def main_arg(x, y, grid_count):
print grid_count
ofac = 4
#average dt of entire time series
diffs = [x[i + 1] - x[i] for i in range(len(x) - 1)]
avgdt = np.average(diffs)
#make time start from 0
x_from0 = modules.phase_start_correct(x)
periods, mag, ph, fr, fi, amp_corr = modules.take_lomb(
x_from0, y, ofac, avgdt)
#get mean of values
mean_array = np.average(y)
#correct magnitude and phase for spectral leakage
zoomfact = 1000
half_annual_mag, half_annual_phase = modules.periodic_interp(
fr, fi, zoomfact, periods, 365.25 / 2., len(y), amp_corr)
annual_mag, annual_phase = modules.periodic_interp(fr, fi, zoomfact,
periods, 365.25, len(y),
amp_corr)
#correct for phase shift as data starts in Oct 2004
n_off = 273.25
if n_off > 365.25 / 2:
n_off = n_off - (365.25 / 2)
offset = ((np.pi * 2) / (365.25 / 2)) * n_off
half_annual_phase = half_annual_phase + offset
if half_annual_phase > np.pi:
half_annual_phase = -np.pi + (half_annual_phase - np.pi)
n_off = 273.25
offset = ((np.pi * 2) / (365.25)) * n_off
annual_phase = annual_phase + offset
if annual_phase > np.pi:
annual_phase = -np.pi + (annual_phase - np.pi)
#convert phase to time
half_annual_phase = modules.convert_phase_units_actual_single(
half_annual_phase, 6)
annual_phase = modules.convert_phase_units_actual_single(annual_phase, 12)
#np.save('mags_phases/mag_spectrums/%i'%(grid_count),mag)
#np.save('mags_phases/phase_spectrums/%i'%(grid_count),ph)
#np.save('mags_phases/periods',periods)
return (half_annual_mag, half_annual_phase, annual_mag, annual_phase,
mean_array)
def main_arg(x,y,grid_count):
print grid_count
ofac = 4
#average dt of entire time series
diffs = [x[i+1]-x[i] for i in range(len(x)-1)]
avgdt = np.average(diffs)
#make time start from 0
x_from0 = modules.phase_start_correct(x)
periods,mag,ph,fr,fi,amp_corr = modules.take_lomb(x_from0,y,ofac,avgdt)
#get mean of values
mean_array = np.average(y)
#correct magnitude and phase for spectral leakage
zoomfact = 1000
half_annual_mag,half_annual_phase = modules.periodic_interp(fr,fi,zoomfact,periods,365.25/2.,len(y),amp_corr)
annual_mag,annual_phase = modules.periodic_interp(fr,fi,zoomfact,periods,365.25,len(y),amp_corr)
#correct for phase shift as data starts in Oct 2004
n_off = 273.25
if n_off > 365.25/2:
n_off = n_off-(365.25/2)
offset = ((np.pi*2)/(365.25/2))*n_off
half_annual_phase = half_annual_phase + offset
if half_annual_phase > np.pi:
half_annual_phase = -np.pi + (half_annual_phase - np.pi)
n_off = 273.25
offset = ((np.pi*2)/(365.25))*n_off
annual_phase = annual_phase + offset
if annual_phase > np.pi:
annual_phase = -np.pi + (annual_phase - np.pi)
#convert phase to time
half_annual_phase = modules.convert_phase_units_actual_single(half_annual_phase,6)
annual_phase = modules.convert_phase_units_actual_single(annual_phase,12)
#np.save('mags_phases/mag_spectrums/%i'%(grid_count),mag)
#np.save('mags_phases/phase_spectrums/%i'%(grid_count),ph)
#np.save('mags_phases/periods',periods)
return (half_annual_mag,half_annual_phase,annual_mag,annual_phase,mean_array)
#print '\nLOMB WINDOWED, OVERSAMPLED'
#print 'Est. Amplitude 1 = ',mag1
#print 'Est. Phase 1 = ',phase1
#print 'Est. Amplitude 2 = ',mag2
#print 'Est. Phase 2 = ',phase2
#print '------------------------------------------\n'
#Lomb WINDOWED, OVERSAMPLED, INTERPOLATED
#-----------------------------------------------
ofac = 4
periods,mag,ph,fr,fi,amp_corr = modules.take_lomb(b,vals,ofac,hourly_step,w=True)
closest_period_1 = min(range(len(periods)), key=lambda i: abs(periods[i]-p1))
closest_period_2 = min(range(len(periods)), key=lambda i: abs(periods[i]-p2))
try:
mag1,phase1 = modules.periodic_interp(fr,fi,1000,periods,p1,len(vals),amp_corr,window='hanning')
except:
mag1 = np.nan
phase1 = np.nan
try:
mag2,phase2 = modules.periodic_interp(fr,fi,1000,periods,p2,len(vals),amp_corr,window='hanning')
except:
mag2 = np.nan
phase2 = np.nan
diff_a1 = (mag1/amp1)*100.
diff_a2 = (mag2/amp2)*100.
diff_p1 = phase_1 - phase1
if diff_p1 > np.pi:
diff_p1 = np.abs(-np.pi + (diff_p1 - np.pi))
#convert site_lon to 0 to 360 degs
if obs_lon < 0:
obs_lon = 360-np.abs(obs_lon)
#transform from UTC time to solar time
sun_time = lon_step_time*obs_lon
print 'sun time = ', sun_time
time_diff = sun_time - 0
if time_diff > 12:
time_diff = time_diff-24
print 'time diff =', time_diff
#correct magnitude and phase for spectral leakage
zoomfact = 1000
daily_obs_mag,daily_obs_phase = modules.periodic_interp(obs_fr,obs_fi,zoomfact,obs_periods,1.,len(obs_var),obs_amp_corr)
daily_model_mag,daily_model_phase = modules.periodic_interp(model_fr,model_fi,zoomfact,model_periods,1.,len(model_var),model_amp_corr)
ha_obs_mag,ha_obs_phase = modules.periodic_interp(obs_fr,obs_fi,zoomfact,obs_periods,(365.25/2.),len(obs_var),obs_amp_corr)
ha_model_mag,ha_model_phase = modules.periodic_interp(model_fr,model_fi,zoomfact,model_periods,(365.25/2.),len(model_var),model_amp_corr)
annual_obs_mag,annual_obs_phase = modules.periodic_interp(obs_fr,obs_fi,zoomfact,obs_periods,365.25,len(obs_var),obs_amp_corr)
annual_model_mag,annual_model_phase = modules.periodic_interp(model_fr,model_fi,zoomfact,model_periods,365.25,len(model_var),model_amp_corr)
#correct for phase shift from sites where raw times do not start from 0
daily_obs_phase = modules.phase_start_point_correct(1.,daily_obs_phase,obs_time)
daily_model_phase = modules.phase_start_point_correct(1.,daily_model_phase,model_time)
ha_obs_phase = modules.phase_start_point_correct((365.25/2.),ha_obs_phase,obs_time)
ha_model_phase = modules.phase_start_point_correct((365.25/2.),ha_model_phase,model_time)
annual_obs_phase = modules.phase_start_point_correct(365.25,annual_obs_phase,obs_time)
annual_model_phase = modules.phase_start_point_correct(365.25,annual_model_phase,model_time)
#convert phase to time
#Lomb WINDOWED, OVERSAMPLED, INTERPOLATED
#-----------------------------------------------
ofac = 4
periods, mag, ph, fr, fi, amp_corr = modules.take_lomb(b,
vals,
ofac,
hourly_step,
w=True)
closest_period_1 = min(range(len(periods)),
key=lambda i: abs(periods[i] - p1))
closest_period_2 = min(range(len(periods)),
key=lambda i: abs(periods[i] - p2))
daily_mag1, daily_phase1 = modules.periodic_interp(fr,
fi,
1000,
periods,
p1,
len(vals),
amp_corr,
window='hanning')
daily_mag2, daily_phase2 = modules.periodic_interp(fr,
fi,
1000,
periods,
p2,
len(vals),
amp_corr,
window='hanning')
print '\nLOMB WINDOWED, OVERSAMPLED, INTERPOLATED'
print 'Est. Amplitude 1 = ', daily_mag1
print 'Est. Phase 1 = ', daily_phase1
print 'Est. Amplitude 2 = ', daily_mag2
]
full_obs_datetimes = np.array(full_obs_datetimes)
obs_datetimes = full_obs_datetimes[valids]
obs_ave = np.mean(obs_var)
#make time start from 0
obs_times_from0 = modules.phase_start_correct(obs_times)
#remove invalid data
periods, mag, ph, fr, fi, amp_corr = modules.take_lomb(obs_times_from0,
obs_var, 4, 1. / 24)
zoomfact = 1000
daily_amp, daily_phase = modules.periodic_interp(fr, fi, zoomfact, periods, 1.,
len(obs_var), amp_corr)
ha_amp, ha_phase = modules.periodic_interp(fr, fi, zoomfact, periods,
365.25 / 2., len(obs_var), amp_corr)
annual_amp, annual_phase = modules.periodic_interp(fr, fi,
zoomfact, periods, 365.25,
len(obs_var), amp_corr)
#correct for phase shift from sites where raw times do not start from 0
daily_phase = modules.phase_start_point_correct(1., daily_phase, obs_times)
ha_phase = modules.phase_start_point_correct(365.25 / 2., ha_phase, obs_times)
annual_phase = modules.phase_start_point_correct(365.25, annual_phase,
obs_times)
lon_step_time = 24. / 360.
#convert site_lon to 0 to 360 degs
interp_fr_peak = interp_fr[closest_period_index_3]
interp_fi_peak = interp_fi[closest_period_index_3]
plt.plot(new_periods, interp_fi, label='Cubic Spline Interpolation')
print 'Cubic Spline Interpolated fr = ', interp_fr_peak
print 'Cubic Spline Interpolated fi = ', interp_fi_peak
print 'Cubic Spline Interpolated Amp = ', np.abs(
complex(interp_fr_peak, interp_fi_peak))
print 'Cubic Spline Interpolated Phase = ', np.angle(
complex(interp_fr_peak, interp_fi_peak))
zoomfact = 998
interp_amp, interp_phase, newreal, newx = modules.periodic_interp(
fr, fi, zoomfact, periods, 1.1, len(vals), amp_corr)
plt.axvline(1.1)
plt.plot(newx, newreal, label='Hann Window Interpolation')
plt.legend()
plt.show()
print 'Hann Interpolated Amp = ', interp_amp
print 'Hann Interpolated Phase = ', interp_phase
#print 'yeah =', np.abs(complex(peak_real_max,peak_imag_max))
#peak_real = peak_fr
#peak_imag = peak_fi
