Simple sampling implementation

Also corrected some comments.
Added more tests

src/Numerics/Distributions/TruncatedNormal.cs

@@ -72,9 +72,9 @@ namespace MathNet.Numerics.Distributions {
 		readonly double _cumulativeDensityWithinBounds;
 
 		/// <summary>
-		/// Initializes a new instance of the TruncatedNormal class with a particular mean, standard deviation, lower bound, and upper bound. The distribution will
-		/// be initialized with the default <seealso cref="System.Random"/> random number generator. The mean and standard deviation are that of the untruncated
-		/// normal distribution.
+		/// Initializes a new instance of the TruncatedNormal class. The distribution will
+		/// be initialized with the default <seealso cref="System.Random"/> random number generator. The mean 
+		/// and standard deviation are that of the untruncated normal distribution.
 		/// </summary>
 		/// <param name="mean">The mean (μ) of the untruncated distribution.</param>
 		/// <param name="stddev">The standard deviation (σ) of the untruncated distribution. Range: σ > 0.</param>
@@ -88,22 +88,26 @@ namespace MathNet.Numerics.Distributions {
 		}
 
 		/// <summary>
-		/// Initializes a new instance of the Normal class with a particular mean and standard deviation. The distribution will
-		/// be initialized with the default <seealso cref="System.Random"/> random number generator.
+		/// Initializes a new instance of the TruncatedNormal class. The distribution will
+		/// be initialized with the provided <seealso cref="System.Random"/> random number generator.
 		/// </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>
+		/// <param name="untruncatedMean">The mean (μ) of the untruncated normal distribution.</param>
+		/// <param name="untruncatedStdDev">The standard deviation (σ) of the untruncated normal distribution. Range: σ > 0.</param>
 		/// <param name="randomSource">The random number generator which is used to draw random samples.</param>
-		public TruncatedNormal(double mean, double stddev, System.Random randomSource, double lowerBound = double.NegativeInfinity, double upperBound = double.PositiveInfinity) 
+		/// <param name="lowerBound">The inclusive lower bound of the truncated distribution. Default is double.NegativeInfinity.</param>
+		/// <param name="upperBound">The inclusive upper bound of the truncated distribution. Must be larger than <paramref name="lowerBound"/>.
+		/// Default is double.PositiveInfinity.</param>
+
+		public TruncatedNormal(double untruncatedMean, double untruncatedStdDev, System.Random randomSource, double lowerBound = double.NegativeInfinity, double upperBound = double.PositiveInfinity) 
 		{
-			if (!IsValidParameterSet(mean, stddev, lowerBound, upperBound)) 
+			if (!IsValidParameterSet(untruncatedMean, untruncatedStdDev, lowerBound, upperBound)) 
 			{
 				throw new ArgumentException(Resources.InvalidDistributionParameters);
 			}
 
 			_random = randomSource ?? SystemRandomSource.Default;
-			_mu = mean;
-			_sigma = stddev;
+			_mu = untruncatedMean;
+			_sigma = untruncatedStdDev;
 			_lowerBound = lowerBound;
 			_upperBound = upperBound;
 			_alpha = (_lowerBound - _mu) / _sigma;
@@ -279,22 +283,26 @@ namespace MathNet.Numerics.Distributions {
 			return _standardNormal.DensityLn((x - _mu) / _sigma) - Math.Log(_sigma) - Math.Log(_cumulativeDensityWithinBounds);
       }
 
-		//TODO: implement sampling, use method described by Mazet here: http://miv.u-strasbg.fr/mazet/rtnorm/
-		// see implementations listed on that page for examples.
 
 		public double Sample() 
 		{
-			throw new NotImplementedException();
+			//TODO: implement sampling more efficiently/accurately, use method described by Mazet here: http://miv.u-strasbg.fr/mazet/rtnorm/
+			// see implementations listed on that page for examples.
+			return InverseCumulativeDistribution(RandomSource.NextDouble());
 		}
 
 		public void Samples(double[] values) 
 		{
-			throw new NotImplementedException();
+			for(int i = 0; i < values.Length; i++) {
+				values[i] = Sample();
+			}
 		}
 
 		public IEnumerable<double> Samples() 
 		{
-			throw new NotImplementedException();
+			while (true) {
+				yield return Sample();
+			}
 		}
 
 		/// <summary>

src/UnitTests/DistributionTests/CommonDistributionTests.cs

@@ -89,8 +89,8 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
                 new StudentT(0.0, 1.0, 5.0),
                 new Triangular(0, 1, 0.7),
                 new Weibull(1.0, 1.0),
-					 new TruncatedNormal(0, 1.0, -5.0, 5.0), //Finite
-					 new TruncatedNormal(0, 1.0, -5.0),      //Semi-finite
+					 new TruncatedNormal(0, 1.0, -1.0, 1.5), //Finite
+					 new TruncatedNormal(0, 1.0, -0.5),      //Semi-finite
             };
 
         [Test]

src/UnitTests/DistributionTests/Continuous/TruncatedNormalTests.cs

@@ -110,7 +110,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
 		[TestCase(Double.PositiveInfinity, 1.0)]
 		public void ValidateCumulativeNoBounds(double x, double p) {
 			var truncatedNormal = new TruncatedNormal(5.0, 2.0);
-			AssertHelpers.AlmostEqualRelative(p, truncatedNormal.CumulativeDistribution(x), 14);
+			AssertHelpers.AlmostEqualRelative(p, truncatedNormal.CumulativeDistribution(x), 14); 
 		}
 
 		/// <summary>
@@ -156,6 +156,61 @@ namespace MathNet.Numerics.UnitTests.DistributionTests.Continuous
 			}
 		}
 
+		/// <summary>
+		/// Validate density when only one bound is are specified. 
+		/// </summary>
+		/// <param name="mean">Mean value.</param>
+		/// <param name="sdev">Standard deviation value.</param>
+		[TestCase(10.0, 0.1, -5.0)]
+		[TestCase(-5.0, 1.0, 3.0)]
+		[TestCase(0.0, 10.0, -10.0)]
+		[TestCase(10.0, 100.0, 15.0)]
+		[TestCase(-5.0, Double.PositiveInfinity, -5.0)]
+		public void ValidateDensitySemiFinite(double mean, double sdev, double lowerBound) {
+			var truncatedNormal = new TruncatedNormal(mean, sdev, lowerBound);
+			var normal = new Normal(mean, sdev);
+			for (var i = 0; i < 11; i++) {
+				var x = i - 5.0;
+				double density;
+				if(x < lowerBound) {
+					density = 0d;
+				} else {
+					var d = (mean - x) / sdev;
+					var pdf = Math.Exp(-0.5 * d * d) / (sdev * Constants.Sqrt2Pi);
+					density = pdf / (1.0 - normal.CumulativeDistribution(lowerBound));
+				}
+				AssertHelpers.AlmostEqualRelative(density, truncatedNormal.Density(x), 14);
+			}
+		}
+
+		/// <summary>
+		/// Validate density when both bounds are specified.
+		/// </summary>
+		/// <param name="mean">Mean value.</param>
+		/// <param name="sdev">Standard deviation value.</param>
+		[TestCase(10.0, 0.1, -5.0, 5.0)]
+		[TestCase(-5.0, 1.0, double.NegativeInfinity, -5.0)]
+		[TestCase(0.0, 10.0, -10.0, 15.0)]
+		[TestCase(10.0, 100.0, 15.0, 100.0)]
+		[TestCase(-5.0, Double.PositiveInfinity, -5.0, 0.0)]
+		public void ValidateDensityFinite(double mean, double sdev, double lowerBound, double upperBound) {
+			var truncatedNormal = new TruncatedNormal(mean, sdev, lowerBound, upperBound);
+			var normal = new Normal(mean, sdev);
+			for (var i = 0; i < 11; i++) {
+				var x = i - 5.0;
+				double density;
+				if (x < lowerBound || upperBound < x) {
+					density = 0d;
+				} else {
+					var d = (mean - x) / sdev;
+					var pdf = Math.Exp(-0.5 * d * d) / (sdev * Constants.Sqrt2Pi);
+					density = pdf / (normal.CumulativeDistribution(upperBound) - normal.CumulativeDistribution(lowerBound));
+				}
+				AssertHelpers.AlmostEqualRelative(density, truncatedNormal.Density(x), 14);
+			}
+		}
+
+
 		/// <summary>
 		/// Validate density log when no bounds are specified. Uses same 
 		/// test cases as the Normal distribution as should be equivalent in this case.