【原创】开源Math.NET基础数学类库使用(12)C#随机数扩展方法

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开源Math.NET基础数学类库使用总目录:【目录】开源Math.NET基础数学类库使用总目录

前言

  真正意义上的随机数(或者随机事件)在某次产生过程中是按照实验过程中表现的分布概率随机产生的,其结果是不可预测的,是不可见的。而计算机中的随机函数是按照一定算法模拟产生的,其结果是确定的,是可见的。我们可以这样认为这个可预见的结果其出现的概率是100%。所以用计算机随机函数所产生的“随机数”并不随机,是伪随机数。伪随机数的作用在开发中的使用非常常见,因此.NET在System命名空间,提供了一个简单的Random随机数生成类型。但这个类型并不能满足所有的需求,本节开始就将陆续介绍Math.NET中有关随机数的扩展以及其他伪随机生成算法编写的随机数生成器。

  今天要介绍的是基于System.Random的扩展方法。

  如果本文显示有问题,请参考:http://www.cnblogs.com/asxinyu/p/4301544.html

1.Random的扩展方法类

  Rondom扩展及随机数相关的类都在Math.NET的MathNet.Numerics.Random命名空间,今天要介绍的 RandomExtensions 类是 扩展Random的静态方法类,可以直接在System.Random的对象上使用,相关功能介绍:

1.可以直接返回填充0-1随机数据的数组,如NextDoubles方法

2.可以返回一个无限长度的IEnumerable接口对象,一直迭代返回double类型的随机数,是NextDoubleSequence方法

3.类似的还可以返回其他类型的随机数据数组,如NextBytes,NextInt32s等

4.还可以单独返回Int32类型和Int64类型的随机数,其范围在该类型的所有值域上,如NextFullRangeInt32,NextFullRangeInt64

5.还可以单独返回Int32类型和Int64类型的随机数,其范围是该类型所有值域上的非负数,如NextInt64;

2.RandomExtensions类的实现

  作为静态类,使用非常简单,为了方便理解,我将注释进行了部分翻译,贴出该类的所有源码,大家可以参考参考: 

  1 /// <summary>这个类是对System.Random类的扩展,扩展方法可以生成更多类型的伪随机数,而不是仅仅是double和Int32类型</summary>
  2 /// <remarks>这个扩展是线程安全的,并且只有在Math.NET提供的随机数发生器或者RandomSource的继承类中被调用</remarks>
  3 public static class RandomExtensions
  4 {
  5     /// <summary>使用(0-1)范围内的均匀随机数填充1个数组</summary>
  6     /// <param name="rnd">Random类型的随机数生成器</param>
  7     /// <param name="values">要填充随机数的数组</param>
  8     /// <remarks>这个扩展是线程安全的,并且只有在Math.NET提供的随机数发生器或者RandomSource的继承类中被调用</remarks>
  9     public static void NextDoubles(this System.Random rnd, double[] values)
 10     {
 11         var rs = rnd as RandomSource;
 12         if (rs != null)
 13         {
 14             rs.NextDoubles(values);
 15             return;
 16         }
 17 
 18         for (var i = 0; i < values.Length; i++)
 19         {
 20             values[i] = rnd.NextDouble();
 21         }
 22     }
 23 
 24     /// <summary>返回一个(0-1)范围内的均匀随机数填充1个数组</summary>
 25     /// <param name="rnd">Random类型的随机数生成器</param>
 26     /// <param name="count">要返回的数组的长度</param>
 27    
 28     public static double[] NextDoubles(this System.Random rnd, int count)
 29     {
 30         var values = new double[count];
 31         NextDoubles(rnd, values);
 32         return values;
 33     }
 34 
 35     /// <summary>返回1个无限的0-1均匀分布随机数序列</summary>
 36     public static IEnumerable<double> NextDoubleSequence(this System.Random rnd)
 37     {
 38         var rs = rnd as RandomSource;
 39         if (rs != null) return rs.NextDoubleSequence();
 40         return NextDoubleSequenceEnumerable(rnd);
 41     }
 42 
 43     static IEnumerable<double> NextDoubleSequenceEnumerable(System.Random rnd)
 44     {
 45         while (true)
 46         {
 47             yield return rnd.NextDouble();
 48         }
 49     }
 50 
 51     /// <summary>返回1个均匀分布的byte数组</summary>
 52     /// <param name="rnd">Random类型的随机数生成器</param>
 53     /// <param name="count">要返回的数组的长度</param>
 54     public static byte[] NextBytes(this System.Random rnd, int count)
 55     {
 56         var values = new byte[count];
 57         rnd.NextBytes(values);
 58         return values;
 59     }
 60 
 61     /// <summary>
 62     /// Fills an array with uniform random numbers greater than or equal to 0.0 and less than 1.0.
 63     /// </summary>
 64     /// <param name="rnd">The random number generator.</param>
 65     /// <param name="values">The array to fill with random values.</param>
 66     /// <param name="minInclusive">Lower bound, inclusive.</param>
 67     /// <param name="maxExclusive">Upper bound, exclusive.</param>
 68     public static void NextInt32s(this System.Random rnd, int[] values, int minInclusive, int maxExclusive)
 69     {
 70         var rs = rnd as RandomSource;
 71         if (rs != null)
 72         {
 73             rs.NextInt32s(values, minInclusive, maxExclusive);
 74             return;
 75         }
 76         for (var i = 0; i < values.Length; i++)
 77         {
 78             values[i] = rnd.Next(minInclusive, maxExclusive);
 79         }
 80     }
 81 
 82     /// <summary>
 83     /// Returns an infinite sequence of uniform random numbers greater than or equal to 0.0 and less than 1.0.
 84     /// </summary>
 85     public static IEnumerable<int> NextInt32Sequence(this System.Random rnd, int minInclusive, int maxExclusive)
 86     {
 87         var rs = rnd as RandomSource;
 88         if (rs != null)
 89         {
 90             return rs.NextInt32Sequence(minInclusive, maxExclusive);
 91         }
 92         return NextInt32SequenceEnumerable(rnd, minInclusive, maxExclusive);
 93     }
 94 
 95     static IEnumerable<int> NextInt32SequenceEnumerable(System.Random rnd, int minInclusive, int maxExclusive)
 96     {
 97         while (true)
 98         {
 99             yield return rnd.Next(minInclusive, maxExclusive);
100         }
101     }
102 
103     /// <summary>返回Int64类型的非负随机数</summary>
104     /// <param name="rnd">Random类型的随机数生成器</param>
105     /// <returns>
106     /// A 64-bit signed integer greater than or equal to 0, and less than <see cref="Int64.MaxValue"/>; that is, 
107     /// the range of return values includes 0 but not <see cref="Int64.MaxValue"/>.
108     /// </returns>
109     /// <seealso cref="NextFullRangeInt64"/>
110     public static long NextInt64(this System.Random rnd)
111     {
112         var buffer = new byte[sizeof (long)];
113 
114         rnd.NextBytes(buffer);
115         var candidate = BitConverter.ToInt64(buffer, 0);
116 
117         candidate &= long.MaxValue;
118         return (candidate == long.MaxValue) ? rnd.NextInt64() : candidate;
119     }
120 
121     /// <summary>
122     /// Returns a random number of the full Int32 range.
123     /// </summary>
124     /// <param name="rnd">The random number generator.</param>
125     /// <returns>
126     /// A 32-bit signed integer of the full range, including 0, negative numbers,
127     /// <see cref="Int32.MaxValue"/> and <see cref="Int32.MinValue"/>.
128     /// </returns>
129     /// <seealso cref="System.Random.Next()"/>
130     public static int NextFullRangeInt32(this System.Random rnd)
131     {
132         var buffer = new byte[sizeof (int)];
133         rnd.NextBytes(buffer);
134         return BitConverter.ToInt32(buffer, 0);
135     }
136 
137     /// <summary>
138     /// Returns a random number of the full Int64 range.
139     /// </summary>
140     /// <param name="rnd">The random number generator.</param>
141     /// <returns>
142     /// A 64-bit signed integer of the full range, including 0, negative numbers,
143     /// <see cref="Int64.MaxValue"/> and <see cref="Int64.MinValue"/>.
144     /// </returns>
145     /// <seealso cref="NextInt64"/>
146     public static long NextFullRangeInt64(this System.Random rnd)
147     {
148         var buffer = new byte[sizeof (long)];
149         rnd.NextBytes(buffer);
150         return BitConverter.ToInt64(buffer, 0);
151     }
152 
153     /// <summary>
154     /// Returns a nonnegative decimal floating point random number less than 1.0.
155     /// </summary>
156     /// <param name="rnd">The random number generator.</param>
157     /// <returns>
158     /// A decimal floating point number greater than or equal to 0.0, and less than 1.0; that is, 
159     /// the range of return values includes 0.0 but not 1.0.
160     /// </returns>
161     public static decimal NextDecimal(this System.Random rnd)
162     {
163         decimal candidate;
164 
165         // 50.049 % chance that the number is below 1.0. Try until we have one.
166         // Guarantees that any decimal in the interval can
167         // indeed be reached, with uniform probability.
168         do
169         {
170             candidate = new decimal(
171                 rnd.NextFullRangeInt32(),
172                 rnd.NextFullRangeInt32(),
173                 rnd.NextFullRangeInt32(),
174                 false,
175                 28);
176         }
177         while (candidate >= 1.0m);
178 
179         return candidate;
180     }
181 }

  其使用非常简单,这里就不再举例子。这种扩展大家也应该写过,后面几篇文章将介绍Math.NET中实现的其他算法的随机数发生器。请关注

3.资源

  源码下载:http://www.cnblogs.com/asxinyu/p/4264638.html

  如果本文显示有问题,请参考本文原文http://www.cnblogs.com/asxinyu/p/4301544.html

.NET数据挖掘与机器学习,作者博客: http://www.cnblogs.com/asxinyu

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posted @ 2015-03-17 08:21  数据之巅  阅读(3479)  评论(0编辑  收藏  举报