We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
dmin
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
Calculate the minimum value of a double-precision floating-point strided array.
bash
npm install @stdlib/stats-base-dmin
javascript
var dmin = require( '@stdlib/stats-base-dmin' );
#### dmin( N, x, stride )
Computes the minimum value of a double-precision floating-point strided array x
.
javascript
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;
var v = dmin( N, x, 1 );
// returns -2.0
The function has the following parameters:
- N: number of indexed elements.
- x: input [Float64Array
][@stdlib/array/float64].
- stride: index increment for x
.
The N
and stride
parameters determine which elements in x
are accessed at runtime. For example, to compute the minimum value of every other element in x
,
javascript
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );
var v = dmin( N, x, 2 );
// returns -2.0
Note that indexing is relative to the first index. To introduce an offset, use [typed array
][mdn-typed-array] views.
javascript
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = dmin( N, x1, 2 );
// returns -2.0
#### dmin.ndarray( N, x, stride, offset )
Computes the minimum value of a double-precision floating-point strided array using alternative indexing semantics.
javascript
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;
var v = dmin.ndarray( N, x, 1, 0 );
// returns -2.0
The function has the following additional parameters:
- offset: starting index for x
.
While [typed array
][mdn-typed-array] views mandate a view offset based on the underlying buffer
, the offset
parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in x
starting from the second value
javascript
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );
var v = dmin.ndarray( N, x, 2, 1 );
// returns -2.0
N <= 0
, both functions return NaN
.
javascript
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var dmin = require( '@stdlib/stats-base-dmin' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
console.log( x );
var v = dmin( x.length, x, 1 );
console.log( v );
@stdlib/stats-base/dmax
][@stdlib/stats/base/dmax]: calculate the maximum value of a double-precision floating-point strided array.
- [@stdlib/stats-base/dnanmin
][@stdlib/stats/base/dnanmin]: calculate the minimum value of a double-precision floating-point strided array, ignoring NaN values.
- [@stdlib/stats-base/min
][@stdlib/stats/base/min]: calculate the minimum value of a strided array.
- [@stdlib/stats-base/smin
][@stdlib/stats/base/smin]: calculate the minimum value of a single-precision floating-point strided array.