diff --git a/numass-main/src/main/kotlin/inr/numass/NumassUtils.kt b/numass-main/src/main/kotlin/inr/numass/NumassUtils.kt
index 189281d0..65f1b523 100644
--- a/numass-main/src/main/kotlin/inr/numass/NumassUtils.kt
+++ b/numass-main/src/main/kotlin/inr/numass/NumassUtils.kt
@@ -19,7 +19,6 @@ import hep.dataforge.context.Context
 import hep.dataforge.data.DataNode
 import hep.dataforge.data.DataSet
 import hep.dataforge.data.binary.Binary
-import hep.dataforge.fx.plots.plusAssign
 import hep.dataforge.io.envelopes.DefaultEnvelopeType
 import hep.dataforge.io.envelopes.Envelope
 import hep.dataforge.io.envelopes.EnvelopeBuilder
@@ -29,13 +28,7 @@ import hep.dataforge.io.markup.SimpleMarkupRenderer
 import hep.dataforge.kodex.nullable
 import hep.dataforge.meta.Meta
 import hep.dataforge.meta.MetaBuilder
-import hep.dataforge.plots.PlotUtils
-import hep.dataforge.plots.XYFunctionPlot
-import hep.dataforge.plots.data.DataPlot
 import hep.dataforge.plots.jfreechart.JFreeChartFrame
-import hep.dataforge.stat.fit.FitResult
-import hep.dataforge.stat.models.XYModel
-import hep.dataforge.tables.Adapters
 import hep.dataforge.tables.ListTable
 import hep.dataforge.tables.Table
 import hep.dataforge.tables.ValueMap
@@ -270,37 +263,37 @@ fun Values.unbox(): Map<String, Any?> {
     return res
 }
 
-fun FitResult.display(context: Context, stage: String = "fit") {
-    val model = optModel(context).get() as XYModel
-
-    val adapter = model.adapter
-
-    val frame = PlotUtils.getPlotManager(context)
-            .getPlotFrame(stage, "plot", Meta.empty())
-
-    val func = { x: Double -> model.spectrum.value(x, parameters) }
-
-    val fit = XYFunctionPlot("fit", function = func)
-    fit.density = 100
-    // ensuring all data points are calculated explicitly
-    data.rows.map { dp -> Adapters.getXValue(adapter, dp).doubleValue() }.sorted().forEach { fit.calculateIn(it) }
-
-    frame.add(fit)
-
-    frame.add(DataPlot.plot("data", adapter, data))
-
-    val residualsFrame = PlotUtils.getPlotManager(context)
-            .getPlotFrame(stage, "residuals", Meta.empty())
-
-    val residual = DataPlot("residuals");
-
-    data.rows.forEach {
-        val x = Adapters.getXValue(adapter, it).doubleValue()
-        val y = Adapters.getYValue(adapter, it).doubleValue()
-        val err = Adapters.optYError(adapter, it).orElse(1.0)
-        residual += Adapters.buildXYDataPoint(x, (y - func(x)) / err, 1.0)
-    }
-
-    residualsFrame.add(residual)
-
-}
+//fun FitResult.display(context: Context, stage: String = "fit") {
+//    val model = optModel(context).get() as XYModel
+//
+//    val adapter = model.adapter
+//
+//    val frame = PlotUtils.getPlotManager(context)
+//            .getPlotFrame(stage, "plot", Meta.empty())
+//
+//    val func = { x: Double -> model.spectrum.value(x, parameters) }
+//
+//    val fit = XYFunctionPlot("fit", function = func)
+//    fit.density = 100
+//    // ensuring all data points are calculated explicitly
+//    data.rows.map { dp -> Adapters.getXValue(adapter, dp).doubleValue() }.sorted().forEach { fit.calculateIn(it) }
+//
+//    frame.add(fit)
+//
+//    frame.add(DataPlot.plot("data", adapter, data))
+//
+//    val residualsFrame = PlotUtils.getPlotManager(context)
+//            .getPlotFrame(stage, "residuals", Meta.empty())
+//
+//    val residual = DataPlot("residuals");
+//
+//    data.rows.forEach {
+//        val x = Adapters.getXValue(adapter, it).doubleValue()
+//        val y = Adapters.getYValue(adapter, it).doubleValue()
+//        val err = Adapters.optYError(adapter, it).orElse(1.0)
+//        residual += Adapters.buildXYDataPoint(x, (y - func(x)) / err, 1.0)
+//    }
+//
+//    residualsFrame.add(residual)
+//
+//}
diff --git a/numass-main/src/main/kotlin/inr/numass/data/Visualization.kt b/numass-main/src/main/kotlin/inr/numass/data/Visualization.kt
index ab16a760..f6d356d3 100644
--- a/numass-main/src/main/kotlin/inr/numass/data/Visualization.kt
+++ b/numass-main/src/main/kotlin/inr/numass/data/Visualization.kt
@@ -44,17 +44,19 @@ fun NumassBlock.plotAmplitudeSpectrum(plotName: String = "spectrum", frameName:
         } else {
             NumassAnalyzer.COUNT_KEY
         }
-        val plot = DataPlot.plot(
-                plotName,
-                Adapters.buildXYAdapter(NumassAnalyzer.CHANNEL_KEY, valueAxis),
-                data
-        ).configure {
+        plots.configure {
             "connectionType" to "step"
             "thickness" to 2
             "showLine" to true
             "showSymbol" to false
             "showErrors" to false
-        }
+        }.setType(DataPlot::class)
+
+        val plot = DataPlot.plot(
+                plotName,
+                Adapters.buildXYAdapter(NumassAnalyzer.CHANNEL_KEY, valueAxis),
+                data
+        )
         plot.configure(meta)
         add(plot)
     }
diff --git a/numass-main/src/main/kotlin/inr/numass/scripts/tristan/ViewPoint.kt b/numass-main/src/main/kotlin/inr/numass/scripts/tristan/ViewPoint.kt
new file mode 100644
index 00000000..11f76f81
--- /dev/null
+++ b/numass-main/src/main/kotlin/inr/numass/scripts/tristan/ViewPoint.kt
@@ -0,0 +1,30 @@
+package inr.numass.scripts.tristan
+
+import hep.dataforge.kodex.toList
+import inr.numass.data.api.MetaBlock
+import inr.numass.data.api.NumassBlock
+import inr.numass.data.api.NumassPoint
+import inr.numass.data.channel
+import inr.numass.data.plotAmplitudeSpectrum
+import inr.numass.data.storage.ProtoNumassPoint
+import java.io.File
+
+
+private fun NumassPoint.getChannels(): Map<Int, NumassBlock> {
+    return blocks.toList().groupBy { it.channel ?: 0 }.mapValues { entry ->
+        if (entry.value.size == 1) {
+            entry.value.first()
+        } else {
+            MetaBlock(entry.value)
+        }
+    }
+}
+
+fun main(args: Array<String>) {
+    val file = File("D:\\Work\\Numass\\data\\17kV\\processed.df").toPath()
+    val point = ProtoNumassPoint.readFile(file)
+    println(point.meta)
+    point.getChannels().forEach{ num, block ->
+        block.plotAmplitudeSpectrum(plotName = num.toString())
+    }
+}
\ No newline at end of file