{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import datetime\n",
    "import cudf\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from cuml.ensemble import RandomForestClassifier\n",
    "from cuml.metrics import accuracy_score\n",
    "\n",
    "import whylogs\n",
    "from whylogs.viz import ProfileVisualizer\n",
    "\n",
    "import warnings\n",
    "warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "heart_data = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/processed.hungarian.data\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This dataset encodes missing values as `?`, so we will replace them with `np.nan` temporarily and then fill them with the median value for the column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "heart_data.replace(\"?\", np.nan, inplace=True)\n",
    "heart_data.fillna(heart_data.median(), inplace=True)\n",
    "heart_data = heart_data.astype('float32')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset does not come packaged with a header, so we will add that next.\n",
    "\n",
    "More information about the data (including the header labels we'll add) can be found in `heart-disease.names`:  \n",
    "https://archive.ics.uci.edu/ml/machine-learning-databases/heart-disease/heart-disease.names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "heart_data.columns = ['age', 'sex', 'cp', 'trestbps', 'chol',\n",
    "                      'fbs', 'restecg', 'thalach', 'exang', \n",
    "                      'oldpeak', 'slope', 'ca', 'thal', 'target']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we will convert this object to an NVIDIA CuDF that works in the GPU."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "</table>\n",
       "<p>293 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      age  sex   cp  trestbps   chol  fbs  restecg  thalach  exang  oldpeak  \\\n",
       "0    29.0  1.0  2.0     120.0  243.0  0.0      0.0    160.0    0.0      0.0   \n",
       "1    29.0  1.0  2.0     140.0  244.0  0.0      0.0    170.0    0.0      0.0   \n",
       "2    30.0  0.0  1.0     170.0  237.0  0.0      1.0    170.0    0.0      0.0   \n",
       "3    31.0  0.0  2.0     100.0  219.0  0.0      1.0    150.0    0.0      0.0   \n",
       "4    32.0  0.0  2.0     105.0  198.0  0.0      0.0    165.0    0.0      0.0   \n",
       "..    ...  ...  ...       ...    ...  ...      ...      ...    ...      ...   \n",
       "288  52.0  1.0  4.0     160.0  331.0  0.0      0.0     94.0    1.0      2.5   \n",
       "289  54.0  0.0  3.0     130.0  294.0  0.0      1.0    100.0    1.0      0.0   \n",
       "290  56.0  1.0  4.0     155.0  342.0  1.0      0.0    150.0    1.0      3.0   \n",
       "291  58.0  0.0  2.0     180.0  393.0  0.0      0.0    110.0    1.0      1.0   \n",
       "292  65.0  1.0  4.0     130.0  275.0  0.0      1.0    115.0    1.0      1.0   \n",
       "\n",
       "     slope   ca  thal  target  \n",
       "0      2.0  0.0   6.0     0.0  \n",
       "1      2.0  0.0   6.0     0.0  \n",
       "2      2.0  0.0   6.0     0.0  \n",
       "3      2.0  0.0   6.0     0.0  \n",
       "4      2.0  0.0   6.0     0.0  \n",
       "..     ...  ...   ...     ...  \n",
       "288    2.0  0.0   6.0     1.0  \n",
       "289    2.0  0.0   6.0     1.0  \n",
       "290    2.0  0.0   6.0     1.0  \n",
       "291    2.0  0.0   7.0     1.0  \n",
       "292    2.0  0.0   6.0     1.0  \n",
       "\n",
       "[293 rows x 14 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cu_heart_data = cudf.from_pandas(heart_data)\n",
    "cu_heart_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above is our first view of the data as a CuDF on the GPU using NVIDIA's RAPIDS toolkit. \n",
    "\n",
    "For simplicity, we'll choose the first 200 rows as training data and the remainder as batches of testing data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train = cu_heart_data.drop(\"target\", axis=1)[:200]\n",
    "y_train = cu_heart_data[\"target\"][:200]\n",
    "\n",
    "X_test1 = cu_heart_data.drop(\"target\", axis=1)[200:231]\n",
    "y_test1 = cu_heart_data[\"target\"][200:231]\n",
    "X_test2 = cu_heart_data.drop(\"target\", axis=1)[231:262]\n",
    "y_test2 = cu_heart_data[\"target\"][231:262]\n",
    "X_test3 = cu_heart_data.drop(\"target\", axis=1)[262:]\n",
    "y_test3 = cu_heart_data[\"target\"][262:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to CuDF, we will use CuML to train a random forest classifier on the `target` variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "RandomForestClassifier(split_criterion=0, handle=<cuml.raft.common.handle.Handle object at 0x7f5fc4a229b0>, verbose=4, output_type='cudf')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cuml_model = RandomForestClassifier(n_estimators=40,\n",
    "                   max_depth=16,\n",
    "                   max_features=1.0,\n",
    "                   random_state=1095)\n",
    "\n",
    "cuml_model.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point, we want to log the data that we've used for training and testing with WhyLogs.\n",
    "\n",
    "To do so, we first create a WhyLogs logging session using `get_or_create_session()`. For logging, we can create a new empty profile and track our CuDF directly from the GPU data structure.\n",
    "\n",
    "In this example, we will do this all from memory instead of writing to a file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARN: Missing config\n"
     ]
    }
   ],
   "source": [
    "session = whylogs.get_or_create_session()\n",
    "profile = session.new_profile(dataset_name=\"cudf-example\")\n",
    "profile.track_dataframe(cu_heart_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One output from WhyLogs is a summary object that can be exported as a Pandas dataframe."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ca</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>exang</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.303754</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.460665</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>sex</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.723549</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.448007</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>thalach</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>138.976109</td>\n",
       "      <td>82.0</td>\n",
       "      <td>23.436071</td>\n",
       "      <td>71.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>175.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>target</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.361775</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.481336</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>trestbps</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>200.0</td>\n",
       "      <td>132.583618</td>\n",
       "      <td>92.0</td>\n",
       "      <td>17.626568</td>\n",
       "      <td>31.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>chol</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>603.0</td>\n",
       "      <td>250.716724</td>\n",
       "      <td>85.0</td>\n",
       "      <td>64.714639</td>\n",
       "      <td>153.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>212.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>277.0</td>\n",
       "      <td>358.0</td>\n",
       "      <td>518.0</td>\n",
       "      <td>603.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>cp</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.986348</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.965049</td>\n",
       "      <td>4.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>oldpeak</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.588055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.909554</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.5</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>fbs</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.068259</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.252622</td>\n",
       "      <td>2.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>thal</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>5.965870</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.502251</td>\n",
       "      <td>3.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      column  count  null_count  bool_count  numeric_count    max        mean  \\\n",
       "0        age  293.0         0.0         0.0          293.0   66.0   47.894198   \n",
       "1    restecg  293.0         0.0         0.0          293.0    2.0    0.211604   \n",
       "2      slope  293.0         0.0         0.0          293.0    3.0    1.962457   \n",
       "3         ca  293.0         0.0         0.0          293.0    0.0    0.000000   \n",
       "4      exang  293.0         0.0         0.0          293.0    1.0    0.303754   \n",
       "5        sex  293.0         0.0         0.0          293.0    1.0    0.723549   \n",
       "6    thalach  293.0         0.0         0.0          293.0  190.0  138.976109   \n",
       "7     target  293.0         0.0         0.0          293.0    1.0    0.361775   \n",
       "8   trestbps  293.0         0.0         0.0          293.0  200.0  132.583618   \n",
       "9       chol  293.0         0.0         0.0          293.0  603.0  250.716724   \n",
       "10        cp  293.0         0.0         0.0          293.0    4.0    2.986348   \n",
       "11   oldpeak  293.0         0.0         0.0          293.0    5.0    0.588055   \n",
       "12       fbs  293.0         0.0         0.0          293.0    1.0    0.068259   \n",
       "13      thal  293.0         0.0         0.0          293.0    7.0    5.965870   \n",
       "\n",
       "     min     stddev  nunique_numbers  ...  ununique_str_upper  \\\n",
       "0   29.0   7.738385             37.0  ...                 0.0   \n",
       "1    0.0   0.449050              3.0  ...                 0.0   \n",
       "2    1.0   0.207620              3.0  ...                 0.0   \n",
       "3    0.0   0.000000              1.0  ...                 0.0   \n",
       "4    0.0   0.460665              2.0  ...                 0.0   \n",
       "5    0.0   0.448007              2.0  ...                 0.0   \n",
       "6   82.0  23.436071             71.0  ...                 0.0   \n",
       "7    0.0   0.481336              2.0  ...                 0.0   \n",
       "8   92.0  17.626568             31.0  ...                 0.0   \n",
       "9   85.0  64.714639            153.0  ...                 0.0   \n",
       "10   1.0   0.965049              4.0  ...                 0.0   \n",
       "11   0.0   0.909554              6.0  ...                 0.0   \n",
       "12   0.0   0.252622              2.0  ...                 0.0   \n",
       "13   3.0   0.502251              3.0  ...                 0.0   \n",
       "\n",
       "    quantile_0.0000  quantile_0.0100  quantile_0.0500  quantile_0.2500  \\\n",
       "0              29.0             31.0             35.0             42.0   \n",
       "1               0.0              0.0              0.0              0.0   \n",
       "2               1.0              1.0              2.0              2.0   \n",
       "3               0.0              0.0              0.0              0.0   \n",
       "4               0.0              0.0              0.0              0.0   \n",
       "5               0.0              0.0              0.0              0.0   \n",
       "6              82.0             87.0             98.0            122.0   \n",
       "7               0.0              0.0              0.0              0.0   \n",
       "8              92.0            100.0            110.0            120.0   \n",
       "9              85.0            129.0            167.0            212.0   \n",
       "10              1.0              1.0              2.0              2.0   \n",
       "11              0.0              0.0              0.0              0.0   \n",
       "12              0.0              0.0              0.0              0.0   \n",
       "13              3.0              3.0              6.0              6.0   \n",
       "\n",
       "    quantile_0.5000  quantile_0.7500  quantile_0.9500  quantile_0.9900  \\\n",
       "0              49.0             54.0             59.0             65.0   \n",
       "1               0.0              0.0              1.0              2.0   \n",
       "2               2.0              2.0              2.0              2.0   \n",
       "3               0.0              0.0              0.0              0.0   \n",
       "4               0.0              1.0              1.0              1.0   \n",
       "5               1.0              1.0              1.0              1.0   \n",
       "6             140.0            155.0            175.0            185.0   \n",
       "7               0.0              1.0              1.0              1.0   \n",
       "8             130.0            140.0            160.0            180.0   \n",
       "9             244.0            277.0            358.0            518.0   \n",
       "10              3.0              4.0              4.0              4.0   \n",
       "11              0.0              1.0              2.5              3.0   \n",
       "12              0.0              0.0              1.0              1.0   \n",
       "13              6.0              6.0              6.0              7.0   \n",
       "\n",
       "    quantile_1.0000  \n",
       "0              66.0  \n",
       "1               2.0  \n",
       "2               3.0  \n",
       "3               0.0  \n",
       "4               1.0  \n",
       "5               1.0  \n",
       "6             190.0  \n",
       "7               1.0  \n",
       "8             200.0  \n",
       "9             603.0  \n",
       "10              4.0  \n",
       "11              5.0  \n",
       "12              1.0  \n",
       "13              7.0  \n",
       "\n",
       "[14 rows x 32 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "summary = profile.flat_summary()[\"summary\"]\n",
    "summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On each batch of inference for our model, we should also log the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "profiles = []\n",
    "\n",
    "# Model inference\n",
    "output1 = X_test1.reset_index(drop=True)\n",
    "output1[\"pred\"] = cuml_model.predict(X_test1)\n",
    "\n",
    "# Log using WhyLogs\n",
    "profiles.append(session.profile_dataframe(output1, \n",
    "        dataset_timestamp=datetime.datetime.now()-datetime.timedelta(days=2)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's repeat this process for our remaining batches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inference and logging on second batch\n",
    "output2 = X_test2.reset_index(drop=True)\n",
    "output2[\"pred\"] = cuml_model.predict(X_test2)\n",
    "#output2 = output2.to_pandas()\n",
    "profiles.append(session.profile_dataframe(output2,\n",
    "        dataset_timestamp=datetime.datetime.now()-datetime.timedelta(days=1)))\n",
    "\n",
    "# Inference and logging on third batch\n",
    "output3 = X_test3.reset_index(drop=True)\n",
    "output3[\"pred\"] = cuml_model.predict(X_test3)\n",
    "#output3 = output3.to_pandas()\n",
    "profiles.append(session.profile_dataframe(output3, dataset_timestamp=datetime.datetime.now()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to profiling and logging the data, WhyLogs also provides a convenient visualization module that works best on multiple dataframes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<whylogs.core.datasetprofile.DatasetProfile at 0x7f5fc41fedc0>,\n",
       " <whylogs.core.datasetprofile.DatasetProfile at 0x7f5fc41fbb50>,\n",
       " <whylogs.core.datasetprofile.DatasetProfile at 0x7f5fc41b7250>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2juysJgCYPX26R/uYOG4soiIj5fd/tH2/O9uiLb8zdXo9vv7v//DR597/nqmqqsbjzz3vFDQ5Ki07g5ff+gdEL18zuoot23fgkcVPuwyaHGm0Wny/5Ce8+MabLn+3HD56FG+8857LoMkVoyRBFH3zM3EwK8tp2ZDBns0oPFtXh0effhb/+3mpfNDkgjeH6MHDWXjmlVdlZw/aWrl2HZb/vtLtNt/9uAQvvfmWbNAkx2g0YsOWrfjb40+itOyMx2P21BCZGUy1Z8+i6NRpnz8WERERERFRezFsIq9kjhrlcgbR4SNtP2FmmQERCLbs2On1SZ/2+PaHH01ljTywZsMGbHXRwP5cUlB4Am+89z40Go3X99VotXjz/X96HQit2bDRo+2MRiO++u6/Xo/rXKNWq/Hz8hWdPQyfKzp1CsUlpa1uZzQa8fa/PsA/P/nMo/1WVlVjxarV7R2ek6rqanz4+b99vl+LjVu34otvvm1T0LNmw0b87+elsuu0Oh3eev9fUKs9+xnfuWePxyf4vXU0Rz7QjoqMRP++fWTXOVKpVBiaIV/2Sq6fU1e2ev0G2Zku7mRlZ+NMuWcXaBQWFWHLjh1tGVqnyjqajXc++BA6NxckuLLv4CF86CLE+/aHH12Gnf6g1elwUiZI7uNiJqbdfbVavPD6Gzh+4kRHDM1qybLlHr9P+n7JTy7fO6xcuw7//ennNoWx5ZWVeOGNN9DY1OT1fd3p0ysVCpmZWMfcXPBARERERETUWVhGj7wSFBSEvr17I//4cad1ZeVtv6KztKxMdubOwAEDMHv6VHRPSECQKghNzc0or6jAydOncTQnV/Yq1msuuwxzzFebf/LlVzhx8qTTNo/c/1d0i4lxWh7XrZvHY46KjMTFc2ZjUFoaBEHAmfJy7NyzV/akQHtIkgSFQoG5M2dg7OhRUCpVOJqTg+UrV1n7Ndj64ptvMWn8OCiVSp+OQ07/vn3x0lOLAQD7Dx3Cj78sc9pm1rSpmDVtmtPy7gltK+0lSRL+9emnss89JCQEl86dg6EZGVAIAo7k5GDFqtVO2+p0Ovzr08/w5osvtFpOx1ZwUBAWXDwPwzIyoNZo8NPy5SgodD6JlpWdjZraWsTFxnr/BLuQ9z76WLZvlyO5fie5x/JlT7qOHD4MUydNQlxcHBQKAU3NzThzphwnTp3C0Zxc1NTWOt3njkWL0NzcDAB4/d13UXvWeaaO5Tj0l8Fpabh03lyEh4Vh285d2LBlq9M2tqHUtAsvwJRJE6FWa/DT8hWyr0ubtm3DNZdfJvt4EeHhGNCvHwYO6I/4+DhEhEcgIjwcYaGhMBgMqGuox8lTp7Fu02anmUy79u5F2Zkz1nJacd26Wb9ehSdP4tMvv3J6vDEjR+LqyxY6Lbd93ayvb8BHX/xbdryD0gZgxpQpSOrRAxqtFjnHjmHVuvVOP4v/XfITJk8Yj1497Utb/r56DUrPyP9OGZqRjrkzZiA2thvKzpRjxcpVOF1S0mEzXCsqnXu4AUDv1FSv9tM7NRU79+x1Wt7azK2OIAgCEnv0wMD+/dGvb29ER0WZjqmIcCiVSmi1OlRVV+NIdja27dzlFHYs/fVXjM/0rl8PAKT2TMGCefOQlNgDJ08X45v//SD7Wr5p6zZMv7ClHGlXfA2wpTcY8O5HH8vO4uzVsyfmzJiOlORkGI0ijp8owm+r1zhdtLJu02ZcOHEiRo8cYV2m0+mQl+8cKvRMTsa82bOQnJSEkJBgqNVqVFRV43RxMY7m5noUiHvq1OnTsjPNUnu23p9wyTL535EAEBkRgVnTpyF94EBERkSgqbkJhUUnsXPPXpwq9myWpKMpkyfhggkTEBwchA2bt2CLzMU3zWo19uw/gCmTJ9ktrz17Fp9//Y3sfhPi47HwkovRJzUVao0aO/bsxeZt251ec0rLzuC/P/2M22V6mLZVaGgoEhISUOHwflfudwgRERHR+cK2x7ht3/RziaUnrWO/c2/Z9q111bO9q7PtDeyqj7G/+Or7ci5j2ERei+3mHNIAQH1D22f7yM0UCgkJwYuLn0CwTLNwi5KyMmzdsdOu10FKchJSkk0nVcPD5ZvQD+jfr12/jFKSkvDC4iecwoRLL5rb5n2683/33G3X02P0iOEYM3IknnzhRacZBdU1Ndizfz8mjhvXIWOxFREejiHpplI6rkrOJMTHW7fxhX0HD6KwyPkki0qpxPNPPIZBaWnWZaNHjsCEsZl4/NnnnU4CFhadxL6DBzF29GiPHlepVOKZx/5u91xGjxiOvz2x2OmkuCRJKCgsxPjMTG+e2jmlXuZnOimxB575+6NuA77CopM4cPiQ3TLbXkYqlfzMSl8eY60ZnJaGF596EiqV6Vfo2NGjUVp2xmVpvcsuvQS33niD9fMRw4bijvvudwrjLA3tI8LD7ZanJCfh608+aj0YnWwq1/bw4qftFkuShINZR6xhU1BQkPXrJRrly5XFxES3+jX95bffZGceXXrRXKceSpPGj8OFEyfiiedfsCsXZpQk/PjLMjxwz5/ttv997Tr5pzh+PB6+/z7r12LE0KGYdsFkPP7c87KvC75Q39AguzwqyrN+NdbtXZTRs/S0Cg0N9XpsbXXDtdfgpj9c1+p2F82aicjISPy+Zq3d8txj+VBrNAjzYswD+vXDi4ufsD7PkcOGoVdKCp599TWnbR0Diq72GuBo/abNqKxyDiUnjhuLh/96n93FH+MzMzFjyhQ8vPgpp/c+/1u61C5samxqkg1Rn3n87+juphdbVXU1tu7c5fI9kDfKK+RL0yXExbm9X1NzM5b99rvsuoEDBuDJh/+GmOhou+UTx43DDddcjX0HDyE42Ls+nDf/4TpcubCl1POYkSMBQbD2ArSVf/y4U9j0y6+/yc6OSuzRA68/96xdf6qJ48ahf58++OKbb522X7V2Ha657DKP+1l5Ij4u1ilscvV9ISIiInLF9oQ9YLqo5csP/omQkBC399PqdLj1z/falUTu7BP+RNR1MWwir7k6ueSq34gnImSaKhsMBpSVl6NPL9elWnomJ+O6K69o8+O21b13/Mlvs1YyBg+SbR4/JH0wpkyaiE3btjutO3j4iF/Cps7gqnzTzGlT7YImi0FpaZg1fRpWrVvvtG7P/gMeh02zpk11OpkZFhaGcZlj8MuvvzltX9EJsxW6ErlG6U1NzaiprUW8m5OU/fv28bg0WWe58bprrEGTxZCMdNmwKSQkBH9weI2KiY7GwLQBOJpjXz5NkiRUVlUjord92GQJ0zUaDfYePIgDhw7jdEkJKiqroNZooNPpWp3VU1hU5OnT89iufc69z8LDw3Hz9X+Q3X5Q2gBkDBqEw0eP2i3fu/8ARKMRSvPzLDtzRrYnnkKhwJ8W3eQUuoWGhmLR9dfj6ZdfaetTccvV77aQENcXQshxFyY1NTf7NWyyfK3PlFdg5549yDl2DCWlZairr4dao4HB4L5vmtFoRNHJU8gYPMjjx7xj0c1Oz3H0yBGIiox0Cl0aGhuhVqsRFtb+sMQf5PoAKgQBf7r5JtlZxkmJPTBhbCbWbtxktzz3WD7q6xusQUVEeDgEQXD6+S4uLnEbNiXEx+PySy9py1NxUnv2rOzy6FbC1oOHs2R71YWGhOCxB//PKWiylTlqpFdjTO2ZgsvnX+q0fOrkybJhk9zv59375d9b3Hjt1bLB0cJLLsaaDRtRXGo/i0yn1+PQkSNOYVZ7yH2tXH1fiIiIiDyl0Wiwc+8+TLvA+XyTrd1793nVe5M6Xlea6UPkiGETec3VL5n2XEHbMzkZ0VFRdleQi6KIBx57AoMHpqFPai8kJyWiZ0oyUlN6IimxR5sfq716Jie77L3RESa4mR0zPjNTNmwqOOFdP6JA4qovy4SxY13eZ+LYsbJhU86xYx4/7pRJ8ieOXF3dbSn51FaVVVUeldcKDw+3u+q/qxiUNgBKpdKu/FJDYyPufuBvyBg0CL1SeyI5KQk9k5PRq2cKEtycOO1KQkNCMDQjw2m5qxKcQ9MHy54wdxVWuzpuNmzZin9/8y3q6us9H6wNV7Nz2qq+oUG2VFdzczOuu+U2r/bV1NyMk6dOW0NGV2W30vr3c/l1Gz50CMLCQj3u8eQNV4GHpz1iLOTKxVmEBLu/mtDX1BoNPvvqP1i/aXOb+wF5c0x1T4hH+qCBsusS4uNlZzc3NTcHTNiUcyzPaZlRkvCn++73aj+SJCE7Lw8Tx5l+n4WEhKBfn95Os/aeffU1pPXvh769eyMlORkpSUlITUlBSnKS3UxvX5ALjAC4nXUOANl5zl8TAJg8YbzPL9a5YMIE2eedEO/Z7+f6+gaUljmX7VQIAsaNkS8XKQgCJozNRPEy59fBnGPHfBo2BQc5f63dvZ4QERERtSY4KAg6vR6btm5tNWzauHWr3X3IPwK15B0RwybyWluvcnVHoVDg6ssWOtXLNxqNyMk7hpw8+1AgJjoaI4YOwcypU+1KzvjDoIHOs2c6Ukpysst1PVPk152ta9sJ6UDg6vjr6fbrJN9b4qxM3w9XXM2wczXlXK7HhTfWbtxkravrztCMdLy4+Ml2PZYrV1+20FSKqBWWspW2oiIjcfHsWVixarXdcr1ej8NHjzrNbkmIj8eo4cMwe/p0lyelu4KkpETrrBBboaHyx0FKkvPXBoDTzCgLubJ2K1atlu2r5I3mZt9eiebrq+pramutYZNjzykLdz/jCoUCyYmJHVJKLypKvvydXEDijqtwRqFQIMwH5c48ZTAY8MxLr7gs++gpbwJ1dzOUXc0QEx1KxHZVao3GpyFnzVn7vnXXXnE5Xnn7HaftCgpPOAWzEeHhGJqRjmkXXIBJ48f5PHjyRm3tWdnlgzvgPZTL388uQlzH19kaF69ncXFxbktFunwP5sV7CyIiIqLOMC5zDLbt3IWDWUdQe/YsYl1cPHm2rg4Hs44AMF3svHWnc09MIiJbDJvIKzqdDkUnT8muS3ZxUtVTCy+5GGqNBj8s/aXVEj519fXYsmMntuzYiTEjR+LRB+5HSCtX2fpKbIx8z6qO4q5Uk6ugoz0lDS0ce0F1Fa5m1rk62Q+YZqPI7suLk6URkc5l4QDIBg/niuSkpHb1Qbn1jzfCaJTw+9q1rZZ5q6quxtqNm7B24ybMmj4N9/7p9k49UepKuIuZFgqFc6kswDTzrD0qq6vx1Xfft2sfAGCUfPvz7OvwqrGpJbhRa+RP3Lc2+6e1WuNt5apc2eniEq/2c6q4WHZ5SnJSu19HvHm9XrFyVbuDJgBezYiSK5VroXTxsxMo2juL1VFjY5Pd5xPHjcO9d9yOz/7zDTQufjYsmpqbsXvffuzetx8D+/fHk4885LZcnSdcvbfS6XRuZ541ufi6hIe17zVRTkSE/D6VSs9+rly9Z3L13qFlvXwQ1aT27TGh0zvPouyo1zsiIiI6P4waPhzZubmoPVuHLdt3YOElF8tut2X7DoiiiG4xMRg5fBjDJiJqFcMm8sruffthcDFjY8TQoe3e/3VXXoG5M2dg09ZtOJh1BMdPnGj16vH9hw7h3998i7tuvaXdj++JoCDvmla3l1brulSTqzIq3pQeMhgMsrMsmpqaZLbufOFhYbLHhEajBVzkgK7KAHkTBLg8GezQP4ZaKJVK3HnrIiy85GJs2rYNh48cReHJolZnAazbuAmpycm4YsF8P43Uc479gny9vaNtO3fJlmsLCwvFDVdfjfGZYxDbrZu1pFV5RQXu+r8H2/WYnnB1cretRLElLHE1k0Crc182qqPKSg3NyHDqrQOYLno4XVKCXj17troPg8Hg1KPLYtCAAR6PxdWMSW9er9dv2SK7fHBaGq654nKk9e+H6Kgoa9j73Y9LPJpl6Y7b4DjAX0Ij2hkoO5L7Hs+ZMQOTxo3Hlh07sP/QIeQfL3Q5A9Aiv7AQ7374ERY/8nC7xtOtm/wv1rr6BrfvNVx9XZp9HMQAbo4vD19/XT0PV+8dWtbL/y6L8HGgViczWz3WxfeFiIiIyBMKhQJTJk3Cst9XYuPWrS7Dpg1bTCX0pk6e5NHFoCdPn8auvfuQnZuH0yXFqKtvgEqpRGy3bkgfNBDzZs/2aKZ7Y2MTflq+HLv27kNlVRXCwsLQp1cvXDRrJi6YOMHj5ymKItZv3oIdu/fgxMmTaGhsRFhoKHql9sTEceMwb9bMVstDy6mrr8eiu+8BAPz59ltx0axZTtu8//En1r8jL5k7B3fesshpm2W/r8Tn//kaCoUCX3/8od05qstv+CMA03nS66++CgBQXlmJu+5/wG4flt5Ntu67607MmjZVduw6nQ6/rlqNLTt2oPRMOQCgV0oKpk+5EPNmz5LtOdua/OPH8fDipwEATz/6iGwFqqdefNla4eaWG2+Q7TH76Vf/wYqVqxATHY1/f/BPt+dTtu7ciVXr1uPkqdPQaDRISIjH+MxMXLVwAaIi7auT1Nc34La/3AeDwYB5s2bh7ttvdft8du/bj5fefAsA8MC997RaatKR0WjE5u3bsXnbDhQWFaGxsRHh4eHo3SsVkyeMx5wZMxDkotqN7Zh/Wr4cu/ftR1V1NcLCwtC3d29cPGcWJo4bh3WbNuO9jz4GAHz0zttI7N7daR+Hjx7FmvUbkFdwHGfPngUEATHR0YjtFoOMwYOROWqkT87lO2LYRB4zGAxYsmy57Lrg4GAMG+Lcx6QtYrt1w+XzL7U2e66rr0d5RQXKyiuQl5+P9Zs2O50AWLdpM277441+D4L8obSszM065x4DANAtxvlKZldX+Gq0WkTKvMgVnTrt4Qj9K7ZbN9mwqaSszGUvr5JS554KgOuTaORbSYk9cN2VV+C6K68AYCqZVl5RibLyMziam4eNW7Y6nWBduXZdlwyb/O14oXz/tTsW3YyZU53fPPqrhGY3FzM8U1NScM+fbvd6f7alGGNkXr8A08+4K0ajEWXl5V4/ridGDB0CQRBkZ+dt3LIVN/3hulb3sWvvPpcXTlj689hyFW5rNPInvz19vdbr9Th12nmGVXhYGJ557FHZk+6thRrnu9DQUISGhjrNOgoPD8eTD/3N6/11T5CfSRcZGYGL58zGxXNmAwAam5pwprwC5RUVKDhxAus2bnIq1bjv4CFUVlWhe0KC1+OwSOwu/3u1uqbGbf/M2NhussuPFRyX/WO8M7nquVdTUwO1RuMyAC8plX9N8vV7i6qaGqdlPWT+mCQiIiLyxvQpF2LZ7ytRWHQSp4qL0Ts11W796eISFBYVWbc94aLKkUVWdrZs8GEwGFBWXo6y8nJs2LIVVy1c4PZvqNPFJXjqpZftSrfrbMrx7z98GEMGt16Bpay8HC+98RZOl9hXpGhobER2bh6yc/Owcs1aPPnwQ7KtAdyJiY5Gr549cbqkBFlHc2Tf3x7JyWm5nZ3jtN52eb8+fdpdFcUTZ+vq8MwrrzpVrMovLER+YSEOZmXhsQcf8LrKTP9+/RAeFoZmtRpZ2dlOYZPeYLCrrnEkO1s2bLJ8zYakD3YZNBmNRrz1/r+webt9//rSsjNYuuJX7NqzFy89vdiuNGR0dBTGZ47B9l27sXnHDtx2041uQ8b1mzcDMF1AN0nm73V3Ghob8dIbbzn1iK9vaMCR7Bwcyc7Bb6vX4KlHHkGP7vJ/p504eRLPvPyqXc9unV6PQ0eO4NCRI5g7cwYGD3TffuLz/3yNZb+vdFpu6g9fhWMFx7F+02b85+MPvXp+nmDYRB77/OtvcOKkfD+Mi+fM9vnVvRYx0dGIiY7GoLQ0TLtgMvr37Yv3P/7EbhudToeSsjL07d3bbrmrF8iuWiJOzq59+6zBm6Pd+/bLLk/r199pWVio/JW7lVVViHQocaTRaLD3wAGvxumvr3X6oIGy5ah27d2LzFHy/YV27t0ruzxj0CCfjs2Xrr/6KuvVK+eauNhYxMXGImPwIMycOhXxsbH4389L7bYpr6xEc3Oz0xsuV8eZaDSekyUN610EFAP69ZNd7upYd6WtP7fRUVFITUlBsUOQe6a8HEmJPRAXG+vxGERRtLt6amB/59cvwNSjpqa2VnbfR3JyfNo3x1Z8XBzGZ47Brr37nNYtX7kKs2dMR3Jiosv7q9VqfPX9f2XXdU9IkO2L5mqmRWVVlezyLTt2uHx8W64Cr+SkJNnH1BsM2HfwkEf79peu+BowZPAg7D902G5Zc3MzgoODkdZf/mdVjuPPgjuRERFI698Paf374YKJEzB6xHA89eLLTtudOHmyXWFTn16pUAiCU9nE4tISDM1Id3m/IYMH41eHnn2AabbmH6+71mVfgM4QHR2FlOQkpwt4jJKEPfv3Y+pk5ysZJUmSfU0AfPveQqPRoKq62ml5vz59fPYYREREdH7q37cvevdKxanTxdi4ZStuvv4Pdus3bjXNauqdmor+ffu2GjYZRSNCQ0KQOXoURgwdgp4pKQgPC0NdXT1OFRdjxarVqKyqwpJly5GSlIRZ06c57aOpuRnPvPKqNWi6cOJEzJg6BTHR0Sg9U4Zlv/2OdRs34VQrF9vV1NbisWeew9m6OoSFhWLuzJkYOWwousXEoKm5GQcPZ2HFqtUoPXMGz776Gt566QWvz2kOzUjH6ZISHM11DpKqa2pwprzC+vnpkhLU1dfblbiWJAk5eXkA4PHF+/GxsXjn1ZdRcLwQ75nPi9535x1IG2D/N3R8XJzs/V95+x8oLinF/IvmYtyYMYiMjEBJWRn+9/NSFJeUYs/+A1izYYPXF4cpFQqkDxqE/YcO2YVsFvkFx+0qkWTnHXP6+62xscn6fR2W4frr8d2PS5B7LB8TxmZixpQL0T0hAWfr6vH7mjXYe+AgysrL8fl/vsbf7vuL3f3mzJiB7bt2o7m5GTv37pV9jw+YZhTt3W86Hzpl8iSvZr6JRiNeeP1N5OXnAzAdI5fOnYse3bujprYW6zZtwq69+1BcUoqnXnoJb7/8ktOFbY2NTXju1desQdO0CyZj2oUXIDoqGmfKy7F85SqsXr8BRadc/zzu2X/AGjT17d0b82bPQmrPFISHhaNZ3YyS0lIczDqCvPz2l9eXc+6dmSOfq6mtxWvvvIvfVq+RXR8ZEYErXIQh3vjw8y+Qe+xYq71dXPUskCs35+pqVNsX/a4uJ++YU2IPALnH5JcDwKgRw5yWuTrZZJkWbevf336HRi/L6IW56Jl0psK3X+vxmWNkl6/ftBnHZPqQHCsowDqZElgAMHb0aJ+OjVo0NDbi06/+4/YXoIXLn2m58nEuf6Y7ZlZLZ3P1fLOOZjstO5KTg+UyV660Zf+evEbK/SwaRBHvfPCRy75LFjqdDrv27sPzr72OH39ZZrcuOSkJiT2cZ0wYjUZ8/p9vnH5HaLVafPlt+/tauXPtFZfLLtfpdHjulddczrqqr2/Ai2++hXIXr4N/uOpK2TKmrl6vt+7YCb1DT8OtO3fikLlpb2tc9aApKS1FTW2t3TJJkvDZl/+RPdHdmbria8D4zEzZ5e9//EmrM8NEUcShI0fwxrvv48PP/+20/qvvvsfBrCyIrQTA3rw38kZoaCh6OVzlCqDVkw2jRgyXPd40Wi1eeesfqK9vkLmXyaEjR2Rf4zrS+DHy7y2++d+PsmNd9tvvTmE7YCq1PHKY83uwtio6dVr2ffGgNM/LbxIRERG5Mv3CCwEAm7Ztt7vgUJIkbNq23bzNBR7tq1+fPvj0/Xfx8F/vw0WzZmFYRgb69+2L0SNH4LJLL8G/3noDI4eb3id9/9PPsu9v//vTz6g2z+r+43XX4qG//gWZo0YirX8/TJ08Ga888zRGDR+OfBcVQCz+9ennOFtXh4T4eLz90ku49cYbMGbkSPTv2xfDhwzBTX+4Di8/vRihISEor6jA0hW/evQcbVkCotqzdSgusX9fmJVtei/bOzUViT16QJIkp7LqJ06esl4MODTd9UVctlQqFfr06oUePVpmuffo0R19evWy+3C8oNyi4Hghnv77I/jTopsxcvgwDOhn+rq+/PRT1uolv69Z59FYHFm+HsdPFDmdD7AEUCOHD0NwcDCam5txwjxrznYbywVuQ92ETbnH8nHjtdfgsQcfwMRx4zCgXz9kjhqJJx76G0YNHw4A2L57j92sIAAYNXyYtTrAuk2bXe5/49at1vYxs6dPb+VZ21u1dp01aJox5UK88OQTmDxhPNL698P4zDF47MEHcPVlCwGYzrk4XnQNAN8vWYLas6a/IW+58QY8cO89GDPS9DNw4aSJeOnpxRifmYljBcddjmPbzl0ATOcVXn7mKcybbfl57INhGRm4aNYsPPp/9+OdV50vVvQFzmwiq5Oni6FUKCFJEpqam1BZVY0jOTnYe+Ag9Hq97H0UCgUe+utfXJZU8sa6TZuxcu06xERHY/iQIejTuxeSkxIRER4BlVKJhibTVNeVa+Vf+OLinK92d3XC7rP//AdXLViAhIR4a3PybjExXk+d9Zd3PvgIOXnHkDlqFJRKJbJzc7H895Wysw/i4+IwTuakyeCBA7B7n/NVuMt++x16vR4TxmaiuVmNdZs2telKdldf6x27duO/KSkYNGCAXUPrIemtT3uWkzlqFPr16eM0y84gilj84su4dO4cDBuSAQECjubmYsXKVbJ9xvr26Y2xo0e1aQzni7IzZ5Cdm+fRtinJSXavAwaDAStWrsKKlauQEB+P4UMyTG+0EnsgIiwcgkJAfX0DDhw+jPWbnXvIqFQqRMs0tu+eEC8bYL374cdYMO8idOsWA4WgsG7bniv6u4I+vXph5x7n2Upffvc9qmpqMCwjHYCAg4cPY+W69TA4BBGtcfX1ycvPxxfffIvhQzIQbtN/ZOCA/tZypZddegl+W7PW6ST3oSNHcMd992Pm1Cno16cP4mJjIRpFNDQ2objEVIrhSE6u9cqmNJmZTPNmzcSX3zkHSFt37kRdfT1mz5iOuG7dUFZejhUrV8nOdvSlAf364erLFjoFY4CpPMMDf38cUy6YbL1arrm5GbnH8rF+8xan0mYWY0ePcllHe3CafB3zvIICPP/q65g/7yIoFArsP3gIK9d5/sdAeHg4uickOM2Q0mi1eOK5F3D5/EuQlJiIs2frsHrDBpd9pjpTV3wNmDVtKpYsW4bKKvtgrujUKdz1fw9i6uTJSB+YhjjzFYZNTU0oKSvDiZMnkXU0G03Npj5GM6ZOcdr3rr378NPyFQgPD8fwIRno16cPUpKTEBkRgeDgYDQ2NqGgsBC/rVkrOza590beGjl8GE6etr96NCfvmIutTSLCw7Hg4nn4YekvTuvyCgpw70MPY9b0aUgfmIaIiAg0N6tx8vRp7N63DwWFJ3DfXXe2e9zeWHjJxfht9RroHN7vlldU4G9PPokFF1+MPr1SoVZrsHPPXmzatk12PxfNnIHo6CifjSs7z/l3cGy3GKeZ/ERERERtMe2Cyfj6+/+iuqYGR3NyMXzoEACm8m5V1dVQCAKmetivprX3QEEqFW654Xo88NgTqKyqwomik3ZVAPR6PdabQ4C+vXvjSpmy+iqVCn+580+4+/8edNlP/uTp09ZKPXfecrPL0s/9+/bFxXPn4OflK7Bu02bceO01Hj1PC9vZN0dycpDaM8X6ueXvqGEZGdDqdSivqMCR7BxMnjDeZhtTAKMQhDafH/PWJRfNxfAhQ5yWR0VGmv+mWY6iU6fQ1Nzs9UyvYeaqB6IoIicvz66Ch+XrMXr4cBiNRmQdzcaR7By7cwFHc3OtY+nTy/liNwvL3+aOBEHAZZdcbLpQTxSRl59vd1GgIAiYNW0qvvtxCbKOHEVldTW6xzuXMF9ncwx6U6UCAH5bY5qkER0VhTtvWSRbCvD6a67Gzj17UVxaijXrN+CGq6+ynmPR6XRYb54Q0L9vX1wm00tNqVDgnj/dhoOHDzv97WJRW3cWADCgX1+XF2sCcOpt5SsMm8jq0y+/8mp7hSDgz7ffak2OfaWuvh5bd+7E1p07Pb5P3z69ZV8kBg9Mky3jUlxSinc+/Mhu2YypU3D/3Xd5P2A/EEURv69Zi99dnEyydeuNN8iW4blw0iR8898fnErhAPB43+707tULYWGhTqWsDKKI735c4rT90m+/btPjCIKAe/50G554/kXoHGa+aLVa/LR8BX5avsLtPoKDgnDP7be7bTZIwI+/LJM9uS7HXQPKqupq2Rl07owZOVK2JNbggQOxZ79zice8/HzrFSQWto00A9WFkybih5+XOv3c6vV6LF3xq9MVWHI/g+5ERUbKlo8CgF9+/Q2//Pqb3TLbxpMx0dG485ab8e6HHzvdt7GpSbY+sKcumTsHazZsROkZ53FlZWdbrxTzpxuuuRrFpaWy4Z9Or8e6jZtczqJ0lNa/Hx649x6X6welDUBSYg/ZGWaWWuVtNXXyJNn+i2Xl5fjgsy+clnt7THW0rvgaEBQUhL/ccQeee+11p/5zWq0WazZswJoNG9r1GM3Nzdi1d5/L0m1yoqOiXAaX3hifOQbLfvvdbtmp4mKnUiCOrlq4AAcOH0ZB4QmndQ2NjW26grSjxMXGYtEN1+MTmffClVXV+Pw/rb9nSU5MxHVXXenTcWXJ/KyPHT2G71+IiIjIJ+Lj4jBsyBAcPnoUG7dutYZNlhJ6Q4dkIEHmXJsn9Ho9ztbVQaPRwiiZLpS2/bO26NQpu5P5x0+csFbYmTHlQpflsxPi4zFqxHDsPXBQdr2l3URISAgyW6lmMzR9MH5evgI1tbUuwwdXusXEWEvLH8nOwbzZLaXnLL2Yhg3JgFanw7qNm5zKy1k+79unt8uZSL42zU1waFuqv7yiEv37ele2eUC/ftZetkeyc6xhk8FgQK757zTL1yPraDaO5OTYtQyxfM2GZqS7fa87dfIkl+ttn8OZikqn9bOnT8N/f/oZRqMRGzZvcapgUlB4wnqRnavzW67U1NZaZ7hdMHGCy9L4SoUCM6dNxVfffY/GpiYcP1GE9EGm/kvHTxSh2XIh4pQLXT7PbjExGDVihOyEAqClJ+3RnFyUlZe7LfvfEVhGj9qkW0wMHn/ob5gzY0ZnDwVKpRJ33Hyz7LoJmZluT4QEgvkXzfW4h8OcGdNx4aSJsusSu3fHPHNj8dYEBwXZXXHhiSCVCjMudL4quyMMHDAAf/vLvXYzpTwVHByMB+69hyVourCwsFAsuuEPsuumX3gBgs1XfZwPevXsiYvnzvFo2+DgYNx3p/ezAea243V85tSpuOXGG7xuINqakJAQPPiXexAW5voqHFsZgwe57PXkKwqFAg/f/1dctXBBu/YzPjMTzzz2d7dXigmCgEXXX+/xPmdMudDjba+YP9/j2T4ZgwbhkjmeHX/+0lVfA0YOH4b7/3yXVzW9O9rtN98kW6bRW0PT09E9wf4Pb0mSZEM/W6GhoXjy4Ydc9pjrai69aK7sVZKe6J6QgCcf/ptPrw5Uq9XIkmkmPe1Cz64uJiIiIvKE5W+J7bt3Q6vTQavTYcfuPQBayux5SqPR4MdfluH//v44rrv1dtzx1//DfY88ivsffQz3P/oYHnz8Ceu2jhUgbGfSO/YgcjRwgOvzOQXmEntarRZX/fFmXH7DH11+vPD6m9b7nTX3ifKGpYepbd+mmtpalJWXQxAEDM1Ix3BzeTlL3ybA9F7aUkXGXX8iX0tNSXG5LjKyJfBSa9Re71upVCLDHJrYBmv5xwuh1WoRHhaGfn37WsvtZefmWUspNjY14aS5ekVrX4+enj4HtfNziI+Lw+gRpgkT6zdvdipXbZlZp1KpMM3D8pEWJ0+3VFsZ5Ob4BOxLYttWaTlV3PIz0NrfUO5mXU03/0w3NDbi/kf+jjfefR/rNm5CmczFvB2BYRN5JToqCldfthDvv/6az0uQeXMFgUWP7t3x1KMPu2xSHRISggfu/bPLPhWBYMK4sXj0//6K6CjXU5IFQcCCi+fhz7ff5nZft954AyaMle8tYZHYvTuefuxRZI4a5fVY/3jdNV5PM22rCWMz8cbzz3k13XjwwIF47blnMWn8uA4cGQGmX85tKa/Zp1cvvPTUYvRMTpZdnxAfjz/ffpvHAey54LY/3ihbXstWbLcYLH74IQxow8/fgovnIXPUyNY3dOHySy/BC08+4fWVT6EhIZh2wWRMHDdWdn1a//54+tFHW72SbuK4cVj88EMIDun4k/xKhQI3/eE6vPjUk17P6u2ekID7/3w3Hv/bAx5duTZp/Djc9Idr3V7VFRoairtvuxV/8GL2TmRkBJ5+9BGX5SQsMkeNxOMPPeiTsMKXuvJrwNTJk/HGC8+5fE/iikqlwoSxmbJXzyUkeP/eKCY6Gn/7y71ur1z0hqnkhHMD5+27drd6324xMXj12adxzeWXIdzF1X3yj+nVEH3mj9ddi8cefEC2b5wchUKBaRdMxlsvveD2D9+22L1vv1Np1JSkJI9r+hMRERF5YuL4cQgJCYFarcHuvfuwa+9eNKvVCA4OxmQvzp2UV1bi/kcfw9f//R+KTp2Sbftgy7FSjW3f8G6tXDTeLcb1esdePZ6S6xndGkswYtu3ydJ7tFfPnoiJjkZCfLxT36aiUzb9mvwYNrm7YNv2787WvneuyPVtsgRPQ9IHQ6lQYFBamqlvk1pt7dt0NCfXpl+T+/e6IW7+7re9CNbVc7BMmjhTXmHXNkKv12PzdlOfsvGZY9yeg5XTaP5+Amj1XFiszXrb+9n+DMS4OcYBIMZN2cqRw4bhzlsWITg4GDq9Hlt37sR7H3+CPz/4EG7/y3344LPPnVqT+FLXOoNAnU6hUEClUiEkOBgREeGIiYpGjx7dkZqSgozBgzBk8OAOO/H0r7feQElpKbLz8nC8sAinS0pQUVWFhsZG6LRaqFQqhIaGokf3BPTt3RtjRo3E+DFjWh3PqOHD8c5rr+D31Wtw+OhRlFdUQq1Wy5aT66rGZ2bi3dfSsHr9Buzetw/lFZXQaLWI7dYNwzLSMW/2LAzyoFROUFAQHnvwAWzbuQsbtmxB/vFCNDU1ISIiAr1Se2Ly+PGYNX0aQoKDZcs3tSY8PBwvP/0U1m/egp179ph/gTZ53UfGU71Se+KlpxbjWEEBdu7Zi5y8YyivrLS+WEdERKBHQgIyBg/ChLFjkTF4UIeMg5xFRUbii3+9j6JTp5Bz7BiOnyhCSWkpKquq0dTUBJ1OB1VQEMLDwpDYowf69+2DcWNGY/SIEa2WB5oxdQr69+uL39esRXZeHqqqqqHWaGSbqJ8LlEol7r/7LkydPBmr1q1HXn4+GhoaTMd39+6YOC4Tc6ab+oSUVzpPFfdk/0889Dds27kLm7dvR2HRSTQ0NLis/ytnSPpgvPXSiziam4u9Bw4iLz8f5RWVaGpqgt5gQGhICGKio9EzJRl9e/fGsIwMZAwe1OoskPRBA/He669i1dp12L57N0rLzkCr06FbTAwGp6VhxtQp7QrK2mpoejqGPpaO08UlOJiVhaO5uSguLUVDQyOamppk64f36tkTUydP8upxrlq4ECOHDcOKlatxNDcXZ+vqEBwUhMQe3TF29GjMmz0LcbGxXn/fU3um4B8vv4SVa9dhx+49OF1aCr1ej24xMejXpw+mT7kAk8aN67Klurrya0Dv1FS8uPhJFBadxM49e5CXX4DSM2VobGqCVqtDaGgooiIikJKchD69emFoRgaGZaS7LLPw7GN/R2VVFY7k5OJ4YSFOFZegvLISDQ0N0Gi1UCgUCAsNRXx8HPqkpmLUiBGYNG4sQt3U5m6LebNnYcmy5XY9PA9mZaGmthZxse77QqlUKtx47TW4csF8bN25C0dzcnH8xAnUNzSgqakJwSEh6BYTjfjYOAzNSMeYkSNke7n5y4SxmRg7ZjT27NuHA4ezkFdQgNras2hqaoIqKAhRkZHomZyMoRnpmDJpUqvBbVvJ9TO89KK5XfbnkoiIiAJTWGgoJo7NxKZt27Fx61ZrqbsJYzNdvkeV849/fYDyykoIgoCZ06ZiyqSJSE1JQUx0tLUnjdFoxJV/NFUmcnzvbvdpK+933L3tt4QMid274/GHHvR4/JZy8d6wDUYsfZuO2PRrshg2JMOub5MldBIE4Zy6kGhouuk52/ZtsoRNlq9HkEqFwQPT7Po2WfpXRUZEdHhv0nFjRiO2Wwxqz9Zh3aZN1u/hrr37rGHP7OnOF9p5pR3Hr69cMncOJk8Yj83bd+BQVhZyjuWjubkZ1TW1WLVuPVav34CrL1voda8yTzBsOg+1tVdOW9x/911e9UHqmZKCnikpmOPj6nyJ3bvjlhtv8Oo+s6ZN9bpGpyNvvtatfa26xcTg2isud6op2hYXTJyACyZOcLtNW59/UFAQLpo1ExfNmunV/dpzXA5KS/MobPPEJ+/+w6vtfXGcdDZvn7OnBEFAvz590K+PdzNePNGnVy/cfdutXt3n+quv8rh/S2L37l4dk94eB96+NgLA6BHDrVO+XfF23BYKhQJTJk/CFC/DEEdD09N9/mY5LDQUl8+/1K6es5wXFz/p08f1RK/UnuiV2hMLLp5nt3zvgQN46c237a6m2n/oEN7/5FOvv+9p/fvj/+652+02bfm+h3r4dfXm52b4kCFej6Ot37eu9hrgqH/fPl7P9nOle0ICZky50Ktyib7WLSYGs6dPs+vvaDQasWbDRlx35RUe7SMsLAxzZkzHnBnT2zQGb1832/M9VCoUmDhuHCaOa/9M6LaMo6y83KlfU0x0dMC/3yAiIqKuafqUKdi0bTsOZh1pWeZFCb3iklLk5B0DYOrb+cfrrpXdznbmhqMomxJoZ+vqXFY7AdzPXrKUNT5bX4/UlJQOrYgQFxtr7YFs6dtkCU4ss3wAU9Bi27fJ8m+f3r3sSr8FuoED+iM0JAQarRZHsnMwYuhQ5B1r6ddkMSwjw65vU8vsJ/f9mnxBqVRixpQp+Gn5CmzftRt33LIIYaGhWLfJ1H85Pi7O6yomABBpU067tZKMZ+vrZO9nWwGlrq6+lZ+BBpfrLLrFxGDhxfOw8OJ5MBqNOHHyJHbu2YvfVq9BU3Mzflj6C9L692+1Apa3WEaPiIiIyIfGjh6Nu25d5LR8w+Yt+Oq77zthRETtd/VlC536Zf2+Zq3dbCfyjRUrVznNwL9iwXyfz1gjIiIiAoARw4Yitls3iKIIURTRLSYGo1q50NHWqZKWvjMXTnJ9AePxwhMu1/Xp1ct6u+B4odvHy3ezvn/fvgBMPZtyjh1zux9fsMzmOZqbg5raWpSeOWPt12Rh27fpbF2ddWZTW/s1ddWZ7kqlEoNt+jYVFBZCY9OvycK2b1N9QwOKTp6yW97R5syYDkEQoNFqsX3nLlRVV+OQOWidOXVKm3pS9+mVar197Phxt9vmF7Ss753acr9ePVtuF5xw/bMCAAVufpbkKBQKDOjXDzdeew2ee+Ix6/JtO3d5tR+PHsvneyQiIiI6z100axauWrjAaflPy1dgxcpVnTAiovaJj4tzmsV3tq4O68yNdMk36urrsW7jJrtl3RMScMmc2Z00IiIiIjrXKRUKTJ9yIYKCghAUFIRpF14ApRcn3I1iS0UHnU7rcruV69a5XDegXz/rzI6NW7e5LJFdXVODg1lZLvczPnOM9fbPy1e43M5XLAFJ7dk6rFxren6Wfk0Wtn2bflu9xtqvaZiXvV4tbC8AM+g7pm1FW1kCtOMnirBn/wEALf2aLGz7NtleZNXWr4e3kpOSrGHgus2bsWHLVhglyVoCsi3iYmOR2tPUw3X7rt1Qq9Wy24lGo7VcdmREBAb062tdl9a/H8LDwwEAG7dsdfkzcLauDgcPH27TOAH7n7X6htZnSHmLYRMRERFRB/jjdddi2gWTnZZ/9p+vsXXnzk4YEVH7XH35ZYjt1s1u2Q9Lf+HsJh/6efkKaLT2J2luueH6VnvcEREREbXHouv/gB++/AI/fPkFbvWyDUVyUqL1tlzfScA0I37X3n0u9xEUFGQ90X/i5En8vOJXp21EUcQ/P/nMbV/wgQMGWMug7Tt4CN/9uMTt2MsrK7F5+3a327gz3GY2zopVqwHIz1iyhFKWbQRBwJA2lqC3fT9eVlHepn10FMtzF0URv5vDN8evh6VvE9Dy9YgID+/wfk225kyfDsA0u+pX8xiGZqQjOTHRzb3cu2TOHACmi8c+/vIr2bDov0t+wumSEtMYZs6w9jMDgODgYGvp9MKiIvzy2+9O9zcajfjXp5+77bG9dcdOaHU6l+sLCgutJS0Te3jfq6w17NlERERE1AEEQcBf7roTvXulQqezfzN4prwCer3e7s0lUVcXFhqKL/71fmcP45x2y403eN1nlIiIiKgz9e/bF717peLU6WKsXLsOTc3NmHbBZMR264aq6hps2roN23fvRsagQW5L21135RXYtnMXqmtq8NV33+PEyZOYMeVCxERHo7TsDJb99jvyCwsxsH9/5Be6LqX317vvxN+eWIzas2fx359+xoHDhzFr2jT06dULwcFBaGhoRNGpU9h/+DCyjmZjwthMTJ3sfJGgJ+JiY5GcmIiy8nI0NzcDkC8HZ+nbZNmmd2oqoqOi2vSY3RMSEB8Xh+qaGvyy4jfEx8ahZ3IylErTnJJuMTEICwtr077ba+CA/ggJCYFWq23165F1NNu6zZD0wW0qX9dWk8aPwydffoXGpiacrTP1UJo1bVq79nnR7FnYtG078vLzsWHzFlRWVeGSOXOQ2KM7as+exdqNm7Fzzx4AQFJiD1x7xeVO+/jDVVdi+65dqD1bh39/8y1OFBVh+oUXIjo6CmXl5VixchVyj+Vj4IAByDeX6xNgX1bxy+++xweffY7xYzMxND0dKUlJCA0NQUNDI7Lz8vDb6jUATKX15syY0a7nLIdhExEREVEHCVKpcNXChZ09DCIiIiIiog4hCAL+789/xlMvvoTGpiZs2b4DW7bvsNumT69eePj++3Dbvfe53E9EeDie/vsjePqll1F7tk52P7OmTcWQ9HTkf/Sxy/3Excbi1WefwevvvIv8wkIcKziOYwWu++iEtzOYGZqRjrJy0wwjx35NFsMdApf29ie6+rKF+OiLf6O8shIvv/W23br77roTs9pYDq69VCoVBqel4fDRowCA8PBwu35NFo7Pv639q9oqODgYUy+YbA1ewsPDMXnC+HbtU6lQ4MmH/4aX3ngLOceO4Uh2Do5k5zhtl9ozBU898gjCZPqxRkVG4qlHH8EzL7+Kuvp6bNq2HZu22c+8mzl1iulnwBw2BQc7X8Da1NyMDZu3YIOLmYbBQUH48+23Ia1/v7Y8VbcYNhERERERERERERFRm/Tv2wdvv/wilvyyHPsOHUJtbS3CwsKQlJiICyZOwCVzZntUFrh3airefe1V/LR8BXbt2YvK6mqEhYaiT69emDNzOqZOnuxRz9Ae3RPw2vPPYtfefdi2cyeOFRzH2fp6iAYDIiIikJyUiMEDB2L8mDEYkj64Xc992JAMrDX33HTs12SREB+PpMQeOFNeAQCygZQ3Lp4zG91iYrBq3XqcOHkSjU1NEEWxXfv0lWFDMqxh05DBg2T7fw1KS7POgAKAoX4OmwBg+oUXWsOmKZMmIsQHZaujIiPx4lNPYvP27di8bTsKi06isbERYWFh6NO7FyaPH28qn6dyHcn069MH7732KpYsX449+/bL/gws+32ldXvHsPSlp57EwawjOJR1BKdLSnC2rg6NTU0ICQ5GUmIiRgwbiotnz0Jijx7tfr5yBMlVtykiIiIiIiIiIiIiIqJzyJoNG/HPTz4FALz23LMYlDagk0fkufc//gRrN25CfFwcPnv/3c4ejh3/FUMkIiIiIiIiIiIiIiLqROs2mWaj9e6VGlBBk1anw+59+wEAg9PSOnk0zhg2ERERERERERERERHROS/32DHkHssHAMybNauTR2OvrLwcrgrRiUYjPvz8C9Q3NAAAZkyd4s+heYQ9m4iIiIiIiIiIiIiI6JxUUVkFvUGP08Ul+OLrbwAAMdHRmDVtaiePzN7/fl6K/OPHMWXSJAwaMAAxMdHQ6XQoOnUaq9dvQGFREQBgxNChGDt6VKeOVQ7DJiIiIiIiIiIiIiIiOic98fwLqKyqslt2xy03IyQkpJNG5FpxSSm++3GJy/UZgwbhob/+BYIg+HFUnmHYRERERERERERERERE57SwsFD0Tu2Fay5fiLGjR3f2cJxcvXABUpKScOjIEVRWVqGuoQGiKCIqMhJp/fvhgokTMWXSRCgUXbM7kiC5KgJ4jrv8hj96tN3QjHS8uPhJt9vsP3QIq9dvQP7x46irb0BMdBQGDhiAuTNnYMzIkR49jlarxW+r12D7rt0oKy+HwWBAQnw8MkePwvyL5qJ7QoJH+yEiIiIiIiIiIiIiIvInzmxqB0mS8MFnn2P1+g12y6tralFdsxc79+zF3Jkz8Ofbb3M7ra2svBwvvPYGSsrK7JYXl5aiuLQUazZsxIP33tMl6zASEREREREREREREdH57bwPm+bNnoWL58x2uT7UTd3Gb/73gzVo6t+3D66YPx9JiT1wprwCP69YgcKik1i9fgNioqNx47XXyO5DrdHgxdfftAZNc2bMwJTJExEcFIys7GwsWbYczc3NeP3d9/Dqs0+jb+/eXj/HAwcOwGg0QhAEqFTn/beciIiIiIiIiIiIiOi8ZjAYIEkSFAoFRvugrOB5nzzEREejT69eXt+v7MwZ/LziVwBAWv9+ePGpxQgJDgYADBwwAOMzx+CJ519AQeEJ/LR8BWZOm4rkxESn/Sxd8SuKS0sBAIuu/wOuWDDfui590EAMHzIETzz/ArRaLT776ms8/+TjXo/VaDQCMM3E0uv1Xt+fiIiIiIiIiIiIiIjOPZb8oL3O+7CprZb9vhKiKAIA7li0yBo0WYSEhOCORYvw6NPPQBRFLP99Je68ZZHdNgaDAStWrgIApPZMwWWXXuL0OOmDBmL29GlYtW49srKzUVB4Amn9+3k1VkEQYGnNFRQU5NV9ifxNkiQYDAYAgEqlcluCkqir4fFLgYzHLwUyHr8UyHj8UiDj8UuBjMcvBToew9Relokpvjp2GDa1gSRJ2L1vHwAgNSUFgwemyW43eGAaeiYno6SsDLv27sMdi262+8YdyclBU3MzAGDmlClQKBSy+5k5dSpWrVsPANi5Z4/XYZNKpYJer0dQUBBGjBjh1X2J/E2n0yErKwsAkJGRgWCHIJeoK+PxS4GMxy8FMh6/FMh4/FIg4/FLgYzHLwU6HsPUXocPH4Zer/dZ6x35dIPcKq+oRHVNLQBgaEa6220t66tralBRWWm3Ljs3z2a7DJf7SOvfz9o7KifvWJvGTERERERERERERERE1BHO+5lN23ftxpYdO1BVVQ2FUonYmBikDxqImVOnYvjQIbL3KS4tsd7umZLidv+pNutPl5QisUePlv2UlNrsJ9nlPpRKJZISE1F06pS1v1NbSJIEnU7X5vsT+YNtXzH2GKNAw+OXAhmPXwpkPH4pkPH4pUDG45cCGY9fCnQ8hqm9LK13fOW8D5tOl7QER9DrUabRoKy8HBu2bMWEsZn46913ISI83O4+VdU11tsJcXFu958QH2+9XV1Tbb8f8+ehISGIjIhoZT9xKDp1CnX19daSeN4yGAzWqZVEgSA3N7ezh0DUZjx+KZDx+KVAxuOXAhmPXwpkPH4pkPH4pUDHY5i6gvM2bAoJCcH4MaMxYthQ9ExOQWhoKOob6nE0Jxcr165DQ2Mjdu3dh5fefAvPPvZ3u7qFarXaejs0NKTVx7HeT6O1W6dWa8z7CPVovC370bQpbCIiIiIiIiIiIiIiIvK18zZs+uz9d2VnE40aPhyXXjQXz736GgqLTlrDp/nzLrJuo7OZltha86ygoJb1jiXsLPvxpAFXkKolXGprKTyVSoUMN72hiLoCvV5vvRojPT2dwSoFFB6/FMh4/FIg4/FLgYzHLwUyHr8UyHj8UqDjMUztlZOTA4PB4LP9nbdhk7uydd1iYvDI/ffjLw8/AoPBgF9XrbYLm4JtfnBb+2bo9S3rg4OD7dZZ9uPJN1RvaAm4HPfjKUEQ2nxfos4QFBTEY5YCFo9fCmQ8fimQ8filQMbjlwIZj18KZDx+KdDxGKa2EATBp/tT+HRv55CkxB4YNXwYAKCsvBw1tbXWdWFhYdbbGofSeI602pb1YQ4l98LCQs370LQ6Hvv9tF52j4iIiIiIiIiIiIiIyB8YNrmR2rOn9XZ1TY31dnxcnPV2lc1yOVXV1Tb3i7dbZ9mPRqtFY1NTK/sxPU5MdDSnRBIRERERERERERERUZfBsMkdSZJd3MsmhCopLXW7i2Kb9b16prjZT5nLfYiiiDPl5QCA1JQUl9sRERERERERERERERH5G8MmN06XlFhvx8XGWm8n9uhu/fxoTq7bfWTn5gEA4uNi0aN7d7t1GYMHW28fzclxuY+CwhPQmMvopQ8a6OHoiYiIiIiIiIiIiIjOP5IEGIxAvRGoEwG9/LwS8iGGTS6cKa/AoawjAIDEHj3sSucJgoDxmWMAmGYu5eUXyO4jL7/AOrNpfGamU8OtYUMyEB4eDgBYv2ULJBczqdZv3my9PXHc2DY+IyIiIiIiIiIiIiKic4dtqFRuAE7qgXwdkKMHcgzASQNQKgK1RsDIwKlDnZdh0+59+yGKosv1Z+vq8No778Bg3uaSObOdtllw8TwolUoAwCdffgmtTme3XqvT4ZMvvwQAKJVKLJg3z2kfQSoV5l80FwBQXFKKpSt+ddom91g+1m7cBAAYmpGOgQMGePIUiYiIiIiIiIiIiIjOCZIE6FsJlSqMQIMEGAAoAYQACAMQar6/sVOfwblP1dkD6AyffPkVPvxcxKTx4zB4YBp6JHRHcHAwGhoacCQnByvXrkNDYyMAIGPwIFwyd47TPnomJ+PySy/BkmXLUVB4Ao898yyuXLAASYk9cKa8Aj8tX47CopMAgMsvvQQpyUmyY7li/qXYunMnSsvO4MvvvkdZeTmmTJqE4OBgZGVn48dflkEURQQHB+P2m27quC8KEREREREREREREVEnkiTAIAFqAGojoJEAnQToAdhOHxFgCpSUMIUcCpvlgmD6VwFTwGRfb4w6ynkZNgFATW0tfl21Gr+uWu1ym0njx+HeO/6EoKAg2fU3XnsNztbXY93GTSgsOok33nvfaZvZ06fhxmuvcfkYYWFhWPzwQ3j+tTdQeuYMVq/fgNXrN9htEx4WhgfuvQf9+/bx8NkREREREREREREREXVNvg6VLB+Wzy0dbTQSwOp5/nFehk33//kuHM3JRV5+Ps5UVKChoRHNajVCQ0KQEB+P9EEDMWPKFKQPGuh2PwqFAvfdeQcmjRuH1es3oKCwEPUNDYiOikJa//64aNZMZI4a2ep4kpOS8NZLL+C3NWuxfdculJ0ph0EUkRAXh8xRIzF/3jz06J7gq6dPRERERERERERERNThJAnQS4AGHRsqUec7L8OmYRkZGJaR4bP9jR09CmNHj2rXPkJDQ3Hlgvm4csF83wyKiIiIiIiIiIiIiMgP2hoqCbYfDJUC2nkZNhERERERERERERERkXcsoZKl/J2WoRKZMWwiIiIiIiIiIiIiIiIrS6jUDEDjJlSyhEUMlYhhExERERERERERERHReUguVNJKgAHtC5UUNuvo/MCwiYiIiIiIiIiIiIjoHMZQiToawyYiIiIiIiIiIiIionOANVSSALVkX/7OaLOdbagUZF7GUInag2ETEREREREREREREVEAkQBAFQQhPAKVUECvdx8qqcz/AgyVqGMwbCIiIiIiIiIiIiIi6oJcz1QKQnDGCABADQCFxFCJOhfDJiIiIiIiIiIiIiKiTiSZQyS1B+XvlACUkGBobgYkCeER4VBAwVCJOhXDJiIiIiIiIiIiIiIiP/A2VHI1UwkSoNFpAaMRIRFhCBIYKlHnYthERERERERERERERORDllCpWQI05g+9m1ApCKawCPCs/J0REuq1GgDmQIohE3Uyhk1ERERERERERERERG3Q0aGSy5lKUgc8GaJ2YNhEREREREREREREROSGZC55p7YJlXQSYEAHh0pEAYJhExERERERERERERER7EMl255K3oZKlhCJoRKdLxg2EREREREREREREdF5haESkW8xbCIiIiIiIiIiIiKicxJDJSL/YNhERERERERERERERAHNEio1m/speRoq2QVLDJWI2oxhExEREREREREREREFBF+GSo7BEkMlorZj2EREREREREREREREXYpkDpPUDJWIAgLDJiIiIiIiIiIiIiLqFEabnkq2oZIegGSzHUMloq6NYRMRERERERERERERdShLqNRsBDQwBUpyoZISpqAoCC2BEcBQiairY9hERERERERERERERD4hGgEdWkIlrQTo3YRKwXA/U8k2WGKoRNR1MWwiIiIiIiIiIiIiIq8wVCIiWwybiIiIiIiIiIiIiEgWQyUi8gTDJiIiIiIiIiIiIqLznFyopJMAAxgqEVHrGDYRERERERERERERnScYKhFRR2DYRERERERERERERHSOEY2AFoCaoRIR+QHDJiIiIiIiIiIiIqIAJZrDJI0RUMMUKDFUIiJ/Y9hERERERERERERE1MV1RKiksNmGoRIRtQfDJiIiIiIiIiIiIqIuwhIq2Za/0zNUIqIujmETERERERERERERkZ8xVCKicwnDJiIiIiIiIiIiIqIOYgmVmo2AFgyViOjcxLCJiIiIiIiIiIiIqJ1sQyUNTP2UPAmVAPvgyDFUUli2YahERF0YwyYiIiIiIiIiIiIiD3VkqMRAiYgCFcMmIiIiIiIiIiIiIgeiEVCjpaeSTjJ9iHAOlZRgqERE5zeGTURERERERERERHTeEgE0Gp1DJYPNNgJMIZElWHIMlRRCyzYMlYjofMSwiYiIiIiIiIiIiM5pkgQYpZaZSs1QQtV/MITgYBQgyJos2YZKIWCoRETkKYZNREREREREREREdE6QJECUTDOULDOVtDY9lVooIASHQDKKCIEEhTlWYqhERNQ2DJuIiIiIiIiIiIgooHgaKgkwzVJSwH6mEiChWasBJCOCQ4KhFBgqERG1B8MmIiIiIiIiIiIi6pLaGyq5mqkkSRKamhoAACFRkVAyXCIiaheGTURERERERERERNSpOipUcjVTSZQ68MkQEZ2HGDYRERERERERERGRX1hCJTVaQiWdi1BJAVOw1J5QiYiI/INhExEREREREREREfmUN6GS40wl22BJYe6l5BgsMVQiIupaGDYRERERERERERFRm9iGSs1GQIvWQ6VQm2WWfxkqEREFNoZNRERERERERERE5JYlVGqGaaYSQyUiIrLFsImIiIiIiIiIiIgAuA6VdBIg2mzHUImIiGwxbCIiIiIiIiIiIjrPOIVKEqCD61BJCSDIZpklM7KESo7BEkMlIqLzC8MmIiIiIiIiIiKic5RjqKQxz1LSw3WopIIpMLIsBxgqERGRewybiIiIiIiIiIiIApwkAQYJUIOhEhER+V+nhE1Fp05hx+49yM3PR11dPdQaDWZNm4prLr8M2bl51u3iYrshOSmpM4ZIRERERERERETU5fgiVBIEhyAJDJWIiKh9/Bo2NTY24V+ffoade/ZYl0kw/UJrbGyEIAj4/OtvcKKoCADQp3dvvP3yi/4cIhERERERERERUafriFDJNlhiqERERL7kt7DpbF0d/v7Ms6ioqITkZrtZ06fik38XAQBOnjqFU8XF6J2a6pcxEhERERERERER+ZMkAXoJ0IChEhERBS5F65v4xuvvvodyc9Ak2Hw4mpCZCdisO3DosH8GSERERERERERE1EEkCdAZgXojUG4ATuqBfB2QowfyDMBJA1BhBBokwABTqBQCIBRAmPkjRACCBdO/IQIQZv4IBxAuAKHm9SoBUAoMmoiIyH/8MrNp74EDyM7NswZIlplNcr/v4uPikNSjB85UVEAAkHMsH5dd6o9REhERERERERERtY9lppKl/J3Ww5lKthdnc6YSEREFGr+ETVu277D7PGPwIFx92UI8/9obsoFTr9RUnKmogASgpLTUH0MkIiIiIiIiIiLymCVUagagcRMqWcIihkpERHQu80vYlJtfAAGmGU3dYmLw9KOPICQkxOX2MdHR1ts1tbUdP0AiIiIiIiIiIiIZcqGS1lzqrj2hksJmHRERUaDzS9hUV1cHwPQLdMSwoW6DJgBQKltaSWm12o4cGhEREREREREREUMlIiKidvBL2GQrSNX6Q9bUnrXeDm4lmCIiIiIiIiIiIvKUNVSSALVkX/7OaLOdbagUZF7GUImIiEieX8KmqKhIVFfXQAJQWFTkdludToecvDxr2b3oqEg/jJCIiIiIiIiIiM4l3oZKKvO/AEMlIiIib/klbOrbuzeqqmsAAEUnT2Htxk2YPX2a7LZffvc9GpuarL/UB/Tr548hEhERERERERFRAGKoRERE1Pn8EjaNGj4cew8ctM5W+tcnn2LDli122xw+mo37H30Mp4uLrdsJAEaPGOGPIRIRERERERERURcmmUMktQehkqWfEkMlIiIi//BL2DRz2lR89+MSNDc3W4OknNw8wHwbAE6dPm29bfndHhUVhamTJ/ljiERERERERERE1AUwVCIiIgo8fgmbwkJDceeti/D2Pz+w/tKXHLaxDZoss5ruvGURgoOD/TFEIiIiIiIiIiLyI0uo1CwBGvOH3k2oFISWC5QZKhEREXUtfgmbAGDq5Mk4W1ePf3/zLSRJgqvf9xIAQRBwy4034IKJE/w1PCIiIiIiIiIi6gAMlYiIiM59fgubAGDhxfOQPjAN3y/5CYePHIVoNNqtVygUGDl0CK6/+ioMSkvz59CIiIiIiIiIiKgdJHPJO7VNqKSTAAMYKhEREZ3r/Bo2AcCgtDQ89egjUKvVKDhxAvX1DQCAmJho9O/TB+Hh4f4ekp1/f/sdlq741fr5808+juFDhri9z/5Dh7B6/QbkHz+OuvoGxERHYeCAAZg7cwbGjBzp0eNqtVr8tnoNtu/ajbLychgMBiTExyNz9CjMv2guuicktOt5ERERERERERH5giVUaoACiqRUKEJCUQgVRL13oZIlRGKoREREFPj8HjZZhIWFtRri+NuJkyex/PeVHm8vSRI++OxzrF6/wW55dU0tqmv2YueevZg7cwb+fPttENy8UyorL8cLr72BkrIyu+XFpaUoLi3Fmg0b8eC992Ds6FFePR8iIiIiIiIioraynamkNt+2n6mkgjKhB2AUIUFgqERERHQe67SwqasxGo341yefQRRFxERHo66+vtX7fPO/H6xBU/++fXDF/PlISuyBM+UV+HnFChQWncTq9RsQEx2NG6+9RnYfao0GL77+pjVomjNjBqZMnojgoGBkZWdjybLlaG5uxuvvvodXn30afXv39t2TJiIiIiIiIqLzXuuhkonjTCUJRqibmgAAQZERUAkCQyUiIqLzFMMmsxWrViO/sBCpKSmYMDYTS5Ytd7t92Zkz+Nlcbi+tfz+8+NRihAQHAwAGDhiA8Zlj8MTzL6Cg8AR+Wr4CM6dNRXJiotN+lq74FcWlpQCARdf/AVcsmG9dlz5oIIYPGYInnn8BWq0Wn331NZ5/8nFfPWUiIiIiIiIiOo9YQqVmcz8lT0Mlu9lKNjOVIElo1jQDRiPCIsOhYqhERER03vJL2HTljTe16X6qoCBER0WhX5/eGJ85BjOmTIFK5fshV1ZX49sffgQA3HXbLTiSndPqfZb9vhKiKAIA7li0yBo0WYSEhOCORYvw6NPPQBRFLP99Je68ZZHdNgaDAStWrgIApPZMwWWXXuL0OOmDBmL29GlYtW49srKzUVB4Amn9+7XpeRIRERERERHRuc+XoZJjCTzbmUqiBMB8boQ5ExER0flN4Y8Hkdr4odfrUV1Tg30HDuKDTz/HXx5+BEWnTvl8fB99/m9oNBrMmDrFoz5SkiRh9759AIDUlBQMHpgmu93ggWnomZwMANi1dx8kSbJbfyQnB03NzQCAmVOmQKGQ/3bMnDrVenvnnj2tPyEiIiIiIiIiOudJEqA2AjUiUGoATuiBPB2QrQfyDUCJCFQbTaGTBFOoFAogzPwRCiBYMH2EmD/CBCBcAMJhuh1iXq8SAIXAknhEREQkzy9hE2DTGLINH5bwqbyiEo8/94K1v5EvbN25E3sPHEBUZCRuueF6j+5TXlGJ6ppaAMDQjHS321rWV9fUoKKy0m5ddm6ezXYZLveR1r8fQkNCAAA5ecc8GiMRERERERERnRuMLkKlo3qggKESERERdQF+7dlkmdfT2vsVx+0Em+VqtRrvfvgxXn326XaPp7GpCZ999R8AwM3XX4eY6GiP7ldcWmK93TMlxe22qTbrT5eUIrFHj5b9lJTa7CfZ5T6USiWSEhNRdOqUtb9TW0iSBJ1O1+b7E/mDXq+XvU0UCHj8UiDj8UuBjMcvBTIev2RLAqADoIYCWgjQQYAegAECJJuzI5aSdirzbcC+DJ5pvWQtfycAECTn8zGWi3shoU0s7QUcbxMFAh6/FOh4DHvGCECCAFGSoDeKduVkz3eOldjayy9hU0J8PARBQGNTE9RqNYCW9zER4eHWdRYCgIiICISEhKC+vh56g8FullN+QQGO5uZiaLr7WUWt+fLb71F7ts7cF2m6x/erqq5peW5xcW63TYiPt96urqm234/589CQEERGRLSynzgUnTqFuvp66PV6BAUFeTxeC4PBgKysLK/vR9RZcnNzO3sIRG3G45cCGY9fCmQ8fimQ8fg9jwgCEBwCRXgEhNAwCCGhEIJDgKAgCAolAPMJIFGEJIqAUTTVzDN/GE0bAJIRktFoWm80mj58fOLIU9VVVZ3yuES+wOOXAh2PYTdCQiEoFKhXN6OsusLaa5B8zy9h0yfv/gPHCo7j+ddehwAgKTER1155OSaNG4cQc3k4rU6Hnbv34H8/L0XpmTMIDg7C4kceQmpKCvYdPIiPvvg3amvPWve5Y9fudoVN2bl5WLtxI5RKJe6+7TYIXswPtwRmABAaGuJ2W8vzAwC1RuuwH415H6GtPqb9fjRtCpuIiIiIiIiIyI8EAQgOhSI8HEJoOITQUAhBwa5DJa3W9Lnlw7RBlwqViIiIiOT4JWyqr2/Ay2+9haamJkRGRuKVZ55GdHSU3TYhwcGYduEFGD1iBP7y8COorT2LF15/A2+//BLGZ2YiLjYWDy9+2jrlO/94YZvHozcY8K/PPoMkSVhw8Tz07d3Lq/vrbEobqFTuv4RBQS3rHUvYWfbT2j4AIEjVEi61tRSeSqVChpveUERdgV6vt17RmZ6ezmCVAgqPXwpkPH4pkPH4pUDG4/fcIMJU/k4DBXTW8ncCDIBM+TvJXNrOVMhHEABBpTB9IMi5/B1ab0fQWURRtF5NH5+QAKVS2ckjIvIcj18KdDyGPaOF6XdxaHQUYhMTwK9Si5ycHBgMBp/tzy9h09Jff8XZunoIAMaOHuUUNNmKjo7C2NGjsGHLVlRX1+CXX3/Djddeg7T+/TGgX18cP1EEAKioqmzzeH5c+guKS0rRPSEef7jyCq/vH2zz5r+1b4Ze37I+ODhYdj+efEP1hpaAy3E/nhIEoc33JeoMQUFBPGYpYPH4pUDG45cCGY9fCmQ8frs+0WgKlZqNgAaAVgJ0EsyhUgslTGFRMGzDIsF0WxCsPZcsgZI1WOqqqZIHlEollAqewqPAxOOXAh2PYdcUkul3tFIAgpRKqAL4d62veVPtzROK1jdpv93797c8oKL1h7TdZtfefdbbfXq1zEBqalajLYpLSrFk2XIAwB2LbvaohJ2jsLAw622NQ2k8R1pty/owh5J7YWGh5n1oWn1M+/14P2YiIiIiIiIi8oxoBNRGoNoAlBiAQj2QqwNyDECBASg1AjVGQGNOmIIBhAIIM3+EAAgWTB8hAhAqAGECEC4A4TDdDhGAIAFQCYBCCOygiYiIiMgvM5uqqqohwJQg7jt4CGq12i6wsaXV6XDgcJZ1+wqb5ma2wZAnoZWcZb//DoPBgMQePaDV6rBl+w6nbU4VF1tvZx3NxtmzdQCAcWNGIzQ0FPFxcS3PrabG7eNVVVdbb8fHxdutM+3nODRaLRqbmhAZEeFmP6bHiYmOZlkFIiIiIiIiIh8QjabyOuo2zVRqmY10Ls5UIiIiIvKGX8KmoKAga5+huro6PPH8C7jx2muROWqk3XYFhSfw+ddfo6a21vrGLcimn1Fzc7P1dkx0dJvGojeXrCuvqMCb7/+z1e3/9/NS6+2P3nkboaGh6NWzp3VZSWmp2/sX26zv1TPFbl2vnj2xA3vM+ynD4IFpsvsQRRFnyssBAKkpKbLbUNtoTSWyTVeRweGDfxQQERERERGdE0RzmKQxAmqYAiWGSkRERES+45ewqW+f3jiSnWOdrXTi5Cm8+PobUKlUiIuLRXBwMGprz6Kpqcl6HwmmN2z9+vSxLisuMQU3AoC4bt38MXRZiT26Iy42FjW1tTiak+t22+zcPABAfFwsenTvbrcuY/Bg6+2jOTkuw6aCwhPQmMvopQ8a2J6hk40zBqDS2PK5U9gE8x8Ogv0fEgq0hFNKh2VKm3+VYIhFRERERETkTx0RKinAv+eIiIiIWuOXsOmimTNxJDsHAKyBkwTTLKPyikqn7S3bAMBFs2YCAOobGlB48qT1DeDgNoYu9999F+6/+y6323z34xL896efAQDPP/k4hg8ZYj8+QcD4zDFYuXYdiktLkZdfIBsU5eUXWGc2jc/MdGq4NWxIBsLDw9Hc3Iz1W7bgigXzZZtyrd+82Xp74rixnj1RalUQgEgB0JsPNslhvQRANN+QbNZLACTHjd1wF2LZBViw/6PGGmQJLbeVgnPgxT96iIiIiIjofGMJlWzL3+kZKhERERF1Gr+ETRdOmogde/Zg+67ddm/uLCSZZQAwecIEXDBxAgBg09ZtMBpN01AEAGNGjujAEbduwcXzsGbDRoiiiE++/BIvPrUYIcHB1vVanQ6ffPklAECpVGLBvHlO+whSqTD/orn4389LUVxSiqUrfsUVC+bbbZN7LB9rN24CAAzNSMfAAQM68FmdXxQCECwBRpiastqGSbL/OgRMksxtVxmU43qjeX92AZbMY7gjF2I5zsayzshy+CNKabPMdjYWQywiIiIiIupKGCoRERERBQa/hE0A8OBf7kVURCRWrV8PwD5csr1tO6PpjlsWWZen9uyJ++66w/r50PT0jhusB3omJ+PySy/BkmXLUVB4Ao898yyuXLAASYk9cKa8Aj8tX47CopMAgMsvvQQpyUmy+7li/qXYunMnSsvO4MvvvkdZeTmmTJqE4OBgZGVn48dflkEURQQHB+P2m27y51M8rwSj9T8y5AIlxxlPcstdfW73r+S8ztVjuhuTES1Blu3j+iLEsg2trDOybD53nH3VWogF8A87IiIiIiIysYRKzUZAC89DJcA+OGKoRERERNQ5/BY2KRUK3H37rZg+5QIs+30lDmYdgVqtttsmLCwMY0aMwPx5Fzn1Jho9Yri/huqxG6+9Bmfr67Fu4yYUFp3EG++977TN7OnTcOO117jcR1hYGBY//BCef+0NlJ45g9XrN2D1+g1224SHheGBe+9B/759XOyF/MHyx4mv/0aRbKb2tTq7ytt/PQixBDiHWXIhFgAYOjDEsgRYElRQpvYFjCIqoECQwRxmOQRXKjDEIiIiIiIKNLahkgamfkq+CJUsFR6IiIiIqHP4LWyySB80COmDBkGSJJypqEBDQyMACdFR0Ujs0V22Z1FXpVAocN+dd2DSuHFYvX4DCgoLUd/QgOioKKT174+LZs1E5qiRre4nOSkJb730An5bsxbbd+1C2ZlyGEQRCXFxyBw1EvPnzUOP7gl+eEbUGWwPeV8e/YEbYglQxMQCgoBaCC0buSFbShAy5QQhU1JQsL+tdNjOsfwGERERERG1jqESERER0fnF72GThSAISE5MRHJiYmcNwaXrr74K1199lcfbjx09CmNHj2rXY4aGhuLKBfNxpUPPJqK2CtQQS4KEpuYmAEBYZAQEKDwOsSy3JTiXE7Sua8dsLMcQyxpgwTnEsi0h6Fha0Gl2F/9YJiIiIqIAJRoBNVp6Kukk04cI51BJCYZKREREROeqTgubiCgwdVSIBZj+GBUlCY3NjQAEhEWGQyH4diaWq+28CbEgOffram9JQcsf096EWJbbDLGIiIiIqKO5CpUMNttY3sda3qM6hkq25bMZKhERERGdW/weNolGI04XF6OishLNajUkY+tnaGdMneKHkRFRZxMEQLAmN5J1VlB7+XwGluXfVkIs29tCK+tF8yf+DLEE2ARXsAmyGGIRERERnZckCTBK3oVKIWCoRERERER+DJt0Oh1+WPoLVq1bj8bGRq/uy7CJiNrD8kdtR8zE6pB/vQix5Laz/byjQyzHkwi2JVAcZ2A59shyCrJ48oGIiIjILyQJECVTmGQJlbQ2PZUsGCoRERERkaf8EjbpdDo8/dIryMvPlz1B6g7foxJRV3WuhFhy27Y2JktPLLsAS+Yx3JELsRxnY1lnZDmUE1TaLLOdjcUQi4iIiKiFN6GS5b0UQyUiIiIiagu/hE3LV65Ebn6+9Y2qp7wNpoiIzgX+CrEst1tb7upzu38l53WO27nri2UbYlmCLNvH9UWIJXuixKbEoOPsq9ZCLIAnWIiIiKhrYKhERERERJ3NL2HTlh07nZYxSCIi8q8OC7EsSRI6djZWe0MsADB0cIgFqKDq3R+S0YgzUEJlsJmN5RBcqcAQi4iIiLzDUImIiIiIuiq/hE1nzpRb39xKAKKjojBqxHDEduuG4KAgKBQKfwyDiIg6gO1JCV+enwjMEEuAEBUNAQLqILRs0ArZUoKQKScImZKCgutAy3I/2OyPiIiIuj5LqKRGS6ikY08lIiIiIurC/BI2KZRKAKaTc91iovHqs8+iR/cEfzw0EREFqEAMsYyShKbmZgBAWGQEBPMDeRpiWW5LcC4naF3XjtlYjiGWXElB289dlRZ0mt3FE1ZERERtIlnCo4hIKMIiUAolDHrPZirZBksKud/t4O9oIiIiIvIfv4RNPZOSUHDiBAQA4zMzGTQREVGn6agQCwAMkoTGpgZAEBAWGQ6Fr0Ith4BJbjtvQixIzv262ltS0HJCy5sQy3KbIRYREZ3rbGcqNRsBLWxnKgUhuP9gAEAjJCgl0+/JUPN9GSoRERERUSDwS9h0wcQJKDhxAgDQ0NDoj4ckIiLyO+t5HkmyzgjyBZ+XEWwZptvHsb0ttLJeNH/izxDL9ipvudlYDLGIiMjfLKFSM0zl7+xDpRa2v8OCIUHT3ARIQHhEOBQQGCoRERERUcDxS9h0ydw5WLluHcorKrH34EEUnTqFvr17++OhiYiIAp7lxJKvzy91hRBLbjvbzzs6xJI7iWftgQX5EMsx8GKIRUR0/nEVKukk8+8uM9tQydVMJUiAWqsFjCJCI8IQJPB3ChEREREFHr+ETcHBwVj8yMN44rkXUFdfj8effR4XzZ6FKZMmoUdCAiIjI/wxDCIiIrJxroRYctu2NiZLTyy7AEvmMdyRC7EcZ2NZr0p3KCeotFlmuW0bbjHEIiLqGpxCJQnQwXWopAQQZLPM8hKucPy9gJbfF6IkATotYL4/X/eJiIiIKBD5JWy68sabrLcFAGqNBr+s+BW/rPi19TsLAn76+quOGxwRERH5lL9CLMttV6GTp9sB9iGTq+3c9cWyDbEsQZbt4/oixLKEVnI9sWyvnFd6GGIBPKFJRGThGCppzLOU9HAdKqlgen21LAfch0pEREREROcyv4RNtudXLCc4PD3nInhzdoaIiIjOWR0WYlmSJHTsbKz2hlgAYOjAEAtQQdU3DTAaUQolVAaH2VgOwZUKDLGIKPBIkum1VA2GSkREREREvuSXsAlwPjHkyXtwxkxERETU0WxPDPryHGGghVgSBAjhEYAgoAGKlpUekC0lCJlygpApKSg437YtM2jb24QncYnIU74IlRx7+zFUIiIiIiJyzW9hExEREdH5JNBCLKMkoUmtBgCER0bYjdrTEMtyW4JzOUHrunbMxnIMseRKCtp+7qq0oNPsLp40JgpYHREq2b6+8PWBiIiIiMgzfgmbEuLjIfBdOhEREVG7dVSIJUoSGpsaAAChkeFQCh0zE8vVdt6EWJDs+3D5oqSg5aSyNyGW5TZDLKKOJ0mAXgI0YKhERERERNQV+SVs+uTdf/jjYYiIiIjIByxBiq/4vIyg5d9WQizb20Ir60XzJ/4MsSwnxV3NxmKIReejtoZKjj8jDJWIiIiIiPyLZfSIiIiIqENZTu76+hxvVwix5Laz/byjQyynE+q2PbAgH2I5Bl4MsagzWEIlS/k7LUMlIiIiIqKAxrCJiIiIiALSuRJiyW3b2pgsPbHsAiyZx3BHLsRynI1lPXnvUE5QabPMcts23LLdH8AT/+czS6jUDEDjJlSyPbYYKhERERERBR6GTURERERENvwVYlluuwqdPN0OsA+ZXG3nri+WbYhlCbJsH9cXIZYltJLriWVbUlDJECsgyYVKWgkwoH2hksJmHRERERERdV1+D5vUGg2yjmajsKgI9Q0N0Op07v96FQTcd+cd/hsgEREREVEH6LAQy5IkoWNnY7U3xAIAQweFWIAKqn6DAMmIYqig0svMxnIIrlRgiNUWDJWIiIiIiEiOX8OmX379DT8s/QXNzc0ebW/545VhExERERGRPNuT8748Tx9IIZYEAUJoKCAIaIZg6pPVjiDLNvhwLNsmF2I53rYtM2i3/wAKUqyhkgSoJfvyd0ab7WxDpSDzMoZKRERERETnH7+FTd/87wcs+WWZyzr0RERERETUdQRSiGWUJOg1agACQiMjIEBoU4hluS3BuZygdZ0PQyy5koK2n7sqLeg0u6sd3yBvQyXLjDC758dQiYiIiIjovOeXsKm07AyWLFsOwLs/VBlMERERERGdWzoixBIlCQ1NjQCAsMhwKHw9I8vhDxO57bwJsSDZ9+HyRUlBBTwMsWAKkhgqERERERGRL/klbFq/eTMkSbL+Menu7yhPtiEiIiIiIpIjANawyVd8XkbQ8m8rIZbtbaGV9aL5E09DLNt+SgyViIiIiIiovfwSNuXm5wNoueJv/ryLUFVdjZ179gLmZYsffQTHCgrw8/IV0Ol0GD1iBK5cON8fwyMiIiIiInLJErD4OmfprBCLoRIREREREfmaovVN2q+ktMz6h1lyUhJuv+mPSIiPt9tm9IjhuO7KK/DkIw8BAA4ePoztu3ZjWEaGP4ZIRERERETkV4JgLn1n/lCaP1TmjyDzR7D5I8T8EWr+CDN/hJs/Ihw+wl18WO8D07+h5v2rzONg0ERERERERN7yS9jUrFYDMF0hl9a/n9tth2VkYOiQDEgAVq5Zi70HDnT8AImIiIiIiM4RrYVYDJWIiIiIiMjX/BI2GY0tLWcjIyMBAEql0m4btTmQAoCeScnW2yvXruvg0REREREREREREREREVFb+SVsioyIsN42GAwAgNCQELttTpw8Zb1dVVMNwFRT/PiJog4fHxEREREREREREREREbWN38ImSzPahoZGAEB8XCyAlia7X33/PQqLirBu02YcOJxlXd7Y1OSPIRIREREREREREREREVEbqPzxIHFxsSguLQUANDSawqZePVOt6yUAx/IL8NATi62fW8Km6KhIfwyRiIiIiIiIiIiIiIiI2sAvM5vS+vWz3j55+jQAYFDaAESZ+zcJMAVMlg/B5t/hQ4b6Y4hERERERERERERERETUBn4Jmwb0N4VNEoDGxkYUFJ6AQqHAgovnWcvrCTYfFqqgIFy1cIE/hkhERERERERERERERERt4JcyesOHDMEdi262fh4aEgIAuHLhAhQWFWHnnr1O9wkODsYD99yNXqk9/TFEIiIiIiIiIiIiIiIiagO/hE1RkZG4ZO4cp+VKhQKP/t/92HvgIHbv24eq6mqoVCoM6NcPs6dPQ3xcnD+GR0RERERERERERERERG3kl7CpNWNHj8LY0aM6exhERERERERERERERETkJb/0bGqPgsLCzh4CERERERERERERERERudAlZjbJOZKTgx+XLsPho0fx09dfdfZwiIiIiIiIiIiIiIiISEaXC5v2HTyEH5f+grz8fEgAhM4eEBERERERERERERERBRxJkiBKEqDs8kXeAl6HhU1Nzc34bfUaHD56FLVnzyIiPALJiYmYM2M6hmakO22/98BBfPvDDyg6eQoAIHXUwIiIiIiIiIiIiIiIqEuTJAmiUYIoGaEzGKE26KHRG6AxWD5E6EQRWoMInfm23miEXjRCL4owGI3QG40IDwrChF4pmJgYCwic3tJROiRsKjp1Gs+8/Arq6+sBwDpDKb+gAJu3bcPsGdNxz59uBwDU1zfgHx98gIOHs6zbwrw9AyciIiIiIiIiIiIiosBiCYoMkhE6gwiN3gC1oSUo0hpMIZFWNAVFenNQpBNFGEQjDEbThyVsMroJCwQASoUCCkGAUhCgMH8oBQFKlQohKiVq1GpoxGgEKbpcsbdzhs+/sgaDAa+98w7qzEET4Bwcrd2w0TzLaQYeefppVFRU2oVMRERERERERERERETkf5IkmYIeSYLOYIBaL0Kt10MjitDqTUGRRjRAJxqtQZFlVpFBNM0mEs1BkUEyQvIgKLINiRQCoBQUUKkUEMyfAwIUljsAEAQBAkzrBIfZSgoB5nUC9EYJKnMJPXfjoPbzedi0Y/celJ0pdwqNbD+XACz99TeUlZejvKISgsx6AOidmoorF8z39RCJiIiIiIiIiIiIiM45RkmyBj1a0QC13mAuPSdCa2j5VycaoTMHRnpRNJWeMzrMKDIa3VYfUwiAQjAHRQrbGUUKBNkERaZYCB4GRaZtFYJgvX/L7ZZ1tutb1jnvs7JZDdHdtCjyGZ+HTXv2H3BaZvuttARL9Q0NWLtho2zIlD5wIK5cuADjxoz29fCIiIiIiIiIiIiIiLoc26DI2pfIHBS1lJ4zBUQagx5Nag0MRiNwptYaErU3KFKZgyJTmGMKisz/ATAHOzCvkwuKBEABoeW2h0GRq31S4PB52HTy9Gm7ACk2Nhazpk1FfFwsqqprsH7zZtTUnrWW1rNsKwEYNXwYrr78MgxNT/f1sIiIiIiIiIiIiIiIOoQlKDKIRmhFUziktpScswuKTH2K9GJLfyLvZxRZwhsJCgAqI6BQ+DoocgiDZGYcMSgiWz4Pm2pqawGYwqPwsDC8/dKLiI6Osq6/9KK5uOdvD0OjVlsDp7CwMPzfn+/C+MxMXw+HiIiIiIiIiIiIiMglS1CkN/cgUovmGUV6g6lPkcEAnUGE1iBCZzT3JxJN2xvMAZNB8jwocpxNpBAEqBQKBCtMpedcBkXmwEcQBECSoNPpAAAhISGm/TEook7k87BJrVYDMP0QjBw2zC5oAoBuMTEYOWwodu7Za93utj/eyKCJiIiIiIiIiIiIiLxilCRr4GOZRaQ2l5/TGgzQiqJ5VpEIvWgTFBlbwiLRaIRoDou8CYqU5vBGpVQgGOagCObgRmhpKQPHoMjM8rmlr5GnQZHCvA91k2kfkVGRDIuo0/k8bBKNRmvaGhfbTXab+NhYu8/HZ47x9TCIiIiIiIiIiIiIqIuSJMk0o0iSYDAHQmq9wdqryBQcmUrO6cx9ivTWoEi0CYokGCQjjF4ERZaQSCkICFIKCFGq7IIiS27jcVBknSHUEgY59ilqCY9kZim18eunYMBEXYjPwyZbCoVCdrngsDw6Kkp2OyIiIiIiIiIiIiLqWqxBkVGCwWgKhTQeBEU60QiDTVBkMErWGUXuWIIipUPpuSClEsFKS4Bjmh3kXVDU0qdINihy08OoPUER0bmoQ8Om0yUl2LB5i/Py4hK7zzds2QpIrl9QZkyd4vOxEREREREREREREZ1v5IIiy4wircFgCokMBmhFozUo0tnMKDK0MSiyzCjyNCgSzAGPu6DIvvxc60GRwsU+iaj9OixskgAcyjqCQ1lHWt3uvQ8/crsNwyYiIiIiIiIiIiI639kGRXrrjCK96V+DAVq9CI1ogM5g6k1kFxSJojkkMgdFRiNENxMAAFjDIdsZRYI5KApRWUIbc1AEtPQpamdQ5KpPEYMioq6rQ2c2uX+p8mw7vmwQERERERERERFRoLMERQbLjCK9CLVBD41eNM8oMpWf04rmoMhg359Ib2zpUeRxUOQwm0jhNigSIEDyPCjyuE8RgyKi80GHhU2+eMnwNKwiIiIiIiIiIiIi6iiSJEG0lJ4TRagdZhRpDKbZRFqDCK1RhN4gWvsU6a2ziYymkMgoeRQUOfYnUggCQpRKCKqW0EYAbIIic3jkIiiS7zvUWp8iBkVE5JkOndlERERERERERERE1JlagiIj9KIRGoMBTTodKhrV0BqNOG04A4MoeRQUGYym2UnuuA+KlObeRIL1Yn2hjUGRAi76FDnMOGJQRET+4POwKSE+ni9cRERERERERERE1G5yQZFab5pJpNGL0Irm0nMGg01/IvuycwbRCFFyFxTVWW+5CoqClUoozEGRwnzu0/p/AS5DHfugyDEMcuxT5FyajkEREQUKn4dNn7z7D1/vkoiIiIiIiIiIiAKMc1CkR7NehNYcFmlFERqDCJ1NUKQzB0UGowi9UYIoGmGQTKXn3M0oEgDZ/kQKQUCISglBcJxRJMFgMAASEBIcBEGh8DwocupJ5L6HERHR+YBl9IiIiIiIiIiIiMiOY1DUbOlPpNdDa+5TpBWN1qBIaxChN5qDImv5OQmih0GRaTaRwhrcKAUFFAKgUikR6hAUWUrOwWZ2EOA+KLLvU2Rar9VoIACIiIiAQsGgiIioPRg2ERERERERERERnUMkSYJoDnp0BiPUBj00ltJzBoNpNpEoQmsQoTPf1ptDJb0o2vQoMgVOngZFSusMINO/oSqFaUaRIJjCIpj7EpnvKbgIddwHRfZhkLt1rX2Nmgx6AEBYkIrBEhFROzFsIiIiIiIiIiIi6iIsQZFBMkJvExSpDQZovQ6KjDC6zonMQZFpNpFt+TmlIEClUlnDHECAwnyH1oIihQBrX6PWwiC72272SUREXR/DJiIiIiIiIiIiIh+QJMkU9EgSdAYDNHrRFBZZys4ZTCGRVjQFRXpRhE40Qm8UYRCNPgiKTOXnVCqFbFAEwDrLyBIC2ZILiux6FqH1PkUMioiIzk8Mm4iIiIiIiIiI6LxnNPcnsgRFar0ItblPkWVGkVY0QGcwQieaZxRZehOJRuiNRtP9zbOS3FSeswZFtrOJTMGOwlx6ri1BkWMYJB8UuZtxxKCIiIjaimETEREREREREREFNGtQZJSgFQ1Q6w3mHkU2QZHBAJ1ohE40/asXRVPpOaPDjCKjEW5yImsopBQEKBS2pecUCLIJigRLwbkODoos5ecYFBERUWc6L8Om5uZm7Dt4CPmFhTheeALVtTWor2+ATqdDREQEUnumIHPUKMyePg3RUVGt7m//oUNYvX4D8o8fR119A2KiozBwwADMnTkDY0aO9GhMWq0Wv61eg+27dqOsvBwGgwEJ8fHIHD0K8y+ai+4JCe192kREREREREREXY4lKDKIRmhFU7k5td5Ucq6l9JzB1KfIHBDpRNE6m8i7oKilJ5FtUKQyB0WmMMccFFn7E8Gup5BsUCQACmv5OQZFRER0/jkvw6b844V48/1/yq6rq69HXX09jubkYumKX/HAPX/G6JEjZLeVJAkffPY5Vq/fYLe8uqYW1TV7sXPPXsydOQN/vv02t28aysrL8cJrb6CkrMxueXFpKYpLS7Fmw0Y8eO89GDt6lHdPlIiIiIiIiIioAxklCUZJglqnh0HSW4Miy0wirSUssik7pxNbys4ZRCMMkudBkWNIpBAEqBQKBCtMM4pcBkXm0Kf1oMghDJKZccSgiIiIyNl5GTYBQEJ8PIYPycCAfv2QEB+H2G6xkCQjqmpqsH3Xbuzcsxf1DQ148c238MYLz6Fv795O+/jmfz9Yg6b+ffvgivnzkZTYA2fKK/DzihUoLDqJ1es3ICY6Gjdee43sONQaDV58/U1r0DRnxgxMmTwRwUHByMrOxpJly9Hc3IzX330Prz77tOw4iIiIiIiIiIi8ZZQk06wg0QidQYTaXH5Oq2/pT6Q1iNAZTEGRzmguO2cNi0zhkVGSYCw641VQpDSHNyqlAsEwB0UwBzfmoMjUssh9UGQpV+dpUOQ444hBERERkW+cl2HTsKFD8Ol777hcf+HEidi5Zy9eefsfMBgM+H7Jz/j7A/fbbVN25gx+XvErACCtfz+8+NRihAQHAwAGDhiA8Zlj8MTzL6Cg8AR+Wr4CM6dNRXJiotNjLV3xK4pLSwEAi67/A65YMN+6Ln3QQAwfMgRPPP8CtFotPvvqazz/5OPtfv5EREREREREFLgk82wiUZJgEEVoDUao9XpoRBEavcHao0gnitAaLLOJWvoT6UVL2TkjRPOsIo+CIsfScwoFFJCgAKBSBUFhSm9aDYosn1uDIbjvU9QSHrmfpURERESd57wMm5QKRavbTBw3FqkpKSguLUV2bq7T+mW/r4QoigCAOxYtsgZNFiEhIbhj0SI8+vQzEEURy39fiTtvWWS3jcFgwIqVqwAAqT1TcNmllzg9TvqggZg9fRpWrVuPrOxsFBSeQFr/fh4/VyIiIiIiIiLqOpyDItFcds5g7U+ksZSdMxigE40tpefMM4ss/YkMkhFGT4MiRctsIqUgIEgpIFipsgtuLNmNx0ERBOi1WggCEBoWat1/a6XpGBQRERGde87LsMlTISEhAACdXm+3XJIk7N63DwCQmpKCwQPTZO8/eGAaeiYno6SsDLv27sMdi262ezN1JCcHTc3NAICZU6ZA4SIEmzl1KlatWw8A2LlnD8MmIiIiIiIiok5gDYqMEgxGUyhkCYoss4m0BgO0otEpKNIbRVN/IqMRBqNknVHkjmNQZJlRFKRUIlhpCXBMoY93QVFLGCQ7o8jDoEiSJDTBCACICAtlgERERHQeY9jkwumSEpw4eRIAkJqSbLeuvKIS1TW1AIChGelu9zM0Ix0lZWWorqlBRWUlEnv0sK7Lzs2z2S7D5T7S+vdDaEgINFotcvKOef1ciIiIiIiIiM53tkGR3mg/o8hVUNRSes4hKDIaIUrugyJLOKS0KTtnCYpCVJbQxhwUAS19iswBj7ugyL5PUetBkcLFPomIiIh8xadh03sffezL3ZkIAu678w7f71eGVqtFdU0t9uzfj59X/Aqj0XR1zvx5F9ltV1xaYr3dMyXF7T5TbdafLim1C5uKS0pt9mMfaNlSKpVISkxE0alT1v5ObSFJEnQ6XZvvf64xQAERAiQIECUJgvu/E8hPLOUpHW8TBQIevxTIePxSIOPxS4GMx69nHGcUqQ0iNHrRGhRpzWXntOY+RdaQyNyjyGC06VFklNoUFAmCgCCFwjyjSDAHRYDt/y0zgJxCHUGAAg5hkXWmkMPnlnAI9tv6KiiSWnnu3rCcN7HcdlWxhagr4vFLgY7HsHckSYJer4MOxtY3Pk/48j0B4OOwaf3mLfDl9TESTG/WOjJsWrdps9uQ7PJLL8G0Cy6wW1ZVXWO9nRAX53b/CfHx1tvVNdX2+zF/HhoSgsiIiFb2E4eiU6dQV18PvV6PoKAgt9vLMRgMyMrK8vp+5ypFtzgI4REQQsLQ2NTQ2cMhGdVVVZ09BKI24/FLgYzHLwUyHr8UyM7V41eSJBgBGCUJBqMROqNkmj1kNJpmDxmN0Bsl6G3+NRglGCTJXG7O9GE0327tFJECsIY0CgjW2UNKAVAJAgSVdS6RdUaRaQsJltN0djOKhJZZSApYbkvW0nUKSA7bwBpEWT6HeRvTmQ7J+o/s1wtAIMaOanObAKJAxOOXAh2PYdf0ohFGCWhqFJGXV4kQiWFTR+mQMnrnwgSRfn364M+334pBac79mNRqtfV2aGiI2/1Y+j4BgFqjddiPxryP0FbHY78fTZvCJiIiIiIiIiJvuAyKRCO0RtOsIZ3RtM4SFjkFRZaQyJOgyFoCziYoEoAgQYCgbAmOgDYGRZYQyBoUudpGsAmKWHqOiIiIqDUdEjb56i2YP0KrCWMzkdb/ZQCATqfDmfIKbNu1Czv37MVb//wXbr/pJowbM9ruPjq93npbpXL/JQwKalnvWMLOsp/W9gEAQaqWcKmtpfBUKhUy3PSGOt/UQQE1BOggICwy3Kez8qjtRFG0XtEZn5AApVLZySMi8hyPXwpkPH4pkPH4pUDWkcevpfScwdyjSKMXodHrTb2JREsJOiN0ogE6gxF6UTTNMhJFU3gkmkrOGSTTv0ZPSs8pBGsJOoUgQKVQIEhlCXFsexMJ1r/BXJWJE2z6D8mXmJMpS2fd1rel50ie0Wi0Xk0fFh7OEk4UUHj8UqDjMewZtVoD0SghIiIMg5N6IyqoQyKRgJSTkwODweCz/fn8Kxtos5oiIyLsStgNHDAAUyZPwoYtW/Huhx/h5Tffwr133oFZ06Zatwm2mVXU2jdDr29ZHxwcbLfOsh9PvqF6Q0vA5bgfTwmC0Ob7notUIqA0AoIEKM1Xy1HXolQqoVTwZBEFJh6/FMh4/FIg4/FLgcz2+JUky6wgU+ijMRig1hugMRig0YvQiuY+RQaDqRSdTZ8ig1E0zS4SjR4FRQLgFBJZwyKVAqGC0jzTxxzeWO4luAmKAGufI9uQyDJzyHYdg6LAZXtiU6FQ8PtFAYXHLwU6HsPeEQQBQUHBCA5m2GTh62PGp1/Z55983Je761QzplyIvQcOYNvOXfjk319iQmYmIiNNoVRYWJh1O41DaTxHWm3L+jCHknthYaHmfWhaHY/9flovu0dERERERESdwzEoUuv1UBtEaC1hkXlmkc5gCowampthkCQI5bXmcnQSRC+CIqVCgEJQWIMbpaCAIAAhKqVsUCRYSs+ZQx/AfVBkO4PI5TqboMiynoiIiIjOHz4Nm4adYyXaxmdmYtvOXdBotdh36BCmXTAZABAfF2fdpqqmxu0+qqqrrbfj4+Lt1pn2cxwarRaNTU12M6yc92N6nJjoaPZrIiIiIiIi6iCStceQqS+RWq83lZ8z6M1l5yxBkeVfI/RG04wiS/k5g/n+ns4oUkimwEalNJpDI0BlCYrMJeMsIZFlVpHgItRxHxTZh0Hu1hEREREReYNzxtyIiY6y3q4019AGgF49e1pvl5SWut1Hsc36Xv/f3n3HSVXeexz/nim77LLs0jsoSEcF6Sqg2AsmaiyxJzHG3Jjc3LR7TTGJ0SSme1NvNEUTY4yJFewKCoqiYgnSBEHawgJLWbbPzDn3j5k5c2bmTN3ZMuzn/Xotc+bUZ2afYXfnO7/nGTY0btuIYcP0qt6InGeXxo8d43qOUCik3TU1kqThQ4e67gMAAAAA3V00KApapgJBU03BgJoDQTUFg2qJVBS1hkJqCYbDotZQSIFI9VEsKDIjYVP2FUXR4eeiwU0Pn0dGtkGRZdnz8paWltrD12UKg+KW04RPAAAAQEfo1LCpsbFRhw4fliRV9eql8vLyzmxOktr9B+zlHo6h6wYNHKC+ffpo/4EDWrNufdpzrF2/QZLUr28fDRwwIG7bxPHj7eU169alDJs2bd6i5sgwehPGjc3tQQAAAABAEXAGRa3BkB0SNUe+wvMTxaqKApGgqDUUCs9NFBcUmTLTTCgcDorCw855HRVAXsOQz+ezwxzJkCd6gBQZjs491PEYigRCyUFRuuHnDElNDeFLVPSqICwCAABAUerwsOlQXZ0ee+JJrXxzlXbt3h23bcjgwZozc4Y+ct65qqqs7OimJVmxcqW9fNSI4fayYRiaNX2ann7+Be2ortaGjZtcg6INGzfZlU2zpk9P+qPh2EkTVV5ersbGRi1ZvlwXXbDQ9Q+LJcuW2ctzZs5o8+MCAAAAgEKyLCsc9FiWWoNBNQdC4aqiYChlUNQaCg8/FwyZCpimQpGgKGiZSlNQZAdFXkeQE67y8UQqilIERY7qoGyCImcwlM08RfmGRJZl2fMmAQAAAMWqQ8OmN99+Rz//zW/V3NQkt78dqnfv1iOLFuup51/Ql2/6nGacMLVd2vHCS8s078Q5KikpSbnP408+pVXvvCtJGjhggCY5qpAk6YJzz9FzS19UKBTS3ffeq+9/+xaVOs7X0tqqu++9V5Lk9Xp1wTnnJF3D7/Np4dln6cFHHtWOndV6dPETuuiChXH7rH9/o55/8SVJ0uSJEzT2mGPye9AAAAAA4MK0LDvoaQ0F1RgIqTkQDoqiQ8+1hIJqDYariFpDsaqiXIOiaCjkNYzwXEWR8MZreOR3BEVGdMC5rIKixDDIPShKNzQd1UQAAABA23RY2LR6zVr98Oe/kGmakuwPlyWxJDU1NemOn/9C3/3GzTp24sSCt+WBhx7WPX+7X3NmztSk8eM0eNAg9ehRqqamZm3dvl3LXlmhde+/L0ny+Xy66dPXy+v1xp1j2JAhuvD88/TQ44u0afMWff27t+riCy7Q4EEDtbtmjx5etEibP9wqSbrw/PM0dMhg17ZctPB8vfzaa6retVv3/v0B7aqp0bwTT1RJSYlWr12rfz32uEKhkEpKSnT9NdcU/LkAAAAAipUVSTVMx9w6IdOUJcPeZkX+sZR837JXSGZ02DVLCsmSIue0HOe3IseZlmRFQhUz0o7w9vD+lhU+X3TZsiyZsuzl6DnjlyNttBTZ17LP72yLFbme81r2csI17Ocnet7IAw5G5ygyE4aeM03XDwVGpQqKfJGgKBzmRIIiI/Y3n3NOIdegyJA8dlVR9kFRqnMCAAAA6HgdEjYFgkHd+bvfyTTNlCFTVHR7yDR152//T//3i5/J5yt8Mw/X1+u5pUv13NKlKffp17evvnDjDZpy3LGu26+67FIdrKvTCy++pM0fbtVPf/XrpH3OOPUUXXXZpSmvUVZWplu+9lXd9uOfqnr3bj27ZKmeXRLfpvKyMn3pps9p9NFHZfnoAAAAUChxoUXifWeIYUX3Sb4f2zccUpiWYuGBI8gwZckyLUeg4QgpZMkyY0GEaYcKkcDClMJ7h88txzWcYYZlL0eDE8f9pMDEstvvdt8ZarjeRh503Pmd6xW7tiwrHKwkPMfRY+RcdoZF0ecw+qG2bXtcn3dFruX4DiXcLw6xACd2L3Gd4dg5uodzXWzouUIHRZnmKSIoAgAAAI5UHRI2LXv5Fe0/cDAuaLIkeTweVfbqJUmqO3w4KYzav3+/XnplhU4/ZX5B2/O9b35d/37vPa1es047qqt18NAhHa6vl9/vV++qSo066ijNOOEEzZ0zW6WlpSnP4/F49IXP3KATZ87Us0uWatPmzao7fFiVvXppzOjROvv00zR96pSM7RkyeLB+/oPb9eRzz2vFypXatbtGwVBI/fv21fSpU7TwnHM0cED/Qj4FAACgC3ILNew3wRMqMTK9mR4NBUw7nAgHEWakusGSJTMSaliWFDRDOtDYLEtS44FDMuSJCyLs86Wt0nCGB1Ys8FB8FYjsQCW+aiPcbsWuk/B4kgIIx3PiDEikxG3Ode7hRXyA5KwgSXyeE4Om+Oc9PkiJrou/XywKEWrY+9uT5iSc27lT3Hr7InHb7GDCIxmWx76GZUkhBSXJ/qBa4jncIg1DkuUYsk2W5Whj4hFW3Fmix0qS4fj+u2cn8c+LW3tSPRf2/QKHMvkERYkVRwRFAAAAAKI6JGyKzn0UNWTwYF135cd1wvHHy+/3SwpXP7397ru69/4HVL17d+zYt98peNg0ZNAgDRk0SGeffnpBzjfjhKltnl+qR48euviChbo4Yc4mAADaQ+Kb9tHlxG3ub653paGnYpUd4VCj0ENPRc8hxao5HMfbIUP8umiwEAs1Ugcdso+LnSfrYCnxvuMN7zbZvb+tZ8iJs4LCeV/OeVvsfcL33AKN1OvThR1SUiARfSNdkjySHKFGYsOjIUOmUCPx8cRCjfCa+Bgjc6iR+kJG9LQpdsu0vX0ChLjvRUIDjIQdE3qBy7GxtdG7liy1NodXlJb2iO8n6Z6LhIeabnum5yn5cWR6jMmPI7mfZQqp4h9jLgEWQREAAACAQuqQsGnTli32H9EVPXvqh9/5tiore8Xt4/f5NGv6dI0bM0Zf+Nr/qKGhQZakD7Zs6YgmAgDaScpQIyHEiL5hn3jf+WZ6dOgpKzLUUqqhp6JVGCmHnpJi+6pwQ0+ZlqmGhkZJUml9swwZjgDFrnfoYkNPJT/PmUOM4hx6SkodaqSr0rD/zSrUSBd22BdKbocnstZKURXhEmqk2C1SpRE9n2XvmFylkchSMBCpDPH74wOQfEONtG/kd+FQI0MY4HZU6jf8c3uecgo0Mm1P9RizeAyZtneFAMvJsiw1WOH/CXv2LCNIAQAAAIAO1iFhU93hw5LCf3ROnzo1KWhy6l1VpelTp+qlV16RJB2KHAsA6XTm0FPRwCMafjiHj0o19FRimBG9bqGGnordOkKOxNAi6VaO/Rh6qq2Mw43FMfSUXN4UTjhH+lAjsrUQQ09FNibvne5N8MgVOzjUyP0N/xTbMwQeblvaK9SQpOamJknhOSWNhJ07o0oj02NI3E7AAAAAAABA5+iQsMkMhezlHmnmQIoqLS1xPRboCtoaaliOd85jw0tFgwrFKjcUCyqcVRzOIaWc28LhRaQyI7Ii5dBTzhAjet2EgCNu6Cm7PYlVGWmqNOz2xp6DlENPxQUZlgKRT9Z7dtWG35ROE3S4P8+dOPRUB4sFGKne4E0MMIpv6KnUoYZbnUbmUCPlhbJ5kzvt9vD91tZWSVJJSUlS6JOP+DfS49e4v+Hvvj3V0FPxx8ZWtC3cObKHnnJ7DEcCy7LkCYT7b8/SkiPyMQIAAAAAjmwh01RLa0DNra1qaQ1oV91h9Sgt1eCK8s5u2hGvQ8KmiooKHTx4UJak99avk2VZKd/AME1Ta9atD79BGDkWaA8f1B7U8m07FTQtGc6AQolBRv4hxhFVpRG97YChp8xwWiZvyHmOxOtG7nsiK9oYakT/z7HfzI+mT47H51YBknhCQ7K/x4lv1jt3btsb+e3zRndBQo0MYYDbUanf8C++oacsy1JTQ7jvlPfsGf96yesxHpmhBgAAAAAA6J4sy1IwFFKzIxCybwPR+wnbAgF7fUugNXzbGr2N7dPc2qpA0L145aTjJuqUr32ugx9t99IhYdOwoUN04OBBSVJ19S799g9/0qevvVqlCVVOLa2t+sO9f9XOXbtkKPyG27ChQzqiieiG9jQ0qjUYUsiy7P6WXKURi0CMdFUa0X0tl3Mk71aYoacim4t56Cm3QMOS1NrSIkNSSWlp3PVzCTzctqQOJtox1HB+r123JbTRdZujjY6d2vIYErcTaBSGZVkKeMIJqN/r4XkFAAAAAABFxzStcMATcIY6rbEQKBBICHwi21z2jwVFsUDJNDv+o/grVq/TW5u36rRJYzv82t1Fh4RNx0+erPfWrrPfSH7hxRf1ysqVOnbiBPXv208ypH21tVqzbr2ampriKgiOnzy5I5qIbqiyR6lG9K7SvsYmlXiMlKEGQ0+lf4xJbUw4Ya7hlWVZaoiUIvWs6Mmb9QAAAAAAAECCYCikhuZmtbQGdbCpRa2BWNjT0hp0VAm5VAIFEiqKEqqDWiNTXBxJDEPqVVbW2c04onVI2HTmglP1z0ceVTAYtIOkpqYmvfnW23H72SNdRRvn9+vMBad2RBPRzQ2q6CmPh1ADAAAAAAAAQNtZlqXWYDAh1GlNGAou9XBxzvDHHkLOcXwwZHb2QywKhmGoT2UvXXLqyRo/bHBnN+eI1iFhU++qKl3+sYt03z/+GRuuTMnz1hgJyx+/+CL1rqrqiCYCAAAAAAAAALqRkGmGK4Lc5g9yrQBqTZo7KFwJFD1HLBBqDQRkWsU4c3vH83m96lHiV2lJSezW709eV+JXqd+v0hK/epSUqNQfuS0J7xtbjm072Noq05IGV5R39sM84nVI2CRJH/vIR7R3b62eWbLEDpXc6kiiL79zzjhdF3/kgg5qHQAAAAAAAACgK7EsS8FQKDkMclQAtbS2xs0V5BYIxQ0h56gYCgRDnf0Qi0ZpUvjjVw+/I9yJ3EYDobjgx14XO97e7i+R1+tpt3YbgYBE6NchOixskqTPXv9JTZo4Xv946BFV797tus/QwYP18Y9drHknndiRTQMAAAAAAAAA5Mg0LbUGE4Z5cwY/gdg257Iz/HGGRXEVRIFWmSZBQTa8Hk9cVU+02idWJVQSv67Er1J/QvCTsC26rsTnZwoSZNShYZMkzT/pJM0/6SRt27FDGz/YrLq6OlmSqiorNfaY0Ro5fHhHNwkAAAAAAAAAjlihkBk3JFxS4JPFtvj9nPMHBTr74RWNEp8vqRLIWfETW3ZUCUXCoriKopISlfp9CgUC6uH3q0+fPirxd/hb/UCcTuuBI4cPJ1gCAAAAAAAA0O1ZlqXWYDCuqic61Jvb8G9JcwslbYsPg4IhhovLhmHIrvaJDffmFvjEgp+4IeP8CYGQIzQq8fvl9RRuuDjLstRQXy9J8vu8BTsvkC/iTgAAAAAAAADIIGSaag04wp3EwCfQqlbHclLokzS3UGy5NRCQybwyWfF5PUmBUHyVkHvgU5o4lJzLvEIlPp8Mg+HigHx0WtjU2NioxqYmWVn8Jzqgf/8OaBEAAAAAAACAYhYIhlxCnYTgJxBQc0urDtfXqyUQUEiGXUnkrAZKDJRag8HOfnhFwzk0XDTYiQt//MlzBGWzrdTvl89LFQ/QFXVo2PTu6vf0xLPPad2GDWpoaMjuIMPQw/f9pX0bBgAAAAAAAKDdWZYVCXICkYDHZY4gO/BJsS0Qv84ZDIVMs7MfYlHweAxHqJMQ7vjjw534CqKSuKogt20lPr88HqqDgO6mw8KmP/31Pi1++hlJUi4FoQblowAAAAAAAECHCYVMxzBwyYFPUtVPqqHl3IaSCwQ6++EVDb/P6z78mx34xA8XFz+3kD+hSih+/iCf18twcQAKqkPCpuUrXtWiSNAkSdn+N0bMBAAAAAAAAMSzLEuBYMgR9CQGQwHXbS2BYPz8Qa2BhCqh8G0wFOrsh1gUDEMqdQ755hb++FPMHxQJghLnG3Ju93o8nf0QASBrHRI2Pf3CC5KSQybCJAAAAAAAAByJTNOKmwPIWSmUWO3jWgHkGC6upTWYdLzJaEBZ8Xk9jsDHEe74S+T1GCr1+9SzvNwOh5ICIUdglLitxOejOggAIjokbPpw67a4oMmS1LdPH/Xt3Vv+Er88pPQAAAAAAADoYIFgKC7UcQ4FF5tXKDH8cRlaLrGCqDWg1mCwsx9e0Sjx++KGi0uqBIqrHkqeIyh++Lj4bT6v1/WalmWpob5ektSzooLQCADaqEPCpmjprSXJ7/frv7/4Bc044YSOuDQAAAAAAACKlGVZag0EY+FOIHn+oORt7uGPc5/oupBpdvZDLAoew0gd/iTMFZS0zg6I3IaPCwdMHg9BDwAUuw4Jmwb066edu3bJkHTizBkETQAAAAAAAEcI0zTV2NwSGTIufq6guPmD4rYlh0F2JZEjUGoJBMRocdnx+7xx8/5kCn+cQ8I5h5ZzhkLR/fw+L5U/AIC0OiRsmnHCVO3ctSt8Qb+/Iy4JAAAAAAAAhauDAsFQXAjUEg2BHHMFuQVCLQnDxTmHm4veRke0QXqGofgh4PwJw8U5qn/cAqFoJZFzuDnnsV4v01QAADpPh4RNFy48Xy+8tEz1DQ1a9fY7amhsVM/y8o64NAAAAAAAQJdnmlakMiga6rgMAeeYHyhd+NPicrxJeVBWvB5PQuDjMn+QHfaEl0scy0lDy/lLHPv5qA4CAByxOiRs6l1Vpa/+5+f1g5/9QnV1dfrm927XNR+/XNOnTumIywMAAAAAALRZMBRKrvZxBj+u22LDybUG4sMjZ6VRayDY2Q+vaJT4fCnDn2jIE5sbKHkIOedcQc65hkojw8UBAIDcFTRsuuX2H6Td3rO8XAdaW7V1+3Z9/yc/VXl5ufr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\n",
      "text/plain": [
       "<Figure size 2000x400 with 1 Axes>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "viz = ProfileVisualizer()\n",
    "viz.set_profiles(profiles)\n",
    "viz.plot_distribution(\"chol\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x400 with 1 Axes>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "viz.plot_uniqueness(\"age\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "RAPIDS Stable",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}