System.Random.Next 方法
方法描述
返回非负随机数。
语法定义(C# System.Random.Next 方法 的用法)
public virtual int Next()
参数/返回值
| 参数值/返回值 | 参数类型/返回类型 | 参数描述/返回描述 |
|---|---|---|
| 返回值 | System.Int32 | 大于等于零且小于 MaxValue 的 32 位带符号整数。 |
提示和注释
Random.Next 生成一个值范围在零与 Int32.MaxValue 之间的随机数。 若要生成值范围在零与其他某个正数之间的随机数，请使用 Random.Next(Int32) 方法重载。 若要生成在不同范围内的随机数，请使用 Random.Next(Int32, Int32) 方法重载。
对继承者的说明
从 .NET Framework 2.0 版开始，如果您从 Random 派生类并重写 Sample 方法，则在调用 Random.Next 方法的基类实现时将不使用由 Sample 方法的派生类实现提供的分布。 而是使用由 Random 基类返回的统一分布。 此行为提高了 Random 类的总体性能。 若要修改此行为以在派生类中调用 Sample 方法，还必须重写 Random.Next 方法。
System.Random.Next 方法例子
该示例通过重写 Sample 方法来提供随机数的分布，并通过重写 Random.Next 方法来使用随机数序列。
using System;
// This derived class converts the uniformly distributed random
// numbers generated by base.Sample( ) to another distribution.
public class RandomProportional : Random
{
// The Sample method generates a distribution proportional to the value
// of the random numbers, in the range [0.0, 1.0].
protected override double Sample( )
{
return Math.Sqrt( base.Sample( ) );
}
public override int Next()
{
return (int) (Sample() * int.MaxValue);
}
}
public class RandomSampleDemo
{
static void Main( )
{
const int rows = 4, cols = 6;
const int runCount = 1000000;
const int distGroupCount = 10;
const double intGroupSize =
( (double)int.MaxValue + 1.0 ) / (double)distGroupCount;
RandomProportional randObj = new RandomProportional( );
int[ ] intCounts = new int[ distGroupCount ];
int[ ] realCounts = new int[ distGroupCount ];
Console.WriteLine(
"\nThe derived RandomProportional class overrides " +
"the Sample method to \ngenerate random numbers " +
"in the range [0.0, 1.0]. The distribution \nof " +
"the numbers is proportional to their numeric values. " +
"For example, \nnumbers are generated in the " +
"vicinity of 0.75 with three times the \n" +
"probability of those generated near 0.25." );
Console.WriteLine(
"\nRandom doubles generated with the NextDouble( ) " +
"method:\n" );
// Generate and display [rows * cols] random doubles.
for( int i = 0; i < rows; i++ )
{
for( int j = 0; j < cols; j++ )
Console.Write( "{0,12:F8}", randObj.NextDouble( ) );
Console.WriteLine( );
}
Console.WriteLine(
"\nRandom integers generated with the Next( ) " +
"method:\n" );
// Generate and display [rows * cols] random integers.
for( int i = 0; i < rows; i++ )
{
for( int j = 0; j < cols; j++ )
Console.Write( "{0,12}", randObj.Next( ) );
Console.WriteLine( );
}
Console.WriteLine(
"\nTo demonstrate the proportional distribution, " +
"{0:N0} random \nintegers and doubles are grouped " +
"into {1} equal value ranges. This \n" +
"is the count of values in each range:\n",
runCount, distGroupCount );
Console.WriteLine(
"{0,21}{1,10}{2,20}{3,10}", "Integer Range",
"Count", "Double Range", "Count" );
Console.WriteLine(
"{0,21}{1,10}{2,20}{3,10}", "-------------",
"-----", "------------", "-----" );
// Generate random integers and doubles, and then count
// them by group.
for( int i = 0; i < runCount; i++ )
{
intCounts[ (int)( (double)randObj.Next( ) /
intGroupSize ) ]++;
realCounts[ (int)( randObj.NextDouble( ) *
(double)distGroupCount ) ]++;
}
// Display the count of each group.
for( int i = 0; i < distGroupCount; i++ )
Console.WriteLine(
"{0,10}-{1,10}{2,10:N0}{3,12:N5}-{4,7:N5}{5,10:N0}",
(int)( (double)i * intGroupSize ),
(int)( (double)( i + 1 ) * intGroupSize - 1.0 ),
intCounts[ i ],
( (double)i ) / (double)distGroupCount,
( (double)( i + 1 ) ) / (double)distGroupCount,
realCounts[ i ] );
}
}
/*
This example of Random.Sample() displays the following output:
The derived RandomProportional class overrides the Sample method to
generate random numbers in the range [0.0, 1.0). The distribution
of the numbers is proportional to the number values. For example,
numbers are generated in the vicinity of 0.75 with three times the
probability of those generated near 0.25.
Random doubles generated with the NextDouble( ) method:
0.59455719 0.17589882 0.83134398 0.35795862 0.91467727 0.54022658
0.93716947 0.54817519 0.94685080 0.93705478 0.18582318 0.71272428
0.77708682 0.95386216 0.70412393 0.86099417 0.08275804 0.79108316
0.71019941 0.84205103 0.41685082 0.58186880 0.89492302 0.73067715
Random integers generated with the Next( ) method:
1570755704 1279192549 1747627711 1705700211 1372759203 1849655615
2046235980 1210843924 1554274149 1307936697 1480207570 1057595022
337854215 844109928 2028310798 1386669369 2073517658 1291729809
1537248240 1454198019 1934863511 1640004334 2032620207 534654791
To demonstrate the proportional distribution, 1,000,000 random
integers and doubles are grouped into 10 equal value ranges. This
is the count of values in each range:
Integer Range Count Double Range Count
------------- ----- ------------ -----
0- 214748363 10,079 0.00000-0.10000 10,148
214748364- 429496728 29,835 0.10000-0.20000 29,849
429496729- 644245093 49,753 0.20000-0.30000 49,948
644245094- 858993458 70,325 0.30000-0.40000 69,656
858993459-1073741823 89,906 0.40000-0.50000 90,337
1073741824-1288490187 109,868 0.50000-0.60000 110,225
1288490188-1503238552 130,388 0.60000-0.70000 129,986
1503238553-1717986917 149,231 0.70000-0.80000 150,428
1717986918-1932735282 170,234 0.80000-0.90000 169,610
1932735283-2147483647 190,381 0.90000-1.00000 189,813
*/
版本信息
.NET Framework 受以下版本支持：4、3.5、3.0、2.0、1.1、1.0 .NET Framework Client Profile 受以下版本支持：4、3.5 SP1 受以下版本支持：
适用平台
Windows 7, Windows Vista SP1 或更高版本, Windows XP SP3, Windows XP SP2 x64 Edition, Windows Server 2008（不支持服务器核心）, Windows Server 2008 R2（支持 SP1 或更高版本的服务器核心）, Windows Server 2003 SP2 .NET Framework 并不是对每个平台的所有版本都提供支持。有关支持的版本的列表，请参见.NET Framework 系统要求。