digital-filter

I have a continuous value for which I'd like to calculate an exponential moving average . Normally I'd just use the standard formula for this: S n = αY + (1-α)S n-1 where S n is the new average, α is the alpha, Y is the sample, and S n-1 is the previous average. Unfortunately, due to various issues I don't have a consistent sample time. I may know I can sample at the most, say, once per millisecond, but due to factors out of my control, I may not be able to take a sample for several milliseconds at a time. A likely more common case, however, is that I simple sample a bit early or late: instead

UPDATE: I found a Scipy Recipe based in this question! So, for anyone interested, go straight to: Contents » Signal processing » Butterworth Bandpass I'm having a hard time to achieve what seemed initially a simple task of implementing a Butterworth band-pass filter for 1-D numpy array (time-series). The parameters I have to include are the sample_rate, cutoff frequencies IN HERTZ and possibly order (other parameters, like attenuation, natural frequency, etc. are more obscure to me, so any "default" value would do). What I have now is this, which seems to work as a high-pass filter but I'm no