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scipy.interpolate.krogh_interpolate
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scipy.interpolate.krogh_interpolate(xi, yi, x, der=0, axis=0)[source]
Convenience function for polynomial interpolation.
See KroghInterpolator for more details.
Parameters : | xi : array_like
yi : array_like
Known y-coordinates, of shape (xi.size, R). Interpreted as
vectors of length R, or scalars if R=1.
x : array_like
Point or points at which to evaluate the derivatives.
der : int or list
How many derivatives to extract; None for all potentially
nonzero derivatives (that is a number equal to the number
of points), or a list of derivatives to extract. This number
includes the function value as 0th derivative.
axis : int, optional
Axis in the yi array corresponding to the x-coordinate values.
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Returns : | d : ndarray
If the interpolator’s values are R-dimensional then the
returned array will be the number of derivatives by N by R.
If x is a scalar, the middle dimension will be dropped; if
the yi are scalars then the last dimension will be dropped.
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Notes
Construction of the interpolating polynomial is a relatively expensive
process. If you want to evaluate it repeatedly consider using the class
KroghInterpolator (which is what this function uses).