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build fix

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This commit is contained in:
Alexander Nozik 2018-01-15 16:49:56 +03:00
parent 8ddf4a30f3
commit 1aa7f0edf5
10 changed files with 42 additions and 48 deletions
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6
numass-main/src/main/java/hep/dataforge/plotfit/PlotFitResultAction.java
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@ -32,7 +32,6 @@ import hep.dataforge.tables.Adapters;
import hep.dataforge.tables.NavigableValuesSource;
import hep.dataforge.tables.ValuesAdapter;
import java.util.function.Function;
import java.util.stream.StreamSupport;
/**
@ -63,13 +62,12 @@ public class PlotFitResultAction extends OneToOneAction<FitResult, FitResult> {
throw new RuntimeException("No adapter defined for data interpretation");
}
Function<Double, Double> function = (x) -> model.getSpectrum().value(x, input.getParameters());
PlotFrame frame = PlotUtils.getPlotManager(context)
.getPlotFrame(getName(), name, metaData.getMeta("frame", Meta.empty()));
XYFunctionPlot fit = new XYFunctionPlot("fit");
fit.setDensity(100, false);
XYFunctionPlot fit = new XYFunctionPlot("fit",(x) -> model.getSpectrum().value(x, input.getParameters()));
fit.setDensity(100);
fit.setSmoothing(true);
// ensuring all data points are calculated explicitly
StreamSupport.stream(data.spliterator(), false)

4
numass-main/src/main/java/inr/numass/Numass.java
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@ -48,7 +48,7 @@ public class Numass {
.ln()
.text("\t")
.content(
MarkupUtils.INSTANCE.markupDescriptor(Descriptors.buildDescriptor("method::hep.dataforge.data.DataManager.read"))
MarkupUtils.markupDescriptor(Descriptors.buildDescriptor("method::hep.dataforge.data.DataManager.read"))
)
.ln()
.text("***Allowed actions***", "red")
@ -60,7 +60,7 @@ public class Numass {
am.getAllActions()
.map(name -> am.optAction(name).get())
.map(ActionDescriptor::build).forEach(descriptor ->
builder.text("\t").content(MarkupUtils.INSTANCE.markupDescriptor(descriptor))
builder.text("\t").content(MarkupUtils.markupDescriptor(descriptor))
);
builder.text("***End of actions list***", "red");

8
numass-main/src/main/kotlin/inr/numass/NumassIO.kt
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@ -126,7 +126,7 @@ class NumassIO : BasicIOManager() {
// String output = source.meta().getString("output", this.meta().getString("output", fileName + ".onComplete"));
outputFile = dir.resolve(fileName)
return if (context.getBoolean("numass.consoleOutput", false)!!) {
return if (context.getBoolean("numass.consoleOutput", false)) {
TeeOutputStream(Files.newOutputStream(outputFile), System.out)
} else {
Files.newOutputStream(outputFile)
@ -153,10 +153,8 @@ fun FitResult.display(context: Context, stage: String = "fit") {
val func = { x: Double -> model.spectrum.value(x, parameters) }
val fit = XYFunctionPlot("fit")
fit.setDensity(100, false)
fit.setSmoothing(true)
fit.setFunction(func)
val fit = XYFunctionPlot("fit",func)
fit.density = 100
// ensuring all data points are calculated explicitly
data.rows.map { dp -> Adapters.getXValue(adapter, dp).doubleValue() }.sorted().forEach { fit.calculateIn(it) }

38
numass-main/src/main/kotlin/inr/numass/NumassPlugin.kt
View File

@ -81,8 +81,8 @@ class NumassPlugin : BasicPlugin() {
}
math.registerBivariate("numass.resolutionTail") { meta ->
val alpha = meta.getDouble("tailAlpha", 0.0)!!
val beta = meta.getDouble("tailBeta", 0.0)!!
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 }
}
@ -121,9 +121,9 @@ class NumassPlugin : BasicPlugin() {
// });
manager.addModel("scatter") { context, meta ->
val A = meta.getDouble("resolution", 8.3e-5)!!//8.3e-5
val from = meta.getDouble("from", 0.0)!!
val to = meta.getDouble("to", 0.0)!!
val A = meta.getDouble("resolution", 8.3e-5)//8.3e-5
val from = meta.getDouble("from", 0.0)
val to = meta.getDouble("to", 0.0)
val sp: ModularSpectrum
sp = if (from == to) {
@ -138,27 +138,27 @@ class NumassPlugin : BasicPlugin() {
}
manager.addModel("scatter-empiric") { context, meta ->
val eGun = meta.getDouble("eGun", 19005.0)!!
val eGun = meta.getDouble("eGun", 19005.0)
val interpolator = buildInterpolator(context, meta, eGun)
val loss = EmpiricalLossSpectrum(interpolator, eGun + 5)
val spectrum = NBkgSpectrum(loss)
val weightReductionFactor = meta.getDouble("weightReductionFactor", 2.0)!!
val weightReductionFactor = meta.getDouble("weightReductionFactor", 2.0)
WeightedXYModel(meta, getAdapter(meta), spectrum) { dp -> weightReductionFactor }
}
manager.addModel("scatter-empiric-variable") { context, meta ->
val eGun = meta.getDouble("eGun", 19005.0)!!
val eGun = meta.getDouble("eGun", 19005.0)
//builder transmisssion with given data, annotation and smoothing
val interpolator = buildInterpolator(context, meta, eGun)
val loss = VariableLossSpectrum.withData(interpolator, eGun + 5)
val tritiumBackground = meta.getDouble("tritiumBkg", 0.0)!!
val tritiumBackground = meta.getDouble("tritiumBkg", 0.0)
val spectrum: NBkgSpectrum
if (tritiumBackground == 0.0) {
@ -167,17 +167,17 @@ class NumassPlugin : BasicPlugin() {
spectrum = CustomNBkgSpectrum.tritiumBkgSpectrum(loss, tritiumBackground)
}
val weightReductionFactor = meta.getDouble("weightReductionFactor", 2.0)!!
val weightReductionFactor = meta.getDouble("weightReductionFactor", 2.0)
WeightedXYModel(meta, getAdapter(meta), spectrum) { dp -> weightReductionFactor }
}
manager.addModel("scatter-analytic-variable") { context, meta ->
val eGun = meta.getDouble("eGun", 19005.0)!!
val eGun = meta.getDouble("eGun", 19005.0)
val loss = VariableLossSpectrum.withGun(eGun + 5)
val tritiumBackground = meta.getDouble("tritiumBkg", 0.0)!!
val tritiumBackground = meta.getDouble("tritiumBkg", 0.0)
val spectrum: NBkgSpectrum
if (tritiumBackground == 0.0) {
@ -190,18 +190,18 @@ class NumassPlugin : BasicPlugin() {
}
manager.addModel("scatter-empiric-experimental") { context, meta ->
val eGun = meta.getDouble("eGun", 19005.0)!!
val eGun = meta.getDouble("eGun", 19005.0)
//builder transmisssion with given data, annotation and smoothing
val interpolator = buildInterpolator(context, meta, eGun)
val smoothing = meta.getDouble("lossSmoothing", 0.3)!!
val smoothing = meta.getDouble("lossSmoothing", 0.3)
val loss = ExperimentalVariableLossSpectrum.withData(interpolator, eGun + 5, smoothing)
val spectrum = NBkgSpectrum(loss)
val weightReductionFactor = meta.getDouble("weightReductionFactor", 2.0)!!
val weightReductionFactor = meta.getDouble("weightReductionFactor", 2.0)
WeightedXYModel(meta, getAdapter(meta), spectrum) { dp -> weightReductionFactor }
}
@ -216,7 +216,7 @@ class NumassPlugin : BasicPlugin() {
manager.addModel("gun") { context, meta ->
val gsp = GunSpectrum()
val tritiumBackground = meta.getDouble("tritiumBkg", 0.0)!!
val tritiumBackground = meta.getDouble("tritiumBkg", 0.0)
val spectrum: NBkgSpectrum
if (tritiumBackground == 0.0) {
@ -234,10 +234,10 @@ class NumassPlugin : BasicPlugin() {
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 stitchBorder = an.getDouble("stitchBorder", eGun - 7)
val nSmooth = an.getInt("nSmooth", 15)
val w = an.getDouble("w", 0.8)!!
val w = an.getDouble("w", 0.8)
if (an.hasValue("transFile")) {
val transmissionFile = an.getString("transFile")

8
numass-main/src/main/kotlin/inr/numass/NumassUtils.kt
View File

@ -141,10 +141,10 @@ object NumassUtils {
set.points.forEach { point ->
val pointMeta = MetaBuilder("point")
.putValue("voltage", point.voltage)
.putValue("index", point.getMeta().getInt("external_meta.point_index", -1))
.putValue("run", point.getMeta().getString("external_meta.session", ""))
.putValue("group", point.getMeta().getString("external_meta.group", ""))
val pointName = "point_" + point.getMeta().getInt("external_meta.point_index", point.hashCode())!!
.putValue("index", point.meta.getInt("external_meta.point_index", -1))
.putValue("run", point.meta.getString("external_meta.session", ""))
.putValue("group", point.meta.getString("external_meta.group", ""))
val pointName = "point_" + point.meta.getInt("external_meta.point_index", point.hashCode())
builder.putData(pointName, point, pointMeta)
}
set.hvData.ifPresent { hv -> builder.putData("hv", hv, Meta.empty()) }

4
numass-main/src/main/kotlin/inr/numass/actions/TransformDataAction.kt
View File

@ -85,8 +85,8 @@ class TransformDataAction : OneToOneAction<Table, Table>() {
.mapToDouble { cor -> cor.relativeErr(point) }
.reduce { d1, d2 -> d1 * d1 + d2 * d2 }.orElse(0.0)
)
val originalCR = point.getDouble(COUNT_RATE_KEY)!!
val originalCRErr = point.getDouble(COUNT_RATE_ERROR_KEY)!!
val originalCR = point.getDouble(COUNT_RATE_KEY)
val originalCRErr = point.getDouble(COUNT_RATE_ERROR_KEY)
cr.add(originalCR * correctionFactor)
if (relativeCorrectionError == 0.0) {
crErr.add(originalCRErr * correctionFactor)

4
numass-main/src/main/kotlin/inr/numass/models/sterile/NumassResolution.kt
View File

@ -40,8 +40,8 @@ class NumassResolution(context: Context, meta: Meta) : AbstractParametricBiFunct
}
meta.hasValue("tailAlpha") -> {
//add polynomial function here
val alpha = meta.getDouble("tailAlpha")!!
val beta = meta.getDouble("tailBeta", 0.0)!!
val alpha = meta.getDouble("tailAlpha")
val beta = meta.getDouble("tailBeta", 0.0)
BivariateFunction { E: Double, U: Double -> 1 - (E - U) * (alpha + E / 1000.0 * beta) / 1000.0 }
}

2
numass-main/src/main/kotlin/inr/numass/models/sterile/NumassTransmission.kt
View File

@ -24,7 +24,7 @@ class NumassTransmission(context: Context, meta: Meta) : AbstractParametricBiFun
private val trapFunc: BivariateFunction
//private val lossCache = HashMap<Double, UnivariateFunction>()
private val adjustX: Boolean = meta.getBoolean("adjustX", false)!!
private val adjustX: Boolean = meta.getBoolean("adjustX", false)
init {
if (meta.hasValue("trapping")) {

2
numass-main/src/main/kotlin/inr/numass/tasks/NumassFitScanSummaryTask.kt
View File

@ -51,7 +51,7 @@ class NumassFitScanSummaryTask : AbstractTask<Table>() {
input.forEach { key, fitRes ->
val pars = fitRes.parameters
val u2Val = pars.getDouble("U2")!! / pars.getError("U2")
val u2Val = pars.getDouble("U2") / pars.getError("U2")
val limit: Double
if (Math.abs(u2Val) < 3) {

14
numass-main/src/main/kotlin/inr/numass/tasks/NumassTasks.kt
View File

@ -106,7 +106,7 @@ val analyzeTask = task("analyze") {
}
pipe<NumassSet, Table> { set ->
SmartAnalyzer().analyzeSet(set, meta).also { res ->
val outputMeta = meta.builder.putNode("data",set.meta)
val outputMeta = meta.builder.putNode("data", set.meta)
context.io.out("numass.analyze", name).use {
NumassUtils.write(it, outputMeta, res)
}
@ -209,8 +209,8 @@ val filterTask = task("filter") {
}
pipe<Table, Table> { data ->
if (meta.hasValue("from") || meta.hasValue("to")) {
val uLo = meta.getDouble("from", 0.0)!!
val uHi = meta.getDouble("to", java.lang.Double.POSITIVE_INFINITY)!!
val uLo = meta.getDouble("from", 0.0)
val uHi = meta.getDouble("to", java.lang.Double.POSITIVE_INFINITY)
this.log.report("Filtering finished")
TableTransform.filter(data, NumassPoint.HV_KEY, uLo, uHi)
} else if (meta.hasValue("condition")) {
@ -264,17 +264,15 @@ val plotFitTask = task("plotFit") {
val frame = PlotUtils.getPlotManager(context)
.getPlotFrame("numass.plotFit", name, meta.getMeta("frame", Meta.empty()))
val fit = XYFunctionPlot("fit").apply {
setFunction(function)
setDensity(100, false)
setSmoothing(true)
val fit = XYFunctionPlot("fit", function).apply {
density = 100
}
frame.add(fit)
// ensuring all data points are calculated explicitly
StreamSupport.stream<Values>(data.spliterator(), false)
.map { dp -> Adapters.getXValue(adapter,dp).doubleValue() }.sorted().forEach { fit.calculateIn(it) }
.map { dp -> Adapters.getXValue(adapter, dp).doubleValue() }.sorted().forEach { fit.calculateIn(it) }
frame.add(DataPlot.plot("data", adapter, data))