#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (division, print_function, absolute_import,
unicode_literals)
from bart.injection import kepler_injection
from bart._turnstile import period_search
import numpy as np
import matplotlib.pyplot as pl
period, size = 278.1045694, 0.05
datasets, ps = kepler_injection(2301306, period, size, t0=20.0)
[pl.plot(d.time, d.flux, ".k") for d in datasets]
pl.savefig("data.png")
periods, epochs, depths, dvar = period_search(datasets,
period - 0.01, period + 0.01, 5,
100.0, 4.0)
mu = [np.mean(d) for d in depths]
print(mu)
pl.clf()
[pl.errorbar(p * np.ones_like(d), d, yerr=np.sqrt(e), fmt=".k")
for p, d, e in zip(periods, depths, dvar)]
pl.plot(periods, mu, ".r")
pl.gca().axhline(size * size)
pl.gca().axvline(period)
pl.savefig("periods.png")
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import (division, print_function, absolute_import,
unicode_literals)
from bart.injection import kepler_injection
from bart._turnstile import period_search
import numpy as np
import matplotlib.pyplot as pl
period, size = 330.0, 0.01
datasets, ps = kepler_injection(2301306, period, size, t0=25.0)
[pl.plot(d.time, d.flux, ".k") for d in datasets]
pl.savefig("data.png")
periods, epochs, dll = period_search(datasets, period - 5.0, period + 5.0,
11, 1e-8, 100.0)
mu = [np.mean(d) for d in dll]
print(mu)
pl.clf()
# [pl.plot(p * np.ones_like(d), d, ".k") for p, d in zip(periods, dll)]
# pl.plot(periods, mu, ".r")
[pl.plot(p, np.max(d), ".k") for p, d in zip(periods, dll)]
pl.gca().axhline(size * size)
pl.gca().axvline(period)
pl.savefig("periods.png")
