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Bump to 0.6.0rc1 (#515)
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.github/workflows/build_workflow.yml

+13-11
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@@ -24,17 +24,17 @@ jobs:
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cancel_others: ${{ env.CANCEL_OTHERS }}
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paths_ignore: ${{ env.PATHS_IGNORE }}
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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name: Checkout Code Repository
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uses: actions/checkout@v3
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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name: Set up Python 3.10
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uses: actions/setup-python@v3
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with:
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python-version: "3.10"
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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# Run all pre-commit hooks on all the files.
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# Getting only staged files can be tricky in case a new PR is opened
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# since the action is run on a branch in detached head state
@@ -59,10 +59,10 @@ jobs:
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paths_ignore: ${{ env.PATHS_IGNORE }}
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do_not_skip: '["push", "workflow_dispatch"]'
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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uses: actions/checkout@v3
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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name: Set up Conda Environment
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uses: conda-incubator/setup-miniconda@v2
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with:
@@ -77,13 +77,13 @@ jobs:
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# Refresh the cache every 24 hours to avoid inconsistencies of package versions
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# between the CI pipeline and local installations.
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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id: get-date
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name: Get Date
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run: echo "today=$(/bin/date -u '+%Y%m%d')" >> $GITHUB_OUTPUT
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shell: bash
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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id: cache
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name: Cache Conda env
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uses: actions/cache@v3
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# Increase this value to reset cache if conda-env/ci.yml has not changed in the workflow
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CACHE_NUMBER: 0
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- if: $${{ steps.skip_check.outputs.should_skip != 'true' || steps.cache.outputs.cache-hit != 'true' }}
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- if: |
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steps.skip_check.outputs.should_skip == 'false' &&
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steps.cache.outputs.cache-hit == 'false'
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name: Update environment
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run: |
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mamba env update -n xcdat_ci -f conda-env/ci.yml
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# Make sure the Python version in the env matches the current matrix version.
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mamba install -c conda-forge python=${{ matrix.python-version }}
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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name: Install xcdat
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# Source: https://github.com/conda/conda-build/issues/4251#issuecomment-1053460542
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run: |
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python -m pip install --no-build-isolation --no-deps -e .
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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name: Run Tests
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run: |
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pytest
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- if: ${{ steps.skip_check.outputs.should_skip != 'true' }}
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- if: ${{ steps.skip_check.outputs.should_skip == 'false' }}
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name: Upload Coverage Report
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uses: codecov/codecov-action@v3
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with:

README.rst

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@@ -70,7 +70,7 @@ robust analysis of climate data. xCDAT's design philosophy is focused on reducin
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overhead required to accomplish certain tasks in xarray. xCDAT aims to be compatible
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with structured grids that are `CF-compliant`_ (e.g., CMIP6). Some key xCDAT features
7272
are inspired by or ported from the core CDAT library, while others leverage powerful
73-
libraries in the xarray ecosystem (e.g., `xESMF`_ and `cf_xarray`_) to deliver
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libraries in the xarray ecosystem (e.g., `xESMF`_, `xgcm`_, `cf_xarray`_) to deliver
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robust APIs.
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The xCDAT core team's mission is to provide a maintainable and extensible package
@@ -123,8 +123,8 @@ For more instructions on how to contribute, please checkout our `Contributing Gu
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.. _GitHub Issue Tracker: https://github.com/xCDAT/xcdat/issues
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.. _Contributing Guide: https://xcdat.readthedocs.io/en/stable/contributing.html
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Available Features
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------------------
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Features
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--------
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* Extension of xarray's ``open_dataset()`` and ``open_mfdataset()`` with post-processing options
130130

@@ -153,15 +153,13 @@ Available Features
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* Horizontal structured regridding
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* Supports rectilinear and curvilinear grids
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* Python implementation of `regrid2`_ for handling cartesian latitude longitude grids
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* API that wraps `xESMF`_
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Planned Features
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----------------
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* Extends the `xESMF`_ horizontal regridding API
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* Python implementation of `regrid2`_ for handling cartesian latitude longitude grids
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* Vertical structured regridding
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* Support rectilinear and curvilinear grids
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* Extends the `xgcm`_ vertical regridding API
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Things We Are Striving For
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--------------------------
@@ -184,8 +182,9 @@ Things We Are Striving For
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* Support for parallelism using `dask`_ where it is both possible and makes sense
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.. _Metadata Interpretation: https://xcdat.readthedocs.io/en/stable/faqs.html#metadata-interpretation
187-
.. _regrid2: https://cdms.readthedocs.io/en/latest/regrid2.html
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.. _xESMF: https://pangeo-xesmf.readthedocs.io/en/latest/
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.. _regrid2: https://cdms.readthedocs.io/en/latest/regrid2.html
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.. _xgcm: https://xgcm.readthedocs.io/en/latest/index.html
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.. _dask: https://dask.org/
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.. _cf_xarray: https://cf-xarray.readthedocs.io/en/latest/index.html
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.. _CF convention: http://cfconventions.org/
@@ -205,6 +204,17 @@ Subscribe to our `mailing list`_ to stay notified of new releases.
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.. _conda-forge: https://anaconda.org/conda-forge/xcdat
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.. _GitHub Releases: https://anaconda.org/conda-forge/xcdat
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Useful Resources
208+
-----------------
209+
210+
We highly encourage you to checkout the awesome resources below to learn more about
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Xarray and Xarray usage in climate science!
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213+
- `Official Xarray Tutorials <https://tutorial.xarray.dev/intro.html>`_
214+
- `Xarray GitHub Discussion Forum <https://github.com/pydata/xarray/discussions>`_
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- `Pangeo Forum <https://foundations.projectpythia.org/core/xarray.html>`_
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- `Project Pythia <https://foundations.projectpythia.org/core/xarray.html>`_
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Acknowledgement
209219
---------------
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docs/index.rst

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@@ -20,7 +20,7 @@ robust analysis of climate data. xCDAT's design philosophy is focused on reducin
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overhead required to accomplish certain tasks in xarray. xCDAT aims to be compatible
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with structured grids that are `CF-compliant`_ (e.g., CMIP6). Some key xCDAT features
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are inspired by or ported from the core CDAT library, while others leverage powerful
23-
libraries in the xarray ecosystem (e.g., `xESMF`_ and `cf_xarray`_) to deliver
23+
libraries in the xarray ecosystem (e.g., `xESMF`_, `xgcm`_, `cf_xarray`_) to deliver
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robust APIs.
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The xCDAT core team's mission is to provide a maintainable and extensible package
@@ -73,8 +73,8 @@ For more instructions on how to contribute, please checkout our `Contributing Gu
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.. _GitHub Issue Tracker: https://github.com/xCDAT/xcdat/issues
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.. _Contributing Guide: https://xcdat.readthedocs.io/en/stable/contributing.html
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Available Features
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------------------
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Features
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--------
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* Extension of xarray's ``open_dataset()`` and ``open_mfdataset()`` with post-processing options
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@@ -103,15 +103,13 @@ Available Features
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* Horizontal structured regridding
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* Supports rectilinear and curvilinear grids
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* Python implementation of `regrid2`_ for handling cartesian latitude longitude grids
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* API that wraps `xESMF`_
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Planned Features
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----------------
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* Extends the `xESMF`_ horizontal regridding API
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* Python implementation of `regrid2`_ for handling cartesian latitude longitude grids
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* Vertical structured regridding
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* Support rectilinear and curvilinear grids
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* Extends the `xgcm`_ vertical regridding API
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Things We Are Striving For
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--------------------------
@@ -134,8 +132,9 @@ Things We Are Striving For
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* Support for parallelism using `dask`_ where it is both possible and makes sense
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.. _Metadata Interpretation: https://xcdat.readthedocs.io/en/stable/faqs.html#metadata-interpretation
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.. _regrid2: https://cdms.readthedocs.io/en/latest/regrid2.html
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.. _xESMF: https://pangeo-xesmf.readthedocs.io/en/latest/
136+
.. _regrid2: https://cdms.readthedocs.io/en/latest/regrid2.html
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.. _xgcm: https://xgcm.readthedocs.io/en/latest/index.html
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.. _dask: https://dask.org/
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.. _cf_xarray: https://cf-xarray.readthedocs.io/en/latest/index.html
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.. _CF convention: http://cfconventions.org/
@@ -155,6 +154,17 @@ Subscribe to our `mailing list`_ to stay notified of new releases.
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.. _conda-forge: https://anaconda.org/conda-forge/xcdat
156155
.. _GitHub Releases: https://anaconda.org/conda-forge/xcdat
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157+
Useful Resources
158+
-----------------
159+
160+
We highly encourage you to checkout the awesome resources below to learn more about
161+
Xarray and Xarray usage in climate science!
162+
163+
- `Official Xarray Tutorials <https://tutorial.xarray.dev/intro.html>`_
164+
- `Xarray GitHub Discussion Forum <https://github.com/pydata/xarray/discussions>`_
165+
- `Pangeo Forum <https://foundations.projectpythia.org/core/xarray.html>`_
166+
- `Project Pythia <https://foundations.projectpythia.org/core/xarray.html>`_
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Acknowledgement
159169
---------------
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setup.py

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test_suite="tests",
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tests_require=test_requires,
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url="https://github.com/xCDAT/xcdat",
38-
version="0.5.0",
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version="0.6.0rc1",
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zip_safe=False,
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)

tbump.toml

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github_url = "https://github.com/xCDAT/xcdat"
33

44
[version]
5-
current = "0.5.0"
5+
current = "0.6.0rc1"
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# Example of a semver regexp.
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# Make sure this matches current_version before

xcdat/__init__.py

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from xcdat.temporal import TemporalAccessor # noqa: F401
2121
from xcdat.utils import compare_datasets # noqa: F401
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23-
__version__ = "0.5.0"
23+
__version__ = "0.6.0rc1"

xcdat/bounds.py

+2-2
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@@ -244,8 +244,8 @@ def get_bounds(
244244
f"No bounds data variables were found for the '{axis}' axis. Make sure "
245245
"the dataset has bound data vars and their names match the 'bounds' "
246246
"attributes found on their related time coordinate variables. "
247-
"Alternatively, you can add bounds with `xcdat.add_missing_bounds` "
248-
"or `xcdat.add_bounds`."
247+
"Alternatively, you can add bounds with `ds.bounds.add_missing_bounds()` "
248+
"or `ds.bounds.add_bounds()`."
249249
)
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251251
bounds: Union[xr.Dataset, xr.DataArray] = self._dataset[

xcdat/temporal.py

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@@ -290,7 +290,7 @@ def group_average(
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>>> custom_seasons = [
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>>> ["Jan", "Feb", "Mar"], # "JanFebMar"
292292
>>> ["Apr", "May", "Jun"], # "AprMayJun"
293-
>>> ["Jul", "Aug", "Sep"], # "JunJulAug"
293+
>>> ["Jul", "Aug", "Sep"], # "JulAugSep"
294294
>>> ["Oct", "Nov", "Dec"], # "OctNovDec"
295295
>>> ]
296296
@@ -326,7 +326,7 @@ def group_average(
326326
>>> custom_seasons = [
327327
>>> ["Jan", "Feb", "Mar"], # "JanFebMar"
328328
>>> ["Apr", "May", "Jun"], # "AprMayJun"
329-
>>> ["Jul", "Aug", "Sep"], # "JunJulAug"
329+
>>> ["Jul", "Aug", "Sep"], # "JulAugSep"
330330
>>> ["Oct", "Nov", "Dec"], # "OctNovDec"
331331
>>> ]
332332
>>>
@@ -445,7 +445,7 @@ def climatology(
445445
>>> custom_seasons = [
446446
>>> ["Jan", "Feb", "Mar"], # "JanFebMar"
447447
>>> ["Apr", "May", "Jun"], # "AprMayJun"
448-
>>> ["Jul", "Aug", "Sep"], # "JunJulAug"
448+
>>> ["Jul", "Aug", "Sep"], # "JulAugSep"
449449
>>> ["Oct", "Nov", "Dec"], # "OctNovDec"
450450
>>> ]
451451
@@ -485,7 +485,7 @@ def climatology(
485485
>>> custom_seasons = [
486486
>>> ["Jan", "Feb", "Mar"], # "JanFebMar"
487487
>>> ["Apr", "May", "Jun"], # "AprMayJun"
488-
>>> ["Jul", "Aug", "Sep"], # "JunJulAug"
488+
>>> ["Jul", "Aug", "Sep"], # "JulAugSep"
489489
>>> ["Oct", "Nov", "Dec"], # "OctNovDec"
490490
>>> ]
491491
>>>
@@ -614,7 +614,7 @@ def departures(
614614
>>> custom_seasons = [
615615
>>> ["Jan", "Feb", "Mar"], # "JanFebMar"
616616
>>> ["Apr", "May", "Jun"], # "AprMayJun"
617-
>>> ["Jul", "Aug", "Sep"], # "JunJulAug"
617+
>>> ["Jul", "Aug", "Sep"], # "JulAugSep"
618618
>>> ["Oct", "Nov", "Dec"], # "OctNovDec"
619619
>>> ]
620620

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