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The GLHMM toolbox provides facilities to fit a variety of Hidden Markov models (HMM) based on the Gaussian distribution, which we generalise as the Gaussian-Linear HMM. Crucially, the toolbox has a focus on finding associations at various levels between brain data (EEG, MEG, fMRI, ECoG, etc) and non-brain data, such as behavioural or physiological variables.

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Dependencies

The required dependencies to use glhmm are:

  • Python >= 3.6

  • NumPy

  • numba

  • scikit-learn

  • scipy

  • matplotlib

  • seaborn

  • cupy (only when using GPU acceleration; requires manual install)

Installation

  • To install the latest development version from the repository, use the following command:
pip install git+https://github.com/vidaurre/glhmm
  • Alternatively, to install the latest stable release from PyPI, use the command:
pip install glhmm

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