| Parameters: |
- inst : Epochs | Evoked
The epochs or evoked object.
- freqs : ndarray, shape (n_freqs,)
The frequencies in Hz.
- n_cycles : float | ndarray, shape (n_freqs,)
The number of cycles globally or for each frequency.
The time-window length is thus T = n_cycles / freq.
- time_bandwidth : float, (optional), defaults to 4.0 (3 good tapers).
Time x (Full) Bandwidth product. Should be >= 2.0.
Choose this along with n_cycles to get desired frequency resolution.
The number of good tapers (least leakage from far away frequencies)
is chosen automatically based on this to floor(time_bandwidth - 1).
E.g., With freq = 20 Hz and n_cycles = 10, we get time = 0.5 s.
If time_bandwidth = 4., then frequency smoothing is (4 / time) = 8 Hz.
- use_fft : bool, defaults to True
The fft based convolution or not.
- return_itc : bool, defaults to True
Return inter-trial coherence (ITC) as well as averaged (or
single-trial) power.
- decim : int | slice, defaults to 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_jobs : int, defaults to 1
The number of jobs to run in parallel.
- picks : array-like of int | None, defaults to None
The indices of the channels to decompose. If None, all available
good data channels are decomposed.
- average : bool, defaults to True
If True average across Epochs.
- verbose : bool, str, int, or None, defaults to None
If not None, override default verbose level (see mne.verbose()
and Logging documentation for more).
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