[Mne_analysis] Fwd: epochs baseline problem (pandas dataframe indexing?)

[Jaakko Leppäkangas]

Hi Tristan,
seems like a typo. You have baseline defined as `(-1, -.05)`, but in the
function call you use `baseline=(-.5,.05)`. Just change that to
`baseline=baseline`.


On 14 April 2016 at 03:27, Nakagawa Tristan T <
nakagawa-t at ifrec.osaka-u.ac.jp> wrote:

>
> Hi,
>
> is the baselining limited to certain kinds of channels?
> I can't get it to work right for physiology (emg,ecg), the means aren't
> 0 for the baseline period.
>
> Here the details:
> I have this raw file:
> https://www.dropbox.com/s/6t4z52tno5tl228/raw.fif?dl=0   (1GB!)
> and I create epochs with the below code, baseline correcting it.
>
> It may also be related to a possible bug or something I'm doing wrong in
> pandas dataframe indexing, see here:
>
> http://stackoverflow.com/questions/36589702/pandas-dataframe-row-multiindex-skip-one/36590006#36590006
>
> Thanks for any input.
> best,
> Tristan
>
> -----------------------------------
>
> import pandas as pd
> import numpy as np
> import matplotlib.pyplot as plt
> import mne
> import scipy.signal as signal
>
> # load data
> raw = Raw('raw.fif', preload = True) #load Data
> raw._first_samps[0]=0 # From my older question, I still need this..
> mne.channels.rename_channels(raw.info,{'BIO003':'emg1','BIO004':'emg2',
>                                        'BIO005':'emg3','BIO006':'emg4',
>                                        'BIO007':'emg5','BIO008':'ecg'})
>
> raw.set_channel_types({'emg1':'emg','emg2':'emg','emg3':'emg','emg4':'emg','emg5':'emg','ecg':'ecg'})
> picks_emg = mne.pick_types(raw.info,emg=True)
> # preprocess emg signals: hilbert envelope!
> raw.filter(10, 150, picks=picks_emg)
>
> # For viewability, I put the events below, load them first!
>
> # Create & save Epochs
> event_id = dict(CS=1, OS=2, NS=3)
> tmin = -1.1  # start of each epoch
> tmax = 6 # end of each epoch
> baseline = (-1, -.05) # in seconds
> epochs = mne.Epochs(raw,events, event_id, tmin=tmin, tmax=tmax,
> proj=False, picks=[0,1,2,3,4,5],
>                     baseline=(-.5,.05), preload=True,reject=None)
>
> # Confirm that mean for baseline period is 0:
> test=epochs['CS'].to_data_frame()
> # mean=test.loc[idx['CS',:, -1000:-50], :].mean() # doesn't work, see
> stackoverflow link!
> mean=test.loc[idx['CS',test.index.levels[1], -1000:-50], :].mean()
> print(mean)
>
> # events
> events=np.array([[ 11527,      0,      1],
>        [ 22344,      0,      2],
>        [ 31541,      0,      3],
>        [ 42542,      0,      2],
>        [ 52757,      0,      3],
>        [ 61972,      0,      1],
>        [ 71586,      0,      3],
>        [ 81785,      0,      3],
>        [ 92786,      0,      3],
>        [103803,      0,      3],
>        [113000,      0,      3],
>        [124001,      0,      2],
>        [135018,      0,      2],
>        [145016,      0,      2],
>        [155616,      0,      2],
>        [164830,      0,      3],
>        [174629,      0,      2],
>        [185629,      0,      1],
>        [196245,      0,      3],
>        [207246,      0,      2],
>        [217645,      0,      1],
>        [226659,      0,      1],
>        [237459,      0,      2],
>        [248476,      0,      1],
>        [258875,      0,      1],
>        [269475,      0,      1],
>        [280091,      0,      1],
>        [289890,      0,      3],
>        [300289,      0,      1],
>        [309503,      0,      2],
>        [319903,      0,      1],
>        [328900,      0,      1],
>        [338515,      0,      3],
>        [347512,      0,      2],
>        [356726,      0,      2],
>        [367526,      0,      3],
>        [377926,      0,      2],
>        [387540,      0,      2],
>        [398557,      0,      3],
>        [407571,      0,      3],
>        [417370,      0,      1],
>        [427168,      0,      2],
>        [437784,      0,      1],
>        [448384,      0,      3],
>        [457782,      0,      1],
>        [467797,      0,      1],
>        [477596,      0,      1],
>        [488012,      0,      2],
>        [498411,      0,      3],
>        [509011,      0,      3],
>        [518626,      0,      2],
>        [529025,      0,      3],
>        [539425,      0,      3],
>        [548639,      0,      2],
>        [557836,      0,      2],
>        [567835,      0,      3],
>        [578852,      0,      1],
>        [588450,      0,      1],
>        [598666,      0,      1],
>        [608064,      0,      2]])
>
>
>
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