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  • 6 commits
  • 4 files changed
  • 2 contributors

Commits on Aug 14, 2026

  1. feat: add as_points tutorial 

    Show the how and why of `as_points` on both render_shapes and
render_labels, using a real Xenium breast-cancer section (~168k cells).
Covers what it draws (one centroid dot per element), what it ignores
(outline_*, shape, contour_px), the matplotlib->datashader backend
switch at ~50k centroids, and the measured speed trade-off: a large
win for shapes (up to ~16x), roughly neutral for labels (a mask
already renders as a fast raster).

Segmentation masks are derived from the real cell_boundaries via
rasterize(return_regions_as_labels=True), since Xenium rep1 ships
outlines as shapes with no native labels element.

The 3.4 GB download makes the notebook too heavy for CI, so it is
excluded from execute.yaml and its committed outputs are trusted.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
    @timtreis @claude
    timtreis and claude committed Aug 14, 2026
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  2. feat: add as_points tutorial 

    Show as_points on render_shapes and render_labels using a real Xenium
breast-cancer section (167780 cells). Covers what it draws (one centroid
dot per element), the appearance controls that still apply (color, size,
cmap, palette), what it ignores (outline_*, shape, contour_px), the
matplotlib and datashader backends with the 50000-centroid switch, and
the measured speed trade-off: a large win for shapes (up to 16x), about
neutral for labels (a mask already renders as a fast raster).

Segmentation masks are derived from the real cell_boundaries via
rasterize(return_regions_as_labels=True), since Xenium rep1 ships
outlines as shapes with no native labels element.

The 3.4 GB download makes the notebook too heavy for CI, so it is
excluded from execute.yaml and its committed outputs are trusted.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
    @timtreis @claude
    timtreis and claude committed Aug 14, 2026
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  3. docs: show the full section both ways in as_points 

    Open the speed section with the entire 167780-cell section rendered as
full geometry and as as_points, coloured by EPCAM. Previously the full
dataset only appeared as as_points in the backend section; the
full-geometry vs as_points comparison was limited to the crop.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
    @timtreis @claude
    timtreis and claude committed Aug 14, 2026
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  4. docs: dedupe full-section render and fix overlapping colorbars 

    The default backend already draws the 167780-cell as_points panel with
datashader, so the backend section's datashader render repeated the
full-section image. Drop that render and explain the backend in prose,
referencing the panel above.

In the shared-scale two-panel crops, draw the colourbar only on the
right panel so it no longer overlaps the neighbouring axes.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
    @timtreis @claude
    timtreis and claude committed Aug 14, 2026
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  5. docs: give the full-section as_points panel full colour coverage 

    At the default marker size the datashader spread left white gaps, so the
whole-section panel looked grainy. Draw it with datashader and size=12 so
each cell spreads into continuous coverage, matching the overview look,
and note in the prose that size controls the spread on that backend.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
    @timtreis @claude
    timtreis and claude committed Aug 14, 2026
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  6. docs: drop the full-section comparison, keep the colourbar fix 

    Revert the whole-slide full-geometry vs as_points panel and its
follow-on tweaks; the notebook reads better without it. This restores
the matplotlib vs datashader backend comparison that had been removed.
The only change kept from that stretch is drawing a single colourbar
per shared-scale panel pair, so they no longer overlap.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
    @timtreis @claude
    timtreis and claude committed Aug 14, 2026
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