scipy.interpolate.LinearNDInterpolator.

__call__

LinearNDInterpolator.__call__(xi)

Evaluate interpolator at given points.

Parameters:

x1, x2, … xn: array-like of float

Points where to interpolate data at. x1, x2, … xn can be array-like of float with broadcastable shape. or x1 can be array-like of float with shape (..., ndim)

simplex_tolerance: float, optional

Multiplier for the default tolerance QHull uses to assign a simplex to the xi in scipy.spatial.Delaunay.find_simplex. Default is 1.0. Increase if there are difficulties assigning points to simplexes; this is most reproducible with points exatly on the border of a very oblique triangle. Only relevant for linear and 2-D cubic interpolation.

Added in version 1.18.0.

Raises:

ValueError

If simplex_tolerance <= 0