pyquest: diffusion analysis of questionnaires.

This version of pyquest includes:

• averaging and difference tree transforms
• multi-tree EMD
• data-driven weighted EMD
• bi-haar coherency measure
• sparse affinity matrices (untested) Added files:
• transform.py
• tree_transforms.ipynb (jupyter notebook demonstrating tree transforms)

A Matlab implementation can be found at https://github.com/gmishne/InformedGeometry-CoupledPendulum

TODO: add demo demonstrating multi-tree EMD and bi-organization local refinement

This version of pyquest includes tri-geometric analysis. Updated files:

• dual_affinity.py
• plot_utils.py
• questionnaire.py
• tree.py and a new IPython notebook:
• JSTSP.ipynb

If you use our software please cite:

• G. Mishne, R. Talmon, I. Cohen, R. R. Coifman and Y. Kluger, "Data-Driven Tree Transforms and Metrics," accepted to IEEE Transactions on Signal and Information Processing over Networks.

• G. Mishne, R. Talmon, R. Meir, J. Schiller, U. Dubin and R. R. Coifman, "Hierarchical Coupled Geometry Analysis for Neuronal Structure and Activity Pattern Discovery," IEEE Journal of Selected Topics in Signal Processing, vol. 10, no. 7, pp. 1238-1253, Oct. 2016.

• J. I. Ankenman, “Geometry and analysis of dual networks on questionnaires,” Ph.D. dissertation, Yale University, 2014.