We have sets of ADC data collected with different front-end filters at acquisition; given an empirically determined roll off in dB/octave or dB/Hz, I'd like to perform equalization (in this case the low frequencies) and I know from sweeps that roll off begins under ~200Hz and -3dB is ~15Hz.

One general example is Bank's algorithm:
http://nullege.com/codes/show/src@p@o@porc-HEAD@porc.py
where people correct sound for their room acoustics.
There is also the Nelson-Kirkeby inverse filter methodology.

Our specific case is flattening the response due to a single-pole RC high-pass filter so I think remez() might be just fine; can anyone here supply links or examples in scipy to this application of remez()?
I'm guessing
scipy.signal.remez(

2,

range(.625, 512, .625),

desired= <inverse of measured gain, range(.625, 256, .625)>,

weight=<unsure of this...>,

Hz=1024,

type=<unsure, what to use for high-pass?>,

maxiter=25,

grid_density=16

)

- Ray