# Next we set invalid points (from telescope homing) to the avg_dc
moon.flatten_invalid_points()
plt.subplot(211)
plt.plot(moon["ha"], moon["volts"])
plt.xlabel(r"Hour angle [h]", fontsize=18)
plt.ylabel(r"Power", fontsize=18)
plt.subplot(212)
trans = np.fft.fft(moon["volts"])
freqs = np.fft.fftfreq(len(trans), 2. * np.pi * 1.0 / 86164.)
plt.plot(np.fft.fftshift(freqs), np.fft.fftshift(abs(trans)**2))
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"]
plt.xlabel(r"Hour angle [h]", fontsize=18)
plt.ylabel(r"Power", fontsize=18)
plt.subplot(212)
trans = np.fft.fft(crab["volts"])
freqs = np.fft.fftfreq(len(trans), 2. * np.pi * 1.0 / 86164.)
plt.plot(np.fft.fftshift(freqs), np.fft.fftshift(abs(trans)**2))
plt.xlabel(r"Frequency [rad$^{-1}$]", fontsize=18)
plt.ylabel(r"Power", fontsize=18)
# First we set invalid points (from telescope homing) to the avg_dc
crab.flatten_invalid_points()
crab["volts_orig"] = crab["volts"]
# Next we find the min and max fringe frequencies that we expect to see in the data
# divide it into chunks since the fringe frequency changes over time
local_fringe_frequencies = fringe_freq(10.0, wl, OBJECTS["3C144"]["dec"], 2.*np.pi*crab["ha"]/24.)
min_freq = np.min(abs(local_fringe_frequencies))
# min_freq = 40.0 # rad^-1 (seen by eye as the limit of good data)
max_freq = np.max(abs(local_fringe_frequencies))
catalog_dec = OBJECTS["3C144"]["dec"]
'''
s2s2 = []
Y_s2 = []
a2s = []
B_to_try = np.arange(5.0, 15.0, 0.01)
for baseline in B_to_try:
a, Y_, s2, cov = fit_components(crab["ha"], crab.normed, #crab["volts"],
lambda ha: np.cos(2*np.pi*(baseline/wl) * np.cos(catalog_dec) * np.sin(2.*np.pi*ha/24.)),
lambda ha: - np.sin(2*np.pi*(baseline/wl) * np.cos(catalog_dec) * np.sin(2.*np.pi*ha/24.))
