scipy tutorial - Baustatik-Info-Server

SciPy Reference Guide, Release 0.8.dev
See also:
splprep, splrep, splint, sproot, splev - evaluation, roots, integral UnivariateSpline, BivariateSpline - an
alternative wrapping
of the FITPACK functions
Notes: Based on algorithms from:
3.5.4 2-D Splines
See Also:
Dierckx P.
[An algorithm for surface fitting with spline functions] Ima J. Numer. Anal. 1 (1981) 267-283.
Dierckx P.
[An algorithm for surface fitting with spline functions] report tw50, Dept. Computer Science,K.U.Leuven,
1980.
Dierckx P.
[Curve and surface fitting with splines, Monographs on] Numerical Analysis, Oxford University
Press, 1993.
scipy.ndimage.map_coordinates
BivariateSpline Bivariate spline s(x,y) of degrees kx and ky on the rectangle [xb,xe] x [yb,
ye] calculated from a given set of data points (x,y,z).
SmoothBivariateSpline(x, Smooth bivariate spline approximation.
y, z, None, None[, ...])
LSQBivariateSpline(x, y, z, Weighted least-squares spline approximation.
tx, ty, None, None)
class BivariateSpline()
Bivariate spline s(x,y) of degrees kx and ky on the rectangle [xb,xe] x [yb, ye] calculated from a given set of
data points (x,y,z).
See also:
bisplrep, bisplev - an older wrapping of FITPACK UnivariateSpline - a similar class for univariate spline interpolation
SmoothUnivariateSpline - to create a BivariateSpline through the
given points
LSQUnivariateSpline - to create a BivariateSpline using weighted
least-squares fitting
Methods
ev(xi, yi) Evaluate spline at points (x[i], y[i]), i=0,...,len(x)-1
get_coeffs() Return spline coefficients.
get_knots() Return a tuple (tx,ty) where tx,ty contain knots positions of the spline with respect to x-,
y-variable, respectively.
get_residual() Return weighted sum of squared residuals of the spline
integral(xa, xb,
ya, yb)
Evaluate the integral of the spline over area [xa,xb] x [ya,yb].
ev(xi, yi)
Evaluate spline at points (x[i], y[i]), i=0,...,len(x)-1
3.5. Interpolation (scipy.interpolate) 205