[Mne_analysis] downsampling in bdf file

[Alexandre Gramfort]

it's possible that mne-python resamples the stim channel as it does
not know it's a stim channel.

it you confirm the bug please share the file so we can fix asap

Alex


On Wed, Jan 14, 2015 at 9:46 PM, Liu Mengting <bigting84 at gmail.com> wrote:
> Ya, I opened it with matlab, see the events, there appears some more event
> (probably twice more), but the original events are well kept (both the
> temporal point and event id are both kept). However in MNE, it appears 100
> times more events than there should be and all their temporal order and
> events id are both messed up.
>
> There is also a error as below:
>
> ValueError: You have 77499 events shorter than the shortest_event.
> These are very unusual and you may want to set min_duration to a larger
> value e.g. x / raw.info['sfreq']. Where x = 1 sample shorter than the
> shortest event length.
>
>
> Thanks,
>
> Mengting
>
> 2015-01-14 15:31 GMT-05:00 Eric Larson <larson.eric.d at gmail.com>:
>
>> I'm not familiar with the edfbrowser routines, but if they use standard
>> low-pass-downsample methods instead of a zero-order hold for the stimulus
>> channel, the low-pass filter ringing will produce many errant events. When
>> you say that you tested the file using MATLAB, you mean that you opened it?
>> Did you look at the stimulus channel to see if the resampling introduced
>> ringing?
>>
>> Cheers,
>> Eric
>>
>>
>> On Wed, Jan 14, 2015 at 12:24 PM, Liu Mengting <bigting84 at gmail.com>
>> wrote:
>>>
>>> Hi MNE users,
>>>
>>> I am tring to use MNE python to process the bdf EEG file. Since our data
>>> is huge, so I first downsampled using the edfbrowser which is a bdf
>>> processing software, then I loaded the downsampled data using
>>> read_raw_edf(), but I found that the STI channel was totally messed up, I
>>> can find far more events than there should be.
>>>
>>> To make sure the file is good, I tested using matlab and everything works
>>> well, do you guys have any idea what is going on please?
>>>
>>> Thanks and appreciate,
>>>
>>> Mengting
>>>
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