/
discover_iter.py
78 lines (68 loc) · 3.01 KB
/
discover_iter.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
import lightkurve as lk
import matplotlib.pyplot as plt
import argparse
from scipy.interpolate import CubicSpline
import numpy as np
from own import process_folded_lc, is_there_a_planet, planet_score
parser = argparse.ArgumentParser(description='Find an exoplanet around a star.')
parser.add_argument('star', type=str, help='the star')
parser.add_argument('quarter', type=int, help='the quarter')
args = parser.parse_args()
tpf = lk.search_targetpixelfile(args.star, quarter=args.quarter).download()
#tpf.plot(frame=100, scale='log', show_colorbar=True)
#plt.show()
lc = tpf.to_lightcurve(aperture_mask=tpf.pipeline_mask)
#lc.plot()
#plt.show();
flat, trend = lc.flatten(window_length=301, return_trend=True)
#ax = lc.errorbar(label=args.star) # plot() returns a matplotlib axes ...
#trend.plot(ax=ax, color='red', lw=2, label='Trend'); # which we can pass to the next plot() to use the same axes
#plt.show();
#flat.errorbar(label=args.star);
#plt.show();
found_fit_periods = []
found_fit_times = []
# TODO
for best_fit_period in np.arange(4.5, 5.0, 0.01):
print(best_fit_period)
for transit_time_at_max_power in np.arange(min(lc.time), min(lc.time) + best_fit_period, 0.01): # 0.001):
# print(best_fit_period, transit_time_at_max_power)
folded = flat.fold(period=best_fit_period, t0=transit_time_at_max_power)
interpolations = process_folded_lc(folded)
if is_there_a_planet(*interpolations):
#folded.bin().scatter() # .errorbar();
#plt.show();
#folded.plot_river()
#plt.show();
print("Found", best_fit_period, transit_time_at_max_power)
print(interpolations)
found_fit_periods.append(best_fit_period)
found_fit_times.append(transit_time_at_max_power)
print()
lowest_found_period = min(found_fit_periods)
highest_found_period = max(found_fit_periods)
best_planet_score = None
best_folded = None
best_result = None
best_interpolations = None
for best_fit_period in np.arange(lowest_found_period, highest_found_period + 0.01 , 0.001):
print(best_fit_period)
for transit_time_at_max_power in np.arange(min(lc.time), min(lc.time) + best_fit_period, 0.001):
# print(best_fit_period, transit_time_at_max_power)
folded = flat.fold(period=best_fit_period, t0=transit_time_at_max_power)
interpolations = process_folded_lc(folded)
if is_there_a_planet(*interpolations):
score = planet_score(*interpolations)
print(best_fit_period, transit_time_at_max_power, interpolations, score)
if best_planet_score is None or score < best_planet_score:
best_planet_score = score
best_folded = folded
best_result = (best_fit_period, transit_time_at_max_power)
best_interpolations = interpolations
# print(interpolations)
best_folded.bin().scatter() # .errorbar();
plt.show();
best_folded.plot_river()
plt.show();
print("Found", best_result[0], best_result[1])
print(best_interpolations)