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 | 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) 2026 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 isInteger = require( '@stdlib/assert/is-integer' ).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 nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
var getShape = require( '@stdlib/ndarray/shape' );
var getOrder = require( '@stdlib/ndarray/order' );
var defaults = require( '@stdlib/ndarray/defaults' );
var format = require( '@stdlib/string/format' );
var base = require( './base.js' );
// VARIABLES //
var DEFAULT_DTYPE = defaults.get( 'dtypes.integer' );
// MAIN //
/**
* Circularly shifts the elements of an input ndarray by a specified number of positions along one or more ndarray dimensions.
*
* @param {ndarrayLike} x - input ndarray
* @param {(ndarrayLike|integer)} k - number of positions to shift
* @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} second argument must be either an ndarray-like object or an integer
* @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} input ndarray
*
* @example
* var array = require( '@stdlib/ndarray/array' );
*
* var x = array( [ 1.0, 2.0, 3.0, 4.0 ], {
* 'shape': [ 2, 2 ],
* 'order': 'row-major'
* });
* // returns <ndarray>[ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]
*
* var y = circshift( x, 1, {
* 'dims': [ 0 ]
* });
* // returns <ndarray>[ [ 3.0, 4.0 ], [ 1.0, 2.0 ] ]
*/
function circshift( x, k ) {
var nargs;
var opts;
var sh;
var ka;
nargs = arguments.length;
// Case: circshift( x, k )
if ( nargs === 2 ) {
// Case: circshift( x, k_scalar )
if ( isInteger( k ) ) {
return base( x, broadcastScalar( k, DEFAULT_DTYPE, [], getOrder( x ) ) );
}
// Case: circshift( x, k_ndarray )
if ( isndarrayLike( k ) ) {
// As the operation is performed across all dimensions, `k` is assumed to be a zero-dimensional ndarray...
return base( x, k );
}
throw new TypeError( format( 'invalid argument. Second argument must be either an ndarray or an integer. Value: `%s`.', k ) );
}
// Case: circshift( x, k, opts )
opts = arguments[ 2 ];
// Case: circshift( x, k_scalar, opts )
if ( isInteger( k ) ) {
if ( hasOwnProp( opts, 'dims' ) ) {
sh = nonCoreShape( getShape( x ), opts.dims );
} else {
sh = [];
}
ka = broadcastScalar( k, DEFAULT_DTYPE, sh, getOrder( x ) );
}
// Case: circshift( x, k_ndarray, opts )
else if ( isndarrayLike( k ) ) {
// When not provided `dims`, the operation is performed across all dimensions and `k` is assumed to be a zero-dimensional ndarray; when `dims` is provided, we need to broadcast `k` to match the shape of the non-core dimensions...
if ( hasOwnProp( opts, 'dims' ) ) {
ka = maybeBroadcastArray( k, nonCoreShape( getShape( x ), opts.dims ) ); // eslint-disable-line max-len
} else {
ka = k;
}
} else {
throw new TypeError( format( 'invalid argument. Second argument must be either an ndarray or an integer. Value: `%s`.', k ) );
}
return base( x, ka, opts );
}
// EXPORTS //
module.exports = circshift;
|