{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6739c4ef",
   "metadata": {},
   "source": [
    "# Tiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d4d63458",
   "metadata": {},
   "outputs": [],
   "source": [
    "from supy.tiles import Tiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2d9e45ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "T = Tiles()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd815b15",
   "metadata": {},
   "source": [
    "### Provide the list of ra and dec"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ebca220",
   "metadata": {},
   "source": [
    "#### Method 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "b45cc439",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=1</i>\n",
       "<table id=\"table4439039408\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>ra</th><th>dec</th><th>hhmmss</th><th>ddmmss</th><th>j2000</th><th>aperture</th><th>matched_idx</th><th>matched_tile</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>str12</th><th>str11</th><th>str20</th><th>int64</th><th>int64</th><th>str6</th></tr></thead>\n",
       "<tr><td>173.6688</td><td>-21.05625</td><td>11:34:40.512</td><td>-21:03:22.5</td><td>J113440.51-21-322.50</td><td>0</td><td>0</td><td>T12180</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=1>\n",
       "   ra       dec       hhmmss    ... aperture matched_idx matched_tile\n",
       "float64   float64     str12     ...  int64      int64        str6    \n",
       "-------- --------- ------------ ... -------- ----------- ------------\n",
       "173.6688 -21.05625 11:34:40.512 ...        0           0       T12180"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ra, dec = 173.6688, -21.05625\n",
    "\n",
    "T.find_overlapping_tiles(ra=ra, dec=dec, list_aperture = 0,\n",
    "                         match_tolerance_minutes=4, fraction_overlap_lower= 0.1 )\n",
    "T.target_table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fccab75f",
   "metadata": {},
   "source": [
    "#### Method 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "407bdd34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=1</i>\n",
       "<table id=\"table4704713264\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>ra</th><th>dec</th><th>hhmmss</th><th>ddmmss</th><th>j2000</th><th>aperture</th><th>matched_idx</th><th>matched_tile</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>str11</th><th>str12</th><th>str21</th><th>int64</th><th>int64</th><th>str6</th></tr></thead>\n",
       "<tr><td>166.63937499999997</td><td>-18.356719444444447</td><td>11:06:33.45</td><td>-18:21:24.19</td><td>J110633.45-18-2124.19</td><td>0</td><td>0</td><td>T12965</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=1>\n",
       "        ra                 dec            hhmmss   ... matched_idx matched_tile\n",
       "     float64             float64          str11    ...    int64        str6    \n",
       "------------------ ------------------- ----------- ... ----------- ------------\n",
       "166.63937499999997 -18.356719444444447 11:06:33.45 ...           0       T12965"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "j2000 = 'J110633.45-182124.19'\n",
    "\n",
    "T.find_overlapping_tiles(j2000=j2000, list_aperture = 0,\n",
    "                         match_tolerance_minutes=4, fraction_overlap_lower= 0.1 )\n",
    "T.target_table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a5355efd",
   "metadata": {},
   "source": [
    "#### Method 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "64b7b2f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=1</i>\n",
       "<table id=\"table4704702224\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>ra</th><th>dec</th><th>hhmmss</th><th>ddmmss</th><th>j2000</th><th>aperture</th><th>matched_idx</th><th>matched_tile</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>str12</th><th>str11</th><th>str20</th><th>int64</th><th>int64</th><th>str6</th></tr></thead>\n",
       "<tr><td>173.6688</td><td>-21.05625</td><td>11:34:40.512</td><td>-21:03:22.5</td><td>J113440.51-21-322.50</td><td>0</td><td>0</td><td>T12180</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=1>\n",
       "   ra       dec       hhmmss    ... aperture matched_idx matched_tile\n",
       "float64   float64     str12     ...  int64      int64        str6    \n",
       "-------- --------- ------------ ... -------- ----------- ------------\n",
       "173.6688 -21.05625 11:34:40.512 ...        0           0       T12180"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc = [173.6688, -21.05625]\n",
    "\n",
    "T.find_overlapping_tiles(loc=loc, list_aperture = 0,\n",
    "                         match_tolerance_minutes=4, fraction_overlap_lower= 0.1 )\n",
    "T.target_table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df8eda1f",
   "metadata": {},
   "source": [
    "### List of localizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "e29c0834",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=2</i>\n",
       "<table id=\"table4704699632\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>ra</th><th>dec</th><th>hhmmss</th><th>ddmmss</th><th>j2000</th><th>aperture</th><th>matched_idx</th><th>matched_tile</th></tr></thead>\n",
       "<thead><tr><th>float64</th><th>float64</th><th>str12</th><th>str12</th><th>str21</th><th>int64</th><th>int64</th><th>str6</th></tr></thead>\n",
       "<tr><td>173.6688</td><td>-21.05625</td><td>11:34:40.512</td><td>-21:03:22.5</td><td>J113440.51-21-322.50</td><td>0</td><td>0</td><td>T12180</td></tr>\n",
       "<tr><td>166.63937499999997</td><td>-18.356719444444447</td><td>11:06:33.45</td><td>-18:21:24.19</td><td>J110633.45-18-2124.19</td><td>0</td><td>1</td><td>T12965</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=2>\n",
       "        ra                 dec         ... matched_idx matched_tile\n",
       "     float64             float64       ...    int64        str6    \n",
       "------------------ ------------------- ... ----------- ------------\n",
       "          173.6688           -21.05625 ...           0       T12180\n",
       "166.63937499999997 -18.356719444444447 ...           1       T12965"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loc = [[173.6688, -21.05625], 'J110633.45-182124.19']\n",
    "\n",
    "T.find_overlapping_tiles(loc=loc, \n",
    "                         match_tolerance_minutes=4, fraction_overlap_lower= 0.1 )\n",
    "T.target_table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57fe616b",
   "metadata": {},
   "source": [
    "### Matched tile information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "601da808",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=2</i>\n",
       "<table id=\"table4704706016\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>id</th><th>ra</th><th>dec</th><th>ra1</th><th>dec1</th><th>ra2</th><th>dec2</th><th>ra3</th><th>dec3</th><th>ra4</th><th>dec4</th><th>matched_idx</th><th>distance_to_boundary</th><th>overlapped_area</th><th>is_within_boundary</th></tr></thead>\n",
       "<thead><tr><th>str6</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>int64</th><th>float64</th><th>int64</th><th>bool</th></tr></thead>\n",
       "<tr><td>T12180</td><td>173.79310344827587</td><td>-21.226415094339615</td><td>174.52835458030515</td><td>-20.767318019947634</td><td>174.53292925678073</td><td>-21.682308083156066</td><td>173.05327763977098</td><td>-21.682308083156066</td><td>173.05785231624662</td><td>-20.767318019947634</td><td>0</td><td>0.2889319800523644</td><td>1</td><td>True</td></tr>\n",
       "<tr><td>T12965</td><td>166.46616541353384</td><td>-18.679245283018858</td><td>167.18993430784832</td><td>-18.220354589450892</td><td>167.1938524736855</td><td>-19.135347060918647</td><td>165.73847835338216</td><td>-19.135347060918647</td><td>165.74239651921934</td><td>-18.220354589450892</td><td>1</td><td>0.13636485499355544</td><td>1</td><td>True</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=2>\n",
       "  id           ra         ... overlapped_area is_within_boundary\n",
       " str6       float64       ...      int64             bool       \n",
       "------ ------------------ ... --------------- ------------------\n",
       "T12180 173.79310344827587 ...               1               True\n",
       "T12965 166.46616541353384 ...               1               True"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "T.tile_table"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e5837b0",
   "metadata": {},
   "source": [
    "### Visualize the tiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "325e8f92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T.visualize_tiles()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1d42bd76",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}