I am very grateful to you and your team for the code that you provided. I am very interested in IOHMM models and want to use my dataset to train a simple UnsupervisedIOHMM. But，there is a problem in using the model.

I was wondering if it is possible to impose constraints on the transition probability when learning with EM. I want to train a specific type of IOHMM where there are no transitions from a higher indexed state to a lower indexed state (also called the Bakis model, left-to-right HMMs). By means of which, if a system goes from any state z𝑖 to another state z𝑗 where 𝑖 <= 𝑗, then it cannot go back to the previous state. Does the existing IOHMM Library have this option? Or How can I add this constraint to the code?