stnmf


Namestnmf JSON
Version 1.1.0 PyPI version JSON
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home_pageNone
SummaryFast and versatile implementation of spike-triggered non-negative matrix factorization based on AF-HALS
upload_time2024-09-25 16:03:03
maintainerNone
docs_urlNone
authorSören J. Zapp, Tim Gollisch
requires_python>=3.10
licenseMIT
keywords retina subunits primate receptive field neuroscience stnmf nmf nnsvd-lrc hals
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            # 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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