v0.0.5

0.0.5

Added

• Public accessor layer for cached archetypal analysis artifacts (get_aa_result, get_aa_cell_weights, get_aa_metrics, get_aa_bootstrap, summarize_aa_metrics) with consistent filtering semantics.
• Comprehensive documentation on caching and retrieval flows, including the new docs/notebooks/data_access.ipynb tutorial and updates to other notebooks.
• New bootstrap and selection-metric plotting enhancements that rely on the unified accessors.

Changed

• Reworked AA caching to remove the eagerly stored adata.uns['AA_metrics_df'], generating summaries on demand instead using summarize_aa_metrics
• Refactored t-ratio significance testing and AA result handling to better reuse cached runs and ensure typing/mypy compliance.
• Updated plotting APIs (plot_var_explained, plot_IC, plot_bootstrap_*, plot_archetypes_*) to require precomputed caches and use the new result filters.
• Streamlined schema defaults and test fixtures after the accessor refactor.
• Multiple unit-test adjustments to align with the new caching workflow.