scipy.interpolate.SmoothSphereBivariateSpline.__call__

SmoothSphereBivariateSpline.__call__(theta, phi, dtheta=0, dphi=0, grid=True)

Evaluate the spline or its derivatives at given positions.

Parameters:

theta, phi : array_like

Input coordinates.

If grid is False, evaluate the spline at points (theta[i], phi[i]), i=0, ..., len(x)-1. Standard Numpy broadcasting is obeyed.

If grid is True: evaluate spline at the grid points defined by the coordinate arrays theta, phi. The arrays must be sorted to increasing order.

dtheta : int, optional

Order of theta-derivative

New in version 0.14.0.

dphi : int

Order of phi-derivative

New in version 0.14.0.

grid : bool

Whether to evaluate the results on a grid spanned by the input arrays, or at points specified by the input arrays.

New in version 0.14.0.