Calculate the cumulative maximum absolute value of a strided array.
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> Calculate the cumulative maximum absolute value of a strided array.
``bash`
npm install @stdlib/stats-base-cumaxabs
`javascript`
var cumaxabs = require( '@stdlib/stats-base-cumaxabs' );
#### cumaxabs( N, x, strideX, y, strideY )
Computes the cumulative maximum absolute value of a strided array.
`javascript
var x = [ 1.0, -2.0, 2.0 ];
var y = [ 0.0, 0.0, 0.0 ];
cumaxabs( x.length, x, 1, y, 1 );
// y => [ 1.0, 2.0, 2.0 ]
`
The function has the following parameters:
- N: number of indexed elements.
- x: input [Array][mdn-array] or [typed array][mdn-typed-array].x
- strideX: stride length for .Array
- y: output [][mdn-array] or [typed array][mdn-typed-array].y
- strideY: stride length for .
The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in x,
`javascript
var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
var v = cumaxabs( 4, x, 2, y, 1 );
// y => [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ]
`
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' );
// Initial arrays...
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y0 = new Float64Array( x0.length );
// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
cumaxabs( 4, x1, -2, y1, 1 );
// y0 =>
`
#### cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
Computes the cumulative maximum absolute value of a strided array using alternative indexing semantics.
`javascript
var x = [ 1.0, -2.0, 2.0 ];
var y = [ 0.0, 0.0, 0.0 ];
cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => [ 1.0, 2.0, 2.0 ]
`
The function has the following additional parameters:
- offsetX: starting index for x.y
- offsetY: starting index for .
While [typed array][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum absolute value of every other value in x starting from the second value and to store in the last N elements of y starting from the last element
`javascript
var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
cumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => [ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0 ]
`
- If N <= 0, both functions return y unchanged.dcumaxabs
- Depending on the environment, the typed versions ([][@stdlib/stats/strided/dcumaxabs], [scumaxabs][@stdlib/stats/strided/scumaxabs], etc.) are likely to be significantly more performant.@stdlib/array-base/accessor
- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [][@stdlib/array/base/accessor]).
`javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var Float64Array = require( '@stdlib/array-float64' );
var cumaxabs = require( '@stdlib/stats-base-cumaxabs' );
var x = discreteUniform( 10, 0, 100, {
'dtype': 'float64'
});
var y = new Float64Array( x.length );
console.log( x );
console.log( y );
cumaxabs( x.length, x, 1, y, -1 );
console.log( y );
`
*
- [@stdlib/stats-base/cumax][@stdlib/stats/base/cumax]: calculate the cumulative maximum of a strided array.
- [@stdlib/stats-base/cuminabs][@stdlib/stats/base/cuminabs]: calculate the cumulative minimum absolute value of a strided array.
- [@stdlib/stats-strided/dcumaxabs][@stdlib/stats/strided/dcumaxabs]: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements.
- [@stdlib/stats-strided/scumaxabs][@stdlib/stats/strided/scumaxabs]: calculate the cumulative maximum absolute value of single-precision floating-point strided array elements.
*
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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[mdn-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Array
[@stdlib/array/base/accessor]: https://www.npmjs.com/package/@stdlib/array-base-accessor
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
[@stdlib/stats/base/cumax]: https://www.npmjs.com/package/@stdlib/stats-base-cumax
[@stdlib/stats/base/cuminabs]: https://www.npmjs.com/package/@stdlib/stats-base-cuminabs
[@stdlib/stats/strided/dcumaxabs]: https://www.npmjs.com/package/@stdlib/stats-strided-dcumaxabs
[@stdlib/stats/strided/scumaxabs]: https://www.npmjs.com/package/@stdlib/stats-strided-scumaxabs