A lot of minor fixes. Moving some code to kotlin

numass-core/src/main/java/inr/numass/data/storage/ClassicNumassPoint.java

@@ -6,6 +6,7 @@ import inr.numass.data.api.NumassBlock;
 import inr.numass.data.api.NumassEvent;
 import inr.numass.data.api.NumassFrame;
 import inr.numass.data.api.NumassPoint;
+import inr.numass.data.legacy.NumassFileEnvelope;
 import org.jetbrains.annotations.NotNull;
 import org.slf4j.LoggerFactory;
 
@@ -13,6 +14,7 @@ import java.io.IOException;
 import java.nio.ByteBuffer;
 import java.nio.ByteOrder;
 import java.nio.channels.ReadableByteChannel;
+import java.nio.file.Path;
 import java.time.Duration;
 import java.time.Instant;
 import java.util.Iterator;
@@ -23,6 +25,10 @@ import java.util.stream.StreamSupport;
  * Created by darksnake on 08.07.2017.
  */
 public class ClassicNumassPoint implements NumassPoint {
+    public static ClassicNumassPoint readFile(Path path) {
+        return new ClassicNumassPoint(NumassFileEnvelope.open(path, true));
+    }
+
     private final Envelope envelope;
 
     public ClassicNumassPoint(Envelope envelope) {

numass-core/src/main/java/inr/numass/data/storage/ProtoNumassPoint.java

@@ -81,7 +81,7 @@ public class ProtoNumassPoint implements NumassPoint {
 
         @Override
         public Duration getLength() {
-            return Duration.ofNanos((long) (getMeta().getInt("b_size") / getMeta().getInt("sample_freq") * 1e9));
+            return Duration.ofNanos((long) (getMeta().getDouble("params.b_size") / getMeta().getDouble("params.sample_freq") * 1e9));
         }
 
         @Override

numass-main/src/main/kotlin/inr/numass/data/ChainGenerator.kt

@@ -8,6 +8,7 @@ import org.apache.commons.math3.random.RandomGenerator
 import java.time.Duration
 import java.time.Instant
 import java.util.*
+import kotlin.collections.ArrayList
 
 interface ChainGenerator {
 
@@ -30,27 +31,84 @@ interface ChainGenerator {
     }
 }
 
+
+private fun RandomGenerator.nextExp(mean: Double): Double {
+    return -mean * Math.log(1 - nextDouble())
+}
+
+private fun RandomGenerator.nextDeltaTime(cr: Double): Long {
+    return (nextExp(1.0 / cr) * 1e9).toLong()
+}
+
 class SimpleChainGenerator(
         val cr: Double,
         private val rnd: RandomGenerator = JDKRandomGenerator(),
-        private val amp: (Long) -> Short = { 1 }
+        private val amp: RandomGenerator.(NumassEvent?, Long) -> Short = { _, _ -> ((nextDouble() + 2.0) * 100).toShort() }
 ) : ChainGenerator {
 
     override fun next(event: NumassEvent?): NumassEvent {
         return if (event == null) {
-            NumassEvent(amp(0), Instant.EPOCH, 0)
+            NumassEvent(rnd.amp(null, 0), Instant.EPOCH, 0)
         } else {
-            val deltaT = generateDeltaTime()
+            val deltaT = rnd.nextDeltaTime(cr)
-            NumassEvent(amp(deltaT), event.blockTime, event.timeOffset + deltaT)
+            NumassEvent(rnd.amp(event, deltaT), event.blockTime, event.timeOffset + deltaT)
+        }
     }
 }
 
-    private fun nextExpDecay(mean: Double): Double {
+class BunchGenerator(
-        return -mean * Math.log(1 - rnd.nextDouble())
+        private val cr: Double,
+        private val bunchRate: Double,
+        private val bunchLength: RandomGenerator.() -> Long,
+        private val rnd: RandomGenerator = JDKRandomGenerator(),
+        private val amp: RandomGenerator.(NumassEvent?, Long) -> Short = { _, _ -> ((nextDouble() + 2.0) * 100).toShort() }
+) : ChainGenerator {
+
+    private val internalGenerator = SimpleChainGenerator(cr, rnd, amp)
+
+    var bunchStart: Long = 0
+    var bunchEnd: Long = 0
+
+    override fun next(event: NumassEvent?): NumassEvent {
+        if (event?.timeOffset ?: 0 >= bunchEnd) {
+            bunchStart = bunchEnd + rnd.nextExp(bunchRate).toLong()
+            bunchEnd = bunchStart + rnd.bunchLength()
+            return NumassEvent(rnd.amp(null, 0), Instant.EPOCH, bunchStart)
+        } else {
+            return internalGenerator.next(event)
+        }
     }
 
-    private fun generateDeltaTime(): Long {
+    override fun generateBlock(start: Instant, length: Long, filter: (NumassEvent, NumassEvent) -> Boolean): NumassBlock {
-        return (nextExpDecay(1.0 / cr) * 1e9).toLong()
+        bunchStart = 0
+        bunchEnd = 0
+        return super.generateBlock(start, length, filter)
+    }
 }
 
+
+class MergingGenerator(private  vararg val generators: ChainGenerator) : ChainGenerator {
+
+    private val waiting: TreeSet<Pair<ChainGenerator, NumassEvent>> = TreeSet(Comparator.comparing<Pair<ChainGenerator, NumassEvent>, Long> { it.second.timeOffset })
+
+    init {
+        generators.forEach { generator ->
+            waiting.add(Pair(generator, generator.next(null)))
         }
+    }
+
+    override fun next(event: NumassEvent?): NumassEvent {
+        val pair = waiting.first()
+        waiting.remove(pair)
+        waiting.add(Pair(pair.first, pair.first.next(pair.second)))
+        return pair.second
+    }
+
+    override fun generateBlock(start: Instant, length: Long, filter: (NumassEvent, NumassEvent) -> Boolean): NumassBlock {
+        generators.forEach { generator ->
+            waiting.add(Pair(generator, generator.next(null)))
+        }
+        return super.generateBlock(start, length, filter)
+    }
+}
+

numass-main/src/main/kotlin/inr/numass/scripts/Bunches.kt

@@ -0,0 +1,46 @@
+package inr.numass.scripts
+
+import hep.dataforge.fx.plots.PlotManager
+import hep.dataforge.kodex.buildContext
+import hep.dataforge.kodex.buildMeta
+import inr.numass.NumassPlugin
+import inr.numass.data.BunchGenerator
+import inr.numass.data.MergingGenerator
+import inr.numass.data.SimpleChainGenerator
+import inr.numass.data.analyzers.NumassAnalyzer
+import inr.numass.data.analyzers.SmartAnalyzer
+import inr.numass.data.api.SimpleNumassPoint
+import java.time.Instant
+
+fun main(args: Array<String>) {
+
+    val context = buildContext("NUMASS", NumassPlugin::class.java, PlotManager::class.java)
+
+    val cr = 10.0
+    val length = 30e9.toLong()
+    val num = 50;
+    val dt = 6.5
+
+    val regularGenerator = SimpleChainGenerator(cr)
+    val bunchGenerator = BunchGenerator(40.0, 0.1, { 2e9.toLong() })
+
+    val generator = MergingGenerator(regularGenerator, bunchGenerator)
+
+    val blocks = (1..num).map {
+        generator.generateBlock(Instant.now().plusNanos(it * length), length)
+    }
+
+    val point = SimpleNumassPoint(10000.0, blocks)
+
+    val meta = buildMeta {
+        "t0.crFraction" to 0.1
+    }
+
+    println("actual count rate: ${point.events.count() / point.length.seconds}")
+
+    val res = SmartAnalyzer().analyze(point,meta)
+            .getDouble(NumassAnalyzer.COUNT_RATE_KEY)
+
+    println("estimated count rate: ${res}")
+
+}

numass-main/src/main/kotlin/inr/numass/scripts/DifferentialSpectrum.kt

@@ -16,77 +16,72 @@
 
 package inr.numass.scripts
 
+import hep.dataforge.description.DescriptorUtils
 import hep.dataforge.fx.plots.PlotManager
 import hep.dataforge.kodex.buildContext
 import hep.dataforge.kodex.buildMeta
 import hep.dataforge.kodex.replaceColumn
 import hep.dataforge.plots.data.DataPlot
-import hep.dataforge.tables.Table
 import inr.numass.NumassPlugin
 import inr.numass.data.NumassDataUtils
 import inr.numass.data.analyzers.NumassAnalyzer
-import inr.numass.data.analyzers.TimeAnalyzer
+import inr.numass.data.analyzers.SmartAnalyzer
-import inr.numass.data.analyzers.getAmplitudeSpectrum
-import inr.numass.data.api.NumassPoint
 import inr.numass.data.api.NumassSet
 import inr.numass.data.storage.NumassStorageFactory
 
-
 fun main(args: Array<String>) {
 
     val context = buildContext("NUMASS", NumassPlugin::class.java, PlotManager::class.java) {
-        rootDir = "D:\\Work\\Numass\\sterile\\2017_05"
+        rootDir = "D:\\Work\\Numass\\sterile\\2017_11"
-        dataDir = "D:\\Work\\Numass\\data\\2017_05"
+        dataDir = "D:\\Work\\Numass\\data\\2017_11"
     }
     //val rootDir = File("D:\\Work\\Numass\\data\\2017_05\\Fill_2")
 
     val storage = NumassStorageFactory.buildLocal(context, "Fill_2", true, false);
 
-    val sets = (2..14).map { "set_$it" }
+    val sets = (1..24).map { "set_$it" }
 
     val loaders = sets.mapNotNull { set ->
         storage.provide("loader::$set", NumassSet::class.java).orElse(null)
     }
 
+    val analyzer = SmartAnalyzer()
+
     val all = NumassDataUtils.join("sum", loaders)
 
-    val t0 = 20e3
 
     val meta = buildMeta {
+        "t0" to 30e3
+        "inverted" to true
         "window.lo" to 400
-        "window.up" to 1800
+        "window.up" to 1600
-        "t0" to t0
-    }
-
-    val filter: (NumassPoint) -> Table = { point ->
-        val analyzer = TimeAnalyzer()
-        val sequence = analyzer.zipEvents(point, meta).filter { it.second.timeOffset - it.first.timeOffset > t0 }.map { it.second }
-        //val sequence = analyzer.getEvents(point,meta).asSequence()
-        getAmplitudeSpectrum(sequence, point.length.toMillis().toDouble() / 1000.0, meta)
     }
 
     val plots = context.getFeature(PlotManager::class.java)
 
-    val frame = plots.getPlotFrame("differential")
+    val frame = plots.getPlotFrame("differential").apply {
+        this.plots.descriptor = DescriptorUtils.buildDescriptor(DataPlot::class)
+        this.plots.configureValue("showLine", true)
+    }
 
     val integralFrame = plots.getPlotFrame("integral")
 
-    for (hv in arrayOf(14000.0, 14500.0, 15000.0, 15500.0)) {
+    for (hv in arrayOf(14000.0, 14500.0, 15000.0, 15500.0, 16050.0)) {
-        val basePoint = all.optPoint(hv).get()
+        val point1 = all.optPoint(hv).get()
 
-        val subPoint = all.optPoint(hv + 200.0).get()
+        val point0 = all.optPoint(hv + 200.0).get()
 
         with(NumassAnalyzer) {
 
-            val baseSpectrum = filter(basePoint).withBinning(50)
+            val spectrum1 = analyzer.getAmplitudeSpectrum(point1, meta).withBinning(50)
 
-            val subSpectrum = filter(subPoint).withBinning(50)
+            val spectrum0 = analyzer.getAmplitudeSpectrum(point0, meta).withBinning(50)
 
-            val res = subtractAmplitudeSpectrum(baseSpectrum, subSpectrum)
+            val res = subtractAmplitudeSpectrum(spectrum1, spectrum0)
 
             val norm = res.getColumn(COUNT_RATE_KEY).stream().mapToDouble { it.doubleValue() }.sum()
 
-            integralFrame.add(DataPlot.plot("point_$hv", AMPLITUDE_ADAPTER, baseSpectrum))
+            integralFrame.add(DataPlot.plot("point_$hv", AMPLITUDE_ADAPTER, spectrum0))
 
             frame.add(DataPlot.plot("point_$hv", AMPLITUDE_ADAPTER, res.replaceColumn(COUNT_RATE_KEY) { getDouble(COUNT_RATE_KEY) / norm }))
         }

numass-main/src/main/kotlin/inr/numass/scripts/InversedChain.kt

@@ -16,108 +16,66 @@
 
 package inr.numass.scripts
 
+import hep.dataforge.description.DescriptorUtils
 import hep.dataforge.fx.plots.PlotManager
 import hep.dataforge.kodex.buildContext
 import hep.dataforge.kodex.buildMeta
-import hep.dataforge.kodex.replaceColumn
-import hep.dataforge.meta.Meta
-import hep.dataforge.plots.PlotPlugin
 import hep.dataforge.plots.data.DataPlot
 import inr.numass.NumassPlugin
 import inr.numass.data.NumassDataUtils
-import inr.numass.data.analyzers.NumassAnalyzer
+import inr.numass.data.analyzers.NumassAnalyzer.Companion.AMPLITUDE_ADAPTER
-import inr.numass.data.analyzers.TimeAnalyzer
+import inr.numass.data.analyzers.NumassAnalyzer.Companion.withBinning
-import inr.numass.data.analyzers.getAmplitudeSpectrum
+import inr.numass.data.analyzers.SmartAnalyzer
 import inr.numass.data.api.NumassSet
 import inr.numass.data.storage.NumassStorageFactory
-import kotlin.streams.asSequence
 
 
 fun main(args: Array<String>) {
 
     val context = buildContext("NUMASS", NumassPlugin::class.java, PlotManager::class.java) {
-        rootDir = "D:\\Work\\Numass\\sterile2017_05"
+        rootDir = "D:\\Work\\Numass\\sterile\\2017_11"
+        dataDir = "D:\\Work\\Numass\\data\\2017_11"
     }
     //val rootDir = File("D:\\Work\\Numass\\data\\2017_05\\Fill_2")
 
-    val storage = NumassStorageFactory.buildLocal(context, "D:\\Work\\Numass\\data\\2017_05\\Fill_2", true, false);
+    val storage = NumassStorageFactory.buildLocal(context, "Fill_2", true, false);
 
-    val sets = (2..14).map { "set_$it" }
+    val sets = (10..24).map { "set_$it" }
 
     val loaders = sets.mapNotNull { set ->
         storage.provide("loader::$set", NumassSet::class.java).orElse(null)
     }
 
-    val all = NumassDataUtils.join("sum", loaders)
+    val set = NumassDataUtils.join("sum", loaders)
-
-    val point = all.optPoint(14000.0).get()
-
-    val t0 = 20e3.toLong()
-
-    val analyzer = TimeAnalyzer()
-
-    val seconds = point.length.toMillis().toDouble() / 1000.0
-
-    val binning = 20
 
 
-    val plots = context.getFeature(PlotPlugin::class.java);
+    val analyzer = SmartAnalyzer()
 
     val meta = buildMeta {
-        node("window"){
+        //        "t0" to 30e3
-            "lo" to 300
+//        "inverted" to true
-            "up" to 2600
+        "window.lo" to 400
-        }
+        "window.up" to 1600
     }
 
-    with(NumassAnalyzer) {
+    val metaForChain = meta.builder.setValue("t0", 15e3)
-        val events = getAmplitudeSpectrum(analyzer.getEvents(point).asSequence(), seconds, meta)
-                .withBinning(binning)
 
-        val eventsNorming = events.getColumn(COUNT_RATE_KEY).stream().mapToDouble{it.doubleValue()}.sum()
+    val metaForChainInverted = metaForChain.builder.setValue("inverted", true)
-
-        println("The norming factor for unfiltered count rate is $eventsNorming")
-
-        val filtered = getAmplitudeSpectrum(
-                analyzer.zipEvents(point, Meta.empty()).filter { it.second.timeOffset - it.first.timeOffset > t0 }.map { it.second },
-                seconds,
-                meta
-        ).withBinning(binning)
-
-        val filteredNorming = filtered.getColumn(COUNT_RATE_KEY).stream().mapToDouble{it.doubleValue()}.sum()
-
-        println("The norming factor for filtered count rate is $filteredNorming")
-
-        val defaultFiltered = getAmplitudeSpectrum(
-                analyzer.getEvents(point, buildMeta {"t0" to t0}).asSequence(),
-                seconds,
-                meta
-        ).withBinning(binning)
-
-        val defaultFilteredNorming = defaultFiltered.getColumn(COUNT_RATE_KEY).stream().mapToDouble{it.doubleValue()}.sum()
-
-        println("The norming factor for default filtered count rate is $defaultFilteredNorming")
 
 
-        plots.getPlotFrame("amps").apply {
+    val plots = context.getFeature(PlotManager::class.java)
-            add(DataPlot.plot("events", AMPLITUDE_ADAPTER, events.replaceColumn(COUNT_RATE_KEY){getDouble(COUNT_RATE_KEY)/eventsNorming}))
+
-            add(DataPlot.plot("filtered", AMPLITUDE_ADAPTER, filtered.replaceColumn(COUNT_RATE_KEY){getDouble(COUNT_RATE_KEY)/filteredNorming}))
+    for (hv in arrayOf(14000.0, 14500.0, 15000.0, 15500.0, 16050.0)) {
-            add(DataPlot.plot("defaultFiltered", AMPLITUDE_ADAPTER, defaultFiltered.replaceColumn(COUNT_RATE_KEY){getDouble(COUNT_RATE_KEY)/defaultFilteredNorming}))
+
-        }
+        val frame = plots.getPlotFrame("integral[$hv]").apply {
-
+            this.plots.descriptor = DescriptorUtils.buildDescriptor(DataPlot::class)
-//        plots.getPlotFrame("ratio").apply {
+            this.plots.configureValue("showLine", true)
-//
-//            add(
-//                    DataPlot.plot(
-//                            "ratio",
-//                            Adapters.DEFAULT_XY_ADAPTER,
-//                            events.zip(filtered) { f, s ->
-//                                Adapters.buildXYDataPoint(f.getDouble(CHANNEL_KEY), f.getDouble(COUNT_RATE_KEY) / s.getDouble(COUNT_RATE_KEY))
-//                            }
-//                    )
-//            )
-//        }
         }
 
+        val point = set.optPoint(hv).get()
 
+        frame.add(DataPlot.plot("raw", AMPLITUDE_ADAPTER, analyzer.getAmplitudeSpectrum(point, meta).withBinning(20)))
+        frame.add(DataPlot.plot("filtered", AMPLITUDE_ADAPTER, analyzer.getAmplitudeSpectrum(point, metaForChain).withBinning(20)))
+        frame.add(DataPlot.plot("invertedFilter", AMPLITUDE_ADAPTER, analyzer.getAmplitudeSpectrum(point, metaForChainInverted).withBinning(20)))
+    }
 }

numass-main/src/main/kotlin/inr/numass/scripts/InversedChainProto.kt

@@ -0,0 +1,61 @@
+/*
+ * 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 inr.numass.scripts
+
+import hep.dataforge.description.DescriptorUtils
+import hep.dataforge.fx.plots.PlotManager
+import hep.dataforge.kodex.buildContext
+import hep.dataforge.kodex.buildMeta
+import hep.dataforge.plots.data.DataPlot
+import inr.numass.NumassPlugin
+import inr.numass.data.analyzers.NumassAnalyzer.Companion.AMPLITUDE_ADAPTER
+import inr.numass.data.analyzers.NumassAnalyzer.Companion.withBinning
+import inr.numass.data.analyzers.SmartAnalyzer
+import inr.numass.data.storage.ProtoNumassPoint
+import java.nio.file.Paths
+
+
+fun main(args: Array<String>) {
+
+    val context = buildContext("NUMASS", NumassPlugin::class.java, PlotManager::class.java)
+
+    val analyzer = SmartAnalyzer()
+
+    val meta = buildMeta {
+        "window.lo" to 800
+        "window.up" to 5600
+    }
+
+    val metaForChain = meta.builder.setValue("t0", 15e3)
+
+    val metaForChainInverted = metaForChain.builder.setValue("inverted", true)
+
+
+    val plots = context.getFeature(PlotManager::class.java)
+
+    val point = ProtoNumassPoint.readFile(Paths.get("D:\\Work\\Numass\\data\\2017_05_frames\\Fill_3_events\\set_33\\p36(30s)(HV1=17000).df"))
+
+    val frame = plots.getPlotFrame("integral").apply {
+        this.plots.descriptor = DescriptorUtils.buildDescriptor(DataPlot::class)
+        this.plots.configureValue("showLine", true)
+    }
+
+    frame.add(DataPlot.plot("raw", AMPLITUDE_ADAPTER, analyzer.getAmplitudeSpectrum(point, meta).withBinning(80)))
+    frame.add(DataPlot.plot("filtered", AMPLITUDE_ADAPTER, analyzer.getAmplitudeSpectrum(point, metaForChain).withBinning(80)))
+    frame.add(DataPlot.plot("invertedFilter", AMPLITUDE_ADAPTER, analyzer.getAmplitudeSpectrum(point, metaForChainInverted).withBinning(80)))
+
+}