distributed.randn - Create distributed array of normally distributed random values
Syntax
RN = distributed.randn(n)
RN = distributed.randn(m, n, ...)
RN
= distributed.randn([m, n, ...])
RN = distributed.randn(..., classname)
Description
RN = distributed.randn(n) creates an n-by-n
distributed array of normally distributed random values with underlying
class double.
RN = distributed.randn(m, n, ...) and RN
= distributed.randn([m, n, ...]) create an m-by-n-by-...
distributed array of normally distributed random values.
RN = distributed.randn(..., classname) specifies
the class of the distributed array D. Valid choices
are the same as for the regular randn function: 'double' (the
default), 'single', 'int8', 'uint8', 'int16', 'uint16', 'int32', 'uint32', 'int64',
and 'uint64'.
Remarks
When you use randn on the workers in the
MATLAB pool, or in a distributed or parallel job (including pmode),
each worker or lab sets its random generator seed to a value that
depends only on the lab index or task ID. Therefore, the array on
each lab is unique for that job. However, if you repeat the job, you
get the same random data.
Examples
Create a 1000-by-1000 distributed matrix of normally distributed
random values of class double:
RN = distributed.randn(1000);
See Also
randn MATLAB function
reference page
codistributed.randn, distributed.rand, distributed.speye, distributed.sprand, distributed.sprandn
 | distributed.rand | | distributed.spalloc |  |
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