Giter Site home page Giter Site logo

app-add-montage's Introduction

Abcdspec-compliant Run on Brainlife.io

app-apply-baseline

This is an app that adds a selected montage to an (M/)EEG raw from the list provided in the MNE package.

  1. Input file is mne/raw
  2. Input value of montage is selected from the dropdown menu (enum choice), and the optional choice of renaming any channels in the montage to correspond to the list of channels in the data is provided as a string.
  3. The output file is mne/raw, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853 NSF-BCS-1636893 NSF-ACI-1916518 NSF-IIS-1912270 NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
  "t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

app-add-montage's People

Contributors

guiomar avatar ksalibay avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.