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Fonction insert - module scipy.interpolate

Signature de la fonction insert

def insert(x, tck, m=1, per=0) 

Description

insert.__doc__

    Insert knots into a B-spline.

    Given the knots and coefficients of a B-spline representation, create a
    new B-spline with a knot inserted `m` times at point `x`.
    This is a wrapper around the FORTRAN routine insert of FITPACK.

    Parameters
    ----------
    x (u) : array_like
        A 1-D point at which to insert a new knot(s).  If `tck` was returned
        from ``splprep``, then the parameter values, u should be given.
    tck : a `BSpline` instance or a tuple
        If tuple, then it is expected to be a tuple (t,c,k) containing
        the vector of knots, the B-spline coefficients, and the degree of
        the spline.
    m : int, optional
        The number of times to insert the given knot (its multiplicity).
        Default is 1.
    per : int, optional
        If non-zero, the input spline is considered periodic.

    Returns
    -------
    BSpline instance or a tuple
        A new B-spline with knots t, coefficients c, and degree k.
        ``t(k+1) <= x <= t(n-k)``, where k is the degree of the spline.
        In case of a periodic spline (``per != 0``) there must be
        either at least k interior knots t(j) satisfying ``t(k+1)<t(j)<=x``
        or at least k interior knots t(j) satisfying ``x<=t(j)<t(n-k)``.
        A tuple is returned iff the input argument `tck` is a tuple, otherwise
        a BSpline object is constructed and returned.

    Notes
    -----
    Based on algorithms from [1]_ and [2]_.

    Manipulating the tck-tuples directly is not recommended. In new code,
    prefer using the `BSpline` objects.

    References
    ----------
    .. [1] W. Boehm, "Inserting new knots into b-spline curves.",
        Computer Aided Design, 12, p.199-201, 1980.
    .. [2] P. Dierckx, "Curve and surface fitting with splines, Monographs on
        Numerical Analysis", Oxford University Press, 1993.

    Examples
    --------
    You can insert knots into a B-spline.

    >>> from scipy.interpolate import splrep, insert
    >>> x = np.linspace(0, 10, 5)
    >>> y = np.sin(x)
    >>> tck = splrep(x, y)
    >>> tck[0]
    array([ 0.,  0.,  0.,  0.,  5., 10., 10., 10., 10.])

    A knot is inserted:

    >>> tck_inserted = insert(3, tck)
    >>> tck_inserted[0]
    array([ 0.,  0.,  0.,  0.,  3.,  5., 10., 10., 10., 10.])

    Some knots are inserted:

    >>> tck_inserted2 = insert(8, tck, m=3)
    >>> tck_inserted2[0]
    array([ 0.,  0.,  0.,  0.,  5.,  8.,  8.,  8., 10., 10., 10., 10.])