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Fixed numass k-task

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Alexander Nozik 2017-10-22 20:46:58 +03:00
parent 6b4dbfd23f
commit 6b8faf4eb7
9 changed files with 449 additions and 435 deletions
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305
numass-main/src/main/java/inr/numass/NumassPlugin.java
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@ -1,305 +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;
import hep.dataforge.actions.ActionManager;
import hep.dataforge.context.BasicPlugin;
import hep.dataforge.context.Context;
import hep.dataforge.context.PluginDef;
import hep.dataforge.kodex.fx.plots.PlotContainer;
import hep.dataforge.maths.MathPlugin;
import hep.dataforge.meta.Meta;
import hep.dataforge.plotfit.PlotFitResultAction;
import hep.dataforge.plots.PlotDataAction;
import hep.dataforge.plots.jfreechart.JFreeChartFrame;
import hep.dataforge.stat.fit.FitManager;
import hep.dataforge.stat.models.ModelManager;
import hep.dataforge.stat.models.WeightedXYModel;
import hep.dataforge.stat.models.XYModel;
import hep.dataforge.tables.ValuesAdapter;
import hep.dataforge.tables.XYAdapter;
import inr.numass.actions.*;
import inr.numass.data.api.NumassAnalyzer;
import inr.numass.data.api.NumassPoint;
import inr.numass.models.*;
import inr.numass.models.sterile.SterileNeutrinoSpectrum;
import inr.numass.tasks.*;
import org.apache.commons.math3.analysis.UnivariateFunction;
import org.apache.commons.math3.util.FastMath;
/**
* @author Alexander Nozik
*/
@PluginDef(group = "inr.numass", name = "numass",
dependsOn = {"hep.dataforge:math", "hep.dataforge:MINUIT"},
support = false,
info = "Numass data analysis tools")
public class NumassPlugin extends BasicPlugin {
/**
* Display a JFreeChart plot frame in a separate stage window
*
* @param title
* @param width
* @param height
* @return
*/
public static JFreeChartFrame displayJFreeChart(String title, double width, double height, Meta meta) {
JFreeChartFrame frame = new JFreeChartFrame(meta);
frame.configureValue("title", title);
PlotContainer.Companion.display(frame, title, width, height);
return frame;
}
public static JFreeChartFrame displayJFreeChart(String title) {
return displayJFreeChart(title, 800, 600, Meta.empty());
}
@Override
public void attach(Context context) {
// StorageManager.buildFrom(context);
super.attach(context);
context.pluginManager().load(new NumassIO());
FitManager fm = context.getFeature(FitManager.class);
loadModels(fm.getModelManager());
loadMath(MathPlugin.buildFrom(context));
ActionManager actions = context.pluginManager().getOrLoad(ActionManager.class);
actions.attach(context);
actions.putAction(MergeDataAction.class);
actions.putAction(MonitorCorrectAction.class);
actions.putAction(SummaryAction.class);
actions.putAction(PlotDataAction.class);
actions.putAction(PlotFitResultAction.class);
actions.putAction(AdjustErrorsAction.class);
actions.putAction(SubstractSpectrumAction.class);
actions.putTask(NumassPrepareTask.class);
actions.putTask(NumassTableFilterTask.class);
actions.putTask(NumassFitScanTask.class);
actions.putTask(NumassSubstractEmptySourceTask.class);
actions.putTask(NumassFitScanSummaryTask.class);
actions.putTask(NumassFitTask.class);
actions.putTask(NumassFitSummaryTask.class);
actions.put(NumassTasksKt.getSelectDataTask());
actions.put(NumassTasksKt.getMonitorTableTask());
}
@Override
public void detach() {
//TODO clean up
super.detach();
}
private void loadMath(MathPlugin math) {
math.registerBivariate("numass.trap.lowFields", (Ei, Ef) -> {
return 3.92e-5 * FastMath.exp(-(Ei - Ef) / 300d) + 1.97e-4 - 6.818e-9 * Ei;
});
math.registerBivariate("numass.trap.nominal", (Ei, Ef) -> {
//return 1.64e-5 * FastMath.exp(-(Ei - Ef) / 300d) + 1.1e-4 - 4e-9 * Ei;
return 1.2e-4 - 4.5e-9 * Ei;
});
math.registerBivariate("numass.resolutionTail", meta -> {
double alpha = meta.getDouble("tailAlpha", 0);
double beta = meta.getDouble("tailBeta", 0);
return (double E, double U) -> 1 - (E - U) * (alpha + E / 1000d * beta) / 1000d;
});
math.registerBivariate("numass.resolutionTail.2017", meta ->
(double E, double U) -> {
double D = E - U;
return 0.99797 - 3.05346E-7 * D - 5.45738E-10 * Math.pow(D, 2) - 6.36105E-14 * Math.pow(D, 3);
});
math.registerBivariate("numass.resolutionTail.2017.mod", meta ->
(double E, double U) -> {
double D = E - U;
return (0.99797 - 3.05346E-7 * D - 5.45738E-10 * Math.pow(D, 2) - 6.36105E-14 * Math.pow(D, 3)) * (1 - 5e-3 * Math.sqrt(E / 1000));
});
}
/**
* Load all numass model factories
*
* @param manager
*/
private void loadModels(ModelManager manager) {
// manager.addModel("modularbeta", (context, an) -> {
// double A = an.getDouble("resolution", 8.3e-5);//8.3e-5
// double from = an.getDouble("from", 14400d);
// double to = an.getDouble("to", 19010d);
// RangedNamedSetSpectrum beta = new BetaSpectrum(getClass().getResourceAsStream("/data/FS.txt"));
// ModularSpectrum sp = new ModularSpectrum(beta, A, from, to);
// NBkgSpectrum spectrum = new NBkgSpectrum(sp);
//
// return new XYModel(spectrum, getAdapter(an));
// });
manager.addModel("scatter", (context, an) -> {
double A = an.getDouble("resolution", 8.3e-5);//8.3e-5
double from = an.getDouble("from", 0);
double to = an.getDouble("to", 0);
ModularSpectrum sp;
if (from == to) {
sp = new ModularSpectrum(new GaussSourceSpectrum(), A);
} else {
sp = new ModularSpectrum(new GaussSourceSpectrum(), A, from, to);
}
NBkgSpectrum spectrum = new NBkgSpectrum(sp);
return new XYModel(spectrum, getAdapter(an));
});
manager.addModel("scatter-empiric", (context, an) -> {
double eGun = an.getDouble("eGun", 19005d);
TransmissionInterpolator interpolator = buildInterpolator(context, an, eGun);
EmpiricalLossSpectrum loss = new EmpiricalLossSpectrum(interpolator, eGun + 5);
NBkgSpectrum spectrum = new NBkgSpectrum(loss);
double weightReductionFactor = an.getDouble("weightReductionFactor", 2.0);
return new WeightedXYModel(spectrum, getAdapter(an), (dp) -> weightReductionFactor);
});
manager.addModel("scatter-empiric-variable", (context, an) -> {
double eGun = an.getDouble("eGun", 19005d);
//builder transmisssion with given data, annotation and smoothing
UnivariateFunction interpolator = buildInterpolator(context, an, eGun);
VariableLossSpectrum loss = VariableLossSpectrum.withData(interpolator, eGun + 5);
double tritiumBackground = an.getDouble("tritiumBkg", 0);
NBkgSpectrum spectrum;
if (tritiumBackground == 0) {
spectrum = new NBkgSpectrum(loss);
} else {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(loss, tritiumBackground);
}
double weightReductionFactor = an.getDouble("weightReductionFactor", 2.0);
WeightedXYModel res = new WeightedXYModel(spectrum, getAdapter(an), (dp) -> weightReductionFactor);
res.setMeta(an);
return res;
});
manager.addModel("scatter-analytic-variable", (context, an) -> {
double eGun = an.getDouble("eGun", 19005d);
VariableLossSpectrum loss = VariableLossSpectrum.withGun(eGun + 5);
double tritiumBackground = an.getDouble("tritiumBkg", 0);
NBkgSpectrum spectrum;
if (tritiumBackground == 0) {
spectrum = new NBkgSpectrum(loss);
} else {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(loss, tritiumBackground);
}
return new XYModel(spectrum, getAdapter(an));
});
manager.addModel("scatter-empiric-experimental", (context, an) -> {
double eGun = an.getDouble("eGun", 19005d);
//builder transmisssion with given data, annotation and smoothing
UnivariateFunction interpolator = buildInterpolator(context, an, eGun);
double smoothing = an.getDouble("lossSmoothing", 0.3);
VariableLossSpectrum loss = ExperimentalVariableLossSpectrum.withData(interpolator, eGun + 5, smoothing);
NBkgSpectrum spectrum = new NBkgSpectrum(loss);
double weightReductionFactor = an.getDouble("weightReductionFactor", 2.0);
WeightedXYModel res
= new WeightedXYModel(spectrum, getAdapter(an), (dp) -> weightReductionFactor);
res.setMeta(an);
return res;
});
manager.addModel("sterile", (context, meta) -> {
SterileNeutrinoSpectrum sp = new SterileNeutrinoSpectrum(context, meta);
NBkgSpectrum spectrum = new NBkgSpectrum(sp);
return new XYModel(spectrum, getAdapter(meta));
});
manager.addModel("gun", (context, an) -> {
GunSpectrum gsp = new GunSpectrum();
double tritiumBackground = an.getDouble("tritiumBkg", 0);
NBkgSpectrum spectrum;
if (tritiumBackground == 0) {
spectrum = new NBkgSpectrum(gsp);
} else {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(gsp, tritiumBackground);
}
return new XYModel(spectrum, getAdapter(an));
});
}
private TransmissionInterpolator buildInterpolator(Context context, Meta an, double eGun) {
String transXName = an.getString("transXName", "Uset");
String transYName = an.getString("transYName", "CR");
double stitchBorder = an.getDouble("stitchBorder", eGun - 7);
int nSmooth = an.getInt("nSmooth", 15);
double w = an.getDouble("w", 0.8);
if (an.hasValue("transFile")) {
String transmissionFile = an.getString("transFile");
return TransmissionInterpolator
.fromFile(context, transmissionFile, transXName, transYName, nSmooth, w, stitchBorder);
} else if (an.hasMeta("transBuildAction")) {
Meta transBuild = an.getMeta("transBuildAction");
try {
return TransmissionInterpolator.fromAction(context,
transBuild, transXName, transYName, nSmooth, w, stitchBorder);
} catch (InterruptedException ex) {
throw new RuntimeException("Transmission builder failed");
}
} else {
throw new RuntimeException("Transmission declaration not found");
}
}
private XYAdapter getAdapter(Meta an) {
if (an.hasMeta(ValuesAdapter.ADAPTER_KEY)) {
return new XYAdapter(an.getMeta(ValuesAdapter.ADAPTER_KEY));
} else {
return new XYAdapter(NumassPoint.HV_KEY, NumassAnalyzer.COUNT_RATE_KEY, NumassAnalyzer.COUNT_RATE_ERROR_KEY);
}
}
}

2
numass-main/src/main/java/inr/numass/tasks/NumassPrepareTask.java
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@ -84,7 +84,7 @@ public class NumassPrepareTask extends AbstractTask<Table> {
); );
model.dependsOn("data", meta.getMetaOrEmpty("data"), "data"); model.dependsOn("select", meta, "data");
} }
private <T, R> DataNode<R> runAction(GenericAction<T, R> action, Context context, DataNode<T> data, Meta meta) { private <T, R> DataNode<R> runAction(GenericAction<T, R> action, Context context, DataNode<T> data, Meta meta) {

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numass-main/src/main/java/inr/numass/tasks/NumassSubstractEmptySourceTask.java
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@ -1,104 +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.tasks;
import hep.dataforge.data.Data;
import hep.dataforge.data.DataNode;
import hep.dataforge.data.DataTree;
import hep.dataforge.data.DataUtils;
import hep.dataforge.io.ColumnedDataWriter;
import hep.dataforge.meta.Meta;
import hep.dataforge.meta.MetaBuilder;
import hep.dataforge.tables.ListTable;
import hep.dataforge.tables.Table;
import hep.dataforge.tables.ValueMap;
import hep.dataforge.values.Values;
import hep.dataforge.workspace.tasks.AbstractTask;
import hep.dataforge.workspace.tasks.TaskModel;
import org.slf4j.LoggerFactory;
import java.io.OutputStream;
import java.util.Optional;
/**
* Created by darksnake on 06-Sep-16.
*/
public class NumassSubstractEmptySourceTask extends AbstractTask<Table> {
@Override
public String getName() {
return "subtractEmpty";
}
@Override
protected DataNode<Table> run(TaskModel model, DataNode<?> data) {
DataTree.Builder<Table> builder = DataTree.builder(Table.class);
DataNode<Table> rootNode = data.getCheckedNode("prepare", Table.class);
Data<Table> emptySource = data.getCheckedNode("empty", Table.class).getData();
rootNode.forEachData(Table.class, input -> {
Data<Table> res = subtract(input, emptySource);
res.getGoal().onComplete((r, err) -> {
if (r != null) {
OutputStream out = model.getContext().io().out("merge", input.getName() + ".subtract");
ColumnedDataWriter.writeTable(out, r,
input.meta().getBuilder().setNode("empty", emptySource.meta()).toString());
}
});
builder.putData(input.getName(), res);
});
return builder.build();
}
@Override
protected void buildModel(TaskModel.Builder model, Meta meta) {
model.dependsOn("prepare", meta, "prepare");
MetaBuilder emptyCfg = new MetaBuilder("prepare")
.setNode(meta.getMeta("prepare"))
.setNode("data", meta.getMeta("empty"))
.setNode(new MetaBuilder("merge").setValue("mergeName", model.getName() + ".empty"));
model.dependsOn("prepare", emptyCfg, "empty");
}
private Data<Table> subtract(Data<Table> mergeData, Data<Table> emptyData) {
return DataUtils.combine(
mergeData,
emptyData,
Table.class,
mergeData.meta(), this::subtract);
}
private Table subtract(Table merge, Table empty) {
ListTable.Builder builder = new ListTable.Builder(merge.getFormat());
merge.getRows().forEach(point -> {
ValueMap.Builder pointBuilder = new ValueMap.Builder(point);
Optional<Values> referencePoint = empty.getRows()
.filter(p -> Math.abs(p.getDouble("Uset") - point.getDouble("Uset")) < 0.1).findFirst();
if (referencePoint.isPresent()) {
pointBuilder.putValue("CR", Math.max(0, point.getDouble("CR") - referencePoint.get().getDouble("CR")));
pointBuilder.putValue("CRerr", Math.sqrt(Math.pow(point.getDouble("CRerr"), 2d) + Math.pow(referencePoint.get().getDouble("CRerr"), 2d)));
} else {
LoggerFactory.getLogger(getClass()).warn("No reference point found for Uset = {}", point.getDouble("Uset"));
}
builder.row(pointBuilder.build());
});
return builder.build();
}
}

305
numass-main/src/main/kotlin/inr/numass/NumassPlugin.kt Normal file
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@ -0,0 +1,305 @@
/*
* 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
import hep.dataforge.actions.ActionManager
import hep.dataforge.context.BasicPlugin
import hep.dataforge.context.Context
import hep.dataforge.context.PluginDef
import hep.dataforge.kodex.fx.plots.PlotContainer
import hep.dataforge.maths.MathPlugin
import hep.dataforge.meta.Meta
import hep.dataforge.plotfit.PlotFitResultAction
import hep.dataforge.plots.PlotDataAction
import hep.dataforge.plots.jfreechart.JFreeChartFrame
import hep.dataforge.stat.fit.FitManager
import hep.dataforge.stat.models.ModelManager
import hep.dataforge.stat.models.WeightedXYModel
import hep.dataforge.stat.models.XYModel
import hep.dataforge.tables.ValuesAdapter
import hep.dataforge.tables.XYAdapter
import inr.numass.actions.*
import inr.numass.data.api.NumassAnalyzer
import inr.numass.data.api.NumassPoint
import inr.numass.models.*
import inr.numass.models.sterile.SterileNeutrinoSpectrum
import inr.numass.tasks.*
import org.apache.commons.math3.analysis.BivariateFunction
import org.apache.commons.math3.util.FastMath
/**
* @author Alexander Nozik
*/
@PluginDef(
group = "inr.numass",
name = "numass",
dependsOn = arrayOf("hep.dataforge:math", "hep.dataforge:MINUIT"),
support = false,
info = "Numass data analysis tools"
)
class NumassPlugin : BasicPlugin() {
override fun attach(context: Context) {
// StorageManager.buildFrom(context);
super.attach(context)
context.pluginManager().load(NumassIO())
val fm = context.getFeature(FitManager::class.java)
loadModels(fm.modelManager)
loadMath(MathPlugin.buildFrom(context))
val actions = context.pluginManager().getOrLoad(ActionManager::class.java)
actions.attach(context)
actions.putAction(MergeDataAction::class.java)
actions.putAction(MonitorCorrectAction::class.java)
actions.putAction(SummaryAction::class.java)
actions.putAction(PlotDataAction::class.java)
actions.putAction(PlotFitResultAction::class.java)
actions.putAction(AdjustErrorsAction::class.java)
actions.putAction(SubstractSpectrumAction::class.java)
//actions.putTask(NumassPrepareTask::class.java)
actions.putTask(NumassTableFilterTask::class.java)
actions.putTask(NumassFitScanTask::class.java)
actions.putTask(NumassFitScanSummaryTask::class.java)
actions.putTask(NumassFitTask::class.java)
actions.putTask(NumassFitSummaryTask::class.java)
actions.put(selectDataTask)
actions.put(analyzeTask)
actions.put(mergeTask)
actions.put(mergeEmptyTask)
actions.put(monitorTableTask)
actions.put(subtractEmptyTask)
}
override fun detach() {
//TODO clean up
super.detach()
}
private fun loadMath(math: MathPlugin) {
math.registerBivariate("numass.trap.lowFields") { Ei, Ef -> 3.92e-5 * FastMath.exp(-(Ei - Ef) / 300.0) + 1.97e-4 - 6.818e-9 * Ei }
math.registerBivariate("numass.trap.nominal") { Ei, Ef ->
//return 1.64e-5 * FastMath.exp(-(Ei - Ef) / 300d) + 1.1e-4 - 4e-9 * Ei;
1.2e-4 - 4.5e-9 * Ei
}
math.registerBivariate("numass.resolutionTail") { meta ->
val alpha = meta.getDouble("tailAlpha", 0.0)!!
val beta = meta.getDouble("tailBeta", 0.0)!!
BivariateFunction { E: Double, U: Double -> 1 - (E - U) * (alpha + E / 1000.0 * beta) / 1000.0 }
}
math.registerBivariate("numass.resolutionTail.2017") { meta ->
BivariateFunction { E: Double, U: Double ->
val D = E - U
0.99797 - 3.05346E-7 * D - 5.45738E-10 * Math.pow(D, 2.0) - 6.36105E-14 * Math.pow(D, 3.0)
}
}
math.registerBivariate("numass.resolutionTail.2017.mod") { meta ->
BivariateFunction { E: Double, U: Double ->
val D = E - U
(0.99797 - 3.05346E-7 * D - 5.45738E-10 * Math.pow(D, 2.0) - 6.36105E-14 * Math.pow(D, 3.0)) * (1 - 5e-3 * Math.sqrt(E / 1000))
}
}
}
/**
* Load all numass model factories
*
* @param manager
*/
private fun loadModels(manager: ModelManager) {
// manager.addModel("modularbeta", (context, an) -> {
// double A = an.getDouble("resolution", 8.3e-5);//8.3e-5
// double from = an.getDouble("from", 14400d);
// double to = an.getDouble("to", 19010d);
// RangedNamedSetSpectrum beta = new BetaSpectrum(getClass().getResourceAsStream("/data/FS.txt"));
// ModularSpectrum sp = new ModularSpectrum(beta, A, from, to);
// NBkgSpectrum spectrum = new NBkgSpectrum(sp);
//
// return new XYModel(spectrum, getAdapter(an));
// });
manager.addModel("scatter") { context, an ->
val A = an.getDouble("resolution", 8.3e-5)!!//8.3e-5
val from = an.getDouble("from", 0.0)!!
val to = an.getDouble("to", 0.0)!!
val sp: ModularSpectrum
if (from == to) {
sp = ModularSpectrum(GaussSourceSpectrum(), A)
} else {
sp = ModularSpectrum(GaussSourceSpectrum(), A, from, to)
}
val spectrum = NBkgSpectrum(sp)
XYModel(spectrum, getAdapter(an))
}
manager.addModel("scatter-empiric") { context, an ->
val eGun = an.getDouble("eGun", 19005.0)!!
val interpolator = buildInterpolator(context, an, eGun)
val loss = EmpiricalLossSpectrum(interpolator, eGun + 5)
val spectrum = NBkgSpectrum(loss)
val weightReductionFactor = an.getDouble("weightReductionFactor", 2.0)!!
WeightedXYModel(spectrum, getAdapter(an)) { dp -> weightReductionFactor }
}
manager.addModel("scatter-empiric-variable") { context, an ->
val eGun = an.getDouble("eGun", 19005.0)!!
//builder transmisssion with given data, annotation and smoothing
val interpolator = buildInterpolator(context, an, eGun)
val loss = VariableLossSpectrum.withData(interpolator, eGun + 5)
val tritiumBackground = an.getDouble("tritiumBkg", 0.0)!!
val spectrum: NBkgSpectrum
if (tritiumBackground == 0.0) {
spectrum = NBkgSpectrum(loss)
} else {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(loss, tritiumBackground)
}
val weightReductionFactor = an.getDouble("weightReductionFactor", 2.0)!!
val res = WeightedXYModel(spectrum, getAdapter(an)) { dp -> weightReductionFactor }
res.meta = an
res
}
manager.addModel("scatter-analytic-variable") { context, an ->
val eGun = an.getDouble("eGun", 19005.0)!!
val loss = VariableLossSpectrum.withGun(eGun + 5)
val tritiumBackground = an.getDouble("tritiumBkg", 0.0)!!
val spectrum: NBkgSpectrum
if (tritiumBackground == 0.0) {
spectrum = NBkgSpectrum(loss)
} else {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(loss, tritiumBackground)
}
XYModel(spectrum, getAdapter(an))
}
manager.addModel("scatter-empiric-experimental") { context, an ->
val eGun = an.getDouble("eGun", 19005.0)!!
//builder transmisssion with given data, annotation and smoothing
val interpolator = buildInterpolator(context, an, eGun)
val smoothing = an.getDouble("lossSmoothing", 0.3)!!
val loss = ExperimentalVariableLossSpectrum.withData(interpolator, eGun + 5, smoothing)
val spectrum = NBkgSpectrum(loss)
val weightReductionFactor = an.getDouble("weightReductionFactor", 2.0)!!
val res = WeightedXYModel(spectrum, getAdapter(an)) { dp -> weightReductionFactor }
res.meta = an
res
}
manager.addModel("sterile") { context, meta ->
val sp = SterileNeutrinoSpectrum(context, meta)
val spectrum = NBkgSpectrum(sp)
XYModel(spectrum, getAdapter(meta))
}
manager.addModel("gun") { context, an ->
val gsp = GunSpectrum()
val tritiumBackground = an.getDouble("tritiumBkg", 0.0)!!
val spectrum: NBkgSpectrum
if (tritiumBackground == 0.0) {
spectrum = NBkgSpectrum(gsp)
} else {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(gsp, tritiumBackground)
}
XYModel(spectrum, getAdapter(an))
}
}
private fun buildInterpolator(context: Context, an: Meta, eGun: Double): TransmissionInterpolator {
val transXName = an.getString("transXName", "Uset")
val transYName = an.getString("transYName", "CR")
val stitchBorder = an.getDouble("stitchBorder", eGun - 7)!!
val nSmooth = an.getInt("nSmooth", 15)!!
val w = an.getDouble("w", 0.8)!!
if (an.hasValue("transFile")) {
val transmissionFile = an.getString("transFile")
return TransmissionInterpolator
.fromFile(context, transmissionFile, transXName, transYName, nSmooth, w, stitchBorder)
} else if (an.hasMeta("transBuildAction")) {
val transBuild = an.getMeta("transBuildAction")
try {
return TransmissionInterpolator.fromAction(context,
transBuild, transXName, transYName, nSmooth, w, stitchBorder)
} catch (ex: InterruptedException) {
throw RuntimeException("Transmission builder failed")
}
} else {
throw RuntimeException("Transmission declaration not found")
}
}
private fun getAdapter(an: Meta): XYAdapter {
return if (an.hasMeta(ValuesAdapter.ADAPTER_KEY)) {
XYAdapter(an.getMeta(ValuesAdapter.ADAPTER_KEY))
} else {
XYAdapter(NumassPoint.HV_KEY, NumassAnalyzer.COUNT_RATE_KEY, NumassAnalyzer.COUNT_RATE_ERROR_KEY)
}
}
}
/**
* Display a JFreeChart plot frame in a separate stage window
*
* @param title
* @param width
* @param height
* @return
*/
@JvmOverloads fun displayJFreeChart(title: String, width: Double = 800.0, height: Double = 600.0, meta: Meta = Meta.empty()): JFreeChartFrame {
val frame = JFreeChartFrame(meta)
frame.configureValue("title", title)
PlotContainer.display(frame, title, width, height)
return frame
}

31
numass-main/src/main/kotlin/inr/numass/NumassUtils.kt
View File

@ -15,6 +15,7 @@
*/ */
package inr.numass package inr.numass
import hep.dataforge.context.Context
import hep.dataforge.data.DataNode import hep.dataforge.data.DataNode
import hep.dataforge.data.DataSet import hep.dataforge.data.DataSet
import hep.dataforge.io.envelopes.DefaultEnvelopeType import hep.dataforge.io.envelopes.DefaultEnvelopeType
@ -26,7 +27,11 @@ import hep.dataforge.io.markup.SimpleMarkupRenderer
import hep.dataforge.meta.Meta import hep.dataforge.meta.Meta
import hep.dataforge.meta.MetaBuilder import hep.dataforge.meta.MetaBuilder
import hep.dataforge.plots.jfreechart.JFreeChartFrame import hep.dataforge.plots.jfreechart.JFreeChartFrame
import hep.dataforge.tables.ListTable
import hep.dataforge.tables.Table
import hep.dataforge.tables.ValueMap
import hep.dataforge.values.Values import hep.dataforge.values.Values
import inr.numass.data.api.NumassAnalyzer
import inr.numass.data.api.NumassPoint import inr.numass.data.api.NumassPoint
import inr.numass.data.api.NumassSet import inr.numass.data.api.NumassSet
import inr.numass.utils.ExpressionUtils import inr.numass.utils.ExpressionUtils
@ -190,3 +195,29 @@ fun addSetMarkers(frame: JFreeChartFrame, sets: Collection<NumassSet>) {
runLater { jfcPlot.addDomainMarker(marker) } runLater { jfcPlot.addDomainMarker(marker) }
} }
} }
/**
* Subtract one energy spectrum from the other one
*/
fun subtract(context: Context, merge: Table, empty: Table): Table {
val builder = ListTable.Builder(merge.format)
merge.rows.forEach { point ->
val pointBuilder = ValueMap.Builder(point)
val referencePoint = empty.rows
.filter { p -> Math.abs(p.getDouble(NumassPoint.HV_KEY)!! - point.getDouble(NumassPoint.HV_KEY)!!) < 0.1 }.findFirst()
if (referencePoint.isPresent) {
pointBuilder.putValue(
NumassAnalyzer.COUNT_RATE_KEY,
Math.max(0.0, point.getDouble(NumassAnalyzer.COUNT_RATE_KEY)!! - referencePoint.get().getDouble(NumassAnalyzer.COUNT_RATE_KEY)!!)
)
pointBuilder.putValue(
NumassAnalyzer.COUNT_RATE_ERROR_KEY,
Math.sqrt(Math.pow(point.getDouble(NumassAnalyzer.COUNT_RATE_ERROR_KEY)!!, 2.0) + Math.pow(referencePoint.get().getDouble(NumassAnalyzer.COUNT_RATE_ERROR_KEY)!!, 2.0)))
} else {
context.logger.warn("No reference point found for voltage = {}", point.getDouble(NumassPoint.HV_KEY))
}
builder.row(pointBuilder.build())
}
return builder.build()
}

89
numass-main/src/main/kotlin/inr/numass/tasks/NumassTasks.kt
View File

@ -1,6 +1,11 @@
package inr.numass.tasks package inr.numass.tasks
import hep.dataforge.data.CustomDataFilter import hep.dataforge.data.CustomDataFilter
import hep.dataforge.data.DataSet
import hep.dataforge.data.DataTree
import hep.dataforge.data.DataUtils
import hep.dataforge.description.ValueDef
import hep.dataforge.io.ColumnedDataWriter
import hep.dataforge.kodex.configure import hep.dataforge.kodex.configure
import hep.dataforge.kodex.fx.plots.PlotManager import hep.dataforge.kodex.fx.plots.PlotManager
import hep.dataforge.kodex.fx.plots.plus import hep.dataforge.kodex.fx.plots.plus
@ -11,21 +16,26 @@ import hep.dataforge.plots.jfreechart.JFreeChartFrame
import hep.dataforge.tables.ListTable import hep.dataforge.tables.ListTable
import hep.dataforge.tables.Table import hep.dataforge.tables.Table
import hep.dataforge.tables.XYAdapter import hep.dataforge.tables.XYAdapter
import hep.dataforge.values.ValueType
import inr.numass.NumassUtils import inr.numass.NumassUtils
import inr.numass.actions.MergeDataAction
import inr.numass.actions.MergeDataAction.MERGE_NAME
import inr.numass.addSetMarkers import inr.numass.addSetMarkers
import inr.numass.data.analyzers.SmartAnalyzer import inr.numass.data.analyzers.SmartAnalyzer
import inr.numass.data.api.NumassSet import inr.numass.data.api.NumassSet
import inr.numass.subtract
val selectDataTask = task("select") { val selectDataTask = task("select") {
model { meta -> model { meta ->
data("*") data("*")
configure(meta.getMetaOrEmpty("data")) configure(meta.getMetaOrEmpty("data"))
} }
transform { data -> transform<NumassSet, NumassSet> { data ->
CustomDataFilter(meta).filter<NumassSet>(data.checked(NumassSet::class.java)) CustomDataFilter(meta).filter<NumassSet>(data.checked(NumassSet::class.java))
} }
} }
@ValueDef(name = "showPlot", type = arrayOf(ValueType.BOOLEAN), info = "Show plot after complete")
val monitorTableTask = task("monitor") { val monitorTableTask = task("monitor") {
model { meta -> model { meta ->
dependsOn("select", meta) dependsOn("select", meta)
@ -45,6 +55,7 @@ val monitorTableTask = task("monitor") {
.map { it -> analyzer.analyzePoint(it, analyzerMeta) } .map { it -> analyzer.analyzePoint(it, analyzerMeta) }
).build() ).build()
if (meta.getBoolean("showPlot", true)) {
context.provide("plots", PlotManager::class.java).ifPresent { context.provide("plots", PlotManager::class.java).ifPresent {
it.display(stage = "monitor") { it.display(stage = "monitor") {
configure { configure {
@ -64,6 +75,7 @@ val monitorTableTask = task("monitor") {
} }
} }
} }
}
context.io().out("numass.monitor", name).use { context.io().out("numass.monitor", name).use {
NumassUtils.write(it, meta, res) NumassUtils.write(it, meta, res)
@ -73,3 +85,78 @@ val monitorTableTask = task("monitor") {
} }
} }
} }
val analyzeTask = task("analyze") {
model { meta ->
dependsOn("select", meta);
configure(meta.getMetaOrEmpty("analyzer"))
}
pipe<NumassSet, Table> {
result { set ->
SmartAnalyzer().analyzeSet(set, meta).also { res ->
context.io().out("numass.analyze", name).use {
NumassUtils.write(it, meta, res)
}
}
}
}
}
val mergeTask = task("merge") {
model { meta ->
dependsOn("analyze", meta)
configure(meta.getMetaOrEmpty("merge"))
}
action<Table, Table>(MergeDataAction())
}
val mergeEmptyTask = task("empty") {
model { meta ->
if (!meta.hasMeta("empty")) {
throw RuntimeException("Empty source data not found ");
}
//replace data node by "empty" node
val newMeta = meta.builder
.removeNode("data")
.removeNode("empty")
.setNode("data", meta.getMeta("empty"))
.setValue(MERGE_NAME, meta.getString(MERGE_NAME, "") + "_empty");
dependsOn("merge", newMeta)
}
transform<Table, Table> { data ->
val builder = DataSet.builder(Table::class.java)
data.forEach {
builder.putData(it.name + "_empty", it.anonymize());
}
builder.build()
}
}
val subtractEmptyTask = task("dif") {
model { meta ->
dependsOn("merge", meta, "data")
dependsOn("empty", meta, "empty")
}
transform<Table,Table> { data ->
val builder = DataTree.builder(Table::class.java)
val rootNode = data.getCheckedNode<Table>("data", Table::class.java)
val empty = data.getCheckedNode<Table>("empty", Table::class.java).data
rootNode.forEachData(Table::class.java, { input ->
val res = DataUtils.combine(input, empty, Table::class.java, input.meta()) { mergeData, emptyData ->
subtract(context, mergeData, emptyData)
}
res.goal.onComplete { r, _ ->
if (r != null) {
val out = context.io().out("numass.merge", input.name + "_subtract")
ColumnedDataWriter.writeTable(out, r,
input.meta().builder.setNode("empty", empty.meta()).toString())
}
}
builder.putData(input.name, res)
})
builder.build()
}
}

4
numass-main/src/test/java/inr/numass/models/PlotScatter.java
View File

@ -16,7 +16,7 @@
package inr.numass.models; package inr.numass.models;
import hep.dataforge.stat.fit.ParamSet; import hep.dataforge.stat.fit.ParamSet;
import inr.numass.NumassPlugin; import inr.numass.NumassPluginKt;
/** /**
* *
@ -36,6 +36,6 @@ public class PlotScatter {
+ "'ionW' = 11.33 ± 0.43\n" + "'ionW' = 11.33 ± 0.43\n"
+ "'exIonRatio' = 4.83 ± 0.36" + "'exIonRatio' = 4.83 ± 0.36"
); );
LossCalculator.plotScatter(NumassPlugin.displayJFreeChart("Loss function"), pars); LossCalculator.plotScatter(NumassPluginKt.displayJFreeChart("Loss function"), pars);
} }
} }

8
numass-main/src/test/java/inr/numass/models/TestNeLossParametrisation.java
View File

@ -18,7 +18,7 @@ package inr.numass.models;
import hep.dataforge.maths.integration.GaussRuleIntegrator; import hep.dataforge.maths.integration.GaussRuleIntegrator;
import hep.dataforge.plots.PlotFrame; import hep.dataforge.plots.PlotFrame;
import hep.dataforge.plots.data.XYFunctionPlot; import hep.dataforge.plots.data.XYFunctionPlot;
import inr.numass.NumassPlugin; import inr.numass.NumassPluginKt;
import org.apache.commons.math3.analysis.UnivariateFunction; import org.apache.commons.math3.analysis.UnivariateFunction;
/** /**
@ -32,7 +32,7 @@ public class TestNeLossParametrisation {
* @param args the command line arguments * @param args the command line arguments
*/ */
public static void main(String[] args) { public static void main(String[] args) {
PlotFrame frame = NumassPlugin.displayJFreeChart("Loss parametrisation test"); PlotFrame frame = NumassPluginKt.displayJFreeChart("Loss parametrisation test");
//JFreeChartFrame.drawFrame("Loss parametrisation test", null); //JFreeChartFrame.drawFrame("Loss parametrisation test", null);
UnivariateFunction oldFunction = LossCalculator.getSingleScatterFunction(); UnivariateFunction oldFunction = LossCalculator.getSingleScatterFunction();
UnivariateFunction newFunction = getSingleScatterFunction(12.86, 16.78, 1.65, 12.38, 4.79); UnivariateFunction newFunction = getSingleScatterFunction(12.86, 16.78, 1.65, 12.38, 4.79);
@ -41,8 +41,8 @@ public class TestNeLossParametrisation {
System.out.println(norm); System.out.println(norm);
frame.add(XYFunctionPlot.plotFunction("old", x->oldFunction.value(x), 0, 30, 300)); frame.add(XYFunctionPlot.plotFunction("old", oldFunction::value, 0, 30, 300));
frame.add(XYFunctionPlot.plotFunction("new", x->newFunction.value(x), 0, 30, 300)); frame.add(XYFunctionPlot.plotFunction("new", newFunction::value, 0, 30, 300));
} }
public static UnivariateFunction getSingleScatterFunction( public static UnivariateFunction getSingleScatterFunction(

4
numass-main/src/test/java/inr/numass/models/TransmissionInterpolatorTest.java
View File

@ -19,7 +19,7 @@ import hep.dataforge.context.Global;
import hep.dataforge.plots.data.DataPlot; import hep.dataforge.plots.data.DataPlot;
import hep.dataforge.plots.data.XYFunctionPlot; import hep.dataforge.plots.data.XYFunctionPlot;
import hep.dataforge.plots.jfreechart.JFreeChartFrame; import hep.dataforge.plots.jfreechart.JFreeChartFrame;
import inr.numass.NumassPlugin; import inr.numass.NumassPluginKt;
/** /**
* *
@ -28,7 +28,7 @@ import inr.numass.NumassPlugin;
public class TransmissionInterpolatorTest { public class TransmissionInterpolatorTest {
public static void main(String[] args) { public static void main(String[] args) {
JFreeChartFrame frame = NumassPlugin.displayJFreeChart("TransmissionInterpolatorTest"); JFreeChartFrame frame = NumassPluginKt.displayJFreeChart("TransmissionInterpolatorTest");
//JFreeChartFrame.drawFrame("TransmissionInterpolatorTest", null); //JFreeChartFrame.drawFrame("TransmissionInterpolatorTest", null);
TransmissionInterpolator interpolator = TransmissionInterpolator.fromFile(Global.instance(), TransmissionInterpolator interpolator = TransmissionInterpolator.fromFile(Global.instance(),
"d:\\sterile-new\\loss2014-11\\.dataforge\\merge\\empty_sum.onComplete", "Uset", "CR", 15, 0.8, 19002d); "d:\\sterile-new\\loss2014-11\\.dataforge\\merge\\empty_sum.onComplete", "Uset", "CR", 15, 0.8, 19002d);