zeros
Create array of all zeros
Syntax
Description
X = zeros
returns the scalar 0
.
X = zeros(
returns
an sz1,...,szN
)sz1
-by-...-by-szN
array of
zeros where sz1,...,szN
indicate the size of each
dimension. For example, zeros(2,3)
returns a 2-by-3
matrix.
X = zeros(___,
returns
an array of zeros of data type typename
)typename
. For example, zeros('int8')
returns
a scalar, 8-bit integer 0
. You can use any of the
input arguments in the previous syntaxes.
Examples
Matrix of Zeros
Create a 4-by-4 matrix of zeros.
X = zeros(4)
X = 4×4
0 0 0 0
0 0 0 0
0 0 0 0
0 0 0 0
3-D Array of Zeros
Clone Size from Existing Array
Create an array of zeros that is the same size as an existing array.
A = [1 4; 2 5; 3 6]; sz = size(A); X = zeros(sz)
X = 3×2
0 0
0 0
0 0
It is a common pattern to combine the previous two lines of code into a single line:
X = zeros(size(A));
Specify Data Type of Zeros
Create a 1-by-3 vector of zeros whose elements are 32-bit unsigned integers.
X = zeros(1,3,'uint32')
X = 1x3 uint32 row vector
0 0 0
class(X)
ans = 'uint32'
Clone Complexity from Existing Array
Create a scalar 0
that is complex like an existing array instead of real valued.
First, create a complex vector.
p = [1+2i 3i];
Create a scalar 0
that is complex like p
.
X = zeros('like',p)
X = 0.0000 + 0.0000i
Clone Sparsity from Existing Array
Create a 10-by-10 sparse matrix.
p = sparse(10,10,pi);
Create a 2-by-3 matrix of zeros that is sparse like p
.
X = zeros(2,3,'like',p)
X = 2x3 sparse double matrix
All zero
Clone Size and Data Type from Existing Array
Create a 2-by-3 array of 8-bit unsigned integers.
p = uint8([1 3 5; 2 4 6]);
Create an array of zeros that is the same size and data type as p
.
X = zeros(size(p),'like',p)
X = 2x3 uint8 matrix
0 0 0
0 0 0
class(X)
ans = 'uint8'
Clone Distributed Array
If you have Parallel Computing Toolbox™, create a 1000-by-1000 distributed array of zeros with underlying data type
int8
. For the distributed
data type, the
'like'
syntax clones the underlying data type in addition to the primary
data type.
p = zeros(1000,'int8','distributed');
Starting parallel pool (parpool) using the 'local' profile ... connected to 6 workers.
Create an array of zeros that is the same size, primary data type, and underlying data
type as p
.
X = zeros(size(p),'like',p);
class(X)
ans = 'distributed'
underlyingType(X)
ans = 'int8'
Input Arguments
n
— Size of square matrix
integer value
Size of square matrix, specified as an integer value.
If
n
is0
, thenX
is an empty matrix.If
n
is negative, then it is treated as0
.
Data Types: double
| single
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
sz1,...,szN
— Size of each dimension (as separate arguments)
integer values
Size of each dimension, specified as separate arguments of integer values.
If the size of any dimension is
0
, thenX
is an empty array.If the size of any dimension is negative, then it is treated as
0
.Beyond the second dimension,
zeros
ignores trailing dimensions with a size of1
. For example,zeros(3,1,1,1)
produces a 3-by-1 vector of zeros.
Data Types: double
| single
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
sz
— Size of each dimension (as a row vector)
integer values
Size of each dimension, specified as a row vector of integer values. Each element of this vector indicates the size of the corresponding dimension:
If the size of any dimension is
0
, thenX
is an empty array.If the size of any dimension is negative, then it is treated as
0
.Beyond the second dimension,
zeros
ignores trailing dimensions with a size of1
. For example,zeros([3 1 1 1])
produces a 3-by-1 vector of zeros.
Example: sz = [2 3 4]
creates a 2-by-3-by-4 array.
Data Types: double
| single
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
typename
— Data type (class) to create
'double'
(default) | 'single'
| 'logical'
| 'int8'
| 'uint8'
| ...
Data type (class) to create, specified as 'double'
, 'single'
, 'logical'
,'int8'
, 'uint8'
, 'int16'
, 'uint16'
, 'int32'
, 'uint32'
, 'int64'
, 'uint64'
,
or the name of another class that provides zeros
support.
p
— Prototype of array to create
array
Prototype of array to create, specified as an array.
Data Types: double
| single
| logical
| int8
| int16
| int32
| int64
| uint8
| uint16
| uint32
| uint64
Complex Number Support: Yes
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
Dimensions must be nonnegative real integers. Empty dimensions are not supported.
GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.
Usage notes and limitations:
Refer to the usage notes and limitations in the C/C++ Code Generation section. The same limitations apply to GPU code generation.
HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.
Dimensions must be nonnegative real integers.
Thread-Based Environment
Run code in the background using MATLAB® backgroundPool
or accelerate code with Parallel Computing Toolbox™ ThreadPool
.
This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.
GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.
The zeros
function
supports GPU array input with these usage notes and limitations:
You can specify
typename
as'gpuArray'
. If you specifytypename
as'gpuArray'
, the default underlying type of the array isdouble
.To create a GPU array with underlying type
datatype
, specify the underlying type as an additional argument beforetypename
. For example,X = zeros(3,datatype,'gpuArray')
creates a 3-by-3 GPU array of zeros with underlying typedatatype
.You can specify the underlying type
datatype
as one of these options:'double'
'single'
'logical'
'int8'
'uint8'
'int16'
'uint16'
'int32'
'uint32'
'int64'
'uint64'
You can also specify the numeric variable
p
as agpuArray
.If you specify
p
as agpuArray
, the underlying type of the returned array is the same asp
.
For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).
Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.
Usage notes and limitations:
You can specify
typename
as'codistributed'
or'distributed'
. If you specifytypename
as'codistributed'
or'distributed'
, the default underlying type of the returned array isdouble
.To create a distributed or codistributed array with underlying type
datatype
, specify the underlying type as an additional argument beforetypename
. For example,X = zeros(3,datatype,'distributed')
creates a 3-by-3 distributed matrix of zeros with underlying typedatatype
.You can specify the underlying type
datatype
as one of these options:'double'
'single'
'logical'
'int8'
'uint8'
'int16'
'uint16'
'int32'
'uint32'
'int64'
'uint64'
You can also specify
p
as acodistributed
ordistributed
array.If you specify
p
as acodistributed
ordistributed
array, the underlying type of the returned array is the same asp
.For additional
codistributed
syntaxes, seezeros (codistributed)
(Parallel Computing Toolbox).
For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).
Version History
Introduced before R2006a
See Also
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