[SciPy-User] inverse filter design, remez?

[R Schumacher]

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>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 
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