Array of rand values
R = rand(sz,
arraytype
)
R = rand(sz,datatype
,arraytype
)
R = rand(sz,'like',P)
R = rand(sz,datatype
,'like',P)
C = rand(sz,codist)
C
= rand(sz,datatype
,codist)
C = rand(sz,___,codist,'noCommunication')
C = rand(sz,___,codist,'like',P)
R = rand(sz,
creates a
matrix with underlying class of double, with arraytype
)rand
values in all elements.
R = rand(sz,
creates a matrix with underlying class of datatype
,arraytype
)datatype
, with
rand
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 = rand(sz,'like',P)
creates an array of
rand
values with the same type and underlying class (data
type) as array P
.
R = rand(sz,
creates an array of datatype
,'like',P)rand
values with the specified underlying
class (datatype
), and the same type as array
P
.
C = rand(sz,codist)
or
C
= rand(sz,
creates
a codistributed array of datatype
,codist)rand
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 = rand(8,codistributor1d()); end
C = rand(sz,___,codist,'noCommunication')
specifies that no interworker communication is to be performed when constructing a
codistributed array, skipping some error checking steps.
C = rand(sz,___,codist,'like',P)
creates a
codistributed array of rand
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 rand
s with
underlying class double:
D = rand(1000,'distributed');
Create a 1000-by-1000 codistributed double matrix of rand
s,
distributed by its second dimension (columns).
spmd(4) C = rand(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
rand
s, distributed by its columns.
spmd(4) codist = codistributor('1d',2,100*[1:numlabs]); C = rand(1000,1000,'single',codist); end
Each worker contains a 100-by-labindex
local piece of
C
.
Create a 1000-by-1000 gpuArray of rand
s with underlying
class double
:
G = rand(1000,'double','gpuArray');
codistributed.sprand
| distributed.sprand
| rand
| randi
| randn