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
 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 STransform).
 decim
int
The decimation factor on the time axis. To reduce memory usage.
 return_itcbool
Return intertrial coherence (ITC) as well as averaged power.
 n_jobs
int
The number of jobs to run in parallel (default 1). Requires the joblib package.
 data
 Returns
See also
References
 1
Stockwell, R. G. “Why use the Stransform.” AMS Pseudodifferential operators: Partial differential equations and timefrequency analysis 52 (2007): 279309.
 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
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), 52295233.
 4
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). Stransform timefrequency analysis of P300 reveals deficits in individuals diagnosed with alcoholism. Clinical Neurophysiology 117 2128–2143