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 | 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x 1x | /**
* @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 isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
var isFunction = require( '@stdlib/assert/is-function' );
var unaryReduceSubarrayBy = require( '@stdlib/ndarray/base/unary-reduce-subarray-by' );
var base = require( '@stdlib/ndarray/base/count-if' );
var spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' );
var indicesComplement = require( '@stdlib/array/base/indices-complement' );
var getShape = require( '@stdlib/ndarray/shape' ); // note: non-base accessor is intentional due to the input array originating in userland
var getOrder = require( '@stdlib/ndarray/base/order' );
var empty = require( '@stdlib/ndarray/empty' );
var defaults = require( '@stdlib/ndarray/defaults' );
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' );
// VARIABLES //
var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' );
// MAIN //
/**
* Counts the number of elements along one or more ndarray dimensions which pass a test implemented by a predicate function.
*
* @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 {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} callback 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 Float64Array = require( '@stdlib/array/float64' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
*
* function predicate( value ) {
* return value > 0.0;
* }
*
* // Create a data buffer:
* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 0.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
*
* // Define the shape of the input array:
* var sh = [ 3, 1, 2 ];
*
* // Define the array strides:
* var sx = [ 4, 4, 1 ];
*
* // Define the index offset:
* var ox = 1;
*
* // Create an input ndarray:
* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
*
* // Perform reduction:
* var out = countIf( x, predicate );
* // returns <ndarray>[ 5 ]
*/
function countIf( x, options, predicate, thisArg ) {
var nargs;
var opts;
var err;
var idx;
var shx;
var shy;
var ctx;
var flg;
var cb;
var o;
var N;
var y;
nargs = arguments.length;
if ( !isndarrayLike( x ) ) {
throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
}
// Case: countIf( x, predicate )
if ( nargs < 3 ) {
cb = options;
if ( !isFunction( cb ) ) {
throw new TypeError( format( 'invalid argument. Second argument must be a function. Value: `%s`.', cb ) );
}
}
// Case: countIf( x, options, predicate, thisArg )
else if ( nargs > 3 ) {
flg = true;
o = options;
cb = predicate;
if ( !isFunction( cb ) ) {
throw new TypeError( format( 'invalid argument. Third argument must be a function. Value: `%s`.', cb ) );
}
ctx = thisArg;
}
// Case: countIf( x, predicate, thisArg )
else if ( isFunction( options ) ) {
cb = options;
ctx = predicate;
}
// Case: countIf( x, options, predicate )
else if ( isFunction( predicate ) ) {
flg = true;
o = options;
cb = predicate;
}
// Case: countIf( x, ???, ??? )
else {
throw new TypeError( format( 'invalid argument. Third argument must be a function. Value: `%s`.', predicate ) );
}
shx = getShape( x );
N = shx.length;
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 );
// Initialize an output array whose shape matches that of the non-reduced dimensions and which has the same memory layout as the input array:
y = empty( shy, {
'dtype': DEFAULT_DTYPE,
'order': getOrder( x )
});
// Perform the reduction:
unaryReduceSubarrayBy( base, [ x, y ], 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 ) {
y = spreadDimensions( N, y, idx );
}
return y;
}
// EXPORTS //
module.exports = countIf;
|