Comments (2)
Perhaps this is a result of the hardcoded
if np.isnan(power[0]) or np.isinf(power[0]):
power[0] = 0
where that condition only happens sometimes. Should the forced behavior be different when center_data=False
?
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I believe the desired power at f = 0 is
power[0] = np.mean(y ** 2 - (y - np.mean(y)) ** 2) / np.mean(y ** 2)
I'll open a pull request.
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