examples/adonmo-daylight-brightness-control.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adonmo's brightness control mechanism using daylight library\n",
    "\n",
    "(*Written on June 1st, 2020*)\n",
    "\n",
    "Adonmo operates more than 500 digital taxitop displays which roam around multiple cities like Hyderabad, Mumbai etc, at various times of the day. Since these screens are present on the road, we, at Adonmo, constantly try our best to ensure that our displays are not causing any kind of distraction to the ongoing trafic. We take several measure to do this - right from the approval of creatives to controlling the brightness of the screens based on various parameters. Of this parameters, time of day remains one of the basic and major factors - through which a base brightness level of the screen is decided.\n",
    "\n",
    "Originally this base brightness value was handpicked for various times of the day and set accordingly for each city. However, this approach has a few problems:\n",
    " - **⭐ Lack of seasonality** - Every few months sunsire/sunset times change because of change in season, and these values have to be constantly updated.\n",
    " - **📍 Not scalable across multiple cities/timezones** - Sun rises earlier in Hyderabad than in Mumbai - relying on timezone IST in not enough. Additionally, if we were to maintain for cities across the world, this solution does not scale.\n",
    " - **⚠️ Possibility of human error** - When brightness values are manually picked and maintained for city and season there is always a chance of human error to creep in.\n",
    "\n",
    "To solve the above issues and come up with a more scalable solution, we built the [\"daylight\" library](https://github.com/adonmo/daylight). Using this we were able to come up with a brightness control mechanism that is not only season-independent, but also works anywhere in the world, and at the same time avoid manual efforts and human errors. Below code demonstrates how we achieved this.\n",
    "\n",
    "\n",
    "## 📦 Initial setup\n",
    "We load pandas, matplotlib and most importantly - [daylight](https://github.com/adonmo/daylight). We also setup three example locations to showcase the end result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import pytz\n",
    "import datetime\n",
    "%matplotlib notebook\n",
    "%pylab inline\n",
    "\n",
    "tz = pytz.timezone(\"Asia/Kolkata\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import daylight\n",
    "\n",
    "# Hyderabad\n",
    "s_hyd = daylight.Sunclock(17.3850, 78.4867)\n",
    "\n",
    "# Mumbai\n",
    "s_mum = daylight.Sunclock(19.075999, 72.877393)\n",
    "\n",
    "# Bangkok\n",
    "s_bkk = daylight.Sunclock(13.736717, 100.523186)\n",
    "\n",
    "\n",
    "# A small helper function which we will use later\n",
    "def epoch(year, month, day, hour=0, minute=0, second=0, tz=pytz.UTC):\n",
    "    return int(tz.localize(datetime.datetime(year, month, day, hour, minute, second)).timestamp())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🧠 Sanity test\n",
    "\n",
    "Let's do a basic test to visualize and ensure that irradiance levels vary thoughout the day as expected. That is we should see higher values around noon, and it should drop sharply on either ends."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_for_day(date, tz):\n",
    "    df = pd.DataFrame([h * 60 + m for h, m in zip(range(24), range(60))], columns=['time_of_day'])\n",
    "    df.set_index('time_of_day')\n",
    "    df['irradiance'] = df['time_of_day'].apply(lambda t: s_hyd.irradiance(epoch(date.year, date.month, date.day, t//60, t%60, tz=tz)))\n",
    "    df['irradiance'].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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YEBfB4M76/9bbiAgPjE5iX1Epr32303YcdQ5cUQhygOgay+0d6/7LGFNgjDkxq8UrQL8zPVY1fK+syCL/aBnTRndBRFsD3mhAXAuGJbXkH19ncvBYme046iy5ohCsARJEJFZEgoDxwIKaO4hImxqLlwMneqF8CYwUkeaOi8QjHeuUj8g7cpyXl2cxpkdrekeH246jnHD/6CSOHa/ghWWZtqOos+R0ITDGVABTqP4C3wq8Z4zZLCKPisjljt3uFJHNIrIBuBO43nFsIfAY1cVkDfCoY53yEc8vzaC0oop7RybajqKc1LlVE67q1543vt9FdmGx7TjqLIg3dgRJTk42KSkptmMoJ+3MP8bwZ79hfP9o/jquh+04ygX2FZUw+OmvGd29NTPH97EdR51ERNYaY5JPXq89i5U1z3yVRqC/H3cOS7AdRblIm2aNuHFQLB+v38umHJ2zwFtoIVBWbNxziE837uP3F8XSsokOJdGQ3HpJJ8JDA3nyi222o6gzpIVAuZ0x1UNJRDQO4vcXx9mOo1ysWaNA7hiawIqMfFZkaJ8fb6CFQLndiox8Vm4v4I6h8TQJCbQdR9WDawfE0L55I/62cBtVOvSEx9NCoNzqxMBy0RGNuOb8GNtxVD0JDvDnvksT2bLvMPM3aNcgT6eFQLnVgg172bLvMPeOTCQ4QAeWa8gu69mW7u2a8syXOvSEp9NCoNzmeEUlz3yVRre2TbmsZ1vbcVQ98/MTpo3qQs6hEt5ctct2HHUKWgiU27y1ajd7DpYwbXQSfjqwnE8YlBDJRQmRvLAsk6KScttxVB20ECi3OFxazvNLMxgUH8lFCTqwnC+ZNjqJopJyXvp6u+0oqg5aCJRbvLw8i4PF5dw/Ksl2FOVm3do244re7Xjtux3sPVRiO46qhRYCVe9yD5fyyoodXNarLT3aN7MdR1kwdWRnjIEZi9JtR1G10EKg6t3MJRlUVFVxnw4s57PaNw9l4oUd+HDdHrbtP2w7jjqJFgJVr7bnHeXdNdn89vwOxLQItR1HWTR5SDxhwQE89UWa7SjqJFoIVL165ss0QgL8mDI03nYUZVl4aBC3XNKJpdty+XH3QdtxVA1aCFS92bjnEJ9v2s/vL44jMizYdhzlASZe2JGIxkHMWJxhO4qqQQuBqjczFqUTHhrITYNibUdRHiIsOIBbLo5jeXoeKTt1DipPoYVA1Ysfdx9kWVoeky6O04Hl1E9cd0EHIsOCmLFY7yDyFFoIVL2YsTiDiMZBTLygo+0oysOEBgVw6yWd+C6zgFVZBbbjKLQQqHqwdlchy9PzuOXiOBoHB9iOozzQtQM6ENUkmGcXpeON0+U2NC4pBCIySkTSRCRTRKbVsn2qiGwRkY0iskREOtTYViki6x2PBa7Io+yasSiDyLAgrrugw+l3Vj4pJNCfyYM78cOOQr7frq0C25wuBCLiD7wIjAa6AhNEpOtJu/0IJBtjegIfAE/V2FZijOnteFzubB5l1+qsAr7NzOfWSzoRGqStAVW38f1jaN00RFsFHsAVLYL+QKYxJssYUwa8A4ytuYMxZpkxptixuApo74LfqzzQjMXpRDUJ5toB2hpQpxYS6M/kofGk7DrIiox823F8misKQTsgu8byHse6utwEfF5jOUREUkRklYiMq+sgEZnk2C8lL0/nQfVEK7fnsyqrkNsHdyIkUCedUad3dXJ72oU30laBZW69WCwi1wLJwNM1VncwxiQD1wAzRaRTbccaY2YbY5KNMclRUTqMsacxxjBzUQatmgYzob9OQanOTHCAP1OGxrM++xBfp+kfeLa4ohDkANE1lts71v2EiAwHHgIuN8YcP7HeGJPjeM4Cvgb6uCCTcrPvMgv4YWchk4fEa2tAnZWr+rUnOkJbBTa5ohCsARJEJFZEgoDxwE/u/hGRPsC/qC4CuTXWNxeRYMfrSGAgsMUFmZQbGWN4dlEabZqF8Jvzok9/gFI1BPr7ccfQBFJzili8Nff0ByiXc7oQGGMqgCnAl8BW4D1jzGYReVRETtwF9DQQBrx/0m2iXYAUEdkALAOmG2O0EHiZ5Rn5rNt9iClD43VCenVOruzTjg4tQnl2UTpVVdoqcDeX3N9njFkILDxp3Z9rvB5ex3ErgR6uyKDsqG4NpNMuvBG/7qetAXVuAvz9uGtYAlPf28BXW/Yzqnsb25F8ivYsVk5ZlpbLhuxD3DE0nqAA/Tipc3d5r7bERTVmxqIMbRW4mf7LVefMGMOMRRlERzTiV/20a4hyzolWQdqBIyzctM92HJ+ihUCds8Vbc0nNKeLOoQkE+utHSTnvlz3bktAyjJmLM6jUVoHb6L9edU6qqqqvDXRsEcoVfU7Vf1CpM+fvJ9wzojOZuUf5dONe23F8hhYCdU6+2rKfrfsOc+ewBAK0NaBcaFS31iS1bsJzizOoqKyyHccn6L9gddaqqgwzF2cQF9WYy3u1tR1HNTB+jlZBVv4x5q/XVoE7aCFQZ+3zTfvZtv8Id2lrQNWTkV1b0a1tU2YtzaBcWwX1Tv8Vq7NSWWWYuTid+JZh/LKntgZU/RARpo7ozK6CYuat+9mINcrFtBCos/JZ6j4yco9y9/AE/P3EdhzVgA1Nakmv9s2YtTSDsgptFdQnLQTqjJ1oDSS2asIY7fmp6plI9bWCPQdL+GDtHttxGjQtBOqMLdiQQ1beMe4enoCftgaUG1zSOYq+MeG8sDSD4xWVtuM0WFoI1BmpqKxi1pJMurRpyqXdWtuOo3xE9bWCRPYWlfLumuzTH6DOiRYCdUbm/ZjDjnxtDSj3Gxjfgv4dI3hhaSal5doqqA9aCNRplVdWMWtpBj3aNWNk11a24ygfIyJMHdmZ3CPHeXPVLttxGiQtBOq03k/ZQ3ZhCVNHdEZEWwPK/QbEteDCTi345zfbKS6rsB2nwdFCoE7peEUlLyzNoE9MOIMTda5oZc8fRnYm/2gZr3+vrQJX00KgTundNdnsLSrV1oCyrl+HCC7pHMW/vtnO0ePaKnAlLQSqTqXllbywNJP+HSMYFB9pO45S3DOiMweLy5nz3Q7bURoULQSqTm+u2kXukeNMHamtAeUZekeHM7xLS2Yvz6KopNx2nAbDJYVAREaJSJqIZIrItFq2B4vIu47tq0WkY41tDzjWp4nIpa7Io5xXXFbBP7/ZzsD4FgyIa2E7jlL/dffwzhwureDVb7VV4CpOFwIR8QdeBEYDXYEJItL1pN1uAg4aY+KBGcCTjmO7AuOBbsAo4B+On6csm7tyF/lHy5g6ItF2FKV+onu7Zozq1ppXv93BoeIy23EaBFe0CPoDmcaYLGNMGfAOMPakfcYCcx2vPwCGSfW5hrHAO8aY48aYHUCm4+cpi46UlvOv5dsZnBhFvw7NbcdR6mfuGdGZo2UVzF6eZTtKg+CKQtAOqNn3e49jXa37GGMqgCKgxRkeC4CITBKRFBFJycvLc0FsVZfXvtvJoeJypo7obDuKUrVKbN2EX/Zsy5yVOyk4etx2HK/nNReLjTGzjTHJxpjkqCi9n72+FBWX8/KKLEZ0bUXP9uG24yhVp7uGJVBaXsm/tFXgNFcUghwgusZye8e6WvcRkQCgGVBwhscqN3rl2yyOlFZwz3BtDSjPFt8yjHG92/H69zvJPVJqO45Xc0UhWAMkiEisiARRffF3wUn7LAAmOl5fBSw1xhjH+vGOu4pigQTgBxdkUufg4LEyXv12B2N6tKZr26a24yh1WncOS6C80vDS19ttR/FqThcCxzn/KcCXwFbgPWPMZhF5VEQud+z2b6CFiGQCU4FpjmM3A+8BW4AvgMnGGB1e0JJ/Lc+iuLySu7U1oLxEx8jG/KpvO95avZt9RSW243gtqf7D3LskJyeblJQU2zEalLwjx7n4qWWM7NaK58b3sR1HqTOWXVjMkGe+ZkL/GB4b1912HI8mImuNMcknr/eai8Wqfv3zm+0cr6jkrmEJtqModVaiI0K5+rxo3lmzmz0Hi23H8UpaCBQHDpfy5qpdXNm3PXFRYbbjKHXWpgyJRxBeWJppO4pX0kKgeHFZJpVVRlsDymu1DW/ENefH8P7aPewqOGY7jtfRQuDjcg6V8M4P2fw6OZroiFDbcZQ6Z7cP7kSAnzBribYKzpYWAh/3wtIMAKYMjbecRCnntGwawnUDOjDvxz1szztqO45X0ULgw3YXFPN+yh7G94+mXXgj23GUctqtgzsRHODPrCUZtqN4FS0EPuy5JRn4+wmTh2hrQDUMkWHBTLywIws27CX9wBHbcbyGFgIflZV3lHk/7uHaAR1o1TTEdhylXOaWi+NoHBTAc4u1VXCmtBD4qOeWZBAc4M9tgzvZjqKUSzVvHMSNAzvyWeo+NuUU2Y7jFbQQ+KD0A0dYsGEvEy/sSGRYsO04SrncTRfF0Tw0kOmfb8MbR09wNy0EPuiZL9NoHBTALRfH2Y6iVL1o1iiQO4Ym8G1mPt+k6/wlp6OFwMesyirgqy0HuG1wJ5o3DrIdR6l6c+2ADnRoEcrfFm6jskpbBaeihcCHVFUZnli4lTbNQrhxYKztOErVq6AAP+4flUTagSN8sDb79Af4MC0EPuSTjXvZuKeIe0cm0ijI33Ycperd6O6t6RsTzt+/Sqe4rMJ2HI+lhcBHlJZX8tQXaXRr25Qr+tQ6LbRSDY6I8NAvupB75DivrNhhO47H0kLgI+as3EnOoRIeGtMFPz+xHUcpt+nXIYJR3Vrzz2+265SWddBC4AMKjh7nxaWZDEtqyYXxkbbjKOV2949OoqyiipnayaxWWgh8wKwlGRSXV/LAmCTbUZSyIjayMdcO6MC7a7LJzNWhJ06mhaCB2553lLdW72b8edHEt2xiO45S1tw5LIHQQH+mf77NdhSP41QhEJEIEVkkIhmO5+a17NNbRL4Xkc0islFEflNj2xwR2SEi6x2P3s7kUT/35OfbCAn0554ROiG98m0RjYO4bUgnFm/N5fvtBbbjeBRnWwTTgCXGmARgiWP5ZMXA74wx3YBRwEwRCa+x/T5jTG/HY72TeVQNq2t0HtOhJJSCGwfG0rZZCE8s3EqVdjL7L2cLwVhgruP1XGDcyTsYY9KNMRmO13uBXCDKyd+rTqOqyvC4dh5T6idCAv2599JEUnOK+GTjXttxPIazhaCVMWaf4/V+oNWpdhaR/kAQsL3G6scdp4xmiEidf7aKyCQRSRGRlLw8HTvkdLTzmFK1G9e7Hd3aNuWpL9IoLa+0HccjnLYQiMhiEdlUy2Nszf1M9RB/dba1RKQN8AZwgzGmyrH6ASAJOA+IAO6v63hjzGxjTLIxJjkqShsUp6Kdx5Sqm5+f8OCYLuQcKmHuyp2243iEgNPtYIwZXtc2ETkgIm2MMfscX/S5dezXFPgMeMgYs6rGzz7RmjguIq8B955VelWrE53Hnr6qp3YeU6oWA+MjGZwYxQvLMrk6OdrnB2B09tTQAmCi4/VEYP7JO4hIEDAPeN0Y88FJ29o4noXq6wubnMzj8wqPlWnnMaXOwAOju3DseAXPL820HcU6ZwvBdGCEiGQAwx3LiEiyiLzi2Odq4GLg+lpuE31LRFKBVCAS+KuTeXzec4vTtfOYUmcgsXUTrk6O5o1VO9lVcMx2HKvEG2fvSU5ONikpKbZjeJzteUe5dMZyfnNeNI9f0cN2HKU8Xu7hUi55+muGJrXkxd/2tR2n3onIWmNM8snrtWdxA/Lk59sIDvDj7uHaeUypM9GyaQi/vziOz1L3sW73QdtxrNFC0ECc6Dx2+5B4oppo5zGlztQtF8cRGRbME59t9dn5jbUQNAA685hS565xcABTR3QmZddBvty833YcK7QQNACfbNzLBu08ptQ5uzq5PfEtw3jyizTKK6tOf0ADo4XAy2nnMaWcF+DvxwOjk9iRf8wnO5lpIfByOvOYUq4xNKklQxKj+PtX6ewuKLYdx620EHix7MJiZi3JYHgX7TymlLNEhMev6IG/n/DAvI0+deFYC4GXMsZw/4cb8RPh0bHdbcdRqkFoG96IaaOT+C6zgPdSsm3HcRstBF7q7R+yWbm9gAfHdKFteCPbcZRqMK7pH0P/2Aj++tlWDhz2jcnutRB4oZxDJTyxcCsD41swoX+07ThKNRf5xyEAAA2ISURBVCh+fsKTv+pJWUUVf/p4k0+cItJC4GWMMTzwUSpVxjD9yp5Uj9enlHKl2MjGTB3RmUVbDvBZ6r7TH+DltBB4mffX7mF5eh73j0oiOiLUdhylGqybBsXSs30zHp6/mcJjZbbj1CstBF7kwOFSHvt0C/07RnDdgA624yjVoAX4+/Hkr3pSVFLOY59usR2nXmkh8BLGGB6al0pZRRVP6oQzSrlFlzZNuX1IPPN+zGHZtlrn3WoQtBB4ifnr97J4ay73XZpIbGRj23GU8hmTh3Sic6swHpyXypHScttx6oUWAi+Qd+Q4j3yymb4x4dygg8op5VbBAf48+aueHDhcyvTPt9mOUy+0EHiBP8/fRHFZJU9d1Qt/PSWklNv1iWnOjQNjeWv1blZlFdiO43JaCDzcZxv38fmm/dw9PIH4lmG24yjls/4wMpGYiFCmfbiRkrJK23FcyqlCICIRIrJIRDIcz83r2K+yxnzFC2qsjxWR1SKSKSLvOia6Vw4FR4/z5/mb6Nm+GZMuirMdRymf1ijIn+m/6sHOgmJmLk63HcelnG0RTAOWGGMSgCWO5dqUGGN6Ox6X11j/JDDDGBMPHARucjJPg/KXT7ZwuLScp67qSYC/Nt6Usu3CTpFM6B/Nyyuy2JB9yHYcl3H222UsMNfxei4w7kwPlOousUOBD87l+Ibuq837WbBhL1OGJJDUuqntOEophwfGdKFlkxDu/3AjZRUNYxIbZwtBK2PMif7X+4FWdewXIiIpIrJKRE582bcADhljKhzLewCdWQU4VFzGQx9vctzD3Ml2HKVUDU1DAvnruO5s23+El77ebjuOSwScbgcRWQy0rmXTQzUXjDFGROoanamDMSZHROKApSKSChSdTVARmQRMAoiJiTmbQ73OY59u5eCxMl67/jwC9ZSQUh5neNdWXN6rLS8sy2B0j9Z0btXEdiSnnPZbxhgz3BjTvZbHfOCAiLQBcDzX2vXOGJPjeM4Cvgb6AAVAuIicKEbtgZxT5JhtjEk2xiRHRUWdxX+id1mWlsuH6/Zw2+BOdG/XzHYcpVQdHr6sK01CAvnjBxuprPLuEUqd/XNzATDR8XoiMP/kHUSkuYgEO15HAgOBLaZ6bNdlwFWnOt6XHC4t54EPU+ncKowpQ+Ntx1FKnUKLsGAevqwr67MP8cqKLNtxnOJsIZgOjBCRDGC4YxkRSRaRVxz7dAFSRGQD1V/8040xJ0Zwuh+YKiKZVF8z+LeTebzaE59tJfdIKU9f1YvgAH/bcZRSp3F5r7aM7t6aJ7/YxtJtB2zHOWfijZMuJCcnm5SUFNsxXOqt1bt4aN4mbrkkjgdGd7EdRyl1ho4dr+A3s78nK+8Y791ygUef0hWRtcaY5JPX65VID7BoywH+7+NNDEmM4r6RibbjKKXOQuPgAF6deB7hjQK5cc4a9h4qsR3prGkhsGzd7oPc8fY6urdrxgvX9NWOY0p5oZZNQ3jthv6UlFVyw2trOOxlo5Tqt45FO/KPcfPcFFo2CeHV68+jcfBp7+ZVSnmoxNZNeOnafmzPO8rkt9ZRXuk9nc20EFiSf/Q417/2A8YY5t7Yn8iwYNuRlFJOGpQQyRNX9mBFRj5/muc9E9/rn6AWFJdVcNOcNRw4XMp/fj9AJ5pRqgG5Ojma7MJinl+aSUyLUCYP8fxbwbUQuFlFZRWT31pHak4R/7oumb4xtQ7YqpTyYlNHdGZ3YTFPf5lG++aNGNvbs0fP0ULgRsYY/m/+Jpal5fHXcd0Z0bWuoZmUUt5MRHjqqp7sKyrlvvc30rppCOfHtbAdq056jcCNnl+ayds/ZDN5SCeuHdDBdhylVD0KDvBn9nX9aB/RiElvrGV73lHbkeqkhcBN3kvJ5tlF6VzZtx33al8BpXxCeGgQc67vT4CfcMNrayg4etx2pFppIXCDr9NyeeCjVC5KiGT6lT2pnopBKeULYlqE8srEZA4cLuXm11MoLfe8aS61ENSz1D1F3P7WOhJbVd9jHBSgb7lSvqZPTHOeG9+b9dmHuOfd9VR52Gil+q1Uj7ILi7lhzhqahwYx54bzCNMOY0r5rFHd2/DQmC58vmk/07/YZjvOT+g3Uz05eKyMia/9QHllFe9MOp+WTUNsR1JKWXbToFh2FxYze3kWbZuFcP3AWNuRAG0R1IuiknJufj2FPQdLeGViMvEtvXv2IqWUa4gIf/5lV4YlteSRT7Yw9b31HjEukRYCF1uy9QAjZ3zD+uxDPPeb3pzXMcJ2JKWUBwnw9+Ola/txx9B4Pv4xh1EzlrMyM99qJi0ELnKouIx73l3PTXNTaB4axMe3D2R0jza2YymlPFBQgB9/GJnIB7ddSHCgP9e8sppHP9li7Y4ivUbgAl9s2sefPt7MoeIy7h6ewO2D4/XuIKXUafWNac5ndw7ibwu38ep3O1iekceMq3vTo717J7fRbysnFBw9zuT/rOPWN9fRulkwn9wxiLuHd9YioJQ6Y6FBATw2rjtzb+zPkdJyrvjHd8xakkGFG4ex1qkqz4Exhk837uPhBZs5WlrBXcMTmHRxHIE6qYxSyglFxeX83/xNLNiwl17R4cy4uhdxUWEu+/n1MlWliESIyCIRyXA8/2woTREZIiLrazxKRWScY9scEdlRY1tvZ/K4Q+6RUm59cy13vP0j0RGhfHrnICYPidcioJRyWrPQQGZN6MPzE/qwM/8YY2at4PXvd9b7vAZOtQhE5Cmg0BgzXUSmAc2NMfefYv8IIBNob4wpFpE5wKfGmA/O5vfaaBEYY5j3Yw5/+WQLJeWV/GFEZ24aFKtTSyql6sWBw6Xc98FGlqfncVFCJE9f1YvWzZzrj1Rfk9ePBeY6Xs8Fxp1m/6uAz40xxU7+XrfaX1TKzXNTmPreBuJbhvH5XRdxyyWdtAgopepNq6YhzL3hPP46rjspOw8ycsY3zF+fUy+/y9m7hloZY/Y5Xu8HTjfA/njg2ZPWPS4ifwaWANOMMVaH5ysqLmdHwTF25h9jp+N5ybZcyiur+PMvuzLxwo74++mgcUqp+iciXDugAwPjI5n63nruemc9MRGh9HHxhFanPTUkIouB1rVsegiYa4wJr7HvQWNMrQlFpA2wEWhrjCmvsW4/EATMBrYbYx6t4/hJwCSAmJiYfrt27TrNf1rdjpSWszO/+H9f+PnH/vv6YPH/evmJQNtmjejRrhnTRifRUaeUVEpZUlFZxbK0PKcmtKrr1NBpWwTGmOGn+KEHRKSNMWaf40s99xQ/6mpg3oki4PjZJ1oTx0XkNeDeU+SYTXWxIDk5+ZwubDw0L5UvN+8n/2jZT9a3aRZCxxaNGdW9DbGRoXRs0ZjYyMZER4QSEuh/Lr9KKaVcKsDfr95mNXT21NACYCIw3fE8/xT7TgAeqLmiRhERqq8vbHIyzym1DW/EsKRWdIxsXP2FH9mYDhGNaRSkX/ZKKd/lbCGYDrwnIjcBu6j+qx8RSQZuNcbc7FjuCEQD35x0/FsiEgUIsB641ck8pzR5SHx9/nillPJKThUCY0wBMKyW9SnAzTWWdwLtatlvqDO/XymllPP0/kellPJxWgiUUsrHaSFQSikfp4VAKaV8nBYCpZTycVoIlFLKx2khUEopH+eVE9OISB7VHdjORSRgd6Zoz6DvQzV9H/5H34tqDfl96GCMiTp5pVcWAmeISEptgy75Gn0fqun78D/6XlTzxfdBTw0ppZSP00KglFI+zhcLwWzbATyEvg/V9H34H30vqvnc++Bz1wiUUkr9lC+2CJRSStWghUAppXycTxUCERklImkikiki02znsUVEdopIqoisF5EU23ncRUReFZFcEdlUY12EiCwSkQzHs2tnBfdAdbwPj4hIjuMzsV5ExtjM6A4iEi0iy0Rki4hsFpG7HOt97jPhM4VARPyBF4HRQFdggoh0tZvKqiHGmN4+dr/0HGDUSeumAUuMMQnAEsdyQzeHn78PADMcn4nexpiFbs5kQwXwB2NMV2AAMNnxneBznwmfKQRAfyDTGJNljCkD3gHGWs6k3MgYsxwoPGn1WGCu4/VcqufObtDqeB98jjFmnzFmneP1EWAr1TMp+txnwpcKQTsgu8byHmqZPtNHGOArEVkrIpNsh7GslTFmn+P1fqCVzTCWTRGRjY5TRw3+dEhNjnnV+wCr8cHPhC8VAvU/g4wxfak+TTZZRC62HcgTmOp7qX31fuqXgE5Ab2Af8He7cdxHRMKAD4G7jTGHa27zlc+ELxWCHCC6xnJ7xzqfY4zJcTznAvOoPm3mqw6ISBsAx3Ou5TxWGGMOGGMqjTFVwMv4yGdCRAKpLgJvGWM+cqz2uc+ELxWCNUCCiMSKSBAwHlhgOZPbiUhjEWly4jUwEth06qMatAXARMfricB8i1msOfHF53AFPvCZEBEB/g1sNcY8W2OTz30mfKpnseOWuJmAP/CqMeZxy5HcTkTiqG4FAAQA//GV90FE3gYGUz3M8AHgYeBj4D0ghuqhza82xjToC6l1vA+DqT4tZICdwC01zpM3SCIyCFgBpAJVjtUPUn2dwLc+E75UCJRSSv2cL50aUkopVQstBEop5eO0ECillI/TQqCUUj5OC4FSSvk4LQRKKeXjtBAopZSP+38LvU2GdyFbdgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Today\n",
    "plot_for_day(datetime.date.today(), tz)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ⭐ Season independence\n",
    "\n",
    "daylight's irradience levels are computed using sun's elevation angle. This makes it possible to get reasonable irradiance values, independent of what season we are in. That is - we should expect to see higher irradiance values in the summer and lower irradiance values in the winter. Let's compare and contrast different days from different seasons to ensure this."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(range(24), columns=['time_of_day'])\n",
    "df.set_index('time_of_day', inplace = True)\n",
    "df['irradiance_eq1'] = df.index.map(lambda t: s_hyd.irradiance(epoch(2020, 3, 20, t, tz=tz)))\n",
    "df['irradiance_ss'] = df.index.map(lambda t: s_hyd.irradiance(epoch(2020, 6, 21, t, tz=tz)))\n",
    "df['irradiance_eq2'] = df.index.map(lambda t: s_hyd.irradiance(epoch(2020, 9, 23, t, tz=tz)))\n",
    "df['irradiance_ws'] = df.index.map(lambda t: s_hyd.irradiance(epoch(2020, 12, 21, t, tz=tz)))\n",
    "ax = df.plot()\n",
    "ax.legend(['March Equinox', 'Summer Solstice', 'Sept Equinox', 'Winter Solstice']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 📍 Location independence\n",
    "\n",
    "Using sun's elevation angle to compute irradiance - also makes it location independent. This makes it possible to get reasonable irradiance values, independent of which city we are calculating it for. Let's compare and contrast days from different cities to ensure this.\n",
    "\n",
    "In the below example you can see Bankok's irradiance values seem to rise earlier and fall earlier as expected - this is because sun rises in the east, and sets in the west."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df = pd.DataFrame(range(24), columns=['time_of_day'])\n",
    "df.set_index('time_of_day', inplace = True)\n",
    "df['irradiance_eq1_hyd'] = df.index.map(lambda t: s_hyd.irradiance(epoch(2020, 3, 20, t, tz=tz)))\n",
    "df['irradiance_eq1_mum'] = df.index.map(lambda t: s_mum.irradiance(epoch(2020, 3, 20, t, tz=tz)))\n",
    "df['irradiance_eq1_bkk'] = df.index.map(lambda t: s_bkk.irradiance(epoch(2020, 3, 20, t, tz=tz)))\n",
    "ax = df.plot()\n",
    "ax.legend(['HYD', 'MUM', 'BKK']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 📈 Irradiance -> Brightness\n",
    "\n",
    "The above sections pretty much cover the overview and benefits of this new brightness control mechanism. However, we do some minor adjustments over these irradiance values to convert them to suitable practical brightness values:\n",
    "\n",
    "- **Normalization** - Irradiance values are between (-1, 1). Generally devices represent brightness values as percentages, i.e in the range (0, 100).\n",
    "- **Fine-Tuning** - From physical testing, we found a slightly sharper rise and fall is a bit more suitable for practical needs, specifically to lower down values in the early mornings and evenings - just to be on the safe side. We achieve this by using this formula - (norm_irradiance)^e where norm_irradiance is a value normalized between 0 and 1.\n",
    "- **Min/max** - Say we want to restrict brightness values within (10, 60) within the original range of (0, 100) - we do the same, but instead we restrict on the lower end which is (0, 42).\n",
    "\n",
    "Below two graphs showcase the final result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = 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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       " * http://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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\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",
       "\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('matplotlib', mpl.mpl_figure_comm);\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": [
    "from matplotlib.ticker import FuncFormatter\n",
    "\n",
    "df = pd.DataFrame([h * 60 + m * 1 for h in range(24) for m in range(60)], columns=['time_of_day'])\n",
    "df.set_index('time_of_day', inplace = True)\n",
    "\n",
    "def brightness(y, m , d, t):\n",
    "    normalized = (s_hyd.irradiance(epoch(y, m, d, t//60, t%60, tz=tz)) + 1) / 2\n",
    "    normalized = math.pow(normalized, math.e)\n",
    "    min_b, max_b = 1, 42\n",
    "    return min_b + (max_b - min_b) * normalized\n",
    "\n",
    "def tick_format(x, pos):\n",
    "    return int(x // 60)\n",
    "\n",
    "df['brightness_eq1'] = df.index.map(lambda t: brightness(2020, 3, 20, t))\n",
    "df['brightness_ss'] = df.index.map(lambda t: brightness(2020, 6, 21, t))\n",
    "df['brightness_eq2'] = df.index.map(lambda t: brightness(2020, 9, 23, t))\n",
    "df['brightness_ws'] = df.index.map(lambda t: brightness(2020, 12, 21, t))\n",
    "%matplotlib notebook\n",
    "ax = df.plot(drawstyle='steps')\n",
    "\n",
    "ax.legend(['March Equinox', 'Summer Solstice', 'Sept Equinox', 'Winter Solstice'])\n",
    "ax.xaxis.set_major_formatter(FuncFormatter(tick_format))\n",
    "ax.set_xlabel(\"Hour of day\")\n",
    "ax.set_ylabel(\"Brightness\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = 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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       " * http://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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.ticker import FuncFormatter\n",
    "\n",
    "df = pd.DataFrame([h * 60 + m * 1 for h in range(24) for m in range(60)], columns=['time_of_day'])\n",
    "df.set_index('time_of_day', inplace = True)\n",
    "\n",
    "def brightness(s, y, m , d, t):\n",
    "    normalized = (s.irradiance(epoch(y, m, d, t//60, t%60, tz=tz)) + 1) / 2\n",
    "    normalized = math.pow(normalized, math.e)\n",
    "    min_b, max_b = 1, 42\n",
    "    return min_b + (max_b - min_b) * normalized\n",
    "\n",
    "def tick_format(x, pos):\n",
    "    return int(x // 60)\n",
    "\n",
    "df['brightness_eq1_hyd'] = df.index.map(lambda t: brightness(s_hyd, 2020, 3, 20, t))\n",
    "df['brightness_eq1_mum'] = df.index.map(lambda t: brightness(s_mum, 2020, 3, 20, t))\n",
    "df['brightness_eq1_bkk'] = df.index.map(lambda t: brightness(s_bkk, 2020, 3, 20, t))\n",
    "%matplotlib notebook\n",
    "ax = df.plot(drawstyle='steps')\n",
    "\n",
    "ax.legend(['HYD', 'MUM', 'BKK'])\n",
    "ax.xaxis.set_major_formatter(FuncFormatter(tick_format))\n",
    "ax.set_xlabel(\"Hour of day\")\n",
    "ax.set_ylabel(\"Brightness\");"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 🆚 Before vs. After\n",
    "\n",
    "Finally we do a little before versus after comparision. Here `old_brightness` represents an example hardcoded brightness control mechanism. We see that new control mechanism looks much neater and smoother comparatively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\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('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",
       "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 = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(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 (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\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 = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\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 nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option);\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\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",
       "\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",
       "\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]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.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, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\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",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = 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.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",
       "            /* 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",
       "            evt.data.type = \"image/png\";\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",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\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(\"No handler for the '\" + msg_type + \"' message type: \", msg);\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(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://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",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\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",
       " * http://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",
       "    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",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\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",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             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",
       "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\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";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.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",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['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 = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\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.get(0);\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",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\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).html('<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/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<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 () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>');\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\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) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('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",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\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",
       "\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('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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JjQQEBq/fH+1EoCqHU6zywm5vJJK5fE/+fk2s8sBwh7zmwCoCQ0EGK+0sloJP3+auNnsckxz3TsrlJ+D02mfXeCAEZjfBEBNaCDAeP+br574ObvIvudD23ciX/k5fLHxiNnlAGGN+U0A1IQGAozFaVB88bMA9MH8JgBqQgMBxvph3ykl8GxJO2t2OaabvuWo8vM4kFlgdjlA2GJ+EwA1oYEAY/GOly+nU31H9Jb3VpldDhC2mN8EQE1oIMA4pwvKlLAT88Mhs8uxjKenbFd+LiWcEgYICvObAKgJDQQYp+f4TUrQqay236lf6pNbXKH8XAYvOmB2OUBYYn4TADWhgQBjeO/q/PXwdWaXYznsGge0YX4TADWhgWBbaetExt0m8vG1hixlw6+WnPc6Sc57naR61C8M2064LhUjrlF+PpUjrzG9Hvn4WpHPuorkpZvdmYBfmN8EQE1oINjWD6+IxLRlYfFddk8zuzMBvzC/CYCa0ECwLU8AXP4/kTMHdV1OJ++WhwdNlocHTZbZPyzXff2RssR8NVf5OVVk7je3nhmPufth4YtmdybgF+Y3AVATGgi25QmAcR/rvuqnvtymfL6tyobX/fXXWa+DQUw/Snrqg+5+mP6ouXUAfmJ+EwA1oYFgW0MvNiQAel/5486ha3RddySyzMEgO75098MHF5pbB+An5jcBUBMaCLY1stNPAXC0rqtdknBSCTRJZ3heNWbR3kzl57Un45x5hRxYoH4O0MG5CWF9zG8CoCY0EGzro2vcwz7rsK6rtcw7WmHC+x3T+z9eb14hxTlqAKwqN68OwE/MbwKgJjQQbMsTALMTdVtlcUW1Embe5gTHfnt84mbl51Zt1mcmK0vUAJi+wZwagAAwvwmAmtBAsCWnQx32OgbAtxcdUIJMYXmVbuuNdGcKypWf25RNJp6Hz9MTBxaYVwPgJ+Y3AVATGgi2dHKPOuyLsnRbLbt/g2eJn930R909Mau3eTUAfmJ+EwA1oYFgSxk71ACokwOZBUqAWbrvlG7rtYuxa1KUn192kUmfwZvSw90T858zZ/tAAJjfBEBNaCDYkicAjr9dt1Xe//F6JcC4XC7d1msX5VUO5ec3YPYec4rY/rnufxgARmF+EwA1oYFgS4eX6BoAnU71SNae4zfpsk47uubt5ebuBj640N0XQy8yZ/tAAJjfBEBNaCDY0rL/ugf98Ct1Wd3CePVcdqlZRbqs0442JGebew7FgkyvU8GUhX77QACY3wRATWgg2NLqd9xD/ps+uqzOEgcwRADvcwLeOyo29AVUFKsB8IgJ2wcCwPwmAGpCA8GWPAFw9TuaV+V97r/3lhzUoTh7e2LyVuXn6XSa8FnKET9dIWb3tNBvGwgA85sAqAkNBFv6po9uAXDEikQlsBRXcAkxrZLPFCk/z+/3ZIa+gE9ucvfGwhdDv20gAMxvAqAmNBBsafiV7iG/7L+aV8XuX/15fp7XDV4R+o0vfMHdGzN7hX7bQACY3wRATWgg2NL4291D/tBiTas5XVCmhJWvNx/VqTj8b/4+5edaXuUI7cZjP+RUMAgLzG8CoCY0EGzJEwAztmtazYDZe5SgUllt0jVsI1B+aaXyc520Pi20G09dQwBEWGB+EwA1oYFgS54BrzEAekLKzUNW6lQYPEzbtZ512OsygWdCu20gAMxvAqAmNBBspyhLHfAn44NezfHcEiWgrEvU73rCcJuwLlX5+Z4trgjdhh3Van+c2Bm67QIBYn4TADWhgWA72YnqgHcG//myPmafriTCVVSrl4Yb9P3+0G7801+5+2Pjx6HdLhAA5jcBUBMaCLbjCYAfXaNpNZ5w8vC4OJ0KQ02m7QZ+v/1Ppwl6N7TbBQLA/CYAakIDwXY8n/HSEAC3p+cqwWRHeq6OxcHbAq9L7GXkloZuw6sGu3vkk5tCt00gQMxvAqAmNBBsJ260e7iP7BT0Kn778XrO/RcCDqd6abh/zQr+85oBW/4/d498+svQbRMIEPObAKgJDQTbifvYPdyHXhzU3b2vV/vE5K06F4eafvXB6tCH7eNbORUMLI/5TQDUhAaC7XgC4A+vBHX3lQdPK4Ek8TTPG6OtT85Wft7HzpaEZqPZSWoAzOME37Am5jcBUBMaCLaz8SNNAbD7yFh2/4aQ02s38HPTQnhaFuVUQXtCt00gAMxvAqAmNBBsZ1S0e7AvGRDwXb0/k/byrN3614Y6PTh2Y+hD99CLfjoVzEeh2yYQAOY3AVATGgi28+X97sG+anDAd/1x/ykliJzKL9O9NNQtLiVH+bknnykKzUbH3Ojuk9hhodkeECDmNwFQExoItvPl/e7BnrI64LvePWwtu39N4H3gTe/PtoRmo4v6uftk1FWh2R4QIOY3AVATGgi28/m9QQXAaodTCSH/NzfBoOJQn4fHxYU2fK99390nX/wmNNsDAsT8JgBqQgPBVhxV6of7AwyAP+xTd/9mFZYbVCDqszXtrPLzjz9+zvgNpqxSe8VRZfz2gAAxvwmAmtBAsJWCk+pQL8oK6K43vruS3b8m8t4N/NiEzcZvsOiM2iuFp43fHhAg5jcBUBMaCLbiCYAfdAzobt5H/742Z69BxaExf/x0U2hD+Psd3P1ynBN+w3qY3wRATWgg2IoSAC8M6G5LEk4qweMkR/+aJv54nvJ72Hk0z/gNet4B3PGl8dsCAsT8JgBqQgPBVlLXBBUAbx7C7l+r8PweHp8UgqOBv33S3S8L/mn8toAAMb8JgJrQQLCVHV8EfI1X792/r3P0r+kem7BZ+X24XC5jNzatp7tXpj5k7HaAIDC/CYCa0ECwlR1fugf63H/4fZeF8ZlK4DiRV2pgcfDHwZMFyu9jT4bBRwPv/MrdL+93MHY7QBCY3wRATWgg2IonAM7v6/ddfvXBanb/Wozn9/HUl9uM3dChReo7xtWVxm4LCBDzmwCoCQ0EW5nxWEABkKN/ranXpC2h2Q1cmqcGwIpi47YDBIH5TQDUhAaCrUx/1D3MZzzm1829j/5l9691eB8NnHTGwNeuqnI1AKatNW47QBCY3wRATWgg2MqMP7mH+f75ft2824h17P61IO+TQj83baexG/MEwP3zjN0OECDmNwFQExoItuIJgAcWNHpTp9fu3/7f7glBcQjEoxNCdFLomY+7e2bm48ZuBwgQ85sAqAkNBFvxvJvjRwBcfegMu38tbH1ytvL7ycg18Pfz9SPunpn3jHHbAILA/I7gADh58mS57bbb5IILLpALLrhAunbtKitWrFC+X15eLv3795eOHTtK69atpU+fPpKVFdj1TWkg2EZlqRoAj6xv9OYPj4tj96+Feb9D2++beOM25DkVTADnjgRCgfkdwQFw6dKlsnz5cklNTZWUlBQZPHiwnHfeeXLo0CEREenXr5906tRJYmNjJT4+Xrp27Srdu3cPaBs0EGyjolgd5JUNv2PkHS5enLk7RAUiUL8bvcH4kH54CecChCUxvyM4ANalQ4cOMnXqVCkoKJDzzjtPFixQd2UlJSVJVFSUbN++3e/10UCwDe8AWNXw9Xy3HclVgkV6Dqf/sKof959Sfk+njLpGc+Fpv/9wAEKJ+W2TAOhwOGTOnDnSvHlzOXz4sMTGxkpUVJTk5+f73K5z584yduzYetdTUVEhhYWFypKZmWn7BoJNFJ3xOwA+MXlr6C43hqB5n6fxv/P3GbORyhK1b1I5FQysgwAY4QHwwIED0rp1a2nWrJm0a9dOli9fLiIis2fPlubNm9e6/T333CNvvfVWveuLiYmRqKioWoudGwg2sX++Osgd1fXezPsUI3/7yv9302GOO4euMX438IhO7r7ZNcW4bQABIgBGeACsrKyUtLQ0iY+Pl0GDBslFF10khw8fDjoA8g4gbGvfHPcQ/+jqBm+WklWkBIr44wZfaxaafbczQ/l9ZReVG7ORcbcGfAlBwGgEwAgPgDX16NFDXn755aB3AddEA8E2PAFw1p8bvNnz03ex+zeMVDmcyu9r6I+HjdnI9y8HdAUZIBSY3zYLgA888ID07dtXOQhk4cKFyveSk5M5CASoz/oRfgVAT5joOX5TiAqDVtcNXmHsbuANozgVDCyH+R3BAXDQoEESFxcnx44dkwMHDsigQYOkSZMmsmbNGhFxnwamc+fOsn79eomPj5du3bpJt27dAtoGDQTbmPGYe4B/8dt6b3Iyv0wJEmsPB3ZOTZjny7gjyu+toLRK/w0ciSUAwnKY3xEcAJ9//nmJjo6W5s2by8UXXyw9evRQwp+IeiLoDh06SKtWraR3795y5syZgLZBA8E25v7dPcBXDa73Jv+dv08JEg4nu3/DRXmVQ/m9TYxN1X8DOSlqACw8rf/6gSAwvyM4AIYCDQTb8ATABo7k9ISI7iNjQ1gY9OD53RmyG9hRrQbA49v0Xz8QBOY3AVATGgi2MfaWBgPg2eIKJUDM23UixMVBq1Erk5TfX3mVQ/8NTLjT3T/rR+i/biAIzG8CoCY0EGzD8w5OPQFwxPJEJUBUOZwhLg5a5ZdWKr+/OTsz9N/ABx3d/bPybf3XDQSB+U0A1IQGgm283949wM/W/RkxT3i4ecjKEBcGvXh+h7e+t0r/la8Z4u6f0dfpv24gCMxvAqAmNBBswxMAi2of3VtUXqWEh8kbjphQHPTgfRCP7udwXDnI3T9jb9F3vUCQmN8EQE1oINiCy6XuAq4jAE7ZlK4Eh7JKAz4/hpDIyC1Vfo+xSTqfxidjO6eCgaUwvwmAmtBAsIWTe9ThXZJb69uGn0gYIeP5PT4weoO+Kz6bqvZQLu8Sw3zMbwKgJjQQbCF5Rb3v3lRUq+eQM+xSYgiZZ7/eaVyY9/RQZrz+6wYCxPwmAGpCA8EWPAHwq9/X+tbSfaeMvYoEQmrfiXzl9xl//Jy+Kx92+U+nghmu73qBIDC/CYCa0ECwhaRl9QbA7iNj2f0bYTy/z6e+1PmkzZ/c7O6jdUP1XS8QBOY3AVATGgi24LkKSI3rADudLiUsDJi9x6TioLdHPt1kTKhfMsDdRyM66bteIAjMbwKgJjQQbGFJ/zoD4O5jeUpQSM8pNqk46C02KcuY32vsh+4++vxe/dYJBIn5TQDUhAaCLXgC4KZPfL78xOSt7P6NQC6X+s7u/81N0G/FqWvVA0EcfF4U5mJ+EwA1oYFgC4v61RkAPSHhyS90/qwYTHfn0DX6h/uiLDUA5nO9aJiL+U0A1IQGgi14hvamMcqXjp4tUQLCtiO1zw2I8DZ3V4by+z1bXKHfij+40N1L6Rv1WycQBOY3AVATGgi2MLKze2jvn698acDsPcZdNgymq3I4ld/vmNXJ+q3Y88fEts/0WycQBOY3AVATGgi24AmAOSnKlwy7YgQsw/M71nU38Oyn3L0071n91gkEgflNANSEBoItjPi5TwDMKapQgsGivZkmFwejjF2Tov81nmc+Xu85JYFQYn4TADWhgRDxSvPU3XY/BcARyxOVYFDlcJpcIIxSWF6l/J7n7srQZ6W7v3b30vvt9VkfECTmNwFQExoIEe/YFjUAVpWLiLpr8Jb3VplcHIzm+V3f/sFqfVaY+GOtfgLMwPwmAGpCAyHieQLg+NtFRKS4oloJBZPWp5lcHIz2xrx9+h7sU16gBsDyAu3rA4LE/CYAakIDIeJ5AuCEu0REZPqWo0ogKKmoNrk4GO2Y1+l+th45q32F1ZVqAExeqX19QJCY3wRATWggRLyNH/kEwDuMOEEwLM3z+350wiZ9VugJgAmz9VkfEATmNwFQExoIEW/loJ8+tN/B59xwQ5YcNLsyhMhTX27TN/TP6u3uqemP6rM+IAjMbwKgJjQQIt7Kt93Des0QWXXojBIEsov4AL9d7EjPVX7vadlF2lc4rae7p+Y8rX1dQJCY3wRATWggRDxPAFwbIz3Hb2L3rw25XC7l9/7vb+O1r9BzKpiYttrXBQSJ+U0A1IQGQsT76BqRmLbiWhOjhIAXZ+42uyqE2P0fr9cv/CctJwDCdMxvAqAmNPdNTyAAACAASURBVBAi3ic3i8S0lZzv31QCwOFT9LvdLNqbqd/u/+IcNQBWluhTIBAg5jcBUBMaCBFv3G0iMW3lw89n6Hs+OISVaq8DgEYsT9S2sqoyNQCm6HSCaSBAzG8CoCY0ECLeTwGw16BP9T0VCMLOTUNW6rcbeGQndwDc8aX2dQFBYH6HQQB0OBySkJAg586dM7uUWmggRDSXS3mnxhMA1x7OMrsqmGTS+jT9TgI+4U53b839uz7FAQFiflswAL722msydepUEXGHv3vvvVeaNGkirVu3lg0bNphbXA00ECJaTrISAO8dNF2iBy6TKofT7KpgkhKvywB+s/24tpUt+hfnAoSpmN8WDIBXXnml7N7tPspw8eLFcsUVV0hKSoq8++670r17d5Or80UDIaKdOagEwOiBy+T2D/i8lt15AqDmXogbzZHAMBXz24IBsEWLFpKZmSkiIi+99JK89tprIiJy9OhRueCCC8wsrRYaCBHtpwCY/V5niR64TGZsPWZ2RTDZ24sOKCFQ07vB6RsJgDAV89uCAbBz586yevVqcTgc0qlTJ1m2zP2B40OHDkn79u1Nrs4XDYSIdiTWJwAWa/3cF8JedmG5EgA3JGcHv6KzaWoALDipX4GAn5jfFgyAMTEx0q5dO7nxxhulc+fOUlFRISIiX3/9tXTt2tXk6nzRQIho6z7w2QUMiKi7gf80cXPwK3E61AB4lCPLEXrMbwsGQBGRBQsWyNixY5VdwSIiM2bMkCVLlphYVW00ECKZI3aESExb2TnkHhm27LDZ5cAinv16pz7nhJzUxR0A1w3VrzjAT8xviwbAmvLz880uoU40ECJZ0pzBIjFt5Zt3ekt2ocarPyBi7M04pwTA1Kyi4Ff04aXuALjiLf2KA/zE/LZgABw1apTMnTtX+f+TTz4pTZs2lSuvvFL2799vYmW10UCIZBs/fEQJgICHy+VSAmC/b+KDX9Ha990B8ONf6Fcc4CfmtwUD4FVXXSVbt24VEZE1a9ZI+/btZfXq1fLCCy/Igw8+aHJ1vmggRCqXyyWn37tKJKatbB/dx+xyYDEPj4vTflWQ1e+6A+CYG/QrDPAT89uCAbBly5Zy4sQJERF59dVX5eWXXxYRkZSUFI4CBkIk/nieHBrivgxc1sYpZpcDi1m2/7QSAHOKKoJbSeZu9UAQri+NEGN+WzAAXn755co7gNdff73Mnz9fRESSk5M5DyAQIv+YukMJgJK2zuxyYDGV1U4lAL6/9FBwK8k9ogbAs2n6Fgg0gvltwQA4YMAAiY6Olj/84Q9y4YUXSnFxsYiIzJkzR+644w6Tq/NFAyFSRQ9cpg5nAiDq8KsPVmvfDezpsRM79SsM8APz24IBsKqqSkaPHi2vvvqq7N27V/n62LFjZcoUa+2KooEQiTLPlcptA+eqw/mYhvO9IWJN2ZSuBMDSyiBPEj6ik7vH1r6vb3FAI5jfFgyA4YQGQiQa9P0B6T5wuhoAHVVmlwQLKiqvUgLgV3Hpwa1k7K0/BcAYPUsDGsX8tmgAnDVrltx7771y+eWXy/Hjx0VEZNy4cZwIGgiB6IHL1AD44aVmlwML8wTAX32wOrgVLH2NPoMpmN8WDICTJ0+Wiy66SIYNGybnn3++pKe7/7KcPn26/O53vzO5Ol80ECJNWaVDogcuk3sHTWMwo1EfLD2shMBqhzPwFWwY6e6zz6x1mU9EPua3BQPgTTfdJIsXLxYRkTZt2igB8ODBg3LhhReaWVotNBAizecbj0j0wGUyePDr7sH8fgezS4KFZReWKwFw2f7Tga/gyHo+agBTML8tGABbtmyp7Pb1DoCpqanSsmVLM0urhQZCpLl28HL3qT0GD1AHM9AATwB8eFxc4Hcuzlb77Nwx3WsD6sP8tmAAvOmmm5TP+nkHwAkTJnAaGMBADqd6ia/VU99zD+UFz5tdFizu5Vm7lb5xBXNC56EXu3vtSKz+xQH1YH5bMABOmTJFrrzySpk7d660bt1a5syZI8OGDVP+bSU0ECLJkoSTyiAvjB1HAIRf0rKLlL7Zk3Eu8BV43gHcMl7/4oB6ML8tGABFRL799lu59tprpUmTJtKkSRO58sorZerUqWaXVQsNhEhy30ex6ol9P/2leyjP72t2WQgDnr555usgTuj83f9z99q8Z/QvDKgH89uiAdCjtLRUsrOzzS6jXjQQIoXLpe7+fXnWbpFpPd1DeckAs0tDGOg5flPwVwX5po+71774jf6FAfVgfls8AFodDYRIsT09Vxngh04VqAHw4Pdml4YwEJeSo/TP6YKywO4cP50DjhByzG8LBsCsrCz5xz/+IZdffrk0a9ZMmjZt6rNYCQ2ESPHkF9t838GZ+hABEH6rdjiV/nlrwf7A7py8Qg2AlaXGFAjUwPy2YAB85JFH5Oabb5bJkyfL4sWLZcmSJT6LldBAiBSe4d1z/CYRp0MdyAcXml0awsTtH6wObjdwZYnab6V5xhQH1MD8tmAAbNOmjSQkJJhdhl9oIESCtOxiZXBvTMkRKctXB3LuEbPLQ5j4bmeG0kclFdX+39FRrfZb4lLjCgS8ML8tGABvuukm2bt3r9ll+IUGQiR4fW6C73ncvANgdaXZ5SFMeC4jGD1wmYxbmxLYnT39tmeWMcUBNTC/LRgAV69eLQ899JAcO3bM7FIaRQMhEniG9h1D17i/QABEkDy99Iu3lwd2x2+fdPfb1w8bUxhQA/PbggGwffv20rx5c2natKm0adNGOnTo4LNYCQ2EcJdbXKEM7QXxme4vZu4mACIoo1clK/1UWe30/44zH3f32+ynjCsO8ML8tmAAnD59usyYMaPexUpoIIQ774Fd5fhpYO/9Rg2AwVzaC7bl/QfFdzsz/L/jnpmcCgYhxfy2YAAMJzQQwp1nWPscubn3W/cg/qaPeYUhbHn6qcvwtf7fKWW1GgCdAbxzCASJ+W3BANi0adM6r/6Rm5vLeQABHVVU1/OhfU8A/PYv5hWHsPXGvH1KXzmdfr6DXJqnBsCKImMLBIT5LWLBANikSZM6A+CpU6ekZcuWJlRUPxoI4ezbHceVQZ1f6vVZvzlPEwARtBN5pUpfrUvM8u9OVeVqAEwK8AASIAjMbwsFwPHjx8v48eOladOmMnz4cOX/48ePl7Fjx8qf//xnuf32280u0wcNhHB2y3ur6j5x7+yn3IP48/vMKQxhz9NXf/x0k/93GtnZ3XfbJxtXGPAT5reFAuBVV10lV111lTRp0kQ6deqk/P+qq66S66+/Xh566CHZsWOH2WX6oIEQrpxOlzKkBy6scemu7/7mHsS7p5lTHMLe36fs8D23pD8mdeFIYIQM89tCAdDjd7/7nZw7d87sMvxCAyFcrTx4RhnQGbk1rr/qCYDx002pDeHv8KlCpb/2Z+b7d6fF/d19N62nscUBwvwWsWAADCc0EMLVbz9eX/91Wz2fxSIAQgNPfz379U7/7rB5HKeCQcgwvy0YAB0Oh0ydOlX+9re/SY8ePeSBBx7wWayEBkI4crnU3b/PTatjOHuG8MHvQ18cIsaDYzfW/0dGXY5tIQAiZJjfFgyAAwYMkNatW8tf//pXee211+T111/3WayEBkI42pGeqwzmgycLat/AM4SLc0JfHCJGXEqO0meZ50obv0PeUbX3CjKNLxC2xvy2YAC88MILZfny8DgNAA2EcNT7sy0NvzPjGcIlZ0NbGCKKw+tAozfm7Wv8Dk6H2nvpG4wuDzbH/LZgALz88sslJSWl8RtaAA2EcOQZyo9OqOMUHZWlBEDo5s6hawLbDfxZN3fvrY0xsiyA+S0WDIBjxoyR/v37+3/qgHqMGDFC7r77bmnTpo1cfPHF0qtXL0lOTva5TXl5ufTv3186duworVu3lj59+khWlp8nLhUaCOEn8bR6dOaWtDoCXsoqNQBW+rHbDmjAwvhMpd8Kyqoav8Owy929t+wN44uDrTG/LRIAe/fu7bO0a9dOrr76annsscdqfc9fDz/8sEyfPl0OHTok+/btk549e0rnzp2lpKREuU2/fv2kU6dOEhsbK/Hx8dK1a1fp3r2739uggRBuXpy5u+HzsyUudQ/gDy8NfXGIOOVV6uUGhy073PgdYj9099+oq4wvDrbG/LZIAHzuuef8XoKVk5MjUVFREhcXJyIiBQUFct5558mCBQuU2yQlJUlUVJRs377dr3XSQAg3nmHcbcS6um/gCYBTHwxtYYhYVw9a5v9u4LXvu/vvo2uMLwy2xvy2SAAMhbS0NImKipKDBw+KiEhsbKxERUVJfr7vSUo7d+4sY8eOrXMdFRUVUlhYqCyZmZm2byCED+9rtK48eKbuG22dQACErr6KS1f6rrSyuuEbn4xXP4Kg8WNAQEMIgDYJgE6nUx599FG59957la/Nnj1bmjdvXuu299xzj7z11lt1ricmJkaioqJqLXZuIISPNxfsUwax01nPcJ3ztHv4jr8jtMUhYhWVVyl999mGtIZvnJeuBsCc5IZvC2hAALRgALz99tvljjvuqLXceeed0r17d3n22Wdl/fr1Aa2zX79+Eh0dLZmZ6rmlggmAvAOIcOYZwjcNWVn/jRb9yz18l74ausIQ8Ty9d/07Kxq/sScA7vjC+MJgWwRACwbAQYMGSbt27eS+++6TN954Q9544w35zW9+I+3atZPXXntNHnzwQWnatKksWbLEr/UNGDBAfv7zn8vRo0d9vh7MLuCaaCCEi/zSSmUIz9mZUf8NPQFwy/jQFYeIN2plktJ/FdWOhm/sCYDL/xea4mBLzG8LBsAXX3xRhg4dWuvrH374obz44osiIvLee+/JXXfd1eB6XC6XDBgwQK644gpJTU2t9X3PQSALFy5UvpacnMxBIIhIw5YdVgZweVUDA3hSFwIgdHeuRP0D5Nsdxxu+8dLXfjoS/ZLQFAdbYn5bMAC2bdtW0tJqf04kLS1N2rZ1XyMyKSlJ2rRp0+B6/v3vf0u7du1k48aNcubMGWUpKytTbtOvXz/p3LmzrF+/XuLj46Vbt27SrVs3v2ulgRAuPMO30SMxPe++bPbvXXDAX57+u3vY2oZvuG0S1wSG4ZjfFgyAl1xyicycObPW12fOnCmXXOL+i/Dw4cNy0UUXNbieug7WiIqKkunTpyu38ZwIukOHDtKqVSvp3bu3nDlTz9GRdaCBEA7KKtVzsX2x8UjDNx7xc/fgPRkfmuJgG28vOqD0YZXDWf8Nsw6pATD/ROgKhK0wvy0YAD/88EM5//zz5dVXX5VvvvlGvvnmG3n11VelVatWMmzYMBERGTt2rPzhD38wuVIaCOFh/LpUZfAWVzRyGg5PAMxtJCgCAcouKlf6cNn+0w3f2BMA980NTXGwHea3BQOgiMi3334rXbt2lQ4dOkiHDh2ka9euMnv2bOX7ZWVlUl5ebmKFbjQQwoHfu39F1MFLAIQBPH1430exDd/Q04er3w1NYbAd5rdFA2C4oIFgdd6X4vpkdSPnVctOYtcbDPWf7/Yq/eio71yUIiLz+7r7cOwtIasN9sL8JgBqQgPB6qZsUq/CUFBa1fCNj8bx4XsYKiNXvRrNptSc+m+4fgS9CEMxvy0SADt06CBnz54VEZH27dsru37rWqyEBoLV3fLeKv93/3oC4KRfG18YbMvTjw+M3lD/jTJ3qwGw7FzIaoN9ML8tEgBnzJghFRUVyr8bWqyEBoKVVVSru3+HLTvc+B3SNxAAYbi+03Yqfemq73q/LpcaANMaOW0MEATmt0UCoEd1dbXMnDlTsrKyzC7FLzQQrGz2jgxl0OaVVDZ+hyUD3AN3wp3GFwfbSjxdqPTlrmN59d/QEwA3jAxdcbAN5rfFAqCIyPnnny/HjzdypniLoIFgZb/6YLX/u39FRFa85R644+8wtjDYnqcv//DJxvpvNOMxdz9+8dvQFQbbYH5bMADef//9snjxYrPL8AsNBKuqrHYqQ3bwogP+3ckTANfVvhQjoKe/frGt8d3AK9/mQBAYhvltwQA4b948ueaaa2TixImybds22b9/v89iJTQQrGpJwsnAdv+KiCx7gwCIkEg4ka/057YjuXXfKHmlGgAdjRzBDgSI+W3BANikSZN6l6ZNm5pdng8aCFZ1ayBH/3p4hu3a940rDPiJpz8fHFvPbuDyArUnT+0NbXGIeMxvCwbA48ePN7hYCQ0EK6pyqLt/35i3z/87fnKze9ju/Mq44oCf9Jm8teHdwN5HAm+dEPoCEdGY3xYMgLm56u6AEydOyJAhQ+R///ufbNq0ycSq6kYDwYq8d/+eKQjgkomeAHhyj3HFAT/x3g28Ne1s3Tea3N3dk988EdriEPGY3xYKgAcOHJDo6Ghp2rSp3HDDDZKQkCCXXnqptGnTRtq2bSvNmjWz3MEhNBCs6KYhKwPf/SsiMvp6AiBCytOnD4+Lq/sGS1/lQBAYgvltoQD4yCOPyGOPPSZbtmyRf/3rX3LllVfK888/L06nU5xOp/Tv319+/WtrnaCWBoLVOJwuZai+PjfB/zuWF6qDlgCIEOn92ZaGdwPv/ZYACEMwvy0UAC+88ELlKN/i4mJp0qSJxMfHK99PSkqSdu3amVVenWggWM2C+ExloGaeK/X/jqcS1EFbUWxcgYAX75NCb6lrN3BBptqXZ1NDXyAiFvPbQgGwSZMmkp2drfy/TZs2kp6ervw/KyuLo4CBRtzw7orgdv96AuCYG40pDKiHp18fnVDH57y9DwTZPS30xSFiMb8tFgBzcnKU/7dp00aOHj2q/J8ACDSsOtijf0XUAPjJTcYUB9Tj6SnbG94N7Pls6vcvh744RCzmt8UCYM+ePaV3797Su3dv+dnPfiYPPfSQ8v+ePXsSAIEGfLP9uDJITxeUBXbnHV8SAGGKtOyihk8KvfBFPgcI3TG/LRQAn3vuOb8WK6GBYCVBH/0rIhL7IUMWpnC51AOXetR1beCtE+hN6I75baEAGI5oIFhFRbVDGaLvLPbz2r/eYoe5B+yy/+pfHNCIZ7/eWf9u4OwkNQDmnzCnQEQc5jcBUBMaCFYxc9uxwK/9680TAJf/T//igEYkn1F3A8el5Ph+0+lUA+DBheYUiIjD/CYAakIDwSo8wzOo3b8iIp/+kgAIU3n6986ha2p/8/0O7v5cOSj0hSEiMb8JgJrQQLCC0spqZXh++OPh4FYyqYt7wC4ZoG9xgJ/+OX2X0sdOZ43dwHOedvfnh5eaUxwiDvObAKgJDQQrmLAuVRmcReVVwa3ks27uAXtkvb7FAX5KzylW+njx3pO+31z7PgeCQFfMbwKgJjQQrEDz7l8RNQCmb9CrLCBgnj6+achK329k7lYDYHFO3XcGAsD8JgBqQgPBbAWlVcrQ/HRtkJfK8r7aQvoGPcsDAvLanL1KP1c5nOo3nA61R9PWmlcgIgbzmwCoCQ0Es8X8cEgZmGWVjuBWkp+hDtecZH0LBAKQXVSu9PP0LUd9v+np0Y0fm1McIgrzmwCoCQ0Es+my+zcvnc9XwTLq7elvnvjpetU3mFMYIgrzmwCoCQ0EM+WVVCqDcta2YxpW9FMAHH6FbrUBwRqxIlHp65KKavUbS1/jDxXohvlNANSEBoKZ/m9egjIoK6udjd+hPid2EQBhGcUV6mmNRq1MUr9xZL0aAMt5zYU2zG8CoCY0EMzU4IlzA7F5LO+swFLq3A3sqFL7NHO3ecUhIjC/CYCa0EAwS1q2eumsZftPa1vZ1gnuofr5vfoUB2g0ZVO60t9ZheXqNzwBcMeX5hWHiMD8JgBqQgPBLI9P3Fz/VRMC5QmA37+kT3GARlUOp9Lfr83Zq35j+qPuXv2sq3nFISIwvwmAmtBAMIPL5VKG4+/HbNC+wsX9CYCwnGveXl57N/D85/i4AnTB/CYAakIDwQzrk7KVwbj7WJ72FU68xz1QZz+lfV2ATlYePKP0+dGzJe4vHlqkBkBHkJc9BIT5LUIA1IQGghm6jVin/dx/3r5+2D1Qt3+uz/oAHTid6jvdfSZvdX+xNE8NgLlHzC0QYY35TQDUhAZCqHl/NqrvtJ36rNQTAA//oM/6AJ30HL9J6XeXy+V7SbiE78wuD2GM+U0A1IQGQqjN2n5cGYjZReWN38EfH3QkAMKS9mScU/p9XWKW+4tf/s7dr9N6mlscwhrzmwCoCQ2EUNPl0m/eKkvVd1RSVumzTkBHnn6/echK9xe+6ePu1w8vNbcwhDXmNwFQExoIoXTO69JvI1Yk6rNS789UVZbqs05ARy/N3O17xZtdUzkSGJoxvwmAmtBACKWBC/crg7C0srrxO/jDOwA6NVxODjBIVmG50vefbzwikndU7dniHLPLQ5hifhMANaGBEEq67/4VESk5SwCE5fn0fnWl2rN8bhVBYn4TADWhgRAqx3NLlAH4w75T+q344PcEQFjepPVpSv+fLigTmXi3u2fn9zW7NIQp5jcBUBMaCKHS45ON+l36zduemXyeCpZXWa2e/uj56btEpj7o7tlRV5ldGsIU85sAqAkNhFDwvvTbnyZu1nflngDIVUBgcTcNWanuBt74kbtvh15sdlkIU8xvAqAmNBBCYUF8pjL4Dp/Sudd2TyMAIixsTTurPA/274pT37ku1eFyiLAd5jcBUBMaCKFgyMEfHl/8xj1Ev/2L/usGdOZ5Htwds1QNgGnrzC4LYYj5TQDUhAaC0QrLq5ShN3jRAf038O2T7iE69x/6rxvQmfc5AV2jr3f37rI3zC4LYYj5TQDUhAaC0V75bq/+5/7z5gmAe2bpv25AZ97nBMz56C5374691eyyEIaY3wRATWggGM0z7K4dvNyYDcz6MwEQYcXznJj2zk9/vHx0tdklIQwxvwmAmtBAMNL29Fxl2K08eFr/Dbhc6ueo9szUf/2AAaZuPirRA5fJXwaNUfu3nNdgBIb5TQDUhAaCke76cI36eSeXjuf+83BUqwP0ZLz+6wcM4HC6T4t008CFav+e2GV2WQgzzG8CoCY0EIxSXuVQwt9z03YasxHvAFh2zphtAAb4w08nRq98r4O7f9cPN7skhBnmNwFQExoIRhmxPFEJgOdKKo3ZCAEQYerQqQKJHrhMjg+51t2/n3UzuySEGeY3AVATGghGMfTcfx65RwiACFvRA5fJD+8+zJHACArzmwCoCQ0EI6RlFynh77udGcZt6NAiNQA6ncZtBzDAJ2tSpO/bw9QeriozuySEEeY3AVATGghG+NUHq5UA6HQacPCHx6HF7sH59cPGbQMwSGW1U24dOF8NgDnJZpeEMML8JgBqQgNBb5XVTiX8PfnFNmM35gmA0/5o7HYAg9w5dI0SAJ3bvzC7HIQR5jcBUBMaCHr7aGWSEgBP5JUau7HF/yYAIqylZhXJmfeiRWLaSta435pdDsII85sAqAkNBL2F5OAPjwXPuwPguNuM3xZgkLh37xWJaStHhtxgdikII8xvAqAmNBD0tPNonhL+FsZnGr/BhS+6A+DWicZvCzDIiu8mKruBM3J4LYZ/mN8EQE1oIOjpxndXGnvlj5o8AXDbJOO3BRik6lymEgD/NGKB2eUgTDC/CYCa0EDQS2F5lRL+np6yPTQb9Rw9SQBEOPM6ofkrb78tVQ5OaYTGMb8JgJrQQNDLSzN3KwGwqLwqNBsdepF7cO6aEprtAQZxjIwWiWkra9+9Xz5amWR2OQgDzG8CoCY0EPTgcrlCe/CHx7DL3AEw72jotgkY4cvficS0lcNDbgvtcwhhi/lNANSEBoIe5u7KUMLfzqN5oduwJwCeOxa6bQJG2PmVshs4euAy2ZiSY3ZFsDjmNwFQExoIejDl3b/qSvUzgARAhLusQ0o/Xz9wEe8ColHMbwKgJjQQtDp6tkQJf5+sSQnhhjepAbAsP3TbBYxQWaL0c9+3h0n0wGVyuoBrA6N+zG8CoCY0ELS67p0VSgAM6dGLR2LVAAhEgp8+0rDw3Z4SPXCZ/PHTTWZXBAtjfhMANaGBoEVpZbV63d/PDb7ub02eADi5e2i3Cxhl/O0iMW3lYMydyvOqsppTwqBuzG8CoCY0ELT45/RdyqDKLioP7cbjpxMAEVk2fuxzIEj0wGUy6PsDZlcFi2J+R3AAjIuLk8cee0wuv/xyiYqKksWLF/t83+VyyZAhQ+Syyy6Tli1bSo8ePSQ1NTWgbdBACJbTadKpXzwW9XMPy49/EfptA0Y4vlUJgNcOXGLecwthgfkdwQFwxYoV8s4778iiRYvqDICjRo2Sdu3ayZIlS2T//v3y+OOPy9VXXy3l5f6/E0MDIVgTY1OVAbUn41zoC1j2hntYLnwh9NsGjFB2TgmA8ZuWK8+vebtOmF0ZLIj5HcEB0FvNAOhyueSyyy6T0aNHK18rKCiQFi1ayJw5c/xeLw2EYJn67p+IGgDXjzBn+4ARPrjQ3dcrBpr/HIOlMb9tGgDT09MlKipKEhISfG7329/+Vl599VW/10sDIRirDp1RBtPC+ExzivjqAQIgIs9HV7v7elpPGbsmRXmeJZzgVEfwxfy2aQDcunWrREVFyenTp31u9+STT8pf//rXetdTUVEhhYWFypKZmWn7BkLgvN+ZcLlc5hTxQUf3oFwbY872ASOsGOju62GXmXeJRYQFAiAB0Od2jQXAmJgYiYqKqrXYuYEQmEOnCpSBNMrMi9aPucE9KI+sN68GQG/JK9XzWzqq5V+z4pXn24m8UrOrg4UQAG0aAIPdBcw7gNDK+x0Jh9Okd/9E1AB4er95NQB6K85WA+CZg1Je5VCeb7e+t8rs6mAhBECbBkDPQSBjxoxRvlZYWMhBIDDUqfwyZRi9OHO3ucV4hiQBEJHG09sbPxIRkYfHxSnPu7ySSpOLg1UwvyM4ABYXF0tCQoIkJCRIVFSUjB07VhISEiQjI0NE3KeBad++vfzwww9y4MAB6dWrF6eBgaGuHayemqK0stq8Qs4dU4dkTrJ5dQBGGHqRu7e/w9WbvAAAHzpJREFU/YuIiOSXVirPu9+P2WBubbAM5ncEB8ANGzbU+Xm9vn37ioh6IuhLL71UWrRoIT169JCUlJSAtkEDwV8FZVXKEHp4XJy5xZyMVwOgWQehAEb5/iV3b4+7VfnSbTGrlOdfcYWJf3zBMpjfERwAQ4EGgr/uGbbWOruhPAFw7K2N3xYIN/vnqX/gOB0iInKmoNy8627DkpjfBEBNaCD4o7iiWhk+d3241uxyRE7sIgAicuWfUAPguWPKl70PwCqrdJhXHyyB+U0A1IQGgj9+N3qDMnjOFPj/GVPDrH7HPRxHX292JYAxPAFw1xTlSyfySpXn4TNf7zSxOFgB85sAqAkNhMYUlquf/bvh3RVml+O29n33cPz4WrMrAYzhCYDznvX5sve7gOVVvAtoZ8xvAqAmNBAa8/sx6rt/p/LLzC7HzRMAVww0uxLAGLN6u3v8i9/6fPlITrHyfPzH1B0mFQcrYH4TADWhgdCQcyXq6SeuHbzc7HJUnl3ABEBEqt1f13uku/e7gBXVvAtoV8xvAqAmNBAa0mW4euRvdpEFPvvn8X4H92Bc/qbZlQDGyElWA2Bpns+30rLVdwF7TdpiUoEwG/ObAKgJDYT65BZXWO+zfx4T73EPxrjRZlcCGMNRrQbAQ4trfdv7XUBTT8oO0zC/CYCa0ECozy/eVq/6kV9qsctPeQLgsc1mVwIYxxMAl/Sv9a1jZ0uU5+d9H8WaUBzMxvwmAGpCA6Eu3tf8vWeYBc77V9OnvyIAIvJ9fp+7z2f2qvPb3u8CWuojGggJ5jcBUBMaCHXxHiwFZVVml+Orqkx9Z4QAiEi2dUKDlzw86/UxjeiBy0woEGZifhMANaGBUNPejHPKQHli8lazy6ntbJo6FMvyza4GMM7xrWqv59R9nff7PopVnq/pOcUhLhBmYn4TADWhgVCT9zsKldVOs8upzRMAR3YyuxLAWC6XGgDr2Q1cVungXUCbYn4TADWhgeBt3q4TyiAZ9P0Bs8upGwEQdvL5vWoIrMcLM3Ypz9v1SdkhLA5mYn4TADWhgeDhcrl83klw1fGZI0vYP48ACPtIXdvobuBqhzM8nrvQFfObAKgJDQSP1+cmKAPk+z2ZZpdTv81jG31HBIgY3ruBv3mi3pt9tiFNef6OXJEUwgJhFuY3AVATGggiIkXlVeHzOaLN49zDcFE/sysBQmP8HX790eP9HK5yWPDzu9AV85sAqAkNBBGRa7xO+pySVWR2OQ3zBMDF/za7EiA0En9sdDewiMjuY3nWPn8ndMX8JgBqQgPh4MkCZWhc/47FLvlWF8/JcQmAsAvv3cDf/a3Bm3q/C8hpYSIb85sAqAkNZG81D/worgiDa4p+9Xv3IJz7d7MrAUJnzA1+7QbOL60Mn49zQBPmNwFQExrI3ob+eFgZFDE/HDK7HP9M+YN7CCb+aHYlQOgcWqwGwNwjDd7039/GK8/ryRsavi3CF/ObAKgJDWRfYXXghzdPAEwKo5oBrZxONQDO79vITX3f2S+vcoSmRoQU85sAqAkNZF/eA+JAZoHZ5fjPMwQJgLCbUdF+nwJpS9rZ8PwDD35jfhMANaGB7GlJwkllMNwas8rscvxXkqsOwFMJZlcDhNbB79X+z89o9ObeAXBr2tkQFIhQYn4TADWhgeynstr3qgHV4XS+sOJsTgIN+/LeDbzoX43evLSy2ue57nRyhZBIwvwmAGpCA9nPdYNXKAPhh32nzC4nMARA2N3wKwJ6DkzZlM65ASMU85sAqAkNZC+xSVn+fy4ofrrInKettXzzBAEQ9pbwnfocKPFvt673c37bkVyDC0SoML8JgJrQQPZRVeOC8WWVDRwZmJeuDhkrLh9dE7ofHGAl1ZXq8+DH1/26S0FZVfh+7AP1Yn4TADWhgezDewDM3dXIB8hj2qlDZudXIru/ttaSdTg0PzTAij68JOB3wr+KS/f/3X+EBeY3AVATGsgevD8H1OiLf9k5dbh8/UhoCgTgv/gZ6nO07Jzfd/N+DVgQn2lggQgF5jcBUBMaKPKdLa7weeGvamz3z4S71OFSmheaIgH4r6pcfY6uGuz33cqrHD6vBQVlVQYWCaMxvwmAmtBAka3mtX53HWsk0Hl/vuijq0NTJIDADb0oqAOiah4I5nJxaphwxfwmAGpCA0W27iNjlRf6p77c1vgd5jytDpW8dOMLBBCcbZO8dgPnB3TX34/ZoLwu/PHTTQYVCKMxvwmAmtBAkWvOzozA/tJ3uXyPtAVgXZWl6nN1/fCA7+792rA03M4HChFhfosQADWhgSLTyfwynxf4korqxu8UO0wdKBnbjS8SgDbvdwj6D7b80kqf14icogoDCoSRmN8EQE1ooMhTXeN8f5tT/bwGKO/+AeFl48fqc7Y88NfwNYd9Pw/I+QHDC/ObAKgJDRR5vF/QB8ze49+dDixQB8n++cYWCEAflSXq8zZudFCr+Of0XZwfMEwxvwmAmtBAkaXL8LXBvZjz7h8QnnR47nq/Zvzhk406FgcjMb8JgJrQQJHj7UUHgju9w6kEdYCs+8DYIgHoa91Q9flbURzUKmp+bGTYMq60Ew6Y3wRATWigyDBv94nAD/rw8H4HwdnA9YEBWI/3buCtE4JeTVG57/WCf+DIYMtjfhMANaGBwt+O9FyfF+7juSX+37nojDo85jxtXJEAjKPTRzjSsot8Xkvij/t/mTmEHvObAKgJDRTeks/4vmD7fcSvx0fXqIOjMoDgCMA6Vg1Wn8dV5ZpWtT4p2+c1JS07uN3KMB7zmwCoCQ0Uvo6dLfF5oZ69IyOwFXjvOppwlzFFAjBeaZ76XN75lebVzdx2zOe15UReqQ5FQm/MbwKgJjRQeKoZ/sasTg58JV8/og6NwtP6FwkgdJTdwO10Wd3w5YmEQItjfhMANaGBwk9Klu9u33cXHwx8JU4Hp34BIsmy/6rPZ0cAB4E14K0F+31ea9Jz2B1sJcxvAqAmNFB42X0sz+cF+Z3FB4Jb0Y+vq8PiTJDrAGAdhafV5/Tuabqt9n/z99U4MCRPt3VDG+Y3AVATGih81DzVy4gVicGtyOXi3T8gEnme08Mu03W17y895PPas2hvpq7rR3CY3wRATWig8PB/8xJ8XoCnbzka/Mp2fqUOitQ1+hUJwFw/vKL7bmCPKZvSfV6D/jd/n67rR+CY3wRATWgg67tq0DKfF94NydnaVsi7f0BkKjipPrf3zNJ99TVPEXP1IK4dbCbmNwFQExrIusqrHD4vttEDl0lGrsYj8dI3eF01YKIeZQKwEs/z+6NrDFn90RpnIIgeuEzKq7iCkBmY3wRATWgga9p5NM+YF1nvd//8vVYwgPCxqJ/hl3Ysq6z9x+nOoxwcEmrMbwKgJjSQ9fQcv6nWi6tLj7CWe0QdDIv7a18fAOspPKU+zw8sMHRTNV+nHvl0k6Hbgy/mNwFQExrIOrKLymu9oI5bm6LfBoZerA6G6kr91gvAWjzP809/Zfimxq5JqfW6lV2k7XJ08A/zmwCoCQ1kDf+YuqP2i2ihji+i3peKmvqgfusFYD0LXzB8N7C3rMLaf7z+7avthm/X7pjfBEBNaCBz7ck4V+uF895Rsfrs8vU26dfqQCg7p++6AVhL/gn1+Z68ImSbfWDMBj4bGELMbwKgJjSQOYrKq2q9UEYPXCapWUX6b6y6Uh0Go6L1Xz8A6/E85yd1Celm07KL63xtKyqvCmkddsD8JgBqQgOFVrXDWeeL48uzdhu30XnPqMMgL9247QCwjjlPe+0GdoZ88/1n76nzta6imlPG6IX5TQDUhAYKjYrq2qdN8CyV1Qa+OHPZN8CeclLU5/2xzaaUUFld9x+8nDtQH8xvAqAmNJCxMnJL630BPJVfZnwBG0aqQyCDD2UDtuJ57n/W1dQysus4SMSzpOcUm1pbOGN+EwA1oYGMMXJFUr0veEfPloSuEN79A+xr5uOWev439AfxO4sP6H/wW4RjfhMANaGB9LM/M1+uHlT3i1v0wGVytrgitAUdWqy++CfMDu22AZjv1F71NeDELrOrUeSXVtb7OnnDuytkR3qu2SWGBeY3AVATGih4TqdLYpOy5LEJm+t9MXt++i7z/qrl3T8AnteAz+81u5JaXC6XDKjnYJHogcvkwbEbZem+U+Jw8s5gXZjfBEBNaCD/uVwuOZBZIG8u2Ce/eHt5vS9adwxdY/7nWk7vU1/4V79rbi0AzDPlD2Hxh2DmuVJ55NPal8H0Xl6bs1d2H8tjV/FPmN8EQE1ooPqdyi+T6VuOylNfbmvwRcnzwnQslJ/ta4z3u38mnAICgEUc3+a1G3in2dX45VR+mfx3/r5GX3cfm7BZJm84Yq3X3hBifhMANbF7A5VXOSTpTKHM2ZkhgxcdkD9/tkVueHdFoy88D4zeINO3HJWySgueyqDgpPqC/+1fzK4GgNk8rwdfPWB2JQGrqHbIvF0n5I+NvDvoWR4eFyf/Ny9BZm0/Lvsz86Wkotrsh2AYu89vEQKgJpHYQJXVTjlbXCFJZwplQ3K2LD9wWibGpsp/5++Tp77cJg+M2SC/fH+1Xy8mnuUfU3fI/N0npLQyDF5MPrlJfcGvLDW7GgBm+/y+sNgN7I/yKocs239a/jUrXq5p4KM4NZfbYlbJA6M3yF8+3yr/+W6vjFqZJEsSTsqaw1myPzNfTheUSWlldVjtXo7E+R0oAqAGRjVQ8pkimbIpXYb+eFgW7c2UhfGZsiA+U+btPiFzd2XIdzszZPaODPlm+3GZte2YzNh6TKZvOSpfbz4qUzalywdLD8vE2FQZvy5VxqxOlrcXHZD+3+6RQd/vl/+bmyC/G71B+k7bKfeOipVuI9bJXR+uCSjQ1bXcOXSN/O2r7TJ6VbJsSTsbnpcuqihWX+g//ZXZ1QCwgqOb1NeFTAOvOmSSskqH7DyaJ+PWpsg/p++S7iNjNc+DbiPWyXXvrJAen2yUv0/ZId1Hxsp/vtsr/5u/T16ds1f6z94jI1ckySerk2XCulR5d/FB+SouXb7efFRmbD0ms7Yfl+92Zsi8XSdkQXymHD6lf0gjABIANTGqgZbP+0IWvftHSyyL3/2jbB71Z9k4opfsGN1HDk54Uo5/9TfJnfmMlM/9p7gWvigSKYv3Z/+Kzuj6OwUQpmpeEcjs16kQLhVzn5dzs56VzKl/l6RJT8nuT/rIppG9ZPNHf5ZlMY/Konf/KD++19PwObR0zue6/1oJgARATYxqoPzlQ31fcFhCu4y9RdffJ4Aw9+1fzH9dsvGS+N3buv9KCYAEQE0Ma6ATO0W2TWIxY9n9tUhZvr6/TwDhrSzf/dpg9uuTXRcDjsAmABIANaGBAAAIP8xvAqAmNBAAAOGH+U0AlEmTJkl0dLS0aNFCunTpIjt3+v9WMw0EAED4YX7bPADOnTtXmjdvLtOmTZPDhw/LSy+9JO3bt5fs7Gy/7k8DAQAQfpjfNg+AXbp0kQEDBij/dzqdcsUVV8jIkSP9uj8NBABA+GF+2zgAVlZWSrNmzWTx4sU+X3/22Wfl8ccf92sdNBAAAOGH+W3jAHjq1CmJioqSbdu2+Xz9zTfflC5dutR5n4qKCiksLFSWzMxM2zcQAADhhgBIAAwoAMbExEhUVFStxc4NBABAuCEA2jgABrMLmHcAAQAIfwRAGwdAEfdBIP/5z3+U/zudTrnyyis5CAQAgAjG/LZ5AJw7d660aNFCZsyYIYmJifLyyy9L+/btJSsry6/700AAAIQf5rfNA6CIyMSJE6Vz587SvHlz6dKli+zYscPv+9JAAACEH+Y3AVATGggAgPDD/CYAakIDAQAQfpjfBEBNCgoKJCoqSjIzM32ODmZhYWFhYWGx7uI5i0dBQYHZUcI0BEANPA3EwsLCwsLCEn5LZmam2VHCNARADZxOp2RmZkpBQYFhf53Y7d1Fuz5uHrs9H7tdHzeP3Z6P3UqPu6CgQDIzM8XpdJodJUxDALSowkJ7fj7Bro9bhMdux8du18ctwmO342O36+O2KgKgRdn1iWLXxy3CY7fjY7fr4xbhsdvxsdv1cVsVAdCi7PpEsevjFuGx2/Gx2/Vxi/DY7fjY7fq4rYoAaFEVFRUSExMjFRUVZpcSUnZ93CI8djs+drs+bhEeux0fu10ft1URAAEAAGyGAAgAAGAzBEAAAACbIQACAADYDAEQAADAZgiAFjRp0iSJjo6WFi1aSJcuXWTnzp1ml2S4yZMny2233SYXXHCBXHDBBdK1a1dZsWKF2WWFxMmTJ+Xvf/+7dOzYUVq2bCm33nqr7N692+yydBcXFyePPfaYXH755RIVFSWLFy/2+b7L5ZIhQ4bIZZddJi1btpQePXpIamqqSdXqq7HHHhMTIzfccIO0atVK2rdvLz169JAdO3aYVK2+GnvsIiKJiYnypz/9Sdq2bSutWrWSu+++WzIyMkyoVj8jRoyQu+++W9q0aSMXX3yx9OrVS5KTk31uU15eLv3795eOHTtK69atpU+fPpKVlWVSxfrw53G//PLLcs0110jLli3loosukscff1ySkpJMqti+CIAWM3fuXGnevLlMmzZNDh8+LC+99JK0b99esrOzzS7NUEuXLpXly5dLamqqpKSkyODBg+W8886TQ4cOmV2aoc6dOyfR0dHy3HPPyc6dO+Xo0aOyevVqOXLkiNml6W7FihXyzjvvyKJFi+oMAqNGjZJ27drJkiVLZP/+/fL444/L1VdfLeXl5SZVrJ/GHvvs2bNl7dq1kp6eLocOHZIXXnhB2rZtKzk5OSZVrJ/GHvuRI0ekY8eO8uabb8revXvlyJEj8sMPP4T9a97DDz8s06dPl0OHDsm+ffukZ8+e0rlzZykpKVFu069fP+nUqZPExsZKfHy8dO3aVbp3725i1dr587i//PJLiYuLk2PHjsmePXvkT3/6k3Tq1EkcDoeJldsPAdBiunTpIgMGDFD+73Q65YorrpCRI0eaWJU5OnToIFOnTjW7DEMNHDhQ7rvvPrPLCLmaQcDlcslll10mo0ePVr5WUFAgLVq0kDlz5vz/9u43pqnrDwP46cptS+ssc+AyxgozDMQtodNIRnQaZTNZTFE3nUqMbDUhGHTrGw0m+2MwUzeNm0HcNJmwBP8sCnMhmoW4KXGuCpVuKNugEXUL4LYXamBqCfX5vVh6s0srrf5sb2mfT9IX93BP+R4x5OGcnnPVKDFi7jUL9l/+A3NPnDgRpaqiI9jYly5dihUrVqhUUfT89ddfEEKgpaUFwL//vyVJwuHDh+V7fv31Vwgh4HQ61SrzoRs57mB+/vlnCCHi8g/fWMYAGEO8Xi+0Wm3AL8iVK1eiuLhYpaqib3h4GAcPHoROp0NnZ6fa5URUXl4eHA4HFi9ejLS0NFitVuzdu1ftsiJuZBC4dOkShBBwu92K+2bNmoW333472uVFVKgA6PV6sW3bNpjNZvz9999RrCzyRo7d5/Nh3LhxqKqqwrx585CWloaCgoKQAXks8ng8EELgwoULAIDvvvsOQghcv35dcZ/FYsGOHTvUKDEiRo57pMHBQTgcDjzzzDPwer1Rri6xMQDGkN7eXggh8OOPPyra161bh4KCApWqip6Ojg6YTCZotVqYzWYcO3ZM7ZIiTq/XQ6/XY8OGDWhvb8eePXtgMBhQV1endmkRNTIInDlzBkII9PX1Ke5bsmQJ3njjjWiXF1H3CoBNTU0wmUzQaDRIT09Ha2urCtVF1six9/f3QwgBo9GIHTt2wO12Y8uWLdBoNDh16pSKlT5cPp8P8+fPx4wZM+S2/fv3Q6fTBdw7ffp0rF+/PprlRUywcfvV1NTAZDJBCIHc3FzO/qmAATCGJHoA9Hq98Hg8cLlcqKysRGpqatzPAEqShMLCQkXb2rVr8eKLL6pUUXQwAAYGwMHBQXg8HjidTtjtdmRlZY35z8GNNHLs/t95y5cvV9xns9mwbNmyaJcXMeXl5cjMzMQff/whtyVCAAw2br8bN26gu7sbLS0tsNlsmDp1alx83ncsYQCMIVwCVioqKkJZWZnaZUSUxWLBqlWrFG27d+9Genq6ShVFB5eAQy9xZmdnY/PmzVGoKHpGjt3r9SIpKQmbNm1S3Ld+/foxvxnCr6KiAhkZGejp6VG0x/sS8L3GHYzX64XRaMSBAweiUBn5MQDGmIKCAqxZs0a+9vl8eOqppxJyE8icOXNQWlqqdhkRtXz58oBNIA6HI2BWMN7caxPI9u3b5babN28m7CYQAJg0aRI++OCDyBcURcHGXlhYGLAJZOHChQGzgmPN3bt3UVFRgfT09KDHGfk3gRw5ckRu++2338b8JpBQ4w7mzp07SE5ORm1tbWSLIwUGwBhz6NAh6PV61NXV4ZdffkFZWRlSUlLG/NlQoVRWVsrHAnR0dKCyshIajQbNzc1qlxZRra2tSEpKwocffgiPx4P9+/fDaDSivr5e7dIeuoGBAbjdbrjdbggh5M98+c9727p1K1JSUvDNN9+go6MDCxYsiJtjYEYb++DgIDZs2ACn04krV67A5XLhrbfegl6vj4tjkEL93BsbGyFJEvbu3QuPx4Pq6mpotVqcPn1a5cr/P6tXr4bZbMapU6fQ398vv27duiXfU15eDovFgu+//x4ulwuFhYVj/o+/UOO+dOkSNm/eDJfLhatXr+LMmTOw2WyYMGFC3H3kIdYxAMag6upqWCwW6HQ6FBQUxM2BsKOx2+3IzMyETqdDWloaioqK4j78+TU1NeH555+HXq/H5MmT43YX8MmTJyGECHj5Z3n9B0E/8cQT0Ov1KCoqQldXl7pFPySjjf327dtYtGgR0tPTodPp8OSTT6K4uDhuNoGE+rkDwBdffIHs7GwYDAbk5+fj6NGj6hX8kAQbsxBCMcvlPwj6scceg9FoxKJFi9Df369e0Q9BqHH39vbi1VdfxcSJEyFJEjIyMlBSUhJwWDRFHgMgERERUYJhACQiIiJKMAyARERERAmGAZCIiIgowTAAEhERESUYBkAiIiKiBMMASERERJRgGACJiIiIEgwDIBHRA9izZw8yMjKg0WjwySefhNXn8uXLQZ95TEQUbQyARKSa0tJSLFiwIKDd//SI69evq1BVaDdv3oQkSaiurkZfXx/++eefsPoxABJRrGAAJCLVqB0Ah4aGHqjfhQsXIIRAT0/PffVjACSiWMEASESquZ8AeOTIEUyZMgU6nQ6ZmZnYvn27oo8QAl9//bWizWw2y88g9YevQ4cOYdasWdDr9Yrnsv7X1atXUVxcDJPJhEcffRRLlizBtWvXAAC1tbUBzzm9fPly0Pc5d+4crFYr9Ho9pk2bhsbGRkUAHB4eht1uR1ZWFgwGA3JycvDpp5/K/VtaWpCUlBTwfNh33nkHM2fODPo9iYjCwQBIRKoJNwC6XC488sgjqKqqQldXF2pra5GcnKwIcOEGwKysLDQ0NKCnpwd9fX0B39vn88FqtWLmzJlwuVw4e/Yspk2bhtmzZwMAbt26hRMnTkAIgdbWVvT392N4eDjgfQYGBpCWloaSkhJcvHgRTU1NmDRpkiIADg0N4f3330dbWxt6enpQX18Po9GIr776Sn6fnJwcfPzxx/L10NAQUlNTsW/fvvD+kYmIgmAAJCLVlJaWQqvVwmQyKV4Gg0ERAEtKSvDKK68o+q5btw5TpkyRr8MNgP+dYQumubkZWq0Wv//+u9zW2dkpBz4AcLvdo878Af9uEnn88cdx+/Ztue2zzz4LuQRcUVGB119/Xb7+6KOPkJeXJ183NDRg3LhxGBwcHHUcRESjYQAkItWUlpbi5ZdfhsfjUbzq6+sVAfCFF17Axo0bFX2PHj0KSZLk2bdwA+APP/wwak07d+5EVlZWQHtKSgq+/PJLAOEFQIfDgTlz5ijafvrpp4AAuGvXLkydOhWpqakwmUyQJAnTp0+Xv/7nn39CkiQ4nU4AgM1mg91uH3UMREShMAASkWrCXQIOJwBqNBo0NjYq7jEajQEBMNQGjGgGwIMHD8JgMKCmpgbt7e3weDwoKytDfn6+ot9rr72GsrIyXLt2DUlJSSFDLBFRKAyARKSacAPgvZaAn3vuOfl64sSJqKmpka+7u7shhLjvADjaEnBbWxuAB18C/vzzzxU1rFmzBnPnzlX0KyoqCgiAx48fh9lsRlVVFXJzc0etn4goHAyARKSacAPg+fPnFZtA6urqAjaBLFu2DHl5eWhvb0dbWxvmzp0LSZLuOwDevXsXVqsVL730Es6fP49z584pNoEA4QXAgYEBpKamYsWKFejs7MSxY8eQnZ2tqGHnzp0YP348vv32W3R1deHdd9/F+PHjAwKgz+fD008/DZ1Oh61bt45aPxFROBgAiUg1D3IMjCRJsFgs2LZtm6JPb28v5s2bB5PJhGeffVaeNbvfAAiMfgwMEF4ABACn04n8/HzodDpYrVY0NDQoarhz5w7efPNNmM1mpKSkYPXq1aisrAwIgADw3nvvQavVBt25TER0vxgAiYjGALvdDpvNpnYZRBQnGACJiGLYjRs3cPr0aRgMBjQ3N6tdDhHFCQZAIqIYNnv2bCQnJ8PhcKhdChHFEQZAIiIiogTDAEhERESUYBgAiYiIiBIMAyARERFRgmEAJCIiIkowDIBERERECYYBkIiIiCjBMAASERERJRgGQCIiIqIEwwBIRERElGD+BwF4dtX3lP1JAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.ticker import FuncFormatter\n",
    "\n",
    "df = pd.DataFrame([h * 60 + m * 1 for h in range(24) for m in range(60)], columns=['time_of_day'])\n",
    "df.set_index('time_of_day', inplace = True)\n",
    "\n",
    "def old_brightness(t):\n",
    "    def f(h):\n",
    "        if h < 6:\n",
    "            return 1\n",
    "        elif h < 9:\n",
    "            return 6\n",
    "        elif h < 17:\n",
    "            return 36\n",
    "        elif h < 18:\n",
    "            return 20\n",
    "        elif h < 19:\n",
    "            return 8\n",
    "        return 1\n",
    "    # linear interpolation for the ending 30m\n",
    "    h, m = t//60, t%60\n",
    "    p, q = m / 60, (60 - m) / 60\n",
    "    return q * f(h) + p * f(h+1)\n",
    "\n",
    "def brightness(s, y, m , d, t):\n",
    "    normalized = (s.irradiance(epoch(y, m, d, t//60, t%60, tz=tz)) + 1) / 2\n",
    "    normalized = math.pow(normalized, math.e)\n",
    "    min_b, max_b = 1, 42\n",
    "    return min_b + (max_b - min_b) * normalized\n",
    "\n",
    "def tick_format(x, pos):\n",
    "    return int(x // 60)\n",
    "\n",
    "df['brightness_eq1_new'] = df.index.map(lambda t: brightness(s_hyd, 2020, 5, 21, t))\n",
    "df['brightness_eq1_old'] = df.index.map(lambda t: old_brightness(t))\n",
    "%matplotlib notebook\n",
    "ax = df.plot(drawstyle='steps')\n",
    "\n",
    "ax.legend(['New', 'Old'])\n",
    "ax.xaxis.set_major_formatter(FuncFormatter(tick_format))\n",
    "ax.set_xlabel(\"Hour of day\")\n",
    "ax.set_ylabel(\"Brightness\");"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "temp",
   "language": "python",
   "name": "temp"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}