when using the lowpassfilter.py code you can see from the pulsed data, and increase in frequency that there is a limit to how good of filtering we can do and get a quick enough response for data to be useful.

here is a second set of python code called bandpassfilterwdetectionofstability.py that can detect when a signal is stable and not changing more than a set percentage. from this data graph it can be seen that when a lot of filtering is done, even though there is no noise, it takes a long long time for sample to stabilize, and in the 100x filtering the signal rarely stabilizes within the times allowed for in simulation.