This is an app that takes multiple MNE.Raw instances and concatenates them using mne.concatenate_raws().
- Input files are mne/Raw.fif files
- The output file is mne/Raw, as well.
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.
We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.
- 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
You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.
- git clone this repo.
- Inside the cloned directory, create
config.jsonwith something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}- Launch the App by executing
main
./mainIf 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 .
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
This App requires MNE/Python to run.