LabelExgal.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f612a5f4-eada-4713-af93-0e4777b5af1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sqlite3\n",
    "import healpy as hp\n",
    "import rubin_sim.maf as maf\n",
    "from rubin_scheduler.scheduler.utils import CurrentAreaMap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4ca5c862-dfcb-4748-9844-3527f0c64d63",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['' 'LMC_SMC' 'bulgy' 'dusty_plane' 'euclid_overlap' 'lowdust' 'nes' 'scp'\n",
      " 'virgo']\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 850x540 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nside = 64\n",
    "sky = CurrentAreaMap(nside=nside)\n",
    "# footprints contains the goal weights per filter, for the sky (all survey modes together)\n",
    "# labels contains the label (survey mode) for each healpix. \n",
    "footprints, labels = sky.return_maps()\n",
    "print(np.unique(labels))\n",
    "\n",
    "wfd_extragalactic = np.where((labels == \"euclid_overlap\") |  (labels ==\"lowdust\"), 1, 0)\n",
    "hp.mollview(wfd_extragalactic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "bb143dfd-87a1-4423-b81b-4d643f9faf58",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "baseline_v4.0_10yrs : /Users/lynnej/opsim/fbs_4.0/baseline_v4.0_10yrs.db\n"
     ]
    }
   ],
   "source": [
    "# You can look at the notes to see if there's anything you should explicitly reject\n",
    "opsdb = '/Users/lynnej/opsim/fbs_4.0/baseline_v4.0_10yrs.db'\n",
    "conn = sqlite3.connect(opsdb)\n",
    "\n",
    "opsim = os.path.split(opsdb)[-1].replace('.db', '')\n",
    "print(opsim, \":\", opsdb)\n",
    "visits = pd.read_sql('select * from observations', conn)\n",
    "ovisitsnp = visits.to_records(index=False)\n",
    "\n",
    "if \"scheduler_note\" not in visits.columns:\n",
    "    print(\"using an older simulation so probably need to use 'note' instead of 'scheduler_note'\")\n",
    "\n",
    "note_col = 'scheduler_note'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8dfbe166-0204-4aa7-9fd1-da0c5870702b",
   "metadata": {},
   "outputs": [],
   "source": [
    "name = 'ExGal'\n",
    "\n",
    "# label the visits based on their spatial location using the WFDlabelStacker\n",
    "# https://github.com/lsst/rubin_sim/blob/3c307d33dcae0a89de7a6925debb8acf7e120606/rubin_sim/maf/stackers/label_stackers.py#L9\n",
    "footpt = np.where((labels == 'lowdust') | (labels == 'euclid_overlap'), 1, 0)\n",
    "stacker = maf.WFDlabelStacker(footprint=footpt, area_id_name=name, exclude_dd=False)\n",
    "ovisitsnp = stacker.run(sim_data=ovisitsnp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "266f77a5-f010-48b3-a569-2a50ce1adb0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Now ovisitsnp has all visits which lie in the extragalactic WFD area labeled as \"WFD\" \n",
    "# But you probably still want to reject non-wfd mode visits so we'll just flip those back\n",
    "labelled_visits = pd.DataFrame(ovisitsnp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7b8f9264-fa35-4d3f-ad65-a283f8dc2323",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['blob_long, gr, a', 'blob_long, gr, b', 'pair_33, ug, a', 'pair_33, ug, b', 'long', 'twilight_near_sun, 0', 'twilight_near_sun, 1', 'twilight_near_sun, 2', 'twilight_near_sun, 3', 'greedy', 'pair_15, iz, a', 'pair_15, iz, b', 'DD:COSMOS', 'pair_15, ri, a', 'pair_15, ri, b', 'pair_33, gr, a', 'pair_33, gr, b', 'pair_15, yy, a', 'pair_15, yy, b', 'pair_33, ri, a', 'pair_33, ri, b', 'pair_33, zy, a', 'pair_33, zy, b', 'pair_33, yy, a', 'pair_33, yy, b', 'pair_15, zy, a', 'pair_15, zy, b', 'blob_long, iz, a', 'blob_long, iz, b', 'pair_33, iz, a', 'pair_33, iz, b', 'pair_33, ur, a', 'pair_33, ur, b', 'DD:ELAISS1', 'blob_long, ri, a', 'blob_long, ri, b', 'DD:XMM_LSS', 'DD:EDFS_a', 'DD:EDFS_b', 'DD:ECDFS', 'DD: RGES_onseason', 'DD: RGES_offseason']\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "scheduler_note\n",
       "DD: RGES_offseason             [NULL]\n",
       "DD: RGES_onseason              [NULL]\n",
       "DD:COSMOS                     [ExGal]\n",
       "DD:ECDFS                      [ExGal]\n",
       "DD:EDFS_a                     [ExGal]\n",
       "                            ...      \n",
       "pair_33, zy, b          [ExGal, NULL]\n",
       "twilight_near_sun, 0    [ExGal, NULL]\n",
       "twilight_near_sun, 1    [ExGal, NULL]\n",
       "twilight_near_sun, 2    [ExGal, NULL]\n",
       "twilight_near_sun, 3    [ExGal, NULL]\n",
       "Name: area_id, Length: 1508, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print([n for n in labelled_visits[note_col].unique() if 'ToO' not in n])\n",
    "labelled_visits[['scheduler_note', 'area_id']].groupby('scheduler_note').area_id.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7a75f780-0f4e-4833-8ece-cd452c7cb478",
   "metadata": {},
   "outputs": [],
   "source": [
    "query = f\"({note_col}.str.contains('DD')) or ({note_col}.str.contains('twilight')) or ({note_col}.str.contains('ToO'))\"\n",
    "special_mode = visits.query(query)\n",
    "col_id = np.where(labelled_visits.columns.values == \"area_id\")[0][0]\n",
    "labelled_visits.iloc[special_mode.index, col_id] = 'NULL'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dd618c50-6df1-47ef-8eb6-dea192b5b7d5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>observationId</th>\n",
       "      <th>fieldRA</th>\n",
       "      <th>fieldDec</th>\n",
       "      <th>observationStartMJD</th>\n",
       "      <th>flush_by_mjd</th>\n",
       "      <th>visitExposureTime</th>\n",
       "      <th>filter</th>\n",
       "      <th>rotSkyPos</th>\n",
       "      <th>rotSkyPos_desired</th>\n",
       "      <th>numExposures</th>\n",
       "      <th>...</th>\n",
       "      <th>moonRA</th>\n",
       "      <th>moonDec</th>\n",
       "      <th>moonDistance</th>\n",
       "      <th>solarElong</th>\n",
       "      <th>moonPhase</th>\n",
       "      <th>cummTelAz</th>\n",
       "      <th>scripted_id</th>\n",
       "      <th>observation_reason</th>\n",
       "      <th>science_program</th>\n",
       "      <th>area_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>200.782211</td>\n",
       "      <td>-50.116498</td>\n",
       "      <td>60796.001439</td>\n",
       "      <td>60796.068648</td>\n",
       "      <td>29.2</td>\n",
       "      <td>r</td>\n",
       "      <td>142.995018</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>83.711608</td>\n",
       "      <td>29.111132</td>\n",
       "      <td>128.922776</td>\n",
       "      <td>142.152585</td>\n",
       "      <td>24.587034</td>\n",
       "      <td>132.523734</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>ExGal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>204.232107</td>\n",
       "      <td>-51.991147</td>\n",
       "      <td>60796.001885</td>\n",
       "      <td>60796.068648</td>\n",
       "      <td>29.2</td>\n",
       "      <td>r</td>\n",
       "      <td>142.513540</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>83.717806</td>\n",
       "      <td>29.110360</td>\n",
       "      <td>131.032507</td>\n",
       "      <td>141.364093</td>\n",
       "      <td>24.589708</td>\n",
       "      <td>134.815659</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NULL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>207.940418</td>\n",
       "      <td>-53.783599</td>\n",
       "      <td>60796.002331</td>\n",
       "      <td>60796.068648</td>\n",
       "      <td>29.2</td>\n",
       "      <td>r</td>\n",
       "      <td>141.167403</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>83.724012</td>\n",
       "      <td>29.109586</td>\n",
       "      <td>133.059975</td>\n",
       "      <td>140.381429</td>\n",
       "      <td>24.592386</td>\n",
       "      <td>136.960725</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NULL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>203.082640</td>\n",
       "      <td>-54.987835</td>\n",
       "      <td>60796.002778</td>\n",
       "      <td>60796.068648</td>\n",
       "      <td>29.2</td>\n",
       "      <td>r</td>\n",
       "      <td>146.759369</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>83.730237</td>\n",
       "      <td>29.108808</td>\n",
       "      <td>130.102187</td>\n",
       "      <td>138.329174</td>\n",
       "      <td>24.595072</td>\n",
       "      <td>139.141162</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NULL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>207.055974</td>\n",
       "      <td>-56.848274</td>\n",
       "      <td>60796.003224</td>\n",
       "      <td>60796.068648</td>\n",
       "      <td>29.2</td>\n",
       "      <td>r</td>\n",
       "      <td>145.009266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
       "      <td>83.736461</td>\n",
       "      <td>29.108030</td>\n",
       "      <td>132.046197</td>\n",
       "      <td>137.294965</td>\n",
       "      <td>24.597759</td>\n",
       "      <td>141.153789</td>\n",
       "      <td>0</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>NULL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 48 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   observationId     fieldRA   fieldDec  observationStartMJD  flush_by_mjd  \\\n",
       "0              0  200.782211 -50.116498         60796.001439  60796.068648   \n",
       "1              1  204.232107 -51.991147         60796.001885  60796.068648   \n",
       "2              2  207.940418 -53.783599         60796.002331  60796.068648   \n",
       "3              3  203.082640 -54.987835         60796.002778  60796.068648   \n",
       "4              4  207.055974 -56.848274         60796.003224  60796.068648   \n",
       "\n",
       "   visitExposureTime filter   rotSkyPos  rotSkyPos_desired  numExposures  ...  \\\n",
       "0               29.2      r  142.995018                0.0             2  ...   \n",
       "1               29.2      r  142.513540                0.0             2  ...   \n",
       "2               29.2      r  141.167403                0.0             2  ...   \n",
       "3               29.2      r  146.759369                0.0             2  ...   \n",
       "4               29.2      r  145.009266                0.0             2  ...   \n",
       "\n",
       "      moonRA    moonDec  moonDistance  solarElong  moonPhase   cummTelAz  \\\n",
       "0  83.711608  29.111132    128.922776  142.152585  24.587034  132.523734   \n",
       "1  83.717806  29.110360    131.032507  141.364093  24.589708  134.815659   \n",
       "2  83.724012  29.109586    133.059975  140.381429  24.592386  136.960725   \n",
       "3  83.730237  29.108808    130.102187  138.329174  24.595072  139.141162   \n",
       "4  83.736461  29.108030    132.046197  137.294965  24.597759  141.153789   \n",
       "\n",
       "   scripted_id  observation_reason  science_program  area_id  \n",
       "0            0                                         ExGal  \n",
       "1            0                                          NULL  \n",
       "2            0                                          NULL  \n",
       "3            0                                          NULL  \n",
       "4            0                                          NULL  \n",
       "\n",
       "[5 rows x 48 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labelled_visits.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8fda16e9-3638-4a35-87f4-2fef53db615f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2038634"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newdb = f'exgal_labelled_{opsim}.db'\n",
    "if os.path.isfile(newdb):\n",
    "    os.remove(newdb)\n",
    "    \n",
    "conn = sqlite3.connect(newdb)\n",
    "\n",
    "labelled_visits.to_sql(name='observations', con=conn, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a79496ad-06bf-4b86-93e4-e692db3f7e35",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "exgal_labelled_baseline_v4.0_10yrs.db\n"
     ]
    }
   ],
   "source": [
    "!ls $newdb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a3ae71f-e0ed-411b-ac6b-bd0500a6af58",
   "metadata": {},
   "outputs": [],
   "source": [
    "# lynnej@tama notebooks % sqlite3 exgal_labelled_baseline_v4.0_10yrs.db \n",
    "# SQLite version 3.45.3 2024-04-15 13:34:05\n",
    "# Enter \".help\" for usage hints.\n",
    "# sqlite> select * from observations limit 1;\n",
    "# 0|200.782210821212|-50.1164984340556|60796.0014392263|60796.0686481482|29.2|r|142.995017640325|0.0|2|1.37960737879413|0.78353725168396|1.19302564834337|1.03266708293825|21.0279565795215|0|124.349156223464|33.6|45.9675478977889|23.9438499398853|46.5327792596511|132.733199166703|277.092454740965|-82.8394295681317|0.125|4.34377657911936|-25.0323607709486||blob_long, gr, a||1|148.947367621645|44.1655527915437|0.0|307.54443047623|273.457997458161|38.1092631808875|14.9774602028322|83.7116078104931|29.1111317773701|128.922776167818|142.152584989914|24.587033631459|132.523734335195|0|||ExGal\n",
    "# sqlite> select distinct(area_id) from observations;\n",
    "# ExGal\n",
    "# NULL\n",
    "# sqlite> \n"
   ]
  }
 ],
 "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": "3.11.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}