isnan

Determine which array elements are NaN

Syntax

TF = isnan(A)

Description

TF = isnan(A) returns a logical array containing 1 (true) where the elements of A are NaN, and 0 (false) where they are not. If A contains complex numbers, isnan(A) contains 1 for elements with either real or imaginary part is NaN, and 0 for elements where both real and imaginary parts are not NaN.

Examples

Determine NaN Elements in Real Numbers

Create a row vector and determine which elements are NaN.

A = 0./[-2 -1 0 1 2]

A = 1×5

     0     0   NaN     0     0

TF = isnan(A)

TF = 1×5 logical array

   0   0   1   0   0

Determine NaN Elements in Complex Numbers

Create an array of complex numbers. Determine whether the complex numbers contain NaN.

A = [2 + 1i, 1/0 + 3i, 1/2 - 1i*NaN]

A = 1×3 complex

   2.0000 + 1.0000i      Inf + 3.0000i   0.5000 +    NaNi

TF = isnan(A)

TF = 1×3 logical array

   0   0   1

Replace NaN Elements

Create an array and find the elements with NaN values.

A = [1,3,5,7,NaN,10,NaN,4,6,8]

A = 1×10

     1     3     5     7   NaN    10   NaN     4     6     8

TF = isnan(A)

TF = 1×10 logical array

   0   0   0   0   1   0   1   0   0   0

Index into A with TF to access the elements of A that are NaN. Replace the NaN values with 0.

A(TF) = 0

A = 1×10

     1     3     5     7     0    10     0     4     6     8

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

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

Tips

• If x is a real scalar, exactly one of isfinite(x), isinf(x), and isnan(x) returns logical 1 (true).

• For a complex scalar z, isinf(z) and isnan(z) can both return logical 1. For example, isinf(complex(Inf,NaN)) and isnan(complex(Inf,NaN)) both return logical 1.

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

The isnan function fully supports tall arrays. For more information, see Tall Arrays.

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

HDL Code Generation
Generate VHDL, Verilog and SystemVerilog code for FPGA and ASIC designs using HDL Coder™.

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 isnan 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™.

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

Version History

Introduced before R2006a