#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2011 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.Drawing;
using System.Linq;
using System.Windows.Forms;
using System.Windows.Forms.DataVisualization.Charting;
using HeuristicLab.Common;
using HeuristicLab.MainForm;
using HeuristicLab.MainForm.WindowsForms;

namespace HeuristicLab.Problems.DataAnalysis.Views {
  [View("Line Chart")]
  [Content(typeof(ITimeSeriesPrognosisSolution))]
  public partial class TimeSeriesPrognosisSolutionLineChartView : DataAnalysisSolutionEvaluationView {
    private const string TARGETVARIABLE_SERIES_NAME = "Target Variable";
    private const string PROGNOSEDVALUES_TRAINING_SERIES_NAME = "Prognosed Values (training)";
    private const string PROGNOSEDVALUES_TEST_SERIES_NAME = "Prognosed Values (test)";
    private const string PROGNOSEDVALUES_ALL_SERIES_NAME = "Prognosed Values (all samples)";
    private int testPrognosisStart;

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

    public TimeSeriesPrognosisSolutionLineChartView()
      : base() {
      InitializeComponent();
      //configure axis
      this.chart.CustomizeAllChartAreas();
      this.chart.ChartAreas[0].CursorX.IsUserSelectionEnabled = true;
      this.chart.ChartAreas[0].CursorX.Interval = 1;
      this.chart.ChartAreas[0].AxisX.ScaleView.Zoomable = true;
      this.chart.ChartAreas[0].AxisX.IsStartedFromZero = true;

      this.chart.ChartAreas[0].CursorY.IsUserSelectionEnabled = true;
      this.chart.ChartAreas[0].CursorY.Interval = 0.1;
      this.chart.ChartAreas[0].AxisY.ScaleView.Zoomable = true;

      this.chart.SuppressExceptions = false;
    }

    private void RedrawChart() {
      this.chart.Series.Clear();
      if (Content != null) {
        this.chart.ChartAreas[0].AxisX.Minimum = 0;
        this.chart.ChartAreas[0].AxisX.Maximum = Content.ProblemData.Dataset.Rows - 1;
        string targetVariable = Content.ProblemData.TargetVariable;

        this.chart.Series.Add(TARGETVARIABLE_SERIES_NAME);
        this.chart.Series[TARGETVARIABLE_SERIES_NAME].LegendText = targetVariable;
        this.chart.Series[TARGETVARIABLE_SERIES_NAME].ChartType = SeriesChartType.FastLine;
        AddDataPoints(chart.Series[TARGETVARIABLE_SERIES_NAME].Points, Enumerable.Range(0, Content.ProblemData.Dataset.Rows), Content.ProblemData.Dataset.GetDoubleValues(targetVariable));
        //this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.DataBindXY(Enumerable.Range(0, Content.ProblemData.Dataset.Rows).ToArray(),
        //  Content.ProblemData.Dataset.GetDoubleValues(targetVariable).ToArray());

        this.chart.Series.Add(PROGNOSEDVALUES_TRAINING_SERIES_NAME);
        this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].LegendText = PROGNOSEDVALUES_TRAINING_SERIES_NAME;
        this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].ChartType = SeriesChartType.FastLine;
        if (prognosedValuesCheckbox.Checked) {
          //this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points
          //  .DataBindXY(Content.ProblemData.TrainingIndices.ToArray(),
          //              Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingIndices.Count().ToEnumerable()).First().ToArray());
          AddDataPoints(chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points, Content.ProblemData.TrainingIndices, Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingIndices.Count().ToEnumerable()).First());
        } else {
          //this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points
          //  .DataBindXY(Content.ProblemData.TrainingIndices.ToArray(),
          //              Content.GetPrognosedValues(Content.ProblemData.TrainingIndices, Enumerable.Repeat(1, Content.ProblemData.TrainingIndices.Count())).SelectMany(x => x).ToArray());
          AddDataPoints(chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points, Content.ProblemData.TrainingIndices, Content.GetPrognosedValues(Content.ProblemData.TrainingIndices, Enumerable.Repeat(1, Content.ProblemData.TrainingIndices.Count())).SelectMany(x => x));
        }
        this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Tag = Content;
        this.chart.DataManipulator.InsertEmptyPoints(1, IntervalType.Number, PROGNOSEDVALUES_TRAINING_SERIES_NAME);
        this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.BorderWidth = 0;
        this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].EmptyPointStyle.MarkerStyle = MarkerStyle.None;


        this.chart.Series.Add(PROGNOSEDVALUES_TEST_SERIES_NAME);
        this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].LegendText = PROGNOSEDVALUES_TEST_SERIES_NAME;
        this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].ChartType = SeriesChartType.FastLine;
        if (prognosedValuesCheckbox.Checked) {
          //this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points
          //  .DataBindXY(Content.ProblemData.TestIndices.ToArray(),
          //              Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestIndices.Count().ToEnumerable()).First().ToArray());
          AddDataPoints(chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points, Content.ProblemData.TestIndices, Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestIndices.Count().ToEnumerable()).First());
        } else {
          //this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points
          //  .DataBindXY(Content.ProblemData.TestIndices.ToArray(),
          //              Content.GetPrognosedValues(Content.ProblemData.TestIndices, Enumerable.Repeat(1, Content.ProblemData.TestIndices.Count())).SelectMany(x => x).ToArray());
          AddDataPoints(chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points, Content.ProblemData.TestIndices, Content.GetPrognosedValues(Content.ProblemData.TestIndices, Enumerable.Repeat(1, Content.ProblemData.TestIndices.Count())).SelectMany(x => x));
        }
        this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Tag = Content;
        UpdateCursorInterval();
        this.UpdateStripLines();
      }
      chart.Refresh();
    }

    private void AddDataPoints(DataPointCollection points, IEnumerable<int> xValues, IEnumerable<double> yValues) {
      var xValuesEnumerator = xValues.GetEnumerator();
      var yValuesEnumerator = yValues.GetEnumerator();

      while (xValuesEnumerator.MoveNext() & yValuesEnumerator.MoveNext()) {
        var xValue = xValuesEnumerator.Current;
        var yValue = yValuesEnumerator.Current;

        if (yValue < (double)decimal.MaxValue && yValue > (double)decimal.MinValue) {
          DataPoint dataPoint = new DataPoint(xValue, yValue);
          points.Add(dataPoint);
        }
      }
    }

    private void UpdateCursorInterval() {
      var estimatedValues = this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
      var targetValues = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Select(x => x.YValues[0]).DefaultIfEmpty(1.0);
      double estimatedValuesRange = estimatedValues.Max() - estimatedValues.Min();
      double targetValuesRange = targetValues.Max() - targetValues.Min();
      double interestingValuesRange = Math.Min(Math.Max(targetValuesRange, 1.0), Math.Max(estimatedValuesRange, 1.0));
      double digits = (int)Math.Log10(interestingValuesRange) - 3;
      double yZoomInterval = Math.Max(Math.Pow(10, digits), 10E-5);
      this.chart.ChartAreas[0].CursorY.Interval = yZoomInterval;
    }

    #region events
    protected override void RegisterContentEvents() {
      base.RegisterContentEvents();
      Content.ModelChanged += new EventHandler(Content_ModelChanged);
      Content.ProblemDataChanged += new EventHandler(Content_ProblemDataChanged);
    }
    protected override void DeregisterContentEvents() {
      base.DeregisterContentEvents();
      Content.ModelChanged -= new EventHandler(Content_ModelChanged);
      Content.ProblemDataChanged -= new EventHandler(Content_ProblemDataChanged);
    }

    protected override void OnContentChanged() {
      base.OnContentChanged();
      RedrawChart();
    }

    private void Content_ProblemDataChanged(object sender, EventArgs e) {
      RedrawChart();
    }
    private void Content_ModelChanged(object sender, EventArgs e) {
      RedrawChart();
    }

    private void targetVariableComboBox_SelectedIndexChanged(object sender, EventArgs e) {
      RedrawChart();
    }
    private void prognosedValuesCheckbox_CheckedChanged(object sender, EventArgs e) {
      RedrawChart();
    }

    private void Chart_MouseDoubleClick(object sender, MouseEventArgs e) {
      HitTestResult result = chart.HitTest(e.X, e.Y);
      if (result.ChartArea != null && (result.ChartElementType == ChartElementType.PlottingArea ||
                                       result.ChartElementType == ChartElementType.Gridlines) ||
                                       result.ChartElementType == ChartElementType.StripLines) {
        foreach (var axis in result.ChartArea.Axes)
          axis.ScaleView.ZoomReset(int.MaxValue);
      }
    }
    #endregion

    private void UpdateStripLines() {
      this.chart.ChartAreas[0].AxisX.StripLines.Clear();

      int[] attr = new int[Content.ProblemData.Dataset.Rows + 1]; // add a virtual last row that is again empty to simplify loop further down
      foreach (var row in Content.ProblemData.TrainingIndices) {
        attr[row] += 1;
      }
      foreach (var row in Content.ProblemData.TestIndices) {
        attr[row] += 2;
      }
      int start = 0;
      int curAttr = attr[start];
      for (int row = 0; row < attr.Length; row++) {
        if (attr[row] != curAttr) {
          switch (curAttr) {
            case 0: break;
            case 1:
              this.CreateAndAddStripLine("Training", start, row, Color.FromArgb(40, Color.Green), Color.Transparent);
              break;
            case 2:
              this.CreateAndAddStripLine("Test", start, row, Color.FromArgb(40, Color.Red), Color.Transparent);
              break;
            case 3:
              this.CreateAndAddStripLine("Training and Test", start, row, Color.FromArgb(40, Color.Green), Color.FromArgb(40, Color.Red), ChartHatchStyle.WideUpwardDiagonal);
              break;
            default: throw new NotSupportedException();
          }
          curAttr = attr[row];
          start = row;
        }
      }
    }

    private void CreateAndAddStripLine(string title, int start, int end, Color color, Color secondColor, ChartHatchStyle hatchStyle = ChartHatchStyle.None) {
      StripLine stripLine = new StripLine();
      stripLine.BackColor = color;
      stripLine.BackSecondaryColor = secondColor;
      stripLine.BackHatchStyle = hatchStyle;
      stripLine.Text = title;
      stripLine.Font = new Font("Times New Roman", 12, FontStyle.Bold);
      // strip range is [start .. end] inclusive, but we evaluate [start..end[ (end is exclusive)
      // the strip should be by one longer (starting at start - 0.5 and ending at end + 0.5)
      stripLine.StripWidth = end - start;
      stripLine.IntervalOffset = start - 0.5; // start slightly to the left of the first point to clearly indicate the first point in the partition
      this.chart.ChartAreas[0].AxisX.StripLines.Add(stripLine);
    }

    private void ToggleSeriesData(Series series) {
      if (series.Points.Count > 0) {  //checks if series is shown
        if (this.chart.Series.Any(s => s != series && s.Points.Count > 0)) {
          series.Points.Clear();
        }
      } else if (Content != null) {
        IEnumerable<int> Indices = null;
        IEnumerable<double> predictedValues = null;

        switch (series.Name) {
          case PROGNOSEDVALUES_TRAINING_SERIES_NAME:
            Indices = Content.ProblemData.TrainingIndices.ToArray();
            predictedValues = Content.GetPrognosedValues(Content.ProblemData.TrainingIndices.Take(1), Content.ProblemData.TrainingPartition.Size.ToEnumerable()).First();
            break;
          case PROGNOSEDVALUES_TEST_SERIES_NAME:
            testPrognosisStart = Content.ProblemData.TestPartition.Start;
            Indices = Content.ProblemData.TestIndices.ToArray();
            predictedValues = Content.GetPrognosedValues(Content.ProblemData.TestIndices.Take(1), Content.ProblemData.TestPartition.Size.ToEnumerable()).First();
            break;
        }
        series.Points.DataBindXY(Indices, predictedValues);
        chart.DataManipulator.InsertEmptyPoints(1, IntervalType.Number, series.Name);
        chart.Legends[series.Legend].ForeColor = Color.Black;
        UpdateCursorInterval();
        chart.Refresh();
      }
    }

    private void chart_MouseMove(object sender, MouseEventArgs e) {
      //HitTestResult result = chart.HitTest(e.X, e.Y);
      //if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME)
      //  Cursor = Cursors.Hand;
      //else
      //  Cursor = Cursors.Default;
    }

    private void chart_MouseDown(object sender, MouseEventArgs e) {
      //HitTestResult result = chart.HitTest(e.X, e.Y);
      //if (result.ChartElementType == ChartElementType.LegendItem && result.Series.Name != TARGETVARIABLE_SERIES_NAME) {
      //  ToggleSeriesData(result.Series);
      //} else if (result.ChartElementType == ChartElementType.Axis || result.ChartElementType == ChartElementType.AxisLabels ||
      //  result.ChartElementType == ChartElementType.TickMarks) {
      //  chart.ChartAreas[0].CursorX.SetCursorPixelPosition(new Point(e.X, e.Y), true);
      //  int pos = (int)Math.Round(chart.ChartAreas[0].CursorX.Position);
      //  if (pos >= Content.ProblemData.TestPartition.Start && pos < Content.ProblemData.TestPartition.End) {
      //    testPrognosisStart = pos;
      //    RedrawChart();
      //  }
      //}
    }

    private void chart_CustomizeLegend(object sender, CustomizeLegendEventArgs e) {
      if (chart.Series.Count != 4) return;
      e.LegendItems[0].Cells[1].ForeColor = this.chart.Series[TARGETVARIABLE_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
      e.LegendItems[1].Cells[1].ForeColor = this.chart.Series[PROGNOSEDVALUES_TRAINING_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
      e.LegendItems[2].Cells[1].ForeColor = this.chart.Series[PROGNOSEDVALUES_TEST_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
      e.LegendItems[3].Cells[1].ForeColor = this.chart.Series[PROGNOSEDVALUES_ALL_SERIES_NAME].Points.Count == 0 ? Color.Gray : Color.Black;
    }
  }
}