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README.md

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@@ -26,8 +26,8 @@ SpatialData’s plotting capabilities allow to quickly visualise all contained m
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For more information on the `spatialdata-plot` library, please refer to the [documentation](https://spatialdata.scverse.org/projects/plot/en/latest/index.html). In particular, the
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- [API documentation][link-api].
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- [Example notebooks][link-notebooks] (section "Visiualizations")
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- [API documentation][link-api].
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- [Example notebooks][link-notebooks] (section "Visiualizations")
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## Installation
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docs/contributing.md

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Many tests will produce plots and check that they are correct by comparing them with a previously saved and serialized version of the same plots. The ground truth images are located in `tests/_images`. Different OS/versions may produce similar but not identical plots (for instance the ticks/padding could vary). To take into account for this please consider the following:
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- you should not use locally generated plots as ground truth images, but you should commit images that have been generated by a GitHub Action. The recommended workflow is to go to the ["actions" page for the repo](https://github.com/scverse/spatialdata-plot/actions/workflows/test.yaml), download the artifacts, and upload them as ground truth (after having reviewed them).
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- the ground truth images need to be updated when a new test is passing, or when a test starts producing a slightly different (but consistent) plot.
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- please never replace the ground truth images without having manually reviewed them.
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- if you run the tests locally in macOS or Windows they will likely fail because the ground truth images are generated using Ubuntu. To overcome this you can use `act`, which will generate a Docker reproducing the environment used in the GitHub Action. After the Docker container is generated you can use it within IDEs to run tests and debug code.
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- in the case of PyCharm, it is easier to create a container from a `Dockerfile` instead of using `act`. Please in such case use the `Dockerfile` made availabel in the repository. If you encountering problems with `act` or `docker`, please [get in touch with the developers via Zulip](https://scverse.zulipchat.com/#narrow/channel/443514-spatialdata-dev) and we will help troubleshoot the issue. See also additional details [here](https://github.com/scverse/spatialdata-plot/pull/397).
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- you should not use locally generated plots as ground truth images, but you should commit images that have been generated by a GitHub Action. The recommended workflow is to go to the ["actions" page for the repo](https://github.com/scverse/spatialdata-plot/actions/workflows/test.yaml), download the artifacts, and upload them as ground truth (after having reviewed them).
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- the ground truth images need to be updated when a new test is passing, or when a test starts producing a slightly different (but consistent) plot.
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- please never replace the ground truth images without having manually reviewed them.
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- if you run the tests locally in macOS or Windows they will likely fail because the ground truth images are generated using Ubuntu. To overcome this you can use `act`, which will generate a Docker reproducing the environment used in the GitHub Action. After the Docker container is generated you can use it within IDEs to run tests and debug code.
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- in the case of PyCharm, it is easier to create a container from a `Dockerfile` instead of using `act`. Please in such case use the `Dockerfile` made availabel in the repository. If you encountering problems with `act` or `docker`, please [get in touch with the developers via Zulip](https://scverse.zulipchat.com/#narrow/channel/443514-spatialdata-dev) and we will help troubleshoot the issue. See also additional details [here](https://github.com/scverse/spatialdata-plot/pull/397).
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## Publishing a release
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Please write documentation for new or changed features and use-cases. This project uses [sphinx][] with the following features:
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- the [myst][] extension allows to write documentation in markdown/Markedly Structured Text
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- [Numpy-style docstrings][numpydoc] (through the [napoloen][numpydoc-napoleon] extension).
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- Jupyter notebooks as tutorials through [myst-nb][] (See [Tutorials with myst-nb](#tutorials-with-myst-nb-and-jupyter-notebooks))
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- [Sphinx autodoc typehints][], to automatically reference annotated input and output types
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- Citations (like {cite:p}`Virshup_2023`) can be included with [sphinxcontrib-bibtex](https://sphinxcontrib-bibtex.readthedocs.io/)
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- the [myst][] extension allows to write documentation in markdown/Markedly Structured Text
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- [Numpy-style docstrings][numpydoc] (through the [napoloen][numpydoc-napoleon] extension).
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- Jupyter notebooks as tutorials through [myst-nb][] (See [Tutorials with myst-nb](#tutorials-with-myst-nb-and-jupyter-notebooks))
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- [Sphinx autodoc typehints][], to automatically reference annotated input and output types
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- Citations (like {cite:p}`Virshup_2023`) can be included with [sphinxcontrib-bibtex](https://sphinxcontrib-bibtex.readthedocs.io/)
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See the [scanpy developer docs](https://scanpy.readthedocs.io/en/latest/dev/documentation.html) for more information
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on how to write documentation.
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#### Hints
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- If you refer to objects from other packages, please add an entry to `intersphinx_mapping` in `docs/conf.py`. Only
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if you do so can sphinx automatically create a link to the external documentation.
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- If building the documentation fails because of a missing link that is outside your control, you can add an entry to
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the `nitpick_ignore` list in `docs/conf.py`
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- If you refer to objects from other packages, please add an entry to `intersphinx_mapping` in `docs/conf.py`. Only
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if you do so can sphinx automatically create a link to the external documentation.
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- If building the documentation fails because of a missing link that is outside your control, you can add an entry to
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the `nitpick_ignore` list in `docs/conf.py`
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#### Building the docs locally
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