diff --git a/cmake/GENIESetup.cmake b/cmake/GENIESetup.cmake
index 11c64b3..0dfd88e 100644
--- a/cmake/GENIESetup.cmake
+++ b/cmake/GENIESetup.cmake
@@ -1,168 +1,166 @@
# Copyright 2016 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/>.
################################################################################
# TODO
# check system for libxml2
# check whether we need the includes
# check if we can use a subset of the GENIE libraries
################################################################################
# Check Dependencies
################################################################################
################################# GENIE ######################################
if(GENIE STREQUAL "")
cmessage(FATAL_ERROR "Variable GENIE is not defined. "
"The location of a pre-built GENIE install must be defined either as"
" $ cmake -DGENIE=/path/to/GENIE or as and environment vairable"
" $ export GENIE=/path/to/GENIE")
endif()
if (BUILD_GEVGEN)
cmessage(STATUS "Building custom gevgen")
LIST(APPEND EXTRA_CXX_FLAGS -D__GEVGEN_ENABLED__)
endif()
# Extract GENIE VERSION
if (GENIE_VERSION STREQUAL "AUTO")
execute_process (COMMAND ${CMAKE_SOURCE_DIR}/cmake/getgenieversion.sh ${GENIE}
OUTPUT_VARIABLE GENIE_VERSION OUTPUT_STRIP_TRAILING_WHITESPACE)
endif()
execute_process (COMMAND genie-config
--libs OUTPUT_VARIABLE GENIE_LD_FLAGS_STR OUTPUT_STRIP_TRAILING_WHITESPACE)
execute_process (COMMAND genie-config
--topsrcdir OUTPUT_VARIABLE GENIE_INCLUDES_DIR OUTPUT_STRIP_TRAILING_WHITESPACE)
string(REGEX MATCH "-L\([^ ]+\) \(.*\)$" PARSE_GENIE_LIBS_MATCH ${GENIE_LD_FLAGS_STR})
cmessage(DEBUG "genie-config --libs: ${GENIE_LD_FLAGS_STR}")
if(NOT PARSE_GENIE_LIBS_MATCH)
cmessage(FATAL_ERROR "Expected to be able to parse the result of genie-config --libs to a lib directory and a list of libraries to include, but got: \"${GENIE_LD_FLAGS_STR}\"")
endif()
set(GENIE_LIB_DIR ${CMAKE_MATCH_1})
set(GENIE_LIBS_RAW ${CMAKE_MATCH_2})
string(REPLACE "-l" "" GENIE_LIBS_STRIPED "${GENIE_LIBS_RAW}")
cmessage(STATUS "GENIE version : ${GENIE_VERSION}")
cmessage(STATUS "GENIE libdir : ${GENIE_LIB_DIR}")
cmessage(STATUS "GENIE libs : ${GENIE_LIBS_STRIPED}")
string(REGEX MATCH "ReinSeghal" WASMATCHED ${GENIE_LIBS_STRIPED})
if(WASMATCHED AND GENIE_VERSION STREQUAL "210")
set(GENIE_SEHGAL ${GENIE_LIBS_STRIPED})
STRING(REPLACE "ReinSeghal" "ReinSehgal" GENIE_LIBS_STRIPED ${GENIE_SEHGAL})
cmessage(DEBUG "Fixed inconsistency in library naming: ${GENIE_LIBS_STRIPED}")
endif()
string(REGEX MATCH "ReWeight" WASMATCHED ${GENIE_LIBS_STRIPED})
if(NOT WASMATCHED)
set(GENIE_LIBS_STRIPED "GReWeight ${GENIE_LIBS_STRIPED}")
cmessage(DEBUG "Force added ReWeight library: ${GENIE_LIBS_STRIPED}")
endif()
string(REPLACE " " ";" GENIE_LIBS_LIST "-Wl,--start-group ${GENIE_LIBS_STRIPED} -Wl,--end-group")
cmessage(DEBUG "genie-config --libs -- MATCH1: ${CMAKE_MATCH_1}")
cmessage(DEBUG "genie-config --libs -- MATCH2: ${CMAKE_MATCH_2}")
cmessage(DEBUG "genie-config --libs -- libs stripped: ${GENIE_LIBS_STRIPED}")
cmessage(DEBUG "genie-config --libs -- libs list: ${GENIE_LIBS_LIST}")
################################ LHAPDF ######################################
if(LHAPDF_LIB STREQUAL "")
cmessage(FATAL_ERROR "Variable LHAPDF_LIB is not defined. The location of a pre-built lhapdf install must be defined either as $ cmake -DLHAPDF_LIB=/path/to/LHAPDF_libraries or as and environment vairable $ export LHAPDF_LIB=/path/to/LHAPDF_libraries")
endif()
if(LHAPDF_INC STREQUAL "")
cmessage(FATAL_ERROR "Variable LHAPDF_INC is not defined. The location of a pre-built lhapdf install must be defined either as $ cmake -DLHAPDF_INC=/path/to/LHAPDF_includes or as and environment vairable $ export LHAPDF_INC=/path/to/LHAPDF_includes")
endif()
if(LHAPATH STREQUAL "")
cmessage(FATAL_ERROR "Variable LHAPATH is not defined. The location of a the LHAPATH directory must be defined either as $ cmake -DLHAPATH=/path/to/LHAPATH or as and environment variable $ export LHAPATH=/path/to/LHAPATH")
endif()
################################ LIBXML ######################################
if(LIBXML2_LIB STREQUAL "")
cmessage(FATAL_ERROR "Variable LIBXML2_LIB is not defined. The location of a pre-built libxml2 install must be defined either as $ cmake -DLIBXML2_LIB=/path/to/LIBXML2_libraries or as and environment vairable $ export LIBXML2_LIB=/path/to/LIBXML2_libraries")
endif()
if(LIBXML2_INC STREQUAL "")
cmessage(FATAL_ERROR "Variable LIBXML2_INC is not defined. The location of a pre-built libxml2 install must be defined either as $ cmake -DLIBXML2_INC=/path/to/LIBXML2_includes or as and environment vairable $ export LIBXML2_INC=/path/to/LIBXML2_includes")
endif()
############################### log4cpp ######################################
if(LOG4CPP_LIB STREQUAL "")
find_program(LOG4CPPCFG log4cpp-config)
if(NOT LOG4CPPCFG STREQUAL "LOG4CPPCFG-NOTFOUND")
execute_process (COMMAND ${LOG4CPPCFG}
--pkglibdir OUTPUT_VARIABLE LOG4CPP_LIB OUTPUT_STRIP_TRAILING_WHITESPACE)
else()
message(FATAL_ERROR "Variable LOG4CPP_LIB is not defined. The location of a pre-built log4cpp install must be defined either as $ cmake -DLOG4CPP_LIB=/path/to/LOG4CPP_libraries or as and environment vairable $ export LOG4CPP_LIB=/path/to/LOG4CPP_libraries")
endif()
endif()
if(LOG4CPP_INC STREQUAL "")
find_program(LOG4CPPCFG log4cpp-config)
if(NOT LOG4CPPCFG STREQUAL "LOG4CPPCFG-NOTFOUND")
execute_process (COMMAND ${LOG4CPPCFG}
--pkgincludedir OUTPUT_VARIABLE LOG4CPP_INC OUTPUT_STRIP_TRAILING_WHITESPACE)
else()
message(FATAL_ERROR "Variable LOG4CPP_INC is not defined. The location of a pre-built log4cpp install must be defined either as $ cmake -DGENIE_LOG4CPP_INC=/path/to/LOG4CPP_includes or as and environment vairable $ export LOG4CPP_INC=/path/to/LOG4CPP_includes")
endif()
endif()
################################################################################
LIST(APPEND EXTRA_CXX_FLAGS -D__GENIE_ENABLED__ -D__GENIE_VERSION__=${GENIE_VERSION})
LIST(APPEND RWENGINE_INCLUDE_DIRECTORIES
${GENIE_INCLUDES_DIR}
${GENIE_INCLUDES_DIR}/GHEP
${GENIE_INCLUDES_DIR}/Ntuple
${GENIE_INCLUDES_DIR}/ReWeight
${GENIE_INCLUDES_DIR}/Apps
${GENIE_INCLUDES_DIR}/FluxDrivers
${GENIE_INCLUDES_DIR}/EVGDrivers
${LHAPDF_INC}
${LIBXML2_INC}
${LOG4CPP_INC})
SAYVARS()
LIST(APPEND EXTRA_LINK_DIRS
${GENIE_LIB_DIR}
${LHAPDF_LIB}
${LIBXML2_LIB}
${LOG4CPP_LIB})
-LIST(APPEND EXTRA_LIBS -Wl,--start-group)
LIST(APPEND EXTRA_LIBS ${GENIE_LIBS_LIST})
-LIST(APPEND EXTRA_LIBS -Wl,--end-group)
LIST(APPEND EXTRA_LIBS LHAPDF xml2 log4cpp)
if(USE_PYTHIA8)
set(NEED_PYTHIA8 TRUE)
set(NEED_ROOTPYTHIA8 TRUE)
else()
set(NEED_PYTHIA6 TRUE)
set(NEED_ROOTPYTHIA6 TRUE)
endif()
set(NEED_ROOTEVEGEN TRUE)
SET(USE_GENIE TRUE CACHE BOOL "Whether to enable GENIE (reweight) support. Requires external libraries. <FALSE>" FORCE)
diff --git a/src/FitBase/Measurement1D.cxx b/src/FitBase/Measurement1D.cxx
index 3306167..5140ffd 100644
--- a/src/FitBase/Measurement1D.cxx
+++ b/src/FitBase/Measurement1D.cxx
@@ -1,1905 +1,1904 @@
// 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();
}
// 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) {
//********************************************************************
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;
LOG(SAM) << "Overriding this and setting fIsRawEvents == true!"
<< 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;
}
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);
}
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());
// 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, 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) {
//********************************************************************
LOG(SAM) << "Filling histogram from " << inhistfile << "->" << histname
<< std::endl;
fDataHist = PlotUtils::GetTH1DFromRootFile(
(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) {
//********************************************************************
LOG(SAM) << "Filling histogram from " << inhistfile << "->" << histname
<< 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;
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;
else
ERR(FTL) << "Covariance matrix provided is incorrect: " << covarFile
<< 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;
}
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 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;
else {
ERR(FTL) << "Correlation matrix provided is incorrect: " << corrFile
<< 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++) {
double val = (*iter) * this->fDataHist->GetBinError(row + 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;
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;
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;
// };
diff --git a/src/FitBase/SampleSettings.h b/src/FitBase/SampleSettings.h
index 358a584..086187d 100644
--- a/src/FitBase/SampleSettings.h
+++ b/src/FitBase/SampleSettings.h
@@ -1,77 +1,75 @@
#ifndef SAMPLESETTINGS_H
#define SAMPLESETTINGS_H
#include "NuisConfig.h"
#include "NuisKey.h"
#include "TH1D.h"
#include "BeamUtils.h"
#include "TPaveText.h"
#include "TCanvas.h"
class SampleSettings {
public:
SampleSettings();
SampleSettings(nuiskey key);
inline std::string Name(){return GetName();};
std::string GetName();
void SetS(std::string name, std::string val);
void SetXTitle(std::string name);
void SetYTitle(std::string name);
void SetZTitle(std::string name);
void SetNormError(double norm);
double GetNormError();
void SetAllowedTypes(std::string allowed, std::string defaulttype="FIX");
void SetEnuRangeFromFlux(TH1D* fluxhist);
void SetEnuRange(double min, double max);
std::string Title();
void DefineAllowedTargets(std::string targ);
void FoundFill(std::string name, std::string substr, bool& cont, bool def);
// void FoundFill(std::string name, std::string substr, double& val, double )
bool Found(std::string name, std::string substr);
void SetTitle(std::string val);
void SetDataInput(std::string val);
void SetErrorInput(std::string val);
std::string GetErrorInput();
std::string GetMapInput();
void SetMapInput(std::string val);
void SetCovarInput(std::string val);
void SetShapeCovarInput(std::string val);
void SetDefault(std::string name, std::string val);
void SetDefault(std::string name, double val);
void SetHasExtraHistograms(bool opt = true);
void DefineAllowedSpecies(std::string species);
void SetSuggestedFlux(std::string str);
void SetDescription(std::string str);
void Write(std::string name="");
std::string GetFullTitles();
bool Has(std::string name){return fKeyValues.Has(name);};
std::string GetDataInput();
std::string PlotTitles();
std::string GetS(std::string name);
int GetI(std::string name);
double GetD(std::string name);
std::string GetCovarInput();
void SetOnlyMC(bool state=true);
bool GetB(std::string name);
void Set(std::string name, int i);
void Set(std::string name, std::string s);
void Set(std::string name, double d);
-
-
std::vector<int> fAllowedTargets;
std::vector<int> fAllowedSpecies;
nuiskey fKeyValues;
bool fHasExtraHistograms;
};
#endif
diff --git a/src/Statistical/StatUtils.cxx b/src/Statistical/StatUtils.cxx
index e052685..b2745f3 100644
--- a/src/Statistical/StatUtils.cxx
+++ b/src/Statistical/StatUtils.cxx
@@ -1,1304 +1,1328 @@
// Copyright 2016 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/>.
*******************************************************************************/
#include "StatUtils.h"
#include "GeneralUtils.h"
#include "NuisConfig.h"
#include "TH1D.h"
//*******************************************************************
Double_t StatUtils::GetChi2FromDiag(TH1D* data, TH1D* mc, TH1I* mask) {
//*******************************************************************
Double_t Chi2 = 0.0;
TH1D* calc_data = (TH1D*)data->Clone();
TH1D* calc_mc = (TH1D*)mc->Clone();
// Add MC Error to data if required
if (FitPar::Config().GetParB("addmcerror")) {
for (int i = 0; i < calc_data->GetNbinsX(); i++) {
double dterr = calc_data->GetBinError(i + 1);
double mcerr = calc_mc->GetBinError(i + 1);
if (dterr > 0.0) {
calc_data->SetBinError(i + 1, sqrt(dterr * dterr + mcerr * mcerr));
}
}
}
// Apply masking if required
if (mask) {
calc_data = ApplyHistogramMasking(data, mask);
calc_mc = ApplyHistogramMasking(mc, mask);
}
// Iterate over bins in X
for (int i = 0; i < calc_data->GetNbinsX(); i++) {
// Ignore bins with zero data or zero bin error
if (calc_data->GetBinError(i + 1) <= 0.0 ||
calc_data->GetBinContent(i + 1) == 0.0)
continue;
// Take mc data difference
double diff =
calc_data->GetBinContent(i + 1) - calc_mc->GetBinContent(i + 1);
double err = calc_data->GetBinError(i + 1);
Chi2 += (diff * diff) / (err * err);
}
// cleanup
delete calc_data;
delete calc_mc;
return Chi2;
};
//*******************************************************************
Double_t StatUtils::GetChi2FromDiag(TH2D* data, TH2D* mc, TH2I* map,
TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate 1D chi2 from 1D Plots
Double_t Chi2 = StatUtils::GetChi2FromDiag(data_1D, mc_1D, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return Chi2;
};
//*******************************************************************
Double_t StatUtils::GetChi2FromCov(TH1D* data, TH1D* mc, TMatrixDSym* invcov,
TH1I* mask, double data_scale,
double covar_scale) {
//*******************************************************************
Double_t Chi2 = 0.0;
TMatrixDSym* calc_cov = (TMatrixDSym*)invcov->Clone();
TH1D* calc_data = (TH1D*)data->Clone();
TH1D* calc_mc = (TH1D*)mc->Clone();
// If a mask if applied we need to apply it before the matrix is inverted
if (mask) {
calc_cov = ApplyInvertedMatrixMasking(invcov, mask);
calc_data = ApplyHistogramMasking(data, mask);
calc_mc = ApplyHistogramMasking(mc, mask);
}
// Add MC Error to data if required
if (FitPar::Config().GetParB("statutils.addmcerror")) {
// Make temp cov
TMatrixDSym* newcov = StatUtils::GetInvert(calc_cov);
// Add MC err to diag
for (int i = 0; i < calc_data->GetNbinsX(); i++) {
double mcerr = calc_mc->GetBinError(i + 1) * sqrt(covar_scale);
double oldval = (*newcov)(i, i);
std::cout << "Adding cov stat " << mcerr * mcerr << " to "
<< (*newcov)(i, i) << std::endl;
(*newcov)(i, i) = oldval + mcerr * mcerr;
}
// Reset the calc_cov to new invert
delete calc_cov;
calc_cov = GetInvert(newcov);
// Delete the tempcov
delete newcov;
}
calc_data->Scale(data_scale);
calc_mc->Scale(data_scale);
(*calc_cov) *= covar_scale;
// iterate over bins in X (i,j)
QLOG(DEB, "START Chi2 Calculation=================");
for (int i = 0; i < calc_data->GetNbinsX(); i++) {
QLOG(DEB,
"[CHI2] i = " << i << " ["
<< calc_data->GetXaxis()->GetBinLowEdge(i + 1) << " -- "
<< calc_data->GetXaxis()->GetBinUpEdge(i + 1) << "].");
for (int j = 0; j < calc_data->GetNbinsX(); j++) {
QLOG(DEB, "[CHI2]\t j = "
<< i << " [" << calc_data->GetXaxis()->GetBinLowEdge(j + 1)
<< " -- " << calc_data->GetXaxis()->GetBinUpEdge(j + 1)
<< "].");
if ((calc_data->GetBinContent(i + 1) != 0 ||
calc_mc->GetBinContent(i + 1) != 0) &&
((*calc_cov)(i, j) != 0)) {
QLOG(DEB, "[CHI2]\t\t Chi2 contribution (i,j) = (" << i << "," << j
<< ")");
QLOG(DEB, "[CHI2]\t\t Data - MC(i) = "
<< calc_data->GetBinContent(i + 1) << " - "
<< calc_mc->GetBinContent(i + 1) << " = "
<< (calc_data->GetBinContent(i + 1) -
calc_mc->GetBinContent(i + 1)));
QLOG(DEB, "[CHI2]\t\t Data - MC(j) = "
<< calc_data->GetBinContent(j + 1) << " - "
<< calc_mc->GetBinContent(j + 1) << " = "
<< (calc_data->GetBinContent(j + 1) -
calc_mc->GetBinContent(j + 1)));
QLOG(DEB, "[CHI2]\t\t Covar = " << (*calc_cov)(i, j));
QLOG(DEB, "[CHI2]\t\t Cont chi2 = "
<< ((calc_data->GetBinContent(i + 1) -
calc_mc->GetBinContent(i + 1)) *
(*calc_cov)(i, j) * (calc_data->GetBinContent(j + 1) -
calc_mc->GetBinContent(j + 1)))
<< " " << Chi2);
Chi2 +=
((calc_data->GetBinContent(i + 1) - calc_mc->GetBinContent(i + 1)) *
(*calc_cov)(i, j) *
(calc_data->GetBinContent(j + 1) - calc_mc->GetBinContent(j + 1)));
} else {
QLOG(DEB, "Skipping chi2 contribution (i,j) = ("
<< i << "," << j
<< "), Data = " << calc_data->GetBinContent(i + 1)
<< ", MC = " << calc_mc->GetBinContent(i + 1)
<< ", Cov = " << (*calc_cov)(i, j));
Chi2 += 0.;
}
}
}
// Cleanup
delete calc_cov;
delete calc_data;
delete calc_mc;
return Chi2;
}
//*******************************************************************
Double_t StatUtils::GetChi2FromCov(TH2D* data, TH2D* mc, TMatrixDSym* invcov,
TH2I* map, TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) {
map = StatUtils::GenerateMap(data);
}
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate 1D chi2 from 1D Plots
Double_t Chi2 = StatUtils::GetChi2FromCov(data_1D, mc_1D, invcov, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return Chi2;
}
//*******************************************************************
Double_t StatUtils::GetChi2FromSVD(TH1D* data, TH1D* mc, TMatrixDSym* cov,
TH1I* mask) {
//*******************************************************************
Double_t Chi2 = 0.0;
TMatrixDSym* calc_cov = (TMatrixDSym*)cov->Clone();
TH1D* calc_data = (TH1D*)data->Clone();
TH1D* calc_mc = (TH1D*)mc->Clone();
// If a mask if applied we need to apply it before the matrix is inverted
if (mask) {
calc_cov = StatUtils::ApplyMatrixMasking(cov, mask);
calc_data = StatUtils::ApplyHistogramMasking(data, mask);
calc_mc = StatUtils::ApplyHistogramMasking(mc, mask);
}
// Decompose matrix
TDecompSVD LU = TDecompSVD((*calc_cov));
LU.Decompose();
TMatrixDSym* cov_U =
new TMatrixDSym(calc_data->GetNbinsX(), LU.GetU().GetMatrixArray(), "");
TVectorD* cov_S = new TVectorD(LU.GetSig());
// Apply basis rotation before adding up chi2
Double_t rotated_difference = 0.0;
for (int i = 0; i < calc_data->GetNbinsX(); i++) {
rotated_difference = 0.0;
// Rotate basis of Data - MC
for (int j = 0; j < calc_data->GetNbinsY(); j++)
rotated_difference +=
(calc_data->GetBinContent(j + 1) - calc_mc->GetBinContent(j + 1)) *
(*cov_U)(j, i);
// Divide by rotated error cov_S
Chi2 += rotated_difference * rotated_difference * 1E76 / (*cov_S)(i);
}
// Cleanup
delete calc_cov;
delete calc_data;
delete calc_mc;
delete cov_U;
delete cov_S;
return Chi2;
}
//*******************************************************************
Double_t StatUtils::GetChi2FromSVD(TH2D* data, TH2D* mc, TMatrixDSym* cov,
TH2I* map, TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = StatUtils::GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate from 1D
Double_t Chi2 = StatUtils::GetChi2FromSVD(data_1D, mc_1D, cov, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return Chi2;
}
//*******************************************************************
double StatUtils::GetChi2FromEventRate(TH1D* data, TH1D* mc, TH1I* mask) {
//*******************************************************************
// If just an event rate, for chi2 just use Poission Likelihood to calculate
// the chi2 component
double chi2 = 0.0;
TH1D* calc_data = (TH1D*)data->Clone();
TH1D* calc_mc = (TH1D*)mc->Clone();
// Apply masking if required
if (mask) {
calc_data = ApplyHistogramMasking(data, mask);
calc_mc = ApplyHistogramMasking(mc, mask);
}
// Iterate over bins in X
for (int i = 0; i < calc_data->GetNbinsX(); i++) {
double dt = calc_data->GetBinContent(i + 1);
double mc = calc_mc->GetBinContent(i + 1);
if (mc <= 0) continue;
if (dt <= 0) {
// Only add difference
chi2 += 2 * (mc - dt);
} else {
// Do the chi2 for Poisson distributions
chi2 += 2 * (mc - dt + (dt * log(dt / mc)));
}
/*
LOG(REC)<<"Evt Chi2 cont = "<<i<<" "
<<mc<<" "<<dt<<" "
<<2 * (mc - dt + (dt+0.) * log((dt+0.) / (mc+0.)))
<<" "<<Chi2<<std::endl;
*/
}
// cleanup
delete calc_data;
delete calc_mc;
return chi2;
}
//*******************************************************************
Double_t StatUtils::GetChi2FromEventRate(TH2D* data, TH2D* mc, TH2I* map,
TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = StatUtils::GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate from 1D
Double_t Chi2 = StatUtils::GetChi2FromEventRate(data_1D, mc_1D, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return Chi2;
}
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromDiag(TH1D* data, TH1D* mc, TH1I* mask) {
//*******************************************************************
// Currently just a placeholder!
(void)data;
(void)mc;
(void)mask;
return 0.0;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromDiag(TH2D* data, TH2D* mc, TH2I* map,
TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = StatUtils::GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate from 1D
Double_t MLE = StatUtils::GetLikelihoodFromDiag(data_1D, mc_1D, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return MLE;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromCov(TH1D* data, TH1D* mc,
TMatrixDSym* invcov, TH1I* mask) {
//*******************************************************************
// Currently just a placeholder !
(void)data;
(void)mc;
(void)invcov;
(void)mask;
return 0.0;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromCov(TH2D* data, TH2D* mc,
TMatrixDSym* invcov, TH2I* map,
TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = StatUtils::GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate from 1D
Double_t MLE =
StatUtils::GetLikelihoodFromCov(data_1D, mc_1D, invcov, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return MLE;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromSVD(TH1D* data, TH1D* mc, TMatrixDSym* cov,
TH1I* mask) {
//*******************************************************************
// Currently just a placeholder!
(void)data;
(void)mc;
(void)cov;
(void)mask;
return 0.0;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromSVD(TH2D* data, TH2D* mc, TMatrixDSym* cov,
TH2I* map, TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = StatUtils::GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate from 1D
Double_t MLE = StatUtils::GetLikelihoodFromSVD(data_1D, mc_1D, cov, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return MLE;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromEventRate(TH1D* data, TH1D* mc,
TH1I* mask) {
//*******************************************************************
// Currently just a placeholder!
(void)data;
(void)mc;
(void)mask;
return 0.0;
};
//*******************************************************************
Double_t StatUtils::GetLikelihoodFromEventRate(TH2D* data, TH2D* mc, TH2I* map,
TH2I* mask) {
//*******************************************************************
// Generate a simple map
if (!map) map = StatUtils::GenerateMap(data);
// Convert to 1D Histograms
TH1D* data_1D = MapToTH1D(data, map);
TH1D* mc_1D = MapToTH1D(mc, map);
TH1I* mask_1D = MapToMask(mask, map);
// Calculate from 1D
Double_t MLE = StatUtils::GetChi2FromEventRate(data_1D, mc_1D, mask_1D);
// CleanUp
delete data_1D;
delete mc_1D;
delete mask_1D;
return MLE;
};
//*******************************************************************
Int_t StatUtils::GetNDOF(TH1D* hist, TH1I* mask) {
//*******************************************************************
TH1D* calc_hist = (TH1D*)hist->Clone();
// If a mask is provided we need to apply it before getting NDOF
if (mask) {
calc_hist = StatUtils::ApplyHistogramMasking(hist, mask);
}
// NDOF is defined as total number of bins with non-zero errors
Int_t NDOF = 0;
for (int i = 0; i < calc_hist->GetNbinsX(); i++) {
if (calc_hist->GetBinError(i + 1) > 0.0) NDOF++;
}
delete calc_hist;
return NDOF;
};
//*******************************************************************
Int_t StatUtils::GetNDOF(TH2D* hist, TH2I* map, TH2I* mask) {
//*******************************************************************
Int_t NDOF = 0;
if (!map) map = StatUtils::GenerateMap(hist);
for (int i = 0; i < hist->GetNbinsX(); i++) {
for (int j = 0; j < hist->GetNbinsY(); j++) {
if (mask->GetBinContent(i + 1, j + 1)) continue;
if (map->GetBinContent(i + 1, j + 1) <= 0) continue;
NDOF++;
}
}
return NDOF;
};
//*******************************************************************
TH1D* StatUtils::ThrowHistogram(TH1D* hist, TMatrixDSym* cov, bool throwdiag,
TH1I* mask) {
//*******************************************************************
TH1D* calc_hist =
(TH1D*)hist->Clone((std::string(hist->GetName()) + "_THROW").c_str());
TMatrixDSym* calc_cov = (TMatrixDSym*)cov->Clone();
Double_t correl_val = 0.0;
// If a mask if applied we need to apply it before the matrix is decomposed
if (mask) {
calc_cov = ApplyMatrixMasking(cov, mask);
calc_hist = ApplyHistogramMasking(calc_hist, mask);
}
// If a covariance is provided we need a preset random vector and a decomp
std::vector<Double_t> rand_val;
TMatrixDSym* decomp_cov;
if (cov) {
for (int i = 0; i < hist->GetNbinsX(); i++) {
rand_val.push_back(gRandom->Gaus(0.0, 1.0));
}
// Decomp the matrix
decomp_cov = StatUtils::GetDecomp(calc_cov);
}
// iterate over bins
for (int i = 0; i < hist->GetNbinsX(); i++) {
- // By Default the errors on the histogram are thrown uncorrelated to the
- // other errors
- // if (throwdiag) {
- // calc_hist->SetBinContent(i + 1, (calc_hist->GetBinContent(i + 1) + \
- // gRandom->Gaus(0.0, 1.0) * calc_hist->GetBinError(i + 1)) );
- // }
+ // By Default the errors on the histogram are thrown uncorrelated to the other errors
+ /*
+ if (throwdiag) {
+ calc_hist->SetBinContent(i + 1, (calc_hist->GetBinContent(i + 1) + \
+ gRandom->Gaus(0.0, 1.0) * calc_hist->GetBinError(i + 1)) );
+ }
+ */
// If a covariance is provided that is also thrown
if (cov) {
correl_val = 0.0;
for (int j = 0; j < hist->GetNbinsX(); j++) {
correl_val += rand_val[j] * (*decomp_cov)(j, i);
}
calc_hist->SetBinContent(
i + 1, (calc_hist->GetBinContent(i + 1) + correl_val * 1E-38));
}
}
delete calc_cov;
delete decomp_cov;
// return this new thrown data
return calc_hist;
};
//*******************************************************************
TH2D* StatUtils::ThrowHistogram(TH2D* hist, TMatrixDSym* cov, TH2I* map,
bool throwdiag, TH2I* mask) {
//*******************************************************************
// PLACEHOLDER!!!!!!!!!
// Currently no support for throwing 2D Histograms from a covariance
(void)hist;
(void)cov;
(void)map;
(void)throwdiag;
(void)mask;
// /todo
// Sort maps if required
// Throw the covariance for a 1D plot
// Unmap back to 2D Histogram
return hist;
}
//*******************************************************************
TH1D* StatUtils::ApplyHistogramMasking(TH1D* hist, TH1I* mask) {
//*******************************************************************
if (!mask) return ((TH1D*)hist->Clone());
// This masking is only sufficient for chi2 calculations, and will have dodgy
// bin edges.
// Get New Bin Count
Int_t NBins = 0;
for (int i = 0; i < hist->GetNbinsX(); i++) {
if (mask->GetBinContent(i + 1)) continue;
NBins++;
}
// Make new hist
std::string newmaskname = std::string(hist->GetName()) + "_MSKD";
TH1D* calc_hist =
new TH1D(newmaskname.c_str(), newmaskname.c_str(), NBins, 0, NBins);
// fill new hist
int binindex = 0;
for (int i = 0; i < hist->GetNbinsX(); i++) {
if (mask->GetBinContent(i + 1)) {
LOG(REC) << "Applying mask to bin " << i + 1 << " " << hist->GetName()
<< std::endl;
continue;
}
calc_hist->SetBinContent(binindex + 1, hist->GetBinContent(i + 1));
calc_hist->SetBinError(binindex + 1, hist->GetBinError(i + 1));
binindex++;
}
return calc_hist;
};
//*******************************************************************
TH2D* StatUtils::ApplyHistogramMasking(TH2D* hist, TH2I* mask) {
//*******************************************************************
TH2D* newhist = (TH2D*)hist->Clone();
if (!mask) return newhist;
for (int i = 0; i < hist->GetNbinsX(); i++) {
for (int j = 0; j < hist->GetNbinsY(); j++) {
if (mask->GetBinContent(i + 1, j + 1) > 0) {
newhist->SetBinContent(i + 1, j + 1, 0.0);
newhist->SetBinContent(i + 1, j + 1, 0.0);
}
}
}
return newhist;
}
//*******************************************************************
TMatrixDSym* StatUtils::ApplyMatrixMasking(TMatrixDSym* mat, TH1I* mask) {
//*******************************************************************
if (!mask) return (TMatrixDSym*)(mat->Clone());
// Get New Bin Count
Int_t NBins = 0;
for (int i = 0; i < mask->GetNbinsX(); i++) {
if (mask->GetBinContent(i + 1)) continue;
NBins++;
}
// make new matrix
TMatrixDSym* calc_mat = new TMatrixDSym(NBins);
int col, row;
// Need to mask out bins in the current matrix
row = 0;
for (int i = 0; i < mask->GetNbinsX(); i++) {
col = 0;
// skip if masked
if (mask->GetBinContent(i + 1) > 0.5) continue;
for (int j = 0; j < mask->GetNbinsX(); j++) {
// skip if masked
if (mask->GetBinContent(j + 1) > 0.5) continue;
(*calc_mat)(row, col) = (*mat)(i, j);
col++;
}
row++;
}
return calc_mat;
};
//*******************************************************************
TMatrixDSym* StatUtils::ApplyMatrixMasking(TMatrixDSym* mat, TH2D* data,
TH2I* mask, TH2I* map) {
//*******************************************************************
if (!map) map = StatUtils::GenerateMap(data);
TH1I* mask_1D = StatUtils::MapToMask(mask, map);
TMatrixDSym* newmat = StatUtils::ApplyMatrixMasking(mat, mask_1D);
delete mask_1D;
return newmat;
}
//*******************************************************************
TMatrixDSym* StatUtils::ApplyInvertedMatrixMasking(TMatrixDSym* mat,
TH1I* mask) {
//*******************************************************************
TMatrixDSym* new_mat = GetInvert(mat);
TMatrixDSym* masked_mat = ApplyMatrixMasking(new_mat, mask);
TMatrixDSym* inverted_mat = GetInvert(masked_mat);
delete masked_mat;
delete new_mat;
return inverted_mat;
};
//*******************************************************************
TMatrixDSym* StatUtils::ApplyInvertedMatrixMasking(TMatrixDSym* mat, TH2D* data,
TH2I* mask, TH2I* map) {
//*******************************************************************
if (!map) map = StatUtils::GenerateMap(data);
TH1I* mask_1D = StatUtils::MapToMask(mask, map);
TMatrixDSym* newmat = ApplyInvertedMatrixMasking(mat, mask_1D);
delete mask_1D;
return newmat;
}
//*******************************************************************
TMatrixDSym* StatUtils::GetInvert(TMatrixDSym* mat) {
//*******************************************************************
TMatrixDSym* new_mat = (TMatrixDSym*)mat->Clone();
// Check for diagonal
bool non_diagonal = false;
for (int i = 0; i < new_mat->GetNrows(); i++) {
for (int j = 0; j < new_mat->GetNrows(); j++) {
if (i == j) continue;
if ((*new_mat)(i, j) != 0.0) {
non_diagonal = true;
break;
}
}
}
// If diag, just flip the diag
if (!non_diagonal or new_mat->GetNrows() == 1) {
for (int i = 0; i < new_mat->GetNrows(); i++) {
if ((*new_mat)(i, i) != 0.0)
(*new_mat)(i, i) = 1.0 / (*new_mat)(i, i);
else
(*new_mat)(i, i) = 0.0;
}
return new_mat;
}
// Invert full matrix
TDecompSVD LU = TDecompSVD((*new_mat));
new_mat =
new TMatrixDSym(new_mat->GetNrows(), LU.Invert().GetMatrixArray(), "");
return new_mat;
}
//*******************************************************************
TMatrixDSym* StatUtils::GetDecomp(TMatrixDSym* mat) {
//*******************************************************************
TMatrixDSym* new_mat = (TMatrixDSym*)mat->Clone();
int nrows = new_mat->GetNrows();
// Check for diagonal
bool diagonal = true;
for (int i = 0; i < nrows; i++) {
for (int j = 0; j < nrows; j++) {
if (i == j) continue;
if ((*new_mat)(i, j) != 0.0) {
diagonal = false;
break;
}
}
}
// If diag, just flip the diag
if (diagonal or nrows == 1) {
for (int i = 0; i < nrows; i++) {
if ((*new_mat)(i, i) > 0.0)
(*new_mat)(i, i) = sqrt((*new_mat)(i, i));
else
(*new_mat)(i, i) = 0.0;
}
return new_mat;
}
TDecompChol LU = TDecompChol(*new_mat);
LU.Decompose();
delete new_mat;
TMatrixDSym* dec_mat = new TMatrixDSym(nrows, LU.GetU().GetMatrixArray(), "");
return dec_mat;
}
//*******************************************************************
void StatUtils::ForceNormIntoCovar(TMatrixDSym* mat, TH1D* hist, double norm) {
//*******************************************************************
if (!mat) mat = MakeDiagonalCovarMatrix(hist);
int nbins = mat->GetNrows();
TMatrixDSym* new_mat = new TMatrixDSym(nbins);
for (int i = 0; i < nbins; i++) {
for (int j = 0; j < nbins; j++) {
double valx = hist->GetBinContent(i + 1) * 1E38;
double valy = hist->GetBinContent(j + 1) * 1E38;
(*new_mat)(i, j) = (*mat)(i, j) + norm * norm * valx * valy;
}
}
// Swap the two
delete mat;
mat = new_mat;
return;
};
//*******************************************************************
void StatUtils::ForceNormIntoCovar(TMatrixDSym* mat, TH2D* data, double norm,
TH2I* map) {
//*******************************************************************
if (!map) map = StatUtils::GenerateMap(data);
TH1D* data_1D = MapToTH1D(data, map);
StatUtils::ForceNormIntoCovar(mat, data_1D, norm);
delete data_1D;
return;
}
//*******************************************************************
TMatrixDSym* StatUtils::MakeDiagonalCovarMatrix(TH1D* data, double scaleF) {
//*******************************************************************
TMatrixDSym* newmat = new TMatrixDSym(data->GetNbinsX());
for (int i = 0; i < data->GetNbinsX(); i++) {
(*newmat)(i, i) =
data->GetBinError(i + 1) * data->GetBinError(i + 1) * scaleF * scaleF;
}
return newmat;
}
//*******************************************************************
TMatrixDSym* StatUtils::MakeDiagonalCovarMatrix(TH2D* data, TH2I* map,
double scaleF) {
//*******************************************************************
if (!map) map = StatUtils::GenerateMap(data);
TH1D* data_1D = MapToTH1D(data, map);
return StatUtils::MakeDiagonalCovarMatrix(data_1D, scaleF);
};
//*******************************************************************
void StatUtils::SetDataErrorFromCov(TH1D* data, TMatrixDSym* cov,
double scale) {
//*******************************************************************
// Check
if (cov->GetNrows() != data->GetNbinsX()) {
- ERR(WRN) << "Nrows in cov don't match nbins in data for SetDataErrorFromCov"
- << std::endl;
+ ERR(FTL) << "Nrows in cov don't match nbins in data for SetDataErrorFromCov" << std::endl;
+ ERR(FTL) << "Nrows = " << cov->GetNrows() << std::endl;
+ ERR(FTL) << "Nbins = " << data->GetNbinsX() << std::endl;
+ //throw;
}
// Set bin errors form cov diag
+ // Check if the errors are set
+ bool ErrorsSet = false;
for (int i = 0; i < data->GetNbinsX(); i++) {
- data->SetBinError(i + 1, sqrt((*cov)(i, i)) * scale);
+ if (ErrorsSet == true) break;
+ if (data->GetBinError(i+1) != 0) ErrorsSet = true;
+ }
+
+ // Now loop over
+ if (ErrorsSet) {
+ for (int i = 0; i < data->GetNbinsX(); i++) {
+ double dataerr = data->GetBinError(i + 1);
+ double coverr = sqrt((*cov)(i, i))*scale;
+ if (fabs(dataerr-coverr) > 1E-44) {
+ ERR(FTL) << "Data error does not match covariance error for bin " << i+1 << " (" << data->GetXaxis()->GetBinLowEdge(i+1) << "-" << data->GetXaxis()->GetBinLowEdge(i+2) << ")" << std::endl;
+ ERR(FTL) << "Data error: " << dataerr << std::endl;
+ ERR(FTL) << "Cov error: " << coverr << std::endl;
+ }
+ }
+ // Else blindly trust the covariance
+ } else {
+ for (int i = 0; i < data->GetNbinsX(); i++) {
+ data->SetBinError(i+1, sqrt((*cov)(i,i))*scale);
+ }
}
return;
}
//*******************************************************************
void StatUtils::SetDataErrorFromCov(TH2D* data, TMatrixDSym* cov, TH2I* map,
- double scale) {
+ double scale) {
//*******************************************************************
// Create map if required
if (!map) map = StatUtils::GenerateMap(data);
// Set Bin Errors from cov diag
int count = 0;
for (int i = 0; i < data->GetNbinsX(); i++) {
for (int j = 0; j < data->GetNbinsY(); j++) {
if (data->GetBinContent(i + 1, j + 1) == 0.0) continue;
count = map->GetBinContent(i + 1, j + 1) - 1;
data->SetBinError(i + 1, j + 1, sqrt((*cov)(count, count)) * scale);
}
}
return;
}
TMatrixDSym* StatUtils::ExtractShapeOnlyCovar(TMatrixDSym* full_covar,
- TH1* data_hist,
- double data_scale) {
+ TH1* data_hist,
+ double data_scale) {
int nbins = full_covar->GetNrows();
TMatrixDSym* shape_covar = new TMatrixDSym(nbins);
// Check nobody is being silly
if (data_hist->GetNbinsX() != nbins) {
ERR(WRN) << "Inconsistent matrix and data histogram passed to "
- "StatUtils::ExtractShapeOnlyCovar!"
- << std::endl;
+ "StatUtils::ExtractShapeOnlyCovar!"
+ << std::endl;
ERR(WRN) << "data_hist has " << data_hist->GetNbinsX() << " matrix has "
- << nbins << std::endl;
+ << nbins << std::endl;
int err_bins = data_hist->GetNbinsX();
if (nbins > err_bins) err_bins = nbins;
for (int i = 0; i < err_bins; ++i) {
ERR(WRN) << "Matrix diag. = " << (*full_covar)(i, i)
- << " data = " << data_hist->GetBinContent(i + 1) << std::endl;
+ << " data = " << data_hist->GetBinContent(i + 1) << std::endl;
}
return NULL;
}
double total_data = 0;
double total_covar = 0;
// Initial loop to calculate some constants
for (int i = 0; i < nbins; ++i) {
total_data += data_hist->GetBinContent(i + 1) * data_scale;
for (int j = 0; j < nbins; ++j) {
total_covar += (*full_covar)(i, j);
}
}
if (total_data == 0 || total_covar == 0) {
ERR(WRN) << "Stupid matrix or data histogram passed to "
- "StatUtils::ExtractShapeOnlyCovar! Ignoring..."
- << std::endl;
+ "StatUtils::ExtractShapeOnlyCovar! Ignoring..."
+ << std::endl;
return NULL;
}
LOG(SAM) << "Norm error = " << sqrt(total_covar) / total_data << std::endl;
// Now loop over and calculate the shape-only matrix
for (int i = 0; i < nbins; ++i) {
double data_i = data_hist->GetBinContent(i + 1) * data_scale;
for (int j = 0; j < nbins; ++j) {
double data_j = data_hist->GetBinContent(j + 1) * data_scale;
double norm_term =
- data_i * data_j * total_covar / total_data / total_data;
+ data_i * data_j * total_covar / total_data / total_data;
double mix_sum1 = 0;
double mix_sum2 = 0;
for (int k = 0; k < nbins; ++k) {
mix_sum1 += (*full_covar)(k, j);
mix_sum2 += (*full_covar)(i, k);
}
double mix_term1 =
- data_i * (mix_sum1 / total_data -
- total_covar * data_j / total_data / total_data);
+ data_i * (mix_sum1 / total_data -
+ total_covar * data_j / total_data / total_data);
double mix_term2 =
- data_j * (mix_sum2 / total_data -
- total_covar * data_i / total_data / total_data);
+ data_j * (mix_sum2 / total_data -
+ total_covar * data_i / total_data / total_data);
(*shape_covar)(i, j) =
- (*full_covar)(i, j) - mix_term1 - mix_term2 - norm_term;
+ (*full_covar)(i, j) - mix_term1 - mix_term2 - norm_term;
}
}
return shape_covar;
}
//*******************************************************************
TH2I* StatUtils::GenerateMap(TH2D* hist) {
//*******************************************************************
std::string maptitle = std::string(hist->GetName()) + "_MAP";
TH2I* map =
- new TH2I(maptitle.c_str(), maptitle.c_str(), hist->GetNbinsX(), 0,
- hist->GetNbinsX(), hist->GetNbinsY(), 0, hist->GetNbinsY());
+ new TH2I(maptitle.c_str(), maptitle.c_str(), hist->GetNbinsX(), 0,
+ hist->GetNbinsX(), hist->GetNbinsY(), 0, hist->GetNbinsY());
Int_t index = 1;
for (int i = 0; i < hist->GetNbinsX(); i++) {
for (int j = 0; j < hist->GetNbinsY(); j++) {
if (hist->GetBinContent(i + 1, j + 1) > 0 &&
hist->GetBinError(i + 1, j + 1) > 0) {
map->SetBinContent(i + 1, j + 1, index);
index++;
} else {
map->SetBinContent(i + 1, j + 1, 0);
}
}
}
return map;
}
//*******************************************************************
TH1D* StatUtils::MapToTH1D(TH2D* hist, TH2I* map) {
//*******************************************************************
if (!hist) return NULL;
// Get N bins for 1D plot
Int_t Nbins = map->GetMaximum();
std::string name1D = std::string(hist->GetName()) + "_1D";
// Make new 1D Hist
TH1D* newhist = new TH1D(name1D.c_str(), name1D.c_str(), Nbins, 0, Nbins);
// map bin contents
for (int i = 0; i < map->GetNbinsX(); i++) {
for (int j = 0; j < map->GetNbinsY(); j++) {
if (map->GetBinContent(i + 1, j + 1) == 0) continue;
newhist->SetBinContent(map->GetBinContent(i + 1, j + 1),
- hist->GetBinContent(i + 1, j + 1));
+ hist->GetBinContent(i + 1, j + 1));
newhist->SetBinError(map->GetBinContent(i + 1, j + 1),
- hist->GetBinError(i + 1, j + 1));
+ hist->GetBinError(i + 1, j + 1));
}
}
// return
return newhist;
}
//*******************************************************************
TH1I* StatUtils::MapToMask(TH2I* hist, TH2I* map) {
//*******************************************************************
TH1I* newhist = NULL;
if (!hist) return newhist;
// Get N bins for 1D plot
Int_t Nbins = map->GetMaximum();
std::string name1D = std::string(hist->GetName()) + "_1D";
// Make new 1D Hist
newhist = new TH1I(name1D.c_str(), name1D.c_str(), Nbins, 0, Nbins);
// map bin contents
for (int i = 0; i < map->GetNbinsX(); i++) {
for (int j = 0; j < map->GetNbinsY(); j++) {
if (map->GetBinContent(i + 1, j + 1) == 0) continue;
newhist->SetBinContent(map->GetBinContent(i + 1, j + 1),
- hist->GetBinContent(i + 1, j + 1));
+ hist->GetBinContent(i + 1, j + 1));
}
}
// return
return newhist;
}
TMatrixDSym* StatUtils::GetCovarFromCorrel(TMatrixDSym* correl, TH1D* data) {
int nbins = correl->GetNrows();
TMatrixDSym* covar = new TMatrixDSym(nbins);
for (int i = 0; i < nbins; i++) {
for (int j = 0; j < nbins; j++) {
(*covar)(i, j) =
- (*correl)(i, j) * data->GetBinError(i + 1) * data->GetBinError(j + 1);
+ (*correl)(i, j) * data->GetBinError(i + 1) * data->GetBinError(j + 1);
}
}
return covar;
}
//*******************************************************************
TMatrixD* StatUtils::GetMatrixFromTextFile(std::string covfile, int dimx,
- int dimy) {
+ int dimy) {
//*******************************************************************
// Determine dim
if (dimx == -1 and dimy == -1) {
std::string line;
std::ifstream covar(covfile.c_str(), std::ifstream::in);
int row = 0;
while (std::getline(covar >> std::ws, line, '\n')) {
int column = 0;
std::vector<double> entries = GeneralUtils::ParseToDbl(line, " ");
if (entries.size() <= 1) {
ERR(WRN) << "StatUtils::GetMatrixFromTextFile, 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++) {
column++;
if (column > dimx) dimx = column;
}
row++;
if (row > dimy) dimy = row;
}
}
// Or assume symmetric
if (dimx != -1 and dimy == -1) {
dimy = dimx;
}
assert(dimy != -1 && " matrix dimy not set.");
// Make new matrix
TMatrixD* mat = new TMatrixD(dimx, dimy);
std::string line;
std::ifstream covar(covfile.c_str(), std::ifstream::in);
int row = 0;
while (std::getline(covar >> std::ws, line, '\n')) {
int column = 0;
std::vector<double> entries = GeneralUtils::ParseToDbl(line, " ");
if (entries.size() <= 1) {
ERR(WRN) << "StatUtils::GetMatrixFromTextFile, 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++) {
// Check Rows
// assert(row > mat->GetNrows() && " covar rows doesn't match matrix
// rows.");
// assert(column > mat->GetNcols() && " covar cols doesn't match matrix
// cols.");
// Fill Matrix
(*mat)(row, column) = (*iter);
column++;
}
row++;
}
return mat;
}
//*******************************************************************
TMatrixD* StatUtils::GetMatrixFromRootFile(std::string covfile,
- std::string histname) {
+ std::string histname) {
//*******************************************************************
std::string inputfile = covfile + ";" + histname;
std::vector<std::string> splitfile = GeneralUtils::ParseToStr(inputfile, ";");
if (splitfile.size() < 2) {
ERR(FTL) << "No object name given!" << std::endl;
throw;
}
// Get file
TFile* tempfile = new TFile(splitfile[0].c_str(), "READ");
// Get Object
TObject* obj = tempfile->Get(splitfile[1].c_str());
if (!obj) {
ERR(FTL) << "Object " << splitfile[1] << " doesn't exist!" << std::endl;
throw;
}
// Try casting
TMatrixD* mat = dynamic_cast<TMatrixD*>(obj);
if (mat) {
TMatrixD* newmat = (TMatrixD*)mat->Clone();
delete mat;
tempfile->Close();
return newmat;
}
TMatrixDSym* matsym = dynamic_cast<TMatrixDSym*>(obj);
if (matsym) {
TMatrixD* newmat = new TMatrixD(matsym->GetNrows(), matsym->GetNrows());
for (int i = 0; i < matsym->GetNrows(); i++) {
for (int j = 0; j < matsym->GetNrows(); j++) {
(*newmat)(i, j) = (*matsym)(i, j);
}
}
delete matsym;
tempfile->Close();
return newmat;
}
TH2D* mathist = dynamic_cast<TH2D*>(obj);
if (mathist) {
TMatrixD* newmat = new TMatrixD(mathist->GetNbinsX(), mathist->GetNbinsX());
for (int i = 0; i < mathist->GetNbinsX(); i++) {
for (int j = 0; j < mathist->GetNbinsX(); j++) {
(*newmat)(i, j) = mathist->GetBinContent(i + 1, j + 1);
}
}
delete mathist;
tempfile->Close();
return newmat;
}
return NULL;
}
//*******************************************************************
TMatrixDSym* StatUtils::GetCovarFromTextFile(std::string covfile, int dim) {
//*******************************************************************
// Delete TempMat
TMatrixD* tempmat = GetMatrixFromTextFile(covfile, dim, dim);
// Make a symmetric covariance
TMatrixDSym* newmat = new TMatrixDSym(tempmat->GetNrows());
for (int i = 0; i < tempmat->GetNrows(); i++) {
for (int j = 0; j < tempmat->GetNrows(); j++) {
(*newmat)(i, j) = (*tempmat)(i, j);
}
}
delete tempmat;
return newmat;
}
//*******************************************************************
TMatrixDSym* StatUtils::GetCovarFromRootFile(std::string covfile,
- std::string histname) {
+ std::string histname) {
//*******************************************************************
TMatrixD* tempmat = GetMatrixFromRootFile(covfile, histname);
TMatrixDSym* newmat = new TMatrixDSym(tempmat->GetNrows());
for (int i = 0; i < tempmat->GetNrows(); i++) {
for (int j = 0; j < tempmat->GetNrows(); j++) {
(*newmat)(i, j) = (*tempmat)(i, j);
}
}
delete tempmat;
return newmat;
}
diff --git a/src/T2K/T2K_CC0pinp_STV_XSec_1Ddat_nu.cxx b/src/T2K/T2K_CC0pinp_STV_XSec_1Ddat_nu.cxx
index fd5a4a6..0cc4155 100644
--- a/src/T2K/T2K_CC0pinp_STV_XSec_1Ddat_nu.cxx
+++ b/src/T2K/T2K_CC0pinp_STV_XSec_1Ddat_nu.cxx
@@ -1,90 +1,87 @@
// Copyright 2016 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/>.
*******************************************************************************/
#include "T2K_SignalDef.h"
#include "T2K_CC0pinp_STV_XSec_1Ddat_nu.h"
//********************************************************************
T2K_CC0pinp_STV_XSec_1Ddat_nu::T2K_CC0pinp_STV_XSec_1Ddat_nu(nuiskey samplekey) {
//********************************************************************
// Sample overview ---------------------------------------------------
std::string descrip = "T2K_CC0pinp_STV_XSec_1Ddat_nu sample. \n" \
"Target: CH \n" \
"Flux: T2K 2.5 degree off-axis (ND280) \n" \
"Signal: CC0piNp (N>=1) with 450M eV < p_p < 1 GeV \n" \
" p_mu > 250 MeV \n" \
" cth_p > 0.6 \n" \
" cth_mu > -0.4 \n";
// Setup common settings
fSettings = LoadSampleSettings(samplekey);
fSettings.SetDescription(descrip);
fSettings.SetXTitle("#delta#it{#alpha}_{T} (GeV c^{-1})");
fSettings.SetYTitle("#frac{d#sigma}{d#delta#it{#alpha}_{T}} (cm^{2} nucleon^{-1} rads^{-1})");
fSettings.SetAllowedTypes("FIX,FREE,SHAPE/DIAG,FULL/NORM/MASK", "FIX/DIAG");
fSettings.SetEnuRange(0.0, 50.0);
fSettings.DefineAllowedTargets("C,H");
// CCQELike plot information
fSettings.SetTitle("T2K_CC0pinp_STV_XSec_1Ddat_nu");
// fSettings.SetDataInput( GeneralUtils::GetTopLevelDir() + "/data/T2K/T2K_CC0pinp_STV_XSec_1Ddat_nu.dat");
fSettings.SetDataInput( FitPar::GetDataBase() + "/T2K/CC0pi/STV/datResults.root;Result" );
fSettings.SetCovarInput( FitPar::GetDataBase() + "/T2K/CC0pi/STV/datResults.root;Correlation_Matrix" );
fSettings.DefineAllowedSpecies("numu");
FinaliseSampleSettings();
// Scaling Setup ---------------------------------------------------
// ScaleFactor automatically setup for DiffXSec/cm2/Nucleon
fScaleFactor = GetEventHistogram()->Integral("width") * double(1E-38) /
(double(fNEvents) * TotalIntegratedFlux("width"));
// Plot Setup -------------------------------------------------------
//SetDataFromTextFile( fSettings.GetDataInput() );
//ScaleData(1E-38);
//SetCovarFromDiagonal();
SetDataFromRootFile( fSettings.GetDataInput() );
SetCorrelationFromRootFile(fSettings.GetCovarInput() );
// Final setup ---------------------------------------------------
FinaliseMeasurement();
};
-
-
-
void T2K_CC0pinp_STV_XSec_1Ddat_nu::FillEventVariables(FitEvent *event) {
fXVar = FitUtils::Get_STV_dalphat(event, 14, true);
return;
};
//********************************************************************
bool T2K_CC0pinp_STV_XSec_1Ddat_nu::isSignal(FitEvent *event)
//********************************************************************
{
return SignalDef::isT2K_CC0pi_STV(event, EnuMin, EnuMax);
}
diff --git a/src/T2K/T2K_CC0pinp_STV_XSec_1Ddpt_nu.cxx b/src/T2K/T2K_CC0pinp_STV_XSec_1Ddpt_nu.cxx
index cc4f9ad..0b862ed 100644
--- a/src/T2K/T2K_CC0pinp_STV_XSec_1Ddpt_nu.cxx
+++ b/src/T2K/T2K_CC0pinp_STV_XSec_1Ddpt_nu.cxx
@@ -1,93 +1,89 @@
// Copyright 2016 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/>.
*******************************************************************************/
#include "T2K_SignalDef.h"
#include "T2K_CC0pinp_STV_XSec_1Ddpt_nu.h"
//********************************************************************
T2K_CC0pinp_STV_XSec_1Ddpt_nu::T2K_CC0pinp_STV_XSec_1Ddpt_nu(nuiskey samplekey) {
//********************************************************************
// Sample overview ---------------------------------------------------
std::string descrip = "T2K_CC0pinp_STV_XSec_1Ddpt_nu sample. \n" \
"Target: CH \n" \
"Flux: T2K 2.5 degree off-axis (ND280) \n" \
"Signal: CC0piNp (N>=1) with 450M eV < p_p < 1 GeV \n"\
" p_mu > 250 MeV \n"\
" cth_p > 0.6 \n"\
" cth_mu > -0.4 \n";\
// Setup common settings
fSettings = LoadSampleSettings(samplekey);
fSettings.SetDescription(descrip);
fSettings.SetXTitle("#delta#it{p}_{T} (GeV c^{-1})");
fSettings.SetYTitle("#frac{d#sigma}{d#delta#it{p}_{T}} (cm^{2} nucleon^{-1} GeV^{-1} c)");
fSettings.SetAllowedTypes("FIX,FREE,SHAPE/DIAG,FULL/NORM/MASK", "FIX/DIAG");
fSettings.SetEnuRange(0.0, 50.0);
fSettings.DefineAllowedTargets("C,H");
// CCQELike plot information
fSettings.SetTitle("T2K_CC0pinp_STV_XSec_1Ddpt_nu");
//fSettings.SetDataInput( GeneralUtils::GetTopLevelDir() + "/data/T2K/T2K_CC0pinp_STV_XSec_1Ddpt_nu.dat");
fSettings.SetDataInput( FitPar::GetDataBase() + "/T2K/CC0pi/STV/dptResults.root;Result" );
fSettings.SetCovarInput( FitPar::GetDataBase() + "/T2K/CC0pi/STV/dptResults.root;Correlation_Matrix" );
fSettings.DefineAllowedSpecies("numu");
FinaliseSampleSettings();
// Scaling Setup ---------------------------------------------------
// ScaleFactor automatically setup for DiffXSec/cm2/Nucleon
fScaleFactor = GetEventHistogram()->Integral("width") * double(1E-38) /
(double(fNEvents) * TotalIntegratedFlux("width"));
// Plot Setup -------------------------------------------------------
//SetDataFromTextFile( fSettings.GetDataInput() );
//SetCovarFromDiagonal();
//ScaleData(1E-38);
SetDataFromRootFile( fSettings.GetDataInput() );
SetCorrelationFromRootFile(fSettings.GetCovarInput() );
//SetCovarianceFromRootFile(fSettings.GetCovarInput() );
// Final setup ---------------------------------------------------
FinaliseMeasurement();
};
-
-
-
-
void T2K_CC0pinp_STV_XSec_1Ddpt_nu::FillEventVariables(FitEvent *event) {
fXVar = FitUtils::Get_STV_dpt(event, 14, true) / 1000.0;
return;
};
//********************************************************************
bool T2K_CC0pinp_STV_XSec_1Ddpt_nu::isSignal(FitEvent *event)
//********************************************************************
{
return SignalDef::isT2K_CC0pi_STV(event, EnuMin, EnuMax);
}
diff --git a/src/T2K/T2K_SignalDef.cxx b/src/T2K/T2K_SignalDef.cxx
index bfb151d..815f313 100644
--- a/src/T2K/T2K_SignalDef.cxx
+++ b/src/T2K/T2K_SignalDef.cxx
@@ -1,311 +1,310 @@
// Copyright 2016 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/>.
*******************************************************************************/
#include "FitUtils.h"
#include "T2K_SignalDef.h"
namespace SignalDef {
// T2K H2O signal definition
bool isCC1pip_T2K_H2O(FitEvent *event, double EnuMin,
double EnuMax) {
if (!isCC1pi(event, 14, 211, EnuMin, EnuMax)) return false;
TLorentzVector Pnu = event->GetHMISParticle(14)->fP;
TLorentzVector Pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector Ppip = event->GetHMFSParticle(211)->fP;
double p_mu = FitUtils::p(Pmu) * 1000;
double p_pi = FitUtils::p(Ppip) * 1000;
double cos_th_mu = cos(FitUtils::th(Pnu, Pmu));
double cos_th_pi = cos(FitUtils::th(Pnu, Ppip));
if (p_mu <= 200 || p_pi <= 200 || cos_th_mu <= 0.3 || cos_th_pi <= 0.3) {
return false;
}
return true;
};
// ******************************************************
// T2K CC1pi+ CH analysis (Raquel's thesis)
// Has different phase space cuts depending on if using Michel tag or not
//
// Essentially consists of two samples: one sample which has Michel e (which we
// can't get pion direction from); this covers backwards angles quite well.
// Measurements including this sample does not have include pion kinematics cuts
// one sample which has PID in FGD and TPC
// and no Michel e. These are mostly
// forward-going so require a pion
// kinematics cut
//
// Essentially, cuts are:
// 1 negative muon
// 1 positive pion
// Any number of nucleons
// No other particles in the final state
//
// MOVE T2K
bool isCC1pip_T2K_CH(FitEvent *event, double EnuMin, double EnuMax,
bool MichelElectron) {
// ******************************************************
if (!isCC1pi(event, 14, 211, EnuMin, EnuMax)) return false;
TLorentzVector Pnu = event->GetHMISParticle(14)->fP;
TLorentzVector Pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector Ppip = event->GetHMFSParticle(211)->fP;
// If this event passes the criteria on particle counting, enforce the T2K
// ND280 phase space constraints
// Will be different if Michel tag sample is included or not
// Essentially, if there's a Michel tag we don't cut on the pion variables
double p_mu = FitUtils::p(Pmu) * 1000;
double p_pi = FitUtils::p(Ppip) * 1000;
double cos_th_mu = cos(FitUtils::th(Pnu, Pmu));
double cos_th_pi = cos(FitUtils::th(Pnu, Ppip));
// If we're using Michel e- requirement we only care about the muon restricted
// phase space and use full pion phase space
if (MichelElectron) {
// Make the cuts on the muon variables
if (p_mu <= 200 || cos_th_mu <= 0.2) {
return false;
} else {
return true;
}
// If we aren't using Michel e- (i.e. we use directional information from
// pion) we need to impose the phase space cuts on the muon AND the pion)
} else {
// Make the cuts on muon and pion variables
if (p_mu <= 200 || p_pi <= 200 || cos_th_mu <= 0.2 || cos_th_pi <= 0.2) {
return false;
} else {
return true;
}
}
// Default to false; should never fire
return false;
};
bool isT2K_CC0pi(FitEvent *event, double EnuMin, double EnuMax,
bool forwardgoing) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
TLorentzVector Pnu = event->GetHMISParticle(14)->fP;
TLorentzVector Pmu = event->GetHMFSParticle(13)->fP;
double CosThetaMu = cos(Pnu.Vect().Angle(Pmu.Vect()));
double p_mu = Pmu.Vect().Mag();
// If we're doing a restricted phase space, Analysis II asks for:
// Cos(theta_mu) > 0.0 and p_mu > 200 MeV
if (forwardgoing) {
if (CosThetaMu < 0.0 || p_mu < 200) return false;
}
return true;
}
bool isT2K_CC0pi1p(FitEvent *event, double EnuMin, double EnuMax) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
// Require at least one FS proton
if (event->NumFSParticle(2212) == 0) return false;
TLorentzVector pnu = event->GetHMISParticle(14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector pp = event->GetHMFSParticle(2212)->fP;
// Proton phase space
if (pp.Vect().Mag() < 500) {
return false;
}
//Need exactly one proton with 500 MeV or more momentum
std::vector<FitParticle*> protons = event->GetAllFSProton();
int nProtonsAboveThresh=0;
for(int i=0; i<protons.size(); i++){
if(protons[i]->p()>500) nProtonsAboveThresh++;
}
if(nProtonsAboveThresh!=1) return false;
return true;
}
//CC0pi antinu in the P0D - TN328
bool isT2K_CC0piAnuP0D(FitEvent *event, double EnuMin, double EnuMax) {
// Require a anumu CC0pi event
if (!isCC0pi(event, -14, EnuMin, EnuMax)) return false;
TLorentzVector pnu = event->GetHMISParticle(-14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(-13)->fP;
double Pmu = pmu.Vect().Mag();
double CosThetaMu = cos(pnu.Vect().Angle(pmu.Vect()));
// Muon phase space
if (Pmu < 400 || Pmu > 3410) return false;
if (Pmu < 530 && CosThetaMu<0.85) return false;
if (Pmu < 670 && CosThetaMu<0.88) return false;
if (Pmu < 800 && CosThetaMu<0.9) return false;
if (Pmu < 1000 && CosThetaMu<0.91) return false;
if (Pmu < 1380 && CosThetaMu<0.92) return false;
if (Pmu < 2010 && CosThetaMu<0.95) return false;
return true;
}
bool isT2K_CC0piNp(FitEvent *event, double EnuMin, double EnuMax) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
// Require at least one FS proton
if (event->NumFSParticle(2212) == 0) return false;
TLorentzVector pnu = event->GetHMISParticle(14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector pp = event->GetHMFSParticle(2212)->fP;
-
// Proton phase space
if (pp.Vect().Mag() < 500) {
return false;
}
//Need exactly one proton with 500 MeV or more momentum
std::vector<FitParticle*> protons = event->GetAllFSProton();
int nProtonsAboveThresh=0;
for(int i=0; i<protons.size(); i++){
if(protons[i]->p()>500) nProtonsAboveThresh++;
}
if(nProtonsAboveThresh<2) return false;
return true;
}
bool isT2K_CC0pi0p(FitEvent *event, double EnuMin, double EnuMax) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
// Require at least one FS proton
if (event->NumFSParticle(2212) == 0) return false;
TLorentzVector pnu = event->GetHMISParticle(14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector pp = event->GetHMFSParticle(2212)->fP;
// Proton phase space
if (pp.Vect().Mag() > 500) {
return false;
}
return true;
}
bool isT2K_CC0pi_STV(FitEvent *event, double EnuMin, double EnuMax) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
// Require at least one FS proton
if (event->NumFSParticle(2212) == 0) return false;
TLorentzVector pnu = event->GetHMISParticle(14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector pp = event->GetHMFSParticle(2212)->fP;
// Muon phase space
// Pmu > 250 MeV, cos(theta_mu) > -0.6 (Sweet phase space!)
if ((pmu.Vect().Mag() < 250) || cos(pnu.Vect().Angle(pmu.Vect())) < -0.6) {
return false;
}
// Proton phase space
// Pprot > 450 MeV, cos(theta_proton) > 0.4
if ((pp.Vect().Mag() < 450) || (pp.Vect().Mag() > 1E3) ||
(cos(pnu.Vect().Angle(pp.Vect())) < 0.4)) {
return false;
}
return true;
}
bool isT2K_CC0pi_ifk(FitEvent *event, double EnuMin, double EnuMax) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
// Require at least one FS proton
if (event->NumFSParticle(2212) == 0) return false;
TLorentzVector pnu = event->GetHMISParticle(14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector pp = event->GetHMFSParticle(2212)->fP;
// Proton phase space
// Pprot > 450 MeV, cos(theta_proton) > 0.4
if ((pp.Vect().Mag() < 450) || (cos(pnu.Vect().Angle(pp.Vect())) < 0.4)) {
return false;
}
return true;
}
bool isT2K_CC0pi_1bin(FitEvent *event, double EnuMin, double EnuMax) {
// Require a numu CC0pi event
if (!isCC0pi(event, 14, EnuMin, EnuMax)) return false;
// Require at least one FS proton
if (event->NumFSParticle(2212) == 0) return false;
TLorentzVector pnu = event->GetHMISParticle(14)->fP;
TLorentzVector pmu = event->GetHMFSParticle(13)->fP;
TLorentzVector pp = event->GetHMFSParticle(2212)->fP;
// Muon phase space
//if ((pmu.Vect().Mag() < 250) || cos(pnu.Vect().Angle(pmu.Vect())) < -0.6) {
// return false;
//}
// Proton phase space
if ((pp.Vect().Mag() < 450) || (cos(pnu.Vect().Angle(pp.Vect())) < 0.4)) {
return false;
}
return true;
}
}
diff --git a/src/Utils/PlotUtils.cxx b/src/Utils/PlotUtils.cxx
index 40d2f13..47942e6 100644
--- a/src/Utils/PlotUtils.cxx
+++ b/src/Utils/PlotUtils.cxx
@@ -1,1029 +1,1033 @@
// Copyright 2016 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/>.
*******************************************************************************/
#include "PlotUtils.h"
#include "FitEvent.h"
#include "StatUtils.h"
// MOVE TO MB UTILS!
// This function is intended to be modified to enforce a consistent masking for
// all models.
TH2D* PlotUtils::SetMaskHist(std::string type, TH2D* data) {
TH2D* fMaskHist = (TH2D*)data->Clone("fMaskHist");
for (int xBin = 0; xBin < fMaskHist->GetNbinsX(); ++xBin) {
for (int yBin = 0; yBin < fMaskHist->GetNbinsY(); ++yBin) {
if (data->GetBinContent(xBin + 1, yBin + 1) == 0)
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 0);
else
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 0.5);
if (!type.compare("MB_numu_2D")) {
if (yBin == 19 && xBin < 8)
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 1.0);
} else {
if (yBin == 19 && xBin < 11)
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 1.0);
}
if (yBin == 18 && xBin < 3)
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 1.0);
if (yBin == 17 && xBin < 2)
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 1.0);
if (yBin == 16 && xBin < 1)
fMaskHist->SetBinContent(xBin + 1, yBin + 1, 1.0);
}
}
return fMaskHist;
};
// MOVE TO GENERAL UTILS?
bool PlotUtils::CheckObjectWithName(TFile* inFile, std::string substring) {
TIter nextkey(inFile->GetListOfKeys());
TKey* key;
while ((key = (TKey*)nextkey())) {
std::string test(key->GetName());
if (test.find(substring) != std::string::npos) return true;
}
return false;
};
// MOVE TO GENERAL UTILS?
std::string PlotUtils::GetObjectWithName(TFile* inFile, std::string substring) {
TIter nextkey(inFile->GetListOfKeys());
TKey* key;
std::string output = "";
while ((key = (TKey*)nextkey())) {
std::string test(key->GetName());
if (test.find(substring) != std::string::npos) output = test;
}
return output;
};
void PlotUtils::CreateNeutModeArray(TH1* hist, TH1* neutarray[]) {
for (int i = 0; i < 60; i++) {
neutarray[i] = (TH1*)hist->Clone(Form("%s_NMODE_%i", hist->GetName(), i));
}
return;
};
void PlotUtils::DeleteNeutModeArray(TH1* neutarray[]) {
for (int i = 0; i < 60; i++) {
delete neutarray[i];
}
return;
};
void PlotUtils::FillNeutModeArray(TH1D* hist[], int mode, double xval,
double weight) {
if (abs(mode) > 60) return;
hist[abs(mode)]->Fill(xval, weight);
return;
};
void PlotUtils::FillNeutModeArray(TH2D* hist[], int mode, double xval,
double yval, double weight) {
if (abs(mode) > 60) return;
hist[abs(mode)]->Fill(xval, yval, weight);
return;
};
THStack PlotUtils::GetNeutModeStack(std::string title, TH1* ModeStack[],
int option) {
(void)option;
THStack allmodes = THStack(title.c_str(), title.c_str());
for (int i = 0; i < 60; i++) {
allmodes.Add(ModeStack[i]);
}
// Credit to Clarence for copying all this out.
// CC
ModeStack[1]->SetTitle("CCQE");
ModeStack[1]->SetFillColor(kBlue);
// ModeStack[1]->SetFillStyle(3444);
ModeStack[1]->SetLineColor(kBlue);
ModeStack[2]->SetTitle("2p/2h Nieves");
ModeStack[2]->SetFillColor(kRed);
// ModeStack[2]->SetFillStyle(3344);
ModeStack[2]->SetLineColor(kRed);
// ModeStack[11]->SetTitle("#it{#nu + p #rightarrow l^{-} + p + #pi^{+}}");
ModeStack[11]->SetTitle("CC1#pi^{+} on p");
ModeStack[11]->SetFillColor(kGreen);
// ModeStack[11]->SetFillStyle(3004);
ModeStack[11]->SetLineColor(kGreen);
// ModeStack[12]->SetTitle("#it{#nu + n #rightarrow l^{-} + p + #pi^{0}}");
ModeStack[12]->SetTitle("CC1#pi^{0} on n");
ModeStack[12]->SetFillColor(kGreen + 3);
// ModeStack[12]->SetFillStyle(3005);
ModeStack[12]->SetLineColor(kGreen);
// ModeStack[13]->SetTitle("#it{#nu + n #rightarrow l^{-} + n + #pi^{+}}");
ModeStack[13]->SetTitle("CC1#pi^{+} on n");
ModeStack[13]->SetFillColor(kGreen - 2);
// ModeStack[13]->SetFillStyle(3004);
ModeStack[13]->SetLineColor(kGreen);
ModeStack[16]->SetTitle("CC coherent");
ModeStack[16]->SetFillColor(kBlue);
// ModeStack[16]->SetFillStyle(3644);
ModeStack[16]->SetLineColor(kBlue);
// ModeStack[17]->SetTitle("#it{#nu + n #rightarrow l^{-} + p + #gamma}");
ModeStack[17]->SetTitle("CC1#gamma");
ModeStack[17]->SetFillColor(kMagenta);
// ModeStack[17]->SetFillStyle(3001);
ModeStack[17]->SetLineColor(kMagenta);
ModeStack[21]->SetTitle("Multi #pi (1.3 < W < 2.0)");
ModeStack[21]->SetFillColor(kYellow);
// ModeStack[21]->SetFillStyle(3005);
ModeStack[21]->SetLineColor(kYellow);
// ModeStack[22]->SetTitle("#it{#nu + n #rightarrow l^{-} + p + #eta^{0}}");
ModeStack[22]->SetTitle("CC1#eta^{0} on n");
ModeStack[22]->SetFillColor(kYellow - 2);
// ModeStack[22]->SetFillStyle(3013);
ModeStack[22]->SetLineColor(kYellow - 2);
// ModeStack[23]->SetTitle("#it{#nu + n #rightarrow l^{-} + #Lambda +
// K^{+}}");
ModeStack[23]->SetTitle("CC1#Labda1K^{+}");
ModeStack[23]->SetFillColor(kYellow - 6);
// ModeStack[23]->SetFillStyle(3013);
ModeStack[23]->SetLineColor(kYellow - 6);
ModeStack[26]->SetTitle("DIS (W > 2.0)");
ModeStack[26]->SetFillColor(kRed);
// ModeStack[26]->SetFillStyle(3006);
ModeStack[26]->SetLineColor(kRed);
// NC
// ModeStack[31]->SetTitle("#it{#nu + n #rightarrow #nu + n + #pi^{0}}");
ModeStack[31]->SetTitle("NC1#pi^{0} on n");
ModeStack[31]->SetFillColor(kBlue);
// ModeStack[31]->SetFillStyle(3004);
ModeStack[31]->SetLineColor(kBlue);
// ModeStack[32]->SetTitle("#it{#nu + p #rightarrow #nu + p + #pi^{0}}");
ModeStack[32]->SetTitle("NC1#pi^{0} on p");
ModeStack[32]->SetFillColor(kBlue + 3);
// ModeStack[32]->SetFillStyle(3004);
ModeStack[32]->SetLineColor(kBlue + 3);
// ModeStack[33]->SetTitle("#it{#nu + n #rightarrow #nu + p + #pi^{-}}");
ModeStack[33]->SetTitle("NC1#pi^{-} on n");
ModeStack[33]->SetFillColor(kBlue - 2);
// ModeStack[33]->SetFillStyle(3005);
ModeStack[33]->SetLineColor(kBlue - 2);
// ModeStack[34]->SetTitle("#it{#nu + p #rightarrow #nu + n + #pi^{+}}");
ModeStack[34]->SetTitle("NC1#pi^{+} on p");
ModeStack[34]->SetFillColor(kBlue - 8);
// ModeStack[34]->SetFillStyle(3005);
ModeStack[34]->SetLineColor(kBlue - 8);
ModeStack[36]->SetTitle("NC Coherent");
ModeStack[36]->SetFillColor(kBlue + 8);
// ModeStack[36]->SetFillStyle(3644);
ModeStack[36]->SetLineColor(kBlue + 8);
// ModeStack[38]->SetTitle("#it{#nu + n #rightarrow #nu + n + #gamma}");
ModeStack[38]->SetTitle("NC1#gamma on n");
ModeStack[38]->SetFillColor(kMagenta);
// ModeStack[38]->SetFillStyle(3001);
ModeStack[38]->SetLineColor(kMagenta);
// ModeStack[39]->SetTitle("#it{#nu + p #rightarrow #nu + p + #gamma}");
ModeStack[39]->SetTitle("NC1#gamma on p");
ModeStack[39]->SetFillColor(kMagenta - 10);
// ModeStack[39]->SetFillStyle(3001);
ModeStack[39]->SetLineColor(kMagenta - 10);
ModeStack[41]->SetTitle("Multi #pi (1.3 < W < 2.0)");
ModeStack[41]->SetFillColor(kBlue - 10);
// ModeStack[41]->SetFillStyle(3005);
ModeStack[41]->SetLineColor(kBlue - 10);
// ModeStack[42]->SetTitle("#it{#nu + n #rightarrow #nu + n + #eta^{0}}");
ModeStack[42]->SetTitle("NC1#eta^{0} on n");
ModeStack[42]->SetFillColor(kYellow - 2);
// ModeStack[42]->SetFillStyle(3013);
ModeStack[42]->SetLineColor(kYellow - 2);
// ModeStack[43]->SetTitle("#it{#nu + p #rightarrow #nu + p + #eta^{0}}");
ModeStack[43]->SetTitle("NC1#eta^{0} on p");
ModeStack[43]->SetFillColor(kYellow - 4);
// ModeStack[43]->SetFillStyle(3013);
ModeStack[43]->SetLineColor(kYellow - 4);
// ModeStack[44]->SetTitle("#it{#nu + n #rightarrow #nu + #Lambda + K^{0}}");
ModeStack[44]->SetTitle("NC1#Lambda1K^{0} on n");
ModeStack[44]->SetFillColor(kYellow - 6);
// ModeStack[44]->SetFillStyle(3014);
ModeStack[44]->SetLineColor(kYellow - 6);
// ModeStack[45]->SetTitle("#it{#nu + p #rightarrow #nu + #Lambda + K^{+}}");
ModeStack[45]->SetTitle("NC1#Lambda1K^{+}");
ModeStack[45]->SetFillColor(kYellow - 10);
// ModeStack[45]->SetFillStyle(3014);
ModeStack[45]->SetLineColor(kYellow - 10);
ModeStack[46]->SetTitle("DIS (W > 2.0)");
ModeStack[46]->SetFillColor(kRed);
// ModeStack[46]->SetFillStyle(3006);
ModeStack[46]->SetLineColor(kRed);
// ModeStack[51]->SetTitle("#it{#nu + p #rightarrow #nu + p}");
ModeStack[51]->SetTitle("NC on p");
ModeStack[51]->SetFillColor(kBlack);
// ModeStack[51]->SetFillStyle(3444);
ModeStack[51]->SetLineColor(kBlack);
// ModeStack[52]->SetTitle("#it{#nu + n #rightarrow #nu + n}");
ModeStack[52]->SetTitle("NC on n");
ModeStack[52]->SetFillColor(kGray);
// ModeStack[52]->SetFillStyle(3444);
ModeStack[52]->SetLineColor(kGray);
return allmodes;
};
TLegend PlotUtils::GenerateStackLegend(THStack stack, int xlow, int ylow,
int xhigh, int yhigh) {
TLegend leg = TLegend(xlow, ylow, xhigh, yhigh);
TObjArray* histarray = stack.GetStack();
int nhist = histarray->GetEntries();
for (int i = 0; i < nhist; i++) {
TH1* hist = (TH1*)(histarray->At(i));
leg.AddEntry((hist), ((TH1*)histarray->At(i))->GetTitle(), "fl");
}
leg.SetName(Form("%s_LEG", stack.GetName()));
return leg;
};
void PlotUtils::ScaleNeutModeArray(TH1* hist[], double factor,
std::string option) {
for (int i = 0; i < 60; i++) {
if (hist[i]) hist[i]->Scale(factor, option.c_str());
}
return;
};
void PlotUtils::ResetNeutModeArray(TH1* hist[]) {
for (int i = 0; i < 60; i++) {
if (hist[i]) hist[i]->Reset();
}
return;
};
//********************************************************************
// This assumes the Enu axis is the x axis, as is the case for MiniBooNE 2D
// distributions
void PlotUtils::FluxUnfoldedScaling(TH2D* fMCHist, TH1D* fhist, TH1D* ehist,
double scalefactor) {
//********************************************************************
// Make clones to avoid changing stuff
TH1D* eventhist = (TH1D*)ehist->Clone();
TH1D* fFluxHist = (TH1D*)fhist->Clone();
// Undo width integral in SF
fMCHist->Scale(scalefactor /
eventhist->Integral(1, eventhist->GetNbinsX() + 1, "width"));
// Standardise The Flux
eventhist->Scale(1.0 / fFluxHist->Integral());
fFluxHist->Scale(1.0 / fFluxHist->Integral());
// Do interpolation for 2D plots?
// fFluxHist = PlotUtils::InterpolateFineHistogram(fFluxHist,100,"width");
// eventhist = PlotUtils::InterpolateFineHistogram(eventhist,100,"width");
// eventhist->Scale(1.0/fFluxHist->Integral());
// fFluxHist->Scale(1.0/fFluxHist->Integral());
// Scale fMCHist by eventhist integral
fMCHist->Scale(eventhist->Integral(1, eventhist->GetNbinsX() + 1));
// Now Get a flux PDF assuming X axis is Enu
TH1D* pdfflux = (TH1D*)fMCHist->ProjectionX()->Clone();
// pdfflux->Write( (std::string(fMCHist->GetName()) + "_PROJX").c_str());
pdfflux->Reset();
// Awful MiniBooNE Check for the time being
bool ismb =
std::string(fMCHist->GetName()).find("MiniBooNE") != std::string::npos;
for (int i = 0; i < pdfflux->GetNbinsX(); i++) {
double Ml = pdfflux->GetXaxis()->GetBinLowEdge(i + 1);
double Mh = pdfflux->GetXaxis()->GetBinLowEdge(i + 2);
// double Mc = pdfflux->GetXaxis()->GetBinCenter(i+1);
// double Mw = pdfflux->GetBinWidth(i+1);
double fluxint = 0.0;
// Scaling to match flux for MB
if (ismb) {
Ml /= 1.E3;
Mh /= 1.E3;
// Mc /= 1.E3;
// Mw /= 1.E3;
}
for (int j = 0; j < fFluxHist->GetNbinsX(); j++) {
// double Fc = fFluxHist->GetXaxis()->GetBinCenter(j+1);
double Fl = fFluxHist->GetXaxis()->GetBinLowEdge(j + 1);
double Fh = fFluxHist->GetXaxis()->GetBinLowEdge(j + 2);
double Fe = fFluxHist->GetBinContent(j + 1);
double Fw = fFluxHist->GetXaxis()->GetBinWidth(j + 1);
if (Fl >= Ml and Fh <= Mh) {
fluxint += Fe;
} else if (Fl < Ml and Fl < Mh and Fh > Ml and Fh < Mh) {
fluxint += Fe * (Fh - Ml) / Fw;
} else if (Fh > Mh and Fl < Mh and Fh > Ml and Fl > Ml) {
fluxint += Fe * (Mh - Fl) / Fw;
} else if (Ml >= Fl and Mh <= Fh) {
fluxint += Fe * (Mh - Ml) / Fw;
} else {
continue;
}
}
pdfflux->SetBinContent(i + 1, fluxint);
}
for (int i = 0; i < fMCHist->GetNbinsX(); i++) {
for (int j = 0; j < fMCHist->GetNbinsY(); j++) {
if (pdfflux->GetBinContent(i + 1) == 0.0) continue;
double binWidth = fMCHist->GetYaxis()->GetBinLowEdge(j + 2) -
fMCHist->GetYaxis()->GetBinLowEdge(j + 1);
fMCHist->SetBinContent(i + 1, j + 1,
fMCHist->GetBinContent(i + 1, j + 1) /
pdfflux->GetBinContent(i + 1) / binWidth);
fMCHist->SetBinError(i + 1, j + 1, fMCHist->GetBinError(i + 1, j + 1) /
pdfflux->GetBinContent(i + 1) /
binWidth);
}
}
delete eventhist;
delete fFluxHist;
return;
};
TH1D* PlotUtils::InterpolateFineHistogram(TH1D* hist, int res,
std::string opt) {
int nbins = hist->GetNbinsX();
double elow = hist->GetXaxis()->GetBinLowEdge(1);
double ehigh = hist->GetXaxis()->GetBinLowEdge(nbins + 1);
bool width = true; // opt.find("width") != std::string::npos;
TH1D* fine = new TH1D("fine", "fine", nbins * res, elow, ehigh);
TGraph* temp = new TGraph();
for (int i = 0; i < nbins; i++) {
double E = hist->GetXaxis()->GetBinCenter(i + 1);
double C = hist->GetBinContent(i + 1);
double W = hist->GetXaxis()->GetBinWidth(i + 1);
if (!width) W = 1.0;
if (W != 0.0) temp->SetPoint(temp->GetN(), E, C / W);
}
for (int i = 0; i < fine->GetNbinsX(); i++) {
double E = fine->GetXaxis()->GetBinCenter(i + 1);
double W = fine->GetBinWidth(i + 1);
if (!width) W = 1.0;
fine->SetBinContent(i + 1, temp->Eval(E, 0, "S") * W);
}
fine->Scale(hist->Integral(1, hist->GetNbinsX() + 1) /
fine->Integral(1, fine->GetNbinsX() + 1));
std::cout << "Interpolation Difference = "
<< fine->Integral(1, fine->GetNbinsX() + 1) << "/"
<< hist->Integral(1, hist->GetNbinsX() + 1) << std::endl;
return fine;
}
//********************************************************************
// This interpolates the flux by a TGraph instead of requiring the flux and MC
// flux to have the same binning
void PlotUtils::FluxUnfoldedScaling(TH1D* mcHist, TH1D* fhist, TH1D* ehist,
double scalefactor, int nevents) {
//********************************************************************
TH1D* eventhist = (TH1D*)ehist->Clone();
TH1D* fFluxHist = (TH1D*)fhist->Clone();
if (FitPar::Config().GetParB("save_flux_debug")) {
std::string name = std::string(mcHist->GetName());
mcHist->Write((name + "_UNF_MC").c_str());
fFluxHist->Write((name + "_UNF_FLUX").c_str());
eventhist->Write((name + "_UNF_EVT").c_str());
TH1D* scalehist = new TH1D("scalehist", "scalehist", 1, 0.0, 1.0);
scalehist->SetBinContent(1, scalefactor);
scalehist->SetBinContent(2, nevents);
scalehist->Write((name + "_UNF_SCALE").c_str());
}
// Undo width integral in SF
mcHist->Scale(scalefactor /
eventhist->Integral(1, eventhist->GetNbinsX() + 1, "width"));
// Standardise The Flux
eventhist->Scale(1.0 / fFluxHist->Integral());
fFluxHist->Scale(1.0 / fFluxHist->Integral());
// Scale mcHist by eventhist integral
mcHist->Scale(eventhist->Integral(1, eventhist->GetNbinsX() + 1));
// Now Get a flux PDF
TH1D* pdfflux = (TH1D*)mcHist->Clone();
pdfflux->Reset();
for (int i = 0; i < mcHist->GetNbinsX(); i++) {
double Ml = mcHist->GetXaxis()->GetBinLowEdge(i + 1);
double Mh = mcHist->GetXaxis()->GetBinLowEdge(i + 2);
// double Mc = mcHist->GetXaxis()->GetBinCenter(i+1);
// double Me = mcHist->GetBinContent(i+1);
// double Mw = mcHist->GetBinWidth(i+1);
double fluxint = 0.0;
for (int j = 0; j < fFluxHist->GetNbinsX(); j++) {
// double Fc = fFluxHist->GetXaxis()->GetBinCenter(j+1);
double Fl = fFluxHist->GetXaxis()->GetBinLowEdge(j + 1);
double Fh = fFluxHist->GetXaxis()->GetBinLowEdge(j + 2);
double Fe = fFluxHist->GetBinContent(j + 1);
double Fw = fFluxHist->GetXaxis()->GetBinWidth(j + 1);
if (Fl >= Ml and Fh <= Mh) {
fluxint += Fe;
} else if (Fl < Ml and Fl < Mh and Fh > Ml and Fh < Mh) {
fluxint += Fe * (Fh - Ml) / Fw;
} else if (Fh > Mh and Fl < Mh and Fh > Ml and Fl > Ml) {
fluxint += Fe * (Mh - Fl) / Fw;
} else if (Ml >= Fl and Mh <= Fh) {
fluxint += Fe * (Mh - Ml) / Fw;
} else {
continue;
}
}
pdfflux->SetBinContent(i + 1, fluxint);
}
// Scale MC hist by pdfflux
for (int i = 0; i < mcHist->GetNbinsX(); i++) {
if (pdfflux->GetBinContent(i + 1) == 0.0) continue;
mcHist->SetBinContent(
i + 1, mcHist->GetBinContent(i + 1) / pdfflux->GetBinContent(i + 1));
mcHist->SetBinError(
i + 1, mcHist->GetBinError(i + 1) / pdfflux->GetBinContent(i + 1));
}
delete eventhist;
delete fFluxHist;
return;
};
// MOVE TO GENERAL UTILS
//********************************************************************
void PlotUtils::Set2DHistFromText(std::string dataFile, TH2* hist, double norm,
bool skipbins) {
//********************************************************************
std::string line;
std::ifstream data(dataFile.c_str(), std::ifstream::in);
int yBin = 0;
while (std::getline(data >> std::ws, line, '\n')) {
std::vector<double> entries = GeneralUtils::ParseToDbl(line, " ");
// Loop over entries and insert them into the histogram
for (uint xBin = 0; xBin < entries.size(); xBin++) {
if (!skipbins or entries[xBin] != -1.0)
hist->SetBinContent(xBin + 1, yBin + 1, entries[xBin] * norm);
}
yBin++;
}
return;
}
// MOVE TO GENERAL UTILS
TH1D* PlotUtils::GetTH1DFromFile(std::string dataFile, std::string title,
std::string fPlotTitles,
std::string alt_name) {
TH1D* tempPlot;
// If format is a root file
if (dataFile.find(".root") != std::string::npos) {
TFile* temp_infile = new TFile(dataFile.c_str(), "READ");
tempPlot = (TH1D*)temp_infile->Get(title.c_str());
tempPlot->SetDirectory(0);
temp_infile->Close();
delete temp_infile;
// Else its a space seperated txt file
} else {
// Make a TGraph Errors
TGraphErrors* gr = new TGraphErrors(dataFile.c_str(), "%lg %lg %lg");
if (gr->IsZombie()) {
exit(-1);
}
double* bins = gr->GetX();
double* values = gr->GetY();
double* errors = gr->GetEY();
int npoints = gr->GetN();
// Fill the histogram from it
tempPlot = new TH1D(title.c_str(), title.c_str(), npoints - 1, bins);
for (int i = 0; i < npoints; ++i) {
tempPlot->SetBinContent(i + 1, values[i]);
// If only two columns are present in the input file, use the sqrt(values)
// as the error
// equivalent to assuming that the error is statistical
if (!errors[i])
tempPlot->SetBinError(i + 1, sqrt(values[i]));
else
tempPlot->SetBinError(i + 1, errors[i]);
}
delete gr;
}
// Allow alternate naming for root files
if (!alt_name.empty()) {
tempPlot->SetNameTitle(alt_name.c_str(), alt_name.c_str());
}
// Allow alternate axis titles
if (!fPlotTitles.empty()) {
tempPlot->SetNameTitle(
tempPlot->GetName(),
(std::string(tempPlot->GetTitle()) + fPlotTitles).c_str());
}
return tempPlot;
};
TH1D* PlotUtils::GetRatioPlot(TH1D* hist1, TH1D* hist2) {
// make copy of first hist
TH1D* new_hist = (TH1D*)hist1->Clone();
// Do bins and errors ourselves as scales can go awkward
for (int i = 0; i < new_hist->GetNbinsX(); i++) {
if (hist2->GetBinContent(i + 1) == 0.0) {
new_hist->SetBinContent(i + 1, 0.0);
}
new_hist->SetBinContent(
i + 1, hist1->GetBinContent(i + 1) / hist2->GetBinContent(i + 1));
new_hist->SetBinError(
i + 1, hist1->GetBinError(i + 1) / hist2->GetBinContent(i + 1));
}
return new_hist;
};
TH1D* PlotUtils::GetRenormalisedPlot(TH1D* hist1, TH1D* hist2) {
// make copy of first hist
TH1D* new_hist = (TH1D*)hist1->Clone();
if (hist1->Integral("width") == 0 or hist2->Integral("width") == 0) {
new_hist->Reset();
return new_hist;
}
Double_t scaleF = hist2->Integral("width") / hist1->Integral("width");
new_hist->Scale(scaleF);
return new_hist;
};
TH1D* PlotUtils::GetShapePlot(TH1D* hist1) {
// make copy of first hist
TH1D* new_hist = (TH1D*)hist1->Clone();
if (hist1->Integral("width") == 0) {
new_hist->Reset();
return new_hist;
}
Double_t scaleF1 = 1.0 / hist1->Integral("width");
new_hist->Scale(scaleF1);
return new_hist;
};
TH1D* PlotUtils::GetShapeRatio(TH1D* hist1, TH1D* hist2) {
TH1D* new_hist1 = GetShapePlot(hist1);
TH1D* new_hist2 = GetShapePlot(hist2);
// Do bins and errors ourselves as scales can go awkward
for (int i = 0; i < new_hist1->GetNbinsX(); i++) {
if (hist2->GetBinContent(i + 1) == 0) {
new_hist1->SetBinContent(i + 1, 0.0);
}
new_hist1->SetBinContent(i + 1, new_hist1->GetBinContent(i + 1) /
new_hist2->GetBinContent(i + 1));
new_hist1->SetBinError(
i + 1, new_hist1->GetBinError(i + 1) / new_hist2->GetBinContent(i + 1));
}
delete new_hist2;
return new_hist1;
};
TH2D* PlotUtils::GetCovarPlot(TMatrixDSym* cov, std::string name,
std::string title) {
TH2D* CovarPlot;
if (cov)
CovarPlot = new TH2D((*cov));
else
CovarPlot = new TH2D(name.c_str(), title.c_str(), 1, 0, 1, 1, 0, 1);
CovarPlot->SetName(name.c_str());
CovarPlot->SetTitle(title.c_str());
return CovarPlot;
}
TH2D* PlotUtils::GetFullCovarPlot(TMatrixDSym* cov, std::string name) {
return PlotUtils::GetCovarPlot(
cov, name + "_COV", name + "_COV;Bins;Bins;Covariance (#times10^{-76})");
}
TH2D* PlotUtils::GetInvCovarPlot(TMatrixDSym* cov, std::string name) {
return PlotUtils::GetCovarPlot(
cov, name + "_INVCOV",
name + "_INVCOV;Bins;Bins;Inv. Covariance (#times10^{-76})");
}
TH2D* PlotUtils::GetDecompCovarPlot(TMatrixDSym* cov, std::string name) {
return PlotUtils::GetCovarPlot(
cov, name + "_DECCOV",
name + "_DECCOV;Bins;Bins;Decomp Covariance (#times10^{-76})");
}
TH1D* PlotUtils::GetTH1DFromRootFile(std::string file, std::string name) {
if (name.empty()) {
std::vector<std::string> tempfile = GeneralUtils::ParseToStr(file, ";");
file = tempfile[0];
name = tempfile[1];
}
TFile* rootHistFile = new TFile(file.c_str(), "READ");
TH1D* tempHist = (TH1D*)rootHistFile->Get(name.c_str())->Clone();
+ if (tempHist == NULL) {
+ ERR(FTL) << "Could not find distribution " << name << " in file " << file << std::endl;
+ throw;
+ }
tempHist->SetDirectory(0);
rootHistFile->Close();
return tempHist;
}
TH2D* PlotUtils::GetTH2DFromRootFile(std::string file, std::string name) {
if (name.empty()) {
std::vector<std::string> tempfile = GeneralUtils::ParseToStr(file, ";");
file = tempfile[0];
name = tempfile[1];
}
TFile* rootHistFile = new TFile(file.c_str(), "READ");
TH2D* tempHist = (TH2D*)rootHistFile->Get(name.c_str())->Clone();
tempHist->SetDirectory(0);
rootHistFile->Close();
delete rootHistFile;
return tempHist;
}
TH1* PlotUtils::GetTH1FromRootFile(std::string file, std::string name) {
if (name.empty()) {
std::vector<std::string> tempfile = GeneralUtils::ParseToStr(file, ";");
file = tempfile[0];
name = tempfile[1];
}
TFile* rootHistFile = new TFile(file.c_str(), "READ");
if (!rootHistFile || rootHistFile->IsZombie()) {
THROW("Couldn't open root file: \"" << file << "\".");
}
TH1* tempHist = dynamic_cast<TH1*>(rootHistFile->Get(name.c_str())->Clone());
if (!tempHist) {
THROW("Couldn't retrieve: \"" << name << "\" from root file: \"" << file
<< "\".");
}
tempHist->SetDirectory(0);
rootHistFile->Close();
delete rootHistFile;
return tempHist;
}
TGraph* PlotUtils::GetTGraphFromRootFile(std::string file, std::string name) {
if (name.empty()) {
std::vector<std::string> tempfile = GeneralUtils::ParseToStr(file, ";");
file = tempfile[0];
name = tempfile[1];
}
TDirectory* olddir = gDirectory;
TFile* rootHistFile = new TFile(file.c_str(), "READ");
if (!rootHistFile || rootHistFile->IsZombie()) {
THROW("Couldn't open root file: \"" << file << "\".");
}
TDirectory* newdir = gDirectory;
TGraph* temp = dynamic_cast<TGraph*>(rootHistFile->Get(name.c_str())->Clone());
if (!temp) {
THROW("Couldn't retrieve: \"" << name << "\" from root file: \"" << file
<< "\".");
}
newdir->Remove(temp);
olddir->Append(temp);
rootHistFile->Close();
olddir->cd();
return temp;
}
/// Returns a vector of named TH1*s found in a single input file.
///
/// Expects a descriptor like: file.root[hist1|hist2|...]
std::vector<TH1*> PlotUtils::GetTH1sFromRootFile(
std::string const& descriptor) {
std::vector<std::string> descriptors =
GeneralUtils::ParseToStr(descriptor, ",");
std::vector<TH1*> hists;
for (size_t d_it = 0; d_it < descriptors.size(); ++d_it) {
std::string& d = descriptors[d_it];
std::vector<std::string> fname = GeneralUtils::ParseToStr(d, "[");
if (!fname.size() || !fname[0].length()) {
THROW("Couldn't find input file when attempting to parse : \""
<< d << "\". Expected input.root[hist1|hist2|...].");
}
if (fname[1][fname[1].length() - 1] == ']') {
fname[1] = fname[1].substr(0, fname[1].length() - 1);
}
std::vector<std::string> histnames =
GeneralUtils::ParseToStr(fname[1], "|");
if (!histnames.size()) {
THROW(
"Couldn't find any histogram name specifiers when attempting to "
"parse "
": \""
<< fname[1] << "\". Expected hist1|hist2|...");
}
TFile* rootHistFile = new TFile(fname[0].c_str(), "READ");
if (!rootHistFile || rootHistFile->IsZombie()) {
THROW("Couldn't open root file: \"" << fname[0] << "\".");
}
for (size_t i = 0; i < histnames.size(); ++i) {
TH1* tempHist =
dynamic_cast<TH1*>(rootHistFile->Get(histnames[i].c_str())->Clone());
if (!tempHist) {
THROW("Couldn't retrieve: \"" << histnames[i] << "\" from root file: \""
<< fname[0] << "\".");
}
tempHist->SetDirectory(0);
hists.push_back(tempHist);
}
rootHistFile->Close();
}
return hists;
}
TH2D* PlotUtils::GetTH2DFromTextFile(std::string file) {
/// Contents should be
/// Low Edfe
return NULL;
}
void PlotUtils::AddNeutModeArray(TH1D* hist1[], TH1D* hist2[], double scaling) {
for (int i = 0; i < 60; i++) {
if (!hist2[i]) continue;
if (!hist1[i]) continue;
hist1[i]->Add(hist2[i], scaling);
}
return;
}
void PlotUtils::ScaleToData(TH1D* data, TH1D* mc, TH1I* mask) {
double scaleF = GetDataMCRatio(data, mc, mask);
mc->Scale(scaleF);
return;
}
void PlotUtils::MaskBins(TH1D* hist, TH1I* mask) {
for (int i = 0; i < hist->GetNbinsX(); i++) {
if (mask->GetBinContent(i + 1) <= 0.5) continue;
hist->SetBinContent(i + 1, 0.0);
hist->SetBinError(i + 1, 0.0);
LOG(REC) << "MaskBins: Set " << hist->GetName() << " Bin " << i + 1
<< " to 0.0 +- 0.0" << std::endl;
}
return;
}
void PlotUtils::MaskBins(TH2D* hist, TH2I* mask) {
for (int i = 0; i < hist->GetNbinsX(); i++) {
for (int j = 0; j < hist->GetNbinsY(); j++) {
if (mask->GetBinContent(i + 1, j + 1) <= 0.5) continue;
hist->SetBinContent(i + 1, j + 1, 0.0);
hist->SetBinError(i + 1, j + 1, 0.0);
LOG(REC) << "MaskBins: Set " << hist->GetName() << " Bin " << i + 1 << " "
<< j + 1 << " to 0.0 +- 0.0" << std::endl;
}
}
return;
}
double PlotUtils::GetDataMCRatio(TH1D* data, TH1D* mc, TH1I* mask) {
double rat = 1.0;
TH1D* newmc = (TH1D*)mc->Clone();
TH1D* newdt = (TH1D*)data->Clone();
if (mask) {
MaskBins(newmc, mask);
MaskBins(newdt, mask);
}
rat = newdt->Integral() / newmc->Integral();
return rat;
}
TH2D* PlotUtils::GetCorrelationPlot(TH2D* cov, std::string name) {
TH2D* cor = (TH2D*)cov->Clone();
cor->Reset();
for (int i = 0; i < cov->GetNbinsX(); i++) {
for (int j = 0; j < cov->GetNbinsY(); j++) {
if (cov->GetBinContent(i + 1, i + 1) != 0.0 and
cov->GetBinContent(j + 1, j + 1) != 0.0)
cor->SetBinContent(i + 1, j + 1,
cov->GetBinContent(i + 1, j + 1) /
(sqrt(cov->GetBinContent(i + 1, i + 1) *
cov->GetBinContent(j + 1, j + 1))));
}
}
if (!name.empty()) {
cor->SetNameTitle(name.c_str(), (name + ";;correlation").c_str());
}
cor->SetMinimum(-1);
cor->SetMaximum(1);
return cor;
}
TH2D* PlotUtils::GetDecompPlot(TH2D* cov, std::string name) {
TMatrixDSym* covarmat = new TMatrixDSym(cov->GetNbinsX());
for (int i = 0; i < cov->GetNbinsX(); i++)
for (int j = 0; j < cov->GetNbinsY(); j++)
(*covarmat)(i, j) = cov->GetBinContent(i + 1, j + 1);
TMatrixDSym* decompmat = StatUtils::GetDecomp(covarmat);
TH2D* dec = (TH2D*)cov->Clone();
for (int i = 0; i < cov->GetNbinsX(); i++)
for (int j = 0; j < cov->GetNbinsY(); j++)
dec->SetBinContent(i + 1, j + 1, (*decompmat)(i, j));
delete covarmat;
delete decompmat;
dec->SetNameTitle(name.c_str(), (name + ";;;decomposition").c_str());
return dec;
}
TH2D* PlotUtils::MergeIntoTH2D(TH1D* xhist, TH1D* yhist, std::string zname) {
std::vector<double> xedges, yedges;
for (int i = 0; i < xhist->GetNbinsX() + 2; i++) {
xedges.push_back(xhist->GetXaxis()->GetBinLowEdge(i + 1));
}
for (int i = 0; i < yhist->GetNbinsX() + 2; i++) {
yedges.push_back(yhist->GetXaxis()->GetBinLowEdge(i + 1));
}
int nbinsx = xhist->GetNbinsX();
int nbinsy = yhist->GetNbinsX();
std::string name =
std::string(xhist->GetName()) + "_vs_" + std::string(yhist->GetName());
std::string titles = ";" + std::string(xhist->GetXaxis()->GetTitle()) + ";" +
std::string(yhist->GetXaxis()->GetTitle()) + ";" + zname;
TH2D* newplot = new TH2D(name.c_str(), (name + titles).c_str(), nbinsx,
&xedges[0], nbinsy, &yedges[0]);
return newplot;
}
//***************************************************
void PlotUtils::MatchEmptyBins(TH1D* data, TH1D* mc) {
//**************************************************
for (int i = 0; i < data->GetNbinsX(); i++) {
if (data->GetBinContent(i + 1) == 0.0 or data->GetBinError(i + 1) == 0.0)
mc->SetBinContent(i + 1, 0.0);
}
return;
}
//***************************************************
void PlotUtils::MatchEmptyBins(TH2D* data, TH2D* mc) {
//**************************************************
for (int i = 0; i < data->GetNbinsX(); i++) {
for (int j = 0; j < data->GetNbinsY(); j++) {
if (data->GetBinContent(i + 1, j + 1) == 0.0 or
data->GetBinError(i + 1, j + 1) == 0.0)
mc->SetBinContent(i + 1, j + 1, 0.0);
}
}
return;
}
//***************************************************
TH1D* PlotUtils::GetProjectionX(TH2D* hist, TH2I* mask) {
//***************************************************
TH2D* maskedhist = StatUtils::ApplyHistogramMasking(hist, mask);
TH1D* hist_X = maskedhist->ProjectionX();
delete maskedhist;
return hist_X;
}
//***************************************************
TH1D* PlotUtils::GetProjectionY(TH2D* hist, TH2I* mask) {
//***************************************************
TH2D* maskedhist = StatUtils::ApplyHistogramMasking(hist, mask);
TH1D* hist_Y = maskedhist->ProjectionY();
delete maskedhist;
return hist_Y;
}