gpvolve-v2 1.0.1

Markov-chain evolutionary dynamics on genotype-phenotype maps. Rust-accelerated.

gpvolve-v2

Markov-chain evolutionary dynamics on genotype-phenotype maps. Rust-accelerated.

gpvolve-v2 lifts a gpgraph-v2 GenotypePhenotypeGraph into a Markov state model and analyzes evolutionary dynamics on top of it. Given a fitness function and a fixation model (SSWM, Moran, McCandlish, Bloom DMS, weak-mutation), it builds a row-stochastic transition matrix and computes stationary distributions, relaxation timescales, mean first passage times, transition path theory committors and reactive flux, dominant pathways, stochastic walker trajectories, PCCA+ metastable sets, and fitness peaks.

This is a clean-break rewrite of harmslab/gpvolve (dormant since 2020) with selective architectural inspiration from the harmsm/gpvolve fork (dormant since 2022). Hot paths (transition matrix assembly and stochastic walker sampling) live in Rust via PyO3 + rayon; spectral analysis stays in scipy.

Why v2

• Drops the dormant msmtools dependency. PCCA+ and TPT are reimplemented natively.
• Fast. Transition matrix assembly and walker sampling run in Rust with rayon parallelism.
• Sound convergence. Stochastic path sampling stops on a real criterion (effective sample size + Gelman-Rubin R-hat), not a Euclidean distance heuristic.
• Typed. Full type hints, mypy --strict in CI.
• Modern tooling. uv + maturin + pyproject.toml. Releases via python-semantic-release. OIDC-based PyPI publishing.
• Consumes the v2 family. Hard deps on gpmap-v2 and gpgraph-v2; speaks their locked SCHEMA.md contracts.

Install

pip install gpvolve-v2

Or with uv:

uv add gpvolve-v2

Plotting support is optional. For matplotlib:

pip install "gpvolve-v2[plot]"

Optional simulation backends (SLiM, tskit):

pip install "gpvolve-v2[sim]"

Python 3.11+. Prebuilt wheels ship for Linux (x86_64, aarch64), macOS (x86_64, aarch64), and Windows (x64).

Status

Pre-release. See CHANGELOG.md for progress and docs/migration/from-v1.md for the v1 to v2 API map.