ArrayTrain (plan §12): simurg train — EGT cluster files from a cohort's GTCs

- simurg/train/clusters.py: vectorised per-locus θ mixture (AA/AB/BB + outlier component, θ-ordered bounds),
  cluster selection and merging, lone clusters homozygous, missing clusters imputed by cross-locus regression
  per assay type, cluster_sep and train (GenTrain-field) scores.
- formats/egt.py: write_egt (EGT v3, data block 9, round-trips through the reader).
- pipeline/train.py: normalised θ/R from GTC raw X/Y + transforms, sex-aware (X females, Y males, MT haploid),
  intensity-only loci as one R cluster.
- scripts/train/concordance_chr.py: array vs 1000G 30x on one chromosome.
Demo (36 GSA v4 PGx arrays, chr22 vs 1000G): trained 99.29 % / NRD 2.6 % vs vendor EGT 99.57 % / 1.55 %.

src/simurg/train/__init__.py

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+"""ArrayTrain: cluster-file training (plan §12)."""