time-to-botec/squiggle/node_modules/@stdlib/random/sample/README.md

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# Sample
> Sample elements from an array-like object.
<section class="intro">
</section>
<!-- /.intro -->
<section class="usage">
## Usage
```javascript
var sample = require( '@stdlib/random/sample' );
```
#### sample( x\[, options] )
Samples elements from an `array`-like object. By default, elements are drawn with replacement from `x` to create an output `array` having the same length as `x`.
```javascript
var out = sample( [ 'a', 'b', 'c' ] );
// e.g., returns [ 'a', 'a', 'b' ]
out = sample( [ 3, 6, 9 ] );
// e.g., returns [ 3, 9, 6 ]
var bool = ( out.length === 3 );
// returns true
```
The function accepts the following `options`:
- **size**: sample size. Default: `N = x.length`.
- **probs**: a probability `array`. Default: `[1/N,...,1/N]`.
- **replace**: `boolean` indicating whether to sample from `x` with replacement. Default: `true`.
By default, the function returns an `array` having the same length as `x`. To generate a sample of a different size, set the `size` option.
```javascript
var out = sample( [ 3, 6, 9 ], {
'size': 10
});
// e.g., returns [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]
out = sample( [ 0, 1 ], {
'size': 20
});
// e.g., returns [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]
```
To draw a sample _without_ replacement, set the `replace` option to `false`. In this case, the `size` option cannot be an integer larger than the number of elements in `x`.
```javascript
var out = sample( [ 1, 2, 3, 4, 5, 6 ], {
'replace': false,
'size': 3
});
// e.g., returns [ 6, 1, 5 ]
out = sample( [ 0, 1 ], {
'replace': false
});
// e.g., returns [ 0, 1 ]
```
By default, the probability of sampling an element is the same for all elements. To assign elements different probabilities, set the `probs` option.
```javascript
var x = [ 1, 2, 3, 4, 5, 6 ];
var out = sample( x, {
'probs': [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ]
});
// e.g., returns [ 5, 6, 6, 5, 6, 4 ]
x = [ 1, 2, 3, 4, 5, 6 ];
out = sample( x, {
'probs': [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ],
'size': 3,
'replace': false
});
// e.g., returns [ 6, 4, 1 ]
```
The `probs` option **must** be a numeric array consisting of nonnegative values which sum to one. When sampling _without_ replacement, note that the `probs` option denotes the initial element probabilities which are then updated after each draw.
#### sample.factory( \[pool, ]\[options] )
Returns a `function` to sample elements from an `array`-like object.
```javascript
var mysample = sample.factory();
var out = mysample( [ 0, 1, 2, 3, 4 ] );
// e.g., returns [ 4, 3, 4, 4 ]
```
If provided an array-like object `pool`, the returned function will always sample from the supplied object.
```javascript
var mysample = sample.factory( [ 1, 2, 3, 4, 5, 6 ] );
var out = mysample();
// e.g., returns [ 2, 4, 1, 6, 5, 1 ]
out = mysample();
// e.g., returns [ 5, 2, 3, 6, 1, 4 ]
```
The function accepts the following `options`:
- **seed**: pseudorandom number generator seed.
- **size**: sample size.
- **mutate**: `boolean` indicating whether to mutate the `pool` when sampling without replacement. Default: `false`.
- **replace**: `boolean` indicating whether to sample with replacement. Default: `true`.
To seed the pseudorandom number generator, set the `seed` option.
```javascript
var mysample = sample.factory({
'seed': 430
});
var out = mysample( [ 1, 2, 3, 4, 5, 6 ] );
// e.g., returns [ 1, 1, 1, 5, 4, 4 ]
mysample = sample.factory( [ 1, 2, 3, 4, 5, 6 ], {
'seed': 430
});
out = mysample();
// e.g., returns [ 1, 1, 1, 5, 4, 4 ]
```
To specify a sample size and/or override the default sample size, set the `size` option.
```javascript
var mysample = sample.factory({
'size': 4
});
var out = mysample( [ 0, 1 ] );
// e.g., returns [ 0, 0, 0, 1 ]
// Override the size option...
out = mysample( [ 0, 1 ], {
'size': 1
});
// e.g., returns [ 1 ]
```
By default, the returned function draws samples _with_ replacement. To override the default `replace` strategy, set the `replace` option.
```javascript
var mysample = sample.factory({
'replace': false
});
var out = mysample( [ 1, 2, 3 ] );
// e.g., returns [ 3, 1, 2 ]
```
If a population from which to sample is provided, the underlying `pool` remains constant for each function invocation. To mutate the `pool` by permanently removing observations when sampling _without_ replacement, set the `mutate` option.
```javascript
var mysample = sample.factory( [ 1, 2, 3, 4, 5, 6 ], {
'mutate': true,
'replace': false,
'size': 3,
'seed': 342
});
var out = mysample();
// e.g., returns [ 6, 5, 3 ]
// Override the mutate option...
out = mysample({
'mutate': false
});
// e.g., returns [ 1, 2, 4 ]
out = mysample();
// e.g., returns [ 1, 2, 4 ]
```
The returned function returns `null` after all population units are exhausted.
```javascript
var mysample = sample.factory( [ 1, 2, 3, 4, 5, 6 ], {
'mutate': true,
'replace': false
});
var out = mysample();
// e.g., returns [ 3, 2, 1, 6, 5, 4 ]
out = mysample();
// returns null
```
</section>
<!-- /.usage -->
<section class="examples">
## Examples
<!-- eslint no-undef: "error" -->
```javascript
var sample = require( '@stdlib/random/sample' );
var out;
var x;
// By default, sample uniformly with replacement:
x = [ 'a', 'b', 'c', 'd' ];
out = sample( x, {
'size': 10
});
// e.g., returns [ 'd', 'c', 'b', 'b', 'b', 'd', 'c', 'c', 'b', 'd' ]
// Sample with replacement with custom probabilities:
x = [ 'a', 'b', 'c', 'd' ];
out = sample( x, {
'probs': [ 0.1, 0.1, 0.2, 0.6 ],
'size': 10
});
// e.g., returns [ 'b', 'a', 'c', 'd', 'd', 'd', 'd', 'c', 'd', 'd' ]
// Sample without replacement:
x = [ 'a', 'b', 'c', 'd' ];
out = sample( x, {
'size': 3,
'replace': false
});
// e.g., returns [ 'd', 'c', 'a' ]
// Sample without replacement when (initial) probabilities are nonuniform:
x = [ 1, 2, 3, 4, 5, 6 ];
out = sample( x, {
'probs': [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ],
'size': 3,
'replace': false
});
// e.g., returns [ 2, 3, 6 ]
```
</section>
<!-- /.examples -->
<!-- Section to include cited references. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
<section class="references">
### References
- Knuth, Donald E. 1997. _The Art of Computer Programming, Volume 2 (3rd Ed.): Seminumerical Algorithms_. Boston, MA, USA: Addison-Wesley Longman Publishing Co., Inc.
- Vose, Michael D. 1991. "A linear algorithm for generating random numbers with a given distribution." _IEEE Transactions on Software Engineering_ 17 (9): 97275. doi:[10.1109/32.92917][@vose:1991].
</section>
<!-- /.references -->
<section class="links">
[@vose:1991]: https://doi.org/10.1109/32.92917
</section>
<!-- /.links -->