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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