{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load Constrained Layout Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Try this yourself](https://colab.research.google.com/github/DTUWindEnergy/TopFarm2/blob/master/docs/notebooks/layout_and_loads.ipynb) (requires google account)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this example, a simple layout optimization is done while adding the fatigue loads of the turbine as constraints in addition to the boundary and spacing constraints. This type of optimization is important to make sure that the loading on the turbines do not increase too much and compromise a component's integrity.\n",
    "\n",
    "Load calculations of the Damage Equivalent Loads (DEL) and Lifetime Damage Equivalent Loads (LDEL) are computed via PyWake for the turbines and flow cases selected. Then, the load constraints can be included either with the `AEPMaxLoadCostModel` or as **post_constraints** in the `TopFarmProblem`. Both types of set ups are included in this example."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Nv2ihk66SNgi"
   },
   "source": [
    "**Install TOPFARM and PyWake if needed**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "executionInfo": {
     "elapsed": 124309,
     "status": "ok",
     "timestamp": 1623707966633,
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     "user_tz": -120
    },
    "id": "HP8XVx4URYcr"
   },
   "outputs": [],
   "source": [
    "# Install TopFarm if needed\n",
    "import importlib\n",
    "if not importlib.util.find_spec(\"topfarm\"):\n",
    "    !pip install git+https://gitlab.windenergy.dtu.dk/TOPFARM/TopFarm2.git"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TbtAki7QSZG4"
   },
   "source": [
    "**First we import basic Python elements and some TOPFARM classes**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "executionInfo": {
     "elapsed": 244,
     "status": "ok",
     "timestamp": 1623708396211,
     "user": {
      "displayName": "Mikkel Friis-Møller",
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    "id": "5YqUNim5R3JG"
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   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from numpy import newaxis as na\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "from topfarm.cost_models.cost_model_wrappers import AEPMaxLoadCostModelComponent\n",
    "from topfarm.easy_drivers import EasyScipyOptimizeDriver\n",
    "from topfarm import TopFarmProblem\n",
    "from topfarm.plotting import NoPlot, XYPlotComp\n",
    "from topfarm.constraint_components.boundary import XYBoundaryConstraint\n",
    "from topfarm.constraint_components.spacing import SpacingConstraint\n",
    "\n",
    "from py_wake.examples.data.lillgrund import LillgrundSite\n",
    "from py_wake.deficit_models.gaussian import IEA37SimpleBastankhahGaussian\n",
    "from py_wake.turbulence_models.stf import STF2017TurbulenceModel\n",
    "from py_wake.examples.data.iea34_130rwt import IEA34_130_1WT_Surrogate \n",
    "from py_wake.superposition_models import MaxSum"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "WjnaXixxSdZL"
   },
   "source": [
    "**Next, we select the site and wind turbine to use**.\n",
    "\n",
    "Usually, adding the loads as constraints into Topfarm's problem requires an accurate calculation of the fatigue loading, which here is done by a surrogate of the IEA3 3.4MW turbine. In addition, it is necessary to specify a turbulence model (`STF2017TurbulenceModel`) that is adequate enough to represent the turbulence intensity in the site, which the surrogate model for the turbine will need for the load calculation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "executionInfo": {
     "elapsed": 1294,
     "status": "ok",
     "timestamp": 1623707974928,
     "user": {
      "displayName": "Mikkel Friis-Møller",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiVrnxS0oNYcvEfwYdFjWYAU5G0YxLXELnknXMi=s64",
      "userId": "10444369613733539918"
     },
     "user_tz": -120
    },
    "id": "E-TFCSUSSt5e"
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "site = LillgrundSite()\n",
    "windTurbines = IEA34_130_1WT_Surrogate()\n",
    "wfm = IEA37SimpleBastankhahGaussian(site, windTurbines, turbulenceModel=STF2017TurbulenceModel(addedTurbulenceSuperpositionModel=MaxSum()))\n",
    "\n",
    "#choosing the flow cases for the optimization - this will determine the speed and accuracy of the simulation\n",
    "wsp = np.asarray([10, 15])\n",
    "wdir = np.arange(0,360,45)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "kC7blGu9h-hR"
   },
   "source": [
    "**Next, we set up the load constraint**\n",
    "\n",
    "In this example, we will calculate nominal loads and use this as a basis for the load constraint. The loads are represented by the Lifetime Damage Equivalent Loads (LDEL)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "executionInfo": {
     "elapsed": 1584,
     "status": "ok",
     "timestamp": 1623709946254,
     "user": {
      "displayName": "Mikkel Friis-Møller",
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      "userId": "10444369613733539918"
     },
     "user_tz": -120
    },
    "id": "hjG7faI1iZBh"
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "x, y = site.initial_position.T\n",
    "\n",
    "#keeping only every second turbine as lillegrund turbines are approx. half the size of the iea 3.4MW\n",
    "x = x[::2]\n",
    "y = y[::2]\n",
    "x_init = x\n",
    "y_init = y\n",
    "n_wt = x.size\n",
    "i = n_wt\n",
    "\n",
    "#choosing a load ratio for the constraint\n",
    "load_fact = 1.002\n",
    "simulationResult = wfm(x,y,wd=wdir, ws=wsp)\n",
    "nom_loads = simulationResult.loads('OneWT')['LDEL'].values\n",
    "max_loads = nom_loads * load_fact\n",
    "s = nom_loads.shape[0]\n",
    "load_signals = ['del_blade_flap', 'del_blade_edge', 'del_tower_bottom_fa',\n",
    "                'del_tower_bottom_ss', 'del_tower_top_torsion']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0v7KeHZvinpG"
   },
   "source": [
    "**Setting up optimization problem**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this optimization, we use the `AEPMaxLoadCostModelComponent` cost model component which already includes the maximum allowable loads as constraints. This means that the **post_constraint** element in the TOPFARM problem is not necessary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "executionInfo": {
     "elapsed": 235,
     "status": "ok",
     "timestamp": 1623709951830,
     "user": {
      "displayName": "Mikkel Friis-Møller",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiVrnxS0oNYcvEfwYdFjWYAU5G0YxLXELnknXMi=s64",
      "userId": "10444369613733539918"
     },
     "user_tz": -120
    },
    "id": "VXXj960rjJt4"
   },
   "outputs": [],
   "source": [
    "#parameters needed for the optimization\n",
    "maxiter = 10\n",
    "tol = 1e-4\n",
    "driver = EasyScipyOptimizeDriver(optimizer='SLSQP', maxiter=maxiter, tol=tol)\n",
    "ec = 1e-2\n",
    "step = 1e-4\n",
    "min_spacing = 260\n",
    "\n",
    "#setting up the boundary\n",
    "xi, xa = x_init.min()-min_spacing, x_init.max()+min_spacing\n",
    "yi, ya = y_init.min()-min_spacing, y_init.max()+min_spacing\n",
    "boundary = np.asarray([[xi, ya], [xa, ya], [xa, yi], [xi, yi]])\n",
    "\n",
    "#setting up cost function - aep and nominal loads calculation\n",
    "def aep_load_func(x, y):\n",
    "    simres = wfm(x, y, wd=wdir, ws=wsp)\n",
    "    aep = simres.aep().sum()\n",
    "    loads = simres.loads('OneWT')['LDEL'].values\n",
    "    return [aep, loads]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: checking out_of_order\n",
      "INFO: checking system\n",
      "INFO: checking solvers\n",
      "INFO: checking dup_inputs\n",
      "INFO: checking missing_recorders\n",
      "INFO: checking unserializable_options\n",
      "INFO: checking comp_has_no_outputs\n",
      "INFO: checking auto_ivc_warnings\n"
     ]
    }
   ],
   "source": [
    "#cost component and topfarm problem\n",
    "cost_comp = AEPMaxLoadCostModelComponent(input_keys=[('x', x_init),('y', y_init)],\n",
    "                                          n_wt = n_wt,\n",
    "                                          aep_load_function = aep_load_func,\n",
    "                                          max_loads = max_loads, \n",
    "                                          objective=True,\n",
    "                                          step={'x': step, 'y': step},\n",
    "                                          output_keys=[('AEP', 0), ('loads', np.zeros((s, i)))]\n",
    "                                          )\n",
    "\n",
    "problem = TopFarmProblem(design_vars={'x': x_init, 'y': y_init},\n",
    "                         n_wt=n_wt,\n",
    "                        constraints=[XYBoundaryConstraint(boundary),\n",
    "                                     SpacingConstraint(min_spacing)],\n",
    "                          cost_comp=cost_comp,\n",
    "                          driver=driver,\n",
    "                          plot_comp=NoPlot(),\n",
    "                          expected_cost=ec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Jt_GXqoHkV_W"
   },
   "source": [
    "**Now we run the optimization**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 398160,
     "status": "ok",
     "timestamp": 1623710355821,
     "user": {
      "displayName": "Mikkel Friis-Møller",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiVrnxS0oNYcvEfwYdFjWYAU5G0YxLXELnknXMi=s64",
      "userId": "10444369613733539918"
     },
     "user_tz": -120
    },
    "id": "kOQhnRLUSGIz",
    "outputId": "1ef8833f-41cb-48f9-c72c-a7c04c9a7376",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "cost, state, recorder = problem.optimize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vZecAwKRh0QK"
   },
   "source": [
    "**We can also do some plotting to visualize the evolution of the AEP and loads for each iteration**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 283
    },
    "executionInfo": {
     "elapsed": 269,
     "status": "ok",
     "timestamp": 1623710386579,
     "user": {
      "displayName": "Mikkel Friis-Møller",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiVrnxS0oNYcvEfwYdFjWYAU5G0YxLXELnknXMi=s64",
      "userId": "10444369613733539918"
     },
     "user_tz": -120
    },
    "id": "miJIu_aMtvwy",
    "outputId": "60fd88b8-a1ca-4b83-d395-a72cd5a13bd8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'AEP [GWh]')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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8RpHSQvfGEhEREYemc3ZERETEoansiIiIiENT2RERERGHprIjIiIiDk1lR0RERByayo6IiIg4NF1UkLz72Rw/fhwvL68ye08eERGR8sYwDNLS0qhRo0aBi6D+ncoOcPz48Ytu0CciIiJlw5EjRwgMDLzsepUdyL+0+ZEjR/D29jY5jYiIiBRGamoqQUFBV71FicoO/3/nYG9vb5UdERGRMuZqp6DoBGURERFxaCo7IiIi4tBUdkRERMShqeyIiIiIQ1PZEREREYemsiMiIiIOTWVHREREHJrKjoiIiDg0lR0RERFxaCo7IiIi4tBUdkRERMShqeyIiIiIQ1PZERERkWKTY7Oz8eAZ7HbDtAymlp1JkyYRERGRf7fxqKgoFixYAMDBgwexWCyXfHz//fcA/PHHHzzwwAMEBQXh7u5OeHg4H330kZkfSUREpFwzDIMDyRl8s+4gg77ZSNPXFnPPZ+vYmZhqWqYKpr0zEBgYyNtvv01oaCiGYTBt2jT69u3Lli1baNCgAYmJiQW2/+KLLxg/fjy9evUCYNOmTfj7+/Ptt98SFBTE2rVreeKJJ3B2dmbo0KFmfCQREZFy59z5bNbuO82qhFOsSkjm6NkLBdb7VnTh2LkL3FTTx5R8FsMwzBtXuoTKlSszfvx4Bg4ceNG6pk2b0qxZMyZPnnzZ1w8ZMoRdu3axbNmyQr9namoqPj4+pKSk4O3tfV25RUREyoscm50th8+xKuEUKxOS2Xb0HH89SuXibKFF7cq0q+9Hu5CqNKrhjZOTpchzFPbvt6kjO39ls9n4/vvvycjIICoq6qL1mzZtIi4ujk8//fSK+0lJSaFy5cpX3CYrK4usrKz856mp5g2tiYiIlHaGYbA/OYPVCcmsSjjFun2nyci2Fdgm1N+TdqFVaVffj1Z1KlPRtdRUDPPLzrZt24iKiiIzMxNPT0/mzZtHw4YNL9pu8uTJhIeH06ZNm8vua+3atcyePZv58+df8T3Hjh3LmDFjbji7iIiIozqbkc2afcn/KzjJHDtX8NBUFQ9X2ob40S7Uj3ahVanm42ZS0qsz/TBWdnY2hw8fJiUlhTlz5vDVV1/x22+/FSg8Fy5coHr16vzrX//i+eefv+R+tm/fTqdOnXj22Wd59dVXr/ielxrZCQoK0mEsEREpt7Jz7Ww+fDb/vJttx1L4a0NwdXaiZR1fbgmpSrtQPxpWL55DU9eisIexTC87f9e1a1fq1avH559/nr9s+vTpDBw4kGPHjlG1atWLXrNz5046derE448/zptvvnnN76lzdkREpLwxDIN9p9JZ9b+Rm9/3n+b83w5NhQV45Y3c1K/KzcGVcXd1NintpZW5c3b+ZLfbC4y6QN4hrNtvv/2SRWfHjh107tyZ6Ojo6yo6IiIi5cWZjGxW701m1Z5TrN6bTGJKZoH1fp6u3BKSd1jqllA/ArxL76Gpa2Fq2Rk5ciS9evWiVq1apKWlMXPmTFasWEFMTEz+Nnv37mXlypX8+uuvF71++/btdO7cmR49ejBixAhOnDgBgLOz8yWLkYiISHmSlWtj06Gz/xu9OcWO46kFD01VcKJVncr5BadBNS/TD00VB1PLTlJSEv379ycxMREfHx8iIiKIiYmhW7du+dt8/fXXBAYG0r1794teP2fOHE6dOsW3337Lt99+m7+8du3aHDx4sCQ+goiISKlhGAYJSen55Wb9/jNcyCl4aKpBNa/8k4pvrlMZN5fSdWiqOJS6c3bMoHN2RESkrEpOz2LN3mRW7klm9d5TnEwteCqIn6eV9qF+tKvvR9sQP/y9HOPQFJThc3ZERETk8jJz8g5NrUw4xao9yRfdhsFawYmb61Sm/f+ueRMW4IXF4niHpq6Fyo6IiEgpZhgG8SfTWJ2QzMqEZDYcOE1mjr3ANg2re+cfmmoR7FsuDk1dC5UdERGRUmjN3mR+2HyU1QnJJKUVPDTl72XNu1pxaN6hqapeVpNSlg0qOyIiIqXI2YxsXv9lJ3O3HMtf5ubiRKs6VWgX6kf7+lUJ9fcs94emroXKjoiISClgGAbztyUy6qcdnM7IxmKBB26uxW2Nq9Ostg5N3QiVHREREZOdTM3k1R+3s3jnSSDvpprv3BNBs1q+JidzDCo7IiIiJjEMg+82HuGN+btIy8ylgpOFIZ1CeLpTPawVNJJTVFR2RERETHD49HlenruVtftOAxAR6MO4eyJoUE3XeytqKjsiIiIlyGY3mLr2IO/GxHMhx4abixPPdwvj0bbBVHB2MjueQ1LZERERKSF7TqbxjzlbiTtyDoDWdSvz9l0RBPt5mBvMwansiIiIFLPsXDuTVuzjk+UJ5NgMvKwVGHlrOPe3DHLIG2+WNio7IiIixeiPI+d46Yet7D6RBkCXBv68cedNVPdxNzlZ+aGyIyIiUgwuZNv4YMkevlq1H7sBlT1cGX17I/pEVNcFAUuYyo6IiEgRW7fvNC/P3cqh0+cB6NukBqP6NKKyh6vJyconlR0REZEikpqZw9hfd/OfDYcBqObtxpt33kSX8ACTk5VvKjsiIiJFYOmuk7wybzsnUjMBeKhVLV7u1QAvNxeTk4nKjoiIyA04nZ7FmP/u5Oc/jgMQXKUib98dQeu6VUxOJn9S2REREbkOhmHw8x/HGf3zDs6ez8HJAoPa1WV41/q4u+pWD6WJyo6IiMg1Sky5wKvztrN0dxIADap5Me6eCCICK5kbTC5JZUdERKSQ7HaD/8QeZuyvu0nPysXV2YlnOofwZId6uFbQrR5KK5UdERGRQjiQnMHLP2xl/YEzADStVYlxd0cQGuBlcjK5GpUdERGRK8i12fl6zQHeW7SHrFw77i7OvNgjjOg2wTjrVg9lgsqOiIjIZexKTOWlH7ay9WgKALeE+DH2rsYEVa5ocjK5Fio7IiIif5OVa+PTZXuZuGIfuXYDb7cKvHpbQ+5tHqhbPZRBKjsiIiJ/sfnwWV6as5WEpHQAejQK4PW+N+Hv7WZyMrleKjsiIiLA+exc3o3Zw5S1BzAM8PN05bW+N9HrpmoazSnjVHZERKTcW52QzMh5Wzly5gIAdzcL5NXe4fjqxp0OQWVHRETKrZQLObw5fyffbTwKQM1K7rx1V2M61K9qcjIpSio7IiJSLsXsOMG/ftxOUloWANFRtXmxZwM8rfrT6Gj0ExURkXLlVFoWo3/ewfxtiQDUrerBO3dH0DK4ssnJpLio7IiISLlgGAbzthzjtV92cu58Ds5OFp5sX5dhXUJxc9GNOx2Zyo6IiDi8Y+cu8M+52/htzykAGlb3Ztw9EdxU08fkZFISVHZERMRh2e0G364/xDsLdpORbcO1ghPPdgnlifZ1cXHWjTvLC5UdERFxSPtOpfPyD1uJPXgWgBa1fXn77ghC/D1NTiYlTWVHREQcSo7Nzper9vPhkgSyc+14uDrzUq8GPNyqNk66cWe5pLIjIiIO4+jZ8wyZsZk//nfjzvb1q/LWnTcR6Ksbd5ZnKjsiIuIQ1u5NZuh/tnAmIxsfdxf+fVtD7mpWU7d6EJUdEREp2wzD4KtVBxi7YBd2AxrX9GHSw800miP5VHZERKTMOp+dy0s/bOO/fxwH8u5p9eadN+m6OVKAyo6IiJRJh05n8OT0Tew+kUYFJwv/7tOQR1rX1mEruYjKjoiIlDkr4pMY9p8tpGbm4udpZeJDzbi5jm73IJemsiMiImWGYRhMXLGPdxfFYxjQtFYlJj3UnGo+bmZHk1JMZUdERMqE9Kxcnv8ujpgdJwF4sFUtRvVpiLWCzs+RK1PZERGRUm/fqXSenL6JvUnpuDo78VrfRtx/cy2zY0kZobIjIiKl2uKdJxkxO460rFyqebsx6eFmNK3la3YsKUNUdkREpFSy2w0+XLKHj5ftBeDm4Mp8+lAzqnpZTU4mZY3KjoiIlDopF3J4bnYcy3YnATCgTTCv9A7XncrluqjsiIhIqRJ/Io0np2/k4OnzWCs4MfauxtzVLNDsWFKGqeyIiEipMX9rIi/O+YPz2TZqVnLn80eac1NNH7NjSRmnsiMiIqaz2Q3Gxezm89/2A9A2pAoTHmhGZQ9Xk5OJI1DZERERU53NyGbYrC2sSkgG4Mn2dXmxRxgVdH6OFBGVHRERMc32YykM/nYTR89ewN3FmXH3RNAnsobZscTBqOyIiIgp5m05yss/bCMr107tKhX5/JHmNKjmbXYscUAqOyIiUqJybHbe+nUXU9YcBKBjWFU+6tcUn4ou5gYTh6WyIyIiJeZUWhZDZ25m/YEzADzTOYThXevj7GQxOZk4MpUdEREpEXFHzjF4+iZOpGbiaa3Ae/dF0qNRNbNjSTmgsiMiIsVuduxh/vXjDrJtdupW9eCLR1oQ4u9pdiwpJ1R2RESk2GTn2hnz3x3MWH8YgO4NA3jvvki83HR+jpQclR0RESkWJ1MzeerbTWw+fA6LBUZ0rc+QTiE46fwcKWEqOyIiUuQ2HjzDUzM2cyotCy+3Cnx8f1M6NfA3O5aUUyo7IiJSZAzD4NvfDzHmvzvJtRuEBXjx+SPNCfbzMDualGMqOyIiUiQyc2y8+uN25mw6CkDviOqMuzsCD6v+1Ii5TL3xyKRJk4iIiMDb2xtvb2+ioqJYsGABAAcPHsRisVzy8f333+fv4/Dhw/Tu3ZuKFSvi7+/Piy++SG5urlkfSUSkXDp27gL3fb6OOZuO4mSBkb0a8MkDTVV0pFQw9b/CwMBA3n77bUJDQzEMg2nTptG3b1+2bNlCgwYNSExMLLD9F198wfjx4+nVqxcANpuN3r17U61aNdauXUtiYiL9+/fHxcWFt956y4yPJCJS7qzdl8zQmVs4k5FNpYoufPJAM24J9TM7lkg+i2EYhtkh/qpy5cqMHz+egQMHXrSuadOmNGvWjMmTJwOwYMECbrvtNo4fP05AQAAAn332GS+99BKnTp3C1dW1UO+ZmpqKj48PKSkpeHvrviwiIoVhGAaTVx9g7ILd2OwGjWp489nDzQmqXNHsaFJOFPbvt6mHsf7KZrMxa9YsMjIyiIqKumj9pk2biIuLK1CC1q1bR+PGjfOLDkCPHj1ITU1lx44dl32vrKwsUlNTCzxERKTwLmTbGD47jjfm78JmN7iraU1+eKqNio6USqYfTN22bRtRUVFkZmbi6enJvHnzaNiw4UXbTZ48mfDwcNq0aZO/7MSJEwWKDpD//MSJE5d9z7FjxzJmzJgi+gQiIuXL4dPneWL6RnafSMPZycK/eocT3SYYi0XXz5HSyfSRnbCwMOLi4li/fj1PPfUU0dHR7Ny5s8A2Fy5cYObMmZc8tHU9Ro4cSUpKSv7jyJEjRbJfERFHt3LPKfp8sprdJ9Lw83RlxuOtGNC2joqOlGqmj+y4uroSEhICQPPmzYmNjeWjjz7i888/z99mzpw5nD9/nv79+xd4bbVq1diwYUOBZSdPnsxfdzlWqxWr1VpUH0FExOEZhsHEFft4d1E8hgGRQZX47OFmVPdxNzuayFWZPrLzd3a7naysrALLJk+ezO23307VqlULLI+KimLbtm0kJSXlL1u8eDHe3t6XPBQmIiLXLj0rl6dnbGZ8TF7Rub9lEN892VpFR8oMU0d2Ro4cSa9evahVqxZpaWnMnDmTFStWEBMTk7/N3r17WblyJb/++utFr+/evTsNGzbkkUceYdy4cZw4cYJXX32VIUOGaORGRKQI7D+VzpPTN5GQlI6Ls4Uxt9/Eg61qmR1L5JqYWnaSkpLo378/iYmJ+Pj4EBERQUxMDN26dcvf5uuvvyYwMJDu3btf9HpnZ2d++eUXnnrqKaKiovDw8CA6OprXXnutJD+GiIhDWrrrJMNnxZGWlYu/l5VJDzeneW1fs2OJXLNSd50dM+g6OyIi/89uN/hoaQIfLU0AoEVtXyY+1Ax/bzeTk4kUVNi/36afoCwiIqVHamYOz82KY+nuvHMh+0fV5tXeDXGtUOpO8RQpNJUdEREBIOFkGk9M38SB5AxcKzjx5h03cW+LILNjidwwlR0RkXLu3PlsJq7Yx9S1B8nOtVPDx43PHmlORGAls6OJFAmVHRGRcupCto0paw8wacU+0jJzAWgX6seH/ZpQxVMzWsVxqOyIiJQzuTY73208ykdL93AyNe+6Zg2qefFSzwZ0DKuqqyGLw1HZEREpJwzDYOH2E4yPiWd/cgYANSu583z3+vRtUhNnJ5UccUwqOyIi5cDafcm8szCeP46cA6CyhytDO4XwUOtaWCs4mxtOpJip7IiIOLAdx1N4Z2E8K/ecAqCiqzOP31KHQe3r4uXmYnI6kZKhsiMi4oAOnz7Pe4vj+SnuOAAVnCw82KoWz3QOpaqXTj6W8kVlR0TEgSSnZzFhaQIzNxwmx5Z3gfw+kTV4vlt9gv08TE4nYg6VHRERB5CelcuXK/fz5ar9nM+2AXnTyF/q2YCbavqYnE7EXCo7IiJlWFaujZnrD/PJsr2czsgGICLQh5d7NqBNiJ/J6URKB5UdEZEyyG43+PmP47y7KJ6jZy8AUMfPgxe6h3Fr42q6Vo7IX6jsiIiUIYZhsGLPKcYtjGdXYioA/l5Wnu0ayn0tgnBx1g07Rf5OZUdEpIzYcvgsby/YzfoDZwDwslZgcMd6PNo2mIqu+nUucjn61yEiUsrtTUrn3Zh4Fu44AYBrBSeio2rzdMcQfD1cTU4nUvqp7IiIlFInUjL5cMkevtt4BLsBTha4u1kgw7vVp2Yld7PjiZQZKjsiIqVMyvkcJv22jylrDpCVawega3gA/+gZRv0AL5PTiZQ9KjsiIqVEZo6NqWsPMnH5XlIzcwFoGezLSz0b0CK4ssnpRMoulR0REZPl2uz8sPkoHyxO4ERqJgD1Azz5R48GdAn31zRykRuksiMiYhLDMIjZcZLxMbvZdyoDgJqV3HmuW33ubFoTZyeVHJGioLIjImKC3/ef5p2Fu9ly+BwAlSq6MLRTCA+3ro2bi7O54UQcjMqOiEgJ2pWYyriFu1kefwoAdxdnBt5Shyc61MXbzcXkdCKOSWVHRKQEHDlznvcX7+HHuGMYBjg7WXjg5iCGdQ7F39vN7HgiDk1lR0SkGJ1Oz+KT5Xv59vdD5NgMAHpHVOeF7mHU8fMwOZ1I+aCyIyJSDDKycvlq1QG+XLWf9Ky8aeS3hPjxj55hRARWMjecSDmjsiMiUoSyc+38Z8NhJixLIDk9G4CbanrzUs8GtAutanI6kfJJZUdEpAjY7Qb/3Xqc9xbt4fCZ8wDUrlKRF7qH0btxdZw0jVzENCo7IiI3aHVCMmMX7GLH8VQA/DytPNs1lPtbBuHi7GRyOhFR2RERuU6GYfDhkgQ+WpoAgKe1Ak+2r8tjt9TBw6pfryKlhf41iohch8wcGy/9sJWf4o4D8HDrWozoFkZlD1eTk4nI36nsiIhcozMZ2TzxzUY2HjpLBScLb955E/1a1jI7lohchsqOiMg12HcqncemxnLo9Hm83Crw2cPNaRviZ3YsEbkClR0RkUJat+80g7/dRMqFHIIquzNlQEtC/L3MjiUiV6GyIyJSCHM2HWXk3K3k2Aya1arEF/1b4OdpNTuWiBSCyo6IyBXY7QbvL97DJ8v3AnBbRHXevTdSdyYXKUNUdkRELiMzx8YL3//BL1sTARjaKYQR3errAoEiZYzKjojIJZxOz2LQNxvZfPgcLs4W3rqzMfe2CDI7lohcB5UdEZG/2ZuUxqNTYzly5gLebhX4/JEWRNWrYnYsEblOKjsiIn+xZm8yg7/dRFpmLrWrVOTrAS2pV9XT7FgicgNUdkRE/md27GFembedXLtBi9q+fNG/ha6ILOIAVHZEpNyz2w3GL4pn0op9APRtUoN37o7QjCsRB6GyIyLlWmaOjRHfxfHrthMADOsSynNdQ7FYNONKxFGo7IhIuXUqLYvHv9nIH0fyZly9c3cEdzULNDuWiBQxlR0RKZf2nEzj0SmxHDt3gUoVXfj84ea0qqsZVyKOSGVHRMqdVQmnePrbzaRl5VLHz4OvB7Skjp+H2bFEpJio7IhIuTJz/WH+9dN2bHaDm+tU5vOHm+OrGVciDk1lR0TKBbvd4O2Fu/li5X4A7mxak7fvboy1gmZciTg6lR0RcXgXsm0Mn72FmB0nARjRrT7PdA7RjCuRcqJQZSc1NfWad+zt7X3NrxERKWpJqZk8/s1Gth5NwdXZifH3RtC3SU2zY4lICSpU2alUqdI1/T8gi8XCnj17qFu37nUHExG5UbtPpPLYlFiOp2TiW9GFL/u3oEVwZbNjiUgJK/RhrDlz5lC58tV/SRiGwa233npDoUREbtSK+CSGztxCelYudat6MGVAS2pX0YwrkfKoUGWndu3atG/fnipVCncNirp16+Li4nJDwURErtf03w8x6qft2A1oXbcynz/cAp+K+p0kUl4VquwcOHDgmna6ffv26wojInIjbHaDt37dxeTVeb+z7mkeyFt3Nsa1gpPJyUTETJqNJSIOISMrl2dnxbFkV96Mqxd7hPF0x3qacSUi11d2li5dytKlS0lKSsJutxdY9/XXXxdJMBGRwjqZmsljU2PZcTwV1wpOvHdvJH0ia5gdS0RKiWsuO2PGjOG1116jRYsWVK9eXf+vSURMtfN4KgOnxZKYkkkVD1e+6N+C5rV9zY4lIqXINZedzz77jKlTp/LII48URx4RkUJbtvskz8zcQka2jRB/T76ObkmtKhXNjiUipcw1l53s7GzatGlTHFlERApt6poDvPbLTuwGtA2pwsSHmuPjrhlXInKxa56i8PjjjzNz5sziyCIiclU2u8Hon3cw+r95RadfiyCmPnqzio6IXFahRnZGjBiR/7/tdjtffPEFS5YsISIi4qLr6bz//vtFm1BE5H/Ss3IZ9p8tLNudBMDLvRrwZPu6OndQRK6oUGVny5YtBZ43adIEuPh6OvqFIyLFJTHlAo9N3ciuxFSsFZz4sF8TejWubnYsESkDClV2li9fXtw5REQua/uxFAZOi+VkahZ+nq582b8FTWtpxpWIFE6hz9mZMmUKhw8fLtI3nzRpEhEREXh7e+Pt7U1UVBQLFiwosM26devo3LkzHh4eeHt70759ey5cuJC/fs+ePfTt2xc/Pz+8vb255ZZbVM5EHMjinSe597N1nEzNon6AJ/OebquiIyLXpNBl5+mnn6ZOnTrUrVuXgQMH8u2333Ls2LEbevPAwEDefvttNm3axMaNG+ncuTN9+/Zlx44dQF7R6dmzJ927d2fDhg3ExsYydOhQnJz+P/Ztt91Gbm4uy5YtY9OmTURGRnLbbbdx4sSJG8omIuYyDIPJqw/wxPSNXMix0S7UjzlPtSGosqaWi8i1sRiGYRRmw6ysLNauXctvv/3G8uXL2bBhA9nZ2YSEhNCpUyc6depEx44dCQgIuKFAlStXZvz48QwcOJDWrVvTrVs3Xn/99Utum5ycTNWqVVm5ciXt2rUDIC0tDW9vbxYvXkzXrl0L9Z6pqan4+PiQkpKCt7f3DeUXkRuXa7Mz5r87mf77IQAebFWLMbc3wsVZ97gSkf9X2L/fhf7NYbVa6dSpE6NHj+a3337j7NmzLFmyhH79+rFz504GDBhAzZo1rzuwzWZj1qxZZGRkEBUVRVJSEuvXr8ff3582bdoQEBBAhw4dWL16df5rqlSpQlhYGN988w0ZGRnk5uby+eef4+/vT/PmzS/7XllZWaSmphZ4iEjpkJaZw+PfbGT674ewWOCVW8N5846bVHRE5Lpd928PJycnnJycsFgsWCwWDMOgVq1a17yfbdu24enpidVqZfDgwcybN4+GDRuyf/9+AEaPHs2gQYNYuHAhzZo1o0uXLiQkJAB5s7+WLFnCli1b8PLyws3Njffff5+FCxfi63v5Y/pjx47Fx8cn/xEUFHR9X4KIFKlj5y5w72frWBF/CjcXJyY91JxBmlouIjeo0IexsrOz+f3331mxYgXLli1j/fr11K5dm/bt29O+fXs6dOhwXaUhOzubw4cPk5KSwpw5c/jqq6/47bffOHfuHG3btmXkyJG89dZb+dtHRETQu3dvxo4di2EY3HHHHeTk5PDKK6/g7u7OV199xc8//0xsbCzVq196WmpWVhZZWVn5z1NTUwkKCtJhLBETbT16joHTNnIqLYuqXlYmR7cgIrCS2bFEpBQr7GGsQt8uwsfHB39/f/r06cOQIUOYNWsW1apVu+Ggrq6uhISEANC8eXNiY2P56KOPePnllwFo2LBhge3Dw8PzZ4UtW7aMX375hbNnz+Z/yIkTJ7J48WKmTZuWv4+/s1qtWK3WG84uIkUjZscJnp21hcwcOw2qeTF5QEtqVnI3O5aIOIhCl53IyEi2bNnCypUr8w9hdezYkSpVqhRpILvdTlZWFsHBwdSoUYP4+PgC6/fs2UOvXr0AOH/+PECB2Vl/Prfb7UWaS0SKnmEYfLlqP2MX7MYwoEP9qnzyYFO83HTrBxEpOoUuO7///jvp6emsXr2a5cuXM27cOB544AHq169Px44d6dChAx06dMDf37/Qbz5y5Eh69epFrVq1SEtLY+bMmaxYsYKYmBgsFgsvvvgio0aNIjIykiZNmjBt2jR2797NnDlzAIiKisLX15fo6Gj+/e9/4+7uzpdffsmBAwfo3bv3tX8bIlJibHaDf/20nZnr80ZqH2ldm1F9GlJBJyKLSBG7pruee3p60rNnT3r27AnkTfNetWoVixcvZtCgQaSnp5Obm1vo/SUlJdG/f38SExPx8fEhIiKCmJgYunXrBsDw4cPJzMzkueee48yZM0RGRrJ48WLq1asHgJ+fHwsXLuSVV16hc+fO5OTk0KhRI3766SciIyOv5aOJSAkyDIMx/93BzPWHsVjg1d4NeaxtsE5EFpFiUegTlP/KbrcTGxvLihUrWL58OWvWrCEjI4PatWtz4MCB4shZrHSdHZGS9fXqA7z2y04sFvj4/qb0iaxhdiQRKYOK/ATlDRs2sGLFClasWMHq1atJT08nMDCQjh078vHHH9OpUyeCg4OLIruIOLBFO07w+vydAIzs1UBFR0SKXaHLTuvWralWrRqdOnXi/fffp1OnTvmHk0RECmPb0RSenRWHYeRdFXlQu7pmRxKRcqDQZWfXrl2EhYUVZxYRcWDHzl3gsWmxXMix0b5+VV67vZHO0RGRElHosvP3opOWlsZfT/dxcnLC09Oz6JKJiMNIy8xh4NRYTqVl0aCaF58+2FSzrkSkxBT6t01cXBy33npr/vMaNWrg6+ub/6hUqRKxsbHFElJEyq5cm50hM7ew+0Ra3pWRB7TUdXREpEQVemRnwoQJ3HLLLQWWTZ8+nZo1a2IYBl9//TUff/wx06dPL/KQIlI2GYbBv3/ewco9p3B3cebraF0ZWURKXqHLztq1axk6dGiBZa1bt6Zu3bwTDN3d3bnvvvuKNp2IlGlfrTqQfy2dj+5vQuNAH7MjiUg5VOjDWIcOHaJq1ar5z1977TX8/Pzyn1evXp2TJ08WbToRKbMWbk/krQW7gLyLBnZvdOP30hMRuR6FLjtubm4cOnQo//lzzz1X4AI+R44coWLFikWbTkTKpLgj5xg+O2+Kef+o2jzWNtjsSCJSjhW67DRt2pQff/zxsuvnzp1L06ZNiyKTiJRhR86c5/FpsWTm2OkUVpV/39ZQU8xFxFSFPmfn6aef5v777yc4OJinnnoq/07jNpuNiRMnMmHCBGbOnFlsQUWk9Eu5kMNjU2NJTs8mvLo3Ex5spinmImK6a7o31ksvvcT48ePx8vLKPzF5//79pKenM2LECMaPH19sQYuT7o0lcuNybHYenRLL6r3JBHhb+XFIW6r7aOaViBSfwv79vuYbgf7+++/85z//ISEhAYDQ0FAeeOABWrdufWOJTaSyI3JjDMPg5R+2MXvjESq6OvPdk1HcVFMzr0SkeBX5jUD/1Lp16zJdbESk6H32235mbzyCkwUmPNBURUdESpVCHUzfunUrdru90DvdsWMHubm51x1KRMqO+VsTeWfhbgBG9WlEl/AAkxOJiBRUqLLTtGlTTp8+XeidRkVFcfjw4esOJSJlw6ZDZ3nuuzgAHm0bTHSbYFPziIhcSqEOYxmGwb/+9a9CX0cnOzv7hkKJSOl3+PR5nvhmI9m5drqG+/Nq74ZmRxIRuaRClZ327dsTHx9f6J1GRUXh7q5ZGCKOKuV8Do9O3cDpjGxuqunNR/c3xdlJ19IRkdKpUGVnxYoVxRxDRMqK7Fw7g7/dxL5TGVT3cWNydEs8rNc810FEpMToal8iUmiGYfDPedtYt/80Hq7OfD2gJQHebmbHEhG5IpUdESm0T5fvZc6mozg7Wfj0oWaEV9d1qUSk9FPZEZFC+SnuGO8u2gPA6Nsb0THM3+REIiKFo7IjIlcVe/AML36/FYBB7erwSOvaJicSESm8ay47WVlZZGRkFEcWESmFDiZn5E0xt9np0SiAkb3CzY4kInJNCl12Tp06Ra9evfD09MTb25vWrVuzd+/e4swmIiY7m5HNo1NjOXs+h8hAHz7s1xQnTTEXkTKm0GXnpZdeIi4ujtdee413332Xc+fOMWjQoOLMJiImysq18eS3mziQnEHNSu58Gd0Cd1dns2OJiFyzQl8cY/HixUydOpUePXoAcNtttxEeHk5WVhZWq7XYAopIyfvzLuYbDpzBy1qBrwe0xN9LU8xFpGwq9MjO8ePHiYyMzH8eGhqK1WolMTGxWIKJiHk+WprAvC3HcHayMPHhZoRV8zI7kojIdbumE5SdnZ0vem4YRpEGEhFzzdtylA+XJADwxh030S60qsmJRERuTKEPYxmGQf369bFY/v/kxPT0dJo2bYqT0/93pjNnzhRtQhEpMb/vP80/5uRNMR/coR4P3FzL5EQiIjeu0GVnypQpxZlDREy271Q6T07fRI7N4NbG1fhHjzCzI4mIFIlCl53o6OjizCEiJjqdnsWjU2JJuZBDk6BKvH9fE00xFxGHUehzdjZs2IDNZrvs+qysLL777rsiCSUiJSczx8YT0zdx+Mx5An3d+Sq6BW4ummIuIo6j0GUnKiqK06dP5z/39vZm//79+c/PnTvHAw88ULTpRKRY2e0GL3z/B5sOncXLrQJTH22Jn6cuJSEijqXQZefvs64uNQtLM7NEypb3F+/hl62JVHCy8PnDzQnx1xRzEXE8RXoj0L/O1BKR0u27jUf4ZHneLV/euqsxbUL8TE4kIlI8dNdzkXJo7d5k/jl3GwBDO4VwX4sgkxOJiBSfQs/GAti5cycnTpwA8g5Z7d69m/T0dACSk5OLPp2IFLm9SWk8+e0mcu0GfSJrMKJbfbMjiYgUK4tRyBNtnJycsFgslzwv58/lFovlijO2SqvU1FR8fHxISUnB29vb7DgixeZUWhZ3TlzD0bMXaF7blxmPt9LMKxEpswr797vQIzsHDhwokmAiYo7MHBuDvtnI0bMXqF2lIl880lxFR0TKhUKXndq1a191m+3bt99QGBEpHna7wYjv4og7cg4fdxe+HtCSKppiLiLlxA2foJyWlsYXX3zBzTffXOCu6CJSeoyLiefXbSdwcbbw+SPNqVfV0+xIIiIl5rrLzsqVK4mOjqZ69eq8++67dO7cmd9//70os4lIEfjPhsN89ts+AN65O4LWdauYnEhEpGRd02ysEydOMHXqVCZPnkxqair33XcfWVlZ/PjjjzRs2LC4MorIdVqVcIpXf8w7vPxsl1DuahZociIRkZJX6JGdPn36EBYWxtatW/nwww85fvw4EyZMKM5sInID4k+k8fS3m7HZDe5sWpPhXUPNjiQiYopCj+wsWLCAYcOG8dRTTxEaql+aIqVZUlomj02NJS0rl5uDK/P23Y11hXMRKbcKPbKzevVq0tLSaN68Oa1ateKTTz7RhQRFSqEL2TYen7aRY+cuUMfPg88faY61gqaYi0j5Veiy07p1a7788ksSExN58sknmTVrFjVq1MBut7N48WLS0tKKM6eIFILNbjB89ha2Hk3Bt6ILUwa0xNfD1exYIiKmKvQVlC8lPj6eyZMnM336dM6dO0e3bt34+eefizJfidAVlMVRvDl/J1+uOoCrsxMzBrWiZXBlsyOJiBSbwv79vqHr7ISFhTFu3DiOHj3Kf/7znxvZlYjcoOm/H+LLVXlXOh9/b4SKjojI/9zQyI6j0MiOlHXL45MYODUWuwHPd6vPM100iUBEHF+JjOyIiPl2Hk9l6IzN2A24u1kgQzuHmB1JRKRUUdkRKcNOpmYycFosGdk2WtetzNi7NMVcROTvVHZEyqiMrFwemxpLYkomdat68PnDLXCtoH/SIiJ/p9+MImWQzW7w7Kwt7DieShUPV6YOuBmfii5mxxIRKZVUdkTKoDfm72TJriRcKzjxRf8W1KpS0exIIiKllsqOSBnzy9bjTFlzEID374ukeW1fcwOJiJRyKjsiZUiOzc74mHgAhnSqx20RNUxOJCJS+qnsiJQh3288yqHT5/HzdOXpjppiLiJSGCo7ImVEZo6Nj5cmAPB0xxA8rBVMTiQiUjao7IiUEd/+fogTqZnU8HHjwVa1zI4jIlJmqOyIlAHpWblMXLEPgGFdQnFzcTY5kYhI2WFq2Zk0aRIRERF4e3vj7e1NVFQUCxYsKLDNunXr6Ny5Mx4eHnh7e9O+fXsuXLhQYJv58+fTqlUr3N3d8fX15Y477ijBTyFS/KasPsCZjGzq+Hlwd/NAs+OIiJQpph70DwwM5O233yY0NBTDMJg2bRp9+/Zly5YtNGrUiHXr1tGzZ09GjhzJhAkTqFChAn/88QdOTv/f0X744QcGDRrEW2+9RefOncnNzWX79u0mfiqRonXufDZfrNwPwHPd6uPirAFZEZFrUeruel65cmXGjx/PwIEDad26Nd26deP111+/5La5ubkEBwczZswYBg4ceN3vqbueS2n29oLdfPbbPhpU8+LXYe1wctK9r0REoAze9dxmszFr1iwyMjKIiooiKSmJ9evX4+/vT5s2bQgICKBDhw6sXr06/zWbN2/m2LFjODk50bRpU6pXr06vXr00siMOIyktk6lrDwDwQvcwFR0RketgetnZtm0bnp6eWK1WBg8ezLx582jYsCH79+cN248ePZpBgwaxcOFCmjVrRpcuXUhIyJt++9dtXn31VX755Rd8fX3p2LEjZ86cuex7ZmVlkZqaWuAhUhp9umwvmTl2mtaqRJdwf7PjiIiUSaaXnbCwMOLi4li/fj1PPfUU0dHR7Ny5E7vdDsCTTz7Jo48+StOmTfnggw8ICwvj66+/Bsjf5pVXXuHuu++mefPmTJkyBYvFwvfff3/Z9xw7diw+Pj75j6CgoOL/oCLX6MiZ88zccBiAF7uHYbFoVEdE5HqYXnZcXV0JCQmhefPmjB07lsjISD766COqV68OQMOGDQtsHx4ezuHDeX8ALrWN1Wqlbt26+dtcysiRI0lJScl/HDlypKg/lsgN+3hpAjk2g7YhVWgT4md2HBGRMsv0svN3drudrKwsgoODqVGjBvHx8QXW79mzh9q1awPQvHlzrFZrgW1ycnI4ePBg/jaXYrVa86e7//kQKU32JqXzw+ajQN65OiIicv1MnXo+cuRIevXqRa1atUhLS2PmzJmsWLGCmJgYLBYLL774IqNGjSIyMpImTZowbdo0du/ezZw5cwDw9vZm8ODBjBo1iqCgIGrXrs348eMBuPfee838aCI35IPFe7Ab0DU8gKa1dFdzEZEbYWrZSUpKon///iQmJuLj40NERAQxMTF069YNgOHDh5OZmclzzz3HmTNniIyMZPHixdSrVy9/H+PHj6dChQo88sgjXLhwgVatWrFs2TJ8ffUHQsqm7cdSmL8tEYsFnu9e3+w4IiJlXqm7zo4ZdJ0dKU0enbKB5fGn6NukBh/d39TsOCIipVaZu86OiEDswTMsjz+Fs5OF57pqVEdEpCio7IiUEoZhMD4m72T7+1oEEuznYXIiERHHoLIjUkqsSkhmw4EzuFZw4pnOoWbHERFxGCo7IqXAX0d1HmldmxqV3E1OJCLiOFR2REqBmB0n2HYshYquzjzVsd7VXyAiIoWmsiNiMpvd4L1FewAYeEsd/DytJicSEXEsKjsiJvsp7hgJSen4uLvweLu6ZscREXE4KjsiJsrOtfPBkrxRnSc71MXH3cXkRCIijkdlR8RE3208wpEzF/DztDKgTbDZcUREHJLKjohJMnNsfLw0AYBnOodQ0dXUu7eIiDgslR0Rk3yz7iBJaVnUrOTO/TcHmR1HRMRhqeyImCAtM4dJK/YB8GzXUKwVnE1OJCLiuFR2REwwefUBzp7PoW5VD+5qWtPsOCIiDk1lR6SEnc3I5qtVBwAY0a0+FZz1z1BEpDjpt6xICfvst32kZ+XSsLo3t95U3ew4IiIOT2VHpASdTM1k6tqDALzYIwwnJ4u5gUREygGVHZESNGFZAlm5dprX9qVjWFWz44iIlAsqOyIl5PDp88zacATIG9WxWDSqIyJSElR2RErIh0v3kGs3aBfqR+u6VcyOIyJSbqjsiJSAhJNpzNtyDMgb1RERkZKjsiNSAt5fvAfDgB6NAogIrGR2HBGRckVlR6SYbT16jgXbT2CxwPPdNaojIlLSVHZEitm7i/YAcGeTmtQP8DI5jYhI+aOyI1KM1u8/zco9p6jgZGF41/pmxxERKZdUdkSKiWEYvLsoHoB+LYOoVaWiyYlERMonlR2RYrJizyliD57FWsGJZzqHmh1HRKTcUtkRKQZ2u8G7MXmjOv2jalPNx83kRCIi5ZfKjkgxWLjjBDuOp+Lh6sxTHUPMjiMiUq6p7IgUsVybnff+d67O4+3qUtnD1eREIiLlm8qOSBGbt+UY+05lUKmiC4+3q2N2HBGRck9lR6QIZeXa+HBJAgBPdaiHl5uLyYlERERlR6QIzY49wrFzF/D3stI/KtjsOCIigsqOSJG5kG1jwrK9ADzTOQR3V2eTE4mICKjsiBSZaesOcioti0Bfd/q1rGV2HBER+R+VHZEikJqZw6QV+wB4rmt9XCvon5aISGmh38giReCrlftJuZBDiL8ndzStaXYcERH5C5UdkRt0Oj2LyasPAPB8t/o4O1lMTiQiIn+lsiNygyat2EdGto3GNX3oeVM1s+OIiMjfqOyI3IDElAt88/shAF7oEYbFolEdEZHSRmVH5AZMWLaX7Fw7NwdXpn2on9lxRETkElR2RK7TweQMvos9AmhUR0SkNFPZEblOHy7ZQ67doGNYVW6uU9nsOCIichkqOyLXIf5EGj/9cRyAF7qHmZxGRESuRGVH5Dq8tygew4BbG1fjppo+ZscREZErUNkRuUZxR86xaOdJnCwwolt9s+OIiMhVqOyIXKN3Y+IBuLNpICH+XianERGRq1HZEbkGa/cls3pvMi7OFoZ3DTU7joiIFILKjkghGYaRP6rzwM21CKpc0eREIiJSGCo7IoW0bHcSmw+fw83FiaGdQsyOIyIihaSyI1IIdrvBu4v2ABDdJhh/bzeTE4mISGGp7IgUwvxtiexKTMXLWoHB7euZHUdERK6Byo7IVeTa7HywOG9UZ1D7uvh6uJqcSEREroXKjshVzN18jP3JGVT2cOWxW+qYHUdERK6Ryo7IFWTl2vhwSd6oztMd6+FprWByIhERuVYqOyJXMHP9YY6nZFLN242HW9c2O46IiFwHlR2Ryzifncuny/cC8EyXENxcnE1OJCIi10NlR+Qypqw5SHJ6NrUqV+S+FkFmxxERkeuksiNyCSkXcvj8t31A3s0+XZz1T0VEpKzSb3CRS/hy5X5SM3OpH+BJn8gaZscREZEboLIj8jen0rL4es0BAJ7vHoazk8XkRCIiciNUdkT+ZuKKvZzPthEZ6EP3hgFmxxERkRuksiPyF8fOXWDG74cBeKFHGBaLRnVERMo6lR2Rv5iwNIFsm53WdStzS4if2XFERKQImFp2Jk2aREREBN7e3nh7exMVFcWCBQsKbLNu3To6d+6Mh4cH3t7etG/fngsXLly0r6ysLJo0aYLFYiEuLq6EPoE4kgPJGXy/6SgAL2pUR0TEYZhadgIDA3n77bfZtGkTGzdupHPnzvTt25cdO3YAeUWnZ8+edO/enQ0bNhAbG8vQoUNxcro49j/+8Q9q1NCsGbl+Hyzeg81u0LmBP81rVzY7joiIFBGLYRiG2SH+qnLlyowfP56BAwfSunVrunXrxuuvv37F1yxYsIARI0bwww8/0KhRI7Zs2UKTJk0K/Z6pqan4+PiQkpKCt7f3DX4CKYt2Hk/l1o9XATB/2C00quFjciIREbmawv79LjXn7NhsNmbNmkVGRgZRUVEkJSWxfv16/P39adOmDQEBAXTo0IHVq1cXeN3JkycZNGgQ06dPp2LFioV6r6ysLFJTUws8pHx7f3E8ALdFVFfRERFxMKaXnW3btuHp6YnVamXw4MHMmzePhg0bsn//fgBGjx7NoEGDWLhwIc2aNaNLly4kJCQAYBgGAwYMYPDgwbRo0aLQ7zl27Fh8fHzyH0FBuhVAebb58FmW7ErC2cnCiG71zY4jIiJFzPSyExYWRlxcHOvXr+epp54iOjqanTt3YrfbAXjyySd59NFHadq0KR988AFhYWF8/fXXAEyYMIG0tDRGjhx5Te85cuRIUlJS8h9Hjhwp8s8lZce7MXmjOnc3q0ndqp4mpxERkaJWwewArq6uhISEANC8eXNiY2P56KOPePnllwFo2LBhge3Dw8M5fDjvOijLli1j3bp1WK3WAtu0aNGChx56iGnTpl3yPa1W60WvkfJpzd5k1u47jauzE8O6hJodR0REioHpZefv7HY7WVlZBAcHU6NGDeLj4wus37NnD7169QLg448/5o033shfd/z4cXr06MHs2bNp1apVieaWsscwDMb9b1TnwVa1CPQt3DlfIiJStphadkaOHEmvXr2oVasWaWlpzJw5kxUrVhATE4PFYuHFF19k1KhRREZG0qRJE6ZNm8bu3buZM2cOALVq1SqwP0/PvEMQ9erVIzAwsMQ/j5QtS3Yl8ceRc7i7ODOkU4jZcUREpJiYWnaSkpLo378/iYmJ+Pj4EBERQUxMDN26dQNg+PDhZGZm8txzz3HmzBkiIyNZvHgx9erVMzO2OAC73cg/V+fRtsFU9dJhTRERR1XqrrNjBl1np/z5Ke4Yz86Kw8utAqv/0Rmfii5mRxIRkWtU5q6zI1JScmx2Pli8B4An29dV0RERcXAqO1LuzNl0lIOnz1PFw5VH29YxO46IiBQzlR0pVzJzbHy8NO+ilEM6heBhLXUTEkVEpIip7Ei5MmP9YRJTMqnu48aDrWpd/QUiIlLmqexIuZGelcvE5XsBeLZLKG4uziYnEhGRkqAxfHF4hmGwdFcS7y6K53RGNnX8PLi7ua7DJCJSXqjsiENbuzeZ8Yvi2XL4HABe1gq8ccdNuDhrUFNEpLxQ2RGHtPnwWd6NiWftvtMAuLk4MaBNHQZ3qEuliq4mpxMRkZKksiMOZVdiKu8timfJriQAXJwtPNSqNk93qoe/l5vJ6URExAwqO+IQ9p9K54MlCfz3j+MAOFngnuaBDOsSqht8ioiUcyo7UqYdPXuej5cm8MPmY9jseXc+uS2iOs91q0+9qp4mpxMRkdJAZUfKpKS0TCYu38fM9YfJttkB6NLAnxHd69Ooho/J6UREpDRR2ZEy5dz5bD5fuZ+paw5yIccGQJt6VXi+exjNa/uanE5EREojlR0pE9Kzcvl69QG+XLmftKxcAJoEVeLFHmG0DfEzOZ2IiJRmKjtSqmXm2Pj290NMXLGPMxnZADSo5sUL3cPoEu6PxWIxOaGIiJR2KjtSKuXY7Hy38QgTlu7lRGomAHX8PHiuW31ua1wdJyeVHBERKRyVHSlVbHaDn+KO8eGSBA6fOQ9ADR83nu0ayt3NAqmgKx+LiMg1UtmRUsEwDGJ2nOC9RXtISEoHwM/TlSGdQniwVS2sFXTTThERuT4qO2IqwzBYmZDMuzHxbDuWAoC3WwUGd6zHgDbBVHTVf6IiInJj9JdETLPhwBnejYlnw8EzAFR0dWbgLXV4vF1dfNxdTE4nIiKOQmVHSty2oym8uyie3/acAsC1ghOPtK7NUx3r4edpNTmdiIg4GpUdKTEJJ9N4b9EeFu44AUAFJwv3tghiWJcQqvu4m5xOREQclcqOFLvDp8/z4ZI9zIs7hmGAxQJ3NKnJ8K6h1K7iYXY8ERFxcCo7UmxOpGQyYVkCs2OPkPu/m3T2aBTAiG5hhFXzMjmdiIiUFyo7UuTOZGQzacVevll3iKzcvJt0tgv144XuYUQGVTI3nIiIlDsqO1JkUjNz+GrlfiavPkBGdt5NOlvU9uWFHmG0rlvF5HQiIlJeqezIDTufncu0tYf47Ld9pFzIAaBRDW9e6BFGx/pVdf8qERExlcqOXLesXBv/WX+YT5bvIzk9C4B6VT14vnsYPRtV0/2rRESkVFDZkWuWa7Mzd/MxPlqawLFzFwAI9HVneNf63Nm0Js4qOSIiUoqo7Eih2e0G87cl8sHiPexPzgDA38vKM11C6dciCNcKukmniIiUPio7xehUWhZZuTazYxSJXYlpvL94D7sSUwHwrejCUx3r8UjrYNxddZNOEREpvVR2itHz3//Byv/dEsFReForMKhdXR67JRgvN92/SkRESj+VnWLk6mzB6iCHdtxdnenXMojB7evh6+FqdhwREZFCU9kpRl9FtzQ7goiISLnnGMMOIiIiIpehsiMiIiIOTWVHREREHJrKjoiIiDg0lR0RERFxaCo7IiIi4tBUdkRERMShqeyIiIiIQ1PZEREREYemsiMiIiIOTWVHREREHJrKjoiIiDg0lR0RERFxaCo7IiIi4tAqmB2gNDAMA4DU1FSTk4iIiEhh/fl3+8+/45ejsgOkpaUBEBQUZHISERERuVZpaWn4+Phcdr3FuFodKgfsdjvHjx/Hy8sLi8VSZPtNTU0lKCiII0eO4O3tXWT7leunn0npop9H6aKfR+min8fVGYZBWloaNWrUwMnp8mfmaGQHcHJyIjAwsNj27+3trf9QSxn9TEoX/TxKF/08Shf9PK7sSiM6f9IJyiIiIuLQVHZERETEoansFCOr1cqoUaOwWq1mR5H/0c+kdNHPo3TRz6N00c+j6OgEZREREXFoGtkRERERh6ayIyIiIg5NZUdEREQcmsqOiIiIODSVnWL06aefEhwcjJubG61atWLDhg1mRyqXxo4dS8uWLfHy8sLf35877riD+Ph4s2PJ/7z99ttYLBaGDx9udpRy69ixYzz88MNUqVIFd3d3GjduzMaNG82OVW7ZbDb+9a9/UadOHdzd3alXrx6vv/76Ve//JJenslNMZs+ezYgRIxg1ahSbN28mMjKSHj16kJSUZHa0cue3335jyJAh/P777yxevJicnBy6d+9ORkaG2dHKvdjYWD7//HMiIiLMjlJunT17lrZt2+Li4sKCBQvYuXMn7733Hr6+vmZHK7feeecdJk2axCeffMKuXbt45513GDduHBMmTDA7WpmlqefFpFWrVrRs2ZJPPvkEyLv/VlBQEM888wwvv/yyyenKt1OnTuHv789vv/1G+/btzY5TbqWnp9OsWTMmTpzIG2+8QZMmTfjwww/NjlXuvPzyy6xZs4ZVq1aZHUX+57bbbiMgIIDJkyfnL7v77rtxd3fn22+/NTFZ2aWRnWKQnZ3Npk2b6Nq1a/4yJycnunbtyrp160xMJgApKSkAVK5c2eQk5duQIUPo3bt3gX8nUvJ+/vlnWrRowb333ou/vz9Nmzblyy+/NDtWudamTRuWLl3Knj17APjjjz9YvXo1vXr1MjlZ2aUbgRaD5ORkbDYbAQEBBZYHBASwe/duk1IJ5I2wDR8+nLZt23LTTTeZHafcmjVrFps3byY2NtbsKOXe/v37mTRpEiNGjOCf//wnsbGxDBs2DFdXV6Kjo82OVy69/PLLpKam0qBBA5ydnbHZbLz55ps89NBDZkcrs1R2pFwZMmQI27dvZ/Xq1WZHKbeOHDnCs88+y+LFi3FzczM7Trlnt9tp0aIFb731FgBNmzZl+/btfPbZZyo7Jvnuu++YMWMGM2fOpFGjRsTFxTF8+HBq1Kihn8l1UtkpBn5+fjg7O3Py5MkCy0+ePEm1atVMSiVDhw7ll19+YeXKlQQGBpodp9zatGkTSUlJNGvWLH+ZzWZj5cqVfPLJJ2RlZeHs7GxiwvKlevXqNGzYsMCy8PBwfvjhB5MSyYsvvsjLL7/M/fffD0Djxo05dOgQY8eOVdm5Tjpnpxi4urrSvHlzli5dmr/MbrezdOlSoqKiTExWPhmGwdChQ5k3bx7Lli2jTp06Zkcq17p06cK2bduIi4vLf7Ro0YKHHnqIuLg4FZ0S1rZt24suxbBnzx5q165tUiI5f/48Tk4F/zw7Oztjt9tNSlT2aWSnmIwYMYLo6GhatGjBzTffzIcffkhGRgaPPvqo2dHKnSFDhjBz5kx++uknvLy8OHHiBAA+Pj64u7ubnK788fLyuuh8KQ8PD6pUqaLzqEzw3HPP0aZNG9566y3uu+8+NmzYwBdffMEXX3xhdrRyq0+fPrz55pvUqlWLRo0asWXLFt5//30ee+wxs6OVWZp6Xow++eQTxo8fz4kTJ2jSpAkff/wxrVq1MjtWuWOxWC65fMqUKQwYMKBkw8gldezYUVPPTfTLL78wcuRIEhISqFOnDiNGjGDQoEFmxyq30tLS+Ne//sW8efNISkqiRo0aPPDAA/z73//G1dXV7HhlksqOiIiIODSdsyMiIiIOTWVHREREHJrKjoiIiDg0lR0RERFxaCo7IiIi4tBUdkRERMShqeyIiIiIQ1PZEZFSZfTo0QQEBGCxWPjxxx8vWr9ixQosFgvnzp0r8WxXMnr0aJo0aWJ2DBG5BF1UUERKjV27dtGwYUPmzZtH69at8fX1xWq1FtgmOzubM2fO5BeiqVOnMnz48BItPxaLhXnz5nHHHXfkL0tPTycrK4sqVaqUWA4RKRzdG0tESo19+/YB0Ldv38ve5sPV1ZVq1aoV+XvbbDYsFstFN2AsLE9PTzw9PYs4lYgUBR3GEpGLdOzYkWHDhvGPf/yDypUrU61aNUaPHl1gm8OHD9O3b188PT3x9vbmvvvu4+TJk1fc77Zt2+jcuTPu7u5UqVKFJ554gvT0dCDvMFCfPn0AcHJyumzZ+ethrBUrVvDoo4+SkpKCxWLBYrHk58zKyuKFF16gZs2aeHh40KpVK1asWJG/n6lTp1KpUiV+/vlnGjZsiNVq5fDhw8TGxtKtWzf8/Pzw8fGhQ4cObN68Of91wcHBANx5551YLJb8538/jGW323nttdcIDAzEarXSpEkTFi5cmL/+4MGDWCwW5s6dS6dOnahYsSKRkZGsW7cuf5tDhw7Rp08ffH198fDwoFGjRvz6669X/I5F5GIqOyJySdOmTcPDw4P169czbtw4XnvtNRYvXgzk/SHv27cvZ86c4bfffmPx4sXs37+ffv36XXZ/GRkZ9OjRA19fX2JjY/n+++9ZsmQJQ4cOBeCFF15gypQpACQmJpKYmHjVjG3atOHDDz/E29s7/zUvvPACAEOHDmXdunXMmjWLrVu3cu+999KzZ08SEhLyX3/+/HneeecdvvrqK3bs2IG/vz9paWlER0ezevVqfv/9d0JDQ7n11ltJS0sDIDY2Fsi7kWxiYmL+87/76KOPeO+993j33XfZunUrPXr04Pbbby/w/gCvvPIKL7zwAnFxcdSvX58HHniA3NxcAIYMGUJWVhYrV65k27ZtvPPOOxo9ErkehojI33To0MG45ZZbCixr2bKl8dJLLxmGYRiLFi0ynJ2djcOHD+ev37FjhwEYGzZsuOQ+v/jiC8PX19dIT0/PXzZ//nzDycnJOHHihGEYhjFv3jzjar+Wli9fbgDG2bNnDcMwjClTphg+Pj4Ftjl06JDh7OxsHDt2rMDyLl26GCNHjsx/HWDExcVd8f1sNpvh5eVl/Pe//81fBhjz5s0rsN2oUaOMyMjI/Oc1atQw3nzzzQLbtGzZ0nj66acNwzCMAwcOGIDx1Vdf5a//8zvctWuXYRiG0bhxY2P06NFXzCciV6eRHRG5pIiIiALPq1evTlJSEpB3InFQUBBBQUH56xs2bEilSpXYtWvXJfe3a9cuIiMj8fDwyF/Wtm1b7HY78fHxRZp927Zt2Gw26tevn38ujaenJ7/99lv+eUGQd/7P3z/nyZMnGTRoEKGhofj4+ODt7U16ejqHDx8u9PunpqZy/Phx2rZtW2B527ZtL/p+/vr+1atXB8j/nocNG8Ybb7xB27ZtGTVqFFu3bi10BhH5fzpBWUQuycXFpcBzi8WC3W43Kc21SU9Px9nZmU2bNuHs7Fxg3V8PA7m7u190blB0dDSnT5/mo48+onbt2litVqKiosjOzi6WrH/9nv/M8uf3/Pjjj9OjRw/mz5/PokWLGDt2LO+99x7PPPNMsWQRcVQa2RGRaxYeHs6RI0c4cuRI/rKdO3dy7tw5GjZseNnX/PHHH2RkZOQvW7NmDU5OToSFhV13FldXV2w2W4FlTZs2xWazkZSUREhISIHH1WZyrVmzhmHDhnHrrbfSqFEjrFYrycnJBbZxcXG56D3/ytvbmxo1arBmzZqL9n257+dygoKCGDx4MHPnzuX555/nyy+/vKbXi4jKjohch65du9K4cWMeeughNm/ezIYNG+jfvz8dOnSgRYsWl3zNQw89hJubG9HR0Wzfvp3ly5fzzDPP8MgjjxAQEHDdWYKDg0lPT2fp0qUkJydz/vx56tevz0MPPUT//v2ZO3cuBw4cYMOGDYwdO5b58+dfcX+hoaFMnz6dXbt2sX79eh566CHc3d0ves+lS5dy4sQJzp49e8n9vPjii7zzzjvMnj2b+Ph4Xn75ZeLi4nj22WcL/dmGDx9OTEwMBw4cYPPmzSxfvpzw8PBCv15E8qjsiMg1s1gs/PTTT/j6+tK+fXu6du1K3bp1mT179mVfU7FiRWJiYjhz5gwtW7bknnvuoUuXLnzyySc3lKVNmzYMHjyYfv36UbVqVcaNGwfkzZbq378/zz//PGFhYdxxxx3ExsZSq1atK+5v8uTJnD17lmbNmvHII48wbNgw/P39C2zz3nvvsXjxYoKCgmjatOkl9zNs2DBGjBjB888/T+PGjVm4cCE///wzoaGhhf5sNpuNIUOGEB4eTs+ePalfvz4TJ04s9OtFJI+uoCwiIiIOTSM7IiIi4tBUdkRERMShqeyIiIiIQ1PZEREREYemsiMiIiIOTWVHREREHJrKjoiIiDg0lR0RERFxaCo7IiIi4tBUdkRERMShqeyIiIiIQ1PZEREREYf2f3LOmGkjOtIaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(recorder['AEP'])\n",
    "plt.title('AEP vs no of iterations')\n",
    "plt.xlabel('no of iterations')\n",
    "plt.ylabel('AEP [GWh]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "executionInfo": {
     "elapsed": 1248,
     "status": "ok",
     "timestamp": 1623710388991,
     "user": {
      "displayName": "Mikkel Friis-Møller",
      "photoUrl": "https://lh3.googleusercontent.com/a-/AOh14GiVrnxS0oNYcvEfwYdFjWYAU5G0YxLXELnknXMi=s64",
      "userId": "10444369613733539918"
     },
     "user_tz": -120
    },
    "id": "ByIaS1WJ7C2T",
    "outputId": "1e6f6299-af70-4b21-fa8a-98ce810373e1"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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3eeWVVzh8+DA9e/bEy8uLQ4cOERkZyVNPPcXIkSNvuY7GjRszd+5cRowYQdOmTfH09KR79+489dRTTJ8+nQEDBrBp0yaqVq3KDz/8wB9//MGHH36Y43+zoaGhBAQEEBMTw3PPPWdrb9u2LS+//DJAjkAE8H//93+sWLGCO++8k8GDB1OnTh0SEhLYvHkzy5Ytu+YB/la3b9myZUyePJkKFSoQHBzMnXfeydtvv22bt+fZZ5/FycmJ6dOnk5GRcc35ZzIzM+nQoQO9e/cmJiaGzz77jNatW9OjR4881QKXb0N/5JFHcHZ2pnv37jRo0ID+/fvz+eefk5iYSLt27Vi/fj2zZs2iZ8+eOc5MXc+bb77JqlWr6NatG1WqVOHMmTN89tlnVKpUidatW1/3fe+99x733HMPLVq04Mknn7Tddu/j48PYsWNzvW03c73vWVhYGM2bN+eVV14hISGBsmXLMmfOHLKysvL8GTVq1ODJJ59kw4YN+Pv789VXX3H69GlmzJiRL9vQt29f5s2bx9NPP82KFSto1aoV2dnZ7N27l3nz5tnmhrqeZ599li+++IJu3boxcuRInJ2dmTx5Mv7+/rYB9GKnTLu/TaSIiI6ONho3bmy4uLgY1apVM6ZNm2a7vfmf5s+fb7Ru3drw8PAwPDw8jFq1ahkRERFGTEyMbZ1bue0+NTXVePTRR43SpUsbQI73nz592hg4cKBRrlw5w8XFxahXr16OW7b/7qGHHjIAY+7cuba2zMxMo1SpUoaLi4tx4cKFq95z+vRpIyIiwggKCjKcnZ2NgIAAo0OHDsbnn39uW+fKbdLff/99nrbrir179xpt27Y13N3dDSDHLfibN282OnfubHh6ehqlSpUy2rdvb/z555853n/ltvDo6GjjqaeeMsqUKWN4enoajz32WI5b1XPrrbfeMipWrGg4ODjkuN380qVLxrhx44zg4GDD2dnZCAoKMl555RXj4sWLOd5fpUoVo1u3blf1u3z5cuO+++4zKlSoYLi4uBgVKlQw+vTpY+zbt8+2zrVuuzcMw1i2bJnRqlUrw93d3fD29ja6d+9um0bhiivfy3/e1n+92+b/6Ubfs9jYWKNjx46Gq6ur4e/vb7z66qtGVFTUNW+PDwsLu2b/V/bLb7/9ZtSvX99wdXU1atWqddX35nq33V+r32v9PmVmZhoTJkwwwsLCDFdXV6NMmTJG48aNjXHjxhlJSUk33AeGYRjHjh0zHnzwQcPb29vw9PQ07r33XmP//v03fZ+UbBbDuMVReCIihWTmzJkMHDiQDRs23PB//yIit0pjiERERMTuaQyRSAFKSEggMzPzussdHR1tj40ojm420Z67u7ttcHdBS01NJTU19YbrlC9fPt9ufReRkkWBSKQA9erVyzab9LVUqVIlXyYVNEtgYOANl/fv3/+qh5gWlEmTJjFu3LgbrnPo0KF8ufVbREoejSESKUCbNm264ezB7u7utGrVqhAryl/Lli274fIKFSpQp06dQqnl4MGDOR7xcC2tW7e2PaJBROTvFIhERETE7mlQtYiIiNg9jSHKJavVysmTJ/Hy8srzdPEiIiJiDsMwSElJoUKFClc9KPvvFIhy6eTJkzd8aKCIiIgUXceOHaNSpUrXXa5AlEtXHpFw7Nixq56vJCIiIkVTcnIyQUFBN31wrwJRLl25TObt7a1AJCIiUszcbLiLBlWLiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4e7momw4BL6WZXISIiUjQ4l4KbPIS1oCgQmelSOrxbwewqREREioZXT4KLhykfrUtmIiIiYvd0hshMzqUup2ERERG5fFw0iQKRmSwW004NioiIyP/okpmIiIjYPQUiERERsXsKRCIiImL3FIhERETE7ikQiYiIiN1TIBIRERG7p0AkIiIidk+BSEREROyeApGIiIjYPQUiERERsXsKRCIiImL3FIhERETE7ikQiYiIiN0zNRCNHz+epk2b4uXlhZ+fHz179iQmJibHOnFxcfTt25eAgAA8PDxo1KgR8+fPz7FOjx49qFy5Mm5ubgQGBtK3b19OnjxpW75y5Uruu+8+AgMD8fDw4I477uDbb78tlG0UERGRos/UQBQdHU1ERARr164lKiqKS5cu0alTJ9LS0mzr9OvXj5iYGBYtWsSOHTvo1asXvXv3ZsuWLbZ12rdvz7x584iJiWH+/PnExsby4IMP2pb/+eef1K9fn/nz57N9+3YGDhxIv379WLx4caFur4iIiBRNFsMwDLOLuCI+Ph4/Pz+io6Np27YtAJ6enkydOpW+ffva1vP19WXChAkMGjTomv0sWrSInj17kpGRgbOz8zXX6datG/7+/nz11Ve5qi05ORkfHx+SkpLw9vbO45aJiIiIGXJ7/C5SY4iSkpIAKFu2rK2tZcuWzJ07l4SEBKxWK3PmzOHixYuEh4dfs4+EhAS+/fZbWrZsed0wdOWz/v45IiIiYr+KTCCyWq0MHz6cVq1aUbduXVv7vHnzuHTpEr6+vri6ujJkyBAiIyMJDQ3N8f6XX34ZDw8PfH19OXr0KAsXLrzuZ82bN48NGzYwcODA666TkZFBcnJyjh8REREpmYpMIIqIiGDnzp3MmTMnR/vo0aNJTExk2bJlbNy4kREjRtC7d2927NiRY70XX3yRLVu2sHTpUhwdHenXrx/Xuhq4YsUKBg4cyBdffEFYWNh16xk/fjw+Pj62n6CgoPzZUBERESlyisQYoqFDh7Jw4UJWrVpFcHCwrT02NpbQ0FB27tyZI7x07NiR0NBQpk2bds3+jh8/TlBQEH/++SctWrSwtUdHR9OtWzcmT57MU089dcOaMjIyyMjIsL1OTk4mKChIY4hERESKkdyOIXIqxJquYhgGzz33HJGRkaxcuTJHGAJIT08HwMEh54ksR0dHrFbrdfu9suzvgWblypXce++9TJgw4aZhCMDV1RVXV9dcb4uIiIgUX6YGooiICGbPns3ChQvx8vIiLi4OAB8fH9zd3alVqxahoaEMGTKESZMm4evry4IFC4iKirLdMr9u3To2bNhA69atKVOmDLGxsYwePZqQkBDb2aEVK1Zw7733MmzYMB544AHb57i4uGhgtYiIiJh7ycxisVyzfcaMGQwYMACA/fv3M2rUKNasWUNqaiqhoaGMHDnSdhv+jh07GDZsGNu2bSMtLY3AwEC6dOnC66+/TsWKFQEYMGAAs2bNuupz2rVrx8qVK3NVq267FxERKX5ye/wuEmOIigMFIhERkeKnWM5DJCIiImIGBSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIiIiYvcUiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9UwPR+PHjadq0KV5eXvj5+dGzZ09iYmJyrBMXF0ffvn0JCAjAw8ODRo0aMX/+/Bzr9OjRg8qVK+Pm5kZgYCB9+/bl5MmTtuUXL15kwIAB1KtXDycnJ3r27FkYmyciIiLFhKmBKDo6moiICNauXUtUVBSXLl2iU6dOpKWl2dbp168fMTExLFq0iB07dtCrVy969+7Nli1bbOu0b9+eefPmERMTw/z584mNjeXBBx+0Lc/Ozsbd3Z3nn3+ejh07Fuo2ioiISNFnMQzDMLuIK+Lj4/Hz8yM6Opq2bdsC4OnpydSpU+nbt69tPV9fXyZMmMCgQYOu2c+iRYvo2bMnGRkZODs751g2YMAAEhMTWbBgQZ5qS05OxsfHh6SkJLy9vfO2YSIiImKK3B6/i9QYoqSkJADKli1ra2vZsiVz584lISEBq9XKnDlzuHjxIuHh4dfsIyEhgW+//ZaWLVteFYbyIiMjg+Tk5Bw/IiIiUjIVmUBktVoZPnw4rVq1om7durb2efPmcenSJXx9fXF1dWXIkCFERkYSGhqa4/0vv/wyHh4e+Pr6cvToURYuXHhb9YwfPx4fHx/bT1BQ0G31JyIiIkVXkQlEERER7Ny5kzlz5uRoHz16NImJiSxbtoyNGzcyYsQIevfuzY4dO3Ks9+KLL7JlyxaWLl2Ko6Mj/fr143auBr7yyiskJSXZfo4dO3bLfYmIiEjR5mR2AQBDhw5l8eLFrFq1ikqVKtnaY2Nj+eSTT9i5cydhYWEANGjQgNWrV/Ppp58ybdo027rlypWjXLly1KhRg9q1axMUFMTatWtp0aLFLdXk6uqKq6vr7W2YiIiIFAumBiLDMHjuueeIjIxk5cqVBAcH51ienp4OgINDzhNZjo6OWK3W6/Z7ZVlGRkY+VywiIiIlkamBKCIigtmzZ7Nw4UK8vLyIi4sDwMfHB3d3d2rVqkVoaChDhgxh0qRJ+Pr6smDBAqKioli8eDEA69atY8OGDbRu3ZoyZcoQGxvL6NGjCQkJyXF2aPfu3WRmZpKQkEBKSgpbt24F4I477ijszRYREZEixtTb7i0WyzXbZ8yYwYABAwDYv38/o0aNYs2aNaSmphIaGsrIkSNtt+Hv2LGDYcOGsW3bNtLS0ggMDKRLly68/vrrVKxY0dZn1apVOXLkyFWfldvN1233IiIixU9uj99Fah6iokyBSEREpPgplvMQiYiIiJhBgUhERETsngKRiIiI2D0FIhEREbF7CkQiIiJi9xSIRERExO4pEImIiIjdUyASERERu6dAJCIiInZPgUhERETsngKRiIiI2D0FIhEREbF7CkQiIiIlyNJdcWw5et7sMoodBSIREZES4j9rj/D0fzbx5KyNHD+fbnY5xYqT2QWIiIjI7TEMg8lR+5jy+wEA7q7tT4C3m8lVFS8KRCIiIsVYVraVVyN3MG/jcQCGdajO8I7VsVgsJldWvCgQiYiIFFPpmVkMnb2F3/eewcECb/esx6N3Vja7rGJJgUhERKQYOpeawROzNrLtWCKuTg588mgj7q7jb3ZZxZYCkYiISDFzLCGdfl+t59DZNEqXcubf/ZvQuEpZs8sq1hSIREREipGdJ5IYMGMDZ1MzqFjanVlPNCPUz9Pssoo9BSIREZFiYvX+eJ7+ZhNpmdnUCvBi1hPN8NfdZPlCgUhERKQYWLDlBCO/30aW1aBFNV+m92uMt5uz2WWVGApEIiIiRZhhGHyx+iDv/rIXgHvrB/J+7wa4OjmaXFnJokAkIiJSRFmtBm//vIev/jgEwJOtg3mta20cHDTHUH5TIBIRESmCMrKyGTFvGz9vPwXAa11rM7htNZOrKrkUiERERIqY5IuXeOrrjaw9mICzo4X3HmxAz4YVzS6rRFMgEhERKULiki4yYMZ69sal4OHiyPS+TWhdvZzZZZV4CkQiIiJFxIEzKfT/agMnEi9QztOVmQObUreij9ll2QUFIhERkSJg05EEnpi5kaQLlwgu58HXTzQjqGwps8uyGwpEIiIiJlu6K47nvttCRpaVO4JK89WAppT1cDG7LLuiQCQiImKib9cdYfSCnVgNuKuWH5882pBSLjo8FzbtcRERERMYhsEHUfv4+PcDAPRuUol376+Hk6ODyZXZJwUiERGRQpaVbeW1yJ3M3XgMgOfvCuVfd9fAYtGEi2ZRIBIRESlE6ZlZDJ29hd/3nsHBAm/1rMtjd1Yxuyy7p0AkIiJSSBLSMnli5ga2HkvE1cmBKX0a0ikswOyyBAUiERGRQnEsIZ3+X63n4Nk0Spdy5t/9m9C4Slmzy5L/UiASEREpYDtPJDFw5gbiUzKoWNqdWU80JdTPy+yy5G8UiERERArQmv1nefo/m0jNyKJWgBeznmiGv7eb2WXJPygQiYiIFJCFW08w8vttXMo2aF6tLJ/3a4K3m7PZZck1KBCJiIgUgC9WHeSdX/YA0K1+IJN7N8DVydHkquR6FIhERETykdVq8M4ve/j3mkMAPNEqmNe71cbBQXMMFWUKRCIiIvkkIyubkd9v56dtJwF4tWstBreppgkXiwEFIhERkXyQfPESQ77exF8Hz+HkYGHSQw3o2bCi2WVJLikQiYiI3KbTyRfp/9V69sal4OHiyLS+jWlTvbzZZUkeKBCJiIjchgNnUun/1XpOJF6gnKcrMwc2pW5FH7PLkjzKVSBKTk7Oc8fe3t55fo+IiEhxsunIeZ6ctYHE9EsEl/Ng1sBmVPYtZXZZcgtyFYhKly6dpwFhFouFffv2Ua1atVsuTEREpCiL2n2a577bzMVLVhoElear/k3w9XQ1uyy5Rbm+ZPbDDz9QtuzNn7liGAZdu3a9raJERESKsu/WH+W1yB1YDWhfszyfPtaIUi4ahVKcOeRmpSpVqtC2bVvatWt305/w8HCqVauGs/PNZ+IcP348TZs2xcvLCz8/P3r27ElMTEyOdeLi4ujbty8BAQF4eHjQqFEj5s+fn2OdHj16ULlyZdzc3AgMDKRv376cPHkyxzrbt2+nTZs2uLm5ERQUxMSJE3Oz6SIiIjaGYfBB1D5e+fFyGOrdpBJf9GuiMFQC5CoQHTp0CF9f31x3unPnToKCgm66XnR0NBEREaxdu5aoqCguXbpEp06dSEtLs63Tr18/YmJiWLRoETt27KBXr1707t2bLVu22NZp37498+bNIyYmhvnz5xMbG8uDDz5oW56cnEynTp2oUqUKmzZt4r333mPs2LF8/vnnud4mERGxb1nZVl6N3MFHy/cD8NxdoUx4oD5Ojrk6lEoRZzEMwzC7iCvi4+Px8/MjOjqatm3bAuDp6cnUqVPp27evbT1fX18mTJjAoEGDrtnPokWL6NmzJxkZGTg7OzN16lRee+014uLicHFxAWDUqFEsWLCAvXv35qq25ORkfHx8SEpK0oBxERE7cyEzm+e+28yyPWdwsMCb99Xl8eZVzC5LciG3x+9bOse3YcMGVqxYwZkzZ7BarTmWTZ48+Va6BCApKQkgx1illi1bMnfuXLp160bp0qWZN28eFy9eJDw8/Jp9JCQk8O2339KyZUvbZbu//vqLtm3b2sIQQOfOnZkwYQLnz5+nTJkyV/WTkZFBRkaG7fWt3GknIiLFX0JaJk/O2sCWo4m4OjnwcZ+GdA4LMLssyWd5DkTvvvsur7/+OjVr1sTf3z/H3We3MzW51Wpl+PDhtGrVirp169ra582bx8MPP4yvry9OTk6UKlWKyMhIQkNDc7z/5Zdf5pNPPiE9PZ3mzZuzePFi27K4uDiCg4NzrO/v729bdq1ANH78eMaNG3fL2yMiIsXfsYR0+s9Yz8H4NHzcnfl3/yY0qXrzG4yk+MlzIProo4/46quvGDBgQL4WEhERwc6dO1mzZk2O9tGjR5OYmMiyZcsoV64cCxYsoHfv3qxevZp69erZ1nvxxRd58sknOXLkCOPGjaNfv34sXrz4lkPaK6+8wogRI2yvk5OTczUuSkRESoYzyRd5YOqfnEnJoGJpd2Y90ZRQPy+zy5ICkudA5ODgQKtWrfK1iKFDh7J48WJWrVpFpUqVbO2xsbF88skn7Ny5k7CwMAAaNGjA6tWr+fTTT5k2bZpt3XLlylGuXDlq1KhB7dq1CQoKYu3atbRo0YKAgABOnz6d4zOvvA4IuPZpT1dXV1xdNZ+EiIi9+mj5fs6kZBBS3oNvBzUnwMfN7JKkAOV5aPy//vUvPv3003z5cMMwGDp0KJGRkfz+++9XXdZKT0+/XKRDzjIdHR2vGrv0d1eWXRkD1KJFC1atWsWlS5ds60RFRVGzZs1rXi4TERH7dvhsGnM3HAPg3fvrKQzZgTyfIRo5ciTdunUjJCSEOnXqXDXf0I8//pjrviIiIpg9ezYLFy7Ey8uLuLg4AHx8fHB3d6dWrVqEhoYyZMgQJk2ahK+vLwsWLCAqKso2RmjdunVs2LCB1q1bU6ZMGWJjYxk9ejQhISG0aNECgEcffZRx48bx5JNP8vLLL7Nz504++ugjPvjgg7xuvoiI2IHJUfvIshqE1yzPndVyP+2MFF95PkP0/PPPs2LFCmrUqIGvry8+Pj45fvJi6tSpJCUlER4eTmBgoO1n7ty5ADg7O/PLL79Qvnx5unfvTv369fn666+ZNWuWbTbsUqVK8eOPP9KhQwdq1qzJk08+Sf369YmOjrZd8vLx8WHp0qUcOnSIxo0b88ILL/DGG2/w1FNP5XXzRUSkhNt1MolF2y5P7vti55omVyOFJc/zEHl5eTFnzhy6detWUDUVSZqHSETEPgycsZ4VMfF0b1CBKX0aml2O3KbcHr/zfIaobNmyhISE3FZxIiIiRdH6QwmsiInHycHCC3fXMLscKUR5DkRjx45lzJgxtgHPIiIiJYFhGExccvnpBb2bBlG1nIfJFUlhyvOg6o8//pjY2Fj8/f2pWrXqVYOqN2/enG/FiYiIFJbf955h45HzuDo5MKxDdbPLkUKW50DUs2fPAihDRETEPFarwXu/xQAwsFUw/t66zd7e5DkQjRkzpiDqEBERMc2ibSfZG5eCl5sTz7TTOFl7lOcxRCIiIiVJZpaV96Munx16ul0IPqWcb/IOKYlyfYYoODj4ps8Fs1gsxMbG3nZRIiIihWXuhqMcS7hAOU9XBraqanY5YpJcB6Lhw4dfd9nhw4eZPn267VEZIiIixUF6ZhYfLT8AwLAOoZRyyfNIEikhcv0vP2zYsKvaEhISeOutt5g6dSp33nknEyZMyNfiRERECtKMPw5zNjWDoLLuPNy0stnliIluKQpfuHCByZMnM2nSJKpUqcKPP/5oe5SGiIhIcZCYnsm06MvDPF64uyYuThpWa8/yFIiys7P54osvGDduHG5ubnz88cc8/vjjNx1bJCIiUtRMiz5IysUsagV40aNBBbPLEZPlOhDNmzeP119/ncTERF577TWeeeYZXFxcCrI2ERGRAhGXdJEZfxwCLj/A1cFB/7G3d7kORI888gju7u706dOHI0eOMGrUqGuuN3ny5HwrTkREpCB8/Pt+MrKsNKlShrtq+ZldjhQBuQ5Ebdu2velt9bp0JiIiRd2hs2nM3XAMgJe61NKxS4A8BKKVK1cWYBkiIiKFY3LUPrKtBu1rlqdZcFmzy5EiQkPqRUTEbuw6mcRP204C8GLnWiZXI0VJrgLRiBEjSEtLy3Wnr7zyCgkJCbdclIiISEG48gDXHg0qUKeCt8nVSFGSq0D00UcfkZ6enutOP/30UxITE2+1JhERkXy37uA5VsbE4+RgYcTdNcwuR4qYXI0hMgyDGjVq5HrgWV7OJomIiBQ0wzCY+N+zQw83DaJqOQ+TK5KiJleBaMaMGXnu2N/fP8/vERERKQjL95xh05HzuDk78HyH6maXI0VQrgJR//79C7oOERGRApFtNWxjhwa2Csbf283kiqQo0l1mIiJSoi3adoKY0yl4uznxdNsQs8uRIkqBSERESqzMLCuTo/YB8HR4CD6lnE2uSIoqBSIRESmx5mw4yrGEC5T3cmVgy2Czy5EiTIFIRERKpPTMLD5efgCA5ztUx93F0eSKpCjLt0C0d+9eatTQvA4iIlI0zPjjMGdTM6jiW4pHmgaZXY4UcfkWiDIyMm744FcREZHCkpieybToy8ekEXfXwNlRF0TkxvQNERGREmdqdCwpF7OoFeBF9/oVzC5HigEFIhERKVHiki4y84/DALzUpSYODrl7yoLYNwUiEREpUT7+fT8ZWVaaVi1D+5p+ZpcjxUSuZqoGKFOmzA2fZZaVlZUvBYmIiNyqQ2fTmLvhGAAvdamV62dwiuQ6EH3wwQf6YomISJH2/tIYsq0Gd9Xyo2nVsmaXI8VIrgPRgAEDCrAMERGR27PzRBKLt5/CYoEXO9c0uxwpZnI9hmj9+vVkZ2dfd3lGRgbz5s3Ll6JERETy6soDXHs0qEDtQG+Tq5HiJteBqEWLFpw7d8722tvbm4MHD9peJyYm0qdPn/ytTkREJBfWHjxH9L54nBwsjLhbkwRL3uU6EBmGccPX12sTEREpSIZhMHHJXgAeaRZEFV8PkyuS4ihfb7vXoGsRESlsy/ecYfPRRNycHXj+rupmlyPFlOYhEhGRYivbatjGDj3RKhg/bzeTK5LiKtd3mQHs3r2buLg44PIpyr1795KamgrA2bNn8786ERGRG1i49QQxp1PwdnNiSNsQs8uRYixPgahDhw45xgnde++9wOVLZYZh6JKZiIgUmswsK5Oj9gHwTHgoPqWcTa5IirNcB6JDhw4VZB0iIiJ58t36oxw/fwE/L1cGtKxqdjlSzOU6EFWpUqUg6xAREcm1tIwspvx+AIDnO1TH3cXR5IqkuMvTJTOA/fv3s3DhQg4fPozFYiE4OJiePXtSrVq1gqhPRETkKjP+OMTZ1Ayq+Jbi4aZBZpcjJUCeAtH48eN54403sFqt+Pn5YRgG8fHxjBo1infffZeRI0cWVJ0iIiIAnE/LZHr05YmBR9xdA2dH3TAtty/X36IVK1bw+uuv89prr3H27FlOnTpFXFycLRCNGjWKVatWFWStIiIiTIuOJSUji9qB3nSvX8HscqSEsBi5nF764YcfpnTp0kyfPv2ay5966ilSUlL47rvv8rXAoiI5ORkfHx+SkpLw9tYzckREzBCXdJF2760gI8vKjAFNaV/Lz+ySpIjL7fE7Tw937du373WX9+3bl7Vr1+atShERkTz4aPl+MrKsNKtalvCa5c0uR0qQXAei06dPU7Vq1esuDw4Otk3aKCIikt8Oxqcyb+MxAF7qUlNz30m+ynUgunjxIi4uLtdd7uzsTGZmZr4UJSIi8k+To/aRbTXoUMuPJlXLml2OlDB5usvsyy+/xNPT85rLUlJS8vzh48eP58cff2Tv3r24u7vTsmVLJkyYQM2aNW3rxMXF8eKLLxIVFUVKSgo1a9bktdde44EHHgDg8OHDvPXWW/z+++/ExcVRoUIFHn/8cV577bUcAW7evHm8++677Nu3j/LlyzN06FBefPHFPNcsIiKFb+eJJBZvP4XFAiM717z5G0TyKNeBqHLlynzxxRc3XScvoqOjiYiIoGnTpmRlZfHqq6/SqVMndu/ejYeHBwD9+vUjMTGRRYsWUa5cOWbPnk3v3r3ZuHEjDRs2ZO/evVitVqZPn05oaCg7d+5k8ODBpKWlMWnSJAB+/fVXHnvsMaZMmUKnTp3Ys2cPgwcPxt3dnaFDh+apZhERKXwT//sA1/saVKB2oG5skfyX67vMCkN8fDx+fn5ER0fTtm1bADw9PZk6dWqOAd2+vr5MmDCBQYMGXbOf9957j6lTp3Lw4OV5Kh599FEuXbrE999/b1tnypQpTJw4kaNHj+bqOrTuMhMRMcdfsefo88VanBws/P5COJV9S5ldkhQj+X6X2c0cP36cp5566rb6SEpKAqBs2f9dG27ZsiVz584lISEBq9XKnDlzuHjxIuHh4Tfs5+99ZGRk4ObmlmMdd3d3jh8/zpEjR67ZR0ZGBsnJyTl+RESkcBmGwcTf9gLQp1llhSEpMPkWiM6dO8e///3vW36/1Wpl+PDhtGrVirp169ra582bx6VLl/D19cXV1ZUhQ4YQGRlJaGjoNfs5cOAAU6ZMYciQIba2zp078+OPP7J8+XKsViv79u3j/fffB+DUqVPX7Gf8+PH4+PjYfoKCNDW8iEhhW7bnDFuOJuLu7Mhzd137775Ifigy851HRESwc+dO5syZk6N99OjRJCYmsmzZMjZu3MiIESPo3bs3O3bsuKqPEydO0KVLFx566CEGDx5sax88eDBDhw7l3nvvxcXFhebNm/PII48A4OBw7V3wyiuvkJSUZPs5duxYPm6tiIjcTLbV4L3/nh16onVV/LzdbvIOkVuXb2OItm3bRqNGjcjOzs7ze4cOHcrChQtZtWoVwcHBtvbY2FjbQOmwsDBbe8eOHQkNDWXatGm2tpMnTxIeHk7z5s2ZOXPmNYNOdnY2cXFxlC9fnuXLl9O1a1fOnDlD+fI3n9xLY4hERArXj5uPM2LeNnzcnVn1Unt83J3NLkmKodwev/P8tPv8ZBgGzz33HJGRkaxcuTJHGAJIT08Hrj6L4+joiNVqtb0+ceIE7du3p3HjxsyYMeO6Z30cHR2pWLEiAN999x0tWrTIVRgSEZHClZGVzeSofQA8Ex6iMCQFLteBqFevXjdcnpiYmOcPj4iIYPbs2SxcuBAvLy/bTNc+Pj64u7tTq1YtQkNDGTJkCJMmTcLX15cFCxYQFRXF4sWLgcthKDw8nCpVqjBp0iTi4+Nt/QcEBABw9uxZfvjhB8LDw7l48SIzZszg+++/Jzo6Os81i4hIwftu3VGOn7+An5cr/VtUNbscsQO5DkQ+Pj43Xd6vX788ffjUqVMBrrpjbMaMGQwYMABnZ2d++eUXRo0aRffu3UlNTSU0NJRZs2bRtWtXAKKiojhw4AAHDhygUqVKOfr5+9XAWbNmMXLkSAzDoEWLFqxcuZJmzZrlqV4RESl4aRlZfLLiAADDOlbH3cXR5IrEHhSpeYiKMo0hEhEpHFOW7+f9qH1U9S1F1Ih2ODsWmft/pBgq9HmIREREbtf5tEw+X3V5Ut0RnWoqDEmh0TdNRESKjKnRsaRkZFEn0Jt76wWaXY7YEQUiEREpEk4lXWDWn4cBeLFLTRwcbv5YJZH8okAkIiJFwsfL95ORZaVZcFnCa2hKFClcCkQiki8Mw+Cv2HNM+i2G4+fTzS5HipmD8anM23gcgJe71MzVQ7dF8pOpEzOKSPFnGAbL95zh05UH2HI0EYBZfx1mfK963Fu/grnFSbHxftQ+sq0GHWv70bhK2Zu/QSSfKRCJyC3Jyrby845TTF0Zy964FABcnByoVMadg/FpDJ29hVX74hnTPQwPV/2pkevbeSKJn7efwmKBkZ1rml2O2Cn9lRKRPMnIyubHzSeYFh3LkXOXL415uDjyeIsqPNk6mDKlXPho2X4+XXmAeRuPs/HweT56pCH1Kt14clexXxN/iwGg5x0VqRWged7EHApEIpIraRlZfLf+KF+sPsjp5AwAypRyZmCrYPq3qIpPqf89a2pk55q0rl6Of83dysGzafSa+gcvdq7JoNbVdOeQ5PBX7DlW7YvH2dHCvzrWMLscsWMKRCJyQ4npmcz68wgz/jxEYvolAAK83Rjcthp9mgVRyuXaf0aaV/Pl12FteHn+dn7bdZp3f9nL6v1nef+hBvh5uxXmJkgRZRgGE3/bC8CjzSpT2beUyRWJPdOjO3JJj+4Qe3Mm+SL/XnOI/6w9QlpmNgBVfEvxTLsQ7m9UEVen3D1fyjAMvlt/jDcX7+LiJStlPVyY9FB97qrlX5DlSzGwdFccT32zCXdnR1a91J7yXq5mlyQlUG6P3zpDJCI5HEtIZ/qqWOZtPE5mlhWAWgFePNs+lK51A3DK46MULBYLj95ZmWbBZXjuu63sOZXMEzM3MqBlVUbdUws3Zz240x5lWw3e++/YoSdbBysMiekUiEQEgH2nU5i6MpZF206Sbb184rhR5dIMvSuU9jX9bntemFA/LyKfbcnEJTF89cchZv55mLUHzzGlT0Oq+3vlxyZIMbJgywn2n0nFx92ZwW2rmV2OiAKRiL3beiyRz1YcYOnu07a2NtXLEdE+lDuDy+brBHluzo680b0ObaqXY+T329gbl8K9U9Yw+t46PHZnZU3GZycysrKZHLUPgGfDQ/Bxd77JO0QKngKRiB26Mqv0pysP8MeBcwBYLNAlLIBnw0ML/Bb59rX8+HV4G16Yt43V+8/y+oKdrNoXz4QH6lPGw6VAP1vM9926o5xIvIC/tyv9W1Y1uxwRQIFIxK5YrQbL957h0xUH2HosEQBHBws976jIM+HVCPUrvEtXfl5uzBrYjK/+OMSEJXtZuvs024+vZvLDDWgZUq7Q6pDClZaRxZTfDwAwrEMNjSGTIkOBSMQOXJlV+rMVscScvjyrtKuTAw83DWJwm2oElTXndmcHBwuD2lSjeTVfnp+zhYPxaTz25TqeDQ9heMcaOOdxALcUfV+tOcS5tEyCy3nwUJNKZpcjYqNAJFKCZWRlM3/T5VmljyZcnlXa09WJvi2q8ESronNnT92KPix+rjXjFu1m7sZjfLoilj8OnOPjRxpqbpoSJCEtk89XHQRgxN0KvFK0KBCJlEBpGVnMXnd5VukzKZdnlS7r4cITrarSt0XVIjmItZSLExMerE/bGuV55cftbD2WSNePV/NWzzDub6gzCSXB1JUHSMnIIqyCN93qBZpdjkgOCkQiJUhieiYz/zzMzD8P22aVDvRx46m21Xi46fVnlS5KutUP5I7KpRk+ZwsbDp/nX3O3sWrfWd68Lwwvt6IX5CR39sYlM+uvIwC82LmmHuEiRU7R/+soIjd1OvkiX64+yLfrjpL+31mlg8t58Ey7EHo2rIiLU/G6NFGxtDvfDW7Opyti+Wj5PiK3nGDTkfN89MgdNKxcxuzyJI9+2xXHiLlbycyy0qKaL+1qlDe7JJGr6NEduaRHd0hRdPRcOtNWxfLDxuNkZl+eVbp2oDcR7UO4p24gjiXgf+EbDycwbM5WTiRewMnBwr/ursHT7UJKxLaVdFarwUfL9/PR8v0AtAzx5ZNHG1FWUytIIcrt8VuBKJcUiKQoiYlLYerKAyzadpL/TipNkypliLgrlPAa5UvcBIdJFy7xWuQOFm8/BUCLar588PAdBPjoIbFFVWpGFiPmbrVN+DmwVVVe61o7z49+EbldCkT5TIFIioItR8/z2cpYov42q3S7GuWJaB9Ks+CyJlZW8AzD4IdNxxmzaBfpmdmULuXMhAfq0zkswOzS5B8On03jqW82su90Ki5ODrx7fz0ebKyB8WIOBaJ8pkAkZjEMgz9jz/HpigP8Gfu/WaW71g3kmfAQ6lYs2Fmli5qD8akMm7OVHSeSAHjszsq83q0O7i6a4K8oWLUvnqGzN5N8MQt/b1em923CHUGlzS5L7JgCUT5TIJLCZrUaLNtzmk9XxrLtv7NKOzlYuL9hRZ4ODyGkvKe5BZooM8vK+0tjmP7fOW2q+3nycZ+G1A7U76ZZDMPgi9UH+b9f92I1oGHl0kx/vDF+3rqsKeZSIMpnCkRS2N5YuJOv/3ubspuzA480rczgttWoWNrd5MqKjtX74xkxbxvxKRm4ODnw6j216N+yaokbQ1XUXbyUzaj521mw9SQADzcJ4s2eYbg66aydmE+BKJ8pEElh2nL0PPd/9icAz4SH8GTrYMp5Fo1ZpYuac6kZvPjDdn7fewaAu2r58d6D9fHV/ioUJxMvMOSbTew4kYSTg4U3utehb/MqCqVSZOT2+K3h/iJFjNVqMHbRLgAeaFSJl7vUUhi6AV9PV/7dvwlju9fBxcmB3/eeoctHq1m9P97s0kq89YcS6PHJGnacSKKshwvfPHkn/VroDJ0UTwpEIkXMD5uOs+14Ep6uTrx8T02zyykWLBYLA1oFszCiFdX9PIlPyaDvv9fz7i97yMyyml1eifSftUd49Iu1nE3NpE6gN4uGtqJFiK/ZZYncMgUikSIk6cIlJizZC8CwDtXx89KA1LyoHejNoqGteezOygB8vuogD0z9k4PxqSZXVnJkZll5NXIHry/YSZbV4N76gcx/piWVyughvFK8KRCJFCEfLdvPubRMQsp70L9lVbPLKZbcXRx55/56TO/bmNKlnNlxIol7p6xh3sZjaMjk7YlPyeCxL9cye91RLBZ4uUstpvRpqCkPpERQIBIpIvadTmHWX4cBGNsjrNg9f6yo6RwWwK/D2tC8WlnSM7N56YftPPfdFpIuXDK7tGJp+/FEenyyhg2Hz+Pl5sRX/ZvyTHiIxgtJiaG/uCJFgGEYjPtpF9lWg051/GlTXQ+/zA+BPu58O6g5L3auiaODhcXbT9H1o9VsPJxgdmnFSuSW4zw07S9OJV0kpLwHCyNa0b6Wn9llieQrBSKRImDJzjj+OHAOVycHRt9bx+xyShRHBwsR7UP54ekWVC5bihOJF+g9/S8+XLaPrGwNuL6RrGwr7/y8m3/N3UZGlpUOtfyIjGhFNTueFFRKLgUiEZNdyMzm7Z/3ADCkXQhBZTU4tSA0rFyGn59vzf0NK2I14MNl++nzxVqOn083u7QiKTE9k4EzN/DF6kMADG0fyhf9muDt5mxyZSIFQ4FIxGTTomM5kXiBiqXdeaZdiNnllGhebs588PAdfPBwAzxdndhw+Dz3fLSan7efMru0IiUmLoUen/zB6v1ncXd25LPHGjGyc00cHDReSEouBSIREx1LSGdadCwAr3Wrrbt1Csn9DSvx8/OtaRBUmpSLWUTM3kzv6X+xePtJLtn5ZbQlO+O4/7M/OJqQTqUy7vz4bEu61gs0uyyRAudkdgEi9uydn/eQkWWlRTVf7qkbYHY5dqWKrwc/PN2CD5ftY1r0QdYfSmD9oQT8vFx5pFllHm1WmQAf+5kHymo1+Gj5fj5avh+AliG+fPJoI8p6uJhcmUjh0LPMcknPMpP8tmb/WR7/9zocHSz8OqwNNfy9zC7Jbp1KusB3644ye/0xzqZmAJcHY3cO8+fx5lVoUc23RN9enpqRxYi5W1m6+zQAA1tV5bWutXFy1EUEKf70cNd8pkAk+elStpV7PlrNgTOpDGxVlTHdw8wuSbg8C/Nvu+L45q8jrP/brfmhfp70bV6FXo0q4lXCBhUfPpvG4K83sv9MKi6ODrxzf10eahJkdlki+UaBKJ8pEEl++nL1Qd7+eQ++Hi78PjIcH/eSdZAtCfbGJfPNX0eI3HKC9MxsAEq5OHJ/w4r0a1GVmgHF/4xe9L54npu9meSLWfh7uzLt8cY0rFzG7LJE8pUCUT5TIJL8Ep+SwV2TVpKSkcWEB+rxcNPKZpckN5B88RKRm0/w9V+HiY1Ps7U3q1qWvi2q0DksoNjNKm4YBl+sPsj//boXqwENK5dm+uON8fO2nzFTYj9ye/zWoGqRQjZxyV5SMrKoX8mHhxrr0kRR5+3mTP+WVenXogp/xZ7jm7VHWLr7NOsPJ7D+cALlvVzp0zSIPndWJtDH3exyb+ripWxGzd/Ogq0nAXi4SRBv9gzD1Ul3OIp90xmiXNIZIskPW46e5/7P/gQg8tmWujxRTJ1KusB364/x3fqjxKf8bxD23bX96deiCi1CiuYg7BOJFxjyzUZ2nkjG0cHCG/fWoV+LKkWyVpH8oktm+UyBSG6X1Wpw/2d/sO14Eg82rsSkhxqYXZLcpswsK0t3x/H1X0dYf+h/g7BDyntcHoTduFKRmdl5/aEEnv12E2dTMynr4cKnjzaiRYiv2WWJFDgFonymQCS3a96GY7w0fzuerk78PrIdfl4ar1GSxMSl8M3aw0RuPkHaPwZh921RhVoB5v3d+M/aI4xdtIssq0GdQG8+79eYSmX0iBixDwpE+UyBSG5H0oVL3DVpJefSMnm9W20GtalmdklSQFIuXiJyywm+/usIB86k2tqbVS3L4y2q0KUQB2FnZlkZs2gX360/CsC99QN578EGmhFd7Epuj9+m3hoxfvx4mjZtipeXF35+fvTs2ZOYmJgc68TFxdG3b18CAgLw8PCgUaNGzJ8/37b88OHDPPnkkwQHB+Pu7k5ISAhjxowhMzMzRz+//fYbzZs3x8vLi/Lly/PAAw9w+PDhwthMET5atp9zaZmElPegX4uqZpcjBcjLzZl+LaoS9a+2fDe4OV3rBeDoYGH94QSe/24LLf/vd95fGsOppAsFWkd8SgaPfrGW79YfxWKBl7rUZEqfhgpDItdhaiCKjo4mIiKCtWvXEhUVxaVLl+jUqRNpaf+7tbVfv37ExMSwaNEiduzYQa9evejduzdbtmwBYO/evVitVqZPn86uXbv44IMPmDZtGq+++qqtj0OHDnHfffdx1113sXXrVn777TfOnj1Lr169Cn2bxf7sO53CrL8OAzC2R1ixu0Vbbo3FYqFFiC+fPdaYP16+i2EdquPn5crZ1Aym/H6A1hNWMOSbjfxx4Cz5faJ++/FEenyyho1HzuPl5sRX/ZvybHioBk+L3ECRumQWHx+Pn58f0dHRtG3bFgBPT0+mTp1K3759bev5+voyYcIEBg0adM1+3nvvPaZOncrBgwcB+OGHH+jTpw8ZGRk4OFw+GP3000/cd999ZGRk4Ox880GPumQmt8IwDB77ch1/xp6jc5g/0/s2MbskMdGl7P/NhL3ub4Owq/13EPYD+TAIO3LLcUbN30FGlpWQ8h583q8JIeU9b7d0kWKrWFwy+6ekpCQAypYta2tr2bIlc+fOJSEhAavVypw5c7h48SLh4eE37OfvfTRu3BgHBwdmzJhBdnY2SUlJfPPNN3Ts2PG6YSgjI4Pk5OQcPyJ5tWRnHH/GnsPVyYHXu9UxuxwxmbOjA/fWr8DcIS34bXhb+javgoeLIwfj0xj3027ufGc5r/y4gz2n8v73JivbytuLd/OvudvIyLLSoZYfkRGtFIZEcqnInCGyWq306NGDxMRE1qxZY2tPTEzk4YcfZunSpTg5OVGqVCm+//57OnXqdM1+Dhw4QOPGjZk0aRKDBw+2tUdHR9O7d2/OnTtHdnY2LVq04JdffqF06dLX7Gfs2LGMGzfuqnadIZLcupCZTcfJ0ZxIvMDzHaoz4u4aZpckRVDKxUss+O8g7P1/G4TdpEoZ+raowj11A296mTUxPZPnvtvC6v1nARjaPpQRd9fAwUGXyESK3V1mzzzzDL/++itr1qyhUqVKtvbnnnuO9evX8+6771KuXDkWLFjABx98wOrVq6lXr16OPk6cOEG7du0IDw/nyy+/tLXHxcXRtm1bevbsSZ8+fUhJSeGNN97AycmJqKioa15Xz8jIICMjw/Y6OTmZoKAgBSLJtQ+i9vHR8v1ULO3OshHtNJhVbsgwDNYdSuCbv47w2644sqyX/zSX83SlT7Mg+jSrTIXSV8+EHROXwuCvN3I0IR13Z0cmPdSAbvUDC7t8kSKrWAWioUOHsnDhQlatWkVwcLCtPTY2ltDQUHbu3ElY2P+eBt6xY0dCQ0OZNm2are3kyZOEh4fTvHlzZs6caRsrBDB69GiWLFnChg0bbG3Hjx8nKCiIv/76i+bNm9+0Ro0hkrw4lpBOx8nRZGRZ+eyxRnStpwOU5N7p5It8t/4os9cd5cx/Z8J2sMDddfzp27wqrUIvz4S9ZGccI+ZtJT0zm0pl3Pm8bxPqVNDfJ5G/KxbPMjMMg+eee47IyEhWrlyZIwwBpKenA+QINwCOjo5YrVbb6xMnTtC+fXsaN27MjBkzrlo/PT39mn0AOfoRyS9v/7ybjCwrLUN8uadugNnlSDHj7+3G8I41iGgfStTu03z912HWHkzgt12n+W3XaaqV96BR5TL8sOk4AC1DfPnk0UaU9XAxuXKR4svUM0TPPvsss2fPZuHChdSsWdPW7uPjg7u7O5cuXaJOnToEBgYyadIkfH19WbBgAS+++CKLFy+ma9eunDhxgvDwcKpUqcKsWbNsQQcgIODygej333+nY8eOjB071nbJ7NVXX2Xv3r3s2bMHd/ebP5BRZ4gkt1bvj6fvv9fj6GDh12FtqOHvZXZJUgLsO53Cf9YeYf6m47aZsAEGtqrKa11r4+RYpO6RESkyisUls+vNiTFjxgwGDBgAwP79+xk1ahRr1qwhNTWV0NBQRo4cabsNf+bMmQwcOPCa/fx90+bMmcPEiRPZt28fpUqVokWLFkyYMIFatWrlqlYFIsmNS9lW7vloNQfOpDKwVVXGdA+7+ZtE8iA1I4vILSdYuiuO+xtWpFejSjd/k4gdKxaBqDhRIJLc+HL1Qd7+eQ++Hi78PjIcH/ei8WBPERF7VSznIRIpzuJTMvho2X7g8mMSFIZERIoPBSKRfDJhyV5SMrKoX8mHhxoHmV2OiIjkgQKRSD7YcvS87Y6fcT3CNCGeiEgxo0AkcpusVoOxi3YB8GDjSjSsXMbkikREJK8UiERu0w+bjrPteBJerk683CV3dy2KiEjRokAkchuSLlxiwpK9AAzrWJ3yXq4mVyQiIrdCgUjkNny4bB/n0jIJ9fOkf8uqZpcjIiK3SIFI5BbtO53C138dAWBM9zo4a6ZgEZFiS3/BRW6BYVweSJ1tNegc5k+b6uXNLklERG6DApHILViyM44/Y8/h6uTA693qmF2OiIjcJgUikTy6kJnN2z/vAWBIuxCCypYyuSIREbldCkQieTQ1OpYTiReoWNqdZ9qFmF2OiIjkAwUikTw4lpDOtOhYAF7rVht3F0eTKxIRkfygQCSSB2//vJvMLCstQ3y5p26A2eWIiEg+USASyaXV++P5bddpHB0sjO0RhsWi55WJiJQUCkQiuXAp28q4n3YD0K9FFWr4e5lckYiI5CcFIpFcmPXnYQ6cScXXw4XhHWuYXY6IiOQzBSKRmziTcpEPl+0H4KUuNfFxdza5IhERyW8KRCI3MXFJDKkZWTSo5MNDjYPMLkdERAqAApHIDWw+ep4fNh0HYGyPMBwcNJBaRKQkUiASuQ6r9fLzygAebFyJhpXLmFyRiIgUFAUikev4ftMxth9PwsvViZe71DK7HBERKUAKRCLXkHThEhOXxAAwrGN1ynu5mlyRiIgUJAUikWv4cNk+zqVlEurnSf+WVc0uR0RECpgCkcg/xMSl8PVfRwAY070Ozo76NRERKen0l17kbwzDYNxPu8i2GnQO86dN9fJmlyQiIoVAgUjkb37dGcefsedwdXLg9W51zC5HREQKiQKRyH9dyMzmnZ/3ADCkXQhBZUuZXJGIiBQWBSKR/5oaHcuJxAtULO3OM+1CzC5HREQKkQKRCHAsIZ1p0bEAvN6tNu4ujiZXJCIihUmBSAR4++fdZGZZaRniS5e6AWaXIyIihUyBSOze6v3x/LbrNI4OFsb2CMNi0fPKRETsjQKR2LVL2Vbb88r6tahCDX8vkysSEREzKBCJXZv152Fi49Pw9XBheMcaZpcjIiImUSASu3Um5SIfLtsPwMtdauHj7mxyRSIiYhYFIrFbE5fEkJqRRYNKPjzYuJLZ5YiIiIkUiMQubT56nh82HQdgbI8wHBw0kFpExJ4pEIndsVoN20DqhxpXomHlMiZXJCIiZlMgErvz/aZjbD+ehJerEy91qWV2OSIiUgQoEIldSbpwiYlLYgAY1rE65b1cTa5IRESKAgUisSsfLtvHubRMQv086d+yqtnliIhIEaFAJHYjJi6Fr/86AsDY7mE4O+rrLyIil+mIIHbBMAzG/bSLbKtBl7AAWlcvZ3ZJIiJShCgQiV1YtO0kf8aew9XJgde61Ta7HBERKWKczC5ApCDFp2Qwcclevv/vnENPtwshqGwpk6sSEZGiRoFISqTMLCuz/jzMx8v3k5KRBcCDjSvxTHiIyZWJiEhRpEAkJc7KmDO8uXg3B+PTAKhfyYexPcJopAkYRUTkOhSIpMQ4fDaNt3/ezbI9ZwAo5+nCS11q8WCjSno0h4iI3JCpg6rHjx9P06ZN8fLyws/Pj549exITE5Njnbi4OPr27UtAQAAeHh40atSI+fPn25YfPnyYJ598kuDgYNzd3QkJCWHMmDFkZmba1hk7diwWi+WqHw8Pj0LbVik4aRlZTFiyl04frGLZnjM4OVgY1DqY30eG07tJkMKQiIjclKlniKKjo4mIiKBp06ZkZWXx6quv0qlTJ3bv3m0LK/369SMxMZFFixZRrlw5Zs+eTe/evdm4cSMNGzZk7969WK1Wpk+fTmhoKDt37mTw4MGkpaUxadIkAEaOHMnTTz+d47M7dOhA06ZNC32bJf8YhsHCrScZ/+seTidnANC2RnneuLcOoX6eJlcnIiLFicUwDMPsIq6Ij4/Hz8+P6Oho2rZtC4CnpydTp06lb9++tvV8fX2ZMGECgwYNumY/7733HlOnTuXgwYPXXL5t2zbuuOMOVq1aRZs2bXJVW3JyMj4+PiQlJeHt7Z3HLZP8tuN4EmN/2sWmI+cBqFy2FG/cW4cOtf2wWHRGSERELsvt8btIjSFKSkoCoGzZsra2li1bMnfuXLp160bp0qWZN28eFy9eJDw8/Ib9/L2Pf/ryyy+pUaNGrsOQFB3nUjOYtDSGORuOYRhQysWRiPahPNk6GDdnR7PLExGRYqrIBCKr1crw4cNp1aoVdevWtbXPmzePhx9+GF9fX5ycnChVqhSRkZGEhoZes58DBw4wZcoU2+Wyf7p48SLffvsto0aNumE9GRkZZGRk2F4nJyffwlZJfrmUbeWbv47wwbJ9pFy8fBt9zzsqMOqe2gT4uJlcnYiIFHdFJhBFRESwc+dO1qxZk6N99OjRJCYmsmzZMsqVK8eCBQvo3bs3q1evpl69ejnWPXHiBF26dOGhhx5i8ODB1/ycyMhIUlJS6N+//w3rGT9+POPGjbu9jZJ8sWb/Wcb9tIv9Z1IBqFvRm7Hdw2hS9fpnAUVERPKiSIwhGjp0KAsXLmTVqlUEBwfb2mNjY20DpcPCwmztHTt2JDQ0lGnTptnaTp48SXh4OM2bN2fmzJk4OFz7BroOHTrg7e1NZGTkDWu61hmioKAgjSEqRMcS0nn75938tus0AGU9XHixc016NwnCUXeOiYhILhSLMUSGYfDcc88RGRnJypUrc4QhgPT0dICrwo2joyNWq9X2+sSJE7Rv357GjRszY8aM64ahQ4cOsWLFChYtWnTT2lxdXXF1dc3rJkk+SM/MYurKWKavOkhmlhVHBwv9WlRheIca+JRyNrs8EREpgUwNRBEREcyePZuFCxfi5eVFXFwcAD4+Pri7u1OrVi1CQ0MZMmQIkyZNwtfXlwULFhAVFcXixYuBy2EoPDycKlWqMGnSJOLj4239BwQE5Pi8r776isDAQO65557C20jJNcMw+Gn7Kcb/sodTSRcBaBXqy5juYdTw9zK5OhERKclMDURTp04FuOqOsRkzZjBgwACcnZ355ZdfGDVqFN27dyc1NZXQ0FBmzZpF165dAYiKiuLAgQMcOHCASpUq5ejn71cDrVYrM2fOZMCAATg66m6kombXySTGLdrN+sMJAFQq487r3erQOcxft9GLiEiBKxJjiIoDzUNUMBLSMnl/aQzfrT+K1QA3ZwciwkMZ3LaabqMXEZHbVizGEIn9ysq28u26o0yO2kfShUsAdG9QgVfuqUWF0u4mVyciIvZGgUgK3Z+xZxm3aDcxp1MAqBXgxbgeYdxZzdfkykRExF4pEEmhOX4+nXd/2cMvOy4Pni9dypkXOtWkT9MgnBxNfc6wiIjYOQUiKXAXMrOZFh3LtOhYMrKsOFjg8eZVGHF3DUqXcjG7PBEREQUiKTiGYfDrzjje+XkPJxIvANC8WlnGdA+jdqAGpouISNGhQCQFYm9cMmMX7WLtwcu30VfwceO1bnXoWi9At9GLiEiRo0Ak+SoxPZMPovbxzdojWA1wdXLg6XYhPN0uBHcX3UYvIiJFkwKR5Itsq8F364/y/tIYzqdfvo3+nroBvNq1NkFlS5lcnYiIyI0pEMltW3fwHGN/2s2eU8kA1PD3ZGz3MFqGljO5MhERkdxRIJJbdjLxAu/+sofF208B4O3mxAudavLYnZV1G72IiBQrCkQmO34+3ewS8swwYMGWE3y68gAXL1mxWKBPs8qM7FSTsh66jV5ERIofBSKT3fV+NJlZVrPLuGVNq5ZhTPcw6lb0MbsUERGRW6ZAZDJXJweK403ogT5u/OvuGvRoUEG30YuISLGnQGSyHWM7m12CiIiI3dPIVxEREbF7CkQiIiJi9xSIRERExO4pEImIiIjdUyASERERu6dAJCIiInZPgUhERETsngKRiIiI2D0FIhEREbF7CkQiIiJi9xSIRERExO4pEImIiIjdUyASERERu6dAJCIiInbPyewCigvDMABITk42uRIRERHJrSvH7SvH8etRIMqllJQUAIKCgkyuRERERPIqJSUFHx+f6y63GDeLTAKA1Wrl5MmTeHl5YbFY8q3f5ORkgoKCOHbsGN7e3vnWr+Sk/Vw4tJ8Lj/Z14dB+LhwFuZ8NwyAlJYUKFSrg4HD9kUI6Q5RLDg4OVKpUqcD69/b21i9bIdB+Lhzaz4VH+7pwaD8XjoLazzc6M3SFBlWLiIiI3VMgEhEREbunQGQyV1dXxowZg6urq9mllGjaz4VD+7nwaF8XDu3nwlEU9rMGVYuIiIjd0xkiERERsXsKRCIiImL3FIhERETE7ikQiYiIiN1TIDLZp59+StWqVXFzc+POO+9k/fr1ZpdUoowfP56mTZvi5eWFn58fPXv2JCYmxuyySrz/+7//w2KxMHz4cLNLKXFOnDjB448/jq+vL+7u7tSrV4+NGzeaXVaJkp2dzejRowkODsbd3Z2QkBDeeuutmz4LS25u1apVdO/enQoVKmCxWFiwYEGO5YZh8MYbbxAYGIi7uzsdO3Zk//79hVKbApGJ5s6dy4gRIxgzZgybN2+mQYMGdO7cmTNnzphdWokRHR1NREQEa9euJSoqikuXLtGpUyfS0tLMLq3E2rBhA9OnT6d+/fpml1LinD9/nlatWuHs7Myvv/7K7t27ef/99ylTpozZpZUoEyZMYOrUqXzyySfs2bOHCRMmMHHiRKZMmWJ2acVeWloaDRo04NNPP73m8okTJ/Lxxx8zbdo01q1bh4eHB507d+bixYsFX5whpmnWrJkRERFhe52dnW1UqFDBGD9+vIlVlWxnzpwxACM6OtrsUkqklJQUo3r16kZUVJTRrl07Y9iwYWaXVKK8/PLLRuvWrc0uo8Tr1q2b8cQTT+Ro69Wrl/HYY4+ZVFHJBBiRkZG211ar1QgICDDee+89W1tiYqLh6upqfPfddwVej84QmSQzM5NNmzbRsWNHW5uDgwMdO3bkr7/+MrGyki0pKQmAsmXLmlxJyRQREUG3bt1yfK8l/yxatIgmTZrw0EMP4efnR8OGDfniiy/MLqvEadmyJcuXL2ffvn0AbNu2jTVr1nDPPfeYXFnJdujQIeLi4nL8/fDx8eHOO+8slOOiHu5qkrNnz5KdnY2/v3+Odn9/f/bu3WtSVSWb1Wpl+PDhtGrVirp165pdTokzZ84cNm/ezIYNG8wupcQ6ePAgU6dOZcSIEbz66qts2LCB559/HhcXF/r37292eSXGqFGjSE5OplatWjg6OpKdnc0777zDY489ZnZpJVpcXBzANY+LV5YVJAUisRsRERHs3LmTNWvWmF1KiXPs2DGGDRtGVFQUbm5uZpdTYlmtVpo0acK7774LQMOGDdm5cyfTpk1TIMpH8+bN49tvv2X27NmEhYWxdetWhg8fToUKFbSfSzBdMjNJuXLlcHR05PTp0znaT58+TUBAgElVlVxDhw5l8eLFrFixgkqVKpldTomzadMmzpw5Q6NGjXBycsLJyYno6Gg+/vhjnJycyM7ONrvEEiEwMJA6derkaKtduzZHjx41qaKS6cUXX2TUqFE88sgj1KtXj759+/Kvf/2L8ePHm11aiXbl2GfWcVGByCQuLi40btyY5cuX29qsVivLly+nRYsWJlZWshiGwdChQ4mMjOT3338nODjY7JJKpA4dOrBjxw62bt1q+2nSpAmPPfYYW7duxdHR0ewSS4RWrVpdNW3Evn37qFKlikkVlUzp6ek4OOQ8PDo6OmK1Wk2qyD4EBwcTEBCQ47iYnJzMunXrCuW4qEtmJhoxYgT9+/enSZMmNGvWjA8//JC0tDQGDhxodmklRkREBLNnz2bhwoV4eXnZrkP7+Pjg7u5ucnUlh5eX11Xjsjw8PPD19dV4rXz0r3/9i5YtW/Luu+/Su3dv1q9fz+eff87nn39udmklSvfu3XnnnXeoXLkyYWFhbNmyhcmTJ/PEE0+YXVqxl5qayoEDB2yvDx06xNatWylbtiyVK1dm+PDhvP3221SvXp3g4GBGjx5NhQoV6NmzZ8EXV+D3sckNTZkyxahcubLh4uJiNGvWzFi7dq3ZJZUowDV/ZsyYYXZpJZ5uuy8YP/30k1G3bl3D1dXVqFWrlvH555+bXVKJk5ycbAwbNsyoXLmy4ebmZlSrVs147bXXjIyMDLNLK/ZWrFhxzb/J/fv3Nwzj8q33o0ePNvz9/Q1XV1ejQ4cORkxMTKHUZjEMTb0pIiIi9k1jiERERMTuKRCJiIiI3VMgEhEREbunQCQiIiJ2T4FIRERE7J4CkYiIiNg9BSIRERGxewpEIlLsjB07Fn9/fywWCwsWLLhq+cqVK7FYLCQmJhZ6bTcyduxY7rjjDrPLEJFr0MSMIlKs7Nmzhzp16hAZGUnz5s0pU6YMrq6uOdbJzMwkISHBFppmzpzJ8OHDCzUgWSwWIiMjczxyIDU1lYyMDHx9fQutDhHJHT3LTESKldjYWADuu+8+LBbLNddxcXEpkKdjZ2dnY7FYrnrwZ255enri6emZz1WJSH7QJTMRuSXh4eE8//zzvPTSS5QtW5aAgADGjh2bY52jR49y33334enpibe3N7179+b06dM37HfHjh3cdddduLu74+vry1NPPUVqaipw+ZJT9+7dAXBwcLhuIPr7JbOVK1cycOBAkpKSsFgsWCwWW50ZGRmMHDmSihUr4uHhwZ133snKlStt/cycOZPSpUuzaNEi6tSpg6urK0ePHmXDhg3cfffdlCtXDh8fH9q1a8fmzZtt76tatSoA999/PxaLxfb6n5fMrFYrb775JpUqVcLV1ZU77riDJUuW2JYfPnwYi8XCjz/+SPv27SlVqhQNGjTgr7/+sq1z5MgRunfvTpkyZfDw8CAsLIxffvnlhvtYRK6mQCQit2zWrFl4eHiwbt06Jk6cyJtvvklUVBRw+WB/3333kZCQQHR0NFFRURw8eJCHH374uv2lpaXRuXNnypQpw4YNG/j+++9ZtmwZQ4cOBWDkyJHMmDEDgFOnTnHq1Kmb1tiyZUs+/PBDvL29be8ZOXIkAEOHDuWvv/5izpw5bN++nYceeoguXbqwf/9+2/vT09OZMGECX375Jbt27cLPz4+UlBT69+/PmjVrWLt2LdWrV6dr166kpKQAsGHDBgBmzJjBqVOnbK//6aOPPuL9999n0qRJbN++nc6dO9OjR48cnw/w2muvMXLkSLZu3UqNGjXo06cPWVlZAERERJCRkcGqVavYsWMHEyZM0FkokVtRKI+QFZESp127dkbr1q1ztDVt2tR4+eWXDcMwjKVLlxqOjo7G0aNHbct37dplAMb69euv2efnn39ulClTxkhNTbW1/fzzz4aDg4MRFxdnGIZhREZGGjf703Xlidrnz583DMMwZsyYYfj4+ORY58iRI4ajo6Nx4sSJHO0dOnQwXnnlFdv7AGPr1q03/Lzs7GzDy8vL+Omnn2xtgBEZGZljvTFjxhgNGjSwva5QoYLxzjvv5FinadOmxrPPPmsYhmEcOnTIAIwvv/zStvzKPtyzZ49hGIZRr149Y+zYsTesT0RuTmeIROSW1a9fP8frwMBAzpw5A1we/BwUFERQUJBteZ06dShdujR79uy5Zn979uyhQYMGeHh42NpatWqF1WolJiYmX2vfsWMH2dnZ1KhRwza2x9PTk+joaNs4Jbg8Humf23n69GkGDx5M9erV8fHxwdvbm9TUVI4ePZrrz09OTubkyZO0atUqR3urVq2u2j9///zAwEAA235+/vnnefvtt2nVqhVjxoxh+/btua5BRP5Hg6pF5JY5OzvneG2xWLBarSZVkzepqak4OjqyadMmHB0dcyz7+yUnd3f3q8Yq9e/fn3PnzvHRRx9RpUoVXF1dadGiBZmZmQVS69/385VaruznQYMG0blzZ37++WeWLl3K+PHjef/993nuuecKpBaRkkpniESkQNSuXZtjx45x7NgxW9vu3btJTEykTp06133Ptm3bSEtLs7X98ccfODg4ULNmzVuuxcXFhezs7BxtDRs2JDs7mzNnzhAaGprj52Z3qP3xxx88//zzdO3albCwMFxdXTl79myOdZydna/6zL/z9vamQoUK/PHHH1f1fb39cz1BQUE8/fTT/Pjjj7zwwgt88cUXeXq/iCgQiUgB6dixI/Xq1eOxxx5j8+bNrF+/nn79+tGuXTuaNGlyzfc89thjuLm50b9/f3bu3MmKFSt47rnn6Nu3L/7+/rdcS9WqVUlNTWX58uWcPXuW9PR0atSowWOPPUa/fv348ccfOXToEOvXr2f8+PH8/PPPN+yvevXqfPPNN+zZs4d169bx2GOP4e7uftVnLl++nLi4OM6fP3/Nfl588UUmTJjA3LlziYmJYdSoUWzdupVhw4bletuGDx/Ob7/9xqFDh9i8eTMrVqygdu3auX6/iFymQCQiBcJisbBw4ULKlClD27Zt6dixI9WqVWPu3LnXfU+pUqX47bffSEhIoGnTpjz44IN06NCBTz755LZqadmyJU8//TQPP/ww5cuXZ+LEicDlu8D69evHCy+8QM2aNenZsycbNmygcuXKN+zv3//+N+fPn6dRo0b07duX559/Hj8/vxzrvP/++0RFRREUFETDhg2v2c/zzz/PiBEjeOGFF6hXrx5Llixh0aJFVK9ePdfblp2dTUREBLVr16ZLly7UqFGDzz77LNfvF5HLNFO1iIiI2D2dIRIRERG7p0AkIiIidk+BSEREROyeApGIiIjYPQUiERERsXsKRCIiImL3FIhERETE7ikQiYiIiN1TIBIRERG7p0AkIiIidk+BSEREROyeApGIiIjYvf8HQCm4b0c+DNkAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_i = recorder['counter'].size\n",
    "loads = recorder['loads'].reshape((n_i,s,n_wt))\n",
    "wt = 0\n",
    "for n, ls in enumerate(load_signals):\n",
    "    plt.plot(loads[:,n,wt])\n",
    "    plt.title(ls+f' turbine {wt}')\n",
    "    plt.plot([0, n_i], [max_loads[n, wt], max_loads[n, wt]])\n",
    "    plt.xlabel('no of iterations')\n",
    "    plt.ylabel('LDEL [Nm]')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Note:\n",
    "\n",
    "Due to the computational expensive nature of this problem, the maximum number of iterations were restricted to 10, for educational purposes. To see a convergence in loading and AEP, the number of iterations must be increased."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting up the load constraints as post_constraints"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively to using the `AEPMaxLoadCostModelComponent`, the common `CostModelComponent` can also be used any load constrained problem. The main difference lies in the way the load constraints are specified within the `TopFarmProblem`. You should set up the load constraint as a **post_constraints** element. Below is an example on how to set up this type of problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: checking out_of_order\n",
      "INFO: checking system\n",
      "INFO: checking solvers\n",
      "INFO: checking dup_inputs\n",
      "INFO: checking missing_recorders\n",
      "INFO: checking unserializable_options\n",
      "INFO: checking comp_has_no_outputs\n",
      "INFO: checking auto_ivc_warnings\n"
     ]
    }
   ],
   "source": [
    "from topfarm.cost_models.cost_model_wrappers import CostModelComponent\n",
    "\n",
    "#redifining the cost function to output arrays instead of float\n",
    "\n",
    "cost_comp = CostModelComponent([('x', x_init), ('y', y_init)],\n",
    "                            n_wt=n_wt,\n",
    "                            cost_function=aep_load_func,\n",
    "                            objective=True,\n",
    "                            output_keys=[('AEP', 0), ('loads', np.zeros((s, i)))])\n",
    "\n",
    "#parameters for optimization\n",
    "maxiter = 5\n",
    "tol = 1e-4\n",
    "ec = 1\n",
    "\n",
    "problem = TopFarmProblem(design_vars={'x': x_init, 'y': y_init},\n",
    "                          n_wt = n_wt,\n",
    "                          post_constraints=[('loads', {'upper': max_loads})],\n",
    "                          constraints=[XYBoundaryConstraint(boundary),\n",
    "                                     SpacingConstraint(min_spacing)],\n",
    "                          cost_comp=cost_comp,\n",
    "                          driver=driver,\n",
    "                          plot_comp=NoPlot(),\n",
    "                          expected_cost=ec)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can evaluate the topfarm problem to make sure it is set up properly without having to run the optimization again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO: checking out_of_order\n",
      "INFO: checking system\n",
      "INFO: checking solvers\n",
      "INFO: checking dup_inputs\n",
      "INFO: checking missing_recorders\n",
      "INFO: checking unserializable_options\n",
      "INFO: checking comp_has_no_outputs\n",
      "INFO: checking auto_ivc_warnings\n"
     ]
    }
   ],
   "source": [
    "%%capture\n",
    "problem.evaluate()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Evaluating the topfarm problem yields the initial conditions in terms of AEP and position of the turbines:\n",
    "\n",
    "    (362.94298203172417,\n",
    "     {'x': array([361469., 360936., 360404., 359871., 360936., 360404., 359871.,\n",
    "             359338., 360670., 360137., 359604., 359071., 360404., 359871.,\n",
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