# pymultipleis
[**Installation**](#installation)
| [**Examples**](https://github.com/richinex/pymultipleis/tree/main/docs/source/examples)
| [**Documentation**](https://pymultipleis.readthedocs.io/en/latest/index.html)
| [**Citing this work**](#citation)
A library for fitting a sequence of electrochemical impedance spectra.
- Implements algorithms for simultaneous and sequential fitting.
- Written in python and based on the [JAX library](https://github.com/google/jax).
- Leverages JAX's in-built automatic differentiation ([autodiff](https://jax.readthedocs.io/en/latest/notebooks/autodiff_cookbook.html)) of Python functions.
- Takes advantage of JAX's just-in-time compilation (JIT) of Python code to [XLA](https://www.tensorflow.org/xla) which runs on GPU or TPU hardware.
## Installation<a id="installation"></a>
pymultipleis requires the following:
- Python (>=3.9)
- [JAX](https://jax.readthedocs.io/en/latest/) (>=0.3.17)
Installing JAX on Linux is natively supported by the JAX team and instructions to do so can be found [here](https://github.com/google/jax#installation).
For Windows systems, the officially supported method is building directly from the source code (see [Building JAX from source](https://jax.readthedocs.io/en/latest/developer.html#building-from-source)).
However, it might be easier to use pre-built JAX wheels which can be found in this [Github repo](https://github.com/cloudhan/jax-windows-builder). Further details
on Windows installation is also provided in this [repo](https://github.com/Dipolar-Quantum-Gases/jaxfit/blob/main/README.md).
After installing JAX, you can now install pymultipleis via the following pip command
```bash
pip install pymultipleis
```
[Getting started with pymultipleis](https://pymultipleis.readthedocs.io/en/latest/quick-start-guide.html#) contains a quick start guide to
fitting your data with ``pymultipleis``.
## Examples
Jupyter notebooks which cover several aspects of ``pymultipleis`` can be found in [Examples](https://github.com/richinex/pymultipleis/tree/main/docs/source/examples).
## Documentation
Details about the ``pymultipleis`` API, can be found in the [reference documentation](https://pymultipleis.readthedocs.io/en/latest/index.html).
## Citing this work<a id="citation"></a>
If you use pymultipleis for academic research, you may cite the library as follows:
```
@misc{Chukwu2022,
author = {Chukwu, Richard},
title = {pymultipleis: a library for fitting a sequence of electrochemical impedance spectra},
publisher = {GitHub},
year = {2022},
url = {https://github.com/richinex/pymultipleis},
}
```
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