Predavanje 03 - Moduli, numpy, matplotlib.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
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   },
   "source": [
    "<font size=\"2\"> [github.com/jankoslavic/pypinm](http://github.com/jankoslavic/pypinm)</font>\n",
    "\n",
    "<center>\n",
    "<img width=300 src=\"./fig/ladisk.png\">\n",
    "<br>\n",
    "<font size=\"7\" color=\"f00e0e\" face=\"garamond\"><b>Moduli, numpy, matplotlib</b></font>\n",
    "<br><br>\n",
    "<font size=\"4\">\n",
    "[izr. prof. dr. Janko Slavič](http://www.ladisk.si/~slavic)\n",
    "</font>\n",
    "<br><br>\n",
    "<font size=\"2\">November 2017</font>\n",
    "</center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    },
    "toc": "true"
   },
   "source": [
    "# Table of Contents\n",
    " <p><div class=\"lev1 toc-item\"><a href=\"#Moduli-(nadaljevanje)\" data-toc-modified-id=\"Moduli-(nadaljevanje)-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Moduli (nadaljevanje)</a></div><div class=\"lev2 toc-item\"><a href=\"#Upravljalnik-paketov-conda\" data-toc-modified-id=\"Upravljalnik-paketov-conda-11\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>Upravljalnik paketov <code>conda</code></a></div><div class=\"lev2 toc-item\"><a href=\"#Upravljalnik-paketov-pip\" data-toc-modified-id=\"Upravljalnik-paketov-pip-12\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>Upravljalnik paketov <code>pip</code></a></div><div class=\"lev1 toc-item\"><a href=\"#Modul-numpy\" data-toc-modified-id=\"Modul-numpy-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Modul <code>numpy</code></a></div><div class=\"lev2 toc-item\"><a href=\"#Osnove-modula-numpy\" data-toc-modified-id=\"Osnove-modula-numpy-21\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>Osnove modula <code>numpy</code></a></div><div class=\"lev2 toc-item\"><a href=\"#Osnove-matričnega-računanja\" data-toc-modified-id=\"Osnove-matričnega-računanja-22\"><span class=\"toc-item-num\">2.2&nbsp;&nbsp;</span>Osnove matričnega računanja</a></div><div class=\"lev2 toc-item\"><a href=\"#Vektorizacija-algoritmov\" data-toc-modified-id=\"Vektorizacija-algoritmov-23\"><span class=\"toc-item-num\">2.3&nbsp;&nbsp;</span>Vektorizacija algoritmov</a></div><div class=\"lev1 toc-item\"><a href=\"#Modul-matplotlib\" data-toc-modified-id=\"Modul-matplotlib-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Modul <code>matplotlib</code></a></div><div class=\"lev2 toc-item\"><a href=\"#Osnovna-uporaba\" data-toc-modified-id=\"Osnovna-uporaba-31\"><span class=\"toc-item-num\">3.1&nbsp;&nbsp;</span>Osnovna uporaba</a></div><div class=\"lev2 toc-item\"><a href=\"#Interaktivna-uporaba\" data-toc-modified-id=\"Interaktivna-uporaba-32\"><span class=\"toc-item-num\">3.2&nbsp;&nbsp;</span>Interaktivna uporaba</a></div><div class=\"lev2 toc-item\"><a href=\"#Napredna-uporaba\" data-toc-modified-id=\"Napredna-uporaba-33\"><span class=\"toc-item-num\">3.3&nbsp;&nbsp;</span>Napredna uporaba</a></div><div class=\"lev2 toc-item\"><a href=\"#Uporaba-primerov-iz-matplotlib.org\" data-toc-modified-id=\"Uporaba-primerov-iz-matplotlib.org-34\"><span class=\"toc-item-num\">3.4&nbsp;&nbsp;</span>Uporaba primerov iz <code>matplotlib.org</code></a></div><div class=\"lev1 toc-item\"><a href=\"#Nekaj-vprašanj-za-razmislek!\" data-toc-modified-id=\"Nekaj-vprašanj-za-razmislek!-4\"><span class=\"toc-item-num\">4&nbsp;&nbsp;</span>Nekaj vprašanj za razmislek!</a></div><div class=\"lev1 toc-item\"><a href=\"#Dodatno\" data-toc-modified-id=\"Dodatno-5\"><span class=\"toc-item-num\">5&nbsp;&nbsp;</span>Dodatno</a></div><div class=\"lev2 toc-item\"><a href=\"#numba\" data-toc-modified-id=\"numba-51\"><span class=\"toc-item-num\">5.1&nbsp;&nbsp;</span><code>numba</code></a></div><div class=\"lev2 toc-item\"><a href=\"#matplotlib:-animacije,-povratni-klic,-XKCD-stil\" data-toc-modified-id=\"matplotlib:-animacije,-povratni-klic,-XKCD-stil-52\"><span class=\"toc-item-num\">5.2&nbsp;&nbsp;</span><code>matplotlib</code>: animacije, povratni klic, XKCD stil</a></div><div class=\"lev2 toc-item\"><a href=\"#Za-najbolj-zagrete\" data-toc-modified-id=\"Za-najbolj-zagrete-53\"><span class=\"toc-item-num\">5.3&nbsp;&nbsp;</span>Za najbolj zagrete</a></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "slide"
    }
   },
   "source": [
    "# Moduli (nadaljevanje)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Poleg vgrajenih modulov in tistih, ki jih pripravimo sami, obstaja še velika množica modulov, ki jih lahko najdemo na spletu in Pythonu dodajajo nove funkcionalnosti. Šele ti moduli naredijo ekosistem Pythona tako uporaben."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "[Anaconda](https://www.anaconda.com/download/) je najbolj popularna distribucija Pythona in ima vključenih že veliko modulov (za podroben seznam glejte to [povezavo](https://docs.anaconda.com/anaconda/packages/pkg-docs)); predvsem pa ima vključene vse bistvene. Najbolj pomembne na področju inženirskih ved bomo spoznali v okviru te knjige."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Modul je tehnično gledano ena datoteka, kadar nek večji modul vsebuje več modulov, pa lahko začnemo govoriti o *paketih*. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Module oz pakete lahko *posodabljamo* ali nameščamo *nove*, pri tem nam pomagajo t. i. *upravljalniki paketov* (angl. *package manager*). Najbolj pogosto uporabljamo:\n",
    "\n",
    "* `pip`: [dokumentacija](https://pip.pypa.io/en/stable/),\n",
    "* `conda`: [dokumentacija](https://conda.io/docs/).\n",
    "\n",
    "Upravljalnika paketov nista povsem ekvivalentna, pogosto uporabo si bomo pogledali spodaj."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Upravljalnik paketov `conda`\n",
    "`conda` uporabljamo predvsem za module/pakete vključene v distribucijo *Anaconda*, in ima še nekatere dodatne sposobnosti (npr. kreiranje navideznega okolja, angl. *virtual environment*)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Če želimo posodobiti vse nameščene pakete znotraj distribucije Anaconda, najprej posodobimo samo `conda`, nato pa pakete. V ukazni vrstici izvedemo sledeča ukaza:\n",
    "```\n",
    "conda update conda\n",
    "conda update --all\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Kateri paketi so nameščeni, preverimo z ukazom (v ukazni vrstici):\n",
    "```\n",
    "conda list\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Namesto izhoda v ukazno vrstico bomo večkrat uporabljali možnost *Jupyter notebooka*, ko s pomočjo klicaja (!) v celici s kodo izvedemo ukaz v ukazni vrstici  (gre za kratko obliko magičnega ukaza `%se` - shell execute, glejte [dokumentacijo](http://ipython.readthedocs.io/en/stable/interactive/magics.html#magic-sx)). Opomba: dva klicaja bi vrnila celoten rezultat neposredno v notebook (ker je izpis zelo dolg, smo se temu izognili).\n",
    "\n",
    "Poglejmo primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['# packages in environment at c:\\\\Users\\\\Janko\\\\Anaconda3:',\n",
       " '#',\n",
       " '_ipyw_jlab_nb_ext_conf    0.1.0            py36he6757f0_0  ',\n",
       " 'alabaster                 0.7.10           py36hcd07829_0  ',\n",
       " 'anaconda                  custom           py36h363777c_0  ']"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rezultat = !conda list\n",
    "rezultat[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Pakete namestimo z ukazom (v ukazni vrstici):\n",
    "```\n",
    "conda install [ime paketa]\n",
    "```\n",
    "in odstranimo z:\n",
    "```\n",
    "conda remove [ime paketa]\n",
    "```\n",
    "Za več glejte [dokumentacijo](https://conda.io/docs/user-guide/getting-started.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Upravljalnik paketov `pip`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`pip` je upravljalnik paketov z daljšo zgodovino kot `conda`; podpira bistveno več paketov ([pypi.org](https://pypi.org)), vendar ni tako odporen na nezdružljivosti kakor `conda`. Razlik je še več, vendar tukaj ne bomo šli v podrobnosti; uporabljate tistega, ki vam namesti željeni paket!\n",
    "\n",
    "Podobno kot pri `conda`, tudi tukaj že nameščene pakete najdemo z ukazom v ukazni vrstici ([dokumentacija](https://pip.pypa.io/en/stable/reference/pip_list/)):\n",
    "```\n",
    "pip list\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Pakete s `pip` namestimo z:\n",
    "```python\n",
    "pip install [ime_paketa]\n",
    "```\n",
    "\n",
    "posodobimo z:\n",
    "```python\n",
    "pip install [ime_paketa] --upgrade\n",
    "```\n",
    "\n",
    "in odstranimo z:\n",
    "```python\n",
    "pip uninstall [ime_paketa]\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Primer namestitve paketa\n",
    "\n",
    "Sicer pa pakete najpogosteje najdemo na spletu ([pypi.org](https://pypi.org)). Pojdite na omenjeni portal in poiščite pakete na temo snemanja posnetkov iz portala [www.youtube.com](https://www.youtube.com).  Z iskanjem \"youtube download\" najdemo obetaven paket `youtube_dl`, ki ga namestimo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Collecting youtube_dl',\n",
       " '  Downloading youtube_dl-2017.11.15-py2.py3-none-any.whl (1.7MB)',\n",
       " 'Installing collected packages: youtube-dl',\n",
       " '  Found existing installation: youtube-dl 2017.11.6',\n",
       " '    Uninstalling youtube-dl-2017.11.6:',\n",
       " '      Successfully uninstalled youtube-dl-2017.11.6',\n",
       " 'Successfully installed youtube-dl-2017.11.15']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "!!pip install \"youtube_dl\" --upgrade"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Sedaj modul uporabimo (za podrobnosi uporabe glejte [dokumentacijo](http://rg3.github.io/youtube-dl/)). Najprej uvozimo celotni paket:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import youtube_dl\n",
    "yt = youtube_dl.YoutubeDL() # kreiramo instanco objekta (kaj to točno pomeni, spoznamo pozneje)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Prenesemo poljubni video:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[youtube] 7VGiJN-sCKk: Downloading webpage\n",
      "[youtube] 7VGiJN-sCKk: Downloading video info webpage\n",
      "[youtube] 7VGiJN-sCKk: Extracting video information\n",
      "[youtube] 7VGiJN-sCKk: Downloading MPD manifest\n",
      "[download] HOZENTREGARJI- JUTR TOČIMO ZASTONJ-7VGiJN-sCKk.mp4 has already been downloaded\n",
      "[download] 100% of 8.14MiB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yt.download(url_list = ['7VGiJN-sCKk'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Modul ``numpy``"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Kakor je omenjeno zgoraj, so v okviru *Anaconda* distribucije Pythona že nameščeni praktično vsi pomembni moduli. V kolikor bi namestili Python *the hard way*, bi sicer morali modul ``numpy`` namestiti posebej (glejte [spletno stran `numpy`](http://www.numpy.org))."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Osnove modula `numpy`\n",
    "\n",
    "Najprej uvozimo modul (uveljavljeno je, da ga uvozimo v kratki obliki `np`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Gre za enega najbolj pomembnih modulov. Na kratko: gre za visoko optimiran modul za numerične izračune!\n",
    "\n",
    "Poglejmo si najprej sintakso za vektor ničel ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.zeros.html)):\n",
    "```python\n",
    "numpy.zeros(shape, dtype=float, order='C')\n",
    "```\n",
    "argumenti so:\n",
    "\n",
    "* `shape` definira obliko (lahko večdimenzijsko numerično polje),\n",
    "* `dtype` definira tip podatka,\n",
    "* `order` definira vrstni red (lahko je C ali F kot Fortran)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ali pa:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0.,  0.,  0.],\n",
       "       [ 0.,  0.,  0.,  0.,  0.]])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros((3,5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Podobno kot `zeros` se obnaša `ones`, vendar je namesto ničel vrednost 1 ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ones.html#numpy.ones)). \n",
    "\n",
    "Poglejmo si primer, kjer definiramo tudi tip `int` (privzeti tip je `float`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 1, 1])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones(4, dtype=int)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Pogosto bomo tudi uporabljali razpon vrednosti `arange` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.arange.html)):\n",
    "```python\n",
    "numpy.arange([start, ]stop, [step, ]dtype=None)\n",
    "```\n",
    "kjer so argumenti:\n",
    "\n",
    "* `start` začetna vrednost razpona (privzeto 0),\n",
    "* `stop` končna vrednost razpona,\n",
    "* `step` korak in \n",
    "* `dtype` tip vrednosti (če tip ni podan, se vzame tip ostalih argumetnov, npr. `step`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo primer razpona od 0 do 9 (kakor vedno pri Pythonu *od* je vključen, *do* pa ni):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4, 5, 6, 7, 8])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ali pa od 7 do 12 po koraku 2, vendar število s plavajočo vejico:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  7.,   9.,  11.])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(7, 12, 2, dtype=float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Še eno funkcijo bomo pogosto uporabili, to je `linspace` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.linspace.html)):\n",
    "```python\n",
    "numpy.linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None)\n",
    "```\n",
    "ki definiranemu razponu vrne numerično polje vrednosti na enaki razdalji (ekvidistanten razmik)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Argumenti so:\n",
    "\n",
    "* `start` začetna vrednost razpona,\n",
    "* `stop` končna vrednost razpona,\n",
    "* `num` število točk/vozlišč, \n",
    "* `endpoint` ali je vrednost pri `stop` vključena ali ne,\n",
    "* `retstep` v primeru `True` vrne funkcija terko `(rezultat, korak)`\n",
    "* `dtype` tip vrednosti (če tip ni podan, se vzame tip ostalih argumetnov, npr. `step`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer generiranja 10 točk na razponu od $-\\pi$ do vključno $+\\pi$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-3.14159265, -2.44346095, -1.74532925, -1.04719755, -0.34906585,\n",
       "        0.34906585,  1.04719755,  1.74532925,  2.44346095,  3.14159265])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linspace(-np.pi, np.pi, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mimogrede smo zgoraj spoznali, da ima `numpy` vgrajene konstante (npr. $\\pi$): "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo še vgrajene funkcije za generiranje naključnih števil. Te najdemo v `numpy.random` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/routines.random.html)). \n",
    "\n",
    "Najprej si poglejmo funkcijo `numpy.random.seed()`, ki se uporablja za ponastavitev generatorja naključnih števil ([dokumetnacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.seed.html#numpy.random.seed)). To pomeni, da lahko z istim semenom (angl. *seed*) različni uporabniki generiramo ista naključna števila!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Spodnja vrstica:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.random.seed(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "bo povzročila, da bo klic generatorja naključnih števil z enakomerno porazdelitvijo `numpy.random.rand()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.random.rand.html#numpy.random.rand)) vedno rezultiral v iste vrednosti:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.5488135 ,  0.71518937,  0.60276338])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.rand(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Preizkusimo ali je res, kar smo zapisali, in ponastavimo seme in kličimo generator:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.5488135 ,  0.71518937,  0.60276338])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "np.random.random(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Zapis matrik in vektorjev"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Matrika je dimenzije ``m x n``, kjer je na prvem mestu ``m`` število vrstic in ``n`` število stolpcev. Primer definiranja matrike dimenzije `m x n = 3 x 2` je: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.,  0.],\n",
       "       [ 0.,  0.],\n",
       "       [ 0.,  0.]])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.zeros((3, 2))\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Vektor je lahko zapisan kot **vrstični vektor**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.zeros(3) # (1 x 3)\n",
    "b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "ali kot **stolpični vektor**:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.],\n",
       "       [ 0.],\n",
       "       [ 0.]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = np.zeros((3, 1)) # 3 x 1\n",
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "V modulu ``numpy`` lahko vektorje in matrike zapisujemo kot:\n",
    "\n",
    "* `numpy.array` (priporočeno, [dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.array.html)),\n",
    "* `numpy.matrix` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.matrix.html)). \n",
    "\n",
    "Priporočena je prva oblika (`numpy.array`), ki pa ne sledi povsem matematičnemu zapisu (več o tem pozneje), nam pa omogoča **enostavnejše** programiranje in je tudi numerično **bolj učinkovit** pristop ([vir](http://wiki.scipy.org/NumPy_for_Matlab_Users#head-e9a492daa18afcd86e84e07cd2824a9b1b651935)). Pristopa `numpy.matrix` tukaj ne bomo obravnavali."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "V angleškem jeziku bomo *array* prevajali kot **večdimenzijsko numerično polje** ali včasih **večdimenzijske sezname** (ker imajo nekatere podobnosti z navadnimi seznami). Nekatere knjige *array* tukaj prevajajo kot *tabela*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Rezanje\n",
    "\n",
    "**Rezanje** (angl. *slicing*) seznamov smo si že pogledali v poglavju Uvod v Python. Podobno rezanje, vendar bolj splošno, velja tudi za numerična polja modula `numpy`. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Sintaksa rezanja ([dokumentacija](http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html)) je:\n",
    "```python\n",
    "numpy_array[od:do:korak]\n",
    "```\n",
    "pri tem velja:\n",
    "\n",
    "* indeksiranje se začne z 0 (kot sicer pri Pythonu),\n",
    "* **`od`** pomeni **>=**,\n",
    "* **`do`** pomeni **<**,\n",
    "* `od`, `do`, `korak` so opcijski parametri,\n",
    "* če parameter `od` ni podan, pomeni od *začetka*,\n",
    "* če parameter `do` ni podan, pomeni do vključno zadnjega,\n",
    "* če parameter `korak` ni podan, pomeni korak 1."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer od elementa 3 do elementa 8 po koraku 2:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 5, 7])"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.arange(10)\n",
    "b[3:8:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer od elementa 3 naprej:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 4, 5, 6, 7, 8, 9])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[3:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer od elementa 3 naprej, vendar vsak tretji:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([3, 6, 9])"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[3::3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer zadnjih 5 elementov, vendar vsak drugi:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 7, 9])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[-5::2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Primer zadnjih 5 elementov brez zadnjih 2, vendar vsak drugi:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 7])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b[-5:-2:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### Poglejmo si še rezanje večdimenzijskega numeričnega polja. \n",
    "\n",
    "Večdimenzijsko rezanje izvedemo tako, da dimenzije ločimo z vejico:\n",
    "```python\n",
    "numpy_array[rezanje0, rezanje1,...]\n",
    "```\n",
    "kjer `rezanje0` reže indeks 0 (prvo dimenzijo) v obliki `od:do:korak`, `rezanje1` reže indeks 1 (drugo dimenzijo) in tako naprej."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo si primer; najprej pripravimo seznam 15 števil (`np.arange`), nato z metodo `reshape()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.reshape.html)) spremenimo obliko v matriko `3 x 5`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1,  2,  3,  4],\n",
       "       [ 5,  6,  7,  8,  9],\n",
       "       [10, 11, 12, 13, 14]])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(15)\n",
    "a = a.reshape((3,5))\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Obliko numeričnega polja lahko preverimo z atributom `shape` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.ndarray.shape.html))."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 5)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Atribute bomo sicer podrobno spoznali pri obravnavi razredov."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Prikažimo vrstice z indeksom 0:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Isti rezultat bi dobili z prikazom vrstice z indeksom 0 in vseh stolpcev:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4])"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0,:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Pogosto želimo dostopati do stoplcev, npr. stolpca z indeksom 1 (torej režemo vse vrstice in stolpec z indeksom 1):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  6, 11])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:,1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo si še primer rezanja prvih dveh vrstic in zadnjih dveh stolpcev:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[3, 4],\n",
       "       [8, 9]])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:2, -2:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podobna logika se uporabi pri dimenzijah višjih od 2."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Operacije nad numeričnimi polji"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Poglejmo si sedaj bolj podrobno nekatere osnovne prednosti numeričnega polja `numpy.array` v primerjavi z navadnim seznamom Python.\n",
    "\n",
    "Najprej pripravimo navaden Pythonov seznam:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = [1, 2, 3, 4, 5, 6, 7]\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "In nato še numerično polje `numpy.array` (kar iz seznama `a`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6, 7])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = np.array(a)\n",
    "b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ko izpišemo `b`, smo opozorjeni, da gre za `array([...])`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Pogljemo, kako se obnaša Pythonov seznam pri množenju:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3, 4, 5, 6, 7, 1, 2, 3, 4, 5, 6, 7]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2*a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Opazimo, da se podvoji seznam, ne pa vrednosti, kar bi morebiti pričakovali."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo, kako se pri množenju obnaša numerično polje `numpy.array`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 2,  4,  6,  8, 10, 12, 14])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "2*b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Opazimo, da se podvojijo vrednosti; tako kakor bi pričakovali, ko množimo na primer skalarno vrednost in vektor!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Aritmetične operacije\n",
    "\n",
    "Izbor aritmetičnih operacij, ki jih ``numpy`` izvaja na nivoju posameznega elementa, je (po naraščajoči prioriteti):\n",
    "\n",
    "* `x + y` vsota,\t \t \n",
    "* `x - y` razlika,\t \t \n",
    "* `x * y` produkt,\t \t \n",
    "* `x / y` deljenje,\t \t \n",
    "* `x // y` celoštevilsko deljenje (rezultat je celo število zaokroženo navzdol),\n",
    "* `x % y` ostanek pri celoštevilskem deljenju,\t \n",
    "* `x ** y`\tvrne `x` na potenco `y`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  3,   4,   3,   0,  -5, -12, -21])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b + 3*b - b**2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Vse aritmetične operacijo so sicer navedene v [dokumentaciji](https://docs.scipy.org/doc/numpy/reference/routines.math.html#arithmetic-operations) in namesto kratkih oblik imamo tudi *dolge*, npr: `numpy.power(x, y)` namesto `x**y`; primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1,  4,  9, 16, 25, 36, 49], dtype=int32)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.power(b, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Mimogrede opazimo, da je rezultat tipa `int32` (integer). Ko smo ustvarili ime `b`, smo namreč ustvarili numerično polje z elementi tipa `int32`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Matematične funkcije\n",
    "\n",
    "`numpy` ponuja praktično vse potrebne matematične (in druge) operacije, navedimo jih po skupinah, kot so strukturirane v [dokumentaciji](https://docs.scipy.org/doc/numpy/reference/routines.math.html#mathematical-functions):\n",
    "\n",
    "* [trigonometrične funkcije](https://docs.scipy.org/doc/numpy/reference/routines.math.html#trigonometric-functions),\n",
    "* [hiperbolične](https://docs.scipy.org/doc/numpy/reference/routines.math.html#hyperbolic-functions),\n",
    "* [funkcije za zaokroževanje](https://docs.scipy.org/doc/numpy/reference/routines.math.html#rounding),\n",
    "* [funkcije za vsoto, produkt in odvod](https://docs.scipy.org/doc/numpy/reference/routines.math.html#sums-products-differences),\n",
    "* [eksponenti in logaritmi](https://docs.scipy.org/doc/numpy/reference/routines.math.html#exponents-and-logarithms),\n",
    "* [posebne](https://docs.scipy.org/doc/numpy/reference/routines.math.html#other-special-functions) ter [preostale](https://docs.scipy.org/doc/numpy/reference/routines.math.html#miscellaneous) funkcije."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo primer funkcije $\\sin()$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  0.00000000e+00,   1.00000000e+00,   1.22464680e-16,\n",
       "        -1.00000000e+00,  -2.44929360e-16])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.linspace(0, 2*np.pi, 5)\n",
    "np.sin(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "source": [
    "Poglejmo še hitrost izvajanja:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.36 µs ± 338 ns per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n100 np.sin(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Podatkovni tipi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "``numpy`` ima vnaprej definirane podatkovne tipe (statično). Celoten seznam možnih tipov je naveden v [dokumentaciji](http://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html).\n",
    "\n",
    "Osredotočili se bomo predvsem na sledeče tipe:\n",
    "\n",
    "* ``int`` - celo število (poljubno veliko)\n",
    "* ``float`` - število s plavajočo vejico ([dokumentacija](https://docs.python.org/dev/library/functions.html#float))\n",
    "* ``complex`` - kompleksno število s plavajočo vejico\n",
    "* ``object`` - python objekt."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo si nekaj primerov (cela števila, število s plavajočo vejico in kompleksna števila):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3, 4])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(5, dtype=int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  1.,  2.,  3.,  4.])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(5, dtype=float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.+0.j,  1.+0.j,  2.+0.j,  3.+0.j,  4.+0.j])"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(5, dtype=complex)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Spreminjanje elementov numeričnega polja (`numpy.array`)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Podatke spreminjamo na podoben način kakor pri navadnih seznamih; v kolikor uporabljamo rezanje, moramo paziti, da so na levi in desni strani enačaja podatki iste oblike (`array.shape`)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo si primer, ko matriki ničel dimenzije `3 x 4` spremenimo element z indeksom `[2, 3]`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   0.,    0.,    0.,    0.],\n",
       "       [   0.,    0.,    0.,    0.],\n",
       "       [   0.,    0.,    0.,  100.]])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.zeros((3, 4))\n",
    "a[2, 3] = 100\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Sedaj spremenimo še elemente prvih dveh vrstic in prvih dveh stolpcev v vrednost 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   1.,    1.,    0.,    0.],\n",
       "       [   1.,    1.,    0.,    0.],\n",
       "       [   0.,    0.,    0.,  100.]])"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:2, :2] = np.ones((2, 2))\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Z 2 pomnožimo stolpec z indeksom 1:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   1.,    2.,    0.,    0.],\n",
       "       [   1.,    2.,    0.,    0.],\n",
       "       [   0.,    0.,    0.,  100.]])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:,1] = 2 * a[:,1]\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Bodite pozorni na to, da na tak način naredimo *pogled* (view) na podatke (**ne naredimo kopije podatkov**). \n",
    "\n",
    "Za primer najprej naredimo novo ime `pogled`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.])"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pogled = a[:, 2]\n",
    "pogled"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Sedaj spremenimo izbrane vrednosti numeričnega polja `a`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[   1.,    2.,    5.,    0.],\n",
       "       [   1.,    2.,    5.,    0.],\n",
       "       [   0.,    0.,    5.,  100.]])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:, 2] = 5\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Vrednosti `pogled` nismo spreminjali. Ker pa ime kaže na isto mesto kakor `a[:, 2]`, so vrednosti spremenjene:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  5.,  5.])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pogled"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Če želimo kopijo, potem moramo narediti tako:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  5.,  5.])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kopija = a[:, 2].copy()\n",
    "kopija"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in rezultat `kopija` ostane nespremenjen:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  5.,  5.])"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:, 2] = 2\n",
    "kopija"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Osnove matričnega računanja"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Če želite ponoviti matematične osnove matričnega računanja, potem sledite tej [povezavi](http://www.fmf.uni-lj.si/~kosir/poucevanje/skripta/matrike.pdf) (gre za kratek in dober pregled prof. dr. T. Koširja). Pogledali bomo, kako matrične račune izvedemo s pomočjo paketa `numpy`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Najprej definirajmo matriki $\\mathbf{A}$ in $\\mathbf{B}$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = np.array([[1, 2], [3, 2]])\n",
    "B = np.array([[1, 1], [2, 2]])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ter vektorja $\\mathbf{x}$ in $\\mathbf{y}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.array([1, 2])\n",
    "y = np.array([3, 4])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Skalarni produkt dveh vektorjev izvedemo s funkcijo `dot()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html)):\n",
    "```python\n",
    "numpy.dot(a, b, out=None)\n",
    "```\n",
    "kjer argumenta `a` in `b` predstavljata numerični polji `numpy.array` (poljubne dimenzije), ki jih želimo množiti. Če sta `a` in `b` dimenzije 1 se izvede skalarni produkt. Pri dimenziji 2 (matrike) se izračuna produkt matrik. Za uporabo funkcije `dot()` pri dimenzijah več kot 2: glejte [dokumentacijo](https://docs.scipy.org/doc/numpy/reference/generated/numpy.dot.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo primer množenja dveh vektorjev, to lahko izvedemo tako:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.dot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "ali tudi tako:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.dot(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Zgoraj smo omenili, da `numpy.array` ne sledi dosledno matematičnemu zapisu. Če bi, bi namreč eden od vektorjev moral biti vrstični, drugi stolpični. `numpy` to poenostavi in zato je koda lažje berljiva in krajša."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo sedaj množenje matrike z vektorjem (opazimo, da transponiranje `x` ni potrebno):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 7])"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.dot(A, x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Lahko pa seveda pripravimo matematično korektno transponirano obliko vektorja (ampak vidimo, da je zapis neroden):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5],\n",
       "       [7]])"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.dot(np.transpose([x]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Transponiranje ima sicer tudi kratko obliko, prek atributa `T`, npr. za matriko $\\mathbf{A}$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1, 3],\n",
       "       [2, 2]])"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo si primer množenja dveh matrik:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5, 5],\n",
       "       [7, 7]])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.dot(A, B)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Od Pythona 3.5 naprej se za množenje matrik (in vektorjev) uporablja tudi operator `@` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.matmul.html#numpy.matmul)), ki omogoča kratek in pregleden zapis.\n",
    "\n",
    "Zgornji primeri zapisani z operatorjem `@`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x @ y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([5, 7])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A @ x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5, 5],\n",
       "       [7, 7]])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A @ B"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "**Vektorski produkt** izračunamo s funkcijo `numpy.cross()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.cross.html)):\n",
    "```python\n",
    "numpy.cross(a, b, axisa=-1, axisb=-1, axisc=-1, axis=None)\n",
    "```\n",
    "kjer `a` in `b` definirata komponente vektorjev. Če sta podani samo dve komponenti ($x$ in $y$), se izračuna skalarna vrednost (komponenta $z$); če so podane tri komponente, je rezultat tudi vektor s tremi komponentami. Uporaba funkcije je možna tudi na večdimenzijskih numeričnih poljih in temu so namenjeni preostali argumenti (glejte dokumentacijo)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer vektorskega produkta ravninskih vektorjev:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(1)"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([1, 0])\n",
    "y = np.array([0, 1])\n",
    "np.cross(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer vektorskega produkta prostorskih vektorjev:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 1])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.array([1, 0, 0])\n",
    "y = np.array([0, 1, 0])\n",
    "np.cross(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Nekatere funkcije knjižnice ``numpy``\n",
    "\n",
    "Pogledali si bomo še nekatere funkcije, ki jih bolj ali manj pogosto potrebujemo."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Enotsko matriko definiramo s funkcijo `numpy.identity()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.identity.html)):\n",
    "```python\n",
    "numpy.identity(n, dtype=None)\n",
    "```\n",
    "kjer argument `n` definira število vrstic in stolpcev pravokotne matrike. Tip `dtype` je privzeto `float`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer enotske matrike:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.,  0.,  0.],\n",
       "       [ 0.,  1.,  0.],\n",
       "       [ 0.,  0.,  1.]])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = np.identity(3)\n",
    "A"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Do diagonalnih elementov matrike dostopamo s pomočjo funkcije `numpy.diagonal()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.diagonal.html))\n",
    "```python\n",
    "numpy.diagonal(a, offset=0, axis1=0, axis2=1)\n",
    "```\n",
    "Če je matrika dvodimenzijska, potem funkcija s privzetimi argumenti vrne diagonalno os. Če je dimenzija višja od 2, se uporabi osi `axis1` in `axis2`, da se izloči dvodimenzijsko polje, nato pa določi diagonalo glede na elemente `[i, i+offset]`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Poglejmo primer izločanja diagonale:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.,  1.,  1.])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.diagonal(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in uporabe `offset=1` za sosednjo diagonalo (najprej pripravimo nesimetirčno matriko):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 10.,   0.])"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A[0, 1] = 10\n",
    "np.diagonal(A, offset=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Podobno sintakso kot `numpy.diagonal()` ima funkcija `numpy.trace()`, ki izračuna vsoto (sled) diagonalnih elementov ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.trace.html)):\n",
    "```python\n",
    "numpy.trace(a, offset=0, axis1=0, axis2=1, \n",
    "            dtype=None, out=None)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer sledi diagonale:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.0"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.trace(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in potem sosednje diagonale:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.trace(A, offset=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Pogosto nas zanimata največji ali najmanjši element nekega numeričnega polja. `numpy` je tukaj zelo splošen. Poglejmo si na primeru funkcije `numpy.max()` ([dokumentacija](https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.amax.html)):\n",
    "```python\n",
    "numpy.max(a, axis=None, out=None)\n",
    "```\n",
    "Izpostavimo argument `axis`, ki pove, čez kateri indeks iščemo maksimalno vrednost. Če je `axis=None` se določi največja vrednost v celotnem polju."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer izračuna največje vrednosti celotnega polja (prej poglejmo `A`):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  1.,  10.,   0.],\n",
       "       [  0.,   1.,   0.],\n",
       "       [  0.,   0.,   1.]])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10.0"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer izračuna največje vrednosti čez vrstice (torej po stolpcih):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  1.,  10.,   1.])"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(A, axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer izračuna največje vrednosti čez stolpce (torej po vrsticah):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 10.,   1.,   1.])"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.max(A, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Par funkcije `max()` je `numpy.argmax()`, kateri določi indekse največje vrednosti.\n",
    "\n",
    "Primer uporabe:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 2], dtype=int64)"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.argmax(A, axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Linearna algebra z ``numpy``"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pozneje bomo linearno algebro bolj podrobno spoznali in bomo sami pisali algoritme. Tukaj si poglejmo nekatere osnove, ki so vgrajene v modul `numpy`.\n",
    "\n",
    "Za primer najprej definirajmo matriko in vektor:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = np.array([[4, -2],\n",
    "              [-2, 4]])\n",
    "b = np.array([1, 2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Inverzno matriko izračunamo z uporabo funkcije `numpy.linalg.inv()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.inv.html)):\n",
    "```python\n",
    "numpy.linalg.inv(a)\n",
    "```"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.33333333,  0.16666667],\n",
       "       [ 0.16666667,  0.33333333]])"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linalg.inv(A)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Sistem linearnih enačb, ki ga definirata matrika koeficientov `a` in vektor konstant `b`, rešimo s pomočjo funkcije `numpy.linalg.solve()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.solve.html)):\n",
    "```python\n",
    "numpy.linalg.solve(a, b)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.66666667,  0.83333333])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rešitev = np.linalg.solve(A, b)\n",
    "rešitev"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Enakost elementov numeričnega polja `a` in `b` (znotraj določene tolerance) preverimo s funkcijo `numpy.isclose()` ([dokumentacija](https://docs.scipy.org/doc/numpy/reference/generated/numpy.isclose.html)):\n",
    "```python\n",
    "numpy.isclose(a, b, rtol=1e-05, atol=1e-08, equal_nan=False)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True], dtype=bool)"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.isclose(np.dot(A, rešitev), b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Vektorizacija algoritmov"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "V tem poglavju želimo izpostaviti vektorizacijo algoritmov. Glede na to kako Python in `numpy` delujeta se je potrebno izogibati zankam. Bistveno hitreje lahko izvajamo izračune, če jih uspemo vektorizirati; to pomeni, da izračune izvajamo na nivoju vektorjev (oz. numeričnih polj) in ne elementov."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Za primer si najprej pripravimo podatke (dva vektorja dolžine 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [],
   "source": [
    "N = 1000\n",
    "a = np.arange(N)\n",
    "b = np.arange(N)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Izračunajmo skalarni produkt vektorjev z uporbo zanke `for`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "332833500"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = 0\n",
    "for i in range(N):\n",
    "    c += a[i] * b[i]\n",
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Izmerimo hitrost:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "869 µs ± 56.6 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n100\n",
    "c = 0\n",
    "for i in range(N):\n",
    "    c += a[i] * b[i]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Isti rezultat pridobimo še v vektorski obliki:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The slowest run took 4.12 times longer than the fastest. This could mean that an intermediate result is being cached.\n",
      "5.75 µs ± 4.02 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n100\n",
    "c = a @ b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vidimo, da je vektorski način bistveno hitrejši (za še hitrejši način glejte `numba` v dodatku)!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Modul ``matplotlib``"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "V Pythonu imamo več možnosti za prikaz rezultatov v grafični obliki. Najbolj uporabni paketi so:\n",
    "\n",
    "* [`matplotlib`](http://matplotlib.org/) za visoko kakovostne, visoko prilagodljive slike (relativno počasno),\n",
    "* [`pyqtgraph`](http://www.pyqtgraph.org/) za kakovostne in prilagodljive uporabniške vmesnike (zelo hitro),\n",
    "* [`bokeh`](https://bokeh.pydata.org/en/latest/) za interaktiven prikaz v brskalniku (relativno hitro)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Obstaja še veliko drugih; dober pregled je naredil Jake VanderPlas na konferenci [PyCon 2017](https://www.youtube.com/watch?v=FytuB8nFHPQ) (sicer avtor paketa za deklerativno vizualizacijo: *Altair*)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Osnovna uporaba\n",
    "\n",
    "Najbolj razširjen in najbolj splošno uporabljen je paket [`matplotlib`](http://matplotlib.org/):\n",
    "<img width=\"400\" src=\"http://matplotlib.org/_static/logo2.svg\">\n",
    "\n",
    "Sposobnosti paketa najbolje prikazuje [galerija](http://matplotlib.org/gallery.html#). Gre za zelo sofisticiran paket in tukaj si bomo na podlagi primerov pogledali nekatere osnove."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Tipično uvozimo `matplotlib.pyplot` kot `plt`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "Znotraj *Jupyter notebooka* obstajata dva načina prikaza slike (v oglatem oklepaju je magic ukaz za proženje):\n",
    "\n",
    "1. `[%matplotlib inline]   `: slike so vključene v notebook (**medvrstični** način),\n",
    "3. `[%matplotlib notebook] `: slike so vključene interaktivno v notebook (**medvrstični interaktivni** način).\n",
    "\n",
    "Opomba: *interaktivni način se v pasivni, spletni/pdf verziji te knjige ne prikaže pravilno*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Tukaj bomo najpogosteje uporabljali *medvrstični* način:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Kratek primer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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0IBE9QkTviXj/74hoh/f1EBHNBd5zAu/dmsd6VHD2lkk8dGghU4TJsYQwEuvH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72ICGwAv8QYuxPAGwD8DBHdNeM19QA8yBi7B8C9AN5KRG+Y8Zo43gPXMv4g4fsYY/ceoJLF3wLw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\nESQKFChQoEAsiiBRoECBAgVi8f8BghqpVLcybLkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8ebc2e630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = np.linspace(1, 130, 44000)\n",
    "žvižg = np.sin(t**2)\n",
    "plt.plot(t, žvižg, label='Žvižg')\n",
    "plt.xlim(1, 10)\n",
    "plt.title('Žvižg: $t^2$ (podpora za LaTeX: $\\\\sqrt{\\\\frac{a}{b}}$)')\n",
    "plt.legend();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Mimogrede, zakaj to imenujemo žvižg (oz. kvadraten žvižg)? Da dobimo odgovor, podatke predvajamo na zvočnik:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source 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7ybrbOa74RTdedjs027PAcunxmLCMr4auhu2NrJursKqNqfKo3+gVp1SmnKXuZQnkr2PfI1mi3qJuocmhr+EhYN6gp2B74BxgCKAAoASgFKAwoBigTGCL4NchLiFQof6iN+K8Iwsj5SRJZTglsOZzZz9n1GjyaZkqiCu+7H0tQu6PL6HwurGY8vxz5LURdkG3tbiseeW7IPxdvZt+2YAYAVZCk4PPhQmGQYe2iKhJ1ksADGVNRY6gD7SQgpHJ0snTwlTylZpWuVdPWFuZHhnWmoSbZ5v/3EzdDl2EXi4eTB7dnyLfW5+H3+cf+d//n/jf5N/EX9bfnN9WHwKe4t523f6delzqXE6b55s1mnjZsVjfmAQXXtZwlXlUeZNx0mJRS5BuDwpOIIzxS71KRMlISAhGxUWABHjC8EGmwF1/E/3LPIO7fjn6+Lp3fXYEdQ/z4HK2cVIwdG8drg5tBuwHqxEqI6k/6CXnVmaRZdelKORF4+7jI+KlojOhjqF24OwgrqB+oBxgB6AAoAcgG6A9oC1gaqC1oM3hc2Gl4iWiseMKo+/kYOUd5eYmuadXqEApcqou6zQsAm1YrnbvXHCI8fuy9HQyNXT2u/fGeVQ6pHv2vQo+nn/ywQbCmgPrhTsGR8fRCRaKV4uTjMoOOk8j0EZRoNKzU70UvVW0VqEXg1iamWZaJpra24KcXZzrnWxd395FXt0fJp9h347f7V/9H/6f8V/VX+sfsh9qnxUe8R5/Xf+dclzXnG/bu1r6GizZU5ivF79WhRXAlPJTmtK6kVIQYg8qjeyMqItfChDI/kdoBg7E8wNVgjcAmH95vdu8vvskucz4uHcoNdx0ljNVchtw6G+87lmtf2wuKybqKek3qBCndWZmJaOk7eQFY6qi3aJe4e6hTSE6YLagQeBc4AbgAKAJoCJgCmBB4Iig3mEDYbdh+eJK4yojlyRR5Rnl7qaP570odil6KkkroeyErfBu5HAgsWQyrnP+tRS2rzfN+W/6lPw7/WR+zUB2QZ7DBYSqhcyHawiFihrLasy0jfdPMpBl0ZAS8RPIVRTWFlcMWDZY09nkWqdbXJwDnNwdZZ3gHkte5t8yX23fmV/0n/+f+h/kH/3fh5+A32oew16M3gcdsdzNnFrbmZrKmi3ZBBhN10sWfNUjlD+S0dHaUJpPUg4CjOwLT4otiIcHXIXuxH6CzIGZwCb+tH0De9Q6Z/j/d1s2O/Sis0+yBDDAr4WuU+0sK87q/Om2aLxnj2bvZd2lGeRk477i6GJh4ethRSEvoKrgdyAUYALgAqATYDWgKSBtoIMhKWFgIedifuLmI5ykYmU25dmmyifH6NJp6WrLrDktMS5yr71w0HJq84x1NDZhd9L5SLrBPHv9t/80QLDCLEOlxRyGj8g+iWhKzExpTb8OzJBQ0YuS/BPhVTsWCFdImHtZIBo2Wv1btNxcXTPdul4v3pRfJx9oH5df9J//n/if31/0H7bfZ58GntQeUF37XRXcn9vZ2wRaX5lsWGrXXBZAVVgUJFLlkZyQSc8ujYsMYIrviXjH/YZ+RPwDd4HxwGv+5n1iO+A6YTjmd3B1wDSWczQxmjBJLwHtxWyUK27qFmkLKA3nH2Y/5TAkcKOBoyOiV2HcoXQg3eCaYGmgC6AAoAigI6ARoFKgpiDMYUUhz+JsYtpjmWRpJQjmOGb3J8QpH2oHq3ysfW2Jbx+wf3Gn8xh0j/YNt5B5F7qifC+9vj8NQNwCacP1RX2GwYiAijmLa8zWTngPkBEeEmDTl5TBlh5XLNgsmRzaPRrM28ucuJ0TndweUh703wRfgF/on/zf/Z/qH8Lfx9+5Hxbe4V5Ynf1dD5yQG/8a3NoqWSfYFhc11ceUzBOEEnCQ0k+qDjjMvws+SbdIKsaaBQYDr0HXgH++p/0R+7657zhkdt81YLPpsntw1m+77izs6auzqkspcWgmpyvmAaVopGFjrGLJ4nrhvyEXYMOghGBZoAOgAqAWID5gO2BNIPLhLOG64hxi0OOX5HElHCYYJySoAKlr6mVrrGz/7h9vibE+MntzwPWNdx/4t7oTO/F9Uf8ygJNCcoPPRaiHPUiMSlRL1M1MjvqQHdG1UsBUfdVtFo0X3VjdGcua59ux3GidC93bHlXe+98Mn4hf7l/+3/nf3x/un6ifTV8c3peePd1P3M4cOVsR2lhZTVhx1wYWC1TCU6uSCJDZj2AN3QxRSv3JJAeExiEEeoKRwSh/fz2XPDH6UDjzdxx1jLQFMobxEq+qLg2s/mt9agupKafYZtil6yTQZAljViK34e5hemDcIJPgYeAGYAFgEuA7IDmgTqD5YTohkGJ74vujj+S3ZXHmfqdc6IwpyusY7HUtnm8T8JRyHzOytQ428HhYOgR78/1lPxbAyIK4RCVFzkexyQ8K5IxxDfPPa1DW0nVThVUGVndXV1ilmaFaiZueHF3dCJ3dnlxexJ9WX5Cf89//n/Qf0R/Wn4UfXF7dHkdd250aXERbmdqbmYpYptdyFizU19O0UgMQxY98TajMDAqniPwHC0WWA93CJABp/rB8+TsFOZY37PYK9LFy4bFcr+Oud6zZ64uqTWkgZ8Vm/WWJZOmj3uMqIkuhxCFT4PsgeiARYADgCKAo4CEgcaCaIRohsWIfYuOjveRs5XCmR+eyKK4p+2sYrISuPu9F8RiytbQb9co3vzk5eve8uL56wD0B/cO8BXYHKojYSr3MGg3rz3GQ6hJUk++VOlZzV5oY7Zns2tbb61ypXVCeH96XXzaffN+qX/6f+Z/bn+RflB9q3uleT93enRZcd1tC2rkZWthpVyVVz9Sp0zRRsNAgDoPNHMtsibSH9gYyhGtCoYDXvw29RfuBucI4CPZXdK7y0PF+b7kuAizaa0MqPaiK56vmYaVspE4jhmLWYj7hf+DaII3gW2ADIASgIGAWIGWgjyERoa1iIWLtY5CkimWZ5r6ntyjC6mBrju0NLpnwM/GZ80p1A/bFeI06Wfwpvfu/jYGeg20FN0b7yLlKbgwZDfiPSxEP0oUUKZV8VrxX6Bk/GgAbalw9HPddmN5g3s8fYt+cH/pf/d/mX/Pfpp9+nvyeYJ3rXR1cd1t52mXZfBg91uvVh1RRUstRdo+UDiWMbEqpyN+HDwV6A2HBiH/uvdZ8AbpxeGe2pfTtcz/xXq/Lbkcs02txaeIop2dBZnHlOWQY41EiouHO4VVg9uBzoAwgAKAQ4DzgBKCn4OZhf6Hy4oAjpmRkpXpmZqeoaP5qJ6ui7S7uijBzcekzqfV0NwY5Hrr7vJu+vMBeAn1EGMYvB/6JhYuCTXOO15Cs0jJTphUHVpRXzFkuGjibKtwD3QMd555w3t6fcB+lX/3f+d/Y39sfgR9K3vjeC52DnOGb5lrS2eeYpldPliTUpxMYEbjPyw5QDImK+UjghwFFXQN1gUz/pH29u5r5/XfnNhn0VzKgcPevHe2VLB5quyks5/Smk6WKpJsjhaLLIiwhaWDDILogDqAAoBAgPWAH4K+g9GFVohKi6uOdZKmljmbKqB1pRWrBbE/t729esRvy5bS6Nle4fHom/BT+BMA0weNDzkX0B5KJqEtzTTHO4pCD0lOT0RV6Vo4YCxlwWnybbtxGHUHeIN6i3wcfjZ/1n/8f6l/236VfdZ7oXn3dttzUHBZbPpnN2MUXpZYw1KgTDNGgj+TOG0xFyqYIvcaOxNsC5IDtfva8wrsTeSr3CrV0s2qxrq/CLmasnespaYqoQucTJf0kgaPhot4iN6FvIMUguaANoACgEyAFIFYghiEUoYEiSuMxY/Nk0GYG51YovGn4q0ktLK6hcGWyN/PWNf63r3mmu6J9oH+ewZwDlcWKR7cJWstzTT6O+xCnEkCUBlW2ls/YURm4WoUb9hyKHYCeWJ7Rn2tfpN/+X/ef0J/JX6IfG562HfIdEFxSG3faAxk0145WURT+kxhRoE/XzgDMXQpuyHfGegR3gnJAbP5ovGf6bPh5dk90sTKgcN8vLu1R68lqVyj8p3tmFKUJZBsjCqJYoYYhE6CBoFCgAKARoAPgVyCK4R7hkqJlIxXkI6UNZlInsGjm6nQr1i2Lr1LxKbLOdP72uTi7eoM8zn7awObC78TzxvCI5ArMTOdOstBtEhRT5pViVsYYUFm/mpJbx9zfHZaebl7k33pfrh//n+9f/R+o33Me3F5lXY5c2JvFGtTZiRhjVuTVT1PkkiZQVg62TIiKzwjMBsHE8gKfQIv+ufxremK4YjZr9EIyprCb7uNtPytxKfsoXmccZfbkryOF4vyh06FMYObgY+ADoAZgK+A0YF8g7CFaoioi2WPnZNNmG+d/qLzqEiv9rX3vEHEzsuV047br+Pw60j0rfwVBXoN0BUOHiwmIC7hNWc9qkSgS0NSi1hxXu5j/GiWbbVxV3V1eA17HH2ffpR/+3/Tfxt/1X0CfKN5vHZPc2Bv9GoQZrhg81rHVDtOVkchQKM45DDtKMggfRgVEJsHGf+W9h7uueVx3VDVX82nxTG+BrctsK6pkqPenZqYzJN5j6eLWYiUhVuDsIGXgA+AGoC3gOeBqIP4hdSIOowlkJGUepnZnqik4ap9sXS4vr9TxyrPOtd63+DnYvD4+JUBMQrDEj8bnCPQK9IzlzsYQ0tKKFGnV8Bda2OjaGFtn3FYdYh4K3s+fb1+qX/+f71/5n56fXl76HjIdRxy6m02aQZkX15IWMlR6EquQyQ8UjRBLPwjixv5ElAKmgHi+DLwk+cS37fWjM6cxvC+kreJsN6pm6PFnWSYf5Mcj0CL74cvhQGDaoFqgASAN4AEgWuCaIT7hh+K040QktKWE5zOofqnkq6NteK8icR5zKfUC92a5UnuDvff/7AIdxEqGr4iJytdM1Q7BENiSmZRB1g8Xv9jR2kPblByBnYrebt7tH0Sf9R/+X+Bf2t+unxveo13F3QScIJrbWbZYM1aUVRrTSZGiD6dNm4uBSZrHa0U1QvtAgL6HfFK6JPfBdepzovGs74ttwGwOancovSciJeekj2Oaooqh4KEdIIFgTSABYB2gIiBOYOIhXGI8YsEkKSUzJl2n5qlMawys5W6UMJayqjSMdvp48XsufW8/sAHuxCiGWkiBCtpM407ZUPoSgxSx1gSX+NkM2r8bjdz3nbteWB8NH5mf/R/3X8if8R9xHskeeh1E3KsbbZoOWM8XcZW30+QSONA4jiWMAsoTB9jFl0NRQQo+w/yCOkf4F7X0s6FxoO+1baHr6GoLaIznLuWzJFujaWJdobng/uBs4ATgBqAyoAhgh2EvIb7idaNR5JJl9ac5qJwqW6w1becv7nHINDI2KThqerK8/z8MgZhD30YeCFHKt8yNDs6Q+dKMVIOWXRfW2W8ao5vy3Nud3J60XyKfpl//n+3f8R+KH3jevl3bXRFcIZrNWZbYP5ZKFPhSzREKjzOMywrTyJDGRQQzwaB/TX0+OrX4d/YG9CYx2G/gbcDsPKoV6I7nKaWoZEyjV+JL4akg8OBjoAIgDCACIGOgr+EmocaizqP9pNGmSSfh6VnrLuzeLuUwwPMu9Sv3dLmGvB3+d0CQQyVFcse1yesMD45gkFrSe9QA1idXrRkQGo4b5VzUndpetZ8lH6if/5/qH+ffuV8fXppd65zUG9Xashkq14KWOxQXUlmQRI5bjCFJ2QeGBWuCzICtPg/7+Dlptye09PKU8IqumOyCqsppMmd9JeykguOBoqohvaD9IGmgAyAKYD8gIOCvoSohz+LfI9alNOZ3Z9ypoetErUJvWHFDc4B1zHgj+kN85/8NQbEDz0ZkiK1K5o0ND13RVVNxFS6WytiD2hcbQxyF3Z4eSh8JX5rf/h/zH/mfkh983rsdzZ012/UajZlBF9HWAlRVUk1QbU44i/IJnUd9hNaCq4AAfdg7drjfdpW0XPI4b+tt+Kvjqi5oW+buJWekCiMXIhBhduCLoE7gAaAjoDSgdKDiYb1iRCO1JI6mDuezaTnq36ziLv4w8LM2NUu37boYPIg/OUFow9KGcsiGSwmNeQ9RUY+TsJVxlw/YyRpa24McwF3RHrOfJ1+rn/+f41/XH5tfMJ5XnZIcoVtHWgWYntbVVSvTJREETwyMwUqmCD5FjYNXwOD+bDv9OVg3AHT58kewbW4uLA0qTSiwpvqlbOQJoxLiCaFvYIVgS6ADICugBOCOoQfh7+KEo8UlLyZAqDcpkCuIrZ3vjHHRNCh2Tnj/+zi9tQAxQqnFGke/CdSMVw6DENUSyhTe1pBYXFnAG3mcRp2l3lWfFR+jH/+f6h/in6mfAB6mnZ6cqdtKGgGYklb/VMsTORDMDsfMr8oHh9LFVcLUAFH90vta+O42UHQFcdCvte14K1rpoOfNJmHk4WOOIqkhtGDw4F+gAOAU4BugVOD/oVsiZaNeJIImD6eEaV1rF+0wryRxb7OOtj34eTr8vUQAC8KPhQuHu0nbTGeOnJD2UvHUy5bA2I7aMptqnLQdjd62Xyxfr1/+n9pfwl+3XvoeDB1uXCLa69lLV8QWGRQNUiQP4M2HS1tI4MZbg9ABQr72/DD5tTcHtOxyZzA77e3rwGo3KBSmm6UOo+/igSHD4TmgYyABIBOgGqBVoMQhpOJ2Y3ckpOY9Z73pY+tr7VLvlPHutBw2mTkh+7H+BMDWw2OF5ohbyv8NDI+AEdZTy9Xc14bZRtraHD6dMp4z3sHfmt/+3+1f5l+qnzpeVx2CXL2bCxntWCbWepRr0n4QNM3UC5+JG8aMhDZBXf7G/HY5r7c4NJNyRbAS7f6rjKnAKBwmY2TYo74iVWGgIN/gVWAA4CLgOyBI4QuhwaLpo8FlRyb3qFCqTqxubmxwhHMzNXP3wnqavTf/lYJvhMFHhko6DFjO3hEF00zVb1cp2PmaW9vOXQ6eGx7yn1Of/d/w3+xfsV8AXpqdgZy22z0ZltgGlk9UdRI7D+UNtws1yKUGCYOnwMR+Y/uKuT12QLQYsYmvV+0G6xppFed8pZDkVeMNIjjhGqCzYAPgDGANIEWg9OFZ4nMjfqS6JiMn9qmxq5Btz3Aq8l405Xd7+d08hH9tAdKEsAcBCcEMa067kO4TPpUpVytYwNqnm9ydHd4p3v6fW1//X+of3B+V3xfeY917HB/a1Jlb17jVrtOBkbTPDIzNSntHm0UyQkT/130u+lB3wLVD8t7wVe4tK+hpy2gZZlWkwuOjonnhRyDMoEvgBKA3YCOgiOFl4jjjAGS5peJnt2l1a1jtni/Asnx0jPdtOdj8ir99we2ElQdvSfeMaQ7/kTaTSdW2F3dZCprsnBtdVB5VHx1fq1/+39ef9Z9Z3sUeOVz324NaXpiMFs9U7FKmkEJOBEuwyMyGXIOlgO1+N/tK+Or2HTOmMQquzuy3akdogybt5Qpj2yKioaLg3OBRoAIgLmAWILhhFCIn4zGkbuXdJ7kpf2tsLbtv6LJvtMu3t3oufOs/qEJhhREH8gp/zPTPTRHD1BUWPJf3GYEbV5y4XaDej59DH/qf9V/z37YfPR5KXZ+cftrq2WaXtRWaU5pReQ77TGWJ/McGBIbBxD8C/Ei5mvb+NDfxjK9BbRoq22jI5yXldeP7orlhsSDkYFRgAaAsYBQguKEYIjEjAeSHZj8npem3q7CtzHBG8tr1Q7g7+r69RcBNAw6FxMiqyztNsVAIErrUhZbkWJMaTxvU3SIeNN7LX6Sf/5/cX/rfXB7BHitc3RuZGiHYetZn1GySDc/QDXgKiwgOBUZCuj+t/Od6LHdCNO2yNG+bLWYrGmk7pw1lkyQQIsZh+GDnoFUgAaAtYBgggSFm4gejYWSxpjTn5+nG7A2ud3C/8yG11/ic+2s+PMDNA9YGkcl7S80OgdEU00FVgxeV2XZa4NxSnYlegx9+H7nf9V/w36zfKh5qXW+cPFqTGTdXLNU30txQn04Fy5UI0gYDA20AVr2Eevy3xPVi8puwNG2yK1kpbid0pbBkJGLTYf+g6qBV4AGgLqAcIImhdaIeI0Ek22ZqaCmqFexqLqHxODOndmq5O/vVvvFBigSZx1qKBszYz0vR2hQ/ljdYPZnOW6bcw94jHsMfoh//n9tf9R9OXufdw9zkW0xZ/tf/ldMT/VFDTyoMdwmvxtoEO8EbPn07aLijNfKzHHCmLhSr7Smz560l3KRFYyqhzmEyoFigASAsoBpgiaF5IicjUKTzZktoVWpMrKzu8PFTtA923rm7fF+/RQJmRTzHworxzUUQNpJBVOCWz5jKWo1cFR1fHmkfMR+2X/gf9h+xHyoeYp1cnBtaoVjy1tNUx5KUUD7NTIrDSCjFAwJY/2+8Tbm5drjz0bFJ7uZsbKohqAlmZ+SA41ciLWEFYKDgAKAkoA0guSEnIhUjQKTm5kPoVGpTLLwuybG2dDy21nn9vKw/mwKExaLIbssizfkQa9L1lRHXe5kvGugcY92fXpifTh/+X+lfzx+wXs5eKtzIm6qZ09gI1g2T5xFazu3MJklKBp+DrMC4/Yl65XfStRfyeu+BLXBqzajdpuSlJqOmYmchauCzoAHgFqAxoFGhNiHcYwJkpSYA6BFqEqx/LpHxRTQS9vU5pbydf5XCiQWwSETLQM4dkJXTI9VCl61ZX5sV3IydwR7xn1wf/5/cH/HfQV7MXdTcndsqGX2XXJVL0xBQr83wCxdIa4VzgnZ/efxFOZ62jTPW8QHulCwS6cNn6iXLZGriy+HwoNsgTOAGoAhgUaDhIbVii6Qg5bHneml1659uMXCmM3e2HzkWvBb/GQIXBQnIKgryDZrQXtL31SDXVNlPWwwciF3AnvLfXZ//n9jf6V9yHrTds9xxmvHZOFcJlSqSoNAyDWSKvkeGRMMB/D63e7y4knX/MsnweG2RK1kpFacLZX6jsyJrYWogsOABYBtgPyBroR9iGCNTZM1mgmit6ortE6+CslH1Onf1uvy9yEERxBJHAkobDNZPrVIaVJdW3xjtWr1cC52VHpcfUF//H+Nf/N9M3tTd1xyWWxZZWpdoVQRS9BA+DWgKuMe3hKsBmr6NO4n4mDW+8oRwL61GKw5ozObGpQAjvKI/YQqgoCAA4C0gJKCmYXCiQOPT5WYnM6k262styjCOM3B2Kjk0PAc/W8JrhW5IXQtxDiNQ7ZNJ1fHX4RnS24LdLZ4QXyjftd/2X+qfkx8xXgcdF1ulWfVXy9Xt02FQ7A4Uy2IIWwVHAm3/FjwHuQn2I/McsHsthWtBqTUm5OUVY4piRyFOIKDgAOAuICggrmF+YlYj8eVOZ2apdau2LiHw8rOhNqa5u7yY//YCzMYUyQbMG47MkZKUKBZG2KnaTJwq3UFejZ9NH/8f4p/4X0De/h2ynGFazdk9FvPUt9IOz7+MkMnJxvIDkQCu/VK6Q/dK9G5xda6nrAop42e4pY7kKeKNIbugt2AB4BsgA6C54TxiCKObZTEmxOkRq1Ht/3BTs0c2Uzlv/FW/vEKche5I6cvIDsGRj5Qrlk/Yttpb3DrdUF6Zn1Rf/5/a3+afY16TnbncGRq12JRWulQtUbPO1MwXSQKGHsL0P4m8p7lWNlzzQ3CQrcureqjjpsvlOCNsYivhOSBV4ANgAeBQoO5hmOLNJEemBCg9qi4sj+9cMgu1Fzg2+yL+UsG/RJ/H7ErdTesQjpNA1fvX+dn1m6rdFZ5y3wCf/V/oH8Gfil7EHfHcVpr2mNaW+9Rske9PCsxGyWqGPoLLP9e8rPlStlFzcLB3ra3rGWjApuik1qNOohOhKGBOoAegEyBwYN4h2eMgZK3mfahKas4tQnAgcuB1+vjn/B7/V0KJReyI+MvmDuyRhVRpVpJY+xqd3Hcdgp7+H2df/V//369fDV5cHR7bmRnPl8eVh1MVEHfNdwpbB2tEMIDzvbw6UzdAtE0xf+5gq/ZpRydY5XDjkyJD4UVgmeACoD+gEKD0Iadi5+RxJj7oC2qQ7Qiv63KxtZN4yDwHv0jCg8XviMPMOA7E0eKUShb1WN4a/1xU3dsezx+u3/nf71+QXx5eHBzMm3QZV5d8VOkSZI+1zKUJukZ+Qzm/9Hy4OU02e/MM8EfttGrZaL0mZWSXIxah5yDLYETgFKA6YHUhAuJg44ulfmc0KWbr0C6ocWh0R/e+eoM+DUFURI8H9Mr9Dd9Q1BOTlheYWVpT3AHdn96q32Af/t/GX/dfE15c3RabhVntl5VVQpL8j8rNNUnERsDDs4Al/OB5rDZR81pwTW2zKtJosaZXJIejB6HaoMMgQuAaYAngj6FqIlYjz6WR55ep2qxT7zvxyvU4ODr7Sn7dAipFaIiPS9VO8lGe1FKWx5k3Gtwcsd30XuFftl/yn9Zfoh7YHfscTtrX2NuWoJQtEUkOvItPyEuFOUGifk+7Cnfb9I0xpq6wq/Jpc2c5pQqjq2IfoSogTWAKICCgT6EVoi/jWiUQJwwpSGv9bmOxc3Rjt6u6wj5dAbRE/Ygvi0GOqtFi1CJWodjbGsicpV3tnt6ftd/y39Ufnh7PXewceFq4mLKWbNPuUT7OJssux+BEhEFlPct6gTdPdD+w2q4oq3Do+yaNZO0jHyHnIMfgQ2AaYAxgmKF8onUj/iWSJ+vqBCzTr5Jyt/W6+NI8dH+XAzFGeUmljOyPxhLplU+X8NnH286dQN6bH1sf/x/G3/KfBF5+XOTbe9lI11KU4BI4zyVMLojdhbxCFP7wO1i4GDT3sYCu+6vwqWcnJeUyo1JiCWEaYEegEeA5YHzhGiJN49Qlp2eCKh0ssO91MmE1q7jK/HU/oEMChpIJxI0RUC8S1VW8V90aMRvzHV6esB9lX/zf9d+R3xIeOdyM2xAZCVb/VDmRQA6bi1VINwSKwVs98TpXdxfz/HCNrdTrGiikZnqkYiLgIbhgrSAAoDLgA+Dxobli16SHpoNoxGtDLjew2TQeN306q/4fwY+FMEh3y5yO1RHYVJ4XHtlT23ccw551nwpf/5/VH8rfYx5f3QUbl9mdl10U3dInzwRMPEiaBWeB7357uta3izRisSauIKtY6NamoSS+IvLhgyDxoACgMCA/4K5huOLbJJCmkyjcK2OuIbEM9Fu3hDs7/ngB7oVUyOCMB09/kgCVAde7Waabvd07nlzfXh/+X/zfml8Y3jtchds92OkWjxQ3kSsOM0rZh6iEKsCq/TN5jzZIcylv+6zIKldn8OWa49uid6EyIE3gC+AsYG5hDyJLo99lhGf0aies1i/2sv92JrmhvSVAp0Qcx7rK9s4HEWHUPlaUWRybENzr3ikfBZ//X9XfyR9bXk7dKBtr2WBXDJS40a3OtMtYCCHEnQEU/ZP6JXaTs2mwMO0zKnhnyOXrI+WifGEz4E3gDCAuoHRhGmJd4/mlp+fiKmAtGfAFs1l2izoPvZuBJISfCABLvQ6L0eJUt9cEGYAbpR0uHlcfXR/+H/ofkZ8G3hzcmFr+mJZWZxO5kJbNiMpZxtVDRj/3fDR4iLV+seEu+evSaXMm42Tp4wxhzuD1IACgMiAJIMPh32MXJOWmxGlsK9Qu83H/dS44tHwHP9pDYwbWCmfNjhD+U6+WWNjyGvUcm94h3wOf/1/UH8JfS95z3P5bMRkSlupUANFfjhCK3odUg/4AJvyaOSO1jnJlrzLsAGmWpz2k++MXYdSg9yAAoDHgCmDIoeijJuT85uSpVewH7zFyCDWA+RC8q0AGA9SHS0rezgSRchQdlv6ZDVtCnRleTJ9Z3/6f+p+O3z1dyVy32o6YlNYSk1CQWQ02ibPGHIK8/uA7UnfftFLxNy3WqzrobGYzJBVimKFA4JEgCqAt4HkhKmJ9I+yl8qgHauJtujCE9Dc3RjslfolCZcXvCVkM2JAi0y2V75hgmrlccx3Jnzjfvl/Zn8rfU553XPqbIxk3VoAUBdESjfEKbMbRA2p/hHwruGw00XGm7ndrTGju5mcke6KyYU+gliAHoCSga+EaYmzj3aXmKD8qn+2+cJB0Crehuwk+9IJYBidJlg0Y0GRTbtYuWJqa7Byc3iffCZ//38mf598cnitcmNrrWKoWHZNPUEmNF0mEhh0Cbf6Cuyh3avPWsLatVaq9Z/aliaP8YhShFmBEIB7gJmCY4bNi8OSMJv1pPGvALz4yK3W7+SP81kCHRGmH8MtRTv7R7tTXF65Z7NvLXYSe1B+23+vf8x9OHr/dDNu62VEXF9RYEVyOMEqfBzUDfz+J/CI4VHTtcXhuAOtRKLImLGQHIoehcqBLIBIgB+Cq4XgiquR9Zmio5CumrqVx1XVquNi8kkBLRDZHhotvzqXR3dTNF6oZ7RvOnYje15+4X+kf6p9+HmbdKZtMWVaW0JQEUTyNhEpnxrQC9j86e053/zQY8OettuqQ6D7liSP2ogzhD+BCYCWgOSC64adjOaTrZzSpjKypr4AzBParOiZ96IGlhU+JGYy3D9xTPhXR2I6a7Jyk3jJfEV//H/ufh18k3dfcZlpW2DGVQBKMj2JLzchbhJjA0z0XeXN1s/IlrtQryqkS5rXkeyKpIUQgj+AN4D4gXyFtoqVkQCa2KP7rkG7fsiC1hzlF/Q9A1gSMiGVL009Kkr9VZpg3Gmicc93THwKf/5/JX+BfBx4BnJUaiJhkFbGSu09NDDLIekSwQOM9H/l0da4yGe7Dq/ao/OZfpGaimCF4oEugEuAN4LthV6LeJIgmzilmrAevZbK0dib57/2BAY1FRkkeTIiQOFMiFjtYudrWHMkeTR9e3/wf5B+YHttdshviWfOXbtSd0YxORkrYhxCDfL9qO6d3wjRIMMXth6qYJ8FljGO/4eIg9qAAoABgdWDc4jLjsWWQ6Akqz+3Z8Rr0hnhOvCW//IOGR7RLOQ6HUhLVEFf1mjmcFR3B3zufv1/MX+NfBl45nEMaqdg2lXNSaw8qS74H88QZwH68cDi89PJxXi4MqwkoXiXU4/TiBCEHIEDgMmAbIPhhxiO+pVqn0SqYLaRw6XRZ+Ch7xn/kw7ZHa8s3TovSHFUdl8UaSdxkHc3fAp//n8Qf0N8oHc6cSlpil+CVDpI4TqpLMcddA7r/mXvHeBN0S3D9LXSqfeei5WzjYyHLoOpgAiATYF0hHCJL5CXmImi361uugbIdNaA5fL0jgQaFFojEzIOQBVN91iFY5dsCnTDeap9sX/QfwV+WHrXdJZtsWRKWolOmkGvM/0kvRUpBn729ebN1z7JgbvLrk2jM5mkkMGJpoRlgQuAn4Aeg36Hr42ZlR6fGapgtsTDEdIQ4YfwOgDtD2MfYS6rPAtKTVZAYbxqmnK8eAp9dH/vf3l+GXvaddFuGmbVWytQSUNhNakmWReuB+b3POjt2DfKUrx0r8+jkpnlkOmJuYRrgQyAoIAng5WH243glYSfoqoPt5rEDtMz4s7xnwFsEfUg/S9JPqFL0VeoYvtrp3OMeZN9rX/Qf/x9OHqSdCFtAWRXWU1NEUDYMdoiURN8A5rz5uOi1AjGU7i5q2ygmZZmjvWHYIO3gAeAU4GUhL+JwJB6mcuji6+KvJfKd9ny6Mn4vAiNGP4n0DbIRK9RUV2AZxJw5nbge+x+/n8Rfyl8UXeccCVoDV59UqNFsjfiKG0ZkgmR+anpGdohy/y8468MpKSZ15DIiZSET4EGgMCAeoMoiLmOEZcQoY2sW7lFxxXWjuVz9YEFexUeJS00aUKaT4lbCGbqbg12Unulfvh/RX+PfOF3TXHuaOZeXFOBRoc4pykeGioKDfoH6lraRcsGvdav7KN4maWQl4lqhDWBA4DbgLqDkohSj96XEqLHrcu66sjr15DnmffEB9IXfieJNrZEyVGPXdZndHBFdy58Gn/9f9N+oXt0dl9vgmb/WwJQu0JiNDElZxVEBQv1/+Rh1XHGb7iTqxKgHZbbjXGH94KBgBqAw4F1hSGLsZIFnPemWbP5wJ7PDN8C70D/gQ+CHwIvvz19SwJYGmOYbFN0K3oIftl/l39CfeV4kXJfanNg9VQVSAg6CStWGzAL3fqd6rbaasv5vJ+vlKMMmTCQKIkRhACBAoAbgUeEeomdkJOZNqRasM29Vsy327LrAvxjDJEcSCxFO0pJG1aDYVFrW3OBeah9vX+5f5t9a3k8cyZrTWHZVfpI5zraKxQc1wtp+wzrB9ueyxK9oK+Do+yYCZAAie+D7IADgDiBiITjiTORWpowpYmxL7/pzXndm+0N/oYOwx5+LnM9ZEsTWExj32yhdHN6O37of3R/4Hw2eItx+2irXsVSfUUMN68npxc6B672SOZQ1gvHuLiXq9+fw5VujQWHooJagDWANoJShnqMk5R6ngSqAbc4xW3UXuTG9F4F4RUGJog1I0SZUbBdMmjzcM13oXxbf/B/W36jetp0Fm17YzBYaEtYPT4uXB71DVL9uex03MjM+b1JsPOjLJkjkACJ4YPfgAWAV4HRhGOK9ZFnm4+mPbM6wUnQKeCU8EIB6xFIIg8y/EDOTkhbM2Zgb6Z25nsIf/1/w35ee9x1Vm7sZMhZGU0YPwIwGCChD+b+L+7F3fHN+L4dsZykrJl/kDuJAoTrgASAUIHKhGSKBJKJm8qmlbOxweHQ4eBs8TYC+BJnIzozK0L4T2NcNmdAcFp3Y3xFf/R/a36yetl0+Ww1Y7lXtkpoPA0t6RxEDGn7oeo42nXKobv9rcWhMJdujqaH9oJzgCmAGYI6hnyMwZTlnryqD7ilxjvWjeZR9zsIAhlaKfk4mkf6VN5gEWtjc7F53X3Vf5B/DX1aeIlxu2gVXslRDEQdNT8luRTVA+DyJOLu0YjCNrQ5p8ybIpJnir+EQ4ECgASBQ4SxiTaRsJr0pc+yCcFf0I7gTPFLAkIT4iPgM/RC2FBOXR5oFXEMeOJ8gX/cf/R9znl/cyNr32DiVGJHnTjWKFUYZAdS9mrl+9RQxbC2XqmWnZCTeIt0hZ+BDIDCgL2D8IhEkJiZwKSLsb2/Fc9P3x7wNgFKEgsjLDNiQmhQ/lzpZ/dw/nfffIJ/23/nfbF5S3PSam1gTFSmRro3zScpFxgG7PTy43nTzMM1tfenTpxykpCKzYRCgQKAEoFshAOKvJF0m/6mJbSrwk7SxuLG8/4EIBbcJuQ27kW0U/VfeWoOc415133Xf4V/4nz5d+Fwu2eyXPlPykFoMhsiLhHx/7Tuxt13zRS+5a8royOYAI/thwyDcoAugECCn4Y3jeiVi6DtrNa6A8ou2gvrSvybDa4eMC/WPlVNaVrVZWFv43Y1fD9/8n9LflF6FnS5a19hOlWDR3o4ZiiTF1AG8PTD4xrTRcOOtDynjZu4ke6JUYT+gASAaIEkhSaLUpOBnYSpIbcZxiTW9uY/+K0J7hqwK6M7e0rxV8ZjwG2wdXB75X7+f7V+EXshdQRt3mLgVkRJSTo4Kl0ZCAiN9j7lbtRuxIq1CqgunDCSPoqAhBGBA4BZgQ6FEYtEk4Gdl6lMt17GhtZ159r4Ygq5G4ssiDxiS9JYl2R5bkd223scf/h/bH5+ekJ01WtfYRRVLUfuN6EnlBYaBYfzL+Jm0X/BxbKApfGZT5DKiIaDnIAcgAiCVobyjL2Vi6AorVm718pX24rsHf64DwghuDF3QfhP9FwsaGpxf3hKfbN/rn86fWR4QnH4Z7JcqE8YQUoxiyAsD4T95uuq2iTKpbp4rOSfJpVzjPWFzYEQgMWA6YNviTqRJJv+po20j8O607/kS/YGCJsZsir4Oh1K1VfeY/tt/HW3exF/+X9qfmx6E3R8a9NgTFQkRqI2ESbEFBADTfHR3/POCL9dsD2j55eTjnKHpYJFgF6A74Lthz+PwJhBpIqxWcBl0F7h7/LBBHwWySdQOMBHy1UrYqRsAHUVe8V+/n+6fv1623RybOxhfVVjR+Q3TSfyFSgESvKv4LDPor/WsJWjI5i3joOHqoJFgGCA+oIHiG6PCpmqpBayCME40VPiA/TvBb8XGCmjOQ1JCFdNY59tyXWiew5/+X9ffkh6yXMBax5gVVPoRB41RyS5EswA2+4/3VLMarzYreSg0ZXYjCWG24EQgMyADoTEidGRDZxFqDq2psU71qTnifmPC1wdlC7gPuxNbVsdZ8FwJ3gqfa9/q38bfQ94nnDvZjJbpU2KPjAu6hwPC/z4DOeb1QLFlrWlp3mbTpFZicSDqoAcgB2Co4aXjdaWMKJsr0W+cM6a32vxhgORFS0nATi1R/lVhGIUbXR1d3v/fvp/YX4+eqVzt2qkX6JS90PsM9UiChHn/sjsDNsPyie6qKvdngeUYIsThUKBAoBXgT2FnotblEWfJqy5urTKxNuQ7b3/6xG9I9Y03UR/U3Bga2s5dKp6nX7+f8V++HqqdP1rHWFDVLFFszWdJMcSjwBU7nTcTcs5u4yskp+PlL6LTIVcgQKARYEghX6LPpQznyOsy7reygjc7+01AHsSYCSHNZZFOFQgYQpsvXQKe9F+/n+Jfnp653PyaslfqFLTQ5gzTSJMEPb9qevH2a7Iubg7qoKd0JJfiluE5IANgNqBQ4YvjXyW96Fkr3y+8M5o4Ijy7wQ+FxEpDDrTSRNYgGTXbuN2d3x2f9B/g32beDFxbGeCW7BNQD6ELdUbkgkc99TkHNNTwtKy7KTsmBKPkoeVgjaAgYB1gwOJDZFom96nLLYFxhXXAOln++YNHSCnMSlCSFGzXiRqW3MoemV+/H/jfiF7ynT/a+9g1lP5RKo0PiMUEY/+EOz82bTIlbj3qSidbZIBihGEvoAZgCeC3IYfjsqXqKN5sfPAwtGN4/H1iwj5GtYswD1cTVZbYWc8cbJ4mn3Zf2J/OHxsdh5ueWO3Vh5I/TerJoYU8QFS7w3dhMsZuyWs+J7ckw2LuoQHgQiAw4EuhjKNqJZeohOwfb9I0BjijPQ+B8oZySvaPJ5MwFrxZu9wg3iDfdR/aX9DfHR2G25mY5BW3kehNzMm8hNDAY7uN9ykyja6R6spniaTeYpThNWAE4ASgseGGI7dl+Cj4LGPwZfSmuQ09/8JlByMLoM/HE8AXeNogXKneSx+93/9fkV74nT3a7dgXVM2RJQz0yFWD4X8xemA1xvG+LVvp9KaZpBniACDUIBmgEKD1Ij+kJKbVagBt0THxNgf6+/9yhBJIwM1l0WmVN1h82yodcx7PH/mf8R943hecV9nHVvcTO08qCtuGaYGuPMO4RDPJb6qrvegWZURjFSFR4ECgIyB3YXcjGKWO6IjsM2/4dD+4sD1ugiFG7Yt5T6zTsVczGiFcrl5PX76f+R+AXtodD1rtF8NUpdCpzGeH+IM3fn65qPUQsM4s+CkjZiDjvyGI4IUgNuAcoTHiraTDJ+IrN+7usy43nXxgwR5F+spbjugSyRap2bhcJp4o33gf0V/1Huhdc9skGEjVNZEADQAIj4PJfwg6Z3WB8XBtCqmk5lHj3+HaYIigLeAJYRaijCTd57tq0a7Kcw33gfxLAQ7F8UpYDumSzpax2YGcbx4u33mfzJ/ontJdU1s4WBHU8xDyjKiIL4Ni/p25+7UXsMss7SkTJg7jrqG94ELgASB24R7i72UbaBGrvi9Ks934XX0tgfMGkYtuz7FTgVdK2nuchZ6en7+f5t+WXpPc6Zpl11mT2g/+C18G18IEvUD4qPPW76SrqOg4JSNi+KEBIEMgP+B0YZojpaYIaW/sxzE19WK6Mb7Gg8YIk80VEXDVEJigm1Adkp8e3/Afxh9kndOb3xkXVc7SHE3YSV1Ehz/x+vp2PDGRrZOp1+axo/Ch4GCJIC5gDuEl4qokzifA624vPvNZuCM8/oGQhruLJI+xE4lXWBpK3NOep1+/n9qful5lnKcaDVcrE1WPZMrzhh1Bfzx1d5yzEC7p6sCnqOSzYm2g4KARID+gqCICJEFnFapq7iqye3bB++GAvcV5yjiOn9LWloaZ3NxJnkHfvZ/6X7legN0a2pWXgxQ4z87Ln4bGwiJ9Drhos4yvVKtYZ+zk4+KKoStgCyAqoIZiFiQN5tzqL63vMgG2zDuxAFPFVooczotSyJa+WZkcSN5CX73f+F+znrWcyNq712DTzc/bC2PGhAHaPMK4GzNALwvrFme0ZLeibWDfoBLgB2D5Ih+kbacSKrjuSfLrd0D8bQEShhNK0o90k2CXABpAHNFeqJ+/X9Nfpx5B3K7Z/daCExJOyEp/RVTApvuS9vbyLu3VKgDmxyQ34eAgiCAzYCFhC+LpZSroPquOL8E0fDjiPdUC9wepzFDQ0JTRGHxbAF2PnyBf7R/13z8dkVu6GIrVWJF7TM5IbgN4/ky5h/TIMGksBCiv5X8iwWFA4EQgDOCXodxjzyae6fdtgPIhNrt7cUBlBXeKCw7DEwWW+xnQHLReW9+/n91ftt5TnL9ZyVbGUwzO94oixWxAc7tWdrOx6C2Oqf6mTWPLYcUgguAHoFHhWyMYZboorOxZ8Kb1N/nufutD0Ij+jVjRw5XmmSzbxF4gn3jfyR/S3tudLlqaF7ITzQ/FC3ZGfwF+fFN3nTL47kKqkuc/pBoiMGCLIC5gGaEG4uulOSgcK/3vxLSTeUx+UAN/CDqM5FFg1VaY8BubHcofc9/UH+uewB1b2s4X6hQGkD2LbAawQan8uDe6ss9ukmqc5wSkW6IwIIqgL6AeYRCi+6UQqHvr5jA1NIv5i76Ug4cIg81sEaSVk1kjG8GeIR95X8ZfyN7HnQ2aqldyE7wPY0rFBgCBNbvD9wuyam38qdsmm6PPocSggmAMoGGheiMKpcLpDizUcTp1ofqsP7hEpomXTmxSiZaWmf4cbx5c37+f1V+gXmhcedml1kISp04xiX7Eb79jens1VnDTLIyo26WUYwchQCBFYBigtmHV5Cmm3upgLlLy2zeZfK2Bt0aWC6nQFVR9l8rbKR1JXyDf6l/k3xYdh5tIWGuUiRC7C99HFUI+PPm36XMsLp9qnSc8pBAiJiCHoDkgOOEBIwWltqi/LEaw8XVhOnV/TQSHiYROY9KKVp3ZyJy5nmOfv1/KH4ceflw9GVVWHRIuTaYI44PH/vO5iHTmcCwr9SgZ5S6ig2EjIBOgFWDjYnPkt2eaK0Svm3QAORM+MsM9iBKNEdGdlZtZNBvVXjBffN/2n5+evxyhGhcW9lLYjpqJ20T8f566pHWuMNtsiGjOpYOjN+E3YAjgLaChohskS2dfKv7uz3OyeEd9rIKAh+FMrlEJ1VhYwhvz3d8feh/A3/TenRzFmn+W4JMCTsHKPsTa//d6trW6cOIsimjNZYAjNCE1IAngM+CuYi+kaOdGay+vCXP0+JE9+4LSyDQM/xFVFZsZOVvcnjZffd/vH4yenVyuWdHWndKtDh1JToRjPzz5/zTK8H/r+ygVpSTiuWDeIBjgKiDMYrSk0ugSK9kwC3TJOfD+30QyyQhOP1J6Fl0Z0hyGnq0fvh/3H1veNVvSGQVVpxFTTOiHyILVvbK4QrOnLv7qpqc2ZAIiGOCEYAhgY2FN43rl2GlPrUWx3HazO6bA1IYZixMP4VQm18obNZ1Y3yjf39/93skdTNraV4bT7I9pSp1FqsB1uyC2DvFhLPWo52WM4zfhNOAK4DtggWJSpJ9nkutT74V0Rzl2/nEDkoj3zb8SCZZ7mb1ce95pn75f959ZHiwb/1jnFXvRGgyhh7SCdz0MOBezO+5Yakmm6GPIIffgQKAloGRhtCOG5okqIy44Mqj3kzzTQgWHRcxxkOhVDRjG28CeK1983/Ffit6RHJGZ35ZSkkaN20jyQ7A+eHkvdDfvcys+Z3NkZ2IqYIbgASBXoULjdeXd6WMtafHSdvs7/0E7hkrLidBXlJZYa5tCHcmfdx/F3/cekpzk2gDW/hK4Tg9JZUQevt85jDSJL/crdKebpIIieGCJYDogCOFuox4lxOlKrVNx/7as+/aBOAZMi5AQYVSiGHebTJ3Qn3ifwF/pHrpcgZoSFoPSs03AyQ6Dwf6/OSv0K69gKydnW+RTIhzghCAMoHThdGN9ZjwpmC30cnB3aPy4wftHCwxD0QSVbxjpG94ePh9/H93fnN5EnGRZUBXhEbVM7UftQpo9WbgQ8yOuc2od5rwjo2Gh4EEgA6Cl4d4kHOcMatLvEfPnuPA+BUOByMAN3NJ2lnBZ8ZymXoBf+F/MH0Cd4Jt9WC0USpA1ixBGP8Cp+3R2BPF+bIGo6uVSYsqhIGAaIDig9SKDZVGoh6yJcTa167sDgJfFwoseT8hUYRgMW3Odhd93H8Lf6h61HLGZ8xZTUm9NqQikA0b+N3icc5pu0+qnpvBjwyHwIECgN+BS4cekBmc5qoZvDjPt+ME+YMOmiOwNzRKoFp9aGVzC3s2f8h/vXwpdj5sQl+TT6I98ikSFZn/IepI1aTBxa8roEqTfYkOgyqA6IBChRmNM5hBpt22jcnK3QHzlgjuHWwye0WRVjBl7nB0eYR++n/KfQN40G50YklTvEFPLo8ZFAR77mHZYcUNs+yic5UGi/GDaICGgEqEmIs7luejNbSwxtDaAfCnBSUb3C80Q6BUnmPBb694Jn7+fyp+tXjIb6VjpFQ0Q9UvFRuNBdzvodp5xvizqKP/lWWLJoR4gHiAJIRkiwCWq6MBtInGutr/77oFTBsUMHpD7VTrYwdw5nhFfv5/A35heERv7mK6UxlCjS6nGQMEQe4B2ePEerJRouCUioqdg0yAsIDHhHOMepeMpT+2F8mI3fvyzghiHhMzSEZyVxFmtnEMetR+6X9Effh2NG1AYHxQXz5wKkIVd/+u6YvUrMCnrgKfM5KZiH2CDYBagV2G747RmqmpCbtvzknj+/jhDlkkwTh/Swdc3GmWdOR7j398f6p7N3RZaWJbu0rhN2Mj2Q3o9zHiW80CurioAJpIjumFI4EagNaCQ4kwk1KgSLCYwrnWEuwBAuIXEC3pQNhSVGLpbjd4933+fzt+vXirb0tj+1MtQmouRRlhA2Pt8devwzaxEqG/k6KJCIMjgAqBtoUEjrSZb6jFuTHNIeL09wQOqyNDOC9L31vSaaB09HuYf29/eXvVc71ohlqbSX02vyH+C+P1E+A2y+23yqZRmPGMAYW+gEmApYO6ilGVGqOrs4XGGNvH8OoG2hzsMYFFAFfkZbpxJ3rrft9//Xxbditsu15yTs07XCe8EZT7jOVP0IG8uqqEm1OPh4ZigQ2Ak4LgiMSS9J8IsIbC4NZ37KUCvxgcLhRCDlR/Y+9v/nhlfvp/sn2cd+ht4WDsUIQ+NiqhFG3+Q+jR0r2+oqwOnXmQRYe6gQOALoIriMqRwp6urhPBYdX76jgBbRftLA9BOFPZYnlvtXhFfv1/0H3OdyZuI2EqUbg+XCq1FGz+L+iq0oi+ZKzNnD2QFoeggQaAVIJ6iEeSb5+Lrx3ClNZQ7KYC6BhoLn1CiVT/Y2VwWnmXfvN/Yn36dutshV8wT208zif2EZL7TuXcz+W7BKrHmqeOA4YegSGAEoPciUmUB6Kqsq7FgNp58O0GKx2EMk9G71fZZpdyzXo5f7d/RHz7dBVq51viSo03fyJgDN/1rd97yvC2p6Upl+qLQ4RxgJKApYSMjAaYuqYzuOfLOOF/9wgOJCQhOVhMMl0ma8d1v3zXf/V+InqCcVplClYNRPEvVxrqA1/tZtexwuSvlp9JkmeIP4IDgMWBeIftkNqd2K1mwPLU1upkAecXrC0EQkxU8mN4cHl5rn7sfyl9e3YWbE9elE1pOmolPg+Y+Czir8zNuCenSpiujLCEkoB0gFeEHYyIlzumwbeNywDhbPceDl8kfDnKTK5dn2ssdgF95n/DfqF5qXAkZHZUHkKvLc4XLQGC6oTU5b9LrU6dcJAXh5CBCYCOgguJS5P7oK6x3MTq2S3w8AZ9HRozGkfZWMdnbHNne3l/gH96e4pz7mcFWUhHRzOlHREHQ/D12dvEo7HooDOT9Ih+ggeAo4FGh8CQxp3urbPAftWk628CKRkVL4FDx1VQZZ1xS3oQf8d/aXwRdftpgVsbSlU20iBCCl7z4NyBx/Gzz6KqlPSJBoMagEaBg4alj2GcUKzvvqTTx+mfAHUXiS0oQqhUb2T9cOl56n7Wf6Z8dHV6ahJctErtNmEhwgrK8zXdv8cZtOSisJTxiQCDGIBQgZ+G2Y+ynMCsf79U1JLqggFmGIEuHEOLVTdlnXFWehl/wH9DfMF0dmnAWhpJFDVVH5IIiPH12pTFGbIkoUOT6YhtggWAxYGeh2KRvZ5Dr2nCkNcI7hYF+hv2MVNGZViYZ2tzfHuHf2p/Jnvfcthmd1c7RbwwphqwA5zsKdYTwQqur52JkAiHeoEQgNSCsIlrlKyi+rPGx2rdMPRZCyQi0TeqSwpdXWsrdhp97n+Qfgt5jW9mYgNS7z7JKUMTHPwU5e3OZLojqMaYzoyfhH+AkoDWhCmNQ5nAqB27wM/65RD9PxTEKuE/41IpYypweHnEfuB/w3yIdWpqyVseSgA2GCAgCdvxDdt3xdCxv6DVkoiIMIICgBGCTYiAklSgVbHyxIXaV/GkCKofpDXWSZVbSWp3db584H/Cfm15D3D3YpRScj8yKosTPfwO5cTOHrrLp2eYd4xghGiAsYA5hdmNSJocqs68v9E76IT/0BZaLWFCMVUpZb9xiHo4f6d/0XvXc/xnpVhXRq0xWRsaBLjs+tWkwG2t+pzaj3uGMIEmgGeD1oo0liClGbeGy7fh7PheEEUn2jxkUDthzG6jeGx+838rfS12M2udXOhKrDaYIGsJ7PHl2h7FVLEwoEeSE4jqgQSAb4IZiceTHaKgs7nHud3i9GsMiiN2OXBNzF7zbGp31n3+f9F9YXfkbLZeUk1OOVkjLwyd9GvdZsdMs8yhf5PhiE+CAoAOgmOIyZLloD6yPcYz3GLz/go8IlA4eUwIXmRsDneqff5/9H2fdzZtEl+wTac5pSNrDMb0gd1pxz+ztKFik8aIPoICgCaCmYghk2Sh5LIIxyDdavQZDGAjcTmKTfxeLG2fd/d9/n+gffN2MGy3XQVMtzd/IR8KZ/Ik2ybFLbHpn/ORxoe7gQmAvoLDidqUoaOYtR/KguD797sP8SbQPJdQl2E5bwV5pH7kf7l8QXW7aY5aQEhyM9wcRwWD7WLWsMAvrYqcV48JhvSARoADhAyMGpjCp3m6mc9o5hr+3RXfLFNCelWqZVRyBXtxf29/AXtMcp5lZ1U4QrssrxXj/SjmU88uunin1pfUi96DO4AMgUmGxI8pnQGutcGW1+DuwwZrHgQ1w0nwW+dqInY9ffd/OX4ReLdthV/9Tbk5cCPpC/fzcNwnxuSxXaAwktuHvIEKgNWCA4pUlWSkq7aGyzji9vnrEUApIj/NUpBj03AgeiF/q3+2e2hzCmcMV/1DiS5wF4X/neeQ0C+7OqhcmCaMBIRCgAKBPIbCjz+dOK4VwiLYmO+iB2gfEzbVSvNcx2vMdp59/n/XfTx3aWy+XcJLFjd3ILAIm/AQ2ebC5q7GnSGQdIYWgTqA5oP6iyyYD6gSu4jQr+ez/7kX6S5vRIZXgWfNc/t7v3/4fqt5CXBqYkhRQT0LJ3APSfdv37/IBrQDolmTkIgKggOAjoKUidSU6aNJtkzLMeIn+lMS2CnfP55TXmSIcaJ6WH9+fxR7QXJWZclUMUFDK8gTl/uN44jMW7fJpH2VA4rGggeA4YFDiPOSjqGPs0/IEd8C90YP/yZQPW5RnmJBcNl5D3+wf7l7S3O2Zm1WBUMzLb4Vgf1a5SjOw7jvpVuWmIoSgw+ArIHZh16S26DIsoDHRd5C9pkOaibYPBJRXmIZcMZ5CX+yf7p7RnOkZklWzELiLFcVBv3Q5JXNLrhjpeKVO4rcggiA3IFFiAmTw6Hss9nIyd/l900QHih5Po9So2MWcWt6Sn+Ffxp7MXIfZVtUhEBRKpISJvrw4dHKpLUuoxuU+YgxggKAgYKXiQKVV6QHt2PMo+Pu+14UESwnQtJVV2Ydc6t7sX8If7Z57W8JYoxQGTxxJWkN4/TE3PDFPrFwny6R/oZCgS6AzoP/i3aYvKg4vDTS4OlcAsQaLzLCR7BaR2rzdUd9+3/4fU53PmwuXa5KbDUwHtYFRu1l1Ra/LatnmmGNmYRggOCAFIbLj6mdLK+tw2rajPItC2YjUDoRT+RgH289edt+xX/xe4RzzWZFVohCUyx3FNr7YuP6y4G2wqNxlCCJOoICgI2CxIlhlfak77eYzSPlrf1OFhsuMUS9VwNoaXR4fOJ/hn5yeN9tMV/1TNk3piA7CIHvZNfLwI6sb5sTjvmEeoDAgMmFZo86ncGuU8Ms2nDyNguSI5k6bk9JYX5vhXn9frF/m3vgctZl+FToQGgqUBKI+fzgm8lEtMah05L7h6eBFIBRg0CLlZfYp267mdGF6UkC+BqkMmdIcFsHa5R2qH3+f4B9RXaSatlasUfTMRMaVgGN6KXQh7oJp+iWwIoIgwqA5IGFiKuT7aK1tU7L5uKa+3gUkCz5QthWbGcUdFV83n+Mfm14u23eXmZMBzeQH+UG+O241RS/56r3meiMOYRBgCWB3YYykcCf+bErx4jeLPcmEIQoVz+/U/dkVXJWe6N/EH+jeZJvPWExTx860yIyCi7xudjEwTCtxpsyjviEdIDRgAyG848lnhewGcVd3AD1Dg6TJp49TVLUY4hx4HqBfz1/F3pBcBpiL1AvO+gjPwso8pjZgcLHrTecfI4ghX6AxYDxhdGPA577rwnFXtwS9TIOxybePZNSGGTCcQh7j38pf9t52G+DYWlPPjrSIg0K5fBR2EXBpqxAm7+NqoRagPuAh4bHkFefpbH8xoreZPeTEB8pE0CMVL5l/nLHe8N/yn7leE5ubV/YTEY3jh+bBmft69Qbvtqp85gNjKuDH4CNgeeH7pI2oiS1/srp4vb7LBWQLS1EI1ioaBl1+Xz4f/l9Dnd+a7pbYkg0MhEa5wC253XPG7mFpXmVl4lXggKAr4JFinaWyqacuifRiOnKAvIbAjQISihdoGzXd1l+539wfBZ0LWc2Vt1B7SpMEvT44d8RyHOy4p8YkaqGAoFagLeE742lm06tOsKV2XTy3AvNJEs8alFTY1Fx2HqGfyx/znmgbwphn04YOVAhNgjK7grW8r5tqkmZNIy0gx6AmIESiEuT06ILtjLMZuSz/RYXkS8qRvtZPGpGdqB9/n9IfZl1P2m4WKpE4i1HFdT7iuJrymy0b6EzklWHQ4E8gEqERI3PmmKsScGx2KnxNAtNJPU7OlFCY1Vx5HqNfx9/n3lFb3lg1E0SOBMgzAY/7XHUYL33qAmYQ4sngwmACoIUieGU96SyuEnP0+dVAcoaLjOFSepcl2zpd21+338wfIZzOmbSVANAoiifD/v1vdzpxHSvPJ37jkSFfYDWgEyGqJB/nzeyEsgu4JL5NxMZLDRDmld6aCR1FX38f7p9ZnZLauZZ4UUJL0sWpvwj48rKlrRuoReSMYctgUmAj4TTjbWbpq3swqva7vOtDeAmgT6aU1Fl7XLie9F/k34yePJsR13TSV8z1ho1AYnn2M4nuF+kUJShiMuBFYCTgx+MYpnRqre/PNdp8DgKnyOTOxpRVGOEcRR7oH/5fiZ5Ym4fX/pLuzVLHagD4On90AW66KV4lWGJIoIIgCiDYotgmJupX77S1f/u3ghhIn06NVClYgtx0HqOfxN/Y3m6boZfaEwoNq8d/gMj6izRIbrzpXeVWokcggmAOIOHi5+Y96nYvmjWru+fCS0jSTv0UExjjnEje6d/6X7yeP9thF4jS6o0BBw2AlHoZc95uICkTZSMiLiBG4DGg5KMIproqyjBAdl38nwM/iXvPVBTQGUAc/572n9sfsJ3I2wJXB5INzFFGFL+b+Swyxy1oqETkhKHFYFcgO+En44DnYSvXcWm3V33cBHKKl5CL1diaD11OH3+f3F9q3UAafVXQEO+K2kSUPiI3iTGKbCBnfWOHoVogASB7IbhkW+h8LSUy2jkZP5xGHoxckhkXHlsBniPfs1/s3tscltkF1JjPCckaAo58LLW5r7TqVyYPIsBgwSAZIIIiqCWo6dcvOzTVu2IB2sh5zn1T6diNXECe6N/537VeK9t6100Sl0zXBo/ACDmFs0wtmWijJJOhyaBVoDohKqOM53nr/3Fhd54+LsSNizTQ5RYmGkmdrh9+n/UfGd0D2dbVQtABShNDvvzKtrywVqsS5qLjK6DFIDmgQ+JQ5X8pYe6BNJ168QF1h+POONO3WGxcL16k3/+fgR5520dXlRKYjNAGgAAwOWdzKi13aETkvaG/4BwgFCFaY9OnlyxxceU4Ln6GBWTLhFGk1o5a0t3R37gfwR83HLMZG9SizwRJA0Kmu/a1ea9xahfl3GKi4ICgPSCP4uKmEOqqL/P16/xLAwkJns+JVQ0ZuFzl3z1f9Z9Una5aZZYpkPOKxQSk/du3cTEpq4FnLGNRoQsgJKBaIhilP6khbkV0arqKgVzH2E4407+YeJw6Hqjf91+n3gtbQZd20iLMRcYmv024w/KPLO5n16Q1oWUgNSAk4aSkVehNbVPzKblIACaGu8zBEvaXpZuh3k2f2J/CXpmb+9fT0xgNR8cpgEb56PNWrZDoj2S+ob4gHuAh4XljyOflrJnyZjiEf2qFz4xrUj0XC9tq3jmfpt/wnqQcHdhHk5eNzQeuAMU6W3P5LeAoySTiIctgVuAG4U5j0OekrFPyHvh/furFl0w80djXMpscHjRfqZ/5XrDcLFhWU6SN1se0AMa6WPPzrdiowSTbochgWOAP4V+j6yeILIAyUri4/yeF1Ex2kgwXW9t3nj+fol/eHoEcKNgAU37NZUc7AEu54bNF7bood+RrobXgJmA+YW7kGSgRrR+ywjlxP+BGhU0XUtRXxBv6HlefzN/anlDbjxeCkqSMt0YDv5V49/JzrIon8qPZIVrgBmBZYcKk4KjFLjXz73pnwROH5o4ZE+pYo1xaHvIf31+lHdba11aW0VELSoTNviZ3YPEEq5Fm/OMvoMRgBWCtImYli2oq70e1nDwcgv0JcU+ylQIZ650IX3+fyd9unQXZ9pU0z79JXULavAQ1pW9Eah7lpyJB4IUgNqDLY2jm5euMMVs3ij5MxRXLmlGVFsobCR4vn6pf9x6jXAxYXlNRzalHLoBu+bdzEq1EqEckSGGn4DXgMWGJpJ3ov22zM7S6OIDyB5LOEZPsGKqcYV70X9cfjV3r2pbWf9DkisuEQT2S9s6wvKrdZmXi/qCAoDQgkaLApllq5rBotpb9Y4QAyuHQ/5Yb2oQd05+1X+Te7pxumJBTzI4lh6XA2/oV85+tvqhuZF3hriAv4CMhtyRK6K9tqLOxuj4A/0emjilTxJj/3G+e95/LX6/duppRFiZQucpSw/+8zvZPMAjqvOXgIpoggiAfYOgjAWbBa7DxDTeMfl+FNwuF0cUXN1srnj9fn5/LHpGb0lf8UorMw4Zzf2j4tHIhLHPnZeOkYQwgKqB7IiklTqn4rye1UzwsguQJqo/2FUYaJF1pX32f2d8InOUZGdRfTriIMQFY+r/z86376JXksqGz4CugGmGvJEiotu28s5M6bEE4R+ZOapQBGTCcjZ88X/Gfc11ZmgtVvo/0ybgC2Lwm9XIvA+ncpXBiJKBOoDLhA2PiZ6GshrKLOSI/+kaDjW9TOBgiHD5erh/jX6Fd/RqbFnAQ+8qIBCR9InZSsD+qbCXOYo5ghCA14NjjUKcw6//xuLgN/y5FyMyOErZXhJvIHqAf/F+enhmbEZb5kVELYYS6/a72zzCnKvsmAmLm4IFgGiDm4wwm3quk8Vn38D6WBbnMC1JCF5/bsx5aH8Qf8Z41mzPW3xG3C0XE233KNyRwtmrEpkdi6GCBYBog6KMRZuhrs7Ftt8j+8oWYDGmSXde2m4Ienx/8350eEtsDFuFRbks0xEW9s/aSMGzqiGYcopLgg6A2IN6jYGcN7Cxx9LhX/0MGYwzn0shYBtwzHqyf5J+eXe8avVY+0LXKbgO6PK112i+NagnlhqJq4E2gMuENY/1nkyzRsu+5XQBGh1gNwdP8GIqcvt77X/Ofbl1Dmh0Vc0+KiXDCeft5NIFunmkRJM4h+mAo4BqhviRwaL5t57QhOtjB+oiyDzCU8Bm23Rmffp/dXwEcxdkZlDgOKQe8QIb53PMQLSpn6qPB4VBgJOB7oj5lROoYL7Q1yzzJQ9lKqBDoFlXa+13yH6Sf0N6Gm+gXp9JFzE2FkT6mN6ExEmtBJqii9OCA4BWg6OMeJsfr6nG8uC6/KoYbDO2S19gZ3AKe8R/XH7gdq9paVfvQFUn1wvH733US7tnpd6TiYcBgZWATIbgkcGiIbj40BTsJAjSI8c9wVSlZ4p1xH3sf+l76nFrYixOJjaCG4r/l+MCyRWx+ZyljdiDDIBwguaKB5kkrFDDbN02+VMVaTAoSVxe/m5AepV/vH6+d/Jq9lipQiApmA1n8erVeLxMpnuU4ocegYOAGoaekX6i67fY0BLsQwgOJBk+IFUCaNV17X3jf597V3GJYftMrDTMGav9peEZx1OvfJuLjDuDAoAHgyWM65qgrk/G0ODW/AQZ+zNoTBphDXF6e91/AX77dS9oSlU5PhwkOgjx66LQpbcyolaR54VygD2BP4gglT6ntr1w1yfzfw8WK5BErVpXbLF4HX9Lfzl5M23OW+dFjywHEaj019jyvkCo35W1iGuBWoCThdKQi6HrtuTPPeucB5wj2z0OVRBo8XUCftx/Z3vbcL5g20s4Mw4YtPuP3wPFYa3TmVKLlIIJgNKDvo1RncWxGcoY5WsBrR15OHlQfWSIc9t8/n/LfGhzTmQ6UCw4VB0IAa/kr8lgsficeo2qgwaAvIKri2GaJK74xa7g8/xfGYo0GE3SYa5x43vvf559DHWnZiVTgDvjIKMEKOjczBu0Ip/8jnmEHYAigm6Kl5jpq23D9901+r0WIzIJSzBginBFe9h/B37rdelntVREPcMihAbz6XrOe7U2oLyP4IQvgOOB6YnZlwGrbMLt3DD5yxVPMVtKrV8zcBh70H8ffhl2JWj2VIM9+SKtBgvqgs51tSegqY/ShCuA8oEQih6YZavuwovd5fmMFhMyFEtOYK9wYnvef+l9m3VfZ+xTPjyGIRwFcOj0zAq09Z7Gjk6EFYBSguiKaJkYrfjE1d9S/P8YajQvTQxi9XEZfPd/Wn1ldItljVFtOWUe0QEm5dbJRbGwnCSNaoMCgBeDg4zLmyiwk8jP43kAHh1KOJlQ0mTrcyF9+39UfFtykmLFTQM1jhnN/DTgOcU7rXSZ5IpKghiAaYQGj2SfsLTSzYPpWgbfIp49OFV6aGh2S369f6l6U29NXnZI6y76EhH2qdk2vxKobJU5iCaBj4B9hqKSYaTPusnU+vDvDS8qRkTfWtBsL3lYf/t+G3gTa41YfEEPJ6EKp+2d0fS3/aHZkGqFRoCxgZmJl5fyqq3Cj902+ioX7jIUTFFhjHHxe/R/Yn1cdFhlG1GyOFwdggCi4zfIq69DmwyMz4IHgNiDEY4rnlGzbcwz6DMF8CHtPMRUPGhRdkl+u3+TehVv2F3BR/MtxRGr9CfYsb2qpkKUbYfXgNaAa4dAlKmmtb0w2Lz03RESLuVH/V02b6p6wX83fiB252dIVEk8KCFOBDvnb8tfsledb418gwKAMIPcjIWcXLFKygXmGQMGIEg7dVNJZ7x1Dn7Of+V6lW9zXmRIji5LEhP1bNjVvbKmN5Rch86A44Cch56UPad/vi7Z5fUjE2IvJ0kaXxRwMXvcf9d9PXV/ZmNS9zmBHnIBUOSfyNWvPpvui7SCC4AXhKOOIZ+1tDzOYOqmB4ckfT8fVy5qqnfdfmZ/PXm1bHdadkPqKDYM3u5r0l64FaK8kD+FN4DpgT+KyZjCrB/FleC1/fIaxja3T3Vk5nM8ffZ/8XthcdZgLkuNMU8V8Pf+2v+/YahklQiIBIG1gCGH8pN5pr29gthf9csSOy8rSTtfQnBXe+V/rH3LdLllRFF/OLwcc/8w4oHG3q2Wmb2KHIIpgACFXpCpofe3GdKs7ikMAymwQ8RaBW17eXx/tX4xd1Zp4FXYPYUiWgXo57zLWLIXnRqNO4MCgJuD1o0mnq6zSc2Y6RkHOiRtPz9XaGrkd/p+SX/LeNprJlmuQbMmpwkX7JbPq7W4n+yOLIQLgMOCLozMm8iwAcog5qAD8SB+PM5Uk2i+dox+kn/AeWhtMVsWRFMpWAy07vzRvLddoRKQyYQegFKCRouAmi6vNcg95MEBMB/xOodToGcldlB+rn8tehhuFVwdRWsqcA287+fSf7jyoXaQ/YQmgDSCC4sxmtau3cfr430B/B7POnZTm2codlN+q38devVt21vJRP8p7wws71HS7rdxoRGQwYQcgGOCeIvdmr2v9sgr5dQCVyAaPJtUhmjHdpZ+iH+PefxsgFoZQw4o1QoG7T7QDbbgn+yOHIQIgOmCl4yLnOmxhsv+58QFPCPJPuxWVGrydwh/NH9yeB9r91cDQJEkIQdN6bXM6LJQnRmNJoMEgN2DfY5Qn2q1l89q7E4KoyfPQlRa6myNeYp/jn6ndkJoKVR1O38f0AEI5MbHmK7embyKBoI2gGeFUJFKo1m6OtV08mwQfi0TSLNeInBqe+x/aX0CdD1k905aNc4Y5fpD3YnBPqm3lQeI8YDXgLuHPpWgqNLAf9wg+hMYtTRwTtpjxHNOffB/hXtMcOFeO0iZLXMQZfIV1SO6DKMVkT6FLYArghuLgZqCr/bIdeVrAzIhJD21VYlpiHfqfkd/mnhAa/ZXzj8dJGsGX+ihy8ixRZxHjLOCEYCGhNOPWaEfuOHSJvBKDqYrlkabXW9vE3vif5d9UnSWZERPijXWGMH69NwbwcCoPpWth82AAYFGiDSWB6qjwqvejvyiGjs3wlDJZSR1+H3Gf3V6UG4EXJVEUynCC4ntV9DNtWefZY67gwKAb4PRjZWeyrQ1z1nslwo/KKdDR1vMbS16uH8efnR1N2ZBUb43Gxv0/Pfe08IdqjaWPYj6gNaA1IePlUOp1cHl3d77ExrTNn9Qp2UZdfh9xH9jeiFurlsURKYo7gqZ7FrP17SOnsCNYIMDgNmDro7jn4O2RtGs7gsNsCrtRTpdRm8Me+N/hH0QdBBka05ZNFIX+vgH2ym/9KbGk7SGfYB5gZyJb5gerXzGG+NcAYsf8Tv0VClpa3fsfj1/WninaulWPz4OIu4DluW8yAOv4JmIitiBUIAFhqaSe6VzvTPZJ/ebFdcyME0nY31zRH3uf1J7tG+9XXFGJCtiDd3uUdFstrafe461gwKAmINDjmmfD7bs0HjuAw3SKjFGkF2ab0d77X9HfXtzGWMPTZ8ySxXA9rvY87z/pD2SwIU/gAqCCIu2mi6wN8pU59kFCiQtQKNYCGw+eYR/fn45di9nPFKTOKwbL/3b3mvCg6mQlbeHw4AbgbuIMpetq//EteEnAJgeSDuSVABpZ3fxfjF/IngrahlWFD2LICMCm+O1xhmtQ5hkiViBl4Ash7aUbqgxwZTd8vuMGp83f1GsZu51ZH6Qf2B5MGzBWDNA8COaBfHmucmjrzGan4rWgVaAN4Yhk1emvL7o2jn57xdDNYNPKmX2dP59u38TelptS1oBQuQllAfU6GvLDbFDm0+LH4I7gMGFXpJXpZS9rNn+98YWPTStTotkk3TVfch/Tnq5bcNahkJqJhIIQunDy06xbJtkiyaCOoC+hWGSZqWyvdvZPvgUF5M0Ak/XZMt08X2+fxh6VG0uWsVBhCUTBznowMpjsKya34rpgVGALoYrk4OmF7932/v52BhCNoFQCmacdUx+l39reSNshli6PzEjmAS75WfIU64JmciJdYGMgB6HxpS5qMvBhN40/Q4cRDkeUxdo83bTfkF/NHgXar5VWjxqH6AAzuHAxC6rmZY3iOGABoGliEqXGazaxQjj6gGxIIs9xVbjarR4aX+aflR2FGe/UZc3Jxos+3nc3r8Mp3qTUIZVgOWB6IrWmr+wV8sM6RwIsyYBQ1lbSm61et5/dn2hc/Ria0xcMWATPvTN1dy5EqLYj0SEBYBcgxeOk5/ItlXSl/DEDwIuhkmtYBhyvHz5f5x76G+NXaNFlikPC+Dr483fsnGc7otTgjGAqoVqkrGlV77n2q350xiANu5QimYLdoR+cn/IeOpqrVZEPTMgNgEm4t7EHKtqlgaIy4AogRiJIphhrY/HHeVHBDAj/z/8WKds03m2f/Z9rHRoZCFOLTMoFd/1MNfzuteiT5B4hAiAQoP2jYGf1LaL0vzwVBCyLkNKYWGncgx9738le/ZuHFy7Q0cndwgm6TLLarBqmoWKsIF0gOOGm5TJqDbCXN96/q4dGzv5VLppHXhEf8F+m3ZPZ8lRVTeKGTb6Odt0vqKlRJKEhSiAgoJwjFidNbSmzwPudg0aLBRItF+McYd8/H+ze/BvaF05RdkoAQqO6mXMXLEVm+qK1YFkgK6GUZR6qPLBLd9l/rYdOzsqVe9pR3hUf6d+THbCZvtQSjZMGNX4zNkVvW6kVpH3hBKA9IJvjeKePLYU0rfwRxDbLpZKyGEHc0V943+4ehRuvFrcQfgk1AVV5mXI2K1NmBSJG4HfgGWINpdtrL3GjOQIBEcjXkCIWTttQnrRf5F9pXOnYqJL/C9nEcLx+tLztmSfvY0Tgw+A34Q5kVukG73z2SH5uhjQNoxRSGewdtJ+Ln++d/VovFNgOX4b7fub3HS/QqaTkpyFKICOgqmM250UtejQou9dDycuHEqDYepyQX3jf6Z63m1SWjdBFyS+BBvlHseirEiXYYjZgCeBR4m4mIiuXsmT50oHjyZzQy5cOm9oe/h/onyacY1fmUc5KywMYOzIzUqympsei9yBZ4DXhsWUValDw/TgjwAkILw9gVfca4l5r3/tfVx0lmOjTPAwMxJX8lHTELdWn5mN9oIVgCSF05FapYK+u9s2+/waFjmlUwJp2Xc9f7h+UnaRZm9QSzXWFvb2pNfVulSipo/4gwKABIS/j3miB7vh1zz3IheZNblQ0GZ/dsp+LX+hd51oElNYOBkaOfq02oK9eKQkkb2ECoBVg2uOmqDBuFzVo/SfFFIz0E5gZZl1dX5of2F40WmgVCI6/xsc/HbcCb+vpfyRL4UVgACDwY2un6W3J9Rp83YTSzL4TcFkN3VRfnx/pXg6aiJVsDqOHKD859xjv+6lI5JAhReA+YK5jaqfrLc81I7zqBOHMjdO+2RidWR+cH9zeN9pnVQGOsUbxPsG3I2+NKWWke+EDYA+g1COkKDXuJ3VEvU2FQU0i08KZhZ2rH4/f8Z3uWgNUx84oxmI+dXZjLyHo12QRYQCgNuDkY9noiy7Ttj19x0YwDbrUeRnRncYf9l+jna9ZmZQ9DQlFu71WtZqufagi45VgwuA44SPkUClt75V3Dn8WRyuOkdVc2rZeI5/JX6zdNNjl0x6MEYR+PCe0Ti1lp06jD+CSIB3hmaUM6mKw7zh3QHhIbw/hVmYbat66X/8fBJy3l+KR6MqAQus6rPLEbCLmZOJLoHmgMCIPJhcrrfJjOjhCKYo0UWDXihxjXz3fy17fm66WiRBYCNWAxbjsMQXqgKVyYZZgBqC8Is6nd20VNHK8DsRkTDJTBJk7XRDfnt/gXjGaT1USTmkGkn6S9q5vHyjM5AdhAKAJIRCkJOj2Lxz2nn62hqCOXRU9WmheIV/L360dLFjP0zhL2oQ5e9p0P6zfZxoi9yBdoBPh/WVdqtuxiDljwWjJUhDk1zib/N7/n/Be4BvB1yYQtgktQRE5J7FwKpnlfeGYIAPgumLSp0StbjRXvH4EWgxpE3WZHx1gn5Rf9t3m2iQUic3KBiX95HXK7pPoZuOR4MPgCqFQ5KBppHAw94g/4sf6T1AWNhsWXrhfxV9InK+Xx1H2CnYCTTpDMpnrhWYi4jMgFqBLIqvmtCxDc6N7UEOCC7OSrFiInT7fZl/33g9aqlUizmpGgn6y9kNvMGij4+5gwWAs4R0kXSlYb+M3fj9hh4WPaVXdmwqetx/K31Ect5fLUfQKbUJ9ui5yQyuwZdNiLaAe4GRil6byLJGz/juyQ+RLzlM32PydFV+aH8ZeOJow1IyN/0XNff/1n25nqAJjvWCH4C2hV2TLqjKwm/hGAKfIt5A1lrQbnp7/X8OfO5valzKQsIkSwSM46zEuKl3lFKGOICQgjWNcJ8QuHLVpfWIFu41w1EuaLV3Tn95fkR1SmSrTPcvFBAi70zPsLI0m2aKZYHKgJ+IYJgCrwTLiup9C68r+khtYWhzuH2vfyp5l2rvVKE5fhqY+R7ZObvnodeOToMRgFiFyJJ/pxnC1OChAVQiv0DZWudukHv+f+R7h2+7W9BBgiPUAvfhGcNLqFeTo4UagBuDc45goZ+6gdgI+QQaRjm0VHlqIHmvf7R9UHM3YZxIJSvKCrfpIcolrqOXHoiggKqBKot9nHy0i9G38dgStzIwT1pmqHYAf9R+JXaJZR1OcjF0EUzwL9BIs4ibh4ppgc2AvYixmJav5Muz698MLy11SrpiW3Qofnh/NHjZaG5SdjbTFqf1LNWTt9qerYxFglaAAofXldOrfsf45iIIwiihRr5fZHJTfct/pHlFa6hVQTrrGsP5BtnrunqhbY4Ngx+A14XRkx6pS8SD46cEfSXKQ4Bd43ChfO9/knrpbN5X3zzAHZ38s9s/vVGjq4+jgwqAH4WKkmOnP8JN4XACaiP9QRVc7W8rfPp/F3vYbSBZWj5XHzL+LN2Dvk6kVZD0gwSAyYTxkZemU8FU4H0BjSJDQYhbkW8AfPx/QHsdbnhZuT6yH4P+bd2xvmqkYpD4gwSAzYT/kbSmgsGW4M4B6CKgQd1b028lfPp/EHu8beZY/D3THpD9ddzJvaSj0Y+sgwqAKoW0krunzsIS4mQDeyQSQxFdsHCVfO9/g3qwbGhXIDy4HFj7SNrPuwOiq44bgx+A64UalLOpO8XN5D0GQSeTRRxfG3JCfct/innsavJUHzldGd336tbMuJSf/4xXglaAIodBlqus08jK6FoKNCsVSethAXQWfnh/D3hbaHRR7TS+FCDzZdLPtGuc6Ip8gc2A6ohCmbSwo80O7rUPSTCGTWZlQnbvftR+8XXjZNlMfC/VDiftxszxr6eYh4ivgKqBZ4s6nee1uNOc9EoWbTbKUmlptnijf7N9CXNhYAdHviigB/rlIsZPqnCUC4YhgBuDxY5Pol68Itt3/AseiT2/WMhtLHv9f+N7KW+wWuU/piAh/6rdl74TpPiPrIMMgFiFNJOnqDLE6+OZBeQmeUU0X0pyZX29fyl5HmqoU1k3Kxdf9VDUTrZznXyLrIGygKCI6ZhpsHzNGe72D7YwDk7vZax2GH+efkN1sWMhS00tSwxs6hDKfK2xlkmHWYBfgjaNG6C9uU7Yqfl2G1Y7DFekbJt69H9PfO1vrFv5QLMhDwBq3iC/ZqQekLWDDIBkhV+T/6jBxK/kiQbvJ4ZGJGD8crp9m399eOBo3VEUNYwUkfKH0cWzY5saiiWBI4EXil+bw7OK0ZnymxQpNfZR+GiPeKB/q33TctxfHEZmJ+YF/OMLxFmo2pIWhQaABYTNkHalicAb4PABoyPQQkFdFnHmfNt/vnn+aqdUTjj1F+r1lNRTtk2dSIuNgc6AF4nUmdOxYc9k8IISUjN7UOxn+nd/f/J9b3O2YBpHbijhBtfku8TWqCeTN4UHgPWDupBspZTAQuAzAv0jNkOlXWZxEX3Pf295ZWrCUyQ3lRZr9BPT77QonIKKQYEPge+JP5vDs7vRA/M4Feo1wVKtaQp5vn9NfeVxVl4FRNUkAQP24CPB0aX0kAyEBoAshSCT46jlxCTlUAf4KK9HQ2HccyV+YH92d/lmF0+GMWYQGe4UzbevH5j9h3uAJILZjNafvrmz2H36rBzNPI5Y721oe/5/XnvcbXBYpTx7HEX6d9iBuaCfsYwRgoWAK4h0mDawus3f7j8RYzLkT6Fn5Hd/f+Z9NXMyYDtGMidTBRLj58Ilp9CRcoQCgNSEjpI0qDPEh+TXBqoojEdBYetzMX5Ufz53hWZfToowMA+97K7Laq4Pl0+HUICUgvCNk6EQvHzbjv3OH8A/EVvHb1587n8zepdrKlWMONIXXfWs0zS1LJxmii2BLYFnijCcPLW603H17BerOEpVtGtGevB/SXyTb7xaSD82H9/8wNpZu/Kgeo1cgmiAw4fkl56vN82F7hoRcDIYUOdnIHiSf7N9pHI0X89EYiU5A9TgtMA2pVuQqoMSgNaFi5Qdq+fHzOhjCyctnUuJZBl2An+cfvB0sWI2SV0qaAjW5S7F1ajhku6EAoB7hASSoae6w0Hk0QbiKPNHvGFWdGV+K3+Ydk1lj0wxLmwMvumxyLar7ZQFhhaAkoM1kBSlpcDg4GYDrSUuRZdf9nLcfXx/tncdZ+pO5TBFD4TsMsvFrWiW1oY0gAGDCI9mo5u+pd4kAZAjXEMuXgtye32lf194M2hTUIIy9BAm7qjM9q5Dl0+HSoC5gm6OjKKVvYvdDQCQIoNCil2jcVB9s3+feJlo0lAMM3wRoe4OzUKvdJdnh06Ar4Jejn6ij72Q3R8AriKpQrFdw3Fgfax/enhTaGlQhDLdEPXtY8yorvqWHIc/gOOC2Y48o4i+tN5cAeojzEOiXmpyq32Of+53XWcWT+kwFQ8i7KnKKq3ZlXSGIoBcg+SPzKSEwPvgwgNDJuhFVWCOcyV+TX/xdq9l00w3LiUMK+nlx9GqHZR9hQiAJ4SNkTmnjMNm5FEHsinzSL1iIHW8fth+cHU6Y5JJZSoJCBTlIcStp9qRS4QFgFyF6JOUqqrH/OgIDC8u3UzFZQd3Vn8SflNz6F9FRWwlwgLj322/06Moj/2CO4AXhxCX767rzMDu4hGsM5JRUmkiedB/2nx7cJ9b2T9CH1D8o9nbuV6fLIy5gc6Afokim2W0XtO39dcYFzr0Vj9tSHv+fwd7wmxCVjw54Be39GbSibN1mhGJrYDugbuMRKANuxDb4P3ZIFZB4FxfcUd9r39oeP9nsk9ZMUEPAexEypusRpULhhKA0YP9kJmmAMMK5DMH0ilDSSRje3XjfqZ+x3QGYs9HIihmBUHiX8FApQqQWoMngLGGeJZJrlXMUe6lEaMzslGGaVB52X+jfOxvqlp+PowdWvqU1+S3tZ0Gi0WBMoHOil6dd7cb19/5Gx0fPmRawG+SfN1/YHmbacJRpzOYETDuJMwQrkGWioYggIGDa5DhpT/CWOOjBm4pDEkRY3516n6afpR0nWEpRz4nUQQP4SvALaQ8j/KCQ4Bjh8eXLLC0zgbxfhRlNh1UX2tgevh/unv2bb5XxTpGGdb1LNP1s5iaComkgAyCKI0coWC829wKADkjs0P1XuVy+n1Yf+V2RWXWS4ws0glX5tXE46e/kR2EDIDchRuVnKyPyqPsNhCJMvZQIGkredd/oXzHb0hazT2JHBH5INZttmucHorxgJuBDox9n2W6s9rl/UAhCUK0XRxyrH1+f213GGbYTKIt4QpI55nFcagVkkGECYDAhfaUfKx/yqvsVxC/MjZRXmlWed5/dnxgb6BZ6DxxG9n34tRFtXmbf4m/gOeB4YzSoC280dwyAJEjK0R1X09zLX40f1B2MmRDSokqfQfc42zCyaUwkFGDLoAGh1CXx6+Dzh3x4BQDN9pUEGzUev5/J3uubLZVCTj5FTLyfs+VsOOXVoc7gCGDzY9DpdXBReP1Bhsq9UkEZDx2MX8tfkVzUl/mQyYjpf8p3H27MaBpjLOB54AVioacxrbH1gb6vB0eP4tbxnAlfa5/Lng7ZylO8i4JDC7oMcbAqCySPYQLgOuFaJVJra/LM+4eEp40+FLKajF6+H+oe5lt5lZYOUQXW/Nw0EWxT5iIh0KAEYO9j0al+MGS42kHrCqRSpJkonZRf/F9nXI5XmJCSiGR/Qjaf7mKnkqLRoFJgVOLmp6XuSjauP12IY9CY169cgB+R394dkVkH0oYKroG1OI9waCkQo/VgleA+ockmXiy9NEZ9RsZIDtzWMFuQnzkf1x5L2mmULMxzQ656lXIXqo2k7aEBICAhb2Ug6zvypTtsRFnNPBS32pMevp/dnscbRBWJzjEFaXxqc6dr/mWtYYegLuDQpGfpwvFK+dHC34u/01GZ014un/yfC9wdFp/PZ8bi/ci1Dq0YZqoiHuAgIKQjrOjOsDb4eYFeSm7SRZkbnZKf/R9h3LtXcxBZSBl/K7YHrhQnWyK9YCvgYqMqaBuvKDdkwFoJTxGbmHNdMt+m35AdI5gGkUYJC8AQ9w1u62f5ItxgSqBF4tsnpq5c9pR/lIikkNhX4NzWX4Cf3F1a2J3R8Am6gLY3nC9ZqH7jNaB3IAkiuycs7dP2B/8PyDHQQBeo3IFfjt/K3aQY+tIYSiTBGjgyL5toqKNFYK2gKGJH5ywtjDX/vozH+NAVF03ct19Un95dghkfUn+KCwF8OA3v72i0Y0mgq6AiIn9m462Fdft+i8f6kBiXUZy5X1Mf1521GMvSZgotQRw4Lu+UqKFjQWCwoDWiYacTLf81+37MiDbQSleznIdfih/2nX1YgFILyctA+neVb0vocKMuIH4gJKKvp3tuOfZ/f09IrNDpV/Jc3x+3n7ldGJh7EXBJJQAXdwMu12fkotJgVqBxYuun3e729wdAUolakbKYSp19X5efnBzEF/pQkch7PzQ2Oq36ZwGisuA/IGAjWWi9r7c4E4FUyn1SYhk3HZyf5R9aHHwW+s+vRwz+EzU+7PmmTSIV4D2gtqP9aV1w/DljgpQLkROyWfGeNZ/Y3y1butX5jkdF27y285Tr26WOoYMgGeE75JzqgTJHOzYEDE0P1Nwa8d6/n+pejZr7FLLM2MQouuOyAyqopI+hBGAc4bflvmvsM9k8yMY5DrJWFhvtHzBfz94zGbZTIssjgjb43vBR6SpjmyCk4BFicybn7aG18f7YSBOQr5eVXNdfu5++XRSYZpFHCSg/yvbw7kunraK+IDFgQyN3aF+vpDgPgV+KUxK72Qxd4t/Tn2ncKNaFj11GqL1qtGLsfOXAYcfgOGD95E0qavH0+q9D1ozsFIla616/n+mehZrmlI8M5gPp+p9xwip05HOgySAI4c4mPaxNtJK9iwbyz1DWxxxhH1xf7p2F2QZSf4njAPO3tS8eKAXjGeBTYHKiwCgPrwn3uQCZiebSL5jiHZmf5l9SXF8WwU+XBto9kHS77EnmBKHIIDmgxSSeakhyHjrhxA2NINTz2sPe/x/K3oYahxRUTFhDVLoP8Uap22QIINRgD2IOprGtKXVFfoDH1dBLV4Xc1J+7X7ZdPBg3UT+Ii3+gtkUuLWcsommgFWCm45vpPvBwuTUCRQucU4yaCl56H/de19tplWyNiAT8e1HyiWrLpNmhA+Ah4ZBl9awG9FX9XoaYT0YWxxxkH1mf3V2f2MeSKMm4gH43AW7554CiwSBxoE5jWWif78R4isHqyt4TMtmZ3jPf2B8Zm4PV1U40xSN76zLOqzkk7uECIAyhrSWJ7Bi0Kr05xnyPNFa+HCGfWh/d3ZzY/pHYiaGAYncjrp8nraK6oDuga6NKaOMwFbjkQgSLb1Nymf/eOV/5ntXbXdVTTaBEiLtXslBqnWSAIQfgCeHgJitsnXTCvhNHRFAXV2xcjh++H7fdMpgb0Q6Ihn9Nti5toCb3ohsgOSCD5DOpi/FmegDDjwyKFIMa8d6/n8/egdqu1CDMCMMueZ4w2elGY95gpyArInhnJe4btp+/5kkkkZ8YvN1S3+1fVRxOFtGPRAanfQk0MavTZbphQOAHoXJlKuto83w8XIX8TpfWR1wNX2Hf992/GN9SMAmrAFz3Em6IJ5lisuAKIJdjl2kRMJ+5QALkS8IUJlpDnr9f+B6KWsyUiMyvw0s6KfEQKaaj6iCioBuiZGcTLg62mz/qiS/RrZiJHZbf4995nB5Wjg8wBgl86TOaa4+lVCFAoDJhSaWrq8s0ND0ahq9PbZbvHHnfSh/YnVuYQdFoiI9/RTYYbYRm4OIVIA6g/WQVahSxzzr8xAyNdNUFm3ee+N/yngxZ59MYythBtHg9r3ZoAOMRYGNgdaMJqKiv7jiWwhFLT5OZ2h4efV/S3vjaxRTBzOGDsLoA8Vppp6PoIKSgKGJBZ0MuUTbsQAQJh1I3mPodo9/En2pb35YlzmoFdXvasuXqyWTN4QbgC+H1Jh/s93UAPqqH5BCo19YdN1+R36jcvRcIT/GG/31EtFEsHKW4IUCgF2Fd5XqrnnPSvQiGrA91VvscQR+DX/wdI5gskPjIDL77NVXtGeZeockgAqE1ZI4qxDLkO+BFZA5j1jEbyZ9hH+rdmBjV0cFJXL/6dm7t+mb6IhjgByD1pBbqJnH0evPET025FX4bVp8xn/sd35lHEowKLgCAt1iuuadE4qpgH2CZo9CpgvFCukQD8Iz41OZbLd75X/FePdmDkxqKgYFMN9AvE6f6origBuCeI7jpF/DOudGDScyl1K2a0t7839EedZnM024K1wGcOBPvRigYosFgeuBAY42pJDCX+ZzDG4xBlJWax579n9xeSFokU0bLLoGwOCLvT+gdosJgeeB/I02pJvCd+aXDJsxNVJ9azV79H9PedxnKE2VKx8GHuDzvMGfI4vvgA+CaY7lpIHDguezDawyIFMqbI176n/beANn+EskKowEjd6Ju6Keboq7gGeCTI9FpkPFg+nED540xFRWbSB8z38PeJFl+0nGJwECD9xSueqcYIl3gPmCsJBfqOnHeuzLEm43GVf2buB8l3/ddnpjKkd3JH7+p9hYtqSaCYg0gNeDoZI+q3jLa/DDFhE7EVr6cLt9L380da9geEMwIAP6XtSlsuKXfYYHgBaFNJXxrvrPVvWoG34/nF1Mc5l+fn78ch5d2z7sGpH0PM9NrruU1oQNgM6GgJiIs3jVP/tzIaREomHRdVt/ZX0ccLFYQzmoFC/uUclkqUuRM4NlgCGJnZwWufvbIQIXKG1KB2ZmeN5/xHt0bFJTpDJfDeTmr8IHpLSNvYE3gS+Mp6Guv4rj+gmEL79QqGrjevl/cXnjZ+hM8CoTBb/eb7tZniGKnoCugiCQvadgxynswBKjN3hXWW8afXt/QnZIYlxFICLJ+9TVtLOGmMOGC4D5hByV+6490Nn1YRxVQGxe6XPVfjB+C3J/W5o8LhiO8T7MpqvAktKDOoBLiEqbe7dM2o4AxSZxSWhlHHjXf+J7nGxnU5MyHg135iTCeaNEjY2BaIHYjNKiVMGS5TsMxzHFUi9ssXvff1d4yGXlST0n/ACk2re3aptWiDqA1oPVkterk8wG8sIYOT0TXHlyXn6pflNzZV3kPpsa4fNDzjatxJNEhCSAw4dxmnW2PdmW//gl3kgQZfZ303/se55sUFNXMrsM8+WPweui2oxkgZeBcI3Yo77CSucdDqQzaVRlbUx8vH9jdwdkcUdCJLv9adfVtDGZCocOgOOEF5Uqr7bQoPZoHXpBf1+xdBp/w33LcGZZuzm5FM3tj8hxqGyQu4KhgFKK5556vE7gEQctLRxPtmmGevx/lnnrZ59MOCrmAzjdw7nQnBCJWIB3gyWSBKvGy2HxWBgNPRhcl3Jxfo5+6nKYXKw9BRkL8lzMeatxkpeDT4DmiJGce7n13LEDFyqSTO5nnnn9f3F6f2m7TqEsXwaF37C7OJ7ciYKACYM2kbepQ8rS7+QW1DswWwxyRH60flNzLl1WPq0ZnvLOzMWrmZKlg02A44ianJq5L90EBHsq+kxHaNV5/n8wevRo502QKyUFP96BukOdQolfgG6DJ5Ipqx7M8PESGdw921wnc6l+TX4ZcjRbwTuzFoXv4clQqeGQ3YKYgEaKAp/YvPzgCQhXLktQtWoae+9/wHg4ZhZK/CY4AHDZRbYJmmOHFIDMhBuVea9q0b732B4NQ/JguHVqfxx9B299Vs41DBDI6LPDS6SIjY6BfoFcjQikYMNx6LkPiDVKVuluEn1tf8J1+mALQ8cem/c50UGv6ZSuhBmAmYd5mvK2UtpCARUoHksOZz95+n+aeqFpqk5CLKkFh96PuimdHolTgJ+Ds5IgrH/NqPP7GsI/fl5HdAp/xH2RcLJYaTjHEl7r6MX0pYqO5YE2gZCM3qIEwg3ndA59NIpVeG7pfHx/8nUzYThD2B6L9wrR/66olIWEIIDlhxab4beK26oCiil3TB1o23n+f/J5SmiyTMwp6gLB2wu4MJvwhyGAgoSplAyvKNG79xgff0N3YSJ2iH/DfBZu51ScM2QN5eXjwOeh54v+gDeCdI9zp+jHuu1LFdQ6vlr7cVJ+lX69cupbTTzpFlbvWMmWqDGQgILSgFKL/6DFv7LkPAycMiNUm22SfJh/ZHbWYeZDcx/990rREa+blHOEJYAciJWbsbim3P8D+CrRTTFpd3r6fzJ5xWZ3SgInzf+b2DO1+5iqhgSArYUal56yldWg/P8j6EfmZC545X9Le9NqEFCYLbsGON/cuimd/IhHgOGDcpN6rXjPJPbDHYRC3GDcdX5/0nwbbsRUPTPEDBDl9L8HoUaLyoCYgoOQNKlIyo3wURi8PTBdonPmfuV9t3CjWPo36BEa6mnEfKRqjW6BtIEzjril+8Xd67ITnzn5WZtxO36gfr9yv1vZOyYWTe4qyHGnTo8aghyBboz4oojCEejrDzw2SVfdb5R9GX9GdCde4j6BGaXxLcvXqeGQuIK9gCGL5KDnvyblAg2bMy9Vem4EfWR/XXXpXx5B+xsg9GrNoqsRkjaDhIA9inGfD74b4/cKwzG2U39tmnyOfxF2DmGTQpgduvXczsms1ZKKg2aAuImYnvy87OHMCbkw41L0bF98oX9qdp5hRkNZHnX2fs9GrSWTq4NcgIqJUp6pvJnhggl/MLxS32xYfKN/bHabYThDPx5P9lHPGK0Ak5iDY4CziZ2eFr0g4hkKFDFAUz9thnyTfxl2BWFrQkkdSPVTzj+sZZJRg32AM4p9n0W+hOOPC3kybVQTbuV8bX9rddpf2kB4G2Hzh8y+qluR3IKxgBGL9qA4wMTl5g2qND5WUm9sfSh/WnQSXoI+xxib8PLJnqjqj0WCCoFXjBCj98Ll6BsRojeqWPFwDn63ftpyo1tcOzYV+OyaxumlIY6bgZeBFI7YpYfG6OwrFVg7pVvgcrp+CX7bcH9YXzfBEHzoicKtohGM84BtgluQW6nzys/xExrCPx5fCnVafwV9SG6YVIIyZwsr48q9/Z7SiWSApINAk6qtRNCd98sf0UQAY1d30H+Tewtr3E+7LCYFDt1vuPCaf4cNgFmF3JbXsoLWUP5JJnJKMWeoef5/k3kKZzpKAyYC/jPWjrKjljqFEYCsh0mb9Li23eUFfi2NUJFr2HvAf+V2KWKeQ1Ie/vWozkGsOJIpg5WAv4qkoBLA5eVVDlg1BFf7b759635jc05c+jukFSTthsaqpdqNeYHGgbmOB6dAyBHvkxe6PbFdQ3Qsf1N96G5cVT4z/AuH4+u98Z62iVqA0IO/k46ui9E0+YshhUZpZDZ47n/Jek1pOk1jKWEBPNn9tEiYA4YDgOWG+JlPt/nbQgQfLIxP9Wqae8t/HXduYtRDZB7k9WfO6qvnkf2CroA2i4ahXsGI5ykQKjebWBtxMX6KfhxyKVobOUgSnOkzw+2iDozmgJaC85CJqsTMLfTHHHtCdWGVdrZ/7HuYa2FQCC0fBbLc1rdImgaHBID4hUiYGrWC2dEB8SnSTdFpFnvif7Z3aGMERaEfCPdXz5asSpIgg6GAEItdoUbBjedQEGs351hccU1+an6vcWdZCTj5EC/o0MHCoUmLroAGgxOSTqwOz8n2cx/sRGJjunfjfwd7pWmATXcpNAHT2G20upemhQqAeIcvmy25Y94HB/QuGVLebIl8gH92dW9fqz9oGY3wRMmRp+WOxYGJgTeOhKb2xyLvBhh4Pode73Rif9B8fG32UvMvCQhN3+i5rZu2hw6AfYV2lyO0lNgNAW0pj03AaR173n+Gd+9iNER8HqX12802q0CRpoLmgC6MWKMCxNXq0xPKOrlbP3Pxfpt9YW+3VT8zhAua4rS8t53TiC2AqYTSleWxANZt/gInlktlaHh68n9EeDVk10VJIGn3as9qrAWS8oK/gKaLiaINw9np7BINOjRb9XLefrN9k2/yVXUzqAuo4q68pJ3AiCmAw4QUllSymdYk/8UnTUz1aMZ66X/Wd2JjqkTYHtf14s0aqxiRjYL6gImMCaQMxSnsUxVJPANdHnQ0fyF9Gm6tU5Ywdgh339W5d5uChwmA0YVDmHW1YdozA7ErqU9ea/J7q38ndmFgnEAiGvLwUclcp5qOnYG/gfyO9qcVys3x/xplQf9ghna9f617w2q/Tosq6wEY2U+0ZZdchRSAG4icnHW7cOGZCqkyc1VZb6d9337icuxafzkTEsbo4sF4oeeKioB3g1+Tm65U0tH61yMjSc1mv3n9f994JWXcRiwhB/i1z26s4JHTgtiAJYyNo57E5etEFWw8RF1cdEp/6nx5bZVSDi+aBnbd7bfvmZ6GAoDKhkOaY7gD3jEHoC8TU9JtEX02fwZ0rlyfO1AU4Oqmw7+in4uzgCCDp5KmrUrR1PkEI4lIcWaZef1/8ng0ZdRGBCG991PPBayJkamC9ICZjGCkyMVQ7c8W6T2BXih1fn9qfD9ssFCkLOQDvNp+tRiYooUPgPSHfpyEu8DhLAttM0JWAXDyfZ1+73E+WSQ3OQ+z5fK+DZ9iiTqAjoTolXayMtc9AEMp7k1fapV7vX9odpBghUCoGRXwMMgwpq6NQYE7goGQkqqszRn2kh+1RXlknHj7f895vmbNSCcjyPkQ0VCtUpLxgtCAKIzHoyzFzex3FsA9f145dYV/THzkawpQsiu3AnPZRLQflxqFIYC7iP6dqr1h5AcOMTaaWJlxiH4Efh1wS1ZMM9oKQOHquuybkocHgBiGIZkct9ncUwYiL+5S5m0rfR1/h3OjW/w5KBJl6CTBlqAxiluAHoQWlXSxMtZl/6komE1BapV7un8/diZgyj+fGNTu3Mb+pNaM+4CvgsWRoqxn0EL51SKxSMhm5Hn5f2B46GPCREAehPQAzAupZI/Iga6BF4+XqHLL7fOzHUxElmM2ePd/A3r9Zu5IDyNu+YDQqazAkamCAYH3jEOlSsdn70sZe0C/YKN2zH8+e3VpW0wOJ5D9U9THr9eThoOTgFGLmKLpw6/rpBVHPVRePnWNfyR8YmsTT0Mq5QBw11eymJVNhFGAFIqJoEbBxOjCErw6ZFwYdEp/xnzQbCBRsSxxA9LZT7T1lu6ELYA1iQ2fW7+j5qYQ4Dj2WjxzEn8wfcptiVJeLjEFdNupteWXYIUbgKiIG54jvkrlVA+3NxRatHLtfmt9V25UU0wvJgZV3F+2YZibhRSAZ4iunZu9ueTLDkU3wlmFcuB+e319boRTfS9PBnPccLZnmJqFFIBviMOdwL3u5AwPiTf/WbFy7n5kfTtuGVPwLq0FzdvatfaXX4UdgMGIXJ6VvuvlFxCFOM1aNXMVfyF9kG0SUqYtQARl2qC0EJfthDCAX4l7nxrAsOfrETQ6JlwNdE5/r3x3bGxQmysIAj3Yx7K9lUqEV4BTiiahVMI+6ocUlDwFXjF1kX8CfOdqHk7MKAX/WNVUsAWUg4OdgKWLZ6NJxZft6ReeP15glHbPfw571WgiSzUlNvu70VGt9ZGmghKBZY1Ipv/IvvEMHElDJ2MmePh/w3kzZm5H0iCd9m7NzKmej8WBx4Gkj9apf82z9u0gikdNZtN5938MePFi9UKeGz3xe8jTpRSN+IDUgnSSIa7Q0nj8gyZSTLxphHuzf9N1+16tPZUVHOvuwnuhcIpZgFKE7JU4s/rYCAPDLI9RXW0cfQ9//3I/Wos3tQ5A5Nm83JzPhwaAXoYkmiq5AuBjCp8zKFcQcXt+7X10b6lUgjD/BrXcUrYTmFKFI4AYiTSfBsDt530SAzsCXbV0fX8ofBRrJE6NKHj+jdRyr0OTIIPTgJ+MNKXax7rwTBvXQvpiI3j5f555xGWfRqQfJ/Xcy1uok45jgUGCFpE8rLDQZvq7JPxK6mgve8R/JnZmXws+yRUc68DCNKEyikqAl4SflmG0jdrkBLEuTFOhbqZ9rn6acd9XWzQBC27gXbkrmlKGCIABiFudtL1x5SUQDDmYW+1zVH+GfNRrGU+LKVr/OtXgr3eTLIPSgKuMZaU/yFTxCxyjQ6tjkXj+fxx5sGQDRZ4d6fKpyX2mVI3+gN6CvZLXrgfUI/5zKD5OSGtOfGl/QHQRXJI5nxDQ5e+9dZ0FiAiAYoZfmsG5BOHACyw1olgnct5+WX3Ebd1RxiyoAj7YSbIOldSDi4CTi6+jKsYk7wMa+EGDYvx3+X+TeYNlCEatHuDzbsoCp5mNDoHLgp+Swq4L1Eb+syiNTo5rdHxWf+FzXluQOGIPeeSpvG6cbYcCgAWHq5uiu0/jOA6HN5RaaXM6f698E2xET4MpEv+71Eav7pLmgv+AcY3TpkjKz/O3HihGq2WxefZ/xHcHYjVBAhn87f7ErKLpimWAUIQ7lh+0mdpPBW0vLFRkb/99VX5dcKlVQjFEB3Xcq7VNl82ERIA2ioKhhsNm7H8X7j8eYUp37X8NelJm+0aUH5n058o8p6WNCoHbguKSTq/m1GT/8ynAT3xs5Hwaf91ykFkUNnEMZOHRuTqaNoYNgHOIdJ6QvwHoLhMtPFJeu3W7fzB7nGgdSi0jO/gqzsepN4+BgTeCRJHyrBjSe/xEJ5VNDGtNfF9/6XM5Wx44nA5v44O7aZvLhgSA24dsnT++lubUEQo7gV1Jdal/cXscacNK3CPc+KzOH6plj42BLYIykeasHdKV/HEnyk08a2d8Un+pc8BacTfIDYrirLq/mm2GCoBSiFKeh78g6HYTkjy8Xgh2yn/ieuFn80imIXz2aMxBqCyOKYG3gqmSKq/11LL/eCpeUAhtKn3qfhJyHVgGNPMJvN5Wt0yYL4U0gO2JPKFzw6PsDhi0QOlh13f5f195yWSXRH4cHvFyx0uktYuFgAiE1ZXgs7La0QVGMCpVO3Bbfud97G4kU8MtGgMV2KuxS5Rbg8+A9IxipivKLPSLH0ZHxWZket5/kHaOX389UxTO6Pa/hp5ciAmAhIYNm0W7cuPsDq444FtwdIV/1XvPaYZLfiQ8+cLO+6ksj3CBX4LdkSGu49PD/scp9E/cbCR9537yccRXZjMRCa/dR7Zul7iEUoDAisyirMVS7+gaX0MDZAh5/H8ReDFi5kAPGG3sEMPIoJSJJYCWhUSZ57jR4FsMdjY7Wn9zUn9SfNdq7EwKJrv6B9DqqraPl4E0gnqRoq1k01v+ginTT9ZsKH3gfsxxcVfiMmII6NyGtdSWaYRrgFOL2qMlxxTxwRwURVVlv3nwfy13fWCFPj4VfOlawKieWYgIgK6GhpsfvKnkZhA6Oj1dV3W1fx97IGjvSDMhlPUsy/SmKo3UgGWDkJRSsjDZmgR7L8xULHBkfst9cG4gUi4sDAHM1X2voZKbgk2B3464qbTOevkEJTdMdWozfFp/iXMlWik2zgsR4BO4ipgqhTyAVIpEojvFG+/5GqtDZ2RTefh/jHcOYSI/xxXc6YvAsp5QiAaA0Ybim8C8i+V1EVA7L17zdc9/mnruZh9H7B4U88DI8aTgi4OAMYR9lj610tyNCEcz9Fc9cgl/03zeaytOOien+5bQH6uxj4mBVIL8kaeu8NRRAKor2VFabsx9W372b1FUsC6IA/XXHrGek/SCGYFHju2o5c3N+I8k/Utqajt8UX9Qc6JZUjWwCsne0raIl6OEYYBEiwGkqscD8gUeeEaNZnZ61H8Ddi5eKDsbEQblJLxSm3eGDoDaiNGfN8L36xgYXUHdYpp4/n8oeAZiOUDHFqDqAsHknlWIBoD0hkychb2q5tMSvzxvX8B26n/VeTtlj0S2G4/vXcUpoiaKMYB7hWOZirkZ4joOqjhWXP10rX8fe9xnMkjpH9DzKskRpdWLeoBdhAaXPLZD3lMKKDWjWWVzW38WfPhpLUtjI133X8yOp1KN0ICJgyiVkrMk2x8HQjJgVwdyBH/KfJxriE0oJjb69c6UqY+OJYHxgr2ThbG42KEE/S+YVe1wtX5IfdBsSE87KFr859Acq4OPbIGLgrySD7D91tkCXi5SVCJweH6YfZ9tdlCfKcf9MtIfrCSQnoFOgh+SKq/w1ccBaC2SU6xvU37DfQxuE1FVKn3+09KarG6QtYE1guGR066R1WwBHC1cU45vS37KfRxuI1FfKn7+ytKLrF+QroE/ggCSCq/d1ccBey2xU8lvYH6wfc5tpVC8Kcf9FtLyq/iPi4Frgn2Sz6/W1tgChC6OVFxwkH5xfSBtmE9sKFr8udDRqjuPT4G+gluTJbF+2KAENTDxVUJx1n4IfQ9s+U1tJjf6tM4sqS6OAYE+g6KUD7PV2h4HizLVV3RyK39ufJJqwku8I1/3DcwLp9qMqoD2g1iWlbXg3VIKgzUyWudzgX+We59o60hWINHzx8h2pEuLV4DxhImYvrii4TkOFTn9XI91zH9zeixmbkU4HJHv6sR4oY6JGYA/hkKbkrwd5tESOj0qYFt3+X/1eCpjQUFfF6LqgMAgnreHAoDyh5GeGsFV6xYY50GoYzl59H8Id4pfWzzIEQjllLuAmtmFKIAfioaiYMZL8QIeDkdlZxB7pn+XdD1bsjZzC8zeNratlg+EpYDajDGnbswA+IwknkxIa8d89H6LcS9WPjBfBPfXebDAknOCk4E9kKSsStNw/6grglI4b0B+wn3LbVJQ+CiT/JnQdKrWjiWBEoNglO+y/NqXB0QzolgUc1p/73s+aZZJ2yAU9MPIQqQQi0iAQYVcmSG6heNsEE073l66dvB/XHnMY+tB5hft6o7ABJ6ThwKAQYhLn0jC5ezfGahDFGUCett/5nVcXUc5Gw4y4Re44JeLhHyANYxCpmvLF/fdIzNMG2vAfPJ+a3HYVaIvhQP51oGvApIkguCBPpFXrpHVDQJJLslUxHDEfgp9zGsuTfwkNPhizPemmoyQgFiEe5eZt7bgtQ0COTpd3XXcf/d56WRRQ1oZPeyTwaye3ocCgBCICp8UwtLs8xnbQ1FlLHrSf491qVw5OMkMwd+8tteWC4SvgDGNAajIzdL5oSahTtNsdX1zfqxv91LqK2L/7dIXrLiPXIHOguCTcLKw2pgHjjMVWX1zeH+IeypoyEduHkfx9cXkoZaJFICRhjucYL666PwVgEDzYgZ59X/idu5eGTveD6fiG7lvmLmEc4AmjFumy8vF98ckL03rayJ9q35TcOdT9yxiAMLTrKwJkHGBuIK2k0qyn9qkB7QzSVmoc4R/Xnu6ZxFHeh0w8OHE/6ALiQmAG4denQbAueoYGHFCcWTQed5/2HUAXXU4zwyO32C2dZbRg8+Azo0tqXvP5fvSKJ5QQ24Ffuh9720cUDEoNvvUzqSodo25gAaE9ZYjt4Hg2A1xOcxdUnbrf2F5hWMaQXgW/+htviGccYYagOqJo6Iox9vyNyCCSYVpMnwtfxZyklYdMJIDlNbSrlOR04FIgqWS17AO2TIGjjKGWElzdX9+e+VnJEdhHeXvcsSKoLmIBICHh02edcGL7BgaV0TtZZd6tn+jdMVaZDU8CenbKbMnlNWCZoEHkN+sRdQ4AQUu+lQlcfJ+n3x4aspKmyEn9DTIV6NBiiKARIbgmzi+7eiRFlhB0GOVeeN/7HXzXCY4Mwyz3m+1qJVrgwuB1Y4JqxDS8f70K19TLHCtfgp9d2syTDYjvPWRyVaky4oygOaFLptSvfjnsBWkQFhjYHnpfx92P114OHoM5d6Jta+VaYMOgeuOO6tg0lv/aizNU3twx37efP1qbUs4IqL0f8h2o0OKIIBbhiecu76q6XUXQUKRZAF60X9Dda9bXDYSCn7cdrM8lNGCcoFLkHetOdV2AmMvPlYJcjR/DXz9aHNInR7a8AfFxaC9iASAuYfgnoDCB+7cGx9GYGdZe3l/OHMoWMMx+ASK106vcpHNgWKCH5PdsanaQgjNNI1apnS8f2J6R2UiQ1gYbOpGv3WcdoYegECKjaPDyBn11SIWTIlrH32VfrhvdFKOKiv9JNBJqZ2Ns4A1hLGXo7jL4rcQfTx0YPh3/n99d45fRztXD2zhdLfaltaD3oBUjnyqstHk/jss3FOlcNx+rHxbakdKlyCw8oHGwqE1iQiAbIdsng7Ct+29Gy1Gh2d4e2p/23JpV6QwkAMH1u2tdpB0gduCfJQPtHvdYQvPN/9cIHbtfyB5m2JKP8ETqOX5ukCZ3oR6gKWMzadpznj7HClrUSVvb35JfdprZkwDIxP1jcg9o/yJFYDShlOdqsBA7GcaIEXaZjJ7gH80c+hXKjEEBFjWGK6DkHSB4oKdlFe07d30C244jV16dvR/v3jLYRY+RxIV5Ie5KphahKyAnI16qaTQ/v2aK4ZTinDdfp18F2q1SbEfivFFxaygiIgCgDaIFKB8xK3w3x4ISaVpcHz1ft1wAVQmLIX+FNHHqcONs4BNhBqYg7kn5HASUD4IYud48H81dvxclDfhCsPcQbPPk4yCvIF8kbqvgdh1BpIz61l4dL1/PnqzZPBBhBYl6OW8dZpbhVyAIYwfp8vNEPv6KIRRV2+Ifhh9NWs6S1ohGPOHxoSh74gDgO6Hpp8LxFXwrh7/SLRpgHznfplwd1NWK4H9/s/OqBuNioDFhD6ZQbtV5ssUhEC8Y8550X/4dLFadDRLByzZK7CykciBhoLUk2mzHN1pCzY4l12ddvh/bHj3YLM8aRD04Xe3j5aWgxCBUY95rKzUmgIxMGlXEXOBfxN7W2YZRNIYROqUvo2b0oVDgJ+LZKYHzWz6jShQUU5vjX4HffBqrEqCIAnyacWNoFmIAoCkiBuhKcbk8lshZ0tyazt9ZX7JbnhQeCc6+eLLdKUNiy6ASYaPnAzACOysGsVFmWeoe0h//HGIVbUtzv/s0Suq1I2tgHaEr5ioutvliRR9QNtj73nHf5x06lk9M74FetecrpSQZYEUg2mV87Vc4PwOnjtOYCd4+3+9dqpdFzgJC4Pct7I6k0GCEYKvkuWxiNsKCjU3A11kdvZ/cXjVYEk8rg/84G22s5Uug1eBcJByrl3XtgVNMwhauXTNf8h5eGPZP64T4eS0ue+XGITYgJ6Ok6vX0wQC7S9sVzVzjn/Rep5lzUIIFyzogbzimfOEhIAujT6p8dD1/hwtN1XkcUh/mHtSZy1Fvhnb6s2+gJuyhVCAFYxrp6nOiPzdKnJT0XAGfyl8m2j8RtMb7OyUwMOcS4YxgEmLFab6zL36NSkjUgNw0H6KfIBpQUhHHVzu0MGknbeGIYDGijal48uW+SYoTlGBb6x+wnwGav1IHB4r73/CHp7xhhqAhYrLpGHLEfmxJ/ZQTm+eftV8MGozSVMeWu+fwjCe94YagIaK06Rzyy/51yccUWtvqH7EfP9p40jrHefuMcLYnciGIIDHik2lG8zw+ZcowFHXb8h+jXxyaQ1I5RzS7TXBGp1nhi+ATIs7pljNU/vwKd9SkHD8fi58hmivRj8bHuytv/ib14VMgBiMoqcsz1n94it2VJBxPX+gezVnxET5GMnpnb14miCFfoAzjYWpnNEBAGguf1bRcoN/23p6ZUhCEBbX5gq7oJhKhM6ApI7sq6nUTQN/MfNYSHTEf9V5S2M2P4MSSuP6t3yWYoNIgXeQ365Y2DsHIjXKW+p18n+CeJ5giDtRDiXfdbQWlHWC+oG4kmWyrdzJC0o59l6od/1/0nZoXTc3eAlu2oawfZGTgfaCdZWJtqzh9RDtPWxicHnUf7d0nFk8MvkDK9U6rMSO0YBNhL2YVLtX57oWAUMZZjB7Y38cci9VkSzW/WbPoaf8i0OAE4afnNHAr+0SHXdI6WnQfJJ+8G4RUDEmEvcryc6iP4kDgF+ILqEHx7b08iM+TsdtN35JfR9rN0oYH7LvicLVnaWGKoBJi3qm/81p/FArQVSYcUh/b3uTZpRDRBfA55K705hNhNWA546SrL/VwAQbM2laPnXlf+d4OWEfPLgOSd9dtOOTVoIjglOThrNK3rUNPTuXYJd47n+VdfxazzN3BV/WBq0nj+OAM4SkmGG7nuc5F59DqmaAez5/X3HNU6EqjvsYza2lxYoagCaH8Z4vxLfxOSEiTH5s0X2yfSdsnEuUIAnxj8N3nueGI4Aci06m8s2J/JsroVTocV9/JnvUZV5CrxX+5ei5j5e4gyWBM5DLrqzYBAhBNvNcuXb9f3Z3UV4NOP4Ji9pMsCSRaIFLg4iWdLhV5BAUAkHnZL96gH9+cotVrCyV/dLO6aZqiyqAu4Yznk7D3/CMILBLR2zFfbh9IWx1S0Igj/ACw/edm4YwgJyLSKdXzzL+TS0WVtlykn96ekRkDUDiEhPjT7eylfGCrIEPktKxhNwrDCE69V9eePB/nXXUWlYzqART1farXY6rgM2EL5rUvb3qoBrJRglpknyofv5uxk9gJb31icc/oT2IBoDAiQ+kRMvf+VUpAVMHcTN/hXuCZhtDSRZW5v25d5eegz2BqJC4rw7auAkHOHZeoXf8f1p2FlzgNDsGttb+rPGOyoCHhKKZI70N6gwaY0bTaIN8rX4Db7hPMyVz9S3H56AFiAmAE4q6pDzMC/uLKg9UunFefw57ZmVyQUMUOeQYuByWDoOggQWS77He3MAM2DqiYMl443/wdHpZYjFPAurS4qkDjWKAyIVznC/BzO7XHodKsGuffc19MWxIS7ofsO/zwfycB4ZTgK+MXalO0rYB4TAiWcV04H/geMJg8DrFDMzczbHikZCBKYNylrG4DOU4FWRCJmZuezV/83CrUqoo5fggyv+iEIkCgByJF6NByg351SjTUg5xPX9Ze/FlDkLJFJDkPLgZlgODr4FQkoeyw93cDf47mWFTec1/GXTiVysvvv9Z0LunrIssgNyGy56RxM3y6iIQThhuc37LfF1p7EZgGhPq47xEmUmE74Cyj3iu3tjYCJA3XV60d/l//XUsW1gzMQRx1OaqgY1zgJqFO5wawfXuPh8TSy9s2H2HfUdrs0mXHUDtl78hmxaFnoBbjlisTNY1Bj41qVzTdv5/2na0XEo1PwZQ1lesV46cgB6FOJvCv37t4R3+SYJrn329fddrfUp2HhHuPcCMm0KFkYAljg2s/9X3BRY1mFzRdv5/z3aSXAw16QXs1fmrFY6NgFGFs5t9wGfu2B7cSh9s2X1+fRtrU0kAHYPs0b5+msOEwYAKj5St+NceCBs3Kl6td/h/2XXDWp0yLQNI09KpxYxOgDyGs51Tw7HxHyKjTfhtdX64fAFpKEYxGZnoX7sKmLODSIEkkf+wP9ynDD07SGFJecl/2HMuV+4tDP5yzv+liooNgAqIW6FZyGL3qSc2UuJwPn82e19l30D/El/iB7ZhlEuCZIKolHS25eKLE19BvWVieyx/jHCiUeUmiPaHx7SgrocVgASL5qawz3z/Wi9dWJF04X+neO9fTjldCuzZAK/Sj+qAcYTlmSq+/eu3HEhJNmuUfbh9m2vfSWgdrOy9vkmamoTZgJCPnq6A2fkJATnAX5V44n+YdFlYQi9L/27PoKbTihGA64c/oV3IlPcFKKNSO3FXf+l6lWScP14RmuBntDaT34HngiqW2rjo5cMWT0TmZ1d8qH6Bbj1OjyLX8S/DZZ3+hWOAaI0lq0XVoQUtNfVcLHf9fx12/lqUMscCk9L/qCKMMoDuhlyf6sX29J4lyFAkcBp/envMZTpBHRM24qi1+pMagqaCi5UEuAbl+xW6Q49nOny1fqJuWk6YIsbxB8M3neCFbYCtja+rDNaQBh42vl2gd/d/inXgWQcx/ADN0ImnP4sYgLWH+qAyyJz3QSj+UoxxbX+ZesJjRT6hD7LeprL3kXOBiYPpl5a7U+lkGpVHQWpNfet9BWw7SoUdeOxJvsWZTIQHgXKQSbDd28IMyDsAYst5pn+0ct1UhSrq+TPKaaJpiAmAhYpTplnPi//PLwdZH3Xxf+V3KV6JNt0GLtapq5aNZoALhrCd2cPk8t4jjk9+b/h+sXskZoFBMBMJ4k61nZPwgeWCWJZquevmIhjIRR1p53w4ft1sZ0vJHp3tKb9MmnyE9IA7kA2wttu+DOQ7LWLreZt/ZHI7VJcpyfgMyXOh3ocWgESLwKdT0dABCjLZWi92/n/QdgNcjjNyA9TS6ajqiyaAXId7oMnHcPdcKEtT3HGEfzt6yWKqPIcNYtyGsHqQAYFohDCaGr+r7fYep0sZbVB+vnydaOxE+Bab5Sm4aJWEgk6CzpRFt4/k8BUNRAlohXx2fpBtV0y9H2rus7+Smo6E8YBFkEKwItxcDZk8zGJEen9/tXHzUtEnv/YMx9mfAIc2gICMCapn1EgFYTWBXap3838fdcxYMy+O/h7OI6W7iQKAaomOpF7Nwf15LkBY1HTuf+V37F3lNc0F19RWqqaMOoDvhsSfA8fK9vInIFPbcYh/G3piYus7eQwq212vp4/IgPqEn5tRwWnw2CE0Ttdu2X7UeztmS0GOEgnhKLSpkpOBeIMPmEG8oeo1HI5J3Gv2fSR9hWkLRgsYbeanuJmViYJWggeVzrdw5REXO0X8aPJ8HX5PbDRK7xxP68y8ZZiWg4KBeZLus9jgchJHQUdm4HvPfqRuzU09IarvjcD/mquE7YBZkJqw1NxcDrs9y2PNekp/knDeUPYke/Piw1udt4WKgJqOyq1k2dIKnzqSYcl5mn8kcm9THii+9sPGbZ+xhkqAM413q4PW1Qf6N6df3XjLf2NzhlW4KnP5K8kuoYyHJYAZjJqpMNRoBdA1El4UeOd/WHQpV8UsmfsVy5eiQYgRgEeLL6ho0osDJTTYXHV39H8KdV5YSS4u/YDMoqPJiAiAtIowpyjRPQL8Mv1bBnf6f351J1lFLzT+Z81LpB+JBIBeipumcNB/AVYyhlvKdv1/t3WIWbovqf7LzZCkQIkDgEKKbqY90FIBNTJzW8N2/X+3dYJZqi+O/qrNcaQsiQSAXoqoppHQtQGYMsRb8nb7f351FVkTL+P9Bc3to+OIB4C0ikmna9GoAn8zelxVd/Z/C3U+WPYtqPzcywejaIgPgEaLVajM0isE6TSQXeh36X9ZdPxWUCzd+jLKwaG+hyKAGYzOqbbUPgbUNgRfp3jQf2RzS1UhKoL4CMghoOuGRIAyjbmrLNfhCDs5z2CKeaJ/JXImU2QnmPVjxS2e+YWAgJmOG64v2hIMHDzrYop6Vn+UcIZQGSQg8kjC65vwhN6AV5D6sMTd0Q9wP09lmXvifqZuZE07IBzuvL5nmdyDbIF3kl+07OEaFDFD8GetfDd+UWy6ScgbjunIuq2WzII3ggWVUbiq5usYVkfBarZ9SH2IaX9FvhZ75HW2yZPOgU6DDJjXvADsPx7US7RtpH4FfD5mrEAcEejez7HLkPaAw4Scm/nB7vEPJJ9Qt3Bif1p6ZWI4O+IK3djkrMeNV4CohsGfwMd0+FMqplW3c91/NXjwXR41EQRj0sSn0YoHgBGJiqQwzo//ADHZWp12/H+DddBYVy6t/IfLhKIBiB2AEowEqk/VOgcHOCJgUXmpfy9y+FLfJrz0WMQ4nXCFtIC/jzywIN1uD1g/amW3e8l+I25cTLUeSOzqvPyXPIPlgS6UP7ei5SAY3kaUarN9QH1MafJE2xVd41O165KBgc2DcpkTv9PuQCF/ToJvI3/yepZjsTxVDA3ar60ojmOAh4afn8HHq/i6Kh9WEnTof8V371yWMy0Cb9AcptSJAoAuisOmS9EeA3Y0m10feN1/nXNJVZ8pc/edxr+eGIaCgN6O7q6t2xsOVj7PZIF7335fbphM0h457Li8v5cbgweCr5QnuOLmjBk2SJBrDn7KfPZn1UI5E5rg5rJJkQmBtIS1m3PC2vJRJe1Rr3GZf315TWAAOOcGudRVqY2LD4CqiAOk0M2B/0UxTFv7dvd/1nRXVx4s9fm9yDagv4ZZgAiOo6002rcMOz0dZD57+n66bgxNPR+D7Nm8wZcUgxOC55SauI3nWRoASSdsQ356fBJna0F0Eb3eQ7EykMOAZIVcneLEvfU1KFdUK3PTf094zl1/NOYC2NA7psmJAoBxinGnbtKdBBM2/17oeLh/WHLnUlsmv/MSwwacyYQGgViRKbMi4f0Tr0OtaBx9v319amBGIBc35LO18ZJzgf6DLJp7wNnwnSO+UBZxg3+9ea1gSjj8BpLUCalJiwqAE4n5pE3PWwEyM+xc6Hfff41z5VTEKCz2IcVunWCFyYBkkLixe99mEmhC3WfUfPd9FmsyR/4X+uQ/tj6ThYHngwSaWMDL8Kkj3FA0cYt/mHlNYLA3Nga/01Ko2IoEgI+J9aWx0PQCwTQnXpB4xX+gcjhTjybB8+XCxZuehCGB3ZEntIninRVBRdppkX1Dfflo8UMSFADh3rILkeyAFYXcnHfEk/VZKK9UgHPgf9R3pFyoMpQAac4opJSIFYAHjIKqp9ZoCao6i2Krei1/Wm+3TaYfheyBvEmX0YJhgguWqrpj6pEdBUxNbu1+O3vNY2M8TQto2NmrxIwmgASIHKMXzTv/fjHUW3J36n/fc0BV9SgZ9tLECZ0fheyAHJEXs2rhphSSRH1pen1SfQxp50PbE5/ga7KtkNGAY4WonbrFKvcFKiBWZXT0f/J20FoUMJ79iMvioV+HQoCyjYWtntq6DaI+dmX3e4N+smxiSUEa5uaUt+yTq4HDg96ZbcA78Wkku1Hica9/53ijXh01BwN00IqlNokKgIGLwqnt1eEIaDqCYrh6IX8Fb/5MiR4m6yC7OJZlgtmChJcPvWvtxiDYTi1wYn8CeutgKThTBnjTzqdmigKAT4qlp0XTIQYBONFg+XlkfzNw2k69IFXt8Lxml8uCdYJzloi7tesqH5VNb288f2x6xmFJOYIHhNSRqMqKA4D7iRannNJ+BX03fWDXeW1/WHAIT+UgbO32vGCXxYJ+gpeWzbsW7Jof/024b05/NXpDYYM4lAaU08unV4oCgHqKDqju0/cG4DiKYVh6QH92b4pNAR9t6zC7JpZUgveC8pffvY/uFiIRUARxkH9VeVhf0zWJA6zQhKUZiQ6A3IuYqkDXjAohPOljaHvHfnptUkoLG1vnrrfOk5SB+4Oems3BI/OTJrhTMnPff6p37FsqMWL+28vZoTeHUYBHjtKuotw4ECpBdWfXfNF9OWpDRfgUQeGPsoeQu4DBhcaetMfZ+f8syVgMdv1/+nTQVnAqHfc+xf2c84QQgfmR6LQk5PEX00fwa11+FXx1ZTQ+vww02QSsmYwbgJeIqKS2z68COTUIXz95kX/zcMxPiiHI7QK9O5eogqqCQZcNvdjtnyHgTwNxlH8ved9e+DRbAlzPWqRpiCGA4IyOrPXZng0KPxlmXHwpfjRrm0ZjFnzib7P9kNCAlIWAnnvHxPkULflYNnb7f6p0IFZlKdj19sP5m3iEVIESk8a2jOaFGiBKgW3Tfjp7TWP9OvIIbdXtqMuKAoBZihuoYdTaBwg6omLyevV+/23dSl4bWedlt3GTbIFThKqbmMOC9SgpAVajdPt/KXbMWL8sS/nyxgmeVYXugI2RdLTc4+0XCUg4bH1+0XujZMs84Qoq1zWqdosGgMqJJac507kGHTkKYrd6DH9QbkpLxxup55O3gZNtgViEyJvZw+X1nylxVut0/X/QdRRYtysZ+MnFJJ3qhCGBbJLrtbnl5RnESWJt0n4uexFjezorCIHUEKg/igOAEIuRqXPWPgpWPGVkv3uCfjds6EehF2vj9rMqkdKAp4XdnkHI7/p0Lj1a/nbsf4hz5FNEJkTyjMBomV6DHILYlUi7LuxiIDFPynCTfxN5X17rM80Ajc23onOHT4B8jp2vK95fEoNDYWmkfet8VGd5QNcOu9rYrNuMHIC+iFClC9GgBHE3/GBQei5/x27YSzcc3+ePt16TWoGJhGKc6MRT9zIr1lfGdf1/xXT9Vc8oyvSlwsea34PDgdCU07ma6vceJE44cHx/X3noXoU0UwHpzeSifodPgI2O1a+S3uoSF0TXadJ9rnyaZkw/XA0u2YSrCowLgIuJ8qZQ0zAH3DnPYid7zH4fbRpJyhhQ5Hu0WpHVgLOFJZ/iyOX7mS9MW6J31n+Gcu5RiyMt76K9RJeJgu+CZZhPvyDxcSV1U2pz7H/fdspZkS2r+dXGoZ0EhSOBppKbtvLmghtvS6NuLX9CerVg1ja1A/TPT6QjiDSA2I3Ermfd4hFZQ3BpuH3DfLpmVT88DefYLKvHiweA6YnDp4jUpghPO/FjrHt8fudrEEczFpXhG7LPj4CAxYaQoVfM3v9rM0ReJ3mFf0twC06THu3pA7kglISBV4QfnNbElPe/K4JYQ3b2f/dzTVRXJuDxzb+emPiCioJllwG+0e9fJMNSGnPnf/1231l9LWP5ZsYyncaESIFTk9S3mehYHRxNxW9vf295yl4INGwAvszGodSGf4DZj0iy8OG2Fp9HWWyifl97G2P4OfcGxtJHpg+JGIDqjFat19uAEFxC6WiWfd183WZUP/8Mc9ilqmOLA4B2ivSoTNa/Cl89h2VefPx9HGofRIISvd3Qrr6NLYBuiBulTNF3BbU4Q2IJe8t+5GxhSIAXnOK8shCQhoDGhr+h1sysAGY0Kl+peVl/QG8gTPkbCudetkyS/4Bvhdme5Mhg/HkwSFxKeLN/PXFiT+4fA+uuuWWUjIFdhF+cdMWS+PYspln4duV/5HIvUmIjg+6jvFGWIIKHg0magMJE9eApTlfAdft/PnSMVFUmifE4vweYsYLhgpCYBMB38j0nRlWodP5/VHV+VsooE/RowX+ZN4NkgiyX/L0o8A0llFO6c/V/LHYMWMQqIPYuw7SaqoMJghmWZrxZ7lUjPVL6cuh/zXY5WUQsr/eHxKCbBYTKgVKVP7sH7RUiQ1Fuctx/O3cIWkwtwPhyxT+cRISjgdOUhLo07E8hq1AZctN/eXd8Wt0tUvntxZGcY4SRgZqUM7re6wMhdFD9cdB/iXeWWvctZvn3xZOcYYSUgaaUTboF7DEhoFAactR/bHdWWpst+/iQxUWcP4SqgfiU0rqp7NkhLlFwct1/IHe8WcgsEfi5xKib/oPWgZCVwrvL7fwiHFL+cup/pHbFWH4rqvZzw8CaoYMbgnKWH71q75ckaVO+c/d/83VwV7opxPTAwY6ZLIN9gqGX7L6J8akmEVWudP5/CnW4VXwnYfKjvxmYpIICgyKZLMEm9DEpEFfGdfl/4XOaU8Ekge8gvWaWEoKyg/ya4sNE9yssYFkAd99/cnIOUYchJuw7unyUf4GVhDSdE8fh+pQv+ltReKh/s3ARTswdU+j7tmSS84C0hdSfwsr+/mcz1V6xeUZ/nG6bSo0ZCeRnsyqQfIAdh+Oi9M6ZA5836WERe7B+IWylRssUTd+Hr9iNJ4DZiGqmrdOyCDQ8KWVlfNV9OGkqQoIPJNpmq32LAoD4inOq8NhGDh1BiGidfah81WUiPbUJlNQRpymJHoCGjQevwd5QFFBG92uofhl762GIN2QDp86Vou2GjICSkC+0IOXKGsBLZG9yfxd5b11XMZP8Z8gDntyEYIEtlPO5D+ytIV5RvXLpf492VFiLKkX14MFtmQuDrYJjmFzAi/PtKBlX7HX1f3BzkVIiI4LtJLvplJKBh4RFnW3Hkvt+MNxc2XiBf6lvGkwcG1XlQ7SPkImABYffoi3PGgRPOJJiant1fiZr6ER8EsvcU614jAmAOoo/qZzXHQ1NQB5ohX23fNll9DxHCfXTbabAiC6APY5vsLngixZiSGdtDH8xerBfPDSH/+fKrp+HhROBH5N4uH7qVSByUEty4X/JdqBYvypJ9bnBNJnsgtWC9JhdweT0ZCpeWKl25H9qcp5QgiCg6om4IpMSgY6Fy58hy9z/nDQFYF569n79bKRHjhWj33ivno0cgFmJsae/1VAL4D5AZ0F9+HxxZq898Qlu1Kym0IgugE6OrrAu4SwXCknmbS5/zXm4XsIywP0kyU+e44RqgYKUxLpg7U0j8FLJc/t/WHXHVecmF/HuvZCWAoLxgwWc8sU9+o8vZFy7eIJ/g2+aSy8aF+T6sqCPWYDjh+OkLdKnB8Q7M2WKfJ19Omg0QLIM69Z7qLOJFYBZjSGvYt95FblHJG0Ffyp6cV+gM5L+xMmrngGFXoFqlLy6d+2EIzVT/XP9fwx1IVXzJfjv27zHlcCBW4QknafHR/yRMfhdhHlCfytuT0lKFxjhcLAQjiSALYmLp8zVoAtgP75nen2sfHhlCTzRBzHSy6TJh2KA7I+bswflTBuqTD9wpX8WeO5aai2894jDNpozg6aCqJhDwSr1BCsgWTJ3zn9mcZNOmR1L5261AJGRgBeHZqNl0PgFeTpwZE18w32MaHxAywzM1jmoe4kdgNCNHLDT4CkXUklBbkt/XHmFXcwwRfuXxkac9oMNguKWs75Q8mYoMVc8dup/fHJdULgfWOkPt/WRv4CKhkyi/86PBEw5rmMIfPN9FGkzQYYNZteeqKaJGYCzjf6vxeAzF29JYG5Ufzl5KV05MI363cW0m7iDQIKSl9K/tPPQKVlY3nbXf6Fx0U61HTbnNbXEkIGAX4cgpI3RZwfrO49lxXxVfSRnOj4DCvvT8KU/iE+Aj489s93kahv+TJVwt3+jd9FZqyuV9WPBk5iQglyD05qwxFj5NS99XPJ4Zn+tbs9Jgxfw4AKwpI0XgNKJEqkn2HwOMELWaTZ+mHt3YmY3PAKqzHKgo4Uhgb6TGLow7bYjulN7dP5/KnQnU/giaexruU6TBIHnhRGhjs1AA1w4LmPme/99F2n/QAcNr9bipyyJKoCDjpixAeO1GblL5m+gfwZ4fFpmLDT2ysHAmJeCXoPwmv7E2PnTLw5dRHlJfwNum0jpFTTff661jAeAx4r+qsfaYBHMRJ9ru36geg1g4TMz/tnImp1jhNWBZ5ZWvk/yyijMV7V22H+JcWdO4hwR5gG04o9WgDeIFKZz1NAKMj/6Z6x9S3wXZIE5WwRozpGhEob5gDeTcrml7GYjp1OIdP5/7XOLUvwhLusyuGuSyoCQhqyi888RBhM7NmW6fEp9y2ZgPagIWdJwpGKHioAqkTS21ui8H8pQ93L2f2J1LFVEJX7u8boelC6Bn4WfoDbNKgOKOH1jF3zOfVBokz8bC5fUFKYpiFuAHZCFtN3m2B1STyhy6X8MdmFWwib77ye83ZRdgUOF158wzB0CpzfoYuB78328aChAtgsa1WymT4hVgPmPV7S15sAdTE8rcup//HU3Vnwmoe/Ou5qUSYFvhUig3MzpAm04fWMffMJ9F2ghP3gK39Nypc6HcoC9kKm1Xuh1H7dQAnP4fzF1q1RwJHPt5rlak/iAKob5oT7PjwXZOjZlyXwvfVZmejxiB+vQM6O3hsWAd5KEuNvr8CKIU5l0/X+Vc7BRmSBz6X22M5GFgI6H/6Rf0wwK3D76Z799G3xeYyE4cQJMzMefLIVxgUiV/7wy8ScoolfKdtB/BHEpTewaquOwsU6OHoDGiXqpUNldEF5En2vNflR6CF8BMqb7GsZbm2SDr4JfmTfDafgFL9xcW3kxf0Zt8UZcEyncp6vnigiAE42YryThdRg0S+ZvrH+Tdx9ZACoG83m+LZasgcyE+p5Py38BaTf1Yvx7z30UaN4+4gkN06GkUYeagMCRjLfr6jwiJVN7dP1/hHNkUQQgo+iitZKQZYAliF6mZ9VsDB5BmmlHfkR7IWHFNIL+hcjynPWDQIImmIvBq/aKLd5b8nhQf8Rtm0f+E6Dc5qv4igiAJI3Wr5nhEhnXS1pwv38edxhYgShM8dq8CJVVgXaFpaDFzVcEGjrvZMV8H33sZYg78AU5z7Ch6oUggTyUpLvt7z0nKlerdtB/33CqTAEaceJzsHONDIDEiperVdzNE4pHym1Uf9l4klsELfj1z8CSlwuCSYTinQDKUACSNodi4XvXfQhokz5MCUTS3qPghsSAtJJLuT/tvyROVb116n/ocV1OABxX5OmxP44ZgCWKfaoD24gSjUY4bTl/JXkjXLAtl/ZEwdOXGoI5hMmd9MlaALE2rGL2e8N9u2cMPpkIhtFAo4+G5IBRk1u6me4kJnVWYHbXfw9x1EwFGkbiKrA0jQeAJItvrJjdSBXvSL5uhn8WeNlZiioo8zW+wZV8gUGFWKCezXYEdjpaZft82nz8ZOo51QMGzeefD4WYgS6W5L7/82ErhFpueG1/LG7yRwYUStxaq4eKEoD5jZixJeQBHIhOGnLwf2V1fFR6I7XrzbenkYqAuIfWpSTVngyxQT5qiH6wenFf/TEA+/bEL5rWgl+DsZspx3v9RzQaYWR7Hn7DaGc/7gmR0t+jxobWgDGTV7rN7osm7lazdsl/cXCaS08YXuB4rimMAoBUjMeuxOC6GPZLqnDQf4B2g1b2JSbuv7nLkr+AEIeJpIfTCAtuQH1pWH7+ehVgwjK3+3zFd5roglKDo5syx6T9izRfYYh7AX5PaJs+5Ah60fqiVIYFgRWU2ru08H0ogliKd59/NG9uSY4Vi90lrNmKDoDWjY6xWORyHBZPiHL3f890MlOXIYfpyLVOkE2A24hTqKjYjhBGRatsKH8ueeNb6SxK9bq/iZakgROFLKC4zfMEOzscZlJ9ZXyCY3M3tQDVyWOd8YNoghOZlcO9+RkxAF+Weop+FmotQbIL9tO3pBOHxIABk0a6/+4BJ31XFnezf6pvEkosFv/dYazpig6A6I3Nsc3kDR2zT/Jy/H9KdB9SFSDX50O0VI8sgLyJKqox21cTwEdJbn1/CHhZWWEpZ/FAvDSUBYFphlejNtLxCcE/OWlRfvN6xl8LMp/6PcRumX6C34NPnd7J6wDMN9xjkXwhfW1lDzpvAyTM555+hAqCBZgtwlP49y9NXld6o35bam5BzQvi04ak7YbWgHGTILsx8FQooli5d45/mm4pSLETZ9s3qrSJL4CDj7a0jOjxIPBSz3T1fzlyRU4WG6Pi5a+9jAKAL4znrmjh3RlKTaxx7X9FdchT+SGN6X+19I87gGeJrqnH2iATwUdmbod/zXe5WFgoG/D1ukaTyYAchwOlqdTDDGFCDGvVft95IF01LkX2O8CilpuBQIXdoA7PzAY5PbFn6H2IewdhkDMH/ETF+pmfgsaDNJ3yyUABUThhZNB813x1ZG44XAEHyj+dyIOfgv2ZUsUj/LUzKWGae9l9dWfQPEMGfM5loAiFv4ExlyvBdPdpLxZeVHqafhBqvUC5CpzSY6NRhhuBxpR4vTbzdisxWwp5JX9ObDhEvw5h1i2mmoengLOSNLpp798ng1jGd4R/N25FR1MSyNm9qNeIWYDxkFy3DeyqJBNWknbCf9Rv6kl3FczcC6sAiiqAeI/qtCHp2CHoU3V15n8rcSpMKxhq3xKtDosPgEKO2rKl5m0fBlJ4dPh/QnIKTnAaoeHNrvqLBIBIjSqxl+RqHXNQn3P+fyBzjE9HHG/jOLC+jAKAhozVr/bi0hsxT/By/n/Hc7RQsh3T5FCxV40EgPiL2a7B4aQaRE5tcvp/PHSFUbAey+UTssKNCICbizOu+eDhGa1NG3L3f4J0/1FDH1fmfrL8jQqAbYvjrZzgixltTfpx9X+ZdCVSax945pKyBI4KgGyL6K2q4KEZhU0LcvZ/g3T1UScfLOZOstmNCICZi0KuI+EjGvRNTnL6fz90cVF5HnTls7F+jQWA9YvxrgfiEBu7TsJy/X/Lc5ZQXh1R5MKw84wCgIKM+K9X42kc1k9kc/5/JXNkT9gbwuJ8rzuMA4BCjVexFeUtHkVRMHT6f0ly1k3kGcrg5q1biwyAOo4Tsz/nWiADUyN16n8zcexLghdp3gGsV4okgG+PLrXZ6e4iDlU2dsl/3m+gSbEUodvSqTaJUIDmkKu34uzpJV9XZHeRf0Nu70ZwEXXYX6f+h5eAppKQulvwRinyWaR4N39cbNVDvg3o1K6kuIYEgbeU4L1F9AItv1ztebV+IGpOQJsJ/dDHoW6FoIEgl6HBoPgZMb5fNXv+fYhnUzwIBbrMsp4qhHSC6ZnWxWz9hjXmYnJ8CH2LZOM3BAAlyHmb+YKOgx2dhMqmAkI6LWaVfcd7H2H3MpP6RcMpmOeB+oTDoK/PTwhFP4VpkX4uejxdjC219CK+zZQEgcSG5qRZ1WAOhUThbFd/LnjYWKEnce7IuHSRX4D8iI2phtvXFPdJMnDWf7x161MyIcrnQbMujgqArovCrjfiqxuOT2dz/n/HcmxOQBrK4J6tDosVgOmOjbRq6dUiO1Vudrt/Qm9USMwSednspyeIlIC7kvS6HvFJKuxaMXn7fh5rnUHZCuTRQKKNhZqBM5f8wU75+zGOYJx7qn1PZkM6bQIayq2cV4M7g12cqcnzAdo5DGaWfbV7yGBDMpH5K8JKl56BioVEovzRBQvUQU1rCX8GeX1anSlO8Cy6MZJ5gJyI9Kjz2nUU00k3cNp/jXVnU1UgtOY0sn2NA4CDjHSwi+Q0Hr1Rr3TvfzVxfUtwFtXcXapKiVWAUJHIuLnuLSh4WZR4L3/ua71C+gvI0saiuYWKgROX88F0+Ugy5GDJe399q2UnOQABpsiOm+mCuoPYnfPLpwRpPN9nLX7IemBevy6Y9Y6+2pT7gP6Gq6XB1j8Qb0ZDbp1/8nYFVo4j1+mjtM6OEIBri4+uUeIiHDZQ63P5f+hxl0yjF9zdDKuUiUqAFZGHuJLuLCiTWa54IX+baxhCEgvK0fOhVIXIgQmYjMNs+zo0XGJifPd8/WOPNvn9y8WGmTiCpoRToJTPvggfQGFq3H5eeQdbDSp28A269pFpgP6I9amM3GYWq0tvcfR/QXS6UKYctOLCrneLEYDmjuy0Weo2JKdWUneEf4xtG0V8DuTUI6Q8hlOBapYuwdj4+THZYNd7Z302ZTs4tf88x2yaeoJShJSfps7cB3U/BWrKfn95OlszKoDw+7nckWOAKYlgqjXdMRdqTOpx+n+1c6BPJxsY4WStsYokgOqPxLay7JomkFhJeDx/+Wt4QkULwNHBoS2F6YGhmKjE6vzPNZ5j43xpfEdi4TPJ+sLCXZeNgdOFTaPo05sNgkRFbXx/YnelVgQk9OlwtIaOCoD6i+GvVOR+Hl1SOHXdfxdwJ0kZExrZI6eJh9aAbJRAvqz1Oi8GXyx72X1/ZvE5ZgGSyDSbsYIbhCifQM6jB3M/ImrYfkx5o1o2KUDvwbgDkUGA9YkcrKXf4RnCTlJz/X8hcp9MOhcF3RCq6oh1gHKSJrsi8v4ru1w9emR+U2icPFMEI8vrnEKDfIOPnRDMWQWIPfBoj37nee5b3Srm8BC6wZFZgHaJM6uQ3t8YBE7zcv5/bnIVTbUXZ91Kqv+IcoBtkjK7R/I2LPVcXHpPfvpnAjyMA1rKUZwHg8GDWZ5FzcEG1z7Xacx+WnmgWgYp4O5KuKWQM4BjihWtEOF8GzBQLXTyfwpxkUqLFDzazafCh8uAXZRkvhv24i+tX4F7kH1qZRk4E/89xnaZF4IBhZqh6tHZC1BDuWxrf4B3nlaiIzXpirPZjQOA7YzksTDnrCEeVcZ2l3+7betEsg2b08yifIXOgYaY5cSj/d82oWRTfcp7WGC6MOn2/r6vlNmAo4ejpyXalRS2SjFx9X/qc5VPkhr+3x6s04lNgIyR87kL8UUrblw1elt+AGjVOxwDvMm+m8iCGYRqnwDP3gjiQEdrJ39WeEFYoyUf6/y0mY4IgFiM87Aq5s4gj1SMdqB/4m0LRbENd9OXoluF6IH4mLLFsP70N3Vln31ceyZf6y7S9BG9ZZOVgJWIuKkE3a4XXU3Ccv5/R3J/TJoW89vjqCyIs4ALlCO+HPYqMBNgvXtTfX5kejb6/BzE35eWgfWFEaSS1QUQGEcsb81/d3VYUtgdDONcruaKJ4BmkDO4Ku+uKWdb03mFfn5oZTyKA/DJwJu+gjOE0Z/Dz+YJ80EQbFV/sHe9VnIjqujPskeNAoDPjcSz2emeJKVXIXgyf1hrx0B/CGzO1Z7QgxaDzZyHy1wFED6gadF+JXnQWXQnvewZth2PDYAajLiwJOYLIfJU13aLfzNttEPZC3vR+aCfhHGC5ZrNyGsChjsBaGl+/nmuW+gpPe8guEWQIoAmi/uuBOT/HmZTFnawfypuPEWYDRDTFKINhSiCApqLxxQBYzpJZzl+UnpoXNYqKPDXuKqQK4Dfin+ud+OBHg9T73W2f05uakW+DSbTGaILhSyCGZq6x1gBrTqDZ0x+LHoEXEAqe+86uEWQIYA/i0CveuSRH+9TZ3aff59tPURMDLzRCqGahH6CKptcyTYDYjyraJ1+h3l/WiQoOO1Mth6PC4BNjEWxEOcuIv9VcndefxNsr0FACdjO8J7Igy6DRJ13zK4Gej+yahl/UHjLV30kYekbs0mNAoAgjp20PetOJi5Z9njZfpNpsT2ZBIXK5Ju0gluEfqAY0b8L4kN6bZx/ZXbOU0Af/+O+ruiKLYDbkF65CPHnK11dzHrkffplLzhW/tfECpiMgTKG/KRR12ESgEnYcPV/mHNoTmEYHt1XqS6IwoCslKa/dPjhMmBiu3xHfBxhETF69u29lpONgO2I6aoy34kaLFCQdOF/r290R9kP1dQao12FBoLNmZTHgQEcO/1nen66ecNaPygQ7fS1y44GgNSMc7LJ6B8krVdWeA9/ZGrJPqQFSMtJnMqCTIR9oEfRJgxnROZtsH/sdbZSpx0x4imtAopUgDWSy7sb9P0uul/LeyB9bmNCNMz5rMA6ldqA84f+qNfcSRh8Trlz8n+CcL5IPxEG1uCjpYXigWWZG8cgAec68Gd9fqp5glrEJ2vsTbVbjgOAYI2Ps0zqvCUBWf94yX4caao8EwPRyISaM4Imhbiig9S6D4pH2G/nfzt0W09FGbXdk6kwiMqA/JRlwJz5NTR8Yyx9s3tgX1ouRPPxupuRPYCcinmuC+SuH3JU3nZ4f2Jsv0HUCP3NA55Ug72DKZ+hz5wKS0NYbaB/KHb+UscdF+LnrMqJY4DAkuK8nvWdMAlhV3yWfLZhkjGj9r29RJN3gHCJOqxD4f4caVLidax/pm28Qw8L+s9an8uDTYP+nQzO/gj7QZZshH+jduNT2B4S45qtHIpVgGmSZrwk9UAw1mBKfJ18vWGGMYD2jL0ak2+An4mqrOnhuh0OUz52mX8TbbhCyAm2zmeebYOugxufuM/iCqxDq22vf8d1HFJ8HKHgoasWiZCA65Ptviz4IjPpYgl9zHt0Xzcu3PJguiORLIA0i9Gv/uXdIVNW33cpf5Vqpz79BDzKQptdggGFnaKy1EUQSEhycPR/ZnOITagW0dogp+6GTYF5l5XEu/4pOQxnUX7ceaZaiSe+62W0pY0CgHyO5LWV7VAp+ltvev193GVZN6z8ucI+lgGBsIfSqB/dFxmMT4N0238Ub95FSQ3J0XKgIIQRg3+dm83OCBJCy2ySf0R27FJRHUPh+KsuiY+AAZQ+v7/42TOIY0l9b3tiXocs3fCHuPKPEYBjjDOyK+krJftYK3mifitouTpTANrFNZh2gaOGmKZJ2k0WZU1pc/J/PXC/R2kPrdO5oZeEtoKCnEnMfAcJQThsfX+XdnxT7R3B4UOsSImLgPyTT7/x+CI0zGNlfUJ7212xK9zvmbdajwiAB415s9rq6iZeWtF5TH7RZpI4zf2Dw56WD4Gfh9moYt2VGR9Q6XTLf1tudkRkC8zP4p5/g7aDfJ+o0FQMRUXabtl/fHRJT34YRdz4pzOHPIFnl8nEUP/+Oc1nkn49ef1Y+iTC6LGxBYwagJmQ17ms8nYu718XfKx8jWG+MBv14rvNkTiAC4vgr4bm1iJoV4p43X73aLg7LwFjxmeYeYGyhuum99pCF2BODXTjf0Fv2EXiDA7RrZ+/g3+D+p4T0NkL/ETBbth/cnQYTxwYwtt6p+6GX4ENmOjFtwBeO8lo1X6WeHJXyiJh5q2v5oo/gBuSf7zz9aYxRWL0fL175l7eLNHwJ7iJjwiAHo3ds5/r7idTW1B6+H15ZU02/frLwLqUpIAHiQSsyeFQHhBUBHdZfzJrDz/RBIDJXpr7gcqF9KR+2OAUl0wpc/N/GHAjR0AOLdJboPWDV4OmnsTPsAv/RNlu3H84dIhOPhe+2peme4adgRWZocfRAmA9LGoof593QFXBHyPj/ax3iYqAOJQWwE36zDU4Zet9WnpQW8UnTOt4s9SMDoAFkCS5LvJTLhFgOXx4fL1gRC8s8/W5fJAVgHCMx7J76gYnzFomegd+j2U+Nrr6ZMBdlI+Abon8rDrj8R95VcR3GX/QabQ87AG2xmaYaoHxhr2nbNweGShQJHW6f4htp0K/CN/MhJyWgu6EBaMT1pUS6EpWcvx/w3AaSC0P1NKroASEV4PLnjDQXwzFRWtv63+JcxJNNBWM2MykpIUfggibwcqABslAb2yVf+d1lFHRGv7d2qhphzqBtZfExf0A/ztwaQh/5nelVQQgJePMrEaJnYDHlDXB2vtvN3lmUX6ReUtZzST755ewL4s7gDiSEr0W9x8zlGN6ffF6jVwvKXzsNLQajQuA/o9WubTyFi/LYI18EXxwXyotpfCat/yOAoATjv61te5YKyZelnv4fPthwDBz9MS6zpAYgG6MBLMY6+onrVucerB9NGT0M+X3rL2HkkOACYtmsNznzyRlWad5P34hZsg2+fpOwCCUfYDciR6uAuUKIlRXv3itfsZnPjmv/aXClJW+gOOIKayI4p0fgFXpdwB/KGlaOwUAr8TclgCBF4iDqm3giR3rUyp3Pn9Mah09/AFoxvaXQIF0hyqpsN7QG5lSiHZpfzZriT6VA9DH3ph4gfeGGqhR3XMajFEFdoh/6GugP84E48iQmaWBnIZSp07cchnHUKR1m39kbGNAqAWiyQqaxYFghs+mp9vPGEtQaHWmf61s00AjBgvKTJrWgUOGkaZb24gYGVBRdap/w2zyQD4GHcpUmteBRIaYpmrboBgxUGB1pn+nbL5A+wXZySKayIFihuKm1dsUGZNQlXWcf1lsN0BYBT/Jt5mqgZ6Gcqec3OYZP1HvdYl/12teP1YEUMgUmX6B+oZHqL7dFBsyUmt2a38fazE+9QIMxzuYR4F5h2WpPd+fHGxTCHdAfy9qrjw1AXbFLpcIgR2IzKoa4YUe6lTBdwN/BGnUOhf/jsPylcaA6oiBrFbjxSCpVpN4sX6bZ6A4mPxYwYqUhIDmiYWu8OVfI6VYeHlFfu5lETa7+dW++pJJgBSL3bDs6E4m2lprerd9+WMkM3/2C7xJkRyAe4yMs0nskylDXWV7AX23YdYv5vL9uH6PBIAjjpe2B/ApLdlfXXwcfCNfJizy7q+1n40IgBCQArop9AwxlmJMff96NVwQKKTqKbK2izOATZLRvaz4OTVyZSl+oXnpWJMj/+VxrsuJjoDflAjCkf2qOWRo5376dzdVrh4H4Y6q6ockgdCXq8bVAlg+Ymt9f/91GlFfGcDbi6Ydhv+BJ5u9y3gIO0Ngbt9/pnOLTKYTL9ZwonGELIPunkLRdQ5MSFNx/n/kcIZHhA1d0Eue9IK3hCyjO9fIFH9NLXTOf69tBUL7BlHKJ5q1ga2G6aeq3WobyVLedkF//GkDPA4AFcQTlsKAGoksrY7kVSIdWFh5R37BZX81w/i1vR+SLIAMjPyy5et/KWtdiXvRfPVgdi4e8T+3XI4DgI+PXbmt89wwpGJffdB6j1voJirpwLDdilqArpNVwN/7YDi0Z8h+NniHVdYe8OBMqrWHQoF2mOXHdAT6P4dsrn/ydNZORRZ92PWj+YTMgvGdDtBkDZlHCXH+f/dweUc6DePP0J3AgguFKKTM2KEWKU8idaR/OWxsP78DMsf2lyGBD4ghqxziGyCSVrl4i36rZrE24fl/vn6SM4Dpi+Gy9uvAKbxdtXuffENgSS2s7+S1hY0NgKaQa7tP9nozjGT8fc15+1g9IzXleq0micaAU5a8xBYBMD3kanN/BHbPUJUYk9pepX+FdoL7nNHOOwzFRqVw/n8ycbxHYQ3ez7GdroIxhaSkoNmmFxpQrnWFf0xryD2yATbFlpbRgAqJUq0b5TsjDVndee59SGT4MqL1vbowkAeAEo4Dty/x2i53YRF9InsfXFonS+mXsKSKa4BWlLHBxv1hOjFpJn8Nd9FSARvP3O2mG4Yagt+bUs3ACqVFEXD8f6BxYkgEDlXQ7J25giuFsKTR2fwXe1DtdXN/zWrcPIEACMTClaWAs4nGrhnnUSWzWph6cH2OYlEwoPIZuJ6OA4DAjxq6CPWPMhpk6H3aeeRY2CKJ5LyssIjzgFyXmsZ3A4M/e2y0f5101k2UFG/WKKIphJSDi6Av1DoS80uhc9d/rW1zQasFi8iXmDiB+odFq7XiGyGkV1Z5Ln4EZdQzUfYau0aQBoA5jn23A/LdL1RiZX2eeqdaHCW85l6ucIm8gFaWGsXkAT0+w2uefxJ1o053FS7XnqJOhHmDUaD40x0S80utc9R/gG0RQRwF8McimBmBVYgdrOjjZyKyWNN5433oYxUyTvRRuTKPAoBfj6G5sfRzMitk932ueVRY4CFW46OrF4gygZqYt8gKBu1BD27ifyNz3kqyEInSPZ8Vg8yE+qMr2aYXelANdmN/PmqtO9X+Q8J3lGiA4opmsbvqJym7Xd17VnwKX/oqn+zosqeLRoB+k7XAF/0rOlBpOX+kdp9RCRlz2t2kH4XYgpOerNHgD0dK3XLnf0JuKkIyBr3IipgqgTqICaz/460iC1kIerp9PGPqMNry8bdVjgaAdZCuu1H3CjUGZn9+k3itVTAect+FqKCG54F/m0HNNgt6Rsxw/n9ocMlFYAp5zPWawIHshjmpaeAyH3tW83hQfkRl2DPx9XS6to8CgCCPbbm69L0yimQeflF5SVc5IGbh8ak5h52Bd5rKy7MJR0UocP5/93CzRmILUs16m+GBtIbKqOrfyB46Vt14V35TZdoz3vVSupmPAoBRj9a5TfVYM/9kQn4GeY5WLh9F4AapyobYgWKbPc1cC75GBnH9fwNw9UQ6CUTLDZp9gYaHsqqB4nEhTFjLedN9aWPwMKHyjLcAjgyAEJHvvAv51jZbZ9p+oXdwUwkbFtzVpWuFs4JWnqPRLBDLSkpz2X9rbXhA5ANfxtGWw4CPiROvOOghJ41ch3uLfFlfBCtB7EayKItjgJeU3ML5/xc9Ymucf9t0u026E/DUmaBug4OEmKMe2RcYNlGbdi9/22gMOWD7074ckhyAMo0xtiPxsS+oYqJ9DnrLWPAh0+LOqoKHh4FRmtnLEQrYRaBw/n82cB1FMAkHy8OZY4HXh46r1+P7IptZaHpkfdNhbi647/m0gowwgASTaMBN/do6EGpqf7R1Sk+LFYvWpqHDgy6EzaIp2DwXplBidjx/CWk0OWn7vL79kRiAbY27tu3xjjBWY9t9pHm4V10gHOFlqdaG4YG+mxrOpwwfSPZx83+pblJCxAXNx5OX4YBFibKuA+gwJ8pcsXtVfI9epimM6rGwPoqcgCmWncVcA0pAe23ef/Jy4Um4DvTP9Jw1gkeGKqiS3+wes1Y9eRF+AGRtMb3yTLetjRSA2JGfvm37Wjk5aUl/InYAUD8WCdfeocyDMoT6opbY3RdLUcV2GH84aMI3nPkHveOQB4CZjgW54PR3M2pldH5teNBUWxzv3CCmZ4XPgvyeA9MZErxMg3Skf2NruTwg/77Bq5M9gD2Mt7S477kuPWKUfQV6blgTIZThkanVhu2BD5zNzqgNKEmjcuN/pG1iQEQDWMXelYuAn4qgsfHrNCvTX9N8Dnv0Wm0k6+QVrPGHZ4EWmujLkwqjRkdx+X8Zb89CCAbFx2GXzoChiauviun0KENeTXyme3ZccSbu5pqtoYgjgf2YSsrbCD5FhXD+f9ZvCkRsB/nIH5jzgDCJza5+6AAonl0VfN17AV0jJ5jnFK7ViBKBuJjsyYII/0RocP5/5m8ZRHAH8MgRmO6AQ4kAr83oWSjoXTN8unuZXIcm6OaBrYqIMIFDmc7KiQnoRfJw/H9Jb/5CFQarxziXwoDciUWwd+r/KR5fo3w5ezxbmSTh5OOrxoeCgaaa88zuC/NHG3Lsf/dtskBaAy3FnJV6gAeLpbJ97e4sNmFVfUx63FhVIYXhR6mahhyC7pxj0LAPF0vQc7t/3msrPT//g8FTky6A2owvtuTxHDEcZC9+13hoVbUc29zBpSGFG4MzoCjVyRQ+T/V1R3/haFg4xPm9vHmQA4B1j/a6r/d6NrFnDH+4dsdQsBbw1m6hg4OnhJOkT9szG09UYHhmft5kKDLt8vW2OI0lgP+SE8He/vE8zWu7f8Bz20pBD9fPdZzzgfKGMqrl4t4iIVrceuB8q1+JKsXqTrDGidCAqpeeyGwHYUQ6cP5/vG+DQ2QGrMcMl7KANYo2sfLrsiuDYCl9d3oZWWohXOH6qGWGR4Kpna/RUBGcTLV0jn9uaqA6IfyYvnWRCoC0jsi5ePaMNTNn+H7jdvpQwRbS1jehZYPXhDOlWdxxHGdV7XgYfpljGTCF8NO0AoxSgLSUCsRvAjlA4W3uf9ZxI0ePClTLVZkkgdaIfa6j6KgodV6DfEF7AFvbI7Pjp6oTh+uBe5wW0L4PcksqdKV/AWttO+T8I7+1kQyAmo62uYb2uTVlZwd/qnZoUOUV3tVzoBuDPIVNpvndOR7bVpl5sH0YYsMt5u2Xss6KkoB6lv/G5QVQQ8Bv/n/yb6dDSAZVx62WmoCvimGyrO2WLQBirH2ceddWIx7T3SOmJoUxg8SgZtaLFv5Q+3bnfsFmojQ29YO44Y0agKiS3MAH/3E9U2zQf/lyDUmmDA3NVZpXgWSItq3b5xwoN156fDt7ylpdI/zi86mzhiqCf53H0cQRQU0udWt/YWmkOI35F7zWjwKAnpB2vSv7GjpPapF/e3TcSwAQFtBRnNSBV4d2qwjlcCVaXNZ75nuFXKklPuWdq2eHzYE9nAHQ9A/cS4B0j385aug54/oovWiQAoAgkKu8UvprOe1phH+zdDdMXBBY0HCc2YFVh3+rKOWkJY5c7nvJeyZcEiWQ5AerHof2geKcCNEiEeBMDnVvf19pezg2+aq7hY8EgByRcr58/Go7N2u0f6dzIkq5DdHNsppkgVuI0q086LUozl68fNt6p1mVIfPgO6jmhbaCfZ/j1EgVQVDAdvF+vWZQNIn0rrdJjS2AspPgwqgBBUAKbvR/MXGERRQIlcg9l6mAnYqRsk7ukS7vYgN+4njaVCEbedpnowOEUoRDpKrbWxzOVU55xn0RYkUt5OxmsQSK1IAvmB3K1gkLRxFy43/4bCU+af/TwGqSEoB+jv25bPcNN5VoUn9vdXRNoBFI0eic7YFEh46rfuU6JipdN3xqe/ZaLiNh4iupO4aIggWfZNT0FCRQxHbqfn1mwTO+8962xYxAgImUasSXA9pBM2/+f+hvFEMEBarFTJVYgDGMzbV78qIyx2XDfil37lDjFTnVjJ+tggiGwajr4dEixFpeezt8I10TJjjlQKsXhwuCa50r0rcSck79dSZ/k2dUNVr1HbhjjS2A5ZN2w54CHEHTbv1/K3ByQ1YF28VblViAPYz6tc3yBzMaZtl+4nZCUO4UNdTGnmyCd4bdqX7jeSQMXN57uXulW+gj5+JoqUSGjYI7n+bUshXlUDR3uX6DZRMytPEGtbaLcoAlljLH7gbgRAVx9H/PbUY/YQBjwZWSEoCkjoe6ZPg3OIJpgX+EdGFLvQ5JzrGaUYG6iAKvQeoiK9lgfX2keUxWmxyC29qjEYRghLakstzTHTtXCno5ffVf0yna6OCtL4iMgbKb2c97ENlMSnVRf1NoRzYn9pO4h40sgPyT0sNFA+BBY2/+f2Fv20E8A8fD8pMrgJWNtLhY9n02fWhZfyJ1fkz6D1DPS5twgXiIkK7S6dgqvGB8fZ15IFZAHAfbaqPgg52EcaXT3RgfSFiBetx8u170J8jmK6xeh/aBXJ1v0l4TRE+Hdu9+SWYCM3LyabXMi3SAVJa7x8sH1EWsceZ/zWxZPen9A78NkQKAVZDEvXn8GDwObNd/SXLtRhEJ2MgBl42AWYuUtH3xLzLKZdV+x3a4T9kTzdKMnf+BV4cwrO3mNSj+Xvl8UHq0Vy4ex9ySpECERIScpNfcQh7GV1l68XzgXgIorub4qzqHEYLXnUnTbBQ6UAt3uX5AZUkxbfCks9WKr4Dcl0vKxwpzSChzuH/Xavw58/l/u/qOD4CnkuPBZAGJQMZu/n+sbxdCMAN0w5STH4AvjhW6UPiOOPppnH/Ic5dJGQxvy42YzoBsiuOylu+XMNlkpX41d3xQoxRf09GdCYJTh0ysP+eyKHZfKX3+ecdWxRw1206jwYPYhEymUt/uIORZO3sufH1ceyTj4vGo4oXvgt+g1NdYGTRU6njSfaFhwSte6quuXoiMgQGcx9D7EXROR3b4fjtmlDKc8W20JIuhgKqXLsreCrNIYnOrf1Fq9DiV+Cm6JY4igNOTB8QKBP5CSXD5f+tt4T5D/9W/U5ECgHSQU76F/V89CW3ufxFxXkSfBWXFoZQ1gIWNDrlS9+E3sGmXf8xzbEmoC8/KApiugPyKNbR18YwySWb/fiR2EE5ZEQ3QbJtigdKIxa/v62gt4GIyfiN4TlKyFhbV055GgvyGuavD5noofV86fdF5KVayG+bZL6JPg3SFDKjw4cojKlwhfDZ7p1lXIHbed6V0hC+Eu6R33Vsf8Fjyelx8zlykJMPioqishSeDv6FX2TAb1FW0eUl9oV+YKMrmrKvuhlOCE5+P1U4X3lJveAZ+JmI1LIjqja4ziKyBs5wc0rYTFFAsd5l+YmR9L/rtP7F0iSuBmpr/zmoQek3wdQl/WWZxMh/xwLOqisqAw5g0zGwNFEvBdFx/EWgTNfXzCrbPi4OAKZe6yb4K50imc5h/jmlmN3z2GrjfjFGAyZWPx14I9UaicsF/02pqObP47bnWjTCAn5SxxVAGQUW5cdx/42shO5n6gbuvjhqAp5MfxJIEzUPwcO1/w2yOPC/81Lxojw6A35LXwiQDnEJJcPZ/dG2yPXT94739jweARZLYwQgCr0HGb/t/+G2NPmj+r75tkAOA1pEhwT0BBkFpb/1/Um4gPwr/Nb+3kAKAkZGxwMMAokA0b/5/gm5tP1z/db/YkAKAdpGHwJoAhUAmb/5/iW5zP1z/cL/SkAKAg5GkwMIArUBAb/5/Z24zPwz/JL+jkAOAuZEIwTsBHEGDb/1/HG6sPmr+k75NkAWAGpKywQYCz0Hsb/l/pm3ePXf9vb3RjwmApZKlwiEDyEJ7cPN/BG3HPDP8o7wwjxOAXZPgw44EA0QuceZ/NWxnO576RrtsjiSARJRlxUsGgUUBctF/Nmu9Obj4qLmJjT6AXZU1x1kIP0fzcq9/A2rGN4L2y7eKjGiAqpZSybcKOkn/c31/mmiCNfzzsrVyi6OAMJi+y2UNcUshdTd/92buMibxX7NHivaA8Zl6zmIQ301VdtZ+FmUJMALu1rANiWaB85uJ0a0TgVCUd1Z+8mLQLJHqHK7Kh/mBOp7t1EQXU1PYeK99h2BCKdTmNKuFhrWCy6Cm2CYbT1Ybett8z11dJc7iJahGhaKDq6O23FAfb1lWe9R7xlogIYHe9aQThMaE36Yg4b4jrlx/fJB6ZleKHPLZqaH2giuGa6ri5W4oBGCOfQh5q1ObFyPVS573gdiHVq7/6lstaGN5fjN3kE9REhrQ45oigdaJo7J18H8y0mY2fwp1EEuvDN3KepeAgC6MWLdD9tM3N2q7f4JyJka2BnPFG5QcgOeOd7xn/FE9jW36f5Rv0EBnAOO/0ZADgAySBcLeAvBCyHDqfzZsCTvJ+Ti6qY1AgKWVBMikCaVI2nN9f2Bo0TTc8nu0sIrhgLqZds60EGZOtnamfgtkJi6q67qu9YfxgVKeW9UHGCVUTXlZfS5fByc55P+ohoV+g3ajs9yUH9ZZj3uJe8NZdx+T3FyjdIOVhSqpeuRQJ2hfbX0oecRTeRfE1N+dz4FCiHOvrewwL8xk1X4sdi5NEg/XzJqYqYCRi1e2R/UmN+1ptn+Icv5FSQbcxKCTEoCNj9W9Pf4hP7pu/n8xbjI+KP3lvAWPHIBBlO7FhgcQRx5znH8eacw1ufMEtd+K2oC1maDOFhHeTgJ3f35GY88sDOpOrUKHW4Lxn+bX3Rp2VlF6lnylXEIjMODapUeEsIT5prjhySS/XfN80nk1VS0ZO9bCngSC6IfQrgzswy6gZNJ+I3b2TJ4OQcwfmJCAEIx2t9P2tTj+atV/fnHqQ6QDXsIOkgKANJHowPsBg0K7cOd/2WsVOlL4rLirjHGAXJcdy3ENEUy7dfJ+LGWCL7/sSq8WiPGBj54M1hoZPlXfeeN8c108JAbhW6ZrhJWEzaak4dsk510Jfad5r1RWGEbVAJ7JgW2IFrDS7ZIw6mUbfy915ErnC6HJX5ZOgIaNYrp8+hw8IG35f3JvGkAK/zy+no8TgOqTpsWFB1FHY3OJf2doYTTe8UKz44k0gZ2bz9HKFAVSjHizfQxgzSeJ5N6oVYXFg56kx94kIg1cdnxjemZWeRo11z+fGYLYh+aucOxmLzll/H6JdX9LhAwSypOWUoB7jWm6pfpePFht+38cb2Y/Gf5SvQyPIIC0lBHHPAnYSDp0V38XZzYyY+8ssdqIoYGDncLUBBibVLF59Xx/XQ0kluDZpSuE6oTgp1jjxiZuX419wXhgUhUV7tGVmyyBC4q8s6byRjUUaaV/sHLORX8FqMOckgSADpH8wHYCQUNTcdV/vGrpN4P1CLYoi9WA8Zl9z44SdFDud/x97GDYKGHlValyhbuDqqQS36gilVyxfAV6UFXOGGHV152wgceII7GC73oyXmdnf+FzAkgICNHF1pMQgAKQO7+KALRBhHDnf49rKznP9gK3m4u5gGmZxM7iEQFQxHcNfhhh/yhv5UypZ4XKg+qkg98zIwtd3XzBeZVUvhdE1AWdeIFUiWeyMvEhNHtolX/3cipGtwWrw4KSA4BckbLBewNMRPxxvX+0aQ42QvMHtBeKMYHWm47SAxZOUz55MX0KXoQkwuDBpQ+EH4WnqLDkYSjAYPp93XcdUOIRo849ma6A24uit7r3JTo+bPN/u28kQIr+WL3ejiqAX5WHyEUL2Upndfh+22RnLunqV60Ah6yCkqEE29weCFrje+p6X1dDG3zXGZ/3gUmISLC17v8xOWdof71zgEcjB8TEEJMGgAKRPcEkAylE/nG5f31pizWF8kqzqolfgcGcGdTPF9FU7XmufEtc5SHy3ZejSIMihlera+glLG1jrX4zdmNMBw3/yTGWPYBTjny8sv2PP31v9X9QbBk6ffdGt5eLxIDemc7PWRNvUYd4lH0qX94l4eFkpjiEBIWQqNHkwCgsYSN+c3cATzgQ28zyl3OABY0ZuvL6OT0wbv5/mW0zPMb5G7l+jI+Ar5gLzooRFFD0d+F9LGA/JzXjUaeIhLWEy6fb4+QnomABfrB3eE+8EEPNKJh6gO2M/Lnk+j09PW7+f3dt6Ttf+bS4QYyfgBuZxs5mEtBQTnisfWVfDSbq4U+mJoQihfyoiOWXKdlhVX71dtBNkw4zy9CWS4AJjiW8h/2cP6Fv8X/pazg5RvYWtueK/YAsmwLS6xWaU4Z55nzFXEMiBN5toymDZYY3rN3pzy26ZP9+I3XzSbkJu8YIlA2AfJCpwNsCP0Q2cqp/xmgMNILwX7GgiOCBC5/U1w4cS1hie1J7IFjRG5bX3p7Tgb6Ip7Hk8HA0C2mzf/Rxt0MqAgDAFZAUgJCUsMfgCvdKrHXPfsNjQSwe6MuqyIWngwSlWeC3JJxefn2MeC9RoxLFzvWYkoCVjI+5qfpJPWhu/X8Abd066fdEt2eL3oCrmm/RgxVyU4V523x9XKwhO926ouaC2YZ1ra3rtS8ZZkd/CnSZR6oG08M0kgKAcpI+xCYHA0hCdDh/wGUlLwvr76ydhhCDTaMY3pkiMl0YfSZ5fFIvFBrQvZmwgCGMybjc+bI8IW7+fyZtAjvy9zC3UIvogPWa/9E7FhhU1HmbfKBbWiDL25+hioJ4hwCvye3NMYZnhX/mckhFxAMrwZ2QDoA/lGXHzgoeS9h1tn4qYx4rr+aEqTaFM4THpgLjkyfEYCJ+O3cKTmcOoMoxljKA945BvnUAiEJ3ccB/RWl+NJzwJ7FkiA+C+5+N2TEeJFojfGJ6Y1XLF1rTw5sMgeiKf7ZF9446+Wz9fx9uhDx4+U24zIvLgHaaZ9HIFeJTzHmWfHNb7h812xehWoLchwiwR+9ZM5torn/ocUJDMQHKvjSPLYAOlobKbg4tTll3Dn5bYNMmFeL6peCDooW/qn7oCC2PZAh/ynTLSMEHesRmkgKAnpLbxDEIK0n8dPh+PGSBLOjnRapvhQ+Eiqbp4rIn/2A7fu92Nk0jDUTJO5UbgAKQVsAZA/hE3nKAfzRnBDGh7Nqt34b7glCjgd5mIwtebn14eJZQWREUzZGXVYAcjum8K/+qQSBxx39eaWU0OvChsA6ISIL8oELbMSDKW8B8gXn+UmMU3s9QmZOA1IyHumb8UT/ab+d/zmqvNq7yirLniN6Be58k2RgeTlpGfB96eVRFFpjRZ5rAgBiMJLnL+vY9HW/zf5Jr5zf584qzWYmtgcOeJdgfHaFZDnxfehJVARc+0sya0YDdi7u4WvqePfFu9X+zaxM4HfScs1yJroHOnkDYSB3JWR58R3rMVJgWztF7msGAIIxKuRP7Sz5ab+9/M2syNxfzwLLxiOCBm5942ZMew1p2fNV5pFMJFUnQd5mUgOWM07r1/Po/UXDafwtqQjXq8PqwH4hLgjKhztv9IIlcCn3/eJVRUhK0zcmXVoA3jl69AQClQstxqX8waD0yl+1TrvSGAIOfo0ffgiQPX8p9s3eTTnEOFsqClRyAKJD1wDcEP0a0c0Z/kGUZLiLp3KqIhRaE9Kbq4xopQWKbftp1jEpkCXvFuZICgNGSpsWWCbhK8XWRfhJizSiR46um+oOthUWru+m5LgNmW39Sc29FKQP2v4+PK4BRln/LGBD5T1x4Zn2aXU8i8NzcoXKC64eusMDwTjUyauB/+G8lP8P7n7krjMaAypqR0rUX4FXLepd7CFiUGk7Vl5wfgfyKSLf7+L48om72f6Brmzc485eywIgGgmSg6tpcIEdcBX3weDtRmBHGzAuXPIASjzC/ZwLqRB1zY38dZrwulekIq4mFJYRHp5Pk9Sn5Ysx+OXUSSVwHesNzkQmAYpR8yPgMok1id+Z9QF98JPPeK6PLgmOHma+N7100t2nYfzZwbj/q+5q5FozRgCGbQNOYGK1WJHs1e9xW1Rh300Kb1oAEjH650vtiPzRw13+qaTs0We9ir0aH4YKDo4PfICXCXwx+CHfITM0LVMegkwOAS5IQxUgJwkoYdnR+W2FsJ8/hIqVhg42Gta1B7VoyiGi8fxNx5kB8/dC6poywgHmaXtLKFypW/HpUexdXBBmG0zib0YAmjNu5Yvz7P5hwy38PaSQzC+5FrsOGP4PHpGXhGSczYW5+HXa2Sh0J0MQXkgWA+pMIyLcMoU15d859v16GI77dJKJxghKIXbEK8t42YWv2f3tuJDzp9xW2PopwgUqeONj7HdRapXxdefZRKBL0zPCWNICEj1LAFwSlRil0FX8oZGUrteXZp0CEhYVJq0vqxC8DZ49/F3KcQkj/KbxDjZKA35mg0TUX31XuelN78FaeGPXSupq1gKuMCrv9/YpBiXGmf6tnvTBE6/qrxYUOhFinG+XmKuJjC39CdMFGHAQ+wGqPOIA0l4DN4hKhUq95YHzkWYocqdYinSmBG4sBuG76hT7rb9p/jGmsM1juS66vhl2DVqVv4mEoP2K2fkJ1tkhmBizCcpAegBOWvssPEUZRJnm/fPxa+B371/mdVYGjihq3avmyPX9v43/zaUI06O6srtGGSoMmpT/iRCg3Yrd+N3WQSCQG4sFAkCOAY5ZSzMIR31FseYl8RlrrHOPWMJ0mgTGLTbjw+hg/T3DNf+pohTL07BqtJobNg8OmieSPKs1jDn8hdE1GWQNjv9iOUIAqmD3P9xRmVHR6sHu6V2EZZ9PWmrKA2YyluwL/q0JGcn9/WmZoLn/oqKnNhAiFSKpW6TYv4WaSf9lx2EEC/sW6YYzRgJCbktSoGrhYDXwBejJTUBOczReXMYDRj0PBnQVISCh1tn4OYtQnmOGGpAuDQYfjr7DwHDY2a/d/HG4GOyL2NrQqifyB16Bs3L8ilV7efSV3c0yqCqnFRZIGgG6UVMm+DrVPmHgLfbZbqx5b2AWeS4Heiti3ovoMP2dwx3+FaKcxx+sDrKWFSIRXqOrmFC2cZWZ/pXI0Q23/0rvYjLiAHpsN1EoaklgLfPZ581LTEv/MnZYkgGWQc8ImB7BJ53VnfptgiSUY356icYJRiHeyHvReOTxt/X/wayk3qfGBsHSH9YJjpJrhCihVYs1+zXRdR0YE47/zjlKAcJj9zxwWhlX7ehp72lWJFmDQrJhZgMmOnL/9AylHuHTSfmZiFCiW4VSk7IKHh7+wDfKYNz9s/n/VbJY4I/OYseSHtoKho6XgMifUYbR+CnXFR6oEJMALj1CAcZgV0E8WwFUXe/d6aFXZFaPPJphHgE2PpMBHBU9IUnWZflBhYSbC3/SigIJIiI2ya/TROZlt+n9Ya/41LvAwr9WGa4P/pQXkkyonZC9/bHN0RJoAkbwajbCAH5tX1OEaOFlVfH95lFHBENLKHZUKgAmSnMUDCw5NkneRfTZdYiCq2aeeYYHLigS4PfvqPxBxqX89Z0Mv1+h+qZeEa4W5q83rDTIBadh/lm8yPRj4Z7WHieaB2qDq3LYjll82fjZ2CEoxBybCCZAzgHyXxc4hFQZV4noce6NV7hWDz/CXPoCvj4nBhgaFSf11TX7pXx8kRN0NofCBeYlXtRr4SD2ub9R/yGiZMTTrL6suhdmETKoK6oUwHmjFfzdwOT4j+Se21onJgXuggNxrI3dfNH4wduJJ4gbGwcWPPYDzl6DPKRblVT17t3p8VEoU3c3WliKAvJCJw+wIkkv9dtJ99103IUDa5J5lgdeKU7jb+6lAlXGOf0hmiS3I5sin7oNDhhGuGO9SNSRr+n9pbSc5TfNbsaCH+ILSpMLitCnOYyp/WHP8Q67/ebthjOqAn5z11vEdtFsyfRh4903LC/3FEZIMgHyVxsssEvhSLHqwewxXixfI0JWYS4Brj0nBgga6STF2K34zX9YiuNvNn5aBaIqLtw/7GkBZcZV/aGaYLbLmnKfWg22Gl67p7zQ2wGv+f6tswTea8eav9YZyg3OmJeUlLIBldX/+cURBWvyPuN6Ka4Ejn9XaBiKyXg9+Z3YZStsGfsF5j0uAqJgF0e4Xb1fce+15OlIOEZrKr5QEgACTwsfxDdBP83iafKJZ4hrN02qahYAmjhS/IwTqR2V1eH5SYEskA92UoL+BFYoAt5P61D9IcZV/SmY/LSrmGKefg8OGiq9N8aA3rmz9f41rtjUx7+OtFoYohLSoX+hhL6tnwH8icKo9CfjhtBGJOoJ7otDfJidSYut+DnQZRacAAbyAjOyA35yp1/8eslyOfVl3AEwBCTTDU5AzgNuX7s/4Ft1WtnsLemBSDRFsyniUAoBqk6TIHQ/hUHR5L3w5WMUYmtHimE6Aho/NwXcHzkrUds59j10kILPYgp0IgSeMaLsOALBE5nPzfmZiJSet30uiJoJHiXe16viTPrVwqH/BZsUtf+Yup5mD3Yb2rw7ygThPbfh/p2oENCHtIqxYheGE5KqA64UywGnufx5u4jmN8xyxVYdJgz2mQ+WmLBNmlH8scV4/vfkQtoaJDIL9oVnf7CZSYvN+2HN6RKz/+LrgiyOBH57C2V4hiF4Xfil2OElXBcq/Wo6EgKCagNQAHLxaCX0meJpNvAqAxOqQJ4B5l5HP2Rb4VtF71nmlUdgPE8mHkwOApZT2yusRQlN5ekF7W1WrFH7NK5YQgB+SrcY6DaFPCHlufMBYMxm80cyYRoDgj7PCyAgcTIZ3Yn3YW3AdyNVkm5+A5I0Iv5gEt0j6dSV+pl5jIaDZ7p0UgSWMqLuqAHhFa3S+fi9hDCVA3WOgnYGeipG4Av1jQt9yMX94Y2wopuC/ojWCSYnCtZ35ez9bcYV/g2WEK9Dj/KTWgiKINrN99sQ85G+/f1RnVS675henfIMlh+uwo/NBOoBu5H/waOEwZukMqSGETYbgrg7x8zcxbfh/WWooM9Hr2KrChJWFEa2+7t41+2v+f5NrLTX77XisWoX8hH2rs+wCNONq/H+hbPA24e/qreaFfIQgquzqYjLqafN/hW1zOIbxLK9khhWE+6hq6f4wE2nnf0Futjnn8jyw0IbCgwqoK+jYL2Bo23/Ybrs6BPQYsSqHg4NMpzDn8C7SZ89/S2+CO970wLFuh1WDwKZ45kcua2fFf5tvDTx09TKynYc3g2amAubdLSxnv3/Kb1s8xvVvsrWHKYM9ptDlsy0VZ71/129tPNT1dbK1hyqDRabh5cgtJme/f8JvQzyf9UWyn4c6g32mNOYdLl9nxX+Nb907JfXfsXGHWoPmpsrmsS7BZ89/NW86O2f0RLEuh4qDgaej54UvSWjbf7puWjpm83Sw1obMg0+ov+iXMPZo6H8cbjw5IfJxr2qGIYRQqR/q5zHIafR/V23gN5nwO67thYuEhqrD63MzvWr8f2psQzbO7tSsYoUOhfSrq+08NdFr/n9Ta2Y0wew+q8qEq4WardjvPjcCbfd/D2pHMnHqfKkqhGaGe69K8no5Tm7jf5to5C/g55GnhYNDh5qxAfXsO69vvn/zZj0tEOV+pd+CRoj4s/33kj4kcYN/FmVQKgDiSaM9gnKJmbY/+2pBpnIuf/1iGyez3vSgpYHNin65xv5xRDJ0uX6nYJ4jK9uFnhuBW4yrvI8Co0fAdR9+D17XH2rX/5ulgCGOIsCeBvxKTXdafTFbxxtz02qZSoAlkOXD7wp3TtF4ZHwJWGsXSs/KlhKAbZL3x4APD1JFejV7k1TFEvHKJ5QCgP2UWsxPFL9VoXvIectQ1Q1uxoeRI4Dblw/RWhmAWd58FXitTJwIxsHzjn2ADZsX1pweSl3zfRV2N0gaA/+8c4wZgZiec9sSJBZh137Bc2RDVP0fuBCK/oGCoiThtynbZIB/EXEzPkv3L7PVhzWDz6Yo54Qvj2jmfwBuojgC8Teuy4XIhIOrf+1yNSls/H+FarAygOo/qf2Dv4ajsCX0ejueb7p/m2ZbLMrjU6R2giOJMrYY+5NB4XIUfztipSXn3H6fQ4H8izK8UQKyR+d1AH5gXZAe39XMmnCAU4+mws4JzE2ieHR8BVgdF7zOSZYKgDCTjMmGEdVTBHtkeidSUg+JxwWSHICZl+TQbxnAWQB9xnfCSzQHUsAOjrOAlZyt2IIhfF+HfpJ01kTM/iS5dIrdgSmi4uCwKfxkin++cGI9IPYPskaHpINZqH3p7jEtavt/QmxpNTztJKuWhBWGJ6938is6/27Kfxhn7Sws5HOkdII7iZS2x/tYQl5z6n47YfUjAdsRnvOAHo2fvl8FYko3d0x9plqIGsrREZgjgMiRRcc1DzRSdnrkellTsBCayIiSFIA/l4DQNhm5WQl9p3dTS3oGhr+OjdiAiJ1I2lAj2mDZfolzmEL2+6S2N4l8gqWkkuRvLX9n1X+Dbi05NfEOrpyFEIWXrFHvejeObep/j2gcL0vm3KXTgp6IW7Vy+lhB7nIFf6lhbyRS2yue84Ayjeq+4QXuSoV3F33RWTcZYtAYlxGA0pI8yYkRHVQ3exF6CVGHDZrFwJBBgIKZQtRNHcZc7H3odVlHdQEYu0GLl4FDoevfESnJZIt/lHDKPB31/7C5hiKEE6oj7LI0BGz7fw9qazGb6HGnRoPwh+uzz/gOQFRyKX9ZYlElEdyVngKBCo28vtAF/kqZdwN9dFmUGKbPkJYJgHaTeMoHE1pVsHt4eWpPUAuBw4iPc4A1mwjXSyD3Xnt+f3RIRKr9zrekiVOCQqRO5HItrGfcfxJuIzjG77usCYW5hZKuK/JPOkxvun8xZhQr0eF3otmBsYoWunYAsEaudf194Vw8HfrTMZk2gECRt8YED2JSqHqVejBSwA53xhqROoBmmVTUoh0wXRN+d3UxRtD/frliiv+BGaPL4hos5WbNf55uADmb8EitNIWUhUqu7PEyOktvuH8NZsAqXeERoruBBovhuoUBq0cvdrt90VufG1HSE5gdgFWSvMhdEUVUYHvFefxPzgu7w4qPeIB9m7DXMiG/X7F+znOvQov737WtiOSCbaaM574w2Gn7f9ZrEDQW6wWpsYNxhwqzEvi5P1FyIH/oYVIkutp0ncOAJo4vwf4I1U3ueAd8GlawE8TKc5MMgPuWq9AFGsNaeH2mdo5IcQKGu0WLqYHioUTh1Co2Zr9/+m5yOeTwVq0qha+Fuq6z8hQ74m+efw9lAile34mgWYEljFm9pgRpSoF3+Hz/WIIXOs5ylQKABpWGzcUWd1jQfMB380pHBdu9YYxHgTyg+t6vKONkmn/zbyE7rfKlrqCFP4WjrWLx/DlUb7F/omXPKRjg+qBugfKLB71eBEJKeHf4fO1YUhf2zTyVAoBWlSPOhBcVWQV9YHcGSgwEubzHi4CBT6Gh4GMqC2a+f+1uMDlr8NSs7YT/ha+vHvSBPMBwc3+0Y8Em5dy6nvWAgo00wCYIY03XeAd84lUfE/zJ2ZIXgPiXh9I/HI1cAH5wdbdFwP4yuJaJeII5pULm4S+Iaft/umuIMyXqC6hLgymIB7Xr+oBC5XOZfgpfvx/c1QmaQoAkkQvH+A+RU0B7xHmbT9kKeMKkjrGASJ3c2tkkh2JHf31xwz1k9ZCwSoa2hFqs+O/xOOFuvH/fZe8p+N+3oFaBVYwHvssFoEsoeHl8I1ejFDrLe5MOgHeX3tG3G0pc9n11dZ5FeP7Tt1uJoILkpVjnDjFWav5/xGrCMRXoaqbFghmJR7fW/R9FPXUNfppcGxwv0p+XEIBoky3LqBQ3V4V8DnhPS0wFg70HjHWBW6EE4RMrrmbSfw9uWTcP7sqqIIQOh5myIvhPQORy435EYE4hKde6mlKAz5CoxsYPmFNTe5x5BU/fCWjB+o3ggISe7twiJy9kjX8FcNI61vGdrRqF7YXSr7D0XD1kcUZ/VGJLJAvakZyOgHCPNsQcDZpRn3pbeuVQMQxjw/2OpoAznQjbUCUIY2R/1XBCPGLzwa6BhYiF1a5981085XBgf+piGyXK2gSdnYArj8XDrwxTUYp6a3oCUUUMZMP1jqmAVZ1M26UlTGNwf5FwtDuw8iquQ4XMhZevifRaPXRxPn8QYsMjYtkLnHiA+Y9TxYAOx1IXe895Xk8ZCmzB443tgOqeut0fKPVkqn80byQ5wu/dq2yExoYistT3SkACc9F+uF89INnVt5kygO6R6siLEuZVLnxteOZLrQWJveSLkIENolvisyzpZ+1/nGyANJzq9acjg5+Ij7Zi/RhFZHXofb9bfBpA0DKWAoA3laLOyBiJWpd9DXZ6RgD/27cvidGC66Y+6Uoz72v1f49orS1L46aisIGaiwe9MAWXS1V4OHzsVXMSt8i/kTqAGpqX1iUhcmD7fmBy6T4S9pqwHIYLhcOtcPK4O7VwYn/BYo0k7Nk8nHmAE5C9xTcPhlNte1h5/E0YCHS/xIxJgeyg6uB7K0Jn5H//bAA19+oWqCKDsYjftvT9u0XEdbN90loCGa7OJpUDgHqW5dBcG4FcIn7IdKJDb/vKtMeHvoMRqq/tjDd6br1/cmWQKNjdxp7cgE+OicK7C+1QhHpPel9QAgvkwfaN84BMn6beYin/Zcx/+G2YNpbsM6l0gzuI6rXm/PBEcXXUfTxbeRkDz0iVA4B5lv/QlBu+XDZ+jHQLQ6D6C7RshwaEBKsQ7+c4SW+ef05krybW21qdnIBzj8vEZA4SU1R7YnnnTcMH975sjHCBx6Ff4hwtaGj2f7NrkDId6NalcIILig26BAJMSXh3tnw7V9wTr8kekjSAFprm1swhHWElf5dxGD2o83GuMYUOhruwmPavP+9yxH4dX9Ye+9M5mBGAz5OszCYXsFlyfSd2T0ZV/uy2mYhEg8GoNOxyNv9tx3+uZagord16nsaAx46tw0wNW1Iee5R5Qk4MCBK/Z4x4gQai4+LBLeZo+38Pa1MxouappBiC1Yreu1YEUUtkeA18CFXCELjGYpB1gGycqNq+JdhjlH9mb944w+6WqtGDzocvtVP8u0R5dcF9uVpwGL3NWZQLgNOXgdODHgJfxX7XclU///UbsMCFioWMr0v1uz6Kctt+bV8WHwfUIZgOgB6UZM0gGIpauH2FdcVESvwWtbyH5IPiqkHvaDm/b4J/QGO4JITZmJtYgC6RSsikEo9WlHyQdz9JnwFwuaGJuYIbpzbq2DQ4bdh/SGZcKSXeoJ7GgOiOJsQVDidTd3sVedFM/AUUvVKL7YEmpCbmGTEPa/p/m2gILeDhJKE9gTeN7sB5CmZQfXoreotPXwn0v7eMZ4HxoRDjNC5Yaf5/S2rEL7DkEqOogQeMmL7UB1tOuXnlenZRyQsGwr+NFoFwoO7gMiwjaPZ/ZmuUMZDmXaT2gUmLHb0lBg1NOHlRe51SOw1Cw16O7ICZn7/fFyt6Z+9/9Wt+Mn3n/qQcgvWKd7xvBYVMBXl4ewRTtg2kw4yO4oBnn4Hf5ipiZ+5//2uCMnbn8aQXggaLpbyxBcNMInlde61SOQ0sw0eO9YDZnzPgnivcZ/R/gmuiMXzmN6TmgX2Lp73qBsdNjXn+ephRxgvawZONKoHwoNfhPy3kaP1/emrcL4/k0qKQgWCMgL8cCYxPQHpTer9PWgmzv3iMiIG2om7kxC9yav1/32gqLbPhzaAggbuNN8JEDApSLXtQeRhN9gW/vAKLIIIzpfznKTN4bOR/pGaIKevdNJ6pgJyP1cVhEDVVQnzhd5pJlwEHuUWJBYN3qIXsYjfjbp1/tWPvJD7ZGptBgBiSY8pvFfxYZ33xdTVFQfyctFmHUYSUrAvyZTybcQt/AGBXH7bTlZcGgEiV7M9mG0ldfn5jc9s/9PWRr12FIoacsZD4HkKCdA9+bFu8GGHNxJMZgEiZe9Y+Iv9hY38ZcH05t+4BqnWDmoiktxEAeUhzd4J831UZEVLGyY+kgDSeGt7mKf1m63/vawsyleYLpMyB4YvBvosIVk9Cejt6QU9tCKW+0ovTgS2kzeZIMhhs6H/BZnopnt3XnZWAIJADx/ERkFa+fAt3eEfB/nm2D4jZg1Grl/BIOx5xJX9sYMIf69OYlwWAgZV80DEc+l2sfsNybj4e9PutvITohr2zcPu+RNV1aH3KWOIUn8mEkVqALpwx2y4nXGXPfzJtFTSb6GClGoI6i4m9SQd4Tvp5dXq8T+II5r7gi9WBTqQk58Ayc2zgfypmYyhb3OeccIACkcXICBQ6WER9EHYqRdb7+rP4hreEBa5K9LE+9HKXfn9dXBuNz92UC4B0mHjVhCG4YWB//m8DOd/tI6kfg0WJarmHAr9Kh3irew9TDw1wwpmNPYG+oZrjgy+davl/CWhEKy7ftp6wgL6PjMazEZZWz3zUdsJGoP1UtXyHVoQBrRTzuz2Ecrh+A178GwvQGJUKgFiYZ9WPIdJhZ3/Ob5A4Q+2aqPCCoolQurcDzUv/eER7zVFOC83AuIyMgUGj4uXHMQJs5n9jZoYoRty0nGWAZZGtyT8VR1mafU91WUN3+eWxE4aThZOwzPfvQaV0531pWskWD8smkkqA1Zv92k4npmXZf5ZstDLL5tejq4FvjE/A1wqFUTN7C3nRS5wDH7p/iQuDEqkK7mY5VXBHf+hgCCDB0zqXAoBellrSlx7wXx1/A3GmOmXvDapVgwiJILl5AvJKtXh0ezFSogvuwLSMlYGJo3TmfDKEbNp/l2UZJ6raiptAgIiS3svNFz9bI34FdIBA9/UCr/SE0obwszb81kWIdup8sVaEERfGVo/QgLifA+FfLYdp/n+7aA4spN/InqmACpBvxwkT2FdBfeV1ZURy+nuyOYaChZewEfhhQvZ0t32BWUgVc8kfkXaAbZ2o3S0qnGf4f4lq+i6c4sGg/YCvjvLEWBDmVbN82nZzRtL8VLTvhuWE864J9rFALXQLfsJa9BbtyumRWICGnFvc9ijkZvF/ImvrL4fjV6EXgViOWsS/D4BVmHwAd7lGFf18tPmG4YT1rh320UBEdP99glqKFnvKoJFkgPacFt2/KWxn93+QauUuY+KDoO2A/I6ixT8Rq1b2fFt2O0U7+/GyV4Z1hZ2wTvjCQjl1jX2/WAoUIMhMkKKAw57d34QsK2n+f8lo4ys031CekICqkNLI1RRaWbh92HTrQUX3wq8hhbqG/LOc/HRG73aYfGRVbw/swwqONIEJorfkOTEBbOB/rWXXJgPa3porgIiT/s15GmtdsX5LcrI8N/EQq4iD4ogwuQcDx0s0eel6SlCzCPq9EYtXgvSmsuvEN7dvWn8HYa8f6NJnlgOA05dA1Rsip2KVf3FuazUc6Q+l24E2jGTAjAuKUrZ7MHg+SdX/e7axh2KEwK3Y9Pk/+3MQfpNaVxYIyjuRe4DXnbPemiu9aP5/9GjzKwzfEJ6CgBSRyckbFm9aCX4HdAZA2vS2rVqEwYewtikAlUlceI97A1LECqC/yosMgu2lb+rBNj5vbn9zYSggN9N/lgOA6ZeJ1Y0iDGOkf/dtbDTg5xKkmYH2jArClg02VEx8THcHR/78DLSnhkmFcbB3+DlDmHVKfYNX+RHpxe6O/oAqocPjnTDSa+B/gGVDJiLZHZoZgIqUBNDsHFRfGX+ycFg5KO3Qp4SC0oq3vbIIhlAVe+Z4w0pyAZq3FIgphEatefTdPwh0AH4jWnwVBcmNkKGADJ+/4NAtN2r3fyVnyCiU26CbNoBQk/zN3Rr3Xdt+jnHnOs3u9ajRgkWKm7x+B6dPzHo0eXNLNAInuEiICoT5rCv0rT/6cwF+GVpXFc7IZJCrgGGfU+F0LqZq8n+TZsonfdremiSAEJRez2ocGV8Uf69wKjnI7GinX4Iyi6m++gmoUYZ7SnggSUP/qrU3h+GEg6+N96xCcnVPfWRXihFIxXqOJ4EwooPlgzIPbb1/uWNAI+XV7ZcCgOWWN9SMIZ1inn/xbQ40IedLo2CByI36wyIQZVYKfe11qEOg+EqwIYXyhhO1o/6ySCV4mnvNUQsKnL4ei2+Cvqdh7dY5HHHzfkdeEBvuzSWTP4AqnKzcISomaP5/62hiK/Ld/ZxUgHySzczjGX1dzX6ccb86V+5nqJqCzYoBvmsJYVF7e0Z47EjQ/iK174YshX+wA/kXRC1233y4VRYP68ItjZqBdKTu6OI1C29qf/lg6B580SaVE4ADmm7ZBidHZvF/k2oILpHgqJ6IgEaRvMrHFxVchn5vckE86u98qeKCTooHvWQIq1BFe4J4ZklI/2y1A4cihXuwGvlDREx2x3xRVXAOP8LKjMOBOqUh6hU3wW9Cf+FfLh27zw+UKYBfm6vbWSnMZ/1/AmlRK6jdqJxHgP6S5s1HG5peC3+hcK440+topgmCIoz5wBENWFSAfLh2IUUH+iGxVoXRhge16v40SXh4Q3uLUBYIpLwRiguDK6r+8Fw9EXNGftRa1RXFyBuQyoB6oHfj/zBtbMh/6WMcI1XVUpcCgASYeNZHJK1k2X++a8kvKeKRn6SA05AjymAX+FuKfklyvzsZ77OonILtipS+cQpyUu57iXfjRv77lLLVhVOG4LOf/T9IHniAeyJRtQgPvTWK/4IaqgrxhT01czJ+a1ofFQDIoo/rgFGh0uRmMkxtq3+yYiAhRNP/lQuAjZkQ2QQngWb2f/FpnSy73jGdUYDUktzNgBvwXiJ/I3CCN0bqGqWugSmNSsP2D7ZWQn1Idb1ByPWerQ6EiohpuYIE8E1nemJ5QEsnAaC2XYfzhEewPvm5RKd2eHwAVEsMBcCIi1yC7Kc/7iw7GHKRfvVbIReyyXiQvYBfoJjjYzHObLl/GWOVIZHTFpYLgKSZW9l1J99m+n9qaZcriN1PnDiAvJOWz3kdY2Bif+puHDWE5wqjN4GljlXGhBNtWQB+mXMXPm/xNKr4gl2Kob2nCRRS43t8d4FGOfu4sWyF3YaCtfT/akoceZp6VE7SBIO5g4gfhPytefaEQrl1+XyMVSwOgcEsjByCE6dD7XI6zXGjfidcOxehyViQyYDHoFzkRzJnbaF/JGL2H9TR9ZQdgBib0NsQKpZo/n+FZ1MoC9r1mQ2ABJak090ha2PEf0xsSzA34kifjYCIkd/Luhn0XQB/fnDbN07q36SSgaCNhcSzEUBYvX0fdP4+Q/KtqhCDRYqavdEJXFIHfDV3skUP+qSw+4Ryhx63HgJUTOp5x3n2S6YBubZHhyCFE7Gj+jZGcnfbe8lRBQnfvOqJSIN3q2PzC0CpdHp9LVckEAzD1ozhgUqmZezeOZtxqn4kXP8WN8kDkOSAiaGu5bczUm52f7Bgkh1Xz2WTSIAwnUDfoC3ZauR/1mTaI2PV8pYFgD2ZH9mgJzpn/X+XaNUpVtuhmhSArJVK070hfWPKf/prgi8o4WmeaoB3ksXN/RusX1J/Am/hNNXmQqICgZqPjchlFs1bnX61cfE5V+wkptGBEI2kw/kQ6le0fRh0tD6r8Qiq0oLTigi/vgsHVJ18L3YqQ8325639g9+IuLq2Bi1QYXsCeFVHuvu7sUqFLYextuMBYEwFepR5N0twAH+1soa5hfKySf2mSJF47HrTTu8ELrkxiH2Eea/o+ARFCncOfCpSMwnDvL6Jc4NDrMD0fkF3dQB9P1U+DTrAVouXgk6p1PAXPtxzx30WWAwRj8PyjOSBlqYi7dQ6P3JnfrBaoBTAxo6OVYEYpK3ptjelcOZ+EV34F8nJJpDmgNOhc+bCNBJvR387XxQbqcy0kZKAw5904/gxim2PfzJh9h1czzWTVYDlnbDgXC8QbMJ/92KcIOHRppQrgDecJt7uLKlq43+OZAkjN9QElhKAt5rW27EqVmn2f/llPSVb1kuXBYBhmb/ZpigbaP5/Omc4J03YeZgCgDWY4NfNJvpm/X9TaPsoDNqMmQaAL5c51igl9WX2f0dphiqX24OaDoBNlsjUtyMOZex/FmrbK+7cWpsagI+Vj9N7Ikdk4H/DavosD94RnCaA85SL0nUhoGPUf09r4y363qacMoB3lLzRpCAcY8l/u2uXLq/fGZ08gBuUItEKILpiwH8HbBcvLuBpnUSA3pO90KcffGK6fzZsYS934JWdSIC/k43QeR9iYrh/RWx4L4ngnp1IgL6TkdCDH2xiuX83bFovZOCCnUWA25PJ0MMfmWK+fwtsCC8J4EKdPoAXlDXROSDrYsZ/wGuBLnff35w1gHGU1tHmIF9j0X9Wa8UtsN5ZnCmA65St0skh9mPdf8xq1Cyy3bKbHYCFlbjT4SKvZOl/IWquK37c6ZoRgEGW+tQvJIdl9H9TaVEqFtsBmgeAIZdy1rIlf2b8f2Jovih52fuYAoAlmCHYaSeTZ/5/S2fzJqjX2JcDgE+ZB9pTKcNo+X8NZvAkpdWclg2Aopon3HArC2rqf6RktCJv00mVI4AgnH/evi1pa8x/EGM/IAnR4JNIgMudEeE7MNtsnn9NYZAddM5mkoCApp/e4+gyXW5cf1pfphqyy92QzoCzoeXmwDXsbwJ/Ml2BF8TISY82gfajKOrDOINxi37VWiEUrcWvjbyBcKam7e47H3P0fT5YhRBvwhKMZoIkqV/xPj+7dDd9a1WuDA2/eIo2gxasVPWwQlN2UXxZUpsIjLvliDSESK+E+UBG4Hc7ewVPTgTut1+HYoW+su7960leefJ5bkvJ/ze064XIhni2kAKsTcV6b3iQRwr7bbCRhGmIerpqB35REXyudmlDFPaVrFaDTIrGvnoMW1U6fah09z7r8LOoQYJ1jF7DvBE/WTl+WnI5OpDrz6RageuOQ8guFyJdBn+8by01CObwoKiAspF2zcwc/GCbf8ps0y9W4BudM4DQlPfSkiLIZO9/f2krKn7aW5kCgEmYx9h5KHto+n/WZTQkiNS2lR+AI5zk3n0uD2yzf8th8R14zjeSkYBgoE7llzR4bxR/Wl1iF1bI5o5ggQalAey/Oq5yEn5/WIsQK8LOi5aCF6r68uxApXWnfDdTbwn+u/qIOYSXrzf6FkdUeMl6gE0UAtm1dIZThoW1rwEyTa96cnhaR4D6ya9HhOqI5LtfCTVTqnyZdcNAt/LWqYCCBoyzwj4RE1k6fjlyvDnE6hCkKoGtj/DJQxnAXlJ/Sm5IMq/igZ5SgOWTmtFlISxk6H/HaWoqg9o5mQKAs5is2ZcpTGnvf61kJiJN0keURoAaniDizjEObl1/+F6DGRnKuI8qgR6k8Or7OWRyJX6lWIgQ98Gei7iCv6oT9A5CPnY+fLVRQAf3uQmI+oT+sX39+EmLeZ55KUq3/SmyCIX6h9e5IwelUTt8PnYDQvjzoaqtgr2LSML3EARZPn4Vckk5E+pxowaBTJBJy+ga/1+Efx9tAjAa4K6cJICqldPU5CSEZv5/WGc4JiDWbpYWgNub297XLntsnX++YPYbOczGkOqA3qJT6aw4z3FUflJZSxF8wsuLq4Kyqi30S0Jqdhd8F1FIBgK5lYdmhVKzVP+aSzZ63HgUSAL75K84hCOJt7y1CoBUHn2cdFA+jO89p8qB6I3WxjgW4VwOf1Fv2TMC5CqfXoC5k6HRwiGgZPF/+Wi9KH/YxpcHgJiaCN04LaFrt3+UYREdH80vkdaAgqL16Hk4x3FQfidZ6RAEwoKL2IJwq1H1ZkP1drB7uk9hBE+32oYZhli1/QHbTQ97zHdaRZf3I61Tg6GKLcDeDrVX/X2fchY6quqkowaBdJDay88bzmCkfydsBS6/3fmaCoCRl0nYqigCafB/ZWRAIf3QRZNzgPWfXeVHNS1wzX5iW+UTjsStjFKClKn18nxBKXYvfCpRGAafuFSHs4VgtOwAG03Wegl40EUC+FutXIOeikPAGA/3VxJ+WHJrOczp8qLigBSRIs1MHeJhw38daxssp9uSmQKAEpnb2lUrrGrOf19iAh7GzWmR0ICOokjpADkpciF+K1hMD1/Aoopeg3WtPPgWRi94r3qXTCgAqbNohbeHrrmCB11SlXxwdcA/zPDep96B3Y0ax+UWnV05f2RuyTFy4TadKIDNlZDVKCafZ/x/lGXgIlbS6ZNfgHmf4eQLNSpwxn4RWzYTvMMtjJiCzKrU9ExDDHeHe/VOBwPmtTKG3oanty0FpVAVfDl2ZEGV8hqpJoI1jeLFqBXUXBt/3G6LMiTimp0ugJWVS9X9JZRn+399ZaEiANKpk2uA7J+n5d01pnCdfjNa5RF4woaL74IfrLL2+ETMd/B6Ik2fAN2zaoXHhwS6Hwj/UtJ87nR3Ph/vf6aGgfGOZ8mdGaBfiX+fbGsuuN2umgWAYJgJ2tUqjmrNfxdiRR3HzLWQBYH4o6DraDt/c4V9eFVTC6m83IiYhJGx1/35SjF6pXjzRu/4vK1gg8OK9MBQECpZan4xccQ2eeZeoHWAfZPc0akin2X9fzlnNyVX1OiURICrnvfjeDQBcMd+31qlEvfCrovmgiKs6PZQRQJ4tnpYTHL/w7L5hGWIqbtDCsRUW33Lc+Y7CewppAmBuZDyzJodamLWfxVq3Cnh2I+XDoDIm6PfdDDfbUl/uF2eFnTGV40ogmOpU/NWQsZ2n3vuTpsCPrXVhWOHSrmIB8NS0HzUdAA+Uu65pVOBuY8my8UbQmG9f/tqTytD2luYB4ALm5Legi9jbV9/PV5IF/zGkI0UgiSpE/MyQr92nnvbTm0CBrW6hYmHurkkCEpT/Hx4dCs9S+3tpCiBWpBpzDQdQ2LVfwZqmSl12DSXFIBhnLzgqTGfbhp/eVynFIjEUoyjgmGrKfbmRO13tXoeTOf+IbKvhN6I/rwVDFFWz32pcls59+jYoaCAspLG0N4hVGX8fxlnsCSB0zyUYIDtny7m1jZocUh+RliyDjK/z4kNhECwmfxQShR6oniORgn4uaz8gqiLP8NVE6Bb+H4ab2wyaOG6nBiAEJde2KopJ2rPf+RhdxyOy86PV4H/pf3u2D5WdXV8VVFdBTu3e4bNhhG4YgYgUrN853TjPd7tLKUsgWmQvczIHcpi4X9KaSUoxtYQliyA9J1g4100MHCnfuhZzhDpwIWKpYMQrzj7T0nAefB4NEeq+BatD4OVizjDcxPQWwV/0m7DMZHgFpwOgNKXxNkwKyFrsn+MYE4aaMmejsCBBKjt8YlBmnaee41OqAEXtEiFM4iru9QKm1WvfdJyajm76HuhjIBKkxzSiSOPZv5/hWXfIX3QX5K5gLSiiOoSO6VzTn0eVMwI6bl2h+6F8bUDBHVQP3yZdTY/Ku/ypUuBFpBTzIwdxmLjfw9pjyf+1XyVPoDongTlFjYwcUx+FlgTDlm+TIl+hOOxCf+TTP56aHdGQ8vzRakDgvyNVMhPGQBgpn9ga20r0Nm7lxGAdJxY4bUycW/UfppagBFHwZSKrYNhr+j7GUogem94tEWY9k+rg4LSjAnG3BZgXnR/nGyGLeTb95gFgDibfd8AMY1uDX/EWxQTnsIsi1mDWK6h+hpJx3nMeI9Gjff8q66CfYxpxTsW/F1nf9ls4i0z3B6ZBIAkm2zfADGVbgl/olvUElfCBItzg7yuM/ugSf15i3jeRar2RKt6gvWMbsZrF9lehn8abIMsvNoumA2ANZwn4bMyiG/HfjNavxBzwCGKAISSsJ/9pUu9eqN3nEPu8y+p8oFGjh/JbBrqYMJ/VGpjKYTXNJYwgHueseQTNlVxMn5mV9IM/7yZiBeF6rPkARlP6nv7dbk/Xu/SpTeBjJCKzTUfF2T3f2dndySW0lGTloAVohPqDTvUcx99HlMIBxG4l4bmht64AgjeU1V9Y3MdOgHpUqF7gPWTw9O4JTNo7X8oY7AdCsy2j3mBLKdV8YRBznZSezRNY//RsVqEqomUv/IPxVm5fp9vqzLm4OebCIC9mODb2y3/bFh/XF0AFQPErYsog/WtffpJSfR5e3h4ReT1d6o3grKNMcijGYtgvX9iakMpK9felTyALZ/25XY3JHLYfcFVXQq2upOHA4astoUFGVLgfDx0ujug6lKimoBak9vS9CTWZ/F/VmPOHf/LnI+IgZKnDvJJQjN3/HoUTND9crDfg3mKiMFYEplbFX8pbs4vvd3MmQKABJuu36wxLm/SfiJaQhCsv6GJb4Q7siAA+E2je0R2FEBw76KlIoEEkbnOxyBNZf5/02WaIYDPbpEHgRSlse50PwF2zXtxTqsAn7KMhH2Jar8IEAda0H4sb5Mxe9/VmgKAHJpY3n4wmW72ftBaGxFTwOCJS4Tjsc3/zE2be0V2/z8972qlFIFGkU3PeyHPZf5/MGV9IFfOv5A5gTGmW/D/QLl2R3vFTHf+yrDug3eKs8G+EgdcLX+hbaYuVtzNmAqAUZzq4fszgnBkft9X6wycvD6IiYWdtYoEl1HNfD90eTsH6rKhfYAulJzUCydIadR/VGFvGpLItY1JggyrE/fPRiZ5MXnqRjL3IKtNgq6NichtGlhh1X84aeUmatQJlISA96F96vM7gXSkfPpQqAPRtDmFq4i4vVMO+likfqVvOjLt3/SaAoBLmuHePjEgb8l+tFlMD4i+AIn7hCe04gJsUH18v3RqPO/qOKKLgO2TTdTfJkJp038pYQkaEshljXOCy6s4+OFHm3mseHdFUfWeqemBvo7GyvwcHmPyf3Jn0yNG0TKS5YCVpGPuiT8ydpJ7ak36/vaw6YOdiknCshPlXFh/qmylLAHaNZckgG6ecOWIN3Nymn1TVNgHGLhbhmeHzboXC8FWMX7vcII0KOJEnAiAP5lk3f0vi27rfkNa5A/ivhSJ+YRHtDsD1lCofF90cDup6TihZoDvlDzW/yifaql/T18YFznF7oswg6iuKPxDS+J6GHd4QXTw8KUdgWOR9c+iItJm93+MY3MdB8vHju+B4Knh9SBGAXk2eaZGgPZTqgmCg46JyvQcP2P1fw5n9yI70IGRF4HdpWvwgUEjd9R6B0vG+0quEIM5jO7F/Rf+X71/6WmpJ8bUBJSPgJCixet2PV91CXymTkIAwrEYhG6KHcLGEyNdZ38vbIwroNg8lkCA6Z/t5ww6zHPqfJBR8wOutAyFEYkNv1MQvloIf/Ftpi7B2xaYGIDcneHkTDd6cod9zlPZBgK33IUSiLe8pw3bWLB+PG/9MCTeiJkHgF2coOI+NXZx8H1rVfIItrh6hmSHE7vFC4NXa34ZcJUyxd+GmgKAZJsm4eUzynAufmtWQQrFud6GAIcduqwKvVZBfpFwcDOi4AubAoDrmnLgRTN8cEd+1FbECiu6AofghtK5XgqLVjh+p3CRM7rgFJsCgPCag+BfM49wP36oVn0K5rnkhgGHMrraCu5WUH5ccPcyDeCgmgKAcpta4TM0AnEUfuVVawn4uIaGZ4c9uyEM5leGfq5vojGc3rKZB4B0nPbiwDXRccN9iFSOB2O37IUViPa8Mg5tWdV+lm6PL2ncUZgXgPydW+UAOPRyQX2MUuYELbUghRaJZL8LEX1bMn8MbbksdtmElj6AFKCL6PE6YXSEfOhPcQFesi6EdYqLwqsUCl6PfwRrHSnJ1VmUi4DFoofsiT4Jdn17lEwy/QCvJ4NCjHTGDhkJYdp/b2i1JGjR35ERgR+mUfG+Qtl3F3qDSCj4IKsggo+OKMswHmhk/n87ZXsfXcwsj+aBL6rs9oRHvHk9eKlDVvLQpjCBcpGv0AckEWjhf1ZhbBmzxlWMI4MGr1f9yUyWe9Z1+j3D6yaic4ABlRHXiirsa2V/q1yEEnzAeonmhLW0jgR4Ukl9x3JqN3fkPJ0MgFWZVN6qMdtva34mV8QKzLm6hk6HTLuNDHZYsX7ybu8vf9wwmByAiJ5+5lI5unPPfLFQLQK9sjuEfYrZwkcVpF6mfzpqgCfu0yeTzICzpIzvakFhd2p6OUnL+G+rKIKVjmnLrh7cZP5/f2QaHtvKTI5Ggu+rfPnRSaN6FneuQKfuCKSwgLmTA9WpKPJqi3+mXb4TZ8HOibeET7RABGFSTX2qcgQ32uO3nAaADJqp3xozsnAafpRVdQi4t+SFS4jmvccP6loof/9sNCx/2LGVYICsoVfr2j3kdXl7NExR/ACuyoIvjb3I9Bs0Y/p/8WVBIMDMMo/0gbSq/ve2SEl6eHd3QWrvd6S9gIyT1tSfKABrhX9hXTUTzsB9ifuEOLWEBXRTnH3mcVc16eFhmwKAiZso4pU1BnKNfTVTKQXntN2EqolAwcQTzV2Uf5hq2icC1AuT24BBpZ/wl0L4d9R5X0dE9lWpoIEzkMzOiCJvZ+d/a2ETGfbFyIuLg8qwFABWT398JXTeObfmbp4XgL6Yy92NMQJwTH5HViYJFrjzhVCIKL5TEHlbRX9QbMAqzNaRlJGAaaMZ7n5AInd/eiFJSfjCqu2BYI9QzRMhmmbyfzFiJhrZxiiMXINBsIH/9k5pfEJ0BDrH5meeFYDjmCLe+DFHcDB+tVVICEm3ooW8iEO/sxGCXG5/ZmsNKf/UfZPIgPOkZfCSQgh4tXnfRnb1l6hwgeeQUNBNJKFozH/NX3QWacOGilqEkbPIA15SY31Dcss1F+JNmwKA/5sw49I2x3ImfXNRjgKPsgaED4uixN0XyGDgf7FnsCKxzgGQvYEPqor3rkhlei93bkDR7Q+jgIAXle3XGSwybQ5/8VnqDd67TIf1hgC75ww5We5+sm36LMvYk5VugISiFO3VP/R2kHoYSfn3U6rIgemPl86sIr1n3X+YYHkXLsTOijaERLOSA1VSan0icmI1fuHTmgSAsZxu5B44enPEfPJPdQDFsHGDI4wXx7sax2L5f6ZlOR9AyymOeIJArfL7Zkyze091ADym6G6fIoBZmJHdvDFQcB9+KlU4ByS2I4V/iVTBYhSWXrR/V2k1JerQE5FvgcuoDfaiRxZ6enfwQCzuJ6N+gESVctjSLLZt5n7nWD8MQ7qbhr+HMb2yD2FbT3/ba3opDtVQk92AvaXk8S9Ez3jaeEtEA/LQpeCAR5ME1Xgp3mtNf01big8DvaiHtoaYurUMSln6flltFCyb17uUl4D5o3XvJkIFeJR5JkYl9E6nIIFCkjzTuifnanh/dFweEVK+KohFhni5bgtpWNR+6m0NLYjYO5WDgG2jvO6UQc93wHmNRpD0kKcqgSOSEtOfJ+BqeH9nXPwQJ74SiF6GyrnfC8dY536YbWgs0tfJlJiAE6S573xCMnhheYNFQ/OUpvuA6JKH1CcpymtMfyZbJA+DvGWHBYePuwcOXlouf1xsIip61WuT3oDypW7y2UQleW14AENA8GSkoYCglKDXTCyVbeR+pFiTC3G5NIZOiNO+5BEgXZJ/Imo0JonROZFxgR2p3PabSIt6x3b1PovrGKE+gGSXZtwDMSVwG37IVEcGBrWlhFyKq8NwF+5g6X/IZpEgEcxYjn2Cs60G/adNNnxDdEo5LeXUnAOAX5vo4jY3SHO+fG9PP/9kr+2CZI0vyp0emmX3fx9iLBkrxQKLPoTas+oE01Pnfadw5TE23dCXNYDFoDLrxD6/doZ6b0h/9ryoWIGmkXzSVifkam9/7Vv7DwK9gIcBh767gg7mWkp/rGurKMXTVZIqgdKnS/V7RzR6IXebPxXsU6FAgG6Xqtx0MXhw9H31U/sE0LMzhCCLi8W2GY9i+38CZYYdB8nCjEeDxbAuARRRPH0vcss0IeCDmRWAD5/J6L887HUYe/lJOvjnqY+B/pBm0V0maGqAf1ZcbRBEvY6H/4bZu8cOMFtZf0tr3yfZ0sGRV4HaqNj24ki9emR2wT3Y6befHoADmWffMjTucVR9WlFtAd+wR4PPjD/J4h1RZfh/DWLJGJHEnoqRhBi1vQZpVVB+W28mLxfazJV6gJGjjO/OQoN453jMQ7LwXKSUgC+VEdktLtpud34ZVp0Hw7XGhFeKAMQ6GLth9X+FZR8eYsnVjEqD/bCwAaRRbn2mcYMzjt5qmCyAlKBG6yc/DHcueidHl/QUp/2ANZOp1eMqGm3wfnxYygpQuJ+FNol+wX8V+F/ffwtnfyCJy9mN0IJUr6b/H1AKfXdyFDUj4FWZG4Con/vpFT6fdn56+Ed99aynFYHdkh7VayribPt+qlj1CmK4oIU+iaHBuxUuYON/wWb0H/LKhY37ggWwnQDwUEd96nHmM87eeJgtgLugqeujP0936nlIRmPzGabPgByUbNfJLDpunX6nViAI+7XHhG2KasTtGFli+3+iZHocpMfmi9uDGrOYBAxUEH7tb+4vltrnlX2A46NU8MBD/XhQeARCTe54olOAF5ef3Owx+XCofVFSRgI4sUmD+IzzyQkfSWbpf3xgBRa8wTiJsoW9uJMLQFkafz1sESmT0+eRXoFbqQX4P0pVe1x1/TpJ5g+dAoAdnNPkrDnEdLZ7Z0tq+V2qkYFBkWvS8iehazp/+FmCDHa57oX1iDHBfxUzYOZ/bWYpH/fJ7YxWg36xwQLJUsx9jHD2MHrbU5ZxgJ+jIfC9Qwt5MXiPQZjt3KFBgNKXA95qM9BxQ32kUOz/O6+0gkaOxMwzIlJou3/vXRISHb6phx2HuLx2ENVcnn85aa8jKM71jmuCKK6T/qJPAX1Ycm40BN9imDSAUqHk7AdBA3gueQFEVvCvo3CAaJa+21cxz3CrfSZSxQGZsA2Dko1xy+YgmGfMf6ReABPWvuuH6IZDvAcQmlyZf01ptyMYzuGOeIJxrgz/FVAlff5xoDMR3sCXRoAwokLuTUKOeKB4fEJ27lGiSYCql/PdizP3cSZ9D1D5/liub4L/jmHOFSSPaY5/LFxTD5W7noZEiMq/NBSIX99/qmZBH8fJtIyGg2GyLAQYVCh+a2+ELqvYh5TIgFSmQvR6R4J6W3bkPADo6p0EgMibs+TrOQt1bnsxSoX3q6gtgdiSuNWmK+ltn34/Vv0GlLQshJqLhsfpHERl83/sYC4Wb8HoiBqGS7rvDUpbdX8dauIkA88+j12CMK7x/ixQN329cekyGt0Ll2CAVaMj8BpEUnm/dxdAfesmoBqA1Zm44Ug34HMdfEZM+fljqn6BxJHd0+gpA23YfldXWQiWtXaEMYu8xiwc4GT2fy5hcxaRweuIIYZ4ukMOm1uCf7lpGiQmzr+OmIIxr1sAXlGNfelwKTEp29WVkYD/pKHyUEYrerR2ez1s6AmeBID3mzrlnTp0dRZ79UjH9Tmn5IAolEvYay6EbxJ+fVMQA0CxIYOdjfXL5CF3aK1//lwkEPm7poZciFXALhVtYO9/aWXhHEDHXYtlhIO1bQiFV+d+sWwnKfDSK5G2gZSrxfviTaR80HLaNObe+JdIgJiiVO+iQzp5wnfkPwHrpp8RgJyaOOPnOL10h3suSiD3GagGgamTi9fQLURvIn6pUyYDNbEWg8SNZcx9Iudom39GXPgO27oxhvCI2sEKF79h+3/8Y30a8MRDiiyF+7eSC+ZZTn/Dap0lWM85j3OC164wAHRRoH2XcEYw+dn9lL+Aeab79INIAnt3dWY6ueR6mwmA6Z4J6is/hHdjee1Dge+YokWALZhs34Y1OHNhfNFMOvpDqmeBSZI31agrMW51fgdVzgRksmODPo13y6ohgWimf4hcLg/muimGCok6wp4XO2L+f1BjSBm1w6qJqoWKuZgNcluHf1ppDCO7zNaNGoNvsasDOlRMfqZubizo1Z6SU4Hxqeb5pUxbfDZzYzUo3/CXToASo1bwxES/eQt34j1r6LydAoDXnArnqTyIdil640Wi8fOjZYA/lw3eZDTBcpV8YE2/+oSqbYFMkmfVBCx6bld+VlS0A2CxD4P7jSPNmCPAaXR/wVp4DHi4P4VIikXFLRuhZPV/oWAAFb+/84cxh9S9zhIqX+J/9GVDHSfHHYuwhNS2iAppWUV/vWo7JaTOso6/gkewZQJrUyd+/W7gLCrWp5JYgS+qbfo6TZJ8t3ItNK7d8JZ0gIykp/LjRpB673UfOyflgpsLgF+fG+txQCp4qni0QYvsU6AVgKaazuPtOWt17HroR9PzV6WMgF6WxtxhM1xyvHy7Tfj6haplgYWSBtbWLAZvH34tU/MB06+aghmPkM9UJnNrG38+WL8IOrUhhBSMacnhH6xnuH/vXFgPr7r0hXKJkMOFGblj+39DYbkVLMAJiDCHBr5FE6Nf6387Zd8bqsVZikeFzLgmDXBbkH/baMkhIsvdjLSD4rMtBylX8H4lbHMnjtCNj3CCRq9dAdVSEX4db94s6dVhknWB9qq7+3hO+3zGcQcyLdtUlcCA86ZI9htKs3sldO42V+BfmEqAOKMH8cFFP3o+dpU7YuV8mw2AxJ/563BBp3gUePs/TOqlngSAlJwg5y0973ateSFEEe/VoSqAppl94vw4HnUMewlIrvMHpXuA9pYR3uE0OHM3fLNLI/g2qPCAgZTb2d8wQnEwfSFPbPxdq4SBRJLb1fksQW/8fVZShwB6rjSCPJAS0jIpOm2gflJVdgSIsfuCZo5/zowlMWsgfxlYNgiEtNWDvowgywkiKWl+f6xaxwtrt7yEQov2x6weJmfAfw1dKA86uq+F7on/xHUbLWXpfz9fWRLuvKiGv4g6wmcYP2P8f0RhWhWGv6WHsoemv4IVYGH9fx1jLBj/waOIxIZCvccSkl/uf85kzhpXxJ6J84UMuzcQ2F3Tf1dmQB2NxpSKPIUEudINNFyuf7xngx+gyIKLnYQnt5oLqFqBf/5omCGOymaMEoR1tY8JNllQfx5qfiNWzD2NnIPus7AH31cdfx9rNiX2zQeONoOOsv8FpVbofgJswSZwz8GO4IJWsXsEilW1fslsICjA0GqPl4JFsCQDjVSEfnRtUSno0f+PW4Jar/sBsVNXfgVuVyrm0oGQKoKTrgAB9lIwfn1uMSu60++QA4LxrTIAXVIPft1u3ytj1EaR5oFyrZP/5lH0fSVvYyzi1IiR0YEXrSD/klHhfVZvuyw21bKRxIHerNv+YFHXfXBv6Sxf1caRvoHJrMT+UlHUfXRv7Cxd1cKRwIHWrNr+Z1HafWJvxCww1aeRyoEGrR7/oFHofTlvcSzZ1HaR24FYrY//+1H+fflu9CtW1C2R9IHOrS4AeVIcfqJuSyup08+QF4JorvoAGVNAfjJudyrR0luQQ4Ilr/UB2lNqfqptdynP0dOPeoIIsB0DvVSYfgltSyik0DePvIIQsXIEwFXKfkxs8yZQz4mODIM+svUF4Vb+fnNrbiXTzcqNaoOUs6YHIVgzf31qvCMvzPyM2YMRtYMJfVllf2hp3CFkyiCMWYS5to4L9VqVfzNozR9zyDmL74SKuMUNhly+f9tmkR1dxkiKmoWIuigQLl7ff15lJRskxFCJX4azvLcS7F/2f7xjiRjIwVSIP4cLv3EVvmH+f/FhvhVNv1eHPYiTwVUYoGP3f/xfwxKyvFqGXIlMxGIbkGXbf9tdmQ/8uWOFnoo3x5gejGeof4tbPgwrt3OEB4xUyvUhkGlafwpZswhCtI+Dmo2mzXYlmGvuflZW+gREsbuCWo8s0RspoW1gfm1TEQE1rvuBS5Ho1OIsqG+rfUxQ/PwXq1OBbpPa2Mcwp3HMfPNMufjup8iAyJUD3ck0mnO/e15JSvS/pF6AXJhi4eQ4fHV/eo1Fsu+NoRqALZv45RQ9SXcIeX1B8upengKAPp7D6ldB+3hWdy49DuY2mxqAkqHE76dFjHpkdZ84B+EamGiAK6X59ABK93suc84z4dsRlfGADKlg+l5ONn2wcLwuoNYgkruBOK33/7pSQn7mbWkpSNFPj8yCsLG7BRBXFX/MatYj3sujjCiEdrarC1dbqH9fZwIeZ8YjitaFirvBEYpf9X+aY/EX6sDYh9mH7sD5F6Fj9H98X6URbLvIhTmKosZPHpVnoH8BWx8L9bX8g/iMpsy9JF1r8X4nVmUEjLB7gh2Q99I8K/Ju4X3uUHv9OqtOgauTlNnGMUlyaXxTS2T2B6Z9gKaXe+BSOFp1g3pXRSjv/aAQgBCcqefZPht4KXj6PsznJZwPgO2gGO9QRYN6VXU+OFrgipeDgD+mw/avS4h8BHIlMdnYNpNygQaspf7qUR9+L26yKVLRNY/lgkKytQb2V0B/1GnqIdHJkovihPO47A7HXeB/8GTSGWDCWYhwhxfAQBdRY/Z/gV9wEQy7lYWViqrHpx+HaHh/hVnOCOKzUoNVjqjPFChbbV9+/1L0/+6snYG1kgvYfDC/caJ87kvs9kGmf4C2l83gzzindTl6VkTD7eifBYBcneTpAEEDeR93OzyF5PSZOYCmo0bz/kjGe09zpDNB23SUJYGTquj8uVDjfcRumSoI0nqP0YIfsrsGH1hLf3xpIiHpyBSLRoVHurIQHV/zf3ZjTBf4v1SHiYgEw7sao2XPf7NcIw1Ht0mEoIxNzMUkm2vUfjZVtwLrrgSCj5EY1rwu9HD5fARNGvj5ppOAVpdX4Io4mnU1eiREXe2GnwOA9Z386hpCe3mEdqA6leKpmGKAaKX19VRLhHzgcYQw2dd4krqBq60uASBUpH5IbN8lQc0IjRWEtbaTDGZcy3+8ZcAa6MJwiHmHfMALGAtk639BXj4P5rjDhOyL8Mp9I/dq9n7bVW0DWa8WgnCRA9bMLg9x5HyWTGj3XaZ7gAKYn+HcOT12qnl9QknrD54DgKGfre2ORGd6RXWhNy7fi5a7gEKoFfrBTnh9s28VLDfT74+vgt2xtwZVWFt/9WjxH4XHVorohWC8dhMrYf5/EmFPEzu82oVqirnHMCAgaVN/EVhNBn6xlII3kNHTwCwVcEx9Ak4N+XOnnIBLl43g/zjrdeF59kKz6z2eA4Cfn83txkSFeg51Bjdm3gOW2oAmqW/77E/IfdRuSypQ0eaOLYPQs0oJSFqcfzhn5xycxAqJBIeFvzgXsGPtf0Re/g53uIyEYYwqzAol/WusfglUuAAOrYuBQZOe2ZAyCHPMe51IRPKQoh6AnJu755s/rHhJdxs8z+MqmVmAY6VV9vdLyXwicaUujtUIkUyCgLA9BXJXQX9eaWQgtcdRiv+F17xBFNph/X8LYIMRfbouhXSLRsopI/1q6H4+VTYCHK6+gaiSpNi6Ma9y+HsSSbTyyqIggI2bwee6P8J4JnesOzfjvZhqgBCmZ/frTBJ9dnA1Lf7TKJCqghWyXAcRWX1/8mfhHUrFPYnqhna/YRfwY+h/rl3nDV23JYQpjQfOMydPbUB+x1GH/XmqB4FclZTdizb5dHx6Y0QD7eCeAoBwn9/tIUW9epl0sTWl3M+UKoFIq6f+rlJyfqJs6CW5zIKMjYS7uKEP6172f6liSRWKvS2GLYqZx4Igk2kwf85WHARpr/6BApKm1/YwaHIRfDpJrvKgohuA95ue6KxAL3mWdiI6U+F6l6CA7Kcz+k5Pt33HbsYpYtA7jpuDtLURDItc13+6ZG8YNsAhhxKJF8XgHRNocn+SWG4GJ7FjgvuQ0NVBL51xdnx+SiH0j6MqgD6bkefVP+d44Ha9OuThwpeWgLanAfo6T7d9u26YKR7QDo65gy22vQwTXeJ/IWRjFzW/uYaUiWLGYR8GaUZ/PFeABJCv/oEbkgPYfzHActN7RkhW8ZOhDYAvnbbqqUL4eYp1iTdU3p2VA4GgqhH+dFJyfntsWyXuywOM8YQuuqQRdWD+f8pgIhKXuhKF04uJy/kkSWx/fq1ST/7FqgiBkpVR3pU3l3XpeWtCWOrknBGABaIX8v1IEnxDcl8wvtZckUmC7bBiBrZYfH+rZ/IcA8SIiLiH+sGyGk5mq39SWpsIqrK2gk+QyNR9Lltxh3yBSt/zMqMggOib4ug5QYF5D3aTOEjfEZbvgEiqx/1eUnV+W2z4JGbLsoszhRu75xJnYf1/ml8uEM24coTkjPvNryfdbfl9FFDG+gmomYDgl2rihTtTd2B4KT5W5aOZWYDtpd33z01wfUdvTSp+0BSOy4OztrgN/F3xf9piDBXfvMaF64rFyVojg2usfmNT//4Yqw6Bm5Wf3hg46XWUeUlBzOi/myWAnKOn9EpLyny5cAotI9NdjyyDlLQ0C05c2n9LZDwXtb5ohiGKC8iVIYxq536ZVIUAL6w8geSUct0QN3514nkSQp7pOJwegDKjIfTtSrV83XA/LUXTZY8tg6e0Xwt5XN1/DGTEFju+NoZoisDIaSIQa8R+x1Nb/0CrD4Gqld7edjghdlp5iUDK5wWbN4CmpEr2vEw1fbZv7Crj0CuOzYPrtjgOe173fxdipBN4uzuFyovoy9MlAm00fuFQfvtWqJyA/5fq4j48unfid6E8VeM9mJKAEKgl+6JQJ34jbQMmDMzViziFfLu6EzBi9n9FXtMNhraqg3qOm9G/KzFw+nzBS/P0n6MigBmcpOlHQgd6NnU4NlDcHpR6gaatswJqVjp/3mhvHuTEsojAh4fC1RtSZ31/VFhKBaCv4oHNkvrZCjRAdLJ6K0TE62qdD4BMohzzVEqbfPBwIC3h0hCPZoOxte8MwF3xf4JiFRSquzyF34tGzGgmcG0GfulPCvohp3GAOpkp5XI+qXjSdtc5EuAxlvuAAatY/wNU2n6JaishScekifGGiMC7GR5mpH+WWecGyLAfgi2S89guM+lz43qgRCrslp0OgEuiPfOLSrJ8sHCALCHSn46mg622RA6/Xvp/Y2E6Evm5pYTZjH3O1CjOboF9lk329tekNYBYm7bos0HneUV1Gjbv28OTn4GSrisEsVduf4xn9Rtowp2H8Ii5xZ0fuGkFf+BUVACfqxCB65XH37w52XaTeA0+heS3mIiAD6iK+0BRWn5LbBgk28muiiqGkb6vF/dkwn+oWjgIq7FLgsuRbNjZMtdz4XpyRMTrNZ0UgPaiaPSmSwl92W+uKibQkY1EhOi4IxHLYP1/Gl+ZDsm2oYPCjpnSLS0icW18ZUma8QShBIAhn8fuDke8e2pywi8t1QyQBoOktAYMY13wf1xieBPSutqEn4w/ztAo7G5ofQFN/PX8oyKAa5yn6phDonondGYz3Nj0kUSCq7FgCONayX+OZNoWr73MhUCLUMvSJVlt+n1bT+X4/qVKgLeaAuhZQd95MHWjNSbbK5PbgeuvNQZjWad/x2XDGE6/WoaJisHJPCSCbD5+hFBS+vmmYoD0mdXmXUCJeZh1hDYG3J+TuYFXr4YF71icfxdmNRmmv3WGbIqMyRIkc2xAfoRQQ/rkpl+AGJod56pAqnlqdQ02edtJk9eB7K9UBo1ZrX+AZTIYtb4bhueKscpWJSxtAn5aT7f4v6VBgCSb3Og9Qjx6oHQ6NIHZL5I5gq2xnQg3W9N/+2O4FYG8VIUEjDTNAiikbnZ9/kyw9ZSjGYAmnRPsDkUyeytzBTEi1mCQ9IKntGEM3V33f3dhwhEWuTeE2I0e0RAsw3CEfGJJMPF5oAKAMqDI8A5JbXzvcGIsaNH4jSeE7LicEWdh93/bXU0MiLTogoWQfdZyMWhzBXttRD3ri5wkgGek/vYiTsN9x21DJmXLIov/hZa+RRiuZaR/A1lWBfeumYE1lGDdEThidsd4Bz7h4/aXuIDsqbb+J1T8foJpmh4yxBOIs4jAxU4ggWq/fsdS3/yMqImAG5nS5c0/dHmNdRM2Mdv2kgCC6rDqB+la0X/rY1wV+LsThYOMhc6eKZ1vAH39SvDyg6EEgHKf3e93SE58E3F3LEvR0o1KhIy5jhInYu5/xVyECu2ydYK6kfzYDTSxdBR6eUGf5yWaZoB2p3/70lGWfgxrISFhxueI74f5w4MejWn0ftZTHf5ZqZ+ApJgz5WI/WXmfdRk2EtvRkhSCX7GlCIhb3n8sYwkUtrqghEyNUtCZK7NwdnznSEDwm58EgI2hKPNMSx59Qm/FKIfN+Yt8hV69LBcvZa1/KVk9BaeufYHBlKPehDkadwZ4zjsg4SuWIYG6rMACYVd8f6BmeBlWvyeGEouWy9EmRG6CfcRM5fSuoguApp7l7t1HMHwvcXUsD9GYjXyEYLrIExpj3X9lW0wI97D1gUOTDtwxNyp21njVPUbjX5fhgEar7AAaVlN/i2fkGoPAjIaZipzK4iXQbal9U01+9QejDYBxnqzuwUcufChxUCzT0HGNmoTTumcUjmPTf8FaSwcasMGB85Nj3YY4w3ZGeEg8d+FCliKB5KwoA9BXjX8KZlQYLL6xhcmLWM3SKGpv/3ycSgvynaACgOmgfvL8Shl9K29TKNfMi4vghb6+Bhl/Znt/LVc4AiGs/oDqlqvicj3AeDF2Eze+2/ySFoK2sXQJW1ztf+5hvRF0uNeD4I7n04kvznI1e3FElOqzm0GAUqZi+lNRj37hamAgRMVIiLeIWMaOIY5rXn5WUBX5YKUtgJScA+yzRZ97FXL7LUfSC45QhBa6whNKY9Z/vFoKB7qvpIF0lILewzlad6J3czo+39yUhoEtr1sGRlrNf6djSRR+umyE34380cEtAXKle7hF8+t8nDCAnaWG+cNQeH4ja7MgccVOiLyIhcbfIc5rRX7FTzr4rqQfgF+dYe34Rgl8RHExLGDQEY3thCW8TBb5ZKl/nljxAzytJoFjlgbiGD20eCR2uTYd24GSToLdsikLt137f0xg/g72tRWDlpCD108zqXTheURAhuVumLuAp6qUADZWZH/gZk4ZsL7Ahd6L4s3BKRZwmnzVSH7vqp4OgHejoPafTg1+bWzXIkfH/IggiCXFiyAma3B+c1Dt+A2lI4BAnVztF0cdfAlxkyucz6KMQIVIvccX/mWEfydXwgF1q9aA7pfP5L0/u3nOdIEzldeMkCGDRLaGD8Jg938BXfQJwbEEgm6T/9yqOAh303ejOh7fm5SngRGw1gePW+d/EGJ6Edm3joOrj+3V9TEjdDJ6AEEo5rCYtYCiqsMAgFZyf2VmURilvVaFj4yVz64rKHEEfKBGpuyxnDGA6qVS+qtRs34RanceE8NChwaK88nkJTFuX32MS4/yiKACgNuhhvQkTcJ9J23uIxPIOYn8hwHFoSBUa1h+z0/d9yOkFIBnnmHv+0i1fLZvuiiazCiLXoa5wO4bo2gFf3JTjPxvp1CAgZvk6j1FoXvNcdwsntD8jBqFE73QFy9mdn+BVpgAYKqngB2ZDuf1QZV6fXNbMBfUpY4jhAe6TRQGZLx/BVkCBOqsCIEvl9vjKz+gedB0OjP+1heQaoOQt2cRMWLifwVbyQYFr2aBrZVM4ec8znjSdX41UdlHkeSCp7UhD7tg9X+LXO0IqrC4gY+UXd8sOyh4i3YpNwvbLZKJgke0ew2pX/x/ml1uCtOx9oHOkw3e/zm2dwF3QDgq3MOSU4Jts3cMAV/+fzleTQt8shqCZpNb3WM5enc7d8Q4rtwGkz2CF7MUDMVe/n9oXokLpbIiglaTRt1XOXl3OHe1OJbc85JFgkKzVAz2Xv5/KV4jC0yyDIKbk83d3jmyd/p2FTjh24ySbYLwszUNlF/8f3xdGwpysduBOJTy3vQ6I3h+duE2kNrTkbaCI7W5Dpxg9X9cXHAIG7CSgTGVteCZPMd4wHUXNabYzJAog9623RAJYuJ/xlojBkmuOYGMlhjjyD6Yebh0tjIk1n6PyIMluaET1GO6f7RYMgMErNeATpge5n5Bi3pec7cvDtPzjaKE/7sCF/dldH8dVp//Uql6gIOax+mzRJZ7p3EZLGnPNozChXG//xpkaAJ/+lJo+z2mLoA1nRfuX0irfIZv1Sc7y1SKNYeDw5MfD2tUfkFPkPbSogWAcKAO83hMuH3tbOgijcZfiA2JO8i3JOltWH3oShrxH58QgEGkrPjxUKp+zGlOHWjBaoZbi6LNZSrecPt740UK6zWbZYC1qPH+u1VsfxNmBRfbu4uEMo6905Mw2XMneipAZ+QqlxyB263YBcJa5H+wYQsQ9bXagqeRkdoyN8J2xXeyOTvdFJNOgsCzXQ3xX/h/kVxjCMqvdIHQlSLiMj57ebx0dDKU1RCPFoRxungVLmWLf6dWEABxqXiAwZpw6n9F53vzcGoqgc07i5CG+MEaHltqfn7gTxz3CKMFgI6gefMATeN9UmyRIRnFuIfZiV3KMydXb698L0iQ7a2cP4BMpzT9llRKf79m7Bd2vK2EDo6l06sw+3MAeoo/geOFlkuBCq+VBx9c9n8mYIANuLNDgkyT0N1oOh54TXbrNQTZu5BNg9a3ixJyY71/clhaAgWrpoCrmdjoRUSTe3lxTys6znyLbIa4wf0dY2p1fpNPj/aJogKAQ6Gw9BtOKH5ka70fR8P6hsqKsszJKb1w9Xt/RTbqd5qHgCaqQwG3V61/9mNCE1m4a4OJkMDYxjVKdhV4Mzp13QeTY4JftHcO5GDsfxlb8wWkrQaBxpfT5cNBz3qxcrUtedB0jMOF8r8hHGNps37CUPH3Z6MGgJig0vOETQ5+p2sUIHnDAofOitrMESrxcNF760Ro6eSZooAMq5oCx1jHf99iaxG2tvOCqJEF2wk4RXcZd5w3jtpokQ+DJ7f7EUBjvX9LWOMBeqqOgGyaU+rCRRZ8ZnDoKKjLQIqAh+DEtiGcbLZ950uz8RqfFYAppZj66FIWf5pn9RgGvcCEHI4e1H8xhXR7eb49HuHwlMqB4LGVCx9f+3+nXPQHBK87gQCXu+T9QJ565HLsLXvQXYzkhYXA/RwCaoJ+jU8t9gqiAoA8onn2yk+OftFpohwtwMOFkIzz0HAuKHNtel9A9+OFll2By68ICXRd/n82XiMKp7CGgeuV9OJ/PyN6kHNGL77R6YyLhZW/BhyBaaB+G1DL9mWiAoABojn2q0+Mfs1phBz+v6yFvIxo0fsuc3MzeqA/CuPulYiBwbBZCmpe/n8fXXMIQq9AgQmX9+RbQct6iXIBLWbPyotchgXC1x4qayR+nE2L8ySgC4BxpNn5jVIQf41nmRh6vIKEqY6B1RszWHW9eHg7Wt5Ak2eC1bSHD+hh1n9HWeEC8aqUgH6azep5RmF8oG8LJ4nJN4mSiPLHXyXEbsZ84kd07ICbb4DHqVwBN1jCf8hi0hDWtaKCrpJg3aU6dXikdbQzBtbejmuESryAGJBnC39VUm/5DaQIgLWgi/SITlx+V2o4HWnAv4W7jKDRbC/Bc+p5lj6k4QCV14F1srwMLGDwf/VaGgWBrMaAa5ky6TtFD3w0cAkoWcp/iVuIiscUJbBux3zFRyzsO5t8gFGqOwLzWNN/8GFeD4e0SoKvk1vflzw7eaJ0RjFm04aNQoUOv88bmWmLfl9PePU8oQWAtqMY+TJSC396Zy8Y37s+hEaPBdfXNDN25Hf+OGTbg5EpgxO4vhPHZIJ/hlVz/b+mJoB2nlrxI0zifcRrjR9UwlqG94sl0CEuPnM2ekQ/NOI1ldCBe7L3DHVg639eWhAEkauggGmaBevyRph8AG+AJcPHX4iOia3KlCiVcM57METC52mYAIEqroUH0lz+fwpeSwmIrzuBaJcV5sNCYXtWcRAqEMwfiuGHjMZDJGNu2nzWR//r95qMgAarcAMAWud/p2AlDYeyzYFRlYbirD9keulySC0pz3SLyoazwzshyWx8fUpK5e7BnFGA+qi7ABdYx39NYp4Pe7Q4gg2UUuC+Pb1503MxLwLRRIwzhhjChB/fa859mEtw8LWdOoD3p2b/KVezfwxjuRBXtWmCi5N03wE9f3kidNEvltGCjAuGssEgH69r233IS57wyp05gPSncf87V7Z/62J3EBW1V4LFk+zfej2uedxzKy/i0CmMT4aBwhMgPWynfdxKbu/+nE6A8qjaAE1YzX/oYdcOuLMFgr6UuOElP0Z6/HI7LejOQIsGh4fEWCKBbSl9zkji7FmbhID5qqUDV1ruf/pf2QtHsYGBgpbf5PxBOXt0cfwpsMvWiUCIzcfrJWpvTnySRf7o7ZjxgBeuzgdHXf5/Dl15B9Ot5oAnmWPp70VqfCpvZiVFxweIG4phzMIq3HH1ehdBx+PUlbWBYbJUDQVh3X8MWbcBc6lXgMqcTO/pSrR9/mttH7vB+YW6jFHSzzCydPd4SjtJ3TWS/oLyty8UbGVaf9NTlfpLpAWAj6Ge9spQ5X7FZwcYLrvgg02Qrtn4N7h3InYSNJfVQY4BheW+UxxMajx+QU0Z8oaeLYChp1f/aVe/f1FiLw/Ds/qBCJWG4h5Ar3o6clsrzcw3iv6HWceqJWZvQXwyRVHoYpgWgSuvcAmNXvl/bVvkBK6rk4Amm+DsEElLfQBtFiETw2OGOoxm0REwcXQceYM7W90nkg+DVrjWFO9lPn/pUjL5NKMCgOGiu/iQUjJ/MGY5FaS4IYMAkh3dVDsPeXt0GjBg0TCMcIZJw2UhNm0xfZNIMeypmqmAcqwFBk1c/n+HXcwHy63agJyZguovR9d8C27oIqLE6IaXix7Q5y74c215SDwS3niS9IIKuJsU32U+f8tS6vjsogKAVqOF+UNTT396ZfATdbfMgt+S3N4KPbd5jnPyLRvPHYtQh8vFPiTKbnx8zEXG6IGYF4Fnr/4JGV/zf39aUANPqmWAnJx072RL5X0ya5Mdsr8qhSqOwdWRNHx2QHdxNrLXHI+chPm9phsfajl+5ExD8b2dRYAUqbUBZ1nnfwZgTgtdsD+B45fW5xVFT3wbb74kJ8Zohw2LFs8NLqpzl3mOPC3ebJIEg3K4ShVoZh5/zlFu98WhBoDKpM/7JFWPf7Bj4RDFtB6C2JSi4pxA+XqNcYgpnsohiS6JvsqrKaBx7XpwQGritZQsggq1QBHzY4V/vlQ4+1SkBIBRok/4jFI9f7dlDxRWt7aCPJPM3yE+LHrGcgMs9cwTik2In8iEJ5lwgHs0QljkwpXZgZ6zkw/vYqR/11Wd/EKlCYCEoTT3wVEhf0Fm3hTzt9mC7JJJ37w9D3rpcjwsG80cikyIq8ijJ7FwbXvoQfDjfJXygSC0RxBtY5N/JlWe+4KkBIBXon34zFJKf1dlThOXtoCC\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import Audio, display\n",
    "display(Audio(data=žvižg, rate=44000))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Aktivirajmo sedaj interaktivni način (glejte tudi ``%matplotlib``):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "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, fig.canvas.height);\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overriden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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>"
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     "output_type": "display_data"
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    {
     "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, fig.canvas.height);\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overriden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img 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width=\"431.66664951377516\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1,2,3], [2,4,5]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Zgornjo sliko lahko sedaj interaktivno klikamo in tudi dopolnjujemo s kodo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "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, fig.canvas.height);\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overriden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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>"
      ]
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     "output_type": "display_data"
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    {
     "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, fig.canvas.height);\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\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\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 overriden (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",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\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": {
      "text/html": [
       "<img 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\" width=\"431.66664951377516\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.title('Pozneje dodani naslov!')\n",
    "plt.xlabel('Čas [$t$]');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Interaktivna uporaba"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pri tem predmetu bomo večkrat uporabljali interaktinivnost pri delu z grafičnimi prikazi. V ta namen najprej uvozimo `interact` iz paketa `ipywidgets`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import interact"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Potem definiramo sliko kot funkcijo z argumenti `amplituda`, `fr`, `faza` in `dušenje`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "def slika(amplituda=1, fr=10, faza=0, dušenje=0.):\n",
    "    t = np.linspace(0, 1, 200)\n",
    "    f = amplituda * np.sin(2*np.pi*fr*t - faza) * np.exp(-dušenje*2*np.pi*fr*t)\n",
    "    plt.plot(t, f)\n",
    "    plt.ylim(-5, 5)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Gremo nazaj na medvrstično uporabo in kličemo funkcijo za izris slike (privzeti argumenti):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MkIYHnCb0FIz/b1RmwS6lOzrh5VyIt/MH4p/bHco55Wx2RdxwAKOHNDTuoaEr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8eb47c080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "slika()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Če funkcijo za izris slike pošljemo v funkcijo `interact`, slednja poskrbi za interaktivne gumbe, s katerimi lahko spreminajmo parametre klicanja funkcije `slika`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MkIYHnCb0FIz/b1RmwS6lOzrh5VyIt/MH4p/bHco55Wx2RdxwAKOHNDTuoaEr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8ed5654e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interact(slika);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Razpon parametov lahko tudi sami definiramo:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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MkIYHnCb0FIz/b1RmwS6lOzrh5VyIt/MH4p/bHco55Wx2RdxwAKOHNDTuoaEr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8ed5b4ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "interact(slika, amplituda=(1, 5, 1), dušenje=(0, 1, 0.05), fr=(10, 100, 1), faza=(0, 2*np.pi, np.pi/180));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Napredna uporaba"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Prikaz več funkcij\n",
    "\n",
    "Poglejmo si preprost primer prikaza več funkcij:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nWcM4b+4t7HGs4hJmi7kjD2BKvA+MEQe5RXbPiLfzEd7ab70v7sga5t1wlJc1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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8ed666e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 10, 100)\n",
    "\n",
    "y1 = np.sin(x)\n",
    "y2 = np.sin(x+1)\n",
    "y3 = np.sin(x**1.2)\n",
    "\n",
    "plt.plot(x, y1, '-', label='$\\sin(x)$ - to je LaTeX izpis', linewidth = 2);\n",
    "plt.plot(x, y2, '.', label='sin(x+1) - to ni', linewidth = 2);\n",
    "plt.plot(x, y3, '--', label='$\\sin(x^{1.2})$ - to spet je: čšž', linewidth = 2);\n",
    "plt.legend(loc=(1.01,0)); \n",
    "plt.savefig('data/prvi plot.pdf')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Prikaz več slik\n",
    "\n",
    "Več slik prikažemo s pomočjo metode `subplot`, ki definira mrežo in lego naslednjega izrisala.\n",
    "```python\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.plot(x, y1, 'r')\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.plot(x, y2, 'g')\n",
    "```\n",
    "V primeru zgoraj `plt.subplot(2, 2, 1)` pomeni: mreža naj bo `2 x 2`, riši v sliko 1 (levo zgoraj). Naslednjič se kliče `plt.subplot(2, 2, 2)` kar pomeni mreža `2 x 2`, riši v sliko 2 (desno zgoraj) in tako naprej. Opazimo, da se indeks slik začne z 1; lahko bi rekli, da gre za nekonsistentnost s Pythonom, razlog pa je v tem, da je bil `matplotlib` rojen v ideji, da bi uporabnikom Pythona uporabil čimbolj podoben način izrisa, kakor so ga poznali v Matlabu."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Delujoči primer je:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BA8rKoXFG+I7AgRsHcDPzptKiiMbaxLWgoP88mSgBIUSzphl1K/c1+sdMseO2m0vPnmx1\na0vmg9WrmZdMSIiycgwezA6LrbE9k4KcjPBl3k4xiTEKSyIeaxLXoHn15vCt6auoHBG+EcgrzEPc\nRW3tu6lfuQcEyHe4pjScndmBpo0b2SlZrUMpG1vDfoKSuLuzJOcxMfxAkxU0r8GUYEySbSj3+9n3\nsfvqbgz3GS67l0xJOtXthDrudTS3p6Fe5X7rFkvqEB6utCSM8HAWNXGnDaQ3S0wEkpPVNbZpacDx\n40pLomnCW4Rj77W9uPdE+zmAY5NiUUgLMdxX4ad2MK+ZsBZh2Jy6Gdn52UqLYzLqVe6xsexdLQqo\nd2+WaGLtWqUlsR7D7xAaqqwcBoYMYRvXMbax6lSKcJ9w6KhOk54dJVmbtBYNqjZAG682SosCgI1t\ndn62pmLNqFe5x8QATZuyvKZqoGJF5tmxbp32PTvWrgU6dWIZp9SApyfQqxc3zVhJgFcAGlZrqDnz\nQUmycrOw/fJ2hLUIU9wkY6BHwx7wdPXEuqR1SotiMupU7unpLARtWJi8sWTKIzwcuHdP2zlAr18H\nTpxQzre9NEJDWQjgpCSlJdEshBCEtQhD/JV4TYcB3py6GXmFeQjzUc8cdXJwwpBmQ7AxZaNmwgCr\nU7nHxQEFBepTQAMGsJAEBpORFlmnX3mobWyHDWPv67SzMlIjoS1CkVeYpynzQUnWJa1DDbcaCKoX\npLQoxQhtHor0p+nYd32f0qKYhDqV+7p1gJcXEBiotCTFqVKF2d7XrdOu+SA2lpm6mjZVWpLi1K3L\nDqtx5W4VQfWCUMOtBtYla3Mc8wrzsOniJgxtNhSODo5Ki1OM/k36w9XJFWsTtbHvpj7l/vQpsGUL\n87+WOiuQJYSGsngs588rLYn5PHwI7Nmjno3UkoSFsThCN23nII7cODo4YlizYdiUsgl5hdrLQ7D7\n6m5k5mYirIXKniwBuDm7oV/jfliXvE4TybPVpz137mSBupQ+XFMaQ4eydy2uMOPi2GawWsfWINd6\n7Xt7KElIixBk5GZg99XdSotiNrFJsXBzdkMf7z5KiyJISPMQpGWm4dTtU0qLUi7qU+7r1rGDLcHB\nSksiTJ06QMeO2rS7r1vHPGTat1daEmF8fIAmTbQ5tiqij3cfuDq5as4lklKK2ORY9G/cH67OrkqL\nI8iQZkPgQBwQm6T+OSqKcieEDCCEJBNCUgkh0yxuSKdjAboGDmSJHNRKSAg7cKMl84HB3DVsmDrN\nXQDzjAoJYU9vmZlKSwNAxLktIwbzwfrk9ZowHxg4cesEbmbdREhzlT5ZAqhZqSaC6gVpYk/D6v9y\nQogjgF8ADATgC2AMIcQy5/SjR1kQKbWaDQxo0XywcycLfqaFsc3PZzcihRF1bstMSPMQ3Mi8oQnz\ngYHYpFg4EAcMbjZYaVHKJKR5CBLuJOBK+hWlRSkTMZZwgQBSKaWXKaV5AFYAsEyDrF/PglkNGiSC\nWBLi48O8TbRkPoiNZSdse/VSWpKy6dKFxbtRx9iKN7dlRkvmAwPrU9aja/2uqOGmcLyjcghpwaaA\n2s1eYij3ZwEUTQGTpi8zn9hYoEcPwMNDBLEkRIXmgzLR6diNc8AAdZu7AHZzHzKEbf7mK35YRLy5\nLTM1K9VEl3pdEJusDeV+Jf0KEu4kqNokY6CJZxP41vTF+hTbV+5CR0iNDH2EkAmEkOOEkOP37gkE\nNiosBF56CZg4UQSRZEBF5oNyOXaMmbsMB4XUTkgI8OgRsHev0pKIM7cVIqR5CM7cOYOrj64qLUq5\nGFbBw5prY46GNA/Bnqt7kJ6TrrQopSKGck8DUK/Iz3UB/F2yEqV0PqW0PaW0fU2hZMyOjsB//qN8\n7HZT6dxZTeaDsomN1Ya5y0DfviyWj/JjK87cVgjDKljt5gMAiE2OhW9NXzTxbKK0KCYR0jwEhbRQ\n1THexVDuxwA0JYQ0IoS4ABgNQP2zyVrUZT4om9hYoHt35dLpmUulSkzBx8YqfRJY03O7afWm8Knh\no3rTzMOch9h7ba8mTDIGOjzbAXXc66h6bK1W7pTSAgCTAGwFkAhgFaVUg8c3LcBgPtin4lgTqanA\nhQvq95IpSWgoC3J25oxiItjC3NaC+SDuYhwKaaGmlLsDccDQZkOxOXUzcgvUmcBHFIdnSmkcpbQZ\npbQxpfRLMdrUBP36Aa6uajAflI5BNq0p9yFD2Ma1wmOr9bkd2iJU9eaD2ORY1HGvgw7PdlBaFLMI\naRGCx3mPsevqLqVFEUSlp1k0gpsbMx+oOZDYunVAq1ZAw4ZKS2IetWoxt0gthnlQEQbzgVoP3Twt\neIotqVswtNlQOBBtqaPgRsGo5FxJtTHetTWaasRgPjh9WmlJjLl7l8WeV1t4X1MJDWXjeu2a0pJo\nFgfigGHNh2Hzxc14WvBUaXGM2HllJx7nPVZV7HZTqehUEQOaDMD65PXQUZ3S4hjBlbu1DBnCjvOr\ncYW5cSPzcVdrFMjyMJiS1Gz20gAhzUPwJP8J4i/HKy2KEeuS1qGyS2X0aqjyw3WlENoiFLce38LR\nm0eVFsUIrtytpWZNIChIncp93TqgQQOgdWulJbGMpk2Bli1tI2+tggQ3CkZll8qqMx8U6goRmxyL\nQU0HoYKTyg/XlcLgpoPh5OCkurEFuHIXh7AwICGBxXlXC48fA9u3s9WvmlIVmktoKDvMdP++0pJo\nlgpOFTCo6SDEJseiUKee/L+H0w7j7pO7CG2h0SdLAB6uHujVsBfWJq1VXZA2rtzFwGDTVtMKc8sW\nFgkyPFxpSawjLOzfaKEciwlrEYZ72fdw8IZ68v+uTVoLZwdnDGwyUGlRrCK0RShSHqQg6b668v9y\n5S4GDRsCAQHqUu4xMcxk1LWr0pJYR9u2QP366hpbDTKw6UC4OLpgbZI6xpFSijWJa9C3cV9UrVhV\naXGswvDkEZMYo7AkxeHKXSzCw4FDh4Bbt5SWBMjNZZupw4axk7RahhBmmtm2DcjKUloazVKlQhX0\n9e6LmMQYVZgPTt8+jauPriK8hcafLAE8U/kZdK7bGWsS1ygtSjG4cheL8HDm666GjdX4eKYItW6S\nMTB8OLthxan3II4WGO4zHNcyruHkrZNKi4KYxBg4EId/wudqneE+w3Hq9ilcTr+stCj/wJW7WPj6\nAi1aAKtXKy0Jk6FKFaB3b6UlEYegIHaoSQ1jq2GGNR8GR+KI1ReUHUdKKVYnrkaPBj1UH7vdVMJ9\n2EJKTaYZrtzFghAgIgLYswdQMuxrfj57ehg2TP2x203F0ZFtrMbFAdnZSkujWaq7VUdwo2CsTlyt\nqGnm/L3zSLqfhAjfCMVkEJtGHo3QxquNqkwzXLmLyfDhLC69kqaZ+HggPR0YMUI5GaQgIoIpdi3E\nz1cxEb4RSH2YioQ7CYrJEH0+GgTkn9WurTDCdwQOpx3G9YzrSosCgCt3cWndGmjSBFi1SjkZoqNZ\nOr1+/ZSTQQp69mTePytXKi2JpglrEQZH4oiV55Ubx+gL0ejeoDu83L0Uk0EKRrRkCyqlzV4GuHIX\nE0KAUaNY+r27d+XvPy+PuQwOHcqSXdgSTk7syWjjRpbom2MRNSvVRHCjYKw6v0oR08z5u+eReD8R\nI3xt7MkSLP1e2zptseq8gou7InDlLjajRrFDN2sUsL1t385MMmPGyN+3HIwaxUwzmzYpLYmmGdVy\nFC6lX1LEa2b5ueVwIA42ZW8vykjfkThy84gqUhty5S42fn7Mc2bFCvn7Xr6cJRe3NZOMgW7dAC8v\n9ntyLCbMJwxODk5YcU7eOUopxfJzyxHcKBi13WvL2rdcjGw5EgCw/Kzyc5Qrd7EhBBg9msVDuS7j\nxkp2NoueOHw44OIiX79y4ujIxjYujj2hcCzC09UTA5oMwPJzy2WNNXPs72O4nH4ZY/xs9MkSzGum\nS70u+OvcX0qLwpW7JIwdy97lXGFu2MCChdmqScbA2LFsb4H7vFvF8/7P42bWTey9tle2PpefXQ4X\nRxeb85IpyVj/sTh395yiHkkAV+7S4O3NsggtXSpfhqYlS4B69ZhXiS3Trh3QrBnw559KS6JphjYf\nisoulbEsYZks/eUX5uPPs39iaLOhqFaxmix9KsUI3xFwJI6yjW1pcOUuFc8/D5w/L0+Gptu3ga1b\nWZ8ONv4nJYSt3pOS2JMKxyLcnN0Q7hOO1YmrkZ0v/cGwLalbcC/7Hl5s/aLkfSlNzUo1MajpICxL\nWIYCXYFicti4JlCQUaOY7XvRIun7Wr6cHZ564QXp+1ID77wD3LgBuLsrLYmmeSngJWTmZspyZH7x\nmcWo6VZT8+F9TeWlgJdw6/EtbL+0XTEZuHKXCk9PdmR+2TIW9EoqKAUWLgQ6dAB8fKTrR024uwPO\nzkpLoXm6N+gObw9vRJ2KkrSf+9n3sSFlA57zfw7OjvbxdxvSbAhquNXAH6f/UEwGrtyl5JVXgIcP\npQ1HcPgwM/+8+qp0fXBsEgfigJcDXsauq7tw6aF0WcSWnFmCvMI8jG8zXrI+1IaLowvG+o9FbHIs\n7mcrk0WMK3cp6dOHJZr4/Xfp+vj9d6BSJeYiyOGYyUsBL8GBOGDByQWStE8pxfwT89G5bmf41/aX\npA+18mrbV5FXmIc/TimzeufKXUocHIAJE1gwryQJUnA9esRirYwZw+LJcDhmUrdKXQxrPgwLTi1A\nboH45sN91/ch+UEyJrSbIHrbaqdlrZbo3qA75p2YBx3Vyd4/V+5S8+qrbGP111/Fb3vhQnZ4aeJE\n8dvm2A0T20/E/ez7iL4QLXrbc4/OhUdFj39Obtobr7d7HZfSL2HbpW2y982Vu9TUqsXC7y5aJG6a\nuMJC4Oef2ZH8Nm3Ea5djd/T27o1m1Zth7tG5ogYTu/boGmISY/Bau9fg5uwmWrtaItwnHF7uXvjx\n8I+y982Vuxy89RZT7GLa3tevB65eZW1zOFbgQBwwteNUHL15FPuu7xOt3Z+P/gwCgjcD3xStTa1R\nwakCJgdOxtZLW3Hu7jlZ++bKXQ46dAB69QJmz2ZH562FUuDrr9lJ2BDbyEHJUZaXAl5CTbeamHlg\npijtPcx5iN9O/IaRLUeibpW6orSpVV5v/zrcnN3w/aHvZe2XK3e5+OAD4OZN5vduLdu3A8eOAdOm\nsTjnHI6VuDq7YlLgJGy6uAlnbp+xur05h+fgcd5jfNj1QxGk0zaerp6IbBOJZQnLZE2gzZW7XPTr\nx+KifPaZdYeaKGVt1K0LvGj7R7k58jE5cDKqVqiK/+76r1XtPHr6CHOOzEG4T7jduT+WxgddP4CT\ngxO+2PuFbH1y5S4XhABffQVcuwbMn295O7GxwIEDwP/9n+0kwOaoAg9XD7wf9D42pGzAoRuHLG7n\nq31fITM3E590/0RE6bTNM5WfwRvt38CSM0uQdF8Ct2gBuHKXk759me39s8/YyVVzyc9n5h0fH2C8\n/Zz248jHlI5TULtSbby99W2LfLOvpF/BnCNzMC5gHFp7tZZAQu0yres0uLu4460tb8mS4pArdzkh\nBPjhB5ZoYto086+fNQtISWHv3NbOkQB3F3fM6jsLR24ewcKTC826llKKKVumMPNDL/nMD1qhVqVa\nmNFzBrZd2oZ1SRKGJNHDlbvctG4NTJ3K3CJ37zb9usREYMYM5jM/eLBk4nE4z7d6Ht0bdMf7O97H\n9QzTs4ktTViKjSkb8WXwl3i2yrMSSqhdJnaYCP9a/nhj0xu49+SepH1x5a4E06ezhBPPPQfcuVN+\n/cePWewYd3dg7lzJxePYN4QQRA2LQqGuEGPWjEF+YX651yTdT8KUzVMQVC8IkwMnyyClNnF2dMay\n8GVIf5qO8evHSxqWwCrlTggZQQg5TwjREULaiyWUzePuDkRHM/NMeHjZSScKCoBx44Bz54C//gJq\n22ZiYbVh73O7sWdjzB86HwdvHMSEjRPKVEL3s+9j6PKhcHF0wZ/hf8LRwVFGSbVHq9qtMKvvLGxI\n2YD3tr0nmf3d2pX7OQDhAORLxGgrtGrF0vAdOcLMLPcEHtFycpgZJiYG+O47oH9/+eW0X+x+bo/2\nG43pPaZj0elFiFwfiZz8HKM6Vx9dRdeorriRcQNrR61Fg2oNFJBUe0wOnIwpgVPww+Ef8PbWt016\nOjIXq3blKKWJAHuM41hARAQ71DRuHODvD/z3v8DQoWyzND6emW8uXwbmzAGmTFFaWruCz23GJz0+\ngY7q8Nnez3D05lFM6zoN3eou7sMbAAAgAElEQVR3w5P8J4hJjMG3B76Fk4MTtr2wDUH1g5QWVzMQ\nQvDDgB9ACMGcI3Ow//p+TOs6DZ3rdsYzlZ8RZd5xlwulGT0a8PUFIiOBSZPYy4CPD1PywcHKycex\nawghmNFrBjrX64wpm6fghbXFUzkOaz4Ms/vNRmPPxgpJqF0ciAN+HPAjOtXthI/iP8KI6BEAWBz4\n+UOtOAujp1zlTgjZAcBL4KuPKaWxpnZECJkAYAIA1K9f32QB7YJWrYCjR4FTp9h7bi4QGMhi0jhy\n+6VU8LltOgOaDEDSpCQcuH4AFx9ehANxQNf6XdHEs4nSomme0X6jEeEbgX3X9iHpfhKaVm8qSrtE\nDGM+IWQ3gPcopcdNqd++fXt6/LhJVTkcsyGEnKCUirIJyuc2R02YM7e5KySHw+HYINa6QoYRQtIA\ndAawiRCyVRyxOBxl4XObo3VEMcuY3Skh9wBcK+XrGgCUSRdeHLXIAXBZhChLjgaU0ppyCmOgjLmt\nlnEDuCxCqEUOQKS5rYhyLwtCyHGx7KW2IAfAZVGzHKaiJnm5LOqVAxBPFm5z53A4HBuEK3cOh8Ox\nQdSo3K333hcHtcgBcFmEUIscpqImebksxqhFDkAkWVRnc+dwOByO9ahx5c7hcDgcK+HKncPhcGwQ\nxZQ7IWQAISSZEJJKCDHKOUcIqUAIWan//gghpKEEMtQjhOwihCTqY3e/JVCnJyEkgxByWv+SLOsv\nIeQqIeSsvh+jM+yE8ZN+TBIIIW0lkKF5kd/1NCEkkxAytUQdycaEEBJFCLlLCDlXpMyTELKdEHJR\n/+5RyrXj9HUuEkLGiSWTOahhXuv74XPbuA/7mtuUUtlfABwBXALgDcAFwBkAviXqTATwm/7zaAAr\nJZCjDoC2+s+VAaQIyNETwEaZxuUqgBplfD8IwGYABEAnAEdk+DvdBjs4IcuYAOgOoC2Ac0XKZgKY\npv88DcC3Atd5Arisf/fQf/aQ4+9WYrwUn9f6tvncLv9vZdNzW6mVeyCAVErpZUppHoAVAEJK1AkB\nsFj/eTWA3oSIG1ybUnqLUnpS/zkLQCIANSd/DAGwhDIOA6hGCKkjYX+9AVyilJZ2mlh0KKV7ATws\nUVx0LiwGECpwaX8A2ymlDyml6QC2AxggmaDCqGJeA3xum4DNz22llPuzAG4U+TkNxhPvnzqU0gIA\nGQCqSyWQ/vG4DYAjAl93JoScIYRsJoS0lEoGABTANkLICcLCyJbElHETk9EAlpfynVxjAgC1KaW3\nAKa0ANQSqCP32AihunkN8LldCjY/t5VK1iG0Uinpk2lKHVEghLgDWANgKqU0s8TXJ8Ee3R4TQgYB\nWAdAnIDLxgRRSv8mhNQCsJ0QkqS/2/8jqsA1Uo2JC4BhAD4U+FrOMTEV2cbGShlklZPPbWPsZW4r\ntXJPA1CvyM91AfxdWh1CiBOAqjB+pLEaQogz2OT/k1IaU/J7SmkmpfSx/nMcAGdCSA2x5dC3/7f+\n/S6AtWCP+UUxZdzEYiCAk5TSOwJyyjYmeu4YHtH173cF6sg5NqWhmnmtb5/PbWHsYm4rpdyPAWhK\nCGmkv4uOBrC+RJ31AAy7whEAdlL97oJY6G2dCwEkUkpnl1LHy2ATJYQEgo3ZAzHl0LddiRBS2fAZ\nQD+wJM1FWQ/gRb1nQScAGYZHOgkYg1IeW+UakyIUnQvjAAhlSdoKoB8hxEPvcdBPXyYnqpjXAJ/b\n5WAfc1uKXWETd44Hge3gXwJLawYAnwEYpv9cEUA0gFQARwF4SyBDV7DHmwQAp/WvQQBeB/C6vs4k\nAOfBPB8OA+gi0Xh46/s4o+/PMCZFZSEAftGP2VkA7SWSxQ1sQlctUibLmID9090CkA+2YhkPZpOO\nB3BR/+6pr9sewIIi176iny+pAF6213nN5zaf25RSHn6Aw+FwbBF+QpXD4XBsEK7cORwOxwbhyp3D\n4XBsEEX83GvUqEEbNmyoRNccO+DEiRP3qUI5VEub20+ePEGlSpXkF0gALot65QDKlsWcuS2KcieE\nRAEYAuAupdSvvPoNGzbE8eNGsYM4HFEghMh2pLwkpc3t3bt3o2fPnha1aXB6ECtKgTWyiI1aZFGL\nHEDZspgzt8UyyyyC/HE8OBybJS0tDW+//TZatmwJJycnVKpUCZ07d8acOXOQm5urtHgcDSCKcqfC\nAXHslsxM4NQpoLBQaUk4WoNSipkzZ6Jp06b48ccfceHCBeh0OuTk5ODw4cOYOnUqfH19ceSIUJgY\nDudfZNtQJYRMIIQcJ4Qcv3fvnlzdyk5iItC6NdC2LfDsswD/H+SYSn5+Pl5++WV88MEHePr0aan1\nLl++jODgYOzcuVNG6ThaQzblTimdTyltTyltX7OmIntdkpORAfTsCeTkAL/8AlSsCDz/PPDkidKS\ncdQOpRSRkZFYvHhx+ZUBZGdnY8iQIThz5ozEknG0CneFFJE5c4C7d4GNG4GJE4FFi4DUVODTT5WW\njKN2vvjiCyxZssSsa3JycjBq1Cg84asHjgBcuYtEejowezYQGgq0b8/KevZkK/d584DHjxUVj6Ni\ndu/ejU9LWQFMmjQJN27cwJEjR9C6dWuj75OTk/Gf//xHahE5GkQU5U4IWQ7gEIDmhJA0Qsh4MdrV\nEn/8wcwyJf9HX3uNKfboaGXk4qibR48e4cUXX4RQjKe5c+di7ty5qFu3LgIDA7Fr1y74+Rl7Gs+b\nNw8JCQlyiMvREGJ5y4yhlNahlDpTSutSSheK0a6WWLECaNcOCAgoXh4UBDRvDiy0uxHhmMKHH36I\nGzduGJVPmzYNkyZNKlbm4eGBVatWwdXVtVi5TqfDO++8I3iD4Ngv3CwjApcuAceOAaNHG39HCDB+\nPHDgAKvH4Rg4duwY5s2bZ1TevXt3fPHFF4LX+Pj44LPPPjMqj4+Px65du0SXUWmePn2KuXPnIigo\nCF5eXvDx8cFrr72GpKQkpUVTPVy5i8CqVex95Ejh78PC2PvmzfLIw1E/Op0OkyZNMlptu7u7Y8mS\nJXB0dCz12smTJ6Nx48ZG5TNnzhRdTiW5fv062rVrhylTpuDgwYO4c+cOkpKSMH/+fAQEBOCXX37h\nTytlwJW7CKxeDXTuDNSvL/x9kyZA48ZcuXP+JTo6GkePHjUq/+yzz9CgQYMyr61QoQK+/PJLo/Kt\nW7fajGvk1atX0aVLF1y4cEHw+9zcXEyaNAlff/21zJJpB67creTePeDkSWDQoLLrDRwI7NoFlHE2\nhWMn5OXl4aOPPjIq9/f3x+TJk01qIyIiQnD1Pnu2YEY9TVFYWIjnn38eN2/eLLfuxx9/jJgYo/Sw\nHNiIct++HYiIYJuXK1YAOp18fcfHs/d+/cquN3AgO9y0d2/Z9Ti2T1RUFC5fvmxU/v3338PJybRY\nfo6OjnjvvfeMyqOjo/Ho0SOrZVSS77//HgcOHDC5/ksvvYS//5Y7F7r60bxyX7sW6N+fbVg+eACM\nGQN8+KF8/W/bBnh4ME+ZsujZE6hQgdXn2C+5ubmCJpV+/fqhb9++ZrU1btw4eHh4FCvLycnBn3/+\naZWMSnL79m1Mnz7dqNzLywvLli3DCy+8YPRdVlYW3n77bRmk0xaaVu4JCcBzzwEdOzJPlAsXgAkT\ngJkzgVihHOIiQyl7aujdGyhj/wsA4OYGdOgA7N8vvVwc9bJw4UKkpaUZlVtiO3Z1dRVUdvPnz9fs\nRuPMmTORk5NTrIwQglWrVmHs2LFYtGgRQkJCjK5btWoVtm/fLpeYmkDTyv2995jSXL+evTs4AD/9\nxIJ2vfGG9Pbt5GQgLQ0wdcHVtStw4gSQnS2tXBx1kpeXh2+++caoPDQ0FG3btrWozVdffdWoLCEh\nQZOHmm7fvo3//e9/RuVTpkxBt27dAAAODg6IioqCUHyqjz/+WLM3NSnQrHLfvp29/u//gKJ/5woV\ngO++A27dAqKipJXBYD83NcZ/t25AQQGPFGmvLFu2TPDAUmmhB0zBz88PnTp1MipfsWKFxW0qxa+/\n/moUDdPNzQ0ff/xxsTJPT0/BjeNjx45h06ZNksqoJTSr3D/7DGjQgAXoKknPnmxz9ZtvgLw86WTY\ntw+oVQto2tS0+p07s0NN3DRjfxQWFgqu2kNCQhBQ8lizmYwdO9aobMWKFZpaxRYUFGChwDHuSZMm\nCa7Sx44di3YCG13Tp0/X1O8tJZpU7mfPMgU5eTJbqZeEELapeuMGsGGDdHLs28dW46ZmP/PwAPz8\nuHK3R/bu3YuLFy8alZdclVrCiBEjjA49Xb16FYcPH7a6bbmIi4sz8nhxcnLC1KlTBesTQjBjxgyj\n8hMnTmAvd0kDoFHlPm8eU+ovvVR6nQEDgGeeAUwMj202N24A164x5W4OXbsChw7xLE32BKVU0IOl\nb9++6NChg9Xt165dG7179zYqj9ZQtLrff//dqGzo0KGoU6dOqdcMGjRIcPxswddfDDSn3J88AZYs\nYUf9q1cvvZ6jI/DCC0BcHHDnjvhy7NvH3s1V7h07AllZbDOWYx9s2bIFlwQCCwkdZLKU0QKBjWJj\nYzVhonjw4AG2bNliVD5hwoQyryOECPr6b9iwASkpKaLJp1U0p9w3bmTK8ZVXyq87bhxbIf/1l/hy\n7N8PVK7MUuqZQ2Agexc4ec6xQSil+OSTT4zKO3XqhB49eojWz7Bhw+DgUPzf+fLlyzh37pxofUjF\nunXrUFBQUKysbt26Jvn9h4eHG4VroJQKet3YG5pT7itWAHXqmLZi9vEB2rRhsV/E5tAhtgovz7+9\nJM2bs5sCV+72wYYNG3D8+HGj8g8//BDE1M0aE6hevTq6d+9uVL5u3TrR+pCKVYbIe0UYOXJkmcHT\nDDg5OWHKlClG5YsWLUK2nfsca0q5Z2ay4FsjR5quVMPCmCK+fVs8ObKy2AGqLl3Mv9bBgR1m4srd\n9tHpdIKr9jZt2mDo0KGi9yd0uEftyj0jIwPxhhgeRRgxYoTJbbz88stGMe4fPXqElStXWi2fltGU\nco+NBXJzgVGjTL8mNJSdJF2/Xjw5jh1j8Ws6d7bs+o4dgTNneBAxWycmJkYwSuPnn38u6qrdgJBy\nP3nyJG7duiV6X2Jx6NAhFJbwLqhfvz46duxochseHh6Cew6//fab1fJpGU0p95gYoG5dQODMRqn4\n+QHe3oCYC5iDB9m7OXIUJTCQHWY6dUo8mYqSksLS+skZQI1jzMaNG43KOnbsiEHlhRC1kEaNGgmm\n4RParFQLQu6aw4cPN/vm98YbbxiVHT16VJMndcVCM8o9J4cF3Ro2zHS/coDVDQ1l0RvFSlJ98CDg\n6wtUq2bZ9QbvrWPHxJHHAKXApElAixbMdBUSwkxZHGX4448/EBcXV+ywzRdffCHJqt3AwIEDjcri\n4uIk688a8vLycEzgn2DYsGFmt9WhQwe0adPGqFzIxdJe0Ixy37GDxWQRePIsl8GD2UnVnTutl0On\nAw4fttwkAzD/ey8vQGCfzSpiYoBffgEiI1kIhs2bgWnTxO2DYzqEEAwcOBDHjh3D559/jtdee03Q\nH11MhJ4Ktm3bhvz8fEn7tYT9+/cbbXpWrVoVQUFBFrUnFGdn6dKlRoHI7AXNKPfYWKBKFdPjuBSl\na1fA3Z35vFtLcjKQnm7ZZqoBQtjqXUzlnpHBVu1t2gC//gq8+y5zF42KAnioa2UhhKBr16747bff\nJF21A0BQUBAqV65crCwzMxOHDh2StF9LEDJb9e/fH87Ozha199xzz8HNza1YWUZGBlZL4S6nATSh\n3HU6FkZg4EDAxcX8611cgD592ErW2jMdhv8Ra5Q7ALRvDyQlMc8bMVi0iHkE/e9/gCHfw7RpzLb/\n/ffi9MFRP87OzoL+4WoMh7t161ajsiFDhljcXtWqVTFSIJGxvZpmNKHcjx0D7t5l9nZLGTQIuH4d\nSEy0TpaDBwFPT6BZM+vaad+e3WhOnrSuHYC1M28e26gt6mTg7c1s71FRgAqfyjkS0U8gLZjalPvN\nmzcF86P279/fqnaFTDP79u1DsoRHwgsLC7F//37MmDED7777LubMmaOKE7KaUO4bNzL/8AEDLG/D\ncK21SaoPHmT2dgcrR659e/Yuhmlm3z5203rtNePvRo4EHj3iwcrsCaGV+7Fjx5Cenq6ANMII+bYH\nBASgVq1aVrXbuXNn+Pr6GpVLtXo/dOgQ/P390a1bN0yfPh2zZ8/G1KlT0bx5c0RGRio65ppR7kFB\nbMVsKfXqMQ8XgSdBk3n4kClRa00yAAsVXL++OB4zCxey/Qgh//++fVmQNTH9/DnqxtvbG97e3sXK\ndDoddu3apZBExgg9SfTp08fqdgkhgqv3RYsWGcWKt5YffvgBXbt2RWIp5oCFCxeiU6dOuHv3rqj9\nmorqlXtaGnD6NGCFKe4fBgxgCTYsPZVscMm1xlOmKGJsqublMcUdFgZUqmT8faVKbL8hNtb6/QaO\ndlCz3Z1Sih07dhiVm5tDtjReeOEFVCgRC/zBgwdYs2aNKO0DwKxZs/DOO+9AV85hkpSUFAwaNAiP\nxfLDNgPVK3dDYpXBg61vq39/dsJ1zx7Lrt+/n21WGoJ/WUtgIMv9+uCB5W3s3s3MLuHhpdcZNgy4\ncgU4f97yfjjaQsjuvlMMX2ARSExMxO0S8UBcXFzQtWtXUdqvXr26YPgCsU6sLl26FO+//77J9U+c\nOIF3331XlL7NQfXKfcMGoFEjZlKxlm7dgIoVLTfN7N3LbOVCK2RLEOMwU0wMk6esRY/h/9zSmxpH\ne/Tq1cvI7TIlJUUwObfc7N6926gsKCjIyI3RGl5//XWjsv379+P06dNWtXvixIlSQxH7+/tj7Nix\nqFixotF38+fPx0HD0XaZULVyz85mJ0uHDjXvVGppuLoyP3lLNlVzcliwL4HAexbTrh37vSxV7jod\nC6swaBD73UqjQQN2cOrAAcv64WgPDw8PwRObarC7C8nQq1cvUfvo0qWLYCiGn376yeI2MzMzMWLE\nCEHb/fjx43Hy5EksW7YM8fHxRoHMAHbDKc+MIyaqVu47drDgWmIG0Bs0iMVeEcidUCZHjjB3QjGV\ne5UqLFSApREijx9niUjKO7VLCNuQ5srdvggODjYqU1q5U0oFV+49LTmdWAaEEEyePNmo/K+//rJ4\ng3PSpEm4cuWKUfno0aMxf/58OOkPmHTp0gXffvutUb2zZ88iJibGor4tQdXKfcMGpgDFVKiG0Bvm\nnlbdu/dfJSkmgYFMuVuy2blpE5PJFBfRoCDm56+Cp3KOTAithuPj4xXNznThwgXcv3+/WFnFihUR\nKNZGVhGef/55eHh4FCvLzc21aPUeHR2NpUuXGpUHBARg4cKFRolSJk6ciPYGf+cifPXVV7KNv2qV\ne2Eh8/AYMMCyU6ml0aQJO4BkrnLfvRto1cryYGGlERjIDmhdu2b+tXFxLDJlWekGDRhuSnz1bj90\n69bNKOHF9evXFQ0BLLRq79Kli5F3ixi4ubkJukX+/PPPyMjIMLmdW7duCUaddHd3R3R0tOBegaOj\nI7755huj8lOnTgmezJUC1Sr3AweAe/eA4cPFb3vQIGDXLtNdIp88YfKI4IZrhMGt0ty9ljt3mFnG\nVC+i1q0BNzeu3O2JypUrCyaQFooxLxd79+41KhPbJFOUt956Cy4lVocZGRmYO3euSddTShEZGYkH\nAi5tc+fORZMmTUq9Njg4WDAuvVwpAFWr3NesYYdvpAh9PXgwc4k01e13zx7mT27lyWhB/P1ZUDNz\nla4hRLdAhFdBnJ3ZBq7YkShtHULIAEJIMiEklRCiuRibQorTWo8RS6GUCip3MXPJluSZZ57Byy+/\nbFQ+c+ZMk2zv8+bNEwyZHB4ejnHjxpV5LSFEMAn6xo0bcfPmzXL7thZVKndKmYtf//5M8YlNjx6A\nhwfrwxS2bmXeKKbkbTUXJydmWjFXucfFsVyyAg4RpdK2LcsAVSLxjeZYvJiFVZA6Xg4hxBHALwAG\nAvAFMIYQIoJTrnwIKXelVu6XLl0y8m93dnaWxN5elA8++MDIPJWVlYXp06eXed3Zs2fxzjvvGJXX\nqlXL5AifgwcPRr169YqV6XQ6REVFlS+4lahSuR84wDb+IiKkad/ZmR3sWb+ercjLY+tWdkMQcF8V\nhaAg4OxZ0xNr5OczmQYONM9FtG1bZopSQUwjq9izh8XTsTAyrDkEAkillF6mlOYBWAHAgowCyhEU\nFGSk2O7cuYOrV6/KLovQqr1FixaCfuFi0qhRI0Hf9Hnz5uFAKauqjIwMRERECMaCX7hwIWrWrGlS\n346OjoiMjDQqj4qKknxjVZXKffFidjAnLEy6PsLD2clOgf2dYly5wmK4Cxz4E42goH+TgJjCoUMs\nfru5p3YNq3wxIlEqSVIS0Ly5LF09C+BGkZ/T9GWawd3dXdBrQwmXSCHl7u/vL0vf06dPN4pzr9Pp\n8OKLL+LRo0fFynNzcxEWFiYY2XHChAlmhyV+5ZVXjLxprl69iiNHjpjVjrk4Sdq6BeTkAKtWsY1U\nKUwyBvr2Ze2vXFm24jYkUA8NlU6WTp1YlMl9+0y7icTFsVWruRu8Pj7s6ePkSWDsWMtkVRpKmXIX\nCNstBULPRUbLLULIBAATAKB27dqCHiGPHz8WLJcDb29vI0WyatUqNGrUSFY5hGLbNGvWTLZxee65\n5zBv3rxiZZcvX0bXrl3xySefYPfu3Xj8+DFmzJiB4wKbU40aNUJYWJhF8rZt29aoze+++w6TJk0y\nqivaXKGUWv0CMABAMoBUANPKq9+uXTtaGn/+SSlAaXx8qVVE45VXKK1UidLMzNLr+PtT2rmz9LJ0\n6kRpx46m1W3ZktJevSzrp0MHy69VA3fvsvkxe3bpdQAcp+LM684Athb5+UMAH5Z1TWlze9euXdb8\n2lYRFxdHwW5K/7waNWokqww3b940ksHBwYFu3LhRNhny8/Npp06djOQAQD08POjw4cNpzZo1Bb93\nd3enSUlJFvcdFRVl1KaXlxctKCgwqlvWXDFnblttlhFz06mwEPjqK/bILaF31D9ERjI3R8PqvCTn\nzzNb+Jgx0svSvz8LQ/DwYdn1UlKYXJY+SbRty1buWo0Qaci50KKFLN0dA9CUENKIEOICYDQAzQVP\nDgoKMjILXLlyBTdu3CjlCvHZL5BQoHXr1qgkVqAmE3BycsLSpUvhLmASSE9Px5o1a3Dv3j3B66Kj\no9HcCltgWFiYUfrA27dvY9++fRa3WR5i2NxF23RasYIprhkzrE+GYQqdOgEtWwK//y6s7BYvZnII\nBJgTnX79mN29vMB9a9eyd0v3IwICmL3ekkNTppKezv6G778PnDolbttJSexdDps7pbQAwCQAWwEk\nAlhFKdVcbM0qVaqgbdu2RuVCNnCpEFLuYkWBNIcmTZpg7dq1Rr7vpeHg4ICoqCgMsCZTEIBq1aph\noIDf8rp166xqtyzEUKGibDrl5wPTp7PDNnIoU4B5mkycyI7/lzw0dv8+y0caEQF4eUkvS2AgC7Ww\nbVvZ9WJiWDTJEt5VJtOqFXs/e9ay68ujoIDZw2fMAH74ge0LXL4sXvvJyez8Q4MG4rVZFpTSOEpp\nM0ppY0rpl/L0Kj7dBWJ47JExTKhalDvAkoKsWbOm3CiU7u7u2LBhA1544QVR+o0QcP9bu3atZF4z\nYih3kzedCCHHCSHHhR59HByA//6XJXOWY9VuIDISaNwY+M9/ivt/z57NTDaffiqPHE5OQO/eLGJl\naYHjrl9nN6KyYreXhyFQnlTK/fPPWcC3BQtY1iqdjskrlm99UhLQtClQwruPUw5CB4XkUu6ZmZmC\nvvVKKXeAJeI+e/ZsqSvy0aNH48yZMxgk4inKwYMHC4aDkOpQmRhqNA1A0XVkXQB/l6xEKZ1PKW1P\nKW0v5CPq6Ai8+CJTcHLi4gJ8/TVw7hzwwQfMPBMfz5T7qFHixJE3lYgI5t9fmhlu0SL2bo2nSJUq\nbNUrhXJ/8gT48Uf2e7zyCovj8+uv7OCUIemKtSQny+YGaVN069ZNML67HHFmDh06ZBTq1tvbG888\n84zkfZeFt7c3Nm/ejEuXLuGDDz7ArFmzsGLFCly7dg3Lly83SlVoLZ6enoI32bUGW6vIiKHcNb/p\nFBHBzDPff8/MFkOGsOBiJoafEI3QUOaeKRB8DoWFbDXcty9g7Zzz95dGuS9fzg5iTZ36b9mIEcyE\nZEUY7X/IzWUmHpk2U20KDw8PtDLY5Iogh91dTSYZIby9vTFgwAC89957GDVqFOrXry9ZX2ECm2Ub\nNmyQpC+rlbstbDoRAvz8M/DttyypxYgRzLRQo4a8cri5sRtNdDTz9y/Kli3AjRvAa69Z34+/P1sB\nm3I611QoBX75hd0ciyYQd3JiN874eOvT/KWmspucj4917dgrSplmhJR7NylieWiAYcOGGZWdPn1a\nklgzoli3bWHTiRDm3bF1K7BkCVCrljJyjBvHVr8LF/5bptMxF1EvLxY2wVr8/dnGp8HzRAwuXGCJ\nzCdMMA6JEBnJlPyyZdb1YUgyz5W7ZSih3PPy8nBY4Oi1mlbuclK/fn3BU7mbxLJbFkGV4QfsmR49\n2L7Df//LQh4DzNZ+8CBT8GLEUzHMLTFNM4a5KeR/X6MG+72s9foyKHduc7cMIY+ZCxcuCPp2i8XJ\nkyeN0tLVqFHDKp9xrTNYIG4IV+52ACHM1v/4MfMymT0bePttoGtXtqoXg+bN2U3i3Dlx2gOAjRtZ\n7JpnS3GCDQ1lTwrWPC0kJrLNYBnPvdgUNWrUQMuWLY3KpVy9l2ZvNyWioq0iFJtmx44dgrlZrYEr\ndxXi48M2T8+fB959l9mxlywRz0XU2ZkpeLGUe3o6e7IoK5CZIc9rbKzl/SQl8c1UaxEKASylchc6\ngWmvJhkDnTp1gqenZ7Gy7Oxs0Te3uXJXKePGMc+QI0dY/laxYzz5+Ymn3LduZRudZQXLq1ePJQux\nVLnrdEy5c3u7dQgpd/xbKiYAAA9BSURBVKkiROp0Oq7cBXB0dER/gcw/mzdvFrUfrtxVTLVq7OSq\nFE+wLVsCV68y84+17NjBkp8IZHQrxsCB7BCWGekr/+H6deZBxJW7dQjZ3c+fP29SViJzuXDhAtLT\n04uVubm5CYZCsDeEQhFw5c4RBcNJ1QsXrG9r716ge/fyzUZ9+rAVviXRTLmnjDjUqlULDRs2NCqX\nwt9dqM0uXboYBdCyR4RW7snJybhy5YpofXDlbqcYlLu1pplbt4CLF5lyL49OnZgv/44d5vdjkFNg\nP5BjJgEBAUZlUphmhJS70JODPVKrVi3BJCpirt65crdTGjVieWGtVe6GvThT/mcrVGD1LFHuCQnM\nE6fEPhTHAoSU+87ywpGaCS0lGTZX7v8iFLeGK3eO1Tg6srg51p4a3bsXqFyZhRI2hT592MZoWpp5\n/Zw9+69/Psc6WrdubVSWlJSEv/82CgllMampqUZxa1xcXCRPhq0lhOzu8fHxyBPp6DhX7naMn5/1\nB5n27mXhBpxMTNhoCAxnjhUgP5/Z3AVCo3AsoFq1aoIKXszVu5CZJzAwEK6urqL1oXU6dOiA6tWr\nFyvLyckRjKBpCVy52zH+/sxmfv++Zdenp7OVvzlhQlq1YqYVc5R7SgqLg8NX7uLRWyD8qtTKvVev\nXqK1bwuU5hJ59OhRUdrnyt2OsTYMgSHncufOpl/j4MBCEZij3A3y8ZW7eAgp9/j4eFESR1BKBRM8\nC/nY2ztCphmhWDyWwJW7HWOtcj94kClrc82ovXoxH/urV02rn5DAzD78dKp4dOvWDU4lbGnXr1/H\nxYsXrW47OTkZt2/fLlbm4uKCzuasAuyE/v37G4ViSEtLQ0pKitVtc+Vux3h5saBeCQmWXX/oELtB\nCOQbLhPD07mpq/eEBBYuwcS0lxwTqFy5Mjp27GhUvq28PI8mIGSS6dy5M7e3C1CzZk3Bv4MYgcS4\ncrdjCLE8cUdhITPLFI3dbiotWwI1a5afDBxgceKPHgUEXII5VtKvXz+jsq0lkwlbwPbt243KuL29\ndIYOHWpUJkYCD67c7Rx/f+brXlre1tK4cAHIyjLP3m6AEOY1Ex/PlHdZXL3KQh8LLG44ViK0mbdr\n1y6rXPEKCgoQHx9vVN6nTx+L27R1hKJE7tu3D48ePbKqXa7c7ZxWrYDsbBakzBwOHmTvlppR+/Zl\nnjrl+dkbNm25chef9u3bG0UnfPLkCQ4cOGBxm8eOHUNmZmaxssqVK3P/9jLw9/dHvXr1ipUVFBRY\nbSLjyt3OMbg7m5uA/dAhZlpp3Niyfg0LOYEn+GIcOQJUrMjdIKXA0dFRcEVtzSlJIYUUHBzM48mU\nASFEEtMMV+52jp8f80Q5edK86w4eZKt2SyNW1q/PkpCbotzbtRMnAxXHGCHTjDVKRUi59+3b1+L2\n7IWSppmqVauicuXKVrVp4rlCjq1SsSLb4DRHud+/z4KFjR9vXd99+wJ//MFC+Qo5UuTlMbnefNO6\nfjilIxTfJCkpCampqWjSpIlZbT148EDQR1to45ZTnF69eiEgIADBwcGoV68e3nzzTaufdvjKnYO2\nbZkSNfX8iuH/11q35WHDmL2/tEBiR44AublAUJB1/XBKx8vLS9AebsnqPS4uDroSO/Pe3t5m3yTs\nkYoVK+LUqVP4/vvvERAQIIoZiyt3Dtq1Yx4pN2+aVv/gQWbKsdY9sWdPlpAkJkb4+40bmTmGO1pI\ni5C9d/369Wa3I3RDGDp0qF3nS1USrtw5MCTGOXHCtPoHDrAokG5u1vXr4gIMHQqsX8+Cg5Vk0yYW\nIrhKFev64ZSNkHLfu3evWdmZ8vLysGXLFpPa5sgDV+4ctG7NwgiYYnd/+pSZS3r0EKfv8HDg4UPj\n7ExXrjA3ybLysnLEoVWrVmhUIkmvTqdDTGmPVALs2rULWVlZxcqqVKmCbuZEleOIClfuHLi5sdju\nBp/ysjDYwcVS7v37A9WrAz//XLzcYBUYPFicfjilQwjByJEjjcpXrVplchsrV640KhswYABceMwI\nxeDKnQMA6NqV2dILC8uut2cPc38Ua0Hm6gpMnsyUuSGfa14e8MMPLOF206bi9MMpGyHlvmfPHqMA\nYELk5uYKrvJHjBghimwcy+DKnQOAKeusLKC8PAF79jAzTrVq4vX95ptMyX/6KQuDsHAhcO0a8Pnn\n4vXBKZs2bdqgcYkTaTqdDkuXLi332q1btyIjI6NYmbu7u6CbJUc+uHLnAPh3Jb5/f+l18vLYyVSx\nTDIGatQAPvwQWL0aCA4G3n+fuT9y92j5IIRg9OjRRuULFiwoN8a70A0gJCQEbtbuuHOsgit3DgCg\nXj2gQQNg377S6+zZww4cCeR5sJr/+z9g+nR2cxk4EFi61PLTrxzLePnll43KUlJSsL+MO/6tW7ew\nbt06o3KhGwVHXrhy5/xD9+5MuZe2UNu4kZ1olUK5E8LMMo8fA6tWASWcNzgy0LhxYwQHBxuVz507\nt9RrFixYgIKCgmJlXl5e/FSqCuDKnfMPwcHAnTvAqVPG31EKbNjADhRJ+bRdsaJ0bXPKJzIy0qhs\n9erVSE5ONirPzc3FvHnzjMpfffVV7iWjArhy5/zD0KGAoyOzfZfkwgXme87PpNg24eHhqFOnTrEy\nSim++eYbo7q//fYbbpY41uzo6IgJEyZIKiPHNLhy5/xD9eps9R4dbWyaWbOGvXO/c9umQoUKePfd\nd43KFy9ejKNHj/7zc1ZWFr788kujeqGhoahbt66kMnJMgyt3TjGGDwdSU4un3svLA377jR04evZZ\n5WTjyMNrr71mlMSDUopXX30VOTk5oJRi4sSJuHfvXrE6hBB8+umncorKKQOu3DnFCAtjQcF++unf\nsuholjXprbeUk0tuCCGzCCFJhJAEQshaQoiInv3qxt3dHR999JFReUJCAgIDA9GnTx8sW7bM6Pvn\nnnsO/jyrimrgyp1TjFq12InRqCi2sZqVBXz9NUusIZDXwZbZDsCPUtoKQAqADxWWR1beeustBAQE\nGJWfO3cOOwUym7u5ueFzfupMVXDlzjHik0+Y/T08nIXlTUpi4QAc7Gi2UEq3UUoNPn6HAdiVIdnJ\nyQkLFiwwOa74//73P6PgYxxlIeWdPpOC9u3b0+PHj8veL8d04uOZkj9+HFi0CBgzRmmJTIcQcoJS\namW0+WLtbQCwklJqbItg308AMAEAateu3W7FihVGdR4/fgx3d3exRLIKc2TZtWsXvvjiC6MkHEUZ\nOnQo3nnnHcllkRK1yAGULUuvXr1Mn9uUUotfAEYAOA9AB6C9qde1a9eOcrRBfr7SEpgPgOPUtPm7\nA8A5gVdIkTofA1gL/UKovFdpc3vXrl3S/cJmYq4sq1evplWqVKEAir0cHBzo559/TgsLC2WTRSrU\nIgelZcti6tymlFqdQ/UcgHAAxicZODaBkw1n2aWUlpnjiRAyDsAQAL31/1h2yfDhw9GrVy/8/vvv\nOHToEHJycuDn54dXXnkFLVu2VFo8TilY9a9LKU0EwNNocWwOQsgAAB8A6EEpzVZaHqXx9PTEBx98\noLQYHDOwoy0yDscsfgZQGcB2QshpQshvSgvE4ZhDuSt3QsgOAF4CX31MKY01taOim04AHhNCjINV\nMGoAuG9quxKiFjkALosQZcnRwNrGKaVNLLnuxIkT9wkh1wS+Usu4AVwWIdQiByDS3BbFW4YQshvA\ne5RSq11gCCHHqYieDlqXA+CyqFkOU1GTvFwW9coBiCcLN8twOByODWKVcieEhBFC0gB0BrCJELJV\nHLE4HA6HYw3WesusBfMBFpP5IrdnKWqRA+CyCKEWOUxFTfJyWYxRixyASLIockKVw+FwONLCbe4c\nDodjgyim3AkhAwghyYSQVELINIHvKxBCVuq/P0IIaSiBDPUIIbsIIYmEkPOEEKOgtoSQnoSQDL2v\n82lCyCdiy1Gkr6uEkLP6fow8jwjjJ/2YJBBC2kogQ/Miv+tpQkgmIWRqiTqSjQkhJIoQcpcQcq5I\nmSchZDsh5KL+3aOUa8fp61zUny6VHTXMa30/fG4b92Ffc9vUOAVivgA4ArgEwBuAC4AzAHxL1JkI\n4Df959FggZvElqMOgLb6z5XBQruWlKMngI0yjctVADXK+H4QgM0ACIBOAI7I8He6DaCBXGMCoDuA\ntgDOFSmbCWCa/vM0AN8KXOcJ4LL+3UP/2UOOv1uJ8VJ8Xuvb5nO7/L+VTc9tpVbugQBSKaWXKaV5\nAFYACClRJwTAYv3n1QB6EyJunANK6S1K6Un95ywAiQDUnGsoBMASyjgMoBohpE55F1lBbwCXKKVC\nh3IkgVK6F8DDEsVF58JiAKECl/YHsJ1S+pBSmg4Wj32AZIIKo4p5DfC5bQI2P7eVUu7PArhR5Oc0\nGE+8f+pQFlc7A0B1qQTSPx63AXBE4OvOhJAzhJDNhBApIyVRANsIIScIO9FbElPGTUxGA1heyndy\njQkA1KaU3gKY0gJQS6CO3GMjhOrmNcDndinY/NxWKuaf0EqlpNuOKXVEgRDiDmANgKmU0swSX58E\ne3R7TAgZBGAdgKZSyAEgiFL6NyGkFlhMkyT93f4fUQWukWpMXAAMg3AGIjnHxFRkGxsrZZBVTj63\njbGXua3Uyj0NQL0iP9cF8HdpdQghTgCqwviRxmoIIc5gk/9PSmlMye8ppZmU0sf6z3EAnAkhNcSW\nQ9/+3/r3u2DnBwJLVDFl3MRiIICTlNI7AnLKNiZ67hge0fXvdwXqyDk2paGaea1vn89tYexibiul\n3I8BaEoIaaS/i44GsL5EnfUADLvCEQB2Uv3ugljobZ0LASRSSmeXUsfLYBMlhASCjdkDMeXQt12J\nEFLZ8BlAP7B4+UVZD+BFvWdBJwAZhkc6CRiDUh5b5RqTIhSdC+MACAWs2wqgHyHEQ+9x0E9fJieq\nmNcAn9vlYB9zW4pdYRN3jgeB7eBfAoswCQCfARim/1wRQDSAVABHAXhLIENXsMebBACn9a9BAF4H\n8Lq+ziSwbFNnwHJpdpFoPLz1fZzR92cYk6KyEAC/6MfsLMzIfmWmLG5gE7pqkTJZxgTsn+4WgHyw\nFct4MJt0PICL+ndPfd32ABYUufYV/XxJBfCyvc5rPrf53KaU8hOqHA6HY4vwE6ocDodjg3DlzuFw\nODYIV+4cDodjg3DlzuFwODYIV+4cDodjg3DlzuFwODYIV+4cDodjg3DlzuFwODbI/wMEpIYLST7Q\nvgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8ed7cbe80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(2, 2, 1)\n",
    "plt.plot(x, y1, 'r')\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.plot(x, y2, 'g')\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.plot(x, y2*y3, 'b')\n",
    "plt.subplot(2, 2, 4)\n",
    "plt.plot(x, y2+y3, 'k', linewidth=5);\n",
    "plt.grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "### Histogram\n",
    "\n",
    "Generirajmo 10000 normalno porazdeljenih vzorcev in jih prikažimo v obliki histograma:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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jo6oOVtXxFwH2beRvZVJVDwHP993HTKrqSFU92r3+OYMvsdX9dvWKGvhF9/a07jFSP79J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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a8ed7a7550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.random.seed(0)\n",
    "x = np.random.normal(size=10000)\n",
    "plt.hist(x);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Uporaba primerov iz ``matplotlib.org``"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Primere iz [galerije](http://matplotlib.org/gallery.html) lahko uvozimo s pomočjo magične funkcije `%load`.\n",
    "\n",
    "Poskusite:\n",
    "\n",
    "* `%load http://matplotlib.org/mpl_examples/lines_bars_and_markers/fill_demo.py`\n",
    "* `%load http://matplotlib.org/examples/widgets/slider_demo.py`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Nekaj vprašanj za razmislek!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Naredite slovar lokalno nameščenih modulov (uporabite izpeljevanje slovarjev, ključ naj bo ime modula, vrednost naj bo verzija).\n",
    "2. S pomočjo slovarja iz prejšnje točke čimbolj preprosto preverite, ali so nameščeni sledeči moduli: ['numpy', 'scipy', 'matplotlib', 'pandas', 'pyjamas', 'openpyxl'].\n",
    "3. Namestite poljubni modul iz https://pypi.org in ga preizkusite.\n",
    "4. Pretvorite navaden Pythonov seznam v ``numpy`` numerično polje. Preverite tip enega in drugega.\n",
    "5. Raziščite funkcije ``np.ones``, ``np.zeros_like``, ``np.arange``, ``np.linspace`` (ali zadnja funkcija lahko vrne korak?).\n",
    "6. Prikažite uporabo rezanja.\n",
    "7. Prikažite razliko med vrstičnim in stolpičnim vektorjem. Prikažite tipične matematične operacije med vektorji in matrikami.\n",
    "8. Ustvarite matriko ničel dimenzije 3 x 2 in drugi stolpec zapolnite z vektorjem enic.\n",
    "9. Ustvarite enotsko matriko dimenzije 5 podatkovnega tipa ``complex``.\n",
    "10. Ustvarite enotsko matriko dimenzije ``N`` in izračunajte vsoto poljubnga stolpca. Poskusite najti najhitrejši (vektoriziran) način in ga primerjajte s pristopom v zanki. Namig: np.sum().\n",
    "11. V matriki iz prejšnje točke zamenjajte poljubna stolpca, nato še poljubni vrstici. Preverite hitrost vaše implementacije.\n",
    "12. S pomočjo funkcije ``np.random.rand`` ustvarite dvorazsežno matriko poljubne dimenzije in najdite največjo in najmanjšo vrednost. Preverite možnost ``axis`` v funkciji ``np.max`` ali ``np.min``.\n",
    "13. V matriki iz prejšnje točke najdite indeks, kjer se nahaja največja vrednost.\n",
    "14. Na primeru preprostega diagrama prikažite razliko med *inline* in *interaktivno* uporabo knjižnice ``matplotlib``.\n",
    "15. Na primeru preprostega diagrama prikažite uporabo vsaj 5 različnih tipov črte in 5 različnih barv.\n",
    "16. Raziščite primere http://matplotlib.org/gallery.html. Za primer si podrobneje poglejte enega od zgledov na temo zaznamb *annotation*. Izbrani primer namestite na vaš računalnik.\n",
    "17. Na primeru preprostega diagrama prikažite uporabo zaznamb.\n",
    "18. Dodatno: Naredite preprosto animacijo.\n",
    "19. Dodatno: Izrišite več krogov naključne lege in velikosti ter poljubne barve. Ob kliku se krogom naj spremeni barva."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Dodatno"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## `numba`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Paket `numba` se v zadnjem obdobju zelo razvija in lahko numerično izvajanje še dodatno pohitri (tudi v povezavi z grafičnimi karticami oz. GPU procesorji). \n",
    "\n",
    "Za zgled tukaj uporabimo `jit` ([just-in-time compilation](http://numba.pydata.org/numba-doc/dev/reference/jit-compilation.html)) iz paketa `numba`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "from numba import jit"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "`jit` uporabimo kot [dekorator](https://docs.python.org/3/glossary.html#term-decorator) funkcije, ki jo želimo pohitriti:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "@jit\n",
    "def skalarni_produkt(a, b):\n",
    "    c = 0\n",
    "    for i in range(N):\n",
    "        c += a[i] * b[i]\n",
    "    return c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Sedaj definirajmo vektorja:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 1000\n",
    "a = np.arange(N)\n",
    "b = np.arange(N)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Preverimo hitrost `numpy` skalarnega produkta:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5.54 µs ± 2.9 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n1000\n",
    "a @ b"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Preverimo še hitrost `numba` pohitrene verzije. Prvi klic izvedemo, da se izvede kompilacija, potem merimo čas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "332833500"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "skalarni_produkt(a, b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.74 µs ± 344 ns per loop (mean ± std. dev. of 7 runs, 1000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n1000\n",
    "skalarni_produkt(a, b)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vidimo, da smo še izboljšali hitrost!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## `matplotlib`: animacije, povratni klic, XKCD stil"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Z `matplotlib` lahko pripravimo tudi **animacije**. Dva primera lahko najdete tukaj:\n",
    "\n",
    "* [Preprosta animacija](./moduli/matplotlib_animacija.py),\n",
    "* [Dvojno nihalo](./moduli/animacija_dvojno_nihalo.py).\n",
    "\n",
    "Več v [dokumentaciji](https://matplotlib.org/api/animation_api.html#animation)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Slika s **povratnim klicem** (angl. *call back*):\n",
    "\n",
    "* [Risanje črte](./moduli/matplotlib_klik.py).\n",
    "\n",
    "Pripravite lahko tudi *na roko* narisane slike (**XKCD stil**):\n",
    "\n",
    "* [XKCD stil](./moduli/xkcd_stil.py)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "## Za najbolj zagrete"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Naučite se še kaj novega na [chrisalbon.com](http://chrisalbon.com/)."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  },
  "latex_envs": {
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