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Code for sampling random subspaces from Elsayed & Lara et al. Nature Communications 2016

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====================================================================
Gamaleldin F. Elsayed, Columbia University
John P. Cunningham, Columbia University
Copyright (C) 2016 Gamaleldin F. Elsayed and John P. Cunningham

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.

You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
====================================================================


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Basic Usage Example

Follow the demo.m file for an example
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sampleRandSubspaces.m

This is the is the core function that generates a null distribution of 
a user defined summary statistic. This summary statistic is a function of 
the random subspaces generated by this method. The function will generate 
random subspaces and will call the function defined user (passed as an input)
 

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alignIx.m

an example of a function of the subspace parameters, which calculates 
the degree of alignment between a dataset and a subspace. 
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The BibTeX citations for the primary papers used in this project are:

@article{elsayed2016reorganization,
  title={Reorganization between preparatory and movement population responses in motor cortex},
  author={Elsayed, Gamaleldin F and Lara, Antonio H and Kaufman, Matthew T and Churchland, Mark M and Cunningham, John P},
  journal={Nature Communications},
  volume={7},
  year={2016},
  publisher={Nature Publishing Group}
}
====================================================================

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Code for sampling random subspaces from Elsayed & Lara et al. Nature Communications 2016

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