stdlib/lib/node_modules/@stdlib/blas/base/dsymv/docs/repl.txt at ccaab177b6475bed835d1b828273d1e9b9895757 · stdlib-js/stdlib · GitHub

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{{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: Float64Array
        Input matrix.

    lda: integer
        Stride of the first dimension of `A` (a.k.a., leading dimension of the
        matrix `A`).

    x: Float64Array
        Input vector.

    sx: integer
        Index increment for `x`.

    β: number
        Scalar constant.

    y: Float64Array
        Output vector.

    sy: integer
        Index increment for `y`.

    Returns
    -------
    y: Float64Array
        Output vector.

    Examples
    --------
    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0 ] );
    > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0 ] );
    > var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 2.0, 1.0 ] );
    > {{alias}}( 'row-major', 'upper', 2, 1.0, A, 2, x, 1, 1.0, y, 1 )
    <Float64Array>[ 4.0, 4.0 ]


{{alias}}.ndarray( uplo, N, α, A, sa1, sa2, oa, 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
    ----------
    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: Float64Array
        Input matrix.

    sa1: integer
        Stride for the first dimension of `A`.

    sa2: integer
        Stride for the second dimension of `A`.

    oa: integer
        Starting index for `A`.

    x: Float64Array
        Input vector.

    sx: integer
        Index increment for `x`.

    ox: integer
        Starting index for `x`.

    β: number
        Scalar constant.

    y: Float64Array
        Output vector.

    sy: integer
        Index increment for `y`.

    oy: integer
        Starting index for `y`.

    Returns
    -------
    y: Float64Array
        Output array.

    Examples
    --------
    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0 ] );
    > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0 ] );
    > var A = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 2.0, 1.0 ] );
    > {{alias}}.ndarray( 'upper', 2, 1.0, A, 2, 1, 0, x, 1, 0, 1.0, y, 1, 0 )
    <Float64Array>[ 4.0, 4.0 ]

    See Also
    --------