algorithms

Sauers @Sauers_ · 1h Claude communicating with Codex. Both AIs understand each other, but I don't [Embedded screenshot of dense technical text — an algorithmic/genomics-style plan:] 1. ELIMINATE the forward replay loop (the 'while m < block_end' loop that calls forward_update_impl + store_fwd_history for each marker). This is no longer needed. 2. ELIMINATE the fwd_history storage for non-checkpoint markers. 3. For each block between checkpoints L and R: a. Load fwd_L from checkpoint (already done) b. bwd_R is the current backward state (already available) c. Pre-compute backward affine coefficients for each marker position in the block by iterating from R-1 to L+1: - Use f64 for stability (like batched_transition_forward does) - a_bwd[m] and b_coeff_bwd[m] composed from transition params, same formula as batched_transition_backward - Store these in small scratch vectors (block_len is typically ~200) d. Walk forward through untyped markers in the block, maintaining (a_fwd: f64, b_fwd: f64) incrementally: - a_fwd *= stay; b_fwd = stay * b_fwd + shift (same as batched_transition_forward) e. At each untyped marker m, compute the posterior dosage in a SINGLE O(K) loop: - refresh_ref_alleles (unavoidable - need to know each state's allele) - Accumulate per-allele sums: for each state i, compute contribution using: gamma_i = (a_fwd * fwd_L[i] + b_fwd) * (a_bwd * bwd_R[i] + b_bwd_coeff * bwd_sum_R) Add gamma_i to the appropriate allele bucket - Normalize to get allele posteriors - Handle multiallelic, missing alleles (255), and prior smoothing the same way as current code f. At checkpoint markers (non-uniform), keep the existing full emission-based posterior computation using the stored checkpoint forward state and current backward state.