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I don't know what to call this filter, but I've been thinking of a log10 filter that preserves signs for quite some time.
sign = np.sign(data) minval = 4 data = np.clip(np.log10(np.abs(data) + 10**(-minval)) + minval, 0, None) * sign
In this case, 1e-4 would be the smallest perceptible value and it would scale in log10 in both directions afterward.
This preserves the positive/negative directionality (as opposed to abslog) but still converts it to a dB-like scale. Very good for visualization!
The text was updated successfully, but these errors were encountered:
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I don't know what to call this filter, but I've been thinking of a log10 filter that preserves signs for quite some time.
In this case, 1e-4 would be the smallest perceptible value and it would scale in log10 in both directions afterward.
This preserves the positive/negative directionality (as opposed to abslog) but still converts it to a dB-like scale. Very good for visualization!
The text was updated successfully, but these errors were encountered: