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:
- 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:
- tree.py and a new IPython notebook:
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.