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`.

Methods

 `__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]. `partial_derivative`(dx, dy) Construct a new spline representing a partial derivative of this spline.

`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