p-j-smith / lipyphilic-tutorials

Interactive tutorials for getting the most out of lipyphilic

lipyphilic tutorials

Interactive tutorials for getting the most out of lipyphilic

lipyphilic-tutorials's Issues

Study Hidden Markov Models (HMM) error

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i was to rerun the HMM code by use own xtc and tpr files, but it report the error as follow:

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......

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• Which version of lipyphilic are you using?
• Which version of Python are you using?
  -python=3.9
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Error with HMM analysis

Discussed in p-j-smith/lipyphilic#117

^{Originally posted by ffavelar July 25, 2023}
I'm trying to run the tutorial of the Hidden Markov Model in Ubuntu 20.04.6 LTS (GNU/Linux 5.15.0-75-generic x86_64) and Python 3.9.10. I get this output:

100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 51/51 [00:01<00:00, 29.28it/s]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 51/51 [00:01<00:00, 46.18it/s]
0%| | 0/3 [00:00<?, ?it/s]
MultinomialHMM has undergone major changes. The previous version was implementing a CategoricalHMM (a special case of MultinomialHMM). This new implementation follows the standard definition for a Multinomial distribution (e.g. as in https://en.wikipedia.org/wiki/Multinomial_distribution). See these issues for details:
hmmlearn/hmmlearn#335
hmmlearn/hmmlearn#340
0%| | 0/3 [00:00<?, ?it/s]
Traceback (most recent call last):
File "HiddenMarkovModel.py", line 370, in
model = model.fit(
File "/home/jorge/.local/lib/python3.9/site-packages/hmmlearn/base.py", line 469, in fit
self._check()
File "/home/jorge/.local/lib/python3.9/site-packages/hmmlearn/hmm.py", line 907, in check
raise ValueError(
ValueError: emissionprob must have shape (n_components, n_features)

I understand that emissionprob_ does not have the proper shape, but I don't know how to fix the code. Any help will be appreciated.