numass-framework/numass-main/src/main/groovy/inr/numass/scripts/FindExIonRatio.groovy

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/*
* 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.scripts
import hep.dataforge.datafitter.ParamSet
import hep.dataforge.maths.integration.RiemanIntegrator
import hep.dataforge.maths.integration.UnivariateIntegrator
import hep.dataforge.plots.PlotFrame
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import hep.dataforge.plots.data.PlottableXYFunction
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import hep.dataforge.plots.jfreechart.JFreeChartFrame
import org.apache.commons.math3.analysis.UnivariateFunction
import org.apache.commons.math3.analysis.solvers.BisectionSolver
import inr.numass.models.LossCalculator
import inr.numass.models.ResolutionFunction
import inr.numass.NumassContext
ParamSet params = new ParamSet()
.setParValue("exPos", 12.76)
.setParValue("ionPos", 13.95)
.setParValue("exW", 1.2)
.setParValue("ionW", 13.5)
.setParValue("exIonRatio", 4.55)
UnivariateFunction scatterFunction = LossCalculator.getSingleScatterFunction(params);
PlotFrame frame = JFreeChartFrame.drawFrame("Differential scatter function", null);
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frame.add(PlottableXYFunction.plotFunction("differential", scatterFunction, 0, 100, 400));
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UnivariateIntegrator integrator = NumassContext.defaultIntegrator;
double border = 13.6;
UnivariateFunction ratioFunction = {e->integrator.integrate(scatterFunction, 0 , e) / integrator.integrate(scatterFunction, e, 100)}
double ratio = ratioFunction.value(border);
println "The true excitation to ionization ratio with border energy $border is $ratio";
double resolution = 1.5d;
def X = 0.527;
LossCalculator calculator = new LossCalculator();
List<Double> lossProbs = calculator.getGunLossProbabilities(X);
UnivariateFunction newScatterFunction = { double d ->
double res = scatterFunction.value(d);
for(i = 1; i < lossProbs.size(); i++){
res += lossProbs.get(i) * calculator.getLossValue(i, d, 0);
}
return res;
}
UnivariateFunction resolutionValue = {double e ->
if (e <= 0d) {
return 0d;
} else if (e >= resolution) {
return 1d;
} else {
return e/resolution;
}
};
UnivariateFunction integral = {double u ->
if(u <= 0d){
return 0d;
} else {
UnivariateFunction integrand = {double e -> resolutionValue.value(u-e) * newScatterFunction.value(e)};
return integrator.integrate(integrand, 0d, u)
}
}
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frame.add(PlottableXYFunction.plotFunction("integral", integral, 0, 100, 800));
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BisectionSolver solver = new BisectionSolver(1e-3);
UnivariateFunction integralShifted = {u ->
def integr = integral.value(u);
return integr/(1-integr) - ratio;
}
double integralBorder = solver.solve(400, integralShifted, 10d, 20d);
println "The integral border is $integralBorder";
double newBorder = 14.43
double integralValue = integral.value(newBorder);
double err = Math.abs(integralValue/(1-integralValue)/ratio - 1d)
println "The relative error ic case of using $newBorder instead of real one is $err";