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- milancurcic · 3 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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1282946332 | https://github.com/pydata/xarray/issues/4285#issuecomment-1282946332 | https://api.github.com/repos/pydata/xarray/issues/4285 | IC_kwDOAMm_X85MeDUc | milancurcic 4133310 | 2022-10-18T20:11:30Z | 2022-10-18T20:12:51Z | NONE | Hi All, Thank you for the detailed discussion and thank you @TomNicholas for pointing it out to me. I read the thread last week and have been digesting it. There are many details that go over my head and will keep re-reading them to develop a better understanding of the problem. Two weeks ago I started working part-time on CloudDrift. This is an NSF EarthCube-funded project led by @selipot. @philippemiron was the lead developer in the first year of the project and he laid the foundation of the data structure that we need and example notebooks. The project's purpose is to make working with Lagrangian data (primarily ocean but generalizable to other kinds) easier for scientists who consume such data while also optimizing the storage of such data. This is use case 1 in Tom's list of use cases here. Clouddrift currently provides an implementation of a Other goals of the project include providing example and tutorial notebooks, writing adapters for canonical ocean Lagrangian datasets, writing methods for oceanographic diagnostics, and more general developer/scientist advocacy kind of work. I am very much interested in making our What do you think should be the next step? Should we plan a video call to explore options? |
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Awkward array backend? 667864088 | |
486390856 | https://github.com/pydata/xarray/issues/1809#issuecomment-486390856 | https://api.github.com/repos/pydata/xarray/issues/1809 | MDEyOklzc3VlQ29tbWVudDQ4NjM5MDg1Ng== | milancurcic 4133310 | 2019-04-24T19:22:52Z | 2019-04-24T19:24:27Z | NONE | I can't seem recreate this with a minimal example, ```python from netCDF4 import Dataset import xarray as xr with Dataset('test.nc', format='NETCDF4', mode='w') as nc: nc.createDimension('dim1', size=0) var = nc.createVariable('var1', 'f8', dimensions=('dim1')) var[:] = [1., 2., 3.] var.setncattr('coordinates', 'dim1') xr.open_dataset('test.nc').to_netcdf('test2.nc') ``` There is something peculiar about how WRF handles the Interestingly, I can workaround the WRF
while this doesn't:
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WRF output : cannot serialize variable 286072335 | |
485210441 | https://github.com/pydata/xarray/issues/1809#issuecomment-485210441 | https://api.github.com/repos/pydata/xarray/issues/1809 | MDEyOklzc3VlQ29tbWVudDQ4NTIxMDQ0MQ== | milancurcic 4133310 | 2019-04-21T01:09:04Z | 2019-04-24T19:24:02Z | NONE | I ran into this issue trying to roundtrip a WRF output file. It looks like xarray raises an error for any NetCDF file that has variables with a
~~Both this choice, and the proposed solution in this issue (delete all ~~The solution that makes more sense to me is to raise a warning and overwrite or ignore the Or perhaps I'm missing something obvious here... Let me know either way. I'd be happy to make a PR to patch this. |
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WRF output : cannot serialize variable 286072335 |
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issue 2