BivariateSpline — SciPy v1.15.2 Manual (original) (raw)
scipy.interpolate.
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 orLSQBivariateSpline 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 |
| 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 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. |