Inverse source estimation (MNE, dSPM, sLORETA, dipole fitting). More...

Classes
class	InvBeamformer
	Computed beamformer spatial filter container. More...
class	InvBeamformerCompute
	Core beamformer math. More...
class	InvDICS
	DICS beamformer (frequency-domain). More...
class	InvLCMV
	LCMV beamformer (time-domain). More...
class	InvDipoleFit
	High-level driver for sequential dipole fitting. More...
struct	dipoleFitFuncsRec
	Forward field computation function pointers and client data for MEG and EEG dipole fitting. More...
struct	FitDipUserRec
	Workspace for the dipole fitting objective function, holding forward model, measured field, and fit limits. More...
class	InvDipoleFitData
	Dipole fit workspace holding sensor geometry, forward model, noise covariance, and projection data. More...
class	InvDipoleFitSettings
	Settings for the `mne_dipole_fit` driver (forward model, guess grid, data, projections, output). More...
class	InvDipoleForward
	Stores forward field matrices and SVD decomposition for magnetic dipole fitting. More...
class	InvEcd
	Single equivalent current dipole with position, orientation, amplitude, and goodness-of-fit. More...
struct	bdipEcdRec
	Binary-format dipole record for file I/O, storing fitted dipole parameters and error estimates. More...
class	InvEcdSet
	Holds a set of Electric Current Dipoles. More...
class	InvGuessData
	Precomputed guess point grid with forward fields for initial dipole position candidates. More...
class	InvHpiDataUpdater
	Preprocesses raw HPI coil data (SSP projection, compensation, sinusoidal model fitting) before dipole localization. More...
struct	CoilParam
	Estimated dipole parameters (position, moment, goodness-of-fit) for a single HPI coil. More...
struct	HpiFitResult
	Complete HPI fit output: per-coil dipole parameters, head-to-device transform, fit error, and head movement distance. More...
class	InvHpiFit
	Drives one HPI fit (per-coil dipole localisation, coil ordering, dewar-to-head transform). More...
struct	DipFitError
	Residual error and moment vector from a single magnetic dipole fit iteration. More...
struct	HPISortStruct
	Helper for sorting HPI coil dipole fits by matching each fit to the nearest expected coil position. More...
class	InvHpiFitData
	Per-coil magnetic-dipole fitter (leadfield, residual, Nelder-Mead refinement) for the HPI pipeline. More...
class	InvHpiModelParameters
	Configuration parameters for the HPI signal model (line frequency, coil frequencies, sample rate, buffer size). More...
class	InvSensorSet
	Stores MEG sensor geometry (positions, orientations, weights, coil count) for a single sensor type. More...
class	InvSensorSetCreator
	Builds InvSensorSet objects from FiffInfo channel definitions, applying SSP projections and compensation. More...
class	InvSignalModel
	Generates the forward sinusoidal model matrix for HPI coil signals at known drive frequencies. More...
struct	InvConnectivity
	Pairwise source connectivity matrix with measure, directionality, and frequency/time metadata. More...
struct	InvFocalDipole
	Single focal dipole with free 3D position, moment, and fit-quality metrics. More...
class	InvLabelTimeCourse
	Extract ROI-level time courses from vertex-level source estimates. More...
class	InvResolutionMatrix
	Resolution matrix analysis for linear inverse operators. More...
struct	InvSourceCoupling
	N-tuple of correlated grid sources with orientations and correlation matrix. More...
class	InvSourceEstimate
	Source-space inverse-solution container with dense grid plus optional focal-dipole, coupling and connectivity layers. More...
class	InvSourceEstimateIO
	Extended I/O methods for InvSourceEstimate. More...
struct	InvToken
	One element of a tokenised neural-source representation. More...
struct	InvTokenizeOptions
	Tokenization options controlling layer inclusion and sub-sampling. More...
class	InvVectorSourceEstimate
	Vector source estimate: each vertex carries a 3D orientation vector across time. More...
class	InvVolumeSourceEstimate
	Volume source estimate: scalar values at voxel locations. More...
struct	InvCMNEResult
	CMNE result. More...
class	InvCMNE
	CMNE inverse solver. More...
struct	InvCMNESettings
	CMNE settings. More...
class	InvMinimumNorm
	Minimum norm estimation. More...
class	SourceMorph
	Morphs source estimates from one subject's source space to another. More...
class	InvDipole
	Stores position, orientation, and correlation of a single current dipole estimated by RAP MUSIC. More...
struct	InvDipolePair
	Pair of correlated dipole indices and orientations found by the RAP MUSIC scanning step. More...
class	InvPwlRapMusic
	Powell-accelerated RAP MUSIC variant using gradient-free optimization for refined dipole fitting. More...
struct	Pair
	Index pair representing two grid points evaluated together in the RAP MUSIC subspace scan. More...
class	InvRapMusic
	RAP MUSIC (Recursively Applied and Projected Multiple Signal Classification) source localization algorithm. More...
struct	TrapMusicDipole
	Result of a TRAP-MUSIC source scan. More...
class	InvTrapMusic
	TRAP-MUSIC (Truncated RAP-MUSIC) source localization. More...
struct	InvGammaMapResult
class	InvGammaMap
	Gamma-MAP sparse inverse solver. More...
struct	InvMxneResult
class	InvMxne
	MxNE sparse inverse solver. More...
struct	InvTfMxneResult
	Result structure for the TF-MxNE solver. More...
struct	InvTfMxneParams
	Parameters for the TF-MxNE solver. More...
class	InvTfMxne
	Time-Frequency Mixed-Norm Estimate (TF-MxNE) sparse inverse solver. More...

Typedefs
using	dipoleFitFuncs = dipoleFitFuncsRec*
	Pointer alias for dipoleFitFuncsRec, used throughout the dipole fitting module.
using	bdipEcd = bdipEcdRec*

Enumerations
enum class	BeamformerWeightNorm { None = 0 , UnitNoiseGain , NAI , UnitNoiseGainInv }
enum class	BeamformerPickOri { None = 0 , Normal , MaxPower , Vector }
enum class	BeamformerInversion { Matrix = 0 , Single }
enum class	Accuracy : int { high = 2 , medium = 1 , low = 0 }
enum class	InvTokenId : int32_t { Pad = 0 , Bos = 1 , Eos = 2 , Sep = 3 , MetaBegin = 10 , MetaEnd = 11 , GridBegin = 20 , GridEnd = 21 , GridRow = 22 , CouplingBegin = 30 , CouplingEnd = 31 , GroupBegin = 32 , GroupEnd = 33 , FocalBegin = 40 , FocalEnd = 41 , DipoleBegin = 42 , DipoleEnd = 43 , ConnBegin = 50 , ConnEnd = 51 , ConnEntryBegin = 52 , ConnEntryEnd = 53 , PosBegin = 60 , PosEnd = 61 , MethodUnknown = 100 , MethodMNE = 101 , MethodDSPM = 102 , MethodSLORETA = 103 , MethodELORETA = 104 , MethodLCMV = 105 , MethodDICS = 106 , MethodSAM = 107 , MethodMixedNorm = 108 , MethodGammaMAP = 109 , MethodDipoleFit = 110 , MethodRapMusic = 111 , MethodPwlRapMusic = 112 , SpaceUnknown = 150 , SpaceSurface = 151 , SpaceVolume = 152 , SpaceMixed = 153 , SpaceDiscrete = 154 , OrientUnknown = 170 , OrientFixed = 171 , OrientFree = 172 , OrientLoose = 173 , Amplitude = 200 , Vertex = 201 , TimeVal = 202 , FreqVal = 203 , PosX = 204 , PosY = 205 , PosZ = 206 , MomX = 207 , MomY = 208 , MomZ = 209 , Goodness = 210 , ChiSquared = 211 , Correlation = 212 , ConnValue = 213 , GridIndex = 214 , ValidTrue = 250 , ValidFalse = 251 , DirectedTrue = 252 , DirectedFalse = 253 , NSources = 280 , NTimes = 281 , NGroups = 282 , NDipoles = 283 , NMeasures = 284 , NIndices = 285 , NFreeDof = 286 , TStep = 287 , MeasCoh = 300 , MeasImCoh = 301 , MeasPlv = 302 , MeasPli = 303 , MeasWpli = 304 , MeasGranger = 305 , MeasPdc = 306 , MeasDtf = 307 , MeasCorrelation = 308 , MeasCrossCorr = 309 , MeasOther = 310 , QuantBinBase = 1000 }
enum class	InvEstimateMethod { Unknown = 0 , MNE , dSPM , sLORETA , eLORETA , LCMV , DICS , SAM , MixedNorm , GammaMAP , DipoleFit , RapMusic , PwlRapMusic }
enum class	InvSourceSpaceType { Unknown = 0 , Surface , Volume , Mixed , Discrete }
enum class	InvOrientationType { Unknown = 0 , Fixed , Free , Loose }

Functions
INVSHARED_EXPORT QList< InvSourceEstimate >	applyInverseEpochs (const QList< Eigen::MatrixXd > &epochs, const MNELIB::MNEInverseOperator &inverse, float lambda2, const QString &method="dSPM", float tmin=0.0f, float tstep=0.001f, bool pickNormal=false)
	Apply inverse operator to each epoch in a list.
INVSHARED_EXPORT InvSourceEstimate	applyInverseRaw (const FIFFLIB::FiffRawData &raw, const MNELIB::MNEInverseOperator &inverse, float lambda2, const QString &method="dSPM", int from=-1, int to=-1, bool pickNormal=false)
	Apply inverse operator to raw data in blocks.
INVSHARED_EXPORT QPair< Eigen::VectorXd, Eigen::RowVectorXf >	estimateSnr (const FIFFLIB::FiffEvoked &evoked, const MNELIB::MNEInverseOperator &inverse, const QString &method="dSPM")
	Estimate SNR from evoked data and inverse operator.
INVSHARED_EXPORT QPair< Eigen::MatrixXd, int >	computeWhitener (const FIFFLIB::FiffCov &noiseCov, int rank=0)
	Compute whitening matrix from a noise covariance.
INVSHARED_EXPORT QPair< Eigen::MatrixXd, Eigen::VectorXd >	computeSourcePsd (const InvSourceEstimate &stc, float sfreq, float fmin=0.0f, float fmax=-1.0f, int nFft=0)
	Compute PSD for a source estimate using Welch's method.
INVSHARED_EXPORT QMap< QString, Eigen::VectorXd >	computeSourceBandPower (const InvSourceEstimate &stc, float sfreq, const QMap< QString, QPair< float, float > > &bands)
	Compute band power for source estimate.
INVSHARED_EXPORT const char *	buildDateTime ()
INVSHARED_EXPORT const char *	buildHash ()
INVSHARED_EXPORT const char *	buildHashLong ()
std::vector< InvToken >	tokenize (const InvSourceEstimate &estimate, const InvTokenizeOptions &options=InvTokenizeOptions())
	Serialise an InvSourceEstimate into a flat token sequence.
InvSourceEstimate	fromTokens (const std::vector< InvToken > &tokens)
	Reconstruct an InvSourceEstimate from a token sequence.
std::vector< int32_t >	tokenIds (const std::vector< InvToken > &tokens)
std::vector< float >	tokenValues (const std::vector< InvToken > &tokens)

Variables
constexpr double	BIG_TIME = 1e6

Detailed Description

Inverse source estimation (MNE, dSPM, sLORETA, dipole fitting).

Typedef Documentation

◆ bdipEcd

using INVLIB::bdipEcd = bdipEcdRec*

Definition at line 111 of file inv_ecd_set.cpp.

◆ dipoleFitFuncs

using INVLIB::dipoleFitFuncs = dipoleFitFuncsRec*

Pointer alias for dipoleFitFuncsRec, used throughout the dipole fitting module.

Definition at line 93 of file inv_dipole_fit_data.h.

Enumeration Type Documentation

◆ Accuracy

enum class INVLIB::Accuracy : int

strong

Enumerator
high
medium
low

Definition at line 67 of file inv_sensor_set.h.

◆ BeamformerInversion

enum class INVLIB::BeamformerInversion

strong

Method for inverting the beamformer denominator matrix G^H Cm^{-1} G.

Enumerator
Matrix	Full matrix inversion per source.
Single	Scalar (diagonal) inversion per source.

Definition at line 66 of file inv_beamformer_settings.h.

◆ BeamformerPickOri

enum class INVLIB::BeamformerPickOri

strong

Orientation picking mode for beamformer filters.

Enumerator
None	Keep all orientations (3 per source for free, 1 for fixed).
Normal	Extract surface normal component only (Z in local coords).
MaxPower	Optimal orientation via max eigenvalue of power matrix.
Vector	Return the full 3-component vector solution.

Definition at line 54 of file inv_beamformer_settings.h.

◆ BeamformerWeightNorm

enum class INVLIB::BeamformerWeightNorm

strong

Weight normalization strategy for beamformer spatial filters.

References:

Sekihara & Nagarajan, "Adaptive Spatial Filters for Electromagnetic Brain Imaging", 2008.
Van Veen et al., IEEE Trans. Biomed. Eng. 44(9), 867-880, 1997.

Enumerator
None	No normalization (raw unit-gain filter).
UnitNoiseGain	Normalize by sqrt(diag(W @ W^H)), Sekihara 2008.
NAI	Neural Activity Index: unit-noise-gain + noise subspace normalization.
UnitNoiseGainInv	Rotation-invariant unit-noise-gain via sqrtm(inner)^{-0.5}.

Definition at line 42 of file inv_beamformer_settings.h.

◆ InvEstimateMethod

enum class INVLIB::InvEstimateMethod

strong

Enumerates the inverse estimation method that produced a source estimate.

Enumerator
Unknown
MNE
dSPM
sLORETA
eLORETA
LCMV
DICS
SAM
MixedNorm
GammaMAP
DipoleFit
RapMusic
PwlRapMusic

Definition at line 36 of file inv_types.h.

◆ InvOrientationType

enum class INVLIB::InvOrientationType

strong

Enumerates the orientation constraint used during source estimation.

Enumerator
Unknown
Fixed
Free
Loose

Definition at line 70 of file inv_types.h.

◆ InvSourceSpaceType

enum class INVLIB::InvSourceSpaceType

strong

Enumerates the source space type underlying a source estimate.

Enumerator
Unknown
Surface
Volume
Mixed
Discrete

Definition at line 57 of file inv_types.h.

◆ InvTokenId

enum class INVLIB::InvTokenId : int32_t

strong

Token vocabulary for the InvSourceEstimate tokenization format.

IDs are organised into ranges: 0..9 Special tokens (PAD, BOS, EOS, SEP) 10..19 Metadata section markers 20..29 Grid section markers 30..39 Coupling section markers 40..49 Focal-dipole section markers 50..59 Connectivity section markers 60..69 Positions section markers 100..149 Method labels 150..169 Source-space labels 170..189 Orientation labels 200..249 Value-carrier tokens (id + continuous float) 250..279 Boolean tokens 280..299 Dimension/size tokens (id + int-as-float) 300..349 Connectivity measure name tokens 1000+ Reserved for external quantisation bins

Enumerator
Pad
Bos	Beginning of sequence.
Eos	End of sequence.
Sep	Separator (between modalities, optional).
MetaBegin
MetaEnd
GridBegin
GridEnd
GridRow	Marks the start of one source's time-course.
CouplingBegin
CouplingEnd
GroupBegin	Start of one N-tuple coupling group.
GroupEnd
FocalBegin
FocalEnd
DipoleBegin	Start of one focal dipole.
DipoleEnd
ConnBegin
ConnEnd
ConnEntryBegin	Start of one connectivity measure.
ConnEntryEnd
PosBegin
PosEnd
MethodUnknown
MethodMNE
MethodDSPM
MethodSLORETA
MethodELORETA
MethodLCMV
MethodDICS
MethodSAM
MethodMixedNorm
MethodGammaMAP
MethodDipoleFit
MethodRapMusic
MethodPwlRapMusic
SpaceUnknown
SpaceSurface
SpaceVolume
SpaceMixed
SpaceDiscrete
OrientUnknown
OrientFixed
OrientFree
OrientLoose
Amplitude	Source amplitude at one (source, time) sample.
Vertex	Vertex / grid index.
TimeVal	Time in seconds.
FreqVal	Frequency in Hz.
PosX	3-D position x component (m).
PosY	3-D position y component (m).
PosZ	3-D position z component (m).
MomX	Dipole moment x component (Am).
MomY	Dipole moment y component (Am).
MomZ	Dipole moment z component (Am).
Goodness	Goodness-of-fit (0..1).
ChiSquared	Chi-squared fit quality.
Correlation	Coupling correlation value.
ConnValue	Pairwise connectivity value.
GridIndex	Grid reference index inside a coupling group.
ValidTrue
ValidFalse
DirectedTrue
DirectedFalse
NSources	Number of grid sources.
NTimes	Number of time samples.
NGroups	Number of coupling groups.
NDipoles	Number of focal dipoles.
NMeasures	Number of connectivity measures.
NIndices	Number of indices in a coupling group.
NFreeDof	Degrees of freedom.
TStep	Time step (s) — grid sampling interval.
MeasCoh
MeasImCoh
MeasPlv
MeasPli
MeasWpli
MeasGranger
MeasPdc
MeasDtf
MeasCorrelation
MeasCrossCorr
MeasOther	Unrecognised metric (name not preserved in token stream).
QuantBinBase	Bins occupy IDs [QuantBinBase .. QuantBinBase + numBins - 1].

Definition at line 62 of file inv_token.h.

Function Documentation

◆ applyInverseEpochs()

INVSHARED_EXPORT QList< InvSourceEstimate > INVLIB::applyInverseEpochs	(	const QList< Eigen::MatrixXd > &	epochs,
		const MNELIB::MNEInverseOperator &	inverse,
		float	lambda2,
		const QString &	method = "dSPM",
		float	tmin = 0.0f,
		float	tstep = 0.001f,
		bool	pickNormal = false )

Apply inverse operator to each epoch in a list.

For each epoch (data matrix), applies the minimum norm inverse and returns a list of source estimates. This is the equivalent of MNE-Python's mne.minimum_norm.apply_inverse_epochs().

Parameters

[in]	epochs	List of epoch data matrices (n_channels x n_times each).
[in]	inverse	Pre-computed inverse operator.
[in]	lambda2	Regularization parameter (1/SNR^2).
[in]	method	"MNE", "dSPM", or "sLORETA".
[in]	tmin	Start time of each epoch (seconds).
[in]	tstep	Time step (1/sfreq).
[in]	pickNormal	If true, keep only the normal component.

Returns: List of source estimates, one per epoch.

◆ applyInverseRaw()

INVSHARED_EXPORT InvSourceEstimate INVLIB::applyInverseRaw	(	const FIFFLIB::FiffRawData &	raw,
		const MNELIB::MNEInverseOperator &	inverse,
		float	lambda2,
		const QString &	method = "dSPM",
		int	from = -1,
		int	to = -1,
		bool	pickNormal = false )

Apply inverse operator to raw data in blocks.

Reads and processes the raw data in chunks, applying the inverse operator to produce a continuous source estimate. Equivalent of MNE-Python's mne.minimum_norm.apply_inverse_raw().

Parameters

[in]	raw	Raw data object.
[in]	inverse	Pre-computed inverse operator.
[in]	lambda2	Regularization parameter (1/SNR^2).
[in]	method	"MNE", "dSPM", or "sLORETA".
[in]	from	First sample to process (default: first_samp).
[in]	to	Last sample to process (default: last_samp).
[in]	pickNormal	If true, keep only the normal component.

Returns: Source estimate spanning the requested time range.

◆ buildDateTime()

const char * INVLIB::buildDateTime ( )

Returns build date and time.

Definition at line 29 of file inv_global.cpp.

◆ buildHash()

const char * INVLIB::buildHash ( )

Returns abbreviated build git hash.

Definition at line 33 of file inv_global.cpp.

◆ buildHashLong()

const char * INVLIB::buildHashLong ( )

Returns full build git hash.

Definition at line 37 of file inv_global.cpp.

◆ computeSourceBandPower()

QMap< QString, VectorXd > INVLIB::computeSourceBandPower	(	const InvSourceEstimate &	stc,
		float	sfreq,
		const QMap< QString, QPair< float, float > > &	bands )

Compute band power for source estimate.

Integrates source PSD within specified frequency bands.

Parameters

[in]	stc	Source estimate.
[in]	sfreq	Sampling frequency (Hz).
[in]	bands	Map of band name -> (fmin, fmax) pairs.

Returns: Map of band name -> power vector (n_sources).

Definition at line 329 of file inv_convenience.cpp.

◆ computeSourcePsd()

QPair< MatrixXd, VectorXd > INVLIB::computeSourcePsd	(	const InvSourceEstimate &	stc,
		float	sfreq,
		float	fmin = 0.0f,
		float	fmax = -1.0f,
		int	nFft = 0 )

Compute PSD for a source estimate using Welch's method.

Takes a source estimate (n_sources x n_times) and computes the power spectral density at each source vertex. Equivalent to MNE-Python's mne.minimum_norm.compute_source_psd().

Parameters

[in]	stc	Source estimate.
[in]	sfreq	Sampling frequency (Hz).
[in]	fmin	Minimum frequency of interest (Hz).
[in]	fmax	Maximum frequency of interest (Hz).
[in]	nFft	FFT length (0 = use data length).

Returns: Pair of (PSD matrix [n_sources x n_freqs], frequency vector).

Definition at line 273 of file inv_convenience.cpp.

◆ computeWhitener()

QPair< MatrixXd, int > INVLIB::computeWhitener	(	const FIFFLIB::FiffCov &	noiseCov,
		int	rank = 0 )

Compute whitening matrix from a noise covariance.

Returns a whitening matrix W such that W * data has identity covariance. Matches MNE-Python's mne.cov.compute_whitener().

Parameters

[in]	noiseCov	Noise covariance matrix.
[in]	rank	Desired rank (0 = auto from eigenvalues).

Returns: Pair of (whitener matrix, effective rank).

Definition at line 217 of file inv_convenience.cpp.

◆ estimateSnr()

QPair< VectorXd, RowVectorXf > INVLIB::estimateSnr	(	const FIFFLIB::FiffEvoked &	evoked,
		const MNELIB::MNEInverseOperator &	inverse,
		const QString &	method = "dSPM" )

Estimate SNR from evoked data and inverse operator.

Computes source-space SNR estimate using the GFP (Global Field Power) of the evoked data and the noise normalization from the inverse operator.

Parameters

[in]	evoked	Evoked data.
[in]	inverse	Inverse operator.
[in]	method	"MNE", "dSPM", or "sLORETA".

Returns: Pair of (SNR time course, times vector).

Definition at line 185 of file inv_convenience.cpp.

◆ fromTokens()

INVSHARED_EXPORT InvSourceEstimate INVLIB::fromTokens ( const std::vector< InvToken > & tokens )

Reconstruct an InvSourceEstimate from a token sequence.

Parses a token stream previously produced by tokenize() and rebuilds the InvSourceEstimate fields (metadata, grid data, positions, couplings, focal dipoles, connectivity). Unknown or out-of-order tokens are silently skipped.

Parameters

[in] tokens The token sequence to decode.

Returns: The reconstructed source estimate.

See also: tokenize, InvToken

Definition at line 353 of file inv_source_estimate_token.cpp.

◆ tokenIds()

std::vector< int32_t > INVLIB::tokenIds ( const std::vector< InvToken > & tokens )

inline

Extract just the integer token IDs from a token sequence (discarding continuous values). Useful for feeding into a purely discrete embedding table.

Parameters

[in] tokens The token sequence.

Returns: Vector of int32_t token IDs.

Definition at line 224 of file inv_token.h.

◆ tokenize()

INVSHARED_EXPORT std::vector< InvToken > INVLIB::tokenize	(	const InvSourceEstimate &	estimate,
		const InvTokenizeOptions &	options = InvTokenizeOptions() )

Serialise an InvSourceEstimate into a flat token sequence.

Converts the full multimodal content of an InvSourceEstimate (grid amplitudes, positions, couplings, focal dipoles, connectivity matrices) into a linear sequence of InvToken elements. Each token carries a vocabulary ID and an optional continuous float value.

The options parameter controls which data layers are emitted and allows sub-sampling of dense grids to fit context-limited attention windows.

Parameters

[in]	estimate	The source estimate to tokenize.
[in]	options	Controls layer inclusion and sub-sampling (default: all layers, no sub-sampling).

Returns: A vector of InvToken representing the serialised estimate.

See also: fromTokens, InvTokenizeOptions, InvToken

Definition at line 198 of file inv_source_estimate_token.cpp.

◆ tokenValues()

std::vector< float > INVLIB::tokenValues ( const std::vector< InvToken > & tokens )

inline

Extract just the continuous values from a token sequence (discarding IDs). Useful as the real-valued branch in a hybrid discrete-continuous embedding.

Parameters

[in] tokens The token sequence.

Returns: Vector of float values.

Definition at line 240 of file inv_token.h.

Variable Documentation

◆ BIG_TIME

double INVLIB::BIG_TIME = 1e6

inlineconstexpr

Definition at line 59 of file inv_dipole_fit_settings.h.

Classes

Typedefs

Enumerations

Functions

Variables

Detailed Description

Typedef Documentation

◆ bdipEcd

◆ dipoleFitFuncs

Enumeration Type Documentation

◆ Accuracy

◆ BeamformerInversion

◆ BeamformerPickOri

◆ BeamformerWeightNorm

◆ InvEstimateMethod

◆ InvOrientationType

◆ InvSourceSpaceType

◆ InvTokenId

Function Documentation

◆ applyInverseEpochs()

◆ applyInverseRaw()

◆ buildDateTime()

◆ buildHash()

◆ buildHashLong()

◆ computeSourceBandPower()

◆ computeSourcePsd()

◆ computeWhitener()

◆ estimateSnr()

◆ fromTokens()

◆ tokenIds()

◆ tokenize()

◆ tokenValues()

Variable Documentation

◆ BIG_TIME