Uniformly distributed random numbers - MATLAB rand (2024)

X = rand

X = rand(n)

X = rand(sz1,...,szN)

X = rand(sz)

X = rand(___,typename)

X = rand(___,"like",p)

X = rand(s,___)

• The data type (class) must be a built-in MATLAB^® numeric type. For other classes, the static rand method is not invoked. For example, rand(sz,'myclass') does not invoke myclass.rand(sz).

• Size arguments must have a fixed size.

• See Variable-Sizing Restrictions for Code Generation of Toolbox Functions (MATLAB Coder).

  • If extrinsic calls are enabled and rand is not called from inside a parfor loop, generated MEX files use the same random number state as MATLAB in serial code. Otherwise, the generated MEX code and standalone code maintain their own random number state that is initialized to the same state as MATLAB.

• The stream syntax rand(s,___) is not supported on a GPU.

• You can specify typename as 'gpuArray'. If you specify typename 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 before typename. For example, X = rand(3,datatype,'gpuArray') creates a 3-by-3 GPU array of random numbers with underlying type datatype.

  You can specify the underlying type datatype as one of these options:

  • 'double'

  • 'single'

• You can also specify the numeric variable p as a gpuArray.

  If you specify p as a gpuArray, the underlying type of the returned array is the same as p.

• The stream syntax rand(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 type datatype, specify the underlying type as an additional argument before typename. For example, X = rand(3,datatype,'distributed') creates a 3-by-3 distributed matrix of random numbers with underlying type datatype.

  You can specify the underlying type datatype as one of these options:

  • 'double'

  • 'single'

• You can also specify p as a codistributed or distributed array.

  If you specify p as a codistributed or distributed array, the underlying type of the returned array is the same as p.

• For additional codistributed syntaxes, see rand (codistributed) (Parallel Computing Toolbox).

The "like" input supports both real and complex prototype arrays. For example:

r = rand(2,2,"like",1i)

r = 0.8147 + 0.9058i 0.6324 + 0.0975i 0.1270 + 0.9134i 0.2785 + 0.5469i

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

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

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

ans = single

This feature is not available when passing a RandStream object as the first input to rand.

There are no plans to remove these inputs, which control the random number generator that underlies rand, randi and randn. However, the rng function is recommended instead for these reasons:

For information on updating your code, see Replace Discouraged Syntaxes of rand and randn.