Crate salmon_model 

salmon-model: statistical models used during quantification.

Currently provides the fragment-length distribution (fld) and automatic library-type detection (libdetect). Bias models (sequence-specific, GC, positional) and the alignment error model are added in later phases.

Re-exports

pub use bias::build_expected_pos;

pub use bias::corrected_effective_length_full;

pub use bias::positional_factor;

pub use bias::BiasInputs;

pub use fld::ambig_frag_log_prob;

pub use fld::smoothed_effective_length;

pub use fld::DiscreteFld;

pub use fld::FragmentLengthDistribution;

pub use gcbias::build_expected_gc;

pub use gcbias::gc_corrected_effective_length;

pub use gcbias::gc_desc;

pub use gcbias::gc_prefix;

pub use gcbias::gc_ratio;

pub use gcbias::GcFragModel;

pub use gcbias::GcRank;

pub use gcbias::GcStore;

pub use gcbias::GcView;

pub use gcbias::GC_SAMP_STRIDE;

pub use libdetect::infer_format_from_counts;

pub use libdetect::LibraryTypeDetector;

pub use posbias::compute_length_quantiles;

pub use posbias::length_class_index;

pub use posbias::SimplePosBias;

pub use posbias::NUM_LENGTH_CLASSES;

pub use posbias::NUM_POS_BINS;

pub use seqbias::build_expected;

pub use seqbias::corrected_effective_length;

pub use seqbias::LogBiasTable;

pub use seqbias::SBModel;

Modules

bias

Unified bias-corrected effective length: composes sequence-specific, GC, and positional bias exactly as salmon’s updateEffectiveLengths does — a single conditional-FLD convolution whose per-fragment factor is the product of the enabled bias terms.

dumps

Aux-output dump helpers shared by reads-mode and alignment-mode quant.

fld

Fragment-length distribution.

gcbias

Fragment-GC bias model (GCFragModel).

libdetect

Automatic library-type detection.

posbias

Positional fragment bias (SimplePosBias) — a port of salmon’s src/model/SimplePosBias.cpp.

seqbias

Sequence-specific bias model (SBModel).

spline

Cubic spline interpolation — a faithful port of the vendored tk::spline (Tino Kluge) used by salmon’s SimplePosBias.

Constants

BIAS_WEIGHT_SCALE

Fixed-point scale for deterministic bias-model mass accumulation. Bias observed models sum per-fragment posterior masses (each in [0,1]) into bins; an f64 += is non-associative, so the accumulated model — and hence bias correction — varies with the worker-thread fragment partition (thread count). Accumulating round_down(mass * BIAS_WEIGHT_SCALE) as integers makes the sum associative (order/thread-count independent). 2^20 keeps the per-contribution resolution at ~1e-6 (ample for these coarse models) while a bin total (~num_fragments × 2^20) stays far below u64::MAX.

Functions

bias_mass_to_fp

Quantize a bias mass ([0,∞), typically a [0,1] posterior) to the fixed-point integer accumulator. Truncates (rounds toward zero) — cheaper than round() and the ≤1-ULP downward bias is negligible and cancels under the model’s normalization.