semvec/pypi-packages huggingface dataset:
miv 0.0.5
Python software for analysis and computing framework used in MiV project.
License: MIT
Requires Python: >=3.8,<3.11

<div align='center'>
<h1> MiV-OS: Spike Analysis and Computing Framework </h1>

[![License][badge-LICENSE]][link-LICENSE]
[![Release pypi][badge-pypi]][link-pypi]
[![Build Status][badge-CI]][link-CI]
[![Documentation Status][badge-docs-status]][link-docs-status]
[![Downloads][badge-pepy-download-count]][link-pepy-download-count]
[![codecov][badge-codecov]][link-codecov]

[//]: # (Remove this line for the first release)
_The package is under pre-alpha development. First Alpha release target mid-May 2022._

</div>

---

Python analysis and computing framework developed for Mind-in-Vitro(MiV) project.

## Installation
[![PyPI version][badge-pypi]][link-pypi]

MiV-OS is compatible with Python 3.8+. The easiest way to install is using python installation package (PIP)

~~~bash
$ pip install MiV-OS
~~~

## Documentation
[![Documentation Status][badge-docs-status]][link-docs-status]

Documentation of the package is available [here][link-docs-status]

## Contribution

If you would like to participate, please read our [contribution guideline](CONTRIBUTING.md)

The development of MiV-OS is lead by the [Gazzola Lab][link-lab-website] at the University of Illinois at Urbana-Champaign.

## List of publications and submissions

## Citation

```
@misc{MiV-OS,
  author = {Gazzola Lab},
  title = {MiV-OS: Analysis and Computation Framework on MiV System and Simulator},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/GazzolaLab/MiV-OS}},
}
```

We ask that any publications which use MiV-OS package to cite the following papers:

```
```

## Developers ✨
_Names arranged alphabetically_
- Arman Tekinalp
- Andrew Dou
- Austin Ellis-Mohr
- Gaurav Upadhyay
- [Seung Hyun Kim](https://github.com/skim0119)

[//]: # (Collection of URLs.)

[link-lab-website]: http://mattia-lab.com/
[link-docs-status]: https://miv-os.readthedocs.io/en/latest/?badge=latest
[link-CI]: https://github.com/GazzolaLab/MiV-OS/actions
[link-LICENSE]: https://github.com/GazzolaLab/MiV-OS/blob/main/LICENSE
[link-pypi]: https://badge.fury.io/py/MiV-OS
[link-pepy-download-count]: https://pepy.tech/project/MiV-OS
[link-codecov]: https://codecov.io/gh/GazzolaLab/MiV-OS

[//]: # (Collection of Badges)

[badge-docs-status]: https://readthedocs.org/projects/miv-os/badge/?version=latest
[badge-CI]: https://github.com/GazzolaLab/MiV-OS/workflows/CI/badge.svg
[badge-LICENSE]: https://img.shields.io/apm/l/atomic-design-ui.svg?style=flat
[badge-pypi]: https://badge.fury.io/py/MiV-OS.svg
[badge-pepy-download-count]: https://pepy.tech/badge/MiV-OS
[badge-codecov]: https://codecov.io/gh/GazzolaLab/MiV-OS/branch/main/graph/badge.svg?token=OM5LYWF5KP
MaxFlowAeiu 0.1.4
Execution of the Fork Fulkerson method to find the maximum flow of a network
License: MIT
Requires Python: >=3.8
Keywords: max flow

# MaxFlowAeiu

**This package executes the Ford-Fulkerson method to find the maximum flow of a network.**

What is proposed with the Ford-Fulkerson algorithm is to search for paths in which the flow can be increased, until the maximum flow or the path with the maximum capacity of the arches is reached. The creators of this algorithm are: L. R. Ford, Jr. and D. R. Fulkerson. The idea is to find a penetration path with a net positive flux linking the source and destination nodes.