# STNMF with AF-HALS
[![Build status](https://github.com/gollischlab/STNMF_with_AFHALS/actions/workflows/pypi.yml/badge.svg)](https://github.com/gollischlab/STNMF_with_AFHALS/deployments/PyPI)
[![Documentation status](https://readthedocs.org/projects/stnmf/badge/?version=latest)](https://stnmf.readthedocs.io/en/latest/?badge=latest)
[![PyPI version](https://img.shields.io/pypi/v/stnmf.svg)](https://pypi.python.org/pypi/stnmf)
[![DOI](https://img.shields.io/badge/DOI-10.1101%2F2024.04.22.590506-007ec6)](https://doi.org/10.1101/2024.04.22.590506)
A fast and versatile implementation of spike-triggered non-negative matrix factorization (STNMF) based on accelerated fast hierarchical alternating least squares (AF-HALS) algorithms.
This Python package allows fast inference of receptive-field subunits from the spiking responses of retinal ganglion cells including methods of hyperparameter tuning.
Described in the paper:
> **Zapp SJ, Khani MH, Schreyer HM, Sridhar S, Ramakrishna V, Krüppel S, Protti DA, Mietsch M, Karamanlis D, Gollisch T (2024). Accelerated spike-triggered non-negative matrix factorization reveals coordinated ganglion cell subunit mosaics in the primate retina. *bioRxiv*, 590506.** https://doi.org/10.1101/2024.04.22.590506
## Documentation
The documentation is available at [https://stnmf.readthedocs.io](https://stnmf.readthedocs.io).
## Installation
Install using `pip` from command-line:
```bash
pip install stnmf
```
## Contact
For feedback and bug reports, please use the [Github issue tracker](https://github.com/gollischlab/STNMF_with_AFHALS/issues).
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"description": "# STNMF with AF-HALS\n\n[![Build status](https://github.com/gollischlab/STNMF_with_AFHALS/actions/workflows/pypi.yml/badge.svg)](https://github.com/gollischlab/STNMF_with_AFHALS/deployments/PyPI)\n[![Documentation status](https://readthedocs.org/projects/stnmf/badge/?version=latest)](https://stnmf.readthedocs.io/en/latest/?badge=latest)\n[![PyPI version](https://img.shields.io/pypi/v/stnmf.svg)](https://pypi.python.org/pypi/stnmf)\n[![DOI](https://img.shields.io/badge/DOI-10.1101%2F2024.04.22.590506-007ec6)](https://doi.org/10.1101/2024.04.22.590506)\n\nA fast and versatile implementation of spike-triggered non-negative matrix factorization (STNMF) based on accelerated fast hierarchical alternating least squares (AF-HALS) algorithms.\n\nThis Python package allows fast inference of receptive-field subunits from the spiking responses of retinal ganglion cells including methods of hyperparameter tuning.\n\nDescribed in the paper:\n\n> **Zapp SJ, Khani MH, Schreyer HM, Sridhar S, Ramakrishna V, Kr\u00fcppel S, Protti DA, Mietsch M, Karamanlis D, Gollisch T (2024). Accelerated spike-triggered non-negative matrix factorization reveals coordinated ganglion cell subunit mosaics in the primate retina. *bioRxiv*, 590506.** https://doi.org/10.1101/2024.04.22.590506\n\n## Documentation\nThe documentation is available at [https://stnmf.readthedocs.io](https://stnmf.readthedocs.io).\n\n## Installation\nInstall using `pip` from command-line:\n\n```bash\npip install stnmf\n```\n\n## Contact\nFor feedback and bug reports, please use the [Github issue tracker](https://github.com/gollischlab/STNMF_with_AFHALS/issues).\n",
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