Distributions: shortcut static sample functions (continuous)

src/Numerics/Distributions/Beta.cs

@@ -561,5 +561,27 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, a, b);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="a">The α shape parameter of the Beta distribution. Range: α ≥ 0.</param>
+        /// <param name="b">The β shape parameter of the Beta distribution. Range: β ≥ 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double a, double b)
+        {
+            return Sample(SystemRandomSource.Default, a, b);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="a">The α shape parameter of the Beta distribution. Range: α ≥ 0.</param>
+        /// <param name="b">The β shape parameter of the Beta distribution. Range: β ≥ 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double a, double b)
+        {
+            return Samples(SystemRandomSource.Default, a, b);
+        }
     }
 }

src/Numerics/Distributions/Cauchy.cs

@@ -361,5 +361,27 @@ namespace MathNet.Numerics.Distributions
                 yield return location + scale*Math.Tan(Constants.Pi*(rnd.NextDouble() - 0.5));
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="location">The location (x0) of the distribution.</param>
+        /// <param name="scale">The scale (γ) of the distribution. Range: γ > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double location, double scale)
+        {
+            return Sample(SystemRandomSource.Default, location, scale);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="location">The location (x0) of the distribution.</param>
+        /// <param name="scale">The scale (γ) of the distribution. Range: γ > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double location, double scale)
+        {
+            return Samples(SystemRandomSource.Default, location, scale);
+        }
     }
 }

src/Numerics/Distributions/Chi.cs

@@ -337,5 +337,25 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, freedom);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="freedom">The degrees of freedom (k) of the distribution. Range: k > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(int freedom)
+        {
+            return Sample(SystemRandomSource.Default, freedom);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="freedom">The degrees of freedom (k) of the distribution. Range: k > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(int freedom)
+        {
+            return Samples(SystemRandomSource.Default, freedom);
+        }
     }
 }

src/Numerics/Distributions/ChiSquared.cs

@@ -330,5 +330,25 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, freedom);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the <c>ChiSquare</c> distribution.
+        /// </summary>
+        /// <param name="freedom">The degrees of freedom (k) of the distribution. Range: k > 0.</param>
+        /// <returns>a sample from the distribution. </returns>
+        public static double Sample(double freedom)
+        {
+            return Sample(SystemRandomSource.Default, freedom);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="freedom">The degrees of freedom (k) of the distribution. Range: k > 0.</param>
+        /// <returns>a sample from the distribution. </returns>
+        public static IEnumerable<double> Samples(double freedom)
+        {
+            return Samples(SystemRandomSource.Default, freedom);
+        }
     }
 }

src/Numerics/Distributions/ContinuousUniform.cs

@@ -364,5 +364,27 @@ namespace MathNet.Numerics.Distributions
                 yield return lower + rnd.NextDouble()*(upper - lower);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the <c>ContinuousUniform</c> distribution.
+        /// </summary>
+        /// <param name="lower">Lower bound. Range: lower ≤ upper.</param>
+        /// <param name="upper">Upper bound. Range: lower ≤ upper.</param>
+        /// <returns>a uniformly distributed sample.</returns>
+        public static double Sample(double lower, double upper)
+        {
+            return Sample(SystemRandomSource.Default, lower, upper);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the <c>ContinuousUniform</c> distribution.
+        /// </summary>
+        /// <param name="lower">Lower bound. Range: lower ≤ upper.</param>
+        /// <param name="upper">Upper bound. Range: lower ≤ upper.</param>
+        /// <returns>a sequence of uniformly distributed samples.</returns>
+        public static IEnumerable<double> Samples(double lower, double upper)
+        {
+            return Samples(SystemRandomSource.Default, lower, upper);
+        }
     }
 }

src/Numerics/Distributions/Erlang.cs

@@ -514,5 +514,27 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, shape, rate);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="shape">The shape (k) of the Erlang distribution. Range: k ≥ 0.</param>
+        /// <param name="rate">The rate or inverse scale (λ) of the Erlang distribution. Range: λ ≥ 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double shape, double rate)
+        {
+            return Sample(SystemRandomSource.Default, shape, rate);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="shape">The shape (k) of the Erlang distribution. Range: k ≥ 0.</param>
+        /// <param name="rate">The rate or inverse scale (λ) of the Erlang distribution. Range: λ ≥ 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double shape, double rate)
+        {
+            return Samples(SystemRandomSource.Default, shape, rate);
+        }
     }
 }

src/Numerics/Distributions/Exponential.cs

@@ -349,5 +349,25 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, rate);
             }
         }
+
+        /// <summary>
+        /// Draws a random sample from the distribution.
+        /// </summary>
+        /// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
+        /// <returns>A random number from this distribution.</returns>
+        public static double Sample(double rate)
+        {
+            return Sample(SystemRandomSource.Default, rate);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the Exponential distribution.
+        /// </summary>
+        /// <param name="rate">The rate (λ) parameter of the distribution. Range: λ ≥ 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double rate)
+        {
+            return Samples(SystemRandomSource.Default, rate);
+        }
     }
 }

src/Numerics/Distributions/FisherSnedecor.cs

@@ -399,5 +399,27 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, d1, d2);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="d1">The first degree of freedom (d1) of the distribution. Range: d1 > 0.</param>
+        /// <param name="d2">The second degree of freedom (d2) of the distribution. Range: d2 > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double d1, double d2)
+        {
+            return Sample(SystemRandomSource.Default, d1, d2);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="d1">The first degree of freedom (d1) of the distribution. Range: d1 > 0.</param>
+        /// <param name="d2">The second degree of freedom (d2) of the distribution. Range: d2 > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double d1, double d2)
+        {
+            return Samples(SystemRandomSource.Default, d1, d2);
+        }
     }
 }

src/Numerics/Distributions/Gamma.cs

@@ -546,5 +546,27 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, shape, rate);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the Gamma distribution.
+        /// </summary>
+        /// <param name="shape">The shape (k, α) of the Gamma distribution. Range: α ≥ 0.</param>
+        /// <param name="rate">The rate or inverse scale (β) of the Gamma distribution. Range: β ≥ 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double shape, double rate)
+        {
+            return Sample(SystemRandomSource.Default, shape, rate);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the Gamma distribution.
+        /// </summary>
+        /// <param name="shape">The shape (k, α) of the Gamma distribution. Range: α ≥ 0.</param>
+        /// <param name="rate">The rate or inverse scale (β) of the Gamma distribution. Range: β ≥ 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double shape, double rate)
+        {
+            return Samples(SystemRandomSource.Default, shape, rate);
+        }
     }
 }

src/Numerics/Distributions/InverseGamma.cs

@@ -343,5 +343,27 @@ namespace MathNet.Numerics.Distributions
 
             return Gamma.Samples(rnd, shape, scale).Select(z => 1.0/z);
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="shape">The shape (α) of the distribution. Range: α > 0.</param>
+        /// <param name="scale">The scale (β) of the distribution. Range: β > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double shape, double scale)
+        {
+            return Sample(SystemRandomSource.Default, shape, scale);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="shape">The shape (α) of the distribution. Range: α > 0.</param>
+        /// <param name="scale">The scale (β) of the distribution. Range: β > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double shape, double scale)
+        {
+            return Samples(SystemRandomSource.Default, shape, scale);
+        }
     }
 }

src/Numerics/Distributions/Laplace.cs

@@ -349,5 +349,27 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, location, scale);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="location">The location (μ) of the distribution.</param>
+        /// <param name="scale">The scale (b) of the distribution. Range: b > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double location, double scale)
+        {
+            return Sample(SystemRandomSource.Default, location, scale);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="location">The location (μ) of the distribution.</param>
+        /// <param name="scale">The scale (b) of the distribution. Range: b > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double location, double scale)
+        {
+            return Samples(SystemRandomSource.Default, location, scale);
+        }
     }
 }

src/Numerics/Distributions/LogNormal.cs

@@ -429,5 +429,27 @@ namespace MathNet.Numerics.Distributions
         {
             return Normal.Samples(rnd, mu, sigma).Select(Math.Exp);
         }
+
+        /// <summary>
+        /// Generates a sample from the log-normal distribution using the <i>Box-Muller</i> algorithm.
+        /// </summary>
+        /// <param name="mu">The log-scale (μ) of the distribution.</param>
+        /// <param name="sigma">The shape (σ) of the distribution. Range: σ ≥ 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double mu, double sigma)
+        {
+            return Sample(SystemRandomSource.Default, mu, sigma);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the log-normal distribution using the <i>Box-Muller</i> algorithm.
+        /// </summary>
+        /// <param name="mu">The log-scale (μ) of the distribution.</param>
+        /// <param name="sigma">The shape (σ) of the distribution. Range: σ ≥ 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double mu, double sigma)
+        {
+            return Samples(SystemRandomSource.Default, mu, sigma);
+        }
     }
 }

src/Numerics/Distributions/Normal.cs

@@ -460,5 +460,27 @@ namespace MathNet.Numerics.Distributions
                 yield return mean + (stddev*sample.Item2);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the normal distribution using the <i>Box-Muller</i> algorithm.
+        /// </summary>
+        /// <param name="mean">The mean (μ) of the normal distribution.</param>
+        /// <param name="stddev">The standard deviation (σ) of the normal distribution. Range: σ ≥ 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double mean, double stddev)
+        {
+            return Sample(SystemRandomSource.Default, mean, stddev);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the normal distribution using the <i>Box-Muller</i> algorithm.
+        /// </summary>
+        /// <param name="mean">The mean (μ) of the normal distribution.</param>
+        /// <param name="stddev">The standard deviation (σ) of the normal distribution. Range: σ ≥ 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double mean, double stddev)
+        {
+            return Samples(SystemRandomSource.Default, mean, stddev);
+        }
     }
 }

src/Numerics/Distributions/Pareto.cs

@@ -374,5 +374,27 @@ namespace MathNet.Numerics.Distributions
                 yield return scale*Math.Pow(rnd.NextDouble(), power);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="scale">The scale (xm) of the distribution. Range: xm > 0.</param>
+        /// <param name="shape">The shape (α) of the distribution. Range: α > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double scale, double shape)
+        {
+            return Sample(SystemRandomSource.Default, scale, shape);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="scale">The scale (xm) of the distribution. Range: xm > 0.</param>
+        /// <param name="shape">The shape (α) of the distribution. Range: α > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double scale, double shape)
+        {
+            return Samples(SystemRandomSource.Default, scale, shape);
+        }
     }
 }

src/Numerics/Distributions/Rayleigh.cs

@@ -337,5 +337,25 @@ namespace MathNet.Numerics.Distributions
                 yield return scale*Math.Sqrt(-2.0*Math.Log(rnd.NextDouble()));
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="scale">The scale (σ) of the distribution. Range: σ > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double scale)
+        {
+            return Sample(SystemRandomSource.Default, scale);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="scale">The scale (σ) of the distribution. Range: σ > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double scale)
+        {
+            return Samples(SystemRandomSource.Default, scale);
+        }
     }
 }

src/Numerics/Distributions/Stable.cs

@@ -489,5 +489,31 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, alpha, beta, scale, location);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the distribution.
+        /// </summary>
+        /// <param name="alpha">The stability (α) of the distribution. Range: 2 ≥ α > 0.</param>
+        /// <param name="beta">The skewness (β) of the distribution. Range: 1 ≥ β ≥ -1.</param>
+        /// <param name="scale">The scale (c) of the distribution. Range: c > 0.</param>
+        /// <param name="location">The location (μ) of the distribution.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double alpha, double beta, double scale, double location)
+        {
+            return Sample(SystemRandomSource.Default, alpha, beta, scale, location);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the distribution.
+        /// </summary>
+        /// <param name="alpha">The stability (α) of the distribution. Range: 2 ≥ α > 0.</param>
+        /// <param name="beta">The skewness (β) of the distribution. Range: 1 ≥ β ≥ -1.</param>
+        /// <param name="scale">The scale (c) of the distribution. Range: c > 0.</param>
+        /// <param name="location">The location (μ) of the distribution.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double alpha, double beta, double scale, double location)
+        {
+            return Samples(SystemRandomSource.Default, alpha, beta, scale, location);
+        }
     }
 }

src/Numerics/Distributions/StudentT.cs

@@ -484,5 +484,29 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, location, scale, freedom);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the Student t-distribution.
+        /// </summary>
+        /// <param name="location">The location (μ) of the distribution.</param>
+        /// <param name="scale">The scale (σ) of the distribution. Range: σ > 0.</param>
+        /// <param name="freedom">The degrees of freedom (ν) for the distribution. Range: ν > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double location, double scale, double freedom)
+        {
+            return Sample(SystemRandomSource.Default, location, scale, freedom);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the Student t-distribution using the <i>Box-Muller</i> algorithm.
+        /// </summary>
+        /// <param name="location">The location (μ) of the distribution.</param>
+        /// <param name="scale">The scale (σ) of the distribution. Range: σ > 0.</param>
+        /// <param name="freedom">The degrees of freedom (ν) for the distribution. Range: ν > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double location, double scale, double freedom)
+        {
+            return Samples(SystemRandomSource.Default, location, scale, freedom);
+        }
     }
 }

src/Numerics/Distributions/Triangular.cs

@@ -416,5 +416,28 @@ namespace MathNet.Numerics.Distributions
             }
         }
 
+        /// <summary>
+        /// Generates a sample from the <c>Triangular</c> distribution.
+        /// </summary>
+        /// <param name="lower">Lower bound. Range: lower ≤ mode ≤ upper</param>
+        /// <param name="upper">Upper bound. Range: lower ≤ mode ≤ upper</param>
+        /// <param name="mode">Mode (most frequent value).  Range: lower ≤ mode ≤ upper</param>
+        /// <returns>a sample from the distribution.</returns>
+        public double Sample(double lower, double upper, double mode)
+        {
+            return Sample(SystemRandomSource.Default, lower, upper, mode);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the <c>Triangular</c> distribution.
+        /// </summary>
+        /// <param name="lower">Lower bound. Range: lower ≤ mode ≤ upper</param>
+        /// <param name="upper">Upper bound. Range: lower ≤ mode ≤ upper</param>
+        /// <param name="mode">Mode (most frequent value).  Range: lower ≤ mode ≤ upper</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public IEnumerable<double> Samples(double lower, double upper, double mode)
+        {
+            return Samples(SystemRandomSource.Default, lower, upper, mode);
+        }
     }
 }

src/Numerics/Distributions/Weibull.cs

@@ -413,5 +413,27 @@ namespace MathNet.Numerics.Distributions
                 yield return SampleUnchecked(rnd, shape, scale);
             }
         }
+
+        /// <summary>
+        /// Generates a sample from the Weibull distribution.
+        /// </summary>
+        /// <param name="shape">The shape (k) of the Weibull distribution. Range: k > 0.</param>
+        /// <param name="scale">The scale (λ) of the Weibull distribution. Range: λ > 0.</param>
+        /// <returns>a sample from the distribution.</returns>
+        public static double Sample(double shape, double scale)
+        {
+            return Sample(SystemRandomSource.Default, shape, scale);
+        }
+
+        /// <summary>
+        /// Generates a sequence of samples from the Weibull distribution.
+        /// </summary>
+        /// <param name="shape">The shape (k) of the Weibull distribution. Range: k > 0.</param>
+        /// <param name="scale">The scale (λ) of the Weibull distribution. Range: λ > 0.</param>
+        /// <returns>a sequence of samples from the distribution.</returns>
+        public static IEnumerable<double> Samples(double shape, double scale)
+        {
+            return Samples(SystemRandomSource.Default, shape, scale);
+        }
     }
 }