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HISTORY.rst

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History
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=======
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v0.9.0 (02 June 2025)
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---------------------
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This release introduces key functional and performance enhancements
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across regridding, averaging, and coordinate handling workflows. Users
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can now output regridding weights and infer vertical target data,
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improving flexibility in vertical and horizontal transformations. Time
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frequency inference logic is more robust through median delta
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computation, and new options for ``skipna`` handling and spatial weight
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thresholds support more accurate and configurable statistical
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operations. Additional improvements to coordinate handling enable
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support for curvilinear grids. The release also includes critical bug
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fixes, expanded documentation, and updated compatibility for modern
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Python environments by dropping Python 3.9 and adding compatibility with
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Python 3.13.
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Enhancements
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~~~~~~~~~~~~
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- Adds option to output regridding weights and create mask for
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regridding by `Jason Boutte`_ in https://github.com/xCDAT/xcdat/pull/752
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- Adds ability to infer target data for vertical regridding by `Jason Boutte`_
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in https://github.com/xCDAT/xcdat/pull/756
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- Use the median of the delta instead of min for time freq inference by
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`Jill Chengzhu Zhang`_ in https://github.com/xCDAT/xcdat/pull/768
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- Add weight threshold option for spatial averaging by `Stephen Po-Chedley`_ in
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https://github.com/xCDAT/xcdat/pull/672
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- Enable ``skipna`` for spatial and temporal mean operations by `Jiwoo Lee`_ in
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https://github.com/xCDAT/xcdat/pull/655
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- Enhance coordinate handling and add curvilinear dataset support by
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`Tom Vo`_ in https://github.com/xCDAT/xcdat/pull/736
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Bug Fixes
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~~~~~~~~~
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- Eliminate performance bottleneck in ``temporal.group_average()`` by
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`will-s-hart <https://github.com/will-s-hart>`_ in https://github.com/xCDAT/xcdat/pull/767
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- Fix incorrect dimension used for temporal weights generation by
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`Tom Vo`_ in https://github.com/xCDAT/xcdat/pull/749
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Documentation
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~~~~~~~~~~~~~
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- Add ``.zenodo.json`` and ``CITATION.cff`` to cite core authors by
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`Tom Vo`_ in https://github.com/xCDAT/xcdat/pull/759
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- Add xCDAT tutorial datasets and update gallery notebooks by
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`Tom Vo`_ in https://github.com/xCDAT/xcdat/pull/705
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- Add endorsement section to docs with Xarray, Pangeo, and WCRP by `Tom Vo`_ in
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https://github.com/xCDAT/xcdat/pull/741,
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https://github.com/xCDAT/xcdat/pull/742,
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https://github.com/xCDAT/xcdat/pull/757
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DevOps
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~~~~~~
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- Make ``scipy`` a required dependency by `Tom Vo`_ in
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https://github.com/xCDAT/xcdat/pull/765
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- Drop Python 3.9 support and add compatibility for Python 3.13 by
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`Tom Vo`_ in https://github.com/xCDAT/xcdat/pull/721
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New Contributors
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~~~~~~~~~~~~~~~~
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- `will-s-hart <https://github.com/will-s-hart>`_ made their first contribution in
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https://github.com/xCDAT/xcdat/pull/767
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**Full Changelog**: https://github.com/xCDAT/xcdat/compare/v0.8.0...v0.9.0
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v0.8.0 (14 February 2025)
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README.rst

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`World Climate Research Programme (WCRP)`_ as a recommended tool for geoscience and
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climate data analysis.
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.. _Xarray ecosystem: https://docs.xarray.dev/en/stable/ecosystem.html#geosciences
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.. _Xarray ecosystem: https://docs.xarray.dev/en/stable/user-guide/ecosystem.html#geosciences
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.. _Pangeo community: https://www.pangeo.io/#ecosystem
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.. _World Climate Research Programme (WCRP): https://wcrp-cmip.org/tools/
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docs/getting-started-guide/overview.rst

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`World Climate Research Programme (WCRP)`_ as a recommended tool for geoscience and
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climate data analysis.
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.. _Xarray ecosystem: https://docs.xarray.dev/en/stable/ecosystem.html#geosciences
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.. _Xarray ecosystem: https://docs.xarray.dev/en/stable/user-guide/ecosystem.html#geosciences
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.. _Pangeo community: https://www.pangeo.io/#ecosystem
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.. _World Climate Research Programme (WCRP): https://wcrp-cmip.org/tools/
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tbump.toml

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github_url = "https://github.com/xCDAT/xcdat"
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[version]
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current = "0.8.0"
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current = "0.9.0"
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# Example of a semver regexp.
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# Make sure this matches current_version before

tests/test_temporal.py

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class TestInferFreq:
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def test_infers_hourly_frequency(self):
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times = xr.DataArray(pd.date_range("2000-01-01", periods=5, freq="H"))
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times = xr.DataArray(pd.date_range("2000-01-01", periods=5, freq="h"))
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freq = _infer_freq(times)
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assert freq == "hour"

xcdat/__init__.py

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from xcdat.temporal import TemporalAccessor # noqa: F401
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from xcdat.utils import compare_datasets # noqa: F401
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__version__ = "0.8.0"
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__version__ = "0.9.0"

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