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| 1 | +/** |
| 2 | +* @license Apache-2.0 |
| 3 | +* |
| 4 | +* Copyright (c) 2024 The Stdlib Authors. |
| 5 | +* |
| 6 | +* Licensed under the Apache License, Version 2.0 (the "License"); |
| 7 | +* you may not use this file except in compliance with the License. |
| 8 | +* You may obtain a copy of the License at |
| 9 | +* |
| 10 | +* http://www.apache.org/licenses/LICENSE-2.0 |
| 11 | +* |
| 12 | +* Unless required by applicable law or agreed to in writing, software |
| 13 | +* distributed under the License is distributed on an "AS IS" BASIS, |
| 14 | +* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 15 | +* See the License for the specific language governing permissions and |
| 16 | +* limitations under the License. |
| 17 | +*/ |
| 18 | + |
| 19 | +'use strict'; |
| 20 | + |
| 21 | +// MODULES // |
| 22 | + |
| 23 | +var dfill = require( '@stdlib/blas/ext/base/dfill' ).ndarray; |
| 24 | +var dscal = require( '@stdlib/blas/base/dscal' ).ndarray; |
| 25 | +var max = require( '@stdlib/math/base/special/max' ); |
| 26 | +var isLayout = require( '@stdlib/blas/base/assert/is-layout' ); |
| 27 | +var isMatrixTriangle = require( '@stdlib/blas/base/assert/is-matrix-triangle' ); |
| 28 | + |
| 29 | + |
| 30 | +// MAIN // |
| 31 | + |
| 32 | +/** |
| 33 | +* Performs the matrix-vector operation `y = alpha*A*x + beta*y` where `alpha` and `beta` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric band matrix, with `K` super-diagonals. |
| 34 | +* |
| 35 | +* @param {string} order - storage layout |
| 36 | +* @param {string} uplo - specifies whether the upper or lower triangular part of the symmetric matrix `A` should be referenced |
| 37 | +* @param {NonNegativeInteger} N - number of elements along each dimension of `A` |
| 38 | +* @param {NonNegativeInteger} K - number of super-diagonals of the matrix `A` |
| 39 | +* @param {number} alpha - scalar constant |
| 40 | +* @param {Float64Array} A - matrix |
| 41 | +* @param {PositiveInteger} LDA - stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`) |
| 42 | +* @param {Float64Array} x - first input array |
| 43 | +* @param {integer} strideX - `x` stride length |
| 44 | +* @param {NonNegativeInteger} offsetX - starting `x` index |
| 45 | +* @param {number} beta - scalar constant |
| 46 | +* @param {Float64Array} y - second input array |
| 47 | +* @param {integer} strideY - `y` stride length |
| 48 | +* @param {NonNegativeInteger} offsetY - starting `y` index |
| 49 | +* @throws {TypeError} first argument must be a valid order |
| 50 | +* @throws {TypeError} second argument must specify whether to reference the lower or upper triangular matrix |
| 51 | +* @throws {RangeError} third argument must be a nonnegative integer |
| 52 | +* @throws {RangeError} sixth argument must be greater than or equal to max(1,N) |
| 53 | +* @throws {RangeError} eighth argument must be non-zero |
| 54 | +* @throws {RangeError} twelfth argument must be non-zero |
| 55 | +* @returns {Float64Array} `y` |
| 56 | +* |
| 57 | +* @example |
| 58 | +* var Float64Array = require( '@stdlib/array/float64' ); |
| 59 | +* |
| 60 | +* var A = new Float64Array( [ 1.0, 2.0, 0.0, 4.0, 3.0, 5.0 ] ); |
| 61 | +* var x = new Float64Array( [ 1.0, 2.0, 3.0 ] ); |
| 62 | +* var y = new Float64Array( [ 0.0, 0.0, 0.0 ] ); |
| 63 | +* |
| 64 | +* dsbmv( 'row-major', 'lower', 3, 1, 1.0, A, 2, x, 1, 0, 0.0, y, 1, 0 ); |
| 65 | +* // y => <Float64Array>[ 2.0, 17.0, 21.0 ] |
| 66 | +*/ |
| 67 | +function dsbmv( order, uplo, N, K, alpha, A, LDA, x, strideX, offsetX, beta, y, strideY, offsetY ) { // eslint-disable-line max-params, max-len |
| 68 | + var temp1; |
| 69 | + var temp2; |
| 70 | + var jmin; |
| 71 | + var ix; |
| 72 | + var iy; |
| 73 | + var jx; |
| 74 | + var jy; |
| 75 | + var ox; |
| 76 | + var oy; |
| 77 | + var i; |
| 78 | + var j; |
| 79 | + |
| 80 | + if ( !isLayout( order ) ) { |
| 81 | + throw new TypeError( 'invalid argument. First argument must be a valid order. Value: `%s`.', order ); |
| 82 | + } |
| 83 | + if ( !isMatrixTriangle( uplo ) ) { |
| 84 | + throw new TypeError( 'invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.', uplo ); |
| 85 | + } |
| 86 | + if ( N < 0 ) { |
| 87 | + throw new RangeError( 'invalid argument. Third argument must be a nonnegative integer. Value: `%d`.', N ); |
| 88 | + } |
| 89 | + if ( K < 0 ) { |
| 90 | + throw new RangeError( 'invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.', K ); |
| 91 | + } |
| 92 | + if ( LDA < max( K + 1 ) ) { |
| 93 | + throw new RangeError( 'invalid argument. Seventh argument must be greater than or equal to ( K + 1 ). Value: `%d`.', N, LDA ); |
| 94 | + } |
| 95 | + if ( strideX === 0 ) { |
| 96 | + throw new RangeError( 'invalid argument. Ninth argument must be non-zero. Value: `%d`.', strideX ); |
| 97 | + } |
| 98 | + if ( strideY === 0 ) { |
| 99 | + throw new RangeError( 'invalid argument. Therteenth argument must be non-zero. Value: `%d`.', strideY ); |
| 100 | + } |
| 101 | + if ( N === 0 || ( alpha === 0.0 && beta === 1.0 ) ) { |
| 102 | + return y; |
| 103 | + } |
| 104 | + // Form: y = beta*y |
| 105 | + if ( beta !== 1.0 ) { |
| 106 | + if ( beta === 0.0 ) { |
| 107 | + dfill( N, 0.0, y, strideY, offsetY ); |
| 108 | + } else { |
| 109 | + dscal( N, beta, y, strideY, offsetY ); |
| 110 | + } |
| 111 | + } |
| 112 | + if ( alpha === 0.0 ) { |
| 113 | + return y; |
| 114 | + } |
| 115 | + ox = offsetX; |
| 116 | + oy = offsetY; |
| 117 | + |
| 118 | + // Form: y = alpha*A*x + y |
| 119 | + if ( |
| 120 | + ( order === 'row-major' && uplo === 'upper' ) || |
| 121 | + ( order === 'column-major' && uplo === 'lower' ) |
| 122 | + ) { |
| 123 | + ix = ox; |
| 124 | + iy = oy; |
| 125 | + for ( i = 0; i < N; i++ ) { |
| 126 | + temp1 = alpha * x[ ix ]; |
| 127 | + temp2 = 0.0; |
| 128 | + jmin = max( 0, i - K ); |
| 129 | + jx = ox + ( jmin * strideX ); |
| 130 | + jy = oy + ( jmin * strideY ); |
| 131 | + for ( j = jmin; j < i; j++ ) { |
| 132 | + y[ jy ] += temp1 * A[ (i - j) + ( j * (K + 1) ) ]; |
| 133 | + temp2 += x[ jx ] * A[ (i - j) + ( j * (K + 1) ) ]; |
| 134 | + jx += strideX; |
| 135 | + jy += strideY; |
| 136 | + } |
| 137 | + y[ iy ] += ( temp1 * A[ 0 + ( i * (K + 1) ) ] ) + ( alpha * temp2 ); |
| 138 | + ix += strideX; |
| 139 | + iy += strideY; |
| 140 | + } |
| 141 | + return y; |
| 142 | + } |
| 143 | + |
| 144 | + // ( order === 'row-major' && uplo === 'lower') || ( order === 'column-major' && uplo === 'upper' ) |
| 145 | + if ( |
| 146 | + ( order === 'row-major' && uplo === 'lower' ) || |
| 147 | + ( order === 'column-major' && uplo === 'upper' ) |
| 148 | + ) { |
| 149 | + ix = ox; |
| 150 | + iy = oy; |
| 151 | + for ( i = 0; i < N; i++ ) { |
| 152 | + temp1 = alpha * x[ ix ]; |
| 153 | + temp2 = 0.0; |
| 154 | + jmin = max( 0, i - K ); |
| 155 | + jx = ox + ( jmin * strideX ); |
| 156 | + jy = oy + ( jmin * strideY ); |
| 157 | + for ( j = jmin; j < i; j++ ) { |
| 158 | + y[ jy ] += temp1 * ( A[ (K + j - i) + ( i * (K + 1) ) ] ); |
| 159 | + temp2 += x[ jx ] * ( A[ (K + j - i) + ( i * (K + 1) ) ] ); |
| 160 | + jx += strideX; |
| 161 | + jy += strideY; |
| 162 | + } |
| 163 | + y[ iy ] += ( temp1 * ( A[ K + ( i * (K + 1) ) ] ) ) + ( alpha * temp2 ); |
| 164 | + ix += strideX; |
| 165 | + iy += strideY; |
| 166 | + } |
| 167 | + return y; |
| 168 | + } |
| 169 | +} |
| 170 | + |
| 171 | + |
| 172 | +// EXPORTS // |
| 173 | + |
| 174 | +module.exports = dsbmv; |
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