This is documentation for an old release of SciPy (version 0.12.0). Read this page in the documentation of the latest stable release (version 1.15.1).
Base class for bivariate splines.
This describes a spline s(x, y) of degrees kx and ky on the rectangle [xb, xe] * [yb, ye] calculated from a given set of data points (x, y, z).
To construct these splines, call either SmoothBivariateSpline or LSQBivariateSpline.
See also
Methods
__call__(x, y[, mth]) | Evaluate spline at the grid points defined by the coordinate arrays |
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]. |