pyS3M

pyS3M (written in support of https://www.biorxiv.org/content/10.64898/2026.04.08.715690v1) is a Python package of classes for analysing spatial-spectral single-molecule localisation microscopy data — fitting, quality filtering, clustering, drift correction, FRC, and simulation — usable from scripts, notebooks, or its desktop GUI. Example notebooks are provided under notebooks/analyses/ (fitting through resolution estimation) and notebooks/simulations/ (generating your own synthetic acquisitions), each running end-to-end against data already bundled with the repo.

Documentation: https://pys3m.readthedocs.io/en/latest/index.html

Installation

Requires Python >=3.11, <3.13 (tested on 3.12.3).

Install into a virtual environment, not your system Python — pyS3M pulls in a large, version-pinned dependency tree (numpy, numba, scikit-learn, PyQt6, ...) that can otherwise clash with other projects. See the venv docs if you're not already using one:

python -m venv .venv
source .venv/bin/activate   # .venv\Scripts\activate on Windows

Clone the repository, then from its root:

pip install .

This installs pyS3M as a real package (import pyS3M.SR_Functions, etc. works from anywhere — no sys.path hacks needed) along with its core analysis dependencies. Optional extras layer on top as needed:

pip install .[notebooks]  # jupyterlab, seaborn, xarray, plotly, ...
pip install .[docs]       # Sphinx + the Read the Docs theme, for building docs locally
pip install .[dev]        # pytest, coverage, black, build

Extras can be combined, e.g. pip install .[notebooks,dev]. For an editable install while developing pyS3M itself, add -e: pip install -e .[dev].

Running the GUI

pys3m-gui

(installed as a console script by pip install .), or equivalently python run_gui.py from the repository root without installing.

Quickstart

See the Getting Started guide for a minimal worked example and installation/GUI details: https://pys3m.readthedocs.io/en/latest/getting-started.html

See notebooks/analyses/ for fuller worked examples (single- and multi-FOV fitting, drift correction, clustering, channel unmixing, Nile Red, FRC) and notebooks/simulations/ for how to generate your own synthetic acquisitions.

License

Copyright © 2026, Cambridge Enterprise Limited, all rights reserved. This software is provided for academic use only — see LICENSE for the full text. For commercial use, contact ls.ipportfolio@enterprise.cam.ac.uk quoting LEE-11475-25.

Contributing

Patches and contributions are very welcome! Please see CONTRIBUTING.md and CODE_OF_CONDUCT.md for more details.