Fix jupyter and analyzers
Fix jupyter and analyzers
This commit is contained in:
parent
d124f376d0
commit
d1ddf89c6e
@ -12,14 +12,18 @@ val tablesVersion: String by rootProject.extra
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kotlin.sourceSets {
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commonMain {
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dependencies {
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api(project(":numass-data-model"))
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api(projects.numass.numassDataModel)
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api("space.kscience:dataforge-io:$dataforgeVersion")
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api("space.kscience:tables-kt:$tablesVersion")
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api("space.kscience:kmath-histograms:$kmathVersion")
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api("space.kscience:kmath-complex:$kmathVersion")
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api("space.kscience:kmath-stat:$kmathVersion")
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api("space.kscience:kmath-histograms:$kmathVersion")
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}
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}
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}
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kscience{
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useAtomic()
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}
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@ -1,112 +0,0 @@
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/*
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* Copyright 2017 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 ru.inr.mass.data.analysis
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import kotlinx.coroutines.flow.*
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import ru.inr.mass.data.api.NumassBlock
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import ru.inr.mass.data.api.NumassEvent
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import ru.inr.mass.data.api.NumassSet
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import ru.inr.mass.data.api.SignalProcessor
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import space.kscience.dataforge.meta.Meta
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import space.kscience.dataforge.meta.get
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import space.kscience.dataforge.meta.int
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import space.kscience.dataforge.values.Value
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import space.kscience.tables.RowTable
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import space.kscience.tables.Table
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/**
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* Created by darksnake on 11.07.2017.
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*/
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public abstract class AbstractAnalyzer(
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private val processor: SignalProcessor? = null,
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) : NumassAnalyzer {
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/**
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* Return unsorted stream of events including events from frames.
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* In theory, events after processing could be unsorted due to mixture of frames and events.
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* In practice usually block have either frame or events, but not both.
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*
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* @param block
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* @return
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*/
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override fun getEvents(block: NumassBlock, meta: Meta): Flow<NumassEvent> {
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val range = meta.getRange()
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return getAllEvents(block).filter { event ->
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event.amplitude.toInt() in range
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}
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}
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protected fun Meta.getRange(): IntRange {
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val loChannel = get("window.lo")?.int ?: 0
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val upChannel = get("window.up")?.int ?: Int.MAX_VALUE
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return loChannel until upChannel
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}
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protected fun getAllEvents(block: NumassBlock): Flow<NumassEvent> {
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return when {
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block.framesCount == 0L -> block.events
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processor == null -> throw IllegalArgumentException("Signal processor needed to analyze frames")
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else -> flow {
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emitAll(block.events)
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emitAll(block.frames.flatMapConcat { processor.analyze(it) })
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}
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}
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}
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// /**
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// * Get table format for summary table
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// *
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// * @param config
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// * @return
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// */
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// protected open fun getTableFormat(config: Meta): ValueTableHeader {
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// return TableFormatBuilder()
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// .addNumber(HV_KEY, X_VALUE_KEY)
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// .addNumber(NumassAnalyzer.LENGTH_KEY)
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// .addNumber(NumassAnalyzer.COUNT_KEY)
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// .addNumber(NumassAnalyzer.COUNT_RATE_KEY, Y_VALUE_KEY)
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// .addNumber(NumassAnalyzer.COUNT_RATE_ERROR_KEY, Y_ERROR_KEY)
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// .addColumn(NumassAnalyzer.WINDOW_KEY)
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// .addTime()
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// .build()
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// }
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override suspend fun analyzeSet(set: NumassSet, config: Meta): Table<Value> = RowTable(
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NumassAnalyzer.length,
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NumassAnalyzer.count,
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NumassAnalyzer.cr,
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NumassAnalyzer.crError,
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// NumassAnalyzer.window,
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// NumassAnalyzer.timestamp
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) {
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set.points.forEach { point ->
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analyzeParent(point, config)
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}
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}
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public companion object {
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// public val NAME_LIST: List<String> = listOf(
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// NumassAnalyzer.LENGTH_KEY,
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// NumassAnalyzer.COUNT_KEY,
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// NumassAnalyzer.COUNT_RATE_KEY,
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// NumassAnalyzer.COUNT_RATE_ERROR_KEY,
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// NumassAnalyzer.WINDOW_KEY,
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// NumassAnalyzer.TIME_KEY
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// )
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}
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}
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@ -1,35 +0,0 @@
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/*
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* Copyright 2017 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 ru.inr.mass.data.analysis
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import ru.inr.mass.data.api.NumassBlock
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import ru.inr.mass.data.api.SignalProcessor
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import space.kscience.dataforge.meta.Meta
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import space.kscience.dataforge.meta.descriptors.MetaDescriptor
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/**
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* Block analyzer that can perform debunching
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* Created by darksnake on 11.07.2017.
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*/
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public class DebunchAnalyzer(processor: SignalProcessor? = null) : AbstractAnalyzer(processor) {
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override suspend fun analyze(block: NumassBlock, config: Meta): NumassAnalyzerResult {
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TODO()
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}
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override val descriptor: MetaDescriptor? = null
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}
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@ -0,0 +1,70 @@
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package ru.inr.mass.data.analysis
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import kotlinx.coroutines.coroutineScope
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import kotlinx.coroutines.flow.collect
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import kotlinx.coroutines.launch
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import ru.inr.mass.data.api.NumassBlock
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import space.kscience.kmath.histogram.LongCounter
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import kotlin.math.min
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public class NumassAmplitudeSpectrum(public val amplitudes: Map<UShort, ULong>) {
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public val minChannel: UShort by lazy { amplitudes.keys.minOf { it } }
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public val maxChannel: UShort by lazy { amplitudes.keys.maxOf { it } }
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public fun binned(binSize: UInt, range: UIntRange = minChannel..maxChannel): Map<UIntRange, Double> {
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val keys = sequence {
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var left = range.first
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do {
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val right = min(left + binSize, range.last)
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yield(left..right)
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left = right
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} while (right < range.last)
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}
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return keys.associateWith { bin -> amplitudes.filter { it.key in bin }.values.sum().toDouble() }
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}
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}
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/**
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* Build an amplitude spectrum with bin of 1.0 counted from 0.0. Some bins could be missing
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*/
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public suspend fun NumassBlock.amplitudeSpectrum(
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extractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
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): NumassAmplitudeSpectrum {
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val map = HashMap<UShort, LongCounter>()
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extractor.extract(this).collect { event ->
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map.getOrPut(event.amplitude) { LongCounter() }.add(1L)
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}
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return NumassAmplitudeSpectrum(map.mapValues { it.value.value.toULong() })
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}
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/**
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* Collect events from block in parallel
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*/
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public suspend fun Collection<NumassBlock>.amplitudeSpectrum(
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extractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
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): NumassAmplitudeSpectrum {
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val hist = List(UShort.MAX_VALUE.toInt()) {
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LongCounter()
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}
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coroutineScope {
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forEach { block ->
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launch {
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extractor.extract(block).collect { event ->
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hist[event.amplitude.toInt()].add(1L)
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}
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}
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}
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}
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val map = hist.mapIndexedNotNull { index, counter ->
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if (counter.value == 0L) {
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null
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} else {
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index.toUShort() to counter.value.toULong()
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}
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}.toMap()
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return NumassAmplitudeSpectrum(map)
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}
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@ -17,42 +17,46 @@
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package ru.inr.mass.data.analysis
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import kotlinx.coroutines.flow.Flow
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import kotlinx.coroutines.flow.collect
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import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.MAX_CHANNEL
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import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.channel
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import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.count
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import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.cr
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import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.crError
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import kotlinx.coroutines.flow.filter
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import ru.inr.mass.data.api.*
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import ru.inr.mass.data.api.NumassPoint.Companion.HV_KEY
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import ru.inr.mass.data.api.NumassPoint.Companion.LENGTH_KEY
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import space.kscience.dataforge.meta.*
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import space.kscience.dataforge.meta.descriptors.Described
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import space.kscience.dataforge.names.Name
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import space.kscience.dataforge.names.asName
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import space.kscience.dataforge.values.*
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import space.kscience.kmath.histogram.Counter
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import space.kscience.kmath.histogram.LongCounter
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import space.kscience.tables.*
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import kotlin.math.max
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import kotlin.math.min
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import kotlin.math.pow
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import kotlin.math.sqrt
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import space.kscience.dataforge.values.ListValue
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import space.kscience.dataforge.values.Value
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import space.kscience.dataforge.values.ValueType
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import space.kscience.dataforge.values.int
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import space.kscience.tables.ColumnHeader
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import space.kscience.tables.MetaRow
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import space.kscience.tables.RowTable
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import space.kscience.tables.Table
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import kotlin.properties.ReadWriteProperty
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public fun MutableMetaProvider.uIntRange(
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default: UIntRange = 0U..Int.MAX_VALUE.toUInt(),
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key: Name? = null,
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): ReadWriteProperty<Any?, UIntRange> = value(
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key,
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reader = { value ->
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val (l, r) = value?.list ?: return@value default
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l.int.toUInt()..r.int.toUInt()
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},
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writer = { range ->
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ListValue(range.first.toInt(), range.last.toInt())
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}
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)
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public class NumassAnalyzerResult : Scheme() {
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public var count: Long? by long(NumassAnalyzer.count.name.asName())
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public var countRate: Double? by double(NumassAnalyzer.cr.name.asName())
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public var countRateError: Double? by double(NumassAnalyzer.crError.name.asName())
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public var length: Long? by long(NumassAnalyzer.length.name.asName())
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public var count: Long by long(0L, NumassAnalyzer.count.name.asName())
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public var countRate: Double by double(0.0, NumassAnalyzer.cr.name.asName())
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public var countRateError: Double by double(0.0, NumassAnalyzer.crError.name.asName())
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public var length: Double by double(0.0, NumassAnalyzer.length.name.asName())
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public var voltage: Double? by double(HV_KEY.asName())
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public var window: UIntRange?
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get() = meta["window"]?.value?.list?.let {
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it[0].int.toUInt().rangeTo(it[1].int.toUInt())
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}
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set(value) {
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meta["window"] = value?.let { ListValue(it.first.toInt(), it.first.toInt()) }
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}
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public var parameters: NumassAnalyzerParameters by spec(NumassAnalyzerParameters)
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public companion object : SchemeSpec<NumassAnalyzerResult>(::NumassAnalyzerResult)
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}
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@ -62,7 +66,9 @@ public class NumassAnalyzerResult : Scheme() {
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* A general raw data analysis utility. Could have different implementations
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* Created by darksnake on 06-Jul-17.
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*/
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public interface NumassAnalyzer : Described {
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public abstract class NumassAnalyzer {
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public abstract val extractor: NumassEventExtractor
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/**
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* Perform analysis on block. The values for count rate, its error and point length in nanos must
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@ -71,67 +77,36 @@ public interface NumassAnalyzer : Described {
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* @param block
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* @return
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*/
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public suspend fun analyze(block: NumassBlock, config: Meta = Meta.EMPTY): NumassAnalyzerResult
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protected abstract suspend fun analyzeInternal(
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block: NumassBlock,
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parameters: NumassAnalyzerParameters,
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): NumassAnalyzerResult
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/**
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* Analysis result for point including hv information
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* @param point
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* @param config
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* @param parameters
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* @return
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*/
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public suspend fun analyzeParent(point: ParentBlock, config: Meta = Meta.EMPTY): NumassAnalyzerResult {
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// //Add properties to config
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// val newConfig = config.builder.apply {
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// if (point is NumassPoint) {
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// setValue("voltage", point.voltage)
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// setValue("index", point.index)
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// }
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// setValue("channel", point.channel)
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// }
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val res = analyze(point, config)
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public suspend fun analyze(
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point: ParentBlock,
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parameters: NumassAnalyzerParameters = NumassAnalyzerParameters.empty(),
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): NumassAnalyzerResult {
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val res = analyzeInternal(point, parameters)
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if (point is NumassPoint) {
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res.voltage = point.voltage
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}
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res.parameters = parameters
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return res
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}
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/**
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* Return unsorted stream of events including events from frames
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*
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* @param block
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* @return
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*/
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public fun getEvents(block: NumassBlock, meta: Meta = Meta.EMPTY): Flow<NumassEvent>
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/**
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* Analyze the whole set. And return results as a table
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*
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* @param set
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* @param config
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* @return
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*/
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public suspend fun analyzeSet(set: NumassSet, config: Meta): Table<Value>
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/**
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* Get the approximate number of events in block. Not all analyzers support precise event counting
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*
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* @param block
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* @param config
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* @return
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*/
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public suspend fun getCount(block: NumassBlock, config: Meta): Long =
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analyze(block, config).getValue(count.name)?.long ?: 0L
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/**
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* Get approximate effective point length in nanos. It is not necessary corresponds to real point length.
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*
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* @param block
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* @param config
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* @return
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*/
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public suspend fun getLength(block: NumassBlock, config: Meta = Meta.EMPTY): Long =
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analyze(block, config).getValue(LENGTH_KEY)?.long ?: 0L
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protected suspend fun NumassBlock.flowFilteredEvents(
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parameters: NumassAnalyzerParameters,
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): Flow<NumassEvent> {
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val window = parameters.window
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return extractor.extract(this).filter { it.amplitude in window }
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}
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public companion object {
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@ -149,120 +124,143 @@ public interface NumassAnalyzer : Described {
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}
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}
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public suspend fun NumassAnalyzer.getAmplitudeSpectrum(
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block: NumassBlock,
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range: UIntRange = 0U..MAX_CHANNEL,
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config: Meta = Meta.EMPTY,
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): Table<Value> {
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val seconds = block.getLength().inWholeMilliseconds.toDouble() / 1000.0
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return getEvents(block, config).getAmplitudeSpectrum(seconds, range)
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}
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/**
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* Calculate number of counts in the given channel
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* Analyze the whole set. And return results as a table
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*
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* @param spectrum
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* @param loChannel
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* @param upChannel
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* @return
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*/
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internal fun Table<Value>.countInWindow(loChannel: Short, upChannel: Short): Long = rows.filter { row ->
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row[channel]?.int in loChannel until upChannel
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}.sumOf { it[count]?.long ?: 0L }
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/**
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* Calculate the amplitude spectrum for a given block. The s
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*
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* @param this@getAmplitudeSpectrum
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* @param length length in seconds, used for count rate calculation
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* @param set
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* @param config
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* @return
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*/
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private suspend fun Flow<NumassEvent>.getAmplitudeSpectrum(
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length: Double,
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range: UIntRange = 0U..MAX_CHANNEL,
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): Table<Value> {
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//optimized for fastest computation
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val spectrum: MutableMap<UInt, LongCounter> = HashMap()
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collect { event ->
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val channel = event.amplitude
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spectrum.getOrPut(channel.toUInt()) {
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LongCounter()
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}.add(1L)
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}
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return RowTable<Value>(channel, count, cr, crError) {
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range.forEach { ch ->
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val countValue: Long = spectrum[ch]?.value ?: 0L
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valueRow(
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channel to ch,
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count to countValue,
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cr to (countValue.toDouble() / length),
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crError to sqrt(countValue.toDouble()) / length
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)
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}
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public suspend fun NumassAnalyzer.analyzeSet(
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set: NumassSet,
|
||||
config: NumassAnalyzerParameters = NumassAnalyzerParameters.empty(),
|
||||
): Table<Value> = RowTable(
|
||||
NumassAnalyzer.length,
|
||||
NumassAnalyzer.count,
|
||||
NumassAnalyzer.cr,
|
||||
NumassAnalyzer.crError,
|
||||
// NumassAnalyzer.window,
|
||||
// NumassAnalyzer.timestamp
|
||||
) {
|
||||
set.points.forEach { point ->
|
||||
addRow(MetaRow(analyze(point, config).meta))
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Apply window and binning to a spectrum. Empty bins are filled with zeroes
|
||||
*/
|
||||
private fun Table<Value>.withBinning(
|
||||
binSize: UInt, range: UIntRange = 0U..MAX_CHANNEL,
|
||||
): Table<Value> = RowTable<Value>(channel, count, cr, crError) {
|
||||
// var chan = loChannel
|
||||
// ?: this.getColumn(NumassAnalyzer.CHANNEL_KEY).stream().mapToInt { it.int }.min().orElse(0)
|
||||
//
|
||||
// val top = upChannel
|
||||
// ?: this.getColumn(NumassAnalyzer.CHANNEL_KEY).stream().mapToInt { it.int }.max().orElse(1)
|
||||
|
||||
val binSizeColumn = newColumn<Value>("binSize")
|
||||
|
||||
var chan = range.first
|
||||
|
||||
while (chan < range.last - binSize) {
|
||||
val counter = LongCounter()
|
||||
val countRateCounter = Counter.real()
|
||||
val countRateDispersionCounter = Counter.real()
|
||||
|
||||
val binLo = chan
|
||||
val binUp = chan + binSize
|
||||
|
||||
rows.filter { row ->
|
||||
(row[channel]?.int ?: 0U) in binLo until binUp
|
||||
}.forEach { row ->
|
||||
counter.add(row[count]?.long ?: 0L)
|
||||
countRateCounter.add(row[cr]?.double ?: 0.0)
|
||||
countRateDispersionCounter.add(row[crError]?.double?.pow(2.0) ?: 0.0)
|
||||
}
|
||||
val bin = min(binSize, range.last - chan)
|
||||
|
||||
valueRow(
|
||||
channel to (chan.toDouble() + bin.toDouble() / 2.0),
|
||||
count to counter.value,
|
||||
cr to countRateCounter.value,
|
||||
crError to sqrt(countRateDispersionCounter.value),
|
||||
binSizeColumn to bin
|
||||
)
|
||||
chan += binSize
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Subtract reference spectrum.
|
||||
*/
|
||||
private fun subtractAmplitudeSpectrum(
|
||||
sp1: Table<Value>, sp2: Table<Value>,
|
||||
): Table<Value> = RowTable<Value>(channel, cr, crError) {
|
||||
sp1.rows.forEach { row1 ->
|
||||
val channelValue = row1[channel]?.double
|
||||
val row2 = sp2.rows.find { it[channel]?.double == channelValue } ?: MapRow(emptyMap())
|
||||
|
||||
val value = max((row1[cr]?.double ?: 0.0) - (row2[cr]?.double ?: 0.0), 0.0)
|
||||
val error1 = row1[crError]?.double ?: 0.0
|
||||
val error2 = row2[crError]?.double ?: 0.0
|
||||
val error = sqrt(error1 * error1 + error2 * error2)
|
||||
valueRow(channel to channelValue, cr to value, crError to error)
|
||||
}
|
||||
}
|
||||
//public suspend fun NumassAnalyzer.getAmplitudeSpectrum(
|
||||
// block: NumassBlock,
|
||||
// range: UIntRange = 0U..MAX_CHANNEL,
|
||||
// config: Meta = Meta.EMPTY,
|
||||
//): Table<Value> {
|
||||
// val seconds = block.getLength().inWholeMilliseconds.toDouble() / 1000.0
|
||||
// return getEvents(block, config).getAmplitudeSpectrum(seconds, range)
|
||||
//}
|
||||
//
|
||||
///**
|
||||
// * Calculate number of counts in the given channel
|
||||
// *
|
||||
// * @param spectrum
|
||||
// * @param loChannel
|
||||
// * @param upChannel
|
||||
// * @return
|
||||
// */
|
||||
//internal fun Table<Value>.countInWindow(loChannel: Short, upChannel: Short): Long = rows.filter { row ->
|
||||
// row[channel]?.int in loChannel until upChannel
|
||||
//}.sumOf { it[count]?.long ?: 0L }
|
||||
//
|
||||
///**
|
||||
// * Calculate the amplitude spectrum for a given block. The s
|
||||
// *
|
||||
// * @param this@getAmplitudeSpectrum
|
||||
// * @param length length in seconds, used for count rate calculation
|
||||
// * @param config
|
||||
// * @return
|
||||
// */
|
||||
//private suspend fun Flow<NumassEvent>.getAmplitudeSpectrum(
|
||||
// length: Double,
|
||||
// range: UIntRange = 0U..MAX_CHANNEL,
|
||||
//): Table<Value> {
|
||||
//
|
||||
// //optimized for fastest computation
|
||||
// val spectrum: MutableMap<UInt, LongCounter> = HashMap()
|
||||
// collect { event ->
|
||||
// val channel = event.amplitude
|
||||
// spectrum.getOrPut(channel.toUInt()) {
|
||||
// LongCounter()
|
||||
// }.add(1L)
|
||||
// }
|
||||
//
|
||||
// return RowTable<Value>(channel, count, cr, crError) {
|
||||
// range.forEach { ch ->
|
||||
// val countValue: Long = spectrum[ch]?.value ?: 0L
|
||||
// valueRow(
|
||||
// channel to ch,
|
||||
// count to countValue,
|
||||
// cr to (countValue.toDouble() / length),
|
||||
// crError to sqrt(countValue.toDouble()) / length
|
||||
// )
|
||||
// }
|
||||
// }
|
||||
//}
|
||||
//
|
||||
///**
|
||||
// * Apply window and binning to a spectrum. Empty bins are filled with zeroes
|
||||
// */
|
||||
//private fun Table<Value>.withBinning(
|
||||
// binSize: UInt, range: UIntRange = 0U..MAX_CHANNEL,
|
||||
//): Table<Value> = RowTable<Value>(channel, count, cr, crError) {
|
||||
//// var chan = loChannel
|
||||
//// ?: this.getColumn(NumassAnalyzer.CHANNEL_KEY).stream().mapToInt { it.int }.min().orElse(0)
|
||||
////
|
||||
//// val top = upChannel
|
||||
//// ?: this.getColumn(NumassAnalyzer.CHANNEL_KEY).stream().mapToInt { it.int }.max().orElse(1)
|
||||
//
|
||||
// val binSizeColumn = newColumn<Value>("binSize")
|
||||
//
|
||||
// var chan = range.first
|
||||
//
|
||||
// while (chan < range.last - binSize) {
|
||||
// val counter = LongCounter()
|
||||
// val countRateCounter = Counter.real()
|
||||
// val countRateDispersionCounter = Counter.real()
|
||||
//
|
||||
// val binLo = chan
|
||||
// val binUp = chan + binSize
|
||||
//
|
||||
// rows.filter { row ->
|
||||
// (row[channel]?.int ?: 0U) in binLo until binUp
|
||||
// }.forEach { row ->
|
||||
// counter.add(row[count]?.long ?: 0L)
|
||||
// countRateCounter.add(row[cr]?.double ?: 0.0)
|
||||
// countRateDispersionCounter.add(row[crError]?.double?.pow(2.0) ?: 0.0)
|
||||
// }
|
||||
// val bin = min(binSize, range.last - chan)
|
||||
//
|
||||
// valueRow(
|
||||
// channel to (chan.toDouble() + bin.toDouble() / 2.0),
|
||||
// count to counter.value,
|
||||
// cr to countRateCounter.value,
|
||||
// crError to sqrt(countRateDispersionCounter.value),
|
||||
// binSizeColumn to bin
|
||||
// )
|
||||
// chan += binSize
|
||||
// }
|
||||
//}
|
||||
//
|
||||
///**
|
||||
// * Subtract reference spectrum.
|
||||
// */
|
||||
//private fun subtractAmplitudeSpectrum(
|
||||
// sp1: Table<Value>, sp2: Table<Value>,
|
||||
//): Table<Value> = RowTable<Value>(channel, cr, crError) {
|
||||
// sp1.rows.forEach { row1 ->
|
||||
// val channelValue = row1[channel]?.double
|
||||
// val row2 = sp2.rows.find { it[channel]?.double == channelValue } ?: MapRow(emptyMap())
|
||||
//
|
||||
// val value = max((row1[cr]?.double ?: 0.0) - (row2[cr]?.double ?: 0.0), 0.0)
|
||||
// val error1 = row1[crError]?.double ?: 0.0
|
||||
// val error2 = row2[crError]?.double ?: 0.0
|
||||
// val error = sqrt(error1 * error1 + error2 * error2)
|
||||
// valueRow(channel to channelValue, cr to value, crError to error)
|
||||
// }
|
||||
//}
|
||||
@ -0,0 +1,46 @@
|
||||
package ru.inr.mass.data.analysis
|
||||
|
||||
import space.kscience.dataforge.meta.*
|
||||
|
||||
public class TimeAnalyzerParameters : Scheme() {
|
||||
|
||||
public enum class AveragingMethod {
|
||||
ARITHMETIC,
|
||||
WEIGHTED,
|
||||
GEOMETRIC
|
||||
}
|
||||
|
||||
public var value: Int? by int()
|
||||
|
||||
/**
|
||||
* The relative fraction of events that should be removed by time cut
|
||||
*/
|
||||
public var crFraction by double()
|
||||
public var min by double(0.0)
|
||||
public var crMin by double(0.0)
|
||||
|
||||
/**
|
||||
* The number of events in chunk to split the chain into. If null, no chunks are used
|
||||
*/
|
||||
public var chunkSize: Int? by int()
|
||||
|
||||
public var inverted: Boolean by boolean(true)
|
||||
public var sortEvents: Boolean by boolean(false)
|
||||
|
||||
/**
|
||||
* Chunk averaging method
|
||||
*/
|
||||
public var averagingMethod: AveragingMethod by enum(AveragingMethod.WEIGHTED)
|
||||
|
||||
public companion object : SchemeSpec<TimeAnalyzerParameters>(::TimeAnalyzerParameters)
|
||||
}
|
||||
|
||||
public class NumassAnalyzerParameters : Scheme() {
|
||||
public var deadTime: Double by double(0.0)
|
||||
public var window: UIntRange by uIntRange()
|
||||
|
||||
public var t0: TimeAnalyzerParameters by spec(TimeAnalyzerParameters)
|
||||
|
||||
|
||||
public companion object : SchemeSpec<NumassAnalyzerParameters>(::NumassAnalyzerParameters)
|
||||
}
|
||||
@ -0,0 +1,22 @@
|
||||
package ru.inr.mass.data.analysis
|
||||
|
||||
import kotlinx.coroutines.flow.Flow
|
||||
import ru.inr.mass.data.api.NumassBlock
|
||||
import ru.inr.mass.data.api.NumassEvent
|
||||
|
||||
public fun interface NumassEventExtractor {
|
||||
public suspend fun extract(block: NumassBlock): Flow<NumassEvent>
|
||||
|
||||
public companion object {
|
||||
/**
|
||||
* A default event extractor that ignores frames
|
||||
*/
|
||||
public val EVENTS_ONLY: NumassEventExtractor = NumassEventExtractor { it.events }
|
||||
}
|
||||
}
|
||||
|
||||
//public fun NumassEventExtractor.filter(
|
||||
// condition: NumassBlock.(NumassEvent) -> Boolean,
|
||||
//): NumassEventExtractor = NumassEventExtractor { block ->
|
||||
// extract(block).filter { block.condition(it) }
|
||||
//}
|
||||
@ -11,11 +11,12 @@ package ru.inr.mass.data.analysis
|
||||
//import ru.inr.mass.data.api.NumassBlock
|
||||
//import ru.inr.mass.data.api.OrphanNumassEvent
|
||||
//import ru.inr.mass.data.api.SimpleBlock
|
||||
//import space.kscience.dataforge.tables.Table
|
||||
//import space.kscience.kmath.chains.Chain
|
||||
//import space.kscience.kmath.chains.MarkovChain
|
||||
//import space.kscience.kmath.chains.StatefulChain
|
||||
//import space.kscience.kmath.stat.RandomGenerator
|
||||
//import space.kscience.tables.Table
|
||||
//import kotlin.math.ln
|
||||
//import kotlin.time.Duration.Companion.nanoseconds
|
||||
//
|
||||
//private fun RandomGenerator.nextExp(mean: Double): Double {
|
||||
|
||||
@ -14,43 +14,29 @@
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
package inr.numass.data.analyzers
|
||||
package ru.inr.mass.data.analysis
|
||||
|
||||
import kotlinx.coroutines.flow.count
|
||||
import ru.inr.mass.data.analysis.AbstractAnalyzer
|
||||
import ru.inr.mass.data.analysis.NumassAnalyzerResult
|
||||
import ru.inr.mass.data.api.NumassBlock
|
||||
import ru.inr.mass.data.api.SignalProcessor
|
||||
import space.kscience.dataforge.meta.Meta
|
||||
import space.kscience.dataforge.meta.descriptors.MetaDescriptor
|
||||
import space.kscience.dataforge.meta.descriptors.value
|
||||
import space.kscience.dataforge.meta.double
|
||||
import space.kscience.dataforge.meta.get
|
||||
import space.kscience.dataforge.meta.int
|
||||
import space.kscience.dataforge.values.ValueType
|
||||
import kotlin.math.sqrt
|
||||
|
||||
/**
|
||||
* A simple event counter
|
||||
* Created by darksnake on 07.07.2017.
|
||||
*/
|
||||
public class SimpleAnalyzer(processor: SignalProcessor? = null) : AbstractAnalyzer(processor) {
|
||||
public class SimpleAnalyzer(
|
||||
override val extractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
|
||||
) : NumassAnalyzer() {
|
||||
|
||||
override val descriptor: MetaDescriptor = MetaDescriptor {
|
||||
value("deadTime", ValueType.NUMBER) {
|
||||
info = "Dead time in nanoseconds for correction"
|
||||
default(0.0)
|
||||
}
|
||||
}
|
||||
override suspend fun analyzeInternal(
|
||||
block: NumassBlock,
|
||||
parameters: NumassAnalyzerParameters
|
||||
): NumassAnalyzerResult {
|
||||
|
||||
override suspend fun analyze(block: NumassBlock, config: Meta): NumassAnalyzerResult {
|
||||
val loChannel = config["window.lo"]?.int ?: 0
|
||||
val upChannel = config["window.up"]?.int ?: Int.MAX_VALUE
|
||||
|
||||
val count: Int = getEvents(block, config).count()
|
||||
val count: Int = block.flowFilteredEvents(parameters).count()
|
||||
val length: Double = block.getLength().inWholeNanoseconds.toDouble() / 1e9
|
||||
|
||||
val deadTime = config["deadTime"]?.double ?: 0.0
|
||||
val deadTime = parameters.deadTime
|
||||
|
||||
val countRate = if (deadTime > 0) {
|
||||
val mu = count.toDouble() / length
|
||||
@ -61,11 +47,10 @@ public class SimpleAnalyzer(processor: SignalProcessor? = null) : AbstractAnalyz
|
||||
val countRateError = sqrt(count.toDouble()) / length
|
||||
|
||||
return NumassAnalyzerResult {
|
||||
this.length = length.toLong()
|
||||
this.length = length
|
||||
this.count = count.toLong()
|
||||
this.countRate = countRate
|
||||
this.countRateError = countRateError
|
||||
this.window = loChannel.toUInt().rangeTo(upChannel.toUInt())
|
||||
//TODO NumassAnalyzer.timestamp to block.startTime
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,104 +0,0 @@
|
||||
///*
|
||||
// * Copyright 2017 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 ru.inr.mass.data.analysis
|
||||
|
||||
import inr.numass.data.analyzers.SimpleAnalyzer
|
||||
import kotlinx.coroutines.flow.Flow
|
||||
import ru.inr.mass.data.api.NumassBlock
|
||||
import ru.inr.mass.data.api.NumassEvent
|
||||
import ru.inr.mass.data.api.NumassSet
|
||||
import ru.inr.mass.data.api.SignalProcessor
|
||||
import space.kscience.dataforge.meta.Meta
|
||||
import space.kscience.dataforge.meta.descriptors.MetaDescriptor
|
||||
import space.kscience.dataforge.meta.get
|
||||
import space.kscience.dataforge.meta.string
|
||||
import space.kscience.dataforge.values.Value
|
||||
import space.kscience.dataforge.values.asValue
|
||||
import space.kscience.dataforge.values.setValue
|
||||
import space.kscience.tables.Table
|
||||
|
||||
/**
|
||||
* An analyzer dispatcher which uses different analyzer for different meta
|
||||
* Created by darksnake on 11.07.2017.
|
||||
*/
|
||||
public open class SmartAnalyzer(processor: SignalProcessor? = null) : AbstractAnalyzer(processor) {
|
||||
private val simpleAnalyzer = SimpleAnalyzer(processor)
|
||||
private val debunchAnalyzer = DebunchAnalyzer(processor)
|
||||
private val timeAnalyzer: NumassAnalyzer = TODO()// TimeAnalyzer(processor)
|
||||
|
||||
override val descriptor: MetaDescriptor? = null
|
||||
|
||||
private fun getAnalyzer(config: Meta): NumassAnalyzer = when (val type = config["type"]?.string) {
|
||||
null -> if (config["t0"] != null) {
|
||||
timeAnalyzer
|
||||
} else {
|
||||
simpleAnalyzer
|
||||
}
|
||||
"simple" -> simpleAnalyzer
|
||||
"time" -> timeAnalyzer
|
||||
"debunch" -> debunchAnalyzer
|
||||
else -> throw IllegalArgumentException("Analyzer $type not found")
|
||||
}
|
||||
|
||||
override suspend fun analyze(block: NumassBlock, config: Meta): NumassAnalyzerResult {
|
||||
val analyzer = getAnalyzer(config)
|
||||
val res = analyzer.analyze(block, config)
|
||||
return NumassAnalyzerResult.read(res.meta).apply {
|
||||
setValue(T0_KEY, 0.0.asValue())
|
||||
}
|
||||
}
|
||||
|
||||
override fun getEvents(block: NumassBlock, meta: Meta): Flow<NumassEvent> =
|
||||
getAnalyzer(meta).getEvents(block, meta)
|
||||
|
||||
|
||||
override suspend fun analyzeSet(set: NumassSet, config: Meta): Table<Value> {
|
||||
return getAnalyzer(config).analyzeSet(set, config)
|
||||
// fun Value.computeExpression(point: NumassPoint): Int {
|
||||
// return when {
|
||||
// this.type == ValueType.NUMBER -> this.int
|
||||
// this.type == ValueType.STRING -> {
|
||||
// val exprParams = HashMap<String, Any>()
|
||||
//
|
||||
// exprParams["U"] = point.voltage
|
||||
//
|
||||
// ExpressionUtils.function(this.string, exprParams).toInt()
|
||||
// }
|
||||
// else -> error("Can't interpret $type as expression or number")
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// val lo = config.getValue("window.lo", 0)
|
||||
// val up = config.getValue("window.up", Int.MAX_VALUE)
|
||||
//
|
||||
// val format = getTableFormat(config)
|
||||
//
|
||||
// return ListTable.Builder(format)
|
||||
// .rows(set.points.map { point ->
|
||||
// val newConfig = config.builder.apply {
|
||||
// setValue("window.lo", lo.computeExpression(point))
|
||||
// setValue("window.up", up.computeExpression(point))
|
||||
// }
|
||||
// analyzeParent(point, newConfig)
|
||||
// })
|
||||
// .build()
|
||||
}
|
||||
|
||||
public companion object : SmartAnalyzer() {
|
||||
public const val T0_KEY: String = "t0"
|
||||
}
|
||||
}
|
||||
@ -15,286 +15,161 @@
|
||||
// */
|
||||
//
|
||||
package ru.inr.mass.data.analysis
|
||||
//
|
||||
//import hep.dataforge.description.ValueDef
|
||||
//import hep.dataforge.description.ValueDefs
|
||||
//import hep.dataforge.meta.Meta
|
||||
//import hep.dataforge.tables.Adapters.*
|
||||
//import hep.dataforge.tables.TableFormat
|
||||
//import hep.dataforge.tables.TableFormatBuilder
|
||||
//import hep.dataforge.values.*
|
||||
//import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.COUNT_KEY
|
||||
//import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.COUNT_RATE_ERROR_KEY
|
||||
//import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.COUNT_RATE_KEY
|
||||
//import ru.inr.mass.data.analysis.NumassAnalyzer.Companion.LENGTH_KEY
|
||||
//import ru.inr.mass.data.analysis.TimeAnalyzer.AveragingMethod.*
|
||||
//import inr.numass.data.api.*
|
||||
//import inr.numass.data.api.NumassPoint.Companion.HV_KEY
|
||||
//import ru.inr.mass.data.api.NumassBlock
|
||||
//import ru.inr.mass.data.api.SignalProcessor
|
||||
//import space.kscience.dataforge.values.ValueType
|
||||
//import java.util.*
|
||||
//import java.util.concurrent.atomic.AtomicLong
|
||||
//import kotlin.collections.List
|
||||
//import kotlin.collections.asSequence
|
||||
//import kotlin.collections.count
|
||||
//import kotlin.collections.first
|
||||
//import kotlin.collections.map
|
||||
//import kotlin.collections.set
|
||||
//import kotlin.collections.sortBy
|
||||
//import kotlin.collections.sumBy
|
||||
//import kotlin.collections.sumByDouble
|
||||
//import kotlin.collections.toMutableList
|
||||
//import kotlin.math.*
|
||||
//import kotlin.streams.asSequence
|
||||
//
|
||||
//
|
||||
///**
|
||||
// * An analyzer which uses time information from events
|
||||
// * Created by darksnake on 11.07.2017.
|
||||
// */
|
||||
//@ValueDefs(
|
||||
// ValueDef(
|
||||
// key = "separateParallelBlocks",
|
||||
// type = [ValueType.BOOLEAN],
|
||||
// info = "If true, then parallel blocks will be forced to be evaluated separately"
|
||||
// ),
|
||||
// ValueDef(
|
||||
// key = "chunkSize",
|
||||
// type = [ValueType.NUMBER],
|
||||
// def = "-1",
|
||||
// info = "The number of events in chunk to split the chain into. If negative, no chunks are used"
|
||||
// )
|
||||
//)
|
||||
//open class TimeAnalyzer(processor: SignalProcessor? = null) : AbstractAnalyzer(processor) {
|
||||
//
|
||||
// override fun analyze(block: NumassBlock, config: Meta): Values {
|
||||
// //In case points inside points
|
||||
// if (block is ParentBlock && (block.isSequential || config.getBoolean("separateParallelBlocks", false))) {
|
||||
// return analyzeParent(block, config)
|
||||
// }
|
||||
//
|
||||
// val t0 = getT0(block, config).toLong()
|
||||
//
|
||||
// val chunkSize = config.getInt("chunkSize", -1)
|
||||
//
|
||||
// val count = super.getEvents(block, config).count()
|
||||
// val length = block.length.toNanos().toDouble() / 1e9
|
||||
//
|
||||
// val res = when {
|
||||
// count < 1000 -> ValueMap.ofPairs(
|
||||
// LENGTH_KEY to length,
|
||||
// COUNT_KEY to count,
|
||||
// COUNT_RATE_KEY to count.toDouble() / length,
|
||||
// COUNT_RATE_ERROR_KEY to sqrt(count.toDouble()) / length
|
||||
// )
|
||||
// chunkSize > 0 -> getEventsWithDelay(block, config)
|
||||
// .chunked(chunkSize) { analyzeSequence(it.asSequence(), t0) }
|
||||
// .toList()
|
||||
// .mean(config.getEnum("mean", WEIGHTED))
|
||||
// else -> analyzeSequence(getEventsWithDelay(block, config), t0)
|
||||
// }
|
||||
//
|
||||
// return ValueMap.Builder(res)
|
||||
// .putValue("blockLength", length)
|
||||
// .putValue(NumassAnalyzer.WINDOW_KEY, config.getRange())
|
||||
// .putValue(NumassAnalyzer.TIME_KEY, block.startTime)
|
||||
// .putValue(T0_KEY, t0.toDouble() / 1000.0)
|
||||
// .build()
|
||||
// }
|
||||
//
|
||||
//
|
||||
// private fun analyzeSequence(sequence: Sequence<Pair<NumassEvent, Long>>, t0: Long): Values {
|
||||
// val totalN = AtomicLong(0)
|
||||
// val totalT = AtomicLong(0)
|
||||
// sequence.filter { pair -> pair.second >= t0 }
|
||||
// .forEach { pair ->
|
||||
// totalN.incrementAndGet()
|
||||
// //TODO add progress listener here
|
||||
// totalT.addAndGet(pair.second)
|
||||
// }
|
||||
//
|
||||
// if (totalN.toInt() == 0) {
|
||||
// error("Zero number of intervals")
|
||||
// }
|
||||
//
|
||||
// val countRate =
|
||||
// 1e6 * totalN.get() / (totalT.get() / 1000 - t0 * totalN.get() / 1000)//1e9 / (totalT.get() / totalN.get() - t0);
|
||||
// val countRateError = countRate / sqrt(totalN.get().toDouble())
|
||||
// val length = totalT.get() / 1e9
|
||||
// val count = (length * countRate).toLong()
|
||||
//
|
||||
// return ValueMap.ofPairs(
|
||||
// LENGTH_KEY to length,
|
||||
// COUNT_KEY to count,
|
||||
// COUNT_RATE_KEY to countRate,
|
||||
// COUNT_RATE_ERROR_KEY to countRateError
|
||||
// )
|
||||
//
|
||||
// }
|
||||
//
|
||||
// override fun analyzeParent(point: ParentBlock, config: Meta): Values {
|
||||
// //Average count rates, do not sum events
|
||||
// val res = point.blocks.map { it -> analyze(it, config) }
|
||||
//
|
||||
// val map = HashMap(res.mean(config.getEnum("mean", WEIGHTED)).asMap())
|
||||
// if (point is NumassPoint) {
|
||||
// map[HV_KEY] = Value.of(point.voltage)
|
||||
// }
|
||||
// return ValueMap(map)
|
||||
// }
|
||||
//
|
||||
// enum class AveragingMethod {
|
||||
// ARITHMETIC,
|
||||
// WEIGHTED,
|
||||
// GEOMETRIC
|
||||
// }
|
||||
//
|
||||
// /**
|
||||
// * Combine multiple blocks from the same point into one
|
||||
// *
|
||||
// * @return
|
||||
// */
|
||||
// private fun List<Values>.mean(method: AveragingMethod): Values {
|
||||
//
|
||||
// if (this.isEmpty()) {
|
||||
// return ValueMap.Builder()
|
||||
// .putValue(LENGTH_KEY, 0)
|
||||
// .putValue(COUNT_KEY, 0)
|
||||
// .putValue(COUNT_RATE_KEY, 0)
|
||||
// .putValue(COUNT_RATE_ERROR_KEY, 0)
|
||||
// .build()
|
||||
// }
|
||||
//
|
||||
// val totalTime = sumByDouble { it.getDouble(LENGTH_KEY) }
|
||||
//
|
||||
// val (countRate, countRateDispersion) = when (method) {
|
||||
// ARITHMETIC -> Pair(
|
||||
// sumByDouble { it.getDouble(COUNT_RATE_KEY) } / size,
|
||||
// sumByDouble { it.getDouble(COUNT_RATE_ERROR_KEY).pow(2.0) } / size / size
|
||||
// )
|
||||
// WEIGHTED -> Pair(
|
||||
// sumByDouble { it.getDouble(COUNT_RATE_KEY) * it.getDouble(LENGTH_KEY) } / totalTime,
|
||||
// sumByDouble { (it.getDouble(COUNT_RATE_ERROR_KEY) * it.getDouble(LENGTH_KEY) / totalTime).pow(2.0) }
|
||||
// )
|
||||
// GEOMETRIC -> {
|
||||
// val mean = exp(sumByDouble { ln(it.getDouble(COUNT_RATE_KEY)) } / size)
|
||||
// val variance = (mean / size).pow(2.0) * sumByDouble {
|
||||
// (it.getDouble(COUNT_RATE_ERROR_KEY) / it.getDouble(
|
||||
// COUNT_RATE_KEY
|
||||
// )).pow(2.0)
|
||||
// }
|
||||
// Pair(mean, variance)
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// return ValueMap.Builder(first())
|
||||
// .putValue(LENGTH_KEY, totalTime)
|
||||
// .putValue(COUNT_KEY, sumBy { it.getInt(COUNT_KEY) })
|
||||
// .putValue(COUNT_RATE_KEY, countRate)
|
||||
// .putValue(COUNT_RATE_ERROR_KEY, sqrt(countRateDispersion))
|
||||
// .build()
|
||||
// }
|
||||
//
|
||||
// @ValueDefs(
|
||||
// ValueDef(key = "t0", type = arrayOf(ValueType.NUMBER), info = "Constant t0 cut"),
|
||||
// ValueDef(
|
||||
// key = "t0.crFraction",
|
||||
// type = arrayOf(ValueType.NUMBER),
|
||||
// info = "The relative fraction of events that should be removed by time cut"
|
||||
// ),
|
||||
// ValueDef(key = "t0.min", type = arrayOf(ValueType.NUMBER), def = "0", info = "Minimal t0")
|
||||
// )
|
||||
// protected fun getT0(block: NumassBlock, meta: Meta): Int {
|
||||
// return if (meta.hasValue("t0")) {
|
||||
// meta.getInt("t0")
|
||||
// } else if (meta.hasMeta("t0")) {
|
||||
// val fraction = meta.getDouble("t0.crFraction")
|
||||
// val cr = estimateCountRate(block)
|
||||
// if (cr < meta.getDouble("t0.minCR", 0.0)) {
|
||||
// 0
|
||||
// } else {
|
||||
// max(-1e9 / cr * ln(1.0 - fraction), meta.getDouble("t0.min", 0.0)).toInt()
|
||||
// }
|
||||
// } else {
|
||||
// 0
|
||||
// }
|
||||
//
|
||||
// }
|
||||
//
|
||||
// private fun estimateCountRate(block: NumassBlock): Double {
|
||||
// return block.events.count().toDouble() / block.length.toMillis() * 1000
|
||||
// }
|
||||
//
|
||||
// fun zipEvents(block: NumassBlock, config: Meta): Sequence<Pair<NumassEvent, NumassEvent>> {
|
||||
// return getAllEvents(block).asSequence().zipWithNext()
|
||||
// }
|
||||
//
|
||||
// /**
|
||||
// * The chain of event with delays in nanos
|
||||
// *
|
||||
// * @param block
|
||||
// * @param config
|
||||
// * @return
|
||||
// */
|
||||
// fun getEventsWithDelay(block: NumassBlock, config: Meta): Sequence<Pair<NumassEvent, Long>> {
|
||||
// val inverted = config.getBoolean("inverted", true)
|
||||
// //range is included in super.getEvents
|
||||
// val events = super.getEvents(block, config).toMutableList()
|
||||
//
|
||||
// if (config.getBoolean("sortEvents", false) || (block is ParentBlock && !block.isSequential)) {
|
||||
// //sort in place if needed
|
||||
// events.sortBy { it.timeOffset }
|
||||
// }
|
||||
//
|
||||
// return events.asSequence().zipWithNext { prev, next ->
|
||||
// val delay = max(next.timeOffset - prev.timeOffset, 0)
|
||||
// if (inverted) {
|
||||
// Pair(next, delay)
|
||||
// } else {
|
||||
// Pair(prev, delay)
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
//
|
||||
// /**
|
||||
// * The filtered stream of events
|
||||
// *
|
||||
// * @param block
|
||||
// * @param meta
|
||||
// * @return
|
||||
// */
|
||||
// override fun getEvents(block: NumassBlock, meta: Meta): List<NumassEvent> {
|
||||
// val t0 = getT0(block, meta).toLong()
|
||||
// return getEventsWithDelay(block, meta)
|
||||
// .filter { pair -> pair.second >= t0 }
|
||||
// .map { it.first }.toList()
|
||||
// }
|
||||
//
|
||||
// public override fun getTableFormat(config: Meta): TableFormat {
|
||||
// return TableFormatBuilder()
|
||||
// .addNumber(HV_KEY, X_VALUE_KEY)
|
||||
// .addNumber(LENGTH_KEY)
|
||||
// .addNumber(COUNT_KEY)
|
||||
// .addNumber(COUNT_RATE_KEY, Y_VALUE_KEY)
|
||||
// .addNumber(COUNT_RATE_ERROR_KEY, Y_ERROR_KEY)
|
||||
// .addColumn(NumassAnalyzer.WINDOW_KEY)
|
||||
// .addTime()
|
||||
// .addNumber(T0_KEY)
|
||||
// .build()
|
||||
// }
|
||||
//
|
||||
// companion object {
|
||||
// const val T0_KEY = "t0"
|
||||
//
|
||||
// val NAME_LIST = arrayOf(
|
||||
// LENGTH_KEY,
|
||||
// COUNT_KEY,
|
||||
// COUNT_RATE_KEY,
|
||||
// COUNT_RATE_ERROR_KEY,
|
||||
// NumassAnalyzer.WINDOW_KEY,
|
||||
// NumassAnalyzer.TIME_KEY,
|
||||
// T0_KEY
|
||||
// )
|
||||
// }
|
||||
//}
|
||||
|
||||
import kotlinx.coroutines.flow.*
|
||||
import ru.inr.mass.data.analysis.TimeAnalyzerParameters.AveragingMethod
|
||||
import ru.inr.mass.data.api.NumassBlock
|
||||
import ru.inr.mass.data.api.NumassEvent
|
||||
import ru.inr.mass.data.api.ParentBlock
|
||||
import space.kscience.kmath.streaming.asFlow
|
||||
import space.kscience.kmath.streaming.chunked
|
||||
import space.kscience.kmath.structures.Buffer
|
||||
import kotlin.math.*
|
||||
|
||||
|
||||
/**
|
||||
* An analyzer which uses time information from events
|
||||
* Created by darksnake on 11.07.2017.
|
||||
*/
|
||||
public open class TimeAnalyzer(override val extractor: NumassEventExtractor) : NumassAnalyzer() {
|
||||
|
||||
override suspend fun analyzeInternal(
|
||||
block: NumassBlock,
|
||||
parameters: NumassAnalyzerParameters,
|
||||
): NumassAnalyzerResult {
|
||||
//Parallel processing and merging of parent blocks
|
||||
if (block is ParentBlock) {
|
||||
val res = block.flowBlocks().map { analyzeInternal(it, parameters) }.toList()
|
||||
return res.combineResults(parameters.t0.averagingMethod)
|
||||
}
|
||||
|
||||
val t0 = getT0(block, parameters.t0).toLong()
|
||||
|
||||
return when (val chunkSize = parameters.t0.chunkSize) {
|
||||
null -> block.flowFilteredEvents(parameters)
|
||||
.byPairs(parameters.t0.inverted)
|
||||
.analyze(t0)
|
||||
// // chunk is larger than a number of event
|
||||
// chunkSize > count -> NumassAnalyzerResult {
|
||||
// this.length = length
|
||||
// this.count = count
|
||||
// this.countRate = count.toDouble() / length
|
||||
// this.countRateError = sqrt(count.toDouble()) / length
|
||||
// }
|
||||
else -> block.flowFilteredEvents(parameters)
|
||||
.byPairs(parameters.t0.inverted)
|
||||
.chunked(chunkSize, Buffer.Companion::auto)
|
||||
.map { it.asFlow().analyze(t0) }
|
||||
.toList()
|
||||
.combineResults(parameters.t0.averagingMethod)
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
|
||||
/**
|
||||
* Analyze given flow of events + delays
|
||||
*/
|
||||
private suspend fun Flow<Pair<NumassEvent, Long>>.analyze(t0: Long): NumassAnalyzerResult {
|
||||
var totalN = 0L
|
||||
var totalT = 0L
|
||||
filter { pair -> pair.second >= t0 }.collect { pair ->
|
||||
totalN++
|
||||
//TODO add progress listener here
|
||||
totalT+= pair.second
|
||||
}
|
||||
|
||||
if (totalN == 0L) {
|
||||
error("Zero number of intervals")
|
||||
}
|
||||
|
||||
val countRate = 1e6 * totalN / (totalT / 1000 - t0 * totalN / 1000)
|
||||
val countRateError = countRate / sqrt(totalN.toDouble())
|
||||
val length = totalT / 1e9
|
||||
val count = (length * countRate).toLong()
|
||||
|
||||
return NumassAnalyzerResult {
|
||||
this.length = totalT / 1e9
|
||||
this.count = count
|
||||
this.countRate = countRate
|
||||
this.countRateError = countRateError
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Combine multiple blocks from the same point into one
|
||||
*
|
||||
* @return
|
||||
*/
|
||||
private fun List<NumassAnalyzerResult>.combineResults(method: AveragingMethod): NumassAnalyzerResult {
|
||||
|
||||
if (this.isEmpty()) {
|
||||
return NumassAnalyzerResult.empty()
|
||||
}
|
||||
|
||||
val totalTime = sumOf { it.length }
|
||||
|
||||
val (countRate, countRateDispersion) = when (method) {
|
||||
AveragingMethod.ARITHMETIC -> Pair(
|
||||
sumOf { it.countRate } / size,
|
||||
sumOf { it.countRateError.pow(2.0) } / size / size
|
||||
)
|
||||
AveragingMethod.WEIGHTED -> Pair(
|
||||
sumOf { it.countRate * it.length } / totalTime,
|
||||
sumOf { (it.countRateError * it.length / totalTime).pow(2.0) }
|
||||
)
|
||||
AveragingMethod.GEOMETRIC -> {
|
||||
val mean = exp(sumOf { ln(it.countRate) } / size)
|
||||
val variance = (mean / size).pow(2.0) * sumOf {
|
||||
(it.countRateError / it.countRate).pow(2.0)
|
||||
}
|
||||
Pair(mean, variance)
|
||||
}
|
||||
}
|
||||
|
||||
return NumassAnalyzerResult {
|
||||
length = totalTime
|
||||
count = sumOf { it.count }
|
||||
this.countRate = countRate
|
||||
this.countRateError = sqrt(countRateDispersion)
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Compute actual t0
|
||||
*/
|
||||
private suspend fun getT0(block: NumassBlock, parameters: TimeAnalyzerParameters): Int {
|
||||
parameters.value?.let { return it }
|
||||
parameters.crFraction?.let { fraction ->
|
||||
val cr = block.events.count().toDouble() / block.getLength().inWholeMilliseconds * 1000
|
||||
if (cr < parameters.crMin) {
|
||||
0
|
||||
} else {
|
||||
max(-1e9 / cr * ln(1.0 - fraction), parameters.min).toInt()
|
||||
}
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
/**
|
||||
* Add a delay after (inverted = false) or before (inverted = true) event to each event
|
||||
*/
|
||||
private suspend fun Flow<NumassEvent>.byPairs(inverted: Boolean = true): Flow<Pair<NumassEvent, Long>> = flow {
|
||||
var prev: NumassEvent?
|
||||
var next: NumassEvent?
|
||||
collect { value ->
|
||||
next = value
|
||||
prev = next
|
||||
if (prev != null && next != null) {
|
||||
val delay = next!!.timeOffset - prev!!.timeOffset
|
||||
if (delay < 0) error("Events are not ordered!")
|
||||
if (inverted) {
|
||||
emit(Pair(next!!, delay))
|
||||
} else {
|
||||
emit(Pair(prev!!, delay))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
}
|
||||
|
||||
@ -1,5 +0,0 @@
|
||||
package ru.inr.mass.data.analysis
|
||||
|
||||
import space.kscience.dataforge.values.Value
|
||||
|
||||
public typealias Values = Map<String, Value>
|
||||
@ -0,0 +1,37 @@
|
||||
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 kotlin.math.max
|
||||
|
||||
public fun <T, R> Flow<T>.zipWithNext(block: (l: T, r: T) -> R): Flow<R> {
|
||||
var current: T? = null
|
||||
return transform { r ->
|
||||
current?.let { l ->
|
||||
emit(block(l, r))
|
||||
}
|
||||
current = r
|
||||
}
|
||||
}
|
||||
|
||||
public fun NumassBlock.timeHistogram(
|
||||
binSize: Double,
|
||||
extractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
|
||||
): UnivariateHistogram = UnivariateHistogram.uniform(binSize) {
|
||||
runBlocking {
|
||||
extractor.extract(this@timeHistogram).zipWithNext { l, r ->
|
||||
if(l.owner == r.owner) {
|
||||
max((r.getTime() - l.getTime()).inWholeMicroseconds,0L)
|
||||
} else {
|
||||
0
|
||||
}
|
||||
}.collect {
|
||||
putValue(it.toDouble())
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -3,14 +3,13 @@ package ru.inr.mass.data.proto
|
||||
import kotlinx.coroutines.flow.toList
|
||||
import kotlinx.coroutines.runBlocking
|
||||
import org.junit.jupiter.api.Test
|
||||
import ru.inr.mass.data.api.NumassPoint
|
||||
import ru.inr.mass.data.api.NumassSet
|
||||
import ru.inr.mass.data.api.ParentBlock
|
||||
import space.kscience.dataforge.context.Context
|
||||
import space.kscience.dataforge.meta.get
|
||||
import space.kscience.dataforge.meta.string
|
||||
import space.kscience.dataforge.values.ListValue
|
||||
import java.nio.file.Path
|
||||
import kotlin.test.Ignore
|
||||
import kotlin.test.assertEquals
|
||||
|
||||
class TestNumassDirectory {
|
||||
@ -31,10 +30,10 @@ class TestNumassDirectory {
|
||||
}
|
||||
|
||||
@Test
|
||||
@Ignore
|
||||
fun testTQDCRead() = runBlocking {
|
||||
val pointPath = Path.of("C:\\Users\\altavir\\Desktop\\p20211122173034(20s).dat")
|
||||
val point: NumassPoint = context.readNumassPointFile(pointPath)!!
|
||||
val pointPath = Path.of("src/test/resources", "testData/tqdc")
|
||||
val set: NumassSet = context.readNumassDirectory(pointPath)
|
||||
val point = set.first { it.voltage == 16000.0 }
|
||||
point.getChannels().forEach { (channel, block) ->
|
||||
println("$channel: $block")
|
||||
if(block is ParentBlock){
|
||||
|
||||
BIN
numass-data-proto/src/test/resources/testData/tqdc/meta
Normal file
BIN
numass-data-proto/src/test/resources/testData/tqdc/meta
Normal file
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
Binary file not shown.
BIN
numass-data-proto/src/test/resources/testData/tqdc/voltage
Normal file
BIN
numass-data-proto/src/test/resources/testData/tqdc/voltage
Normal file
Binary file not shown.
@ -13,11 +13,14 @@ val plotlyVersion: String by rootProject.extra
|
||||
val kmathVersion: String by rootProject.extra
|
||||
|
||||
dependencies {
|
||||
implementation(project(":numass-data-proto"))
|
||||
implementation(project(":numass-model"))
|
||||
implementation(project(":numass-analysis"))
|
||||
implementation(projects.numassDataProto)
|
||||
implementation(projects.numassModel)
|
||||
implementation(projects.numassAnalysis)
|
||||
implementation("space.kscience:dataforge-workspace:$dataforgeVersion")
|
||||
implementation("space.kscience:plotlykt-core:$plotlyVersion")
|
||||
implementation("space.kscience:kmath-histograms:$kmathVersion")
|
||||
implementation("space.kscience:kmath-for-real:$kmathVersion")
|
||||
implementation("space.kscience:plotlykt-jupyter:$plotlyVersion")
|
||||
implementation("space.kscience:kmath-jupyter:$kmathVersion")
|
||||
}
|
||||
|
||||
kscience{
|
||||
jupyterLibrary("ru.inr.mass.notebook.NumassJupyter")
|
||||
}
|
||||
@ -0,0 +1,40 @@
|
||||
package ru.inr.mass.notebook
|
||||
|
||||
|
||||
import org.jetbrains.kotlinx.jupyter.api.HTML
|
||||
import org.jetbrains.kotlinx.jupyter.api.libraries.JupyterIntegration
|
||||
import ru.inr.mass.data.api.NumassBlock
|
||||
import ru.inr.mass.data.api.NumassSet
|
||||
import ru.inr.mass.workspace.Numass
|
||||
import ru.inr.mass.workspace.numassSet
|
||||
import space.kscience.plotly.Plotly
|
||||
|
||||
internal class NumassJupyter : JupyterIntegration() {
|
||||
override fun Builder.onLoaded() {
|
||||
repositories(
|
||||
"https://repo.kotlin.link"
|
||||
)
|
||||
|
||||
import(
|
||||
"ru.inr.mass.models.*",
|
||||
"ru.inr.mass.data.analysis.*",
|
||||
"ru.inr.mass.workspace.*",
|
||||
"ru.inr.mass.data.api.*",
|
||||
"ru.inr.mass.data.proto.*",
|
||||
"space.kscience.dataforge.data.*",
|
||||
"kotlinx.coroutines.*",
|
||||
"kotlinx.coroutines.flow.*",
|
||||
)
|
||||
|
||||
import<Numass>()
|
||||
|
||||
|
||||
render<NumassBlock> {
|
||||
|
||||
}
|
||||
|
||||
render<NumassSet> { numassSet ->
|
||||
HTML(Plotly.numassSet(numassSet).render(), true)
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,6 +1,8 @@
|
||||
package ru.inr.mass.workspace
|
||||
package ru.inr.mass.scripts
|
||||
|
||||
import ru.inr.mass.data.proto.NumassDirectorySet
|
||||
import ru.inr.mass.workspace.Numass.readNumassRepository
|
||||
import ru.inr.mass.workspace.numassSet
|
||||
import space.kscience.dataforge.data.DataTree
|
||||
import space.kscience.dataforge.data.await
|
||||
import space.kscience.dataforge.data.getData
|
||||
@ -11,6 +13,6 @@ suspend fun main() {
|
||||
val repo: DataTree<NumassDirectorySet> = readNumassRepository("D:\\Work\\Numass\\data\\2018_04")
|
||||
//val dataPath = Path.of("D:\\Work\\Numass\\data\\2018_04\\Adiabacity_19\\set_4\\")
|
||||
//val testSet = NUMASS.context.readNumassDirectory(dataPath)
|
||||
val testSet = repo.getData("Adiabacity_19.set_4")?.await() ?: error("Not found")
|
||||
Plotly.numassDirectory(testSet).makeFile()
|
||||
val testSet = repo.getData("Adiabacity_19.set_3")?.await() ?: error("Not found")
|
||||
Plotly.numassSet(testSet).makeFile()
|
||||
}
|
||||
@ -2,7 +2,7 @@ package ru.inr.mass.scripts
|
||||
|
||||
import kotlinx.coroutines.flow.collect
|
||||
import ru.inr.mass.data.proto.NumassDirectorySet
|
||||
import ru.inr.mass.workspace.readNumassRepository
|
||||
import ru.inr.mass.workspace.Numass.readNumassRepository
|
||||
import space.kscience.dataforge.data.DataTree
|
||||
import space.kscience.dataforge.data.filter
|
||||
import space.kscience.dataforge.meta.string
|
||||
|
||||
@ -1,13 +1,10 @@
|
||||
package ru.inr.mass.scripts
|
||||
|
||||
import kotlinx.coroutines.flow.toList
|
||||
import kotlinx.html.code
|
||||
import kotlinx.html.h2
|
||||
import kotlinx.html.p
|
||||
import kotlinx.serialization.json.Json
|
||||
import ru.inr.mass.workspace.readNumassDirectory
|
||||
import space.kscience.dataforge.io.JsonMetaFormat
|
||||
import space.kscience.dataforge.io.toString
|
||||
import ru.inr.mass.workspace.Numass.readNumassDirectory
|
||||
import space.kscience.dataforge.meta.MetaSerializer
|
||||
import space.kscience.plotly.*
|
||||
|
||||
@ -33,18 +30,18 @@ suspend fun main() {
|
||||
h2 { +"Analysis" }
|
||||
plot {
|
||||
histogram {
|
||||
name="max"
|
||||
x.numbers = frames.map { frame -> frame.signal.maxOf { it.toUShort().toInt() - Short.MAX_VALUE } }
|
||||
name = "max"
|
||||
x.numbers = frames.map { frame -> frame.signal.maxOf { it.toUShort().toInt() - Short.MAX_VALUE } }
|
||||
}
|
||||
|
||||
histogram {
|
||||
name="max-min"
|
||||
xbins{
|
||||
name = "max-min"
|
||||
xbins {
|
||||
size = 2.0
|
||||
}
|
||||
x.numbers = frames.map { frame ->
|
||||
frame.signal.maxOf { it.toUShort().toInt() - Short.MAX_VALUE } -
|
||||
frame.signal.minOf { it.toUShort().toInt() - Short.MAX_VALUE }
|
||||
frame.signal.maxOf { it.toUShort().toInt() - Short.MAX_VALUE } -
|
||||
frame.signal.minOf { it.toUShort().toInt() - Short.MAX_VALUE }
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -0,0 +1,47 @@
|
||||
package ru.inr.mass.workspace
|
||||
|
||||
import kotlinx.coroutines.Dispatchers
|
||||
import kotlinx.coroutines.runBlocking
|
||||
import kotlinx.coroutines.withContext
|
||||
import ru.inr.mass.data.api.NumassSet
|
||||
import ru.inr.mass.data.proto.NumassDirectorySet
|
||||
import ru.inr.mass.data.proto.readNumassDirectory
|
||||
import space.kscience.dataforge.data.*
|
||||
import space.kscience.dataforge.names.Name
|
||||
import space.kscience.dataforge.names.NameToken
|
||||
import java.nio.file.Files
|
||||
import java.nio.file.Path
|
||||
import kotlin.io.path.ExperimentalPathApi
|
||||
import kotlin.io.path.exists
|
||||
import kotlin.io.path.isDirectory
|
||||
import kotlin.io.path.relativeTo
|
||||
import kotlin.streams.toList
|
||||
|
||||
object Numass {
|
||||
fun readNumassDirectory(path: String): NumassDirectorySet = NUMASS.context.readNumassDirectory(path)
|
||||
|
||||
@OptIn(ExperimentalPathApi::class)
|
||||
fun readNumassRepository(path: Path): DataTree<NumassDirectorySet> = runBlocking {
|
||||
ActiveDataTree {
|
||||
@Suppress("BlockingMethodInNonBlockingContext")
|
||||
withContext(Dispatchers.IO) {
|
||||
Files.walk(path).filter {
|
||||
it.isDirectory() && it.resolve("meta").exists()
|
||||
}.toList().forEach { childPath ->
|
||||
val name = Name(childPath.relativeTo(path).map { segment ->
|
||||
NameToken(segment.fileName.toString())
|
||||
})
|
||||
val value = NUMASS.context.readNumassDirectory(childPath)
|
||||
static(name, value, value.meta)
|
||||
}
|
||||
}
|
||||
//TODO add file watcher
|
||||
}
|
||||
}
|
||||
|
||||
fun readNumassRepository(path: String): DataTree<NumassDirectorySet> = readNumassRepository(Path.of(path))
|
||||
}
|
||||
|
||||
operator fun DataSet<NumassSet>.get(name: String): NumassSet? = runBlocking {
|
||||
getData(Name.parse(name))?.await()
|
||||
}
|
||||
@ -1,57 +0,0 @@
|
||||
@file:Suppress("EXPERIMENTAL_API_USAGE")
|
||||
package ru.inr.mass.workspace
|
||||
|
||||
import kotlinx.coroutines.flow.collect
|
||||
import kotlinx.coroutines.runBlocking
|
||||
import ru.inr.mass.data.api.NumassPoint
|
||||
import space.kscience.dataforge.context.logger
|
||||
import space.kscience.dataforge.context.warn
|
||||
import space.kscience.kmath.histogram.UnivariateHistogram
|
||||
import space.kscience.kmath.histogram.center
|
||||
import space.kscience.kmath.histogram.put
|
||||
import space.kscience.kmath.misc.UnstableKMathAPI
|
||||
import space.kscience.kmath.structures.DoubleBuffer
|
||||
import space.kscience.kmath.structures.asBuffer
|
||||
|
||||
|
||||
/**
|
||||
* Build an amplitude spectrum with bin of 1.0 counted from 0.0. Some bins could be missing
|
||||
*/
|
||||
fun NumassPoint.spectrum(): UnivariateHistogram = UnivariateHistogram.uniform(1.0) {
|
||||
runBlocking {
|
||||
events.collect {
|
||||
putValue(it.amplitude.toDouble())
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
operator fun UnivariateHistogram.component1(): DoubleBuffer = bins.map { it.domain.center }.toDoubleArray().asBuffer()
|
||||
operator fun UnivariateHistogram.component2(): DoubleBuffer = bins.map { it.value }.toDoubleArray().asBuffer()
|
||||
|
||||
fun Collection<NumassPoint>.spectrum(): UnivariateHistogram {
|
||||
if (distinctBy { it.voltage }.size != 1) {
|
||||
NUMASS.logger.warn { "Spectrum is generated from points with different hv value: $this" }
|
||||
}
|
||||
|
||||
return UnivariateHistogram.uniform(1.0) {
|
||||
runBlocking {
|
||||
this@spectrum.forEach { point ->
|
||||
point.events.collect { put(it.amplitude.toDouble()) }
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Re-shape the spectrum with the increased bin size and range. Throws a error if new bin is smaller than before.
|
||||
*/
|
||||
@OptIn(UnstableKMathAPI::class)
|
||||
fun UnivariateHistogram.reShape(
|
||||
binSize: Int,
|
||||
channelRange: IntRange,
|
||||
): UnivariateHistogram = UnivariateHistogram.uniform(binSize.toDouble()) {
|
||||
this@reShape.bins.filter { it.domain.center.toInt() in channelRange }.forEach { bin ->
|
||||
if (bin.domain.volume() > binSize.toDouble()) error("Can't reShape the spectrum with increased binning")
|
||||
putValue(bin.domain.center, bin.value)
|
||||
}
|
||||
}
|
||||
@ -1,39 +0,0 @@
|
||||
package ru.inr.mass.workspace
|
||||
|
||||
import kotlinx.coroutines.Dispatchers
|
||||
import kotlinx.coroutines.withContext
|
||||
import ru.inr.mass.data.proto.NumassDirectorySet
|
||||
import ru.inr.mass.data.proto.readNumassDirectory
|
||||
import space.kscience.dataforge.data.ActiveDataTree
|
||||
import space.kscience.dataforge.data.DataTree
|
||||
import space.kscience.dataforge.data.static
|
||||
import space.kscience.dataforge.names.Name
|
||||
import space.kscience.dataforge.names.NameToken
|
||||
import java.nio.file.Files
|
||||
import java.nio.file.Path
|
||||
import kotlin.io.path.ExperimentalPathApi
|
||||
import kotlin.io.path.exists
|
||||
import kotlin.io.path.isDirectory
|
||||
import kotlin.io.path.relativeTo
|
||||
import kotlin.streams.toList
|
||||
|
||||
fun readNumassDirectory(path: String): NumassDirectorySet = NUMASS.context.readNumassDirectory(path)
|
||||
|
||||
@OptIn(ExperimentalPathApi::class)
|
||||
suspend fun readNumassRepository(path: Path): DataTree<NumassDirectorySet> = ActiveDataTree {
|
||||
@Suppress("BlockingMethodInNonBlockingContext")
|
||||
withContext(Dispatchers.IO) {
|
||||
Files.walk(path).filter {
|
||||
it.isDirectory() && it.resolve("meta").exists()
|
||||
}.toList().forEach { childPath ->
|
||||
val name = Name(childPath.relativeTo(path).map { segment ->
|
||||
NameToken(segment.fileName.toString())
|
||||
})
|
||||
val value = NUMASS.context.readNumassDirectory(childPath)
|
||||
static(name, value, value.meta)
|
||||
}
|
||||
}
|
||||
//TODO add file watcher
|
||||
}
|
||||
|
||||
suspend fun readNumassRepository(path: String): DataTree<NumassDirectorySet> = readNumassRepository(Path.of(path))
|
||||
@ -1,8 +1,13 @@
|
||||
package ru.inr.mass.workspace
|
||||
|
||||
import kotlinx.coroutines.runBlocking
|
||||
import kotlinx.html.h1
|
||||
import kotlinx.html.h2
|
||||
import ru.inr.mass.data.api.NumassPoint
|
||||
import ru.inr.mass.data.analysis.NumassAmplitudeSpectrum
|
||||
import ru.inr.mass.data.analysis.NumassEventExtractor
|
||||
import ru.inr.mass.data.analysis.amplitudeSpectrum
|
||||
import ru.inr.mass.data.analysis.timeHistogram
|
||||
import ru.inr.mass.data.api.NumassSet
|
||||
import ru.inr.mass.data.proto.HVData
|
||||
import ru.inr.mass.data.proto.NumassDirectorySet
|
||||
import space.kscience.dataforge.values.asValue
|
||||
@ -14,29 +19,29 @@ import space.kscience.kmath.operations.asIterable
|
||||
import space.kscience.kmath.structures.Buffer
|
||||
import space.kscience.kmath.structures.DoubleBuffer
|
||||
import space.kscience.plotly.*
|
||||
import space.kscience.plotly.models.Scatter
|
||||
import space.kscience.plotly.models.Trace
|
||||
import space.kscience.plotly.models.TraceValues
|
||||
import space.kscience.plotly.models.*
|
||||
|
||||
/**
|
||||
* Plot a kmath histogram
|
||||
*/
|
||||
@OptIn(UnstableKMathAPI::class)
|
||||
fun Plot.histogram(histogram: UnivariateHistogram, block: Scatter.() -> Unit): Trace = scatter {
|
||||
fun Plot.histogram(histogram: UnivariateHistogram, block: Scatter.() -> Unit = {}): Trace = scatter {
|
||||
x.numbers = histogram.bins.map { it.domain.center }
|
||||
y.numbers = histogram.bins.map { it.value }
|
||||
line.shape = LineShape.hv
|
||||
block()
|
||||
}
|
||||
|
||||
fun Plot.amplitudeSpectrum(
|
||||
point: NumassPoint,
|
||||
binSize: Int = 20,
|
||||
range: IntRange = 0..2000,
|
||||
name: String = point.toString(),
|
||||
fun Plot.histogram(
|
||||
spectrum: NumassAmplitudeSpectrum,
|
||||
binSize: UInt = 20U,
|
||||
block: Scatter.() -> Unit = {},
|
||||
): Trace = scatter {
|
||||
histogram(point.spectrum().reShape(binSize, range)) {
|
||||
this.name = name
|
||||
}
|
||||
val binned = spectrum.binned(binSize)
|
||||
x.numbers = binned.keys.map { (it.first + it.last).toDouble() / 2.0 }
|
||||
y.numbers = binned.values
|
||||
line.shape = LineShape.hv
|
||||
block()
|
||||
}
|
||||
|
||||
/**
|
||||
@ -47,26 +52,44 @@ fun Plot.hvData(data: HVData): Trace = scatter {
|
||||
y.numbers = data.map { it.value }
|
||||
}
|
||||
|
||||
fun Plotly.numassDirectory(set: NumassDirectorySet, binSize: Int = 20, range: IntRange = 0..2000): PlotlyPage =
|
||||
fun Plotly.numassSet(
|
||||
set: NumassSet,
|
||||
amplitudeBinSize: UInt = 20U,
|
||||
eventExtractor: NumassEventExtractor = NumassEventExtractor.EVENTS_ONLY,
|
||||
): PlotlyPage =
|
||||
Plotly.page {
|
||||
h1 {
|
||||
+"Numass point set ${set.path}"
|
||||
+"Numass point set ${ShapeType.path}"
|
||||
}
|
||||
h2 {
|
||||
+"Amplitude spectrum"
|
||||
}
|
||||
plot {
|
||||
set.points.sortedBy { it.index }.forEach {
|
||||
amplitudeSpectrum(it, binSize, range)
|
||||
runBlocking {
|
||||
set.points.sortedBy { it.index }.forEach {
|
||||
histogram(it.amplitudeSpectrum(eventExtractor), amplitudeBinSize)
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
set.getHvData()?.let { entries ->
|
||||
h2 {
|
||||
+"HV"
|
||||
h2 {
|
||||
+"Time spectra"
|
||||
}
|
||||
plot {
|
||||
set.points.sortedBy { it.index }.forEach {
|
||||
histogram(it.timeHistogram(1e3))
|
||||
}
|
||||
plot {
|
||||
hvData(entries)
|
||||
layout.yaxis.type = AxisType.log
|
||||
|
||||
}
|
||||
if (set is NumassDirectorySet) {
|
||||
set.getHvData()?.let { entries ->
|
||||
h2 {
|
||||
+"HV"
|
||||
}
|
||||
plot {
|
||||
hvData(entries)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user