Monero Analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# An Empirical Analysis of Traceability in the Monero Blockchain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy.stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from matplotlib.ticker import FuncFormatter\n",
    "from matplotlib.dates import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set_style(\"ticks\")\n",
    "FIGSIZE = (8, 5)\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from py2neo import Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "password = \"YOUR-PASSWORD-HERE\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "graph = Graph(user=\"neo4j\", password=password)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_data_frame(cursor):\n",
    "    return pd.DataFrame(list(map(dict, cursor)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Deducible Inputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Number of deducible spends\n",
    "\n",
    "- Returns all deducible spends between block heights `min_height` and `max_height`\n",
    "- Returns the number of available mixins, the index of the true spend and of the mixins (to calculate the position)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def deducible_spends(min_height, max_height):\n",
    "    query = \"\"\"\n",
    "      MATCH (o:UniqueSpend)<-[:SPENDS]-(:Input)<-[TX_INPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE b.height >= {min_height} AND b.height < {max_height}\n",
    "      WITH o\n",
    "      MATCH (o)<-[:SPENDS]-(i:Input)-[:REFERENCES]->(x)\n",
    "      WHERE NOT x = o AND i.anonset > 1000\n",
    "      RETURN ID(i) as iid, i.anonset as anonset, o.index as idx, COLLECT(x.index) as refs, i.mixin as mixins\n",
    "    \"\"\"\n",
    "    \n",
    "    df = to_data_frame(graph.run(query, min_height=min_height, max_height=max_height))\n",
    "    df.refs.apply(lambda x: x.sort(reverse=True))\n",
    "    df['position'] = df.apply(lambda row: sorted(row.refs + [row.idx], reverse=True).index(row.idx), axis=1)\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "spends_uniform = deducible_spends(0, 1009827)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "spends_triangular = deducible_spends(1009827, 1201528)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "spends_recent = deducible_spends(1201528, 1288775) # 1288774 was the max height in our paper"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Total number of inputs\n",
    "\n",
    "- Returns the total number of inputs with a certain amount of mixins between block heights `min_height` and `max_height`.\n",
    "- Ignores inputs where less than 1000 possible mixins are available (i.e. `anonset > 1000`).\n",
    "- Ignores RingCT transactions (i.e. `value > 0`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def total_inputs(min_height, max_height):\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)<-[:TX_INPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE b.height >= {min_height} AND b.height < {max_height} AND i.anonset > 1000 AND i.value > 0\n",
    "      WITH i\n",
    "      RETURN i.mixin as mixins, COUNT(*) as cnt\n",
    "    \"\"\"\n",
    "    df = pd.DataFrame(list(map(dict, graph.run(query, min_height=min_height, max_height=max_height))))\n",
    "    # aggregate mixins >= 10 into a single value\n",
    "    mixins_greater_ten = df[df.mixins >= 10].cnt.sum()\n",
    "    df = df[df.mixins <= 10]\n",
    "    df.loc[df.mixins == 10, 'cnt'] = mixins_greater_ten\n",
    "    df = df.sort_values(by=['mixins'])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs_uniform = total_inputs(0, 1009827)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs_triangular = total_inputs(1009827, 1201528)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "inputs_recent = total_inputs(1201528, 1288775)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Table 2: Monero transaction inputs where the real input can be deduced"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_row_deducible(df, counts, mixin):\n",
    "    if counts[counts.mixins == mixin].cnt.any():\n",
    "        total = counts[counts.mixins == mixin].iloc[0].cnt\n",
    "        deducible = len(df[(df.mixins == mixin)])\n",
    "        percent = deducible / total\n",
    "    else:\n",
    "        total = 0\n",
    "        deducible = 0\n",
    "        percent = None\n",
    "    result = pd.DataFrame({\n",
    "        \"total\": total,\n",
    "        \"deducible\": deducible,\n",
    "        \"percent\": percent\n",
    "    }, index=[mixin])\n",
    "    return result[[\"total\", \"deducible\", \"percent\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "total_deducible_uniform = pd.concat([compute_row_deducible(spends_uniform, inputs_uniform, mixin) for mixin in range(1, 11)])\n",
    "total_deducible_triangular = pd.concat([compute_row_deducible(spends_triangular, inputs_triangular, mixin) for mixin in range(1, 11)])\n",
    "total_deducible_recent = pd.concat([compute_row_deducible(spends_recent, inputs_recent, mixin) for mixin in range(1, 11)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total</th>\n",
       "      <th>deducible</th>\n",
       "      <th>percent</th>\n",
       "      <th>total</th>\n",
       "      <th>deducible</th>\n",
       "      <th>percent</th>\n",
       "      <th>total</th>\n",
       "      <th>deducible</th>\n",
       "      <th>percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>683458</td>\n",
       "      <td>608087</td>\n",
       "      <td>0.889721</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>250520</td>\n",
       "      <td>206276</td>\n",
       "      <td>0.823391</td>\n",
       "      <td>1882681</td>\n",
       "      <td>1209259</td>\n",
       "      <td>0.642307</td>\n",
       "      <td>732251</td>\n",
       "      <td>308926</td>\n",
       "      <td>0.421885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>634520</td>\n",
       "      <td>480500</td>\n",
       "      <td>0.757265</td>\n",
       "      <td>564525</td>\n",
       "      <td>376920</td>\n",
       "      <td>0.667676</td>\n",
       "      <td>126795</td>\n",
       "      <td>65738</td>\n",
       "      <td>0.518459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>217493</td>\n",
       "      <td>156767</td>\n",
       "      <td>0.720791</td>\n",
       "      <td>376432</td>\n",
       "      <td>192348</td>\n",
       "      <td>0.510977</td>\n",
       "      <td>145687</td>\n",
       "      <td>33022</td>\n",
       "      <td>0.226664</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>87077</td>\n",
       "      <td>43214</td>\n",
       "      <td>0.496273</td>\n",
       "      <td>48806</td>\n",
       "      <td>26599</td>\n",
       "      <td>0.544994</td>\n",
       "      <td>3900</td>\n",
       "      <td>950</td>\n",
       "      <td>0.243590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>115199</td>\n",
       "      <td>65546</td>\n",
       "      <td>0.568981</td>\n",
       "      <td>224202</td>\n",
       "      <td>119716</td>\n",
       "      <td>0.533965</td>\n",
       "      <td>24817</td>\n",
       "      <td>7890</td>\n",
       "      <td>0.317927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3671</td>\n",
       "      <td>1680</td>\n",
       "      <td>0.457641</td>\n",
       "      <td>4499</td>\n",
       "      <td>1770</td>\n",
       "      <td>0.393421</td>\n",
       "      <td>1711</td>\n",
       "      <td>235</td>\n",
       "      <td>0.137347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2216</td>\n",
       "      <td>1067</td>\n",
       "      <td>0.481498</td>\n",
       "      <td>5048</td>\n",
       "      <td>1968</td>\n",
       "      <td>0.389857</td>\n",
       "      <td>1458</td>\n",
       "      <td>249</td>\n",
       "      <td>0.170782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1811</td>\n",
       "      <td>838</td>\n",
       "      <td>0.462728</td>\n",
       "      <td>3264</td>\n",
       "      <td>1069</td>\n",
       "      <td>0.327512</td>\n",
       "      <td>264</td>\n",
       "      <td>48</td>\n",
       "      <td>0.181818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>57363</td>\n",
       "      <td>7419</td>\n",
       "      <td>0.129334</td>\n",
       "      <td>46791</td>\n",
       "      <td>12237</td>\n",
       "      <td>0.261525</td>\n",
       "      <td>9145</td>\n",
       "      <td>1609</td>\n",
       "      <td>0.175943</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     total  deducible   percent    total  deducible   percent   total  \\\n",
       "1   683458     608087  0.889721        0          0       NaN       0   \n",
       "2   250520     206276  0.823391  1882681    1209259  0.642307  732251   \n",
       "3   634520     480500  0.757265   564525     376920  0.667676  126795   \n",
       "4   217493     156767  0.720791   376432     192348  0.510977  145687   \n",
       "5    87077      43214  0.496273    48806      26599  0.544994    3900   \n",
       "6   115199      65546  0.568981   224202     119716  0.533965   24817   \n",
       "7     3671       1680  0.457641     4499       1770  0.393421    1711   \n",
       "8     2216       1067  0.481498     5048       1968  0.389857    1458   \n",
       "9     1811        838  0.462728     3264       1069  0.327512     264   \n",
       "10   57363       7419  0.129334    46791      12237  0.261525    9145   \n",
       "\n",
       "    deducible   percent  \n",
       "1           0       NaN  \n",
       "2      308926  0.421885  \n",
       "3       65738  0.518459  \n",
       "4       33022  0.226664  \n",
       "5         950  0.243590  \n",
       "6        7890  0.317927  \n",
       "7         235  0.137347  \n",
       "8         249  0.170782  \n",
       "9          48  0.181818  \n",
       "10       1609  0.175943  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([total_deducible_uniform, total_deducible_triangular, total_deducible_recent], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Table 3. Percentage of deducible transaction inputs where the real input is the “newest” input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def compute_row_newest(df, mixin):\n",
    "    if mixin < 10:\n",
    "        deducible = len(df[(df.mixins == mixin)])\n",
    "        newest = len(df[(df.mixins == mixin) & (df.position == 0)])\n",
    "    else:\n",
    "        deducible = len(df[(df.mixins >= mixin)])\n",
    "        newest = len(df[(df.mixins >= mixin) & (df.position == 0)])\n",
    "    if deducible > 0:\n",
    "        percent = newest / deducible\n",
    "    else:\n",
    "        percent = None\n",
    "    return pd.DataFrame({\n",
    "        \"deducible\": deducible,\n",
    "        \"newest\": newest,\n",
    "        \"percent\": percent\n",
    "    }, index=[mixin])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "percent_deducible_uniform = pd.concat([compute_row_newest(spends_uniform, mixin) for mixin in range(1, 11)])\n",
    "percent_deducible_triangular = pd.concat([compute_row_newest(spends_triangular, mixin) for mixin in range(1, 11)])\n",
    "percent_deducible_recent = pd.concat([compute_row_newest(spends_recent, mixin) for mixin in range(1, 11)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>deducible</th>\n",
       "      <th>newest</th>\n",
       "      <th>percent</th>\n",
       "      <th>deducible</th>\n",
       "      <th>newest</th>\n",
       "      <th>percent</th>\n",
       "      <th>deducible</th>\n",
       "      <th>newest</th>\n",
       "      <th>percent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>608087</td>\n",
       "      <td>585424</td>\n",
       "      <td>0.962731</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>206276</td>\n",
       "      <td>191372</td>\n",
       "      <td>0.927747</td>\n",
       "      <td>1209259</td>\n",
       "      <td>1126924</td>\n",
       "      <td>0.931913</td>\n",
       "      <td>308926</td>\n",
       "      <td>293051</td>\n",
       "      <td>0.948612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>480500</td>\n",
       "      <td>461154</td>\n",
       "      <td>0.959738</td>\n",
       "      <td>376920</td>\n",
       "      <td>353246</td>\n",
       "      <td>0.937191</td>\n",
       "      <td>65738</td>\n",
       "      <td>59693</td>\n",
       "      <td>0.908044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>156767</td>\n",
       "      <td>139626</td>\n",
       "      <td>0.890659</td>\n",
       "      <td>192348</td>\n",
       "      <td>149722</td>\n",
       "      <td>0.778391</td>\n",
       "      <td>33022</td>\n",
       "      <td>18889</td>\n",
       "      <td>0.572013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>43214</td>\n",
       "      <td>39854</td>\n",
       "      <td>0.922247</td>\n",
       "      <td>26599</td>\n",
       "      <td>24971</td>\n",
       "      <td>0.938795</td>\n",
       "      <td>950</td>\n",
       "      <td>473</td>\n",
       "      <td>0.497895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>65546</td>\n",
       "      <td>51816</td>\n",
       "      <td>0.790529</td>\n",
       "      <td>119716</td>\n",
       "      <td>102378</td>\n",
       "      <td>0.855174</td>\n",
       "      <td>7890</td>\n",
       "      <td>6458</td>\n",
       "      <td>0.818504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1680</td>\n",
       "      <td>1522</td>\n",
       "      <td>0.905952</td>\n",
       "      <td>1770</td>\n",
       "      <td>989</td>\n",
       "      <td>0.558757</td>\n",
       "      <td>235</td>\n",
       "      <td>115</td>\n",
       "      <td>0.489362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1067</td>\n",
       "      <td>964</td>\n",
       "      <td>0.903468</td>\n",
       "      <td>1968</td>\n",
       "      <td>1310</td>\n",
       "      <td>0.665650</td>\n",
       "      <td>249</td>\n",
       "      <td>163</td>\n",
       "      <td>0.654618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>838</td>\n",
       "      <td>692</td>\n",
       "      <td>0.825776</td>\n",
       "      <td>1069</td>\n",
       "      <td>355</td>\n",
       "      <td>0.332086</td>\n",
       "      <td>48</td>\n",
       "      <td>40</td>\n",
       "      <td>0.833333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11997</td>\n",
       "      <td>10822</td>\n",
       "      <td>0.902059</td>\n",
       "      <td>12970</td>\n",
       "      <td>11750</td>\n",
       "      <td>0.905937</td>\n",
       "      <td>1682</td>\n",
       "      <td>1480</td>\n",
       "      <td>0.879905</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    deducible  newest   percent  deducible   newest   percent  deducible  \\\n",
       "1      608087  585424  0.962731          0        0       NaN          0   \n",
       "2      206276  191372  0.927747    1209259  1126924  0.931913     308926   \n",
       "3      480500  461154  0.959738     376920   353246  0.937191      65738   \n",
       "4      156767  139626  0.890659     192348   149722  0.778391      33022   \n",
       "5       43214   39854  0.922247      26599    24971  0.938795        950   \n",
       "6       65546   51816  0.790529     119716   102378  0.855174       7890   \n",
       "7        1680    1522  0.905952       1770      989  0.558757        235   \n",
       "8        1067     964  0.903468       1968     1310  0.665650        249   \n",
       "9         838     692  0.825776       1069      355  0.332086         48   \n",
       "10      11997   10822  0.902059      12970    11750  0.905937       1682   \n",
       "\n",
       "    newest   percent  \n",
       "1        0       NaN  \n",
       "2   293051  0.948612  \n",
       "3    59693  0.908044  \n",
       "4    18889  0.572013  \n",
       "5      473  0.497895  \n",
       "6     6458  0.818504  \n",
       "7      115  0.489362  \n",
       "8      163  0.654618  \n",
       "9       40  0.833333  \n",
       "10    1480  0.879905  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([percent_deducible_uniform, percent_deducible_triangular, percent_deducible_recent], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Figure 5: Fraction of transaction inputs that can be deduced and transactions including at least one deducible input"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_all_inputs():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)<-[:TX_INPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      RETURN b.timestamp as timestamp, COUNT(i) as cnt\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    df.timestamp = pd.to_datetime(df.timestamp, unit='s')\n",
    "    df = df.resample('1d', on='timestamp').sum()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_zero_mixins():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)\n",
    "      WHERE i.mixin = 0\n",
    "      WITH i\n",
    "      MATCH (i)<-[:TX_INPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      RETURN b.timestamp as timestamp, COUNT(i) as cnt\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    df.timestamp = pd.to_datetime(df.timestamp, unit='s')\n",
    "    df = df.resample('1d', on='timestamp').sum()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_deducible():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)\n",
    "      WHERE (i)-[:SPENDS]->()\n",
    "      WITH i\n",
    "      MATCH (i)<-[:TX_INPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      RETURN b.timestamp as timestamp, COUNT(i) as cnt\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    df.timestamp = pd.to_datetime(df.timestamp, unit='s')\n",
    "    df = df.resample('1d', on='timestamp').sum()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_all_transactions():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)<-[:TX_INPUT]-(tx:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE b.height > 0 AND NOT tx:Coinbase AND i.mixin > 0\n",
    "      RETURN b.timestamp as timestamp, COUNT(DISTINCT(tx)) as cnt\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    df.timestamp = pd.to_datetime(df.timestamp, unit='s')\n",
    "    df = df.resample('1d', on='timestamp').sum()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "def time_deducible_transactions():\n",
    "    query = \"\"\"\n",
    "      MATCH ()<-[:SPENDS]-(i:Input)<-[:TX_INPUT]-(tx:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE b.height > 0 AND i.mixin > 0\n",
    "      WITH tx, b.timestamp as timestamp\n",
    "      RETURN timestamp, COUNT(DISTINCT(tx)) as cnt\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    df.timestamp = pd.to_datetime(df.timestamp, unit='s')\n",
    "    df = df.resample('1d', on='timestamp').sum()\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_time_all_inputs = time_all_inputs()\n",
    "df_time_zero_mixins = time_zero_mixins()\n",
    "df_time_deducible = time_deducible()\n",
    "df_time_all_transactions = time_all_transactions()\n",
    "df_time_deducible_transactions = time_deducible_transactions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_time = pd.DataFrame({\n",
    "    \"All deducible inputs\": df_time_deducible.div(df_time_all_inputs).cnt,\n",
    "    \"0 mixin inputs\": df_time_zero_mixins.div(df_time_all_inputs).cnt,\n",
    "    \"Deducible transactions\": df_time_deducible_transactions.div(df_time_all_transactions).cnt\n",
    "}, index=df_time_all_transactions.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1eb6e2e48>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_time.resample(\"1d\").mean().fillna(0).rolling(window=7, min_periods=7, center=True).mean().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Age distributions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All Inputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def age_dist_all():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)<-[:TX_INPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE b.height >= 900000 AND b.height <= 1200000 AND i.anonset > 1000\n",
    "      WITH i, b.timestamp as ts1\n",
    "      MATCH (i)-[:REFERENCES]->(o:Output)<-[:TX_OUTPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      RETURN ID(i) as inId, COLLECT(ts1 - b.timestamp) as times\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_age_all = age_dist_all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_all = list(itertools.chain.from_iterable(df_age_all.times))\n",
    "age_all = [x / (24*60*60) for x in age_all]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=FIGSIZE)\n",
    "plt.hist(age_all, 99)\n",
    "\n",
    "plt.yticks(range(0, 3500000, 500000), [x for x in range(0, 3500000, 500000)])\n",
    "\n",
    "plt.xlabel('Spend time (in days)')\n",
    "sns.despine()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ruled out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def age_dist_fake():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)<-[:TX_INPUT]-(tx:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE b.height >= 900000 AND b.height <= 1200000 AND i.anonset > 1000\n",
    "      WITH i, b.timestamp as ts1\n",
    "      MATCH (i)-[:REFERENCES]->(o:UniqueSpend)<-[:TX_OUTPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      WHERE NOT (i)-[:SPENDS]->(o)\n",
    "      RETURN ID(i) as inId, COLLECT(ts1 - b.timestamp) as times\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_age_fake = age_dist_fake()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_fake = list(itertools.chain.from_iterable(df_age_fake.times))\n",
    "age_fake = [x / (24*60*60) for x in age_fake]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABkAAAAPoCAYAAACGezKDAAAgAElEQVR4Xuzde7BW1X0/4GVA44B2vOAVZvBS8RJ0ao0anYojeEkUpwpIBETFS5WIFQ1FnQjSeE3xErWgthqNGtBoVMALKoKMRgVra4toaKS1wZSqlRHHOCJEfrP2r+cMvOwD7+Gcvc9Z+332TGbwvOu2n+/6K5/Za22xdu3atcFDgAABAgQIECBAgAABAgQIECBAgAABAgQIEKiQwBYCkApV06sQIECAAAECBAgQIECAAAECBAgQIECAAAECmYAAxEYgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKicgAKlcSb0QAQIECBAgQIAAAQIECBAgQIAAAQIECBAgIACxBwgQIECAAAECBAgQIECAAAECBAgQIECAAIHKCQhAKldSL0SAAAECBAgQIECAAAECBAgQIECAAAECBAgIQOwBAgQIECBAgAABAgQIECBAgAABAgQIECBAoHICApDKldQLESBAgAABAgQIECBAgAABAgQIECBAgAABAgIQe4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBConIAApHIl9UIECBAgQIAAAQIECBAgQIAAAQIECBAgQICAAMQeIECAAAECBAgQIECAAAECBAgQIECAAAECBConIACpXEm9EAECBAgQIECAAAECBAgQIECAAAECBAgQICAAsQcIECBAgAABAgQIECBAgAABAgQIECBAgACBygkIQCpXUi9EgAABAgQIECBAgAABAgQIECBAgAABAgQICEDsAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKByAgKQypXUCxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQICEHuAAAECBAgQIECAAAECBAgQIECAAAECBAgQqJyAAKRyJfVCBAgQIECAAAECBAgQIECAAAECBAgQIECAgADEHiBAgAABAgQIECBAgAABAgQIECBAgAABAgQqJyAAqVxJvRABAgQIECBAgAABAgQIECBAgAABAgQIECAgALEHCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcoJCEAqV1IvRIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAhA7AECBAgQIECAAAECBAgQIECAAAECBAgQIECgcgICkMqV1AsRIECAAAECBAgQIECAAAECBAgQIECAAAECAhB7gAABAgQIECBAgAABAgQIECBAgAABAgQIEKicgACkciX1QgQIECBAgAABAgQIECBAgAABAgQIECBAgIAAxB4gQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKicgAKlcSb0QAQIECBAgQIAAAQIECBAgQIAAAQIECBAgIACxBwgQIECAAAECBAgQIECAAAECBAgQIECAAIHKCQhAKldSL0SAAAECBAgQIECAAAECBAgQIECAAAECBAgIQOwBAgQIECBAgAABAgQIECBAgAABAgQIECBAoHICApDKldQLESBAgAABAgQIECBAgAABAgQIECBAgAABAgIQe4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBConIAApHIl9UIECBAgQIAAAQIECBAgQIAAAQIECBAgQICAAMQeIECAAAECBAgQIECAAAECBAgQIECAAAECBConIACpXEm9EAECBAgQIECAAAECBAgQIECAAAECBAgQICAAsQcIECBAgAABAgQIECBAgAABAgQIECBAgACBygkIQCpXUi9EgAABAgQIECBAgAABAgQIECBAgAABAgQICEDsAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKByAgKQypXUCxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQICEHuAAAECBAgQIECAAAECBAgQIECAAAECBAgQqJyAAKRyJfVCBAgQIECAAAECBAgQIECAAAECBAgQIECAgADEHiBAgAABAgQIECBAgAABAgQIECBAgAABAgQqJyAAqVxJvRABAgQIECBAgAABAgQIECBAgAABAgQIECAgALEHCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcoJCEAqV1IvRIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAhA7AECBAgQIECAAAECBAgQIECAAAECBAgQIECgcgICkMqV1AsRIECAAAECBAgQIECAAAECBAgQIECAAAECAhB7gAABAgQIECBAgAABAgQIECBAgAABAgQIEKicgACkciX1QgQIECBAgAABAgQIECBAgAABAgQIECBAgIAAxB4gQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKicgAKlcSb0QAQIECBAgQIAAAQIECBAgQIAAAQIECBAgIACxBwgQIECAAAECBAgQIECAAAECBAgQIECAAIHKCQhAKldSL0SAAAECBAgQIECAAAECBAgQIECAAAECBAgIQOwBAgQIECBAgAABAgQIECBAgAABAgQIECBAoHICApDKldQLESBAgAABAgQIECBAgAABAgQIECBAgAABAgIQe4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBConIAApHIl9UIECBAgQIAAAQIECBAgQIAAAQIECBAgQICAAMQeIECAAAECBAgQIECAAAECBAgQIECAAAECBConIACpXEm9EAECBAgQIECAAAECBAgQIECAAAECBAgQICAAsQcIECBAgAABAgQIECBAgAABAgQIECBAgACBygkIQCpXUi9EgAABAgQIECBAgAABAgQIECBAgAABAgQICEDsAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKByAgKQypXUCxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQICEHuAAAECBAgQIECAAAECBAgQIECAAAECBAgQqJyAAKRyJfVCBAgQIECAAAECBAgQIECAAAECBAgQIECAgADEHiBAgAABAgQIECBAgAABAgQIECBAgAABAgQqJyAAqVxJvRABAgQIECBAgAABAgQIECBAgAABAgQIECAgALEHCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcoJCEAqV1IvRIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAhA7AECBAgQIECAAAECBAgQIECAAAECBAgQIECgcgICkMqV1AsRIECAAAECBAgQIECAAAECBAgQIECAAAECAhB7gAABAgQIECBAgAABAgQIECBAgAABAgQIEKicgACkciX1QgQIECBAgAABAgQIECBAgAABAgQIECBAgIAAxB4gQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKicgAKlcSb0QAQIECBAgQIAAAQIECBAgQIAAAQIECBAgIACxBwgQIECAAAECBAgQIECAAAECBAgQIECAAIHKCQhAKldSL0SAAAECBAgQIECAAAECBAgQIECAAAECBAgIQOwBAgQIECBAgAABAgQIECBAgAABAgQIECBAoHICApDKldQLESBAgAABAgQIECBAgAABAgQIECBAgAABAgIQe4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBConIAApHIl9UIECBAgQIAAAQIECBAgQIAAAQIECBAgQICAAMQeIECAAAECBAgQIECAAAECBAgQIECAAAECBConIACpXEm9EAECBAgQIECAAAECBAgQIECAAAECBAgQICAAsQcIECBAgAABAgQIECBAgAABAgQIECBAgACBygkIQCpXUi9EgAABAgQIECBAgAABAgQIECBAgAABAgQICEDsAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKByAgKQypXUCxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQICEHuAAAECBAgQIECAAAECBAgQIECAAAECBAgQqJyAAKRyJfVCBAgQIECAAAECBAgQIECAAAECBAgQIECAgADEHiBAgAABAgQIECBAgAABAgQIECBAgAABAgQqJyAAqVxJvRABAgQIECBAgAABAgQIECBAgAABAgQIECAgALEHCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcoJCEAqV1IvRIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAhA7AECBAgQIECAAAECBAgQIECAAAECBAgQIECgcgICkMqV1AsRIECAAAECBAgQIECAAAECBAgQIECAAAECAhB7gAABAgQIECBAgAABAgQIECBAgAABAgQIEKicgACkciX1QgQIECBAgAABAgQIECBAgAABAgQIECBAgIAAxB4gQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKicgAKlcSb0QAQIECBAgQIAAAQIECBAgQIAAAQIECBAgIACxBwgQIECAAAECBAgQIECAAAECBAgQIECAAIHKCQhAKldSL0SAAAECBAgQIECAAAECBAgQIECAAAECBAgIQOwBAgQIECBAgAABAgQIECBAgAABAgQIECBAoHICApDKldQLESBAgAABAgQIECBAgAABAgQIECBAgAABAgIQe4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBConIAApHIl9UIECBAgQIAAAQIECBAgQIAAAQIECBAgQICAAMQeIECAAAECBAgQIECAAAECBAgQIECAAAECBConIACpXEm9EAECBAgQIECAAAECBAgQIECAAAECBAgQICAAsQcIECBAgAABAgQIECBAgAABAgQIECBAgACBygkIQCpXUi9EgAABAgQIECBAgAABAgQIECBAgAABAgQICEBauQeef/758Mtf/jIsWrQo/OEPfwg9evQIBx98cBg6dGg44ogjWhxt9erVYfr06WHmzJlh6dKlYe3ataFnz57h2GOPDaNGjQrbbbfdRleyZMmScM8994QFCxaEFStWZO379u0bhg8fHvr167fRvo06dytLqzkBAgQIECBAgAABAgQIECBAgAABAgQIVEhAAFJnMWOI8Dd/8zfh2WefbbHH97///fC3f/u3YYsttlivzapVq8J5550XFi5cmNt35513Dvfee2/o06dP7u8vvvhiuOSSS0JcQ94zcuTIcNVVV+X+1qhz11lWzQgQIECAAAECBAgQIECAAAECBAgQIECgogICkDoLe+ONN4b77rsva/3d7343nHPOOaFXr17h97//fRZezJ49O/tt7NixYfTo0euNetlll4Wnn346bLnllmHMmDFh4MCBYauttgrz588PkydPDitXrsy+BnnqqadCt27d1uv7zjvvhGHDhoUvv/wyHHjggWH8+PFhn332CR988EG46667wpw5c7L2EydODCNGjNjgbRp17jrLqhkBAgQIECBAgAABAgQIECBAgAABAgQIVFRAAFJHYT/88MMwYMCA7AuMk046Kdxyyy0b9Iqhx9y5c8Of/MmfhFdeeSV885vfzNrEo7KGDBmS/XvSpElZmLHuEwOOeHxWHPvSSy8NF1544Xq/X3DBBeGll14KvXv3Dk888UTo3r178+/xGK0YuMTwJR6JFb8U2WabbZp/b9S56yipJgQIECBAgAABAgQIECBAgAABAgQIECBQcQEBSB0Ffvjhh8PVV1+dtXzmmWfC3nvvvUGveDRWDCPiM2PGjLDffvtl/276AiN+LRLvD+nSpcsGfePxVY8++mj2RUkMMZqeeFfIiSeemP3n9ddfHwYPHrxB3+XLl4f+/fuHr7/+OsSvVE499dTmNo06dx0l1YQAAQIECBAgQIAAAQIECBAgQIAAAQIEKi4gAKmzwP/zP/8T/vM//7PFi87XDUDicVd/+qd/ml10fthhh4XPPvssbOyejnnz5jV/+bFueHL//feHG264IbtT5NVXXw077LBD7moHDRoUFi9enF2oPmXKlKxNo85dZzk1I0CAAAECBAgQIECAAAECBAgQIECAAIGKCwhA2qHA8fiqeCdIvOQ83uURv/To2rVrWLZsWRZKxKf264x1p41HbPXr1y/703XXXdd8ZNbll18ennzyyWzMeLxWS0/TFyS77bZbdlxWfBp17nYopyEIECBAgAABAgQIECBAgAABAgQIECBAoAICApDNLOIXX3wRPvroo/DP//zPIX6psWTJkuyS86lTpzaHGa+//no466yzshkeeuihcOihh+bOFo+vOuigg7J7QOJdIk1HaZ1xxhnhjTfeCIcffnh44IEHWlxpnPO2227LvhR5++23s/ClUefezHLqRoAAAQIECBAgQIAAAQIECBAgQIAAAQIVExCAbGZBR4wYEf7pn/6puXf8+uKnP/1p+LM/+7Pmv617LNbMmTPDvvvu2+JsMeT49NNPQxx34sSJWbt44fp7770Xjj/++HDHHXe02PfBBx8M1157bfb7a6+9lh2V1ahz11vOeKTZxp41a9aEFStWhJ133jn06NEjC5U8BAgQIECAAAECBAgQIECAAAECBAgQIJCOgABkM2t1zDHHhP/+7/9er/f+++8f4nFU3/72t7O/x+Or4jFW8YnHYvXu3bvF2eIRWPEorCFDhmTHYMUnHp8Vj7I6+eSTw0033dRi33iBepw3PvPnzw+77rprw85dbzk3FkbVjtFkWu/Y2hEgQIAAAQIECBAgQIAAAQIECBAgQIBAxwsIQDazBv/xH/8RevXqFT7//PPw4osvZgFF/IJj6623Dvfdd1/48z//8zBr1qwwbty4bIbNCUBOOOGE8P77729WANKoc9dbTgFIvVLaESBAgAABAgQIECBAgAABAgQIECBAIE0BAUg71e3f//3fs683Vq1aFQ4++ODw8MMPhzlz5oSLLroomyEGEn369GlxtqYjsOK9HxMmTMjanXLKKeHdd98NMQi5/fbbW+y77hFY8e6P7bffvmHnrrecmzoCK97vctppp2XD+QKkXlXtCBAgQIAAAQIECBAgQIAAAQIECBAg0HkEBCDtWIt4DFU8jio+8S6OeH/HyJEjs/+eNm1aOOSQQ3JnW/cS9IsvvjiMGTMmaxf7Lly4MBx55JHZVyUtPVOmTMkCki5dumSXoH/jG9/I+jXi3O1VzhiQHH300dlwApD2UjUOAQIECBAgQIAAAQIECBAgQIAAAQIEyhMQgLSj9fTp08OkSZOyEWMQEu/iOOqoo7L/jkdkxbs88p5490e8AyQ+119/fRg8eHD273gZ+iOPPBL22GOP8Nxzz7W40qbgZffddw/z5s3L2sUvGBpx7vYqpwCkvSSNQ4AAAQIECBAgQIAAAQIECBAgQIAAgY4REIDU4f4P//AP4aWXXgo77LBD+Pu///sWe9x///3hhhtuyH5vOvKq6Wirc845p/lC9NoB5s6dG0aPHp39OV6cHi9Tj89DDz0UrrnmmuzLjvhFxzbbbJM796BBg8LixYvDgAEDwtSpU5vbNOrcdZR0k00EIJsk0oAAAQIECBAgQIAAAQIECBAgQIAAAQKdWkAAUkd5rr322hDv2ejatWuIYcUuu+yS2+vcc88Nr7zySujevXuId3FstdVWYfz48WHGjBlhr732Cs8880zYYostNujb9AXHTjvtFF5++eXmNsuWLQvHHnts1v7mm28OAwcO3KDv8uXLQ//+/UM8Rit+fTJs2LDmNo06dx0l3WQTAcgmiTQgQIAAAQIECBAgQIAAAQIECBAgQIBApxYQgNRRnn/7t39rvhD7L//yL8Pf/d3fbdDr6aefDpdddln293UvMo93gZx99tnZ3+ORViNGjFiv7zvvvBOGDh0aVq9eHcaNGxfOP//89X4fPnx4ePPNN7NjsB577LGw7bbbNv++du3aMHbs2DB79uzs4vMYznTr1q3590adu46SbrKJAGSTRBoQIECAAAECBAgQIECAAAECBAgQIECgUwsIQOosz+WXX54dTxWfY445Jgsq9txzz/DJJ5+EJ554IsTjr/74xz+G3r17h1/+8pdhu+22ax45Hm8Vw4l4lFXsN2TIkLD11ltnl2tPnjw5fPrpp6FXr17ZlyK1x1wtWrQoC0jiFx59+vTJjtE64IADQvzy48477wwvvPBCNk9euBL/3qhz11nWFpsJQNoqqD8BAgQIECBAgAABAgQIECBAgAABAgQ6VkAAUqf/V199FX74wx+G559/vsUe8e6OeEdIDDPWfVauXBni8VgxzMh7evToEaZNm5aFJ3nP448/HiZMmBDWrFmT+/uoUaPCFVdckftbo85dZ1lbbCYAaaug/gQIECBAgAABAgQIECBAgAABAgQIEOhYAQFIK/3nzJkTHn300RCPxfrss8+yLzZi8HHSSSeFU045JWy55Za5I8YjrqZPn55djr506dIQA5WePXs2f02y4447bnQlS5YsCffee29YsGBB9tVJPOqqb9++IR6R1XRPSEsDNOrcrSztes0FIG3R05cAAQIECBAgQIAAAQIECBAgQIAAAQIdLyAA6fgaWEEnFBCAdMKiWBIBAgQIECBAgAABAgQIECBAgAABAgRaISAAaQWWpo0jIABpnFp7UwIECBAgQIAAAQIECBAgQIAAAQIEqikgAKlmXb1VGwUEIG0E1J0AAQIECBAgQIAAAQIECBAgQIAAAQIdLCAA6eACmL5zCghAOmddrIoAAQIECBAgQIAAAQIECBAgQIAAAQL1CghA6pXSrqEEBCANVW4vS4AAAQIECBAgQIAAAQIECBAgQIBABQUEIBUsqldqu4AApO2GRiBAgAABAgQIECBAgAABAgQIECBAgEBHCghAOlLf3J1WQADSaUtjYQQIECBAgAABAgQIECBAgAABAgQIEKhLQABSF5NGjSYgAGm0intfAgQIECBAgAABAgQIECBAgAABAgSqJiAAqVpFvU+7CAhA2oXRIAQIECBAgAABAgQIECBAgAABAgQIEOgwAQFIh9GbuDMLCEA6c3WsjQABAgQIECBAgAABAgQIECBAgAABApsWEIBs2kiLBhQQgDRg0b0yAQIECBAgQIAAAQIECBAgQIAAAQKVEhCAVKqcXqa9BAQg7SVpHAIECBAgQIAAAQIECBAgQIAAAQIECHSMgACkY9zN2skFBCCdvECWR4AAAQIECBAgQIAAAQIECBAgQIAAgU0ICEBsEQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BArkszggAACAASURBVAKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCCbAT1//vzwq1/9Krz11lthxYoVYauttgq9e/cORx99dDjzzDPDDjvssMGon376aTj88MM3Odt2220XFixYkNtuyZIl4Z577sl+j/PGtn379g3Dhw8P/fr12+jYq1evDtOnTw8zZ84MS5cuDWvXrg09e/YMxx57bBg1alQ21saeVOfeJHgLDQQgmyunHwECBAgQIECAAAECBAgQIECAAAECBDqHgACkFXVYs2ZNuOKKK8KsWbNa7LXjjjuGKVOmhIMPPni9Nq+++moWNGzqaSkAefHFF8Mll1wSYpCR94wcOTJcddVVub+tWrUqnHfeeWHhwoW5v++8887h3nvvDX369Mn9PdW5N2W9sd8FIG3R05cAAQIECBAgQIAAAQIECBAgQIAAAQIdLyAAaUUNfvKTn4Sf/exnWY8BAwZkocKee+4ZPv744xC/Cpk6dWr44osvsq8p4pcWu+yyS/Po//iP/xhuuummsOuuu4ZnnnmmxVm32GKL0K1bt/V+f+edd8KwYcPCl19+GQ488MAwfvz4sM8++4QPPvgg3HXXXWHOnDlZ+4kTJ4YRI0ZsMPZll10Wnn766bDllluGMWPGhIEDB2ZfrcQ1T548OaxcuTL7GuSpp56q1NytKO0GTQUgbdHTlwABAgQIECBAgAABAgQIECBAgAABAh0vIACpswYffvhh6N+/f4hfgZx88slZmFH7LFq0KJx++ulZmxhExECi6Rk7dmx49tlnw/HHHx/uuOOOOmf9/80uuOCC8NJLL2XHbD3xxBOhe/fuzf3jUVZx7NmzZ2fBS/xaY5tttmn+Pa5pyJAh2X9PmjQpC1LWfWK4MnTo0OzLkksvvTRceOGF6/2e6tytAs5pLABpq6D+BAgQIECAAAECBAgQIECAAAECBAgQ6FgBAUid/r/4xS/Cj3/846z13Llzsy8m8p54TFUMI+LvsV3TE4OP//qv/wo//OEPw1/91V/VOWvI7us48cQTs/bXX399GDx48AZ9ly9fnoUzX3/9dbjxxhvDqaee2tym6euPXr16heeffz506dJlg/7x6KxHH300xDYxQGl6Up67buAWGgpA2iqoPwECBAgQIECAAAECBAgQIECAAAECBDpWQABSp/+tt94a7r///uzril//+tct9rrlllvC3XffnR039fbbb2ftPv/88/Dtb387u3g8jnHEEUfUOWvI2t9www0hHo0V7xHJu2A9DjZo0KCwePHi7FLzeAdJfOJ8hx12WPjss8/Cxu4ImTdvXvOXHzNmzAj77bdf1j/VuevG3UhDAUh7KBqDAAECBAgQIECAAAECBAgQIECAAAECHScgAGmlfQwz1j1iqrZ70xcgPXr0aA5KFixYEM4888wsxHj44YfD448/Hl555ZXw0UcfZWMddNBB2ZFZRx999Aarufzyy8OTTz65wRcltQ2bvuLYbbfdsuOy4rNs2bIsEIlP7Zch6/aPx3v169cv+9N1113XfGRWqnO3sqS5zQUg7aFoDAIECBAgQIAAAQIECBAgQIAAAQIECHScgACkHe1jkHDccceFVatWhRNOOCHcfvvt2ej33XdfFkB84xvfyP4X7wjJe+JXHNdcc03o2rVr889nnHFGeOONN8Lhhx8eHnjggRZXGy9gv+2227KQJX55Esd4/fXXw1lnnZX1eeihh8Khhx6a2z8enRVDmHgPyOjRo7M7ReKT6tztUVIBSHsoGoMAAQIECBAgQIAAAQIECBAgQIAAAQIdJyAAaSf7eNxUvEC86euLn//85+E73/lONnq89+Opp57K/h0vMr/ooouyo6niMVlvvfVWdin6b37zm+z3+KXIj370o+ZVnXTSSeG9997b5OXpDz74YLj22muzfq+99lp2VFa8dL0pzJg5c2bYd999W3zbGLB8+umn613enurc9ZQ0Bhwbe+LXOaeddlrWZP78+WHXXXetZ1htCBAgQIAAAQIECBAgQIAAAQIECBAgQKCTCAhA2qkQ8YLyGHrEZ+DAgeHmm29uHnnMmDHZcVgx/IhfYtQeofXll19mX2rEMCR+wRHv4WgKK+IRVvEoq5NPPjncdNNNLa42XmIej8Fa9/+wj0dnxWOs4hMvQI/zt/TEI7DiFyxDhgzJjsGKT6pz11PSjYVBtf0FIPWIakOAAAECBAgQIECAAAECBAgQIECAAIHOJSAAaWM94pcf8XireGF4fPr06ZPd89G9e/cNRo5HTMWvPvKeeGzV4MGDs5/OPvvscOWVV2b/jkdpvf/++5sVgMyaNSuMGzcuG2dzApBU566npAKQepS0IUCAAAECBAgQIECAAAECBAgQIECAQLoCApA21O6rr77KjquKx0vFZ++9986+Atlpp502a9SmrzAOPvjgLESJzymnnBLefffd9e4UyRt83SOw4t0f22+/fZgzZ0523FZ8YhgSw5mWnqYjsOK9HxMmTEh67nrwHYFVj5I2BAgQIECAAAECBAgQIECAAAECBAgQSFdAALKZtYv3ZcSjreIF5fH51re+Fe65557s7o3NfU4//fTwL//yL2GPPfYIzz33XDbMyJEjw8KFC8ORRx6ZXabe0jNlypTs0vUuXbpkl6DHy9Zjv9g/PtOmTQuHHHJIbvd1L0G/+OKLs/dKee7N9V+3n0vQ20PRGAQIECBAgAABAgQIECBAgAABAgQIEOg4AQHIZtj/7ne/C+eff352NFV8jjrqqHDbbbflHnu17vDxuKx4x0dLz6BBg8LixYvD/vvvH+L9HfGZOHFieOSRR9YLRfL6x/s/4j0gu+++e5g3b17WJF7kHdcWn3h/SLxHJO+Jd3/Er0/iE+8yaTqKK9W5N6OkG3QRgLSHojEIECBAgAABAgQIECBAgAABAgQIECDQcQICkFba//a3vw1nnnlmWLFiRdZz6NCh4eqrrw5du3bNHelf//VfwyWXXJK1nzRpUoghR97zxz/+MRx66KHhD3/4Q/je974XfvrTn2bN4qXp11xzTfZlR/yio/YC9aaxmsKTAQMGhKlTpzZP0XS01TnnnNN8IXrt/HPnzg2jR4/O/hyDlxjApD53K8u6QXMBSFsF9SdAgAABAgQIECBAgAABAgQIECBAgEDHCghAWuG/bNmyMGzYsPDxxx9nvWKw8YMf/GCjI/zv//5v+Iu/+IsQv/747ne/m30pkve88MILzUdP3XDDDc1BSZzz2GOPzbrcfPPNYeDAgRt0X758eejfv3+IR1nFkCWusekZP358mDFjRthrr73CM888k/sFStPXI/Hukpdffrm5Tcpzt6KsuU0FIG0V1J8AAQIECBAgQIAAAQIECBAgQIAAAQIdKyAAqdN/9erVId7REe/XiM+VV14Zzj777Lp6n3vuueGVV17JgoUHHnggHHbYYev1i4HK97///fD73/8+7LrrruH5558P3/zmN5vbDB8+PLz55pvZMViPPfZY2HbbbZt/i8HK2LFjw+zZs7OLz+PXHN26dWv+/bXXXmteZzzSasSIEevN/c4772RfscT3GzduXHa017pPqnPXVZiNNBKAtFVQfwIECBAgQIAAAQIECBAgQIAAAQIECHSsgACkTv+mo6hi83hE1XXXXbfJnt27d8/a/OY3v8lChlWrVmXhxF//9V+HY445Jrsz5PXXXw+33nprFn7EY7Tuvvvu7IuRdZ9FixZl/eMXHn369MmOsjrggANC/PLjzjvvDPHrkfjkBRzx7/F4qxiMxGO0YsAxZMiQsPXWW4f58+eHyZMnh3ihe69evbIvRWqP2Ep57k0WaCMNBCBt0dOXAAECBAgQIECAAAECBAgQIECAAAECHS8gAKmzBscdd1yIl5+35lmyZElz8xg2XHbZZeHzzz/PHSIGI/EC8hiu5D2PP/54mDBhQlizZk3u76NGjQpXXHFF7m8rV64M8SuUGGbkPT169AjTpk0LvXv3rtTcralVbVsBSFv09CVAgAABAgQIECBAgAABAgQIECBAgEDHCwhA6qhBvMD8iCOOqKPl+k3WDUDiLx9++GG4//77s3s2Pvjgg6zxbrvtFvr16xfOOuussPvuu290jjjevffeGxYsWBA++eST7GuSvn37hnhMVdM9IS0NEI+4mj59epg1a1ZYunRp+Oqrr0LPnj2zL1HiVyE77rhjJeduddH+r4MAZHPl9CNAgAABAgQIECBAgAABAgQIECBAgEDnEBCAdI46WEUnExCAdLKCWA4BAgQIECBAgAABAgQIECBAgAABAgRaKSAAaSWY5o0hIABpjDp7SwIECBAgQIAAAQIECBAgQIAAAQIEqisgAKlubb1ZGwQEIG3A05UAAQIECBAgQIAAAQIECBAgQIAAAQKdQEAA0gmKYAmdT0AA0vlqYkUECBAgQIAAAQIECBAgQIAAAQIECBBojYAApDVa2jaMgACkYUrtRQkQIECAAAECBAgQIECAAAECBAgQqKiAAKSihfVabRMQgLTNT28CBAgQIECAAAECBAgQIECAAAECBAh0tIAApKMrYP5OKSAA6ZRlsSgCBAgQIECAAAECBAgQIECAAAECBAjULSAAqZtKw0YSEIA0UrW9KwECBAgQIECAAAECBAgQIECAAAECVRQQgFSxqt6pzQICkDYTGoAAAQIECBAgQIAAAQIECBAgQIAAAQIdKiAA6VB+k3dWAQFIZ62MdREgQIAAAQIECBAgQIAAAQIECBAgQKA+AQFIfU5aNZiAAKTBCu51CRAgQIAAAQIECBAgQIAAAQIECBConIAApHIl9ULtISAAaQ9FYxAgQIAAAQIECBAgQIAAAQIECBAgQKDjBAQgHWdv5k4sIADpxMWxNAIECBAgQIAAAQIECBAgQIAAAQIECNQhIACpA0mTxhMQgDRezb0xAQIECBAgQIAAAQIECBAgQIAAAQLVEhCAVKue3qadBAQg7QRpGAIECBAgQIAAAQIECBAgQIAAAQIECHSQgACkg+BN27kFBCCduz5WR4AAAQIECBAgQIAAAQIECBAgQIAAgU0JCEA2JeT3hhQQgDRk2b00AQIECBAgQIAAAQIECBAgQIAAAQIVEhCAVKiYXqX9BAQg7WdpJAIECBAgQIAAAQIECBAgQIAAAQIECHSEgACkI9TN2ekFBCCdvkQWSIAAAQIECBAgQIAAAQIECBAgQIAAgY0KCEBsEAI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECALVV1aAAAIABJREFUAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEDsCQI5AgIQ24IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0q6f1RckIAApCNawBAgQIECAAAECBAgQIECAAAECBAgQKElAAFIStGnSEhCApFUvqyVAgAABAgQIECBAgAABAgQIECBAgECtgADEniCQIyAAsS0IECBAgAABAgQIECBAgAABAgQIECCQtoAAJO36WX1BAgKQgmANS4AAAQIECBAgQIAAAQIECBAgQIAAgZIEBCAlQZsmLQEBSFr1sloCBAgQIECAAAECBAgQIECAAAECBAjUCghA7AkCOQICENuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNKun9UXJCAAKQjWsAQIECBAgAABAgQIECBAgAABAgQIEChJQABSErRp0hIQgKRVL6slQIAAAQIECBAgQIAAAQIECBAgQIBArYAAxJ4gkCMgALEtCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt+ll9QQICkIJgDUuAAAECBAgQIECAAAECBAgQIECAAIGSBAQgJUGbJi0BAUha9bJaAgQIECBAgAABAgQIECBAgAABAgQI1AoIQOwJAjkCAhDbggABAgQIECBAgAABAgQIECBAgAABAmkLCEDSrp/VFyQgACkI1rAECBAgQIAAAQIECBAgQIAAAQIECBAoSUAAUhK0adISEICkVS+rJUCAAAECBAgQIECAAAECBAgQIECAQK2AAMSeIJAjIACxLQgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7fpZfUECApCCYA1LgAABAgQIECBAgAABAgQIECBAgACBkgQEICVBmyYtAQFIWvWyWgIECBAgQIAAAQIECBAgQIAAAQIECNQKCEA2Y0/Mnz8//OpXvwpvvfVWWLFiRdhqq61C7969w9FHHx3OPPPMsMMOO+SOunr16jB9+vQwc+bMsHTp0rB27drQs2fPcOyxx4ZRo0aF7bbbbqOrWbJkSbjnnnvCggULsnlj+759+4bhw4eHfv36bbRvo869GeXNughANldOPwIECBAgQIAAAQIECBAgQIAAAQIECHQOAQFIK+qwZs2acMUVV4RZs2a12GvHHXcMU6ZMCQcffPB6bVatWhXOO++8sHDhwty+O++8c7j33ntDnz59cn9/8cUXwyWXXBJikJH3jBw5Mlx11VW5vzXq3K0o7QZNBSBt0dOXAAECBAgQIECAAAECBAgQIECAAAECHS8gAGlFDX7yk5+En/3sZ1mPAQMGZIHGnnvuGT7++OMQvwqZOnVq+OKLL7IvM+JXHrvsskvz6Jdddll4+umnw5ZbbhnGjBkTBg4cmH05EvtNnjw5rFy5Mvsa5KmnngrdunVbb1XvvPNOGDZsWPjyyy/DgQceGMaPHx/22Wef8MEHH4S77rorzJkzJ2s/ceLEMGLEiA3eqFHnbkVpBSBtwdKXAAECBAgQIECAAAECBAgQIECAAAECnVBAAFJnUT788MPQv3//EL8COfnkk8NNN920Qc9FixaF008/PWsTg4gYSMQn/n3IkCHZvydNmpSFGes+MeAYOnRo9nXHpZdeGi688ML1fr/gggvCSy+9lB2z9cQTT4Tu3bs3/x6P0Ro7dmyYPXt2FrzEL0W22Wab5t8bde46y9piM1+AtFVQfwIECBAgQIAAAQIECBAgQIAAAQIECHSsgACkTv9f/OIX4cc//nHWeu7cudnXGnlPPKYqhhHx99guPk1fYPTq1Ss8//zzoUuXLht0jcdXPfrooyG2iSFG0xPvCjnxxBOz/7z++uvD4MGDN+i7fPnyLJz5+uuvw4033hhOPfXU5jaNOnedZW2xmQCkrYL6EyBAgAABAgQIECBAgAABAgQIECBAoGMFBCB1+t96663h/vvvz76u+PWvf91ir1tuuSXcfffd2VFXb7/9dnbR+WGHHRY+++yzsLF7OubNm9f85ceMGTPCfvvtl80R57zhhhvCFltsEV599dUWL1gfNGhQWLx4cXaheryDJD6NOnedJd1oMwFIeygagwABAgQIECBAgAABAgQIECBAgAABAh0nIABppf3nn3++3hFTtd2bvgDp0aNHFpQsW7YsCyXiU/t1xrp94xFb/fr1y/503XXXNR+Zdfnll4cnn3xyvS9K8pbc9AXJbrvtlh2XFZ9GnbuVJc1tLgBpD0VjECBAgAABAgQIECBAgAABAgQIECBAoOMEBCDtaB9DjOOOOy6sWrUqnHDCCeH2228Pr7/+ejjrrLOyWR566KFw6KGH5s4Yj6866KCDsntARo8end3rEZ8zzjgjvPHGG+Hwww8PDzzwQIurjRew33bbbdmXIvHLk65duzbs3O1RUgFIeygagwABAgQIECBAgAABAgQIECBAgAABAh0nIABpJ/t43FS8vLzp64uf//zn4Tvf+U549tlnm8OMmTNnhn333bfFGWPI8emnn653gfpJJ50U3nvvvXD88ceHO+64o8W+Dz74YLj22muz31977bXsqKxGnbueksaAY2PPRx99FE477bSsyfz588Ouu+5az7DaECBAgAABAgQIECBAgAABAgQIECBAgEAnERCAtFMh4gXlMfSIz8CBA8PNN9+c/TseXxWPsYpPvAC9d+/eLc4Yj8CKX5EMGTIkOwYrPvH4rHiU1cknnxxuuummFvvGC9TjMVjxafo/7Bt17npKurEgqra/AKQeUW0IECBAgAABAgQIECBAgAABAgQIECDQuQQEIG2sR/zyI97tES8rj0+fPn3Cww8/HLp3757996xZs8K4ceOyf29OABKP0nr//fc3KwBp1LnrKakApB4lbQgQIECAAAECBAgQIECAAAECBAgQIJCugACkDbX76quvwo9+9KMQj7aKz9577519BbLTTjs1jzpnzpxw0UUXNYchMSBp6Wk6Aive+zFhwoSs2SmnnBLefffd5jtFWuq77hFY8d6R7bffPjTq3PWU1BFY9ShpQ4AAAQIECBAgQIAAAQIECBAgQIAAgXQFBCCbWbt4V8eYMWOyC8rj861vfSvcc8892d0b6z4LFy4MI0eOzP40bdq0cMghh+TOuO4l6BdffHE2dnxi3zjGkUceGe67774WVztlypTs0vUuXbpkl6B/4xvfyPo14tybWdL1urkEvT0UjUGAAAECBAgQIECAAAECBAgQIECAAIGOExCAbIb97373u3D++ednR1PF56ijjgq33XZb87FX6w4ZL9OOv8cn3uER7/LIe+LdH/EOkPjE+0QGDx6c/XvixInhkUceCXvssUd47rnnWlxtvP8j3gOy++67h3nz5mXtGnXuzSjpBl0EIO2haAwCBAgQIECAAAECBAgQIECAAAECBAh0nIAApJX2v/3tb8OZZ54ZVqxYkfUcOnRouPrqq0PXrl1bHKnpaKtzzjmn+UL02sZz584No0ePzv4cLy/ff//9s38/9NBD4Zprrsm+7IhfdGyzzTa58wwaNCgsXrw4DBgwIEydOrW5TaPO3cqybtBcANJWQf0JECBAgAABAgQIECBAgAABAgQIECDQsQICkFb4L1u2LAwbNix8/PHHWa9LLrkk/OAHP9jkCOPHjw8zZswIe+21V3jmmWfCFltssUGfpi844v0hL7/8cnObOOexxx6btb/55pvDwIEDN+i7fPny0L9//xCP0Zo0aVK2xqanUefeZFE20UAA0lZB/QkQIECAAAECBAgQIECAAAECBAgQINCxAgKQOv1Xr14dTj/99Ox+jfhceeWV4eyzz66r92uvvdbcNh5pNWLEiPX6vfPOO9mXJHGOcePGZcdrrfsMHz48vPnmm9kxWI899ljYdtttm39eu3ZtGDt2bJg9e3Z28Xn8kqRbt27Nvzfq3HUVZiONBCBtFdSfAAECBAgQIECAAAECBAgQIECAAAECHSsgAKnTv+koqtj8e9/7Xrjuuus22bN79+7NbeLxVjGciEdZxYBjyJAhYeuttw7z588PkydPDvFS9V69emVfitQec7Vo0aIsIIlfePTp0yc7RuuAAw4I8cuPO++8M7zwwgvZPHnhSvx7o869yQIJQNpCpC8BAgQIECBAgAABAgQIECBAgAABAgQ6tYAApM7yHHfccSFeft6aZ8mSJc3NV65cGc4999wQw4y8p0ePHmHatGmhd+/eub8//vjjYcKECWHNmjW5v48aNSpcccUVub816tytqVVtW1+AtEVPXwIECBAgQIAAAQIECBAgQIAAAQIECHS8gACkjhrEC8+POOKIOlqu32TdACT+Eo+4mj59epg1a1ZYunRp+Oqrr0LPnj3DMccck30VsuOOO250jjjevffeGxYsWBA++eST7Kirvn37hnhEVtM9IS0N0Khzt7po/9dBALK5cvoRIECAAAECBAgQIECAAAECBAgQIECgcwgIQDpHHayikwkIQDpZQSyHAAECBAgQIECAAAECBAgQIECAAAECrRQQgLQSTPPGEBCANEadvSUBAgQIECBAgAABAgQIECBAgAABAtUVEIBUt7berA0CApA24OlKgAABAgQIECBAgAABAgQIECBAgACBTiAgAOkERbCEzicgAOl8NbEiAgQIECBAgAABAgQIECBAgAABAgQItEZAANIaLW0bRkAA0jCl9qIECBAgQIAAAQIECBAgQIAAAQIECFRUQABS0cJ6rbYJCEDa5qc3AQIECBAgQIAAAQIECBAgQIAAAQIEOlpAANLRFTB/pxQQgHTKslgUAQIECBAgQIAAAQIECBAgQIAAAQIE6hYQgNRNpWEjCQhAGqna3pUAAQIECBAgQIAAAQIECBAgQIAAgSoKCECqWFXv1GYBAUibCQ1AgAABAgQIECBAgAABAgQIECBAgACBDhUQgHQov8k7q4AApLNWxroIECBAgAABAgQIECBAgAABAgQIECBQn4AApD4nrRpMQADSYAX3ugQIECBAgAABAgQIECBAgAABAgQIVE5AAFK5knqh9hAQgLSHojEIECBAgAABAgQIECBAgAABAgQIECDQcQICkI6zN3MnFhCAdOLiWBoBAgQIECBAgAABAgQIECBAgAABAgTqEBCA1IGkSeMJCEAar+bemAABAgQIECBAgAABAgQIECBAgACBagkIQKpVT2/TTgICkHaCNAwBAgQIECBAgAABAgQIECBAgAABAgQ6SEAA0kHwpu3cAgKQzl0fqyNAgAABAgQIECBAgAABAgQIECBAgMCmBAQgmxLye0MKCEAasuxemgABAgQIECBAgAABAgQIECBAgACBCgkIQCpUTK/SfgICkPazNBIBAgQIECBAgAABAgQIECBAgAABAgQ6QkAA0hHq5uz0AgKQTl8iCyRAgAABAgQIECBAgAABAgQIECBAgMBGBQQgNgiBHAEBiG1BgAABAgQIECBAgAABAgQIECBAgACBtAUEIGnXz+oLEhCAFARrWAIECBAgQIAAAQIECBAgQIAAAQIECJQkIAApCdo0aQkIQNKql9USIECAAAECBAgQIECAAAECBAgQIECgVkAAYk8QyBEQgNgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/ay+IAEBSEGwhiVAgAABAgQIECBAgAABAgQIECBAgEBJAgKQkqBNk5aAACStelktAQIECBAgQIAAAQIECBAgQIAAAQIEagUEIPYEgRwBAYhtQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp18/qCxIQgBQEa1gCBAgQIECAAAECBAgQIECAAAECBAiUJCAAKQnaNGkJCEDSqpfVEiBAgAABAgQIECBAgAABAgQIECBAoFZAAGJPEMgREIDYFgQIECBAgAABAgQIECBAgAABAgQIEEhbQACSdv2sviABAUhBsIYlQIAAAQIECBAgQIAAAQIECBAgQIBASQICkJKgTZOWgAAkrXpZLQECBAgQIECAAAECBAgQIECAAAECBGoFBCD2BIEcAQGIbUGAAAECBAgQIECAAAECBAgQIECAAIG0BQQgadfP6gsSEIAUBGtYAgQIECBAgAABAgQIECBAgAABAgQIlCQgACkJ2jRpCQhA0qqX1RIgQIAAAQIECBAgQIAAAQIECBAgQKBWQABiTxDIERCA2BYECBAgQIAAAQIECBAgQIAAAQIECBBIW0AAknb9rL4gAQFIQbCGJUCAAAECBAgQIECAAAECBAgQIECAQEkCApCSoE2TloAAJK16WS0BAgQIECBAgAABAgQIECBAgAABAgRqBQQg9gSBHAEBiG1BgAABAgQIECBAgAABAgQIECBAgACBtAUEIGnXz+oLEhCAFARrWAIECBAgQIAAAQIECBAgQIAAAQIECJQkIAApCdo0aQkIQNKql9USIECAAAECBAgQIECAAAECBAgQIECgVkAAYk8QyBEQgNgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/ay+IAEBSEGwhiVAgAABAgQIECBAgAABAgQIECBAgEBJAgKQkqBNk5aAACStelktAQIECBAgQIAAAQIECBAgQIAAAQIEagUEIPYEgRwBAYhtQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp18/qCxIQgBQEa1gCBAgQIECAAAECBAgQIECAAAECBAiUJCAAKQnaNGkJCEDSqpfVEiBAgAABAgQIECBAgAABAgQIECBAoFZAAGJPEMgREIDYFgQIECBAgAABAgQIECBAgAABAgQIEEhbQACSdv2sviABAUhBsIYlQIAAAQIECBAgQIAAAQIECBAgQIBASQICkJKgTZOWgAAkrXpZLQECBAgQIECAAAECBAgQIECAAAECBGoFBCD2BIEcAQGIbUGAAAECBAgQIECAAAECBAgQIECAAIG0BQQgadfP6gsSEIAUBGtYAgQIECBAgAABAgQIECBAgAABAgQIlCQgACkJ2jRpCQhA0qqX1RIgQIAAAQIECBAgQIAAAQIECBAgQKBWQABiTxDIERCA2BYECBAgQIAAAQIECBAgQIAAAQIECBBIW0AAknb9rL4gAQFIQbCGJUCAAAECBAgQIECAAAECBAgQIECAQEkCApCSoE2TloAAJK16WS0BAgQIECBAgAABAgQIECBAgAABAgRqBQQg9gSBHAEBiG1BgAABAgQIECBAgAABAgQIECBAgACBtAUEIGnXz+oLEhCAFARrWAIECBAgQIAAAQIECBAgQIAAAQIECJQkIAApCdo0aQkIQNKql9USIECAAAECBAgQIECAAAECBAgQIECgVkAAYk8QyBEQgNgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/ay+IAEBSEGwhiVAgAABAgQIECBAgAABAgQIECBAgEBJAgKQkqBNk5aAACStelktAQIECBAgQIAAAQIECBAgQIAAAQIEagUEIPYEgRwBAYhtQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp18/qCxIQgBQEa1gCBAgQIECAAAECBAgQIECAAAECBAiUJCAAKQnaNGkJCEDSqpfVEiBAgAABAgQIECBAgAABAgQIECBAoFZAAGJPEMgREIDYFgQIECBAgAABAgQIECBAgAABAgQIEEhbQACSdv2sviABAUhBsIYlQIAAAQIECBAgQIAAAQIECBAgQIBASQICkJKgTZOWgAAkrXpZLQECBAgQIECAAAECBAgQIECAAAECBGoFBCD2BIEcAQGIbUGAAAECBAgQIECAAAECBAgQIECAAIG0BQQgadfP6gsSEIAUBGtYAgQIECBAgAABAgQIECBAgAABAgQIlCQgACkJ2jRpCQhA0qqX1RIgQIAAAQIECBAgQIAAAQIECBAgQKBWQABiTxDIERCA2BYECBAgQIAAAQIECBAgQIAAAQIECBBIW0AAknb9rL4gAQFIQbCGJUCAAAECBAgQ+H/s3Q2wFeV9P/AHMNb68o/vRbGDSSq+BJ12jDpxGjJBoo0vqQLaAFI1JlVHjcRYNFOhdiToRJ1WDWgbrVaM1mp8f0FFlJqIYE3bUTBkpLGDHUZTHbC2RbHyn2c79xYOe7l77jm7Z59zPmemU/XsPs9vP7/nnnvPfrO7BAgQIECAAAECBAgQqEhAAFIRtGnSEhCApNUv1RIgQIAAAQIECBAgQIAAAQIECBAgQKBRQABiTRDIERCAWBYECBAgQIAAAQIECBAgQIAAAQIECBBIW0AAknb/VF+SgACkJFjDEiBAgAABAgQIECBAgAABAgQIECBAoCIBAUhF0KZJS0AAkla/VEuAAAECBAgQIECAAAECBAgQIECAAIFGAQGINUEgR0AAYlkQIECAAAECBAgQIECAAAECBAgQIEAgbQEBSNr9U31JAgKQkmANS4AAAQIECBAgQIAAAQIECBAgQIAAgYoEBCAVQZsmLQEBSFr9Ui0BAgQIECBAgAABAgQIECBAgAABAgQaBQQg1gSBHAEBiGVBgAABAgQIECBAgAABAgQIECBAgACBtAUEIGn3T/UlCQhASoI1LAECBAgQIECAAAECBAgQIECAAAECBCoSEIBUBG2atAQEIGn1S7UECBAgQIAAAQIECBAgQIAAAQIECBBoFBCAWBMEcgQEIJYFAQIECBAgQIAAAQIECBAgQIAAAQIE0hYQgKTdP9WXJCAAKQnWsAQIECBAgAABAgQIECBAgAABAgQIEKhIQABSEbRp0hIQgKTVL9USIECAAAECBAgQIECAAAECBAgQIECgUUAAYk0QyBEQgFgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/1RfkoAApCRYwxIgQIAAAQIECBAgQIAAAQIECBAgQKAiAQFIRdCmSUtAAJJWv1RLgAABAgQIECBAgAABAgQIECBAgACBRgEBiDVBIEdAAGJZECBAgAABAgQIECBAgAABAgQIECBAIG0BAUja/VN9SQICkJJgDUuAAAECBAgQIECAAAECBAgQIECAAIGKBAQgFUGbJi0BAUha/VItAQIECBAgQIAAAQIECBAgQIAAAQIEGgUEINYEgRwBAYhlQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp90/1JQkIQEqCNSwBAgQIECBAgAABAgQIECBAgAABAgQqEhCAVARtmrQEBCBp9Uu1BAgQIECAAAECBAgQIECAAAECBAgQaBQQgFgTBHIEBCCWBQECBAgQIECAAAECBAgQIECAAAECBNIWEICk3T/VlyQgACkJ1rAECBAgQIAAAQIECBAgQIAAAQIECBCoSEAAUhG0adISEICk1S/VEiBAgAABAgQIECBAgAABAgQIECBAoFFAAGJNEMgREIBYFgQIECBAgAABAgQIECBAgAABAgQIEEhbQACSdv9UX5KAAKQkWMMSIECAAAECBAgQIECAAAECBAgQIECgIgEBSEXQpklLQACSVr9US4AAAQIECBAgQIAAAQIECBAgQIAAgUYBAYg1QSBHQABiWRAgQIAAAQIECBAgQIAAAQIECBAgQCBtAQFI2v1TfUkCApCSYA1LgAABAgQIECBAgAABAgQIECBAgACBigQEIBVBmyYtAQFIWv1SLQECBAgQIECAAAECBAgQIECAAAECBBoFBCDWBIEcAQGIZUGAAAECBAgQIECAAAECBAgQIECAAIG0BQQgafdP9SUJCEBKgjUsAQIECBAgQIAAAQIECBAgQIAAAQIEKhIQgFQEbZq0BAQgafVLtQQIECBAgAABAgQIECBAgAABAgQIEGgUEIBYEwRyBAQglgUBAgQIECBAgAABAgQIECBAgAABAgTSFhCApN0/1ZckIAApCdawBAgQIECAAAECBAgQIECAAAECBAgQqEhAANIi9Jw5c8KCBQvCVVddFSZOnDjgaOvWrQtHHXXUoLPtuuuuYdmyZbnbrVq1Ktxyyy3Z+++++26I244dOzZMnTo1jBs3bptjb9y4Mdx9993h4YcfDqtXrw6bNm0Ko0aNChMmTAhnnXVWNta2XqnOPSj4ABsIQIYqZz8CBAgQIECAAAECBAgQIECAAAECBAjUQ0AA0kIfFi1aFC688MLw8ccfDxqAvPDCC1nQMNhroADkmWeeCRdddFGIQUbea/r06eHyyy/Pfe+DDz4I3/jGN8Ly5ctz3997773DrbfeGsaMGZP7fqpzD2a9rfcFIK3o2ZcAAQIECBAgQIAAAQIECBAgQIAAAQKdFxCADLEHixcvDt/61rf6A4nBrgD54Q9/GK699towcuTI8Pjjjw8467Bhw8KOO+64xfsrV64MU6ZMCRs2bAiHHnpomDlzZjjggAPCm2++GW6++eYQg5j4mj17dpg2bdpWY1988cXhscceC5/4xCfCBRdcEE488cSw/fbbhyVLloRrrrkmrF+/Prsa5NFHH+2quYfY2mw3AUgrevYlQIAAAQIECBAgQIAAAQIECBAgQIBA5wUEIE32IF7t8YMf/CDcdNNN2ZUffa/BApAZM2aEJ554Ihx77LHhxhtvbGrWc845Jzz33HNh9OjR4YEHHgg77bRT//7xVlZx7IULF2a3sYpXa+y8887977/yyith8uTJ2b9fccUVWZCy+SuGK6eddloW5Hz7298O55577hbvpzp3U8A5GwtAWhVjvvfhAAAgAElEQVS0PwECBAgQIECAAAECBAgQIECAAAECBDorIABpwv/5558P3//+98MvfvGLbK/PfvazYcWKFdk/DxaAxODjX//1X8N3vvOd8Ed/9EeFZ43P6zj++OOz7efOnRsmTZq01b5r164N48ePzwKZq6++Opxyyin92/Rd/bHffvuFp556KowYMWKr/eOts+69994Qt4kBSt8r5bkLAw+woQCkVUH7EyBAgAABAgQIECBAgAABAgQIECBAoLMCApAm/A888MBs63grqXilxFe/+tXw5S9/Oftv2wpA3n///fC5z30ue/D47bffHj7/+c8XnjVuH8eOt8aKzxHZfffdc/eND2CPYUx8qPm8efOybeJ8Rx55ZHjvvffCtp4R8uyzz/Zf+fHQQw+Fgw46KNs/1bkL425jQwFIOxSNQYAAAQIECBAgQIAAAQIECBAgQIAAgc4JCECasI/BQAw84i2nPvOZz2TP4DjmmGOyEbYVgCxbtiz84R/+YRZi/O3f/m24//77w09+8pPw9ttvZ7erOuyww7Jnd3zxi1/cqppLL700PPjgg9kzOuJzRwZ69V3Fsc8++2S3y4qvNWvWZIFIfDVeGbL5OG+99VYYN25c9p++973v9d8yK9W5m2jpgJsKQNqhaAwCBAgQIECAAAECBAgQIECAAAECBAh0TkAA0oT9L3/5y/CpT32qf4+iAchtt92WBRDDhw/P/u+jjz7KnTVexXHllVeG7bbbrv/9008/Pbz00kvhqKOOCnfccceA1c6fPz9cf/31Wcjy6quvZmO8+OKL4Ywzzsj2ufPOO8MRRxyRu3+8dVYMYeJzQM4777ws4ImvVOduoqUDbioAaYeiMQgQIECAAAECBAgQIECAAAECBAgQINA5AQFIC/ZFA5D43I9HH300myk+yPz888/Pbk0Vb6X1T//0T9lD0X/+859n78crRf7kT/6kv6oTTjghvP7664M+PH3BggVhzpw52X5Lly7NbpUVH7reF2Y8/PDDoe8WXnmHHAOWdevWZVeizJ49O9sk1bmLtDQGHNt6xatzTj311GyTJUuWhJEjRxYZ1jYECBAgQIAAAQIECBAgQIAAAQIECBAgUBMBAUgLjSgagFxwwQXhpz/9aRZ+xCsx4m2vNn9t2LAhu1IjhiHxCo74HI6+sCLewireyuqkk04K11577YDVxoeYx9tgbX7CPt46K97GKr7iA9Dj/AO94i2w4q2wJk+enN0GK75SnbtIS7cVBjXuLwApImobAgQIECBAgAABAgQIECBAgAABAgQI1EtAANJCP4oGIH1TxFtMxas+8l7xtlWTJk3K3jrzzDPDd7/73eyfjzvuuPDGG28MKQB55JFHwiWXXJKNM5QAJNW5i7RUAFJEyTYECBAgQIAAAQIECBAgQIAAAQIECBBIV0AA0kLvmg1ABpuq7yqM3/md38kelh5fJ598cnjttdeyIOSGG24YcIjNb4EVn/2x2267hUWLFmW324qvGIaMGTNmwP37boEVn/sxa9aspOcezDm+7xZYRZRsQ4AAAQIECBAgQIAAAQIECBAgQIAAgXQFBCAt9K7dAcjXvva18I//+I9h//33D08++WRW2fTp08Py5cvD0UcfHeLD1Ad6zZs3LwtIRowYkT0EPT5sPe4X94+vu+66Kxx++OG5u2/+EPQLL7wwxFt2pTx3Cy3t39VD0NuhaAwCBAgQIECAAAECBAgQIECAAAECBAh0TkAA0oJ9swHIpk2bsmd8DPSaOHFiWLFiRTj44INDfH5HfMUHkt9zzz1bhCJ5+8fnf8TngOy7777h2WefzTaJD/L+whe+kP1zfH5IfI5I3is++yNefRJfc+fO7b8VV6pzt9DS/l0FIO1QNAYBAgQIECBAgAABAgQIECBAgAABAgQ6JyAAacG+SADyz//8z+Giiy4K7777brjiiitCDDnyXv/zP/8TjjjiiPCf//mf4Stf+Ur4i7/4i2yz+ND0K6+8MruyI17R0fgA9b6x+sKTY445JsyfP79/ir5bW33961/vfyB64/yLFy8O5513XvafY/ASA5jU526hrdmuApBWBe1PgAABAgQIECBAgAABAgQIECBAgACBzgoIQFrwLxKA/Pu//3v43d/93RCv/vi93/u9cP311+fO+PTTT/ffeuqqq67qD0rWrFkTJkyYkO1z3XXXhRNPPHGr/deuXRvGjx8f4q2sYsgyZcqU/m1mzpwZHnroofDpT386PP7447lXoPRdPbLXXnuF559/vn+blOduoa0CkFbx7E+AAAECBAgQIECAAAECBAgQIECAAIEaCAhAWmhCkQAkDn/22WeHn/zkJ1mwcMcdd4Qjjzxyi1l/9atfhT/4gz8I//Zv/xZGjhwZnnrqqfBrv/Zr/dtMnTo1vPzyy9ltsO67776wyy679L8Xg5UZM2aEhQsXZg8+j1dz7Ljjjv3vL126NJx55pnZv8dbWk2bNm2LuVeuXBlOO+20sHHjxnDJJZeEb37zm1u8n+rcLbQ129UVIK0K2p8AAQIECBAgQIAAAQIECBAgQIAAAQKdFRCAtOBfNAD5+c9/noUMH3zwQRZOfOtb3wpf+tKXwk477RRefPHF8Od//udZ+LHddtuFv/zLv8yuGNn89corr2T7xys8xowZk93K6pBDDgnxyo+bbropxKtHBgo44n+Pt7eKwUi8jVYMOCZPnhx22GGHsGTJknDNNdeEdevWhf322y+7UqTxFlspz91CawUgreDZlwABAgQIECBAgAABAgQIECBAgAABAjUQEIC00ISiAUicIoYNF198cXj//fdzZ4zBSHwAeXz+R97r/vvvD7NmzQofffRR7vtnnXVWuOyyy3LfW79+fXYVSgwz8l577rlnuOuuu8Lo0aO7au4WWisAaQXPvgQIECBAgAABAgQIECBAgAABAgQIEKiBgACkhSY0E4DEad56661w++23Z8/ZiPvG1z777BPGjRsXzjjjjLDvvvtus5pVq1aFW2+9NSxbtiy888472dUkY8eODfE2VX3PCRlogHiLq7vvvjs88sgjYfXq1eHDDz8Mo0aNyq5EiVeF7LHHHl0591Db6xZYQ5WzHwECBAgQIECAAAECBAgQIECAAAECBOohIACpRx9UUTMBAUjNGqIcAgQIECBAgAABAgQIECBAgAABAgQINCkgAGkSzOa9ISAA6Y0+O0oCBAgQIECAAAECBAgQIECAAAECBLpXQADSvb11ZC0ICEBawLMrAQIECBAgQIAAAQIECBAgQIAAAQIEaiAgAKlBE5RQPwEBSP16oiICBAgQIECAAAECBAgQIECAAAECBAg0IyAAaUbLtj0jIADpmVY7UAIECBAgQIAAAQIECBAgQIAAAQIEulRAANKljXVYrQkIQFrzszcBAgQIECBAgAABAgQIECBAgAABAgQ6LSAA6XQHzF9LAQFILduiKAIECBAgQIAAAQIECBAgQIAAAQIECBQWEIAUprJhLwkIQHqp246VAAECBAgQIECAAAECBAgQIECAAIFuFBCAdGNXHVPLAgKQlgkNQIAAAQIECBAgQIAAAQIECBAgQIAAgY4KCEA6ym/yugoIQOraGXURIECAAAECBAgQIECAAAECBAgQIECgmIAApJiTrXpMQADSYw13uAQIECBAgAABAgQIECBAgAABAgQIdJ2AAKTrWuqA2iEgAGmHojEIECBAgAABAgQIECBAgAABAgQIECDQOQEBSOfszVxjAQFIjZujNAIECBAgQIAAAQIECBAgQIAAAQIECBQQEIAUQLJJ7wkIQHqv546YAAECBAgQIECAAAECBAgQIECAAIHuEhCAdFc/HU2bBAQgbYI0DAECBAgQIECAAAECBAgQIECAAAECBDokIADpELxp6y0gAKl3f1RHgAABAgQIECBAgAABAgQIECBAgACBwQQEIIMJeb8nBQQgPdl2B02AAAECBAgQIECAAAECBAgQIECAQBcJCEC6qJkOpX0CApD2WRqJAAECBAgQIECAAAECBAgQIECAAAECnRAQgHRC3Zy1FxCA1L5FCiRAgAABAgQIECBAgAABAgQIECBAgMA2BQQgFgiBHAEBiGVBgAABAgQIECBAgAABAgQIECBAgACBtAUEIGn3T/UlCQhASoI1LAECBAgQIECAAAECBAgQIECAAAECBCoSEIBUBG2atAQEIGn1S7UECBAgQIAAAQIECBAgQIAAAQIECBBoFBCAWBMEcgQEIJYFAQIECBAgQIAAAQIECBAgQIAAAQIE0hYQgKTdP9WXJCAAKQnWsAQIECBAgAABAgQIECBAgAABAgQIEKhIQABSEbRp0hIQgKTVL9USIECAAAECBAgQIECAAAECBAgQIECgUUAAYk0QyBEQgFgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/1RfkoAApCRYwxIgQIAAAQIECBAgQIAAAQIECBAgQKAiAQFIRdCmSUtAAJJWv1RLgAABAgQIECBAgAABAgQIECBAgACBRgEBiDVBIEdAAGJZECBAgAABAgQIECBAgAABAgQIECBAIG0BAUja/VN9SQICkJJgDUuAAAECBAgQIECAAAECBAgQIECAAIGKBAQgFUGbJi0BAUha/VItAQIECBAgQIAAAQIECBAgQIAAAQIEGgUEINYEgRwBAYhlQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp90/1JQkIQEqCNSwBAgQIECBAgAABAgQIECBAgAABAgQqEhCAVARtmrQEBCBp9Uu1BAgQIECAAAECBAgQIECAAAECBAgQaBQQgFgTBHIEBCCWBQECBAgQIECAAAECBAgQIECAAAECBNIWEICk3T/VlyQgACkJ1rAECBAgQIAAAQIECBAgQIAAAQIECBCoSEAAUhG0adISEICk1S/VEiBAgAABAgQIECBAgAABAgQIECBAoFFAAGJNEMgREIBYFgQIECBAgAABAgQIECBAgAABAgQIEEhbQACSdv9UX5KAAKQkWMMSIECAAAECBAgQIECAAAECBAgQIECgIgEBSEXQpklLQACSVr9US4AAAQIECBAgQIAAAQIECBAgQIAAgUYBAYg1QSBHQABiWRAgQIAAAQIECBAgQIAAAQIECBAgQCBtAQFI2v1TfUkCApCSYA1LgAABAgQIECBAgAABAgQIECBAgACBigQEIBVBmyYtAQFIWv1SLQECBAgQIECAAAECBAgQIECAAAECBBoFBCDWBIEcAQGIZUGAAAECBAgQIECAAAECBAgQIECAAIG0BQQgafdP9SUJCEBKgjUsAQIECBAgQIAAAQIECBAgQIAAAQIEKhIQgFQEbZq0BAQgafVLtQQIECBAgAABAgQIECBAgAABAgQIEGgUEIBYEwRyBAQglgUBAgQIECBAgAABAgQIECBAgAABAgTSFhCApN0/1ZckIAApCdawBAgQIECAAAECBAgQIECAAAECBAgQqEhAAFIRtGnSEhCApNUv1RIgQIAAAQIECBAgQIAAAQIECBAgQKBRQABiTRDIERCAWBYECBAgQIAAAQIECBAgQIAAAQIECBBIW0AAknb/VF+SgACkJFjDEiBAgAABAgQIECBAgAABAgQIECBAoCIBAUhF0KZJS0AAkla/VEuAAAECBAgQIECAAAECBAgQIECAAIFGAQGINUEgR0AAYlkQIECAAAECBAgQIECAAAECBAgQIEAgbQEBSNr9U31JAgKQkmANS4AAAQIECBAgQIAAAQIECBAgQIAAgYoEBCAVQZsmLQEBSFr9Ui0BAgQIECBAgAABAgQIECBAgAABAgQaBQQg1gSBHAEBiGVBgAABAgQIECBAgAABAgQIECBAgACBtAUEIGn3T/UlCQhASoI1LAECBAgQIECAAAECBAgQIECAAAECBCoSEIBUBG2atAQEIGn1S7UECBAgQIAAAQIECBAgQIAAAQIECBBoFBCAWBMEcgQEIJYFAQIECBAgQIAAAQIECBAgQIAAAQIE0hYQgKTdP9WXJCAAKQnWsAQIECBAgAABAgQIECBAgAABAgQIEKhIQABSEbRp0hIQgKTVL9USIECAAAECBAgQIECAAAECBAgQIECgUUAAYk0QyBEQgFgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/1RfkoAApCRYwxIgQIAAAQIECBAgQIAAAQIECBAgQKAiAQFIRdCmSUtAAJJWv1RLgAABAgQIECBAgAABAgQIECBAgACBRgEBiDVBIEdAAGJZECBAgAABAgQIECBAgAABAgQIECBAIG0BAUja/VN9SQICkJJgDUuAAAECBAgQIECAAAECBAgQIECAAIGKBAQgFUGbJi0BAUha/VItAQIECBAgQIAAAQIECBAgQIAAAQIEGgUEINYEgRwBAYhlQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp90/1JQkIQEqCNSwBAgQIECBAgAABAgQIECBAgAABAgQqEhCAVARtmrQEBCBp9Uu1BAgQIECAAAECBAgQIECAAAECBAgQaBQQgFgTBHIEBCCWBQECBAgQIECAAAECBAgQIECAAAECBNIWEICk3T/VlyQgACkJ1rAECBAgQIAAAQIECBAgQIAAAQIECBCoSEAAUhG0adISEICk1S/VEiBAgAABAgQIECBAgAABAgQIECBAoFFAAGJNEMgREIBYFgQIECBAgAABAgQIECBAgAABAgQIEEhbQACSdv9UX5KAAKQkWMMSIECAAAECBAgQIECAAAECBAgQIECgIgEBSEXQpklLQACSVr9US4AAAQIECBAgQIAAAQIECBAgQIAAgUYBAYg1QSBHQABiWRAgQIAAAQIECBAgQIAAAQIECBAgQCBtAQFI2v1TfUkCApCSYA1LgAABAgQIECBAgAABAgQIECBAgACBigQEIBVBmyYtAQFIWv1SLQECBAgQIECAAAECBAgQIECAAAECBBoFBCDWBIEcAQGIZUGAAAECBAgQIECAAAECBAgQIECAAIG0BQQgafdP9SUJCEBKgjUsAQIECBAgQIAAAQIECBAgQIAAAQIEKhIQgFQEbZq0BAQgafVLtQQIECBAgAABAgQIECBAgAABAgQIEGgUEIBYEwRyBAQglgUBAgQIECBAgAABAgQIECBAgAABAgTSFhCApN0/1ZckIAApCdawBAgQIECAAAECBAgQIECAAAECBAgQqEhAAFIRtGnSEhCApNUv1RIgQIAAAQIECBAgQIAAAQIECBAgQKBRQABiTRDIERCAWBYECBAgQIAAAQIECBAgQIAAAQIECBBIW0AAknb/VF+SgACkJFjDEiBAgAABAgQIECBAgAABAgQIECBAoCIBAUhF0KZJS0AAkla/VEuAAAECBAgQIECAAAECBAgQIECAAIFGAQGINUEgR0AAYlkQIECAAAECBAgQIECAAAECBAgQIEAgbQEBSNr9U31JAgKQkmANS4AAAQIECBAgQIAAAQIECBAgQIAAgYoEBCAVQZsmLQEBSFr9Ui0BAgQIECBAgAABAgQIECBAgAABAgQaBQQg1gSBHAEBiGVBgAABAgQIECBAgAABAgQIECBAgACBtAUEIGn3T/UlCQhASoI1LAECBAgQIECAAAECBAgQIECAAAECBCoSEIBUBG2atAQEIGn1S7UECBAgQIAAAQIECBAgQIAAAQIECBBoFBCAWBMEcgQEIJYFAQIECBAgQIAAAQIECBAgQIAAAQIE0hYQgKTdP9WXJCAAKQnWsAQIECBAgAABAgQIECBAgAABAgQIEKhIQABSEbRp0hIQgKTVL9USIECAAAECBAgQIECAAAECBAgQIECgUUAAYk0QyBEQgFgWBAgQIECAAAECBAgQIECAAAECBAgQSFtAAJJ2/1RfkoAApCRYwxIgQIAAAQIECBAgQIAAAQIECBAgQKAiAQFIRdCmSUtAAJJWv1RLgAABAgQIECBAgAABAgQIECBAgACBRgEBiDVBIEdAAGJZECBAgAABAgQIECBAgAABAgQIECBAIG0BAUja/VN9SQICkJJgDUuAAAECBAgQIECAAAECBAgQIECAAIGKBAQgFUGbJi0BAUha/VItAQIECBAgQIAAAQIECBAgQIAAAQIEGgUEINYEgRwBAYhlQYAAAQIECBAgQIAAAQIECBAgQIAAgbQFBCBp90/1JQkIQEqCNSwBAgQIECBAgAABAgQIECBAgAABAgQqEhCAVARtmrQEBCBp9Uu1BAgQIECAAAECBAgQIECAAAECBAgQaBQQgFgTBHIEBCCWBQECBAgQIECAAAECBAgQIECAAAECBNIWEICk3T/VlyQgACkJ1rAECBAgQIAAAQIECBAgQIAAAQIECBCoSEAA0iL0nDlzwoIFC8JVV10VJk6cuM3RNm7cGO6+++7w8MMPh9WrV4dNmzaFUaNGhQkTJoSzzjor7Lrrrtvcf9WqVeGWW24Jy5YtC++++262/dixY8PUqVPDuHHjzN1iLzffXQDSRkxDESBAgAABAgQIECBAgAABAgQIECBAoAMCApAW0BctWhQuvPDC8PHHHw8agHzwwQfhG9/4Rli+fHnujHvvvXe49dZbw5gxY3Lff+aZZ8JFF10UYoiS95o+fXq4/PLLc9/r1blbaG0QgLSiZ18CBAgQIECAAAECBAgQIECAAAECBAh0XkAAMsQeLF68OHzrW9/qDyQGuwLk4osvDo899lj4xCc+ES644IJw4oknhu233z4sWbIkXHPNNWH9+vXZ1SCPPvpo2HHHHbeoauXKlWHKlClhw4YN4dBDDw0zZ84MBxxwQHjzzTfDzTffHGIQE1+zZ88O06ZN2+qIenXuIbY2200A0oqefQkQIECAAAECBAgQIECAAAECBAgQINB5AQFIkz2IV3v84Ac/CDfddFN25Uffa1sByCuvvBImT56cbXrFFVdkYcbmrxhwnHbaaVmY8u1vfzuce+65W7x/zjnnhOeeey6MHj06PPDAA2GnnXbqfz/eRmvGjBlh4cKF2S2x4pUiO++8c//7vTp3k23danMBSKuC9idAgAABAgQIECBAgAABAgQIECBAgEBnBQQgTfg///zz4fvf/374xS9+ke312c9+NqxYsSL7520FIH1XYOy3337hqaeeCiNGjNhq1nj7qnvvvTfEbWKI0feKzwo5/vjjs3+dO3dumDRp0lb7rl27NowfPz4LZK6++upwyimn9G/Tq3M30dbcTQUgrQranwABAgQIECBAgAABAgQIECBAgAABAp0VEIA04X/ggQdmW8fbWMWrNL761a+GL3/5y9l/GygAiVdoHHnkkeG9994L23pOx7PPPtt/5cdDDz0UDjrooGzc22+/PRt72LBh4YUXXgi77757bsXxAewxjIkPVJ83b162Ta/O3URLB9xUANIORWMQIECAAAECBAgQIECAAAECBAgQIECgcwICkCbsYygRA494y6nPfOYz2TM4jjnmmG0GIGvWrMlCifhqvDpj86nfeuutMG7cuOw/fe973+u/Zdall14aHnzwwez5IPG5IwO9+q4g2WeffbLbZcVXr87dREsH3FQA0g5FYxAgQIAAAQIECBAgQIAAAQIECBAgQKBzAgKQJux/+ctfhk996lP9exQJQF588cVwxhlnZPvceeed4YgjjsidMd6+6rDDDsueA3LeeedlIUt8nX766eGll14KRx11VLjjjjsGrHb+/Pnh+uuvz64UefXVV8N2220XenXuJloqAGkHljEIECBAgAABAgQIECBAgAABAgQIECBQQwEBSAtNKRKAPPHEE/1hxsMPPxz6bqOVN20MOdatWxemTZsWZs+enW1ywgknhNdffz0ce+yx4cYbbxyw2gULFoQ5c+Zk7y9dujS7VVavzl2kpfEKj2293n777XDqqadmmyxZsiSMHDmyyLC2IUCAAAECBAgQIECAAAECBAgQIECAAIGaCAhAWmhEkQAk3r4q3sYqvuID0EePHj3gjPEWWPFWWJMnT85ugxVf8fZZ8VZWJ510Urj22msH3Dc+QD3eBmvzE/a9OneRlm4riGrcXwBSRNQ2BAgQIECAAAECBAgQIECAAAECBAgQqJeAAKSFfhQJQB555JFwySWXZLMMJQA57rjjwhtvvDGkAKRX5y7SUgFIESXbECBAgAABAgQIECBAgAABAgQIECBAIF0BAUgLvSsSgCxatCicf/752SwxkBgzZsyAM/bdAis+92PWrFnZdieffHJ47bXXQgxCbrjhhgH33fwWWPHZH7vttlvo1bmLtNQtsIoo2YYAAQIECBAgQIAAAQIECBAgQIAAAQLpCghAWuhdkQBk+fLlYfr06dksd911Vzj88MNzZ9z8IegXXnhhuOCCC7Lt4r5xjKOPPjrcdtttA1Y7b968LCAZMWJE9hD04cOHZ/v14twttLR/1xiQfPGLX8z+3S2w2iFqDAIECBAgQIAAAQIECBAgQIAAAQIECFQrIABpwbtIABIfpv2FL3whmyU+wyM+yyPvFZ/9EZ8BEl9z584NkyZNyv45Pgz9nnvuCfvvv3948sknB6w2Pv8jPgdk3333Dc8++2y2Xa/O3UJL+3cVgLRD0RgECBAgQIAAAQIECBAgQIAAAQIECBDonIAApAX7IgFIHL7v1lZf//rX+x+I3jjt4sWLw3nnnZf95/jw8oMPPjj75zvvvDNceeWV2ZUd8YqOnXfeObfiiRMnhhUrVoRjjjkmzJ8/v3+bXp27hbZmuwpAWhW0PwECBAgQIECAAAECBAgQIECAAAECBDorIABpwb9oADJz5szw0EMPhU9/+tPh8ccfD8OGDdtq1r4rOPbaa6/w/PPP92+zZs2aMGHChGz76667Lpx44olb7bt27dowfvz4EG+jdcUVV4QpU6b0b9Orc7fQVgFIq3j2J0CAAAECBAgQIECAAAECBAgQIECAQA0EBL/nmW8AACAASURBVCAtNKFoALJ06dJw5plnZjPFW1pNmzZti1lXrlwZTjvttLBx48ZwySWXhG9+85tbvD916tTw8ssvZ7fBuu+++8Iuu+zS//6mTZvCjBkzwsKFC7MHn8crSXbcccf+93t17hbaKgBpFc/+BAgQIECAAAECBAgQIECAAAECBAgQqIGAAKSFJhQNQOIU8fZWMZyIt7KKAcfkyZPDDjvskD1g+5prrgnr1q0L++23X3alSONtrl555ZUsIIlXeIwZMya7jdYhhxwS4pUfN910U3j66acHDFd6ee4WWusWWK3g2ZcAAQIECBAgQIAAAQIECBAgQIAAAQI1EBCAtNCEZgKQ9evXh7PPPjvEMCPvteeee4a77rorjB49Ovf9+++/P8yaNSt89NFHue+fddZZ4bLLLst9r1fnbqG1ApBW8OxLgAABAgQIECBAgAABAgQIECBAgACBGggIQFpoQjMBSJwm3uLq7rvvDo888khYvXp1+PDDD8OoUaPCl770peyqkD322GOb1axatSrceuutYdmyZeGdd97JbnU1duzYEG+R1feckIEG6NW5h9peD0Efqpz9CBAgQIAAAQIECBAgQIAAAQIECBAgUA8BAUg9+qCKmgkIQGrWEOUQIECAAAECBAgQIECAAAECBAgQIECgSQEBSJNgNu8NAQFIb/TZURIgQIAAAQIECBAgQIAAAQIECBAg0L0CApDu7a0ja0FAANICnl0JECBAgAABAgQIECBAgAABAgQIECBQAwEBSA2aoIT6CQhA6tcTFREgQIAAAQIECBAgQIAAAQIECBAgQKAZAQFIM1q27RkBAUjPtNqBEiBAgAABAgQIECBAgAABAgQIECDQpQICkC5trMNqTUAA0pqfvQkQIECAAAECBAgQIECAAAECBAgQINBpAQFIpztg/loKCEBq2RZFESBAgAABAgQIECBAgAABAgQIECBAoLCAAKQwlQ17SUAA0kvddqwECBAgQIAAAQIECBAgQIAAAQIECHSjgACkG7vqmFoWEIC0TGgAAgQIECBAgAABAgQIECBAgAABAgQIdFRAANJRfpPXVUAAUtfOqIsAAQIECBAgQIAAAQIECBAgQIAAAQLFBAQgxZxs1WMCApAea7jDJUCAAAECBAgQIECAAAECBAgQIECg6wQEIF3XUgfUDgEBSDsUjUGAAAECBAgQIECAAAECBAgQIECAAIHOCQhAOmdv5hoLCEBq3BylESBAgAABAgQIECBAgAABAgQIECBAoICAAKQAkk16T0AA0ns9d8QECBAgQIAAAQIECBAgQIAAAQIECHSXgACku/rpaNokIABpE6RhCBAgQIAAAQIECBAgQIAAAQIECBAg0CEBAUiH4E1bbwEBSL37ozoCBAgQIECAAAECBAgQIECAAAECBAgMJiAAGUzI+z0pIADpybY7aAIECBAgQIAAAQIECBAgQIAAAQIEukhAANJFzXQo7RMQgLTP0kgECBAgQIAAAQIECBAgQIAAAQIECBDohIAApBPq5qy9gACk9i1SIAECBAgQIECAAAECBAgQIECAAAECBLYpIACxQAjkCAhALAsCBAgQIECAAAECBAgQIECAAAECBAikLSAASbt/qi9JQABSEqxhCRAgQIAAAQIECBAgQIAAAQIECBAgUJGAAKQiaNOkJSAASatfqiVAgAABAgQIECBAgAABAgQIECBAgECjgADEmiCQIyAAsSwIECBAgAABAgQIECBAgAABAgQIECCQtoAAJO3+qb4kAQFISbCGJUCAAAECBAgQIECAAAECBAgQIECAQEUCApCKoE2TloAAJK1+qZYAAQIECBAgQIAAAQIECBAgQIAAAQKNAgIQa4JAjoAAxLIgQIAAAQIECBAgQIAAAQIECBAgQIBA2gICkLT7p/qSBAQgJcEalgABAgQIECBAgAABAgQIECBAgAABAhUJCEAqgjZNWgICkLT6pVoCBAgQIECAAAECBAgQIECAAAECBAg0CghArAkCOQICEMuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNLun+pLEhCAlARrWAIECBAgQIAAAQIECBAgQIAAAQIECFQkIACpCNo0aQkIQNLql2oJECBAgAABAgQIECBAgAABAgQIECDQKCAAsSYI5AgIQCwLAgQIECBAgAABAgQIECBAgAABAgQIpC0gAEm7f6ovSUAAUhKsYQkQIECAAAECBAgQIECAAAECBAgQIFCRgACkImjTpCUgAEmrX6olQIAAAQIECBAgQIAAAQIECBAgQIBAo4AAxJogkCMgALEsCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt/qm+JAEBSEmwhiVAgAABAgQIECBAgAABAgQIECBAgEBFAgKQiqBNk5aAACStfqmWAAECBAgQIECAAAECBAgQIECAAAECjQICEGuCQI6AAMSyIECAAAECBAgQIECAAAECBAgQIECAQNoCApC0+6f6kgQEICXBGpYAAQIECBAgQIAAAQIECBAgQIAAAQIVCQhAKoI2TVoCApC0+qVaAgQIECBAgAABAgQIECBAgAABAgQINAoIQKwJAjkCAhDLggABAgQIECBAgAABAgQIECBAgAABAmkLCEDS7p/qSxIQgJQEa1gCBAgQIECAAAECBAgQIECAAAECBAhUJCAAqQjaNGkJCEDS6pdqCRAgQIAAAQIECBAgQIAAAQIECBAg0CggALEmCOQICEAsCwIECBAgQIAAAQIECBAgQIAAAQIECKQtIABJu3+qL0lAAFISrGEJECBAgAABAgQIECBAgAABAgQIECBQkYAApCJo06QlIABJq1+qJUCAAAECBAgQIECAAAECBAgQIECAQKOAAMSaIJAjIACxLAgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7f6pviQBAUhJsIYlQIAAAQIECBAgQIAAAQIECBAgQIBARQICkIqgTZOWgAAkrX6plgABAgQIECBAgAABAgQIECBAgAABAo0CAhBrgkCOgADEsiBAgAABAgQIECBAgAABAgQIECBAgEDaAgKQtPun+pIEBCAlwRqWAAECBAgQIECAAAECBAgQIECAAAECFQkIQCqCNk1aAgKQtPqlWgIECBAgQIAAAQIECBAgQIAAAQIECDQKCECsCQI5AgIQy4IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0u6f6ksSEICUBGtYAgQIECBAgAABAgQIECBAgAABAgQIVCQgAKkI2jRpCQhA0uqXagkQIECAAAECBAgQIECAAAECBAgQINAoIACxJgjkCAhALAsCBAgQIECAAAECBAgQIECAAAECBAikLSAASbt/qi9JQABSEqxhCRAgQIAAAQIECBAgQIAAAQIECBAgUJGAAKQiaNOkJSAASatfqiVAgAABAgQIECBAgAABAgQIECBAgECjgADEmiCQIyAAsSwIECBAgAABAgQIECBAgAABAgQIECCQtoAAJO3+qb4kAQFISbCGJUCAAAECBAgQIECAAAECBAgQIECAQEUCApCKoE2TloAAJK1+qZYAAQIECBAgQIAAAQIECBAgQIAAAQKNAgIQa4JAjoAAxLIgQIAAAQIECBAgQIAAAQIECBAgQIBA2gICkLT7p/qSBAQgJcEalgABAgQIECBAgAABAgQIECBAgAABAhUJCEAqgjZNWgICkLT6pVoCBAgQIECAAAECBAgQIECAAAECBAg0CghArAkCOQICEMuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNLun+pLEhCAlARrWAIECBAgQIAAAQIECBAgQIAAAQIECFQkIACpCNo0aQkIQNLql2oJECBAgAABAgQIECBAgAABAgQIECDQKCAAsSYI5AgIQCwLAgQIECBAgAABAgQIECBAgAABAgQIpC0gAEm7f6ovSUAAUhKsYQkQIECAAAECBAgQIECAAAECBAgQIFCRgACkImjTpCUgAEmrX6olQIAAAQIECBAgQIAAAQIECBAgQIBAo4AAxJogkCMgALEsCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt/qm+JAEBSEmwhiVAgAABAgQIECBAgAABAgQIECBAgEBFAgKQiqBNk5aAACStfqmWAAECBAgQIECAAAECBAgQIECAAAECjQICEGuCQI6AAMSyIECAAAECBAgQIECAAAECBAgQIECAQNoCApC0+6f6kgQEICXBGpYAAQIECBAgQIAAAQIECBAgQIAAAQIVCQhAKoI2TVoCApC0+qVaAgQIECBAgAABAgQIECBAgAABAgQINAoIQKwJAjkCAhDLggABAgQIECBAgAABAgQIECBAgAABAmkLCEDS7p/qSxIQgJQEa1gCBAgQIECAAAECBAgQIECAAAECBAhUJCAAqQjaNGkJCEDS6pdqCRAgQIAAAQIECBAgQIAAAQIECBAg0CggALEmCOQICEAsCwIECBAgQIAAAQIECBAgQIAAAQIECKQtIABJu3+qL0lAAFISrGEJECBAgAABAgQIECBAgAABAgQIECBQkYAApCJo06QlIABJq1+qJUCAAAECBAgQIECAAAECBAgQIECAQKOAAMSaIJAjIACxLAgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7f6pviQBAUhJsIYlQIAAAQIECBAgQIAAAQIECBAgQIBARQICkIqgTZOWgAAkrX6plgABAgQIECBAgAABAgQIECBAgAABAo0CAhBrgkCOgADEsiBAgAABAgQIECBAgAABAgQIECBAgEDaAgKQtPun+pIEBCAlwRqWAAECBAgQIECAAAECBAgQIECAAAECFQkIQCqCNk1aAgKQtPqlWgIECBAgQIAAAQIECBAgQIAAAQIECDQKCECsCQI5AgIQy4IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0u6f6ksSEICUBGtYAgQIECBAgAABAgQIECBAgAABAgQIVCQgAKkI2jRpCQhA0uqXagkQIECAAAECBAgQIECAAAECBAgQINAoIACxJgjkCAhALAsCBAgQIECAAAECBAgQIECAAAECBAikLSAASbt/qi9JQABSEqxhCRAgQIAAAQIECBAgQIAAAQIECBAgUJGAAKQiaNOkJSAASatfqiVAgAABAgQIECBAgAABAgQIECBAgECjgADEmiCQIyAAsSwIECBAgAABAgQIECBAgAABAgQIECCQtoAAJO3+qb4kAQFISbCGJUCAAAECBAgQIECAAAECBAgQIECAQEUCApCKoE2TloAAJK1+qZYAAQIECBAgQIAAAQIECBAgQIAAAQKNAgIQa4JAjoAAxLIgQIAAAQIECBAgQIAAAQIECBAgQIBA2gICkLT7p/qSBAQgJcEalgABAgQIECBAgAABAgQIECBAgAABAhUJCEAqgjZNWgICkLT6pVoCBAgQIECAAAECBAgQIECAAAECBAg0CghArAkCOQICEMuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNLun+pLEhCAlARrWAIECBAgQIAAAQIECBAgQIAAAQIECFQkIACpCNo0aQkIQNLql2oJECBAgAABAgQIECBAgAABAgQIECDQKCAAsSYI5AgIQCwLAgQIECBAgAABAgQIECBAgAABAgQIpC0gAEm7f6ovSUAAUhKsYQkQIECAAAECBAgQIECAAAECBAgQIFCRgACkImjTpCUgAEmrX6olQIAAAQIECBAgQIAAAQIECBAgQIBAo4AAxJogkCMgALEsCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt/qm+JAEBSEmwhiVAgAABAgQIECBAgAABAgQIECBAgEBFAgKQiqBNk5aAACStfqmWAAECBAgQIECAAAECBAgQIECAAAECjQICkArXxJw5c8KCBQsGnXHWrFnh9NNP32K7jRs3hrvvvjs8/PDDYfXq1WHTpk1h1KhRYcKECeGss84Ku+666zbHXbVqVbjlllvCsmXLwrvvvpttP3bs2DB16tQwbty4be6b8tyDYg+wgQBkqHL2I0CAAAECBAgQIECAAAECBAgQIECAQD0EBCAV9mHKlCnhZz/72aAzNgYgH3zwQfjGN74Rli9fnrvv3nvvHW699dYwZsyY3PefeeaZcNFFF4UYZOS9pk+fHi6//PLc91Kee1DobWwgAGlFz74ECBAgQIAAAQIECBAgQIAAAQIECBDovIAApKIefPzxx+Hwww8P//Vf/xX+9E//NPz+7//+gDNvv/324ROf+ET/+xdffHF47LHHsv92wQUXhBNPPDHEbZYsWRKuueaasH79+uxqkEcffTTsuOOOW4y7cuXKEIOXDRs2hEMPPTTMnDkzHHDAAeHNN98MN998c1i0aFG2/ezZs8O0adO2qinVuVttqwCkVUH7EyBAgAABAgQIECBAgAABAgQIECBAoLMCApCK/ONtq44//vhstngbqwMPPLDQzK+88kqYPHlytu0VV1yRhRmbv2LAcdppp2VXd3z7298O55577hbvn3POOeG5554Lo0ePDg888EDYaaed+t+Pt9GaMWNGWLhwYXZLrHilyM4779z/fspzF8LdxkYCkFYF7U+AAAECBAgQIECAAAECBAgQIECAAIHOCghAKvKPoccf//EfZ1do/MM//EMYMWJEoZn7rsDYb7/9wlNPPZW7X7x91b333hviNjHE6HttHrrMnTs3TJo0aas5165dG8aPHx/iFSpXX311OOWUU/q3SXXuQrCDbCQAaYeiMQgQIECAAAECBAgQIECAAAECBAgQINA5AQFIRfYxXLjtttvC5z73ufCjH/2o0KzxCo0jjzwyvPfee2Fbz+l49tln+6/8eOihh8JBBx2UjX/77beHq666KgwbNiy88MILYffdd8+dd+LEiWHFihXZA9XnzZuXbZPy3IVwBSDtYDIGAQIECBAgQIAAAQIECBAgQIAAAQIEaisgAKmoNTHAiA8xj/8/Pqw8XhHy2muvZbeuis/vOOaYY8LZZ58ddtttt/6K1qxZk4US8dV4dcbmZb/11lth3Lhx2X/63ve+13/LrEsvvTQ8+OCD2fiLFy8e8Ej7riDZZ599sttlxVfKc7ejpa4AaYeiMQgQIECAAAECBAgQIECAAAECBAgQINA5AQFIBfbxaop45cf777+fPcg8hh55r3iFxk033RR++7d/O3v7xRdfDGeccUb2z3feeWc44ogjcveLt6867LDDsnHPO++87Lke8XX66aeHl156KRx11FHhjjvuGPBI58+fH66//vrsSpFXX301bLfddknP3Y6WCkDaoWgMAgQIECBAgAABAgQIECBAgAABAgQIdE5AAFKB/RtvvBGOO+64bKYYMsSHlsf/i1dm/OpXvwqPPPJI+Ou//uvw0UcfhU9+8pPhxz/+cfjN3/zN8MQTT/SHGYM9OD2GHOvWrQvTpk0Ls2fPzuY64YQTwuuvvx6OPfbYcOONNw54pAsWLAhz5szJ3l+6dGl2q6yU5y7S0hhwbOv19ttvh1NPPTXbZMmSJWHkyJFFhrUNAQIECBAgQIAAAQIECBAgQIAAAQIECNREQABSQSOWLVsWZs6cGeJJ9fhMjpNPPnmrWeMDzi+88MLsv8ew5IYbbshuXxVvYxVf8f3Ro0cPWG28BVa8FdbkyZOz22DFV7x9VryV1UknnRSuvfbaAfeND1CPt8GKr76T/SnPXaSlBx54YJHNtjApvIMNCRAgQIAAAQIECBAgQIAAAQIECBAgQKDjAgKQClvw4Ycfhu23337AGc8999wQH2g+fPjw7BZUf//3fx8uueSSbPuhBCAxSIlXnwwlAIlXpaQ6d5GWCkCKKNmGAAECBAgQIECAAAECBAgQIECAAAEC6QoIQGrUu82vxIi3xPrv//7vcP7552cVxkAiPjx9oFffLbDicz9mzZqVbRavNIkPWu+7omSgfTe/BVYMXuKD2BctWpTs3EVa6hZYRZRsQ4AAAQIECBAgQIAAAQIECBAgQIAAgXQFBCA16t1PfvKTcPbZZ2cVxVtW/cZv/EaYPn169u933XVXOPzww3Or3fwh6PE2WhdccEG2Xdx3+fLl4eijjw633XbbgEc6b9687JZbI0aMyB6CHq9AifulOnc7Wuoh6O1QNAYBAgQIECBAgAABAgQIECBAgAABAgQ6JyAAqdB+06ZN2UPQB3rF21/F22DFVwwlDjvssPCFL3wh+/cYiMRbWeW94rM/4jNA4mvu3Llh0qRJ2T/Hh6Hfc889Yf/99w9PPvnkgPPG53/Eq0/23Xff7BZc8RWfV5Lq3O1oqQCkHYrGIECAAAECBAgQIECAAAECBAgQIECAQOcEBCAV2H/nO98J8eqOnXfeOTzzzDMDzvjDH/6w/2Hljz/+ePjMZz4T+m5t9fWvf73/geiNAyxevDicd9552X+ODy8/+OCDs3++8847w5VXXpld2RGv6Ijz570mTpwYVqxYEY455pgwf/78/k1SnbsdLRWAtEPRGAQIECBAgAABAgQIECBAgAABAgQIEOicgACkAvs/+7M/y25hFV+PPfZY+K3f+q2tZo1Xh5xyyinZMztGjRqVBSXxapGZM2eGhx56KHz6058OMRTJu4Kk7wqOvfbaKzz//PP926xZsyZMmDAhm+u6664LJ5544lbzrl27NowfPz7E22hdccUVYcqUKf3bpDp3O1oqAGmHojEIECBAgAABAgQIECBAgAABAgQIECDQOQEBSAX2P/vZz/qDhfg8jviA88Yg46/+6q+ykCK+4q2rpk2blv3z0qVLw5lnnrnVf+8re+XKleG0004LGzduDJdcckn45je/ucURTZ06Nbz88svZbbDuu+++sMsuu/S/H0OXGTNmhIULF2YPPo9Xkuy4447976c8d6ttFYC0Kmh/AgQIECBAgAABAgQIECBAgAABAgQIdFZAAFKRf7wN1qOPPprNFm8tFR9UHq8Eic/a+NGPfhT+7u/+LnvvyCOPDH/zN3+TPYi87xVvbxXDiXgrqxhwTJ48Oeywww5hyZIl4Zprrgnr1q0L++23X3alSONtrl555ZUsIIlXeIwZMya7jdYhhxwS4pUfN910U3j66aezaTYPXTYnSXXuVtsqAGlV0P4ECBAgQIAAAQIECBAgQIAAAQIECBDorIAApCL/DRs2ZFdb9D1kPG/aeHXIjTfeuFWIsX79+nD22WeHGGbkvfbcc8/sFlujR4/Off/+++8Ps2bNCh999FHu+2eddVa47LLLct9Lee5WWisAaUXPvgQIECBAgAABAgQIECBAgAABAgQIEOi8gACkwh7EW0499dRT4cc//nEWZvzHf/xH+OQnPxkOOuig7PkfJ5xwQu4zPmKJ8RZXd999d3jkkUfC6tWrw4cffpg9K+RLX/pSdlXIHnvssc0jWbVqVbj11lvDsmXLwjvvvJPd6mrs2LEh3iKr7zkhAw2Q8txDba8AZKhy9iNAgAABAgQIECBAgAABAgQIECBAgEA9BAQg9eiDKmomIACpWUOUQ4AAAQIECBAgQIAAAQIECBAgQIAAgSYFBCBNgtm8NwQEIL3RZ0dJgAABAgQIECBAgAABAgQIECBAgED3CghAure3jqwFAQFIC3h2JUCAAAECBAgQIECAAAECBAgQIECAQA0EBCA1aIIS6icgAKlfT1REgAABAgQIECBAgAABAgQIECBAgACBZgQEIM1o2bZnBAQgPdNqB0qAAAECBAgQIECAAAECBAgQIECAQJcKCEC6tLEOqzUBAUhrfvYmQIAAAQIECBAgQIAAAQIECBAgQIBApwUEIJ3ugPlrKSAAqWVbFEWAAAECBAgQIECAAAECBAgQIECAAIHCAgKQwlQ27CUBAUgvdduxEiBAgAABAgQIECBAgAABAgQIECDQjQICkG7sqmNqWUAA0jKhAQgQIECAAAECBAgQIECAAAECBAgQINBRAQFIR/lNXlcBAUhdO6MuAgQIECBAgAABAgQIECBAgAABAgQIFBMQgBRzslWPCQhAeqzhDpcAAQIECBAgQIAAAQIECBAgQIAAga4TEIB0XUsdUDsEBCDtUDQGAQIECBAgQIAAAQIECBAgQIAAAQIEOicgAOmcvZlrLCAAqXFzlEaAAAECBAgQIECAAAECBAgQIECAAIECAgKQAkg26T0BAUjv9dwREyBAgAABAgQIECBAgAABAgQIECDQXQICkO7qp6Npk4AApE2QhiFAgAABAgQIECBAgAABAgQIECBAgECHBAQgHYI3bb0FBCD17o/qCBAgQIAAAQIECBAgQIAAAQIECBAgMJiAAGQwIe/3pIAApCfb7qAJECBAgAABAgQIECBAgAABAgQIEOgiAQFIFzXTobRPQADSPksjESBAgAABAgQIECBAgAABAgQIECBAoBMCApBOqJuz9gICkNq3SIEECBAgQIAAAQIECBAgQIAAAQIECBDYpoAAxAIhkCMgALEsCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt/qm+JAEBSEmwhiVAgAABAgQIECBAgAABAgQIECBAgEBFAgKQiqBNk5aAACStfqmWAAECBAgQIECAAAECBAgQIECAAAECjQICEGuCQI6AAMSyIECAAAECBAgQIECAAAECBAgQIECAQNoCApC0+6f6kgQEICXBGpYAAQIECBAgQIAAAQIECBAgQIAAAQIVCQhAKoI2TVoCApC0+qVaAgQIECBAgAABAgQIECBAgAABAgQINAoIQKwJAjkCAhDLggABAgQIECBAgAABAgQIECBAgAABAmkLCEDS7p/qSxIQgJQEa1gCBAgQIECAAAECBAgQIECAAAECBAhUJCAAqQjaNGkJCEDS6pdqCRAgQIAAAQIECBAgQIAAAQIECBAg0CggALEmCOQICEAsCwIECBAgQIAAAQIECBAgQIAAAQIECKQtIABJkrHNHAAAIABJREFUu3+qL0lAAFISrGEJECBAgAABAgQIECBAgAABAgQIECBQkYAApCJo06QlIABJq1+qJUCAAAECBAgQIECAAAECBAgQIECAQKOAAMSaIJAjIACxLAgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7f6pviQBAUhJsIYlQIAAAQIECBAgQIAAAQIECBAgQIBARQICkIqgTZOWgAAkrX6plgABAgQIECBAgAABAgQIECBAgAABAo0CAhBrgkCOgADEsiBAgAABAgQIECBAgAABAgQIECBAgEDaAgKQtPun+pIEBCAlwRqWAAECBAgQIECAAAECBAgQIECAAAECFQkIQCqCNk1aAgKQtPqlWgIECBAgQIAAAQIECBAgQIAAAQIECDQKCECsCQI5AgIQy4IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0u6f6ksSEICUBGtYAgQIECBAgAABAgQIECBAgAABAgQIVCQgAKkI2jRpCQhA0uqXagkQIECAAAECBAgQIECAAAECBAgQINAoIACxJgjkCAhALAsCBAgQIECAAAECBAgQIECAAAECBAikLSAASbt/qi9JQABSEqxhCRAgQIAAAQIECBAgQIAAAQIECBAgUJGAAKQiaNOkJSAASatfqiVAgAABAgQIECBAgAABAgQIECBAgECjgADEmiCQIyAAsSwIECBAgAABAgQIECBAgAABAgQIECCQtoAAJO3+qb4kAQFISbCGJUCAAAECBAgQIECAAAECBAgQIECAQEUCApCKoE2TloAAJK1+qZYAAQIECBAgQIAAAQIECBAgQIAAAQKNAgIQa4JAjoAAxLIgQIAAAQIECBAgQIAAAQIECBAgQIBA2gICkLT7p/qSBAQgJcEalgABAgQIECBAgAABAgQIECBAgAABAhUJCEAqgjZNWgICkLT6pVoCBAgQIECAAAECBAgQIECAAAECBAg0CghArAkCOQICEMuCAAECBAgQIECAAAECBAgQIECAAAECaQsIQNLun+pLEhCAlARrWAIECBAgQIAAAQIECBAgQIAAAQIECFQkIACpCNo0aQkIQNLql2oJECBAgAABAgQIECBAgAABAgQIECDQKCAAsSYI5AgIQCwLAgQIECBAgAABAgQIECBAgAABAgQIpC0gAEm7f6ovSUAAUhKsYQkQIECAAAECBAgQIECAAAECBAgQIFCRgACkImjTpCUgAEmrX6olQIAAAQIECBAgQIAAAQIECBAgQIBAo4AAxJogkCMgALEsCBAgQIAAAQIECBAgQIAAAQIECBAgkLaAACTt/qm+JAEBSEmwhiVAgAABAgQIECBAgAABAgQIECBAgEBFAgKQiqBNk5aAACStfqmWAAECBAgQIECAAAECBAgQIECAAAECjQICEGuCQI6AAMSyIECAAAECBAgQIECAAAECBAgQIECAQNoCApC0+6f6kgQEICXBGpYAAQIECBAgQIAAAQIECBAgQIAAAQIVCQhAKoI2TVoCApC0+qVaAgQIECBAgAABAgQIECBAgAABAgQINAoIQKwJAjkCAhDLggABAgQIECBAgAABAgQIECBAgAABAmkLCEDS7p/qSxIQgJQEa1gCBAgQIECAAAECBAgQIECAAAECBAhUJCAAqQjaNGkJCEDS6pdqCRAgQIAAAQIECBAgQIAAAQIECBAg0CggALEmCOQICEAsCwIECBAgQIAAAQIECBAgQIAAAQIECKQtIABJu3+qL0lAAFISrGEJECBAgAABAgQIECBAgAABAgQIECBQkYAApCJo06QlIABJq1+qJUCAAAECBAgQIECAAAECBAgQIECAQKOAAMSaIJAjIACxLAgQIECAAAECBAgQIECAAAECBAgQIJC2gAAk7f6pviQBAUhJsIYlQIAAAQIECBAgQIAAAQIECBAgQIBARQICkIqgTZOWgAAkrX6plgABAgQIECBAgAABAgQIECBAgAABAo0CAhBrgkCOgADEsiBAgAABAgQIECBAgAABAgQIECBAgEDaAgKQtPun+pIEBCAlwRqWAAECBAgQIECAAAECBAgQIECAAAECFQkIQCqCNk1aAgKQtPqlWgIECBAgQIAAAQIECBAgQIAAAQIECDQKCECsCQI5AgIQy4IAAQIECBAgQIAAAQIECBAgQIAAAQJpCwhA0u6f6ksSEICUBGtYAgQIECBAgAABAgQIECBAgAABAgQIVCQgAKkI2jRpCQhA0uqXagkQIECAAAECBAgQIECAAAECBAgQINAoIACxJgjkCAhALAsCBAgQIECAAAECBAgQIECAAAECBAikLSAASbt/qi9JQABSEqxhCRAgQIAAAQIECBAgQIAAAQIECBAgUJGAAKQiaNOkJSAASatfqiVAgAABAgQIECBAgAABAgQIECBAgECjgADEmiCQIyAAsSwIECBAgAABAgQIECBAgAABAgQIECCQtoAAJO3+qb4kAQFISbCGJUCAAAECBAgQIECAAAECBAgQIECAQEUCApCKoE2TloAAJK1+qZYAAQIECBAgQIAAAQIECBAgQIAAAQKNAgIQa4JAjoAAxLIgQIAAAQIECBAgQIAAAQIECBAgQIBA2gICkLT7p/qSBAQgJcEalgABAgQIECBAoOcF/ufjTeHt/9gwqMPI/7dDGDZs2KDb9doGRfz23mWHMGI4u15bG46XAAECBAgQ2FpAAGJVEMgREIBYFgQIECBAgAABAgMJFDkBHfftpRP4RUz6PNau/+/w+asWD7rAVs89PjuJ38zYgw7aBRsU8fvFnK+E7bcb3gVH6xAIECBAgAABAq0JCEBa87N3lwoIQLq0sQ6LAAECBAgQIDCAQDMn2YucgI7TDOUEfpE6Ng9Ximw/lCCmyLib11HEpM+jyLab+xXZnvWWC7vPww88AQIECBAgQKDXBQQgvb4CHH+ugADEwiBAgAABAgQIpC9Q5CR+M1clVHECv8jJ/irCgTLr6PTYVfSx3WuvzJ5XEail/2niCAgQIECAAIFUBQQgqXZO3aUKCEBK5TU4AQIECBAgQGBIAkVOKm9+MrfIifZmToY3s+1QT1gXqbnMsR3j1kuzGZOyti2z50Mde0g/xHYiQIAAAQIECFQsIACpGNx0aQgIQNLokyoJECBAgACBegoUCSr6rrxoZlvhwP/1u6wT7c2MO9QT5/r4v31M3bqZn916flKpigABAgQIEOgFAQFIL3TZMTYtIABpmswOBAgQIECAQBcLFDnRGQ+/rNtJ1eVEcV3qaPbkeTN1N7NtmXWUOXZdjrEudVRh3cUfjw6NAAECBAgQqLmAAKTmDVJeZwQEIJ1xNysBAgQIECBQnUCRUKOZQKOKk6iuHPi/9dHMyfOyti2z52WO3YxHL9RRxTEW+bzZPESt7pPQTAQIECBAgEC3CwhAur3Djm9IAgKQIbHZiQABAgQIEOigQLMnGIuECU4Ub9nQunhUccK6yPoos44yx65LH+tSRx2tO/hRamoCBAgQIECgywQEIF3WUIfTHgEBSHscjUKAAAECBAhsLVAkqEjx+Rh1PIla5CR+Myehm9m2TI8yx3aMW//MNmNS1rZl9rzMsZvx2LyOZj4n/Z4hQIAAAQIECGxLQABifRDIERCAWBYECBAgQKC7BIqcTItHPJTgodmxnZT/37XVzInRZrYtc+y61OEYqwspWNffutnP4CLbD+V3QXf91nQ0BAgQIECgewQEIN3TS0fSRgEBSBsxDUWAAAECBEoSaOYkVpHQocwTnWWO7aR8dSdoWVdn3Qs/M9ZTd62nIr+T4hFXEa4UqaWvjpJ+RRuWAAECBAjURkAAUptWKKROAgKQOnVDLQQIECCQskCRkzBDPSFUJNRwgrG7TjAW6XkvnDh3jNb1569avM1fDXX57KtLHan/zDT7u7TIZ2Vfb4qMXUVYUmYdZY6d8t9oaidAgECvCAhAeqXTjrMpAQFIU1w2JkCAAIEuEGjm5EAz2xY5CZP6iSnH+H8/AM2c7CxrW+upO8KBXuhjMz8DZXqUObZj7I6fx2bCkir+Rw1F/g7ZvI4iv6fLPMa9d9khjBg+rAv+WnQIBAgQSFNAAJJm31RdsoAApGRgwxMgQIDAkASKfOFv5tYaQz050MyJhCLbOvnWHSfIeqGPTuZ2x1qtSx/rUkcv/Ow6Rj+7nbxqaul3x4d9PvnrQ/rbz04ECBAg0LqAAKR1QyN0oYAApAub6pAIECBQQ4EigUaZIUUvnBBygtFJr3ae9LKerCfrKYRmfg6a2bbM30llju0Yq/tcSNX6F3O+ErbfbngN/xJVEgECBHpDQADSG312lE0KCECaBLM5AQIECgoUOeE/1CsYUhq77xg7fXVEL5wQSvVkSTN1N7NtmT0vc+y6HGNd6ugF6144RuupuhPnvbCeeuEYU/+ZKfjnss0IECBAoM0CApA2gxquOwQEIN3RR0dBgEA1As0ED0VO+Kf+5dYx/u+6q0sf61JHsybN1N3MtmXWUebYdTnGutTRC9a9cIzWkwCknVcU+Zmp/3pq5m/mItvGI67iAfXVfKMwCwECBMoTEICUZ2vkhAUEIAk3T+kEekSg2S9FRbYf6pUX7T7h74RQ/b/At7vnvXDSxjFa1050CkYbfwr8vvO54HOhuc8FPzMD/8z0yFcgh0mAAIEhCQhAhsRmp24XEIB0e4cdH4F6CjQTUhQ5AV3mCdcyx/bl1gmhdp4Qsp6sJ+vJCca6Bg8+n3w+tfPzqRf+NvMzM/DPTDPfI+r5TUhVBAgQKE9AAFKerZETFhCAJNw8pRMoWaDIl4tYQjNXUzTzPAhf/JwscbLEydy6nsx18s3nk88nn08+nxYP+pdoM3/LNbOtz2CfwUU/g5v9PjPoorYBAQIEai4gAKl5g5TXGQEBSGfczUqgUwJFvgQ0E1L0whdQx9gdX7J7oY91OXnUC9a9cIzWU3d89tWlj3Wpoxd+dh2jn92i4UCnr7Ku4+dCp76jmZcAAQLtEhCAtEvSOF0lIADpqnY6mC4RKBJSxEPt9isv6vilqMgXxWbqbmbbMk9olDm2Y6zuRAzr6qx74WfGerKe2nkS1Xqyntq5nnwGW09lraci38P23mWHMGL4sC755ukwCBDoNgEBSLd11PG0RUAA0hbGpgcp8ofVUE5uFxl3qCfOi4zdTM2b19E0YA12KOIxVOsiJ9l98fPFr6wvfkXWXzMnsprZtsx1XebYdTnGutTRC9a9cIzWk98z7fw9Yz1ZT+1cTz6DradOrqdfzPlK2H674TX4RqoEAgQIbC0gALEqCOQI9FIA0uwJ62YWTLNjd+sJxqF+uS3iN9Rwpd1j1+X2UL74+eLXyS9+zfysN7Ntmeu6zLHrcox1qaMXrHvhGK0nv2fa+XvGerKe2rmefAZbT3VYT82cL7AtAQIEqhIQgFQlbZ4hC6xatSrccsstYdmyZeHdd98Nu+66axg7dmyYOnVqGDdu3JDH3daOvRSAFAkdNv9jupkT582OXWT7Zr4oNrNtL3xhcIy+FNXhS1G7f87LXNdljl2Xz6deOEbWPvva+dlnPVlP1pMHvTf+FPhcqO5zgXV11kP9G7HI+QK3yyrlNJZBCRDYhoAAxPKotcAzzzwTLrroorBx48bcOqdPnx4uv/zyth+DAKT+f1ildBLVH+rWk5MlTpY4WbJ40N/VzXxWlrXtUL/sF/mdVObYzXiUWUeZY9flGOtSRy9Y98IxWk/+Rmzn34h+ZqynVNbT0u+OD/t88tcH/dvQBgQIEGiXgACkXZLGabvAypUrw5QpU8KGDRvCoYceGmbOnBkOOOCA8Oabb4abb745LFq0KJtz9uzZYdq0aW2dXwDij8d2/vHoy631ZD0JQAQgApBeODHVC8fod7rf6X6n+53ud7rf6b3w+67MYxSAtPX0lcEIECggIAApgGSTzgicc8454bnnngujR48ODzzwQNhpp536C9m0aVOYMWNGWLhwYXZLrHilyM4779y2QgUgvtz6cuvLbV2/3Dr55vOpnZ9PZX65rctarUsdvWDdC8doPfkMbudnsPVkPbVzPfkMtp5SWU8emN62U1cGIkCgoIAApCCUzaoVWL16dTj++OOzSefOnRsmTZq0VQFr164N48ePDx9//HG4+uqrwymnnNK2IgUg/nhs5x+PvtxaT9aTQK2ugZqTJT6f2vn5ZD1ZT9aT33d+33Xu6gifwT6DU/sMbtsJHAMRIEBgEAEBiCVSS4Hbb789XHXVVWHYsGHhhRdeCLvvvntunRMnTgwrVqwIEyZMCPPmzWvbsQhA/PHYzj8eBSDWk/XkhJATQp07IeQz2Gewz2CfwXX9DPb55POpnZ9PAhDrKbX1VOSB6bGrHpretlNdBiLQswICkJ5tfb0P/NJLLw0PPvhgGDVqVFi8eOCTJvEB6Pfee2/YZ599sttlteslAPHHYzv/ePTl1nqynpx8q+vJNydLfD618/PJerKerCe/7/y+61zg7zPYZ3C3fga7ZVa7znQZh0DvCghAerf3tT7y008/Pbz00kvhqKOOCnfccceAtc6fPz9cf/312ZUir776athuu+3aclwCEH88tvOPRwGI9WQ9OSHkhFDnTgj5DPYZ7DPYZ3BdP4N9Pvl8aufnkwDEeur29dSWkz0GIUCgJwUEID3Z9vof9AknnBBef/31cOyxx4Ybb7xxwIIXLFgQ5syZk72/dOnSAW+V1ThADDi29YrPF/na176WbRKvMNl7773rjzbECt96b0P4/Xk/HXTvn146PowYPiwU2b6ZbePEzWxf1ra9UIdj3HqZW09bmjTjYT11x3rqhT7WZV33gnUvHKP11B2ffXXpY13q6IWfXcfoZ3ew77x1+XmsSx11/JmJt8z69/c/2Oa5i713+bXsfyDrVU+BPffcs23/w+V6HqGq6iogAKlrZ3q8rvhMjzVr1oSTTjopXHvttQNqxHAi3gYrvpYsWRJGjhxZSO7AAw8stJ2NCBAgQIAAAQIECBAgQIAAAQIECBBoTaCZ83atzWRvAlsKCECsiFoKHHfcceGNN94QgNSyO4oiQIAAAQIECBAgQIAAAQIECBAgUFxAAFLcypbtFRCAtNfTaG0SOPnkk8Nrr70WYhByww03DDjq5rfAevHFF8Nuu+1WqILBboH1wQcfhH/5l38Je+yxR3ZbrXY9W6RQcRVs9Pbbb4dTTz01m6nbb/FVAacpCLRdwM9o20kNSKCtAn5G28ppMAJtFfDz2VZOgxFou4Cf0baTGpBAWwXK/Bl1C6y2tspgTQgIQJrAsml1AtOnTw/Lly8PRx99dLjtttsGnHjevHlZQDJixIjsIejDhw+vrsiEZ+qlh7wn3Cal97CAn9Eebr5DT0LAz2gSbVJkjwr4+ezRxjvsZAT8jCbTKoX2qICf0R5tfJcftgCkyxuc6uHNnj073HPPPWH//fcPTz755ICHEZ//Ea9g2Pf/t3cn4DaV7//Hb8qXDJFSMiSJShQqUcnYYEgZUqhEIhpFlEqiSSgUKlPJUIikDJEhRUSTUoomFVJEkYr6X5/n/1/nv21rn7P32eecvc9e7+e6vtdPztprref1rPXbx3M/z32XKmVLlizJrd3N8fvmCy3HybkgAjEJ8I7GxMXBCOS4AO9ojpNzQQSiFuD9jJqKAxFIiADvaELYuSgCUQvwjkZNxYG5SIAASC4arCDd6qRJk2zgwIFuZ4d2ghQuXNi3+y1btrTPPvvMGjZsaKNGjQoSUVx95QstLj4+jEC2C/COZjsxF0AgLgHe0bj4+DAC2SrA+5mtvJwcgbgFeEfjJuQECGSrAO9otvJy8gQJEABJEDyXTV9g8+bN1qhRI3fQ0KFDrVmzZod8YMuWLdagQQP7999/rX///ta2bVtYoxTgCy1KKA5DIEECvKMJgueyCEQpwDsaJRSHIZAAAd7PBKBzSQRiEOAdjQGLQxFIgADvaALQuWS2CxAAyXZiLpBZgXbt2tnatWtdGqwZM2ZYkSJF0k7133//2R133GHz5893hc8XL15sBQsWzOylAvc5vtACN+R0OJcJ8I7msgHjdgMnwDsauCGnw7lIgPczFw0WtxpIAd7RQA47nc5FAryjuWiwuNWoBQiARE3FgTktsG7dOmvTpo3b4VGpUiXr06ePVa5c2bTzY/To0bZw4UJ3S6oX0r59+5y+vVx9Pb7QcvXwcfMBEOAdDcAg08VcLcA7mquHj5tPcQHezxQfYLqX6wV4R3P9ENKBFBfgHU3xAQ5o9wiABHTgc0u3Z86caffff7/t37/f95Y7duxod999d27pTtLcJ19oSTMU3AgCvgK8ozwYCCS3AO9oco8PdxdsAd7PYI8/vU9+Ad7R5B8j7jDYAryjwR7/VO09AZBUHdkU6teGDRts3LhxtmrVKvv1119dqqsqVaqYUmR5dUJSqLs50hW+0HKEmYsgkGkB3tFM0/FBBHJEgHc0R5i5CAKZEuD9zBQbH0IgxwR4R3OMmgshkCkB3tFMsfGhJBcgAJLkA8TtIYAAAggggAACCCCAAAIIIIAAAggggAACCCCAQOwCBEBiN+MTCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkOQCBECSfIC4PQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEIhdgABI7GZ8AgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBJJcgABIkg8Qt4cAAggggAACCCCAAAIIIIAAAggggAACCCCAAAKxCxAAid2MTyCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggECSCxAASfIB4vYQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgdgECILGb8QkEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIcgECIEk+QNweAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIxC5AACR2Mz6BQK4W2LBhg40dO9ZWrVplO3bssGLFilmVKlWsXbt2duGFF+bqvnHzCCSLwLJly+yVV16xjz76yL1n//vf/6xcuXJWt25du+6666x48eK+t/rPP//Y1KlT7bXXXrNNmzbZf//9Z6VLl7ZGjRpZx44d3fuaXuP9TpYngPvITQJ79+61Fi1a2Lfffmu33HKL3XrrrbyfuWkAudeUEvjjjz9s4sSJtmjRIvv+++/tr7/+slKlSrnvzxtuuMGOO+64iP3VuzxhwgSbP3++++xhhx3mvnsbN27svnsLFCiQrtWaNWvs+eeftw8++MB2797tvqvPOuss99nq1aunlDOdQSCzAitXrrRJkybZxx9/bL/99psVKlTITj31VPc92rx5c8ubNy/foZnF5XMIZELgoYceshdffNEeffRRa9myZbpnSOS/NeO9diZo+AgCBwkQAOGBQCBAAm+99Zbdfvvtpi8fv3bttdfafffdFyARuopA1grs37/f7r77bpszZ07EEx999NE2cuTIQyZTNMnTuXNnW716te9njz32WBs3bpxVqlTJ9+e831k7lpwtOAL9+vWzl19+2XU4UgCE9zM4zwM9TZzAF198YTfeeKP9/PPPvjehRQBjxoyxM84445Cf79y509q3b+8WD/i1k046yQU3IgVQJk+ebAMHDnQLD8KbJnR79erlAjA0BIIsMGjQIBs/fnxEggsuuMD9jhsebOQ7NMhPDX3PTgEtFtDCnX///TfDAEgi38N4r52dhpw7OAIEQIIz1vQ04ALr16+3tm3b2r59+6xq1arWu3dvq1ixov3www/2zDPPuJV2apoI0j8gaQggELtA6D8MGzZs6AIa5cuXt+3bt5t2hYwaNcq0QlWTONrlEToRc+edd9obb7xh+fLlc5OwzZo1cztH9LnBgwfbrl273G6Q119/3QoWLHjQzfF+xz5WfAIBCSxdutS6du2ahhEpAML7yfOCQPYK6HtS33taUV6kSBHr0aOH1atXz7SwYMmSJTZs2DD7888/TYsB5s2bZ4ULF067IU38aCfzhx9+6FajK1ih7+ADBw7Y3LlzbcSIEW4niQInCnaGr1DX9+xNN93kJpDq1Kljt912m5UtW9YFU5588knTzpA8efLY6NGjrX79+tkLwdkRSFKB6dOnpy2Uq1atmt1xxx3u35Jbt251O6/0+6laq1at7JFHHjmoF3yHJumgclu5WmDx4sXu+8pb3JrRDpBEvofxXDtXDxI3n1QCBECSaji4GQSyT0ATPJroUSqAWbNmuX8gek2r3fRLrFIGaGJWK8lD/2GZfXfFmRFIHYFt27ZZgwYN3GTNZZddZkOGDDmkc+vWrbOrr77aHaNAowKOavr71q1buz/379/fBStDmwIcbdq0cb/galJIEzWhjfc7dZ4jepJzAkpPp3f1l19+SbuoXwCE9zPnxoQrBVegZ8+eaQF+pcDSYp3QFhqsDF+so99ftcNZTTtEwlO6hn5W381670N/B1bani+//NJq1Kjh0ogcfvjhaT//+++/XQosBVe0oEEBlUgpfoI7evQ8CAIXXXSRSy2nncgzZsyw/PnzH9Rt7x1WsFBBRW+RD9+hQXg66GNOCihY//TTT7ugvP7stfQCIIl8D+O9dk7acq3UFiAAktrjS+8QcAJawdakSRP3Z63I0cqc8LZlyxY3easv0ccee8zlcaUhgED0AkqfMWDAAPcBrcjRbg2/pkkaTdbo5zpOzVsVU6ZMGXvzzTdd3vLwpvR0Wn2nYxSk9Brvd/RjxJEIhAp0797dvUvKlzxz5kz3I78ACO8nzw0C2SugIKSCFtqxoUnULl26+F7wkksusR9//NHVGQhdYX7VVVe5mlvnnHOOq03g11RHa8WKFVazZk0X5PDa8uXL3W5NtRdeeMFq1ap1yMfXrl3rdpio6bM6Bw2BIAloZ9a5557ruqwdVkpVF960U8rLIqDJWQVM1PgODdKTQl+zW0DfWY8//rgL2qudfvrE6K05AAAgAElEQVTp9tlnn7k/pxcASeR7GM+1s9uT8wdLgABIsMab3gZUQDmP9YWoFTn6x1+kAsyaBNIXqAouK38rDQEEohdQmgy9a9o99e6770b84BNPPGHPPvusS3X16aefunzjmkxRwdX06vAoBYi382P27Nmu4KQa73f0Y8SRCHgCXioPBSKVjk6FjtXCAyC8nzwzCGS/gLeA4IgjjnC/p4anefTuQGmswleda2JWQQu9q6rBpUCHX1NgRDU+tHvjvffes6JFi7rDvOKxRx55pPt7vwUIOnft2rVNdUY6dOhgffv2zX4UroBAEgnod1QFGNWUNaBbt26H3J2Komu3sppSvioNHd+hSTSI3EpKCJxyyimuH/p3pP5dqAUBXrAxUgAkke9hvNdOiUGjE0kjQAAkaYaCG0Eg+wT69Oljr7766kErzv2u5q0wP/744126LBoCCMQu8Mcff6SbQs7bAXLMMce4QMnmzZtd0FEtvd1XSrHlpfV4+OGH01Jm8X7HPkZ8ItgCSuFx+eWXu3oCWvGtVa3ePyjDAyC8n8F+Vuh9zgh432PhuzN0daV+1ERPpKaghYISauntzgjdxaGFAwpoqF1zzTX2/vvvH7IzJPx63g6Ss88+2xSwoSEQNAHtwPr2229d3Q/tmlSdutCm1HSqsaP3VTucVa+H79CgPSX0N7sFtABOAQ8FIitUqODquSrYqBYpAJLI9zDea2e3J+cPlgABkGCNN70NqID3jztN8iivcqSm1TrDhw93O0W0Mj00B3JA6eg2AlkqoCCGfmnVKlb9Q1KFWUMnb7RC1VthF35hpadTAVdNBmnlnX7xDZ284f3O0qHiZCkqoBQ7StGhfP6hK7kjBUB4P1P0QaBbSSXg7UDW6nHt0lBqOn0fKq3V3r17rUSJEm6hgL77vLoCXgdeeeWVtB0Z2ilZqlQp376pUHPdunXdz7Tr48orr3R/VlHzn376yaXC0+RRpHbvvfe6ugclS5Z09Q1oCARNQClatYhHv48qEHjrrbe6YMj27dtdUHDatGmOREWZb775ZvdnvkOD9pTQ3+wW+Oabb1w9Kq9FEwBJ5HsY77Wz25PzB0uAAEiwxpveBlSgadOmtnHjRrv44ovtqaeeiqiglXP6R6HaypUrI6bKCigj3UYgLgFtAdZWZW93lZdrfN68eWnBDKXi8SZi/S6mIIfSfYQWUOf9jmtY+HDABLxAv1bNzZo1Ky2dTqQACO9nwB4QupsQgQsuuMBNoqqugFLtaBW5XytWrJg988wzVr169bQfjx071gYPHuz+W7s8lIbSr2l3ppfqrnfv3nbDDTe4w6pVq+Z2g2mHh1JoRWraoTlhwgSXnksBVBoCQRRQcFL1B7QTJLwpg4AW51xxxRVpP+I7NIhPCX3OSYFoAiCJfA/jvXZOWnKt1BcgAJL6Y0wPEXCr5rT98LLLLrMhQ4ZEFPFyousArW7TKjcaAghkjYAKtiroodasWTMbOnSo+7PS0yn9h5pW15UrVy7iBZUCS7tIWrdubUqDpcb7nTXjw1lSX0A7G6+++mqXk1wTrFWqVEnrdKQACO9n6j8X9DDxAgpoeDs9FAjR6vIePXpY1apVbc+ePaYJFP3+qmNUx051sJReR00167SbUk117CLtXt6/f78rFqumVezdu3d3fz7ttNPcinYtUNA1IzXV+VLwRTVC1q9fn3g07gCBBAjo3VMKOb93QCmxWrRo4YIgXr1JvkMTMEhcMlAC0QRAEvkexnvtQA0mnc12AQIg2U7MBRBIvICXs5UASOLHgjsInoAmW7VyVP9gVKtUqZK99NJLVqhQIfffc+bMsV69erk/ZyYAwvsdvGeKHscusG/fPjcx8/XXX7u0Har1EdoiBUB4P2O35hMIxCrgBSH0Oe10HDdu3CF1P1Sn47rrrnPBimuvvdZUt05NQQkFJ9QyEwBRIFSpJQmAxDpqHB80AWUJULYAtbZt27r3sGzZsrZz5073++uwYcNMO620w1Ipl1Xrju/QoD0l9DenBaIJgCTyPYz32jntyfVSW4AASGqPL71DwAloK/Lnn3+eVnMgEktoCizlazzqqKMQRACBOAT+/vtvU95wpbZS0z8KtQtE+cy9tmjRorRcyfolUQGSSM1LgaW6Pvfffz/vdxxjw0eDJTBgwACXo1wryhWADF8lHikAwvsZrOeE3iZGwNsBoqsrNV3lypV9b0RBCtX5UB2Qt99+2x2j71TtsFT74IMP0hYXhJ8gNAWWdl126tTJHaK6W0q7pf/2dmP6XZwUWIl5NrhqcgisWLHCpYlT69mzp3Xp0uWQG/viiy9cYEQ7tVq1auXeS75Dk2P8uIvUFYgmAJLI9zDea6fuyNGzRAgQAEmEOtdEIIcFtEJn9erVdt5557n8xZGal0ZA2/uVKiRv3rw5fKdcDoHUEVCtDq0y16pVNaXeUK5yLy2A11O9m3pH1aZMmZKWozxcIrQIeugKdt7v1Hlm6En2CCxfvtw6d+7s6n1oclWByPAWKQDC+5k9Y8JZEQgV8GqAFClSxNasWRMRZ/z48TZo0CD3c6/eh95pr3aHgiLhRdK9k23ZssXq1avn/lPBDO0IU2vQoIH9+OOPrii6VwfP7wb69u1rKrheunRpW7x4MQOIQKAElNZKqehU50N1QPRvRb+m91PvqRYZ6F1et24dv+MG6kmhszktEE0AJJG/y8Z77Zz25HqpLUAAJLXHl94h4AT69evn8p2feOKJtmDBgogqSiegOiClSpVyK+xoCCCQOYHvv//eFXP1ikTWqVPHhg8f7rsy9eeffzb9XE05zpWqzq+p9odqgKhpVZ1W1/F+Z258+FSwBDQ5qknSWJsmeZTTnPczVjmORyA2AdXmUWFxpcx59913I3542rRpabsfdZyO1+f0ebWpU6dajRo1fD+vgEm7du3cz7RrpFatWu7PKob+zjvv2Pnnn+8mbiM1rX7XKnjtGJk0aVJsHeRoBHK5gJdN4NJLL3W/z0Zq+vejdmqpafezsgnwHZrLB5/bT2qBaAIgify3ZrzXTmp8bi7XCRAAyXVDxg0jELuA/qE2cOBAt1pHUfjChQv7nqRly5Yuf3LDhg1t1KhRsV+ITyCAgH311VcuT/mOHTucRps2beyBBx6IWJhVx3iprdJLwaEVp926dXPnVEE55UxX4/3moUMgfYF4AiBlypTh/eQBQyCbBR588EG3A1I7j7VrMtLvqfrdVJOv+fLls08++cQdr9RWKpquelta8NO+fXvfu/XSvObJk8eU5rVYsWLuOG/F+tFHH+2CL/p5eNO5a9eu7Wod6PtdqS1pCARJoGnTprZx40a3Y2r06NERux4aAJkxY4ZLO8nvuEF6UuhrTgtEEwBJ9L814/n/ATntyfVSW4AASGqPL71DwAls3rzZGjVq5P48dOhQa9as2SEySg2gX2qVZqd///4uhysNAQRiE9C7pndn+/bt7oO33367de/ePcOT9O7d22bPnm0nnXSSzZ0713cCxtuhpfohSunjTdLwfmfIywEBF1AtHhU5Tq95q8a7du1q+p9awYIF3XvG+xnwB4juZ7vAsmXL0moKKCCh1eZ+TcENpdU566yzXMDEa97fK5WWCqj7NW8Hx5lnnmnaSeK1lStX2vXXX+/+U/WBVI8kvIXuHhkzZkzabsxsh+ECCCSJgFK6Lly40AUO9Tuodkf6tcGDB7t0r0qBpXfryCOP5Ds0ScaQ20hNgWgDIIn8XTaea6fmqNGrRAkQAEmUPNdFIIcFtO1f/4BTGiytyFGeZa9pZZtyu86fP99tVdZKc0380BBAIHoBTbAqDYfq56jdc889aZMqGZ0ldALGbwXr+vXr3U4SXaNXr14uvVZo4/3OSJifI5C+QKQaIPoU7ydPDwLZK7B//367+OKLXS2OkiVLulobSm8V2vQ7qhYVqKlWh2p2eE3pW7VIQO3ZZ59Nq/Xh/Xzp0qVpgc0nn3zSmjRpkvZZLfzRIiFdW4FQpccKndxVALVDhw6uwHrFihVtzpw5vosUsleIsyOQWAEtzunRo4e7iUi7lbVDRO+liqCH7hThOzSxY8fVU1sg2gBIIt/DeK+d2iNI73JSgABITmpzLQQSKKAidJpA1T/0KlWqZH369LHKlSubdn5oK7NW9aillz4ggbfPpRFIegEvFZVutHHjxvbwww9neM+FChVKO0bprRR8VKo6BThat25tBQoUMK2M1Yo6FVVXOh7tFAlPD8L7nSE1ByCQrkB6ARB9kPeTBwiB7BVQHQ599+n3VBUaV7BDdToUHFHQ4emnn3aLAKpVq+Z2f4QWYT5w4ID7ztRiAX1v6rNekEMTt0qbtW/fPtPuD+3yUOqs0KbfgbXCXU01PjTRqx2ZX3/9tSlgorRc2g2mFFya2KUhEDQBLZbTTimlj1NTwFLp4CpUqOACHkp99dRTT9muXbvcIjsFJcuXL8/vuEF7UOhvjgtEGwBJ9O+y8fweneOoXDBlBQiApOzQ0jEEDhWYOXOmKx6pf0z6NaUHUK50GgIIxC5w0UUXmYqfx9I2bNiQdrj+0ahirApm+DWthtWkT7ly5Xx/zvsdizzHInCwQEYBEN5PnhgEsl/gjTfesL59+7pghV87/fTTXRBCu0TCm3ZwaKeG0kL6NU3G6ju0ePHivj8fOXKkjRgxwvdnCn7ovjThS0MgqAK7d+92wcUVK1ZEJNDvqnqPlKYutPEdGtSnhn5nt0AsAZBEvofxXju7HTl/MAQIgARjnOklAmkCmnBVfuRVq1bZr7/+6lJdValSxZRCx6sTAhcCCMQmoILnKpAaawsNgOizWt06depUt9p106ZNptQbWglbv359tzJWRVrTa7zfsY4AxyPwfwUyCoDwfvKkIJAzAj/99JNNmDDB3n77bdu6davlz5/frSRv3ry5tWrVyu3wiNT27Nljzz//vC1YsMAFQrQzRIsGLrnkEtMin9Bdl37nUH2RiRMnupSx2nWp+gWqCaKV7zVr1swZAK6CQBILaIfWm2++aa+++qpL+ar3RO+kUixrd5Tq8RQtWtS3B/yOm8QDy63lWoFYAiCJ/l023v8fkGsHiRtPGgECIEkzFNwIAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIZJUAAZCskuQ8CCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggkDQCBECSZii4EQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEMgqAQIgWSXJeRBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCBpBAiAJM1QcCMIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCQVQIEQLJKkvMggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBA0ggQAEmaoeBGEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIKsECIBklSTnQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgaQRIACSNEPBjSCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBWCRAAySpJzoMAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJJI0AAJGmGghtBAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBrBIgAJJVkpwHAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEkkaAAEjSDAU3ggACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAlklQAAkqyQ5DwIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCSNAAGQpBkKbgQBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQSySoAASFZJch4EEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBIGgECIEkzFNwIAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIZJUAAZCskuQ8CCCAAAIIIIAAAggERODAgQN22GGHBaS3dBMBBBBAAAEEEEAAAQRyqwABkNw6ctw3AggggAACCCCAQESB/fv329y5c23x4sW2bt0627Fjhzv2qKOOspNPPtnq1KljLVq0sMKFCwdS8ZRTTnH9fvTRR61ly5YxGaxYscLGjBljEyZMOOhzM2fOtHvuucf93VtvvWVlypSJ6by54eA77rjDFi5caLNnz3bPkdq1115rq1evtpo1a9qLL76YVN2IZ5yTpSPTp0+3++67z/1P1jQEEEAAAQQQQAABBGIRIAASixbHIoAAAggggAACCCS9wIYNG+zOO++0jRs3pnuvxYsXt379+lnjxo2Tvk9ZfYOZnRh/+eWXnVnp0qVdcCm0pXoAREGP3r17W/v27Z2B1wiAZPXTefD5/v33Xxek++abb0zPWIUKFbL3gpwdAQQQQAABBBBAIKUECICk1HDSGQQQQAABBBBAINgC27Zts1atWtn27dvtmGOOsRtvvNFq165txx57rOXJk8f083fffdeee+4527lzp0vjNGrUKKtXr16g4DIbAHnqqafs6aef9g2AvPnmmzZ48GDnOGnSJDvuuONSxnTXrl12ySWX2N9//22LFi0yBc+81rNnT/vkk0/sjDPOsKFDhyZVnzM7zknVCTP3znbq1MnOPfdcmzhxYrLdHveDAAIIIIAAAgggkMQCBECSeHC4NQQQQAABBBBAAIHYBB566CGXhqhYsWI2a9YsK1WqlO8Jvv32W2vdurX9/vvvduKJJ9q8efMsb968sV0sFx+d2Ynx9AIguZgjw1v3nqvu3bvb7bffnuHxyXJAZsc5We4/9D7atWtna9eutWHDhgVy11Yyjgn3hAACCCCAAAII5AYBAiC5YZS4RwQQQAABBBBAAIGoBBo2bGg//PCDqxWgmgHptbFjx6btWJgxY4ZVrVo1qmukwkGZnRgPYgBk69atdtFFF5lSMS1dutRKlCiRax6BzI5zMnZw/vz5Lvik2itz5swJVMAyGceDe0IAAQQQQAABBHKLAAGQ3DJS3CcCCCCAAAIIIIBAhgJKQ/TXX3/ZlVdeaVq1n15TjRDVClFhdBW3rl69etrhd999t9tB0qRJE3viiSdsypQpNm3aNPvuu+9c4fRKlSrZNddcYw0aNEj3Gh9++KFNnjzZ1qxZY7/++qsdccQR7rNNmzZ1O1Dy5ct3yOe9mhK33HKL3Xzzzaa6G6+++qpt2rTJVNxdO1Z0X9ddd50VKFDA9/pK1aTPqGbC119/bQcOHLDTTjvNOnTo4CbzY50YD63vEX5BpSRSaqJINUAUkFJgSk3F0f/77z979tlnbfny5a44vVKV1a9f3/X16KOPdsfp3l966SX78ssv3fEyu/7669Nd+a/xfOGFF2zlypX2888/2//+9z9npdRVGivZZ6YNGjTIxo8f7/qgdGnhLVINEC9Y5BVHV3+VGkzpsv744w+XIkyp15SmLbPpwuIdZz2fGjftrJDZvn373POtOhvq79VXX20FCxZM6/LIkSNtxIgRaWMZqdD9Tz/95N4NjZ1SpumZU/vzzz9t6tSppnRpX331lXtXtVurcuXK7pm+7LLLXFo6v6a+XnjhhS51ncbBe6YyM6Z8BgEEEEAAAQQQQCA4AgRAgjPW9BQBBBBAAAEEEEh5AU2iKlCgSVsFHjSxmpkWGgBRaqzXX3/d9zQqzqxAS/ikrXYLPP744zZhwoSIl9e9PfPMM4dMfnsT6l26dLF169a5CX2/ps9rQr1QoUIH/VhBhZtuusk+/vhj38917tzZtPtF7dFHH3UFpjNqWRUAUTBh4MCBLgAQ3k444QQXdOrfv79b4e/XtKtHPuFNzqo/okCPX1PRdtV90e6BWJom3evUqWO//fab6d6vuOKKQz4eTQCkRo0abqz9WtGiRd04KsgTS4tnnOUkZwX10mu6JwUsFBRR27x5swtmKLCh2id6Rv2arFUPRX175513XDBKhrJSUCtSU7BIn40UrOrbt6+98sorLhAyZsyYWLg4FgEEEEAAAQQQQCCgAgRAAjrwdBsBBBBAAAEEEEhFAU2KDhkyxHVNuysaNWrkdgDUqlXL7fSItnkBEAVS9u7d63ZP9O7d2/1fTQJrVfuyZcvc6fzqQqhOwejRo93PL774Yrd7QavqVXNERbT1eQUBdD7t8MifP3/arXkT6poE1or5Fi1auIljTeJrB4rOvWLFCnf8rbfeatopEtq8zytwo90FCnAceeSRptX+stGOEK9FGwDRzhOt1tfODf1PtVW8oJB2oSgAFM0OEPVT/ZLlBRdc4Dy0q2Du3LnulsqXL2/ffPONu2eZqXi9dkxosl67CooUKeIm1EN3vkyfPj0t3Zkm0BX8kavuV8cOHz7ctm/fbiVLlnQBltAC5hk9DxpjTfLnyZPHFeL2dqj4eXs7PbyfeTtAvHHUDiON1emnn+6CAQrQqV6NWmaKe8czzuPGjXMBOjXtRtJuIu3mkJl20ujZ1fPi94x5tTi0i+i1117zJWzevLlt2LDBrrrqKhswYIA7pl+/fu5Z1zvVq1cvF1jSeG7ZssUFCr1z9ejRw42hX/PSYB1++OEuMKjnmoYAAggggAACCCCAQHoCBEB4PhBAAAEEEEAAAQRSRkAT9d26dbO33377oD5pArtixYp21llnuclmTb5r8jVS8wIg+rlWwSsdU+hOC+3wUOBjyZIlbjJ+4cKFbrJeTQXWGzdu7GpGRKpFokl9pRfSSnxdq2PHjmm34k1s6y86depkffr0Oeg2tStBQRVNHOveQndL6D68gIgmnNu3b3/QZzXxrtRbCuKoRRsA8U6SXg2QaAIgCspoBX/ozhxNumtFv+5NTS4PPvjgQfftBSL0l9otcc4557ifK4BSt25d27Nnjwt26f7Ci9krBdfll1/uAk7R1IYJvbB2q+h62p0iW7+W0Q4QfaZatWruPOEpz5R6bd68eS7AoqBWtMGZeMZZz6WCD7/88oudf/75pmCIrh/aFHhT4HDbtm0uNZyef68piKFnS02BKwX2QpsCKAqqqCnIc/bZZ7s/Kwip9FWq46F3J7RpR4nSs61ateqQZzr0ONVj0XirKbB16aWX+o4Jf4kAAggggAACCCCAgCdAAIRnAQEEEEAAAQQQQCClBBRUUM0GpdLZvXu3b980Ea0aBUrjU65cuUOOCQ2AeDUuwg8KTQcUGmzwakZo5b92DYSnqPLOo1XwCl6cdNJJbhLca6Er+zUp7rdzxUsFpNX03kp9ff62226zBQsWuNoX+r9+7Y033nC1T9RyOgASKXXRDTfc4HZrqGmHTNmyZQ+6dY2jF/RQaqVmzZq5n2uC3dth4Pc57yRPPvmkS0GlsVi9erVpB0E0TcEipSFTcEU7VfxaNAGQ0DoYoedQrRMvwDVjxgyrWrVqNLcV1zgraKSgh57fNm3auICgX1NNFpnq/VDNDq9pLBQ4USDOb/eTZ60dS6r54gVXlAZMgSoF5bwASuh1VRNEdXI09vpspKbnQPfgFxyMCo+DEEAAAQQQQAABBAIlQAAkUMNNZxFAAAEEEEAAgeAIqKCzdoIsXbrU3nvvPfvxxx8P6bxqEzzyyCOu+HJo8wIgJUqUSJuY95PT51TTQHURNMmt1qpVK/v0009dqiMvxZHfZ7VjwivUrvvzAh3ehHp6QQwFARTg0eTyF198kXZ6TWZ7tRZUL8OvaXW/JqO1EyCnAyB+Kbt0j0qJNXv2bJfS6P333z/ktnWvSmulFnrPXsBHdppsj9Tk6+060A6UKlWqRPUiaPeDUqApDZaCZX4tmgCInkO/QucqjK6aLGqhO1syurnsHGftovr888/t4YcfdsE1BSMWL1580C2lF2hTsEjBFaWxUjorr3Xt2tW9i2o6RrtEFEhRnZBYmoI2qm9Tv379iHVVYjkfxyKAAAIIIIAAAgiktgABkNQeX3qHAAIIIIAAAggg8P8ElDJKKXY06awJXU1sq2k3wJQpU+zMM89Ms/ICIOedd166hcyVbkrpiLRyXyv41bzJ6VjgtRPAm+D3JtTDUw+Fns9LRaW/U60FNQU2lGpJLVKxcO8c2v2igFBOB0D80nLpnjxvv8l2755Vc0It9J5VK+Szzz6Lhdrt5NAEfEZNOyW89E133XVXWqAi/HPRBEAUEAtPf6Xz6HlU/Q21SDuNwq+XleOsZ0D3oLow33//vasxoxosSkvmNb8x0c4Q7RBRCw0offTRR67uh1p4eiydt23bti4NltdUO0bvjlJyKYjojXF6Y6O6NgooKY2aarrQEEAAAQQQQAABBBBIT4AACM8HAggggAACCCCAQOAEtEtCqaq0C0NNAQGvaLn+25uQVx2EESNGRPTx0liF7tbQzg+too+lha7+jzShHno+vwCI6jUoxZSadpZceeWVEW9BNTG0cySnAyCRrpfZAIhqoWjSPpamcb/iiisy/Eiop2qSqDaJX4smAOIFqcI/n5kASFaMs55/BaOU2kr1N0Kb0oQp8KPC8evXr/fdAfLPP/+4Ojo6T2gqKj132vWkd8B7t0LPrbojSkWm4IjSXYU3XVc7T/Q+RWpK36Y0buntkMpwcDkAAQQQQAABBBBAIDACBEACM9R0FAEEEEAAAQQQSG0BTapqpb3qYniFwDPqsVfj4ZhjjnH1OrzmTchnlGZHaZWUeil0t4YKravgdpMmTUz1EGJtmQ2AaNX+GWec4S537733pu0s8Lu+irRr1X9uD4A0b97c7YDR7p1p06bFSp3u8dEGGnI6ABLvOCt4oWCO3hW1mjVrWu3atV3xcdWjUWBBheS94F6kXTkKCmnn1PHHH+9SW4UWV7/nnnvs+uuvj+irY1VbRe+c6two1ZYXNNT5VBNHNXT8moqoz58/nwBIlj7tnAwBBBBAAAEEEEhdAQIgqTu29AwBBBBAAAEEEAiUgFeXQAEQraxXfY+MmlewvHDhwrZ27dq0w70AyMknn+xWm0dqXiBBRblVl0PNqwuS0aS8Vt57BaJDz0s+1+MAAAxVSURBVJ/ZAIjOoZRdWlmvVEP9+/f3vW0ViVeQRqmUcnsARHUmlixZYuEBrPCOR7JO7/lQEEtOaio636FDB9/DczoAEu84z5kzxwU31PScd+zY0bdfXmH6SAGQ0HRX2u2hmjvt2rUzpbVSiiqNSbRtx44dbkeWUsGpDR482BTc8mtKGab3O9Iuk2ivyXEIIIAAAggggAACwRAgABKMcaaXCCCAAAIIIIBAygu88MILrqC5Wnopi0IhVMdA9QzC6214ARAFKPTzMmXKHOKnmgaXXnqp+/shQ4akFVL3Vsartoh2h5QsWdLX/v7773cpiHRu3buCMGrxBEC8+9Yqel1bk9HhbeXKlWmr82MNgKjQu9Jv+U2KaxJcK//VdG3P7IcffrCGDRu6v8/qFFhjx451k+Vq2gESWscltN9Ku6RjS5Uq5YrVn3DCCVG9D+ecc47t3r3bFAxQoXa/logASDzjPGDAAJs8ebLrinZeKGAY3hQcU4orBYG8HR5+ffdSkKm4vXamPPfcc+5z48aNO+jwTz75xI39pk2b3LUrVqx4yOl27drldqOoKUCjWh9+zQswqmaIxpKGAAIIIIAAAggggEB6AgRAeD4QQAABBBBAAAEEUkJA9Qg0IauJVKXP0eSoJmMjtWXLlpl2ECgdT3hdCG+CWZ9VHZDhw4cftFtD6Xq6du1q77zzjhUrVsxN+HsBjM8//zytxoRqi+g+wgMRH3/8sbVv3968WgqhE8bxBEDef/99u+aaa1yXlQZME9OhTZPUWqXvpT+KNQCiOinDhg2zEiVKuL6HtkQEQFRTQmnK/v77b1dMW/UnwlMnqbi36qHo+ShfvrxLr+S388bvOVFBb+100HOlwI9fS0QAJJ5xVo0NFVxXmz59elraNK9veh+UQs2r4ZHe7hovIFalShU3Bl9++aXv7g3VE6lXr55LcyVTBWHC23vvvZe2y0Z1d/TehTft5FGQREEpvX+qB0JDAAEEEEAAAQQQQCA9AQIgPB8IIIAAAggggAACKSOgSXkFNRRYUNPOA6Wnqly5sh111FG2Z88e++qrr1xaq9dff92UDkoT6CNHjjwoSBEaANF5dIzqfWjngGpnaIJWOynU/III3i4Q/VyFnbt16+buQSvqFXjRZLoCNfnz53c7F0499dS0MYgnAKKTaKfC7Nmz3fk02azzaRJbRc+feOIJ02p8BWTU91gDIFOnTnWptRRAUNBGE98FChRw/UhEAER9DN0FojoWCvrUqFHDTcgrVZICNlu3bnX3PGbMGKtTp07Uz/tjjz1mEyZMcLtZFOTya4kIgMQzznr+unTp4rqi51nPuoJHeh4UGFN/Q9PBKaCkIJBf27x5szVq1MjZKjih3SSq6+G3q0S7g7ygSsuWLV2aNrnqnVy9erWrl6NAiXacaGeUXwo7vbt6n9W026Ru3bpRjyUHIoAAAggggAACCARTgABIMMedXiOAAAIIIIAAAikroMDEAw88YN999126fdSkrYqg33fffW4SP7R5ARDtdKhQoYJpdXp40+fvuusulx4pvCkAo0DBjBkzIt5DoUKFXEBCK+NDW7wBENViUAqhhQsX+l5bE8/qj1J4xRoA2bhxo6vNoMlyr3nnSFQARBPvCkhpd4r+7Nfy5cvnngntBImlLV++3Dp37uw+okLfmpwPb4kKgMQzzto5kV5tm2OPPda0e+mll15y3VVNj+OOOy7i8/TBBx+4n+nZ8FKShR/8+++/O8tIwRQdr0CdAmuhAcHQ8+h+NI56X1U8Xe8QDQEEEEAAAQQQQACB9AQIgPB8IIAAAggggAACCKScgFb/KwCgCex169aZiixrAlYTpqrJUbt2bVezQ4WU/ZoXAFGtC61Gf/75593qddWz0CStaoZ06tQp4ue9cypVkSZtVWtBq9vz5s1rZcuWdbsQVFTbrz5IvAEQXVtpjBYsWOCurbREqumgQI6CHwr6qHZJZgIgOvf8+fPdjhkFmDQRrVRECgIlKgDiWWuHy6RJk9xugm3btjkD1fyoVauWqXC2+h9rU8omjZWen4EDB1qbNm0OOUWiAiDxjLMCRdp5NGvWLPd8KDWaUrgpRZgCH9o5pJ0Z2kElR9Wr8VKrhQN4QQn9vXbjpLfDRp5Ku6U0ZLqu905qJ4p2WWmcihQpEnGYvMBN48aN3c4eGgIIIIAAAggggAACGQkQAMlIiJ8jgAACCCCAAAIIBE4gNACyePHiwPWfDv9/AU20a3eJAikqVk87WECBFAVItFtK6bXC691klZeCJarpo50vqvXiFUzPqvNzHgQQQAABBBBAAIHUFCAAkprjSq8QQAABBBBAAAEE4hAgABIHXop9dOfOnW5XhCbetatIdSto/1/A2wGjHVF9+vTJNprJkye74umq76JaNDQEEEAAAQQQQAABBKIRIAASjRLHIIAAAggggAACCARKgABIoIY7w86qroXSO2X3JH+GN5JkB6xZs8bat2/v7mru3LmZSjMWbZdatGhh69evd4XsL7zwwmg/xnEIIIAAAggggAACARcgABLwB4DuI4AAAggggAACCBwqQACEpyJUQDVAmjZt6naBvPXWW1a8ePHAAqluyC+//GK//fabTZkyxfbu3et2yChNWHa1RYsW2c0332znnnuuTZw4Mbsuw3kRQAABBBBAAAEEUlCAAEgKDipdQgABBBBAAAEEEIhPgABIfH6p+GkVlb/ttttc8fq+ffumYhej6tOgQYNs/PjxaccWLVrUFVMvXbp0VJ+P9aADBw5Ys2bNbOvWrTZnzhxSkMUKyPEIIIAAAggggEDABQiABPwBoPsIIIAAAggggAAChwoQAOGp8BPo2bOnKRAye/bsbE33lMz6SnWlWhx//fWXVa9e3fSuVKpUKdtu+eWXX7Z+/frZAw88YO3atcu263BiBBBAAAEEEEAAgdQUIACSmuNKrxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQCLQAAZBADz+dRwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgNQUIgKTmuNIrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQCLUAAJNDDT+cRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEhNAQIgqTmu9AoBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgUALEAAJ9PDTeQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEUlOAAEhqjiu9QgABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAg0AIEQAI9/HQeAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIHUFCAAkprjSq8QQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEAi0AAGQQA8/nUcAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAIDUFCICk5rjSKwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEAi1AACTQw0/nEUAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBITQECIKk5rvQKAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIFACxAACfTw03kEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBFJTgABIao4rvUIAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAINACBEACPfx0HgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACB1BQgAJKa40qvEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBAItAABkEAPP51HAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCA1BQiApOa40isEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBAItQAAk0MNP5xFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQSE0BAiCpOa70CgEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBQAsQAAn08NN5BBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRSU4AASGqOK71CAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQCDQAgRAAj38dB4BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgdQUIACSmuNKrxBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQCLQAAZBADz+dRwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgNQUIgKTmuNIrBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQCLfB/AIQj/RNa3Dh9AAAAAElFTkSuQmCC\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=FIGSIZE)\n",
    "plt.hist(age_fake, 99)\n",
    "\n",
    "plt.yticks(range(0, 3500000, 500000), [x for x in range(0, 3500000, 500000)])\n",
    "\n",
    "plt.xlabel('Spend time (in days)')\n",
    "sns.despine()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### True spends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "def age_dist_true():\n",
    "    query = \"\"\"\n",
    "      MATCH ()<-[:SPENDS]-(i:Input)<-[:TX_INPUT]-(tx:Transaction)-[:IN_BLOCK]->(b)\n",
    "      WHERE b.height >= 900000 AND b.height <= 1200000 AND i.mixin > 0 AND i.anonset > 1000\n",
    "      WITH i, b.timestamp as ts1\n",
    "      MATCH (i)-[:SPENDS]->(o:UniqueSpend)<-[:TX_OUTPUT]-(:Transaction)-[:IN_BLOCK]->(b:Block)\n",
    "      RETURN ID(i) as inId, COLLECT(ts1 - b.timestamp) as times\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_age_true = age_dist_true()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "age_true = list(itertools.chain.from_iterable(df_age_true.times))\n",
    "age_true = [x / (24*60*60) for x in age_true]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img src=\"data:image/png;base64,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\" width=\"800\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=FIGSIZE)\n",
    "plt.hist(age_true, 99)\n",
    "\n",
    "plt.yticks(range(0, 3500000, 500000), [x for x in range(0, 3500000, 500000)])\n",
    "\n",
    "plt.xlabel('Spend time (in days)')\n",
    "sns.despine()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit Distribution to Ground Truth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "def spendTimes():\n",
    "    query = \"\"\"\n",
    "      MATCH (i:Input)<-[:TX_INPUT]-(tx:Transaction)-[:IN_BLOCK]->(b2:Block)\n",
    "      WHERE i.mixin > 0 AND (i)-[:SPENDS]->()\n",
    "      WITH i, b2.timestamp as ts\n",
    "      MATCH (b1:Block)<-[:IN_BLOCK]-(:Transaction)-[:TX_OUTPUT]->(:Output)<-[:SPENDS]-(i)\n",
    "      RETURN ID(i) as iId, ts - b1.timestamp as timeDiff\n",
    "    \"\"\"\n",
    "    df = to_data_frame(graph.run(query))\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_spend_times = spendTimes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_spend_times.loc[df_spend_times['timeDiff'] <= 0, 'timeDiff'] = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "log_spend_times = np.log(df_spend_times.timeDiff)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "shape, loc, scale = scipy.stats.gamma.fit(log_spend_times)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gamma Distribution\n",
      "Shape: 19.54, Rate: 1.61\n"
     ]
    }
   ],
   "source": [
    "print(\"Gamma Distribution\")\n",
    "print(\"Shape: {}, Rate: {}\".format(round(shape, 2), round(1/scale, 2)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}