Misc

numass-control/cryotemp/src/main/java/inr/numass/control/cryotemp/PKT8VirtualPort.java

@@ -32,7 +32,7 @@ public class PKT8VirtualPort extends VirtualPort implements Metoid {
             case "s":
                 String[] letters = {"a", "b", "c", "d", "e", "f", "g", "h"};
                 for (String letter : letters) {
-                    Meta channelMeta = MetaUtils.findNodeByValue(meta(), "channel", "letter", Value.of(letter));
+                    Meta channelMeta = MetaUtils.findNodeByValue(meta(), "channel", "letter", Value.of(letter)).orElse(Meta.empty());
 
                     double average;
                     double sigma;

numass-core/src/main/java/inr/numass/data/analyzers/SmartAnalyzer.java

@@ -28,8 +28,8 @@ public class SmartAnalyzer extends AbstractAnalyzer {
     @Override
     public Values analyze(NumassBlock block, Meta config) {
         //TODO add result caching
-        //TODO do something more... smart... using information from point if block is point
-        switch (config.getString("type", "simple")) {
+        if(config.hasValue("type")) {
+            switch (config.getString("type")) {
                 case "simple":
                     return simpleAnalyzer.analyze(block, config);
                 case "time":
@@ -39,5 +39,12 @@ public class SmartAnalyzer extends AbstractAnalyzer {
                 default:
                     throw new IllegalArgumentException("Analyzer not found");
             }
+        } else {
+            if(config.hasValue("t0")){
+                return timeAnalyzer.analyze(block,config);
+            } else {
+                return simpleAnalyzer.analyze(block,config);
+            }
+        }
     }
 }

numass-main/src/main/groovy/inr/numass/scripts/PrintLossFunctions.groovy

@@ -10,7 +10,7 @@ import inr.numass.models.LossCalculator
 
 LossCalculator loss = LossCalculator.instance()
 
-def X = 0.34
+def X = 0.36
 
 def lossProbs = loss.getGunLossProbabilities(X);
 
@@ -30,11 +30,11 @@ printf("%8s\t%8s\t%8s\t%8s\t%n",
  */
 
 def singleScatter = loss.getSingleScatterFunction(
-        12.587,
-        11.11,
-        1.20,
-        11.02,
-        2.43
+        12.860,
+        16.62,
+        1.71,
+        12.09,
+        4.59
 );
 
 for (double d = 0; d < 30; d += 0.3) {