Release v0.3.2 — VectorizedSCLayer + Perfection Sprint · anulum/scpn-control

What's New

VectorizedSCLayer + Rust backend path in SNN compiler (512x real-time when pip install "scpn-control[neuro]")
Two-tier import: v3.8.0+ preferred → legacy bit-ops → numpy float fallback
Detection test + forward-path benchmark

Docker: Multi-stage Dockerfile + .devcontainer/devcontainer.json
pre-commit: ruff, mypy, check-yaml, trailing-whitespace, cargo fmt/clippy (manual stage)
MkDocs: Theory page (SPN math, Kuramoto, UPDE, Lyapunov, H-inf), Architecture page (Mermaid diagrams, Rust/Python boundary), mkdocstrings autodoc for key classes, MathJax + Mermaid rendering
CI: 13 → 17 jobs (pre-commit, notebook-smoke, e2e-diiid, python-benchmark, rmse-gate)
GitHub: Issue templates (bug report, feature request), PR template
Zenodo: .zenodo.json metadata + tools/export_zenodo_dataset.py
README: Codecov + Zenodo badges, Limitations section, sc-neurocore engine callout
ROADMAP.md: v0.3.x → v0.4.0 → v0.5.0 → Future
CITATION.cff: Version + date updated
CONTRIBUTING.md: pre-commit setup, job count

Replaced sys.path.insert hacks with pythonpath = ["src", "tests", "."] in pytest config
Fixed requirements.txt for Streamlit Cloud (. instead of scpn-control>=0.2.0)
Created validation/__init__.py for proper package resolution

pip install scpn-control
scpn-control demo --steps 1000

With SNN acceleration:

pip install "scpn-control[neuro]"

Full stack:

pip install "scpn-control[dashboard,ws,neuro]"
scpn-control live --port 8765 --zeta 0.5