Science Use Case - Inspecting a Candidate List.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Science User Case - Inspecting a Candidate List"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ogle et al. (2016) mined the NASA/IPAC Extragalactic Database (NED) to identify a new type of galaxy: Superluminous Spiral Galaxies. Here's the paper: \n",
    "\n",
    "Here's the paper: https://ui.adsabs.harvard.edu//#abs/2016ApJ...817..109O/abstract\n",
    "\n",
    "Table 1 lists the positions of these Super Spirals. Based on those positions, let's create multiwavelength cutouts for each super spiral to see what is unique about this new class of objects."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import some python modules so we don't get inundated with unimportant warnings when we run our notebook cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "import sys\n",
    "sys.path.append('workshop-dev-master')\n",
    "from navo_utils.image import Image, ImageColumn\n",
    "from navo_utils.spectra import Spectra, SpectraColumn\n",
    "from navo_utils.cone import Cone\n",
    "from navo_utils.tap import Tap\n",
    "from navo_utils.utils import astropy_table_from_votable_response\n",
    "from astropy.table import Table\n",
    "\n",
    "# Utility functions used in the workshop.\n",
    "import navo_utils.utils"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Search NED for objects in this paper."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astroquery.ned import Ned\n",
    "objects_in_paper = Ned.query_refcode('2016ApJ...817..109O')\n",
    "objects_in_paper.show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The NED query returns all objects in the paper, not just the galaxies in Table 1. Let's filter these results to only include the galaxies."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hint: There is a difference between strings and byte strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Let's see whether we are dealing with strings or byte strings\n",
    "objects_in_paper['Type'].data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Byte strings it is!\n",
    "galaxies = objects_in_paper[objects_in_paper['Type'] == b'G']\n",
    "\n",
    "galaxies.show_in_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Search the NAVO Registry for WISE, GALEX, and SDSS image services"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from navo_utils.registry import Registry\n",
    "\n",
    "wise_services = Registry.query(keyword='allwise', service_type='image')\n",
    "\n",
    "print(f'{len(wise_services)} result(s) found.')\n",
    "\n",
    "wise_services"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "galex_services = Registry.query(keyword='galex', service_type='image')\n",
    "\n",
    "print(f'{len(galex_services)} result(s) found.')\n",
    "\n",
    "galex_services"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sdss_services = Registry.query(keyword='sdss', service_type='image')\n",
    "\n",
    "print(f'{len(sdss_services)} result(s) found.')\n",
    "\n",
    "sdss_services"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# For each position, show the corresponding WISE, GALEX, and SDSS images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.coordinates import SkyCoord  # High-level coordinates\n",
    "from navo_utils.image import Image\n",
    "import astropy.units as u #is this needed?\n",
    "\n",
    "    missions = ['GALEX', '2MASS', 'AllWISE']\n",
    "\n",
    "    base_urls = ['http://mast.stsci.edu/portal_vo/Mashup/VoQuery.asmx/SiaV1?MISSION=GALEX&amp;', \n",
    "             'http://irsa.ipac.caltech.edu/ibe/sia/twomass/allsky/allsky?',\n",
    "             'https://irsa.ipac.caltech.edu/ibe/sia/wise/allwise/p3am_cdd?']\n",
    "\n",
    "    #Create an astropy table with this info.\n",
    "    search_list = Table([missions, base_urls], names = ('mission', 'access_url'))\n",
    "\n",
    "    size = '0'  #diameter in degrees\n",
    "\n",
    "for object in galaxies:\n",
    "    pos = SkyCoord(object['RA(deg)'], object['DEC(deg)'], frame=\"icrs\", unit=(u.deg, u.deg))\n",
    "    \n",
    "    for mission in missions:\n",
    "        \n",
    "        wise_results = Image.query(coords=pos, radius=size, service=wise_services[0])\n",
    "        table = wise_results[0]\n",
    "        table.show_in_notebook()\n",
    "        galex_results = Image.query(coords=pos, radius=size, service=galex_services[0])\n",
    "\n",
    "        sdss_results = Image.query(coords=pos, radius=size, service=sdss_services[0])\n",
    "        \n",
    "        #xid = SDSS.query_region(pos, spectro=True) #requires matches to have spectroscopy, not just photometry:\n",
    "        #im = SDSS.get_images(matches=xid, band='g')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Grab the SDSS images for each super spiral"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astroquery.sdss import SDSS\n",
    "from astropy.coordinates import SkyCoord  # High-level coordinates\n",
    "import astropy.units as u\n",
    "\n",
    "for object in galaxies:\n",
    "    pos = SkyCoord(object['RA(deg)'], object['DEC(deg)'], frame=\"icrs\", unit=(u.deg, u.deg))\n",
    "    xid = SDSS.query_region(pos, spectro=True) #requires matches to have spectroscopy, not just photometry:\n",
    "    im = SDSS.get_images(matches=xid, band='g')"
   ]
  }
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