- scipy.interpolate.splrep(x, y, w=None, xb=None, xe=None, k=3, task=0, s=None, t=None, full_output=0, per=0, quiet=1): Find the B-spline representation of 1-D curve. Given the set of data points
(x[i], y[i])determine a smooth spline approximation of degree k on the intervalxb <= x <= xe. - class scipy.interpolate.UnivariateSpline(x, y, w=None, bbox=[None, None], k=3, s=None, ext=0, check_finite=False): One-dimensional smoothing spline fit to a given set of data points. Fits a spline y = spl(x) of degree k to the provided x, y data. s specifies the number of knots by specifying a smoothing condition.
It looks like quite the same, except this note in the UnivariateSpline manual:
splrep: An older, non object-oriented wrapping of FITPACK
Return values are not described for UnivariateSpline.
So, is UnivariateSpline a replacement for splrep, or are use cases not totally the same?