Metadata-Version: 2.1
Name: pyexafs
Version: 1.0.0b5
Summary: A simple package for fast analysis of EXAFS data
Author-email: Sebastian Paripsa <paripsa@uni-wuppertal.de>
License: MIT License
        
        Copyright (c) [2022-2024] [FRANK FÖRSTE, SEBASTIAN PARIPSA]
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Project-URL: Homepage, https://github.com/San-WierPa/pyexafs
Keywords: research-and-development,exafs,data-science
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Development Status :: 4 - Beta
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: xraylarch==0.9.66
Requires-Dist: scipy
Provides-Extra: dev
Requires-Dist: black; extra == "dev"
Requires-Dist: isort; extra == "dev"

# PyEXAFS

[![Test Status](https://github.com/San-WierPa/pyexafs/workflows/Test/badge.svg?branch=main)](https://github.com/San-WierPa/pyexafs/actions?query=workflow%3ATest)
[![code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![imports: isort](https://img.shields.io/badge/imports-isort-ef8336.svg)](https://github.com/PyCQA/isort)

Developed by Frank Foerste and Sebastian Paripsa, **PyExafs** aims to streamline the workflow<br>
for XAS researchers, from data acquisition to final analysis.

## Introduction

**PyExafs** is designed to facilitate the automated quality assessment<br>
of X-ray Absorption Fine Structure (XAFS) measurements. Leveraging the robust capabilities of the Larch library,<br>
**PyExafs** enables researchers to efficiently process, analyse, and visualise XAFS data, ensuring adherence to stringent quality criteria.

With a single execution, **PyExafs** provides a fast analysis of a dataset, instantly delivering:

+ Absorbance
+ Normalized Absorbance
+ $\chi(k)$
+ $\chi(R)$

These results are presented according to well-defined quality standards, enabling users to quickly evaluate<br>
the integrity of their data.

Key features include:

+ Automated Quality Control: Implements rigorous routines to verify the quality of XAFS measurements.
+ Data Preprocessing: Efficiently handles data loading, preprocessing, and energy calibration.
+ Visualisation: Generates comprehensive plots for raw, normalized, k-space, and R-space data,<br>
supporting both detailed analysis and publication-quality figures.
+ Noise Estimation and Fitting: Provides tools for estimating noise and fitting the first shell,<br>
crucial for accurate data interpretation.

## Installation

Easy:

```sh
python -m pip install pyexafs
```

## Usage

To use the `pyexafs` package, run the following command and provide the path to your data file:

```sh
python -m pyexafs <path_to_data_file>
```

For example:

```sh
python -m pyexafs /path/to/your/datafile.txt
```
