Example #1
0
 public void CanCreateStable(double alpha, double beta, double scale, double location)
 {
     var n = new Stable(alpha, beta, scale, location);
     Assert.AreEqual(alpha, n.Alpha);
     Assert.AreEqual(beta, n.Beta);
     Assert.AreEqual(scale, n.Scale);
     Assert.AreEqual(location, n.Location);
 }
Example #2
0
 public void CanSampleSequence()
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     var ied = n.Samples();
     GC.KeepAlive(ied.Take(5).ToArray());
 }
Example #3
0
 public void CanSample()
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     n.Sample();
 }
Example #4
0
 public void ValidateDensityLn(double alpha, double beta, double scale, double location, double x, double dln)
 {
     var n = new Stable(alpha, beta, scale, location);
     AssertHelpers.AlmostEqualRelative(dln, n.DensityLn(x), 15);
 }
Example #5
0
 public void ValidateMaximum()
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.AreEqual(Double.PositiveInfinity, n.Maximum);
 }
Example #6
0
 public void ValidateMinimum(double beta)
 {
     var n = new Stable(1.0, beta, 1.0, 1.0);
     Assert.AreEqual(Math.Abs(beta) != 1 ? Double.NegativeInfinity : 0.0, n.Minimum);
 }
 public void SetBetaFail(double beta)
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.That(() => n.Beta = beta, Throws.ArgumentException);
 }
Example #8
0
 public void ValidateToString()
 {
     var n = new Stable(1.2d, 0.3d, 1d, 2d);
     Assert.AreEqual("Stable(α = 1.2, β = 0.3, c = 1, μ = 2)", n.ToString());
 }
Example #9
0
 public void ValidateEntropyThrowsNotSupportedException()
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.Throws<NotSupportedException>(() => { var e = n.Entropy; });
 }
Example #10
0
 public void SetScaleFail(double scale)
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.Throws<ArgumentOutOfRangeException>(() => n.Scale = scale);
 }
Example #11
0
 public void SetLocationFail()
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.Throws<ArgumentOutOfRangeException>(() => n.Location = Double.NaN);
 }
Example #12
0
 public void SetBetaFail(double beta)
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.Throws<ArgumentOutOfRangeException>(() => n.Beta = beta);
 }
Example #13
0
 public void SetAlphaFail(double alpha)
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.Throws<ArgumentOutOfRangeException>(() => n.Alpha = alpha);
 }
 public void SetScaleFail(double scale)
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.That(() => n.Scale = scale, Throws.ArgumentException);
 }
 public void SetLocationFail()
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.That(() => n.Location = Double.NaN, Throws.ArgumentException);
 }
Example #16
0
 public void ValidateCumulativeDistribution(double alpha, double beta, double scale, double location, double x, double cdf)
 {
     var n = new Stable(alpha, beta, scale, location);
     AssertHelpers.AlmostEqualRelative(cdf, n.CumulativeDistribution(x), 15);
 }
Example #17
0
 public void ValidateSkewness()
 {
     var n = new Stable(2.0, 1.0, 1.0, 1.0);
     if (n.Alpha == 2)
     {
         Assert.AreEqual(0.0, n.Skewness);
     }
 }
Example #18
0
 public void ValidateMedian(double location)
 {
     var n = new Stable(1.0, 0.0, 1.0, location);
     if (n.Beta == 0)
     {
         Assert.AreEqual(location, n.Mode);
     }
 }
        /// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/Stable_distribution">Stable distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the Stable distribution class with parameters Alpha = 2.0, Beta = 0, Scale = 1, Location = 0.
            var stable = new Stable(2.0, 0, 1, 0);
            Console.WriteLine(@"1. Initialize the new instance of the Stable distribution class with parameters Alpha = {0}, Beta = {1}, Scale = {2}, Location = {3}", stable.Alpha, stable.Beta, stable.Scale, stable.Location);
            Console.WriteLine();

            // 2. Distributuion properties:
            Console.WriteLine(@"2. {0} distributuion properties:", stable);

            // Cumulative distribution function
            Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", stable.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));

            // Probability density
            Console.WriteLine(@"{0} - Probability density at location '0.3'", stable.Density(0.3).ToString(" #0.00000;-#0.00000"));

            // Log probability density
            Console.WriteLine(@"{0} - Log probability density at location '0.3'", stable.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));

            // Largest element in the domain
            Console.WriteLine(@"{0} - Largest element in the domain", stable.Maximum.ToString(" #0.00000;-#0.00000"));

            // Smallest element in the domain
            Console.WriteLine(@"{0} - Smallest element in the domain", stable.Minimum.ToString(" #0.00000;-#0.00000"));

            // Mean
            Console.WriteLine(@"{0} - Mean", stable.Mean.ToString(" #0.00000;-#0.00000"));

            // Median
            Console.WriteLine(@"{0} - Median", stable.Median.ToString(" #0.00000;-#0.00000"));

            // Mode
            Console.WriteLine(@"{0} - Mode", stable.Mode.ToString(" #0.00000;-#0.00000"));

            // Variance
            Console.WriteLine(@"{0} - Variance", stable.Variance.ToString(" #0.00000;-#0.00000"));

            // Standard deviation
            Console.WriteLine(@"{0} - Standard deviation", stable.StdDev.ToString(" #0.00000;-#0.00000"));

            // Skewness
            Console.WriteLine(@"{0} - Skewness", stable.Skewness.ToString(" #0.00000;-#0.00000"));
            Console.WriteLine();

            // 3. Generate 10 samples of the Stable distribution
            Console.WriteLine(@"3. Generate 10 samples of the Stable distribution");
            for (var i = 0; i < 10; i++)
            {
                Console.Write(stable.Sample().ToString("N05") + @" ");
            }

            Console.WriteLine();
            Console.WriteLine();

            // 4. Generate 100000 samples of the Stable(1) distribution and display histogram
            Console.WriteLine(@"4. Generate 100000 samples of the Stable(2, 0, 1, 0) distribution and display histogram");
            var data = new double[100000];
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = stable.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 5. Generate 100000 samples of the Stable(1, 0, 1, 0) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the Stable(1, 0, 1, 0) distribution and display histogram");
            stable.Alpha = 1;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = stable.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 6. Generate 100000 samples of the Stable(1.5, 1, 1, 5) distribution and display histogram
            Console.WriteLine(@"6. Generate 100000 samples of the Stable(1.5, 1, 1, 5) distribution and display histogram");
            stable.Alpha = 1.5;
            stable.Beta = 1;
            stable.Location = 5;
            stable.Scale = 5;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = stable.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
        }
 public void SetAlphaFail(double alpha)
 {
     var n = new Stable(1.0, 1.0, 1.0, 1.0);
     Assert.That(() => n.Alpha = alpha, Throws.ArgumentException);
 }