distributed.sprand

Create distributed sparse array of uniformly distributed pseudo-random values

Syntax

DS = distributed.sprand(m,n,density)
DS = distributed.sprand(___,typename)

Description

DS = distributed.sprand(m,n,density) creates an m-by-n sparse distributed array with approximately density*m*n uniformly distributed nonzero double entries.

DS = distributed.sprand(___,typename) also specifies the data type (class) of the sparse distributed array. The typename input can be either "single" or "double". (since R2025a)

Examples

Create a 1000-by-1000 sparse distributed double array DS with approximately 1000 nonzeros. 

DS = distributed.sprand(1000,1000,0.001);

Create a random 500-by-1000 sparse distributed single-precision array with density 0.1.

DS = distributed.sprand(500,1000,0.1,"single");

Tips

When you use sprand on the workers in the parallel pool, or in an independent or communicating job, each worker sets its random generator seed to a value that depends only on the spmdIndex or task ID. Therefore, the array on each worker is unique for that job. However, if you repeat the job, you get the same random data.

Version History

Introduced in R2009b

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See Also

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