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  • rabernat · 3 ✖

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  • xarray / vtk integration · 3 ✖

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  • MEMBER · 3 ✖
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810683846 https://github.com/pydata/xarray/issues/4470#issuecomment-810683846 https://api.github.com/repos/pydata/xarray/issues/4470 MDEyOklzc3VlQ29tbWVudDgxMDY4Mzg0Ng== rabernat 1197350 2021-03-31T01:22:29Z 2021-03-31T01:22:29Z MEMBER

I just saw this very cool tweet about ipyvista / iris integration and it reminded me of this thread.

Are there any clear steps we can take to help advance the vtk / pyvista / xarray integration further?

 
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   xarray / vtk integration 710357592
700670814 https://github.com/pydata/xarray/issues/4470#issuecomment-700670814 https://api.github.com/repos/pydata/xarray/issues/4470 MDEyOklzc3VlQ29tbWVudDcwMDY3MDgxNA== rabernat 1197350 2020-09-29T12:31:42Z 2020-09-29T20:06:51Z MEMBER

You can see an example of using xarray with structured curvilinear coordinates here: - http://xarray.pydata.org/en/stable/examples/multidimensional-coords.html - http://xarray.pydata.org/en/stable/examples/ROMS_ocean_model.html

And with unstructured data here: - http://gallery.pangeo.io/repos/rsignell-usgs/esip-gallery/02_National_Water_Model.html - http://gallery.pangeo.io/repos/rsignell-usgs/esip-gallery/01_hurricane_ike_water_levels.html

The key concept is that xarray supports both dimensions coordinates and non-dimension coordinates. The dimension coordinates must be 1D, but the non-dimension coordinates can have any dimensionality. For a regular lat-lon grid, a variable might have dimensions like this temp(time, depth, lat, lon) A structured curvilinear 2D grid might instead look like temp(time, depth, j, i) with additional coordinate variables lon(j, i) lat(j, i) which can be used for visualization (but not, currently, for indexing) A fully unstructured mesh in 2D would instead look like temp(time, depth, cell_id) lon(cell_id) lat(cell_id)

This is exactly what netCDF does to encode these data types. Anything that can go into a netCDF file can be represented in Xarray. You just don't get the full functionality in terms of label-based selection. That will hopefully change as we implement more flexible indexing (see https://github.com/pydata/xarray/projects/1).

Another limitation of xarray is that it has no explicit notion of "cell bounds," other than recognizing these as coordinates (see #2844). Our xgcm package works around this limitation in some simple ways.

 
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   xarray / vtk integration 710357592
700671843 https://github.com/pydata/xarray/issues/4470#issuecomment-700671843 https://api.github.com/repos/pydata/xarray/issues/4470 MDEyOklzc3VlQ29tbWVudDcwMDY3MTg0Mw== rabernat 1197350 2020-09-29T12:33:46Z 2020-09-29T12:33:46Z MEMBER

A key point I forgot to make...if downstream packages or accessor implementers know how to do something useful with these extra coordinates, they are free to do so! The data are there...xarray just doesn't currently make much use of them.

 
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   xarray / vtk integration 710357592

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