettings();
/// \brief Read 1D data inputs from a text file.
///
/// Inputfile should have the format: \n
/// low_binedge_1 bin_content_1 bin_error_1 \n
/// low_binedge_2 bin_content_2 bin_error_2 \n
/// .... .... .... \n
/// high_bin_edge_N 0.0 0.0
virtual void SetDataFromTextFile(std::string datafile);
/// \brief Read 1D data inputs from a root file.
///
/// inhistfile specifies the path to the root file
/// histname specifies the name of the histogram.
///
/// If no histogram name is given the inhistfile value
/// is automatically parsed with ';' so that: \n
/// 'myhistfile.root;myhistname' \n
/// will also work.
virtual void SetDataFromRootFile(std::string inhistfile,
std::string histname = "");
/// \brief Set data bin errors to sqrt(entries)
///
/// \warning REQUIRES DATA HISTOGRAM TO BE SET FIRST
///
/// Sets the data errors as the sqrt of the bin contents
/// Should be use for counting experiments
virtual void SetPoissonErrors();
/// \brief Make diagonal covariance from data
///
/// \warning If no histogram passed, data must be setup first!
/// Setup the covariance inputs by taking the data histogram
/// errors and setting up a diagonal covariance matrix.
///
/// If no data is supplied, fDataHist is used if already set.
virtual void SetCovarFromDiagonal(TH1D *data = NULL);
/// \brief Read the data covariance from a text file.
///
/// Inputfile should have the format: \n
/// covariance_11 covariance_12 covariance_13 ... \n
/// covariance_21 covariance_22 covariance_23 ... \n
/// ... ... ... ... \n
///
/// If no dimensions are given, it is assumed from the number
/// entries in the first line of covfile.
virtual void SetCovarFromTextFile(std::string covfile, int dim = -1);
virtual void SetCovarFromMultipleTextFiles(std::string covfiles,
int dim = -1);
/// \brief Read the data covariance from a ROOT file.
///
/// - covfile specifies the full path to the file
/// - histname specifies the name of the covariance object. Both TMatrixDSym
/// and TH2D are supported.
///
/// If no histogram name is given the inhistfile value
/// is automatically parsed with ; so that: \n
/// mycovfile.root;myhistname \n
/// will also work.
virtual void SetCovarFromRootFile(std::string covfile, std::string histname);
/// \brief Read the inverted data covariance from a text file.
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromTextFile.
///
/// If no dimensions are given, it is assumed from the number
/// entries in the first line of covfile.
virtual void SetCovarInvertFromTextFile(std::string covfile, int dim = -1);
/// \brief Read the inverted data covariance from a ROOT file.
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromRootFile.
///
/// If no histogram name is given the inhistfile value
/// is automatically parsed with ; so that: \n
/// mycovfile.root;myhistname \n
/// will also work.
virtual void SetCovarInvertFromRootFile(std::string covfile,
std::string histname);
/// \brief Read the data correlations from a text file.
///
/// \warning REQUIRES DATA HISTOGRAM TO BE SET FIRST
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromTextFile.
///
/// If no dimensions are given, it is assumed from the number
/// entries in the first line of covfile.
virtual void SetCorrelationFromTextFile(std::string covfile, int dim = -1);
/// \brief Read the data correlations from multiple text files.
///
/// \warning REQUIRES DATA HISTOGRAM TO BE SET FIRST
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromTextFile.
///
/// If no dimensions are given, it is assumed from the number
/// entries in the first line of first covfile.
virtual void SetCorrelationFromMultipleTextFiles(std::string corrfiles,
int dim = -1);
/// \brief Read the data correlations from a ROOT file.
///
/// \warning REQUIRES DATA TO BE SET FIRST
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromRootFile.
///
/// If no histogram name is given the inhistfile value
/// is automatically parsed with ; so that: \n
/// mycovfile.root;myhistname \n
/// will also work.
virtual void SetCorrelationFromRootFile(std::string covfile,
std::string histname);
/// \brief Try to extract a shape-only matrix from the existing covariance
virtual void SetShapeCovar();
/// \brief Read the cholesky decomposed covariance from a text file and turn
/// it into a covariance
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromTextFile.
///
/// If no dimensions are given, it is assumed from the number
/// entries in the first line of covfile.
virtual void SetCholDecompFromTextFile(std::string covfile, int dim = -1);
/// \brief Read the cholesky decomposed covariance from a ROOT file and turn
/// it into a covariance
///
/// Inputfile should have similar format to that shown
/// in SetCovarFromRootFile.
///
/// If no histogram name is given the inhistfile value
/// is automatically parsed with ; so that: \n
/// mycovfile.root;myhistname \n
/// will also work.
virtual void SetCholDecompFromRootFile(std::string covfile,
std::string histname);
/// \brief Scale the data by some scale factor
virtual void ScaleData(double scale);
/// \brief Scale the covariaince and its invert/decomp by some scale factor.
virtual void ScaleCovar(double scale);
/// \brief Setup a bin masking histogram and apply masking to data
///
/// \warning REQUIRES DATA HISTOGRAM TO BE SET FIRST
///
/// Reads in a list of bins in a text file to be masked. Format is: \n
/// bin_index_1 1 \n
/// bin_index_2 1 \n
/// bin_index_3 1 \n
///
/// If 0 is given then a bin entry will NOT be masked. So for example: \n\n
/// 1 1 \n
/// 2 1 \n
/// 3 0 \n
/// 4 1 \n\n
/// Will mask only the 1st, 2nd, and 4th bins.
///
/// Masking can be turned on by specifiying the MASK option when creating a
/// sample. When this is passed NUISANCE will look in the following locations
/// for the mask file:
/// - FitPar::Config().GetParS(fName + ".mask")
/// - "data/masks/" + fName + ".mask";
virtual void SetBinMask(std::string maskfile);
/// \brief Final constructor setup
/// \warning Should be called right at the end of the constructor.
///
/// Contains a series of checks to ensure the data and inputs have been setup.
/// Also creates the MC histograms needed for fitting.
virtual void FinaliseMeasurement();
/// \brief Set the current fit options from a string.
///
/// This is called twice for each sample, once to set the default
/// and once to set the current setting (if anything other than default given)
///
/// For this to work properly it requires the default and allowed types to be
/// set correctly. These should be specified as a string listing options.
///
/// To split up options so that NUISANCE can automatically detect ones that
/// are conflicting. Any options separated with the '/' symbol are non
/// conflicting and can be given together, whereas any separated with the ','
/// symbol cannot be specified by the end user at the same time.
///
/// Default Type Examples:
/// - DIAG/FIX = Default option will be a diagonal covariance, with FIXED
/// norm.
/// - MASK/SHAPE = Default option will be a masked hist, with SHAPE always on.
///
/// Allowed Type examples:
/// - 'FULL/DIAG/NORM/MASK' = Any of these options can be specified.
/// - 'FULL,FREE,SHAPE/MASK/NORM' = User can give either FULL, FREE, or SHAPE
/// as on option. MASK and NORM can also be included as options.
virtual void SetFitOptions(std::string opt);
/*
Smearing
*/
/// \brief Read in smearing matrix from file
///
/// Set the smearing matrix from a text file given the size of the matrix
virtual void SetSmearingMatrix(std::string smearfile, int truedim,
int recodim);
/// \brief Apply smearing to MC true to get MC reco
///
/// Apply smearing matrix to fMCHist using fSmearingMatrix
virtual void ApplySmearingMatrix(void);
/*
Reconfigure Functions
*/
/// \brief Create a Measurement1D box
///
/// Creates a new 1D variable box containing just fXVar.
///
/// This box is the bare minimum required by the JointFCN when
/// running fast reconfigures during a routine.
/// If for some reason a sample needs extra variables to be saved then
/// it should override this function creating its own MeasurementVariableBox
/// that contains the extra variables.
virtual MeasurementVariableBox *CreateBox() {
return new MeasurementVariableBox1D();
};
/// \brief Reset all MC histograms
///
/// Resets all standard histograms and those registered to auto
/// process to zero.
///
/// If extra histograms are not included in auto processing, then they must be
/// reset by overriding this function and doing it manually if required.
virtual void ResetAll(void);
/// \brief Fill MC Histograms from XVar
///
/// Fill standard histograms using fXVar, Weight read from the variable box.
///
/// WARNING : Any extra MC histograms need to be filled by overriding this
/// function, even if they have been set to auto process.
virtual void FillHistograms(void);
// \brief Convert event rates to final histogram
///
/// Apply standard scaling procedure to standard mc histograms to convert from
/// raw events to xsec prediction.
///
/// If any distributions have been set to auto process
/// that is done during this function call, and a differential xsec is
/// assumed. If that is not the case this function must be overriden.
virtual void ScaleEvents(void);
/// \brief Scale MC by a factor=1/norm
///
/// Apply a simple normalisation scaling if the option FREE or a
/// norm_parameter has been specified in the NUISANCE routine.
virtual void ApplyNormScale(double norm);
/*
Statistical Functions
*/
/// \brief Get Number of degrees of freedom
///
/// Returns the number bins inside the data histogram accounting for
/// any bin masking applied.
virtual int GetNDOF(void);
/// \brief Return Data/MC Likelihood at current state
///
/// Returns the likelihood of the data given the current MC prediction.
/// Diferent likelihoods definitions are used depending on the FitOptions.
virtual double GetLikelihood(void);
/*
Fake Data
*/
/// \brief Set the fake data values from either a file, or MC
///
/// - Setting from a file "path": \n
/// When reading from a file the full path must be given to a standard
/// nuisance output. The standard MC histogram should have a name that matches
/// this sample for it to be read in.
/// \n\n
/// - Setting from "MC": \n
/// If the MC option is given the current MC prediction is used as fake data.
virtual void SetFakeDataValues(std::string fakeOption);
/// \brief Reset fake data back to starting fake data
///
/// Reset the fake data back to original fake data (Reset back to before
/// ThrowCovariance was first called)
virtual void ResetFakeData(void);
/// \brief Reset fake data back to original data
///
/// Reset the data histogram back to the true original dataset for this sample
/// before any fake data was defined.
virtual void ResetData(void);
/// \brief Generate fake data by throwing the covariance.
///
/// Can be used on fake MC data or just the original dataset.
/// Call ResetFakeData or ResetData to return to values before the throw.
virtual void ThrowCovariance(void);
/// \brief Throw the data by its assigned errors and assign this to MC
///
/// Used when creating data toys by assign the MC to this thrown data
/// so that the likelihood is calculated between data and thrown data
virtual void ThrowDataToy(void);
/*
Access Functions
*/
/// \brief Returns nicely formatted MC Histogram
///
/// Format options can also be given in the samplesettings:
/// - linecolor
/// - linestyle
/// - linewidth
/// - fillcolor
/// - fillstyle
///
/// So to have a sample line colored differently in the xml cardfile put: \n
/// <sample name="MiniBooNE_CCQE_XSec_1DQ2_nu" input="NEUT:input.root"
/// linecolor="2" linestyle="7" linewidth="2" />
virtual TH1D *GetMCHistogram(void);
/// \brief Returns nicely formatted data Histogram
///
/// Format options can also be given in the samplesettings:
/// - datacolor
/// - datastyle
/// - datawidth
///
/// So to have a sample data colored differently in the xml cardfile put: \n
/// <sample name="MiniBooNE_CCQE_XSec_1DQ2_nu" input="NEUT:input.root"
/// datacolor="2" datastyle="7" datawidth="2" />
virtual TH1D *GetDataHistogram(void);
/// \brief Returns a list of all MC histograms.
///
/// Override this if you have extra histograms that need to be
/// accessed outside of the Measurement1D class.
virtual std::vector<TH1 *> GetMCList(void);
/// \brief Returns a list of all Data histograms.
///
/// Override this if you have extra histograms that need to be
/// accessed outside of the Measurement1D class.
virtual std::vector<TH1 *> GetDataList(void);
/// \brief Returns a list of all Mask histograms.
///
/// Override this if you have extra histograms that need to be
/// accessed outside of the Measurement1D class.
virtual std::vector<TH1 *> GetMaskList(void);
/// \brief Returns a list of all Fine histograms.
///
/// Override this if you have extra histograms that need to be
/// accessed outside of the Measurement1D class.
virtual std::vector<TH1 *> GetFineList(void);
/*
Write Functions
*/
/// \brief Save the current state to the current TFile directory \n
///
/// Data/MC are both saved by default.
/// A range of other histograms can be saved by setting the
/// config option 'drawopts'.
///
/// Possible options: \n
/// - FINE = Write Fine Histogram \n
/// - WEIGHTS = Write Weighted MC Histogram (before scaling) \n
/// - FLUX = Write Flux Histogram from MC Input \n
/// - EVT = Write Event Histogram from MC Input \n
/// - XSEC = Write XSec Histogram from MC Input \n
/// - MASK = Write Mask Histogram \n
/// - COV = Write Covariance Histogram \n
/// - INVCOV = Write Inverted Covariance Histogram \n
/// - DECMOP = Write Decomp. Covariance Histogram \n
/// - RESIDUAL= Write Resudial Histograms \n
/// - RATIO = Write Data/MC Ratio Histograms \n
/// - SHAPE = Write MC Shape Histograms norm. to Data \n
/// - CANVMC = Build MC Canvas Showing Data, MC, Shape \n
/// - MODES = Write PDG Stack \n
/// - CANVPDG = Build MC Canvas Showing Data, PDGStack \n
///
/// So to save a range of these in parameters/config.xml set: \n
/// <config drawopts='FINE/COV/SHAPE/RATIO' />
virtual void Write(std::string drawOpt);
virtual void WriteRatioPlot();
virtual void WriteShapePlot();
virtual void WriteShapeRatioPlot();
double TotalIntegratedFlux(std::string intOpt, double low, double high);
//*
// OLD DEFUNCTIONS
//
/// OLD FUNCTION
virtual void SetupMeasurement(std::string input, std::string type,
FitWeight *rw, std::string fkdt);
/// OLD FUNCTION
virtual void SetupDefaultHist(void);
/// OLD FUNCTION
virtual void SetDataValues(std::string dataFile);
/// OLD FUNCTION
virtual void SetDataFromFile(std::string inhistfile, std::string histname);
/// OLD FUNCTION
virtual void SetDataFromDatabase(std::string inhistfile,
std::string histname);
/// OLD FUNCTION
virtual void SetCovarMatrix(std::string covarFile);
/// OLD FUNCTION
virtual void SetCovarMatrixFromText(std::string covarFile, int dim,
double scale = 1.0);
/// OLD FUNCTION
virtual void SetCovarMatrixFromCorrText(std::string covarFile, int dim);
/// OLD FUNCTION
virtual void SetCovarFromDataFile(std::string covarFile, std::string covName,
bool FullUnits = false);
////// JOINT MEAS1D Functions //////
/*
Reconfigure Functions
*/
/// Call reconfigure on every sub sample
virtual void Reconfigure();
/// Stitch the sub sample plots together to make a final fMCHist after
/// reconfigure has been called
virtual void MakePlots();
virtual std::vector<MeasurementBase *> GetSubSamples();
virtual void ConvertEventRates();
/*
Access Functions
*/
virtual std::vector<TH1 *> GetFluxList();
virtual std::vector<TH1 *> GetEventRateList();
virtual std::vector<TH1 *> GetXSecList();
//! Return a flux integrated across all sub samples
virtual TH1D *GetCombinedFlux();
//! Return an event rate integrated across all sub samples
virtual TH1D *GetCombinedEventRate();
virtual TH1D *GetEventHistogram() { return GetCombinedEventRate(); };
virtual TH1D *GetXSecHistogram() {
NUIS_ERR(WRN,
"XSec histogram not properly implemented for joint measurements.");
return MeasurementBase::GetXSecHistogram();
};
virtual TH1D *GetFluxHistogram() { return GetCombinedFlux(); };
protected:
// Data
TH1D *fDataHist; ///< default data histogram
TH1D *fDataOrig; ///< histogram to store original data before throws.
TH1D *fDataTrue; ///< histogram to store true dataset
std::string fPlotTitles; ///< Plot title x and y for the histograms
// MC
TH1D *fMCHist; ///< default MC Histogram used in the chi2 fits
TH1D *fMCFine; ///< finely binned MC histogram
TH1D *fMCStat; ///< histogram with unweighted events to properly calculate
TH1D *fMCWeighted; ///< Weighted histogram before xsec scaling
TH1I *fMaskHist; ///< Mask histogram for neglecting specific bins
TMatrixD *fSmearMatrix; ///< Smearing matrix (note, this is not symmetric)
TrueModeStack *fMCHist_Modes; ///< Optional True Mode Stack
// Statistical
TMatrixDSym *covar; ///< Inverted Covariance
TMatrixDSym *fFullCovar; ///< Full Covariance
TMatrixDSym *fDecomp; ///< Decomposed Covariance
TMatrixDSym *fCorrel; ///< Correlation Matrix
TMatrixDSym *fShapeCovar; ///< Shape-only covariance
TMatrixDSym *fCovar; ///< New FullCovar
TMatrixDSym *fInvert; ///< New covar
double fNormError; ///< Sample norm error
// Fake Data
bool fIsFakeData; ///< Flag: is the current data fake from MC
std::string fFakeDataInput; ///< Input fake data file path
TFile *fFakeDataFile; ///< Input fake data file
// Fit specific flags
std::string fFitType; ///< Current fit type
std::string fAllowedTypes; ///< Fit Types Possible
std::string fDefaultTypes; ///< Starting Default Fit Types
bool fIsShape; ///< Flag : Perform Shape-only fit
bool fIsFree; ///< Flag : Perform normalisation free fit
bool fIsDiag; ///< Flag : only include uncorrelated diagonal errors
bool fIsMask; ///< Flag : Apply bin masking
bool fIsRawEvents; ///< Flag : Are bin contents just event rates
bool fIsEnu1D; ///< Flag : Perform Flux Unfolded Scaling
bool fIsChi2SVD; ///< Flag : Use alternative Chi2 SVD Method (Do not use)
bool fAddNormPen; ///< Flag : Add a normalisation penalty term to the chi2.
bool fIsFix; ///< Flag : keeping norm fixed
bool fIsFull; ///< Flag : using full covariaince
bool fIsDifXSec; ///< Flag : creating a dif xsec
bool fIsChi2; ///< Flag : using Chi2 over LL methods
bool fIsSmeared; ///< Flag : Apply smearing?
+ bool fSaveFine; ///< Flag : Save the MC FINE histogram or not
/// OLD STUFF TO REMOVE
TH1D *fMCHist_PDG[61]; ///< REMOVE OLD MC PDG Plot
// Arrays for data entries
Double_t *fXBins; ///< REMOVE xBin edges
Double_t *fDataValues; ///< REMOVE data bin contents
Double_t *fDataErrors; ///< REMOVE data bin errors
Int_t fNDataPointsX; ///< REMOVE number of data points
//// JOINT MEAS1D OBJECTS ////
std::vector<MeasurementBase *> fSubChain; //!< Vector of experimental classes
//! that are the sub measurements
std::vector<std::string>
fSubInFiles; //!< vector of input files for each of the sub measurements.
bool fIsRatio; //!< Flag: is this sample a hist1/hist2 ratio sample
bool fIsSummed; //!< Flag: is this sample a combination hist1 + hist2
bool fSaveSubMeas; //!< Flag: Save each of the histograms from the sub
//! samples as well as this joint samples plots
double fLikelihood;
};
/*! @} */
#endif

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