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Calculate the minimum value of a strided array according to a mask.
npm install @stdlib/stats-base-mskmin
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tag without installation and bundlers, use the ES Module available on theesm
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branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
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branch (see README).
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var mskmin = require( '@stdlib/stats-base-mskmin' );
Computes the minimum value of a strided array x
according to a mask
.
var x = [ 1.0, -2.0, -4.0, 2.0 ];
var mask = [ 0, 0, 1, 0 ];
var v = mskmin( x.length, x, 1, mask, 1 );
// returns -2.0
The function has the following parameters:
- N: number of indexed elements.
- x: input
Array
ortyped array
. - strideX: index increment for
x
. - mask: mask
Array
ortyped array
. If amask
array element is0
, the corresponding element inx
is considered valid and included in computation. If amask
array element is1
, the corresponding element inx
is considered invalid/missing and excluded from computation. - strideMask: index increment for
mask
.
The N
and stride
parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in x
,
var floor = require( '@stdlib/math-base-special-floor' );
var x = [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, -5.0, -6.0 ];
var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];
var N = floor( x.length / 2 );
var v = mskmin( N, x, 2, mask, 2 );
// returns -7.0
Note that indexing is relative to the first index. To introduce offsets, use typed array
views.
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );
var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = mskmin( N, x1, 2, mask1, 2 );
// returns -2.0
Computes the minimum value of a strided array according to a mask
and using alternative indexing semantics.
var x = [ 1.0, -2.0, -4.0, 2.0 ];
var mask = [ 0, 0, 1, 0 ];
var v = mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 );
// returns -2.0
The function has the following additional parameters:
- offsetX: starting index for
x
. - offsetMask: starting index for
mask
.
While 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
var floor = require( '@stdlib/math-base-special-floor' );
var x = [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ];
var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];
var N = floor( x.length / 2 );
var v = mskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
// returns -2.0
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var mskmin = require( '@stdlib/stats-base-mskmin' );
var mask;
var x;
var i;
x = new Float64Array( 10 );
mask = new Uint8Array( x.length );
for ( i = 0; i < x.length; i++ ) {
if ( randu() < 0.2 ) {
mask[ i ] = 1;
} else {
mask[ i ] = 0;
}
x[ i ] = round( (randu()*100.0) - 50.0 );
}
console.log( x );
console.log( mask );
var v = mskmin( x.length, x, 1, mask, 1 );
console.log( v );
@stdlib/stats-base/dmskmin
: calculate the minimum value of a double-precision floating-point strided array according to a mask.@stdlib/stats-base/min
: calculate the minimum value of a strided array.@stdlib/stats-base/mskmax
: calculate the maximum value of a strided array according to a mask.@stdlib/stats-base/nanmin
: calculate the minimum value of a strided array, ignoring NaN values.@stdlib/stats-base/smskmin
: calculate the minimum value of a single-precision floating-point strided array according to a mask.
This package is part of 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, see the main project repository.
See LICENSE.
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