BotSharp/BotSharp.NLP/Models/SVM/RangeTransform.cs

246 lines
9.1 KiB
C#

/*
* SVM.NET Library
* Copyright (C) 2008 Matthew Johnson
*
* This program 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.
*
* This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
*/
using System;
using System.IO;
using System.Threading;
using System.Globalization;
namespace SVM.BotSharp.MachineLearning
{
/// <summary>
/// Class which encapsulates a range transformation.
/// </summary>
public class RangeTransform : IRangeTransform
{
/// <summary>
/// Default lower bound for scaling (-1).
/// </summary>
public const int DEFAULT_LOWER_BOUND = -1;
/// <summary>
/// Default upper bound for scaling (1).
/// </summary>
public const int DEFAULT_UPPER_BOUND = 1;
/// <summary>
/// Determines the Range transform for the provided problem. Uses the default lower and upper bounds.
/// </summary>
/// <param name="prob">The Problem to analyze</param>
/// <returns>The Range transform for the problem</returns>
public static RangeTransform Compute(Problem prob)
{
return Compute(prob, DEFAULT_LOWER_BOUND, DEFAULT_UPPER_BOUND);
}
/// <summary>
/// Determines the Range transform for the provided problem.
/// </summary>
/// <param name="prob">The Problem to analyze</param>
/// <param name="lowerBound">The lower bound for scaling</param>
/// <param name="upperBound">The upper bound for scaling</param>
/// <returns>The Range transform for the problem</returns>
public static RangeTransform Compute(Problem prob, double lowerBound, double upperBound)
{
double[] minVals = new double[prob.MaxIndex];
double[] maxVals = new double[prob.MaxIndex];
for (int i = 0; i < prob.MaxIndex; i++)
{
minVals[i] = double.MaxValue;
maxVals[i] = double.MinValue;
}
for (int i = 0; i < prob.Count; i++)
{
for (int j = 0; j < prob.X[i].Length; j++)
{
int index = prob.X[i][j].Index - 1;
double value = prob.X[i][j].Value;
minVals[index] = Math.Min(minVals[index], value);
maxVals[index] = Math.Max(maxVals[index], value);
}
}
for (int i = 0; i < prob.MaxIndex; i++)
{
if (minVals[i] == double.MaxValue || maxVals[i] == double.MinValue)
{
minVals[i] = 0;
maxVals[i] = 0;
}
}
return new RangeTransform(minVals, maxVals, lowerBound, upperBound);
}
private double[] _inputStart;
private double[] _inputScale;
private double _outputStart;
private double _outputScale;
private int _length;
/// <summary>
/// Constructor.
/// </summary>
/// <param name="minValues">The minimum values in each dimension.</param>
/// <param name="maxValues">The maximum values in each dimension.</param>
/// <param name="lowerBound">The desired lower bound for all dimensions.</param>
/// <param name="upperBound">The desired upper bound for all dimensions.</param>
public RangeTransform(double[] minValues, double[] maxValues, double lowerBound, double upperBound)
{
_length = minValues.Length;
if(maxValues.Length != _length)
throw new Exception("Number of max and min values must be equal.");
_inputStart = new double[_length];
_inputScale = new double[_length];
for (int i = 0; i < _length; i++)
{
_inputStart[i] = minValues[i];
_inputScale[i] = maxValues[i] - minValues[i];
}
_outputStart = lowerBound;
_outputScale = upperBound - lowerBound;
}
private RangeTransform(double[] inputStart, double[] inputScale, double outputStart, double outputScale, int length)
{
_inputStart = inputStart;
_inputScale = inputScale;
_outputStart = outputStart;
_outputScale = outputScale;
_length = length;
}
/// <summary>
/// Transforms the input array based upon the values provided.
/// </summary>
/// <param name="input">The input array</param>
/// <returns>A scaled array</returns>
public Node[] Transform(Node[] input)
{
Node[] output = new Node[input.Length];
for (int i = 0; i < output.Length; i++)
{
int index = input[i].Index;
double value = input[i].Value;
output[i] = new Node(index, Transform(value, index));
}
return output;
}
/// <summary>
/// Transforms this an input value using the scaling transform for the provided dimension.
/// </summary>
/// <param name="input">The input value to transform</param>
/// <param name="index">The dimension whose scaling transform should be used</param>
/// <returns>The scaled value</returns>
public double Transform(double input, int index)
{
index--;
double tmp = input - _inputStart[index];
if (_inputScale[index] == 0)
return 0;
tmp /= _inputScale[index];
tmp *= _outputScale;
return tmp + _outputStart;
}
/// <summary>
/// Writes this Range transform to a stream.
/// </summary>
/// <param name="stream">The stream to write to</param>
/// <param name="r">The range to write</param>
public static void Write(Stream stream, RangeTransform r)
{
TemporaryCulture.Start();
StreamWriter output = new StreamWriter(stream);
output.WriteLine(r._length);
output.Write(r._inputStart[0]);
for(int i=1; i<r._inputStart.Length; i++)
output.Write(" " + r._inputStart[i]);
output.WriteLine();
output.Write(r._inputScale[0]);
for (int i = 1; i < r._inputScale.Length; i++)
output.Write(" " + r._inputScale[i]);
output.WriteLine();
output.WriteLine("{0} {1}", r._outputStart, r._outputScale);
output.Flush();
TemporaryCulture.Stop();
}
/// <summary>
/// Writes this Range transform to a file. This will overwrite any previous data in the file.
/// </summary>
/// <param name="outputFile">The file to write to</param>
/// <param name="r">The Range to write</param>
public static void Write(string outputFile, RangeTransform r)
{
FileStream s = File.Open(outputFile, FileMode.Create);
try
{
Write(s, r);
}
finally
{
s.Close();
}
}
/// <summary>
/// Reads a Range transform from a file.
/// </summary>
/// <param name="inputFile">The file to read from</param>
/// <returns>The Range transform</returns>
public static RangeTransform Read(string inputFile)
{
FileStream s = File.OpenRead(inputFile);
try
{
return Read(s);
}
finally
{
s.Close();
}
}
/// <summary>
/// Reads a Range transform from a stream.
/// </summary>
/// <param name="stream">The stream to read from</param>
/// <returns>The Range transform</returns>
public static RangeTransform Read(Stream stream)
{
TemporaryCulture.Start();
StreamReader input = new StreamReader(stream);
int length = int.Parse(input.ReadLine());
double[] inputStart = new double[length];
double[] inputScale = new double[length];
string[] parts = input.ReadLine().Split();
for (int i = 0; i < length; i++)
inputStart[i] = double.Parse(parts[i]);
parts = input.ReadLine().Split();
for (int i = 0; i < length; i++)
inputScale[i] = double.Parse(parts[i]);
parts = input.ReadLine().Split();
double outputStart = double.Parse(parts[0]);
double outputScale = double.Parse(parts[1]);
TemporaryCulture.Stop();
return new RangeTransform(inputStart, inputScale, outputStart, outputScale, length);
}
}
}