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Alexander Nozik 2016-07-27 20:18:42 +03:00
parent fbcc8eef94
commit 23e2997b0f
14 changed files with 181 additions and 54 deletions
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1
numass-main/build.gradle
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@ -14,6 +14,7 @@ dependencies {
compile project(':dataforge-fx')
compile project(':dataforge-plots')
compile project(':numass-storage')
compile project(':dataforge-grind')
}
task workbench(dependsOn: classes, type: JavaExec){

17
numass-main/src/main/groovy/inr/numass/scripts/SterileDemo.groovy
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@ -42,6 +42,8 @@ import static java.util.Locale.setDefault;
import inr.numass.utils.TritiumUtils;
import inr.numass.data.SpectrumDataAdapter;
import hep.dataforge.io.FittingIOUtils
import hep.dataforge.meta.Meta
import hep.dataforge.grind.GrindMetaBuilder
/**
*
@ -50,9 +52,16 @@ import hep.dataforge.io.FittingIOUtils
setDefault(Locale.US);
ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), 8.3e-5, 13990d, 18600d);
//ParametricFunction beta = new BetaSpectrum();
//ParametricFunction beta = new SterileNeutrinoSpectrum();
//ModularSpectrum beta = new ModularSpectrum(new BetaSpectrum(), 8.3e-5, 13990d, 18600d);
//beta.setCaching(false)
Meta cfg = new GrindMetaBuilder().meta{
resolution(width: 8.3e-5)
}.build();
ParametricFunction beta = new SterileNeutrinoSpectrum(cfg);
NBkgSpectrum spectrum = new NBkgSpectrum(beta);
XYModel model = new XYModel(spectrum, new SpectrumDataAdapter());
@ -65,10 +74,10 @@ allPars.setPar("E0", 18574.94, 1.4);
allPars.setPar("mnu2", 0d, 1d);
allPars.setPar("msterile2", 1000d * 1000d,0);
allPars.setPar("U2", 0.0, 1e-4, -1d, 1d);
allPars.setPar("X", 0.04000, 0.01, 0d, Double.POSITIVE_INFINITY);
allPars.setPar("X", 0.04, 0.01, 0d, Double.POSITIVE_INFINITY);
allPars.setPar("trap", 1.634, 0.01,0d, Double.POSITIVE_INFINITY);
FittingIOUtils.printSpectrum(GlobalContext.out(), spectrum, allPars, 14000.0, 18600.0, 400);
FittingIOUtils.printSpectrum(GlobalContext.out(), spectrum, allPars, 14000, 18600.0, 400);
//SpectrumGenerator generator = new SpectrumGenerator(model, allPars, 12316);
//

4
numass-main/src/main/java/inr/numass/NumassContext.java
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@ -34,10 +34,6 @@ import java.io.PrintWriter;
*/
public class NumassContext extends Context {
public static UnivariateIntegrator defaultIntegrator = new GaussRuleIntegrator(300);
public static UnivariateIntegrator highDensityIntegrator = new GaussRuleIntegrator(500);
public NumassContext(Context parent, Meta config) {
super(parent, "numass", config);
init();

42
numass-main/src/main/java/inr/numass/NumassIntegrator.java Normal file
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@ -0,0 +1,42 @@
/*
* 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;
import hep.dataforge.maths.integration.GaussRuleIntegrator;
import hep.dataforge.maths.integration.UnivariateIntegrator;
/**
*
* @author Alexander Nozik
*/
public class NumassIntegrator {
private static UnivariateIntegrator fastInterator;
private static UnivariateIntegrator defaultIntegrator;
private static UnivariateIntegrator highDensityIntegrator;
public static UnivariateIntegrator getFastInterator() {
if (fastInterator == null) {
fastInterator = new GaussRuleIntegrator(100);
}
return fastInterator;
}
public static UnivariateIntegrator getDefaultIntegrator() {
if (defaultIntegrator == null) {
defaultIntegrator = new GaussRuleIntegrator(300);
}
return defaultIntegrator;
}
public static UnivariateIntegrator getHighDensityIntegrator() {
if (highDensityIntegrator == null) {
highDensityIntegrator = new GaussRuleIntegrator(500);
}
return highDensityIntegrator;
}
}

3
numass-main/src/main/java/inr/numass/actions/ShowLossSpectrumAction.java
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@ -40,6 +40,7 @@ import hep.dataforge.tables.MapPoint;
import hep.dataforge.tables.Table;
import hep.dataforge.tables.XYAdapter;
import hep.dataforge.values.NamedValueSet;
import inr.numass.NumassIntegrator;
import inr.numass.NumassContext;
import inr.numass.models.ExperimentalVariableLossSpectrum;
import inr.numass.models.LossCalculator;
@ -178,7 +179,7 @@ public class ShowLossSpectrumAction extends OneToOneAction<FitState, FitState> {
}
public static double calcultateIonRatio(NamedValueSet set, double threshold) {
UnivariateIntegrator integrator = NumassContext.highDensityIntegrator;
UnivariateIntegrator integrator = NumassIntegrator.getHighDensityIntegrator();
UnivariateFunction integrand = LossCalculator.getSingleScatterFunction(set);
return 1d - integrator.integrate(integrand, 5d, threshold);
}

3
numass-main/src/main/java/inr/numass/models/CustomNBkgSpectrum.java
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@ -7,6 +7,7 @@ package inr.numass.models;
import hep.dataforge.fitting.parametric.ParametricFunction;
import hep.dataforge.values.NamedValueSet;
import inr.numass.NumassIntegrator;
import inr.numass.NumassContext;
import inr.numass.utils.TritiumUtils;
import org.apache.commons.math3.analysis.UnivariateFunction;
@ -21,7 +22,7 @@ public class CustomNBkgSpectrum extends NBkgSpectrum {
public static CustomNBkgSpectrum tritiumBkgSpectrum(ParametricFunction source, double amplitude){
UnivariateFunction differentialBkgFunction = TritiumUtils.tritiumBackgroundFunction(amplitude);
UnivariateFunction integralBkgFunction =
(x) -> NumassContext.defaultIntegrator
(x) -> NumassIntegrator.getDefaultIntegrator()
.integrate(differentialBkgFunction, x, 18580d);
return new CustomNBkgSpectrum(source, integralBkgFunction);
}

11
numass-main/src/main/java/inr/numass/models/GunSpectrum.java
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@ -19,14 +19,12 @@ import hep.dataforge.exceptions.NotDefinedException;
import hep.dataforge.fitting.parametric.AbstractParametricFunction;
import hep.dataforge.maths.integration.UnivariateIntegrator;
import hep.dataforge.values.NamedValueSet;
import inr.numass.NumassContext;
import static java.lang.Math.abs;
import inr.numass.NumassIntegrator;
import static java.lang.Math.exp;
import static java.lang.Math.sqrt;
import org.apache.commons.math3.analysis.UnivariateFunction;
import static java.lang.Math.abs;
import static java.lang.Math.abs;
import static java.lang.Math.abs;
/**
*
@ -38,10 +36,9 @@ public class GunSpectrum extends AbstractParametricFunction {
private final double cutoff = 4d;
protected final UnivariateIntegrator integrator;
public GunSpectrum() {
super(list);
integrator = NumassContext.defaultIntegrator;
integrator = NumassIntegrator.getDefaultIntegrator();
}
@Override
@ -50,7 +47,9 @@ public class GunSpectrum extends AbstractParametricFunction {
final double sigma = set.getDouble("sigma");
final double resA = set.getDouble("resA");
if(sigma == 0) throw new NotDefinedException();
if (sigma == 0) {
throw new NotDefinedException();
}
UnivariateFunction integrand;
switch (parName) {

3
numass-main/src/main/java/inr/numass/models/LossCalculator.java
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@ -46,7 +46,7 @@ public class LossCalculator {
private static final LossCalculator instance = new LossCalculator();
private static final UnivariateIntegrator integrator = new GaussRuleIntegrator(100);
// private static final UnivariateIntegrator tailIntegrator = new GaussRuleIntegrator(50);
public static UnivariateFunction getSingleScatterFunction() {
final double A1 = 0.204;
@ -282,6 +282,7 @@ public class LossCalculator {
* @return
*/
public List<Double> getLossProbabilities(double X) {
List<Double> res = new ArrayList<>();
double prob;
if (X > 0) {

3
numass-main/src/main/java/inr/numass/models/LossResConvolution.java
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@ -15,6 +15,7 @@
*/
package inr.numass.models;
import inr.numass.NumassIntegrator;
import inr.numass.NumassContext;
import org.apache.commons.math3.analysis.BivariateFunction;
import org.apache.commons.math3.analysis.UnivariateFunction;
@ -38,7 +39,7 @@ class LossResConvolution implements BivariateFunction {
public double value(final double Ein, final double U) {
UnivariateFunction integrand = (double Eout) -> loss.value(Ein, Eout) * res.value(Eout, U);
//Энергия в принципе не может быть больше начальной и меньше напряжения
return NumassContext.defaultIntegrator.integrate(integrand, U, Ein);
return NumassIntegrator.getDefaultIntegrator().integrate(integrand, U, Ein);
}
}

5
numass-main/src/main/java/inr/numass/models/TransmissionConvolution.java
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@ -18,6 +18,7 @@ package inr.numass.models;
import hep.dataforge.fitting.parametric.AbstractParametricFunction;
import hep.dataforge.fitting.parametric.ParametricFunction;
import hep.dataforge.values.NamedValueSet;
import inr.numass.NumassIntegrator;
import inr.numass.NumassContext;
import org.apache.commons.math3.analysis.BivariateFunction;
import org.apache.commons.math3.analysis.UnivariateFunction;
@ -58,7 +59,7 @@ class TransmissionConvolution extends AbstractParametricFunction {
}
return trans.value(E, U) * spectrum.derivValue(parName, E, set);
};
return NumassContext.defaultIntegrator.integrate(integrand, Math.max(U, min), max + 1d);
return NumassIntegrator.getDefaultIntegrator().integrate(integrand, Math.max(U, min), max + 1d);
}
@Override
@ -80,6 +81,6 @@ class TransmissionConvolution extends AbstractParametricFunction {
}
return trans.value(E, U) * spectrum.value(E, set);
};
return NumassContext.defaultIntegrator.integrate(integrand, Math.max(U, min), max + 1d);
return NumassIntegrator.getDefaultIntegrator().integrate(integrand, Math.max(U, min), max + 1d);
}
}

5
numass-main/src/main/java/inr/numass/models/VariableLossSpectrum.java
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@ -21,6 +21,7 @@ import hep.dataforge.fitting.parametric.ParametricFunction;
import hep.dataforge.maths.integration.UnivariateIntegrator;
import hep.dataforge.values.NamedValueSet;
import hep.dataforge.values.ValueProvider;
import inr.numass.NumassIntegrator;
import inr.numass.NumassContext;
import java.util.List;
import org.apache.commons.math3.analysis.BivariateFunction;
@ -101,9 +102,9 @@ public class VariableLossSpectrum extends AbstractParametricFunction {
UnivariateFunction integrand = (double x) -> transmission.value(x, set) * lossFunction.value(x, U - shift);
UnivariateIntegrator integrator;
if (eMax - U > 150) {
integrator = NumassContext.highDensityIntegrator;
integrator = NumassIntegrator.getHighDensityIntegrator();
} else {
integrator = NumassContext.defaultIntegrator;
integrator = NumassIntegrator.getDefaultIntegrator();
}
return noLossProb * transmission.value(U - shift, set) + integrator.integrate(integrand, U, eMax);
}

35
numass-main/src/main/java/inr/numass/models/sterile/NumassBeta.java
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@ -13,7 +13,12 @@ import static java.lang.Math.exp;
import static java.lang.Math.sqrt;
/**
* A bi-function for beta-spectrum calculation taking energy and final state as input.
* A bi-function for beta-spectrum calculation taking energy and final state as
* input.
* <p>
* dissertation p.33
* </p>
*
* @author Alexander Nozik <altavir@gmail.com>
*/
public class NumassBeta extends AbstractParametricBiFunction {
@ -25,6 +30,16 @@ public class NumassBeta extends AbstractParametricBiFunction {
super(list);
}
/**
* Beta spectrum derivative
*
* @param n parameter number
* @param E0
* @param mnu2
* @param E
* @return
* @throws NotDefinedException
*/
private double derivRoot(int n, double E0, double mnu2, double E) throws NotDefinedException {
double D = E0 - E;//E0-E
double res;
@ -71,6 +86,7 @@ public class NumassBeta extends AbstractParametricBiFunction {
/**
* Derivative of spectrum with sterile neutrinos
*
* @param name
* @param E
* @param E0
@ -104,11 +120,14 @@ public class NumassBeta extends AbstractParametricBiFunction {
}
/**
* The part independent of neutrino mass. Includes global normalization
* constant, momentum and Fermi correction
*
* @param E
* @return
*/
private double factor(double E) {
return K * pfactor(E);
}
private double pfactor(double E) {
double me = 0.511006E6;
double Etot = E + me;
double pe = sqrt(E * (E + 2d * me));
@ -118,7 +137,7 @@ public class NumassBeta extends AbstractParametricBiFunction {
double Fn = y / abs(1d - exp(-y));
double Fermi = Fn * (1.002037 - 0.001427 * ve);
double res = Fermi * pe * Etot;
return res;
return K * res;
}
@Override
@ -127,7 +146,8 @@ public class NumassBeta extends AbstractParametricBiFunction {
}
/**
* Bare beta spectrum with Mintz negative mass correction
* Bare beta spectrum with Mainz negative mass correction
*
* @param E0
* @param mnu2
* @param E
@ -155,6 +175,7 @@ public class NumassBeta extends AbstractParametricBiFunction {
/**
* beta-spectrum with sterile neutrinos
*
* @param E
* @param E0
* @param pars

38
numass-main/src/main/java/inr/numass/models/sterile/NumassTransmission.java
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@ -6,6 +6,7 @@
package inr.numass.models.sterile;
import hep.dataforge.fitting.parametric.AbstractParametricBiFunction;
import hep.dataforge.meta.Meta;
import hep.dataforge.values.NamedValueSet;
import inr.numass.models.LossCalculator;
import org.apache.commons.math3.analysis.BivariateFunction;
@ -21,16 +22,21 @@ public class NumassTransmission extends AbstractParametricBiFunction {
private final LossCalculator calculator;
private final BivariateFunction trapFunc;
public NumassTransmission() {
// private BicubicInterpolatingFunction cache;
// private double cachedX;
// private Meta cacheMeta;
public NumassTransmission(Meta meta) {
super(list);
this.calculator = LossCalculator.instance();
trapFunc = LossCalculator.getTrapFunction();
trapFunc = getTrapFunction(meta.getNodeOrEmpty("trapping"));
// if (meta.hasNode("cache")) {
// cacheMeta = meta.getNode("cache");
// }
}
public NumassTransmission(BivariateFunction trapFunc) {
super(list);
this.calculator = LossCalculator.instance();
this.trapFunc = trapFunc;
private BivariateFunction getTrapFunction(Meta meta) {
return LossCalculator.getTrapFunction();
}
@Override
@ -59,9 +65,27 @@ public class NumassTransmission extends AbstractParametricBiFunction {
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;
}
}

39
numass-main/src/main/java/inr/numass/models/sterile/SterileNeutrinoSpectrum.java
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@ -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"};
@ -50,6 +57,8 @@ public class SterileNeutrinoSpectrum extends AbstractParametricFunction {
*/
private final ParametricBiFunction resolution;
private boolean useMC;
public SterileNeutrinoSpectrum(Context context, Meta configuration) {
super(list);
rnd = new SynchronizedRandomGenerator(new JDKRandomGenerator());
@ -58,8 +67,13 @@ 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() {
@ -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);
}
}