from __future__ import division
from scipy import signal

fig, axs = subplots(2,1,sharex=True)
subplots_adjust( hspace = .2 )
fig.set_size_inches((5,5))

t_fir_coeff = [0.01665389596732681,
  0.07353658710395161,
  0.10040345335534452,
  0.04751332314075821,
  -0.06317967799551721,
  -0.09143711477971043,
  0.06319322564548596,
  0.31257963657965065,
  0.43524399610103215,
  0.31257963657965065,
  0.06319322564548596,
  -0.09143711477971043,
  -0.06317967799551721,
  0.04751332314075821,
  0.10040345335534452,
  0.07353658710395161,
  0.01665389596732681]

# Default si coefficients
si_default_fir_coeff = [0x1, 0x3, 0x8, 0x11, 0x21, 0x36, 0x4d, 0x60, 0x67]

# Reflects an array of coefficients about the last element
def sym_fir_coeff(coeff):
    for i in range(len(coeff)-2, -1, -1):
        coeff.append(coeff[i])

    return coeff
# Normalises the si's 8-bit coefficients to 0 - 1
def si_normalise_coeff(coeff):
    return [x / 0x300 for x in coeff]

si_default = si_normalise_coeff(sym_fir_coeff(si_default_fir_coeff))

print si_default
print len(si_default)

fir_coeff = si_default

ax=axs[0]
w,h=signal.freqz(fir_coeff,1) # Compute impulse response
ax.plot(w,20*log10(abs(h)))
ax.set_ylabel(r"$20 \log_{10} |H(\omega)| $",fontsize=18)
ax.grid()

ax=axs[1]
ax.plot(w,angle(h)/pi*180)
ax.set_xlabel(r'$\omega$ (radians/s)',fontsize=18)
ax.set_ylabel(r"$\phi $ (deg)",fontsize=18)
ax.set_xlim(xmax = pi)
ax.grid()