Dotnet/FastRng
Dotnet/FastRng
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Thorsten Sommer 2023-07-06 10:26:12 +02:00
parent 38764d5d97
commit e8cf1284d7
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55 changed files with 3485 additions and 3567 deletions
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21
FastRng/Distributions/BetaA2B2.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class BetaA2B2 : Distribution
{
public sealed class BetaA2B2 : Distribution
private const float ALPHA = 2f;
private const float BETA = 2f;
private const float CONSTANT = 4f;
public BetaA2B2(IRandom rng) : base(rng)
{
private const float ALPHA = 2f;
private const float BETA = 2f;
private const float CONSTANT = 4f;
public BetaA2B2(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow(x, ALPHA - 1f) * MathF.Pow(1f - x, BETA - 1f);
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow(x, ALPHA - 1f) * MathF.Pow(1f - x, BETA - 1f);
}

21
FastRng/Distributions/BetaA2B5.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class BetaA2B5 : Distribution
{
public sealed class BetaA2B5 : Distribution
private const float ALPHA = 2f;
private const float BETA = 5f;
private const float CONSTANT = 12.2f;
public BetaA2B5(IRandom rng) : base(rng)
{
private const float ALPHA = 2f;
private const float BETA = 5f;
private const float CONSTANT = 12.2f;
public BetaA2B5(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow(x, ALPHA - 1f) * MathF.Pow(1f - x, BETA - 1f);
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow(x, ALPHA - 1f) * MathF.Pow(1f - x, BETA - 1f);
}

23
FastRng/Distributions/BetaA5B2.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
{
public sealed class BetaA5B2 : Distribution
{
private const float ALPHA = 5f;
private const float BETA = 2f;
private const float CONSTANT = 12.2f;
namespace FastRng.Distributions;
public BetaA5B2(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow(x, ALPHA - 1f) * MathF.Pow(1f - x, BETA - 1f);
public sealed class BetaA5B2 : Distribution
{
private const float ALPHA = 5f;
private const float BETA = 2f;
private const float CONSTANT = 12.2f;
public BetaA5B2(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow(x, ALPHA - 1f) * MathF.Pow(1f - x, BETA - 1f);
}

21
FastRng/Distributions/CauchyLorentzX0.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class CauchyLorentzX0 : Distribution
{
public sealed class CauchyLorentzX0 : Distribution
private const float CONSTANT = 0.31f;
private const float SCALE = 0.1f;
private const float MEDIAN = 0.0f;
public CauchyLorentzX0(IRandom rng) : base(rng)
{
private const float CONSTANT = 0.31f;
private const float SCALE = 0.1f;
private const float MEDIAN = 0.0f;
public CauchyLorentzX0(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * (1.0f / (MathF.PI * SCALE)) * ((SCALE * SCALE) / (MathF.Pow(x - MEDIAN, 2f) + (SCALE * SCALE)));
}
private protected override float ShapeFunction(float x) => CONSTANT * (1.0f / (MathF.PI * SCALE)) * ((SCALE * SCALE) / (MathF.Pow(x - MEDIAN, 2f) + (SCALE * SCALE)));
}

21
FastRng/Distributions/CauchyLorentzX1.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class CauchyLorentzX1 : Distribution
{
public sealed class CauchyLorentzX1 : Distribution
private const float CONSTANT = 0.31f;
private const float SCALE = 0.1f;
private const float MEDIAN = 1.0f;
public CauchyLorentzX1(IRandom rng) : base(rng)
{
private const float CONSTANT = 0.31f;
private const float SCALE = 0.1f;
private const float MEDIAN = 1.0f;
public CauchyLorentzX1(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * (1.0f / (MathF.PI * SCALE)) * ((SCALE * SCALE) / (MathF.Pow(x - MEDIAN, 2f) + (SCALE * SCALE)));
}
private protected override float ShapeFunction(float x) => CONSTANT * (1.0f / (MathF.PI * SCALE)) * ((SCALE * SCALE) / (MathF.Pow(x - MEDIAN, 2f) + (SCALE * SCALE)));
}

41
FastRng/Distributions/ChiSquareK1.cs
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@ -1,27 +1,26 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class ChiSquareK1 : Distribution
{
public sealed class ChiSquareK1 : Distribution
private const float K = 1.0f;
private const float K_HALF = K * 0.5f;
private const float K_HALF_MINUS_ONE = K_HALF - 1.0f;
private const float CONSTANT = 0.252f;
private static readonly float DIVISOR;
static ChiSquareK1()
{
private const float K = 1.0f;
private const float K_HALF = K * 0.5f;
private const float K_HALF_MINUS_ONE = K_HALF - 1.0f;
private const float CONSTANT = 0.252f;
private static readonly float DIVISOR;
static ChiSquareK1()
{
var twoToTheKHalf = MathF.Pow(2f, K_HALF);
var gammaKHalf = MathTools.Gamma(K_HALF);
DIVISOR = twoToTheKHalf * gammaKHalf;
}
public ChiSquareK1(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((MathF.Pow(x, K_HALF_MINUS_ONE) * MathF.Exp(-x * 0.5f)) / DIVISOR);
var twoToTheKHalf = MathF.Pow(2f, K_HALF);
var gammaKHalf = MathTools.Gamma(K_HALF);
DIVISOR = twoToTheKHalf * gammaKHalf;
}
public ChiSquareK1(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((MathF.Pow(x, K_HALF_MINUS_ONE) * MathF.Exp(-x * 0.5f)) / DIVISOR);
}

41
FastRng/Distributions/ChiSquareK10.cs
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@ -1,27 +1,26 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class ChiSquareK10 : Distribution
{
public sealed class ChiSquareK10 : Distribution
private const float K = 10.0f;
private const float K_HALF = K * 0.5f;
private const float K_HALF_MINUS_ONE = K_HALF - 1.0f;
private const float CONSTANT = 0.252f;
private static readonly float DIVISOR;
static ChiSquareK10()
{
private const float K = 10.0f;
private const float K_HALF = K * 0.5f;
private const float K_HALF_MINUS_ONE = K_HALF - 1.0f;
private const float CONSTANT = 0.252f;
private static readonly float DIVISOR;
static ChiSquareK10()
{
var twoToTheKHalf = MathF.Pow(2f, K_HALF);
var gammaKHalf = MathTools.Gamma(K_HALF);
DIVISOR = twoToTheKHalf * gammaKHalf;
}
public ChiSquareK10(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((MathF.Pow(x, K_HALF_MINUS_ONE) * MathF.Exp(-x * 0.5f)) / DIVISOR);
var twoToTheKHalf = MathF.Pow(2f, K_HALF);
var gammaKHalf = MathTools.Gamma(K_HALF);
DIVISOR = twoToTheKHalf * gammaKHalf;
}
public ChiSquareK10(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((MathF.Pow(x, K_HALF_MINUS_ONE) * MathF.Exp(-x * 0.5f)) / DIVISOR);
}

39
FastRng/Distributions/ChiSquareK4.cs
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@ -1,27 +1,26 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class ChiSquareK4 : Distribution
{
public sealed class ChiSquareK4 : Distribution
{
private const float K = 4.0f;
private const float K_HALF = K * 0.5f;
private const float K_HALF_MINUS_ONE = K_HALF - 1.0f;
private const float CONSTANT = 0.252f;
private const float K = 4.0f;
private const float K_HALF = K * 0.5f;
private const float K_HALF_MINUS_ONE = K_HALF - 1.0f;
private const float CONSTANT = 0.252f;
private static readonly float DIVISOR;
private static readonly float DIVISOR;
static ChiSquareK4()
{
var twoToTheKHalf = MathF.Pow(2, K_HALF);
var gammaKHalf = MathTools.Gamma(K_HALF);
DIVISOR = twoToTheKHalf * gammaKHalf;
}
public ChiSquareK4(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((MathF.Pow(x, K_HALF_MINUS_ONE) * MathF.Exp(-x * 0.5f)) / DIVISOR);
static ChiSquareK4()
{
var twoToTheKHalf = MathF.Pow(2, K_HALF);
var gammaKHalf = MathTools.Gamma(K_HALF);
DIVISOR = twoToTheKHalf * gammaKHalf;
}
public ChiSquareK4(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((MathF.Pow(x, K_HALF_MINUS_ONE) * MathF.Exp(-x * 0.5f)) / DIVISOR);
}

116
FastRng/Distributions/Distribution.cs
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@ -2,74 +2,62 @@ using System;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public abstract class Distribution : IDistribution
{
public abstract class Distribution : IDistribution
private readonly ShapeFitter fitter;
protected Distribution(IRandom rng)
{
private readonly ShapeFitter fitter;
private readonly IRandom random;
protected Distribution(IRandom rng)
{
if (rng == null)
throw new ArgumentNullException(nameof(rng), "An IRandom implementation is needed.");
this.random = rng;
this.fitter = new ShapeFitter(this.ShapeFunction, this.random, 100);
}
private protected abstract float ShapeFunction(float x);
if (rng == null)
throw new ArgumentNullException(nameof(rng), "An IRandom implementation is needed.");
public async ValueTask<float> GetDistributedValue(CancellationToken token = default) => await this.fitter.NextNumber(token);
this.fitter = new ShapeFitter(this.ShapeFunction, rng, 100);
}
private protected abstract float ShapeFunction(float x);
public async ValueTask<uint> NextNumber(uint rangeStart, uint rangeEnd, CancellationToken cancel = default)
{
if (rangeStart > rangeEnd)
{
var tmp = rangeStart;
rangeStart = rangeEnd;
rangeEnd = tmp;
}
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (uint) ((distributedValue * range) + rangeStart);
}
public async ValueTask<ulong> NextNumber(ulong rangeStart, ulong rangeEnd, CancellationToken cancel = default(CancellationToken))
{
if (rangeStart > rangeEnd)
{
var tmp = rangeStart;
rangeStart = rangeEnd;
rangeEnd = tmp;
}
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (ulong) ((distributedValue * range) + rangeStart);
}
public async ValueTask<float> NextNumber(float rangeStart, float rangeEnd, CancellationToken cancel = default(CancellationToken))
{
if (rangeStart > rangeEnd)
{
var tmp = rangeStart;
rangeStart = rangeEnd;
rangeEnd = tmp;
}
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (distributedValue * range) + rangeStart;
}
public async ValueTask<float> NextNumber(CancellationToken cancel = default) => await this.NextNumber(0.0f, 1.0f, cancel);
public async ValueTask<float> GetDistributedValue(CancellationToken token = default) => await this.fitter.NextNumber(token);
public async ValueTask<bool> HasDecisionBeenMade(float above, float below = 1, CancellationToken cancel = default)
{
var number = await this.NextNumber(cancel);
return number > above && number < below;
}
public async ValueTask<uint> NextNumber(uint rangeStart, uint rangeEnd, CancellationToken cancel = default)
{
// Swap the values if the range start is greater than the range end:
if (rangeStart > rangeEnd)
(rangeStart, rangeEnd) = (rangeEnd, rangeStart);
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (uint) ((distributedValue * range) + rangeStart);
}
public async ValueTask<ulong> NextNumber(ulong rangeStart, ulong rangeEnd, CancellationToken cancel = default)
{
// Swap the values if the range start is greater than the range end:
if (rangeStart > rangeEnd)
(rangeStart, rangeEnd) = (rangeEnd, rangeStart);
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (ulong) ((distributedValue * range) + rangeStart);
}
public async ValueTask<float> NextNumber(float rangeStart, float rangeEnd, CancellationToken cancel = default)
{
// Swap the values if the range start is greater than the range end:
if (rangeStart > rangeEnd)
(rangeStart, rangeEnd) = (rangeEnd, rangeStart);
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (distributedValue * range) + rangeStart;
}
public async ValueTask<float> NextNumber(CancellationToken cancel = default) => await this.NextNumber(0.0f, 1.0f, cancel);
public async ValueTask<bool> HasDecisionBeenMade(float above, float below = 1, CancellationToken cancel = default)
{
var number = await this.NextNumber(cancel);
return number > above && number < below;
}
}

19
FastRng/Distributions/ExponentialLa10.cs
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@ -1,16 +1,15 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class ExponentialLa10 : Distribution
{
public sealed class ExponentialLa10 : Distribution
private const float LAMBDA = 10.0f;
private const float CONSTANT = 0.1106f;
public ExponentialLa10(IRandom rng) : base(rng)
{
private const float LAMBDA = 10.0f;
private const float CONSTANT = 0.1106f;
public ExponentialLa10(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(-LAMBDA * x);
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(-LAMBDA * x);
}

19
FastRng/Distributions/ExponentialLa5.cs
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@ -1,16 +1,15 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class ExponentialLa5 : Distribution
{
public sealed class ExponentialLa5 : Distribution
private const float LAMBDA = 5.0f;
private const float CONSTANT = 0.2103f;
public ExponentialLa5(IRandom rng) : base(rng)
{
private const float LAMBDA = 5.0f;
private const float CONSTANT = 0.2103f;
public ExponentialLa5(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(-LAMBDA * x);
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(-LAMBDA * x);
}

37
FastRng/Distributions/GammaA5B15.cs
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@ -1,26 +1,25 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class GammaA5B15 : Distribution
{
public sealed class GammaA5B15 : Distribution
{
private const float ALPHA = 5.0f;
private const float BETA = 15.0f;
private const float CONSTANT = 0.341344210715475f;
private const float ALPHA = 5.0f;
private const float BETA = 15.0f;
private const float CONSTANT = 0.341344210715475f;
private static readonly float GAMMA_ALPHA;
private static readonly float BETA_TO_THE_ALPHA;
private static readonly float GAMMA_ALPHA;
private static readonly float BETA_TO_THE_ALPHA;
static GammaA5B15()
{
GAMMA_ALPHA = MathTools.Gamma(ALPHA);
BETA_TO_THE_ALPHA = MathF.Pow(BETA, ALPHA);
}
public GammaA5B15(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((BETA_TO_THE_ALPHA * MathF.Pow(x, ALPHA - 1.0f) * MathF.Exp(-BETA * x)) / GAMMA_ALPHA);
static GammaA5B15()
{
GAMMA_ALPHA = MathTools.Gamma(ALPHA);
BETA_TO_THE_ALPHA = MathF.Pow(BETA, ALPHA);
}
public GammaA5B15(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ((BETA_TO_THE_ALPHA * MathF.Pow(x, ALPHA - 1.0f) * MathF.Exp(-BETA * x)) / GAMMA_ALPHA);
}

19
FastRng/Distributions/IDistribution.cs
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@ -1,20 +1,19 @@
using System.Threading;
using System.Threading.Tasks;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public interface IDistribution
{
public interface IDistribution
{
public ValueTask<float> GetDistributedValue(CancellationToken token);
public ValueTask<float> GetDistributedValue(CancellationToken token);
public ValueTask<uint> NextNumber(uint rangeStart, uint rangeEnd, CancellationToken cancel = default);
public ValueTask<uint> NextNumber(uint rangeStart, uint rangeEnd, CancellationToken cancel = default);
public ValueTask<ulong> NextNumber(ulong rangeStart, ulong rangeEnd, CancellationToken cancel = default);
public ValueTask<ulong> NextNumber(ulong rangeStart, ulong rangeEnd, CancellationToken cancel = default);
public ValueTask<float> NextNumber(float rangeStart, float rangeEnd, CancellationToken cancel = default);
public ValueTask<float> NextNumber(float rangeStart, float rangeEnd, CancellationToken cancel = default);
public ValueTask<float> NextNumber(CancellationToken cancel = default);
public ValueTask<float> NextNumber(CancellationToken cancel = default);
public ValueTask<bool> HasDecisionBeenMade(float above, float below = 1.0f, CancellationToken cancel = default);
}
public ValueTask<bool> HasDecisionBeenMade(float above, float below = 1.0f, CancellationToken cancel = default);
}

19
FastRng/Distributions/InverseExponentialLa10.cs
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@ -1,16 +1,15 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class InverseExponentialLa10 : Distribution
{
public sealed class InverseExponentialLa10 : Distribution
private const float LAMBDA = 10.0f;
private const float CONSTANT = 4.539992976248453e-06f;
public InverseExponentialLa10(IRandom rng) : base(rng)
{
private const float LAMBDA = 10.0f;
private const float CONSTANT = 4.539992976248453e-06f;
public InverseExponentialLa10(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(LAMBDA * x);
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(LAMBDA * x);
}

19
FastRng/Distributions/InverseExponentialLa5.cs
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@ -1,16 +1,15 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class InverseExponentialLa5 : Distribution
{
public sealed class InverseExponentialLa5 : Distribution
private const float LAMBDA = 5.0f;
private const float CONSTANT = 0.001347589399817f;
public InverseExponentialLa5(IRandom rng) : base(rng)
{
private const float LAMBDA = 5.0f;
private const float CONSTANT = 0.001347589399817f;
public InverseExponentialLa5(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(LAMBDA * x);
}
private protected override float ShapeFunction(float x) => CONSTANT * LAMBDA * MathF.Exp(LAMBDA * x);
}

39
FastRng/Distributions/InverseGammaA3B05.cs
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@ -1,27 +1,26 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class InverseGammaA3B05 : Distribution
{
public sealed class InverseGammaA3B05 : Distribution
private const float ALPHA = 3.0f;
private const float BETA = 0.5f;
private const float CONSTANT = 0.213922656884911f;
private static readonly float FACTOR_LEFT;
static InverseGammaA3B05()
{
private const float ALPHA = 3.0f;
private const float BETA = 0.5f;
private const float CONSTANT = 0.213922656884911f;
private static readonly float FACTOR_LEFT;
static InverseGammaA3B05()
{
var gammaAlpha = MathTools.Gamma(ALPHA);
var betaToTheAlpha = MathF.Pow(BETA, ALPHA);
var gammaAlpha = MathTools.Gamma(ALPHA);
var betaToTheAlpha = MathF.Pow(BETA, ALPHA);
FACTOR_LEFT = CONSTANT * (betaToTheAlpha / gammaAlpha);
}
public InverseGammaA3B05(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => FACTOR_LEFT * MathF.Pow(x, -ALPHA - 1.0f) * MathF.Exp(-BETA / x);
FACTOR_LEFT = CONSTANT * (betaToTheAlpha / gammaAlpha);
}
public InverseGammaA3B05(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => FACTOR_LEFT * MathF.Pow(x, -ALPHA - 1.0f) * MathF.Exp(-BETA / x);
}

37
FastRng/Distributions/LaplaceB01M0.cs
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@ -1,24 +1,23 @@
using System;
namespace FastRng.Distributions
{
public sealed class LaplaceB01M0 : Distribution
{
private const float B = 0.1f;
private const float MU = 0.0f;
private const float CONSTANT = 0.221034183615129f;
private static readonly float FACTOR_LEFT;
static LaplaceB01M0()
{
FACTOR_LEFT = CONSTANT / (2.0f * B);
}
public LaplaceB01M0(IRandom rng) : base(rng)
{
}
namespace FastRng.Distributions;
private protected override float ShapeFunction(float x) => FACTOR_LEFT * MathF.Exp(-MathF.Abs(x - MU) / B);
public sealed class LaplaceB01M0 : Distribution
{
private const float B = 0.1f;
private const float MU = 0.0f;
private const float CONSTANT = 0.221034183615129f;
private static readonly float FACTOR_LEFT;
static LaplaceB01M0()
{
FACTOR_LEFT = CONSTANT / (2.0f * B);
}
public LaplaceB01M0(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => FACTOR_LEFT * MathF.Exp(-MathF.Abs(x - MU) / B);
}

37
FastRng/Distributions/LaplaceB01M05.cs
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@ -1,24 +1,23 @@
using System;
namespace FastRng.Distributions
{
public sealed class LaplaceB01M05 : Distribution
{
private const float B = 0.1f;
private const float MU = 0.5f;
private const float CONSTANT = 0.2f;
private static readonly float FACTOR_LEFT;
static LaplaceB01M05()
{
FACTOR_LEFT = CONSTANT / (2.0f * B);
}
public LaplaceB01M05(IRandom rng) : base(rng)
{
}
namespace FastRng.Distributions;
private protected override float ShapeFunction(float x) => FACTOR_LEFT * MathF.Exp(-MathF.Abs(x - MU) / B);
public sealed class LaplaceB01M05 : Distribution
{
private const float B = 0.1f;
private const float MU = 0.5f;
private const float CONSTANT = 0.2f;
private static readonly float FACTOR_LEFT;
static LaplaceB01M05()
{
FACTOR_LEFT = CONSTANT / (2.0f * B);
}
public LaplaceB01M05(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => FACTOR_LEFT * MathF.Exp(-MathF.Abs(x - MU) / B);
}

37
FastRng/Distributions/LogNormalS1M0.cs
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@ -1,24 +1,23 @@
using System;
namespace FastRng.Distributions
{
public sealed class LogNormalS1M0 : Distribution
{
private const float SIGMA = 1.0f;
private const float MU = 0.0f;
private const float CONSTANT = 1.51998658387455f;
private static readonly float FACTOR;
static LogNormalS1M0()
{
FACTOR = SIGMA * MathF.Sqrt(2f * MathF.PI);
}
public LogNormalS1M0(IRandom rng) : base(rng)
{
}
namespace FastRng.Distributions;
private protected override float ShapeFunction(float x) => (CONSTANT / (x * FACTOR)) * MathF.Exp( -(MathF.Pow(MathF.Log(x) - MU, 2f) / (2f * MathF.Pow(SIGMA, 2f))));
public sealed class LogNormalS1M0 : Distribution
{
private const float SIGMA = 1.0f;
private const float MU = 0.0f;
private const float CONSTANT = 1.51998658387455f;
private static readonly float FACTOR;
static LogNormalS1M0()
{
FACTOR = SIGMA * MathF.Sqrt(2f * MathF.PI);
}
public LogNormalS1M0(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => (CONSTANT / (x * FACTOR)) * MathF.Exp( -(MathF.Pow(MathF.Log(x) - MU, 2f) / (2f * MathF.Pow(SIGMA, 2f))));
}

21
FastRng/Distributions/NormalS02M05.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class NormalS02M05 : Distribution
{
public sealed class NormalS02M05 : Distribution
private const float SQRT_2_PI = 2.506628275f;
private const float STD_DEV = 0.2f;
private const float MEAN = 0.5f;
public NormalS02M05(IRandom rng) : base(rng)
{
private const float SQRT_2_PI = 2.506628275f;
private const float STDDEV = 0.2f;
private const float MEAN = 0.5f;
public NormalS02M05(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => 1.0f / (STDDEV * SQRT_2_PI) * MathF.Exp(-0.5f * MathF.Pow((x - MEAN) / STDDEV, 2.0f));
}
private protected override float ShapeFunction(float x) => 1.0f / (STD_DEV * SQRT_2_PI) * MathF.Exp(-0.5f * MathF.Pow((x - MEAN) / STD_DEV, 2.0f));
}

47
FastRng/Distributions/StudentTNu1.cs
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@ -1,29 +1,28 @@
using System;
namespace FastRng.Distributions
{
public sealed class StudentTNu1 : Distribution
{
private const float NU = 1.0f;
private const float START = 0.0f;
private const float COMPRESS = 1.0f;
private const float CONSTANT = 3.14190548592729f;
private static readonly float DIVIDEND;
private static readonly float DIVISOR;
private static readonly float EXPONENT;
static StudentTNu1()
{
DIVIDEND = MathTools.Gamma((NU + 1.0f) * 0.5f);
DIVISOR = MathF.Sqrt(NU * MathF.PI) * MathTools.Gamma(NU * 0.5f);
EXPONENT = -((NU + 1.0f) * 0.5f);
}
public StudentTNu1(IRandom rng) : base(rng)
{
}
namespace FastRng.Distributions;
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow((DIVIDEND / DIVISOR) * MathF.Pow(1.0f + MathF.Pow(START + x * COMPRESS, 2f) / NU, EXPONENT), COMPRESS);
public sealed class StudentTNu1 : Distribution
{
private const float NU = 1.0f;
private const float START = 0.0f;
private const float COMPRESS = 1.0f;
private const float CONSTANT = 3.14190548592729f;
private static readonly float DIVIDEND;
private static readonly float DIVISOR;
private static readonly float EXPONENT;
static StudentTNu1()
{
DIVIDEND = MathTools.Gamma((NU + 1.0f) * 0.5f);
DIVISOR = MathF.Sqrt(NU * MathF.PI) * MathTools.Gamma(NU * 0.5f);
EXPONENT = -((NU + 1.0f) * 0.5f);
}
public StudentTNu1(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * MathF.Pow((DIVIDEND / DIVISOR) * MathF.Pow(1.0f + MathF.Pow(START + x * COMPRESS, 2f) / NU, EXPONENT), COMPRESS);
}

107
FastRng/Distributions/Uniform.cs
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@ -2,70 +2,57 @@ using System;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class Uniform : IDistribution
{
public sealed class Uniform : IDistribution
private readonly IRandom rng;
public Uniform(IRandom rng)
{
private readonly IRandom rng;
this.rng = rng ?? throw new ArgumentNullException(nameof(rng), "An IRandom implementation is needed.");
}
public async ValueTask<float> GetDistributedValue(CancellationToken token = default) => await this.rng.GetUniform(token);
public Uniform(IRandom rng)
{
if (rng == null)
throw new ArgumentNullException(nameof(rng), "An IRandom implementation is needed.");
this.rng = rng;
}
public async ValueTask<uint> NextNumber(uint rangeStart, uint rangeEnd, CancellationToken cancel = default)
{
// Swap the values if the range start is greater than the range end:
if (rangeStart > rangeEnd)
(rangeStart, rangeEnd) = (rangeEnd, rangeStart);
public async ValueTask<float> GetDistributedValue(CancellationToken token = default) => await this.rng.GetUniform(token);
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (uint) ((distributedValue * range) + rangeStart);
}
public async ValueTask<ulong> NextNumber(ulong rangeStart, ulong rangeEnd, CancellationToken cancel = default)
{
// Swap the values if the range start is greater than the range end:
if (rangeStart > rangeEnd)
(rangeStart, rangeEnd) = (rangeEnd, rangeStart);
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (ulong) ((distributedValue * range) + rangeStart);
}
public async ValueTask<float> NextNumber(float rangeStart, float rangeEnd, CancellationToken cancel = default)
{
// Swap the values if the range start is greater than the range end:
if (rangeStart > rangeEnd)
(rangeStart, rangeEnd) = (rangeEnd, rangeStart);
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (distributedValue * range) + rangeStart;
}
public async ValueTask<float> NextNumber(CancellationToken cancel = default) => await this.NextNumber(0.0f, 1.0f, cancel);
public async ValueTask<uint> NextNumber(uint rangeStart, uint rangeEnd, CancellationToken cancel = default)
{
if (rangeStart > rangeEnd)
{
var tmp = rangeStart;
rangeStart = rangeEnd;
rangeEnd = tmp;
}
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (uint) ((distributedValue * range) + rangeStart);
}
public async ValueTask<ulong> NextNumber(ulong rangeStart, ulong rangeEnd, CancellationToken cancel = default(CancellationToken))
{
if (rangeStart > rangeEnd)
{
var tmp = rangeStart;
rangeStart = rangeEnd;
rangeEnd = tmp;
}
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (ulong) ((distributedValue * range) + rangeStart);
}
public async ValueTask<float> NextNumber(float rangeStart, float rangeEnd, CancellationToken cancel = default(CancellationToken))
{
if (rangeStart > rangeEnd)
{
var tmp = rangeStart;
rangeStart = rangeEnd;
rangeEnd = tmp;
}
var range = rangeEnd - rangeStart;
var distributedValue = await this.GetDistributedValue(cancel);
return (distributedValue * range) + rangeStart;
}
public async ValueTask<float> NextNumber(CancellationToken cancel = default) => await this.NextNumber(0.0f, 1.0f, cancel);
public async ValueTask<bool> HasDecisionBeenMade(float above, float below = 1, CancellationToken cancel = default)
{
var number = await this.NextNumber(cancel);
return number > above && number < below;
}
public async ValueTask<bool> HasDecisionBeenMade(float above, float below = 1, CancellationToken cancel = default)
{
var number = await this.NextNumber(cancel);
return number > above && number < below;
}
}

21
FastRng/Distributions/WeibullK05La1.cs
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@ -1,17 +1,16 @@
using System;
namespace FastRng.Distributions
namespace FastRng.Distributions;
public sealed class WeibullK05La1 : Distribution
{
public sealed class WeibullK05La1 : Distribution
private const float K = 0.5f;
private const float LAMBDA = 1.0f;
private const float CONSTANT = 0.221034183615129f;
public WeibullK05La1(IRandom rng) : base(rng)
{
private const float K = 0.5f;
private const float LAMBDA = 1.0f;
private const float CONSTANT = 0.221034183615129f;
public WeibullK05La1(IRandom rng) : base(rng)
{
}
private protected override float ShapeFunction(float x) => CONSTANT * ( (K / LAMBDA) * MathF.Pow(x / LAMBDA, K - 1.0f) * MathF.Exp(-MathF.Pow(x/LAMBDA, K)));
}
private protected override float ShapeFunction(float x) => CONSTANT * ( (K / LAMBDA) * MathF.Pow(x / LAMBDA, K - 1.0f) * MathF.Exp(-MathF.Pow(x/LAMBDA, K)));
}

29
FastRng/IRandom.cs
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@ -2,22 +2,21 @@ using System;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng
namespace FastRng;
/// <summary>
/// Interface for random number generators.
/// </summary>
public interface IRandom : IDisposable
{
/// <summary>
/// Interface for random number generators.
/// Returns a uniform distributed pseudo-random number from the interval (0,1].
/// This means, the result 0 is impossible, whereas 1 is possible.
/// </summary>
public interface IRandom : IDisposable
{
/// <summary>
/// Returns a uniform distributed pseudo-random number from the interval (0,1].
/// This means, the result 0 is impossible, whereas 1 is possible.
/// </summary>
/// <remarks>
/// This method is thread-safe. You can consume numbers from the same generator
/// by using multiple threads at the same time.
/// </remarks>
/// <param name="cancel">An optional cancellation token.</param>
public ValueTask<float> GetUniform(CancellationToken cancel = default);
}
/// <remarks>
/// This method is thread-safe. You can consume numbers from the same generator
/// by using multiple threads at the same time.
/// </remarks>
/// <param name="cancel">An optional cancellation token.</param>
public ValueTask<float> GetUniform(CancellationToken cancel = default);
}

131
FastRng/MathTools.cs
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@ -1,83 +1,82 @@
using System;
namespace FastRng
namespace FastRng;
/// <summary>
/// Provides some mathematical function, which are not available within in the .NET framework.
/// </summary>
public static class MathTools
{
private static readonly float SQRT_2 = MathF.Sqrt(2.0f);
private static readonly float SQRT_PI = MathF.Sqrt(MathF.PI);
/// <summary>
/// Provides some mathematical function, which are not available within in the .NET framework.
/// The mathematical gamma function.
/// </summary>
public static class MathTools
/// <param name="z">The value for which you want calculate gamma.</param>
public static float Gamma(float z)
{
private static readonly float SQRT_2 = MathF.Sqrt(2.0f);
private static readonly float SQRT_PI = MathF.Sqrt(MathF.PI);
/// <summary>
/// The mathematical gamma function.
/// </summary>
/// <param name="z">The value for which you want calculate gamma.</param>
public static float Gamma(float z)
{
// Source: http://rosettacode.org/wiki/Gamma_function#Go
// Source: http://rosettacode.org/wiki/Gamma_function#Go
const float F1 = 6.5f;
const float A1 = .99999999999980993f;
const float A2 = 676.5203681218851f;
const float A3 = 1259.1392167224028f;
const float A4 = 771.32342877765313f;
const float A5 = 176.61502916214059f;
const float A6 = 12.507343278686905f;
const float A7 = .13857109526572012f;
const float A8 = 9.9843695780195716e-6f;
const float A9 = 1.5056327351493116e-7f;
const float F1 = 6.5f;
const float A1 = .99999999999980993f;
const float A2 = 676.5203681218851f;
const float A3 = 1259.1392167224028f;
const float A4 = 771.32342877765313f;
const float A5 = 176.61502916214059f;
const float A6 = 12.507343278686905f;
const float A7 = .13857109526572012f;
const float A8 = 9.9843695780195716e-6f;
const float A9 = 1.5056327351493116e-7f;
var t = z + F1;
var x = A1 +
A2 / z -
A3 / (z + 1) +
A4 / (z + 2) -
A5 / (z + 3) +
A6 / (z + 4) -
A7 / (z + 5) +
A8 / (z + 6) +
A9 / (z + 7);
var t = z + F1;
var x = A1 +
A2 / z -
A3 / (z + 1) +
A4 / (z + 2) -
A5 / (z + 3) +
A6 / (z + 4) -
A7 / (z + 5) +
A8 / (z + 6) +
A9 / (z + 7);
return MathTools.SQRT_2 * MathTools.SQRT_PI * MathF.Pow(t, z - 0.5f) * MathF.Exp(-t) * x;
}
return SQRT_2 * SQRT_PI * MathF.Pow(t, z - 0.5f) * MathF.Exp(-t) * x;
}
/// <summary>
/// The mathematical factorial function for floating-point numbers.
/// </summary>
/// <param name="x">The value, for which you want to know the factorial.</param>
public static float Factorial(float x) => MathTools.Gamma(x + 1.0f);
/// <summary>
/// The mathematical factorial function for floating-point numbers.
/// </summary>
/// <param name="x">The value, for which you want to know the factorial.</param>
public static float Factorial(float x) => Gamma(x + 1.0f);
/// <summary>
/// The mathematical factorial function for integer numbers.
/// </summary>
/// <param name="x">The value, for which you want to know the factorial.</param>
/// <exception cref="ArgumentOutOfRangeException">Throws, when x is greater than 20. Due to limitations of 64bit ulong type.</exception>
public static ulong Factorial(uint x)
{
if (x > 20)
throw new ArgumentOutOfRangeException(nameof(x), $"Cannot compute {x}!, since ulong.max is 18_446_744_073_709_551_615.");
/// <summary>
/// The mathematical factorial function for integer numbers.
/// </summary>
/// <param name="x">The value, for which you want to know the factorial.</param>
/// <exception cref="ArgumentOutOfRangeException">Throws, when x is greater than 20. Due to limitations of 64bit ulong type.</exception>
public static ulong Factorial(uint x)
{
if (x > 20)
throw new ArgumentOutOfRangeException(nameof(x), $"Cannot compute {x}!, since ulong.max is 18_446_744_073_709_551_615.");
ulong accumulator = 1;
for (uint factor = 1; factor <= x; factor++)
accumulator *= factor;
ulong accumulator = 1;
for (uint factor = 1; factor <= x; factor++)
accumulator *= factor;
return accumulator;
}
return accumulator;
}
/// <summary>
/// The mathematical factorial function for integer numbers.
/// </summary>
/// <param name="x">The value, for which you want to know the factorial.</param>
/// <exception cref="ArgumentOutOfRangeException">Throws, when x is greater than 20. Due to limitations
/// of 64bit ulong type. Throws also, when x is less than 0.</exception>
public static ulong Factorial(int x)
{
if(x < 0)
throw new ArgumentOutOfRangeException(nameof(x), "Given value must be greater as zero.");
/// <summary>
/// The mathematical factorial function for integer numbers.
/// </summary>
/// <param name="x">The value, for which you want to know the factorial.</param>
/// <exception cref="ArgumentOutOfRangeException">Throws, when x is greater than 20. Due to limitations
/// of 64bit ulong type. Throws also, when x is less than 0.</exception>
public static ulong Factorial(int x)
{
if(x < 0)
throw new ArgumentOutOfRangeException(nameof(x), "Given value must be greater as zero.");
return MathTools.Factorial((uint) x);
}
return Factorial((uint) x);
}
}

685
FastRng/MultiThreadedRng.cs
View File

@ -4,354 +4,353 @@ using System.Diagnostics.CodeAnalysis;
using System.Threading;
using System.Threading.Tasks;
namespace FastRng
namespace FastRng;
/// <summary>
/// A fast multi-threaded pseudo random number generator.
/// </summary>
/// <remarks>
/// Please note, that Math.NET's (https://www.mathdotnet.com/) random number generator is in some situations faster.
/// Unlike Math.NET, MultiThreadedRng is multi-threaded and async. Consumers can await the next number without
/// blocking resources. Additionally, consumers can use a token to cancel e.g. timeout an operation as well.<br/><br/>
///
/// MultiThreadedRng using a shape fitter (a rejection sampler) to enforce arbitrary shapes of probabilities for
/// desired distributions. By using the shape fitter, it is even easy to define discontinuous, arbitrary functions
/// as shapes. Any consumer can define and use own distributions.<br/><br/>
///
/// This class uses the George Marsaglia's MWC algorithm. The algorithm's implementation based loosely on John D.
/// Cook's (johndcook.com) implementation (https://www.codeproject.com/Articles/25172/Simple-Random-Number-Generation).
/// Thanks John for the inspiration.<br/><br/>
///
/// Please notice: When using the debug environment, MultiThreadedRng uses a smaller buffer size. Please ensure,
/// that the production environment uses a release build, though.
/// </remarks>
public sealed class MultiThreadedRng : IRandom, IDisposable
{
#if DEBUG
private const int BUFFER_SIZE = 10_000;
#else
private const int BUFFER_SIZE = 1_000_000;
#endif
// The queue size means, how many buffer we store in a queue at the same time:
private const int QUEUE_SIZE = 2;
// Gets used to stop the producer threads:
private readonly CancellationTokenSource producerTokenSource = new();
// The time a thread waits e.g. to check if the queue needs a new buffer:
private readonly TimeSpan waiter = TimeSpan.FromMilliseconds(10);
// The first queue, where to store buffers of random uint numbers:
private readonly ConcurrentQueue<uint[]> queueIntegers = new();
// The second queue, where to store buffers of uniform random floating point numbers:
private readonly ConcurrentQueue<float[]> queueFloats = new();
// The uint producer thread:
private Thread producerRandomUint;
// The uniform float producer thread:
private Thread producerRandomUniformDistributedFloat;
// Variable w and z for the uint generator. Both get used
// as seeding variable as well (cf. constructors)
private uint mW;
private uint mZ;
// This is the current buffer for the consumer side i.e. the public interfaces:
private float[] currentBuffer = Array.Empty<float>();
// The current pointer to the next current buffer's address to read from:
private int currentBufferPointer = BUFFER_SIZE;
#region Constructors
/// <summary>
/// A fast multi-threaded pseudo random number generator.
/// Creates a multi-threaded random number generator.
/// </summary>
/// <remarks>
/// Please note, that Math.NET's (https://www.mathdotnet.com/) random number generator is in some situations faster.
/// Unlike Math.NET, MultiThreadedRng is multi-threaded and async. Consumers can await the next number without
/// blocking resources. Additionally, consumers can use a token to cancel e.g. timeout an operation as well.<br/><br/>
///
/// MultiThreadedRng using a shape fitter (a rejection sampler) to enforce arbitrary shapes of probabilities for
/// desired distributions. By using the shape fitter, it is even easy to define discontinuous, arbitrary functions
/// as shapes. Any consumer can define and use own distributions.<br/><br/>
///
/// This class uses the George Marsaglia's MWC algorithm. The algorithm's implementation based loosely on John D.
/// Cook's (johndcook.com) implementation (https://www.codeproject.com/Articles/25172/Simple-Random-Number-Generation).
/// Thanks John for the inspiration.<br/><br/>
///
/// Please notice: When using the debug environment, MultiThreadedRng uses a smaller buffer size. Please ensure,
/// that the production environment uses a release build, though.
/// This constructor uses the user's current local time
/// to derive necessary parameters for the generator.
/// Thus, the results are depending on the time, where
/// the generator was created.
/// </remarks>
public sealed class MultiThreadedRng : IRandom, IDisposable
public MultiThreadedRng()
{
#if DEBUG
private const int BUFFER_SIZE = 10_000;
#else
private const int BUFFER_SIZE = 1_000_000;
#endif
// The queue size means, how many buffer we store in a queue at the same time:
private const int QUEUE_SIZE = 2;
// Gets used to stop the producer threads:
private readonly CancellationTokenSource producerTokenSource = new CancellationTokenSource();
// The time a thread waits e.g. to check if the queue needs a new buffer:
private readonly TimeSpan waiter = TimeSpan.FromMilliseconds(10);
// The first queue, where to store buffers of random uint numbers:
private readonly ConcurrentQueue<uint[]> queueIntegers = new ConcurrentQueue<uint[]>();
// The second queue, where to store buffers of uniform random floating point numbers:
private readonly ConcurrentQueue<float[]> queueFloats = new ConcurrentQueue<float[]>();
// The uint producer thread:
private Thread producerRandomUint;
// The uniform float producer thread:
private Thread producerRandomUniformDistributedFloat;
// Variable w and z for the uint generator. Both get used
// as seeding variable as well (cf. constructors)
private uint mW;
private uint mZ;
// This is the current buffer for the consumer side i.e. the public interfaces:
private float[] currentBuffer = Array.Empty<float>();
// The current pointer to the next current buffer's address to read from:
private int currentBufferPointer = BUFFER_SIZE;
#region Constructors
/// <summary>
/// Creates a multi-threaded random number generator.
/// </summary>
/// <remarks>
/// This constructor uses the user's current local time
/// to derive necessary parameters for the generator.
/// Thus, the results are depending on the time, where
/// the generator was created.
/// </remarks>
public MultiThreadedRng()
{
//
// Initialize the mW and mZ by using
// the system's time.
//
var now = DateTime.Now;
var ticks = now.Ticks;
this.mW = (uint) (ticks >> 16);
this.mZ = (uint) (ticks % 4_294_967_296);
this.StartProducerThreads();
}
/// <summary>
/// Creates a multi-threaded random number generator.
/// </summary>
/// <remarks>
/// A multi-threaded random number generator created by this constructor is
/// deterministic. It's behaviour is not depending on the time of its creation.<br/><br/>
///
/// <b>Please note:</b> Although the number generator and all distributions are deterministic,
/// the behavior of the consuming application might be non-deterministic. This is possible if
/// the application with multiple threads consumes the numbers. The scheduling of the threads
/// is up to the operating system and might not be predictable.
/// </remarks>
/// <param name="seedU">A seed value to generate a deterministic generator.</param>
public MultiThreadedRng(uint seedU)
{
this.mW = seedU;
this.mZ = 362_436_069;
this.StartProducerThreads();
}
/// <summary>
/// Creates a multi-threaded random number generator.
/// </summary>
/// <remarks>
/// A multi-threaded random number generator created by this constructor is
/// deterministic. It's behaviour is not depending on the time of its creation.<br/><br/>
///
/// <b>Please note:</b> Although the number generator and all distributions are deterministic,
/// the behavior of the consuming application might be non-deterministic. This is possible if
/// the application with multiple threads consumes the numbers. The scheduling of the threads
/// is up to the operating system and might not be predictable.
/// </remarks>
/// <param name="seedU">The first seed value.</param>
/// <param name="seedV">The second seed value.</param>
public MultiThreadedRng(uint seedU, uint seedV)
{
this.mW = seedU;
this.mZ = seedV;
this.StartProducerThreads();
}
private void StartProducerThreads()
{
this.producerRandomUint = new Thread(() => this.RandomProducerUint(this.producerTokenSource.Token)) {IsBackground = true};
this.producerRandomUint.Start();
this.producerRandomUniformDistributedFloat = new Thread(() => this.RandomProducerUniformDistributedFloat(this.producerTokenSource.Token)) {IsBackground = true};
this.producerRandomUniformDistributedFloat.Start();
}
#endregion
#region Producers
[ExcludeFromCodeCoverage]
private async void RandomProducerUint(CancellationToken cancellationToken)
{
try
{
while (!cancellationToken.IsCancellationRequested)
{
// A local next buffer, which gets filled next:
var nextBuffer = new uint[BUFFER_SIZE];
// Produce the necessary number of random uints:
for (var n = 0; n < nextBuffer.Length && !cancellationToken.IsCancellationRequested; n++)
{
this.mZ = 36_969 * (this.mZ & 65_535) + (this.mZ >> 16);
this.mW = 18_000 * (this.mW & 65_535) + (this.mW >> 16);
nextBuffer[n] = (this.mZ << 16) + this.mW;
}
// Inside this loop, we try to enqueue the produced buffer:
while (!cancellationToken.IsCancellationRequested)
{
try
{
// Ensure, that we do not produce more buffers, as configured:
if (this.queueIntegers.Count < QUEUE_SIZE)
{
this.queueIntegers.Enqueue(nextBuffer);
break;
}
// The queue was full. Wait a moment and try it again:
await Task.Delay(this.waiter, cancellationToken);
}
catch (TaskCanceledException)
{
// The producers should be stopped:
return;
}
}
}
}
catch (OperationCanceledException)
{
}
}
[ExcludeFromCodeCoverage]
private async void RandomProducerUniformDistributedFloat(CancellationToken cancellationToken)
{
try
{
while (!cancellationToken.IsCancellationRequested)
{
// A local source buffer of uints:
uint[] bufferSource = null;
// Try to get the next source buffer:
while (!this.queueIntegers.TryDequeue(out bufferSource) && !cancellationToken.IsCancellationRequested)
await Task.Delay(this.waiter, cancellationToken);
// Case: The producers should be stopped:
if(bufferSource == null)
return;
// A local buffer to fill with uniform floats:
var nextBuffer = new float[BUFFER_SIZE];
// Generate the necessary number of floats:
for (var n = 0; n < nextBuffer.Length && !cancellationToken.IsCancellationRequested; n++)
nextBuffer[n] = (bufferSource[n] + 1.0f) * 2.328306435454494e-10f;
// Inside this loop, we try to enqueue the generated buffer:
while (!cancellationToken.IsCancellationRequested)
{
try
{
// Ensure, that the queue contains only the configured number of buffers:
if (this.queueFloats.Count < QUEUE_SIZE)
{
this.queueFloats.Enqueue(nextBuffer);
break;
}
// The queue was full. Wait a moment and try it again:
await Task.Delay(this.waiter, cancellationToken);
}
catch (TaskCanceledException)
{
return;
}
}
}
}
catch (OperationCanceledException)
{
}
}
#endregion
#region Implementing interface
/// <summary>
/// Returns a uniform distributed pseudo-random number from the interval (0,1].
/// This means, the result 0 is impossible, whereas 1 is possible.
/// </summary>
/// <remarks>
/// This method is thread-safe. You can consume numbers from the same generator
/// by using multiple threads at the same time.
/// </remarks>
/// <param name="cancel">An optional cancellation token.</param>
public async ValueTask<float> GetUniform(CancellationToken cancel = default)
{
while (!cancel.IsCancellationRequested)
{
// Check, if we need a new buffer to read from:
if (this.currentBufferPointer >= BUFFER_SIZE)
{
// Create a local copy of the current buffer's pointer:
var currentBufferReference = this.currentBuffer;
// Here, we store the next buffer until we implement it:
var nextBuffer = Array.Empty<float>();
// Try to get the next buffer from the queue:
while (this.currentBufferPointer >= BUFFER_SIZE && currentBufferReference == this.currentBuffer && !this.queueFloats.TryDequeue(out nextBuffer))
{
//
// Case: There is no next buffer available.
// Must wait for producer(s) to provide next.
//
try
{
await Task.Delay(this.waiter, cancel);
}
catch (TaskCanceledException)
{
//
// Case: The consumer cancelled the request.
//
return float.NaN;
}
}
//
// Note: In general, it does not matter if the following compare-exchange is successful.
// 1st case: It was successful -- everything is fine. But we are responsible to re-set the currentBufferPointer.
// 2nd case: It was not successful. This means, that another thread was successful, though.
// That case is fine as well. But we would loose one buffer of work. Thus, we
// check for this case and preserve the buffer full of work.
//
// Try to implement the dequeued buffer without locking other threads:
if (Interlocked.CompareExchange(ref this.currentBuffer, nextBuffer, currentBufferReference) != currentBufferReference)
{
//
// Case: Another thread updated the buffer already.
// Thus, we enqueue our copy of the next buffer to preserve it.
//
this.queueFloats.Enqueue(nextBuffer);
// Next? We can go ahead and yield a random number...
}
else
{
//
// Case: We updated the buffer.
//
this.currentBufferPointer = 0;
// Next? We can go ahead and yield a random number...
}
}
// Made a local copy of the current pointer:
var myPointer = this.currentBufferPointer;
// Increment the pointer for the next thread or call:
var nextPointer = myPointer + 1;
// Try to update the pointer without locking other threads:
if (Interlocked.CompareExchange(ref this.currentBufferPointer, nextPointer, myPointer) == myPointer)
{
//
// Case: Success. We updated the pointer and, thus, can use the pointer to read a number.
//
return this.currentBuffer[myPointer];
}
//
// Case: Another thread updated the pointer already. Must restart the process
// to get a random number.
//
}
//
// Case: The consumer cancelled the request.
//
return float.NaN;
}
private void StopProducer() => this.producerTokenSource.Cancel();
/// <summary>
/// Disposes this generator. It is important to dispose a generator,
/// when it is no longer needed. Otherwise, the background threads
/// are still running.
/// </summary>
public void Dispose() => this.StopProducer();
#endregion
//
// Initialize the mW and mZ by using
// the system's time.
//
var now = DateTime.Now;
var ticks = now.Ticks;
this.mW = (uint) (ticks >> 16);
this.mZ = (uint) (ticks % 4_294_967_296);
this.StartProducerThreads();
}
/// <summary>
/// Creates a multi-threaded random number generator.
/// </summary>
/// <remarks>
/// A multi-threaded random number generator created by this constructor is
/// deterministic. It's behaviour is not depending on the time of its creation.<br/><br/>
///
/// <b>Please note:</b> Although the number generator and all distributions are deterministic,
/// the behavior of the consuming application might be non-deterministic. This is possible if
/// the application with multiple threads consumes the numbers. The scheduling of the threads
/// is up to the operating system and might not be predictable.
/// </remarks>
/// <param name="seedU">A seed value to generate a deterministic generator.</param>
public MultiThreadedRng(uint seedU)
{
this.mW = seedU;
this.mZ = 362_436_069;
this.StartProducerThreads();
}
/// <summary>
/// Creates a multi-threaded random number generator.
/// </summary>
/// <remarks>
/// A multi-threaded random number generator created by this constructor is
/// deterministic. It's behaviour is not depending on the time of its creation.<br/><br/>
///
/// <b>Please note:</b> Although the number generator and all distributions are deterministic,
/// the behavior of the consuming application might be non-deterministic. This is possible if
/// the application with multiple threads consumes the numbers. The scheduling of the threads
/// is up to the operating system and might not be predictable.
/// </remarks>
/// <param name="seedU">The first seed value.</param>
/// <param name="seedV">The second seed value.</param>
public MultiThreadedRng(uint seedU, uint seedV)
{
this.mW = seedU;
this.mZ = seedV;
this.StartProducerThreads();
}
private void StartProducerThreads()
{
this.producerRandomUint = new Thread(() => this.RandomProducerUint(this.producerTokenSource.Token)) {IsBackground = true};
this.producerRandomUint.Start();
this.producerRandomUniformDistributedFloat = new Thread(() => this.RandomProducerUniformDistributedFloat(this.producerTokenSource.Token)) {IsBackground = true};
this.producerRandomUniformDistributedFloat.Start();
}
#endregion
#region Producers
[ExcludeFromCodeCoverage]
private async void RandomProducerUint(CancellationToken cancellationToken)
{
try
{
while (!cancellationToken.IsCancellationRequested)
{
// A local next buffer, which gets filled next:
var nextBuffer = new uint[BUFFER_SIZE];
// Produce the necessary number of random uints:
for (var n = 0; n < nextBuffer.Length && !cancellationToken.IsCancellationRequested; n++)
{
this.mZ = 36_969 * (this.mZ & 65_535) + (this.mZ >> 16);
this.mW = 18_000 * (this.mW & 65_535) + (this.mW >> 16);
nextBuffer[n] = (this.mZ << 16) + this.mW;
}
// Inside this loop, we try to enqueue the produced buffer:
while (!cancellationToken.IsCancellationRequested)
{
try
{
// Ensure, that we do not produce more buffers, as configured:
if (this.queueIntegers.Count < QUEUE_SIZE)
{
this.queueIntegers.Enqueue(nextBuffer);
break;
}
// The queue was full. Wait a moment and try it again:
await Task.Delay(this.waiter, cancellationToken);
}
catch (TaskCanceledException)
{
// The producers should be stopped:
return;
}
}
}
}
catch (OperationCanceledException)
{
}
}
[ExcludeFromCodeCoverage]
private async void RandomProducerUniformDistributedFloat(CancellationToken cancellationToken)
{
try
{
while (!cancellationToken.IsCancellationRequested)
{
// A local source buffer of uints:
uint[] bufferSource = null;
// Try to get the next source buffer:
while (!this.queueIntegers.TryDequeue(out bufferSource) && !cancellationToken.IsCancellationRequested)
await Task.Delay(this.waiter, cancellationToken);
// Case: The producers should be stopped:
if(bufferSource == null)
return;
// A local buffer to fill with uniform floats:
var nextBuffer = new float[BUFFER_SIZE];
// Generate the necessary number of floats:
for (var n = 0; n < nextBuffer.Length && !cancellationToken.IsCancellationRequested; n++)
nextBuffer[n] = (bufferSource[n] + 1.0f) * 2.328306435454494e-10f;
// Inside this loop, we try to enqueue the generated buffer:
while (!cancellationToken.IsCancellationRequested)
{
try
{
// Ensure, that the queue contains only the configured number of buffers:
if (this.queueFloats.Count < QUEUE_SIZE)
{
this.queueFloats.Enqueue(nextBuffer);
break;
}
// The queue was full. Wait a moment and try it again:
await Task.Delay(this.waiter, cancellationToken);
}
catch (TaskCanceledException)
{
return;
}
}
}
}
catch (OperationCanceledException)
{
}
}
#endregion
#region Implementing interface
/// <summary>
/// Returns a uniform distributed pseudo-random number from the interval (0,1].
/// This means, the result 0 is impossible, whereas 1 is possible.
/// </summary>
/// <remarks>
/// This method is thread-safe. You can consume numbers from the same generator
/// by using multiple threads at the same time.
/// </remarks>
/// <param name="cancel">An optional cancellation token.</param>
public async ValueTask<float> GetUniform(CancellationToken cancel = default)
{
while (!cancel.IsCancellationRequested)
{
// Check, if we need a new buffer to read from:
if (this.currentBufferPointer >= BUFFER_SIZE)
{
// Create a local copy of the current buffer's pointer:
var currentBufferReference = this.currentBuffer;
// Here, we store the next buffer until we implement it:
var nextBuffer = Array.Empty<float>();
// Try to get the next buffer from the queue:
while (this.currentBufferPointer >= BUFFER_SIZE && currentBufferReference == this.currentBuffer && !this.queueFloats.TryDequeue(out nextBuffer))
{
//
// Case: There is no next buffer available.
// Must wait for producer(s) to provide next.
//
try
{
await Task.Delay(this.waiter, cancel);
}
catch (TaskCanceledException)
{
//
// Case: The consumer cancelled the request.
//
return float.NaN;
}
}
//
// Note: In general, it does not matter if the following compare-exchange is successful.
// 1st case: It was successful -- everything is fine. But we are responsible to re-set the currentBufferPointer.
// 2nd case: It was not successful. This means, that another thread was successful, though.
// That case is fine as well. But we would loose one buffer of work. Thus, we
// check for this case and preserve the buffer full of work.
//
// Try to implement the dequeued buffer without locking other threads:
if (Interlocked.CompareExchange(ref this.currentBuffer, nextBuffer, currentBufferReference) != currentBufferReference)
{
//
// Case: Another thread updated the buffer already.
// Thus, we enqueue our copy of the next buffer to preserve it.
//
this.queueFloats.Enqueue(nextBuffer);
// Next? We can go ahead and yield a random number...
}
else
{
//
// Case: We updated the buffer.
//
this.currentBufferPointer = 0;
// Next? We can go ahead and yield a random number...
}
}
// Made a local copy of the current pointer:
var myPointer = this.currentBufferPointer;
// Increment the pointer for the next thread or call:
var nextPointer = myPointer + 1;
// Try to update the pointer without locking other threads:
if (Interlocked.CompareExchange(ref this.currentBufferPointer, nextPointer, myPointer) == myPointer)
{
//
// Case: Success. We updated the pointer and, thus, can use the pointer to read a number.
//
return this.currentBuffer[myPointer];
}
//
// Case: Another thread updated the pointer already. Must restart the process
// to get a random number.
//
}
//
// Case: The consumer cancelled the request.
//
return float.NaN;
}
private void StopProducer() => this.producerTokenSource.Cancel();
/// <summary>
/// Disposes this generator. It is important to dispose a generator,
/// when it is no longer needed. Otherwise, the background threads
/// are still running.
/// </summary>
public void Dispose() => this.StopProducer();
#endregion
}

115
FastRng/ShapeFitter.cs
View File

@ -3,76 +3,75 @@ using System.Threading;
using System.Threading.Tasks;
using FastRng.Distributions;
namespace FastRng
namespace FastRng;
/// <summary>
/// ShapeFitter is a rejection sampler, cf. https://en.wikipedia.org/wiki/Rejection_sampling
/// </summary>
public sealed class ShapeFitter
{
private readonly float[] probabilities;
private readonly IRandom rng;
private readonly float max;
private readonly float sampleSize;
private readonly IDistribution uniform;
/// <summary>
/// ShapeFitter is a rejection sampler, cf. https://en.wikipedia.org/wiki/Rejection_sampling
/// Creates a shape fitter instance.
/// </summary>
public sealed class ShapeFitter
/// <param name="shapeFunction">The function which describes the desired shape.</param>
/// <param name="rng">The random number generator instance to use.</param>
/// <param name="sampleSize">The number of sampling steps to sample the given function.</param>
public ShapeFitter(Func<float, float> shapeFunction, IRandom rng, ushort sampleSize = 50)
{
private readonly float[] probabilities;
private readonly IRandom rng;
private readonly float max;
private readonly float sampleSize;
private readonly IDistribution uniform;
this.rng = rng;
this.uniform = new Uniform(rng);
this.sampleSize = sampleSize;
this.probabilities = new float[sampleSize];
/// <summary>
/// Creates a shape fitter instance.
/// </summary>
/// <param name="shapeFunction">The function which describes the desired shape.</param>
/// <param name="rng">The random number generator instance to use.</param>
/// <param name="sampleSize">The number of sampling steps to sample the given function.</param>
public ShapeFitter(Func<float, float> shapeFunction, IRandom rng, ushort sampleSize = 50)
var sampleStepSize = 1.0f / sampleSize;
var nextStep = 0.0f + sampleStepSize;
var maxValue = 0.0f;
for (var n = 0; n < sampleSize; n++)
{
this.rng = rng;
this.uniform = new Uniform(rng);
this.sampleSize = sampleSize;
this.probabilities = new float[sampleSize];
var sampleStepSize = 1.0f / sampleSize;
var nextStep = 0.0f + sampleStepSize;
var maxValue = 0.0f;
for (var n = 0; n < sampleSize; n++)
{
this.probabilities[n] = shapeFunction(nextStep);
if (this.probabilities[n] > maxValue)
maxValue = this.probabilities[n];
this.probabilities[n] = shapeFunction(nextStep);
if (this.probabilities[n] > maxValue)
maxValue = this.probabilities[n];
nextStep += sampleStepSize;
}
this.max = maxValue;
nextStep += sampleStepSize;
}
/// <summary>
/// Returns a random number regarding the given shape.
/// </summary>
/// <param name="token">An optional cancellation token.</param>
/// <returns>The next value regarding the given shape.</returns>
public async ValueTask<float> NextNumber(CancellationToken token = default)
{
while (!token.IsCancellationRequested)
{
var x = await this.rng.GetUniform(token);
if (float.IsNaN(x))
return x;
var nextBucket = (int)MathF.Floor(x * this.sampleSize);
if (nextBucket >= this.probabilities.Length)
nextBucket = this.probabilities.Length - 1;
var threshold = this.probabilities[nextBucket];
var y = await this.uniform.NextNumber(0.0f, this.max, token);
if (float.IsNaN(y))
return y;
if(y > threshold)
continue;
this.max = maxValue;
}
/// <summary>
/// Returns a random number regarding the given shape.
/// </summary>
/// <param name="token">An optional cancellation token.</param>
/// <returns>The next value regarding the given shape.</returns>
public async ValueTask<float> NextNumber(CancellationToken token = default)
{
while (!token.IsCancellationRequested)
{
var x = await this.rng.GetUniform(token);
if (float.IsNaN(x))
return x;
}
var nextBucket = (int)MathF.Floor(x * this.sampleSize);
if (nextBucket >= this.probabilities.Length)
nextBucket = this.probabilities.Length - 1;
var threshold = this.probabilities[nextBucket];
var y = await this.uniform.NextNumber(0.0f, this.max, token);
if (float.IsNaN(y))
return y;
if(y > threshold)
continue;
return float.NaN;
return x;
}
return float.NaN;
}
}

81
FastRngTests/DecisionTester.cs
View File

@ -6,57 +6,56 @@ using NUnit.Framework;
using Uniform = FastRng.Distributions.Uniform;
using WeibullK05La1 = FastRng.Distributions.WeibullK05La1;
namespace FastRngTests
namespace FastRngTests;
[ExcludeFromCodeCoverage]
public class DecisionTester
{
[ExcludeFromCodeCoverage]
public class DecisionTester
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task DecisionUniform01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task DecisionUniform01()
{
using var rng = new MultiThreadedRng();
var dist = new Uniform(rng);
using var rng = new MultiThreadedRng();
var dist = new Uniform(rng);
var neededCoinTossesA = 0;
var neededCoinTossesB = 0;
var neededCoinTossesC = 0;
var neededCoinTossesA = 0;
var neededCoinTossesB = 0;
var neededCoinTossesC = 0;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.0f, 0.1f)) neededCoinTossesA++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.5f, 0.6f)) neededCoinTossesB++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.8f, 0.9f)) neededCoinTossesC++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.0f, 0.1f)) neededCoinTossesA++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.5f, 0.6f)) neededCoinTossesB++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.8f, 0.9f)) neededCoinTossesC++;
var values = new[] {neededCoinTossesA, neededCoinTossesB, neededCoinTossesC};
var max = values.Max();
var min = values.Min();
var values = new[] {neededCoinTossesA, neededCoinTossesB, neededCoinTossesC};
var max = values.Max();
var min = values.Min();
TestContext.WriteLine($"Coin tosses: a={neededCoinTossesA}, b={neededCoinTossesB}, c={neededCoinTossesC}");
Assert.That(max - min, Is.LessThanOrEqualTo(250));
}
TestContext.WriteLine($"Coin tosses: a={neededCoinTossesA}, b={neededCoinTossesB}, c={neededCoinTossesC}");
Assert.That(max - min, Is.LessThanOrEqualTo(250));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task DecisionWeibull01()
{
using var rng = new MultiThreadedRng();
var dist = new WeibullK05La1(rng);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task DecisionWeibull01()
{
using var rng = new MultiThreadedRng();
var dist = new WeibullK05La1(rng);
var neededCoinTossesA = 0;
var neededCoinTossesB = 0;
var neededCoinTossesC = 0;
var neededCoinTossesA = 0;
var neededCoinTossesB = 0;
var neededCoinTossesC = 0;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.0f, 0.1f)) neededCoinTossesA++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.5f, 0.6f)) neededCoinTossesB++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.8f, 0.9f)) neededCoinTossesC++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.0f, 0.1f)) neededCoinTossesA++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.5f, 0.6f)) neededCoinTossesB++;
for(var n = 0; n < 100; n++) while (!await dist.HasDecisionBeenMade(0.8f, 0.9f)) neededCoinTossesC++;
var values = new[] {neededCoinTossesA, neededCoinTossesB, neededCoinTossesC};
var max = values.Max();
var min = values.Min();
var values = new[] {neededCoinTossesA, neededCoinTossesB, neededCoinTossesC};
var max = values.Max();
var min = values.Min();
TestContext.WriteLine($"Coin tosses: a={neededCoinTossesA}, b={neededCoinTossesB}, c={neededCoinTossesC}");
Assert.That(max - min, Is.LessThanOrEqualTo(2_800));
}
TestContext.WriteLine($"Coin tosses: a={neededCoinTossesA}, b={neededCoinTossesB}, c={neededCoinTossesC}");
Assert.That(max - min, Is.LessThanOrEqualTo(2_800));
}
}

121
FastRngTests/Distributions/BetaA2B2.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class BetaA2B2
{
[ExcludeFromCodeCoverage]
public class BetaA2B2
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.BetaA2B2(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.BetaA2B2(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0396f).Within(0.3f));
Assert.That(result[1], Is.EqualTo(0.0784f).Within(0.3f));
Assert.That(result[2], Is.EqualTo(0.1164f).Within(0.3f));
Assert.That(result[0], Is.EqualTo(0.0396f).Within(0.3f));
Assert.That(result[1], Is.EqualTo(0.0784f).Within(0.3f));
Assert.That(result[2], Is.EqualTo(0.1164f).Within(0.3f));
Assert.That(result[21], Is.EqualTo(0.6864f).Within(0.3f));
Assert.That(result[22], Is.EqualTo(0.7084f).Within(0.3f));
Assert.That(result[23], Is.EqualTo(0.7296f).Within(0.3f));
Assert.That(result[21], Is.EqualTo(0.6864f).Within(0.3f));
Assert.That(result[22], Is.EqualTo(0.7084f).Within(0.3f));
Assert.That(result[23], Is.EqualTo(0.7296f).Within(0.3f));
Assert.That(result[50], Is.EqualTo(0.9996f).Within(0.3f));
Assert.That(result[50], Is.EqualTo(0.9996f).Within(0.3f));
Assert.That(result[75], Is.EqualTo(0.7296f).Within(0.3f));
Assert.That(result[85], Is.EqualTo(0.4816f).Within(0.3f));
Assert.That(result[90], Is.EqualTo(0.3276f).Within(0.3f));
Assert.That(result[75], Is.EqualTo(0.7296f).Within(0.3f));
Assert.That(result[85], Is.EqualTo(0.4816f).Within(0.3f));
Assert.That(result[90], Is.EqualTo(0.3276f).Within(0.3f));
Assert.That(result[97], Is.EqualTo(0.0784f).Within(0.3f));
Assert.That(result[98], Is.EqualTo(0.0396f).Within(0.3f));
Assert.That(result[99], Is.EqualTo(0.0000f).Within(0.3f));
}
Assert.That(result[97], Is.EqualTo(0.0784f).Within(0.3f));
Assert.That(result[98], Is.EqualTo(0.0396f).Within(0.3f));
Assert.That(result[99], Is.EqualTo(0.0000f).Within(0.3f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.BetaA2B2(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.BetaA2B2(null));
}
}

121
FastRngTests/Distributions/BetaA2B5.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class BetaA2B5
{
[ExcludeFromCodeCoverage]
public class BetaA2B5
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.BetaA2B5(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.BetaA2B5(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.11719271f).Within(0.3f));
Assert.That(result[1], Is.EqualTo(0.22505783f).Within(0.3f));
Assert.That(result[2], Is.EqualTo(0.32401717f).Within(0.3f));
Assert.That(result[0], Is.EqualTo(0.11719271f).Within(0.3f));
Assert.That(result[1], Is.EqualTo(0.22505783f).Within(0.3f));
Assert.That(result[2], Is.EqualTo(0.32401717f).Within(0.3f));
Assert.That(result[21], Is.EqualTo(0.99348410f).Within(0.3f));
Assert.That(result[22], Is.EqualTo(0.98639433f).Within(0.3f));
Assert.That(result[23], Is.EqualTo(0.97684451f).Within(0.3f));
Assert.That(result[21], Is.EqualTo(0.99348410f).Within(0.3f));
Assert.That(result[22], Is.EqualTo(0.98639433f).Within(0.3f));
Assert.That(result[23], Is.EqualTo(0.97684451f).Within(0.3f));
Assert.That(result[50], Is.EqualTo(0.35868592f).Within(0.3f));
Assert.That(result[50], Is.EqualTo(0.35868592f).Within(0.3f));
Assert.That(result[75], Is.EqualTo(0.03076227f).Within(0.03f));
Assert.That(result[85], Is.EqualTo(0.00403061f).Within(0.03f));
Assert.That(result[90], Is.EqualTo(0.00109800f).Within(0.01f));
Assert.That(result[75], Is.EqualTo(0.03076227f).Within(0.03f));
Assert.That(result[85], Is.EqualTo(0.00403061f).Within(0.03f));
Assert.That(result[90], Is.EqualTo(0.00109800f).Within(0.01f));
Assert.That(result[97], Is.EqualTo(0.00000191f).Within(0.000003f));
Assert.That(result[98], Is.EqualTo(0.00000012f).Within(0.0000003f));
Assert.That(result[99], Is.EqualTo(0.00000000f).Within(0.0000003f));
}
Assert.That(result[97], Is.EqualTo(0.00000191f).Within(0.000003f));
Assert.That(result[98], Is.EqualTo(0.00000012f).Within(0.0000003f));
Assert.That(result[99], Is.EqualTo(0.00000000f).Within(0.0000003f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B5(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B5(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B5(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA2B5(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.BetaA2B5(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.BetaA2B5(null));
}
}

121
FastRngTests/Distributions/BetaA5B2.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class BetaA5B2
{
[ExcludeFromCodeCoverage]
public class BetaA5B2
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.BetaA5B2(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.BetaA5B2(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0000001f).Within(0.0000003f));
Assert.That(result[1], Is.EqualTo(0.0000019f).Within(0.00001f));
Assert.That(result[2], Is.EqualTo(0.0000096f).Within(0.0004f));
Assert.That(result[0], Is.EqualTo(0.0000001f).Within(0.0000003f));
Assert.That(result[1], Is.EqualTo(0.0000019f).Within(0.00001f));
Assert.That(result[2], Is.EqualTo(0.0000096f).Within(0.0004f));
Assert.That(result[21], Is.EqualTo(0.0222918f).Within(0.03f));
Assert.That(result[22], Is.EqualTo(0.0262883f).Within(0.03f));
Assert.That(result[23], Is.EqualTo(0.0307623f).Within(0.03f));
Assert.That(result[21], Is.EqualTo(0.0222918f).Within(0.03f));
Assert.That(result[22], Is.EqualTo(0.0262883f).Within(0.03f));
Assert.That(result[23], Is.EqualTo(0.0307623f).Within(0.03f));
Assert.That(result[50], Is.EqualTo(0.4044237f).Within(0.2f));
Assert.That(result[50], Is.EqualTo(0.4044237f).Within(0.2f));
Assert.That(result[75], Is.EqualTo(0.9768445f).Within(0.15f));
Assert.That(result[85], Is.EqualTo(0.9552714f).Within(0.15f));
Assert.That(result[90], Is.EqualTo(0.8004420f).Within(0.35f));
Assert.That(result[75], Is.EqualTo(0.9768445f).Within(0.15f));
Assert.That(result[85], Is.EqualTo(0.9552714f).Within(0.15f));
Assert.That(result[90], Is.EqualTo(0.8004420f).Within(0.35f));
Assert.That(result[97], Is.EqualTo(0.2250578f).Within(0.03f));
Assert.That(result[98], Is.EqualTo(0.1171927f).Within(0.03f));
Assert.That(result[99], Is.EqualTo(0f).Within(0.0004f));
}
Assert.That(result[97], Is.EqualTo(0.2250578f).Within(0.03f));
Assert.That(result[98], Is.EqualTo(0.1171927f).Within(0.03f));
Assert.That(result[99], Is.EqualTo(0f).Within(0.0004f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA5B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA5B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA5B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestBetaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.BetaA5B2(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.BetaA5B2(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.BetaA5B2(null));
}
}

125
FastRngTests/Distributions/CauchyLorentzX0.cs
View File

@ -5,83 +5,82 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class CauchyLorentzX0
{
[ExcludeFromCodeCoverage]
public class CauchyLorentzX0
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyDistribution01()
{
// The properties of the cauchy distribution cannot be tested by mean, media or variance,
// cf. https://en.wikipedia.org/wiki/Cauchy_distribution#Explanation_of_undefined_moments
// The properties of the cauchy distribution cannot be tested by mean, media or variance,
// cf. https://en.wikipedia.org/wiki/Cauchy_distribution#Explanation_of_undefined_moments
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.976990739772031f).Within(0.06f));
Assert.That(result[1], Is.EqualTo(0.948808314586299f).Within(0.06f));
Assert.That(result[2], Is.EqualTo(0.905284997403441f).Within(0.06f));
Assert.That(result[0], Is.EqualTo(0.976990739772031f).Within(0.06f));
Assert.That(result[1], Is.EqualTo(0.948808314586299f).Within(0.06f));
Assert.That(result[2], Is.EqualTo(0.905284997403441f).Within(0.06f));
Assert.That(result[21], Is.EqualTo(0.168965864241396f).Within(0.04f));
Assert.That(result[22], Is.EqualTo(0.156877686354491f).Within(0.04f));
Assert.That(result[23], Is.EqualTo(0.145970509936354f).Within(0.04f));
Assert.That(result[21], Is.EqualTo(0.168965864241396f).Within(0.04f));
Assert.That(result[22], Is.EqualTo(0.156877686354491f).Within(0.04f));
Assert.That(result[23], Is.EqualTo(0.145970509936354f).Within(0.04f));
Assert.That(result[50], Is.EqualTo(0.036533159835978f).Within(0.01f));
Assert.That(result[50], Is.EqualTo(0.036533159835978f).Within(0.01f));
Assert.That(result[75], Is.EqualTo(0.016793067514802f).Within(0.01f));
Assert.That(result[85], Is.EqualTo(0.01316382933791f).Within(0.005f));
Assert.That(result[90], Is.EqualTo(0.011773781734516f).Within(0.005f));
Assert.That(result[75], Is.EqualTo(0.016793067514802f).Within(0.01f));
Assert.That(result[85], Is.EqualTo(0.01316382933791f).Within(0.005f));
Assert.That(result[90], Is.EqualTo(0.011773781734516f).Within(0.005f));
Assert.That(result[97], Is.EqualTo(0.010168596941156f).Within(0.005f));
Assert.That(result[98], Is.EqualTo(0.009966272570142f).Within(0.005f));
Assert.That(result[99], Is.EqualTo(0.00976990739772f).Within(0.005f));
}
Assert.That(result[97], Is.EqualTo(0.010168596941156f).Within(0.005f));
Assert.That(result[98], Is.EqualTo(0.009966272570142f).Within(0.005f));
Assert.That(result[99], Is.EqualTo(0.00976990739772f).Within(0.005f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.CauchyLorentzX0(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.CauchyLorentzX0(null));
}
}

125
FastRngTests/Distributions/CauchyLorentzX1.cs
View File

@ -5,83 +5,82 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class CauchyLorentzX1
{
[ExcludeFromCodeCoverage]
public class CauchyLorentzX1
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyDistribution01()
{
// The properties of the cauchy distribution cannot be tested by mean, media or variance,
// cf. https://en.wikipedia.org/wiki/Cauchy_distribution#Explanation_of_undefined_moments
// The properties of the cauchy distribution cannot be tested by mean, media or variance,
// cf. https://en.wikipedia.org/wiki/Cauchy_distribution#Explanation_of_undefined_moments
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX1(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX1(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.009966272570142f).Within(0.003f));
Assert.That(result[1], Is.EqualTo(0.010168596941156f).Within(0.004f));
Assert.That(result[2], Is.EqualTo(0.010377123221893f).Within(0.005f));
Assert.That(result[0], Is.EqualTo(0.009966272570142f).Within(0.003f));
Assert.That(result[1], Is.EqualTo(0.010168596941156f).Within(0.004f));
Assert.That(result[2], Is.EqualTo(0.010377123221893f).Within(0.005f));
Assert.That(result[21], Is.EqualTo(0.015956672819692f).Within(0.005f));
Assert.That(result[22], Is.EqualTo(0.016366904083094f).Within(0.005f));
Assert.That(result[23], Is.EqualTo(0.016793067514802f).Within(0.005f));
Assert.That(result[21], Is.EqualTo(0.015956672819692f).Within(0.005f));
Assert.That(result[22], Is.EqualTo(0.016366904083094f).Within(0.005f));
Assert.That(result[23], Is.EqualTo(0.016793067514802f).Within(0.005f));
Assert.That(result[50], Is.EqualTo(0.039454644029179f).Within(0.015f));
Assert.That(result[50], Is.EqualTo(0.039454644029179f).Within(0.015f));
Assert.That(result[75], Is.EqualTo(0.145970509936354f).Within(0.03f));
Assert.That(result[85], Is.EqualTo(0.333365083503296f).Within(0.1f));
Assert.That(result[90], Is.EqualTo(0.545171628270584f).Within(0.1f));
Assert.That(result[75], Is.EqualTo(0.145970509936354f).Within(0.03f));
Assert.That(result[85], Is.EqualTo(0.333365083503296f).Within(0.1f));
Assert.That(result[90], Is.EqualTo(0.545171628270584f).Within(0.1f));
Assert.That(result[97], Is.EqualTo(0.948808314586302f).Within(0.06f));
Assert.That(result[98], Is.EqualTo(0.976990739772032f).Within(0.03f));
Assert.That(result[99], Is.EqualTo(0.986760647169751f).Within(0.02f));
}
Assert.That(result[97], Is.EqualTo(0.948808314586302f).Within(0.06f));
Assert.That(result[98], Is.EqualTo(0.976990739772032f).Within(0.03f));
Assert.That(result[99], Is.EqualTo(0.986760647169751f).Within(0.02f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestCauchyGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.CauchyLorentzX0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.CauchyLorentzX1(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.CauchyLorentzX1(null));
}
}

127
FastRngTests/Distributions/ChiSquareK1.cs
View File

@ -5,83 +5,82 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class ChiSquareK1
{
[ExcludeFromCodeCoverage]
public class ChiSquareK1
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK1(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK1(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
var value = await dist.NextNumber();
fqa.CountThis(value);
}
for (var n = 0; n < 100_000; n++)
{
var value = await dist.NextNumber();
fqa.CountThis(value);
}
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.00032041964207f).Within(0.004f));
Assert.That(result[1], Is.EqualTo(0.70380551227703f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.571788691668126f).Within(0.05f));
Assert.That(result[0], Is.EqualTo(1.00032041964207f).Within(0.004f));
Assert.That(result[1], Is.EqualTo(0.70380551227703f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.571788691668126f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.192011337664754f).Within(0.07f));
Assert.That(result[22], Is.EqualTo(0.186854182385981f).Within(0.07f));
Assert.That(result[23], Is.EqualTo(0.182007652359976f).Within(0.07f));
Assert.That(result[21], Is.EqualTo(0.192011337664754f).Within(0.07f));
Assert.That(result[22], Is.EqualTo(0.186854182385981f).Within(0.07f));
Assert.That(result[23], Is.EqualTo(0.182007652359976f).Within(0.07f));
Assert.That(result[50], Is.EqualTo(0.109088865614875f).Within(0.06f));
Assert.That(result[50], Is.EqualTo(0.109088865614875f).Within(0.06f));
Assert.That(result[75], Is.EqualTo(0.07886274821701f).Within(0.02f));
Assert.That(result[85], Is.EqualTo(0.070520397849883f).Within(0.02f));
Assert.That(result[90], Is.EqualTo(0.066863009640287f).Within(0.02f));
Assert.That(result[75], Is.EqualTo(0.07886274821701f).Within(0.02f));
Assert.That(result[85], Is.EqualTo(0.070520397849883f).Within(0.02f));
Assert.That(result[90], Is.EqualTo(0.066863009640287f).Within(0.02f));
Assert.That(result[97], Is.EqualTo(0.062214737436948f).Within(0.02f));
Assert.That(result[98], Is.EqualTo(0.061590997922187f).Within(0.02f));
Assert.That(result[99], Is.EqualTo(0.060976622578824f).Within(0.02f));
}
Assert.That(result[97], Is.EqualTo(0.062214737436948f).Within(0.02f));
Assert.That(result[98], Is.EqualTo(0.061590997922187f).Within(0.02f));
Assert.That(result[99], Is.EqualTo(0.060976622578824f).Within(0.02f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ChiSquareK1(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ChiSquareK1(null));
}
}

137
FastRngTests/Distributions/ChiSquareK10.cs
View File

@ -5,83 +5,82 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class ChiSquareK10
{
[ExcludeFromCodeCoverage]
public class ChiSquareK10
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareDistribution01()
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK10(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK10(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
var value = await dist.NextNumber();
fqa.CountThis(value);
}
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0000000164021588f).Within(0.0000002f));
Assert.That(result[1], Is.EqualTo(0.0000002611256437f).Within(0.000003f));
Assert.That(result[2], Is.EqualTo(0.0000013153553250f).Within(0.00002f));
Assert.That(result[21], Is.EqualTo(0.003459320622874f).Within(0.005f));
Assert.That(result[22], Is.EqualTo(0.004111875573379f).Within(0.005f));
Assert.That(result[23], Is.EqualTo(0.004850674298859f).Within(0.005f));
Assert.That(result[50], Is.EqualTo(0.086418773275056f).Within(0.05f));
Assert.That(result[75], Is.EqualTo(0.376092741436046f).Within(0.08f));
Assert.That(result[85], Is.EqualTo(0.586569751611096f).Within(0.08f));
Assert.That(result[90], Is.EqualTo(0.717189736168766f).Within(0.08f));
Assert.That(result[97], Is.EqualTo(0.931477764640217f).Within(0.08f));
Assert.That(result[98], Is.EqualTo(0.965244855212136f).Within(0.08f));
Assert.That(result[99], Is.EqualTo(0.999827884370044f).Within(0.08f));
var value = await dist.NextNumber();
fqa.CountThis(value);
}
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0000000164021588f).Within(0.0000002f));
Assert.That(result[1], Is.EqualTo(0.0000002611256437f).Within(0.000003f));
Assert.That(result[2], Is.EqualTo(0.0000013153553250f).Within(0.00002f));
Assert.That(result[21], Is.EqualTo(0.003459320622874f).Within(0.005f));
Assert.That(result[22], Is.EqualTo(0.004111875573379f).Within(0.005f));
Assert.That(result[23], Is.EqualTo(0.004850674298859f).Within(0.005f));
Assert.That(result[50], Is.EqualTo(0.086418773275056f).Within(0.05f));
Assert.That(result[75], Is.EqualTo(0.376092741436046f).Within(0.08f));
Assert.That(result[85], Is.EqualTo(0.586569751611096f).Within(0.08f));
Assert.That(result[90], Is.EqualTo(0.717189736168766f).Within(0.08f));
Assert.That(result[97], Is.EqualTo(0.931477764640217f).Within(0.08f));
Assert.That(result[98], Is.EqualTo(0.965244855212136f).Within(0.08f));
Assert.That(result[99], Is.EqualTo(0.999827884370044f).Within(0.08f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ChiSquareK10(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ChiSquareK10(null));
}
}

121
FastRngTests/Distributions/ChiSquareK4.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class ChiSquareK4
{
[ExcludeFromCodeCoverage]
public class ChiSquareK4
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK4(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK4(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.016417705906679f).Within(0.02f));
Assert.That(result[1], Is.EqualTo(0.032671644513723f).Within(0.02f));
Assert.That(result[2], Is.EqualTo(0.048763041010352f).Within(0.02f));
Assert.That(result[0], Is.EqualTo(0.016417705906679f).Within(0.02f));
Assert.That(result[1], Is.EqualTo(0.032671644513723f).Within(0.02f));
Assert.That(result[2], Is.EqualTo(0.048763041010352f).Within(0.02f));
Assert.That(result[21], Is.EqualTo(0.32518779111264f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.338273451612642f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.351220492939994f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.32518779111264f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.338273451612642f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.351220492939994f).Within(0.05f));
Assert.That(result[50], Is.EqualTo(0.65209223303425f).Within(0.08f));
Assert.That(result[50], Is.EqualTo(0.65209223303425f).Within(0.08f));
Assert.That(result[75], Is.EqualTo(0.857562207152294f).Within(0.099f));
Assert.That(result[85], Is.EqualTo(0.923072405412387f).Within(0.099f));
Assert.That(result[90], Is.EqualTo(0.952623623874265f).Within(0.099f));
Assert.That(result[75], Is.EqualTo(0.857562207152294f).Within(0.099f));
Assert.That(result[85], Is.EqualTo(0.923072405412387f).Within(0.099f));
Assert.That(result[90], Is.EqualTo(0.952623623874265f).Within(0.099f));
Assert.That(result[97], Is.EqualTo(0.990616879396201f).Within(0.099f));
Assert.That(result[98], Is.EqualTo(0.995734077068522f).Within(0.099f));
Assert.That(result[99], Is.EqualTo(1.00077558852585f).Within(0.1f));
}
Assert.That(result[97], Is.EqualTo(0.990616879396201f).Within(0.099f));
Assert.That(result[98], Is.EqualTo(0.995734077068522f).Within(0.099f));
Assert.That(result[99], Is.EqualTo(1.00077558852585f).Within(0.1f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK4(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK4(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK4(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestChiSquareGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ChiSquareK4(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ChiSquareK4(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ChiSquareK4(null));
}
}

121
FastRngTests/Distributions/ExponentialLa10.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class ExponentialLa10
{
[ExcludeFromCodeCoverage]
public class ExponentialLa10
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa10(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa10(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.00075018434777f).Within(0.05f));
Assert.That(result[1], Is.EqualTo(0.905516212904248f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.81934495207398f).Within(0.05f));
Assert.That(result[0], Is.EqualTo(1.00075018434777f).Within(0.05f));
Assert.That(result[1], Is.EqualTo(0.905516212904248f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.81934495207398f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.122548293148741f).Within(0.12f));
Assert.That(result[22], Is.EqualTo(0.110886281157421f).Within(0.12f));
Assert.That(result[23], Is.EqualTo(0.10033405633809f).Within(0.12f));
Assert.That(result[21], Is.EqualTo(0.122548293148741f).Within(0.12f));
Assert.That(result[22], Is.EqualTo(0.110886281157421f).Within(0.12f));
Assert.That(result[23], Is.EqualTo(0.10033405633809f).Within(0.12f));
Assert.That(result[50], Is.EqualTo(0.00674300170146f).Within(0.005f));
Assert.That(result[50], Is.EqualTo(0.00674300170146f).Within(0.005f));
Assert.That(result[75], Is.EqualTo(0.000553499285385f).Within(0.001f));
Assert.That(result[85], Is.EqualTo(0.000203621007796f).Within(0.001f));
Assert.That(result[90], Is.EqualTo(0.00012350238419f).Within(0.001f));
Assert.That(result[75], Is.EqualTo(0.000553499285385f).Within(0.001f));
Assert.That(result[85], Is.EqualTo(0.000203621007796f).Within(0.001f));
Assert.That(result[90], Is.EqualTo(0.00012350238419f).Within(0.001f));
Assert.That(result[97], Is.EqualTo(0.0000613294689720f).Within(0.0008f));
Assert.That(result[98], Is.EqualTo(0.0000554931983541f).Within(0.0008f));
Assert.That(result[99], Is.EqualTo(0.0000502123223173f).Within(0.0008f));
}
Assert.That(result[97], Is.EqualTo(0.0000613294689720f).Within(0.0008f));
Assert.That(result[98], Is.EqualTo(0.0000554931983541f).Within(0.0008f));
Assert.That(result[99], Is.EqualTo(0.0000502123223173f).Within(0.0008f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ExponentialLa10(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ExponentialLa10(null));
}
}

121
FastRngTests/Distributions/ExponentialLa5.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class ExponentialLa5
{
[ExcludeFromCodeCoverage]
public class ExponentialLa5
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa5(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa5(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.0002177398625f).Within(0.05f));
Assert.That(result[1], Is.EqualTo(0.951436545064811f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.905034437210948f).Within(0.05f));
Assert.That(result[0], Is.EqualTo(1.0002177398625f).Within(0.05f));
Assert.That(result[1], Is.EqualTo(0.951436545064811f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.905034437210948f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.35001394450853f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.332943563002074f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.31670571382568f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.35001394450853f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.332943563002074f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.31670571382568f).Within(0.05f));
Assert.That(result[50], Is.EqualTo(0.082102871800213f).Within(0.01f));
Assert.That(result[50], Is.EqualTo(0.082102871800213f).Within(0.01f));
Assert.That(result[75], Is.EqualTo(0.023522866606758f).Within(0.01f));
Assert.That(result[85], Is.EqualTo(0.014267339801329f).Within(0.01f));
Assert.That(result[90], Is.EqualTo(0.011111415409621f).Within(0.01f));
Assert.That(result[75], Is.EqualTo(0.023522866606758f).Within(0.01f));
Assert.That(result[85], Is.EqualTo(0.014267339801329f).Within(0.01f));
Assert.That(result[90], Is.EqualTo(0.011111415409621f).Within(0.01f));
Assert.That(result[97], Is.EqualTo(0.007830082099077f).Within(0.008f));
Assert.That(result[98], Is.EqualTo(0.007448204488898f).Within(0.008f));
Assert.That(result[99], Is.EqualTo(0.007084951269538f).Within(0.008f));
}
Assert.That(result[97], Is.EqualTo(0.007830082099077f).Within(0.008f));
Assert.That(result[98], Is.EqualTo(0.007448204488898f).Within(0.008f));
Assert.That(result[99], Is.EqualTo(0.007084951269538f).Within(0.008f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.ExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ExponentialLa5(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.ExponentialLa5(null));
}
}

121
FastRngTests/Distributions/GammaA5B15.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class GammaA5B15
{
[ExcludeFromCodeCoverage]
public class GammaA5B15
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestGammaDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestGammaDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.GammaA5B15(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.GammaA5B15(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0000929594237282f).Within(0.0008f));
Assert.That(result[1], Is.EqualTo(0.0012801746797876f).Within(0.002f));
Assert.That(result[2], Is.EqualTo(0.0055781488254349f).Within(0.004f));
Assert.That(result[0], Is.EqualTo(0.0000929594237282f).Within(0.0008f));
Assert.That(result[1], Is.EqualTo(0.0012801746797876f).Within(0.002f));
Assert.That(result[2], Is.EqualTo(0.0055781488254349f).Within(0.004f));
Assert.That(result[21], Is.EqualTo(0.9331608887752720f).Within(0.09f));
Assert.That(result[22], Is.EqualTo(0.9594734828891280f).Within(0.09f));
Assert.That(result[23], Is.EqualTo(0.9790895765535350f).Within(0.09f));
Assert.That(result[21], Is.EqualTo(0.9331608887752720f).Within(0.09f));
Assert.That(result[22], Is.EqualTo(0.9594734828891280f).Within(0.09f));
Assert.That(result[23], Is.EqualTo(0.9790895765535350f).Within(0.09f));
Assert.That(result[50], Is.EqualTo(0.3478287795336570f).Within(0.06f));
Assert.That(result[50], Is.EqualTo(0.3478287795336570f).Within(0.06f));
Assert.That(result[75], Is.EqualTo(0.0403399049422936f).Within(0.009f));
Assert.That(result[85], Is.EqualTo(0.0163628388658126f).Within(0.009f));
Assert.That(result[90], Is.EqualTo(0.0097147611446660f).Within(0.005f));
Assert.That(result[75], Is.EqualTo(0.0403399049422936f).Within(0.009f));
Assert.That(result[85], Is.EqualTo(0.0163628388658126f).Within(0.009f));
Assert.That(result[90], Is.EqualTo(0.0097147611446660f).Within(0.005f));
Assert.That(result[97], Is.EqualTo(0.0041135143233153f).Within(0.008f));
Assert.That(result[98], Is.EqualTo(0.0036872732029996f).Within(0.008f));
Assert.That(result[99], Is.EqualTo(0.0033038503429554f).Within(0.008f));
}
Assert.That(result[97], Is.EqualTo(0.0041135143233153f).Within(0.008f));
Assert.That(result[98], Is.EqualTo(0.0036872732029996f).Within(0.008f));
Assert.That(result[99], Is.EqualTo(0.0033038503429554f).Within(0.008f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestGammaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.GammaA5B15(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestGammaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.GammaA5B15(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestGammaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.GammaA5B15(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestGammaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.GammaA5B15(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.GammaA5B15(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.GammaA5B15(null));
}
}

121
FastRngTests/Distributions/InverseExponentialLa10.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class InverseExponentialLa10
{
[ExcludeFromCodeCoverage]
public class InverseExponentialLa10
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa10(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa10(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0000501746820562f).Within(0.0003f));
Assert.That(result[1], Is.EqualTo(0.0000554515994322f).Within(0.0003f));
Assert.That(result[2], Is.EqualTo(0.0000612834950532f).Within(0.0003f));
Assert.That(result[0], Is.EqualTo(0.0000501746820562f).Within(0.0003f));
Assert.That(result[1], Is.EqualTo(0.0000554515994322f).Within(0.0003f));
Assert.That(result[2], Is.EqualTo(0.0000612834950532f).Within(0.0003f));
Assert.That(result[21], Is.EqualTo(0.00040973497898f).Within(0.00045f));
Assert.That(result[22], Is.EqualTo(0.000452827182887f).Within(0.00050f));
Assert.That(result[23], Is.EqualTo(0.000500451433441f).Within(0.0006f));
Assert.That(result[21], Is.EqualTo(0.00040973497898f).Within(0.00045f));
Assert.That(result[22], Is.EqualTo(0.000452827182887f).Within(0.00050f));
Assert.That(result[23], Is.EqualTo(0.000500451433441f).Within(0.0006f));
Assert.That(result[50], Is.EqualTo(0.007446583070924f).Within(0.003f));
Assert.That(result[50], Is.EqualTo(0.007446583070924f).Within(0.003f));
Assert.That(result[75], Is.EqualTo(0.090717953289412f).Within(0.02f));
Assert.That(result[85], Is.EqualTo(0.246596963941606f).Within(0.05f));
Assert.That(result[90], Is.EqualTo(0.406569659740598f).Within(0.08f));
Assert.That(result[75], Is.EqualTo(0.090717953289412f).Within(0.02f));
Assert.That(result[85], Is.EqualTo(0.246596963941606f).Within(0.05f));
Assert.That(result[90], Is.EqualTo(0.406569659740598f).Within(0.08f));
Assert.That(result[97], Is.EqualTo(0.81873075307798f).Within(0.08f));
Assert.That(result[98], Is.EqualTo(0.904837418035957f).Within(0.08f));
Assert.That(result[99], Is.EqualTo(0.999999999999999f).Within(0.08f));
}
Assert.That(result[97], Is.EqualTo(0.81873075307798f).Within(0.08f));
Assert.That(result[98], Is.EqualTo(0.904837418035957f).Within(0.08f));
Assert.That(result[99], Is.EqualTo(0.999999999999999f).Within(0.08f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa10(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.InverseExponentialLa10(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.InverseExponentialLa10(null));
}
}

121
FastRngTests/Distributions/InverseExponentialLa5.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class InverseExponentialLa5
{
[ExcludeFromCodeCoverage]
public class InverseExponentialLa5
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa5(rng);
var fqa = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa5(rng);
var fqa = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fqa.CountThis(await dist.NextNumber());
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fqa.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.007083408929052f).Within(0.008f));
Assert.That(result[1], Is.EqualTo(0.007446583070924f).Within(0.008f));
Assert.That(result[2], Is.EqualTo(0.007828377549226f).Within(0.008f));
Assert.That(result[0], Is.EqualTo(0.007083408929052f).Within(0.008f));
Assert.That(result[1], Is.EqualTo(0.007446583070924f).Within(0.008f));
Assert.That(result[2], Is.EqualTo(0.007828377549226f).Within(0.008f));
Assert.That(result[21], Is.EqualTo(0.020241911445804f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.021279736438377f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.022370771856166f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.020241911445804f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.021279736438377f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.022370771856166f).Within(0.05f));
Assert.That(result[50], Is.EqualTo(0.08629358649937f).Within(0.02f));
Assert.That(result[50], Is.EqualTo(0.08629358649937f).Within(0.02f));
Assert.That(result[75], Is.EqualTo(0.301194211912202f).Within(0.03f));
Assert.That(result[85], Is.EqualTo(0.496585303791409f).Within(0.05f));
Assert.That(result[90], Is.EqualTo(0.637628151621772f).Within(0.06f));
Assert.That(result[75], Is.EqualTo(0.301194211912202f).Within(0.03f));
Assert.That(result[85], Is.EqualTo(0.496585303791409f).Within(0.05f));
Assert.That(result[90], Is.EqualTo(0.637628151621772f).Within(0.06f));
Assert.That(result[97], Is.EqualTo(0.904837418035959f).Within(0.08f));
Assert.That(result[98], Is.EqualTo(0.951229424500713f).Within(0.08f));
Assert.That(result[99], Is.EqualTo(1f).Within(0.08f));
}
Assert.That(result[97], Is.EqualTo(0.904837418035959f).Within(0.08f));
Assert.That(result[98], Is.EqualTo(0.951229424500713f).Within(0.08f));
Assert.That(result[99], Is.EqualTo(1f).Within(0.08f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestExponentialGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseExponentialLa5(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.InverseExponentialLa5(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.InverseExponentialLa5(null));
}
}

121
FastRngTests/Distributions/InverseGammaA3B05.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class InverseGammaA3B05
{
[ExcludeFromCodeCoverage]
public class InverseGammaA3B05
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestInverseGammaDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestInverseGammaDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseGammaA3B05(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseGammaA3B05(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0000000000000003f).Within(0.0000001f));
Assert.That(result[1], Is.EqualTo(0.0000011605257228f).Within(0.00001f));
Assert.That(result[2], Is.EqualTo(0.0009536970016103f).Within(0.0015f));
Assert.That(result[0], Is.EqualTo(0.0000000000000003f).Within(0.0000001f));
Assert.That(result[1], Is.EqualTo(0.0000011605257228f).Within(0.00001f));
Assert.That(result[2], Is.EqualTo(0.0009536970016103f).Within(0.0015f));
Assert.That(result[21], Is.EqualTo(0.5880485243048120f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.5433842148912880f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.5017780549216030f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.5880485243048120f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.5433842148912880f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.5017780549216030f).Within(0.05f));
Assert.That(result[50], Is.EqualTo(0.0741442015957425f).Within(0.009f));
Assert.That(result[50], Is.EqualTo(0.0741442015957425f).Within(0.009f));
Assert.That(result[75], Is.EqualTo(0.0207568945092484f).Within(0.006f));
Assert.That(result[85], Is.EqualTo(0.0136661506653688f).Within(0.006f));
Assert.That(result[90], Is.EqualTo(0.0112550619601327f).Within(0.006f));
Assert.That(result[75], Is.EqualTo(0.0207568945092484f).Within(0.006f));
Assert.That(result[85], Is.EqualTo(0.0136661506653688f).Within(0.006f));
Assert.That(result[90], Is.EqualTo(0.0112550619601327f).Within(0.006f));
Assert.That(result[97], Is.EqualTo(0.0087026933539773f).Within(0.005f));
Assert.That(result[98], Is.EqualTo(0.0083995375385004f).Within(0.005f));
Assert.That(result[99], Is.EqualTo(0.0081094156379928f).Within(0.005f));
}
Assert.That(result[97], Is.EqualTo(0.0087026933539773f).Within(0.005f));
Assert.That(result[98], Is.EqualTo(0.0083995375385004f).Within(0.005f));
Assert.That(result[99], Is.EqualTo(0.0081094156379928f).Within(0.005f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestInverseGammaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseGammaA3B05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestInverseGammaGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseGammaA3B05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestInverseGammaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseGammaA3B05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestInverseGammaGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.InverseGammaA3B05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.InverseGammaA3B05(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.InverseGammaA3B05(null));
}
}

121
FastRngTests/Distributions/LaplaceB01M0.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class LaplaceB01M0
{
[ExcludeFromCodeCoverage]
public class LaplaceB01M0
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M0(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M0(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.0000000000000000f).Within(0.05f));
Assert.That(result[1], Is.EqualTo(0.9048374180359590f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.8187307530779810f).Within(0.05f));
Assert.That(result[0], Is.EqualTo(1.0000000000000000f).Within(0.05f));
Assert.That(result[1], Is.EqualTo(0.9048374180359590f).Within(0.05f));
Assert.That(result[2], Is.EqualTo(0.8187307530779810f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.1224564282529820f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.1108031583623340f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.1002588437228040f).Within(0.05f));
Assert.That(result[21], Is.EqualTo(0.1224564282529820f).Within(0.05f));
Assert.That(result[22], Is.EqualTo(0.1108031583623340f).Within(0.05f));
Assert.That(result[23], Is.EqualTo(0.1002588437228040f).Within(0.05f));
Assert.That(result[50], Is.EqualTo(0.0067379469990855f).Within(0.003f));
Assert.That(result[50], Is.EqualTo(0.0067379469990855f).Within(0.003f));
Assert.That(result[75], Is.EqualTo(0.0005530843701478f).Within(0.0015f));
Assert.That(result[85], Is.EqualTo(0.0002034683690106f).Within(0.0015f));
Assert.That(result[90], Is.EqualTo(0.0001234098040867f).Within(0.0015f));
Assert.That(result[75], Is.EqualTo(0.0005530843701478f).Within(0.0015f));
Assert.That(result[85], Is.EqualTo(0.0002034683690106f).Within(0.0015f));
Assert.That(result[90], Is.EqualTo(0.0001234098040867f).Within(0.0015f));
Assert.That(result[97], Is.EqualTo(0.0000612834950532f).Within(0.0002f));
Assert.That(result[98], Is.EqualTo(0.0000554515994322f).Within(0.0002f));
Assert.That(result[99], Is.EqualTo(0.0000501746820562f).Within(0.0002f));
}
Assert.That(result[97], Is.EqualTo(0.0000612834950532f).Within(0.0002f));
Assert.That(result[98], Is.EqualTo(0.0000554515994322f).Within(0.0002f));
Assert.That(result[99], Is.EqualTo(0.0000501746820562f).Within(0.0002f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.LaplaceB01M0(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.LaplaceB01M0(null));
}
}

121
FastRngTests/Distributions/LaplaceB01M05.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class LaplaceB01M05
{
[ExcludeFromCodeCoverage]
public class LaplaceB01M05
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M05(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M05(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.0074465830709244f).Within(0.004f));
Assert.That(result[1], Is.EqualTo(0.0082297470490200f).Within(0.004f));
Assert.That(result[2], Is.EqualTo(0.0090952771016958f).Within(0.01f));
Assert.That(result[0], Is.EqualTo(0.0074465830709244f).Within(0.004f));
Assert.That(result[1], Is.EqualTo(0.0082297470490200f).Within(0.004f));
Assert.That(result[2], Is.EqualTo(0.0090952771016958f).Within(0.01f));
Assert.That(result[21], Is.EqualTo(0.0608100626252180f).Within(0.02f));
Assert.That(result[22], Is.EqualTo(0.0672055127397498f).Within(0.02f));
Assert.That(result[23], Is.EqualTo(0.0742735782143340f).Within(0.02f));
Assert.That(result[21], Is.EqualTo(0.0608100626252180f).Within(0.02f));
Assert.That(result[22], Is.EqualTo(0.0672055127397498f).Within(0.02f));
Assert.That(result[23], Is.EqualTo(0.0742735782143340f).Within(0.02f));
Assert.That(result[50], Is.EqualTo(1.0000000000000000f).Within(0.2f));
Assert.That(result[50], Is.EqualTo(1.0000000000000000f).Within(0.2f));
Assert.That(result[75], Is.EqualTo(0.0742735782143335f).Within(0.01f));
Assert.That(result[85], Is.EqualTo(0.0273237224472924f).Within(0.01f));
Assert.That(result[90], Is.EqualTo(0.0165726754017612f).Within(0.01f));
Assert.That(result[75], Is.EqualTo(0.0742735782143335f).Within(0.01f));
Assert.That(result[85], Is.EqualTo(0.0273237224472924f).Within(0.01f));
Assert.That(result[90], Is.EqualTo(0.0165726754017612f).Within(0.01f));
Assert.That(result[97], Is.EqualTo(0.0082297470490200f).Within(0.004f));
Assert.That(result[98], Is.EqualTo(0.0074465830709243f).Within(0.004f));
Assert.That(result[99], Is.EqualTo(0.0067379469990854f).Within(0.004f));
}
Assert.That(result[97], Is.EqualTo(0.0082297470490200f).Within(0.004f));
Assert.That(result[98], Is.EqualTo(0.0074465830709243f).Within(0.004f));
Assert.That(result[99], Is.EqualTo(0.0067379469990854f).Within(0.004f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLaplaceGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LaplaceB01M05(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.LaplaceB01M05(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.LaplaceB01M05(null));
}
}

121
FastRngTests/Distributions/LogNormalS1M0.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class LogNormalS1M0
{
[ExcludeFromCodeCoverage]
public class LogNormalS1M0
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLogNormalDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLogNormalDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LogNormalS1M0(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LogNormalS1M0(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(0.001505531f).Within(0.003f));
Assert.That(result[1], Is.EqualTo(0.014408709f).Within(0.01f));
Assert.That(result[2], Is.EqualTo(0.043222256f).Within(0.02f));
Assert.That(result[0], Is.EqualTo(0.001505531f).Within(0.003f));
Assert.That(result[1], Is.EqualTo(0.014408709f).Within(0.01f));
Assert.That(result[2], Is.EqualTo(0.043222256f).Within(0.02f));
Assert.That(result[21], Is.EqualTo(0.876212056f).Within(0.15f));
Assert.That(result[22], Is.EqualTo(0.895582226f).Within(0.15f));
Assert.That(result[23], Is.EqualTo(0.912837250f).Within(0.15f));
Assert.That(result[21], Is.EqualTo(0.876212056f).Within(0.15f));
Assert.That(result[22], Is.EqualTo(0.895582226f).Within(0.15f));
Assert.That(result[23], Is.EqualTo(0.912837250f).Within(0.15f));
Assert.That(result[50], Is.EqualTo(0.948062005f).Within(0.2f));
Assert.That(result[50], Is.EqualTo(0.948062005f).Within(0.2f));
Assert.That(result[75], Is.EqualTo(0.768584762f).Within(0.089f));
Assert.That(result[85], Is.EqualTo(0.697303612f).Within(0.089f));
Assert.That(result[90], Is.EqualTo(0.663570581f).Within(0.089f));
Assert.That(result[75], Is.EqualTo(0.768584762f).Within(0.089f));
Assert.That(result[85], Is.EqualTo(0.697303612f).Within(0.089f));
Assert.That(result[90], Is.EqualTo(0.663570581f).Within(0.089f));
Assert.That(result[97], Is.EqualTo(0.618792767f).Within(0.089f));
Assert.That(result[98], Is.EqualTo(0.612636410f).Within(0.089f));
Assert.That(result[99], Is.EqualTo(0.606540679f).Within(0.089f));
}
Assert.That(result[97], Is.EqualTo(0.618792767f).Within(0.089f));
Assert.That(result[98], Is.EqualTo(0.612636410f).Within(0.089f));
Assert.That(result[99], Is.EqualTo(0.606540679f).Within(0.089f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLogNormalGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LogNormalS1M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLogNormalGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LogNormalS1M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLogNormalGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LogNormalS1M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestLogNormalGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.LogNormalS1M0(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.LogNormalS1M0(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.LogNormalS1M0(null));
}
}

123
FastRngTests/Distributions/NormalS02M05.cs
View File

@ -5,76 +5,75 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class NormalS02M05
{
[ExcludeFromCodeCoverage]
public class NormalS02M05
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestNormalDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestNormalDistribution01()
const float MEAN = 0.5f;
const float STANDARD_DEVIATION = 0.2f;
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.NormalS02M05(rng);
var stats = new RunningStatistics();
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
const float MEAN = 0.5f;
const float STANDARD_DEVIATION = 0.2f;
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.NormalS02M05(rng);
var stats = new RunningStatistics();
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
var nextNumber = await dist.NextNumber();
stats.Push(nextNumber);
fra.CountThis(nextNumber);
}
fra.NormalizeAndPlotEvents(TestContext.WriteLine);
TestContext.WriteLine($"mean={MEAN} vs. {stats.Mean}");
TestContext.WriteLine($"variance={STANDARD_DEVIATION * STANDARD_DEVIATION} vs {stats.Variance}");
Assert.That(stats.Mean, Is.EqualTo(MEAN).Within(0.01f), "Mean is out of range");
Assert.That(stats.Variance, Is.EqualTo(STANDARD_DEVIATION*STANDARD_DEVIATION).Within(0.01f), "Variance is out of range");
var nextNumber = await dist.NextNumber();
stats.Push(nextNumber);
fra.CountThis(nextNumber);
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestNormalGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.NormalS02M05(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
TestContext.WriteLine($"mean={MEAN} vs. {stats.Mean}");
TestContext.WriteLine($"variance={STANDARD_DEVIATION * STANDARD_DEVIATION} vs {stats.Variance}");
Assert.That(stats.Mean, Is.EqualTo(MEAN).Within(0.01f), "Mean is out of range");
Assert.That(stats.Variance, Is.EqualTo(STANDARD_DEVIATION*STANDARD_DEVIATION).Within(0.01f), "Variance is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestNormalGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.NormalS02M05(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestNormalGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.NormalS02M05(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestNormalGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.NormalS02M05(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.NormalS02M05(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.NormalS02M05(null));
}
}

121
FastRngTests/Distributions/StudentTNu1.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class StudentTNu1
{
[ExcludeFromCodeCoverage]
public class StudentTNu1
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestStudentTDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestStudentTDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.StudentTNu1(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.StudentTNu1(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.000000000f).Within(0.2f));
Assert.That(result[1], Is.EqualTo(0.999700120f).Within(0.2f));
Assert.That(result[2], Is.EqualTo(0.999200719f).Within(0.2f));
Assert.That(result[0], Is.EqualTo(1.000000000f).Within(0.2f));
Assert.That(result[1], Is.EqualTo(0.999700120f).Within(0.2f));
Assert.That(result[2], Is.EqualTo(0.999200719f).Within(0.2f));
Assert.That(result[21], Is.EqualTo(0.953929798f).Within(0.2f));
Assert.That(result[22], Is.EqualTo(0.949852788f).Within(0.2f));
Assert.That(result[23], Is.EqualTo(0.945631619f).Within(0.2f));
Assert.That(result[21], Is.EqualTo(0.953929798f).Within(0.2f));
Assert.That(result[22], Is.EqualTo(0.949852788f).Within(0.2f));
Assert.That(result[23], Is.EqualTo(0.945631619f).Within(0.2f));
Assert.That(result[50], Is.EqualTo(0.793667169f).Within(0.095f));
Assert.That(result[50], Is.EqualTo(0.793667169f).Within(0.095f));
Assert.That(result[75], Is.EqualTo(0.633937627f).Within(0.09f));
Assert.That(result[85], Is.EqualTo(0.574902276f).Within(0.09f));
Assert.That(result[90], Is.EqualTo(0.547070729f).Within(0.09f));
Assert.That(result[75], Is.EqualTo(0.633937627f).Within(0.09f));
Assert.That(result[85], Is.EqualTo(0.574902276f).Within(0.09f));
Assert.That(result[90], Is.EqualTo(0.547070729f).Within(0.09f));
Assert.That(result[97], Is.EqualTo(0.510150990f).Within(0.09f));
Assert.That(result[98], Is.EqualTo(0.505075501f).Within(0.09f));
Assert.That(result[99], Is.EqualTo(0.500050000f).Within(0.09f));
}
Assert.That(result[97], Is.EqualTo(0.510150990f).Within(0.09f));
Assert.That(result[98], Is.EqualTo(0.505075501f).Within(0.09f));
Assert.That(result[99], Is.EqualTo(0.500050000f).Within(0.09f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestStudentTGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.StudentTNu1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestStudentTGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.StudentTNu1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestStudentTGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.StudentTNu1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestStudentTGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.StudentTNu1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.StudentTNu1(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.StudentTNu1(null));
}
}

491
FastRngTests/Distributions/Uniform.cs
View File

@ -5,293 +5,292 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class Uniform
{
[ExcludeFromCodeCoverage]
public class Uniform
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformDistribution01()
const float A = 0.0f;
const float B = 1.0f;
const float MEAN = 0.5f * (A + B);
const float VARIANCE = (1.0f / 12.0f) * (B - A) * (B - A);
using var rng = new MultiThreadedRng();
var stats = new RunningStatistics();
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
const float A = 0.0f;
const float B = 1.0f;
const float MEAN = 0.5f * (A + B);
const float VARIANCE = (1.0f / 12.0f) * (B - A) * (B - A);
using var rng = new MultiThreadedRng();
var stats = new RunningStatistics();
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
{
var value = await rng.GetUniform();
stats.Push(value);
fra.CountThis(value);
}
fra.NormalizeAndPlotEvents(TestContext.WriteLine);
fra.PlotOccurence(TestContext.WriteLine);
TestContext.WriteLine($"mean={MEAN} vs. {stats.Mean}");
TestContext.WriteLine($"variance={VARIANCE} vs {stats.Variance}");
Assert.That(stats.Mean, Is.EqualTo(MEAN).Within(0.01f), "Mean is out of range");
Assert.That(stats.Variance, Is.EqualTo(VARIANCE).Within(0.001f), "Variance is out of range");
var value = await rng.GetUniform();
stats.Push(value);
fra.CountThis(value);
}
fra.NormalizeAndPlotEvents(TestContext.WriteLine);
fra.PlotOccurence(TestContext.WriteLine);
TestContext.WriteLine($"mean={MEAN} vs. {stats.Mean}");
TestContext.WriteLine($"variance={VARIANCE} vs {stats.Variance}");
Assert.That(stats.Mean, Is.EqualTo(MEAN).Within(0.01f), "Mean is out of range");
Assert.That(stats.Variance, Is.EqualTo(VARIANCE).Within(0.001f), "Variance is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task KolmogorovSmirnovTest()
{
// Kolmogorov-Smirnov test for distributions.
// See Knuth volume 2, page 48-51 (third edition).
// This test should *fail* on average one time in 1000 runs.
// That's life with random number generators: if the test passed all the time,
// the source wouldn't be random enough! If the test were to fail more frequently,
// the most likely explanation would be a bug in the code.
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task KolmogorovSmirnovTest()
{
// Kolmogorov-Smirnov test for distributions.
// See Knuth volume 2, page 48-51 (third edition).
// This test should *fail* on average one time in 1000 runs.
// That's life with random number generators: if the test passed all the time,
// the source wouldn't be random enough! If the test were to fail more frequently,
// the most likely explanation would be a bug in the code.
const int NUM_ROUNDS = 10_000;
const float FAILURE_PROBABILITY = 0.001f; // probability of test failing with normal distributed input
const float P_LOW = 0.25f * FAILURE_PROBABILITY;
const float P_HIGH = 1.0f - 0.25f * FAILURE_PROBABILITY;
const int NUM_ROUNDS = 10_000;
const float FAILURE_PROBABILITY = 0.001f; // probability of test failing with normal distributed input
const float P_LOW = 0.25f * FAILURE_PROBABILITY;
const float P_HIGH = 1.0f - 0.25f * FAILURE_PROBABILITY;
var samples = new float[NUM_ROUNDS];
using var rng = new MultiThreadedRng();
int n;
var samples = new float[NUM_ROUNDS];
using var rng = new MultiThreadedRng();
int n;
for (n = 0; n != NUM_ROUNDS; ++n)
samples[n] = await rng.GetUniform();
for (n = 0; n != NUM_ROUNDS; ++n)
samples[n] = await rng.GetUniform();
Array.Sort(samples);
Array.Sort(samples);
var jMinus = 0;
var jPlus = 0;
var kPlus = -float.MaxValue;
var kMinus = -float.MaxValue;
var jMinus = 0;
var jPlus = 0;
var kPlus = -float.MaxValue;
var kMinus = -float.MaxValue;
for (n = 0; n != NUM_ROUNDS; ++n)
for (n = 0; n != NUM_ROUNDS; ++n)
{
var cdf = samples[n];
var temp = (n + 1.0f) / NUM_ROUNDS - cdf;
if (kPlus < temp)
{
var cdf = samples[n];
var temp = (n + 1.0f) / NUM_ROUNDS - cdf;
if (kPlus < temp)
{
kPlus = temp;
jPlus = n;
}
temp = cdf - (n + 0.0f) / NUM_ROUNDS;
if (kMinus < temp)
{
kMinus = temp;
jMinus = n;
}
kPlus = temp;
jPlus = n;
}
temp = cdf - (n + 0.0f) / NUM_ROUNDS;
if (kMinus < temp)
{
kMinus = temp;
jMinus = n;
}
}
var sqrtNumReps = MathF.Sqrt(NUM_ROUNDS);
kPlus *= sqrtNumReps;
kMinus *= sqrtNumReps;
var sqrtNumReps = MathF.Sqrt(NUM_ROUNDS);
kPlus *= sqrtNumReps;
kMinus *= sqrtNumReps;
// We divide the failure probability by four because we have four tests:
// left and right tests for K+ and K-.
var cutoffLow = MathF.Sqrt(0.5f * MathF.Log(1.0f / (1.0f - P_LOW))) - 1.0f / (6.0f * sqrtNumReps);
var cutoffHigh = MathF.Sqrt(0.5f * MathF.Log(1.0f / (1.0f - P_HIGH))) - 1.0f / (6.0f * sqrtNumReps);
// We divide the failure probability by four because we have four tests:
// left and right tests for K+ and K-.
var cutoffLow = MathF.Sqrt(0.5f * MathF.Log(1.0f / (1.0f - P_LOW))) - 1.0f / (6.0f * sqrtNumReps);
var cutoffHigh = MathF.Sqrt(0.5f * MathF.Log(1.0f / (1.0f - P_HIGH))) - 1.0f / (6.0f * sqrtNumReps);
TestContext.WriteLine($"K+ = {kPlus} | K- = {kMinus}");
TestContext.WriteLine($"K+ max at position {jPlus} = {samples[jPlus]}");
TestContext.WriteLine($"K- max at position {jMinus} = {samples[jMinus]}");
TestContext.WriteLine($"Acceptable interval: [{cutoffLow}, {cutoffHigh}]");
TestContext.WriteLine($"K+ = {kPlus} | K- = {kMinus}");
TestContext.WriteLine($"K+ max at position {jPlus} = {samples[jPlus]}");
TestContext.WriteLine($"K- max at position {jMinus} = {samples[jMinus]}");
TestContext.WriteLine($"Acceptable interval: [{cutoffLow}, {cutoffHigh}]");
Assert.That(kPlus, Is.GreaterThanOrEqualTo(cutoffLow), "K+ is lower than low cutoff");
Assert.That(kPlus, Is.LessThanOrEqualTo(cutoffHigh), "K+ is higher than high cutoff");
Assert.That(kMinus, Is.GreaterThanOrEqualTo(cutoffLow), "K- is lower than low cutoff");
Assert.That(kMinus, Is.LessThanOrEqualTo(cutoffHigh), "K- is lower than high cutoff");
}
Assert.That(kPlus, Is.GreaterThanOrEqualTo(cutoffLow), "K+ is lower than low cutoff");
Assert.That(kPlus, Is.LessThanOrEqualTo(cutoffHigh), "K+ is higher than high cutoff");
Assert.That(kMinus, Is.GreaterThanOrEqualTo(cutoffLow), "K- is lower than low cutoff");
Assert.That(kMinus, Is.LessThanOrEqualTo(cutoffHigh), "K- is lower than high cutoff");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.Uniform(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.Uniform(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.Uniform(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
var dist = new FastRng.Distributions.Uniform(rng);
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformGeneratorWithRange04()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await rng.GetUniform();
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestUniformGeneratorWithRange04()
{
using var rng = new MultiThreadedRng();
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await rng.GetUniform();
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestRange05Uint()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0, 100)]++;
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestRange05Uint()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0, 100)]++;
for (var n = 0; n < distribution.Length - 1; n++)
Assert.That(distribution[n], Is.GreaterThan(0));
}
for (var n = 0; n < distribution.Length - 1; n++)
Assert.That(distribution[n], Is.GreaterThan(0));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestRange05Ulong()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0UL, 100)]++;
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestRange05Ulong()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0UL, 100)]++;
for (var n = 0; n < distribution.Length - 1; n++)
Assert.That(distribution[n], Is.GreaterThan(0));
}
for (var n = 0; n < distribution.Length - 1; n++)
Assert.That(distribution[n], Is.GreaterThan(0));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestRange05Float()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[(uint)MathF.Floor(await dist.NextNumber(0.0f, 100.0f))]++;
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestRange05Float()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[(uint)MathF.Floor(await dist.NextNumber(0.0f, 100.0f))]++;
for (var n = 0; n < distribution.Length - 1; n++)
Assert.That(distribution[n], Is.GreaterThan(0));
}
for (var n = 0; n < distribution.Length - 1; n++)
Assert.That(distribution[n], Is.GreaterThan(0));
}
[Test]
[Category(TestCategories.NORMAL)]
public async Task TestDistribution001Uint()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0, 100)]++;
[Test]
[Category(TestCategories.NORMAL)]
public async Task TestDistribution001Uint()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0, 100)]++;
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 600));
}
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 600));
}
[Test]
[Category(TestCategories.NORMAL)]
public async Task TestDistribution001Ulong()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0UL, 100)]++;
[Test]
[Category(TestCategories.NORMAL)]
public async Task TestDistribution001Ulong()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0UL, 100)]++;
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 600));
}
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 600));
}
[Test]
[Category(TestCategories.NORMAL)]
public async Task TestDistribution001Float()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[(uint)MathF.Floor(await dist.NextNumber(0.0f, 100.0f))]++;
[Test]
[Category(TestCategories.NORMAL)]
public async Task TestDistribution001Float()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 1_000_000;
for (var n = 0; n < runs; n++)
distribution[(uint)MathF.Floor(await dist.NextNumber(0.0f, 100.0f))]++;
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 600));
}
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 600));
}
[Test]
[Category(TestCategories.LONG_RUNNING)]
public async Task TestDistribution002Uint()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 100_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0, 100)]++;
[Test]
[Category(TestCategories.LONG_RUNNING)]
public async Task TestDistribution002Uint()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 100_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0, 100)]++;
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 6_000));
}
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 6_000));
}
[Test]
[Category(TestCategories.LONG_RUNNING)]
public async Task TestDistribution002Ulong()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 100_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0UL, 100)]++;
[Test]
[Category(TestCategories.LONG_RUNNING)]
public async Task TestDistribution002Ulong()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 100_000_000;
for (var n = 0; n < runs; n++)
distribution[await dist.NextNumber(0UL, 100)]++;
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 6_000));
}
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 6_000));
}
[Test]
[Category(TestCategories.LONG_RUNNING)]
public async Task TestDistribution002Float()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 100_000_000;
for (var n = 0; n < runs; n++)
distribution[(uint)MathF.Floor(await dist.NextNumber(0.0f, 100.0f))]++;
[Test]
[Category(TestCategories.LONG_RUNNING)]
public async Task TestDistribution002Float()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.Uniform(rng);
var distribution = new uint[101];
var runs = 100_000_000;
for (var n = 0; n < runs; n++)
distribution[(uint)MathF.Floor(await dist.NextNumber(0.0f, 100.0f))]++;
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 6_000));
}
Assert.That(distribution[..^1].Max() - distribution[..^1].Min(), Is.InRange(0, 6_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.Uniform(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.Uniform(null));
}
}

121
FastRngTests/Distributions/WeibullK05La1.cs
View File

@ -5,80 +5,79 @@ using System.Threading.Tasks;
using FastRng;
using NUnit.Framework;
namespace FastRngTests.Distributions
namespace FastRngTests.Distributions;
[ExcludeFromCodeCoverage]
public class WeibullK05La1
{
[ExcludeFromCodeCoverage]
public class WeibullK05La1
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestWeibullDistribution01()
{
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestWeibullDistribution01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.WeibullK05La1(rng);
var fra = new FrequencyAnalysis();
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.WeibullK05La1(rng);
var fra = new FrequencyAnalysis();
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
for (var n = 0; n < 100_000; n++)
fra.CountThis(await dist.NextNumber());
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
var result = fra.NormalizeAndPlotEvents(TestContext.WriteLine);
Assert.That(result[0], Is.EqualTo(1.000000000f).Within(0.2f));
Assert.That(result[1], Is.EqualTo(0.678415772f).Within(0.09f));
Assert.That(result[2], Is.EqualTo(0.536595233f).Within(0.09f));
Assert.That(result[0], Is.EqualTo(1.000000000f).Within(0.2f));
Assert.That(result[1], Is.EqualTo(0.678415772f).Within(0.09f));
Assert.That(result[2], Is.EqualTo(0.536595233f).Within(0.09f));
Assert.That(result[21], Is.EqualTo(0.147406264f).Within(0.02f));
Assert.That(result[22], Is.EqualTo(0.142654414f).Within(0.02f));
Assert.That(result[23], Is.EqualTo(0.138217760f).Within(0.02f));
Assert.That(result[21], Is.EqualTo(0.147406264f).Within(0.02f));
Assert.That(result[22], Is.EqualTo(0.142654414f).Within(0.02f));
Assert.That(result[23], Is.EqualTo(0.138217760f).Within(0.02f));
Assert.That(result[50], Is.EqualTo(0.075769787f).Within(0.095f));
Assert.That(result[50], Is.EqualTo(0.075769787f).Within(0.095f));
Assert.That(result[75], Is.EqualTo(0.053016799f).Within(0.05f));
Assert.That(result[85], Is.EqualTo(0.047144614f).Within(0.05f));
Assert.That(result[90], Is.EqualTo(0.044629109f).Within(0.05f));
Assert.That(result[75], Is.EqualTo(0.053016799f).Within(0.05f));
Assert.That(result[85], Is.EqualTo(0.047144614f).Within(0.05f));
Assert.That(result[90], Is.EqualTo(0.044629109f).Within(0.05f));
Assert.That(result[97], Is.EqualTo(0.041484591f).Within(0.05f));
Assert.That(result[98], Is.EqualTo(0.041067125f).Within(0.05f));
Assert.That(result[99], Is.EqualTo(0.040656966f).Within(0.05f));
}
Assert.That(result[97], Is.EqualTo(0.041484591f).Within(0.05f));
Assert.That(result[98], Is.EqualTo(0.041067125f).Within(0.05f));
Assert.That(result[99], Is.EqualTo(0.040656966f).Within(0.05f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestWeibullGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.WeibullK05La1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestWeibullGeneratorWithRange01()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.WeibullK05La1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(-1.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(-1.0f), "Min out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestWeibullGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.WeibullK05La1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public async Task TestWeibullGeneratorWithRange02()
{
using var rng = new MultiThreadedRng();
var dist = new FastRng.Distributions.WeibullK05La1(rng);
var samples = new float[1_000];
for (var n = 0; n < samples.Length; n++)
samples[n] = await dist.NextNumber(0.0f, 1.0f);
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
Assert.That(samples.Min(), Is.GreaterThanOrEqualTo(0.0f), "Min is out of range");
Assert.That(samples.Max(), Is.LessThanOrEqualTo(1.0f), "Max is out of range");
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.WeibullK05La1(null));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void NoRandomNumberGenerator01()
{
Assert.Throws<ArgumentNullException>(() => new FastRng.Distributions.WeibullK05La1(null));
}
}

121
FastRngTests/FrequencyAnalysis.cs
View File

@ -3,82 +3,81 @@ using System.Diagnostics.CodeAnalysis;
using System.Linq;
using System.Text;
namespace FastRngTests
namespace FastRngTests;
[ExcludeFromCodeCoverage]
public sealed class FrequencyAnalysis
{
[ExcludeFromCodeCoverage]
public sealed class FrequencyAnalysis
private readonly uint[] data;
public FrequencyAnalysis(int samples = 100)
{
private readonly uint[] data;
public FrequencyAnalysis(int samples = 100)
this.data = new uint[samples];
}
public void CountThis(float value)
{
var bucket = (int)MathF.Floor(value * this.data.Length);
this.data[bucket]++;
}
public float[] GetNormalizedEvents()
{
var max = (float) this.data.Max();
var result = new float[this.data.Length];
for (var n = 0; n < this.data.Length; n++)
{
this.data = new uint[samples];
result[n] = this.data[n] / max;
}
public void CountThis(float value)
{
var bucket = (int)MathF.Floor(value * this.data.Length);
this.data[bucket]++;
}
return result;
}
public float[] GetNormalizedEvents()
{
var max = (float) this.data.Max();
var result = new float[this.data.Length];
for (var n = 0; n < this.data.Length; n++)
{
result[n] = this.data[n] / max;
}
private float[] Normalize()
{
var max = (float)this.data.Max();
var result = new float[this.data.Length];
for (var n = 0; n < this.data.Length; n++)
result[n] = this.data[n] / max;
return result;
}
return result;
}
private float[] Normalize()
{
var max = (float)this.data.Max();
var result = new float[this.data.Length];
for (var n = 0; n < this.data.Length; n++)
result[n] = this.data[n] / max;
return result;
}
public float[] NormalizeAndPlotEvents(Action<string> writer)
{
var result = this.Normalize();
FrequencyAnalysis.Plot(result, writer, "Event Distribution");
public float[] NormalizeAndPlotEvents(Action<string> writer)
{
var result = this.Normalize();
Plot(result, writer, "Event Distribution");
return result;
}
return result;
}
public void PlotOccurence(Action<string> writer)
public void PlotOccurence(Action<string> writer)
{
var data = this.data.Select(n => n > 0f ? 1.0f : 0.0f).ToArray();
Plot(data, writer, "Occurrence Distribution");
}
private static void Plot(float[] data, Action<string> writer, string name)
{
const int HEIGHT = 16;
var values = new float[data.Length];
for (var n = 0; n < data.Length; n++)
{
var data = this.data.Select(n => n > 0f ? 1.0f : 0.0f).ToArray();
FrequencyAnalysis.Plot(data, writer, "Occurrence Distribution");
values[n] = data[n] * HEIGHT;
}
private static void Plot(float[] data, Action<string> writer, string name)
var sb = new StringBuilder();
for (var line = HEIGHT; line > 0; line--)
{
const int HEIGHT = 16;
var values = new float[data.Length];
for (var n = 0; n < data.Length; n++)
{
values[n] = data[n] * HEIGHT;
}
var sb = new StringBuilder();
for (var line = HEIGHT; line > 0; line--)
{
for (var column = 0; column < data.Length; column++)
sb.Append(values[column] >= line ? '█' : '░');
for (var column = 0; column < data.Length; column++)
sb.Append(values[column] >= line ? '█' : '░');
writer.Invoke(sb.ToString());
sb.Clear();
}
writer.Invoke(name);
writer.Invoke(string.Empty);
writer.Invoke(sb.ToString());
sb.Clear();
}
writer.Invoke(name);
writer.Invoke(string.Empty);
}
}

663
FastRngTests/MathToolsTests.cs
View File

@ -3,339 +3,338 @@ using System.Diagnostics.CodeAnalysis;
using FastRng;
using NUnit.Framework;
namespace FastRngTests
namespace FastRngTests;
[ExcludeFromCodeCoverage]
public class MathToolsTests
{
[ExcludeFromCodeCoverage]
public class MathToolsTests
#region Gamma
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest01()
{
#region Gamma
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest01()
{
Assert.That(MathTools.Gamma(-0.5f), Is.EqualTo(-3.544907701811087f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest02()
{
Assert.That(MathTools.Gamma(0.1f), Is.EqualTo(9.51350975f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest03()
{
Assert.That(MathTools.Gamma(0.5f), Is.EqualTo(1.772453850905517f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest04()
{
Assert.That(MathTools.Gamma(1.0f), Is.EqualTo(1.0f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest05()
{
Assert.That(MathTools.Gamma(1.5f), Is.EqualTo(0.8862269254527587f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest06()
{
Assert.That(MathTools.Gamma(2.0f), Is.EqualTo(1.0f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest07()
{
Assert.That(MathTools.Gamma(3.0f), Is.EqualTo(2.0f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest08()
{
Assert.That(MathTools.Gamma(10.0f), Is.EqualTo(362_880.719f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest09()
{
Assert.That(MathTools.Gamma(140.0f), Is.EqualTo(float.NaN));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest10()
{
Assert.That(MathTools.Gamma(170.0f), Is.EqualTo(float.NaN));
}
#endregion
#region Factorial (integer)
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger01()
{
Assert.That(MathTools.Factorial(0), Is.EqualTo(1));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger02()
{
Assert.That(MathTools.Factorial(1), Is.EqualTo(1));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger03()
{
Assert.That(MathTools.Factorial(2), Is.EqualTo(2));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger04()
{
Assert.That(MathTools.Factorial(3), Is.EqualTo(6));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger05()
{
Assert.That(MathTools.Factorial(4), Is.EqualTo(24));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger06()
{
Assert.That(MathTools.Factorial(5), Is.EqualTo(120));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger07()
{
Assert.That(MathTools.Factorial(6), Is.EqualTo(720));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger08()
{
Assert.That(MathTools.Factorial(7), Is.EqualTo(5_040));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger09()
{
Assert.That(MathTools.Factorial(8), Is.EqualTo(40_320));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger10()
{
Assert.That(MathTools.Factorial(9), Is.EqualTo(362_880));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger11()
{
Assert.That(MathTools.Factorial(10), Is.EqualTo(3_628_800));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger12()
{
Assert.That(MathTools.Factorial(11), Is.EqualTo(39_916_800));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger13()
{
Assert.That(MathTools.Factorial(12), Is.EqualTo(479_001_600));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger14()
{
Assert.That(MathTools.Factorial(13), Is.EqualTo(6_227_020_800));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger15()
{
Assert.That(MathTools.Factorial(14), Is.EqualTo(87_178_291_200));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger16()
{
Assert.That(MathTools.Factorial(15), Is.EqualTo(1_307_674_368_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger17()
{
Assert.That(MathTools.Factorial(16), Is.EqualTo(20_922_789_888_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger18()
{
Assert.That(MathTools.Factorial(17), Is.EqualTo(355_687_428_096_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger19()
{
Assert.That(MathTools.Factorial(18), Is.EqualTo(6_402_373_705_728_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger20()
{
Assert.That(MathTools.Factorial(19), Is.EqualTo(121_645_100_408_832_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger21()
{
Assert.That(MathTools.Factorial(20), Is.EqualTo(2_432_902_008_176_640_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger22()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(21));
// Note: 21! is not possible in C# until we got 128 bit integers, since:
// ulong.max == 18_446_744_073_709_551_615 < 51_090_942_171_709_400_000
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger23()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(45_646));
// Note: 45_646! is not possible in C# since:
// ulong.max == 18_446_744_073_709_551_615
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger24()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(-1));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger25()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(-6_565));
}
#endregion
#region Factorial (floating point)
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint01()
{
Assert.That(MathTools.Factorial(0.5f), Is.EqualTo(0.886226925f).Within(1e6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint02()
{
Assert.That(MathTools.Factorial(1.5f), Is.EqualTo(1.329340388f).Within(1e6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint03()
{
Assert.That(MathTools.Factorial(-1.5f), Is.EqualTo(-1.329340388f).Within(1e6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint04()
{
Assert.That(MathTools.Factorial(7.5f), Is.EqualTo(14_034.407293483f).Within(1e6f));
}
#endregion
Assert.That(MathTools.Gamma(-0.5f), Is.EqualTo(-3.544907701811087f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest02()
{
Assert.That(MathTools.Gamma(0.1f), Is.EqualTo(9.51350975f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest03()
{
Assert.That(MathTools.Gamma(0.5f), Is.EqualTo(1.772453850905517f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest04()
{
Assert.That(MathTools.Gamma(1.0f), Is.EqualTo(1.0f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest05()
{
Assert.That(MathTools.Gamma(1.5f), Is.EqualTo(0.8862269254527587f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest06()
{
Assert.That(MathTools.Gamma(2.0f), Is.EqualTo(1.0f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest07()
{
Assert.That(MathTools.Gamma(3.0f), Is.EqualTo(2.0f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest08()
{
Assert.That(MathTools.Gamma(10.0f), Is.EqualTo(362_880.719f).Within(1e-6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest09()
{
Assert.That(MathTools.Gamma(140.0f), Is.EqualTo(float.NaN));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void GammaTest10()
{
Assert.That(MathTools.Gamma(170.0f), Is.EqualTo(float.NaN));
}
#endregion
#region Factorial (integer)
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger01()
{
Assert.That(MathTools.Factorial(0), Is.EqualTo(1));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger02()
{
Assert.That(MathTools.Factorial(1), Is.EqualTo(1));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger03()
{
Assert.That(MathTools.Factorial(2), Is.EqualTo(2));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger04()
{
Assert.That(MathTools.Factorial(3), Is.EqualTo(6));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger05()
{
Assert.That(MathTools.Factorial(4), Is.EqualTo(24));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger06()
{
Assert.That(MathTools.Factorial(5), Is.EqualTo(120));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger07()
{
Assert.That(MathTools.Factorial(6), Is.EqualTo(720));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger08()
{
Assert.That(MathTools.Factorial(7), Is.EqualTo(5_040));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger09()
{
Assert.That(MathTools.Factorial(8), Is.EqualTo(40_320));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger10()
{
Assert.That(MathTools.Factorial(9), Is.EqualTo(362_880));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger11()
{
Assert.That(MathTools.Factorial(10), Is.EqualTo(3_628_800));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger12()
{
Assert.That(MathTools.Factorial(11), Is.EqualTo(39_916_800));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger13()
{
Assert.That(MathTools.Factorial(12), Is.EqualTo(479_001_600));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger14()
{
Assert.That(MathTools.Factorial(13), Is.EqualTo(6_227_020_800));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger15()
{
Assert.That(MathTools.Factorial(14), Is.EqualTo(87_178_291_200));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger16()
{
Assert.That(MathTools.Factorial(15), Is.EqualTo(1_307_674_368_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger17()
{
Assert.That(MathTools.Factorial(16), Is.EqualTo(20_922_789_888_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger18()
{
Assert.That(MathTools.Factorial(17), Is.EqualTo(355_687_428_096_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger19()
{
Assert.That(MathTools.Factorial(18), Is.EqualTo(6_402_373_705_728_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger20()
{
Assert.That(MathTools.Factorial(19), Is.EqualTo(121_645_100_408_832_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger21()
{
Assert.That(MathTools.Factorial(20), Is.EqualTo(2_432_902_008_176_640_000));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger22()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(21));
// Note: 21! is not possible in C# until we got 128 bit integers, since:
// ulong.max == 18_446_744_073_709_551_615 < 51_090_942_171_709_400_000
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger23()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(45_646));
// Note: 45_646! is not possible in C# since:
// ulong.max == 18_446_744_073_709_551_615
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger24()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(-1));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialInteger25()
{
Assert.Throws<ArgumentOutOfRangeException>(() => MathTools.Factorial(-6_565));
}
#endregion
#region Factorial (floating point)
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint01()
{
Assert.That(MathTools.Factorial(0.5f), Is.EqualTo(0.886226925f).Within(1e6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint02()
{
Assert.That(MathTools.Factorial(1.5f), Is.EqualTo(1.329340388f).Within(1e6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint03()
{
Assert.That(MathTools.Factorial(-1.5f), Is.EqualTo(-1.329340388f).Within(1e6f));
}
[Test]
[Category(TestCategories.COVER)]
[Category(TestCategories.NORMAL)]
public void FactorialFloatingPoint04()
{
Assert.That(MathTools.Factorial(7.5f), Is.EqualTo(14_034.407293483f).Within(1e6f));
}
#endregion
}

1131
FastRngTests/MultiThreadedRngTests.cs
View File

File diff suppressed because it is too large Load Diff

241
FastRngTests/PerformanceTests.cs
View File

@ -9,129 +9,128 @@ using MathNet.Numerics.Distributions;
using MathNet.Numerics.Random;
using NUnit.Framework;
namespace FastRngTests
namespace FastRngTests;
[ExcludeFromCodeCoverage]
public class PerformanceTests
{
[ExcludeFromCodeCoverage]
public class PerformanceTests
#region FastRng
[Test]
[Category(TestCategories.PERFORMANCE)]
public async Task Generate1MUniform()
{
#region FastRng
using var rng = new MultiThreadedRng();
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = await rng.GetUniform();
stopwatch.Stop();
[Test]
[Category(TestCategories.PERFORMANCE)]
public async Task Generate1MUniform()
{
using var rng = new MultiThreadedRng();
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = await rng.GetUniform();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M uniform distributed random numbers in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public async Task Generate1MNormal()
{
using var rng = new MultiThreadedRng();
var dist = new NormalS02M05(rng);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = await dist.NextNumber();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M normal distributed random numbers in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public async Task Generate1MChiSquare()
{
using var rng = new MultiThreadedRng();
var dist = new ChiSquareK4(rng);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = await dist.NextNumber();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M chi-square distributed random numbers in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
#endregion
#region Math.NET
[Test]
[Category(TestCategories.PERFORMANCE)]
public void ComparisonMathNet1MUniform()
{
var rng = new Xorshift(true);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = (float) rng.NextDouble();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M uniform distributed random numbers by means of Math.NET in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public void ComparisonMathNet1MNormal()
{
var rng = new Xorshift(true);
var dist = new Normal(stddev: 0.2f, mean: 0.5f, randomSource: rng);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = (float) dist.Sample();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M normal distributed random numbers by means of Math.NET in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public void ComparisonMathNet1MChiSquare()
{
var rng = new Xorshift(true);
var dist = new ChiSquared(4);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = (float) dist.Sample();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M chi-squared distributed random numbers by means of Math.NET in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
#endregion
TestContext.WriteLine($"Generated 1M uniform distributed random numbers in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public async Task Generate1MNormal()
{
using var rng = new MultiThreadedRng();
var dist = new NormalS02M05(rng);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = await dist.NextNumber();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M normal distributed random numbers in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public async Task Generate1MChiSquare()
{
using var rng = new MultiThreadedRng();
var dist = new ChiSquareK4(rng);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = await dist.NextNumber();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M chi-square distributed random numbers in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
#endregion
#region Math.NET
[Test]
[Category(TestCategories.PERFORMANCE)]
public void ComparisonMathNet1MUniform()
{
var rng = new Xorshift(true);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = (float) rng.NextDouble();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M uniform distributed random numbers by means of Math.NET in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public void ComparisonMathNet1MNormal()
{
var rng = new Xorshift(true);
var dist = new Normal(stddev: 0.2f, mean: 0.5f, randomSource: rng);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = (float) dist.Sample();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M normal distributed random numbers by means of Math.NET in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
[Test]
[Category(TestCategories.PERFORMANCE)]
public void ComparisonMathNet1MChiSquare()
{
var rng = new Xorshift(true);
var dist = new ChiSquared(4);
var data = new float[1_000_000];
var stopwatch = new Stopwatch();
Thread.Sleep(TimeSpan.FromSeconds(10)); // Warm-up phase of generator
stopwatch.Start();
for (uint n = 0; n < data.Length; n++)
data[n] = (float) dist.Sample();
stopwatch.Stop();
TestContext.WriteLine($"Generated 1M chi-squared distributed random numbers by means of Math.NET in {stopwatch.Elapsed.Minutes} minute(s), {stopwatch.Elapsed.Seconds} second(s), and {stopwatch.Elapsed.Milliseconds} milliseconds.");
}
#endregion
}

73
FastRngTests/RunningStatistics.cs
View File

@ -1,49 +1,44 @@
using System;
using System.Diagnostics.CodeAnalysis;
namespace FastRngTests
namespace FastRngTests;
[ExcludeFromCodeCoverage]
internal sealed class RunningStatistics
{
[ExcludeFromCodeCoverage]
internal sealed class RunningStatistics
{
private float previousM;
private float previousS;
private float nextM;
private float nextS;
public RunningStatistics()
{
}
public int NumberRecords { get; private set; } = 0;
private float previousM;
private float previousS;
private float nextM;
private float nextS;
private int NumberRecords { get; set; } = 0;
public void Clear() => this.NumberRecords = 0;
public void Clear() => this.NumberRecords = 0;
public void Push(float x)
{
this.NumberRecords++;
public void Push(float x)
{
this.NumberRecords++;
// See Knuth TAOCP vol 2, 3rd edition, page 232
if (this.NumberRecords == 1)
{
this.previousM = this.nextM = x;
this.previousS = 0.0f;
}
else
{
this.nextM = this.previousM + (x - this.previousM) / this.NumberRecords;
this.nextS = this.previousS + (x - this.previousM) * (x - this.nextM);
// set up for next iteration
this.previousM = this.nextM;
this.previousS = this.nextS;
}
// See Knuth TAOCP vol 2, 3rd edition, page 232
if (this.NumberRecords == 1)
{
this.previousM = this.nextM = x;
this.previousS = 0.0f;
}
else
{
this.nextM = this.previousM + (x - this.previousM) / this.NumberRecords;
this.nextS = this.previousS + (x - this.previousM) * (x - this.nextM);
// set up for next iteration
this.previousM = this.nextM;
this.previousS = this.nextS;
}
public float Mean => this.NumberRecords > 0 ? this.nextM : 0.0f;
public float Variance => this.NumberRecords > 1 ? this.nextS / (this.NumberRecords - 1f) : 0.0f;
public float StandardDeviation => MathF.Sqrt(this.Variance);
}
public float Mean => this.NumberRecords > 0 ? this.nextM : 0.0f;
public float Variance => this.NumberRecords > 1 ? this.nextS / (this.NumberRecords - 1f) : 0.0f;
public float StandardDeviation => MathF.Sqrt(this.Variance);
}

17
FastRngTests/TestCategories.cs
View File

@ -1,11 +1,10 @@
namespace FastRngTests
namespace FastRngTests;
public static class TestCategories
{
public class TestCategories
{
public const string COVER = "cover";
public const string PERFORMANCE = "performance";
public const string NORMAL = "normal";
public const string EXAMPLE = "example";
public const string LONG_RUNNING = "long running";
}
public const string COVER = "cover";
public const string PERFORMANCE = "performance";
public const string NORMAL = "normal";
public const string EXAMPLE = "example";
public const string LONG_RUNNING = "long running";
}