Base class for bivariate splines.
This describes a spline
s(x, y)of degrees
kyon the rectangle
[xb, xe] * [yb, ye]calculated from a given set of data points
(x, y, z).
a similar class for univariate spline interpolation
to create a BivariateSpline through the given points
to create a BivariateSpline using weighted least-squares fitting
__call__(x, y[, dx, dy, grid])
Evaluate the spline or its derivatives at given positions.
ev(xi, yi[, dx, dy])
Evaluate the spline at points
Return spline coefficients.
Return a tuple (tx,ty) where tx,ty contain knots positions of the spline with respect to x-, y-variable, respectively.
Return weighted sum of squared residuals of the spline approximation: sum ((w[i]*(z[i]-s(x[i],y[i])))**2,axis=0)
integral(xa, xb, ya, yb)
Evaluate the integral of the spline over area [xa,xb] x [ya,yb].