lcsim-contrib/src/main/java/org/lcsim/contrib/sATLAS
diff -N TrackAnalysisDriver.java
--- /dev/null 1 Jan 1970 00:00:00 -0000
+++ TrackAnalysisDriver.java 28 Apr 2009 21:18:08 -0000 1.1
@@ -0,0 +1,648 @@
+/*
+ * To change this template, choose Tools | Templates
+ * and open the template in the editor.
+ */
+package org.lcsim.contrib.sATLAS;
+
+import org.lcsim.contrib.mgraham.sATLASDigi.*;
+import hep.aida.IHistogram1D;
+import hep.aida.IHistogramFactory;
+import hep.physics.matrix.SymmetricMatrix;
+import hep.physics.vec.BasicHep3Vector;
+import hep.physics.vec.Hep3Vector;
+
+import hep.physics.vec.VecOp;
+import java.util.ArrayList;
+import java.util.List;
+
+import java.util.Set;
+//import org.lcsim.contrib.Partridge.TrackingTest.FindableTrack.Ignore;
+//import org.lcsim.contrib.Partridge.TrackingTest.TrackAnalysis;
+import org.lcsim.contrib.mgraham.sATLASDigi.FindableTrack.Ignore;
+import org.lcsim.event.EventHeader;
+import org.lcsim.event.LCRelation;
+import org.lcsim.event.MCParticle;
+import org.lcsim.event.RelationalTable;
+import org.lcsim.event.Track;
+import org.lcsim.event.RawTrackerHit;
+import org.lcsim.event.SimTrackerHit;
+import org.lcsim.event.base.BaseRelationalTable;
+import org.lcsim.fit.helicaltrack.HelicalTrackCross;
+import org.lcsim.fit.helicaltrack.HelicalTrackFit;
+import org.lcsim.fit.helicaltrack.HelicalTrackHit;
+import org.lcsim.fit.helicaltrack.HelicalTrackStrip;
+import org.lcsim.fit.helicaltrack.HelixParamCalculator;
+import org.lcsim.fit.helicaltrack.HelixUtils;
+import org.lcsim.fit.helicaltrack.MultipleScatter;
+import org.lcsim.fit.helicaltrack.TrackDirection;
+import org.lcsim.recon.tracking.seedtracker.SeedCandidate;
+import org.lcsim.recon.tracking.seedtracker.SeedStrategy;
+import org.lcsim.recon.tracking.seedtracker.SeedTrack;
+import org.lcsim.recon.tracking.seedtracker.StrategyXMLUtils;
+import org.lcsim.util.Driver;
+import org.lcsim.util.aida.AIDA;
+
+/**
+ *
+ * @author partridge
+ */
+public class TrackAnalysisDriver extends Driver {
+
+ private AIDA aida = AIDA.defaultInstance();
+ private IHistogram1D pTeff1;
+ private IHistogram1D pTeff2;
+ private IHistogram1D thetaeff;
+ private IHistogram1D ctheff;
+ private IHistogram1D etaeff;
+ private IHistogram1D etafake;
+ private IHistogram1D d0eff1;
+ private IHistogram1D d0eff2;
+ private IHistogram1D z0eff1;
+ private IHistogram1D z0eff2;
+ private IHistogram1D fakes;
+ private IHistogram1D nfakes;
+ int trk_count = 0;
+ int nevt = 0;
+
+ public TrackAnalysisDriver() {
+
+ // Define the efficiency histograms
+ IHistogramFactory hf = aida.histogramFactory();
+ pTeff1 = hf.createHistogram1D("Efficiency vs pT", "", 100, 0., 5., "type=efficiency");
+ pTeff2 = hf.createHistogram1D("Efficiency vs pT full", "", 100, 0., 50., "type=efficiency");
+ thetaeff = hf.createHistogram1D("Efficiency vs theta", "", 72, 0., 180., "type=efficiency");
+ ctheff = hf.createHistogram1D("Efficiency vs cos(theta)", "", 50, -1., 1., "type=efficiency");
+ etaeff = hf.createHistogram1D("Efficiency vs eta", "", 50, -2., 2., "type=efficiency");
+ etafake = hf.createHistogram1D("Fake rate vs eta", "", 50, -2., 2., "type=efficiency");
+ d0eff1 = hf.createHistogram1D("Efficiency vs d0", "", 50, -5., 5., "type=efficiency");
+ d0eff2 = hf.createHistogram1D("Efficiency vs d0 full", "", 24, -12., 12., "type=efficiency");
+ z0eff1 = hf.createHistogram1D("Efficiency vs z0", "", 50, -5., 5., "type=efficiency");
+ z0eff2 = hf.createHistogram1D("Efficiency vs z0 full", "", 24, -12., 12., "type=efficiency");
+ fakes = hf.createHistogram1D("Number of mis-matched hits (unnormalized)", "", 10, 0., 10.);
+ nfakes = hf.createHistogram1D("Number of mis-matched hits (normalized)", "", 10, 0., 10.);
+
+ }
+
+ @Override
+ public void process(EventHeader event) {
+
+ // Increment the event counter
+ nevt++;
+
+ // Get the magnetic field
+ Hep3Vector IP = new BasicHep3Vector(0., 0., 0.);
+ double bfield = event.getDetector().getFieldMap().getField(IP).z();
+// dump SThit information
+
+ String[] input_hit_collections = {"VtxBarrHits", "VtxEndcapHits", "SCTShortBarrHits", "SCTLongBarrHits", "SCTShortEndcapHits", "SCTLongEndcapHits"};
+ for (String input : input_hit_collections) {
+ List<SimTrackerHit> sthits = event.getSimTrackerHits(input);
+ int[] nhits = {0, 0, 0, 0, 0, 0};
+ for (SimTrackerHit st : sthits) {
+ String detector = st.getDetectorElement().getName();
+ int layer = st.getLayerNumber();
+ double[] hp = st.getPoint();
+ Hep3Vector hitPos = new BasicHep3Vector(hp[0], hp[1], hp[2]);
+ double r = Math.sqrt(hp[0] * hp[0] + hp[1] * hp[1]);
+ double theta = Math.atan2(r, hp[2]);
+// double eta = -Math.log(r / (2 * Math.abs(hp[2])));
+ double eta = -Math.log(Math.tan(theta / 2));
+ double phi = Math.atan2(hp[1], hp[0]);
+// System.out.println("r= " + r + " theta = "+theta+" eta = " + eta+ " phi=" + phi);
+ nhits[layer]++;
+ aida.cloud1D(input + " layer " + layer + " STHit eta").fill(eta);
+ aida.cloud1D(input + " layer " + layer + " STHit phi").fill(phi);
+ aida.cloud2D(input + " layer " + layer + " STHit phi vs eta").fill(eta, phi);
+ aida.histogram2D(input + " layer " + layer + " STHit phi vs eta occupancy", 100, -2.5, 2.5, 100, -3.2, 3.2).fill(eta, phi);
+ }
+ int i = 0;
+ while (i < 6) {
+ if (nhits[i] > 0) {
+ aida.cloud1D(input + "layer " + i + " number of ST hits").fill(nhits[i]);
+ }
+ i++;
+ }
+ }
+
+ List<HelicalTrackHit> hthits = event.get(HelicalTrackHit.class, "HelicalTrackHits");
+ for (HelicalTrackHit HelTrHit : hthits) {
+ }
+
+ // Get the list of strategies being used
+// String sfile = "autogen_ttbar_sid02_vs.xml";
+// List<SeedStrategy> slist = StrategyXMLUtils.getStrategyListFromResource(
+// StrategyXMLUtils.getDefaultStrategiesPrefix() + sfile);
+
+ String sfile = StrategyXMLUtils.getDefaultStrategiesPrefix() + "sATLASBarrel-SM08.xml";
+ List<SeedStrategy> slist = StrategyXMLUtils.getStrategyListFromResource(sfile);
+
+ // Find the minimum pT among the strategies
+ double ptCut = 9999.;
+ for (SeedStrategy s : slist) {
+ if (s.getMinPT() < ptCut) {
+ ptCut = s.getMinPT();
+ }
+ }
+
+ // Create a relational table that maps TrackerHits to MCParticles
+ RelationalTable hittomc = new BaseRelationalTable(RelationalTable.Mode.MANY_TO_MANY, RelationalTable.Weighting.UNWEIGHTED);
+ List<LCRelation> mcrelations = event.get(LCRelation.class, "HelicalTrackMCRelations");
+ for (LCRelation relation : mcrelations) {
+ hittomc.add(relation.getFrom(), relation.getTo());
+ }
+
+ // Instantiate the class that determines if a track is "findable"
+ FindableTrack findable = new FindableTrack(event);
+
+ // Create a map between tracks and the associated MCParticle
+ List<Track> tracklist = event.getTracks();
+ RelationalTable trktomc = new BaseRelationalTable(RelationalTable.Mode.MANY_TO_MANY, RelationalTable.Weighting.UNWEIGHTED);
+
+ // Analyze the tracks in the event
+ for (Track track : tracklist) {
+
+ // Calculate the track pT and cos(theta)
+ double px = track.getPX();
+ double py = track.getPY();
+ double pz = track.getPZ();
+ double pt = Math.sqrt(px * px + py * py);
+ double cth = pz / Math.sqrt(pt * pt + pz * pz);
+ double th = Math.atan2(pt, pz);
+ double eta = -Math.log(Math.tan(th / 2));
+ double d0 = track.getTrackParameter(HelicalTrackFit.dcaIndex);
+ double z0 = track.getTrackParameter(HelicalTrackFit.z0Index);
+
+ SeedTrack st = (SeedTrack) track;
+
+ SeedCandidate seed = st.getSeedCandidate();
+
+ HelicalTrackFit helixTrack = seed.getHelix();
+ double[] chisq = helixTrack.chisq();
+ double nhchisq = helixTrack.nhchisq();
+ aida.cloud1D("Track Chi2-Circle Fit").fill(chisq[0]);
+ aida.cloud1D("Track Chi2-RZ Fit").fill(chisq[1]);
+ aida.cloud1D("NH Track Chi2").fill(nhchisq);
+ if (nhchisq != 0) {
+ aida.cloud1D("NH!=0 Track Chi2-Circle Fit").fill(chisq[0]);
+ aida.cloud1D("NH!=0 Track Chi2-RZ Fit").fill(chisq[1]);
+
+ }
+ List<HelicalTrackHit> hitlist = seed.getHits();
+ for (HelicalTrackHit hit : hitlist) {
+ int nhits = hit.getRawHits().size();
+ aida.cloud1D(hit.Detector() + " nHits").fill(nhits);
+ Hep3Vector HTHPos = hit.getCorrectedPosition();
+ double rHit = Math.sqrt(HTHPos.x() * HTHPos.x() + HTHPos.y() * HTHPos.y());
+ double zHit = HTHPos.z();
+ double etaHit = -Math.log(Math.tan(Math.atan2(rHit, zHit) / 2));
+// System.out.println("Looping over hit in " + hit.Detector());
+ double hitchisq = hit.chisq();
+ double s = helixTrack.PathMap().get(hit);
+ Hep3Vector posonhelix = HelixUtils.PointOnHelix(helixTrack, s);
+
+ if (hit instanceof HelicalTrackCross) {
+ HelicalTrackCross cross = (HelicalTrackCross) hit;
+ TrackDirection trkdir = HelixUtils.CalculateTrackDirection(helixTrack, s);
+ cross.setTrackDirection(trkdir, helixTrack.covariance());
+ List<HelicalTrackStrip> clusterlist = cross.getStrips();
+ double du_stereo = 0;
+ double du_axial = 0;
+ for (HelicalTrackStrip cluster : clusterlist) {
+ int nstrips = cluster.rawhits().size();
+ aida.cloud1D(hit.Detector() + " nStrips-per-layer").fill(nstrips);
+ Hep3Vector corigin = cluster.origin();
+ Hep3Vector u = cluster.u();
+ List<RawTrackerHit> rawhits = cluster.rawhits();
+ double umc = -999999;
+ double stenergy = -999999;
+ String stripdir = "axial";
+ double umeas = cluster.umeas();
+ double charge = cluster.dEdx();
+ double layer = cluster.layer();
+ for (RawTrackerHit rhit : rawhits) {
+ String deName = rhit.getDetectorElement().getName();
+ if (deName.contains("sensor1")) {
+ stripdir = "stereo";
+ }
+ // System.out.println("Layer number " + rhit.getLayerNumber() + " " + deName);
+ List<SimTrackerHit> sthits = rhit.getSimTrackerHits();
+ int nsthits = sthits.size();
+ aida.cloud1D(hit.Detector() + " associated ST hits").fill(nsthits);
+ aida.cloud1D(hit.Detector() + " layer" + stripdir + " associated ST hits").fill(nsthits);
+ if (nsthits == 1) {
+ double[] sthitD = sthits.get(0).getPoint();
+ BasicHep3Vector sthit = new BasicHep3Vector(sthitD);
+ stenergy = sthits.get(0).getdEdx();
+ Hep3Vector vdiff = VecOp.sub(sthit, corigin);
+ umc = VecOp.dot(vdiff, u);
+ }
+ }
+
+
+ aida.cloud2D(hit.Detector() + "clusterSize vs eta").fill(etaHit, nstrips);
+ // System.out.println("filling...");
+ if (umc != -999999) {
+ aida.cloud2D(hit.Detector() + "cluster vs STHit dedx").fill(stenergy, charge);
+ aida.cloud2D(hit.Detector() + "cluster dedx vs delte(u)").fill(umeas - umc, charge);
+ if (stripdir.contains("stereo")) {
+ du_stereo = umeas - umc;
+ }
+ if (stripdir.contains("axial")) {
+ du_axial = umeas - umc;
+ }
+ aida.cloud1D(hit.Detector() + "layer=" + stripdir + " delta(u)").fill(umeas - umc);
+ aida.cloud1D(hit.Detector() + " delta(u)").fill(umeas - umc);
+ if (nstrips == 1) {
+ aida.cloud1D(hit.Detector() + "layer=" + stripdir + " delta(u)--1 strip").fill(umeas - umc);
+ aida.cloud1D(hit.Detector() + " delta(u)--1 strip").fill(umeas - umc);
+ }
+ if (nstrips == 2) {
+ aida.cloud1D(hit.Detector() + "layer=" + stripdir + " delta(u)--2 strip").fill(umeas - umc);
+ aida.cloud1D(hit.Detector() + " delta(u)--2 strip").fill(umeas - umc);
+ }
+ if (nstrips == 3) {
+ aida.cloud1D(hit.Detector() + "layer=" + stripdir + " delta(u)--3 strip").fill(umeas - umc);
+ aida.cloud1D(hit.Detector() + " delta(u)--3 strip").fill(umeas - umc);
+ }
+ }
+
+ }
+ aida.cloud2D(hit.Detector() + " delta(u) stereo v axial").fill(du_stereo, du_axial);
+ }
+ MultipleScatter ms = seed.getMSMap().get(hit);
+ double msphi = ms.drphi();
+ double msz = ms.dz();
+ Hep3Vector hitpos = hit.getCorrectedPosition();
+ SymmetricMatrix cov = hit.getCorrectedCovMatrix();
+// double rHit = getr(hitpos.x(), hitpos.y());
+// double rHel = getr(posonhelix.x(), posonhelix.y());
+// double phiHet = getphi(hitpos.x(), hitpos.y());
+// double phiHel = getr(posonhelix.x(), posonhelix.y());
+ double dxdy = Math.sqrt(Math.pow(hitpos.x() - posonhelix.x(), 2) + Math.pow(hitpos.y() - posonhelix.y(), 2));
+ double dxdyErr = getdxdyErr(hitpos, posonhelix, cov);
+ double dz = posonhelix.z() - hitpos.z();
+
+ double dzErr = Math.sqrt(cov.e(2, 2));
+ aida.cloud1D(hit.Detector() + " dxdy").fill(dxdy);
+ aida.cloud1D(hit.Detector() + " dz").fill(dz);
+ aida.cloud1D(hit.Detector() + " dxdy Pull").fill(dxdy / dxdyErr);
+ aida.cloud1D(hit.Detector() + " dz Pull").fill(dz / dzErr);
+ if (Math.abs(dz) > 4) {
+ aida.cloud1D(hit.Detector() + "Bad dz--nHits").fill(nhits);
+ }
+ aida.cloud1D("NH Chi2 for Hits on Track").fill(hitchisq);
+ }
+
+ // Analyze the hits on the track
+ TrackAnalysis tkanal = new TrackAnalysis(track, hittomc);
+
+ // Calculate purity and make appropriate plots
+ int nbad = tkanal.getNBadHits();
+ int nhits = tkanal.getNHits();
+ double purity = tkanal.getPurity();
+ aida.histogram1D("Mis-matched hits for all tracks", 10, 0., 10.).fill(nbad);
+ aida.histogram1D("Mis-matched hits " + nhits + " hit tracks", 10, 0., 10.).fill(nbad);
+
+ // Generate a normalized histogram after 1000 events
+ trk_count++;
+ if (nevt <= 1000) {
+ fakes.fill(nbad);
+ }
+
+ // Make plots for fake, non-fake, and all tracks
+ if (purity < 0.5) {
+ aida.histogram1D("Hits for fake tracks", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for fake tracks", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for fake tracks", 100, -1., 1.).fill(cth);
+ aida.histogram1D("d0 for fake tracks", 50, -10., 10.).fill(d0);
+ aida.histogram1D("z0 for fake tracks", 50, -10., 10.).fill(z0);
+ aida.histogram1D("eta for fake tracks", 100, -2., 2.).fill(eta);
+ etafake.fill(eta, 1.0);
+ } else {
+ aida.histogram1D("Hits for non-fake tracks", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for non-fake tracks", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for non-fake tracks", 100, -1., 1.).fill(cth);
+ aida.histogram1D("d0 for non-fake tracks", 50, -10., 10.).fill(d0);
+ aida.histogram1D("z0 for non-fake tracks", 50, -10., 10.).fill(z0);
+ aida.histogram1D("eta for non-fake tracks", 100, -2., 2.).fill(eta);
+ etafake.fill(eta, 0.0);
+ }
+ aida.histogram1D("Hits for all tracks", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for all tracks", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for all tracks", 100, -1., 1.).fill(cth);
+ aida.histogram1D("d0 for all tracks", 50, -10., 10.).fill(d0);
+ aida.histogram1D("z0 for all tracks", 50, -10., 10.).fill(z0);
+ aida.histogram1D("eta for all tracks", 100, -2., 2.).fill(eta);
+ aida.cloud2D("Hits vs eta for all tracks").fill(eta, nhits);
+ // Now analyze MC Particles on this track
+ MCParticle mcp = tkanal.getMCParticle();
+ if (mcp != null) {
+
+ // Create a map between the tracks found and the assigned MC particle
+ trktomc.add(track, tkanal.getMCParticle());
+
+ // Calculate the MC momentum and polar angle
+ Hep3Vector pmc = mcp.getMomentum();
+ double pxmc = pmc.x();
+ double pymc = pmc.y();
+ double ptmc = Math.sqrt(pxmc * pxmc + pymc * pymc);
+ double pxtk = track.getPX();
+ double pytk = track.getPY();
+ double pttk = Math.sqrt(pxtk * pxtk + pytk * pytk);
+
+ // Calculate the helix parameters for this MC particle and pulls in pT, d0
+ HelixParamCalculator helix = new HelixParamCalculator(mcp, bfield);
+ double d0tk = track.getTrackParameter(HelicalTrackFit.dcaIndex);
+ double d0mc = helix.getDCA();
+ double d0err = Math.sqrt(track.getErrorMatrix().diagonal(HelicalTrackFit.dcaIndex));
+ double curv = track.getTrackParameter(HelicalTrackFit.curvatureIndex);
+ double curverr = Math.sqrt(track.getErrorMatrix().diagonal(HelicalTrackFit.curvatureIndex));
+ double pterr = pttk * curverr / curv;
+ double d0pull = (d0tk - d0mc) / d0err;
+ double ptpull = (pttk - ptmc) / pterr;
+ double ptresid = (pttk - ptmc);
+ double d0resid = (d0tk - d0mc);
+ // Plot the pt and d0 pulls for various purity intervals
+ if (nbad == 0) {
+ aida.histogram2D("pT MC vs pT Reco for 0 Bad Hits",
+ 100, 0., 5., 100, 0., 5.).fill(ptmc, pttk);
+ aida.histogram2D("d0 MC vs d0 Reco for 0 Bad Hits",
+ 100, -0.2, 0.2, 100, -0.2, 0.2).fill(d0mc, d0tk);
+ aida.histogram1D("pT Pull for 0 Bad Hits", 100, -10., 10.).fill(ptpull);
+ aida.histogram1D("d0 pull for 0 Bad Hits", 100, -10., 10.).fill(d0pull);
+ aida.cloud1D("pT Residual for 0 Bad Hits").fill(ptresid);
+ aida.cloud1D("d0 Residual for 0 Bad Hits").fill(d0resid);
+
+ } else if (purity > 0.5) {
+ aida.histogram2D("pT MC vs pT Reco for 0.5 < purity < 1",
+ 100, 0., 5., 100, 0., 5.).fill(ptmc, pttk);
+ aida.histogram2D("d0 MC vs d0 Reco for 0.5 < purity < 1",
+ 100, -0.2, 0.2, 100, -0.2, 0.2).fill(d0mc, d0tk);
+ aida.histogram1D("pT Pull for 0.5 < purity < 1", 100, -10., 10.).fill(ptpull);
+ aida.histogram1D("d0 pull for 0.5 < purity < 1", 100, -10., 10.).fill(d0pull);
+ aida.cloud1D("pT Residual for 0.5 < purity < 1").fill(ptresid);
+ aida.cloud1D("d0 Residual for 0.5 < purity < 1").fill(d0resid);
+ } else if (purity < 0.5) {
+ aida.histogram2D("pT MC vs pT Reco for purity <= 0.5",
+ 100, 0., 5., 100, 0., 5.).fill(ptmc, pttk);
+ aida.histogram2D("d0 MC vs d0 Reco for purity <= 0.5",
+ 100, -0.2, 0.2, 100, -0.2, 0.2).fill(d0mc, d0tk);
+ aida.histogram1D("pT Pull for purity <= 0.5", 100, -10., 10.).fill(ptpull);
+ aida.histogram1D("d0 pull for purity <= 0.5", 100, -10., 10.).fill(d0pull);
+ aida.cloud1D("pT Residual for purity <= 0.5").fill(ptresid);
+ aida.cloud1D("d0 Residial for purity <= 0.5").fill(d0resid);
+ }
+ }
+ }
+
+ // Make the normalized fake plot after the specified number of events
+ if (nevt == 1000) {
+ double wgt = 1. / trk_count;
+ for (int i = 0; i < 10; i++) {
+ System.out.println(" Entries: " + fakes.binEntries(i) + " for mismatches: " + i);
+ for (int j = 0; j < fakes.binHeight(i); j++) {
+ nfakes.fill(i, wgt);
+ }
+ }
+ System.out.println("Normalization: " + nfakes.sumAllBinHeights() + " after ntrk = " + trk_count);
+ }
+
+ // Now loop over all MC Particles
+ List<MCParticle> mclist = event.getMCParticles();
+ for (MCParticle mcp : mclist) {
+
+ // Calculate the pT and polar angle of the MC particle
+ double px = mcp.getPX();
+ double py = mcp.getPY();
+ double pz = mcp.getPZ();
+ double pt = Math.sqrt(px * px + py * py);
+ double p = Math.sqrt(pt * pt + pz * pz);
+ double cth = pz / p;
+ double theta = 180. * Math.acos(cth) / Math.PI;
+ double eta = -Math.log(Math.tan(Math.atan2(pt, pz) / 2));
+ // Find the number of layers hit by this mc particle
+// System.out.println("MC pt=" + pt);
+ int nhits = findable.LayersHit(mcp);
+
+ // Calculate the helix parameters for this MC particle
+ HelixParamCalculator helix = new HelixParamCalculator(mcp, bfield);
+ double d0 = helix.getDCA();
+ double z0 = helix.getZ0();
+
+ // Check cases where we have multiple tracks associated with this MC particle
+ Set<Track> trklist = trktomc.allTo(mcp);
+ int ntrk = trklist.size();
+// if (ntrk > 1) {
+ // Count tracks where the assigned MC particle has more than 1 hit
+// int nmulthits = 0;
+// for (Track trk : trklist) {
+// TrackAnalysis tkanal = new TrackAnalysis(trk, hittomc);
+// if (tkanal.getNBadHits() < tkanal.getNHits() - 1)
+// nmulthits++;
+// }
+ // Flag any anomalous cases that we find
+// if (nmulthits > 1) {
+// System.out.println("2 tracks associated with a single MC Particle");
+// for (Track trk : trklist) System.out.println(trk.toString());
+// }
+// }
+
+ // Make pT efficiency plot
+ if (findable.isFindable(mcp, slist, Ignore.NoPTCut)) {
+ double wgt = 0.;
+ if (ntrk > 0) {
+ wgt = 1.;
+ }
+ pTeff1.fill(pt, wgt);
+ pTeff2.fill(pt, wgt);
+ }
+
+ // Make angular efficiency plot
+ if (findable.isFindable(mcp, slist)) {
+ double wgt = 0.;
+ if (ntrk > 0) {
+ wgt = 1.;
+ }
+ thetaeff.fill(theta, wgt);
+ ctheff.fill(cth, wgt);
+ etaeff.fill(eta, wgt);
+ }
+
+ // Make d0 efficiency plot
+ if (findable.isFindable(mcp, slist, Ignore.NoDCACut)) {
+ double wgt = 0.;
+ if (ntrk > 0) {
+ wgt = 1.;
+ }
+ d0eff1.fill(d0, wgt);
+ d0eff2.fill(d0, wgt);
+ }
+
+ // Make z0 efficiency plot
+ if (findable.isFindable(mcp, slist, Ignore.NoZ0Cut)) {
+ double wgt = 0.;
+ if (ntrk > 0) {
+ wgt = 1.;
+ }
+ z0eff1.fill(z0, wgt);
+ z0eff2.fill(z0, wgt);
+ }
+
+ // Select charged MC particles
+ if (mcp.getCharge() == 0) {
+ continue;
+ }
+
+ // Select mcp that fail the final state requirement
+ if (mcp.getGeneratorStatus() != mcp.FINAL_STATE) {
+ aida.histogram1D("Hits for non-final state particles", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for non-final state particles", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for non-final state particles", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for non-final state particles", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for non-final state particles", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for non-final state particles", 100, -100., 100.).fill(z0);
+ aida.cloud2D("Hits vs eta for non-final state particles").fill(eta, nhits);
+ continue;
+ }
+
+ // Make plots for the base sample
+ aida.histogram1D("Hits for base MC selection", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for base MC selection", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for base MC selection", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for base MC selection", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for base MC selection", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for base MC selection", 100, -100., 100.).fill(z0);
+ aida.cloud2D("Hits vs eta for base MC selection").fill(eta, nhits);
+
+ // Make plots for findable tracks
+ if (findable.isFindable(mcp, slist)) {
+ aida.histogram1D("Hits for findable tracks", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for findable tracks", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for findable tracks", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for findable tracks", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for findable tracks", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for findable tracks", 100, -100., 100.).fill(z0);
+ aida.cloud2D("Hits vs eta for findable tracks").fill(eta, nhits);
+ continue;
+ }
+
+ // Create the running list of conditions to ignore
+ List<Ignore> ignores = new ArrayList<Ignore>();
+
+ // select mc particles that fail on the z0 cut
+
+ ignores.add(Ignore.NoZ0Cut);
+ if (findable.isFindable(mcp, slist, ignores)) {
+ aida.histogram1D("Hits for z0 check failures", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for z0 check failures", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for z0 check failures", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for z0 check failures", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for z0 check failures", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for z0 check failures", 100, -100., 100.).fill(z0);
+ continue;
+ }
+
+ // Select mc particles that fail on the d0 cut
+ ignores.add(Ignore.NoDCACut);
+ if (findable.isFindable(mcp, slist, ignores)) {
+ aida.histogram1D("Hits for d0 check failures", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for d0 check failures", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for d0 check failures", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for d0 check failures", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for d0 check failures", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for d0 check failures", 100, -100., 100.).fill(z0);
+ continue;
+ }
+
+ // select mc particles that fail the confirm check
+ ignores.add(Ignore.NoConfirmCheck);
+ if (findable.isFindable(mcp, slist, ignores)) {
+ aida.histogram1D("Hits for confirm check failures", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for confir check failures", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for confirm check failures", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for confirm check failures", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for seed confirm failures", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for seed confirm failures", 100, -100., 100.).fill(z0);
+ continue;
+ }
+
+ // select mc particles that fail on the seed check
+ ignores.add(Ignore.NoSeedCheck);
+ if (findable.isFindable(mcp, slist, ignores)) {
+ aida.histogram1D("Hits for seed check failures", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for seed check failures", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for seed check failures", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for seed check failures", 100, -1., 1.).fill(eta);
+ aida.histogram1D("d0 for seed check failures", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for seed check failures", 100, -100., 100.).fill(z0);
+ continue;
+ }
+
+ // Select mc particles that fail the number of hit cut
+ ignores.add(Ignore.NoMinHitCut);
+ if (findable.isFindable(mcp, slist, ignores)) {
+ aida.histogram1D("Hits for nhit check failures", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for nhit check failures", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for nhit check failures", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for nhit check failures", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for nhit check failures", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for nhit check failures", 100, -100., 100.).fill(z0);
+ continue;
+ }
+
+ // Select mc particles that fail on the pT cut
+ ignores.add(Ignore.NoPTCut);
+ if (findable.isFindable(mcp, slist, ignores)) {
+ aida.histogram1D("Hits for pT check failures", 20, 0., 20.).fill(nhits);
+ aida.histogram1D("pT for pT check failures", 100, 0., 10.).fill(pt);
+ aida.histogram1D("cos(theta) for pT check failures", 100, -1., 1.).fill(cth);
+ aida.histogram1D("eta for pT check failures", 100, -2., 2.).fill(eta);
+ aida.histogram1D("d0 for pT check failures", 100, -100., 100.).fill(d0);
+ aida.histogram1D("z0 for pT check failures", 100, -100., 100.).fill(z0);
+ } else {
+ System.out.println("MC Particle is not findable with all ignores set!!");
+ }
+
+ }
+ return;
+ }
+
+ private double getr(double x, double y) {
+ return Math.sqrt(x * x + y * y);
+ }
+
+ protected double drcalc(Hep3Vector pos, SymmetricMatrix cov) {
+ double x = pos.x();
+ double y = pos.y();
+ double r2 = x * x + y * y;
+ return Math.sqrt((x * x * cov.e(0, 0) + y * y * cov.e(1, 1) + 2. * x * y * cov.e(0, 1)) / r2);
+ }
+
+ protected double drphicalc(Hep3Vector pos, SymmetricMatrix cov) {
+ double x = pos.x();
+ double y = pos.y();
+ double r2 = x * x + y * y;
+ return Math.sqrt((y * y * cov.e(0, 0) + x * x * cov.e(1, 1) - 2. * x * y * cov.e(0, 1)) / r2);
+ }
+
+ private double getphi(double x, double y) {
+ double phi = Math.atan2(y, x);
+ if (phi < 0.) {
+ phi += 2. * Math.PI;
+ }
+ return phi;
+ }
+
+ private double getdxdy(Hep3Vector hitpos, Hep3Vector posonhelix) {
+ return Math.sqrt(Math.pow(hitpos.x() - posonhelix.x(), 2) + Math.pow(hitpos.y() - posonhelix.y(), 2));
+ }
+
+ private double getdxdyErr(Hep3Vector hitpos, Hep3Vector posonhelix, SymmetricMatrix cov) {
+ double dxdySq = Math.pow(hitpos.x() - posonhelix.x(), 2) + Math.pow(hitpos.y() - posonhelix.y(), 2);
+ double ErrSqDxDySq = 4 * (cov.e(0, 0) * Math.pow(hitpos.x() - posonhelix.x(), 2) + cov.e(1, 1) * Math.pow(hitpos.y() - posonhelix.y(), 2));
+ double error = Math.sqrt(ErrSqDxDySq / dxdySq) / 2;
+ return error;
+ }
+}
+
+
