#!/usr/bin/env python
# coding: utf-8
# # How to recover a known planet in Kepler data?
# This tutorial will demonstrate the basic steps required to recover the signal of [Kepler-10b](https://en.wikipedia.org/wiki/Kepler-10b), the first rocky planet that was discovered by Kepler!
#
# Let's start by downloading the pixel data for this target for one of Kepler's observing quarters:
# In[1]:
import lightkurve as lk
tpf = lk.search_targetpixelfile("Kepler-10", quarter=3).download()
# Let's use the `plot` method to show the pixel data at one point in time (frame index 100). We'll also pass along a few plotting arguments.
# In[2]:
tpf.plot(frame=100, scale='log', show_colorbar=True);
# The target pixel file appears to show one bright star with a core brightness of approximately 50,000 electrons/seconds.
# Now, we will use the ``to_lightcurve`` method to create a simple aperture photometry lightcurve using the
# mask defined by the pipeline which is stored in `tpf.pipeline_mask`.
# In[3]:
lc = tpf.to_lightcurve(aperture_mask=tpf.pipeline_mask)
# Let's take a look at the output lightcurve.
# In[4]:
lc.plot();
# Now let's use the `flatten` method, which removes long-term variability that we are not interested in using a high-pass filter called *Savitzky-Golay*.
# In[5]:
flat, trend = lc.flatten(window_length=301, return_trend=True)
# Let's plot the trend estimated in red:
# In[6]:
ax = lc.errorbar(label="Kepler-10") # 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
# and the flat lightcurve:
# In[7]:
flat.errorbar(label="Kepler-10");
# Now, let's run a period search function using the well-known Box-Least Squares algorithm (BLS), which was added to the [AstroPy package](http://docs.astropy.org) in version 3.1.
#
# We will use the BLS algorithm to search a pre-defined grid of transit periods:
# In[8]:
import numpy as np
periodogram = flat.to_periodogram(method="bls", period=np.arange(0.3, 1.5, 0.001))
periodogram.plot();
# It looks like we found a strong signal with a periodicity of 0.8 days!
# In[9]:
best_fit_period = periodogram.period_at_max_power
print('Best fit period: {:.3f}'.format(best_fit_period))
# In[10]:
flat.fold(period=best_fit_period, t0=periodogram.transit_time_at_max_power).errorbar();
# We successfully recovered the planet!