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#include "TFile.h"
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#include "TNtuple.h"
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#include "TMath.h"
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#include "TMVA/Factory.h"
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#include "TMVA/Tools.h"
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#include "TMVA/Config.h"
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#include <unistd.h>
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#include <iostream>
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#include <fstream>
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#include <string.h>
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#include <map>
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#include <cassert>
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#include "KinematicsStruct.h"
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#include "HistHeaders.h"
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#include "filestuff.h"
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#include "ZZMatrixElement/MELA/interface/Mela.h"
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#include "ZZMatrixElement/MELA/interface/PseudoMELA.h"
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#include "ZZMatrixElement/MELA/src/computeAngles.h"
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using namespace std;
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void setTrainingVal(TString name, double *val, filestuff *fs);
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void setFractions(float mH, float mH_lo, float mH_hi, float &frac_lo, float &frac_hi);
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void setNevents(int nEvtMax, int nSigTrainMax, int nSigTestMax, int nBkgTrainMax, int nBkgTestMax, TString &nSig, TString &nBkg);
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int main(int argc, char** argv) {
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if( argc < 7 ) {
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cerr << "usage: makeBDTWeights.exe <config> <outputrootfile> <weightname> <varstring> <mH> [wL] [wH] [mH_lo] [mH_hi]" << endl;
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cerr << "\t... where [wL,wH] are the requested mass window and [mH_lo,mH_hi] are used for interpolation" << endl;
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return 1;
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}
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cout << "argc: " << argc << endl;
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for(int iarg=0; iarg<argc; iarg++)
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cout << "argv[" << iarg << "]: " << argv[iarg] << endl;
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char * config = argv[1];
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cout << "config: " << config << endl;
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// TString ntupledir;
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vector<TString> classes,fileNames,types,indirs,dsets,wgtStrs;
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vector<double> fileFracs,fileMasses;
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vector<TFile*> inFiles;
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vector<TTree*> inTrees;
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vector<filestuff*> fsv;
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bool multiclass(false);
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bool multisigs(false);
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bool noFakeTest(false);
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bool useMela(false);
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TString NTrees(""),NNodesMax(""),Shrinkage(""),nCuts(""),NormMode("");
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int nMax=1000000;
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ifstream ifs(config);
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assert(ifs.is_open());
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string line;
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while(getline(ifs,line)) {
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if(line[0]=='#') continue;
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stringstream ss(line);
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if(line[0]=='^') {
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TString dummy;
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// if(TString(line).Contains("^ntupledir")) ss >> dummy >> ntupledir;
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if(TString(line).Contains("^multiclass")){ multiclass = true; cout << "multiclass" << multiclass << endl; }
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if(TString(line).Contains("^multisigs" )){ multisigs = true; cout << "multisigs" << multisigs << endl; }
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if(TString(line).Contains("^noFakeTest")){ noFakeTest = true; cout << "noFakeTest" << noFakeTest << endl; }
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if(TString(line).Contains("^NTrees" )){ ss >> dummy >> NTrees; cout << "NTrees" << NTrees << endl; }
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if(TString(line).Contains("^NNodesMax" )){ ss >> dummy >> NNodesMax; cout << "NNodesMax" << NNodesMax << endl; }
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if(TString(line).Contains("^Shrinkage" )){ ss >> dummy >> Shrinkage; cout << "Shrinkage" << Shrinkage << endl; }
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if(TString(line).Contains("^nCuts" )){ ss >> dummy >> nCuts; cout << "nCuts" << nCuts << endl; }
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if(TString(line).Contains("^NormMode" )){ ss >> dummy >> NormMode; cout << "NormMode" << NormMode << endl; }
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if(TString(line).Contains("^nMax" )){ ss >> dummy >> nMax; cout << "nMax" << nMax << endl; }
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if(TString(line).Contains("^useMela" )){ useMela = true; cout << "useMela" << useMela << endl; }
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continue;
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}
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TString cls,indir,type,dset,wgtStr;
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double frac,fileMass;
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bool isdata;
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ss >> cls >> type >> frac >> wgtStr >> indir >> dset >> fileMass >> isdata;
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// assert(cls=="sig" || cls=="sig2" || cls=="sig3" || cls=="bkg");
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classes.push_back(cls);
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types.push_back(type);
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indirs.push_back(indir);
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dsets.push_back(dset);
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TString fname(indir+"/"+dset+"/merged.root");
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fsv.push_back(new filestuff(dset, fname, dset, isdata, 2012));
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fileNames.push_back(/*ntupledir+"/"+*/fname);
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fileFracs.push_back(frac);
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wgtStrs.push_back(wgtStr);
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fileMasses.push_back(fileMass);
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cout << " pushing back: " << cls << " " << setw(12) << frac << " " << fname << " " << fileMass << endl;
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inFiles.push_back(TFile::Open(fileNames.back()));
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if(!inFiles.back()->IsOpen()) {
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cout << fileNames.back() << " not open!" << endl;
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assert(0);
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}
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inTrees.push_back((TTree*)inFiles.back()->Get("zznt"));
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assert(inTrees.back());
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}
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ifs.close();
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char * outputrootfile = argv[2];
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char * weightname = argv[3];
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char * varstring = argv[4];
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float mH = strtof(argv[5],NULL);
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float wH=900, wL=100;
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if( argc > 6 ) {
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wL = strtof(argv[6], NULL);
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wH = strtof(argv[7], NULL);
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}
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float mH_lo=0,mH_hi=0;
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float frac_lo=1,frac_hi=1;
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map<double,double> mH_fracs;
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mH_fracs[-1] = 1; // this means zz
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assert( argc > 8);
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mH_lo = strtof(argv[8],NULL);
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mH_hi = strtof(argv[9],NULL);
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if(mH_lo!=0 && mH_hi!=0) {
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// set the fraction to use for each input file, with more events from the closer mass point
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// NOTE: we only use these fractions if the fraction from the config file is -1
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setFractions(mH,mH_lo,mH_hi,frac_lo,frac_hi);
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mH_fracs[mH_lo] = frac_lo;
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mH_fracs[mH_hi] = frac_hi;
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} else {
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mH_fracs[mH] = 1;
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}
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cerr
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<< "name: " << weightname << endl
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<< "output: " << outputrootfile << endl
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<< "variables: " << varstring << endl
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<< "mH: " << mH << endl
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<< "mass window:" << endl
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<< " wL: " << wL << endl
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<< " wH: " << wH << endl
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<< "masses from which to interpolate:" << endl
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<< " mH_lo: " << mH_lo << endl
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<< " mH_hi: " << mH_hi << endl
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<< "weights for interpolation:" << endl
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<< " frac_lo: " << frac_lo << endl
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<< " frac_hi: " << frac_hi << endl
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<< endl;
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// get the list of variables we're going to use
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vector<double> varVals;
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TString varStr(varstring);
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varStr.ReplaceAll(":"," ");
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vector<TString> vars,specs;
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stringstream ss(varStr.Data());
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while(!ss.eof()) {
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TString var;
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ss >> var;
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vars.push_back(var);
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cout << "VAR: " << var << endl;
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varVals.push_back(double(0));
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}
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specs.push_back("m4l"); varVals.push_back(double(0));
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specs.push_back("run"); varVals.push_back(double(0));
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specs.push_back("lumi"); varVals.push_back(double(0));
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specs.push_back("evt"); varVals.push_back(double(0));
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assert(varVals.size() == (vars.size() + specs.size()));
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TFile *outputFile = new TFile(outputrootfile, "RECREATE");
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TMVA::Tools::Instance();
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TString facStr("!V:!Silent:!DrawProgressBar");
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if(multiclass) facStr = facStr+":AnalysisType=multiclass";
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TMVA::Factory* factory = new TMVA::Factory(weightname, outputFile, facStr);
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for(unsigned ivar=0; ivar<vars.size(); ivar++) factory->AddVariable( vars[ivar], 'F');
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for(unsigned ispec=0; ispec<specs.size(); ispec++) factory->AddSpectator(specs[ispec], 'F');
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char buf[256];
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sprintf( buf, "(m4l>%f && m4l<%f)", (float)wL, (float)wH );
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TString cutStr(buf);
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cout << "cutStr: " << cutStr << endl;
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bool useWgts(true);
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vector<vector<TString> > files;
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vector<double> passFracs,nPassCutv,baseWgts;
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cout << setw(13) << "class" << setw(6) << "type" << setw(12) << " nPass " << setw(8) << "nTot" << setw(10) << " frac" << setw(12) << "baseWgt" << endl;
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for(unsigned ifile=0; ifile<fileNames.size(); ifile++) {
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if(fileFracs[ifile] == -1) fileFracs[ifile] = mH_fracs[fileMasses[ifile]];
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double nPass(0),nTot(0),passFrac(0);
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if(useWgts) {
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TH1D hPass("hPass","",100,0,1000);
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TH1D hTot("hTot","",100,0,1000);
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TString wgtStr(wgtStrs[ifile].Contains("wInterf") ? "1" : wgtStrs[ifile]); // tree doesn't have a wInterf leaf
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inTrees[ifile]->Draw("m4l>>hPass",wgtStr+"*"+cutStr);
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inTrees[ifile]->Draw("m4l>>hTot",wgtStr);
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passFrac = hPass.Integral() / hTot.Integral();
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nPass = hPass.Integral();
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nTot = hTot.Integral();
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} else {
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nPass = double(inTrees[ifile]->GetEntries(cutStr));
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passFrac = nPass / inTrees[ifile]->GetEntries();
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nTot = inTrees[ifile]->GetEntries();
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}
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passFracs.push_back(passFrac);
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nPassCutv.push_back(nPass);
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double baseWgt(fileFracs[ifile] / nPass);
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// if(fsv[ifile]->dataset_.Contains("fakes",TString::kIgnoreCase) && noFakeTest)
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// baseWgt /= 2; // if we're putting all the fakes into training, divide weights by two
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baseWgts.push_back(baseWgt);
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cout << setw(13) << classes[ifile] << "(" << setw(5) << types[ifile] << "): " << setw(10) << nPass << " / " << setw(12) << nTot
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<< setw(6) << setprecision(5) << fileFracs[ifile] << setw(15) << baseWgt
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<< setw(30) << dsets[ifile] << " " << indirs[ifile]
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<< endl;
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}
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Mela *mela(0);
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if(useMela) mela = new Mela(false, 8);
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for(unsigned ifs=0; ifs<fsv.size(); ifs++) {
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filestuff *fs = fsv[ifs];
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cout << "starting: " << fs->dataset_ << endl;
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double tot(0);
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for(unsigned ientry=0; ientry<fs->getentries("zznt"); ientry++) {
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fs->getentry(ientry,"kinematics","zznt");
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if(fs->kine->m4l < wL || fs->kine->m4l > wH) continue;
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fs->getentry(ientry,"","zznt");
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if(ientry<100)
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cout << fs->ji->nJets << endl;
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for(unsigned ivar=0; ivar<vars.size(); ivar++)
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setTrainingVal(vars[ivar], &varVals[ivar], fs);
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for(unsigned ispec=vars.size(); ispec<varVals.size(); ispec++)
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setTrainingVal(specs[ispec-vars.size()], &varVals[ispec], fs);
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// train on even events
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// if noFakeTest train on *all* the lljj events since we don't have many to start with
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double wgt(baseWgts[ifs]);
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if(wgtStrs[ifs] == "w") wgt *= fs->weights->w;
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else if(wgtStrs[ifs] == "1") wgt *= 1;
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else if(wgtStrs[ifs] == "wInterf") wgt *= getInterferenceWeight(fs,mela);
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else assert(0);
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if(wgt<.000000001 || wgt>5) { cout << "bad wgt?" << wgt << endl;}
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if((ientry%2)==0 || (fs->dataset_.Contains("fakes",TString::kIgnoreCase) && noFakeTest))
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factory->AddEvent(classes[ifs], TMVA::Types::kTraining, varVals, wgt);
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if((ientry%2)!=0)
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factory->AddEvent(classes[ifs], TMVA::Types::kTesting, varVals, wgt);
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tot += wgt;
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}
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cout << " " << tot << endl;
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}
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if(NTrees=="") NTrees = "10000";
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if(NNodesMax=="") NNodesMax = "10";
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if(Shrinkage=="") Shrinkage = "0.05";
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if(nCuts=="") nCuts = "20";
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if(NormMode=="") NormMode = "EqualNumEvents";
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assert(NormMode=="NumEvents" || NormMode=="EqualNumEvents");
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factory->PrepareTrainingAndTestTree( "", "SplitMode=Random:V:NormMode="+NormMode);
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factory->BookMethod( TMVA::Types::kBDT, "BDTG", "!H:V:NTrees="+NTrees
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+":NNodesMax="+NNodesMax
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+":BoostType=Grad:Shrinkage="+Shrinkage
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+":UseBaggedGrad:GradBaggingFraction=0.50:nCuts="+nCuts
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// +":nTrain_Signal=100:nTest_Signal=100:nTrain_Background=100:nTest_Background=100:nTrain_Signal2=100:nTest_Signal2=100"
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+":IgnoreNegWeights");
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factory->TrainAllMethods();
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factory->TestAllMethods();
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factory->EvaluateAllMethods();
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std::cerr << "closing ... " << std::endl;
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outputFile->Close();
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}
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//----------------------------------------------------------------------------------------
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void setFractions(float mH, float mH_lo, float mH_hi, float &frac_lo, float &frac_hi)
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{
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double delta = mH_hi - mH_lo;
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frac_lo = (mH_hi - mH)/delta;
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frac_hi = (mH - mH_lo)/delta;
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}
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//----------------------------------------------------------------------------------------
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void setNevents(int nEvtMax, int nSigTrainMax, int nSigTestMax, int nBkgTrainMax, int nBkgTestMax, TString &nSig, TString &nBkg)
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{
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// we want nEvtMax, but if there's fewer than this in any of the trees, we reduce our expectations
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| 281 |
if(fabs(nSigTrainMax-nSigTestMax)/double(nSigTrainMax) > 0.1) {
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assert(0);
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}
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if(fabs(nBkgTrainMax-nBkgTestMax)/double(nBkgTrainMax) > 0.1) {
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assert(0);
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}
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nEvtMax = min(nEvtMax,nSigTrainMax);
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nEvtMax = min(nEvtMax,nSigTestMax);
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nEvtMax = min(nEvtMax,nBkgTrainMax);
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nEvtMax = min(nEvtMax,nBkgTestMax);
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stringstream ss;
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ss << nEvtMax;
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ss >> nSig;
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nBkg = nSig;
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// ss << min(nSigTrainMax,nSigTestMax) << " " << min(nBkgTrainMax,nBkgTestMax);
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// ss >> nSig >> nBkg;
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}
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| 299 |
//----------------------------------------------------------------------------------------
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| 300 |
// void setTrainingVals(vector<TString> vars, vector<double> &varVals, vector<TString> specs, vector<double> &specVals, filestuff *fs)
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| 301 |
void setTrainingVal(TString name, double *val, filestuff *fs)
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| 302 |
{
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| 303 |
if(name=="costheta1") *val = fs->angles->costheta1;
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| 304 |
else if(name=="costheta2") *val = fs->angles->costheta2;
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| 305 |
else if(name=="costhetastar") *val = fs->angles->costhetastar;
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| 306 |
else if(name=="Phi") *val = fs->angles->Phi;
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| 307 |
else if(name=="Phi1") *val = fs->angles->Phi1;
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else if(name=="mZ1") *val = fs->kine->mZ1;
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| 309 |
else if(name=="mZ2") *val = fs->kine->mZ2;
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| 310 |
// pt variables
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// else if(name=="ZZpt/m4l") *val = fs->kine->ZZpt/fs->kine->m4l;
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// else if(name=="ZZdotZ1/(m4l*mZ1)") *val = fs->kine->ZZdotZ1/(fs->kine->m4l*fs->kine->mZ1);
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// else if(name=="ZZdotZ2/(m4l*mZ2)") *val = fs->kine->ZZdotZ2/(fs->kine->m4l*fs->kine->mZ2);
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else if(name=="ZZpt") *val = fs->kine->ZZpt/fs->kine->m4l;
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else if(name=="ZZdotZ1") *val = fs->kine->ZZdotZ1/(fs->kine->m4l*fs->kine->mZ1);
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else if(name=="ZZdotZ2") *val = fs->kine->ZZdotZ2/(fs->kine->m4l*fs->kine->mZ2);
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| 317 |
else if(name=="ZZptCosDphiZ1pt") *val = fs->kine->ZZptZ1ptCosDphi;
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| 318 |
else if(name=="ZZptCosDphiZ2pt") *val = fs->kine->ZZptZ2ptCosDphi;
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| 319 |
// else if(name=="Z1pt/m4l") *val = fs->kine->Z1pt/fs->kine->m4l;
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| 320 |
// else if(name=="Z2pt/m4l") *val = fs->kine->Z2pt/fs->kine->m4l;
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| 321 |
else if(name=="Z1pt") *val = fs->kine->Z1pt/fs->kine->m4l;
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| 322 |
else if(name=="Z2pt") *val = fs->kine->Z2pt/fs->kine->m4l;
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| 323 |
else if(name=="ZZy") *val = fs->kine->ZZy;
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| 324 |
// jet variables
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| 325 |
else if(name=="nJets" ) *val = fs->vk->getval("nJets");
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| 326 |
else if(name=="mjj" ) *val = fs->vk->getval("mjj");
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| 327 |
else if(name=="dEta" ) *val = fs->vk->getval("dEta");
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| 328 |
else if(name=="etaProd" ) *val = fs->vk->getval("etaProd");
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| 329 |
else if(name=="dphiJ1HiPtZ" ) *val = fs->vk->getval("dphiJ1HiPtZ");
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| 330 |
else if(name=="dphiJ1LoPtZ" ) *val = fs->vk->getval("dphiJ1LoPtZ");
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| 331 |
else if(name=="dEtaJ1HiPtZ" ) *val = fs->vk->getval("dEtaJ1HiPtZ");
|
| 332 |
else if(name=="dEtaJ1LoPtZ" ) *val = fs->vk->getval("dEtaJ1LoPtZ");
|
| 333 |
else if(name=="J1dotHiPtZ" ) *val = fs->vk->getval("J1dotHiPtZ");
|
| 334 |
else if(name=="J1dotLoPtZ" ) *val = fs->vk->getval("J1dotLoPtZ");
|
| 335 |
else if(name=="dphiJ2HiPtZ" ) *val = fs->vk->getval("dphiJ2HiPtZ");
|
| 336 |
else if(name=="dphiJ2LoPtZ" ) *val = fs->vk->getval("dphiJ2LoPtZ");
|
| 337 |
else if(name=="dEtaJ2HiPtZ" ) *val = fs->vk->getval("dEtaJ2HiPtZ");
|
| 338 |
else if(name=="dEtaJ2LoPtZ" ) *val = fs->vk->getval("dEtaJ2LoPtZ");
|
| 339 |
else if(name=="J2dotHiPtZ" ) *val = fs->vk->getval("J2dotHiPtZ");
|
| 340 |
else if(name=="J2dotLoPtZ" ) *val = fs->vk->getval("J2dotLoPtZ");
|
| 341 |
// spectators
|
| 342 |
else if(name=="m4l") *val = fs->kine->m4l;
|
| 343 |
else if(name=="run") *val = fs->info->run;
|
| 344 |
else if(name=="lumi") *val = fs->info->lumi;
|
| 345 |
else if(name=="evt") *val = fs->info->evt;
|
| 346 |
else { cout << name << " not found!" << endl; assert(0); }
|
| 347 |
}
|
