smarkov
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
1 maintainer
Metadata
1 maintainer
Release files for smarkov 1.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| smarkov-1.0.tar.gz | 4.8 kB | Details |
Release files / smarkov-1.0.tar.gz
| Download URL | smarkov-1.0.tar.gz |
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