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[pre-commit.ci] pre-commit autoupdate (#417)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Tim Treis <[email protected]>
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.github/workflows/test.yaml

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pytest -v --cov --color=yes --cov-report=xml
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- name: Archive figures generated during testing
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if: always()
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uses: actions/upload-artifact@v3
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uses: actions/upload-artifact@v4
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with:
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name: visual_test_results_${{ matrix.os }}-python${{ matrix.python }}
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path: /home/runner/work/spatialdata-plot/spatialdata-plot/tests/figures/*

.pre-commit-config.yaml

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skip: []
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repos:
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- repo: https://github.com/psf/black
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rev: 24.10.0
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rev: 25.1.0
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hooks:
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- id: black
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- repo: https://github.com/pre-commit/mirrors-prettier
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hooks:
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- id: blacken-docs
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- repo: https://github.com/pre-commit/mirrors-mypy
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rev: v1.14.1
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rev: v1.15.0
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hooks:
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- id: mypy
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additional_dependencies: [numpy, types-requests]
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exclude: tests/|docs/
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.9.3
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rev: v0.9.9
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hooks:
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- id: ruff
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args: [--fix, --exit-non-zero-on-fix]

README.md

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[link-api]: https://spatialdata.scverse.org/projects/plot/en/latest/api.html
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[link-design-doc]: https://spatialdata.scverse.org/en/latest/design_doc.html
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[link-notebooks]: https://spatialdata.scverse.org/en/latest/tutorials/notebooks/notebooks.html
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[//]: # (numfocus-fiscal-sponsor-attribution)
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[//]: # "numfocus-fiscal-sponsor-attribution"
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spatialdata-plot is part of the scverse® project ([website](https://scverse.org), [governance](https://scverse.org/about/roles)) and is fiscally sponsored by [NumFOCUS](https://numfocus.org/).
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If you like scverse® and want to support our mission, please consider making a tax-deductible [donation](https://numfocus.org/donate-to-scverse) to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.

src/spatialdata_plot/pl/utils.py

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def _datshader_get_how_kw_for_spread(
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reduction: Literal["sum", "mean", "any", "count", "std", "var", "max", "min"] | None
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reduction: Literal["sum", "mean", "any", "count", "std", "var", "max", "min"] | None,
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) -> str:
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# Get the best input for the how argument of ds.tf.spread(), needed for numerical values
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reduction = reduction or "sum"

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