#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System;
using System.Collections.Generic;
using System.Linq;
using System.Windows.Forms;
using HeuristicLab.Core.Views;
using HeuristicLab.Data;
using HeuristicLab.MainForm;
using HeuristicLab.Optimization;

namespace HeuristicLab.Analysis.Statistics {
  [View("Result Correlation View")]
  [Content(typeof(RunCollection), false)]
  public sealed partial class ResultCorrelationView : ItemView {
    public ResultCorrelationView() {
      InitializeComponent();
      stringConvertibleMatrixView.Minimum = -1.0;
      stringConvertibleMatrixView.Maximum = 1.0;
    }

    public new RunCollection Content {
      get { return (RunCollection)base.Content; }
      set { base.Content = value; }
    }

    public override bool ReadOnly {
      get { return true; }
      set { /*not needed because results are always readonly */}
    }

    protected override void OnContentChanged() {
      base.OnContentChanged();
      resultComboBox.Items.Clear();

      if (Content != null) {
        UpdateResultComboBox();
      }
    }

    #region events
    protected override void RegisterContentEvents() {
      base.RegisterContentEvents();
      Content.ItemsAdded += new HeuristicLab.Collections.CollectionItemsChangedEventHandler<IRun>(Content_ItemsAdded);
      Content.ItemsRemoved += new HeuristicLab.Collections.CollectionItemsChangedEventHandler<IRun>(Content_ItemsRemoved);
      Content.CollectionReset += new HeuristicLab.Collections.CollectionItemsChangedEventHandler<IRun>(Content_CollectionReset);

      RegisterRunEvents(Content);
    }

    private void RegisterRunEvents(IEnumerable<IRun> runs) {
      foreach (IRun run in runs)
        run.Changed += new EventHandler(run_Changed);
    }

    protected override void DeregisterContentEvents() {
      base.DeregisterContentEvents();
      Content.ItemsAdded -= new HeuristicLab.Collections.CollectionItemsChangedEventHandler<IRun>(Content_ItemsAdded);
      Content.ItemsRemoved -= new HeuristicLab.Collections.CollectionItemsChangedEventHandler<IRun>(Content_ItemsRemoved);
      Content.CollectionReset -= new HeuristicLab.Collections.CollectionItemsChangedEventHandler<IRun>(Content_CollectionReset);

      DeregisterRunEvents(Content);
    }

    private void DeregisterRunEvents(IEnumerable<IRun> runs) {
      foreach (IRun run in runs)
        run.Changed -= new EventHandler(run_Changed);
    }

    private void Content_CollectionReset(object sender, HeuristicLab.Collections.CollectionItemsChangedEventArgs<IRun> e) {
      DeregisterRunEvents(e.OldItems);
      RegisterRunEvents(e.Items);
      //RebuildInfluenceDataTable();
    }

    private void Content_ItemsRemoved(object sender, HeuristicLab.Collections.CollectionItemsChangedEventArgs<IRun> e) {
      DeregisterRunEvents(e.Items);
      //RebuildInfluenceDataTable();
    }

    private void Content_ItemsAdded(object sender, HeuristicLab.Collections.CollectionItemsChangedEventArgs<IRun> e) {
      RegisterRunEvents(e.Items);
      //RebuildInfluenceDataTable();
    }

    private void run_Changed(object sender, EventArgs e) {
      if (InvokeRequired)
        this.Invoke(new EventHandler(run_Changed), sender, e);
      else {
        IRun run = (IRun)sender;
        UpdateRun(run);
      }
    }
    #endregion

    private void UpdateRun(IRun run) {
      //TODO: hacky di hack... this is baaaadddd
      RebuildCorrelationTable();
    }

    private void UpdateResultComboBox() {
      resultComboBox.Items.Clear();
      var results = (from run in Content
                     from result in run.Results
                     select result.Key).Distinct().ToArray();

      resultComboBox.Items.AddRange(results);
      if (resultComboBox.Items.Count > 0) resultComboBox.SelectedItem = resultComboBox.Items[0];
    }


    private List<string> GetRowNames() {
      string resultName = (string)resultComboBox.SelectedItem;
      var runs = Content.Where(x => x.Results.ContainsKey(resultName) && x.Visible);
      List<string> ret = new List<string>();

      foreach (var r in runs) {
        var ress = r.Results.Where(y => y.Value is DoubleValue).Select(z => z.Key);
        foreach (var s in ress) {
          if (!ret.Contains(s))
            ret.Add(s);
        }
      }

      return ret;
    }

    private void RebuildCorrelationTable() {
      string resultName = (string)resultComboBox.SelectedItem;

      var columnNames = new string[2];
      columnNames[0] = "Pearson product-moment correlation coefficient";
      columnNames[1] = "Spearman's rank correlation coefficient";
      var rowNames = GetRowNames();

      var runs = Content.Where(x => x.Results.ContainsKey(resultName) && x.Visible);

      DoubleMatrix dt = new DoubleMatrix(rowNames.Count(), columnNames.Count());
      dt.RowNames = rowNames;
      dt.ColumnNames = columnNames;

      int j = 0;
      foreach (var rowName in rowNames) {
        var resultRowVals = runs.Where(x => x.Results.ContainsKey(rowName)).Where(x => x.Results[rowName] is DoubleValue).Select(x => ((DoubleValue)x.Results[rowName]).Value);
        var resultVals = runs.Where(x => x.Results.ContainsKey(resultName)).Where(x => x.Results[resultName] is DoubleValue).Select(x => ((DoubleValue)x.Results[resultName]).Value);

        if (resultVals.Contains(double.NaN)
          || resultRowVals.Contains(double.NaN)
          || resultVals.Contains(double.NegativeInfinity)
          || resultVals.Contains(double.PositiveInfinity)
          || resultRowVals.Contains(double.NegativeInfinity)
          || resultRowVals.Contains(double.PositiveInfinity)) {
          dt[j, 0] = double.NaN;
          dt[j++, 1] = double.NaN;
        } else {
          dt[j, 0] = alglib.pearsoncorr2(resultVals.ToArray(), resultRowVals.ToArray());
          dt[j++, 1] = alglib.spearmancorr2(resultVals.ToArray(), resultRowVals.ToArray());
        }
      }

      stringConvertibleMatrixView.Content = dt;
    }

    private void calculateCorrelation_Click(object sender, EventArgs e) {
      RebuildCorrelationTable();
    }
  }
}