Visualization gallery notebook (not executed in CI) - #5
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…of CI examples/04_visualization.ipynb is the rendered reference for compileml.viz. Notebooks 01 and 03 show the plots in context using defaults; this one documents the options, which had no visual documentation anywhere: - waterfall arrow anatomy (adaptive heads, barbs) on a wide-spread decision - max_features truncation with the remainder bar closing the arithmetic exactly (printed alongside the figure: -207418 == -207418) - the depth>2 interaction residual drawn as its own bar — first artifact in the repo to exhibit it - waterfall_svg rendered inline, with byte-determinism shown - color_by outcome vs impact; value_color feature-value gradients with the values= construction; sort_metric mean/sum/max - band_conditioned facets and target_band focus; band_ladder on score-only payloads; restyling via colors=/labels=/ax= The notebook opts out of CI execution via metadata.compileml.ci_execute, read by run_notebooks.py — the declaration travels with the file, so it survives renames and is visible to anyone opening the notebook. Every API it demonstrates is already covered by tests/test_viz.py, so CI execution would re-prove covered code; what the notebook adds is rendered evidence, and the committed figures double as visual regression material in PR diffs.
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examples/04_visualization.ipynb— the rendered reference forcompileml.viz.Notebooks 01 and 03 show the plots in context using defaults. This one documents the options, which had no visual documentation anywhere:
max_featurestruncation with the remainder bar closing the arithmetic exactly — printed next to the figure:-207418 == -207418waterfall_svgrendered inline, byte-determinism showncolor_byoutcome vs impact;value_colorfeature-value gradients including the non-obviousvalues=construction;sort_metricmean/sum/maxtarget_bandfocus;band_ladderon cheap score-only payloads; restyling viacolors=/labels=/ax=CI: the notebook opts out of execution via
metadata.compileml.ci_execute = false, read byrun_notebooks.py. Declaring it in the notebook's own metadata means it survives renames and is visible to anyone opening the file. Rationale:tests/test_viz.pyalready covers every API shown, so CI execution would re-prove covered code — what the notebook adds is rendered evidence, and the committed figures double as visual-regression material in PR diffs.Measured, for the record: the drivers were not the cost. 150 explained rows at 8 features is 0.18 s; the notebooks job spends its 111 s in sklearn teacher training. Skipping 04 saves roughly 10 s — the better argument for skipping is coverage, not time. Flipping it back is a one-line metadata change if you'd rather CI ran it.
Local gate green: ruff/black, full suite,
mkdocs build --strict.