#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 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;
using System.Collections.Generic;
using System.Globalization;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis;

namespace HeuristicLab.DataPreprocessing {
  [Item("PreprocessingData", "Represents data used for preprocessing.")]
  [StorableClass]
  public class PreprocessingData : NamedItem, IPreprocessingData {

    [Storable] private List<PreprocessingDataColumn> dataColumns;

    public IList<PreprocessingDataColumn> DataColumns {
      get { return dataColumns; }
    }


    #region Constructor, Cloning & Persistence
    public PreprocessingData(IDataAnalysisProblemData problemData)
      : base() {
      Name = "Preprocessing Data";

      dataColumns = new List<PreprocessingDataColumn>();
      Transformations = new List<ITransformation>();
      selection = new Dictionary<int, IList<int>>();

      Import(problemData);

      RegisterEventHandler();
    }

    protected PreprocessingData(PreprocessingData original, Cloner cloner)
      : base(original, cloner) {
      dataColumns = new List<PreprocessingDataColumn>(original.dataColumns.Select(cloner.Clone));
      TrainingPartition = cloner.Clone(original.TrainingPartition);
      TestPartition = cloner.Clone(original.TestPartition);
      Transformations = new List<ITransformation>(original.Transformations.Select(cloner.Clone));

      InputVariables = new List<string>(original.InputVariables);
      TargetVariable = original.TargetVariable;

      RegisterEventHandler();
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new PreprocessingData(this, cloner);
    }

    [StorableConstructor]
    protected PreprocessingData(bool deserializing)
      : base(deserializing) { }
    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      RegisterEventHandler();
    }

    private void RegisterEventHandler() {
      Changed += (s, e) => {
        switch (e.Type) {
          case DataPreprocessingChangedEventType.DeleteRow:
          case DataPreprocessingChangedEventType.Any:
          case DataPreprocessingChangedEventType.Transformation:
            int maxRowIndex = Math.Max(0, Rows);
            TrainingPartition.Start = Math.Min(TrainingPartition.Start, maxRowIndex);
            TrainingPartition.End = Math.Min(TrainingPartition.End, maxRowIndex);
            TestPartition.Start = Math.Min(TestPartition.Start, maxRowIndex);
            TestPartition.End = Math.Min(TestPartition.End, maxRowIndex);
            break;
        }
      };
    }
    #endregion

    #region Cells
    public bool IsCellEmpty(int columnIndex, int rowIndex) {
      return !dataColumns[columnIndex].IsValidValue(rowIndex);
    }

    public T GetCell<T>(int columnIndex, int rowIndex) {
      return dataColumns[columnIndex].TypeSwitch<T>(
        c => c[rowIndex],
        c => c[rowIndex],
        c => c[rowIndex]);
    }

    public void SetCell<T>(int columnIndex, int rowIndex, T value) {
      SaveSnapshot(DataPreprocessingChangedEventType.ChangeItem, columnIndex, rowIndex);

      for (int i = Rows; i <= rowIndex; i++)
        InsertRow(i);
      for (int i = Columns; i <= columnIndex; i++)
        InsertColumn<T>(i.ToString(), i);

      dataColumns[columnIndex].TypeSwitch<T>(value,
        (c, v) => c[rowIndex] = v,
        (c, v) => c[rowIndex] = v,
        (c, v) => c[rowIndex] = v);

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.ChangeItem, columnIndex, rowIndex);
    }

    public string GetCellAsString(int columnIndex, int rowIndex) {
      return dataColumns[columnIndex].GetValue(rowIndex);
    }

    public IEnumerable<T> GetValues<T>(int columnIndex, bool considerSelection) {
      return dataColumns[columnIndex].TypeSwitch<T>(
        c => c.GetValues(considerSelection ? selection[columnIndex] : null),
        c => c.GetValues(considerSelection ? selection[columnIndex] : null),
        c => c.GetValues(considerSelection ? selection[columnIndex] : null));
    }

    public void SetValues<T>(int columnIndex, IEnumerable<T> values) {
      SaveSnapshot(DataPreprocessingChangedEventType.ChangeColumn, columnIndex, -1);
      if (VariableHasType<T>(columnIndex)) {
        var name = dataColumns[columnIndex].Name;
        if (dataColumns[columnIndex].IsType<double>()) {
          dataColumns[columnIndex] = new DoublePreprocessingDataColumn(name, (IEnumerable<double>)values);
        } else if (dataColumns[columnIndex].IsType<string>()) {
          dataColumns[columnIndex] = new StringPreprocessingDataColumn(name, (IEnumerable<string>)values);
        } else if (dataColumns[columnIndex].IsType<DateTime>()) {
          dataColumns[columnIndex] = new DateTimePreprocessingDataColumn(name, (IEnumerable<DateTime>)values);
        } else {
          throw new ArgumentException("Unknown column type");
        }
      } else {
        throw new ArgumentException("The datatype of column " + columnIndex + " must be of type " + dataColumns[columnIndex].GetType().Name + " but was " + typeof(T).Name);
      }
      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.ChangeColumn, columnIndex, -1);
    }

    public bool SetValue(string value, int columnIndex, int rowIndex) {
      var column = dataColumns[columnIndex];
      bool successful = column.SetValue(value, rowIndex);

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.ChangeColumn, columnIndex, -1);

      return successful;
    }

    public int Columns {
      get { return dataColumns.Count; }
    }

    public int Rows {
      get { return dataColumns.Any() ? dataColumns.Max(c => c.Length) : 0; }
    }
    #endregion

    #region Rows
    public void InsertRow(int rowIndex) {
      SaveSnapshot(DataPreprocessingChangedEventType.DeleteRow, -1, rowIndex);

      foreach (var column in dataColumns) {
        column.TypeSwitch(
          c => c.Values.Insert(rowIndex, double.NaN),
          c => c.Values.Insert(rowIndex, null),
          c => c.Values.Insert(rowIndex, DateTime.MinValue));
      }

      if (TrainingPartition.Start <= rowIndex && rowIndex <= TrainingPartition.End) {
        TrainingPartition.End++;
        if (TrainingPartition.End <= TestPartition.Start) {
          TestPartition.Start++;
          TestPartition.End++;
        }
      } else if (TestPartition.Start <= rowIndex && rowIndex <= TestPartition.End) {
        TestPartition.End++;
        if (TestPartition.End <= TrainingPartition.Start) {
          TestPartition.Start++;
          TestPartition.End++;
        }
      }

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.AddRow, -1, rowIndex);
    }

    public void DeleteRow(int rowIndex) {
      DeleteRows(new[] { rowIndex });
    }
    public void DeleteRows(IEnumerable<int> rowIndices) {
      SaveSnapshot(DataPreprocessingChangedEventType.AddRow, -1, -1);

      foreach (int rowIndex in rowIndices.OrderByDescending(x => x)) {
        foreach (var column in dataColumns) {
          column.TypeSwitch(
            c => c.Values.RemoveAt(rowIndex),
            c => c.Values.RemoveAt(rowIndex),
            c => c.Values.RemoveAt(rowIndex));
        }

        if (TrainingPartition.Start <= rowIndex && rowIndex <= TrainingPartition.End) {
          TrainingPartition.End--;
          if (TrainingPartition.End <= TestPartition.Start) {
            TestPartition.Start--;
            TestPartition.End--;
          }
        } else if (TestPartition.Start <= rowIndex && rowIndex <= TestPartition.End) {
          TestPartition.End--;
          if (TestPartition.End <= TrainingPartition.Start) {
            TestPartition.Start--;
            TestPartition.End--;
          }
        }
      }

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.DeleteRow, -1, -1);
    }

    public void InsertColumn<T>(string variableName, int columnIndex) {
      SaveSnapshot(DataPreprocessingChangedEventType.DeleteColumn, columnIndex, -1);

      if (typeof(T) == typeof(double)) {
        dataColumns.Insert(columnIndex, new DoublePreprocessingDataColumn(variableName, Enumerable.Repeat<double>(double.NaN, Rows)));
      } else if (typeof(T) == typeof(string)) {
        dataColumns.Insert(columnIndex, new StringPreprocessingDataColumn(variableName, Enumerable.Repeat<string>(string.Empty, Rows)));
      } else if (typeof(T) == typeof(DateTime)) {
        dataColumns.Insert(columnIndex, new DateTimePreprocessingDataColumn(variableName, Enumerable.Repeat<DateTime>(DateTime.MinValue, Rows)));
      } else {
        throw new ArgumentException("The datatype of column " + variableName + " must be of type double, string or DateTime");
      }

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.AddColumn, columnIndex, -1);
    }

    public void DeleteColumn(int columnIndex) {
      SaveSnapshot(DataPreprocessingChangedEventType.AddColumn, columnIndex, -1);

      dataColumns.RemoveAt(columnIndex);

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.DeleteColumn, columnIndex, -1);
    }

    public void RenameColumn(int columnIndex, string name) {
      if (columnIndex < 0 || columnIndex > dataColumns.Count)
        throw new ArgumentOutOfRangeException("columnIndex");

      SaveSnapshot(DataPreprocessingChangedEventType.ChangeColumn, columnIndex, -1);

      dataColumns[columnIndex].Name = name;

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.ChangeColumn, -1, -1);
    }

    public void RenameColumns(IList<string> names) {
      if (names == null) throw new ArgumentNullException("names");
      if (names.Count != dataColumns.Count) throw new ArgumentException("number of names must match the number of columns.", "names");

      SaveSnapshot(DataPreprocessingChangedEventType.ChangeColumn, -1, -1);

      for (int i = 0; i < names.Count; i++)
        dataColumns[i].Name = names[i];

      if (!IsInTransaction)
        OnChanged(DataPreprocessingChangedEventType.ChangeColumn, -1, -1);
    }

    public bool AreAllStringColumns(IEnumerable<int> columnIndices) {
      return columnIndices.All(VariableHasType<string>);
    }
    #endregion

    #region Variables
    public IEnumerable<string> VariableNames {
      get { return dataColumns.Select(c => c.Name); }
    }

    public IEnumerable<string> GetDoubleVariableNames() {
      return dataColumns.OfType<DoublePreprocessingDataColumn>().Select(c => c.Name);
    }

    public string GetVariableName(int columnIndex) {
      return dataColumns[columnIndex].Name;
    }

    public int GetColumnIndex(string variableName) {
      return dataColumns.FindIndex(c => c.Name == variableName);
    }

    public bool VariableHasType<T>(int columnIndex) {
      return dataColumns[columnIndex].IsType<T>();
    }

    public Type GetVariableType(int columnIndex) {
      return dataColumns[columnIndex].GetValueType();
    }

    public IList<string> InputVariables { get; private set; }
    public string TargetVariable { get; private set; } // optional
    #endregion

    #region Partitions
    [Storable]
    public IntRange TrainingPartition { get; set; }
    [Storable]
    public IntRange TestPartition { get; set; }
    #endregion

    #region Transformations
    [Storable]
    public IList<ITransformation> Transformations { get; protected set; }
    #endregion

    #region Validation
    public bool Validate(string value, out string errorMessage, int columnIndex) {
      if (columnIndex < 0 || columnIndex > VariableNames.Count()) {
        throw new ArgumentOutOfRangeException("column index is out of range");
      }

      bool valid = false;
      errorMessage = string.Empty;
      if (VariableHasType<double>(columnIndex)) {
        if (string.IsNullOrWhiteSpace(value)) {
          valid = true;
        } else {
          double val;
          valid = double.TryParse(value, out val);
          if (!valid) {
            errorMessage = "Invalid Value (Valid Value Format: \"" + FormatPatterns.GetDoubleFormatPattern() + "\")";
          }
        }
      } else if (VariableHasType<string>(columnIndex)) {
        valid = value != null;
        if (!valid) {
          errorMessage = "Invalid Value (string must not be null)";
        }
      } else if (VariableHasType<DateTime>(columnIndex)) {
        DateTime date;
        valid = DateTime.TryParse(value, out date);
        if (!valid) {
          errorMessage = "Invalid Value (Valid Value Format: \"" + CultureInfo.CurrentCulture.DateTimeFormat + "\"";
        }
      } else {
        throw new ArgumentException("column " + columnIndex + " contains a non supported type.");
      }

      return valid;
    }
    #endregion

    #region Import & Export
    public void Import(IDataAnalysisProblemData problemData) {
      var dataset = problemData.Dataset;
      InputVariables = new List<string>(problemData.AllowedInputVariables);
      TargetVariable = problemData is IRegressionProblemData ? ((IRegressionProblemData)problemData).TargetVariable
        : problemData is IClassificationProblemData ? ((IClassificationProblemData)problemData).TargetVariable
        : null;

      dataColumns.Clear();
      foreach (var variableName in problemData.Dataset.VariableNames) {
        if (dataset.VariableHasType<double>(variableName)) {
          dataColumns.Add(new DoublePreprocessingDataColumn(variableName, dataset.GetDoubleValues(variableName)));
        } else if (dataset.VariableHasType<string>(variableName)) {
          dataColumns.Add(new StringPreprocessingDataColumn(variableName, dataset.GetStringValues(variableName)));
        } else if (dataset.VariableHasType<DateTime>(variableName)) {
          dataColumns.Add(new DateTimePreprocessingDataColumn(variableName, dataset.GetDateTimeValues(variableName)));
        } else {
          throw new ArgumentException("The datatype of column " + variableName + " must be of type double, string or DateTime");
        }
      }

      TrainingPartition = new IntRange(problemData.TrainingPartition.Start, problemData.TrainingPartition.End);
      TestPartition = new IntRange(problemData.TestPartition.Start, problemData.TestPartition.End);
    }

    public Dataset ExportToDataset() {
      IList<IList> values = new List<IList>();

      for (int i = 0; i < Columns; i++) {
        var doubleColumn = dataColumns[i] as DoublePreprocessingDataColumn;
        var stringColumn = dataColumns[i] as StringPreprocessingDataColumn;
        var dateTimeColumn = dataColumns[i] as DateTimePreprocessingDataColumn;
        if (doubleColumn != null) values.Add(new List<double>(doubleColumn.GetValues()));
        else if (stringColumn != null) values.Add(new List<string>(stringColumn.GetValues()));
        else if (dateTimeColumn != null) values.Add(new List<DateTime>(dateTimeColumn.GetValues()));
        else throw new InvalidOperationException("Column type not supported for export");
      }

      return new Dataset(VariableNames, values);
    }
    #endregion

    #region Selection
    [Storable]
    protected IDictionary<int, IList<int>> selection;
    public IDictionary<int, IList<int>> Selection {
      get { return selection; }
      set {
        selection = value;
        OnSelectionChanged();
      }
    }
    public void ClearSelection() {
      Selection = new Dictionary<int, IList<int>>();
    }

    public event EventHandler SelectionChanged;
    protected void OnSelectionChanged() {
      var listeners = SelectionChanged;
      if (listeners != null) listeners(this, EventArgs.Empty);
    }
    #endregion

    #region Transactions
    // Snapshot/History are not storable/cloneable on purpose
    private class Snapshot {
      public List<PreprocessingDataColumn> DataColumns { get; set; }

      public IntRange TrainingPartition { get; set; }
      public IntRange TestPartition { get; set; }
      public IList<ITransformation> Transformations { get; set; }
      public DataPreprocessingChangedEventType ChangedType { get; set; }

      public int ChangedColumn { get; set; }
      public int ChangedRow { get; set; }
    }

    public event DataPreprocessingChangedEventHandler Changed;
    protected virtual void OnChanged(DataPreprocessingChangedEventType type, int column, int row) {
      var listeners = Changed;
      if (listeners != null) listeners(this, new DataPreprocessingChangedEventArgs(type, column, row));
    }

    private const int MaxUndoDepth = 5;

    private readonly IList<Snapshot> undoHistory = new List<Snapshot>();
    private readonly Stack<DataPreprocessingChangedEventType> eventStack = new Stack<DataPreprocessingChangedEventType>();

    public bool IsInTransaction { get { return eventStack.Count > 0; } }

    private void SaveSnapshot(DataPreprocessingChangedEventType changedType, int column, int row) {
      if (IsInTransaction) return;

      var cloner = new Cloner();
      var currentSnapshot = new Snapshot {
        DataColumns = new List<PreprocessingDataColumn>(dataColumns.Select(cloner.Clone)),
        TrainingPartition = new IntRange(TrainingPartition.Start, TrainingPartition.End),
        TestPartition = new IntRange(TestPartition.Start, TestPartition.End),
        Transformations = new List<ITransformation>(Transformations),
        ChangedType = changedType,
        ChangedColumn = column,
        ChangedRow = row
      };

      if (undoHistory.Count >= MaxUndoDepth)
        undoHistory.RemoveAt(0);

      undoHistory.Add(currentSnapshot);
    }

    public bool IsUndoAvailable {
      get { return undoHistory.Count > 0; }
    }

    public void Undo() {
      if (IsUndoAvailable) {
        Snapshot previousSnapshot = undoHistory[undoHistory.Count - 1];
        dataColumns = previousSnapshot.DataColumns;
        TrainingPartition = previousSnapshot.TrainingPartition;
        TestPartition = previousSnapshot.TestPartition;
        Transformations = previousSnapshot.Transformations;
        undoHistory.Remove(previousSnapshot);
        OnChanged(previousSnapshot.ChangedType,
          previousSnapshot.ChangedColumn,
          previousSnapshot.ChangedRow);
      }
    }

    public void InTransaction(Action action, DataPreprocessingChangedEventType type = DataPreprocessingChangedEventType.Any) {
      BeginTransaction(type);
      action();
      EndTransaction();
    }

    public void BeginTransaction(DataPreprocessingChangedEventType type) {
      SaveSnapshot(type, -1, -1);
      eventStack.Push(type);
    }

    public void EndTransaction() {
      if (eventStack.Count == 0)
        throw new InvalidOperationException("There is no open transaction that can be ended.");

      var @event = eventStack.Pop();
      OnChanged(@event, -1, -1);
    }
    #endregion

    /* #region Statistics
     public T GetMin<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) {
       try {
         return dataColumns[columnIndex].TypeSwitch<T>(
           col => col.GetMin(considerSelection ? Selection[columnIndex] : null),
           col => col.GetMin(considerSelection ? Selection[columnIndex] : null),
           col => col.GetMin(considerSelection ? Selection[columnIndex] : null));
       } catch (InvalidOperationException) {
         return emptyValue;
       }
     }

     public T GetMax<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) {
       var values = GetValuesWithoutMissingValues<T>(columnIndex, considerSelection);
       return values.Any() ? values.Max() : emptyValue;
     }

     public T GetMean<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) {
       return 


       if (typeof(T) == typeof(double)) {
         var values = GetValuesWithoutMissingValues<double>(columnIndex, considerSelection);
         return values.Any() ? Convert<T>(values.Average()) : emptyValue;
       }
       if (typeof(T) == typeof(string)) {
         return Convert<T>(string.Empty);
       }
       if (typeof(T) == typeof(DateTime)) {
         var values = GetValuesWithoutMissingValues<DateTime>(columnIndex, considerSelection);
         return values.Any() ? Convert<T>(AggregateAsDouble(values, Enumerable.Average)) : emptyValue;
       }

       throw new InvalidOperationException(typeof(T) + " not supported");
     }

     public T GetMedian<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) where T : IComparable<T> {
       if (typeof(T) == typeof(double)) {// IEnumerable<double> is faster  
         var doubleValues = GetValuesWithoutMissingValues<double>(columnIndex, considerSelection);
         return doubleValues.Any() ? Convert<T>(doubleValues.Median()) : emptyValue;
       }
       var values = GetValuesWithoutMissingValues<T>(columnIndex, considerSelection);
       return values.Any() ? values.Quantile(0.5) : emptyValue;
     }

     public T GetMode<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) where T : IEquatable<T> {
       var values = GetValuesWithoutMissingValues<T>(columnIndex, considerSelection);
       return values.Any() ? values.GroupBy(x => x).OrderByDescending(g => g.Count()).Select(g => g.Key).First() : emptyValue;
     }

     public T GetStandardDeviation<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) {
       if (typeof(T) == typeof(double)) {
         var values = GetValuesWithoutMissingValues<double>(columnIndex, considerSelection);
         return values.Any() ? Convert<T>(values.StandardDeviation()) : emptyValue;
       }
       // For DateTime, std.dev / variance would have to be TimeSpan
       //if (typeof(T) == typeof(DateTime)) {
       //  var values = GetValuesWithoutMissingValues<DateTime>(columnIndex, considerSelection);
       //  return values.Any() ? Convert<T>(AggregateAsDouble(values, EnumerableStatisticExtensions.StandardDeviation)) : emptyValue;
       //}
       return default(T);
     }

     public T GetVariance<T>(int columnIndex, bool considerSelection = false, T emptyValue = default(T)) {
       if (typeof(T) == typeof(double)) {
         var values = GetValuesWithoutMissingValues<double>(columnIndex, considerSelection);
         return values.Any() ? Convert<T>(values.Variance()) : emptyValue;
       }
       // DateTime variance often overflows long, thus the corresponding DateTime is invalid
       //if (typeof(T) == typeof(DateTime)) {
       //  var values = GetValuesWithoutMissingValues<DateTime>(columnIndex, considerSelection);
       //  return values.Any() ? Convert<T>(AggregateAsDouble(values, EnumerableStatisticExtensions.Variance)) : emptyValue;
       //}
       return default(T);
     }

     public T GetQuantile<T>(double alpha, int columnIndex, bool considerSelection = false, T emptyValue = default(T)) where T : IComparable<T> {
       if (typeof(T) == typeof(double)) {// IEnumerable<double> is faster  
         var doubleValues = GetValuesWithoutMissingValues<double>(columnIndex, considerSelection);
         return doubleValues.Any() ? Convert<T>(doubleValues.Quantile(alpha)) : emptyValue;
       }
       var values = GetValuesWithoutMissingValues<T>(columnIndex, considerSelection);
       return values.Any() ? values.Quantile(alpha) : emptyValue;
     }

     public int GetDistinctValues<T>(int columnIndex, bool considerSelection = false) {
       var values = GetValuesWithoutMissingValues<T>(columnIndex, considerSelection);
       return values.GroupBy(x => x).Count();
     }

     private IEnumerable<T> GetValuesWithoutMissingValues<T>(int columnIndex, bool considerSelection) {
       return GetValues<T>(columnIndex, considerSelection).Where(x =>
         ColumnTypeSwitch<T, bool>(dataColumns[columnIndex], x,
           (c, v) => c.IsValidValue(v),
           (c, v) => c.IsValidValue(v),
           (c, v) => c.IsValidValue(v)
       ));
     }

     private static DateTime AggregateAsDouble(IEnumerable<DateTime> values, Func<IEnumerable<double>, double> func) {
       return new DateTime((long)(func(values.Select(x => (double)x.Ticks / TimeSpan.TicksPerSecond)) * TimeSpan.TicksPerSecond));
     }

     public int GetMissingValueCount() {
       int count = 0;
       for (int i = 0; i < Columns; ++i) {
         count += GetMissingValueCount(i);
       }
       return count;
     }
     public int GetMissingValueCount(int columnIndex) {
       int sum = 0;
       for (int i = 0; i < Rows; i++) {
         if (IsCellEmpty(columnIndex, i))
           sum++;
       }
       return sum;
     }
     public int GetRowMissingValueCount(int rowIndex) {
       int sum = 0;
       for (int i = 0; i < Columns; i++) {
         if (IsCellEmpty(i, rowIndex))
           sum++;
       }
       return sum;
     }
     #endregion  */
  }

  // Adapted from HeuristicLab.Common.EnumerableStatisticExtensions
  internal static class EnumerableExtensions {
    public static T Quantile<T>(this IEnumerable<T> values, double alpha) where T : IComparable<T> {
      T[] valuesArr = values.ToArray();
      int n = valuesArr.Length;
      if (n == 0) throw new InvalidOperationException("Enumeration contains no elements.");

      var pos = n * alpha;

      return Select((int)Math.Ceiling(pos) - 1, valuesArr);

    }

    private static T Select<T>(int k, T[] arr) where T : IComparable<T> {
      int i, ir, j, l, mid, n = arr.Length;
      T a;
      l = 0;
      ir = n - 1;
      for (;;) {
        if (ir <= l + 1) {
          // Active partition contains 1 or 2 elements.
          if (ir == l + 1 && arr[ir].CompareTo(arr[l]) < 0) {
            // Case of 2 elements.
            Swap(arr, l, ir);
          }
          return arr[k];
        } else {
          mid = (l + ir) >> 1; // Choose median of left, center, and right elements
          Swap(arr, mid, l + 1); // as partitioning element a. Also

          if (arr[l].CompareTo(arr[ir]) > 0) {  // rearrange so that arr[l] arr[ir] <= arr[l+1],
            Swap(arr, l, ir); // . arr[ir] >= arr[l+1]
          }

          if (arr[l + 1].CompareTo(arr[ir]) > 0) {
            Swap(arr, l + 1, ir);
          }
          if (arr[l].CompareTo(arr[l + 1]) > 0) {
            Swap(arr, l, l + 1);
          }
          i = l + 1; // Initialize pointers for partitioning.
          j = ir;
          a = arr[l + 1]; // Partitioning element.
          for (;;) { // Beginning of innermost loop.
            do i++; while (arr[i].CompareTo(a) < 0); // Scan up to find element > a.
            do j--; while (arr[j].CompareTo(a) > 0); // Scan down to find element < a.
            if (j < i) break; // Pointers crossed. Partitioning complete.
            Swap(arr, i, j);
          } // End of innermost loop.
          arr[l + 1] = arr[j]; // Insert partitioning element.
          arr[j] = a;
          if (j >= k) ir = j - 1; // Keep active the partition that contains the
          if (j <= k) l = i; // kth element.
        }
      }
    }

    private static void Swap<T>(T[] arr, int i, int j) {
      T temp = arr[i];
      arr[i] = arr[j];
      arr[j] = temp;
    }
  }
}