v3.0.1

Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog,
and this project adheres to Semantic Versioning.

[3.0.1]

Fixed

• get_mapping_scores no longer raises IndexError when the connectivity
  matrix contains explicit stored zeros — _compute_csim now calls
  eliminate_zeros() before nonzero(). (#172)
• _calculate_blast_graph is now compatible with pandas ≥3.0, which returns
  StringArray (no .flatten() method) from .values on string columns.
  Replaced .values.flatten() with np.asarray(...). (#173)
• GenePairFinder.find_genes now honours the w1t/w2t SAM-weight threshold
  parameters instead of using a hardcoded 0.2. (#166)
• prepare_SAMap_loadings now falls back to adata.uns["sam"]["run_args"]
  when run_args is not at the top level, supporting AnnData produced by
  scanpy.external.tl.sam. (#156)
• sankey_plot now renders all adjacent species pairs instead of being
  hardcoded for exactly 3 species. (#130)
• _find_link_genes_avg coerces sparse matrix indices to int64 before
  fancy-indexing, avoiding scipy's int32 overflow (ValueError: negative dimensions are not allowed) on very large datasets. (#118)

Changed

• README updated for v3.0.0: Python ≥3.11 requirement, simplified conda/pip
  install instructions, fixed "Anacodna" typo, updated import paths.
  (#171, #137, #136, #132)

[3.0.0] - UNRELEASED

Breaking

• sc-sam removed as a dependency. The SAM algorithm is now vendored
  under samap.sam. All internal imports route through samap.sam — no
  external SAM package is installed or required. If you were importing
  samalg directly, switch to samap.sam.
• _smart_expand default switched from matrix-power to BFS. Produces
  slightly different marginal neighbours (~1% edge difference on the
  golden-suite data) — the matpow path wasted one budget slot per cell on
  a self-loop artefact. Pass legacy=True for bit-exact 2.x reproduction.

Added

• GPU backend via SAMAP(backend="auto"|"cpu"|"cuda"). Dispatches
  numpy/scipy ↔ cupy/cupyx, hnswlib ↔ FAISS for kNN, and scanpy ↔
  rapids-singlecell for Leiden/UMAP. Install with pip install sc-samap[gpu]
  (see docs/performance.md for conda details). "auto" picks CUDA if
  available, else CPU.
• N² → N-linear memory rewrites (see docs/performance.md for the full
  model):
  • Precomposed feature translation — projection precomposes
    G · diag(W/σ) · PCs so the cells × genes Xtr intermediate is never
    materialised. Iteration-invariant state (XᵀX, means, own-species
    projection) is computed once. ~2× wall and ~2× memory on the benchmark
    suite; gains grow with N.
  • Streaming mutual-NN — coarsening streams per-species-pair blocks
    directly into a CSR builder instead of materialising dense N × N products.
  • Batched correlation refinement — streams gene-pair batches
    (default batch_size=512); computes only the columns of the smoothed
    expression matrix referenced per batch. Peak memory drops from
    O(N × G_active) to O(N × 1024). ~4× less memory; ~3-5× slower on small
    data where the full matrix fits — pass batch_size=None to opt out.
  • BFS neighbourhood expansion — numba BFS kernel replaces matrix-power
    _smart_expand. ~5× faster at 3k cells, memory-bounded.
• Randomized SVD with implicit centering for sparse PCA — available
  via svd_solver="randomized" on samap.sam.pca._pca_with_sparse. Faster
  on GPU and at high PC counts; slightly different numerics. Default remains
  ARPACK.
• Phase-level benchmark suite — benchmarks/bench_samap.py compares
  legacy vs optimized paths for each rewritten phase.
• docs/performance.md — memory model, backend selection, tuning, scaling
  estimates.

Fixed

• Dead random-walk computation in _mapper (result written then immediately
  discarded; preserved only the binarization side effect).
• thr → align_thr kwarg misroute in analysis.enrichment (was falling
  through to an unrelated p-value threshold).
• Deprecated .A matrix attribute → np.asarray() in several hot paths.
• Stale root setup.py removed (pyproject.toml is authoritative).
• Broken SAMGUI import and dead gui() method removed.
• Duplicated _q helper consolidated into samap.utils.q.
• Dead mdata['xsim'] store removed.
• __version__ is now dynamic via importlib.metadata.

Changed

• src/samap/core/mapping.py split into focused modules: homology.py,
  correlation.py, projection.py, coarsening.py, expand.py. The
  SAMAP class remains in mapping.py; all existing imports work unchanged.
• _refine_corr / _refine_corr_parallel default batch_size changed
  from None (materialized) to 512 (streaming).
• _smart_expand default legacy changed from True (matpow) to
  False (BFS).
• Golden regression fixture regenerated to reflect the BFS and streaming
  defaults.

v3.0.0

Major modernization release.

• N² → N-linear memory optimizations
• GPU backend support
• Vendored SAM (no more sam-algorithm dependency)
• Modernized codebase (PR #170, #174)
• Requires Python ≥3.11
• PyPI package renamed: pip install sc-samap

See CHANGELOG.md for details.