Changeset 9166 for branches/OaaS/HeuristicLab.Services.Optimization.Web/Mappings/tsp.cs

Timestamp:

01/15/13 15:50:53 (12 years ago)

Author:

fschoepp

Message:

#1888:

• Model: OptimizationScenario may be a tree of algorithms (and problems)
• Model: Renamed InputParameters to ProblemParameters (as they are the parameters of a problem)
• Model: Added JobExecutionDetails which contain Repetitions + Group (resource to use)
• ScenarioParser parses the new XML scenario files
• Website + Model: You are now able to add/remove rows from a table (no JavaScript involved yet)
• Website + Controller: Added repetitions (enables batch jobs) and group (resource to use) to OaaS which will be used by the controller to schedule the job
• Website: Updated templates to use new model structure
• Website + Scenarios: Added the new algorithm Benchmark Algorithm
• Controller: Added a singleton to make the (Azure/Mockup)-DAL exchangeable
• Controller: Added mockup classes for DAL + IScenarioManager
• Website/Result Page: Line Diagrams will be added via JavaScript, crawling their data using AJAX
• Website: Most configuration parameters can be set in the ServiceDefinition directly
• Added a mockup for the Membership classes: These can be used if no network connection is available or if other parts of the app shall be tested
• Scenarios: Updated TSP mappings to new xsd

File:

• branches/OaaS/HeuristicLab.Services.Optimization.Web/Mappings/tsp.cs (modified) (1 diff)

branches/OaaS/HeuristicLab.Services.Optimization.Web/Mappings/tsp.cs

@@ -4 +4 @@
 using System.Text;
 using HeuristicLab.Data;
-using HeuristicLab.Services.Optimization.ControllerService.Model; 
+using HeuristicLab.Services.Optimization.ControllerService.Model;
 using HeuristicLab.Optimization;
 using HeuristicLab.Services.Optimization.ControllerService;
 using HeuristicLab.Algorithms.GeneticAlgorithm;
 using HeuristicLab.Problems.TravelingSalesman;
-public class TSPScenarioMapper : IScenarioMapper {
-  public void MapScenario(OptimizationScenario scenario, IAlgorithm algorithm) {
-    Console.WriteLine("Mapping scenario!");
-    var ga = algorithm as GeneticAlgorithm;
-    var problem = algorithm.Problem as TravelingSalesmanProblem;
-                  
-    problem.BestKnownQuality = HLMapper.ConvertToDoubleValue(scenario.InputParameters.FindByName("BestKnownQuality"));
-    problem.BestKnownSolution = HLMapper.ConvertToPermutation(scenario.InputParameters.FindByName("BestKnownSolution"));
-    problem.Coordinates = HLMapper.ConvertToDoubleMatrix(scenario.InputParameters.FindByName("Coordinates"));
-    var evalParam = HLMapper.GetStringValue(scenario.InputParameters.FindByName("EvaluatorParameter"));
-    if (evalParam == "HeuristicLab.Problems.TravelingSalesman.TSPRoundedEuclideanPathEvaluator") {
-      problem.EvaluatorParameter.Value = new TSPRoundedEuclideanPathEvaluator();
+namespace HeuristicLab.Mappers {
+  public class TSPScenarioMapper : IScenarioMapper {
+    public void MapScenario(OptimizationScenario scenario, out IAlgorithm algorithm) {
+      Console.WriteLine("Mapping scenario!");
+      var ga = new GeneticAlgorithm();
+      var problem = new TravelingSalesmanProblem();
+      ga.Problem = problem;
+      algorithm = ga;
+
+      problem.BestKnownQuality = HLMapper.ConvertToDoubleValue(scenario.FirstAlgorithm.Problem.Parameters.FindByName("BestKnownQuality"));
+      problem.BestKnownSolution = HLMapper.ConvertToPermutation(scenario.FirstAlgorithm.Problem.Parameters.FindByName("BestKnownSolution"));
+      problem.Coordinates = HLMapper.ConvertToDoubleMatrix(scenario.FirstAlgorithm.Problem.Parameters.FindByName("Coordinates"));
+      var evalParam = HLMapper.GetStringValue(scenario.FirstAlgorithm.Problem.Parameters.FindByName("EvaluatorParameter"));
+      if (evalParam == "HeuristicLab.Problems.TravelingSalesman.TSPRoundedEuclideanPathEvaluator") {
+        problem.EvaluatorParameter.Value = new TSPRoundedEuclideanPathEvaluator();
+      }
+      else if (evalParam == "HeuristicLab.Problems.TravelingSalesman.TSPGeoPathEvaluator") {
+        problem.EvaluatorParameter.Value = new TSPGeoPathEvaluator();
+      }
+      else {
+        problem.EvaluatorParameter.Value = new TSPEuclideanPathEvaluator();
+      }
+      problem.UseDistanceMatrix = HLMapper.ConvertToBoolValue(scenario.FirstAlgorithm.Problem.Parameters.FindByName("UseDistanceMatrix"));
+      Console.WriteLine("Mapping algorithm...");
+      ga.Mutator = HLMapper.FindInItemSet<HeuristicLab.Optimization.IManipulator>(ga.MutatorParameter.ValidValues, scenario.FirstAlgorithm.Parameters.FindByName("Mutator"));
+      ga.CrossoverParameter.Value = HLMapper.FindOperator<HeuristicLab.Optimization.ICrossover>(problem, scenario.FirstAlgorithm.Parameters.FindByName("CrossoverParameter"));
+      ga.Elites = HLMapper.ConvertToIntValue(scenario.FirstAlgorithm.Parameters.FindByName("Elites"));
+      ga.MaximumGenerations = HLMapper.ConvertToIntValue(scenario.FirstAlgorithm.Parameters.FindByName("MaximumGenerations"));
+      ga.MutationProbability = HLMapper.ConvertToPercentValue(scenario.FirstAlgorithm.Parameters.FindByName("MutationProbability"));
+      ga.PopulationSize = HLMapper.ConvertToIntValue(scenario.FirstAlgorithm.Parameters.FindByName("PopulationSize"));
+      ga.Seed = HLMapper.ConvertToIntValue(scenario.FirstAlgorithm.Parameters.FindByName("Seed"));
+      ga.Selector = HLMapper.FindInItemSet<HeuristicLab.Optimization.ISelector>(ga.SelectorParameter.ValidValues, scenario.FirstAlgorithm.Parameters.FindByName("Selector"));
+      ga.SetSeedRandomly = HLMapper.ConvertToBoolValue(scenario.FirstAlgorithm.Parameters.FindByName("SetSeedRandomly"));
     }
-    else if (evalParam == "HeuristicLab.Problems.TravelingSalesman.TSPGeoPathEvaluator") {
-      problem.EvaluatorParameter.Value = new TSPGeoPathEvaluator();
-    }
-    else {
-      problem.EvaluatorParameter.Value = new TSPEuclideanPathEvaluator();
-    }
-    problem.UseDistanceMatrix = HLMapper.ConvertToBoolValue(scenario.InputParameters.FindByName("UseDistanceMatrix"));
-    Console.WriteLine("Mapping algorithm...");
-    ga.Mutator = HLMapper.FindInItemSet<HeuristicLab.Optimization.IManipulator>(ga.MutatorParameter.ValidValues, scenario.AlgorithmParameters.FindByName("Mutator"));
-    ga.CrossoverParameter.Value = HLMapper.FindOperator<HeuristicLab.Optimization.ICrossover>(problem, scenario.AlgorithmParameters.FindByName("CrossoverParameter"));
-    ga.Elites = HLMapper.ConvertToIntValue(scenario.AlgorithmParameters.FindByName("Elites"));
-    ga.MaximumGenerations = HLMapper.ConvertToIntValue(scenario.AlgorithmParameters.FindByName("MaximumGenerations"));
-    ga.MutationProbability = HLMapper.ConvertToPercentValue(scenario.AlgorithmParameters.FindByName("MutationProbability"));                
-    ga.PopulationSize = HLMapper.ConvertToIntValue(scenario.AlgorithmParameters.FindByName("PopulationSize"));
-    ga.Seed = HLMapper.ConvertToIntValue(scenario.AlgorithmParameters.FindByName("Seed"));
-    ga.Selector = HLMapper.FindInItemSet<HeuristicLab.Optimization.ISelector>(ga.SelectorParameter.ValidValues, scenario.AlgorithmParameters.FindByName("Selector"));
-    ga.SetSeedRandomly = HLMapper.ConvertToBoolValue(scenario.AlgorithmParameters.FindByName("SetSeedRandomly"));
   }
 }