]> gerrit.simantics Code Review - simantics/sysdyn.git/commitdiff
Bugfix. (refs #4238)
authormiettinen <miettinen@ac1ea38d-2e2b-0410-8846-a27921b304fc>
Thu, 27 Jun 2013 11:14:58 +0000 (11:14 +0000)
committermiettinen <miettinen@ac1ea38d-2e2b-0410-8846-a27921b304fc>
Thu, 27 Jun 2013 11:14:58 +0000 (11:14 +0000)
git-svn-id: https://www.simantics.org/svn/simantics/sysdyn/trunk@27665 ac1ea38d-2e2b-0410-8846-a27921b304fc

org.simantics.modelica/src/org/simantics/modelica/data/SimulationResult.java
org.simantics.sysdyn/src/org/simantics/sysdyn/adapter/distribution/IDistribution.java

index d4091285cff0b0c490d6f69cb3bdf4f84c1c9317..96f1c5a3c1afd8c31be84d855a6bbf3f18c2d901 100644 (file)
@@ -461,13 +461,14 @@ public class SimulationResult {
             ds = new DataSet(variable, timesArray, resArray);\r
             try {\r
                    for (DataSet tempds : variables){\r
-                       if (tempds.name.equals(variable))\r
+                       if (tempds.name.equals(variable)) {\r
                            // We should never need to go there unless some change in\r
                            // the logic of reading variables are made.\r
                            // Also helps in seeking memory leaks.\r
                                System.err.println("Find me and add a comment that I was printed, please.");\r
                                // If it seems that in no case we need to go here, comment this try catch.\r
                            return null;\r
+                       }\r
                    }\r
             } catch (ConcurrentModificationException e) {\r
             }\r
index 760ed446bed467c71726ae9047706866a33d58b4..a0949854ef847d5550df47b98fd891bf8a6f8c76 100644 (file)
@@ -19,7 +19,7 @@ public interface IDistribution {
      * When random numbers are used to generate the Monte Carlo simulation parameters, the probability\r
      * is itself selected randomly (between (0,1); at the domain endpoints the value is undefined).\r
      * \r
-     * @param randomVariable\r
+     * @param probability\r
      * @return Inverse cumulative distribution function at probability, i.e. the random variable at the\r
      * point where the cumulative distribution function yields probability.\r
      */\r