#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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 .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Problems.DataAnalysis.Evaluators;
using Microsoft.VisualStudio.TestTools.UnitTesting;
namespace HeuristicLab.Problems.DataAnalysis.Tests {
[TestClass()]
public class StatisticCalculatorsTest {
private double[,] testData = new double[,] {
{5,1,1,1,2,1,3,1,1,2},
{5,4,4,5,7,10,3,2,1,2},
{3,1,1,1,2,2,3,1,1,2},
{6,8,8,1,3,4,3,7,1,2},
{4,1,1,3,2,1,3,1,1,2},
{8,10,10,8,7,10,9,7,1,4},
{1,1,1,1,2,10,3,1,1,2},
{2,1,2,1,2,1,3,1,1,2},
{2,1,1,1,2,1,1,1,5,2},
{4,2,1,1,2,1,2,1,1,2},
{1,1,1,1,1,1,3,1,1,2},
{2,1,1,1,2,1,2,1,1,2},
{5,3,3,3,2,3,4,4,1,4},
{8,7,5,10,7,9,5,5,4,4},
{7,4,6,4,6,1,4,3,1,4},
{4,1,1,1,2,1,2,1,1,2},
{4,1,1,1,2,1,3,1,1,2},
{10,7,7,6,4,10,4,1,2,4},
{6,1,1,1,2,1,3,1,1,2},
{7,3,2,10,5,10,5,4,4,4},
{10,5,5,3,6,7,7,10,1,4}
};
[TestMethod]
public void CalculateMeanAndVarianceTest() {
System.Random random = new System.Random(31415);
int n = testData.GetLength(0);
int cols = testData.GetLength(1);
{
for (int col = 0; col < cols; col++) {
double scale = random.NextDouble() * 1E7;
IEnumerable x = from rows in Enumerable.Range(0, n)
select testData[rows, col] * scale;
double[] xs = x.ToArray();
double mean_alglib, variance_alglib;
mean_alglib = variance_alglib = 0.0;
double tmp = 0;
alglib.samplemoments(xs, n, out mean_alglib, out variance_alglib, out tmp, out tmp);
var calculator = new OnlineMeanAndVarianceCalculator();
for (int i = 0; i < n; i++) {
calculator.Add(xs[i]);
}
double mean = calculator.Mean;
double variance = calculator.Variance;
Assert.AreEqual(mean_alglib, mean, 1E-6 * scale);
Assert.AreEqual(variance_alglib, variance, 1E-6 * scale);
}
}
}
[TestMethod]
public void CalculatePearsonsRSquaredTest() {
System.Random random = new System.Random(31415);
int n = testData.GetLength(0);
int cols = testData.GetLength(1);
for (int c1 = 0; c1 < cols; c1++) {
for (int c2 = c1 + 1; c2 < cols; c2++) {
{
double c1Scale = random.NextDouble() * 1E7;
double c2Scale = random.NextDouble() * 1E7;
IEnumerable x = from rows in Enumerable.Range(0, n)
select testData[rows, c1] * c1Scale;
IEnumerable y = from rows in Enumerable.Range(0, n)
select testData[rows, c2] * c2Scale;
double[] xs = x.ToArray();
double[] ys = y.ToArray();
double r2_alglib = alglib.pearsoncorrelation(xs, ys, n);
r2_alglib *= r2_alglib;
var r2Calculator = new OnlinePearsonsRSquaredEvaluator();
for (int i = 0; i < n; i++) {
r2Calculator.Add(xs[i], ys[i]);
}
double r2 = r2Calculator.RSquared;
Assert.AreEqual(r2_alglib, r2, 1E-6 * Math.Max(c1Scale, c2Scale));
}
}
}
}
}
}