@stdlib/strided/base/docs/types/index.d.ts

Strided.

/*
* @license Apache-2.0
*
* Copyright (c) 2021 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

// TypeScript Version: 4.1

/* eslint-disable max-lines */

import binary = require( './../../../base/binary' );
import binaryAddonDispatch = require( './../../../base/binary-addon-dispatch' );
import binaryDtypeSignatures = require( './../../../base/binary-dtype-signatures' );
import binarySignatureCallbacks = require( './../../../base/binary-signature-callbacks' );
import cmap = require( './../../../base/cmap' );
import dmap = require( './../../../base/dmap' );
import dmap2 = require( './../../../base/dmap2' );
import dmskmap = require( './../../../base/dmskmap' );
import dmskmap2 = require( './../../../base/dmskmap2' );
import dtypeEnum2Str = require( './../../../base/dtype-enum2str' );
import dtypeResolveEnum = require( './../../../base/dtype-resolve-enum' );
import dtypeResolveStr = require( './../../../base/dtype-resolve-str' );
import dtypeStr2Enum = require( './../../../base/dtype-str2enum' );
import mapBy = require( './../../../base/map-by' );
import mapBy2 = require( './../../../base/map-by2' );
import maxViewBufferIndex = require( './../../../base/max-view-buffer-index' );
import metaDataProps = require( './../../../base/meta-data-props' );
import minViewBufferIndex = require( './../../../base/min-view-buffer-index' );
import mskunary = require( './../../../base/mskunary' );
import mskunaryAddonDispatch = require( './../../../base/mskunary-addon-dispatch' );
import mskunaryDtypeSignatures = require( './../../../base/mskunary-dtype-signatures' );
import mskunarySignatureCallbacks = require( './../../../base/mskunary-signature-callbacks' );
import nullary = require( './../../../base/nullary' );
import nullaryAddonDispatch = require( './../../../base/nullary-addon-dispatch' );
import offsetView = require( './../../../base/offset-view' );
import quaternary = require( './../../../base/quaternary' );
import quinary = require( './../../../base/quinary' );
import reinterpretBoolean = require( './../../../base/reinterpret-boolean' );
import reinterpretComplex = require( './../../../base/reinterpret-complex' );
import reinterpretComplex64 = require( './../../../base/reinterpret-complex64' );
import reinterpretComplex128 = require( './../../../base/reinterpret-complex128' );
import smap = require( './../../../base/smap' );
import smap2 = require( './../../../base/smap2' );
import smskmap = require( './../../../base/smskmap' );
import smskmap2 = require( './../../../base/smskmap2' );
import stride2offset = require( './../../../base/stride2offset' );
import ternary = require( './../../../base/ternary' );
import unary = require( './../../../base/unary' );
import unaryAddonDispatch = require( './../../../base/unary-addon-dispatch' );
import unaryBy = require( './../../../base/unary-by' );
import unaryDtypeSignatures = require( './../../../base/unary-dtype-signatures' );
import unarySignatureCallbacks = require( './../../../base/unary-signature-callbacks' );
import zmap = require( './../../../base/zmap' );

/**
* Interface describing the `base` namespace.
*/
interface Namespace {
	/**
	* Applies a binary callback to strided input array elements and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing two input arrays and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the input and output arrays
	* @param fcn - binary callback
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function add( x, y ) {
	*     return x + y;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1 ];
	*
	* ns.binary( [ x, y, z ], shape, strides, add );
	*
	* console.log( z );
	* // => <Float64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function add( x, y ) {
	*     return x + y;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1 ];
	* var offsets = [ 0, 0, 0 ];
	*
	* ns.binary.ndarray( [ x, y, z ], shape, strides, offsets, add );
	*
	* console.log( z );
	* // => <Float64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*/
	binary: typeof binary;

	/**
	* Returns a function which dispatches to a native add-on applying a unary function to two input strided arrays.
	*
	* @param addon - add-on function
	* @param fallback - fallback function
	* @returns dispatch function
	*
	* @example
	* function addon( N, dtypeX, x, strideX, dtypeY, y, strideY, dtypeZ, z, strideZ ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, dtypeY, y, strideY, dtypeZ, z, strideZ ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.binaryAddonDispatch function:
	* var f = ns.binaryAddonDispatch( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.binaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 'generic', [ 3, 4 ], 1, 'generic', [ 0, 0 ], 1 );
	*
	* @example
	* function addon( N, dtypeX, x, strideX, dtypeY, y, strideY, dtypeZ, z, strideZ ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, dtypeZ, z, strideZ, offsetZ ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.binaryAddonDispatch function:
	* var f = ns.binaryAddonDispatch.ndarray( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.binaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 0, 'generic', [ 3, 4 ], 1, 0, 'generic', [ 0, 0 ], 1, 0 );
	*/
	binaryAddonDispatch: typeof binaryAddonDispatch;

	/**
	* Generates a list of binary interface signatures from strided array data types.
	*
	* ## Notes
	*
	* -   The function returns a strided array having a stride length of `3` (i.e., every `3` elements define a binary interface signature).
	* -   For each signature (i.e., set of three consecutive non-overlapping strided array elements), the first two elements are the input data types and the third element is the return data type.
	* -   All signatures follow type promotion rules.
	*
	* @param dtypes1 - list of supported data types for the first argument
	* @param dtypes2 - list of supported data types for the second argument
	* @param dtypes3 - list of supported data types for the output
	* @param options - options
	* @param options.enums - boolean flag indicating whether to return signatures as a list of enumeration constants
	* @throws must provide recognized data types
	* @returns strided array containing binary interface signatures
	*
	* @example
	* var dtypes = [
	*     'float64',
	*     'float32',
	*     'int32',
	*     'uint8'
	* ];
	*
	* var sigs = ns.binaryDtypeSignatures( dtypes, dtypes, dtypes );
	* // returns [ 'float32', 'float32', 'float32', ... ]
	*/
	binaryDtypeSignatures: typeof binaryDtypeSignatures;

	/**
	* Assigns callbacks to binary interfaces according to type promotion rules.
	*
	* ## Notes
	*
	* -   The function assumes that the provided signature array has the following properties:
	*
	*     -   a strided array having a stride length of `3` (i.e., every `3` elements define a binary interface signature).
	*     -   for each signature (i.e., set of three consecutive non-overlapping strided array elements), the first two elements are the input data types and the third element is the return data type.
	*     -   all signatures follow type promotion rules.
	*
	* @param table - callback table
	* @param table.default - default callback
	* @param table.complex64 - callback for single-precision complex floating-point numbers
	* @param table.complex128 - callback for double-precision complex floating-point numbers
	* @param signatures - strided array containing binary interface signatures
	* @returns list of callbacks
	*
	* @example
	* var signatures = require( './../../../base/binary-dtype-signatures' );
	* var add = require( '@stdlib/math/base/ops/add' );
	* var cadd = require( '@stdlib/complex/float64/base/add' );
	* var caddf = require( '@stdlib/complex/float32/base/add' );
	*
	* var dtypes = [
	*     'float64',
	*     'float32',
	*     'int32',
	*     'uint8'
	* ];
	*
	* var sigs = signatures( dtypes, dtypes, dtypes );
	* // returns [...]
	*
	* var table = {
	*     'default': add,
	*     'complex64': caddf,
	*     'complex128': cadd
	* };
	*
	* var list = ns.binarySignatureCallbacks( table, sigs );
	* // returns [...]
	*/
	binarySignatureCallbacks: typeof binarySignatureCallbacks;

	/**
	* Applies a unary function to a single-precision complex floating-point strided input array and assigns results to a single-precision complex floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - destination array
	* @param strideY - `y` stride length
	* @param fcn - unary function to apply
	* @returns `y`
	*
	* @example
	* var Complex64Array = require( '@stdlib/array/complex64' );
	* var real = require( '@stdlib/complex/float64/real' );
	* var imag = require( '@stdlib/complex/float64/imag' );
	* var Complex64 = require( '@stdlib/complex/float32/ctor' );
	*
	* function scale( x ) {
	*     var re = real( x );
	*     var im = imag( x );
	*     return new Complex64( re*10.0, im*10.0 );
	* }
	*
	* var x = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0 ] );
	* var y = new Complex64Array( x.length );
	*
	* ns.cmap( x.length, x, 1, y, 1, scale );
	*
	* var v = y.get( 0 );
	* // returns <Complex64>
	*
	* var re = real( v );
	* // returns 10.0
	*
	* var im = imag( v );
	* // returns 10.0
	*
	* @example
	* var Complex64Array = require( '@stdlib/array/complex64' );
	* var real = require( '@stdlib/complex/float64/real' );
	* var imag = require( '@stdlib/complex/float64/imag' );
	* var Complex64 = require( '@stdlib/complex/float32/ctor' );
	*
	* function scale( x ) {
	*     var re = real( x );
	*     var im = imag( x );
	*     return new Complex64( re*10.0, im*10.0 );
	* }
	*
	* var x = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0, 4.0, 4.0, 5.0, 5.0 ] );
	* var y = new Complex64Array( x.length );
	*
	* ns.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, scale );
	*
	* var v = y.get( 0 );
	* // returns <Complex64>
	*
	* var re = real( v );
	* // returns 10.0
	*
	* var im = imag( v );
	* // returns 10.0
	*/
	cmap: typeof cmap;

	/**
	* Applies a unary function to a double-precision floating-point strided input array and assigns results to a double-precision floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - destination array
	* @param strideY - `y` stride length
	* @param fcn - unary function to apply
	* @returns `y`
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.dmap( x.length, x, 1, y, 1, identity );
	* // y => <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, identity );
	* // y => <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]
	*/
	dmap: typeof dmap;

	/**
	* Applies a binary function to double-precision floating-point strided input arrays and assigns results to a double-precision floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - input array
	* @param strideY - `y` stride length
	* @param z - destination array
	* @param strideZ - `z` stride length
	* @param fcn - binary function to apply
	* @returns `z`
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var add = require( '@stdlib/math/base/ops/add' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.dmap2( x.length, x, 1, y, 1, z, 1, add );
	* // z => <Float64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var add = require( '@stdlib/math/base/ops/add' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, add );
	* // z => <Float64Array>[ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*/
	dmap2: typeof dmap2;

	/**
	* Applies a unary function to a double-precision floating-point strided input array according to a strided mask array and assigns results to a double-precision floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param mask - mask array
	* @param strideMask - `mask` stride length
	* @param y - destination array
	* @param strideY - `y` stride length
	* @param fcn - unary function to apply
	* @returns `y`
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	* var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.dmskmap( x.length, x, 1, m, 1, y, 1, identity );
	* // y => <Float64Array>[ 1.0, 2.0, 0.0, 4.0, 5.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	* var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, identity );
	* // y => <Float64Array>[ 1.0, 2.0, 0.0, 4.0, 5.0 ]
	*/
	dmskmap: typeof dmskmap;

	/**
	* Applies a binary function to double-precision floating-point strided input arrays according to a strided mask array and assigns results to a double-precision floating-point strided output array
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - input array
	* @param strideY - `y` stride length
	* @param mask - mask array
	* @param strideMask - `mask` stride length
	* @param z - destination array
	* @param strideZ - `z` stride length
	* @param fcn - binary function to apply
	* @returns `z`
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	* var add = require( '@stdlib/math/base/ops/add' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	*
	* ns.dmskmap2( x.length, x, 1, m, 1, y, 1, add );
	* // z => <Float64Array>[ 2.0, 4.0, 0.0, 8.0, 10.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	* var add = require( '@stdlib/math/base/ops/add' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	*
	* ns.dmskmap2.ndarray( x.length, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, add );
	* // z => <Float64Array>[ 2.0, 4.0, 0.0, 8.0, 10.0 ]
	*/
	dmskmap2: typeof dmskmap2;

	/**
	* Returns the data type string associated with a strided array data type enumeration constant.
	*
	* @param dtype - data type enumeration constant
	* @returns data type string
	*
	* @example
	* var str2enum = require( './../../../base/dtype-str2enum' );
	*
	* var v = str2enum( 'float64' );
	* // returns <number>
	*
	* var dt = ns.dtypeEnum2Str( v );
	* // returns 'float64'
	*/
	dtypeEnum2Str: typeof dtypeEnum2Str;

	/**
	* Returns the enumeration constant associated with a strided array data type value.
	*
	* ## Notes
	*
	* -   Downstream consumers of this function should **not** rely on specific integer values (e.g., `INT8 == 0`). Instead, the function should be used in an opaque manner.
	*
	* @param dtype - data type value
	* @returns enumeration constant
	*
	* @example
	* var v = ns.dtypeResolveEnum( 'float64' );
	* // returns <number>
	*/
	dtypeResolveEnum: typeof dtypeResolveEnum;

	/**
	* Returns the data type string associated with a strided array data type value.
	*
	* @param dtype - data type value
	* @returns data type string
	*
	* @example
	* var str2enum = require( './../../../base/dtype-str2enum' );
	*
	* var v = ns.dtypeResolveStr( str2enum( 'float64' ) );
	* // returns 'float64'
	*/
	dtypeResolveStr: typeof dtypeResolveStr;

	/**
	* Returns the enumeration constant associated with a strided array data type string.
	*
	* ## Notes
	*
	* -   Downstream consumers of this function should **not** rely on specific integer values (e.g., `INT8 == 0`). Instead, the function should be used in an opaque manner.
	*
	* @param dtype - data type string
	* @returns enumeration constant
	*
	* @example
	* var v = ns.dtypeStr2Enum( 'float64' );
	* // returns <number>
	*/
	dtypeStr2Enum: typeof dtypeStr2Enum;

	/**
	* Applies a unary function to each element retrieved from a strided input array according to a callback function and assigns results to a strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - destination array
	* @param strideY - `y` stride length
	* @param fcn - unary function to apply to callback return values
	* @param clbk - callback function
	* @param thisArg - callback execution context
	* @returns `y`
	*
	* @example
	* var abs = require( '@stdlib/math/base/special/abs' );
	*
	* function accessor( v ) {
	*     return v * 2.0;
	* }
	*
	* var x = [ 1.0, -2.0, 3.0, -4.0, 5.0 ];
	* var y = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
	*
	* ns.mapBy( x.length, x, 1, y, 1, abs, accessor );
	* // y => [ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*
	* @example
	* var abs = require( '@stdlib/math/base/special/abs' );
	*
	* function accessor( v ) {
	*     return v * 2.0;
	* }
	*
	* var x = [ 1.0, -2.0, 3.0, -4.0, 5.0 ];
	* var y = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
	*
	* ns.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, abs, accessor );
	* // y => [ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*/
	mapBy: typeof mapBy;

	/**
	* Applies a binary function to each pair of elements retrieved from strided input arrays according to a callback function and assigns results to a strided output array
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - input array
	* @param strideY - `y` stride length
	* @param z - destination array
	* @param strideZ - `z` stride length
	* @param fcn - binary function to apply to callback return values
	* @param clbk - callback function which returns an array-like object containing two values
	* @param thisArg - callback execution context
	* @returns `z`
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add' );
	*
	* function accessor( values ) {
	*     values[ 0 ] *= 2.0;
	*     values[ 1 ] *= 2.0;
	* }
	*
	* var x = [ 1.0, -2.0, 3.0, -4.0, 5.0 ];
	* var y = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
	* var z = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
	*
	* ns.mapBy2( x.length, x, 1, y, 1, z, 1, add, accessor );
	* // z => [ 4.0, 0.0, 12.0, 0.0, 20.0 ]
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add' );
	*
	* function accessor( values ) {
	*     values[ 0 ] *= 2.0;
	*     values[ 1 ] *= 2.0;
	* }
	*
	* var x = [ 1.0, -2.0, 3.0, -4.0, 5.0 ];
	* var y = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];
	* var z = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
	*
	* ns.mapBy2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, add, accessor );
	* // z => [ 4.0, 0.0, 12.0, 0.0, 20.0 ]
	*/
	mapBy2: typeof mapBy2;

	/**
	* Returns the maximum accessible index based on a set of provided strided array parameters.
	*
	* @param N - number of indexed elements
	* @param stride - stride length
	* @param offset - starting index
	* @returns maximum accessible index
	*
	* @example
	* var idx = ns.maxViewBufferIndex( 3, 2, 10 );
	* // returns 14
	*/
	maxViewBufferIndex: typeof maxViewBufferIndex;

	/**
	* Defines non-enumerable read-only properties which expose strided array function meta data.
	*
	* @param meta - function meta data
	* @param meta.nargs - total number of arguments (excluding offsets)
	* @param meta.nin - total number of input arrays
	* @param meta.nout - total number of output arrays
	* @param dtypes - list of strided array data types
	* @param obj - object on which to define properties
	* @param bool - boolean indicating whether the provided object should describe an "ndarray" function interface
	* @returns object on which properties were defined
	*
	* @example
	* // Define strided array function meta data:
	* var meta = {
	*     'nargs': 7,
	*     'nin': 1,
	*     'nout': 1
	* };
	*
	* // Define the list of strided array data types:
	* var dtypes = [
	*     'float64', 'float64',
	*     'float32', 'float32',
	*     'generic', 'generic'
	* ];
	*
	* // Define an object/function on which to set the properties:
	* var obj = {};
	*
	* // Set the properties:
	* ns.metaDataProps( meta, dtypes, obj, false );
	*/
	metaDataProps: typeof metaDataProps;

	/**
	* Returns the minimum accessible index based on a set of provided strided array parameters.
	*
	* @param N - number of indexed elements
	* @param stride - stride length
	* @param offset - starting index
	* @returns minimum accessible index
	*
	* @example
	* var idx = ns.minViewBufferIndex( 3, -2, 10 );
	* // returns 6
	*/
	minViewBufferIndex: typeof minViewBufferIndex;

	/**
	* Applies a unary callback to elements in a strided input array according to elements in a strided mask array and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing one input array, a mask array, and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the strided arrays
	* @param fcn - unary callback
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	*
	* function scale( x ) {
	*     return x * 10.0;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	* var y = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1 ];
	*
	* ns.mskunary( [ x, m, y ], shape, strides, scale );
	*
	* console.log( y );
	* // => <Float64Array>[ 10.0, 20.0, 0.0, 40.0, 50.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	*
	* function scale( x ) {
	*     return x * 10.0;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	* var y = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1 ];
	* var offsets = [ 0, 0, 0 ];
	*
	* ns.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, scale );
	*
	* console.log( y );
	* // => <Float64Array>[ 10.0, 20.0, 0.0, 40.0, 50.0 ]
	*/
	mskunary: typeof mskunary;

	/**
	* Returns a function which dispatches to a native add-on applying a unary function to an input strided array according to a mask strided array.
	*
	* @param addon - add-on function
	* @param fallback - fallback function
	* @returns dispatch function
	*
	* @example
	* function addon( N, dtypeX, x, strideX, dtypeMask, mask, strideMask, dtypeY, y, strideY ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, dtypeMask, mask, strideMask, dtypeY, y, strideY ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.mskunaryAddonDispatch function:
	* var f = ns.mskunaryAddonDispatch( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.mskunaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 'generic', [ 0, 0 ], 1, 'generic', [ 0, 0 ], 1 );
	*
	* @example
	* function addon( N, dtypeX, x, strideX, dtypeMask, mask, strideMask, dtypeY, y, strideY ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, offsetX, dtypeMask, mask, strideMask, offsetMask, dtypeY, y, strideY, offsetY ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.mskunaryAddonDispatch function:
	* var f = ns.mskunaryAddonDispatch.ndarray( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.mskunaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 0, 'generic', [ 0, 0 ], 1, 0, 'generic', [ 0, 0 ], 1, 0 );
	*/
	mskunaryAddonDispatch: typeof mskunaryAddonDispatch;

	/**
	* Generates a list of masked unary interface signatures from strided array data types.
	*
	* ## Notes
	*
	* -   The function returns a strided array having a stride length of `3` (i.e., every `3` elements define a masked unary interface signature).
	* -   For each signature (i.e., set of three consecutive non-overlapping strided array elements), the first element is the input data type, the second element is the mask data type, and the last element is the return data type.
	* -   All signatures follow type promotion rules.
	* -   The mask array data type is always `uint8`.
	*
	* @param dtypes1 - list of supported data types for the first argument
	* @param dtypes2 - list of supported data types for the output argument
	* @param options - options
	* @param options.enums - boolean flag indicating whether to return signatures as a list of enumeration constants
	* @throws must provide recognized data types
	* @returns strided array containing masked unary interface signatures
	*
	* @example
	* var dtypes = [
	*     'float64',
	*     'float32',
	*     'int32',
	*     'uint8'
	* ];
	*
	* var sigs = ns.mskunaryDtypeSignatures( dtypes, dtypes );
	* // e.g., returns [ 'float32', 'uint8', 'float32', ... ]
	*/
	mskunaryDtypeSignatures: typeof mskunaryDtypeSignatures;

	/**
	* Assigns callbacks to masked unary interfaces according to type promotion rules.
	*
	* ## Notes
	*
	* -   The function assumes that the provided signature array has the following properties:
	*
	*     -   a strided array having a stride length of `3` (i.e., every `3` elements define a masked unary interface signature).
	*     -   for each signature (i.e., set of three consecutive non-overlapping strided array elements), the first element is the input data type, the second element is the mask data type, and the last element is the return data type.
	*     -   all signatures (excluding the mask data type) follow type promotion rules.
	*
	* @param table - callback table
	* @param table.default - default callback
	* @param table.complex64 - callback for single-precision complex floating-point numbers
	* @param table.complex128 - callback for double-precision complex floating-point numbers
	* @param signatures - strided array containing masked unary interface signatures
	* @returns list of callbacks
	*
	* @example
	* var signatures = require( './../../../base/mskunary-dtype-signatures' );
	* var identity = require( '@stdlib/math/base/special/identity' );
	* var cidentity = require( '@stdlib/math/base/special/cidentity' );
	* var cidentityf = require( '@stdlib/math/base/special/cidentityf' );
	*
	* var dtypes = [
	*     'float64',
	*     'float32',
	*     'int32',
	*     'uint8'
	* ];
	*
	* var sigs = signatures( dtypes, dtypes );
	* // returns [...]
	*
	* var table = {
	*     'default': identity,
	*     'complex64': cidentityf,
	*     'complex128': cidentity
	* };
	*
	* var list = ns.mskunarySignatureCallbacks( table, sigs );
	* // returns [...]
	*/
	mskunarySignatureCallbacks: typeof mskunarySignatureCallbacks;

	/**
	* Applies a nullary callback and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride length for the output array
	* @param fcn - nullary callback
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function fill() {
	*     return 3.0;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	*
	* var shape = [ x.length ];
	* var strides = [ 1 ];
	*
	* ns.nullary( [ x ], shape, strides, fill );
	*
	* console.log( x );
	* // => <Float64Array>[ 3.0, 3.0, 3.0, 3.0, 3.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function fill() {
	*     return 3.0;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	*
	* var shape = [ x.length ];
	* var strides = [ 1 ];
	* var offsets = [ 0 ];
	*
	* ns.nullary.ndarray( [ x ], shape, strides, offsets, fill );
	*
	* console.log( x );
	* // => <Float64Array>[ 3.0, 3.0, 3.0, 3.0, 3.0 ]
	*/
	nullary: typeof nullary;

	/**
	* Returns a function which dispatches to a native add-on applying a nullary function.
	*
	* @param addon - add-on function
	* @param fallback - fallback function
	* @returns dispatch function
	*
	* @example
	* function addon( N, dtypeX, x, strideX ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.nullaryAddonDispatch function:
	* var f = ns.nullaryAddonDispatch( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.nullaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1 );
	*
	* @example
	* function addon( N, dtypeX, x, strideX ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, offsetX ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.nullaryAddonDispatch function:
	* var f = ns.nullaryAddonDispatch.ndarray( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.nullaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 0 );
	*/
	nullaryAddonDispatch: typeof nullaryAddonDispatch;

	/**
	* Returns a typed array view having the same data type as a provided input typed array and starting at a specified index offset.
	*
	* @param x - input array
	* @param offset - starting index
	* @returns typed array view
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( 10 );
	*
	* var out = ns.offsetView( x, 0 );
	* // returns <Float64Array>
	*
	* var bool = ( out.buffer === x.buffer );
	*/
	offsetView: typeof offsetView;

	/**
	* Applies a quaternary callback to strided input array elements and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing four input arrays and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the input and output arrays
	* @param fcn - quaternary callback
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add4' );
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var u = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1, 1, 1 ];
	*
	* ns.quaternary( [ x, y, z, w, u ], shape, strides, add );
	*
	* console.log( u );
	* // => <Float64Array>[ 4.0, 8.0, 12.0, 16.0, 20.0 ]
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add4' );
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var u = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1, 1, 1 ];
	* var offsets = [ 0, 0, 0, 0, 0 ];
	*
	* ns.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, add );
	*
	* console.log( u );
	* // => <Float64Array>[ 4.0, 8.0, 12.0, 16.0, 20.0 ]
	*/
	quaternary: typeof quaternary;

	/**
	* Applies a quinary callback to strided input array elements and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing five input arrays and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the input and output arrays
	* @param fcn - quinary callback
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add5' );
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var v = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1, 1, 1, 1 ];
	*
	* ns.quinary( [ x, y, z, w, u, v ], shape, strides, add );
	*
	* console.log( v );
	* // => <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add5' );
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var v = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1, 1, 1, 1 ];
	* var offsets = [ 0, 0, 0, 0, 0, 0 ];
	*
	* ns.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, add );
	*
	* console.log( v );
	* // => <Float64Array>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
	*/
	quinary: typeof quinary;

	/**
	* Reinterprets a `BooleanArray` as a `Uint8Array`.
	*
	* @param x - input array
	* @param offset - starting index
	* @returns `Uint8Array` view
	*
	* @example
	* var BooleanArray = require( '@stdlib/array/bool' );
	*
	* var x = new BooleanArray( 10 );
	*
	* var out = ns.reinterpretBoolean( x, 0 );
	* // returns <Uint8Array>
	*
	* var bool = ( out.buffer === x.buffer );
	* // returns true
	*/
	reinterpretBoolean: typeof reinterpretBoolean;

	/**
	* Reinterprets a `Complex128Array` as a `Float64Array`.
	*
	* @param x - input array
	* @param offset - starting index
	* @returns `Float64Array` view
	*
	* @example
	* var Complex128Array = require( '@stdlib/array/complex128' );
	*
	* var x = new Complex128Array( 10 );
	*
	* var out = ns.reinterpretComplex( x, 0 );
	* // returns <Float64Array>
	*
	* var bool = ( out.buffer === x.buffer );
	*/
	reinterpretComplex: typeof reinterpretComplex;

	/**
	* Reinterprets a `Complex64Array` as a `Float32Array`.
	*
	* @param x - input array
	* @param offset - starting index
	* @returns `Float32Array` view
	*
	* @example
	* var Complex64Array = require( '@stdlib/array/complex64' );
	*
	* var x = new Complex64Array( 10 );
	*
	* var out = ns.reinterpretComplex64( x, 0 );
	* // returns <Float32Array>
	*
	* var bool = ( out.buffer === x.buffer );
	*/
	reinterpretComplex64: typeof reinterpretComplex64;

	/**
	* Reinterprets a `Complex128Array` as a `Float64Array`.
	*
	* @param x - input array
	* @param offset - starting index
	* @returns `Float64Array` view
	*
	* @example
	* var Complex128Array = require( '@stdlib/array/complex128' );
	*
	* var x = new Complex128Array( 10 );
	*
	* var out = ns.reinterpretComplex128( x, 0 );
	* // returns <Float64Array>
	*
	* var bool = ( out.buffer === x.buffer );
	*/
	reinterpretComplex128: typeof reinterpretComplex128;

	/**
	* Applies a unary function to a single-precision floating-point strided input array and assigns results to a single-precision floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - destination array
	* @param strideY - `y` stride length
	* @param fcn - unary function to apply
	* @returns `y`
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.smap( x.length, x, 1, y, 1, identity );
	* // y => <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.smap.ndarray( x.length, x, 1, 0, y, 1, 0, identity );
	* // y => <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]
	*/
	smap: typeof smap;

	/**
	* Applies a binary function to single-precision floating-point strided input arrays and assigns results to a single-precision floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - input array
	* @param strideY - `y` stride length
	* @param z - destination array
	* @param strideZ - `z` stride length
	* @param fcn - binary function to apply
	* @returns `z`
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	* var addf = require( '@stdlib/math/base/ops/addf' );
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.smap2( x.length, x, 1, y, 1, z, 1, addf );
	* // z => <Float32Array>[ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	* var addf = require( '@stdlib/math/base/ops/addf' );
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, addf );
	* // z => <Float32Array>[ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*/
	smap2: typeof smap2;

	/**
	* Applies a unary function to a single-precision floating-point strided input array according to a strided mask array and assigns results to a single-precision floating-point strided output array.
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param mask - mask array
	* @param strideMask - `mask` stride length
	* @param y - destination array
	* @param strideY - `y` stride length
	* @param fcn - unary function to apply
	* @returns `y`
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	* var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.smskmap( x.length, x, 1, m, 1, y, 1, identity );
	* // y => <Float32Array>[ 1.0, 2.0, 0.0, 4.0, 5.0 ]
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	*
	* function identity( x ) {
	*     return x;
	* }
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	* var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	*
	* ns.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, identity );
	* // y => <Float32Array>[ 1.0, 2.0, 0.0, 4.0, 5.0 ]
	*/
	smskmap: typeof smskmap;

	/**
	* Applies a binary function to single-precision floating-point strided input arrays according to a strided mask array and assigns results to a single-precision floating-point strided output array
	*
	* @param N - number of indexed elements
	* @param x - input array
	* @param strideX - `x` stride length
	* @param y - input array
	* @param strideY - `y` stride length
	* @param mask - mask array
	* @param strideMask - `mask` stride length
	* @param z - destination array
	* @param strideZ - `z` stride length
	* @param fcn - binary function to apply
	* @returns `z`
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	* var addf = require( '@stdlib/math/base/ops/addf' );
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	*
	* ns.smskmap2( x.length, x, 1, m, 1, y, 1, addf );
	* // z => <Float32Array>[ 2.0, 4.0, 0.0, 8.0, 10.0 ]
	*
	* @example
	* var Float32Array = require( '@stdlib/array/float32' );
	* var Uint8Array = require( '@stdlib/array/uint8' );
	* var addf = require( '@stdlib/math/base/ops/addf' );
	*
	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0, 0.0 ] );
	* var m = new Uint8Array( [ 0, 0, 1, 0, 0 ] );
	*
	* ns.smskmap2.ndarray( x.length, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, addf );
	* // z => <Float32Array>[ 2.0, 4.0, 0.0, 8.0, 10.0 ]
	*/
	smskmap2: typeof smskmap2;

	/**
	* Returns the index offset which specifies the location of the first indexed value in a strided array.
	*
	* @param N - number of indexed elements
	* @param stride - index increment
	* @returns offset
	*
	* @example
	* var offset = ns.stride2offset( 10, -10 );
	* // returns 90
	*/
	stride2offset: typeof stride2offset;

	/**
	* Applies a ternary callback to strided input array elements and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing three input arrays and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the input and output arrays
	* @param fcn - ternary callback
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add3' );
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var w = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1, 1 ];
	*
	* ns.ternary( [ x, y, z, w ], shape, strides, add );
	*
	* console.log( w );
	* // => <Float64Array>[ 3.0, 6.0, 9.0, 12.0, 15.0 ]
	*
	* @example
	* var add = require( '@stdlib/math/base/ops/add3' );
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var w = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1, 1, 1 ];
	* var offsets = [ 0, 0, 0, 0 ];
	*
	* ns.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, add );
	*
	* console.log( w );
	* // => <Float64Array>[ 3.0, 6.0, 9.0, 12.0, 15.0 ]
	*/
	ternary: typeof ternary;

	/**
	* Applies a unary callback to elements in a strided input array and assigns results to elements in a strided output array.
	*
	* @param arrays - array-like object containing one input array and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the input and output arrays
	* @param fcn - unary callback
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function scale( x ) {
	*     return x * 10.0;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1 ];
	*
	* ns.unary( [ x, y ], shape, strides, scale );
	*
	* console.log( y );
	* // => <Float64Array>[ 10.0, 20.0, 30.0, 40.0, 50.0 ]
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	*
	* function scale( x ) {
	*     return x * 10.0;
	* }
	*
	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
	* var y = new Float64Array( x.length );
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1 ];
	* var offsets = [ 0, 0 ];
	*
	* ns.unary.ndarray( [ x, y ], shape, strides, offsets, scale );
	*
	* console.log( y );
	* // => <Float64Array>[ 10.0, 20.0, 30.0, 40.0, 50.0 ]
	*/
	unary: typeof unary;

	/**
	* Returns a function which dispatches to a native add-on applying a unary function to an input strided array.
	*
	* @param addon - add-on function
	* @param fallback - fallback function
	* @returns dispatch function
	*
	* @example
	* function addon( N, dtypeX, x, strideX, dtypeY, y, strideY ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, dtypeY, y, strideY ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.unaryAddonDispatch function:
	* var f = ns.unaryAddonDispatch( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.unaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 'generic', [ 0, 0 ], 1 );
	*
	* @example
	* function addon( N, dtypeX, x, strideX, dtypeY, y, strideY ) {
	*     // Call into native add-on...
	* }
	*
	* function fallback( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY ) {
	*     // Fallback JavaScript implementation...
	* }
	*
	* // Create a ns.unaryAddonDispatch function:
	* var f = ns.unaryAddonDispatch.ndarray( addon, fallback );
	*
	* // ...
	*
	* // Invoke the ns.unaryAddonDispatch function with strided array arguments:
	* f( 2, 'generic', [ 1, 2 ], 1, 0, 'generic', [ 0, 0 ], 1, 0 );
	*/
	unaryAddonDispatch: typeof unaryAddonDispatch;

	/**
	* Applies a unary function to each element retrieved from a strided input array according to a callback function and assigns results to a strided output array.
	*
	* @param arrays - array-like object containing one input array and one output array
	* @param shape - array-like object containing a single element, the number of indexed elements
	* @param strides - array-like object containing the stride lengths for the input and output arrays
	* @param fcn - unary function to apply to callback return values
	* @param clbk - callback function
	* @param thisArg - callback execution context
	*
	* @example
	* var abs = require( '@stdlib/math/base/special/abs' );
	*
	* function accessor( v ) {
	*     return v * 2.0;
	* }
	*
	* var x = [ 1.0, -2.0, 3.0, -4.0, 5.0 ];
	* var y = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1 ];
	*
	* ns.unaryBy( [ x, y ], shape, strides, abs, accessor );
	* // y => [ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*
	* @example
	* var abs = require( '@stdlib/math/base/special/abs' );
	*
	* function accessor( v ) {
	*     return v * 2.0;
	* }
	*
	* var x = [ 1.0, -2.0, 3.0, -4.0, 5.0 ];
	* var y = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
	*
	* var shape = [ x.length ];
	* var strides = [ 1, 1 ];
	* var offsets = [ 0, 0 ];
	*
	* ns.unaryBy.ndarray( [ x, y ], shape, strides, offsets, abs, accessor );
	* // y => [ 2.0, 4.0, 6.0, 8.0, 10.0 ]
	*/
	unaryBy: typeof unaryBy;

	/**
	* Generates a list of unary interface signatures from strided array data types.
	*
	* ## Notes
	*
	* -   The function returns a strided array having a stride length of `2` (i.e., every `2` elements define a unary interface signature).
	* -   For each signature (i.e., set of two consecutive non-overlapping strided array elements), the first element is the input data type and the second element is the return data type.
	* -   All signatures follow type promotion rules.
	*
	* @param dtypes1 - list of supported data types for the first argument
	* @param dtypes