[Mne_analysis] Fwd: [Martinos-python] .drop_bad problem

Elena Orekhova orekhova.elena.v at gmail.com
Wed Feb 6 06:35:19 EST 2019
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        External Email - Use Caution        

*Dear Alexandre and Alexander,*

I also fwd this message to the mne_analysis at nmr.mgh.harvard.edu


Results of .drop_bad in v 0.16.2 (python 3.6.6) and .drop_bad_epochs in
0.12.dev (python 2.7.6) are different.

This is not filtering. I tested performance of the  .drop_bad in v 0.16.2
(python 3.6.6) and .drop_bad_epochs in  0.12.dev (python 2.7.6) without any
additional operations on the data.  Result is clearly different! The
difference, however, starts only after the 25th epoch.



I did:


*data=epochs_rej.get_data() *


*average_over_epoch=np.mean(np.mean(data [:, 0:306, :], 2),1) *

The  ‘*average_over_epoch*’ is exactly the same in both versions up to the
25th epoch, but is absolutely different afterwards.



I uploaded the epoches and the corresponding raw files:


 https://we.tl/t-Rmfow2yf2k

and

https://we.tl/t-N69ztC2qtt



Best regards,
Elena


---------- Forwarded message ---------
From: Alexandre Gramfort <alexandre.gramfort at telecom-paristech.fr>
Date: Tue, 5 Feb 2019 at 22:40
Subject: Re: [Martinos-python] .drop_bad problem
To: Rockhill, Alexander P. <AROCKHILL at mgh.harvard.edu>
Cc: Elena Orekhova <orekhova.elena.v at gmail.com>


hi,

you should ask such questions on the MNE mailing list:

https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis

it could be due to the change in default parameters for filtering if you
apply any.

my 2c

Alex


On Tue, Feb 5, 2019 at 7:54 PM Rockhill, Alexander P. <
AROCKHILL at mgh.harvard.edu> wrote:

> Hi Elena,
>
>
>    What do you mean by the real order of the epochs was different? It may
> be helpful share the output of epochs.events before and after using
> .drop_bad for both versions.
>
>
> Best,
>
>
> Alex
>
>
> Translational NeuroEngineering Laboratory
> Division of Neurotherapeutics, Department of Psychiatry
> Massachusetts General Hospital, Martinos Center
> 149 13th St Charlestown #2301, Boston, MA 02129
> ------------------------------
> *From:* martinos-python-bounces at nmr.mgh.harvard.edu <
> martinos-python-bounces at nmr.mgh.harvard.edu> on behalf of Elena Orekhova <
> orekhova.elena.v at gmail.com>
> *Sent:* Tuesday, February 5, 2019 12:43:25 PM
> *To:* martinos-python at nmr.mgh.harvard.edu
> *Subject:* [Martinos-python] .drop_bad problem
>
>
>         External Email - Use Caution
>
> Dear experts,
>
> I moved from MNE version 0.12.dev0 (Python:  2.7.6 | 64-bit |)  to mne
> version 0.16.2 (3.6.6 |Anaconda, Inc.|) and noticed a problem.
>
> There was a difference in the result after applying
>
> epochs.drop_bad (reject=reject, flat=flat) in the two MNE versions.
>
>
>
> Although the number and the order of the events left after applying
> ‘.drop_bad’ (or ‘.drop_bad_epochs’ in 0.12.dev0) was exactly the same in
> the two MNE versions,  the real order of the epochs was different.  Inspection
> of the results suggests that the error is in the 0.16.2, not 0.12.dev0
>
>
>
> Below is the information about software I used.
>
>
>
> Best regards,
>
> Elena
>
>
>
> ###########################
>
> *mne:           0.12.dev0:*
>
> mne.sys_info()
>
> Platform:      Darwin-18.2.0-x86_64-i386-64bit
>
> Python:        2.7.6 | 64-bit |
>
> (default, Sep 15 2014, 17:43:19) [GCC 4.2.1 (Apple Inc. build 5666) (dot
> 3)]
>
> Executable:    /Users/elena/Library/Enthought/Canopy_64bit/
> User/bin/pythonw
>
> *mne:           0.12.dev0 *
>
> numpy:         1.10.4
>
> {lapack=mkl_lapack95_lp64, blas=mkl_intel_lp64}
>
> scipy:         0.17.0
>
> matplotlib:    1.4.2
>
> sklearn:       0.17
>
> nibabel:       2.0.1
>
> nitime:        Not found
>
> mayavi:        4.4.3
>
> nose:          1.3.4
>
> pandas:        0.15.2
>
> pycuda:        Not found
>
> skcuda:        Not found
>
>
>
> ###########################
>
> *mne:           0.16.2: *
>
> mne.sys_info()
>
> Platform:      Darwin-18.2.0-x86_64-i386-64bit
>
> Python:        3.6.6 |Anaconda, Inc.|
>
> (default, Jun 28 2018, 11:07:29)
>
> [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]
>
> Executable:    /Users/elena/anaconda3/envs/mne/bin/python
>
> CPU:           i386: 4 cores
>
> Memory:        16.0 GB
>
> mne:           0.16.2
>
> numpy:         1.15.2 {blas=mkl_rt, lapack=mkl_rt}
>
> scipy:         1.1.0
>
> matplotlib:    3.0.0 {backend=Qt5Agg}
>
> sklearn:       0.20.0
>
> nibabel:       2.3.1
>
> mayavi:        4.6.2 {qt_api=pyqt5}
>
> pycuda:        Not found
>
> skcuda:        Not found
>
> pandas:        0.23.4
>
>
>
>
>
> _______________________________________________
> martinos-python mailing list
> martinos-python at nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/martinos-python



-- 
Best regards,
Elena V. Orekhova
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