float AnalyzeResponseUniformity::getFitBoundary(std::string &strInputExp, std::shared_ptr<TH1F> hInput, TSpectrum &specInput){
//Variable Declaration
map<string, float> map_key2Val;
//Search the input expression for each of the supported keywords
//Store these Keywords with their values
for (int i=0; i < vec_strSupportedKeywords.size(); ++i) { //Loop Through Supported Keywords
if ( strInputExp.find( vec_strSupportedKeywords[i] ) != std::string::npos ) { //Case: Keyword Found!
map_key2Val[vec_strSupportedKeywords[i]] = getValByKeyword( vec_strSupportedKeywords[i], hInput, specInput );
} //End Case: Keyword Found!
} //End Loop Through Supported Keywords
//Check if map_key2Val has any entries, if so user requested complex expression; parse!
//If map_key2Val is empty, user has a numeric input; convert to float!
if (map_key2Val.size() > 0) { //Case: Complex Expression!
//Setup the expression parser
symbol_table_t symbol_table; //Stores the variables in expression and maps them to C++ objects
expression_t expression; //Stores the actual expression & the symbol table
parser_t parser; //Parses the information for evaluation
//Load all found keywords into the symbol table
for (auto iterMap = map_key2Val.begin(); iterMap != map_key2Val.end(); ++iterMap) {
symbol_table.add_variable( (*iterMap).first, (*iterMap).second);
}
//Give the expression the variables it should have
expression.register_symbol_table(symbol_table);
//Compile the parsing
parser.compile(strInputExp, expression);
//Return value to the user
return expression.value();
} //End Case: Complex Expression!
else{ //Case: Numeric Input
return stofSafe( strInputExp );
} //End Case: Numeric Input
} //End AnalyzeResponseUniformity::getFitBoundary()
//Uniformity
//Loads parameters defined in file read by inputFileStream and sets tehm to the aSetupUniformity
//Note this should only be called within the Uniformity heading if the user has configured the file correctly
void ParameterLoaderAnaysis::loadAnalysisParametersUniformity(ifstream &inputFileStream, AnalysisSetupUniformity &aSetupUniformity){
//Variable Declaration
bool bExitSuccess = false;
pair<string,string> pair_strParam; //Input file is setup in <Field, Value> pairs; not used here yet but placeholder
//string strField = ""; //From input file we have <Field,Value> pairs
string strLine = ""; //Line taken from the input file
//string strHeading = ""; //For storing detector heading
vector<string> vec_strList; //For storing char separated input; not used here yet but placeholder
if (bVerboseMode_IO) { //Case: User Requested Verbose Error Messages - I/O
printClassMethodMsg("ParameterLoaderAnaysis","loadAnalysisParametersUniformity", "Found Uniformity Heading");
} //End Case: User Requested Verbose Error Messages - I/O
while ( getlineNoSpaces(inputFileStream, strLine) ) {
//Does the user want to comment out this line?
if ( 0 == strLine.compare(0,1,"#") ) continue;
//Do we reach the end of the section?
if ( 0 == strLine.compare(strSecEnd_Uniformity ) ) break;
//Should we be storing histogram/fit setup parameters?
if ( 0 == strLine.compare(strSecBegin_Uniformity_Fit) ) { //Case: Fit Setup
loadAnalysisParametersFits(inputFileStream, aSetupUniformity.histoSetup_clustADC);
continue; //Tell it to move to the next loop iteration (e.g. line in file)
} //End Case: Fit Setup
else if( 0 == strLine.compare(strSecBegin_Uniformity_Histo) ){ //Case: Histo Setup
loadAnalysisParametersHistograms(inputFileStream, aSetupUniformity);
continue; //Tell it to move to the next loop iteration (e.g. line in file)
} //End Case: Histo Setup
//Debugging
cout<<"strLine: = " << strLine.c_str() << endl;
//Parse the line
pair_strParam = getParsedLine(strLine,bExitSuccess);
if (bExitSuccess) { //Case: Parameter Fetched Correctly
//transform(pair_strParam.first.begin(), pair_strParam.second.end(),pair_strParam.first.begin(),toupper);
string strTmp = pair_strParam.first;
transform(strTmp.begin(), strTmp.end(), strTmp.begin(), toupper);
pair_strParam.first = strTmp;
//cout<<pair_strParam.first<<"\t"<<pair_strParam.second;
if ( 0 == pair_strParam.first.compare("CUT_ADC_MIN") ) {
aSetupUniformity.selClust.iCut_ADCNoise = stoiSafe(pair_strParam.first,pair_strParam.second);
//cout<<"\t"<<aSetupUniformity.selClust.iCut_ADCNoise<<endl;
} //End Case: Minimum ADC Value
else if( 0 == pair_strParam.first.compare("CUT_CLUSTERMULTI_MIN") ){ //Case: Min Cluster Multiplicity
aSetupUniformity.selClust.iCut_MultiMin = stoiSafe(pair_strParam.first,pair_strParam.second);
} //End Case: Max Cluster Multiplicity
else if( 0 == pair_strParam.first.compare("CUT_CLUSTERMULTI_MAX") ){
aSetupUniformity.selClust.iCut_MultiMax = stoiSafe(pair_strParam.first,pair_strParam.second);
} //End Case:
else if( 0 == pair_strParam.first.compare("CUT_CLUSTERSIZE_MIN") ) {
aSetupUniformity.selClust.iCut_SizeMin = stoiSafe(pair_strParam.first,pair_strParam.second);
//cout<<"\t"<<aSetupUniformity.selClust.iCut_SizeMin<<endl;
} //End Case: Min Cluster Size
else if( 0 == pair_strParam.first.compare("CUT_CLUSTERSIZE_MAX") ) {
aSetupUniformity.selClust.iCut_SizeMax = stoiSafe(pair_strParam.first,pair_strParam.second);
//cout<<"\t"<<aSetupUniformity.selClust.iCut_SizeMax<<endl;
} //End Case: Max Cluster Size
else if( 0 == pair_strParam.first.compare("CUT_CLUSTERTIME_MIN") ) {
aSetupUniformity.selClust.iCut_TimeMin = stoiSafe(pair_strParam.first,pair_strParam.second);
//cout<<"\t"<<aSetupUniformity.selClust.iCut_TimeMin<<endl;
} //End Case: Min Cluster Time
else if( 0 == pair_strParam.first.compare("CUT_CLUSTERTIME_MAX") ) {
aSetupUniformity.selClust.iCut_TimeMax = stoiSafe(pair_strParam.first,pair_strParam.second);
//cout<<"\t"<<aSetupUniformity.selClust.iCut_TimeMax<<endl;
} //End Case: Max Cluster Time
if( 0 == pair_strParam.first.compare("EVENT_FIRST") ){ //Case: ADC Spectrum Fit Equation
aSetupUniformity.iEvt_First = stoiSafe(pair_strParam.second);
} //End Case: ADC Spectrum Fit Equation
else if( 0 == pair_strParam.first.compare("EVENT_TOTAL") ){ //Case: ADC Spectrum Fit Equation
aSetupUniformity.iEvt_Total = stoiSafe(pair_strParam.second);
} //End Case: ADC Spectrum Fit Equation
else if( 0 == pair_strParam.first.compare("UNIFORMITY_GRANULARITY") ){ //Case: Uniformity Granularity
aSetupUniformity.iUniformityGranularity = stoiSafe(pair_strParam.first,pair_strParam.second);
} //End Case: Uniformity Granularity
else if( 0 == pair_strParam.first.compare("UNIFORMITY_TOLERANCE") ){ //Case: Uniformity Granularity
aSetupUniformity.fUniformityTolerance = stofSafe(pair_strParam.first,pair_strParam.second);
} //End Case: Uniformity Granularity
else{ //Case: Parameter Not Recognized
printClassMethodMsg("ParameterLoaderAnaysis","loadAnalysisParametersUniformity","Error!!! Parameter Not Recognizd:\n");
printClassMethodMsg("ParameterLoaderAnaysis","loadAnalysisParametersUniformity",( "\tField = " + pair_strParam.first + "\n" ).c_str() );
printClassMethodMsg("ParameterLoaderAnaysis","loadAnalysisParametersUniformity",( "\tValue = " + pair_strParam.second + "\n" ).c_str() );
} //End Case: Parameter Not Recognized
} //End Case: Parameter Fetched Correctly
else{ //Case: Parameter Failed to fetch correctly
printClassMethodMsg("ParameterLoaderAnaysis","loadAnalysisParametersUniformity","Error!!! I didn't parse parameter correctly\n");
printClassMethodMsg("ParameterLoaderAnaysis","loadAnalysisParametersUniformity",("\tCurrent line: " + strLine).c_str() );
} //End Case: Parameter Failed to fetch correctly
} //End Loop through Uniformity Heading
return;
} //End ParameterLoaderAnaysis::loadAnalysisParametersUniformity()
TF1 AnalyzeResponseUniformity::getFit(int iEta, int iPhi, int iSlice, HistoSetup & setupHisto, shared_ptr<TH1F> hInput, TSpectrum &specInput ){
//Variable Declaration
float fLimit_Max = setupHisto.fHisto_xUpper, fLimit_Min = setupHisto.fHisto_xLower;
vector<string>::const_iterator iterVec_IGuess; //Iterator to use for setting initial guess of fit
vector<float> vec_fFitRange;
for (auto iterRange = aSetup.histoSetup_clustADC.vec_strFit_Range.begin(); iterRange != aSetup.histoSetup_clustADC.vec_strFit_Range.end(); ++iterRange) { //Loop Over Fit Range
vec_fFitRange.push_back( getFitBoundary( (*iterRange), hInput, specInput ) );
} //End Loop Over Fit Range
if (vec_fFitRange.size() > 1) {
fLimit_Min = (*std::min_element(vec_fFitRange.begin(), vec_fFitRange.end() ) );
fLimit_Max = (*std::max_element(vec_fFitRange.begin(), vec_fFitRange.end() ) );
}
TF1 ret_Func( getNameByIndex(iEta, iPhi, iSlice, "fit", setupHisto.strHisto_Name).c_str(), setupHisto.strFit_Formula.c_str(), fLimit_Min, fLimit_Max);
//Check to see if the number of parameters in the TF1 meets the expectation
if ( ret_Func.GetNpar() < setupHisto.vec_strFit_ParamIGuess.size() || ret_Func.GetNpar() < setupHisto.vec_strFit_ParamLimit_Min.size() || ret_Func.GetNpar() < setupHisto.vec_strFit_ParamLimit_Max.size() ) { //Case: Set points for initial parameters do not meet expectations
printClassMethodMsg("AnalyzeResponseUniformity","getFit","Error! Number of Parameters in Function Less Than Requested Initial Guess Parameters!");
printClassMethodMsg("AnalyzeResponseUniformity","getFit", ("\tNum Parameter: " + getString( ret_Func.GetNpar() ) ).c_str() );
printClassMethodMsg("AnalyzeResponseUniformity","getFit", ("\tNum Initial Guesses: " + getString( setupHisto.vec_strFit_ParamIGuess.size() ) ).c_str() );
printClassMethodMsg("AnalyzeResponseUniformity","getFit", ("\tNum Initial Guess Limits (Min): " + getString( setupHisto.vec_strFit_ParamLimit_Min.size() ) ).c_str() );
printClassMethodMsg("AnalyzeResponseUniformity","getFit", ("\tNum Initial Guess Limits (Max): " + getString( setupHisto.vec_strFit_ParamLimit_Max.size() ) ).c_str() );
printClassMethodMsg("AnalyzeResponseUniformity","getFit", "No Initial Parameters Have Been Set! Please Cross-Check Input Analysis Config File" );
return ret_Func;
} //End Case: Set points for initial parameters do not meet expectations
//Set Fit Parameters - Initial Value
//------------------------------------------------------
//Keywords are AMPLITUDE, MEAN, PEAK, SIGMA
for (int i=0; i<setupHisto.vec_strFit_ParamIGuess.size(); ++i) { //Loop over parameters - Initial Guess
iterVec_IGuess = std::find(vec_strSupportedKeywords.begin(), vec_strSupportedKeywords.end(), setupHisto.vec_strFit_ParamIGuess[i]);
if ( iterVec_IGuess == vec_strSupportedKeywords.end() ) { //Case: No Keyword Found; Try to set a Numeric Value
ret_Func.SetParameter(i, stofSafe( setupHisto.vec_strFit_ParamIGuess[i] ) );
} //End Case: No Keyword Found; Try to set a Numeric Value
else{ //Case: Keyword Found; Set Value based on Keyword
ret_Func.SetParameter(i, getValByKeyword( (*iterVec_IGuess), hInput, specInput ) );
} //End Case: Keyword Found; Set Value based on Keyword
} //End Loop over parameters - Initial Guess
//Set Fit Parameters - Boundaries
//------------------------------------------------------
if (setupHisto.vec_strFit_ParamLimit_Min.size() == setupHisto.vec_strFit_ParamLimit_Max.size() ) { //Check: Stored Parameter Limits Match
//Here we use vec_strFit_ParamLimit_Min but we know it has the same number of parameters as vec_strFit_ParamLimit_Max
//For each fit parameter, set the boundary
for (int i=0; i<setupHisto.vec_strFit_ParamLimit_Min.size(); ++i) { //Loop over boundary parameters
fLimit_Min = getFitBoundary(setupHisto.vec_strFit_ParamLimit_Min[i], hInput, specInput);
fLimit_Max = getFitBoundary(setupHisto.vec_strFit_ParamLimit_Max[i], hInput, specInput);
//cout<<"(fLimit_Min, fLimit_Max) = (" << fLimit_Min << ", " << fLimit_Max << ")\n";
(fLimit_Max > fLimit_Min) ? ret_Func.SetParLimits(i, fLimit_Min, fLimit_Max ) : ret_Func.SetParLimits(i, fLimit_Max, fLimit_Min );
} //End Loop over boundary parameters
} //End Check: Stored Parameter Limits Match
//Set Fit Parameters - Fixed?
//------------------------------------------------------
//Placeholder; maybe we add functionality in the future
//Set Other Fit Data Members
//------------------------------------------------------
ret_Func.SetLineColor(kRed);
ret_Func.SetLineWidth(3);
//Delete Pointers
//delete iterVec_IGuess;
//Return fit
//------------------------------------------------------
return ret_Func;
} //End AnalyzeResponseUniformity::getFit()
