Press n or j to go to the next uncovered block, b, p or k for the previous block.
| 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 | 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 3x 234x 234x 234x 234x 234x 234x 234x 234x 234x 234x 234x 234x 234x 234x 61x 61x 234x 41x 41x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 132x 234x 16x 16x 11x 11x 16x 116x 116x 61x 61x 17x 17x 17x 17x 4x 4x 13x 13x 5x 5x 5x 8x 8x 8x 8x 17x 44x 44x 44x 44x 20x 20x 24x 24x 24x 61x 55x 55x 55x 55x 27x 27x 28x 28x 20x 20x 20x 8x 8x 8x 8x 47x 55x 10x 10x 37x 37x 37x 234x 61x 26x 26x 35x 61x 22x 22x 61x 49x 234x 3x 3x 46x 46x 46x 46x 46x 46x 46x 234x 27x 234x 13x 13x 34x 234x 3x 3x 3x 3x 3x | /**
* @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 isPlainObject = require( '@stdlib/assert/is-plain-object' );
var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive;
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
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 getShape = require( '@stdlib/ndarray/shape' );
var getOrder = require( '@stdlib/ndarray/order' );
var format = require( '@stdlib/string/format' );
var defaults = require( '@stdlib/ndarray/defaults' );
var base = require( './base.js' ).assign;
// VARIABLES //
var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' );
// MAIN //
/**
* Returns the index of the first element in an ndarray which is less than a corresponding element in another ndarray along an ndarray dimension and assigns the results to a provided output ndarray.
*
* @param {ndarrayLike} x - first input ndarray
* @param {ndarrayLike} y - second input ndarray
* @param {(ndarrayLike|integer)} [fromIndex=0] - index from which to begin searching
* @param {ndarrayLike} out - output ndarray
* @param {Options} [options] - function options
* @param {integer} [options.dim=-1] - dimension over which to perform operation
* @throws {TypeError} first argument must be an ndarray-like object
* @throws {TypeError} second argument must be an ndarray-like object
* @throws {TypeError} third argument must be either an ndarray-like object or an integer
* @throws {TypeError} output argument must be an ndarray-like object
* @throws {TypeError} options argument must be an object
* @throws {RangeError} dimension index must not exceed input ndarray bounds
* @throws {RangeError} first argument must have at least one dimension
* @throws {Error} must provide valid options
* @returns {ndarray} output ndarray
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
* var zeros = require( '@stdlib/ndarray/zeros' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
*
* // Create a data buffer:
* var xbuf = new Float64Array( [ 1.0, 2.0, -3.0, 4.0, -5.0, 6.0 ] );
*
* // Define the shape of the input array:
* var shape = [ 2, 3 ];
*
* // Define the array strides:
* var strides = [ 3, 1 ];
*
* // Define the index offset:
* var offset = 0;
*
* // Create an input ndarray:
* var x = new ndarray( 'float64', xbuf, shape, strides, offset, 'row-major' );
*
* // Create a second input ndarray:
* var y = scalar2ndarray( 0.0, {
* 'dtype': 'float64'
* });
*
* // Create an output ndarray:
* var z = zeros( [ 2 ], {
* 'dtype': 'int32'
* });
*
* // Perform operation:
* var out = assign( x, y, z );
* // returns <ndarray>[ 2, 1 ]
*
* var bool = ( out === z );
* // returns true
*/
function assign( x, y, fromIndex, out ) {
var hasOptions;
var options;
var nargs;
var opts;
var fidx;
var iflg;
var ord;
var sh;
var v;
var o;
nargs = arguments.length;
if ( !isndarrayLike( x ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) );
}
if ( !isndarrayLike( y ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be an ndarray. Value: `%s`.', y ) );
}
// Resolve input ndarray meta data:
ord = getOrder( x );
// Initialize an options object:
opts = {
'dims': [ -1 ] // default behavior is to perform a reduction over the last dimension
};
// Initialize the `fromIndex` to the first element along a dimension:
fidx = 0;
// Initialize a flag indicating whether the `fromIndex` argument is a scalar:
iflg = true;
// Initialize a flag indicating whether an `options` argument was provided:
hasOptions = false;
// Case: assign( x, y, out )
if ( nargs <= 3 ) {
o = fromIndex;
if ( !isndarrayLike( o ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be an ndarray. Value: `%s`.', o ) );
}
}
// Case: assign( x, y, ???, ??? )
else if ( nargs === 4 ) {
// Case: assign( x, y, from_index, out )
if ( isndarrayLike( out ) ) {
o = out;
// Case: assign( x, y, from_index_scalar, out )
if ( isInteger( fromIndex ) ) {
fidx = fromIndex;
}
// Case: assign( x, y, from_index_ndarray, out )
else if ( isndarrayLike( fromIndex ) ) {
fidx = fromIndex;
iflg = false;
}
// Case: assign( x, y, ???, out )
else {
throw new TypeError( format( 'invalid argument. Third argument must be either an ndarray or an integer. Value: `%s`.', fromIndex ) );
}
}
// Case: assign( x, y, out, options )
else {
o = fromIndex;
if ( !isndarrayLike( o ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be an ndarray. Value: `%s`.', o ) );
}
options = out;
hasOptions = true;
}
}
// Case: assign( x, y, from_index, out, options )
else { // nargs > 4
// Case: assign( x, y, from_index_scalar, out, options )
if ( isInteger( fromIndex ) ) {
fidx = fromIndex;
}
// Case: assign( x, y, from_index_ndarray, out, options )
else if ( isndarrayLike( fromIndex ) ) {
fidx = fromIndex;
iflg = false;
}
// Case: assign( x, y, ???, out, options )
else {
throw new TypeError( format( 'invalid argument. Third argument must be either an ndarray or an integer. Value: `%s`.', fromIndex ) );
}
o = out;
if ( !isndarrayLike( o ) ) {
throw new TypeError( format( 'invalid argument. Fourth argument must be an ndarray. Value: `%s`.', o ) );
}
options = arguments[ 4 ];
hasOptions = true;
}
if ( hasOptions ) {
if ( !isPlainObject( options ) ) {
throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
}
// Resolve provided options...
if ( hasOwnProp( options, 'dim' ) ) {
opts.dims[ 0 ] = options.dim;
}
}
sh = getShape( x );
if ( sh.length < 1 ) {
throw new RangeError( 'invalid argument. First argument must have at least one dimension.' );
}
// Broadcast the second input ndarray to match the shape of the first input ndarray:
v = maybeBroadcastArray( y, sh );
// Resolve the list of non-reduced dimensions:
sh = nonCoreShape( sh, opts.dims );
// Broadcast the `fromIndex` to match the shape of the non-reduced dimensions...
if ( iflg ) {
fidx = broadcastScalar( fidx, DEFAULT_DTYPE, sh, ord );
} else {
fidx = maybeBroadcastArray( fidx, sh );
}
return base( x, v, fidx, o, opts );
}
// EXPORTS //
module.exports = assign;
|