mne.time_frequency.tfr_array_stockwell¶

mne.time_frequency.tfr_array_stockwell(data, sfreq, fmin=None, fmax=None, n_fft=None, width=1.0, decim=1, return_itc=False, n_jobs=1)[source]¶

Compute power and intertrial coherence using Stockwell (S) transform.

See [1], [2], [3], [4] for more information.

Parameters:

Parameters:	data : ndarray The signal to transform. Any dimensionality supported as long as the last dimension is time. sfreq : float The sampling frequency. fmin : None, float The minimum frequency to include. If None defaults to the minimum fft frequency greater than zero. fmax : None, float The maximum frequency to include. If None defaults to the maximum fft. n_fft : int \| None The length of the windows used for FFT. If None, it defaults to the next power of 2 larger than the signal length. width : float The width of the Gaussian window. If < 1, increased temporal resolution, if > 1, increased frequency resolution. Defaults to 1. (classical S-Transform). decim : int The decimation factor on the time axis. To reduce memory usage. return_itc : bool Return intertrial coherence (ITC) as well as averaged power. n_jobs : int Number of parallel jobs to use.
Returns:	st_power : ndarray The multitaper power of the Stockwell transformed data. The last two dimensions are frequency and time. itc : ndarray The intertrial coherence. Only returned if return_itc is True. freqs : ndarray The frequencies.

data : ndarray: The signal to transform. Any dimensionality supported as long as the last dimension is time.
sfreq : float: The sampling frequency.
fmin : None, float: The minimum frequency to include. If None defaults to the minimum fft frequency greater than zero.
fmax : None, float: The maximum frequency to include. If None defaults to the maximum fft.
n_fft : int | None: The length of the windows used for FFT. If None, it defaults to the next power of 2 larger than the signal length.
width : float: The width of the Gaussian window. If < 1, increased temporal resolution, if > 1, increased frequency resolution. Defaults to 1. (classical S-Transform).
decim : int: The decimation factor on the time axis. To reduce memory usage.
return_itc : bool: Return intertrial coherence (ITC) as well as averaged power.
n_jobs : int: Number of parallel jobs to use.

Returns:

st_power : ndarray: The multitaper power of the Stockwell transformed data. The last two dimensions are frequency and time.
itc : ndarray: The intertrial coherence. Only returned if return_itc is True.
freqs : ndarray: The frequencies.

References

[1]	(1, 2) Stockwell, R. G. “Why use the S-transform.” AMS Pseudo-differential operators: Partial differential equations and time-frequency analysis 52 (2007): 279-309.

[2]	(1, 2) Moukadem, A., Bouguila, Z., Abdeslam, D. O, and Dieterlen, A. Stockwell transform optimization applied on the detection of split in heart sounds (2014). Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 22nd European, pages 2015–2019.

[3]	(1, 2) Wheat, K., Cornelissen, P. L., Frost, S.J, and Peter C. Hansen (2010). During Visual Word Recognition, Phonology Is Accessed within 100 ms and May Be Mediated by a Speech Production Code: Evidence from Magnetoencephalography. The Journal of Neuroscience, 30 (15), 5229-5233.

[4]	(1, 2) K. A. Jones and B. Porjesz and D. Chorlian and M. Rangaswamy and C. Kamarajan and A. Padmanabhapillai and A. Stimus and H. Begleiter (2006). S-transform time-frequency analysis of P300 reveals deficits in individuals diagnosed with alcoholism. Clinical Neurophysiology 117 2128–2143