{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "# Fitting Pre-Industrial Experience to a Model: Lecture Support\n",
    "\n",
    "* <https://github.com/braddelong/LSF18E101B/blob/master/Fitting_Pre-Industrial_Experience_to_a_Model-Lecture_Support.ipynb>\n",
    "* <http://nbviewer.jupyter.org/github/braddelong/LSF18E101B/blob/master/Fitting_Pre-Industrial_Experience_to_a_Model-Lecture_Support.ipynb>\n",
    "* <http://datahub.berkeley.edu/user-redirect/interact?account=&repo=nbviewer.jupyter.org&branch=braddelong&path=LSF18E101B/blob/master/Fitting_Pre-Industrial_Experience_to_a_Model-Lecture_Support.ipynb>\n",
    "* <https://www.icloud.com/keynote/0OzjdiQ0B1z4NlvvDrOkkat9w>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "notes"
    }
   },
   "source": [
    "## Setting up the Python/Jupyter environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
       "    return false;}"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%javascript\n",
    "\n",
    "IPython.OutputArea.prototype._should_scroll = function(lines) {\n",
    "    return false;}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# keep output cells from shifting to autoscroll: little scrolling\n",
    "# subwindows within the notebook are an annoyance..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# libraries\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make sure graphs are displayed in main notebook\n",
    "\n",
    "%matplotlib inline  \n",
    "\n",
    "plt.style.use('seaborn-whitegrid') # graphics setup\n",
    "figure_size = plt.rcParams[\"figure.figsize\"]\n",
    "figure_size[0] = 10\n",
    "figure_size[1] = 7\n",
    "plt.rcParams[\"figure.figsize\"] = figure_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAuoAAAMQCAYAAABxGUBtAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvhp/UCwAAIABJREFUeJzs3Xm4XFWZ7/Hv7wxJCISEIWSeICHMBAwyqIgiCk5gi7aILSA2V1uveu3BoQexHbodWmxb225auOAIXCdQUURGkTEhzCRkIJCJzAmBQJJzznv/WKtIpVJnCuecXVX5fZ6nnlO19rDeXaf2rrfWXnttRQRmZmZmZlZbmooOwMzMzMzMduZE3czMzMysBjlRNzMzMzOrQU7UzczMzMxqkBN1MzMzM7Ma5ETdzMzMzKwGOVG33ZqkyZJC0hVFx2KJpFPy/+TiomPpD321fZLOz+s5v28iq1/5fbi16Di6Uquf64H6HEm6ItczuT/rMWs0TtStpklqlvSXkm6TtE7SNkmrJD0k6XuS3l50jANFUquk90v6paQlkl6QtFnSk5J+IemDkvYsOs7uDPSPo1xXSOqQdFAX891SNu/5AxFbrShLos4vOpZ6Iuldkn6Xj0nbJK2V9JikH0o6r+j4BpKki/Nn6JSiY+mpss99+WNz/h/+m6SRRcdo1lJ0AGadkdQM/Bo4HdgA/AZYCuwLHAS8FzgEuK6oGAeKpEOAnwGHkd6Lm4EngTZgHHAycBbwL4C/XHbWRjreXQh8tnKipGnAa8vmM+uSpEuBvwReIB2bngT2BA4E3gacAlxZtsi9wKHAmgENtHZ8BvhXYFnRgVRxLfBAfj4KeDPwSeCdkl4REWsLi8x2e/5Cslp2DilJfxB4bURsLJ8oaShwfBGBDSRJY4CbgLHAfwCfjYjnqsx3GvC1AQ6vXqwEVgAXSPqniGirmP5BQKQfhmcNdHBWXyS9ipSkLwVOjIilFdNbSYn6SyJiMzB3oGKsNRGxgrQP1qJfRsQVpReShgB3A0cDHwU+X1BcZu76YjXtpPz3isokHdIXX0TcUlkuabCkT+fuMZslPSvpj5Le3ZvKJY2R9B1JiyVtlbRa0s8lvaJivjflU6Zfqih/fdnp1AkV067J5Qf2IJQvk5L0H0fEx6ol6QARcSMws6Kel7qZSDpY0tX5NH1H+SlqSdMkfV/Ssryty/PraRXr+195fX9ZUf6BstPGgyum3SvpRUl75P65T+ZJ51Wccj6/cpskzZD0G0kb8rpvk3RS5Xw99D/AaOCtFXW0AucBdwKPdrZwT9+jsvlHSbpM0srcTemB7rpDSNpX0r9Iejwvs1HSTZLe2Out7UeShkr6TN6m5yU9J+kuSedUzHdO/t9+o5P1DJa0XtIzklqqLHtLnv5ifk/+ofLz1UWMwyT9o6RH8jFgk6SFeR94Rfdr6NKr8t+fVSbpABGxLe+P5fFU7aMu6dZc3irpn3KML0qaW76fSfqQpIfz52KppM9LaupJHWXTF0ta3JMNlPQ6SZcqdQN5Ntf7iKTPKSWyO6wX+Fx+Wd6FLMrm6bSPuqR3S7o9f95fyNv5mWr/69I25M/g1yQ9LWmLpAWSPiVJPdm+rkTEi8CP8svjqsTQ6TUR1bZTOx6HJ0u6StKa/H+eJemt1dZlBk7UrbaVTjce3NMFJA0CbiB1AWkFvgP8IK/jaklf7uF6pgCzgL8CFgL/ltf7FuDOigPrH4GtwKkVq3l92fOXpuUvklOAxRGxqJs4hpLOLEAPWnWqtBSXHATcA0wmfQFdCjyb6ziOtK3vA+4Dvk5qTToXmCWpPPm/qXJ7stK27gGcWBb/cOBY4K6IeAG4Ffj3PPnBvE2lR+nUc8lMUvI8BPgeqbX71cBNkqZ3sp1d+QnwPKn1vNzbSae7/6ezBXv5HiFpvxz7B4AngG+Stu+/gP/TSR2TgNnAp4HVed6rSd0lfqeKH0ddxFq6OPCKnszfW5JGAHeQfkC2A5eTuniMBH4s6Ytls/8C2AicW5mIZ2cCI4Afln92JV0G/BiYCvyctB+vA75Aei+6PBuc97HfAf9M+px/D/guqfvJyZR9RvP8ve2j3+tjUw9cBVxE2scuA/YBLs3/z28AXwLuB/6bdLz5J+Bv+7D+Sp8C3kj63P436T3cClwM/Fapa2LJN4Hb8vMr2XG/7lI+Jpc+5z8Gvk06u/Vl4AalH9KVWoHfA+8Efptj24PUteaferGNXYaW/27ro/UBTCJ9BieTvpeuBo4ArpX0uj6sxxpJRPjhR00+gGNIXwwdpIPanwGTulnmM0AA1wMtZeUHAIvztJPKyifnsisq1nNDLv/7ivKTSP2Y1wJ7lZXfnsuHl5XdRfpiXQP8oKz86Lzuy3rwHpyc512yi+9hafsC+HKV6QIez9PPrZj257l8LtBUVv4UsApQWdlyUoLRDnyhrPzMvI5/7O49L5t+SlnM51dM+1+5/D978R4EsDQ//17+P40vm/47UjI5FPhiZb27+B5dmssvqZh/JumLP4CLK6bdmj/r76koH0FKll4ARpWVn9/Je1Qqr/r+dvIeXVFtXd3M+3cV5UPye9kBzCgr/+88/1urrOs3edqRVeL/ObBHxfwX52kfr/I/vrXs9ZG57BdV6mwC9tnV7c/zjyNdKxKka2TeC0yjbJ/o4nNd7f8epB+AI8rKDyQd/9aTzkKNq/hMrCH9oGvpro6y6YtJDQTVPi+Vn6MDq20P6cdSAH/eyf/mlG4+N5PLyk7MZU8Do8vKW4Bf5WmfrbINpWP8HmXlB+T/yQag9eV87klJ/0N52l9XWW6Hz1sPtnMy249pn6uY/02l7enp/urH7vVwi7rVrIiYQ2rBXJn//gxYrDSywi8kva3KYh8gHfQ+GWUtdBGxivQFAzu3qO5A0nhSS9LTwFcrYrqT1DK7L+mHQ8lNQDPpgkQkDSMlZTcCt7BjC/SpZct0Z3T+W/UCrNzadnHFY0aVWVdSvXXrJNIFuXdFxI/KJ0TE1aSW0+mkluySm0mtp0fmGA4DxgA/Jf0w2dVtrfSnKOs3ml1OSrRfuQvrg9Rq3kz6nJRasU8DfhSpD3E1vXqPcgvgucAmUvJSPv8stp9Sf4mko0mfnZ9FxFUVy2wgdSsYQmpB7M4vSK2Tn+nBvL2SzxS8D5gVEZX7xoukVliREteS0gWVO3T7kTSalKTMiYiHyyZ9nPQ//kCkszDlvkD6kXxuD0OuXJ6I6IiI9RXFnyG9Z7/oyUojYhnwDtLZtreR/qdPABuVRoF5X0WLc098Ov+vS3UsIn22RpB+/C4rm7aBlMjuT/rR0OciYlFERJVJ38x/39QH1Xwg//1iRDxTVncb8NekH32dHa8/Vv75yMf4a4HhpP2xN84qO37+JzCPdHy7nXQmpq88RWoMeElE3ED6rtnVY5o1OF9MajUtIq6R9AvgdaRE6Jj89yzSwfX7pNaQyMnxVGBZRFS7aOvm/PeYbqotTf9jRFQ77XkzKVk5Bvh+WdnFpMT0OlLS1UJKUBcDZ0s6NCIeZ3s3kZvpXun0a7UvTEitYa+tKFvMzt1IHoyILVWWP7abWG5m+/t+e1nZ+aRtfYjt23MTqeXok5KGRcSmPO050une3ppVWRAR2yStJHUL6LWIuEfSw8AHcheND5JaWDvt9kLv36NDSK3zf4wq11aQWlDPqygrdcUY3kn/4tJIPod2EScAuc5q9faF40g/dDrrB13qpvBSnBFxp6QngLdJ2qcsST43r+uK0ry5q9fRpNbiT3TS3XgL3b8Pj5H2gXPyj7FrSUnvrIjYWjlz7MKFjhFxi6SDSf3VX0v6/7+KlMC+iXQNxls72e+q2enzTjpTBalLVKVS4j6elAD2KaWhXj9O+kFyMDCM7ccj6JsfCJ3uWxHxhKSlwBRJI8p/xAAbI2JBlfUtyX97e3w4Mz/K3Qi8pZPvgF31QES0VylfQkV3LLMSJ+pW8/KB8vf5URq28Z2k1tX3k1rBfklqSYHOv3BL5SO6qXJX1nM3qf9zqQX5VNJp6ztIiTPAqZLmk7qzPFbegtSFUl1VvxQj4pTS85x4/n0n6+msrl3Z1vJ+6pfkv0vzF+tNwN8Br5V0H3A46ZRuZ33nu7Khk/I2UoK3q/4H+BZpRKELgNn57E1nevseleZf2cn81f4X++W/p+VHZ/bqYtpAKMV5HFUusitTGeeVpD7W72F7C+V5pG5APymbbx9SMjiS7Rcn9lpEtEt6Pam/8tnAV/KkTZKuBD4TnVyU3ct6OkjXqPwRXuobfxppe98AfJjtLdDdravaj6vSftPVtGp9uF+WfFboZlIr7yOkvtSr2d5f+3NAjy7q7UZP9q2Jeb7y40FXxwbo/fHhgoi4In+3HEg6c/PnpM9ql2dge6mruN3DwaryB8PqTkS0R8Q1pCQRtrfolr7MRu+8FJC6Z5TP15leryf/mLgDOFxpOMVTSV0lNkfEE6Rh3N5A+uIbRs9a0yG1sm0BJqiT0UV6qLMW+V3Z1uWkU8OvzaMynML25P0O0g+UN7D9R0tPt3Wg/IDUJeK/ST+ALu1m/t6+R6W/ozqZv9p6Sst8PCLUxeOCbmLtb6U4L+kmzsoL435A6sZwHoCkY0hdC66PiNVV1j+nm/V3O7JHRKyPiP8TERNI/cc/SLqW4KP0bXeG8jojIn4P/EMuen1X8/eDjvy3s0a44Z2UVzqTdKy6MiKOjIiLIuLvI+Ji0n7TV/rqmN0n8nfLfFLXrXuAC1X9pnpB5+9xdw1BZr3iRN3q2ab8VwC5q8VCYFwnSW0pebi/m/WWWldf3cnoEp2tp5Ssvod0JX95v+ybSQntaRXzdin3my61OPbVaAblStt6SifTS+XVtnUvUovhiPy6FO/dpCS9vEtMudKp35fTKr7L8in0n5K6DDzPji261fT2PZoLbAZm5FFvOpu/3N3572u6iaVo95KSwV7FGRFLSPvA8XnEnlLXnysr5nuONETm4ZL2ffnhvrTeBRFxGamLynPs3M2hr+1wbBpApW5FEyonSJpKz5PIqfnvz6pMq+xqV7Ir+3Wn+1aOdzzwZEW3l36Xz5R8PL/8apXrDdZT/T1uBqpdI2S2y5yoW81SGkf5NFWMFZynjSbdcAS2952G1B1GwNfKD66S9gf+sWyeTkUaF/lGUn/rT1TUezyptWU9O194Vmo5/nSOoTJRH04a7rGD1E+5p/6e1Ff1fZIuyX1Hq+lpa1m5P5Fax18t6ezyCfn1yaSL5O6oWK60rZ+peF16fgRp2MO1pGEYy60ntUhN3IV4+8o/kPrevin/wOtKr96jfHblR6QzJxdXzD+TKhdC5otM/wj8maQPVE7Pyx4p6YDuNkzScEmH5DM7fSpfsPcjYKbSGOU7/ZCVdFAe3rTSFfnvhaQhR9eShtys9A1gEHB5Hgqycv37SDp258V2mGeKpMOrTNqH1GXjhYr5x+T3rEf7kKTTJf1ZtaEDJe3F9uPG7ZXT+9lc0nCUZ5Z/ViTtQeru1VOL899TyguV7vvwlcqZs9KQlb3Zr0vH4n+Q9NIdlfOx++ukHOWyXqyvz0TEPaTP53RSF8ty9wITtfP9Df6BNASjWZ9xH3WrZceTWjWekXQH22+UM4U0nvkepIvEflq2zNeBM0gtZg9Kup50Yd+7SMN3fTUiKpPOaj5EStC+lg/Gs0gtKO8iJdoXVEnw5pDGej6AnS+gLCXtB5AuaOtxC1FELJd0Kmm4uk+QLlK7GViUYxlFuohtGmnYxB7f/TBfhHse6YfJ1ZKuzctPJ12wuwl4f25hKndLrvsAYG75iBR5Wy8m9TP+aeXIERHxnKR7gNdIKo2W0Q5cFxEP9TT2lyMiniaNtNCTeXflPfos6azCJ3JyfgfpNP6fk4aVq3Y6/b2kHzmXSfoY6dT7BlKr4lGkHz8nkv7HXXkH8H9JrdXn92Qby3xQZTfCqvDj3K3jo6TP2j8Df5H3zZWkm3IdSuq7fg7b99eSn5OSyE+Q+lX/R7UL9SLicqUbEv0VsFBSaVSMfUn7/sl5+z7UxXYcDfxC0mxSH+vlpM/jmbnuymTzX0it/BdQdnFrFw4hdb1bL+mPwHzysJ+kY9MI0v/v2z1YV5/JF1v/O6lRYk6+EL+FdCZvOdsvTu3Or4AFpAvDjyQd2yaSbhb2G6on46Vjwr9IOoLcuh8RX6wybyneOyV9lXRdyyOSfko6y3UG6fN+B8XebfmfSP/Pz0n6UdmFyF8nXTB8raSrScf9k0ifz1vp/OybWe9FDYwR6Ycf1R6kxPgjpJbreaQv+a2kC4yuJ4280lRluSGkROkRUsvZJtIB/5wq806mkzGnSf2Xv0saUWEraSSKXwLHdRHzz/L6flNl2rw87Su7+H4MIiUT15FGfHgxb99TpB8sF1I2tnt321cx33RSP+IVpAvGVgA/BKZ3sczsvO7vVJS3kn6oBPDhTpadSkoG1pK+3F8ay5hdGAu6m20L8jjqPZh3p3HUd/U9IvW7vZx0Ed4LpFFIzu9q+0it8J/N7+1zebknScnRRcCeZfOeXy1WXt446l09PlHxWfwo6aZOG0nXUTxN+pH2CWC/Tur5Xtn6XtFNTG8ltWiuIu1/z5B+/H4ROKTK//jWstfjSTfM+VNebgvpOpHfAmd0sf07/d87iW1/0tCCPyGNMLM+fyZWkxLWvwIGVSxT9f9OHke9m//L5CrTLqbKuOWks3mfJnUD3Mr2YWaH0rtx1CeQzp4sy5/DR0kJdUvl+122zPvYPuZ/lG9XN9vyHtIxehPpuPYo6UzikN7s/529Jz343Hf6f2f7Mf1/V5S/ndSA8yLpOHYVqTV9p+2k+3tHdPoZ8MMPRXR2jZmZmZmZmRXFfdTNzMzMzGqQE3UzMzMzsxrkRN3MzMzMrAY5UTczMzMzq0FO1M3MzMzMapATdTMzMzOzGuRE3czMzMysBjlRNzMzMzOrQU7UzczMzMxqkBN1MzMzM7Ma5ETdzMzMzKwGOVE3MzMzM6tBTtTNzMzMzGqQE3UzMzMzsxrkRN3MzMzMrAY5UTczMzMzq0FO1M3MzMzMapATdTMzMzOzGuRE3czMzMysBjlRNzMzMzOrQU7UzczMzMxqkBN1MzMzM7Ma5ETdzMzMzKwGOVE3MzMzM6tBTtTNzMzMzGqQE3UzMzMzsxrkRN3MzMzMrAY5UTczMzMzq0FO1M3MzMzMapATdTMzMzOzGuRE3czMzMysBjlRNzMzMzOrQU7UzczMzMxqkBN1MzMzM7Ma5ETdzMzMzKwGOVE3MzMzM6tBTtTNzMzMzGqQE3UzMzMzsxrkRN3MzMzMrAY5UTczMzMzq0FO1M3MzMzMapATdTMzMzOzGuRE3czMzMysBjlRNzMzMzOrQU7UzczMzMxqkBN1MzMzM7Ma5ETdzMzMzKwGOVE3MzMzM6tBTtTNzMzMzGqQE3UzMzMzsxrkRN3MzMzMrAY5UTczMzMzq0FO1M3MzMzMapATdTMzMzOzGuRE3czMzMysBjlRt5dF0q2SPlh0HGb1TNIXJa2R9Ex+/Q5JSyQ9J+kYSY9KOqUH63lO0oH9HnAfkDRd0hxJmyR9rA/Xe4WkL/bV+sxqiaRzJf3+ZSxf+He2pIsl/bDIGOqJE3UDQNJiSW8oOo5KkkLS8zkBeU7ShqJjMuutvH+9UPY5fk7St/O0CcBfA4dFxOi8yNeBj0bEXhExJyIOj4hbu6snz7+o3zakb/0dcGtEDIuIb1VOrIWEwmxXSXqvpFl5X18h6beSXv1y1xsRP4qIN5bVE5Kmvtz15nWNkHS5pGfyD+gnJH2qP+qynmspOgAzAEktEdHWyeSjI2JBP63bbKC8LSL+UKV8ErA2IlZVlD06MGEVZhJwVdFBdEaSAEVER9GxWH2R9Eng08CHgBuArcDpwJnAHQWG1p1LgD2BQ4GNwMHAEYVGZG5Rt65J2kfSryWtlrQ+Px9fMdtBku6VtFHStZL2LVv+7fm0/YbcQnZo2bTFkj4l6SHgeUm9+uEo6S8lLZC0TtJ1ksaWTQtJH5E0H5ifyw6XdGOef6Wkz+byJkmflrRQ0lpJ15Rvg1l/yWexbgTG5pa3n0h6DmgGHpS0MM/30hkvSc2SPps/r5skzc6t8ju0eEkaLOnrkp7On/f/krRHnnaKpKWS/lrSqtzid0FZXHtI+jdJT+X9+o5c9htJ/7tiGx6SdFYn21d1/5d0M/A64Nt5uw/u5fv2/3Kr30ZJt0s6vGKW/fO+vknSbZImlS17kqT78rL3STqpbNqtkr4k6U/AZqAuuhFZ7ZA0HPhn4CMR8fOIeD4itkXEryLib/M8r5R0V94vVkj6tqRBZesISR+TtEipS9zXJDXlaedLuiM/vz0v8mDej/68h9/ZnTkO+HFErI+IjoiYGxE/7ayuXN7V93DV79yK96s1H/d+Vv4e2HZO1K07TcD/JbV+TQReAL5dMc/7gQ8AY4E24FsA+cv3J8AngJHA9cCvKnbGc4C3ACN60+ot6fXAvwDvBsYAT7Fz69xZwPHAYZKGAX8AfpfjnArclOf7WJ73tXnaeuA7PY3FbFflFvYzgOW528o5EbFXnnx0RBxUZbFPkvabNwN7k/a9zVXm+wqpRWwG6fM+DvinsumjgeG5/ELgO5L2ydO+DrwCOAnYl9RNpQO4EnhfaQWSjs7LX19ZeVf7f0S8Hvgj27v3PNHpm1Tdb4FpwAHA/cCPKqafC3wB2B94oDQ9/wD/DekYtR/wDeA3kvYrW/YvgIuAYaTjillvnAgMAX7RxTztwP8hfT5PBE4F/qpinncAM4FjSS3xH6hcSUScnJ8enfejq+nZd3Zn7ga+JOkCSdO6q6ur7+FuvnPJ8+wB/BLYArw7Irb2MM7dS0T44QfAYuANPZhvBrC+7PWtwL+WvT6MdJqvGfhH4JqyaU3AMuCUsjo/0E19ATwLbMiPb+Xyy4Cvls23F7ANmFy23OvLpp8DzOmkjseBU8tej8nrain6/+JHYzzyZ/25ss/xBuAv87RTgKUV8wcwtWL5N+Tn84AzO6knSF+IAp4HDiqbdiLwZFmdL5R/xoFVwAl5P32B9IVcuf7BwDpgWn79deA/O4mlu/3/VuCDXbxnXU4vm29E3u7h+fUVwFVl0/ciJUYTSEn4vRXL3wWcX1bnPxf9efGjfh+kH4nP9HKZTwC/KHsdwOllr/8KuCk/Px+4o2LeqV2su9p3dtX9CtgD+CwwO38HLgDO6Kwuuvgepuvv3IuB64DbSD+aVfT/rZYf7qNuXZI0lNRv7XSg1No2TFJzRLTn10vKFnkKaCW1FIylrEUqIjokLSG1wFFl2c4cGzv3UR9Lakkrrfs5SWvzuhdXWfcEYGEn658E/EJSeV/UdmAUKbEw6wtnRfU+6r3V1We5ZCQwFJgtqVQm0g/okrWx41mszaQv2v1JLYI71RERWyRdA7xP0udJX8ZndxJDT/b/XpPUDHwJeBdpO0v77f6kfrVQtu/nY8O6HM8OMWVP0ftjklln1pK6XnV6bVQ+2/QNUov5UNL1grMrZqv8Xh1LD/TwO7uqiHgB+DLwZUl7k/rZ/z9JEyNiXZVFuvoe7u44dQIpVzgncvZu1bnri3Xnr4HpwPERsTdQOv2lsnkmlD2fSPpFvQZYTkqC0wIpY5jAjsnvru6glevek3Qqu7N1LwGqdSMoTTsjIkaUPYZEhJN0q0VdfZZL1pBaxQ8v+0wPj+3darpb9sUu6riS1Gp4KrA5Iu7qZL6e7P+74r2krgBvIHXdmVyqomyel45JkvYidd9ZXhlTNpG+OSaZQTpD8yKpO2VnvgvMJZ2Z2pvUiq2KeSq/V5f3sP6efGd3KyKeJSXtewJTOpmtq+/h7o5Tvyd1m7lJ0qjexLa7caJu5VolDSl7tJD6ab4AbMj9Oz9XZbn3STos/5L/Z+Cn+Zf7NcBbJJ0qqZV0ANkC3NkHsf4YuEDSDEmDSQeUeyJicSfz/xoYLekTShfZDZN0fJ72X6R+eZMAJI2UdGYfxGjWH74HfEHSNCVHVfSxJtJIJf8DXCLpAABJ4yS9qbuV52UvB74haazSxasn5v2MnJh3AP8G/KCLVfXF/t9ScUxqJR2TtpBaLoeS9v1Kb5b06nw9zBdIx4YlpH7yBysNndeSL4g7jHR8MHvZImIj6VqQ70g6S9LQfMHkGZK+mmcbRurS+ZykQ4APV1nV3+YLQycAHweu7qTKlex40XNPvrOrkvSPko6TNEjSkFzvBlJ3u2p1dfU93NV3LgAR8dW8jpsk7d/TOHc3TtSt3PWkHbz0uBj4Jqnf2hrShSa/q7LcD0j9Qp8hnTL/GEBEzCNdePYfefm3kYaoe9kXjETETaQ+sD8DVpB+ub+ni/k3AaflGJ4hjQTzujz530n95X4vaRNpO4+vth6zl+FX2nEc9a4uNuvKN0hJ8O9JX/aXkfbRSp8i9TG9W9KzpAu7pvewjr8BHgbuI/VJ/wo7fl98HzgS6PSmJX20/3+XHY9J/zfX/RSp1e4x0v5a6cekBGUd6aLYc3NMa4G3kn40rCVdJPvWiFjTi5jMuhQR3yBd9P0PwGpS6/JHSRdOQtq/3gtsIv2grpaEX0vqDvMA6QLoyzqp7mLgSqURZN5Nz76zOw2dtI+VzoifBrwlIp6rVldX38PdfOdurzDiC6T35Q/yaGtVyV2DzMysNyS9H7goIl72DVzMbEeSgtQtZpfvH2KNwy3qZmbWY7mL218BlxYdi5lZo3OibmZmPZL7uK8m9VX9ccHhmJk1PHd9MTMzMzOrQW5RNzMzMzOrQb7hUbb//vvH5MmTiw7DrGbMnj17TUSMLDqOary/mu2olvdX8D5rVqmn+6wT9Wzy5MnMmjWr6DDMaoakyjs41gzvr2Y7quX9FbzPmlXq6T7rri9mZmZmZjXIibqZmZmZWQ1yom5mZmZmVoOcqJuZmZmZ1SAn6mZmZmZmNciJupmZmZlZDXKibmZmZmZWg5yom5mZmZnVICfqZmZmZmY1yIm6mZmZmVkNcqJuZmZmZlaDnKib7WZ+fMPX+O2fflB0GGZmZg1l43Pr+M+f/x2PL5rdZ+ts6bM1mVld+OHTVzKyYw/OeNVfFB2KmZlZw5gz9za+u+m3dMzp4NADX9HRJzc1AAAgAElEQVQn63SibrYbaWvbxsoWOLR9v36tR9JiYBPQDrRFxExJ+wJXA5OBxcC7I2K9JAH/DrwZ2AycHxH3v5z6v/TD87n7hb5r0TAr2tV/cTdDh+xZdBhm1oUnlqWvroNGH91n63SibrYbeWzRfWxtEqOGTByI6l4XEWvKXn8auCki/lXSp/PrTwFnANPy43jgu/nvLhs2eAT7Pj/k5azCrKY0SUWHYGbdWL5hPgBHH3xyn63TibrZbuSxxXcDMGn/w4qo/kzglPz8SuBWUqJ+JvD9iAjgbkkjJI2JiBW7WtHH3vXNlxmqmZlZ76zasoIRLR2MHTmpz9bpi0nNdiNPrXkMgMOnnNjfVQXwe0mzJV2Uy0aVku/894BcPg5YUrbs0ly2A0kXSZoladbq1av7MXQzM7PeW8NGRrX1bRu4W9TNdiPPbH6aIc3BYVNm9ndVr4qI5ZIOAG6UNLeLeaud04+dCiIuBS4FmDlz5k7TzczMirSyeRuHtu/bp+t0i7rZbmR1+1rGtImm5uZ+rScilue/q4BfAK8EVkoaA5D/rsqzLwUmlC0+HljerwGamZn1oWfWLGFdSxMHDB7Tp+uti0Rd0gRJt0h6XNKjkj6ey/eVdKOk+fnvPrlckr4laYGkhyQdW+wWmNWGVc1bGBl79WsdkvaUNKz0HHgj8AhwHXBenu084Nr8/Drg/Xm/PQHY+HL6p5uZmQ20OfNuBWD8iOl9ut66SNSBNuCvI+JQ4ATgI5IOY/soEtOAm/Jr2HEUiYtIo0iY7dY2Pb+BlS1wQOsB3c/88owC7pD0IHAv8JuI+B3wr8BpkuYDp+XXANcDi4AFwP8Af9XfAZqZmfWlBcvT0IyHTjiuT9dbF33Uc+ta6SK0TZIeJ11sNmCjSJjVuwfm3U6HxNg9D+zXeiJiEbDTILIRsRY4tUp5AB/p16DMzMz60fJNC2lqCmZM77uhGaF+WtRfImkycAxwDx5FwqzH5i2dBcDUse4JZmZm1pdWta1mVBsM23NEn663rhJ1SXsBPwM+ERHPdjVrlbKqo0hExMyImDly5Mi+CtOsJi1ZPw+AY6afUmwgZmZmDWa1nuOA9sF9vt66SdQltZKS9B9FxM9zsUeRMOuhlVuWs29bB6P3n9D9zGZmZtYjbW3bWNES7N/ct0MzQp0k6pIEXAY8HhHfKJvkUSTMemgNzzKqvbXoMMzMzBrK3MX382KTGD10Yp+vuy4uJgVeBfwF8LCkB3LZZ0mjRlwj6ULgaeBdedr1wJtJo0hsBi4Y2HDNas8zLW0c3eYuXmZmZn3pkUV/AmDy/kf0+brrIlGPiDuo3u8cPIqEWbeWrJjPxuYmRrWMLToUMzOzhrJ4zaMAHHHgSX2+7rro+mJmL8+c+bcDMGHfQwuOxMzMrLE8s/lphnQEh02Z2efrrosWdTN7eRY9k3qMHTKxb2/EYGZmtrtb3b6OMSGampv7fN1uUTfbDSx/7klaIjj64NcUHYqZmVlDWd28hZGxV7+s24m62W5g9bbVjG6DoUP2LDoUMzOzhrHp+Q2sbIEDWg/ofuZd4K4vZruB1U2bGdmxR9FhmJmZNZT7595Gh8TYPQ/sl/W7Rd2swZVuxDCyab+iQzEzM2so85bOAmDq2GP7Zf1uUTdrcA8tuJutTWLMHpOLDsXMzKyhLN0wD4Bjpp/SL+t3om7W4B578k4AJo88suBIzMzMGsuqLSvYt7mD0ftP6Jf1u+uLWYN7au1jABw11SO+mJmZ9aXVPMuo9tZ+W78TdbMGt+KFp9i7vYOp4w8vOhQzM7OG0dHezvKWNkZpn36rw11fzBrcqtjAmLaWfrkRg5mZ2e5q/tMP8VxzE6MHTeq3OtyibtbglrdsY5RGFB2GmZlZQ5kz/xYADjrgqH6rwy3qZg1s0ZJH2djcxOjW/rnIxczMbHf15OqHADhm2uv6rQ63qJs1sPufuBWAKft7xBczM7O+tHzzU+zV3sG0if3Xou5E3ayBLVw5B4Cjpr624EjMzMway8pYz9h+vgbMibpZA1vx/GKGdnRwxIHHFR2KmZlZQ3mmZRujGN6vdbiPulkDWxnrGLut2SO+mJmZ9aGnlj/B+uYmRreM79d63KJu1sBWNG/hAPYuOgwzM7OGcv+8mwGYvP8R/VqPW9TNGtTy1U+xtqWJ0S3jig7FzMysocx/5n4Ajjiwf+/67RZ1swY16/E/ADBp38MKjsTM+sMll1zC4YcfzhFHHAEwRdIQSVMk3SNpvqSrJQ0CkDQ4v16Qp08urUfSZ3L5PElvKis/PZctkPTpsvKqdZjtTlY8v5ghHcFRU0/o13qcqJs1qAUrZgNwxORXFRyJmfW1ZcuW8a1vfYtZs2bxyCOPAAh4D/AV4JKImAasBy7Mi1wIrI+IqcAleT4kHZaXOxw4HfhPSc2SmoHvAGcAhwHn5Hnpog6z3cbKjjWM29ZES0trv9bjRN2sQS3btIhBHcGM6f17Ws7MitHW1sYLL7xAW1sbpO/zFcDrgZ/mWa4EzsrPz8yvydNPlaRcflVEbImIJ4EFwCvzY0FELIqIrcBVwJl5mc7qMNttPNO8hQMY1u/1OFE3a1Ar29cwtk0MGjS46FDMrI+NGzeOv/mbv2HixImMGTMGoB2YDWyIiLY821KgdJHKOGAJQJ6+EdivvLximc7K9+uiDrPdwjNrlrC6pYnRg8f2e11O1M0a1MrmFxkVexUdhpn1g/Xr13Pttdfy5JNPsnz5ckjf52dUmTXyX3Uyra/KdyLpIkmzJM1avXp1tVnM6tLsuTcBMHGf/r8GzIm6WQNau+EZVrbAqNbRRYdiZv3gD3/4A1OmTGHkyJG0trYCbABOAkZIKo3oNh5Ynp8vBSYA5OnDgXXl5RXLdFa+pos6dhARl0bEzIiYOXLkyJezuWY1Zf7ydA3Y4ZNP7Pe66iJRl3S5pFWSHikru1rSA/mxWNIDuXyypBfKpv1XcZGbFWPW4zcTEhNHHFJ0KGbWDyZOnMjdd9/N5s2biQiAYcBjwC3A2Xm284Br8/Pr8mvy9JsjLXgd8J48KswUYBpwL3AfMC2P8DKIdMHpdXmZzuow2y0s3bSA1giOmX5yv9dVL+OoXwF8G/h+qSAi/rz0XNK/kfrblSyMiBkDFp1ZjXli6X0AHDKxf4eNMrNiHH/88Zx99tkce+yxtLS0QOqScinwG+AqSV8E5gCX5UUuA34gaQGpJf09ABHxqKRrSEl+G/CRiGgHkPRR4AagGbg8Ih7N6/pUJ3WY7RZWta9hbIcYMnhov9dVF4l6RNxePuZruXwF+rtJV6GbGfD0s/NoaQ6OO/wNRYdiZv3k85//PJ///OcBkPRkRGwBFpFGbNlBRLwIvKvaeiLiS8CXqpRfD1xfpbxqHWa7i+VNm5ncMTB3/a6Lri/deA2wMiLml5VNkTRH0m2SOh2bzhe6WKNa0baKcdvE0CF7Fh2KmZlZw1i5dhkrW5sYM2j8gNTXCIn6OcBPyl6vACZGxDHAJ4EfS6r6s8cXulijWt7yAmOi/8d3NTMz253c/chvAZiy35EDUl9dJ+r5qvM/A64uleWbNqzNz2cDC4GDi4nQbOAtXbWY1S1NjBk8ML/2zczMdhfzlt8LwIyDXjsg9dV1og68AZgbEUtLBZJG5lsfI+lA0hXsiwqKz2zAzXr0BmDgfu2bmZntLpY9t4ihHR0cdfBJA1JfXSTqkn4C3AVMl7RU0oV50nvYsdsLwMnAQ5IeJN3i+EMRsW7gojUr1rwVacSXY6a9ruBIzMzMGsszsZbx21poaWkdkPrqZdSXczopP79K2c+An/V3TGa1atnzi9izpYOjpvb/jRjMzMx2Fx3t7Sxr2crR7fsPWJ11kaibWc+tiHWM39ZCU3Nz0aGYmZk1jPlPP8TG5ibGDpo8YHXWRdcXM+uZ9Gt/G6O1T9GhmJmZNZTZT/wBgKmjjhmwOt2ibtZAHl88h03NTYwbPLnoUMzMzBrKglUPAPDKw04fsDqdqJs1kPvnlX7tzyw4EjMzs8ay/IWn2be5gynjDhmwOt31xayBLFqTfu2fcPibCo7EzMyssTzDRsa2Dx7QOp2omzWQZS8uYb+2DiaMmVZ0KGZmZg1j69YtLG3tYHTTwI34Ak7UzRrKSj3LuLYhRYcBgKRmSXMk/Tq/niLpHknzJV0taVAuH5xfL8jTJxcZt5mZWaX7593GliYxYdjANoQ5UTdrEC9u2czSlmB088iiQyn5OPB42euvAJdExDRgPVC6cdmFwPqImApckuczMzOrGQ8tug2AQ8efMKD1OlE3axCzHr+VrU1iwt7Fd3uRNB54C/C9/FrA60l3Cwa4EjgrPz8zvyZPPzXPb2ZmVhMWr3sMRXDCEQM34gs4UTdrGA8/+UcADp1QE3ck/Sbwd0BHfr0fsCEi2vLrpcC4/HwcsAQgT9+Y5zczM6sJK7YuZ0wb7DN8YM9aO1E3axCL1z9CcwQnHDmwv/YrSXorsCoiZpcXV5k1ejCtfL0XSZoladbq1av7IFIzM7OeWd78PGPb9xzwep2omzWIZdtWMH6bGL7XvkWH8irg7ZIWA1eRurx8ExghqXTvhvHA8vx8KTABIE8fDqyrXGlEXBoRMyNi5siRNdMP38zMGtwza5awvFWMGzx+wOt2om7WIJa2vMDY2LvoMIiIz0TE+IiYDLwHuDkizgVuAc7Os50HXJufX5dfk6ffHBE7taibmZkV4a6HfwPA1JEzBrxuJ+pmDWDB04+wtqWJ8XtMLjqUrnwK+KSkBaQ+6Jfl8suA/XL5J4FPFxSfmZnZTuYuvxuA4w45Y8Drbul+FjOrdfc+/lsADh41s+BIdhQRtwK35ueLgFdWmedF4F0DGpiZmVkPLXl+EcNbOjh08jEDXrdb1M0awPyV6brNE494S8GRmJmZNZblbGDitsE0NTcPeN1O1M0awNIXn2ZkWweTxh5cdChmZmYNY/OLz7OktYOxzaMKqd9dX8wawDI9y/i2oUWHYWZm1lDuefh3bG0Sk4YdWkj9blE3q3PrN65mWSuMGzS26FDMzMwaykOLbwdgxoGnFFK/E3WzOnfnw7+hQ2LKvkcVHYqZmVlDeWrjXAZ3BMcd/oZC6nfXF7M69+iSOwGYOa2Yg4iZmVmjWt6xiokdTQwZXEz3Ureom9W5Jc/NZ8+ODmZMf3XRoZiZmTWMjvZ2lrRsZQzF3fHbLepmdW55rGPittZCho0yMzNrVI8suo9nm5uYMOSgwmJwi7pZHdu6dQtPt7Yztmlk0aGYmZk1lFlzbwDg0HEnFhaDW9TN6tisx2/mxSYxcej0okMxMzNrKAvXPIAUvProtxYWQ120qEu6XNIqSY+UlV0saZmkB/LjzWXTPiNpgaR5kt5UTNRm/W/OwpsBOGLiqwqOxMzMrLEs27qMsW2w34jRhcVQF4k6cAVwepXySyJiRn5cDyDpMOA9wOF5mf+U5M671pAWrXuYQR3Bqwr8tW9mZtaInm55ngkdexcaQ10k6hFxO7Cuh7OfCVwVEVsi4klgAfDKfgvOrEBLO1YyaVsTew4dVnQoZmZmDeOJpx5idUsTE/c4sNA46iJR78JHJT2Uu8bsk8vGAUvK5lmay8waSlvbNha3bmW89i86FDMzs4Zy1yO/AuCwcScVGkc9J+rfBQ4CZgArgH/L5aoyb1RbgaSLJM2SNGv16tX9E6VZP7n30T+wuamJyXsfWnQoZmZmDeWJVbNQBCcfc1ahcdRtoh4RKyOiPSI6gP9he/eWpcCEslnHA8s7WcelETEzImaOHOnh7ay+zH7i9wAcc+DrC47EzMyssSzZtpTx22DkPmMLjaNuE3VJY8pevgMojQhzHfAeSYMlTQGmAfcOdHxm/W3RxkcZ3BGceNQZRYdiZmbWUJ5u3sz4GF50GPUxjrqknwCnAPtLWgp8DjhF0gxSt5bFwP8CiIhHJV0DPAa0AR+JiPYi4jbrT0s7VjGpo5khg4cWHYqZmVnDeHzRbNa2NDFp8NSiQ6mPRD0izqlSfFkX838J+FL/RWRWrK1bt/BU6zZObBvT/cxmZmbWY3c9+msAjhhf/D1K6rbri9nu7J5HbuCFpiamDD+s6FDMzMwayvzVs2mK4ORj3lF0KPXRom5mO5q94A8AvGLqGwqOxMzMrLEs2baMCU1in+HFDzTiFnWzOvTkxsfYo6OD4494U9GhmJmZNYyO9naean2R8TGi6FAAt6ib1aWlsZpJ21oZNGhw0aGYmZk1jEcW3sOG5iYmD55WdCiAW9TN6s6LWzbzVGs745sOKDoUMzOzhnL3478B4MhJJxccSeIWdbM6c+eD17OlSRw47IiiQzEzM2soC9Y8QEtz8OoZby86FMCJulndmbPoJgBeMe20giMxMzNrLEvaVzChQwzfa9+iQwHc9cWs7ix89jGGtXfwysM94ouZmVlfaWvbxpOtW5jI/kWH8hIn6mZ15mmtY8q2IbS0tBYdipmZWcO466Hf8nxTE1OH107XUifqZnVk5dplPN0aTBo0sehQzMzMGsp9838HwCunv7ngSLZzH3WzOnLL7GsIicNGnVB0KGZmZg1l4bOPMqy5trqWukXdrI48uvxOAF57zLsKjsTMzKyxPEXtdS11om5WR57aupjx24IJow8sOhQzK9iGDRs4++yzOeSQQwAOl3SipH0l3Shpfv67D4CSb0laIOkhSceW1iPpvDz/fEnnlZW/QtLDeZlvSVIur1qHWT0rdS2dOGhC0aHswIm6WZ3oaG/nyZbNTOrwd6KZwcc//nFOP/105s6dC/AY8DjwaeCmiJgG3JRfA5wBTMuPi4DvQkq6gc8BxwOvBD5Xlnh/N89bWu70XN5ZHWZ1q1a7ljpRN6sT98/9Ixuamzhwr0OKDsXMCvbss89y++23c+GFF5aKIiI2AGcCV+ayK4Gz8vMzge9HcjcwQtIY4E3AjRGxLiLWAzcCp+dpe0fEXRERwPcr1lWtDrO6Vepaesox7yw4kh35YlKzOnHX49cBcOxBbyw4EjMr2qJFixg5ciQXXHABDz74IMAkSXsCoyJiBUBErJB0QF5kHLCkbBVLc1lX5UurlNNFHWZ166mtixnfFEwYM63oUHbgFnWzOrFw/UPs0dHBq2e8pehQzKxgbW1t3H///Xz4wx9mzpw5AB103QVFVcpiF8p7TNJFkmZJmrV69ereLGo2oDra21ncsplJHSOKDmUnTtTN6sTTsYop2wYxZPDQokMxs4KNHz+e8ePHc/zxx5eK1gPHAitztxXy31V5+lKg/Cq58cDybsrHVymnizp2EBGXRsTMiJg5cuTIXdpOs4HwwLw7WN/cxJQa7FrqRN2sDmx8bh1PDupgYvPYokMxsxowevRoJkyYwLx580pFe5MuKL0OKI3cch5wbX5+HfD+PPrLCcDG3H3lBuCNkvbJF5G+EbghT9sk6YQ82sv7K9ZVrQ6zunTn478C4NgDTys4kp25j7pZHbh19s9pk5g+8hVFh2JmNeI//uM/OPfcc9m6dSvAHsCXSQ1w10i6EHgaKN104XrgzcACYDNwAUBErJP0BeC+PN8/R8S6/PzDwBV53b/ND4B/7aQOs7q0YN0DDGkJXnPM24oOZSdO1M3qwINP3QzAyUf/WcGRmFmtmDFjBrNmzQJA0sI8agvAqZXz5pFbPlJtPRFxOXB5lfJZwBFVytdWq8OsXi1mFVO2tdRk11J3fTGrAwtfmM/YbcHBk2YUHYqZmVnDWL1+OYtbO5jSUls3Oipxom5W4zra21nYupkpvtGRmZlZn7rpvqtolzhi9KuKDqUqd30xq3F3PnwDG5ubOHjPI4sOxczMrKE8uOx2mhSc9spziw6lKifqZjXu7rnpRkcnHvr2giMxMzNrLIu3PcUkidH7u+vLLpN0uaRVkh4pK/uapLmSHpL0C0kjcvlkSS9IeiA//qu4yM1evgXPPsKI9g6OP7z2ho0yMzOrV5tffJ6FrVuZQu3eXLcuEnXS8FCnV5TdCBwREUcBTwCfKZu2MCJm5MeHBihGs36xqGkDB23bk6bm5qJDMTMzaxi3zf45LzQ1MX2/2h36uC4S9Yi4HVhXUfb7iGjLL+9mxzuomTWEeU/OYUWrOHDotKJDMTMzayizF/0egJOPemfBkXSuLhL1HvgA22/EADBF0hxJt0l6TVFBmb1cNz9wDQCvmFI/3V4kDZF0r6QHJT0q6fO5fIqkeyTNl3S1pEG5fHB+vSBPn1xk/GZmtntYuPkJRm3r4IipxxcdSqfqPlGX9PdAG/CjXLQCmBgRxwCfBH4sae9Olr1I0ixJs1avXj0wAZv1wrw19zGkI3jdzLq68d8W4PURcTQwAzg937L8K8AlETENWA9cmOe/EFgfEVOBS/J8ZmZm/aajvZ2FLc9xYMeIokPpUl0n6pLOA94KnJvvukZEbMl3TSMiZgMLgYOrLR8Rl0bEzIiYOXLkyIEK26zHnmQlB21rZeiQPYsOpccieS6/bM2PAF4P/DSXXwmclZ+fmV+Tp58qSQMUrpmZ7YZmPXYL61uamDrs8KJD6VLdJuqSTgc+Bbw9IjaXlY+U1JyfHwhMAxYVE6XZrlu5dhmLW4MprROLDqXXJDVLegBYRbrweyGwoey6kqXAuPx8HLAEIE/fCOw3sBGbmdnu5I7HfgnAidPfWnAkXauLRF3ST4C7gOmSlkq6EPg2MAy4sWIYxpOBhyQ9SGqd+1BErKu6YrMa9of7fkSHxJFjX110KL0WEe0RMYN0kfcrgUOrzZb/Vms9j8oCd1UzM7O+Mn/jg+zd3sGJR51RdChdqosbHkXEOVWKL+tk3p8BP+vfiMz634PLbqO5OTh15nuLDmWXRcQGSbcCJwAjJLXkVvPxwPI821JgArBUUgswnIpRnvK6LgUuBZg5c+ZOibyZmVlPLWxaz0HbhtLS0lp0KF2qixZ1s93RwvalHLS1mVH7jet+5hqSu5+VbkC2B/AG4HHgFuDsPNt5wLX5+XX5NXn6zaVrTszMzPraQ0/cyYpWcfDQQ4oOpVt10aJutrtZvX45iwa1c1r7pKJD2RVjgCvztSJNwDUR8WtJjwFXSfoiMIftZ8UuA34gaQGpJf09RQRtZma7h5sfuAqAEw5+e8GRdK+wRF1SE7BXRDxbVAxmtep3d32fNokZ408pOpRei4iHgGOqlC8i9VevLH8RqKvxJ83MrH7N3TCH4S0dnPKKs7qfuWAD2vVF0o8l7S1pT+AxYJ6kvx3IGMzqwYMrbqMlgjNOOL/oUMzMzBrKgqZ1TNu2V833T4eB76N+WG5BPwu4HpgI/MUAx2BW8xa1L2Pq1hb2Ge7x/c3MzPrK/Y/dxsrWJg7eq9pgZLVnoBP1VkmtpET92ojYRpVh2Mx2Z8+sWcKiQR1Mbam/8dPNzMxq2a0PXw3ASYe8o+BIemagE/X/BhYDewK3S5oEuI+6WZnf3XMF7RJHj39d0aGYmZk1lLkbH2REewevmVHbNzoqGdBEPSK+FRHjIuLN+TbjTwHORszKPLziDlojOP1E9wozMzPrKx3t7cxv3sC0bcNoam4uOpweGeiLSUdJukzSb/Prw9g+frKZAQtiOVO3tjBi2P5Fh2JmZtYw7n3sJta0NHHwsMOLDqXHBrrryxXADcDY/PoJ4BMDHINZzVq6ajFPtgZTW6cUHYqZmVlD+eMj6cb1rz7snQVH0nMDnajvHxHXAB0A+Vbi7QMcg1nN+v09VxISx058Q9GhmJmZNZR5zz7Evm0dnHTkm4oOpccGOlF/XtJ+5JFeJJ0AbBzgGMxq1oPP3M6QjuBNJ5xbdChmZmYNo61tG/Nan+Xg9uF10z8dBv7OpJ8ErgMOkvQnYCRw9gDHYFaz5mkl07cOYdieI4oOxczMrGHcfN9P2dDcxOF7zSw6lF4Z0EQ9Iu6X9FpgOiBgXh5L3Wy3d//cP7KsVbx68GFFh2JmZtZQ/vTELwE447gLCo6kdwY0UZf0/oqiYyUREd8fyDjMatFNc34IwClHvLvgSMzMzBrLE1ueYJJg+pRjig6lVwa668txZc+HAKcC9wNO1G239/imBxjZ3MFJR51RdChmZmYNY/3G1cwbtI3XtY0rOpReG+iuL/+7/LWk4cAPBjIGs1q0desW5rY8x1Ft+9bVRS5mZma17td/uoxtEseOP7XoUHptoFvUK20GphUcg1nhbrz3J2xqbuLIEScUHYqZmVlDuX/5zQxqDt7yqg8UHUqvDXQf9V+Rh2YkDQ15GHDNQMZgVovumv8rpODNx19YdChmZmYN5YlYwfStg+ryjt8D3aL+9bLnbcBTEbF0gGMwqznzti3kQJqYMu6QokMxMzNrGI8unMXTg+BsTS86lF0y0H3UbxvI+szqwTNrlrBgUBuntU8qOhQzM7OGcuPsKwF4zSHvLDiSXTMgibqkTWzv8rLDJCAiYu+BiMOsFv36zu/RJjFzYv3c0tjMzKwePLJ+Fvu0dHDKK95RdCi7ZEAS9YgYNhD1mNWjOc/cxtDWDs44qfI2A2ZmZrartm7dwuOtz3JE2z51O6JaIaO+SDqANI46ABHxdBFxmBWto72dx5tXc+jWPRm254iiwzEzM2sY1//pCp5tbmLGiFcVHcouaxrIyiS9XdJ84EngNmAx8NuBjMGsltw86+esbmniqBEziw7FzMysody56DqaI3jbqz9cdCi7bEATdeALwAnAExExhXRn0j91t5CkyyWtkvRIWdm+km6UND//3SeXS9K3JC2Q9JCkY/trY8xertseT6OTvvWEiwqOxMzMrLE81vE007e2Mv6AyUWHsssGOlHfFhFrgSZJTRFxCzCjB8tdAZxeUfZp4KaImAbclF8DnEG6idI04CLgu30RuFl/eHzrExy0RRw8qSe7wf9n777DpCrPN45/n5ktSJHei0DEAqKAiNgLiGg0WBIjNowmxphi1F+MNUYTYzSWaIw1YknsHZaUM3kAACAASURBVJWoWIgVEBApgoBIWUBAcWEB2TbP749z0GHd3s7M7P25rrmYec8579w77Dv7zJlz3iMiIiLVMXvheyzLgf7N0nva48Yu1PPNrCXwNvCwmd1KMJ96pdz9LWB9meYxwIPh/QeB45LaH/LAFKCNmXWtl/Qi9eizlQtYmFPK7tl9o44iIiKSUf47fTwAIwaeGnGSummUQt3MbjezAwiK6C3Ab4GXgU+BY2vZbWd3Xw0Q/tspbO8OrEhaLy9sE0kpL7x3F27GQf1OiDqKiIhIRplbMIsuxc7+ex4VdZQ6aaxZXxYRXJW0K/A48Ki7P1j5JrVm5bSVN4c7ZnYOweEx9OrVq4HiiJRv9ldTaRtPMGr42KijiIiIZIz8gi+Yn7OVA0o6p+20jNs0yh51d7/V3fcDDiE4hOV+M5tvZlea2S617HbNtkNawn/Xhu15QM+k9XoAqyrIdY+7D3X3oR07dqxlDJGa21q4hY+zNtK/tB1ZWdlRxxEREckYz791N4UxY2j3I6KOUmeNeoy6uy9z9+vdfTBwCnACML+W3U0AxoX3xwHPJ7WfEc7+MhzYsO0QGZFU8eI791MQjzG400FRRxEREckoM1a9TrOE84OD039GtcaeRz3bzI41s4cJ5k9fCJxYje0eBd4HdjWzPDM7G/grcEQ4L/sR4WOAicASYDFwL3Be/f8kInXz/mcTyHJnTBrP7SoiIpJqEqWlzI2tYfeiHWjdsl3UceqsUY5RN7MjgLHA94FpwGPAOe6+uTrbu3tFB/GOKGddB35Zy6giDS5RWsocVtK/MJcuHXpWvYGIiIhUy8vvP8y6rBjHtNw36ij1orFOJr0MeAT4P3cvO82iSJMyecazrM42RrbYO+ooIiIiGWXyJ48TjzsnHvSbqKPUi0Yp1N39sMZ4HpF08Nq8hzFzjtv/V1FHERERyShzfBm7FWWzU7fazlWSWhr7gkciTd6cksXsUhRnl532jDqKiIhIxnhn1kTyso2BzfeKOkq9UaEu0oimz5vM0hzYc4c9oo4iIiKSUV796H4Ajt333IiT1J/GOkZdRICJM+4B4Ji903/KKBERkVQyp/ATdsbYs9/wqKPUG+1RF2lEs7fOo3cRDOl/SNRRRCQDlJaWMnjwYICdAcysj5lNNbNFZva4meWE7bnh48Xh8t7b+jCzS8P2T8zsyKT20WHbYjO7JKm93OcQidLcxVNZnOsMzN016ij1SoW6SCNZuGw2C3NKGZi1c9RRRCRD3Hrrrey+++7JTdcDt7h7P+Ar4Oyw/WzgK3ffGbglXA8z6w+cDAwARgN3mFnczOLAP4GjgP7A2HDdyp5DJDIvTL0TgFF7/STiJPVLhbpII3nuvdtxM0YOODXqKCKSAfLy8njppZf46U9/CoCZGXA48FS4yoPAceH9MeFjwuUjwvXHAI+5e6G7f0ZwscBh4W2xuy9x9yKC65+MqeI5RCLz0eaP6FHsHDjo6Kij1CsV6iKNZGbBB3Qrdg7d+/ioo4hIBvjtb3/LDTfcQCz2zZ/y9kC+u5eEj/OA7uH97sAKgHD5hnD9b9rLbFNRe2XPIRKJhctmMz+nmL1ifaOOUu9UqIs0goXLZjE/p5ghsb7E4vGo44hImnvxxRfp1KkTe++93YXTrJxVvYpl9dX+HWZ2jplNN7Pp69atK28VkXrx9Du3kDDjqL0y7ygszfoi0giefufvJMwYnYFvIiLS+N59910mTJjAxIkT2bp1K0Ar4O9AGzPLCvd49wBWhZvkAT2BPDPLAloD65Pat0neprz2Lyp5ju24+z3APQBDhw4tt5gXqQ8zN39IL4ND9h4TdZR6pz3qIo1g5uZZ7FSUmW8iItL4rrvuOvLy8li6dCmPPfYYQIG7nwq8CfwwXG0c8Hx4f0L4mHD5G+7uYfvJ4awwfYB+wDTgA6BfOMNLDsEJpxPCbSp6DpFGN3fxVBbkljI4KzOuRFqWCnWRBjZ70RQW5JYyKEPfREQkpfweuNDMFhMcT35f2H4f0D5svxC4BMDd5wFPAB8DLwO/dPfScG/5r4BXgPnAE+G6lT2HSKN75v3bADhm6M8jTtIwdOiLSAN7bso/gMx9ExGRaB166KEQzNaCuy8hmLFlO+6+FfhRedu7+7XAteW0TwQmltNe7nOIRGHW13PoazB84KioozQI7VEXaWCzvp5D36LMfRMRERGJwsyP/8eiXGdwzoCoozQYFeoiDWj6vMksynWG5Gbum4iIiEgUnvvgnwD8YN9fRpyk4ahQF2lAE6YHbyJj9v1VxEkaj5n1NLM3zWy+mc0zs/PD9nZmNim87PgkM2sbtpuZ3RZepny2mQ2J9icQEZF08GHRfHYpjDFkt4OijtJgVKiLNJBEaSnTi+aza2GMQbseGHWcxlQCXOTuuwPDgV+Glx6/BHg9vOz46+FjCC5R3i+8nQPc2fiRRUQknbwx7SmW5sCQ5oOjjtKgVKiLNJCX33+YFTnGvq2GRx2lUbn7anefGd4vIJgxojvbX8K87KXNH/LAFII5mrs2cmwREUkjL82+lyx3TjnskqpXTmMq1EUayCvzHyQn4YwdcWnUUSJjZr2BwcBUoLO7r4agmAc6hatVdKlyERGR79hauIXplsdehc3p0323qOM0KBXqIg1g85YCZsQ/Z1BxK3p06h11nEiYWUvgaeC37r6xslXLafvOVQx1OXIREQF48vXbWJ8VY/8uR0YdpcGpUBdpAI++9jc2xGMc3P2YqKNEwsyyCYr0h939mbB5zbZDWsJ/14btlV3C/Bvufo+7D3X3oR07dmy48CIiktL+l/c8O5YmGDvyoqijNDgV6iIN4J3VL9O2NMGPR14QdZRGZ2ZGcKXC+e5+c9Ki5EuYl720+Rnh7C/DgQ3bDpERERFJtmrdMmZlF7B3aWdatWgTdZwGpyuTitSzZasW8lHuFg4t6U6z3OZRx4nCAcDpwBwzmxW2XQb8FXjCzM4GlvPtVRInAkcTXFlxC/CTxo0rIiLp4tHX/0phzDhy9zOijtIoVKiL1LNH3ryOEjOO3uPsqKNEwt3fofzjzgFGlLO+A5l7tQoREak3Uza+T4+Yc9R+p0cdpVGkdaFuZrsCjyc19QX+ALQBfgZsO+PsMnef2MjxpImasmU6vYEjhv846igiIiIZ4/3ZL7Mgt5Tj6U8sHo86TqNI60Ld3T8BBgGYWRxYCTxL8NX5Le5+Y4TxpAl6+b2HWZIDp2QNjTqKiIhIRnl62q1kZTmnHXZZ1FEaTSadTDoC+NTdl0UdRJquF+beS27COf2Iq6KOIiIikjEKNuczJbacQYUt2GWnQVHHaTSZVKifDDya9PhXZjbbzMabWduoQknTsebLlUzPXsfQ4rZNdu50ERGRhvCfV65jQzzGiF4nRB2lUWVEoW5mOcAPgCfDpjuB7xEcFrMauKmC7XQBFak3D716DVtiMY7adVzVK4uIiEi1vfXFq3QuTnDyERdGHaVRZUShDhwFzHT3NQDuvsbdS909AdwLDCtvI11ARerTewXvs1MRHHugZhcUERGpLx/Me525uSUMz9qNrKzsqOM0qkwp1MeSdNjLtqsfho4H5jZ6ImlSXn3/URbnOvvtMKTJnIkuIiLSGJ6YcjNxd049uOmcRLpNWs/6AmBmzYEjgJ8nNd9gZoMAB5aWWSZS7ybMvYfcLOeMUVdEHUVERCRjbN5SwFSWsldhc3bvu3fUcRpd2hfq7r4FaF+mrWnMgi8pIW/tUqZlrWVocVt6du0XdRwREZGMMX7iVXyVFeNnXU+MOkok0r5QF4na/a9cwdexGMcPPC/qKCIiIhnlzfWv0SPmjB11UdRRIpEpx6iLRKKoqJC3C2exW2GcI/c7Jeo4IiIiGeOFt8azKNc5eIehTe4k0m1UqIvUwX9euZ7V2cbhHY+KOoqIiEhGmbDgXzRPJDhr9LVRR4mMCnWROpi0+jk6lCQYd5ROIhUREakvC5fNYnrORvYr7Ubn9t2jjhMZFeoitfT2zAnMzS3mwHh/mjdrEXUcERGRjPHAG1dTYsbJ+/4u6iiRUqEuUkuPz7iFnITzkxF/jDqKiIhIxijYnM87iYXstTWX4QNHRR0nUirURWphyYp5TMlax7DitvTtOSDqOCIiIhnj3hcv46usGEftdFLUUSKn6RlFauHe1y6jMGacOuzSqKOIiIhkjJKSYiYVvEUfN8Ye0TSnZEymPeoiNfRl/ue85YsZsrUZBw46Ouo4IiIiGeOBiX8mL9sY1e5IYvF41HEipz3qIjV014u/Z2M8xgnf+3nUUURERDLKy58/R+dYgp8ec03UUVKC9qiL1MCWrZt5o3A6uxXGGXPIT6OOIyIikjGeffMuPslNMGKHfWiW2zzqOClBhbpIDdz3whWszYpxdLcTo44iIiKSUZ5ddB+tSxOce8zfoo6SMlSoi1RTSUkxr+S/Rs8i5/TRl0QdR0REJGNMnv4sH+Zu5WDbhbatO0YdJ2WoUBeppvEv/ZFlOTC6zUiysrKjjiMiIpIx/j3jeponEvz8yOujjpJSVKiLVENJSTEvrJ1A92Ln3DF6ExEREakvk6c/ywe5mzjU+7JTt12ijpNSVKiLVMP4l/7I0hz4fusjyMnJjTqOiIhIxvj3jOvZwZ3zRt8UdZSUo0JdpArJe9N/PuavUccRERHJGNqbXjkV6iJV0N50ERGRhvGQ9qZXSoW6SCW0N11ERKRhvPnB03zQbLP2pldChbpIJe587vfB3vQ2o7Q3XUREpB7d/+FfaZFIaG96JVSoi1SgYHM+z+e/Qp8i+MVxmulFRESkvjz9xh18mLuVUbH+2pteCRXqIhW49ZnfsCY7xo97nq5500VEROpJorSURxbfTfuSBBccd0fUcVKaCnWRcqxat4yXi2ewR2E2p46+OOo4IiIiGeNfL/6RhbkJjmlxkK5CWgUV6iLl+PsLv2RDPMa4PS6KOoqIiEjG2Fq4hWfXPUuPYudXx98cdZyUp0JdpIx5n07nDVvKvoUtGb3/qVHHERERyRi3PX0+ednGiZ1OoFlu86jjpLysqAPUlZktBQqAUqDE3YeaWTvgcaA3sBQ4yd2/iiqjpJdbXz+fRA6ce8B1UUcRERHJGHlrlzJh63vsVpLNWd+/Kuo4aSFT9qgf5u6D3H1o+PgS4HV37we8Hj4WqdJzb97N+7kbGZnozdABh0YdR0REJGPcOOFnFMSMc/a8lFg8HnWctJAphXpZY4AHw/sPAsdFmEXSRFFRIfcvvp0OJQl+d/w9UccRERHJGP+b8TyTs1ZzUHFHjhj+46jjpI1MKNQdeNXMZpjZOWFbZ3dfDRD+2ymydJI2bnvmfJbkwIltjqJj225RxxEREckIidJS7prxR5onnIuOvjPqOGkl7Y9RBw5w91Vm1gmYZGYLqrthWNifA9CrV6+GyidpIG/tUp7b8ja7lWRz3mm6uJGIiEh9+deLf2BubgmnZA2jT/fdoo6TVtJ+j7q7rwr/XQs8CwwD1phZV4Dw37UVbHuPuw9196EdO2oez6bshufPYmPM+NnA3+u4ORERkXqy7qtVPPbFc+xUBBf88J9Rx0k7aV2om1kLM2u17T4wCpgLTADGhauNA56PJqGkg+cn38Pk7LUcXtKVUfuNjTqOiIhIxvjL02fyRdz4Wb9fazrGWkjrQh3oDLxjZh8B04CX3P1l4K/AEWa2CDgifCzyHZu3FHD3otvoWOpcfuKDVW8gIpICVqxYwWGHHcbuu+/OgAEDIDwXy8zamdkkM1sU/ts2bDczu83MFpvZbDMbsq0vMxsXrr/IzMYlte9tZnPCbW4zM6vsOUTKmvjOQ7yRtYpDizsx5tBzqt5AviOtC3V3X+Lue4W3Ae5+bdj+pbuPcPd+4b/ro84qqem6x89kRY5xepeTdQKpiKSNrKwsbrrpJubPn8+UKVMAOplZfyqenvgooF94Owe4E4KiG7gK2Jfg0NGrkgrvO8N1t203OmzXFMhSpS1bN3Pn/L/RttS55Lj7o46TttK6UBepi/c++i8T7ROGFbbkzO9fGXUcEZFq69q1K0OGBDvFW7VqBfA10J2KpyceAzzkgSlAm/AcriOBSe6+Prww4CRgdLhsR3d/390deKhMX5oCWSp1w+NnszQHTut4It067hR1nLSlQl2apKKiQm6eegnNEs7vj9RUUSKSvpYuXQrQHJhKxdMTdwdWJG2WF7ZV1p5XTjuVPIcIEOwIezExl7237sBPf3BN1HHSmgp1aZKue2wcn+Qm+HGrkeyy06Co44iI1MqmTZs48cQTAVa4+8ZKVrVy2rwW7dVmZueY2XQzm75u3bqabCppbGvhFm6c+nty3bl01N1Rx0l7KtSlyXnzg6d5PjGXoVub8+sTbo46TkYys/FmttbM5ia11fgkNxGpWHFxMSeeeCKnnnoqQH7YXNH0xHlAz6TNewCrqmjvUU57Zc+xHU2B3DT9+ZHTWZTrnNb2B+zaZ3DUcdKeCnVpUjZvKeDmWX+kZcK58ujxmjO94TzAtyeebVOjk9xEpGLuztlnn83uu+/OhRdemLyooumJJwBnhB+MhwMbwsNWXgFGmVnb8MPzKOCVcFmBmQ0PZ3s5o0xfmgJZvuOV9x/hJfuEfbe25BfHXxd1nIyQCVcmFam2ax47haU5cEG7k+jbc0DUcTKWu79lZr3LNI8BDg3vPwhMBn5P0kluwBQza2NmXbcdAysi3/Xuu+/y73//m4EDBzJo0CCA/mZ2NMF0xE+Y2dnAcuBH4SYTgaOBxcAW4CcA7r7ezP4EfBCud03STGm/IPjQvQPw3/BGJc8hTdiGTeu5de5faB1zrvrBQ1HHyRgq1KXJeGLSbbwc+4wDCtty1rFXRR2nKdruBDQzq+okNxXqIhU48MADCT7bBszsY3efGD4cUXb98IPwL8vry93HA+PLaZ8O7FFO+5flPYc0bVc++kNW5BgXdzyNnl37RR0nY+jQF2kSFi+fyx3L76ZbCfzpR49HHUe2V62T1nRimohIarr72Ut5M2cdo4q7cfrRmla/PqlQl4xXUlLMH14+g00x4+K9rtaFjaJT05PctqMT00REUs/0eZO5P38C/QqNP532TNRxMo4Kdcl4V//nFObkFvPjZgdw2D4nRh2nKavpSW4iIpLCCjbn8+f3fkPM4YqD/0nzZi2ijpRxdIy6ZLQnJt3GBOaz79ZWXHTaHVHHaTLM7FGCE0c7mFkewSXKa3SSm4iIpLYrHjmRT3Oc89ueyJDdDoo6TkZSoS4Za+aCt7ltxd10LzWu/eFTmoqxEbn72AoW1egkNxERSU03P34eb+SsZVRxN119tAHp0BfJSF/mf85Vb59HKXDlvjfSuX33KrcRERGRqk146z7+8/VbDNyazbWnPxt1nIymQl0yTqK0lIufOJ5l2c55XU5nvz3LXndHREREamP+khncvOhmOpTA9T94nGa5zaOOlNFUqEvG+cO/T2Ja7iaOtwGaJkpERKSefLVhHZe/9hO2xOCyQX/SfOmNQIW6ZJR/PHkBz9tChhe24qrTHok6joiISEYoKirkgse+z+KcBOe0P5FDhx4fdaQmQYW6ZIzHXr2F8Zsn0b8wi5tPnaiTR0VEROpBorSU3z14NDOafc2Ps/bWyaONSIW6ZITJ05/l7yv/Rbdi46bjnqVVizZRRxIREckIf3r4tG9meLn8tAejjtOkqFCXtDfrk3e45qMraJaA6w65mx6dekcdSUREJCP848kLeMrnMmxrC64/88Wo4zQ5KtQlrc1fMoOL3z6XrQZX7PFH9txl/6gjiYiIZIR7nr+c+5IOKc3Kyo46UpOjQl3S1uLlc7nwjXFsiDuX7nwRI/f9UdUbiYiISJUefOla7vzqeb5XFOe2E1+kdct2UUdqklSoS1pasXoRF7wylnVx+F2v8zj24LOijiQiIpIRHnv1Fv6x9lF6FRu3Hve8LhoYIRXqknY+W7mAX714AiuznQu7jeOHI3T1eRERkfrwyCs3cdPK++hcYvz96Cd13lfEsqIOIFITn3z2IRe8djprs+C3nU7hlCN/F3UkERGRjDD+hWu4/csn6F5i3DTqYfp03y3qSE2eCnVJG7M+eYeL3z6X/Czn4h4/56QjfhN1JBERkYxwxzMXc+/GifQuinHbsU/rqqMpIq0PfTGznmb2ppnNN7N5ZnZ+2P5HM1tpZrPC29FRZ5W6eefDF7nonZ9TEHOu+N6FKtJFRETqyY2PncvdGyeyc1EWd57wkor0FJLue9RLgIvcfaaZtQJmmNmkcNkt7n5jhNmknjz52u3csvxOsoCrd7+CUfuNjTqSiIhI2kuUlnLpg8cxMb6UPQtzuf3kl2nbumPUsSRJWhfq7r4aWB3eLzCz+YBOTc4g/3jqQu7f9CqdE8a1B97JkN0OijqSiIhI2ivYnM+FDx/NlNwCDipsx43jJtK8WYuoY0kZaX3oSzIz6w0MBqaGTb8ys9lmNt7M2kYWTGolUVrKlQ/8iHs2T2LnoizuOWaCinQREZF6sGL1In768GFMyS3gON+N289+Q0V6isqIQt3MWgJPA791943AncD3gEEEe9xvqmC7c8xsuplNX7duXaPllcqt+2oVP/3XATxnCxhe2Ir7Tp1Mzy59o44lIiKS9l6b+iRnvXQ8i3KK+VnzEfzpzCeJxeNRx5IKpPWhLwBmlk1QpD/s7s8AuPuapOX3Ai+Wt6273wPcAzB06FBv+LRSlWlzXuPqKReQl+v80PbgyrMf1huIiIhIPfjHUxfyYMGrtDLn6r4X6WKBaSCtC3UzM+A+YL6735zU3jU8fh3geGBuFPmkZu5/8U/cs/YxYnH4fdezOOXIi6KOJCIikvY2byngikdO5LXs1exWnMW1Rz7ELjvtGXUsqYa0LtSBA4DTgTlmNitsuwwYa2aDAAeWAj+PJp5Ux4ZN67nq0ZN4PWcNfUtjXHXQHToeXUREpB5Mm/Maf5lyIZ/mOIcXdea6M57X8ehpJK0LdXd/B7ByFk1s7CxSO+98+CLXT7+UpTkwoqgzV499gtYt20UdS0REJO3d+uT5PLLpNeJx+HWb4zhnzLVRR5IaSutCXdJXSUkxNz5xLk8VTqVZ3Lmow8mc+f0ro44lIiKS9lasXsQ1L4xjSm4Buxdnc8Vhd7Fnv+FRx5JaUKEujW7anNe48f3/Y35uKQOLcrhq1H3s2mdw1LFERETS3t3PXcbDXz5PQY7xg8QuXHXmo+Tk5EYdS2pJhbo0mqKiQq5//GyeL5lFdpZzZu7BXHDa7ZrVRUREpI4WLpvNX1/5GR/kbqFvIsYf9vgDI/f9UdSxpI5UqEujeOGt8dz3yd/5NMcZVNSMS0bexYDvDY06loiISForKirk5qfOY8LWKWzNMY6nP5ed8QDNcptHHU3qgQp1aVCLl8/lxpd/wbu5+bSPJfh5y6M477TrtRddRESkjp57827GL76dz3JgQEkOv9rnTxw4+JioY0k9UqEuDaJgcz63PvNrXiqeydYc48jinvzu+H/RuX33qKOJiIiktdmLpnD7mxfxfu5GOsYSnNfqGH5+2l+0EywDqVCXelVUVMgdz/2OFze+zprsGANLcjlv2J85cNDRUUcTERFJa8tWLeS2ib9mcnwlngNHlfbm9yf+i/ZtukQdTRqICnWpF4nSUh6YeC3PfP4ky3Kgr8e4tMsZnDzyQn3CFxERqYN1X63i1ud+zWss4OssY7+itpx7yHUM2vXAqKNJA1OhLnVSVFTI/S/9kYlfvMiSHOhmznk7HsvPjr2GrKzsqOOJiIikrRWrF3HXyxcz2ReyMR5j760t+MnQyzlk7zFRR5NGokJdamXzlgLufuESXi34HyuzjW7m/KTZwZz747/p0sQiIiJ18MlnH3Lv65fxdnw5W2IxBhc250c7/4JjDz4r6mjSyFSoS40sXj6XB964indLF/BFVozebpzX6mjOPuYaXVBBRESkDl5+72Gem3snH2TnU5IF+xTuyCmDL+LwYT+MOppERIW6VMvEdx7iuY/vZnrOBorN2KM0l3FdjueM0ZfpGHQREZFa2rylgPETr2Ly+tdZmJtgh+wE+5d04vThlzNs4Mio40nEVKhLhZatWsgjb17H1M0z+DTXaZ6d4MDizpw09ELN0yoiIlIHk6c/ywuz7uKDWB5fxWN0izk/jg3hzKOuoUen3lHHkxShQl22s7VwC4+9dhNvrXyRWTmbKTajj8HJ8b05+/t/okuHnlFHFBERSUvBDrC/MHXzTD7NdbKynD0Lm/OzLicydtRFmoRBvkOFurC1cAvPTP4n7y57idlZ68iPx2idleCQku4cvcfZHDH8x1FHFBERSUsrVi/iybduYWb+VOblFlJiRl+Dk+NDGHvIxfTtOSDqiJLCVKg3UQWb83nuf3fxft5EZmd9yYZ4jB2yEwws3pH9OhzB2JG/o0XzVlHHFBERSTsLl81mwvt3MHPjNObnFFFiRud4gsNLenLUwLMZue+Poo4oaUKFehMyc8HbvDrzAT7eNJv52V+zNWY0z06wZ3Fr9u0wkh8e9hvatOoQdUwREZG0UlRUyH/f/zdTPp3A/JKlfJrrAHSNOSNLezFi91MZte/JmnxBakyFegZb8fkSJn3wb+aseZdPfBUrcgyALjFnv5JODOl2GMcf8ktat2wXcVIREZH0kSgtZfrHb/LWvKdYsOEj5mdvZGM8Rizm9CPOGO/HIbudxIh9fqjiXOpEhXoGWbZqIZOm/4d5a6fwqa9mabbjZuTEnV2Lctgv1p8Re57K8D1G6Y1DRESkmhKlpUydN4m35z3DooK5LIpv4MusGABtsxLsUdKWvdrsz7H7/YyeXftFnFYyiQr1NFWwOZ/JM55h9vK3WLZlEctjG1iZHewxz407Oxdnc6z3YXDPERyx71jtNRcREammz1Yu4O2PnmH+mmmsKFrB0uytbIgHhXm7eIJ+pTty1A4DOKD/b4r5uwAAIABJREFUCew/8Ejt/JIGo0I9Daxat4xpc19mwepp5G1ewkr/kqU5CUosKMzbxxP0LmnBsOydGNxrBCOHnUyrFm0iTi0iIpLaEqWlzF3yATMXTmLJF3NYWbiCFbECVoc7vsycXjFjYEk7+u7QnwMHHM++A45QYS6NRoV6Clnz5UpmLfwfi1d/yLL8+XxesoZVsS2syY59s07LeIJeJTmMLO1Bvw6D2X/AD9hj530jTC0iIpLaEqWlLFo+mzlL3mPJmlnkbf6U1b6elVnFFMS//RvbKZ6gV0lL9s/uw4DuB3Lw4OPp3L57hMmlqVOh3si+zP+cuZ9OZdHKmazM/4Q1W1fzBRtYGy/+5ng3gHjM6W5G79Id2T+7B3077MmQXY5gj7776JO8iIhIGYnSUpasnM/8pdP4bM1sVhcsYV3JOtbZJj7PSrAl9u3f2OZZCXoWZzGktBM9mvVl1677sM+A0boiqKQcFer1qKSkmCUr5/Np3kcsXzeftQXL+bJwDfmlG/gq9jVfxBNsTPrkDtAmK0Hnkix2K21Hp6wudG/dj37dhrDPgJE6fEVERCRUsDmfRSvmsGTlbFauX8i6TXmsL/6CfC/gq3gR6+JQGLNv1o/FnM4x6Fiay34lbencvAe92vdn9977Majf/trpJWlBhXo1zfz4fyxfs4A1+UtZv2U1+YVfsrEknwL/moJYIRtiCfLjRqnZdts1jyfo4DHaJnLoyY60i3ekY4se9O2yJ3vufDA9u/SN6CcSERGJXsHmfGYu+B8rv1jMFxtX8NXXa9hQtJ6CRAEFfM1GKyY/7tsdogJADNrGE7QvjdM10YL+tKFddhe6tu7LLj32Zq9dDtQOL0l7GVuom9lo4FYgDvzL3f9al/4uee+X35xcAsGhKW3iTutEjB0TuXT35uxobWid256OrXqxU6f+7LbTELp36qtP7SLVUN9jVkQaTn2O13dmvcDFi2/Yri037rQDdkzE6ZxoQT9a0irWhrbNOtG1bV/6dB3I7n2G6iJ9kvEyslA3szjwT+AIIA/4wMwmuPvHte3z1K5jicey6Nb+e/Tqshu9u+1KVlZ2fUUWadIaYsyKSMOo7/E6eNdD+cWaOXRqvRPdO36Pvt0H0rFNF+3kEiFDC3VgGLDY3ZcAmNljwBig1n/0x33/8nqKJiLlqPcxKyINpl7Ha5cOPTnvhBuqXlGkCYpVvUpa6g6sSHqcF7aJSGrSmBVJHxqvIo0kU/eoWzlt/p2VzM4BzgkfbjKzT6rotwPwRR2z1adUypNKWUB5qlKdPDs1RpBQlWNW47XepVKeVMoC6ZknpcYrpP2YTaUsoDxVSaU81c1SrTGbqYV6HtAz6XEPYFXZldz9HuCe6nZqZtPdfWjd49WPVMqTSllAeaqSanmoxpjVeK1fqZQnlbKA8lRDxv+NTaUsoDxVSaU89Z0lUw99+QDoZ2Z9zCwHOBmYEHEmEamYxqxI+tB4FWkkGblH3d1LzOxXwCsEU0eNd/d5EccSkQpozIqkD41XkcaTkYU6gLtPBCbWc7fV/gqvkaRSnlTKAspTlVTL0xBjNtV+RuWpWCplAeWpUhP4G5tKWUB5qpJKeeo1i7l/5/wPERERERGJWKYeoy4iIiIiktZUqIfMbJCZTTGzWWY23cyGhe1mZreZ2WIzm21mQ5K2GWdmi8LbuKT2vc1sTrjNbWZW3lRW1cn0azP7xMzmmdkNSe2Xhn1/YmZHJrWPDtsWm9klSe19zGxqmPPx8OSfWjGz/zMzN7MO4eNGf33M7G9mtiB8vmfNrE0qvDYVZC33eeubmfU0szfNbH74+3J+2N7OzCaFP98kM2sbttf4/y3VpNqY1XitNIfG7PbPofGqv7Hl5dF4rXnWzB+v7q5bcPjPq8BR4f2jgclJ9/9LMG/scGBq2N4OWBL+2za83zZcNg3YL9zmv9v6rWGew4DXgNzwcafw3/7AR0Au0Af4lOBknnh4vy+QE67TP9zmCeDk8P5dwC9q+Rr1JDh5aBnQIarXBxgFZIX3rweuj/q1qSBnhc/bAL+/XYEh4f1WwMLw9bgBuCRsvyTptarx/1uq3UihMYvGq8ZszZ5H41V/YzVe6/471STGq/aof8uBHcP7rfl2TtgxwEMemAK0MbOuwJHAJHdf7+5fAZOA0eGyHd39fQ/+Zx4CjqtFnl8Af3X3QgB3X5uU5zF3L3T3z4DFBJdz/uaSzu5eBDwGjAk/TR8OPBVu/2At8wDcAlzM9he2aPTXx91fdfeS8OEUgjl8t2WJ6rUpT7nPW4/9f8PdV7v7zPB+ATCf4EqBYwh+Ltj+56vR/1tDZK4HqTRmNV4roTG7PY3XyMcrpN6Y1XituSYxXlWof+u3wN/MbAVwI3Bp2F7RpZIra88rp72mdgEOCr8y+p+Z7VPLPO2B/KRBV6s8ZvYDYKW7f1RmUVSvzzZnEXxyrU2WenltKhHJZbbNrDcwGJgKdHb31RC82QCdqsiWTpcGT6Uxq/FafRqzSTRe9TdW47XWmsR4zdjpGctjZq8BXcpZdDkwArjA3Z82s5OA+4CRVHyp5Jq21zRPFsFXI8OBfYAnzKxvJf2X96GrPvNcRvB12Hc2q+HzVvfS0xVmcffnw3UuB0qAh6vIUufXppYauv/vPqFZS+Bp4LfuvrGSwxPr/PvbGFJpzGq81j6PxmwFT6bx2mT+xmq8Vp6nlprEeG1Shbq7j6xomZk9BJwfPnwS+Fd4v6JLJecBh5Zpnxy29yhn/Zrm+QXwTPj11TQzSwAdKslDBe1fEHztkhV+qq1xHjMbSHA82kfhL2YPYKYFJwM1yOtT2WsTZhoHHAOMCF8jKslCBe3Vfm1qqVqX2a4vZpZN8CbysLs/EzavMbOu7r46/Opt29e7Nf1/i0QqjVmN1+/kr1aepFwas0k0XpvW31iNV41XajtevZ4Puk/XG8ExR4eG90cAM8L732f7kwKm+bcnBXxG8Im8bXi/Xbjsg3DdbSdzHF2LPOcC14T3dyH4usSAAWx/MscSghMqssL7ffj2pIoB4fZPsv3JHOfV8bVayrcnuzT660NwTNfHQMcy7ZG/NmXyVPi8DfD7awTHI/69TPvf2P5klxtq+/+WardUGrMarxqzNXwejVf9jdV4rfvvVJMYr5EP3lS5AQcCM8L/6KnA3kn/Qf8kOLN4DjA0aZuzCE6mWAz8JKl9KDA33OZ2CC4sVcM8OcB/wn5mAocnLbs87PsTks7oJjjTeGG47PKk9r4EZ4IvDgdNbh1fq+Q3kkZ/fcL+VgCzwttdqfLalJO13OdtoN9fB2YnvS5HExwj+DqwKPx325t5jf/fUu2WSmNW41Vjtha/uxqv0f5OpuSY1XjVeC1705VJRURERERSkGZ9ERERERFJQSrURURERERSkAp1EREREZEUpEJdRERERCQFqVAXEREREUlBKtSlwVngHTM7KqntJDN7OcpcIvJdGq8i6UVjNrNpekZpFGa2B8EcqoMJLpAwCxjt7p/Woc9tVzsTkXqk8SqSXjRmM5cKdWk0ZnYDsBloARS4+5/CyxT/kuDiE+8Bv3L3hJndAwwBdgAed/drwj7ygLsJrpz2d3d/MoIfRSTjabyKpBeN2cyUFXUAaVKuJrgCXBEwNNwDcDywv7uXhG8cJwOPEFyWd72ZZQFvmtlT7v5x2M9mdz8gih9ApAnReBVJLxqzGUiFujQad99sZo8Dm9y90MxGAvsA080Mgk/2K8LVx5rZ2QS/o92A/sC2N5HHGze5SNOj8SqSXjRmM5MKdWlsifAGYMB4d78yeQUz6wecDwxz93wz+w/QLGmVzY2SVEQ0XkXSi8ZshtGsLxKl14CTzKwDgJm1N7NewI5AAbDRzLoCR0aYUUQCGq8i6UVjNgNoj7pExt3nmNnVwGtmFgOKgXOB6QRfwc0FlgDvRpdSREDjVSTdaMxmBs36IiIiIiKSgnToi4iIiIhIClKhLiIiIiKSglSoi4iIiIikIBXqIiIiIiIpSIW6iIiIiEgKUqEuIiIiIpKCVKiLiIiIiKQgFeoiIiIiIilIhbqIiIiISApSoS4iIiIikoJUqIuIiIiIpCAV6iIiIiIiKUiFuoiIiIhIClKhLiIiGcXMDjWzvKhzSNNlZqea2at12H6ymf20PjNlIjObZ2aHRp2jIalQl3phZmea2Rwz22Jmn5vZnWbWpprbLjWzkfWYpV77E6mruoyPcPuMGSNmlmVmm8xsWFLbqWbm5bQtiCKjNB1mdoqZTQ9/J1eb2X/N7MC69uvuD7v7qKTncTPbua79JvVnZvY7M1tkZl+b2XIz+6uZ5dagj/rOVGl/4ftgafhabzSzj8zsmBr0/4CZ/Tm5zd0HuPvkOsROeSrUpc7M7CLgeuB3QGtgOLATMMnMcqLMJhK1pj4+zCwr+bG7lwDvA4ckNR8MLCin7a26Pl9d1GdfknrM7ELg78BfgM5AL+AOYEyUuarpNuAc4AygFXAUcDjwRJShquF9d28JtCF4rR+ryU6LJsndddOt1jdgR2ATcFKZ9pbAWuAs4AHgz0nLDgXywvv/BhLA12E/FwO9ASd4E1oFrAYuStq+Rv1F/Rrp1nRv1Rkf4eOUGiPb1gcuA74AlgKnJi3PBW4ElgNrgLuAHcps+3vgc+Df5fR/JfBC0uOPgTPLaTst6fn+Hv6sq8L7uRU9X/LPG67zm7C/HuHjY4BZQD7wHrBn0rpLw75mA4VAVtS/R7rV/43gQ/Mm4EeVrDOM4ENlfjjGbgdykpZ7+Lu1JBwnfwNi4bIzgXfC+2+F624On/PHQFvgRWAd8FV4v0dS35OBn1aQqx9QCgwr094z/J09vLw+qpGpqnFfo/7Kyf3N+uHj5uE2+yS1PRmO4w1hnwPC9nOAYqAo7P+FsH0pMDK8X+H7RDrftEdd6mp/oBnwTHKju28C/gscUdnG7n46wR/7Y929pbvfkLT4MII3pFHAJdX5qr6K/kQaW53GR7huVGOkC9AB6A6MA+4xs13DZdcDuwCDgJ3Ddf5QZtt2BN8cnFNO328BB5hZzMw6AC0I9gQOS2rbjW/3qF9O8E3EIGAvggLqiuo8n5ldSVAgHOLueWY2BBgP/BxoD9wNTChzyMBY4PtAGw++AZDMsx/B2Hy2knVKgQsIxsF+wAjgvDLrHA8MBYYQ7Ik/q2wn7n5weHevcMw9TnBEw/0Ev7O9CD44317N7CMIPohOK/M8K4ApVO99pbxMUPm4r01/5TKzOPATguJ7WdKi/xK8p3UCZgIPh/3fE96/Iez/2HK6rep9Ii2pUJe66gB8UcEfs9Xh8tq62t03u/scgje0sXXoSyQKDTk+oOHHyJXuXuju/wNeAk4yMwN+Blzg7uvdvYDg0IGTk7ZLAFeF235dTr9TCfamDQQOItjLtgX4LKltmbsvD9c/FbjG3de6+zrgauD0Kp7PzOxm4EjgsHA7wux3u/tUdy919wcJ9kIOT+rvNndfUUF2yQztqXhsAuDuM9x9iruXuPtSgg91h5RZ7fpwHCwn2INbrTHo7l+6+9PuviUcQ9eW03dFOhC8f5SnPt5XvjPu69hfsuFmlg9sJfhW7jR3X7ttobuPd/cCdy8E/gjsZWatq9l3Ve8TaUmFutTVF0CHCo7l7Bour60VSfeXAd3q0JdIFBpyfEDDjpGv3H1zOf13JCiyZ5hZfvhH9+WwfZt17r61oo7DZdMIjkM/GHg7XPROUlvy8end2H6vW9mftbzna0Owd/06d9+Q1L4TcNG27GH+nmX6S35dJTN9ScVjEwAz28XMXgxPAN9I8IG0bBFcqzFoZs3N7G4zWxb2/RbQJtzTXHbdeeEJmJvM7CCC942uFXRd1/eVisZ9fZni7m0IDv2ZQPChHAj2socnxH4aviZLw0XV/eBR1ftEWlKhLnX1PsHeqBOSG82sBcHJLa8THLPWPGlxlzJ9eAV990y634vgmDPq0J9IY6vO+IDUHCNtw5xl+/+C4Gv6Ae7eJry19uAEsZr0/xZBQX4Q3xbqbye1JRfqqwgK7LJZKnu+rwiORb/fzA5Ial8BXJuUvY27N3f3R2uYX9Lb+wR7dY+rZJ07CU5y7ufuOxIcu21l1qloDFblImBXYN+w722HjpTtHw9mNmkZ3t4G3gB6Js+SBGBmPQm+Garu+0p5Khr3te2vXOHhf+cBp5vZ4LD5FILDh0YSnEPQO2zf9ppUNS6rep9ISyrUpU7CPVVXA/8ws9Fmlm1mvQlOCMkjOLFrFnC0mbUzsy7Ab8t0swboW073V4Z7HQYQHMu27Zi32vYn0qiqOT4gdcfI1WaWE+7FOwZ40t0TwL3ALWbWCcDMupvZkdXoL9lbBMfY9yQ40ROCPeqHEhxjmlyoPwpcYWYdw+PX/wD8p6on8GDatlOBZ81s37D5XuBcM9s3nOKuhZl938xa1TC/pLFwbP4B+KeZHReOo2wzO8rMtp230QrYCGwys92AX5TT1e/MrG1YJJ/Pt2OwrLJjrhXBB958M2sHXFWD7AsJTuB+2MyGh3uiBwBPA6+5+2vhqrOAE8KfbWfg7CoybfOdcV/H/ir6Ob4E/sW357e0Itix8SXBB4K/1LD/Wr1PpLyGOENVt6Z3IxiwcwneeNYQHMvXNlzWjODNayPBTAoXsP2MDGMITm7LB/6P785o8TlJM1PUtL+oXxvddKtsfITLU2qM8O3sD5cT7EFfDpxepv+/EMx2sRGYD/wmedtqvCYtCU4km1Cm/WNgVZm2ZgTT0a0Ob7cBzSp6vrJtBCeGrgH2Dh+PBj7g29k8ngRahcuWEs4ioVvm3wg+yE0n2Fv8OcEx2fuHy7ZNG7qJ4Nuea9h+1pLkWV++BG4C4uGyM8use274u5ZPcMx3N4JZVDYBCwlObnbCWYaoZNaXcHmMYHaixQTvKyuAG7aNi3CdDsCrQAHwLsEx35Vlqmrc16i/cjJv95qEbT0IivM9w/eE58P+lxFMPenAzuG6/fh2tqbnwrZvxiuVvE+k883CH04kZYR7HD8Dsl0zLoh8R0OPEQuu9Pcfd+9R332LZAozc4LDYhZHnaU+aNynJh36IiIiIiKSglSoi4iIiIikIB36IiIiIiKSgrRHXUREREQkBalQFxERERFJQRVekaup6dChg/fu3TvqGCIpY8aMGV+4e8eq12x8VY3XvC8Ws8EKGy+QSAPbvd3uxKzifWupPF6h8jG7cfNXrNia9telEflGx1hrOrWtfPKc6o5ZFeqh3r17M3369KhjiKQMM1tW9VrRqGq8bt5SQFFxhVewF0k7rVu2Ixb/ztXlv5HK4xUqH7MlJcUUbM5v5EQiDWeHZi1oltu80nWqO2ZVqItIxmnRvBUt0IUmRdJBVlY2bVun7JcBIpHSMeoiIiIiIilIhbqIiIiISApSoS4iIiIikoJUqIuIiIiIpCAV6iIiIiIiKUiFuoiIiIhIClKhLiIiIiKSglSoi4iIiIikIBXqIiIiIiIpSIW6iIiIiEgKUqEu0sT89eGz+Oczv4s6hoiIiFQhK+oAItK43vh6Gj03tYw6hoiIiFRBe9RFmpAtWzezNgs6ZHeMOoqIiIhUQYW6SBMye9G7lJrRtWXvOvdlZuPNbK2ZzS1n2f+ZmZtZh/CxmdltZrbYzGab2ZCkdceZ2aLwNq7OwURERDKECnWRJuST5R8A0KfTwPro7gFgdNlGM+sJHAEsT2o+CugX3s4B7gzXbQdcBewLDAOuMrO29RFOREQk3alQF2lCVqxfAMDA7x1Q577c/S1gfTmLbgEuBjypbQzwkAemAG3MrCtwJDDJ3de7+1fAJMop/kVERJoiFeoiTciarXm0Kk3Qu9tuDdK/mf0AWOnuH5VZ1B1YkfQ4L2yrqF1ERKTJa7BC3cyamdk0M/vIzOaZ2dVhex8zmxoej/q4meWE7bnh48Xh8t5JfV0atn9iZkcmtY8O2xab2SVJ7eU+h0hTt87z6VqSRSwer/e+zaw5cDnwh/IWl9PmlbSX1/85ZjbdzKavW7eu9kFFRETSREPuUS8EDnf3vYBBwGgzGw5cD9zi7v2Ar4Czw/XPBr5y950Jvjq/HsDM+gMnAwMIvhK/w8ziZhYH/klw7Gt/YGy4LpU8h0iTtiZeRAdaNVT33wP6AB+Z2VKgBzDTzLoQ7CnvmbRuD2BVJe3f4e73uPtQdx/asaNmrRERkczXYIV6eCzqpvBhdnhz4HDgqbD9QeC48P6Y8DHh8hFmZmH7Y+5e6O6fAYsJTjobBix29yXuXgQ8BowJt6noOUSarHVfreKLrBidcro2SP/uPsfdO7l7b3fvTVCED3H3z4EJwBnh7C/DgQ3uvhp4BRhlZm3Dk0hHhW0iIiJNXoMeox7u+Z4FrCU4SexTIN/dS8JVko9H/eZY1XD5BqA9NT+2tX0lzyHSZH244H8A9GjTr176M7NHgfeBXc0sz8wq++ZqIrCE4IP2vcB5AO6+HvgT8EF4uyZsExERafIa9Mqk7l4KDDKzNsCzwO7lrRb+W9NjWMv7kFHjY14JpoqjV69e5a0ikjEWrZ4JwC7d966X/tx9bBXLeyfdd+CXFaw3HhhfL6FEREQySKPM+uLu+cBkYDjBtGzbPiAkH4/6zbGq4fLWBFO/1fTY1i8qeY6yuXTMqzQZqzYsxtwZvNshUUcRERGRamjIWV86hnvSMbMdgJHAfOBN4IfhauOA58P7E8LHhMvfCPfCTQBODmeF6UNwwZRpBF+T9wtneMkhOOF0QrhNRc8h0mStLV5DpxKnTasOUUcRERGRamjIQ1+6Ag+Gs7PEgCfc/UUz+xh4zMz+DHwI3Beufx/wbzNbTLAn/WQAd59nZk8AHwMlwC/DQ2ows18RnHgWB8a7+7ywr99X8BwiTdY620SnRG7UMURERKSaGqxQd/fZwOBy2pcQzNhStn0r8KMK+roWuLac9okEJ6lV6zlEmqpEaSmrs0oZXtIp6igiIiJSTboyqUgTsGj5bLbEYnRp3iPqKCIiIlJNKtRFmoDZn74LwE4dBkScRERERKpLhbpIE/DZutkA7NHngIiTiIiISHWpUBdpAj7fvIzchNO/7z5RRxEREZFqatALHolIalhX+iVd3cjKyo46ioiIiFST9qiLNAFr41vpmGgRdQwRERGpARXqIhlu85YC1mRBx2xdfVdERCSdqFAXyXAfLXqHUjO6teobdRQRERGpARXqIhluwfJpAPTtvFfESURERKQmVKiLZLjl6+cDMHi3wyNOIiIiIjWhWV9EMtznhXm0jyfo0al31FFERESkBrRHXSTDrWUjXUtzoo4hIiIiNaRCXSSDJUpLWZldSidrH3UUERERqSEV6iIZbO6SD9gSi9G1xU5RRxEREZEaUqEuksHmfPoWAN/rNDjiJCIiIlJTKtRFMthn6+YAMHiXQ6MNIiIpz8x6mtmbZjbfzOaZ2fnlrHOomW0ws1nh7Q9RZBVpKjTri0gGW/31ClpnJejbffeoo4hI6isBLnL3mWbWCphhZpPc/eMy673t7sdEkE+kydEedZEMtpZ8upZkE4vHo44iIinO3Ve7+8zwfgEwH+gebSqRpk2FukiGSpSWsiqrmE60iTqKiKQZM+sNDAamlrN4PzP7yMz+a2YDGjWYSBOjQ19EMtSSlfPZGI/RNbtX1FFEJI2YWUvgaeC37r6xzOKZwE7uvsnMjgaeA/pV0M85wDkAvXrpfUikNrRHXSRDzfzkDQD6dNwj4iQiki7MLJugSH/Y3Z8pu9zdN7r7pvD+RCDbzDqU15e73+PuQ919aMeOHRs0t0imUqEukqGWrJ0FwF47HxJxEhFJB2ZmwH3AfHe/uYJ1uoTrYWbDCOqILxsvpUjTokNfRDLU6i3LaJ6VoH+foVFHEZH0cABwOjDHzGaFbZcBvQDc/S7gh8AvzKwE+Bo42d09irAiTYEKdZEMtcbX0704rhlfRKRa3P0dwKpY53bg9sZJJCI69EUkQ30eL6ITraOOISIiIrWkPeoiGWjF50v4MitGlyxNgSwiIpKutEddJAPNXPAaADu11xTHIiIi6UqFukgGWvT5TAD26LN/gz2HmY03s7VmNjep7W9mtsDMZpvZs2bWJmnZpWa22Mw+MbMjk9pHh22LzeySBgssIiKSZlSoi2SgvILF7JBIMHjXgxvyaR4ARpdpmwTs4e57AguBSwHMrD9wMjAg3OYOM4ubWRz4J3AU0B8YG64rIiLS5KlQF8lAn/uX9CiOk5WV3WDP4e5vAevLtL3q7iXhwylAj/D+GOAxdy9098+AxcCw8LbY3Ze4exHwWLiuiIhIk6dCXSQDrcwqonP0M76cBfw3vN8dWJG0LC9sq6hdRESkyVOhLpJhFi6bTX48RvcdekeWwcwuB0qAh7c1lbOaV9JeXp/nmNl0M5u+bt26+gkqIiKSwlSoi2SY6QsmAbBz58GRPL+ZjQOOAU5NumJhHtAzabUewKpK2r/D3e9x96HuPrRjx471H1z+v717j5O6rPs//vrMnkBRzionAXU9oBkiclBLEw+IJVZqaiUe7rgzK+1wF1Z3lub90+rOw515SEgsj6kpFkageBZ0RQIBkQU5rKAuRzkEy+58fn/MtTmus8vuMjPfObyfj8c89jvXXPOd9w5czIfvfL/XJSIiOUaFukiBWfr+6wAMPfTUrL+2mY0Gfgic6e7bkh6aApxnZhVmNhCoBF4BXgUqzWygmZWTuOB0SrZzi4iI5CIteCRSYFb/awVdS+MctP8RGX0dM7sfOBHoYWY1wNUkZnmpAKabGcAsd/+6uy8ws4eAhSROibnc3RvCfr4JTANKgEnuviCjwUVERPKECnWRAvMum+hdX57x13H381M0T2yh/3XAdSnapwJT0xhNRESkIOjUF5ECUl+/k5qyOPvFekQdRURERHZTxgp1M+tnZjPNbJGZLTCzK0L7z8zsHTObG25jkp7TppULw3mts81siZkaoznkAAAgAElEQVQ9GM5xJZwH+2DoP9vMBmTq9xTJJXMWPcv2mNGv00FRRxEREZHdlMkj6vXA99z9MGAEcHnSioM3uvvgcJsK7V658Iawr0pgA3BpaL8U2ODuBwE3hn4iBW/usmcBOLTv8IiTiIiIyO7KWKHu7mvcfU7Y3gwsouWFTNq0cqElrlQ7CXg4PH8ycFbSviaH7YeBUaG/SEFbsT5xHeaII0ZHnERERER2V1bOUQ+nnhwFzA5N3zSzeWY2ycy6hra2rlzYHdiYtFx58oqG/35OeHxT6C9S0NbUrabXTqd7l/2ijiIiIiK7KeOFupl1Ah4BrnT3D4DbgAOBwcAa4H8bu6Z4eksrF7a0omGrVjvUSodSaNaUbKFXQ8eoY4iIiEgaZLRQN7MyEkX6ve7+KIC7v+fuDe4eB35P4tQWaPvKhWuBLmZW2qT9I/sKj3cG1jfNp5UOpZBs2rKeNaXQq6xX1FFEREQkDTI564uRmFN5kbv/Jqk9uYr4PPBG2G7TyoVhafKZwNnh+eOAx5P2NS5snw08nbSUuUhBmj1/Gg1m9O9yWNRRREREJA0yueDRccBXgflmNje0/YjErC2DSZyKshz4T4B2rlz4Q+ABM/sF8DofLrYyEfijmVWTOJJ+XgZ/T5GcsHDVywAcMeC4iJOIiIhIOmSsUHf3F0h9rnizKxC2deVCd1/Gh6fOJLdvB85pS16RfLfigzepKHGOOfzkqKOIiIhIGmTyiLqIZNGaeC37x2N0qNgj6igiIiKSBlmZnlFEMive0MDK0jp60S3qKCIiIpImOqIuUgDeWDqbzSUx+nU4MOooIiIikiY6oi5SAKoWTwfgsD4jI04iIiIi6aJCXaQALF07F3Pn2CPHRB1FRERE0kSnvogUgHfq3qFPCfTs2jvqKCIiIpImOqIuUgBqSrbSO75X1DFEREQkjVSoi+S5mveX815ZjD4V/aKOIiIiImmkQl0kz708768AVPYcEnESERERSScV6iJ5bvGaVwAYfvjoiJOIiIhIOuliUpE8V/Ovt+laEufg/oOjjiIiIiJppCPqInnuHdtIv/oOUccQERGRNFOhLpLHtm7bTE2Z07t0v6ijiIiISJqpUBfJYy/Nm0q9GQO7Hh51FBEREUkzFeoieWz+iucAGHzgZyJOIiIiIummQl0kjy3/YBF7xOMMO/zkqKOIiIhImqlQF8ljNb6WATvLKS0tizqKiIiIpJkKdZE8tW37VlaUxekb2zfqKCIiIpIBmkddJE+9OPev1MWMAzsfGXUUERERyQAdURfJU/9cPhOAoZWnRpxERAqBmfUzs5lmtsjMFpjZFSn6mJndYmbVZjbPzIZEkVWkWKhQF8lTyze/SaeGOEMHRTPji5lNMrP3zeyNpLZuZjbdzJaEn11De7Mf7mY2LvRfYmbjovhdRASAeuB77n4YMAK43MwGNelzOlAZbuOB27IbUaS4qFAXyVM1vp4B9eXESkqiinA3MLpJ2wTgKXevBJ4K96GZD3cz6wZcDQwHhgFXNxb3IpJd7r7G3eeE7c3AIqBPk25jgXs8YRbQxcx6ZTmqSNFQoS6ShzZv3ciK8jh9S6L7fHT354D1TZrHApPD9mTgrKT2VB/upwHT3X29u28ApvPx4l9EsszMBgBHAbObPNQHWJV0v4aPF/ON+xhvZlVmVlVbW5uJmCIFT4W6SB56Ye4T1JtxULdPRh2lqX3dfQ0kjs4B+4T25j7cW/2hLyLZYWadgEeAK939g6YPp3iKp9qPu9/p7kPdfWjPnj3THVOkKKhQF8lD81Y8C8Axh42JOEmrNffh3uoPfR2dE8k8MysjUaTf6+6PpuhSA/RLut8XWJ2NbCLFSIW6SB5aseUtOjfEGVx5bNRRmnqv8XzV8PP90N7ch3urP/R1dE4ks8zMgInAInf/TTPdpgAXhgvERwCbGr9FE5H0U6EukodW2Qb67+wQ5YWkzZkCNM7cMg54PKk91Yf7NOBUM+saLiI9NbSJSPYdB3wVOMnM5obbGDP7upl9PfSZCiwDqoHfA9+IKKtIUdCCRyJ5ZuPmtdSUOafEo51owczuB04EephZDYnZW64HHjKzS4GVwDmh+1RgDIkP923AxQDuvt7MrgVeDf2ucfemF6iKSBa4+wukPh0tuY8Dl2cnkYioUBfJM8+/PiVxIWn3oyLN4e7nN/PQqBR9m/1wd/dJwKQ0RhMRESkIOvVFJM/MW/kcACMGnRFxEhEREckkHVEXyTPLt71Fj5I4R1aOiDqKiIiIZJCOqIvkmRWxDxhQ3ynqGCIiIpJhKtRF8kj1yjdYU2YM6HhA1FFEREQkw1Soi+SR5/6ZWH/kyH4nRJxEREREMk2FukgeebP2FUrcOXHIF6OOIiIiIhmmi0lF8siq+nfob0bXzlqZU0REpNBl7Ii6mfUzs5lmtsjMFpjZFaG9m5lNN7Ml4WfX0G5mdouZVZvZPDMbkrSvcaH/EjMbl9R+tJnND8+5JSx/3OxriOSzurodLCuroz8q0kVERIpBJk99qQe+5+6HASOAy81sEDABeMrdK4Gnwn2A04HKcBsP3AaJopvEiofDgWHA1UmF922hb+PzRof25l5DJG+9NG8q22IxDuzyiaijiIiISBZkrFB39zXuPidsbwYWAX2AscDk0G0ycFbYHgvc4wmzgC5m1gs4DZju7uvdfQMwHRgdHtvb3V8Oqx7e02RfqV5DJG9VVU8DYPihWuhIRESkGGTlYlIzGwAcBcwG9nX3NZAo5oF9Qrc+wKqkp9WEtpbaa1K008JriOStZR8sZO+GOMMGjYo6ioiIiGRBxgt1M+sEPAJc6e4ftNQ1RZu3o70t2cabWZWZVdXW1rblqSJZt8I2MHBnR2IlJVFHERERkSzIaKFuZmUkivR73f3R0PxeOG2F8PP90F4D9Et6el9g9S7a+6Zob+k1PsLd73T3oe4+tGdPXaAnuWt17QpWlTn9y/ePOoqIiIhkSSZnfTFgIrDI3X+T9NAUoHHmlnHA40ntF4bZX0YAm8JpK9OAU82sa7iI9FRgWnhss5mNCK91YZN9pXoNkbz0zJyHcTMO7z0y6igiIiKSJZmcR/044KvAfDObG9p+BFwPPGRmlwIrgXPCY1OBMUA1sA24GMDd15vZtcCrod817r4+bF8G3A10BJ4MN1p4DZG89MbqFzBzThxybtRRREREJEsyVqi7+wukPo8c4GNXw4WZWy5vZl+TgEkp2quAI1K0r0v1GiL56u2dKxhgRu+e/aOOIiIiIlmSlVlfRKT9tu/YxtKyHQzU5EUiIiJFRYW6SI575rW/8K9YjEO6Hx11FBEREckiFeoiOa5qaWKho08f+cWIk4iIiEg2ZfJiUhFJg6XbFrNvSZwjDhoedRQRERHJIh1RF8lh8YYGlpZu4YB4l6ijiIiISJbpiLpIDqtaOJMNpTEO2uPwqKOIiIhIlumIukgOe2HhYwCMPOSzEScRERGRbFOhLpLDqjfNY++GOCOPPD3qKCIiIpJlKtRFctiy2HoOrN+D0tKyqKOIiIhIlqlQF8lR1Svf4J0y44CKA6OOIiIiIhFQoS6So55+/X4Ajup/UsRJREREJAoq1EVy1IL3Z9Mh7pw87Pyoo4iIiEgEVKiL5KilvEdlXTl77rFX1FFEREQkAm0q1M0sZmZ7ZyqMiCQsW7WAFeVwUAedny4iIlKsdlmom9l9Zra3me0JLAQWm9l/ZT6aSPGaXvUnAIYOHB1xEhEREYlKa46oD3L3D4CzgKnA/sBXM5pKpMgtWDubjvE4Jw87L+oo7WJm3zGzBWb2hpndb2YdzGygmc02syVm9qCZlYe+FeF+dXh8QLTpRUREckNrCvUyMysjUag/7u47Ac9sLJHiVs37VNZ1YI8Oe0Ydpc3MrA/wbWCoux8BlADnATcAN7p7JbABuDQ85VJgg7sfBNwY+omIiBS91hTqdwDLgT2B58ysP/BBJkOJFLO3VsxlVblR2aEy6ii7oxToaGalwB7AGuAk4OHw+GQS//kHGBvuEx4fZWaWxawiIiI5aZeFurvf4u593H2MJ6wAPpOFbCJFacZr9wEw7MAxESdpH3d/B/g1sJJEgb4JeA3Y6O71oVsN0Cds9wFWhefWh/7ds5lZREQkF7XmYtJ9zWyimT0Z7g8CxmU8mUiRWrjuFfaMxznpmLOjjtIuZtaVxFHygUBvEt/GnZ6ia+MpdKmOnn/s9DozG29mVWZWVVtbm664IiIiOas1p77cDUwj8YEL8BZwZaYCiRS7altLZV1HOlTsEXWU9joZeNvda8M1LY8CxwJdwqkwAH2B1WG7BugHEB7vDKxvulN3v9Pdh7r70J49e2b6dxAREYlcawr1Hu7+EBCHf3813ZDRVCJFatGy13inzKjseHDUUXbHSmCEme0RzjUfRWJq15lA49cE44DHw/YUPvyW7mzgaXfXBesiIlL0WlOobzWz7oSvos1sBIlzSEUkzWa8lpg/fXjlZyNO0n7uPpvERaFzgPkk/p25E/gh8F0zqyZxDvrE8JSJQPfQ/l1gQtZDi4iI5KDSXXfhuySOeB1oZi8CPfnwqJiIpNGCDa/SuTTOqGPOiTrKbnH3q4GrmzQvA4al6LsdyO9fWKRAmNkk4LPA+2F61aaPn0ji27C3Q9Oj7n5N9hKKFJddFuruPsfMTgAOIXHR1+Jw3qmIpFG8oYE3SzZwSP3elJaWRR1HRIrT3cBvgXta6PO8u+fv134ieWSXhbqZXdikaYiZ4e4tDWIRaaPnXp/CutIYZ3Y6KuooIlKk3P05rQ4skjtac+rLMUnbHUhcGDaHlv+3LSJt9NyixFpAJw9p+n9jEZGcMtLM/kli5qbvu/uCqAOJFKrWnPryreT7ZtYZ+GPGEokUqcXb3qRfzDmyckTUUUREmjMH6O/uW8xsDPAYkHIZZTMbD4wH2H///bOXUKSAtGbWl6a20cygFJH22bRlPYvLd3Cw9Yo6iohIs9z9A3ffEranAmVm1qOZvlr7QGQ3teYc9Sf4cJXAGDAIeCiToUSKzd9e/AM7YsbgfT4ddRQRkWaZ2X7Ae+7uZjaMRF2wLuJYIgWrNeeo/zppux5Y4e41GcojUpTmrJpBaalzxrGXRh1FRIqYmd0PnAj0MLMaEtOslgG4++0kpme+zMzqgX8B52mBMpHMac056s9mI4hIMVvsNRxcV0bPrr2jjiIiRczdz9/F478lMX2jiGRBs4W6mW3mw1NePvIQ4O6+d8ZSiRSRt1bMY3k5fJ6Doo4iIiIiOaTZQt3d98pmEJFi9fdXJgEw8qAzI04iIiIiuaQ156gDYGb7kJhHHQB3X5mRRCJFZt6G2XQtjXPK8POijiIiIiI5ZJfTM5rZmWa2BHgbeBZYDjyZ4VwiRWH7jm0sLP2AQfXdKC0tizqOiIiI5JDWzKN+LTACeMvdB5JYmfTFjKYSKRJ/e/FuNpfEOKrn8VFHERERkRzTmkJ9p7uvA2JmFnP3mcDgXT3JzCaZ2ftm9kZS28/M7B0zmxtuY5Ieu8rMqs1ssZmdltQ+OrRVm9mEpPaBZjbbzJaY2YNmVh7aK8L96vD4gFa9EyIRmPX2Xyl153PHfz3qKCIiIpJjWlOobzSzTsDzwL1mdjOJ+dR35W5gdIr2G919cLhNBTCzQcB5wOHhOb8zsxIzKwFuBU4nsdDS+aEvwA1hX5XABqBxAupLgQ3ufhBwY+gnkpMWxldxSF0ZvXv2jzqKiIiI5JhmC3Uz+62ZHQeMBbYBVwJ/B5YCn9vVjt39OWB9K3OMBR5w9x3u/jZQDQwLt2p3X+budcADwFgzM+Ak4OHw/MnAWUn7mhy2HwZGhf4iOWXu4hdYWQ6DOg7adWcREREpOi0dUV9CYlXSBcD/A45w98nufks4Faa9vmlm88KpMV1DWx9gVVKfmtDWXHt3YKO71zdp/8i+wuObQn+RnPL3qsS0jCcf+ZWIk4iIiEguarZQd/eb3X0kcAKJI+N/MLNFZvbfZnZwO1/vNuBAEue4rwH+N7SnOuLt7WhvaV8fY2bjzazKzKpqa2tbyi2Sdm9smUevnc6II06NOoqIiIjkoF2eo+7uK9z9Bnc/CrgA+AKwqD0v5u7vuXuDu8eB35M4tQUSR8T7JXXtC6xuoX0t0MXMSpu0f2Rf4fHONHMKjrvf6e5D3X1oz5492/MribTLhk21vFm+nUH0IlZSEnUcERERyUGtmUe9zMw+Z2b3kpg//S3gi+15MTPrlXT380DjjDBTgPPCjC0DgUrgFeBVoDLM8FJO4oLTKe7uwEzg7PD8ccDjSfsaF7bPBp4O/UVyxmPP386OmDGsn46mi4iISGrNrkxqZqcA5wNnkCiaHwDGu/vW1uzYzO4HTgR6mFkNcDVwopkNJnEqynLgPwHcfYGZPQQsJDGjzOXu3hD2801gGlACTHL3BeElfgg8YGa/AF4HJob2icAfzayaxJF0LfcoOefV1TPYoyzO547/WtRRREREJEc1W6gDPwLuA77v7q2dveXf3P38FM0TU7Q19r8OuC5F+1Rgaor2ZXx46kxy+3bgnDaFFcmiurodzC9dyyd27s1ee3aJOo6IiIjkqGYLdXf/TDaDiBSLJ16YyMaSGEd3+XTUUURERCSHtWbBIxFJoxeWPUZ53PnCCd+OOoqIiIjkMBXqIlkUb2hgPu8wqK4D+3bvs+sniIiISNFSoS6SRTNeeYj3ymIM7nxM1FFEREQkx6lQF8mimYvuJ+bO54/7ZtRRREREJMe1NOuLiKTZ/Ia3OaS+lAP6HR51FBEREclxOqIukiWvzJ/BinI4suMnoo4iIiIieUCFukiWTJ1zFwBjjhkfcRIRERHJByrURbLk9boFVO4whhz6qaijZJyZdTGzh83sTTNbZGYjzaybmU03syXhZ9fQ18zsFjOrNrN5ZjYk6vwiIiK5QIW6SBbMmv8PlpXD4OI57eVm4O/ufijwSWARMAF4yt0rgafCfYDTgcpwGw/clv24IiIiuUeFukgW/LXqDgC+MLLwFzkys72BTwMTAdy9zt03AmOByaHbZOCssD0WuMcTZgFdzKxXlmOLiIjkHBXqIlkwt/4tDt1RwhEHDY86SjYcANQCfzCz183sLjPbE9jX3dcAhJ/7hP59gFVJz68JbSIiIkVNhbpIhj372uOsKIchex4VdZRsKQWGALe5+1HAVj48zSUVS9HmH+tkNt7Mqsysqra2Nj1JRUREcpgKdZEM+/s/JxJz54vHfyfqKNlSA9S4++xw/2EShft7jae0hJ/vJ/Xvl/T8vsDqpjt19zvdfai7D+3Zs2fGwouIiOQKFeoiGRRvaGBOfBmD6so4uP+RUcfJCnd/F1hlZoeEplHAQmAKMC60jQMeD9tTgAvD7C8jgE2Np8iIiIgUM61MKpJBM155iNVlxsnlw6KOkm3fAu41s3JgGXAxiQMDD5nZpcBK4JzQdyowBqgGtoW+IiIiRU+FukgG/WPBPZSWOuee8L2oo2SVu88FhqZ4aFSKvg5cnvFQIiIieUanvohkSF3dDqpsJZ/Y0ZH+vQ+OOo6IiIjkGRXqIhny56dvZl1pjOP2PSXqKCIiIpKHVKiLZMgzKx9jr4Y4F5zyg6ijiIiISB5SoS6SAe+uXcXrZR8wpGEf9tqzS9RxREREJA+pUBfJgPueup4dMePUQ74SdRQRERHJU5r1RSQDZm16kd4x57PHXRR1FBEREclTOqIukmZz3nyeRRUNHFNyCLGSkqjjiIiISJ5SoS6SZo+8fCMAXxh5ZcRJREREJJ+pUBdJo/r6ncxuWMzhO0oZcuinoo4jIiIieUyFukgaPTjjRt4ri/HpHpo7XURERHaPCnWRNJqx4hE6N8T56mk/ijqKiEibmdkkM3vfzN5o5nEzs1vMrNrM5pnZkGxnFCkmKtRF0uStFXOZW7GV4fG+mjtdRPLV3cDoFh4/HagMt/HAbVnIJFK0VKiLpMmfnvkf6s344jG6iFRE8pO7Pwesb6HLWOAeT5gFdDGzXtlJJ1J8VKiLpEF9/U5m7VzIYTtKOPaTp0cdR0QkU/oAq5Lu14Q2EckAFeoiafDw0//HmjLjU91OijqKiEgmWYo2T9nRbLyZVZlZVW1tbYZjiRQmFeoiafCP5Q+yV0OcC0f/JOooIiKZVAP0S7rfF1idqqO73+nuQ919aM+ePbMSTqTQqFAX2U3zlsxiTvlWjo3vT+dO3aKOIyKSSVOAC8PsLyOATe6+JupQIoWqNOoAIvnuT89di5fABcdrSkYRyW9mdj9wItDDzGqAq4EyAHe/HZgKjAGqgW3AxdEkFSkOKtRFdsPGzWt5yZZz1I49tRKpiOQ9dz9/F487cHmW4ogUvYyd+pJq0QQz62Zm081sSfjZNbQ3u4CCmY0L/ZeY2bik9qPNbH54zi1mZi29hkgmTJr6UzaVxDj9gAuijiIiIiIFJpPnqN/NxxdNmAA85e6VwFPhPjSzgIKZdSPxtdtwYBhwdVLhfVvo2/i80bt4DZG0ijc08MwHz9O/Ds456VtRxxEREZECk7FCvZlFE8YCk8P2ZOCspPZUCyicBkx39/XuvgGYDowOj+3t7i+Hr+HuabKvVK8hklZ/efYO3i6HEzodS6ykJOo4IiIiUmCyPevLvo1Xh4ef+4T25hZQaKm9JkV7S68hklZ/XTKZvRri/MeYX0QdRURERApQrkzP2NwCCm1tb9uLajEGaadX5s/gtYqtHOcD6NpZ8wOLiIhI+mW7UH8vnLZC+Pl+aG9uAYWW2vumaG/pNT5GizFIe90z6xeUAl87+bqoo4iIiEiBynahPgVonLllHPB4UnuqBRSmAaeaWddwEempwLTw2GYzGxFme7mwyb5SvYZIWry1Yh4vl65l5M7uHNx/cNRxREREpEBlbB71ZhZNuB54yMwuBVYC54TuKRdQcPf1ZnYt8Grod427N16gehmJmWU6Ak+GGy28hkha3PXUj9gZg68MvyrqKCIiIlLAMlaot7BowqgUfZtdQMHdJwGTUrRXAUekaF+X6jVE0uG9de/wAm9z9I5OjDyy6eyjIiIiIumjlUlF2uCOqT9gc0mMsw++LOooIiIiUuBUqIu00uatG5lZN5fDGso44/iLoo4jIiIiBS5XpmcUyXm3PvZd1pbG+MKAC6OOIiIiIkVAhbpIK2zeupFp22dz6I4Szh11RdRx8oKZlZjZ62b213B/oJnNNrMlZvagmZWH9opwvzo8PiDK3CIiIrlChbpIKzQeTf/igAuJlZREHSdfXAEsSrp/A3Cju1cCG4BLQ/ulwAZ3Pwi4MfQTEREpeirURXZBR9Pbzsz6AmcAd4X7BpwEPBy6TAbOCttjw33C46NCfxERkaKmQl1kF3Q0vV1uAn4AxMP97sBGd68P92uAPmG7D7AKIDy+KfQXEREpairURVqwact6/qGj6W1iZp8F3nf315KbU3T1VjyWvN/xZlZlZlW1tbVpSCoiIpLbVKiLtOCmRy+ntjTGOQMv0dH01jsOONPMlgMPkDjl5Sagi5k1TgnbF1gdtmuAfgDh8c7Aeppw9zvdfai7D+3Zs2dmfwMREZEcoEJdpBmr3l3GtPp5fHJ7Oeee8u2o4+QNd7/K3fu6+wDgPOBpd/8yMBM4O3QbBzwetqeE+4THnw6rFYuIiBQ1Feoizbj5b5ezJWZcctRVUUcpFD8Evmtm1STOQZ8Y2icC3UP7d4EJEeUTERHJKVqZVCSFeUtmMTO2ipF1XThp2Nm7foKk5O7PAM+E7WXAsBR9tgPnZDWYiIhIHtARdZEUfjfzv3CDy064PuooIiIiUqRUqIs08fQrD/Ny+QY+U9+HwYccH3UcERERKVIq1EWSxBsauH3uL+gUd64847dRxxEREZEipkJdJMkdU37CoooGzuwwkn69KqOOIyIiIkVMhbpIsGFTLX9eP4UBdfCds2+NOo6IiIgUORXqIsEvH/0PaktjXHTgZZSXV0QdR0RERIqcCnURYM6bzzOdpQzf0YkvnvSNqOOIiIiIqFAXiTc0cOOz3yGG8+3P3Bh1HBERERFAhboItz9+FXM77ODM0iEcWTki6jgiIiIigAp1KXKr3l3GAxv/xoF1xg++dFfUcURERET+TYW6FLX/N+ViPogZ3zjiKl1AKiIiIjlFhboUrT/P+C3PV6zn5Pp+nDry/KjjiIiIiHxEadQBRKJQu2E1v19+O/sBV539h6jjiIiIiHyMjqhLUfr5w1/m3VL4z4GX0b3LflHHEREREfkYFepSdP449XqeLV/LKfV9OHvU5VHHEREREUlJp75IUVm1ZgkT1/yRfnHjp+ffH3UcERERkWbpiLoUjXhDAz9/4kI2lRhXHPEjOnfqFnUkERERkWapUJeicdPD32J2xRbO8EM4beQFUccRERERaZEKdSkKz772OPdte47Dd5Ty0y/fF3UcERERkV1SoS4Fb93Gd7lhzo/ZI+5cc9oftLCRiIiI5AUV6lLwfvzQOdSUwdf7XsLB/QdHHUdEJGeZ2WgzW2xm1WY2IcXjF5lZrZnNDbf/iCKnSLHQrC9S0P73gct4sWIjZzQcwAWnfS/qOCIiOcvMSoBbgVOAGuBVM5vi7gubdH3Q3b+Z9YAiRUhH1KVgPf7Mnfxp+/N8YnsZP/vyA1HHERHJdcOAandf5u51wAPA2IgziRQ1FepSkBYsreI3S2+mZz3ccOaDdKjYI+pIIiK5rg+wKul+TWhr6otmNs/MHjazftmJJlKcIinUzWy5mc0P57dVhbZuZjbdzJaEn11Du5nZLeF8uXlmNiRpP+NC/yVmNi6p/eiw/+rwXMv+bylR2bRlPT956hK2x+DHR11Hv16VUUcSEckHqT4rvcn9J4AB7n4kMAOY3OzOzMabWZWZVdXW1qYxpkjxiPKI+mfcfbC7Dw33JwBPuXsl8FS4D3A6UBlu44HbIFHYA1cDw0l8XXd1Y3Ef+ogztY4AABKtSURBVIxPet7ozP86kgviDQ18/77PUl3hfK37FznhaH1rKyLSSjVA8hHyvsDq5A7uvs7dd4S7vweObm5n7n6nuw9196E9e/ZMe1iRYpBLp76M5cP/mU8Gzkpqv8cTZgFdzKwXcBow3d3Xu/sGYDowOjy2t7u/7O4O3JO0LylwEyaPZVbFZsbGD+Y/zrwm6jgiIvnkVaDSzAaaWTlwHjAluUP4jG10JrAoi/lEik5Us7448A8zc+AOd78T2Nfd1wC4+xoz2yf0be6cuZbaa1K0S4H75f3jebJkBZ+u68Y1lzwUdRwRkbzi7vVm9k1gGlACTHL3BWZ2DVDl7lOAb5vZmUA9sB64KLLAIkUgqkL9OHdfHYrx6Wb2Zgt9mztnrq3tH9+x2XgSp8iw//77t5xYctof/not9+54iU/u6MD/XvQksZKSqCOJiOQdd58KTG3S9tOk7auAq7KdS6RYRXLqi7uvDj/fB/5C4hzz9xq/Ugs/3w/dmztnrqX2vinaU+XQ+XMF4LGZd/C72gcZWBfjxnOnaIYXERERKQhZL9TNbE8z26txGzgVeIPEeXCNM7eMAx4P21OAC8PsLyOATeEUmWnAqWbWNVxEeiowLTy22cxGhNleLkzalxSYJ1/8I9cvv4XuDfDL0/5Ez669o45U9Mysn5nNNLNFZrbAzK4I7W2e2UlERKSYRXHqy77AX8KMiaXAfe7+dzN7FXjIzC4FVgLnhP5TgTFANbANuBjA3deb2bUkLn4BuMbd14fty4C7gY7Ak+EmBWbmq4/wi8XXs1fc+PWJEzm4/5FRR5KEeuB77j4n/Kf8NTObTuJc1qfc/fqwNPkE4Id8dGan4SRmbRoeSXIREZEckvVC3d2XAZ9M0b4OGJWi3YHLm9nXJGBSivYq4IjdDis566V/PsnV839KucMNx97KEQeprssV4VutxgvDN5vZIhIXdI8FTgzdJgPPkCjU/z2zEzDLzLqYWa/Gi8tFRESKVS5NzyjSKs9U/YUJVd8H4Lqhv2bIoBMiTiTNMbMBwFHAbJrM7ATsamYnERGRoqZCXfLK31+6lx/P+wkx4H+G/IpjP3l61JGkGWbWCXgEuNLdP2ipa4q2j83UpFUORUSk2KhQl7zx2Mw7+Nni/6FjHH494laOHzwm6kjSDDMrI1Gk3+vuj4bmts7s9BGapUlERIqNCnXJC3f/7VquW/5/dGkwbjpxEkMPPzHqSNKMMNvSRGCRu/8m6aG2zuwkIiJS1KJa8Eik1a6/71Lur5vNgHrjV6feq9ldct9xwFeB+WY2N7T9CLieNszsJCIiUuxUqEvOqq/fyYTJZzKttIbBOzrwm3OnaJ70PODuL5D6vHNo48xOIiIixUyFuuSkdRvf5QcPnsUrHbZyYl0PfnXR37TiqIiIiBQVnaMuOadqwTNc9OdTeLViC2fb4dx8yQwV6SIiIlJ0dERdcsqfnryB3625B0rgv/b5Kl8dMyHqSCIiIiKRUKEuOaGubgfX3HcBT7CYfg0xrj72Jo45/GOnM4uIiIgUDRXqErkFS6u49qmvsaCinuHb9+KGL/2F7l32izqWiIiISKRUqEuk7ppyNX9Y+zA7y+DiDidy5VduIVZSEnUsERERkcipUJdIrK5dwXWPXchz5es5oCHGhOG/YuSRo6OOJSIiIpIzVKhL1k3+23VMfvc+1pUZp+3sx9UX3M9ee3aJOpaIiIhITlGhLlmzas0SfvHExbxUsYn94zH+55DvccbxF0UdS0RERCQnqVCXjKur28HNj3ybx//1AlvLjc82HMCPLrhHR9FFREREWqBCXTJqynMTmfTmzSytcA6tL+OywT/hpGFnRx1LREREJOepUJeMmPfWS/zumR/wYsUmupfE+c9Op/ONr9ygGV1EREREWkmFuqTVslUL+L9p3+HZ0tVYGYyu358ffOEuenbtHXU0ERERkbyiQl3SYnXtCm7965XM4C22lxrH1XXj65/5JUdWjog6moiIiEheUqEuu2XZqgXcPv2HPGdvszUWY+j2Tlw67L85/qjPRh1NREREJK+pUJd2mbdkFpOe/W9eKFlDXQyG1nXiS5+4gtNGXhB1NBEREZGCoEJdWi3e0MCjz9zO1KX3MKd8K1YKw+u68pVhV3H84DFRxxMREREpKCrUZZc2bKrlrqk/4bktL7G8HPYqjXNy/f585VM/ZvAhx0cdT0RERKQgqVCXlOINDUx57i7+seQ+Xitby7ZYjAHARRXHc8np19C1c8+oI4qIiIgUNBXq8hFzF7/Awy/fyKv1i1ldZnQsizNkZzdOq/wyYz/9Nc2DLiIiIpIlKtSFOQuf5Ymq25i7fSHVFQ4Gh8fLOL3jp/jyKRM0B7qIiIhIBFSoF6F4QwPPznmMmQsfYN6OxSytcAAONOMLDGLsMd9gyKATIk4pIiIiUtxUqBeJ99a9wxMv3sHr7z7HopJaaktjAFRinG1H8Llh32DIoZ+KOKWIiIiINFKhXqA2bVnP9Nn38/rKGSzduZzF5TupN2OPsjiD6jpxxp5DGH3MpRx+4NCoo4qIiIhICirUC8R7697hmTl/Zm7NMyzbuYLqsp3UxQwzZ4AZo+r7Maz/6Zxx3MXsucdeUccVERERkV1QoZ6Htm3fyguvT2Hu20/z9pY3WWkbWVXmuBkxcwYS44SGPhzR41hOOear9NvvgKgji4iIiEgbqVDPcavWLGHWgmlUv1dFzba3WeMbWFkWZ0fMAOhcGmfAzo580vtx6D7HcPIxX6Z3z/4RpxYRERGR3aVCPQfEGxqorlnA/KUvsKL2DVZveZt3699nden2f1/0CbB3SZy+9eV8qmE/KjsPZsShZzD4kOM1t7mIiIhIAVKhniV1dTt4c8XrLK2ZS83axazZspzane9Ra1t4t7SBrbEPC/LSEqdv3DiooQsnlPXjgB6DGXroKRzSf7CKchEREZEioUI9Derrd7LsnUWsfHcxa9Yt5d1Nb7PuX2tYX7+OjWxlfWwna0uNBrN/P8fM2Sfm7NNQwbD6HuzbsR/7dzuMw/qP4IiDhtGhYo8IfyMRERERiZoK9Vb6w1+v5d1Ny9i4Yy2b6zfxgW9jc2wHm2JxNpZ8tAgHiMWc7iVO94YyBsY7M6ShKz069qZXlwMZsN8gjjz4eDp36hbRbyMiIiIiua5gC3UzGw3cDJQAd7n79buzv4fefZCaMiMWc7qWOJ3jMfaKV9DbO7K3daFLRXe67dmbfTv3Z0Dvwzl0wBAdFRdpg3SPWRFpu12NQzOrAO4BjgbWAV9y9+XZzilSLAqyUDezEuBW4BSgBnjVzKa4+8L27vPnw2+iy977MKDXIZSXV6QrqoiQmTErIm3TynF4KbDB3Q8ys/OAG4AvZT+tSHGI7bpLXhoGVLv7MnevAx4Axu7WDj9xMgf3P1JFukhmpH3MikibtWYcjgUmh+2HgVFmTc79FJG0KdRCvQ+wKul+TWgTkdykMSsSvdaMw3/3cfd6YBPQPSvpRIpQQZ76AqT6371/rJPZeGB8uLvFzBbvYr89gLW7mS2dcilPLmUB5dmV1uTJ5spZuxyzGq9pl0t5cikL5GeedIzX1nx2turzFfJ+zOZSFlCeXcmlPK3N0qoxW6iFeg3QL+l+X2B1007ufidwZ2t3amZV7j509+OlRy7lyaUsoDy7kmt5aMWY1XhNr1zKk0tZoKjztOazs7FPjZmVAp2B9al2ls9jNpeygPLsSi7lSXeWQj315VWg0swGmlk5cB4wJeJMItI8jVmR6LVmHE4BxoXts4Gn3T3lEXUR2X0FeUTd3evN7JvANBJTTE1y9wURxxKRZmjMikSvuXFoZtcAVe4+BZgI/NHMqkkcST8vusQiha8gC3UAd58KTE3zblv9FV6W5FKeXMoCyrMruZYnE2M2135H5WleLmWBIs6Tahy6+0+TtrcD52To5XPpfc+lLKA8u5JLedKaxfSNlYiIiIhI7inUc9RFRERERPKaCvXAzAab2Swzm2tmVWY2LLSbmd1iZtVmNs/MhiQ9Z5yZLQm3cUntR5vZ/PCcW9q7GISZfcvMFpvZAjP7ZVL7VWHfi83stKT20aGt2swmJLUPNLPZIeeD4SKhdjGz75uZm1mPcD/r74+Z/crM3gyv9xcz65IL700zWVO+brqZWT8zm2lmi8LflytCezczmx5+v+lm1jW0t/nPLdfk2pjVeG0xh8bsR19D41WfsanyaLy2PWvhj1d31y1x+s8/gNPD9hjgmaTtJ0nMHTsCmB3auwHLws+uYbtreOwVYGR4zpON+21jns8AM4CKcH+f8HMQ8E+gAhgILCVx0U9J2D4AKA99BoXnPAScF7ZvBy5r53vUj8RFRiuAHlG9P8CpQGnYvgG4Ier3ppmczb5uBv7+9gKGhO29gLfC+/FLYEJon5D0XrX5zy3XbuTQmEXjVWO2ba+j8arPWI3X3f87VRTjVUfUP+TA3mG7Mx/OHTsWuMcTZgFdzKwXcBow3d3Xu/sGYDowOjy2t7u/7Ik/mXuAs9qR5zLgenffAeDu7yflecDdd7j720A1iWWfUy79HP43fRKJpZ4hsfRze/IA3Aj8gI8ubpH198fd/+GJFfEAZpGY67cxS1TvTSqtWY47Ldx9jbvPCdubgUUkVhBMXu47+fdr059bJjKnQS6NWY3XFmjMfpTGa+TjFXJvzGq8tl1RjFcV6h+6EviVma0Cfg1cFdqbW1K5pfaaFO1tdTDwqfCV0bNmdkw783QHNiYNunblMbMzgXfc/Z9NHorq/Wl0CYn/ubYnS1remxa0ZjnutDOzAcBRwGxgX3dfA4l/bIB9dpEtksztlEtjVuO19TRmk2i86jNW47XdimK8Fuz0jKmY2QxgvxQP/RgYBXzH3R8xs3NJzBV7Ms0vl9zW9rbmKSXx1cgI4BjgITM7oIX9p/pPVzrz/IjE12Efe1obX7dVeVrK4u6Phz4/BuqBe3eRZbffm3bK9P4//oJmnYBHgCvd/YMWTk/c7b+/2ZBLY1bjtf15NGabeTGN16L5jNV4bTlPOxXFeC2qQt3dT27uMTO7B7gi3P0zcFfYbm5J5RrgxCbtz4T2vin6tzXPZcCj4eurV8wsDvRoIQ/NtK8l8bVLafhfbZvzmNknSJyP9s/wF7MvMMcSFwNl5P1p6b0JmcYBnwVGhfeIFrLQTHur35t2as1y3GljZmUk/hG5190fDc3vmVkvd18Tvnpr/Hq3rX9ukcilMavx+rH8rcqTlEtjNonGa3F9xmq8arzS3vHqaT7pPl9vJM45OjFsjwJeC9tn8NGLAl7xDy8KeJvE/8i7hu1u4bFXQ9/GiznGtCPP14FrwvbBJL4uMeBwPnoxxzISF1SUhu2BfHhRxeHh+X/moxdzfGM336vlfHixS9bfHxLndC0EejZpj/y9aZKn2dfNwN9fI3E+4k1N2n/FRy92+WV7/9xy7ZZLY1bjVWO2ja+j8arPWI3X3f87VRTjNfLBmys34HjgtfAHPRs4OukP6FYSVxbPB4YmPecSEhdTVAMXJ7UPBd4Iz/ktJBaWamOecuBPYT9zgJOSHvtx2Pdikq7oJnGl8VvhsR8ntR9A4krw6jBoKnbzvUr+hyTr70/Y3ypgbrjdnivvTYqsKV83Q39/HZiX9L6MIXGO4FPAkvCz8R/zNv+55dotl8asxqvGbDv+7mq8Rvt3MifHrMarxmvTm1YmFRERERHJQZr1RUREREQkB6lQFxERERHJQSrURURERERykAp1EREREZEcpEJdRERERCQHqVCXjLOEF8zs9KS2c83s71HmEpGP03gVyS8as4VN0zNKVpjZESTmUD2KxAIJc4HR7r50N/bZuNqZiKSRxqtIftGYLVwq1CVrzOyXwFZgT2Czu18blim+nMTiEy8B33T3uJndCQwBOgIPuvs1YR81wB0kVk67yd3/HMGvIlLwNF5F8ovGbGEqjTqAFJWfk1gBrg4YGo4AfB441t3rwz8c5wH3kViWd72ZlQIzzexhd18Y9rPV3Y+L4hcQKSIaryL5RWO2AKlQl6xx961m9iCwxd13mNnJwDFAlZlB4n/2q0L3883sUhJ/R3sDg4DGf0QezG5ykeKj8SqSXzRmC5MKdcm2eLgBGDDJ3f87uYOZVQJXAMPcfaOZ/QnokNRla1aSiojGq0h+0ZgtMJr1RaI0AzjXzHoAmFl3M9sf2BvYDHxgZr2A0yLMKCIJGq8i+UVjtgDoiLpExt3nm9nPgRlmFgN2Al8Hqkh8BfcGsAx4MbqUIgIaryL5RmO2MGjWFxERERGRHKRTX0REREREcpAKdRERERGRHKRCXUREREQkB6lQFxERERHJQSrURURERERykAp1EREREZEcpEJdRERERCQHqVAXEREREclB/x/LgxAMOkaydQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x864 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The blue line is the initial balanced-growth path;\n",
      "the orange line is the alternative balanced growth path;\n",
      "the green line is the track of the economy as it transitions\n",
      "from the baseline to the alternative BGP.\n",
      " \n",
      "0.000441 is the baseline labor-force growth rate\n",
      "0.0 is the baseline efficiency-of-labor growth rate\n",
      "0.15 is the baseline savings rate\n",
      " \n",
      "0.000441 is the alternative labor-force growth rate\n",
      "0.0 is the alternative efficiency-of-labor growth rate\n",
      "0.15 is the alternative savings-investment rate\n",
      " \n",
      "0.05 is the depreciation rate\n",
      "0.5 is the orientation-of-growth-toward-capital parameter\n",
      " \n",
      " \n",
      " \n",
      "85.1394697049457  = Labor Force in Year 0\n"
     ]
    }
   ],
   "source": [
    "# FUNCTION FOR CALCULATING AND GRAPHING THE LEVELS OF \n",
    "# SOLOW GROWTH MODEL VARIABLES IN MALTHUSIAN SIMULATIONS\n",
    "#\n",
    "# might as well put \"check that common libraries are active\" as a default header\n",
    "# in every long python code cell...\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import scipy as sp\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "\n",
    "# we are going to want to see what happens for lots of\n",
    "# different model parameter values and base conditions,\n",
    "# so stuff our small simulation program inside a function, so \n",
    "# we can then invoke it with a single line...\n",
    "#\n",
    "# we are going to assume the economy starts on its base\n",
    "# balanced growth path...\n",
    "#\n",
    "# we are going to want to keep track not just of what the\n",
    "# economy's variables are at each point in time, but also \n",
    "# what the base and alternative balanced-growth path \n",
    "# values of variables are. Given the parameters, the new BGP \n",
    "# is attracting the economy to it at the speed (1-α)(n+g+δ), \n",
    "# closing that fraction of the gap between its current state \n",
    "# and the balanced growth path attractor every period...\n",
    "\n",
    "def sgm_malthus_10000yr_run(L0, E0, n=0.000, g=0.00, s=0.15, \n",
    "    alpha=0.5, delta=0.05, Delta_s=0, Delta_g=0, Delta_n=0, \n",
    "    T = 10000, graphs=\"LEVELS\"):\n",
    "\n",
    "    sg_df = pd.DataFrame(index=range(T),columns=['Year',\n",
    "        'Labor', \n",
    "        'Efficiency',\n",
    "        'Capital',\n",
    "        'Output',\n",
    "        'Output_per_Worker',\n",
    "        'Capital_Output_Ratio',\n",
    "        'Population',\n",
    "        'BGP_base_Labor',\n",
    "        'BGP_base_Efficiency',\n",
    "        'BGP_base_Output',\n",
    "        'BGP_base_Output_per_Worker',\n",
    "        'BGP_base_Capital_Output_Ratio',\n",
    "        'BGP_base_Capital',\n",
    "        'BGP_base_Population',\n",
    "        'BGP_alt_Labor',\n",
    "        'BGP_alt_Efficiency',\n",
    "        'BGP_alt_Output',\n",
    "        'BGP_alt_Output_per_Worker',\n",
    "        'BGP_alt_Capital_Output_Ratio',\n",
    "        'BGP_alt_Capital',\n",
    "        'BGP_alt_Population'],\n",
    "        dtype='float')\n",
    "\n",
    "    sg_df.Year[0] = -8000\n",
    "    sg_df.Labor[0] = L0\n",
    "    sg_df.Population[0] = 2 * L0\n",
    "    sg_df.BGP_base_Labor[0] = L0\n",
    "    sg_df.BGP_base_Population[0] = 2 * sg_df.BGP_base_Labor[0]\n",
    "    sg_df.BGP_alt_Labor[0] = L0\n",
    "    sg_df.Efficiency[0] = E0\n",
    "    sg_df.BGP_base_Efficiency[0] = E0\n",
    "    sg_df.BGP_alt_Efficiency[0] = E0\n",
    "    sg_df.BGP_alt_Population[0] = 2 * sg_df.BGP_alt_Labor[0]\n",
    "\n",
    "    KoverY_base_steady_state = s/(n+g+delta)\n",
    "    YoverL_base_steady_state = ((s/(n+g+delta))**(alpha/(1-alpha)) \n",
    "        * E0)\n",
    "    KoverL_base_steady_state = (YoverL_base_steady_state *\n",
    "        KoverY_base_steady_state)\n",
    "    \n",
    "    sg_df.Capital[0] = KoverL_base_steady_state * L0\n",
    "    sg_df.Output[0] = (sg_df.Capital[0]**alpha * (sg_df.Labor[0] * \n",
    "        sg_df.Efficiency[0])**(1-alpha))\n",
    "    sg_df.Output_per_Worker[0] = sg_df.Output[0]/sg_df.Labor[0]\n",
    "    sg_df.Capital_Output_Ratio[0] = sg_df.Capital[0]/sg_df.Output[0]\n",
    "    \n",
    "    sg_df.BGP_base_Capital_Output_Ratio[0] = (s / (n + g + delta))\n",
    "    sg_df.BGP_base_Output_per_Worker[0] = sg_df.Efficiency[0] * (\n",
    "        sg_df.BGP_base_Capital_Output_Ratio[0]*(alpha/(1 - alpha)))\n",
    "    sg_df.BGP_base_Output[0] = sg_df.BGP_base_Output_per_Worker[0] * sg_df.Labor[0]\n",
    "    sg_df.BGP_base_Capital[0] = sg_df.BGP_base_Output[0] * (\n",
    "        sg_df.BGP_base_Capital_Output_Ratio[0])\n",
    "    \n",
    "    sg_df.BGP_alt_Capital_Output_Ratio[0] = ((s + Delta_s) / \n",
    "        (n + Delta_n + g + Delta_g + delta))\n",
    "    sg_df.BGP_alt_Output_per_Worker[0] = sg_df.Efficiency[0] * (\n",
    "        sg_df.BGP_alt_Capital_Output_Ratio[0]*(alpha/(1 - alpha)))\n",
    "    sg_df.BGP_alt_Output[0] = sg_df.BGP_alt_Output_per_Worker[0] * sg_df.Labor[0]\n",
    "    sg_df.BGP_alt_Capital[0] = sg_df.BGP_alt_Output[0] * (\n",
    "        sg_df.BGP_alt_Capital_Output_Ratio[0])\n",
    "    \n",
    "    for i in range(T):\n",
    "        sg_df.Year[i+1] = sg_df.Year[i]+1\n",
    "        sg_df.Labor[i+1] = (sg_df.Labor[i] * np.exp(n + Delta_n))\n",
    "        sg_df.Population[i+1] = 2 * sg_df.Labor[i+1]\n",
    "        sg_df.Efficiency[i+1] = (sg_df.Efficiency[i] * np.exp(g + Delta_g))\n",
    "        KoverY_current = sg_df.Capital[i]/sg_df.Output[i]\n",
    "        sg_df.Capital[i+1] = (sg_df.Capital[i] * np.exp((s+Delta_s)/ \n",
    "            KoverY_current - delta))\n",
    "        sg_df.Output[i+1] = (sg_df.Capital[i+1]**alpha * \n",
    "            (sg_df.Labor[i+1] * sg_df.Efficiency[i+1])**(1-alpha))\n",
    "        sg_df.Output_per_Worker[i+1] = sg_df.Output[i+1]/sg_df.Labor[i+1]\n",
    "        sg_df.Capital_Output_Ratio[i+1] = (sg_df.Capital[i+1]/\n",
    "            sg_df.Output[i+1])\n",
    "\n",
    "    for i in range(T):\n",
    "        sg_df.BGP_base_Labor[i+1] = (sg_df.BGP_base_Labor[i] * np.exp(n))\n",
    "        sg_df.BGP_base_Population[i+1] = 2 * sg_df.BGP_base_Labor[i+1]\n",
    "        sg_df.BGP_base_Efficiency[i+1] = (sg_df.BGP_base_Efficiency[i] * np.exp(g))\n",
    "        sg_df.BGP_base_Capital_Output_Ratio[i+1] = (s / (n + g + delta))\n",
    "        sg_df.BGP_base_Output_per_Worker[i+1] = sg_df.BGP_base_Efficiency[i+1] * (\n",
    "            sg_df.BGP_base_Capital_Output_Ratio[i+1]**(alpha/(1 - alpha)))\n",
    "        sg_df.BGP_base_Output[i+1] = (sg_df.BGP_base_Output_per_Worker[i+1] * \n",
    "            sg_df.BGP_base_Labor[i+1])\n",
    "        sg_df.BGP_base_Capital[i+1] = (s / (n + g + delta))**(1/(1-alpha)) * (\n",
    "            sg_df.Efficiency[i+1] * sg_df.Labor[i+1])\n",
    "\n",
    "    for i in range(T):\n",
    "        sg_df.BGP_alt_Labor[i+1] = (sg_df.BGP_alt_Labor[i] * np.exp(n + Delta_n))\n",
    "        sg_df.BGP_alt_Population[i+1] = 2 * sg_df.BGP_alt_Labor[i+1]\n",
    "        sg_df.BGP_alt_Efficiency[i+1] = (sg_df.BGP_alt_Efficiency[i] * np.exp(g+Delta_g))\n",
    "        sg_df.BGP_alt_Capital_Output_Ratio[i+1] = ((s+ Delta_s) / \n",
    "            (n + Delta_n + g + Delta_g + delta))\n",
    "        sg_df.BGP_alt_Output_per_Worker[i+1] = sg_df.BGP_alt_Efficiency[i+1] * (\n",
    "            sg_df.BGP_alt_Capital_Output_Ratio[i+1]**(alpha/(1 - alpha)))\n",
    "        sg_df.BGP_alt_Output[i+1] = (sg_df.BGP_alt_Output_per_Worker[i+1] * \n",
    "            sg_df.BGP_alt_Labor[i+1])\n",
    "        sg_df.BGP_alt_Capital[i+1] = ((s + Delta_s) / (n + Delta_n + g + Delta_g + delta))**(1/(1-alpha)) * (\n",
    "            sg_df.BGP_alt_Efficiency[i+1] * sg_df.BGP_alt_Labor[i+1])  \n",
    "\n",
    "    sg_df.Population = 2 * sg_df.Labor\n",
    "    \n",
    "    sg_df = sg_df.set_index(\"Year\")\n",
    "        \n",
    "    if (graphs == \"LEVELS\"):\n",
    "        fig = plt.figure(figsize=(12, 12))\n",
    "\n",
    "        ax1 = plt.subplot(2,3,1)\n",
    "        sg_df.BGP_base_Labor.plot(ax = ax1, title = \"BGP (base) Labor\")\n",
    "        sg_df.BGP_alt_Labor.plot(ax = ax1, title = \"BGP (alt) Labor\")\n",
    "        sg_df.Labor.plot(ax = ax1, title = \"Labor Force\")\n",
    "        plt.ylabel(\"Values\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax2 = plt.subplot(2,3,2)\n",
    "        sg_df.BGP_base_Efficiency.plot(ax = ax2, title = \"BGP (base) Efficiency\")\n",
    "        sg_df.BGP_alt_Efficiency.plot(ax = ax2, title = \"BGP (alt) Efficiency\")\n",
    "        sg_df.Efficiency.plot(ax = ax2, title = \"Efficiency of Labor\")\n",
    "        plt.ylim(0, )\n",
    "    \n",
    "        ax3 = plt.subplot(2,3,3)\n",
    "        sg_df.BGP_base_Capital.plot(ax = ax3, title = \"BGP (base) Capital Stock\")\n",
    "        sg_df.BGP_alt_Capital.plot(ax = ax3, title = \"BGP (alt) Capital Stock\")\n",
    "        sg_df.Capital.plot(ax = ax3, title = \"Capital Stock\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax4 = plt.subplot(2,3,4)\n",
    "        sg_df.BGP_base_Output.plot(ax = ax4, title = \"BGP (base) Output\")\n",
    "        sg_df.BGP_alt_Output.plot(ax = ax4, title = \"BGP (alt) Output\")\n",
    "        sg_df.Output.plot(ax = ax4, title = \"Output\")\n",
    "        plt.ylabel(\"Values\")\n",
    "        plt.xlabel(\"Year\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax5 = plt.subplot(2,3,5)\n",
    "        sg_df.BGP_base_Output_per_Worker.plot(ax = ax5, title = \"BGP (base) Output per Worker\")\n",
    "        sg_df.BGP_alt_Output_per_Worker.plot(ax = ax5, title = \"BGP (alt) Output per Worker\")\n",
    "        sg_df.Output_per_Worker.plot(ax = ax5, title = \"Output per Worker\")\n",
    "        plt.xlabel(\"Year\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax6 = plt.subplot(2,3,6)\n",
    "        sg_df.BGP_base_Capital_Output_Ratio.plot(ax = ax6, \n",
    "            title = \"BGP (base) Capital-Output Ratio\")\n",
    "        sg_df.BGP_alt_Capital_Output_Ratio.plot(ax = ax6, \n",
    "            title = \"BGP (alt) Capital-Output Ratio\")\n",
    "        sg_df.Capital_Output_Ratio.plot(ax = ax6, \n",
    "            title = \"Capital-Output Ratio\")\n",
    "        plt.xlabel(\"Year\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        plt.suptitle('Solow Growth Model: Levels: Simulation Run', size = 20)\n",
    "\n",
    "        plt.show()\n",
    "        \n",
    "    if (graphs == \"LOGS\"):\n",
    "        fig = plt.figure(figsize=(12, 12))\n",
    "\n",
    "        ax1 = plt.subplot(2,3,1)\n",
    "        np.log(sg_df.BGP_base_Labor).plot(ax = ax1, title = \"BGP (base) Labor\")\n",
    "        np.log(sg_df.BGP_alt_Labor).plot(ax = ax1, title = \"BGP (alt) Labor\")\n",
    "        np.log(sg_df.Labor).plot(ax = ax1, title = \"Log Labor Force\")\n",
    "        plt.ylabel(\"Values\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax2 = plt.subplot(2,3,2)\n",
    "        np.log(sg_df.BGP_base_Efficiency).plot(ax = ax2, title = \"BGP (base) Efficiency\")\n",
    "        np.log(sg_df.BGP_alt_Efficiency).plot(ax = ax2, title = \"BGP (alt) Efficiency\")\n",
    "        np.log(sg_df.Efficiency).plot(ax = ax2, title = \"Log Efficiency of Labor\")\n",
    "        plt.ylim(0, )\n",
    "    \n",
    "        ax3 = plt.subplot(2,3,3)\n",
    "        np.log(sg_df.BGP_base_Capital).plot(ax = ax3, title = \"BGP (base) Capital Stock\")\n",
    "        np.log(sg_df.BGP_alt_Capital).plot(ax = ax3, title = \"BGP (alt) Capital Stock\")\n",
    "        np.log(sg_df.Capital).plot(ax = ax3, title = \"Log Capital Stock\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax4 = plt.subplot(2,3,4)\n",
    "        np.log(sg_df.BGP_base_Output).plot(ax = ax4, title = \"BGP (base) Output\")\n",
    "        np.log(sg_df.BGP_alt_Output).plot(ax = ax4, title = \"BGP (alt) Output\")\n",
    "        np.log(sg_df.Output).plot(ax = ax4, title = \"Log Output\")\n",
    "        plt.ylabel(\"Values\")\n",
    "        plt.xlabel(\"Year\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax5 = plt.subplot(2,3,5)\n",
    "        np.log(sg_df.BGP_base_Output_per_Worker).plot(ax = ax5, title = \"BGP (base) Output per Worker\")\n",
    "        np.log(sg_df.BGP_alt_Output_per_Worker).plot(ax = ax5, title = \"BGP (alt) Output per Worker\")\n",
    "        np.log(sg_df.Output_per_Worker).plot(ax = ax5, title = \"Log Output per Worker\")\n",
    "        plt.xlabel(\"Year\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        ax6 = plt.subplot(2,3,6)\n",
    "        sg_df.BGP_base_Capital_Output_Ratio.plot(ax = ax6, \n",
    "            title = \"BGP (base) Capital-Output Ratio\")\n",
    "        sg_df.BGP_alt_Capital_Output_Ratio.plot(ax = ax6, \n",
    "            title = \"BGP (alt) Capital-Output Ratio\")\n",
    "        sg_df.Capital_Output_Ratio.plot(ax = ax6, \n",
    "            title = \"Capital-Output Ratio\")\n",
    "        plt.xlabel(\"Year\")\n",
    "        plt.ylim(0, )\n",
    "\n",
    "        plt.suptitle('Solow Growth Model: Logs: Simulation Run', size = 20)\n",
    "\n",
    "        plt.show()\n",
    "    \n",
    "    if ((graphs != \"LEVELS\") and (graphs != \"LOGS\")):\n",
    "        fig = \"NONE\"\n",
    "        \n",
    "    print(\"The blue line is the initial balanced-growth path;\")\n",
    "    print(\"the orange line is the alternative balanced growth path;\")\n",
    "    print(\"the green line is the track of the economy as it transitions\")\n",
    "    print(\"from the baseline to the alternative BGP.\")\n",
    "    print(\" \")\n",
    "    \n",
    "    print(n + Delta_n, \"is the baseline labor-force growth rate\")\n",
    "    print(g + Delta_g, \"is the baseline efficiency-of-labor growth rate\")\n",
    "    print(s + Delta_s, \"is the baseline savings rate\")\n",
    "    print(\" \")\n",
    "          \n",
    "    print(n + Delta_n, \"is the alternative labor-force growth rate\")\n",
    "    print(g + Delta_g, \"is the alternative efficiency-of-labor growth rate\")\n",
    "    print(s + Delta_s, \"is the alternative savings-investment rate\")\n",
    "    print(\" \")\n",
    "    \n",
    "    print(delta, \"is the depreciation rate\")\n",
    "    print(alpha, \"is the orientation-of-growth-toward-capital parameter\")\n",
    "    \n",
    "    \n",
    "    SGM_dict = {}\n",
    "    SGM_dict[\"df\"] = sg_df\n",
    "    SGM_dict[\"plots\"] = fig\n",
    "    \n",
    "    return SGM_dict\n",
    "\n",
    "output = sgm_malthus_10000yr_run(L0=2.5, E0=504.41000009638856, \n",
    "    T = 10019, n= 0.000441 , graphs = \"LEVELS\")\n",
    "\n",
    "print(\" \")\n",
    "print(\" \")\n",
    "print(\" \")\n",
    "print(output[\"df\"].Labor[0], \" = Labor Force in Year 0\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "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>Labor</th>\n",
       "      <th>Efficiency</th>\n",
       "      <th>Capital</th>\n",
       "      <th>Output</th>\n",
       "      <th>Output_per_Worker</th>\n",
       "      <th>Capital_Output_Ratio</th>\n",
       "      <th>Population</th>\n",
       "      <th>BGP_base_Labor</th>\n",
       "      <th>BGP_base_Efficiency</th>\n",
       "      <th>BGP_base_Output</th>\n",
       "      <th>...</th>\n",
       "      <th>BGP_base_Capital_Output_Ratio</th>\n",
       "      <th>BGP_base_Capital</th>\n",
       "      <th>BGP_base_Population</th>\n",
       "      <th>BGP_alt_Labor</th>\n",
       "      <th>BGP_alt_Efficiency</th>\n",
       "      <th>BGP_alt_Output</th>\n",
       "      <th>BGP_alt_Output_per_Worker</th>\n",
       "      <th>BGP_alt_Capital_Output_Ratio</th>\n",
       "      <th>BGP_alt_Capital</th>\n",
       "      <th>BGP_alt_Population</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>-8000.0</th>\n",
       "      <td>2.500000</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11151.642515</td>\n",
       "      <td>3750.000001</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3750.000001</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11151.642515</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>2.500000</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3750.000001</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11151.642515</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7999.0</th>\n",
       "      <td>2.501103</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11156.561474</td>\n",
       "      <td>3751.654115</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.002205</td>\n",
       "      <td>2.501103</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3751.654115</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11156.561474</td>\n",
       "      <td>5.002205</td>\n",
       "      <td>2.501103</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3751.654115</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11156.561474</td>\n",
       "      <td>5.002205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7998.0</th>\n",
       "      <td>2.502206</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11161.482603</td>\n",
       "      <td>3753.308960</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.004412</td>\n",
       "      <td>2.502206</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3753.308960</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11161.482603</td>\n",
       "      <td>5.004412</td>\n",
       "      <td>2.502206</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3753.308960</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11161.482603</td>\n",
       "      <td>5.004412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7997.0</th>\n",
       "      <td>2.503310</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11166.405902</td>\n",
       "      <td>3754.964534</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.006619</td>\n",
       "      <td>2.503310</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3754.964534</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11166.405902</td>\n",
       "      <td>5.006619</td>\n",
       "      <td>2.503310</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3754.964534</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11166.405902</td>\n",
       "      <td>5.006619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7996.0</th>\n",
       "      <td>2.504414</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11171.331373</td>\n",
       "      <td>3756.620839</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.008828</td>\n",
       "      <td>2.504414</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3756.620839</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11171.331373</td>\n",
       "      <td>5.008828</td>\n",
       "      <td>2.504414</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3756.620839</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11171.331373</td>\n",
       "      <td>5.008828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7995.0</th>\n",
       "      <td>2.505519</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11176.259017</td>\n",
       "      <td>3758.277874</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.011037</td>\n",
       "      <td>2.505519</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3758.277874</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11176.259017</td>\n",
       "      <td>5.011037</td>\n",
       "      <td>2.505519</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3758.277874</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11176.259017</td>\n",
       "      <td>5.011037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7994.0</th>\n",
       "      <td>2.506624</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11181.188834</td>\n",
       "      <td>3759.935640</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.013248</td>\n",
       "      <td>2.506624</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3759.935640</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11181.188834</td>\n",
       "      <td>5.013248</td>\n",
       "      <td>2.506624</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3759.935640</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11181.188834</td>\n",
       "      <td>5.013248</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7993.0</th>\n",
       "      <td>2.507729</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11186.120826</td>\n",
       "      <td>3761.594137</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.015459</td>\n",
       "      <td>2.507729</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3761.594137</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11186.120826</td>\n",
       "      <td>5.015459</td>\n",
       "      <td>2.507729</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3761.594137</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11186.120826</td>\n",
       "      <td>5.015459</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7992.0</th>\n",
       "      <td>2.508836</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11191.054993</td>\n",
       "      <td>3763.253366</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.017671</td>\n",
       "      <td>2.508836</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3763.253366</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11191.054993</td>\n",
       "      <td>5.017671</td>\n",
       "      <td>2.508836</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3763.253366</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11191.054993</td>\n",
       "      <td>5.017671</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7991.0</th>\n",
       "      <td>2.509942</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11195.991336</td>\n",
       "      <td>3764.913327</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.019884</td>\n",
       "      <td>2.509942</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3764.913327</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11195.991336</td>\n",
       "      <td>5.019884</td>\n",
       "      <td>2.509942</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3764.913327</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11195.991336</td>\n",
       "      <td>5.019884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7990.0</th>\n",
       "      <td>2.511049</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11200.929857</td>\n",
       "      <td>3766.574020</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.022099</td>\n",
       "      <td>2.511049</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3766.574020</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11200.929857</td>\n",
       "      <td>5.022099</td>\n",
       "      <td>2.511049</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3766.574020</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11200.929857</td>\n",
       "      <td>5.022099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7989.0</th>\n",
       "      <td>2.512157</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11205.870557</td>\n",
       "      <td>3768.235445</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.024314</td>\n",
       "      <td>2.512157</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3768.235445</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11205.870557</td>\n",
       "      <td>5.024314</td>\n",
       "      <td>2.512157</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3768.235445</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11205.870557</td>\n",
       "      <td>5.024314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7988.0</th>\n",
       "      <td>2.513265</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11210.813436</td>\n",
       "      <td>3769.897603</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.026530</td>\n",
       "      <td>2.513265</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3769.897603</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11210.813436</td>\n",
       "      <td>5.026530</td>\n",
       "      <td>2.513265</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3769.897603</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11210.813436</td>\n",
       "      <td>5.026530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7987.0</th>\n",
       "      <td>2.514374</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11215.758495</td>\n",
       "      <td>3771.560495</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.028747</td>\n",
       "      <td>2.514374</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3771.560495</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11215.758495</td>\n",
       "      <td>5.028747</td>\n",
       "      <td>2.514374</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3771.560495</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11215.758495</td>\n",
       "      <td>5.028747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7986.0</th>\n",
       "      <td>2.515483</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11220.705735</td>\n",
       "      <td>3773.224120</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.030965</td>\n",
       "      <td>2.515483</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3773.224120</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11220.705735</td>\n",
       "      <td>5.030965</td>\n",
       "      <td>2.515483</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3773.224120</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11220.705735</td>\n",
       "      <td>5.030965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7985.0</th>\n",
       "      <td>2.516592</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11225.655157</td>\n",
       "      <td>3774.888479</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.033185</td>\n",
       "      <td>2.516592</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3774.888479</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11225.655157</td>\n",
       "      <td>5.033185</td>\n",
       "      <td>2.516592</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3774.888479</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11225.655157</td>\n",
       "      <td>5.033185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7984.0</th>\n",
       "      <td>2.517702</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11230.606763</td>\n",
       "      <td>3776.553572</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.035405</td>\n",
       "      <td>2.517702</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3776.553572</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11230.606763</td>\n",
       "      <td>5.035405</td>\n",
       "      <td>2.517702</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3776.553572</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11230.606763</td>\n",
       "      <td>5.035405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7983.0</th>\n",
       "      <td>2.518813</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11235.560553</td>\n",
       "      <td>3778.219399</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.037626</td>\n",
       "      <td>2.518813</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3778.219399</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11235.560553</td>\n",
       "      <td>5.037626</td>\n",
       "      <td>2.518813</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3778.219399</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11235.560553</td>\n",
       "      <td>5.037626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7982.0</th>\n",
       "      <td>2.519924</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11240.516528</td>\n",
       "      <td>3779.885961</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.039848</td>\n",
       "      <td>2.519924</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3779.885961</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11240.516528</td>\n",
       "      <td>5.039848</td>\n",
       "      <td>2.519924</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3779.885961</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11240.516528</td>\n",
       "      <td>5.039848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7981.0</th>\n",
       "      <td>2.521036</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11245.474689</td>\n",
       "      <td>3781.553258</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.042071</td>\n",
       "      <td>2.521036</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3781.553258</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11245.474689</td>\n",
       "      <td>5.042071</td>\n",
       "      <td>2.521036</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3781.553258</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11245.474689</td>\n",
       "      <td>5.042071</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7980.0</th>\n",
       "      <td>2.522148</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11250.435037</td>\n",
       "      <td>3783.221291</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.044295</td>\n",
       "      <td>2.522148</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3783.221291</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11250.435037</td>\n",
       "      <td>5.044295</td>\n",
       "      <td>2.522148</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3783.221291</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11250.435037</td>\n",
       "      <td>5.044295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7979.0</th>\n",
       "      <td>2.523260</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11255.397573</td>\n",
       "      <td>3784.890060</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.046520</td>\n",
       "      <td>2.523260</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3784.890060</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11255.397573</td>\n",
       "      <td>5.046520</td>\n",
       "      <td>2.523260</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3784.890060</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11255.397573</td>\n",
       "      <td>5.046520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7978.0</th>\n",
       "      <td>2.524373</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11260.362298</td>\n",
       "      <td>3786.559564</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.048746</td>\n",
       "      <td>2.524373</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3786.559564</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11260.362298</td>\n",
       "      <td>5.048746</td>\n",
       "      <td>2.524373</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3786.559564</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11260.362298</td>\n",
       "      <td>5.048746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7977.0</th>\n",
       "      <td>2.525487</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11265.329213</td>\n",
       "      <td>3788.229805</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.050973</td>\n",
       "      <td>2.525487</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3788.229805</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11265.329213</td>\n",
       "      <td>5.050973</td>\n",
       "      <td>2.525487</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3788.229805</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11265.329213</td>\n",
       "      <td>5.050973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7976.0</th>\n",
       "      <td>2.526601</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11270.298318</td>\n",
       "      <td>3789.900783</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.053201</td>\n",
       "      <td>2.526601</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3789.900783</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11270.298318</td>\n",
       "      <td>5.053201</td>\n",
       "      <td>2.526601</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3789.900783</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11270.298318</td>\n",
       "      <td>5.053201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7975.0</th>\n",
       "      <td>2.527715</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11275.269616</td>\n",
       "      <td>3791.572498</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.055430</td>\n",
       "      <td>2.527715</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3791.572498</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11275.269616</td>\n",
       "      <td>5.055430</td>\n",
       "      <td>2.527715</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3791.572498</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11275.269616</td>\n",
       "      <td>5.055430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7974.0</th>\n",
       "      <td>2.528830</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11280.243107</td>\n",
       "      <td>3793.244950</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.057660</td>\n",
       "      <td>2.528830</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3793.244950</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11280.243107</td>\n",
       "      <td>5.057660</td>\n",
       "      <td>2.528830</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3793.244950</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11280.243107</td>\n",
       "      <td>5.057660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7973.0</th>\n",
       "      <td>2.529945</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11285.218791</td>\n",
       "      <td>3794.918140</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.059891</td>\n",
       "      <td>2.529945</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3794.918140</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11285.218791</td>\n",
       "      <td>5.059891</td>\n",
       "      <td>2.529945</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3794.918140</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11285.218791</td>\n",
       "      <td>5.059891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7972.0</th>\n",
       "      <td>2.531061</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11290.196670</td>\n",
       "      <td>3796.592068</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.062123</td>\n",
       "      <td>2.531061</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3796.592068</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11290.196670</td>\n",
       "      <td>5.062123</td>\n",
       "      <td>2.531061</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3796.592068</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11290.196670</td>\n",
       "      <td>5.062123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-7971.0</th>\n",
       "      <td>2.532178</td>\n",
       "      <td>504.41</td>\n",
       "      <td>11295.176745</td>\n",
       "      <td>3798.266734</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>5.064356</td>\n",
       "      <td>2.532178</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3798.266734</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11295.176745</td>\n",
       "      <td>5.064356</td>\n",
       "      <td>2.532178</td>\n",
       "      <td>504.41</td>\n",
       "      <td>3798.266734</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>11295.176745</td>\n",
       "      <td>5.064356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989.0</th>\n",
       "      <td>204.678352</td>\n",
       "      <td>504.41</td>\n",
       "      <td>912999.924439</td>\n",
       "      <td>307017.527924</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>409.356704</td>\n",
       "      <td>204.678352</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307017.527924</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>912999.924439</td>\n",
       "      <td>409.356704</td>\n",
       "      <td>204.678352</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307017.527924</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>912999.924439</td>\n",
       "      <td>409.356704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990.0</th>\n",
       "      <td>204.768635</td>\n",
       "      <td>504.41</td>\n",
       "      <td>913402.646200</td>\n",
       "      <td>307152.952513</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>409.537270</td>\n",
       "      <td>204.768635</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307152.952513</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>913402.646200</td>\n",
       "      <td>409.537270</td>\n",
       "      <td>204.768635</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307152.952513</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>913402.646200</td>\n",
       "      <td>409.537270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991.0</th>\n",
       "      <td>204.858958</td>\n",
       "      <td>504.41</td>\n",
       "      <td>913805.545599</td>\n",
       "      <td>307288.436837</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>409.717916</td>\n",
       "      <td>204.858958</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307288.436837</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>913805.545599</td>\n",
       "      <td>409.717916</td>\n",
       "      <td>204.858958</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307288.436837</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>913805.545599</td>\n",
       "      <td>409.717916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992.0</th>\n",
       "      <td>204.949321</td>\n",
       "      <td>504.41</td>\n",
       "      <td>914208.622717</td>\n",
       "      <td>307423.980923</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>409.898641</td>\n",
       "      <td>204.949321</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307423.980923</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>914208.622717</td>\n",
       "      <td>409.898641</td>\n",
       "      <td>204.949321</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307423.980923</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>914208.622717</td>\n",
       "      <td>409.898641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993.0</th>\n",
       "      <td>205.039723</td>\n",
       "      <td>504.41</td>\n",
       "      <td>914611.877631</td>\n",
       "      <td>307559.584797</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>410.079446</td>\n",
       "      <td>205.039723</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307559.584797</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>914611.877631</td>\n",
       "      <td>410.079446</td>\n",
       "      <td>205.039723</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307559.584797</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>914611.877631</td>\n",
       "      <td>410.079446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994.0</th>\n",
       "      <td>205.130166</td>\n",
       "      <td>504.41</td>\n",
       "      <td>915015.310419</td>\n",
       "      <td>307695.248486</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>410.260331</td>\n",
       "      <td>205.130166</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307695.248486</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>915015.310419</td>\n",
       "      <td>410.260331</td>\n",
       "      <td>205.130166</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307695.248486</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>915015.310419</td>\n",
       "      <td>410.260331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995.0</th>\n",
       "      <td>205.220648</td>\n",
       "      <td>504.41</td>\n",
       "      <td>915418.921161</td>\n",
       "      <td>307830.972015</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>410.441296</td>\n",
       "      <td>205.220648</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307830.972015</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>915418.921161</td>\n",
       "      <td>410.441296</td>\n",
       "      <td>205.220648</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307830.972015</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>915418.921161</td>\n",
       "      <td>410.441296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996.0</th>\n",
       "      <td>205.311170</td>\n",
       "      <td>504.41</td>\n",
       "      <td>915822.709934</td>\n",
       "      <td>307966.755412</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>410.622340</td>\n",
       "      <td>205.311170</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307966.755412</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>915822.709934</td>\n",
       "      <td>410.622340</td>\n",
       "      <td>205.311170</td>\n",
       "      <td>504.41</td>\n",
       "      <td>307966.755412</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>915822.709934</td>\n",
       "      <td>410.622340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997.0</th>\n",
       "      <td>205.401732</td>\n",
       "      <td>504.41</td>\n",
       "      <td>916226.676817</td>\n",
       "      <td>308102.598702</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>410.803465</td>\n",
       "      <td>205.401732</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308102.598702</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>916226.676817</td>\n",
       "      <td>410.803465</td>\n",
       "      <td>205.401732</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308102.598702</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>916226.676817</td>\n",
       "      <td>410.803465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998.0</th>\n",
       "      <td>205.492335</td>\n",
       "      <td>504.41</td>\n",
       "      <td>916630.821889</td>\n",
       "      <td>308238.501913</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>410.984669</td>\n",
       "      <td>205.492335</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308238.501913</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>916630.821889</td>\n",
       "      <td>410.984669</td>\n",
       "      <td>205.492335</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308238.501913</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>916630.821889</td>\n",
       "      <td>410.984669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999.0</th>\n",
       "      <td>205.582977</td>\n",
       "      <td>504.41</td>\n",
       "      <td>917035.145228</td>\n",
       "      <td>308374.465070</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>411.165953</td>\n",
       "      <td>205.582977</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308374.465070</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>917035.145228</td>\n",
       "      <td>411.165953</td>\n",
       "      <td>205.582977</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308374.465070</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>917035.145228</td>\n",
       "      <td>411.165953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000.0</th>\n",
       "      <td>205.673659</td>\n",
       "      <td>504.41</td>\n",
       "      <td>917439.646913</td>\n",
       "      <td>308510.488200</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>411.347318</td>\n",
       "      <td>205.673659</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308510.488200</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>917439.646913</td>\n",
       "      <td>411.347318</td>\n",
       "      <td>205.673659</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308510.488200</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>917439.646913</td>\n",
       "      <td>411.347318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001.0</th>\n",
       "      <td>205.764381</td>\n",
       "      <td>504.41</td>\n",
       "      <td>917844.327023</td>\n",
       "      <td>308646.571329</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>411.528762</td>\n",
       "      <td>205.764381</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308646.571329</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>917844.327023</td>\n",
       "      <td>411.528762</td>\n",
       "      <td>205.764381</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308646.571329</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>917844.327023</td>\n",
       "      <td>411.528762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002.0</th>\n",
       "      <td>205.855143</td>\n",
       "      <td>504.41</td>\n",
       "      <td>918249.185636</td>\n",
       "      <td>308782.714484</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>411.710286</td>\n",
       "      <td>205.855143</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308782.714484</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>918249.185636</td>\n",
       "      <td>411.710286</td>\n",
       "      <td>205.855143</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308782.714484</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>918249.185636</td>\n",
       "      <td>411.710286</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003.0</th>\n",
       "      <td>205.945945</td>\n",
       "      <td>504.41</td>\n",
       "      <td>918654.222831</td>\n",
       "      <td>308918.917692</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>411.891890</td>\n",
       "      <td>205.945945</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308918.917692</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>918654.222831</td>\n",
       "      <td>411.891890</td>\n",
       "      <td>205.945945</td>\n",
       "      <td>504.41</td>\n",
       "      <td>308918.917692</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>918654.222831</td>\n",
       "      <td>411.891890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004.0</th>\n",
       "      <td>206.036787</td>\n",
       "      <td>504.41</td>\n",
       "      <td>919059.438687</td>\n",
       "      <td>309055.180979</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>412.073575</td>\n",
       "      <td>206.036787</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309055.180979</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>919059.438687</td>\n",
       "      <td>412.073575</td>\n",
       "      <td>206.036787</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309055.180979</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>919059.438687</td>\n",
       "      <td>412.073575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005.0</th>\n",
       "      <td>206.127670</td>\n",
       "      <td>504.41</td>\n",
       "      <td>919464.833282</td>\n",
       "      <td>309191.504371</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>412.255339</td>\n",
       "      <td>206.127670</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309191.504371</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>919464.833282</td>\n",
       "      <td>412.255339</td>\n",
       "      <td>206.127670</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309191.504371</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>919464.833282</td>\n",
       "      <td>412.255339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006.0</th>\n",
       "      <td>206.218592</td>\n",
       "      <td>504.41</td>\n",
       "      <td>919870.406696</td>\n",
       "      <td>309327.887894</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>412.437184</td>\n",
       "      <td>206.218592</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309327.887894</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>919870.406696</td>\n",
       "      <td>412.437184</td>\n",
       "      <td>206.218592</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309327.887894</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>919870.406696</td>\n",
       "      <td>412.437184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007.0</th>\n",
       "      <td>206.309554</td>\n",
       "      <td>504.41</td>\n",
       "      <td>920276.159007</td>\n",
       "      <td>309464.331576</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>412.619109</td>\n",
       "      <td>206.309554</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309464.331576</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>920276.159007</td>\n",
       "      <td>412.619109</td>\n",
       "      <td>206.309554</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309464.331576</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>920276.159007</td>\n",
       "      <td>412.619109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008.0</th>\n",
       "      <td>206.400557</td>\n",
       "      <td>504.41</td>\n",
       "      <td>920682.090294</td>\n",
       "      <td>309600.835444</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>412.801114</td>\n",
       "      <td>206.400557</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309600.835444</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>920682.090294</td>\n",
       "      <td>412.801114</td>\n",
       "      <td>206.400557</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309600.835444</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>920682.090294</td>\n",
       "      <td>412.801114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009.0</th>\n",
       "      <td>206.491600</td>\n",
       "      <td>504.41</td>\n",
       "      <td>921088.200637</td>\n",
       "      <td>309737.399522</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>412.983199</td>\n",
       "      <td>206.491600</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309737.399522</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>921088.200637</td>\n",
       "      <td>412.983199</td>\n",
       "      <td>206.491600</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309737.399522</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>921088.200637</td>\n",
       "      <td>412.983199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010.0</th>\n",
       "      <td>206.582683</td>\n",
       "      <td>504.41</td>\n",
       "      <td>921494.490114</td>\n",
       "      <td>309874.023839</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>413.165365</td>\n",
       "      <td>206.582683</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309874.023839</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>921494.490114</td>\n",
       "      <td>413.165365</td>\n",
       "      <td>206.582683</td>\n",
       "      <td>504.41</td>\n",
       "      <td>309874.023839</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>921494.490114</td>\n",
       "      <td>413.165365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011.0</th>\n",
       "      <td>206.673806</td>\n",
       "      <td>504.41</td>\n",
       "      <td>921900.958804</td>\n",
       "      <td>310010.708420</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>413.347611</td>\n",
       "      <td>206.673806</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310010.708420</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>921900.958804</td>\n",
       "      <td>413.347611</td>\n",
       "      <td>206.673806</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310010.708420</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>921900.958804</td>\n",
       "      <td>413.347611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012.0</th>\n",
       "      <td>206.764969</td>\n",
       "      <td>504.41</td>\n",
       "      <td>922307.606786</td>\n",
       "      <td>310147.453293</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>413.529938</td>\n",
       "      <td>206.764969</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310147.453293</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>922307.606786</td>\n",
       "      <td>413.529938</td>\n",
       "      <td>206.764969</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310147.453293</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>922307.606786</td>\n",
       "      <td>413.529938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013.0</th>\n",
       "      <td>206.856172</td>\n",
       "      <td>504.41</td>\n",
       "      <td>922714.434139</td>\n",
       "      <td>310284.258483</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>413.712345</td>\n",
       "      <td>206.856172</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310284.258483</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>922714.434139</td>\n",
       "      <td>413.712345</td>\n",
       "      <td>206.856172</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310284.258483</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>922714.434139</td>\n",
       "      <td>413.712345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014.0</th>\n",
       "      <td>206.947416</td>\n",
       "      <td>504.41</td>\n",
       "      <td>923121.440943</td>\n",
       "      <td>310421.124017</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>413.894832</td>\n",
       "      <td>206.947416</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310421.124017</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>923121.440943</td>\n",
       "      <td>413.894832</td>\n",
       "      <td>206.947416</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310421.124017</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>923121.440943</td>\n",
       "      <td>413.894832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015.0</th>\n",
       "      <td>207.038700</td>\n",
       "      <td>504.41</td>\n",
       "      <td>923528.627276</td>\n",
       "      <td>310558.049923</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>414.077400</td>\n",
       "      <td>207.038700</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310558.049923</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>923528.627276</td>\n",
       "      <td>414.077400</td>\n",
       "      <td>207.038700</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310558.049923</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>923528.627276</td>\n",
       "      <td>414.077400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016.0</th>\n",
       "      <td>207.130024</td>\n",
       "      <td>504.41</td>\n",
       "      <td>923935.993219</td>\n",
       "      <td>310695.036226</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>414.260048</td>\n",
       "      <td>207.130024</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310695.036226</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>923935.993219</td>\n",
       "      <td>414.260048</td>\n",
       "      <td>207.130024</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310695.036226</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>923935.993219</td>\n",
       "      <td>414.260048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017.0</th>\n",
       "      <td>207.221389</td>\n",
       "      <td>504.41</td>\n",
       "      <td>924343.538849</td>\n",
       "      <td>310832.082954</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>414.442777</td>\n",
       "      <td>207.221389</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310832.082954</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>924343.538849</td>\n",
       "      <td>414.442777</td>\n",
       "      <td>207.221389</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310832.082954</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>924343.538849</td>\n",
       "      <td>414.442777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018.0</th>\n",
       "      <td>207.312793</td>\n",
       "      <td>504.41</td>\n",
       "      <td>924751.264246</td>\n",
       "      <td>310969.190132</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>414.625587</td>\n",
       "      <td>207.312793</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310969.190132</td>\n",
       "      <td>...</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>924751.264246</td>\n",
       "      <td>414.625587</td>\n",
       "      <td>207.312793</td>\n",
       "      <td>504.41</td>\n",
       "      <td>310969.190132</td>\n",
       "      <td>1500.0</td>\n",
       "      <td>2.973771</td>\n",
       "      <td>924751.264246</td>\n",
       "      <td>414.625587</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10019 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              Labor  Efficiency        Capital         Output  \\\n",
       "Year                                                            \n",
       "-8000.0    2.500000      504.41   11151.642515    3750.000001   \n",
       "-7999.0    2.501103      504.41   11156.561474    3751.654115   \n",
       "-7998.0    2.502206      504.41   11161.482603    3753.308960   \n",
       "-7997.0    2.503310      504.41   11166.405902    3754.964534   \n",
       "-7996.0    2.504414      504.41   11171.331373    3756.620839   \n",
       "-7995.0    2.505519      504.41   11176.259017    3758.277874   \n",
       "-7994.0    2.506624      504.41   11181.188834    3759.935640   \n",
       "-7993.0    2.507729      504.41   11186.120826    3761.594137   \n",
       "-7992.0    2.508836      504.41   11191.054993    3763.253366   \n",
       "-7991.0    2.509942      504.41   11195.991336    3764.913327   \n",
       "-7990.0    2.511049      504.41   11200.929857    3766.574020   \n",
       "-7989.0    2.512157      504.41   11205.870557    3768.235445   \n",
       "-7988.0    2.513265      504.41   11210.813436    3769.897603   \n",
       "-7987.0    2.514374      504.41   11215.758495    3771.560495   \n",
       "-7986.0    2.515483      504.41   11220.705735    3773.224120   \n",
       "-7985.0    2.516592      504.41   11225.655157    3774.888479   \n",
       "-7984.0    2.517702      504.41   11230.606763    3776.553572   \n",
       "-7983.0    2.518813      504.41   11235.560553    3778.219399   \n",
       "-7982.0    2.519924      504.41   11240.516528    3779.885961   \n",
       "-7981.0    2.521036      504.41   11245.474689    3781.553258   \n",
       "-7980.0    2.522148      504.41   11250.435037    3783.221291   \n",
       "-7979.0    2.523260      504.41   11255.397573    3784.890060   \n",
       "-7978.0    2.524373      504.41   11260.362298    3786.559564   \n",
       "-7977.0    2.525487      504.41   11265.329213    3788.229805   \n",
       "-7976.0    2.526601      504.41   11270.298318    3789.900783   \n",
       "-7975.0    2.527715      504.41   11275.269616    3791.572498   \n",
       "-7974.0    2.528830      504.41   11280.243107    3793.244950   \n",
       "-7973.0    2.529945      504.41   11285.218791    3794.918140   \n",
       "-7972.0    2.531061      504.41   11290.196670    3796.592068   \n",
       "-7971.0    2.532178      504.41   11295.176745    3798.266734   \n",
       "...             ...         ...            ...            ...   \n",
       " 1989.0  204.678352      504.41  912999.924439  307017.527924   \n",
       " 1990.0  204.768635      504.41  913402.646200  307152.952513   \n",
       " 1991.0  204.858958      504.41  913805.545599  307288.436837   \n",
       " 1992.0  204.949321      504.41  914208.622717  307423.980923   \n",
       " 1993.0  205.039723      504.41  914611.877631  307559.584797   \n",
       " 1994.0  205.130166      504.41  915015.310419  307695.248486   \n",
       " 1995.0  205.220648      504.41  915418.921161  307830.972015   \n",
       " 1996.0  205.311170      504.41  915822.709934  307966.755412   \n",
       " 1997.0  205.401732      504.41  916226.676817  308102.598702   \n",
       " 1998.0  205.492335      504.41  916630.821889  308238.501913   \n",
       " 1999.0  205.582977      504.41  917035.145228  308374.465070   \n",
       " 2000.0  205.673659      504.41  917439.646913  308510.488200   \n",
       " 2001.0  205.764381      504.41  917844.327023  308646.571329   \n",
       " 2002.0  205.855143      504.41  918249.185636  308782.714484   \n",
       " 2003.0  205.945945      504.41  918654.222831  308918.917692   \n",
       " 2004.0  206.036787      504.41  919059.438687  309055.180979   \n",
       " 2005.0  206.127670      504.41  919464.833282  309191.504371   \n",
       " 2006.0  206.218592      504.41  919870.406696  309327.887894   \n",
       " 2007.0  206.309554      504.41  920276.159007  309464.331576   \n",
       " 2008.0  206.400557      504.41  920682.090294  309600.835444   \n",
       " 2009.0  206.491600      504.41  921088.200637  309737.399522   \n",
       " 2010.0  206.582683      504.41  921494.490114  309874.023839   \n",
       " 2011.0  206.673806      504.41  921900.958804  310010.708420   \n",
       " 2012.0  206.764969      504.41  922307.606786  310147.453293   \n",
       " 2013.0  206.856172      504.41  922714.434139  310284.258483   \n",
       " 2014.0  206.947416      504.41  923121.440943  310421.124017   \n",
       " 2015.0  207.038700      504.41  923528.627276  310558.049923   \n",
       " 2016.0  207.130024      504.41  923935.993219  310695.036226   \n",
       " 2017.0  207.221389      504.41  924343.538849  310832.082954   \n",
       " 2018.0  207.312793      504.41  924751.264246  310969.190132   \n",
       "\n",
       "         Output_per_Worker  Capital_Output_Ratio  Population  BGP_base_Labor  \\\n",
       "Year                                                                           \n",
       "-8000.0             1500.0              2.973771    5.000000        2.500000   \n",
       "-7999.0             1500.0              2.973771    5.002205        2.501103   \n",
       "-7998.0             1500.0              2.973771    5.004412        2.502206   \n",
       "-7997.0             1500.0              2.973771    5.006619        2.503310   \n",
       "-7996.0             1500.0              2.973771    5.008828        2.504414   \n",
       "-7995.0             1500.0              2.973771    5.011037        2.505519   \n",
       "-7994.0             1500.0              2.973771    5.013248        2.506624   \n",
       "-7993.0             1500.0              2.973771    5.015459        2.507729   \n",
       "-7992.0             1500.0              2.973771    5.017671        2.508836   \n",
       "-7991.0             1500.0              2.973771    5.019884        2.509942   \n",
       "-7990.0             1500.0              2.973771    5.022099        2.511049   \n",
       "-7989.0             1500.0              2.973771    5.024314        2.512157   \n",
       "-7988.0             1500.0              2.973771    5.026530        2.513265   \n",
       "-7987.0             1500.0              2.973771    5.028747        2.514374   \n",
       "-7986.0             1500.0              2.973771    5.030965        2.515483   \n",
       "-7985.0             1500.0              2.973771    5.033185        2.516592   \n",
       "-7984.0             1500.0              2.973771    5.035405        2.517702   \n",
       "-7983.0             1500.0              2.973771    5.037626        2.518813   \n",
       "-7982.0             1500.0              2.973771    5.039848        2.519924   \n",
       "-7981.0             1500.0              2.973771    5.042071        2.521036   \n",
       "-7980.0             1500.0              2.973771    5.044295        2.522148   \n",
       "-7979.0             1500.0              2.973771    5.046520        2.523260   \n",
       "-7978.0             1500.0              2.973771    5.048746        2.524373   \n",
       "-7977.0             1500.0              2.973771    5.050973        2.525487   \n",
       "-7976.0             1500.0              2.973771    5.053201        2.526601   \n",
       "-7975.0             1500.0              2.973771    5.055430        2.527715   \n",
       "-7974.0             1500.0              2.973771    5.057660        2.528830   \n",
       "-7973.0             1500.0              2.973771    5.059891        2.529945   \n",
       "-7972.0             1500.0              2.973771    5.062123        2.531061   \n",
       "-7971.0             1500.0              2.973771    5.064356        2.532178   \n",
       "...                    ...                   ...         ...             ...   \n",
       " 1989.0             1500.0              2.973771  409.356704      204.678352   \n",
       " 1990.0             1500.0              2.973771  409.537270      204.768635   \n",
       " 1991.0             1500.0              2.973771  409.717916      204.858958   \n",
       " 1992.0             1500.0              2.973771  409.898641      204.949321   \n",
       " 1993.0             1500.0              2.973771  410.079446      205.039723   \n",
       " 1994.0             1500.0              2.973771  410.260331      205.130166   \n",
       " 1995.0             1500.0              2.973771  410.441296      205.220648   \n",
       " 1996.0             1500.0              2.973771  410.622340      205.311170   \n",
       " 1997.0             1500.0              2.973771  410.803465      205.401732   \n",
       " 1998.0             1500.0              2.973771  410.984669      205.492335   \n",
       " 1999.0             1500.0              2.973771  411.165953      205.582977   \n",
       " 2000.0             1500.0              2.973771  411.347318      205.673659   \n",
       " 2001.0             1500.0              2.973771  411.528762      205.764381   \n",
       " 2002.0             1500.0              2.973771  411.710286      205.855143   \n",
       " 2003.0             1500.0              2.973771  411.891890      205.945945   \n",
       " 2004.0             1500.0              2.973771  412.073575      206.036787   \n",
       " 2005.0             1500.0              2.973771  412.255339      206.127670   \n",
       " 2006.0             1500.0              2.973771  412.437184      206.218592   \n",
       " 2007.0             1500.0              2.973771  412.619109      206.309554   \n",
       " 2008.0             1500.0              2.973771  412.801114      206.400557   \n",
       " 2009.0             1500.0              2.973771  412.983199      206.491600   \n",
       " 2010.0             1500.0              2.973771  413.165365      206.582683   \n",
       " 2011.0             1500.0              2.973771  413.347611      206.673806   \n",
       " 2012.0             1500.0              2.973771  413.529938      206.764969   \n",
       " 2013.0             1500.0              2.973771  413.712345      206.856172   \n",
       " 2014.0             1500.0              2.973771  413.894832      206.947416   \n",
       " 2015.0             1500.0              2.973771  414.077400      207.038700   \n",
       " 2016.0             1500.0              2.973771  414.260048      207.130024   \n",
       " 2017.0             1500.0              2.973771  414.442777      207.221389   \n",
       " 2018.0             1500.0              2.973771  414.625587      207.312793   \n",
       "\n",
       "         BGP_base_Efficiency  BGP_base_Output         ...          \\\n",
       "Year                                                  ...           \n",
       "-8000.0               504.41      3750.000001         ...           \n",
       "-7999.0               504.41      3751.654115         ...           \n",
       "-7998.0               504.41      3753.308960         ...           \n",
       "-7997.0               504.41      3754.964534         ...           \n",
       "-7996.0               504.41      3756.620839         ...           \n",
       "-7995.0               504.41      3758.277874         ...           \n",
       "-7994.0               504.41      3759.935640         ...           \n",
       "-7993.0               504.41      3761.594137         ...           \n",
       "-7992.0               504.41      3763.253366         ...           \n",
       "-7991.0               504.41      3764.913327         ...           \n",
       "-7990.0               504.41      3766.574020         ...           \n",
       "-7989.0               504.41      3768.235445         ...           \n",
       "-7988.0               504.41      3769.897603         ...           \n",
       "-7987.0               504.41      3771.560495         ...           \n",
       "-7986.0               504.41      3773.224120         ...           \n",
       "-7985.0               504.41      3774.888479         ...           \n",
       "-7984.0               504.41      3776.553572         ...           \n",
       "-7983.0               504.41      3778.219399         ...           \n",
       "-7982.0               504.41      3779.885961         ...           \n",
       "-7981.0               504.41      3781.553258         ...           \n",
       "-7980.0               504.41      3783.221291         ...           \n",
       "-7979.0               504.41      3784.890060         ...           \n",
       "-7978.0               504.41      3786.559564         ...           \n",
       "-7977.0               504.41      3788.229805         ...           \n",
       "-7976.0               504.41      3789.900783         ...           \n",
       "-7975.0               504.41      3791.572498         ...           \n",
       "-7974.0               504.41      3793.244950         ...           \n",
       "-7973.0               504.41      3794.918140         ...           \n",
       "-7972.0               504.41      3796.592068         ...           \n",
       "-7971.0               504.41      3798.266734         ...           \n",
       "...                      ...              ...         ...           \n",
       " 1989.0               504.41    307017.527924         ...           \n",
       " 1990.0               504.41    307152.952513         ...           \n",
       " 1991.0               504.41    307288.436837         ...           \n",
       " 1992.0               504.41    307423.980923         ...           \n",
       " 1993.0               504.41    307559.584797         ...           \n",
       " 1994.0               504.41    307695.248486         ...           \n",
       " 1995.0               504.41    307830.972015         ...           \n",
       " 1996.0               504.41    307966.755412         ...           \n",
       " 1997.0               504.41    308102.598702         ...           \n",
       " 1998.0               504.41    308238.501913         ...           \n",
       " 1999.0               504.41    308374.465070         ...           \n",
       " 2000.0               504.41    308510.488200         ...           \n",
       " 2001.0               504.41    308646.571329         ...           \n",
       " 2002.0               504.41    308782.714484         ...           \n",
       " 2003.0               504.41    308918.917692         ...           \n",
       " 2004.0               504.41    309055.180979         ...           \n",
       " 2005.0               504.41    309191.504371         ...           \n",
       " 2006.0               504.41    309327.887894         ...           \n",
       " 2007.0               504.41    309464.331576         ...           \n",
       " 2008.0               504.41    309600.835444         ...           \n",
       " 2009.0               504.41    309737.399522         ...           \n",
       " 2010.0               504.41    309874.023839         ...           \n",
       " 2011.0               504.41    310010.708420         ...           \n",
       " 2012.0               504.41    310147.453293         ...           \n",
       " 2013.0               504.41    310284.258483         ...           \n",
       " 2014.0               504.41    310421.124017         ...           \n",
       " 2015.0               504.41    310558.049923         ...           \n",
       " 2016.0               504.41    310695.036226         ...           \n",
       " 2017.0               504.41    310832.082954         ...           \n",
       " 2018.0               504.41    310969.190132         ...           \n",
       "\n",
       "         BGP_base_Capital_Output_Ratio  BGP_base_Capital  BGP_base_Population  \\\n",
       "Year                                                                            \n",
       "-8000.0                       2.973771      11151.642515             5.000000   \n",
       "-7999.0                       2.973771      11156.561474             5.002205   \n",
       "-7998.0                       2.973771      11161.482603             5.004412   \n",
       "-7997.0                       2.973771      11166.405902             5.006619   \n",
       "-7996.0                       2.973771      11171.331373             5.008828   \n",
       "-7995.0                       2.973771      11176.259017             5.011037   \n",
       "-7994.0                       2.973771      11181.188834             5.013248   \n",
       "-7993.0                       2.973771      11186.120826             5.015459   \n",
       "-7992.0                       2.973771      11191.054993             5.017671   \n",
       "-7991.0                       2.973771      11195.991336             5.019884   \n",
       "-7990.0                       2.973771      11200.929857             5.022099   \n",
       "-7989.0                       2.973771      11205.870557             5.024314   \n",
       "-7988.0                       2.973771      11210.813436             5.026530   \n",
       "-7987.0                       2.973771      11215.758495             5.028747   \n",
       "-7986.0                       2.973771      11220.705735             5.030965   \n",
       "-7985.0                       2.973771      11225.655157             5.033185   \n",
       "-7984.0                       2.973771      11230.606763             5.035405   \n",
       "-7983.0                       2.973771      11235.560553             5.037626   \n",
       "-7982.0                       2.973771      11240.516528             5.039848   \n",
       "-7981.0                       2.973771      11245.474689             5.042071   \n",
       "-7980.0                       2.973771      11250.435037             5.044295   \n",
       "-7979.0                       2.973771      11255.397573             5.046520   \n",
       "-7978.0                       2.973771      11260.362298             5.048746   \n",
       "-7977.0                       2.973771      11265.329213             5.050973   \n",
       "-7976.0                       2.973771      11270.298318             5.053201   \n",
       "-7975.0                       2.973771      11275.269616             5.055430   \n",
       "-7974.0                       2.973771      11280.243107             5.057660   \n",
       "-7973.0                       2.973771      11285.218791             5.059891   \n",
       "-7972.0                       2.973771      11290.196670             5.062123   \n",
       "-7971.0                       2.973771      11295.176745             5.064356   \n",
       "...                                ...               ...                  ...   \n",
       " 1989.0                       2.973771     912999.924439           409.356704   \n",
       " 1990.0                       2.973771     913402.646200           409.537270   \n",
       " 1991.0                       2.973771     913805.545599           409.717916   \n",
       " 1992.0                       2.973771     914208.622717           409.898641   \n",
       " 1993.0                       2.973771     914611.877631           410.079446   \n",
       " 1994.0                       2.973771     915015.310419           410.260331   \n",
       " 1995.0                       2.973771     915418.921161           410.441296   \n",
       " 1996.0                       2.973771     915822.709934           410.622340   \n",
       " 1997.0                       2.973771     916226.676817           410.803465   \n",
       " 1998.0                       2.973771     916630.821889           410.984669   \n",
       " 1999.0                       2.973771     917035.145228           411.165953   \n",
       " 2000.0                       2.973771     917439.646913           411.347318   \n",
       " 2001.0                       2.973771     917844.327023           411.528762   \n",
       " 2002.0                       2.973771     918249.185636           411.710286   \n",
       " 2003.0                       2.973771     918654.222831           411.891890   \n",
       " 2004.0                       2.973771     919059.438687           412.073575   \n",
       " 2005.0                       2.973771     919464.833282           412.255339   \n",
       " 2006.0                       2.973771     919870.406696           412.437184   \n",
       " 2007.0                       2.973771     920276.159007           412.619109   \n",
       " 2008.0                       2.973771     920682.090294           412.801114   \n",
       " 2009.0                       2.973771     921088.200637           412.983199   \n",
       " 2010.0                       2.973771     921494.490114           413.165365   \n",
       " 2011.0                       2.973771     921900.958804           413.347611   \n",
       " 2012.0                       2.973771     922307.606786           413.529938   \n",
       " 2013.0                       2.973771     922714.434139           413.712345   \n",
       " 2014.0                       2.973771     923121.440943           413.894832   \n",
       " 2015.0                       2.973771     923528.627276           414.077400   \n",
       " 2016.0                       2.973771     923935.993219           414.260048   \n",
       " 2017.0                       2.973771     924343.538849           414.442777   \n",
       " 2018.0                       2.973771     924751.264246           414.625587   \n",
       "\n",
       "         BGP_alt_Labor  BGP_alt_Efficiency  BGP_alt_Output  \\\n",
       "Year                                                         \n",
       "-8000.0       2.500000              504.41     3750.000001   \n",
       "-7999.0       2.501103              504.41     3751.654115   \n",
       "-7998.0       2.502206              504.41     3753.308960   \n",
       "-7997.0       2.503310              504.41     3754.964534   \n",
       "-7996.0       2.504414              504.41     3756.620839   \n",
       "-7995.0       2.505519              504.41     3758.277874   \n",
       "-7994.0       2.506624              504.41     3759.935640   \n",
       "-7993.0       2.507729              504.41     3761.594137   \n",
       "-7992.0       2.508836              504.41     3763.253366   \n",
       "-7991.0       2.509942              504.41     3764.913327   \n",
       "-7990.0       2.511049              504.41     3766.574020   \n",
       "-7989.0       2.512157              504.41     3768.235445   \n",
       "-7988.0       2.513265              504.41     3769.897603   \n",
       "-7987.0       2.514374              504.41     3771.560495   \n",
       "-7986.0       2.515483              504.41     3773.224120   \n",
       "-7985.0       2.516592              504.41     3774.888479   \n",
       "-7984.0       2.517702              504.41     3776.553572   \n",
       "-7983.0       2.518813              504.41     3778.219399   \n",
       "-7982.0       2.519924              504.41     3779.885961   \n",
       "-7981.0       2.521036              504.41     3781.553258   \n",
       "-7980.0       2.522148              504.41     3783.221291   \n",
       "-7979.0       2.523260              504.41     3784.890060   \n",
       "-7978.0       2.524373              504.41     3786.559564   \n",
       "-7977.0       2.525487              504.41     3788.229805   \n",
       "-7976.0       2.526601              504.41     3789.900783   \n",
       "-7975.0       2.527715              504.41     3791.572498   \n",
       "-7974.0       2.528830              504.41     3793.244950   \n",
       "-7973.0       2.529945              504.41     3794.918140   \n",
       "-7972.0       2.531061              504.41     3796.592068   \n",
       "-7971.0       2.532178              504.41     3798.266734   \n",
       "...                ...                 ...             ...   \n",
       " 1989.0     204.678352              504.41   307017.527924   \n",
       " 1990.0     204.768635              504.41   307152.952513   \n",
       " 1991.0     204.858958              504.41   307288.436837   \n",
       " 1992.0     204.949321              504.41   307423.980923   \n",
       " 1993.0     205.039723              504.41   307559.584797   \n",
       " 1994.0     205.130166              504.41   307695.248486   \n",
       " 1995.0     205.220648              504.41   307830.972015   \n",
       " 1996.0     205.311170              504.41   307966.755412   \n",
       " 1997.0     205.401732              504.41   308102.598702   \n",
       " 1998.0     205.492335              504.41   308238.501913   \n",
       " 1999.0     205.582977              504.41   308374.465070   \n",
       " 2000.0     205.673659              504.41   308510.488200   \n",
       " 2001.0     205.764381              504.41   308646.571329   \n",
       " 2002.0     205.855143              504.41   308782.714484   \n",
       " 2003.0     205.945945              504.41   308918.917692   \n",
       " 2004.0     206.036787              504.41   309055.180979   \n",
       " 2005.0     206.127670              504.41   309191.504371   \n",
       " 2006.0     206.218592              504.41   309327.887894   \n",
       " 2007.0     206.309554              504.41   309464.331576   \n",
       " 2008.0     206.400557              504.41   309600.835444   \n",
       " 2009.0     206.491600              504.41   309737.399522   \n",
       " 2010.0     206.582683              504.41   309874.023839   \n",
       " 2011.0     206.673806              504.41   310010.708420   \n",
       " 2012.0     206.764969              504.41   310147.453293   \n",
       " 2013.0     206.856172              504.41   310284.258483   \n",
       " 2014.0     206.947416              504.41   310421.124017   \n",
       " 2015.0     207.038700              504.41   310558.049923   \n",
       " 2016.0     207.130024              504.41   310695.036226   \n",
       " 2017.0     207.221389              504.41   310832.082954   \n",
       " 2018.0     207.312793              504.41   310969.190132   \n",
       "\n",
       "         BGP_alt_Output_per_Worker  BGP_alt_Capital_Output_Ratio  \\\n",
       "Year                                                               \n",
       "-8000.0                     1500.0                      2.973771   \n",
       "-7999.0                     1500.0                      2.973771   \n",
       "-7998.0                     1500.0                      2.973771   \n",
       "-7997.0                     1500.0                      2.973771   \n",
       "-7996.0                     1500.0                      2.973771   \n",
       "-7995.0                     1500.0                      2.973771   \n",
       "-7994.0                     1500.0                      2.973771   \n",
       "-7993.0                     1500.0                      2.973771   \n",
       "-7992.0                     1500.0                      2.973771   \n",
       "-7991.0                     1500.0                      2.973771   \n",
       "-7990.0                     1500.0                      2.973771   \n",
       "-7989.0                     1500.0                      2.973771   \n",
       "-7988.0                     1500.0                      2.973771   \n",
       "-7987.0                     1500.0                      2.973771   \n",
       "-7986.0                     1500.0                      2.973771   \n",
       "-7985.0                     1500.0                      2.973771   \n",
       "-7984.0                     1500.0                      2.973771   \n",
       "-7983.0                     1500.0                      2.973771   \n",
       "-7982.0                     1500.0                      2.973771   \n",
       "-7981.0                     1500.0                      2.973771   \n",
       "-7980.0                     1500.0                      2.973771   \n",
       "-7979.0                     1500.0                      2.973771   \n",
       "-7978.0                     1500.0                      2.973771   \n",
       "-7977.0                     1500.0                      2.973771   \n",
       "-7976.0                     1500.0                      2.973771   \n",
       "-7975.0                     1500.0                      2.973771   \n",
       "-7974.0                     1500.0                      2.973771   \n",
       "-7973.0                     1500.0                      2.973771   \n",
       "-7972.0                     1500.0                      2.973771   \n",
       "-7971.0                     1500.0                      2.973771   \n",
       "...                            ...                           ...   \n",
       " 1989.0                     1500.0                      2.973771   \n",
       " 1990.0                     1500.0                      2.973771   \n",
       " 1991.0                     1500.0                      2.973771   \n",
       " 1992.0                     1500.0                      2.973771   \n",
       " 1993.0                     1500.0                      2.973771   \n",
       " 1994.0                     1500.0                      2.973771   \n",
       " 1995.0                     1500.0                      2.973771   \n",
       " 1996.0                     1500.0                      2.973771   \n",
       " 1997.0                     1500.0                      2.973771   \n",
       " 1998.0                     1500.0                      2.973771   \n",
       " 1999.0                     1500.0                      2.973771   \n",
       " 2000.0                     1500.0                      2.973771   \n",
       " 2001.0                     1500.0                      2.973771   \n",
       " 2002.0                     1500.0                      2.973771   \n",
       " 2003.0                     1500.0                      2.973771   \n",
       " 2004.0                     1500.0                      2.973771   \n",
       " 2005.0                     1500.0                      2.973771   \n",
       " 2006.0                     1500.0                      2.973771   \n",
       " 2007.0                     1500.0                      2.973771   \n",
       " 2008.0                     1500.0                      2.973771   \n",
       " 2009.0                     1500.0                      2.973771   \n",
       " 2010.0                     1500.0                      2.973771   \n",
       " 2011.0                     1500.0                      2.973771   \n",
       " 2012.0                     1500.0                      2.973771   \n",
       " 2013.0                     1500.0                      2.973771   \n",
       " 2014.0                     1500.0                      2.973771   \n",
       " 2015.0                     1500.0                      2.973771   \n",
       " 2016.0                     1500.0                      2.973771   \n",
       " 2017.0                     1500.0                      2.973771   \n",
       " 2018.0                     1500.0                      2.973771   \n",
       "\n",
       "         BGP_alt_Capital  BGP_alt_Population  \n",
       "Year                                          \n",
       "-8000.0     11151.642515            5.000000  \n",
       "-7999.0     11156.561474            5.002205  \n",
       "-7998.0     11161.482603            5.004412  \n",
       "-7997.0     11166.405902            5.006619  \n",
       "-7996.0     11171.331373            5.008828  \n",
       "-7995.0     11176.259017            5.011037  \n",
       "-7994.0     11181.188834            5.013248  \n",
       "-7993.0     11186.120826            5.015459  \n",
       "-7992.0     11191.054993            5.017671  \n",
       "-7991.0     11195.991336            5.019884  \n",
       "-7990.0     11200.929857            5.022099  \n",
       "-7989.0     11205.870557            5.024314  \n",
       "-7988.0     11210.813436            5.026530  \n",
       "-7987.0     11215.758495            5.028747  \n",
       "-7986.0     11220.705735            5.030965  \n",
       "-7985.0     11225.655157            5.033185  \n",
       "-7984.0     11230.606763            5.035405  \n",
       "-7983.0     11235.560553            5.037626  \n",
       "-7982.0     11240.516528            5.039848  \n",
       "-7981.0     11245.474689            5.042071  \n",
       "-7980.0     11250.435037            5.044295  \n",
       "-7979.0     11255.397573            5.046520  \n",
       "-7978.0     11260.362298            5.048746  \n",
       "-7977.0     11265.329213            5.050973  \n",
       "-7976.0     11270.298318            5.053201  \n",
       "-7975.0     11275.269616            5.055430  \n",
       "-7974.0     11280.243107            5.057660  \n",
       "-7973.0     11285.218791            5.059891  \n",
       "-7972.0     11290.196670            5.062123  \n",
       "-7971.0     11295.176745            5.064356  \n",
       "...                  ...                 ...  \n",
       " 1989.0    912999.924439          409.356704  \n",
       " 1990.0    913402.646200          409.537270  \n",
       " 1991.0    913805.545599          409.717916  \n",
       " 1992.0    914208.622717          409.898641  \n",
       " 1993.0    914611.877631          410.079446  \n",
       " 1994.0    915015.310419          410.260331  \n",
       " 1995.0    915418.921161          410.441296  \n",
       " 1996.0    915822.709934          410.622340  \n",
       " 1997.0    916226.676817          410.803465  \n",
       " 1998.0    916630.821889          410.984669  \n",
       " 1999.0    917035.145228          411.165953  \n",
       " 2000.0    917439.646913          411.347318  \n",
       " 2001.0    917844.327023          411.528762  \n",
       " 2002.0    918249.185636          411.710286  \n",
       " 2003.0    918654.222831          411.891890  \n",
       " 2004.0    919059.438687          412.073575  \n",
       " 2005.0    919464.833282          412.255339  \n",
       " 2006.0    919870.406696          412.437184  \n",
       " 2007.0    920276.159007          412.619109  \n",
       " 2008.0    920682.090294          412.801114  \n",
       " 2009.0    921088.200637          412.983199  \n",
       " 2010.0    921494.490114          413.165365  \n",
       " 2011.0    921900.958804          413.347611  \n",
       " 2012.0    922307.606786          413.529938  \n",
       " 2013.0    922714.434139          413.712345  \n",
       " 2014.0    923121.440943          413.894832  \n",
       " 2015.0    923528.627276          414.077400  \n",
       " 2016.0    923935.993219          414.260048  \n",
       " 2017.0    924343.538849          414.442777  \n",
       " 2018.0    924751.264246          414.625587  \n",
       "\n",
       "[10019 rows x 21 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output[\"df\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "170.2789394098914 = model population at Roman Empire founding\n",
      "212.28674094681443 = model population in 500 AD\n",
      "264.6578639613148 = model population in 1000 AD\n",
      "329.94893908194734 = model population in 1500 AD\n",
      "368.4068552704084 = model population in 1750 AD\n",
      "393.601081321362 = model population in 1900 AD\n",
      "411.3473175209178 = model population in 2000 AD\n"
     ]
    }
   ],
   "source": [
    "print(output[\"df\"].Population[0], \"= model population at Roman Empire founding\")\n",
    "print(output[\"df\"].Population[500], \"= model population in 500 AD\")\n",
    "print(output[\"df\"].Population[1000], \"= model population in 1000 AD\")\n",
    "print(output[\"df\"].Population[1500], \"= model population in 1500 AD\")\n",
    "print(output[\"df\"].Population[1750], \"= model population in 1750 AD\")\n",
    "print(output[\"df\"].Population[1900], \"= model population in 1900 AD\")\n",
    "print(output[\"df\"].Population[2000], \"= model population in 2000 AD\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<https://github.com/braddelong/LSS18E101b/blob/master/2018-02-04_Malthusian.ipynb>\n",
    "\n",
    "<http://datahub.berkeley.edu/user-redirect/interact?account=braddelong&repo=LSS18E101b&branch=master&path=2018-02-04_Malthusian.ipynb>\n",
    "\n"
   ]
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}