[no commit message]

numass-main/src/main/groovy/inr/numass/scripts/OldTest.groovy

@@ -27,7 +27,7 @@ import hep.dataforge.likelihood.BayesianManager
 import inr.numass.data.SpectrumDataAdapter
 import inr.numass.models.BetaSpectrum;
 import inr.numass.models.ModularSpectrum;
-import inr.numass.models.ModularTritiumSpectrum
+
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.models.RangedNamedSetSpectrum;
 import inr.numass.models.ResolutionFunction
@@ -52,7 +52,7 @@ File fssfile = new File("c:\\Users\\Darksnake\\Dropbox\\PlayGround\\FS.txt");
 BivariateFunction resolution = new ResolutionFunction(2.28e-4);
 //resolution.setTailFunction(ResolutionFunction.getRealTail())
 
-ModularTritiumSpectrum sp = new ModularTritiumSpectrum(resolution, 18395d, 18580d, fssfile);
+ModularSpectrum sp = new ModularSpectrum(new BetaSpectrum(fssfile), resolution, 18395d, 18580d);
 sp.setCaching(false);
 //RangedNamedSetSpectrum beta = new BetaSpectrum(fssfile);
 //ModularSpectrum sp = new ModularSpectrum(beta, 2.28e-4, 18395d, 18580d);

numass-main/src/main/groovy/inr/numass/scripts/ResolutionTest.groovy

@@ -26,7 +26,8 @@ import hep.dataforge.datafitter.models.XYModel;
 import hep.dataforge.exceptions.NamingException;
 import inr.numass.data.SpectrumDataAdapter;
 import inr.numass.data.SpectrumGenerator;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.BetaSpectrum
+import inr.numass.models.ModularSpectrum;
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.utils.DataModelUtils;
 import java.io.FileNotFoundException;
@@ -44,7 +45,7 @@ GlobalContext global = GlobalContext.instance();
 
 FitManager fm = new FitManager();
 
-ModularTritiumSpectrum beta = new ModularTritiumSpectrum(9e-5, 14390d, 19001d, null);
+ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), 9e-5, 14390d, 19001d);
 beta.setCaching(false);
 
 NBkgSpectrum spectrum = new NBkgSpectrum(beta);

numass-main/src/main/groovy/inr/numass/scripts/SignificanceTest.groovy

@@ -19,7 +19,8 @@ import hep.dataforge.meta.MetaBuilder;
 import hep.dataforge.context.GlobalContext;
 import hep.dataforge.datafitter.ParamSet;
 import inr.numass.data.SpectrumInformation;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.ModularSpectrum;
+import inr.numass.models.BetaSpectrum;
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.models.ResolutionFunction;
 import java.util.HashMap;
@@ -43,8 +44,8 @@ UnivariateFunction reolutionTail = {x ->
     }
 };
 
-ModularTritiumSpectrum beta = new ModularTritiumSpectrum(
+ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(),
-    new ResolutionFunction(8.3e-5, reolutionTail), 14490d, 19001d, null);
+    new ResolutionFunction(8.3e-5, reolutionTail), 14490d, 19001d);
 beta.setCaching(false);
 NBkgSpectrum spectrum = new NBkgSpectrum(beta);
 

numass-main/src/main/groovy/inr/numass/scripts/Simulate.groovy

@@ -29,7 +29,8 @@ import hep.dataforge.exceptions.NamingException;
 import hep.dataforge.exceptions.PackFormatException;
 import inr.numass.data.SpectrumDataAdapter;
 import inr.numass.data.SpectrumGenerator;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.BetaSpectrum
+import inr.numass.models.ModularSpectrum;
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.utils.DataModelUtils;
 import hep.dataforge.plotfit.PlotFitResultAction;
@@ -50,7 +51,7 @@ new MINUITPlugin().startGlobal();
 
 FitManager fm = new FitManager();
 
-ModularTritiumSpectrum beta = new ModularTritiumSpectrum(8.3e-5, 13990d, 18600d, null);
+ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), 8.3e-5, 13990d, 18600d);
 //beta.setCaching(false);
 
 NBkgSpectrum spectrum = new NBkgSpectrum(beta);

numass-main/src/main/groovy/inr/numass/scripts/SystTransmission.groovy

@@ -29,7 +29,8 @@ import hep.dataforge.exceptions.NamingException;
 import hep.dataforge.exceptions.PackFormatException;
 import inr.numass.data.SpectrumDataAdapter;
 import inr.numass.data.SpectrumGenerator;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.BetaSpectrum
+import inr.numass.models.ModularSpectrum
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.models.ResolutionFunction
 import inr.numass.utils.DataModelUtils;
@@ -56,7 +57,7 @@ FitManager fm = new FitManager();
 ResolutionFunction resolution = new ResolutionFunction(8.3e-5);
 //resolution.setTailFunction(ResolutionFunction.getRealTail());
 resolution.setTailFunction(ResolutionFunction.getAngledTail(0.00325));
-ModularTritiumSpectrum beta = new ModularTritiumSpectrum(resolution, 18395d, 18580d, null);
+ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), resolution, 18395d, 18580d);
 beta.setCaching(false);
 
 NBkgSpectrum spectrum = new NBkgSpectrum(beta);

numass-main/src/main/groovy/inr/numass/scripts/Systematics.groovy

@@ -29,7 +29,8 @@ import hep.dataforge.exceptions.NamingException;
 import hep.dataforge.exceptions.PackFormatException;
 import inr.numass.data.SpectrumDataAdapter;
 import inr.numass.data.SpectrumGenerator;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.BetaSpectrum
+import inr.numass.models.ModularSpectrum;
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.models.ResolutionFunction
 import inr.numass.utils.DataModelUtils;
@@ -55,7 +56,7 @@ FitManager fm = new FitManager();
 
 BivariateFunction resolution = new ResolutionFunction(8.3e-5);
 
-ModularTritiumSpectrum beta = new ModularTritiumSpectrum(resolution, 13490d, 18575d, null);
+ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), resolution, 13490d, 18575d);
 beta.setCaching(false);
 
 NBkgSpectrum spectrum = new NBkgSpectrum(beta);

numass-main/src/main/groovy/inr/numass/scripts/TritiumTest.groovy

@@ -25,7 +25,8 @@ import hep.dataforge.datafitter.models.XYModel;
 import hep.dataforge.likelihood.BayesianManager
 import static hep.dataforge.maths.RandomUtils.setSeed;
 import inr.numass.data.SpectrumGenerator;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.BetaSpectrum
+import inr.numass.models.ModularSpectrum
 import inr.numass.models.NBkgSpectrum;
 import static inr.numass.utils.DataModelUtils.getUniformSpectrumConfiguration;
 import java.io.File;
@@ -40,7 +41,7 @@ setSeed(543982);
 
 //        TritiumSpectrum beta = new TritiumSpectrum(2e-4, 13995d, 18580d);
 File fssfile = new File("c:\\Users\\Darksnake\\Dropbox\\PlayGround\\FS.txt");
-ModularTritiumSpectrum beta = new ModularTritiumSpectrum(8.3e-5, 14400d, 19010d, null);
+ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(),8.3e-5, 14400d, 19010d);
 beta.setCaching(false);
 NBkgSpectrum spectrum = new NBkgSpectrum(beta);
 XYModel model = new XYModel("tritium", spectrum);

numass-main/src/main/java/inr/numass/NumassPlugin.java

@@ -36,6 +36,7 @@ import inr.numass.actions.MonitorCorrectAction;
 import inr.numass.actions.PrepareDataAction;
 import inr.numass.actions.ReadNumassDataAction;
 import inr.numass.actions.ReadNumassStorageAction;
+import inr.numass.actions.ShowEnergySpectrumAction;
 import inr.numass.actions.ShowLossSpectrumAction;
 import inr.numass.actions.SlicingAction;
 import inr.numass.actions.SummaryAction;
@@ -45,6 +46,7 @@ import inr.numass.models.EmpiricalLossSpectrum;
 import inr.numass.models.ExperimentalVariableLossSpectrum;
 import inr.numass.models.GaussSourceSpectrum;
 import inr.numass.models.GunSpectrum;
+import inr.numass.models.LossCalculator;
 import inr.numass.models.ModularSpectrum;
 import inr.numass.models.NBkgSpectrum;
 import inr.numass.models.RangedNamedSetSpectrum;
@@ -83,6 +85,7 @@ public class NumassPlugin extends BasicPlugin {
         actions.registerAction(ShowLossSpectrumAction.class);
         actions.registerAction(AdjustErrorsAction.class);
         actions.registerAction(ReadNumassStorageAction.class);
+        actions.registerAction(ShowEnergySpectrumAction.class);
     }
 
     @Override
@@ -211,6 +214,9 @@ public class NumassPlugin extends BasicPlugin {
             if (!an.getBoolean("caching", false)) {
                 sp.setCaching(false);
             }
+            //Adding trapping energy dependence
+            //Intercept = 4.95745, B1 = -0.36879, B2 = 0.00827
+            sp.setTrappingFunction((Ei,Ef)->LossCalculator.getTrapFunction().value(Ei, Ef)*(4.95745-0.36879*Ei+0.00827*Ei*Ei));
             NBkgSpectrum spectrum = new NBkgSpectrum(sp);
 
             return new XYModel("tritium", spectrum, getAdapter(an));

numass-main/src/main/java/inr/numass/actions/ShowEnergySpectrumAction.java

@@ -0,0 +1,130 @@
+/*
+ * To change this license header, choose License Headers in Project Properties.
+ * To change this template file, choose Tools | Templates
+ * and open the template in the editor.
+ */
+package inr.numass.actions;
+
+import hep.dataforge.actions.OneToOneAction;
+import hep.dataforge.context.Context;
+import hep.dataforge.description.TypedActionDef;
+import hep.dataforge.io.ColumnedDataWriter;
+import hep.dataforge.io.reports.Reportable;
+import hep.dataforge.meta.Laminate;
+import hep.dataforge.meta.Meta;
+import hep.dataforge.meta.MetaBuilder;
+import hep.dataforge.plots.PlotsPlugin;
+import hep.dataforge.plots.XYPlotFrame;
+import hep.dataforge.plots.XYPlottable;
+import hep.dataforge.plots.data.PlottableData;
+import hep.dataforge.tables.DataPoint;
+import hep.dataforge.tables.ListTable;
+import hep.dataforge.tables.MapPoint;
+import hep.dataforge.tables.Table;
+import hep.dataforge.tables.TableFormatBuilder;
+import hep.dataforge.tables.XYAdapter;
+import hep.dataforge.values.ValueType;
+import inr.numass.storage.NMPoint;
+import inr.numass.storage.NumassData;
+import java.io.OutputStream;
+import java.util.ArrayList;
+import java.util.Collection;
+import java.util.LinkedHashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.stream.Collectors;
+
+/**
+ *
+ * @author Alexander Nozik
+ */
+@TypedActionDef(inputType = NumassData.class, outputType = Table.class, name = "energySpectrum", info = "Generate output table and optionally plot for detector energy spectra")
+public class ShowEnergySpectrumAction extends OneToOneAction<NumassData, Table> {
+
+    @Override
+    protected Table execute(Context context, Reportable log, String name, Laminate inputMeta, NumassData input) {
+        int binning = inputMeta.getInt("binning", 20);
+        boolean normalize = inputMeta.getBoolean("normalize", true);
+        List<NMPoint> points = input.getNMPoints();
+
+        if (points.isEmpty()) {
+            logger().error("Empty data");
+            return null;
+        }
+
+        //build header
+        List<String> names = new ArrayList<>();
+        for (int i = 0; i < points.size(); i++) {
+            names.add(String.format("%d: %.2f", i, points.get(i).getUset()));
+        }
+
+        LinkedHashMap<String, Map<Double, Double>> valueMap = points.stream()
+                .collect(Collectors.toMap(
+                        p -> names.get(points.indexOf(p)),
+                        p -> p.getMapWithBinning(binning, normalize),
+                        (v1, v2) -> v1,
+                        () -> new LinkedHashMap<>()
+                ));
+
+        Collection<Double> rows = valueMap.values().stream().findAny().get().keySet();
+
+        //Building table format
+        TableFormatBuilder formatBuilder = new TableFormatBuilder();
+        formatBuilder.addColumn("channel",ValueType.NUMBER);
+        names.stream().forEach((columnName) -> {
+            formatBuilder.addColumn(columnName, ValueType.NUMBER);
+        });
+
+        ListTable.Builder builder = new ListTable.Builder(formatBuilder.build());
+        rows.stream().forEachOrdered((Double channel) -> {
+            MapPoint.Builder mb = new MapPoint.Builder();
+            mb.putValue("channel", channel);
+            valueMap.entrySet().forEach((Map.Entry<String, Map<Double, Double>> entry) -> {
+                mb.putValue(entry.getKey(), entry.getValue().get(channel));
+            });
+            builder.addRow(mb.build());
+        });
+
+        OutputStream out = buildActionOutput(context, name);
+        Table table = builder.build();
+
+        ColumnedDataWriter.writeDataSet(out, table, inputMeta.toString());
+
+        if (inputMeta.hasNode("plot") || inputMeta.getBoolean("plot", false)) {
+            XYPlotFrame frame = (XYPlotFrame) PlotsPlugin
+                    .buildFrom(context).buildPlotFrame(getName(), name,
+                    inputMeta.getNode("plot", Meta.empty()));
+            fillDetectorData(valueMap).forEach(frame::add);
+
+        }
+        return table;
+    }
+
+    private List<XYPlottable> fillDetectorData(LinkedHashMap<String, Map<Double, Double>> map) {
+        List<XYPlottable> plottables = new ArrayList<>();
+        Meta plottableConfig = new MetaBuilder("plot")
+                .setValue("connectionType", "step")
+                .setValue("thickness", 2)
+                .setValue("showLine", true)
+                .setValue("showSymbol", false)
+                .setValue("showErrors", false)
+                .build();
+
+        int index = 0;
+        for (Map.Entry<String, Map<Double, Double>> entry : map.entrySet()) {
+            index++;
+            String seriesName = String.format("%d: %s", index, entry.getKey());
+
+            String[] nameList = {"x", "y"};
+            List<DataPoint> data = entry.getValue().entrySet().stream()
+                    .map(e -> new MapPoint(nameList, e.getKey(), e.getValue()))
+                    .collect(Collectors.toList());
+            PlottableData datum = PlottableData.plot(seriesName, new XYAdapter(), data);
+            datum.configure(plottableConfig);
+            plottables.add(datum);
+        }
+        return plottables;
+
+    }
+
+}

numass-main/src/main/java/inr/numass/actions/ShowLossSpectrumAction.java

@@ -228,7 +228,7 @@ public class ShowLossSpectrumAction extends OneToOneAction<FitState, FitState> {
                         new MetaBuilder("plot").setValue("plotTitle", "Ion ratio Distribution for " + name)
                 );
 //        XYPlotFrame frame = JFreeChartFrame.drawFrame("Ion ratio Distribution for " + name, null);
-        frame.add(PlottableData.plot("ionRatio", hist, new XYAdapter("binCenter", "count")));
+        frame.add(PlottableData.plot("ionRatio", new XYAdapter("binCenter", "count"), hist));
 
         return new DescriptiveStatistics(res).getStandardDeviation();
     }

numass-main/src/main/java/inr/numass/models/LossCalculator.java

@@ -126,7 +126,7 @@ public class LossCalculator {
         return getSingleScatterFunction(exPos, ionPos, exW, ionW, exIonRatio);
     }
 
-    static BivariateFunction getTrapFunction() {
+    public static BivariateFunction getTrapFunction() {
         return (double Ei, double Ef) -> {
             double eps = Ei - Ef;
             if (eps > 10) {

numass-main/src/main/java/inr/numass/models/ModularSpectrum.java

@@ -35,9 +35,10 @@ public class ModularSpectrum extends AbstractParametricFunction {
     private static final String[] list = {"X", "trap"};
     private LossCalculator calculator;
     List<NamedSpectrumCaching> cacheList;
-    NamedSpectrumCaching trapping;
+    NamedSpectrumCaching trappingCache;
     BivariateFunction resolution;
     RangedNamedSetSpectrum sourceSpectrum;
+    BivariateFunction trappingFunction;
     boolean caching = true;
     double cacheMin;
     double cacheMax;
@@ -84,6 +85,12 @@ public class ModularSpectrum extends AbstractParametricFunction {
         this(source, new ResolutionFunction(resA));
     }
 
+    public void setTrappingFunction(BivariateFunction trappingFunction) {
+        this.trappingFunction = trappingFunction;
+    }
+
+    
+    
     /**
      * Отдельный метод нужен на случай, если бета-спектр(FSS) или разрешение
      * будут меняться в процессе
@@ -91,7 +98,8 @@ public class ModularSpectrum extends AbstractParametricFunction {
     private void setupCache() {
 
         //обновляем кэши для трэппинга и упругого прохождения
-        BivariateFunction trapFunc = LossCalculator.getTrapFunction();
+        //Using external trappingCache function if provided
+        BivariateFunction trapFunc = trappingFunction != null ? trappingFunction : LossCalculator.getTrapFunction();
         BivariateFunction trapRes = new LossResConvolution(trapFunc, resolution);
 
         ParametricFunction elasticSpectrum = new TransmissionConvolution(sourceSpectrum, resolution, sourceSpectrum);
@@ -105,8 +113,8 @@ public class ModularSpectrum extends AbstractParametricFunction {
         TritiumSpectrumCaching elasticCache = new TritiumSpectrumCaching(elasticSpectrum, cacheMin, cacheMax);
         elasticCache.setCachingEnabled(caching);
         cacheList.add(elasticCache);
-        this.trapping = new TritiumSpectrumCaching(trapSpectrum, cacheMin, cacheMax);
+        this.trappingCache = new TritiumSpectrumCaching(trapSpectrum, cacheMin, cacheMax);
-        this.trapping.setCachingEnabled(caching);
+        this.trappingCache.setCachingEnabled(caching);
     }
 
     /**
@@ -150,7 +158,7 @@ public class ModularSpectrum extends AbstractParametricFunction {
 
                 return derivSum;
             case "trap":
-                return this.trapping.value(U, set);
+                return this.trappingCache.value(U, set);
             default:
                 if (sourceSpectrum.names().contains(parName)) {
                     List<Double> probs = calculator.getLossProbabilities(X);
@@ -161,7 +169,7 @@ public class ModularSpectrum extends AbstractParametricFunction {
                         sum += probs.get(i) * cacheList.get(i).derivValue(parName, U, set);
                     }
 
-                    sum += this.getTrap(set) * this.trapping.derivValue(parName, U, set);
+                    sum += this.getTrap(set) * this.trappingCache.derivValue(parName, U, set);
                     return sum;
                 } else {
                     return 0;
@@ -184,29 +192,30 @@ public class ModularSpectrum extends AbstractParametricFunction {
 
     /**
      * Set the boundaries and recalculate cache
+     *
      * @param cacheMin
      * @param cacheMax
      */
-    public void setCachingBoundaries(double cacheMin, double cacheMax){
+    public void setCachingBoundaries(double cacheMin, double cacheMax) {
         this.cacheMin = cacheMin;
         this.cacheMax = cacheMax;
         setupCache();
     }
 
     public final void setCaching(boolean caching) {
-        if(caching && (cacheMin == Double.NaN || cacheMax == Double.NaN)){
+        if (caching && (cacheMin == Double.NaN || cacheMax == Double.NaN)) {
             throw new IllegalStateException("Cahing boundaries are not defined");
         }
 
         this.caching = caching;
-        this.trapping.setCachingEnabled(caching);
+        this.trappingCache.setCachingEnabled(caching);
         for (NamedSpectrumCaching sp : this.cacheList) {
             sp.setCachingEnabled(caching);
         }
     }
 
     public void setSuppressWarnings(boolean suppress) {
-        this.trapping.setSuppressWarnings(suppress);
+        this.trappingCache.setSuppressWarnings(suppress);
         for (NamedSpectrumCaching sp : this.cacheList) {
             sp.setSuppressWarnings(suppress);
 
@@ -228,7 +237,7 @@ public class ModularSpectrum extends AbstractParametricFunction {
             res += probs.get(i) * cacheList.get(i).value(U, set);
         }
 
-        res += this.getTrap(set) * this.trapping.value(U, set);
+        res += this.getTrap(set) * this.trappingCache.value(U, set);
         return res;
     }
 }

numass-main/src/main/java/inr/numass/models/ModularTritiumSpectrum.java

@@ -1,216 +0,0 @@
-/* 
- * Copyright 2015 Alexander Nozik.
- *
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *      http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- */
-package inr.numass.models;
-
-import hep.dataforge.functions.AbstractParametricFunction;
-import hep.dataforge.functions.ParametricFunction;
-import hep.dataforge.maths.NamedDoubleSet;
-import java.io.File;
-import java.util.ArrayList;
-import java.util.List;
-import org.apache.commons.math3.analysis.BivariateFunction;
-import org.slf4j.LoggerFactory;
-
-/**
- * Modular tritium spectrum with separate calculation for different transmission
- * components
- *
- * @author Darksnake
- */
-public class ModularTritiumSpectrum extends AbstractParametricFunction {
-
-    private static final String[] list = {"U2", "E0", "mnu2", "msterile2", "X", "trap"};
-    ParametricFunction bareBeta;
-    boolean caching;
-    private LossCalculator calculator;
-    double elow;
-    double endpoint;
-    File fssfile;
-    BivariateFunction resolution;
-    List<NamedSpectrumCaching> scatterList;
-    NamedSpectrumCaching trapping;
-
-//    NamedSpectrumCaching elastic;
-//    NamedSpectrumCaching inelastic;
-//    NamedSpectrumCaching inelastic2;
-    /**
-     *
-     * @param resolution
-     * @param elow - нижняя граница кэширования. Должна быть с небольшим запасом
-     * по отношению к данным
-     * @param endpoint - верхняя граница кэширования, может быть без запаса.
-     * @param fssFile
-     */
-    public ModularTritiumSpectrum(BivariateFunction resolution, double elow, double endpoint, File fssFile) {
-        super(list);
-        assert (endpoint > elow);
-        this.elow = elow;
-        this.endpoint = endpoint;
-        this.fssfile = fssFile;
-        this.resolution = resolution;
-        this.calculator = LossCalculator.instance();
-        setupCache();
-    }
-
-    /**
-     *
-     * @param resA - относительная ширина разрешения
-     * @param elow - нижняя граница кэширования. Должна быть с небольшим запасом
-     * по отношению к данным
-     * @param endpoint - верхняя граница кэширования, может быть без запаса.
-     * @param fssFile
-     */
-    public ModularTritiumSpectrum(double resA, double elow, double endpoint, File fssFile) {
-        this(new ResolutionFunction(resA), elow, endpoint, fssFile);
-    }
-
-    @Override
-    public double derivValue(String parName, double U, NamedDoubleSet set) {
-        if (U >= endpoint) {
-            return 0;
-        }
-        double X = this.getX(set);
-        switch (parName) {
-            case "U2":
-            case "E0":
-            case "mnu2":
-            case "msterile2":
-                List<Double> probs = calculator.getLossProbabilities(X);
-                updateScatterCache(probs.size() - 1);
-                double sum = 0;
-
-                for (int i = 0; i < probs.size(); i++) {
-                    sum += probs.get(i) * scatterList.get(i).derivValue(parName, U, set);
-                }
-
-                return sum + this.getTrap(set) * this.trapping.derivValue(parName, U, set);
-            case "X":
-                List<Double> probDerivs = calculator.getLossProbDerivs(X);
-                updateScatterCache(probDerivs.size() - 1);
-                double derivSum = 0;
-
-                for (int i = 0; i < probDerivs.size(); i++) {
-                    derivSum += probDerivs.get(i) * scatterList.get(i).value(U, set);
-                }
-
-                return derivSum;
-
-//                return (X / 3 - 0.5) * this.elastic.value(x, set)
-//                        + (0.5 - 2 * X / 3) * this.inelastic.value(x, set)
-//                        + (X / 3) * this.inelastic2.value(x, set);
-            case "trap":
-                return this.trapping.value(U, set);
-            default:
-                return 0;
-        }
-    }
-
-    private double getTrap(NamedDoubleSet set) {
-        return set.getValue("trap");
-    }
-
-    private double getX(NamedDoubleSet set) {
-        return set.getValue("X");
-    }
-
-    @Override
-    public boolean providesDeriv(String name) {
-        return true;
-    }
-
-    public void setCaching(boolean caching) {
-        this.caching = caching;
-        this.trapping.setCachingEnabled(caching);
-        for (NamedSpectrumCaching sp : this.scatterList) {
-            sp.setCachingEnabled(caching);
-        }
-    }
-
-    public void setSuppressWarnings(boolean suppress) {
-        this.trapping.setSuppressWarnings(suppress);
-        for (NamedSpectrumCaching sp : this.scatterList) {
-            sp.setSuppressWarnings(suppress);
-            
-        }
-    }
-
-    /**
-     * Отдельный метод нужен на случай, если бета-спектр(FSS) или разрешение
-     * будут меняться в процессе
-     */
-    private void setupCache() {
-        if (fssfile == null) {
-            bareBeta = new BetaSpectrum();
-        } else {
-            bareBeta = new BetaSpectrum(fssfile);
-        }
-        
-        //обновляем кэши для трэппинга и упругого прохождения
-        BivariateFunction trapFunc = LossCalculator.getTrapFunction();
-        BivariateFunction trapRes = new LossResConvolution(trapFunc, resolution);
-        
-        ParametricFunction elasticSpectrum = new TransmissionConvolution(bareBeta, resolution, endpoint);
-        ParametricFunction trapSpectrum = new TransmissionConvolution(bareBeta, trapRes, endpoint);
-        scatterList = new ArrayList<>();
-        //добавляем нулевой порядок - упругое рассеяние
-        scatterList.add(new TritiumSpectrumCaching(elasticSpectrum, elow, endpoint));
-        this.trapping = new TritiumSpectrumCaching(trapSpectrum, elow, endpoint);
-        /**
-         * обнуляем кэш рассеяния
-         */
-        
-    }
-
-    /**
-     * Обновляем кэш рассеяния если требуемый порядок выше, чем тот, что есть
-     *
-     * @param order
-     */
-    private void updateScatterCache(int order) {
-        if (order >= scatterList.size()) {
-           LoggerFactory.getLogger(getClass())
-                    .debug("Updating scatter cache up to order of '{}'", order);
-            // здесь можно сэкономить вызовы, начиная с scatterList.size(), но надо это?
-            for (int i = 1; i < order + 1; i++) {
-                BivariateFunction loss = calculator.getLossFunction(i);
-                BivariateFunction lossRes = new LossResConvolution(loss, resolution);
-                ParametricFunction inelasticSpectrum = new TransmissionConvolution(bareBeta, lossRes, endpoint);
-                TritiumSpectrumCaching spCatch = new TritiumSpectrumCaching(inelasticSpectrum, elow, endpoint);
-                spCatch.setCachingEnabled(caching);
-                //TODO сделать пороверку
-                scatterList.add(i, spCatch);
-            }
-        }
-    }
-
-    @Override
-    public double value(double x, NamedDoubleSet set) {
-        if (x >= endpoint) {
-            return 0;
-        }
-        double X = this.getX(set);
-
-        List<Double> probs = calculator.getLossProbabilities(X);
-        updateScatterCache(probs.size() - 1);
-        double res = 0;
-
-        for (int i = 0; i < probs.size(); i++) {
-            res += probs.get(i) * scatterList.get(i).value(x, set);
-        }
-
-        return res + this.getTrap(set) * this.trapping.value(x, set);
-    }
-}

numass-main/src/main/java/inr/numass/workbench/Workbench.java

@@ -13,7 +13,7 @@ import javafx.fxml.FXMLLoader;
 import javafx.scene.Parent;
 import javafx.scene.Scene;
 import javafx.stage.Stage;
-
+import javafx.stage.WindowEvent;
 
 /**
  *
@@ -34,6 +34,10 @@ public class Workbench extends Application {
         primaryStage.setTitle("Numass workbench");
         primaryStage.setScene(scene);
         primaryStage.show();
+
+        scene.getWindow().setOnCloseRequest((WindowEvent event) -> {
+            controller.getContext().processManager().getRootProcess().cancel(true);
+        });
     }
 
     /**

numass-main/src/test/java/inr/numass/run/NumassSpectrumTest.java

@@ -19,7 +19,8 @@ import hep.dataforge.context.GlobalContext;
 import hep.dataforge.datafitter.MINUITPlugin;
 import hep.dataforge.datafitter.ParamSet;
 import hep.dataforge.exceptions.NamingException;
-import inr.numass.models.ModularTritiumSpectrum;
+import inr.numass.models.BetaSpectrum;
+import inr.numass.models.ModularSpectrum;
 import java.io.File;
 import java.io.FileNotFoundException;
 import java.util.Locale;
@@ -64,7 +65,7 @@ public class NumassSpectrumTest {
         allPars.setParError("trap", 0.01d);
         allPars.setParDomain("trap", 0d, Double.POSITIVE_INFINITY);
 
-        ModularTritiumSpectrum betaNew = new ModularTritiumSpectrum(1e-4, 14390d, 19001d, new File("d:\\PlayGround\\FS.txt"));
+        ModularSpectrum betaNew = new ModularSpectrum(new BetaSpectrum(new File("d:\\PlayGround\\FS.txt")), 1e-4, 14390d, 19001d);
         betaNew.setCaching(false);
 
         System.out.println(betaNew.value(17000d, allPars));

numass-storage/src/main/java/inr/numass/storage/NumassDataLoader.java

@@ -28,6 +28,7 @@ import hep.dataforge.storage.api.Storage;
 import hep.dataforge.storage.loaders.AbstractLoader;
 import hep.dataforge.tables.Table;
 import hep.dataforge.values.Value;
+import static inr.numass.storage.RawNMPoint.MAX_EVENTS_PER_POINT;
 import java.io.File;
 import java.io.IOException;
 import java.io.InputStream;
@@ -193,6 +194,13 @@ public class NumassDataLoader extends AbstractLoader implements ObjectLoader<Env
         } else {
             pointTime = envelope.meta().getValue("acquisition_time").doubleValue();
         }
+
+        //Check if the point is composite
+        boolean segmented = envelope.meta().hasValue("events") && envelope.meta().getValue("events").isList();
+        
+        if (!segmented && events.size() > MAX_EVENTS_PER_POINT) {
+            pointTime = events.get(events.size() - 1).getTime() - events.get(0).getTime();
+        }
         RawNMPoint raw = new RawNMPoint(u, u,
                 events,
                 pointTime,

numass-storage/src/main/java/inr/numass/storage/RawNMPoint.java

@@ -105,9 +105,7 @@ public class RawNMPoint implements Cloneable {
         if (Double.isNaN(length)) {
             throw new Error();
         }
-        if(events.size()>MAX_EVENTS_PER_POINT){
+
-            return events.get(events.size()-1).getTime()-events.get(0).getTime();
-        }
         return length;
     }