private void butPareto_Click(object sender, RoutedEventArgs e)
{
Reset(ChartType.Pareto);
modelChart = Pareto.Create();
controller.ChartModel = modelChart;
RenderChart();
}
public void ValidateToString()
{
System.Threading.Thread.CurrentThread.CurrentCulture = System.Globalization.CultureInfo.InvariantCulture;
var n = new Pareto(1d, 2d);
Assert.AreEqual("Pareto(xm = 1, α = 2)", n.ToString());
}
public void CanCreatePareto([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Scale);
Assert.AreEqual(shape, n.Shape);
}
public void CanSampleSequence()
{
var n = new Pareto(1.0, 1.0);
var ied = n.Samples();
ied.Take(5).ToArray();
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="PowerOp"]/message_doc[@name="XAverageConditional(Pareto, Gamma, double)"]/*'/>
public static Gamma XAverageConditional(Pareto pow, Gamma x, double y)
{
// factor is delta(pow - x^y)
// marginal for x is Pareto(x^y; s,L) Ga(x; a,b)
// =propto x^(a-1-y(s+1)) exp(-bx) for x >= L^(1/y)
// we can compute moments via the incomplete Gamma function.
// change variables to: z=bx, dz=b dx
// int_LL^inf x^(c-1) exp(-bx) dx = int_(bLL)^inf z^(c-1)/b^c exp(-z) dz = gammainc(c,bLL,inf)/b^c
double lowerBound = System.Math.Pow(pow.LowerBound, 1 / y);
double b = x.Rate;
double c = x.Shape - y * (pow.Shape + 1);
double bL = b * lowerBound;
double m, m2;
if (y > 0)
{
// note these ratios can be simplified
double z = MMath.GammaUpper(c, bL);
m = MMath.GammaUpper(c + 1, bL) * c / z / b;
m2 = MMath.GammaUpper(c + 2, bL) * c * (c + 1) / z / (b * b);
}
else
{
double z = MMath.GammaLower(c, bL);
m = MMath.GammaLower(c + 1, bL) * c / z / b;
m2 = MMath.GammaLower(c + 2, bL) * c * (c + 1) / z / (b * b);
}
double v = m2 - m * m;
Gamma xPost = Gamma.FromMeanAndVariance(m, v);
Gamma result = new Gamma();
result.SetToRatio(xPost, x, true);
return(result);
}
public void CanCreatePareto(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Scale);
Assert.AreEqual(shape, n.Shape);
}
public void ValidateMedian(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale * Math.Pow(2.0, 1.0 / shape), n.Median);
}
public void ValidateCumulativeDistribution(double scale, double shape, double x)
{
var n = new Pareto(scale, shape);
double expected = 1.0 - Math.Pow(scale / x, shape);
Assert.AreEqual(expected, n.CumulativeDistribution(x));
Assert.AreEqual(expected, Pareto.CDF(scale, shape, x));
}
public void ValidateInverseCumulativeDistribution(double scale, double shape, double x)
{
var n = new Pareto(scale, shape);
double cdf = 1.0 - Math.Pow(scale / x, shape);
Assert.AreEqual(x, n.InverseCumulativeDistribution(cdf), 1e-12);
Assert.AreEqual(x, Pareto.InvCDF(scale, shape, cdf), 1e-12);
}
public void ValidateMean([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
if (shape > 1)
{
Assert.AreEqual(shape * scale / (shape - 1.0), n.Mean);
}
}
public void ValidateCumulativeDistribution(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape,
[Values(0.1, 1.0, 2.0, 2.1, 10.0, 12.0, Double.PositiveInfinity)] double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(1.0 - Math.Pow(scale / x, shape), n.CumulativeDistribution(x));
}
public void ValidateMean(double scale, double shape)
{
var n = new Pareto(scale, shape);
if (shape > 1)
{
Assert.AreEqual(shape * scale / (shape - 1.0), n.Mean);
}
}
public void ValidateDensity(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape,
[Values(0.1, 1.0, 2.0, 2.1, 10.0, 12.0, Double.PositiveInfinity)] double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(shape * Math.Pow(scale, shape) / Math.Pow(x, shape + 1.0), n.Density(x));
}
public void ValidateDensityLn(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape,
[Values(0.1, 1.0, 2.0, 2.1, 10.0, 12.0, Double.PositiveInfinity)] double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(Math.Log(n.Density(x)), n.DensityLn(x));
}
public void ValidateDensity(double scale, double shape, double x, double expected)
{
var dist = new Pareto(scale, shape);
Assert.AreEqual(expected, dist.Density(x), 1e-12);
Assert.AreEqual(expected, Pareto.PDF(scale, shape, x), 1e-12);
Assert.AreEqual(Math.Log(expected), dist.DensityLn(x), 1e-12);
Assert.AreEqual(Math.Log(expected), Pareto.PDFLn(scale, shape, x), 1e-12);
}
public void TestDistribution(double xm, double a)
{
var expectedMean = a * xm / (a - 1);
var expectedVariance = (xm * xm * a) / ((a - 1) * (a - 1) * (a - 2));
var distribution = new Pareto(xm, a);
var list = Enumerable.Range(1, 10000000).Select(x => distribution.Sample()).ToList();
var calculatedMean = Statistics.Mean(list);
calculatedMean.ShouldBe(expectedMean, 0.05 * expectedMean);
Statistics.Variance(list).ShouldBe(expectedVariance, 0.5 * expectedVariance);
}
// Pareto = Pareto ^ y ////////////////////////////////////////////////////////////////////
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="PowerOp"]/message_doc[@name="PowAverageConditional(Pareto, double)"]/*'/>
public static Pareto PowAverageConditional(Pareto x, double y)
{
if (y < 0)
{
throw new NotSupportedException("Pareto raised to a negative power (" + y + ") cannot be represented by a Pareto distribution");
}
// p(x) =propto 1/x^(s+1)
// z = x^y implies
// p(z) = p(x = z^(1/y)) (1/y) z^(1/y-1)
// =propto z^(-(s+1)/y+1/y-1) = z^(-s/y-1)
return(new Pareto(x.Shape / y, System.Math.Pow(x.LowerBound, y)));
}
public void ValidateVariance(double scale, double shape)
{
var n = new Pareto(scale, shape);
if (shape <= 2.0)
{
Assert.AreEqual(double.PositiveInfinity, n.Variance);
}
else
{
Assert.AreEqual(scale * scale * shape / ((shape - 1.0) * (shape - 1.0) * (shape - 2.0)), n.Variance);
}
}
public static void Main()
{
// 实例化算例分配引擎
MOCBA mocba = new MOCBA();
// 创建有限解集
var candidates = Enumerable.Range(1, 4)
.SelectMany(i => Enumerable.Range(1, 4)
.SelectMany(j => Enumerable.Range(1, 4)
.Select(k => new StochasticSolution(new double[] { i, j, k }))))
.ToDictionary(s => s.Decisions, s => s);
// 初始测量
foreach (var sol in candidates.Values)
{
Exercise_7.Evaluate(sol, nReps: 5);
}
int h = 0;
while (true)
{
int budgetPerSolution = 2;
// Equal Allocation - 平均分配
//foreach (var sol in candidates.Values) Exercise_7.Evaluate(sol, budgetPerSolution);
// MOCBA - 依据当前随机解结果分配算力，执行测量
foreach (var alloc in
mocba.Alloc(candidates.Count * budgetPerSolution, candidates.Values))
{
Exercise_7.Evaluate(candidates[alloc.Key], alloc.Value);
}
Console.Clear();
Console.WriteLine("Iteration: {0}", h++);
// 获取并显示当前帕里多集
foreach (var sol in Pareto.GetParetoSet(candidates.Values, sol => sol.Objectives)
.OrderBy(sol => sol.Objectives[0]))
{
Console.WriteLine(sol);
}
Console.WriteLine("Total Budget: {0}", candidates.Values.Sum(sol => sol.Observations.Count));
// 显示当前近似正确选择概率
Console.WriteLine("APCS-M: {0:F4}", mocba.APCS_M(candidates.Values));
Console.ReadKey();
}
}
public void Initialize(float mean, float coefficientOfVariation)
{
if (coefficientOfVariation >= 16 || coefficientOfVariation <= 0)
{
throw new ArgumentOutOfRangeException("coefficientOfVariation", "CoefficientOfVariation should be from range (0,16)");
}
double m = mean;
double sd = mean * coefficientOfVariation;
double v = sd * sd;
//double a = 1 + Math.Sqrt(1 + m*m/v);
double a = 1 / coefficientOfVariation * 16;
double xm = m * (a - 1) / a;
Distribution = new Pareto(xm, a);
Sum = 0;
}
/// <include file='FactorDocs.xml' path='factor_docs/message_op_class[@name="UniformPlusMinusOp"]/message_doc[@name="LogEvidenceRatio(double, Pareto)"]/*'/>
public static double LogEvidenceRatio(double sample, Pareto upperBound)
{
// factor is 1/(2*upperBound)
// result is int_y^inf 1/(2*x)*s*L^s/x^(s+1) dx = 0.5*s*L^s/y^(s+1)/(s+1)
// where y = max(sample,L)
double x = System.Math.Abs(sample);
double result = -MMath.Ln2 + System.Math.Log(upperBound.Shape / (upperBound.Shape + 1));
if (upperBound.LowerBound < x)
{
result += upperBound.Shape * System.Math.Log(upperBound.LowerBound) - (upperBound.Shape + 1) * System.Math.Log(x);
}
else
{
result -= System.Math.Log(upperBound.LowerBound);
}
return(result);
}
public void ValidateMedian(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale * Math.Pow(2.0, 1.0 / shape), n.Median);
}
public void ValidateSkewness(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual((2.0 * (shape + 1.0) / (shape - 3.0)) * Math.Sqrt((shape - 2.0) / shape), n.Skewness);
}
public void ValidateStdDev(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual((scale * Math.Sqrt(shape)) / ((shape - 1.0) * Math.Sqrt(shape - 2.0)), n.StdDev);
}
public void ValidateMean(double scale, double shape)
{
var n = new Pareto(scale, shape);
if (shape > 1)
{
Assert.AreEqual(shape * scale / (shape - 1.0), n.Mean);
}
}
public void ValidateToString()
{
var n = new Pareto(1d, 2d);
Assert.AreEqual("Pareto(xm = 1, α = 2)", n.ToString());
}
public void ValidateEntropy([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(Math.Log(shape / scale) - (1.0 / shape) - 1.0, n.Entropy);
}
public void CanSample()
{
var n = new Pareto(1.0, 1.0);
n.Sample();
}
public void ValidateDensityLn(double scale, double shape, double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(Math.Log(n.Density(x)), n.DensityLn(x));
}
public void ValidateDensity(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape,
[Values(0.1, 1.0, 2.0, 2.1, 10.0, 12.0, Double.PositiveInfinity)] double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(shape * Math.Pow(scale, shape) / Math.Pow(x, shape + 1.0), n.Density(x));
}
public void ValidateDensityLn(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape,
[Values(0.1, 1.0, 2.0, 2.1, 10.0, 12.0, Double.PositiveInfinity)] double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(Math.Log(n.Density(x)), n.DensityLn(x));
}
public void ValidateCumulativeDistribution(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape,
[Values(0.1, 1.0, 2.0, 2.1, 10.0, 12.0, Double.PositiveInfinity)] double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(1.0 - Math.Pow(scale / x, shape), n.CumulativeDistribution(x));
}
public void CanCreatePareto([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Scale);
Assert.AreEqual(shape, n.Shape);
}
public void ValidateMaximum()
{
var n = new Pareto(1.0, 1.0);
Assert.AreEqual(Double.PositiveInfinity, n.Maximum);
}
public void ParetoCreateFailsWithBadParameters(
[Values(Double.NaN, 1.0, Double.NaN, 1.0, -1.0, -1.0, 0.0, 0.0, 1.0)] double scale,
[Values(1.0, Double.NaN, Double.NaN, -1.0, 1.0, -1.0, 0.0, 1.0, 0.0)] double shape)
{
Assert.Throws<ArgumentOutOfRangeException>(() => { var n = new Pareto(scale, shape); });
}
public void CanSampleSequence()
{
var n = new Pareto(1.0, 1.0);
var ied = n.Samples();
ied.Take(5).ToArray();
}
public void ValidateSkewness([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual((2.0 * (shape + 1.0) / (shape - 3.0)) * Math.Sqrt((shape - 2.0) / shape), n.Skewness);
}
public void CanCreatePareto(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Scale);
Assert.AreEqual(shape, n.Shape);
}
public void ParetoCreateFailsWithBadParameters(double scale, double shape)
{
Assert.Throws <ArgumentOutOfRangeException>(() => { var n = new Pareto(scale, shape); });
}
public void ValidateToString()
{
var n = new Pareto(1.0, 2.0);
Assert.AreEqual("Pareto(Scale = 1, Shape = 2)", n.ToString());
}
public void SetShapeFailsWithNegativeShape()
{
var n = new Pareto(1.0, 1.0);
Assert.Throws<ArgumentOutOfRangeException>(() => n.Shape = -1.0);
}
public void ValidateStdDev([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual((scale * Math.Sqrt(shape)) / ((shape - 1.0) * Math.Sqrt(shape - 2.0)), n.StdDev);
}
public void ValidateVariance(double scale, double shape)
{
var n = new Pareto(scale, shape);
if (shape <= 2.0)
{
Assert.AreEqual(double.PositiveInfinity, n.Variance);
}
else
{
Assert.AreEqual(scale * scale * shape / ((shape - 1.0) * (shape - 1.0) * (shape - 2.0)), n.Variance);
}
}
public void ValidateMinimum(double scale)
{
var n = new Pareto(scale, 1.0);
Assert.AreEqual(scale, n.Minimum);
}
public void ValidateEntropy(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(Math.Log(shape / scale) - (1.0 / shape) - 1.0, n.Entropy);
}
public void ValidateMaximum()
{
var n = new Pareto(1.0, 1.0);
Assert.AreEqual(Double.PositiveInfinity, n.Maximum);
}
public void ValidateMode(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Mode);
}
public void ValidateMinimum([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale)
{
var n = new Pareto(scale, 1.0);
Assert.AreEqual(scale, n.Minimum);
}
public void ValidateMinimum(double scale)
{
var n = new Pareto(scale, 1.0);
Assert.AreEqual(scale, n.Minimum);
}
public void ValidateMedian(
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale,
[Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale * Math.Pow(2.0, 1.0 / shape), n.Median);
}
public void ValidateDensity(double scale, double shape, double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(shape * Math.Pow(scale, shape) / Math.Pow(x, shape + 1.0), n.Density(x));
}
public void ValidateMode([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Mode);
}
public void CanSample()
{
var n = new Pareto(1.0, 1.0);
n.Sample();
}
public void ValidateEntropy(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(Math.Log(shape / scale) - (1.0 / shape) - 1.0, n.Entropy);
}
public void ValidateCumulativeDistribution(double scale, double shape, double x)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(1.0 - Math.Pow(scale / x, shape), n.CumulativeDistribution(x));
}
public void ValidateSkewness(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual((2.0 * (shape + 1.0) / (shape - 3.0)) * Math.Sqrt((shape - 2.0) / shape), n.Skewness);
}
public void ParetoCreateFailsWithBadParameters(double scale, double shape)
{
Assert.Throws<ArgumentOutOfRangeException>(() => { var n = new Pareto(scale, shape); });
}
public void ValidateMode(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale, n.Mode);
}
public void ValidateMedian(double scale, double shape)
{
var n = new Pareto(scale, shape);
Assert.AreEqual(scale * Math.Pow(2.0, 1.0 / shape), n.Median);
}
public void ValidateMean([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double shape)
{
var n = new Pareto(scale, shape);
if (shape > 1)
{
Assert.AreEqual(shape * scale / (shape - 1.0), n.Mean);
}
}