ne,~=

Determine inequality

Syntax

A ~= B

ne(A,B)

Description

A~=Breturns a logical array with elements set to logical1(true) where arraysAandBare not equal; otherwise, the element is logical0(false). The test compares both real and imaginary parts of numeric arrays.nereturns logical1(true) whereAorBhave NaN or undefinedcategoricalelements.

ne(A,B)is an alternative way to executeA ~= B, but is rarely used. It enables operator overloading for classes.

Examples

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Inequality of Two Vectors

Open Live Script

Create two vectors containing both real and imaginary numbers, then compare the vectors for inequality.

A = [1+i 3 2 4+i]; B = [1 3+i 2 4+i]; A ~= B

ans =1x4 logical array1 1 0 0

Thenefunction tests both real and imaginary parts for inequality, and returns logical1(true) where one or both parts are not equal.

Find Characters

Open Live Script

创建一个特征向量。

M ='masterpiece';

Test for the presence of a specific character using~=.

M ~='n'

ans =1x11 logical array1 1 1 1 1 1 1 1 1 1 1

The value of logical1(true) indicates the absence of the character'n'. The character is not present in the vector.

Find Values in Categorical Array

Open Live Script

Create a categorical array with two values:'heads'and'tails'.

A = categorical({'heads''heads''tails';'tails''heads''tails'})

A =2x3 categoricalheads heads tails tails heads tails

Find all values not in the'heads'category.

A ~='heads'

ans =2x3 logical array0 0 1 1 0 1

A value of logical1(true) indicates a value not in the category. SinceAonly has two categories,A ~= 'heads'returns the same answer asA == 'tails'.

Compare the rows ofAfor inequality.

A(1,:) ~= A(2,:)

ans =1x3 logical array1 0 0

A value of logical1(true) indicates where the rows have unequal category values.

Compare Floating-Point Numbers

Open Live Script

Many numbers expressed in decimal text cannot be represented exactly as binary floating numbers. This leads to small differences in results that the~=operator reflects.

Perform a few subtraction operations on numbers expressed in decimal and store the result inC.

C = 0.5-0.4-0.1

C = -2.7756e-17

With exact decimal arithmetic,Cshould be equal toexactly0. Its small value is due to the nature of binary floating-point arithmetic.

CompareCto0for inequality.

C ~= 0

ans =logical1

Compare floating-point numbers using a tolerance,tol, instead of using~=.

tol = eps(0.5); abs(C-0) > tol

ans =logical0

The two numbers,Cand0, are closer to one another than two consecutive floating-point numbers near0.5. In many situations,Cmay act like0.

Inequality of Two Datetime Arrays

Open Live Script

Compare the elements of twodatetimearrays for inequality.

Create twodatetimearrays in different time zones.

t1 = [2014,04,14,9,0,0;2014,04,14,10,0,0]; A = datetime(t1,'TimeZone','America/Los_Angeles'); A.Format ='d-MMM-y HH:mm:ss Z'

A =2x1 datetime14-Apr-2014 09:00:00 -0700 14-Apr-2014 10:00:00 -0700

t2 = [2014,04,14,12,0,0;2014,04,14,12,30,0]; B = datetime(t2,'TimeZone','America/New_York'); B.Format ='d-MMM-y HH:mm:ss Z'

B =2x1 datetime14-Apr-2014 12:00:00 -0400 14-Apr-2014 12:30:00 -0400

Check where elements inAandBare not equal.

A~=B

ans =2x1 logical array0 1

Input Arguments

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`A`,`B`—操作数
scalars|vectors|matrices|multidimensional arrays

操作数, specified as scalars, vectors, matrices, or multidimensional arrays. InputsAandBmust either be the same size or have sizes that are compatible (for example,Ais anM-by-Nmatrix andBis a scalar or1-by-Nrow vector). For more information, seeCompatible Array Sizes for Basic Operations.

You can compare numeric inputs of any type, and the comparison does not suffer loss of precision due to type conversion.

If one input is acategoricalarray, the other input can be acategoricalarray, a cell array of character vectors, or a single character vector. A single character vector expands into a cell array of character vectors of the same size as the other input. If both inputs are ordinalcategoricalarrays, they must have the same sets of categories, including their order. If both inputs arecategoricalarrays that are not ordinal, they can have different sets of categories. SeeCompare Categorical Array Elementsfor more details.
If one input is adatetimearray, the other input can be adatetimearray, a character vector, or a cell array of character vectors.
If one input is adurationarray, the other input can be adurationarray or a numeric array. The operator treats each numeric value as a number of standard 24-hour days.
如果一个输入是一个年代tring array, the other input can be a string array, a character vector, or a cell array of character vectors. The corresponding elements ofAandBare compared lexicographically.

Extended Capabilities

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

This function fully supports tall arrays. For more information, seeTall Arrays.

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

Code generation does not support usingneto test inequality between an enumeration member and a string array, a character array, or a cell array of character arrays.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

Code generation does not support usingneto test inequality between an enumeration member and a string array, a character array, or a cell array of character arrays.

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, seeRun 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, seeRun 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, seeRun MATLAB Functions with Distributed Arrays(Parallel Computing Toolbox).

Version History

Introduced before R2006a

expand all

R2020b: Implicit expansion change affects`categorical`,`datetime`, and`duration`arrays

Behavior changed in R2020b

圣arting in R2020b,nesupports implicit expansion when the arguments arecategorical,datetime, ordurationarrays. Between R2020a and R2016b, implicit expansion was supported only for numeric and string data types.

R2016b: Implicit expansion change affects arguments for operators

Behavior changed in R2016b

圣arting in R2016b with the addition of implicit expansion, some combinations of arguments for basic operations that previously returned errors now produce results. For example, you previously could not add a row and a column vector, but those operands are now valid for addition. In other words, an expression like[1 2] + [1; 2]previously returned a size mismatch error, but now it executes.

If your code uses element-wise operators and relies on the errors that MATLAB^®previously returned for mismatched sizes, particularly within atry/catchblock, then your code might no longer catch those errors.

For more information on the required input sizes for basic array operations, seeCompatible Array Sizes for Basic Operations.

ne,~=

Syntax

Description

Examples

Inequality of Two Vectors

Find Characters

Find Values in Categorical Array

Compare Floating-Point Numbers

Inequality of Two Datetime Arrays

Input Arguments

`A`,`B`—操作数
scalars|vectors|matrices|multidimensional arrays

Extended Capabilities

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

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`.

GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Version History

R2020b: Implicit expansion change affects`categorical`,`datetime`, and`duration`arrays

R2016b: Implicit expansion change affects arguments for operators

See Also

Topics

ne,~=

Syntax

Description

Examples

Inequality of Two Vectors

Find Characters

Find Values in Categorical Array

Compare Floating-Point Numbers

Inequality of Two Datetime Arrays

Input Arguments

A,B—操作数scalars|vectors|matrices|multidimensional arrays

Extended Capabilities

Tall ArraysCalculate with arrays that have more rows than fit in memory.

C/C++ Code GenerationGenerate C and C++ code using MATLAB® Coder™.

GPU Code GenerationGenerate CUDA® code for NVIDIA® GPUs using GPU Coder™.

HDL Code GenerationGenerate Verilog and VHDL code for FPGA and ASIC designs using HDL Coder™.

Thread-Based EnvironmentRun code in the background using MATLAB®backgroundPoolor accelerate code with Parallel Computing Toolbox™ThreadPool.

GPU ArraysAccelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Distributed ArraysPartition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

Version History

R2020b: Implicit expansion change affectscategorical,datetime, anddurationarrays

R2016b: Implicit expansion change affects arguments for operators

See Also

Topics

`A`,`B`—操作数
scalars|vectors|matrices|multidimensional arrays

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

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`.

GPU Arrays
Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

Distributed Arrays
Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

R2020b: Implicit expansion change affects`categorical`,`datetime`, and`duration`arrays