length

Length of largest array dimension

Syntax

L = length(X)

Description

L = length(X) returns the length of the largest array dimension in X. For vectors, the length is simply the number of elements. For arrays with more dimensions, the length is max(size(X)). The length of an empty array is zero.

Examples

Number of Vector Elements

Find the length of a uniformly spaced vector in the interval [5,10].

v = 5:10

v = 1×6

     5     6     7     8     9    10

L = length(v)

L = 6

Length of Rectangular Matrix

Find the length of a 3-by-7 matrix of zeros.

X = zeros(3,7);
L = length(X)

L = 7

String Array

Create a string array and compute its length, which is the number of elements in each row.

X = ["a" "b" "c"; "d" "e" "f"]

X = 2x3 string
    "a"    "b"    "c"
    "d"    "e"    "f"

L = length(X)

L = 3

Length of Structure Fields

Create a structure with fields for Day and Month. Use the structfun function to apply length to each field.

S = struct('Day',[1 13 14 26],'Month',{{'Jan','Feb', 'Mar'}})

S = struct with fields:
      Day: [1 13 14 26]
    Month: {'Jan'  'Feb'  'Mar'}

L = structfun(@(field) length(field),S)

L = 2×1

     4
     3

Input Arguments

X — Input array

scalar | vector | matrix | multidimensional array

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

Complex Number Support: Yes

Tips

• To find the number of characters in a string or character vector, use the strlength function.

• length does not operate on tables. To examine the dimensions of a table, use the height, width, or size functions.

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™.

HDL Code Generation
Generate Verilog and VHDL 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™.

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).