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Simple Markov and HMM

Project description

Simple, lightweight and easy to read implementation of Markov chains and HMMs.

This is a toy project, don’t expect any exciting speeds or robustness.

Happy hacking!

Installing

pip3 install git+git://github.com/greenify/smarkov.git

Hacking

git clone https://github.com/greenify/smarkov
cd smarkov
python3 setup.py develop

Train with a corpus

from smarkov import Markov
chain = Markov(["AGACAGACGAC"])

Attributes

corpus: given corpus (a corpus_entry needs to be a tuple or array)
order: maximal order to look back for a given state (default 1) tokenize: function how to split an element of the corpus (e.g sentences into words)

Generate text from a chain

print("".join(chain.generate_text()))

Generate_text() generates exactly one element from the Markov chain. In other words: It goes in the Markov chain the universal start state to universal end state.

More Examples

See examples

Coming

Documentation how to use it with HMM.

License

MIT

Project details


Release history Release notifications

This version
History Node

1.0

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Filename, size & hash SHA256 hash help File type Python version Upload date
smarkov-1.0.tar.gz (4.8 kB) Copy SHA256 hash SHA256 Source None Jan 21, 2016

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