#region License Information /* HeuristicLab * Copyright (C) 2002-2012 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.Linq; using System.Windows.Forms; using HeuristicLab.Optimization; using HeuristicLab.PluginInfrastructure; using HeuristicLab.Problems.Instances; namespace HeuristicLab.Optimizer { public partial class CreateExperimentDialog : Form { private IOptimizer optimizer; public IOptimizer Optimizer { get { return optimizer; } set { optimizer = value; experiment = null; okButton.Enabled = optimizer != null; } } private Experiment experiment; public Experiment Experiment { get { return experiment; } } public CreateExperimentDialog() : this(null) { } public CreateExperimentDialog(IOptimizer optimizer) { InitializeComponent(); Optimizer = optimizer; experiment = null; instancesListView.Items.Clear(); instancesListView.Groups.Clear(); FillOrHideInstanceListView(); } private void FillOrHideInstanceListView() { if (Optimizer != null && optimizer is IAlgorithm) { var algorithm = (IAlgorithm)Optimizer; if (algorithm.Problem != null) { var instanceProviders = GetProblemInstanceProviders(algorithm.Problem); if (instanceProviders.Any()) { foreach (var provider in instanceProviders) { var group = new ListViewGroup(provider.Name, provider.Name); group.Tag = provider; instancesListView.Groups.Add(group); IEnumerable descriptors = ((dynamic)provider).GetDataDescriptors(); foreach (var d in descriptors) { var item = new ListViewItem(d.Name, group); item.Checked = true; item.Tag = d; instancesListView.Items.Add(item); } } instancesListView.AutoResizeColumns(ColumnHeaderAutoResizeStyle.ColumnContent); if (instancesListView.Items.Count > 0) return; } } } instancesLabel.Visible = false; instancesListView.Visible = false; Height = 130; } private IEnumerable GetProblemInstanceProviders(IProblem problem) { var consumerTypes = problem.GetType().GetInterfaces() .Where(x => x.IsGenericType && x.GetGenericTypeDefinition() == typeof(IProblemInstanceConsumer<>)); if (consumerTypes.Any()) { var instanceTypes = consumerTypes .Select(x => x.GetGenericArguments().First()) .Select(x => typeof(IProblemInstanceProvider<>).MakeGenericType(x)); foreach (var type in instanceTypes) { foreach (var provider in ApplicationManager.Manager.GetInstances(type)) yield return (IProblemInstanceProvider)provider; } } } private void createBatchRunCheckBox_CheckedChanged(object sender, EventArgs e) { repetitionsNumericUpDown.Enabled = createBatchRunCheckBox.Checked; } private void repetitionsNumericUpDown_Validated(object sender, EventArgs e) { if (repetitionsNumericUpDown.Text == string.Empty) repetitionsNumericUpDown.Text = repetitionsNumericUpDown.Value.ToString(); } private void okButton_Click(object sender, EventArgs e) { experiment = new Experiment(); if (instancesListView.CheckedItems.Count == 0) { AddOptimizer((IOptimizer)Optimizer.Clone()); } else { foreach (var item in instancesListView.CheckedItems.OfType()) { var descriptor = (IDataDescriptor)item.Tag; var provider = (IProblemInstanceProvider)item.Group.Tag; var algorithm = (IAlgorithm)Optimizer.Clone(); ((dynamic)algorithm.Problem).Load(((dynamic)provider).LoadData(descriptor)); AddOptimizer(algorithm); } } Experiment.Prepare(true); } private void AddOptimizer(IOptimizer optimizer) { if (createBatchRunCheckBox.Checked) { var batchRun = new BatchRun(); batchRun.Repetitions = (int)repetitionsNumericUpDown.Value; batchRun.Optimizer = optimizer; experiment.Optimizers.Add(batchRun); } else { experiment.Optimizers.Add(optimizer); } } } }