Started to remove PlotManager

numass-control/cryotemp/src/main/kotlin/inr/numass/control/cryotemp/PKT8Display.kt

@@ -200,7 +200,7 @@ class PKT8Display : DeviceDisplayFX<PKT8Device>(), PKT8ValueListener {
         }
 
         private fun getPlot(channelName: String): Plot? {
-            return plotFrame[channelName] ?: device.channels.values.find { it.name == channelName }?.let {
+            return plotFrame[channelName] as? Plot ?: device.channels.values.find { it.name == channelName }?.let {
                 TimePlot(it.name).apply {
                     configure(it.meta)
                     plotFrame.add(this)

numass-main/src/main/java/hep/dataforge/plotfit/PlotFitResultAction.java

@@ -22,9 +22,9 @@ import hep.dataforge.description.TypedActionDef;
 import hep.dataforge.meta.Laminate;
 import hep.dataforge.meta.Meta;
 import hep.dataforge.plots.PlotFrame;
-import hep.dataforge.plots.PlotUtils;
 import hep.dataforge.plots.XYFunctionPlot;
 import hep.dataforge.plots.data.DataPlot;
+import hep.dataforge.plots.output.PlotOutputKt;
 import hep.dataforge.stat.fit.FitResult;
 import hep.dataforge.stat.fit.FitState;
 import hep.dataforge.stat.models.XYModel;
@@ -62,9 +62,7 @@ public class PlotFitResultAction extends OneToOneAction<FitResult, FitResult> {
             throw new RuntimeException("No adapter defined for data interpretation");
         }
 
-
+        PlotFrame frame = PlotOutputKt.getPlotFrame(context, getName(), name, metaData.getMeta("frame", Meta.empty()));
-        PlotFrame frame = PlotUtils.INSTANCE.getPlotManager(context)
-                .getPlotFrame(getName(), name, metaData.getMeta("frame", Meta.empty()));
 
         XYFunctionPlot fit = new XYFunctionPlot("fit", Meta.empty(), (Double x) -> model.getSpectrum().value(x, input.getParameters()));
         fit.setDensity(100);

numass-main/src/main/kotlin/inr/numass/actions/TimeAnalyzerAction.kt

@@ -6,9 +6,9 @@ import hep.dataforge.description.*
 import hep.dataforge.kodex.configure
 import hep.dataforge.maths.histogram.UnivariateHistogram
 import hep.dataforge.meta.Laminate
-import hep.dataforge.plots.PlotPlugin
 import hep.dataforge.plots.XYFunctionPlot
 import hep.dataforge.plots.data.DataPlot
+import hep.dataforge.plots.output.getPlotFrame
 import hep.dataforge.tables.Adapters
 import hep.dataforge.tables.Table
 import hep.dataforge.values.ValueType
@@ -40,8 +40,6 @@ class TimeAnalyzerAction : OneToOneAction<NumassPoint, Table>() {
     override fun execute(context: Context, name: String, input: NumassPoint, inputMeta: Laminate): Table {
         val log = getLog(context, name);
 
-        val pm = context[PlotPlugin::class.java];
-
         val initialEstimate = analyzer.analyze(input, inputMeta)
         val trueCR = initialEstimate.getDouble("cr")
 
@@ -62,9 +60,7 @@ class TimeAnalyzerAction : OneToOneAction<NumassPoint, Table>() {
 
         if (inputMeta.getBoolean("plotHist", true)) {
 
-            val histPlot = pm.getPlotFrame(name, "histogram");
+            val histPlot = context.getPlotFrame(name, "histogram") {
-
-            histPlot.configure {
                 node("xAxis") {
                     "title" to "delay"
                     "units" to "us"
@@ -88,7 +84,7 @@ class TimeAnalyzerAction : OneToOneAction<NumassPoint, Table>() {
 
             histPlot.add(
                     XYFunctionPlot.plot(name + "_theory", 0.0, binSize * binNum) {
-                        trueCR/1e6 * initialEstimate.getInt(NumassAnalyzer.COUNT_KEY) * binSize * Math.exp( - it * trueCR / 1e6)
+                        trueCR / 1e6 * initialEstimate.getInt(NumassAnalyzer.COUNT_KEY) * binSize * Math.exp(-it * trueCR / 1e6)
                     }
             )
         }
@@ -103,16 +99,15 @@ class TimeAnalyzerAction : OneToOneAction<NumassPoint, Table>() {
                 configure(inputMeta.getMetaOrEmpty("plot"))
             }
 
-            pm.getPlotFrame(name, "stat-method")
+            context.getPlotFrame(name, "stat-method") {
-                    .configure {
+                "xAxis" to {
-                        "xAxis" to {
+                    "title" to "delay"
-                            "title" to "delay"
+                    "units" to "us"
-                            "units" to "us"
+                }
-                        }
+                "yAxis" to {
-                        "yAxis" to {
+                    "title" to "Relative count rate"
-                            "title" to "Relative count rate"
+                }
-                        }
+            }.add(statPlot)
-                    }.add(statPlot)
 
             (1..100).map { inputMeta.getDouble("t0Step", 1000.0) * it }.map { t ->
                 val result = analyzer.analyze(input, inputMeta.builder.setValue("t0", t))

numass-main/src/main/kotlin/inr/numass/actions/TimeSpectrumAction.kt

@@ -7,8 +7,8 @@ import hep.dataforge.kodex.buildMeta
 import hep.dataforge.kodex.configure
 import hep.dataforge.maths.histogram.UnivariateHistogram
 import hep.dataforge.meta.Laminate
-import hep.dataforge.plots.PlotPlugin
 import hep.dataforge.plots.data.DataPlot
+import hep.dataforge.plots.output.getPlotFrame
 import hep.dataforge.tables.Adapters
 import hep.dataforge.tables.Table
 import hep.dataforge.values.ValueType
@@ -43,7 +43,6 @@ class TimeSpectrumAction : OneToOneAction<NumassPoint, Table>() {
         val t0 = inputMeta.getDouble("t0", 30e3);
         val loChannel = inputMeta.getInt("window.lo", 500);
         val upChannel = inputMeta.getInt("window.up", 10000);
-        val pm = context.get(PlotPlugin::class.java);
 
 
         val trueCR = analyzer.analyze(input, buildMeta {
@@ -70,9 +69,7 @@ class TimeSpectrumAction : OneToOneAction<NumassPoint, Table>() {
 
         if (inputMeta.getBoolean("plotHist", true)) {
 
-            val histPlot = pm.getPlotFrame(name, "histogram");
+            val histPlot = context.getPlotFrame(name, "histogram"){
-
-            histPlot.configure {
                 node("xAxis") {
                     "axisTitle" to "delay"
                     "axisUnits" to "us"
@@ -107,7 +104,7 @@ class TimeSpectrumAction : OneToOneAction<NumassPoint, Table>() {
                 configure(inputMeta.getMetaOrEmpty("plot"))
             }
 
-            pm.getPlotFrame(name, "stat-method").add(statPlot)
+            context.getPlotFrame(name, "stat-method").add(statPlot)
 
             (1..100).map { 1000 * it }.map { t ->
                 val result = analyzer.analyze(input, buildMeta {