issue_comments: 386874264

This data as json

html_url issue_url id node_id user created_at updated_at author_association body reactions performed_via_github_app issue
https://github.com/pydata/xarray/pull/2104#issuecomment-386874264 https://api.github.com/repos/pydata/xarray/issues/2104 386874264 MDEyOklzc3VlQ29tbWVudDM4Njg3NDI2NA== 6815844 2018-05-06T12:00:33Z 2018-05-06T12:00:33Z MEMBER

RegularGridInterpolator handles NaNs pretty much the same way @shoyer describes it.

I did not certainly realize how RegularGridInterpolator works, but it seems to work with nan including array too as you pointed out. But higher order interpolations (RegularGridInterpolator is linear), such as RectBivariateSpline, would not work (return an all nan array) when just 1 nan is included in the target array. It is the same with higher order interpolations in scipy.interpolate.interp1d such as cubic.

Why don't leave the NaN handling part to the actual function doing the interpolation?

It is the original behavior of scipy.interpolate functions (except for linear or nearest methods), which do some matrix inversions in its algorithm.

I think the addition of the linear interpolation is still nice, but it would be nicer if we could also implement nan-skipping interpolations, which will enable us to use higher order interpolation with nan-including arrays.

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   320275317