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  • WeatherGod · 2 ✖

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  • API design for pointwise indexing · 2 ✖

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  • CONTRIBUTOR · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
342576941 https://github.com/pydata/xarray/issues/475#issuecomment-342576941 https://api.github.com/repos/pydata/xarray/issues/475 MDEyOklzc3VlQ29tbWVudDM0MjU3Njk0MQ== WeatherGod 291576 2017-11-07T18:29:12Z 2017-11-07T18:29:12Z CONTRIBUTOR

Yeah, we need to move something forward, because the main benefit of xarray is the ability to manage datasets from multiple sources in a consistent way. And data from different sources will almost always be in different projections.

My current problem that I need to solve right now is that I am ingesting model data that is in a LCC projection and ingesting radar data that is in a simple regular lat/lon grid. Both dataset objects have latitude and longitude coordinate arrays, I just need to get both datasets to have the same lat/lon grid.

I guess I could continue using my old scipy-based solution (using map_coordinates() or RectBivariateSpline), but at the very least, it would make sense to have some documentation demonstrating how one might go about this very common problem, even if it is showing how to use the scipy-based tools with xarrays. If that is of interest, I can see what I can write up after I am done my immediate task.

 
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   API design for pointwise indexing 95114700
342553465 https://github.com/pydata/xarray/issues/475#issuecomment-342553465 https://api.github.com/repos/pydata/xarray/issues/475 MDEyOklzc3VlQ29tbWVudDM0MjU1MzQ2NQ== WeatherGod 291576 2017-11-07T17:11:49Z 2017-11-07T17:11:49Z CONTRIBUTOR

So, what has become the consensus for performing regridding/resampling? I see a lot of suggestions, but I have no sense of what is mature enough to use in production-level code. I also haven't seen anything in the documentation about this topic, even if it just refers people to another project.

 
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   API design for pointwise indexing 95114700

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