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0.1.3

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This commit is contained in:
Alexander Nozik 2022-06-07 12:16:02 +03:00
parent 5d3e6948db
commit b911790238
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7 changed files with 26 additions and 25 deletions
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2
build.gradle.kts
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@ -14,7 +14,7 @@ allprojects {
val dataforgeVersion by extra("0.5.2")
val tablesVersion: String by extra("0.1.5")
val kmathVersion by extra("0.3.0-dev-18")
val kmathVersion by extra("0.3.0")
val plotlyVersion: String by extra("0.5.0")
ksciencePublish{

8
numass-analysis/src/jvmMain/kotlin/ru/inr/mass/data/analysis/timeHistogram.kt
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@ -1,12 +1,14 @@
package ru.inr.mass.data.analysis
import kotlinx.coroutines.flow.Flow
import kotlinx.coroutines.flow.collect
import kotlinx.coroutines.flow.transform
import kotlinx.coroutines.runBlocking
import ru.inr.mass.data.api.NumassBlock
import ru.inr.mass.data.api.getTime
import space.kscience.kmath.histogram.UnivariateHistogram
import space.kscience.kmath.histogram.Histogram
import space.kscience.kmath.histogram.UniformHistogram1D
import space.kscience.kmath.histogram.uniform1D
import space.kscience.kmath.operations.DoubleField
import kotlin.math.max
import kotlin.time.DurationUnit
@ -23,7 +25,7 @@ public fun <T, R> Flow<T>.zipWithNext(block: (l: T, r: T) -> R): Flow<R> {
public fun NumassBlock.timeHistogram(
binSize: Double,
extractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
): UnivariateHistogram = UnivariateHistogram.uniform(binSize) {
): UniformHistogram1D<Double> = Histogram.uniform1D(DoubleField, binSize).produce {
runBlocking {
extractor.extract(this@timeHistogram).zipWithNext { l, r ->
if(l.owner == r.owner) {

12
numass-model/src/commonMain/kotlin/ru/inr/mass/models/NumassTransmission.kt
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@ -7,8 +7,8 @@ package ru.inr.mass.models
import space.kscience.kmath.expressions.Symbol
import space.kscience.kmath.expressions.symbol
import space.kscience.kmath.functions.Function1D
import space.kscience.kmath.functions.PiecewisePolynomial
import space.kscience.kmath.functions.UnivariateFunction
import space.kscience.kmath.functions.asFunction
import space.kscience.kmath.integration.*
import space.kscience.kmath.operations.DoubleField
@ -84,7 +84,7 @@ public class NumassTransmission(
public val trap: Symbol by symbol
public val thickness: Symbol by symbol
private val cache = HashMap<Int, UnivariateFunction<Double>>()
private val cache = HashMap<Int, Function1D<Double>>()
private const val ION_POTENTIAL = 15.4//eV
@ -130,7 +130,7 @@ public class NumassTransmission(
return exp(-x)
}
private fun getCachedSpectrum(order: Int): UnivariateFunction<Double> {
private fun getCachedSpectrum(order: Int): Function1D<Double> {
return when {
order <= 0 -> error("Non-positive loss cache order")
order == 1 -> singleScatterFunction
@ -147,7 +147,7 @@ public class NumassTransmission(
* @param order
* @return
*/
private fun getLoss(order: Int): UnivariateFunction<Double> = getCachedSpectrum(order)
private fun getLoss(order: Int): Function1D<Double> = getCachedSpectrum(order)
private fun getLossProbDerivs(x: Double): List<Double> {
val res = ArrayList<Double>()
@ -260,7 +260,7 @@ public class NumassTransmission(
* @return
*/
@Synchronized
private fun getNextLoss(margin: Double, loss: UnivariateFunction<Double>): PiecewisePolynomial<Double> {
private fun getNextLoss(margin: Double, loss: Function1D<Double>): PiecewisePolynomial<Double> {
val res = { x: Double ->
DoubleField.simpsonIntegrator.integrate(5.0..margin, IntegrandMaxCalls(200)) { y ->
loss(x - y) * singleScatterFunction(y)
@ -324,7 +324,7 @@ public class NumassTransmission(
private val w1 = 1.85
private val w2 = 12.5
public val singleScatterFunction: UnivariateFunction<Double> = { eps: Double ->
public val singleScatterFunction: Function1D<Double> = { eps: Double ->
when {
eps <= 0 -> 0.0
eps <= b -> {

4
numass-model/src/commonMain/kotlin/ru/inr/mass/models/functionCaching.kt
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@ -1,15 +1,15 @@
package ru.inr.mass.models
import space.kscience.kmath.functions.Function1D
import space.kscience.kmath.functions.PiecewisePolynomial
import space.kscience.kmath.functions.UnivariateFunction
import space.kscience.kmath.interpolation.SplineInterpolator
import space.kscience.kmath.interpolation.interpolatePolynomials
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.structures.DoubleBuffer
import kotlin.math.abs
public fun UnivariateFunction<Double>.cache(
public fun Function1D<Double>.cache(
range: ClosedFloatingPointRange<Double>,
numCachePoints: Int,
): PiecewisePolynomial<Double> {

7
numass-workspace/src/main/kotlin/ru/inr/mass/scripts/extract_data.kt
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@ -1,7 +1,5 @@
package ru.inr.mass.scripts
import kotlinx.datetime.DateTimeUnit
import kotlinx.datetime.plus
import ru.inr.mass.data.api.NumassBlock
import ru.inr.mass.data.api.channels
import ru.inr.mass.workspace.Numass
@ -29,8 +27,9 @@ fun main() {
channels.forEach { (key, block) ->
targetDir.resolve("channel-$key.csv").write {
block.listFrames().forEach { frame ->
val frameTime = pointTime.plus(frame.timeOffset, DateTimeUnit.NANOSECOND)
writeUtf8String("$frameTime,")
// val frameTime = pointTime.plus(frame.timeOffset, DateTimeUnit.NANOSECOND)
// writeUtf8String("$frameTime,")
writeUtf8String("${frame.timeOffset},")
val line = frame.signal.joinToString(",", postfix = "\n" )
writeUtf8String(line)
}

4
numass-workspace/src/main/kotlin/ru/inr/mass/scripts/gun_sim.kt
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@ -5,8 +5,8 @@ import space.kscience.kmath.functions.asFunction
import space.kscience.kmath.integration.integrate
import space.kscience.kmath.integration.splineIntegrator
import space.kscience.kmath.integration.value
import space.kscience.kmath.interpolation.SplineInterpolator
import space.kscience.kmath.interpolation.interpolatePolynomials
import space.kscience.kmath.interpolation.splineInterpolator
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.real.step
import space.kscience.plotly.Plotly
@ -28,7 +28,7 @@ fun main() {
Pair(e.toDouble(), p.toDouble())
}.toList()
val interpolated = SplineInterpolator.double
val interpolated = DoubleField.splineInterpolator
.interpolatePolynomials(backScatteringSpectrum)
.asFunction(DoubleField, 0.0)

12
numass-workspace/src/main/kotlin/ru/inr/mass/workspace/plots.kt
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@ -12,8 +12,8 @@ import ru.inr.mass.data.proto.HVData
import ru.inr.mass.data.proto.NumassDirectorySet
import space.kscience.dataforge.values.asValue
import space.kscience.dataforge.values.double
import space.kscience.kmath.histogram.UnivariateHistogram
import space.kscience.kmath.histogram.center
import space.kscience.kmath.domains.center
import space.kscience.kmath.histogram.Histogram1D
import space.kscience.kmath.misc.UnstableKMathAPI
import space.kscience.kmath.operations.asIterable
import space.kscience.kmath.structures.Buffer
@ -26,9 +26,9 @@ import kotlin.time.DurationUnit
* Plot a kmath histogram
*/
@OptIn(UnstableKMathAPI::class)
fun Plot.histogram(histogram: UnivariateHistogram, block: Scatter.() -> Unit = {}): Trace = scatter {
fun Plot.histogram(histogram: Histogram1D<Double, Double>, block: Scatter.() -> Unit = {}): Trace = scatter {
x.numbers = histogram.bins.map { it.domain.center }
y.numbers = histogram.bins.map { it.value }
y.numbers = histogram.bins.map { it.binValue }
line.shape = LineShape.hv
block()
}
@ -58,7 +58,7 @@ fun Plotly.plotNumassBlock(
block: NumassBlock,
amplitudeBinSize: UInt = 20U,
eventExtractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
splitChannels: Boolean = true
splitChannels: Boolean = true,
): PlotlyFragment = Plotly.fragment {
plot {
runBlocking {
@ -105,7 +105,7 @@ fun Plotly.plotNumassSet(
h2 { +"Time spectra" }
plot {
spectra.forEach { (point,spectrum) ->
spectra.forEach { (point, spectrum) ->
val countRate = runBlocking {
spectrum.sum().toDouble() / point.getLength().toDouble(DurationUnit.SECONDS)
}