abs

Absolute value and complex magnitude

Syntax

Y = abs(X)

Description

Y = abs(X) returns the absolute value of each element in array X.

If X is complex, abs(X) returns the complex magnitude.

Examples

Absolute Value of Scalar

y = abs(-5)

y = 5

Absolute Value of Vector

Create a numeric vector of real values.

x = [1.3 -3.56 8.23 -5 -0.01]'

x = 5×1

    1.3000
   -3.5600
    8.2300
   -5.0000
   -0.0100

Find the absolute value of the elements of the vector.

y = abs(x)

y = 5×1

    1.3000
    3.5600
    8.2300
    5.0000
    0.0100

Magnitude of Complex Number

y = abs(3+4i)

y = 5

Input Arguments

X — Input array

scalar | vector | matrix | multidimensional array

Input array, specified as a scalar, vector, matrix, or multidimensional array. If X is complex, then it must be a single or double array. The size and data type of the output array is the same as the input array.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | duration

More About

Absolute Value

The absolute value (or modulus) of a real number is the corresponding nonnegative value that disregards the sign.

For a real value, a, the absolute value is:

• a, if a is greater than or equal to zero

• -a, if a is less than zero

abs(-0) returns 0.

Complex Magnitude

The complex magnitude (or modulus) is the length of a vector from the origin to a complex value plotted in the complex plane.

For a complex value, $$|a+bi|$$ is defined as $$\sqrt{a^2+b^2}$$.

Extended Capabilities

Tall Arrays

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

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

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.

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™.

This function fully supports GPU arrays. 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).