Update spectrum computation
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014628f2fd
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@ -19,12 +19,14 @@ import space.kscience.kmath.data.ColumnarData
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import space.kscience.kmath.misc.Symbol
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import space.kscience.kmath.misc.Symbol
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.misc.UnstableKMathAPI
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import space.kscience.kmath.misc.symbol
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import space.kscience.kmath.misc.symbol
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import space.kscience.kmath.real.div
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import space.kscience.kmath.real.sum
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import space.kscience.kmath.structures.Buffer
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import space.kscience.kmath.structures.Buffer
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import space.kscience.kmath.structures.DoubleBuffer
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import space.kscience.kmath.structures.DoubleBuffer
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@OptIn(UnstableKMathAPI::class)
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@OptIn(UnstableKMathAPI::class)
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public class FSS(public val es: DoubleBuffer, public val ps: DoubleBuffer) : ColumnarData<Double> {
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public class FSS(public val es: Buffer<Double>, public val ps: Buffer<Double>) : ColumnarData<Double> {
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override val size: Int get() = ps.size
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override val size: Int get() = ps.size
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@ -47,7 +49,7 @@ public class FSS(public val es: DoubleBuffer, public val ps: DoubleBuffer) : Col
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}.toList()
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}.toList()
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val es = DoubleBuffer(data.size) { data[it].first }
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val es = DoubleBuffer(data.size) { data[it].first }
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val ps = DoubleBuffer(data.size) { data[it].second }
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val ps = DoubleBuffer(data.size) { data[it].second }
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FSS(es, ps)
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FSS(es, ps / ps.sum())
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}
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}
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}
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}
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}
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}
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@ -42,5 +42,9 @@ public class NBkgSpectrum(public val source: Spectrum) : DifferentiableSpectrum
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public val norm: Symbol by symbol
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public val norm: Symbol by symbol
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public val bkg: Symbol by symbol
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public val bkg: Symbol by symbol
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}
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}
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}
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}
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/**
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* Apply transformation adding norming-factor and the background
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*/
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public fun Spectrum.withNBkg(): NBkgSpectrum = NBkgSpectrum(this)
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@ -67,10 +67,10 @@ public class NumassTransmission(
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else -> null
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else -> null
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}
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}
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override fun invoke(x: Double, y: Double, arguments: Map<Symbol, Double>): Double {
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override fun invoke(ei: Double, ef: Double, arguments: Map<Symbol, Double>): Double {
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// loss part
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// loss part
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val thickness = arguments[thickness] ?: 0.0
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val thickness = arguments[thickness] ?: 0.0
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val loss = getTotalLossValue(thickness, x, y)
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val loss = getTotalLossValue(thickness, ei, ef)
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// double loss;
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// double loss;
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//
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//
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// if(eIn-eOut >= 300){
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// if(eIn-eOut >= 300){
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@ -84,7 +84,7 @@ public class NumassTransmission(
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// }
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// }
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//trapping part
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//trapping part
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val trap = arguments[trap] ?: 1.0 * trapFunc(x, y, arguments)
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val trap = (arguments[trap] ?: 1.0) * trapFunc(ei, ef, arguments)
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return loss + trap
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return loss + trap
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}
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}
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@ -155,13 +155,11 @@ public class NumassTransmission(
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* @param order
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* @param order
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* @return
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* @return
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*/
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*/
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private fun getLoss(order: Int): UnivariateFunction<Double> {
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private fun getLoss(order: Int): UnivariateFunction<Double> = getCachedSpectrum(order)
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return getCachedSpectrum(order)
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}
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private fun getLossProbDerivs(x: Double): List<Double> {
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private fun getLossProbDerivs(x: Double): List<Double> {
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val res = ArrayList<Double>()
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val res = ArrayList<Double>()
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val probs = getLossProbabilities(x)
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val probs = lossProbabilities(x)
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var delta = exp(-x)
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var delta = exp(-x)
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res.add((delta - probs[0]) / x)
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res.add((delta - probs[0]) / x)
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@ -209,7 +207,7 @@ public class NumassTransmission(
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return res
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return res
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}
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}
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private fun getLossProbabilities(x: Double): List<Double> =
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public fun lossProbabilities(x: Double): List<Double> =
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lossProbCache.getOrPut(x) { calculateLossProbabilities(x) }
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lossProbCache.getOrPut(x) { calculateLossProbabilities(x) }
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private fun getLossProbability(order: Int, X: Double): Double {
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private fun getLossProbability(order: Int, X: Double): Double {
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@ -220,7 +218,7 @@ public class NumassTransmission(
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1.0
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1.0
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}
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}
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}
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}
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val probs = getLossProbabilities(X)
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val probs = lossProbabilities(X)
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return if (order >= probs.size) {
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return if (order >= probs.size) {
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0.0
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0.0
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} else {
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} else {
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@ -228,11 +226,11 @@ public class NumassTransmission(
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}
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}
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}
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}
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private fun getLossValue(order: Int, Ei: Double, Ef: Double): Double {
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private fun getLossValue(order: Int, ei: Double, ef: Double): Double {
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return when {
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return when {
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Ei - Ef < 5.0 -> 0.0
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ei - ef < 5.0 -> 0.0
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Ei - Ef >= getMargin(order) -> 0.0
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ei - ef >= getMargin(order) -> 0.0
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else -> getLoss(order).invoke(Ei - Ef)
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else -> getLoss(order).invoke(ei - ef)
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}
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}
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}
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}
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@ -303,17 +301,17 @@ public class NumassTransmission(
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/**
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/**
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* Значение полной функции потерь с учетом всех неисчезающих порядков
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* Значение полной функции потерь с учетом всех неисчезающих порядков
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*
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*
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* @param x
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* @param thickness
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* @param Ei
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* @param Ei
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* @param Ef
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* @param Ef
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* @return
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* @return
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*/
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*/
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private fun getTotalLossValue(x: Double, Ei: Double, Ef: Double): Double {
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private fun getTotalLossValue(thickness: Double, Ei: Double, Ef: Double): Double {
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return if (x == 0.0) {
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return if (thickness == 0.0) {
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0.0
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0.0
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} else {
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} else {
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val probs = getLossProbabilities(x)
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val probs = lossProbabilities(thickness)
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(1 until probs.size).sumByDouble { i ->
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(1 until probs.size).sumOf { i ->
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probs[i] * getLossValue(i, Ei, Ef)
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probs[i] * getLossValue(i, Ei, Ef)
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}
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}
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}
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}
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@ -468,9 +466,8 @@ public class NumassTransmission(
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//
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//
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// }
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// }
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internal val defaultTrapping: Kernel = Kernel { e, u, arguments ->
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internal val defaultTrapping: Kernel = Kernel { ei, ef, _ ->
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val d = e - u
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1.2e-4 - 4.5e-9 * ei
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0.99797 - 3.05346E-7 * d - 5.45738E-10 * d.pow(2.0) - 6.36105E-14 * d.pow(3.0)
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}
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}
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}
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}
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@ -33,7 +33,6 @@ public class SterileNeutrinoSpectrum(
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public val fss: FSS? = FSS.default,
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public val fss: FSS? = FSS.default,
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) : DifferentiableSpectrum {
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) : DifferentiableSpectrum {
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/**
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/**
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* auxiliary function for trans-res convolution
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* auxiliary function for trans-res convolution
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*/
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*/
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@ -4,30 +4,94 @@ import inr.numass.models.sterile.NumassBeta.e0
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import inr.numass.models.sterile.NumassBeta.mnu2
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import inr.numass.models.sterile.NumassBeta.mnu2
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import inr.numass.models.sterile.NumassBeta.msterile2
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import inr.numass.models.sterile.NumassBeta.msterile2
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import inr.numass.models.sterile.NumassBeta.u2
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import inr.numass.models.sterile.NumassBeta.u2
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import inr.numass.models.sterile.NumassResolution
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import inr.numass.models.sterile.NumassTransmission
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import inr.numass.models.sterile.NumassTransmission.Companion.thickness
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import inr.numass.models.sterile.NumassTransmission.Companion.thickness
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import inr.numass.models.sterile.NumassTransmission.Companion.trap
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import inr.numass.models.sterile.SterileNeutrinoSpectrum
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import inr.numass.models.sterile.SterileNeutrinoSpectrum
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import kotlinx.html.code
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import ru.inr.mass.models.NBkgSpectrum.Companion.bkg
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import ru.inr.mass.models.NBkgSpectrum.Companion.norm
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import ru.inr.mass.models.withNBkg
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import ru.inr.mass.workspace.buffer
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import ru.inr.mass.workspace.buffer
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import space.kscience.kmath.misc.Symbol
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import space.kscience.kmath.misc.Symbol
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import space.kscience.kmath.real.step
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import space.kscience.kmath.real.step
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import space.kscience.plotly.Plotly
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import space.kscience.plotly.*
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import space.kscience.plotly.makeFile
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import space.kscience.plotly.models.ScatterMode
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import space.kscience.plotly.models.ScatterMode
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import space.kscience.plotly.scatter
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import space.kscience.plotly.models.appendXY
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import kotlin.math.pow
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fun main() {
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fun main() {
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val spectrum = SterileNeutrinoSpectrum()
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val spectrum = SterileNeutrinoSpectrum().withNBkg()
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val args: Map<Symbol, Double> = mapOf(
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val args: Map<Symbol, Double> = mapOf(
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norm to 8e5,
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bkg to 2.0,
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mnu2 to 0.0,
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mnu2 to 0.0,
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e0 to 18575.0,
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e0 to 18575.0,
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msterile2 to 1e6,
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msterile2 to 1000.0.pow(2),
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u2 to 1e-2,
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u2 to 1e-2,
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thickness to 0.2
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thickness to 0.1,
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trap to 1.0
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)
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)
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Plotly.plot {
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Plotly.page {
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plot {
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scatter {
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scatter {
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name = "Computed spectrum"
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mode = ScatterMode.lines
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mode = ScatterMode.lines
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x.buffer = 14000.0..18600.0 step 10.0
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x.buffer = 14000.0..18600.0 step 10.0
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y.numbers = x.numbers.map { spectrum(it.toDouble(), args) }
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y.numbers = x.doubles.map { spectrum(it, args) }
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}
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scatter {
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name = "Old spectrum"
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mode = ScatterMode.markers
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javaClass.getResource("/old-spectrum.dat").readText().lines().map {
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val (u, w) = it.split("\t")
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appendXY(u.toDouble(), w.toDouble())
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}
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}
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layout {
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title = "Sterile neutrino spectrum"
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}
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}
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plot {
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val resolution = NumassResolution()
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scatter {
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name = "resolution"
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x.buffer = 14000.0..14015.0 step 0.1
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y.numbers = x.doubles.map { resolution(it, 14005.0, args) }
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}
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layout {
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title = "Resolution, U = 14005.0"
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}
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}
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plot {
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val transmission = NumassTransmission()
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scatter {
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name = "transmission"
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x.buffer = 14000.0..14100.0 step 0.2
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y.numbers = x.doubles.map { transmission(it, 14005.0, args) }
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}
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layout {
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title = "Resolution, U = 14005.0"
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}
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}
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code {
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+"""
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norm to 8e5,
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bkg to 2.0,
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mnu2 to 0.0,
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e0 to 18575.0,
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msterile2 to 1000.0.pow(2),
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u2 to 1e-2,
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thickness to 0.1,
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trap to 1.0
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""".trimIndent()
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}
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}
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}.makeFile()
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}.makeFile()
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println(spectrum(14000.0, args))
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}
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}
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461
numass-workspace/src/main/resources/old-spectrum.dat
Normal file
461
numass-workspace/src/main/resources/old-spectrum.dat
Normal file
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14000.0 21144.06826503362
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14730.0 12584.94741175745
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14740.0 12487.397543672685
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18030.0 35.13403855083936
|
||||||
|
18040.0 33.28241970446307
|
||||||
|
18050.0 31.501328016008742
|
||||||
|
18060.0 29.789232968602683
|
||||||
|
18070.0 28.14480287113967
|
||||||
|
18080.0 26.566892964175935
|
||||||
|
18090.0 25.053956614987822
|
||||||
|
18100.0 23.604395867135885
|
||||||
|
18110.0 22.21670656050556
|
||||||
|
18120.0 20.889529413788292
|
||||||
|
18130.0 19.62201632664601
|
||||||
|
18140.0 18.412882964633525
|
||||||
|
18150.0 17.260422663377845
|
||||||
|
18160.0 16.16336469143388
|
||||||
|
18170.0 15.120474319163025
|
||||||
|
18180.0 14.130233108077414
|
||||||
|
18190.0 13.190878829930073
|
||||||
|
18200.0 12.301470618491864
|
||||||
|
18210.0 11.460817915538579
|
||||||
|
18220.0 10.667432266646426
|
||||||
|
18230.0 9.91985795035206
|
||||||
|
18240.0 9.21683299142454
|
||||||
|
18250.0 8.556612650396238
|
||||||
|
18260.0 7.938160755458398
|
||||||
|
18270.0 7.3601775328248
|
||||||
|
18280.0 6.8213004386287
|
||||||
|
18290.0 6.320297242431397
|
||||||
|
18300.0 5.855529641786286
|
||||||
|
18310.0 5.425186892341504
|
||||||
|
18320.0 5.028036943022659
|
||||||
|
18330.0 4.6631960393091365
|
||||||
|
18340.0 4.32930799884052
|
||||||
|
18350.0 4.0249367725373055
|
||||||
|
18360.0 3.7486423441053933
|
||||||
|
18370.0 3.499083287193633
|
||||||
|
18380.0 3.2748421288122014
|
||||||
|
18390.0 3.0745715651847014
|
||||||
|
18400.0 2.8964113339074795
|
||||||
|
18410.0 2.7395339740716547
|
||||||
|
18420.0 2.60254765486773
|
||||||
|
18430.0 2.4840384601692094
|
||||||
|
18440.0 2.38261999444518
|
||||||
|
18450.0 2.2966842827978713
|
||||||
|
18460.0 2.225103820486433
|
||||||
|
18470.0 2.166504319747381
|
||||||
|
18480.0 2.119417872453323
|
||||||
|
18490.0 2.082513315540327
|
||||||
|
18500.0 2.0544548933160414
|
||||||
|
18510.0 2.033862847336914
|
||||||
|
18520.0 2.019465429438452
|
||||||
|
18530.0 2.010044135140901
|
||||||
|
18540.0 2.004413085375449
|
||||||
|
18550.0 2.0014591003363216
|
||||||
|
18560.0 2.0002524725947946
|
||||||
|
18570.0 2.0000024904161795
|
||||||
|
18580.0 2.0
|
||||||
|
18590.0 2.0
|
||||||
|
18600.0 2.0
|
||||||
Loading…
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Reference in New Issue
Block a user