[Mne_analysis] Mne_analysis Digest, Vol 127, Issue 12
d p
aglasis at gmail.com
Wed Aug 8 04:31:06 EDT 2018
External Email - Use Caution
Thanks @Eric for your comments!
I'll try working directly with the .data. From your comments, that seems
safer than to go back and forth between the mne objects and data frames.
As for the timing with the EvokedArray call, you are right. The constructor
manages the timing correctly specifying the tmin and sampling frequency in
the info. I was sure I did that already yesterday before sending the
original email with my wrong timing issue, but obviously I was doing
something wrong, because I tried again now, and it worked perfectly.
Best,
D.
On 7 August 2018 at 22:35, <mne_analysis-request at nmr.mgh.harvard.edu> wrote:
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> Today's Topics:
>
> 1. Re: Fwd: Convert pandas dataframe back to Evoked (UPDATED!)
> (Eric Larson)
> 2. Re: Wavelet Features Extraction (Alejandro Weinstein)
> 3. Re: Wavelet Features Extraction (Badar Almarri)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 7 Aug 2018 14:23:32 -0600
> From: Eric Larson <larson.eric.d at gmail.com>
> Subject: Re: [Mne_analysis] Fwd: Convert pandas dataframe back to
> Evoked (UPDATED!)
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID:
> <CAGu2niVioWgmdH6tCWg5aRy9JnDLMGPzMVPsJz8oRhEeaNB-1A at mail.
> gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> >
> > Sorry for spamming, but the second I pressed "send" I realized that I
> > could simply set the time points correctly as NewEvoked.times =
> > OriginalEvoked.times. That seems to work fine and that would solve my
> main
> > question.
> >
>
> This is not a safe operation because it creates inconsistencies between
> various parameters of the EvokedArray object.
>
> Given `tmin` in the `EvokedArray` constructor and `info['sfreq']`, you
> should be able to get `evoked.times` to be correct (assuming equal spacing
> of samples, which is implicitly required for EvokedArray). Perhaps you
> weren't setting `tmin` properly, or `info['sfreq']` was not set to the
> correct value?
>
> Regarding to/frame dataframe, I would instead just use `evoked.data`
> directly as a NumPy array, do my computations there, and then create a new
> object with EvokedArray.
>
> Eric
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> Message: 2
> Date: Tue, 7 Aug 2018 16:35:20 -0400
> From: Alejandro Weinstein <alejandro.weinstein at gmail.com>
> Subject: Re: [Mne_analysis] Wavelet Features Extraction
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID:
> <CAPFc=oxHvKy+MOWfqrGDGJVFoUOmyv=XJAM=qqpQ1E
> d0_j0mhg at mail.gmail.com>
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>
> > If you're interested in feature extraction, you might want to look into
> mne-features: https://mne-tools.github.io/mne-features/api.html.
>
> This is great! Could this library be advertised somewhere in the
> MNE-Python website or documentation? This would avoid people (like me
> :) reinventing the wheel.
>
> And perhaps more generally, could we have something equivalent to
> scikit-learn-contrib
> (https://github.com/scikit-learn-contrib/scikit-learn-
> contrib/blob/master/README.md),
> to collect MNE-compatible projects?
>
> Alejandro
>
>
>
> ------------------------------
>
> Message: 3
> Date: Tue, 7 Aug 2018 16:35:43 -0400
> From: Badar Almarri <badar.almarri at uconn.edu>
> Subject: Re: [Mne_analysis] Wavelet Features Extraction
> To: mne_analysis at nmr.mgh.harvard.edu
> Message-ID:
> <CAPjek2=VRJL-Pa4Se1T9WDpPWqvxgvr9Seq5LtsoTa
> Dn2RQgpA at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
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>
> Thank you, all!
>
> Best,
> Badar Almarri
> Graduate Student
> Dept. of Computer Science and Engr.
> University of Connecticut
> badar.almarri at uconn.edu
> <http://www.linkedin.com/pub/badar-almarri/48/b09/8b8>
>
>
> On Mon, Aug 6, 2018 at 6:06 PM Rodrigo Ramele <rramele at gmail.com> wrote:
>
> > External Email - Use Caution
> >
> > Hey hi !
> >
> > If you are interested in a good explanation of what you will find
> > extracting features between STFT, Wavelets and eventually MP, check out
> > this excellent paper: http://www.jneurosci.org/content/36/12/3399.short
> > <https://na01.safelinks.protection.outlook.com/?url=
> http%3A%2F%2Fwww.jneurosci.org%2Fcontent%2F36%2F12%
> 2F3399.short&data=02%7C01%7Cbadar.almarri%40uconn.edu%
> 7C9c73384d68ff4be056f308d5fbe8d41e%7C17f1a87e2a254eaab9df9d439034
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> Bk1SzKhDw8Vvc%3D&reserved=0>
> >
> > Your regards!
> >
> >
> > 2018-08-03 20:53 GMT-03:00 Mainak Jas <mainakjas at gmail.com>:
> >
> >> External Email - Use Caution
> >>
> >> Hi,
> >>
> >> If you're interested in feature extraction, you might want to look into
> >> mne-features: https://mne-tools.github.io/mne-features/api.html
> >> <https://na01.safelinks.protection.outlook.com/?url=
> https%3A%2F%2Fmne-tools.github.io%2Fmne-features%2Fapi.html&data=02%7C01%
> 7Cbadar.almarri%40uconn.edu%7C9c73384d68ff4be056f308d5fbe8d41e%
> 7C17f1a87e2a254eaab9df9d439034b080%7C0%7C0%7C636691899775592192&sdata=
> AY6NUgNVywCBXMEZRlJGQWZ21hEpOBk3qEATnYhlKIM%3D&reserved=0>
> >> .
> >>
> >> It should fit your needs.
> >>
> >> Best,
> >> Mainak
> >>
> >> On Fri, Aug 3, 2018 at 5:48 PM, Badar Almarri <badar.almarri at uconn.edu>
> >> wrote:
> >>
> >>> External Email - Use Caution
> >>>
> >>> Greetings,
> >>>
> >>> I use short time Fourier transform to extract features from the
> >>> time-series EEG signals. Now I plan to use Wavelet that I don't have
> any
> >>> prior experience in.
> >>>
> >>> Can someone provide a Python implementation (or MNE - btw, I couldn't
> >>> digest mne morlet for some reason!)? Also, what output I should
> expect, and
> >>> what features can be computed from the Wavelet transform output to be
> ready
> >>> to fit a learner?
> >>>
> >>> A question I would also like to ask those who're concerned about
> feature
> >>> extraction, why would I use Wavelet over STFT, or vice versa?
> >>>
> >>>
> >>> Thank you,
> >>> Badar Almarri
> >>> Graduate Student
> >>> Dept. of Computer Science and Engr.
> >>> University of Connecticut
> >>> badar.almarri at uconn.edu
> >>>
> >>> <https://na01.safelinks.protection.outlook.com/?url=
> http%3A%2F%2Fwww.linkedin.com%2Fpub%2Fbadar-almarri%2F48%
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