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Welcome to the NMHS data processing toolbox. This code was used for analyzing data in the paper “Analysis of Neural Circuits with Non-Linear Multi-Dimensional Hidden State Models”. 
Authors: Joshua Slocum and Danil Tyulmankov
Citation: 

The newest version of the code can be found at:
https://github.com/jfslocum/NMHS

FORMATTING CONVENTIONS
- For brevity, all functions use a packed format for input and output of models. Packing and unpacking functions are in the utils folder
- Transfer matrices follow a pattern of "to, from, from...". E.g. tr(i,j,k) is the probability of transitioning to state i given the process is in state j and its neighbor is in state k. Note that this means all rows must sum to 1.
- Emission matrices follow a pattern of "state, emission": em(s, e) is the likelihood of emitting 'e' given state 's'. Note that this means all columns must sum to 1. 
- All data sequences are assumed to be row-vectors. 



LICENSE AGREEMENT
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Thus, subject to the terms herein, M.I.T.  grants a royalty-free, non-transferable, non-exclusive license under its copyrights to use, reproduce, display, perform and modify the software solely for non-commercial research and/or academic testing purposes.   In order to obtain any other license rights, including the right to use the software or filed patents for commercial purposes, you must contact the M.I.T. Technology Licensing Office and enter into additional license agreements with M.I.T.