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@ -14,6 +14,7 @@ dependencies {
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compile project(':dataforge-fx')
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compile project(':dataforge-plots')
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compile project(':numass-storage')
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compile project(':dataforge-grind')
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}
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task workbench(dependsOn: classes, type: JavaExec){
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@ -42,6 +42,8 @@ import static java.util.Locale.setDefault;
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import inr.numass.utils.TritiumUtils;
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import inr.numass.data.SpectrumDataAdapter;
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import hep.dataforge.io.FittingIOUtils
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import hep.dataforge.meta.Meta
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import hep.dataforge.grind.GrindMetaBuilder
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/**
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*
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@ -50,9 +52,16 @@ import hep.dataforge.io.FittingIOUtils
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setDefault(Locale.US);
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ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), 8.3e-5, 13990d, 18600d);
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//ParametricFunction beta = new BetaSpectrum();
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//ParametricFunction beta = new SterileNeutrinoSpectrum();
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//ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), 8.3e-5, 13990d, 18600d);
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//beta.setCaching(false)
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Meta cfg = new GrindMetaBuilder().meta{
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resolution(width: 8.3e-5)
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}.build();
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ParametricFunction beta = new SterileNeutrinoSpectrum(cfg);
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NBkgSpectrum spectrum = new NBkgSpectrum(beta);
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XYModel model = new XYModel(spectrum, new SpectrumDataAdapter());
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@ -65,10 +74,10 @@ allPars.setPar("E0", 18574.94, 1.4);
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allPars.setPar("mnu2", 0d, 1d);
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allPars.setPar("msterile2", 1000d * 1000d,0);
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allPars.setPar("U2", 0.0, 1e-4, -1d, 1d);
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allPars.setPar("X", 0.04000, 0.01, 0d, Double.POSITIVE_INFINITY);
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allPars.setPar("X", 0.04, 0.01, 0d, Double.POSITIVE_INFINITY);
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allPars.setPar("trap", 1.634, 0.01,0d, Double.POSITIVE_INFINITY);
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FittingIOUtils.printSpectrum(GlobalContext.out(), spectrum, allPars, 14000.0, 18600.0, 400);
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FittingIOUtils.printSpectrum(GlobalContext.out(), spectrum, allPars, 14000, 18600.0, 400);
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//SpectrumGenerator generator = new SpectrumGenerator(model, allPars, 12316);
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//
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@ -34,10 +34,6 @@ import java.io.PrintWriter;
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*/
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public class NumassContext extends Context {
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public static UnivariateIntegrator defaultIntegrator = new GaussRuleIntegrator(300);
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public static UnivariateIntegrator highDensityIntegrator = new GaussRuleIntegrator(500);
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public NumassContext(Context parent, Meta config) {
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super(parent, "numass", config);
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init();
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42
numass-main/src/main/java/inr/numass/NumassIntegrator.java
Normal file
42
numass-main/src/main/java/inr/numass/NumassIntegrator.java
Normal file
@ -0,0 +1,42 @@
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/*
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* To change this license header, choose License Headers in Project Properties.
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* To change this template file, choose Tools | Templates
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* and open the template in the editor.
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*/
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package inr.numass;
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import hep.dataforge.maths.integration.GaussRuleIntegrator;
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import hep.dataforge.maths.integration.UnivariateIntegrator;
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/**
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*
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* @author Alexander Nozik
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*/
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public class NumassIntegrator {
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private static UnivariateIntegrator fastInterator;
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private static UnivariateIntegrator defaultIntegrator;
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private static UnivariateIntegrator highDensityIntegrator;
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public static UnivariateIntegrator getFastInterator() {
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if (fastInterator == null) {
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fastInterator = new GaussRuleIntegrator(100);
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}
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return fastInterator;
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}
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public static UnivariateIntegrator getDefaultIntegrator() {
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if (defaultIntegrator == null) {
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defaultIntegrator = new GaussRuleIntegrator(300);
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}
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return defaultIntegrator;
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}
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public static UnivariateIntegrator getHighDensityIntegrator() {
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if (highDensityIntegrator == null) {
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highDensityIntegrator = new GaussRuleIntegrator(500);
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}
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return highDensityIntegrator;
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}
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}
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@ -40,6 +40,7 @@ import hep.dataforge.tables.MapPoint;
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import hep.dataforge.tables.Table;
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import hep.dataforge.tables.XYAdapter;
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import hep.dataforge.values.NamedValueSet;
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import inr.numass.NumassIntegrator;
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import inr.numass.NumassContext;
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import inr.numass.models.ExperimentalVariableLossSpectrum;
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import inr.numass.models.LossCalculator;
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@ -79,7 +80,7 @@ public class ShowLossSpectrumAction extends OneToOneAction<FitState, FitState> {
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new MetaBuilder("plot")
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.setValue("plotTitle", "Differential scattering crossection for " + name)
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);
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switch (input.getModel().meta().getString("name","")) {
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switch (input.getModel().meta().getString("name", "")) {
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case "scatter-variable":
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scatterFunction = LossCalculator.getSingleScatterFunction(pars);
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calculateRatio = true;
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@ -178,7 +179,7 @@ public class ShowLossSpectrumAction extends OneToOneAction<FitState, FitState> {
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}
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public static double calcultateIonRatio(NamedValueSet set, double threshold) {
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UnivariateIntegrator integrator = NumassContext.highDensityIntegrator;
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UnivariateIntegrator integrator = NumassIntegrator.getHighDensityIntegrator();
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UnivariateFunction integrand = LossCalculator.getSingleScatterFunction(set);
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return 1d - integrator.integrate(integrand, 5d, threshold);
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}
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@ -7,6 +7,7 @@ package inr.numass.models;
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import hep.dataforge.fitting.parametric.ParametricFunction;
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import hep.dataforge.values.NamedValueSet;
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import inr.numass.NumassIntegrator;
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import inr.numass.NumassContext;
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import inr.numass.utils.TritiumUtils;
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import org.apache.commons.math3.analysis.UnivariateFunction;
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@ -21,7 +22,7 @@ public class CustomNBkgSpectrum extends NBkgSpectrum {
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public static CustomNBkgSpectrum tritiumBkgSpectrum(ParametricFunction source, double amplitude){
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UnivariateFunction differentialBkgFunction = TritiumUtils.tritiumBackgroundFunction(amplitude);
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UnivariateFunction integralBkgFunction =
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(x) -> NumassContext.defaultIntegrator
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(x) -> NumassIntegrator.getDefaultIntegrator()
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.integrate(differentialBkgFunction, x, 18580d);
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return new CustomNBkgSpectrum(source, integralBkgFunction);
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}
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@ -19,14 +19,12 @@ import hep.dataforge.exceptions.NotDefinedException;
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import hep.dataforge.fitting.parametric.AbstractParametricFunction;
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import hep.dataforge.maths.integration.UnivariateIntegrator;
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import hep.dataforge.values.NamedValueSet;
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import inr.numass.NumassContext;
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import static java.lang.Math.abs;
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import inr.numass.NumassIntegrator;
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import static java.lang.Math.exp;
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import static java.lang.Math.sqrt;
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import org.apache.commons.math3.analysis.UnivariateFunction;
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import static java.lang.Math.abs;
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import static java.lang.Math.abs;
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import static java.lang.Math.abs;
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/**
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*
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@ -37,11 +35,10 @@ public class GunSpectrum extends AbstractParametricFunction {
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private static final String[] list = {"pos", "resA", "sigma"};
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private final double cutoff = 4d;
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protected final UnivariateIntegrator integrator;
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public GunSpectrum() {
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super(list);
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integrator = NumassContext.defaultIntegrator;
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integrator = NumassIntegrator.getDefaultIntegrator();
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}
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@Override
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@ -50,8 +47,10 @@ public class GunSpectrum extends AbstractParametricFunction {
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final double sigma = set.getDouble("sigma");
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final double resA = set.getDouble("resA");
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if(sigma == 0) throw new NotDefinedException();
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if (sigma == 0) {
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throw new NotDefinedException();
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}
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UnivariateFunction integrand;
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switch (parName) {
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case "pos":
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@ -139,13 +138,13 @@ public class GunSpectrum extends AbstractParametricFunction {
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final double pos = set.getDouble("pos");
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final double sigma = set.getDouble("sigma");
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final double resA = set.getDouble("resA");
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if (sigma <1e-5 ) {
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if (sigma < 1e-5) {
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return transmissionValueFast(U, pos, resA);
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}
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UnivariateFunction integrand = (double E) -> transmissionValueFast(U, E, resA) * getGauss(E, pos, sigma);
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if (pos + cutoff * sigma < U) {
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return 0;
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} else if (pos - cutoff * sigma > U * (1 + resA)) {
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@ -46,7 +46,7 @@ public class LossCalculator {
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private static final LossCalculator instance = new LossCalculator();
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private static final UnivariateIntegrator integrator = new GaussRuleIntegrator(100);
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// private static final UnivariateIntegrator tailIntegrator = new GaussRuleIntegrator(50);
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public static UnivariateFunction getSingleScatterFunction() {
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final double A1 = 0.204;
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@ -282,6 +282,7 @@ public class LossCalculator {
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* @return
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*/
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public List<Double> getLossProbabilities(double X) {
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List<Double> res = new ArrayList<>();
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double prob;
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if (X > 0) {
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@ -15,6 +15,7 @@
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*/
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package inr.numass.models;
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import inr.numass.NumassIntegrator;
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import inr.numass.NumassContext;
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import org.apache.commons.math3.analysis.BivariateFunction;
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import org.apache.commons.math3.analysis.UnivariateFunction;
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@ -38,7 +39,7 @@ class LossResConvolution implements BivariateFunction {
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public double value(final double Ein, final double U) {
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UnivariateFunction integrand = (double Eout) -> loss.value(Ein, Eout) * res.value(Eout, U);
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//Энергия в принципе не может быть больше начальной и меньше напряжения
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return NumassContext.defaultIntegrator.integrate(integrand, U, Ein);
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return NumassIntegrator.getDefaultIntegrator().integrate(integrand, U, Ein);
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}
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}
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@ -18,6 +18,7 @@ package inr.numass.models;
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import hep.dataforge.fitting.parametric.AbstractParametricFunction;
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import hep.dataforge.fitting.parametric.ParametricFunction;
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import hep.dataforge.values.NamedValueSet;
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import inr.numass.NumassIntegrator;
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import inr.numass.NumassContext;
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import org.apache.commons.math3.analysis.BivariateFunction;
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import org.apache.commons.math3.analysis.UnivariateFunction;
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@ -58,7 +59,7 @@ class TransmissionConvolution extends AbstractParametricFunction {
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}
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return trans.value(E, U) * spectrum.derivValue(parName, E, set);
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};
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return NumassContext.defaultIntegrator.integrate(integrand, Math.max(U, min), max + 1d);
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return NumassIntegrator.getDefaultIntegrator().integrate(integrand, Math.max(U, min), max + 1d);
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}
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@Override
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@ -80,6 +81,6 @@ class TransmissionConvolution extends AbstractParametricFunction {
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}
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return trans.value(E, U) * spectrum.value(E, set);
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};
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return NumassContext.defaultIntegrator.integrate(integrand, Math.max(U, min), max + 1d);
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return NumassIntegrator.getDefaultIntegrator().integrate(integrand, Math.max(U, min), max + 1d);
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}
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}
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@ -21,6 +21,7 @@ import hep.dataforge.fitting.parametric.ParametricFunction;
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import hep.dataforge.maths.integration.UnivariateIntegrator;
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import hep.dataforge.values.NamedValueSet;
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import hep.dataforge.values.ValueProvider;
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import inr.numass.NumassIntegrator;
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import inr.numass.NumassContext;
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import java.util.List;
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import org.apache.commons.math3.analysis.BivariateFunction;
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@ -101,9 +102,9 @@ public class VariableLossSpectrum extends AbstractParametricFunction {
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UnivariateFunction integrand = (double x) -> transmission.value(x, set) * lossFunction.value(x, U - shift);
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UnivariateIntegrator integrator;
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if (eMax - U > 150) {
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integrator = NumassContext.highDensityIntegrator;
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integrator = NumassIntegrator.getHighDensityIntegrator();
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} else {
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integrator = NumassContext.defaultIntegrator;
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integrator = NumassIntegrator.getDefaultIntegrator();
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}
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return noLossProb * transmission.value(U - shift, set) + integrator.integrate(integrand, U, eMax);
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}
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@ -13,7 +13,12 @@ import static java.lang.Math.exp;
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import static java.lang.Math.sqrt;
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/**
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* A bi-function for beta-spectrum calculation taking energy and final state as input.
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* A bi-function for beta-spectrum calculation taking energy and final state as
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* input.
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* <p>
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* dissertation p.33
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* </p>
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*
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* @author Alexander Nozik <altavir@gmail.com>
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*/
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public class NumassBeta extends AbstractParametricBiFunction {
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@ -25,6 +30,16 @@ public class NumassBeta extends AbstractParametricBiFunction {
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super(list);
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}
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/**
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* Beta spectrum derivative
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*
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* @param n parameter number
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* @param E0
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* @param mnu2
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* @param E
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* @return
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* @throws NotDefinedException
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*/
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private double derivRoot(int n, double E0, double mnu2, double E) throws NotDefinedException {
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double D = E0 - E;//E0-E
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double res;
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@ -71,12 +86,13 @@ public class NumassBeta extends AbstractParametricBiFunction {
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/**
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* Derivative of spectrum with sterile neutrinos
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*
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* @param name
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* @param E
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* @param E0
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* @param pars
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* @return
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* @throws NotDefinedException
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* @throws NotDefinedException
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*/
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private double derivRootsterile(String name, double E, double E0, NamedValueSet pars) throws NotDefinedException {
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double mnu2 = getParameter("mnu2", pars);
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@ -104,11 +120,14 @@ public class NumassBeta extends AbstractParametricBiFunction {
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}
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/**
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* The part independent of neutrino mass. Includes global normalization
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* constant, momentum and Fermi correction
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*
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* @param E
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* @return
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*/
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private double factor(double E) {
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return K * pfactor(E);
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}
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private double pfactor(double E) {
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double me = 0.511006E6;
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double Etot = E + me;
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double pe = sqrt(E * (E + 2d * me));
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@ -118,7 +137,7 @@ public class NumassBeta extends AbstractParametricBiFunction {
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double Fn = y / abs(1d - exp(-y));
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double Fermi = Fn * (1.002037 - 0.001427 * ve);
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double res = Fermi * pe * Etot;
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return res;
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return K * res;
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}
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@Override
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@ -127,11 +146,12 @@ public class NumassBeta extends AbstractParametricBiFunction {
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}
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/**
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* Bare beta spectrum with Mintz negative mass correction
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* Bare beta spectrum with Mainz negative mass correction
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*
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* @param E0
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* @param mnu2
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* @param E
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* @return
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* @return
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*/
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private double root(double E0, double mnu2, double E) {
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/*чистый бета-спектр*/
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@ -155,10 +175,11 @@ public class NumassBeta extends AbstractParametricBiFunction {
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/**
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* beta-spectrum with sterile neutrinos
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*
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* @param E
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* @param E0
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* @param pars
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* @return
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* @return
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*/
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private double rootsterile(double E, double E0, NamedValueSet pars) {
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double mnu2 = getParameter("mnu2", pars);
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@ -189,7 +210,7 @@ public class NumassBeta extends AbstractParametricBiFunction {
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@Override
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public double derivValue(String parName, double fs, double eIn, NamedValueSet pars) {
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double E0 = getParameter("E0", pars);
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return derivRootsterile(parName,eIn, E0 - fs, pars);
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return derivRootsterile(parName, eIn, E0 - fs, pars);
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}
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@Override
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@ -6,6 +6,7 @@
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package inr.numass.models.sterile;
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import hep.dataforge.fitting.parametric.AbstractParametricBiFunction;
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import hep.dataforge.meta.Meta;
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import hep.dataforge.values.NamedValueSet;
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import inr.numass.models.LossCalculator;
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import org.apache.commons.math3.analysis.BivariateFunction;
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@ -21,16 +22,21 @@ public class NumassTransmission extends AbstractParametricBiFunction {
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private final LossCalculator calculator;
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private final BivariateFunction trapFunc;
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public NumassTransmission() {
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// private BicubicInterpolatingFunction cache;
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// private double cachedX;
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// private Meta cacheMeta;
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public NumassTransmission(Meta meta) {
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super(list);
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this.calculator = LossCalculator.instance();
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trapFunc = LossCalculator.getTrapFunction();
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trapFunc = getTrapFunction(meta.getNodeOrEmpty("trapping"));
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// if (meta.hasNode("cache")) {
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// cacheMeta = meta.getNode("cache");
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// }
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}
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public NumassTransmission(BivariateFunction trapFunc) {
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super(list);
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this.calculator = LossCalculator.instance();
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this.trapFunc = trapFunc;
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private BivariateFunction getTrapFunction(Meta meta) {
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return LossCalculator.getTrapFunction();
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}
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@Override
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@ -52,16 +58,34 @@ public class NumassTransmission extends AbstractParametricBiFunction {
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public static double getX(double eIn, NamedValueSet set) {
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//From our article
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return set.getDouble("X")*Math.log(eIn / ION_POTENTIAL) * eIn * ION_POTENTIAL / 1.9580741410115568e6;
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return set.getDouble("X") * Math.log(eIn / ION_POTENTIAL) * eIn * ION_POTENTIAL / 1.9580741410115568e6;
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||||
}
|
||||
|
||||
|
||||
public static double p0(double eIn, NamedValueSet set) {
|
||||
return LossCalculator.instance().getLossProbability(0, getX(eIn, set));
|
||||
}
|
||||
|
||||
// private synchronized void setupCache(double X) {
|
||||
// if (this.cachedX != X) {
|
||||
// double cacheLo = cacheMeta.getDouble("lo", 14000);
|
||||
// double cacheHi = cacheMeta.getDouble("hi", 18575);
|
||||
// int numPoints = cacheMeta.getInt("numPoints", 1000);
|
||||
// double[] eIns = GridCalculator.getUniformUnivariateGrid(cacheLo, cacheHi, numPoints);
|
||||
// double[] eOuts = GridCalculator.getUniformUnivariateGrid(cacheLo, cacheHi, numPoints);
|
||||
// double[][] vals = MathUtils.calculateFunction(calculator.getTotalLossBivariateFunction(X), eOuts, eOuts);
|
||||
// this.cachedX = X;
|
||||
// this.cache = new BicubicInterpolator().interpolate(eIns, eOuts, vals);
|
||||
// }
|
||||
// }
|
||||
@Override
|
||||
public double value(double eIn, double eOut, NamedValueSet set) {
|
||||
return calculator.getTotalLossValue(getX(eIn, set), eIn, eOut) + getParameter("trap", set) * trapFunc.value(eIn, eOut);
|
||||
//calculate X taking into account its energy dependence
|
||||
double X = getX(eIn, set);
|
||||
// loss part
|
||||
double loss = calculator.getTotalLossValue(X, eIn, eOut);
|
||||
//trapping part
|
||||
double trap = getParameter("trap", set) * trapFunc.value(eIn, eOut);
|
||||
return loss + trap;
|
||||
}
|
||||
|
||||
}
|
||||
|
@ -7,11 +7,14 @@ package inr.numass.models.sterile;
|
||||
|
||||
import hep.dataforge.context.Context;
|
||||
import hep.dataforge.context.GlobalContext;
|
||||
import hep.dataforge.description.NodeDef;
|
||||
import hep.dataforge.description.ValueDef;
|
||||
import hep.dataforge.exceptions.NotDefinedException;
|
||||
import hep.dataforge.fitting.parametric.AbstractParametricFunction;
|
||||
import hep.dataforge.fitting.parametric.ParametricBiFunction;
|
||||
import hep.dataforge.meta.Meta;
|
||||
import hep.dataforge.values.NamedValueSet;
|
||||
import inr.numass.NumassIntegrator;
|
||||
import inr.numass.NumassContext;
|
||||
import inr.numass.models.FSS;
|
||||
import java.util.stream.DoubleStream;
|
||||
@ -28,6 +31,10 @@ import org.apache.commons.math3.random.SynchronizedRandomGenerator;
|
||||
*
|
||||
* @author Alexander Nozik
|
||||
*/
|
||||
@NodeDef(name = "resolution")
|
||||
@NodeDef(name = "transmission")
|
||||
@ValueDef(name = "fssFile")
|
||||
|
||||
public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
|
||||
private static final String[] list = {"X", "trap", "E0", "mnu2", "msterile2", "U2"};
|
||||
@ -49,6 +56,8 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
* variables:Eout,U; parameters: "X", "trap"
|
||||
*/
|
||||
private final ParametricBiFunction resolution;
|
||||
|
||||
private boolean useMC;
|
||||
|
||||
public SterileNeutrinoSpectrum(Context context, Meta configuration) {
|
||||
super(list);
|
||||
@ -58,10 +67,15 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
fssDistribution = new EnumeratedRealDistribution(rnd, fss.getEs(), fss.getPs());
|
||||
}
|
||||
|
||||
transmission = new NumassTransmission();
|
||||
transmission = new NumassTransmission(configuration.getNodeOrEmpty("transmission"));
|
||||
resolution = new NumassResolution(configuration.getNode("resolution", Meta.empty()));
|
||||
this.useMC = configuration.getBoolean("useMC",false);
|
||||
}
|
||||
|
||||
|
||||
public SterileNeutrinoSpectrum(Meta configuration) {
|
||||
this(GlobalContext.instance(),configuration);
|
||||
}
|
||||
|
||||
public SterileNeutrinoSpectrum() {
|
||||
this(GlobalContext.instance(), Meta.empty());
|
||||
}
|
||||
@ -96,7 +110,7 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
}
|
||||
|
||||
private boolean useDirect() {
|
||||
return true;
|
||||
return !useMC;
|
||||
}
|
||||
|
||||
@Override
|
||||
@ -104,6 +118,12 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
return source.providesDeriv(name) && transmission.providesDeriv(name) && resolution.providesDeriv(name);
|
||||
}
|
||||
|
||||
/**
|
||||
* Random E generator
|
||||
* @param a
|
||||
* @param b
|
||||
* @return
|
||||
*/
|
||||
private double rndE(double a, double b) {
|
||||
return rnd.nextDouble() * (b - a) + a;
|
||||
}
|
||||
@ -157,6 +177,15 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
return Math.pow(eMax - u, 2d) / 2d * sum / num;
|
||||
}
|
||||
|
||||
/**
|
||||
* Direct Gauss-Legandre integration
|
||||
* @param u
|
||||
* @param sourceFunction
|
||||
* @param transmissionFunction
|
||||
* @param resolutionFunction
|
||||
* @param set
|
||||
* @return
|
||||
*/
|
||||
private double integrateDirect(
|
||||
double u,
|
||||
ParametricBiFunction sourceFunction,
|
||||
@ -175,7 +204,7 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
fsSource = (eIn) -> {
|
||||
double res = 0;
|
||||
for (int i = 0; i < fss.size(); i++) {
|
||||
res += fss.getP(i) * sourceFunction.value(fss.getE(i), u, set);
|
||||
res += fss.getP(i) * sourceFunction.value(fss.getE(i), eIn, set);
|
||||
}
|
||||
return res;
|
||||
};
|
||||
@ -185,7 +214,7 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
|
||||
BivariateFunction transRes = (eIn, usp) -> {
|
||||
UnivariateFunction integrand = (eOut) -> transmissionFunction.value(eIn, eOut, set) * resolutionFunction.value(eOut, usp, set);
|
||||
return NumassContext.defaultIntegrator.integrate(integrand, usp, eIn);
|
||||
return NumassIntegrator.getDefaultIntegrator().integrate(integrand, usp, eIn);
|
||||
};
|
||||
|
||||
UnivariateFunction integrand = (eIn) -> {
|
||||
@ -193,7 +222,7 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
|
||||
return fsSource.value(eIn) * (p0 * resolutionFunction.value(eIn, u, set) + transRes.value(eIn, u));
|
||||
};
|
||||
|
||||
return NumassContext.defaultIntegrator.integrate(integrand, u, eMax);
|
||||
return NumassIntegrator.getDefaultIntegrator().integrate(integrand, u, eMax);
|
||||
}
|
||||
|
||||
}
|
||||
|
Loading…
Reference in New Issue
Block a user