#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2010 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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Threading;
using HeuristicLab.Algorithms.GeneticAlgorithm;
using HeuristicLab.Optimization;
using HeuristicLab.Problems.TestFunctions;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace HeuristicLab.Clients.Hive.Tests {
  [TestClass]
  public class ExperimentManagerTests {
    private TestContext testContextInstance;
    public TestContext TestContext {
      get { return testContextInstance; }
      set { testContextInstance = value; }
    }

    [ClassInitialize]
    public static void MyClassInitialize(TestContext testContext) {
      //ServiceLocator.Instance = new MockServiceLocator();
    }

    [TestMethod]
    public void TestExperimentUpload() {
      var rhc = new RefreshableHiveExperiment();
      var optimizer = CreateOptimizer();
      rhc.HiveJobs.Add(new OptimizerHiveJob(optimizer));
      
      HiveClient.StartExperiment((Exception ex) => TestContext.WriteLine(ex.ToString()), rhc, new CancellationToken());

      while (rhc.ExecutionState != Core.ExecutionState.Stopped) {
        Thread.Sleep(500);
      }
    }

    private IOptimizer CreateOptimizer() {
      var ga = new GeneticAlgorithm();
      ga.Engine = new SequentialEngine.SequentialEngine();
      ga.Problem = new SingleObjectiveTestFunctionProblem();
      return ga;
    }
  }
}