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from scipy import interpolate
P = interpolate.Akima1DInterpolator(xi, yi, axis=axis)
if der == 0:
return P(x)
elif interpolate._isscalar(der):
return P(x, der=der)
else:
return [P(x, nu) for nu in der]
There is no interpolate._isscalar so this would raise if it were ever reached. AFAICT we have only one test that gets to this function, must always have der == 0