scipy.interpolate.BivariateSpline¶
- class scipy.interpolate.BivariateSpline[source]¶
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).
This class is meant to be subclassed, not instantiated directly. To construct these splines, call either SmoothBivariateSpline or LSQBivariateSpline.
See also
- UnivariateSpline
- a similar class for univariate spline interpolation
- SmoothBivariateSpline
- to create a BivariateSpline through the given points
- LSQBivariateSpline
- to create a BivariateSpline using weighted least-squares fitting
- SphereBivariateSpline
- bivariate spline interpolation in spherical cooridinates
- bisplrep
- older wrapping of FITPACK
- bisplev
- older wrapping of FITPACK
Methods
__call__(x, y[, mth, dx, dy, grid]) Evaluate the spline or its derivatives at given positions. ev(xi, yi[, dx, dy]) Evaluate the spline at points Returns the interpolated value at (xi[i], yi[i]), i=0,...,len(xi)-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].