plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def extract_data(root):\n",
    "    result_dict = {}  # Create an empty dictionary to store the results\n",
    "    # Walk through all directories and subdirectories\n",
    "    for folder, subdirs, files in os.walk(root):\n",
    "        if os.path.basename(folder).startswith(\"o3cpu\") and \"state\" not in os.path.basename(folder) and \"2000tries\" not in os.path.basename(folder):\n",
    "            # Check if 'terminaloutput.txt' is not in the list of files in the folder\n",
    "            if \"terminaloutput.txt\" in files or \"terminaloutput.txt\" not in files:\n",
    "                # open the \"stats.txt\" file and read the last line\n",
    "                with open(os.path.join(folder, \"stats.txt\")) as f:\n",
    "                    overallMisses = 0\n",
    "                    # read all lines into a list\n",
    "                    lines = f.readlines()\n",
    "                    for line in lines:\n",
    "                        if \"simSeconds\" in line:\n",
    "                            # extract the simSeconds value from the line\n",
    "                            simSeconds = float(line.split()[1])\n",
    "                        if \"system.cpu.numCycles\" in line:\n",
    "                            # extract the numCycles value from the line\n",
    "                            numCycles = int(line.split()[1])\n",
    "                        if \"system.cpu.branchPred.condPredicted\" in line:\n",
    "                            # extract the conditional predicted branches value from the line\n",
    "                            condPredicted = int(line.split()[1])\n",
    "                        if \"system.cpu.branchPred.condIncorrect\" in line:\n",
    "                            # extract the conditional incorrect branches value from the line\n",
    "                            condIncorrect = int(line.split()[1])\n",
    "                        if \"system.cpu.commit.branchMispredicts\" in line:\n",
    "                            # extract the branch mispredicts value from the line\n",
    "                            branchMispredicts = int(line.split()[1])\n",
    "                        if \"overallMisses::total\" in line:\n",
    "                            # extract the overall misses value from the line\n",
    "                            overallMisses += int(line.split()[1])\n",
    "                result_dict[os.path.basename(folder)] = {\"Seconds\": simSeconds, \"Cycles\": numCycles, \"Conditional Predicted\": condPredicted,\n",
    "                                                         \"Conditional Incorrect\": condIncorrect, \"Branch Mispredicts\": branchMispredicts,\n",
    "                                                         \"Overall Cache Misses\": overallMisses}  # Create an empty dictionary for the folder\n",
    "\n",
    "    return result_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Branch Predictor\tSeconds\t\tCycles\t\tConditional Predicted\tConditional Incorrect\tBranch Mispredicts\tOverall Cache Misses\n",
      "bimodebp\t\t0.008116\t\t8116133\t\t857885\t\t\t\t6890\t\t\t\t6308\t\t\t\t56763\n",
      "localBP\t\t0.008116\t\t8116491\t\t863387\t\t\t\t7684\t\t\t\t7302\t\t\t\t56884\n",
      "ltage\t\t0.567366\t\t567365605\t\t50246568\t\t\t\t41038\t\t\t\t40579\t\t\t\t3898824\n",
      "multiperspective perceptron 64KB\t\t3.019915\t\t3019915267\t\t275222893\t\t\t\t3325693\t\t\t\t3325101\t\t\t\t19507590\n",
      "multiperspective perceptron 8KB\t\t0.240178\t\t240177980\t\t22681575\t\t\t\t114187\t\t\t\t113674\t\t\t\t1637081\n",
      "multiperspective perceptron tage 64kb\t\t2.068201\t\t2068200769\t\t186528069\t\t\t\t791390\t\t\t\t743424\t\t\t\t14107147\n",
      "multiperspective perceptron tage 8kb\t\t1.888016\t\t1888016027\t\t170538832\t\t\t\t732909\t\t\t\t688196\t\t\t\t12821993\n",
      "TAGE\t\t0.008017\t\t8016975\t\t815200\t\t\t\t2685\t\t\t\t2224\t\t\t\t56570\n",
      "tage sc l 64kb\t\t2.197581\t\t2197580504\t\t195777696\t\t\t\t771585\t\t\t\t771121\t\t\t\t14925645\n",
      "tage sc l 8kb\t\t2.100039\t\t2100038862\t\t191772063\t\t\t\t765089\t\t\t\t764627\t\t\t\t14304415\n",
      "tournamentBP\t\t0.022431\t\t22430566\t\t2195718\t\t\t\t10817\t\t\t\t10356\t\t\t\t154371\n"
     ]
    }
   ],
   "source": [
    "data = extract_data(\".\")\n",
    "\n",
    "# print data in a table\n",
    "print(\"Branch Predictor\\tSeconds\\t\\tCycles\\t\\tConditional Predicted\\tConditional Incorrect\\tBranch Mispredicts\\tOverall Cache Misses\")\n",
    "for key, value in data.items():\n",
    "    print(\"{}\\t\\t{}\\t\\t{}\\t\\t{}\\t\\t\\t\\t{}\\t\\t\\t\\t{}\\t\\t\\t\\t{}\".format(\" \".join(key.split(\"-\")[2:]), value[\"Seconds\"], value[\"Cycles\"], value[\"Conditional Predicted\"],\n",
    "                                                                         value[\"Conditional Incorrect\"], value[\"Branch Mispredicts\"],\n",
    "                                                                         value[\"Overall Cache Misses\"]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(xvalues, yvalues, title):\n",
    "    import matplotlib.pyplot as plt\n",
    "    import numpy as np\n",
    "    import plotly.graph_objects as go\n",
    "    from plotly.offline import iplot\n",
    "    from plotly.offline import plot\n",
    "    import plotly.tools as tls\n",
    "    import os\n",
    "\n",
    "    if not os.path.exists(\"graph_output\"):\n",
    "        os.mkdir(\"graph_output\")\n",
    "    \n",
    "    \n",
    "    fig = plt.figure(figsize=(10, 10))\n",
    "    ax = fig.add_subplot(111)\n",
    "    print(xvalues)\n",
    "\n",
    "    xticks = {\n",
    "        'o3cpu-spectre-tage-sc-l-64kb': \"TAGE SC L 64KB\",\n",
    "        'o3cpu-spectre-localBP': \"Local BP\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-8KB': \"MPP 8KB\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-tage-64kb' : \"MPP TAGE 64KB\",\n",
    "        'o3cpu-spectre-ltage': \"LTAGE\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-64KB' : \"MPP 64KB\",\n",
    "        'o3cpu-spectre-bimodebp': \"BiMode BP\",\n",
    "        'o3cpu-spectre-tournamentBP' : \"Tournament BP\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-tage-8kb': \"MPP TAGE 8KB\",\n",
    "        'o3cpu-spectre-TAGE': \"TAGE\",\n",
    "        'o3cpu-spectre-tage-sc-l-8kb': \"TAGE SC L 8KB\",\n",
    "    }\n",
    "\n",
    "    ax.bar(np.arange(len(xvalues)), yvalues, width=0.8, color=\"blue\", align=\"center\")\n",
    "    ax.set_xticks(np.arange(len(xvalues)))\n",
    "    # set xticks to the branch predictor names\n",
    "    ax.set_xticklabels([xticks[x] for x in xvalues], rotation=90)\n",
    "    # ax.set_xticklabels(xvalues, rotation=90)\n",
    "    ax.set_ylabel(title)\n",
    "    ax.set_xlabel(\"Branch Predictors\")\n",
    "    ax.set_title(title + \" for Each Branch Predictor\")\n",
    "\n",
    "    for i, value in enumerate(yvalues):\n",
    "        if value > 10000:\n",
    "            # make text scientific notation and reduce font size\n",
    "            ax.text(i, value, \"{:.1e}\".format(value), ha='center', va='bottom', fontsize=8)\n",
    "        else:\n",
    "            # reduce to 2 decimal places only if value is greater than 0.01\n",
    "            if value > 0.01:\n",
    "                value = round(value, 2)\n",
    "            ax.text(i, value, str(value), ha='center', va='bottom')\n",
    "\n",
    "    plt.savefig(title + \".png\", bbox_inches=\"tight\")\n",
    "    plt.show()\n",
    "    plotly_fig = tls.mpl_to_plotly(ax.figure)\n",
    "    \n",
    "    #iplot(plotly_fig)\n",
    "    \n",
    "    colors = \"Blue\"\n",
    "    pfig = go.Figure(data=[go.Bar(x=[xticks[x] for x in xvalues],y=yvalues,text=[f'{val:.2e}' for val in yvalues],textposition=\"outside\", marker_color=colors)])\n",
    "    \n",
    "    #t = {family = \"Open Sans\", size = 14,color = 'blue'}\n",
    "    pfig.update_layout(width=900,height=900,title=title + \" for Each Benchmark\", xaxis_title=\"Branch Predictors\", yaxis_title=title, font=dict(family=\"Sans-Serif\", size=16) )\n",
    "    pfig.update_yaxes(tickformat=\".2e\")\n",
    "    output_file_name = \"graph_output/\" + title + \".png\"\n",
    "    pfig.write_image(output_file_name)\n",
    "    pfig.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a list of the branchpredictors names\n",
    "branchpredictors = []\n",
    "for key, value in data.items():\n",
    "    branchpredictors.append(key)\n",
    "    # # if data length is more than 3, then take every value from the 2nd and join them with a hyphen\n",
    "    # # also capitalize the first letter of each word\n",
    "    # if len(key.split(\"-\")) > 3:\n",
    "    #     branchpredictors.append(\" \".join(key.split(\"-\")[2:]).title())\n",
    "    # else:\n",
    "    #     # if bp is in the branchpredictors name, then remove it and capitalize the first letter of each word\n",
    "    #     # not case sensitive\n",
    "    #     if \"bp\" in key.split(\"-\")[2] or \"BP\" in key.split(\"-\")[2]:\n",
    "    #         # remove the \"bp\" from the branchpredictors name and capitalize the first letter of each word\n",
    "    #         branchpredictors.append(key.split(\"-\")[2].replace(\"bp\", \"\").replace(\"BP\", \"\").title())\n",
    "    #     else:\n",
    "    #         branchpredictors.append(key.split(\"-\")[2].title())\n",
    "\n",
    "# Create a list of the number of cycles\n",
    "cycles = []\n",
    "for key, value in data.items():\n",
    "    cycles.append(value[\"Cycles\"])\n",
    "\n",
    "# Create a list of the number of seconds\n",
    "seconds = []\n",
    "for key, value in data.items():\n",
    "    seconds.append(value[\"Seconds\"])\n",
    "\n",
    "# Create a list of the number of conditional predicted branches\n",
    "condPredicted = []\n",
    "for key, value in data.items():\n",
    "    condPredicted.append(value[\"Conditional Predicted\"])\n",
    "\n",
    "# Create a list of the number of conditional incorrect branches\n",
    "condIncorrect = []\n",
    "for key, value in data.items():\n",
    "    condIncorrect.append(value[\"Conditional Incorrect\"])\n",
    "\n",
    "# Create a list of the number of branch mispredicts\n",
    "branchMispredicts = []\n",
    "for key, value in data.items():\n",
    "    branchMispredicts.append(value[\"Branch Mispredicts\"])\n",
    "\n",
    "# Create a list of the number of overall cache misses\n",
    "overallMisses = []\n",
    "for key, value in data.items():\n",
    "    overallMisses.append(value[\"Overall Cache Misses\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.9.13\n",
      "['o3cpu-spectre-bimodebp', 'o3cpu-spectre-localBP', 'o3cpu-spectre-ltage', 'o3cpu-spectre-multiperspective-perceptron-64KB', 'o3cpu-spectre-multiperspective-perceptron-8KB', 'o3cpu-spectre-multiperspective-perceptron-tage-64kb', 'o3cpu-spectre-multiperspective-perceptron-tage-8kb', 'o3cpu-spectre-TAGE', 'o3cpu-spectre-tage-sc-l-64kb', 'o3cpu-spectre-tage-sc-l-8kb', 'o3cpu-spectre-tournamentBP']\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\anime\\AppData\\Local\\Packages\\PythonSoftwareFoundation.Python.3.9_qbz5n2kfra8p0\\LocalCache\\local-packages\\Python39\\site-packages\\plotly\\matplotlylib\\renderer.py:645: UserWarning:\n",
      "\n",
      "Looks like the annotation(s) you are trying \n",
      "to draw lies/lay outside the given figure size.\n",
      "\n",
      "Therefore, the resulting Plotly figure may not be \n",
      "large enough to view the full text. To adjust \n",
      "the size of the figure, use the 'width' and \n",
      "'height' keys in the Layout object. Alternatively,\n",
      "use the Margin object to adjust the figure's margins.\n",
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      "3.9.13\n",
      "['o3cpu-spectre-bimodebp', 'o3cpu-spectre-localBP', 'o3cpu-spectre-ltage', 'o3cpu-spectre-multiperspective-perceptron-64KB', 'o3cpu-spectre-multiperspective-perceptron-8KB', 'o3cpu-spectre-multiperspective-perceptron-tage-64kb', 'o3cpu-spectre-multiperspective-perceptron-tage-8kb', 'o3cpu-spectre-TAGE', 'o3cpu-spectre-tage-sc-l-64kb', 'o3cpu-spectre-tage-sc-l-8kb', 'o3cpu-spectre-tournamentBP']\n"
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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "marker": {
          "color": "Blue"
         },
         "text": [
          "8.12e-03",
          "8.12e-03",
          "5.67e-01",
          "3.02e+00",
          "2.40e-01",
          "2.07e+00",
          "1.89e+00",
          "8.02e-03",
          "2.20e+00",
          "2.10e+00",
          "2.24e-02"
         ],
         "textposition": "outside",
         "type": "bar",
         "x": [
          "BiMode BP",
          "Local BP",
          "LTAGE",
          "MPP 64KB",
          "MPP 8KB",
          "MPP TAGE 64KB",
          "MPP TAGE 8KB",
          "TAGE",
          "TAGE SC L 64KB",
          "TAGE SC L 8KB",
          "Tournament BP"
         ],
         "y": [
          0.008116,
          0.008116,
          0.567366,
          3.019915,
          0.240178,
          2.068201,
          1.888016,
          0.008017,
          2.197581,
          2.100039,
          0.022431
         ]
        }
       ],
       "layout": {
        "font": {
         "family": "Sans-Serif",
         "size": 16
        },
        "height": 900,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
              "size": 10,
              "solidity": 0.2
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
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   "source": [
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  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.9.13\n",
      "['o3cpu-spectre-bimodebp', 'o3cpu-spectre-localBP', 'o3cpu-spectre-ltage', 'o3cpu-spectre-multiperspective-perceptron-64KB', 'o3cpu-spectre-multiperspective-perceptron-8KB', 'o3cpu-spectre-multiperspective-perceptron-tage-64kb', 'o3cpu-spectre-multiperspective-perceptron-tage-8kb', 'o3cpu-spectre-TAGE', 'o3cpu-spectre-tage-sc-l-64kb', 'o3cpu-spectre-tage-sc-l-8kb', 'o3cpu-spectre-tournamentBP']\n"
     ]
    },
    {
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      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "data": [
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          "MPP TAGE 8KB",
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        "width": 900,
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         }
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     },
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   ],
   "source": [
    "plot(branchpredictors, condPredicted, \"Conditional Predicted Branches\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.9.13\n",
      "['o3cpu-spectre-bimodebp', 'o3cpu-spectre-localBP', 'o3cpu-spectre-ltage', 'o3cpu-spectre-multiperspective-perceptron-64KB', 'o3cpu-spectre-multiperspective-perceptron-8KB', 'o3cpu-spectre-multiperspective-perceptron-tage-64kb', 'o3cpu-spectre-multiperspective-perceptron-tage-8kb', 'o3cpu-spectre-TAGE', 'o3cpu-spectre-tage-sc-l-64kb', 'o3cpu-spectre-tage-sc-l-8kb', 'o3cpu-spectre-tournamentBP']\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
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     },
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   ],
   "source": [
    "plot(branchpredictors, condIncorrect, \"Conditional Incorrect Branches\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.9.13\n",
      "['o3cpu-spectre-bimodebp', 'o3cpu-spectre-localBP', 'o3cpu-spectre-ltage', 'o3cpu-spectre-multiperspective-perceptron-64KB', 'o3cpu-spectre-multiperspective-perceptron-8KB', 'o3cpu-spectre-multiperspective-perceptron-tage-64kb', 'o3cpu-spectre-multiperspective-perceptron-tage-8kb', 'o3cpu-spectre-TAGE', 'o3cpu-spectre-tage-sc-l-64kb', 'o3cpu-spectre-tage-sc-l-8kb', 'o3cpu-spectre-tournamentBP']\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
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         "marker": {
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         },
         "text": [
          "6.31e+03",
          "7.30e+03",
          "4.06e+04",
          "3.33e+06",
          "1.14e+05",
          "7.43e+05",
          "6.88e+05",
          "2.22e+03",
          "7.71e+05",
          "7.65e+05",
          "1.04e+04"
         ],
         "textposition": "outside",
         "type": "bar",
         "x": [
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          "MPP 64KB",
          "MPP 8KB",
          "MPP TAGE 64KB",
          "MPP TAGE 8KB",
          "TAGE",
          "TAGE SC L 64KB",
          "TAGE SC L 8KB",
          "Tournament BP"
         ],
         "y": [
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       "layout": {
        "font": {
         "family": "Sans-Serif",
         "size": 16
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        "height": 900,
        "template": {
         "data": {
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             "color": "#2a3f5f"
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            "error_y": {
             "color": "#2a3f5f"
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             "line": {
              "color": "#E5ECF6",
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            },
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            },
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             "startlinecolor": "#2a3f5f"
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            "type": "carpet"
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           {
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            "type": "choropleth"
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          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
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            "colorscale": [
             [
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              "#0d0887"
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          },
          "title": {
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        "width": 900,
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   ],
   "source": [
    "plot(branchpredictors, branchMispredicts, \"Branch Mispredicts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.9.13\n",
      "['o3cpu-spectre-bimodebp', 'o3cpu-spectre-localBP', 'o3cpu-spectre-ltage', 'o3cpu-spectre-multiperspective-perceptron-64KB', 'o3cpu-spectre-multiperspective-perceptron-8KB', 'o3cpu-spectre-multiperspective-perceptron-tage-64kb', 'o3cpu-spectre-multiperspective-perceptron-tage-8kb', 'o3cpu-spectre-TAGE', 'o3cpu-spectre-tage-sc-l-64kb', 'o3cpu-spectre-tage-sc-l-8kb', 'o3cpu-spectre-tournamentBP']\n"
     ]
    },
    {
     "data": {
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zuv/++yUpx/M0p3rPnTtn7f9ly5YpMzNT48aNy/Zc09/3/7777rO58u7j46M6derkef9nzJghHx8fVahQQaGhodqwYYOioqI0cuRIm3YDBgyw2c+YmBgdPHhQTzzxhM6dO2c9jlNTU9W+fXutW7dOmZmZysjI0I8//qjw8HBVqVLFuvy9996rsLCwW9a3ePFiBQUF5Xh1Oqdj4Ubbt2/X6dOnNXz4cHl4eFind+3aVXXr1rXekXCjvFztBHAd4eoW1q1bp27dusnf3z9f34mSdS/53188DIrCKitQZIWs3Pw9hGU9X7Bw4UJrm4ULFyo4OFi1a9eWdP1WHcMw9Morr8jHx8fmNX78eEnS6dOnbbZTrVq1bNu+fPmyxo0bp4CAALm7u6t8+fLy8fFRYmKikpKS8rnn/8fLy8tmH28lMzNT7733nmrVqmVTz+7du23qOXz4sOrUqZOngTBu/IVLkjVoXbhwQVL++vJmnnjiCa1atUpxcXFatmyZnnjiiTwvO3z4cNWuXVudO3dW5cqVNWjQIK1cudKmzeuvv67ExETVrl1bDRo00AsvvKDdu3db59uzP7dalz3OnDmjS5cuqU6dOtnm3XvvvcrMzMw2/HhOx+TN1KpVSx06dMj2yjrOpOu3Jvbo0UPe3t7y8vKSj4+PdUCFrGMo67m8nJ6D+zsPD49sz0uWKVPGevzcSokSJax1durUSSNGjNC3336rAwcO5DiEfE59cv78eY0YMUIVK1aUp6enfHx8rO1yOk9vdcwfPnxYLi4uNqE0N39fV9b68rr/jzzyiFatWqWff/5ZW7Zs0dmzZzVlypRsoe7v+50V+AcMGJDtOP7888+VlpampKQknTlzRpcvX1atWrWybTunY/HvDh8+nKfjICdHjx7NdTt169a1zs/i6upq2rOFwN2AZ65uITU1VUFBQRo0aJB69uxp9/KjRo3K9te49u3bWx80BQobb29v+fn53fKX1d27d6tSpUrWXxDd3d0VHh6upUuX6uOPP1ZCQoI2bNigCRMmWJfJGr571KhRuf519u/PNNz4V+Es//rXvzRz5kyNHDlSzZs3t34hbJ8+fUwZIrxu3bqSrj8TER4efsv2EyZM0CuvvKJBgwbpjTfeUNmyZeXi4qKRI0fmu57crowY//95lvz05c10795d7u7uGjBggNLS0tS7d+88L1uhQgXFxMToxx9/1IoVK7RixQrNnDlTERER+vLLLyVdf07v8OHDWr58uX766Sd9/vnneu+99zRt2jQNGTLErv251boKWk7H5O1ITExUmzZt5OXlpddff101atSQh4eHduzYodGjR+frGLLnylpehYSEyNvbW+vWrcs2L6c+6d27tzZu3KgXXnhBwcHBKlmypDIzM9WpU6cc9+lWx7w9bnddlStXVocOHW7Z7u/7nbVf//nPf3Id/rxkyZJKS0vLUx2FwY1X5gHcGuHqFjp37nzT77RIS0vTSy+9pPnz5ysxMVH169fXO++8o7Zt20q6/iGa9dC0JO3atcv6fSFAYfXwww/rs88+0/r1660jf93o119/1ZEjRzRs2DCb6Y8//ri+/PJLrV69Wvv27ZNhGNZbAiVZb7u655578vSLS24WLVqkAQMGaMqUKdZpV65cUWJiYr7XeaOWLVuqTJkymj9/vv7973/f8hfVRYsWqV27dpoxY4bN9MTERJUvX976vkaNGtqyZYuuXr1628OZm9WXWTw9PRUeHq65c+davzTZHm5uburWrZu6deumzMxMDR8+XNOnT9crr7xiDUVly5bVwIEDNXDgQKWkpKh169Z69dVXNWTIELv352brsoePj4+KFy+uAwcOZJu3f/9+ubi4KCAgwK512is6Olrnzp3TkiVL1Lp1a+v0rJHpsmQNePL777+b8m+eHxkZGUpJSblluwsXLmj16tV67bXXNG7cOOv027mVs0aNGsrMzNQff/xRaL+3KevfyMvL66b/Rj4+PvL09MyxP3I6FnPazo0jsOYkt9sDs273PXDggB588MFs287r7cAAcsafIm7TM888o02bNmnBggXavXu3evXqpU6dOuX6A+Tzzz9X7dq1cx2FDSgMXnjhBXl6emrYsGHZhk0+f/68/vnPf6p48eJ64YUXbOZ16NBBZcuW1cKFC7Vw4UI1a9bM5raZChUqqG3btpo+fbpOnTqVbbs5PcuRk2LFimX7C/QHH3xwW8NM36h48eIaPXq09u3bp9GjR+f41+65c+dq69atudbzzTffZHvm6dFHH9XZs2f14YcfZlufvX+dN6svbzRq1CiNHz9er7zyil3L/f0YcXFxUcOGDSXJ+hf6v7cpWbKkatasaZ1vz/7cal32KFasmDp27Kjly5fbDOWfkJCgefPmqWXLlja37xWErPB+4zGQnp6ujz/+2KZd48aNVa1aNU2dOjXbHxLyc3XHXr/88otSUlIUFBR0y7Y57ZMkTZ06Nd/bDw8Pl4uLi15//fVsV77uxP7nRUhIiGrUqKHJkyfnGEKzjuNixYopLCxMy5YtU1xcnHX+vn379OOPP95yO48++qh27dqlpUuXZpuX1RdZjx/8/Vhp0qSJKlSooGnTptmcMytWrNC+ffvUtWvXW+8ogFxx5eo2xMXFaebMmYqLi7MOtTxq1CitXLlSM2fOtLkdSrr+l/WvvvpKY8aMcUS5QJ7VqlVLX375pfr166cGDRpo8ODBqlatmo4cOaIZM2bo7Nmzmj9/vs3Q4dL1qw49e/bUggULlJqaqsmTJ2db90cffaSWLVuqQYMGevLJJ1W9enUlJCRo06ZNOn78eI7fDfV3Dz/8sObMmSNvb2/dd9992rRpk37++WeVK1fOtD544YUXtHfvXk2ZMkW//PKLHnvsMfn6+io+Pl7Lli3T1q1btXHjRms9r7/+ugYOHKgWLVpoz549+uqrr7J9wXJERIRmz56tqKgobd26Va1atVJqaqp+/vlnDR8+3OZLfPPCjL68UVBQUJ5+cf67IUOG6Pz583rwwQdVuXJlHT16VB988IGCg4N17733Sro+wEDbtm0VEhKismXLavv27Vq0aJGeeeYZu/cnL+uyx5tvvqlVq1apZcuWGj58uFxdXTV9+nSlpaVZv8vtduzYsUNz587NNr1GjRpq3ry5WrRooTJlymjAgAF69tlnZbFYNGfOnGyBwcXFRZ988om6deum4OBgDRw4UH5+ftq/f7/27t2bp1/K8yopKcla87Vr13TgwAF98skn8vT0zNPPMC8vL7Vu3VqTJk3S1atXValSJf3000/ZrsbZo2bNmnrppZf0xhtvqFWrVurZs6fc3d21bds2+fv7a+LEiflet1lcXFz0+eefq3PnzqpXr54GDhyoSpUq6cSJE/rll1/k5eWl7777TtL1YeVXrlypVq1aafjw4bp27Zo++OAD1atX75a3Zb/wwgtatGiRevXqpUGDBikkJETnz5/Xt99+q2nTpikoKEg1atRQ6dKlNW3aNJUqVUolSpRQaGioqlWrpnfeeUcDBw5UmzZt1LdvX+tQ7IGBgXruuefuRFcBzuuOj09YhOlvQzNnDVtaokQJm5erq6vRu3fvbMvPmzfPcHV1NeLj4+9g1UD+7d692+jbt6/h5+dn3HPPPYavr6/Rt29fY8+ePbkus2rVKkOSYbFYjGPHjuXY5vDhw0ZERITh6+tr3HPPPUalSpWMhx9+2Fi0aJG1Tdaw19u2bcu2/IULF4yBAwca5cuXN0qWLGmEhYUZ+/fvzzZccX6HYr/RokWLjI4dOxply5Y1XF1dDT8/P+Pxxx83oqOjrW2uXLliPP/884afn5/h6elpPPDAA8amTZuMNm3aGG3atLFZ36VLl4yXXnrJqFatmrVPH3vsMesw4LkNF24Y1z+Dxo8fb3df5kb/fyj2m8nLUOxZfVShQgXDzc3NqFKlijFs2DDj1KlT1jZvvvmm0axZM6N06dKGp6enUbduXeOtt94y0tPT7d6fvK7r727Wtzt27DDCwsKMkiVLGsWLFzfatWtnbNy40abNzY7Jm20vt9eNx+qGDRuM+++/3/D09DT8/f2NF1980fjxxx+zHb+GYRjr1683HnroIaNUqVJGiRIljIYNGxoffPCBdf6AAQOMEiVKZKsn69/yVv4+FLvFYjHKli1rdO/e3fjtt99yXOeNx0eW48ePGz169DBKly5teHt7G7169TJOnjyZ7TjObR1Z/R0bG2sz/YsvvjAaNWpkuLu7G2XKlDHatGljrFq1yjq/atWqOQ7Vn9P5mJO8nBdZny3ffPNNjvN37txp9OzZ0yhXrpzh7u5uVK1a1ejdu7exevVqm3Zr1641QkJCDDc3N6N69erGtGnTcvx3+vtnm2EYxrlz54xnnnnGqFSpkuHm5mZUrlzZGDBggHH27Flrm+XLlxv33Xef4erqmm1Y9oULF1r7sWzZska/fv2M48eP22wjt2MJQO4shlFIrqUXARaLRUuXLrU+4L5w4UL169dPe/fuzfZMRsmSJa3fZp+lffv28vLyyvEyPgAAAICijdsCb0OjRo2UkZGh06dP3/IZqtjYWP3yyy/69ttv71B1AAAAAO4kwtUtpKSk6NChQ9b3sbGxiomJUdmyZVW7dm3169dPERERmjJliho1aqQzZ85o9erVatiwoc1DoV988YX8/PxuOvIgAAAAgKKL2wJvITo6Wu3atcs2fcCAAZo1a5auXr2qN998U7Nnz9aJEydUvnx53X///XrttdfUoEEDSde/96Jq1aqKiIjQW2+9dad3AQAAAMAdQLgCAAAAABPwPVcAAAAAYALCFQAAAACYgAEtcpCZmamTJ0+qVKlSslgsji4HAAAAgIMYhqGLFy/K399fLi43vzZFuMrByZMnFRAQ4OgyAAAAABQSx44dU+XKlW/ahnCVg1KlSkm63oFeXl4OrgYAAACAoyQnJysgIMCaEW6GcJWDrFsBvby8CFcAAAAA8vS4EANaAAAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJjAoeFq4sSJatq0qUqVKqUKFSooPDxcBw4cuOVy33zzjerWrSsPDw81aNBA//vf/2zmG4ahcePGyc/PT56enurQoYMOHjxYULsBAAAAAI4NV2vXrtXTTz+tzZs3a9WqVbp69ao6duyo1NTUXJfZuHGj+vbtq8GDB2vnzp0KDw9XeHi4fv/9d2ubSZMm6b///a+mTZumLVu2qESJEgoLC9OVK1fuxG4BAAAAuAtZDMMwHF1EljNnzqhChQpau3atWrdunWObxx9/XKmpqfr++++t0+6//34FBwdr2rRpMgxD/v7+ev755zVq1ChJUlJSkipWrKhZs2apT58+t6wjOTlZ3t7eSkpKkpeXlzk7BwAAAKDIsScbFKpnrpKSkiRJZcuWzbXNpk2b1KFDB5tpYWFh2rRpkyQpNjZW8fHxNm28vb0VGhpqbfN3aWlpSk5OtnkBAAAAgD0KTbjKzMzUyJEj9cADD6h+/fq5touPj1fFihVtplWsWFHx8fHW+VnTcmvzdxMnTpS3t7f1FRAQcDu7AgAAAOAuVGjC1dNPP63ff/9dCxYsuOPbHjt2rJKSkqyvY8eO3fEaAAAAABRtro4uQJKeeeYZff/991q3bp0qV65807a+vr5KSEiwmZaQkCBfX1/r/Kxpfn5+Nm2Cg4NzXKe7u7vc3d1vYw8AAAAA3O0ceuXKMAw988wzWrp0qdasWaNq1ardcpnmzZtr9erVNtNWrVql5s2bS5KqVasmX19fmzbJycnasmWLtQ0AAAAAmM2hV66efvppzZs3T8uXL1epUqWsz0R5e3vL09NTkhQREaFKlSpp4sSJkqQRI0aoTZs2mjJlirp27aoFCxZo+/bt+vTTTyVJFotFI0eO1JtvvqlatWqpWrVqeuWVV+Tv76/w8HCH7CcAAAAA5+fQcPXJJ59Iktq2bWszfebMmYqMjJQkxcXFycXl/y6wtWjRQvPmzdPLL7+sf//736pVq5aWLVtmMwjGiy++qNTUVA0dOlSJiYlq2bKlVq5cKQ8PjwLfJwAAAAB3p0L1PVeFBd9zBQAAAEAqwt9zBQAAAABFFeEKAAAAAExAuAJQZF25ckXh4eGqXbu2goKC9NBDD+nQoUM5tv3+++9Vt25d1apVSz179lRycrJpdRw8eFAtWrRQ7dq11bRpU+3du1eSdO7cOQUHB1tftWvXlqurq86fP2/atgEAQOFBuAJQpA0dOlQHDhzQrl279Mgjj2jIkCHZ2qSkpGjw4MFatmyZDh48KH9/f73xxht2befIkSPZBt/JMmzYMA0dOlR//vmnRo8ebR2Qp1y5coqJibG+hg4dqs6dO6ts2bL27iYAACgCCFcAiiwPDw916dJFFotFknT//ffryJEj2dqtWLFCjRo1Ut26dSVJw4cP1/z5863z58yZo9DQUDVu3FitW7fWrl278lzD6dOntX37dvXv31+S9Oijj+rYsWM5XkGbMWOGBg8ebM8uAgCAIsShQ7EDgJnef/99PfLII9mmx8XFqWrVqtb3gYGBOnXqlK5du6YtW7Zo/vz5Wrdundzd3fXrr7/qiSeesN7adyvHjh2Tn5+fXF2vf5xaLBZVqVJFcXFxqlmzprXdxo0bdeHCBT388MO3uZcAAKCwIlwBcAoTJkzQoUOHtHr1aruWW758uXbt2qXQ0FDrtPPnz+vy5ctKSEiwfvl4enq64uLiFBwcLElq2LChZs+eneftzJgxQxEREdYQBgAAnA8/5QEUeZMnT9aSJUv0888/q3jx4tnmV6lSRatWrbK+P3LkiPVqk2EYGjBggCZMmJBtucDAQMXExFiXiYyMVHR0tE2bgIAA61WwrPXFxcWpSpUq1jYpKSn6+uuvtW3bNnN2GAAAFEo8cwWgSHv33Xc1f/58rVq1SqVLl86xTadOnbRjxw7t379fkvTxxx+rT58+kqTu3btr7ty5iouLkyRlZmZq+/bted5+hQoV1LhxY82dO1eStHjxYlWuXNnmlsCFCxcqKCjI+swXAABwTly5AlBkHT9+XM8//7yqV6+udu3aSZLc3d21ZcsWjRs3Tv7+/vrnP/+pUqVK6fPPP1d4eLiuXbum+vXr68svv5QktWrVSpMmTVKPHj107do1paenq2vXrmrSpEme65g+fboiIyM1YcIEeXl5aebMmTbzZ8yYoSeffNK8HQcAAIWSxTAMw9FFFDbJycny9vZWUlKSvLy8HF0OAAAAAAexJxtwWyAAAAAAmIDbAgEUKf//K62cBvcOAADgPLhyBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACRwartatW6du3brJ399fFotFy5Ytu2n7yMhIWSyWbK969epZ27z66qvZ5tetW7eA9wQAAADA3c6h4So1NVVBQUH66KOP8tT+/fff16lTp6yvY8eOqWzZsurVq5dNu3r16tm0W79+fUGUDwAAAABWro7ceOfOndW5c+c8t/f29pa3t7f1/bJly3ThwgUNHDjQpp2rq6t8fX1NqxMAAAAAbqVIP3M1Y8YMdejQQVWrVrWZfvDgQfn7+6t69erq16+f4uLibrqetLQ0JScn27wAAAAAwB5FNlydPHlSK1as0JAhQ2ymh4aGatasWVq5cqU++eQTxcbGqlWrVrp48WKu65o4caL1qpi3t7cCAgIKunwAAAAATsZiGIbh6CIkyWKxaOnSpQoPD89T+4kTJ2rKlCk6efKk3Nzccm2XmJioqlWr6t1339XgwYNzbJOWlqa0tDTr++TkZAUEBCgpKUleXl527QeAgmWxOLoCcxWOT2AAAJCb5ORkeXt75ykbOPSZq/wyDENffPGF/vGPf9w0WElS6dKlVbt2bR06dCjXNu7u7nJ3dze7TAAAAAB3kSJ5W+DatWt16NChXK9E3SglJUWHDx+Wn5/fHagMAAAAwN3KoeEqJSVFMTExiomJkSTFxsYqJibGOgDF2LFjFRERkW25GTNmKDQ0VPXr1882b9SoUVq7dq2OHDmijRs3qkePHipWrJj69u1boPsCAAAA4O7m0NsCt2/frnbt2lnfR0VFSZIGDBigWbNm6dSpU9lG+ktKStLixYv1/vvv57jO48ePq2/fvjp37px8fHzUsmVLbd68WT4+PgW3IwAAAADueoVmQIvCxJ6H1gDcWQxoAQAA7iR7skGRfOYKAAAAAAobwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAABO4tlnn1VgYKAsFotiYmJybBMdHS1PT08FBwdbX5cvXzathi1btigoKEi1a9fWgw8+qBMnTkiS9uzZY7PNwMBAlS1b1rTtAoUB4QoAAMBJPPbYY1q/fr2qVq1603Z16tRRTEyM9eXp6WnXdqKjoxUZGZltemZmpvr166epU6fqzz//VJcuXTRy5EhJUoMGDWy2+fDDD6tfv352bRco7AhXAAAATqJ169aqXLnyba1j8uTJatasmRo3bqxOnTrp6NGjeV72t99+k6urq9q1aydJGjZsmL777jtduXLFpt2VK1f01VdfafDgwbdVK1DYODRcrVu3Tt26dZO/v78sFouWLVt20/bR0dGyWCzZXvHx8TbtPvroIwUGBsrDw0OhoaHaunVrAe4FAABA0XL48GE1btxYTZs21ccff2ydPm/ePB04cECbNm3Sjh071K9fPw0fPjzP642Li7O5alaqVCl5eXnp5MmTNu2WLFmi6tWrKzg4+Lb3BShMXB258dTUVAUFBWnQoEHq2bNnnpc7cOCAvLy8rO8rVKhg/f+FCxcqKipK06ZNU2hoqKZOnaqwsDAdOHDAph0AAMDdqHHjxjp+/Li8vb11/PhxdenSReXLl1fv3r21bNkybdu2TSEhIZKkjIwM63IbN260Bq2UlBSdP3/eGo46deqkt99+O881zJgxg6tWcEoODVedO3dW586d7V6uQoUKKl26dI7z3n33XT355JMaOHCgJGnatGn64Ycf9MUXX2jMmDG3Uy4AAECRd+MfqCtXrqy+ffvq119/Ve/evWUYhsaOHauhQ4dmW65FixbWQTKio6M1a9YszZo1y6ZNlSpVbG4jvHjxopKSkuTv72+dFhsbq82bN2vx4sXm7hhQCBTJZ66Cg4Pl5+enhx56SBs2bLBOT09P12+//aYOHTpYp7m4uKhDhw7atGlTrutLS0tTcnKyzQsAAMAZnTp1SpmZmZKuh5/vv/9ejRo1kiSFh4dr2rRpOn/+vCTp6tWr2rlzZ57XHRISoqtXr+qXX36RJE2fPl3dunWTh4eHtc0XX3yhHj165PqHcqAoK1Lhys/PT9OmTdPixYu1ePFiBQQEqG3bttqxY4ck6ezZs8rIyFDFihVtlqtYsWK257JuNHHiRHl7e1tfAQEBBbofAAAABWHYsGGqXLmyjh8/rrCwMNWsWVOSNGTIEH377beSpMWLF6tBgwYKCgrS/fffr4ceesh6x0+/fv0UGRmpdu3aKSgoSMHBwVqzZk2et+/i4qK5c+dqxIgRql27tr7//nu999571vmZmZmaNWsWtwTCaVkMwzAcXYQkWSwWLV26VOHh4XYt16ZNG1WpUkVz5szRyZMnValSJW3cuFHNmze3tnnxxRe1du1abdmyJcd1pKWlKS0tzfo+OTlZAQEBSkpKsrl0DsDxLBZHV2CuwvEJDAAAcpOcnCxvb+88ZQOHPnNlhmbNmmn9+vWSpPLly6tYsWJKSEiwaZOQkCBfX99c1+Hu7i53d/cCrRMAAACAcytStwXmJCYmRn5+fpIkNzc3hYSEaPXq1db5mZmZWr16tc2VLAAAAGdhsTjXCyjKHHrlKiUlRYcOHbK+j42NVUxMjMqWLasqVapo7NixOnHihGbPni1Jmjp1qqpVq6Z69erpypUr+vzzz7VmzRr99NNP1nVERUVpwIABatKkiZo1a6apU6cqNTXVei8xAAAAABQEh4ar7du3W7/BW7oejCRpwIABmjVrlk6dOqW4uDjr/PT0dD3//PM6ceKEihcvroYNG+rnn3+2Wcfjjz+uM2fOaNy4cYqPj1dwcLBWrlyZbZALAAAAADBToRnQojCx56E1AHeWs90ywicwgNvF5yJQsOzJBkX+mSsAAAAAKAwIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAACcyrPPPqvAwEBZLBbFxMTctK1hGHrwwQdVunRpU2s4ePCgWrRoodq1a6tp06bau3evJOncuXMKDg62vmrXri1XV1edP3/e1O3DMQhXAAAAcCqPPfaY1q9fr6pVq96y7XvvvacaNWrkaztHjhxR27Ztc5w3bNgwDR06VH/++adGjx6tyMhISVK5cuUUExNjfQ0dOlSdO3dW2bJl81UDChfCFQAAAJxK69atVbly5Vu227t3r5YtW6YxY8ZkmzdnzhyFhoaqcePGat26tXbt2pXn7Z8+fVrbt29X//79JUmPPvqojh07pkOHDmVrO2PGDA0ePDjP60bh5uroAgAAAIA77erVq3ryySc1Y8YMFStWzGbehg0bNH/+fK1bt07u7u769ddf9cQTT1hv7buVY8eOyc/PT66u13/VtlgsqlKliuLi4lSzZk1ru40bN+rChQt6+OGHzdsxOBThCgAAAHed1157TT179tS9996rI0eO2Mxbvny5du3apdDQUOu08+fP6/Lly0pISFB4eLgkKT09XXFxcQoODpYkNWzYULNnz85zDTNmzFBERIQ1hKHo418SAAAAd521a9cqLi5OH374oa5du6bk5GQFBgZq27ZtMgxDAwYM0IQJE7ItFxgYaB0k48iRI4qMjFR0dLRNm4CAAJ06dUrXrl2Tq6urDMNQXFycqlSpYm2TkpKir7/+Wtu2bSvI3cQdxjNXAAAAuOv8+uuvOnr0qI4cOaL169fLy8tLR44ckY+Pj7p37665c+cqLi5OkpSZmant27fned0VKlRQ48aNNXfuXEnS4sWLVblyZZtbAhcuXKigoCDVrVvX3B2DQxGuAABFHsMuA7jRsGHDVLlyZR0/flxhYWHWUDNkyBB9++23t1y+VatWmjRpknr06KGgoCDVq1dPCxYssKuG6dOna/r06apdu7befvttzZw502Y+A1k4J4thGIajiyhskpOT5e3traSkJHl5eTm6HAA3sFgcXYG5+AQ2x7p161S9enW1bNlSy5Ytsz7/kJN3331X+/bt0zfffKPExES7tpPbLUCS9OCDDyoiIkKRkZFatGiR3nnnnRxv95k8ebLWrl2r7777zq5tA7nhcxEoWPZkA65cAQCKPIZdBu5uFovzvVA0MaAFAOCuwLDLAICCRrgCANwVGHYZAFDQ+HQHANwVGHYZAFDQeOYKAHBXYNhlAEBBI1wBAIo8hl0GABQGDMWeA4ZiBwovZxtBiU9gALeLz0Xn6wOJnw+FCUOxAwAAAMAdxoAWAIAih79SAwAKI65cAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAADiBZ599VoGBgbJYLIqJicmxzaZNmxQcHKzg4GDVq1dPw4YNU1pammk1bNmyRUFBQapdu7YefPBBnThxQpK0Z88e63aDg4MVGBiosmXLmrZdACgsCFcAADiBxx57TOvXr1fVqlVzbRMUFKRt27YpJiZGe/bs0enTp/Xxxx/btZ3o6GhFRkZmm56Zmal+/fpp6tSp+vPPP9WlSxeNHDlSktSgQQPFxMRYXw8//LD69etn13YBoCggXAEA4ARat26typUr37RN8eLFdc8990iS0tPTdfnyZVksFuv8yZMnq1mzZmrcuLE6deqko0eP5nn7v/32m1xdXdWuXTtJ0rBhw/Tdd9/pypUrNu2uXLmir776SoMHD87zugGgqCBcAQBwFzly5IiCgoJUvnx5eXt7a/jw4ZKkefPm6cCBA9q0aZN27Nihfv36WeflRVxcnM1Vs1KlSsnLy0snT560abdkyRJVr15dwcHBpuwPABQmro4uAAAA3DmBgYHatWuXUlJS1L9/fy1ZskR9+vTRsmXLtG3bNoWEhEiSMjIyrMts3LjRGrRSUlJ0/vx5azjq1KmT3n777Txvf8aMGVy1AuC0CFcAANyFSpYsqT59+uirr75Snz59ZBiGxo4dq6FDh2Zr26JFC+sgGdHR0Zo1a5ZmzZpl06ZKlSo2txFevHhRSUlJ8vf3t06LjY3V5s2btXjx4gLZJwBwNG4LBADgLnHo0CFdvXpV0vVnrpYuXaqGDRtKksLDwzVt2jSdP39eknT16lXt3Lkzz+sOCQnR1atX9csvv0iSpk+frm7dusnDw8Pa5osvvlCPHj1UunRpk/YIAAoXrlwBAOAEhg0bph9++EHx8fEKCwtTqVKldOjQIQ0ZMkTdu3dX9+7dtWbNGv33v/9VsWLFdO3aNbVv316vvPKKJKlfv346d+6cdUCKa9euadCgQWrUqFGetu/i4qK5c+dq2LBhunLlivz9/TVnzhzr/MzMTM2aNUuzZ882f+cBoJCwGIZhOLqIwiY5OVne3t5KSkqSl5eXo8sBcIMbBjZzCnwC54+zHQcSxwLyz9nOh/ycC87WBxKfCYWJPdmA2wIBAAAAwATcFggAQBHlbH+t5y/1AIo6rlwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYwKHhat26derWrZv8/f1lsVi0bNmym7ZfsmSJHnroIfn4+MjLy0vNmzfXjz/+aNPm1VdflcVisXnVrVu3APcCAAAAABwcrlJTUxUUFKSPPvooT+3XrVunhx56SP/73//022+/qV27durWrZt27txp065evXo6deqU9bV+/fqCKB8AAAAArFwdufHOnTurc+fOeW4/depUm/cTJkzQ8uXL9d1336lRo0bW6a6urvL19TWrTAAAAAC4pSL9zFVmZqYuXryosmXL2kw/ePCg/P39Vb16dfXr109xcXE3XU9aWpqSk5NtXgAAAABgjyIdriZPnqyUlBT17t3bOi00NFSzZs3SypUr9cknnyg2NlatWrXSxYsXc13PxIkT5e3tbX0FBATcifIBAAAAOBGLYRiGo4uQJIvFoqVLlyo8PDxP7efNm6cnn3xSy5cvV4cOHXJtl5iYqKpVq+rdd9/V4MGDc2yTlpamtLQ06/vk5GQFBAQoKSlJXl5edu0HgIJlsTi6AnMVjk/gosfZjgMpf8eCs/UD50P+cBw4Xx9InA+FSXJysry9vfOUDRz6zFV+LViwQEOGDNE333xz02AlSaVLl1bt2rV16NChXNu4u7vL3d3d7DIBAAAA3EWK3G2B8+fP18CBAzV//nx17dr1lu1TUlJ0+PBh+fn53YHqAAAAANytHHrlKiUlxeaKUmxsrGJiYlS2bFlVqVJFY8eO1YkTJzR79mxJ128FHDBggN5//32FhoYqPj5ekuTp6Slvb29J0qhRo9StWzdVrVpVJ0+e1Pjx41WsWDH17dv3zu8gAAAAgLuGQ69cbd++XY0aNbIOox4VFaVGjRpp3LhxkqRTp07ZjPT36aef6tq1a3r66afl5+dnfY0YMcLa5vjx4+rbt6/q1Kmj3r17q1y5ctq8ebN8fHzu7M4BAAAAuKsUmgEtChN7HloDcGc520PLfALnj7MdBxIP8UucD/nFceB8fSBxPhQm9mSDIvfMFQAAAAAURoQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwgd3hauXKlVq/fr31/UcffaTg4GA98cQTunDhgqnFAQAAAEBRYXe4euGFF5ScnCxJ2rNnj55//nl16dJFsbGxioqKMr1AAAAAACgKXO1dIDY2Vvfdd58kafHixXr44Yc1YcIE7dixQ126dDG9QAAAAAAoCuy+cuXm5qZLly5Jkn7++Wd17NhRklS2bFnrFS0AAAAAuNvYfeWqZcuWioqK0gMPPKCtW7dq4cKFkqQ///xTlStXNr1AAAAAACgK7L5y9eGHH8rV1VWLFi3SJ598okqVKkmSVqxYoU6dOpleIAAAAAAUBRbDMAxHF1HYJCcny9vbW0lJSfLy8nJ0OQBuYLE4ugJz8QmcP852HEj5OxacrR84H/KH48D5+kDifChM7MkG+fqeq8OHD+vll19W3759dfr0aUnXr1zt3bs3P6sDAAAAgCLP7nC1du1aNWjQQFu2bNGSJUuUkpIiSdq1a5fGjx9veoEAAAAAUBTYHa7GjBmjN998U6tWrZKbm5t1+oMPPqjNmzebWhwAAAAAFBV2h6s9e/aoR48e2aZXqFBBZ8+eNaUoAAAAAChq7A5XpUuX1qlTp7JN37lzp3XkQAAAAAC429gdrvr06aPRo0crPj5eFotFmZmZ2rBhg0aNGqWIiIiCqBEAAAAACj27w9WECRNUt25dBQQEKCUlRffdd59at26tFi1a6OWXXy6IGgEAAACg0Mv391wdO3ZMe/bsUUpKiho1aqRatWqZXZvD8D1XQOHlbN9lwveY5I+zHQcS3+0jcT7kF8eB8/WBxPlQmNiTDVzzu5GAgAAFBAQoIyNDe/bs0YULF1SmTJn8rg4AAAAAijS7bwscOXKkZsyYIUnKyMhQmzZt1LhxYwUEBCg6Otrs+gAAAACgSLA7XC1atEhBQUGSpO+++05//fWX9u/fr+eee04vvfSS6QUCAAAAQFFgd7g6e/asfH19JUn/+9//1Lt3b9WuXVuDBg3Snj17TC8QAAAAAIoCu8NVxYoV9ccffygjI0MrV67UQw89JEm6dOmSihUrZnqBAAAAAFAU2D2gxcCBA9W7d2/5+fnJYrGoQ4cOkqQtW7aobt26phcIAAAAAEWB3eHq1VdfVf369XXs2DH16tVL7u7ukqRixYppzJgxphcIAAAAAEVBvr/n6kaJiYkqXbq0CeUUDnzPFVB4Odt3mfA9JvnjbMeBxHf7SJwP+cVx4Hx9IHE+FCb2ZAO7n7l65513tHDhQuv73r17q1y5cqpcubJ2795tf7UAAAAA4ATsDlfTpk1TQECAJGnVqlVatWqVVqxYoU6dOmnUqFGmFwgAAAAARYHdz1zFx8dbw9X333+v3r17q2PHjgoMDFRoaKjpBQIAAABAUWD3lasyZcro2LFjkqSVK1daRws0DEMZGRnmVgcAAAAARYTdV6569uypJ554QrVq1dK5c+fUuXNnSdLOnTtVs2ZN0wsEAAAAgKLA7nD13nvvKTAwUMeOHdOkSZNUsmRJSdKpU6c0fPhw0wsEAAAAgKLAlKHYnQ1DsQOFl7MNt8sncP4423EgMfy0xPmQXxwHztcHEudDYWJPNsjTlatvv/1WnTt31j333KNvv/32pm27d++e90oBAAAAwEnk6cqVi4uL4uPjVaFCBbm45D4GhsVicYpBLbhyBRRezvbXSf4ymT/OdhxI/LVe4nzIL44D5+sDifOhMDH9ylVmZmaO/w8AAAAAuM7uodgBAAAAANnlebTA2bNn56ldREREvosBAAAAgKIqz6MFuri4qGTJknJ1dVVui1gsFp0/f97UAh2BZ66AwsvZ7qvnnvr8cbbjQOI5E4nzIb84DpyvDyTOh8LE9GeuJOnee+9VQkKC+vfvr0GDBqlhw4a3XSgAAAAAOIs8P3O1d+9e/fDDD7p8+bJat26tJk2a6JNPPlFycnJB1gcAAAAARYJdA1qEhoZq+vTpOnXqlJ599ll9/fXX8vPzU79+/ZSWllZQNQIAAABAoZev0QI9PT0VERGh1157Tc2aNdOCBQt06dIls2sDAAAAgCLD7nB14sQJTZgwQbVq1VKfPn3UtGlT7d27V2XKlCmI+gAAAACgSMjzgBZff/21Zs6cqbVr1yosLExTpkxR165dVaxYsYKsDwAAAACKBLuGYq9SpYr69eunihUr5tru2WefNa04R2EodqDwcrbhdhlqN3+c7TiQGH5a4nzIL44D5+sDifOhMLEnG+Q5XAUGBspyiyPXYrHor7/+ynulhRThCii8nO0HKD8888fZjgOJXyglzof84jhwvj6QOB8KkwL5nqsjR47cbl0AAAAA4LTyNVogAAAAAMAW4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwQb7C1eHDh/Xyyy+rb9++On36tCRpxYoV2rt3r6nFAQAAAEBRYXe4Wrt2rRo0aKAtW7ZoyZIlSklJkSTt2rVL48ePN71AAAAAACgK7A5XY8aM0ZtvvqlVq1bJzc3NOv3BBx/U5s2bTS0OAAAAAIoKu8PVnj171KNHj2zTK1SooLNnz5pSFAAAAAAUNXaHq9KlS+vUqVPZpu/cuVOVKlUypSgAAAAAKGrsDld9+vTR6NGjFR8fL4vFoszMTG3YsEGjRo1SREREQdQIAAAAAIWe3eFqwoQJqlu3rgICApSSkqL77rtPrVu3VosWLfTyyy8XRI0AAAAAUOhZDMMw8rNgXFycfv/9d6WkpKhRo0aqVauW2bU5THJysry9vZWUlCQvLy9HlwPgBhaLoyswV/4+geFsx4GUv2PB2fqB8yF/OA6crw8kzofCxJ5s4JrfjVSpUkVVqlTJ7+IAAAAA4FTsDlcZGRmaNWuWVq9erdOnTyszM9Nm/po1a0wrDgAAAACKCrvD1YgRIzRr1ix17dpV9evXl8UZr8MCAAAAgJ3sDlcLFizQ119/rS5duhREPQAAAABQJNk9WqCbm5tq1qxZELUAAAAAQJFld7h6/vnn9f777yufgwwCAAAAgFPK022BPXv2tHm/Zs0arVixQvXq1dM999xjM2/JkiXmVQcAAAAARUSewpW3t7fN+x49ehRIMQAAAABQVOUpXM2cObOg6wAAAACAIs3uZ65iY2N18ODBbNMPHjyoI0eOmFETAAAAABQ5doeryMhIbdy4Mdv0LVu2KDIy0oyaAAAAAKDIsTtc7dy5Uw888EC26ffff79iYmLMqAkAAAAAihy7w5XFYtHFixezTU9KSlJGRoYpRQEAAABAUWN3uGrdurUmTpxoE6QyMjI0ceJEtWzZ0tTiAAAAAKCoyNNogTd655131Lp1a9WpU0etWrWSJP36669KTk7WmjVrTC8QAAAAAIoCu69c3Xfffdq9e7d69+6t06dP6+LFi4qIiND+/ftVv379gqgRAAAAAAo9i2EYhqOLKGySk5Pl7e2tpKQkeXl5ObocADewWBxdgbn4BM4fZzsOpPwdC87WD5wP+cNx4Hx9IHE+FCb2ZAO7bwvMcunSJcXFxSk9Pd1mesOGDfO7SgAAAAAosuwOV2fOnNHAgQO1YsWKHOczYiAAAACAu5Hdz1yNHDlSiYmJ2rJlizw9PbVy5Up9+eWXqlWrlr799lu71rVu3Tp169ZN/v7+slgsWrZs2S2XiY6OVuPGjeXu7q6aNWtq1qxZ2dp89NFHCgwMlIeHh0JDQ7V161a76gIAAAAAe9kdrtasWaN3331XTZo0kYuLi6pWrar+/ftr0qRJmjhxol3rSk1NVVBQkD766KM8tY+NjVXXrl3Vrl07xcTEaOTIkRoyZIh+/PFHa5uFCxcqKipK48eP144dOxQUFKSwsDCdPn3artoAAAAAwB52D2jh5eWl3bt3KzAwUFWrVtW8efP0wAMPKDY2VvXq1dOlS5fyV4jFoqVLlyo8PDzXNqNHj9YPP/yg33//3TqtT58+SkxM1MqVKyVJoaGhatq0qT788ENJUmZmpgICAvSvf/1LY8aMyVMtDGgBFF7O9tAyDyznj7MdBxIP8UucD/nFceB8fSBxPhQm9mQDu69c1alTRwcOHJAkBQUFafr06Tpx4oSmTZsmPz+//FWcR5s2bVKHDh1spoWFhWnTpk2SpPT0dP322282bVxcXNShQwdrm5ykpaUpOTnZ5gUAAAAA9rB7QIsRI0bo1KlTkqTx48erU6dO+uqrr+Tm5pbj809mio+PV8WKFW2mVaxYUcnJybp8+bIuXLigjIyMHNvs378/1/VOnDhRr732WoHUDAAAAODuYHe46t+/v/X/Q0JCdPToUe3fv19VqlRR+fLlTS3uThk7dqyioqKs75OTkxUQEODAigAAAAAUNXaFq+TkZJUsWVIuLv93N2Hx4sUVHByslJQU04v7O19fXyUkJNhMS0hIkJeXlzw9PVWsWDEVK1Ysxza+vr65rtfd3V3u7u4FUjMAAACAu0Oen7launSpmjRpoitXrmSbd/nyZTVt2lTfffedqcX9XfPmzbV69WqbaatWrVLz5s0lSW5ubgoJCbFpk5mZqdWrV1vbAAAAAEBByHO4+uSTT/Tiiy+qePHi2eaVKFFCo0ePto7Ql1cpKSmKiYlRTEyMpOtDrcfExCguLk7S9dv1IiIirO3/+c9/6q+//tKLL76o/fv36+OPP9bXX3+t5557ztomKipKn332mb788kvt27dPTz31lFJTUzVw4EC7agMAAAAAe+Q5XP3+++9q27ZtrvNbt26tPXv22LXx7du3q1GjRmrUqJGk68GoUaNGGjdunCTp1KlT1qAlSdWqVdMPP/ygVatWKSgoSFOmTNHnn3+usLAwa5vHH39ckydP1rhx4xQcHKyYmBitXLky2yAXAAAAAGCmPH/Plaenp3bu3Km6devmOH/fvn1q3LixLl++bGqBjsD3XAGFl7N9lwnfY5I/znYcSHy3j8T5kF8cB87XBxLnQ2FSIN9zFRgYqO3bt+c6f/v27apatWreqwQAAAAAJ5LncNWzZ0+99NJL2Ubik65//9TLL7+sRx991NTiAAAAAKCoyPNtgRcvXlTz5s0VFxen/v37q06dOpKk/fv366uvvlJAQIA2b96sUqVKFWjBdwK3BQKFl7Pd+sFtH/njbMeBxK1QEudDfnEcOF8fSJwPhYk92SDP33NVqlQpbdiwQWPHjtXChQt14cIFSVLp0qXVv39/vfXWW04RrAAAAAAgP/J85epGhmHo7NmzMgxDPj4+sjjZnwu4cgUUXk72ccNfJvPJ2Y4Dib/WS5wP+cVx4Hx9IHE+FCYFcuXqRhaLRT4+PvkqDgAAAACcUZ4HtAAAAAAA5I5wBQAAAAAmIFwBAAAAgAkIVwAAAABggjwNaPHf//43zyt89tln810MAAAAABRVeRqKvVq1anlbmcWiv/7667aLcjSGYgcKL2cbbpehdvPH2Y4DieGnJc6H/OI4cL4+kDgfChPTh2KPjY01pTAAAAAAcFY8cwUAAAAAJsjTlauoqKg8r/Ddd9/NdzEAAAAAUFTlKVzt3LkzTyuzOOMNrwAAAACQB3kKV7/88ktB1wEAAAAARRrPXAEAAACACfJ05ervtm/frq+//lpxcXFKT0+3mbdkyRJTCgMAAACAosTuK1cLFixQixYttG/fPi1dulRXr17V3r17tWbNGnl7exdEjQAAAABQ6NkdriZMmKD33ntP3333ndzc3PT+++9r//796t27t6pUqVIQNQIAAABAoWd3uDp8+LC6du0qSXJzc1NqaqosFouee+45ffrpp6YXCAAAAABFgd3hqkyZMrp48aIkqVKlSvr9998lSYmJibp06ZK51QEAAABAEWH3gBatW7fWqlWr1KBBA/Xq1UsjRozQmjVrtGrVKrVv374gagQAAACAQs/ucPXhhx/qypUrkqSXXnpJ99xzjzZu3KhHH31UL7/8sukFAgAAAEBRYFe4unbtmr7//nuFhYVJklxcXDRmzJgCKQwAAAAAihK7nrlydXXVP//5T+uVKwAAAADAdXYPaNGsWTPFxMQUQCkAAAAAUHTZ/czV8OHDFRUVpWPHjikkJEQlSpSwmd+wYUPTigMAAACAosJiGIZhzwIuLtkvdlksFhmGIYvFooyMDNOKc5Tk5GR5e3srKSlJXl5eji4HwA0sFkdXYC77PoGRxdmOAyl/x4Kz9QPnQ/5wHDhfH0icD4WJPdnA7itXsbGx+S4MAAAAAJyV3eGqatWqBVEHAAAAABRpdg9oIUlz5szRAw88IH9/fx09elSSNHXqVC1fvtzU4gAAAACgqLA7XH3yySeKiopSly5dlJiYaH3GqnTp0po6darZ9QEAAABAkWB3uPrggw/02Wef6aWXXlKxYsWs05s0aaI9e/aYWhwAAAAAFBV2h6vY2Fg1atQo23R3d3elpqaaUhQAAAAAFDV2h6tq1arl+CXCK1eu1L333mtGTQAAAABQ5Ng9WmBUVJSefvppXblyRYZhaOvWrZo/f74mTpyozz//vCBqBAAAAIBCz+5wNWTIEHl6eurll1/WpUuX9MQTT8jf31/vv/+++vTpUxA1AgAAAEChZzGM/H//86VLl5SSkqIKFSqYWZPD2fMtzADuLIvF0RWYK/+fwHc3ZzsOpPwdC87WD5wP+cNx4Hx9IHE+FCb2ZAO7n7l68803FRsbK0kqXry40wUrAAAAAMgPu8PVN998o5o1a6pFixb6+OOPdfbs2YKoCwAAAACKFLvD1a5du7R79261bdtWkydPlr+/v7p27ap58+bp0qVLBVEjAAAAABR6t/XMlSRt2LBB8+bN0zfffKMrV64oOTnZrNochmeugMLL2e6r5576/HG240DiOROJ8yG/OA6crw8kzofCpECfufq7EiVKyNPTU25ubrp69ertrg4AAAAAiqR8havY2Fi99dZbqlevnpo0aaKdO3fqtddeU3x8vNn1AQAAAECRYPf3XN1///3atm2bGjZsqIEDB6pv376qVKlSQdQGAAAAAEWG3eGqffv2+uKLL3TfffcVRD0AAAAAUCTZHa7eeustSbIOwV6+fHlzKwIAAACAIsiuZ64SExP19NNPq3z58qpYsaIqVqyo8uXL65lnnlFiYmIBlQgAAAAAhV+er1ydP39ezZs314kTJ9SvXz/de++9kqQ//vhDs2bN0urVq7Vx40aVKVOmwIoFAAAAgMIqz+Hq9ddfl5ubmw4fPqyKFStmm9exY0e9/vrreu+990wvEgAAAAAKuzzfFrhs2TJNnjw5W7CSJF9fX02aNElLly41tTgAAAAAKCryHK5OnTqlevXq5Tq/fv36fM8VAAAAgLtWnsNV+fLldeTIkVznx8bGqmzZsmbUBAAAAABFTp7DVVhYmF566SWlp6dnm5eWlqZXXnlFnTp1MrU4AAAAACgqLIZhGHlpePz4cTVp0kTu7u56+umnVbduXRmGoX379unjjz9WWlqatm/froCAgIKuucAlJyfL29tbSUlJ8vLycnQ5AG5gsTi6AnPl7RMYf+dsx4GUv2PB2fqB8yF/OA6crw8kzofCxJ5skOfRAitXrqxNmzZp+PDhGjt2rLIymcVi0UMPPaQPP/zQKYIVAAAAAORHnsOVJFWrVk0rVqzQhQsXdPDgQUlSzZo1edYKAAAAwF3PrnCVpUyZMmrWrJnZtQAAAABAkZXnAS0AAAAAALkjXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYIJCEa4++ugjBQYGysPDQ6Ghodq6dWuubdu2bSuLxZLt1bVrV2ubyMjIbPM7dep0J3YFAAAAwF3K1dEFLFy4UFFRUZo2bZpCQ0M1depUhYWF6cCBA6pQoUK29kuWLFF6err1/blz5xQUFKRevXrZtOvUqZNmzpxpfe/u7l5wOwEAAADgrufwK1fvvvuunnzySQ0cOFD33Xefpk2bpuLFi+uLL77IsX3ZsmXl6+trfa1atUrFixfPFq7c3d1t2pUpU+ZO7A4AAACAu5RDw1V6erp+++03dejQwTrNxcVFHTp00KZNm/K0jhkzZqhPnz4qUaKEzfTo6GhVqFBBderU0VNPPaVz587luo60tDQlJyfbvAAAAADAHg4NV2fPnlVGRoYqVqxoM71ixYqKj4+/5fJbt27V77//riFDhthM79Spk2bPnq3Vq1frnXfe0dq1a9W5c2dlZGTkuJ6JEyfK29vb+goICMj/TgEAAAC4Kzn8mavbMWPGDDVo0EDNmjWzmd6nTx/r/zdo0EANGzZUjRo1FB0drfbt22dbz9ixYxUVFWV9n5ycTMACAAAAYBeHXrkqX768ihUrpoSEBJvpCQkJ8vX1vemyqampWrBggQYPHnzL7VSvXl3ly5fXoUOHcpzv7u4uLy8vmxcAAAAA2MOh4crNzU0hISFavXq1dVpmZqZWr16t5s2b33TZb775Rmlpaerfv/8tt3P8+HGdO3dOfn5+t10zAAAAAOTE4aMFRkVF6bPPPtOXX36pffv26amnnlJqaqoGDhwoSYqIiNDYsWOzLTdjxgyFh4erXLlyNtNTUlL0wgsvaPPmzTpy5IhWr16tRx55RDVr1lRYWNgd2ScAAAAAdx+HP3P1+OOP68yZMxo3bpzi4+MVHByslStXWge5iIuLk4uLbQY8cOCA1q9fr59++inb+ooVK6bdu3fryy+/VGJiovz9/dWxY0e98cYbfNcVAAAAgAJjMQzDcHQRhU1ycrK8vb2VlJTE81dAIWOxOLoCc/EJnD/OdhxI+TsWnK0fOB/yh+PA+fpA4nwoTOzJBg6/LRAAAAAAnAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExSKcPXRRx8pMDBQHh4eCg0N1datW3NtO2vWLFksFpuXh4eHTRvDMDRu3Dj5+fnJ09NTHTp00MGDBwt6NwAAAADcxRwerhYuXKioqCiNHz9eO3bsUFBQkMLCwnT69Olcl/Hy8tKpU6esr6NHj9rMnzRpkv773/9q2rRp2rJli0qUKKGwsDBduXKloHcHAAAAwF3K4eHq3Xff1ZNPPqmBAwfqvvvu07Rp01S8eHF98cUXuS5jsVjk6+trfVWsWNE6zzAMTZ06VS+//LIeeeQRNWzYULNnz9bJkye1bNmyO7BHAAAAAO5GDg1X6enp+u2339ShQwfrNBcXF3Xo0EGbNm3KdbmUlBRVrVpVAQEBeuSRR7R3717rvNjYWMXHx9us09vbW6GhobmuMy0tTcnJyTYvAAAAALCHQ8PV2bNnlZGRYXPlSZIqVqyo+Pj4HJepU6eOvvjiCy1fvlxz585VZmamWrRooePHj0uSdTl71jlx4kR5e3tbXwEBAbe7awAAAADuMg6/LdBezZs3V0REhIKDg9WmTRstWbJEPj4+mj59er7XOXbsWCUlJVlfx44dM7FiAAAAAHcDh4ar8uXLq1ixYkpISLCZnpCQIF9f3zyt45577lGjRo106NAhSbIuZ8863d3d5eXlZfMCAAAAAHs4NFy5ubkpJCREq1evtk7LzMzU6tWr1bx58zytIyMjQ3v27JGfn58kqVq1avL19bVZZ3JysrZs2ZLndQIAAACAvVwdXUBUVJQGDBigJk2aqFmzZpo6dapSU1M1cOBASVJERIQqVaqkiRMnSpJef/113X///apZs6YSExP1n//8R0ePHtWQIUMkXR9JcOTIkXrzzTdVq1YtVatWTa+88or8/f0VHh7uqN0EAAAA4OQcHq4ef/xxnTlzRuPGjVN8fLyCg4O1cuVK64AUcXFxcnH5vwtsFy5c0JNPPqn4+HiVKVNGISEh2rhxo+677z5rmxdffFGpqakaOnSoEhMT1bJlS61cuTLblw0DAAAAgFkshmEYji6isElOTpa3t7eSkpJ4/gooZCwWR1dgLj6B88fZjgMpf8eCs/UD50P+cBw4Xx9InA+FiT3ZoMiNFggAAAAAhRHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCgAAAABMQLgCAAAAABMQrgAAAADABIQrAAAAADAB4QoAAAAATEC4AgAAAAATEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuAIAAAAAExCuAAAAAMAEhCsAAAAAMAHhCijCOnbsqIYNGyo4OFitWrXSzp07s7XJzMzUqFGjVL9+fdWtW1eDBw9Wenq6aTUcPHhQLVq0UO3atdW0aVPt3bvXOi8tLU3PPPOMatWqpQYNGqh///6mbRcAAKCwIVwBRdjXX3+t3bt3KyYmRlFRUYqMjMzWZsaMGdqxY4d27Nihffv2ycXFRe+//75d2zly5Ijatm2b47xhw4Zp6NCh+vPPPzV69GibGsaMGSOLxaI///xTe/bs0eTJk+3aLgAAQFFCuAKKsNKlS1v/PykpSRaLJVubXbt2qUOHDnJzc5PFYlHnzp01Z84c6/w5c+YoNDRUjRs3VuvWrbVr1648b//06dPavn279YrUo48+qmPHjunQoUNKTU3VjBkz9NZbb1nr8vX1zeeeAgAAFH6EK6CIi4iIUEBAgF555RWb0JQlJCRE3377rZKTk3X16lV9/fXXOnLkiCRpw4YNmj9/vtatW6cdO3borbfe0hNPPJHnbR87dkx+fn5ydXWVJFksFlWpUkVxcXE6fPiwypYtqwkTJqhJkyZq1aqVVq9ebco+AwAAFEauji4AwO2ZPXu2JOnLL7/U6NGj9b///c9mfmRkpI4ePao2bdrI09NTHTp00E8//SRJWr58uXbt2qXQ0FBr+/Pnz+vy5ctKSEhQeHi4JCk9PV1xcXEKDg6WJDVs2NC63dxcu3ZNR48e1X333ae3335bO3fu1EMPPaS9e/eqYsWKJu09AABA4WExDMNwdBGFTXJysry9vZWUlCQvLy9HlwPkmaenp44fP65y5crl2mbBggX66KOP9Ouvv+qFF17QPffcowkTJtx0vUeOHFFkZKSio6Ntpp8+fVo1a9bU+fPn5erqKsMw5Ofnp/Xr16t06dKqWLGi0tPTVaxYMUlS06ZNNXHiRHXo0CHf+5jDnY9FGp/A+eNsx4GUv2PB2fqB8yF/OA6crw8kzofCxJ5swG2BQBGVmJiokydPWt8vW7ZM5cqVU9myZW3aXblyRRcuXJAknT17Vm+//bZefPFFSVL37t01d+5cxcXFSbo+suD27dvzXEOFChXUuHFjzZ07V5K0ePFiVa5cWTVr1lT58uXVvn17/fjjj5Kk2NhYxcbG6t57783/TgMAABRi3BYIFFFJSUnq1auXLl++LBcXF/n4+Oj777+XxWLRkCFD1L17d3Xv3l1JSUlq27atXFxclJmZqREjRqhbt26SpFatWmnSpEnq0aOHrl27pvT0dHXt2lVNmjTJcx3Tp09XZGSkJkyYIC8vL82cOdM6b9q0aRo8eLBGjx4tFxcXTZ8+XZUqVTK9LwAAAAoDbgvMAbcFAoWXs936wSdw/jjbcSBxK5TE+ZBfHAfO1wcS50NhYk824MoVUIQ42w8PfnAAAABnwjNXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQpFuProo48UGBgoDw8PhYaGauvWrbm2/eyzz9SqVSuVKVNGZcqUUYcOHbK1j4yMlMVisXl16tSpoHcDAAAAwF3M4eFq4cKFioqK0vjx47Vjxw4FBQUpLCxMp0+fzrF9dHS0+vbtq19++UWbNm1SQECAOnbsqBMnTti069Spk06dOmV9zZ8//07sDgAAAIC7lMUwDMORBYSGhqpp06b68MMPJUmZmZkKCAjQv/71L40ZM+aWy2dkZKhMmTL68MMPFRERIen6lavExEQtW7YsXzUlJyfL29tbSUlJ8vLyytc6gIJgsTi6AnPl59OHPoDkfMeBxPkgcT7kF8eB8/WBxPlQmNiTDRx65So9PV2//fabOnToYJ3m4uKiDh06aNOmTXlax6VLl3T16lWVLVvWZnp0dLQqVKigOnXq6KmnntK5c+dyXUdaWpqSk5NtXgAAAABgD4eGq7NnzyojI0MVK1a0mV6xYkXFx8fnaR2jR4+Wv7+/TUDr1KmTZs+erdWrV+udd97R2rVr1blzZ2VkZOS4jokTJ8rb29v6CggIyP9OAQAAALgruTq6gNvx9ttva8GCBYqOjpaHh4d1ep8+faz/36BBAzVs2FA1atRQdHS02rdvn209Y8eOVVRUlPV9cnIyAQsAAACAXRx65ap8+fIqVqyYEhISbKYnJCTI19f3pstOnjxZb7/9tn766Sc1bNjwpm2rV6+u8uXL69ChQznOd3d3l5eXl80LAAAAAOzh0HDl5uamkJAQrV692jotMzNTq1evVvPmzXNdbtKkSXrjjTe0cuVKNWnS5JbbOX78uM6dOyc/Pz9T6gYAAACAv3P4UOxRUVH67LPP9OWXX2rfvn166qmnlJqaqoEDB0qSIiIiNHbsWGv7d955R6+88oq++OILBQYGKj4+XvHx8UpJSZEkpaSk6IUXXtDmzZt15MgRrV69Wo888ohq1qypsLAwh+wjAAAAAOfn8GeuHn/8cZ05c0bjxo1TfHy8goODtXLlSusgF3FxcXJx+b8M+Mknnyg9PV2PPfaYzXrGjx+vV199VcWKFdPu3bv15ZdfKjExUf7+/urYsaPeeOMNubu739F9AwAAAHD3cPj3XBVGfM8VCitn+x4PvsuE7zHJL2c7DiTOB4nzIb84DpyvDyTOh8KkyHzPFQAAAAA4C8IVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAUMQ9++yzCgwMlMViUUxMTK7t9uzZo7Zt2+ree+/VvffeqyVLlphWw5YtWxQUFKTatWvrwQcf1IkTJ6zzLly4oH79+ql27dqqV6+exowZY9p2AQAoTAhXAFDEPfbYY1q/fr2qVq2aa5tLly7pkUce0Ztvvql9+/bp999/V6tWrezaTnR0tCIjI7NNz8zMVL9+/TR16lT9+eef6tKli0aOHGmdP2jQIDVq1Eh//vmn9u7dazMPAABnQrgCgCKudevWqly58k3bzJs3T/fff79atmwpSSpWrJh8fHys8ydPnqxmzZqpcePG6tSpk44ePZrn7f/2229ydXVVu3btJEnDhg3Td999pytXrujQoUPavn27oqKirO19fX3t2T0AAIoMwhUA3AX++OMPubu76+GHH1ZwcLAiIiJ05swZSdeD14EDB7Rp0ybt2LFD/fr10/Dhw/O87ri4OJurZqVKlZKXl5dOnjypP/74Q5UrV9ZTTz2lkJAQdezYUTt37jR9/wAAKAxcHV0AAKDgXbt2TT///LM2b94sf39//fvf/9ZTTz2lRYsWadmyZdq2bZtCQkIkSRkZGdblNm7caA1aKSkpOn/+vIKDgyVJnTp10ttvv33L7W7dulUTJkzQ9OnTtWLFCj388MM6cuSI7rnnnoLZWQAAHIRwBQB3gSpVqqhdu3aqVKmSJKl///4KCwuTJBmGobFjx2ro0KHZlmvRooV1kIzo6GjNmjVLs2bNyrbuG28jvHjxopKSkuTv76/z58+rUqVK1lsGO3furPT0dB09elQ1a9YsgD0FAMBxuC0QAO4CvXv31rZt25ScnCxJ+t///qegoCBJUnh4uKZNm6bz589Lkq5evWrXrXshISG6evWqfvnlF0nS9OnT1a1bN3l4eCgkJEReXl7avXu3JGnr1q0yDEMBAQFm7h4AAIUCV64AoIgbNmyYfvjhB8XHxyssLEylSpXSoUOHNGTIEHXv3l3du3dXlSpV9O9//1stWrSQi4uLKlWqpE8//VSS1K9fP507d856denatWvWEf7ywsXFRXPnztWwYcN05coV+fv7a86cOZIki8WiL7/8Uk8++aQuX74sd3d3LV68WO7u7gXTGQAAOJDFMAzD0UUUNsnJyfL29lZSUpK8vLwcXQ5gZbE4ugJz5efThz6A5HzHgcT5IHE+5BfHgfP1gcT5UJjYkw24cgUARYyz/RLBLxAAAGfBM1cAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAAAJiBcAQAAAIAJCFcAAAAAYALCFQAAAACYgHAFAAAAACYgXAEAAACACQhXAAAAAGACwhUAAAAAmIBwBQAAAAAmIFwBAAAAgAkIVwAAAABgAsIVAAAAAJiAcAUAAAA4mWeffVaBgYGyWCyKiYnJsU10dLQ8PT0VHBxsfV2+fNm0GrZs2aKgoCDVrl1bDz74oE6cOGGdZ7FY1KBBA+t2f/31V9O260iEKwAAAMDJPPbYY1q/fr2qVq1603Z16tRRTEyM9eXp6WnXdqKjoxUZGZltemZmpvr166epU6fqzz//VJcuXTRy5EibNr/++qt1u61atbJru4UV4QoAAABwMq1bt1blypVvax2TJ09Ws2bN1LhxY3Xq1ElHjx7N87K//fabXF1d1a5dO0nSsGHD9N133+nKlSu3VVNhR7gqggIDA1WnTh3rZdSFCxdmazNz5kybS7zly5dXz549Tavh4MGDatGihWrXrq2mTZtq7969OdZgsVi0bNky07abhT4AAOSEnw+AfQ4fPqzGjRuradOm+vjjj63T582bpwMHDmjTpk3asWOH+vXrp+HDh+d5vXFxcTZXzUqVKiUvLy+dPHnSOq19+/YKCgpSVFSUUlNTzdkhRzOQTVJSkiHJSEpKcnQpOapataqxc+dOu5apV6+esWjRIruWiY2NNdq0aZPjvHbt2hkzZ840DMMwvvnmG6NJkybZlm3evLlx//33G0uXLrVru3lxt/aB5Fwv+oA+oA/oh9vtg7+7G38+OPrfrTAcB46uubD0Q05udk4kJSUZiYmJhmEYxrFjx4wGDRoYCxcuNAzDMHr16mUEBgYaQUFBRlBQkFG/fn2jfv36hmEYxoYNG6zTa9SoYZQpU8b6fvTo0YZhGMaiRYuMjh072mzPx8fHOHz4sGEYhnH06FHDMAwjJSXF6N+/v/HUU0+Zt9MmsycbcOXqLrBlyxadPn1a3bt3t06bM2eOQkND1bhxY7Vu3Vq7du3K8/pOnz6t7du3q3///pKkRx99VMeOHdOhQ4ckXb/HdsiQIfrggw/k7u5u7s7kE30AAMgJPx9wN/Py8pK3t7ckqXLlyurbt691YAnDMDR27FjrM1F79uzRnj17JEktWrSwTv/888/VvXt36/u3335bklSlShWb2wgvXryopKQk+fv7W+dLUokSJTR8+HAGtIBjRUREqEGDBho8eLDOnDlz07YzZszQP/7xD91zzz2SpA0bNmj+/Plat26dduzYobfeektPPPFEnrd97Ngx+fn5ydXVVdL10V6qVKmiuLg4SdK7776rBx54QCEhIfncu7yhDwAAOeHnA5A3p06dUmZmpqTr4ef7779Xo0aNJEnh4eGaNm2azp8/L0m6evWqdu7cmed1h4SE6OrVq/rll18kSdOnT1e3bt3k4eGhCxcu6NKlS5Ku/8Fh4cKF1u0Wda6OLgD2W7dunapUqaKrV6/q5Zdf1oABA/S///0vx7apqalasGCBNm/ebJ22fPly7dq1S6GhodZp58+f1+XLl5WQkKDw8HBJUnp6uuLi4hQcHCxJatiwoWbPnn3T2n7//XctXrxY69atu72dvAX6AACQE34+ANcNGzZMP/zwg+Lj4xUWFqZSpUrp0KFDGjJkiLp3767u3btr8eLF+uSTT+Tq6qpr166pV69eGjhwoCSpX79+OnfunHVAimvXrmnQoEF5DkEuLi6aO3euhg0bpitXrsjf319z5syRJO3fv1/Dhg2TxWLRtWvX1LhxY73//vsF0xF3WsHfpVj0FPZnrm508uRJo2TJkrnOnzlzpnH//ffbTBs1apQxduzYW647t/vJExISjFKlShlXr141DMMwMjMzjYoVKxoHDx40Pv74Y8PX19eoWrWqUbVqVcPd3d3w8fExPv74Y/t2zA53Ux84+v7vwnA/uaNrpg/oA/qhcPXBzdwtPx8c/e9WGI4DR9dcWPoBBcOebMA/XQ4Kc7hKSUkxLly4YH0/ZcoUo1WrVrm2b9mypfHZZ5/ZTFu3bp0REBBgfZAwIyPD2LZtW7Zlb/awbps2bWwe1g0JCcm1ndkDWtzNfeDoD/rC8IPD0TXTB/QB/VC4+uBGd+vPB0f/uxWG48DRNdMPhacPCoI92YDbAouYhIQEPfroo8rIyJBhGKpevbr1NoQbL/NK0oEDBxQTE5PtdohWrVpp0qRJ6tGjh65du6b09HR17dpVTZo0yXMd06dPV2RkpCZMmCAvLy/NnDnTvJ28BfoAAJATfj4AcDSLYRiGo4v46KOP9J///Efx8fEKCgrSBx98oGbNmuXa/ptvvtErr7yiI0eOqFatWnrnnXfUpUsX63zDMDR+/Hh99tlnSkxM1AMPPKBPPvlEtWrVylM9ycnJ8vb2VlJSkry8vG57/wCzWCyOrsBc+fn0oQ/oA8n5+kCiH6T89QE4DiTn6wOJfpAKz2eCPdnA4aMFLly4UFFRURo/frx27NihoKAghYWF6fTp0zm237hxo/r27avBgwdr586dCg8PV3h4uH7//Xdrm0mTJum///2vpk2bpi1btqhEiRIKCwtz+m+EBgAAAOA4Dr9yFRoaqqZNm+rDDz+UdH04xoCAAP3rX//SmDFjsrV//PHHlZqaqu+//9467f7771dwcLCmTZsmwzDk7++v559/XqNGjZIkJSUlqWLFipo1a5b69Olzy5oK25Ur/grhfH0g0Q8SfSDRBxJ9kIV+oA8k+kCiD7LQD0XzypVDn7lKT0/Xb7/9prFjx1qnubi4qEOHDtq0aVOOy2zatElRUVE208LCwrRs2TJJUmxsrOLj49WhQwfrfG9vb4WGhmrTpk05hqu0tDSlpaVZ3yclJUm63pEwH916Hf1AH0j0gUQfZKEf6AOJPpDogyz0Q+Hpg6xMkJdrUg4NV2fPnlVGRoYqVqxoM71ixYrav39/jsvEx8fn2D4+Pt46P2tabm3+buLEiXrttdeyTQ8ICMjbjsAu//+LwO969AN9INEHEn2QhX6gDyT6QKIPstAPha8PLl68KO9bFMVogZLGjh1rczUsMzNT58+fV7ly5WRxtuuruUhOTlZAQICOHTtWKG6FdBT6gT6Q6AOJPshCP9AHEn0g0QcSfZDlbuwHwzB08eJF+fv737KtQ8NV+fLlVaxYMSUkJNhMT0hIkK+vb47L+Pr63rR91n8TEhLk5+dn0ybrW9T/zt3dXe7u7jbTSpcubc+uOA0vL6+75kS5GfqBPpDoA4k+yEI/0AcSfSDRBxJ9kOVu64dbXbHK4tDRAt3c3BQSEqLVq1dbp2VmZmr16tVq3rx5jss0b97cpr0krVq1ytq+WrVq8vX1tWmTnJysLVu25LpOAAAAALhdDr8tMCoqSgMGDFCTJk3UrFkzTZ06VampqRo4cKAkKSIiQpUqVdLEiRMlSSNGjFCbNm00ZcoUde3aVQsWLND27dv16aefSpIsFotGjhypN998U7Vq1VK1atX0yiuvyN/fX+Hh4Y7aTQAAAABOzuHh6vHHH9eZM2c0btw4xcfHKzg4WCtXrrQOSBEXFycXl/+7wNaiRQvNmzdPL7/8sv7973+rVq1aWrZsmerXr29t8+KLLyo1NVVDhw5VYmKiWrZsqZUrV8rDw+OO719R4e7urvHjx2e7PfJuQz/QBxJ9INEHWegH+kCiDyT6QKIPstAPN+fw77kCAAAAAGfg0GeuAAAAAMBZEK4AAAAAwASEKwAAAAAwAeEKAAAAAExAuLoLGYahgwcPau/evbp27ZqjywEKFcMwtGbNGv3www+6cOGCo8sBHC49PV0pKSmOLuOOOH369E3nX7t2TVu3br1D1QCOl5ycrFWrVumHH37QmTNnHF1OkUC4usvExsaqYcOGqlu3rho2bKgaNWpo+/btji7rjktNTdVTTz2lSpUqycfHR3369OFD4y6UmJioAQMGqEGDBnryySeVnJysVq1aqUOHDurWrZvuvfde7d6929Fl3hHnzp2z/v+xY8c0btw4vfDCC/r1118dWNWddfDgQS1evFixsbGSpB9++EGtW7dW06ZN9dZbb+luGFx35syZ+te//qWvvvpKkjR27FiVKlVK3t7eeuihh2yOE2fk5+dnE7AaNGigY8eOWd+fO3dOzZs3d0Rpd9TFixf122+/WUP1jh07FBERoV69elmPDWf3yy+/aMqUKdqwYYMkafr06apSpYp8fHz05JNP6vLlyw6usODFxMSobt266tSpk7p166aaNWvqxx9/dHRZhZ+Bu8qjjz5q1K1b15g3b56xZMkSo0WLFkbjxo0dXdYd99xzzxklSpQwhg4daowYMcLw8fExwsPDHV1WoZOZmWkkJCQ4uowCM3jwYOP/tXffYVGc69/Av7v0LiACSlEpAgqKHUmCClasOXoiHhRsP5FjJVgSe0tQjFHjMYlKsWL3GEvEhlgQJSKgFBVFQAVREKVLed4/eJm4gIo5MkN27s91cYWZWeS7BHbnnnme57aysmKrVq1iPXr0YE5OTqxnz54sOjqa3bhxg/Xu3ZsNGTJE6JiNKiEhgZmbmzOpVMratWvHbt26xQwNDZmmpibT1tZmCgoK7OjRo0LHbHRHjhxhioqKTFlZmamoqLAdO3YwVVVVNnDgQObu7s4UFRVZQECA0DEb1apVq5iamhpzc3Njenp6zMfHhxkZGbGAgAC2du1aZmJiwnx8fISO2agkEonMa56mpiZ78OABt52dnc0kEokQ0XgTGRnJtLS0mEQiYXp6eiw8PJxpaWkxGxsb1r59eyaVStnWrVuFjtmotm7dyhQUFJilpSVTUVFh3333HdPQ0GA+Pj7M19eXaWtrs/nz5wsds9H179+f9erVi0VFRbHY2Fg2cuRIZmlpKXSsJo+KK5ExNDRkly9f5rafPn3KpFIpKywsFDAV/1q3bs0OHDjAbf/xxx9MUVGRlZeXC5iKf2pqaiwnJ4fbHjx4MHv69Cm3nZ2dzaRSqRDReNGyZUt28eJFxhhjjx8/ZhKJhEVERHDHr1+/zgwNDQVKx4+BAweyIUOGsCtXrrCpU6eyVq1asYkTJ7LKykpWWVnJfH19WY8ePYSO2ei6dOnCvv32W1ZVVcWCg4OZmpoa+/HHH7njv/76K7OxsREuIA8sLS3Z3r17GWOMxcTEMKlUyg4dOsQdP3XqFDMzMxMqHi8aUlzJ82siY4x9/vnnbOLEiezx48dsxYoVrFmzZuybb77hjq9cuZJ17NhRuIA8aN++Pdu0aRNjjLHff/+dKSoqstDQUO74gQMHmIWFhVDxeKOvr89u3rzJbb98+ZJJJBL26tUrAVM1fVRciYxEImHZ2dky+zQ0NNjDhw8FSiQMRUVF9uTJE5l9ampqLD09XaBEwhD7VVoFBQWZYlJNTY2lpqZy21lZWXJ/IqWvr8/i4+MZY4wVFBQwiUTC/vjjD+54cnIy09HRESgdfzQ1Nbn/95WVlUxBQYHdvn2bO56WlsbU1NSEiscLZWVllpGRIbOdkpLCbT9+/JgpKSkJEY03VFwxpqOjw5KTkxljjJWVlTGpVMri4uK44/fv32eamppCxeOFmpoae/ToEbetpKTEkpKSuO309HSmrKwsRDRe1f57YKz6b0Js54wfS1HoYYmEXxKJBIWFhVBTU+P2SaVSFBQU4PXr19w+bW1tIeLxpqqqCkpKSjL7FBUVUVlZKVCipksikQgdodFUVVVBQUGB21ZQUJB5vvL83Gvk5eXByMgIAKCpqQkNDQ3o6upyx3V1dVFQUCBUPN4UFRVBS0sLQPVropqaGtTV1bnjampqKCsrEyoeL8rLy6GiosJtKysry7xOiuE1UiKRoKCgAKqqqmCMce+ZNe+Pb79PyqvXr19DT08PQPXvgLq6Ove3AQBaWlooLi4WKh4vSktLZc6TVFRUZP42VFRURLMgWFJSErKzs7ltxhiSk5Nl3hccHByEiNZkUXElMowxWFtb19nn6OjIfS6RSOT+DZQxBldXVygq/vknUFxcjKFDh0JZWZnbFxsbK0Q8wqPt27dDU1MTQPVKYKGhoWjevDkAiKKoAOoWkWIoKmuTSCR1Cmsx/hzePpFijCElJYVb1ODFixdCRuNF7ffIt98fa7bl/feC/haoyH6bq6trncV8hgwZAolEIppzxo9FxZXIRERECB2hSVi6dGmdfcOHDxcgibDE/iZqZmaGbdu2cdtGRkbYtWtXncfIO29vb+6qbGlpKXx8fKChoQEAcn+3pkbNSXXN739hYSEcHR0hlUq542JQ+0RqyJAhACBzIiXP6D2y7sXH2hcexXDHhorsajUrp5KPI2FieccghNQhlUqho6PDvUnk5+dDW1tb5oTy9evXdFVKjnl7ezfoJCEkJISHNMLZsWNHgx7n5eXVyEmEk56e3qDHmZubN3ISIqTly5c36HH1XaSUF5GRkQ16nIuLSyMnIX9HVFwRMMYQERGBkpIS9OrVS2a+hdi8efMGb9684YaJyTuxn1BeunQJX3zxxXsfM2PGDPz00088JWqaCgsL5f5voqKiQmaYcH2SkpJgZ2fHUyL+PX36FC1btnzvY/bt24cxY8bwlEh4iYmJMheXFBQU0L59ewETNQ1ZWVkwNjYWOkajKSgokJlnVp/IyEhRFldFRUXYv38/SkpK0L9/f1hZWQkdqenhaeEM0kS8fPmSjR8/nnXo0IFNnjyZvXr1ijk7OzOJRMIkEgkzNDTkVg6Td8HBwWz69Ols9+7djDHGFixYwJSVlZlUKmVubm7sxYsXAickjU1HR4fdunXrncenT5/OtLS0+AskgPXr17/3+OvXr1mvXr14SiOcf/7zn+89npiYKPfL8rdv3569fPnyncfDwsLkfrXAS5cusa5du3LbmpqaTCqVcu+RUqmUnT17VsCEjW/OnDnvPf706VNmbW3NUxphuLi4sNLS0ncev3jxotyvmMhY9aqIX3zxBdPU1GRubm4sPT2dWVtbc38P6urqLDIyUuiYTY5U6OKO8Mvf3x/Xrl3DmDFjcPv2bQwcOBCVlZW4du0arl+/DltbWyxcuFDomI1u9erV+Pe//42UlBTMnDkT06ZNQ2hoKFasWIGAgACkpKRg0aJFQsfkXc2qkTUfNRPZ5dXkyZMxcOBApKam1jk2a9YshISE4Pjx4wIk48+3336LnTt31nussLAQAwcORG5uLs+p+Hft2jX4+PjUeyw5ORl9+/ZFr169eE7FLwMDAwwaNKjeleAOHDiAcePGYfXq1QIk48+WLVswbtw4mX0RERFIS0vDw4cPMWvWLPz8888CpeNHSEjIO/8/Z2VloXfv3jAwMOA5Fb9yc3Pxz3/+E1VVVXWOXbp0Ce7u7vD29uY/GM/8/f3x5s0b/PLLL1BXV8eAAQNgZWWFrKwsPHv2DIMGDcKyZcuEjtn0CF3dEX5R09Rq1Cyz2q1bt9igQYO47ZqrtDUfCgoK7MaNGwImbHwTJkxg5ubmMn3PZs2axdTV1dmFCxcETMaPgwcPMlVVVXbs2DGZ/YWFhczZ2ZlZWVnJ9AKTV0lJSax58+YyzVIZq+7zZWRkxIYPH84qKioESsePgoIC1qVLF9avXz/25s0bbv+BAweYsrIyCwgIEDAdPywtLWX6m9XucxUbG8uMjY2FiMabS5cuMXV1dbZlyxaZ/VlZWaxdu3asZ8+erKCgQKB0/Hjy5Alr27YtGzdunMz+S5cuMS0tLebr6ytQMn4ZGhqy69evM8YYy83NZRKJhEVFRXHH4+LimL6+vlDxmiwqrkSGmqZWo2aZ1SZOnMhWr17NbWtqarI9e/awixcvsoiICDZu3Djm6ekpYMLGV1lZyUaOHMlsbW3Zixcv2Jw5c5iamho7d+6c0NF4s23bNqaurs5daCksLGSfffYZs7S0rNNsW57duHGDaWlpscDAQMbYn4XV0KFDWXl5ucDp+JGTk8NsbGzYqFGjWFVVFTt48CBTUlKSeZ2QZ6qqqjLvDYcPH2ZFRUXc9qNHj0TRPPbEiRNMRUWFhYWFMcaqzw1sbGxY9+7d2evXrwVOx4/U1FRmbGzMZs6cyRhj7PLly0xTU5NNnTpV4GT8kUgkLDs7m9vW0NAQXVPtv4KKK5Gh7vPV6OdQzcbGhsXGxnLbtX8O0dHRoriDV1ZWxtzc3JiBgQFTV1eX+zkV9VmzZg3T1tZmERER7PPPP2dt27ZlmZmZQsfi3fnz55mamhpbunQpa9myJXN3d2dlZWVCx+JVRkYGMzMzY66urkxZWZmtXLlS6Ei8MTAwkBnNUVtERARr3rw5f4EEtGfPHqaqqspCQkKYra0t69q1K8vPzxc6Fq/i4+OZrq4u8/LyYtra2mzKlClCR+IVnSv9NdTnSoSoaWo1sTfLBKqXXn577PyKFSu43wUAMDY2xrNnz4SIxotNmzZxn/fu3RuXL1/GgAEDkJSUhKSkJO7YzJkzhYjHq3nz5iEvLw+urq5o3bo1Ll68CBMTE6Fj8a5v377Yu3cvRo8ejf79++Po0aNQUlISOhYvEhISuM8DAwMxfvx4jBgxAsOGDZM55uDgIEQ8XvTo0QM7d+5E79696z0eGhqKHj168BtKIGPHjkV+fj4mTZqEzp0749y5c9DR0RE6Fi9qmgS3bt0ae/bswciRIzFixAgEBgbKNBDW1tYWKiJvlixZAnV1dQDVKyqvXr2a+z2ob34moaXYRad169YN6mkj743jpFIp1xSzNjF1HdfT08Px48fh7Oxc7/GrV69i6NChyMvL4zkZP9q0afPBx0gkEjx8+JCHNML48ssvZbZPnTqFjh07olWrVjL7jxw5wmcs3unq6sq8NhYUFEBNTa3O8uzy+rcAyL4uvv36WPtzeX5djIiIgJubG/z8/DB37ly0aNECAJCTk4M1a9Zg48aNOHPmDPr27Stw0sbj6Ogo87eQlJQEU1PTOkuTx8bG8h2NNzV/CzXe/v2v2Zb3vwWg+qJjQ84Zqfm2LLpzJTKPHj0SOkKTIO/FY0M5Ojriv//97zuLqyNHjsh0pZc39HuAOleiPTw8BEoirA0bNggdQXD09wD06dMHP/30E+bMmYP169dDW1sbEokEr169gqKiIjZs2CDXhRUAjBgxQmZ7+PDhwgQREBUL1S5evCh0hL8lunNFiIgdPnwYY8aMwYYNGzBt2jRIpdXdGSorK7FlyxZ8/fXX2Lt3L0aNGiVwUn7VXJUkhIhTZmYmDh06hPv37wMArKysMGrUKJiamgqcjBDS1FFxRYjIzZ8/H4GBgdDS0kLbtm0BAA8fPkRhYSH8/PwQGBgocEL+KSsrIz4+Hra2tkJHERQVmcDy5cvx73//W2YuojzLycnBnTt30KVLF+jo6ODZs2fYsWMHqqqq4O7uDnt7e6EjCio5ORlBQUFYt26d0FF4FxoaipEjR4pm3lVlZSXS09PRunVrSKVSlJWV4dixY6iqqkKfPn1gaGgodETSRFFxRQhBdHQ0wsLCZK7Senh4oGfPngIna1x+fn717t+4cSM8PT2hr68PAFi/fj2fsXhVVlaGhQsX4saNG3B3d8f8+fOxatUqBAQEAACGDRuGX375Re4nbr89Sb0GYwwGBga4cuUKbGxsAMj3BPaLFy9iyJAhKC4uhqGhIU6fPo0hQ4ZATU0NUqkUjx49wm+//Yb+/fsLHZVXRUVF2LdvH4KCghAdHQ07OzvcuXNH6Fi8E9NFp4SEBAwYMAA5OTmws7PDqVOnMHjwYKSlpUEikUBJSQnh4eHo1q2b0FFJE0TFFSHknfLz87F7925Mnz5d6CiNQiqVomPHjmjWrJnM/sjISHTt2hUaGhqQSCS4cOGCMAF54Ofnh/3798PDwwOnTp1Cnz59cOLECXz33XeQSqVYsmQJBg0aJLOyojxSUFCod//bizvI+wT2zz//HB07dkRAQAB++eUXbNiwASNGjMDmzZsBAHPnzkVUVBSuXr0qcFJ+XL16FUFBQThw4ABKSkowZ84cTJ48mSu05ZWenl69+/Pz86Gtrc0NH5fnxV0GDhwILS0tLF26FNu3b8eZM2fQoUMH7NmzBxKJBBMmTEB2djbOnj0rdFTSBFFxRQip4/z58wgKCsLRo0ehrq6O3NxcoSM1ioCAAGzduhXbt2+XmaSupKSE+Ph42NnZCZiOH2ZmZggODoabmxsePnwIKysrHDlyhJvEfvbsWUyZMkXuF8MxMTFBp06d8PXXX3Mnj4wxuLm5Yfv27dzKki4uLkLGbFQ6OjqIjY2FhYUFKioqoKamhpiYGHTq1AkAcP/+fXTr1g35+fmC5mxMOTk5CA0NRXBwMF69egUPDw+MHTsWTk5OonlN0NLSgouLC0aPHs3tY4xh8uTJWLFiBbeSqJeXl1ARG52enh6uXr0KW1tblJSUQEtLC1FRUejevTsAIDExES4uLqJp25KRkQFTU9M6w8QZY8jMzISZmZlAyZomqdABiHAePHiARYsWwcPDAzk5OQCA33//HYmJiQInI0LIzMzEihUr0KZNG/Tv3x8SiQRHjx7leoHJowULFmD//v2YNm0a/P39UV5eLnQk3r148QLW1tYAgLZt20JBQQGWlpbccSsrKzx//lyoeLxJSEiAkpISVq5cCUtLS7i4uHDLEHfv3h0uLi5yXVgB1cO+SktLAVT3s6mqquK2AaCkpETue36Zm5vj9u3b2LhxI548eYL169eja9euQsfi1a1bt5CTk4MLFy7gH//4B7y8vODt7Q2JRIIRI0bAy8tLrgsroLpoqGnDUPu/QPWd7qqqKkGyCaFNmzb1vg/k5eU1qKWJ2FBxJVKRkZGwt7fH9evXceTIEa55bnx8PJYuXSpwusbl6OiIzp07N+hD3pWXl+PgwYMYMGAA2rVrh7i4OAQGBkIqlWLhwoUYOHCg3J9MdevWDTdv3sTz58/RtWtX3LlzR1SLOJiZmeHatWsAgJiYGEgkEty4cYM7fv369To9r+SRnp4ejh49itGjR6N79+4ICwsTOhLvnJ2dsWDBAly9ehVz5sxB586dsWrVKhQVFaG4uBgrV66U+0LD3NwcV65cwaVLl3Dv3j2h4wjC0tISUVFRMDIyQqdOnUQzDPRtXbp0wZo1a/DkyRN8//33aNOmDTc8FgB++ukndOjQQcCE/HrX4kaFhYVQVVUVIFHTRn2uRGrBggVYtWoV/Pz8ZBoD9u3bV+YFRB7V7uEhZq1atYKNjQ08PT2xb98+6OrqAhBfryNNTU3s2LED+/btg5ubm1zPq6nNx8cH3t7e2L59O27evIl169bh22+/RUpKCqRSKX7++Wd8/fXXQsfkzbRp0+Di4oKxY8fi+PHjQsfhVWBgINzd3fH555/DxsYGZ8+eha+vLzcnUVdXF6dPnxY2ZCNLSUnh5lp169YN1tbW8PT0BABRXXRRVFTEmjVrMGDAAIwdOxb/+te/RPX8v//+ewwaNAghISHQ19dHREQEJk2aBGNjY0ilUrx8+VIUrw81iz5JJBIsXrwY6urq3LHKykpcv36dGzZM/kRzrkRKU1MTt2/fRps2baClpYX4+Hi0bdsWjx49go2NjcxQECK/9PT0YG9vD09PT3z11VfcSmhimnNUW2ZmJmJjY+Hq6gpNTU2h4/Bi7969uHbtGnr16gUPDw9cvHgRS5YsQXFxMYYOHYrFixdz85DE4s2bN1iwYAEiIiJw5MgRUQ19yc3N5VbKBKrnYJaUlMDJyUlmv7wrLCxEWFgYQkJCEB0dzRXdI0aMgIGBgdDxeJObm4spU6YgIiIC0dHRaNeundCReFFUVISUlBS0a9cOmpqaKC0txZ49e1BSUoJ+/fqJ4ufQp08fANWjnZycnKCsrMwdU1ZWRuvWreHv7w8rKyuhIjZJVFyJlImJCQ4cOIBevXrJFFdHjx6Fv78/Hjx4IHREwoPS0lIcPnyYW2J40KBBXKEVFxcnyuIKACoqKmTG1xNCxGHFihXw9/eXuUIP/NnfateuXcjLyxPl/EwiXhMmTMDGjRvluhXFp0TFlUj5+/vj+vXrOHjwIKytrREbG4tnz55h/PjxGD9+vNzPu6pRWVmJH3/8EQcOHEBGRgbevHkjc1yel5qt7cGDBwgJCcGOHTvw5MkTeHh4wNvbG3379n3nMtV/d6dPn0arVq1gb2+PqqoqrF69Gr/88guys7NhbGyM6dOnY/78+aIaDkOq5efn4+DBg8jIyIC5uTlGjx4tmuapYqagoICsrCy0aNGi3uMVFRX47bff8OWXX/KcTDgVFRWIiIhARkYGWrdujd69e8vtewIhnwQjolRWVsYmT57MFBUVmUQiYUpKSkwqlTJPT09WUVEhdDzeLF68mBkbG7N169YxVVVVtnLlSjZp0iSmr6/PNm7cKHS8Rrdjxw5WWloqs6+yspKdOnWK/eMf/2DKyspMX19foHSNr127duzSpUuMMca+++47pq+vz9avX89+//13tmHDBmZoaMgCAgIETkn4MHLkSHbw4EHGGGN37txhzZs3ZwYGBqxHjx7M0NCQGRkZsaSkJIFTksYmkUjYs2fPhI4hqOnTp7Pjx48zxhjLzMxkNjY2TEFBgRkaGjIFBQVmb2/PHj9+LHBKwqfCwkK2aNEi5uTkxCwsLFibNm1kPogsunMlchkZGbhz5w4KCwvh6OgounGzFhYW2LRpE9zd3aGlpYW4uDhuX3R0NPbu3St0xEb1oau0z58/x65du7hJrfJGVVUV9+7dg5mZGezt7bFkyRKZ3i4nT57E7Nmzcf/+fQFTEj7o6ekhKioKNjY2GDx4MHR1dRESEgJlZWWUl5dj2rRpyMzMRHh4uNBRSSOSSqV49uyZqOZU1WZkZIRz586hQ4cO+Oqrr5CXl4ewsDA0b94ceXl58PLygqqqKg4ePCh0VMITDw8PREZGYty4cTA2Nq4zmmPWrFkCJWuaaFKByJmZmYm6+Vt2djbs7e0BVC/y8erVKwDAkCFDsHjxYiGj8eJD11YMDAzktrACqk+onz59CjMzMzx//lymvxMAWFtb48mTJwKlI3wqLS3l2g7ExcXh5MmT3ORtJSUlzJs3j2sgSuSbtbX1B4cCy/OQ8VevXkFDQwMAEBUVhcOHD6N58+YAql8zv//+e26hAyIOv//+O06ePAlnZ2eho/wtUHElIh9zkrx+/fpGTNJ0mJiYICsrC2ZmZrCwsMCZM2fQuXNnxMTEQEVFReh4vBDzfKKRI0di9erV+O9//4vhw4djy5Yt2Lp1K/cz+emnn0SxzCxjDKmpqXjz5g3atWsnysU8HBwccOHCBVhYWMDIyAjp6elwdHTkjqenp0NNTU3AhI3vxo0b6NKlyzvn05SVleHYsWP45z//yXMyfi1fvlzU8+usra1x48YNbjXh169fyxwvKCgQVQPd+iQkJKBr16515mnLK11dXejp6Qkd429DfO+gInbr1i2Z7djYWFRUVHDLid67dw8KCgro0qWLEPEEMXLkSJw/fx49evTAjBkz4OnpiaCgIGRkZGDOnDlCx+OFq6vrB0+mY2NjeUrDr++++w5ubm6wsbGBk5MTDh48iLNnz8La2hqpqanIy8uT+2FgaWlpGDZsGJKSkgBUX3A4fPiw3DeLrW3x4sUYP348lJSUMHPmTMyZMwe5ubmwtbXF3bt3sXTpUowbN07omI3KyclJZpiwtrY24uLi0LZtWwDVi3x4eHjIfXE1ZsyYdw6VFoM5c+bA398fhoaG+OabbzBz5kz89NNP3N/CrFmzRLWgR30YY6Lqh7hy5UosWbIEO3bsqLOSJqmL5lyJ1Pr163Hx4kXs2LGDaxz78uVLTJgwAZ9//rmomoa+LTo6GlFRUbCyssLQoUOFjtPopFIpvv766w/2c5Ln1SPLy8sRFBSE48eP4+HDh6iqqoKxsTGcnZ0xbdo0mJiYCB2xUY0aNQqJiYlYsmQJVFVVsW7dOpSWluLmzZtCR+Pd4cOHMXv2bDx9+lRmyKyKigp8fHywbt06uV4lTSqVIjs7myss3m7TAQDPnj2DsbGxXN+1+NA8VLFYv349Fi9ezBURFRUV3LFhw4Zh165doukDWJ/4+Hh07txZNAWWo6MjHjx4AMYYWrduzQ2hriGvF2D/KiquRKpVq1Y4c+YM2rdvL7P/zp076N+/P54+fSpQMsKn2idTtT1+/BgrVqzA1q1beU5G+GJkZIRDhw7hs88+AwBkZWXBxMQEr1+/5uZdiEllZSViY2NlCu0uXbpAS0tL6GiNriHFVcuWLeX6hPJDr4likp+fj7Nnz9a56CS2ha/qI7biavny5e89Ls8XYP8KGhYoUq9fv8bz58/r7H/+/DkKCgoESCSM77//HoaGhpg4caLM/uDgYDx//hzz588XKBk/PjTfKjc3F0FBQVRcybGcnByZkyVjY2OoqakhJycHbdq0ETCZMBQUFNCtWzd069ZN6ChEAPJ8V+5jNWvWTGb1VDGpPc+sNjGdJwFUPH0sKq5EauTIkZgwYQJ++OEHbgWs69evY+7cuaIaS/3rr7/Wu9x6+/btMWbMGLkvrujGNZFIJCgsLJRZrEEqlaKgoEDmBENbW1uIeIRnSUlJyM7OBlD9+pCSkoLCwkIAwIsXL4SMRghvmjVr9t6Lj4wx0S0GlZ+fj0OHDuHBgweYO3cu9PT0EBsbC0NDQ7Rq1UroeE0KDQsUqeLiYvj7+yM4OBjl5eUAAEVFRUyaNAmBgYGiGQ6kqqqK5OTkOlfoHz58CDs7O5SWlgqUjB/p6ekwNTWFVCqt97jYhj6IkVQqrXOS8PaJQ83n9Dsg/2p+F+o7LajZT78LRAwiIyMb9DgXF5dGTtI0JCQkwM3NDTo6Onj06BHu3r2Ltm3bYtGiRcjIyMDOnTuFjtik0J0rkVJXV8eWLVsQGBiIBw8eAKhuqCuWoqqGqakprl69Wqe4unr1Klq2bClQKv6Ym5sLHYEILCIiQugIpIlIS0sTOgIhTYJYiqaG8vPzg7e3N9auXSsz/3Tw4MEYO3asgMmaJiquRE5DQ4PrXSC2wgoApkyZgtmzZ6O8vBx9+/YFAJw/fx7z5s0TxYqJHxoCmp+fz08QAYm9xxOdRJAadLGFEFKfmJgY/Prrr3X2t2rVihtGTP4krrMIwqmqqsKqVavwww8/cOPptbS08PXXX2PhwoXvHCYmb+bOnYvc3Fz4+vpyzQBVVVUxf/58fPPNNwKna3wfapSpo6OD8ePH85SGf9Tjqfq1IDAwEL/99hvevHkDV1dXLF26VO4b5tZGDXSrvX79mptfd+rUKZkluBUUFODu7i5UNNJEiK2BLqluR1HfIh/37t2DgYGBAImaNppzJVLffPMNgoKCsHz5cjg7OwMArly5gmXLlmHKlClYvXq1wAn5VVhYiOTkZKipqcHKygoqKipCRyI8oB5P1c0hly1bBjc3N6ipqSE8PBweHh4IDg4WOhqvavc3qt1AVwzLkJ84cQKLFy/mGs5raWmhqKiIOy6RSLB//36MGjVKqIikCaC5uOIzefJk5Obm4sCBA9DT00NCQgIUFBQwYsQIfPHFF9iwYYPQEZsUKq5EqmXLlvjll18wbNgwmf3Hjh2Dr68vnjx5IlAy4Tx+/BgA5L5pLPkT9XgCrKys4O/vj6lTpwIAzp07B3d3d5SUlIjmDjZADXSB6uawI0aM4FpT1P4ZrF27FhcvXsSpU6eEjEkERsWV+Lx69QqjRo3CH3/8gYKCArRs2RLZ2dlwcnLCqVOnRPN+2VDieeckMvLy8mBjY1Nnv42NDfLy8gRIJIyqqiqsWLECOjo6MDc3h7m5OZo1a4aVK1fK9UkUqfa+Hk9ikZGRgcGDB3Pbbm5ukEgk1Ei8HvK+9PLt27e5kQz1GTRoEP744w8eExEijMrKSiQkJKCkpKTOseLiYiQkJIjqHEFHRwdnz57F8ePHsWnTJkyfPh2nTp1CZGQkFVb1oDlXItWxY0ds3rwZmzZtktm/efNmdOzYUaBU/Fu4cCGCgoIQEBBQZ3hkaWmp6IZHig31eAIqKiqgqqoqs09JSYlr0UDEIysrS2ZIdEREBExNTbltTU1NvHr1SohohEfUQBfYtWsXNm/ejOvXr9c5pqysjIkTJ2L27Nnw9PQUIJ1wPvvsM26kB3k3Kq5Eau3atXB3d8e5c+fg5OQEALh27RoyMzNFNeRjx44d2L59u8zwSAcHB7Rq1Qq+vr5UXMk5xhisra3r7HN0dOQ+l/e+PowxeHt7y5xUl5aWwsfHR+aK5JEjR4SIxyuxN9DV09NDamoqWrduDQB1Fna5f/8+t7oskV/UQBcICgqCv79/vQvcKCoqYt68edi8ebOoiquYmBhEREQgJyenzl279evXC5SqaaI5VyL29OlT/Oc//0FKSgoAwNbWFr6+vqLo71RDVVUVCQkJdU6w7969i06dOtU7JIDID2oUCUyYMKFBjwsJCWnkJMKiBrrAmDFjUFxcjN9++63e40OGDIGGhgb279/PczLCJ3pdBFq0aIEbN25wFxpqS0tLQ/fu3fH8+XN+gwnku+++w6JFi9CuXTsYGhrKFNcSiQQXLlwQMF3TQ8UVEbUePXqgR48edYZHzpgxAzExMYiOjhYoGSGET+np6Q16nDz3grp16xacnJwwdOhQzJs3j7vodPfuXaxZswYnT55EVFQUOnfuLHBSQhqXhoYGrl27BgcHh3qPJyQkwMnJSWY1TXlmaGiINWvWwNvbW+gofws0LFBkMjIyGvQ4MzOzRk7SNNDwSHGjHk+khjwXTQ3l6OiI/fv3Y/LkyXWGgerq6mLfvn1UWBFRsLKyQlRU1DuLqytXrsgshiTvpFLpexe7IbLozpXIvD1+uOZ//du3d8Uw9KU2Gh4pXtTjCdyy2x8ihp8JNdCtVlxcjPDwcNy/fx9A9Ylm//79aVUwIhpr167F2rVrceHChToFVnx8PFxdXTFv3jzMmzdPoIT8Wrt2LZ4+fUr9rBqIiiuRUVRUhImJCby9vTF06FAoKtZ/81JMKwbW5/Hjx1ixYgW2bt0qdBTSiKjHU/UVSXNzczg6OtY736jG0aNHeUzFP2qg+36MMZw+fRpBQUE4dOiQ0HEIaVTl5eXo378/rly5Ajc3N651TUpKCs6dOwdnZ2ecPXsWSkpKAiflR1VVFdzd3XHv3j3Y2dnVed5iWPDoY1BxJTLZ2dnYsWMHQkJCkJ+fD09PT0yaNAm2trZCR2tSqEmiOKioqCA1NVVmuWlVVVWkpqaKppn0v//9b4SFhcHc3BwTJkyAp6enKFeEowa69UtLS0NwcDBCQ0Px/PlzuLm54cSJE0LHIqTRlZeX48cff8TevXtx//59bnXZsWPHYvbs2VBWVhY6Im+mT5+O7du3o0+fPnUWtADkf8Gjj0XFlYhduXIFISEhOHjwIOzs7DBp0iRMmjRJNFfs34eKK3FQUFBAdnY2DAwMuH1aWlpISEhAmzZtBEzGr7KyMhw5cgTBwcGIioqCu7s7Jk2ahP79+8v9kss12rRpg9OnT6Ndu3YA6hZXt2/fhqurqygaTJeVleHQoUMICgrClStXUFlZiXXr1mHSpEly3fONVKusrERiYiKsrKzqzD8tLi5GamoqOnToQOcKIqKlpYV9+/aJZmj0/4qKK4Jnz57Bw8MDkZGReP78uSivWtdGxZU4SKVSDBo0SKbH0/Hjx9G3b1/R9XiqkZ6ejtDQUOzcuRMVFRVITEyEpqam0LEanaqqKlJSUrill//44w907NiRG/6SlpYGGxsblJWVCZiycd28eRNBQUEICwuDpaUlxo0bh6+++gomJiaIj4+HnZ2d0BEJD0JDQ7kGurX7PFVUVKBnz56ibKBbWlqK/fv3o6ioCP369RPVghbm5uYIDw/nhkeS96PLDiIWFRWFyZMnw9raGoWFhfjPf/6DZs2aCR2LEN54eXmhRYsW0NHR4T48PT3RsmVLmX1i8na/JzFdXKhpoFuja9euMvMKxNBAt0ePHlBRUUF0dDRiYmIwc+ZMGBoaCh2L8KwhDXTlfT6yn58fZsyYwW2/efMGPXv2xJQpU/Dtt9/C0dER165dEzAhv5YtW4alS5eiuLhY6Ch/C7QUu8hkZWVh586dCAkJwcuXL/Gvf/0LV69eRYcOHYSOxqsvv/zyvcfz8/P5CUIERePEq709LPDKlSsYMmQINm/ejIEDB4pm6M8XX3yBTZs2wc3Nrd7jmzZtwhdffMFzKn65uroiKCgIOTk5GDduHAYMGCCaYaHkT3fv3kXPnj3febxbt25ITk7mMRH/zpw5g++++47b3rNnDzIyMnD//n2YmZlh4sSJWLVqFU6ePClgSv5s2rQJDx48gKGhIVq3bl1nQYvY2FiBkjVNVFyJjJmZGVq1agUvLy8MGzYMSkpKqKqqQkJCgszj3tXbQV586G6Ejo4Oxo8fz1MaQoTj6+uLffv2wdTUFBMnTkRYWBiaN28udCzezZ8/H05OThg9enS9DXTPnTuHqKgogVM2rvDwcGRmZiIkJATTpk1DSUkJvvrqKwCgIktEioqK8Pr163ceLygokPs7GBkZGTLDYM+cOYNRo0Zx/fBmzZqFwYMHCxWPdyNGjBA6wt8KzbkSmbevQte8Wdb+FRBbnysiXtTjqfo1wczMDI6Oju89gRbDvLNjx45h8uTJyMvLk9mvq6uL7du3i+4E4+zZswgJCcHRo0dhamqKUaNGYdSoUdRIWM516tQJPj4+8PHxqff4li1bsHXrVsTFxfEbjEfNmjVDTEwMN6+qTZs2WLx4Mfee8ejRI9ja2qKkpETImKSJojtXIpOWliZ0BEKajNDQ0Ab1eJJn48ePp7sS/9/w4cPRr18/0TbQnThxIjZu3AgtLS0AQL9+/dCvXz+8fPkSu3fvRnBwMNasWUMX3+Tc2LFjsWjRIvTq1aveBrpLliyR++a5tra2OH78OPz8/JCYmIiMjAz06dOHO56enk7zEck70Z0rQohoUY8n0hBiaaCroKCArKwstGjR4p2PiY2NpTtXco4a6FY3TR8zZgw+++wzJCYmolu3bjh+/Dh3fP78+UhLS8OBAwcETMmfyspK/Pjjjzhw4AAyMjLw5s0bmeO17/aLHRVXIpKQkMD1pqg9x6o2eZ9zRUgN6vFE3kVsDXSlUimys7PfW1wRcaAGusD58+dx4sQJGBkZYcaMGVBXV+eOLV++HC4uLujdu7dwAXm0ZMkSbN++HV9//TUWLVqEhQsX4tGjR/jvf/+LJUuWYObMmUJHbFKouBKRt984315uuTaac0XESqw9nsifxNxAVyqV4v79+zJNtesj7z8HQogsCwsLbNq0Ce7u7tDS0kJcXBy3Lzo6Gnv37hU6YpNCc65EJC0tjXvTpLlXhNQl1h5PpP4GumFhYTAxMcGAAQNEU1DUrJJYH8YYXXwTKTE30CVAdnY27O3tAQCampp49eoVAGDIkCFYvHixkNGaJCquRKRmCdHanxMiZtTjiQDVDXRnzJiB6OhotGvXTug4gjl06BDNOxQ5Pz8/lJeX46effgLwZwPdpKQkqKurY968eTh79iycnJwETkr4YmJigqysLJiZmcHCwgJnzpxB586dERMTAxUVFaHjNTlUXIlUbm4u9PX1AQCZmZnYtm0bSkpKMGzYMHz++ecCpyOEH9TjidSgBrrVnJ2dac6VyFEDXVLbyJEjcf78ee4ilKenJ4KCgpCRkYE5c+YIHa/JoTlXInP79m0MHToUmZmZsLKywr59+zBw4EAUFRVBKpWiqKgIhw4dEl0/FyJO1OOJvK2mgW5ISAjXQHfLli1ISEiAra2t0PEaHS1oQYDqOXWxsbGwtLQEAHh4eEBLSwtbt24FAMTFxWHw4MF4+vSpkDGJgK5du4Zr167BysoKQ4cOFTpOk0NjXkRm3rx5sLe3x6VLl9C7d28MGTIE7u7uePXqFV6+fImpU6ciICBA6JiE8GL8+PHo06cPmjVrBh0dnXd+EHEwNTXFkiVLkJaWhl27duH58+dQVFTE8OHD8e233yI2NlboiI3K3NwcCgoKQscgApNKpTKLXUVHR6Nnz57cdrNmzfDy5UshovEmJyfnvccrKipw48YNntI0PU5OTvDz86PC6h3ozpXING/eHBcuXICDgwMKCwuhra2NmJgYdOnSBUB1H4uePXsiPz9f2KCEEMKj2g10a7zdQDchIYEWcyByz8nJCaNHj+Ya6Do4OCA1NRVt2rQBAERGRsLLywuPHj0SNmgjqt3zzd7eHqdOnYKpqSkA4NmzZ2jZsqWoXg/u37+PiIgI5OTkoKqqSubYkiVLBErVNFFxJTK1h31oaWkhPj4ebdu2BSDOFwxCCKEGuoRUowa6DTtXMjY2rlNkyKtt27Zh2rRpaN68OYyMjGSG0UskErm/q/+xaEELEao9t0SMk7YJIeRtDbnOSIUVEYORI0fi1KlTOHHiBPr3748ZM2bIHFdXV4evr69A6ZoOMZ07rVq1CqtXr8b8+fOFjvK3QMWVCHl7e3NLZ5aWlsLHxwcaGhoAqpelJoQQMSooKICqqup7HyOWfldE3FxdXeHq6lrvsaVLl/Kchgjt5cuXGD16tNAx/jaouBIZLy8vmW1PT886jxk/fjxfcQghpMmgBrrVzzM1NRVv3rxBu3btoKhIpwlEfCQSCXexpeZvv7CwEK9fvwYA7r9iMXr0aJw5cwY+Pj5CR/lboDlXhBBCRE8qleLw4cMfbKDr4uLCUyL+paWlYdiwYUhKSgJQ3Tj08OHD6Nq1q8DJCOGXVCqVGfZXU2DV3pb3iy01vv/+e6xfvx7u7u6wt7eHkpKSzPGZM2cKlKxpouKKEEKI6FGPJ2DUqFFITEzEkiVLoKqqinXr1qG0tBQ3b94UOhohvIqMjGzQ4+T5YsvbalaKrI9EIsHDhw95TNP0UXFFCCFE9Ki4AoyMjHDo0CF89tlnAICsrCyYmJjg9evX3LxcQoi4MMaQkZGBFi1aQE1NTeg4fwvURJgQQojoUQPd6sapVlZW3LaxsTHU1NQ+2FCVyBdqoFtXYmIiEhISuI/ExEShI/GGMQYrKys8fvxY6Ch/G1RcEUIIEb20tDTo6+sLHUNQb0/ar/mQSqUoKCiQ2Ufkm7GxsUyBZW9vj8zMTG47NzcXTk5OQkTjzeXLl9GtWzduu2fPnnB0dESnTp3QqVMnODg44Ny5cwIm5I9UKoWVlRVyc3OFjvK3QcUVIYQQQsAYg7W1NXR1dbmPwsJCODo6QldXF82aNYOurq7QMUkjqz1b5NGjRygvL3/vY+TNli1bMG7cOJl9ERERSEtLw8OHDzFr1iz8/PPPAqXjX0BAAObOnYs7d+4IHeVvgdZYJYQQQggiIiKEjkD+JuS9ge4ff/yBhQsXyuwzMTGBubk5AGDcuHFwd3cXIpogxo8fj+LiYnTs2BHKysp15l7l5eUJlKxpouKKEEIIIaJZ+YyQD3n8+DF0dHS47R07dsDIyIjb1tPTE9UwuQ0bNggd4W+FiitCCCEE1EC3qqoKgYGB+O233/DmzRu4urpi6dKltEKYyFADXUBLSwsPHjyAqakpAODLL7+UOZ6WlgZtbW0hognCy8tL6Ah/K7QUOyGEENGjBrrAypUrsWzZMri5uUFNTQ3h4eHw8PBAcHCw0NEIj6iBLjB06FAYGBi883ff29sbL168wIkTJ3hOJoyMjIz3HjczM+Mpyd8DFVeEEEJEjxroAlZWVvD398fUqVMBAOfOnYO7uztKSkogldL6V2JBDXSr5x+6ubnBz88Pc+fO5frf5eTkYM2aNdi4cSPOnDmDvn37CpyUH7UL7trkudD+K6i4IoQQInrUQBdQUVFBamoqNxQKAFRVVZGamgoTExMBkxHCvy1btmDOnDmoqKiAtrY2JBIJXr16BUVFRfzwww+YPn260BF5Ex8fL7NdXl6OW7duYf369Vi9enWdYZNiR8UVIYQQ0ZNKpcjKyoKhoSG3T1NTE7dv30abNm0ETMYfBQUFZGdnw8DAgNunpaWFhIQE0fwMSF2JiYkydyYUFBTQvn17ARPxJzMzE4cOHcL9+/cBVN/dHTVqlMwFCDE7efIkAgMDcfHiRaGjNClUXBFCCBE9BQUF3Lt3T6awMDExwZUrV9C6dWtunzxPYpdKpRg0aBBUVFS4fcePH0ffvn1l7t4dOXJEiHiEJ5cvX4afnx9iYmIAVBfYxcXFXG8riUSC8PBwuLm5CRlTUMnJyQgKCsK6deuEjiKo1NRUdOzYEUVFRUJHaVKouCKEECJ69c0peHsivxgm8U+YMKFBjwsJCWnkJERIHh4ecHJywsyZMwFUF1cnT56Eubk5GGPYtGkT0tPTcfjwYYGT8quoqAj79u1DUFAQoqOjYWdnJ5qmurVXiGSMISsrC8uWLUNKSgri4uKECdZEiWudWUIIIaQe1ECXiiZSjRroyrp69SqCgoJw4MABlJSUYM6cOQgODoaNjY3Q0XjTrFmzei8+mZqaYt++fQKlarqouCKEECJ68rzyGSEfgxroVq8KGBoaiuDgYLx69QoeHh64ePEinJycMHHiRFEVVkDdi09SqRQGBgawtLQUXT/AhqCfCCGEENGjBrrAxIkTG/Q46nsl36iBLmBubo5Ro0Zh48aN6Nevn+hbEdDFp49DxRUhhBDRW716tUwD3Y0bNyInJ0dUhURoaCjMzc3h6OgImo4tXj169MDOnTvRu3fveo+HhoaiR48e/Ibimbm5Oa5cuQIzMzOYm5uL7k5VfR48eIANGzYgOTkZAGBnZ4dZs2bBwsJC4GRNDxVXhBBCRG/nzp3YsmVLnQa627dvF81V62nTpiEsLAxpaWmYMGECPD09oaenJ3QswjM/Pz+4ublBX1+/3ga6u3fvxpkzZwRO2bhSUlK4uVbdunWDtbU1PD09AeC9zXTlVXh4OIYNG4ZOnTrB2dkZQPVctPbt2+P48ePo16+fwAmbFlotkBBCiOhRA91qZWVlOHLkCIKDgxEVFQV3d3dMmjQJ/fv3F+VJpVhRA90/FRYWIiwsDCEhIYiOjoaLiwvGjh2LESNGyLRukGeOjo4YMGAAAgICZPYvWLAAZ86cQWxsrEDJmiYqrgghhIgeNdCtKz09HaGhodi5cycqKiqQmJgITU1NoWMRnoi5ge6KFSvg7+8PdXV1mf01/a127dqFvLw8lJeXC5SQX6qqqrh9+zasrKxk9t+7dw8ODg4oLS0VKFnTRMMCCSGEiB5jDN7e3jINdEtLS+Hj4yPaBro1vb8YY3Ld34vUz9TUFHPmzKmzXwwNdJcvXw4fH586xZWtrS3WrVuHgIAA/PbbbwKl45+BgQHi4uLqFFdxcXHcsFHyJ3EMJCeEEELew8vLCy1atICOjg734enpiZYtW8rsk3dlZWUICwtDv379YG1tjdu3b2Pz5s3IyMigu1YiVlRUhKCgIPTq1Qvt27fH6dOnhY7UqD40qEtRUbH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      "text/plain": [
       "<Figure size 1000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
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           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
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        },
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        },
        "width": 900,
        "xaxis": {
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          "text": "Branch Predictors"
         }
        },
        "yaxis": {
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         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(branchpredictors, overallMisses, \"Overall Cache Misses\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "# Load the variable from the file\n",
    "with open('more_iters_data.pkl', 'rb') as f:\n",
    "    more_iters_data = pickle.load(f)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Seconds_def', 'Cycles_def', 'Conditional Predicted_def',\n",
      "       'Conditional Incorrect_def', 'Branch Mispredicts_def',\n",
      "       'Overall Cache Misses_def', 'Seconds_2000tries', 'Cycles_2000tries',\n",
      "       'Conditional Predicted_2000tries', 'Conditional Incorrect_2000tries',\n",
      "       'Branch Mispredicts_2000tries', 'Overall Cache Misses_2000tries'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "# create a dataframe from the data\n",
    "import pandas as pd\n",
    "df1 = pd.DataFrame.from_dict(data, orient=\"index\")\n",
    "\n",
    "# join df1 with more_iters_data with suffixes for the same columns\n",
    "df = df1.join(more_iters_data, lsuffix=\"_def\", rsuffix=\"_2000tries\")\n",
    "\n",
    "\n",
    "print(df.columns)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_grouped_bar_chart(dataframe, stat, y_limit=None):\n",
    "    import matplotlib.pyplot as plt\n",
    "    import numpy as np\n",
    "    import plotly.graph_objects as go\n",
    "    from plotly.offline import iplot\n",
    "    from plotly.offline import plot\n",
    "    import plotly.tools as tls\n",
    "    import os\n",
    "\n",
    "    if not os.path.exists(\"graph_output\"):\n",
    "        os.mkdir(\"graph_output\")\n",
    "    stats_def = f\"{stat}_def\"\n",
    "    stats_2000tries = f\"{stat}_2000tries\"\n",
    "    # Extract the relevant columns\n",
    "    subset_data = dataframe[[stats_def, stats_2000tries]]\n",
    "\n",
    "    xticks = {\n",
    "        'o3cpu-spectre-tage-sc-l-64kb': \"TAGE SC L 64KB\",\n",
    "        'o3cpu-spectre-localBP': \"Local BP\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-8KB': \"MPP 8KB\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-tage-64kb' : \"MPP TAGE 64KB\",\n",
    "        'o3cpu-spectre-ltage': \"LTAGE\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-64KB' : \"MPP 64KB\",\n",
    "        'o3cpu-spectre-bimodebp': \"BiMode BP\",\n",
    "        'o3cpu-spectre-tournamentBP' : \"Tournament BP\",\n",
    "        'o3cpu-spectre-multiperspective-perceptron-tage-8kb': \"MPP TAGE 8KB\",\n",
    "        'o3cpu-spectre-TAGE': \"TAGE\",\n",
    "        'o3cpu-spectre-tage-sc-l-8kb': \"TAGE SC L 8KB\",\n",
    "    }\n",
    "\n",
    "    # Rename the index\n",
    "    subset_data = subset_data.rename(index=xticks)\n",
    "\n",
    "    # Create a bar chart with a wider gap between bars\n",
    "    ax = subset_data.plot(kind='bar', figsize=(10, 6), width=0.8)  # Adjust the width here\n",
    "    ax.set_xlabel('Branch Predictors')\n",
    "    ax.set_ylabel(stat)\n",
    "\n",
    "    # Set the title and position it below the chart\n",
    "    title = f'{stat} for 1000 iterations and 2000 iterations'\n",
    "    ax.set_title(title)\n",
    "    ax.title.set_position([0.5, 1.05])  # Adjust the y value to control the separation\n",
    "\n",
    "    ax.legend(['Default (1000 iterations)', '2000 iterations'])\n",
    "    ax.get_legend().remove()\n",
    "\n",
    "    if y_limit is not None:\n",
    "        ax.set_ylim(0, y_limit)\n",
    "\n",
    "    for i, (index, row) in enumerate(subset_data.iterrows()):\n",
    "        for j, value in enumerate(row):\n",
    "            if value > 10000:\n",
    "                if value > y_limit:\n",
    "                    pass\n",
    "                    #ax.text(i, y_limit, \"{:.1e}\".format(value), ha='center', va='bottom', fontsize=8)\n",
    "                # else:\n",
    "                #     # Format value in scientific notation and reduce font size\n",
    "                #     ax.text(i + j * 0.1, value, \"{:.1e}\".format(value), ha='center', va='bottom', fontsize=8)\n",
    "            else:\n",
    "                if value > y_limit:\n",
    "                    value = round(value, 2)\n",
    "                    #ax.text(i, y_limit, str(value), ha='center', va='bottom')\n",
    "                # else:\n",
    "                #     value = round(value, 2)\n",
    "                #     ax.text(i + j * 0.1, value, str(value), ha='center', va='bottom')\n",
    "\n",
    "    plt.show()\n",
    "    plotly_fig = tls.mpl_to_plotly(ax.figure)\n",
    "    \n",
    "    \n",
    "    \n",
    "    #colors = \"Blue\"\n",
    "    #pfig = go.Figure(data=[go.Bar(x=[xticks[x] for x in xvalues],y=yvalues,text=[f'{val:.2e}' for val in yvalues],textposition=\"outside\", marker_color=colors)])\n",
    "    \n",
    "    #t = {family = \"Open Sans\", size = 14,color = 'blue'}\n",
    "    #pfig.update_layout(width=900,height=900,title=title + \" for Each Benchmark\", xaxis_title=\"Branch Predictors\", yaxis_title=title, font=dict(family=\"Sans-Serif\", size=16) )\n",
    "    #pfig.update_yaxes(tickformat=\".2e\")\n",
    "    plotly_fig.update_xaxes(labelalias={0:\"BiMode BP\", 1:\"Local BP\",2:\"LTAGE\",3:\"MPP 64KB\",4:\"MPP 8KB\",5:\"MPP TAGE 64KB\",6:\"MPP TAGE 8KB\",7:\"TAGE\",8:\"TAGE SC L 64KB\",9:\"TAGE SC L 8KB\",10:\"Tournament BP\"})\n",
    "    y_limit_plotly = 2 \n",
    "    output_file_name = \"graph_output/SecondsAndIterations.png\"\n",
    "    \n",
    "    for i, value in enumerate(plotly_fig.data[0].y):\n",
    "        annotation_y = min(value, y_limit_plotly)\n",
    "        plotly_fig.add_annotation(\n",
    "            x=plotly_fig.data[0].x[i],\n",
    "            y=min(value, y_limit_plotly),\n",
    "            text=str(value),\n",
    "            font=dict(\n",
    "                size=8\n",
    "            ),\n",
    "            showarrow=True,\n",
    "            yshift=2 if value < max(plotly_fig.data[0].y) else -2,  # Adjust position based on value\n",
    "        )\n",
    "    for i, value in enumerate(plotly_fig.data[1].y):\n",
    "        plotly_fig.add_annotation(\n",
    "            x=plotly_fig.data[1].x[i],\n",
    "            y=min(value, y_limit_plotly),\n",
    "            text=str(value),\n",
    "            font=dict(\n",
    "                size=8\n",
    "            ),\n",
    "            showarrow=True,\n",
    "            yshift=10 if value < max(plotly_fig.data[1].y) else -10,  # Adjust position based on value\n",
    "        )\n",
    "    plotly_fig.update_layout(\n",
    "        bargap=0.3,\n",
    "        bargroupgap=0.2\n",
    "    )\n",
    "    plotly_fig.update_layout(yaxis=dict(range=[0, y_limit_plotly]),showlegend=True,\n",
    "    legend=dict(\n",
    "        orientation=\"v\",\n",
    "        yanchor=\"bottom\",\n",
    "        y=0.8,\n",
    "        xanchor=\"left\",\n",
    "        x=0.01,\n",
    "        bordercolor=\"Black\",\n",
    "        borderwidth=1\n",
    "    ))\n",
    "    plotly_fig.data[0].name=\"Default (1000 Iterations)\"\n",
    "    plotly_fig.data[1].name=\"2000 Iterations\"\n",
    "    plotly_fig.write_image(output_file_name)\n",
    "    #iplot(plotly_fig)\n",
    "    plotly_fig.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
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