Automatic scaling while loading single channel data about visbrain

[EtienneCmb]

GitMate.io thinks a possibly related issue is #7 (Add .rec loading capability).

[EtienneCmb]

@raphaelvallat I think this a part of your code, can you take a look at it?

[raphaelvallat]

Hi @skjerns
Yes, I agree that the current implementation is not adequate for the two situations that you describe. Plus, I also think that the ptp might sometimes be biased in cases of very strong artefacts. As a more robust check, we could use the interquartile range (scipy.stats.iqr) and check for each individual channel:

# Assume that the inter-quartile amplitude of EEG data is ~50 uV
from scipy.stats import iqr
iqr_data = iqr(data, axis=1)

for idx_chan, iqr_chan in enumerate(iqr_data):
    if iqr_chan < 1:
        mult_fact = np.floor(np.log10(50 / iqr_chan))
        warn("Wrong channel data amplitude. Multiplying data amplitude by 10^%i" % mult_fact)
        data[idx_chan, :] *= 10 ** mult_fact

If you have any ideas for a better check, please feel free to create a PR!
Thanks

[skjerns]

I think this is a good solution for now, and should cover most cases.

I suspect that there might be some problems however in case of non-EEG data (like Heartrate or temperature), but don't have a sample file right now to check it.

PR is created #33