isrow

Determine if input is row vector

Syntax

tf = isrow(V)

Description

tf = isrow(V) returns logical 1 (true) if V is a row vector. Otherwise, it returns logical 0 (false). A row vector is a two-dimensional array that has a size of 1-by-N, where N is a nonnegative integer.

Examples

Determine Row Vector

Create a vector. Determine if it is a row vector.

V = rand(5,1);
tf = isrow(V)

tf = logical
   0

Find the conjugate transpose of the vector. Determine if it is a row vector.

Vt = V';
tf = isrow(Vt)

tf = logical
   1

Determine Row Vector from Scalar

Create a scalar, which is a 1-by-1 array.

V = 5;

Determine if the scalar V is also a row vector.

tf = isrow(V)

tf = logical
   1

Determine Row Vector from Character Vector and String Scalar

Create an array of characters. Determine if it is a row vector.

V = 'Hello, World!';
tf = isrow(V)

tf = logical
   1

Check the dimension of V by using size. V is a 1-by-13 character vector, which is also a row vector.

sz = size(V)

sz = 1×2

     1    13

Now create a string scalar by enclosing a piece of text in double quotes.

V = "Hello, World!";

Check if the scalar V is also a row vector.

tf = isrow(V)

tf = logical
   1

Input Arguments

V — Input array

scalar | vector | matrix | multidimensional array

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

Algorithms

• If the input array V has more than two dimensions, then isrow(V) returns logical 0 (false). For example, an array of size 1-by-1-by-N is not a row vector.

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 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™.

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).

Version History

Introduced in R2010b