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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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| 1388326248 | I_kwDOAMm_X85SwC1o | 7093 | xarray allows several types for netcdf attributes. Is it expected ? | ghislainp 10563614 | open | 0 | 3 | 2022-09-27T20:20:46Z | 2022-10-04T20:46:32Z | CONTRIBUTOR | What is your issue?Xarray is permissive regarding the type of the attributes. If using a wrong type, the error reveals the valid types: For serialization to netCDF files, its value must be of one of the following types: str, Number, ndarray, number, list, tuple Using a non iterable type used to raise an Exception when reading the saved netcdf, but this is now solved with #7085 The pending question is whether it is valid to save netcdf attributes with type other than a string or not. The following lines are working (in a notebook): ```python xr.DataArray([1, 2, 3], attrs={'units': 1}, name='x').to_netcdf("tmp.nc") !ncdump tmp.nc xr.DataArray([1, 2, 3], attrs={'units': np.nan}, name='x').to_netcdf("tmp.nc") !ncdump tmp.nc xr.DataArray([1, 2, 3], attrs={'units': ['xarray', 'is', 'very', 'permissive', ]}, name='x').to_netcdf("tmp.nc") !ncdump tmp.nc ``` On the other hand, the following line raises an error: ```python xr.DataArray([1, 2, 3], attrs={'units': None}, name='x').to_netcdf("tmp.nc") ``` |
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xarray 13221727 | issue | ||||||||
| 709503596 | MDU6SXNzdWU3MDk1MDM1OTY= | 4465 | combine_by_coords could use allclose instead of equal to compare coordinates | ghislainp 10563614 | open | 0 | 4 | 2020-09-26T09:26:05Z | 2020-09-26T21:30:35Z | CONTRIBUTOR | Is your feature request related to a problem? Please describe. When a coordinate in different dataset / netcdf files has slightly different values, combine_by_coords considers the coordinate are different and attempts a concatenation of the coordinates. Concretely, I produce netcdf with (lat, lon, time) coordinates, annually. Apparently the lat is not the same in all the files (difference is 1e-14), which I suspect is due to different pyproj version used to produce the lon,lat grid. Reprocessing all the annual netcdf is not an option. When using open_mfdataset on these netcdf, the lat coordinate is concatenated which leads to a MemoryError in my case. Describe the solution you'd like Two options: - add a coord_tolerance argument to xr.combine_by_coords and use np.allclose to compare the coordinates. In line 69 combine.py the comparison uses strict equality "if not all(index.equals(indexes[0]) for index in indexes[1:]):". This does not break the compatibility because coord_tolerance=0 should be the default.
Describe alternatives you've considered
Additional context |
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xarray 13221727 | issue |
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