scipy.interpolate.SmoothBivariateSpline.__call__

SmoothBivariateSpline.__call__(x, y, dx=0, dy=0, grid=True)

Evaluate the spline or its derivatives at given positions.

Parameters:

x, y : array_like

Input coordinates.

If grid is False, evaluate the spline at points (x[i], y[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 x, y. The arrays must be sorted to increasing order.

Note that the axis ordering is inverted relative to the output of meshgrid.

dx : int

Order of x-derivative

New in version 0.14.0.

dy : int

Order of y-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.