{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import three_parameter_screening as tps\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Generation\n",
    "Uses the Inverse Transform Method\n",
    "<a class=\"anchor\" id=\"inverse_transform\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rng = np.random.default_rng(seed=42)\n",
    "t_w = tps.transition_survival_rvs(rng, w=0.001, size=1000000)\n",
    "t_q = tps.sojourn_survival_rvs(rng, mu=1, t_w=t_w)\n",
    "age_cutoff = 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Exploration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preclinical Transition Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  t_w\n",
      "count  1000000.000000\n",
      "mean       500.026476\n",
      "std        288.635568\n",
      "min          0.000125\n",
      "25%        249.990623\n",
      "50%        499.810121\n",
      "75%        750.106231\n",
      "max        999.999717\n"
     ]
    }
   ],
   "source": [
    "t_w_df = pd.DataFrame({\n",
    "    't_w': t_w\n",
    "})\n",
    "print(t_w_df.describe())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot histogram with density=True\n",
    "plt.hist(t_w, bins=30, density=True, alpha=0.6, color='b', edgecolor='black')\n",
    "\n",
    "# Labels and title\n",
    "plt.xlabel('Age')\n",
    "plt.ylabel('Density')\n",
    "plt.title('Density Histogram')\n",
    "\n",
    "# Show plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t_w_cutoff = t_w[t_w < age_cutoff]\n",
    "# Plot histogram with density=True\n",
    "plt.hist(t_w_cutoff, bins=30, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "\n",
    "# Labels and title\n",
    "plt.xlabel('Age? of Transition to Preclinical Status')\n",
    "plt.ylabel('Frequency (n=1*10^6)')\n",
    "plt.title('Preclinical Transition Age? Histogram')\n",
    "\n",
    "# Show plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([94.17734789, 63.8172561 , 43.80376579, ..., 66.94287416,\n",
       "       29.59360772, 18.48943743], shape=(99714,))"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t_w_cutoff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.099714"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(t_w_cutoff)/len(t_w)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "lifetime_preclinical_percentage:  0.099714\n"
     ]
    }
   ],
   "source": [
    "preclinical_percentage = len(t_w_cutoff)/len(t_w)\n",
    "print(\"lifetime_preclinical_percentage: \", preclinical_percentage)\n",
    "\n",
    "# Tells us what percentage of people will go to preclinical state in their lifetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clinical Transition Exploration\n",
    "See [Inverse Transform](#inverse_transform) for data source."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                  t_q\n",
      "count  1000000.000000\n",
      "mean         0.999463\n",
      "std          1.000218\n",
      "min          0.000004\n",
      "25%          0.287533\n",
      "50%          0.692339\n",
      "75%          1.385773\n",
      "max         15.131814\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t_q_df = pd.DataFrame({\n",
    "    't_q': t_q\n",
    "})\n",
    "\n",
    "print(t_q_df.describe())\n",
    "plt.hist(t_q, bins=30, density=True, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Value')\n",
    "plt.ylabel('Density')\n",
    "plt.title('Density Histogram')\n",
    "plt.show()\n",
    "\n",
    "t_q_cutoff = t_q[t_q < age_cutoff]\n",
    "\n",
    "# Plot histogram with density=True\n",
    "plt.hist(t_q_cutoff, bins=30, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Age? of Transition to Clinical Status')\n",
    "plt.ylabel('Frequency (n=1*10^6)')\n",
    "plt.title('Clinical Transition Age? Histogram')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Combined Verification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>first_transition</th>\n",
       "      <th>second_transition</th>\n",
       "      <th>sojourn_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>773.956049</td>\n",
       "      <td>775.156064</td>\n",
       "      <td>1.200016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>438.878440</td>\n",
       "      <td>439.497455</td>\n",
       "      <td>0.619015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>858.597920</td>\n",
       "      <td>858.613326</td>\n",
       "      <td>0.015406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>697.368029</td>\n",
       "      <td>697.777527</td>\n",
       "      <td>0.409498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>94.177348</td>\n",
       "      <td>95.061607</td>\n",
       "      <td>0.884259</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   first_transition  second_transition  sojourn_time\n",
       "0        773.956049         775.156064      1.200016\n",
       "1        438.878440         439.497455      0.619015\n",
       "2        858.597920         858.613326      0.015406\n",
       "3        697.368029         697.777527      0.409498\n",
       "4         94.177348          95.061607      0.884259"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a dataframe with the transitions\n",
    "transitions_df = pd.DataFrame({\n",
    "    'first_transition': t_w,\n",
    "    'second_transition': t_w + t_q,\n",
    "    'sojourn_time': t_q\n",
    "})\n",
    "\n",
    "# Display the first few rows to verify\n",
    "transitions_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original shape: (1000000, 3)\n",
      "Filtered shape: (99714, 3)\n"
     ]
    },
    {
     "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>first_transition</th>\n",
       "      <th>second_transition</th>\n",
       "      <th>sojourn_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>94.177348</td>\n",
       "      <td>95.061607</td>\n",
       "      <td>0.884259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>63.817256</td>\n",
       "      <td>66.938448</td>\n",
       "      <td>3.121192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>43.803766</td>\n",
       "      <td>45.038359</td>\n",
       "      <td>1.234593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>7.362270</td>\n",
       "      <td>8.573102</td>\n",
       "      <td>1.210833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>30.817835</td>\n",
       "      <td>30.993871</td>\n",
       "      <td>0.176037</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    first_transition  second_transition  sojourn_time\n",
       "4          94.177348          95.061607      0.884259\n",
       "17         63.817256          66.938448      3.121192\n",
       "27         43.803766          45.038359      1.234593\n",
       "51          7.362270           8.573102      1.210833\n",
       "68         30.817835          30.993871      0.176037"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Filter the dataframe so only persons with d_w <= age_cutoff remain\n",
    "filtered_transitions_df = transitions_df[transitions_df['first_transition'] <= age_cutoff]\n",
    "\n",
    "# Print the shape to see how many rows remain\n",
    "print(f\"Original shape: {transitions_df.shape}\")\n",
    "print(f\"Filtered shape: {filtered_transitions_df.shape}\")\n",
    "\n",
    "# Display the first few rows of the filtered dataframe\n",
    "filtered_transitions_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "preview_amount = 100\n",
    "# Create a figure with a reasonable size\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "# Plot first transitions in one color and second transitions in another\n",
    "plt.scatter(range(preview_amount), filtered_transitions_df['first_transition'][:preview_amount], \n",
    "           label='First Transition', alpha=0.6, color='blue')\n",
    "plt.scatter(range(preview_amount), filtered_transitions_df['second_transition'][:preview_amount], \n",
    "           label='Second Transition', alpha=0.6, color='red')\n",
    "\n",
    "# Customize the plot\n",
    "plt.xlabel('Person ID')\n",
    "plt.ylabel('Time of Transition')\n",
    "plt.title('Transition Times by Person')\n",
    "plt.legend()\n",
    "\n",
    "# If there are many points, limit the x-axis to show first 100 persons for better visibility\n",
    "plt.xlim(-1, 100)  # Adjust this number based on how many points you want to see\n",
    "\n",
    "# Add grid for better readability\n",
    "plt.grid(True, alpha=0.3)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Integral Verification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "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>first_transition</th>\n",
       "      <th>second_transition</th>\n",
       "      <th>sojourn_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>94.177348</td>\n",
       "      <td>95.061607</td>\n",
       "      <td>0.884259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>63.817256</td>\n",
       "      <td>66.938448</td>\n",
       "      <td>3.121192</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>43.803766</td>\n",
       "      <td>45.038359</td>\n",
       "      <td>1.234593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>7.362270</td>\n",
       "      <td>8.573102</td>\n",
       "      <td>1.210833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>30.817835</td>\n",
       "      <td>30.993871</td>\n",
       "      <td>0.176037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999968</th>\n",
       "      <td>26.630438</td>\n",
       "      <td>28.168056</td>\n",
       "      <td>1.537619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999977</th>\n",
       "      <td>39.125133</td>\n",
       "      <td>39.940033</td>\n",
       "      <td>0.814900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999978</th>\n",
       "      <td>66.942874</td>\n",
       "      <td>68.587374</td>\n",
       "      <td>1.644500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999992</th>\n",
       "      <td>29.593608</td>\n",
       "      <td>29.960425</td>\n",
       "      <td>0.366817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999993</th>\n",
       "      <td>18.489437</td>\n",
       "      <td>18.640261</td>\n",
       "      <td>0.150824</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>99714 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        first_transition  second_transition  sojourn_time\n",
       "4              94.177348          95.061607      0.884259\n",
       "17             63.817256          66.938448      3.121192\n",
       "27             43.803766          45.038359      1.234593\n",
       "51              7.362270           8.573102      1.210833\n",
       "68             30.817835          30.993871      0.176037\n",
       "...                  ...                ...           ...\n",
       "999968         26.630438          28.168056      1.537619\n",
       "999977         39.125133          39.940033      0.814900\n",
       "999978         66.942874          68.587374      1.644500\n",
       "999992         29.593608          29.960425      0.366817\n",
       "999993         18.489437          18.640261      0.150824\n",
       "\n",
       "[99714 rows x 3 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "filtered_transitions_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = filtered_transitions_df.shape[0]\n",
    "\n",
    "# Convert the columns to numpy arrays and sort them.\n",
    "first_transitions = np.sort(filtered_transitions_df['first_transition'].values)\n",
    "second_transitions = np.sort(filtered_transitions_df['second_transition'].values)\n",
    "\n",
    "ages = np.arange(age_cutoff)\n",
    "\n",
    "# For each age in 'ages', the number of preclinical transitions (first_transition <= age)\n",
    "# is given by the insertion point on the right:\n",
    "# searchsorted return indeces where new elements shall be placed in a sorted array in order for\n",
    "# the array to stay sorted. If two elements are equal, the index of the new element will be\n",
    "# as if it were placed on the right of the existing element in this case. \n",
    "preclinical_transition_riemann = np.searchsorted(first_transitions, ages, side='right')/n\n",
    "\n",
    "# For clinical transitions, we need the count of rows with second_transition >= age.\n",
    "# That equals the total count minus the number with second_transition < age.\n",
    "clinical_transition_riemann = (len(second_transitions) - np.searchsorted(second_transitions, ages, side='left'))/n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.        , 0.01004874, 0.02049863, 0.03041699, 0.04085685,\n",
       "       0.05124657, 0.0610847 , 0.07097298, 0.08085123, 0.0907696 ,\n",
       "       0.10092866, 0.11053613, 0.12076539, 0.13018232, 0.14004052,\n",
       "       0.15031991, 0.16057926, 0.17038731, 0.18034579, 0.19025413,\n",
       "       0.19998195, 0.2098602 , 0.21994905, 0.22941613, 0.23977576,\n",
       "       0.24936318, 0.25941192, 0.26962112, 0.27933891, 0.28930742,\n",
       "       0.29995788, 0.30974587, 0.32033616, 0.33075596, 0.3405941 ,\n",
       "       0.3506629 , 0.36071164, 0.37031911, 0.38012716, 0.3899653 ,\n",
       "       0.39988367, 0.40985218, 0.4197204 , 0.42924765, 0.43942676,\n",
       "       0.44941533, 0.4596847 , 0.46957298, 0.47999278, 0.48942977,\n",
       "       0.49936819, 0.50904587, 0.51889404, 0.52920352, 0.53870068,\n",
       "       0.54890988, 0.55868785, 0.56874662, 0.57871513, 0.58847303,\n",
       "       0.59820085, 0.60824959, 0.61799747, 0.6279359 , 0.63858636,\n",
       "       0.64836432, 0.65867381, 0.66871252, 0.67886154, 0.68904066,\n",
       "       0.69889885, 0.70914816, 0.71940751, 0.72909521, 0.73911387,\n",
       "       0.74934312, 0.75922137, 0.76945063, 0.77949937, 0.78953808,\n",
       "       0.80017851, 0.81049802, 0.82029605, 0.83057545, 0.84077462,\n",
       "       0.85092364, 0.86120304, 0.87080049, 0.88085926, 0.89127906,\n",
       "       0.90109714, 0.91108571, 0.9212247 , 0.93140381, 0.9417133 ,\n",
       "       0.9516417 , 0.96148986, 0.97068616, 0.98068476, 0.99022204])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The first value is the relative number of people who experianced the transition S_0 -> S_P\n",
    "# before age 0, the next is the same but before reaching age 1, then before reaching age 2\n",
    "# and so on.\n",
    "\n",
    "preclinical_transition_riemann"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.        , 0.99623924, 0.98875785, 0.9795816 , 0.96966324,\n",
       "       0.95931364, 0.94911447, 0.9394769 , 0.92930782, 0.9193694 ,\n",
       "       0.90921034, 0.89960286, 0.88952404, 0.8796859 , 0.87022885,\n",
       "       0.85977897, 0.8493692 , 0.83947089, 0.82965281, 0.81973444,\n",
       "       0.80959544, 0.79987765, 0.7899994 , 0.78015123, 0.77019275,\n",
       "       0.76018413, 0.75029585, 0.74067834, 0.73057946, 0.72047055,\n",
       "       0.71017109, 0.70026275, 0.68980284, 0.67980424, 0.66942455,\n",
       "       0.65979702, 0.64950759, 0.63956917, 0.62947029, 0.61987284,\n",
       "       0.6097539 , 0.60023668, 0.59032834, 0.58022946, 0.57068215,\n",
       "       0.5607337 , 0.55068496, 0.5405961 , 0.5301061 , 0.52045851,\n",
       "       0.51040977, 0.5009427 , 0.49142548, 0.48132659, 0.47067613,\n",
       "       0.46080791, 0.45109012, 0.44123192, 0.43121327, 0.42135508,\n",
       "       0.411888  , 0.40177909, 0.39179052, 0.38205267, 0.37190364,\n",
       "       0.36176465, 0.35186634, 0.34157691, 0.3313978 , 0.32094791,\n",
       "       0.31093929, 0.3006298 , 0.29027017, 0.28048218, 0.27051367,\n",
       "       0.26079588, 0.25086748, 0.24077863, 0.23026857, 0.2203502 ,\n",
       "       0.21029143, 0.19984155, 0.18976272, 0.17945324, 0.16929418,\n",
       "       0.15906493, 0.1491967 , 0.13906773, 0.12886856, 0.11848888,\n",
       "       0.10892152, 0.09901318, 0.08894438, 0.07876527, 0.06839561,\n",
       "       0.05804601, 0.04817779, 0.03871071, 0.02923361, 0.01937541])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Relative number of people whose second trasnition is time is >= their age\n",
    "\n",
    "clinical_transition_riemann"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(range(len(preclinical_transition_riemann)), preclinical_transition_riemann, \n",
    "           label='First Transition', alpha=0.6, color='blue')\n",
    "plt.scatter(range(len(clinical_transition_riemann)), clinical_transition_riemann, \n",
    "           label='Second Transition', alpha=0.6, color='red')\n",
    "plt.scatter(range(len(clinical_transition_riemann)), \n",
    "            preclinical_transition_riemann * clinical_transition_riemann, \n",
    "           label='Second Transition', alpha=0.6, color='green')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## History Generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def determine_screening_times(t_w, t_q, screening_times, beta, detection_rule=None):\n",
    "    \"\"\"\n",
    "    Determines which screening times a person undergoes given preclinical (t_w) and clinical (t_q) transition times.\n",
    "    This version includes all screening times between t_w and t_q (as a list) and uses a Bernoulli trial with probability beta \n",
    "    at each screening time to decide detection. Once a detection occurs, the screening schedule may be modified via detection_rule.\n",
    "    \n",
    "    Parameters:\n",
    "      t_w (np.array): 1D array of preclinical transition times (onset) for each person.\n",
    "      t_q (np.array): 1D array of clinical transition times for each person.\n",
    "      screening_times (np.array): 1D sorted array of scheduled screening times.\n",
    "      beta (float): Detection probability for a screening (Bernoulli probability).\n",
    "      detection_rule (function, optional): Function that takes (detection_time, screening_times) and returns extra screening times \n",
    "                                           after detection.\n",
    "      \n",
    "    Returns:\n",
    "      results_df (pd.DataFrame): DataFrame with columns:\n",
    "           't_w' - preclinical transition time,\n",
    "           't_q' - clinical transition time,\n",
    "           'all_screening_times' - list of all scheduled screenings between t_w and t_q,\n",
    "           'final_screening_times' - list of screenings up to (and including) detection (with possible additions),\n",
    "           'detected' - Boolean indicating if detection occurred,\n",
    "           'detection_time' - Time at which detection occurred (or np.nan if none).\n",
    "    \"\"\"\n",
    "    # Convert inputs to numpy arrays (if not already)\n",
    "    t_w = np.asarray(t_w)\n",
    "    t_q = np.asarray(t_q)\n",
    "    screening_times = np.asarray(screening_times)\n",
    "    \n",
    "    print(t_w.shape)\n",
    "    n = t_w.shape[0]\n",
    "    \n",
    "    # Precompute indices for the screening_times that fall within [t_w, t_q) for each person.\n",
    "    lower_idx = np.searchsorted(screening_times, t_w, side='left')\n",
    "    upper_idx = np.searchsorted(screening_times, t_q, side='left')\n",
    "\n",
    "    # Consider using list comprehension\n",
    "    # validScrTimes=[t for t in screeningTime if t > t_w]\n",
    "    # validScrTimes=[t for t in validScrTime if t < t_q]\n",
    "    \n",
    "    results = []\n",
    "    \n",
    "    for i in range(n):\n",
    "        # Get all screening times between t_w[i] and t_q[i]\n",
    "        valid_screenings = screening_times[lower_idx[i]:upper_idx[i]]\n",
    "        all_screenings = list(valid_screenings)\n",
    "        \n",
    "        final_screenings = []\n",
    "        detection_occurred = False\n",
    "        detection_time = np.nan\n",
    "        \n",
    "        # Simulate detection at each screening within the valid interval.\n",
    "        for t in valid_screenings:\n",
    "            final_screenings.append(t)\n",
    "            # Bernoulli trial: detection occurs if random number < beta.\n",
    "            if np.random.rand() < beta:\n",
    "                detection_occurred = True\n",
    "                detection_time = t\n",
    "                if detection_rule is not None:\n",
    "                    final_screenings.extend(detection_rule(t, screening_times))\n",
    "                break  # Stop further screenings after detection\n",
    "        \n",
    "        # If no detection occurred, final screenings remain as all valid screenings.\n",
    "        if not detection_occurred:\n",
    "            final_screenings = all_screenings\n",
    "            \n",
    "        results.append({\n",
    "            \"t_w\": t_w[i],\n",
    "            \"t_q\": t_q[i],\n",
    "            \"all_screening_times\": all_screenings,\n",
    "            \"final_screening_times\": final_screenings,\n",
    "            \"detected\": detection_occurred,\n",
    "            \"detection_time\": detection_time\n",
    "        })\n",
    "    \n",
    "    results_df = pd.DataFrame(results)\n",
    "    return results_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def detection_rule(t_detection, screening_times):\n",
    "    \"\"\"\n",
    "    Adjusts screening schedule after detection.\n",
    "    Example: Schedule additional screenings every 0.5 time units for the next 2 periods.\n",
    "    \n",
    "    Parameters:\n",
    "    - t_detection (float): The time at which detection occurred.\n",
    "    - screening_times (np.array): Original screening schedule.\n",
    "    \n",
    "    Returns:\n",
    "    - new_screenings (list): List of new screening times.\n",
    "    \"\"\"\n",
    "    return [t_detection + 0.5, t_detection + 1.0]  # Example new schedule"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(99714,)\n"
     ]
    }
   ],
   "source": [
    "beta = 0.9 # From original problem formulation\n",
    "screening_interval = 1 # Assume screening occurs every year\n",
    "screening_times = np.arange(40, 91, screening_interval) \n",
    "# Generous interpretation of ACS Breast Cancer Screening Guidelines | American Cancer Society\n",
    "# https://www.cancer.org/cancer/types/breast-cancer/screening-tests-and-early-detection/american-cancer-society-recommendations-for-the-early-detection-of-breast-cancer.html\n",
    "\n",
    "histories = determine_screening_times(filtered_transitions_df['first_transition'], \n",
    "    filtered_transitions_df['second_transition'], screening_times, beta)\n",
    "\n",
    "\n",
    "\n",
    "# first = np.searchsorted(screening_times, t_w_cutoff, side='left')\n",
    "# last = np.searchsorted(screening_times, (t_c), side='right')\n",
    "# print(screening_times[first[0]])\n",
    "# print(screening_times[last[0]])\n",
    "# print(t_w_cutoff[0])\n",
    "# print(t_c[0])\n",
    "# print(screening_times[95:96])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>t_w</th>\n",
       "      <th>t_q</th>\n",
       "      <th>all_screening_times</th>\n",
       "      <th>final_screening_times</th>\n",
       "      <th>detected</th>\n",
       "      <th>detection_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>94.177348</td>\n",
       "      <td>95.061607</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>63.817256</td>\n",
       "      <td>66.938448</td>\n",
       "      <td>[64, 65, 66]</td>\n",
       "      <td>[64]</td>\n",
       "      <td>True</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>43.803766</td>\n",
       "      <td>45.038359</td>\n",
       "      <td>[44, 45]</td>\n",
       "      <td>[44, 45]</td>\n",
       "      <td>True</td>\n",
       "      <td>45.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7.362270</td>\n",
       "      <td>8.573102</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>30.817835</td>\n",
       "      <td>30.993871</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>58.302742</td>\n",
       "      <td>58.817196</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>22.712073</td>\n",
       "      <td>25.674626</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>90.047861</td>\n",
       "      <td>90.326187</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>87.649919</td>\n",
       "      <td>89.246482</td>\n",
       "      <td>[88, 89]</td>\n",
       "      <td>[88]</td>\n",
       "      <td>True</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>96.390962</td>\n",
       "      <td>98.051598</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>False</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         t_w        t_q all_screening_times final_screening_times  detected  \\\n",
       "0  94.177348  95.061607                  []                    []     False   \n",
       "1  63.817256  66.938448        [64, 65, 66]                  [64]      True   \n",
       "2  43.803766  45.038359            [44, 45]              [44, 45]      True   \n",
       "3   7.362270   8.573102                  []                    []     False   \n",
       "4  30.817835  30.993871                  []                    []     False   \n",
       "5  58.302742  58.817196                  []                    []     False   \n",
       "6  22.712073  25.674626                  []                    []     False   \n",
       "7  90.047861  90.326187                  []                    []     False   \n",
       "8  87.649919  89.246482            [88, 89]                  [88]      True   \n",
       "9  96.390962  98.051598                  []                    []     False   \n",
       "\n",
       "   detection_time  \n",
       "0             NaN  \n",
       "1            64.0  \n",
       "2            45.0  \n",
       "3             NaN  \n",
       "4             NaN  \n",
       "5             NaN  \n",
       "6             NaN  \n",
       "7             NaN  \n",
       "8            88.0  \n",
       "9             NaN  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "histories.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Verification (beta = 0.9) (screening_interval = 0-99)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Screening Frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Screening Summary Statistics\n",
      "count    99714.000000\n",
      "mean         0.510199\n",
      "std          0.906753\n",
      "min          0.000000\n",
      "25%          0.000000\n",
      "50%          0.000000\n",
      "75%          1.000000\n",
      "max         10.000000\n",
      "Name: all_screening_times, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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2LtVH9erVy5w78jQLCwvMnTsXc+fOxfXr1xEXF4dvvvkGy5Ytg4WFBb7++mtxvAYNGpR6faNGjRATE1Muk3+vX78uFglPj1GyvUmTJhr3+9Zbbz1zgvPTx66kgJJy7F7F0+NaWFgAAJycnMpsL8nnypUrAICAgIBn9p2VlaVWCD7NwcEBK1euxIoVK3DlyhXExMRgzpw5mDJlChwcHDB06FDxkriU421gYICaNWuqtV25cgVZWVmwtbUt8zV37txR25+SD+enPT2vztDQUJwfWELqex14/s/b3Nxc/N17+nf36d/FF6lXrx58fX2fuf3p/jMyMpCZmYlVq1Y981JjyTG7fv16mX/Xyvr9lOrKlSu4ePFiqWP79NglXvQ3JyMjA9nZ2S98/1haWqJnz57YtGkTZsyYAeC/S3NvvfXWM98TbwoWTSSZp6dnmf86eVJ53jDwWX09Pbm0LBs2bEBgYCD8/f0xfvx42NraQl9fH5GRkeIHT3nn9TR9ff0y2wUN7/Lh4uKCIUOGoFevXqhduzY2btyIr7/+WqM+XuVYVtQYRkZGz+yrvI6dpp417ovyKTmLNG/ePLi7u5cZa2pqKikHmUyG+vXro379+vDz80O9evWwceNGDB06VNLrSygUCvEfNSVUKhVsbW3LnK8CQPxwLtmf9evXl/kPmKe/efis4yOVtn7eT3v6PVlyHD755JNnFsTNmjXTeJzn/a48eSxUKhWaNm2KBQsWlBn/dDFfnsdx0KBB2LZtG44cOYKmTZtix44d+Oyzz0q9p940LJqoXLi4uEClUuHKlSviGQjgv0nEmZmZ4uTmEv/88w8EQVD743H58mUAEC+PlPxrMzMzU+1SxNNndMryv//9D7Vr18Yvv/yiNkZERIRanCZFnqb7WN6qV6+OOnXq4Ny5c2I+AHDp0qVSsUlJSahRo4Z4lql69erIzMwsFSflWLq4uDxzjCfzePLnpekYr7uSSyLm5ubPPZOhqdq1a6N69epITU1VG+fcuXMvNU6dOnWwZ88e+Pj4PLdoLRnH1ta2XPfnZZX87iUnJ6NevXpi+z///FOh49rY2MDMzAzFxcUvPA4l96x7+u9aWb87z/t9rF27trhep04dnD59Gp07dy6Xf5Da2NjA3Nxc/BvyPN26dYONjQ02btwILy8vPHr0CAMHDnzlHF53b3bJSOWm5IZxT36bBID4L6Snv+Vy+/ZttW9eZWdn48cff4S7u7v4L9uSP9wHDx4U43Jzc7Fu3boX5lPyL64n/4V19OhRxMfHq8WV3BeorD9gT9N0H1/W6dOncffu3VLt169fx4ULF8TT/Q4ODnB3d8e6devU8j937hz+/PNPtZv41alTB1lZWThz5ozYlpqaKunbbz169MCxY8fUjl1ubi5WrVqFWrVqiXNAyvp5FRcXS/4G1evMw8MDderUwTfffFPm3bszMjKe+/qjR48iNze3VPuxY8dw79498WfesmVLuLq6YtGiRaXes1LOJnz00UcoLi4WL7k8qaioSOxTqVTC3Nwcs2bNKvMbiy/an/JWcvPJFStWqLUvXbq0QsfV19dHnz598PPPP5dZaDx5HHr06IHbt2/jf//7n9j26NGjMt//derUwd9//612z7WdO3fixo0banEfffQRbt26he+++65UH48fPy7zPfM8enp68Pf3x++//44TJ06U2v7ke8jAwAD9+/fH1q1bsXbtWjRt2vSlzqpVNTzTROWiefPmCAgIwKpVq5CZmYkOHTrg2LFjWLduHfz9/dW+Tg78N38pKCgIx48fh52dHVavXo309HSsWbNGjOnatSucnZ0RFBSE8ePHQ19fH6tXr4aNjQ1SUlKem8+7776LX375Bb169YKfnx+Sk5MRFRUFNzc3tQ81IyMjuLm5YcuWLahfvz6srKzQpEmTMq/5a7qPLys2NhYRERF477330Lp1a5iamuLatWtYvXo18vPz1e5JM2/ePHTv3h3e3t4ICgrC48ePsXTpUlhYWKjF9evXDxMnTkSvXr0watQoPHr0CCtXrkT9+vVfODF+0qRJ+Omnn9C9e3eMGjUKVlZWWLduHZKTk/Hzzz+Lp+sbN26M1q1bIzw8HPfv34eVlRU2b96MoqKicjkuukxPTw/ff/89unfvjsaNG2Pw4MF46623cOvWLezbtw/m5ub4/fffn/n69evXY+PGjejVqxc8PDwgl8tx8eJFrF69GoaGhvjiiy/EcVauXImePXvC3d0dgwcPhoODA5KSknD+/HnExMQ8N88OHTrg008/RWRkJBITE9G1a1dUq1YNV65cwbZt27B48WJ88MEHMDc3x8qVKzFw4EC0bNkS/fr1E3/vdu3aBR8fHyxbtqxcj+HzeHh4oE+fPli0aBHu3buH1q1b48CBA+LZ6Yp8juDs2bOxb98+eHl5YdiwYXBzc8P9+/dx8uRJ7NmzB/fv3wcADBs2DMuWLcOgQYOQkJAABwcHrF+/vswbtg4dOhT/+9//0K1bN3z00Ue4evUqNmzYoDaJGwAGDhyIrVu3YsSIEdi3bx98fHxQXFyMpKQkbN26FTExMS+cMvG0WbNm4c8//0SHDh0wfPhwNGrUCKmpqdi2bRsOHTqkdlZ/0KBBWLJkCfbt24c5c+ZofvCqIq18Z49eKyVfJS/rK6pPKiwsFKZNmya4uroK1apVE5ycnITw8HAhLy9PLc7FxUXw8/MTYmJihGbNmgkKhUJo2LChsG3btlJ9JiQkCF5eXoJcLhecnZ2FBQsWSLrlgEqlEmbNmiW4uLgICoVCaNGihbBz584yv3p/5MgRwcPDQ5DL5WpfXy7ra+ma7uPTns6zLNeuXROmTJkitG7dWrC1tRUMDAwEGxsbwc/PT+22BiX27Nkj+Pj4CEZGRoK5ubnQs2dP4cKFC6Xi/vzzT6FJkyaCXC4XGjRoIGzYsEHSLQcEQRCuXr0qfPDBB4KlpaVgaGgoeHp6Cjt37iw1xtWrVwVfX19BoVAIdnZ2whdffCHExsaWecuBxo0bl3p9yVfD582bV2obJHy1/Ekvc8uB4OBgSfmU3Ebh6ffsqVOnhN69ewvW1taCQqEQXFxchI8++kiIi4t7bq5nzpwRxo8fL7Rs2VKwsrISDAwMBAcHB+HDDz8UTp48WSr+0KFDQpcuXQQzMzPBxMREaNasmdrXygMCAgQTE5Nnjrdq1SrBw8NDMDIyEszMzISmTZsKEyZMEG7fvl1qP5VKpWBhYSEYGhoKderUEQIDA4UTJ068cKxnHeOybjmQkZGhFlfW73hubq4QHBwsWFlZCaampoK/v79w6dIlAYAwe/bsZ+6rIDz/ffVkbk///Eukp6cLwcHBgpOTk1CtWjXB3t5e6Ny5s7Bq1Sq1uOvXrwvvvfeeYGxsLNSoUUMIDQ0Vb+fw5PtfEARh/vz5wltvvSUoFArBx8dHOHHiRJl/HwoKCoQ5c+YIjRs3FhQKhVC9enXBw8NDmDZtmpCVlfXC/Mv6fb5+/bowaNAgwcbGRlAoFELt2rWF4ODgUrdpEQRBaNy4saCnpyfcvHnzmcfuTcJnz1Glq1WrFpo0aVLqZnykG5ycnKBUKvH9999rOxWi50pMTESLFi2wYcMG8Y7numb//v3o1KkT9u3bV6HPjKwoLVq0gJWVFeLi4rSdik7gnCYiEhUWFuLevXtqD7gl0gWPHz8u1bZo0SLo6emhffv2Wsio6jtx4gQSExMxaNAgbaeiMziniYgA/Hfzus2bN4uPgyDSJXPnzkVCQgI6deoEAwMD7N69G7t378bw4cNLffWeXs25c+eQkJCA+fPnw8HBocxHtrypWDQREYD/Jrz+888/mDlzJrp06aLtdIjUtGnTBrGxsZgxYwZycnLg7OyMqVOn4ssvv9R2alXO//73P0yfPh0NGjTATz/9VOqB0W8yzmkiIiIikoBzmoiIiIgkYNFEREREJIFW5zTVqlWrzEcsfPbZZ1i+fDny8vIwduxYbN68Gfn5+VAqlVixYgXs7OzE2JSUFIwcORL79u2DqakpAgICEBkZqfZspP379yMsLAznz5+Hk5MTJk+ejMDAQLUxly9fjnnz5iEtLQ3NmzfH0qVL4enpKXlfVCoVbt++DTMzswq90RoRERGVH0EQ8PDhQzg6Or742XravEnUnTt3hNTUVHF5+iZ4I0aMEJycnIS4uDjhxIkTQuvWrYU2bdqIry8qKhKaNGki+Pr6CqdOnRL++OMPoUaNGkJ4eLgYc+3aNcHY2FgICwsTLly4ICxdulTQ19cXoqOjxZjNmzcLcrlcWL16tXD+/Hlh2LBhgqWlpZCeni55X27cuCEA4MKFCxcuXLi8hsuNGzde+FmvUxPBR48ejZ07d+LKlSvIzs6GjY0NNm3ahA8++ADAfw8IbdSoEeLj49G6dWvs3r0b7777Lm7fvi2efYqKisLEiRORkZEBuVyOiRMnYteuXWrPDerXrx8yMzMRHR0NAPDy8sLbb78tPhZApVLByckJn3/+OSZNmiQp96ysLFhaWuLGjRswNzcvz8NCREREFSQ7OxtOTk7IzMyEhYXFc2N15pYDBQUF2LBhA8LCwiCTyZCQkIDCwkK1J0s3bNgQzs7OYtEUHx+Ppk2bql2uUyqVGDlyJM6fP48WLVogPj6+1NOplUolRo8eLY6bkJCA8PBwcbuenh58fX1LPdz1Sfn5+cjPzxfXHz58COC/p5yzaCIiInq9SJlaozMTwbdv347MzExxrlFaWhrkcrnawwMBwM7ODmlpaWLMkwVTyfaSbc+Lyc7OxuPHj3H37l0UFxeXGVPSR1kiIyNhYWEhLry5GhERUdWmM0XTDz/8gO7du8PR0VHbqUgSHh6OrKwscblx44a2UyIiIqIKpBOX565fv449e/bgl19+Edvs7e1RUFCAzMxMtbNN6enpsLe3F2OOHTum1ld6erq4reS/JW1Pxpibm8PIyAj6+vrQ19cvM6akj7IoFAooFArNd5aIiIheSzpxpmnNmjWwtbWFn5+f2Obh4YFq1aqpPVn50qVLSElJgbe3NwDA29sbZ8+exZ07d8SY2NhYmJubw83NTYx5+unMsbGxYh9yuRweHh5qMSqVCnFxcWIMERERkdbPNKlUKqxZswYBAQFq91aysLBAUFAQwsLCYGVlBXNzc3z++efw9vZG69atAQBdu3aFm5sbBg4ciLlz5yItLQ2TJ09GcHCweBZoxIgRWLZsGSZMmIAhQ4Zg79692Lp1K3bt2iWOFRYWhoCAALRq1Qqenp5YtGgRcnNzMXjw4Mo9GERERKS7JN+IqILExMQIAIRLly6V2vb48WPhs88+E6pXry4YGxsLvXr1ElJTU9Vi/v33X6F79+6CkZGRUKNGDWHs2LFCYWGhWsy+ffsEd3d3QS6XC7Vr1xbWrFlTaqylS5cKzs7OglwuFzw9PYW///5bo/3IysoSAAhZWVkavY6IiIi0R5PPb526T9PrLDs7GxYWFsjKyuItB4iIiF4Tmnx+68ScJiIiIiJdx6KJiIiISAIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCSB1u8ITtLcv38fOTk5lT6uqakprKysKn1cIiIiXcOi6TVw//59hIZGICOjoNLHtrGRY/HiaSyciIjojcei6TWQk5ODjIwCGBkNgbGxQ6WN++hRKjIyViMnJ4dFExERvfFYNL1GjI0dYGrqXKljPn5cqcMRERHpLE4EJyIiIpKARRMRERGRBCyaiIiIiCRg0UREREQkAYsmIiIiIglYNBERERFJwKKJiIiISAIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQQsmoiIiIgkYNFEREREJAGLJiIiIiIJWDQRERERScCiiYiIiEgCFk1EREREErBoIiIiIpKARRMRERGRBCyaiIiIiCRg0UREREQkAYsmIiIiIglYNBERERFJoPWi6datW/jkk09gbW0NIyMjNG3aFCdOnBC3C4KAKVOmwMHBAUZGRvD19cWVK1fU+rh//z4GDBgAc3NzWFpaIigoCDk5OWoxZ86cQbt27WBoaAgnJyfMnTu3VC7btm1Dw4YNYWhoiKZNm+KPP/6omJ0mIiKi145Wi6YHDx7Ax8cH1apVw+7du3HhwgXMnz8f1atXF2Pmzp2LJUuWICoqCkePHoWJiQmUSiXy8vLEmAEDBuD8+fOIjY3Fzp07cfDgQQwfPlzcnp2dja5du8LFxQUJCQmYN28epk6dilWrVokxR44cQf/+/REUFIRTp07B398f/v7+OHfuXOUcDCIiItJpMkEQBG0NPmnSJBw+fBh//fVXmdsFQYCjoyPGjh2LcePGAQCysrJgZ2eHtWvXol+/frh48SLc3Nxw/PhxtGrVCgAQHR2NHj164ObNm3B0dMTKlSvx5ZdfIi0tDXK5XBx7+/btSEpKAgD07dsXubm52Llzpzh+69at4e7ujqioqBfuS3Z2NiwsLJCVlQVzc/NXOi5PS0lJwfDhM2Ft/SVMTZ3Lte/nyclJwb17M7Fq1Zdwdq68cYmIiCqLJp/fWj3TtGPHDrRq1QoffvghbG1t0aJFC3z33Xfi9uTkZKSlpcHX11dss7CwgJeXF+Lj4wEA8fHxsLS0FAsmAPD19YWenh6OHj0qxrRv314smABAqVTi0qVLePDggRjz5DglMSXjPC0/Px/Z2dlqCxEREVVdWi2arl27hpUrV6JevXqIiYnByJEjMWrUKKxbtw4AkJaWBgCws7NTe52dnZ24LS0tDba2tmrbDQwMYGVlpRZTVh9PjvGsmJLtT4uMjISFhYW4ODk5abz/RERE9PrQatGkUqnQsmVLzJo1Cy1atMDw4cMxbNgwSZfDtC08PBxZWVnicuPGDW2nRERERBVIq0WTg4MD3Nzc1NoaNWqElJQUAIC9vT0AID09XS0mPT1d3GZvb487d+6obS8qKsL9+/fVYsrq48kxnhVTsv1pCoUC5ubmagsRERFVXVotmnx8fHDp0iW1tsuXL8PFxQUA4OrqCnt7e8TFxYnbs7OzcfToUXh7ewMAvL29kZmZiYSEBDFm7969UKlU8PLyEmMOHjyIwsJCMSY2NhYNGjQQv6nn7e2tNk5JTMk4RERE9GbTatE0ZswY/P3335g1axb++ecfbNq0CatWrUJwcDAAQCaTYfTo0fj666+xY8cOnD17FoMGDYKjoyP8/f0B/Hdmqlu3bhg2bBiOHTuGw4cPIyQkBP369YOjoyMA4OOPP4ZcLkdQUBDOnz+PLVu2YPHixQgLCxNzCQ0NRXR0NObPn4+kpCRMnToVJ06cQEhISKUfFyIiItI9Btoc/O2338avv/6K8PBwTJ8+Ha6urli0aBEGDBggxkyYMAG5ubkYPnw4MjMz0bZtW0RHR8PQ0FCM2bhxI0JCQtC5c2fo6emhT58+WLJkibjdwsICf/75J4KDg+Hh4YEaNWpgypQpavdyatOmDTZt2oTJkyfjiy++QL169bB9+3Y0adKkcg4GERER6TSt3qepKuF9moiIiF4/r819moiIiIheFyyaiIiIiCRg0UREREQkAYsmIiIiIglYNBERERFJwKKJiIiISAIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQQsmoiIiIgkYNFEREREJAGLJiIiIiIJWDQRERERScCiiYiIiEgCFk1EREREErBoIiIiIpKARRMRERGRBCyaiIiIiCRg0UREREQkAYsmIiIiIglYNBERERFJwKKJiIiISAIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQRaLZqmTp0KmUymtjRs2FDcnpeXh+DgYFhbW8PU1BR9+vRBenq6Wh8pKSnw8/ODsbExbG1tMX78eBQVFanF7N+/Hy1btoRCoUDdunWxdu3aUrksX74ctWrVgqGhIby8vHDs2LEK2WciIiJ6PWn9TFPjxo2RmpoqLocOHRK3jRkzBr///ju2bduGAwcO4Pbt2+jdu7e4vbi4GH5+figoKMCRI0ewbt06rF27FlOmTBFjkpOT4efnh06dOiExMRGjR4/G0KFDERMTI8Zs2bIFYWFhiIiIwMmTJ9G8eXMolUrcuXOncg4CERER6TytF00GBgawt7cXlxo1agAAsrKy8MMPP2DBggV455134OHhgTVr1uDIkSP4+++/AQB//vknLly4gA0bNsDd3R3du3fHjBkzsHz5chQUFAAAoqKi4Orqivnz56NRo0YICQnBBx98gIULF4o5LFiwAMOGDcPgwYPh5uaGqKgoGBsbY/Xq1ZV/QIiIiEgnab1ounLlChwdHVG7dm0MGDAAKSkpAICEhAQUFhbC19dXjG3YsCGcnZ0RHx8PAIiPj0fTpk1hZ2cnxiiVSmRnZ+P8+fNizJN9lMSU9FFQUICEhAS1GD09Pfj6+ooxRERERAbaHNzLywtr165FgwYNkJqaimnTpqFdu3Y4d+4c0tLSIJfLYWlpqfYaOzs7pKWlAQDS0tLUCqaS7SXbnheTnZ2Nx48f48GDByguLi4zJikp6Zm55+fnIz8/X1zPzs7WbOeJiIjotaLVoql79+7i/zdr1gxeXl5wcXHB1q1bYWRkpMXMXiwyMhLTpk3TdhpERERUSbR+ee5JlpaWqF+/Pv755x/Y29ujoKAAmZmZajHp6emwt7cHANjb25f6Nl3J+otizM3NYWRkhBo1akBfX7/MmJI+yhIeHo6srCxxuXHjxkvtMxEREb0edKpoysnJwdWrV+Hg4AAPDw9Uq1YNcXFx4vZLly4hJSUF3t7eAABvb2+cPXtW7VtusbGxMDc3h5ubmxjzZB8lMSV9yOVyeHh4qMWoVCrExcWJMWVRKBQwNzdXW4iIiKjq0mrRNG7cOBw4cAD//vsvjhw5gl69ekFfXx/9+/eHhYUFgoKCEBYWhn379iEhIQGDBw+Gt7c3WrduDQDo2rUr3NzcMHDgQJw+fRoxMTGYPHkygoODoVAoAAAjRozAtWvXMGHCBCQlJWHFihXYunUrxowZI+YRFhaG7777DuvWrcPFixcxcuRI5ObmYvDgwVo5LkRERKR7tDqn6ebNm+jfvz/u3bsHGxsbtG3bFn///TdsbGwAAAsXLoSenh769OmD/Px8KJVKrFixQny9vr4+du7ciZEjR8Lb2xsmJiYICAjA9OnTxRhXV1fs2rULY8aMweLFi1GzZk18//33UCqVYkzfvn2RkZGBKVOmIC0tDe7u7oiOji41OZyIiIjeXDJBEARtJ1EVZGdnw8LCAllZWeV+qS4lJQXDh8+EtfWXMDV1Lte+nycnJwX37s3EqlVfwtm58sYlIiKqLJp8fuvUnCYiIiIiXcWiiYiIiEiClyqaioqKsGfPHnz77bd4+PAhAOD27dvIyckp1+SIiIiIdIXGE8GvX7+Obt26ISUlBfn5+ejSpQvMzMwwZ84c5OfnIyoqqiLyJCIiItIqjc80hYaGolWrVnjw4IHaXbt79epV6n5IRERERFWFxmea/vrrLxw5cgRyuVytvVatWrh161a5JUZERESkSzQ+06RSqVBcXFyq/ebNmzAzMyuXpIiIiIh0jcZFU9euXbFo0SJxXSaTIScnBxEREejRo0d55kZERESkMzS+PDd//nwolUq4ubkhLy8PH3/8Ma5cuYIaNWrgp59+qogciYiIiLRO46KpZs2aOH36NDZv3owzZ84gJycHQUFBGDBggNrEcCIiIqKq5KWePWdgYIBPPvmkvHMhIiIi0lmSiqYdO3ZI7vC999576WSIiIiIdJWkosnf319SZzKZrMxv1hERERG97iQVTSqVqqLzICIiItJpfGAvERERkQQvVTTFxcXh3XffRZ06dVCnTh28++672LNnT3nnRkRERKQzNC6aVqxYgW7dusHMzAyhoaEIDQ2Fubk5evTogeXLl1dEjkRERERap/EtB2bNmoWFCxciJCREbBs1ahR8fHwwa9YsBAcHl2uCRERERLpA4zNNmZmZ6NatW6n2rl27Iisrq1ySIiIiItI1GhdN7733Hn799ddS7b/99hvefffdckmKiIiISNdofHnOzc0NM2fOxP79++Ht7Q0A+Pvvv3H48GGMHTsWS5YsEWNHjRpVfpkSERERaZHGRdMPP/yA6tWr48KFC7hw4YLYbmlpiR9++EFcl8lkLJqIiIioytC4aEpOTq6IPIiIiIh02ivd3FIQBAiCUF65EBEREemslyqafvzxRzRt2hRGRkYwMjJCs2bNsH79+vLOjYiIiEhnaHx5bsGCBfjqq68QEhICHx8fAMChQ4cwYsQI3L17F2PGjCn3JImIiIi0TeOiaenSpVi5ciUGDRoktr333nto3Lgxpk6dyqKJiIiIqiSNL8+lpqaiTZs2pdrbtGmD1NTUckmKiIiISNdoXDTVrVsXW7duLdW+ZcsW1KtXr1ySIiIiItI1Gl+emzZtGvr27YuDBw+Kc5oOHz6MuLi4MospIiIioqpA4zNNffr0wdGjR1GjRg1s374d27dvR40aNXDs2DH06tWrInIkIiIi0jqNzzQBgIeHBzZs2FDeuRARERHprJe6T9PVq1cxefJkfPzxx7hz5w4AYPfu3Th//ny5JkdERESkKzQumg4cOICmTZvi6NGj+Pnnn5GTkwMAOH36NCIiIso9QSIiIiJdoHHRNGnSJHz99deIjY2FXC4X29955x38/fff5ZocERERka7QuGg6e/ZsmRO+bW1tcffu3XJJioiIiEjXaFw0WVpalnkTy1OnTuGtt94ql6SIiIiIdI3GRVO/fv0wceJEpKWlQSaTQaVS4fDhwxg3bpzao1WIiIiIqhKNi6ZZs2ahYcOGcHJyQk5ODtzc3NC+fXu0adMGkydProgciYiIiLRO4/s0yeVyfPfdd5gyZQrOnj2LnJwctGjRgo9QISIioipNctGkUqkwb9487NixAwUFBejcuTMiIiJgZGRUkfkRERER6QTJl+dmzpyJL774AqampnjrrbewePFiBAcHV2RuRERERDpDctH0448/YsWKFYiJicH27dvx+++/Y+PGjVCpVOWSyOzZsyGTyTB69GixLS8vD8HBwbC2toapqSn69OmD9PR0tdelpKTAz88PxsbGsLW1xfjx41FUVKQWs3//frRs2RIKhQJ169bF2rVrS42/fPly1KpVC4aGhvDy8sKxY8fKZb+IiIioapBcNKWkpKBHjx7iuq+vL2QyGW7fvv3KSRw/fhzffvstmjVrptY+ZswY/P7779i2bRsOHDiA27dvo3fv3uL24uJi+Pn5oaCgAEeOHMG6deuwdu1aTJkyRYxJTk6Gn58fOnXqhMTERIwePRpDhw5FTEyMGLNlyxaEhYUhIiICJ0+eRPPmzaFUKsVHxBARERFJLpqKiopgaGio1latWjUUFha+UgI5OTkYMGAAvvvuO1SvXl1sz8rKwg8//IAFCxbgnXfegYeHB9asWYMjR46Idx7/888/ceHCBWzYsAHu7u7o3r07ZsyYgeXLl6OgoAAAEBUVBVdXV8yfPx+NGjVCSEgIPvjgAyxcuFAca8GCBRg2bBgGDx4MNzc3REVFwdjYGKtXr36lfSMiIqKqQ3LRJAgCAgMD0bt3b3HJy8vDiBEj1No0FRwcDD8/P/j6+qq1JyQkoLCwUK29YcOGcHZ2Rnx8PAAgPj4eTZs2hZ2dnRijVCqRnZ0tPjw4Pj6+VN9KpVLso6CgAAkJCWoxenp68PX1FWPKkp+fj+zsbLWFiIiIqi7J354LCAgo1fbJJ5+80uCbN2/GyZMncfz48VLb0tLSIJfLYWlpqdZuZ2eHtLQ0MebJgqlke8m258VkZ2fj8ePHePDgAYqLi8uMSUpKembukZGRmDZtmrQdJSIiotee5KJpzZo15TrwjRs3EBoaitjY2FKX/V4H4eHhCAsLE9ezs7Ph5OSkxYyIiIioIml8R/DykpCQgDt37qBly5YwMDCAgYEBDhw4gCVLlsDAwAB2dnYoKChAZmam2uvS09Nhb28PALC3ty/1bbqS9RfFmJubw8jICDVq1IC+vn6ZMSV9lEWhUMDc3FxtISIioqpLa0VT586dcfbsWSQmJopLq1atMGDAAPH/q1Wrhri4OPE1ly5dQkpKCry9vQEA3t7eOHv2rNq33GJjY2Fubg43Nzcx5sk+SmJK+pDL5fDw8FCLUalUiIuLE2OIiIiINH6MSnkxMzNDkyZN1NpMTExgbW0ttgcFBSEsLAxWVlYwNzfH559/Dm9vb7Ru3RoA0LVrV7i5uWHgwIGYO3cu0tLSMHnyZAQHB0OhUAAARowYgWXLlmHChAkYMmQI9u7di61bt2LXrl3iuGFhYQgICECrVq3g6emJRYsWITc3F4MHD66ko0FERES6TmtFkxQLFy6Enp4e+vTpg/z8fCiVSqxYsULcrq+vj507d2LkyJHw9vaGiYkJAgICMH36dDHG1dUVu3btwpgxY7B48WLUrFkT33//PZRKpRjTt29fZGRkYMqUKUhLS4O7uzuio6NLTQ4nIiKiN5dMEAThRUEtW7ZEXFwcqlevjunTp2PcuHEwNjaujPxeG9nZ2bCwsEBWVla5z29KSUnB8OEzYW39JUxNncu17+fJyUnBvXszsWrVl3B2rrxxiYiIKosmn9+S5jRdvHgRubm5AIBp06YhJyfn1bMkIiIieo1Iujzn7u6OwYMHo23bthAEAd988w1MTU3LjH3yESZEREREVYWkomnt2rWIiIjAzp07IZPJsHv3bhgYlH6pTCZj0URERERVkqSiqUGDBti8eTOA/x4xEhcXB1tb2wpNjIiIiEiXaPztOZVKVRF5EBEREem0l7rlwNWrV7Fo0SJcvHgRAODm5obQ0FDUqVOnXJMjIiIi0hUa3xE8JiYGbm5uOHbsGJo1a4ZmzZrh6NGjaNy4MWJjYysiRyIiIiKt0/hM06RJkzBmzBjMnj27VPvEiRPRpUuXckuOiIiISFdofKbp4sWLCAoKKtU+ZMgQXLhwoVySIiIiItI1GhdNNjY2SExMLNWemJjIb9QRERFRlaXx5blhw4Zh+PDhuHbtGtq0aQMAOHz4MObMmYOwsLByT5CIiIhIF2hcNH311VcwMzPD/PnzER4eDgBwdHTE1KlTMWrUqHJPkIiIiEgXaFw0yWQyjBkzBmPGjMHDhw8BAGZmZuWeGBEREZEuean7NJVgsURERERvCo0nghMRERG9iVg0EREREUnAoomIiIhIAo2LpmvXrlVEHkREREQ6TeOiqW7duujUqRM2bNiAvLy8isiJiIiISOdoXDSdPHkSzZo1Q1hYGOzt7fHpp5/i2LFjFZEbERERkc7QuGhyd3fH4sWLcfv2baxevRqpqalo27YtmjRpggULFiAjI6Mi8iQiIiLSqpeeCG5gYIDevXtj27ZtmDNnDv755x+MGzcOTk5OGDRoEFJTU8szTyIiIiKteumi6cSJE/jss8/g4OCABQsWYNy4cbh69SpiY2Nx+/ZtvP/+++WZJxEREZFWaXxH8AULFmDNmjW4dOkSevTogR9//BE9evSAnt5/9ZerqyvWrl2LWrVqlXeuRERERFqjcdG0cuVKDBkyBIGBgXBwcCgzxtbWFj/88MMrJ0dERESkKzQumq5cufLCGLlcjoCAgJdKiIiIiEgXaTynac2aNdi2bVup9m3btmHdunXlkhQRERGRrtG4aIqMjESNGjVKtdva2mLWrFnlkhQRERGRrtG4aEpJSYGrq2updhcXF6SkpJRLUkRERES6RuOiydbWFmfOnCnVfvr0aVhbW5dLUkRERES6RuOiqX///hg1ahT27duH4uJiFBcXY+/evQgNDUW/fv0qIkciIiIirdP423MzZszAv//+i86dO8PA4L+Xq1QqDBo0iHOaiIiIqMrSuGiSy+XYsmULZsyYgdOnT8PIyAhNmzaFi4tLReRHREREpBM0LppK1K9fH/Xr1y/PXIiIiIh0lsZFU3FxMdauXYu4uDjcuXMHKpVKbfvevXvLLTkiIiIiXaFx0RQaGoq1a9fCz88PTZo0gUwmq4i8iIiIiHSKxkXT5s2bsXXrVvTo0aMi8iEiIiLSSRrfckAul6Nu3boVkQsRERGRztK4aBo7diwWL14MQRAqIh8iIiIinaTx5blDhw5h37592L17Nxo3boxq1aqpbf/ll1/KLTkiIiIiXaFx0WRpaYlevXpVRC5EREREOkvjy3Nr1qx57qKJlStXolmzZjA3N4e5uTm8vb2xe/ducXteXh6Cg4NhbW0NU1NT9OnTB+np6Wp9pKSkwM/PD8bGxrC1tcX48eNRVFSkFrN//360bNkSCoUCdevWxdq1a0vlsnz5ctSqVQuGhobw8vLCsWPHNNoXIiIiqto0LpoAoKioCHv27MG3336Lhw8fAgBu376NnJwcjfqpWbMmZs+ejYSEBJw4cQLvvPMO3n//fZw/fx4AMGbMGPz+++/Ytm0bDhw4gNu3b6N3797i64uLi+Hn54eCggIcOXIE69atw9q1azFlyhQxJjk5GX5+fujUqRMSExMxevRoDB06FDExMWLMli1bEBYWhoiICJw8eRLNmzeHUqnEnTt3XubwEBERURUkEzSc0X39+nV069YNKSkpyM/Px+XLl1G7dm2EhoYiPz8fUVFRr5SQlZUV5s2bhw8++AA2NjbYtGkTPvjgAwBAUlISGjVqhPj4eLRu3Rq7d+/Gu+++i9u3b8POzg4AEBUVhYkTJyIjIwNyuRwTJ07Erl27cO7cOXGMfv36ITMzE9HR0QAALy8vvP3221i2bBmA/56l5+TkhM8//xyTJk2SlHd2djYsLCyQlZUFc3PzVzoGT0tJScHw4TNhbf0lTE2dy7Xv58nJScG9ezOxatWXcHauvHGJiIgqiyaf3xqfaQoNDUWrVq3w4MEDGBkZie29evVCXFyc5tn+n+LiYmzevBm5ubnw9vZGQkICCgsL4evrK8Y0bNgQzs7OiI+PBwDEx8ejadOmYsEEAEqlEtnZ2eLZqvj4eLU+SmJK+igoKEBCQoJajJ6eHnx9fcWYsuTn5yM7O1ttISIioqpL44ngf/31F44cOQK5XK7WXqtWLdy6dUvjBM6ePQtvb2/k5eXB1NQUv/76K9zc3JCYmAi5XA5LS0u1eDs7O6SlpQEA0tLS1Aqmku0l254Xk52djcePH+PBgwcoLi4uMyYpKemZeUdGRmLatGka7y8RERG9njQ+06RSqVBcXFyq/ebNmzAzM9M4gQYNGiAxMRFHjx7FyJEjERAQgAsXLmjcT2ULDw9HVlaWuNy4cUPbKREREVEF0rho6tq1KxYtWiSuy2Qy5OTkICIi4qUerVJyh3EPDw9ERkaiefPmWLx4Mezt7VFQUIDMzEy1+PT0dNjb2wMA7O3tS32brmT9RTHm5uYwMjJCjRo1oK+vX2ZMSR9lUSgU4rf+ShYiIiKqujQumubPn4/Dhw/Dzc0NeXl5+Pjjj8VLc3PmzHnlhFQqFfLz8+Hh4YFq1aqpzZO6dOkSUlJS4O3tDQDw9vbG2bNn1b7lFhsbC3Nzc7i5uYkxT8+1io2NFfuQy+Xw8PBQi1GpVIiLixNjiIiIiDSe01SzZk2cPn0amzdvxpkzZ5CTk4OgoCAMGDBAbWK4FOHh4ejevTucnZ3x8OFDbNq0Cfv370dMTAwsLCwQFBSEsLAwWFlZwdzcHJ9//jm8vb3RunVrAP+d9XJzc8PAgQMxd+5cpKWlYfLkyQgODoZCoQAAjBgxAsuWLcOECRMwZMgQ7N27F1u3bsWuXbvEPMLCwhAQEIBWrVrB09MTixYtQm5uLgYPHqzp4SEiIqIqSuOiCQAMDAzwySefvPLgd+7cwaBBg5CamgoLCws0a9YMMTEx6NKlCwBg4cKF0NPTQ58+fZCfnw+lUokVK1aIr9fX18fOnTsxcuRIeHt7w8TEBAEBAZg+fboY4+rqil27dmHMmDFYvHgxatasie+//x5KpVKM6du3LzIyMjBlyhSkpaXB3d0d0dHRpSaHExER0ZtL4/s0/fjjj8/dPmjQoFdK6HXF+zQRERG9fjT5/Nb4TFNoaKjaemFhIR49egS5XA5jY+M3tmgiIiKiqk3jieAPHjxQW3JycnDp0iW0bdsWP/30U0XkSERERKR1L/XsuafVq1cPs2fPLnUWioiIiKiqKJeiCfhvcvjt27fLqzsiIiIinaLxnKYdO3aorQuCgNTUVCxbtgw+Pj7llhgRERGRLtG4aPL391dbl8lksLGxwTvvvIP58+eXV15EREREOkXjokmlUlVEHkREREQ6rdzmNBERERFVZRqfaQoLC5Mcu2DBAk27JyIiItJJGhdNp06dwqlTp1BYWIgGDRoAAC5fvgx9fX20bNlSjJPJZOWXJREREZGWaVw09ezZE2ZmZli3bh2qV68O4L8bXg4ePBjt2rXD2LFjyz1JIiIiIm3TeE7T/PnzERkZKRZMAFC9enV8/fXX/PYcERERVVkaF03Z2dnIyMgo1Z6RkYGHDx+WS1JEREREukbjoqlXr14YPHgwfvnlF9y8eRM3b97Ezz//jKCgIPTu3bsiciQiIiLSOo3nNEVFRWHcuHH4+OOPUVhY+F8nBgYICgrCvHnzyj1BIiIiIl2gcdFkbGyMFStWYN68ebh69SoAoE6dOjAxMSn35IiIiIh0xUvf3DI1NRWpqamoV68eTExMIAhCeeZFREREpFM0Lpru3buHzp07o379+ujRowdSU1MBAEFBQbzdABEREVVZGhdNY8aMQbVq1ZCSkgJjY2OxvW/fvoiOji7X5IiIiIh0hcZzmv7880/ExMSgZs2aau316tXD9evXyy0xIiIiIl2i8Zmm3NxctTNMJe7fvw+FQlEuSRERERHpGo2Lpnbt2uHHH38U12UyGVQqFebOnYtOnTqVa3JEREREukLjy3Nz585F586dceLECRQUFGDChAk4f/487t+/j8OHD1dEjkRERERap/GZpiZNmuDy5cto27Yt3n//feTm5qJ37944deoU6tSpUxE5EhEREWmdRmeaCgsL0a1bN0RFReHLL7+sqJyIiIiIdI5GZ5qqVauGM2fOVFQuRERERDpL48tzn3zyCX744YeKyIWIiIhIZ2k8EbyoqAirV6/Gnj174OHhUeqZcwsWLCi35IiIiIh0hcZF07lz59CyZUsAwOXLl9W2yWSy8smKiIiISMdILpquXbsGV1dX7Nu3ryLzISIiItJJkuc01atXDxkZGeJ63759kZ6eXiFJEREREekayUWTIAhq63/88Qdyc3PLPSEiIiIiXaTxt+eIiIiI3kSSiyaZTFZqojcnfhMREdGbQvJEcEEQEBgYCIVCAQDIy8vDiBEjSt1y4JdffinfDImIiIh0gOSiKSAgQG39k08+KfdkiIiIiHSV5KJpzZo1FZkHERERkU7jRHAiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBJo/MBeerMUFOTh1q1blT6uqakprKysKn1cIiKiZ9Fq0RQZGYlffvkFSUlJMDIyQps2bTBnzhw0aNBAjMnLy8PYsWOxefNm5OfnQ6lUYsWKFbCzsxNjUlJSMHLkSOzbtw+mpqYICAhAZGQkDAz+/+7t378fYWFhOH/+PJycnDB58mQEBgaq5bN8+XLMmzcPaWlpaN68OZYuXQpPT88KPw66Kj8/E0lJFxAevhKGhkaVOraNjRyLF09j4URERDpDq0XTgQMHEBwcjLfffhtFRUX44osv0LVrV1y4cEG8aeaYMWOwa9cubNu2DRYWFggJCUHv3r1x+PBhAEBxcTH8/Pxgb2+PI0eOIDU1FYMGDUK1atUwa9YsAEBycjL8/PwwYsQIbNy4EXFxcRg6dCgcHBygVCoBAFu2bEFYWBiioqLg5eWFRYsWQalU4tKlS7C1tdXOAdKyoqJcFBQooFAEwtq6bqWN++hRKjIyViMnJ4dFExER6QyZ8PSTeLUoIyMDtra2OHDgANq3b4+srCzY2Nhg06ZN+OCDDwAASUlJaNSoEeLj49G6dWvs3r0b7777Lm7fvi2efYqKisLEiRORkZEBuVyOiRMnYteuXTh37pw4Vr9+/ZCZmYno6GgAgJeXF95++20sW7YMAKBSqeDk5ITPP/8ckyZNemHu2dnZsLCwQFZWFszNzcv1uKSkpGD48Jmwtv4SpqbO5dr386Snx+PQofFo23YV7OzcKm3cnJwU3Ls3E6tWfQln58rbXyIievNo8vmtUxPBs7KyAEA8u5CQkIDCwkL4+vqKMQ0bNoSzszPi4+MBAPHx8WjatKna5TqlUons7GycP39ejHmyj5KYkj4KCgqQkJCgFqOnpwdfX18x5mn5+fnIzs5WW4iIiKjq0pmiSaVSYfTo0fDx8UGTJk0AAGlpaZDL5bC0tFSLtbOzQ1pamhjzZMFUsr1k2/NisrOz8fjxY9y9exfFxcVlxpT08bTIyEhYWFiIi5OT08vtOBEREb0WdKZoCg4Oxrlz57B582ZtpyJJeHg4srKyxOXGjRvaTomIiIgqkE7cciAkJAQ7d+7EwYMHUbNmTbHd3t4eBQUFyMzMVDvblJ6eDnt7ezHm2LFjav2lp6eL20r+W9L2ZIy5uTmMjIygr68PfX39MmNK+niaQqGAQqF4uR0mIiKi145WzzQJgoCQkBD8+uuv2Lt3L1xdXdW2e3h4oFq1aoiLixPbLl26hJSUFHh7ewMAvL29cfbsWdy5c0eMiY2Nhbm5Odzc3MSYJ/soiSnpQy6Xw8PDQy1GpVIhLi5OjCEiIqI3m1bPNAUHB2PTpk347bffYGZmJs4fsrCwgJGRESwsLBAUFISwsDBYWVnB3Nwcn3/+Oby9vdG6dWsAQNeuXeHm5oaBAwdi7ty5SEtLw+TJkxEcHCyeCRoxYgSWLVuGCRMmYMiQIdi7dy+2bt2KXbt2ibmEhYUhICAArVq1gqenJxYtWoTc3FwMHjy48g8MERER6RytFk0rV64EAHTs2FGtfc2aNeKNJxcuXAg9PT306dNH7eaWJfT19bFz506MHDkS3t7eMDExQUBAAKZPny7GuLq6YteuXRgzZgwWL16MmjVr4vvvvxfv0QQAffv2RUZGBqZMmYK0tDS4u7sjOjq61ORwIiIiejNptWiScosoQ0NDLF++HMuXL39mjIuLC/7444/n9tOxY0ecOnXquTEhISEICQl5YU5ERET05tGZb88RERER6TIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQQsmoiIiIgkYNFEREREJAGLJiIiIiIJWDQRERERScCiiYiIiEgCFk1EREREErBoIiIiIpKARRMRERGRBCyaiIiIiCRg0UREREQkAYsmIiIiIglYNBERERFJwKKJiIiISAIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQQsmoiIiIgkYNFEREREJAGLJiIiIiIJWDQRERERScCiiYiIiEgCrRZNBw8eRM+ePeHo6AiZTIbt27erbRcEAVOmTIGDgwOMjIzg6+uLK1euqMXcv38fAwYMgLm5OSwtLREUFIScnBy1mDNnzqBdu3YwNDSEk5MT5s6dWyqXbdu2oWHDhjA0NETTpk3xxx9/lPv+EhER0etLq0VTbm4umjdvjuXLl5e5fe7cuViyZAmioqJw9OhRmJiYQKlUIi8vT4wZMGAAzp8/j9jYWOzcuRMHDx7E8OHDxe3Z2dno2rUrXFxckJCQgHnz5mHq1KlYtWqVGHPkyBH0798fQUFBOHXqFPz9/eHv749z585V3M4TERHRa8VAm4N3794d3bt3L3ObIAhYtGgRJk+ejPfffx8A8OOPP8LOzg7bt29Hv379cPHiRURHR+P48eNo1aoVAGDp0qXo0aMHvvnmGzg6OmLjxo0oKCjA6tWrIZfL0bhxYyQmJmLBggVicbV48WJ069YN48ePBwDMmDEDsbGxWLZsGaKioirhSBAREZGu09k5TcnJyUhLS4Ovr6/YZmFhAS8vL8THxwMA4uPjYWlpKRZMAODr6ws9PT0cPXpUjGnfvj3kcrkYo1QqcenSJTx48ECMeXKckpiSccqSn5+P7OxstYWIiIiqLp0tmtLS0gAAdnZ2au12dnbitrS0NNja2qptNzAwgJWVlVpMWX08OcazYkq2lyUyMhIWFhbi4uTkpOkuEhER0WtEZ4smXRceHo6srCxxuXHjhrZTIiIiogqks0WTvb09ACA9PV2tPT09Xdxmb2+PO3fuqG0vKirC/fv31WLK6uPJMZ4VU7K9LAqFAubm5moLERERVV06WzS5urrC3t4ecXFxYlt2djaOHj0Kb29vAIC3tzcyMzORkJAgxuzduxcqlQpeXl5izMGDB1FYWCjGxMbGokGDBqhevboY8+Q4JTEl4xARERFptWjKyclBYmIiEhMTAfw3+TsxMREpKSmQyWQYPXo0vv76a+zYsQNnz57FoEGD4OjoCH9/fwBAo0aN0K1bNwwbNgzHjh3D4cOHERISgn79+sHR0REA8PHHH0MulyMoKAjnz5/Hli1bsHjxYoSFhYl5hIaGIjo6GvPnz0dSUhKmTp2KEydOICQkpLIPCREREekord5y4MSJE+jUqZO4XlLIBAQEYO3atZgwYQJyc3MxfPhwZGZmom3btoiOjoahoaH4mo0bNyIkJASdO3eGnp4e+vTpgyVLlojbLSws8OeffyI4OBgeHh6oUaMGpkyZonYvpzZt2mDTpk2YPHkyvvjiC9SrVw/bt29HkyZNKuEoEBER0etAq0VTx44dIQjCM7fLZDJMnz4d06dPf2aMlZUVNm3a9NxxmjVrhr/++uu5MR9++CE+/PDD5ydMREREbyydndNEREREpEtYNBERERFJwKKJiIiISAIWTUREREQSsGgiIiIikkCr354j0jX3799HTk5OpY9ramoKKyurSh+XiIikY9FE9H/u37+P0NAIZGQUVPrYNjZyLF48jYUTEZEOY9FE9H9ycnKQkVEAI6MhMDZ2qLRxHz1KRUbGauTk5LBoIiLSYSyaiJ5ibOwAU1PnSh3z8eNKHY6IiF4CJ4ITERERScCiiYiIiEgCFk1EREREErBoIiIiIpKARRMRERGRBCyaiIiIiCRg0UREREQkAYsmIiIiIglYNBERERFJwKKJiIiISAIWTUREREQSsGgiIiIikoBFExEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQQsmoiIiIgkMNB2AkQEFBTk4datW5U+rqmpKaysrCp9XCKi1xGLJiIty8/PRFLSBYSHr4ShoVGljm1jI8fixdNYOBERScCiiUjLiopyUVCggEIRCGvrupU27qNHqcjIWI2cnBwWTUREErBoItIRRkb2MDV1rtQxHz+u1OGIiF5rnAhOREREJAGLJiIiIiIJWDQRERERScCiiYiIiEgCTgQnokp3//595OTkVPq4vC8VEb0KFk1EVKnu37+P0NAIZGQUVPrYvC8VEb0KFk1PWb58OebNm4e0tDQ0b94cS5cuhaenp7bTIqoycnJykJFRACOjITA2dqi0cXlfKiJ6VSyanrBlyxaEhYUhKioKXl5eWLRoEZRKJS5dugRbW1ttp0dUpRgbO/C+VET0WmHR9IQFCxZg2LBhGDx4MAAgKioKu3btwurVqzFp0iQtZ0dEr4rP+COiV8Gi6f8UFBQgISEB4eHhYpuenh58fX0RHx+vxcyIqDy8ic/409aE+8LCQlSrVq3Sx2VxShWNRdP/uXv3LoqLi2FnZ6fWbmdnh6SkpFLx+fn5yM/PF9ezsrIAANnZ2eWe28OHD1FUVICsrH9QWPiw3Pt/9rj/QqUqwsOHVyGXC5U27qNH6Xj8OAeXL1/Gw4eVt7+pqanIy8vlca5g2jrODx6cR16ePgoLO8LY+K1KGzc//z5SUnbi5MmTcHCovDlcWVlZ+Oab71ABf5Keq6AgDykpV+Di0rDSCydzcwHjxg2HhYVFpY5Llcfc3Lzcf74ln9uCIOHvr0CCIAjCrVu3BADCkSNH1NrHjx8veHp6loqPiIgQAHDhwoULFy5cqsBy48aNF9YKPNP0f2rUqAF9fX2kp6ertaenp8Pe3r5UfHh4OMLCwsR1lUqF+/fvw9raGjKZrFxzy87OhpOTE27cuAFzc/Ny7Zv+Px7nysHjXDl4nCsHj3PlqahjLQgCHj58CEdHxxfGsmj6P3K5HB4eHoiLi4O/vz+A/wqhuLg4hISElIpXKBRQKBRqbZaWlhWao7m5OX8pKwGPc+Xgca4cPM6Vg8e58lTEsZZ6yY9F0xPCwsIQEBCAVq1awdPTE4sWLUJubq74bToiIiJ6c7FoekLfvn2RkZGBKVOmIC0tDe7u7oiOji41OZyIiIjePCyanhISElLm5ThtUigUiIiIKHU5kMoXj3Pl4HGuHDzOlYPHufLowrGWCYKU79gRERERvdn0tJ0AERER0euARRMRERGRBCyaiIiIiCRg0UREREQkAYsmHbd8+XLUqlULhoaG8PLywrFjx7SdUpUTGRmJt99+G2ZmZrC1tYW/vz8uXbqk7bSqtNmzZ0Mmk2H06NHaTqVKunXrFj755BNYW1vDyMgITZs2xYkTJ7SdVpVSXFyMr776Cq6urjAyMkKdOnUwY8YMac8vo2c6ePAgevbsCUdHR8hkMmzfvl1tuyAImDJlChwcHGBkZARfX19cuXKl0vJj0aTDtmzZgrCwMERERODkyZNo3rw5lEol7ty5o+3UqpQDBw4gODgYf//9N2JjY1FYWIiuXbsiNzdX26lVScePH8e3336LZs2aaTuVKunBgwfw8fFBtWrVsHv3bly4cAHz589H9erVtZ1alTJnzhysXLkSy5Ytw8WLFzFnzhzMnTsXS5cu1XZqr7Xc3Fw0b94cy5cvL3P73LlzsWTJEkRFReHo0aMwMTGBUqlEXl5e5SRYHg+7pYrh6ekpBAcHi+vFxcWCo6OjEBkZqcWsqr47d+4IAIQDBw5oO5Uq5+HDh0K9evWE2NhYoUOHDkJoaKi2U6pyJk6cKLRt21bbaVR5fn5+wpAhQ9TaevfuLQwYMEBLGVU9AIRff/1VXFepVIK9vb0wb948sS0zM1NQKBTCTz/9VCk58UyTjiooKEBCQgJ8fX3FNj09Pfj6+iI+Pl6LmVV9WVlZAAArKystZ1L1BAcHw8/PT+19TeVrx44daNWqFT788EPY2tqiRYsW+O6777SdVpXTpk0bxMXF4fLlywCA06dP49ChQ+jevbuWM6u6kpOTkZaWpvb3w8LCAl5eXpX2ucg7guuou3fvori4uNQjXOzs7JCUlKSlrKo+lUqF0aNHw8fHB02aNNF2OlXK5s2bcfLkSRw/flzbqVRp165dw8qVKxEWFoYvvvgCx48fx6hRoyCXyxEQEKDt9KqMSZMmITs7Gw0bNoS+vj6Ki4sxc+ZMDBgwQNupVVlpaWkAUObnYsm2isaiiegJwcHBOHfuHA4dOqTtVKqUGzduIDQ0FLGxsTA0NNR2OlWaSqVCq1atMGvWLABAixYtcO7cOURFRbFoKkdbt27Fxo0bsWnTJjRu3BiJiYkYPXo0HB0deZyrMF6e01E1atSAvr4+0tPT1drT09Nhb2+vpayqtpCQEOzcuRP79u1DzZo1tZ1OlZKQkIA7d+6gZcuWMDAwgIGBAQ4cOIAlS5bAwMAAxcXF2k6xynBwcICbm5taW6NGjZCSkqKljKqm8ePHY9KkSejXrx+aNm2KgQMHYsyYMYiMjNR2alVWyWefNj8XWTTpKLlcDg8PD8TFxYltKpUKcXFx8Pb21mJmVY8gCAgJCcGvv/6KvXv3wtXVVdspVTmdO3fG2bNnkZiYKC6tWrXCgAEDkJiYCH19fW2nWGX4+PiUumXG5cuX4eLioqWMqqZHjx5BT0/9I1RfXx8qlUpLGVV9rq6usLe3V/tczM7OxtGjRyvtc5GX53RYWFgYAgIC0KpVK3h6emLRokXIzc3F4MGDtZ1alRIcHIxNmzbht99+g5mZmXht3MLCAkZGRlrOrmowMzMrNUfMxMQE1tbWnDtWzsaMGYM2bdpg1qxZ+Oijj3Ds2DGsWrUKq1at0nZqVUrPnj0xc+ZMODs7o3Hjxjh16hQWLFiAIUOGaDu111pOTg7++ecfcT05ORmJiYmwsrKCs7MzRo8eja+//hr16tWDq6srvvrqKzg6OsLf379yEqyU7+jRS1u6dKng7OwsyOVywdPTU/j777+1nVKVA6DMZc2aNdpOrUrjLQcqzu+//y40adJEUCgUQsOGDYVVq1ZpO6UqJzs7WwgNDRWcnZ0FQ0NDoXbt2sKXX34p5Ofnazu119q+ffvK/HscEBAgCMJ/tx346quvBDs7O0GhUAidO3cWLl26VGn5yQSBty8lIiIiehHOaSIiIiKSgEUTERERkQQsmoiIiIgkYNFEREREJAGLJiIiIiIJWDQRERERScCiiYiIiEgCFk1EpBX//vsvZDIZEhMTtZ2KKCkpCa1bt4ahoSHc3d21nU6508VjTvQ6YdFE9IYKDAyETCbD7Nmz1dq3b98OmUympay0KyIiAiYmJrh06ZLa862elJGRgZEjR8LZ2RkKhQL29vZQKpU4fPhwJWerOScnJ6SmpvLRNUQviUUT0RvM0NAQc+bMwYMHD7SdSrkpKCh46ddevXoVbdu2hYuLC6ytrcuM6dOnD06dOoV169bh8uXL2LFjBzp27Ih79+691JjFxcWV9pBXfX192Nvbw8CAjx0lehksmojeYL6+vrC3t0dkZOQzY6ZOnVrqUtWiRYtQq1YtcT0wMBD+/v6YNWsW7OzsYGlpienTp6OoqAjjx4+HlZUVatasiTVr1pTqPykpCW3atIGhoSGaNGmCAwcOqG0/d+4cunfvDlNTU9jZ2WHgwIG4e/euuL1jx44ICQnB6NGjUaNGDSiVyjL3Q6VSYfr06ahZsyYUCgXc3d0RHR0tbpfJZEhISMD06dMhk8kwderUUn1kZmbir7/+wpw5c9CpUye4uLjA09MT4eHheO+999TiPv30U9jZ2Yn7tXPnTgDA2rVrYWlpiR07dsDNzQ0KhQIpKSnIz8/HuHHj8NZbb8HExAReXl7Yv3+/2viHDh1Cu3btYGRkBCcnJ4waNQq5ubni9lq1amHWrFkYMmQIzMzM4OzsrPag3qcvz+3fvx8ymQxxcXFo1aoVjI2N0aZNG1y6dElt3K+//hq2trYwMzPD0KFDMWnSJLX3xP79++Hp6QkTExNYWlrCx8cH169fL/PnQPQ6Y9FE9AbT19fHrFmzsHTpUty8efOV+tq7dy9u376NgwcPYsGCBYiIiMC7776L6tWr4+jRoxgxYgQ+/fTTUuOMHz8eY8eOxalTp+Dt7Y2ePXuKZ20yMzPxzjvvoEWLFjhx4gSio6ORnp6Ojz76SK2PdevWQS6X4/Dhw4iKiiozv8WLF2P+/Pn45ptvcObMGSiVSrz33nu4cuUKACA1NRWNGzfG2LFjkZqainHjxpXqw9TUFKampti+fTvy8/PLHEelUqF79+44fPgwNmzYgAsXLmD27NnQ19cXYx49eoQ5c+bg+++/x/nz52Fra4uQkBDEx8dj8+bNOHPmDD788EN069ZNzO/q1avo1q0b+vTpgzNnzmDLli04dOgQQkJC1MafP38+WrVqhVOnTuGzzz7DyJEjSxVBT/vyyy8xf/58nDhxAgYGBhgyZIi4bePGjZg5cybmzJmDhIQEODs7Y+XKleL2oqIi+Pv7o0OHDjhz5gzi4+MxfPjwN/YSL1VxlfZoYCLSKQEBAcL7778vCIIgtG7dWhgyZIggCILw66+/Ck/+aYiIiBCaN2+u9tqFCxcKLi4uan25uLgIxcXFYluDBg2Edu3aietFRUWCiYmJ8NNPPwmCIAjJyckCAGH27NliTGFhoVCzZk1hzpw5giAIwowZM4SuXbuqjX3jxg0BgPhk8w4dOggtWrR44f46OjoKM2fOVGt7++23hc8++0xcb968uRAREfHcfv73v/8J1atXFwwNDYU2bdoI4eHhwunTp8XtMTExgp6e3jOfvL5mzRoBgJCYmCi2Xb9+XdDX1xdu3bqlFtu5c2chPDxcEARBCAoKEoYPH662/a+//hL09PSEx48fC4IgCC4uLsInn3wiblepVIKtra2wcuVKQRD+/zE/deqUIAj//4nye/bsEV+za9cuAYDYp5eXlxAcHKw2ro+Pj/ieuHfvngBA2L9//3OPG1FVwDNNRIQ5c+Zg3bp1uHjx4kv30bhxY+jp/f8/KXZ2dmjatKm4rq+vD2tra9y5c0ftdd7e3uL/GxgYoFWrVmIep0+fxr59+8QzPKampmjYsCGA/868lPDw8HhubtnZ2bh9+zZ8fHzU2n18fDTe5z59+uD27dvYsWMHunXrhv3796Nly5ZYu3YtACAxMRE1a9ZE/fr1n9mHXC5Hs2bNxPWzZ8+iuLgY9evXV9vXAwcOiPt5+vRprF27Vm27UqmESqVCcnKy2NeT/cpkMtjb25c65k978jUODg4AIL7m0qVL8PT0VIt/ct3KygqBgYFQKpXo2bMnFi9ejNTU1OeOR/S64mxAIkL79u2hVCoRHh6OwMBAtW16enoQBEGtrbCwsFQf1apVU1uXyWRltmky6TknJwc9e/bEnDlzSm0r+XAHABMTE8l9lgdDQ0N06dIFXbp0wVdffYWhQ4ciIiICgYGBMDIyeuHrjYyM1C5f5eTkQF9fHwkJCWqX8YD/LgmWxHz66acYNWpUqf6cnZ3F/3+ZY/7ka0ry0uTntGbNGowaNQrR0dHYsmULJk+ejNjYWLRu3VpyH0SvA55pIiIAwOzZs/H7778jPj5erd3GxgZpaWlqhVN53ufn77//Fv+/qKgICQkJaNSoEQCgZcuWOH/+PGrVqoW6deuqLZoUSubm5nB0dCx1W4DDhw/Dzc3tlffBzc1NnJDdrFkz3Lx5E5cvX5b8+hYtWqC4uBh37twptZ/29vYA/jsWFy5cKLW9bt26kMvlr7wPz9KgQQMcP35cre3p9ZJ9CA8Px5EjR9CkSRNs2rSpwnIi0hYWTUQEAGjatCkGDBiAJUuWqLV37NgRGRkZmDt3Lq5evYrly5dj9+7d5Tbu8uXL8euvvyIpKQnBwcF48OCBOBE5ODgY9+/fR//+/XH8+HFcvXoVMTExGDx4MIqLizUaZ/z48ZgzZw62bNmCS5cuYdKkSUhMTERoaKjkPu7du4d33nkHGzZswJkzZ5CcnIxt27Zh7ty5eP/99wEAHTp0QPv27dGnTx/ExsYiOTkZu3fvVvum3tPq16+PAQMGYNCgQfjll1+QnJyMY8eOITIyErt27QIATJw4EUeOHEFISAgSExNx5coV/Pbbb6Umgpe3zz//HD/88APWrVuHK1eu4Ouvv8aZM2fEM1LJyckIDw9HfHw8rl+/jj///BNXrlwRC1+iqoRFExGJpk+fXuqyTKNGjbBixQosX74czZs3x7Fjx8r8ZtnLmj17NmbPno3mzZvj0KFD2LFjB2rUqAEA4tmh4uJidO3aFU2bNsXo0aNhaWmpNn9KilGjRiEsLAxjx45F06ZNER0djR07dqBevXqS+zA1NYWXlxcWLlyI9u3bo0mTJvjqq68wbNgwLFu2TIz7+eef8fbbb6N///5wc3PDhAkTXljkrVmzBoMGDcLYsWPRoEED+Pv74/jx4+Klt2bNmuHAgQO4fPky2rVrhxYtWmDKlClwdHTU6DhoasCAAQgPD8e4cePQsmVLJCcnIzAwEIaGhgAAY2NjJCUloU+fPqhfvz6GDx+O4OBgfPrppxWaF5E2yISnJysQERE9R5cuXWBvb4/169drOxWiSsWJ4ERE9EyPHj1CVFQUlEol9PX18dNPP2HPnj2IjY3VdmpElY5nmoiI6JkeP36Mnj174tSpU8jLy0ODBg0wefJk9O7dW9upEVU6Fk1EREREEnAiOBEREZEELJqIiIiIJGDRRERERCQBiyYiIiIiCVg0EREREUnAoomIiIhIAhZNRERERBKwaCIiIiKSgEUTERERkQT/D6RKRRDZiNKWAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How can I verify the results visually?\n",
    "# - Summary statistics\n",
    "\n",
    "# Number of screenings\n",
    "print(\"Screening Summary Statistics\")\n",
    "sojourn_time_screenings = histories['all_screening_times'].apply(len)\n",
    "print(sojourn_time_screenings.describe())\n",
    "\n",
    "plt.hist(sojourn_time_screenings, bins=15, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Number of Screenings')\n",
    "plt.ylabel('Frequency of People')\n",
    "plt.title('Population Soujourn Time Screening Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Interval Cancers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Interval Cancer Statistics\n",
      "Proportion of people with cancer who were not detected: 69376 70%\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Propertion of people with no screenings in sojourn period: 67158 67%\n",
      "Proportion not detected due to no screening: 97%\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# - Aggregate by reasons for not being caught\n",
    "\n",
    "print('Interval Cancer Statistics')\n",
    "undetected_indices = histories[~histories['detected']]\n",
    "print('Proportion of people with cancer who were not detected:', len(undetected_indices), \n",
    "    '{:.0%}'.format(len(undetected_indices)/len(histories)))\n",
    "no_screening_times_indices = histories[histories['all_screening_times'].apply(len) == 0] \n",
    "print('Propertion of people with no screenings in sojourn period:', len(no_screening_times_indices),\n",
    "    '{:.0%}'.format(len(no_screening_times_indices)/len(histories)))\n",
    "print('Proportion not detected due to no screening:', \n",
    "    '{:.0%}'.format(len(no_screening_times_indices)/len(undetected_indices)))\n",
    "\n",
    "plt.hist(undetected_indices['t_w'], bins=100, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Age of Preclinical Transition')\n",
    "plt.ylabel('Frequency of People')\n",
    "plt.title('Preclinical Transition Age Distribution of Undetected People')\n",
    "plt.show()\n",
    "\n",
    "plt.hist(undetected_indices['t_q'] - undetected_indices['t_w'], bins=80, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Length of Sojourn Time')\n",
    "plt.ylabel('Frequency of People')\n",
    "plt.title('Sojourn Time Distribution of Undetected People')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Late Age Preclinical Transition"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "elderly_undetected = undetected_indices[undetected_indices['t_w'] > 35]\n",
    "plt.hist(elderly_undetected['t_w'], bins=130, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Age of Preclinical Transition')\n",
    "plt.ylabel('Frequency of People')\n",
    "plt.title('Preclinical Transition Age (> 90) Distribution of Undetected People')\n",
    "plt.show()\n",
    "\n",
    "# focus on one year (should be exponential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Screening Frequency of Interval Cancers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Undetected Cancer Screening Frequency Summary Statistics\n",
      "count    69376.000000\n",
      "mean         0.033167\n",
      "std          0.185790\n",
      "min          0.000000\n",
      "25%          0.000000\n",
      "50%          0.000000\n",
      "75%          0.000000\n",
      "max          3.000000\n",
      "Name: all_screening_times, dtype: float64\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "undetected_all_screening_times = undetected_indices['all_screening_times'].apply(len)\n",
    "\n",
    "print(\"Undetected Cancer Screening Frequency Summary Statistics\")\n",
    "print(undetected_all_screening_times.describe())\n",
    "\n",
    "plt.hist(undetected_all_screening_times, bins=20, density=False, alpha=0.6, color='b', edgecolor='black')\n",
    "plt.xlabel('Number of Screenings')\n",
    "plt.ylabel('Frequency of People')\n",
    "plt.title('Undetected Sojourn Time Screening Frequency')\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}