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The StateSpace class is at this stage living its own little separate existence - e.g., it is not strictly needed for estimating a matrix. (Right now a new transition matrix has an implicit hardwired state space that is formed by its dimension - say states 0, 1, ... N). The main implemented functionality of StateSpace is to validate whether an input data set has the expected labels. In the future the plan is to build on this and specify for example absorbing states and other non-permissible transitions, and also identify the stucture from datasets.
What to study next depends a little bit on what you are interested to do with the library. I have put together a little high level howto here and there is an eLearning module that you could follow here.
In terms of "examples to study after state_space_operations.py" - perhaps annotating/reordering scripts a README.md in examples folder could be helpful as well - 545833f.
Maybe I should make README.md correction a separate issue, once merged and close thins one?
I'm looking at StateSpace class to understand better how
transitionMatrix
generally works.I reviewed state_space_operations.py as usage example of StateSpace class for data rating scales manipulation, but what file should be the next example to see?
Many thanks for guidance!
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