Marcus Cuda
11 years ago
4 changed files with 319 additions and 0 deletions
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// <copyright file="MovingStatistics.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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//
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// Copyright (c) 2009-2015 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using System; |
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using System.Collections.Generic; |
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using MathNet.Numerics.Properties; |
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namespace MathNet.Numerics.Statistics |
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{ |
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/// <summary>
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/// Running statistics over a window of data, allows updating by adding values.
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/// </summary>
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public class MovingStatistics |
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{ |
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readonly double[] _oldValues; |
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readonly int _windowSize; |
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int _lastIndex; |
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double _m1; |
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double _m2; |
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double _m3; |
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double _m4; |
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double _max = double.NegativeInfinity; |
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double _min = double.PositiveInfinity; |
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public MovingStatistics(int windowSize) |
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{ |
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if (windowSize < 1) |
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{ |
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throw new ArgumentException(string.Format(Resources.ArgumentMustBePositive), "windowSize"); |
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} |
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_windowSize = windowSize; |
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_oldValues = new double[_windowSize]; |
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} |
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public MovingStatistics(int windowSize, IEnumerable<double> values) : this(windowSize) |
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{ |
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PushRange(values); |
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} |
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public int WindowSize |
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{ |
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get { return _windowSize; } |
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} |
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/// <summary>
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/// Gets the total number of samples.
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/// </summary>
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public long Count { get; private set; } |
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/// <summary>
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/// Returns the minimum value in the sample data.
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/// Returns NaN if data is empty or if any entry is NaN.
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/// </summary>
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public double Minimum |
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{ |
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get { return Count > 0 ? _min : double.NaN; } |
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} |
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/// <summary>
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/// Returns the maximum value in the sample data.
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/// Returns NaN if data is empty or if any entry is NaN.
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/// </summary>
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public double Maximum |
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{ |
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get { return Count > 0 ? _max : double.NaN; } |
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} |
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/// <summary>
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/// Evaluates the sample mean, an estimate of the population mean.
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/// Returns NaN if data is empty or if any entry is NaN.
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/// </summary>
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public double Mean |
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{ |
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get { return Count > 0 ? _m1 : double.NaN; } |
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} |
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/// <summary>
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/// Estimates the unbiased population variance from the provided samples.
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/// On a dataset of size N will use an N-1 normalizer (Bessel's correction).
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/// Returns NaN if data has less than two entries or if any entry is NaN.
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/// </summary>
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public double Variance |
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{ |
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get { return Count < 2 ? double.NaN : _m2/(Count - 1); } |
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} |
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/// <summary>
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/// Evaluates the variance from the provided full population.
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/// On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset.
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/// Returns NaN if data is empty or if any entry is NaN.
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/// </summary>
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public double PopulationVariance |
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{ |
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get { return Count < 2 ? double.NaN : _m2/Count; } |
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} |
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/// <summary>
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/// Estimates the unbiased population standard deviation from the provided samples.
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/// On a dataset of size N will use an N-1 normalizer (Bessel's correction).
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/// Returns NaN if data has less than two entries or if any entry is NaN.
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/// </summary>
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public double StandardDeviation |
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{ |
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get { return Count < 2 ? double.NaN : Math.Sqrt(_m2/(Count - 1)); } |
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} |
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/// <summary>
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/// Evaluates the standard deviation from the provided full population.
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/// On a dataset of size N will use an N normalizer and would thus be biased if applied to a subset.
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/// Returns NaN if data is empty or if any entry is NaN.
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/// </summary>
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public double PopulationStandardDeviation |
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{ |
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get { return Count < 2 ? double.NaN : Math.Sqrt(_m2/Count); } |
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} |
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/* /// <summary>
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/// Estimates the unbiased population skewness from the provided samples.
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/// Uses a normalizer (Bessel's correction; type 2).
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/// Returns NaN if data has less than three entries or if any entry is NaN.
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/// </summary>
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public double Skewness |
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{ |
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get { return Count < 3 ? double.NaN : (Count*_m3*Math.Sqrt(_m2/(Count - 1))/(_m2*_m2*(Count - 2)))*(Count - 1); } |
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} |
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/// <summary>
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/// Evaluates the population skewness from the full population.
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/// Does not use a normalizer and would thus be biased if applied to a subset (type 1).
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/// Returns NaN if data has less than two entries or if any entry is NaN.
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/// </summary>
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public double PopulationSkewness |
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{ |
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get { return Count < 2 ? double.NaN : Math.Sqrt(Count)*_m3/Math.Pow(_m2, 1.5); } |
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} |
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/// <summary>
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/// Estimates the unbiased population kurtosis from the provided samples.
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/// Uses a normalizer (Bessel's correction; type 2).
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/// Returns NaN if data has less than four entries or if any entry is NaN.
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/// </summary>
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public double Kurtosis |
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{ |
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get { return Count < 4 ? double.NaN : ((double) Count*Count - 1)/((Count - 2)*(Count - 3))*(Count*_m4/(_m2*_m2) - 3 + 6.0/(Count + 1)); } |
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} |
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/// <summary>
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/// Evaluates the population kurtosis from the full population.
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/// Does not use a normalizer and would thus be biased if applied to a subset (type 1).
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/// Returns NaN if data has less than three entries or if any entry is NaN.
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/// </summary>
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public double PopulationKurtosis |
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{ |
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get { return Count < 3 ? double.NaN : Count*_m4/(_m2*_m2) - 3.0; } |
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}*/ |
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/// <summary>
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/// Update the running statistics by adding another observed sample (in-place).
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/// </summary>
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public void Push(double value) |
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{ |
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if (Count < _windowSize) |
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{ |
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_oldValues[Count] = value; |
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Count++; |
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var d = value - _m1; |
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var s = d/Count; |
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// var s2 = s * s;
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var t = d*s*(Count - 1); |
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_m1 += s; |
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// _m4 += t * s2 * (Count * Count - 3 * Count + 3) + 6 * s2 * _m2 - 4 * s * _m3;
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// _m3 += t * s * (Count - 2) - 3 * s * _m2;
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_m2 += t; |
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if (value < _min || double.IsNaN(value)) |
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{ |
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_min = value; |
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} |
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if (value > _max || double.IsNaN(value)) |
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{ |
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_max = value; |
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} |
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} |
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else |
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{ |
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var oldValue = _oldValues[_lastIndex]; |
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var d = value - oldValue; |
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var s = d/Count; |
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// var s2 = s * s;
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var oldM1 = _m1; |
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_m1 += s; |
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var x = (value - _m1 + oldValue - oldM1); |
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var t = d*x; |
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_m2 += t; |
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// _m4 += t * s2 * (Count * Count - 3 * Count + 3) + 6 * s2 * _m2 - 4 * s * _m3;
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// _m3 += t * (x /(Count-1) - 3 * s * _m2;
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_oldValues[_lastIndex] = value; |
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_lastIndex++; |
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if (_lastIndex == WindowSize) |
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{ |
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_lastIndex = 0; |
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} |
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_max = value > _max || double.IsNaN(value) ? value : _oldValues.Maximum(); |
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_min = value < _min || double.IsNaN(value)? value : _oldValues.Minimum(); |
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} |
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} |
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/// <summary>
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/// Update the running statistics by adding a sequence of observed sample (in-place).
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/// </summary>
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public void PushRange(IEnumerable<double> values) |
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{ |
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foreach (var value in values) |
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{ |
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Push(value); |
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} |
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} |
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} |
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} |
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@ -0,0 +1,66 @@ |
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// <copyright file="MovingStatisticsTests.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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//
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// Copyright (c) 2009-2015 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
|
|||
// files (the "Software"), to deal in the Software without
|
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// restriction, including without limitation the rights to use,
|
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
|
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
|
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
|
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using System; |
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using System.Collections.Generic; |
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using System.Diagnostics; |
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using System.Runtime.InteropServices; |
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using MathNet.Numerics.Distributions; |
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using MathNet.Numerics.Random; |
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using MathNet.Numerics.Statistics; |
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using NUnit.Framework; |
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namespace MathNet.Numerics.UnitTests.StatisticsTests |
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{ |
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#if !PORTABLE
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[TestFixture, Category("Statistics")] |
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public class MovingStatisticsTests |
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{ |
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[Test] |
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public void QuickTest() |
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{ |
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var data = new double[1000000]; |
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(new Normal(50, 10, new SystemRandomSource(0))).Samples(data); |
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var ms = new MovingStatistics(5, data); |
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ms.PushRange(new[] { 11.11, 22.22, 33.33, 44.44, 55.55 }); |
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Assert.AreEqual(5, ms.Count); |
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Assert.AreEqual(11.11, ms.Minimum); |
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Assert.AreEqual(55.55, ms.Maximum); |
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Assert.AreEqual(33.33, ms.Mean, 1e-11); |
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Assert.AreEqual(308.58025, ms.Variance, 1e-10); |
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//AssertHelpers.AlmostEqualRelative(stats0.Mean, ms.Mean, 14);
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//AssertHelpers.AlmostEqualRelative(stats0.Variance, ms.Variance, 14);
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//AssertHelpers.AlmostEqualRelative(stats0.StandardDeviation, ms.StandardDeviation, 14);
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} |
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} |
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#endif
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} |
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