{{alias}}( order, uplo, N, α, A, lda, x, sx, β, y, sy ) Performs the matrix-vector operation `y = α*A*x + β*y` where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. Indexing is relative to the first index. To introduce an offset, use typed array views. If `N` is equal to `0`, the function returns `y` unchanged. If `α` equals `0` and `β` equals `1`, the function returns `y` unchanged. Parameters ---------- order: string Row-major (C-style) or column-major (Fortran-style) order. Must be either 'row-major' or 'column-major'. uplo: string Specifies whether to reference the upper or lower triangular part of `A`. Must be either 'upper' or 'lower'. N: integer Number of elements along each dimension of `A`. α: number Scalar constant. A: Float32Array Matrix. lda: integer Stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`). x: Float32Array Input vector. sx: integer Index increment for `x`. β: number Scalar constant. y: Float32Array Output vector. sy: integer Index increment for `y`. Returns ------- y: Float32Array Output vector. Examples -------- > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0 ] ); > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0 ] ); > var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 2.0, 1.0 ] ); > {{alias}}( 'row-major', 'upper', 2, 1.0, A, 2, x, 1, 1.0, y, 1 ) [ 4.0, 4.0 ] {{alias}}.ndarray( order, uplo, N, α, A, lda, x, sx, ox, β, y, sy, oy ) Performs the matrix-vector operation `y = α*A*x + β*y` using alternative indexing semantics and where `α` and `β` are scalars, `x` and `y` are `N` element vectors, and `A` is an `N` by `N` symmetric matrix. While typed array views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. Parameters ---------- order: string Row-major (C-style) or column-major (Fortran-style) order. Must be either 'row-major' or 'column-major'. uplo: string Specifies whether to reference the upper or lower triangular part of `A`. Must be either 'upper' or 'lower'. N: integer Number of elements along each dimension of `A`. α: number Scalar constant. A: Float32Array Matrix. lda: integer Stride of the first dimension of `A` (a.k.a., leading dimension of the matrix `A`). x: Float32Array Input vector. sx: integer Index increment for `x`. ox: integer Starting index for `x`. β: number Scalar constant. y: Float32Array Output vector. sy: integer Index increment for `y`. oy: integer Starting index for `y`. Returns ------- y: Float32Array Output array. Examples -------- > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0 ] ); > var y = new {{alias:@stdlib/array/float32}}( [ 1.0, 1.0 ] ); > var A = new {{alias:@stdlib/array/float32}}( [ 1.0, 2.0, 2.0, 1.0 ] ); > var ord = 'row-major'; > {{alias}}.ndarray( ord, 'upper', 2, 1.0, A, 2, x, 1, 0, 1.0, y, 1, 0 ) [ 4.0, 4.0 ] See Also --------