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* @license Apache-2.0
*
* Copyright (c) 2026 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.
*/
'use strict';
// MODULES //
var hasOwnProp = require( '@stdlib/assert/has-own-property' );
var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
var isComplexLike = require( '@stdlib/assert/is-complex-like' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var isObject = require( '@stdlib/assert/is-plain-object' );
var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
var getDType = require( '@stdlib/ndarray/dtype' );
var getShape = require( '@stdlib/ndarray/shape' );
var getOrder = require( '@stdlib/ndarray/order' );
var format = require( '@stdlib/string/format' );
var base = require( './base.js' );
// FUNCTIONS //
/**
* Tests if a value is a numeric scalar (number or complex-like).
*
* @private
* @param {*} value - value to test
* @returns {boolean} boolean indicating whether value is a numeric scalar
*/
function isScalar( value ) {
return isNumber( value ) || isComplexLike( value );
}
// MAIN //
/**
* Multiplies each element in an input ndarray by a scalar constant and adds a scalar constant to each result along one or more ndarray dimensions.
*
* @param {ndarrayLike} x - input ndarray
* @param {(ndarrayLike|number|ComplexLike)} alpha - scalar constant to multiply
* @param {(ndarrayLike|number|ComplexLike)} beta - scalar constant to add
* @param {Options} [options] - function options
* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation
* @throws {TypeError} first argument must be an ndarray-like object
* @throws {TypeError} second argument must be either an ndarray-like object, a number, or a complex number
* @throws {TypeError} third argument must be either an ndarray-like object, a number, or a complex number
* @throws {TypeError} options argument must be an object
* @throws {RangeError} dimension indices must not exceed input ndarray bounds
* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
* @throws {Error} must provide valid options
* @returns {ndarray} output ndarray
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
*
* // Create a data buffer:
* var xbuf = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ] );
*
* // Define the shape of the input array:
* var sh = [ 2, 2, 2 ];
*
* // Define the array strides:
* var sx = [ 4, 2, 1 ];
*
* // Define the index offset:
* var ox = 0;
*
* // Create an input ndarray:
* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
*
* // Perform operation:
* var out = axpb( x, 5.0, 3.0 );
* // returns <ndarray>[ [ [ -7.0, 8.0 ], [ 18.0, -22.0 ] ], [ [ 23.0, 3.0 ], [ -2.0, -12.0 ] ] ]
*/
function axpb( x, alpha, beta ) {
var isScalarAlpha;
var isScalarBeta;
var options;
var nargs;
var ord;
var dt;
var sh;
nargs = arguments.length;
if ( !isndarrayLike( x ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) );
}
if ( nargs < 3 ) {
throw new TypeError( 'invalid invocation. Insufficient arguments. Must provide at least three arguments.' );
}
// Cache scalar checks:
isScalarAlpha = isScalar( alpha );
isScalarBeta = isScalar( beta );
// Validate alpha and beta arguments:
if ( !isScalarAlpha && !isndarrayLike( alpha ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be either an ndarray, a number, or a complex number. Value: `%s`.', alpha ) );
}
if ( !isScalarBeta && !isndarrayLike( beta ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be either an ndarray, a number, or a complex number. Value: `%s`.', beta ) );
}
// Resolve input ndarray meta data:
dt = getDType( x );
ord = getOrder( x );
// Case: axpb( x, alpha, beta, options )
if ( nargs > 3 ) {
options = arguments[ 3 ];
if ( !isObject( options ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
}
// Resolve the shape for broadcasting:
if ( hasOwnProp( options, 'dims' ) ) {
sh = nonCoreShape( getShape( x ), options.dims );
} else {
sh = [];
}
} else {
sh = [];
}
// Broadcast alpha to match the appropriate shape:
if ( isScalarAlpha ) {
alpha = broadcastScalar( alpha, dt, sh, ord );
} else {
alpha = maybeBroadcastArray( alpha, sh );
}
// Broadcast beta to match the appropriate shape:
if ( isScalarBeta ) {
beta = broadcastScalar( beta, dt, sh, ord );
} else {
beta = maybeBroadcastArray( beta, sh );
}
// Case: axpb( x, alpha, beta )
if ( nargs === 3 ) {
return base( x, alpha, beta );
}
// Case: axpb( x, alpha, beta, options )
return base( x, alpha, beta, options );
}
// EXPORTS //
module.exports = axpb;
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