issue_comments: 947480352

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https://github.com/pydata/xarray/issues/1603#issuecomment-947480352 https://api.github.com/repos/pydata/xarray/issues/1603 947480352 IC_kwDOAMm_X844eWcg 38346144 2021-10-20T09:15:41Z 2021-10-20T09:15:41Z NONE

Hi @weipeng1999,

I'm not sure to fully understand your suggestion, would you mind sharing some illustrative examples?

It is useful to have two distinct coordinate variable vs data variable concepts. Although both are data arrays, the former is used to locate data in the dimensional space(s) defined by all dimensions in the dataset while the latter is used to store field data.

It also helps to have a clear separation between the coordinate variable and index concepts. An index is a specific data structure or object that allows efficient data extraction or alignment based one or more coordinate labels. Sometimes an index object may be handled like a data array (like pandas indexes) but this is not always the case (e.g., a KD-Tree).

Currently in Xarray the index concept is hidden behind "dimension" coordinate variables. The goal of the explicit index refactor is to bring it to the light and make it available to any coordinate (and also open it to custom index structures, not only pandas indexes).

It looks like what you suggest is some kind of implicit (co-)indexes hidden behind any dataset variable(s)? We actually took the opposite direction, trying to make everything explicit.

Try to explain my idea, I make a PPT.

 
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