# 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 or RectBivariateSpline.

UnivariateSpline

a smooth univariate spline to fit a given set of data points.

SmoothBivariateSpline

a smoothing bivariate spline through the given points

LSQBivariateSpline

a bivariate spline using weighted least-squares fitting

RectSphereBivariateSpline

a bivariate spline over a rectangular mesh on a sphere

SmoothSphereBivariateSpline

a smoothing bivariate spline in spherical coordinates

LSQSphereBivariateSpline

a bivariate spline in spherical coordinates using weighted least-squares fitting

RectBivariateSpline

a bivariate spline over a rectangular mesh.

bisplrep

a function to find a bivariate B-spline representation of a surface

bisplev

a function to evaluate a bivariate B-spline and its derivatives

Methods

 __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 get_coeffs(self) Return spline coefficients. get_knots(self) Return a tuple (tx,ty) where tx,ty contain knots positions of the spline with respect to x-, y-variable, respectively. get_residual(self) 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].

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