) matplotlib.rc('font', **font) B = 10.06 wl = 3e8 / 10.67e9 datafile = "../data/sun-4_3_2014-22.npz" logfile = "../data/logs/sun-4_3_2014-22-log" sun = Analyzer(datafile, logfile, dt=1.0) # First we will remove that raised section at the end (starts at index 26000) sun.slice(0, 26000) # Next we set invalid points (from telescope homing) to the avg_dc sun.flatten_invalid_points() plt.subplot(211) plt.plot(sun["ha"], sun["volts"]) plt.xlabel(r"Hour angle [h]", fontsize=18) plt.ylabel(r"Power", fontsize=18) plt.subplot(212) trans = np.fft.fft(sun["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, sun["dec"], 2.*np.pi*sun["ha"]/24.)
obs.long = np.deg2rad(-122.2573) obs.date = ephem.date("2014-04-06 20:12:45") damoon.compute(obs) for i, lst in enumerate(moon["lst"]): moon["ra"][i] = 24. * damoon.ra / (2. * np.pi) moon["dec"][i] = np.rad2deg(damoon.dec) obs.date += 1. / 86164. damoon.compute(obs) moon.data["ha"] = moon.data["lst"] - moon.data["ra"] moon.data["ha"] -= (24.0 * (moon.data["ha"] > 12.0)) moon.slice(0, len(moon["volts"])-5000) # 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))
crab = Analyzer(datafile, logfile, dt=1.0, ra=24. * OBJECTS["3C144"]["ra"] / (2. * np.pi)) plt.subplot(211) plt.plot(crab["ha"], crab["volts"]) 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 = []