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* @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 hasOwnProp = require( '@stdlib/assert/has-own-property' );
var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
var isString = require( '@stdlib/assert/is-string' ).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 getShape = require( '@stdlib/ndarray/shape' );
var getOrder = require( '@stdlib/ndarray/order' );
var format = require( '@stdlib/string/format' );
var nonCoreShape = require( './non_core_shape.js' );
var base = require( './base.js' );
// MAIN //
/**
* Sorts an input ndarray along one or more ndarray dimensions using heapsort.
*
* @param {ndarrayLike} x - input ndarray
* @param {(ndarrayLike|number|string)} [sortOrder] - sort order
* @param {Options} [options] - function options
* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation
* @throws {TypeError} first argument must be an ndarray-like object
* @throws {TypeError} sort order argument must be either an ndarray-like object, a numeric value, or a valid string
* @throws {TypeError} options argument must be an object
* @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 ndarray2array = require( '@stdlib/ndarray/to-array' );
* 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, 1, 2 ];
*
* // Define the array strides:
* var sx = [ 2, 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 operation:
* var out = sorthp( x );
* // returns <ndarray>
*
* var arr = ndarray2array( out );
* // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ]
*/
function sorthp( x ) {
var nargs;
var opts;
var ord;
var sh;
var o;
nargs = arguments.length;
// Resolve input ndarray meta data:
ord = getOrder( x );
// Case: sorthp( x )
if ( nargs < 2 ) {
return base( x, broadcastScalar( 1.0, 'generic', [], ord ) );
}
o = arguments[ 1 ];
// Case: sorthp( x, ??? )
if ( nargs === 2 ) {
// Case: sorthp( x, sortOrder_ndarray )
if ( isndarrayLike( o ) ) {
// As the operation is performed across all dimensions, `o` is assumed to be a zero-dimensional ndarray...
return base( x, o );
}
// Case: sorthp( x, sortOrder_scalar )
if ( isNumber( o ) ) {
return base( x, broadcastScalar( o, 'generic', [], ord ) );
}
// Case: sorthp( x, sortOrder_string )
if ( isString( o ) ) {
if ( o === 'asc' || o === 'ascending' ) {
o = 1.0;
} else if ( o === 'dsc' || o === 'descending' ) {
o = -1.0;
} else {
throw new TypeError( format( 'invalid argument. Second argument must be a valid sort order. Value: `%s`.', o ) );
}
return base( x, broadcastScalar( o, 'generic', [], ord ) );
}
// Case: sorthp( x, opts )
opts = o;
o = 1.0;
// Intentionally fall through...
}
// Case: sorthp( x, sortOrder, opts )
else { // nargs > 2
opts = arguments[ 2 ];
}
// Case: sorthp( x, sortOrder_ndarray, opts )
if ( isndarrayLike( o ) ) {
// When not provided `dims`, the operation is performed across all dimensions and `o` is assumed to be a zero-dimensional ndarray; when `dims` is provided, we need to broadcast `o` to match the shape of the non-core dimensions...
if ( hasOwnProp( opts, 'dims' ) ) {
o = maybeBroadcastArray( o, nonCoreShape( getShape( x ), opts.dims ) ); // eslint-disable-line max-len
}
}
// Case: sorthp( x, sortOrder_scalar, opts )
else if ( isNumber( o ) ) {
if ( hasOwnProp( opts, 'dims' ) ) {
sh = nonCoreShape( getShape( x ), opts.dims );
} else {
sh = [];
}
o = broadcastScalar( o, 'generic', sh, getOrder( x ) );
}
// Case: sorthp( x, sortOrder_string, opts )
else if ( isString( o ) ) {
if ( o === 'asc' || o === 'ascending' ) {
o = 1.0;
} else if ( o === 'dsc' || o === 'descending' ) {
o = -1.0;
} else {
throw new TypeError( format( 'invalid argument. Second argument must be a valid sort order. Value: `%s`.', o ) );
}
if ( hasOwnProp( opts, 'dims' ) ) {
sh = nonCoreShape( getShape( x ), opts.dims );
} else {
sh = [];
}
o = broadcastScalar( o, 'generic', sh, getOrder( x ) );
} else {
throw new TypeError( format( 'invalid argument. Second argument must be either an ndarray, a numeric scalar value, or a valid sort order string. Value: `%s`.', o ) );
}
return base( x, o, opts );
}
// EXPORTS //
module.exports = sorthp;
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