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 smooth univariate spline to fit a given set of data points.
a smoothing bivariate spline through the given points
a bivariate spline using weighted least-squares fitting
a bivariate spline over a rectangular mesh on a sphere
a smoothing bivariate spline in spherical coordinates
a bivariate spline in spherical coordinates using weighted least-squares fitting
a bivariate spline over a rectangular mesh.
a function to find a bivariate B-spline representation of a surface
a function to evaluate a bivariate B-spline and its derivatives
__call__(self, x, y[, dx, dy, grid])
Evaluate the spline or its derivatives at given positions.
ev(self, 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(self, xa, xb, ya, yb)
Evaluate the integral of the spline over area [xa,xb] x [ya,yb].