Changeset 16610 for branches/2925_AutoDiffForDynamicalModels/AutoDiffForDynamicalModelsTest/TestOdeIdentification.cs

Timestamp:

02/16/19 06:53:44 (5 years ago)

Author:

gkronber

Message:

#2925: added support for multiple training episodes (and log, exp functions)

File:

• branches/2925_AutoDiffForDynamicalModels/AutoDiffForDynamicalModelsTest/TestOdeIdentification.cs (modified) (1 diff)

branches/2925_AutoDiffForDynamicalModels/AutoDiffForDynamicalModelsTest/TestOdeIdentification.cs

@@ -42 +42 @@
       Assert.AreEqual(6.8350792038369173E-20, ((DoubleValue)alg.Results["SNMSE"].Value).Value, 1E-8);
     }
+    [TestMethod]
+    public void RunOdeIdentificationMultipleEpisodes() {
+      var alg = new OdeParameterIdentification();
+      var dynProb = new Problem();
+      var parser = new HeuristicLab.Problems.Instances.DataAnalysis.TableFileParser();
+      // var fileName = @"C:\reps\HEAL\EuroCAST - Kronberger\DataGeneration\test.csv";
+      var fileName = @"C:\reps\HEAL\EuroCAST - Kronberger\DataGeneration\s-system.csv";
+      parser.Parse(fileName, true);
+      var prov = new HeuristicLab.Problems.Instances.DataAnalysis.RegressionCSVInstanceProvider();
+      var regressionProblemData = prov.ImportData(fileName);
+      regressionProblemData.TrainingPartition.Start = 0;
+      regressionProblemData.TrainingPartition.End = 61;
+      regressionProblemData.TestPartition.Start = 61;
+      var allowedInputs = new List<string>(); // empty
+      var targets = new List<string>(new[] { "y1", "y2", "y3", "y4", "y5" });
+      foreach (var checkedItem in regressionProblemData.InputVariables) {
+        regressionProblemData.InputVariables.SetItemCheckedState(checkedItem, allowedInputs.Contains(checkedItem.Value));
+      }
+      dynProb.Load(regressionProblemData);
+
+      foreach (var checkedItem in dynProb.TargetVariables) {
+        dynProb.TargetVariables.SetItemCheckedState(checkedItem, targets.Contains(checkedItem.Value));
+      }
+
+      dynProb.TrainingEpisodesParameter.Value.Add(new IntRange(0, 30));
+      dynProb.TrainingEpisodesParameter.Value.Add(new IntRange(30, 61));
+      dynProb.NumericIntegrationStepsParameter.Value.Value = 1;
+
+      var rand = new FastRandom(1234);
+      var expressions = new string[] {
+"1.0*(y3*exp(log(y5)*0.1)) + 1.0*(y1*y1)",
+"1.0*(y1*y1) + 1.0*(y2*y2)",
+"1.0*exp(log(y2)*0.1) + 1.0*exp(log(y2)*0.1)*(y3*y3)",
+"1.0*(y1*y1)*exp(log(y5)*0.1) + 1.0*(y4*y4)",
+"1.0*(y4*y4)+1.0*(y5*y5)"
+      };
+
+      alg.CreateSolution(dynProb, expressions, 200, rand);
+      Assert.AreEqual(0.0, ((DoubleValue)alg.Results["SNMSE"].Value).Value, 1E-8);
+    }
   }
 }