Add normalization and contrast tutorial#9
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Covers the norm= argument end-to-end on the blobs dataset: fixed contrast limits, clip under/over vs clamp, LogNorm/PowerNorm/SymLogNorm, percentile contrast via PercentileNormalize, per-channel norm lists for images, and norms on shapes/points/labels. Linked into tutorials/index.md. Note: PercentileNormalize ships in the next spatialdata-plot release; the execute CI will pass once that release is published.
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Summary
Adds a
tutorials/normalization_and_contrast.ipynbtutorial covering thenorm=argument end-to-end on theblobsdataset:normis and when limits autoscaleNormalize(vmin, vmax)LogNorm,PowerNorm,SymLogNormPercentileNormalize(broadcast + per-channel list)transfunc, true RGB imagesCommitted with outputs; linked into
tutorials/index.mdwith a thumbnail in_static/img/normalization_and_contrast.png.The notebook uses
PercentileNormalize(scverse/spatialdata-plot#725), which is onmainbut not yet in a published release. TheexecuteCI re-runs against the latestspatialdata-plotrelease, so it will fail until a release including #725 is published. Outputs in the committed notebook were generated against the dev build.Companion gallery PR in
scverse/spatialdata-plotlinks this tutorial with the same thumbnail.