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Manifold Oblique Random Forests Demonstration on Simulated and Example Datasets

This project reproduces some of the simulation and example data results in the MORF paper.

This will produce examples of:

  1. simulation examples (see paper and notebooks for full details)
  2. neural fragility seizure outcome classification
  3. sEEG time series to classify movement from non-motor brain regions

Primarily, you should refer to the notebooks/ to look at experiments rendered.

System Requirements

Generally to run the figure generation, one simply needs a standard computer with enough RAM. Minimally to generate the figures, probably a computer with 2GB RAM is sufficient.

We ran tests on computer with the following:

RAM: 16+ GB CPU: 4+ cores, i7 or equivalent

Software: Mac OSX or Linux Ubuntu 18.04+. One should use Python3.6+.

Installation Guide

Setup environment from pipenv. The Pipfile contains the Python libraries needed to run the figure generation in notebook.

pipenv install --dev

# use pipenv to install private repo
pipenv install -e [email protected]:adam2392/eztrack

# or
pipenv install -e /Users/adam2392/Documents/eztrack

# if dev versions are needed
pipenv install https://api.github.com/repos/mne-tools/mne-bids/zipball/master --dev
pipenv install https://api.github.com/repos/mne-tools/mne-python/zipball/master --dev

Instructions for Use

Run the notebook from beginning to end to generate figures, by pointing the path to the data/ folder here. To setup an ipykernel to expose your Python virtual environment to the Jupyter kernel:

make ipykernel

In order to build ReRF, we use a custom version that is at neurodata/SPORF#353. Build the C++ code from that PR, and then run pip install.

pip install -e <SPORF_DIR>

Neural fragility dataset

See paper for all details: https://www.biorxiv.org/content/10.1101/862797v4

sEEG motor movement in non-motor brain region dataset

See the following papers for more information.