Notebooks/6_Planetary_Nebulae__Advanced_usage_of_HiPS_and_MOCs.ipynb

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    "# The MASH planeraty nebulae catalog: Advanced usage of HiPS and MOCs to explore complex regions of interest\n",
    "\n",
    "Stefania Amodea¹, Matthieu Baumann¹, Thomas Boch¹, Caroline Bot¹, Katarina A. Lutz¹, Manon Marchand¹.\n",
    "\n",
    "1. Université de Strasbourg, CNRS, Observatoire Astronomique de Strasbourg, UMR 7550, F-67000, Strasbourg, France\n",
    "\n",
    "Thomas Boch and Caroline Bot wrote the original version of this tutorial, available on the [EURO-VO tutorials page](http://www.euro-vo.org/?q=science/scientific-tutorials). It was presented at the workshop \"[Detecting the unexpected, Discovery in the Era of Astronomically Big Data](https://www.lsstcorporation.org/node/107)\". The version here is an adaptation to jupyter notebooks by the Strasbourg astronomical Data Center ([CDS](https://cdsweb.u-strasbg.fr/)) team.\n",
    "\n",
    "*** \n",
    "\n",
    "## Introduction\n",
    "\n",
    "This tutorial demonstrates an advanced usage of Hierarchical Progressive Surveys ([HiPS](https://ui.adsabs.harvard.edu/abs/2017ivoa.spec.0519F/abstract)) and Multi-Order Coverage ([MOC](https://www.ivoa.net/documents/MOC/)) maps. Wis this tutorial, you will: \n",
    "\n",
    "1. learn how to find fits files\n",
    "2. build a map of the coverage of all the fits files \n",
    "3. select only the parts of this map that correspond to low-extinction regions\n",
    "4. retrieve objects from large catalogs inside the obtained map -- that has a non-trivial shape and non-necessarily-connected regions\n",
    "5. combine catalogs to visualize a color-color diagram"
   ]
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   "source": [
    "# Standard Library\n",
    "from pathlib import Path\n",
    "\n",
    "# Astronomy tools\n",
    "import astropy.units as u\n",
    "from astropy.coordinates import Angle, SkyCoord, match_coordinates_sky\n",
    "from astropy.io import fits\n",
    "\n",
    "# Access astronomical databases\n",
    "import pyvo\n",
    "from astroquery.vizier import Vizier\n",
    "\n",
    "# Moc and HEALPix tools\n",
    "import cdshealpix\n",
    "import mocpy\n",
    "\n",
    "# For plots\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Data handling\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1: Finding the images\n",
    "\n",
    "We want to find all Short-Red images in the Macquarie/AAO/Strasbourg Hα Planetary Galactic catalog ([MASH](https://vizier.cfa.harvard.edu/vizier/MASH/index.htx)) using the VizieR associated data service.\n",
    "\n",
    "[![Vizier](https://custom-icon-badges.demolab.com/badge/Vizier-gray.svg?logo=vizier&logoColor=orange&logoWidth=20)](https://vizier.cds.unistra.fr/viz-bin/VizieR \"https://vizier.cds.unistra.fr/viz-bin/VizieR\")\n",
    "\n",
    "The [VizieR](https://vizier.cds.unistra.fr/) service at CDS inventories astronomical catalogs published in the literature. Some of these catalogs contain data associated with publications and the tables therein. This data can be browsed and explored through the VizieR-associated data service, linked to the traditional VizieR table service. Here we look for images associated with the MASH catalog of planetary nebulae ([Parker *et. al.* 2006-2008](https://ui.adsabs.harvard.edu/abs/2006yCat.5127....0P/abstract)). The MASH fits files are cut-outs extracted from a larger Hα and Short Red survey to constitute a set of regions of interest around planetary nebulae. \n",
    "\n",
    "To find VizieR-associated data, we use the Table Access Protocol (TAP) with the VizieR endpoint. Through the VizieR TAP endpoint, we can search for tables, their content, and information on associated data. \n",
    "\n",
    "First, we search for the MASH catalog:"
   ]
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     "data": {
      "text/html": [
       "<div><i>Table length=5</i>\n",
       "<table id=\"table140505956309104\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>schema_name</th><th>table_name</th><th>table_type</th><th>description</th><th>utype</th><th>nrows</th></tr></thead>\n",
       "<thead><tr><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
       "<tr><td>J_MNRAS</td><td>J/MNRAS/412/223/table4</td><td>table</td><td>The nine MASH PNe detected and possibly detected in the PMN survey ( Bojicic I.S., Parker Q.A., Filipovic M.D., Frew D.J.)</td><td></td><td>9</td></tr>\n",
       "<tr><td>J_MNRAS</td><td>J/MNRAS/412/223/table1</td><td>table</td><td>MASH PNe detected in the NVSS ( Bojicic I.S., Parker Q.A., Filipovic M.D., Frew D.J.)</td><td></td><td>201</td></tr>\n",
       "<tr><td>V_combined</td><td>V/127A/mash2</td><td>table</td><td>The MASH-II Supplement (from paper II) ( Parker Q.A., Acker A., Frew D.J., Hartley M., Peyaud A.E.J., Phillipps S., Russeil D., Beaulieu S.F., Cohen M., Koppen J., Marcout J., Miszalski B., Morgan D.H., Morris R.A.H., Ochsenbein F., Pierce M.J.,)</td><td></td><td>335</td></tr>\n",
       "<tr><td>V_combined</td><td>V/127A/mash1</td><td>table</td><td>The MASH Catalog of Planetary Nebulae (paper I) ( Parker Q.A., Acker A., Frew D.J., Hartley M., Peyaud A.E.J., Phillipps S., Russeil D., Beaulieu S.F., Cohen M., Koppen J., Marcout J., Miszalski B., Morgan D.H., Morris R.A.H., Ochsenbein F., Pierce M.J.,)</td><td></td><td>903</td></tr>\n",
       "<tr><td>J_MNRAS</td><td>J/MNRAS/412/223/mpgs2</td><td>table</td><td>MASH PNe detected in the MPGS-2 (Cat. VIII/82) ( Bojicic I.S., Parker Q.A., Filipovic M.D., Frew D.J.)</td><td></td><td>81</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "schema_name       table_name       table_type ... utype  nrows \n",
       "   object           object           object   ... object object\n",
       "----------- ---------------------- ---------- ... ------ ------\n",
       "    J_MNRAS J/MNRAS/412/223/table4      table ...             9\n",
       "    J_MNRAS J/MNRAS/412/223/table1      table ...           201\n",
       " V_combined           V/127A/mash2      table ...           335\n",
       " V_combined           V/127A/mash1      table ...           903\n",
       "    J_MNRAS  J/MNRAS/412/223/mpgs2      table ...            81"
      ]
     },
     "execution_count": 2,
     "metadata": {},
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    }
   ],
   "source": [
    "# give the address of the service, you can also directly visit the website\n",
    "tap_vizier = pyvo.dal.TAPService(\"https://tapvizier.cds.unistra.fr/TAPVizieR/tap\")\n",
    "\n",
    "# a query that searches for all tables with the words MASH and Parker in their description\n",
    "query = \"\"\"\n",
    "        SELECT  *  FROM tables \n",
    "        WHERE description LIKE '%MASH%Parker%'\n",
    "        \"\"\"\n",
    "\n",
    "mash_catalogues = tap_vizier.search(query).to_table()\n",
    "mash_catalogues"
   ]
  },
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   "source": [
    "In this tutorial, we are interested in the tables belonging to the catalogs `V/127A`. This includes tables `V/127A/mash1` and `V/127A/mash2`. To have a look at the content of these tables, we look at their first lines like this:"
   ]
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      "text/html": [
       "<div><i>Table length=5</i>\n",
       "<table id=\"table140505988274528\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>recno</th><th>n_PNG</th><th>PNG</th><th>Name</th><th>RAJ2000</th><th>DEJ2000</th><th>GLon</th><th>GLat</th><th>MajDiam</th><th>MinDiam</th><th>CS</th><th>Morph</th><th>Tel</th><th>ObsDate</th><th>HaExp</th><th>HaFld</th><th>Comments</th><th>img</th><th>ImageHa</th><th>ImageSr</th><th>AssocData</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th>arcsec</th><th>arcsec</th><th></th><th></th><th></th><th>&apos;Y:M:D&apos;</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>int32</th><th>str1</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th></tr></thead>\n",
       "<tr><td>29</td><td>L</td><td>G234.7-02.2</td><td>PHR0724-2021</td><td>111.05458333333331</td><td>-20.36361111111111</td><td>234.7045</td><td>-2.2774</td><td>134.5</td><td>54.0</td><td></td><td>A</td><td>SA</td><td>2452672.0</td><td>HA18201</td><td>HA842</td><td>Large, very faint diffuse arcuate nebula; has [NII]~2xH-alpha, nothing in blue</td><td>1029</td><td>img_ha</td><td>img_sr</td><td>fits</td></tr>\n",
       "<tr><td>2</td><td>P</td><td>G227.3-12.0</td><td>PHR0633-1808</td><td>98.35374999999999</td><td>-18.13972222222222</td><td>227.3207</td><td>-12.0289</td><td>17.0</td><td>15.0</td><td></td><td>Ea</td><td>SA</td><td>2452672.0</td><td>HA18191</td><td>HA926</td><td>Very faint, partial arcuate nebula also observed M1 060100; [NII]~0.8xH-alpha, strong [SII], only weak H-beta in blue - inconclusive</td><td>1002</td><td>img_ha</td><td>img_sr</td><td>fits</td></tr>\n",
       "<tr><td>16</td><td>T</td><td>G227.2-03.4</td><td>PHR0705-1419</td><td>106.41041666666665</td><td>-14.318055555555553</td><td>227.2852</td><td>-3.4029</td><td>15.0</td><td>15.0</td><td></td><td>E</td><td>SA</td><td>2452668.0</td><td>HA18244</td><td>HA1017</td><td>Small, circular PN around a faint central star; also observed M1 040100; [NII]~0.7 H-alpha, [OIII]&gt;&gt;H-beta</td><td>1016</td><td>img_ha</td><td>img_sr</td><td>fits</td></tr>\n",
       "<tr><td>5</td><td>L</td><td>G223.6-06.8</td><td>PHR0646-1235</td><td>101.60583333333332</td><td>-12.598888888888887</td><td>223.6338</td><td>-6.8035</td><td>40.0</td><td>37.0</td><td></td><td>E</td><td>SA</td><td>2453788.0</td><td>HA18194</td><td>HA1016</td><td>Slightly oval very faint PN candidate - has [OIII] and H-alpha</td><td>1005</td><td>img_ha</td><td>img_sr</td><td>fits</td></tr>\n",
       "<tr><td>10</td><td>P</td><td>G224.3-05.5</td><td>PHR0652-1240</td><td>103.08458333333331</td><td>-12.67611111111111</td><td>224.3504</td><td>-5.5463</td><td>187.0</td><td>180.0</td><td></td><td>I</td><td>SA</td><td>2452670.0</td><td>HA18244</td><td>HA1017</td><td>Faint, extended S-shaped emission nebula, possible evolved PN, also observed M1 080100; has [NII]~0.8Ha, [OIII], strong [SII], [OIII]&gt;H-beta</td><td>1010</td><td>img_ha</td><td>img_sr</td><td>fits</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "recno n_PNG     PNG         Name     ...  img   ImageHa ImageSr AssocData\n",
       "                                     ...                                 \n",
       "int32  str1    object      object    ... object  object  object   object \n",
       "----- ----- ----------- ------------ ... ------ ------- ------- ---------\n",
       "   29     L G234.7-02.2 PHR0724-2021 ...   1029  img_ha  img_sr      fits\n",
       "    2     P G227.3-12.0 PHR0633-1808 ...   1002  img_ha  img_sr      fits\n",
       "   16     T G227.2-03.4 PHR0705-1419 ...   1016  img_ha  img_sr      fits\n",
       "    5     L G223.6-06.8 PHR0646-1235 ...   1005  img_ha  img_sr      fits\n",
       "   10     P G224.3-05.5 PHR0652-1240 ...   1010  img_ha  img_sr      fits"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = \"\"\"\n",
    "        SELECT TOP 5 * FROM \\\"V/127A/mash1\\\" \n",
    "        \"\"\"\n",
    "mash1_head = tap_vizier.search(query).to_table()\n",
    "mash1_head"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the last column of this table is called `AssocData` and contains the entry `fits`. If you look at this table on the VizieR web interface, you can download the associated fits file. Within this notebook, we query the `obscore` database to get the URLs to the fits file. Using the `astropy.io.fits` module, we can open the fits files from their URLs."
   ]
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   "cell_type": "code",
   "execution_count": 4,
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       "<div><i>Table length=5</i>\n",
       "<table id=\"table140505986757824\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>access_estsize</th><th>access_format</th><th>access_url</th><th>bib_reference</th><th>calib_level</th><th>dataproduct_type</th><th>em_band</th><th>em_max</th><th>em_min</th><th>extension</th><th>facility_name</th><th>has_wcs</th><th>instrument_name</th><th>obs_collection</th><th>obs_id</th><th>obs_publisher_did</th><th>oidsaada</th><th>o_ucd</th><th>pol_states</th><th>s_dec</th><th>s_fov</th><th>s_ra</th><th>s_region</th><th>s_resolution</th><th>target_name</th><th>t_exptime</th><th>t_max</th><th>t_min</th><th>t_resolution</th></tr></thead>\n",
       "<thead><tr><th>kbyte</th><th></th><th></th><th></th><th></th><th></th><th>spect</th><th></th><th></th><th>meta.code</th><th></th><th>meta.code</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>deg</th><th>deg</th><th>deg</th><th></th><th>arcsec</th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>object</th><th>object</th><th>object</th><th>int32</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>int32</th><th>object</th><th>int32</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>object</th><th>float64</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>610560</td><td>application/fits</td><td>https://cdsarc.cds.unistra.fr/saadavizier/download?oid=864975549779410945</td><td>2006MNRAS.373...79P</td><td>-1</td><td>image</td><td>Optical</td><td>1e-06</td><td>3e-07</td><td>--</td><td>UKST</td><td>5</td><td>SuperCOSMOS I</td><td>V/127A</td><td>1032_sr.fits</td><td>ivo://CDS.VizieR/V/127A?res=1032_sr.fits</td><td>864975549779410945</td><td>obs.image</td><td>NotSet</td><td>-13.784389854801203</td><td>0.0713021682865721</td><td>111.43275777455307</td><td>Polygon ICRS  111.46664940645094 -13.81781914701963  111.39832407190251 -13.817324215795937  111.3988758446347 -13.750955924906409  111.46718176614709 -13.751450706358609</td><td>0.948991575097523</td><td></td><td>--</td><td>--</td><td>51226.0</td><td>--</td></tr>\n",
       "<tr><td>740160</td><td>application/fits</td><td>https://cdsarc.cds.unistra.fr/saadavizier/download?oid=864975549779410951</td><td>2006MNRAS.373...79P</td><td>-1</td><td>image</td><td>Optical</td><td>1e-06</td><td>3e-07</td><td>--</td><td>UKST</td><td>5</td><td>SuperCOSMOS I</td><td>V/127A</td><td>1034_ha.fits</td><td>ivo://CDS.VizieR/V/127A?res=1034_ha.fits</td><td>864975549779410951</td><td>obs.image</td><td>NotSet</td><td>-17.12049297622673</td><td>0.07123944496920925</td><td>111.78451610217952</td><td>Polygon ICRS  111.8191479048229 -17.153711083791936  111.74974303867411 -17.15359964722061  111.74989666803143 -17.087268981666405  111.8192767884711 -17.087380370020252</td><td>0.9485038734315203</td><td></td><td>--</td><td>--</td><td>52338.0</td><td>--</td></tr>\n",
       "<tr><td>596160</td><td>application/fits</td><td>https://cdsarc.cds.unistra.fr/saadavizier/download?oid=864975549779410955</td><td>2006MNRAS.373...79P</td><td>-1</td><td>image</td><td>Optical</td><td>1e-06</td><td>3e-07</td><td>--</td><td>UKST</td><td>5</td><td>SuperCOSMOS I</td><td>V/127A</td><td>1034_sr.fits</td><td>ivo://CDS.VizieR/V/127A?res=1034_sr.fits</td><td>864975549779410955</td><td>obs.image</td><td>NotSet</td><td>-17.120533969278245</td><td>0.07124314880377468</td><td>111.7845314034197</td><td>Polygon ICRS  111.8191637002453 -17.153753988164176  111.74975722819107 -17.153640656320004  111.7499114759699 -17.08730806317958  111.81929320101966 -17.087421346614327</td><td>0.9485285228101485</td><td></td><td>--</td><td>--</td><td>50871.0</td><td>--</td></tr>\n",
       "<tr><td>731520</td><td>application/fits</td><td>https://cdsarc.cds.unistra.fr/saadavizier/download?oid=864975549779410959</td><td>2006MNRAS.373...79P</td><td>-1</td><td>image</td><td>Optical</td><td>1e-06</td><td>3e-07</td><td>--</td><td>UKST</td><td>5</td><td>SuperCOSMOS I</td><td>V/127A</td><td>1036_ha.fits</td><td>ivo://CDS.VizieR/V/127A?res=1036_ha.fits</td><td>864975549779410959</td><td>obs.image</td><td>NotSet</td><td>-21.862099427980556</td><td>0.07130134708963763</td><td>112.69528726569132</td><td>Polygon ICRS  112.73146814532774 -21.89490077932626  112.65997554014551 -21.895645624610193  112.659123005937 -21.829290184523508  112.73058240266795 -21.828545713789918</td><td>0.9488088411876365</td><td></td><td>--</td><td>--</td><td>51163.0</td><td>--</td></tr>\n",
       "<tr><td>590400</td><td>application/fits</td><td>https://cdsarc.cds.unistra.fr/saadavizier/download?oid=864975549779410960</td><td>2006MNRAS.373...79P</td><td>-1</td><td>image</td><td>Optical</td><td>1e-06</td><td>3e-07</td><td>--</td><td>UKST</td><td>5</td><td>SuperCOSMOS I</td><td>V/127A</td><td>1005_sr.fits</td><td>ivo://CDS.VizieR/V/127A?res=1005_sr.fits</td><td>864975549779410960</td><td>obs.image</td><td>NotSet</td><td>-12.59878194718445</td><td>0.06695119600443825</td><td>101.605805625331</td><td>Polygon ICRS  101.64022494465036 -12.631531553985315  101.57226287333897 -12.63235954506209  101.57139509987323 -12.56602794013158  101.63933959085792 -12.565200170324758</td><td>0.9485060738987898</td><td></td><td>--</td><td>--</td><td>51156.0</td><td>--</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "access_estsize  access_format   ...  t_min  t_resolution\n",
       "    kbyte                       ...                     \n",
       "    int64           object      ... float64   float64   \n",
       "-------------- ---------------- ... ------- ------------\n",
       "        610560 application/fits ... 51226.0           --\n",
       "        740160 application/fits ... 52338.0           --\n",
       "        596160 application/fits ... 50871.0           --\n",
       "        731520 application/fits ... 51163.0           --\n",
       "        590400 application/fits ... 51156.0           --"
      ]
     },
     "execution_count": 4,
     "metadata": {},
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    }
   ],
   "source": [
    "obs_tap_vizier = pyvo.dal.TAPService(\n",
    "    \"https://cdsarc.cds.unistra.fr/saadavizier.tap/tap\",\n",
    ")\n",
    "query = \"\"\"\n",
    "        SELECT TOP 5  *  FROM obscore \n",
    "        WHERE obs_collection='V/127A'   \n",
    "        \"\"\"\n",
    "mash_fits = obs_tap_vizier.search(query).to_table()\n",
    "mash_fits"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, the result from this query provides information on the fits files associated with the MASH catalogs. In particular, the column `access_url` provides the location of the data. To get the first image we could do:\n",
    "\n",
    "`image = fits.open(mash_fits['access_url'][0])`\n",
    "\n",
    "and then work on the image, plot it or save it to our machine. However, downloading all the data takes quite some time. For this tutorial, **we prepared a subsample of 335 of these Short Red images that will run promptly** but we encourage you to try accessing the full Short Red sample on your own later. The subsample is available either at http://astro.u-strasbg.fr/~bot/BochBot.tar.gz or in the Data Folder of this repository."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: Create a MOC of the MASH images\n",
    "\n",
    "The multi-order coverage (MOC) map of a set of images represents their sky coverage. MOCs can describe arbitrary zones in the sky which do not need to be connected. You'll see that the union or intersection of two MOCs requires few time and computational effort. Catalogs can also be filtered by MOCs. \n",
    "\n",
    "Here we want to use the fits files just downloaded to create a MOC map corresponding to the coverage of the MASH images.\n",
    "\n",
    "### Organising data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Where to find fits images downloaded from the archive above\n",
    "datadir = Path(\"Data/MASH_Sample/\")\n",
    "datadir.mkdir(parents=True, exist_ok=True)\n",
    "# Make new directory where to save MOCs\n",
    "outdir = Path(\"Data/Result_moc/\")\n",
    "outdir.mkdir(parents=True, exist_ok=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In most cases, we could ignore the next cell.  However, some possible deprecated keywords in the fits header would hamper the MOC creation and would cause errors in the underlying `astropy.wcs.WCS` module. This is why we rewrite the headers of the fits files so that they only contain the useful keywords needed to define the coordinate frame correctly before using `mocpy`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create the MOC\n",
    "\n",
    "Here we can create the MOC of the MASH images with the `MOCPy` module. This can take a few seconds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: FITSFixedWarning: RADECSYS= 'FK5 ' \n",
      "the RADECSYS keyword is deprecated, use RADESYSa. [astropy.wcs.wcs]\n"
     ]
    }
   ],
   "source": [
    "# Get a list of the fits files and create the MOC\n",
    "mash_file_list = datadir.glob(\n",
    "    \"*_sr_modified.fits\",\n",
    ")  # glob allows to find all paths that end with _sr_modified.fits in datadir\n",
    "moc_mash = mocpy.MOC.from_fits_images(mash_file_list, max_norder=15)\n",
    "moc_mash.save(str(outdir / \"mash_moc.fits\"), overwrite=True)\n",
    "# this takes a bit of time because a lot of files are opened and processed to extract the moc"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot the MOC\n",
    "\n",
    "We can chose between two of the MOCpy methods to plot the MOC"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# A one-liner for a very fast vizualisation\n",
    "moc_mash.display_preview()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# With a bit more control over the output, the MOC.wcs method\n",
    "fig = plt.figure(figsize=(10, 7))\n",
    "wcs = moc_mash.wcs(fig)\n",
    "ax = fig.add_subplot(projection=wcs)\n",
    "ax.grid(True)  # noqa: FBT003\n",
    "moc_mash.fill(ax, wcs, color=\"purple\", alpha=0.5)\n",
    "moc_mash.border(ax, wcs, color=\"purple\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see how the MOC has arbitrary shapes and not all regions are connected.\n",
    "\n",
    "And for more control over the plot parameters, there is also the mocpy.WCS method (!)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Load an archival extinction map and create the MOC of the low extinction regions\n",
    "\n",
    "Different works (e.g. [Schlegel et al. 1998](https://iopscience.iop.org/article/10.1086/305772), [Schlafly  & Finkbeiner 2011](https://ui.adsabs.harvard.edu/abs/2011AAS...21831803S/abstract), [Green et al. 2015](https://iopscience.iop.org/article/10.1088/0004-637X/810/1/25)...) have created extinction maps of the sky that are publicly available. Some of these maps are all-sky maps, while others have higher resolutions, or come from different methods... They can be found in HEALPix format (among others) on the Legacy Archive for Microwave Background Data Analysis ([LAMBDA](https://lambda.gsfc.nasa.gov/)) website or on the Analysis Center for Extended Data ([CADE](http://cade.irap.omp.eu/dokuwiki/doku.php?id=start)) website. \n",
    "\n",
    "For this tutorial, we will download the well-known all-sky extinction map from Schlegel *et al.* from the LAMBDA  website and define the low extinction area for which $0 < E(B-V) < 0.5$ as a MOC. It has an [information page](https://lambda.gsfc.nasa.gov/product/foreground/fg_sfd_info.html).\n",
    "\n",
    "The map is available here: https://lambda.gsfc.nasa.gov/data/foregrounds/SFD/lambda_sfd_ebv.fits and we save it to disc. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "ext_map = fits.open(\n",
    "    \"https://lambda.gsfc.nasa.gov/data/foregrounds/SFD/lambda_sfd_ebv.fits\",\n",
    ")\n",
    "ext_map.writeto(outdir / \"Schlegel_extinction_map.fits\", overwrite=True)\n",
    "ext_map.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are only interested in regions with low extinction. So we aim to get a MOC of all regions where the extinction values from the Schlegel *et al.* map are between 0 and 0.5mag. The extinction map we got from the NASA webpage is in the HEALPix format. This is an efficient presentation of all-sky maps. The HEALPix tesselation is also used by MOCs. So to get the MOC from the extinction map, we do the following. \n",
    "\n",
    "First, we check the coordinate system in the map header. We will need to convert to equatorial coordinates, change the projection of the map, and set the order (*i.e.* resolution) of the map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SIMPLE  =                    T / file does conform to FITS standard             \n",
       "BITPIX  =                   32 / number of bits per data pixel                  \n",
       "NAXIS   =                    0 / number of data axes                            \n",
       "EXTEND  =                    T / FITS dataset may contain extensions            \n",
       "COMMENT   FITS (Flexible Image Transport System) format is defined in 'Astronomy\n",
       "COMMENT   and Astrophysics', volume 376, page 359; bibcode: 2001A&A...376..359H \n",
       "DATE    = '2003-02-05T00:00:00' /file creation date (YYYY-MM-DDThh:mm:ss UT)    \n",
       "OBJECT  = 'ALL-SKY '           / Portion of sky given                           \n",
       "COMMENT   This file contains an all-sky Galactic reddening map, E(B-V), based on\n",
       "COMMENT   the derived reddening maps of Schlegel, Finkbeiner and Davis (1998).  \n",
       "COMMENT   Software and data files downloaded from their website were used to    \n",
       "COMMENT   interpolate their high resolution dust maps onto pixel centers        \n",
       "COMMENT   appropriate for a HEALPix Nside=512 projection in Galactic            \n",
       "COMMENT   coordinates. This file is distributed and maintained by LAMBDA.       \n",
       "REFERENC= 'Legacy Archive for Microwave Background Data Analysis (LAMBDA)      '\n",
       "REFERENC= '                http://lambda.gsfc.nasa.gov/                        '\n",
       "REFERENC= 'Maps of Dust Infrared Emission for Use in Estimation of Reddening an'\n",
       "REFERENC= ' Cosmic Microwave Background Radiation Foregrounds',                '\n",
       "REFERENC= ' Schlegel, Finkbeiner & Davis 1998 ApJ 500, 525                     '\n",
       "REFERENC= 'Berkeley mirror site for SFD98 data: http://astron.berkeley.edu/dust'\n",
       "REFERENC= 'Princeton mirror site for SFD98 data:                               '\n",
       "REFERENC= '                           http://astro/princeton.edu/~schlegel/dust'\n",
       "REFERENC= 'HEALPix Home Page: http://www.eso.org/science/healpix/              '\n",
       "RESOLUTN=                    9 / Resolution index                               \n",
       "SKYCOORD= 'Galactic'           / Coordinate system                              \n",
       "PIXTYPE = 'HEALPIX '           / Pixel algorithm                                \n",
       "ORDERING= 'NESTED  '           / Ordering scheme                                \n",
       "NSIDE   =                  512 / Resolution parameter                           \n",
       "NPIX    =              3145728 / # of pixels                                    \n",
       "FIRSTPIX=                    0 / First pixel (0 based)                          \n",
       "LASTPIX =              3145727 / Last pixel (0 based)                           "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# open the downloaded FITS file\n",
    "hdul = fits.open(outdir / \"Schlegel_extinction_map.fits\")\n",
    "hdr = hdul[0].header\n",
    "hdr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3145728,)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "FITS_rec([( 9.625492, 1.), (46.090515, 1.), ( 8.18071 , 1.), ...,\n",
       "          (15.149189, 1.), (14.107367, 1.), (15.463686, 1.)],\n",
       "         dtype=(numpy.record, [('TEMPERATURE', '>f4'), ('N_OBS', '>f4')]))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print((hdul[1].data).shape)\n",
    "hdul[1].data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The data field here has a specific shape. It contains tuples for which the first value is the extinction (named 'TEMPERATURE') and the second one is the number of observations of the value (you can check that it is `1` everywhere)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "extinction_values = hdul[1].data[\"TEMPERATURE\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " Let's extract the information about the number of sides and the order of the healpix map from the header of the fits file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "nside = hdul[0].header[\"NSIDE\"]\n",
    "norder = hdul[0].header[\"RESOLUTN\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The header allows to see that this map is in galactic coordinates. We will need to convert this into equatorial coordinates to compare with our other maps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We can check the the NPIX value corresponds to the one in the header here: 3145728\n"
     ]
    }
   ],
   "source": [
    "# Creation of an HEALpix grid at order 9 in nested ordering\n",
    "healpix_index = np.arange(12 * 4**norder, dtype=np.uint64)\n",
    "print(\n",
    "    f\"We can check the the NPIX value corresponds to the one in the header here: {len(healpix_index)}\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (ICRS): (ra, dec) in deg\n",
       "    [( 45.        ,  0.0746039 ), ( 45.08789062,  0.14920793),\n",
       "     ( 44.91210938,  0.14920793), ..., (315.08789062, -0.14920793),\n",
       "     (314.91210938, -0.14920793), (315.        , -0.0746039 )]>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get the coordinates of the centers of these healpix cells\n",
    "center_coordinates_in_equatorial = cdshealpix.healpix_to_skycoord(\n",
    "    healpix_index,\n",
    "    depth=9,\n",
    ")\n",
    "center_coordinates_in_equatorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<SkyCoord (Galactic): (l, b) in deg\n",
       "    [(176.8796283 , -48.85086427), (176.89078038, -48.7358142 ),\n",
       "     (176.70525363, -48.86216423), ..., ( 48.82487228, -28.4122831 ),\n",
       "     ( 48.7216889 , -28.26178141), ( 48.84578935, -28.29847774)]>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Convert this into galactic coordinates\n",
    "center_coordinates_in_galactic = center_coordinates_in_equatorial.galactic\n",
    "center_coordinates_in_galactic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate the bilinear interpolation we must apply to each healpix cell to get the values in the other coordinate system\n",
    "healpix, weights = cdshealpix.bilinear_interpolation(\n",
    "    center_coordinates_in_galactic.l,\n",
    "    center_coordinates_in_galactic.b,\n",
    "    depth=norder,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.08981742, 0.0991632 , 0.08249644, ..., 0.08323811, 0.08352184,\n",
       "       0.0820533 ])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Apply the interpolation\n",
    "ext_map_equatorial_nested = (extinction_values[healpix.data] * weights.data).sum(axis=1)\n",
    "ext_map_equatorial_nested"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we declare which pixel we want to use, let's take all pixels with an extinction lower than 0.5:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The low extinction criteria keeps 86.74% of the sky map\n"
     ]
    }
   ],
   "source": [
    "low_extinction_index = np.where(ext_map_equatorial_nested < 0.5)[0]\n",
    "print(\n",
    "    f\"The low extinction criteria keeps {round((len(low_extinction_index)/ len(extinction_values)*100), 2)}% of the sky map\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And let's create a MOC from this criteria"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "moc_low_extinction = mocpy.MOC.from_healpix_cells(\n",
    "    low_extinction_index,\n",
    "    np.full(\n",
    "        (\n",
    "            len(\n",
    "                low_extinction_index,\n",
    "            )\n",
    "        ),\n",
    "        norder,\n",
    "    ),\n",
    "    norder,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 4:  Find out which regions are covered by the MASH short-red images in the low extinction regions defined above\n",
    "\n",
    "To find out the sky regions of the MASH sample that are at low extinction, we build the intersection of the two MOCs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The intersection of the two MOCs covers 0.0013% of the sky\n"
     ]
    }
   ],
   "source": [
    "moc_intersection = moc_low_extinction.intersection(moc_mash)\n",
    "# Once the intersection is bluit, we can for example print the sky fraction :\n",
    "print(\n",
    "    f\"The intersection of the two MOCs covers {round(moc_intersection.sky_fraction * 100, 4)}% of the sky\",\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can visualize the coverage of the two MOCs and their intersection. The grey area is where the extinction is low. The blue one is the MASH coverage. The tiny red dots show the MASH coverage in low extinction regions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7fca149d8ca0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(111, figsize=(10, 8))\n",
    "\n",
    "with mocpy.WCS(\n",
    "    fig,\n",
    "    fov=200 * u.deg,\n",
    "    center=SkyCoord(200, -20, unit=\"deg\", frame=\"icrs\"),\n",
    "    coordsys=\"icrs\",\n",
    "    rotation=Angle(0, u.degree),\n",
    "    projection=\"AIT\",\n",
    ") as wcs:\n",
    "    ax = fig.add_subplot(1, 1, 1, projection=wcs)\n",
    "\n",
    "    moc_low_extinction.fill(\n",
    "        ax=ax,\n",
    "        wcs=wcs,\n",
    "        alpha=0.5,\n",
    "        fill=True,\n",
    "        color=\"grey\",\n",
    "        label=\"low extinction\",\n",
    "    )\n",
    "    moc_mash.fill(\n",
    "        ax=ax,\n",
    "        wcs=wcs,\n",
    "        alpha=0.5,\n",
    "        fill=True,\n",
    "        color=\"dodgerblue\",\n",
    "        label=\"MASH coverage\",\n",
    "    )\n",
    "    moc_intersection.fill(\n",
    "        ax=ax,\n",
    "        wcs=wcs,\n",
    "        alpha=0.5,\n",
    "        fill=True,\n",
    "        color=\"crimson\",\n",
    "        label=\"MASH in low extinction regions\",\n",
    "    )\n",
    "    # Sets labels\n",
    "    ax.set_xlabel(\"RA\")\n",
    "    ax.set_ylabel(\"Dec\")\n",
    "    # Sets ticks\n",
    "    lon, lat = ax.coords[0], ax.coords[1]\n",
    "    lon.set_major_formatter(\"hh:mm:ss\")\n",
    "    lat.set_major_formatter(\"dd:mm\")\n",
    "    lon.set_ticklabel(exclude_overlapping=True)\n",
    "    lat.set_ticklabel(exclude_overlapping=True)\n",
    "    lon.set_ticks(spacing=2 * u.hourangle)\n",
    "plt.legend(bbox_to_anchor=(1, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 5: Query the 2MASS and Gaia Catalogues by MOC\n",
    "\n",
    "Without the usage of MOC, querying for sources in the low extinction regions covered by the MASH subsample would be tedious or even impossible. Indeed, one would need to load the whole catalog and make selections which would not be possible given the size of some catalogs. Alternatively, one would need to query the catalog field by field, which would take time and several queries. Instead, here we will use the power of MOC files to query large catalogs directly in the covered regions only. We will use coverages of the low extinction and MASH regions to query for sources from the Gaia and 2MASS surveys in these highly non-continuous and non-trivial shape areas.\n",
    "\n",
    "First, let's see which Gaia and 2MASS catalogs are available on VizieR. We could, as above, use the TAP endpoint of VizieR. But we show below the `Vizier` module in the `astroquery` package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: The unit 'pix' has been deprecated in the VOUnit standard. [astropy.units.format.utils]\n",
      "WARNING: UnitsWarning: The unit 'ct' has been deprecated in the VOUnit standard. [astropy.units.format.utils]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "II/126 :  IRAS Serendipitous Survey Catalog (IPAC 1986)\n",
      "II/241 :  2MASS Catalog Incremental Data Release (IPAC/UMass, 2000)\n",
      "II/246 :  2MASS All-Sky Catalog of Point Sources (Cutri+ 2003)\n",
      "II/281 :  2MASS 6X Point Source Working Database / Catalog (Cutri+ 2006)\n",
      "II/307 :  WISE Preliminary Data Release (Cutri+ 2011)\n",
      "II/311 :  WISE All-Sky Data Release (Cutri+ 2012)\n",
      "II/328 :  AllWISE Data Release (Cutri+ 2013)\n",
      "II/365 :  The CatWISE2020 catalog (updated version 28-Jan-2021) (Marocco+, 2021)\n",
      "VII/233 :  The 2MASS Extended sources (IPAC/UMass, 2003-2006)\n",
      "J/ApJ/560/566 :  K-band galaxy luminosity function from 2MASS (Kochanek+, 2001)\n",
      "J/ApJ/564/421 :  Spectra of T dwarfs. I. (Burgasser+, 2002)\n",
      "J/ApJ/569/23 :  Optical polarisation of 2MASS QSOs (Smith+, 2002)\n",
      "J/ApJ/635/214 :  Chandra X-ray sources and NIR identifications (Ebisawa+, 2005)\n",
      "J/ApJ/713/330 :  Spitzer observations of major-merger galaxies (Xu+, 2010)\n",
      "J/ApJ/719/550 :  Deep NIR imaging of {rho} Oph cloud core (Marsh+, 2010)\n",
      "J/ApJ/741/68 :  Main Belt asteroids with WISE/NEOWISE. I. (Masiero+, 2011)\n",
      "J/ApJ/742/40 :  Jovian Trojans asteroids with WISE/NEOWISE (Grav+, 2011)\n",
      "J/ApJ/743/156 :  NEOWISE observations of NEOs: preliminary results (Mainzer+, 2011)\n",
      "J/ApJ/744/197 :  WISE/NEOWISE observations of Hilda asteroids (Grav+, 2012)\n",
      "J/ApJ/759/L8 :  WISE/NEOWISE observations of main belt asteroids (Masiero+, 2012)\n",
      "J/ApJ/760/L12 :  WISE/NEOWISE NEOs preliminary thermal fits (Mainzer+, 2012)\n",
      "J/ApJ/780/92 :  Light curves of the RR Lyr SDSS J015450.17+001500.7 (Szabo+, 2014)\n",
      "J/ApJ/783/122 :  AllWISE motion survey (Kirkpatrick+, 2014)\n",
      "J/ApJ/784/110 :  NEOWISE observations of 105 near-Earth objects (Mainzer+, 2014)\n",
      "J/ApJ/792/30 :  NEOWISE magnitudes for near-Earth objects (Mainzer+, 2014)\n",
      "J/ApJ/805/90 :  WISE ELIRGs and comparison with QSOs (Tsai+, 2015)\n",
      "J/ApJ/814/117 :  NEOWISE Reactivation mission: 1st yr data (Nugent+, 2015)\n",
      "J/ApJ/874/82 :  Follow-up photometry & spectroscopy of PTF14jg (Hillenbrand+, 2019)\n",
      "J/ApJS/95/1 :  Atlas of Quasar Energy Distributions (Elvis+ 1994)\n",
      "J/ApJS/172/663 :  Infrared observations of the Pleiades (Stauffer+, 2007)\n",
      "J/ApJS/175/191 :  Variables from 2MASS calibration fields (Plavchan+, 2008)\n",
      "J/ApJS/190/100 :  NIR proper motion survey using 2MASS (Kirkpatrick+, 2010)\n",
      "J/ApJS/199/26 :  The 2MASS Redshift Survey (2MRS) (Huchra+, 2012)\n",
      "J/ApJS/224/36 :  The AllWISE motion survey (AllWISE2) (Kirkpatrick+, 2016)\n",
      "J/ApJS/234/23 :  The WISE AGN candidates catalogs (Assef+, 2018)\n",
      "J/AJ/112/62 :  Quasar absorption-line systems (Tanner+ 1996)\n",
      "J/AJ/125/2521 :  2MASS6x survey of the Lockman Hole (Beichman+, 2003)\n",
      "J/AJ/126/63 :  Host galaxies of 2MASS-QSOs with z<=3 (Hutchings+, 2003)\n",
      "J/AJ/127/646 :  Unbiased census of AGN in 2MASS (Francis+, 2004)\n",
      "J/AJ/135/2245 :  Absolute spectrum of the Sun and Vega for 0.2-30um (Rieke+, 2008)\n",
      "J/AJ/144/148 :  Infrared photometry of brown dwarf and Hyper-LIRG (Griffith+, 2012)\n",
      "J/AJ/152/63 :  NEOWISE reactivation mission: 2nd yr data (Nugent+, 2016)\n",
      "J/AJ/154/53 :  WISE/NEOWISE observations of comets (Bauer+, 2017)\n",
      "J/AJ/154/168 :  NEOWISE: thermal model fits for NEOs and MBAs (Masiero+, 2017)\n",
      "J/AJ/156/60 :  Thermal model fits for short-arc NEOs with NEOWISE (Masiero+, 2018)\n",
      "J/PASP/113/10 :  Sub-mJy radio sources complete sample (Masci+, 2001)\n"
     ]
    }
   ],
   "source": [
    "catalog_list_twomass = Vizier.find_catalogs(\"Cutri\")\n",
    "for k, v in catalog_list_twomass.items():\n",
    "    print(k, \": \", v.description)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: Unit 'x' not supported by the VOUnit standard.  [astropy.units.format.vounit]\n",
      "WARNING: UnitsWarning: Unit 'Earth' not supported by the VOUnit standard.  [astropy.units.format.vounit]\n",
      "WARNING: UnitsWarning: Unit 'Sun' not supported by the VOUnit standard. Did you mean uN? [astropy.units.format.vounit]\n",
      "WARNING: UnitsWarning: The unit 'au' has been deprecated in the VOUnit standard. Suggested: 1.4959787e+11m. [astropy.units.format.utils]\n",
      "WARNING: UnitsWarning: The unit 'pix' has been deprecated in the VOUnit standard. [astropy.units.format.utils]\n",
      "WARNING: UnitsWarning: The unit 'a' has been deprecated in the VOUnit standard. Suggested: 365.25d. [astropy.units.format.utils]\n",
      "WARNING: UnitsWarning: Unit 'kau' not supported by the VOUnit standard. Did you mean 1000a, kA, ka (deprecated), kadu or ku? [astropy.units.format.vounit]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I/345 :  Gaia DR2 (Gaia Collaboration, 2018)\n",
      "I/347 :  Distances to 1.33 billion stars in Gaia DR2 (Bailer-Jones+, 2018)\n",
      "I/349 :  StarHorse, Gaia DR2 photo-astrometric distances (Anders+, 2019)\n",
      "II/360 :  Gaia DR2 x AllWISE catalogue (Marton+, 2019)\n",
      "IV/35 :  Gaia DR2-WISE Galactic Plane Matches (Wilson+, 2018)\n",
      "VI/156 :  M-dwarf Lum-Temp-Radius relationships (Morrell+, 2019)\n",
      "VII/285 :  Gaia DR2 quasar and galaxy classification (Bailer-Jones+, 2019)\n",
      "J/ApJ/862/138 :  BANYAN. XIII. Nearby young assoc. with Gaia DR2 (Gagne+, 2018)\n",
      "J/ApJ/863/89 :  Gaia DR2 PMs of stars in ultra-faint MW satellites (Simon, 2018)\n",
      "J/ApJ/866/99 :  Revised radii of KIC stars & planets using Gaia DR2 (Berger+, 2018)\n",
      "J/ApJ/867/151 :  YSOs in the Gould Belt regions with Gaia-DR2 data (Dzib+, 2018)\n",
      "J/ApJ/868/70 :  Hot subdwarf stars from Gaia DR2 and LAMOST DR5 (Lei+, 2018)\n",
      "J/ApJ/870/32 :  Kinematics in young star clusters & associations (Kuhn+, 2019)\n",
      "J/ApJ/872/85 :  Detached eclipsing binaries with Gaia parallaxes (Graczyk+, 2019)\n",
      "J/ApJ/873/132 :  ICRF3 radio-loud quasars with Gaia DR2 data (Makarov+, 2019)\n",
      "J/ApJ/874/138 :  Gaia and LAMOST DR4 M giant members of Sgr stream (Li+, 2019)\n",
      "J/ApJ/875/77 :  Proper motions of MW satellites with Gaia & DES (Pace+, 2019)\n",
      "J/ApJ/877/29 :  Opt & NIR SMARTS/ANDICAM photometry for DQ Tau (Muzerolle+, 2019)\n",
      "J/ApJ/878/111 :  Members in Serpens Molecular Cloud with Gaia DR2 (Herczeg+, 2019)\n",
      "J/ApJ/881/7 :  Hot subdwarf stars from LAMOST DR5 & Gaia DR2 (Luo+, 2019)\n",
      "J/ApJ/881/135 :  Hot subdwarf stars from Gaia DR2 and LAMOST DR5. II. (Lei+, 2019)\n",
      "J/ApJ/883/8 :  Cand. young OB stars from GALEX & Gaia DR2 (Casetti-Dinescu+, 2019)\n",
      "J/ApJ/884/6 :  Known members of Orion A with Gaia DR2 data (McBride+, 2019)\n",
      "J/ApJ/886/100 :  High-mass white dwarfs in Gaia DR2 (Cheng+, 2019)\n",
      "J/ApJ/887/126 :  Follow-up obs. of the PSJ0147+4630 lens system (Goicoechea+, 2019)\n",
      "J/ApJ/888/73 :  Varstrometry of SDSS quasars with Gaia DR2 data (Hwang+, 2020)\n",
      "J/ApJ/889/99 :  Gaia DR2 Blanco 1 member candidates (Zhang+, 2020)\n",
      "J/ApJ/889/117 :  Hot subdwarf stars from Gaia DR2 & LAMOST DR6+7. I. (Lei+, 2020)\n",
      "J/ApJ/889/176 :  Very low-mass binaries with Gaia DR2 data (Faherty+, 2020)\n",
      "J/ApJ/898/64 :  Hot subdwarf stars from Gaia with LAMOST sp. II. RVs (Luo+, 2020)\n",
      "J/ApJ/898/173 :  Solar analog rotations from Kepler & Gaia (Do Nascimento+, 2020)\n",
      "J/ApJ/899/83 :  723 Gaia DR2 White dwarfs cand. in Local Galactic Halo (Kim+, 2020)\n",
      "J/ApJ/910/46 :  Galactic anticenter substructure stars from LAMOST (Li+, 2021)\n",
      "J/ApJ/913/120 :  4FGL blazars with Gaia DR2 data (Zeng+, 2021)\n",
      "J/ApJ/914/16 :  NGC 5128 GCs from PISCes, Gaia DR2 and NSC (Hughes+, 2021)\n",
      "J/ApJ/914/122 :  Stellar polarimetry with Gaia DR2 data (Doi+, 2021)\n",
      "J/ApJ/914/123 :  Gaia DR2 and EDR3 stars with sp. follow-up (Ibata+, 2021)\n",
      "J/ApJ/915/103 :  Oscillator strength ref. for Indus_0 & Indus_13 (Hansen+, 2021)\n",
      "J/ApJ/921/42 :  Gaia GraL. VI. Quadruply imaged lensed QSOs (Stern+, 2021)\n",
      "J/ApJS/245/32 :  Newly identified star clusters in Gaia DR2 (Liu+, 2019)\n",
      "J/ApJS/246/4 :  Catalog of ultrawide binary stars from Gaia DR2 (Tian+, 2020)\n",
      "J/ApJS/252/3 :  High-velocity stars in the Gal. halo from LAMOST & Gaia (Li+, 2021)\n",
      "J/ApJS/253/58 :  Ages of field stars from white dwarf comp. in Gaia (Qiu+, 2021)\n",
      "J/ApJS/254/20 :  Stellar groups in Taurus field from Gaia DR2 & LAMOST (Liu+, 2021)\n",
      "J/ApJS/256/28 :  Hot subdwarf stars with Gaia DR2 and LAMOST DR7 data (Luo+, 2021)\n",
      "J/ApJS/260/8 :  541 new open cluster candidates (He+, 2022)\n",
      "J/A+A/616/A7 :  Gaia DR2 radial velocity standard stars catalog (Soubiran+, 2018)\n",
      "J/A+A/616/A12 :  Gaia DR2 sources in GC and dSph (Gaia Collaboration+, 2018)\n",
      "J/A+A/616/A37 :  Close encounters to the Sun in Gaia DR2 (Bailer-Jones+, 2018)\n",
      "J/A+A/616/L2 :  Planetary Nebulae distances in Gaia DR2 (Kimeswenger+, 2018)\n",
      "J/A+A/616/L15 :  Parallaxes and Proper Motions of OB stars (Xu+, 2018)\n",
      "J/A+A/617/A135 :  20 years of photometric microlensing (Mustill+, 2018)\n",
      "J/A+A/618/A44 :  Predicted microlensing events from Gaia DR2 (Bramich, 2018)\n",
      "J/A+A/618/A56 :  Gaia GraL. II. Known multiply imaged quasars (Ducourant+, 2018)\n",
      "J/A+A/618/A59 :  Gaia DR2 confirmed new nearby open clusters (Castro-Ginard+, 2018)\n",
      "J/A+A/618/A93 :  Gaia DR2 open clusters in the Milky Way (Cantat-Gaudin+, 2018)\n",
      "J/A+A/619/A8 :  Cepheid period-luminosity-metallicity relation (Groenewegen, 2018)\n",
      "J/A+A/619/A106 :  3D shape of Orion A from Gaia DR2 (Grossschedl+, 2018)\n",
      "J/A+A/619/A155 :  Open cluster kinematics with Gaia DR2 (Soubiran+, 2018)\n",
      "J/A+A/619/A180 :  Gaia DR2 photometric sensitivity curves (Maiz Apellaniz+, 2018)\n",
      "J/A+A/619/L8 :  Ultra-cool dwarfs candidates in Gaia DR2 (Reyle, 2018)\n",
      "J/A+A/620/A91 :  New asteroid models (Durech+, 2018)\n",
      "J/A+A/620/A128 :  Gaia DR2 study of Herbig Ae/Be stars (Vioque+, 2018)\n",
      "J/A+A/620/A141 :  Physical properties of AM CVn stars (Ramsay+, 2018)\n",
      "J/A+A/620/A155 :  Gaia proper motions of 7 UFD galaxies (Massari+, 2018)\n",
      "J/A+A/620/A172 :  Solar neighbourhood young stars 3D mapping (Zari+, 2018)\n",
      "J/A+A/621/A38 :  Gaia catalogue of hot subluminous stars (Geier+, 2019)\n",
      "J/A+A/621/A48 :  Gaia-DR2 extended kinematical maps. I. (Lopez-Corredoira+, 2019)\n",
      "J/A+A/621/L2 :  Hyades tidal tails revealed by Gaia DR2 (Roeser+, 2019)\n",
      "J/A+A/621/L3 :  Hyades tidal tails with Gaia DR2 (Meingast+, 2019)\n",
      "J/A+A/622/A60 :  Gaia DR2 misclassified RR Lyrae list (Clementini+, 2019)\n",
      "J/A+A/622/A165 :  Gaia GraL. III. New lensed systems (Delchambre+, 2019)\n",
      "J/A+A/622/L13 :  Stellar stream in Gaia DR2 discovery (Meingast+, 2019)\n",
      "J/A+A/623/A22 :  IC 4996 Vilnius phot. and Gaia DR2 astrometry (Straizys+, 2019)\n",
      "J/A+A/623/A25 :  Photometric and astrometric study of NGC 6530 (Damiani+, 2019)\n",
      "J/A+A/623/A72 :  Binarity of Hipparcos stars from Gaia pm anomaly (Kervella+, 2019)\n",
      "J/A+A/623/A108 :  Age of 269 GDR2 open clusters (Bossini+, 2019)\n",
      "J/A+A/623/A110 :  Gaia DR2. Variable stars in CMD (Gaia Collaboration+, 2019)\n",
      "J/A+A/623/A112 :  The Sco OB2 population from Gaia DR2 data (Damiani+, 2019)\n",
      "J/A+A/623/A116 :  Galactic Cepheids and RR Lyrae multiplicity. I. (Kervella+, 2019)\n",
      "J/A+A/623/A117 :  Galactic Cepheids and RR Lyrae multiplicity. II (Kervella+, 2019)\n",
      "J/A+A/623/A129 :  New satellites of the LMC search (Fritz+, 2019)\n",
      "J/A+A/624/A78 :  Masses and ages of 1059 HARPS-GTO stars (Delgado Mena+, 2019)\n",
      "J/A+A/624/A126 :  New open clusters in Perseus direction (Cantat-Gaudin+, 2019)\n",
      "J/A+A/625/A14 :  Reclassification of Cepheids in the Gaia DR2 (Ripepi+, 2019)\n",
      "J/A+A/626/A80 :  Census of Rho Oph candidate members from Gaia DR2 (Canovas+, 2019)\n",
      "J/A+A/627/A35 :  New open clusters in Galactic anti-centre (Castro-Ginard+, 2019)\n",
      "J/A+A/627/A119 :  Extended halo of NGC 2682 (M 67) (Carrera+ 2019)\n",
      "J/A+A/628/A81 :  Gaia DR2-based catalogue of 237 Ap stars (Scholz+, 2019)\n",
      "J/A+A/629/A114 :  sigma Ori GTC+INT spectroscopy (Caballero+, 2019)\n",
      "J/A+A/630/A119 :  Gaia DR2 distances to two clusters (Maiz Apellaniz, 2019)\n",
      "J/A+A/630/A137 :  Structure and kinematics of the Taurus region (Galli+, 2019)\n",
      "J/A+A/630/A150 :  Astrometric data for 211 GAPN sample (Gonzalez-Santamaria+, 2019)\n",
      "J/A+A/631/A2 :  List of new asteroid models (Durech+, 2019)\n",
      "J/A+A/631/A145 :  HIP stars DEC proper motions comparison (Damljanovic+, 2019)\n",
      "J/A+A/633/A98 :  Gaia16aye microlensing event photometry (Wyrzykowski+, 2020)\n",
      "J/A+A/633/A99 :  Gaia DR2 open clusters in the Milky Way. II (Cantat-Gaudin+, 2020)\n",
      "J/A+A/633/A135 :  Solar neighbourhood carbon stars properties (Abia+, 2020)\n",
      "J/A+A/634/A98 :  Corona-Australis DANCe. I. (Galli+, 2020)\n",
      "J/A+A/635/A45 :  570 new open clusters in the Galactic disc (Castro-Ginard+, 2020)\n",
      "J/A+A/635/L3 :  Candidate member stars of the Sagittarius stream (Antoja+, 2020)\n",
      "J/A+A/636/A20 :  OGLE-III parallax events with Gaia DR2 (Wyrzykowski+, 2020)\n",
      "J/A+A/637/A95 :  16 open clusters UBVI and Gaia DR2 photometry (Perren+, 2020)\n",
      "J/A+A/638/A21 :  New Herbig Ae/Be and classical Be stars catalog (Vioque+, 2020)\n",
      "J/A+A/638/A103 :  Central stars of planetary nebulae in Gaia DR2 (Chornay+, 2020)\n",
      "J/A+A/638/A104 :  Gaia DR2 candidate RR Lyrae of Sgr stream & dwarf (Ramos+, 2020)\n",
      "J/A+A/641/A79 :  FEDReD. Extinction map with 2MASS and Gaia DR2 (Hottier+, 2020)\n",
      "J/A+A/642/A21 :  Astrometric parameters for 135 OB stars (Russeil+, 2020)\n",
      "J/A+A/643/A148 :  Lupus DANCe. Census and 6D structure with Gaia-DR2 (Galli+, 2020)\n",
      "J/A+A/644/A17 :  Astrometrically-selected QSO candidates (Heintz+, 2020)\n",
      "J/A+A/645/A72 :  Radial velocities of UCAC4 721-037069 (Clavel+, 2021)\n",
      "J/A+A/645/A116 :  NGC 2808, NGC 6266 and NGC 6397 Gaia DR2 sources (Kundu+, 2021)\n",
      "J/A+A/646/A46 :  Chamaeleon DANCe. Stellar population with Gaia-DR2 (Galli+, 2021)\n",
      "J/A+A/646/A99 :  Gaia DR2 Monoceros and ACS candidates (Ramos+, 2021)\n",
      "J/A+A/646/A104 :  Improving the open cluster census. I. (Hunt+, 2021)\n",
      "J/A+A/646/A183 :  Transit photometry of NGTS-14Ab (Smith+, 2021)\n",
      "J/A+A/648/A44 :  Large-amplitude variables in Gaia DR2 (Mowlavi+, 2021)\n",
      "J/A+A/653/A160 :  Updated radial velocities from Gaia DR2 (Seabroke+, 2021)\n",
      "J/A+A/657/A131 :  Ten new systems with O stars (Maiz Apellaniz+, 2022)\n",
      "J/AJ/156/94 :  APOGEE and Gaia DR2 analysis of IC 166 (Schiappacasse-Ulloa+, 2018)\n",
      "J/AJ/156/139 :  Main belt asteroid shape distrib. from Gaia DR2 (Mommert+, 2018)\n",
      "J/AJ/156/259 :  Robo-AO detected close binaries in Gaia DR2 (Ziegler+, 2018)\n",
      "J/AJ/156/264 :  California-Kepler Survey. VII. Planet radius gap (Fulton+, 2018)\n",
      "J/AJ/157/78 :  Double & multiple star systems from GaiaDR2 (Jimenez-Esteban+, 2019)\n",
      "J/AJ/158/20 :  K-M stars of class I candidate RSGs in Gaia DR2 (Messineo+, 2019)\n",
      "J/AJ/158/109 :  Occurrence rates of planets orbiting FGK stars (Hsu+, 2019)\n",
      "J/AJ/158/155 :  SB candidates from the RAVE & Gaia DR2 surveys (Birko+, 2019)\n",
      "J/AJ/159/84 :  Machine-learning regression of extinction in Gaia DR2 (Bai+, 2020)\n",
      "J/AJ/159/95 :  IC 1369 Vilnius photometry and Gaia DR2 astrometry (Straizys+, 2020)\n",
      "J/AJ/159/121 :  V-band light curve & RVs of the Cepheid V473Lyr (Evans+, 2020)\n",
      "J/AJ/159/139 :  Multiple M dwarf stars with Robo-AO and Gaia DR2 (Lamman+, 2020)\n",
      "J/AJ/159/166 :  Membership & properties of moving groups with Gaia (Ujjwal+, 2020)\n",
      "J/AJ/159/259 :  Opt-NIR light curve of the quasar 3C 273 (Sobrino Figaredo+, 2020)\n",
      "J/AJ/160/138 :  68 Gaia DR2 ultra-short-period planet host stars (Hamer+, 2020)\n",
      "J/AJ/160/284 :  2590 binary stars in Hipparcos and Gaia DR2 (Makarov, 2020)\n",
      "J/AJ/161/65 :  THYME. IV. 3 Exoplanets around TOI-451 B (Newton+, 2021)\n",
      "J/AJ/161/231 :  A list of ~330000 stars Kepler missed (Wolniewicz+, 2021)\n",
      "J/AJ/161/234 :  1.7 million K and M dwarfs cross-matching (Medan+, 2021)\n",
      "J/AJ/161/237 :  Positions of Triton with Sheshan Station telescope (Zhang+, 2021)\n",
      "J/AJ/162/181 :  RVel & Hipparcos positions of epsilon Eridani (Llop-sayson+, 2021)\n",
      "J/AJ/163/219 :  Gaia DR2 stellar flybys in the Sco-Cen OB association (Ma+, 2022)\n",
      "J/PASP/130/L4101 :  NGC 2112, 2477, 7789 and Col 261 members (Gao+ 2018)\n",
      "J/PASP/131/D4101 :  Likely Pleiades members with Gaia DR2 (Gao, 2019)\n",
      "J/MNRAS/480/467 :  Surface gravities for 15 000 Kepler stars (Pande+, 2018)\n",
      "J/MNRAS/480/4505 :  A white dwarf catalogue from Gaia-DR2 (Jimenez-Esteban+, 2018)\n",
      "J/MNRAS/480/5242 :  (non-)existence of five sparse open clusters (Kos+, 2018)\n",
      "J/MNRAS/481/1195 :  Gaia DR2 RR Lyrae stars as standard candles (Muraveva+, 2018)\n",
      "J/MNRAS/481/3887 :  Astrometry and photometry of 7 open clusters (Dias+, 2018)\n",
      "J/MNRAS/482/4570 :  Gaia DR2 white dwarf candidates (Gentile Fusillo+, 2019)\n",
      "J/MNRAS/482/5138 :  Galactic GC mean proper motions & velocities (Baumgardt+, 2019)\n",
      "J/MNRAS/482/5222 :  DA and DB white dwarfs properties in Gaia DR2 (Tremblay+, 2019)\n",
      "J/MNRAS/483/5508 :  Three new Galactic star clusters (Ferreira+, 2019)\n",
      "J/MNRAS/484/1838 :  Spatial substructure of Cygnus OB2 (Berlanas+, 2019)\n",
      "J/MNRAS/484/2832 :  Proper motions of Milky Way globular clusters (Vasiliev, 2019)\n",
      "J/MNRAS/485/4906 :  GC number density profiles using Gaia DR2 (de Boer+, 2019)\n",
      "J/MNRAS/485/5573 :  Gaia-DR2 100pc white dwarf population (Torres+, 2019)\n",
      "J/MNRAS/486/2477 :  Catalogue of members of NGC 6530 (Wright+, 2019)\n",
      "J/MNRAS/486/5726 :  80 young open clusters from Gaia DR2 (Dias+, 2019)\n",
      "J/MNRAS/487/1462 :  The metal-rich halo tail extended in z (Fernandez-Alvar+, 2019)\n",
      "J/MNRAS/487/2385 :  Distances and ages of 150 open clusters (Monteiro+, 2019)\n",
      "J/MNRAS/487/2771 :  Gaia-DR2 distance to the W3 Complex (Navarete+, 2019)\n",
      "J/MNRAS/487/4832 :  Period-luminosity relation of red supergiants (Chatys+, 2019)\n",
      "J/MNRAS/488/2743 :  Giant Galactic dwarf satellite in Gaia DR2 (Torrealba+, 2019)\n",
      "J/MNRAS/488/2892 :  Gaia DR2 extremely low-mass WD candidates (Pelisoli+, 2019)\n",
      "J/MNRAS/488/3024 :  Globular clusters members with Gaia DR2 (Bustos Fierro+, 2019)\n",
      "J/MNRAS/489/2079 :  Calibration of distances with deep learning (Leung+, 2019)\n",
      "J/MNRAS/489/3093 :  Gaia DR2 parallax of globular clusters (Shao+, 2019)\n",
      "J/MNRAS/490/157 :  Fastest stars in the Galaxy with Gaia DR2 (Marchetti+, 2019)\n",
      "J/MNRAS/490/5647 :  Correlations in unbound star trajectories (Montanari+, 2019)\n",
      "J/MNRAS/492/1164 :  Abundances of Gaia DR2 wide binaries (Hawkins+, 2020)\n",
      "J/MNRAS/492/L40 :  Disentangling cataclysmic variables in Gaia DR2 (Abril+, 2020)\n",
      "J/MNRAS/493/2339 :  Internal motions in OB-associations (Melnik+, 2020)\n",
      "J/MNRAS/495/663 :  Gaia DR2 OB associations (Ward+, 2020)\n",
      "J/MNRAS/496/2021 :  New Galactic open clusters (Ferreira+, 2020)\n",
      "J/MNRAS/502/6080 :  New members of Cygnus OB2 from Gaia DR2 (Orellana+, 2021)\n",
      "J/MNRAS/502/L90 :  Gaia DR2 Galactic bulge new star clusters (Ferreira+, 2021)\n",
      "J/MNRAS/503/3660 :  Gaia Spectrophotometric Standard Stars. V. (Pancino+, 2021)\n",
      "J/MNRAS/504/356 :  Updated parameters of 1743 open clusters (Dias+, 2021)\n",
      "J/MNRAS/505/1135 :  Gaia/IPHAS catalogue of Ha-excess sources (Fratta+, 2021)\n",
      "J/AZh/97/733 :  Binary Star Pop. with Common Proper Motion (Sapozhnikov+, 2020)\n",
      "J/AZh/98/239 :  Orbits of Four Visual Binaries (Romanenko+, 2021)\n",
      "J/AN/340/386 :  Catalogue of spectroscopic binary candidate stars (Jack, 2019)\n",
      "J/AN/341/770 :  Corrected proper motion for HIP stars (Damljanovic, 2020)\n",
      "J/AN/342/538 :  Frolov 1 and NGC 7510 CCD UBV photometry (Yontan+, 2021)\n",
      "J/AcA/68/351 :  Predicted Microlensing Events by nearby VLM objects (Nielsen+ 2018)\n",
      "J/other/ApSS/365.112 :  Kinematic data for high luminosity stars (Melnik+, 2020)\n",
      "J/other/RAA/21.93 :  74 new open clusters found in Gaia DR2 (He+, 2021)\n",
      "J/other/JDSO/15.434 :  New Binary Systems from Data of Gaia DR2 (Romanov, 2019)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: Unit 'k' not supported by the VOUnit standard. Did you mean K? [astropy.units.format.vounit]\n"
     ]
    }
   ],
   "source": [
    "catalog_list_gaia = Vizier.find_catalogs(\"Gaia DR2\", max_catalogs=1000)\n",
    "for k, v in catalog_list_gaia.items():\n",
    "    print(k, \": \", v.description)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For 2MASS we will want to use `II/246 :  2MASS All-Sky Catalog of Point Sources (Cutri+ 2003)` and for Gaia `I/345 :  Gaia DR2 (Gaia Collaboration, 2018)`. Before we query the full two tables we only look at a few sources for each table to understand which columns are available. The query below will give us 50 sources each -- the default for the `get_catalogs` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TableList with 1 tables:\n",
      "\t'0:II/246/out' with 15 column(s) and 50 row(s) \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=50</i>\n",
       "<table id=\"table140505900973120\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>RAJ2000</th><th>DEJ2000</th><th>_2MASS</th><th>Jmag</th><th>e_Jmag</th><th>Hmag</th><th>e_Hmag</th><th>Kmag</th><th>e_Kmag</th><th>Qflg</th><th>Rflg</th><th>Bflg</th><th>Cflg</th><th>Xflg</th><th>Aflg</th></tr></thead>\n",
       "<thead><tr><th>deg</th><th>deg</th><th></th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th></th><th></th><th></th><th></th><th></th><th></th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>str17</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>str3</th><th>str3</th><th>str3</th><th>str3</th><th>uint8</th><th>uint8</th></tr></thead>\n",
       "<tr><td>44.880847</td><td>0.616721</td><td>02593140+0037001</td><td>13.799</td><td>0.025</td><td>13.222</td><td>0.026</td><td>13.167</td><td>0.037</td><td>AAA</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.919229</td><td>0.610531</td><td>02594061+0036379</td><td>16.794</td><td>0.158</td><td>16.093</td><td>0.170</td><td>15.451</td><td>0.206</td><td>CCC</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.921658</td><td>0.617475</td><td>02594119+0037029</td><td>14.666</td><td>0.033</td><td>14.261</td><td>0.043</td><td>14.140</td><td>0.067</td><td>AAA</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.906036</td><td>0.626795</td><td>02593744+0037364</td><td>15.339</td><td>0.050</td><td>14.535</td><td>0.051</td><td>13.654</td><td>0.045</td><td>AAA</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.935480</td><td>0.621464</td><td>02594451+0037172</td><td>16.350</td><td>0.198</td><td>15.759</td><td>0.266</td><td>15.198</td><td>0.208</td><td>CDC</td><td>222</td><td>111</td><td>ccc</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.937738</td><td>0.624476</td><td>02594505+0037281</td><td>8.227</td><td>0.023</td><td>8.079</td><td>--</td><td>7.871</td><td>--</td><td>AUU</td><td>166</td><td>100</td><td>c00</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.937798</td><td>0.625384</td><td>02594507+0037313</td><td>8.562</td><td>0.048</td><td>8.094</td><td>0.042</td><td>7.972</td><td>0.063</td><td>AAA</td><td>111</td><td>111</td><td>ccc</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.915768</td><td>0.634722</td><td>02593978+0038049</td><td>16.275</td><td>0.104</td><td>15.532</td><td>0.098</td><td>15.565</td><td>0.228</td><td>AAD</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.897343</td><td>0.629454</td><td>02593536+0037460</td><td>15.688</td><td>0.064</td><td>15.529</td><td>0.102</td><td>15.062</td><td>0.150</td><td>AAB</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>44.856553</td><td>0.682358</td><td>02592557+0040564</td><td>13.869</td><td>--</td><td>13.752</td><td>--</td><td>13.295</td><td>0.059</td><td>UUE</td><td>002</td><td>001</td><td>00c</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.785319</td><td>0.640323</td><td>02590847+0038251</td><td>16.398</td><td>0.134</td><td>15.889</td><td>0.148</td><td>15.408</td><td>0.195</td><td>BBC</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.788202</td><td>0.655162</td><td>02590916+0039185</td><td>15.973</td><td>0.089</td><td>15.531</td><td>0.122</td><td>14.965</td><td>0.137</td><td>ABB</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.806605</td><td>0.671498</td><td>02591358+0040173</td><td>15.770</td><td>0.071</td><td>15.275</td><td>0.080</td><td>15.149</td><td>0.155</td><td>AAB</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.771958</td><td>0.697915</td><td>02590526+0041524</td><td>16.373</td><td>0.126</td><td>15.634</td><td>0.170</td><td>15.013</td><td>0.149</td><td>BCB</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.794553</td><td>0.719519</td><td>02591069+0043102</td><td>16.459</td><td>0.131</td><td>16.263</td><td>0.219</td><td>16.233</td><td>--</td><td>BDU</td><td>220</td><td>110</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.816167</td><td>0.725490</td><td>02591588+0043317</td><td>14.996</td><td>0.047</td><td>14.406</td><td>0.030</td><td>14.239</td><td>0.071</td><td>AAA</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.461157</td><td>0.461605</td><td>02575067+0027417</td><td>15.449</td><td>0.059</td><td>14.891</td><td>0.070</td><td>14.732</td><td>0.087</td><td>AAA</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.445146</td><td>0.474037</td><td>02574683+0028265</td><td>16.127</td><td>0.113</td><td>15.826</td><td>0.166</td><td>15.801</td><td>0.242</td><td>BCD</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>44.459680</td><td>0.483199</td><td>02575032+0028595</td><td>14.214</td><td>0.032</td><td>13.861</td><td>0.036</td><td>13.713</td><td>0.040</td><td>AAA</td><td>222</td><td>111</td><td>000</td><td>0</td><td>0</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=50>\n",
       " RAJ2000    DEJ2000        _2MASS        Jmag   e_Jmag ... Bflg Cflg  Xflg  Aflg\n",
       "   deg        deg                        mag     mag   ...                      \n",
       " float64    float64        str17       float32 float32 ... str3 str3 uint8 uint8\n",
       "---------- ---------- ---------------- ------- ------- ... ---- ---- ----- -----\n",
       " 44.880847   0.616721 02593140+0037001  13.799   0.025 ...  111  000     0     0\n",
       " 44.919229   0.610531 02594061+0036379  16.794   0.158 ...  111  000     0     0\n",
       " 44.921658   0.617475 02594119+0037029  14.666   0.033 ...  111  000     0     0\n",
       " 44.906036   0.626795 02593744+0037364  15.339   0.050 ...  111  000     0     0\n",
       " 44.935480   0.621464 02594451+0037172  16.350   0.198 ...  111  ccc     0     0\n",
       " 44.937738   0.624476 02594505+0037281   8.227   0.023 ...  100  c00     0     0\n",
       " 44.937798   0.625384 02594507+0037313   8.562   0.048 ...  111  ccc     0     0\n",
       " 44.915768   0.634722 02593978+0038049  16.275   0.104 ...  111  000     0     0\n",
       " 44.897343   0.629454 02593536+0037460  15.688   0.064 ...  111  000     0     0\n",
       "       ...        ...              ...     ...     ... ...  ...  ...   ...   ...\n",
       " 44.856553   0.682358 02592557+0040564  13.869      -- ...  001  00c     0     0\n",
       " 44.785319   0.640323 02590847+0038251  16.398   0.134 ...  111  000     0     0\n",
       " 44.788202   0.655162 02590916+0039185  15.973   0.089 ...  111  000     0     0\n",
       " 44.806605   0.671498 02591358+0040173  15.770   0.071 ...  111  000     0     0\n",
       " 44.771958   0.697915 02590526+0041524  16.373   0.126 ...  111  000     0     0\n",
       " 44.794553   0.719519 02591069+0043102  16.459   0.131 ...  110  000     0     0\n",
       " 44.816167   0.725490 02591588+0043317  14.996   0.047 ...  111  000     0     0\n",
       " 44.461157   0.461605 02575067+0027417  15.449   0.059 ...  111  000     0     0\n",
       " 44.445146   0.474037 02574683+0028265  16.127   0.113 ...  111  000     0     0\n",
       " 44.459680   0.483199 02575032+0028595  14.214   0.032 ...  111  000     0     0"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_twomass = Vizier.get_catalogs(\"II/246\")\n",
    "print(test_twomass)\n",
    "test_twomass[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TableList with 20 tables:\n",
      "\t'0:I/345/gaia2' with 32 column(s) and 50 row(s) \n",
      "\t'1:I/345/rvstdcat' with 32 column(s) and 50 row(s) \n",
      "\t'2:I/345/rvstdmes' with 7 column(s) and 50 row(s) \n",
      "\t'3:I/345/allwise' with 2 column(s) and 50 row(s) \n",
      "\t'4:I/345/iers' with 2 column(s) and 50 row(s) \n",
      "\t'5:I/345/cepheid' with 25 column(s) and 50 row(s) \n",
      "\t'6:I/345/rrlyrae' with 23 column(s) and 50 row(s) \n",
      "\t'7:I/345/lpv' with 13 column(s) and 50 row(s) \n",
      "\t'8:I/345/varres' with 9 column(s) and 50 row(s) \n",
      "\t'9:I/345/shortts' with 9 column(s) and 50 row(s) \n",
      "\t'10:I/345/tsstat' with 13 column(s) and 50 row(s) \n",
      "\t'11:I/345/numtrans' with 4 column(s) and 50 row(s) \n",
      "\t'12:I/345/transits' with 20 column(s) and 50 row(s) \n",
      "\t'13:I/345/rm' with 9 column(s) and 50 row(s) \n",
      "\t'14:I/345/rmseg' with 16 column(s) and 50 row(s) \n",
      "\t'15:I/345/rmout' with 2 column(s) and 50 row(s) \n",
      "\t'16:I/345/ssoobj' with 6 column(s) and 50 row(s) \n",
      "\t'17:I/345/ssoorb' with 19 column(s) and 50 row(s) \n",
      "\t'18:I/345/ssores' with 10 column(s) and 50 row(s) \n",
      "\t'19:I/345/ssoobs' with 7 column(s) and 50 row(s) \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=50</i>\n",
       "<table id=\"table140505900972544\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>RA_ICRS</th><th>e_RA_ICRS</th><th>DE_ICRS</th><th>e_DE_ICRS</th><th>Source</th><th>Plx</th><th>e_Plx</th><th>pmRA</th><th>e_pmRA</th><th>pmDE</th><th>e_pmDE</th><th>Dup</th><th>FG</th><th>e_FG</th><th>Gmag</th><th>e_Gmag</th><th>FBP</th><th>e_FBP</th><th>BPmag</th><th>e_BPmag</th><th>FRP</th><th>e_FRP</th><th>RPmag</th><th>e_RPmag</th><th>BP-RP</th><th>RV</th><th>e_RV</th><th>Teff</th><th>AG</th><th>E_BP-RP_</th><th>Rad</th><th>Lum</th></tr></thead>\n",
       "<thead><tr><th>deg</th><th>mas</th><th>deg</th><th>mas</th><th></th><th>mas</th><th>mas</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th></th><th></th><th></th><th>mag</th><th>mag</th><th></th><th></th><th>mag</th><th>mag</th><th></th><th></th><th>mag</th><th>mag</th><th>mag</th><th>km / s</th><th>km / s</th><th>K</th><th>mag</th><th>mag</th><th>solRad</th><th>solLum</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>uint8</th><th>float32</th><th>float32</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float64</th></tr></thead>\n",
       "<tr><td>43.37567140984</td><td>0.0787</td><td>1.64767103696</td><td>0.0624</td><td>1199434042673152</td><td>0.2597</td><td>0.0806</td><td>5.630</td><td>0.180</td><td>-11.762</td><td>0.137</td><td>0</td><td>3953</td><td>5.578</td><td>16.6960</td><td>0.0015</td><td>2269</td><td>15.95</td><td>16.9616</td><td>0.0076</td><td>2538</td><td>15.98</td><td>16.2506</td><td>0.0068</td><td>0.7110</td><td>--</td><td>--</td><td>6178.67</td><td>0.2280</td><td>0.1035</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.37501305522</td><td>2.3985</td><td>1.65561930146</td><td>1.9277</td><td>1199434042672896</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>1</td><td>111.4</td><td>1.406</td><td>20.5716</td><td>0.0137</td><td>65.92</td><td>8.151</td><td>20.8038</td><td>0.1343</td><td>180.1</td><td>6.338</td><td>19.1234</td><td>0.0382</td><td>1.6804</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.39513270047</td><td>0.1276</td><td>1.66076645797</td><td>0.1179</td><td>1199468402410624</td><td>1.2089</td><td>0.1449</td><td>2.465</td><td>0.279</td><td>-6.976</td><td>0.244</td><td>0</td><td>1314</td><td>2.141</td><td>17.8916</td><td>0.0018</td><td>398</td><td>11.42</td><td>18.8517</td><td>0.0312</td><td>1430</td><td>9.682</td><td>16.8733</td><td>0.0073</td><td>1.9783</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.37664436023</td><td>0.0398</td><td>1.66474921324</td><td>0.0336</td><td>1199537121887616</td><td>2.7472</td><td>0.0434</td><td>5.349</td><td>0.084</td><td>-1.891</td><td>0.072</td><td>0</td><td>1.232e+04</td><td>7.005</td><td>15.4614</td><td>0.0006</td><td>4113</td><td>17.66</td><td>16.3159</td><td>0.0047</td><td>1.211e+04</td><td>42.33</td><td>14.5544</td><td>0.0038</td><td>1.7615</td><td>--</td><td>--</td><td>3999.00</td><td>0.4920</td><td>0.2305</td><td>0.68</td><td>0.108</td></tr>\n",
       "<tr><td>43.37133802402</td><td>0.0426</td><td>1.67097166249</td><td>0.0353</td><td>1199537121887488</td><td>3.0263</td><td>0.0463</td><td>-6.832</td><td>0.088</td><td>-0.149</td><td>0.076</td><td>0</td><td>1.01e+04</td><td>6.026</td><td>15.6773</td><td>0.0006</td><td>3114</td><td>17.36</td><td>16.6179</td><td>0.0061</td><td>1.042e+04</td><td>22.19</td><td>14.7171</td><td>0.0023</td><td>1.9009</td><td>--</td><td>--</td><td>3849.10</td><td>0.0730</td><td>0.0385</td><td>0.64</td><td>0.080</td></tr>\n",
       "<tr><td>43.37037401008</td><td>0.0591</td><td>1.67298947920</td><td>0.0502</td><td>1199537121887232</td><td>3.1012</td><td>0.0643</td><td>-6.557</td><td>0.126</td><td>0.241</td><td>0.105</td><td>0</td><td>5374</td><td>5.161</td><td>16.3627</td><td>0.0010</td><td>1458</td><td>16.53</td><td>17.4420</td><td>0.0123</td><td>5955</td><td>17.24</td><td>15.3247</td><td>0.0031</td><td>2.1173</td><td>--</td><td>--</td><td>3629.00</td><td>0.2912</td><td>0.1525</td><td>0.55</td><td>0.047</td></tr>\n",
       "<tr><td>43.28964426631</td><td>2.2481</td><td>1.61837293176</td><td>2.7001</td><td>1199571481659904</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>0</td><td>185.1</td><td>2.015</td><td>20.0200</td><td>0.0118</td><td>179.7</td><td>9.093</td><td>19.7150</td><td>0.0549</td><td>509.2</td><td>8.803</td><td>17.9946</td><td>0.0188</td><td>1.7204</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.28266478407</td><td>0.1879</td><td>1.61673564165</td><td>0.2327</td><td>1199567185943808</td><td>2.9764</td><td>0.2883</td><td>45.350</td><td>0.398</td><td>-37.403</td><td>0.396</td><td>0</td><td>839.2</td><td>1.861</td><td>18.3787</td><td>0.0024</td><td>140.3</td><td>11.59</td><td>19.9839</td><td>0.0897</td><td>1090</td><td>9.65</td><td>17.1686</td><td>0.0096</td><td>2.8153</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.28541334923</td><td>0.1972</td><td>1.62910580263</td><td>0.2925</td><td>1199670265163008</td><td>0.3526</td><td>0.3248</td><td>-0.637</td><td>0.421</td><td>1.528</td><td>0.446</td><td>0</td><td>842.1</td><td>2.046</td><td>18.3750</td><td>0.0026</td><td>365.5</td><td>10.56</td><td>18.9441</td><td>0.0314</td><td>739.7</td><td>13.66</td><td>17.5893</td><td>0.0201</td><td>1.3548</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>43.16260585484</td><td>0.6304</td><td>1.63909018647</td><td>0.6567</td><td>1201560050910976</td><td>0.5479</td><td>0.7111</td><td>17.964</td><td>1.262</td><td>-4.538</td><td>1.243</td><td>0</td><td>197.1</td><td>1.535</td><td>19.9519</td><td>0.0085</td><td>96.65</td><td>17.38</td><td>20.3884</td><td>0.1952</td><td>243.9</td><td>19.17</td><td>18.7938</td><td>0.0853</td><td>1.5946</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.18328248057</td><td>8.6373</td><td>1.65409284989</td><td>2.3734</td><td>1201598706261248</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>0</td><td>89.12</td><td>1.449</td><td>20.8134</td><td>0.0177</td><td>58.07</td><td>12.11</td><td>20.9414</td><td>0.2264</td><td>59.16</td><td>16.44</td><td>20.3319</td><td>0.3018</td><td>0.6095</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.21840897363</td><td>0.0617</td><td>1.65948241460</td><td>0.0700</td><td>1201667425669504</td><td>0.4540</td><td>0.0731</td><td>3.966</td><td>0.124</td><td>3.945</td><td>0.133</td><td>0</td><td>5465</td><td>4.957</td><td>16.3444</td><td>0.0010</td><td>2883</td><td>17.56</td><td>16.7017</td><td>0.0066</td><td>3788</td><td>20.21</td><td>15.8160</td><td>0.0058</td><td>0.8857</td><td>--</td><td>--</td><td>5635.63</td><td>0.2535</td><td>0.1298</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.21564596936</td><td>0.4823</td><td>1.66024893820</td><td>0.5461</td><td>1201663129995264</td><td>1.4655</td><td>0.5736</td><td>2.869</td><td>1.014</td><td>0.636</td><td>1.094</td><td>0</td><td>234.6</td><td>1.388</td><td>19.7625</td><td>0.0064</td><td>91.28</td><td>10.27</td><td>20.4504</td><td>0.1221</td><td>275.5</td><td>9.663</td><td>18.6617</td><td>0.0381</td><td>1.7887</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.20386956231</td><td>0.1152</td><td>1.66081348887</td><td>0.1243</td><td>1201667425669888</td><td>0.2775</td><td>0.1406</td><td>1.284</td><td>0.249</td><td>-2.669</td><td>0.260</td><td>0</td><td>1856</td><td>2.826</td><td>17.5168</td><td>0.0017</td><td>992.7</td><td>36.83</td><td>17.8593</td><td>0.0403</td><td>1309</td><td>14.67</td><td>16.9699</td><td>0.0122</td><td>0.8894</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.12139599208</td><td>17.1743</td><td>1.61414835070</td><td>8.1939</td><td>1201804864208000</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>1</td><td>112.6</td><td>2.928</td><td>20.5597</td><td>0.0282</td><td>27.37</td><td>15.66</td><td>21.7583</td><td>0.6211</td><td>266.1</td><td>12.32</td><td>18.6994</td><td>0.0503</td><td>3.0589</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.14339449010</td><td>0.0270</td><td>1.65068368722</td><td>0.0263</td><td>1202384684461440</td><td>3.3337</td><td>0.0319</td><td>54.576</td><td>0.056</td><td>-61.800</td><td>0.055</td><td>0</td><td>4.091e+04</td><td>14.45</td><td>14.1587</td><td>0.0004</td><td>1.731e+04</td><td>30.26</td><td>14.7556</td><td>0.0019</td><td>3.394e+04</td><td>107.3</td><td>13.4351</td><td>0.0034</td><td>1.3204</td><td>--</td><td>--</td><td>5049.69</td><td>--</td><td>--</td><td>0.52</td><td>0.159</td></tr>\n",
       "<tr><td>43.09609491604</td><td>0.0432</td><td>1.63648124122</td><td>0.0364</td><td>1202075446817152</td><td>2.8015</td><td>0.0453</td><td>19.838</td><td>0.091</td><td>-14.500</td><td>0.075</td><td>0</td><td>5.243e+05</td><td>327.6</td><td>11.3894</td><td>0.0007</td><td>2.91e+05</td><td>253</td><td>11.6918</td><td>0.0009</td><td>3.361e+05</td><td>390.1</td><td>10.9459</td><td>0.0013</td><td>0.7460</td><td>-2.33</td><td>0.66</td><td>5926.00</td><td>0.4810</td><td>0.2410</td><td>1.53</td><td>2.618</td></tr>\n",
       "<tr><td>43.09701024614</td><td>0.1373</td><td>1.64733321106</td><td>0.1376</td><td>1202075446851968</td><td>1.9128</td><td>0.1646</td><td>-6.063</td><td>0.273</td><td>1.246</td><td>0.247</td><td>0</td><td>1598</td><td>3.348</td><td>17.6797</td><td>0.0023</td><td>398.2</td><td>5.162</td><td>18.8510</td><td>0.0141</td><td>1856</td><td>16.5</td><td>16.5906</td><td>0.0097</td><td>2.2604</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>43.07008499536</td><td>2.3747</td><td>1.64028324280</td><td>6.6744</td><td>1202109806879360</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>0</td><td>91.25</td><td>2.553</td><td>20.7878</td><td>0.0304</td><td>67.64</td><td>37.05</td><td>20.7759</td><td>0.5948</td><td>147.4</td><td>29.38</td><td>19.3404</td><td>0.2164</td><td>1.4355</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=50>\n",
       "    RA_ICRS     e_RA_ICRS     DE_ICRS     ... E_BP-RP_   Rad      Lum   \n",
       "      deg          mas          deg       ...   mag     solRad   solLum \n",
       "    float64      float64      float64     ... float32  float32  float64 \n",
       "--------------- --------- --------------- ... -------- ------- ---------\n",
       " 43.37567140984    0.0787   1.64767103696 ...   0.1035      --        --\n",
       " 43.37501305522    2.3985   1.65561930146 ...       --      --        --\n",
       " 43.39513270047    0.1276   1.66076645797 ...       --      --        --\n",
       " 43.37664436023    0.0398   1.66474921324 ...   0.2305    0.68     0.108\n",
       " 43.37133802402    0.0426   1.67097166249 ...   0.0385    0.64     0.080\n",
       " 43.37037401008    0.0591   1.67298947920 ...   0.1525    0.55     0.047\n",
       " 43.28964426631    2.2481   1.61837293176 ...       --      --        --\n",
       " 43.28266478407    0.1879   1.61673564165 ...       --      --        --\n",
       " 43.28541334923    0.1972   1.62910580263 ...       --      --        --\n",
       "            ...       ...             ... ...      ...     ...       ...\n",
       " 43.16260585484    0.6304   1.63909018647 ...       --      --        --\n",
       " 43.18328248057    8.6373   1.65409284989 ...       --      --        --\n",
       " 43.21840897363    0.0617   1.65948241460 ...   0.1298      --        --\n",
       " 43.21564596936    0.4823   1.66024893820 ...       --      --        --\n",
       " 43.20386956231    0.1152   1.66081348887 ...       --      --        --\n",
       " 43.12139599208   17.1743   1.61414835070 ...       --      --        --\n",
       " 43.14339449010    0.0270   1.65068368722 ...       --    0.52     0.159\n",
       " 43.09609491604    0.0432   1.63648124122 ...   0.2410    1.53     2.618\n",
       " 43.09701024614    0.1373   1.64733321106 ...       --      --        --\n",
       " 43.07008499536    2.3747   1.64028324280 ...       --      --        --"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_gaia = Vizier.get_catalogs(\"I/345\")\n",
    "print(test_gaia)\n",
    "test_gaia[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you will see below, we only need coordinates, 2MASS photometry in the H and K band, and Gaia photometry in the Gaia G band. So we'll query the tables `II/246/out` for 2MASS and `I/345/gaia2` for Gaia DR2:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=19784</i>\n",
       "<table id=\"table140505950158176\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>_2MASS</th><th>RAJ2000</th><th>DEJ2000</th><th>errHalfMaj</th><th>errHalfMin</th><th>errPosAng</th><th>Jmag</th><th>Hmag</th><th>Kmag</th><th>e_Jmag</th><th>e_Hmag</th><th>e_Kmag</th><th>Qfl</th><th>Rfl</th><th>X</th><th>MeasureJD</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>arcsec</th><th>arcsec</th><th>deg</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th></th><th></th><th></th><th>d</th></tr></thead>\n",
       "<thead><tr><th>str17</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>str3</th><th>int16</th><th>uint8</th><th>float64</th></tr></thead>\n",
       "<tr><td>07004924-2609161</td><td>105.205199</td><td>-26.154478</td><td>0.06</td><td>0.06</td><td>90.0</td><td>12.241</td><td>11.679</td><td>11.401</td><td>0.027</td><td>0.026</td><td>0.023</td><td>AAA</td><td>222</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005553-2609080</td><td>105.231379</td><td>-26.152241</td><td>0.07</td><td>0.07</td><td>45.0</td><td>15.443</td><td>14.916</td><td>14.773</td><td>0.033</td><td>0.049</td><td>0.109</td><td>AAB</td><td>222</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005410-2608455</td><td>105.225439</td><td>-26.145973</td><td>0.06</td><td>0.06</td><td>90.0</td><td>10.554</td><td>10.259</td><td>10.203</td><td>0.024</td><td>0.024</td><td>0.019</td><td>AAA</td><td>222</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005605-2608553</td><td>105.233576</td><td>-26.14872</td><td>0.06</td><td>0.06</td><td>90.0</td><td>11.891</td><td>11.6</td><td>11.596</td><td>0.026</td><td>0.024</td><td>0.023</td><td>AAA</td><td>222</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005809-2608512</td><td>105.242043</td><td>-26.147581</td><td>0.21</td><td>0.2</td><td>109.0</td><td>16.746</td><td>16.293</td><td>15.534</td><td>0.138</td><td>0.199</td><td>--</td><td>BCU</td><td>220</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005247-2609231</td><td>105.218641</td><td>-26.156427</td><td>0.08</td><td>0.08</td><td>135.0</td><td>15.602</td><td>15.26</td><td>15.049</td><td>0.063</td><td>0.077</td><td>0.147</td><td>AAB</td><td>222</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005211-2609189</td><td>105.217137</td><td>-26.155258</td><td>0.06</td><td>0.06</td><td>90.0</td><td>14.179</td><td>13.935</td><td>13.901</td><td>0.041</td><td>0.043</td><td>0.065</td><td>AAA</td><td>222</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005137-2609029</td><td>105.214075</td><td>-26.150816</td><td>0.19</td><td>0.19</td><td>45.0</td><td>16.608</td><td>16.15</td><td>16.086</td><td>0.131</td><td>0.17</td><td>--</td><td>BCU</td><td>220</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>07005056-2609004</td><td>105.210699</td><td>-26.150122</td><td>0.15</td><td>0.15</td><td>45.0</td><td>16.472</td><td>15.976</td><td>15.562</td><td>0.125</td><td>0.15</td><td>--</td><td>BBU</td><td>220</td><td>0</td><td>2451208.5657</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>12404417-5347160</td><td>190.18405</td><td>-53.7878</td><td>0.08</td><td>0.07</td><td>5.0</td><td>15.549</td><td>14.867</td><td>14.521</td><td>0.07</td><td>0.086</td><td>0.104</td><td>AAA</td><td>222</td><td>0</td><td>2451312.531</td></tr>\n",
       "<tr><td>12404086-5347259</td><td>190.17025</td><td>-53.79055</td><td>0.08</td><td>0.07</td><td>5.0</td><td>15.313</td><td>14.878</td><td>14.915</td><td>0.056</td><td>0.067</td><td>0.144</td><td>AAB</td><td>222</td><td>0</td><td>2451312.531</td></tr>\n",
       "<tr><td>12404683-5347492</td><td>190.195133</td><td>-53.797001</td><td>0.08</td><td>0.07</td><td>5.0</td><td>15.064</td><td>14.632</td><td>14.569</td><td>0.052</td><td>0.073</td><td>0.099</td><td>AAA</td><td>222</td><td>0</td><td>2451312.531</td></tr>\n",
       "<tr><td>12404640-5347396</td><td>190.193372</td><td>-53.794361</td><td>0.07</td><td>0.06</td><td>0.0</td><td>13.27</td><td>12.911</td><td>12.881</td><td>0.023</td><td>0.031</td><td>0.031</td><td>AAA</td><td>222</td><td>0</td><td>2451312.531</td></tr>\n",
       "<tr><td>12093034-5553408</td><td>182.376454</td><td>-55.894691</td><td>0.23</td><td>0.22</td><td>65.0</td><td>16.436</td><td>15.895</td><td>16.865</td><td>0.131</td><td>0.19</td><td>--</td><td>BCU</td><td>220</td><td>0</td><td>2451384.4889</td></tr>\n",
       "<tr><td>12093037-5553252</td><td>182.376575</td><td>-55.89035</td><td>0.27</td><td>0.26</td><td>43.0</td><td>16.389</td><td>16.026</td><td>16.561</td><td>0.127</td><td>0.217</td><td>--</td><td>BDU</td><td>220</td><td>0</td><td>2451384.4889</td></tr>\n",
       "<tr><td>12093089-5553446</td><td>182.378724</td><td>-55.895725</td><td>0.17</td><td>0.17</td><td>145.0</td><td>16.26</td><td>15.616</td><td>15.839</td><td>0.117</td><td>0.157</td><td>--</td><td>BCU</td><td>220</td><td>0</td><td>2451384.4889</td></tr>\n",
       "<tr><td>12093019-5553333</td><td>182.375829</td><td>-55.892605</td><td>0.07</td><td>0.07</td><td>17.0</td><td>15.282</td><td>14.897</td><td>14.683</td><td>0.051</td><td>0.095</td><td>0.119</td><td>AAB</td><td>222</td><td>0</td><td>2451384.4889</td></tr>\n",
       "<tr><td>12093246-5553264</td><td>182.385279</td><td>-55.890694</td><td>0.06</td><td>0.06</td><td>17.0</td><td>13.705</td><td>13.012</td><td>12.816</td><td>0.027</td><td>0.032</td><td>0.035</td><td>AAA</td><td>222</td><td>0</td><td>2451384.4889</td></tr>\n",
       "<tr><td>12093324-5553089</td><td>182.388524</td><td>-55.885818</td><td>0.08</td><td>0.07</td><td>3.0</td><td>15.77</td><td>15.261</td><td>14.976</td><td>0.074</td><td>0.111</td><td>0.139</td><td>ABB</td><td>222</td><td>0</td><td>2451384.4889</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=19784>\n",
       "     _2MASS       RAJ2000    DEJ2000   errHalfMaj ...  Rfl    X    MeasureJD  \n",
       "                    deg        deg       arcsec   ...                  d      \n",
       "     str17        float64    float64    float32   ... int16 uint8   float64   \n",
       "---------------- ---------- ---------- ---------- ... ----- ----- ------------\n",
       "07004924-2609161 105.205199 -26.154478       0.06 ...   222     0 2451208.5657\n",
       "07005553-2609080 105.231379 -26.152241       0.07 ...   222     0 2451208.5657\n",
       "07005410-2608455 105.225439 -26.145973       0.06 ...   222     0 2451208.5657\n",
       "07005605-2608553 105.233576  -26.14872       0.06 ...   222     0 2451208.5657\n",
       "07005809-2608512 105.242043 -26.147581       0.21 ...   220     0 2451208.5657\n",
       "07005247-2609231 105.218641 -26.156427       0.08 ...   222     0 2451208.5657\n",
       "07005211-2609189 105.217137 -26.155258       0.06 ...   222     0 2451208.5657\n",
       "07005137-2609029 105.214075 -26.150816       0.19 ...   220     0 2451208.5657\n",
       "07005056-2609004 105.210699 -26.150122       0.15 ...   220     0 2451208.5657\n",
       "             ...        ...        ...        ... ...   ...   ...          ...\n",
       "12404417-5347160  190.18405   -53.7878       0.08 ...   222     0  2451312.531\n",
       "12404086-5347259  190.17025  -53.79055       0.08 ...   222     0  2451312.531\n",
       "12404683-5347492 190.195133 -53.797001       0.08 ...   222     0  2451312.531\n",
       "12404640-5347396 190.193372 -53.794361       0.07 ...   222     0  2451312.531\n",
       "12093034-5553408 182.376454 -55.894691       0.23 ...   220     0 2451384.4889\n",
       "12093037-5553252 182.376575  -55.89035       0.27 ...   220     0 2451384.4889\n",
       "12093089-5553446 182.378724 -55.895725       0.17 ...   220     0 2451384.4889\n",
       "12093019-5553333 182.375829 -55.892605       0.07 ...   222     0 2451384.4889\n",
       "12093246-5553264 182.385279 -55.890694       0.06 ...   222     0 2451384.4889\n",
       "12093324-5553089 182.388524 -55.885818       0.08 ...   222     0 2451384.4889"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "twomass = moc_intersection.query_vizier_table(\"II/246/out\", max_rows=20000)\n",
    "twomass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=20000</i>\n",
       "<table id=\"table140505578232304\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>ra_epoch2000</th><th>dec_epoch2000</th><th>errHalfMaj</th><th>errHalfMin</th><th>errPosAng</th><th>source_id</th><th>ra</th><th>ra_error</th><th>dec</th><th>dec_error</th><th>parallax</th><th>parallax_error</th><th>pmra</th><th>pmra_error</th><th>pmdec</th><th>pmdec_error</th><th>duplicated_source</th><th>phot_g_mean_flux</th><th>phot_g_mean_flux_error</th><th>phot_g_mean_mag</th><th>phot_bp_mean_flux</th><th>phot_bp_mean_flux_error</th><th>phot_bp_mean_mag</th><th>phot_rp_mean_flux</th><th>phot_rp_mean_flux_error</th><th>phot_rp_mean_mag</th><th>bp_rp</th><th>radial_velocity</th><th>radial_velocity_error</th><th>rv_nb_transits</th><th>teff_val</th><th>a_g_val</th><th>e_bp_min_rp_val</th><th>radius_val</th><th>lum_val</th></tr></thead>\n",
       "<thead><tr><th>deg</th><th>deg</th><th>arcsec</th><th>arcsec</th><th>deg</th><th></th><th>deg</th><th>mas</th><th>deg</th><th>mas</th><th>mas</th><th>mas</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th></th><th>e-/s</th><th>e-/s</th><th>mag</th><th>e-/s</th><th>e-/s</th><th>mag</th><th>e-/s</th><th>e-/s</th><th>mag</th><th>mag</th><th>km / s</th><th>km / s</th><th></th><th>K</th><th>mag</th><th>mag</th><th>Rsun</th><th>Lsun</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>int64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>bool</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>int16</th><th>float64</th><th>float32</th><th>float32</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>105.2066061184302</td><td>-26.1538940663577</td><td>0.004</td><td>0.004</td><td>0.0</td><td>2920762586611045376</td><td>105.20658290054</td><td>0.1161</td><td>-26.15393087599</td><td>0.149</td><td>0.136</td><td>0.1944</td><td>-4.84</td><td>0.253</td><td>-8.549</td><td>0.271</td><td>False</td><td>602.539</td><td>1.1074</td><td>18.738403</td><td>267.377</td><td>5.59862</td><td>19.283577</td><td>535.627</td><td>6.13289</td><td>17.939764</td><td>1.343813</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>105.2052022499317</td><td>-26.1544492445426</td><td>0.001</td><td>0.001</td><td>0.0</td><td>2920762586615338752</td><td>105.20527986473</td><td>0.0267</td><td>-26.15425317585</td><td>0.0358</td><td>15.1333</td><td>0.0454</td><td>16.181</td><td>0.059</td><td>45.539</td><td>0.066</td><td>False</td><td>16217.1</td><td>8.55749</td><td>15.163431</td><td>2736.6</td><td>12.0165</td><td>16.75836</td><td>21463.4</td><td>32.9159</td><td>13.932673</td><td>2.825687</td><td>--</td><td>--</td><td>0</td><td>3928.82</td><td>0.1227</td><td>0.094</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>105.2254316259827</td><td>-26.1459685548036</td><td>0.001</td><td>0.001</td><td>0.0</td><td>2920762724054281728</td><td>105.22540767106</td><td>0.0161</td><td>-26.14597192505</td><td>0.0217</td><td>3.0363</td><td>0.0265</td><td>-4.994</td><td>0.034</td><td>-0.783</td><td>0.039</td><td>False</td><td>447474.0</td><td>150.212</td><td>11.561445</td><td>240915.0</td><td>221.395</td><td>11.896729</td><td>295385.0</td><td>244.062</td><td>11.085948</td><td>0.810782</td><td>12.24</td><td>0.54</td><td>10</td><td>5789.0</td><td>0.359</td><td>0.195</td><td>1.38</td><td>1.916</td></tr>\n",
       "<tr><td>105.2255476000922</td><td>-26.1406471806866</td><td>0.062</td><td>0.038</td><td>90.0</td><td>2920762724052466816</td><td>105.22555538166</td><td>2.0243</td><td>-26.14064454062</td><td>1.4671</td><td>-4.0178</td><td>1.6818</td><td>1.622</td><td>3.991</td><td>0.613</td><td>2.468</td><td>False</td><td>76.608</td><td>1.20685</td><td>20.97768</td><td>36.0788</td><td>7.86989</td><td>21.458258</td><td>65.0345</td><td>7.80032</td><td>20.229061</td><td>1.229197</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>105.2186311670325</td><td>-26.156438621226</td><td>0.002</td><td>0.001</td><td>0.0</td><td>2920762685395330944</td><td>105.21862542833</td><td>0.0384</td><td>-26.1564233977</td><td>0.0518</td><td>0.4535</td><td>0.0652</td><td>-1.196</td><td>0.088</td><td>3.536</td><td>0.101</td><td>False</td><td>3596.37</td><td>2.41419</td><td>16.798706</td><td>1782.51</td><td>6.52961</td><td>17.223808</td><td>2630.98</td><td>10.0304</td><td>16.211626</td><td>1.012182</td><td>--</td><td>--</td><td>0</td><td>5324.0</td><td>0.2803</td><td>0.14</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>105.2119407930607</td><td>-26.148242191244</td><td>0.012</td><td>0.011</td><td>0.0</td><td>2920762689690245120</td><td>105.21193444979</td><td>0.3448</td><td>-26.14822964561</td><td>0.433</td><td>0.6099</td><td>0.6059</td><td>-1.322</td><td>0.699</td><td>2.914</td><td>0.795</td><td>False</td><td>151.185</td><td>0.741582</td><td>20.239592</td><td>58.4888</td><td>5.62295</td><td>20.933706</td><td>147.958</td><td>5.41634</td><td>19.336573</td><td>1.597134</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>105.2101027197529</td><td>-26.1493188643026</td><td>0.003</td><td>0.002</td><td>0.0</td><td>2920762685393857664</td><td>105.21008829533</td><td>0.075</td><td>-26.14929289497</td><td>0.1004</td><td>0.5265</td><td>0.1263</td><td>-3.007</td><td>0.157</td><td>6.032</td><td>0.181</td><td>False</td><td>1089.74</td><td>1.25074</td><td>18.09506</td><td>474.512</td><td>8.77005</td><td>18.66077</td><td>951.979</td><td>11.217</td><td>17.315351</td><td>1.345419</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>105.233577941629</td><td>-26.1487114377012</td><td>0.001</td><td>0.001</td><td>0.0</td><td>2920762655334900352</td><td>105.23358687293</td><td>0.0188</td><td>-26.14871224799</td><td>0.0281</td><td>0.6511</td><td>0.0338</td><td>1.862</td><td>0.039</td><td>-0.188</td><td>0.05</td><td>False</td><td>141155.0</td><td>27.6249</td><td>12.814123</td><td>79733.0</td><td>74.3211</td><td>13.097294</td><td>90552.3</td><td>113.271</td><td>12.369671</td><td>0.727623</td><td>--</td><td>--</td><td>0</td><td>6290.0</td><td>--</td><td>--</td><td>3.03</td><td>12.909</td></tr>\n",
       "<tr><td>105.2298314760221</td><td>-26.1384116458451</td><td>0.006</td><td>0.005</td><td>0.0</td><td>2920762719755070720</td><td>105.2298328238</td><td>0.1448</td><td>-26.13840364909</td><td>0.2119</td><td>-0.4599</td><td>0.2489</td><td>0.281</td><td>0.308</td><td>1.857</td><td>0.383</td><td>False</td><td>1198.17</td><td>3.55001</td><td>17.99207</td><td>586.998</td><td>6.56335</td><td>18.429798</td><td>1042.57</td><td>5.6909</td><td>17.216658</td><td>1.213141</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>286.6944839297623</td><td>-16.5791122649035</td><td>0.013</td><td>0.012</td><td>90.0</td><td>4088730220650842112</td><td>286.69447423648</td><td>0.4206</td><td>-16.57914487135</td><td>0.3966</td><td>0.1547</td><td>0.435</td><td>-2.158</td><td>0.825</td><td>-7.573</td><td>0.752</td><td>False</td><td>249.761</td><td>1.3222</td><td>19.694551</td><td>114.872</td><td>17.7943</td><td>20.200851</td><td>200.298</td><td>10.7865</td><td>19.007727</td><td>1.193125</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6993829324819</td><td>-16.5821039497348</td><td>0.004</td><td>0.003</td><td>90.0</td><td>4088730216353585920</td><td>286.69937395748</td><td>0.1357</td><td>-16.58213272386</td><td>0.1369</td><td>0.1246</td><td>0.1411</td><td>-1.998</td><td>0.238</td><td>-6.683</td><td>0.215</td><td>False</td><td>1981.79</td><td>3.06034</td><td>17.445724</td><td>844.279</td><td>10.0523</td><td>18.035173</td><td>1643.97</td><td>10.3648</td><td>16.722185</td><td>1.312988</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6963834136197</td><td>-16.5849153146221</td><td>0.002</td><td>0.001</td><td>90.0</td><td>4088730220669538688</td><td>286.69637839819</td><td>0.0527</td><td>-16.58490847684</td><td>0.0491</td><td>0.0708</td><td>0.055</td><td>-1.116</td><td>0.102</td><td>1.588</td><td>0.089</td><td>False</td><td>9283.59</td><td>7.20664</td><td>15.769075</td><td>3756.87</td><td>14.4613</td><td>16.414322</td><td>7967.53</td><td>26.8564</td><td>15.008611</td><td>1.405711</td><td>--</td><td>--</td><td>0</td><td>4809.62</td><td>0.348</td><td>0.1653</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6938297521173</td><td>-16.5806976451671</td><td>0.037</td><td>0.033</td><td>0.0</td><td>4088730220650841472</td><td>286.69380780318</td><td>0.8091</td><td>-16.58070500216</td><td>0.7449</td><td>1.6569</td><td>0.9279</td><td>-4.886</td><td>2.144</td><td>-1.709</td><td>2.399</td><td>False</td><td>126.719</td><td>1.9013</td><td>20.431263</td><td>248.985</td><td>155.818</td><td>19.360956</td><td>117.25</td><td>48.3755</td><td>19.589136</td><td>-0.22818</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6937302999216</td><td>-16.586352116054</td><td>0.017</td><td>0.015</td><td>90.0</td><td>4088730186289924096</td><td>286.6937419687</td><td>0.5747</td><td>-16.58637019079</td><td>0.5313</td><td>0.6284</td><td>0.5059</td><td>2.597</td><td>1.078</td><td>-4.198</td><td>0.941</td><td>False</td><td>242.495</td><td>1.42055</td><td>19.726606</td><td>187.615</td><td>8.71396</td><td>19.668219</td><td>258.771</td><td>12.5838</td><td>18.729631</td><td>0.938587</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6923263914704</td><td>-16.5950076068847</td><td>0.016</td><td>0.014</td><td>90.0</td><td>4088730117570391680</td><td>286.69228689634</td><td>0.5148</td><td>-16.59503562694</td><td>0.486</td><td>0.0273</td><td>0.4912</td><td>-8.791</td><td>1.005</td><td>-6.508</td><td>0.919</td><td>False</td><td>254.175</td><td>1.17755</td><td>19.675533</td><td>166.733</td><td>7.80453</td><td>19.796333</td><td>186.025</td><td>13.988</td><td>19.087994</td><td>0.70834</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6990751669917</td><td>-16.5854870711225</td><td>0.031</td><td>0.03</td><td>0.0</td><td>4088730220650832384</td><td>286.69907017979</td><td>0.8828</td><td>-16.58550441555</td><td>0.8566</td><td>0.4562</td><td>0.795</td><td>-1.11</td><td>1.964</td><td>-4.028</td><td>1.977</td><td>False</td><td>127.25</td><td>1.32415</td><td>20.426722</td><td>93.6008</td><td>14.2788</td><td>20.42319</td><td>101.515</td><td>14.6011</td><td>19.745594</td><td>0.677595</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.699727987182</td><td>-16.5849042116214</td><td>0.003</td><td>0.003</td><td>90.0</td><td>4088730216353575936</td><td>286.69972717633</td><td>0.1016</td><td>-16.58492114919</td><td>0.0954</td><td>0.1231</td><td>0.1025</td><td>-0.18</td><td>0.191</td><td>-3.934</td><td>0.172</td><td>False</td><td>2902.42</td><td>3.65924</td><td>17.031467</td><td>1430.36</td><td>11.801</td><td>17.462772</td><td>2171.63</td><td>25.1919</td><td>16.419954</td><td>1.042818</td><td>--</td><td>--</td><td>0</td><td>5063.84</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6915147248319</td><td>-16.5880323030601</td><td>0.012</td><td>0.011</td><td>90.0</td><td>4088730186289926528</td><td>286.69151218666</td><td>0.4126</td><td>-16.58806439493</td><td>0.3824</td><td>0.2903</td><td>0.4003</td><td>-0.565</td><td>0.793</td><td>-7.454</td><td>0.721</td><td>False</td><td>311.3</td><td>1.37999</td><td>19.455416</td><td>147.821</td><td>8.99601</td><td>19.92705</td><td>232.117</td><td>9.25892</td><td>18.847652</td><td>1.079397</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "<tr><td>286.6980906584381</td><td>-16.589175455702</td><td>0.003</td><td>0.003</td><td>90.0</td><td>4088730117570395264</td><td>286.69809065844</td><td>3.096</td><td>-16.5891754557</td><td>2.5481</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>False</td><td>115.568</td><td>1.27166</td><td>20.531275</td><td>91.317</td><td>15.7204</td><td>20.450008</td><td>100.718</td><td>11.8582</td><td>19.754148</td><td>0.69586</td><td>--</td><td>--</td><td>0</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=20000>\n",
       "   ra_epoch2000     dec_epoch2000   errHalfMaj ... radius_val lum_val\n",
       "       deg               deg          arcsec   ...    Rsun      Lsun \n",
       "     float64           float64       float32   ...  float64   float64\n",
       "----------------- ----------------- ---------- ... ---------- -------\n",
       "105.2066061184302 -26.1538940663577      0.004 ...         --      --\n",
       "105.2052022499317 -26.1544492445426      0.001 ...         --      --\n",
       "105.2254316259827 -26.1459685548036      0.001 ...       1.38   1.916\n",
       "105.2255476000922 -26.1406471806866      0.062 ...         --      --\n",
       "105.2186311670325  -26.156438621226      0.002 ...         --      --\n",
       "105.2119407930607  -26.148242191244      0.012 ...         --      --\n",
       "105.2101027197529 -26.1493188643026      0.003 ...         --      --\n",
       " 105.233577941629 -26.1487114377012      0.001 ...       3.03  12.909\n",
       "105.2298314760221 -26.1384116458451      0.006 ...         --      --\n",
       "              ...               ...        ... ...        ...     ...\n",
       "286.6944839297623 -16.5791122649035      0.013 ...         --      --\n",
       "286.6993829324819 -16.5821039497348      0.004 ...         --      --\n",
       "286.6963834136197 -16.5849153146221      0.002 ...         --      --\n",
       "286.6938297521173 -16.5806976451671      0.037 ...         --      --\n",
       "286.6937302999216  -16.586352116054      0.017 ...         --      --\n",
       "286.6923263914704 -16.5950076068847      0.016 ...         --      --\n",
       "286.6990751669917 -16.5854870711225      0.031 ...         --      --\n",
       " 286.699727987182 -16.5849042116214      0.003 ...         --      --\n",
       "286.6915147248319 -16.5880323030601      0.012 ...         --      --\n",
       "286.6980906584381  -16.589175455702      0.003 ...         --      --"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gaia = moc_intersection.query_vizier_table(\"I/345/gaia2\", max_rows=20000)\n",
    "gaia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 6: Cross-match Gaia and WISE sources in all fields\n",
    "\n",
    "We now want to find sources in the selected region (observed in the MASH regions of interest and at low extinction) that are common to the Wide Infrared Survey Explorer ([WISE](https://irsa.ipac.caltech.edu/Missions/wise.html)) and Gaia catalogs. To do so, we will perform a cross-match of the Gaia and WISE catalogs. Alternatively, we could use the CDS XMatch service via the corresponding `astroquery` module.\n",
    "\n",
    "To do so, let's first inspect the `match_coordinates_sky` function from `astropy.coordinates`. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function match_coordinates_sky in module astropy.coordinates.matching:\n",
      "\n",
      "match_coordinates_sky(matchcoord, catalogcoord, nthneighbor=1, storekdtree='kdtree_sky')\n",
      "    Finds the nearest on-sky matches of a coordinate or coordinates in\n",
      "    a set of catalog coordinates.\n",
      "    \n",
      "    This finds the on-sky closest neighbor, which is only different from the\n",
      "    3-dimensional match if ``distance`` is set in either ``matchcoord``\n",
      "    or ``catalogcoord``.\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    matchcoord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord`\n",
      "        The coordinate(s) to match to the catalog.\n",
      "    catalogcoord : `~astropy.coordinates.BaseCoordinateFrame` or `~astropy.coordinates.SkyCoord`\n",
      "        The base catalog in which to search for matches. Typically this will\n",
      "        be a coordinate object that is an array (i.e.,\n",
      "        ``catalogcoord.isscalar == False``)\n",
      "    nthneighbor : int, optional\n",
      "        Which closest neighbor to search for.  Typically ``1`` is desired here,\n",
      "        as that is correct for matching one set of coordinates to another.\n",
      "        The next likely use case is ``2``, for matching a coordinate catalog\n",
      "        against *itself* (``1`` is inappropriate because each point will find\n",
      "        itself as the closest match).\n",
      "    storekdtree : bool or str, optional\n",
      "        If a string, will store the KD-Tree used for the computation\n",
      "        in the ``catalogcoord`` in ``catalogcoord.cache`` with the\n",
      "        provided name.  This dramatically speeds up subsequent calls with the\n",
      "        same catalog. If False, the KD-Tree is discarded after use.\n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    idx : int array\n",
      "        Indices into ``catalogcoord`` to get the matched points for each\n",
      "        ``matchcoord``. Shape matches ``matchcoord``.\n",
      "    sep2d : `~astropy.coordinates.Angle`\n",
      "        The on-sky separation between the closest match for each\n",
      "        ``matchcoord`` and the ``matchcoord``. Shape matches ``matchcoord``.\n",
      "    dist3d : `~astropy.units.Quantity` ['length']\n",
      "        The 3D distance between the closest match for each ``matchcoord`` and\n",
      "        the ``matchcoord``. Shape matches ``matchcoord``.  If either\n",
      "        ``matchcoord`` or ``catalogcoord`` don't have a distance, this is the 3D\n",
      "        distance on the unit sphere, rather than a true distance.\n",
      "    \n",
      "    Notes\n",
      "    -----\n",
      "    This function requires `SciPy <https://www.scipy.org/>`_ to be installed\n",
      "    or it will fail.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(match_coordinates_sky)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We generate the coordinates in the appropriate format\n",
    "twomass_coord = SkyCoord(ra=twomass[\"RAJ2000\"], dec=twomass[\"DEJ2000\"], unit=u.deg)\n",
    "gaia_coord = SkyCoord(ra=gaia[\"ra_epoch2000\"], dec=gaia[\"dec_epoch2000\"], unit=u.deg)\n",
    "\n",
    "index, separation_2d, _ = match_coordinates_sky(twomass_coord, gaia_coord)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true,
    "tags": [
     "output_scroll"
    ]
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=2461</i>\n",
       "<table id=\"table140505834355152\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>_2MASS</th><th>RAJ2000</th><th>DEJ2000</th><th>Hmag</th><th>Kmag</th><th>Gmag</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>mag</th><th>mag</th><th>mag</th></tr></thead>\n",
       "<thead><tr><th>str17</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float64</th></tr></thead>\n",
       "<tr><td>07004924-2609161</td><td>105.205199</td><td>-26.154478</td><td>11.679</td><td>11.401</td><td>15.163431</td></tr>\n",
       "<tr><td>07005553-2609080</td><td>105.231379</td><td>-26.152241</td><td>14.916</td><td>14.773</td><td>17.04277</td></tr>\n",
       "<tr><td>07005410-2608455</td><td>105.225439</td><td>-26.145973</td><td>10.259</td><td>10.203</td><td>11.561445</td></tr>\n",
       "<tr><td>07005605-2608553</td><td>105.233576</td><td>-26.14872</td><td>11.6</td><td>11.596</td><td>12.814123</td></tr>\n",
       "<tr><td>07005809-2608512</td><td>105.242043</td><td>-26.147581</td><td>16.293</td><td>15.534</td><td>18.124905</td></tr>\n",
       "<tr><td>07005247-2609231</td><td>105.218641</td><td>-26.156427</td><td>15.26</td><td>15.049</td><td>16.798706</td></tr>\n",
       "<tr><td>07005211-2609189</td><td>105.217137</td><td>-26.155258</td><td>13.935</td><td>13.901</td><td>15.073216</td></tr>\n",
       "<tr><td>07005137-2609029</td><td>105.214075</td><td>-26.150816</td><td>16.15</td><td>16.086</td><td>18.203348</td></tr>\n",
       "<tr><td>07005056-2609004</td><td>105.210699</td><td>-26.150122</td><td>15.976</td><td>15.562</td><td>18.129118</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>19064553-1634404</td><td>286.689742</td><td>-16.577908</td><td>13.019</td><td>12.891</td><td>14.491944</td></tr>\n",
       "<tr><td>19064594-1635515</td><td>286.691417</td><td>-16.597643</td><td>15.619</td><td>15.301</td><td>20.496124</td></tr>\n",
       "<tr><td>19064668-1634538</td><td>286.694521</td><td>-16.581614</td><td>15.432</td><td>14.542</td><td>17.792925</td></tr>\n",
       "<tr><td>19064720-1635472</td><td>286.696689</td><td>-16.596464</td><td>15.485</td><td>15.537</td><td>17.76891</td></tr>\n",
       "<tr><td>19064817-1634479</td><td>286.700747</td><td>-16.579975</td><td>15.088</td><td>14.954</td><td>16.522064</td></tr>\n",
       "<tr><td>19064785-1634555</td><td>286.699402</td><td>-16.582111</td><td>15.25</td><td>14.904</td><td>17.445724</td></tr>\n",
       "<tr><td>19064793-1635057</td><td>286.699732</td><td>-16.584917</td><td>15.312</td><td>15.112</td><td>17.031467</td></tr>\n",
       "<tr><td>19065153-1635084</td><td>286.714737</td><td>-16.58567</td><td>15.863</td><td>14.698</td><td>18.407427</td></tr>\n",
       "<tr><td>19065170-1635040</td><td>286.715418</td><td>-16.584455</td><td>13.256</td><td>13.168</td><td>15.601813</td></tr>\n",
       "<tr><td>19065195-1635199</td><td>286.716468</td><td>-16.588884</td><td>15.119</td><td>15.102</td><td>16.665237</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=2461>\n",
       "     _2MASS       RAJ2000    DEJ2000     Hmag    Kmag     Gmag  \n",
       "                    deg        deg       mag     mag      mag   \n",
       "     str17        float64    float64   float32 float32  float64 \n",
       "---------------- ---------- ---------- ------- ------- ---------\n",
       "07004924-2609161 105.205199 -26.154478  11.679  11.401 15.163431\n",
       "07005553-2609080 105.231379 -26.152241  14.916  14.773  17.04277\n",
       "07005410-2608455 105.225439 -26.145973  10.259  10.203 11.561445\n",
       "07005605-2608553 105.233576  -26.14872    11.6  11.596 12.814123\n",
       "07005809-2608512 105.242043 -26.147581  16.293  15.534 18.124905\n",
       "07005247-2609231 105.218641 -26.156427   15.26  15.049 16.798706\n",
       "07005211-2609189 105.217137 -26.155258  13.935  13.901 15.073216\n",
       "07005137-2609029 105.214075 -26.150816   16.15  16.086 18.203348\n",
       "07005056-2609004 105.210699 -26.150122  15.976  15.562 18.129118\n",
       "             ...        ...        ...     ...     ...       ...\n",
       "19064553-1634404 286.689742 -16.577908  13.019  12.891 14.491944\n",
       "19064594-1635515 286.691417 -16.597643  15.619  15.301 20.496124\n",
       "19064668-1634538 286.694521 -16.581614  15.432  14.542 17.792925\n",
       "19064720-1635472 286.696689 -16.596464  15.485  15.537  17.76891\n",
       "19064817-1634479 286.700747 -16.579975  15.088  14.954 16.522064\n",
       "19064785-1634555 286.699402 -16.582111   15.25  14.904 17.445724\n",
       "19064793-1635057 286.699732 -16.584917  15.312  15.112 17.031467\n",
       "19065153-1635084 286.714737  -16.58567  15.863  14.698 18.407427\n",
       "19065170-1635040 286.715418 -16.584455  13.256  13.168 15.601813\n",
       "19065195-1635199 286.716468 -16.588884  15.119  15.102 16.665237"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Decide the maximum separation between objects to be considered acceptable matches\n",
    "max_separation = 1.0 * u.arcsec\n",
    "# Apply constraint on the two catalogs\n",
    "sep_constraint = separation_2d < max_separation\n",
    "twomass_matches = twomass[sep_constraint]\n",
    "gaia_matches = gaia[index[sep_constraint]]\n",
    "# Select only interesting columns from twomass_matches\n",
    "match_catalog = twomass_matches[\"_2MASS\", \"RAJ2000\", \"DEJ2000\", \"Hmag\", \"Kmag\"]\n",
    "# Add column G magnitude from gaia\n",
    "match_catalog[\"Gmag\"] = gaia_matches[\"phot_g_mean_mag\"]\n",
    "match_catalog"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 7: Build a color-color diagram\n",
    "\n",
    "We now use the data we got from the cross-match to get a WISE/Gaia color-color diagram for all the sources in the low extinction sky regions covered by the MASH survey:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "ax.plot(\n",
    "    match_catalog[\"Hmag\"] - match_catalog[\"Kmag\"],\n",
    "    match_catalog[\"Gmag\"] - match_catalog[\"Hmag\"],\n",
    "    linestyle=\"\",\n",
    "    marker=\".\",\n",
    ")\n",
    "ax.set_xlabel(\"H - Ks [mag]\", fontsize=16)\n",
    "ax.set_ylabel(\"G - H [mag]\", fontsize=16)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "cds-tutos",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  },
  "vscode": {
   "interpreter": {
    "hash": "18fabf4b7284864439f771ae90661426265feb3ce932d65d859d3ebdb8aac045"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}