Shared utilities (I/O helpers, spectral analysis, layout management, warp algorithms). More...

Classes
struct	AnnotateMusclParams
	Parameters for muscle artifact annotation. More...
struct	AnnotateAmplitudeParams
	Parameters for amplitude-based annotation. More...
struct	ArtifactDetectEcgParams
	ECG R-peak detection parameters (defined outside class to avoid Clang/GCC default-argument issues with nested structs). More...
struct	ArtifactDetectEogParams
	EOG blink / saccade detection parameters (defined outside class to avoid Clang/GCC default-argument issues with nested structs). More...
class	ArtifactDetect
	ECG and EOG physiological artifact event detection. More...
struct	BadChannelDetectParams
	Bad-channel detection parameters (defined outside class to avoid Clang/GCC default-argument issues with nested structs). More...
class	BadChannelDetect
	Automated detection of bad MEG/EEG channels using flat, variance, and correlation criteria. More...
struct	LofBadChannelParams
struct	BadChannelsMaxwellParams
	Parameters for SSS-based bad channel detection. More...
struct	BadChannelsMaxwellResult
	Result of SSS-based bad channel detection. More...
struct	BridgedElectrodeParams
struct	DerivationRule
	A single derivation rule mapping input channels (with weights) to one output channel. More...
class	ChannelDerivation
	Channel derivation and re-referencing utilities. More...
class	ConnectivityAec
	Amplitude Envelope Correlation connectivity. More...
class	CosineFilter
	Creates a cosine filter response in the frequency domain. More...
struct	CsdResult
	Result of a Cross-Spectral Density computation. More...
class	Csd
	Cross-Spectral Density (CSD) estimator. More...
struct	DpssResult
	Result of a DPSS taper computation. More...
class	Dpss
	Discrete Prolate Spheroidal Sequences (Slepian tapers). More...
class	EogRegression
	Remove EOG artifacts via linear regression. More...
struct	EpochExtractorParams
	Epoch extraction parameters (defined outside class to avoid Clang/GCC default-argument issues with nested structs). More...
class	EpochExtractor
	Segments continuous raw data into fixed-length epochs locked to events. More...
struct	InfomaxResult
class	ExtendedInfomax
struct	FilterChpiParams
	Parameters for cHPI notch filtering. More...
class	FilterIO
	Processes txt files which hold filter coefficients. More...
class	FilterParameter
	Named filter-design parameter descriptor holding a human-readable name and description (e.g. design method or filter type). More...
class	FilterKernel
	The FilterKernel class provides methods to create/design a FIR filter kernel. More...
struct	FineCalEntry
	Per-sensor fine calibration entry. More...
class	FineCalibration
	Fine calibration data for SSS. More...
class	FirFilter
	Discoverable façade over the FilterKernel FIR-filter engine. More...
struct	IcaResult
	Result of an ICA decomposition. More...
class	ICA
	Independent Component Analysis using the FastICA algorithm (deflationary, logcosh nonlinearity). More...
struct	IirBiquad
	Coefficients of one second-order IIR section (biquad). More...
class	IirFilter
	Butterworth IIR filter design and application using second-order sections. More...
struct	HeadPosEntry
	A head position entry (time, translation, rotation quaternion). More...
struct	MaxwellMoveCompParams
	Parameters for Maxwell movement compensation. More...
class	MaxwellMovementComp
	Maxwell movement compensation using SSS. More...
struct	MorletTfrResult
	Result of a Morlet TFR computation for one channel. More...
class	MorletTfr
	Complex Morlet wavelet time-frequency representation. More...
struct	MultitaperPsdResult
	Result of a multitaper PSD computation. More...
class	MultitaperPsd
	Multitaper power spectral density estimator using DPSS (Slepian) tapers. More...
struct	MultitaperTfrResult
	Result of a multitaper TFR computation. More...
class	MultitaperTfr
	Sliding-window multitaper time-frequency representation. More...
class	ParksMcClellan
	Parks-McClellan equiripple FIR filter design algorithm (Remez exchange). More...
struct	PeakFinderParams
class	PicardIca
	Independent Component Analysis using the Picard algorithm. More...
class	Resample
	Polyphase anti-aliased rational resampling for MEG/EEG data. More...
struct	SimulateStcParams
	Parameters for source time course simulation. More...
struct	SpectogramInputData
	Input parameters for short-time Fourier transform spectrogram computation. More...
class	Spectrogram
	Computes time-frequency spectrograms via short-time Fourier transform with configurable window and overlap. More...
struct	SSSParams
	Implements Signal Space Separation (SSS) and temporal SSS (tSSS) for MEG data. More...
class	SSS
struct	SurfaceLaplacianResult
	Result of a surface Laplacian (CSD) computation. More...
class	SurfaceLaplacian
	Surface Laplacian / Current Source Density (CSD) transformation. More...
struct	WelchPsdResult
	Result of a Welch PSD computation. More...
class	WelchPsd
	Welch's averaged-periodogram power spectral density estimator. More...
struct	XdawnResult
	Result of an xDAWN decomposition. More...
class	Xdawn
	Event-related response enhancement with xDAWN spatial filtering. More...
class	KMeans
	Lloyd-style K-means clustering with configurable metric, seeding and replicates. More...
class	Linalg
	Static Eigen-based linear-algebra helpers used across MATHLIB and the inverse solvers. More...
class	Numerics
	Static scalar/per-vector numerical helpers (GCD, log2, histograms, baseline rescaling). More...
class	SimplexAlgorithm
	Header-only Nelder–Mead simplex minimiser with templated cost and report functors. More...
struct	TaperedSpectraInputData
	Per-row input bundle for parallel multi-taper spectral estimation (data row, taper matrix, FFT length). More...
class	Spectral
	Static multi-taper spectra, PSD and CSD estimator for MEG/EEG time series. More...
struct	FitUser
	Cost-function workspace for Sphere::fit_sphere_simplex: holds the `nx3` point cloud and a verbose-report flag. More...
class	Sphere
	3-D sphere value type with algebraic and Nelder–Mead best-fit factories. More...
class	Warp
	Thin-plate-spline 3-D warp fitted from landmark correspondences. More...
class	CircularBuffer
	Thread-safe lock-free circular (ring) buffer for producer-consumer data exchange between threads. More...
class	ICommand
	The ICommand interface provides the base class of every command of the command design pattern. More...
class	MNELogger
	Custom Qt message handler that formats and routes qDebug/qWarning/qCritical output to file or console. More...
class	IObserver
	The IObserver interface provides the base class of every observer of the observer design pattern. More...
class	Subject
	The Subject class provides the base class of every subject of the observer design pattern. More...
class	IOUtils
	Eigen matrix I/O utilities. More...
class	LayoutLoader
	Reads ANT .elc electrode files and MNE .lout 2-D channel layouts into Qt/STL containers. More...
struct	fitUserRec
	Workspace for sphere-fitting used by the layout maker, holding 3-D point coordinates and fit parameters. More...
class	LayoutMaker
	Make layout files from given 3D points. More...
struct	ElectrodePosition
	Represents an electrode position in a montage. More...
class	StandardMontage
	Standard EEG montage with named electrode positions. More...
struct	DigitizedPoint
	A single digitised point captured during the alignment session. More...
class	AcquiredPoints
	In-memory store of all points captured during a session. More...
struct	FastrakSample
	One decoded sample from a Fastrak ASCII stream. More...
class	FastrakParser
	Streaming parser for Fastrak / FastSCAN ASCII records. More...
struct	PolhemusSerialConfig
	Settings used to open a real Polhemus serial connection. More...
class	PolhemusConnection
	Polhemus digitizer connection (mock + serial-port backends). More...
class	PolhemusCoregistration
	Head–device coregistration engine driven by a Polhemus Fastrak. More...
struct	PythonRunnerResult
	Script execution result container. More...
struct	PythonRunnerConfig
	Script execution configuration. More...
class	PythonRunner
	Python script launcher with logging and progress support. More...
class	PythonTestHelper
struct	ReportSection
	A section in the report (title + HTML content). More...
class	Report
	Simple HTML report builder for MEG/EEG analysis results. More...
class	SelectionIO
	Reader/writer for MNE .sel channel-selection files and Brainstorm .mon montage files. More...

Typedefs
typedef CircularBuffer< int >	CircularBuffer_int
typedef CircularBuffer< short >	CircularBuffer_short
typedef CircularBuffer< char >	CircularBuffer_char
typedef CircularBuffer< double >	CircularBuffer_double
typedef CircularBuffer< QPair< int, int > >	CircularBuffer_pair_int_int
typedef CircularBuffer< QPair< double, double > >	CircularBuffer_pair_double_double
typedef CircularBuffer< Eigen::MatrixXd >	CircularBuffer_Matrix_double
typedef CircularBuffer< Eigen::MatrixXf >	CircularBuffer_Matrix_float
using	fitUser = fitUserRec*
using	PythonLineCallback = std::function<void(int channel, const QString& line)>
using	PythonProgressCallback = std::function<void(float pct, const QString& msg)>

Enumerations
enum class	StimArtifactMode { Linear , Window }
	Mode for stimulus artifact repair. More...
enum class	KMeansDistance { SquaredEuclidean , CityBlock , Cosine , Correlation , Hamming }
	Distance metric for K-Means clustering. More...
enum class	KMeansStart { Sample , Uniform , Cluster }
	Initialization strategy for K-Means clustering. More...
enum class	KMeansEmptyAction { Error , Drop , Singleton }
	Action to take when a K-Means cluster becomes empty. More...
enum class	PointKind { Fiducial = 0 , Eeg , HeadShape }
	Logical category of a captured point. More...
enum class	FiducialId { LPA = 1 , NAS = 2 , RPA = 3 }
	Identifier for the three cardinal fiducials. More...

Functions
DSPSHARED_EXPORT FIFFLIB::FiffAnnotations	annotateMusclZscore (const Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, double sfreq, const AnnotateMusclParams &params=AnnotateMusclParams())
	Detect muscle artifacts via high-frequency z-score and annotate bad segments.
DSPSHARED_EXPORT FIFFLIB::FiffAnnotations	annotateAmplitude (const Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, double sfreq, const AnnotateAmplitudeParams &params=AnnotateAmplitudeParams())
	Annotate segments where amplitude exceeds thresholds or is too flat.
DSPSHARED_EXPORT QStringList	findBadChannelsLof (const Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, const LofBadChannelParams &params=LofBadChannelParams())
	Detect bad channels using Local Outlier Factor (LOF).
DSPSHARED_EXPORT Eigen::VectorXd	computeLofScores (const Eigen::MatrixXd &features, int k)
	Compute LOF scores for a feature matrix.
DSPSHARED_EXPORT BadChannelsMaxwellResult	findBadChannelsMaxwell (const Eigen::MatrixXd &matData, const FIFFLIB::FiffInfo &info, const BadChannelsMaxwellParams &params=BadChannelsMaxwellParams())
	Detect bad MEG channels using SSS reconstruction residuals.
DSPSHARED_EXPORT Eigen::MatrixXd	computeElectricalDistance (const Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info)
	Compute electrical distance matrix between EEG channels.
DSPSHARED_EXPORT QList< QPair< int, int > >	computeBridgedElectrodes (const Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, const BridgedElectrodeParams &params=BridgedElectrodeParams())
	Detect bridged EEG electrodes.
DSPSHARED_EXPORT void	setEegReference (Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, const QStringList &refChannels=QStringList(), bool projection=false)
	Re-reference EEG channels to average, specific channel(s), or REST.
DSPSHARED_EXPORT void	addReferenceChannels (Eigen::MatrixXd &data, FIFFLIB::FiffInfo &info, const QStringList &chNames)
	Add reference channel(s) back as zero-filled rows.
DSPSHARED_EXPORT void	setBipolarReference (Eigen::MatrixXd &data, FIFFLIB::FiffInfo &info, const QStringList &anodes, const QStringList &cathodes, bool dropOriginals=true)
	Create bipolar derivations from EEG channels.
DSPSHARED_EXPORT void	filterChpi (Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, double sfreq, const QVector< double > &hpiFreqs, const FilterChpiParams &params=FilterChpiParams())
	Remove cHPI excitation signals from MEG data by notch filtering.
DSPSHARED_EXPORT void	filterChpi (Eigen::MatrixXd &data, const FIFFLIB::FiffInfo &info, double sfreq, const FilterChpiParams &params=FilterChpiParams())
	Overload that attempts to extract cHPI frequencies from FiffInfo.
DSPSHARED_EXPORT QList< QPair< int, double > >	peakFinder (const Eigen::VectorXd &data, const PeakFinderParams &params=PeakFinderParams())
	Find peaks in a 1D signal.
DSPSHARED_EXPORT Eigen::VectorXd	peakProminences (const Eigen::VectorXd &data, const QList< int > &peakIndices)
	Compute prominence of each peak.
DSPSHARED_EXPORT INVLIB::InvSourceEstimate	simulateStc (const Eigen::VectorXi &activeVertices, const Eigen::VectorXi &allVertices, const SimulateStcParams &params=SimulateStcParams())
	Create a synthetic source time course.
DSPSHARED_EXPORT INVLIB::InvSourceEstimate	simulateStcFromWaveforms (const Eigen::MatrixXd &waveforms, const Eigen::VectorXi &activeVertices, const Eigen::VectorXi &allVertices, float tmin=0.0f, float tstep=0.001f)
	Create a synthetic source time course from custom waveforms.
DSPSHARED_EXPORT FIFFLIB::FiffEvoked	simulateEvoked (const MNELIB::MNEForwardSolution &fwd, const INVLIB::InvSourceEstimate &stc, const FIFFLIB::FiffInfo &info, const FIFFLIB::FiffCov &noiseCov, int nave=1, int seed=42)
	Simulate evoked data from a source estimate and forward model.
DSPSHARED_EXPORT FIFFLIB::FiffEvoked	simulateEvokedNoiseless (const MNELIB::MNEForwardSolution &fwd, const INVLIB::InvSourceEstimate &stc, const FIFFLIB::FiffInfo &info)
	Simulate evoked data without noise.
DSPSHARED_EXPORT Eigen::MatrixXd	makeSpharaProjector (const Eigen::MatrixXd &matBaseFct, const Eigen::VectorXi &vecIndices, int iOperatorDim, int iNBaseFct, int iSkip=0)
DSPSHARED_EXPORT void	fixStimArtifact (Eigen::MatrixXd &data, const Eigen::MatrixXi &events, double sfreq, int eventId=-1, double tmin=0.0, double tmax=0.01, StimArtifactMode mode=StimArtifactMode::Linear)
	Repair stimulus artifacts by interpolating or zeroing data around events.
constexpr auto	timeNowNow ()
constexpr auto	dateToday ()
constexpr auto	dateTimeNow ()
constexpr auto	gitHash ()
constexpr auto	gitHashLong ()
const char *	buildDateTime ()
const char *	buildHash ()
const char *	buildHashLong ()

Detailed Description

Shared utilities (I/O helpers, spectral analysis, layout management, warp algorithms).

Typedef Documentation

◆ CircularBuffer_char

typedef CircularBuffer<char> UTILSLIB::CircularBuffer_char

Defines CircularBuffer of char type.

Definition at line 296 of file circularbuffer.h.

◆ CircularBuffer_double

typedef CircularBuffer<double> UTILSLIB::CircularBuffer_double

Defines CircularBuffer of double type.

Definition at line 297 of file circularbuffer.h.

◆ CircularBuffer_int

typedef CircularBuffer<int> UTILSLIB::CircularBuffer_int

Defines CircularBuffer of integer type.

Definition at line 294 of file circularbuffer.h.

◆ CircularBuffer_Matrix_double

typedef CircularBuffer< Eigen::MatrixXd > UTILSLIB::CircularBuffer_Matrix_double

Defines CircularBuffer of Eigen::MatrixXd type.

Definition at line 300 of file circularbuffer.h.

◆ CircularBuffer_Matrix_float

typedef CircularBuffer< Eigen::MatrixXf > UTILSLIB::CircularBuffer_Matrix_float

Defines CircularBuffer of Eigen::MatrixXf type.

Definition at line 301 of file circularbuffer.h.

◆ CircularBuffer_pair_double_double

typedef CircularBuffer< QPair<double, double> > UTILSLIB::CircularBuffer_pair_double_double

Defines CircularBuffer of double Pair type.

Definition at line 299 of file circularbuffer.h.

◆ CircularBuffer_pair_int_int

typedef CircularBuffer< QPair<int, int> > UTILSLIB::CircularBuffer_pair_int_int

Defines CircularBuffer of integer Pair type.

Definition at line 298 of file circularbuffer.h.

◆ CircularBuffer_short

typedef CircularBuffer<short> UTILSLIB::CircularBuffer_short

Defines CircularBuffer of short type.

Definition at line 295 of file circularbuffer.h.

◆ fitUser

using UTILSLIB::fitUser = fitUserRec*

Definition at line 77 of file layoutmaker.h.

◆ PythonLineCallback

using UTILSLIB::PythonLineCallback = std::function<void(int channel, const QString& line)>

Line-level callback signature.

Parameters

channel	0 = stdout, 1 = stderr.
line	The text line (without trailing newline).

Definition at line 96 of file python_runner.h.

◆ PythonProgressCallback

using UTILSLIB::PythonProgressCallback = std::function<void(float pct, const QString& msg)>

Progress callback signature.

Parameters

pct	Progress percentage 0.0 – 100.0.
msg	Optional message accompanying the progress update.

Definition at line 105 of file python_runner.h.

Enumeration Type Documentation

◆ FiducialId

enum class UTILSLIB::FiducialId

strong

Identifier for the three cardinal fiducials.

Numerically aligned with the FIFF ident field used for cardinal points (1 = LPA, 2 = NAS, 3 = RPA).

Enumerator
LPA
NAS
RPA

Definition at line 64 of file acquired_points.h.

◆ KMeansDistance

enum class UTILSLIB::KMeansDistance

strong

Distance metric for K-Means clustering.

Enumerator
SquaredEuclidean	Squared Euclidean distance (default).
CityBlock	Manhattan / city-block distance.
Cosine	Cosine distance.
Correlation	Correlation distance.
Hamming	Hamming distance (binary data only).

Definition at line 76 of file kmeans.h.

◆ KMeansEmptyAction

enum class UTILSLIB::KMeansEmptyAction

strong

Action to take when a K-Means cluster becomes empty.

Enumerator
Error	Treat as an error (default).
Drop	Drop the empty cluster.
Singleton	Replace with the farthest point from its centroid.

Definition at line 94 of file kmeans.h.

◆ KMeansStart

enum class UTILSLIB::KMeansStart

strong

Initialization strategy for K-Means clustering.

Enumerator
Sample	Random sample of data points (default).
Uniform	Uniform random within data range.
Cluster	Sub-sample then cluster.

Definition at line 86 of file kmeans.h.

◆ PointKind

enum class UTILSLIB::PointKind

strong

Logical category of a captured point.

Maps onto the FIFF point-kind constants on export (FIFFV_POINT_CARDINAL / FIFFV_POINT_EEG / FIFFV_POINT_EXTRA).

Enumerator
Fiducial	Anatomical landmark (NAS / LPA / RPA).
Eeg	Named EEG electrode contact.
HeadShape	Free head-shape point (continuous mode).

Definition at line 51 of file acquired_points.h.

◆ StimArtifactMode

enum class UTILSLIB::StimArtifactMode

strong

Mode for stimulus artifact repair.

Enumerator
Linear	Linear interpolation across the artifact window.
Window	Zero-pad (set to zero) the artifact window.

Definition at line 42 of file stim_artifact.h.

Function Documentation

◆ addReferenceChannels()

DSPSHARED_EXPORT void UTILSLIB::addReferenceChannels	(	Eigen::MatrixXd &	data,
		FIFFLIB::FiffInfo &	info,
		const QStringList &	chNames )

Add reference channel(s) back as zero-filled rows.

When EEG data was recorded with a physical reference electrode, that channel is implicit (all zeros after re-referencing). This function adds it back explicitly so it can participate in average re-referencing or source localization.

Parameters

[in,out]	data	Data matrix. Rows are added at the end.
[in,out]	info	Measurement info. New EEG channels are appended.
[in]	chNames	Names of the reference channel(s) to add.

◆ annotateAmplitude()

DSPSHARED_EXPORT FIFFLIB::FiffAnnotations UTILSLIB::annotateAmplitude	(	const Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		double	sfreq,
		const AnnotateAmplitudeParams &	params = AnnotateAmplitudeParams() )

Annotate segments where amplitude exceeds thresholds or is too flat.

Scans each channel independently:

If any sample exceeds dPeakMax or falls below dPeakMin, that time point is annotated.
If peak-to-peak amplitude in a sliding window < dFlatMin, the window is annotated as "BAD_flat".

Parameters

[in]	data	Raw data matrix (n_channels × n_times).
[in]	info	Measurement info (for channel names).
[in]	sfreq	Sampling frequency in Hz.
[in]	params	Detection parameters.

Returns: FiffAnnotations with bad entries.

◆ annotateMusclZscore()

DSPSHARED_EXPORT FIFFLIB::FiffAnnotations UTILSLIB::annotateMusclZscore	(	const Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		double	sfreq,
		const AnnotateMusclParams &	params = AnnotateMusclParams() )

Detect muscle artifacts via high-frequency z-score and annotate bad segments.

Algorithm:

Bandpass filter data in muscle frequency band (default 110–140 Hz).
Compute Hilbert envelope (approximated via absolute value of filtered signal).
Compute z-score of the envelope across time for each MEG channel.
Average z-score across channels.
Threshold: mark time points where average z-score > threshold.
Merge adjacent annotations and apply minimum duration.

Parameters

[in]	data	Raw data matrix (n_channels × n_times).
[in]	info	Measurement info.
[in]	sfreq	Sampling frequency in Hz.
[in]	params	Detection parameters.

Returns: FiffAnnotations with "BAD_muscle" entries.

◆ buildDateTime()

const char * UTILSLIB::buildDateTime ( )

Returns build date and time.

Definition at line 32 of file utils_global.cpp.

◆ buildHash()

const char * UTILSLIB::buildHash ( )

Returns abbreviated build git hash.

Definition at line 36 of file utils_global.cpp.

◆ buildHashLong()

const char * UTILSLIB::buildHashLong ( )

Returns full build git hash.

Definition at line 40 of file utils_global.cpp.

◆ computeBridgedElectrodes()

DSPSHARED_EXPORT QList< QPair< int, int > > UTILSLIB::computeBridgedElectrodes	(	const Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		const BridgedElectrodeParams &	params = BridgedElectrodeParams() )

Detect bridged EEG electrodes.

Finds pairs of EEG channels whose electrical distance falls below the threshold, indicating a physical or gel bridge.

Parameters

[in]	data	Data matrix (n_channels x n_times).
[in]	info	FiffInfo with channel types.
[in]	params	Detection parameters.

Returns: List of bridged electrode pairs as (channel_index_1, channel_index_2) using indices into info.chs.

◆ computeElectricalDistance()

DSPSHARED_EXPORT Eigen::MatrixXd UTILSLIB::computeElectricalDistance	(	const Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info )

Compute electrical distance matrix between EEG channels.

Electrical distance is defined as the standard deviation of the difference signal between two channels, normalised by the geometric mean of their individual standard deviations. Bridged electrodes will have near-zero electrical distance.

Parameters

[in]	data	Data matrix (n_channels x n_times).
[in]	info	FiffInfo with channel types.

Returns: Electrical distance matrix (n_eeg x n_eeg), with EEG channel indices stored in the order they appear in info.

◆ computeLofScores()

DSPSHARED_EXPORT Eigen::VectorXd UTILSLIB::computeLofScores	(	const Eigen::MatrixXd &	features,
		int	k )

Compute LOF scores for a feature matrix.

Pure algorithmic LOF implementation operating on feature vectors.

Parameters

[in]	features	Feature matrix (n_points x n_features).
[in]	k	Number of neighbours.

Returns: LOF score for each point (n_points x 1). Values > 1 indicate outliers.

◆ dateTimeNow()

auto UTILSLIB::dateTimeNow ( )

constexpr

Returns build date and time (time preprocessor was run). Must be called in compiled function to return correctly.

Definition at line 61 of file buildinfo.h.

◆ dateToday()

auto UTILSLIB::dateToday ( )

constexpr

Returns build date (time preprocessor was run). Must be called in compiled function to return correctly.

Definition at line 51 of file buildinfo.h.

◆ filterChpi() [1/2]

DSPSHARED_EXPORT void UTILSLIB::filterChpi	(	Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		double	sfreq,
		const FilterChpiParams &	params = FilterChpiParams() )

Overload that attempts to extract cHPI frequencies from FiffInfo.

Tries to read HPI coil frequencies from the FiffInfo metadata. Because the FiffInfo HPI frequency storage varies across file versions, this overload may not always succeed. If frequencies cannot be determined, a warning is logged and no filtering is applied. In that case, use the explicit-frequency overload instead.

Parameters

[in,out]	data	Data matrix (n_channels x n_times). Modified in-place.
[in]	info	Measurement info.
[in]	sfreq	Sampling frequency in Hz.
[in]	params	Filtering parameters.

◆ filterChpi() [2/2]

DSPSHARED_EXPORT void UTILSLIB::filterChpi	(	Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		double	sfreq,
		const QVector< double > &	hpiFreqs,
		const FilterChpiParams &	params = FilterChpiParams() )

Remove cHPI excitation signals from MEG data by notch filtering.

Applies a zero-phase Butterworth band-stop (notch) filter at each specified cHPI frequency. Only MEG channels are filtered by default.

Parameters

[in,out]	data	Data matrix (n_channels x n_times). Modified in-place.
[in]	info	Measurement info (used to identify MEG channels if bMegOnly is true).
[in]	sfreq	Sampling frequency in Hz.
[in]	hpiFreqs	List of cHPI excitation frequencies in Hz. Typical Elekta/MEGIN system: {83, 143, 203, 263, 293}.
[in]	params	Filtering parameters.

◆ findBadChannelsLof()

DSPSHARED_EXPORT QStringList UTILSLIB::findBadChannelsLof	(	const Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		const LofBadChannelParams &	params = LofBadChannelParams() )

Detect bad channels using Local Outlier Factor (LOF).

Computes features for each channel (standard deviation, kurtosis, max absolute amplitude) and applies the LOF algorithm to identify outlier channels. LOF compares the local density of a point's neighbourhood to the densities of its neighbours.

Parameters

[in]	data	Data matrix (n_channels x n_times).
[in]	info	FiffInfo with channel types.
[in]	params	LOF parameters.

Returns: List of bad channel names.

◆ findBadChannelsMaxwell()

DSPSHARED_EXPORT BadChannelsMaxwellResult UTILSLIB::findBadChannelsMaxwell	(	const Eigen::MatrixXd &	matData,
		const FIFFLIB::FiffInfo &	info,
		const BadChannelsMaxwellParams &	params = BadChannelsMaxwellParams() )

Detect bad MEG channels using SSS reconstruction residuals.

Computes the SSS reconstruction of the data, then flags channels whose residual (difference between original and reconstructed) is anomalously large relative to the population of channels.

Parameters

[in]	matData	MEG data (n_channels x n_times). Should include all channels (MEG and non-MEG).
[in]	info	Measurement info with channel positions.
[in]	params	Detection parameters.

Returns: Detection result with bad channel names, indices, residuals, z-scores.

◆ fixStimArtifact()

DSPSHARED_EXPORT void UTILSLIB::fixStimArtifact	(	Eigen::MatrixXd &	data,
		const Eigen::MatrixXi &	events,
		double	sfreq,
		int	eventId = -1,
		double	tmin = 0.0,
		double	tmax = 0.01,
		StimArtifactMode	mode = StimArtifactMode::Linear )

Repair stimulus artifacts by interpolating or zeroing data around events.

For each event sample, the data in the window [event + tmin_samples, event + tmax_samples] is either linearly interpolated from the boundary values or set to zero.

Parameters

[in,out]	data	Data matrix (n_channels x n_times). Modified in-place.
[in]	events	Event matrix (Nx3: [sample, before, after]). Only the sample column (col 0) is used to locate artifact windows.
[in]	sfreq	Sampling frequency in Hz.
[in]	eventId	If >= 0, only process events where column 2 (after) matches this value. If < 0, process all events. Default: -1.
[in]	tmin	Start of artifact window in seconds relative to event (negative = before event). Default: 0.0 (event onset).
[in]	tmax	End of artifact window in seconds relative to event. Default: 0.01 (10 ms after event).
[in]	mode	Repair mode (Linear interpolation or zero-padding). Default: StimArtifactMode::Linear.

◆ gitHash()

auto UTILSLIB::gitHash ( )

constexpr

Returns short version of the hash of the current git commit

Definition at line 70 of file buildinfo.h.

◆ gitHashLong()

auto UTILSLIB::gitHashLong ( )

constexpr

Returns entire hash of the current git commit

Definition at line 83 of file buildinfo.h.

◆ makeSpharaProjector()

DSPSHARED_EXPORT Eigen::MatrixXd UTILSLIB::makeSpharaProjector	(	const Eigen::MatrixXd &	matBaseFct,
		const Eigen::VectorXi &	vecIndices,
		int	iOperatorDim,
		int	iNBaseFct,
		int	iSkip = 0 )

Constructs a SPHARA operator.

Parameters

[in]	matBaseFct	The SPHARA basis functions.
[in]	vecIndices	The indices of the positions in the final oeprator which are to be filled with the basis functions weights (i.e. these indices could respond to the indices of gradioemteres in a VectorView system).
[in]	iOperatorDim	The dimensions of the final SPHARA operator. Make sure that these correspond to the dimensions of the data matrix you want tol multiply with the SPHARA operator.
[in]	iNBaseFct	The number of SPHARA basis functions to take.
[in]	iSkip	The value to skip when reading the vecIndices variabel. I.e. use this when dealing with VectorView triplets, which include two gradiometers.

Returns: Returns the final SPHARA operator with dimensions (iOperatorDim,iOperatorDim).

◆ peakFinder()

DSPSHARED_EXPORT QList< QPair< int, double > > UTILSLIB::peakFinder	(	const Eigen::VectorXd &	data,
		const PeakFinderParams &	params = PeakFinderParams() )

Find peaks in a 1D signal.

A peak is a sample that is strictly greater than both its neighbours. Additional filtering by height, distance, and prominence can be applied.

Parameters

[in]	data	1D signal (row vector or VectorXd).
[in]	params	Peak detection parameters.

Returns: List of (peak_index, peak_value) pairs, sorted by index.

◆ peakProminences()

DSPSHARED_EXPORT Eigen::VectorXd UTILSLIB::peakProminences	(	const Eigen::VectorXd &	data,
		const QList< int > &	peakIndices )

Compute prominence of each peak.

Prominence is the vertical distance from a peak to the highest valley on either side before reaching a higher peak.

Parameters

[in]	data	1D signal.
[in]	peakIndices	Indices of detected peaks.

Returns: Prominence value for each peak.

◆ setBipolarReference()

DSPSHARED_EXPORT void UTILSLIB::setBipolarReference	(	Eigen::MatrixXd &	data,
		FIFFLIB::FiffInfo &	info,
		const QStringList &	anodes,
		const QStringList &	cathodes,
		bool	dropOriginals = true )

Create bipolar derivations from EEG channels.

Creates new bipolar channels by subtracting cathode from anode for each pair. The original channels are replaced with the bipolar derivations.

Parameters

[in,out]	data	Data matrix. Replaced with bipolar derivation rows.
[in,out]	info	Measurement info. Updated with new bipolar channel info.
[in]	anodes	List of anode channel names.
[in]	cathodes	List of cathode channel names (same length as anodes).
[in]	dropOriginals	If true, remove the original anode/cathode channels from the output (default: true).

◆ setEegReference()

DSPSHARED_EXPORT void UTILSLIB::setEegReference	(	Eigen::MatrixXd &	data,
		const FIFFLIB::FiffInfo &	info,
		const QStringList &	refChannels = QStringList(),
		bool	projection = false )

Re-reference EEG channels to average, specific channel(s), or REST.

Only modifies rows corresponding to EEG channels (kind == FIFFV_EEG_CH). Non-EEG channels are left untouched.

Parameters

[in,out]	data	Data matrix (n_channels x n_times). Modified in-place.
[in]	info	Measurement info (used to identify EEG channels).
[in]	refChannels	Reference channel name(s). Empty or "average" -> average reference (mean of all good EEG channels). Single channel name -> re-reference to that channel. Multiple channel names -> re-reference to mean of those channels.
[in]	projection	If true, add an SSP projector for average reference instead of modifying data. (default: false — modify data directly)

◆ simulateEvoked()

FiffEvoked UTILSLIB::simulateEvoked	(	const MNELIB::MNEForwardSolution &	fwd,
		const INVLIB::InvSourceEstimate &	stc,
		const FIFFLIB::FiffInfo &	info,
		const FIFFLIB::FiffCov &	noiseCov,
		int	nave = 1,
		int	seed = 42 )

Simulate evoked data from a source estimate and forward model.

Projects the source estimate through the forward model to generate sensor-space data, optionally adding noise from a noise covariance.

Equivalent to MNE-Python's mne.simulation.simulate_evoked().

Parameters

[in]	fwd	Forward solution (gain matrix).
[in]	stc	Source time course.
[in]	info	Measurement info (for output channel info).
[in]	noiseCov	Noise covariance for additive noise (optional).
[in]	nave	Number of averages (noise scaled by 1/sqrt(nave)).
[in]	seed	Random seed for noise generation.

Returns: Simulated evoked data.

Definition at line 146 of file simulate.cpp.

◆ simulateEvokedNoiseless()

FiffEvoked UTILSLIB::simulateEvokedNoiseless	(	const MNELIB::MNEForwardSolution &	fwd,
		const INVLIB::InvSourceEstimate &	stc,
		const FIFFLIB::FiffInfo &	info )

Simulate evoked data without noise.

Projects source estimate through forward model (no noise added).

Parameters

[in]	fwd	Forward solution.
[in]	stc	Source time course.
[in]	info	Measurement info.

Returns: Simulated noiseless evoked data.

Definition at line 197 of file simulate.cpp.

◆ simulateStc()

DSPSHARED_EXPORT INVLIB::InvSourceEstimate UTILSLIB::simulateStc	(	const Eigen::VectorXi &	activeVertices,
		const Eigen::VectorXi &	allVertices,
		const SimulateStcParams &	params = SimulateStcParams() )

Create a synthetic source time course.

Generates an InvSourceEstimate with Gaussian-envelope waveforms at specified source vertices. Each active source has a Gaussian temporal profile centered at different times.

Parameters

[in]	activeVertices	Vertex indices for active sources.
[in]	allVertices	Full vertex index vector for the source space.
[in]	params	Simulation parameters (sfreq, tmin, duration).

Returns: Simulated source estimate.

◆ simulateStcFromWaveforms()

DSPSHARED_EXPORT INVLIB::InvSourceEstimate UTILSLIB::simulateStcFromWaveforms	(	const Eigen::MatrixXd &	waveforms,
		const Eigen::VectorXi &	activeVertices,
		const Eigen::VectorXi &	allVertices,
		float	tmin = 0.0f,
		float	tstep = 0.001f )

Create a synthetic source time course from custom waveforms.

Parameters

[in]	waveforms	Waveform data (n_active_sources x n_times).
[in]	activeVertices	Vertex indices for the active sources.
[in]	allVertices	Full vertex index vector.
[in]	tmin	Start time (s).
[in]	tstep	Time step (s).

Returns: Simulated source estimate with zeros at inactive vertices.

◆ timeNowNow()

auto UTILSLIB::timeNowNow ( )

constexpr

Returns build time (time preprocessor was run). Must be called in compiled function to return correctly.

Definition at line 42 of file buildinfo.h.

Classes

Typedefs

Enumerations

Functions

Detailed Description

Typedef Documentation

◆ CircularBuffer_char

◆ CircularBuffer_double

◆ CircularBuffer_int

◆ CircularBuffer_Matrix_double

◆ CircularBuffer_Matrix_float

◆ CircularBuffer_pair_double_double

◆ CircularBuffer_pair_int_int

◆ CircularBuffer_short

◆ fitUser

◆ PythonLineCallback

◆ PythonProgressCallback

Enumeration Type Documentation

◆ FiducialId

◆ KMeansDistance

◆ KMeansEmptyAction

◆ KMeansStart

◆ PointKind

◆ StimArtifactMode

Function Documentation

◆ addReferenceChannels()

◆ annotateAmplitude()

◆ annotateMusclZscore()

◆ buildDateTime()

◆ buildHash()

◆ buildHashLong()

◆ computeBridgedElectrodes()

◆ computeElectricalDistance()

◆ computeLofScores()

◆ dateTimeNow()

◆ dateToday()

◆ filterChpi() [1/2]

◆ filterChpi() [2/2]

◆ findBadChannelsLof()

◆ findBadChannelsMaxwell()

◆ fixStimArtifact()

◆ gitHash()

◆ gitHashLong()

◆ makeSpharaProjector()

◆ peakFinder()

◆ peakProminences()

◆ setBipolarReference()

◆ setEegReference()

◆ simulateEvoked()

◆ simulateEvokedNoiseless()

◆ simulateStc()

◆ simulateStcFromWaveforms()

◆ timeNowNow()