cast

Convert variable to different data type

Syntax

B = cast(A,newclass)

B = cast(A,'like',p)

Description

B = cast(A,newclass) converts A to the data type (class) newclass, where newclass is the name of a built-in data type compatible with A. The cast function truncates any values in A that are outside the range of newclass 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, sparsity, and complexity (real or complex) as the variable p. If A and p are both 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 = 1x2 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 = 1x3 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 = 2x3 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)       3.1416

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

B = cast(A,'like',p)

B = 
   All zero sparse: 2x3

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

Input array, specified as a scalar, vector, matrix, or multidimensional array.

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

newclass — New class

'single' | 'double' | 'int8' | 'int16' | 'int32' | 'int64' | 'uint8' | 'uint16' | 'uint32' | 'uint64' | 'logical' | 'char'

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.

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

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.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

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).