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* @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 isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
var arraylike2object = require( '@stdlib/array/base/arraylike2object' );
var abs = require( '@stdlib/math/base/special/abs' );
var accessors = require( './accessors.js' );
// MAIN //
/**
* Generates a Fiedler matrix using alternative indexing semantics.
*
* @param {NonNegativeInteger} N - number of indexed elements in `x`
* @param {Collection} x - input array containing coefficients
* @param {integer} strideX - stride length for `x`
* @param {NonNegativeInteger} offsetX - starting index for `x`
* @param {Collection} out - output array
* @param {integer} strideOut1 - stride length for the first dimension of `out`
* @param {integer} strideOut2 - stride length for the second dimension of `out`
* @param {NonNegativeInteger} offsetOut - starting index for `out`
* @returns {Collection} output matrix
*
* @example
* var x = [ 1.0, 4.0, 12.0 ];
* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
*
* gfiedler( 3, x, 1, 0, out, 3, 1, 0 );
* // out => [ 0.0, 3.0, 11.0, 3.0, 0.0, 8.0, 11.0, 8.0, 0.0 ]
*/
function gfiedler( N, x, strideX, offsetX, out, strideOut1, strideOut2, offsetOut ) { // eslint-disable-line max-len
var ix0;
var ix1;
var so1;
var so2;
var ox;
var oo;
var io;
var ij;
var v;
var i;
var j;
if ( N <= 0 ) {
return out;
}
// As a Fiedler matrix is symmetric, generating the transposed matrix yields the same matrix, and, thus, when the output matrix is stored in column-major order, we can swap the strides so that the innermost loop always moves over contiguous memory, thus ensuring cache optimal traversal...
if ( isRowMajor( [ strideOut1, strideOut2 ] ) ) {
so1 = strideOut1;
so2 = strideOut2;
} else { // column-major
so1 = strideOut2;
so2 = strideOut1;
}
ox = arraylike2object( x );
oo = arraylike2object( out );
if ( ox.accessorProtocol || oo.accessorProtocol ) {
accessors( N, ox, strideX, offsetX, oo, so1, so2, offsetOut );
return out;
}
// Fill the matrix with the pairwise absolute differences between the coefficients...
ix0 = offsetX;
io = offsetOut;
for ( i = 0; i < N; i++ ) {
v = x[ ix0 ];
ix1 = offsetX;
ij = io;
for ( j = 0; j < N; j++ ) {
out[ ij ] = abs( v - x[ ix1 ] );
ix1 += strideX;
ij += so2;
}
ix0 += strideX;
io += so1;
}
return out;
}
// EXPORTS //
module.exports = gfiedler;
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