Adds open_datatree and load_datatree to the tutorial module #10082
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xarray/tests/test_tutorial.py
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| cache_dir = tmp_path / tutorial._default_cache_dir_name | ||
| ds = tutorial.open_dataset(self.testfile, cache_dir=cache_dir).load() | ||
| ds = tutorial.open_dataset(testfile, cache_dir=cache_dir).load() |
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it's probably better to just hard-code the dataset name into the test, there's no point in parametrizing this (to be clear, this part of the test suite is pretty old):
| ds = tutorial.open_dataset(testfile, cache_dir=cache_dir).load() | |
| ds = tutorial.open_dataset("tiny", cache_dir=cache_dir).load() |
| url = external_urls[name] | ||
| else: | ||
| path = pathlib.Path(name) | ||
| if not path.suffix: |
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do the hdf5 file work with both netcdf4 and h5netcdf? Otherwise we might need to specialize, like we do with grib
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Yes, imerghh_730.HDF5 and imerghh_830.HDF5, works for both engines. I think if we wanted to add hdf5 files without named dimensions we would want to specify the engine as h5netcdf.
EDIT:
Since pydata/xarray-data#32 was merged, we do have to explicitly add the extension, e.g. xr.tutorial.open_datatree('imerghh_830.hdf5'), otherwise it defaults to .nc
| from xarray import DataArray, tutorial | ||
| from xarray.tests import assert_identical, network | ||
| from xarray import DataArray, DataTree, tutorial | ||
| from xarray.testing import assert_identical |
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Updated this to use the xarray.testing module's assert_identical because xarray.tests didn't support DataTree objects.
TomNicholas
added
topic-documentation
topic-DataTree
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FYI these checks look like they are failing in main 😬 |
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yep, that's a change to |
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Sure! Is there a issue for this yet? I can get a PR started and you can jump in when you're free. |
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there's #10084, but nothing else. I think you can just open the PR |
| * ``"imerghh_730"``: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 from 2021-08-29T07:30:00.000Z | ||
| * ``"imerghh_830"``: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 from 2021-08-29T08:30:00.000Z |
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I think this is good to go, though I do think that for tutorial documentation on xarray.DataTree we might want to add some other possible datasets because these two don't really have a structure that fully requires/shows off the use of DataTree (as I discussed with @eni-awowale the other day).
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Yeah that makes sense to me! I think we can modify the IMERG dataset as you suggested and maybe note that the modified version is derived from this original product.
* main: (85 commits) Adds open_datatree and load_datatree to the tutorial module (pydata#10082) Fix version in requires_zarr_v3 fixture (pydata#10145) Fix `open_datatree` when `decode_cf=False` (pydata#10141) [docs] `DataTree` cannot be constructed from `DataArray` (pydata#10142) Refactor datetime and timedelta encoding for increased robustness (pydata#9498) Fix test_distributed::test_async (pydata#10138) Refactor concat / combine / merge into `xarray/structure` (pydata#10134) Split `apply_ufunc` out of `computation.py` (pydata#10133) Refactor modules from `core` into `xarray.computation` (pydata#10132) Refactor compatibility modules into xarray.compat package (pydata#10131) Fix type issues from pandas stubs (pydata#10128) Don't skip tests when on a `mypy` branch (pydata#10129) Change `python_files` in `pyproject.toml` to a list (pydata#10127) Better `uv` compatibility (pydata#10124) explicitly cast the dtype of `where`'s condition parameter to `bool` (pydata#10087) Use `to_numpy` in time decoding (pydata#10081) Pin pandas stubs (pydata#10119) Fix broken Zarr test (pydata#10109) Update asv badge url in README.md (pydata#10113) fix and supress some test warnings (pydata#10104) ...
Adds
open_datatreeandload_datatreeto the tutorial modulewhats-new.rstapi.rst