A Python package for working with battery discharge data
Project description
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Ampere - Advanced Model Package for ElectRochemical Experiments
------------
`Ampere` is a Python module for working with battery models.
Using a [scikit-learn-like API](https://arxiv.org/abs/1309.0238), we hope to make visualizing, fitting, and analyzing impedance spectra more intuitive and reproducible.
<i>Ampere is currently in the alpha phase and new features are rapidly being added.</i>
If you have a feature request or find a bug, please feel free to [file an issue](https://github.com/nealde/Ampere/issues) or, better yet, make the code improvements and [submit a pull request](https://help.github.com/articles/creating-a-pull-request-from-a-fork/)! The goal is to build an open-source tool that the entire electrochemical community can improve and use!
impedance.py currently provides:
- a simple API for fitting, predicting, and plotting impedance
- equivalent circuit fitting with customizable models
- convenient Nyquist plots including confidence interval estimation for fit circuits
several features are currently being improved upon:
- implementation of measurement models as a data validation method
- interactive plotting with altair
- adding more impedance elements
- physics-based impedance models for lithium-ion batteries
### Installation
#### Dependencies
battery.py requires:
- Python (>=3.5)
- SciPy (>=1.0)
- NumPy (>=1.14)
- Matplotlib (>=2.0)
- Cython
Several example notebooks are provided in the examples/ directory. Opening these will require Jupyter notebook or Jupyter lab.
#### User Installation
The easiest way to install Ampere is using pip:
`pip install ampere`
#### Examples and Documentation
Several examples can be found in the `examples/` directory (the [fitting_tutorial.ipynb](https://github.com/ECSHackWeek/impedance.py/blob/master/examples/fitting_tutorial.ipynb) is a great place to start) and the documentation can be found at [impedancepy.readthedocs.io](https://impedancepy.readthedocs.io/en/latest/).
[![Build Status](https://travis-ci.org/ECSHackWeek/impedance.py.svg?branch=master)](https://travis-ci.org/ECSHackWeek/impedance.py)
[![Coverage Status](https://coveralls.io/repos/github/ECSHackWeek/impedance.py/badge.svg?branch=master)](https://coveralls.io/github/ECSHackWeek/impedance.py?branch=master)
[![Documentation Status](https://readthedocs.org/projects/impedancepy/badge/?version=latest)](https://impedancepy.readthedocs.io/en/latest/?badge=latest)
-->
Ampere - Advanced Model Package for ElectRochemical Experiments
------------
`Ampere` is a Python module for working with battery models.
Using a [scikit-learn-like API](https://arxiv.org/abs/1309.0238), we hope to make visualizing, fitting, and analyzing impedance spectra more intuitive and reproducible.
<i>Ampere is currently in the alpha phase and new features are rapidly being added.</i>
If you have a feature request or find a bug, please feel free to [file an issue](https://github.com/nealde/Ampere/issues) or, better yet, make the code improvements and [submit a pull request](https://help.github.com/articles/creating-a-pull-request-from-a-fork/)! The goal is to build an open-source tool that the entire electrochemical community can improve and use!
impedance.py currently provides:
- a simple API for fitting, predicting, and plotting impedance
- equivalent circuit fitting with customizable models
- convenient Nyquist plots including confidence interval estimation for fit circuits
several features are currently being improved upon:
- implementation of measurement models as a data validation method
- interactive plotting with altair
- adding more impedance elements
- physics-based impedance models for lithium-ion batteries
### Installation
#### Dependencies
battery.py requires:
- Python (>=3.5)
- SciPy (>=1.0)
- NumPy (>=1.14)
- Matplotlib (>=2.0)
- Cython
Several example notebooks are provided in the examples/ directory. Opening these will require Jupyter notebook or Jupyter lab.
#### User Installation
The easiest way to install Ampere is using pip:
`pip install ampere`
#### Examples and Documentation
Several examples can be found in the `examples/` directory (the [fitting_tutorial.ipynb](https://github.com/ECSHackWeek/impedance.py/blob/master/examples/fitting_tutorial.ipynb) is a great place to start) and the documentation can be found at [impedancepy.readthedocs.io](https://impedancepy.readthedocs.io/en/latest/).
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