plt.xlabel(r"Frequency [rad$^{-1}$]", fontsize=18)
plt.ylabel(r"Power", fontsize=18)
# Now we remove the dc offset, as well as high frequency noise
local_fringe_frequencies = fringe_freq(B, wl, moon["dec"], 2.*np.pi*moon["ha"]/24.)
bandpass = FourierFilter(min_freq=0.001, max_freq=max(local_fringe_frequencies))
# moon["volts"] = np.real(bandpass(moon["t"], moon["volts"])[1])
moon.flatten_invalid_points()
# moon["volts"] = moon.real_boxcar(200)
moon["volts"] = np.load("moonshine.npz")["volts"]
plt.figure()
plt.plot(moon["ha"], moon["volts"])
plt.xlabel(r"Hour angle [h]", fontsize=18)
plt.ylabel(r"Power", fontsize=18)
plt.plot(moon["ha"], moon.envelope(50))
'''
mooncopy = moon.copyslice(3600, 7100)
mooncopy["ha"] = mooncopy["ha"]
positive_values = mooncopy["volts"] >= 0.0
enveloper = FourierFilter(max_freq=0.01)
_, envelope = enveloper(mooncopy["t"], mooncopy["volts"] * positive_values)
phi_to_try = np.arange(0.0, np.pi, np.pi/300.)
s2s = []
Y_s = []
a_s = []
Y_ = Y_s[np.argmin(s2s)]
print C1, C2, C3
ha1 = (-C2 + np.sqrt(C2**2. - 4*C1*C3)) / (2.*C3)
ha2 = (-C2 - np.sqrt(C2**2. - 4*C1*C3)) / (2.*C3)
print ha1
print ha2
'''
minima_spots = [(500, 4000), (4500, 7500), (21000, 23000), (24500, 25550)]
obs_zeros = []
plottypairs = []
for start, end in minima_spots:
# Cut out a small window around the guessed envelope
# fit a quadratic to find minima
(C1, C2, C3), Y_, s2, cov = fit_components(sun["ha"][start: end], sun.envelope(50)[start:end],
lambda ha: ha ** 2,
lambda ha: ha,
lambda ha: 1,
)
plottypairs.append((sun["ha"][start:end], Y_))
vertex = -C2 / (2. * C1)
obs_zeros.append(vertex)
'''
_, aa = zip(*sorted(zip(b, a)))
min_ha = aa[0]
obs_zeros.append(min_ha)
print "found", min_ha
plottypairs.append((a, b))
