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Random.Next Method

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Returns a nonnegative random number.

Namespace:  System
Assembly:  mscorlib (in mscorlib.dll)

Syntax

'Declaration
Public Overridable Function Next As Integer
public virtual int Next()

Return Value

Type: System.Int32
A 32-bit signed integer greater than or equal to zero and less than MaxValue.

Remarks

Random.Next generates a random number whose value ranges from zero to less than Int32.MaxValue. To generate a random number whose value ranges from zero to some other positive number, use the Random.Next(Int32) method overload. To generate a random number within a different range, use the Random.Next(Int32, Int32) method overload.

Notes to Inheritors

If you derive a class from Random and override the Sample method, the distribution provided by the derived class implementation of the Sample method is not used in calls to the base class implementation of the Random.Next method. Instead, the uniform distribution returned by the base Random class is used. This behavior improves the overall performance of the Random class. To modify this behavior to call the Sample method in the derived class, you must also override the Random.Next method.

Examples

The following code example generates random integers with various overloads of the Next method.

' Example of the Random.Next( ) methods.

Module Example

   ' Generate random numbers with no bounds specified.
   Sub NoBoundsRandoms(ByVal outputBlock As System.Windows.Controls.TextBlock, ByVal seed As Integer)

      outputBlock.Text &= String.Format(vbCrLf & _
          "Random object, seed = {0}, no bounds:", seed) & vbCrLf
      Dim randObj As New Random(seed)

      ' Generate six random integers from 0 to int.MaxValue.
      Dim j As Integer
      For j = 0 To 5
         outputBlock.Text &= String.Format("{0,11} ", randObj.Next())
      Next j
      outputBlock.Text &= vbCrLf
   End Sub

   ' Generate random numbers with an upper bound specified.
   Sub UpperBoundRandoms(ByVal outputBlock As System.Windows.Controls.TextBlock, ByVal seed As Integer, ByVal upper As Integer)

      outputBlock.Text &= String.Format(vbCrLf & _
          "Random object, seed = {0}, upper bound = {1}:", _
          seed, upper) & vbCrLf
      Dim randObj As New Random(seed)

      ' Generate six random integers from 0 to the upper bound.
      Dim j As Integer
      For j = 0 To 5
         outputBlock.Text &= String.Format("{0,11} ", randObj.Next(upper))
      Next j
      outputBlock.Text &= vbCrLf
   End Sub

   ' Generate random numbers with both bounds specified.
   Sub BothBoundsRandoms(ByVal outputBlock As System.Windows.Controls.TextBlock, _
       ByVal seed As Integer, ByVal lower As Integer, ByVal upper As Integer)

      outputBlock.Text &= String.Format(vbCrLf & _
          "Random object, seed = {0}, lower = {1}, " & _
          "upper = {2}:", seed, lower, upper) & vbCrLf
      Dim randObj As New Random(seed)

      ' Generate six random integers from the lower to 
      ' upper bounds.
      Dim j As Integer
      For j = 0 To 5
         outputBlock.Text &= String.Format("{0,11} ", _
             randObj.Next(lower, upper))
      Next j
      outputBlock.Text &= vbCrLf
   End Sub

   Public Sub Demo(ByVal outputBlock As System.Windows.Controls.TextBlock)
      outputBlock.Text &= String.Format( _
          "This example of the Random.Next( ) methods" & _
          vbCrLf & "generates the following output." & vbCrLf) & vbCrLf
      outputBlock.Text &= String.Format( _
          "Create Random objects all with the same seed " & _
          "and generate" & vbCrLf & "sequences of numbers " & _
          "with different bounds. Note the effect " & vbCrLf & _
          "that the various combinations " & _
          "of bounds have on the sequences.") & vbCrLf

      NoBoundsRandoms(outputBlock, 234)

      UpperBoundRandoms(outputBlock, 234, Int32.MaxValue)
      UpperBoundRandoms(outputBlock, 234, 2000000000)
      UpperBoundRandoms(outputBlock, 234, 200000000)

      BothBoundsRandoms(outputBlock, 234, 0, Int32.MaxValue)
      BothBoundsRandoms(outputBlock, 234, Int32.MinValue, Int32.MaxValue)
      BothBoundsRandoms(outputBlock, 234, -2000000000, 2000000000)
      BothBoundsRandoms(outputBlock, 234, -200000000, 200000000)
      BothBoundsRandoms(outputBlock, 234, -2000, 2000)
   End Sub
End Module

' This example of the Random.Next( ) methods
' generates the following output.
' 
' Create Random objects all with the same seed and generate
' sequences of numbers with different bounds. Note the effect
' that the various combinations of bounds have on the sequences.
' 
' Random object, seed = 234, no bounds:
'  2091148258  1024955023   711273344  1081917183  1833298756   109460588
' 
' Random object, seed = 234, upper bound = 2147483647:
'  2091148258  1024955023   711273344  1081917183  1833298756   109460588
' 
' Random object, seed = 234, upper bound = 2000000000:
'  1947533580   954563751   662424922  1007613896  1707392518   101943116
' 
' Random object, seed = 234, upper bound = 200000000:
'   194753358    95456375    66242492   100761389   170739251    10194311
' 
' Random object, seed = 234, lower = 0, upper = 2147483647:
'  2091148258  1024955023   711273344  1081917183  1833298756   109460588
' 
' Random object, seed = 234, lower = -2147483648, upper = 2147483647:
'  2034812868   -97573602  -724936960    16350718  1519113864 -1928562472
' 
' Random object, seed = 234, lower = -2000000000, upper = 2000000000:
'  1895067160   -90872498  -675150156    15227793  1414785036 -1796113767
' 
' Random object, seed = 234, lower = -200000000, upper = 200000000:
'   189506716    -9087250   -67515016     1522779   141478503  -179611377
' 
' Random object, seed = 234, lower = -2000, upper = 2000:
'        1895         -91        -676          15        1414       -1797
// Example of the Random.Next( ) methods.
using System;

public class Example
{
   // Generate random numbers with no bounds specified.
   static void NoBoundsRandoms(System.Windows.Controls.TextBlock outputBlock, int seed)
   {
      outputBlock.Text += String.Format(
          "\nRandom object, seed = {0}, no bounds:", seed) + "\n";
      Random randObj = new Random(seed);

      // Generate six random integers from 0 to int.MaxValue.
      for (int j = 0; j < 6; j++)
         outputBlock.Text += String.Format("{0,11} ", randObj.Next());
      outputBlock.Text += "\n";
   }

   // Generate random numbers with an upper bound specified.
   static void UpperBoundRandoms(System.Windows.Controls.TextBlock outputBlock, int seed, int upper)
   {
      outputBlock.Text += String.Format(
          "\nRandom object, seed = {0}, upper bound = {1}:",
          seed, upper) + "\n";
      Random randObj = new Random(seed);

      // Generate six random integers from 0 to the upper bound.
      for (int j = 0; j < 6; j++)
         outputBlock.Text += String.Format("{0,11} ", randObj.Next(upper));
      outputBlock.Text += "\n";
   }

   // Generate random numbers with both bounds specified.
   static void BothBoundsRandoms(System.Windows.Controls.TextBlock outputBlock, int seed, int lower, int upper)
   {
      outputBlock.Text += String.Format(
          "\nRandom object, seed = {0}, lower = {1}, " +
          "upper = {2}:", seed, lower, upper) + "\n";
      Random randObj = new Random(seed);

      // Generate six random integers from the lower to 
      // upper bounds.
      for (int j = 0; j < 6; j++)
         outputBlock.Text += String.Format("{0,11} ",
             randObj.Next(lower, upper));
      outputBlock.Text += "\n";
   }

   public static void Demo(System.Windows.Controls.TextBlock outputBlock)
   {
      outputBlock.Text += String.Format(
          "This example of the Random.Next( ) methods\n" +
          "generates the following output.\n") + "\n";
      outputBlock.Text += String.Format(
          "Create Random objects all with the same seed and " +
          "generate\nsequences of numbers with different " +
          "bounds. Note the effect\nthat the various " +
          "combinations of bounds have on the sequences.") + "\n";

      NoBoundsRandoms(outputBlock, 234);

      UpperBoundRandoms(outputBlock, 234, Int32.MaxValue);
      UpperBoundRandoms(outputBlock, 234, 2000000000);
      UpperBoundRandoms(outputBlock, 234, 200000000);

      BothBoundsRandoms(outputBlock, 234, 0, Int32.MaxValue);
      BothBoundsRandoms(outputBlock, 234, Int32.MinValue, Int32.MaxValue);
      BothBoundsRandoms(outputBlock, 234, -2000000000, 2000000000);
      BothBoundsRandoms(outputBlock, 234, -200000000, 200000000);
      BothBoundsRandoms(outputBlock, 234, -2000, 2000);
   }
}

/*
This example of the Random.Next( ) methods
generates the following output.

Create Random objects all with the same seed and generate
sequences of numbers with different bounds. Note the effect
that the various combinations of bounds have on the sequences.

Random object, seed = 234, no bounds:
 2091148258  1024955023   711273344  1081917183  1833298756   109460588

Random object, seed = 234, upper bound = 2147483647:
 2091148258  1024955023   711273344  1081917183  1833298756   109460588

Random object, seed = 234, upper bound = 2000000000:
 1947533580   954563751   662424922  1007613896  1707392518   101943116

Random object, seed = 234, upper bound = 200000000:
  194753358    95456375    66242492   100761389   170739251    10194311

Random object, seed = 234, lower = 0, upper = 2147483647:
 2091148258  1024955023   711273344  1081917183  1833298756   109460588

Random object, seed = 234, lower = -2147483648, upper = 2147483647:
 2034812868   -97573602  -724936960    16350718  1519113864 -1928562472

Random object, seed = 234, lower = -2000000000, upper = 2000000000:
 1895067160   -90872498  -675150156    15227793  1414785036 -1796113767

Random object, seed = 234, lower = -200000000, upper = 200000000:
  189506716    -9087250   -67515016     1522779   141478503  -179611377

Random object, seed = 234, lower = -2000, upper = 2000:
       1895         -91        -676          15        1414       -1797
*/

The following code example derives a class from Random to generate a sequence of random numbers whose distribution differs from the uniform distribution generated by the Sample method of the base class. It overrides the Sample method to provide the distribution of random numbers, and overrides the Random.Next method to use series of random numbers.

' This derived class converts the uniformly distributed random 
' numbers generated by base.Sample( ) to another distribution.
Public Class RandomProportional
   Inherits Random

   ' The Sample method generates a distribution proportional to the value 
   ' of the random numbers, in the range [0.0, 1.0].
   Protected Overrides Function Sample() As Double
      Return Math.Sqrt(MyBase.Sample())
   End Function

   Public Overrides Function [Next]() As Integer
      Return Sample() * Integer.MaxValue
   End Function
End Class

Module Example
   Public Sub Demo(ByVal outputBlock As System.Windows.Controls.TextBlock)
      Const rows As Integer = 4, cols As Integer = 6
      Const runCount As Integer = 1000000
      Const distGroupCount As Integer = 10
      Const intGroupSize As Double = _
          (CDbl(Integer.MaxValue) + 1.0) / _
          CDbl(distGroupCount)

      Dim randObj As New RandomProportional()

      Dim intCounts(distGroupCount) As Integer
      Dim realCounts(distGroupCount) As Integer
      Dim i As Integer, j As Integer

      outputBlock.Text &= vbCrLf & _
          "The derived RandomProportional class overrides " & _
          "the Sample method to " & vbCrLf & _
          "generate random numbers in the range " & _
          "[0.0, 1.0]. The distribution " & vbCrLf & _
          "of the numbers is proportional to their numeric " & _
          "values. For example, " & vbCrLf & _
          "numbers are generated in the vicinity of 0.75 " & _
          "with three times " & vbCrLf & "the " & _
          "probability of those generated near 0.25." & vbCrLf
      outputBlock.Text &= vbCrLf & _
          "Random doubles generated with the NextDouble( ) " & _
          "method:" & vbCrLf & vbCrLf

      ' Generate and display [rows * cols] random doubles.
      For i = 0 To rows - 1
         For j = 0 To cols - 1
            outputBlock.Text &= String.Format("{0,12:F8}", randObj.NextDouble())
         Next j
         outputBlock.Text &= vbCrLf
      Next i

      outputBlock.Text &= vbCrLf & _
          "Random integers generated with the Next( ) " & _
          "method:" & vbCrLf & vbCrLf

      ' Generate and display [rows * cols] random integers.
      For i = 0 To rows - 1
         For j = 0 To cols - 1
            outputBlock.Text &= String.Format("{0,12}", randObj.Next())
         Next j
         outputBlock.Text &= vbCrLf
      Next i

      outputBlock.Text &= String.Format(vbCrLf & _
          "To demonstrate the proportional distribution, " & _
          "{0:N0} random " & vbCrLf & _
          "integers and doubles are grouped into {1} " & _
          "equal value ranges. This " & vbCrLf & _
          "is the count of values in each range:" & vbCrLf, _
          runCount, distGroupCount) & vbCrLf
      outputBlock.Text &= String.Format("{0,21}{1,10}{2,20}{3,10}", _
          "Integer Range", "Count", "Double Range", "Count") & vbCrLf
      outputBlock.Text &= String.Format("{0,21}{1,10}{2,20}{3,10}", _
          "-------------", "-----", "------------", "-----") & vbCrLf

      ' Generate random integers and doubles, and then count 
      ' them by group.
      For i = 0 To runCount - 1
         intCounts(Fix(CDbl(randObj.Next()) / _
             intGroupSize)) += 1
         realCounts(Fix(randObj.NextDouble() * _
             CDbl(distGroupCount))) += 1
      Next i

      ' Display the count of each group.
      For i = 0 To distGroupCount - 1
         outputBlock.Text &= String.Format( _
             "{0,10}-{1,10}{2,10:N0}{3,12:N5}-{4,7:N5}{5,10:N0}", _
             Fix(CDbl(i) * intGroupSize), _
             Fix(CDbl(i + 1) * intGroupSize - 1.0), _
             intCounts(i), _
             CDbl(i) / CDbl(distGroupCount), _
             CDbl(i + 1) / CDbl(distGroupCount), _
             realCounts(i)) & vbCrLf
      Next i
   End Sub
End Module
' This example of Random.Sample() generates 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 their numeric 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:
'    
'      0.28377004  0.75920598  0.33430371  0.66720626  0.97080243  0.27353772
'      0.17787962  0.54618410  0.08145080  0.56286100  0.99002910  0.64898614
'      0.27673277  0.99455281  0.93778966  0.76162002  0.70533771  0.44375798
'      0.55939883  0.87383136  0.66465779  0.77392566  0.42393411  0.82409159
'    
'    Random integers generated with the Next( ) method:
'    
'      1364479914  1230312341  1657373812  1526222928   988564704   700078020
'      1801013705  1541517421  1146312560   338318389  1558995993  2027260859
'       884520932  1320070465   570200106  1027684711   943035246  2088689333
'       630809089  1705728475  2140787648  2097858166  1863010875  1386804198
'    
'    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     9,892     0.00000-0.10000     9,928
'     214748364- 429496728    30,341     0.10000-0.20000    30,101
'     429496729- 644245093    49,958     0.20000-0.30000    49,964
'     644245094- 858993458    70,099     0.30000-0.40000    70,213
'     858993459-1073741823    90,801     0.40000-0.50000    89,553
'    1073741824-1288490187   109,699     0.50000-0.60000   109,427
'    1288490188-1503238552   129,438     0.60000-0.70000   130,339
'    1503238553-1717986917   149,886     0.70000-0.80000   150,000
'    1717986918-1932735282   170,338     0.80000-0.90000   170,128
'    1932735283-2147483647   189,548     0.90000-1.00000   190,347
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 Example
{
   public static void Demo(System.Windows.Controls.TextBlock outputBlock)
   {
      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];

      outputBlock.Text +=
          "\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." + "\n";
      outputBlock.Text +=
          "\nRandom doubles generated with the NextDouble( ) " +
          "method:\n" + "\n";

      // Generate and display [rows * cols] random doubles.
      for (int i = 0; i < rows; i++)
      {
         for (int j = 0; j < cols; j++)
            outputBlock.Text += String.Format("{0,12:F8}", randObj.NextDouble());
         outputBlock.Text += "\n";
      }

      outputBlock.Text +=
          "\nRandom integers generated with the Next( ) " +
          "method:\n" + "\n";

      // Generate and display [rows * cols] random integers.
      for (int i = 0; i < rows; i++)
      {
         for (int j = 0; j < cols; j++)
            outputBlock.Text += String.Format("{0,12}", randObj.Next());
         outputBlock.Text += "\n";
      }

      outputBlock.Text += String.Format(
          "\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) + "\n";
      outputBlock.Text += String.Format(
          "{0,21}{1,10}{2,20}{3,10}", "Integer Range",
          "Count", "Double Range", "Count") + "\n";
      outputBlock.Text += String.Format(
          "{0,21}{1,10}{2,20}{3,10}", "-------------",
          "-----", "------------", "-----") + "\n";

      // 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++)
         outputBlock.Text += String.Format(
             "{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]) + "\n";
   }
}

/*
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
*/

Version Information

Silverlight

Supported in: 5, 4, 3

Silverlight for Windows Phone

Supported in: Windows Phone OS 7.1, Windows Phone OS 7.0

XNA Framework

Supported in: Xbox 360, Windows Phone OS 7.0

Platforms

For a list of the operating systems and browsers that are supported by Silverlight, see Supported Operating Systems and Browsers.