{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Basic, Part C: Step Scan with Scaler and Motor\n",
    "\n",
    "From *APS Python Training for Bluesky Data Acquisition*.\n",
    "\n",
    "**Objective**\n",
    "\n",
    "Step scan of scaler and motor with table and plot.\n",
    "\n",
    "In this lesson, we'll show how to use the tools provided with Bluesky to show the data as it is acquired using both a table representation and a graphical view, as well. These capabilities are provided by using callbacks. In lessons 1 and 2, we wrote our own simple callback to view the documents that come from the RunEngine during execution of a plan. Quickly, the data became too complex for simple viewing.\n",
    "\n",
    "The *LiveTable* and *LivePlot* callbacks provide a table and graphical view of the data from the plan. We'll get to those first. Later, we'll show the *BestEffortCallback*, which combines both those callbacks plus a little more. For routine work, we'll want to use *BestEffortCallback* all the time. We'll show how to make that happen so we *set it and forget about it*.\n",
    "\n",
    "-------\n",
    "\n",
    "**note**:  This tutorial expects to find an EPICS IOC on the local network configured as a synApps `xxx` [IOC](https://github.com/epics-modules/xxx) with prefix `gp:`.\n",
    "\n",
    "<details>\n",
    "A docker container is available to provide this IOC.  See this URL for instructions:  https://github.com/prjemian/epics-docker/tree/main/v1.1/n5_custom_synApps/README.md\n",
    "</details>\n",
    "\n",
    "Starting with the configuration from the basic scaler and motor notebooks, we first group the `import`s together as is common Python practice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ophyd import EpicsMotor\n",
    "from ophyd.scaler import ScalerCH\n",
    "from bluesky import RunEngine\n",
    "import bluesky.plans as bp"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, make a RunEngine (for scanning) and connect our motor and scaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "RE = RunEngine({})\n",
    "\n",
    "P = \"gp:\"\n",
    "m1 = EpicsMotor(f\"{P}m1\", name=\"m1\")\n",
    "scaler = ScalerCH(f\"{P}scaler1\", name=\"scaler\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reconfigure the scaler for channel names, set the counting time to 0.5 s, and read the scaler values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('clock', {'value': 16000000.0, 'timestamp': 1684257328.660073}),\n",
       "             ('I0', {'value': 7.0, 'timestamp': 1684257328.660073}),\n",
       "             ('scint', {'value': 7.0, 'timestamp': 1684257328.660073}),\n",
       "             ('scaler_time', {'value': 1.6, 'timestamp': 1684257328.660073})])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaler.channels.chan01.chname.put(\"clock\")\n",
    "scaler.channels.chan02.chname.put(\"I0\")\n",
    "scaler.channels.chan03.chname.put(\"scint\")\n",
    "\n",
    "scaler.preset_time.put(0.4)\n",
    "\n",
    "scaler.select_channels()\n",
    "scaler.read()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Showing the data\n",
    "\n",
    "In lessons 1 and 2, we wrote a *callback* routine that printed information as the scan prpogressed (that is, we *printed select content from the stream of documents emitted by the RunEngine while executing a plan*).  But our callback was simple and we found there is a lot of content in the documents from the RunEngine.\n",
    "\n",
    "The [simplest example of a Bluesky callback](https://blueskyproject.io/bluesky/callbacks.html#simplest-working-example) is the `print` function.  We want a callback function that understands our data and uses reasonable assumptions to show that data as it is being acquired.\n",
    "\n",
    "One method to display our data is in a [table](https://blueskyproject.io/bluesky/callbacks.html#livetable) that updates as the scan progresses.  We'll import the `LiveTable` callback from the Bluesky library:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bluesky.callbacks import LiveTable"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`LiveTable()` shows acquired data as a plan is executed.  The argument is the list of detectors to show in the table.  First, we'll count the scaler 5 times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "+-----------+------------+------------+------------+-------------+------------+\n",
      "|   seq_num |       time |         I0 |      clock | scaler_time |      scint |\n",
      "+-----------+------------+------------+------------+-------------+------------+\n",
      "|         1 | 12:16:30.3 |          1 |    4000000 |       0.400 |          2 |\n",
      "|         2 | 12:16:31.0 |          2 |    5000000 |       0.500 |          1 |\n",
      "|         3 | 12:16:31.5 |          3 |    5000000 |       0.500 |          3 |\n",
      "|         4 | 12:16:32.0 |          2 |    5000000 |       0.500 |          2 |\n",
      "|         5 | 12:16:32.5 |          1 |    5000000 |       0.500 |          3 |\n",
      "+-----------+------------+------------+------------+-------------+------------+\n",
      "generator count ['3b77f60f'] (scan num: 1)\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('3b77f60f-deab-4dd3-8ae1-cde3f40e90e1',)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RE(bp.count([scaler], 5), LiveTable([scaler]))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You see columns for the data collection sequence number, the time of collection, and each of the *named* scaler channels.  At the end, the short form for the scan's `uid` is shown as well as `scan num` which is a more convenient reference to the scan.  The user has control to set or reset `scan num` so do not rely on that number to be unique.\n",
    "\n",
    "Next, we'll scan with motor and scaler, as we did in the [basic_motor](_basic_c.ipynb) lesson, displaying the acquired data in a `LiveTable`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "+-----------+------------+------------+------------------+------------+------------+-------------+------------+\n",
      "|   seq_num |       time |         m1 | m1_user_setpoint |         I0 |      clock | scaler_time |      scint |\n",
      "+-----------+------------+------------+------------------+------------+------------+-------------+------------+\n",
      "|         1 | 12:16:39.0 |     1.0000 |           1.0000 |          2 |    5000000 |       0.500 |          1 |\n",
      "|         2 | 12:16:40.8 |     2.0000 |           2.0000 |          1 |    5000000 |       0.500 |          3 |\n",
      "|         3 | 12:16:42.6 |     3.0000 |           3.0000 |          2 |    5000000 |       0.500 |          2 |\n",
      "|         4 | 12:16:44.4 |     4.0000 |           4.0000 |          1 |    5000000 |       0.500 |          3 |\n",
      "|         5 | 12:16:46.3 |     5.0000 |           5.0000 |          2 |    5000000 |       0.500 |          2 |\n",
      "+-----------+------------+------------+------------------+------------+------------+-------------+------------+\n",
      "generator scan ['08cc8fdd'] (scan num: 2)\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('08cc8fdd-c541-4905-aa21-974024e0ae66',)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RE(bp.scan([scaler], m1, 1, 5, 5), LiveTable([m1, scaler]))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to the data columns from `count` above, the motor position (both where the motor reported as its position and where the motor was told to go, respectively) are shown."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---------\n",
    "There is a callback routine that will plot the data as it is acquired.  When starting graphics, it is necessary to first initialize the graphics manager of the display.  The setup is specific to the graphics manager.  For command line or python program use, see https://blueskyproject.io/bluesky/callbacks.html#aside-making-plots-update-live.\n",
    "\n",
    "For jupyter notebooks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll import the `LivePlot` callback from the Bluesky library:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bluesky.callbacks import LivePlot"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Count the scaler 5 times.  We'll just plot the `scint` signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('0890967d-f1fb-4364-a6f4-8a924b9d4fd9',)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.count([scaler],num=5), LivePlot(\"scint\"))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To scan, we need to tell `LivePlot` to plot `scint` *vs.* the motor:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('5d3b0b3e-8d1d-49af-b1d2-6e07cea61d99',)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.scan([scaler], m1, 1, 5, 5), LivePlot(\"scint\", \"m1\"))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "------------------\n",
    "Both the table and the plot are very useful diagnostics for routine use.  They have been combined in the [*Best-Efforts Callback*](https://blueskyproject.io/bluesky/callbacks.html#best-effort-callback) which provides visualization for any plan.  It uses [user-configurable information](https://blueskyproject.io/bluesky/callbacks.html#hints) that is part of every ophyd device to make reasonable assumptions about what information is appropriate to display in the context of the current plan.\n",
    "\n",
    "We'll import the `BestEffortCallback` callback from the Bluesky library:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from bluesky.callbacks.best_effort import BestEffortCallback\n",
    "bec = BestEffortCallback()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Count the scaler 5 times:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Transient Scan ID: 5     Time: 2023-05-16 12:18:51\n",
      "Persistent Unique Scan ID: '519c4326-fd1b-489a-a951-00ee64f74dcf'\n",
      "New stream: 'primary'\n",
      "+-----------+------------+------------+------------+------------+\n",
      "|   seq_num |       time |      clock |         I0 |      scint |\n",
      "+-----------+------------+------------+------------+------------+\n",
      "|         1 | 12:18:52.1 |    5000000 |          2 |          2 |\n",
      "|         2 | 12:18:53.0 |    5000000 |          3 |          2 |\n",
      "|         3 | 12:18:53.8 |    5000000 |          3 |          2 |\n",
      "|         4 | 12:18:54.6 |    5000000 |          2 |          2 |\n",
      "|         5 | 12:18:55.3 |    5000000 |          2 |          2 |\n",
      "+-----------+------------+------------+------------+------------+\n",
      "generator count ['519c4326'] (scan num: 5)\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('519c4326-fd1b-489a-a951-00ee64f74dcf',)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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J4/HI6/UqKyvL7nIAABHQ1d/9jr5UCwCA0xCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAQNiCs7y8vMOfrV27NlynBQAgrMIWnFdccYUOHjx40va33npL3/jGN8J1WgAAwipswTlp0iRNnjxZtbW1wW1r1qzRVVddpV/+8pfhOi0AAGEVtuD8/e9/r4EDB+rqq6/WkSNH9Le//U1XX3217rvvPv3kJz8J12kBAAirsAWny+XS0qVLlZqaqssuu0zf+ta3VFpaqjvuuCNcpwQAIOxclmVZofqwzZs3n7SttrZWN954o66++mr90z/9U3D7qFGjQnXakPP5fPJ4PPJ6vcrKyrK7HABABHT1d39IgzMhIUEul0snfuSJ7wP/2+Vyqbm5OVSnDTmCEwDiT1d/9yeF8qS7du0K5ccBAOA4IQ3O/v37h/LjAABwnLANDiotLdXChQtP2r5w4UI9+OCD4TotAABhFbbg/N3vfqehQ4eetH348OF68sknw3VaAADCKmzBWVlZqfz8/JO29+nTRxUVFeE6LQAAYRW24CwqKtJbb7110va33npLBQUFXfqMe+65Ry6Xq80rLy+v02PKyso0duxYpaamatCgQfRuAQAhFdLBQSf64Q9/qDlz5qixsVGXXnqpJOl///d/deedd+qnP/1plz9n+PDhev3114PvExMTO9x3165duuqqq/SjH/1If/rTn/TWW2/pxz/+sfr06aPrrruu+40BAOCYsAXnnXfeqUOHDunHP/6xjh49KklKTU3VXXfdpZKSkq4XmJR0yl5mwJNPPql+/frpkUcekSSdc845WrdunR566KGoCU7LsnS40bnPuAJAuKUlJ8rlctldRofCFpwul0sPPvig/uVf/kXbtm1TWlqazjrrLLndbqPP2bFjhwoKCuR2uzV+/Hg98MADGjRoULv7vvPOO5o8eXKbbVOmTNGCBQvU2Nio5OTkdo/z+/3y+/3B9z6fz6jGUDrc2Kxhv3jNtvMDgN0+um+K0lPCFk+nLewLWffo0UP5+fnq2bOncWiOHz9eS5Ys0WuvvaannnpKlZWVmjhxYrvLlUmtA5Jyc3PbbMvNzVVTU5Oqq6s7PE9paak8Hk/wVVRUZFQnACB+hC3SW1padP/99+vhhx9WXV2dJCkzM1M//elPdffddysh4dSZfeWVVwb/98iRIzVhwgQNHjxYTz/9tObOndvuMV/t3p843V9HSkpK2nyez+ezLTzTkhP10X1TbDk3ADhBWnLHY1mcIGzBeffdd2vBggX61a9+pa997WuyLEtvvfWW7rnnHh05ckT/9m//ZvyZGRkZGjlypHbs2NHuz/Py8lRZWdlmW1VVlZKSktS7d+8OP9ftdhv3hsPF5XI5+hIFAMS7sP2Gfvrpp/WHP/xB3/rWt4LbiouL1bdvX/34xz/uVnD6/X5t27ZNkyZNavfnEyZM0F/+8pc221auXKnzzjuvw/ubAACYCNs9zkOHDrU7c9DQoUN16NChLn3GvHnzVFZWpl27dundd9/V9ddfL5/Pp+nTp0tqvcQ6bdq04P4zZszQF198oblz52rbtm1auHChFixYoHnz5oWmUQCAuBe24CwuLtbjjz9+0vbHH39cxcXFXfqMPXv26MYbb9SQIUN07bXXKiUlRWvXrg1OJl9RUaHdu3cH9x84cKBeeeUVrV69WqNHj9a//uu/6rHHHouaR1EAAM4X0vU4T1RWVqarr75a/fr104QJE+RyufT222+rvLxcr7zySoeXW52A9TgBIP509Xd/2HqcX//61/XJJ5/o7/7u71RTU6NDhw7p2muv1fbt2x0dmgAAdCZsPc5oRo8TAOJPV3/3h3RU7ebNm7u876hRo0J5agAAIiKkwTl69Gi5XC6dqhPrcrnU3Mx8rACA6BPS4Ny1a1coPw4AAMcJaXAGHhORWud/zc3N1Q9+8IM2+yxcuFAHDhzQXXfdFcpTAwAQEWEbVfu73/2u3QkQhg8fzuLSAICoFbbgrKysVH5+/knb+/Tpo4qKinCdFgCAsApbcBYVFemtt946aftbb72lgoKCcJ0WAICwCtsk7z/84Q81Z84cNTY26tJLL5Uk/e///q/uvPNO/fSnPw3XaQEACKuwBeedd96pQ4cO6cc//rGOHj0qSUpNTdVdd92lkpKScJ0WAICwCvvMQXV1ddq2bZvS0tJ01llnOWbdy84wcxAAxB9bZg5qT48ePTRu3LhwnwYAgIgI2+AgAABiEcEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABqIqOEtLS+VyuTRnzpxO93viiSd0zjnnKC0tTUOGDNGSJUsiUyAAIOYl2V1AV73//vv6/e9/r1GjRnW63/z581VSUqKnnnpK48aN03vvvacf/ehH6tmzp6655poIVQsAiFVR0eOsq6vT9773PT311FPq2bNnp/v+8Y9/1G233aYbbrhBgwYN0j/8wz/o1ltv1YMPPtjhMX6/Xz6fr80LAID2REVwzpw5U1dffbUuv/zyU+7r9/uVmpraZltaWpree+89NTY2tntMaWmpPB5P8FVUVBSSugEAscfxwbls2TJt2LBBpaWlXdp/ypQp+sMf/qD169fLsiytW7dOCxcuVGNjo6qrq9s9pqSkRF6vN/gqLy8PZRMAADHE0fc4y8vLdccdd2jlypUn9SI78i//8i+qrKzUBRdcIMuylJubq5tvvlm//vWvlZiY2O4xbrdbbrc7lKUDAGKUo3uc69evV1VVlcaOHaukpCQlJSWprKxMjz32mJKSktTc3HzSMWlpaVq4cKEaGhr0+eefa/fu3RowYIAyMzN1xhln2NAKAEAscXSP87LLLtOWLVvabLvllls0dOhQ3XXXXR32ICUpOTlZhYWFklov937zm99UQoKj/04AAEQBRwdnZmamRowY0WZbRkaGevfuHdxeUlKivXv3Bp/V/OSTT/Tee+9p/Pjx+vLLL/Wb3/xGH374oZ5++umI1w8AiD2ODs6uqKio0O7du4Pvm5ub9fDDD2v79u1KTk7WJZdcorffflsDBgywr0gAQMxwWZZl2V2E0/h8Pnk8Hnm9XmVlZdldDgAgArr6u5+bfgAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMRFVwlpaWyuVyac6cOZ3u9+c//1nFxcVKT09Xfn6+brnlFh08eDAyRQIAYlrUBOf777+v3//+9xo1alSn+7355puaNm2abr31Vm3dulXPPfec3n//ff3whz+MUKUAgFgWFcFZV1en733ve3rqqafUs2fPTvddu3atBgwYoNtvv10DBw7UhRdeqNtuu03r1q2LULUAgFgWFcE5c+ZMXX311br88stPue/EiRO1Z88evfLKK7IsS/v379fzzz+vq6++usNj/H6/fD5fmxcAAO1xfHAuW7ZMGzZsUGlpaZf2nzhxov785z/rhhtuUEpKivLy8pSdna3f/va3HR5TWloqj8cTfBUVFYWqfABAjHF0cJaXl+uOO+7Qn/70J6WmpnbpmI8++ki33367fvGLX2j9+vV69dVXtWvXLs2YMaPDY0pKSuT1eoOv8vLyUDUBABBjXJZlWXYX0ZGXXnpJf/d3f6fExMTgtubmZrlcLiUkJMjv97f5mSTddNNNOnLkiJ577rngtjfffFOTJk3Svn37lJ+ff8rz+nw+eTweeb1eZWVlha5BAADH6urv/qQI1mTssssu05YtW9psu+WWWzR06FDdddddJ4WmJDU0NCgpqW2zAvs5+G8EAECUcHRwZmZmasSIEW22ZWRkqHfv3sHtJSUl2rt3r5YsWSJJuuaaa/SjH/1I8+fP15QpU1RRUaE5c+bo/PPPV0FBQcTbAACILY4Ozq6oqKjQ7t27g+9vvvlm1dbW6vHHH9dPf/pTZWdn69JLL9WDDz5oY5UAgFjh6HucduEeJwDEn67+7nf0qFoAAJyG4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBgIKqCs7S0VC6XS3PmzOlwn5tvvlkul+uk1/DhwyNXKAAgZkVNcL7//vv6/e9/r1GjRnW636OPPqqKiorgq7y8XL169dLf//3fR6hSAEAsi4rgrKur0/e+9z099dRT6tmzZ6f7ejwe5eXlBV/r1q3Tl19+qVtuuSVC1QIAYlmS3QV0xcyZM3X11Vfr8ssv1/3332907IIFC3T55Zerf//+He7j9/vl9/uD771eryTJ5/N1r2AAQNQJ/M63LKvT/RwfnMuWLdOGDRv0/vvvGx9bUVGhv/71r3rmmWc63a+0tFT33nvvSduLioqMzwkAiG61tbXyeDwd/tzRwVleXq477rhDK1euVGpqqvHxixcvVnZ2tqZOndrpfiUlJZo7d27wfUtLiw4dOqTevXvL5XJ1eJzP51NRUZHKy8uVlZVlXJ8TxEIbpNhoRyy0QaIdThILbZAi1w7LslRbW6uCgoJO93N0cK5fv15VVVUaO3ZscFtzc7PWrFmjxx9/XH6/X4mJie0ea1mWFi5cqJtuukkpKSmdnsftdsvtdrfZlp2d3eU6s7KyovofpRQbbZBiox2x0AaJdjhJLLRBikw7OutpBjg6OC+77DJt2bKlzbZbbrlFQ4cO1V133dVhaEpSWVmZPv30U916663hLhMAEEccHZyZmZkaMWJEm20ZGRnq3bt3cHtJSYn27t2rJUuWtNlvwYIFGj9+/EnHAwBwOqLicZTOVFRUaPfu3W22eb1evfDCC2Hvbbrdbv3yl7886TJvNImFNkix0Y5YaINEO5wkFtogOa8dLutU424BAEBQ1Pc4AQCIJIITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGEiyuwAnamlp0b59+5SZmSmXy2V3OQCACLAsS7W1tSooKFBCQsf9SoKzHfv27VNRUZHdZQAAbFBeXq7CwsIOf05wtiMzM1NS6/95WVlZNlcDAIgEn8+noqKiYAZ0hOBsR+DybFZWFsEJAHHmVLfoGBwEAIABghMAAAMEJwAABrjHCQAIam5uVmNjo91lhEVycrISExNP+3MITgCALMtSZWWlampq7C4lrLKzs5WXl3daz+gTnACAYGjm5OQoPT095iZ/sSxLDQ0NqqqqkiTl5+d3+7MITgCIc83NzcHQ7N27t93lhE1aWpokqaqqSjk5Od2+bMvgIACIc4F7munp6TZXEn6BNp7OfVyCEwAg6dQP/seCULSR4AQAwADBCQCAAYITABC17rnnHrlcrjavvLy8sJ6TUbUAgKg2fPhwvf7668H3oZjkoDMEJwAgqiUlJYW9l9nmfBE7EwAgaliWpcONzRE/b1pyovHI1x07dqigoEBut1vjx4/XAw88oEGDBoWpQoITANCOw43NGvaL1yJ+3o/um6L0lK5H0/jx47VkyRKdffbZ2r9/v+6//35NnDhRW7duDdtkDgQnACBqXXnllcH/PXLkSE2YMEGDBw/W008/rblz54blnAQnAOAkacmJ+ui+Kbac93RkZGRo5MiR2rFjR4gqOhnBCQA4icvlMrpk6hR+v1/btm3TpEmTwnYOnuMEAEStefPmqaysTLt27dK7776r66+/Xj6fT9OnTw/bOaPvzwkAAI7Zs2ePbrzxRlVXV6tPnz664IILtHbtWvXv3z9s5yQ4AQBRa9myZRE/J5dqAQAwQHACAGCA4AQAwADBCQCAAYITACCpdX7aWBeKNhKcABDnkpOTJUkNDQ02VxJ+gTYG2twdPI4CAHEuMTFR2dnZqqqqkiSlp6cbr1DidJZlqaGhQVVVVcrOzj6tNTsJTgBAcD3LQHjGquzs7NNeu5PgBADI5XIpPz9fOTk5amxstLucsEhOTj6tnmaAo4Nz/vz5mj9/vj7//HNJ0vDhw/WLX/yizTIyX1VWVqa5c+dq69atKigo0J133qkZM2ZEqGIAiG6JiYkhCZdY5ujBQYWFhfrVr36ldevWad26dbr00kv17W9/W1u3bm13/127dumqq67SpEmTtHHjRv385z/X7bffrhdeeCHClQMAYpXLirLxx7169dK///u/69Zbbz3pZ3fddZdWrFihbdu2BbfNmDFDH3zwgd55550un8Pn88nj8cjr9SorKyskdcMeviON2rLHq+j6V+4cCQnS6KLsqFxeCjDV1d/9UfNfQ3Nzs5577jnV19drwoQJ7e7zzjvvaPLkyW22TZkyRQsWLFBjY2OHw4/9fr/8fn/wvc/nC13hsNUti97X+i++tLuMqDZleK5+d9N5dpcBOIbjg3PLli2aMGGCjhw5oh49emj58uUaNmxYu/tWVlYqNze3zbbc3Fw1NTWpurpa+fn57R5XWlqqe++9N+S1w17ew43B0Byal2lzNdGnqcXSp1V1evvTg2ppsZSQEFuPJwDd5fjgHDJkiDZt2qSamhq98MILmj59usrKyjoMz68+exS4Et3ZM0klJSWaO3du8L3P51NRUVEIqoedNu+pkSQV9UrTq3MusreYKNTU3KIR97ymWn+TdlbX68ycHnaXBDiC44MzJSVFZ555piTpvPPO0/vvv69HH31Uv/vd707aNy8vT5WVlW22VVVVKSkpSb179+7wHG63W263O7SFw3Ybd9dIksYU9bS3kCiVlJigEQUerfviS31QXkNwAsc4elRteyzLanM/8kQTJkzQqlWr2mxbuXKlzjvvvNOaXgnRaePu1su0Y/pl21tIFCsuypZ0vPcOwOHB+fOf/1z/93//p88//1xbtmzR3XffrdWrV+t73/uepNZLrNOmTQvuP2PGDH3xxReaO3eutm3bpoULF2rBggWaN2+eXU2ATSzL0sbyGknSmH70OLtrVKFHkrRpj9fmSgDncPSl2v379+umm25SRUWFPB6PRo0apVdffVVXXHGFJKmiokK7d+8O7j9w4EC98sor+slPfqInnnhCBQUFeuyxx3TdddfZ1QTY5PODDappaFRKUoKG5fNIUXcVF2ZLkrbt8+loU4tSkhz9tzYQEY4OzgULFnT688WLF5+07etf/7o2bNgQpooQLTYcG007oiCLX/anoX/vdHnSkuU93KjtlbUaeawHCsQzfqMgJm0sbw3Oc7lMe1pcLtcJl2tr7C0GcAiCEzEpOKKW4DxtowMDhI7dMwbiHcGJmNNwtEkfV9ZKYkRtKIw6dp/zA3qcgCSCEzFoyx6vmlss5Wa5le9JtbucqFd87FLtjqo61fmbbK4GsB/BiZgTfAylqGfMrWJvh5ysVOV7UmVZ0od7eSwFIDgRc5j4IPQCj6UwEQJAcCLGWJalDQwMCrlRRa2Xaz8op8cJEJyIKXtrDutArV9JCS6N7Mszh6FSzAAhIIjgREwJPIZyTn6W0lIS7S0mhgQmPtjz5WEdrGt/rmggXhCciCnHn9/MtrWOWJOVmqxBfTIkSZuZtxZxjuBETAnMGERwht5oLtcCkghOxBB/U7O27vVJYg3OcAhMvfcBMwghzhGciBkf7fPpaHOLeqYnq3/vdLvLiTnH1+b0yrIse4sBbERwImacOD8tEx+E3jn5WUpKcOlg/VHt+fKw3eUAtiE4ETOOzxiUbWsdsSo1OVFD8zMlMUAI8Y3gRMwIrMHJxAfhwwxCAMGJGFHlO6K9NYflcknFRUx8EC6B4NzEACHEMYITMSFwmfbsnExlpibbW0wMCwwQ+nBv6wo0QDwiOBETmPggMs7M6aH0lETVH23WZwfq7C4HsAXBiZjAiiiRkZjg0oi+PM+J+EZwIuo1NbcER3kyMCj8AgtbM4MQ4hXBiai3fX+tDjc2K9OdpDP79LC7nJg3KjiylkdSEJ8ITkS9wP3N4qJsJSQw8UG4jT42QGhbhU/+pmZ7iwFsQHAi6jEwKLIKe6apZ3qyGpstbauotbscIOIITkS9wMCgc7m/GREul+uEeWtrbK0FsAPBiaj2Zf1R7ayul3T8EiLCbxQTISCOEZyIapuO9XgGnpGhnhkp9hYTR0Yfm52JAUKIRwQnolrw/ia9zYgK9Dg/O1Cn2iON9hYDRBjBiajGxAf2OKOHW32z02RZ0pa99DoRXwhORK2WFit4j42JDyIvMJn+B+UEJ+ILwYmotbO6TrVHmpSanKAheZl2lxN3RrHEGOIUwYmoteHY/c1RfbOVnMg/5UgrZgYhxCl+2yBqBe9v9s+2t5A4NbLQI5dL2ltzWAdq/XaXA0QMwYmodXxELfc37dDjhLmBuVyLeEJwIirV+Zu0fX/rdG+MqLVP4D4nS4whnhCciEqby2tkWVLf7DTlZqXaXU7cCkyE8AH3ORFHCE5EpY3Hejij6W3aKtjj3FMjy7LsLQaIEIITUSk4MIgZg2w1ND9TyYku1TQ0qvzQYbvLASKC4ETUsSzrhKXEGBhkJ3dSooblZ0lq7XUC8YDgRNQpP3RYB+uPKjnRpeEFWXaXE/cYIIR4Q3Ai6mw4dpl2eIFHqcmJNleD42tzMkAI8YHgRNRhYndnKS5sHVm7Za9XTc0tNlcDhB/BiaizkYndHWVQnx7q4U7S4cZmfXqgzu5ygLAjOBFVjjQ266N9PkmMqHWKxASXRvQ9NkCI+5yIAwQnosqHe71qarF0Rg+3Cnum2V0OjikOPs/JfU7EPoITUeX4YyjZcrlc9haDoOMDhGpsrQOIBIITUWVjOQODnGjUsQFCH1fU6khjs83VAOFFcCKqsCKKM/XNTtMZPVLU1GLpowqf3eUAYUVwImpUeA+rwntECS6p+Njk4nAGl8vFRAiIGwQnokagtzk0L0vpKUn2FoOTBAYIMRECYh3BiajBxAfONiqwxBg9TsQ4ghNRg4ndnS3Q49xZXS/v4UZ7iwHCiOBEVDja1KIte1svAdLjdKZeGSkq6tX6bO0WLtcihhGciAofV/rkb2qRJy1ZA3tn2F0OOnDiwtZArCI4ERUCl2lHF2UrIYGJD5xqdHCAUI2tdQDhRHAiKjAwKDoEJkL4oJxLtYhdBCeiwoZjPc5zGRjkaCP6epTgkip9R7Tfd8TucoCwIDjheNV1fu0+1CDp+JyocKYMd5LOysmUxGMpiF0EJxxv07He5pk5PeRJS7a3GJxSYFYnJkJArCI44XjBid3pbUYFRtYi1hGccDwmPoguJ069Z1mWvcUAYUBwwtGaW6zgvTJG1EaHIXmZSklKkPdwo7442GB3OUDIEZxwtB1Vtao/2qz0lESdnZtpdznogpSkBA3Lz5LE5VrEJoITjha4TFtcmK1EJj6IGqOP3Y/meU7EIoITjhaY+ODc/tn2FgIjwYkQ6HEiBjk6OEtLSzVu3DhlZmYqJydHU6dO1fbt20953J///GcVFxcrPT1d+fn5uuWWW3Tw4MEIVIxQC0x8MKaIgUHRJPC87dZ9XjU2t9hbDBBijg7OsrIyzZw5U2vXrtWqVavU1NSkyZMnq76+vsNj3nzzTU2bNk233nqrtm7dqueee07vv/++fvjDH0awcoSC93CjPq2qkySNZmBQVBnYO0OZ7iQdaWzRJ/tr7S4HCKkkuwvozKuvvtrm/aJFi5STk6P169froosuaveYtWvXasCAAbr99tslSQMHDtRtt92mX//612GvF6EVGE3br1e6zujhtrcYGElIcGlkoUdvf3ZQm/d4NbzAY3dJQMg4usf5VV5v60CDXr16dbjPxIkTtWfPHr3yyiuyLEv79+/X888/r6uvvrrDY/x+v3w+X5sX7Hf8+c1sW+tA9wQu17JSCmJN1ASnZVmaO3euLrzwQo0YMaLD/SZOnKg///nPuuGGG5SSkqK8vDxlZ2frt7/9bYfHlJaWyuPxBF9FRUXhaAIMMWNQdCs+NkBoEyNrEWOiJjhnzZqlzZs3a+nSpZ3u99FHH+n222/XL37xC61fv16vvvqqdu3apRkzZnR4TElJibxeb/BVXl4e6vJhyLIsZgyKcoEe5yf7a3X4aLO9xQAh5Oh7nAGzZ8/WihUrtGbNGhUWFna6b2lpqb72ta/pn//5nyVJo0aNUkZGhiZNmqT7779f+fn5Jx3jdrvldnMPzUl2VdfLe7hR7qQEnXPsYXpEl7ysVPXJdOtArV9b93l13oCOb7EA0cTRPU7LsjRr1iy9+OKLeuONNzRw4MBTHtPQ0KCEhLbNSkxMDH4eokOgtzmyr0cpSY7+Z4oOuFyu4Ly1H7BSCmKIo38jzZw5U3/605/0zDPPKDMzU5WVlaqsrNThw4eD+5SUlGjatGnB99dcc41efPFFzZ8/Xzt37tRbb72l22+/Xeeff74KCgrsaAa6YcOxiQ8YGBTdAvc5WZsTscTRl2rnz58vSbr44ovbbF+0aJFuvvlmSVJFRYV2794d/NnNN9+s2tpaPf744/rpT3+q7OxsXXrppXrwwQcjVTZCgPubsYGRtYhFjg7OrlxaXbx48UnbZs+erdmzZ4ehIkRCw9EmfVzZ+kgQPc7oFph67/ODDappOKrs9BSbKwJOn6Mv1SI+bd7jVYvVOrgk35Nmdzk4DdnpKerfO11S6/cKxAKCE47DxAex5fjC1jW21gGECsEJx9nIwKCYMoqJEBBjCE44imVZ2nhsBCYDg2JDcG3OPTU8EoaYQHDCUfbWHNaBWr+SElwa2ZeJwWPB8AKPEhNcOlDrV6XviN3lAKeN4ISjBNbfHFaQpdTkRHuLQUikpSTq7NxMSdIHXK5FDCA44SjB+5tM7B5TghMhMEAIMYDghKMw8UFsGsXIWsQQghOO4W9q1kf7mPggFhUXtfY4N+/xqqWFAUKIbgQnHGPrPp+ONreoV0aK+vVKt7schNDZuZlyJyWo9kiTdh2st7sc4LQQnHCM4GXaomy5XC57i0FIJScmaETfQK+zxt5igNNEcMIxmPggto0KrpTCyFpEN4ITjhHocZ7LwKCYdOJECEA0IzjhCFW+I9pbc1gulzSKR1FiUmBk7dZ9Ph1tarG3GOA0EJxwhMDEB0NyM9XD7ejV7tBNA3qnKys1SUebWvTJ/lq7ywG6jeCEI2ws5/5mrHO5XMGFrblci2hGcMIRjo+o5f5mLDs+QKjG3kKA00BwwnZNzS3BRxTocca242tzMrIW0YvghO0+rqzVkcYWZbqTNLhPD7vLQRgFLtV+sr9WDUeb7C0G6CaCE7YLrL85ul+2EhKY+CCW5WalKi8rVS2W9OFen93lAN1CcMJ2xyc+4P5mPOA+J6IdwQnbHV8RJdvWOhAZjKxFtCM4Yasv649qV3XrpN+jjw0cQWwLDBAiOBGtCE7YatOxy3WDzshQz4wUe4tBRIw8dqm2/NBhHao/anM1gDmCE7YK3N8czWXauOFJS9agMzIksVIKohPBCVsFRtQyMCi+sFIKohnBCdu0tFjadMIanIgfgQFC9DgRjQhO2OazA3Wq9TcpLTlRQ/My7S4HETTqhAFClmXZWwxgiOCEbQKPoYwq9CgpkX+K8WR4QZaSElyqrjuqfd4jdpcDGOG3FWxzfEUU7m/Gm9TkRA05dpWBiRAQbQhO2GbDFzWSmPggXo3ieU5EKYITtqg90qhPqloXM2ZgUHwaXdQ6snYzI2sRZQhO2GLzHq8sS+qbnaacrFS7y4ENAj3OLXu9amlhgBCiB8EJWxyf2D3b3kJgm7NyeigtOVF1/ibtrK6zuxygywhO2OL4xO4MDIpXSYkJGtE3S5K0icu1iCIEJyLOsqwTZgzKtrUW2Csw4TsTISCaEJyIuN2HGnSo/qhSEhM0vCDL7nJgo1GBJcZ4JAVRhOBExAUu0w7vmyV3UqK9xcBWxcfmrN1WUaujTS02VwN0DcGJiNsQGBhUxP3NeNevV7qy05N1tLlFH1f67C4H6BKCExF3fGBQtq11wH4ul+v4RAhcrkWUIDgRUYePNmtbRWvPguCEJI0OLDG2h5G1iA4EJyLqw31eNbVY6pPpVt/sNLvLgQPQ40S0ITgRUcGJD4qy5XK5bK4GTjDq2NR7nx6oU52/yeZqgFMjOBFRTHyAr8rJTFWBJ1WWJW3hci2iAMGJiAoE57nc38QJio89z8lECIgGBCcipsJ7WJW+I0pMcGnksQEhgMQSY4guBCciJrD+5tC8TKWnJNlbDBwlMBHCB8xZiyhAcCJiWBEFHRlR6JHLJe2tOazqOr/d5QCdIjgRMcGJ3ZkxCF+RlZqsQWdkSOI+J5yP4EREHG1q0Za9rZfh6HGiPcXBCd+5XAtnIzgREdsqfDra1CJPWrIGHutZACcqZoAQogTBiYg48f4mEx+gPccfSfHKsix7iwE6QXAiIgL3N89l4gN04Jz8TCUnunSo/qj2fHnY7nKADhGciAhWRMGpuJMSNTSvdWFzLtfCyQhOhF11nV+7DzXI5Tp+OQ5oT/GxeWs3M/UeHIzgRNgFeptn9umhrNRke4uBowVmENrESilwMIITYcfEB+iq0ceuSHy416vmFgYIwZkIToQdK6Kgqwb36aH0lEQ1HG3Wp1V1dpcDtIvgRFg1t1jBgR70OHEqiQkujex7bN5aBgjBoQhOhNUn+2vVcLRZPdxJOisn0+5yEAWOzyBUY2sdQEcIToRV4DJtcZFHiQlMfIBTG1XIyFo4G8GJsAoODGJid3RRYOq9jyt9OtLYbG8xQDsIToTVBkbUwlBhzzT1ykhRY7OlbRU+u8sBTkJwImy8DY367EC9pOOPGQCn4nK5ggtbc7kWTuTo4CwtLdW4ceOUmZmpnJwcTZ06Vdu3bz/lcX6/X3fffbf69+8vt9utwYMHa+HChRGoGCfadGxUZP/e6erdw21vMYgqgYkQGCAEJ0qyu4DOlJWVaebMmRo3bpyampp09913a/Lkyfroo4+UkdHx0lTf+c53tH//fi1YsEBnnnmmqqqq1NTUFMHKIZ14fzPb3kIQdQJXKHgkBU7k6OB89dVX27xftGiRcnJytH79el100UUdHlNWVqadO3eqV69ekqQBAwaEu1S0g4kP0F2BkbWfHaiX70gjUzXCURx9qfarvN7W+x2BQGzPihUrdN555+nXv/61+vbtq7PPPlvz5s3T4cMdL1Pk9/vl8/navHB6Wlqs4HyjDAyCqd493CrsmSZJ+pD7nHCYqAlOy7I0d+5cXXjhhRoxYkSH++3cuVNvvvmmPvzwQy1fvlyPPPKInn/+ec2cObPDY0pLS+XxeIKvoqKicDQhruw6WC/v4Ua5kxKCS0UBJgKPpWzici0cJmqCc9asWdq8ebOWLl3a6X4tLS1yuVz685//rPPPP19XXXWVfvOb32jx4sUd9jpLSkrk9XqDr/Ly8nA0Ia4ELtOOKvQoJSlq/pnBQYITIZTT44SzOPoeZ8Ds2bO1YsUKrVmzRoWFhZ3um5+fr759+8rj8QS3nXPOObIsS3v27NFZZ5110jFut1tuN6M+Q+n4iijc30T3BKbe20yPEw7j6K6AZVmaNWuWXnzxRb3xxhsaOHDgKY/52te+pn379qmu7vjKCp988okSEhJOGboInQ2BgUGMqEU3jejrkcsl7fMeUVXtEbvLAYIcHZwzZ87Un/70Jz3zzDPKzMxUZWWlKisr21xyLSkp0bRp04Lvv/vd76p379665ZZb9NFHH2nNmjX653/+Z/3gBz9QWlqaHc2IO/X+Jm2vbB1gRY8T3dW6MEAPSVyuhbM4Ojjnz58vr9eriy++WPn5+cHXs88+G9ynoqJCu3fvDr7v0aOHVq1apZqaGp133nn63ve+p2uuuUaPPfaYHU2IS5v3eNViSfmeVOV5Uu0uB1EsOBECl2vhII6+x2lZp14BfvHixSdtGzp0qFatWhWGitAVG8uZnxahUVyUrefX79EHPJICB3F0jxPRKTjxASui4DQdn7O2pkt/SAORQHAipCzLOmHGoGxba0H0G5qXpZTEBNU0NGr3oQa7ywEkEZwIsT1fHlZ1nV/JiS6N6Os59QFAJ1KSEnROQesEGlyuhVMQnAipjcem2RuWn6XU5ER7i0FMCFyuZaUUOAXBiZDa8AUTHyC0AlPvMRECnILgREhtZGJ3hFhxUWuPc8ter5qaW2yuBiA4EUJHGpv10b7W+1CMqEWoDDqjh3q4k3SksUU7qupOfQAQZgQnQmbrPp8amy31zkhRUS9maUJoJCS4NLIv9znhHAQnQub4xO7ZcrlcNleDWDLq2OVaRtbCCQhOhMzx+5tcpkVojWaAEByE4ETIbGLiA4TJqGOr7HxcWasjjc32FoO4R3AiJPb7jmhvzWEluI5PzA2ESoEnVWf0cKu5xdLWfT67y0GcIzgREoH7m2fnZqqH29FrByAKuVwuJkKAYxCcCInj89NyfxPhUXzsci33OWE3ghMhwcTuCLdRhYyshTMQnDhtjc0t2ry3RpJ0LsGJMAlMvberul7ehkZ7i0FcIzhx2rZX1upIY4syU5M06IwedpeDGNUzI0X9eqVLUvAPNcAOBCdOW2Bg0OiibCUkMPEBwmdUcGFrLtfCPgQnTlvg/ua5DAxCmI0+NkCIkbWwE8GJ08aKKIiUwDPCHzCyFjYiOHFaDtUf1a7qeknHewNAuIzom6UEl7Tf51el94jd5SBOEZw4LZvKW+9vDuqToez0FJurQaxLT0nS2bmZkuh1wj4EJ05L8PlN1t9EhBQz4TtsRnDitDDxASItuMRYOSNrYQ+CE93W3GJpEwODEGEn9jgty7K3GMQlghPd9tmBOtX5m5Sekqghx+47AeE2JC9TKUkJ8h1p0ucHG+wuB3GI4ES3BSY+GFXoUVIi/5QQGcmJCRpekCWJ5zlhD37bodtYEQV2KeZ5TtiI4ES3bTjW4xzD85uIsOIi1uaEfcKy4vCePXs0f/58vf3226qsrJTL5VJubq4mTpyoGTNmqKioKBynRQT5jjRqR1WdJGk0A4MQYYEe59Z9PjU2tyiZWwWIoJD/a3vzzTd1zjnnaPny5SouLta0adP0/e9/X8XFxXrppZc0fPhwvfXWW6E+LSJsc7lXliUV9kxTTmaq3eUgzgzonaHM1CT5m1q0vbLW7nIQZ0Le4/zJT36iH/7wh/qP//iPDn8+Z84cvf/++6E+NSIoMDCI+5uwQ0KCS6MKPXrr04PavMerEX09dpeEOBLyHueHH36oGTNmdPjz2267TR9++GGoT4sIC07szv1N2IQZhGCXkAdnfn6+3n777Q5//s477yg/Pz/Up0UEWZZ1Qo8z295iELcCK6VsYoAQIizkl2rnzZunGTNmaP369briiiuUm5srl8ulyspKrVq1Sn/4wx/0yCOPhPq0iKAvDjboy4ZGpSQlaHgBl8hgj8BqPDuq6tRwtEnpKWEZ6wicJOT/0n784x+rd+/e+o//+A/97ne/U3NzsyQpMTFRY8eO1ZIlS/Sd73wn1KdFBG08tiLKiIIspSQxmhH2yPOkKifTrapav7bu82ncgF52l4Q4EZY/0W644QbdcMMNamxsVHV1tSTpjDPOUHJycjhOhwhj4gM4RXFRtlZ9tF8flNcQnIiYkAfntdde26X9XnzxxVCfGhGygfubcIjiQk9rcO5hpRRETsiD0+PhnlcsO3y0WdsqWp+bo8cJuxUfu8/JyFpEUsiDc9GiRaH+SDjIlr1eNbdYysl0q8DDxAew16i+2ZKODVirP6qeGSn2FoS4wMgOGDnxMRSXy2VzNYh3nvRkDeidLknavJfLtYgMghNGGBgEpwleruV5TkQIwYkusywrODDoXIITDjGKJcYQYQQnuqzCe0RVtX4lJrg0krlB4RCjjy0xtqncK8uybK4G8YDgRJcFLtOek5+ptJREe4sBjhmW71FigkvVdX5VeI/YXQ7iAMGJLju+cDWXaeEcaSmJGpKbKYnHUhAZBCe6jInd4VTFJ1yuBcKN4ESX+Jua9eE+nyRG1MJ5RrHEGCKI4ESXbKuo1dGmFmWf8Nwc4BSBtTm37PGqpYUBQggvghNdErxMW8TEB3Ces3N7KDU5QbX+Ju2srre7HMQ4ghNdEhhRy/ObcKKkxASNOLY2LJdrEW4EJ7oksAYn9zfhVMGJEJhBCGFGcOKUDtT6VX7osFwuaVQREx/AmQIja1liDOFGcOKUAvc3z8rpoaxUFiOHMwUGCH20z6ejTS32FoOYRnDilDYeu/TFxAdwsv690+VJS9bR5hZtr6y1uxzEMIITp8TEB4gGLpdLowoDl2tr7C0GMY3gRKeamlu0+dg9IwYGwemKGSCECCA40alP9tep4WizeriTdGZOD7vLAToVXJuTAUIII4ITnQo8hjK6KFuJCUx8AGcrPnapdkdVrer9TTZXg1hFcKJTgYkPuL+JaJCTlap8T6paLOnDvfQ6ER4EJzrFwCBEGwYIIdwITnSopuGoPjvQOu/naB5FQZQI3OdkIgSEC8GJDm06NjJxQO909cpIsbcYoIsYWYtwIzjRoeP3N+ltInqM6Nt6qXbPl4d1sM5vczWIRQQnOhScMYj7m4ginrRkDeqTIUnazAAhhIGjg7O0tFTjxo1TZmamcnJyNHXqVG3fvr3Lx7/11ltKSkrS6NGjw1dkjGppsbQpuAYnPU5EFy7XIpwcHZxlZWWaOXOm1q5dq1WrVqmpqUmTJ09Wff2pF6r1er2aNm2aLrvssghUGnt2VtfLd6RJqckJGpqfaXc5gJHA85xMhIBwSLK7gM68+uqrbd4vWrRIOTk5Wr9+vS666KJOj73tttv03e9+V4mJiXrppZfCWGVsCjyGMqpvtpITHf33FXCSUYGRteU1sixLLheTdyB0ouo3otfb+tdjr169Ot1v0aJF+uyzz/TLX/6yS5/r9/vl8/navOId9zcRzYblZykpwaWD9Ue1t+aw3eUgxkRNcFqWpblz5+rCCy/UiBEjOtxvx44d+tnPfqY///nPSkrqWoe6tLRUHo8n+CoqKgpV2VFrwxdMfIDolZqcGLzF8EE5l2sRWlETnLNmzdLmzZu1dOnSDvdpbm7Wd7/7Xd177706++yzu/zZJSUl8nq9wVd5eXkoSo5adf4mfbK/dT1DHkVBtBp1bIDQZmYQQog5+h5nwOzZs7VixQqtWbNGhYWFHe5XW1urdevWaePGjZo1a5YkqaWlRZZlKSkpSStXrtSll1560nFut1tutzts9UebzXtq1GJJBZ5U5Wal2l0O0C2jC7P1zLu7mXoPIefo4LQsS7Nnz9by5cu1evVqDRw4sNP9s7KytGXLljbb/vM//1NvvPGGnn/++VMej1ZMfIBYMKqodWTtlj1eNbdYrO6DkHF0cM6cOVPPPPOMXn75ZWVmZqqyslKS5PF4lJaWJqn1MuvevXu1ZMkSJSQknHT/MycnR6mpqZ3eF0VbrIiCWHBWTqbSUxJVf7RZOw/U6axcHqtCaDj6Huf8+fPl9Xp18cUXKz8/P/h69tlng/tUVFRo9+7dNlYZWyzL0qbywMAgepyIXokJLo0oaO11bmIiBISQo4PTsqx2XzfffHNwn8WLF2v16tUdfsY999yjTZs2hb3WWLHny8Oqrjuq5ESXhhdk2V0OcFqKi5gIAaHn6OBE5G04NvHBsAKPUpMTba4GOD2BkbUMEEIoEZxoI3h/89jMK0A0C8xZu63CJ39Ts73FIGYQnGgjMNUeA4MQC4p6palnerIamy19XFFrdzmIEQQngo40NmvrvtbpBs9lYBBigMvl4nItQo7gRNDWfV41tVg6o0eKCnum2V0OEBLFwQnfGSCE0CA4ERS4vzm6qCerSSBmBJYYo8eJUCE4ERQIznP7Z9taBxBKgUu1nx2oU+2RRnuLQUwgOBEUHBhUxP1NxI4+mW71zU6TZUlb9nK5FqeP4IQkqdJ7RPu8R5TgkkYdu7QFxAomQkAoEZyQpOA0e0PyspThdvQUxoCx4Mhapt5DCBCckCRtYGJ3xLDAVRR6nAgFghOSTry/mW1vIUAYjOzrkcsl7a05rAO1frvLQZQjOKHG5pbgX+KsiIJYlJmarMF9ekhqXagdOB0EJ/RxRa38TS3KSk3SoDMy7C4HCIvi4AxCXK7F6SE4oY0nrL+ZkMDEB4hNgZG1DBDC6SI4cXxFFAYGIYYFepyb99TIsix7i0FUIzhxwooo3N9E7Bqan6nkRJe+bGhU+aHDdpeDKEZwxrlD9Uf1+cEGSdLoY3+RA7HInZSoc/KzJDFvLU4PwRnnAr3NwX0y5ElPtrkaILxOvFwLdBfBGeeO39/kMi1iX2AiBJYYw+kgOOPc8RG12fYWAkTA6GMTfGzZ61VTc4u9xSBqEZxxrLnFCv7lzYooiAeD+vRQRkqiDjc269MDdXaXgyhFcMaxT6vqVOdvUnpKoobkZdpdDhB2iQkujQzMW8vlWnQTwRnHAgODiguzlcjEB4gTgQFCmxgghG4iOOMYEx8gHo1iZC1OE8EZx06cag+IF4Gp9z6uqNWRxmabq0E0IjjjlO9Io3ZUtQ6OGM1SYogjfbPT1DsjRU0tlj6q8NldDqIQwRmnPiivkWVJRb3S1CfTbXc5QMS4XC4VH/tjcTMTvqMbCM44Fby/yWMoiEPBiRBYYgzdQHDGqeMTu2fbWwhgg0CPkzlr0R0EZxyyLEsbj12iOpeBQYhDgUdSdh6ol/dwo73FIOoQnHHo84MNqmloVEpSQnC1CCCe9MpIUVGvNEnSh3u5XAszBGccClymHdnXo5Qk/gkgPgWe59zEACEY4rdmHDo+MCjb1joAOxUHpt7jPicMEZxxiIkPgBPX5uRSLcwQnHGm4WiTtlXUSmJELeLbiL4eJbikCu8RVfmO2F0OogjBGWe27PGqucVSbpZb+Z5Uu8sBbJPhTtJZOa2rAvE8J0wQnHEm8BjKmKKecrlYEQXxLTgRAgOEYIDgjDOBEbXn9s+2txDAAZgIAd1BcMYRy7K0IbiUGAODgBMHCFmWZW8xiBoEZxzZ5z2iA7V+JSW4NKLAY3c5gO2G5GUqJTFB3sON+uJgg93lIEoQnHEkcJn2nPwspaUk2lwNYL+UpAQNK2idPYvLtegqgjOOBCc+4DEUIKg4OECIkbXoGoIzjmxgRRTgJMG1OelxoosIzjjhb2rW1r2tq92zBidwXGDO2g/3edXU3GJvMYgKBGec+GifT0ebW9QrI0X9e6fbXQ7gGIPOyFCmO0lHGlv0yf46u8tBFCA448SJE7sz8QFwXEKCSyMD9zm5XIsuIDjjRHDGIO5vAicZFXyes8bWOhAdCM44sXE3K6IAHRldxMhadB3BGQeqao9oz5eH5XIdn5sTwHGBHuf2/bU6fLTZ3mLgeARnHNh07P7m2TmZykxNtrcYwIHyPanqk+lWc4uljyrodaJzBGcc2MDEB0CnXC5XcCKETVyuxSkQnHFgIxMfAKdUzAAhdBHBGeOamlu0+dgivQwMAjo2KrDEGGtz4hQIzhi3fX+tDjc2K9OdpDP79LC7HMCxApdqPz/YoJqGozZXAycjOGNcYOKD0f2ylZDAxAdAR7LTj8+qFbhKA7SH4IxxJ84YBKBzTISAriA4Y9zGciY+ALoquMQYPU50guCMYTUNR7XzQL0kaTQ9TuCUihkghC4gOGNYYH7agWdkqGdGir3FAFFgeEGWEhNcqqr1q9J7xO5y4FAEZwzj/iZgJj0lSWfltI4+30SvEx0gOGMYEx8A5gK3NRgghI4QnDGqpcUK/sXMwCCg6wIja1mbEx0hOGPUzuo61R5pUmpygobmZdpdDhA1AisIbd7jVUuLZXM1cCKCM0YFJnYfVZitpES+ZqCrhuRlyp2UoNojTfr8YL3d5cCBHP0btbS0VOPGjVNmZqZycnI0depUbd++vdNjXnzxRV1xxRXq06ePsrKyNGHCBL322msRqtg5NrIiCtAtyYkJGl6QJYnLtWifo4OzrKxMM2fO1Nq1a7Vq1So1NTVp8uTJqq/v+K/ANWvW6IorrtArr7yi9evX65JLLtE111yjjRs3RrBy+wUHBhVxfxMwdfx5TiZCwMmS7C6gM6+++mqb94sWLVJOTo7Wr1+viy66qN1jHnnkkTbvH3jgAb388sv6y1/+ojFjxoSrVEep8zfpk/21kuhxAt1RzAAhdMLRwflVXm/rX3+9evXq8jEtLS2qra3t9Bi/3y+/3x987/P5ul+kA2wur1GLJfXNTlNuVqrd5QBRJ9Dj3LrPp8bmFiUzTgAniJp/DZZlae7cubrwwgs1YsSILh/38MMPq76+Xt/5znc63Ke0tFQejyf4KioqCkXJtgnMGDSa3ibQLQN6pysrNUlHm1q0vbLW7nLgMFETnLNmzdLmzZu1dOnSLh+zdOlS3XPPPXr22WeVk5PT4X4lJSXyer3BV3l5eShKtk3g/ua5PL8JdIvL5eJ5TnQoKoJz9uzZWrFihf72t7+psLCwS8c8++yzuvXWW/Vf//Vfuvzyyzvd1+12Kysrq80rWlmWxYhaIASKi449z8kAIXyFo+9xWpal2bNna/ny5Vq9erUGDhzYpeOWLl2qH/zgB1q6dKmuvvrqMFfpLOWHDutg/VGlnDCkHoA5epzoiKODc+bMmXrmmWf08ssvKzMzU5WVlZIkj8ejtLQ0Sa2XWffu3aslS5ZIag3NadOm6dFHH9UFF1wQPCYtLU0ej8eehkRQYP3NYQVZcicl2lwNEL0Cc9Z+sr9WDUeblJ7i6F+XiCBHX6qdP3++vF6vLr74YuXn5wdfzz77bHCfiooK7d69O/j+d7/7nZqamjRz5sw2x9xxxx12NCHiuEwLhEZuVqpys9xqsaQP90b3SHuElqP/hLKsU88TuXjx4jbvV69eHZ5iosTxFVEYGAScruLCbK38aL8276nR+QO7/hgcYpuje5wwc6SxWVv3tf5lzBqcwOkLPM/J2pw4EcEZQz7c61VTi6UzerhV2DPN7nKAqBeYQWjzHkbW4jiCM4YE7m+e2y9bLpfL3mKAGDDy2BJjuw816FD9UZurgVMQnDEkMKKW+5tAaHjSkjXwjAxJ0mYeS8ExBGcMYUQtEHrFJyxsDUgEZ8yo8B5WhfeIElzHV7AHcPqCEyEwQAjHEJwxYtOx3ubQvCwe1AZCKLg25x5vlx6RQ+wjOGNEYEUULtMCoTW8IEtJCS5V1/m1z3vE7nLgAARnjNjwBQODgHBITU7UkLxMSa1r3QIEZww42tSiLXtbBy7Q4wRCL3CfcxMjayGCMyZ8XOmTv6lFnrRkDTo2dB5A6ARH1rLEGERwxoQTH0Nh4gMg9AIDhLbs9aqlhQFC8Y7gjAHBid2LuL8JhMNZOT2UmpygOn+TdlbX2V0ObEZwxgBG1ALhlZSYoJF9Wy/XfsDl2rhHcEa5g3V+fXGwQdLxy0kAQi84EQIDhOIewRnlAssdnZnTQ560ZHuLAWLYiRMhIL4RnFFuQ/D+Zra9hQAxLjCydts+n442tdhcDexEcEa54yNqGRgEhFO/XunKTk/W0eYWfVzps7sc2IjgjGLNLVZw4ulz+2fbWgsQ61wu1wn3OblcG88Izii2o6pW9UeblZGSqLNyMu0uB4h5gcu1rJQS3wjOKBa4TFtclK3EBCY+AMKt+FiPk0Wt4xvBGcWCEx/w/CYQEaOKWnucO6rqVOdvsrka2IXgjGLBgUHMGARERE5mqgo8qbIs6cO93OeMVwRnlPIebtSOqtapv0bT4wQiJjhAiPuccYvgjFKB/2j79UrXGT3c9hYDxJHARAibGVkbtwjOKHXiiigAIicwsnYTPc64RXBGqY3lrQODzmXiAyCiRhwLzr01h3Wwzm9zNbADwRmFLMuixwnYJCs1WYP7tC4Yz+Xa+ERwRqFd1fXyHm6UOylBQ/Oy7C4HiDuB5zm5XBufCM4oFOhtjuzrUUoSXyEQaccHCNXYWgfswW/dKBS4v8llWsAeowJT7+3xyrIsm6tBpBGcUYgVUQB7nZOfpeRElw7VH9WeLw/bXQ4ijOCMMg1Hm/RxZa0kepyAXVKTE4PjCz7gcm3cITijzOY9XjW3WMrLSlW+J83ucoC4Fbhcy8ja+ENwRpnAZVrW3wTsFRggxNR78YfgjDLBFVGY2B2wVeCRlC17W68CIX4QnFHEsixtPPbXLfc3AXudmdND6SmJajjarM8O1NldDiKI4Iwie2sO60CtX0kJLo3o67G7HCCuJZ7w3yETIcQXgjOKBO5vDivIUmpyor3FANBoJkKISwRnFDm+cHW2rXUAaBWcCKGckbXxhOCMIsdnDGJgEOAEgQFCH1f65G9qtrcYRAzBGSX8Tc3autcniYFBgFMU9kxTr4wUNTZb2lZRa3c5iBCCM0ps3efT0eYW9c5IUb9e6XaXA0CSy+U64XJtjb3FIGIIzihx4vqbLpfL3mIABAUu1zL1XvwgOKNEcOID7m8CjlJcRI8z3hCcUYIRtYAzjTrW49xZXS/fkUZ7i0FEEJxRoMp3RHtrDsvlkkYRnICjnNHDrb7ZabIs6UMmfI8LBGcUCEyzNyQ3Uz3cSfYWA+AkgYkQPiA44wLBGQVOHBgEwHkYWRtfCM4osIEVUQBHC9znZOq9+EBwOlxTc0vwP0bW4AScaWShRy6XtM97RFW1R+wuB2FGcDrcx5W1OtLYoszUJA06o4fd5QBoRw93ks7s0/rf52bmrY15BKfDBQYGjS7KVkICEx8ATlXMSilxg+B0OCY+AKJD8bEBQpsYWRvzCE6H28SIWiAqnNjjtCzL3mIQVgSng31Zf1Q7q+slSaOPjdoD4ExD87KUkpigmoZG7T7UYHc5CCOC08E2HbtXMuiMDPXMSLG3GACdSklK0Dn5mZKYCCHWEZwOtvGL1vubo7lMC0SF4OVaJkKIaQSngwVG1J7LwCAgKoxiibG4QHA6VEuLxcAgIMqMPrbE2Id7fWpqbrG5GoQLwelQnx2oU62/SWnJiRqSm2l3OQC6YNAZPdTDnaTDjc3aUVVndzkIE4LToQITu48q9Cgpka8JiAYJCS6N7Nva62QihNjFb2SH2ljOxAdANBp17HLtJqbei1kEp0OxlBgQnYpZKSXmEZwOVOdv0vb9tZKkMceGtwOIDoFHUrZX1upIY7O9xSAsHB2cpaWlGjdunDIzM5WTk6OpU6dq+/btpzyurKxMY8eOVWpqqgYNGqQnn3wyAtWGzgflNbIsqW92mnKyUu0uB4CBAk+qzuiRoqYWS1v3+ewuB2Hg6OAsKyvTzJkztXbtWq1atUpNTU2aPHmy6uvrOzxm165duuqqqzRp0iRt3LhRP//5z3X77bfrhRdeiGDlpycwsfu5/bm/CUQbl8vF5doYl2R3AZ159dVX27xftGiRcnJytH79el100UXtHvPkk0+qX79+euSRRyRJ55xzjtatW6eHHnpI1113XbvH+P1++f3+4Hufz96/EoP3N7lMC0SlUYXZ+t+Pq/TMu7t5LKUb7rlmuFKSnNuvc3RwfpXX2zpKrVevXh3u884772jy5Mlttk2ZMkULFixQY2OjkpOTTzqmtLRU9957b2iL7SbLsoIzBjEwCIhO4wa0Xi3aUVVHcHbDL745zO4SOhU1wWlZlubOnasLL7xQI0aM6HC/yspK5ebmttmWm5urpqYmVVdXKz8//6RjSkpKNHfu3OB7n8+noqKi0BVvoLnF0t1XnaON5V9qWEGWLTUAOD0TBvfWv18/ShXeI3aXEpUSE1x2l9CpqAnOWbNmafPmzXrzzTdPua/L1fb/9MDaeF/dHuB2u+V2u0+/yBBISkzQdWMLdd3YQrtLAdBNLpdLf3+ePX98I/yiIjhnz56tFStWaM2aNSos7DxQ8vLyVFlZ2WZbVVWVkpKS1Lt373CWCQCIA869+6rWnuKsWbP04osv6o033tDAgQNPecyECRO0atWqNttWrlyp8847r937mwAAmHB0cM6cOVN/+tOf9MwzzygzM1OVlZWqrKzU4cOHg/uUlJRo2rRpwfczZszQF198oblz52rbtm1auHChFixYoHnz5tnRBABAjHF0cM6fP19er1cXX3yx8vPzg69nn302uE9FRYV2794dfD9w4EC98sorWr16tUaPHq1//dd/1WOPPdbhoygAAJhwWYGRMwjy+XzyeDzyer3KymJkKwDEg67+7nd0jxMAAKchOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgIEkuwtwIsuyJEk+n8/mSgAAkRL4nR/IgI4QnO2ora2VJBUVFdlcCQAg0mpra+XxeDr8ucs6VbTGoZaWFu3bt0+ZmZlyuVwd7ufz+VRUVKTy8nJlZWVFsMLQiYU2SLHRjlhog0Q7nCQW2iBFrh2WZam2tlYFBQVKSOj4TiY9znYkJCSosLCwy/tnZWVF9T9KKTbaIMVGO2KhDRLtcJJYaIMUmXZ01tMMYHAQAAAGCE4AAAwQnKfB7Xbrl7/8pdxut92ldFsstEGKjXbEQhsk2uEksdAGyXntYHAQAAAG6HECAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGkuwuwIlaWlq0b98+ZWZmyuVy2V0OACACLMtSbW2tCgoKlJDQcb+S4GzHvn37VFRUZHcZAAAblJeXq7CwsMOfE5ztyMzMlNT6f15WVpbN1QAAIsHn86moqCiYAR0hONsRuDyblZVFcAJAnDnVLToGBwEAYIDgBADAAMEJAIAB7nECAIKam5vV2NhodxlhkZycrMTExNP+HIITACDLslRZWamamhq7Swmr7Oxs5eXlndYz+gQnACAYmjk5OUpPT4+5yV8sy1JDQ4OqqqokSfn5+d3+LIITAOJcc3NzMDR79+5tdzlhk5aWJkmqqqpSTk5Oty/bMjgIAOJc4J5menq6zZWEX6CNp3Mfl+AEAEg69YP/sSAUbSQ4AQAwQHACAGCA4AQARK177rlHLperzSsvLy+s52RULQAgqg0fPlyvv/568H0oJjnoDMEJAIhqSUlJYe9ltjlfxM4EAIgalmXpcGNzxM+blpxoPPJ1x44dKigokNvt1vjx4/XAAw9o0KBBYaqQ4AQAtONwY7OG/eK1iJ/3o/umKD2l69E0fvx4LVmyRGeffbb279+v+++/XxMnTtTWrVvDNpkDwQkAiFpXXnll8H+PHDlSEyZM0ODBg/X0009r7ty5YTknwQkAOElacqI+um+KLec9HRkZGRo5cqR27NgRoopORnACAE7icrmMLpk6hd/v17Zt2zRp0qSwnYPnOAEAUWvevHkqKyvTrl279O677+r666+Xz+fT9OnTw3bO6PtzAgCAY/bs2aMbb7xR1dXV6tOnjy644AKtXbtW/fv3D9s5CU4AQNRatmxZxM/JpVoAAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCQJLW0tNhdQtiFoo08jgIAcS4lJUUJCQnat2+f+vTpo5SUFOMVSpzOsiwdPXpUBw4cUEJCglJSUrr9WQQnAMS5hIQEDRw4UBUVFdq3b5/d5YRVenq6+vXrp4SE7l9wJTgBAEpJSVG/fv3U1NSk5ubIr8MZCYmJiUpKSjrt3rSt9zhLS0s1btw4ZWZmKicnR1OnTtX27ds7PaaiokLf/e53NWTIECUkJGjOnDnt7vfCCy9o2LBhcrvdGjZsmJYvXx6GFgBA7HC5XEpOTlZqampMvpKTk0NyCdrW4CwrK9PMmTO1du1arVq1Sk1NTZo8ebLq6+s7PMbv96tPnz66++67VVxc3O4+77zzjm644QbddNNN+uCDD3TTTTfpO9/5jt59991wNQUAECdclmVZdhcRcODAAeXk5KisrEwXXXTRKfe/+OKLNXr0aD3yyCNttt9www3y+Xz661//Gtz2jW98Qz179tTSpUtP+bk+n08ej0der1dZWVnG7QAARJ+u/u531OMoXq9XktSrV6/T+px33nlHkydPbrNtypQpevvtt9vd3+/3y+fztXkBANAexwSnZVmaO3euLrzwQo0YMeK0PquyslK5ublttuXm5qqysrLd/UtLS+XxeIKvoqKi0zo/ACB2OSY4Z82apc2bN3fpUmpXfPUGsGVZHd4ULikpkdfrDb7Ky8tDUgMAIPY44nGU2bNna8WKFVqzZo0KCwtP+/Py8vJO6l1WVVWd1AsNcLvdcrvdp31eAEDss7XHaVmWZs2apRdffFFvvPGGBg4cGJLPnTBhglatWtVm28qVKzVx4sSQfD4AIH7Z2uOcOXOmnnnmGb388svKzMwM9hI9Ho/S0tIktV5G3bt3r5YsWRI8btOmTZKkuro6HThwQJs2bVJKSoqGDRsmSbrjjjt00UUX6cEHH9S3v/1tvfzyy3r99df15ptvRraBAICYY+vjKB3dc1y0aJFuvvlmSdLNN9+szz//XKtXr+70uP79++vzzz8Pvn/++ef1//7f/9POnTs1ePBg/du//ZuuvfbaLtXF4ygAEH+6+rvfUc9xOgXBCQDxJyqf4wQAwOkITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMGBrcJaWlmrcuHHKzMxUTk6Opk6dqu3bt5/yuLKyMo0dO1apqakaNGiQnnzyyTY/X7x4sVwu10mvI0eOhKspAIA4YWtwlpWVaebMmVq7dq1WrVqlpqYmTZ48WfX19R0es2vXLl111VWaNGmSNm7cqJ///Oe6/fbb9cILL7TZLysrSxUVFW1eqamp4W4SACDGJdl58ldffbXN+0WLFiknJ0fr16/XRRdd1O4xTz75pPr166dHHnlEknTOOedo3bp1euihh3TdddcF93O5XMrLywtb7QCA+OSoe5xer1eS1KtXrw73eeeddzR58uQ226ZMmaJ169apsbExuK2urk79+/dXYWGhvvnNb2rjxo0dfqbf75fP52vzAgCgPY4JTsuyNHfuXF144YUaMWJEh/tVVlYqNze3zbbc3Fw1NTWpurpakjR06FAtXrxYK1as0NKlS5Wamqqvfe1r2rFjR7ufWVpaKo/HE3wVFRWFrmEAgJjimOCcNWuWNm/erKVLl55yX5fL1ea9ZVlttl9wwQX6/ve/r+LiYk2aNEn/9V//pbPPPlu//e1v2/28kpISeb3e4Ku8vPw0WwMAiFW23uMMmD17tlasWKE1a9aosLCw033z8vJUWVnZZltVVZWSkpLUu3fvdo9JSEjQuHHjOuxxut1uud3u7hUPAIgrtvY4LcvSrFmz9OKLL+qNN97QwIEDT3nMhAkTtGrVqjbbVq5cqfPOO0/JyckdnmfTpk3Kz88PSd0AgPhla3DOnDlTf/rTn/TMM88oMzNTlZWVqqys1OHDh4P7lJSUaNq0acH3M2bM0BdffKG5c+dq27ZtWrhwoRYsWKB58+YF97n33nv12muvaefOndq0aZNuvfVWbdq0STNmzIho+wAAscfWS7Xz58+XJF188cVtti9atEg333yzJKmiokK7d+8O/mzgwIF65ZVX9JOf/ERPPPGECgoK9Nhjj7V5FKWmpkb/+I//qMrKSnk8Ho0ZM0Zr1qzR+eefH/Y2AQBim8sKjKxBkM/nk8fjkdfrVVZWlt3lAAAioKu/+x0zqhYAgGhAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYKBbwXnfffepoaHhpO2HDx/Wfffdd9pFAQDgVC7LsizTgxITE1VRUaGcnJw22w8ePKicnBw1NzeHrEA7+Hw+eTweeb1eZWVl2V0OACACuvq7v1s9Tsuy5HK5Ttr+wQcfqFevXt35SAAAokKSyc49e/aUy+WSy+XS2Wef3SY8m5ubVVdXpxkzZoS8SAAAnMIoOB955BFZlqUf/OAHuvfee+XxeII/S0lJ0YABAzRhwoSQFwkAgFMYBef06dMlSQMHDtTEiROVnJwclqIAAHAqo+AM+PrXv66WlhZ98sknqqqqUktLS5ufX3TRRSEpDgAAp+lWcK5du1bf/e539cUXX+irg3JdLlfUj6oFAKAj3QrOGTNm6LzzztP//M//KD8/v90RtgAAxKJuBeeOHTv0/PPP68wzzwx1PQAAOFq3nuMcP368Pv3009M+eWlpqcaNG6fMzEzl5ORo6tSp2r59+ymPKysr09ixY5WamqpBgwbpySefPGmfF154QcOGDZPb7dawYcO0fPny064XAIBuBefs2bP105/+VIsXL9b69eu1efPmNq+uKisr08yZM7V27VqtWrVKTU1Nmjx5surr6zs8ZteuXbrqqqs0adIkbdy4UT//+c91++2364UXXgju88477+iGG27QTTfdpA8++EA33XSTvvOd7+jdd9/tTnMBAAjq1pR7CQkn563L5QrOKNTdwUEHDhxQTk6OysrKOhyZe9ddd2nFihXatm1bcNuMGTP0wQcf6J133pEk3XDDDfL5fPrrX/8a3Ocb3/iGevbsqaVLl56yDjun3LMsS4cbGVwFIH6lJSfaMnamq7/7u3WPc9euXd0urDNer1eSOp2275133tHkyZPbbJsyZYoWLFigxsZGJScn65133tFPfvKTk/Z55JFH2v1Mv98vv98ffO/z+brZgtN3uLFZw37xmm3nBwC7fXTfFKWndCueIqJblfXv3z/UdciyLM2dO1cXXnihRowY0eF+lZWVys3NbbMtNzdXTU1Nqq6uVn5+fof7VFZWtvuZpaWluvfee0+/EQCAmNfl4FyxYoWuvPJKJScna8WKFZ3u+61vfcu4kFmzZmnz5s168803T7nvV7vwgavNJ25vb5+Ouv4lJSWaO3du8L3P51NRUVGXaw+ltOREfXTfFFvODQBOkJacaHcJnepycE6dOlWVlZXB0a8d6c49ztmzZ2vFihVas2aNCgsLO903Ly/vpJ5jVVWVkpKS1Lt37073+WovNMDtdsvtdhvVHC4ul8vRlygAIN51eVRtS0tLcP3NlpaWDl8moWlZlmbNmqUXX3xRb7zxhgYOHHjKYyZMmKBVq1a12bZy5Uqdd955wblzO9pn4sSJXa4NAID2dOtxlFCZOXOm/vSnP+mZZ55RZmamKisrVVlZqcOHDwf3KSkp0bRp04LvZ8yYoS+++EJz587Vtm3btHDhQi1YsEDz5s0L7nPHHXdo5cqVevDBB/Xxxx/rwQcf1Ouvv645c+ZEsnkAgFhkdcPs2bOtRx999KTtv/3tb6077rijy58jqd3XokWLgvtMnz7d+vrXv97muNWrV1tjxoyxUlJSrAEDBljz588/6bOfe+45a8iQIVZycrI1dOhQ64UXXuhyXV6v15Jkeb3eLh8DAIhuXf3d363nOPv27asVK1Zo7NixbbZv2LBB3/rWt7Rnz57TDnQ72fkcJwDAHl393d+tS7UHDx5ss4h1QFZWlqqrq7vzkQAARIVuBeeZZ56pV1999aTtf/3rXzVo0KDTLgoAAKfq1nMPc+fO1axZs3TgwAFdeumlkqT//d//1UMPPaRHH300pAUCAOAk3QrOH/zgB/L7/fq3f/s3/eu//qskaeDAgXryySfbjIAFACDWdOtS7eHDhzV9+nTt2bNH+/fv1+bNmzVr1qwOJxgAACBWdCs4v/3tb2vJkiWSpOTkZF1++eX6zW9+o6lTp2r+/PkhLRAAACfpVnBu2LBBkyZNkiQ9//zzys3N1RdffKElS5boscceC2mBAAA4SbeCs6GhQZmZmZJap7K79tprlZCQoAsuuEBffPFFSAsEAMBJuv04yksvvaTy8nK99tprwfUxq6qqmDAAABDTuhWcv/jFLzRv3jwNGDBA48eP14QJEyS19j7HjBkT0gIBAHCSbk25J7UuKF1RUaHi4mIlJLTm73vvvaesrCwNHTo0pEVGGlPuAUD86erv/m4v/JiXl6e8vLw2284///zufhwAAFHB1mXFAACINgQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMCArcG5Zs0aXXPNNSooKJDL5dJLL710ymOeeOIJnXPOOUpLS9OQIUO0ZMmSNj9fvHixXC7XSa8jR46EqRUAgHiSZOfJ6+vrVVxcrFtuuUXXXXfdKfefP3++SkpK9NRTT2ncuHF677339KMf/Ug9e/bUNddcE9wvKytL27dvb3NsampqyOsHAMQfW4Pzyiuv1JVXXtnl/f/4xz/qtttu0w033CBJGjRokNauXasHH3ywTXC6XC7l5eWFvF4AAKLqHqff7z+p55iWlqb33ntPjY2NwW11dXXq37+/CgsL9c1vflMbN2485ef6fL42LwAA2hNVwTllyhT94Q9/0Pr162VZltatW6eFCxeqsbFR1dXVkqShQ4dq8eLFWrFihZYuXarU1FR97Wtf044dOzr83NLSUnk8nuCrqKgoUk0CAEQZl2VZlt1FSK2XV5cvX66pU6d2uM/hw4c1c+ZM/fGPf5RlWcrNzdX3v/99/frXv9b+/fuVk5Nz0jEtLS0699xzddFFF+mxxx5r93P9fr/8fn/wvc/nU1FRkbxer7Kysk67bQAA5/P5fPJ4PKf83R9VPc60tDQtXLhQDQ0N+vzzz7V7924NGDBAmZmZOuOMM9o9JiEhQePGjeu0x+l2u5WVldXmBQBAe6IqOAOSk5NVWFioxMRELVu2TN/85jeVkNB+UyzL0qZNm5Sfnx/hKgEAscjWUbV1dXX69NNPg+937dqlTZs2qVevXurXr59KSkq0d+/e4LOan3zyid577z2NHz9eX375pX7zm9/oww8/1NNPPx38jHvvvVcXXHCBzjrrLPl8Pj322GPatGmTnnjiiYi3DwAQe2wNznXr1umSSy4Jvp87d64kafr06Vq8eLEqKiq0e/fu4M+bm5v18MMPa/v27UpOTtYll1yit99+WwMGDAjuU1NTo3/8x39UZWWlPB6PxowZozVr1uj888+PWLsAALHLMYODnKSrN4gBALEjJgcHAQBgN4ITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAM2Bqca9as0TXXXKOCggK5XC699NJLpzzmiSee0DnnnKO0tDQNGTJES5YsOWmfF154QcOGDZPb7dawYcO0fPnyMFQPAIhHtgZnfX29iouL9fjjj3dp//nz56ukpET33HOPtm7dqnvvvVczZ87UX/7yl+A+77zzjm644QbddNNN+uCDD3TTTTfpO9/5jt59991wNQMAEEdclmVZdhchSS6XS8uXL9fUqVM73GfixIn62te+pn//938PbpszZ47WrVunN998U5J0ww03yOfz6a9//Wtwn2984xvq2bOnli5d2qVafD6fPB6PvF6vsrKyutcgAEBU6erv/qi6x+n3+5WamtpmW1pamt577z01NjZKau1xTp48uc0+U6ZM0dtvv93p5/p8vjYvAADaE1XBOWXKFP3hD3/Q+vXrZVmW1q1bp4ULF6qxsVHV1dWSpMrKSuXm5rY5Ljc3V5WVlR1+bmlpqTweT/BVVFQU1nYAAKJXVAXnv/zLv+jKK6/UBRdcoOTkZH3729/WzTffLElKTEwM7udyudocZ1nWSdtOVFJSIq/XG3yVl5eHpX4AQPSLquBMS0vTwoUL1dDQoM8//1y7d+/WgAEDlJmZqTPOOEOSlJeXd1Lvsqqq6qRe6IncbreysrLavAAAaE9UBWdAcnKyCgsLlZiYqGXLlumb3/ymEhJamzJhwgStWrWqzf4rV67UxIkT7SgVABBjkuw8eV1dnT799NPg+127dmnTpk3q1auX+vXrp5KSEu3duzf4rOYnn3yi9957T+PHj9eXX36p3/zmN/rwww/19NNPBz/jjjvu0EUXXaQHH3xQ3/72t/Xyyy/r9ddfD466BQDgdNja41y3bp3GjBmjMWPGSJLmzp2rMWPG6Be/+IUkqaKiQrt37w7u39zcrIcffljFxcW64oordOTIEb399tsaMGBAcJ+JEydq2bJlWrRokUaNGqXFixfr2Wef1fjx4yPaNgBAbHLMc5xOwnOcABB/YvI5TgAA7EZwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4AQAwADBCQCAAYITAAADBCcAAAYITgAADBCcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBggOAEAMAAwQkAgAGCEwAAAwQnAAAGkuwuwIksy5Ik+Xw+mysBAERK4Hd+IAM6QnC2o7a2VpJUVFRkcyUAgEirra2Vx+Pp8Ocu61TRGodaWlq0b98+ZWZmyuVydbifz+dTUVGRysvLlZWVFcEKQycW2iDFRjtioQ0S7XCSWGiDFLl2WJal2tpaFRQUKCGh4zuZ9DjbkZCQoMLCwi7vn5WVFdX/KKXYaIMUG+2IhTZItMNJYqENUmTa0VlPM4DBQQAAGCA4AQAwQHCeBrfbrV/+8pdyu912l9JtsdAGKTbaEQttkGiHk8RCGyTntYPBQQAAGKDHCQCAAYITAAADBCcAAAYITgAADBCcnfjP//xPDRw4UKmpqRo7dqz+7//+r8N9V69eLZfLddLr448/jmDFJ1uzZo2uueYaFRQUyOVy6aWXXjrlMWVlZRo7dqxSU1M1aNAgPfnkk+EvtBOmbXDid1FaWqpx48YpMzNTOTk5mjp1qrZv337K45z2XXSnHU78PubPn69Ro0YFH6ifMGGC/vrXv3Z6jNO+C9M2OPF7+KrS0lK5XC7NmTOn0/3s/i4Izg48++yzmjNnju6++25t3LhRkyZN0pVXXqndu3d3etz27dtVUVERfJ111lkRqrh99fX1Ki4u1uOPP96l/Xft2qWrrrpKkyZN0saNG/Xzn/9ct99+u1544YUwV9ox0zYEOOm7KCsr08yZM7V27VqtWrVKTU1Nmjx5surr6zs8xonfRXfaEeCk76OwsFC/+tWvtG7dOq1bt06XXnqpvv3tb2vr1q3t7u/E78K0DQFO+h5O9P777+v3v/+9Ro0a1el+jvguLLTr/PPPt2bMmNFm29ChQ62f/exn7e7/t7/9zZJkffnllxGornskWcuXL+90nzvvvNMaOnRom2233XabdcEFF4Sxsq7rShui4buoqqqyJFllZWUd7uP078KyutaOaPg+LMuyevbsaf3hD39o92fR8F1YVudtcPL3UFtba5111lnWqlWrrK9//evWHXfc0eG+Tvgu6HG24+jRo1q/fr0mT57cZvvkyZP19ttvd3rsmDFjlJ+fr8suu0x/+9vfwllmWLzzzjsntXvKlClat26dGhsbbaqqe5z8XXi9XklSr169OtwnGr6LrrQjwKnfR3Nzs5YtW6b6+npNmDCh3X2c/l10pQ0BTvweZs6cqauvvlqXX375Kfd1wnfBJO/tqK6uVnNzs3Jzc9tsz83NVWVlZbvH5Ofn6/e//73Gjh0rv9+vP/7xj7rsssu0evVqXXTRRZEoOyQqKyvbbXdTU5Oqq6uVn59vU2Vd5/TvwrIszZ07VxdeeKFGjBjR4X5O/y662g6nfh9btmzRhAkTdOTIEfXo0UPLly/XsGHD2t3Xqd+FSRuc+j0sW7ZMGzZs0Pvvv9+l/Z3wXRCcnfjqkmKWZXW4zNiQIUM0ZMiQ4PsJEyaovLxcDz30kCN+WZtor93tbXcqp38Xs2bN0ubNm/Xmm2+ecl8nfxddbYdTv48hQ4Zo06ZNqqmp0QsvvKDp06errKysw+Bx4ndh0gYnfg/l5eW64447tHLlSqWmpnb5OLu/Cy7VtuOMM85QYmLiSb3Lqqqqk/7S6cwFF1ygHTt2hLq8sMrLy2u33UlJSerdu7dNVZ0+p3wXs2fP1ooVK/S3v/3tlEvXOfm7MGlHe5zwfaSkpOjMM8/Ueeedp9LSUhUXF+vRRx9td1+nfhcmbWiP3d/D+vXrVVVVpbFjxyopKUlJSUkqKyvTY489pqSkJDU3N590jBO+C4KzHSkpKRo7dqxWrVrVZvuqVas0ceLELn/Oxo0bbb+cZmrChAkntXvlypU677zzlJycbFNVp8/u78KyLM2aNUsvvvii3njjDQ0cOPCUxzjxu+hOO9pj9/fRHsuy5Pf72/2ZE7+L9nTWhvbY/T1cdtll2rJlizZt2hR8nXfeefre976nTZs2KTEx8aRjHPFdRGwYUpRZtmyZlZycbC1YsMD66KOPrDlz5lgZGRnW559/blmWZf3sZz+zbrrppuD+//Ef/2EtX77c+uSTT6wPP/zQ+tnPfmZJsl544QW7mmBZVutotY0bN1obN260JFm/+c1vrI0bN1pffPGFZVknt2Pnzp1Wenq69ZOf/MT66KOPrAULFljJycnW888/b1cTjNvgxO/in/7pnyyPx2OtXr3aqqioCL4aGhqC+0TDd9Gddjjx+ygpKbHWrFlj7dq1y9q8ebP185//3EpISLBWrlxpWVZ0fBembXDi99Cer46qdeJ3QXB24oknnrD69+9vpaSkWOeee26bIffTp0+3vv71rwffP/jgg9bgwYOt1NRUq2fPntaFF15o/c///I8NVbcVGIL+1df06dMtyzq5HZZlWatXr7bGjBljpaSkWAMGDLDmz58f+cJPYNoGJ34X7dUvyVq0aFFwn2j4LrrTDid+Hz/4wQ+C/2336dPHuuyyy4KBY1nR8V2YtsGJ30N7vhqcTvwuWFYMAAAD3OMEAMAAwQkAgAGCEwAAAwQnAAAGCE4AAAwQnAAAGCA4AQAwQHACAGCA4ATixOrVq+VyuVRTU2N3KUBUY+YgIEZdfPHFGj16tB555BFJrQu0Hzp0SLm5uY5YlgyIVqzHCcSJlJQU5eXl2V0GEPW4VAvEoJtvvlllZWV69NFH5XK55HK5tHjx4jaXahcvXqzs7Gz993//t4YMGaL09HRdf/31qq+v19NPP60BAwaoZ8+emj17dpt1EY8ePao777xTffv2VUZGhsaPH6/Vq1fb01DABvQ4gRj06KOP6pNPPtGIESN03333SZK2bt160n4NDQ167LHHtGzZMtXW1uraa6/Vtddeq+zsbL3yyivauXOnrrvuOl144YW64YYbJEm33HKLPv/8cy1btkwFBQVavny5vvGNb2jLli0666yzItpOwA4EJxCDPB6PUlJSlJ6eHrw8+/HHH5+0X2Njo+bPn6/BgwdLkq6//nr98Y9/1P79+9WjRw8NGzZMl1xyif72t7/phhtu0GeffaalS5dqz549KigokCTNmzdPr776qhYtWqQHHnggco0EbEJwAnEsPT09GJqSlJubqwEDBqhHjx5ttlVVVUmSNmzYIMuydPbZZ7f5HL/fr969e0emaMBmBCcQx5KTk9u8d7lc7W5raWmRJLW0tCgxMVHr169XYmJim/1ODFsglhGcQIxKSUlpM6gnFMaMGaPm5mZVVVVp0qRJIf1sIFowqhaIUQMGDNC7776rzz//XNXV1cFe4+k4++yz9b3vfU/Tpk3Tiy++qF27dun999/Xgw8+qFdeeSUEVQPOR3ACMWrevHlKTEzUsGHD1KdPH+3evTskn7to0SJNmzZNP/3pTzVkyBB961vf0rvvvquioqKQfD7gdMwcBACAAXqcAAAYIDgBADBAcAIAYIDgBADAAMEJAIABghMAAAMEJwAABghOAAAMEJwAABggOAEAMEBwAgBg4P8DKeRUXP9tSwEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 500x1500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.count([scaler], num=5), bec)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You might see both the `LiveTable` and the `LivePlot` output tangled up here in the jupyter notebook.  Each is created on demand and then updated as the plan progresses.  When executing in a command line environment, the `LivePlot` is shown in a separate window.\n",
    "\n",
    "Repeat the same scan, noting that we do not need to inform the callback what to display:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Transient Scan ID: 6     Time: 2023-05-16 12:19:05\n",
      "Persistent Unique Scan ID: '50711505-9676-44d3-adf6-a176390b4995'\n",
      "New stream: 'primary'\n",
      "+-----------+------------+------------+------------+------------+------------+\n",
      "|   seq_num |       time |         m1 |      clock |         I0 |      scint |\n",
      "+-----------+------------+------------+------------+------------+------------+\n",
      "|         1 | 12:19:10.1 |     1.0000 |    5000000 |          2 |          2 |\n",
      "|         2 | 12:19:12.2 |     2.0000 |    5000000 |          3 |          2 |\n",
      "|         3 | 12:19:14.3 |     3.0000 |    5000000 |          2 |          1 |\n",
      "|         4 | 12:19:16.3 |     4.0000 |    5000000 |          3 |          2 |\n",
      "|         5 | 12:19:18.4 |     5.0000 |    5000000 |          3 |          2 |\n",
      "+-----------+------------+------------+------------+------------+------------+\n",
      "generator scan ['50711505'] (scan num: 6)\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('50711505-9676-44d3-adf6-a176390b4995',)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.scan([scaler], m1, 1, 5, 5), bec)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because this is such a useful tool, we want to make this callback happen all the time.  The RunEngine manages a list of such callbacks.  We'll make a new RunEngine and *subscribe* the `BestEffortCallback` to it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "RE = RunEngine({})\n",
    "RE.subscribe(bec)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Repeat the count of the scaler (without adding the callback in the command):"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In jupyter notebook, we can see the `LiveTable` after our scan command.  To see the `LivePlot`, we have to look up a few cells, where the plots of scaler channels *vs.* `m1` are shown, our latest data identified by `scan num` in the legend.RE(bp.count([scaler], num=5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Transient Scan ID: 1     Time: 2023-05-16 12:19:30\n",
      "Persistent Unique Scan ID: '0ff73331-444c-4c2d-8056-31ed673961b1'\n",
      "New stream: 'primary'\n",
      "+-----------+------------+------------+------------+------------+\n",
      "|   seq_num |       time |      clock |         I0 |      scint |\n",
      "+-----------+------------+------------+------------+------------+\n",
      "|         1 | 12:19:31.4 |    5000000 |          2 |          2 |\n",
      "|         2 | 12:19:32.2 |    5000000 |          1 |          2 |\n",
      "|         3 | 12:19:33.0 |    5000000 |          2 |          2 |\n",
      "|         4 | 12:19:33.8 |    5000000 |          1 |          1 |\n",
      "|         5 | 12:19:34.6 |    5000000 |          2 |          2 |\n",
      "+-----------+------------+------------+------------+------------+\n",
      "generator count ['0ff73331'] (scan num: 1)\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('0ff73331-444c-4c2d-8056-31ed673961b1',)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.count([scaler], num=5))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In jupyter notebook, we can see the `LiveTable` after our count command.  To see the `LivePlot`, we have to look up a few cells, where the plots of scaler channels *vs.* *time* are shown, our latest data identified by `scan num` in the legend.\n",
    "\n",
    "Then, repeat the scan (again, without adding the callback in the command):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Transient Scan ID: 2     Time: 2023-05-16 12:19:42\n",
      "Persistent Unique Scan ID: '08024823-0c76-4e4d-9f7d-52d9db1b5471'\n",
      "New stream: 'primary'\n",
      "+-----------+------------+------------+------------+------------+------------+\n",
      "|   seq_num |       time |         m1 |      clock |         I0 |      scint |\n",
      "+-----------+------------+------------+------------+------------+------------+\n",
      "|         1 | 12:19:47.7 |     1.0000 |    4000000 |          2 |          1 |\n",
      "|         2 | 12:19:49.7 |     2.0000 |    5000000 |          2 |          1 |\n",
      "|         3 | 12:19:51.8 |     3.0000 |    5000000 |          2 |          1 |\n",
      "|         4 | 12:19:53.8 |     4.0000 |    5000000 |          3 |          2 |\n",
      "|         5 | 12:19:55.9 |     5.0000 |    5000000 |          2 |          2 |\n",
      "+-----------+------------+------------+------------+------------+------------+\n",
      "generator scan ['08024823'] (scan num: 2)\n",
      "\n",
      "\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "('08024823-0c76-4e4d-9f7d-52d9db1b5471',)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "RE(bp.scan([scaler], m1, 1, 5, 5))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In jupyter notebook, we can see the `LiveTable` after our scan command.  Notice that the number of columns displayed is less than when we called `LiveTable` ourselves.  To see the `LivePlot`, we have to look up a few cells, where the plots of scaler channels *vs.* `m1` are shown, our latest data identified by `scan num` in the legend."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "We'll show this code as a python program:\n",
    "\n",
    "```\n",
    "#!/usr/bin/env python\n",
    "\n",
    "\"\"\"Basic: Step scan with scaler and motor\"\"\"\n",
    "\n",
    "from ophyd import EpicsMotor\n",
    "from ophyd.scaler import ScalerCH\n",
    "from bluesky import RunEngine\n",
    "import bluesky.plans as bp\n",
    "from bluesky.callbacks import LiveTable\n",
    "from bluesky.callbacks import LivePlot\n",
    "from bluesky.callbacks.best_effort import BestEffortCallback\n",
    "from apstools.devices import use_EPICS_scaler_channels\n",
    "\n",
    "\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "RE = RunEngine({})\n",
    "\n",
    "P = \"gp:\"\n",
    "m1 = EpicsMotor(f\"{P}m1\", name=\"m1\")\n",
    "scaler = ScalerCH(f\"{P}scaler1\", name=\"scaler\")\n",
    "m1.wait_for_connection()\n",
    "scaler.wait_for_connection()\n",
    "scaler.preset_time.put(0.4)\n",
    "scaler.select_channels()\n",
    "print(scaler.read())\n",
    "\n",
    "RE(bp.count([scaler], num=5), LiveTable([scaler]))\n",
    "RE(bp.scan([scaler], m1, 1, 5, 5), LiveTable([m1, scaler]))\n",
    "\n",
    "RE(bp.count([scaler], num=5), LivePlot(\"scint\"))\n",
    "RE(bp.scan([scaler], m1, 1, 5, 5), LivePlot(\"scint\", \"m1\"))\n",
    "\n",
    "bec =  BestEffortCallback()\n",
    "RE(bp.count([scaler], num=5), bec)\n",
    "RE(bp.scan([scaler], m1, 1, 5, 5), bec)\n",
    "\n",
    "RE = RunEngine({})\n",
    "RE.subscribe(bec)\n",
    "\n",
    "RE(bp.count([scaler], num=5))\n",
    "RE(bp.scan([scaler], m1, 1, 5, 5))\n",
    "```"
   ]
  }
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