Bayesian Single-Cutoff Residence Time Analysis (basicrta)
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A package to extract binding kinetics from molecular dynamics simulations based on Sexton (2025) 1.
basicrta is bound by a Code of Conduct.
Installation
To build basicrta from source,
we highly recommend using virtual environments.
If possible, we strongly recommend that you use
Anaconda as your package manager.
Below we provide instructions both for conda and
for pip.
With conda
Ensure that you have conda installed.
Create a virtual environment and activate it:
conda create --name basicrta
conda activate basicrta
Install the development and documentation dependencies:
conda env update --name basicrta --file devtools/conda-envs/test_env.yaml
conda env update --name basicrta --file docs/requirements.yaml
Build this package from source:
pip install -e .
If you want to update your dependencies (which can be risky!), run:
conda update --all
And when you are finished, you can exit the virtual environment with:
conda deactivate
With pip
To build the package from source, run:
pip install .
If you want to create a development environment, install the dependencies required for tests and docs with:
pip install ".[test,doc]"
Copyright
The basicrta source code is hosted at https://github.com/becksteinlab/basicrta and is available under the GNU General Public License, version 3 (see the file LICENSE).
Copyright (c) 2024, Ricky Sexton
Acknowledgements
Project based on the MDAnalysis Cookiecutter version 0.1. Please cite MDAnalysis when using basicrta in published work.
-
Sexton, R.; Fazel, M.; Schweiger, M.; Pressé, S.; Beckstein, O. Bayesian Nonparametric Analysis of Residence Times for Protein-Lipid Interactions in Molecular Dynamics Simulations. Journal of Chemical Theory and Computation 2025 21 (8), 4203-4220 DOI:
10.1021/acs.jctc.4c01522 <http://doi.org/10.1021/acs.jctc.4c01522>_ ↩
Metadata
Release files for basicrta 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| basicrta-1.2.0.tar.gz | 790.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| basicrta-1.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.6 MB
Release files / basicrta-1.2.0.tar.gz
| Download URL | basicrta-1.2.0.tar.gz |
|---|---|
| Size | 790.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
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twine/6.1.0 CPython/3.12.8
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Provenance
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Signed by GitHub Actions, verified by PyPI on Nov 29, 2025.
Transparency logRelease files / basicrta-1.2.0-py3-none-any.whl
| Download URL | basicrta-1.2.0-py3-none-any.whl |
|---|---|
| Size | 805.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
488631dc8372478df90d1e1a9c3dfa66706da57a254e859092d2e63593be6395
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.12.8
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Nov 29, 2025.
Transparency log