I don't find it confusing that this didn't work with Python, but I do find it confusing that it worked with Matlab.
CIC filters don't work with floating point numbers.
UPDATE:
Interestingly, at least with the version of scipy I have, lfilter doesn't work with integer arrays -- I get a NotImplemented error. Here is a numpy version of a CIC filter that is about twice as fast as a pure Python implementation on my machine:
# Implements an in-memory CIC decimator using numpy.
from math import log
from numpy import int32, int64, array
def cic_decimator(source, decimation_factor=32, order=5, ibits=1, obits=16):
# Calculate the total number of bits used internally, and the output
# shift and mask required.
numbits = order * int(round(log(decimation_factor) / log(2))) + ibits
outshift = numbits - obits
outmask = (1 << obits) - 1
# If we need more than 64 bits, we can't do it...
assert numbits <= 64
# Create a numpy array with the source
result = array(source, int64 if numbits > 32 else int32)
# Do the integration stages
for i in range(order):
result.cumsum(out=result)
# Decimate
result = array(result[decimation_factor - 1 : : decimation_factor])
# Do the comb stages. Iterate backwards through the array,
# because we use each value before we replace it.
for i in range(order):
result[len(result) - 1 : 0 : -1] -= result[len(result) - 2 : : -1]
# Normalize the output
result >>= outshift
result &= outmask
return result