#!/usr/bin/env python
# coding: utf-8

# # Quickstart

# If you have a working version of Python 2 or 3 on your system
# (we recommend [Anaconda Python](https://www.continuum.io/downloads)),
# you can simply install the latest stable release of the *lightkurve* package using ``pip``:
# ```
# $ pip install lightkurve
# ```
# With *lightkurve* installed, it is easy to extract brightness time series data (astronomers call this a *lightcurve*)
# from the tiny images of stars collected by the Kepler spacecraft.
# 
# For example, let's download and display the pixels of a famous star named [KIC 8462852](https://en.wikipedia.org/wiki/KIC_8462852), also known as *Tabby's Star* or *Boyajian's Star*.
# 
# First, we start Python and import the `KeplerTargetPixelFile` class:

# In[1]:


from lightkurve import KeplerTargetPixelFile


# Next, we obtain the Kepler pixel data for the star from the [data archive](https://archive.stsci.edu/kepler/):

# In[2]:


tpf = KeplerTargetPixelFile.from_archive(8462852, quarter=16,
                                         quality_bitmask='hardest');


# Next, let's display the first image in this data set:

# In[3]:


get_ipython().run_line_magic('matplotlib', 'inline')
tpf.plot(frame=1);


# It looks like the star is an isolated object, so we can extract a lightcurve by simply summing up all the pixel values in each image:

# In[4]:


lc = tpf.to_lightcurve(aperture_mask='all');


# The above method returned a `KeplerLightCurve` object which gives us access to the flux over time, which are both available as array objects.  The time is in units of *days* and the flux is in units *electrons/second*.

# In[5]:


lc.time, lc.flux


# We can plot these data using the `plot()` method:

# In[6]:


lc.plot(linestyle='solid');


# The plot reveals a short-lived 20% dip in the brightness of the star.  It looks like we re-discovered one of the [intriguing dips in Tabby's star](https://en.wikipedia.org/wiki/KIC_8462852#Luminosity)!