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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 isRowMajor = require( '@stdlib/ndarray/base/assert/is-row-major' );
// MAIN //
/**
* Initializes columns K+1:N of a matrix to columns of the unit matrix.
*
* @private
* @param {PositiveInteger} M - number of rows in matrix `A`
* @param {PositiveInteger} N - number of columns in matrix `A`
* @param {NonNegativeInteger} K - starting column index for initialization
* @param {Float64Array} A - input matrix
* @param {integer} strideA1 - stride of the first dimension of `A`
* @param {integer} strideA2 - stride of the second dimension of `A`
* @param {NonNegativeInteger} offsetA - index offset for `A`
* @returns {Float64Array} matrix `A` with columns K+1:N initialized as unit matrix columns
*
* @example
* var Float64Array = require( '@stdlib/array/float64' );
*
* var A = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 ] );
* initUnitColumns( 3, 3, 1, A, 1, 3, 0 );
* // A => <Float64Array>[ 1.0, 2.0, 3.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0 ]
*/
function initUnitColumns( M, N, K, A, strideA1, strideA2, offsetA ) {
var ia1;
var ia2;
var del;
var da;
var i;
var j;
// Initialize columns k+1:n to columns of the unit matrix
if ( isRowMajor( [ strideA1, strideA2 ] ) ) {
ia2 = offsetA + (K*strideA2);
da = strideA1 - ((N-K) * strideA2);
for ( i = 0; i < M; i++ ) {
for ( j = K; j < N; j++ ) {
if ( i === j ) {
A[ ia2 ] = 1.0;
} else {
A[ ia2 ] = 0.0;
}
ia2 += strideA2;
}
ia2 += da;
}
} else {
ia1 = offsetA + (K*strideA1) + (K*strideA2);
ia2 = offsetA + (K*strideA2);
da = strideA2 - (M * strideA1);
del = strideA1 + strideA2;
for ( i = K; i < N; i++ ) {
for ( j = 0; j < M; j++ ) {
A[ ia2 ] = 0.0;
ia2 += strideA1;
}
A[ ia1 ] = 1.0;
ia2 += da;
ia1 += del;
}
}
return A;
}
// EXPORTS //
module.exports = initUnitColumns;
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