
{{alias}}( N, k, x,sx, N1,p,sp, N2,a,sa, out,so, w,sw )
    Calculates the k-th discrete forward difference of a strided array.

    The `N` and stride parameters determine which elements in the strided arrays
    are accessed at runtime.

    Indexing is relative to the first index. To introduce an offset, use a typed
    array view.

    If `N + N1 + N2 <= 1` or `k >= N + N1 + N2`, the function returns the
    output array unchanged.

    Parameters
    ----------
    N: integer
        Number of indexed elements.

    k: integer
        Number of times to recursively compute differences.

    x: Array|TypedArray
        Input array.

    sx: integer
        Stride length for `x`.

    N1: integer
        Number of indexed elements for `p`.

    p: Array|TypedArray
        Array containing values to prepend prior to computing differences.

    sp: integer
        Stride length for `p`.

    N2: integer
        Number of indexed elements for `a`.

    a: Array|TypedArray
        Array containing values to append prior to computing differences.

    sa: integer
        Stride length for `a`.

    out: Array|TypedArray
        Output array. Must have `N + N1 + N2 - k` indexed elements.

    so: integer
        Stride length for `out`.

    w: Array|TypedArray
        Workspace array. Must have `N + N1 + N2 - 1` indexed elements.

    sw: integer
        Stride length for `w`.

    Returns
    -------
    out: Array|TypedArray
        Output array.

    Examples
    --------
    // Standard usage:
    > var x = [ 1.0, -2.0, 2.0 ];
    > var p = [ 0.0 ];
    > var a = [ 3.0 ];
    > var out = [ 0.0, 0.0, 0.0, 0.0 ];
    > var w = [ 0.0, 0.0, 0.0, 0.0 ];
    > {{alias}}( x.length, 1, x, 1, 1, p, 1, 1, a, 1, out, 1, w, 1 )
    [ 1.0, -3.0, 4.0, 1.0 ]

    // Using `N` and stride parameters:
    > x = [ 2.0, 4.0, 6.0, 8.0, 10.0 ];
    > p = [ 1.0 ];
    > a = [ 11.0 ];
    > out = [ 0.0, 0.0, 0.0, 0.0 ];
    > w = [ 0.0, 0.0, 0.0, 0.0 ];
    > {{alias}}( 3, 1, x, 2, 1, p, 1, 1, a, 1, out, 1, w, 1 )
    [ 1.0, 4.0, 4.0, 1.0 ]

    // Using view offsets:
    > var x0 = new {{alias:@stdlib/array/float64}}( [ 2.0, 4.0, 6.0, 8.0, 10.0 ] );
    > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
    > p = [ 1.0 ];
    > a = [ 11.0 ];
    > out = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
    > w = [ 0.0, 0.0, 0.0, 0.0, 0.0 ];
    > {{alias}}( x1.length, 1, x1, 1, 1, p, 1, 1, a, 1, out, 1, w, 1 )
    [ 3.0, 2.0, 2.0, 2.0, 1.0 ]


{{alias}}.ndarray( N, k, x,sx,ox, N1,p,sp,op, N2,a,sa,oa, out,so,oo, w,sw,ow )
    Calculates the k-th discrete forward difference of a strided array using
    alternative indexing semantics.

    While typed array views mandate a view offset based on the underlying
    buffer, the offset parameters support indexing semantics based on starting
    indices.

    Parameters
    ----------
    N: integer
        Number of indexed elements.

    k: integer
        Number of times to recursively compute differences.

    x: Array|TypedArray
        Input array.

    sx: integer
        Stride length for `x`.

    ox: integer
        Starting index for `x`.

    N1: integer
        Number of indexed elements for `p`.

    p: Array|TypedArray
        Array containing values to prepend prior to computing differences.

    sp: integer
        Stride length for `p`.

    op: integer
        Starting index for `p`.

    N2: integer
        Number of indexed elements for `a`.

    a: Array|TypedArray
        Array containing values to append prior to computing differences.

    sa: integer
        Stride length for `a`.

    oa: integer
        Starting index for `a`.

    out: Array|TypedArray
        Output array. Must have `N + N1 + N2 - k` indexed elements.

    so: integer
        Stride length for `out`.

    oo: integer
        Starting index for `out`.

    w: Array|TypedArray
        Workspace array. Must have `N + N1 + N2 - 1` indexed elements.

    sw: integer
        Stride length for `w`.

    ow: integer
        Starting index for `w`.

    Returns
    -------
    out: Array|TypedArray
        Output array.

    Examples
    --------
    // Standard usage:
    > var x = [ 1.0, -2.0, 2.0 ];
    > var p = [ 0.0 ];
    > var a = [ 3.0 ];
    > var out = [ 0.0, 0.0, 0.0, 0.0 ];
    > var w = [ 0.0, 0.0, 0.0, 0.0 ];
    > {{alias}}.ndarray( 3, 1, x,1,0, 1, p,1,0, 1, a,1,0, out,1,0, w,1,0 )
    [ 1.0, -3.0, 4.0, 1.0 ]

    // Advanced indexing:
    > x = [ 1.0, -2.0, 2.0 ];
    > p = [ 0.0 ];
    > a = [ 3.0 ];
    > out = [ 0.0, 0.0, 0.0 ];
    > w = [ 0.0, 0.0, 0.0 ];
    > {{alias}}.ndarray( 2, 1, x,1,1, 1, p,1,0, 1, a,1,0, out,1,0, w,1,0 )
    [ -2.0, 4.0, 1.0 ]

    See Also
    --------
