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SNR in calculation in `add_noise_evoked` might be incorrect

See original GitHub issue

I’m trying to see how the data is scaled to achieve a given SNR in add_noise_evoked in mne-python/mne/simulation/evoked.py, but do not really get it.

The SNR in this function is defined as the standard SNR in dB, which is:

SNR = 10 * log10 [ var(signal) / var(noise) ]

The piece of code that should do this is:

tmp = 10 * np.log10(np.mean((evoked.data[:, tmask] ** 2).ravel()) / np.mean((noise.data ** 2).ravel()))
noise.data = 10 ** ((tmp - float(snr)) / 20) * noise.data

However, I am think that it should be instead:

tmp =  np.log10(np.mean((evoked.data[:, tmask] ** 2).ravel()) / np.mean((noise.data ** 2).ravel()))
noise.data = 10 ** (tmp - float(snr) / 10) * noise.data

Is this a bug, or am I missing something?

Issue Analytics

State:
Created 7 years ago
Comments:7 (7 by maintainers)

Top GitHub Comments

1reaction

clamuscommented, Jun 13, 2016

Should I go ahead and fix this?

0reactions

agramfortcommented, Jun 15, 2016

lol 😃

yes please just add a test but don’t update what’s new

thx

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