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A Python implementation of CSSR for epsilon-transducers.

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Name		Name	Last commit message	Last commit date
Latest commit History 30 Commits
data		data
simulation-codes-paper		simulation-codes-paper
simulation-codes		simulation-codes
transCSSR_results		transCSSR_results
.gitignore		.gitignore
README.md		README.md
compute_mixed_matrix.py		compute_mixed_matrix.py
demo_CSSR.py		demo_CSSR.py
demo_predict_Lstep_bc.py		demo_predict_Lstep_bc.py
demo_predict_presynch_eT.py		demo_predict_presynch_eT.py
demo_predict_presynch_eT_bc.py		demo_predict_presynch_eT_bc.py
demo_transCSSR.py		demo_transCSSR.py
demo_transCSSR_bc.py		demo_transCSSR_bc.py
filter_data_methods.py		filter_data_methods.py
simulate_eM.py		simulate_eM.py
simulate_eT.py		simulate_eT.py
transCSSR.py		transCSSR.py
transCSSR_bc.py		transCSSR_bc.py
walkthrough_transCSSR_bc.py		walkthrough_transCSSR_bc.py

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transCSSR

A Python implementation of the Causal State Splitting Reconstruction (CSSR) algorithm for inferring epsilon-transducers from data generated by discrete-valued, discrete-time input/output systems. This page provides the full source code, released under the GNU Public License.

This implementation has been tested on Mac OS X 10.10.3, but should work on any Unix-based OS. It requires the following Python dependencies:

These packages may be installed individually. A useful collection of these and related libraries for scientific computing with Python may be installed using Enthought or Anaconda.

Visualization of the epsilon-machines requires Graphviz or similar software for reading dot files.