Metadata-Version: 2.1
Name: eztao
Version: 0.1.0
Summary: A toolkit for Active Galactic Nuclei (AGN) time-series analysis.
Home-page: https://github.com/ywx649999311/EzTao
License: MIT
Author: Weixiang Yu
Author-email: wy73@drexel.edu
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: celerite (>=0.4.0,<0.5.0)
Requires-Dist: matplotlib (>=3.3.1,<4.0.0)
Requires-Dist: numba (>=0.51.2,<0.52.0)
Requires-Dist: numpy (>=1.19.1,<2.0.0)
Requires-Dist: scipy (>=1.5.2,<2.0.0)
Project-URL: Repository, https://github.com/ywx649999311/EzTao
Description-Content-Type: text/markdown

![tests](https://github.com/ywx649999311/EzTao/workflows/tests/badge.svg)
# EzTao (易道)
**EzTao** is a toolkit for conducting AGN time-series/variability analysis, mainly utilizing the continuous-time auto-regressive moving average model (CARMA)

## Installation
```
pip install eztao
```

#### Dependencies
>```
>python = "^3.7"
>numpy = "^1.19.1"
>celerite = "^0.4.0"
>matplotlib = "^3.3.1"
>scipy = "^1.5.2"
>numba = "^0.51.2"
>```

## Development
`poetry` is used to solve dependencies and to build/publish this package. Below shows how setup the environment for development (assuming you already have `poetry` installed on your machine). 

1. Clone this repository, and enter the repository folder.
2. Create a python virtual environment and activate it. 
    ```
    python -m venv env
    source env/bin/activate
    ```
3. Install dependencies and **EzTao** in editable mode.
   ```
   poetry install
   ```

Now you should be ready to start adding new features. Be sure to checkout the normal practice regarding how to use `poetry` on its website. When you are ready to push, also make sure the poetry.lock file is checked-in if any dependency has changed. 

