espm 1.0.0

Electron SPectro-Microscopy Python Library

espm: The Electron Spectro-Microscopy Python Library

.. image:: https://readthedocs.org/projects/espm/badge/?version=latest :target: https://espm.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status

The espm package is designed for the simulation and analysis of scanning transmission electron microscopy (STEM) hyperspectral data analysis. Currently it only supports energy dispersive X-ray spectroscopy (EDXS) data but we will try to extend it to electron energy loss spectroscopy (EELS) data in the future. The main components of the package are:

• The simulation of STEM-EDXS datasets using :mod:espm.datasets which combines :mod:espm.weights for the simulation of spatial distributions and :mod:èspm.models for the simulation of spectra.
• The hyperspectral unmixing of STEM-EDXS spectrum images using :mod:espm.estimators. This module contains algorithms to perform non-negative matrix factorization with diverse regularisation (e.g. Laplacian or L1) and contraints (e.g. simplex).
• The :mod:espm.models module can also be used to perform a physics-guided decomposition of STEM-EDXS datasets.

Installation

You can install this package from PyPi using::

$ pip install espm

If you want to develop, please use the option::

$ git clone https://github.com/adriente/espm.git
$ cd espm
$ pip install cython
$ pip install -e ".[dev]" 

Getting started

Try the api.ipynb notebook in the notebooks folder.

Documentation

The documentation is available at https://espm.readthedocs.io/en/latest/

You can get started with the following notebooks:

• https://espm.readthedocs.io/en/latest/introduction/notebooks/api.html
• https://espm.readthedocs.io/en/latest/introduction/notebooks/toy-problem.html

CITING

If you use this library, please cite the following paper::

@article{teurtrie2023espm,
title={espm: A Python library for the simulation of STEM-EDXS datasets},
author={Teurtrie, Adrien and Perraudin, Nathana{\"e}l and Holvoet, Thomas and Chen, Hui and Alexander, Duncan TL and Obozinski, Guillaume and H{\'e}bert, C{\'e}cile},
journal={Ultramicroscopy},
pages={113719},
year={2023},
publisher={Elsevier}
}