Some fixes

numass-main/src/main/kotlin/inr/numass/NumassPlugin.kt

@@ -58,7 +58,6 @@ class NumassPlugin : BasicPlugin() {
     }
 
     private val tasks = listOf(
-            NumassFitScanTask,
             NumassFitScanSummaryTask,
             NumassFitSummaryTask,
             selectTask,
@@ -71,7 +70,8 @@ class NumassPlugin : BasicPlugin() {
             filterTask,
             fitTask,
             plotFitTask,
-            histogramTask
+            histogramTask,
+            fitScanTask
     )
 
     @Provides(Task.TASK_TARGET)
@@ -220,6 +220,13 @@ class NumassPlugin : BasicPlugin() {
         }
 
         library.addModel("sterile") { context, meta ->
+            val sp = SterileNeutrinoSpectrum(context, meta)
+            val spectrum = NBkgSpectrum(sp)
+
+            XYModel(meta, getAdapter(meta), spectrum)
+        }
+
+        library.addModel("sterile-corrected") { context, meta ->
             val sp = SterileNeutrinoSpectrum(context, meta)
             val spectrum = NBkgSpectrumWithCorrection(sp)
 

numass-main/src/main/kotlin/inr/numass/scripts/analysis/Run2017_05.kt

@@ -0,0 +1,20 @@
+package inr.numass.scripts.analysis
+
+import hep.dataforge.context.Global
+import hep.dataforge.fx.output.FXOutputManager
+import hep.dataforge.workspace.FileBasedWorkspace
+import java.io.File
+
+fun main(args: Array<String>) {
+    FXOutputManager().startGlobal()
+
+    val configPath = File("D:\\Work\\Numass\\sterile2017_05\\workspace.groovy").toPath()
+    val workspace = FileBasedWorkspace.build(Global, configPath)
+    workspace.context.setValue("cache.enabled", false)
+
+    //val meta = workspace.getTarget("group_3")
+
+    val result = workspace.runTask("scansum", "group_3").first().get()
+    println("Complete!")
+
+}

numass-main/src/main/kotlin/inr/numass/scripts/analysis/Run2017_11.kt

@@ -1,6 +1,7 @@
 package inr.numass.scripts.analysis
 
 import hep.dataforge.context.Global
+import hep.dataforge.fx.output.FXOutputManager
 import hep.dataforge.plots.plotData
 import hep.dataforge.tables.Adapters
 import hep.dataforge.tables.Table
@@ -19,6 +20,8 @@ fun main(args: Array<String>) {
 //        }
 //    }
 
+    FXOutputManager().startGlobal()
+
 
     val configPath = File("D:\\Work\\Numass\\sterile2017_11\\workspace.groovy").toPath()
 

numass-main/src/main/kotlin/inr/numass/scripts/threshold/FitAllWithPower.kt

@@ -20,6 +20,7 @@ import hep.dataforge.buildContext
 import hep.dataforge.fx.output.FXOutputManager
 import hep.dataforge.io.DirectoryOutput
 import hep.dataforge.io.plus
+import hep.dataforge.io.render
 import hep.dataforge.meta.buildMeta
 import hep.dataforge.nullable
 import hep.dataforge.plots.data.DataPlot
@@ -27,6 +28,8 @@ import hep.dataforge.plots.jfreechart.JFreeChartPlugin
 import hep.dataforge.plots.plotData
 import hep.dataforge.storage.files.FileStorage
 import hep.dataforge.tables.Adapters
+import hep.dataforge.tables.filter
+import hep.dataforge.tables.sort
 import inr.numass.NumassPlugin
 import inr.numass.data.NumassDataUtils
 import inr.numass.data.api.NumassSet
@@ -36,8 +39,8 @@ import inr.numass.subthreshold.Threshold
 
 fun main(args: Array<String>) {
     val context = buildContext("NUMASS", NumassPlugin::class.java, JFreeChartPlugin::class.java) {
-        rootDir = "D:\\Work\\Numass\\sterile\\2017_11"
+        rootDir = "D:\\Work\\Numass\\sterile\\2017_05"
-        dataDir = "D:\\Work\\Numass\\data\\2017_11"
+        dataDir = "D:\\Work\\Numass\\data\\2017_05"
         output = FXOutputManager() + DirectoryOutput()
     }
 
@@ -59,18 +62,21 @@ fun main(args: Array<String>) {
         plots.setType<DataPlot>()
     }
 
-    val sets = (36..42).map { "set_$it" }.map { setName ->
+    val sets = (1..18).map { "set_$it" }.map { setName ->
-        storage.provide(setName, NumassSet::class.java).nullable ?: error("Set does not exist")
+        storage.provide(setName, NumassSet::class.java).nullable
-    }
+    }.filterNotNull()
-    val name = "fill_2[36-42]"
+
+    val name = "fill_2[1-18]"
 
     val sum = NumassDataUtils.join(name, sets)
 
     val correctionTable = Threshold.calculateSubThreshold(sum, meta).filter {
         it.getDouble("correction") in (1.0..1.2)
-    }
+    }.sort("voltage")
 
     frame.plotData("${name}_cor", correctionTable, Adapters.buildXYAdapter("U", "correction"))
     frame.plotData("${name}_a", correctionTable, Adapters.buildXYAdapter("U", "a"))
     frame.plotData("${name}_beta", correctionTable, Adapters.buildXYAdapter("U", "beta"))
+
+    context.output.render(correctionTable,"numass.correction", "fill_2[1-18]")
 }

numass-main/src/main/kotlin/inr/numass/tasks/NumassFitScanSummaryTask.kt

@@ -43,7 +43,7 @@ object NumassFitScanSummaryTask : AbstractTask<Table>(Table::class.java) {
     override val name = "scansum"
 
     @TypedActionDef(name = "sterileSummary", inputType = FitResult::class, outputType = Table::class)
-    private class FitSummaryAction : ManyToOneAction<FitResult, Table>("sterileSummary",FitResult::class.java,Table::class.java) {
+    private class FitSummaryAction : ManyToOneAction<FitResult, Table>("sterileSummary", FitResult::class.java,Table::class.java) {
 
         override fun execute(context: Context, nodeName: String, input: Map<String, FitResult>, meta: Laminate): Table {
             val builder = ListTable.Builder("m", "U2", "U2err", "U2limit", "E0", "trap")

numass-main/src/main/kotlin/inr/numass/tasks/NumassTasks.kt

@@ -24,6 +24,7 @@ import hep.dataforge.tables.*
 import hep.dataforge.useMeta
 import hep.dataforge.values.ValueType
 import hep.dataforge.values.Values
+import hep.dataforge.values.asValue
 import hep.dataforge.workspace.tasks.task
 import inr.numass.NumassUtils
 import inr.numass.actions.MergeDataAction
@@ -366,3 +367,60 @@ val histogramTask = task("histogram") {
         return@join table
     }
 }
+
+val fitScanTask = task("fitscan") {
+    model { meta ->
+        dependsOn(filterTask, meta)
+        configure{
+            setNode(meta.getMetaOrEmpty("scan"))
+            setNode(meta.getMeta("fit"))
+        }
+    }
+
+    splitAction<Table, FitResult> {
+        val scanMeta = meta.getMeta("scan")
+        val scanValues = if (scanMeta.hasValue("masses")) {
+            scanMeta.getValue("masses").list.map { it -> Math.pow(it.double * 1000, 2.0).asValue() }
+        } else {
+            scanMeta.getValue("values", listOf(2.5e5, 1e6, 2.25e6, 4e6, 6.25e6, 9e6)).list
+        }
+
+        val scanParameter = scanMeta.getString("parameter", "msterile2")
+        scanValues.forEach { scanValue ->
+            val resultName = String.format("%s[%s=%s]", this.name, scanParameter, scanValue.string)
+            val fitMeta = meta.getMeta("fit").builder.apply {
+                setValue("@nameSuffix", String.format("[%s=%s]", scanParameter, scanValue.string))
+                if (hasMeta("params.$scanParameter")) {
+                    setValue("params.$scanParameter.value", scanValue)
+                } else {
+                    getMetaList("params.param").stream()
+                            .filter { par -> par.getString("name") == scanParameter }
+                            .forEach { it.setValue("value", it) }
+                }
+            }
+
+            fragment(resultName) {
+                result { data ->
+                    context.output["numass.fitscan", name].stream.use { out ->
+                        val writer = PrintWriter(out)
+                        writer.printf("%n*** META ***%n")
+                        writer.println(fitMeta.toString())
+                        writer.flush()
+
+                        FitHelper(context).fit(data, fitMeta)
+                                .setListenerStream(out)
+                                .report(log)
+                                .run()
+                                .also {
+                                    if (fitMeta.getBoolean("printLog", true)) {
+                                        writer.println()
+                                        log.entries.forEach { entry -> writer.println(entry.toString()) }
+                                        writer.println()
+                                    }
+                                }
+                    }
+                }
+            }
+        }
+    }
+}