issue_comments: 946337314

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https://github.com/pydata/xarray/issues/1603#issuecomment-946337314 https://api.github.com/repos/pydata/xarray/issues/1603 946337314 IC_kwDOAMm_X844Z_Yi 38346144 2021-10-19T03:32:13Z 2021-10-19T03:33:54Z NONE

Well, maybe we can consider the coordinates in a more generic way.

Let us define coordinate an array in data set cause co-indexed when we index its data set. It means that:

  • If A1,A2,A3 are in a same data set S, we index S[ {'A1':I} ] will return a new data set which not only have indexed A1, but they also been Indexed that the A2 A3 which have dims shared with A1. This behavior I call it co-index.

Use dims to determined the way how other array of the data set will be co-indexed.

  • If all dims of A1(as coordinate) are also in A2(as regular array co-indexed), obviously the behavior can simply follow the old behavior, just change at the same dim and contain others.
  • If A1 has a dim which not in A2, we should broadcast A2 at the dim, because the older behavior is to consider None dim as broadcast-able dim during other operation so co-index should follow it.

Some compatibility issues:

  • maybe need a New Type like DataArray but only have dims instead of both dims and coordinate
  • just define how Dataset to deal with index, maybe DataArray is simlar.
 
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