refactor numass resolution
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parent
57e3439220
commit
d41ff5fefc
@ -136,9 +136,7 @@ class ListTable @JvmOverloads constructor(override val format: TableFormat, poin
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* @throws NamingException
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*/
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@Throws(NamingException::class)
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fun row(vararg values: Any): Builder {
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return row(ValueMap.of(format.namesAsArray(), *values))
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}
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fun row(vararg values: Any): Builder = row(ValueMap.of(format.namesAsArray(), *values))
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fun row(values: ValueProvider): Builder {
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val names = format.namesAsArray()
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@ -146,17 +144,12 @@ class ListTable @JvmOverloads constructor(override val format: TableFormat, poin
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return row(ValueMap(map))
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}
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fun row(vararg values: NamedValue): Builder {
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return row(ValueMap.of(*values))
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}
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fun row(vararg values: NamedValue): Builder = row(ValueMap.of(*values))
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fun row(vararg values: Pair<String, Any>): Builder {
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return row(ValueMap.of(values.map { NamedValue.of(it.first, it.second) }))
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}
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fun row(vararg values: Pair<String, Any>): Builder =
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row(ValueMap.of(values.map { NamedValue.of(it.first, it.second) }))
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fun row(map: Map<String, Any>): Builder {
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return row(ValueMap.ofMap(map))
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}
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fun row(map: Map<String, Any>): Builder = row(ValueMap.ofMap(map))
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fun rows(points: Iterable<Values>): Builder {
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for (point in points) {
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@ -170,16 +163,12 @@ class ListTable @JvmOverloads constructor(override val format: TableFormat, poin
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return this
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}
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fun build(): Table {
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return ListTable(format, points)
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}
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fun build(): ListTable = ListTable(format, points)
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/**
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* Build table without points name check
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*/
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fun buildUnsafe(): Table {
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return ListTable(format, points, true)
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}
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fun buildUnsafe(): Table = ListTable(format, points, true)
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}
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companion object {
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@ -52,8 +52,6 @@ interface Table : NavigableValuesSource, MetaMorph {
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*/
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fun getColumn(name: String): Column
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@JvmDefault
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override fun toMeta(): Meta {
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val res = MetaBuilder("table")
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res.putNode("format", format.toMeta())
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File diff suppressed because it is too large
Load Diff
@ -1,77 +0,0 @@
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package inr.numass.scripts
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import hep.dataforge.context.Context
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import hep.dataforge.context.Global
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import hep.dataforge.grind.GrindShell
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import hep.dataforge.grind.helpers.PlotHelper
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import hep.dataforge.stat.fit.ParamSet
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import inr.numass.NumassPlugin
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import inr.numass.models.sterile.NumassResolution
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import inr.numass.models.sterile.SterileNeutrinoSpectrum
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import static hep.dataforge.grind.Grind.buildMeta
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Context ctx = Global.instance()
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ctx.getPlugins().load(FXPlotManager)
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ctx.getPlugins().load(NumassPlugin.class)
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GrindShell shell = new GrindShell(ctx)
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shell.eval {
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PlotHelper plot = plots
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ParamSet params = new ParamSet(buildMeta {
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N(value: 2.7e+06, err: 30, lower: 0)
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bkg(value: 5.0, err: 0.1)
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E0(value: 18575.0, err: 0.1)
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mnu2(value: 0, err: 0.01)
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msterile2(value: 1000**2, err: 1)
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U2(value: 0.0, err: 1e-3)
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X(value: 0.0, err: 0.01, lower: 0)
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trap(value: 1.0, err: 0.05)
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})
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def meta1 = buildMeta {
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resolution(width: 8.3e-5, tail: "(0.99797 - 3.05346E-7*D - 5.45738E-10 * D**2 - 6.36105E-14 * D**3)")
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}
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def meta2 = buildMeta {
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resolution(width: 8.3e-5, tail: "(0.99797 - 3.05346E-7*D - 5.45738E-10 * D**2 - 6.36105E-14 * D**3)*(1-5e-3*sqrt(E/1000))")
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}
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def resolution1 = new NumassResolution(
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ctx,
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meta1.getMeta("resolution")
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)
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def resolution2 = new NumassResolution(
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ctx,
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meta2.getMeta("resolution")
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)
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plot.plot(frame: "resolution", from: 13500, to: 19000) { x ->
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resolution1.value(x, 14000, params)
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}
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plot.plot(frame: "resolution", from: 13500, to: 19000) { x ->
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resolution2.value(x, 14000, params)
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}
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def spectrum1 = new SterileNeutrinoSpectrum(ctx, meta1)
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def spectrum2 = new SterileNeutrinoSpectrum(ctx, meta2)
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def x = []
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def y1 = []
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def y2 = []
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(13500..19000).step(100).each {
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x << it
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y1 << spectrum1.value(it, params)
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y2 << spectrum2.value(it, params)
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}
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plot.plot(x, y1, "spectrum1", "spectrum")
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plot.plot(x, y2, "spectrum2", "spectrum")
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}
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@ -26,7 +26,9 @@ import hep.dataforge.values.Values
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*
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* @author Darksnake
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*/
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open class NBkgSpectrum(private val source: ParametricFunction) : AbstractParametricFunction(*combineNamesWithEquals(source.namesAsArray(), *list)) {
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open class NBkgSpectrum(
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private val source: ParametricFunction,
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) : AbstractParametricFunction(*combineNamesWithEquals(source.namesAsArray(), *list)) {
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var counter = MultiCounter(this.javaClass.name)
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@ -13,40 +13,16 @@ import hep.dataforge.values.Values
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import inr.numass.models.ResolutionFunction
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import inr.numass.utils.ExpressionUtils
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import org.apache.commons.math3.analysis.BivariateFunction
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import java.lang.Math.sqrt
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import java.util.*
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import kotlin.math.sqrt
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/**
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* @author [Alexander Nozik](mailto:altavir@gmail.com)
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*/
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class NumassResolution(context: Context, meta: Meta) : AbstractParametricBiFunction(list) {
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private val resA: Double = meta.getDouble("A", 8.3e-5)
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private val resB = meta.getDouble("B", 0.0)
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private val tailFunction: BivariateFunction = when {
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meta.hasValue("tail") -> {
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val tailFunctionStr = meta.getString("tail")
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if (tailFunctionStr.startsWith("function::")) {
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FunctionLibrary.buildFrom(context).buildBivariateFunction(tailFunctionStr.substring(10))
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} else {
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BivariateFunction { E, U ->
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val binding = HashMap<String, Any>()
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binding["E"] = E
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binding["U"] = U
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binding["D"] = E - U
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ExpressionUtils.function(tailFunctionStr, binding)
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}
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}
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}
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meta.hasValue("tailAlpha") -> {
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//add polynomial function here
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val alpha = meta.getDouble("tailAlpha")
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val beta = meta.getDouble("tailBeta", 0.0)
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BivariateFunction { E: Double, U: Double -> 1 - (E - U) * (alpha + E / 1000.0 * beta) / 1000.0 }
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}
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else -> ResolutionFunction.getConstantTail()
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}
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class NumassResolution(
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val resA: Double = 8.3e-5,
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val resB: Double = 0.0,
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val tailFunction: BivariateFunction = ResolutionFunction.getConstantTail(),
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) : AbstractParametricBiFunction(list) {
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override fun derivValue(parName: String, x: Double, y: Double, set: Values): Double {
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return 0.0
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@ -82,6 +58,35 @@ class NumassResolution(context: Context, meta: Meta) : AbstractParametricBiFunct
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companion object {
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private val list = arrayOf<String>() //leaving
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internal fun fromMeta(context: Context, meta: Meta) = NumassResolution(
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meta.getDouble("A", 8.3e-5),
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meta.getDouble("B", 0.0),
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when {
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meta.hasValue("tail") -> {
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val tailFunctionStr = meta.getString("tail")
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if (tailFunctionStr.startsWith("function::")) {
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FunctionLibrary.buildFrom(context).buildBivariateFunction(tailFunctionStr.substring(10))
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} else {
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BivariateFunction { E, U ->
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val binding = HashMap<String, Any>()
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binding["E"] = E
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binding["U"] = U
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binding["D"] = E - U
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ExpressionUtils.function(tailFunctionStr, binding)
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}
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}
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}
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meta.hasValue("tailAlpha") -> {
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//add polynomial function here
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val alpha = meta.getDouble("tailAlpha")
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val beta = meta.getDouble("tailBeta", 0.0)
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BivariateFunction { E: Double, U: Double -> 1 - (E - U) * (alpha + E / 1000.0 * beta) / 1000.0 }
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}
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else -> ResolutionFunction.getConstantTail()
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}
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)
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}
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}
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@ -48,7 +48,7 @@ class SterileNeutrinoSpectrum @JvmOverloads constructor(
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configuration: Meta,
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val source: ParametricBiFunction = NumassBeta(),
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val transmission: ParametricBiFunction = NumassTransmission(context, configuration.getMetaOrEmpty("transmission")),
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val resolution: ParametricBiFunction = NumassResolution(context, configuration.getMeta("resolution", Meta.empty()))
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val resolution: ParametricBiFunction = NumassResolution.fromMeta(context, configuration.getMeta("resolution", Meta.empty()))
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) : AbstractParametricFunction(*list) {
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@ -0,0 +1,155 @@
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/*
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* Copyright 2018 Alexander Nozik.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package inr.numass.scripts.models
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import hep.dataforge.buildContext
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import hep.dataforge.configure
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import hep.dataforge.fx.FXPlugin
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import hep.dataforge.fx.output.FXOutputManager
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import hep.dataforge.meta.Meta
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import hep.dataforge.plots.Plot
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import hep.dataforge.plots.data.DataPlot
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import hep.dataforge.plots.jfreechart.JFreeChartPlugin
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import hep.dataforge.plots.output.plotFrame
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import hep.dataforge.plots.plotFunction
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import hep.dataforge.stat.fit.FitManager
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import hep.dataforge.stat.fit.FitStage
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import hep.dataforge.stat.fit.FitState
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import hep.dataforge.stat.fit.ParamSet
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import hep.dataforge.stat.models.XYModel
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import hep.dataforge.step
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import hep.dataforge.tables.Adapters.X_AXIS
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import hep.dataforge.tables.Table
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import hep.dataforge.values.ValueMap
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import inr.numass.NumassPlugin
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import inr.numass.data.SpectrumAdapter
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import inr.numass.data.SpectrumGenerator
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import inr.numass.models.NBkgSpectrum
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import inr.numass.models.sterile.NumassResolution
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import inr.numass.models.sterile.SterileNeutrinoSpectrum
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import org.apache.commons.math3.analysis.interpolation.SplineInterpolator
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import java.io.PrintWriter
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private fun getCustomResolution(): NumassResolution {
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val correctionDataString = """
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10 0.376892
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12 0.1615868
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13 0.1009648
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14 0.0677539
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15 0.0487972
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16 0.037275
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17 0.02958922
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18 0.02511696
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19 0.02247986
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""".trimIndent()
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val correctionData = correctionDataString.lines().map { line ->
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val (u, cor) = line.split("\t")
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u.toDouble() * 1000 to cor.toDouble()
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}
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val correctionInterpolation = SplineInterpolator().interpolate(
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correctionData.map { it.first }.toDoubleArray(),
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correctionData.map { it.second }.toDoubleArray()
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)
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return NumassResolution(tailFunction = { e, _ -> 1.0 - correctionInterpolation.value(e) })
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}
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private fun XYModel.plot(name: String, params: ParamSet): Plot {
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val x = (14000.0..19000.0).step(100.0).toList()
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val y = x.map { spectrum.value(it, params) }
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return DataPlot.plot(name, x.toDoubleArray(), y.toDoubleArray())
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}
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fun main() {
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val context = buildContext(
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"NUMASS",
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NumassPlugin::class.java,
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FXPlugin::class.java,
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JFreeChartPlugin::class.java
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) {
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output = FXOutputManager()
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}
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val params = ParamSet().apply {
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setPar("N", 8e5, 6.0, 0.0, Double.POSITIVE_INFINITY)
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setPar("bkg", 2.0, 0.03)
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setPar("E0", 18575.0, 1.0)
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setPar("mnu2", 0.0, 1.0)
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setParValue("msterile2", (1000 * 1000).toDouble())
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setPar("U2", 0.0, 1e-3)
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setPar("X", 0.0, 0.01)
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setPar("trap", 1.0, 0.01)
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}
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val customResolution = getCustomResolution()
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context.plotFrame("fit", stage = "resolution") {
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plots.configure {
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"showLine" to true
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"showSymbol" to false
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"showErrors" to false
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"thickness" to 2.0
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}
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plots.setType<DataPlot>()
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plotFunction("custom", 14000.0, 18000.0, 1000) { x ->
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customResolution.value(x, 14100.0, params)
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}
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val basicResolution = NumassResolution()
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plotFunction("basic", 14000.0, 18000.0, 1000) { x ->
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basicResolution.value(x, 14100.0, params)
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}
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}
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val dataSpectrum = NBkgSpectrum(SterileNeutrinoSpectrum(context, Meta.empty(), resolution = customResolution))
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val t = 30 * 50 // time in seconds per point
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val adapter = SpectrumAdapter(Meta.empty())
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val fm = context.getOrLoad(FitManager::class.java)
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val x = (14000.0..18500.0).step(100.0).toList()
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val dataModel = XYModel(Meta.empty(), adapter, dataSpectrum)
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val generator = SpectrumGenerator(dataModel, params, 12316)
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val configuration = x.map { ValueMap.ofPairs(X_AXIS to it, "time" to t) }
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val data: Table = generator.generateData(configuration)
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val modelSpectrum = NBkgSpectrum(SterileNeutrinoSpectrum(context, Meta.empty(), resolution = NumassResolution()))
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val fitModel = XYModel(Meta.empty(), adapter, modelSpectrum)
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context.plotFrame("fit", stage = "plots") {
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plots.configure {
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"showLine" to true
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"showSymbol" to false
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"showErrors" to false
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"thickness" to 4.0
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}
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plots.setType<DataPlot>()
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+dataModel.plot("Data", params)
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+fitModel.plot("Fit-start", params)
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}
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val state = FitState(data, fitModel, params)
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val res = fm.runStage(state, "QOW", FitStage.TASK_RUN, "N", "E0", "bkg", "trap")
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res.printState(PrintWriter(System.out))
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val resU2 = fm.runStage(res.optState().get(), "QOW", FitStage.TASK_RUN, "N", "E0", "bkg", "trap", "U2")
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resU2.printState(PrintWriter(System.out))
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}
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