issue_comments: 852833408

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/issues/5376#issuecomment-852833408 https://api.github.com/repos/pydata/xarray/issues/5376 852833408 MDEyOklzc3VlQ29tbWVudDg1MjgzMzQwOA== 4160723 2021-06-02T08:07:38Z 2021-06-02T08:07:38Z MEMBER

What would be other examples like ImagePyramidIndex, outside of the multi-scale context?

There can be many examples like spatial indexes, complex grid indexes (select cell centers/faces of a staggered grid), distributed indexes, etc. Some of them are illustrated in a presentation I gave a couple of weeks ago (slides here). Although all those examples actually do data indexing.

In the multi-scale context, I admit that the name "index" may sound confusing since an ImagePyramidIndex would not really perform any data indexing based on some coordinate labels. Perhaps ImageRescaler would be a better name?

Such ImageRescaler might still fit well the broad purpose Xarray indexes IMHO since it would enable efficient data visualization through extraction and resampling.

The goal with Xarray custom indexes is to allow (many) kinds of objects with a scope possibly much more narrow than, e.g., pandas.Index, and that could possibly be reused in a broader range of operations like data selection, resampling, alignment, etc. Xarray indexes will be explicitly part of Xarray's Dataset/DataArray data model alongside data variables, coordinates and attributes, but unlike the latter they're not intended to wrap any (meta)data. Instead, they could wrap any structure or object that may be built from the (meta)data and that would enable efficient operations on the data (a-priori based on coordinate labels, although in some contexts like multi-scale this might be more accessory?).

 
{
    "total_count": 0,
    "+1": 0,
    "-1": 0,
    "laugh": 0,
    "hooray": 0,
    "confused": 0,
    "heart": 0,
    "rocket": 0,
    "eyes": 0
}
   902009258