FIRフィルター係数の計算 / array(0 to TAPS - 1)(COEFF_WIDTH

import scipy.signal
import numpy as np
"""
構文: scipy.signal.firwin(numtaps, cutoff, width=None, window='hamming', pass_zero=True, scale=True, nyq=None, fs=None)

pass_zero: True, False, 'bandpass', 'lowpass', 'highpass', 'bandstop'

window :
    boxcar, triang        , blackman, hamming , hann  , bartlett   , flattop, parzen, 
    bohman, blackmanharris, nuttall , barthann, cosine, exponential, tukey  , taylor, 
    kaiser (needs beta)                          , gaussian (needs standard deviation), 
    general_cosine (needs weighting coefficients), general_gaussian (needs power, width), 
    general_hamming (needs window coefficient)   , dpss (needs normalized half-bandwidth), 
    chebwin (needs attenuation)}
"""
COEFF_WIDTH = 4
NUM_COEFFS  = 11
SAMPLE_FREQ = 100
CUT_OFFS    = [10, 20]
FILTER_TYPE = "bandpass"
WINDOW      = "hamming"

#係数を計算して、
coeffs = scipy.signal.firwin(NUM_COEFFS, CUT_OFFS, window=WINDOW, pass_zero=FILTER_TYPE, scale=True, fs=SAMPLE_FREQ)
print(*coeffs, sep=',')

#係数が範囲(-1≦ 係数 < 約1)を超えていないか確かめて、
print("No Good")  if len(coeffs[coeffs < -1]) + len(coeffs[coeffs > 1 - 1/2**(COEFF_WIDTH - 1)]) else print("IS OK")

#係数を固定小数点数化(整数化。符号に1ビット、整数部なし、残りを小数ビットに割り当て)して、
coeffs = np.asarray(np.round(coeffs * 2**(COEFF_WIDTH - 1)), dtype=np.int64)
print(*coeffs, sep=",")

#それが負数であったら2の補数にずらして、
coeffs = np.asarray(np.where(coeffs < 0, coeffs + 2**COEFF_WIDTH, coeffs), dtype=np.uint64)
print(*coeffs, sep=",")

#array(0 to TAPS - 1)(COEFF_WIDTH - 1 downto 0)の形に体裁を整えて出力する。
print("(", end="")
print(*["(" + str(COEFF_WIDTH) + 'd"' + str(coeff) + '")' for coeff in coeffs], sep=",\n", end=")")

-3.703826560324038e-18,-0.04068736077594257,-0.12858579923434713,-0.07806890642738276,0.20878284966338043,0.3958935452581824,0.20878284966338043,-0.07806890642738276,-0.12858579923434713,-0.04068736077594257,-3.703826560324038e-18
IS OK
0,0,-1,-1,2,3,2,-1,-1,0,0
0,0,15,15,2,3,2,15,15,0,0
((4d"0"),
(4d"0"),
(4d"15"),
(4d"15"),
(4d"2"),
(4d"3"),
(4d"2"),
(4d"15"),
(4d"15"),
(4d"0"),
(4d"0"))