<p><span style="padding: 3px 10px; border-radius: 5px; color: #ffffff; font-weight: bold; display: inline-block; background-color: #ff0000;"> External Email - Use Caution </span></p><p></p><div dir="ltr"><div dir="ltr">Dear All,<div><br></div><div>The response from epochs.drop_log is [['NO_DATA']], yet i get the message "1 bad epochs dropped"</div><div><br></div><div>Is there anyway to figure out why all my epochs are being dropped?</div><div><br></div><div><b><u>source code below</u></b></div><div> channames = ['Cz','Fz','C3','C4','F3','F4','P7','P8'] </div><div> ch_types = ['eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg']<br> # Sampling rate of the Nautilus machine<br> sfreq = 250 # Hz for eeg<br> # Create the info structure needed by MNE<br> info = mne.create_info(ch_names=channames, sfreq=sfreq, ch_types=ch_types)<br> raw = mne.io.RawArray(dataconv1, info)<br> raw.set_annotations(None)<br> raw.del_proj()<br> picks =mne.pick_types(<a href="http://raw.info">raw.info</a>, meg=False, eeg=True, stim=True, eog=False,exclude='bads')<br> raw=raw.filter(0.1, 120, fir_design='firwin')<br> raw=raw.notch_filter(np.arange(50, 120, 50), picks=picks, filter_length='auto', phase='zero')<br> evenfile=mne.make_fixed_length_events(raw, id=1, start=0, stop=None, duration=4.0, first_samp=True, overlap=0.0)<br> 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)<br> print(epochs.drop_log)<br></div><div>data = epochs.get_data()<br></div><div><br></div><div><br></div><div><br></div><div><div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div style="font-size:12.8px"><span style="color:rgb(51,51,51);font-family:"Droid Serif"">A. Ighoyota ben</span></div><div style="font-size:12.8px"><span style="color:rgb(51,51,51);font-family:"Droid Serif"">Junior Researcher HCI (PhD in-view) </span></div><div style="font-size:12.8px"><span style="color:rgb(51,51,51);font-family:"Droid Serif";font-size:12.8px">Tallinn University, Estonia</span><br></div><div style="font-size:12.8px"><span style="color:rgb(51,51,51);font-family:"Droid Serif"">School of digital Technologies.</span></div><div style="font-size:12.8px"><span style="color:rgb(51,51,51);font-family:"Droid Serif"">mobile:<a href="tel:+372%205832%206393" value="+37258326393" style="color:rgb(17,85,204)" target="_blank">+372582</a>78794</span></div><div style="font-size:12.8px"><span style="color:rgb(51,51,51);font-family:"Droid Serif"">skype: ighoyota-ben</span></div></div></div></div></div></div><br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Fri, 24 Jul 2020 at 04:58, <<a href="mailto:mne_analysis-request@nmr.mgh.harvard.edu">mne_analysis-request@nmr.mgh.harvard.edu</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Send Mne_analysis mailing list submissions to<br>
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<br>
Today's Topics:<br>
<br>
1. Re: epoch dropped problem (Alexandre Gramfort)<br>
2. Re: loading the subject from BRAINSTORM (Alexandre Gramfort)<br>
3. Re: Mne_analysis Digest, Vol 150, Issue 40 (<a href="mailto:balandongiv@gmail.com" target="_blank">balandongiv@gmail.com</a>)<br>
<br>
<br>
----------------------------------------------------------------------<br>
<br>
Message: 1<br>
Date: Thu, 23 Jul 2020 22:57:00 +0200<br>
From: Alexandre Gramfort <<a href="mailto:alexandre.gramfort@inria.fr" target="_blank">alexandre.gramfort@inria.fr</a>><br>
Subject: Re: [Mne_analysis] epoch dropped problem<br>
To: Discussion and support forum for the users of MNE Software<br>
<<a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a>><br>
Message-ID:<br>
<CADeotZoS51gPzBn+oLTxCnLTgtpGy=<a href="mailto:1DyWrFEnOhfM8Ouuevjg@mail.gmail.com" target="_blank">1DyWrFEnOhfM8Ouuevjg@mail.gmail.com</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
External Email - Use Caution <br>
<br>
What do epochs.drop_log and epochs.plot_drop_log() give you?<br>
<br>
Alex<br>
<br>
<br>
<br>
------------------------------<br>
<br>
Message: 2<br>
Date: Thu, 23 Jul 2020 22:58:15 +0200<br>
From: Alexandre Gramfort <<a href="mailto:alexandre.gramfort@inria.fr" target="_blank">alexandre.gramfort@inria.fr</a>><br>
Subject: Re: [Mne_analysis] loading the subject from BRAINSTORM<br>
To: Discussion and support forum for the users of MNE Software<br>
<<a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a>><br>
Message-ID:<br>
<<a href="mailto:CADeotZrjoB0oSOmbXpzESX-_39Dwmqr6VNiSobMqg_043nOD9w@mail.gmail.com" target="_blank">CADeotZrjoB0oSOmbXpzESX-_39Dwmqr6VNiSobMqg_043nOD9w@mail.gmail.com</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
External Email - Use Caution <br>
<br>
hi,<br>
<br>
no it's not that simple as Brainstorm decimates the cortex while MNE<br>
subsamples the high resolution mesh.<br>
<br>
Alex<br>
<br>
<br>
On Thu, Jul 23, 2020 at 4:06 PM Abdallah Qusaibe<br>
<<a href="mailto:abdallah.qusaibe@gmail.com" target="_blank">abdallah.qusaibe@gmail.com</a>> wrote:<br>
><br>
> External Email - Use Caution<br>
><br>
> Hi All,<br>
><br>
> Can we load in mne the subject (inorder to use the cortex mesh) used in Brainstorm,<br>
><br>
> Cheers<br>
> Abdallah<br>
> _______________________________________________<br>
> Mne_analysis mailing list<br>
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<br>
Message: 3<br>
Date: Fri, 24 Jul 2020 09:55:33 +0800<br>
From: <<a href="mailto:balandongiv@gmail.com" target="_blank">balandongiv@gmail.com</a>><br>
Subject: Re: [Mne_analysis] Mne_analysis Digest, Vol 150, Issue 40<br>
To: <<a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a>><br>
Message-ID: <004e01d6615d$85632b50$902981f0$@<a href="http://gmail.com" rel="noreferrer" target="_blank">gmail.com</a>><br>
Content-Type: text/plain; charset="us-ascii"<br>
<br>
External Email - Use Caution <br>
<br>
Dear Clemens, Larson, Phillip,<br>
<br>
Thanks for the detail explanation, really appreciate it.<br>
<br>
Just a suggestion, maybe part of the discussion can be incorporated<br>
somewhere along with mne FAQ or equivalent. This might be helpful,<br>
especially to those new in the field.<br>
<br>
Rodney<br>
<br>
<br>
-----Original Message-----<br>
From: <a href="mailto:mne_analysis-bounces@nmr.mgh.harvard.edu" target="_blank">mne_analysis-bounces@nmr.mgh.harvard.edu</a><br>
<<a href="mailto:mne_analysis-bounces@nmr.mgh.harvard.edu" target="_blank">mne_analysis-bounces@nmr.mgh.harvard.edu</a>> On Behalf Of<br>
<a href="mailto:mne_analysis-request@nmr.mgh.harvard.edu" target="_blank">mne_analysis-request@nmr.mgh.harvard.edu</a><br>
Sent: Thursday, 23 July, 2020 9:10 PM<br>
To: <a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a><br>
Subject: Mne_analysis Digest, Vol 150, Issue 40<br>
<br>
Send Mne_analysis mailing list submissions to<br>
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When replying, please edit your Subject line so it is more specific than<br>
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<br>
Today's Topics:<br>
<br>
1. Re: Why does MNE resample method does not sample the data<br>
point to point? (Eric Larson)<br>
2. Re: Why does MNE resample method does not sample the data<br>
point to point? (Brunner, Clemens (<a href="mailto:clemens.brunner@uni-graz.at" target="_blank">clemens.brunner@uni-graz.at</a>))<br>
3. Re: Why does MNE resample method does not sample the data<br>
point to point? (Phillip Alday)<br>
<br>
<br>
----------------------------------------------------------------------<br>
<br>
Message: 1<br>
Date: Thu, 23 Jul 2020 08:40:56 -0400<br>
From: Eric Larson <<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>><br>
Subject: Re: [Mne_analysis] Why does MNE resample method does not<br>
sample the data point to point?<br>
To: Discussion and support forum for the users of MNE Software<br>
<<a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a>><br>
Message-ID:<br>
<<a href="mailto:CAGu2niVV%2B79nq5Yu17B4VzB3PS71x7sFTy8HKNukDxnaDdi6hQ@mail.gmail.com" target="_blank">CAGu2niVV+79nq5Yu17B4VzB3PS71x7sFTy8HKNukDxnaDdi6hQ@mail.gmail.com</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
External Email - Use Caution <br>
<br>
><br>
> My understanding of downsampling is that it is an operation to <br>
> decrease the sample rate of x by keeping the first sample and then <br>
> every nth sample after the first.<br>
><br>
<br>
Resampling typically consists of two steps: low-pass filtering to avoid<br>
aliasing, then sample rate reduction (subselecting samples from the<br>
resulting signal). The low-passing actually changes the values, so the<br>
subselection-of-filtered-data step will not necessarily yield points that<br>
were "on" the original signal.<br>
<br>
<br>
> May I know whether this issue is due to the ringing artifacts or due <br>
> to other problems?<br>
><br>
<br>
In this case it's likely due to the (implicit) low-pass filtering in the<br>
frequency-domain resampling of the signal. It looks pretty reasonable to me.<br>
If you want to play around with it a bit, you can<br>
<br>
1. Call scipy.signal.resample directly on your data and see how closely it<br>
matches.<br>
2. Pad your signal, call scipy.signal.resample, and remove the (now<br>
reduced-length) padding -- this is what MNE does internally.<br>
3. Use scipy.signal.resample_poly directly on your data.<br>
4. Manually low-pass filter and then directly subselect samples from the<br>
low-passed signal, which is what resample_poly does internally.<br>
<br>
Hopefully these all give similar results for your signal(s).<br>
<br>
Eric<br>
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Message: 2<br>
Date: Thu, 23 Jul 2020 12:57:29 +0000<br>
From: "Brunner, Clemens (<a href="mailto:clemens.brunner@uni-graz.at" target="_blank">clemens.brunner@uni-graz.at</a>)"<br>
<<a href="mailto:clemens.brunner@uni-graz.at" target="_blank">clemens.brunner@uni-graz.at</a>><br>
Subject: Re: [Mne_analysis] Why does MNE resample method does not<br>
sample the data point to point?<br>
To: Discussion and support forum for the users of MNE Software<br>
<<a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a>><br>
Message-ID: <<a href="mailto:21199B34-7BD6-4C1B-81CC-749DFB86E3FC@uni-graz.at" target="_blank">21199B34-7BD6-4C1B-81CC-749DFB86E3FC@uni-graz.at</a>><br>
Content-Type: text/plain; charset="us-ascii"<br>
<br>
External Email - Use Caution <br>
<br>
Also note that the resample example<br>
(<a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.html" rel="noreferrer" target="_blank">https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.<br>
html</a>) shows upsampling, i.e. the data has a lower sampling rate than the<br>
resampled result. However, in the case of downsampling it is usually<br>
necessary to avoid aliasing of frequencies above the resampled Nyquist<br>
frequency. Therefore, the signal is typically low-pass filtered before the<br>
resampling step. As Eric mentioned, this anti-aliasing filter is what<br>
actually changes the signal values, but it is necessary to avoid aliasing<br>
artifacts.<br>
<br>
AFAIK, scipy.signal.resample doesn't include an anti-aliasing filter, but<br>
both scipy.signal.resample_poly as well as scipy.signal.decimate apply such<br>
a low-pass filter before resampling. That's also what MNE does.<br>
<br>
Clemens<br>
<br>
<br>
> On 23.07.2020, at 14:40, Eric Larson <<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>> wrote:<br>
> <br>
> External Email - Use Caution <br>
> <br>
> <br>
> My understanding of downsampling is that it is an operation to decrease<br>
the sample rate of x by keeping the first sample and then every nth sample<br>
after the first.<br>
> <br>
> Resampling typically consists of two steps: low-pass filtering to avoid<br>
aliasing, then sample rate reduction (subselecting samples from the<br>
resulting signal). The low-passing actually changes the values, so the<br>
subselection-of-filtered-data step will not necessarily yield points that<br>
were "on" the original signal.<br>
> <br>
> May I know whether this issue is due to the ringing artifacts or due to<br>
other problems?<br>
> <br>
> In this case it's likely due to the (implicit) low-pass filtering in <br>
> the frequency-domain resampling of the signal. It looks pretty <br>
> reasonable to me. If you want to play around with it a bit, you can<br>
> <br>
> 1. Call scipy.signal.resample directly on your data and see how closely it<br>
matches.<br>
> 2. Pad your signal, call scipy.signal.resample, and remove the (now<br>
reduced-length) padding -- this is what MNE does internally.<br>
> 3. Use scipy.signal.resample_poly directly on your data.<br>
> 4. Manually low-pass filter and then directly subselect samples from the<br>
low-passed signal, which is what resample_poly does internally.<br>
> <br>
> Hopefully these all give similar results for your signal(s).<br>
> <br>
> Eric<br>
> <br>
> _______________________________________________<br>
> Mne_analysis mailing list<br>
> <a href="mailto:Mne_analysis@nmr.mgh.harvard.edu" target="_blank">Mne_analysis@nmr.mgh.harvard.edu</a><br>
> <a href="https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis" rel="noreferrer" target="_blank">https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis</a><br>
<br>
<br>
<br>
<br>
<br>
------------------------------<br>
<br>
Message: 3<br>
Date: Thu, 23 Jul 2020 15:09:44 +0200<br>
From: Phillip Alday <<a href="mailto:phillip.alday@mpi.nl" target="_blank">phillip.alday@mpi.nl</a>><br>
Subject: Re: [Mne_analysis] Why does MNE resample method does not<br>
sample the data point to point?<br>
To: Discussion and support forum for the users of MNE Software<br>
<<a href="mailto:mne_analysis@nmr.mgh.harvard.edu" target="_blank">mne_analysis@nmr.mgh.harvard.edu</a>>, "Brunner, Clemens<br>
(<a href="mailto:clemens.brunner@uni-graz.at" target="_blank">clemens.brunner@uni-graz.at</a>)" <<a href="mailto:clemens.brunner@uni-graz.at" target="_blank">clemens.brunner@uni-graz.at</a>><br>
Message-ID: <<a href="mailto:16e39842-34bd-465d-9491-b5651302add4@mpi.nl" target="_blank">16e39842-34bd-465d-9491-b5651302add4@mpi.nl</a>><br>
Content-Type: text/plain; charset="utf-8"<br>
<br>
External Email - Use Caution <br>
<br>
I think the up- vs. downsampling distinction is also really important for<br>
expectations here, as is the distinction between decimating and resampling<br>
(I recall there was a thread about that a few years back with similar<br>
confusion, if somebody wants to do the effort of searching for it)<br>
<br>
Phillip<br>
<br>
On 23/7/20 2:57 pm, Brunner, Clemens (<a href="mailto:clemens.brunner@uni-graz.at" target="_blank">clemens.brunner@uni-graz.at</a>) wrote:<br>
> External Email - Use Caution <br>
><br>
> Also note that the resample example<br>
(<a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.html" rel="noreferrer" target="_blank">https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.resample.<br>
html</a>) shows upsampling, i.e. the data has a lower sampling rate than the<br>
resampled result. However, in the case of downsampling it is usually<br>
necessary to avoid aliasing of frequencies above the resampled Nyquist<br>
frequency. Therefore, the signal is typically low-pass filtered before the<br>
resampling step. As Eric mentioned, this anti-aliasing filter is what<br>
actually changes the signal values, but it is necessary to avoid aliasing<br>
artifacts.<br>
><br>
> AFAIK, scipy.signal.resample doesn't include an anti-aliasing filter, but<br>
both scipy.signal.resample_poly as well as scipy.signal.decimate apply such<br>
a low-pass filter before resampling. That's also what MNE does.<br>
><br>
> Clemens<br>
><br>
><br>
>> On 23.07.2020, at 14:40, Eric Larson <<a href="mailto:larson.eric.d@gmail.com" target="_blank">larson.eric.d@gmail.com</a>> wrote:<br>
>><br>
>> External Email - Use Caution <br>
>><br>
>><br>
>> My understanding of downsampling is that it is an operation to decrease<br>
the sample rate of x by keeping the first sample and then every nth sample<br>
after the first.<br>
>><br>
>> Resampling typically consists of two steps: low-pass filtering to avoid<br>
aliasing, then sample rate reduction (subselecting samples from the<br>
resulting signal). The low-passing actually changes the values, so the<br>
subselection-of-filtered-data step will not necessarily yield points that<br>
were "on" the original signal.<br>
>> <br>
>> May I know whether this issue is due to the ringing artifacts or due to<br>
other problems?<br>
>><br>
>> In this case it's likely due to the (implicit) low-pass filtering in <br>
>> the frequency-domain resampling of the signal. It looks pretty <br>
>> reasonable to me. If you want to play around with it a bit, you can<br>
>><br>
>> 1. Call scipy.signal.resample directly on your data and see how closely<br>
it matches.<br>
>> 2. Pad your signal, call scipy.signal.resample, and remove the (now<br>
reduced-length) padding -- this is what MNE does internally.<br>
>> 3. Use scipy.signal.resample_poly directly on your data.<br>
>> 4. Manually low-pass filter and then directly subselect samples from the<br>
low-passed signal, which is what resample_poly does internally.<br>
>><br>
>> Hopefully these all give similar results for your signal(s).<br>
>><br>
>> Eric<br>
>><br>
>> _______________________________________________<br>
>> Mne_analysis mailing list<br>
>> <a href="mailto:Mne_analysis@nmr.mgh.harvard.edu" target="_blank">Mne_analysis@nmr.mgh.harvard.edu</a><br>
>> <a href="https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis" rel="noreferrer" target="_blank">https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis</a><br>
><br>
><br>
> _______________________________________________<br>
> Mne_analysis mailing list<br>
> <a href="mailto:Mne_analysis@nmr.mgh.harvard.edu" target="_blank">Mne_analysis@nmr.mgh.harvard.edu</a><br>
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End of Mne_analysis Digest, Vol 150, Issue 44<br>
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