The hmmus project has some HMM algorithms implemented in C, and it is meant to be useful under the following conditions:
* The sequence of observations to be analyzed is so long that it does not fit conveniently in RAM.
* Likelihoods per hidden state per position have been precalculated.
* Numerical stability is important, but is not so important that error bounds on the output are required.
* The number of hidden states is small.
* The matrix of probabilities of transitions between hidden states is dense.
* Binary data files are acceptable as input and output.
This project would be especially useless in the following cases:
* User friendly or pedagogically informative software is desired.
* All of the data can fit in RAM and numerical stability is not an issue.
* The hidden state transitions are defined by a large sparse graph.
* The emission distributions are uncomplicated (e.g. finite or normal).
Operating system requirements:
* This project was developed using Ubuntu, so it will probably work on Debian-based Linux distributions.
* It might work with non-Debian-based Unix variants.
* It probably will not work on Windows.
Major dependencies:
* A C compiler which is not too different from gcc.
Product's homepage
Requirements:
· Python
· Argparse
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