[Mne_analysis] mn.time_frequency.tfr_array_stockwell
Eric Larson
larson.eric.d at gmail.com
Fri Jul 10 14:21:36 EDT 2020
External Email - Use Caution
Looks like stockwell is internally only meant to work on 3D arrays. I've
opened a pull request to fix the checks:
https://github.com/mne-tools/mne-python/pull/7996
In your case you should be able to get something useful by passing a 3D
array like signal[np.newaxis]. The power and frequencies should not be
empty. If they are, please open an issue with a little snippet of code we
can use to reproduce the problem.
Eric
On Thu, Jul 9, 2020 at 4:52 PM Paul Fishback <fishbacp at mail.gvsu.edu> wrote:
> External Email - Use Caution
>
> Thanks again. Now, a different message appears:
>
> Warning (from warnings module):
> File "/Users/fishbacp/Desktop/Python_Sabbatical/plot_stockwell.py", line
> 188
> st_power, itc, freqs =
> mn.time_frequency.tfr_array_stockwell(signal,Fs, fmin=min_freq,
> fmax=max_freq)
> RuntimeWarning: The input signal is shorter (123200) than "n_fft"
> (131072). Applying zero padding.
>
> This warning message comes from the function, _check_input_st.
>
> I looked at this function separately and, while n_times is correct, n_fft
> is larger, even if I simply use the default value
> in mn.time_frequency.tfr_array_stockwell.
>
> Eventually, mn.time_frequency.tfr_array_stockwell runs and I return to the
> shell (in Idle); however I inserted a line to print st_power and freqs,
> which came back empty
>
> Paul
>
>
>
> On Thu, Jul 9, 2020 at 3:21 PM Eric Larson <larson.eric.d at gmail.com>
> wrote:
>
>> External Email - Use Caution
>>
>> For now you can work around it by doing `data = data[np.newaxis]` to make
>> it of shape `(n_epochs, n_channels, n_times)` (which appears to be what the
>> function actually wants). Can you open an issue on the MNE-Python issue
>> tracker so that we don't forget to fix this? It should really just operate
>> along the last dimension and not assume that's 2.
>>
>> Eric
>>
>>
>> On Thu, Jul 9, 2020 at 3:18 PM Paul Fishback <fishbacp at mail.gvsu.edu>
>> wrote:
>>
>>> External Email - Use Caution
>>>
>>> Hi Alex,
>>>
>>> Thanks so much for responding to my message. I tried what you suggested,
>>> but I'm still getting an error:
>>>
>>> raw=mn.io.read_raw_edf('/Users/fishbacp/Desktop/11.edf', preload=True)
>>> Fs=raw.info['sfreq']
>>>
>>> data,times=raw[:,:]
>>> print('data: '+str(data.shape)) #This indicates the data shape is
>>> 46-by-123200, which makes sense for my recording: 46 channels, 10 minute
>>> time length, and sampling frequency 200 Hz.
>>>
>>> signal = data[[0]]
>>> print('signal: '+str(signal.shape)) # This produces 1-by-123200 for
>>> this channel
>>> min_freq = 5
>>> max_freq = 100
>>> st_power, itc, freqs = mn.time_frequency.tfr_array_stockwell(signal,Fs,
>>> fmin=min_freq, fmax=max_freq)
>>>
>>> This is the error message:
>>>
>>> Traceback (most recent call last):
>>> File "/Users/fishbacp/Desktop/Python_Sabbatical/plot_stockwell.py",
>>> line 145, in <module>
>>> st_power, itc, freqs =
>>> mn.time_frequency.tfr_array_stockwell(signal,Fs, fmin=min_freq,
>>> fmax=max_freq)
>>> File
>>> "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/mne/time_frequency/_stockwell.py",
>>> line 172, in tfr_array_stockwell
>>> n_out = data.shape[2] // decim + bool(data.shape[2] % decim)
>>> IndexError: tuple index out of range
>>>
>>> Lines-171-173 in the script, located at
>>> https://github.com/mne-tools/mne-python/blob/maint/0.20/mne/time_frequency/_stockwell.py#L101-L199 are
>>> as follows:
>>>
>>> [image: image.png]
>>>
>>> I don't see how data.shape[2] could even be defined if data lacks a
>>> third dimension.
>>>
>>> I'm not wed to using this implementation of the stockwell transform. I
>>> tried it first because I enjoy using MNE, but if you know of other good
>>> implementations, I would enjoy hearing about them.
>>>
>>> Many, many thanks.
>>>
>>> Best,
>>>
>>> Paul
>>>
>>> On Thu, Jul 9, 2020 at 10:38 AM Alexandre Gramfort <
>>> alexandre.gramfort at inria.fr> wrote:
>>>
>>>> External Email - Use Caution
>>>>
>>>> hi Paul,
>>>>
>>>> try:
>>>>
>>>> import numpy as np
>>>> import mne
>>>>
>>>> raw = mne.io.read_raw_edf('/Users/fishbacp/Desktop/EEG_file.edf',
>>>> preload=True)
>>>> Fs = raw.info['sfreq']
>>>> data, times=raw[:, :]
>>>> signal = data[[0]]
>>>> min_freq = 5
>>>> max_freq = 100
>>>> st_power, itc, freqs = mne.time_frequency.tfr_array_stockwell(signal,
>>>> Fs, fmin=min_freq, fmax=max_freq)
>>>>
>>>> --
>>>>
>>>> signal must be a 2d array with dimensions: channel x time
>>>>
>>>> Alex
>>>>
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>>>
>>>
>>> --
>>> 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
>>> 616.331.2040
>>> 616.331.3120 (fax)
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>
>
>
> --
> Professor of Mathematics, Grand Valley State University
> President, Pi Mu Epsilon National Honorary Mathematics Society, Inc.
>
> Department of Mathematics (MAK C-2-408)
> Grand Valley State University
> 1 Campus Dr.
> Allendale, MI 49401
> fishbacp at mail.gvsu.edu
> 616.331.2040
> 616.331.3120 (fax)
> _______________________________________________
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