mne.time_frequency.tfr_morlet

mne.time_frequency.tfr_morlet(inst, freqs, n_cycles, use_fft=False, return_itc=True, decim=1, n_jobs=1, picks=None, zero_mean=True, average=True, output='power', verbose=None)[source]

Compute Time-Frequency Representation (TFR) using Morlet wavelets.

Parameters
instEpochs | Evoked

The epochs or evoked object.

freqsndarray, shape (n_freqs,)

The frequencies in Hz.

n_cyclesfloat | ndarray, shape (n_freqs,)

The number of cycles globally or for each frequency.

use_fftbool, default False

The fft based convolution or not.

return_itcbool, default True

Return inter-trial coherence (ITC) as well as averaged power. Must be False for evoked data.

decimint | slice, default 1

To reduce memory usage, decimation factor after time-frequency decomposition. If int, returns tfr[…, ::decim]. If slice, returns tfr[…, decim].

Note

Decimation may create aliasing artifacts.

n_jobsint, default 1

The number of jobs to run in parallel.

picksarray_like of int | None, default None

The indices of the channels to decompose. If None, all available good data channels are decomposed.

zero_meanbool, default True

Make sure the wavelet has a mean of zero.

New in version 0.13.0.

averagebool, default True

If True average across Epochs.

New in version 0.13.0.

outputstr

Can be “power” (default) or “complex”. If “complex”, then average must be False.

New in version 0.15.0.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more).

Returns
powerAverageTFR | EpochsTFR

The averaged or single-trial power.

itcAverageTFR | EpochsTFR

The inter-trial coherence (ITC). Only returned if return_itc is True.