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