Array of randn values
R = randn(sz,arraytype)
R = randn(sz,datatype,arraytype)
R = randn(sz,'like',P)
R = randn(sz,datatype,'like',P)
C = randn(sz,codist)
C
= rand(sz,datatype,codist)
C = randn(sz,___,codist,'noCommunication')
C = randn(sz,___,codist,'like',P)
R = randn(sz, creates
a matrix with underlying class of double, with arraytype)randn values in all elements.
R = randn(sz, creates
a matrix with underlying class of datatype,arraytype)datatype,
with randn values in all elements.
The size and type of array are specified by the argument options according to the following table.
| Argument | Values | Descriptions |
|---|---|---|
sz | n | Specifies size as an n-by-n matrix. |
m,n or [m n] | Specifies size as an m-by-n matrix. | |
m,n,...,k or [m
n ... k] | Specifies size as an m-by-n-by-...-by-k array. | |
arraytype | 'distributed' | Specifies distributed array. |
'codistributed' | Specifies codistributed array, using the default distribution scheme. | |
'gpuArray' | Specifies gpuArray. | |
datatype | 'double' (default), 'single' | Specifies underlying class of the array, i.e., the data type of its elements. |
R = randn(sz,'like',P) creates
an array of randn values with the same type and
underlying class (data type) as array P.
R = randn(sz, creates
an array of datatype,'like',P)randn values with the specified underlying
class (datatype), and the same type as
array P.
C = randn(sz,codist) or C
= rand(sz, creates
a codistributed array of datatype,codist)randn values with the
specified size and underlying class (the default datatype is 'double').
The codistributor object codist specifies the distribution
scheme for creating the codistributed array. For information on constructing
codistributor objects, see the reference pages for codistributor1d and codistributor2dbc. To use the default
distribution scheme, you can specify a codistributor constructor without
arguments. For example:
spmd
C = randn(8,codistributor1d());
endC = randn(sz,___,codist,'noCommunication') specifies
that no interworker communication is to be performed when constructing
a codistributed array, skipping some error checking steps.
C = randn(sz,___,codist,'like',P) creates
a codistributed array of randn values with the
specified size, underlying class, and distribution scheme. If either
the class or codistributor argument is omitted, the characteristic
is acquired from the codistributed array P.
Create a 1000-by-1000 distributed array of randn values
with underlying class double:
D = randn(1000,'distributed');
Create a 1000-by-1000 codistributed double matrix of randn values,
distributed by its second dimension (columns).
spmd(4) C = randn(1000,'codistributed'); end
With four workers, each worker contains a 1000-by-250 local
piece of C.
Create a 1000-by-1000 codistributed single matrix
of randn values, distributed by its columns.
spmd(4) codist = codistributor('1d',2,100*[1:numlabs]); C = randn(1000,1000,'single',codist); end
Each worker contains a 100-by-labindex local
piece of C.
Create a 1000-by-1000 gpuArray of randn values
with underlying class double:
G = randn(1000,'double','gpuArray');
codistributed.sprandn | distributed.sprandn | rand | randi | randn