Skip to main content

A tool for electromagnetic modelling of the head and sensitivity analysis.

Project description

shamo

version python documentation tutorials codestyle docstyle license
doi

Introduction

Constructing accurate subject specific head model is of main interest in the fields of source imaging (EEG/MEG) and brain stimulation (tDCS/tMS). shamo is an open source python package to calculate EEG leadfields, current flows, and electric potential distribution in the head. From a labelled 3D image of the head, the whole process is fully automatized, relying only on a few parameter files, e.g. conductivities (including white matter anisotropy) plus source and electrode locations. Since there is no non-invasive method to measure the electromagnetic (EM) properties of the head tissues, shamo can also be used to assess the sensitivity of the EM head model to these parameters.

Philosophy

The idea leading the development of shamo is to provide a versatile, intuitive and extendable toolbox for electromagnetic modelling of the head. Every object is though to be savable/loadable as a dictionary and stored as a JSON file on disk. shamo is built around three main concepts:

  1. Problem: The definition of a task to perform. Computing the EEG leadfield or simulating tDCS for examples.
  2. Solution: The object resulting from the resolution of a problem.
  3. Surrogate: If the problem-solution pair is parametric, e.g. some parameters are random variables, surrogate can be used to produce parametric models.

One of the leading rules while working on shamo was to use already existing quality tools to perform key steps. Thus, the finite element generation is achieved by interfacing with CGAL and Gmsh, the physical problem resolution is done with GetDP, the Gaussian processes are generated with scikit-learn and the sensitivity analysis uses SALib.

Documentation

The documentation of shamo is available here and tutorials are available in the form of jupyter notebooks in this repository.

FAQ

Where can you get help about shamo?

If you need help with your project involving shamo, head over to this page and pick up the help template. Make sure your question does not already exist fy searching the issues.

We'll be happy to give you some help!

Where does the name "shamo" come from?

The name "shamo", pronounced [ʃɑ:mɔ:], stands for "Stochastic HeAd MOdelling".

In french, it sounds like the word "chameau" which is the translation for "camel". This is a reference to the bematists, those ancient greek and egyptians who were able to measure distances with a high accuracy by counting the steps of a camel. They were involved in the accurate calculation of the circumference of the Earth by limiting distance measurement errors.

As did the old bematists, this tool aims at raising the accuracy in outcome of neuro- studies by providing more insights on the errors involved.

How to contribute?

You can contribute to shamo in several ways like adding new features, fixing bugs or improving documentation and examples.

For more information, refer to this document.

How to cite?

If you use shamo in your work, please cite this paper (Available in open access on both Orbi and Arxiv):

@article{grignard_shamo_2022,
	title = {Shamo: A Tool for Electromagnetic Modeling, Simulation and Sensitivity} {Analysis of the Head},
	issn = {1559-0089},
	shorttitle = {Shamo},
	doi = {10.1007/s12021-022-09574-7},
	language = {en},
	journal = {Neuroinformatics},
	author = {Grignard, Martin and Geuzaine, Christophe and Phillips, Christophe},
	month = mar,
	year = {2022},
}

License

Copyright (C) 2020 GIGA CRC In-Vivo Imaging, Liège, Belgium

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

For more information, refer to the full license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

shamo-1.2.1.tar.gz (66.7 kB view details)

Uploaded Source

Built Distribution

shamo-1.2.1-py2.py3-none-any.whl (90.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file shamo-1.2.1.tar.gz.

File metadata

  • Download URL: shamo-1.2.1.tar.gz
  • Upload date:
  • Size: 66.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for shamo-1.2.1.tar.gz
Algorithm Hash digest
SHA256 a7bae0854d07aa830029a06008688794d091f299998553bbe6c5044abb71db8b
MD5 7c9aa1ecf33167a3d15df13ec8b29ac1
BLAKE2b-256 b490d86f9468c79d948a8e7cde553d19225cf35cdf42eb073d3ed665b4cd183d

See more details on using hashes here.

File details

Details for the file shamo-1.2.1-py2.py3-none-any.whl.

File metadata

  • Download URL: shamo-1.2.1-py2.py3-none-any.whl
  • Upload date:
  • Size: 90.7 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for shamo-1.2.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 a40c489dbf7f1539d8b6e19a5b4ade3248b7cb001ce3a504511362193ecc5f69
MD5 3db3c765cd9943ffd4003e48aef07367
BLAKE2b-256 0a1f4d69ed6c8c3e5ac73461714741887d87683c42adbe9749efc1ed45dc888a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page