osl_dynamics.analysis.gmm#

Functions related to Gaussian Mixture Models (GMMs).

Module Contents#

Functions#

fit_gaussian_mixture(X[, logit_transform, ...])

Fits a two-component Gaussian Mixture Model (GMM).

Attributes#

_logger

osl_dynamics.analysis.gmm._logger[source]#
osl_dynamics.analysis.gmm.fit_gaussian_mixture(X, logit_transform=False, standardize=True, p_value=None, one_component_percentile=None, n_sigma=0, label_order='mean', sklearn_kwargs=None, return_statistics=False, show_plot=False, plot_filename=None, plot_kwargs=None, log_message=True)[source]#

Fits a two-component Gaussian Mixture Model (GMM).

Parameters:

  • X (np.ndarray) – Data to fit GMM to. Must be 1D.

  • logit_transform (bool, optional) – Should we logit transform the X?

  • standardize (bool, optional) – Should we standardize X?

  • p_value (float, optional) – Used to determine a threshold. We ensure the data points assigned to the ‘on’ component have a probability of less than p_value of belonging to the ‘off’ component.

  • one_component_percentile (float, optional) – Percentile threshold if only one component is found. Should be between 0 and 100. E.g. for the 95th percentile, one_component_percentile=95.

  • n_sigma (float, optional) – Number of standard deviations of the ‘off’ component the mean of the ‘on’ component must be for the fit to be considered to have two components.

  • label_order (str, optional) – How do we order the inferred classes?

  • sklearn_kwargs (dict, optional) – Dictionary of keyword arguments to pass to sklearn.mixture.GaussianMixture.

  • return_statistics (bool, optional) – Should we return statistics of the Gaussian mixture components?

  • show_plot (bool, optional) – Should we show the GMM fit to the distribution of X.

  • plot_filename (str, optional) – Filename to save a plot of the Gaussian mixture model.

  • plot_kwargs (dict, optional) – Keyword arguments to pass to utils.plotting.plot_gmm Only used if plot_filename is not None.

  • log_message (bool) – Should we log a message?

Returns:

threshold – Threshold for the on class.

Return type:

float