1 files changed, 0 insertions, 51 deletions
diff --git a/Emby.Server.Implementations/TextEncoding/NLangDetect/Extensions/RandomExtensions.cs b/Emby.Server.Implementations/TextEncoding/NLangDetect/Extensions/RandomExtensions.cs
deleted file mode 100644
index 5b2fce60b..000000000
--- a/Emby.Server.Implementations/TextEncoding/NLangDetect/Extensions/RandomExtensions.cs
+++ /dev/null
@@ -1,51 +0,0 @@
-using System;
-
-namespace NLangDetect.Core.Extensions
-{
-    public static class RandomExtensions
-    {
-        private const double _Epsilon = 2.22044604925031E-15;
-
-        private static readonly object _mutex = new object();
-
-        private static double _nextNextGaussian;
-        private static bool _hasNextNextGaussian;
-
-        /// <summary>
-        /// Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.
-        /// The general contract of nextGaussian is that one double value, chosen from (approximately) the usual normal distribution with mean 0.0 and standard deviation 1.0, is pseudorandomly generated and returned.
-        /// </summary>
-        /// <remarks>
-        /// Taken from: http://download.oracle.com/javase/6/docs/api/java/util/Random.html (nextGaussian())
-        /// </remarks>
-        public static double NextGaussian(this Random random)
-        {
-            lock (_mutex)
-            {
-                if (_hasNextNextGaussian)
-                {
-                    _hasNextNextGaussian = false;
-
-                    return _nextNextGaussian;
-                }
-
-                double v1, v2, s;
-
-                do
-                {
-                    v1 = 2.0 * random.NextDouble() - 1.0; // between -1.0 and 1.0
-                    v2 = 2.0 * random.NextDouble() - 1.0; // between -1.0 and 1.0
-                    s = v1 * v1 + v2 * v2;
-                }
-                while (s >= 1.0 || Math.Abs(s - 0.0) < _Epsilon);
-
-                double multiplier = Math.Sqrt(-2.0 * Math.Log(s) / s);
-
-                _nextNextGaussian = v2 * multiplier;
-                _hasNextNextGaussian = true;
-
-                return v1 * multiplier;
-            }
-        }
-    }
-}