Operation reference

Every step in a pipeline names one of these operations. Parameters go in the step’s params table; anything not listed is rejected, and missing parameters take the defaults shown. modewise ops --json gives the same information as JSON Schema, for tools and agents.

ceemdan

CEEMDAN, improved form: noise-assisted EMD whose modes sum to the signal (docs/emd.md).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
count	integer	—	s_number: consecutive siftings with extrema and zero crossings within one (2 by default).
epsilon	number	0.2	ceemdan only: noise scale ε.
max_imfs	integer	—	Stop after this many IMFs (the rest is the residual); all by default, at most ⌊log₂ n⌋ − 1 for eemd.
sd	number	0.05	rilling: the envelope mean relative to the mode amplitude must stay below this on all but a fraction tol of samples.
sd2	number	0.5	rilling: the same ratio must stay below this everywhere (0.5; memd 0.75).
seed	integer	0	eemd and ceemdan: noise seed.
siftings	integer	—	fixed: siftings per IMF (10 by default).
stop	rilling, s_number, fixed	"rilling"	When sifting stops: rilling (thresholds sd, sd2, tol), s_number (count) or fixed (siftings); fixed for eemd, rilling otherwise.
tol	number	0.05	rilling: the fraction of samples allowed above sd (0.05; memd 0.075).
trials	integer	100	eemd and ceemdan: noise realisations.

cwt

Morlet continuous wavelet transform power on log-spaced frequencies, with a cone of influence (docs/time-frequency.md).

• Inputs: signal (series)

• Outputs: power (time_frequency)

Parameter	Type	Default	Meaning
f_max	number	required	Highest frequency in Hz, at most Nyquist.
f_min	number	required	Lowest frequency in Hz, above 0. The transform analyses the geometric centres of log-spaced bins.
n_bins	integer	required	Number of log-spaced frequencies.
omega0	number	6.0	Morlet wavenumber (Torrence and Compo use 6).
rectify	boolean	false	Divide power by scale to remove the bias towards low frequencies (Liu et al. 2007).

eemd

Ensemble EMD: the mean of EMDs of the signal plus seeded white noise (docs/emd.md).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
count	integer	—	s_number: consecutive siftings with extrema and zero crossings within one (2 by default).
max_imfs	integer	—	Stop after this many IMFs (the rest is the residual); all by default, at most ⌊log₂ n⌋ − 1 for eemd.
noise_sd	number	0.2	eemd only: noise SD relative to the signal’s.
sd	number	—	rilling: the envelope mean relative to the mode amplitude must stay below this on all but a fraction tol of samples.
sd2	number	—	rilling: the same ratio must stay below this everywhere (0.5; memd 0.75).
seed	integer	0	eemd and ceemdan: noise seed.
siftings	integer	10	fixed: siftings per IMF (10 by default).
stop	rilling, s_number, fixed	"fixed"	When sifting stops: rilling (thresholds sd, sd2, tol), s_number (count) or fixed (siftings); fixed for eemd, rilling otherwise.
tol	number	—	rilling: the fraction of samples allowed above sd (0.05; memd 0.075).
trials	integer	100	eemd and ceemdan: noise realisations.

emd

Empirical mode decomposition of each channel on its own (docs/emd.md).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
count	integer	—	s_number: consecutive siftings with extrema and zero crossings within one (2 by default).
max_imfs	integer	—	Stop after this many IMFs (the rest is the residual); all by default, at most ⌊log₂ n⌋ − 1 for eemd.
sd	number	0.05	rilling: the envelope mean relative to the mode amplitude must stay below this on all but a fraction tol of samples.
sd2	number	0.5	rilling: the same ratio must stay below this everywhere (0.5; memd 0.75).
siftings	integer	—	fixed: siftings per IMF (10 by default).
stop	rilling, s_number, fixed	"rilling"	When sifting stops: rilling (thresholds sd, sd2, tol), s_number (count) or fixed (siftings); fixed for eemd, rilling otherwise.
tol	number	0.05	rilling: the fraction of samples allowed above sd (0.05; memd 0.075).

epoch

Cuts windows around events out of a full-run series, decomposition, instantaneous attributes or time–frequency map, with an explicit haemodynamic lag (docs/epochs.md).

• Inputs: data (series or decomposition or instantaneous or time_frequency), events (events)

• Outputs: epochs (epochs)

Parameter	Type	Default	Meaning
lag_s	number	required	Required: shift added to event times (haemodynamic delay in fMRI; 0 for EEG).
conditions	list of string	—	Keep only these event labels; all by default.
merge_gap_s	number	—	Merge consecutive same-label events (trials) into blocks when gaps are at most this long.
min_cycles	number	1.0	A mode or frequency is resolvable in an epoch when frequency × epoch length ≥ this, and, for maps with a cone of influence, the whole epoch is outside it (docs/epochs.md).
window	duration or table (tmax_s, tmin_s)	"duration"	"duration" uses each event’s own length (blocks); { tmin_s = -0.2, tmax_s = 0.5 } uses a fixed window around each onset (trials).

functional_connectivity

Functional connectivity per component (and per epoch): Pearson correlation or phase locking value (docs/connectivity.md).

• Inputs: data (series or decomposition or epochs)

• Outputs: matrices (functional_connectivity)

Parameter	Type	Default	Meaning
measure	pearson, plv	required	pearson (correlation) or plv (phase locking value).
fisher_z	boolean	false	Return atanh(r) (pearson only); the diagonal becomes NaN.

hilbert

Instantaneous amplitude and frequency of every mode from its analytic signal (docs/time-frequency.md).

• Inputs: modes (decomposition)

• Outputs: attributes (instantaneous)

Parameter	Type	Default	Meaning
padding	mirror, none	"mirror"	Extend the signal before the FFT (mirror); none matches scipy.signal.hilbert.

hilbert_spectrum

Hilbert spectrum: instantaneous amplitude or power of the modes binned on a frequency grid over time (docs/time-frequency.md).

• Inputs: attributes (instantaneous)

• Outputs: power (time_frequency)

Parameter	Type	Default	Meaning
f_max	number	required	Highest edge of the frequency grid in Hz.
f_min	number	required	Lowest edge of the frequency grid in Hz (above 0 for a log grid).
n_bins	integer	required	Number of bins, each [low, high).
scale	linear, log	"linear"	linear or log bins (log bins report geometric centres).
weight	power, amplitude	"power"	power (amplitude²) or amplitude.

memd

Multivariate EMD: the same IMFs in every channel, from projections on many directions (docs/emd.md).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
count	integer	—	s_number: consecutive siftings with extrema and zero crossings within one (2 by default).
max_imfs	integer	—	Stop after this many IMFs (the rest is the residual); all by default, at most ⌊log₂ n⌋ − 1 for eemd.
num_directions	integer	64	memd only: projection directions; use at least twice the channels.
sd	number	0.075	rilling: the envelope mean relative to the mode amplitude must stay below this on all but a fraction tol of samples.
sd2	number	0.75	rilling: the same ratio must stay below this everywhere (0.5; memd 0.75).
siftings	integer	—	fixed: siftings per IMF (10 by default).
stop	rilling, s_number, fixed	"rilling"	When sifting stops: rilling (thresholds sd, sd2, tol), s_number (count) or fixed (siftings); fixed for eemd, rilling otherwise.
tol	number	0.075	rilling: the fraction of samples allowed above sd (0.05; memd 0.075).

modwt_mra

MODWT multiresolution analysis: octave-band details and a smooth that sum to each channel (docs/wavelets.md).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
boundary	periodic, reflection	"periodic"	periodic (as the MODWT is defined) or reflection (fewer edge effects for non-periodic series).
levels	integer	—	Deepest level; by default the deepest whose filter fits the series.
wavelet	string	"sym4"	sym4 is MATLAB’s default and Percival and Walden’s LA(8).

mvmd

Multivariate variational mode decomposition: K modes shared by all channels (Rehman and Aftab 2019).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
alpha	number	required	Bandwidth penalty; larger means narrower modes.
num_modes	integer	required	Number of modes K.
init	zero, linear, exponential, uniform	"zero"	Starting centre frequencies: zero, linear (evenly over [0, 0.5], as Dmocrito/mvmd), exponential, or uniform ((0.5/K)·k, as the original MATLAB VMD and MVMD codes and vmdpy).
max_iterations	integer	500	Iteration cap.
tau	number	0.01	Dual ascent step; 0 lets noise stay out of the modes.
tolerance	number	0.001	Stop when the mean squared update falls below this.

na_mvmd

Noise-assisted MVMD: MVMD with white-noise channels appended, less sensitive to K (Zisou et al. 2021).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
alpha	number	required	Bandwidth penalty; larger means narrower modes.
num_modes	integer	required	Number of modes K.
init	zero, linear, exponential, uniform	"zero"	Starting centre frequencies: zero, linear (evenly over [0, 0.5], as Dmocrito/mvmd), exponential, or uniform ((0.5/K)·k, as the original MATLAB VMD and MVMD codes and vmdpy).
max_iterations	integer	500	Iteration cap.
noise_channels	integer	1	na_mvmd only: white-noise channels appended before decomposing.
noise_sd	number	0.8	na_mvmd only: noise SD relative to the unit-SD signal channels.
seed	integer	0	na_mvmd only: seed for the noise.
tau	number	0.01	Dual ascent step; 0 lets noise stay out of the modes.
tolerance	number	0.001	Stop when the mean squared update falls below this.

reconstruct

Sums chosen modes of a decomposition back into a series, for example to keep one band.

• Inputs: modes (decomposition)

• Outputs: signal (series)

Parameter	Type	Default	Meaning
modes	list of integer	required	Mode indices to sum, counted from the lowest frequency.

region_average

Averages channels by region, hemisphere or tag (functional connectivity in Fisher z) (docs/regions.md).

• Inputs: data (series or decomposition or time_frequency or epochs or functional_connectivity), channels (channels)

• Outputs: averaged (series or decomposition or time_frequency or epochs or functional_connectivity)

Parameter	Type	Default	Meaning
by	region, hemisphere, tag	required	Group channels by region, hemisphere or tag.
split_hemispheres	boolean	false	Keep left and right apart: PFCm_left, PFCm_right.
tag	string	—	Tag key to group by when by = "tag", for example yeo17.

select

Keeps the channels whose name, region, hemisphere or tags match the rules (docs/regions.md).

• Inputs: data (series or decomposition or instantaneous or time_frequency or epochs or functional_connectivity or loadings or channels), channels (channels)

• Outputs: selected (series or decomposition or instantaneous or time_frequency or epochs or functional_connectivity or loadings or channels)

Parameter	Type	Default	Meaning
rules	list of table (hemisphere, name, region, tags)	required	Channels matching any rule are kept. A rule has any of name, region, hemisphere (left/right) and tags (a table); all of them must match. Text matches exactly, or with * wildcards.

spectrum

Power spectral density per channel as one frame: a periodogram, or Welch’s method with segments (as scipy.signal).

• Inputs: signal (series)

• Outputs: power (time_frequency)

Parameter	Type	Default	Meaning
detrend	none, constant, linear	"constant"	Per segment: none, constant (mean) or linear.
overlap_s	number	—	Overlap between segments in seconds; half a segment when absent.
segment_s	number	—	Welch segment length in seconds; the whole run when absent.
window	boxcar, hann	"boxcar"	boxcar or hann (periodic).

stft

Short-time Fourier transform power with a periodic Hann window.

• Inputs: signal (series)

• Outputs: power (time_frequency)

Parameter	Type	Default	Meaning
hop	integer	required	Step between frames in samples.
window_len	integer	required	Window length in samples (periodic Hann).

vlmd

Variational latent mode decomposition: modes of a few latent signals and sparse channel loadings (docs/vlmd.md).

• Inputs: signal (series)

• Outputs: modes (decomposition), latent_modes (decomposition), loadings (loadings)

Parameter	Type	Default	Meaning
num_modes	integer	required	Number of modes K.
alpha	number	100.0	Bandwidth penalty; larger means narrower modes.
max_iterations	integer	1000	Iteration cap.
num_latents	integer	—	Number of latent components L, at most the number of channels; one per channel by default.
reg_lambda	number	0.01	Sparsity of the loadings, on the reference code’s scale.
reg_rho	number	1.0	ADMM penalty.
tau	number	0.9	Dual step, in [0, 1].
tolerance	number	0.001	Stop when the summed squared relative change of the centre frequencies falls to this.

vmd

Variational mode decomposition of each channel on its own (Dragomiretskiy and Zosso 2014).

• Inputs: signal (series)

• Outputs: modes (decomposition)

Parameter	Type	Default	Meaning
alpha	number	required	Bandwidth penalty; larger means narrower modes.
num_modes	integer	required	Number of modes K.
init	zero, linear, exponential, uniform	"zero"	Starting centre frequencies: zero, linear (evenly over [0, 0.5], as Dmocrito/mvmd), exponential, or uniform ((0.5/K)·k, as the original MATLAB VMD and MVMD codes and vmdpy).
max_iterations	integer	500	Iteration cap.
tau	number	0.01	Dual ascent step; 0 lets noise stay out of the modes.
tolerance	number	0.001	Stop when the mean squared update falls below this.