[Mne_analysis] Mne_analysis Digest, Vol 150, Issue 44
Ben Ighoyota Ajenaghughrure
ighoyota at tlu.ee
Fri Jul 24 08:44:29 EDT 2020
External Email - Use Caution
Dear All,
The response from epochs.drop_log is [['NO_DATA']], yet i get the message
"1 bad epochs dropped"
Is there anyway to figure out why all my epochs are being dropped?
*source code below*
channames = ['Cz','Fz','C3','C4','F3','F4','P7','P8']
ch_types = ['eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg']
# Sampling rate of the Nautilus machine
sfreq = 250 # Hz for eeg
# Create the info structure needed by MNE
info = mne.create_info(ch_names=channames, sfreq=sfreq,
ch_types=ch_types)
raw = mne.io.RawArray(dataconv1, info)
raw.set_annotations(None)
raw.del_proj()
picks =mne.pick_types(raw.info, meg=False, eeg=True, stim=True,
eog=False,exclude='bads')
raw=raw.filter(0.1, 120, fir_design='firwin')
raw=raw.notch_filter(np.arange(50, 120, 50), picks=picks,
filter_length='auto', phase='zero')
evenfile=mne.make_fixed_length_events(raw, id=1, start=0,
stop=None, duration=4.0, first_samp=True, overlap=0.0)
epochs = mne.Epochs(raw, evenfile, event_id=event_id, tmin=-0.2,
tmax=4, picks=picks, baseline=(-0.2, 0), event_repeated='drop',proj=False,
preload=True, reject_by_annotation=None)
print(epochs.drop_log)
data = epochs.get_data()
A. Ighoyota ben
Junior Researcher HCI (PhD in-view)
Tallinn University, Estonia
School of digital Technologies.
mobile:+372582 <+372%205832%206393>78794
skype: ighoyota-ben
On Fri, 24 Jul 2020 at 04:58, <mne_analysis-request at nmr.mgh.harvard.edu>
wrote:
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> Today's Topics:
>
> 1. Re: epoch dropped problem (Alexandre Gramfort)
> 2. Re: loading the subject from BRAINSTORM (Alexandre Gramfort)
> 3. Re: Mne_analysis Digest, Vol 150, Issue 40 (balandongiv at gmail.com)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 23 Jul 2020 22:57:00 +0200
> From: Alexandre Gramfort <alexandre.gramfort at inria.fr>
> Subject: Re: [Mne_analysis] epoch dropped problem
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID:
> <CADeotZoS51gPzBn+oLTxCnLTgtpGy=
> 1DyWrFEnOhfM8Ouuevjg at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
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> What do epochs.drop_log and epochs.plot_drop_log() give you?
>
> Alex
>
>
>
> ------------------------------
>
> Message: 2
> Date: Thu, 23 Jul 2020 22:58:15 +0200
> From: Alexandre Gramfort <alexandre.gramfort at inria.fr>
> Subject: Re: [Mne_analysis] loading the subject from BRAINSTORM
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID:
> <
> CADeotZrjoB0oSOmbXpzESX-_39Dwmqr6VNiSobMqg_043nOD9w at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> hi,
>
> no it's not that simple as Brainstorm decimates the cortex while MNE
> subsamples the high resolution mesh.
>
> Alex
>
>
> On Thu, Jul 23, 2020 at 4:06 PM Abdallah Qusaibe
> <abdallah.qusaibe at gmail.com> wrote:
> >
> > External Email - Use Caution
> >
> > Hi All,
> >
> > Can we load in mne the subject (inorder to use the cortex mesh) used in
> Brainstorm,
> >
> > Cheers
> > Abdallah
> > _______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
>
> ------------------------------
>
> Message: 3
> Date: Fri, 24 Jul 2020 09:55:33 +0800
> From: <balandongiv at gmail.com>
> Subject: Re: [Mne_analysis] Mne_analysis Digest, Vol 150, Issue 40
> To: <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID: <004e01d6615d$85632b50$902981f0$@gmail.com>
> Content-Type: text/plain; charset="us-ascii"
>
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>
> Dear Clemens, Larson, Phillip,
>
> Thanks for the detail explanation, really appreciate it.
>
> Just a suggestion, maybe part of the discussion can be incorporated
> somewhere along with mne FAQ or equivalent. This might be helpful,
> especially to those new in the field.
>
> Rodney
>
>
> -----Original Message-----
> From: mne_analysis-bounces at nmr.mgh.harvard.edu
> <mne_analysis-bounces at nmr.mgh.harvard.edu> On Behalf Of
> mne_analysis-request at nmr.mgh.harvard.edu
> Sent: Thursday, 23 July, 2020 9:10 PM
> To: mne_analysis at nmr.mgh.harvard.edu
> Subject: Mne_analysis Digest, Vol 150, Issue 40
>
> Send Mne_analysis mailing list submissions to
> mne_analysis at nmr.mgh.harvard.edu
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>
> Today's Topics:
>
> 1. Re: Why does MNE resample method does not sample the data
> point to point? (Eric Larson)
> 2. Re: Why does MNE resample method does not sample the data
> point to point? (Brunner, Clemens (clemens.brunner at uni-graz.at))
> 3. Re: Why does MNE resample method does not sample the data
> point to point? (Phillip Alday)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 23 Jul 2020 08:40:56 -0400
> From: Eric Larson <larson.eric.d at gmail.com>
> Subject: Re: [Mne_analysis] Why does MNE resample method does not
> sample the data point to point?
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID:
> <
> CAGu2niVV+79nq5Yu17B4VzB3PS71x7sFTy8HKNukDxnaDdi6hQ at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> >
> > My understanding of downsampling is that it is an operation to
> > decrease the sample rate of x by keeping the first sample and then
> > every nth sample after the first.
> >
>
> Resampling typically consists of two steps: low-pass filtering to avoid
> aliasing, then sample rate reduction (subselecting samples from the
> resulting signal). The low-passing actually changes the values, so the
> subselection-of-filtered-data step will not necessarily yield points that
> were "on" the original signal.
>
>
> > May I know whether this issue is due to the ringing artifacts or due
> > to other problems?
> >
>
> In this case it's likely due to the (implicit) low-pass filtering in the
> frequency-domain resampling of the signal. It looks pretty reasonable to
> me.
> If you want to play around with it a bit, you can
>
> 1. Call scipy.signal.resample directly on your data and see how closely it
> matches.
> 2. Pad your signal, call scipy.signal.resample, and remove the (now
> reduced-length) padding -- this is what MNE does internally.
> 3. Use scipy.signal.resample_poly directly on your data.
> 4. Manually low-pass filter and then directly subselect samples from the
> low-passed signal, which is what resample_poly does internally.
>
> Hopefully these all give similar results for your signal(s).
>
> Eric
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> ------------------------------
>
> Message: 2
> Date: Thu, 23 Jul 2020 12:57:29 +0000
> From: "Brunner, Clemens (clemens.brunner at uni-graz.at)"
> <clemens.brunner at uni-graz.at>
> Subject: Re: [Mne_analysis] Why does MNE resample method does not
> sample the data point to point?
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>
> Message-ID: <21199B34-7BD6-4C1B-81CC-749DFB86E3FC at uni-graz.at>
> Content-Type: text/plain; charset="us-ascii"
>
> External Email - Use Caution
>
> Also note that the resample example
> (
> https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.
> html
> <https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.html>)
> shows upsampling, i.e. the data has a lower sampling rate than the
> resampled result. However, in the case of downsampling it is usually
> necessary to avoid aliasing of frequencies above the resampled Nyquist
> frequency. Therefore, the signal is typically low-pass filtered before the
> resampling step. As Eric mentioned, this anti-aliasing filter is what
> actually changes the signal values, but it is necessary to avoid aliasing
> artifacts.
>
> AFAIK, scipy.signal.resample doesn't include an anti-aliasing filter, but
> both scipy.signal.resample_poly as well as scipy.signal.decimate apply such
> a low-pass filter before resampling. That's also what MNE does.
>
> Clemens
>
>
> > On 23.07.2020, at 14:40, Eric Larson <larson.eric.d at gmail.com> wrote:
> >
> > External Email - Use Caution
> >
> >
> > My understanding of downsampling is that it is an operation to decrease
> the sample rate of x by keeping the first sample and then every nth sample
> after the first.
> >
> > Resampling typically consists of two steps: low-pass filtering to avoid
> aliasing, then sample rate reduction (subselecting samples from the
> resulting signal). The low-passing actually changes the values, so the
> subselection-of-filtered-data step will not necessarily yield points that
> were "on" the original signal.
> >
> > May I know whether this issue is due to the ringing artifacts or due to
> other problems?
> >
> > In this case it's likely due to the (implicit) low-pass filtering in
> > the frequency-domain resampling of the signal. It looks pretty
> > reasonable to me. If you want to play around with it a bit, you can
> >
> > 1. Call scipy.signal.resample directly on your data and see how closely
> it
> matches.
> > 2. Pad your signal, call scipy.signal.resample, and remove the (now
> reduced-length) padding -- this is what MNE does internally.
> > 3. Use scipy.signal.resample_poly directly on your data.
> > 4. Manually low-pass filter and then directly subselect samples from the
> low-passed signal, which is what resample_poly does internally.
> >
> > Hopefully these all give similar results for your signal(s).
> >
> > Eric
> >
> > _______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
>
>
>
> ------------------------------
>
> Message: 3
> Date: Thu, 23 Jul 2020 15:09:44 +0200
> From: Phillip Alday <phillip.alday at mpi.nl>
> Subject: Re: [Mne_analysis] Why does MNE resample method does not
> sample the data point to point?
> To: Discussion and support forum for the users of MNE Software
> <mne_analysis at nmr.mgh.harvard.edu>, "Brunner, Clemens
> (clemens.brunner at uni-graz.at)" <clemens.brunner at uni-graz.at>
> Message-ID: <16e39842-34bd-465d-9491-b5651302add4 at mpi.nl>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> I think the up- vs. downsampling distinction is also really important for
> expectations here, as is the distinction between decimating and resampling
> (I recall there was a thread about that a few years back with similar
> confusion, if somebody wants to do the effort of searching for it)
>
> Phillip
>
> On 23/7/20 2:57 pm, Brunner, Clemens (clemens.brunner at uni-graz.at) wrote:
> > External Email - Use Caution
> >
> > Also note that the resample example
> (
> https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.
> html
> <https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.html>)
> shows upsampling, i.e. the data has a lower sampling rate than the
> resampled result. However, in the case of downsampling it is usually
> necessary to avoid aliasing of frequencies above the resampled Nyquist
> frequency. Therefore, the signal is typically low-pass filtered before the
> resampling step. As Eric mentioned, this anti-aliasing filter is what
> actually changes the signal values, but it is necessary to avoid aliasing
> artifacts.
> >
> > AFAIK, scipy.signal.resample doesn't include an anti-aliasing filter, but
> both scipy.signal.resample_poly as well as scipy.signal.decimate apply such
> a low-pass filter before resampling. That's also what MNE does.
> >
> > Clemens
> >
> >
> >> On 23.07.2020, at 14:40, Eric Larson <larson.eric.d at gmail.com> wrote:
> >>
> >> External Email - Use Caution
> >>
> >>
> >> My understanding of downsampling is that it is an operation to decrease
> the sample rate of x by keeping the first sample and then every nth sample
> after the first.
> >>
> >> Resampling typically consists of two steps: low-pass filtering to avoid
> aliasing, then sample rate reduction (subselecting samples from the
> resulting signal). The low-passing actually changes the values, so the
> subselection-of-filtered-data step will not necessarily yield points that
> were "on" the original signal.
> >>
> >> May I know whether this issue is due to the ringing artifacts or due to
> other problems?
> >>
> >> In this case it's likely due to the (implicit) low-pass filtering in
> >> the frequency-domain resampling of the signal. It looks pretty
> >> reasonable to me. If you want to play around with it a bit, you can
> >>
> >> 1. Call scipy.signal.resample directly on your data and see how closely
> it matches.
> >> 2. Pad your signal, call scipy.signal.resample, and remove the (now
> reduced-length) padding -- this is what MNE does internally.
> >> 3. Use scipy.signal.resample_poly directly on your data.
> >> 4. Manually low-pass filter and then directly subselect samples from the
> low-passed signal, which is what resample_poly does internally.
> >>
> >> Hopefully these all give similar results for your signal(s).
> >>
> >> Eric
> >>
> >> _______________________________________________
> >> Mne_analysis mailing list
> >> Mne_analysis at nmr.mgh.harvard.edu
> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >
> >
> > _______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
>
>
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