Find the Bspline representation of 1D curve.
Given the set of data points (x[i], y[i]) determine a smooth spline approximation of degree k on the interval xb <= x <= xe.
Parameters :  x, y : array_like
w : array_like
xb, xe : float
k : int
task : {1, 0, 1}
s : float
t : int
full_output : bool
per : bool
quiet : bool


Returns :  tck : tuple
fp : array, optional
ier : int, optional
msg : str, optional

See also
UnivariateSpline, BivariateSpline, splprep, splev, sproot, spalde, splint, bisplrep, bisplev
Notes
See splev for evaluation of the spline and its derivatives. Uses the FORTRAN routine curfit from FITPACK.
References
Based on algorithms described in [1], [2], [3], and [4]:
[R40]  P. Dierckx, “An algorithm for smoothing, differentiation and integration of experimental data using spline functions”, J.Comp.Appl.Maths 1 (1975) 165184. 
[R41]  P. Dierckx, “A fast algorithm for smoothing data on a rectangular grid while using spline functions”, SIAM J.Numer.Anal. 19 (1982) 12861304. 
[R42]  P. Dierckx, “An improved algorithm for curve fitting with spline functions”, report tw54, Dept. Computer Science,K.U. Leuven, 1981. 
[R43]  P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993. 
Examples
>>> x = linspace(0, 10, 10)
>>> y = sin(x)
>>> tck = splrep(x, y)
>>> x2 = linspace(0, 10, 200)
>>> y2 = splev(x2, tck)
>>> plot(x, y, 'o', x2, y2)