docs/source/tutorials/01-target-pixel-files.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What are TargetPixelFile objects?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Target Pixel Files (TPFs) are a file common to Kepler/K2 and the TESS mission. They contain movies of the pixel data centered on a single target star.\n",
    "\n",
    "TPFs can be thought of as stacks of images, with one image for every timestamp the telescope took data. Each timestamp is referred to as a **cadence**. These images are cut out 'postage stamps' of the full observation to make them easier to work with. \n",
    "\n",
    "TPFs are given in FITS files, which you can read more about [here](https://fits.gsfc.nasa.gov/fits_primer.html). *Lightkurve* includes tools for you to work directly with these files easily and intuitively.\n",
    "\n",
    "In this tutorial we'll cover the basics of working with TPFs. In *lightkurve* there are classes to work with each mission. For example `KeplerTargetPixelFile` deals with data from the Kepler (and K2) mission. `TessTargetPixelFile` deals with data from the TESS mission. We'll use a Kepler TPF as an example.\n",
    "\n",
    "To load a `KeplerTargetPixelFile` from a local path or remote url, simply create a new object using the location of the file as the parameter:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightkurve import KeplerTargetPixelFile\n",
    "tpf = KeplerTargetPixelFile(\"https://archive.stsci.edu/pub/kepler/target_pixel_files/0069/006922244/kplr006922244-2010078095331_lpd-targ.fits.gz\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also search for the url automatically using the `search_targetpixelfile()` function. This will search for the right file in the [MAST data archive](https://archive.stsci.edu/kepler/) which holds all of the Kepler and K2 data.\n",
    "In this case we want the Target Pixel File with Kepler ID 6922244 for Quarter 4 (Kepler's observations were split into quarters of a year):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from lightkurve import search_targetpixelfile\n",
    "tpf = search_targetpixelfile(6922244, quarter=4).download()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can also pass the name of the target or its astronomical coordinates as a parameter to `search_targetpixelfile()`.\n",
    "\n",
    "The above code has created a variable named `tpf` which is a Python object of type `KeplerTargetPixelFile`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KeplerTargetPixelFile Object (ID: 6922244)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can access lots of meta data using this object in a simple way. For example, we can find the mission name, and the quarter that the data was taken in by typing the following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Kepler'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.mission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.quarter"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can find the full list of properties in the [API documentation](http://lightkurve.keplerscience.org/api/targetpixelfile.html) on this object."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most interesting data in a `KeplerTargetPixelFile` object are the `flux` and `time` values which give access to the brightness of the observed target over time. You can access the timestamps of the observations using the `time` property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([352.37632485, 352.39675805, 352.43762445, ..., 442.16263546,\n",
       "       442.18306983, 442.2035041 ])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, `time` is in the Kepler-specific *Barycentric Kepler Julian Day* format (BKJD). You can easily convert this into [AstroPy Time objects](http://docs.astropy.org/en/stable/time/) using the `astropy_time` property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Time object: scale='tdb' format='jd' value=[2455185.37632485 2455185.39675805 2455185.43762445 ... 2455275.16263546\n",
       " 2455275.18306983 2455275.2035041 ]>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.astropy_time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In turn, this gives you access to human-readable ISO timestamps using the `astropy_time.iso` property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2009-12-19 21:01:54.467', '2009-12-19 21:31:19.895',\n",
       "       '2009-12-19 22:30:10.752', ..., '2010-03-19 15:54:11.704',\n",
       "       '2010-03-19 16:23:37.233', '2010-03-19 16:53:02.754'], dtype='<U23')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.astropy_time.iso"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Beware:** these timestamps are in the Solar System Barycentric frame (TDB) and do not include corrections for light travel time or leap seconds.  To use a different time scale, such as the Earth-centered UTC system, you can use [AstroPy's time scale conversion features](http://docs.astropy.org/en/stable/time/#time-scale).  For example: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['2009-12-19 21:00:48.283', '2009-12-19 21:30:13.712',\n",
       "       '2009-12-19 22:29:04.569', ..., '2010-03-19 15:53:05.518',\n",
       "       '2010-03-19 16:22:31.048', '2010-03-19 16:51:56.568'], dtype='<U23')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.astropy_time.utc.iso"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, let's look at the actual image data, which is available via the `flux` property:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4116, 5, 5)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.flux.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `flux` data is a 4116x5x5 array in units electrons/second. The first axis is the time axis, and the images themselves are 5 pixels by 5 pixels. You can use the `plot` method on the `KeplerTargetPixelFile` object to view the data. (By default, this will show just one cadence of the data. But you can pass the cadence you want to look at to the `frame` keyword if you would like to check a particular flux point for thruster firings, cosmic rays or asteroids.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 848.5x400 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 401,
       "width": 518
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "tpf.plot(frame=0);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The values shown in this image are also directly accessible as an array:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[          nan, 5.6079335e+00, 5.1491142e+01, 8.4241745e+01,\n",
       "        3.0221334e+01],\n",
       "       [4.4045620e+01, 7.6861229e+01, 1.1227759e+03, 3.2262029e+03,\n",
       "        4.5486777e+02],\n",
       "       [2.5911165e+01, 2.2907593e+02, 9.3626543e+03, 2.3606273e+04,\n",
       "        1.2087750e+03],\n",
       "       [4.0100830e+01, 8.8543927e+02, 1.7102118e+03, 2.6254871e+03,\n",
       "        7.0796606e+02],\n",
       "       [1.5719417e+02, 8.3713440e+02, 5.1021539e+02, 1.1501041e+03,\n",
       "        1.8313370e+02]], dtype=float32)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.flux[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can use normal `numpy` methods on these to find the shape, mean etc!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now turn this Target Pixel File into a light curve, with a single flux value for every time value. Each of the pixels are 4 arcseconds across. The point spread function (PSF) of the telescope causes the light from the star fall onto several different pixels, which can be seen in the image above. Because of this spreading, we have to sum up many pixels to collect all the light from the source. To do this we sum up all the pixels in an **aperture**. An aperture is a pixel mask, where we take only the pixels related to the target. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The *Kepler* pipeline adds an aperture mask to each target pixel file. This aperture determines which pixels are summed to create a 1-D light curve of the target. There are some science cases where you might want to create a different aperture. For example, there may be a nearby contaminant or you may want to measure the background. \n",
    "\n",
    "The standard pipeline aperture is easily accessed in a `KeplerTargetPixelFile` object using `tpf.pipeline_mask`, which is a boolean array:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[False, False, False, False, False],\n",
       "       [False, False,  True,  True, False],\n",
       "       [False, False,  True,  True, False],\n",
       "       [False,  True,  True,  True, False],\n",
       "       [False, False, False,  True, False]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.pipeline_mask"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also plot this aperture over the target pixel file above to see if the flux of the star is all contained within the aperture."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 848.5x400 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 401,
       "width": 518
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tpf.plot(aperture_mask=tpf.pipeline_mask);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that we have the aperture we can create a Simple Aperture Photometry light curve in the next tutorial."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, note that you can inspect all the raw metadata of the target by taking a look at the 'header' of the FITS file, which contains information about the data set. Let's just print the first 10 lines:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMPLE  =                    T / conforms to FITS standards                     \n",
       "BITPIX  =                    8 / array data type                                \n",
       "NAXIS   =                    0 / number of array dimensions                     \n",
       "EXTEND  =                    T / file contains extensions                       \n",
       "NEXTEND =                    2 / number of standard extensions                  \n",
       "EXTNAME = 'PRIMARY '           / name of extension                              \n",
       "EXTVER  =                    1 / extension version number (not format version)  \n",
       "ORIGIN  = 'NASA/Ames'          / institution responsible for creating this file \n",
       "DATE    = '2015-09-23'         / file creation date.                            \n",
       "CREATOR = '917482 TargetPixelExporterPipelineModule' / pipeline job and program "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.header[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can look at the values in the second extension of the fits file by accessing the AstroPy FITS `HDUList` object. For example, to look at all the column titles:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "TTYPE1  = 'TIME    '           / column title: data time stamps                 \n",
       "TTYPE2  = 'TIMECORR'           / column title: barycenter - timeslice correction\n",
       "TTYPE3  = 'CADENCENO'          / column title: unique cadence number            \n",
       "TTYPE4  = 'RAW_CNTS'           / column title: raw pixel counts                 \n",
       "TTYPE5  = 'FLUX    '           / column title: calibrated pixel flux            \n",
       "TTYPE6  = 'FLUX_ERR'           / column title: 1-sigma calibrated uncertainty   \n",
       "TTYPE7  = 'FLUX_BKG'           / column title: calibrated background flux       \n",
       "TTYPE8  = 'FLUX_BKG_ERR'       / column title: 1-sigma cal. background uncertain\n",
       "TTYPE9  = 'COSMIC_RAYS'        / column title: cosmic ray detections            \n",
       "TTYPE10 = 'QUALITY '           / column title: pixel quality flags              \n",
       "TTYPE11 = 'POS_CORR1'          / column title: column position correction       \n",
       "TTYPE12 = 'POS_CORR2'          / column title: row position correction          \n",
       "TTYPE13 = 'RB_LEVEL'           / column title: rolling band level               "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tpf.hdu[1].header['TTYPE*']"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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