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Fix to task generics.

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This commit is contained in:
Alexander Nozik 2018-07-15 19:29:28 +03:00
parent 57650d6512
commit d6b93d67e5
16 changed files with 84 additions and 67 deletions
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13
numass-control/dante/src/main/kotlin/inr/numass/control/dante/DanteTest.kt
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@ -18,7 +18,7 @@ package inr.numass.control.dante
import hep.dataforge.context.Context
import hep.dataforge.context.Global
import hep.dataforge.fx.plots.display
import hep.dataforge.fx.plots.displayPlot
import hep.dataforge.kodex.configure
import hep.dataforge.kodex.nullable
import hep.dataforge.meta.KMetaBuilder
@ -79,7 +79,7 @@ fun NumassBlock.plotAmplitudeSpectrum(plotName: String = "spectrum", frameName:
val lo = meta.optNumber("window.lo").nullable?.toInt()
val up = meta.optNumber("window.up").nullable?.toInt()
val data = SimpleAnalyzer().getAmplitudeSpectrum(this, meta.getMetaOrEmpty("spectrum")).withBinning(binning, lo, up)
context.display(
context.displayPlot {
chart {
val valueAxis = if (meta.getBoolean("normalize", false)) {
NumassAnalyzer.COUNT_RATE_KEY
@ -92,16 +92,17 @@ fun NumassBlock.plotAmplitudeSpectrum(plotName: String = "spectrum", frameName:
"showLine" to true
"showSymbol" to false
"showErrors" to false
}.setType(DataPlot::class)
}.setType<DataPlot>()
val plot = DataPlot.plot(
plotName,
Adapters.buildXYAdapter(NumassAnalyzer.CHANNEL_KEY, valueAxis),
data
data,
Adapters.buildXYAdapter(NumassAnalyzer.CHANNEL_KEY, valueAxis)
)
plot.configure(meta)
add(plot)
}
)
}
}

3
numass-main/src/main/kotlin/inr/numass/NumassPlugin.kt
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@ -70,7 +70,8 @@ class NumassPlugin : BasicPlugin() {
transformTask,
filterTask,
fitTask,
plotFitTask
plotFitTask,
histogramTask
)
@Provides(Task.TASK_TARGET)

2
numass-main/src/main/kotlin/inr/numass/actions/PlotFitResultAction.kt
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@ -68,7 +68,7 @@ object PlotFitResultAction : OneToOneAction<FitResult, FitResult>() {
StreamSupport.stream(data.spliterator(), false)
.map { dp -> Adapters.getXValue(adapter, dp).double }.sorted().forEach{ fit.calculateIn(it) }
context.plot(listOf(fit,DataPlot.plot("data", adapter, data)), this.name, name)
context.plot(listOf(fit,DataPlot.plot("data", data, adapter)), this.name, name)
return input
}

12
numass-main/src/main/kotlin/inr/numass/data/Visualization.kt
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@ -18,13 +18,13 @@ package inr.numass.data
import hep.dataforge.context.Context
import hep.dataforge.context.Global
import hep.dataforge.fx.plots.display
import hep.dataforge.fx.plots.displayPlot
import hep.dataforge.kodex.configure
import hep.dataforge.kodex.nullable
import hep.dataforge.meta.KMetaBuilder
import hep.dataforge.meta.buildMeta
import hep.dataforge.plots.data.DataPlot
import hep.dataforge.plots.jfreechart.JFreeChartFrame
import hep.dataforge.plots.jfreechart.chart
import hep.dataforge.tables.Adapters
import inr.numass.data.analyzers.NumassAnalyzer
import inr.numass.data.analyzers.SmartAnalyzer
@ -38,8 +38,8 @@ fun NumassBlock.plotAmplitudeSpectrum(plotName: String = "spectrum", frameName:
val lo = meta.optNumber("window.lo").nullable?.toInt()
val up = meta.optNumber("window.up").nullable?.toInt()
val data = SmartAnalyzer().getAmplitudeSpectrum(this, meta.getMetaOrEmpty("spectrum")).withBinning(binning, lo, up)
context.display {
JFreeChartFrame().apply {
context.displayPlot {
chart {
val valueAxis = if (meta.getBoolean("normalize", false)) {
NumassAnalyzer.COUNT_RATE_KEY
} else {
@ -55,8 +55,8 @@ fun NumassBlock.plotAmplitudeSpectrum(plotName: String = "spectrum", frameName:
val plot = DataPlot.plot(
plotName,
Adapters.buildXYAdapter(NumassAnalyzer.CHANNEL_KEY, valueAxis),
data
data,
Adapters.buildXYAdapter(NumassAnalyzer.CHANNEL_KEY, valueAxis)
)
plot.configure(meta)
add(plot)

4
numass-main/src/main/kotlin/inr/numass/models/mc/BetaSampler.kt
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@ -1,7 +1,7 @@
package inr.numass.models.mc
import hep.dataforge.context.Global
import hep.dataforge.fx.plots.display
import hep.dataforge.fx.plots.displayPlot
import hep.dataforge.maths.chain.Chain
import hep.dataforge.meta.buildMeta
import hep.dataforge.plots.XYFunctionPlot
@ -47,7 +47,7 @@ fun main(args: Array<String>) {
50 * distribution.density(18600.0 - it)
}
Global.display {
Global.displayPlot {
chart {
add(spectrumPlot)
add(distributionPlot)

6
numass-main/src/main/kotlin/inr/numass/scripts/InversedChain.kt
View File

@ -72,8 +72,8 @@ fun main(args: Array<String>) {
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)))
frame.add(DataPlot.plot("raw", analyzer.getAmplitudeSpectrum(point, meta).withBinning(20), AMPLITUDE_ADAPTER))
frame.add(DataPlot.plot("filtered", analyzer.getAmplitudeSpectrum(point, metaForChain).withBinning(20), AMPLITUDE_ADAPTER))
frame.add(DataPlot.plot("invertedFilter", analyzer.getAmplitudeSpectrum(point, metaForChainInverted).withBinning(20), AMPLITUDE_ADAPTER))
}
}

6
numass-main/src/main/kotlin/inr/numass/scripts/InversedChainProto.kt
View File

@ -51,8 +51,8 @@ fun main(args: Array<String>) {
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)))
frame.add(DataPlot.plot("raw", analyzer.getAmplitudeSpectrum(point, meta).withBinning(80), AMPLITUDE_ADAPTER))
frame.add(DataPlot.plot("filtered", analyzer.getAmplitudeSpectrum(point, metaForChain).withBinning(80), AMPLITUDE_ADAPTER))
frame.add(DataPlot.plot("invertedFilter", analyzer.getAmplitudeSpectrum(point, metaForChainInverted).withBinning(80), AMPLITUDE_ADAPTER))
}

4
numass-main/src/main/kotlin/inr/numass/scripts/models/DifferentialSpectrum.kt
View File

@ -81,9 +81,9 @@ fun main(args: Array<String>) {
val norm = res.getColumn(COUNT_RATE_KEY).stream().mapToDouble { it.double }.sum()
integralFrame.add(DataPlot.plot("point_$hv", AMPLITUDE_ADAPTER, spectrum0))
integralFrame.add(DataPlot.plot("point_$hv", spectrum0, AMPLITUDE_ADAPTER))
frame.add(DataPlot.plot("point_$hv", AMPLITUDE_ADAPTER, res.replaceColumn(COUNT_RATE_KEY) { getDouble(COUNT_RATE_KEY) / norm }))
frame.add(DataPlot.plot("point_$hv", res.replaceColumn(COUNT_RATE_KEY) { getDouble(COUNT_RATE_KEY) / norm }, AMPLITUDE_ADAPTER))
}
}
}

2
numass-main/src/main/kotlin/inr/numass/tasks/NumassFitScanSummaryTask.kt
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@ -25,7 +25,7 @@ import inr.numass.NumassUtils
* @author Alexander Nozik
*/
object NumassFitScanSummaryTask : AbstractTask<Table>(Table::class.java) {
override fun run(model: TaskModel, data: DataNode<*>): DataNode<Table> {
override fun run(model: TaskModel, data: DataNode<Any>): DataNode<Table> {
val builder = DataSet.edit(Table::class)
val action = FitSummaryAction()
val input = data.checked(FitResult::class.java)

2
numass-main/src/main/kotlin/inr/numass/tasks/NumassFitScanTask.kt
View File

@ -24,7 +24,7 @@ import hep.dataforge.workspace.tasks.TaskModel
*/
object NumassFitScanTask : AbstractTask<FitResult>(FitResult::class.java) {
override fun run(model: TaskModel, data: DataNode<*>): DataNode<FitResult> {
override fun run(model: TaskModel, data: DataNode<Any>): DataNode<FitResult> {
val config = model.meta
val scanParameter = config.getString("parameter", "msterile2")

2
numass-main/src/main/kotlin/inr/numass/tasks/NumassFitSummaryTask.kt
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@ -30,7 +30,7 @@ import inr.numass.actions.SummaryAction
object NumassFitSummaryTask : AbstractTask<Table>(Table::class.java) {
override val name: String = "summary"
override fun run(model: TaskModel, data: DataNode<*>): DataNode<out Table> {
override fun run(model: TaskModel, data: DataNode<Any>): DataNode<Table> {
val actionMeta = model.meta.getMeta("summary")
val checkedData = data.getCheckedNode("fit", FitState::class.java)
return SummaryAction.run(model.context, checkedData, actionMeta)

43
numass-main/src/main/kotlin/inr/numass/tasks/NumassTasks.kt
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@ -4,9 +4,6 @@ import hep.dataforge.data.CustomDataFilter
import hep.dataforge.data.DataSet
import hep.dataforge.data.DataTree
import hep.dataforge.data.DataUtils
import hep.dataforge.description.Description
import hep.dataforge.description.ValueDef
import hep.dataforge.description.ValueDefs
import hep.dataforge.io.output.stream
import hep.dataforge.io.render
import hep.dataforge.kodex.nullable
@ -44,9 +41,13 @@ import java.io.PrintWriter
import java.util.*
import java.util.concurrent.atomic.AtomicLong
import java.util.stream.StreamSupport
import kotlin.collections.set
@Description("Select data from initial data pool")
val selectTask = task("select") {
descriptor {
info = "Select data from initial data pool"
}
model { meta ->
data("*")
configure(meta.getMetaOrEmpty("data"))
@ -59,8 +60,10 @@ val selectTask = task("select") {
}
}
@Description("Count the number of events for each voltage and produce a table with the results")
val analyzeTask = task("analyze") {
descriptor {
info = "Count the number of events for each voltage and produce a table with the results"
}
model { meta ->
dependsOn(selectTask, meta);
configure(MetaUtils.optEither(meta, "analyzer", "prepare").orElse(Meta.empty()))
@ -73,11 +76,11 @@ val analyzeTask = task("analyze") {
}
}
@ValueDefs(
ValueDef(key = "showPlot", type = [ValueType.BOOLEAN], info = "Show plot after complete"),
ValueDef(key = "monitorVoltage", type = [ValueType.NUMBER], info = "The voltage for monitor point")
)
val monitorTableTask = task("monitor") {
descriptor {
value("showPlot", types = listOf(ValueType.BOOLEAN), info = "Show plot after complete")
value("monitorVoltage", types = listOf(ValueType.NUMBER), info = "The voltage for monitor point")
}
model { meta ->
dependsOn(selectTask, meta)
configure(meta.getMetaOrEmpty("monitor"))
@ -99,7 +102,7 @@ val monitorTableTask = task("monitor") {
).build()
if (meta.getBoolean("showPlot", true)) {
val plot = DataPlot.plot(name, Adapters.buildXYAdapter("timestamp", "cr", "crErr"), res)
val plot = DataPlot.plot(name, res, Adapters.buildXYAdapter("timestamp", "cr", "crErr"))
context.plot(plot, "numass.monitor", name) {
"xAxis.title" to "time"
"xAxis.type" to "time"
@ -259,7 +262,7 @@ val plotFitTask = task("plotFit") {
StreamSupport.stream<Values>(data.spliterator(), false)
.map { dp -> Adapters.getXValue(adapter, dp).double }.sorted().forEach { fit.calculateIn(it) }
val dataPlot = DataPlot.plot("data", adapter, data)
val dataPlot = DataPlot.plot("data", data, adapter)
context.plot(listOf(fit, dataPlot), "numass.plotFit", name)
@ -267,10 +270,11 @@ val plotFitTask = task("plotFit") {
}
}
@Description("""
Combine amplitude spectra from multiple sets, but with the same U.
""")
val histogramTask = task("histogram") {
descriptor {
value("plot",types = listOf(ValueType.BOOLEAN), defaultValue = false, info = "Show plot of the spectra")
info = "Combine amplitude spectra from multiple sets, but with the same U"
}
model { meta ->
dependsOn(selectTask, meta)
configure(meta.getMetaOrEmpty("histogram"))
@ -314,10 +318,19 @@ val histogramTask = task("histogram") {
row(values)
}
}
//TODO increase binning
context.output.render(table, stage = "numass.histogram", name = name, meta = meta)
//TODO add plot
if (meta.getBoolean("plot", false)) {
context.plot("$name.plot", stage = "numass.histogram") {
plots.setType<DataPlot>()
table.format.names.filter { it != "channel" }.forEach {
+DataPlot.plot(it, table, adapter = Adapters.buildXYAdapter("channel", it))
}
}
}
return@join table
}

3
numass-main/src/test/java/inr/numass/models/PlotScatter.java
View File

@ -17,6 +17,7 @@ package inr.numass.models;
import hep.dataforge.stat.fit.ParamSet;
import inr.numass.NumassPluginKt;
import inr.numass.models.misc.LossCalculator;
/**
*
@ -36,6 +37,6 @@ public class PlotScatter {
+ "'ionW' = 11.33 ± 0.43\n"
+ "'exIonRatio' = 4.83 ± 0.36"
);
LossCalculator.plotScatter(NumassPluginKt.displayChart("Loss function"), pars);
LossCalculator.INSTANCE.plotScatter(NumassPluginKt.displayChart("Loss function"), pars);
}
}

3
numass-main/src/test/java/inr/numass/models/TestNeLossParametrisation.java
View File

@ -19,6 +19,7 @@ import hep.dataforge.maths.integration.GaussRuleIntegrator;
import hep.dataforge.plots.PlotFrame;
import hep.dataforge.plots.XYFunctionPlot;
import inr.numass.NumassPluginKt;
import inr.numass.models.misc.LossCalculator;
import org.apache.commons.math3.analysis.UnivariateFunction;
/**
@ -34,7 +35,7 @@ public class TestNeLossParametrisation {
public static void main(String[] args) {
PlotFrame frame = NumassPluginKt.displayChart("Loss parametrisation test");
//JFreeChartFrame.drawFrame("Loss parametrisation test", null);
UnivariateFunction oldFunction = LossCalculator.getSingleScatterFunction();
UnivariateFunction oldFunction = LossCalculator.INSTANCE.getSingleScatterFunction();
UnivariateFunction newFunction = getSingleScatterFunction(12.86, 16.78, 1.65, 12.38, 4.79);
Double norm = new GaussRuleIntegrator(200).integrate(0d, 100d, newFunction);

8
numass-viewer/src/main/kotlin/inr/numass/viewer/AmplitudeView.kt
View File

@ -138,16 +138,16 @@ class AmplitudeView : View(title = "Numass amplitude spectrum plot", icon = Imag
return@runGoal if (channels.size == 1) {
DataPlot.plot(
key,
adapter,
channels.values.first().withBinning(binning)
channels.values.first().withBinning(binning),
adapter
)
} else {
val group = PlotGroup.typed<DataPlot>(key)
channels.forEach { key, spectrum ->
val plot = DataPlot.plot(
key.toString(),
adapter,
spectrum.withBinning(binning)
spectrum.withBinning(binning),
adapter
)
group.add(plot)
}

2
numass-viewer/src/main/kotlin/inr/numass/viewer/SlowControlView.kt
View File

@ -54,7 +54,7 @@ class SlowControlView : View(title = "Numass slow control view", icon = ImageVie
names.forEach {
val adapter = Adapters.buildXYAdapter("timestamp", it);
val plot = DataPlot.plot(it, adapter, plotData).configure {
val plot = DataPlot.plot(it, plotData, adapter).configure {
"showLine" to true
"showSymbol" to false
"showErrors" to false