bitcmp

Bit-wise complement

Syntax

cmp = bitcmp(A)

cmp = bitcmp(A,assumedtype)

Description

cmp = bitcmp(A) returns the bit-wise complement of A.

cmp = bitcmp(A,assumedtype) assumes that A is of assumedtype.

Examples

Complement of a Negative Integer

A = int8(-11);
cmp = bitcmp(A)

cmp = int8
    10

You can see the complement operation when the numbers are shown in binary.

original = bitget(A,8:-1:1)

original = 1x8 int8 row vector

   1   1   1   1   0   1   0   1

complement = bitget(bitcmp(A),8:-1:1)

complement = 1x8 int8 row vector

   0   0   0   0   1   0   1   0

Complement of Unsigned Integers

cmp = bitcmp(64,'uint8')

cmp = 191

maxint = intmax('uint8') - 64

maxint = uint8
    191

The complement of an unsigned integer is equal to itself subtracted from the maximum integer of its data type.

Input Arguments

A — Input value

signed integer array | unsigned integer array | double array

Input value, specified as a signed integer array, unsigned integer array, or double array.

• If A is a double array, and assumedtype is not specified, then MATLAB^® treats A as an unsigned 64-bit integer.

• If assumedtype is specified, then all elements in A must have integer values within the range of assumedtype.

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

assumedtype — Assumed data type of A

'uint64' | 'uint32' | 'uint16' | 'uint8' | 'int64' | 'int32' | 'int16' | 'int8'

Assumed data type of A, specified as 'uint64', 'uint32', 'uint16', 'uint8', 'int64', 'int32', 'int16', or 'int8'.

• If A is a double array, then assumedtype can specify any valid integer type, but defaults to 'uint64'.

• If A is an integer type array, then assumedtype must specify that same integer type.

Data Types: char | string

Output Arguments

cmp — Bit-wise complement

signed integer array | unsigned integer array | double array

Bit-wise complement, returned as a signed integer array, unsigned integer array, or double array. cmp is the same size and type as A.

Extended Capabilities

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™.

Usage notes and limitations:

• The input argument A must be a gpuArray of unsigned integers.

• 64-bit integers are not supported.

• The assumedtype argument is not supported.

For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).