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* @license Apache-2.0
*
* Copyright (c) 2022 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';
// MAIN //
/**
* Applies a unary function to each element retrieved from a one-dimensional input ndarray according to a callback function and assigns results to elements in an equivalently shaped output ndarray.
*
* @private
* @param {Object} x - object containing input ndarray meta data
* @param {string} x.dtype - data type
* @param {Collection} x.data - data buffer
* @param {NonNegativeIntegerArray} x.shape - dimensions
* @param {IntegerArray} x.strides - stride lengths
* @param {NonNegativeInteger} x.offset - index offset
* @param {string} x.order - specifies whether `x` is row-major (C-style) or column-major (Fortran-style)
* @param {Object} y - object containing output ndarray meta data
* @param {string} y.dtype - data type
* @param {Collection} y.data - data buffer
* @param {NonNegativeIntegerArray} y.shape - dimensions
* @param {IntegerArray} y.strides - stride lengths
* @param {NonNegativeInteger} y.offset - index offset
* @param {string} y.order - specifies whether `y` is row-major (C-style) or column-major (Fortran-style)
* @param {Function} fcn - unary function to apply to callback return values
* @param {Callback} clbk - callback
* @param {*} [thisArg] - callback execution context
* @returns {void}
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* function scale( x ) {
* return x * 10.0;
* }
*
* function accessor( v ) {
* return v * 2.0;
* }
*
* // Create data buffers:
* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );
* var ybuf = new Float64Array( 4 );
*
* // Define the shape of the input and output arrays:
* var shape = [ 4 ];
*
* // Define the array strides:
* var sx = [ 2 ];
* var sy = [ 1 ];
*
* // Define the index offsets:
* var ox = 1;
* var oy = 0;
*
* // Create the input and output ndarray-like objects:
* var x = {
* 'dtype': 'float64',
* 'data': xbuf,
* 'shape': shape,
* 'strides': sx,
* 'offset': ox,
* 'order': 'row-major'
* };
* var y = {
* 'dtype': 'float64',
* 'data': ybuf,
* 'shape': shape,
* 'strides': sy,
* 'offset': oy,
* 'order': 'row-major'
* };
*
* // Apply the unary function:
* unary1d( x, y, scale, accessor );
*
* console.log( y.data );
* // => <Float64Array>[ 40, 80, 120, 160 ]
*/
function unary1d( x, y, fcn, clbk, thisArg ) {
var xbuf;
var ybuf;
var dx0;
var dy0;
var S0;
var ix;
var iy;
var i0;
var v;
var i;
// Note on variable naming convention: S#, dx#, dy#, i# where # corresponds to the loop number, with `0` being the innermost loop...
// Extract loop variables: dimensions and loop offset (pointer) increments...
S0 = x.shape[ 0 ];
dx0 = x.strides[ 0 ];
dy0 = y.strides[ 0 ];
// Set the pointers to the first indexed elements in the respective ndarrays...
ix = x.offset;
iy = y.offset;
// Cache references to the input and output ndarray buffers...
xbuf = x.data;
ybuf = y.data;
// Iterate over the ndarray dimensions...
i = 0;
for ( i0 = 0; i0 < S0; i0++ ) {
v = clbk.call( thisArg, xbuf[ ix ], i, [ ix, iy ], [ x, y ] );
if ( v !== void 0 ) {
ybuf[ iy ] = fcn( v );
}
ix += dx0;
iy += dy0;
i += 1;
}
}
// EXPORTS //
module.exports = unary1d;
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