pyquest: diffusion analysis of transposable arrays
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.gitattributes
.gitignore
JSTSP.ipynb
LICENSE
README.md
SN_basic.npz
affinity.py
ankenman_diss.pdf
artificial_data.py
barcode.py
bin_tree_build.py
dual_affinity.py
flex_tree_build.py
haar.py
imports.py
markov.py
plot_utils.py
py_load_data.py
question_tree.py
questionnaire.py
thesis_SN.ipynb
thesis_ad1.ipynb
thesis_ad2.ipynb
thesis_binary_tree.ipynb
thesis_flex_tree.ipynb
thesis_haar.ipynb
thesis_mmpi.ipynb
thesis_spin_cycling.ipynb
transform.py
tree.py
tree_recon.py
tree_transforms.ipynb
tree_util.py
tree_viewer.py
viewer_files.py

README.md

pyquest

pyquest: diffusion analysis of questionnaires.

Aug. 2017

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

Aug. 2016

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.