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    @stdlib/stats-base-mskmax
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    0.0.9 • Public • Published

    mskmax

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    Calculate the maximum value of a strided array according to a mask.

    Installation

    npm install @stdlib/stats-base-mskmax

    Usage

    var mskmax = require( '@stdlib/stats-base-mskmax' );

    mskmax( N, x, strideX, mask, strideMask )

    Computes the maximum 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 = mskmax( x.length, x, 1, mask, 1 );
    // returns 2.0

    The function has the following parameters:

    • N: number of indexed elements.
    • x: input Array or typed array.
    • strideX: index increment for x.
    • mask: mask Array or typed array. If a mask array element is 0, the corresponding element in x is considered valid and included in computation. If a mask array element is 1, the corresponding element in x 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 maximum 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 = mskmax( N, x, 2, mask, 2 );
    // returns 4.0

    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 = mskmax( N, x1, 2, mask1, 2 );
    // returns 4.0

    mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )

    Computes the maximum 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 = mskmax.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 maximum 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 = mskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
    // returns 4.0

    Notes

    • If N <= 0, both functions return NaN.
    • Depending on the environment, the typed versions (dmskmax, smskmax, etc.) are likely to be significantly more performant.

    Examples

    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 mskmax = require( '@stdlib/stats-base-mskmax' );
    
    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 = mskmax( x.length, x, 1, mask, 1 );
    console.log( v );

    See Also


    Notice

    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.

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    License

    See LICENSE.

    Copyright

    Copyright © 2016-2022. The Stdlib Authors.

    Install

    npm i @stdlib/stats-base-mskmax

    Homepage

    stdlib.io

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    0.0.9

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