Examples

mirpy ships four runnable marimo notebooks under examples/. They are self-contained (they run on the bundled prototypes / test assets — no downloads) and double as living documentation for the three tiers. Install the extra and open one:

pip install "mirpy-lib[examples]"     # marimo, matplotlib, umap-learn
marimo edit examples/quickstart.py   # interactive; or `marimo run …` for read-only

Notebook	What it shows
examples/quickstart.py	Clonotype embedding end-to-end: TCREmp.embed a VDJdb-style set, PCA-denoise, cluster antigen-specific TCRs, and a UMAP coloured by epitope. The epitope colouring and the F1 table need a local VDJdb slim dump at tests/assets/vdjdb.slim.txt.gz (gitignored — see SOURCES.md); without it the notebook falls back to the bundled prototypes and colours by CDR3 length.
examples/density.py	Background subtraction (Theory T6): fit a density space, run balloon neighbor_enrichment against a P_gen / control background, and pull out the enriched convergent family.
examples/theory.py	Reproduces the supplementary results S1–S3 on bundled data — the distance laws (Gamma / extreme-value), the D↔d correlation, and prototype-source robustness.
examples/trajectory_and_twin.py	Exposure trajectory, generative loop, digital twin: fit a PhenoPath-style covariate- disentangled trajectory (mir.track) on a synthetic cohort with a known covariate and a planted severity axis, fit a generative density over RepertoireDescriptor vectors (mir.generate), perturb one donor (“what if hotter”) and draw new synthetic donor states via the digital-twin glue (mir.twin).

The full benchmark suite (VDJdb Table S1, density, repertoire / TCGA cohorts) and its result docs live in the companion 2026-mirpy-analysis repository; this repo keeps the library, its tests, and these bundled-data examples.