Pipeline for easy single particle detection, linking/tracking, and analysis
The structure for this repo was made using a cookiecutter from the Centre for Advanced Research Computing, University College London.
Michael Shannon (m.j.shannon@pm.me)
Michael Shannon (m.j.shannon@pm.me)
SPTnano requires Python 3.10–3.12.
We recommend installing in a project specific virtual environment created using
a environment management tool such as
Conda. To install the latest
development version of SPTnano using pip in the currently active
environment run
pip install git+https://github.com/Michael-shannon/SPTnano.gitAlternatively create a local clone of the repository with
git clone https://github.com/Michael-shannon/SPTnano.gitand then install in editable mode by running
pip install -e .How to run the application on your local system.
Tests can be run across all compatible Python versions in isolated environments
using tox by running
toxTo run tests manually in a Python environment with pytest installed run
pytest testsagain from the root of the repository.
The MkDocs HTML documentation can be built locally by running
tox -e docsfrom the root of the repository. The built documentation will be written to
site.
Alternatively to build and preview the documentation locally, in a Python
environment with the optional docs dependencies installed, run
mkdocs serve- Initial Research
- Minimum viable product <-- You are Here
- Alpha Release
- Feature-Complete Release
This work was funded by Cure Huntingtons Disease Initiative (CHDI) and The Rockefeller University.