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Fill a strided array with pseudorandom numbers drawn from a lognormal distribution.
import lognormal from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-strided-lognormal@deno/mod.js';
You can also import the following named exports from the package:
import { ndarray } from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-strided-lognormal@deno/mod.js';
Fills a strided array with pseudorandom numbers drawn from a lognormal distribution.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
// 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
,
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
views.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
// 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 thestate
andseed
options. In order to seed the underlying pseudorandom number generator, one must seed the providedprng
(assuming the providedprng
is seedable). - seed: pseudorandom number generator seed.
- state: a
Uint32Array
containing pseudorandom number generator state. If provided, the function ignores theseed
option. - copy:
boolean
indicating whether to copy a provided pseudorandom number generator state. Setting this option tofalse
allows sharing state between two or more pseudorandom number generators. Setting this option totrue
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.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
import minstd from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-minstd@deno/mod.js';
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.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
var opts = {
'seed': 12345
};
var out = new Float64Array( 10 );
lognormal( out.length, [ 2.0 ], 0, [ 5.0 ], 0, out, 1, opts );
Fills a strided array with pseudorandom numbers drawn from a lognormal distribution using alternative indexing semantics.
import Float64Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float64@deno/mod.js';
// 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
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,
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()
.
- 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.
import zeros from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-zeros@deno/mod.js';
import zeroTo from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-base-zero-to@deno/mod.js';
import logEach from 'https://cdn.jsdelivr.net/gh/stdlib-js/console-log-each@deno/mod.js';
import lognormal from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-strided-lognormal@deno/mod.js';
// 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 );
@stdlib/random-base/lognormal
: log-normally distributed pseudorandom numbers.@stdlib/random-array/lognormal
: create an array containing pseudorandom numbers drawn from a lognormal distribution.
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For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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