scipy.interpolate.barycentric_interpolate¶

scipy.interpolate.
barycentric_interpolate
(xi, yi, x, axis=0)[source]¶ Convenience function for polynomial interpolation.
Constructs a polynomial that passes through a given set of points, then evaluates the polynomial. For reasons of numerical stability, this function does not compute the coefficients of the polynomial.
This function uses a “barycentric interpolation” method that treats the problem as a special case of rational function interpolation. This algorithm is quite stable, numerically, but even in a world of exact computation, unless the x coordinates are chosen very carefully  Chebyshev zeros (e.g. cos(i*pi/n)) are a good choice  polynomial interpolation itself is a very illconditioned process due to the Runge phenomenon.
Parameters: xi : array_like
1d array of x coordinates of the points the polynomial should pass through
yi : array_like
The y coordinates of the points the polynomial should pass through.
x : scalar or array_like
Points to evaluate the interpolator at.
axis : int, optional
Axis in the yi array corresponding to the xcoordinate values.
Returns: y : scalar or array_like
Interpolated values. Shape is determined by replacing the interpolation axis in the original array with the shape of x.
See also
Notes
Construction of the interpolation weights is a relatively slow process. If you want to call this many times with the same xi (but possibly varying yi or x) you should use the class
BarycentricInterpolator
. This is what this function uses internally.