I have a N-dimensional dataset, for which I need to apply multivariate interpolation. Is there a possible way to use different kind of interpolation methods in different dimensions? I considered to do this since I want to reduce the overall interpolation error, by choosing the interpolation type for each dimension. So far I only found methods which use a single interpolation type (e.g. cubic spline, linear,...) for all dimensions (such as the Matlab function interpn or the Scipy libary, ...). I'm already very thankful for a reference to literature, as I couldn't find anything.
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First, have a look at https://en.wikipedia.org/wiki/Multivariate_interpolation – Claude Leibovici Feb 10 '19 at 09:24
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Thank you. However, this source also uses the same interpolation type in all dimensions, if I'm correct? – jochim Feb 10 '19 at 09:29
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There is a bunch of different methods which are partly listed in the linked page. Have also a look at https://docs.scipy.org/doc/scipy/reference/interpolate.html This is a huge domain. – Claude Leibovici Feb 10 '19 at 09:50
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I'm familiar with multivariate interpolation in Matlab or using Scipy. Unfortunately, the interpolation method cannot be set to be different for each dimension for this available code. – jochim Feb 10 '19 at 10:01