source: branches/DataPreprocessing/HeuristicLab.DataPreprocessing/3.3/Implementations/ChartLogic.cs @ 10914

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2014 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.Drawing;
using HeuristicLab.Analysis;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Common;

namespace HeuristicLab.DataPreprocessing {

  public class ChartLogic : IChartLogic {
    private const int MAX_DISTINCT_VALUES_FOR_CLASSIFCATION = 20;
    private ITransactionalPreprocessingData preprocessingData;

    public ChartLogic(ITransactionalPreprocessingData preprocessingData) {
      this.preprocessingData = preprocessingData;
    }

    #region IChartLogic Members

    public DataRow CreateDataRow(string variableName, DataRowVisualProperties.DataRowChartType chartType) {
      IList<double> values = preprocessingData.GetValues<double>(variableName);
      DataRow row = new DataRow(variableName, "", values);
      row.VisualProperties.ChartType = chartType;
      return row;
    }

    public DataRow CreateDataRowRange(string variableName,int start, int end, DataRowVisualProperties.DataRowChartType chartType) {
      IList<double> values = preprocessingData.GetValues<double>(variableName);
      IList<double> valuesRange = new List<double>();
      for (int i = 0; i < values.Count; i++) {
        if (i >= start && i <= end)
          valuesRange.Add(values[i]);
        else
          valuesRange.Add(Double.NaN);
      }

      DataRow row = new DataRow(variableName, "", valuesRange);
      row.VisualProperties.ChartType = chartType;
      return row;
    }

    public IEnumerable<double> GetVariableValues(string variableName) {
      return preprocessingData.GetValues<double>(preprocessingData.GetColumnIndex(variableName));
    }

    public IEnumerable<string> GetVariableNames() {
      List<string> doubleVariableNames = new List<string>();

      //only return variable names from type double
      foreach (string variableName in preprocessingData.VariableNames) {
        if (preprocessingData.IsType<double>(preprocessingData.GetColumnIndex(variableName)))
          doubleVariableNames.Add(variableName);
      }

      return doubleVariableNames;
    }

    public IEnumerable<string> GetVariableNamesForHistogramClassification() {
      List<string> doubleVariableNames = new List<string>();

      //only return variable names from type double
      foreach (string variableName in preprocessingData.VariableNames)
      {
        int columnIndex           = preprocessingData.GetColumnIndex(variableName);
        bool isDouble             = preprocessingData.IsType<double>(columnIndex);
        double distinctValueCount = preprocessingData.GetValues<double>(columnIndex).GroupBy(x => x).Count();
        bool distinctValuesOk     = distinctValueCount <= MAX_DISTINCT_VALUES_FOR_CLASSIFCATION;

        if (isDouble && distinctValuesOk)
              doubleVariableNames.Add(variableName);
      }

      return doubleVariableNames;
    }

    public ICheckedItemList<StringValue> CreateVariableItemList() {
      ICheckedItemList<StringValue> itemList = new CheckedItemList<StringValue>();
      foreach (string name in GetVariableNames()) {
        itemList.Add(new StringValue(name), true);
      }
      return new ReadOnlyCheckedItemList<StringValue>(itemList);
    }

    public event DataPreprocessingChangedEventHandler Changed {
      add { preprocessingData.Changed += value; }
      remove { preprocessingData.Changed -= value; }
    }

    public event EventHandler SelectionChanged {
      add { preprocessingData.SelectionChanged += value; }
      remove { preprocessingData.SelectionChanged -= value; }
    }

    public string GetVariableNameByIndex(int index) {
      return preprocessingData.GetVariableName(index);
    }


    public List<DataRow> CreateAllDataRows(DataRowVisualProperties.DataRowChartType chartType) {
      List<DataRow> dataRows = new List<DataRow>();
      foreach (var name in GetVariableNames())
        dataRows.Add(CreateDataRow(name, chartType));
      return dataRows;
    }

    public List<DataRow> CreateAllSelectedDataRows(DataRowVisualProperties.DataRowChartType chartType) {
      List<DataRow> dataRows = new List<DataRow>();
      foreach (var name in GetVariableNames()) {
        DataRow row = CreateSelectedDataRow(name, chartType);
        if(row != null)
          dataRows.Add(row);
  }
      return dataRows;
    }

    public DataRow CreateSelectedDataRow(string variableName, DataRowVisualProperties.DataRowChartType chartType) {
      
      IDictionary<int,IList<int>> selection = preprocessingData.GetSelection();
      int variableIndex = preprocessingData.GetColumnIndex(variableName);

      if (selection.Keys.Contains(variableIndex))
      {
        List<int> selectedIndices = new List<int>(selection[variableIndex]);
        //need selection with more than 1 value
        if(selectedIndices.Count < 2)
          return null;

        selectedIndices.Sort();
        int start = selectedIndices[0];     
        int end = selectedIndices[selectedIndices.Count-1];

        DataRow rowSelect = CreateDataRowRange(variableName, start, end, chartType);
        return rowSelect;
      }
      else
       return null;
    }

    public ScatterPlot CreateScatterPlot(string name, string variableNameX, string variableNameY) {
      ScatterPlot scatterPlot = new ScatterPlot(name, "");
      

      List<double> xValues = GetVariableValues(variableNameX).ToList();
      List<double> yValues = GetVariableValues(variableNameY).ToList();

      List<Point2D<double>> points = new List<Point2D<double>>();

      for( int i = 0; i < xValues.Count; i++)
      {
          Point2D<double> point = new Point2D<double>(xValues[i],yValues[i]);
          points.Add(point);
      }

      ScatterPlotDataRow scdr = new ScatterPlotDataRow(variableNameX + " - " + variableNameY,"",points);
      scatterPlot.Rows.Add(scdr);
      return scatterPlot;
    }

    #endregion
  }
}