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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 | 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 13x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 4x 8x 8x 8x 8x 4x 4x 4x 2x 13x 13x 13x 13x 13x | /** * @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. */ 'use strict'; // MAIN // /** * Applies a unary callback to elements in a two-dimensional input ndarray 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 {Callback} fcn - unary callback * @returns {void} * * @example * var Float64Array = require( '@stdlib/array/float64' ); * * function scale( x ) { * return x * 10.0; * } * * // 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 = [ 2, 2 ]; * * // Define the array strides: * var sx = [ 4, 1 ]; * var sy = [ 2, 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: * unary2d( x, y, scale ); * * console.log( y.data ); * // => <Float64Array>[ 20.0, 30.0, 60.0, 70.0 ] */ function unary2d( x, y, fcn ) { var xbuf; var ybuf; var dx0; var dx1; var dy0; var dy1; var sh; var S0; var S1; var sx; var sy; var ix; var iy; var i0; var i1; // Note on variable naming convention: S#, dx#, dy#, i# where # corresponds to the loop number, with `0` being the innermost loop... // Extract loop variables for purposes of loop interchange: dimensions and loop offset (pointer) increments... sh = x.shape; sx = x.strides; sy = y.strides; if ( x.order === 'row-major' ) { // For row-major ndarrays, the last dimensions have the fastest changing indices... S0 = sh[ 1 ]; S1 = sh[ 0 ]; dx0 = sx[ 1 ]; // offset increment for innermost loop dx1 = sx[ 0 ] - ( S0*sx[1] ); // offset increment for outermost loop dy0 = sy[ 1 ]; dy1 = sy[ 0 ] - ( S0*sy[1] ); } else { // order === 'column-major' // For column-major ndarrays, the first dimensions have the fastest changing indices... S0 = sh[ 0 ]; S1 = sh[ 1 ]; dx0 = sx[ 0 ]; // offset increment for innermost loop dx1 = sx[ 1 ] - ( S0*sx[0] ); // offset increment for outermost loop dy0 = sy[ 0 ]; dy1 = sy[ 1 ] - ( S0*sy[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... for ( i1 = 0; i1 < S1; i1++ ) { for ( i0 = 0; i0 < S0; i0++ ) { ybuf[ iy ] = fcn( xbuf[ ix ] ); ix += dx0; iy += dy0; } ix += dx1; iy += dy1; } } // EXPORTS // module.exports = unary2d; |