[Mne_analysis] mn.time_frequency.tfr_array_stockwell

Paul Fishback fishbacp at mail.gvsu.edu
Wed Jul 8 17:15:22 EDT 2020
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I'm reading in an EDF (not FIF) file and would like to compute the
Stockwell Transform for a single channel using
time_frequency.tfr_array_stockwell as
described at

It says that the last dimension of my data is time. I'm not sure what that
means, but I interpret it to be that, for a single channel, the first
column consists of signal readings and the second consists of corresponding

Here's what I've tried for the first channel of my signal, which is 10
minutes long with sampling frequency 200

import numpy as np
import mne as mn

raw=mn.io.read_raw_edf('/Users/fishbacp/Desktop/EEG_file.edf', preload=True)

signal=np.array([data[0,:],times]).T  #Creates a number_of_times -by- 2
array, whose second column consists of times.


st_power, itc, freqs=mn.time_frequency.tfr_array_stockwell(signal,

This results in the following error:

line 172, in tfr_array_stockwell
    n_out = data.shape[2] // decim + bool(data.shape[2] % decim)
IndexError: tuple index out of range

I gather that I'm not interpreting how my input signal should be formatted.

Thanks for any assistance you can provide.

Paul F.

Professor of Mathematics, Grand Valley State University

Department of Mathematics (MAK C-2-408)
Grand Valley State University
1 Campus Dr.
Allendale, MI 49401
fishbacp at mail.gvsu.edu
616.331.3120 (fax)
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