Skip to content

prakash-kavi/nice

 
 

Repository files navigation

NICE Tools

Get the latest code

To get the latest code using git, simply type:

git clone git://github.com/nice-tools/nice.git

If you don't have git installed, you can download a zip or tarball of the latest code: https://github.com/nice-tools/nice/archives/master

Install nice

As any Python packages, to install NICE, go in the nice source code directory and do:

python setup.py install

or if you don't have admin access to your python setup (permission denied when install) use:

python setup.py install --user

You can also install the latest latest development version with pip:

pip install -e git+https://github.com/nice-tools/nice#egg=nice-dev --user

Dependencies

The required dependencies to build the software are: * python >= 2.7 | python >= 3.4 * scipy >= 0.18.1 * numpy >= 1.11.1 * h5py >= 2.6.0

And principally, mne-python >= 0.13: http://mne-tools.github.io/stable/index.html

Some functions require pandas >= 0.7.3.

To run the tests you will also need nose >= 0.10.

To use wSMI with CSD you need pycsd: https://github.com/nice-tools/pycsd/

Optimizations (optional)

Aditionally, we ship optimized versions of some algorithms. They can be compiled using the conda CLANG and openmp. Both can be installed as follows:

conda install clang
conda install openmp

To build, go to the nice soure code directory and do:

CC=clang make

Then set backend='c' or 'openmp' instead of the defalut backend='python' in markers functions

If running on osx 10.15, then you might face this error:

/anaconda3/include/python3.7m/Python.h:25:10: fatal error: 'stdio.h' file not found

Running this command will fix it:

sudo ln -s /Library/Developer/CommandLineTools/SDKs/MacOSX.sdk/usr/include/* /usr/local/include/

Running the test suite

To run the test suite, you need nosetests and the coverage modules. Run the test suite using:

nosetests

from the root of the project.

Cite

If you use this code in your project, please cite:

Engemann D.A.*, Raimondo F.*, King JR., Rohaut B., Louppe G.,
Faugeras F., Annen J., Cassol H., Gosseries O., Fernandez-Slezak D.,
Laureys S., Naccache L., Dehaene S. and Sitt J.D. (2018).
Robust EEG-based cross-site and cross-protocol classification of
states of consciousness. Brain. Vol 141 (11), 3160–3178, doi:10.1093/brain/awy251

Licensing

NICE is licensed under the GNU Affero General Public License version 3:

This software is OSI Certified Open Source Software. OSI Certified is a certification mark of the Open Source Initiative.

Copyright (c) 2017, authors of NICE - All rights reserved.

  • This program is free software: you can redistribute it and/or modify it under the terms of the GNU Affero 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 Affero General Public License for more details.
  • You should have received a copy of the GNU Affero General Public License along with this program. If not, see <http://www.gnu.org/licenses/>.
  • You can be released from the requirements of the license by purchasing a commercial license. Buying such a license is mandatory as soon as you develop commercial activities as mentioned in the GNU Affero General Public License version 3 without disclosing the source code of your own applications.

About

NICE project for MEG and EEG data analysis.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 56.7%
  • Csound Document 21.6%
  • C 19.9%
  • Makefile 1.8%