npm package: @stdlib/random-strided-lognormal
Description: Fill a strided array with pseudorandom numbers drawn from a lognormal distribution.
Author: The Stdlib Authors
Latest version: 0.2.2

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# Lognormal Random Numbers

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> Fill a strided array with pseudorandom numbers drawn from a [lognormal][@stdlib/random/base/lognormal] distribution.

<section class="installation">

## Installation

```bash
npm install @stdlib/random-strided-lognormal
```

</section>

<section class="usage">

## Usage

```javascript
var lognormal = require( '@stdlib/random-strided-lognormal' );
```

#### lognormal( N, mu, sm, sigma, ss, out, so\[, options] )

Fills a strided array with pseudorandom numbers drawn from a [lognormal][@stdlib/random/base/lognormal] distribution.

```javascript
var Float64Array = require( '@stdlib/array-float64' );

// Create an array:
var out = new Float64Array( 10 );

// Fill the array with pseudorandom numbers:
lognormal( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1 );
```

The function has the following parameters:

-   **N**: number of indexed elements.
-   **mu**: location parameter.
-   **sm**: index increment for `mu`.
-   **sigma**: scale parameter.
-   **ss**: index increment for `sigma`.
-   **out**: output array.
-   **so**: index increment for `out`.

The `N` and stride parameters determine which strided array elements are accessed at runtime. For example, to access every other value in `out`,

```javascript
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

lognormal( 3, [ 2.0 ], 0, [ 5.0 ], 0, out, 2 );
```

Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.

<!-- eslint-disable stdlib/capitalized-comments -->

```javascript
var Float64Array = require( '@stdlib/array-float64' );

// Initial arrays...
var mu0 = new Float64Array( [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ] );
var sigma0 = new Float64Array( [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ] );

// Create offset views...
var mu1 = new Float64Array( mu0.buffer, mu0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var sigma1 = new Float64Array( sigma0.buffer, sigma0.BYTES_PER_ELEMENT*3 ); // start at 4th element

// Create an output array:
var out = new Float64Array( 3 );

// Fill the output array:
lognormal( out.length, mu1, -2, sigma1, 1, out, 1 );
```

The function accepts the following `options`:

-   **prng**: pseudorandom number generator for generating uniformly distributed pseudorandom numbers on the interval `[0,1)`. If provided, the function **ignores** both the `state` and `seed` options. In order to seed the underlying pseudorandom number generator, one must seed the provided `prng` (assuming the provided `prng` is seedable).
-   **seed**: pseudorandom number generator seed.
-   **state**: a [`Uint32Array`][@stdlib/array/uint32] containing pseudorandom number generator state. If provided, the function ignores the `seed` option.
-   **copy**: `boolean` indicating whether to copy a provided pseudorandom number generator state. Setting this option to `false` allows sharing state between two or more pseudorandom number generators. Setting this option to `true` ensures that an underlying generator has exclusive control over its internal state. Default: `true`.

To use a custom PRNG as the underlying source of uniformly distributed pseudorandom numbers, set the `prng` option.

```javascript
var Float64Array = require( '@stdlib/array-float64' );
var minstd = require( '@stdlib/random-base-minstd' );

var opts = {
    'prng': minstd.normalized
};

var out = new Float64Array( 10 );
lognormal( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1, opts );
```

To seed the underlying pseudorandom number generator, set the `seed` option.

```javascript
var Float64Array = require( '@stdlib/array-float64' );

var opts = {
    'seed': 12345
};

var out = new Float64Array( 10 );
lognormal( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1, opts );
```

#### lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo\[, options] )

Fills a strided array with pseudorandom numbers drawn from a [lognormal][@stdlib/random/base/lognormal] distribution using alternative indexing semantics.

```javascript
var Float64Array = require( '@stdlib/array-float64' );

// Create an array:
var out = new Float64Array( 10 );

// Fill the array with pseudorandom numbers:
lognormal.ndarray( out.length, [ 2.0 ], 0, 0, [ 5.0 ], 0, 0, out, 1, 0 );
```

The function has the following additional parameters:

-   **om**: starting index for `mu`.
-   **os**: starting index for `sigma`.
-   **oo**: starting index for `out`.

While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the offset parameters support indexing semantics based on starting indices. For example, to access every other value in `out` starting from the second value,

```javascript
var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];

lognormal.ndarray( 3, [ 2.0 ], 0, 0, [ 5.0 ], 0, 0, out, 2, 1 );
```

The function accepts the same `options` as documented above for `lognormal()`.

</section>

<!-- /.usage -->

<section class="notes">

## Notes

-   If `N <= 0`, both functions leave the output array unchanged.
-   Both functions support array-like objects having getter and setter accessors for array element access.

</section>

<!-- /.notes -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var zeros = require( '@stdlib/array-zeros' );
var zeroTo = require( '@stdlib/array-base-zero-to' );
var logEach = require( '@stdlib/console-log-each' );
var lognormal = require( '@stdlib/random-strided-lognormal' );

// Specify a PRNG seed:
var opts = {
    'seed': 1234
};

// Create an array:
var x1 = zeros( 10, 'float64' );

// Create a list of indices:
var idx = zeroTo( x1.length );

// Fill the array with pseudorandom numbers:
lognormal( x1.length, [ 2.0 ], 0, [ 5.0 ], 0, x1, 1, opts );

// Create a second array:
var x2 = zeros( 10, 'generic' );

// Fill the array with the same pseudorandom numbers:
lognormal( x2.length, [ 2.0 ], 0, [ 5.0 ], 0, x2, 1, opts );

// Print the array contents:
logEach( 'x1[%d] = %.2f; x2[%d] = %.2f', idx, x1, idx, x2 );
```

</section>

<!-- /.examples -->

<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->

<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/random-base/lognormal`][@stdlib/random/base/lognormal]</span><span class="delimiter">: </span><span class="description">log-normally distributed pseudorandom numbers.</span>
-   <span class="package-name">[`@stdlib/random-array/lognormal`][@stdlib/random/array/lognormal]</span><span class="delimiter">: </span><span class="description">create an array containing pseudorandom numbers drawn from a lognormal distribution.</span>

</section>

<!-- /.related -->

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* * *

## Notice

This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.

For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib].

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---

## License

See [LICENSE][stdlib-license].


## Copyright

Copyright &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

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[@stdlib/random/base/lognormal]: https://www.npmjs.com/package/@stdlib/random-base-lognormal

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