using System;
using System.Collections.Generic;
using System.Text;
using System.Runtime.Serialization;
using CategoryTheory;
using DataPerformer;
using DataPerformer.Interfaces;
namespace Regression
{
/// <summary>
/// Combined selection
/// </summary>
[Serializable()]
public class CombinedSelection :CategoryObject, ISerializable, IStructuredSelection,
IStructuredSelectionConsumer, IPostSetArrow, IStructuredSelectionCollection
{
#region Fields
/// <summary>
/// Selection
/// </summary>
protected IStructuredSelection selection;
/// <summary>
/// Weights
/// </summary>
protected IStructuredSelection weights;
/// <summary>
/// All selections
/// </summary>
protected List<IStructuredSelectionCollection> selections = new List<IStructuredSelectionCollection>();
/// <summary>
/// Numbers
/// </summary>
protected int[,] num = new int[2, 2];
#endregion
#region Ctor
/// <summary>
/// Default constructor
/// </summary>
public CombinedSelection()
{
}
/// <summary>
/// Deserializable cinstructor
/// </summary>
/// <param name="info">Serialization Info</param>
/// <param name="context">Streaming Context</param>
protected CombinedSelection(SerializationInfo info, StreamingContext context)
{
num = info.GetValue("Num", num.GetType()) as int[,];
}
#endregion
#region ISerializable Members
void ISerializable.GetObjectData(SerializationInfo info, StreamingContext context)
{
info.AddValue("Num", num, num.GetType());
}
#endregion
#region IStructuredSelection Members
int IStructuredSelection.DataDimension
{
get { return selection.DataDimension; }
}
double? IStructuredSelection.this[int n]
{
get { return selection[n]; }
}
double IStructuredSelection.GetWeight(int n)
{
if (weights.DataDimension <= n)
{
return 1;
}
double? a = weights[n];
if (a == null)
{
return 1;
}
return (double)a;
}
double IStructuredSelection.GetApriorWeight(int n)
{
return selection.GetApriorWeight(n);
}
int IStructuredSelection.GetTolerance(int n)
{
return selection.GetTolerance(n);
}
void IStructuredSelection.SetTolerance(int n, int tolerance)
{
selection.SetTolerance(n, tolerance);
}
bool IStructuredSelection.HasFixedAmount
{
get { return selection.HasFixedAmount; }
}
string IStructuredSelection.Name
{
get { return selection.Name + "_" + weights.Name; }
}
#endregion
#region IStructuredSelectionConsumer Members
void IStructuredSelectionConsumer.Add(IStructuredSelectionCollection selection)
{
selections.Add(selection);
}
void IStructuredSelectionConsumer.Remove(IStructuredSelectionCollection selection)
{
selections.Remove(selection);
}
#endregion
#region IPostSetArrow Members
void IPostSetArrow.PostSetArrow()
{
post();
}
#endregion
#region IStructuredSelectionCollection Members
int IStructuredSelectionCollection.Count
{
get { return 1; }
}
IStructuredSelection IStructuredSelectionCollection.this[int i]
{
get { return this; }
}
#endregion
#region Specific Members
public int[,] Numbers
{
get
{
return num;
}
}
public IList<IStructuredSelectionCollection> Selections
{
get
{
return selections;
}
}
/*
public void Set(IStructuredSelectionCollection selection, IStructuredSelection weight, int nSel, int nWeght)
{
num[0, 0] = selections.IndexOf(selection);
num[0, 1] = nSel;
num[1, 0] = selections.IndexOf(weight);
num[1, 1] = nWeght;
post();
}
*/
public void Set(IStructuredSelectionCollection selection, int nSel, bool b)
{
int k = b ? 0 : 1;
num[k, 0] = selections.IndexOf(selection);
num[k, 1] = nSel;
post();
}
private void post()
{
if (num[0, 0] < selections.Count)
{
if (num[0, 1] < selections[num[0, 0]].Count)
{
selection = selections[num[0, 0]][num[0, 1]];
}
}
if (num[1, 0] < selections.Count)
{
if (num[1, 1] < selections[num[1, 0]].Count)
{
weights = selections[num[1, 0]][num[1, 1]];
}
}
}
#endregion
}
}
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