tutorial_change_units.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "serial-significance",
   "metadata": {},
   "source": [
    "<div>\n",
    "<img src=\"images/Logo_Gaia_may_23_2022.png\" width=\"300\" align=\"right\"/>\n",
    "</div>\n",
    "\n",
    "\n",
    "# Tutorial:  Transform input & output units using Astropy+Astroquery\n",
    "\n",
    "<br />\n",
    "<br />\n",
    "<br />\n",
    "<br />\n",
    "<br />\n",
    "\n",
    "\n",
    "**Release number:** \n",
    "v1.0 (2022-13-06)\n",
    "\n",
    "\n",
    "**Applicable Gaia Data Releases:**\n",
    "Gaia EDR3, Gaia DR3\n",
    "\n",
    "**Author:**\n",
    "Héctor Cánovas Cabrera; hector.canovas@esa.int\n",
    "\n",
    "**Summary:** \n",
    "\n",
    "This code shows how to use the [Astropy.units](https://docs.astropy.org/en/stable/units/index.html) Python module to transform the units associated to different fields in several Gaia DR3 catalogues. For more information, see also the [Astropy equivalencies](https://docs.astropy.org/en/stable/units/equivalencies.html) documentation.\n",
    "\n",
    "**Useful URLs:**\n",
    "\n",
    "* [Questions or suggestions](https://www.cosmos.esa.int/web/gaia/questions)\n",
    "* [Tutorials, documentation, and more](https://www.cosmos.esa.int/web/gaia-users/archive)\n",
    "* [Known issues in the Gaia data](https://www.cosmos.esa.int/web/gaia-users/known-issues)\n",
    "* [Gaia data credits and acknowledgements](https://www.cosmos.esa.int/web/gaia-users/credits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fresh-montana",
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy import units as u\n",
    "from astroquery.gaia import Gaia\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "damaged-adobe",
   "metadata": {},
   "source": [
    "## Connect to the Gaia Archive\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "understanding-zambia",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Login to gaia TAP server [astroquery.gaia.core]\n",
      "User: hcanovas\n",
      "Password: ········\n",
      "OK\n",
      "INFO: Login to gaia data server [astroquery.gaia.core]\n",
      "OK\n"
     ]
    }
   ],
   "source": [
    "Gaia.login()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mature-prairie",
   "metadata": {},
   "source": [
    "##  Retrieve all sources contained in a spherical volume (roughly) centred on the Solar System barycentre, and estimate their distances in light years\n",
    "\n",
    "The query below retrieves all Gaia (E)DR3 sources having distance estimates lower than 10 light years and RUWE <1.4. Then it converts distance units (parallax) to light years, and radial velocity units to m/s. Note the use of Python f-strings (https://docs.python.org/3/tutorial/inputoutput.html) to easily include variables into the ADQL query."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "equivalent-soundtrack",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Query finished. [astroquery.utils.tap.core]\n",
      "Table size (rows): 4\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=4</i>\n",
       "<table id=\"table140562477754128\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>source_id</th><th>ra</th><th>dec</th><th>parallax</th><th>distance_gspphot</th><th>teff_gspphot</th><th>azero_gspphot</th><th>phot_g_mean_mag</th><th>radial_velocity</th><th>distance_lightyear</th><th>radial_velocity_ms</th></tr></thead>\n",
       "<thead><tr><th></th><th>deg</th><th>deg</th><th>mas</th><th>pc</th><th>K</th><th>mag</th><th>mag</th><th>km / s</th><th>lyr</th><th>m / s</th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>float64</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></tr></thead>\n",
       "<tr><td>5853498713190525696</td><td>217.39232147200883</td><td>-62.67607511676666</td><td>768.0665391873573</td><td>1.3011</td><td>2829.3542</td><td>0.0</td><td>8.984749</td><td>-21.942726</td><td>4.243621</td><td>-21942.727</td></tr>\n",
       "<tr><td>4472832130942575872</td><td>269.44850252543836</td><td>4.739420051112412</td><td>546.975939730948</td><td>1.8275</td><td>3099.6335</td><td>1e-04</td><td>8.1939745</td><td>-110.46822</td><td>5.960508</td><td>-110468.23</td></tr>\n",
       "<tr><td>762815470562110464</td><td>165.83095967577933</td><td>35.948653032660104</td><td>392.75294543876464</td><td>2.5453</td><td>3511.045</td><td>0.0</td><td>6.551172</td><td>-85.11064</td><td>8.301659</td><td>-85110.64</td></tr>\n",
       "<tr><td>4075141768785646848</td><td>282.4587890175222</td><td>-23.83709744872712</td><td>336.0266016683708</td><td>2.9762</td><td>3117.376</td><td>0.0002</td><td>9.126414</td><td>-11.11644</td><td>9.707067</td><td>-11116.439</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=4>\n",
       "     source_id              ra                dec              parallax      distance_gspphot ... phot_g_mean_mag radial_velocity distance_lightyear radial_velocity_ms\n",
       "                           deg                deg                mas                pc        ...       mag            km / s            lyr               m / s       \n",
       "       int64             float64            float64            float64           float32      ...     float32         float32          float32            float32      \n",
       "------------------- ------------------ ------------------ ------------------ ---------------- ... --------------- --------------- ------------------ ------------------\n",
       "5853498713190525696 217.39232147200883 -62.67607511676666  768.0665391873573           1.3011 ...        8.984749      -21.942726           4.243621         -21942.727\n",
       "4472832130942575872 269.44850252543836  4.739420051112412   546.975939730948           1.8275 ...       8.1939745      -110.46822           5.960508         -110468.23\n",
       " 762815470562110464 165.83095967577933 35.948653032660104 392.75294543876464           2.5453 ...        6.551172       -85.11064           8.301659          -85110.64\n",
       "4075141768785646848  282.4587890175222 -23.83709744872712  336.0266016683708           2.9762 ...        9.126414       -11.11644           9.707067         -11116.439"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dist_lim    = 10.0 * u.lightyear                                # Spherical radius in Light Years\n",
    "dist_lim_pc = dist_lim.to(u.parsec, equivalencies=u.parallax()) # Spherical radius in Parsec\n",
    "\n",
    "query = f\"SELECT source_id, ra, dec, parallax, distance_gspphot, teff_gspphot, azero_gspphot, phot_g_mean_mag, radial_velocity \\\n",
    "FROM gaiadr3.gaia_source \\\n",
    "WHERE distance_gspphot <= {dist_lim_pc.value}\\\n",
    "AND ruwe <1.4\"\n",
    "\n",
    "job     = Gaia.launch_job_async(query)\n",
    "results = job.get_results()\n",
    "print(f'Table size (rows): {len(results)}')\n",
    "\n",
    "results['distance_lightyear'] = results['distance_gspphot'].to(u.lightyear)\n",
    "results['radial_velocity_ms'] = results['radial_velocity'].to(u.meter/u.second)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27a557c8",
   "metadata": {},
   "source": [
    "## Retrieve sources with estimated $\\mathrm{H\\alpha}$ equivalent widths above an arbitrary threshold in nm. Convert it to  $\\unicode{x212B}$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "341afa3e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Query finished. [astroquery.utils.tap.core]\n",
      "Table size (rows): 19\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=19</i>\n",
       "<table id=\"table140562477760176\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>source_id</th><th>classprob_dsc_allosmod_star</th><th>teff_gspphot</th><th>logg_gspphot</th><th>mh_gspphot</th><th>distance_gspphot</th><th>azero_gspphot</th><th>radius_gspphot</th><th>ew_espels_halpha</th><th>spectraltype_esphs</th><th>ew_espels_halpha_AA</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th>K</th><th>log(cm.s**-2)</th><th>dex</th><th>pc</th><th>mag</th><th>solRad</th><th>nm</th><th></th><th>Angstrom</th></tr></thead>\n",
       "<thead><tr><th>int64</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>object</th><th>float32</th></tr></thead>\n",
       "<tr><td>6014696635395955200</td><td>1.0</td><td>5806.3936</td><td>4.3735</td><td>-4.084</td><td>152.1869</td><td>5.8891</td><td>0.9871</td><td>-7.905174</td><td>M</td><td>-79.051735</td></tr>\n",
       "<tr><td>548687019867141248</td><td>1.0</td><td>3469.1199</td><td>4.8496</td><td>-0.1202</td><td>234.534</td><td>0.0096</td><td>0.4027</td><td>-7.546674</td><td>M</td><td>-75.466736</td></tr>\n",
       "<tr><td>6237174395139447808</td><td>1.0</td><td>3220.2583</td><td>4.5578</td><td>0.4907</td><td>136.8067</td><td>0.655</td><td>0.6153</td><td>-7.336281</td><td>M</td><td>-73.36281</td></tr>\n",
       "<tr><td>5977507918028936576</td><td>0.9999994</td><td>3126.9832</td><td>4.8348</td><td>0.4441</td><td>183.2773</td><td>0.9097</td><td>0.3931</td><td>-7.310384</td><td>M</td><td>-73.103836</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></tr>\n",
       "<tr><td>5788126115413073920</td><td>1.0</td><td>3110.1384</td><td>3.8806</td><td>0.4897</td><td>184.8856</td><td>1.2249</td><td>1.1557</td><td>-5.578936</td><td>M</td><td>-55.78936</td></tr>\n",
       "<tr><td>148449845165337600</td><td>1.0</td><td>5933.19</td><td>4.5812</td><td>-3.7281</td><td>139.1848</td><td>7.3076</td><td>0.6936</td><td>-5.4947324</td><td>M</td><td>-54.947323</td></tr>\n",
       "<tr><td>5201160663373986176</td><td>1.0</td><td>4325.425</td><td>4.0847</td><td>0.172</td><td>181.1893</td><td>9.0735</td><td>1.4356</td><td>-5.2507443</td><td>M</td><td>-52.507442</td></tr>\n",
       "<tr><td>6021414101695348736</td><td>1.0</td><td>4610.3657</td><td>4.6517</td><td>-4.0795</td><td>161.0902</td><td>4.1502</td><td>0.5191</td><td>-5.1868486</td><td>O</td><td>-51.868484</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=19>\n",
       "     source_id      classprob_dsc_allosmod_star teff_gspphot  logg_gspphot mh_gspphot ... azero_gspphot radius_gspphot ew_espels_halpha spectraltype_esphs ew_espels_halpha_AA\n",
       "                                                     K       log(cm.s**-2)    dex     ...      mag          solRad            nm                                 Angstrom     \n",
       "       int64                  float32             float32       float32     float32   ...    float32       float32         float32            object             float32      \n",
       "------------------- --------------------------- ------------ ------------- ---------- ... ------------- -------------- ---------------- ------------------ -------------------\n",
       "6014696635395955200                         1.0    5806.3936        4.3735     -4.084 ...        5.8891         0.9871        -7.905174                  M          -79.051735\n",
       " 548687019867141248                         1.0    3469.1199        4.8496    -0.1202 ...        0.0096         0.4027        -7.546674                  M          -75.466736\n",
       "6237174395139447808                         1.0    3220.2583        4.5578     0.4907 ...         0.655         0.6153        -7.336281                  M           -73.36281\n",
       "5977507918028936576                   0.9999994    3126.9832        4.8348     0.4441 ...        0.9097         0.3931        -7.310384                  M          -73.103836\n",
       "                ...                         ...          ...           ...        ... ...           ...            ...              ...                ...                 ...\n",
       "5788126115413073920                         1.0    3110.1384        3.8806     0.4897 ...        1.2249         1.1557        -5.578936                  M           -55.78936\n",
       " 148449845165337600                         1.0      5933.19        4.5812    -3.7281 ...        7.3076         0.6936       -5.4947324                  M          -54.947323\n",
       "5201160663373986176                         1.0     4325.425        4.0847      0.172 ...        9.0735         1.4356       -5.2507443                  M          -52.507442\n",
       "6021414101695348736                         1.0    4610.3657        4.6517    -4.0795 ...        4.1502         0.5191       -5.1868486                  O          -51.868484"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = f\"SELECT source_id, classprob_dsc_allosmod_star, teff_gspphot, logg_gspphot, mh_gspphot, distance_gspphot, azero_gspphot, radius_gspphot, ew_espels_halpha,  spectraltype_esphs \\\n",
    "FROM gaiadr3.astrophysical_parameters \\\n",
    "WHERE ew_espels_halpha BETWEEN -10 AND -5 AND \\\n",
    "distance_gspphot <300 \\\n",
    "AND spectraltype_esphs != 'unknown' \\\n",
    "ORDER BY ew_espels_halpha\"\n",
    "\n",
    "job     = Gaia.launch_job_async(query)\n",
    "results = job.get_results()\n",
    "print(f'Table size (rows): {len(results)}')\n",
    "\n",
    "results['ew_espels_halpha_AA'] = results['ew_espels_halpha'].to(u.Angstrom)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1e14d27",
   "metadata": {},
   "source": [
    "## Retrieve masses from low-mass binary pairs, and convert them to Jupiter masses.\n",
    "\n",
    "Note: Brown dwarfs upper limit ~ 0.075 $M_{\\odot}$ (~ 75 $M_\\mathrm{Jup}$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1a3732d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Query finished. [astroquery.utils.tap.core]\n",
      "Table size (rows): 5\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=5</i>\n",
       "<table id=\"table140561949593456\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>source_id</th><th>m1</th><th>m1_lower</th><th>m1_upper</th><th>m2</th><th>m2_lower</th><th>m2_upper</th><th>fluxratio</th><th>fluxratio_lower</th><th>fluxratio_upper</th><th>combination_method</th><th>m1_ref</th><th>flag</th><th>m1_jup_mass</th><th>m2_jup_mass</th></tr></thead>\n",
       "<thead><tr><th></th><th>solMass</th><th>solMass</th><th>solMass</th><th>solMass</th><th>solMass</th><th>solMass</th><th></th><th></th><th></th><th></th><th></th><th></th><th>jupiterMass</th><th>jupiterMass</th></tr></thead>\n",
       "<thead><tr><th>int64</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>object</th><th>object</th><th>object</th><th>float32</th><th>float32</th></tr></thead>\n",
       "<tr><td>4580216762992082048</td><td>0.118804775</td><td>0.07159802</td><td>0.16601153</td><td>--</td><td>0.04972383</td><td>0.07908957</td><td>--</td><td>0.13</td><td>--</td><td>Orbital+M1</td><td>IsocLum</td><td></td><td>124.45579</td><td>nan</td></tr>\n",
       "<tr><td>5557776367807067648</td><td>0.12185247</td><td>0.07464338</td><td>0.17008784</td><td>0.067699336</td><td>0.053124726</td><td>0.08328539</td><td>--</td><td>0.0</td><td>0.0</td><td>Orbital+M1</td><td>IsocLum</td><td></td><td>127.64845</td><td>70.919495</td></tr>\n",
       "<tr><td>845583819682861184</td><td>0.122110225</td><td>0.074233726</td><td>0.16946633</td><td>0.08028531</td><td>0.06197444</td><td>0.09972578</td><td>--</td><td>0.0</td><td>0.0</td><td>Orbital+M1</td><td>IsocLum</td><td></td><td>127.918465</td><td>84.104126</td></tr>\n",
       "<tr><td>4406489184157821952</td><td>0.122521155</td><td>0.07496838</td><td>0.1705908</td><td>0.07285931</td><td>0.05727609</td><td>0.089689784</td><td>--</td><td>0.0</td><td>0.0</td><td>Orbital+M1</td><td>IsocLum</td><td></td><td>128.34894</td><td>76.324905</td></tr>\n",
       "<tr><td>3230836376154368384</td><td>0.124612674</td><td>0.076774806</td><td>0.17298208</td><td>0.04927069</td><td>0.038072873</td><td>0.0609185</td><td>--</td><td>0.0</td><td>0.0</td><td>Orbital+M1</td><td>IsocLum</td><td></td><td>130.53995</td><td>51.614277</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=5>\n",
       "     source_id           m1       m1_lower   m1_upper       m2       m2_lower    m2_upper  ... fluxratio_upper combination_method  m1_ref  flag  m1_jup_mass m2_jup_mass\n",
       "                      solMass     solMass    solMass     solMass     solMass     solMass   ...                                                   jupiterMass jupiterMass\n",
       "       int64          float32     float32    float32     float32     float32     float32   ...     float32           object        object object   float32     float32  \n",
       "------------------- ----------- ----------- ---------- ----------- ----------- ----------- ... --------------- ------------------ ------- ------ ----------- -----------\n",
       "4580216762992082048 0.118804775  0.07159802 0.16601153          --  0.04972383  0.07908957 ...              --         Orbital+M1 IsocLum          124.45579         nan\n",
       "5557776367807067648  0.12185247  0.07464338 0.17008784 0.067699336 0.053124726  0.08328539 ...             0.0         Orbital+M1 IsocLum          127.64845   70.919495\n",
       " 845583819682861184 0.122110225 0.074233726 0.16946633  0.08028531  0.06197444  0.09972578 ...             0.0         Orbital+M1 IsocLum         127.918465   84.104126\n",
       "4406489184157821952 0.122521155  0.07496838  0.1705908  0.07285931  0.05727609 0.089689784 ...             0.0         Orbital+M1 IsocLum          128.34894   76.324905\n",
       "3230836376154368384 0.124612674 0.076774806 0.17298208  0.04927069 0.038072873   0.0609185 ...             0.0         Orbital+M1 IsocLum          130.53995   51.614277"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = f\"SELECT * \\\n",
    "FROM gaiadr3.binary_masses \\\n",
    "WHERE m1 <0.125 \\\n",
    "ORDER BY m1\"\n",
    "\n",
    "job     = Gaia.launch_job_async(query)\n",
    "results = job.get_results()\n",
    "print(f'Table size (rows): {len(results)}')\n",
    "\n",
    "results['m1_jup_mass'] = results['m1'].to(u.jupiterMass)\n",
    "results['m2_jup_mass'] = results['m2'].to(u.jupiterMass)\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe88c1fd",
   "metadata": {},
   "source": [
    "## Select Cepheids with Fundamental pulsation mode below 15 hours."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d3b0a8a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Query finished. [astroquery.utils.tap.core]\n",
      "Table size (rows): 9\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=9</i>\n",
       "<table id=\"table140561949597968\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>source_id</th><th>pf</th><th>pf_error</th><th>teff_gspphot</th><th>logg_gspphot</th><th>mh_gspphot</th><th>distance_gspphot</th><th>azero_gspphot</th><th>radius_gspphot</th><th>ew_espels_halpha</th><th>spectraltype_esphs</th><th>pf_hour</th></tr></thead>\n",
       "<thead><tr><th></th><th>d</th><th>d</th><th>K</th><th>log(cm.s**-2)</th><th>dex</th><th>pc</th><th>mag</th><th>solRad</th><th>nm</th><th></th><th>h</th></tr></thead>\n",
       "<thead><tr><th>int64</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>object</th><th>float64</th></tr></thead>\n",
       "<tr><td>5188379665334866176</td><td>0.6219627800893595</td><td>8.736139e-06</td><td>6173.523</td><td>3.1676</td><td>-0.9927</td><td>2478.2385</td><td>0.1601</td><td>5.1871</td><td>0.19384572</td><td>unknown</td><td>14.927</td></tr>\n",
       "<tr><td>4685852200899088512</td><td>0.5822570063616527</td><td>1.6833055e-06</td><td>5521.2</td><td>4.7306</td><td>-3.7822</td><td>3203.7131</td><td>0.0121</td><td>0.5741</td><td>--</td><td></td><td>13.974</td></tr>\n",
       "<tr><td>5861380317401194752</td><td>0.5866106007286351</td><td>1.3795823e-06</td><td>9060.484</td><td>4.1245</td><td>-0.7119</td><td>1867.7528</td><td>4.696</td><td>1.8368</td><td>0.03517555</td><td>F</td><td>14.079</td></tr>\n",
       "<tr><td>5861754598036185344</td><td>0.6002593393511508</td><td>2.7811316e-06</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>0.2204732</td><td>G</td><td>14.406</td></tr>\n",
       "<tr><td>5926569816398338304</td><td>0.5910341676058103</td><td>8.15525e-07</td><td>8406.448</td><td>4.065</td><td>-1.2239</td><td>1941.2487</td><td>3.4149</td><td>1.7847</td><td>0.16679318</td><td>B</td><td>14.185</td></tr>\n",
       "<tr><td>4702941119846080128</td><td>0.5644549970314298</td><td>5.2175283e-06</td><td>6616.0835</td><td>4.5777</td><td>-2.4239</td><td>6389.3247</td><td>0.0061</td><td>0.7866</td><td>--</td><td></td><td>13.547</td></tr>\n",
       "<tr><td>5422477922959825792</td><td>0.5597106717764326</td><td>1.2912872e-06</td><td>8226.137</td><td>3.5066</td><td>-0.066</td><td>1930.5466</td><td>5.4515</td><td>4.6715</td><td>0.26228103</td><td>B</td><td>13.433</td></tr>\n",
       "<tr><td>5864522588553955584</td><td>0.5990258658944467</td><td>1.9770755e-07</td><td>7514.7837</td><td>3.3402</td><td>-0.296</td><td>2169.1348</td><td>4.0485</td><td>5.2538</td><td>0.23103149</td><td>F</td><td>14.377</td></tr>\n",
       "<tr><td>4688941489297074944</td><td>0.6209256688645836</td><td>3.7721848e-06</td><td>7132.224</td><td>4.582</td><td>-1.9969</td><td>7770.706</td><td>0.0011</td><td>0.8403</td><td>--</td><td></td><td>14.902</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=9>\n",
       "     source_id              pf            pf_error   teff_gspphot  logg_gspphot mh_gspphot ... azero_gspphot radius_gspphot ew_espels_halpha spectraltype_esphs pf_hour\n",
       "                            d                d            K       log(cm.s**-2)    dex     ...      mag          solRad            nm                              h   \n",
       "       int64             float64          float32      float32       float32     float32   ...    float32       float32         float32            object       float64\n",
       "------------------- ------------------ ------------- ------------ ------------- ---------- ... ------------- -------------- ---------------- ------------------ -------\n",
       "5188379665334866176 0.6219627800893595  8.736139e-06     6173.523        3.1676    -0.9927 ...        0.1601         5.1871       0.19384572            unknown  14.927\n",
       "4685852200899088512 0.5822570063616527 1.6833055e-06       5521.2        4.7306    -3.7822 ...        0.0121         0.5741               --                     13.974\n",
       "5861380317401194752 0.5866106007286351 1.3795823e-06     9060.484        4.1245    -0.7119 ...         4.696         1.8368       0.03517555                  F  14.079\n",
       "5861754598036185344 0.6002593393511508 2.7811316e-06           --            --         -- ...            --             --        0.2204732                  G  14.406\n",
       "5926569816398338304 0.5910341676058103   8.15525e-07     8406.448         4.065    -1.2239 ...        3.4149         1.7847       0.16679318                  B  14.185\n",
       "4702941119846080128 0.5644549970314298 5.2175283e-06    6616.0835        4.5777    -2.4239 ...        0.0061         0.7866               --                     13.547\n",
       "5422477922959825792 0.5597106717764326 1.2912872e-06     8226.137        3.5066     -0.066 ...        5.4515         4.6715       0.26228103                  B  13.433\n",
       "5864522588553955584 0.5990258658944467 1.9770755e-07    7514.7837        3.3402     -0.296 ...        4.0485         5.2538       0.23103149                  F  14.377\n",
       "4688941489297074944 0.6209256688645836 3.7721848e-06     7132.224         4.582    -1.9969 ...        0.0011         0.8403               --                     14.902"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pf_lim_hd = 15 * u.hour\n",
    "pf_lim_dd = pf_lim_hd.to(u.day)\n",
    "\n",
    "query = f'SELECT source_id, pf, pf_error, ap.teff_gspphot, ap.logg_gspphot, ap.mh_gspphot, ap.distance_gspphot, ap.azero_gspphot, ap.radius_gspphot, ap.ew_espels_halpha,  ap.spectraltype_esphs \\\n",
    "FROM gaiadr3.vari_cepheid \\\n",
    "JOIN gaiadr3.astrophysical_parameters AS ap USING (source_id) \\\n",
    "WHERE pf <{pf_lim_dd.value}'\n",
    "\n",
    "\n",
    "job     = Gaia.launch_job_async(query)\n",
    "results = job.get_results()\n",
    "print(f'Table size (rows): {len(results)}')\n",
    "\n",
    "results['pf_hour']        = results['pf'].to(u.hour)\n",
    "results['pf_hour'].format = '5.3f'\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afaaeee8",
   "metadata": {},
   "source": [
    "## Compute Flux density (in mJy) from XP sampled spectrum. \n",
    "\n",
    "The code below retrieves XP sample spectra for 10 arbitrary sources in Gaia DR3. This product can be downloaded via a dedicated DataLink server (for details, see the DataLink tutorials available [here](https://www.cosmos.esa.int/web/gaia-users/archive/datalink-products)). Note: the download of this product raises a warning in the Astropy.units module. This is a known issue and we are working on it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf93c85b",
   "metadata": {},
   "source": [
    "### Retrieve a set of sources with XP Sampled spectra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "973951d9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: Query finished. [astroquery.utils.tap.core]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=10</i>\n",
       "<table id=\"table140561405989872\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>solution_id</th><th>DESIGNATION</th><th>source_id</th><th>random_index</th><th>ref_epoch</th><th>ra</th><th>ra_error</th><th>dec</th><th>dec_error</th><th>parallax</th><th>parallax_error</th><th>parallax_over_error</th><th>pm</th><th>pmra</th><th>pmra_error</th><th>pmdec</th><th>pmdec_error</th><th>ra_dec_corr</th><th>ra_parallax_corr</th><th>ra_pmra_corr</th><th>ra_pmdec_corr</th><th>dec_parallax_corr</th><th>dec_pmra_corr</th><th>dec_pmdec_corr</th><th>parallax_pmra_corr</th><th>parallax_pmdec_corr</th><th>pmra_pmdec_corr</th><th>astrometric_n_obs_al</th><th>astrometric_n_obs_ac</th><th>astrometric_n_good_obs_al</th><th>astrometric_n_bad_obs_al</th><th>astrometric_gof_al</th><th>astrometric_chi2_al</th><th>astrometric_excess_noise</th><th>astrometric_excess_noise_sig</th><th>astrometric_params_solved</th><th>astrometric_primary_flag</th><th>nu_eff_used_in_astrometry</th><th>pseudocolour</th><th>pseudocolour_error</th><th>ra_pseudocolour_corr</th><th>dec_pseudocolour_corr</th><th>parallax_pseudocolour_corr</th><th>pmra_pseudocolour_corr</th><th>pmdec_pseudocolour_corr</th><th>astrometric_matched_transits</th><th>visibility_periods_used</th><th>astrometric_sigma5d_max</th><th>matched_transits</th><th>new_matched_transits</th><th>matched_transits_removed</th><th>ipd_gof_harmonic_amplitude</th><th>ipd_gof_harmonic_phase</th><th>ipd_frac_multi_peak</th><th>ipd_frac_odd_win</th><th>ruwe</th><th>scan_direction_strength_k1</th><th>scan_direction_strength_k2</th><th>scan_direction_strength_k3</th><th>scan_direction_strength_k4</th><th>scan_direction_mean_k1</th><th>scan_direction_mean_k2</th><th>scan_direction_mean_k3</th><th>scan_direction_mean_k4</th><th>duplicated_source</th><th>phot_g_n_obs</th><th>phot_g_mean_flux</th><th>phot_g_mean_flux_error</th><th>phot_g_mean_flux_over_error</th><th>phot_g_mean_mag</th><th>phot_bp_n_obs</th><th>phot_bp_mean_flux</th><th>phot_bp_mean_flux_error</th><th>phot_bp_mean_flux_over_error</th><th>phot_bp_mean_mag</th><th>phot_rp_n_obs</th><th>phot_rp_mean_flux</th><th>phot_rp_mean_flux_error</th><th>phot_rp_mean_flux_over_error</th><th>phot_rp_mean_mag</th><th>phot_bp_rp_excess_factor</th><th>phot_bp_n_contaminated_transits</th><th>phot_bp_n_blended_transits</th><th>phot_rp_n_contaminated_transits</th><th>phot_rp_n_blended_transits</th><th>phot_proc_mode</th><th>bp_rp</th><th>bp_g</th><th>g_rp</th><th>radial_velocity</th><th>radial_velocity_error</th><th>rv_method_used</th><th>rv_nb_transits</th><th>rv_nb_deblended_transits</th><th>rv_visibility_periods_used</th><th>rv_expected_sig_to_noise</th><th>rv_renormalised_gof</th><th>rv_chisq_pvalue</th><th>rv_time_duration</th><th>rv_amplitude_robust</th><th>rv_template_teff</th><th>rv_template_logg</th><th>rv_template_fe_h</th><th>rv_atm_param_origin</th><th>vbroad</th><th>vbroad_error</th><th>vbroad_nb_transits</th><th>grvs_mag</th><th>grvs_mag_error</th><th>grvs_mag_nb_transits</th><th>rvs_spec_sig_to_noise</th><th>phot_variable_flag</th><th>l</th><th>b</th><th>ecl_lon</th><th>ecl_lat</th><th>in_qso_candidates</th><th>in_galaxy_candidates</th><th>non_single_star</th><th>has_xp_continuous</th><th>has_xp_sampled</th><th>has_rvs</th><th>has_epoch_photometry</th><th>has_epoch_rv</th><th>has_mcmc_gspphot</th><th>has_mcmc_msc</th><th>in_andromeda_survey</th><th>classprob_dsc_combmod_quasar</th><th>classprob_dsc_combmod_galaxy</th><th>classprob_dsc_combmod_star</th><th>teff_gspphot</th><th>teff_gspphot_lower</th><th>teff_gspphot_upper</th><th>logg_gspphot</th><th>logg_gspphot_lower</th><th>logg_gspphot_upper</th><th>mh_gspphot</th><th>mh_gspphot_lower</th><th>mh_gspphot_upper</th><th>distance_gspphot</th><th>distance_gspphot_lower</th><th>distance_gspphot_upper</th><th>azero_gspphot</th><th>azero_gspphot_lower</th><th>azero_gspphot_upper</th><th>ag_gspphot</th><th>ag_gspphot_lower</th><th>ag_gspphot_upper</th><th>ebpminrp_gspphot</th><th>ebpminrp_gspphot_lower</th><th>ebpminrp_gspphot_upper</th><th>libname_gspphot</th></tr></thead>\n",
       "<thead><tr><th></th><th></th><th></th><th></th><th>yr</th><th>deg</th><th>mas</th><th>deg</th><th>mas</th><th>mas</th><th>mas</th><th></th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th>mas / yr</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>mas</th><th></th><th></th><th></th><th>1 / um</th><th>1 / um</th><th>1 / um</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>mas</th><th></th><th></th><th></th><th></th><th>deg</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>deg</th><th></th><th></th><th>electron / s</th><th>electron / s</th><th></th><th>mag</th><th></th><th>electron / s</th><th>electron / s</th><th></th><th>mag</th><th></th><th>electron / s</th><th>electron / s</th><th></th><th>mag</th><th></th><th></th><th></th><th></th><th></th><th></th><th>mag</th><th>mag</th><th>mag</th><th>km / s</th><th>km / s</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>d</th><th>km / s</th><th>K</th><th>log(cm.s**-2)</th><th>dex</th><th></th><th>km / s</th><th>km / s</th><th></th><th>mag</th><th>mag</th><th></th><th></th><th></th><th>deg</th><th>deg</th><th>deg</th><th>deg</th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th></th><th>K</th><th>K</th><th>K</th><th>log(cm.s**-2)</th><th>log(cm.s**-2)</th><th>log(cm.s**-2)</th><th>dex</th><th>dex</th><th>dex</th><th>pc</th><th>pc</th><th>pc</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th>mag</th><th></th></tr></thead>\n",
       "<thead><tr><th>int64</th><th>object</th><th>int64</th><th>int64</th><th>float64</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float64</th><th>float32</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>float32</th><th>float32</th><th>int16</th><th>int16</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>bool</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>int16</th><th>int16</th><th>float32</th><th>int16</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>int16</th><th>int16</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>bool</th><th>int16</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>int16</th><th>int16</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>int16</th><th>int16</th><th>int16</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>int16</th><th>float32</th><th>float32</th><th>int16</th><th>float32</th><th>float32</th><th>int16</th><th>float32</th><th>object</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>bool</th><th>bool</th><th>int16</th><th>bool</th><th>bool</th><th>bool</th><th>bool</th><th>bool</th><th>bool</th><th>bool</th><th>bool</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>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>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>object</th></tr></thead>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937173266047638272</td><td>5937173266047638272</td><td>314958060</td><td>2016.0</td><td>250.22690656136763</td><td>0.0239966</td><td>-51.60318993759893</td><td>0.017609632</td><td>0.6521282730801226</td><td>0.030326193</td><td>21.503796</td><td>16.673893</td><td>1.8685996067645547</td><td>0.031973384</td><td>-16.568857116365553</td><td>0.025367465</td><td>0.010337387</td><td>-0.21418677</td><td>-0.10345264</td><td>-0.4363342</td><td>-0.10887727</td><td>-0.40680984</td><td>0.06184543</td><td>0.030531619</td><td>0.018303124</td><td>0.1261247</td><td>392</td><td>0</td><td>392</td><td>0</td><td>6.1149173</td><td>592.8164</td><td>0.13811097</td><td>6.2785025</td><td>31</td><td>False</td><td>1.4527762</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>45</td><td>20</td><td>0.045606557</td><td>48</td><td>17</td><td>0</td><td>0.017614717</td><td>26.214508</td><td>0</td><td>0</td><td>1.2267392</td><td>0.18513173</td><td>0.27097407</td><td>0.13742293</td><td>0.41828167</td><td>-153.08228</td><td>-0.24025124</td><td>6.9000425</td><td>-33.213203</td><td>False</td><td>411</td><td>26589.599916908806</td><td>7.248126</td><td>3668.4792</td><td>14.625587</td><td>47</td><td>11275.952258059631</td><td>15.611262</td><td>722.296</td><td>15.208159</td><td>47</td><td>22326.68693522532</td><td>17.63591</td><td>1265.9788</td><td>13.875834</td><td>1.2637513</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1.332325</td><td>0.582572</td><td>0.749753</td><td>-86.44704</td><td>18.858374</td><td>2</td><td>8</td><td>6</td><td>7</td><td>3.9088132</td><td>--</td><td>--</td><td>425.07895</td><td>--</td><td>6250.0</td><td>1.0</td><td>-1.0</td><td>111</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>NOT_AVAILABLE</td><td>334.5316527259258</td><td>-3.398680882782161</td><td>256.083604219929</td><td>-29.114880107260994</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>True</td><td>True</td><td>False</td><td>1.020579e-13</td><td>5.143651e-13</td><td>0.9999964</td><td>15001.529</td><td>15000.393</td><td>15004.231</td><td>4.2155</td><td>4.2095</td><td>4.2199</td><td>-0.2306</td><td>-0.2623</td><td>-0.2103</td><td>2439.8772</td><td>2429.876</td><td>2454.8875</td><td>3.24</td><td>3.2385</td><td>3.2413</td><td>2.8408</td><td>2.8396</td><td>2.8418</td><td>1.5555</td><td>1.5548</td><td>1.5561</td><td>OB</td></tr>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937144197726034816</td><td>5937144197726034816</td><td>409734603</td><td>2016.0</td><td>251.46476095641572</td><td>0.16335373</td><td>-50.77317140047803</td><td>0.13020523</td><td>0.6378314286856485</td><td>0.25412685</td><td>2.509894</td><td>1.292189</td><td>-0.4120940440736278</td><td>0.23243496</td><td>-1.2247167218950332</td><td>0.1760335</td><td>0.03803266</td><td>-0.17221262</td><td>-0.074222684</td><td>-0.3912635</td><td>-0.08951158</td><td>-0.36605006</td><td>0.13065445</td><td>0.08541156</td><td>0.029731749</td><td>0.2990954</td><td>420</td><td>0</td><td>390</td><td>30</td><td>79.74002</td><td>21668.531</td><td>1.7483033</td><td>821.74414</td><td>95</td><td>False</td><td>--</td><td>1.3202974</td><td>0.04097113</td><td>-4.5607594e-05</td><td>0.014479563</td><td>-0.17473318</td><td>-0.08003091</td><td>0.14245875</td><td>45</td><td>17</td><td>0.34106937</td><td>50</td><td>16</td><td>0</td><td>0.13933316</td><td>7.6331325</td><td>84</td><td>0</td><td>4.983722</td><td>0.22662018</td><td>0.27790675</td><td>0.2764132</td><td>0.6595103</td><td>168.91518</td><td>-13.659251</td><td>14.864428</td><td>-33.067112</td><td>False</td><td>378</td><td>19542.730498352787</td><td>25.998741</td><td>751.6799</td><td>14.959904</td><td>48</td><td>7419.4852809890235</td><td>23.214443</td><td>319.6064</td><td>15.662608</td><td>47</td><td>27307.319652656457</td><td>31.529078</td><td>866.09955</td><td>13.657198</td><td>1.7769679</td><td>0</td><td>48</td><td>0</td><td>47</td><td>0</td><td>2.0054102</td><td>0.7027044</td><td>1.3027058</td><td>-47.441692</td><td>3.7269695</td><td>2</td><td>12</td><td>7</td><td>8</td><td>5.1557302</td><td>--</td><td>--</td><td>783.4667</td><td>--</td><td>4500.0</td><td>1.5</td><td>-1.5</td><td>111</td><td>--</td><td>--</td><td>--</td><td>13.278212</td><td>0.22160137</td><td>5</td><td>--</td><td>NOT_AVAILABLE</td><td>335.66898647365656</td><td>-3.4418802794696344</td><td>256.8171486425856</td><td>-28.178722254754728</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>False</td><td>True</td><td>False</td><td>1.0209601e-13</td><td>5.891978e-12</td><td>0.9999927</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>1636148068921376768</td><td>Gaia DR3 5937144197726039936</td><td>5937144197726039936</td><td>440987907</td><td>2016.0</td><td>251.45836750025484</td><td>0.015479398</td><td>-50.77132195865252</td><td>0.01100153</td><td>1.4683939054423996</td><td>0.022162465</td><td>66.25589</td><td>8.608242</td><td>-2.619945655163551</td><td>0.021888493</td><td>-8.19986026582952</td><td>0.015430358</td><td>0.043865558</td><td>-0.15064028</td><td>-0.064317875</td><td>-0.39369085</td><td>-0.11211365</td><td>-0.38227904</td><td>0.047593243</td><td>0.09975452</td><td>0.017356893</td><td>0.28807402</td><td>414</td><td>0</td><td>413</td><td>1</td><td>-0.6554093</td><td>391.31244</td><td>0.0</td><td>0.0</td><td>31</td><td>False</td><td>1.479171</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>47</td><td>18</td><td>0.03172368</td><td>50</td><td>17</td><td>0</td><td>0.016953178</td><td>17.956432</td><td>0</td><td>0</td><td>0.97633344</td><td>0.22421812</td><td>0.33453202</td><td>0.21561244</td><td>0.5046696</td><td>165.80637</td><td>-8.486173</td><td>19.770205</td><td>-32.0365</td><td>False</td><td>413</td><td>45637.21393929329</td><td>25.960531</td><td>1757.946</td><td>14.039069</td><td>47</td><td>20717.43005789006</td><td>40.85247</td><td>507.12796</td><td>14.547703</td><td>45</td><td>35631.80963292374</td><td>57.79166</td><td>616.5563</td><td>13.3683</td><td>1.2347213</td><td>0</td><td>7</td><td>0</td><td>1</td><td>0</td><td>1.1794024</td><td>0.5086336</td><td>0.67076874</td><td>-22.728088</td><td>5.2690153</td><td>2</td><td>19</td><td>11</td><td>10</td><td>8.166246</td><td>--</td><td>--</td><td>927.7823</td><td>--</td><td>5750.0</td><td>1.0</td><td>0.0</td><td>111</td><td>--</td><td>--</td><td>--</td><td>12.9804535</td><td>0.038362145</td><td>8</td><td>--</td><td>VARIABLE</td><td>335.66776888882777</td><td>-3.437603465412785</td><td>256.8123082079012</td><td>-28.17747204543682</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>True</td><td>False</td><td>True</td><td>True</td><td>False</td><td>1.02699967e-13</td><td>5.1298115e-13</td><td>0.99993294</td><td>5139.183</td><td>5115.769</td><td>5207.8975</td><td>4.2553</td><td>4.2251</td><td>4.3571</td><td>-0.5361</td><td>-0.5776</td><td>-0.4635</td><td>618.9207</td><td>517.5465</td><td>644.5404</td><td>0.4595</td><td>0.44</td><td>0.5095</td><td>0.3682</td><td>0.3522</td><td>0.4089</td><td>0.1983</td><td>0.1897</td><td>0.2201</td><td>MARCS</td></tr>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937144197726350592</td><td>5937144197726350592</td><td>205487013</td><td>2016.0</td><td>251.47234546031828</td><td>0.019895842</td><td>-50.76727118486512</td><td>0.013826283</td><td>0.17526834572993327</td><td>0.030309262</td><td>5.782666</td><td>5.1607804</td><td>-1.1711576390867762</td><td>0.027722465</td><td>-5.026136086985977</td><td>0.019159406</td><td>0.115696535</td><td>-0.3214559</td><td>-0.16002212</td><td>-0.41005212</td><td>-0.14725529</td><td>-0.4040042</td><td>0.02630467</td><td>0.20778184</td><td>0.08896684</td><td>0.30612004</td><td>410</td><td>0</td><td>410</td><td>0</td><td>-0.27591974</td><td>385.7335</td><td>0.0</td><td>0.0</td><td>31</td><td>False</td><td>1.2827144</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>47</td><td>17</td><td>0.04084493</td><td>50</td><td>17</td><td>0</td><td>0.008956739</td><td>161.39064</td><td>0</td><td>0</td><td>0.9895006</td><td>0.28802025</td><td>0.32991526</td><td>0.3129251</td><td>0.54236054</td><td>168.28624</td><td>-10.720112</td><td>16.289307</td><td>-33.000294</td><td>False</td><td>420</td><td>27706.444290150273</td><td>8.531579</td><td>3247.5166</td><td>14.5809145</td><td>47</td><td>5856.201268238487</td><td>47.27629</td><td>123.87184</td><td>15.919502</td><td>47</td><td>34065.93357095369</td><td>95.46398</td><td>356.84595</td><td>13.417095</td><td>1.4408971</td><td>0</td><td>0</td><td>0</td><td>1</td><td>0</td><td>2.502407</td><td>1.3385878</td><td>1.1638193</td><td>-34.97791</td><td>1.6097668</td><td>2</td><td>22</td><td>14</td><td>10</td><td>8.293457</td><td>--</td><td>--</td><td>745.5058</td><td>--</td><td>4250.0</td><td>1.5</td><td>-0.75</td><td>111</td><td>--</td><td>--</td><td>--</td><td>12.794375</td><td>0.08171257</td><td>8</td><td>--</td><td>NOT_AVAILABLE</td><td>335.67660215737334</td><td>-3.4417039070621684</td><td>256.82157391305276</td><td>-28.17219510543954</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>True</td><td>True</td><td>False</td><td>1.0203731e-13</td><td>5.096712e-13</td><td>0.9999985</td><td>4727.4097</td><td>4608.9995</td><td>4901.4683</td><td>2.0874</td><td>1.9288</td><td>2.3259</td><td>-0.2883</td><td>-0.3037</td><td>-0.2808</td><td>4549.154</td><td>3597.4263</td><td>5327.672</td><td>3.5258</td><td>3.3969</td><td>3.6897</td><td>2.484</td><td>2.382</td><td>2.6159</td><td>1.3457</td><td>1.2868</td><td>1.4217</td><td>PHOENIX</td></tr>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937173300407375616</td><td>5937173300407375616</td><td>169494443</td><td>2016.0</td><td>250.24704334410666</td><td>0.017679643</td><td>-51.59382627681073</td><td>0.012922672</td><td>0.20778617875849348</td><td>0.022678073</td><td>9.162427</td><td>5.6557727</td><td>-4.489017938427424</td><td>0.0233065</td><td>-3.440419031965129</td><td>0.018091926</td><td>0.014787478</td><td>-0.29111868</td><td>-0.006672091</td><td>-0.39784777</td><td>-0.120790765</td><td>-0.38303235</td><td>0.08639189</td><td>-0.050483014</td><td>0.010714794</td><td>0.11505898</td><td>370</td><td>370</td><td>370</td><td>0</td><td>0.7452751</td><td>966.22327</td><td>0.13048622</td><td>16.01963</td><td>31</td><td>False</td><td>1.2832072</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>42</td><td>20</td><td>0.032927927</td><td>45</td><td>15</td><td>0</td><td>0.03093478</td><td>5.903772</td><td>0</td><td>0</td><td>1.0267888</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>False</td><td>387</td><td>263292.32756901917</td><td>235.24489</td><td>1119.2266</td><td>12.136271</td><td>42</td><td>54151.05636197208</td><td>211.6225</td><td>255.88516</td><td>13.504525</td><td>40</td><td>315749.28631923825</td><td>759.4236</td><td>415.77493</td><td>10.999539</td><td>1.4049037</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2.5049858</td><td>1.3682537</td><td>1.1367321</td><td>14.852337</td><td>0.80758554</td><td>1</td><td>17</td><td>13</td><td>12</td><td>48.121964</td><td>6.8776093</td><td>1.9254254e-10</td><td>928.10736</td><td>10.115913</td><td>4250.0</td><td>1.0</td><td>-0.5</td><td>444</td><td>--</td><td>--</td><td>--</td><td>10.492216</td><td>0.01811704</td><td>4</td><td>--</td><td>NOT_AVAILABLE</td><td>334.5469715366394</td><td>-3.4018896184545313</td><td>256.0961002935055</td><td>-29.103702474942565</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>False</td><td>True</td><td>False</td><td>1.02024136e-13</td><td>5.0960543e-13</td><td>0.9999998</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>1636148068921376768</td><td>Gaia DR3 5937081353758582016</td><td>5937081353758582016</td><td>1530038650</td><td>2016.0</td><td>251.6453157948988</td><td>0.018873343</td><td>-51.61333388705421</td><td>0.0132323485</td><td>0.19899952026593154</td><td>0.023696996</td><td>8.397669</td><td>1.5678374</td><td>-0.5856565999864463</td><td>0.026226835</td><td>-1.4543452822051757</td><td>0.019187879</td><td>0.18300082</td><td>-0.22813645</td><td>-0.16516718</td><td>-0.40139687</td><td>-0.0036018759</td><td>-0.38657758</td><td>-0.1487166</td><td>-0.017912302</td><td>0.080677986</td><td>0.37858176</td><td>433</td><td>0</td><td>429</td><td>4</td><td>1.057775</td><td>443.72272</td><td>0.0</td><td>0.0</td><td>31</td><td>False</td><td>1.3178779</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>50</td><td>20</td><td>0.03926723</td><td>53</td><td>19</td><td>0</td><td>0.015814753</td><td>1.7933123</td><td>0</td><td>0</td><td>1.0357476</td><td>0.19043407</td><td>0.32772923</td><td>0.23566131</td><td>0.41409686</td><td>171.96785</td><td>-10.144089</td><td>17.043184</td><td>-34.528023</td><td>False</td><td>455</td><td>27294.443449297396</td><td>6.930448</td><td>3938.3374</td><td>14.597181</td><td>49</td><td>6879.836171656016</td><td>9.31669</td><td>738.4421</td><td>15.744597</td><td>48</td><td>30135.04225336285</td><td>19.934744</td><td>1511.6844</td><td>13.550216</td><td>1.3561324</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2.1943817</td><td>1.1474161</td><td>1.0469656</td><td>-122.37873</td><td>2.0260947</td><td>2</td><td>17</td><td>10</td><td>11</td><td>7.6918716</td><td>--</td><td>--</td><td>763.8885</td><td>--</td><td>4250.0</td><td>1.0</td><td>-0.5</td><td>111</td><td>--</td><td>--</td><td>--</td><td>13.023737</td><td>0.089120515</td><td>7</td><td>--</td><td>NOT_AVAILABLE</td><td>335.1007709312551</td><td>-4.072115096889941</td><td>257.08181538353045</td><td>-28.993992671997994</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>True</td><td>True</td><td>False</td><td>1.0202967e-13</td><td>5.096331e-13</td><td>0.9999993</td><td>4540.0796</td><td>4532.843</td><td>4547.935</td><td>2.3788</td><td>2.3651</td><td>2.4102</td><td>0.2313</td><td>0.2303</td><td>0.2339</td><td>2491.513</td><td>2411.611</td><td>2523.5083</td><td>2.4429</td><td>2.4335</td><td>2.4527</td><td>1.7478</td><td>1.7406</td><td>1.7555</td><td>0.9238</td><td>0.92</td><td>0.928</td><td>MARCS</td></tr>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937081383743372032</td><td>5937081383743372032</td><td>1388896741</td><td>2016.0</td><td>251.62238319226026</td><td>0.029433807</td><td>-51.62029027189454</td><td>0.020515807</td><td>0.6924009910207137</td><td>0.036633335</td><td>18.900845</td><td>5.762399</td><td>-2.1962513998024753</td><td>0.041033864</td><td>-5.32744995436843</td><td>0.03017893</td><td>0.07881943</td><td>-0.18317024</td><td>-0.0902052</td><td>-0.41693145</td><td>-0.055258308</td><td>-0.37683496</td><td>-0.017432967</td><td>0.018904045</td><td>0.15508316</td><td>0.29985723</td><td>424</td><td>270</td><td>424</td><td>0</td><td>21.224941</td><td>2526.7124</td><td>0.28364065</td><td>67.70416</td><td>31</td><td>False</td><td>1.5341111</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>49</td><td>20</td><td>0.060006</td><td>54</td><td>17</td><td>0</td><td>0.031195693</td><td>14.095997</td><td>29</td><td>0</td><td>1.8156136</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>False</td><td>352</td><td>128395.12969023235</td><td>50.17742</td><td>2558.8228</td><td>12.915996</td><td>49</td><td>67358.68812353928</td><td>57.54373</td><td>1170.5652</td><td>13.267558</td><td>50</td><td>92071.00855188111</td><td>108.90684</td><td>845.4107</td><td>12.337588</td><td>1.2417114</td><td>0</td><td>49</td><td>0</td><td>50</td><td>0</td><td>0.9299698</td><td>0.3515625</td><td>0.5784073</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>NOT_AVAILABLE</td><td>335.086222112606</td><td>-4.065747567198785</td><td>257.0668428683234</td><td>-29.002917747180796</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>True</td><td>True</td><td>False</td><td>1.02131946e-13</td><td>5.1014396e-13</td><td>0.99998915</td><td>9607.438</td><td>9513.894</td><td>9772.668</td><td>3.9733</td><td>3.9396</td><td>4.0248</td><td>0.3169</td><td>0.2221</td><td>0.3834</td><td>1375.4949</td><td>1294.5084</td><td>1433.022</td><td>1.9518</td><td>1.9397</td><td>1.9703</td><td>1.7455</td><td>1.7337</td><td>1.7639</td><td>0.9426</td><td>0.9359</td><td>0.9528</td><td>A</td></tr>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937173334767134336</td><td>5937173334767134336</td><td>1157832125</td><td>2016.0</td><td>250.21566824117917</td><td>0.059527557</td><td>-51.595920889486656</td><td>0.04271079</td><td>0.4702682635100296</td><td>0.07166432</td><td>6.5620975</td><td>3.4092753</td><td>-1.938231765299124</td><td>0.07593253</td><td>-2.804713168282807</td><td>0.060880087</td><td>0.051077027</td><td>-0.20518416</td><td>-0.080830626</td><td>-0.43357953</td><td>-0.09915663</td><td>-0.3913832</td><td>0.03832911</td><td>0.002058486</td><td>0.05821425</td><td>0.137561</td><td>374</td><td>0</td><td>372</td><td>2</td><td>45.74267</td><td>3584.2673</td><td>0.56429577</td><td>112.12796</td><td>31</td><td>False</td><td>1.514927</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>43</td><td>20</td><td>0.10856331</td><td>46</td><td>17</td><td>0</td><td>0.044881888</td><td>22.828472</td><td>13</td><td>0</td><td>3.0976706</td><td>0.15475534</td><td>0.29480875</td><td>0.12611878</td><td>0.39342368</td><td>-159.89705</td><td>-4.4460692</td><td>11.778325</td><td>-32.8211</td><td>False</td><td>386</td><td>31558.894737116752</td><td>21.077711</td><td>1497.2638</td><td>14.439563</td><td>41</td><td>16130.656604160753</td><td>18.109373</td><td>890.7352</td><td>14.819412</td><td>36</td><td>23815.380522198586</td><td>71.041046</td><td>335.2341</td><td>13.805752</td><td>1.2657616</td><td>3</td><td>8</td><td>0</td><td>4</td><td>0</td><td>1.0136604</td><td>0.37984943</td><td>0.633811</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>NOT_AVAILABLE</td><td>334.53250037174223</td><td>-3.3886382930011103</td><td>256.0744276709499</td><td>-29.10877333882436</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>True</td><td>True</td><td>False</td><td>1.0207059e-13</td><td>5.0983745e-13</td><td>0.99999523</td><td>9269.764</td><td>9201.429</td><td>9449.048</td><td>3.7875</td><td>3.7318</td><td>3.9789</td><td>0.2939</td><td>-0.0666</td><td>0.4526</td><td>3178.5076</td><td>2359.795</td><td>3469.735</td><td>2.1056</td><td>2.0933</td><td>2.1177</td><td>1.8642</td><td>1.8523</td><td>1.876</td><td>1.0085</td><td>1.0021</td><td>1.0152</td><td>A</td></tr>\n",
       "<tr><td>1636148068921376768</td><td>Gaia DR3 5937173334780460032</td><td>5937173334780460032</td><td>678129793</td><td>2016.0</td><td>250.21356325663368</td><td>0.23394246</td><td>-51.59396329321622</td><td>0.19552518</td><td>-0.3508260735074602</td><td>0.30190325</td><td>-1.162048</td><td>1.6001855</td><td>1.073248649206787</td><td>0.29730964</td><td>-1.1868996821513624</td><td>0.2584137</td><td>0.06328716</td><td>-0.20351417</td><td>-0.07027874</td><td>-0.41031334</td><td>-0.17773803</td><td>-0.37811938</td><td>0.16410476</td><td>-0.0030481764</td><td>-0.0031035203</td><td>0.14021164</td><td>373</td><td>9</td><td>341</td><td>32</td><td>150.71007</td><td>132927.52</td><td>2.3321652</td><td>3471.7947</td><td>95</td><td>False</td><td>--</td><td>1.6892734</td><td>0.057007648</td><td>-0.0964132</td><td>-0.03026436</td><td>-0.07226244</td><td>0.04191873</td><td>0.24999605</td><td>40</td><td>19</td><td>0.42922014</td><td>46</td><td>46</td><td>0</td><td>0.18801957</td><td>15.406193</td><td>71</td><td>0</td><td>10.78346</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>--</td><td>False</td><td>282</td><td>64011.30718913338</td><td>48.864918</td><td>1309.9645</td><td>13.671725</td><td>41</td><td>42860.99511271846</td><td>53.568825</td><td>800.1108</td><td>13.758387</td><td>40</td><td>54560.38493285597</td><td>48.257896</td><td>1130.6001</td><td>12.905702</td><td>1.5219402</td><td>0</td><td>1</td><td>0</td><td>0</td><td>0</td><td>0.852685</td><td>0.08666134</td><td>0.76602364</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>NOT_AVAILABLE</td><td>334.5331071374701</td><td>-3.386363373671223</td><td>256.0726035824586</td><td>-29.107040650639295</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>False</td><td>True</td><td>False</td><td>1.6654e-09</td><td>7.449532e-10</td><td>0.9999764</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>1636148068921376768</td><td>Gaia DR3 5937144266449624832</td><td>5937144266449624832</td><td>1623142172</td><td>2016.0</td><td>251.43324440910578</td><td>0.014669927</td><td>-50.77413489978534</td><td>0.010906572</td><td>0.41842144724333197</td><td>0.020740218</td><td>20.174398</td><td>1.853632</td><td>0.3252629089347102</td><td>0.019978473</td><td>-1.8248714140155078</td><td>0.015091202</td><td>-0.04721357</td><td>-0.12086837</td><td>-0.003795892</td><td>-0.47315618</td><td>-0.14569509</td><td>-0.4635919</td><td>0.13550735</td><td>0.06636885</td><td>-0.08241941</td><td>0.14478737</td><td>439</td><td>0</td><td>438</td><td>1</td><td>-1.5463891</td><td>423.98978</td><td>0.0</td><td>0.0</td><td>95</td><td>False</td><td>--</td><td>1.4685915</td><td>0.0034969677</td><td>-0.074927785</td><td>0.111765906</td><td>-0.20162709</td><td>-0.12379193</td><td>0.14058335</td><td>50</td><td>17</td><td>0.028448544</td><td>52</td><td>52</td><td>0</td><td>0.016981049</td><td>11.932347</td><td>0</td><td>0</td><td>0.94709694</td><td>0.20634997</td><td>0.29949948</td><td>0.20517065</td><td>0.5272535</td><td>177.81488</td><td>-7.7354107</td><td>14.658453</td><td>-32.942963</td><td>False</td><td>436</td><td>54841.20365068016</td><td>12.59829</td><td>4353.067</td><td>13.8396</td><td>50</td><td>24517.535498153924</td><td>22.031908</td><td>1112.8195</td><td>14.36485</td><td>48</td><td>44526.903642145546</td><td>30.803144</td><td>1445.5311</td><td>13.126339</td><td>1.2589884</td><td>0</td><td>50</td><td>0</td><td>1</td><td>0</td><td>1.2385111</td><td>0.52525043</td><td>0.71326065</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>NOT_AVAILABLE</td><td>335.6552971174124</td><td>-3.427339589205473</td><td>256.7949289949452</td><td>-28.182537219651195</td><td>False</td><td>False</td><td>0</td><td>True</td><td>True</td><td>False</td><td>False</td><td>False</td><td>False</td><td>True</td><td>False</td><td>1.0206264e-13</td><td>5.956727e-11</td><td>0.999996</td><td>8596.297</td><td>8481.228</td><td>8603.199</td><td>3.452</td><td>3.4049</td><td>3.4684</td><td>-0.3281</td><td>-0.3338</td><td>-0.3236</td><td>2582.0444</td><td>2537.1003</td><td>2722.1555</td><td>2.4509</td><td>2.4126</td><td>2.4537</td><td>2.1134</td><td>2.0769</td><td>2.1157</td><td>1.1535</td><td>1.1325</td><td>1.1548</td><td>PHOENIX</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=10>\n",
       "    solution_id             DESIGNATION               source_id      random_index ref_epoch ... ebpminrp_gspphot ebpminrp_gspphot_lower ebpminrp_gspphot_upper libname_gspphot\n",
       "                                                                                      yr    ...       mag                 mag                    mag                          \n",
       "       int64                   object                   int64           int64      float64  ...     float32             float32                float32              object    \n",
       "------------------- ---------------------------- ------------------- ------------ --------- ... ---------------- ---------------------- ---------------------- ---------------\n",
       "1636148068921376768 Gaia DR3 5937173266047638272 5937173266047638272    314958060    2016.0 ...           1.5555                 1.5548                 1.5561              OB\n",
       "1636148068921376768 Gaia DR3 5937144197726034816 5937144197726034816    409734603    2016.0 ...               --                     --                     --                \n",
       "1636148068921376768 Gaia DR3 5937144197726039936 5937144197726039936    440987907    2016.0 ...           0.1983                 0.1897                 0.2201           MARCS\n",
       "1636148068921376768 Gaia DR3 5937144197726350592 5937144197726350592    205487013    2016.0 ...           1.3457                 1.2868                 1.4217         PHOENIX\n",
       "1636148068921376768 Gaia DR3 5937173300407375616 5937173300407375616    169494443    2016.0 ...               --                     --                     --                \n",
       "1636148068921376768 Gaia DR3 5937081353758582016 5937081353758582016   1530038650    2016.0 ...           0.9238                   0.92                  0.928           MARCS\n",
       "1636148068921376768 Gaia DR3 5937081383743372032 5937081383743372032   1388896741    2016.0 ...           0.9426                 0.9359                 0.9528               A\n",
       "1636148068921376768 Gaia DR3 5937173334767134336 5937173334767134336   1157832125    2016.0 ...           1.0085                 1.0021                 1.0152               A\n",
       "1636148068921376768 Gaia DR3 5937173334780460032 5937173334780460032    678129793    2016.0 ...               --                     --                     --                \n",
       "1636148068921376768 Gaia DR3 5937144266449624832 5937144266449624832   1623142172    2016.0 ...           1.1535                 1.1325                 1.1548         PHOENIX"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "query = f\"SELECT TOP 10 * FROM gaiadr3.gaia_source \\\n",
    "WHERE has_xp_sampled = 'True'\"\n",
    "\n",
    "job     = Gaia.launch_job_async(query)\n",
    "results = job.get_results()\n",
    "results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "930f5922",
   "metadata": {},
   "source": [
    "### Retrieve the XP Sampled spectra from DataLink\n",
    "\n",
    "The metadata of the XP Sampled products raises an Astropy units warning. This is a known issue and we are also working on it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "977c094b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: Unit 'em' not supported by the VOUnit standard. Did you mean Elm or Em? [astropy.units.format.vounit]\n",
      "WARNING: UnitsWarning: Unit 'wl' not supported by the VOUnit standard.  [astropy.units.format.vounit]\n"
     ]
    }
   ],
   "source": [
    "datalink = Gaia.load_data(results['source_id'], data_structure = 'INDIVIDUAL', retrieval_type = 'XP_SAMPLED')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ba7cb461",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=343</i>\n",
       "<table id=\"table140561406303136\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>wavelength</th><th>flux</th><th>flux_error</th><th>flux_jy</th><th>flux_mjy</th></tr></thead>\n",
       "<thead><tr><th>nm</th><th>W / (m2 nm)</th><th>W / (m2 nm)</th><th>Jy</th><th>mJy</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float32</th><th>float32</th><th>float64</th><th>float64</th></tr></thead>\n",
       "<tr><td>336.0</td><td>7.9894715e-17</td><td>1.2711064e-17</td><td>0.003008679305218825</td><td>3.0087</td></tr>\n",
       "<tr><td>338.0</td><td>6.811754e-17</td><td>1.1104153e-17</td><td>0.0025958026386069277</td><td>2.5958</td></tr>\n",
       "<tr><td>340.0</td><td>5.87597e-17</td><td>8.086387e-18</td><td>0.0022657746024016693</td><td>2.2658</td></tr>\n",
       "<tr><td>342.0</td><td>5.7587097e-17</td><td>7.838529e-18</td><td>0.0022467600885352906</td><td>2.2468</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>1014.0</td><td>7.951429e-17</td><td>3.393551e-17</td><td>0.027270959468149857</td><td>27.2710</td></tr>\n",
       "<tr><td>1016.0</td><td>8.386952e-17</td><td>3.6400103e-17</td><td>0.028878252085620608</td><td>28.8783</td></tr>\n",
       "<tr><td>1018.0</td><td>8.631832e-17</td><td>3.7284885e-17</td><td>0.0298385594395844</td><td>29.8386</td></tr>\n",
       "<tr><td>1020.0</td><td>9.186709e-17</td><td>3.9505603e-17</td><td>0.031881563667395155</td><td>31.8816</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=343>\n",
       "wavelength      flux       flux_error         flux_jy        flux_mjy\n",
       "    nm      W / (m2 nm)   W / (m2 nm)            Jy            mJy   \n",
       " float64      float32       float32           float64        float64 \n",
       "---------- ------------- ------------- --------------------- --------\n",
       "     336.0 7.9894715e-17 1.2711064e-17  0.003008679305218825   3.0087\n",
       "     338.0  6.811754e-17 1.1104153e-17 0.0025958026386069277   2.5958\n",
       "     340.0   5.87597e-17  8.086387e-18 0.0022657746024016693   2.2658\n",
       "     342.0 5.7587097e-17  7.838529e-18 0.0022467600885352906   2.2468\n",
       "       ...           ...           ...                   ...      ...\n",
       "    1014.0  7.951429e-17  3.393551e-17  0.027270959468149857  27.2710\n",
       "    1016.0  8.386952e-17 3.6400103e-17  0.028878252085620608  28.8783\n",
       "    1018.0  8.631832e-17 3.7284885e-17    0.0298385594395844  29.8386\n",
       "    1020.0  9.186709e-17 3.9505603e-17  0.031881563667395155  31.8816"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x504 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Extract XP sampled spectra for a given source =======\n",
    "outputs = [datalink[key][0] for key in datalink.keys()]\n",
    "xp      = outputs[5].to_table()                        #  Plot the different spectra by changing '5' to e.g., 0, 1, ..., 9\n",
    "\n",
    "# Add flux-density columns ============================\n",
    "xp['flux_jy']         = xp['flux'].to(u.Jansky, equivalencies = u.spectral_density(xp['wavelength'].value * xp['wavelength'].unit))\n",
    "xp['flux_mjy']        = xp['flux_jy'].to(u.millijansky)\n",
    "xp['flux_mjy'].format = '7.4f'\n",
    "display(xp)\n",
    "\n",
    "\n",
    "# Plotter ==============================================\n",
    "def make_canvas(xlabel = '', ylabel = '', fontsize = 12):\n",
    "    plt.xlabel(xlabel,  fontsize = fontsize)\n",
    "    plt.ylabel(ylabel, fontsize = fontsize)\n",
    "    plt.xticks(fontsize = fontsize)\n",
    "    plt.yticks(fontsize = fontsize)\n",
    "    plt.grid()\n",
    "\n",
    "fig       = plt.figure(figsize=[30,7])\n",
    "\n",
    "plt.subplot(121)\n",
    "plt.plot(xp['wavelength'], xp['flux'], linewidth = 2)\n",
    "make_canvas(xlabel = f\"Wavelength [{xp['wavelength'].unit}]\", ylabel = f\"Flux [{xp['flux'].unit}]\", fontsize = 22)\n",
    "\n",
    "plt.subplot(122)\n",
    "plt.plot(xp['wavelength'], xp['flux_mjy'], linewidth = 2)\n",
    "make_canvas(xlabel = f\"Wavelength [{xp['wavelength'].unit}]\", ylabel = f\"Flux density [{xp['flux_mjy'].unit}]\", fontsize = 22)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3f68a74a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
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