Add rapid IVCSR filter/normalize loader - #3
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Reproduces parafac2.normalize.prepare_dataset (min-count cell/gene filtering, per-cell depth normalization, log10 transform) directly against the on-disk VCSR/IVCSR layout instead of through AnnData's generic read + fancy-indexing path. Cell filtering needs no decode: a VCSR row's total is derivable from major_ptr/values/value_ptr alone. Gene filtering and normalization require every nonzero to be visited, so indices are decoded once (via the existing parallel decoder) and the filter/compact/normalize tail runs as fused numba passes rather than scipy's per-step, single- threaded, temp-array-heavy pipeline. On a 1.94M x 27K-gene / 3.3B-nonzero dataset this completes in ~17s at ~53GB peak RSS. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01C8AcDah6zjdbJdGGYuMCQS
…romotion in load_and_normalize
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This PR introduces a rapid IVCSR filter and normalization loader (
load_filtered_normalized_ivcsr).Summary of Changes
main.