def seach_one_koi(KOI):
# Check if vetting file exists already
figure_out_path = '_FAIL0-5d_' + str(KOI)
figure_out_path2 = 'GOOD0-5d_' + str(KOI)
if figure_out_path in " ".join(
glob.glob("*.png")) or figure_out_path2 in " ".join(
glob.glob("*.png")):
print('Vetting sheet for this KOI exists already, skipping KOI', KOI)
else:
print('Working on file', KOI)
time, flux = loadkoi(str(KOI))
row = numpy.argmax(catalog["KOI"].astype(int) == int(float(KOI)))
KIC = catalog["KIC"][row]
print('row', row)
print('KIC', KIC)
max_t14 = T14(R_s=catalog["R_star"][row],
M_s=catalog["mass"][row],
P=period_max)
window = 3 * max_t14
print('R_star, mass, max_t14, window', catalog["R_star"][row],
catalog["mass"][row], max_t14, window)
if time is not None:
# Remove known planets
periods, t0s, tdurs = get_planets(KIC)
print('periods', periods)
for no in range(len(periods)):
print('Removing planet', no + 1, periods[no], t0s[no],
tdurs[no])
intransit = transit_mask(time, periods[no], 2 * tdurs[no],
t0s[no])
flux = flux[~intransit]
time = time[~intransit]
time, flux = cleaned_array(time, flux)
print('Next planet is number', no + 2)
# Detrend data and remove high outliers
print('Detrending with window...', window)
#print(time)
#print(flux)
trend1 = trend(time, flux, window=window, c=5)
#plt.scatter(time, flux, s=1, color='black')
#plt.plot(time, trend1, color='red')
#plt.show()
#trend = scipy.signal.medfilt(flux, 31)
#trend = scipy.signal.savgol_filter(trend, 25, 2)
rawflux = flux.copy()
rawtime = time.copy()
y_filt = flux / trend1
y_filt = sigma_clip(y_filt, sigma_upper=3, sigma_lower=1e10)
time, y_filt = cleaned_array(time, y_filt)
#plt.close()
#plt.scatter(time, y_filt, s=1, color='black')
#plt.show()
a = catalog["ld1"][row]
b = catalog["ld2"][row]
print('LD ab = ', a, b)
try:
model = transitleastsquares(time, y_filt)
results = model.power(
#n_transits_min=1,
u=(a, b),
R_star=catalog["R_star"][row],
R_star_max=catalog["R_star"][row] +
2 * catalog["rad_up"][row],
# sign is OK, is negative in catalog:
R_star_min=catalog["R_star"][row] +
2 * catalog["rad_down"][row],
M_star=catalog["mass"][row],
M_star_max=catalog["mass"][row] +
2 * catalog["mass_up"][row],
M_star_min=catalog["mass"][row] +
2 * catalog["mass_down"][row],
oversampling_factor=5,
duration_grid_step=1.05,
use_threads=1,
period_min=period_min,
period_max=period_max,
show_progress_bar=False,
T0_fit_margin=0.1)
tls_worked = True
#except ValueError:
# tls_worked = False
valid = True
if tls_worked:
# Check if phase space has gaps
bins = numpy.linspace(0, 1, 100)
digitized = numpy.digitize(results.folded_phase, bins)
bin_means = [
results.folded_phase[digitized == i].mean()
for i in range(1, len(bins))
]
#print('bin_means', bin_means)
if numpy.isnan(bin_means).any():
print('Vetting fail! Phase bins contain NaNs')
valid = False
if results.distinct_transit_count == 1 and results.transit_count >= 2:
valid = False
print(
'Vetting fail! results.distinct_transit_count==1 and results.transit_count == 2'
)
if results.distinct_transit_count == 2 and results.transit_count >= 3:
valid = False
print(
'Vetting fail! results.distinct_transit_count==2 and results.transit_count == 3'
)
if results.SDE < 8:
valid = False
print('Vetting fail! results.SDE < 8', results.SDE)
if results.snr < 7:
valid = False
print('Vetting fail! results.snr < 7', results.snr)
upper_transit_depths = results.transit_depths + results.transit_depths_uncertainties
if results.transit_count == 2 and max(
upper_transit_depths) > 1:
valid = False
print('Vetting fail! 2 transits, only 1 significant')
upper_transit_depths = results.transit_depths + results.transit_depths_uncertainties
if results.transit_count == 3 and max(
upper_transit_depths) > 1:
valid = False
print(
'Vetting fail! 3 transits, not all 3 significant')
upper_transit_depths = results.transit_depths + results.transit_depths_uncertainties
if results.transit_count == 4 and max(
upper_transit_depths) > 1:
valid = False
print(
'Vetting fail! 4 transits, not all 4 significant')
if results.depth < 0.95:
valid = False
print('Vetting fail! Transit depth < 0.95',
results.depth)
print('Signal detection efficiency (SDE):',
format(results.SDE, '.1f'))
print('SNR:', format(results.snr, '.1f'))
print('Search completed')
#if valid:
print('Attempting figure...')
make_figure(KOI=str(KOI),
planet_number=no + 2,
results=results,
t=time,
y=flux,
y_filt=y_filt,
trend=trend1,
rawtime=rawtime,
rawflux=rawflux,
catalog=catalog,
row=row,
valid=valid)
#else:
# print('No figure made, vetting failed!')
else:
print('TLS failed')
process = psutil.Process(os.getpid())
ram_mb = process.memory_info().rss / 2**20
print('RAM (MB)', ram_mb)
if ram_mb > 25000:
sys.exit()
except:
pass
def seach_one_koi(KOI):
print('Working on file', KOI)
time, flux = loadkoi(str(KOI))
#KOI = 1206.01
#print(catalog["KOI"])
#catalog_KOIs =
#catalog_KOIs = round(catalog_KOIs, 0)
#print(catalog_KOIs)
#print(int(float(KOI)))
#print(catalog["KOI"].astype(int)[:20])
row = numpy.argmax(catalog["KOI"].astype(int) == int(float(KOI)))
KIC = catalog["KIC"][row]
print('row', row)
print('KIC', KIC)
max_t14 = T14(R_s=catalog["R_star"][row],
M_s=catalog["mass"][row],
P=period_max)
window = 3 * max_t14
print('R_star, mass, max_t14, window', catalog["R_star"][row],
catalog["mass"][row], max_t14, window)
#"KIC","KOI","KepName","Period","T0","T14","ld1","ld2","R_star","rad_up","rad_down","mass","mass_up","mass_down"
#10337517,1165.01,,7.053934488,136.357253,0.07185,0.1959,0.5086,0.863,0.073,-0.065,0.854,0.054,-0.045
#plt.scatter(time, flux, s=1)
#plt.show()
#print(time)
#print(flux)
if time is not None:
# Remove known planets
periods, t0s, tdurs = get_planets(KIC)
print('periods', periods)
for no in range(len(periods)):
print('Removing planet', no + 1, periods[no], t0s[no], tdurs[no])
intransit = transit_mask(time, periods[no], 2 * tdurs[no], t0s[no])
flux = flux[~intransit]
time = time[~intransit]
time, flux = cleaned_array(time, flux)
print('Next planet is number', no + 2)
# Detrend data and remove high outliers
print('Detrending...')
#print(time)
#print(flux)
trend1 = trend(time, flux, window=window, c=5)
#plt.scatter(time, flux, s=1, color='black')
#plt.plot(time, trend1, color='red')
#plt.show()
#trend = scipy.signal.medfilt(flux, 31)
#trend = scipy.signal.savgol_filter(trend, 25, 2)
rawflux = flux.copy()
rawtime = time.copy()
y_filt = flux / trend1
y_filt = sigma_clip(y_filt, sigma_upper=3, sigma_lower=1e10)
time, y_filt = cleaned_array(time, y_filt)
#plt.close()
#plt.scatter(time, y_filt, s=1, color='black')
#plt.show()
a = catalog["ld1"][row]
b = catalog["ld2"][row]
print('LD ab = ', a, b)
model = transitleastsquares(time, y_filt)
results = model.power(
#n_transits_min=1,
u=(a, b),
R_star=catalog["R_star"][row],
R_star_max=catalog["R_star"][row] + 2 * catalog["rad_up"][row],
# sign is OK, is negative in catalog:
R_star_min=catalog["R_star"][row] + 2 * catalog["rad_down"][row],
M_star=catalog["mass"][row],
M_star_max=catalog["mass"][row] + 2 * catalog["mass_up"][row],
M_star_min=catalog["mass"][row] + 2 * catalog["mass_down"][row],
oversampling_factor=5,
duration_grid_step=1.05,
use_threads=1,
#period_min=4.9,
#period_max=5.0,
show_progress_bar=False,
period_max=period_max,
T0_fit_margin=0.1)
tls_worked = True
#except ValueError:
# tls_worked = False
valid = True
if tls_worked:
# Check if phase space has gaps
bins = numpy.linspace(0, 1, 100)
digitized = numpy.digitize(results.folded_phase, bins)
bin_means = [
results.folded_phase[digitized == i].mean()
for i in range(1, len(bins))
]
#print('bin_means', bin_means)
if numpy.isnan(bin_means).any():
print('Vetting fail! Phase bins contain NaNs')
valid = False
if results.distinct_transit_count == 1 and results.transit_count >= 2:
valid = False
print(
'Vetting fail! results.distinct_transit_count==1 and results.transit_count == 2'
)
if results.distinct_transit_count == 2 and results.transit_count >= 3:
valid = False
print(
'Vetting fail! results.distinct_transit_count==2 and results.transit_count == 3'
)
if results.SDE < 8:
valid = False
print('Vetting fail! results.SDE < 8', results.SDE)
if results.snr < 7:
valid = False
print('Vetting fail! results.snr < 7', results.snr)
upper_transit_depths = results.transit_depths + results.transit_depths_uncertainties
if results.transit_count == 2 and max(upper_transit_depths) > 1:
valid = False
print('Vetting fail! 2 transits, only 1 significant')
upper_transit_depths = results.transit_depths + results.transit_depths_uncertainties
if results.transit_count == 3 and max(upper_transit_depths) > 1:
valid = False
print('Vetting fail! 3 transits, not all 3 significant')
upper_transit_depths = results.transit_depths + results.transit_depths_uncertainties
if results.transit_count == 4 and max(upper_transit_depths) > 1:
valid = False
print('Vetting fail! 4 transits, not all 4 significant')
if results.depth < 0.95:
valid = False
print('Vetting fail! Transit depth < 0.95', results.depth)
#if results.SDE > 9: # 9
print('Signal detection efficiency (SDE):',
format(results.SDE, '.1f'))
print('SNR:', format(results.snr, '.1f'))
print('Search completed')
# Make figure
#ttime.sleep(1)
#valid = True
if valid:
print('Valid result, attempting figure...')
make_figure(KOI=str(KOI),
planet_number=no + 2,
results=results,
t=time,
y=flux,
y_filt=y_filt,
trend=trend1,
rawtime=rawtime,
rawflux=rawflux)
#ttime.sleep(1)
#print('Figure made')
else:
print('No figure made, vetting failed!')
else:
print('TLS failed')
process = psutil.Process(os.getpid())
ram_mb = process.memory_info().rss / 2**20
print('RAM (MB)', ram_mb)
if ram_mb > 25000:
sys.exit()