cast

Convert variable to different data type

Syntax

b =cast(A,newclass)

b = cast（a，'like'，p）

Description

B= cast(A,新级)convertsAto the data type (class)新级, where新级is the name of a built-in data type compatible withA。这castfunction truncates any values inAthat are outside the range of新级to the nearest endpoint.

将浮点数转换为整数时castfunction 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.

example

B= cast(A，'喜欢'，p)convertsAto the same data type, sparsity, and complexity (real or complex) as the variablep。IfA和p都是真实的B也是真实的。否则，Bis complex.

Examples

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转换数字数据类型

打开实时脚本

Convertint8values touint8。

Define a vector of 8-bit integers.

a = int8（[ -  5 5]）;

Convertato unsigned 8-bit integers. The –5 value outside the range ofuint8is truncated to 0.

b =cast(a,“uint8”)

b =1x2 uint8 row vector0 5

Convert Vector to Existing Data Type

打开实时脚本

创建32位签名整数的1 x-3向量。

A = int32([-12 34 56])

A =1x3 int32 row vector-12 34 56

创建复杂数量的数据类型double。

p = 1+2i

p = 1.0000 + 2.0000i

ConvertAto the same data type and complexity as the variablep。

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

打开实时脚本

创建一个2 x-3矩阵的零矩阵，其元素是32位未签名的整数。

a =零（2,3，'uint32')

A =2x3 uint32 matrix0 0 0 0 0 0

创建数据类型的2 by-2稀疏矩阵double。

p =稀疏（2,2，pi）

p =（2,2）3.1416

ConvertAto the same data type and sparsity as the variablep。

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

b =All zero sparse: 2x3

Input Arguments

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`A`—Input array
scalar|vector|matrix|multidimensional array

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

`新级`—New class
`'single'`|`'double'`|`'int8'`|`'int16'`|`'int32'`|`'int64'`|`“uint8”`|`'uint16'`|`'uint32'`|`'uint64'`|`'logical'`|`'char'`|`'fi'`|`'sym'`

New class, specified as'single','double','int8','int16','int32','int64',“uint8”,'uint16','uint32','uint64','logical','char','fi', or'sym'。

`p`—Prototype
scalar|vector|matrix|multidimensional array

原型，指定为标量，矢量，矩阵或多维数组。

兼容性考虑

expand all

这`新级`input argument is case-sensitive

Behavior changed in R2021b

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

For example, to convert adoublevalue toint8data type, you must usecast(1.234,'int8')。命令cast(1.234,'Int8')now errors.

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
使用GPU CODER™为NVIDIA®GPU生成CUDA®代码。

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, seeRun MATLAB Functions in Thread-Based Environment。

GPU Arrays
使用并行计算工具箱™在图形处理单元（GPU）上运行加速代码。

Usage notes and limitations:

对于语法b = cast（a，'like'，p）, the outputBis agpuArrayif and only ifpis agpuArray。

For more information, seeRun 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:

对于语法b = cast（a，'like'，p）, the outputBis a distributed array if and only ifp是一个分布式数组。

For more information, see运行具有分布式数组的MATLAB功能(Parallel Computing Toolbox)。

cast

Syntax

Description

Examples

转换数字数据类型

Convert Vector to Existing Data Type

Convert Matrix to Existing Data Type

Input Arguments

`A`—Input array
scalar|vector|matrix|multidimensional array

`新级`—New class
`'single'`|`'double'`|`'int8'`|`'int16'`|`'int32'`|`'int64'`|`“uint8”`|`'uint16'`|`'uint32'`|`'uint64'`|`'logical'`|`'char'`|`'fi'`|`'sym'`

`p`—Prototype
scalar|vector|matrix|multidimensional array

兼容性考虑

这`新级`input argument is case-sensitive

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
使用GPU CODER™为NVIDIA®GPU生成CUDA®代码。

Thread-Based Environment
Run code in the background using MATLAB®`backgroundPool`or accelerate code with Parallel Computing Toolbox™`ThreadPool`。

GPU Arrays
使用并行计算工具箱™在图形处理单元（GPU）上运行加速代码。

Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

See Also

Topics

MATLAB Documentation

金宝app

用Matlab介绍深度学习

cast

Syntax

Description

Examples

转换数字数据类型

Convert Vector to Existing Data Type

Convert Matrix to Existing Data Type

Input Arguments

A—Input arrayscalar|vector|matrix|multidimensional array

新级—New class'single'|'double'|'int8'|'int16'|'int32'|'int64'|“uint8”|'uint16'|'uint32'|'uint64'|'logical'|'char'|'fi'|'sym'

p—Prototypescalar|vector|matrix|multidimensional array

兼容性考虑

这新级input argument is case-sensitive

Extended Capabilities

C/C++ Code GenerationGenerate C and C++ code using MATLAB® Coder™.

GPU Code Generation使用GPU CODER™为NVIDIA®GPU生成CUDA®代码。

Thread-Based EnvironmentRun code in the background using MATLAB®backgroundPoolor accelerate code with Parallel Computing Toolbox™ThreadPool。

GPU Arrays使用并行计算工具箱™在图形处理单元（GPU）上运行加速代码。

Distributed ArraysPartition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

See Also

Topics

MATLAB Documentation

金宝app

用Matlab介绍深度学习

`A`—Input array
scalar|vector|matrix|multidimensional array

`新级`—New class
`'single'`|`'double'`|`'int8'`|`'int16'`|`'int32'`|`'int64'`|`“uint8”`|`'uint16'`|`'uint32'`|`'uint64'`|`'logical'`|`'char'`|`'fi'`|`'sym'`

`p`—Prototype
scalar|vector|matrix|multidimensional array

这`新级`input argument is case-sensitive

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
使用GPU CODER™为NVIDIA®GPU生成CUDA®代码。

Thread-Based Environment
Run code in the background using MATLAB®`backgroundPool`or accelerate code with Parallel Computing Toolbox™`ThreadPool`。

GPU Arrays
使用并行计算工具箱™在图形处理单元（GPU）上运行加速代码。

Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.