issue_comments: 407522046
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https://github.com/pydata/xarray/issues/2288#issuecomment-407522046 | https://api.github.com/repos/pydata/xarray/issues/2288 | 407522046 | MDEyOklzc3VlQ29tbWVudDQwNzUyMjA0Ng== | 1828519 | 2018-07-24T19:21:05Z | 2018-07-24T19:21:05Z | CONTRIBUTOR | @snowman2 Awesome. Thanks for the info, this is really good stuff to know. In your own projects and use of raster-like data, do you ever deal with non-uniform/non-projected data? How do you prefer to handle/store individual lon/lat values for each pixel? Also it looks like xarray would have to be updated to add the "crs" coordinate since currently it is not considered a coordinate variable. So a new library may need to have custom to_netcdf/open_dataset methods, right? It kind of seems like a new library may be needed for this although I was hoping to avoid it. All of the conversions we've talked about could be really useful to a lot of people. I'm not aware of an existing library that handles these conversions as one of its main purposes and they always end up as a "nice utility" that helps the library as a whole. It seems like a library to solve this issue should be able to do the following:
Beyond reading/writing NetCDF and geotiff files I would be worried that this new library could easily suffer from major scope creep. Especially since this is one of the main purposes of the satpy library, even if it is dedicated to satellite imagery right now. @snowman2 I'm guessing the data cube project has similar use cases. If the reading/writing is limited to a specific set of formats then I could see pyresample being a playground for this type of functionality. The main reason for a playground versus a new from-scratch package would be the use of existing utilities in pyresample assuming resampling is a major feature of this new specification. Yet another braindump...complete. |
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