cast

Convert variable to different data type

Syntax

B = cast(A,newclass)

B = cast(A,like=p)

Description

B = cast(A,newclass) returns the data in A converted to the data type (class) newclass, where newclass is the name of a built-in data type compatible with A. Any values in A that are outside the range of newclass are truncated in B to the nearest endpoint.

When converting a floating-point number to an integer, the cast function rounds the number to the nearest integer. If the floating-point number has a fractional part of exactly 0.5, then it rounds away from zero to the integer with larger magnitude.

B = cast(A,like=p) converts A to the same data type and sparsity as the variable p. The complexity (real or complex) of B is determined by both A and p. If both A and p are real, then B is also real. Otherwise, B is complex.

Examples

Convert Numeric Data Type

Convert int8 values to uint8.

Define a vector of 8-bit integers.

a = int8([-5 5]);

Convert a to unsigned 8-bit integers. The –5 value outside the range of uint8 is truncated to 0.

b = cast(a,"uint8")

b = 1×2 uint8 row vector

   0   5

Convert Vector to Existing Data Type

Create a 1-by-3 vector of 32-bit signed integers.

A = int32([-12 34 56])

A = 1×3 int32 row vector

   -12    34    56

Create a complex number of the data type double.

p = 1+2i

p = 
1.0000 + 2.0000i

Convert A to the same data type and complexity as the variable p.

B = cast(A,like=p)

B = 1×3 complex

 -12.0000 + 0.0000i  34.0000 + 0.0000i  56.0000 + 0.0000i

Convert Matrix to Existing Data Type

Create a 2-by-3 matrix of zeros whose elements are 32-bit unsigned integers.

A = zeros(2,3,"uint32")

A = 2×3 uint32 matrix

   0   0   0
   0   0   0

Create a 2-by-2 sparse matrix of the data type double.

p = sparse(2,2,pi)

p = 2×2 sparse double matrix (1 nonzero)
   (2,2)       3.1416

Convert A to the same data type and sparsity as the variable p.

B = cast(A,like=p)

B = 2×3 sparse double matrix
   All zero

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

Input array, specified as a scalar, vector, matrix, or multidimensional array. The data type of A can be a built-in data type or other data type that supports conversion to the specified new data type.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char
Complex Number Support: Yes

newclass — New class

"single" | "double" | "int8" | "int16" | "int32" | "int64" | ...

New class, specified as "single", "double", "int8", "int16", "int32", "int64", "uint8", "uint16", "uint32", "uint64", "logical", or "char".

p — Prototype

scalar | vector | matrix | multidimensional array

Prototype, specified as a scalar, vector, matrix, or multidimensional array. The data type of p can be a built-in data type or other compatible data type that supports conversion from the input data type.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical | char
Complex Number Support: Yes

Output Arguments

B — Output array

scalar | vector | matrix | multidimensional array

Output array, returned as a scalar, vector, matrix, or multidimensional array.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

• Enumeration inputs must be scalar valued at compile time. Arrays of enumerations are not supported.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• Enumeration inputs must be scalar valued at compile time. Arrays of enumerations are not supported.

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 cast function supports GPU array input with these usage notes and limitations:

• For the syntax B = cast(A,like=p), the output B is a gpuArray if and only if p is a gpuArray.

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:

• For the syntax B = cast(A,like=p), the output B is a distributed array if and only if p is a distributed array.

For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a

R2022a: cast returns consistent output for subclass of MATLAB numeric types

Starting in R2022a, the syntax cast(A,like=p) returns output consistent with the prototype p when the data type of p is a subclass of MATLAB^® numeric types.

For example, this code now returns an output that has the same data type as p:

p = matlab.lang.OnOffSwitchState.on;
x = cast(1,like=p)

x = 

  OnOffSwitchState enumeration

    on

In previous releases, the code returns x = 1 with data type logical.

R2021b: The newclass input argument is case-sensitive

Starting in R2021b, the newclass input argument of the syntax cast(A,newclass) is case-sensitive. You must specify newclass as a character vector or a string of lowercase letters that represents the new data type.

For example, to convert a double value to the int8 data type, you must use cast(1.234,"int8"). The command cast(1.234,"Int8") now errors.