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InvGammaMap

Namespace: INVERSELIB  ·  Library: Inverse Library

Python equivalent

mne.inverse_sparse.gamma_map in MNE-Python.

#include <inv/inv_gamma_map.h>

class INVLIB::InvGammaMap

Gamma-MAP sparse inverse solver (Sparse Bayesian Learning).

Iteratively estimates source variance hyperparameters (gamma) and prunes sources whose gamma falls below a threshold, yielding a sparse solution.

Gamma-MAP sparse inverse solver.

Static Methods​

compute(matGain, matData, matNoiseCov, nIterations, tolerance, gammaThreshold)​

Compute the Gamma-MAP inverse solution.

Parameters:

  • matGain : const Eigen::MatrixXd & Forward gain matrix (n_channels x n_sources).

  • matData : const Eigen::MatrixXd & Measurement data (n_channels x n_times).

  • matNoiseCov : const Eigen::MatrixXd & Noise covariance matrix (n_channels x n_channels).

  • nIterations : int Maximum number of EM iterations.

  • tolerance : double Convergence tolerance on relative gamma change.

  • gammaThreshold : double Threshold below which sources are pruned.

Returns:

  • InvGammaMapResult — The Gamma-MAP result containing the sparse source estimate.

Authors of this file​