randi - Uniformly distributed random integers - MATLAB (original) (raw)

Uniformly distributed random integers

Syntax

Description

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi([imax](#buf2csg-imax)) returns a random scalar integer between 1 andimax.

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi([imax](#buf2csg-imax),[n](#buf2csg-n)) returns an n-by-n matrix of random integers drawn from the discrete uniform distribution on the interval [1,imax].

example

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi([imax](#buf2csg-imax),[sz1,...,szN](#buf2csg-sz1szN)) returns an sz1-by-...-by-szN array wheresz1,...,szN indicate the size of each dimension. For example, randi(10,3,4) returns a 3-by-4 array of random integers between 1 and 10.

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi([imax](#buf2csg-imax),[sz](#buf2csg-sz)) returns an array where size vector sz definessize(X). For example, randi(10,[3 4]) returns a 3-by-4 array of random integers between 1 and 10.

example

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi(___,[typename](#buf2csg-classname)) returns an array of random integers between 1 andimax of data type typename. Thetypename input can be "single","double", "int8","uint8", "int16","uint16", "int32","uint32", or "logical". You can use any of the input arguments in the previous syntaxes.

example

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi(___,like=[p](#buf2csg-p)) returns an array of random integers like p; that is, with the same data type and complexity (real or complex) as p. You can specify either typename or like, but not both.

example

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi([[imin](#buf2csg-imin),[imax](#buf2csg-imax)],___) returns an array containing integers drawn from the discrete uniform distribution on the interval [imin,imax], using any of the above syntaxes.

example

[X](#mw%5F96306de0-b3bd-435e-9b1b-e119130506e7) = randi([s](#mw%5F3f3e135a-0842-44f9-989f-5004615a9bb7),___) generates integers from random number stream s instead of the default global stream. To create a stream, use RandStream. You can specify s followed by any of the input argument combinations in previous syntaxes.

Examples

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Generate a 5-by-5 matrix of random integers between 1 and 10. The first input to randi indicates the largest integer in the sampling interval (the smallest integer in the interval is 1).

r = 5×5

 9     1     2     2     7
10     3    10     5     1
 2     6    10    10     9
10    10     5     8    10
 7    10     9    10     7

Generate a 10-by-1 column vector of uniformly distributed random integers from the sample interval [-5,5].

r = 10×1

 3
 4
-4
 5
 1
-4
-2
 1
 5
 5

Save the current state of the random number generator and create a 1-by-5 vector of random integers.

s = rng; r = randi(10,1,5)

Restore the state of the random number generator to s, and then create a new 1-by-5 vector of random integers. The values are the same as before.

rng(s); r1 = randi(10,1,5)

Create a 3-by-2-by-3 array of uniformly distributed random integers between 1 and 500.

X = X(:,:,1) =

408 457 453 317 64 49

X(:,:,2) =

140 483 274 79 479 486

X(:,:,3) =

479 71 243 211 401 458

Create a 1-by-4 vector of random numbers between 1 and 100 whose elements are of type int16.

r = randi(100,1,4,"int16")

r = 1×4 int16 row vector

82 91 13 92

Create a matrix of uniformly distributed random integers between 1 and 10 with the same size as an existing array.

A = [3 2; -2 1]; sz = size(A); X = randi(10,sz)

It is a common pattern to combine the previous two lines of code into a single line:

Create a 2-by-2 matrix of 8-bit signed integers.

Create an array of random integers that is the same size and data type as p.

X = randi(10,size(p),like=p)

X = 2×2 int8 matrix

9    2

10 10

Since R2022a

Generate 10 random complex integers from the discrete uniform distribution over a square domain with real and imaginary parts in the interval [-5,5].

a = randi([-5,5],10,1,like=1i)

a = 10×1 complex

3.0000 + 4.0000i -4.0000 + 5.0000i 1.0000 - 4.0000i -2.0000 + 1.0000i 5.0000 + 5.0000i -4.0000 + 5.0000i 5.0000 + 0.0000i 3.0000 - 4.0000i -1.0000 + 5.0000i 3.0000 + 5.0000i

Since R2023a

Create a 5-by-5 matrix of random logical values (0s and 1s) with a discrete uniform distribution.

r = randi([0 1],5,"logical")

r = 5×5 logical array

1 0 0 0 1 1 0 1 0 0 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1

Input Arguments

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Largest integer in sample interval, specified as a positive integer.randi draws values from the uniform distribution in the sample interval [1,imax].

Example: randi(10,5)

Smallest integer in sample interval, specified as a scalar integer.

Both imin and imax must be integers that satisfy imin ≤ imax.

For example, randi([50,100],5) returns a 5-by-5 matrix of random integers between (and including) 50 and 100.

Size of square matrix, specified as an integer value.

• If n is 0, thenX is an empty matrix.
• If n is negative, then it is treated as0.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Size of each dimension, specified as separate arguments of integer values.

• If the size of any dimension is 0, thenX is an empty array.
• If the size of any dimension is negative, then it is treated as0.
• Beyond the second dimension, randi ignores trailing dimensions with a size of 1. For example,randi([5,10],3,1,1,1) produces a 3-by-1 vector of random integers between 5 and 10.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Size of each dimension, specified as a row vector of integer values. Each element of this vector indicates the size of the corresponding dimension:

• If the size of any dimension is 0, thenX is an empty array.
• If the size of any dimension is negative, then it is treated as0.
• Beyond the second dimension, randi ignores trailing dimensions with a size of 1. For example,randi([5,10],[3 1 1 1]) produces a 3-by-1 vector of random integers between 5 and 10.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Data type (class) to create, specified as "double","single", "int8","uint8", "int16","uint16", "int32","uint32", "logical", or the name of another class that provides randi support.

Example: randi(5,5,"int8")

Prototype of array to create, specified as a numeric or logical array.

Example: randi(5,5,like=p)

Data Types: single | double | int8 | int16 | int32 | uint8 | uint16 | uint32 | logical
Complex Number Support: Yes

Random number stream, specified as a RandStream object.

Example: s = RandStream("dsfmt19937"); randi(s,[5,10],[3 1])

Output Arguments

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Output array, returned as a scalar, vector, matrix, or multidimensional array.

More About

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The underlying number generator for randi is a pseudorandom number generator, which creates a deterministic sequence of numbers that appear random. These numbers are predictable if the seed and the deterministic algorithm of the generator are known. While not truly random, the generated numbers pass various statistical tests of randomness, satisfying the independent and identically distributed (i.i.d.) condition, and justifying the name pseudorandom.

Tips

• The sequence of numbers produced by randi is determined by the internal settings of the uniform pseudorandom number generator that underlies rand,randi, and randn. You can control that shared random number generator using rng.
• The arrays returned by randi can contain repeated integer values. This behavior is sometimes referred to as sampling with replacement. Userandperm if you require all unique values.
• If imin and imax are outside the range of the output type (as specified by typename or by the prototype p), then randi first creates random integers within the interval [imin,imax] and converts any resulting out-of-range integers to the minimum or maximum value of the output type. For example:
  rng default;
  r = randi([-10 10],1,10)
  r =
  7 9 -8 9 3 -8 -5 1 10 10
  rng default;
  r = randi([-10 10],1,10,"logical")
  r =
  1×10 logical array
  1 1 0 1 1 0 0 1 1 1

Extended Capabilities

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Usage notes and limitations:

• If used, the input argument typename must be"double","single","int8", "uint8","int16", "uint16","int32", "uint32", or"logical". Other classes are not supported, even if the class defines a static randi method.
• If used, size arguments n, sz, and sz1,...,szN must be fixed size.
• The code generator uses double-precision math to compute single-precision outputs.
• In most cases, generated MEX files use the same random number state as MATLAB®. If you disable extrinsic calls or you callrandi from inside aparfor-loop, the generated MEX code and standalone code maintain their own random number state that is initialized to the MATLAB default, which isrng(0,"twister").

The randi function supports GPU array input with these usage notes and limitations:

• You can specify typename as 'gpuArray'. If you specifytypename as 'gpuArray', the default underlying type of the array is double.
  To create a GPU array with underlying type datatype, specify the underlying type as an additional argument beforetypename. For example, X = randi(imax,3,datatype,'gpuArray') creates a 3-by-3 GPU array of random integers in the range [1 imax] with underlying type datatype.
  You can specify the underlying type datatype as one of these options:
  • 'double'
  • 'single'
  • 'logical'
  • 'int8'
  • 'uint8'
  • 'int16'
  • 'uint16'
  • 'int32'
  • 'uint32'
• You can also specify the numeric variable p as agpuArray.
  If you specify p as a gpuArray, the underlying type of the returned array is the same as p.
• To use the stream syntax,randi(`s`,___), on a GPU,s must be a parallel.gpu.RandStream (Parallel Computing Toolbox) object.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Usage notes and limitations:

• The stream syntax randi(`s`,___) is not supported for codistributed or distributed arrays.
• You can specify typename as 'codistributed' or'distributed'. If you specify typename as'codistributed' or 'distributed', the default underlying type of the returned array is double.
  To create a distributed or codistributed array with underlying typedatatype, specify the underlying type as an additional argument before typename. For example,X = randi(imax,3,datatype,'distributed') creates a 3-by-3 distributed matrix of random integers in the range [1 imax] with underlying type datatype.
  You can specify the underlying type datatype as one of these options:
  • 'double'
  • 'single'
  • 'int8'
  • 'uint8'
  • 'int16'
  • 'uint16'
  • 'int32'
  • 'uint32'
  • 'logical'
• You can also specify p as a codistributed or distributed array.
  If you specify p as a codistributed ordistributed array, the underlying type of the returned array is the same as p.
• For additional codistributed syntaxes, see randi (codistributed) (Parallel Computing Toolbox).

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced in R2008b

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You can create a random logical array by specifying typename as"logical" or the prototype p as a logical array. For example, see Random Logical Array.

The like name-value argument supports both real and complex prototype arrays. For example:

r =

2.0000 + 2.0000i 2.0000 + 1.0000i 1.0000 + 2.0000i 1.0000 + 2.0000i

All syntaxes support this feature. Also, you can now use like with a RandStream object as the first input ofrandi.

To generate random numbers with the same data type as an existing variable, use the syntax randi(__,'like',p). For example:

A = single(pi); r = randi(4,4,'like',A); class(r)

This feature is not available when passing aRandStream object as the first input torandi.

Specifying a dimension that is not an integer causes an error. Use floor to convert non-integer size inputs to integers.