isfloat

R2026b

Determine if input is floating-point array

Syntax

tf = isfloat(A)

Description

tf = isfloat(A) returns true if A is a floating-point array and false otherwise. Floating-point types in MATLAB^® include single and double (and subclasses of single and double).

Examples

Determine Whether Numbers Are Floating-Point Type

Determine if the following numbers are a floating-point type.

The real number pi in double precision is a floating-point type.

tf = isfloat(pi)

tf = logical
   1

Complex numbers in double precision are a floating-point type.

tf = isfloat(3+7i)

tf = logical
   1

Single-precision numbers are a floating-point type.

tf = isfloat(realmax("single"))

tf = logical
   1

A logical value is not a floating-point type.

tf = isfloat(true)

tf = logical
   0

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

Input array, specified as a scalar, vector, matrix, or multidimensional array. Floating-point types in MATLAB include single and double (and subclasses of single and double).

Extended Capabilities

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

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

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

The isfloat 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 isfloat function fully supports GPU arrays. To run the function on a GPU, specify the input data as a gpuArray (Parallel Computing Toolbox). 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™.

The isfloat function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a