SAMBA is a Python package providing sampling methods via matrix-based distance measures to mitigate autocorrelation.
The package can be installed via pip:
$ pip install samba_sampler
Detailed information on the usage of the package can be found in the documentation. For a quick start, the following example shows how to use the package:
import samba_sampler as samba
sampler = samba.LanguageSampler() # Default parameters
print(sampler.sample(5))
Version 0.3.2 (2023-07-18)
- Added taxa filtering, applying to the Glottolog data
Version 0.3.1 (2023-07-17)
- Added first version of the walking distance matrix derived from Guzman Naranjo & Jäger (2023).
Version 0.3 (2023-07-13)
- Initial release, following on the
arcaverborum
project.
While the author can be contacted directly for support, it is recommended that third parties use GitHub standard features, such as issues and pull requests, to contribute, report problems, or seek support.
Contributing guidelines, including a code of conduct, can be found in the CONTRIBUTING.md file.
The library is developed by Tiago Tresoldi (tiago@tresoldi.org).
The library is developed in the context of the Cultural Evolution of Texts project, with funding from the Riksbankens Jubileumsfond (grant agreement ID: MXM19-1087:1).
If you use samba_sampler
, please cite it as:
Tresoldi, Tiago (2023). SAMBA (Sampling Algorithms with Matrix-Based Weight Allocation): a Python package providing sampling methods via matrix-based distance measures to mitigate autocorrelation. Version 0.3. Uppsala: Uppsala University.
In BibTeX:
@misc{Tresoldi2023samba,
author = {Tresoldi, Tiago},
title = {SAMBA (Sampling Algorithms with Matrix-Based Weight Allocation): a Python package providing sampling methods via matrix-based distance measures to mitigate autocorrelation. Version 0.3.},
howpublished = {\url{https://github.com/tresoldi/samba_sampler}},
address = {Uppsala},
published = {Upssala University},
year = {2023}
}