scipy.interpolate.BivariateSpline#
- class BivariateSpline[source]#
Base class for bivariate splines.
This describes a spline
s(x, y)of degreeskxandkyon 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.
See Also#
- 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
- __init__()#
Methods
__init__()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.