[Mne_analysis] Differences between command line and python?

[Alexandre Gramfort]

ok

let's check at which step the difference appears.

Can you check that the evoked match by plotting them in Python?
Same question for the noise covariances

If they match let's look at the inverse computation but first please
check the above.

Alex





On Thu, Apr 7, 2016 at 6:42 PM, Cushing, Cody <CCUSHING1 at mgh.harvard.edu> wrote:
> Hi Alex,
>
> Thanks for the reply.  I'm happy to provide whatever additional details, I just didn't want to bloat the original email too much.
>
> So, I switched to 'meg=True' in my picks, but it didn't change the end result.  Also, just so its clear, I have all the mags listed in the bad channel file to essentially pick grads for the batch version, so all mags are excluded in both streams.
>
> And I do really want my tmax at 0.06 since there is a 60ms delay on our projector here, so time 0.06s is my true time 0s in the epoch. bmax is set at 0.06 in the .ave/.cov txt file as well (batch bmax equals python tmax for the covariance computation, yes? the .cov txt file has the user define the tmin/tmax of the epoch [-.03 1.0] as well as the bmin/bmax for the computation.
>
> Cheers,
> Cody
> ________________________________________
> From: mne_analysis-bounces at nmr.mgh.harvard.edu [mne_analysis-bounces at nmr.mgh.harvard.edu] on behalf of Alexandre Gramfort [alexandre.gramfort at telecom-paristech.fr]
> Sent: Thursday, April 07, 2016 12:18 PM
> To: Discussion and support forum for the users of MNE Software
> Subject: Re: [Mne_analysis] Differences between command line and python?
>
> I miss some details but at first sight meg='grad' could be the error.
> Can you try with meg='True'
>
> next test is to make sure you really want to do:
>
> cov=mne.compute_covariance(epochs, tmin=-0.03, tmax=0.06);
>
> and not
>
> cov=mne.compute_covariance(epochs, tmin=-0.03, tmax=0);
>
> to be checked in the .ave txt file you used with the command line.
>
> Alex
>
> On Thu, Apr 7, 2016 at 4:32 PM, Cushing, Cody <CCUSHING1 at mgh.harvard.edu> wrote:
>> Hi all,
>>
>> I've been noticing some pretty serious differences in dSPM values as I
>> transfer my dataset from the batch stream to the python stream.  I believe
>> these differences are related to the computation of the noise covariance
>> matrix.  Can anyone tell me the difference between implementing either of
>> these on the same raw file with the same bad channels marked and the same
>> events file:
>>
>> mne_process_raw --raw $rawfile1 --digtrig STI101 --projon --cov $covfile
>> --ave $avefile --events $eventfile --allevents --filteroff --saveavetag
>> "_cmdtest-ave" --savecovtag "_cmdtest-cov"
>>
>> with rejection parameters identical to below.  In the .ave & .cov files:
>> tmin, tmax = -0.03, 1.0  bmin, bmax = -.03, .06
>>
>> versus implementing this in python:
>>
>> picks = mne.pick_types(raw.info, meg='grad', eeg=False, stim=False,
>> eog=True,
>>                        include=include, exclude='bads')
>>
>> epochs = mne.Epochs(raw, events, event_id, tmin, tmax, picks=picks,
>>                     baseline=(-0.03, 0.06), reject=dict(grad=2000e-13,
>> eog=800e-6),
>>                     preload=False, proj=True)
>>     epochs.drop_bad_epochs()
>>
>> cov=mne.compute_covariance(epochs, tmin=-0.03, tmax=0.06);
>>     mne.write_cov(cov2save,cov);
>>
>> evoked =
>> [epochs['1'].average(),epochs['2'].average(),epochs['3'].average(),epochs['4'].average(),epochs['5'].average(),epochs['6'].average(),epochs['7'].average(),epochs['8'].average(),epochs['9'].average
>> (),epochs['10'].average(),epochs['11'].average(),epochs['12'].average()]
>>
>>    mne.write_evokeds(fname2save, evoked)  # save evoked data to disk
>>
>> Because as far as I can tell they seem to be doing the same thing?  But
>> there's some pretty stark differences in the SNR estimate and dSPM values
>> after putting both -ave.fif & -cov.fif files through the same fwd/inverse
>> solution commands based on the same source space for things as simple as the
>> initial response in the visual cortex (that I'd be happy to share with
>> whoever, I just wanted to make sure some silly option wasn't off that was
>> throwing everything off).
>>
>> Thanks for any help.
>>
>> Cheers,
>> Cody
>>
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