Feature request: Subtract trace in decibels

Antti Huovilainen

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May 15, 2017
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Hi,

Another low hanging fruit:
Add feature to calculate dB(A) - dB(B). This should be trivial to implement and would be useful to separate the effects of comb filtering / modal ringing (can't be compensated with EQ above 100 Hz) from general tonality (can largely be compensated with EQ).
 
That's largely what A/B produces, albeit taking phase into account. Can you give some example data illustrating the use you have in mind?
 
In that case, it appears that A/B has a bug that makes it unusable if the first response is original but the second response has been generated by averaging. In that case the resulting response is at -240 dB for all points (or a NaN is interpreted as -240 dB).

My use cases are comparing the difference between L & R (to see if the tonality differs too much) and for visualizing the amount of ripple vs tonality (subtract third octave averaged response from the original) .
 
In that case, it appears that A/B has a bug that makes it unusable if the first response is original but the second response has been generated by averaging. In that case the resulting response is at -240 dB for all points (or a NaN is interpreted as -240 dB).
Behaves as expected for me, no odd results. Can you post an mdat file with data that shows that problem?
 
Here's an mdat which shows the problem.
I applied Psychoacoustic smoothing to L1, pressed "Average the Responses" (with only L1 selected), then chose the "A / B" trace arithmetic with L1 as A and Average as B. Resulting response is -240 dB at all points.
 

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Thanks, problem occurs when the B trace is 96 PPO log spaced and the A trace is linear spaced. If you swap the order of A and B it will work OK, or turn off the option to allow 96 PPO log spacing in the analysis preferences before producing the average. Either highlights a different bug though in that the ratio of a smoothed measurement to the magnitude-only average derived from it isn't the 0 dB flat line it should be. A workaround for that is to use a vector average (or a vector sum which is easier for multiple measurements) instead. I'll address both issues at the weekend.
 
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