fix: widen CTOF tdcadc time distribution (#222)

detectors/src/main/java/org/jlab/clas/timeline/fitter/CTOFFitter.groovy

@@ -34,103 +34,72 @@ class CTOFFitter {
     return f1
   }
 
-  static F1D tdcadcdifffit(H1F h1) {
-    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -5.0, 5.0)
-    double hAmp  = h1.getBinContent(h1.getMaximumBin());
-    double hMean = h1.getAxis().getBinCenter(h1.getMaximumBin())
-    double hRMS  = h1.getRMS();
-    double factor1 = 3.0
-    double factor2 = 1.57
-    double rangeMin = (hMean - factor1*0.5);
-    double rangeMax = (hMean + factor2*0.5);
-    f1.setRange(rangeMin, rangeMax);
-    f1.setParameter(0, hAmp);
-    // f1.setParLimits(0, hAmp*0.8, hAmp*1.2);
-    f1.setParameter(1, hMean);
-    // f1.setParLimits(1, 0, 0.5);
-    f1.setParameter(2, 1);
-    // f1.setParLimits(2, 0.5*hRMS, 1.5*hRMS);
-
-    def makefit = {func->
-      hMean = func.getParameter(1)
-      hRMS = func.getParameter(2).abs()
-      func.setRange(hMean-2*hRMS,hMean+2*hRMS)
-      DataFitter.fit(func,h1,"Q")
-      return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
-    }
-
-    def fits1 = (0..20).collect{makefit(f1)}
-    def bestfit = fits1.sort()[0]
-    f1.setParameters(*bestfit[1])
-    //makefit(f1)
-    return f1
-  }
-
 
-  static F1D tdcadcdifffit_right(H1F h1) {
-    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -5.0, 5.0)
-    def peakbin = (1000..1500).max{h1.getBinContent(it)}
-    double hAmp  = h1.getBinContent(peakbin);
-    double hMean = h1.getAxis().getBinCenter(peakbin)
-    double hRMS  = h1.getRMS();
-    double factor1 = 3.0
-    double factor2 = 1.57
-    double rangeMin = (hMean - factor1*0.5);
-    double rangeMax = (hMean + factor2*0.5);
-    f1.setRange(rangeMin, rangeMax);
-    f1.setParameter(0, hAmp);
-    // f1.setParLimits(0, hAmp*0.8, hAmp*1.2);
-    f1.setParameter(1, hMean);
-    // f1.setParLimits(1, 0, 0.5);
-    f1.setParameter(2, 1);
-    // f1.setParLimits(2, 0.5*hRMS, 1.5*hRMS);
-
-    def makefit = {func->
-      hMean = func.getParameter(1)
-      hRMS = func.getParameter(2).abs()
-      func.setRange(hMean-2*hRMS,hMean+2*hRMS)
-      DataFitter.fit(func,h1,"Q")
-      return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
+  static def tdcadcdifffit(H1F h1) {
+
+    def fit_peak = { peakbin, prefix ->
+      def f1 = new F1D("${prefix}:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -5.0, 5.0)
+      double hAmp  = h1.getBinContent(peakbin);
+      double hMean = h1.getAxis().getBinCenter(peakbin)
+      double hRMS  = h1.getRMS();
+      double factor1 = 3.0
+      double factor2 = 1.57
+      double rangeMin = (hMean - factor1*0.5);
+      double rangeMax = (hMean + factor2*0.5);
+      f1.setRange(rangeMin, rangeMax);
+      f1.setParameter(0, hAmp);
+      // f1.setParLimits(0, hAmp*0.8, hAmp*1.2);
+      f1.setParameter(1, hMean);
+      // f1.setParLimits(1, 0, 0.5);
+      f1.setParameter(2, 1);
+      // f1.setParLimits(2, 0.5*hRMS, 1.5*hRMS);
+
+      def makefit = {func->
+        hMean = func.getParameter(1)
+        hRMS = func.getParameter(2).abs()
+        func.setRange(hMean-2*hRMS,hMean+2*hRMS)
+        DataFitter.fit(func,h1,"Q")
+        return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
+      }
+
+      def fits1 = (0..20).collect{makefit(f1)}
+      def bestfit = fits1.sort()[0]
+      f1.setParameters(*bestfit[1])
+      //makefit(f1)
+      return f1
     }
 
-    def fits1 = (0..20).collect{makefit(f1)}
-    def bestfit = fits1.sort()[0]
-    f1.setParameters(*bestfit[1])
-    //makefit(f1)
-    return f1
-  }
-
-  static F1D tdcadcdifffit_left(H1F h1) {
-    def f1 = new F1D("fit:"+h1.getName(), "[amp]*gaus(x,[mean],[sigma])", -5.0, 5.0)
-    def peakbin = (400..900).max{h1.getBinContent(it)}
-    double hAmp  = h1.getBinContent(peakbin);
-    double hMean = h1.getAxis().getBinCenter(peakbin)
-    double hRMS  = h1.getRMS();
-    double factor1 = 3.0
-    double factor2 = 1.57
-    double rangeMin = (hMean - factor1*0.5);
-    double rangeMax = (hMean + factor2*0.5);
-    f1.setRange(rangeMin, rangeMax);
-    f1.setParameter(0, hAmp);
-    // f1.setParLimits(0, hAmp*0.8, hAmp*1.2);
-    f1.setParameter(1, hMean);
-    // f1.setParLimits(1, 0, 0.5);
-    f1.setParameter(2, 1);
-    // f1.setParLimits(2, 0.5*hRMS, 1.5*hRMS);
-
-    def makefit = {func->
-      hMean = func.getParameter(1)
-      hRMS = func.getParameter(2).abs()
-      func.setRange(hMean-2*hRMS,hMean+2*hRMS)
-      DataFitter.fit(func,h1,"Q")
-      return [func.getChiSquare(), (0..<func.getNPars()).collect{func.getParameter(it)}]
+    // find the highest peak, and fit it
+    def bins = (1..h1.getAxis().getNBins())
+    def peakbin1 = bins.max{h1.getBinContent(it)}
+    def func1 = fit_peak(peakbin1,'fit1')
+
+    // find the 2nd highest peak by excluding the region around the 1st highest
+    // peak, and searching for the new highest max, then fit it
+    def peak1Start = func1.getParameter(1) - 2*func1.getParameter(2)
+    def peak1End   = func1.getParameter(1) + 2*func1.getParameter(2)
+    def peakbin2 = bins
+      .collect{ [ it, h1.getBinContent(it) ] }
+      .findAll{ h1.getAxis().getBinCenter(it[0]) < peak1Start || h1.getAxis().getBinCenter(it[0]) > peak1End }
+      .max{ it[1] }[0]
+    def func2 = fit_peak(peakbin2,'fit2')
+
+    // decide which fit result is upstream and downstream
+    def funcs = func1.getParameter(1) < func2.getParameter(1) ? [func1,func2] : [func2,func1]
+
+    // create a summed combination (since the front-end seems to prefer this)
+    def combinedFunc = new F1D(
+      "fit:"+h1.getName(),
+      "[ampUpstream]*gaus(x,[meanUpstream],[sigmaUpstream])+[ampDownstream]*gaus(x,[meanDownstream],[sigmaDownstream])",
+      funcs[0].getParameter(1) - 3*funcs[0].getParameter(2),
+      funcs[1].getParameter(1) + 3*funcs[1].getParameter(2))
+    [0,1,2].each{
+      combinedFunc.setParameter(it, funcs[0].getParameter(it))
+      combinedFunc.setParameter(it+3, funcs[1].getParameter(it))
     }
+    funcs.add(combinedFunc)
 
-    def fits1 = (0..20).collect{makefit(f1)}
-    def bestfit = fits1.sort()[0]
-    f1.setParameters(*bestfit[1])
-    //makefit(f1)
-    return f1
+    return funcs // [ upstream fit, downstream fit, combined fit ]
   }
 
 

detectors/src/main/java/org/jlab/clas/timeline/run_detectors.groovy

@@ -69,8 +69,7 @@ def engines = [
     new cnd.cnd_zdiff()],
   out_CTOF: [new ctof.ctof_edep(),
     new ctof.ctof_time(),
-    new ctof.ctof_tdcadc_left(),
-    new ctof.ctof_tdcadc_right()],
+    new ctof.ctof_tdcadc()],
   out_FT: [new ft.ftc_pi0_mass(),
     new ft.ftc_time_charged(),
     new ft.ftc_time_neutral(),

detectors/src/main/java/org/jlab/clas/timeline/run_detectors_rgb.groovy

@@ -70,8 +70,7 @@ def engines = [
     new cnd.cnd_zdiff()],
   out_CTOF: [new ctof.ctof_edep(),
     new ctof.ctof_time(),
-    new ctof.ctof_tdcadc_left(),
-    new ctof.ctof_tdcadc_right(),
+    new ctof.ctof_tdcadc(),
     new particle_mass_ctof_and_ftof.ctof_m2_pim(),
     new particle_mass_ctof_and_ftof.ctof_m2_pip()],
   out_FT: [new ft.ftc_pi0_mass(),

detectors/src/main/java/org/jlab/clas/timeline/timeline/ctof/ctof_tdcadc.groovy

@@ -11,9 +11,19 @@ def data = new ConcurrentHashMap()
 
 def processDirectory(dir, run) {
   def h1 = dir.getObject('/ctof/CTOF TDC-ADC Time Difference')
-  def f1 = CTOFFitter.tdcadcdifffit(h1)
-
-  data[run] = [run:run, h1:h1, f1:f1, mean:f1.getParameter(1), sigma:f1.getParameter(2).abs(), chi2:f1.getChiSquare()]
+  def f1s = CTOFFitter.tdcadcdifffit(h1)
+
+  data[run]  = [
+    run:        run,
+    h1:         h1,
+    meanUpstream:   f1s[0].getParameter(1),
+    sigmaUpstream:  f1s[0].getParameter(2).abs(),
+    chi2Upstream:   f1s[0].getChiSquare(),
+    meanDownstream:  f1s[1].getParameter(1),
+    sigmaDownstream: f1s[1].getParameter(2).abs(),
+    chi2Downstream:  f1s[1].getChiSquare(),
+    f1Combined: f1s[2],
+  ]
 }
 
 
@@ -22,25 +32,30 @@ def close() {
 
 
   ['mean', 'sigma'].each{name->
-    def grtl = new GraphErrors(name)
-    grtl.setTitle("TDC time - FADC time averaged over CTOF counters (" + name +")")
-    grtl.setTitleY("TDC time - FADC time averaged over CTOF counters (" + name + ") (ns)")
-    grtl.setTitleX("run number")
+    def grtlUpstream  = new GraphErrors("upstream_${name}")
+    def grtlDownstream = new GraphErrors("downstream_${name}")
+    [grtlUpstream,grtlDownstream].each{ grtl ->
+      grtl.setTitle("TDC time - FADC time averaged over CTOF counters")
+      grtl.setTitleY("TDC time - FADC time averaged over CTOF counters [ns]")
+      grtl.setTitleX("run number")
+    }
 
     TDirectory out = new TDirectory()
 
     data.sort{it.key}.each{run,it->
       out.mkdir('/'+it.run)
       out.cd('/'+it.run)
       out.addDataSet(it.h1)
-      out.addDataSet(it.f1)
-      grtl.addPoint(it.run, it[name], 0, 0)
+      out.addDataSet(it.f1Combined)
+      grtlUpstream.addPoint(it.run, it["${name}Upstream"], 0, 0)
+      grtlDownstream.addPoint(it.run, it["${name}Downstream"], 0, 0)
     }
 
     out.mkdir('/timelines')
     out.cd('/timelines')
-    out.addDataSet(grtl)
-    out.writeFile('ctof_tdcadc_time_'+name+'.hipo')
+    out.addDataSet(grtlUpstream)
+    out.addDataSet(grtlDownstream)
+    out.writeFile("ctof_tdcadc_time_${name}.hipo")
   }
 }
 }

monitoring/src/main/java/org/jlab/clas12/monitoring/central.java

@@ -122,7 +122,7 @@ public central(int reqrunNum, String reqOutputDir, boolean reqTimeBased) {
 		H_CTOF_edep_z.setTitle("CTOF PathLCorrected Edep vs z");
 		H_CTOF_edep_z.setTitleX("z/10 (cm)");
 		H_CTOF_edep_z.setTitleY("E (MeV)");
-		H_CTOF_tdcadc_dt = new H1F("CTOF TDC-ADC Time Difference","CTOF TDC-ADC Time Difference",2250,-10.,80.);
+		H_CTOF_tdcadc_dt = new H1F("CTOF TDC-ADC Time Difference","CTOF TDC-ADC Time Difference",4750,-10.,180.);
 		H_CTOF_tdcadc_dt.setTitle("CTOF TDC_time-ADC_time");
 		H_CTOF_tdcadc_dt.setTitleX("Delta_t (ns)");
 		H_CTOF_tdcadc_dt.setTitleY("counts");