Inverse Solutions

mne.minimum_norm:

Linear inverse solvers based on L2 Minimum Norm Estimates (MNE).

InverseOperator	InverseOperator class to represent info from inverse operator.
apply_inverse(evoked, inverse_operator[, ...])	Apply inverse operator to evoked data.
apply_inverse_cov(cov, info, inverse_operator)	Apply inverse operator to covariance data.
apply_inverse_epochs(epochs, ...[, method, ...])	Apply inverse operator to Epochs.
apply_inverse_raw(raw, inverse_operator, lambda2)	Apply inverse operator to Raw data.
compute_source_psd(raw, inverse_operator[, ...])	Compute source power spectral density (PSD).
compute_source_psd_epochs(epochs, ...[, ...])	Compute source power spectral density (PSD) from Epochs.
compute_rank_inverse(inv)	Compute the rank of a linear inverse operator (MNE, dSPM, etc.).
estimate_snr(evoked, inv[, verbose])	Estimate the SNR as a function of time for evoked data.
make_inverse_operator(info, forward, noise_cov)	Assemble inverse operator.
prepare_inverse_operator(orig, nave, lambda2)	Prepare an inverse operator for actually computing the inverse.
read_inverse_operator(fname[, verbose])	Read the inverse operator decomposition from a FIF file.
source_band_induced_power(epochs, ...[, ...])	Compute source space induced power in given frequency bands.
source_induced_power(epochs, ...[, label, ...])	Compute induced power and phase lock.
write_inverse_operator(fname, inv[, verbose])	Write an inverse operator to a FIF file.
make_inverse_resolution_matrix(forward, ...)	Compute resolution matrix for linear inverse operator.
resolution_metrics(resmat, src[, function, ...])	Compute spatial resolution metrics for linear solvers.
get_cross_talk(resmat, src, idx[, mode, ...])	Get cross-talk (CTFs) function for vertices.
get_point_spread(resmat, src, idx[, mode, ...])	Get point-spread (PSFs) functions for vertices.

mne.inverse_sparse:

Non-Linear sparse inverse solvers.

mixed_norm(evoked, forward, noise_cov[, ...])	Mixed-norm estimate (MxNE) and iterative reweighted MxNE (irMxNE).
tf_mixed_norm(evoked, forward, noise_cov[, ...])	Time-Frequency Mixed-norm estimate (TF-MxNE).
gamma_map(evoked, forward, noise_cov, alpha)	Hierarchical Bayes (Gamma-MAP) sparse source localization method.
make_stc_from_dipoles(dipoles, src[, verbose])	Convert a list of spatio-temporal dipoles into a SourceEstimate.

mne.beamformer:

Beamformers for source localization.

Beamformer	A computed beamformer.
read_beamformer(fname)	Read a beamformer filter.
make_lcmv(info, forward, data_cov[, reg, ...])	Compute LCMV spatial filter.
apply_lcmv(evoked, filters[, max_ori_out, ...])	Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.
apply_lcmv_epochs(epochs, filters[, ...])	Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.
apply_lcmv_raw(raw, filters[, start, stop, ...])	Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.
apply_lcmv_cov(data_cov, filters[, verbose])	Apply Linearly Constrained Minimum Variance (LCMV) beamformer weights.
make_dics(info, forward, csd[, reg, ...])	Compute a Dynamic Imaging of Coherent Sources (DICS) spatial filter.
apply_dics(evoked, filters[, verbose])	Apply Dynamic Imaging of Coherent Sources (DICS) beamformer weights.
apply_dics_csd(csd, filters[, verbose])	Apply Dynamic Imaging of Coherent Sources (DICS) beamformer weights.
apply_dics_epochs(epochs, filters[, ...])	Apply Dynamic Imaging of Coherent Sources (DICS) beamformer weights.
rap_music(evoked, forward, noise_cov[, ...])	RAP-MUSIC source localization method.
make_lcmv_resolution_matrix(filters, ...)	Compute resolution matrix for LCMV beamformer.

Dipole(times, pos, amplitude, ori, gof[, ...])	Dipole class for sequential dipole fits.
DipoleFixed(info, data, times, nave, aspect_kind)	Dipole class for fixed-position dipole fits.
fit_dipole(evoked, cov, bem[, trans, ...])	Fit a dipole.

mne.dipole:

Single-dipole functions and classes.

get_phantom_dipoles([kind])

Get standard phantom dipole locations and orientations.

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mne.minimum_norm.InverseOperator