[Mne_analysis] epoch dropped problem (Alexandre Gramfort)
Ben Ighoyota Ajenaghughrure
ighoyota at tlu.ee
Sat Jul 25 06:17:43 EDT 2020
External Email - Use Caution
Dear Alexandre Gramfort,
Evenfile contains a single row and three columns, the first cell holds the
epoch timestamp, the second cell contains duration of event and the third
cell contains the event code.
The vent file was created using mne.make_fixed_length_events, with
start-0, duration=4
Initially the raw was 4seconds. and I guess this was too short as you
rightly pointed out.
Now i decided to make them 8s, taking 4seconds earlier than the event
occurrence, and 4seconds starting from event occurrence. This led to two
equal epochs, each 4s long.
After applying the suggestions from Dan, the first epoch of 4seconds is
dropped and the second epoch of 4seconds is retained. Although I do not
need the first epoch of 4s. So I think it's ok for my current application.
Thank you very much for the help.
Best Regards.
A. Ighoyota ben
Junior Researcher HCI (PhD in-view)
Tallinn University, Estonia
School of digital Technologies.
On Sat, 25 Jul 2020 at 12:59, <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: Epochs being dropped Mne_analysis Digest, Vol 150, Issue
> 48 (Ben Ighoyota Ajenaghughrure)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Fri, 24 Jul 2020 19:57:02 +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:
> <
> CADeotZrkpzwqwC3372KKbUqCk8Hd6rtLA9S9O207C3xuW3aY+A at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> how long is your raw file?
>
> what does evenfile contain?
>
> I suspect your raw file is too short
>
> A
>
>
>
> ------------------------------
>
> Message: 2
> Date: Sat, 25 Jul 2020 12:55:46 +0300
> From: Ben Ighoyota Ajenaghughrure <ighoyota at tlu.ee>
> Subject: Re: [Mne_analysis] Epochs being dropped Mne_analysis Digest,
> Vol 150, Issue 48
> To: mne_analysis at nmr.mgh.harvard.edu
> Message-ID:
> <
> CAOQEtu4Fd4TqvJksTS6EmWFtAmeMQPU5Qwp7_a8+2osDpy3Bfg at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> External Email - Use Caution
>
> Dear Dan McCloy
>
> Thank you very much for the response.
>
> Indeed, after applying your recommendations, my epochs are no longer
> dropped.
>
> Many thanks.
>
> Best Regards
> A. Ighoyota ben
> Junior Researcher HCI (PhD in-view)
> Tallinn University, Estonia
> School of digital Technologies.
> On Fri, 24 Jul 2020 at 20:54, <mne_analysis-request at nmr.mgh.harvard.edu>
> wrote:
>
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> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of Mne_analysis digest..."
> >
> >
> > Today's Topics:
> >
> > 1. Re: Mne_analysis Digest, Vol 150, Issue 44 (Dan McCloy)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Fri, 24 Jul 2020 17:52:25 +0000
> > From: Dan McCloy <dan at mccloy.info>
> > Subject: Re: [Mne_analysis] Mne_analysis Digest, Vol 150, Issue 44
> > To: Discussion and support forum for the users of MNE Software
> > <mne_analysis at nmr.mgh.harvard.edu>
> > Message-ID:
> >
> >
> <dRFmRgmbpvIP98vsyaoCX2-mkltYZA9aOR-ecOdDFU7DSjmTymlqZntI79NCy0fzHN0E0ehHRWbl9K50-7CiScMib79Zh5eupoO9T5Tx94g=@
> > mccloy.info>
> >
> > Content-Type: text/plain; charset="utf-8"
> >
> > External Email - Use Caution
> >
> > It's hard to know for sure why Epochs are getting dropped because your
> > example code doesn't include the definition of `dataconv1` (nor
> > `event_id`). However, with your given code you are guaranteed to have the
> > first epoch get dropped, because your call to `make_fixed_length_events`
> > starts at zero, but you're trying to make epochs with `tmin=-0.2`. If
> your
> > first event is at time zero, there isn't any data before that, so the
> first
> > epoch will always get dropped with error "NO_DATA". If you change the
> > `start` parameter of `make_fixed_length_events` to be >0.2, that won't
> > happen.
> >
> > Here is a (simplified) version of your code that uses fake data (random
> > numbers); when I run this I see the first epoch dropped because "NO_DATA"
> > and the last epoch dropped because "TOO_SHORT", but the other 8 epochs in
> > the middle are retained. I skipped defining `picks` (your example was
> > picking all channels, which is the default anyway) and I skipped
> filtering
> > because I'm using fake data so there's no way to know from my code
> whether
> > filtering is influencing the epoch dropping of your real data.
> >
> > ```
> > import numpy as np
> > import mne
> > rng = np.random.default_rng()
> > channames = ['Cz','Fz','C3','C4','F3','F4','P7','P8']
> > ch_types = ['eeg','eeg','eeg','eeg','eeg','eeg','eeg','eeg']
> > sfreq = 250 # Hz for eeg
> > # fake data
> > dataconv1 = rng.normal(size=(len(channames), 40 * sfreq)) # 40 seconds of
> > data
> > # 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)
> > evenfile = mne.make_fixed_length_events(raw, id=1, start=0, stop=None,
> > duration=4.0, first_samp=True,
> > overlap=0.0)
> > event_id = dict(foo=1)
> > epochs = mne.Epochs(raw, evenfile, event_id=event_id, tmin=-0.2, tmax=4,
> > baseline=(-0.2, 0), event_repeated='drop',
> > proj=False, preload=True, reject_by_annotation=None)
> > print(epochs.drop_log)
> > ```
> >
> > -- dan
> > Daniel McCloy
> > https://dan.mccloy.info
> > Research Scientist
> > Institute for Learning and Brain Sciences
> > University of Washington
> >
> > ??????? Original Message ???????
> > On Friday, July 24, 2020 5:44 AM, Ben Ighoyota Ajenaghughrure <
> > ighoyota at tlu.ee> wrote:
> >
> > > 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](tel:+372%205832%206393)78794
> > > skype: ighoyota-ben
> > >
> > > On Fri, 24 Jul 2020 at 04:58, <
> mne_analysis-request at nmr.mgh.harvard.edu>
> > wrote:
> > >
> > >> Send Mne_analysis mailing list submissions to
> > >> mne_analysis at nmr.mgh.harvard.edu
> > >>
> > >> To subscribe or unsubscribe via the World Wide Web, visit
> > >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> > >> or, via email, send a message with subject or body 'help' to
> > >> mne_analysis-request at nmr.mgh.harvard.edu
> > >>
> > >> You can reach the person managing the list at
> > >> mne_analysis-owner at nmr.mgh.harvard.edu
> > >>
> > >> When replying, please edit your Subject line so it is more specific
> > >> than "Re: Contents of Mne_analysis digest..."
> > >>
> > >> 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"
> > >>
> > >> External Email - Use Caution
> > >>
> > >> 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"
> > >>
> > >> External Email - Use Caution
> > >>
> > >> 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
> > >>
> > >> To subscribe or unsubscribe via the World Wide Web, visit
> > >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> > >> or, via email, send a message with subject or body 'help' to
> > >> mne_analysis-request at nmr.mgh.harvard.edu
> > >>
> > >> You can reach the person managing the list at
> > >> mne_analysis-owner at nmr.mgh.harvard.edu
> > >>
> > >> When replying, please edit your Subject line so it is more specific
> than
> > >> "Re: Contents of Mne_analysis digest..."
> > >>
> > >> 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
> > ](mailto:
> > CAGu2niVV%2B79nq5Yu17B4VzB3PS71x7sFTy8HKNukDxnaDdi6hQ 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
> > >> -------------- next part --------------
> > >> An HTML attachment was scrubbed...
> > >> URL:
> > >> [
> >
> http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20200723/
> > >> a8812d4e/attachment-0001.html](
> >
> http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20200723/a8812d4e/attachment-0001.html
> > )
> > >>
> > >> ------------------------------
> > >>
> > >> 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
> > >>>>
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