/*
* @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.
*/

// TypeScript Version: 4.1

/// <reference types="@stdlib/types"/>

import { ArrayLike } from '@stdlib/types/array';
import { ndarray, typedndarray } from '@stdlib/types/ndarray';

/**
* Returns a boolean indicating whether an element passes a test.
*
* @returns boolean indicating whether an ndarray element passes a test
*/
type Nullary<ThisArg> = ( this: ThisArg ) => boolean;

/**
* Returns a boolean indicating whether an element passes a test.
*
* @param value - current array element
* @returns boolean indicating whether an ndarray element passes a test
*/
type Unary<T, ThisArg> = ( this: ThisArg, value: T ) => boolean;

/**
* Returns a boolean indicating whether an element passes a test.
*
* @param value - current array element
* @param indices - current array element indices
* @returns boolean indicating whether an ndarray element passes a test
*/
type Binary<T, ThisArg> = ( this: ThisArg, value: T, indices: Array<number> ) => boolean;

/**
* Returns a boolean indicating whether an element passes a test.
*
* @param value - current array element
* @param indices - current array element indices
* @param arr - input array
* @returns boolean indicating whether an ndarray element passes a test
*/
type Ternary<T, U, ThisArg> = ( this: ThisArg, value: T, indices: Array<number>, arr: U ) => boolean;

/**
* Returns a boolean indicating whether an element passes a test.
*
* @param value - current array element
* @param indices - current array element indices
* @param arr - input array
* @returns boolean indicating whether an ndarray element passes a test
*/
type Predicate<T, U, ThisArg> = Nullary<ThisArg> | Unary<T, ThisArg> | Binary<T, ThisArg> | Ternary<T, U, ThisArg>;

/**
* Base options.
*/
interface BaseOptions {
	/**
	* List of dimensions over which to perform the reduction.
	*/
	dims?: ArrayLike<number>;
}

/**
* Options.
*/
interface Options<T> extends BaseOptions {
	/**
	* Boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions. Default: `false`.
	*/
	keepdims?: boolean;

	/**
	* Sentinel value.
	*/
	sentinel?: T | typedndarray<T>;
}

/**
* Assign options.
*/
interface AssignOptions<T> extends BaseOptions {
	/**
	* Sentinel value.
	*/
	sentinel?: T | typedndarray<T>;
}

/**
* Interface describing `find`.
*/
interface Find {
	/**
	* Returns a new ndarray containing the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions.
	*
	* @param x - input ndarray
	* @param predicate - predicate function
	* @param thisArg - predicate execution context
	* @returns output ndarray
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
	* var ndarray = require( './../../../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 sh = [ 3, 2 ];
	*
	* // Define the array strides:
	* var sx = [ 2, 1 ];
	*
	* // Define the index offset:
	* var ox = 0;
	*
	* // Create an input ndarray:
	* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
	*
	* // Perform the operation:
	* var out = find( x, isEven );
	* // returns <ndarray>
	*
	* var v = out.get();
	* // returns 2.0
	*/
	<T = unknown, U extends typedndarray<T> = typedndarray<T>, ThisArg = unknown>( x: U, predicate: Predicate<T, U, ThisArg>, thisArg?: ThisParameterType<Predicate<T, U, ThisArg>> ): U;

	/**
	* Returns a new ndarray containing the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions.
	*
	* @param x - input ndarray
	* @param options - function options
	* @param options.dims - list of dimensions over which to perform a reduction
	* @param options.keepdims - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions (default: false)
	* @param options.sentinel - sentinel value
	* @param predicate - predicate function
	* @param thisArg - predicate execution context
	* @returns output ndarray
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
	* var ndarray = require( './../../../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 sh = [ 3, 2 ];
	*
	* // Define the array strides:
	* var sx = [ 2, 1 ];
	*
	* // Define the index offset:
	* var ox = 0;
	*
	* // Create an input ndarray:
	* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
	*
	* var opts = {
	*    'dims': [ 0 ]
	* };
	*
	* // Perform the operation:
	* var out = find( x, opts, isEven );
	* // returns <ndarray>
	*/
	<T = unknown, V = T, U extends typedndarray<T | V> = typedndarray<T | V>, ThisArg = unknown>( x: U, options: Options<V>, predicate: Predicate<T, U, ThisArg>, thisArg?: ThisParameterType<Predicate<T, U, ThisArg>> ): U;

	/**
	* Finds the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions and assigns results to a provided output ndarray.
	*
	* @param x - input ndarray
	* @param out - output ndarray
	* @param predicate - predicate function
	* @param thisArg - predicate execution context
	* @returns output ndarray
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var ndarray = require( './../../../ctor' );
	* var isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
	* var empty = require( './../../../empty' );
	*
	* // 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 = [ 3, 2 ];
	*
	* // Define the array strides:
	* var sx = [ 2, 1 ];
	*
	* // Define the index offset:
	* var ox = 0;
	*
	* // Create an input ndarray:
	* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
	*
	* // Create an output ndarray:
	* var y = empty( [], {
	*     'dtype': 'float64'
	* });
	*
	* // Perform the operation:
	* var out = find.assign( x, y, isEven );
	* // returns <ndarray>
	*
	* var v = out.get();
	* // returns 2.0
	*/
	assign<T = unknown, U extends typedndarray<T> = typedndarray<T>, ThisArg = unknown>( x: ndarray, out: U, predicate: Predicate<T, U, ThisArg>, thisArg?: ThisParameterType<Predicate<T, U, ThisArg>> ): U;

	/**
	* Finds the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions and assigns results to a provided output ndarray.
	*
	* @param x - input ndarray
	* @param out - output ndarray
	* @param options - function options
	* @param options.dims - list of dimensions over which to perform a reduction
	* @param options.sentinel - sentinel value
	* @param predicate - predicate function
	* @param thisArg - predicate execution context
	* @returns output ndarray
	*
	* @example
	* var Float64Array = require( '@stdlib/array/float64' );
	* var ndarray = require( './../../../ctor' );
	* var isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
	* var empty = require( './../../../empty' );
	*
	* // 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 = [ 3, 2 ];
	*
	* // Define the array strides:
	* var sx = [ 2, 1 ];
	*
	* // Define the index offset:
	* var ox = 0;
	*
	* // Create an input ndarray:
	* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
	*
	* // Create an output ndarray:
	* var y = empty( [], {
	*     'dtype': 'float64'
	* });
	*
	* // Perform the operation:
	* var out = find.assign( x, y, {}, isEven );
	* // returns <ndarray>
	*/
	assign<T = unknown, U extends typedndarray<T> = typedndarray<T>, V = T, ThisArg = unknown>( x: ndarray, out: U, options: AssignOptions<V>, predicate: Predicate<T, U, ThisArg>, thisArg?: ThisParameterType<Predicate<T, U, ThisArg>> ): U;
}

/**
* Returns a new ndarray containing the first elements which pass a test implemented by a predicate function along one or more ndarray dimensions.
*
* @param x - input ndarray
* @param options - function options
* @param options.dims - list of dimensions over which to perform a reduction
* @param options.keepdims - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions (default: false)
* @param options.sentinel - sentinel value
* @param predicate - predicate function
* @param thisArg - predicate execution context
* @returns output ndarray
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
* 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 sh = [ 3, 2 ];
*
* // Define the array strides:
* var sx = [ 2, 1 ];
*
* // Define the index offset:
* var ox = 0;
*
* // Create an input ndarray:
* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
*
* // Perform the operation:
* var out = find( x, isEven );
* // returns <ndarray>
*
* var v = out.get();
* // returns 2.0
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
* var ndarray = require( '@stdlib/ndarray/ctor' );
* var isEven = require( '@stdlib/assert/is-even' ).isPrimitive;
* var empty = require( '@stdlib/ndarray/empty' );
*
* // 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 = [ 3, 2 ];
*
* // Define the array strides:
* var sx = [ 2, 1 ];
*
* // Define the index offset:
* var ox = 0;
*
* // Create an input ndarray:
* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
*
* // Create an output ndarray:
* var y = empty( [], {
*     'dtype': 'float64'
* });
*
* // Perform the operation:
* var out = find.assign( x, y, isEven );
* // returns <ndarray>
*
* var v = out.get();
* // returns 2.0
*/
declare var find: Find;


// EXPORTS //

export = find;