Metadata-Version: 2.1
Name: mlpf
Version: 0.0.2
Summary: Machine learning for power flow
Home-page: 
Author: Viktor Todosijevic
Author-email: todosijevicviktor998@gmail.com
License: MIT
Keywords: machine learning,power
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
License-File: LICENCE.txt
Requires-Dist: numpy
Requires-Dist: pandapower
Requires-Dist: PYPOWER
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: tqdm
Requires-Dist: torchmetrics

<p align="center">
<img src="images/logo.png" width="650">
</p>

__MLPF__ is a python library for (optimal) power flow calculations with machine learning.
It offers:

* efficient loss functions compatible with both _PyTorch_ and _scikit-learn_!
* utilities such as data structures and loading pipelines that make it easy to go from
  _pandapower_ nets or _PYPOWER_ case files to arrays and tensors in just one line of code!
* visualization and description tools to take a quick look at your data

## Usage

-[ ] One big TODO

### Data loading

### Loss

#### scikit-learn

#### torch

### Indepth examples

## Installation

### Pip

-[ ] TODO Publish package

### Development

```
git clone https://github.com/viktor-ktorvi/mlpf.git
cd mlpf

conda env create -f environment.yml
conda activate mlpfenv
```
