Determine equality

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

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

`ans = `*1x4 logical array*
0 0 1 1

The `eq`

function tests both real and imaginary parts for equality, and returns logical `1`

(`true`

) only where both parts are equal.

Create a character vector.

`M = 'masterpiece';`

Test for the presence of a specific character using `==`

.

`M == 'e'`

`ans = `*1x11 logical array*
0 0 0 0 1 0 0 0 1 0 1

The value of logical `1`

(`true`

) indicates the presence of the character `'e'`

.

Create a categorical array with two values: `'heads'`

and `'tails'`

.

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

`A = `*2x3 categorical array*
heads heads tails
tails heads tails

Find all values in the `'heads'`

category.

`A == 'heads'`

`ans = `*2x3 logical array*
1 1 0
0 1 0

A value of logical `1`

(`true`

) indicates a value in the category.

Compare the rows of `A`

for equality.

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

`ans = `*1x3 logical array*
0 1 1

A value of logical `1`

(`true`

) indicates where the rows have equal category values.

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 in `C`

.

C = 0.5-0.4-0.1

C = -2.7756e-17

With exact decimal arithmetic, `C`

should be equal to *exactly* `0`

. Its small value is due to the nature of binary floating-point arithmetic.

Compare `C`

to `0`

for equality.

C == 0

`ans = `*logical*
0

Compare floating-point numbers using a tolerance, `tol`

, instead of using `==`

.

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

`ans = `*logical*
1

The two numbers, `C`

and `0`

, are closer to one another than two consecutive floating-point numbers near `0.5`

. In many situations, `C`

may act like `0`

.

Compare the elements of two `datetime`

arrays.

Create two `datetime`

arrays 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 datetime array*
14-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 datetime array*
14-Apr-2014 12:00:00 -0400
14-Apr-2014 12:30:00 -0400

Check where elements in `A`

and `B`

are equal.

A==B

`ans = `*2x1 logical array*
1
0

`A`

, `B`

— Operandsscalars | vectors | matrices | multidimensional arrays

Operands, specified as scalars, vectors, matrices, or multidimensional
arrays. Numeric or string inputs `A`

and
`B`

must either be the same size or have sizes that are
compatible (for example, `A`

is an
`M`

-by-`N`

matrix and
`B`

is a scalar or
`1`

-by-`N`

row vector). For more
information, see Compatible 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 `A`

and `B`

are categorical,
datetime, or duration arrays, then they must be the same size unless one is
a scalar.

If one input is a categorical array, the other input can be a categorical array, 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 ordinal categorical arrays, they must have the same sets of categories, including their order. If both inputs are categorical arrays that are not ordinal, they can have different sets of categories. See Compare Categorical Array Elements for more details.

If one input is a datetime array, the other input can be a datetime array, a character vector, or a cell array of character vectors.

If one input is a duration array, the other input can be a duration array or a numeric array. The operator treats each numeric value as a number of standard 24-hour days.

If one input is a string array, the other input can be a string array, a character vector, or a cell array of character vectors. The corresponding elements of

`A`

and`B`

are compared lexicographically.

**Data Types: **`single`

| `double`

| `int8`

| `int16`

| `int32`

| `int64`

| `uint8`

| `uint16`

| `uint32`

| `uint64`

| `logical`

| `char`

| `string`

| `categorical`

| `datetime`

| `duration`

**Complex Number Support: **Yes

When comparing handle objects, use

`==`

to test whether objects have the same handle. Use`isequal`

to determine if objects with different handles have equal property values.

*Behavior changed in R2016b*

Starting 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 a `try`

/`catch`

block, then your code might no longer catch those errors.

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

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

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

Generate C and C++ code using MATLAB® Coder™.

Usage notes and limitations:

Code generation does not support using

`eq`

to test equality between an enumeration member and a string array, a character array, or a cell array of character 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).

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).

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