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Module « scipy.interpolate »

Fonction bisplrep - module scipy.interpolate

Signature de la fonction bisplrep

def bisplrep(x, y, z, w=None, xb=None, xe=None, yb=None, ye=None, kx=3, ky=3, task=0, s=None, eps=1e-16, tx=None, ty=None, full_output=0, nxest=None, nyest=None, quiet=1) 

Description

help(scipy.interpolate.bisplrep)

Find a bivariate B-spline representation of a surface.

Given a set of data points (x[i], y[i], z[i]) representing a surface
z=f(x,y), compute a B-spline representation of the surface. Based on
the routine SURFIT from FITPACK.

Parameters
----------
x, y, z : ndarray
    Rank-1 arrays of data points.
w : ndarray, optional
    Rank-1 array of weights. By default ``w=np.ones(len(x))``.
xb, xe : float, optional
    End points of approximation interval in `x`.
    By default ``xb = x.min(), xe=x.max()``.
yb, ye : float, optional
    End points of approximation interval in `y`.
    By default ``yb=y.min(), ye = y.max()``.
kx, ky : int, optional
    The degrees of the spline (1 <= kx, ky <= 5).
    Third order (kx=ky=3) is recommended.
task : int, optional
    If task=0, find knots in x and y and coefficients for a given
    smoothing factor, s.
    If task=1, find knots and coefficients for another value of the
    smoothing factor, s.  bisplrep must have been previously called
    with task=0 or task=1.
    If task=-1, find coefficients for a given set of knots tx, ty.
s : float, optional
    A non-negative smoothing factor. If weights correspond
    to the inverse of the standard-deviation of the errors in z,
    then a good s-value should be found in the range
    ``(m-sqrt(2*m),m+sqrt(2*m))`` where m=len(x).
eps : float, optional
    A threshold for determining the effective rank of an
    over-determined linear system of equations (0 < eps < 1).
    `eps` is not likely to need changing.
tx, ty : ndarray, optional
    Rank-1 arrays of the knots of the spline for task=-1
full_output : int, optional
    Non-zero to return optional outputs.
nxest, nyest : int, optional
    Over-estimates of the total number of knots. If None then
    ``nxest = max(kx+sqrt(m/2),2*kx+3)``,
    ``nyest = max(ky+sqrt(m/2),2*ky+3)``.
quiet : int, optional
    Non-zero to suppress printing of messages.

Returns
-------
tck : array_like
    A list [tx, ty, c, kx, ky] containing the knots (tx, ty) and
    coefficients (c) of the bivariate B-spline representation of the
    surface along with the degree of the spline.
fp : ndarray
    The weighted sum of squared residuals of the spline approximation.
ier : int
    An integer flag about splrep success. Success is indicated if
    ier<=0. If ier in [1,2,3] an error occurred but was not raised.
    Otherwise an error is raised.
msg : str
    A message corresponding to the integer flag, ier.

See Also
--------
splprep, splrep, splint, sproot, splev
UnivariateSpline, BivariateSpline

Notes
-----
See `bisplev` to evaluate the value of the B-spline given its tck
representation.

If the input data is such that input dimensions have incommensurate
units and differ by many orders of magnitude, the interpolant may have
numerical artifacts. Consider rescaling the data before interpolation.

References
----------
.. [1] Dierckx P.:An algorithm for surface fitting with spline functions
   Ima J. Numer. Anal. 1 (1981) 267-283.
.. [2] Dierckx P.:An algorithm for surface fitting with spline functions
   report tw50, Dept. Computer Science,K.U.Leuven, 1980.
.. [3] Dierckx P.:Curve and surface fitting with splines, Monographs on
   Numerical Analysis, Oxford University Press, 1993.

Examples
--------
Examples are given :ref:`in the tutorial <tutorial-interpolate_2d_spline>`.

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