function from_data

deeptime.markov.hmm.init.gaussian.from_data(trajs, n_hidden_states, reversible, transition_matrix_kwargs=None)

Makes an initial guess HMM with Gaussian output model.

To this end, a Gaussian mixture model is estimated using scikit-learn.

Parameters:

  • trajs (array_like or list of array_like) – Trajectories which are used for making the initial guess.

  • n_hidden_states (int) – Number of hidden states.

  • reversible (bool) – Whether the hidden transition matrix is estimated so that it is reversible.

  • transition_matrix_kwargs (dict, optional, default=None) – Optional keyword arguments that are passed to transition_matrix.

Returns:

hmm_init – An initial guess for the HMM

Return type:

HiddenMarkovModel

See also

deeptime.markov.hmm.GaussianOutputModel

The type of output model this heuristic uses.

deeptime.markov.hmm.init.discrete.metastable_from_data, deeptime.markov.hmm.init.discrete.metastable_from_msm