not, ~

Find logical NOT

Syntax

~A

not(A)

Description

~A returns a logical array of the same size as A. The array contains logical 1 (true) values where A is zero and logical 0 (false) values where A is nonzero.

not(A) is an alternate way to execute ~A, but is rarely used. It enables operator overloading for classes.

Examples

Logical Negation of Matrix

Create a 3-by-3 identity matrix.

A = eye(3)

A = 3×3

     1     0     0
     0     1     0
     0     0     1

Find the logical negation of A. The new matrix has type logical.

B = ~A

B = 3x3 logical array

   0   1   1
   1   0   1
   1   1   0

Conditional Code Execution

Execute code based on a condition using the logical not operator in the context of an if loop.

Create a logical variable A.

A = false;

Use A to write an if/else code block. Wrap the if/else block in a for loop so that it executes four times.

for k = 1:4
    if ~A
        disp('IF block')
        A = true;
    else
        disp('ELSE block')
    end
end

IF block
ELSE block
ELSE block
ELSE block

On the first iteration, A is false, so the if block executes since ~A is true. However, the if block also changes the value of A to true. In the remaining iterations, ~A is false and the else block executes.

Input Arguments

A — Input array

scalar | vector | matrix | multidimensional array

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

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

Tips

• You also can use the ~ symbol as a placeholder output argument in a function call. For example, [~,i] = max(A) suppresses the first output of the max function, returning only the indices of the maximum values. For more information, see Ignore Function Inputs.

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 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).