logical

Convert numeric values to logicals

Syntax

L = logical(A)

Description

L = logical(A) converts A into an array of logical values. Any nonzero element of A is converted to logical 1 (true) and zeros are converted to logical 0 (false). Complex values and NaNs cannot be converted to logical values and result in a conversion error.

Examples

Pick Odd Elements from Numeric Matrix

Pick out the odd-numbered elements of a numeric matrix.

Create a numeric matrix.

A = [1 -3 2;5 4 7;-8 1 3];

Find the modulus, mod(A,2), and convert it to a logical array for indexing.

L = logical(mod(A,2))

L = 3×3 logical array

   1   1   0
   1   0   1
   0   1   1

The array has logical 1 (true) values where A is odd.

Use L as a logical index to pick out the odd elements of A.

A(L)

ans = 6×1

     1
     5
    -3
     1
     7
     3

The result is a vector containing all odd elements of A.

Use the logical NOT operator, ~, on L to find the even elements of A.

A(~L)

ans = 3×1

    -8
     4
     2

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

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

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

Tips

• Most arithmetic operations involving logical arrays return double values. For example, adding zero to a logical array returns a double array.

• Logical arrays also are created by the relational operators (==,<,>,~=, etc.) and functions like any, all, isnan, isinf, and isfinite.

Extended Capabilities

Tall Arrays

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

The logical 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™.

The logical 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