component_failure_model.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8f5e1a26",
   "metadata": {},
   "source": [
    "# Component Failure Prediction\n",
    "## Model Training File"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04b7dbd8",
   "metadata": {},
   "source": [
    "### Task\n",
    "1. Predict Component Level (serial number) unscheduled removals [quick link](#model_prediction)\n",
    "2. Show different stages of ML Pipeline (EDA, feature selection, data manipulation)\n",
    "3. Bring ML Pipeline in production (TBU)\n",
    "4. Provide API endpoints (TBU)\n",
    "5. requirements.txt file [quick link](#requirements)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d4d7a27",
   "metadata": {},
   "source": [
    "<a id='index'></a>\n",
    "### Index\n",
    "- [Libraries](#libraries)\n",
    "- 9. [Model Building and Training](#model_building)\n",
    "    - 9.1 [Kaplan Meier Model](#km)\n",
    "    - 9.2 [Kaplan Meier Estimate of Individual Features](#kmi)\n",
    "        - 9.2.1 [Estimation for Operator](#km1)\n",
    "        - 9.2.2 [Estimation for Fleet](#km2)\n",
    "        - 9.2.3 [Estimation for Aircraft](#km3)        \n",
    "    - 9.3 [Cox Proportional Hazard Model](#cph)\n",
    "        - 9.3.1 [CoxPH Model Data Summary](#cphs)\n",
    "        - 9.3.2 [Individual Component Survival Regression](#cphi)    \n",
    "- 10. [Model Predicted Probability](#model_prediction)\n",
    "- [Requirements.txt](#requirements)\n",
    "- [End](#end)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02eb01bb",
   "metadata": {},
   "source": [
    "<a id='report'></a>\n",
    "### Report Links\n",
    "\n",
    "- 1. Data Cleaning (Other File)\n",
    "- 2. Exploratory Analysis (Other File)\n",
    "- 3. Feature Selection (Other File)\n",
    "- 4. Feature Engineering (Other File)\n",
    "- 5. [Model Training](#cphs)\n",
    "- 6. [Model Summary](#cphs)\n",
    "- 7. [Individual Component Predictions](#model_prediction)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a492bfed",
   "metadata": {},
   "source": [
    "<a id='libraries'></a>\n",
    "###  Libraries\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "01ea710c",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import sys\n",
    "sys.path.append('/usr/local/lib/python2.7/dist-packages')\n",
    "sys.path.append('/Library/Frameworks/Python.framework/Versions/3.9/lib/python3.9/site-packages')\n",
    "\n",
    "import pandas as pd\n",
    "import session_info\n",
    "\n",
    "# EDA\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Lifeline package for the Survival Analysis\n",
    "from lifelines.plotting import plot_lifetimes\n",
    "from lifelines import KaplanMeierFitter\n",
    "from lifelines import CoxPHFitter  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9abdd5fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "figsize(12,6)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50429ed7",
   "metadata": {},
   "source": [
    "<a id='model_building'></a>\n",
    "## 9. Model Building and Training\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8ecabee7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   FLEET_CD  AIRCRAFT_CD OPERATOR_CD  TIME_SINCE_INSTALL_CYCLES  \\\n",
      "0       737          479         VST                          0   \n",
      "1       737          478         VST                       2325   \n",
      "2       737          478         VST                          8   \n",
      "3       737          479         VST                         24   \n",
      "4       737          479         VST                          6   \n",
      "\n",
      "   REPETITIVE_FAULT_QT     MEL_QTY  REMOVED_BOOL  COMPONENT_LIFE_DAYS  \\\n",
      "0                    0  165.974648             1                    0   \n",
      "1                    9  366.000000             1                  848   \n",
      "2                    1    1.000000             1                    2   \n",
      "3                    2    7.000000             1                   15   \n",
      "4                    1  165.974648             1                    1   \n",
      "\n",
      "   AIRCRAFT_AGE  \n",
      "0          8030  \n",
      "1          5840  \n",
      "2          6570  \n",
      "3          6935  \n",
      "4          7300  \n"
     ]
    }
   ],
   "source": [
    "df = pd.read_csv('data/processed/filtered_data.csv')\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d9dcb36",
   "metadata": {},
   "source": [
    "<a id='km'></a>\n",
    "### 9.1 Kaplan Meier Model\n",
    "#### Estimate of Component Failure\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "41b4e1e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timeline'>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "durations = df['COMPONENT_LIFE_DAYS'] ## Time to event data of censored and event data\n",
    "event_observed = df['REMOVED_BOOL']  ## It has removed as (1) and installed as (0)\n",
    "\n",
    "## create a kmf object as km\n",
    "km = KaplanMeierFitter() ## instantiate the class to create an object\n",
    "\n",
    "## Fit the data into the model\n",
    "km.fit(durations, event_observed, label='Kaplan Meier Estimate')\n",
    "\n",
    "## Create an estimate\n",
    "km.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fbd1d985",
   "metadata": {},
   "source": [
    "<a id='kmi'></a>\n",
    "### 9.2 Kaplan Meier Estimation for Individual Features\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef56e5f8",
   "metadata": {},
   "source": [
    "<a id='km1'></a>\n",
    "#### 9.2.1 Kaplan Meier Estimation for Operator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fbb4092f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmf = KaplanMeierFitter() \n",
    "\n",
    "\n",
    "T = df['COMPONENT_LIFE_DAYS']     ## time to event\n",
    "E = df['REMOVED_BOOL']      ## event occurred or censored\n",
    "\n",
    "\n",
    "groups = df['OPERATOR_CD']             ## Create the cohorts from the 'Contract' column\n",
    "ix1 = (groups == 'VST')   ## Cohort 1\n",
    "ix2 = (groups == 'JUE')         ## Cohort 2\n",
    "         ## Cohort 3\n",
    "\n",
    "\n",
    "kmf.fit(T[ix1], E[ix1], label='Operator VST')    ## fit the cohort 1 data\n",
    "ax = kmf.plot()\n",
    "\n",
    "\n",
    "kmf.fit(T[ix2], E[ix2], label='Operator JUE')         ## fit the cohort 2 data\n",
    "ax1 = kmf.plot(ax=ax)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4b3899fb",
   "metadata": {},
   "source": [
    "<a id='km2'></a>\n",
    "#### 9.2.2 Kaplan Meier Estimation for Fleet\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "10747f2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmf = KaplanMeierFitter() \n",
    "\n",
    "groups = df['FLEET_CD']             ## Create the cohorts from the 'Contract' column\n",
    "ix1 = (groups == 737)   ## Cohort 1\n",
    "ix2 = (groups == 787)         ## Cohort 2\n",
    "         ## Cohort 3\n",
    "\n",
    "kmf.fit(T[ix1], E[ix1], label='Fleet 737')    ## fit the cohort 1 data\n",
    "ax = kmf.plot()\n",
    "\n",
    "kmf.fit(T[ix2], E[ix2], label='Fleet 737')         ## fit the cohort 2 data\n",
    "ax1 = kmf.plot(ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b551d9f",
   "metadata": {},
   "source": [
    "<a id='km3'></a>\n",
    "#### 9.2.3 Kaplan Meier Estimation for Aircraft\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e29e0e1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "763    1576\n",
       "784    1472\n",
       "955    1361\n",
       "478    1317\n",
       "835    1177\n",
       "479    1092\n",
       "527     965\n",
       "915     830\n",
       "925     499\n",
       "708      34\n",
       "Name: AIRCRAFT_CD, dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['AIRCRAFT_CD'].value_counts(dropna= False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "225462fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timeline'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmf = KaplanMeierFitter() \n",
    "\n",
    "groups = df['AIRCRAFT_CD']\n",
    "ix1 = (groups == 763)\n",
    "ix2 = (groups == 784)\n",
    "ix3 = (groups == 955)\n",
    "ix4 = (groups == 478)\n",
    "\n",
    "\n",
    "\n",
    "## fit the cohort 1 data\n",
    "kmf.fit(T[ix1], E[ix1], label='Aircraft 763')\n",
    "ax = kmf.plot()\n",
    "## fit the cohort 2 data\n",
    "kmf.fit(T[ix2], E[ix2], label='Aircraft 784')\n",
    "ax1 = kmf.plot(ax=ax)\n",
    "## fit the cohort 3 data\n",
    "kmf.fit(T[ix3], E[ix3], label='Aircraft 955')\n",
    "kmf.plot(ax=ax1)\n",
    "## fit the cohort 4 data\n",
    "kmf.fit(T[ix4], E[ix4], label='Aircraft 478')\n",
    "kmf.plot(ax=ax1)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "2e06babd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timeline'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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AV155hePHj583IMfjcXbu3MnOnTv53ve+V9n+67/+6+zbt4/du3eTzWb5m7/5GwB+7/d+r7L/n/zJn/C2t72N5ubmCbV5shSQRUREROagdDrNT37yE7761a/yyCOPVLYfOXKE9evXA/C1r32N++67j7e//e3cddddpNNpPvCBD7BhwwY2btzIt771LQBSqRQf//jH2bRpE8899xyf/exnuemmm1i/fj0f/vCHsdby+OOP8xd/8Rd8+ctf5s477+RTn/oUzzzzDJs3b57USnr33nsvxhiMMdx8882cOHFi1D5jLUU9lULTdmQRERER4c9+9mfs69l34R0n4drma/nkzZ887z7f/e53ueeee7jmmmtYsGABL730EjfeeOOo/V5++WV27dpFc3Mzn/zkJ2loaGD37t0A9Pb2ApDJZNi6dStf+MIXAFi3bh2f/vSnAXjf+97HY489xnve8x4eeughUqkUn/jEJ9i+fTuf//zneeyxx8ZsXy6XY8uWLYRCIT71qU/xC7/wCyMeLxaL/P3f/z3//b//9xHbh4aG+Jd/+Re++MUvXvhCXST1IIuIiIjMQQ8//DAPPvggAA8++OCIMotqd999d6VU4YknnuCjH/1o5bGmpiYgqBe+//77K9ufeuoptm7dyoYNG3jyySfZs2fPpNt39OhRduzYwTe+8Q1++7d/m0OHDo14/CMf+QhvfetbueOOO0Zs/+d//mduu+22aSuvAPUgi4iIiEyrC/X0Toeenh6efPJJdu/ejTEGz/MwxvC5z31u1L7JZPKCx4vFYriuCwQ9vx/5yEfYsWMHy5cv5zOf+Qy5XG7SbVy6dCkAq1evZtu2bbzyyitceeWVAPzxH/8xnZ2d/PVf//Wo5z3yyCPTWl4B6kEWERERmXO++c1v8r73vY+jR49y5MgRjh8/zqpVq3jmmWfO+7y7776bL33pS5X7wyUW1YbDcEtLC+l0eswBfwB1dXUMDg6O+Vhvby/5fB6Arq4unn32WdatWwfA3/zN3/DDH/6Qhx9+GMcZGVX7+/t5+umnee9733ve13GpFJBFRERE5piHH36YX/zFXxyx7f777x+3zGLYH/7hH9Lb28v69evZtGkTTz311Kh9Ghsb+dCHPsT69et517vexU033TTmsTZu3IjrumzatGnUIL29e/eyZcsWNm3aVBnQNxyQH3roITo6OnjLW97C5s2b+exnP1t53ne+8x3e+c53TqjX+1IYa2sz1diWLVvsjh07anLuWvuVr2zGWp8/uu2LbFz/1lo3R0RERKbY3r17Wbt2ba2bMS+Nde2NMS9Za7dM9BjqQRYRERERqaKALCIiIiJSRQFZRERERKSKAnINFfxirZsgIiIi06RW47zms6m65grINWPI+flaN0JERESmQSwWo7u7WyH5MrLW0t3dTSwWu+RjaaEQERERkSm2bNkyTpw4QWdnZ62bMq/EYjGWLVt2ycdRQBYRERGZYuFwmFWrVtW6GXKRVGIhIiIiIlJFAVlEREREpIoCsoiIiIhIFQVkEREREZEqCsgiIiIiIlUUkEVEREREqiggi4iIiIhUUUCuof6hQq2bICIiIiLnUEAWEREREamigCwiIiIiUkUBWURERESkigKyiIiIiEgVBWQRERERkSoKyDXiW/jxm7VuhYiIiIicSwG5BsJucNlfPOnWuCUiIiIici4F5BqIuA6OAWytWyIiIiIi51JAFhERERGpooAsIiIiIlJFAblmLMaWat0IERERETmHAnItWRUhi4iIiMw0CsgiIiIiIlUUkGvIAtmCV+tmiIiIiEgVBeQaMtanVCrUuhkiIiIiUkUBuWYMxi9BMVvrhoiIiIhIFQVkEREREZEqCsg1krJD3Ov/mIHBwVo3RURERESqKCDXQrIVgLv8n0FhqMaNEREREZFqEwrIxph7jDH7jTEHjTGfGuPxFcaYp4wxrxhjdhlj7p36ps4hdW2kTQILhAZP1Lo1IiIiIlLlggHZGOMCXwLeDawDfs0Ys+6c3f4Q+Edr7fXAg8BfTnVD5yZDLtNX60aIiIiISJWJ9CDfDBy01h621haAR4D3nrOPBerLtxuAU1PXxLltaKAPSvlaN0NEREREyiYSkJcCx6vunyhvq/YZ4N8YY04AjwP/bqwDGWM+bIzZYYzZ0dnZeRHNnTtM+f9yvsHzteS0iIiIyEwxVYP0fg34mrV2GXAv8PfGmFHHttZ+xVq7xVq7pbW1dYpOPbsVi0VKXrHWzRARERGRsokE5JPA8qr7y8rbqv0m8I8A1trngBjQMhUNnMtynsuPTkUZ6OmqdVNEREREpGwiAflF4GpjzCpjTIRgEN73ztnnGHAXgDFmLUFAnt81FBfgOpZbnL3Udb1CtutorZsjIiIiImUXDMjW2hLwMeCHwF6C2Sr2GGM+a4y5r7zbx4EPGWNeBR4GfsNaq8La87DxOgC2+T8jXSjVuDUiIiIiMiw0kZ2stY8TDL6r3vbpqtuvA7dNbdPmtmKimVfNNRgg099b6+aIiIiISJlW0quV8hhGYwzu0BnIdNe4QSIiIiICCsg1ZwHPt2R6zh33KCIiIiK1oIBcI8acvW1DcUrZdO0aIyIiIiIVCsg1YjEE/ceWghNlqPs4+F6tmyUiIiIy7ykg14g1DhbDRn8fi7tfJNPfA8WhWjdLREREZN5TQK4R13H5V/cmAMKnnqc3D4ODfbVtlIiIiIgoINeKwXBw6bU876+lP2/wvSKDg5laN0tERERk3lNArqGbV2eJu0HdsROOke44VOMWiYiIiIgCcg3ZcAJrLRv8vSzsf5XC0ABoAUIRERGRmlJArqF4tIknnKAOeUHnDorpPkp5DdQTERERqSUF5BpKxOM85t7BbmctxjEUi3m6O47XulkiIiIi85oCcg254Sg+DpkS9OSAUIzezlO1bpaIiIjIvKaAXCN7e/ays/Mlrm3tAKAvD6F4ioJW1BMRERGpKQXkGrh39b0A7OzcyYa2U8Rdnw3+XjrfeJFCfweer4F6IiIiIrWigFwDv3zNL7O2eS0H+w5yiG5eT60BYEn3CxQLBQb6e2vcQhEREZH5SwG5Rm5dcisAh/On6bmihd3OWgCijke2SwP1RERERGpFAblG7lpxF1c1XoXrhuj3ivj4ABTdBPmhgRq3TkRERGT+UkCuMccxtJgQvrVYLCYSJzJ4FIrZWjdNREREZF5SQK4xY1yioWbAMlQy/Gt7ilI+C1nVIYuIiIjUggJyrRlDqGkpyVCBW5y91J94mv5sEQZO1rplIiIiIvOSAvIM4CYa6WldBcDbvGfxo00w1FPjVomIiIjMT6FaN0AgFo1ysGkd0dOncICCCeFl+3FzAxCrr3XzREREROYV9SDXiMVibbAgSKq+kYITC7Zan0zJoZjPQXGoto0UERERmYcUkGskEUpQsiX29+7nle7niMSTGAyb7QHSB35MzgP6VYcsIiIicrkpINfI4tRirm+9HoAXTr9AQ30j++qCxUJW9D5PMZQCtOS0iIiIyOWmgFwjiVCCt694O1c2XMn+3v3syB8iv3Qxr5hrCEotAK9U62aKiIiIzDsKyDVijOGK+ivY1LoJgN0Dr+OEI0DQb9w15EGmo4YtFBEREZmfFJBrKBqKcv2i61nTtIY3Bg7zauFNADbb/dSffhYKQ5AfrHErRUREROYXBeQaijgRXOOydfFWAPZ6p3jCuQmA+o6fgl/SQD0RERGRy0wBuYaS4SQhJ8S25dtY07SGUDjC983tvGKupuh7eJEU9B6pdTNFRERE5hUF5BnEccNYDGCw1uKH64NeZBERERG5bBSQa6xUFYAPpo9QSL4MQMvgIcyhH0EhE9Qii4iIiMhloYBcQ2EnTNgJU/JLlTrkXPJ1nnBvBsAc+TFggpAsIiIiIpeFAnINhd0wETdCrpSr1CEb4J+dOziVWoFvAS8HPYdq3VQRERGReUMBucYWJRfRnes+u8E4HBuoY7Dg4vk+JBdCMVe7BoqIiIjMMwrINbaqfhWJcKJyvxg5QrjxBTLFEPmST943kO0F36thK0VERETmDwXkGkuEE8TdOJ1DnZU65FTzSxig6Pkc7fcgPwBD3ec/kIiIiIhMCQXkGeCqpqtIF9PcsfQOrqy/urK9Jf0GoUM/xIZiMNhewxaKiIiIzB8KyDPAosQi2pJt9OZ7cRwDOPyf8op6Te3P0edFoesNzWYhIiIichkoIM8AETfCyvqVZEtZAKwxPO6+lVN1yzEGOgsR8Aow1FPjloqIiIjMfQrIM0RropWoE8Vav2qrxTHQnSngWaseZBEREZHLQAF5hoiH4iyrW4bF4kXeJJt8FawHxpLJlWjPEMxmISIiIiLTSgF5BomH46xtXgtALr4HA9T3HWB13zN05l389Bko5WvbSBEREZE5TgF5BlmUWMRtS28jXFxNrmR40r0BgIWdL3Amazh58hi0765xK0VERETmNgXkGaQh2oDjONTFDAB/0PHrHI5djTHQnIzRQQte71EoDNW4pSIiIiJzlwLyDNMQaaAuYWlKBIP1BgvBf6JY2GHAj5Ae7IesZrMQERERmS4KyDNMMpzEYBk0R1nUth1rLcnevTSffBIX8EwYBjtq3UwRERGROUsBeYZpjDayoXUTAIXE6zxRXjCkof2nhFyHtB8FY2rZRBEREZE5TQF5homH4qxrXsei6CowDl/M/BxH49eS7N3L4jPbSRc86D8Juf5aN1VERERkTlJAnmGaY820pVoxBpLRYNv3vFsBaO18nqxJYDMd0LGnhq0UERERmbsUkGeYsBsmGU5i8aiLOayo6+ULA+/geHwtBsNQwcOrXwH9J7T0tIiIiMg0UECegdqSbVgLPnBtaycAJzPQmwffWnI2DMUcnHy5tg0VERERmYMUkGegsBPGcSynsoeJL3iVD67pAmB5di+L2rfTlc5D43JId0Df8Rq3VkRERGRuUUCegeKhOGubNgKwr3CKdyzsYEcsqENe0vMzBnNFPOOCcaFzH3jFWjZXREREZE5RQJ6BYqEYNy+6hYXRVfiOSzs5fhi+i93OWhwDXekCfUMFSC2EgZOQ7a11k0VERETmDAXkGSoR8wm7Bt93sNaCtQCk+vaxtONpBrIlcMPghKH3zRq3VkRERGTuUECegeKhOKlIimjIwRqDDcUx1uMb+aDMoq3nBc4M5ij5FhILNJuFiIiIyBRSQJ6BHBP8Z3Ecg2MM3U6Cty8c5GEvKLNwHUOu6FPyfXBCUMqDV6pxq0VERETmBgXkGaop1oTnl4iGXE6UfG5d3MuGZh8gWFWvYzu5og+hKBSz4BVq3GIRERGRuUEBeYZalloGQNh1MOFmhqINGOvxdOjsqno96Xyws3GhlKtVU0VERETmFAXkGaouUofF4joOsQgcKxmwlh+G7yLTtJamwf3wxr/gWwtePpgTWUREREQumQLyDJUMJ8u1yJZljY2c8fOAz+5ueDYc9CKvfuNrePt+ALEG6HojWF1PRERERC7JhAKyMeYeY8x+Y8xBY8ynxtnnV4wxrxtj9hhjvjG1zZx/jDE4xsG3Pisamyk6ltsXZAD4n5m7OLX2NwEoHXwK4k0w1AXtu2vZZBEREZE54YIB2RjjAl8C3g2sA37NGLPunH2uBn4fuM1aex3w21Pf1PknZEIAJCIh2hY0c3Obw8bGPLu74RveXQw0XEvJC+ZHpm4pDJ4C369hi0VERERmv4n0IN8MHLTWHrbWFoBHgPees8+HgC9Za3sBrLVnpraZ85SBg30HefrE07TUxxlqXcfbFga9yE+fBMcY6vr3Udr3OITjkBuATGeNGy0iIiIyu00kIC8FjlfdP1HeVu0a4BpjzLPGmOeNMfeMdSBjzIeNMTuMMTs6OxXkLuQdK94BwAunX6Boc0SbmrhticvGpmDO44HFQS2yd3A7GBN8DZ6uVXNFRERE5oSpGqQXAq4GtgG/Bvw/xpjGc3ey1n7FWrvFWrultbV1ik49d/3CVb/A6obVAISdMIlYkXx8IVgPgN5ld9FfH5RZlHwL8QXQfShYOERERERELspEAvJJYHnV/WXlbdVOAN+z1hattW8CBwgCs1wi3wY1xY5xKPp5et1mwFQedx3Iez6n+7MQTYFfgkKmRq0VERERmf0mEpBfBK42xqwyxkSAB4HvnbPPowS9xxhjWghKLg5PXTPnp4gbqdwOO2HCkQKxcARjPXZ3ww+OBrNdhBzDid4snm+DFfVy/TVstYiIiMjsdsGAbK0tAR8DfgjsBf7RWrvHGPNZY8x95d1+CHQbY14HngJ+z1rbPV2Nni9S4RSOcbBYom6Unmw3GSfJW5cF/9meLvfju44hW/DoGSoEg/X6jtaw1SIiIiKz24RqkK21j1trr7HWXmmt/S/lbZ+21n6vfNtaa3/XWrvOWrvBWvvIdDZ6vgi7YVzjcqD3AM+ffh5METdsuG3zOjY25sEGU7wle/eyvPNp+ocKEGuEgXboeL22jRcRERGZpbSS3gy3dfFWAF5sfxHHOIRd6LH1WCfM7h5TWVXv6sN/h3vwhxCKQrQOOvdpTmQRERGRi6CAPMPdtuQ2rmy8snJ/eVOCbNHnLVe3AfA/02+vrKrXfOb5YKdoHeTTwcIhIiIiIjIpCsgz3IL4Amy5lCLv5YlE8+RLHrdft5INzRbjF+hddhfpxrVYa8kWvWA+ZDcMQ701br2IiIjI7KOAPMOlwqnKbddxSUYdljTG6csW8MJJdvVF+ZfDBYyBxoH9ePseD3aOpCDdXqNWi4iIiMxeCsizgCXoQXaNS6Y0yMoFSXJFn1uvXgQEs1n0twW1yOGjzwRPCseC+ZDz6Zq0WURERGS2UkCe4VzHxVrL/t797OjYQX++n6ZkhKjr8LZrWrmuNcKuvgjf8Mqr6vlBmCYUg0w3dB2s7QsQERERmWUUkGe4+kg9Nyy8AYCdZ3YyWBikLuZSHw9R8i23Xr0QCHqRXQdKnk/BK89eUbcIMmdq1XQRERGRWUkBeRa4ZfEtrGlag2McsqUsnvVwHIds0eOutYvY2FQE62OMoWFgP0OvPRY8MZKEXB8UhmrafhEREZHZRAF5FsiWspXbIScEQFt9lEy+iHXCWOOyu8epzIkcOvLjYGcnFITjo89WFhURERERkfNTQJ7hYqEYTbEmSn4JgFwpR7qQZnFjHMdx8K1l2xIPgP+ZuYt047Wk+vad7UVuWgmDHTB4ukavQERERGR2UUCe4UJOiCWpJZWZLCJuBM961MfCxEIOhZLPXdcuZFNDDoCBxbcB4B/aHhzAccE40Lm/Fs0XERERmXUUkGeBsBuuLBZijCFXCsJwa12UnqE8+dQyrHHAL5UXDQl6kXOvfz84QLIV8gNQzI53ChEREREpU0CeBZqiTfgEM1P4vs+xgWMAXLWwjpJn8cNJvHCC3b0hfnD0bC+yOfx0cIBQFNJn4PB2zYssIiIicgEKyLNAfaQe17gANMebGSgMANAYDxOPuBRKPrde3QbA0ycsvcuCOZGLnh+UZhgDLdcEdcgnXwLfq9lrEREREZnpFJBnAccE/5n29+7n2ZPPkvNyDBQGcBzDwroYPZk8b79uGRuaPYwNBvO5DqT69tH10veCgxgHGpYHC4d07KnVSxERERGZ8RSQZ4nNrZsBeOH0C4RMiM5MJwArmhNk8iU83+K7MYxfAmsrZRbhoz8mnQ9CM6EYpBZC33Hw/Vq8DBEREZEZTwF5FjDGcNcVd3FV41VAMLPF8fRxABoTYZY1J2gfyGGdCNYJYfwivcvuItO0Fgz0ZwtnDxatg3QHdL9Ri5ciIiIiMuMpIM8SdZE6fOtXbpf8Er71SURCrFtSjzFgjcOu3jD/cqRUeV7jwH7CB//17IEcF+JN0HkASvnL/TJEREREZjwF5FmiMdpYuR1yQvTn++nOdgOwsC5GQzzMpuXBPv/j9QQ/OAr9bcHKetHjz9CXLZ49WLIFst3Q8+blar6IiIjIrKGAPEskQolKD7JjHEJOiK5sV+Xxlc0Jbl7VzP/35iYAnj5JpcyiYWA/pdcfH3nAaAN0vAbpzsv2GkRERERmAwXkWSLqRjGYyv1UOFWZ7g1gQSpKybPcuX4VG5pKmPJiIsO9yOFjPyZTOFt6QbIlWDjk5EswoGWoRURERIYpIM8SyXASY0xlyemQEyJfVUNcHw8TizhYN4IXaWBXf4wfHPFH9CJndj828qCNKyDXB4efhpOvaGYLERERERSQZ42wG8Y1Lgd6D7D9+HYiboTBwiAlP+gVNoBrHHJFj1uvXgjAj08EC4IM9yIvfO1vKOytKrUwDtQvhUQTdO6DgRNQXtJaREREZL5SQJ5Fbm67GSjPheyEyHm5Sh2y4xiakmGGCh53rV3Eda1hdvWG+cHRoBb51NrfBCDys7+ktO+ceuRwIvg69BSceuWyviYRERGRmUYBeRa5Y+kdXNlwZeV+1I3SMdRRub8gGcErl0nctvrsYD0IQvKJaz8IQG7/kxS9c3qKE82QaNHUbyIiIjLvKSDPIi2JFiyW/b372X58O3WROjqHOitlFnWxMLlSUFZx17olbGwssLsbfnA0eH7/8neQbryWgufzRufg6JDshqDvWDBHsoiIiMg8pYA8i8RDcTa0bACCMot4KE5ntpPnTz9PyS8FA/VCLkXPxw/FuGNlHDjbiwzBqnzNgwew+37AK8d66MlUrbIXTkAkASdehIFTl/OliYiIiMwYCsizSMSNcMviW1jTtAYIwu7K+pWcSp/i+OBxUtEQdbEw/eVFQbZtvIqNDbmRvcjlAXtX9O8gV/Q5eGaQglc1e0WsEYwL2d7L+dJEREREZgwF5FkkGU5S8AojtoWcEM2xZt7ofQPP91jRHCdfLrMoheu5c0lQflFdi5xpWkuqby9X9f2E/myJ108NjDgm0RSceR36jmtWCxEREZl3FJBnkUQoQTKcHFGHDNAQbaA/38/r3a/T1hDHGMNQoQSOyzuuaWJTQ3ZE0B3uRV6y96usHfwpmXwJvzoIxxoAF448Ax2vX74XKCIiIjIDKCDPIq7jEnJCI6Z7G7YwsZAjA0co2jRXL0zRmQ5mo0i3Xo/vRNjdYyplFtXTvi3b91XW7foTul7+LunqlfZSrRCth64DUMxdnhcoIiIiMgMoIM8yvvV5y5K3VOqQhyXCCTzrsbtrN9csqqMuGgpKLYzD7asbgZGD9YZDcqZpLXVDx4kcfYaX3uxh5/E+PL/cmxxrgFIODvwQ9v9AU8CJiIjIvKCAPMu0JlpH1SEPW5RYRH++H588C1JR+oaGB+utZmNjfsRgPQhC8pEtf0S+/grqsse5cd/niB7+V4YK3tmd6pcEQTndAW88Af0nIds3ja9QREREpLZCtW6ATE4sFBv3sZAT/Od85sQzYOvpzCRZVL8U343x1hVRdvXBF3cF+777irPPG65Jjg8eZbHvM5D7eepi5beGcYJ1rJtWw1A3HP0pWB8aVwQlGIvWgTHT8EpFREREakM9yLOMwdCX7wMYMVBv2KLkIuLhOH3FdgY4yO6Og/hYbrv5Zj62KfjP/cVdY/ck5+quwGDIFr2RU79BEIKTLVDXBvGmICyfeR0G28H3EBEREZkrFJBnmeV1y4k6UbYu3gqMHKg3LB6Ks6phKUubQpzM7uFE+jgYhztu2Mi/Wx8MxPviLvjUT0cGZYCGgX3k9zzO/vaByqp8o4TjQdmFE4IDP4DDP4bC0JS+ThEREZFaUUCeZWKhGBE3wlsWBwP1xupFhmARkSsXLKY1VcehvoP05bvw3Chv3Xwtv31NDxuaLYf7Rw7cO7uIyIuc6s+x63gf6Xxp1LErki3QuBL6jsAb/6op4URERGROUECeZRzj0BhrZKg0dN5e5GErGhbi2yK7e57n9b4dHCyc4daV8N82nWJ1AyMG7p1dRGQf6wefI533OHgmHcypPB43DAuuCnqTT78KmW4tLiIiIiKzmgLyLNQca6Yv38e25dvO24sMkIiGiDmNJNwFFLwcJ7NHedktcMbrZ9vikavswdle5KX7vsrN+/8r0cP/yivH+tjfPji6LrlarAHcaNCTfPrVKXqlIiIiIpefAvIstLxuOYlQAqDSi/z1178+ZkhuiEdY0hAnX3RIhFK0xNooROp5zeS4qXk/65vtqF7k4fmR4+ljrOh/kXgkxPHeLC8d6eXNrsz4DUu1BkG57zj0HoH84NS+cBEREZHLQAF5Fgo5IcJOmHQhzbbl23j/uvcD45datNRHsdZS9ILSh/pIEza5lN2FDlY1B8m4etBe9awWscGjrNn5X1g3+CyRkMOR7gwHOgbxxiujiKTAK8CbP4bBjql/8SIiIiLTTPMgz0IhJ8SyumUc6j9EKpJi2/JtvHD6hUqpxbbl20bs35SI0JKK0pUu0JKKABBLriDiGzbYnXh4HOhexuH+CGAqcyQPl1ske/eS7N0LgNN2J8e6h3Adw5WtqdGNMwZSCyHTCV4+mALOcafpSoiIiIhMPfUgz1IL4gswnF2g40ID9pY0xgEo+Wd7fgt1y0m13MRtbT38yjXbWVpXZHc3/O9DadoL3Rxf/BYO3PApTq39zeAYe7/KNTv/C1f1/4TT/Vl2n+wnWxxnKrhQDE6+HCxRfepVKGan4mWLiIiITDv1IM9SyXASx5z9+2a4F/nY4DH+7Gd/BgShebg3uSkZYUEqwun+LIsb4pVoXUi0YaKNxM68yNVNRznQezXbT0JryyHCTgiDYXnrOnz7QZran6v0JreceY6TzTfzcu7tLKqPEnYdLJAMh2iti0K0DiLJoA75+POQOQNLbwxW5nMjEElc3gsmIiIiMkEKyLNU2AmDBd/6laA83IsMwSp7+3v3A1RC8qrWJAXPHxWSrRvDbbqOO0NH2Nc1wKH+et48s5Jblg6S8bIczB3jWOMClrZ+gBs699PY8VNSvXtZ07ePJd0/o3PhLZxefCeeF7THdRtoiIVxHScYtBetg/4TcPD/BMtUOw40XhGUYjReoaWqRUREZEYxtkZz1m7ZssXu2LGjJueeK544+gRhJ0wiPLo3dvvx7Xz99a8D8P5176+E5KFCib2nBujLFllUH6M6mrrFNLteO8k/HVwJwC9de4ZblgYzUeT9Av1emsWRFq6ILmHxyZ/Q2PHTSm3yqbW/Se+yu+gdKuBbSyzksHlFExF3jCqe4hBk+6CUh2gKwjFYcSvEG6fmwoiIiIhUMca8ZK3dMtH9VYM8i7XEW+gv9I/52HizWyQiIa5alKIhFuZUf3bEctK+43LLkj5+ZfVhAL69byHPn6wDIOpEaHTrOF3sYkfmdV5ftJFDN/7fI+qTm078H5oSERYko+RK/vjzJocTUL8EmlZCvBnSXXDwR/DmM3BqJ7S/Bvn0JV4dERERkYujHuRZrCfXw1PHnmJF/Ypx9/mzn/0ZxwaPsaIu2Ge4LrlQ8jjem+XNzjSL6uM45a5ktzBAov8NnjtRzzcPBs9Z3Zhlc9tgpTc542dJe0MknDgro4u5ov0Frtr/D8DInuSrF9bRUhfBnUgJhVeAQiZYhS8/AE4YInFYcgM0Lr+EqyQiIiLz3WR7kFWDPIs1RhtpjjVzdOAoK+pWYMYIomPVJb9w+gW2Lt7K25a9jYFskfaBLEsaglkuvEg9+eRSbl+4Dz8UY2d7HYf74hzui7Ozva4clCHpxBnwMhzKn2B3wwJuWf1z3HL4+yzZ+1UABlreyt7T/US7XOrjYa5sTRILnWe6NzcC8WAKOhLNQVDO9sKRZyC1CFbeAaHI1F08ERERkXGoB3mW68/382L7iwA0RBvOu+/249srM12sqFvBJ2/+JIWSx4tHemiIRyr1yG5hkETPaxjrU4o28vzJ+kpQhpG1yRAMzOso9rC1+xC3HH4MgEzTWvrbbqWj7U66M3nqYiHq42HaGmJEXIdkZIJ/m/kl6DsGiQXBLBj1iyd1fUREREQm24OsgDwHHOw9yKudr7KsbtmIqd/GU112sXXxVhKlDeQKPo3JcKUcIpTtIp4+ilNIU4y3AvD8yTq+vW8hMHZI7iz1salzD9d2H6B5qINsagVHtvwRWCj6MJAtEHIdPN8n4rqkYi6rWlKkohMIy4OnIZyEtT93EVdIRERE5jOVWMxDVzZeyZGBI3Rnu2lNtF5w/+Gyi+GSiyvrr2Z5fBNXujeRK/osqo9RircwFIqR7HoV45ewTqgSiL+9b2ElKA9vc4zDonAzxxe/hdcXbuI9rz/M0r799B76OofbbqIl1MCyVBthE8K3Fs+3dAwUKHlpViyIYy2kYiGcqjKRsGvOLoaSaIGhrmAQ36L14OqtKyIiItNDPchzxMn0SV7ueJnmWDMRd2K1usMlF8PzJV/deA2ZfAmA65puZGPzrcT73yCc7cLx8hSjjVgnMqIneXXjyBXyhgfzrW5/kS2HvgdAe/0KXmu6ktNLbmddYjUxJwqAby0D2RIYS77kE6kKxCVriYccVremaEkF+5MbgHRHUKOcXBDUKS9cB9F61SeLiIjIuFRiMY/97PTPODZ4jCvqr5jU84aDMkC24HEscxCAZYkrWdt4AxubbyXWf5Bo5jTWOFg3wrMdbexsrxtxnFPpCEtSBR668RQAq9tfZEXnLhYOHAHgRN1SXFxOLNzM4bYtWCyt4WbCJugNTjlxok4QdH1rGcyVMAZcx+AaQ0td8FhDqERjLAS5XsCBUDToVQ5Fg/AcSV7M5RMREZE5SgF5HhsqDrH9+HaaYk2EnIsrQTgzkOO7B37E8ewuTgwdAoKgDHBdcg03JtYQGerA8bJgHIrRJij3+v7VS0sqIbl6WrjhoAxUwnJ7/RX4Npgn+WDLOna1XkdruJGF4WZSToKEGwPAK++TLXhYoFDySUZD1MXOvj4334/j5XFKWZL1zfir3oYNJ2iqSxEJaapvERGR+U41yPNYIpxgQXwBxwaOkQwnqYvUEQvFJnWMZCzEDa23cUX6JjobXmF//8sAnBg6xImhQ/hLkmxqvQnjF0l2v0ao0I8XrsMal81tg9Bex6l0BNrrKgH5cNtNHG67CTgblh3AMS4LB46wZPA4a7r3sX/BGvYu3ISPZVF4AYtCzTSGg17qVDQIun7Ekit69A8Vq185kCBPA7HOTkzn98gWLXbB1STqm7lqYYr6eOhsPfOw+qWqZRYREZFR1IM8xxT9Ip1DnfTn+9nZuZMlySVjLkV9PtmCx/72AbozeZqTUSKuw66en/KjU/8EnC29uCFxLdHMSSKZdkqxZrxQMA3cX720BKBSanE+55ZhnKlficVSsh5HWzdQt/rXJzQzx7ncYhovl2YgV8I4hmjIkIyEqYsFczE7+QGculYaF19NONl49omhaFDTPO6BI6p3FhERmWVUYiEAFL0i+3v3c2LwBI5xaIo1Ter5vm/Z3zHA0a4hFjfGCTmGXT0/ZW/fy5XSi7uX/DIbm24hOniMyNBpXC9LId42otQCGFFuMZ7qMgyoLsVYwamFN+Jd8R4SzuR6wyuvxVpKXtDzPNyJXCx5kB8g4ZQqC6w4fgEDeE4YgGQ0xJpFdWd7nv1iEJDDcUguhPjwNbXBPM3hhMKziIjIDKSALCMc7j/MKx2vsDCxcNLlFoWSx4GOND2ZAiXPp7UuhmMY1ZsMsLZ+I7f5CfBLPHtmCTs7gl7Y4cVFzl2u+kLO7Vl+ZtW76Fh6B2vjqyf1Gi7EP8/7v2MgR0tdlCtbUmdrnr0ClApQHDq74/DtusWwaB1EUsH9aB1MZJltERERmVYKyDKCb312de6iI9PBYHGQZDhJQ6SBsBue0POttQzkihzuzDCQLRF2oSEeqfQmA5Ue5Xe13MMtbituYXDE4iLVq/CNNy3ceKqni9u+6m6OLd7K0sgi2sILJnchLoJvLT3pPM2pCBuWNl5g5xIMnA5qmo0LXj6YTaN6yj3jwvKbIX6BY4mIiMiUUkCWMfXn+xnID3Aqc4oTgydojjWTGu7pnOgxsgX2tQ+SK3g0p6IMVwaP7FFexfWmiS2xK7GhKJ4bBOPhoFxtor3LwyG5o/4Kvrv2V/HwqXeTREwI17isjC6pTA831fIln7DLhQPyuXwPyjNwVAz1wOq3QerCi7mIiIjI1JmWWSyMMfcA/x1wgb+x1v7pOPvdD3wTuMlaq/Q7gzREG2iINrCsbhmN0UYO9BzAsx4N0YaJHyMe4bolDew/PUDnQI5F9UHJxsbmWwEq9ckneJNXvTM4pTy2PN3c+sYreWjp2hHHq+5dPtwXHxWgIehhZulNrOjcRVOmnV/Y+4/Y8v/ebFnPztZ1dJX6aHLriTtRFoQaqA9NLvhPC8cl+HaponILERGRWeGCPcjGGBc4ANwNnABeBH7NWvv6OfvVAd8HIsDHLhSQ1YNcW2/2v8kbvW/Qn++nNdFKMjzxxTUGs0V2neyj4Fma4mHC7tlZJoZLL4xfxC1lsCbE0WIHAD/XcDs3JNeOOt5Yvcswsof550pPc5cXLGaSipS4Kh+UdZypX8mbLevZs3ADOVsgasIsDDezLLKIiDOxMpLzuege5LGkz8Cqt6oHWURE5DKb8hILY8xbgM9Ya99Vvv/7ANbaPzlnv78AfgT8HvAJBeSZr+SX2Nu9l8P9h3GMQ1uybcLPzRY8jnZn6Ern8XxLyA16R11jqIuFMV6W2OAxQrkeXh7ax/eGghkqrogsHveY6+NXjgjQ5yvL+Hepf+Eu7wU222CZ7J1mDQBPuDfzqHsbW9qyvO+qxsqy1hdLAVlERGT2m44Si6XA8ar7J4Ct55z0BmC5tfb7xpjfm+jJpbZCTogNrRtYlFzEzjM76RzqHLECXzKcJOSExpyHOB5xuXZxPelckUIp+COr5Psc6gzmHk5F42Qb12D8EuvTbdDlsKtwAvwSFsolCGdLDtqL3QAjAvItS0fXJQ+H5u/zNr4fetuInuXNdj+bS/u5vbAD3oSnTt5IbuVd/OKqSwvJIiIiMr9c8jJixhgH+G/Ab0xg3w8DHwZYsWLFpZ5apsjCxEI2tW5isHA2jPYX+uka6qLoF7HYcXuXU7GRZQyebznaM0RPJk9DPELYDZGvX8XaSB3rfA9jfSJDpwkVBgGPUqQBa0L8Xc8PaS928/WuxyrHOrdHGcYKzVdzgKsBKJWnhmvJF7gqf4hbSnt5/sBLFA95OMYZtZJeYxTclbfSu+yui7hqIiIiMldNJCCfBJZX3V9W3jasDlgPbC8vuNAGfM8Yc9+5ZRbW2q8AX4GgxOIS2i1TbFFyEYuSi0ZtPzN0ht1duzkzdAbPerQl2ioLa4xlcWOcxY1xdp/sp1D0CLvBQLVSrKWyTyGxCKeUJTp0GqeUxS0MsinUBpx9S4zVo3wh1Uta97W/SOOJPcQKHhaLZ30MBscYDIZMCTb4e2HvXrr3/3TM4zVGoTFqg1i9+5xvldXb4Jp7Jtw2ERERmT0mUoMcIhikdxdBMH4R+L+stXvG2X87qkGeU6y1DBQGeLH9Rbqz3SytW0rEiZw3KL9+qp+uwQKNiTCuc/7ZG0K5bmKDR3FLQ1hjcLw8Xx18ntNeH23hBayPXzWpoDyWgl8k4+ew+NSHUhxoX0rL8ed5W2nscJwpBf8mQkFIXlFfFZA7Xgv+XbR+5JMuFJpVgywiIlITU16DbK0tGWM+BvyQYN6qv7XW7jHGfBbYYa393sU3V2YDYwwN0Qa2Lt7K692v053rxvd9WhOtY9YnAyyqj5EteAzmixQ9S10sRCzkjrlvKbaAdGwBxnpgLW6+j3V2AJvZy9FCO0cL7byWPTRmycVERZwwESeMZ30y3hBtLQcIty7kJfNLLI8soiFUh4HKoL6fHIWnT8KhfsvqGDx2T9V0eAf+BQ5vH3mCjteCr3O3V1tyQxCQRUREZEbTQiEyaR2ZDl7vfp3BwiCu4xJzYyTCiRED/IYVSh5Hu4boGMyRL3nEwiHCrkM87GIMnK9v2Sllef304+zJ7OVIKSi5uCKy+JKC8jC/vIjHoDdEkRJhE8LHZ3mkjaQTJ+HGSDgx/uOzQYnFY798gfmixwrN1XrehIZl8BvfVw+yiIjIZTYtC4WIVBuuVz41eIqefA99uT6ODx5nSWoJUXfkjBGRkMvVbXVc0Zqgsz9PzvPpyxRI54pkSx6JSIi66NhvQz8U59rl97NhqJ3XzjzJa7k3OVI4zdHCaV7LBvMgX2xYHu75bqhaVGTIy3Gi0EHeLxBzojSF6sn6bRNbpe+ae85fXvEvnwKvOOl2ioiIyOWngCwXbUndEpbULcHzPXZ27uRQ3yEWJRaRCCdG7RtxXZY2l7e3BrNdnO7LcqBjEM/3sTYI09XlytHy/WKijbXLfoGbz7zMC15HJRwfPScsw8UHZiDoNSYGbrlm2Rui4JcoWY+nuo6zMrGQ5fFWQmbsUhERERGZGxSQ5ZK5jsv1C68n7IQ5nT5Nx1AH9ZF6YqEYUTeKY5xRtcquY1jSGCcRCWGxDGSDHmWnPPBvKF+iP1vAGENdLIRvopQiddySL3Jz/RK8UIKXhvbzWu5I5ZjDgRkmN/vFWIJV+MKETQiMpWQ9Xuw7QNQJsyS24JKOLSIiIjObArJMCcc4bGzdyLXN19KR6WCgMMCp9Ck865EpZLBYFsQXjCjBcBxDcyooX1iQGlmaYa1lIFfkjY40uaJPvugxmFxL1O0inusgAdwUvYJb3BZ8N04pUs/LmX18v/8nfL//J5c8qK+awdAYTlKyJTQ3oYiIyNyngCxTKuJGWF4fTJt9Xct1AAwWBnmj9w2ODhylMdpIKpI63yGA8swZ8QhbVjYDkCt6+NaSLdSzv72VXiyulyVUyhDPnCI8eIbrvEaKkY287nfQXuzGt3ZKArKIiIjMLwrIMu3qInXcsOgG4qE4h/sPk/NyAORLeRzjEHaC1fiSkSTxUHzMY8TCQd1vIhJiy6pz3rb+lWA98pk0S7oP8vOFNH/e/gSnSt387ZlgFsKNiau5MbX2vLNmiIiIiIACslxGaxes5aqmqyr3BwuDFLxC5faerj1YLMlwksZo47gLkUTccwbJle9HInFIxKBU4A6vnRd6X6fkWw7lz3ByoINSPs0N0dXBc7wCHg7EG3Dd6uWyz55zrAVOhrw8Rd8j7GignoiIyFylgCyX1XBvMUBzrLlye2FiIU2xJjKFDEcGjnBi8ASpSIqmWNPkThCtgyhs2/A+tvnBXMfbTzzN1/f+PT/K7+RIfAiAG5rWcr1ZTG6wB1Pu0QZwvByeG8PzLJmCB/7CIKhne0l4BV4ZfJF8/SrWN14F1VPaKTCLiIjMGQrIMiM4xqEl3kJLvIWldUvpzfXy01M/JeWlCI/o4Z3MQYOZM7atuBOM4YXTLwCwv3c/b/QdYGfTGgC2Lt7KtuXbwPchP1h5+sHONMVDTjD13OLNJKxHy8BJrBODYhaK5WDt5cF64MYgsQDOswS3iIiIzHwKyDLjhJwQrYlWrqi7glOZU1hrCTkhkpHkqIVIJmrb8m1BCAa2H98+Iizv791fuT9s6+KtbFuxjVi0m6LnQ7y8kl4oDPFWaN1wdufCEGQ6oX039B2FcAK8QhCU3fIiI14R/FKwXURERGY0BWSZsTYv2swGfwOd2U6ODhylI9NBc7yZiBMZtz55IsYLy8OqQ3NvXZFQdjPw8+MfMJKAyBXBUtKFTLAt1welqjAcSQU9zbk+aFh60W0XERGR6aeALDOa67i0JdtoibfwSscr9OX7OJE7wfK65TjGwWBwL6H+tzosD6sOzYXQYQp1h/mzn+1h6+Kt3LjoxvEP5rgQqw9uD/87LBwPArKIiIjMeArIMiuEnBA3Lb6JoeIQu7t205frI+SEyHk5HOPQEG0YMQDwUlSH5t/5zvfJhF/h2OAxgPMHZBEREZkTFJBlVkmEE2xdvLVyvz3TztGBo3RnuwHwrEdrvPWSepVHnK9wC+7QzbQu/NspOZ6IiIjMfArIMqu1JdtoS7ZhrWWwOMirZ16lY6iDRDhBY7Sx1s0TERGRWcipdQNEpoIxhvpIPbcvvZ3rF15P0S9ybOAYvvVr3TQRERGZZRSQZU4xxrCifgW3LbmNhYmFnEqfYqAwMCXH3t+7n5+e+umUHEtERERmLgVkmZMaog1sbN3IugXrcHB4s/9NBguDF9WjbC2sSGwE4H/v/988fvhHU91cERERmUEUkGXOaog2sKZ5DW9Z8hbWLlhLxInQnmmnJ9tD0StO6BiOMZQ8n2tSW3nrwgcAePLoM+w60cfR7gyDuYkdR0RERGYPDdKTOS8WirGhZQNDxSE6hjpoz7TTkekg4kawWJpjzYSc8b8VjDHEwi43LbyNg4M7MMCRriEGcgUW1sVY3hyv7Bt2HRYkoxgD9bEwjqNlp0VERGYbBWSZNxLhBKsaVrG8bjmdQ50AvDnwJp1DnYTdMNliluZ4M1E3imvccVfrcxxDa12U1roofUMFDncOAWCtJVfyiLouQ8USiUiI5mSEpY1xVl6uFykiIiKXTAFZ5p2QE2JxajEQTBOXLWUBONx3mFOZUxS8Aj25HppjzZT8EhY77rEaE5FxHolSKPl0pwucGcjRnCviFjwOHusjZgeoi4WxQEM8TNg1RENTM2+ziIiIXDoFZJnXjDEkwgkA1reuZ33r+mCKuP5jFG2RsHMMz2boyQ+QCtVf4GgjRUIOrXVRsgUPz7cY39KfK3K0fRAwZIsloiEHxxjq48EqgI4xrGhOVI7hGGhKBiE8FQ2N26stIiIiU0cBWeQcYSfMlU1XApAId5MrOLTGm+nLd+FZD5fJLWkdj7g4jsFxTNBjXBcrPxIFoOj5eH7QS92fK7L7ZD8Avm/Jl3ziEZd80SMRDdFWHyMZDb5t62JBCUcsrN5nERGRqaSALHIexhhcJ8RV9es5kz153nKLC7KWcKYdmq4dsTnsOgxn3PHCrm8tuaLH6f4cANmih7WWaMgh5AaT0RhgUX2MaGjk5DSOA2318UpAFxERkfNTQBaZIMdc2qyI1riEioPEe/cBUEy0AVAKp+A8s2gE5zYkIiHOLXn2/bOBPVfy6BjIjXpuOl/iYEcGi2VVSxLHGBoSYVpSUfU+i4iIjEEBWeQCTvZm+exjeyj6BbpSIepjF7l8tTE4Xo74wJs4xQy27w2cUoZCvI18aim5hqtgkjXG1dPIjRWg4exAwnSuxIneLNmih+dZomEH1zEsrIuRjJ4NynWxEMuaEqp3FhGReUsBWeQ8fm7DYvqGCpX7haKhq+jzx//8GsYYbruyhbvWLprw8UqRerxIA0Sbgg1+M6FCP/VndpDof4NcagWF1LIRz/HCSaxz6aURqVjw7d5Yvu/7loLn05XO05UOtuVLPvmSRyo6gOvAiuYE1yyqq5RxiIiIzAcKyCLn8ctblrMgFaE1FSNd7OczP4N03pLO9HOi22Xv6UGePHACAAeHkBOu9LxOKDw7LqVYM6VoE25xkHjfG8QH3jz7cCkbBGTjYqxHMd7K0Dk1zABeKHHBMo1Rp3YMMccdVWbhW4tvLUN5j5eP9XGsZ2jMaeiMgXVL6llYGXQoIiIyNyggi0xQKtxAaypBIpbm166P8dzBIfYedyl4eSw+1vq4TggwHO8y7D09yLOHurjtyhbWXejgxuBF6vEiY0wl53vBLrZENH2C8NCZEQ+7pSG8SB2+Eynv55FPLQtC8wgWjEsx3jr6FG6sUt7hGFOees4hFQtR9MYuKelOF3j+UDetdVEMhhULEkRDzphzQ7taUVBERGYRBWSRi+AYh9uuTnHb1We3WWsp2SKeLfHTNzK8ebqOvacH2Xt6kPtSGYzv8X//LAnnqVZ421J49xXnnizovbW4FJJLRj2nZC3Glir3TSlLvP/wGEe3OKU0fig1YquxRYqRZvxQvHzfo5BYRCnaRCnWPO4iJksa4+SKHkMFj8FckfaBLIWSJRYZ+QJDjsPm5Y0jeqpjYYdERD9+RERkZtJvKJEpYowhbCKEibBtTYxNqzrZdyzJsfZGSF/4+bu7g6+nT46/z5gB2hisOVuj7EXCeOMeYXTvsfFLGK+AW8wA4HhZwrlunFIOLxQP5o8DMCEyzddRjDVXnpsAMJAKsjV+KDFqoGHfUIGXjvZU7hdKPuGQw1tWt9BaFx3/xYqIiNSIArLINHCMw4LoIq5adoLbr6lj6XNhnFKRP7juDHXx0b3AAD84ev5wfKEAPWZ4ngDrhLBV9ct+eWVB7Mg5n8O5TlKdL2PHme7OsUVKkSb8UFVNsrXUGZdcw2ogqJX2U0na+3O8eKSHK5oTNCTCtNZFtdy2iIjMGArIItOoKdJKX76bbCnDst4DFI8/xoEV94ze0VquX5zk7hVNhMzYQfF8Afqie5/P55ye4GJ84fl390sYv4BTyo7YHir0E8mewfFylKJN9C5/B4vqo6TzJQ51pknnS6SiIZqSESKhC8+WYS201cdY2ZKcxIsRERGZOAVkkWkUcaNE3CjHlt/Jst4D3HF0O+29Z+uDD7dcx4FFN5D3CxwvtJPIx3GMg299mkP1rImvrOz77ivGD7gX2/t8sb3OYzm3J3pYYXiwoPWJZDtIdbwIxhBNLMYPxyEMBS/PUMEhV7xwQM4VPU70DLH7ZB8N8QhvvWZ02YiIiMilUEAWuQBrwSuvWHexC00fuOKdhLPdrGx/Aac8Sm/hwBHaBo5xVddejrVu5NCiLZWlrH3jc7rYRdGWMOUi4NZwEy2hxjFX9DtfeIaxA/R0lWyMyziUIg2EC/04pSGimVPYci+1W8ySbbiKQiKYFs+L1FUGDQ6zGHBCpKIhbLn84/RAjqPdGZY0xjGg+ZpFRGRKKCCLnEfIMdTHwqTzRTzfUiz5eL6Pb2GyM5cdWnILx5qvwgsFpQGr219kRecuFg4cYeHAEVZ07hqxvy3H5SMt69m98Drai90sibRQ76ZGHdtgqHMTRE2kPFhw5Lf2WAH6spdsUB7EB3jh1Dnbs0QzJ4lmTuKWMvhuFHtOqYk1DoXEYqx7dhq5hdki+14usj+1iFIoyapFjSxpWUBD4tIXVhERkfnLWHuxfWKXZsuWLXbHjh01ObfIxbDW8muP/RsO9O1nQWRpuRfTEHaDpHxt4w1sbL6V8XJzbOBNwrmuSkAeNhyUx7Jw4AgAZ+pXYrF4dvScxIda1vFq6zrCTqjSO93k1ld6nivtx5Jy47RFWkYF6HNNpGQDYMOC4N8p720eg1PKYvzCqO1uMYM1IbKFEgULpUgTV7bGoW4xLQuX4CQXgKvALCIynxljXrLWbpnw/grIIhP3d3v+jm+/8W1cE8LzLbmih2+hPRfUFS+KrsIYw+rkZq5t2Eo87BIJuThm/IB8PucLzzAyQA+zlb7nkay1ePi4uBgDERPGwSG9+HZ6l92FwVRWAbyQ6gB9blg+1+UIz8OMlyOdK0Axh/UKLImVKDVeQePqm2hqOqeBxgFHJRkiIvOBArLINOrN9fLC6RdYEB8ZtrYf384Lp1/A8y0H+w8AcM+yX+WKxBYGs0UaExESg28SyXVjYimccfuZJ+dCAXoslmApaYtlyeBxAE7VLccxDnEnioMJeqLPaWJ/2630Lrtr1PEuVKoBo8Pz5QjNuZKHV8xD3wkSyQRrljQTHq6LsT6Ek9C4AqJ10HTFqFk7RERk7lBAFplG4wXkatuPb+frr38dgPetfT9LIjfgWUts4E1Id5KxMcDgWR9D0LMbqZoDOFo11Zkx5xZKTK3qgH12QKDFNSEMwbLTYROmoS8I/f2N1wDg4OCcEyjHCtDjDQ6EIDRfjqDsW0tnOk885NKcinDNolTwOnP9UMxCKQ/1bUFghiA81y+B5lXT2zAREblsFJBFptFEAjKMDMnvX/d+ti3fBp1vQKYTPxIEsULJp+Rb0vmzy0T3Z4v4w9+TFgqej2NMZRaNSMghVC4LCLnTE56LtoRnPSyWIT9HyIS4tmMnV3a9DoCPJWQc4k6sMmdzsncvAJmmtec9dn/brXzDu4unT164NON8JhusfWvxfEtXOk9LXZRkxCUZDbGwLkbIloKQPKyYASyseAuk2sDVWGYRkdlOAVlkGk00IMPIkLymaU3QW+kVwBl7IZCtjdeybcGGEdsKno/vW/KeT7bgkc6XcEwQrnMlH99aIuWpzawF1zG455YKGCr7TAVrLb3eAJagjhlgTccrlQA9an8srnFoGeokV3cFR7b8EXDhgYDjuZQeaM/65Ao+RS/4uqatjiUN8dE7DvVAaQiufAekNM+yiMhsp4AsMo0mE5DhbG0yEATk4hCEoqP2258JkuKa5NLKtrEC8zCLpegFgwSHDRU8CqXRs1yk8yU8H4qeRyzsYoBI2LnkOmhrxx4MOJb2YjcP7n+UBZkzpFPLRj3e03YL6eXvAghqoMdZzhrOBuvD/bC6Af701otrfzpfpORZFjfEWNWaHDXrB/3HIbUQ6svtbVgG0dFT7ImIyMyngCwyjSYbkEfwSnD02eC2X4JweYW5UIztva/zQt++yq7nBubzheULGS7Z6ErnKZZ8cp7PUN6j6PmEyz3LbtWkzmHHIeROffHG0lPPsqprz6jt1QMFIah7Hu6ZrrTJhOhtewvdS+8EIGRc/u/nnEpIHjbZHuVCySdTKLJ1VUtlur4KrxjUKUPwb2IBNCwdfZBqTggWrtW0ciIiM4wCssg0uqSADJDtB3zIdIP1guA11BOUXSQWBAEL2N69uxKYx+pdPtdkA7TnW3Iln3yxRL509mdA0fMrddCOAddxiIfHLgmZKufOxBHM9Xy2TR4+ywaDa3CqbjkWS8i4DBWiDBbO9jQPlQzf9W6lYd3buPcKg2sm1u6OgRzrlzawsG50z/4IuYFgAN/5FIfg2nuDmTFERGTGUEAWmUaXHJDP5fuQH4Tug8HgsNwgxOpH7LJ94CAvDBwq3zOjpl+bSIAeNpEgnS8F9bnZfImuTIFsySM8xnzBvvVJhMPT0tt8ruoQbaEyiLC6LGK4J/p5fy0x16vM6fyku5X2ZTdx67Ih2sILSLmJEcfuGcrTkoqyvClBbIw/Bgwje9jPK90By2+GUGz0Y7GGMctrRERk+ikgi0yj3lwvTx57krZkG5GqJY+nRDELma7R24a6g0Ut/FLQ4xwZudDI9v4DvJA+wojkPMacvpOtcwYo+j754ti9pj2ZAj2ZPK7j4lufWMjFMeayBOaxrG5/kcYTe0gX3Er/8/U2mJ7uFXMNrakMIeMGPcsWTi28nsIVP0/J9+lNFwi5DsnQ6AF7rgNXtqZoiIcvPNgx2xOU0pwrPwiJJhjvPeN7wR9GC66axCsuS7aqpENE5AIUkEWmkW99XjnzCp1DnWSKGeJVgcpaS1O8ibAzTWHF84IeynMHxhWGYKgLhksKvAKUsqPC2Pb+A7wwcLCy3/5sOwBr4m1gnCAsN68PdjZmQgtnpPMlrLUMZIsUPMtQwTs7TV1ZyfeJhtzK9HQQLGA3araNabC6/UVCh/dT8A0RxycZKVEXLdE2cAwISjYOtaxj36LNePg0h+oJEVwfg2FpZCH92SIOLolQhJULkjQnIyPmqp4Qa4M/cMZ93A/C9QTLQiq8Alz9TkhO0ScaIiJzlAKyyGXgW5/eXG9lFoe8l+do/1F6871Ya8l7eRqiDTREGy5wpGnglcDLj/1Yprtyc/uZHbzQvRv80tne5XgbYIPSD2NGBjZD0JPN+D3Pnj96XoveTJ6BXKlS8uB5lkyxRDzkEpls0LwIz5+sY2d7HYf7gj9mVjdm+bnS07zXfZar8kHpypn6lSOW6D7cch2vtK4lYkIUbYm4ieF6MQqeR8R1RwRkH0s87LK8OTF6JgxrWRJfQNI9W3LhYEiOVYJxMQbby9MGjvPHRigaBGjN5Swi85wCskgNlfwSJb/E0YGj7OneQyqcoinWVOtmXdCI6eisDQYQeoXg9jDfA7/I/nxQBvL+hbewreGakQcKJUbP82xMZfDhsNP9OToGsgCEXZd4xJ3WFQPhbFAGKmH5vy59lG3Fn43Yb+HAEQB2XHkfh9tuwlpLzhYqjw8v2jLMt5ZMoURbXZxYZGTgz9s8yUio8scBBIMQF8eaWJNcNmo1QoNDwp1EnbK1jPpEoVqmE5beMPIPnXA8mL5ORGQeUUAWmQF863Ni8AR7u/cScSOkInNg/tzCEBQG2d7+M75+6DsArKmvWo7ZLwW91+cmXd9ja/2VbGu4OshyieZKqMwVPHqGihRKPp5vCU1gQRNrLQZIRi++V/T5k3V8e18QEn/p2jPcsnSw8tjq9hfZcuh7wNmQfCEFzx81B3UQpC3uOQMcC7bIgDdYnspu5MWKuC6bFgTBuS4a1Dyn3Bht8aZRYXpChnrAL569P/zfKFzVgx1OwOptEEmMerqIyFyhgCwyg+zt3su+nn3EQjGstXjWY2Fi7N47gxnR0ziTjehxvoD9vfsBWFO/Ggrps73JVa91S/0abm28bkLHyxV92vuzlHyL5/s0xC9usORwSF7dmOWhG0+NeKw6JJ+pXwnAsdaNEwrLl6Irn8bzffKeR8gx+Pj41qcpmmRFcxBgzzerRioU57q6FZM7ac/RIBwPHzK+AFbdcfEv4hIkwgrpIjI9FJBFZhDf+mSKmaC61VpeOfMKRa845n6DxUHioTixcr1qxI0Qm6pa1RoaEaYL6XIJhx98GcP+bAcAaxKLKzXO1caqdx6uFd57epBCySdV7k2e8HRsZX/10hKAUQEZRk4tN1x2MRyWxzMdIbpkfXrSeaLh4NqEHENj8uwfBQ3xMCHHYLF0FwZGDRKd0DR1ld8DNpjLedmEf4dMGde4bGzdSMiZe/XSETdCfaT+wjuKyLRRQBaZhYp+kdPp0wwUBjDGkC/lOTZwjMZYY2XgVywUO+8SzLOKV4BSMJBw+6mf8sKpn0KpEKQ5a4MvxzkbnuOLgvKMqvrmrY3XcGNyDe19OXBcCh7kih6JiDvmfMZj+auXlnAqHWFJqsDmtsERpRbVzl3MZCyNmXb6km1s3/CbEzr3xcqVvEqezZWCnubzffLgYFjZkiQWci4clH0/+CNm1e1T2OKJ6c314lnvwjvOMr71SYQSXNdy9hOSWCimwCxymSkgi8wRe7r2kPWCgWz9+X76cn00RBvG/Rh62qaXu1y8cjjy8kFIA7a3v8ALnTvL24vBQEED+4dOA+VeZ2vB9/AxeL5P0TdB/7JxcBxnRJXv+viV3JBcW7k/1gwX5zpfcK62bfdXKyH5YkxXCUemUMJiwFqaEuFKT/SYrMUpZMgtvWXK2zFfWWvpK/QwXMNS9PM0RJu4InURc15PkOu4NEXn7tR/xhiWNyUuyyw4MncoIIvMQZ7v8Wb/m7w58CYhM/oj6IJXIFPKEAvFKHgF6sJ1Y878FXWjRCczS8IMNeasGwBeIZhqzvcolYr4vi1PVxfieCmY9/mKyOJRxxvIuxT7NxPP3jhi+7nB+VJ7mccz0RKOc00mVBc9S9G7wFLZ1idUytDTMr211vOZbz3Spf7pnbXFOKxMrmPc6f9muYLnc8fVrdTF5l45zlxnjGFBbAHuubMdXZ5zKyCLzDd5L0+2GIS405nTlPzSqDl5h0pDdGW7GCoNkQglSIaThN3w7O95Hou1FAp5iuku8u0H6OzqZrdzhj2FYIGQ4MpYrHHBGI4Wxg7PA3mXdMElmt3A6dNB2cGl9DKP52LC9URC9eR7pS1uMcPgopsn1RaZWQaKZ+don4sGs0XWLm4gEb38IUsuTckvsW35NuoidZf93JMNyPrzS2QOqO4Zbow1jrtfpphhID9AV7aLrmwXfbk+fOvjGIeSLdEab50bg6SMIRKNEYkuI9m4iP6Tp1mdKdCa92hNRXAdQyR9AscvESoM8LPIcXblj5/tiTYOYKiPevSaExSjR1nRsJN0waXvnFNlSw6nh2D7m6N7Z1MRj/royLrac8s8AA633TTp8ooLherGTHvl2DK/1Idn/tzrl8KWCjTHmkipB3nW6cp21boJE6YeZJF5bKg4RNEvUvJL7OvZR0+2h6ItEjIhQk4I13HHHEzkGnfWTEk3zPMte0710zdUxABF36cpHiZZ6MQtZhjuV3ZKGSK5LoqxFqxxeTmzl9eyh8Y97nAv87mypaA+Mh46G5yL0aMAhPNXjHmsaHYD8eyNl9wjDROviR7Zy2xxCwMMtt3CXP14Xma/vmyBTcsUkGejrmwXty+9XT3IIjKzVQ/4u3XJrZT8Ev2FfvJeHt/6HO47zFBxaMRzSn6Jvnwfi1OLiYfil7vJF811DBuWNlD0fAqepXMgx/HeLKFEG8654x579hLOd+OH4tyQXDuqx3ciqlfuG5aNv0Q+vnvM/YvRoxSjR+kL7xnRIx3NbuAtDddMOjAfa914wX0WDhxh4cCRET3RJxtXsafxaqx78VMMWuPghzSnsYjMXupBFpFJKfpFXut6jRODJyZUjmGtpeAVWJJaMqN6ndO5EvvaB+gdKrC4IT6qvzQ68CbxwSOUIvWAwXejTGev6nBPdXWP9HCPcymzakRP9LCxSjgmI1YYIFbMVO6HvAIlN0x//FKXorbYSda2r09cxQ3JdZd4XpkPBvMeq9dsIpVK1ropMklzrgfZGHMP8N8BF/gba+2fnvP47wL/H6AEdAIftNYenXCrRWTWCDthNrduZk3TmgkNBPKsx8sdL3N04Ch1kboxQ3I8FL/svdGpWIjrVzTxsze7KXo+kXOWuS7FFpD38sFCG8U00fQpStGGCxzV4IUTXEyQHqun+uXMXn7ad4T0GOE4W3LIlpwxyzuqnS9E5yL15KpKaBozwfR59lLr0IcXgpmgo8UOjhZO81rmwKWdd4baEFvJjYlrat2MOSOaGxi5hLrINLjgT0FjjAt8CbgbOAG8aIz5nrX29ardXgG2WGuHjDG/BfxX4Feno8EiUnvGmEktC3zH0js4lTk15iqCQ6UhTg6eJF2e+3ioODTi2BZLU6xpxKwcU1UD7TqGhniY7nSB5uTIJau9SD3Zcng0fonI0Cku9PdAJHsGxyviuxe3/PW5zlfeMVYJx7kO98XpYeyZN8byn/P/FYDfjX54Uu28VKly6cmp/GU97WVRjB7laLGDH3a1V7YN15rLxVkU6+fDGy68n8ilmEg3wc3AQWvtYQBjzCPAe4FKQLbWPlW1//PAv5nKRorI7OY6Lsvrlo/7+HULzq4y1jHUQXXp1+H+w2QKmcoqgiW/xGBxkEQoMe5qZMMDDCdiUX2MnkyBjsEc8dAYzzGGuliIfGrFBY/lFvpxvTzGHx3eg17ZqSvRuGXphQfyTSREzwTx7I1zNjCeW3c+XGs+Xi36VFAAF7l0EwnIS4HjVfdPAFvPs/9vAj+4lEaJyPxS3Rvcds6sC4tTI+cmLvpFOoc6ebP/TcYaQ5H38nQMdYzq4R5e8jcVSY3Y3pyMsGFZA+lsacz82j6Qo70/SzziUh+PcL61u7xoA062B3NOu4xfwM13459n4JuxPt6kB7aZcm/12MF7IiG62pLdQRfuQxtOTbIdMr7F5a9AZVaUSGFaztZe7GZBXYH3t4xeEGeuyKe7gQv/wSpyKaZ0FgtjzL8BtgBvG+fxDwMfBlixQm9uEZm8sBNmSWoJS1JLxnzc8z0GC6ND4Yn0CQ72HSTn5cBCzsvRGG0EwHWhIQXJcHJU6caCVJTBfInjPUOcGcgRcR3i4ZE9zSHXEHYd8qkVY/Y0G7+EUxq/zMHgE0lPPpS6pSHcUvYigrXUysXOijJRX+96jPZiN1/vemzazlFrvlckuudVXFcTcc02rYlWbl96e62bMSETeXedBKo/G11W3jaCMeYdwB8Ab7PWjllJZq39CvAVCGaxmHRrRUQuwHXcMRdLqY/Wc0V9MP+wxXK0/yg+ZweSdQ510pHpqMzMkSllKgE6FYuwcWkDA9kSnenciFLkomfpTudpjEcIu2P35FonhHeBUdul5gsNABwtOvAm0cxJ3HEGLDl+gWKsBc1pPH+sj19Z6yaIzAkTCcgvAlcbY1YRBOMHgf+regdjzPXAXwP3WGvPTHkrRUQukWOcEVMLbWgdOcqn6BUpVgXNk+mTFP0iuVKO9kw7mDS4MFaOHSplODXYi+OcDaK+b8mWCsTCDhGnurTCEHdTYw4ydDCk4uHy7QvL162gkBy7Jx0g1fUqbmGwvDLg8ElcPHf2zF8tkzPdPdQzQT7dzbLrbidV31jrpsgkzaaV9C4YkK21JWPMx4AfEkzz9rfW2j3GmM8CO6y13wM+B6SAfyr/0D9mrb1vGtstIjKlwm6YsHt27t6rm66u3C54hfNOaff25RbPH/m4Zy2Hus4wmO8fsb09e5refBep0Ogp7zoGCgxmk1gsuaJPLOyU2+aQjIzx49q4WHf8wYjZupW4fu7sBt8jku0k5J1tk+NlKUZbKlO7NWba2bb7q+MeU6TWuiONtF83Oz6ml9lrQgU81trHgcfP2fbpqtvvmOJ2iYjMGJGLnLbt+qUrR23z/PUcHzxOwRs9SOtY/THyXp5iyTJULAWLrJR8ugfCZEsFDAaLJRU5G+TDVb3WxhgcczYwlxILKZ1zjnzdihGDCOP9BwnnurDG5UTT1RjNLysioqWmRUQuJ9dxWdmwcszHltcvp+SfjbRFv8irZ15lQaKE5wf10if6hsh6JQyQL1kKRY9wyAEsmVI/CXfk1HcWSEZC49ZHZ+qWQiqYOaS9+Vp2d+3ED489fd50MhjiTnRGrbYoM1M+3c2yWjdC5jwFZBGRGWKs1QTvXHHnuPtn8iWGCsEqeb71eXPg0KjFWE72DXFmMI+1hmjIIRI6T3Wz79NIkqJz+QNyj9dHtjiIayZSfT27uMYl4Yw/xZ9MzhizO4pMOQVkEZFZKhkNkYye/TG+qH79qH3SbSWGCiXODOQ52TdEyD1fQPZYGDlEIdoyHc09r7pikpydnrmBa8nH53i+Ha8q1YVwiTjh8zxLzicedgg5+qRBppcCsojIHJaKhkhFQyysi7F+6QWmkvM98Ooh1XR5GjdCLc45/XzrcyCTIl/u2c/7RU4XelkQnr4eZQdD2JnDv95zJQjPvU8aZGaZw99BIiIiteUYh2tTZ5cSyPtFbP8hitY/z7MuTWdhgMXRJtVzi1wCBWQREZHLJOqE2dp07bSe4yc9e+gqTnyJ8VmnmIZcD1RPYSizQsSJ4Jrxp6acSRSQRUTkLOuDX4K5/BH9HHdb07rzzts962XOwPI7IT43y3LmOmeWDMTVT0AREQk4bhA6BtvBvZRBZA4kF0xZs2RyDHN9cXETrA45S4KWzE4KyCIictayLVDIXNox2l+DoW7mekyTGgnF9AmHTDu9w0RE5Kx406V/dN2gZRxEZHbT5xMiIiIiIlUUkEVEREREqiggi4iIiIhUUUAWEREREamigCwiIiIiUkUBWURERESkigKyiIiIiEgVBWQRERERkSoKyCIiIiIiVRSQRURERESqKCCLiIiIiFRRQBYRERERqaKALCIiIiJSxVhra3NiYzqBozU5+czQAnTVuhGzhK7VxOlaTZyu1cToOk2crtXE6VpNnK7VxJ3vWl1hrW2d6IFqFpDnO2PMDmvtllq3YzbQtZo4XauJ07WaGF2nidO1mjhdq4nTtZq4qbxWKrEQEREREamigCwiIiIiUkUBuXa+UusGzCK6VhOnazVxulYTo+s0cbpWE6drNXG6VhM3ZddKNcgiIiIiIlXUgywiIiIiUkUBuQaMMfcYY/YbYw4aYz5V6/bUkjFmuTHmKWPM68aYPcaY/1De/hljzEljzM7y171Vz/n98rXbb4x5V+1af/kZY44YY3aXr8mO8rZmY8yPjDFvlP9tKm83xpj/Ub5Wu4wxN9S29ZePMWZN1XtnpzFmwBjz23pfBYwxf2uMOWOMea1q26TfR8aYf1ve/w1jzL+txWuZbuNcq88ZY/aVr8d3jDGN5e0rjTHZqvfXX1U958by9+7B8vU0NXg502qcazXp77m5/jtynOv0v6uu0RFjzM7y9vn+nhovI0z/zytrrb4u4xfgAoeA1UAEeBVYV+t21fB6LAZuKN+uAw4A64DPAJ8YY/915WsWBVaVr6Vb69dxGa/XEaDlnG3/FfhU+fangD8r374X+AFggFuAF2rd/hpdMxdoB67Q+6ryet8K3AC8drHvI6AZOFz+t6l8u6nWr+0yXat3AqHy7T+rulYrq/c75zg/K18/U76e7671a7tM12pS33Pz4XfkWNfpnMe/AHxa76nzZoRp/3mlHuTL72bgoLX2sLW2ADwCvLfGbaoZa+1pa+3L5duDwF5g6Xme8l7gEWtt3lr7JnCQ4JrOZ+8F/q58+++AX6ja/nUbeB5oNMYsrkH7au0u4JC19nwLE82r95W19sdAzzmbJ/s+ehfwI2ttj7W2F/gRcM+0N/4yG+taWWv/1VpbKt99Hlh2vmOUr1e9tfZ5G/y2/jpnr++cMc77ajzjfc/N+d+R57tO5V7gXwEePt8x5tF7aryMMO0/rxSQL7+lwPGq+yc4fyCcN4wxK4HrgRfKmz5W/ojkb4c/PkHXzwL/aox5yRjz4fK2Rdba0+Xb7cCi8u35fq2GPcjIXzZ6X41tsu8jXbPABwl6rIatMsa8Yox52hhzR3nbUoLrM2y+XavJfM/N9/fVHUCHtfaNqm16TzEqI0z7zysFZJkRjDEp4FvAb1trB4AvA1cCm4HTBB85Cdxurb0BeDfwUWPMW6sfLPckaGqaMmNMBLgP+KfyJr2vJkDvo4kxxvwBUAL+obzpNLDCWns98LvAN4wx9bVq3wyh77nJ+TVG/kGv9xRjZoSK6fp5pYB8+Z0EllfdX1beNm8ZY8IEb/x/sNZ+G8Ba22Gt9ay1PvD/cPbj7nl9/ay1J8v/ngG+Q3BdOoZLJ8r/ninvPq+vVdm7gZettR2g99UFTPZ9NK+vmTHmN4CfB369/AuacrlAd/n2SwS1tNcQXJfqMox5c60u4ntu3r6vjDEh4JeA/z28Te+psTMCl+HnlQLy5fcicLUxZlW5d+tB4Hs1blPNlOutvgrstdb+t6rt1bWyvwgMj/b9HvCgMSZqjFkFXE0wUGHOM8YkjTF1w7cJBgq9RnBNhkfk/lvgu+Xb3wPeXx7VewvQX/WR1HwxojdG76vzmuz76IfAO40xTeWPzd9Z3jbnGWPuAf4jcJ+1dqhqe6sxxi3fXk3wPjpcvl4Dxphbyj/z3s/Z6zunXcT33Hz+HfkOYJ+1tlI6Md/fU+NlBC7Hz6vpHH2or3FHZd5LMBLzEPAHtW5Pja/F7QQfjewCdpa/7gX+Hthd3v49YHHVc/6gfO32MwdH7Z7nWq0mGNH9KrBn+L0DLAD+D/AG8ATQXN5ugC+Vr9VuYEutX8Nlvl5JoBtoqNqm91XwWh8m+Oi2SFCL95sX8z4iqL89WP76QK1f12W8VgcJ6hmHf2b9VXnf+8vfmzuBl4H3VB1nC0E4PAR8kfJCXXPpa5xrNenvubn+O3Ks61Te/jXgoXP2ne/vqfEywrT/vNJKeiIiIiIiVVRiISIiIiJSRQFZRERERKSKArKIiIiISBUFZBERERGRKgrIIiIiIiJVFJBFRKaRMabRGPOR8u0lxphvTtFxP2OM+UT59meNMe+YiuOKiAia5k1EZDoZY1YCj1lr10/xcT8DpK21n5/K44qIiHqQRUSm258CVxpjdhpj/skY8xoESxUbYx41xvzIGHPEGPMxY8zvGmNeMcY8b4xpLu93pTHmX4wxLxljnjHGXHvuCYwxXzPGPFC+fcQY88fGmJeNMbuH9y+vxPi3xpiflc/x3st4DUREZhUFZBGR6fUp4JC1djPwe+c8th74JeAm4L8AQ9ba64HnCJaOBfgK8O+stTcCnwD+cgLn7LLW3gB8ufwcCFYte9JaezNwJ/C58pLlIiJyjlCtGyAiMo89Za0dBAaNMf3AP5e37wY2GmNSwK3APxljhp8TncBxv13+9yWCAA7wTuC+4bplIAasAPZe2ksQEZl7FJBFRGonX3Xbr7rvE/x8doC+cu/zxRzX4+zPeQPcb63df3FNFRGZP1RiISIyvQaBuot5orV2AHjTGPPLACaw6SLb8UPg35lyV7Qx5vqLPI6IyJyngCwiMo2std3As+XBeZ+7iEP8OvCbxphXgT3AxQ6u+/8BYWCXMWZP+b6IiIxB07yJiIiIiFRRD7KIiIiISBUFZBERERGRKgrIIiIiIiJVFJBFRERERKooIIuIiIiIVFFAFhERERGpooAsIiIiIlJFAVlEREREpMr/H+RU1YUEF9h2AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "kmf = KaplanMeierFitter() \n",
    "ix5 = (groups == 835)\n",
    "ix6 = (groups == 479)\n",
    "ix7 = (groups == 527)\n",
    "\n",
    "## fit the cohort 5 data\n",
    "kmf.fit(T[ix5], E[ix5], label='Aircraft 835')\n",
    "ax2 = kmf.plot()\n",
    "## fit the cohort 6 data\n",
    "kmf.fit(T[ix6], E[ix6], label='Aircraft 479')\n",
    "ax3 = kmf.plot(ax=ax2)\n",
    "## fit the cohort 7 data\n",
    "kmf.fit(T[ix7], E[ix7], label='Aircraft 527')\n",
    "kmf.plot(ax=ax3)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "deb45dc4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='timeline'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kmf = KaplanMeierFitter() \n",
    "ix8 = (groups == 915)\n",
    "ix9 = (groups == 925)\n",
    "ix10 = (groups == 708)\n",
    "\n",
    "\n",
    "\n",
    "## fit the cohort 8 data\n",
    "kmf.fit(T[ix8], E[ix8], label='Aircraft 915')\n",
    "ax4 = kmf.plot()\n",
    "## fit the cohort 9 data\n",
    "kmf.fit(T[ix9], E[ix9], label='Aircraft 925')\n",
    "ax5 = kmf.plot(ax=ax4)\n",
    "## fit the cohort 10 data\n",
    "kmf.fit(T[ix10], E[ix10], label='Aircraft 708')\n",
    "kmf.plot(ax=ax5)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a9995ec",
   "metadata": {},
   "source": [
    "<a id='cph'></a>\n",
    "### 9.3 Cox Proportional Hazard Model \n",
    "\n",
    "On Running Cox Proportional Model, the features **AIRCRAFT_CD, OPERATOR_CD, and FLEET_CD** showed high correlation for the model to train, therefore had to be dropped.\n",
    "\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2b06c554",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "df.drop(['AIRCRAFT_CD','OPERATOR_CD','FLEET_CD'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5879959c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   TIME_SINCE_INSTALL_CYCLES  REPETITIVE_FAULT_QT     MEL_QTY  REMOVED_BOOL  \\\n",
      "0                          0                    0  165.974648             1   \n",
      "1                       2325                    9  366.000000             1   \n",
      "2                          8                    1    1.000000             1   \n",
      "3                         24                    2    7.000000             1   \n",
      "4                          6                    1  165.974648             1   \n",
      "\n",
      "   COMPONENT_LIFE_DAYS  AIRCRAFT_AGE  \n",
      "0                    0          8030  \n",
      "1                  848          5840  \n",
      "2                    2          6570  \n",
      "3                   15          6935  \n",
      "4                    1          7300  \n"
     ]
    }
   ],
   "source": [
    "print(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "960ce700",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8))\n",
    "sns.heatmap(df.corr(),annot=True, cmap='viridis')\n",
    "plt.title('Correlation matrix of Numerical Data',fontsize =15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0ed2101",
   "metadata": {},
   "source": [
    "<a id='cphs'></a>\n",
    "#### 9.3.1 CoxPH Model Data Summary\n",
    "\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "81ea24b3",
   "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",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>model</th>\n",
       "      <td>lifelines.CoxPHFitter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>duration col</th>\n",
       "      <td>'COMPONENT_LIFE_DAYS'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>event col</th>\n",
       "      <td>'REMOVED_BOOL'</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>baseline estimation</th>\n",
       "      <td>breslow</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of observations</th>\n",
       "      <td>10323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>number of events observed</th>\n",
       "      <td>8182</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>partial log-likelihood</th>\n",
       "      <td>-67955.53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time fit was run</th>\n",
       "      <td>2021-12-21 05:50:53 UTC</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div><table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th style=\"min-width: 12px;\"></th>\n",
       "      <th style=\"min-width: 12px;\">coef</th>\n",
       "      <th style=\"min-width: 12px;\">exp(coef)</th>\n",
       "      <th style=\"min-width: 12px;\">se(coef)</th>\n",
       "      <th style=\"min-width: 12px;\">coef lower 95%</th>\n",
       "      <th style=\"min-width: 12px;\">coef upper 95%</th>\n",
       "      <th style=\"min-width: 12px;\">exp(coef) lower 95%</th>\n",
       "      <th style=\"min-width: 12px;\">exp(coef) upper 95%</th>\n",
       "      <th style=\"min-width: 12px;\">z</th>\n",
       "      <th style=\"min-width: 12px;\">p</th>\n",
       "      <th style=\"min-width: 12px;\">-log2(p)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TIME_SINCE_INSTALL_CYCLES</th>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-41.96</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REPETITIVE_FAULT_QT</th>\n",
       "      <td>-0.05</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.06</td>\n",
       "      <td>-0.04</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.96</td>\n",
       "      <td>-12.55</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>117.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEL_QTY</th>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-9.55</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>69.43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIRCRAFT_AGE</th>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>-0.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.00</td>\n",
       "      <td>-5.62</td>\n",
       "      <td>&lt;0.005</td>\n",
       "      <td>25.63</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table><br><div>\n",
       "<style scoped>\n",
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       "        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",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Concordance</th>\n",
       "      <td>0.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Partial AIC</th>\n",
       "      <td>135919.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>log-likelihood ratio test</th>\n",
       "      <td>5050.55 on 4 df</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-log2(p) of ll-ratio test</th>\n",
       "      <td>inf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/latex": [
       "\\begin{tabular}{lrrrrrrrrrr}\n",
       "\\toprule\n",
       "{} &  coef &  exp(coef) &  se(coef) &  coef lower 95\\% &  coef upper 95\\% &  exp(coef) lower 95\\% &  exp(coef) upper 95\\% &      z &    p &  -log2(p) \\\\\n",
       "covariate                 &       &            &           &                 &                 &                      &                      &        &      &           \\\\\n",
       "\\midrule\n",
       "TIME\\_SINCE\\_INSTALL\\_CYCLES & -0.00 &       1.00 &      0.00 &           -0.00 &           -0.00 &                 1.00 &                 1.00 & -41.96 & 0.00 &       inf \\\\\n",
       "REPETITIVE\\_FAULT\\_QT       & -0.05 &       0.95 &      0.00 &           -0.06 &           -0.04 &                 0.95 &                 0.96 & -12.55 & 0.00 &    117.63 \\\\\n",
       "MEL\\_QTY                   & -0.00 &       1.00 &      0.00 &           -0.00 &           -0.00 &                 1.00 &                 1.00 &  -9.55 & 0.00 &     69.43 \\\\\n",
       "AIRCRAFT\\_AGE              & -0.00 &       1.00 &      0.00 &           -0.00 &           -0.00 &                 1.00 &                 1.00 &  -5.62 & 0.00 &     25.63 \\\\\n",
       "\\bottomrule\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "<lifelines.CoxPHFitter: fitted with 10323 total observations, 2141 right-censored observations>\n",
       "             duration col = 'COMPONENT_LIFE_DAYS'\n",
       "                event col = 'REMOVED_BOOL'\n",
       "      baseline estimation = breslow\n",
       "   number of observations = 10323\n",
       "number of events observed = 8182\n",
       "   partial log-likelihood = -67955.53\n",
       "         time fit was run = 2021-12-21 05:50:53 UTC\n",
       "\n",
       "---\n",
       "                            coef  exp(coef)   se(coef)   coef lower 95%   coef upper 95%  exp(coef) lower 95%  exp(coef) upper 95%\n",
       "covariate                                                                                                                         \n",
       "TIME_SINCE_INSTALL_CYCLES  -0.00       1.00       0.00            -0.00            -0.00                 1.00                 1.00\n",
       "REPETITIVE_FAULT_QT        -0.05       0.95       0.00            -0.06            -0.04                 0.95                 0.96\n",
       "MEL_QTY                    -0.00       1.00       0.00            -0.00            -0.00                 1.00                 1.00\n",
       "AIRCRAFT_AGE               -0.00       1.00       0.00            -0.00            -0.00                 1.00                 1.00\n",
       "\n",
       "                               z      p   -log2(p)\n",
       "covariate                                         \n",
       "TIME_SINCE_INSTALL_CYCLES -41.96 <0.005        inf\n",
       "REPETITIVE_FAULT_QT       -12.55 <0.005     117.63\n",
       "MEL_QTY                    -9.55 <0.005      69.43\n",
       "AIRCRAFT_AGE               -5.62 <0.005      25.63\n",
       "---\n",
       "Concordance = 0.80\n",
       "Partial AIC = 135919.06\n",
       "log-likelihood ratio test = 5050.55 on 4 df\n",
       "-log2(p) of ll-ratio test = inf"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Using Cox Proportional Hazards model\n",
    "cph = CoxPHFitter() \n",
    "cph.fit(df, 'COMPONENT_LIFE_DAYS', event_col='REMOVED_BOOL')  \n",
    "cph.print_summary()    ## HAve a look at the significance of the features"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63ec9cab",
   "metadata": {},
   "source": [
    "<a id='cphi'></a>\n",
    "#### 9.3.2 Individual Component Survival Regression\n",
    "\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5b347555",
   "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>TIME_SINCE_INSTALL_CYCLES</th>\n",
       "      <th>REPETITIVE_FAULT_QT</th>\n",
       "      <th>MEL_QTY</th>\n",
       "      <th>AIRCRAFT_AGE</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>274</td>\n",
       "      <td>2</td>\n",
       "      <td>51.0</td>\n",
       "      <td>6570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>225</td>\n",
       "      <td>0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>7300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>206</td>\n",
       "      <td>0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1411</td>\n",
       "      <td>2</td>\n",
       "      <td>200.0</td>\n",
       "      <td>6935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>42</td>\n",
       "      <td>1</td>\n",
       "      <td>7.0</td>\n",
       "      <td>6205</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    TIME_SINCE_INSTALL_CYCLES  REPETITIVE_FAULT_QT  MEL_QTY  AIRCRAFT_AGE\n",
       "20                        274                    2     51.0          6570\n",
       "21                        225                    0     32.0          7300\n",
       "22                        206                    0     23.0          7300\n",
       "23                       1411                    2    200.0          6935\n",
       "24                         42                    1      7.0          6205"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## Survival curve at the Componenet level. Selecting any 5 Components (rows 20 till 25).\n",
    "\n",
    "cols = ['COMPONENT_LIFE_DAYS', 'REMOVED_BOOL', 'TIME_SINCE_INSTALL_CYCLES', 'REPETITIVE_FAULT_QT',\n",
    "        'MEL_QTY', 'AIRCRAFT_AGE']\n",
    "df = df[cols]\n",
    "tr_rows = df.iloc[20:25, 2:]\n",
    "tr_rows"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1cdb444d",
   "metadata": {},
   "source": [
    "<a id='model_prediction'></a>\n",
    "## 10. Model Prediction for Individual Component\n",
    "In Days\n",
    "\n",
    "[Go to Index](#index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "446b5383",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cph.predict_survival_function(tr_rows).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9da43ee9",
   "metadata": {},
   "source": [
    "<a id='requirements'></a>\n",
    "### Requirements.txt (libraries used in session)\n",
    "Click below to expand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "032f3832",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<details>\n",
       "<summary>Click to view session information</summary>\n",
       "<pre>\n",
       "-----\n",
       "cycler              0.10.0\n",
       "dateutil            2.8.2\n",
       "lifelines           0.26.4\n",
       "matplotlib          3.4.3\n",
       "numpy               1.21.3\n",
       "pandas              1.3.4\n",
       "seaborn             0.11.2\n",
       "session_info        1.0.0\n",
       "-----\n",
       "</pre>\n",
       "<details>\n",
       "<summary>Click to view modules imported as dependencies</summary>\n",
       "<pre>\n",
       "PIL                         8.4.0\n",
       "anyio                       NA\n",
       "appnope                     0.1.2\n",
       "astor                       0.8.1\n",
       "attr                        21.2.0\n",
       "autograd                    NA\n",
       "autograd_gamma              NA\n",
       "babel                       2.9.1\n",
       "backcall                    0.2.0\n",
       "beta_ufunc                  NA\n",
       "binom_ufunc                 NA\n",
       "certifi                     2021.05.30\n",
       "cffi                        1.14.6\n",
       "charset_normalizer          2.0.4\n",
       "cython_runtime              NA\n",
       "debugpy                     1.4.1\n",
       "decorator                   5.0.9\n",
       "defusedxml                  0.7.1\n",
       "entrypoints                 0.3\n",
       "formulaic                   0.2.4\n",
       "future                      0.18.2\n",
       "idna                        3.2\n",
       "interface_meta              1.2.4\n",
       "ipykernel                   6.3.1\n",
       "ipython_genutils            0.2.0\n",
       "jedi                        0.18.0\n",
       "jinja2                      3.0.1\n",
       "json5                       NA\n",
       "jsonschema                  3.2.0\n",
       "jupyter_server              1.10.2\n",
       "jupyterlab_server           2.7.2\n",
       "kiwisolver                  1.3.2\n",
       "markupsafe                  2.0.1\n",
       "matplotlib_inline           NA\n",
       "mpl_toolkits                NA\n",
       "nbclassic                   NA\n",
       "nbformat                    5.1.3\n",
       "nbinom_ufunc                NA\n",
       "packaging                   21.0\n",
       "parso                       0.8.2\n",
       "pexpect                     4.8.0\n",
       "pickleshare                 0.7.5\n",
       "pkg_resources               NA\n",
       "prometheus_client           NA\n",
       "prompt_toolkit              3.0.20\n",
       "ptyprocess                  0.7.0\n",
       "pvectorc                    NA\n",
       "pydev_ipython               NA\n",
       "pydevconsole                NA\n",
       "pydevd                      2.5.0\n",
       "pydevd_concurrency_analyser NA\n",
       "pydevd_file_utils           NA\n",
       "pydevd_plugins              NA\n",
       "pydevd_tracing              NA\n",
       "pyexpat                     NA\n",
       "pygments                    2.10.0\n",
       "pyparsing                   2.4.7\n",
       "pyrsistent                  NA\n",
       "pytz                        2021.1\n",
       "requests                    2.26.0\n",
       "scipy                       1.7.1\n",
       "send2trash                  NA\n",
       "sitecustomize               NA\n",
       "six                         1.16.0\n",
       "sniffio                     1.2.0\n",
       "storemagic                  NA\n",
       "terminado                   0.11.1\n",
       "tornado                     6.1\n",
       "traitlets                   5.1.0\n",
       "uritemplate                 3.0.1\n",
       "urllib3                     1.26.6\n",
       "wcwidth                     0.2.5\n",
       "websocket                   1.2.1\n",
       "wrapt                       1.13.3\n",
       "zmq                         22.2.1\n",
       "</pre>\n",
       "</details> <!-- seems like this ends pre, so might as well be explicit -->\n",
       "<pre>\n",
       "-----\n",
       "IPython             7.27.0\n",
       "jupyter_client      7.0.2\n",
       "jupyter_core        4.7.1\n",
       "jupyterlab          3.1.10\n",
       "notebook            6.4.3\n",
       "-----\n",
       "Python 3.9.7 (default, Sep  3 2021, 12:37:55) [Clang 12.0.5 (clang-1205.0.22.9)]\n",
       "macOS-12.0.1-x86_64-i386-64bit\n",
       "-----\n",
       "Session information updated at 2021-12-21 00:53\n",
       "</pre>\n",
       "</details>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "session_info.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46e397e3",
   "metadata": {},
   "source": [
    "<a id='end'></a>\n",
    "EOF\n",
    "\n",
    "[Go to Index](#index)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}