# rand

Uniformly distributed random numbers

## Syntax

• `X = rand` example
• `X = rand(n)` example
• `X = rand(sz1,...,szN)` example
• `X = rand(sz)` example
• `X = rand(___,typename)` example
• `X = rand(___,'like',p)` example

## Description

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````X = rand` returns a single uniformly distributed random number between 0 and 1.```

example

````X = rand(n)` returns an `n`-by-`n` matrix of random numbers.```

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````X = rand(sz1,...,szN)` returns an `sz1`-by-...-by-`szN` array of random numbers where `sz1,...,szN` indicate the size of each dimension. For example, `rand(3,4)` returns a 3-by-4 matrix.```

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````X = rand(sz)` returns an array of random numbers where size vector `sz` specifies `size(X)`. For example, `rand([3 4])` returns a 3-by-4 matrix.```

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``` `X = rand(___,typename)` returns an array of random numbers of data type `typename`. The `typename` input can be either `'single'` or `'double'`. You can use any of the input arguments in the previous syntaxes. ```

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````X = rand(___,'like',p)` returns an array of random numbers like `p`; that is, of the same object type as `p`. You can specify either `typename` or `'like'`, but not both.```

The sequence of numbers produced by `rand` is determined by the internal settings of the uniform pseudorandom number generator that underlies `rand`, `randi`, and `randn`. You can control that shared random number generator using `rng`.

 Note:   Use the `rng` function instead of `rand` or `randn` with the `'seed'`, `'state'`, or `'twister'` inputs. For more information, see Replace Discouraged Syntaxes of rand and randn

## Examples

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### Matrix of Random Numbers

Generate a 5-by-5 matrix of uniformly distributed random numbers between 0 and 1.

`r = rand(5)`
```r = 0.5468 0.6791 0.8852 0.3354 0.6538 0.5211 0.3955 0.9133 0.6797 0.4942 0.2316 0.3674 0.7962 0.1366 0.7791 0.4889 0.9880 0.0987 0.7212 0.7150 0.6241 0.0377 0.2619 0.1068 0.9037```

### Random Numbers Within Specified Interval

Generate a 10-by-1 column vector of uniformly distributed numbers in the interval `[-5,5]`.

`r = -5 + (5+5)*rand(10,1)`
```r = 3.1472 4.0579 -3.7301 4.1338 1.3236 -4.0246 -2.2150 0.4688 4.5751 4.6489```

In general, you can generate `N` random numbers in the interval `[a,b]` with the formula ```r = a + (b-a).*rand(N,1)```.

### Random Integers

Use the `randi` function (instead of `rand`) to generate 5 random integers from the uniform distribution between 10 and 50.

`r = randi([10 50],1,5)`
```r = 43 47 15 47 35```

### Random Complex Numbers

Generate a single random complex number with real and imaginary parts in the interval `[0,1]`.

`a = rand + 1i*rand`
```a = 0.8147 + 0.9058i```

### Reset Random Number Generator

Save the current state of the random number generator and create a 1-by-5 vector of random numbers.

```s = rng; r = rand(1,5)```
```r = 0.0975 0.2785 0.5469 0.9575 0.9649```

Restore the state of the random number generator to `s`, and then create a new 1-by-5 vector of random numbers. The values are the same as before.

```rng(s); r1 = rand(1,5)```
```r1 = 0.0975 0.2785 0.5469 0.9575 0.9649```

Always use the `rng` function (rather than the `rand` or `randn` functions) to specify the settings of the random number generator. For more information, see Replace Discouraged Syntaxes of rand and randn.

### 3-D Array of Random Numbers

Create a 3-by-2-by-3 array of random numbers.

`X = rand([3,2,3])`
```X(:,:,1) = 0.8909 0.1978 0.3342 0.0305 0.6987 0.7441 X(:,:,2) = 0.5000 0.6099 0.4799 0.6177 0.9047 0.8594 X(:,:,3) = 0.8055 0.2399 0.5767 0.8865 0.1829 0.0287 ```

### Specify Data Type of Random Numbers

Create a 1-by-4 vector of random numbers whose elements are single precision.

```r = rand(1,4,'single') ```
```r = 0.1270 0.9134 0.6324 0.0975 ```
`class(r)`
```ans = single```

### Clone Size from Existing Array

Create a matrix of random numbers with the same size as an existing array.

```A = [3 2; -2 1]; sz = size(A); X = rand(sz)```
```X = 0.4899 0.9787 0.1679 0.7127```

It is a common pattern to combine the previous two lines of code into a single line:

`X = rand(size(A));`

### Clone Size and Data Type from Existing Array

Create a 2-by-2 matrix of single precision random numbers.

```p = single([3 2; -2 1]); ```

Create an array of random numbers that is the same size and data type as `p`.

```X = rand(size(p),'like',p) ```
```X = 0.5005 0.0596 0.4711 0.6820 ```
`class(X)`
```ans = single```

### Clone Distributed Array

If you have Parallel Computing Toolbox™, create a 1000-by-1000 distributed array of random numbers with underlying data type `single`. For the `distributed` data type, the `'like'` syntax clones the underlying data type in addition to the primary data type.

`p = rand(1000,'single','distributed');`

Create an array of random numbers that is the same size, primary data type, and underlying data type as `p`.

`X = rand(size(p),'like',p);`
`class(X)`
```ans = distributed```
```classUnderlying(X) ```
```ans = single```

## Input Arguments

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### `n` — Size of square matrixinteger value

Size of square matrix, specified as an integer value.

• If `n` is `0`, then `X` is an empty matrix.

• If `n` is negative, then it is treated as `0`.

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

### `sz1,...,szN` — Size of each dimension (as separate arguments)integer values

Size of each dimension, specified as separate arguments of integer values.

• If the size of any dimension is `0`, then `X` is an empty array.

• If the size of any dimension is negative, then it is treated as `0`.

• Beyond the second dimension, `rand` ignores trailing dimensions with a size of 1. For example, `rand(3,1,1,1)` produces a 3-by-1 vector of random numbers.

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

### `sz` — Size of each dimension (as a row vector)integer values

Size of each dimension, specified as a row vector of integer values. Each element of this vector indicates the size of the corresponding dimension:

• If the size of any dimension is `0`, then `X` is an empty array.

• If the size of any dimension is negative, then it is treated as `0`.

• Beyond the second dimension, `rand` ignores trailing dimensions with a size of 1. For example, `rand([3,1,1,1]) ` produces a 3-by-1 vector of random numbers.

Example: `sz = [2,3,4]` creates a 2-by-3-by-4 array.

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

### `typename` — Data type (class) to create`'double'` (default) | `'single'`

Data type (class) to create, specified as the string `'double'`, `'single'`, or the name of another class that provides `rand` support.

Example: `rand(5,'single')`

### `p` — Prototype of array to createnumeric array

Prototype of array to create, specified as a numeric array.

Example: `rand(5,'like',p)`

Data Types: `single` | `double`
Complex Number Support: Yes