Metadata-Version: 2.4
Name: e-chem
Version: 1.0.5
Summary: echemkit is a lightweight Python library designed for seamless electrochemical data analysis.
Home-page: https://gitlab.tuwien.ac.at/iap/aip/anp/electrochemistry/basic-ec/e-chem
Author: Philipp Saboi, Nico Sonderhof, Lorenz Unterberger, Richard W. van Nieuwenhoven, Markus Valtiner
Author-email: nico.sonderhof@tuwien.ac.at
Project-URL: Homepage, https://researchdata.tuwien.ac.at/uploads/4exfe-yx784
Keywords: todo
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.1
Description-Content-Type: text/markdown
Requires-Dist: matplotlib>=3.5.1
Requires-Dist: numpy>=1.26
Requires-Dist: pandas>=2.2.3
Requires-Dist: scipy>=1.15.3
Requires-Dist: cvxopt
Requires-Dist: scikit-learn
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
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# EC-python Lib

echemkit is a lightweight Python library designed for seamless electrochemical data analysis directly within Jupyter notebooks. It provides intuitive tools for loading, processing, and visualising data from standard potentiostat systems such as BioLogic, PalmSens, and Squidstat. The package supports cyclic voltammetry (CV), chrono-potentiometry (CP), electrochemically active surface area (ECSA) analysis, and Tafel slope evaluation through a consistent, object-oriented API. Researchers can quickly import raw measurement files, extract key parameters, apply smoothing or compensation routines, and generate publication-ready plots—all in an interactive environment. With clear syntax and modular design, echemkit enables reproducible, open electrochemical analysis suitable for education, prototyping, and advanced research workflows.

[![PyPI](https://img.shields.io/pypi/v/e-chem.svg)](https://pypi.org/project/e-chem/)
[![Python](https://img.shields.io/pypi/pyversions/e-chem.svg)](https://pypi.org/project/e-chem/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](license.md)
[![DOI](https://img.shields.io/badge/DOI-10.48436%2F4exfe--yx784-blue.svg)](https://researchdata.tuwien.ac.at/uploads/4exfe-yx784)

## Features

- Load and analyse cyclic voltammetry, chrono-potentiometry, PEIS, ECSA, and Tafel data.
- Work directly with common potentiostat exports from BioLogic, PalmSens, and Squidstat.
- Process electrochemical data in Python and Jupyter notebooks with a consistent API.
- Generate publication-ready plots using NumPy, pandas, SciPy, and matplotlib.
- Run PEIS equivalent-circuit fitting and DRT workflows, including vendored headless pyDRTtools components.

## Quick Setup

Install the latest published package from PyPI:

```bash
pip install e-chem
```

For local development, clone the repository and install it in editable mode:

```bash
git clone https://gitlab.tuwien.ac.at/iap/aip/anp/electrochemistry/basic-ec/e-chem.git
cd e-chem
pip install -e .
```

Basic import pattern:

```python
from e_chem import cv, peis
```

## Project Links

- PyPI package: [e-chem](https://pypi.org/project/e-chem/)
- Project homepage / research data record: [10.48436/4exfe-yx784](https://researchdata.tuwien.ac.at/uploads/4exfe-yx784)
- Source repository: [TU Wien GitLab](https://gitlab.tuwien.ac.at/iap/aip/anp/electrochemistry/basic-ec/e-chem)

## Citation

If you use echemkit for scientific research or publication, please cite:

```text
DOI: 10.48436/4exfe-yx784
```

## License And Attribution

This project is distributed under the [MIT License](license.md).

Parts of the PEIS/DRT implementation include code acquired and adapted from [pyDRTtools](https://github.com/ciuccislab/pyDRTtools). Those components are vendored into this repository to support headless, notebook-friendly DRT analysis without requiring the original GUI stack.
