eelbrain.cwt_morlet

eelbrain.cwt_morlet(y, frequencies, use_fft=True, n_cycles=3.0, zero_mean=True, output='magnitude', decim=1)

Time frequency decomposition with Morlet wavelets (mne-python)

Parameters

• y (NDVar) – Input signal.

• frequencies (Union[Sequence[float], float]) – Frequencies of interest. For a scalar, the output will not contain a frequency dimension.

• use_fft (bool) – Compute convolution with FFT or temporal convolution.

• n_cycles (Union[float, Sequence[float]]) – Number of cycles. Fixed number or one per frequency.

• zero_mean (bool) – Make sure the wavelets are zero mean.

• output (Literal[‘complex’, ‘power’, ‘phase’, ‘magnitude’]) – Format of the data in the returned NDVar. Default is the complex wavelet transform.

• decim (int) – Decimate the time axis by this factor.

Returns

Time frequency decompositions.

Return type

tfr