feat: add ndarray/base/find

lib/node_modules/@stdlib/ndarray/base/find/README.md

@@ -0,0 +1,246 @@
+<!--
+
+@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.
+
+-->
+
+# find
+
+> Return the first element in an ndarray which passes a test implemented by a predicate function.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+<!-- eslint-disable no-redeclare -->
+
+```javascript
+var find = require( '@stdlib/ndarray/base/find' );
+```
+
+<!-- eslint-enable no-redeclare -->
+
+#### find( arrays, predicate\[, thisArg] )
+
+Returns the first element in an ndarray which passes a test implemented by a predicate function.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+function isEven( value ) {
+    return value % 2.0 === 0.0;
+}
+
+// Create a data buffer:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+
+// Define the shape of the input array:
+var shape = [ 3, 1, 2 ];
+
+// Define the array strides:
+var sx = [ 4, 4, 1 ];
+
+// Define the index offset:
+var ox = 0;
+
+// Create the input ndarray-like object:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': shape,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+// Create an ndarray-like object containing a sentinel value:
+var sentinelValue = {
+    'dtype': 'float64',
+    'data': new Float64Array( [ NaN ] ),
+    'shape': [],
+    'strides': [ 0 ],
+    'offset': 0,
+    'order': 'row-major'
+};
+
+// Perform reduction:
+var out = find( [ x, sentinelValue ], isEven );
+// returns 2.0
+```
+
+The function accepts the following arguments:
+
+-   **arrays**: array-like object containing an input ndarray and a zero-dimensional ndarray containing a sentinel value. The sentinel value is returned when no element in an input ndarray passes a test implemented by the predicate function.
+-   **predicate**: predicate function.
+-   **thisArg**: predicate function execution context (_optional_).
+
+Each provided ndarray should be an object with the following properties:
+
+-   **dtype**: data type.
+-   **data**: data buffer.
+-   **shape**: dimensions.
+-   **strides**: stride lengths.
+-   **offset**: index offset.
+-   **order**: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style).
+
+The predicate function is provided the following arguments:
+
+-   **value**: current array element.
+-   **indices**: current array element indices.
+-   **arr**: the input ndarray.
+
+To set the predicate function execution context, provide a `thisArg`.
+
+<!-- eslint-disable no-invalid-this, max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+function isEven( value ) {
+    this.count += 1;
+    return value % 2.0 === 0.0;
+}
+
+// Create a data buffer:
+var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+
+// Define the shape of the input array:
+var shape = [ 3, 1, 2 ];
+
+// Define the array strides:
+var sx = [ 4, 4, 1 ];
+
+// Define the index offset:
+var ox = 0;
+
+// Create the input ndarray-like object:
+var x = {
+    'dtype': 'float64',
+    'data': xbuf,
+    'shape': shape,
+    'strides': sx,
+    'offset': ox,
+    'order': 'row-major'
+};
+
+// Create an ndarray-like object containing a sentinel value:
+var sentinelValue = {
+    'dtype': 'float64',
+    'data': new Float64Array( [ NaN ] ),
+    'shape': [],
+    'strides': [ 0 ],
+    'offset': 0,
+    'order': 'row-major'
+};
+
+var ctx = {
+    'count': 0
+};
+
+// Perform reduction:
+var out = find( [ x, sentinelValue ], isEven, ctx );
+// returns 2.0
+
+var count = ctx.count;
+// returns 2
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before performing the operation in order to achieve better performance.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray2array = require( '@stdlib/ndarray/base/to-array' );
+var find = require( '@stdlib/ndarray/base/find' );
+
+function isEven( value ) {
+    return value % 2.0 === 0.0;
+}
+
+var x = {
+    'dtype': 'float64',
+    'data': discreteUniform( 10, 0.0, 10.0, {
+        'dtype': 'float64'
+    }),
+    'shape': [ 5, 2 ],
+    'strides': [ 2, 1 ],
+    'offset': 0,
+    'order': 'row-major'
+};
+console.log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
+
+var sv = {
+    'dtype': 'float64',
+    'data': new Float64Array( [ NaN ] ),
+    'shape': [],
+    'strides': [ 0 ],
+    'offset': 0,
+    'order': x.order
+};
+console.log( 'Sentinel Value: %d', sv.data[ 0 ] );
+
+var out = find( [ x, sv ], isEven );
+console.log( out );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<section class="links">
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/ndarray/base/find/benchmark/benchmark.10d_columnmajor.js

@@ -0,0 +1,147 @@
+/**
+* @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';
+
+/* eslint-disable stdlib/no-redeclare */
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isInteger = require( '@stdlib/math/base/assert/is-integer' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var pkg = require( './../package.json' ).name;
+var find = require( './../lib/10d.js' );
+
+
+// VARIABLES //
+
+var types = [ 'float64' ];
+var order = 'column-major';
+
+
+// FUNCTIONS //
+
+/**
+* Callback function.
+*
+* @param {*} value - ndarray element
+* @returns {boolean} result
+*/
+function clbk( value ) {
+	return value < 0.0;
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - ndarray length
+* @param {NonNegativeIntegerArray} shape - ndarray shape
+* @param {string} xtype - ndarray data type
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len, shape, xtype ) {
+	var x;
+
+	x = discreteUniform( len, 1, 100, {
+		'dtype': xtype
+	});
+	x = {
+		'dtype': xtype,
+		'data': x,
+		'shape': shape,
+		'strides': shape2strides( shape, order ),
+		'offset': 0,
+		'order': order
+	};
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var out;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			out = find( x, NaN, clbk );
+			if ( isInteger( out ) ) {
+				b.fail( 'should not return an integer' );
+			}
+		}
+		b.toc();
+		if ( isInteger( out ) ) {
+			b.fail( 'should not return an integer' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var sh;
+	var t1;
+	var f;
+	var i;
+	var j;
+
+	min = 1; // 10^min
+	max = 5; // 10^max
+
+	for ( j = 0; j < types.length; j++ ) {
+		t1 = types[ j ];
+		for ( i = min; i <= max; i++ ) {
+			len = pow( 10, i );
+
+			sh = [ len/2, 2, 1, 1, 1, 1, 1, 1, 1, 1 ];
+			f = createBenchmark( len, sh, t1 );
+			bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f );
+
+			sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, len/2 ];
+			f = createBenchmark( len, sh, t1 );
+			bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f );
+
+			len = floor( pow( len, 1.0/10.0 ) );
+			sh = [ len, len, len, len, len, len, len, len, len, len ];
+			len *= pow( len, 9 );
+			f = createBenchmark( len, sh, t1 );
+			bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+order+',xtype='+t1, f );
+		}
+	}
+}
+
+main();