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Merge pull request #22 from HSE-LAMBDA/pypi
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hombit authored Jun 29, 2022
2 parents c4ce0d2 + f4c5592 commit 28b7e6d
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12 changes: 10 additions & 2 deletions README.md
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# Welcome to Fulu

[![PyPI version](https://badge.fury.io/py/fulu.svg)](https://badge.fury.io/py/fulu)
[![Downloads](https://pepy.tech/badge/fulu)](https://pepy.tech/project/fulu)
[![Tests](https://github.com/HSE-LAMBDA/fulu/actions/workflows/tests.yml/badge.svg)](https://github.com/HSE-LAMBDA/fulu/actions/workflows/tests.yml)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

`Fulu` is a python library of methods for astronomical light curves approximation based on machine learning. It was named after the variable star Zeta Cassiopeiae 590 light-years from the Sun and officially named [Fulu](https://simbad.cds.unistra.fr/simbad/sim-id?Ident=HR153).


![](images/cas.png)
![](https://raw.githubusercontent.com/HSE-LAMBDA/fulu/master/images/cas.png)
_Cassiopeia constellation [[source]](https://en.wikipedia.org/wiki/File:Cassiopeia_constellation_map.svg)_

The library contains our implementation of light curve approximation method based on Gaussian Processes described in [1], and several other methods based on Normalizing Flows, Shallow and Bayesian Neural Networks considered in [2].
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## Install

```sh
pip install fulu
```
or

```sh
python3 -m pip install git+https://github.com/HSE-LAMBDA/fulu
```
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t_approx=t_aug, flux_approx=flux_aug,
flux_err_approx=flux_err_aug, passband_approx=passband_aug)
```
![](images/ex.png)
![](https://raw.githubusercontent.com/HSE-LAMBDA/fulu/master/images/ex.png)

Please find a plotting example in [`notebooks_examples/plotting.ipynb`](notebooks_examples/plotting.ipynb)
4 changes: 2 additions & 2 deletions setup.cfg
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[metadata]
name = fulu
version = 0.1.1
author = Mikhail Hushchyn
author_email = mhushchyn@hse.ru
author = Mikhail Hushchyn, Konstantin Malanchev
author_email = mhushchyn@hse.ru, malanchev@physics.msu.ru
description = Light curve approximation and augmentation
long_description = file: README.md
long_description_content_type = text/markdown
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