interactive_select_DMD_pattern.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "62b7d242",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Created TAP+ (v1.2.1) - Connection:\n",
      "\tHost: gea.esac.esa.int\n",
      "\tUse HTTPS: True\n",
      "\tPort: 443\n",
      "\tSSL Port: 443\n",
      "Created TAP+ (v1.2.1) - Connection:\n",
      "\tHost: geadata.esac.esa.int\n",
      "\tUse HTTPS: True\n",
      "\tPort: 443\n",
      "\tSSL Port: 443\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import astropy.units as u\n",
    "from astropy import coordinates, units as u, wcs\n",
    "from astropy.io.votable import parse\n",
    "from astropy.table import Table, Column, QTable\n",
    "from astropy.io import fits\n",
    "from astropy.visualization import simple_norm\n",
    "\n",
    "\n",
    "from ipyaladin import Aladin\n",
    "from ipywidgets import Layout, Box, widgets\n",
    "import ipyaladin.aladin_widget as ipyal\n",
    "from ipywidgets import interact, interactive, fixed, interact_manual\n",
    "import ipywidgets as widgets\n",
    "\n",
    "from astroquery.gaia import Gaia\n",
    "from astroquery.vizier import Vizier\n",
    "\n",
    "from astropy.wcs import WCS\n",
    "from astropy.wcs.utils import skycoord_to_pixel\n",
    "from astropy.nddata import CCDData\n",
    "from astropy.coordinates import SkyCoord\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.gridspec import GridSpec\n",
    "from matplotlib.patches import Rectangle\n",
    "from matplotlib.patches import Polygon\n",
    "\n",
    "\n",
    "import importlib \n",
    "\n",
    "from skimage import transform\n",
    "\n",
    "\n",
    "%matplotlib notebook\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "506b36d8",
   "metadata": {},
   "source": [
    "# We want to create a DMD slit pattern for a certain FoV using GAIA data\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "55f900da",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import functions to do stuff\n",
    "import setup_obs_functions as sof"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fb18e775",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "coords= <SkyCoord (ICRS): (ra, dec) in deg\n",
      "    (92.03522917, 24.34865)>\n"
     ]
    }
   ],
   "source": [
    "# test coordinates are from a SAMI image I've been using\n",
    "\n",
    "RA = '06:08:8.455'                                                         \n",
    "DEC = '24:20:55.14'\n",
    "coords = SkyCoord(RA,DEC,unit=(u.hourangle,u.degree), frame='icrs')\n",
    "\n",
    "\n",
    "print(\"coords=\",coords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e3074b90",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "324cc133db1f47c3ab553567e35b83e6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Aladin(fov=0.06666666666666667, options=['allow_full_zoomout', 'coo_frame', 'fov', 'full_screen', 'log', 'over…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# General field of view we are looking for can be shown by aladin\n",
    "\n",
    "\n",
    "### NOTICE HOW THE IMAGES ARE FLIPPED IN X/RA ###\n",
    "\n",
    "fov = 4*u.arcmin\n",
    "aladin = ipyal.Aladin(target=coords.to_string(), fov=fov.to(u.degree).to_value(), survey='DSS')\n",
    "\n",
    "aladin"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "00abd23b",
   "metadata": {},
   "source": [
    "# Gaia query\n",
    "\n",
    "We have a field of stars on which we wish to center slits made by the DMD.\n",
    "\n",
    "We need Gaia astrometry for this, so select sets of stars to observe based on a Gaia query.\n",
    "Link to info about returned tables: https://gea.esac.esa.int/archive/documentation/GDR2/Gaia_archive/chap_datamodel/sec_dm_main_tables/ssec_dm_gaia_source.html\n",
    "\n",
    "Passbands:\\\n",
    "Full G-band (330–1050 nm) \t\\\n",
    "GBP-band (330–680 nm) - bluer \\\n",
    "GRP-band (630–1050 nm) - redder \n",
    "\n",
    "Blue-Red color column is 'bp_rp', larger number means redder (faint in blue, bright in red)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "832fa84f",
   "metadata": {},
   "outputs": [
    {
     "ename": "HTTPError",
     "evalue": "OK",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mHTTPError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/var/folders/7t/yf4p3jc93t5dhyzmjpcn802h0000gn/T/ipykernel_22916/870877700.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mimportlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msof\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;31m# GAIA query routine is in setup_obs_functions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mtable1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msof\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubmit_gaia_query\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoords\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/allSAMOS/Massimo_SAMOS_GUI/SAMOS_DMD_tools_massimo/SAMOS-DMD-Tools/setup_obs_functions.py\u001b[0m in \u001b[0;36msubmit_gaia_query\u001b[0;34m(coordinates, width, height, **kwargs)\u001b[0m\n\u001b[1;32m     48\u001b[0m         \u001b[0mheight\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mQuantity\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mu\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marcmin\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 50\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mGaia\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mquery_object_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcoordinate\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcoordinates\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mheight\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mheight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     51\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     52\u001b[0m         \u001b[0mpandacat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_pandas\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/envs/astroconda2/lib/python3.7/site-packages/astroquery/gaia/core.py\u001b[0m in \u001b[0;36mquery_object_async\u001b[0;34m(self, coordinate, radius, width, height, verbose, columns)\u001b[0m\n\u001b[1;32m    269\u001b[0m         \"\"\"\n\u001b[1;32m    270\u001b[0m         return self.__query_object(coordinate, radius, width, height,\n\u001b[0;32m--> 271\u001b[0;31m                                    async_job=True, verbose=verbose, columns=columns)\n\u001b[0m\u001b[1;32m    272\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    273\u001b[0m     def __cone_search(self, coordinate, radius, table_name=MAIN_GAIA_TABLE,\n",
      "\u001b[0;32m/opt/anaconda3/envs/astroconda2/lib/python3.7/site-packages/astroquery/gaia/core.py\u001b[0m in \u001b[0;36m__query_object\u001b[0;34m(self, coordinate, radius, width, height, async_job, verbose, columns)\u001b[0m\n\u001b[1;32m    211\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    212\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0masync_job\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 213\u001b[0;31m                 \u001b[0mjob\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlaunch_job_async\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverbose\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    214\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    215\u001b[0m                 \u001b[0mjob\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlaunch_job\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mquery\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mverbose\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/opt/anaconda3/envs/astroconda2/lib/python3.7/site-packages/astroquery/utils/tap/core.py\u001b[0m in \u001b[0;36mlaunch_job_async\u001b[0;34m(self, query, name, output_file, output_format, verbose, dump_to_file, background, upload_resource, upload_table_name, autorun)\u001b[0m\n\u001b[1;32m    422\u001b[0m                 self.__connHandler.dump_to_file(suitableOutputFile,\n\u001b[1;32m    423\u001b[0m                                                 response)\n\u001b[0;32m--> 424\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mrequests\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexceptions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mHTTPError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreason\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    425\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    426\u001b[0m             location = self.__connHandler.find_header(\n",
      "\u001b[0;31mHTTPError\u001b[0m: OK"
     ]
    }
   ],
   "source": [
    "importlib.reload(sof)\n",
    "# GAIA query routine is in setup_obs_functions\n",
    "table1 = sof.submit_gaia_query(coords)\n",
    "\n",
    "\n",
    "# Pick some criteria for targets so that we aren't overwhelmed\n",
    "pandacat = table1.to_pandas().drop(columns='index')\n",
    "criteria=(pandacat['phot_bp_mean_mag'] > 10) & (pandacat['phot_rp_mean_mag'] < 15)\n",
    "\n",
    "pandacat2 = pandacat[criteria].where(np.isnan(pandacat.parallax)==False).dropna(how='all').reset_index(drop=True)\n",
    "table2 = QTable.from_pandas(pandacat2, index=True)\n",
    "\n",
    "\n",
    "table2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cfc44304",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: Unit 'e' not supported by the VOUnit standard.  [astropy.units.format.vounit]\n",
      "WARNING: UnitsWarning: Unit 'Sun' not supported by the VOUnit standard. Did you mean uN? [astropy.units.format.vounit]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TableList with 9 tables:\n",
      "\t'0:I/324/igsl3' with 18 column(s) and 261 row(s) \n",
      "\t'1:I/337/gaia' with 14 column(s) and 222 row(s) \n",
      "\t'2:I/345/gaia2' with 32 column(s) and 255 row(s) \n",
      "\t'3:I/347/gaia2dis' with 9 column(s) and 212 row(s) \n",
      "\t'4:I/350/gaiaedr3' with 39 column(s) and 260 row(s) \n",
      "\t'5:I/352/gedr3dis' with 10 column(s) and 244 row(s) \n",
      "\t'6:VI/137/gum_mw' with 17 column(s) and 299 row(s) \n",
      "\t'7:VI/137/gum_gal' with 11 column(s) and 2 row(s) \n",
      "\t'8:VI/145/attitude' with 18 column(s) and 3 row(s) \n"
     ]
    },
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>ra</th>\n",
       "      <th>ra_error</th>\n",
       "      <th>dec</th>\n",
       "      <th>dec_error</th>\n",
       "      <th>DESIGNATION</th>\n",
       "      <th>parallax</th>\n",
       "      <th>parallax_error</th>\n",
       "      <th>pmRA</th>\n",
       "      <th>e_pmRA</th>\n",
       "      <th>pmDE</th>\n",
       "      <th>...</th>\n",
       "      <th>phot_rp_mean_mag</th>\n",
       "      <th>e_RPmag</th>\n",
       "      <th>BP-RP</th>\n",
       "      <th>RV</th>\n",
       "      <th>e_RV</th>\n",
       "      <th>Teff</th>\n",
       "      <th>AG</th>\n",
       "      <th>E_BP-RP_</th>\n",
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       "      <th>Lum</th>\n",
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       "      <th>0</th>\n",
       "      <td>92.063366</td>\n",
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       "      <td>0.8414</td>\n",
       "      <td>2.702</td>\n",
       "      <td>2.111</td>\n",
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       "      <td>19.3802</td>\n",
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       "      <td>0.5776</td>\n",
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       "      <th>2</th>\n",
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       "      <td>24.316703</td>\n",
       "      <td>0.7313</td>\n",
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       "      <td>1.1294</td>\n",
       "      <td>0.9072</td>\n",
       "      <td>2.455</td>\n",
       "      <td>1.794</td>\n",
       "      <td>-1.200</td>\n",
       "      <td>...</td>\n",
       "      <td>19.2254</td>\n",
       "      <td>0.0529</td>\n",
       "      <td>2.2676</td>\n",
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       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>92.063900</td>\n",
       "      <td>0.1465</td>\n",
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       "      <td>0.285</td>\n",
       "      <td>0.612</td>\n",
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       "      <td>17.2057</td>\n",
       "      <td>0.0092</td>\n",
       "      <td>1.1095</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>92.059589</td>\n",
       "      <td>0.3767</td>\n",
       "      <td>24.318097</td>\n",
       "      <td>0.3575</td>\n",
       "      <td>3426274976012779008</td>\n",
       "      <td>0.5562</td>\n",
       "      <td>0.4031</td>\n",
       "      <td>-0.930</td>\n",
       "      <td>0.717</td>\n",
       "      <td>-0.348</td>\n",
       "      <td>...</td>\n",
       "      <td>18.2780</td>\n",
       "      <td>0.0485</td>\n",
       "      <td>1.3611</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>250</th>\n",
       "      <td>92.025810</td>\n",
       "      <td>0.0326</td>\n",
       "      <td>24.377271</td>\n",
       "      <td>0.0288</td>\n",
       "      <td>3426281989697771648</td>\n",
       "      <td>0.9675</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>1.543</td>\n",
       "      <td>0.061</td>\n",
       "      <td>-0.042</td>\n",
       "      <td>...</td>\n",
       "      <td>14.3284</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>1.0582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5322.2</td>\n",
       "      <td>0.7065</td>\n",
       "      <td>0.3558</td>\n",
       "      <td>1.1</td>\n",
       "      <td>0.879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>251</th>\n",
       "      <td>92.028858</td>\n",
       "      <td>1.6539</td>\n",
       "      <td>24.372897</td>\n",
       "      <td>1.5234</td>\n",
       "      <td>3426281985404456192</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>18.8904</td>\n",
       "      <td>0.0710</td>\n",
       "      <td>2.1935</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>252</th>\n",
       "      <td>92.064649</td>\n",
       "      <td>9.4590</td>\n",
       "      <td>24.380417</td>\n",
       "      <td>8.2768</td>\n",
       "      <td>3426282054124172160</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>92.065280</td>\n",
       "      <td>0.1367</td>\n",
       "      <td>24.379481</td>\n",
       "      <td>0.1257</td>\n",
       "      <td>3426282058417231104</td>\n",
       "      <td>0.3421</td>\n",
       "      <td>0.1498</td>\n",
       "      <td>0.176</td>\n",
       "      <td>0.273</td>\n",
       "      <td>-0.628</td>\n",
       "      <td>...</td>\n",
       "      <td>17.1888</td>\n",
       "      <td>0.0187</td>\n",
       "      <td>1.1213</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>254</th>\n",
       "      <td>92.022655</td>\n",
       "      <td>0.6098</td>\n",
       "      <td>24.381853</td>\n",
       "      <td>0.5491</td>\n",
       "      <td>3426284940337035392</td>\n",
       "      <td>-0.6096</td>\n",
       "      <td>0.6072</td>\n",
       "      <td>0.726</td>\n",
       "      <td>1.191</td>\n",
       "      <td>-0.795</td>\n",
       "      <td>...</td>\n",
       "      <td>18.8242</td>\n",
       "      <td>0.0841</td>\n",
       "      <td>1.3422</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>255 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            ra  ra_error        dec  dec_error          DESIGNATION  parallax  \\\n",
       "0    92.063366    0.9510  24.334737     0.8349  3426275014669166336   -0.1893   \n",
       "1    92.059580    0.6417  24.318587     0.5776  3426274976018035456       NaN   \n",
       "2    92.066264    0.8201  24.316703     0.7313  3426274941658341504    1.1294   \n",
       "3    92.063900    0.1465  24.327438     0.1347  3426275010372538752    0.2982   \n",
       "4    92.059589    0.3767  24.318097     0.3575  3426274976012779008    0.5562   \n",
       "..         ...       ...        ...        ...                  ...       ...   \n",
       "250  92.025810    0.0326  24.377271     0.0288  3426281989697771648    0.9675   \n",
       "251  92.028858    1.6539  24.372897     1.5234  3426281985404456192       NaN   \n",
       "252  92.064649    9.4590  24.380417     8.2768  3426282054124172160       NaN   \n",
       "253  92.065280    0.1367  24.379481     0.1257  3426282058417231104    0.3421   \n",
       "254  92.022655    0.6098  24.381853     0.5491  3426284940337035392   -0.6096   \n",
       "\n",
       "     parallax_error   pmRA  e_pmRA   pmDE  ...  phot_rp_mean_mag  e_RPmag  \\\n",
       "0            0.8414  2.702   2.111 -1.249  ...           19.3802   0.0777   \n",
       "1               NaN    NaN     NaN    NaN  ...               NaN      NaN   \n",
       "2            0.9072  2.455   1.794 -1.200  ...           19.2254   0.0529   \n",
       "3            0.1385  1.060   0.285  0.612  ...           17.2057   0.0092   \n",
       "4            0.4031 -0.930   0.717 -0.348  ...           18.2780   0.0485   \n",
       "..              ...    ...     ...    ...  ...               ...      ...   \n",
       "250          0.0345  1.543   0.061 -0.042  ...           14.3284   0.0019   \n",
       "251             NaN    NaN     NaN    NaN  ...           18.8904   0.0710   \n",
       "252             NaN    NaN     NaN    NaN  ...               NaN      NaN   \n",
       "253          0.1498  0.176   0.273 -0.628  ...           17.1888   0.0187   \n",
       "254          0.6072  0.726   1.191 -0.795  ...           18.8242   0.0841   \n",
       "\n",
       "      BP-RP  RV  e_RV    Teff      AG  E_BP-RP_  Rad    Lum  \n",
       "0    1.2912 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "1       NaN NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "2    2.2676 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "3    1.1095 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "4    1.3611 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "..      ...  ..   ...     ...     ...       ...  ...    ...  \n",
       "250  1.0582 NaN   NaN  5322.2  0.7065    0.3558  1.1  0.879  \n",
       "251  2.1935 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "252     NaN NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "253  1.1213 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "254  1.3422 NaN   NaN     NaN     NaN       NaN  NaN    NaN  \n",
       "\n",
       "[255 rows x 32 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from astroquery.vizier import Vizier\n",
    "\n",
    "Vizier.ROW_LIMIT = -1\n",
    "viz_tables = Vizier.query_region(coordinates=coords, width = u.Quantity(4., u.arcmin),\n",
    "                        height = u.Quantity(4., u.arcmin), catalog=\"gaia\",)\n",
    "#viz_tables = Vizier.query_region(coordinates=\"83.632944 -5.443575\",height=height,width=width, \n",
    "#                                 catalog=\"2MASS\")\n",
    "\n",
    "print(viz_tables)\n",
    "table1 = viz_tables[2]\n",
    "#table1.sort(\"DEJ2000\")\n",
    "\n",
    "pandacat = table1.to_pandas()#.drop(columns='index')\n",
    "pandacat = pandacat.rename(columns={\"RA_ICRS\": \"ra\", \"e_RA_ICRS\": \"ra_error\",\n",
    "                                    \"DE_ICRS\":\"dec\", \"e_DE_ICRS\":\"dec_error\",\n",
    "                                   \"BPmag\":\"phot_bp_mean_mag\", \"RPmag\":\"phot_rp_mean_mag\",\n",
    "                                   \"Plx\": \"parallax\", \"e_Plx\":\"parallax_error\",\n",
    "                                   \"Source\":\"DESIGNATION\"})\n",
    "criteria=(pandacat['phot_bp_mean_mag'] > 10) & (pandacat['phot_rp_mean_mag'] < 15)\n",
    "pandacat2 = pandacat[criteria].where(np.isnan(pandacat.parallax)==False).dropna(how='all').reset_index(drop=True)\n",
    "table2 = QTable.from_pandas(pandacat2, index=True)\n",
    "\n",
    "pandacat"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9c31b7b",
   "metadata": {},
   "source": [
    "\n",
    "# Now show the selected Gaia stars in the aladin viewer.\n",
    "\n",
    "You can also change the center of our field of view and redo the query if you want.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c397495a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "99306b33f18d407399a24f7d8c608e52",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Aladin(fov=0.06, options=['allow_full_zoomout', 'coo_frame', 'fov', 'full_screen', 'log', 'overlay_survey', 'o…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import ipyaladin.aladin_widget as ipyal\n",
    "importlib.reload(ipyal)\n",
    "\n",
    "aladin = ipyal.Aladin(target=coords.to_string(), fov=0.06,survey='dss')\n",
    "\n",
    "\n",
    "aladin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "aa09f163",
   "metadata": {},
   "outputs": [],
   "source": [
    "#then overplot stars in our selected group\n",
    "\n",
    "#need to create new gaia table or else it won't show for some reason\n",
    "aladin_table = QTable(table2[['index','ra','ra_error','dec', 'dec_error', 'parallax', 'parallax_error']])\n",
    "\n",
    "aladin.add_table(aladin_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34637be6",
   "metadata": {},
   "source": [
    "# Find center coordinates of target field\n",
    "\n",
    "Now that we have selected some stars in the general FoV from our initial coordinates, find the center coordinates of these selected stars to get a target center for the CCD. FoV is ~3.1$'$=186$''$ according to SAMI manual.\n",
    "\n",
    "Generally, we want to know where we should point the telescope such that those pointing coordinates fall in the center of our CCD.\n",
    "\n",
    "Right now, I am assuming that the telescope pointing will correspond to the center of our CCD.  This will be adjusted/fine-tuned when we run tests at SOAR.\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3fe51095",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "92.03352487209 24.353934677035\n"
     ]
    }
   ],
   "source": [
    "RA_Center = (np.max(table2['ra'])-np.min(table2['ra'])) /2. + np.min(table2['ra'])\n",
    "\n",
    "\n",
    "DEC_Center = (np.max(table2['dec'])-np.min(table2['dec'])) /2. + np.min(table2['dec'])\n",
    "\n",
    "targ_center_coords = SkyCoord(RA_Center,DEC_Center,unit=u.deg,frame='icrs')\n",
    "print(RA_Center, DEC_Center)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "0afd4217",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "92.05852487209 92.00852487208999 24.378934677034998 24.328934677035\n"
     ]
    },
    {
     "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>ra</th>\n",
       "      <th>ra_error</th>\n",
       "      <th>dec</th>\n",
       "      <th>dec_error</th>\n",
       "      <th>DESIGNATION</th>\n",
       "      <th>parallax</th>\n",
       "      <th>parallax_error</th>\n",
       "      <th>pmRA</th>\n",
       "      <th>e_pmRA</th>\n",
       "      <th>pmDE</th>\n",
       "      <th>...</th>\n",
       "      <th>phot_rp_mean_mag</th>\n",
       "      <th>e_RPmag</th>\n",
       "      <th>BP-RP</th>\n",
       "      <th>RV</th>\n",
       "      <th>e_RV</th>\n",
       "      <th>Teff</th>\n",
       "      <th>AG</th>\n",
       "      <th>E_BP-RP_</th>\n",
       "      <th>Rad</th>\n",
       "      <th>Lum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>92.018255</td>\n",
       "      <td>0.0277</td>\n",
       "      <td>24.330598</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.8945</td>\n",
       "      <td>0.0306</td>\n",
       "      <td>1.491</td>\n",
       "      <td>0.053</td>\n",
       "      <td>-6.844</td>\n",
       "      <td>...</td>\n",
       "      <td>14.1452</td>\n",
       "      <td>0.0014</td>\n",
       "      <td>1.0449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5191.67</td>\n",
       "      <td>0.7640</td>\n",
       "      <td>0.3793</td>\n",
       "      <td>1.38</td>\n",
       "      <td>1.251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>92.041362</td>\n",
       "      <td>0.0334</td>\n",
       "      <td>24.351779</td>\n",
       "      <td>0.0303</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2972</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>-0.520</td>\n",
       "      <td>0.063</td>\n",
       "      <td>-7.936</td>\n",
       "      <td>...</td>\n",
       "      <td>14.3674</td>\n",
       "      <td>0.0016</td>\n",
       "      <td>1.4799</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4512.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.97</td>\n",
       "      <td>9.207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>92.041540</td>\n",
       "      <td>0.0783</td>\n",
       "      <td>24.350118</td>\n",
       "      <td>0.0707</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>1.2908</td>\n",
       "      <td>0.0872</td>\n",
       "      <td>-0.487</td>\n",
       "      <td>0.146</td>\n",
       "      <td>-9.876</td>\n",
       "      <td>...</td>\n",
       "      <td>13.6541</td>\n",
       "      <td>0.0032</td>\n",
       "      <td>1.3132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4881.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>92.043725</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>24.353994</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.4434</td>\n",
       "      <td>0.0255</td>\n",
       "      <td>0.682</td>\n",
       "      <td>0.046</td>\n",
       "      <td>-3.245</td>\n",
       "      <td>...</td>\n",
       "      <td>13.4870</td>\n",
       "      <td>0.0021</td>\n",
       "      <td>0.6710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6426.80</td>\n",
       "      <td>0.5480</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>2.57</td>\n",
       "      <td>10.188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>92.022504</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>24.362833</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2861</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>-0.424</td>\n",
       "      <td>0.040</td>\n",
       "      <td>-2.382</td>\n",
       "      <td>...</td>\n",
       "      <td>13.0238</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>0.4606</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7893.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.54</td>\n",
       "      <td>43.811</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>92.013527</td>\n",
       "      <td>0.0229</td>\n",
       "      <td>24.350910</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.1597</td>\n",
       "      <td>0.0253</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.043</td>\n",
       "      <td>-0.626</td>\n",
       "      <td>...</td>\n",
       "      <td>13.1843</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>0.2306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9235.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>92.030885</td>\n",
       "      <td>0.1641</td>\n",
       "      <td>24.365329</td>\n",
       "      <td>0.1505</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>3.5513</td>\n",
       "      <td>0.1795</td>\n",
       "      <td>-2.747</td>\n",
       "      <td>0.308</td>\n",
       "      <td>-1.035</td>\n",
       "      <td>...</td>\n",
       "      <td>14.1319</td>\n",
       "      <td>0.0024</td>\n",
       "      <td>1.6591</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4146.96</td>\n",
       "      <td>0.1890</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>92.023776</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>24.371611</td>\n",
       "      <td>0.0895</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2122</td>\n",
       "      <td>0.1116</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.185</td>\n",
       "      <td>-1.800</td>\n",
       "      <td>...</td>\n",
       "      <td>13.5245</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>1.4032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4519.31</td>\n",
       "      <td>0.4028</td>\n",
       "      <td>0.1918</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>92.050200</td>\n",
       "      <td>0.0408</td>\n",
       "      <td>24.357410</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>1.1278</td>\n",
       "      <td>0.0427</td>\n",
       "      <td>2.856</td>\n",
       "      <td>0.078</td>\n",
       "      <td>-3.185</td>\n",
       "      <td>...</td>\n",
       "      <td>14.8740</td>\n",
       "      <td>0.0063</td>\n",
       "      <td>1.2211</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4885.50</td>\n",
       "      <td>0.4933</td>\n",
       "      <td>0.2513</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.396</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>92.047229</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>24.356098</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.2032</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.508</td>\n",
       "      <td>0.078</td>\n",
       "      <td>-1.970</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9516</td>\n",
       "      <td>0.0034</td>\n",
       "      <td>0.8524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5543.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>92.025493</td>\n",
       "      <td>0.0245</td>\n",
       "      <td>24.374722</td>\n",
       "      <td>0.0215</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.3319</td>\n",
       "      <td>0.0257</td>\n",
       "      <td>0.844</td>\n",
       "      <td>0.045</td>\n",
       "      <td>-1.443</td>\n",
       "      <td>...</td>\n",
       "      <td>12.8985</td>\n",
       "      <td>0.0018</td>\n",
       "      <td>1.4139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4773.00</td>\n",
       "      <td>0.5260</td>\n",
       "      <td>0.2540</td>\n",
       "      <td>7.61</td>\n",
       "      <td>27.060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>92.035511</td>\n",
       "      <td>0.0413</td>\n",
       "      <td>24.373138</td>\n",
       "      <td>0.0376</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.3276</td>\n",
       "      <td>0.0448</td>\n",
       "      <td>0.481</td>\n",
       "      <td>0.077</td>\n",
       "      <td>-2.304</td>\n",
       "      <td>...</td>\n",
       "      <td>14.9465</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>0.7895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5805.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>92.041283</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>24.360133</td>\n",
       "      <td>0.2472</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>-0.2532</td>\n",
       "      <td>0.3066</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.525</td>\n",
       "      <td>0.191</td>\n",
       "      <td>...</td>\n",
       "      <td>14.1988</td>\n",
       "      <td>0.0015</td>\n",
       "      <td>1.0731</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5050.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>92.025810</td>\n",
       "      <td>0.0326</td>\n",
       "      <td>24.377271</td>\n",
       "      <td>0.0288</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.9675</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>1.543</td>\n",
       "      <td>0.061</td>\n",
       "      <td>-0.042</td>\n",
       "      <td>...</td>\n",
       "      <td>14.3284</td>\n",
       "      <td>0.0019</td>\n",
       "      <td>1.0582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5322.20</td>\n",
       "      <td>0.7065</td>\n",
       "      <td>0.3558</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.879</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ra  ra_error        dec  dec_error   DESIGNATION  parallax  \\\n",
       "0   92.018255    0.0277  24.330598     0.0249  3.426276e+18    0.8945   \n",
       "1   92.041362    0.0334  24.351779     0.0303  3.426276e+18    0.2972   \n",
       "2   92.041540    0.0783  24.350118     0.0707  3.426276e+18    1.2908   \n",
       "3   92.043725    0.0244  24.353994     0.0218  3.426276e+18    0.4434   \n",
       "4   92.022504    0.0204  24.362833     0.0181  3.426276e+18    0.2861   \n",
       "5   92.013527    0.0229  24.350910     0.0204  3.426276e+18    0.1597   \n",
       "6   92.030885    0.1641  24.365329     0.1505  3.426276e+18    3.5513   \n",
       "7   92.023776    0.1003  24.371611     0.0895  3.426276e+18    0.2122   \n",
       "8   92.050200    0.0408  24.357410     0.0368  3.426282e+18    1.1278   \n",
       "9   92.047229    0.0394  24.356098     0.0356  3.426282e+18    0.2032   \n",
       "10  92.025493    0.0245  24.374722     0.0215  3.426282e+18    0.3319   \n",
       "11  92.035511    0.0413  24.373138     0.0376  3.426282e+18    0.3276   \n",
       "12  92.041283    0.2605  24.360133     0.2472  3.426282e+18   -0.2532   \n",
       "13  92.025810    0.0326  24.377271     0.0288  3.426282e+18    0.9675   \n",
       "\n",
       "    parallax_error   pmRA  e_pmRA   pmDE  ...  phot_rp_mean_mag  e_RPmag  \\\n",
       "0           0.0306  1.491   0.053 -6.844  ...           14.1452   0.0014   \n",
       "1           0.0356 -0.520   0.063 -7.936  ...           14.3674   0.0016   \n",
       "2           0.0872 -0.487   0.146 -9.876  ...           13.6541   0.0032   \n",
       "3           0.0255  0.682   0.046 -3.245  ...           13.4870   0.0021   \n",
       "4           0.0224 -0.424   0.040 -2.382  ...           13.0238   0.0025   \n",
       "5           0.0253  0.072   0.043 -0.626  ...           13.1843   0.0026   \n",
       "6           0.1795 -2.747   0.308 -1.035  ...           14.1319   0.0024   \n",
       "7           0.1116  0.175   0.185 -1.800  ...           13.5245   0.0015   \n",
       "8           0.0427  2.856   0.078 -3.185  ...           14.8740   0.0063   \n",
       "9           0.0416  0.508   0.078 -1.970  ...           14.9516   0.0034   \n",
       "10          0.0257  0.844   0.045 -1.443  ...           12.8985   0.0018   \n",
       "11          0.0448  0.481   0.077 -2.304  ...           14.9465   0.0020   \n",
       "12          0.3066  0.639   0.525  0.191  ...           14.1988   0.0015   \n",
       "13          0.0345  1.543   0.061 -0.042  ...           14.3284   0.0019   \n",
       "\n",
       "     BP-RP  RV  e_RV     Teff      AG  E_BP-RP_   Rad     Lum  \n",
       "0   1.0449 NaN   NaN  5191.67  0.7640    0.3793  1.38   1.251  \n",
       "1   1.4799 NaN   NaN  4512.18     NaN       NaN  4.97   9.207  \n",
       "2   1.3132 NaN   NaN  4881.16     NaN       NaN  1.33   0.900  \n",
       "3   0.6710 NaN   NaN  6426.80  0.5480    0.2280  2.57  10.188  \n",
       "4   0.4606 NaN   NaN  7893.67     NaN       NaN  3.54  43.811  \n",
       "5   0.2306 NaN   NaN  9235.00     NaN       NaN   NaN     NaN  \n",
       "6   1.6591 NaN   NaN  4146.96  0.1890    0.0990  0.57   0.088  \n",
       "7   1.4032 NaN   NaN  4519.31  0.4028    0.1918   NaN     NaN  \n",
       "8   1.2211 NaN   NaN  4885.50  0.4933    0.2513  0.88   0.396  \n",
       "9   0.8524 NaN   NaN  5543.66     NaN       NaN   NaN     NaN  \n",
       "10  1.4139 NaN   NaN  4773.00  0.5260    0.2540  7.61  27.060  \n",
       "11  0.7895 NaN   NaN  5805.57     NaN       NaN   NaN     NaN  \n",
       "12  1.0731 NaN   NaN  5050.11     NaN       NaN   NaN     NaN  \n",
       "13  1.0582 NaN   NaN  5322.20  0.7065    0.3558  1.10   0.879  \n",
       "\n",
       "[14 rows x 32 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# From these center coordinates, we want to get the edges of the ~3' x 3' field of view, since not all of the \n",
    "# selected stars will be within that frame.\n",
    "\n",
    "RA_max = RA_Center + 1.5/60.  # 1.5' is half of 3' (!)\n",
    "RA_min = RA_Center - 1.5/60. \n",
    "if DEC_Center >= 0:\n",
    "    DEC_max = DEC_Center + 1.5/60.  \n",
    "    DEC_min = DEC_Center - 1.5/60.\n",
    "else:\n",
    "    DEC_min = -(-DEC_Center + 1.5/60.)  \n",
    "    DEC_max = -(-DEC_Center - 1.5/60.)\n",
    "\n",
    "\n",
    "print(RA_max,RA_min,DEC_max,DEC_min)\n",
    "\n",
    "# Want to make sure selected stars are not within ~5 arcsec of the edges\n",
    "\n",
    "edge_deg = (5.*u.arcsec).to(u.deg).value\n",
    "\n",
    "\n",
    "finaltable = table2[(table2['ra']>RA_min+edge_deg) \\\n",
    "                            & (table2['ra']<RA_max-edge_deg) \\\n",
    "                            & (table2['dec']>DEC_min+edge_deg) & (table2['dec']<DEC_max-edge_deg) ]\n",
    "\n",
    "finaldf = finaltable.to_pandas().drop(columns='index')\n",
    "len(finaltable)\n",
    "finaldf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "643d0978",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "92.03352487209 24.353934677035\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "WCS Keywords\n",
       "\n",
       "Number of WCS axes: 2\n",
       "CTYPE : 'RA---TAN'  'DEC--TAN'  \n",
       "CRVAL : 92.03352487209  24.353934677035  \n",
       "CRPIX : 540.0  540.0  \n",
       "CD1_1 CD1_2  : -4.7762345679012e-05  0.0  \n",
       "CD2_1 CD2_2  : -0.0  4.77623456790123e-05  \n",
       "NAXIS : 1080  1080"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a new WCS, but use the DMD scalings/rotations\n",
    "\n",
    "DMD_Scale = (3.095*60)/1080\n",
    "crmirror1 = 540  # center x of 1080x1080 DMD array\n",
    "# really the array is 2048x1080 but we'll restrict it to mirrors within the FoV)\n",
    "crmirror2 = 540 # center y of 1080x1080 DMD array\n",
    "\n",
    "dmd_wcs = sof.create_wcs(pixscale1=DMD_Scale,pixscale2=DMD_Scale, pos_angle=0., naxis1=1080, naxis2=1080,\n",
    "                     crval1=RA_Center, crval2=DEC_Center, crpix1=crmirror1, crpix2=crmirror2)\n",
    "\n",
    "\n",
    "print(RA_Center, DEC_Center)\n",
    "dmd_wcs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "db734110",
   "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>ra</th>\n",
       "      <th>ra_error</th>\n",
       "      <th>dec</th>\n",
       "      <th>dec_error</th>\n",
       "      <th>DESIGNATION</th>\n",
       "      <th>parallax</th>\n",
       "      <th>parallax_error</th>\n",
       "      <th>pmRA</th>\n",
       "      <th>e_pmRA</th>\n",
       "      <th>pmDE</th>\n",
       "      <th>...</th>\n",
       "      <th>BP-RP</th>\n",
       "      <th>RV</th>\n",
       "      <th>e_RV</th>\n",
       "      <th>Teff</th>\n",
       "      <th>AG</th>\n",
       "      <th>E_BP-RP_</th>\n",
       "      <th>Rad</th>\n",
       "      <th>Lum</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>92.018255</td>\n",
       "      <td>0.0277</td>\n",
       "      <td>24.330598</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.8945</td>\n",
       "      <td>0.0306</td>\n",
       "      <td>1.491</td>\n",
       "      <td>0.053</td>\n",
       "      <td>-6.844</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5191.67</td>\n",
       "      <td>0.7640</td>\n",
       "      <td>0.3793</td>\n",
       "      <td>1.38</td>\n",
       "      <td>1.251</td>\n",
       "      <td>830.311388</td>\n",
       "      <td>50.420097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>92.041362</td>\n",
       "      <td>0.0334</td>\n",
       "      <td>24.351779</td>\n",
       "      <td>0.0303</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2972</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>-0.520</td>\n",
       "      <td>0.063</td>\n",
       "      <td>-7.936</td>\n",
       "      <td>...</td>\n",
       "      <td>1.4799</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4512.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.97</td>\n",
       "      <td>9.207</td>\n",
       "      <td>389.511856</td>\n",
       "      <td>493.867550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>92.041540</td>\n",
       "      <td>0.0783</td>\n",
       "      <td>24.350118</td>\n",
       "      <td>0.0707</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>1.2908</td>\n",
       "      <td>0.0872</td>\n",
       "      <td>-0.487</td>\n",
       "      <td>0.146</td>\n",
       "      <td>-9.876</td>\n",
       "      <td>...</td>\n",
       "      <td>1.3132</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4881.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.900</td>\n",
       "      <td>386.121700</td>\n",
       "      <td>459.095856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>92.043725</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>24.353994</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.4434</td>\n",
       "      <td>0.0255</td>\n",
       "      <td>0.682</td>\n",
       "      <td>0.046</td>\n",
       "      <td>-3.245</td>\n",
       "      <td>...</td>\n",
       "      <td>0.6710</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6426.80</td>\n",
       "      <td>0.5480</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>2.57</td>\n",
       "      <td>10.188</td>\n",
       "      <td>344.435441</td>\n",
       "      <td>540.259272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>92.022504</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>24.362833</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2861</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>-0.424</td>\n",
       "      <td>0.040</td>\n",
       "      <td>-2.382</td>\n",
       "      <td>...</td>\n",
       "      <td>0.4606</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7893.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.54</td>\n",
       "      <td>43.811</td>\n",
       "      <td>749.193519</td>\n",
       "      <td>725.316687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>92.013527</td>\n",
       "      <td>0.0229</td>\n",
       "      <td>24.350910</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.1597</td>\n",
       "      <td>0.0253</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.043</td>\n",
       "      <td>-0.626</td>\n",
       "      <td>...</td>\n",
       "      <td>0.2306</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9235.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>920.442011</td>\n",
       "      <td>475.706055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>92.030885</td>\n",
       "      <td>0.1641</td>\n",
       "      <td>24.365329</td>\n",
       "      <td>0.1505</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>3.5513</td>\n",
       "      <td>0.1795</td>\n",
       "      <td>-2.747</td>\n",
       "      <td>0.308</td>\n",
       "      <td>-1.035</td>\n",
       "      <td>...</td>\n",
       "      <td>1.6591</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4146.96</td>\n",
       "      <td>0.1890</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.088</td>\n",
       "      <td>589.341478</td>\n",
       "      <td>777.555619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>92.023776</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>24.371611</td>\n",
       "      <td>0.0895</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2122</td>\n",
       "      <td>0.1116</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.185</td>\n",
       "      <td>-1.800</td>\n",
       "      <td>...</td>\n",
       "      <td>1.4032</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4519.31</td>\n",
       "      <td>0.4028</td>\n",
       "      <td>0.1918</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>724.928818</td>\n",
       "      <td>909.093181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>92.050200</td>\n",
       "      <td>0.0408</td>\n",
       "      <td>24.357410</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>1.1278</td>\n",
       "      <td>0.0427</td>\n",
       "      <td>2.856</td>\n",
       "      <td>0.078</td>\n",
       "      <td>-3.185</td>\n",
       "      <td>...</td>\n",
       "      <td>1.2211</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4885.50</td>\n",
       "      <td>0.4933</td>\n",
       "      <td>0.2513</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.396</td>\n",
       "      <td>220.956341</td>\n",
       "      <td>611.776552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>92.047229</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>24.356098</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.2032</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.508</td>\n",
       "      <td>0.078</td>\n",
       "      <td>-1.970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.8524</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5543.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277.610042</td>\n",
       "      <td>584.309080</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>92.025493</td>\n",
       "      <td>0.0245</td>\n",
       "      <td>24.374722</td>\n",
       "      <td>0.0215</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.3319</td>\n",
       "      <td>0.0257</td>\n",
       "      <td>0.844</td>\n",
       "      <td>0.045</td>\n",
       "      <td>-1.443</td>\n",
       "      <td>...</td>\n",
       "      <td>1.4139</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4773.00</td>\n",
       "      <td>0.5260</td>\n",
       "      <td>0.2540</td>\n",
       "      <td>7.61</td>\n",
       "      <td>27.060</td>\n",
       "      <td>692.171754</td>\n",
       "      <td>974.220339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>92.035511</td>\n",
       "      <td>0.0413</td>\n",
       "      <td>24.373138</td>\n",
       "      <td>0.0376</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.3276</td>\n",
       "      <td>0.0448</td>\n",
       "      <td>0.481</td>\n",
       "      <td>0.077</td>\n",
       "      <td>-2.304</td>\n",
       "      <td>...</td>\n",
       "      <td>0.7895</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5805.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>501.115726</td>\n",
       "      <td>941.063051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>92.041283</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>24.360133</td>\n",
       "      <td>0.2472</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>-0.2532</td>\n",
       "      <td>0.3066</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.525</td>\n",
       "      <td>0.191</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0731</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5050.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>391.033659</td>\n",
       "      <td>668.770988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>92.025810</td>\n",
       "      <td>0.0326</td>\n",
       "      <td>24.377271</td>\n",
       "      <td>0.0288</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.9675</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>1.543</td>\n",
       "      <td>0.061</td>\n",
       "      <td>-0.042</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0582</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5322.20</td>\n",
       "      <td>0.7065</td>\n",
       "      <td>0.3558</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.879</td>\n",
       "      <td>686.133173</td>\n",
       "      <td>1027.599985</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14 rows × 34 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ra  ra_error        dec  dec_error   DESIGNATION  parallax  \\\n",
       "0   92.018255    0.0277  24.330598     0.0249  3.426276e+18    0.8945   \n",
       "1   92.041362    0.0334  24.351779     0.0303  3.426276e+18    0.2972   \n",
       "2   92.041540    0.0783  24.350118     0.0707  3.426276e+18    1.2908   \n",
       "3   92.043725    0.0244  24.353994     0.0218  3.426276e+18    0.4434   \n",
       "4   92.022504    0.0204  24.362833     0.0181  3.426276e+18    0.2861   \n",
       "5   92.013527    0.0229  24.350910     0.0204  3.426276e+18    0.1597   \n",
       "6   92.030885    0.1641  24.365329     0.1505  3.426276e+18    3.5513   \n",
       "7   92.023776    0.1003  24.371611     0.0895  3.426276e+18    0.2122   \n",
       "8   92.050200    0.0408  24.357410     0.0368  3.426282e+18    1.1278   \n",
       "9   92.047229    0.0394  24.356098     0.0356  3.426282e+18    0.2032   \n",
       "10  92.025493    0.0245  24.374722     0.0215  3.426282e+18    0.3319   \n",
       "11  92.035511    0.0413  24.373138     0.0376  3.426282e+18    0.3276   \n",
       "12  92.041283    0.2605  24.360133     0.2472  3.426282e+18   -0.2532   \n",
       "13  92.025810    0.0326  24.377271     0.0288  3.426282e+18    0.9675   \n",
       "\n",
       "    parallax_error   pmRA  e_pmRA   pmDE  ...   BP-RP  RV  e_RV     Teff  \\\n",
       "0           0.0306  1.491   0.053 -6.844  ...  1.0449 NaN   NaN  5191.67   \n",
       "1           0.0356 -0.520   0.063 -7.936  ...  1.4799 NaN   NaN  4512.18   \n",
       "2           0.0872 -0.487   0.146 -9.876  ...  1.3132 NaN   NaN  4881.16   \n",
       "3           0.0255  0.682   0.046 -3.245  ...  0.6710 NaN   NaN  6426.80   \n",
       "4           0.0224 -0.424   0.040 -2.382  ...  0.4606 NaN   NaN  7893.67   \n",
       "5           0.0253  0.072   0.043 -0.626  ...  0.2306 NaN   NaN  9235.00   \n",
       "6           0.1795 -2.747   0.308 -1.035  ...  1.6591 NaN   NaN  4146.96   \n",
       "7           0.1116  0.175   0.185 -1.800  ...  1.4032 NaN   NaN  4519.31   \n",
       "8           0.0427  2.856   0.078 -3.185  ...  1.2211 NaN   NaN  4885.50   \n",
       "9           0.0416  0.508   0.078 -1.970  ...  0.8524 NaN   NaN  5543.66   \n",
       "10          0.0257  0.844   0.045 -1.443  ...  1.4139 NaN   NaN  4773.00   \n",
       "11          0.0448  0.481   0.077 -2.304  ...  0.7895 NaN   NaN  5805.57   \n",
       "12          0.3066  0.639   0.525  0.191  ...  1.0731 NaN   NaN  5050.11   \n",
       "13          0.0345  1.543   0.061 -0.042  ...  1.0582 NaN   NaN  5322.20   \n",
       "\n",
       "        AG  E_BP-RP_   Rad     Lum           x            y  \n",
       "0   0.7640    0.3793  1.38   1.251  830.311388    50.420097  \n",
       "1      NaN       NaN  4.97   9.207  389.511856   493.867550  \n",
       "2      NaN       NaN  1.33   0.900  386.121700   459.095856  \n",
       "3   0.5480    0.2280  2.57  10.188  344.435441   540.259272  \n",
       "4      NaN       NaN  3.54  43.811  749.193519   725.316687  \n",
       "5      NaN       NaN   NaN     NaN  920.442011   475.706055  \n",
       "6   0.1890    0.0990  0.57   0.088  589.341478   777.555619  \n",
       "7   0.4028    0.1918   NaN     NaN  724.928818   909.093181  \n",
       "8   0.4933    0.2513  0.88   0.396  220.956341   611.776552  \n",
       "9      NaN       NaN   NaN     NaN  277.610042   584.309080  \n",
       "10  0.5260    0.2540  7.61  27.060  692.171754   974.220339  \n",
       "11     NaN       NaN   NaN     NaN  501.115726   941.063051  \n",
       "12     NaN       NaN   NaN     NaN  391.033659   668.770988  \n",
       "13  0.7065    0.3558  1.10   0.879  686.133173  1027.599985  \n",
       "\n",
       "[14 rows x 34 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We can now convert the sky coordinates RA and DEC to pixel coordinates using the WCS\n",
    "\n",
    "pixcoords = np.asarray([skycoord_to_pixel(wcs=dmd_wcs,\n",
    "                                    coords= SkyCoord(finaldf.loc[i,\"ra\"],\n",
    "                                    finaldf.loc[i,\"dec\"], unit=\"deg\")) for i in finaldf.index])\n",
    "\n",
    "finaldf[\"x\"] = pixcoords[:,0]\n",
    "finaldf[\"y\"] = pixcoords[:,1]\n",
    "\n",
    "finaldf"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d52d7d7f",
   "metadata": {},
   "source": [
    "# Download an image from the HiPS server \n",
    "\n",
    "Image should have the same size/scalings/wcs as DMD so we can select stars and see what the pattern will look like."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8135756d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "http://alasky.u-strasbg.fr/hips-image-services/hips2fits?hips=2MASS%2FJ&ra=92.03352487209&dec=24.353934677035&fov=0.051583333333333335&projection=TAN&width=1080&height=1080\n",
      "Filename: /Users/danakoeppe/.astropy/cache/download/url/009fddf57e0682e8a3b070c984d248b8/contents\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU      24   (1080, 1080)   float32   \n",
      "Strasbourg_DMDscale_92.03352487209_24.353934677035.fits\n",
      "scale of DSS image:  0.1719444560583132 \n",
      "\n"
     ]
    }
   ],
   "source": [
    "from urllib.parse import urlencode\n",
    "\n",
    "#get image with DMD params to see how we can get mirrors to match up with stars\n",
    "\n",
    "hips = '2MASS/J'#'CDS/P/DSS2/red'\n",
    "#result = hips2fits.query_with_wcs(\n",
    "#   hips=hips,\n",
    "#   wcs=w,\n",
    "#   get_query_payload=False,\n",
    "#   format='fits',\n",
    "#   min_cut=0.5,\n",
    "#   max_cut=99.5,\n",
    "#   cmap=Colormap('viridis'),\n",
    "#)\n",
    "query_params = { \n",
    "             'hips': '2MASS/J',\n",
    "#             'wcs': w, \n",
    "             'ra': RA_Center, \n",
    "             'dec': DEC_Center,\n",
    "             'fov': (3.095 * u.arcmin).to(u.deg).value, \n",
    "             'projection': 'TAN',\n",
    "             'width': 1080, \n",
    "             'height': 1080 \n",
    "             }                                                                                               \n",
    "url = f'http://alasky.u-strasbg.fr/hips-image-services/hips2fits?{urlencode(query_params)}' \n",
    "print(url)\n",
    "hdul = fits.open(url)\n",
    "hdul.info()\n",
    "header = hdul[0].header\n",
    "image = hdul[0].data\n",
    "\n",
    "#hdul[0].data = np.fliplr(hdul[0].data)\n",
    "#to save\n",
    "filename  = \"Strasbourg_DMDscale_\"+str(np.round(RA_Center,13))+\"_\"+str(np.round(DEC_Center,13))+\".fits\"\n",
    "hdul.writeto(filename,overwrite=True)\n",
    "print(filename)\n",
    "#print(header)\n",
    "print('scale of DSS image: ',header['CDELT2']*3600.,'\\n')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8a8bc96",
   "metadata": {},
   "source": [
    "# Pick out slits interactively\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "aa54b623",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "importlib.reload(sof)\n",
    "\n",
    "# testing slit iterator \n",
    "\n",
    "\n",
    "fig1, ax1 = plt.subplots()\n",
    "fig1.figsize=(8,8)\n",
    "\n",
    "hipsnorm = simple_norm(data=image, stretch='log')\n",
    "\n",
    "im1 = ax1.imshow(image, origin='lower',cmap='gray',norm=hipsnorm,)#extent=[-512, 512, -512, 512])\n",
    "\n",
    "\n",
    "SlIter = sof.JupyterSlitSizeIterator(df=finaldf, fig=fig1, ax=ax1, imshape=image.shape)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a5bdc805",
   "metadata": {},
   "outputs": [],
   "source": [
    "# can also set the slit size manually instead of using the slider\n",
    "\n",
    "SlIter.x_slider.set_val(20)\n",
    "SlIter.y_slider.set_val(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "141fe7fe",
   "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>ra</th>\n",
       "      <th>ra_error</th>\n",
       "      <th>dec</th>\n",
       "      <th>dec_error</th>\n",
       "      <th>DESIGNATION</th>\n",
       "      <th>parallax</th>\n",
       "      <th>parallax_error</th>\n",
       "      <th>pmRA</th>\n",
       "      <th>e_pmRA</th>\n",
       "      <th>pmDE</th>\n",
       "      <th>...</th>\n",
       "      <th>e_RV</th>\n",
       "      <th>Teff</th>\n",
       "      <th>AG</th>\n",
       "      <th>E_BP-RP_</th>\n",
       "      <th>Rad</th>\n",
       "      <th>Lum</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>dx</th>\n",
       "      <th>dy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>92.050200</td>\n",
       "      <td>0.0408</td>\n",
       "      <td>24.357410</td>\n",
       "      <td>0.0368</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>1.1278</td>\n",
       "      <td>0.0427</td>\n",
       "      <td>2.856</td>\n",
       "      <td>0.078</td>\n",
       "      <td>-3.185</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4885.50</td>\n",
       "      <td>0.4933</td>\n",
       "      <td>0.2513</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.396</td>\n",
       "      <td>220.956341</td>\n",
       "      <td>611.776552</td>\n",
       "      <td>86</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>92.047229</td>\n",
       "      <td>0.0394</td>\n",
       "      <td>24.356098</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.2032</td>\n",
       "      <td>0.0416</td>\n",
       "      <td>0.508</td>\n",
       "      <td>0.078</td>\n",
       "      <td>-1.970</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5543.66</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>277.610042</td>\n",
       "      <td>584.309080</td>\n",
       "      <td>56</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>92.043725</td>\n",
       "      <td>0.0244</td>\n",
       "      <td>24.353994</td>\n",
       "      <td>0.0218</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.4434</td>\n",
       "      <td>0.0255</td>\n",
       "      <td>0.682</td>\n",
       "      <td>0.046</td>\n",
       "      <td>-3.245</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6426.80</td>\n",
       "      <td>0.5480</td>\n",
       "      <td>0.2280</td>\n",
       "      <td>2.57</td>\n",
       "      <td>10.188</td>\n",
       "      <td>344.435441</td>\n",
       "      <td>540.259272</td>\n",
       "      <td>59</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>92.041540</td>\n",
       "      <td>0.0783</td>\n",
       "      <td>24.350118</td>\n",
       "      <td>0.0707</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>1.2908</td>\n",
       "      <td>0.0872</td>\n",
       "      <td>-0.487</td>\n",
       "      <td>0.146</td>\n",
       "      <td>-9.876</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4881.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.900</td>\n",
       "      <td>386.121700</td>\n",
       "      <td>459.095856</td>\n",
       "      <td>64</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>92.041362</td>\n",
       "      <td>0.0334</td>\n",
       "      <td>24.351779</td>\n",
       "      <td>0.0303</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2972</td>\n",
       "      <td>0.0356</td>\n",
       "      <td>-0.520</td>\n",
       "      <td>0.063</td>\n",
       "      <td>-7.936</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4512.18</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4.97</td>\n",
       "      <td>9.207</td>\n",
       "      <td>389.511856</td>\n",
       "      <td>493.867550</td>\n",
       "      <td>63</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>92.041283</td>\n",
       "      <td>0.2605</td>\n",
       "      <td>24.360133</td>\n",
       "      <td>0.2472</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>-0.2532</td>\n",
       "      <td>0.3066</td>\n",
       "      <td>0.639</td>\n",
       "      <td>0.525</td>\n",
       "      <td>0.191</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5050.11</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>391.033659</td>\n",
       "      <td>668.770988</td>\n",
       "      <td>58</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>92.035511</td>\n",
       "      <td>0.0413</td>\n",
       "      <td>24.373138</td>\n",
       "      <td>0.0376</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.3276</td>\n",
       "      <td>0.0448</td>\n",
       "      <td>0.481</td>\n",
       "      <td>0.077</td>\n",
       "      <td>-2.304</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5805.57</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>501.115726</td>\n",
       "      <td>941.063051</td>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>92.030885</td>\n",
       "      <td>0.1641</td>\n",
       "      <td>24.365329</td>\n",
       "      <td>0.1505</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>3.5513</td>\n",
       "      <td>0.1795</td>\n",
       "      <td>-2.747</td>\n",
       "      <td>0.308</td>\n",
       "      <td>-1.035</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4146.96</td>\n",
       "      <td>0.1890</td>\n",
       "      <td>0.0990</td>\n",
       "      <td>0.57</td>\n",
       "      <td>0.088</td>\n",
       "      <td>589.341478</td>\n",
       "      <td>777.555619</td>\n",
       "      <td>50</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>92.025810</td>\n",
       "      <td>0.0326</td>\n",
       "      <td>24.377271</td>\n",
       "      <td>0.0288</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.9675</td>\n",
       "      <td>0.0345</td>\n",
       "      <td>1.543</td>\n",
       "      <td>0.061</td>\n",
       "      <td>-0.042</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5322.20</td>\n",
       "      <td>0.7065</td>\n",
       "      <td>0.3558</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.879</td>\n",
       "      <td>686.133173</td>\n",
       "      <td>1027.599985</td>\n",
       "      <td>68</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>92.025493</td>\n",
       "      <td>0.0245</td>\n",
       "      <td>24.374722</td>\n",
       "      <td>0.0215</td>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>0.3319</td>\n",
       "      <td>0.0257</td>\n",
       "      <td>0.844</td>\n",
       "      <td>0.045</td>\n",
       "      <td>-1.443</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4773.00</td>\n",
       "      <td>0.5260</td>\n",
       "      <td>0.2540</td>\n",
       "      <td>7.61</td>\n",
       "      <td>27.060</td>\n",
       "      <td>692.171754</td>\n",
       "      <td>974.220339</td>\n",
       "      <td>65</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>92.023776</td>\n",
       "      <td>0.1003</td>\n",
       "      <td>24.371611</td>\n",
       "      <td>0.0895</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2122</td>\n",
       "      <td>0.1116</td>\n",
       "      <td>0.175</td>\n",
       "      <td>0.185</td>\n",
       "      <td>-1.800</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>4519.31</td>\n",
       "      <td>0.4028</td>\n",
       "      <td>0.1918</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>724.928818</td>\n",
       "      <td>909.093181</td>\n",
       "      <td>94</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>92.022504</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>24.362833</td>\n",
       "      <td>0.0181</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.2861</td>\n",
       "      <td>0.0224</td>\n",
       "      <td>-0.424</td>\n",
       "      <td>0.040</td>\n",
       "      <td>-2.382</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7893.67</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.54</td>\n",
       "      <td>43.811</td>\n",
       "      <td>749.193519</td>\n",
       "      <td>725.316687</td>\n",
       "      <td>61</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>92.018255</td>\n",
       "      <td>0.0277</td>\n",
       "      <td>24.330598</td>\n",
       "      <td>0.0249</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.8945</td>\n",
       "      <td>0.0306</td>\n",
       "      <td>1.491</td>\n",
       "      <td>0.053</td>\n",
       "      <td>-6.844</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5191.67</td>\n",
       "      <td>0.7640</td>\n",
       "      <td>0.3793</td>\n",
       "      <td>1.38</td>\n",
       "      <td>1.251</td>\n",
       "      <td>830.311388</td>\n",
       "      <td>50.420097</td>\n",
       "      <td>70</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>92.013527</td>\n",
       "      <td>0.0229</td>\n",
       "      <td>24.350910</td>\n",
       "      <td>0.0204</td>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>0.1597</td>\n",
       "      <td>0.0253</td>\n",
       "      <td>0.072</td>\n",
       "      <td>0.043</td>\n",
       "      <td>-0.626</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9235.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>920.442011</td>\n",
       "      <td>475.706055</td>\n",
       "      <td>72</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14 rows × 36 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           ra  ra_error        dec  dec_error   DESIGNATION  parallax  \\\n",
       "0   92.050200    0.0408  24.357410     0.0368  3.426282e+18    1.1278   \n",
       "1   92.047229    0.0394  24.356098     0.0356  3.426282e+18    0.2032   \n",
       "2   92.043725    0.0244  24.353994     0.0218  3.426276e+18    0.4434   \n",
       "3   92.041540    0.0783  24.350118     0.0707  3.426276e+18    1.2908   \n",
       "4   92.041362    0.0334  24.351779     0.0303  3.426276e+18    0.2972   \n",
       "5   92.041283    0.2605  24.360133     0.2472  3.426282e+18   -0.2532   \n",
       "6   92.035511    0.0413  24.373138     0.0376  3.426282e+18    0.3276   \n",
       "7   92.030885    0.1641  24.365329     0.1505  3.426276e+18    3.5513   \n",
       "8   92.025810    0.0326  24.377271     0.0288  3.426282e+18    0.9675   \n",
       "9   92.025493    0.0245  24.374722     0.0215  3.426282e+18    0.3319   \n",
       "10  92.023776    0.1003  24.371611     0.0895  3.426276e+18    0.2122   \n",
       "11  92.022504    0.0204  24.362833     0.0181  3.426276e+18    0.2861   \n",
       "12  92.018255    0.0277  24.330598     0.0249  3.426276e+18    0.8945   \n",
       "13  92.013527    0.0229  24.350910     0.0204  3.426276e+18    0.1597   \n",
       "\n",
       "    parallax_error   pmRA  e_pmRA   pmDE  ...  e_RV     Teff      AG  \\\n",
       "0           0.0427  2.856   0.078 -3.185  ...   NaN  4885.50  0.4933   \n",
       "1           0.0416  0.508   0.078 -1.970  ...   NaN  5543.66     NaN   \n",
       "2           0.0255  0.682   0.046 -3.245  ...   NaN  6426.80  0.5480   \n",
       "3           0.0872 -0.487   0.146 -9.876  ...   NaN  4881.16     NaN   \n",
       "4           0.0356 -0.520   0.063 -7.936  ...   NaN  4512.18     NaN   \n",
       "5           0.3066  0.639   0.525  0.191  ...   NaN  5050.11     NaN   \n",
       "6           0.0448  0.481   0.077 -2.304  ...   NaN  5805.57     NaN   \n",
       "7           0.1795 -2.747   0.308 -1.035  ...   NaN  4146.96  0.1890   \n",
       "8           0.0345  1.543   0.061 -0.042  ...   NaN  5322.20  0.7065   \n",
       "9           0.0257  0.844   0.045 -1.443  ...   NaN  4773.00  0.5260   \n",
       "10          0.1116  0.175   0.185 -1.800  ...   NaN  4519.31  0.4028   \n",
       "11          0.0224 -0.424   0.040 -2.382  ...   NaN  7893.67     NaN   \n",
       "12          0.0306  1.491   0.053 -6.844  ...   NaN  5191.67  0.7640   \n",
       "13          0.0253  0.072   0.043 -0.626  ...   NaN  9235.00     NaN   \n",
       "\n",
       "    E_BP-RP_   Rad     Lum           x            y  dx  dy  \n",
       "0     0.2513  0.88   0.396  220.956341   611.776552  86   3  \n",
       "1        NaN   NaN     NaN  277.610042   584.309080  56   3  \n",
       "2     0.2280  2.57  10.188  344.435441   540.259272  59   3  \n",
       "3        NaN  1.33   0.900  386.121700   459.095856  64   3  \n",
       "4        NaN  4.97   9.207  389.511856   493.867550  63   3  \n",
       "5        NaN   NaN     NaN  391.033659   668.770988  58   3  \n",
       "6        NaN   NaN     NaN  501.115726   941.063051  61   3  \n",
       "7     0.0990  0.57   0.088  589.341478   777.555619  50   3  \n",
       "8     0.3558  1.10   0.879  686.133173  1027.599985  68   3  \n",
       "9     0.2540  7.61  27.060  692.171754   974.220339  65   3  \n",
       "10    0.1918   NaN     NaN  724.928818   909.093181  94   3  \n",
       "11       NaN  3.54  43.811  749.193519   725.316687  61   3  \n",
       "12    0.3793  1.38   1.251  830.311388    50.420097  70   3  \n",
       "13       NaN   NaN     NaN  920.442011   475.706055  72   3  \n",
       "\n",
       "[14 rows x 36 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "SlIter.df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "f06c540c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accepting first target 0\n",
      "skipping target 1\n",
      "accepting target 2\n",
      "\n",
      "\n",
      "skipping target 3\n",
      "skipping target 4\n",
      "skipping target 5\n",
      "accepting target 6\n",
      "\n",
      "\n",
      "accepting target 7\n",
      "\n",
      "\n",
      "accepting target 8\n",
      "\n",
      "\n",
      "skipping target 9\n",
      "skipping target 10\n",
      "accepting target 11\n",
      "\n",
      "\n",
      "accepting target 12\n",
      "\n",
      "\n",
      "accepting target 13\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "importlib.reload(sof)\n",
    "\n",
    "DMDPattern, dmd_slits, good_index = \\\n",
    "                    sof.create_dmd_pattern_from_target_table(SlIter.df,wcs=dmd_wcs,\n",
    "                                                    ra_center=RA_Center,dec_center=DEC_Center,\n",
    "                                                    slit_xsize=SlIter.df.dx.values,slit_ysize=SlIter.df.dy.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cbb561e0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>target</th>\n",
       "      <th>ra</th>\n",
       "      <th>dec</th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>dx1</th>\n",
       "      <th>dy1</th>\n",
       "      <th>dx2</th>\n",
       "      <th>dy2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>92.050200</td>\n",
       "      <td>24.357410</td>\n",
       "      <td>220.956341</td>\n",
       "      <td>611.776552</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>92.043725</td>\n",
       "      <td>24.353994</td>\n",
       "      <td>344.435441</td>\n",
       "      <td>540.259272</td>\n",
       "      <td>29.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>29.5</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>92.035511</td>\n",
       "      <td>24.373138</td>\n",
       "      <td>501.115726</td>\n",
       "      <td>941.063051</td>\n",
       "      <td>30.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>30.5</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>92.030885</td>\n",
       "      <td>24.365329</td>\n",
       "      <td>589.341478</td>\n",
       "      <td>777.555619</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>25.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.426282e+18</td>\n",
       "      <td>92.025810</td>\n",
       "      <td>24.377271</td>\n",
       "      <td>686.133173</td>\n",
       "      <td>1027.599985</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>34.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>92.022504</td>\n",
       "      <td>24.362833</td>\n",
       "      <td>749.193519</td>\n",
       "      <td>725.316687</td>\n",
       "      <td>30.5</td>\n",
       "      <td>1.5</td>\n",
       "      <td>30.5</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>92.018255</td>\n",
       "      <td>24.330598</td>\n",
       "      <td>830.311388</td>\n",
       "      <td>50.420097</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.426276e+18</td>\n",
       "      <td>92.013527</td>\n",
       "      <td>24.350910</td>\n",
       "      <td>920.442011</td>\n",
       "      <td>475.706055</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>36.0</td>\n",
       "      <td>1.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         target         ra        dec           x            y   dx1  dy1  \\\n",
       "0  3.426282e+18  92.050200  24.357410  220.956341   611.776552  43.0  1.5   \n",
       "1  3.426276e+18  92.043725  24.353994  344.435441   540.259272  29.5  1.5   \n",
       "2  3.426282e+18  92.035511  24.373138  501.115726   941.063051  30.5  1.5   \n",
       "3  3.426276e+18  92.030885  24.365329  589.341478   777.555619  25.0  1.5   \n",
       "4  3.426282e+18  92.025810  24.377271  686.133173  1027.599985  34.0  1.5   \n",
       "5  3.426276e+18  92.022504  24.362833  749.193519   725.316687  30.5  1.5   \n",
       "6  3.426276e+18  92.018255  24.330598  830.311388    50.420097  35.0  1.5   \n",
       "7  3.426276e+18  92.013527  24.350910  920.442011   475.706055  36.0  1.5   \n",
       "\n",
       "    dx2  dy2  \n",
       "0  43.0  1.5  \n",
       "1  29.5  1.5  \n",
       "2  30.5  1.5  \n",
       "3  25.0  1.5  \n",
       "4  34.0  1.5  \n",
       "5  30.5  1.5  \n",
       "6  35.0  1.5  \n",
       "7  36.0  1.5  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DMDPattern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a89fae8a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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