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 | 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 2x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 124x 20x 20x 104x 124x 11x 9x 9x 2x 2x 93x 93x 10x 10x 10x 10x 9x 9x 1x 1x 83x 83x 1x 1x 1x 82x 82x 64x 64x 64x 64x 18x 18x 18x 18x 68x 68x 68x 68x 68x 68x 124x 65x 65x 32x 32x 65x 36x 124x 3x 3x 36x 36x 36x 36x 36x 36x 36x 36x 36x 36x 124x 16x 124x 20x 20x 36x 124x 124x 36x 36x 36x 36x 36x 36x 36x 36x 36x 36x 36x 36x 124x 16x 16x 36x 124x 2x 2x 2x 2x 2x | /**
* @license Apache-2.0
*
* Copyright (c) 2025 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 isFunction = require( '@stdlib/assert/is-function' );
var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var hasOwnProp = require( '@stdlib/assert/has-own-property' );
var unaryReduceSubarrayBy = require( '@stdlib/ndarray/base/unary-reduce-subarray-by' );
var base = require( '@stdlib/ndarray/base/find' );
var spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' );
var indicesComplement = require( '@stdlib/array/base/indices-complement' );
var getDType = require( '@stdlib/ndarray/dtype' );
var getShape = require( '@stdlib/ndarray/shape' );
var getOrder = require( '@stdlib/ndarray/base/order' );
var empty = require( '@stdlib/ndarray/empty' );
var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
var takeIndexed = require( '@stdlib/array/base/take-indexed' );
var zeroTo = require( '@stdlib/array/base/zero-to' );
var objectAssign = require( '@stdlib/object/assign' );
var format = require( '@stdlib/string/format' );
var DEFAULTS = require( './defaults.json' );
var validate = require( './validate.js' );
var getSentinel = require( './sentinel.js' );
// MAIN //
/**
* Returns a new ndarray containing the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions.
*
* @param {ndarray} x - input ndarray
* @param {Options} [options] - function options
* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction
* @param {boolean} [options.keepdims=false] - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions
* @param {(*|ndarray)} [options.sentinel] - sentinel value
* @param {Function} predicate - predicate function
* @param {*} [thisArg] - predicate function execution context
* @throws {TypeError} first argument must be an ndarray-like object
* @throws {TypeError} options argument must be an object
* @throws {TypeError} predicate argument must be a function
* @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 isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
* var array = require( '@stdlib/ndarray/array' );
*
* // Create an input ndarray:
* var x = array( [ [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ], [ 7.0, 8.0 ] ] ] );
* // returns <ndarray>
*
* // Perform reduction:
* var out = find( x, isEven );
* // returns <ndarray>
*
* var v = out.get();
* // returns 2.0
*/
function find( x, options, predicate, thisArg ) { // eslint-disable-line stdlib/no-redeclare
var sentinel;
var nargs;
var opts;
var err;
var idx;
var shx;
var shy;
var ord;
var out;
var flg;
var ctx;
var sv;
var cb;
var dt;
var N;
var o;
nargs = arguments.length;
if ( !isndarrayLike( x ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
}
// Case: find( x, predicate )
if ( nargs < 3 ) {
if ( !isFunction( options ) ) {
throw new TypeError( format( 'invalid argument. Callback argument must be a function. Value: `%s`.', options ) );
}
cb = options;
}
// Case: find( x, options, predicate, thisArg )
else if ( nargs > 3 ) {
flg = true;
o = options;
cb = predicate;
if ( !isFunction( cb ) ) {
throw new TypeError( format( 'invalid argument. Callback argument must be a function. Value: `%s`.', cb ) );
}
ctx = thisArg;
}
// Case: find( x, predicate, thisArg )
else if ( isFunction( options ) ) {
cb = options;
ctx = predicate;
}
// Case: find( x, options, predicate )
else if ( isFunction( predicate ) ) {
flg = true;
o = options;
cb = predicate;
}
// Case: find( x, ???, ??? )
else {
throw new TypeError( format( 'invalid argument. Callback argument must be a function. Value: `%s`.', predicate ) );
}
dt = getDType( x );
shx = getShape( x );
N = shx.length;
// Resolve function options:
opts = objectAssign( {}, DEFAULTS );
if ( flg ) {
err = validate( opts, N, o );
if ( err ) {
throw err;
}
}
// When a list of dimensions is not provided, reduce the entire input array across all dimensions...
if ( opts.dims === null ) {
opts.dims = zeroTo( N );
}
// Resolve the list of non-reduced dimensions:
idx = indicesComplement( N, opts.dims );
// Resolve the output array shape:
shy = takeIndexed( shx, idx );
// Resolve input array meta data:
ord = getOrder( x );
// Resolve the sentinel value to use when unable to find an element satisfying a provided predicate function...
if ( hasOwnProp( opts, 'sentinel' ) ) {
sentinel = opts.sentinel;
} else {
sentinel = getSentinel( dt );
}
// Broadcast the sentinel value to match the output array shape...
if ( isndarrayLike( sentinel ) ) {
sv = maybeBroadcastArray( sentinel, shy );
} else {
sv = broadcastScalar( sentinel, dt, shy, ord );
}
// Initialize an output array whose shape matches that of the non-reduced dimensions and which has the same dtype as the input array:
out = empty( shy, {
'dtype': dt,
'order': ord
});
// Perform the reduction:
unaryReduceSubarrayBy( base, [ x, out, sv ], opts.dims, cb, ctx );
// Check whether we need to reinsert singleton dimensions which can be useful for broadcasting the returned output array to the shape of the original input array...
if ( opts.keepdims ) {
out = spreadDimensions( N, out, idx );
}
return out;
}
// EXPORTS //
module.exports = find;
|