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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 isColumnMajor = require( '@stdlib/ndarray/base/assert/is-column-major-string' );
var resolveLayout = require( '@stdlib/blas/base/layout-resolve-str' );
var stride2offset = require( '@stdlib/strided/base/stride2offset' );
var max = require( '@stdlib/math/base/special/fast/max' );
var format = require( '@stdlib/string/format' );
var resolveMode = require( './mode.js' );
var ndarray = require( './ndarray.js' );
// MAIN //
/**
* Generates a convolution matrix.
*
* @param {(integer|string)} order - storage layout
* @param {string} mode - convolution mode
* @param {NonNegativeInteger} m - number of indexed elements in `x`
* @param {NonNegativeInteger} N - number of columns in the output matrix
* @param {Collection} x - input array
* @param {integer} strideX - stride length for `x`
* @param {Collection} out - output array
* @param {PositiveInteger} ldo - stride length between successive contiguous vectors of the matrix `out` (a.k.a., leading dimension of `out`)
* @throws {TypeError} first argument must be a valid order
* @throws {TypeError} second argument must be a valid mode
* @throws {RangeError} eighth argument must be a valid stride
* @returns {Collection} output matrix
*
* @example
* var x = [ 1.0, 2.0, 3.0 ];
* var out = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
*
* gconvolutionMatrix( 'row-major', 'full', 3, 3, x, 1, out, 3 );
* // out => [ 1.0, 0.0, 0.0, 2.0, 1.0, 0.0, 3.0, 2.0, 1.0, 0.0, 3.0, 2.0, 0.0, 0.0, 3.0 ]
*/
function gconvolutionMatrix( order, mode, m, N, x, strideX, out, ldo ) {
var iscm;
var tmp;
var sa1;
var sa2;
var ox;
var k;
var l;
l = resolveLayout( order );
if ( l === null ) {
throw new TypeError( format( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ) );
}
if ( mode !== 'full' && mode !== 'same' && mode !== 'valid' ) {
throw new TypeError( format( 'invalid argument. Second argument must be a valid mode. Value: `%s`.', mode ) );
}
if ( m <= 0 || N <= 0 ) {
return out;
}
tmp = resolveMode( mode, m, N, [ 0, 0 ] );
k = tmp[ 0 ];
iscm = isColumnMajor( l );
if ( iscm ) {
if ( ldo < max( 1, k ) ) {
throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.', k, ldo ) );
}
sa1 = 1;
sa2 = ldo;
} else { // order === 'row-major'
if ( ldo < max( 1, N ) ) {
throw new RangeError( format( 'invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.', N, ldo ) );
}
sa1 = ldo;
sa2 = 1;
}
ox = stride2offset( m, strideX );
return ndarray( mode, m, N, x, strideX, ox, out, sa1, sa2, 0 );
}
// EXPORTS //
module.exports = gconvolutionMatrix;
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