Minor fix to ColumnTable
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da77fbdeaf
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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 inr.numass.scripts
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import hep.dataforge.buildContext
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import hep.dataforge.meta.buildMeta
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import hep.dataforge.nullable
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import hep.dataforge.plots.PlotGroup
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import hep.dataforge.plots.data.DataPlot
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import hep.dataforge.tables.ColumnTable
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import inr.numass.NumassPlugin
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import inr.numass.data.analyzers.*
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import inr.numass.data.analyzers.NumassAnalyzer.Companion.AMPLITUDE_ADAPTER
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import inr.numass.data.api.NumassSet
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import inr.numass.data.storage.NumassDirectory
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import inr.numass.displayChart
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fun main(args: Array<String>) {
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val context = buildContext("NUMASS", NumassPlugin::class.java) {
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rootDir = "D:\\Work\\Numass\\sterile\\2017_11"
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dataDir = "D:\\Work\\Numass\\data\\2017_11"
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}
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//val rootDir = File("D:\\Work\\Numass\\data\\2017_05\\Fill_2")
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val storage = NumassDirectory.read(context, "Fill_3b")!!
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val sets = listOf("set_2", "set_17")
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val analyzer = SmartAnalyzer()
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val meta = buildMeta {
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// "t0" to 30e3
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// "inverted" to true
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"window.lo" to 400
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"window.up" to 1600
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}
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val t0 = 15e3
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val metaForChain = meta.builder.apply {
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setValue("t0", t0)
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setValue("inverted", false)
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}
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val metaForChainInverted = metaForChain.builder.setValue("inverted", true)
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val hv = 14000.0
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val frame = displayChart("integral[$hv]").apply {
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this.plots.setType<DataPlot>()
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this.plots.configureValue("showLine", true)
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}
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val normalizedFrame = displayChart("normalized[$hv]").apply {
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this.plots.setType<DataPlot>()
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this.plots.configureValue("showLine", true)
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}
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sets.forEach { setName ->
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val set = storage.provide(setName, NumassSet::class.java).nullable ?: error("Set does not exist")
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val point = set.optPoint(hv).get()
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val group = PlotGroup(setName)
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frame.add(group)
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val rawSpectrum = analyzer.getAmplitudeSpectrum(point, meta).withBinning(20)
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group.add(DataPlot.plot("raw", rawSpectrum, AMPLITUDE_ADAPTER))
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val rawNorm = rawSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).maxBy { it.double }!!.double
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val normalizedSpectrum = ColumnTable.copy(rawSpectrum)
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.replaceColumn(NumassAnalyzer.COUNT_RATE_KEY) { it.getDouble(NumassAnalyzer.COUNT_RATE_KEY) / rawNorm }
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normalizedFrame.add(DataPlot.plot("${setName}_raw", normalizedSpectrum, AMPLITUDE_ADAPTER))
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println("[$setName] Raw spectrum integral: ${rawSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).sumByDouble { it.double }}")
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group.add(DataPlot.plot("filtered", analyzer.getAmplitudeSpectrum(point, metaForChain).withBinning(20), AMPLITUDE_ADAPTER))
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val filteredSpectrum = analyzer.getAmplitudeSpectrum(point, metaForChainInverted).withBinning(20)
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group.add(DataPlot.plot("invertedFilter", filteredSpectrum, AMPLITUDE_ADAPTER))
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val filteredNorm = filteredSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).maxBy { it.double }!!.double
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val normalizedFilteredSpectrum = ColumnTable.copy(filteredSpectrum)
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.replaceColumn(NumassAnalyzer.COUNT_RATE_KEY) { it.getDouble(NumassAnalyzer.COUNT_RATE_KEY) / filteredNorm }
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normalizedFrame.add(DataPlot.plot(setName, normalizedFilteredSpectrum, AMPLITUDE_ADAPTER))
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val sequence = TimeAnalyzer()
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.getEventsWithDelay(point, metaForChainInverted)
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.filter { pair -> pair.second <= t0 }
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.map { it.first }
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val pileupSpectrum = getAmplitudeSpectrum(sequence, point.length.toMillis().toDouble() / 1000.0).withBinning(20)
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group.add(DataPlot.plot("pileup", pileupSpectrum, AMPLITUDE_ADAPTER))
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println("[$setName] Pileup spectrum integral: ${pileupSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).sumByDouble { it.double }}")
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}
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}
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@ -0,0 +1,117 @@
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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 inr.numass.scripts
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import hep.dataforge.buildContext
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import hep.dataforge.meta.buildMeta
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import hep.dataforge.nullable
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import hep.dataforge.plots.PlotGroup
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import hep.dataforge.plots.data.DataPlot
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import hep.dataforge.tables.ColumnTable
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import inr.numass.NumassPlugin
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import inr.numass.data.analyzers.*
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import inr.numass.data.analyzers.NumassAnalyzer.Companion.AMPLITUDE_ADAPTER
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import inr.numass.data.api.NumassSet
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import inr.numass.data.storage.NumassDirectory
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import inr.numass.displayChart
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fun main(args: Array<String>) {
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val context = buildContext("NUMASS", NumassPlugin::class.java) {
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rootDir = "D:\\Work\\Numass\\sterile\\2017_11"
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dataDir = "D:\\Work\\Numass\\data\\2017_11"
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}
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//val rootDir = File("D:\\Work\\Numass\\data\\2017_05\\Fill_2")
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val storage = NumassDirectory.read(context, "Adiabacity_19")!!
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val sets = listOf("set_2")
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val analyzer = SmartAnalyzer()
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val meta = buildMeta {
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// "t0" to 30e3
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// "inverted" to true
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"window.lo" to 400
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"window.up" to 2600
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}
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val t0 = 15e3
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val metaForChain = meta.builder.apply {
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setValue("t0", t0)
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setValue("inverted", false)
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}
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val metaForChainInverted = metaForChain.builder.setValue("inverted", true)
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val hv = 18000.0
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val frame = displayChart("integral[$hv]").apply {
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this.plots.setType<DataPlot>()
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this.plots.configureValue("showLine", true)
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}
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val normalizedFrame = displayChart("normalized[$hv]").apply {
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this.plots.setType<DataPlot>()
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this.plots.configureValue("showLine", true)
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}
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sets.forEach { setName ->
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val set = storage.provide(setName, NumassSet::class.java).nullable ?: error("Set does not exist")
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val point = set.optPoint(hv).get()
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val group = PlotGroup(setName)
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frame.add(group)
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val rawSpectrum = analyzer.getAmplitudeSpectrum(point, meta).withBinning(20)
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group.add(DataPlot.plot("raw", rawSpectrum, AMPLITUDE_ADAPTER))
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val rawNorm = rawSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).maxBy { it.double }!!.double
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val normalizedSpectrum = ColumnTable.copy(rawSpectrum)
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.replaceColumn(NumassAnalyzer.COUNT_RATE_KEY) { it.getDouble(NumassAnalyzer.COUNT_RATE_KEY) / rawNorm }
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normalizedFrame.add(DataPlot.plot("${setName}_raw", normalizedSpectrum, AMPLITUDE_ADAPTER))
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println("[$setName] Raw spectrum integral: ${rawSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).sumByDouble { it.double }}")
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group.add(DataPlot.plot("filtered", analyzer.getAmplitudeSpectrum(point, metaForChain).withBinning(20), AMPLITUDE_ADAPTER))
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val filteredSpectrum = analyzer.getAmplitudeSpectrum(point, metaForChainInverted).withBinning(20)
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group.add(DataPlot.plot("invertedFilter", filteredSpectrum, AMPLITUDE_ADAPTER))
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val filteredNorm = filteredSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).maxBy { it.double }!!.double
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val normalizedFilteredSpectrum = ColumnTable.copy(filteredSpectrum)
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.replaceColumn(NumassAnalyzer.COUNT_RATE_KEY) { it.getDouble(NumassAnalyzer.COUNT_RATE_KEY) / filteredNorm }
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normalizedFrame.add(DataPlot.plot(setName, normalizedFilteredSpectrum, AMPLITUDE_ADAPTER))
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val sequence = TimeAnalyzer()
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.getEventsWithDelay(point, metaForChainInverted)
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.filter { pair -> pair.second <= t0 }
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.map { it.first }
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val pileupSpectrum = getAmplitudeSpectrum(sequence, point.length.toMillis().toDouble() / 1000.0).withBinning(20)
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group.add(DataPlot.plot("pileup", pileupSpectrum, AMPLITUDE_ADAPTER))
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println("[$setName] Pileup spectrum integral: ${pileupSpectrum.getColumn(NumassAnalyzer.COUNT_RATE_KEY).sumByDouble { it.double }}")
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}
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}
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