{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# First\n",
    "My first PyROOT interactive session\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Wim Lavrijsen  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 24, 2022 at 04:09 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to JupyROOT 6.27/01\n"
     ]
    }
   ],
   "source": [
    "from ROOT import TCanvas, TF1, TPaveLabel, TPad, TText\n",
    "from ROOT import gROOT\n",
    "\n",
    "\n",
    "nut = TCanvas( 'nut', 'FirstSession', 100, 10, 700, 900 )\n",
    "nut.Range( 0, 0, 20, 24 )\n",
    "nut.SetFillColor( 10 )\n",
    "nut.SetBorderSize( 2 )\n",
    "\n",
    "pl = TPaveLabel( 3, 22, 17, 23.7, 'My first PyROOT interactive session', 'br' )\n",
    "pl.SetFillColor( 18 )\n",
    "pl.Draw()\n",
    "\n",
    "t = TText( 0, 0, 'a' )\n",
    "t.SetTextFont( 62 )\n",
    "t.SetTextSize( 0.025 )\n",
    "t.SetTextAlign( 12 )\n",
    "t.DrawText( 2, 20.3, 'PyROOT provides ROOT bindings for Python, a powerful interpreter.' )\n",
    "t.DrawText( 2, 19.3, 'Blocks of lines can be entered typographically.' )\n",
    "t.DrawText( 2, 18.3, 'Previous typed lines can be recalled.' )\n",
    "\n",
    "t.SetTextFont( 72 )\n",
    "t.SetTextSize( 0.026 )\n",
    "t.DrawText( 3, 17, r'>>>  x, y = 5, 7' )\n",
    "t.DrawText( 3, 16, r'>>>  import math; x*math.sqrt(y)' )\n",
    "t.DrawText( 3, 14, r'>>>  for i in range(2,7): print \"sqrt(%d) = %f\" % (i,math.sqrt(i))' )\n",
    "t.DrawText( 3, 10, r'>>>  import ROOT; f1 = ROOT.TF1( \"f1\", \"sin(x)/x\", 0, 10 )' )\n",
    "t.DrawText( 3,  9, r'>>>  f1.Draw()' )\n",
    "t.SetTextFont( 81 )\n",
    "t.SetTextSize( 0.018 )\n",
    "t.DrawText( 4, 15,   '13.228756555322953' )\n",
    "t.DrawText( 4, 13.3, 'sqrt(2) = 1.414214' )\n",
    "t.DrawText( 4, 12.7, 'sqrt(3) = 1.732051' )\n",
    "t.DrawText( 4, 12.1, 'sqrt(4) = 2.000000' )\n",
    "t.DrawText( 4, 11.5, 'sqrt(5) = 2.236068' )\n",
    "t.DrawText( 4, 10.9, 'sqrt(6) = 2.449490' )\n",
    "\n",
    "pad = TPad( 'pad', 'pad', .2, .05, .8, .35 )\n",
    "pad.SetFillColor( 42 )\n",
    "pad.SetFrameFillColor( 33 )\n",
    "pad.SetBorderSize( 10 )\n",
    "pad.Draw()\n",
    "pad.cd()\n",
    "pad.SetGrid()\n",
    "\n",
    "f1 = TF1( 'f1', 'sin(x)/x', 0, 10 )\n",
    "f1.Draw()\n",
    "nut.cd()\n",
    "nut.Update()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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mF90123Kkdjw8A12mKdENe65m10zVfPSKUcSOe5iC22tZIayELvhozLyOuWORKkARfKyi+2LX7MzVTxPPn9Lh+tEzITwK+XrTld1FHovb/0DBnmpd8ImSE9pF4qUhS1yrHH4CM7FIWLZoINInUND7G7sL9nPoVnCfq7AMmeuL7pHcH7jPqi2P24XoW+FO2U+1q+1UTOMqxLY0YW1HK3auQCFT266K9N7Irml3x52Eq04nU9vuz+gRtFd5exvn6t+mZpdEP2KuwO4D5fYu/Dxmylye76vIfI4yaYZbucK43F120X107Z+rGZd19E7D1r/8efv27Wg1LhgoRE88d210lzVbANtyu/pxexS29G79zEni9jS8uNlPR5nuy8QAexsohKI3hdG3nDDmWDBQcN1lqTRVmGC4C+G7Nhe7vv38R+OksL0PyxmtN1lZ6y3f9Ze6Y0t19li2tjN5hRXbP1DI13aqYc5UUaYtWTydmZfFfOPd9esScyuH3JXdtiLRt8I/bTHCg2ULFr6bORNcVYSVmQkUolXkdiq1y5JIeTZ/037c3Ifa7lq0/mXJKgKF1Ccuc3GI1kbqSPVZ3+1O9CQP0+mysReWaG8nM1pyGdX5O+XZvEJdwU3tqYzCTJ3LzAAKp/xkpmulrrN5Ye42i2hPcnT90kzPlEqI9hO6RGzuurNHR0ej0Uhnceo8Tfmzrmt5Nz8fKqxtKZXmGG4uS2wHZmqdInvUMvpvFT2aYe4zD3p+hVQ6ejTlWEwmkz6zz2wF2vTtGTXXWepu6+WFHEedZ9onHVvt9nQdUKRMFnpm9pl96cpmJ2OGZZOKlTXlYd3ibN/btrXvajoDSrJcc31A9CMfTkrteQJn1u9/XLTedLKzPe151Hbp9vB7FERZlqlnhauqOjo60gYpPF9L80S4fNpdq1/XtTsX7YVjPB5HowQ9+4edx03T9Lza5oUN8ODPlSuP3khVVaXfalAUxdHR0TQ90TqsbbenqdqWhVLbYYVv8MpbrOBS1TRNNE05yeu61lb56Oioyz4RmjFvS5zKSE6AIhaRzGvpz0doXCvnpH1YaV5t27qDIn/aWLxIxA2iHPTlExsU/cgvS//aCNccj8c8oLE6B9Gj4NhvPSpm3euEnQ2FuesV+qieXLU1QXsN0q+7GfzR0uuOfh7ySdmHDN36UkIJxlOJuH6XaAeM9gRoIrKbdV1XVXV6eqoNyVyXe13Z3YoJre3q7Dlvt7xIXJTnEtbesAt6tAIH0Dqx6djalh5CXZ5PLew/WHpcJaeEnGPDqi56xxldHmrOpFaQKKF/74vLPezHcrcKulDXdx8B+2HU7rR5ubKtgUyEsh/5PFfCzN1CcfZdc/nEw4vPzAIQQCzBBoc9VkT2KzpFQNnTK9zWDnGlBts0F30dnXkws8L7z1HQXFxS4eZ2HpabVeT21G1ol9hEbAHCaVBuxNFmbSfi9dnx1OBlvrbdLVqf2k5VdSrH6EitG8SNvhtW4BLTsTPswgOR33Fbk27DsDxOJiOV/4iVweOR0ayjhXTnp0u5ik1BDQtQnP8oZc5PV/PhpyO6p/YDYmsjnFVgW7syPUdElugcBXtmFoZduecchdREBzeBw+6Ce8vNG+jOH/2wfsL1o7VRzZrX4uot+unOVAX6O9BAwZ6X4bbRRjcaPaj8hSZTpLkmM4ZXhGiZwxKGWYfphElFG2A3mymsgbByqtj8snzFRqOHJdZ2+JarhD61nW/gu0RMuWA6rhXpcypGdzysMXcEFwwUusQn0V3cdadSWbsDkWrVut6BQvSsDnfWhgJh7tEKjG7uAovMZaSMTWx0e6eBQnc+onWbhHm5rfoECnYH88ciEyiE9xjR9cPaqIKJomFlunojUFidx7qhw5m7TsYFMmPnM9mpSYuvliHfPCgR9FypLZ51PpFMt/ziEyD6F2PAasvNdGYii5dHS6LfVmk/uYNre+mHyUp9xAbU6oBNZFAmdX2beVBsPQ/7CPS0yDm23LO9ZxZ9MpXKl4liS7lkDSsGluUQAwUZwJYxs53YfRsobLosWDdpbnVyrpwMmbm6W0LnV27kIybN/CIfmWhAhp5soLDpsmAJ9vaphwz78wGbLQkw03Q6lYd07NzYLb/+2l/f2EgBCKyBJTrEHgWdvbwr3VaN+fXkTZcFm6HPcezEabAHZ+ziD84csj04AWAdYqAAAAB6OsTvUQAAAD0RKAAAgCQCBQAAkESgAAAAkggUAABAEoECAABIIlAAAABJBAoAACCJQAEAACQRKAAAgCQCBQAAkESgAAAAkggUAABAEoECAABIIlAAAABJBAoAACCJQAEAACQRKAAAgCQCBQAAkLSHgUJd15Pz6rpumkZXaJpGli+Sy1ISmUn2pa7rfO7y2u7j7pJdC3d5z6SO7J7JH83FK2GPPwjA9nh80wVYibZtwz/Lsjw9PY2usJRclm4ymWgWVVVlcl91SdapbVvZnXCX16BpmqOjo6Iouq5bdUZt247H4/Ctuq7ruq6qaiM1sFztmei+SCUUCxxrPVv0z2HpAMjYz0BBTKfToijatpXrkbyIXpq3k15DZ15GZU93aNeQITfETdPsQaCQt/c7COyHPRx6UOPxeDweV1XVpyNBBywy/fyZXs1wJCKTYJ+s9XXTNDO7UuUeVBsYHW1JFUBzdCn32dP83tkU3O5ImplSOQPK36eQtjNci2o3cS/6pCP1P7PY+lam2HqT3batPYipfCW1TIX0ObE1BXcKuV2zg3qakS1h/siG78o+2k9l5gyM5p4RrbfJiscKgf3U7R29TUktkfvv8M9otYQ3PVVVuUT09XQ6la161nMma7ukLMvUhnZlyT16l6YphDnK7kQ3DPMVZVlGy5zZnXCTVPrzln/eQqbuYsPEpT5npiMrSDWGK+spEc1XKz9VbHdwdQXZ6+iO6JrznthaHveWLExlFM2lyNa2HjK7L9GVMx8od7bb1eQtW3hdM3W2AMjY50AhddGJtrJyBdG39IJiLzf2qmQTiV6SXPphkzBX1k6fQKGqqul0qg1PmKaLb6JvZarXbiVlttd9l7gWI1qqaPqSjssuk0WmkHYrm/50OnVrpoLITDq6U6ldtum4eCJ6cF3z6f4MKz9M1q4514kdBgqZXYum7PbU1bYrYTSdcF8yH6hMoJCpNwBzOaBAIbwr7WItol0Sdk6UZemuay7xLmiqU+XMZ91lL219AgVd2b7r0rTXXN2XaOtla8BVZlmWGl6E0Zi97kcPgROtc1fI6O11ppA2zXz9uILNlY67Z82fSJmqztRVJsZ1+zLviW3LE74rm7t0okXqEuGUy6jPmvpZi+Ye3SpzKMM9AtDTPs9R0J2cns1q7PMgVjgl0PYGn56e6owHy46z6sWrruujo6PRaNRzZHSJsxGjXf06siulGo1GdrkttrwbHQmWPdWijsfj09NT2XY8Huu28uyAM2wHZSs7V0PLn5p0osP8strgB/DmSkeKpytrDWjJ7UGJHqAorbTUMwJhrUarJX9izyxPuF/5As/7AEJYRfaz1j93VwxJWQ5c/zoHYO3zUw9qPB6XZSlPPSx9orWkXBSFPNImC7uuk8uTtjSTySQaYVhre/7bVYLesldVJRPopNhHR0fT6bR/6z45e55TttJAZEFhtUTLHyrLcimx11zphCtL/ORWm6sdlXNMI92ZDV4+TBxA29qqqqQw6/wGCJ1QKbm7+Y8Zcj5rUXnIAhhmn3sUlLZ8IXvbIS/sFVAuuHZbeyMu9H7aTg6X16enp91Z72hYgDDrVT8FrjlWZ7RFkZZAYh0pdqpIsomtLq0TGyUsXlpXLfIMi5bBlT9aSLunw8owVzph9bq3Bh9fd4K56rUPXOgK+bMrPLHzZdMApaqq8XgcjTnscxDF/LfvroqaptHzSqMEyb1/Nepuum6w5sxcJQQO16bGPFYnczXPjEMXZ/cr+lre1W3dJLvMaLFrXexbTp+sh81RiI5bp3J0u2DfCnO3g8RuElxYV8X5OQq6a33mKBTnG5uwxtw8xGghw0PQc45CdX5SZ590XB3alW3l2J3KzFFw+xXdpDDCHHue2GF5UtMvXFJF8KiIzCqwhe8/R6FLf9aiOzJzjkK4m66Gox9JAKFDCRRk0rWskJp+5S6XbmV7cQwTcY1WWIBUaTNZh1e9sFThmvlAIcxRl4f1Fm3GwjXDuX6FaTPstX7eQCEsZKb88xYyVT8u5f7pdMHZYo9CeCKlatjNFnR7bdfUXGyadoX+J7Y9QJkYSNPRFWzgGGY0V6CQqr1oUYv0AxH2lIhGkwQKwFwe61b8VbU7RLoio93mtlN3rtR6bpXJehUyu9N/T1Nlbpb39Zczj8iKKjbcaq50llXs4nxvefjd0tIzL70dwzLVt2R+SX54JZqOLdhSTuPUGTj4UK7nO7mBPUagAGw7be1cQ24DhWEJyoQS9+ewpLbwSqITikvzOy8A5nUQTz0Au0tb4mJ58/b1OSD7tKFMFVxK+ltC944oAVgEgQKw1eT3SopYlKDzUQYke3p6qk8DLfgc6bLCl6VL1RuAuTD0AAAAkg7iexQAAMAwBAoAACCJQAEAACQRKAAAgCQCBQAAkESgAAAAkggUAABAEoECAABIIlAAAABJBAoAACCJQAEAACQRKAAAgCQCBQAAkESgAAAAkggUAABAEoECAABIIlAAAABJBAoAACCJQAEAACQRKAAAgKQ9DBTqup6cV9f1KjKSxFeR8pZomia1j1LJWrH7VBWya03TbLogMyzlEGQOMQCIxzddgOULw4K2beu6nk6n4/F4Wbk0TdO27bJS66Ou67quy7I8PT1dT45t26b2UXe/qqr1V8VKyfnTtu0Sz5YV0UOgrwcnAgApexgoiLIs9QIql/6jo6Ou65aV/ng8nk6ny0ptp1EVALDH9nDoQY3H4/F4XFWVRAzC9rXKPbpbbrthw15oWUGW2M3t+uFgh0tW8rLr2OGS6L40TSOZatwTTVP3SwqpC11Hut3Z1FtzjdfYqghzd0lFqzqsh3znf6qqbeL2LU1TN5w5uJBaM1N7bls9UrpaqtgD9mimzJ4OSA3A4er2juxXWZa6RAOFruv03rcsS13NRhJiOp26De227rXNN0xE39I/JVktYWZDJaW1R01eVFUVpulWdmuGd/+Zt9w+uvJIdq4qoim4cmZqKV8PqTVTiWcqOZV+fs1M+aP1Y9dJFTt6yGST6BEJj7gmvsRDDABiDy8QcuHTC6i9Mro/y7K0V/AwOHBNoL00u7dck6B/2iJFAwUXi9gG2HENg1szmrs0D9HCyFvRNj4MnsLC9AkUqqpyld+nqqMVGGYd3crumqtYLcZ0OrXBYpi+LX++9lwW0ULmy+Mq0O67jfmiRzkTKMxM3NVDdBcAQOzhBaJIcLdo4T2i/Jlpe6Lp2EztzWXm3WigoFFLimsYogWQ12Erq3uR6giJvjWztc4ECmEXQr6qbeOdr4ewMnUTSUdeRBvmaKmi6dsYIixkqjCZqpMl0QK4aGA6ncoMG/3TVZeNPDKBguuqkTWjp2K0HgBA7PMcBSUNiZvErn/qCO5oNBqNRkdHR3Y1uZLaUd7MZPjwrZkD4Xqlbtv26OhoNBqlpimk8pJx98J0dAv7p77WKe6jM7pOOPt9KdP+bTFSVS2PGMiaPetBy1ZV1enpqf5Z17WkHB2Ajw7K5NNX9hkQV3upBwdsdrKOFG80GtniyVua43g8Pj091RNDN3FnZopWslSjPcT6lubVv0IAHKx9fuph3scI3fCzXEyrqqrrWqcQruLC2nWdPGGoD+aNRqOuxwMaUjZtcsLhcxW2ZG7l9TQY4/HYPtHnCnN6ejqsHpQ0pfrAS8+WtaeyLLUaB9deWZZhCGJTdiaTidZYVVW21Z9pI4cYwP45iB6FPHtv6h6RsKT1yjTGhfkKh/DWrTCttXveQVPuYnPlMvQW3N2Suuzs+nb6gtvZsItldbPiw9y1X8RNnkixXzQkN+habOlgWPDrAcJDWZi21nIDqS0AACAASURBVJW/T9eLbKuP4YTNtq127QmQvbAjKTPZ3gKXl+13cS+0DNv/TVMA1m2jAx8rIfsVnafWxZ5WsJtEZ/BFF0bnObpEwin3bjjAbugazrDkdk1Xcre/biadS9OW0w2l65/hQxZO/zkKqfmSLndXD5npEXbN6NS86HHU1VwiYfp2x22FzKy9VP24erAH2kVFtuR2Wkxx/jjOnKNgAxo3zdaenPYoR2sJALo9nsw4V6AQ3r/OTDNMJ+zpTaXvWpHUo3GpkkcztZu4Z/PCPcpkF5YzrI1ugUAhU9U96yFcU1eLRkhVMBG16zeZMVrIsPzRQkafXsmcIam3bHbatNsQMxooZKrIvRV9poNAAYD1WLe8LyvcddHxgmGJRFPIvNU/d5dI0zQyEm+Powxsy51rKtNMdvlyLsXM3PsUIFrO5RZ+QO0NTnNmdkvMaw2HGMDeIFDYYTKu37atm7lpA4UNFg8AsAf29qmHQ6Cz+tf2M1EAgEPzv7jp3GnyzL1b+MQTTzzxxBNlWT7xxBObKBQAYH8w9AAAAJL4HgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkEShgOUaByWSS36RpmnAr0TTNWkoNAJiBQAFLEG3Xx+Nxfqu2bVNvzdwWALAej3Vdt+kyYG7SMNvWNFyS2tCt03PDvMlk0rbtdDpdJJ2maY6OjoqiWDAdAMASESjsHm1Qy7I8PT11f2Y2lOa8KAo96OGSYUaj0bISIUoAgK3C0MNCJpPJZDJJDajn3x2NRnVdD8h0PB6XZVmcdd33jBKiJIXpdDqgGEr3QmcYDNgviRKqqiJKAICtQqCwkLZt27Y9OjqKto75d4uiqOtaJv3NO3evqip5Ie1rURR9ogTXBstkw7Isw7ZZCtZzfmJY+Lqu59ojLYnuFwBgSxAoLMQ2bGGrH75rwwV9Nx9MRLmmvWefv/RDKOlOiEYYqWY+dbtfluV0Ou26TkuSmajo1HWdKQkAYLOYo7AcdV3bZt7WatM02hbO+26GTi+Ya1Bf5wFIplVVLf0mXgcReqbM1AQA2Gb0KCyfu3Evzt+Iz/tulI0tBkwIkDGR4nyfx3L13xF5QZQAANuJHoWFuI6EwtxJN03Ttu2wd3tmWpale2ZBE0ylo3MaMtnpYxSh8Gxx/QfuMQotZyoOoDsBALYcgcJw+UZ3kXcztBWXrSQdfeTB/RnShrxIj3HYdaxosnZHlDT8M78XQSMeTkIA2FqPb7oAu0qm+1VVFb1d1nejEYC0jsPmB+jDkLKtdCq4dr3P3Xnmkci5JhVOp1PX/aBhgZYqVR7tb+ifHQBgzehR2Dej0ShzTFd0E69PSYRf+3h0dMQ5BgC7ix6FvTKZTFI36HZWxILfsBSK9hlIlLD0vAAA60SPwv6YTCbj8XjmNMZVPBKZypFZigCw6wgUDoV8+yHfkQwAmAuBAgAASOILlwAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQ2FV1Xdd1velSbN7du3fv3r27osSbpmmaZkWJOyvdkWFOT09PT0/z6zx48OD27dvrKQ+AjXis67pNlwFza5rm6OioKIotOXxN07RtW5bleDxeaUYSG2lGd+/efe2114qV1cNkMhmPx1VVLT1lV2Onp6dPP/10saEDKoUpisLuqRTpzp07+fDl9u3bP/jBD27duvW9731v1eUEsBH0KOyqsizLstx0Kf7k6OiormtpbFZK+lE0o9XlOBqNJpNJ27ZN04xGo6X3K7gaW0PVZUitun18+umny7Kc2ckh8cGHH364stIB2DAChZ0kt7naLWy7iF1fcdh77FZO9S03Z6LL9bV9KxW4ZDZJ9e2fnnEru4ykfb1z545uFS1Aisvd/llVlSTetm1VVXrf37+eMzuidEekX0T/7LkjmZGRVJ1Hl8ue2t6g0WikxZh5GhQECsB+67CD5NhVVdV13cnJifyp7aW81uX2QEdXdqfBdDpNnST6lr5w3fLT6dQVVVewa1ZV5TbU9cNo4+TkJFwuGUX3Rda3qZVlGdahJihJuT9tJWSq7s6dO6madMu1YNEam7kj+QMkZ4Kr8MJ0O2kNaKbuhU1HiuE2sXUYTfP999+PlhbAriNQWIhciMPWsc+77vo+F9vG2NbFtab2T2l1UivfuXNHUtZmxg1tuHd1HdcsRSuhT/HcvtjcJdkwIxsJuVxcRUXr2cY6tuHUYk+nU1kuS4bV87J2JCy2Wzl/+KQGwgjDpWajlvAIugLoCleuXCkIFID9RaCwEHvNDVujnu9mgokod6V213FtoqTF0kbI3Zfr3aptk6LtZTQvuzuZVs3upkvB3bjb23qNWlzKLmu3p9GSzIzk8scourL7M1PPuiPRW3D9U3ckteOWhgLypz0ZbOgTrW3bu5PaL9edkNpxmwKBArDfCBQWEs6Ht81S+G6qi7hPQxVuKH+6NsZd1rUBsyunmoGwo94FJdFy5gsfbbo0C7cvWuY7d+5owVzzmQpiwqqYyd5Pz6z8ueq5z46EzXmfHXFdDjYGCtNx1RsdiHGnhKxjRz1sImF3QsfQA7DvCBSWIzXi3nXddDp1d679342K3p6m7qr1btW+a1sgm1rYZEaDEts4hZ0Qbu+iTWCqjYxOh5RdSyVl98VVxUzhRIQU12EQ5u7qeaU7EqZsl2d6C8IVwoVhbdgCh90J0U0A7BOeeli+sJGw88nnfTdk56jr9PjJZBItg6wsf+rKNhe7QviuzGyXJfr9TrbA+lxf9BsUUk/9RYsnjyMWwTC/7NrMpFJVkSHfRSHyD0Bq7n3q2e2IBhnL2pGu66bTqY1N7Zr5g1vEjm+4jqVHVp/ntFk/ePAgtSGAPbHhQGXHZYYP3KV8rnfzZGU3+0/eyt/4hmPh0TtO7Y2ITiBw50y0Nzv1br6DIVryItFtHnb1u6rouk6erchMJi1MA5nahWhFhbnbil3ujti9qKpKJpBmKlDfdTMSoqM8bmF0AKU734fh6lMmKNy6dStTewB2GoHCcPbqOXgmY/TdjOhMxtRAQ3e+0Up1G7ix8yI2V78Lwgi3SbQ9TjVd4b7MnPnvMkrtaSrKcWzDr6XKTCl1iefjswV3JDq0JHVoD4pN3D6tkHo3E+dp+jMDhTCciq4PYJ/wCR9I2qHUDau+G91WWqZhz0b2mcmYulvVlQvDDoTnH9APl3Tnm66wtLahCosXnWrnCukm2emSsCcjWhXRNsxFBrrXmU4FV1f5+Cy6I+G7fXYkDHeKgL7lDl++u8hVhVvN7b57ekLdunWroDsB2Hf81sMBka/bOzk5mUwmMhAeHQXXceueP9wg6y/lVx4ypRqQkXwt8bxf17gUy92R6OYiTEQT16kS+c+4O9xykrhNJKmyLF1lRlcGsGcIFA7FZn92aP3kd7Om0+mqf6dqa0krHn4JZp7EBBJNFme/FyXzWN2ZU5blhx9++P777//lX/7lUgsOYLvw1MOh2OzPDq1Z0zR1XR9ylKD6PEdjyViJnC0SbEmU4KKNBw8efPjhh7du3SJKAPbe45suANbHzXHbY+PxmBBBjvW89TCZTOyXROkXJ4Tp0JcAHAiGHgAAQBJDDwAAIIlAAQAAJBEoAACAJAIFAACQRKAAAACSCBQAAEASgQIAAEgiUAAAAEkECgAAIIlAAQAAJBEoAACAJAIFAACQRKAAAACSCBQAAEASgQIAAEgiUAAAAEkECgAAIIlAAQAAJBEoAACAJAIFAACQRKAAAACSHt90AdBX0zTj8ThcWBRFuDy6ebhmavO6rsuytMtlTaHLowtTievK0WRnLpxrF1L7FS6fKy8AOED0KOyGuq7rug4XSksWvuVMJhP3wm5lF8qfZVm2bauNqE0/9Tos7Xg81oY2umbTNG3bRjfPLLSlTe2XJOvSmUwm4/HY7tdceQHAgeqw9abT6XQ6raoqtULmLU3BJuUW2hRsUtFkZ65gsxiwZmrl6Lv998uuMHMXer4LAIeAoYcdIPfl0Zvv4myYoE8KkkhVVW5h0zSaQlmWdV1XVWUXKrdQb83tOIVkEQ6U6G26FqAwd/92YTRZl8i8+yXryFtN0+jK/fMCgMNEoLDbbC/6TNGQQvr/bSvbtq10uZ+enrqV7Zp2BR0EsRnZiQ4uOJA/7djEZDLR1PSFDBYscb+k7bdpzpsXABwa5ijstvF4XFVVqrPBCucnFkFrWpy14qenp6enp/1vqaULQdOsqqp/wXRH8snqkrIs3SSDPvsl24qZu5DKCwAOEIHCHmqaxjVvqda0OH+vv0iO+toFDYskq4MFKUvcr5l5AcBhYuhhB8j9sbR/2i7KQnk8wa1/dHRUFEXXdbq5bCuJyO1+cTZeoJtLy1pVlXTC24F8TcctsV0OtpNfZx7YsYnibAKELrS7oGMHqf0K87L7ZZcfHR3ZzgwtWDhJon9eAHCwHtPmBAAAwGHoAQAAJBEoAACAJAIFAACQRKAAAACSCBQAAEASgQIAAEgiUAAAAEkECgAAIIlAAQAAJBEoAACAJAIFAACQRKAAAACSCBQAAEASgQIAAEgiUAAAAEkECgAAIIlAAQAAJBEoAACAJAIFAACQRKAAAACSCBQAAEASgQIAAEgiUAAAAEkECgAAIIlAAQAAJP2vqqo2XQYM1zTNf/7nf47H42UlVRTFE088Eb5b13XbtkvJaOOapvnDH/5gd/P4+Pizzz67ePHigNR++ctf/vu///u1a9eWVr6YX//61//xH//xxz/+8Ytf/OKCSdkDnT/oK3L37t3/+Z//+cIXvrBgOrbwb7/99r/+67/+1V/91TIKOLww4/F4ndVb17V8JO/cuXN6evrHP/5x2Dk82N27d5um2arLwunp6R/+8Ac5u27fvj2dTo+Ojoqi+M53vmM/pD/96U//7d/+7ZlnntlYQXdLh91kI7ylJChJVVWVyWspGW2W7Mt0OpU/r169aj8Ot2/fjm6V+vhUVfXzn/+8KIqXX355pcWW7F555ZU+K0+n06qqdB+jSZVl2XVdWZb6eumixbhz505RFCcnJ/KnFMAu0ULeuXMnn77dkW984xtFUfzkJz9ZVsmjNTOdTsNPgSzUD4jdMF+9uu+uisqy7HNE7EdSXj98+LDvHg5SVZU9oHIoN3VZmHl2XblyRYv3s5/9rCiKb3/727rmzZs3i6J477331lvqXbUPl/7DpFfJVHswL7k8RVOrqqrnxWvLyTVdd0SjBBsuhFdb2xI4Ul1FUXz1q19dacmvXLly5cqVnivbFjT1rpY8bKiWRWMpXXJycmIL5ipTV7tz507/llLS/8lPflIUxZe//OXFi+06WW1JonWla0pJUq9TW7l9l9xnFlKCDCnMw4cPr169evXq1fn3dT7ubFlplNmzMDZ3d3bdunXrypUrt27dsuvryu+9915RFDdv3lxnmXcXgcJO0qYrfOvk5MTdnOkm7kW4Qs+3bBap7KLbuvQfPnwYtso9E7fLw3VSG9pKe/jwoatD+TPVqRCmow1A6lik2HoI69zVgLx48ODBgwcPeqaQaZ+62J2oK1v+TIi+Pj4+Pj4+1tc2cbuazU6aGXltbwTlch/NvTOnU/gRmPcopNIvglBGX2eafN3NfPUK28zbLq5oj0VINrGFyfQlZD6AqQN9csatHK1w6fiZeR2YmWmXPruiu5A/u7que//9999//33986tf/WpRFD/72c9S6yODato92mMZDfCV7bnVlsNeoaz84ILNSPsb9UVmQ7242KuMttBKb4akkcgnbndT1w+7ssNKcJdX6UWw92Gyycz+W61MXSLXoJ///OfhXqc2lx6a8CDaPdJ9t52otgB2T22ro1INmw1x9HXYcWLLb0uruci2x8fH8qe+iBZDUtAjUpj2WA63Lk9FujZNLY+r2NgRm4MbmdJCymfHrexONu1FiFavZYtqcyz69e64PQ3PZLc77ojICIKtydQe6bGIXnPkdZ/rQDfr7HLlsQULryHRs0uKoWfX+++/78pDoLAIqmkhme76me+mLiIzhR9ybVTsx6wwF1z3EY0WtUj0Iro7CZt+NK9UUTV9/TPs8LcXHZu4fv7tRSTcI/tuOPidvy7cvn27z4UjWlEuUOgTdYV7Ie+6y66tMZ2gYN91KdjL8VzDUrphmGaXrnZJ/9VXX7ULr169Gm2HXJ3InzLKYPc0OjXB7VeYuCa44DSFsGWV29kidjTdbvavbd1EUtAJDX0uCLL7dk1JLdoTlvq0uj/dPYA9BzROcnWeuubkryFF7JyPfmx1H8Pp9tGT3CbYdd2tW7fckm9/+9vF+WkKbgVkUE0Lsadv+CHv+e6AeQYuzbD1khXkmmvbgEzUEi1kFzR77kMe3tNb+rHXlF2Hv/sz1bpr92b0Xdk89a690qUuxBol5LsTUhGABAo6nzEzpcMeC5emHBqtgbBDSIYe3N18FxyRYSPH7gbd9sCHHSQuRw34Xn31VZeg6zOwO+Vami47iS9VaWF7GQ0UioR8VRQ9bvSH1bZr6rreUxO6oHnTT1D01I2eG8X5kY7i/Ec7+vHpgkuERhWp9a3o2VWcD21TZ1d4DekSZ5fNWjrh7LSeVKDAfMY+CBQWEka7tjEO37Xnev7dPPvRsn3UbgV3N9AzQcd9JmVNveLnA4XUfj18+PD27du2RyEstl0iibusXdlsEytsapkd1GLko4RwjNYVUnsUMsJj4S6U4T4+ePDAbpLqck9d0Htyd3Lh0G+0g9quYKOEsBipqrOzMYqzgM+dcmHNRwd3UlmEnd7urItuYtstvbVN3c0P6xq04+5Fvzhven4KRTerJ8zVkks8emU4OTnRbp7i/FBRmFR4HkY7hFyXw4Czy1VI9OyylyBZojMZu7Nonh6FYaim5XCtvn1revao1YB3o9x1M/qQkv3QzrzpyTSB3fnPZBiU5B+RcheXLjZBoTDDq+4D77JLXQ5kN8Nkw3dd8WxhBkxNcG/lNxfh5TV/V9d13SuvvBKuEMZS7qI5bx9VtDVNJejKIH/qHMYuaMijsawje227GXSTTHTlUuh5FPrTTo7omEs3tLadwgxwhPXvyuNOQg1zw5XDWnKnirsyuH2026aS6nnD0MU+nnZ5OBvGnV2uhqNHIVzBTmaUJcxRGIZqWo7U5KDu7HnfYe/m85I/wzjAfWjd1WFmgo79TIZhQSYKyVzNdTzV/pmPQjIdJ7aByc+Dswv1VqzPYw6ZWEq+R6HnFSc8yjZ0iO6j60R1R9M1yfmYbyYXtkrXQqra3UxGu4I7o9xza9FqCeM5fR2eY2G8tcTHI5Xe6Ntxq+igzCK56NQEm1RpHgmx7LG2S/IzGe3uFEH7aqea6ifIfdLDS4T7uPX5ToXM2RXuka1tl6xbGH5qwpmMXRAWyPcoXLp0KVNgKAKFhWSGD1wEMNe7ean7AF1B/syH5JkELfeZzE+GSFWOLnF3P254NR+FZB5wiJZEerDlTztlTOSjBJkWnrp4OS+//HJhJijIkc0/mlgE1247czt6gZOZjOF101Vyn2GmkNw3u57w4vxtrrsN1TNKZzK6BO3CcAg5zL07O8Ru4mqYmhbJJvjlL3+5mHOCwsxugOL8xBGbu5tnl08nwz5MEVZyal/CM1M+Qe7cmznQYFOT16kJBy6psG12x8h+guT4RsdrZp5d0RqeGYamZjLaLzu5dOlSwQSF3ggUhrMXncEzGaPv9sk3nFVUxGYU97npyRQjOpMxnGeXmcloP8D2C47CCQozo5DobrqyFbFHHsJAoUjoYjde0fsel5Tb62iF275lW8hMDWj6biZjKjv9c66TKl+qfLVHn83TdWxHVDRQcN+aIFvpGLmN88LihW1PmH50SCW1stuFsMWd2Zk3Fzs1oTMfw3B8IbWbbi5w9NMatsE29+J8V5Y7yuFHz0ZOYeFdR4tbecDZFa1hd5KHgUI4k1HWZ9xhMGpqIL2xiDYe9rYjlJ+BP5P9EAr3Gct30kaLWiRaweh4YWoOQbScdjfdBAX3rIG7NoXZuZAodZejdEPbXdyZ7gRHWruZjbHluhO681dMx87Vjx6ssAaiMxnDTbSSbcqxYxIXbU31fHBdX9GOHDeT0bYNXXbooTgfZUZbqe58YOduOruz7oRvfOMb/Xc5Tzs5ogWIdt0PUJz/0Nl6TqUp+65buZmM7tBHS5vqYHA171Z2bbN7tzv/UU11XUTr0J170bPL1YYNHLvYVUj+1JmM8v3NdCcs4rEufXeF3XJ6eloUxWQy2XRBZpBR7cG/oqS7ORqNiqI4OTmxuyzvFkE9yMo9z/a6rpum0aQy5kp2Mpm0bVuW5enpadM0RVGs4td0BqcsG6a21WRll2Uv+hcjWlHRMzZ1Gqf26+233/7Hf/zHMPFFRH/oaLmHLJrazCzkFJpOp6l1JpPJeDwOhzX7yF9AFtx9PbuiiWji9jMyM7X82aXcuz/96U+fffbZS5cu/fa3v517Nw7WBoMUoCf7jY2yZGZPidN/ZbnFmTmA3QXfs9SzDINvQLfEsL1Y3dXmoK5jrm/M6f9lDFtr2NmVmtLR8T1LSzJaVQACLI/e5bz22muj0Wg0GrVtW8xzEynXUHtbE9U0TV3XmTs29ctf/vK3v/3tyy+//Dd/8zc9yyDcONFu0Qqcdy+kN7tPJ81cXnzxxaIo5JGHQyCnpZz8TtM0TdP0/0Rss3nPLlk/PLt+/vOf//M///NXv/rVH/3oR7LkW9/6VlEU8otQ6O/xTRcA6KXrurt378olUoaQ5xpk6dkZOx6P+3euvvzyyz/84Q97rtw0jVzOVjHcsE7D9uLu3burKExRFD/5yU+ef/75FSW+habTaTRQmOvU3U6DPyOZs+vb3/62Rgnivffe+7u/+7sh5TtgzFEAAABJDD0AAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgVE1HW9trxm/v7C4BTC5dH9WrwAALDHCBQOQr4ttM2n/CpSWZbyU8u6fEW/Xl3X9VxBSbi+/C7tzDVT+5UpwLxlA4C9RKBwEKJNqXJhRFVV8pP2dqvxeLz0O2/5DZj+PwBT17X7bae6rqM/SBhNObpfReIXaMK8AOAw8euRO0DuhrU9019Mbtu2LEtp9pqmkSbT3QRXVSW/Pyt/hs2naxH13TB6mEwmMxt1KZXbMLVy5jdzoymHPz6bSrxt2zDQia5ZVVXYbRDNCwAOE4HCDpBmT5o6bb9lYVEU4/HYNvbSotv77PF4rCuHmqaJvpXZJGN1v3Xbvzz5Zr5PV8GwfQeAvUSgsAOkV0BufKNNoFu4YFMtvQLDWsq5ehTmSlYjpFRko6T3pW3bcACiT5QwV14AsPcIFHZA0zR6px7t/19kQF0mH9gRh0Xup5fVo2CLNG+yrjdFE+y5X6vrFAGAXfRY13WbLgNmkOBApyNoa6eD69KjIE2+3EnL+q6ZlBTCaQp2qGI0Gmn6Ou+hWDiAiEqVVopRlmU4UVGeWdDlUgOSgiub9MHokE1qvyRBWSecKWnXBIDDRKCwD6SrfPB9sJvTMHgdAMD+4fHIfdC2bc9nB6L6RAAM1QPAYWKOwj5Yw7N8DNsDwGFi6AEAACQx9AAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAiKappFfpFxPXj1XU+Hy6Mp98oqm2b9UALD3CBQOQr7Zq+varlnX9Xg8btvWLp9MJqsoWF3XNpcUW377O5m6rS1eXdeyjkt5MpmMx+O6rm1q0dylEogVAKDg1yMPRNu2mZ9/bJpGf0V6PB7LmlVV2UZ0PB43TbPc35Bsmqbn717afG2gYH/8WotXlqW8kLBA1tEXVVVJxKAphzvVti0/qw0AgkBhB+hdvvwpbVjTNG3blmUpDWfTNKenp0Vwi1xVle1a10ZUaQvqcpTEbTq2fc0U1Tbkxfm23JHU3PoDSKY21tHldhdscGC3lRe2ZqTSFiwVAOwHAoUdIK2gNGPagGnTaO+bi7MWXYIGIeMIqQbbdicsLnqDvkT9OyFc9JCiFdUnDAKAA0SgsAPkBle6CqLNpFu4eIMn7b3txuhprh6FAaJtv5ZW38pHCdHYSCqZWAEAHAKFHSANmLRh0Rvf6PBBT8udfLCsHoVFiiSdLq5CyrLMp8m8BACIeqzruk2XATNIcKDTEbQ90+kI0qMgTX7bttIi2kF3O6EhnKZghyq038Kt2bMnfy6p0hZFMRqNyrK0Ayi6iV1Na0CnaMi2tpz6WqrRrunmediKlWhjPB4TPQA4cAQK+0BbtWGbuzkNg9cBAOwfvkdhH7Rtu8izA30iAG6sAeAwMUdhH/R8EGARzPIDgMPE0AMAAEhi6AEAACQRKAAAgCQCBQAAkESgAAAAkggUAABAEoECAABIIlAAAABJBAoAACCJQAEAACQRKAAAgCQCBcTJL1Kugf5U9ExN04Slii4sEuVPLeyfLAAcGgKFg5Bv88Kmuq5rt3AymayiVHVdl2VZ1/XMVlnLYwvWNI38bKYtniQ7Ho/DXZCFNi/d0K4czQsADhOBwkHI/wh1tJF2Pxc5Ho9XcYddVdV4PK6qqs/PZI/HY1equq41BS2eLJTEbZMfLmyaZnzG7p0uX3T3AGD38TPTO0BvkeVP8owxwQAAIABJREFUafDkZrosS2lim6Y5PT0tgptgaUG1FSzLMtrWhkvCdOSOfGZRXZPvErf6t8S2FS/LUhpym4J0FbiFqezsCvoL3XahvrZ5AcBhIlDYAW3byn1zYZpMWVictZHaHkuLLkGDGI/HunKoaRr7VtM02nYOMOxGPAxWQouUKiVaLQvWAADsGQKFHSC9AnKLH23D3MJF7oDlvrxtW2kv501qrh4FXX9mlGA7DBansVG0w2C5eQHArmOOwg6QxqyqqnBEQCwy584Nz5+enkpGw/oGtJwqs3ImSog+hiAv2rbVgtl5CWEIFQ5YhKXVsMbNUQjzAoDD9FjXdZsuA2aQyQE6HUFbVo0PpI2UJl86A2R926DqhIawn8ANVRRnsyJ0vKPofes/l9FopAnqHAt9qyxLu8T2VditwoXFWY25NKMLbR26nQ2TBYADRKCwD+QOePC9bxgoDFsHALB/GHrYB23b9nm8MKVPBMCNNQAcJiYz7oM1zNJnqB4ADhNDDwAAIImhBwAAkESgAAAAkggUAABAEoECAABIIlAAAABJBAoAACCJQAEAACQRKAAAgCQCBQAAkESgAAAAkggU4DVn1pOd/tDzTNFSZYoavpVZ0xVjnTUAANuMQOEg5Ns820Y2TRP9IcrJZLKKUtV1XZZlXdczW2UtgC2tvnbF04bf/pbVZDIZj8dhXrKt/XnMVLIAcID49ciD0LZt5ucfm6axzWRZluHK4/G4aZql/4ak5Cvtdz5x/S1sG8fYYtvitW3rfhe7rmtZUlWVRAy6PPor27LCIj/eDQD7gUBhB8j9sbZt0uDJrX9ZltKYNU0jDZ7rQq+qyvaih0GAtqB2iaRpl7v2NVNU17i6xK1lhR2SqWYkcY/sss1CX4f5hjHQKqIiANhFBAo7QFpBabe0ydemUW7HtZmUFt3eJY/H4/AOW7nuhPF4rA2kS6cPu3l/YbCyyJpt20oI1Wd9qc+yLO3OymhI/1IBwB4jUNgBcn8sXQXS/jlu4bJuhQekM1ePQhF0BuSlWm6JTuy72nES3cTFRrYrQkcctHuGfgUAB45AYQdIAyYtVrT/f5F73+VOPpirRyETJYRF6r+PVVWFDXxZltHdzJc2tRUAHI7Huq7bdBkwgwQHOh1B20udjiA9CtLkt20rbZudjmAnNITTFGyve2rNuW79exqNRvZu3g5zjEajsix1iTyqoIMvOhCjNeA2tzVjR1KkiuyatgskrNhiVo8IAOw9AoV9EE7cm0ufuQgD5isAAPYA36OwD2T63uDN+0QA3FgDwGFijsI+iM5wXC7G6QHgMDH0AAAAkhh6AAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKiGuaRn5ratXsTzUuUarw4fLonq5t9wFgyxEoHIR8m+ea6qZpZIn9fYfJZLKKUtV1XZal/Ip0n03qug4Di3BhXdfj8ThMNrqme5FaCACHiUDhIOR/W9K1pm3bVlXlfgVqPB6v4g5bMqqqqs+vX9Z1Hf6IZbhQl0STDX/dajweu4VN04QLAeAw8euRO0DuvLXdklawaZq2bcuylLawaRr5tWh3E1xVle1FL8vStX9hQyu/RSmNpU1nMpnMbDulVK4AqZXnaombpun/I5la+KZptACyp5lOAt1KC1aWpasHADg0BAo7wN7ia5MvC4uikD52bQ6lRZegQYzHY105ZJvS4nxLH72Dzxt2I94no+guRDeUGpC90MJk4oxw5GUNP9sNALuCQGEHSK+AtGfRNswtXPwOWFLoMxzgzNWjoOvPjBJsp4iNbKILi6LQOMnONpCASeIA1z1TnO9OsP03AHDgCBR2gB0yj/b/D7j1VzL5QNOU1nRwUefqUchECa7DP5Ws7TiJJqIhlOtiCVdu29Z2P0ip+gQxALDfHuu6btNlwAwSHOh0BDvoLi+kOZQmX26aZX3b8umEhnCaghuqsL0C9oZ76a3maDSy6dsyjEajsizDOEAeZHDL3ULpZnB1pW9JUKU1oHWYGn8hUABw4AgU9oE0jYN7y12gMHgdAMD+4fHIfdC27SLjBX0iAG6sAeAwMUdhH6xhlj6T+wDgMDH0AAAAkhh6AAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkPb7pAmCguq6LoqiqatMF6UVKa5VlOR6Poys3TdO2rbzO7KBdzaVm3wr1rzRJZ6WVvM0102flO3fuRN+9evXqtWvXUttadV1Hd9me4eHZ/utf//qDDz74p3/6p5mJZxKJkr2WItnX/bfKr+k2mVmeO3fuvPbaaz3TdAbsvi1eURT9d6d/spk01/CJwxAddtB0Ot2qwzedTquqmk6n0XczH/uqqmau6dbpzO5bZVnqCouf87Yk7q0l1vyW10xZlpmVp9Ppw4cPU+/evn07TCo8Q6L52v11r7uue+WVV1IFdgvtx6T/R8bWrX3dZ6vURyAk5bGHJkpq+OrVq9EcHz58ODOLeXe/C062/jtl83W75s7M1I7Lan0qHOu0LS0N5jKdTsuynHmVWZv89VTbm/KMvWSEq+ma+qdN2V7F3GpaIdGMdGH/PSrL0l4l9WK3rJpfvGZs8TI1oxU4V83MXPn27duy8GrAVpqmEN39aDskb0ku9nV3dmiuXLny4MEDm0t4qth8XbSRYSs2rOSoAZ/HnoVJrXn79u1o9GBlgq0+W9nj3qecbnN3NQjTTNXqvDliDTgeu8p+zE5OTk5OTvS1Xc2+FV3ZvWvTF9Hlrgx9PvnuMuquXPnri66WaqpTV7T+10e3j26PivOWdccT3RfXrEZrxt6fuSWrqJnUylevXs0kEvaC2Hfzt9Q2hrCvHzx4IElplOCysCeh3VAK0+fm2BY1LPbxGbeVCyjdn5m962Z9SKWSXeeBLnn48KF96+EZ3WU5bezrPrsvZQs/CDM3zBwIF+qlDn3/0xJrw/HYSbblODk5kT/taPGdO3d0uf3gRVeOXsGj79oLh5YhdXWIlla5tid17XCrpe5NU1e0meuHpXU30FLszH38IqI148qcqpnoauEeaQX2rJmo1MqyMHVrW1WVrbdoBJPJ0fUPdV135coVe2gkVnCHJtz38HVecT5A1NevvvpqcZ6GC9GGMPXRcOee/UiGf3ZngYIdytHuBO3RkXfdnwN23+1IN+sewG0bPRDhZy3MJSzDsj5iWAoChYXIZyN1TuffLRa4MbWfXtvkh73E+lpuUFIr61XJdjyGH3t37SvL0nV3h0WNNuFuYebu1r6Vub9JvZUqWKaZzOzRsP6JlGiZXbu+/pqJiq6sExSuXr162wgHzmW1cPxorr767vzshCtXrti3lntoQholyMCK+1zYHbRxthszkpXDhtCmFla1NP82UChMB4OWSg+Hmx0yF3ek5upREOGBCJfkzz0ChS1EoLCQwghb/Z7vZoKJKBehuzZPQwGJDPQGRf7UlbVj035ow+uCS1z/tLuT/9hn5uu5jv1oCj3HWfPNYVj5crObCtRS5cnfCXVBb4Q9xJldW7xmMnFPqu8kVTNR0ZX1/tVxHQzRAkQPVv+SvPLKK275zEOzIN07+VPiBt1TuzthF449iNHacN17bi9coOBmJ9ioJaz8YbupJR8QfqX6JMIrRn5KE/MZtwqBwkLCa71t9cN3U5Py8p+cVKbyp7zWLgHXZmigYFe2H2O7fvghd9e1aDn7fOyj3JU0mkK+eKk6cYWft0FKlWfmYUrtaX7XQn1ytIcyPKxhLnbhXDWTWlmbKDeN0fUohIcmM+4zk2xopzHa5atrXezRefXVV+0chXzg7sqWmisQPfrCDT0UsfkKeiAW2cfwSM01PmULkwkLZp57/c9MrA2BwnK4Vt++NTWzvud9Nyo6IBrtIejMzYp9V6MKl1r4IY8GJZlBhJArj90kHNNNbW6fVYs2h9G3FpzJmMpluRMUojWjVbGimpmrAUhVoyyc2TiF4d2wcYfOzGQM31ruoQkdHx8X5+mORz8jYUs5zT5GocmGk4vtZMboww667YL7mApx+h+p8GoQLpn5qVzKvmC5+GbG5QvvFO0XjMz7bki+A0e2Oj09lYWTySRaBllZ/tSVbS52hfBd+dIVWaJfDWQLrF/Ik/9iFvuuvnabSF6W7pQ2LTZHpQXTHUwl2EfqK4Y0teV+BU20ZlJZq9HoT59cG6GGJdcKdDUTHvSMfDW6ru+QPV1tggOq8YMPPoguX9GhsY6OjrquOz4+1v394IMPpBW0nxGlf0bL5sppP7zhdyvJXsu3V33ve99zIz42qdSXXy0oM0bmZK4GukQ+ralzb9hnFiu36Uhlt2WGD6bT6eB382RlN5NR3nIzErrzXQi6cmqcQl7rDYS7G4jehubHhvvMZOwSUx90YXgvEt6eRsuQWi6Vnx8rCbeaeSeUup4OnuPZmZtFu1pYM9EKTD1x2iU6KlLVEt0LnTqX/86fLnYPPXi2mjz14KYxdvM/6lmlvxwsSoZUdLhBexdkia3MsDsq2t9gE9dPZfTzJWGBPuPguhPs6E/PGsjsfmpC0swNUyl0wSk9c9QpNTSDzSJQGM42BoNnMs77qYgOiKYGGjQjN5OxOB/Ra9xg39UV3ACBazB0k+gVJHoFD2d72YniTnQ+RCgaDeQrPxXcpLYaPJNx5tyLsGbCvVhFzbhDlhqPiGan97Wp2nB5hRltZCZj5qyYmW8Re+TBVWZqmN99iPRdG9mHD0Z258cdivNhmR4C+eIEeT3zkYfM7kcjXdfA549a/syMhrPRFPK7gPXjkAw0Pfuq0egnR9+NbrtI1NxnJqNelaIzGV3/pB0TDZulmXOVw3gi+m50F6I30+FFKpVmtJD5XDI74t6dd6t5RSttkZqJrpavmT5FmjmTMb+b0bwGT2uXpBaZyZg5KzL6T1CYOeffrqwfTxdG6Ar2+5tdd0IYGbhto2a29+7D1X9igS2DS9zFH5nDRHfC1nqsS9+LYM/IwPbJyclkMpFBazezQcw74rvEH4/pn/WCw9Kj0Wg6na5uSHvp1lYza1DXdV3X0pW9/tybppEJB/NuqK3s0dHR4Nwnk0nbtj3PPfnASlGPj497/shW3szdT50/g+vNJpvfa7u/2C6bjFKwRq534ZDJwMqmS3HQilV+50FGvqtvDfrfNIffs7S4wbu/hnobPCCFNaBH4VDcvXtXJlQf+BGfTCbj8Xgj97JQm7p3HI1Gm+rJsGUoy9I9h+IcHx8/88wzV69eXe5TAINP/lX3wEl3xcYPDVIe33QBsD52iuLByl+gsR7T6TT1GOpKbUOUnJmgat2+fTt8VHJBg0/+NdQbUcI2o0cBAAAk8YVLAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAICkxzddACykaZq2bauqmmuruq7tn2VZFkUxHo+XWLA8LfavfvWr3/zmNz/4wQ/WljUAYC6PdV236TJgiLqutb13B3E0GpVleXp6Gt2waZqjo6NweWaTpdMS3rp160c/+tEvfvGLv/7rv15P1gCAuTD0sKskSijLcjqd2oWj0ajIdg+0bSsvyrKUvgRdPplMVlRaS0ooQclf/MVfFEXxox/9aA35AgAGYOhhJzVNIy+0D0BaX2UjgJnb6uYaQ8i7GjfY17/+9a/lxde+9jWbpg1NJAtdYv+U+EbHSqQj4Te/+U1yVwEAG0WPwu6ZTCY6djAajaQZdt0DM3sUXCShLbekNhqNnn766clkMplMRqORbPLqq6+ORqO/PDMajSRoqOv66OhIIxUpnpZQ3rV/2uwAAFuOQGEh0pTqPfpc745GIzepsCcbBJRlKX+enp6enp72b4BdJBHtgWjbVqOKV1999fvf/35RFFeuXLly5Yqs8L3vfS+6lf3TRgbSLWHHStSvfvWrniUHAKwTgcJCpCmV++mw1c+/W5xNKcgEE1EaDVRV5aYfau9CalvNyK2jrft4PNY0y7I8OTnpum4ymXzwwQdFUbzyyisaPUS53dTspMyy4TofrwAALIhAYSH2Dj5s9cN3bTuq7+aDiYwwIJjZEtuAwC63kYquY6cmtG3bdd3Vq1dfffVVzffq1auuGDrF0v4pe+recnjqAQC2E4HCQqqq6rqu6zrX6tt3p9OpbTh1LD//boY26qmAoE+PgiPBgb3vd4mUZSkTFL7//e9/+OGHslACBZe4ne5gk3XvAgB2AoHC8oXttJtVMNe7oVTP/8wAokgEAdptkAoUyrKU4ODBgwdd173yyiuy3D74UAQTFV0XQrTYt27dKs4ekgQAbCEej1yI/dYjUVWV3kC3bTvs3bzURITUNIjCzHkU9sHFuq7tfb+y6WuUIJGBzGoMU2vb1n0xQ3H+IcwiCGLkwcjvfOc7sR0FAGyBDkPZatQxiKW82yffVJplWeoSfb5gOp3aP0Oa2snJiTsxHjx4oKvp8w7yOtwd+VPDBVuY6PnGSQgAW46hh4F0xF3aYHc7ru9KLbt3tYs++m5PqUEKe8vupi5GO//lux3tHAu3wte+9jWNDz788EMdd+hTpPA7oe0kCZni8Itf/CKVIABg4/itB/Qi363kJiXMZTKZtG07nU4lavnVr371t3/7t0XwQxUAgK1CoIA1kR+j0nkY8nwHpx8AbDmGHrAm9rce5GEHBh0AYPvx1APWZzqd6hwIfloaAHYCQw8AACCJoQcAAJBEoAAAAJIIFAAAQBKBAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJL4rYdt9/vj/7PpIgDAqnzh2subLgJmoEcBAAAkESgAAIAkAgUAAJBEoAAciudfeiu/whv3j3suT60JYP8QKACH4qknL2befeP+8VNfiq/w8Sef2T9/98lnqTUB7B8CBWBvvXH/2N7629b9d5985noF3rx/8pUnL8pbdrWiKL75wjXbG/Hm/eOvPHkxXA3AXiJQAPbTF5/57seffPbxJ5998ZnvFkXxu08++4dv/UtRFG/cP37+pbfevH8s60gb/8b942++8LRs+OZZePH8S299/OlnRVF85cmLH3/6e5f+x59+JtGDpgxgL/E9CsAekub/7R9/vYjNJ/j409//98MfFkXx8SefffzpZ1958uLHn3ymAxNv//jrElt8/OnvJQVNUzoSZM0XX7j2/CdvvXH/+M37J5IagL1EjwKwh2QQ4YvPfDc680A7D+ysBbvaN1942jX/T33pC9K78PGnn734wjVZ+PaPv/7m/RNNDcBeIlAA9tN/P/zh//u//7soin/41r/MO4fg47PxCLtQIomPg6kJHzNBAdhrBArAHpKJCF958uKLL1zTzoA8XUea//9++MM375+Yd38vb9lOiH/41r9IrwNPSwJ7jEAB2EMvvnDt409///xLb33xme9+/OnvdbAg5ZsvXNOOgX/41r/I1IRvvvC0fdjhK09etOMOz7/0lgw6yADESnYDwBZ4rOu6TZcBOfwoFAaTvoGvZL8+QX3xme+m5iT+7pPPbIgALBE/CrX96FEA9tZXnrzYM0ooiuKbLzydGkF48/4xUQJwsAgUABRFUWRCgW8SJQAHjEABwJ+kYoX+3RIA9g+BAgAASCJQAAAASQQKAAAgiUABAAAkESgAAIAkAgUAAJBEoAAAAJIIFAAAQBKBAgAASHp80wXA9vriM9/ddBEArEnqJ8EAAgXkvHf8aNNFALByz167vOkiYHsx9AAAAJIIFJDz7LXL9t+KslhFsmvOYj25sCNblcV6cuFeHxv3WNd1my4Dcn5//H82lfUXn/kuQw/AIXj22uVNzVH4wrWXN5Iv+qNHAQAAJBEoYMP2pvOWHTm0LNaTC0MP2DiGHrYdQw8AVo2hB2TQo4Bz3rh/vOkiAAC2CIEC/uz5l9568/6JXfL31y7Lv9Vlujedt+zIoWWxnlwYesDGESjgz97+8def+tIX7JLHzv655yT1aUm9ig1+IaMbi6ez2SyKonjv+NEeZGGRxcwXe3P2AhnMUdh2a56j8PxLb73946/La52jEO1R+C+mLwD7gjkKyKBHAbP91/Ej/acLlzUksTedt+zIoWWxnly448fG0aOw7bahRyFkQwS6FoBdR48CMuhRwDkaJeTZ3oVVz3YEAGwQgQKGW8pIxN503rIjh5bFenJh6AEbx9DDttuJL1xyIQKDEcBuYegBGfQoYAnCeY4bLAwAYIkIFJDz7Dw/M+0mLvTPYqEibkcW68mFHdmqLNaTC0MP2DiGHrbdTgw9OBolMAYB7ASGHpBBjwKWb0C/AgBgOxEoYCX6xwp703nLjhxaFuvJhaEHbBxDD9tuF4ceFGMQwE5g6AEZ9ChghRiDAIBdR6CA1ZoZK+xN5y07cmhZrCcXhh6wcQw9bLudHnpQjEEA24yhB2Q8vukCYKu5u5nBccN/HT+SWOHvr10mVgCAHcLQA3LeO35k/y2SVGoMYm86b9mRQ8tiPbkw9ICNY+hh2+3H0INiDALYQgw9IIMeBawV8QEA7BYCBWyGdi3sTectO3JoWawnF4YesHEMPWy7PRt6EBIl0LsAbAmGHpBBjwI2hm9hAoDtR6CADbBPQOxN5y07cmhZrCcXhh6wcQw9bLvNDj24JcsdieAJCGBLMPSADL5wCTkrmqMg+BYmANh+DD1gk9bzq1H0Qm9bLvuRxXpyYegBG8fQw7bby6ceHB6CADaLoQdk0KOAbcFDEACwhQgUsGHPrn6CAr3Q25bLfmSxnlwYesDGMfSw7ZY+9PDG/eOPP/ns7R9/3S0siuLFF67ZhWsbeih4AgLYKIYekEGPwmH53SefFUXx9o+//vxLb+nC519668UXrj31pYsSLmwE8QEAbCcChcPy5v1j121QFMVTT1584/7xm/ePn/rSRffWs9cuZ/4Vpl908AuXTvgbEEvPYkUvnjVfHrW7WfBirhdrOLXWc/YCGQw9bLvlDj08/9JbMuigL+T1U09e/PiTz775wrWvPPnnWGGdQw+CAQhgIxh6QAY9CoflqScvyuiD8+IL197+8dff3NzQgyA+AIBtQ6BwWF584dqb94/fuH/81JMXi6KQmQoy9PD8S299MxiVWINoz+dyH5VcT+fqGnJhR7Yqi/XkwtAANo6hh213CF+45PD9S8CaMfSADHoUsKX4/iUA2AYECtiwsGd16T8AQS/0tuWyH1msJxeGHrBxDD1suz3+mek8BiCAtWHoARn8zDRyNjJHweIXqAFgsxh6wIalelaXOABBL/S25bIfWawnF4YesHEMPWy7A3zqwWIAAlgDhh6QQY8CdgBPQADAphAoYMPyPatL6UugF3rbctmPLNaTC0MP2DiGHrbdgQ89FPwABLB6DD0ggx4FbDviAwDYIAIF5Dwb/K70KrLouebgmQr0Qm9bLvuRxXpyYegBG8fQw7Zj6EHw+AOwOgw9IIMeBewSHn8AgDUjUMCG9exZXaQvgV7obctlP7JYTy4MPWDjGHrYdgw9KB5/AFaEoQdk0KOAnUF8AADrR6CADRvQszrvTAV6obctl/3IYj25MPSAjWPoYdsx9ODw+AOwdAw9IIOfmUaOu5vZnriBn58GgPVg6AE57x0/sv9WkcW8PasDfn6aXuhty2U/slhPLgw9YOMYeth2DD1EMQABLBFDD8igRwE7jO9fAoBVI1DAhg3rWZ1rAIJe6G3LZT+yWE8uDD1g4xh62HYMPWQwAAEsBUMPyKBH4eC8cf/4+ZfeChe+cf94I+VZHAMQALA6BAqH5XeffFYUxds//rqNFZ5/6a2nvnTxqS9d3EissEjPas++BHqhty2X/chiPbkw9ICNI1A4LG/eP37xhWvh8o8//ezjTz8L33r22uXMv8JcxQa/kNGNBdP5+9VnMfPFe8eP9iALiyxmvljDqbWesxfIYI7CtlvuHIXnX3rr7R9/3b4oiuKLz3z3//3f//3xp58VRWFjhe2foyCYqQAsiDkKyKBH4bA89eRFGX04t/BLX/jKkxdffOHax8Fba7CsG5rMTAV6obctl/3IYj25cMePjaNHYdst/amH519666knLxZF8eIL16Rf4Y37xxIifPOFa1958qKuuSs9CgWdCsBi6FFABr/1cHB0xEFfv/jCteKFzRVoefgBCABYOoYesGFL6VnNxwf0Qm9bLvuRxXpyYegBG8fQw7bjC5d6YvQBGIyhB2TQo4C9wpcvAcByESgg59ngixNWkcVS0sn0JdALvW257EcW68mFoQdsHEMP246hh/60O4EBCGAuDD0ggx4F7A/iAwBYOgIFbNgqelbdTAV6obctl/3IYj25MPSAjWPoYdsx9DAvBiCAeTH0gAx6FLBviA8AYIkIFLBhq+tZDX9ScqX2phd6P3aEugKWhaGHbbfZoQe3ZIdGIvj+JaA/hh6QwW89IGeHIoMofv0BABbE0AM2bEU9qzY+oBd623LZjyzWkwtDD9g4hh62HU89DMbjD0BPDD0ggx4F7C3iAwBYHIECNmwNPavr+aWovemF3o8doa6AZWHoYdsx9LAgHn8AZmLoARn0KOAg8PPTADAMgQJyduhnplPW1pewN73Q+7Ej1BWwLAw9bDuGHhbH4w9AHkMPyKBHAfuP+AAABiNQwIbtTectO3JoWawnF4YesHEMPWw7hh6WgtEHIIOhB2TQo4CDQHwAAMMQKBycN+4fP//SW9Hl6y9MsfbO29U9J7k3vdD7sSP/v737R24b2/IAfF01G2kuQArZpXS4AjvjK6YKrUSzCyViyAlZpayietifAAANuElEQVR7BXTqkkJ5AXw76ZoANgcP5IUpEhf3Avi+UsBm2zwESAsH54c/1hV0RaMwLa/v+xDCy9N9o1d43u7W229Z3lIP6UZVIvVQobcFGUGVcZTop8po4j+GS6MwLevt7mG1OPm/5jd/HD/ZuI7C8WUVDrs7A3rwuYy34YEHRT2AGAczlq7bgxmXj5uXp/v6g8Pj+jOVfg5m/LK4S12lXiLdFZ17XpBBVxlHiX6q9LYgDmYkxkRhWua3syp9aFg+bt5+/DvLYQpZhrcpjlQYzRR6HAtiXUFXNArT8rBarLe75+1ufjsLIVRHKrw83b883c9v/oilEmPi9AeAD9EoTM7L0/3DalH1BPWsoZE79KaHiPRkic6HCrkWZIhVxlGinyqOISA7xyiUzgWXUnD9JahzjAItTBSYIv0BwJk0CmSWd3jbYQAxmin0OBbEuoKuiB5Klzd6aDwzsiQi3amSMCyiB1r8V+43QNFG1hmc9Hlxp1cAiBE9kFnG4W23/cFoptDjWBDrCroieiidsx6ScvoDBNEDrUwUmDT9AUA7jQKZFTK8vf70h0IWZBBVxlGinyqiB7ITPZRO9NADpz8wcaIHWpgoAABRGgXafFnc1X8SlUjxsheUuDJ9KGdByq8yjhL9VBE9kJ3ooXSih35IH5gy0QMtTBTg/3V+S0mAodMokFkhw9vrZwmFLMggqoyjRD9VRA9kJ3ooneihNy6+xGSJHmhhogA/6Q8AjmkUyKzA4e1lRyoUuCDFVhlHiX6qiB7ITvRQOreZ7pnTH5gg0QMt3GaaNlPoDE5y72mAiuiBzEob3h76g48GEKUtSMlVxlGinyqiB7ITPZTOWQ9ZCCCYFNEDLUwUIMr1lwA0CmRW5vD2gllCmQtSZpVxlOiniuiB7EQPpes8enje7t7e9y9P940nQwgPq0X9ySlHD8H1l5gS0QMtTBSm5fV9H0J4ebpfPm4OTy4fNw+rxfxmVn8S/QFA0ChMzXq7a4wNQghfj545aNxm+viu04e56MUPunqdRCXCr9HCb/9w/U7ciR70UMKDDz0o/Nv70a86nCR6KF230cPycVOFDocHlZN5xMSjh4rTH5gC0QMtTBSmZX47q9KHuuftbn4za3QJ1Dn9AZgsjcK0PKwW6+3uebub385CCNVBCevtt/V2t3zcVIc09qzw48bPnyUUviBFVRlHiX6qiAbITvRQOhdcyk76wOiJHmhhogBnkT4A06RRILPyh7dnzhLKX5ByqoyjRD9VRA9kJ3ooneihBC6+xLiJHmjhNtO0aezNTLZv+Hv3XfQATJPogTZ/7b7Xf1KUGNbwtqVdGNaC5K0yjhL9VBE9kJ3ooXSih3IIICYi1g6O+HMXPdBC9ADnEkCMz4c+0PY/POI2gokTPZDZEIe3JzcYQ1yQXFWyl/i8uKt+Yn/g7933xs9vK/72NS8jeiA70UPpRA+lEUAMVNJA4eSLD+gbInqghegBPkYAMSz9HHBweLV6ufrjATUN0CB6ILPsU+iLNbZAw12Q/qv0U+I4CPhQlHBmlcYzsde/OJgQPZCd6KF0eaOHxjOSiAMBRMmO+4Nc76Ry3B9kf0sNogdaiB5oozOIEUAUqNjt8XEw4U5jDIjogcyGPug+/Oof+oL0WSXFeSiNLuFTL5vhjy5II5U4J48QPZCd6KF0znoomf3C7EpLGc5X1PxD9EAL0QNc6/PibkDbpzEZ9GkF8giGQvRAZkMcdB/Uf6cPekF6rnJ9ifrE/uRZBgNaVyfziG5LwDVED6UTPRTO6Q89G27WcI5ceYTogRaiB7iK0x96M+4WoVIt1PFVm0a5sAyF6IE2XxZ39Z9EJVK8bM8lwgdvL3SZAY3TOy/ROBzhtxvOQa+r46s2aUbJSPRQOtHDINjtS2fQRyx2ooc1IHqghYkCdMZuX+d0CeE/FzzFDSqhnUaBzMocdH/UyXsCdW7Q4/QLSrSf19BJiSv1tq4uuFITdEX0UDrRw4A4A6JDVmZMijMjRA+0MFHgp+ftbvm4yf0uhs0mrRONayTkfTMFcqgjPdMoEEIIr+/7EMLL033/vUI5g+4OqyT6xT2ycfqxxjj9mi5h9Osq/GceIYkgHY0CIYSw3u4eVovj5xunRx6fLXn4LXbxgyrduP518pYIIfy1+/6ldi3nzx2tn+MSSZeirucSjRbh03Vvo4elKOTbe1hR4ejYhcvWGDQ4RqF0/RyjsHzcvDzd1x8ExyhcweT8o6yx611z7IJjFGhhokAIIcxvZ1X60L9RRg/pTnZP8bL9V2mUSNEljHVdtTh57II8guuZKJSut7Melo+b+e0shHDIIEwUrmEX+UxWVCIfOtrDRIEW7vXAT4fEgU64B8RvuZhSUvXbRrhyKNcQPZBZUcPbFFU6bBfGNE5P3SWMaV1d89ddponriR5K54JLg2aufswgIYuT/cFh/YseaGGiAAnZEDboEnI5PtQxONqR82gUaHN84YQUJVK8bM8lflulk1/HJSzINQ4r4VP6LmHo6ypdiZMdA7QQPZRO9DACAohgJZRN9EALEwVIrp97S5ZMlwDDpVEgsyEOby+o0kmvUMKCXOC4S5jIhz6UEtBO9FA60cOYTG3H2qGLQyF6oIWJAvRnUhmELgHGQaNAZqMZ3p5Z5ZpeoagFaVE/6e7kAfZT+9ALLwHtRA+lEz2M0ogvqWuQMESiB1q41wNtGnsz+oZufV7cjWxTOrWDMGAKRA+0+Wv3vf6TosRohrcfqnJZAFHgghw04oYUJT6k5HVVWgloJ3oonehhxEaz/y1uGDrRAy1MFCCbcZwE0X7cIjB0GgUyG83w9rIqH+oVClyQy4YiE//QSysB7UQPpRM9TMEQR/dDfM/EiB5oYaIA+dU3tOXHEI17E+sSYNw0CmQ2muHtlVXqAX+sVyhhQRotwmVdgg+9qBLQTvRQurzRQ+MZSUQPij0VwhRhxEQPtHDBJdroDPr39+57tUku6nJMugSYLNEDmY1meNthlVgGkWVBfnvjhutLpDC4Dz1jCWgneiidsx4mK/tOfKNNMUgYMdEDLUQPUKhDBhF6v4mUFgE4ED2Q2WiGtymqNEb9jfMSUzg+9TFFl+BDL6oEtBM9lK7z6OF5u3t737883TeeDCE8rBb1J0UPRUm3l3+y+TBFmBTRAy1ED9Py+r4PIbw83S8fN4deoXr8+r6vP0lpqi13I4wIV2zRY8MJLQJQJ3qYlvV21xgbhBC+Hj1z8GVx1/ITanPRix909Tp5S9QLJS3x6WhDXoUF9cig/XUaf7jy9+77p19BQ+qlGNOD0Xx7oYXooXRXRg/VCKHy5+3sMDNoDA9O5hGih/JdeciC4QEV0QMtRA8j9+ftrP6f89vZ6/u+8eTzdje/mR1PGijfZTeJ0B8A59MoTMvDarF83Lz9mM1vZ+HXXGG9/Ta/2a+3YX6boV34srhLPbfooUQ/VdpLdLX5z74gQynRT5V+FgRaiB5K54JLQGqiB1o4mJHMejiWqp/DtSzI1Er0U8XBhmSnUQAAohyjQJvG3owkAmBqNAq00RkATJzogY85mZie+eT5aeuZf/f8Jy/+uz2UOL/umVVyravz38yZVXzo51fpfF3BgUYBAIjSKAAAUa6jULq811HIVRromesoEONgRqJy/eIAoByiB0543u6Wj5veaiV98eftrn5nrHRVkpYIIby+71MvyPJxs3zcpP5Elo+bdAtSvX71k6jEoVDqD72Hf4aHRajuMp/6C8ZAaRRoqn5ZvDzd99ArLB836+23RC9e/RJ8WC3+9T//m6hEqN1SK/XqSroUIYTX9/38dvbydJ/ufh+Hr9Y62Sb2YbV4ebpv3Ae1c9WCJP3Qq+9V0n+G9X996+0u6efCoGkUaFpvd73dGurl6X5+80eiFz/cEjNdiRDCw2rx5+2sh339r6v/Tlri7cf+LfFu5duP/fxm9rzdpd6QP293XxN/h9/e90knCm+/7vL69uPfiUoc/+v7uloYKnBMo8BoVdvv5eMm9TYjhPD2I+Gv1x42eyGEav/15ek+3eji7X1f9Qqppy9vR/dSH5yvq0UPAUqlGiZVj5N+kxkojQJN8/T7x/14fd9XA9Wk24xDwJGuRAhhvd2tt9/6mQwnnPHczuY3s9Sb8B76qup7lfRD//P2Z9+WdB52qPX265/8/GbYDRYpOOuBpip5ffsxmw98n6zarFb7ZOlm3dX+cdJ19bBahNXP0DpdlfBrXaVbluqrtd4mevmf3t73qfu2anc/6Ydetbkh5cfR8Lzdvb3vU6dCDJHrKJQu43UUAFJzHYXyiR4AgCiNAgAQpVEAAKI0CgBAlEYBAIjSKAAAURoFACBKowAARGkUAIAojQIAEKVRAACiNAoAQJRGAQCI0igAAFEaBQAgSqMAAERpFACAqE///PNP7vcAABTKRAEAiNIoAABRGgUAIEqjAABEaRQAgCiNAgAQpVEAAKI0CgBAlEYBAIjSKAAAURoFACBKowAARGkUAIAojQIAEKVRAACiNAoAQJRGAQCI0igAAFEaBQAgSqMAAERpFACAKI0CABClUQAAojQKAECURgEAiNIoAABRGgUAIEqjAABEaRQAgCiNAgAQpVEAAKI0CgBAlEYBAIjSKAAAURoFACBKowAARGkUAIAojQIAEKVRAACiNAoAQJRGAQCI0igAAFEaBQAg6v8AdqDfB4BmT9gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ROOT import gROOT \n",
    "gROOT.GetListOfCanvases().Draw()"
   ]
  }
 ],
 "metadata": {
  "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": "3.8.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}