#region License Information
/* HeuristicLab
* Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Text;
using System.Windows.Forms;
using HeuristicLab.PluginInfrastructure;
using System.Net;
using System.ServiceModel;
using HeuristicLab.CEDMA.DB.Interfaces;
using HeuristicLab.CEDMA.DB;
using System.ServiceModel.Description;
using System.Linq;
using HeuristicLab.CEDMA.Core;
using HeuristicLab.GP.StructureIdentification;
using HeuristicLab.Data;
using HeuristicLab.Grid;
using System.Diagnostics;
using HeuristicLab.Core;
using System.Threading;
using HeuristicLab.Modeling;
namespace HeuristicLab.CEDMA.Server {
public abstract class ExecuterBase : IExecuter {
private IDispatcher dispatcher;
protected IDispatcher Dispatcher {
get { return dispatcher; }
}
private IStore store;
private int maxActiveJobs;
public int MaxActiveJobs {
get { return maxActiveJobs; }
set {
if (value < 0) throw new ArgumentException("Only positive values are allowed for MaxActiveJobs");
maxActiveJobs = value;
}
}
public ExecuterBase(IDispatcher dispatcher, IStore store) {
maxActiveJobs = 10;
this.dispatcher = dispatcher;
this.store = store;
}
public void Start() {
new Thread(StartJobs).Start();
}
protected abstract void StartJobs();
protected void SetResults(IScope src, IScope target) {
foreach (IVariable v in src.Variables) {
target.AddVariable(v);
}
foreach (IScope subScope in src.SubScopes) {
target.AddSubScope(subScope);
}
foreach (KeyValuePair alias in src.Aliases) {
target.AddAlias(alias.Key, alias.Value);
}
}
protected void StoreResults(IAlgorithm finishedAlgorithm) {
Entity modelEntity = new Entity(Ontology.CedmaNameSpace + Guid.NewGuid());
IModel model = finishedAlgorithm.Model;
List statements = new List();
statements.Add(new Statement(modelEntity, Ontology.InstanceOf, Ontology.TypeModel));
statements.Add(new Statement(modelEntity, Ontology.TargetVariable, new Literal(model.TargetVariable)));
statements.Add(new Statement(modelEntity, Ontology.Name, new Literal(finishedAlgorithm.Description)));
statements.Add(new Statement(modelEntity, Ontology.TrainingMeanSquaredError, new Literal(model.TrainingMeanSquaredError)));
statements.Add(new Statement(modelEntity, Ontology.ValidationMeanSquaredError, new Literal(model.ValidationMeanSquaredError)));
statements.Add(new Statement(modelEntity, Ontology.TestMeanSquaredError, new Literal(model.TestMeanSquaredError)));
statements.Add(new Statement(modelEntity, Ontology.TrainingCoefficientOfDetermination, new Literal(model.TrainingCoefficientOfDetermination)));
statements.Add(new Statement(modelEntity, Ontology.ValidationCoefficientOfDetermination, new Literal(model.ValidationCoefficientOfDetermination)));
statements.Add(new Statement(modelEntity, Ontology.TestCoefficientOfDetermination, new Literal(model.TestCoefficientOfDetermination)));
statements.Add(new Statement(modelEntity, Ontology.TrainingVarianceAccountedFor, new Literal(model.TrainingVarianceAccountedFor)));
statements.Add(new Statement(modelEntity, Ontology.ValidationVarianceAccountedFor, new Literal(model.ValidationVarianceAccountedFor)));
statements.Add(new Statement(modelEntity, Ontology.TestVarianceAccountedFor, new Literal(model.TestVarianceAccountedFor)));
statements.Add(new Statement(modelEntity, Ontology.TrainingMeanAbsolutePercentageError, new Literal(model.TrainingMeanAbsolutePercentageError)));
statements.Add(new Statement(modelEntity, Ontology.ValidationMeanAbsolutePercentageError, new Literal(model.ValidationMeanAbsolutePercentageError)));
statements.Add(new Statement(modelEntity, Ontology.TestMeanAbsolutePercentageError, new Literal(model.TestMeanAbsolutePercentageError)));
statements.Add(new Statement(modelEntity, Ontology.TrainingMeanAbsolutePercentageOfRangeError, new Literal(model.TrainingMeanAbsolutePercentageOfRangeError)));
statements.Add(new Statement(modelEntity, Ontology.ValidationMeanAbsolutePercentageOfRangeError, new Literal(model.ValidationMeanAbsolutePercentageOfRangeError)));
statements.Add(new Statement(modelEntity, Ontology.TestMeanAbsolutePercentageOfRangeError, new Literal(model.TestMeanAbsolutePercentageOfRangeError)));
for (int i = 0; i < finishedAlgorithm.Dataset.Columns; i++) {
try {
string variableName = finishedAlgorithm.Dataset.GetVariableName(i);
double qualImpact = model.GetVariableQualityImpact(variableName);
double evalImpact = model.GetVariableEvaluationImpact(variableName);
Entity inputVariableEntity = new Entity(Ontology.CedmaNameSpace + Guid.NewGuid());
statements.Add(new Statement(inputVariableEntity, Ontology.InstanceOf, Ontology.TypeVariableImpact));
statements.Add(new Statement(modelEntity, Ontology.HasInputVariable, inputVariableEntity));
statements.Add(new Statement(inputVariableEntity, Ontology.EvaluationImpact, new Literal(evalImpact)));
statements.Add(new Statement(inputVariableEntity, Ontology.QualityImpact, new Literal(qualImpact)));
statements.Add(new Statement(inputVariableEntity, Ontology.Name, new Literal(variableName)));
}
catch (ArgumentException) {
// ignore
}
}
byte[] serializedModel = PersistenceManager.SaveToGZip(model.Data);
statements.Add(new Statement(modelEntity, Ontology.SerializedData, new Literal(Convert.ToBase64String(serializedModel))));
store.AddRange(statements);
}
public abstract string[] GetJobs();
}
}