使用BeagleBone Black上的numpy（不是scipy！）编程一个butterworth过滤器

Question

I am a new user of Python and an amateur programmer in general - I am hoping to be able to filter a signal using just the numpy library. It will be programmed onto a BeagleBone Black and the OS is Angstrom Linux, so the furthest numpy library it will update to is 1.4 and due to either rumored data limitations (I am not actually sure how to check) or just the version of numpy being too early, scipy will not work on the board.

So the first solution is to get a new operating system but I would not know where to start; I am more comfortable in the realm of putting equations into a program.

I was hoping to use the filtfilt function but maybe it would be best to start with lfilter. This site seemed helpful for implementing it but it is a bit beyond me: http://docs.scipy.org/doc/scipy-0.13.0/reference/generated/scipy.signal.lfilter.html
I am capable of getting the filter coefficients in MATLAB then transferring them to the BeagleBone. The x is just the array that is my signal which I can upload.

The second section is a bit of a jump - so is there a way to perform a z-transform in just numpy, not scipy? Also, based on all of the secrecy of the filter algorithm in MATLAB, I do not have faith in working that out, but is there some sort of mathematical algorithm description, or better yet code, describing how I may accomplish this?

Thanks for your patience in reading through this and the response. Please do not use complicated language in the response!

-Rob

Answer 1

For the filter design functions, you can copy the code from sicpy.signal.filter_design.py, they are almost pure python code.

But to do lfilter for IIR filters, you need a for loop for every sample in the data array. Since for loop in Python is slow, I think you need to implement it in C, and call it throught ctypes. Do you have ac compile in the target machine?

If you can design your filter as a FIR filter, then you can use numpy.convolve(b, x) .