Demo of astroplan for real-time observatory updates

astroplan_realtime_update.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# `astroplan`: Interactive observation status\n",
    "\n",
    "Design your own real time display built on [astroplan](http://astroplan.readthedocs.org/) and [astropy](http://astropy.readthedocs.org/)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "observatory_name = 'Palomar' # Must be in astroplan database\n",
    "target_names = ['Sextans A', 'VV124']    # Resolved with Sesame\n",
    "\n",
    "STRFTIME_FORMAT = '%Y-%m-%d %H:%M:%S' # Format for date/times"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Setup code (run this if you change the above)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from collections import OrderedDict\n",
    "from time import sleep\n",
    "\n",
    "import numpy as np\n",
    "import pytz\n",
    "\n",
    "import astropy.units as u\n",
    "from astropy.time import Time\n",
    "from astropy.coordinates import Angle\n",
    "\n",
    "from astroplan import FixedTarget, Observer\n",
    "from astroplan import plots as app\n",
    "\n",
    "from IPython import display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "from matplotlib import rcParams\n",
    "from matplotlib import style as mplstyle\n",
    "rcParams['axes.color_cycle'] = mplstyle.library['bmh']['axes.color_cycle']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "targets = [FixedTarget.from_name(target_name) for target_name in target_names]\n",
    "obs = Observer.at_site(observatory_name, timezone=pytz.timezone('US/Pacific'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def deltatime_to_str(dt, precision=0):   \n",
    "    dtsec = dt.to(u.second).value\n",
    "    isneg = dtsec < 0\n",
    "    dtsec = np.abs(dtsec)\n",
    "    \n",
    "    h = dtsec // 3600\n",
    "    m = (dtsec % 3600) // 60\n",
    "    s = (dtsec % 60)\n",
    "    \n",
    "    tofmt = '{0}{1:02.0f}:{2:02.0f}:{3:02.'+str(precision)+'f}'\n",
    "    return tofmt.format('-' if isneg else '+', h, m, s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def global_info_table(obs, currtime):        \n",
    "    globaldct = OrderedDict()\n",
    "    \n",
    "    globaldct['Observatory'] = obs.name\n",
    "    globaldct['UTC'] = currtime.utc.datetime.strftime(STRFTIME_FORMAT)\n",
    "    if obs.timezone.zone != 'UTC':\n",
    "        globaldct['Local Time'] = obs.astropy_time_to_datetime(currtime).strftime(STRFTIME_FORMAT)\n",
    "    globaldct['LST'] = '$' + obs.local_sidereal_time(currtime).to_string(format='latex') + '$'\n",
    "    \n",
    "    mdrows = []\n",
    "    mdrows.append('<table>')\n",
    "    for k, v in globaldct.items():\n",
    "        mdrows.append('<tr><td><b>{0}</b></td><td>{1}</td></tr>'.format(k, v))\n",
    "    mdrows.append('</table>')\n",
    "    \n",
    "    return display.Markdown('\\n'.join(mdrows))\n",
    "\n",
    "def targetless_info_table(obs, currtime, whichevent='nearest', show_deltas=True):\n",
    "    timesdct = OrderedDict()\n",
    "    timesdct['Sunset'] = obs.sun_set_time(currtime, which=whichevent)\n",
    "    timesdct['Evening civil twilight'] = obs.twilight_evening_civil(currtime, which=whichevent)\n",
    "    timesdct['Evening nautical twilight'] = obs.twilight_evening_nautical(currtime, which=whichevent)\n",
    "    timesdct['Evening astro twilight'] = obs.twilight_evening_astronomical(currtime, which=whichevent)\n",
    "    timesdct['Midnight'] = obs.midnight(currtime, which=whichevent)\n",
    "    timesdct['Morning astro twilight'] = obs.twilight_morning_astronomical(currtime, which=whichevent)\n",
    "    timesdct['Morning nautical twilight'] = obs.twilight_morning_nautical(currtime, which=whichevent)\n",
    "    timesdct['Morning civil twilight'] = obs.twilight_morning_civil(currtime, which=whichevent)\n",
    "    timesdct['Sunrise'] = obs.sun_rise_time(currtime, which=whichevent)\n",
    "    \n",
    "    show_local = obs.timezone.zone != 'UTC'\n",
    "    \n",
    "    mdrows = []\n",
    "    mdrows.append('<table>')\n",
    "    \n",
    "    row_items = ['', '<b>UTC</b>']\n",
    "    if show_local:\n",
    "        row_items.append('<b>Local Time ({0})</b>'.format(obs.timezone))\n",
    "    if show_deltas:\n",
    "        row_items.append('<b>Time Until(+) / Since(-)</b>')\n",
    "    mdrows.append('<tr><td>' + '</td><td>'.join(row_items) +'</td></tr>')\n",
    "     \n",
    "    for k, v in timesdct.items():  \n",
    "        row_items = ['<b>' + k + '</b>']\n",
    "        row_items.append(v.utc.datetime.strftime(STRFTIME_FORMAT))\n",
    "        if show_local:\n",
    "            row_items.append(obs.astropy_time_to_datetime(v).strftime(STRFTIME_FORMAT))\n",
    "        if show_deltas:\n",
    "            row_items.append(deltatime_to_str(v - currtime))\n",
    "        mdrows.append('<tr><td>' + '</td><td>'.join(row_items) +'</td></tr>')\n",
    "                      \n",
    "    mdrows.append('</table>')\n",
    "    \n",
    "    return display.Markdown('\\n'.join(mdrows))\n",
    "\n",
    "def targets_info_table(obs, currtime, targets, whichevent='nearest', show_deltas=True, \n",
    "                       angle_or_airmass=0*u.deg):\n",
    "    if hasattr(angle_or_airmass, 'unit') and angle_or_airmass.unit.is_equivalent(u.deg):\n",
    "        horiz_angle = angle_or_airmass\n",
    "    else:\n",
    "        horiz_angle = 1/np.cos(angle_or_airmass)\n",
    "    show_local = obs.timezone.zone != 'UTC'\n",
    "    \n",
    "    rows = ['<table>']\n",
    "    \n",
    "    # each element creates a row i\n",
    "    row_gens = OrderedDict()\n",
    "    row_gens['Target'] = lambda target: target.name\n",
    "    row_gens['RA'] = lambda target: '$' + target.coord.icrs.ra.to_string(u.hourangle, format='latex', precision=2) + '$'\n",
    "    row_gens['Dec'] = lambda target: '$' + target.coord.icrs.dec.to_string(format='latex', precision=1) + '$'\n",
    "    row_gens['Altitude'] = lambda target: '${0.deg:.1f}^{{\\circ}}$'.format(obs.altaz(currtime, target).alt)\n",
    "    row_gens['Azimuth'] = lambda target: '${0.deg:.1f}^{{\\circ}}$'.format(obs.altaz(currtime, target).az)\n",
    "    row_gens['Zenith Angle'] = lambda target: '${0.value:.1f}^{{\\circ}}$'.format(obs.altaz(currtime, target).zen.to(u.deg))\n",
    "    row_gens[r'Airmass [$\\sec{z}$]'] = lambda target: '${0.value:.1f}$'.format(obs.altaz(currtime, target).secz)\n",
    "    row_gens['Parallactic Angle'] = lambda target: '${0.value:.1f}^{{\\circ}}$'.format(obs.parallactic_angle(currtime, target).to(u.deg))\n",
    "    row_gens['Hour Angle'] = lambda target: '${0.value:.1f}^{{\\circ}}$'.format(obs.target_hour_angle(currtime, target).to(u.deg))\n",
    "    row_gens['Moon separation '] = lambda target: r'${0.value:.1f} ^{{\\circ}}$'.format(obs.moon_altaz(currtime).separation(target.coord).to(u.deg))\n",
    "    \n",
    "    for row_name, generator_func in row_gens.items():\n",
    "        row_items = ['<b>' + row_name + '</b>']\n",
    "        for target in targets:\n",
    "            row_items.append(generator_func(target))\n",
    "        rows.append('<tr><td>' + '</td><td>'.join(row_items) + '</td></tr>')\n",
    "    \n",
    "    # These functions make time objects which are then repeated for all the relevant times\n",
    "    time_row_gens = OrderedDict()\n",
    "    time_row_gens['Rise Time [<TIME>]'] = lambda target: obs.target_rise_time(currtime, target, whichevent, horiz_angle)\n",
    "    time_row_gens['Set Time [<TIME>]'] = lambda target: obs.target_set_time(currtime, target, whichevent, horiz_angle)\n",
    "    time_row_gens['Transit Time [<TIME>]'] = lambda target: obs.target_meridian_transit_time(currtime, target, whichevent)\n",
    "    \n",
    "    #these convert time objects to strings\n",
    "    time_to_str_gens = OrderedDict()\n",
    "    time_to_str_gens['UTC'] = lambda time: time.utc.datetime.strftime(STRFTIME_FORMAT)\n",
    "    if show_local:\n",
    "        time_to_str_gens['Local'] = lambda time: obs.astropy_time_to_datetime(time).strftime(STRFTIME_FORMAT)\n",
    "    if show_deltas:\n",
    "        time_to_str_gens['Until(+) / Since(-)'] = lambda time: deltatime_to_str(time - currtime)\n",
    "\n",
    "    for time_name, time_to_str_func in time_to_str_gens.items():\n",
    "        for row_name, time_generator_func in time_row_gens.items():\n",
    "            row_items = ['<b>' + row_name.replace('<TIME>', time_name) + '</b>']\n",
    "            for target in targets:\n",
    "                row_items.append(time_to_str_func(time_generator_func(target)))\n",
    "            rows.append('<tr><td>' + '</td><td>'.join(row_items) + '</td></tr>')\n",
    "        \n",
    "    rows.append('</table>')\n",
    "    return display.Markdown('\\n'.join(rows))\n",
    "\n",
    "def display_all_tables(obs, currtime, targets, immediate=True):\n",
    "    if immediate:\n",
    "        display.display(global_info_table(obs, currtime))\n",
    "        display.display(targetless_info_table(obs, currtime))\n",
    "        display.display(targets_info_table(obs, currtime, targets))\n",
    "    else:\n",
    "        todisp = []\n",
    "        todisp.append(global_info_table(obs, currtime))\n",
    "        todisp.append(targetless_info_table(obs, currtime))\n",
    "        todisp.append(targets_info_table(obs, currtime, targets))\n",
    "        for d in todisp:\n",
    "            display.display(d)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def sky_plot(obs, currtime, targets, ax=None):\n",
    "    color_cycle = rcParams['axes.color_cycle']\n",
    "    \n",
    "    for i, target in enumerate(targets):\n",
    "        app.plot_sky(target, obs, currtime, style_kwargs={'color': color_cycle[i%len(color_cycle)]}, ax=ax)\n",
    "    \n",
    "    circle = np.linspace(0,2*np.pi, 100)\n",
    "    plt.plot(circle, [np.degrees(np.arccos(1/2.0))]*len(circle), color='k', lw=1, label=r'$\\sec\\,z=2$')\n",
    "    \n",
    "    plt.legend(loc='center left', bbox_to_anchor=(1.25, 0.5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Sky Plots for the closest night"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x109a51990>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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XAX+Q7+Gg2AYAAEBOOY+PkKTYRkbo/QJ+INcBf4SV72Z+L5Gk2Mb2edwLBQAAyAaKbVQu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\nmZlZm7iybWZmZmbWJv8PSoBls8ZyIVUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x105f22f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8))\n",
    "ax = plt.gca()   \n",
    "color_cycle = rcParams['axes.color_cycle']\n",
    "midnight = obs.midnight(Time.now())\n",
    "\n",
    "sunrise = obs.sun_set_time(midnight)\n",
    "sunset = obs.sun_rise_time(midnight)\n",
    "\n",
    "for i, target in enumerate(targets):    \n",
    "    app.plot_airmass(target, obs, midnight, style_kwargs={'color': color_cycle[i%len(color_cycle)]}, ax=ax)\n",
    "    \n",
    "plt.axvline(midnight.plot_date, ls=':', color='k')\n",
    "plt.axvline(obs.twilight_evening_astronomical(midnight).plot_date, ls=':', color='k')\n",
    "plt.axvline(obs.twilight_morning_astronomical(midnight).plot_date, ls=':', color='k')\n",
    "plt.xlim(sunrise.plot_date, sunset.plot_date)\n",
    "\n",
    "plt.legend(loc=0)\n",
    "plt.xlabel('UTC', fontsize=24)\n",
    "plt.ylabel('Airmass [sec z]', fontsize=24)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Real-time updates    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "<table>\n",
       "<tr><td><b>Observatory</b></td><td>Palomar</td></tr>\n",
       "<tr><td><b>UTC</b></td><td>2015-09-15 23:30:45</td></tr>\n",
       "<tr><td><b>Local Time</b></td><td>2015-09-15 16:30:45</td></tr>\n",
       "<tr><td><b>LST</b></td><td>$$15^\\mathrm{h}21^\\mathrm{m}44.0903^\\mathrm{s}$$</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "<table>\n",
       "<tr><td></td><td><b>UTC</b></td><td><b>Local Time (US/Pacific)</b></td><td><b>Time Until(+) / Since(-)</b></td></tr>\n",
       "<tr><td><b>Sunset</b></td><td>2015-09-16 01:50:13</td><td>2015-09-15 18:50:13</td><td>+02:19:28</td></tr>\n",
       "<tr><td><b>Evening civil twilight</b></td><td>2015-09-16 02:19:03</td><td>2015-09-15 19:19:03</td><td>+02:48:19</td></tr>\n",
       "<tr><td><b>Evening nautical twilight</b></td><td>2015-09-16 02:48:10</td><td>2015-09-15 19:48:10</td><td>+03:17:25</td></tr>\n",
       "<tr><td><b>Evening astro twilight</b></td><td>2015-09-16 03:17:43</td><td>2015-09-15 20:17:43</td><td>+03:46:58</td></tr>\n",
       "<tr><td><b>Midnight</b></td><td>2015-09-16 07:42:55</td><td>2015-09-16 00:42:55</td><td>+08:12:10</td></tr>\n",
       "<tr><td><b>Morning astro twilight</b></td><td>2015-09-15 12:07:30</td><td>2015-09-15 05:07:30</td><td>-11:23:15</td></tr>\n",
       "<tr><td><b>Morning nautical twilight</b></td><td>2015-09-15 12:37:08</td><td>2015-09-15 05:37:08</td><td>-10:53:37</td></tr>\n",
       "<tr><td><b>Morning civil twilight</b></td><td>2015-09-15 13:06:18</td><td>2015-09-15 06:06:18</td><td>-10:24:27</td></tr>\n",
       "<tr><td><b>Sunrise</b></td><td>2015-09-15 13:35:11</td><td>2015-09-15 06:35:11</td><td>-09:55:34</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/markdown": [
       "<table>\n",
       "<tr><td><b>Target</b></td><td>Sextans A</td><td>VV124</td></tr>\n",
       "<tr><td><b>RA</b></td><td>$$10^\\mathrm{h}11^\\mathrm{m}00.50^\\mathrm{s}$$</td><td>$$9^\\mathrm{h}16^\\mathrm{m}03.32^\\mathrm{s}$$</td></tr>\n",
       "<tr><td><b>Dec</b></td><td>$$-4^\\circ41{}^\\prime29.0{}^{\\prime\\prime}$$</td><td>$$52^\\circ50{}^\\prime29.5{}^{\\prime\\prime}$$</td></tr>\n",
       "<tr><td><b>Altitude</b></td><td>$7.7^{\\circ}$</td><td>$25.3^{\\circ}$</td></tr>\n",
       "<tr><td><b>Azimuth</b></td><td>$259.1^{\\circ}$</td><td>$318.0^{\\circ}$</td></tr>\n",
       "<tr><td><b>Zenith Angle</b></td><td>$82.3^{\\circ}$</td><td>$64.7^{\\circ}$</td></tr>\n",
       "<tr><td><b>Airmass [$\\sec{z}$]</b></td><td>$7.4$</td><td>$2.3$</td></tr>\n",
       "<tr><td><b>Parallactic Angle</b></td><td>$55.4^{\\circ}$</td><td>$67.3^{\\circ}$</td></tr>\n",
       "<tr><td><b>Hour Angle</b></td><td>$77.7^{\\circ}$</td><td>$91.4^{\\circ}$</td></tr>\n",
       "<tr><td><b>Moon separation </b></td><td>$47.5 ^{\\circ}$</td><td>$79.3 ^{\\circ}$</td></tr>\n",
       "<tr><td><b>Rise Time [UTC]</b></td><td>2015-09-15 12:35:11</td><td>2015-09-16 07:24:39</td></tr>\n",
       "<tr><td><b>Set Time [UTC]</b></td><td>2015-09-16 00:08:06</td><td>2015-09-16 03:25:44</td></tr>\n",
       "<tr><td><b>Transit Time [UTC]</b></td><td>2015-09-15 18:21:38</td><td>2015-09-15 17:27:08</td></tr>\n",
       "<tr><td><b>Rise Time [Local]</b></td><td>2015-09-15 05:35:11</td><td>2015-09-16 00:24:39</td></tr>\n",
       "<tr><td><b>Set Time [Local]</b></td><td>2015-09-15 17:08:06</td><td>2015-09-15 20:25:44</td></tr>\n",
       "<tr><td><b>Transit Time [Local]</b></td><td>2015-09-15 11:21:38</td><td>2015-09-15 10:27:08</td></tr>\n",
       "<tr><td><b>Rise Time [Until(+) / Since(-)]</b></td><td>-10:55:34</td><td>+07:53:55</td></tr>\n",
       "<tr><td><b>Set Time [Until(+) / Since(-)]</b></td><td>+00:37:21</td><td>+03:54:60</td></tr>\n",
       "<tr><td><b>Transit Time [Until(+) / Since(-)]</b></td><td>-05:09:06</td><td>-06:03:37</td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.Markdown object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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PlFIbtc5FRETEkkfkh0QkBMC94eHh75rN5movvfSS6cknn4TZbNY6GlHQSU9Px4cffuj5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hAAAg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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d2b5f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "refresh_interval = 1*u.minute\n",
    "refresh_interval = None # comment this to get real-time updates\n",
    "\n",
    "fig = plt.figure(figsize=(12, 10))\n",
    "ax = None\n",
    "\n",
    "while True:\n",
    "    currtime = Time.now()\n",
    "    \n",
    "    display.clear_output(True)\n",
    "    display_all_tables(obs, currtime, targets, immediate=False)\n",
    "    \n",
    "    if ax is not None:\n",
    "        plt.cla()\n",
    "    sky_plot(obs, currtime, targets, ax=ax)\n",
    "    ax = plt.gca()\n",
    "    \n",
    "    if refresh_interval is None:\n",
    "        break\n",
    "    else:\n",
    "        display.display(fig)\n",
    "        \n",
    "        timeleft = (currtime + refresh_interval) - Time.now()\n",
    "        if timeleft.value > 0:\n",
    "            sleep(timeleft.to(u.second).value)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}