Kirchoff_Plate_Main_Non_Observer_LDE.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finite Element Analysis of Kirchhoff Thin Plates\n",
    "\n",
    "This notebook consists of control systems without observer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys, os\n",
    "import datetime\n",
    "now = datetime.datetime.now()\n",
    "sys.path.append(\"../\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving the outputs in a text file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "morph_modes = [3]\n",
    "directory = \"Kirchhoff_Non_Observer_LDE_Mode_\" + str(morph_modes) + \"_{}_{}_{}\".format(now.year, now.month, now.day)\n",
    "if not os.path.exists(directory):\n",
    "\tos.makedirs(directory)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import scipy.linalg as sl\n",
    "import Thin_Plate_Library as TPL\n",
    "from scipy.integrate import odeint\n",
    "from control import lqr\n",
    "from matplotlib import pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "solve = np.linalg.solve\n",
    "rank = np.linalg.matrix_rank\n",
    "det = np.linalg.det"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plate details\n",
    "xlength, ylength, thickness = 0.6, 0.2, 0.2e-3\n",
    "E_p, nu_p, rho = 70e9, 0.3, 2700*thickness\n",
    "I_p = thickness**3/12\n",
    "\n",
    "Cmat_p = E_p/(1-nu_p**2)*np.array([[1,nu_p, 0], [nu_p,1,0], [0,0,(1-nu_p)/2]])\n",
    "Dmat_p = Cmat_p*I_p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# PZT details\n",
    "pzt_thickness = 0.2e-3\n",
    "pzt_density = 7750*pzt_thickness\n",
    "Spzt = sl.block_diag(np.array([[16.4, -5.74, -7.22], [-5.74, 16.4, -7.22], [-7.22, -7.22, 18.8]]), 47.5,47.5,44.3)*1e-12\n",
    "Ce_pzt = np.linalg.inv(Spzt)[np.ix_([0,1,5],[0,1,5])]\n",
    "d_mt = np.zeros((6,3))\n",
    "d_mt[4,0], d_mt[3,1], d_mt[0,2], d_mt[1,2], d_mt[2,2] = 584e-12, 584e-12, -171e-12, -171e-12, 374e-12\n",
    "d_mt = d_mt[np.ix_([0,1,5],[2])]\n",
    "e_mt = Ce_pzt.dot(d_mt); e_mt[1:3] = 0\n",
    "ep0 = 8.854e-12\n",
    "eps_pzt = 1730*ep0 - d_mt.T.dot(e_mt)\n",
    "\n",
    "Zpzt = (pzt_thickness*thickness+pzt_thickness**2)/2\n",
    "I_pzt = (8*pzt_thickness**3+12*pzt_thickness**2*thickness+6*pzt_thickness*thickness**2+thickness**3)/24 - thickness**3/24\n",
    "\n",
    "Dmat_pzt = Ce_pzt*I_pzt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Node matrix:\n",
      "[[ 0  5 10 15 20 25 30 35 40 45 50 55 60]\n",
      " [ 1  6 11 16 21 26 31 36 41 46 51 56 61]\n",
      " [ 2  7 12 17 22 27 32 37 42 47 52 57 62]\n",
      " [ 3  8 13 18 23 28 33 38 43 48 53 58 63]\n",
      " [ 4  9 14 19 24 29 34 39 44 49 54 59 64]]\n",
      " \n",
      "Element Matrix:\n",
      "[[ 0  4  8 12 16 20 24 28 32 36 40 44]\n",
      " [ 1  5  9 13 17 21 25 29 33 37 41 45]\n",
      " [ 2  6 10 14 18 22 26 30 34 38 42 46]\n",
      " [ 3  7 11 15 19 23 27 31 35 39 43 47]]\n",
      " \n"
     ]
    }
   ],
   "source": [
    "# FEA details\n",
    "node_detail = (13, 5)\n",
    "nodes, nodes_x, nodes_y, total_nodes, elements, elements_x, elements_y, total_elements = TPL.node_element_details(node_detail)\n",
    "\n",
    "elementSet = np.arange(0, total_elements)\n",
    "nodeSet = np.arange(0, total_nodes)\n",
    "\n",
    "elementMatrix = elementSet.reshape(elements).T\n",
    "nodeMatrix = nodeSet.reshape(nodes).T\n",
    "\n",
    "print(\"Node matrix:\")\n",
    "print(nodeMatrix)\n",
    "print(\" \")\n",
    "print(\"Element Matrix:\")\n",
    "print(elementMatrix)\n",
    "print(\" \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "coordinates, X, Y, Xmap, Ymap = TPL.coordinates(xlength, ylength, nodes_x, nodes_y)\n",
    "\n",
    "# piezoelectric patch details\n",
    "npzt_elm_x, npzt_elm_y = 2, 2\n",
    "# npzt_elm_x, npzt_elm_y = 12, 4\n",
    "\n",
    "nx, ny = int(elements_x/npzt_elm_x), int(elements_y/npzt_elm_y)\n",
    "total_sensors = nx*ny\n",
    "\n",
    "element_for_pzt_x, element_for_pzt_y = np.arange(0, elements_x).reshape((nx,npzt_elm_x)), np.arange(0, elements_y).reshape((ny,npzt_elm_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6 2\n"
     ]
    }
   ],
   "source": [
    "print(nx, ny)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Actuator Elements:\n",
      "\n",
      "[[ 0  4  1  5]\n",
      " [ 8 12  9 13]\n",
      " [16 20 17 21]\n",
      " [24 28 25 29]\n",
      " [32 36 33 37]\n",
      " [40 44 41 45]\n",
      " [ 2  6  3  7]\n",
      " [10 14 11 15]\n",
      " [18 22 19 23]\n",
      " [26 30 27 31]\n",
      " [34 38 35 39]\n",
      " [42 46 43 47]]\n",
      " \n",
      "Sensor Elements:\n",
      "\n",
      "[[ 0  4  1  5]\n",
      " [ 8 12  9 13]\n",
      " [16 20 17 21]\n",
      " [24 28 25 29]\n",
      " [32 36 33 37]\n",
      " [40 44 41 45]\n",
      " [ 2  6  3  7]\n",
      " [10 14 11 15]\n",
      " [18 22 19 23]\n",
      " [26 30 27 31]\n",
      " [34 38 35 39]\n",
      " [42 46 43 47]]\n",
      " \n"
     ]
    }
   ],
   "source": [
    "pzt_element_sensors = np.zeros((total_sensors, npzt_elm_x*npzt_elm_y), dtype=\"int\")\n",
    "n = 0\n",
    "actuator_address = []\n",
    "for i in range(ny):\n",
    "    vertpzt = element_for_pzt_y[i,:]\n",
    "    for j in range(nx):\n",
    "        horzpzt = element_for_pzt_x[j,:]\n",
    "        pzt_elms = elementMatrix[vertpzt,:][:,horzpzt]\n",
    "        pzt_element_sensors[n,:] = pzt_elms.ravel()\n",
    "        actuator_address.append([j,i])\n",
    "        n += 1\n",
    "\n",
    "pzt_element_actuators = pzt_element_sensors\n",
    "total_actuators = pzt_element_actuators.shape[0]\n",
    "\n",
    "print(\"Actuator Elements:\\n\")\n",
    "print(pzt_element_actuators)\n",
    "print(\" \")\n",
    "\n",
    "print(\"Sensor Elements:\\n\")\n",
    "print(pzt_element_sensors)\n",
    "print(\" \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "connectivity = TPL.connectivity(elements_x, elements_y, nodeMatrix)\n",
    "\n",
    "dofpn = 3\n",
    "tdof = total_nodes*dofpn\n",
    "edof = 4*dofpn\n",
    "\n",
    "w_total = np.arange(0, tdof, dofpn)\n",
    "tx_total = np.arange(1, tdof, dofpn)\n",
    "ty_total = np.arange(2, tdof, dofpn)\n",
    "\n",
    "w_el = np.arange(0, edof, dofpn)\n",
    "tx_el = np.arange(1, edof, dofpn)\n",
    "ty_el = np.arange(2, edof, dofpn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "support_condition=\"cy\"\n",
    "node_arrest = TPL.node_arresting(coordinates, support_condition)\n",
    "dof_arrest = TPL.node2dof(node_arrest, dofpn).T.ravel()\n",
    "non_dof_arrest = np.delete(np.arange(0,tdof), dof_arrest)\n",
    "k_size = non_dof_arrest.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "vec = np.array([-np.sqrt(3/7+2/7*np.sqrt(6/5)),-np.sqrt(3/7-2/7*np.sqrt(6/5)),np.sqrt(3/7-2/7*np.sqrt(6/5)),np.sqrt(3/7+2/7*np.sqrt(6/5))])\n",
    "gpoints = TPL.combvec(vec,vec)\n",
    "gp = gpoints.shape[0]\n",
    "\n",
    "weights = np.zeros(gpoints.shape)\n",
    "\n",
    "for i in range(gp):\n",
    "\tif gpoints[i,0] > 0.5 or gpoints[i,0] < -0.5:\n",
    "\t\tweights[i,0] = (18-np.sqrt(30))/36\n",
    "\telse:\n",
    "\t\tweights[i,0] = (18+np.sqrt(30))/36\n",
    "\tif gpoints[i,1] > 0.5 or gpoints[i,1] < -0.5:\n",
    "\t\tweights[i,1] = (18-np.sqrt(30))/36\n",
    "\telse:\n",
    "\t\tweights[i,1] = (18+np.sqrt(30))/36"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Constucting system model matrices...\n"
     ]
    }
   ],
   "source": [
    "print(\"Constucting system model matrices...\")\n",
    "Mglobal = np.zeros((tdof, tdof), dtype=\"float\")\n",
    "Kglobal = np.zeros((tdof, tdof), dtype=\"float\")\n",
    "Kpglobal = np.zeros((tdof, tdof), dtype=\"float\")\n",
    "Mpglobal = np.zeros((tdof, tdof), dtype=\"float\")\n",
    "Kup_a_global = np.zeros((tdof, total_actuators), dtype=\"float\")\n",
    "Kup_s_global = np.zeros((tdof, total_sensors), dtype=\"float\")\n",
    "Kpp_a_global = np.zeros((total_actuators, total_actuators), dtype=\"float\")\n",
    "Kpp_s_global = np.zeros((total_sensors, total_sensors), dtype=\"float\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "for element in range(total_elements):\n",
    "\tnode_address = connectivity[element, :]\n",
    "\tdof_address = TPL.node2dof(node_address, dofpn).T.ravel()\n",
    "\telement_coordinates = coordinates[node_address, :]\n",
    "\txx, yy = element_coordinates[:,0], element_coordinates[:,1]\n",
    "\tMe, Ke = 0, 0\n",
    "\tMep, Kep = 0, 0\n",
    "\tKup_a, Kup_s = 0, 0\n",
    "\tKpp_a, Kpp_s = 0, 0\n",
    "\tfor i in range(gp):\n",
    "\t\tgx, gy = gpoints[i,0], gpoints[i,1]\n",
    "\t\tmapped_coord, Jac = TPL.GaussMapper(gx, gy, element_coordinates)\n",
    "\t\tJ = Jac*weights[i,:].prod()\n",
    "\t\tx, y = mapped_coord\n",
    "\t\tBw, Bm, Bpzt = TPL.DerivMatrices(x, y, xx, yy)\n",
    "\t\tMe += rho*Bm.T.dot(Bm)*J\n",
    "\t\tKe += Bw.T.dot(Dmat_p).dot(Bw)*J\n",
    "\t\tif np.any(pzt_element_actuators==element):\n",
    "\t\t\tMep += pzt_density*Bm.T.dot(Bm)*J\n",
    "\t\t\tKep += Bw.T.dot(Dmat_pzt).dot(Bw)*J\n",
    "\t\t\tBz = np.array([[1/pzt_thickness]])\n",
    "\t\t\tKup_a += -Zpzt*Bpzt.T.dot(e_mt).dot(Bz)*J\n",
    "\t\t\tKpp_a += Bz.T.dot(eps_pzt).dot(Bz)*J\n",
    "\n",
    "\t\tif np.any(pzt_element_sensors==element):\n",
    "\t\t\tMep += pzt_density*Bm.T.dot(Bm)*J\n",
    "\t\t\tKep += Bw.T.dot(Dmat_pzt).dot(Bw)*J\n",
    "\t\t\tBz = np.array([[1/pzt_thickness]])\n",
    "\t\t\tKup_s += -Zpzt*Bpzt.T.dot(e_mt).dot(Bz)*J\n",
    "\t\t\tKpp_s += Bz.T.dot(eps_pzt).dot(Bz)*J\n",
    "\n",
    "\tMglobal[np.ix_(dof_address, dof_address)] += Me\n",
    "\tKglobal[np.ix_(dof_address, dof_address)] += Ke\n",
    "\n",
    "\tMpglobal[np.ix_(dof_address, dof_address)] += Mep\n",
    "\tKpglobal[np.ix_(dof_address, dof_address)] += Kep\n",
    "\n",
    "\tif np.any(pzt_element_actuators==element):\n",
    "\t\tadr = np.where(pzt_element_actuators==element)[0]\n",
    "\t\tKup_a_global[np.ix_(dof_address, adr)] += Kup_a\n",
    "\t\tKpp_a_global[np.ix_(adr, adr)] += Kpp_a\n",
    "\tif np.any(pzt_element_sensors==element):\n",
    "\t\tadr = np.where(pzt_element_sensors==element)[0]\n",
    "\t\tKup_s_global[np.ix_(dof_address, adr)] += Kup_s\n",
    "\t\tKpp_s_global[np.ix_(adr, adr)] += Kpp_s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "Kb = Kglobal[np.ix_(non_dof_arrest, non_dof_arrest)]\n",
    "Mb = Mglobal[np.ix_(non_dof_arrest, non_dof_arrest)]\n",
    "\n",
    "Ktotal = Kglobal + Kpglobal\n",
    "Mtotal = Mglobal + Mpglobal\n",
    "\n",
    "K = Ktotal[np.ix_(non_dof_arrest, non_dof_arrest)]\n",
    "M = Mtotal[np.ix_(non_dof_arrest, non_dof_arrest)]\n",
    "\n",
    "Kup_act = Kup_a_global[np.ix_(non_dof_arrest)]\n",
    "Kup_sen = Kup_s_global[np.ix_(non_dof_arrest)]\n",
    "\n",
    "Kpu_act = Kup_act.T\n",
    "Kpu_sen = Kup_sen.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Checking for symmetry...\n",
      "True\n",
      "True\n",
      "True\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "# Check symmetry\n",
    "print(\"Checking for symmetry...\")\n",
    "print(TPL.check_symmetric(Kb))\n",
    "print(TPL.check_symmetric(Mb))\n",
    "print(TPL.check_symmetric(K))\n",
    "print(TPL.check_symmetric(M))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Obtaining the mode shapes and frequencies of the system...\n",
      "(5, 13)\n",
      "(5, 13)\n"
     ]
    }
   ],
   "source": [
    "print(\"Obtaining the mode shapes and frequencies of the system...\")\n",
    "EigenVectors, EigenValues, _ = TPL.spectrum(Kglobal, Mglobal, non_dof_arrest)\n",
    "_, _, Frequencies = TPL.spectrum(Ktotal, Mtotal, non_dof_arrest)\n",
    "# morph_modes = [0,1,2]\n",
    "mode = 0\n",
    "for idx, i in enumerate(morph_modes):\n",
    "    mode += EigenVectors[:, i]\n",
    "\n",
    "mode1 = TPL.normalize(mode, w_total, 0.2)\n",
    "\n",
    "morph_2 = [1]\n",
    "\n",
    "mode = 0\n",
    "for i in morph_2:\n",
    "    mode += EigenVectors[:, i]\n",
    "\n",
    "mode2 = TPL.normalize(mode, w_total, 0.2)\n",
    "\n",
    "init_shape = TPL.vec2shape(mode1, w_total, nodes)\n",
    "print(init_shape.shape)\n",
    "print(Xmap.shape)\n",
    "\n",
    "# file_name = directory + \"/shapes\"\n",
    "# print(file_name)\n",
    "# storage = {\"Xmap\":Xmap, \"Ymap\":Ymap, \"Z\":init_shape, \"mode\":morph_modes}\n",
    "# TPL.savemat(file_name, storage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.2568446991897502\n",
      "0.30907345096286204\n"
     ]
    }
   ],
   "source": [
    "cdr = 2.0/100\n",
    "w1 = Frequencies[0]*2*np.pi\n",
    "w2 = Frequencies[1]*2*np.pi\n",
    "damping_coefs = solve(np.array([[0.5/w1, 0.5*w1], [0.5/w2, 0.5*w2]]), np.vstack([cdr, cdr]))\n",
    "print(Frequencies[0])\n",
    "print(Frequencies[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Preparing initial conditions...\n"
     ]
    }
   ],
   "source": [
    "print(\"Preparing initial conditions...\")\n",
    "x_reference = mode1[non_dof_arrest]\n",
    "xd_referecene = np.zeros(x_reference.shape)\n",
    "X_reference = np.hstack([x_reference, xd_referecene])\n",
    "X_initial = np.zeros(X_reference.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Constructing state space model...\n"
     ]
    }
   ],
   "source": [
    "print(\"Constructing state space model...\")\n",
    "Os = np.zeros((k_size, k_size))\n",
    "Is = np.eye(k_size, k_size)\n",
    "C = damping_coefs[0]*M + damping_coefs[1]*K\n",
    "# C = 0*M + 0*K\n",
    "# Piezoelectric forces\n",
    "S = -solve(Kpp_s_global, Kpu_sen)\n",
    "B = -solve(M, Kup_act)\n",
    "\n",
    "# State Transition matrix\n",
    "A21 = -solve(M, K)\n",
    "A22 = -solve(M, C)\n",
    "\n",
    "Asys = np.vstack([np.hstack([Os, Is]), np.hstack([A21, A22])])\n",
    "Bsys = np.vstack([np.zeros((k_size, total_actuators)), B])\n",
    "Csys = np.hstack([S, np.zeros((total_sensors, k_size))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Controller implementation\n",
    "# LQR controller\n",
    "_, Klqr = TPL.lqr_controller(Asys, Bsys)\n",
    "_, Kodi, _ = TPL.ODI_controller_v1(A21, A22, B, S, 100, 100)\n",
    "# W = 50*np.eye(2*k_size, 2*k_size)\n",
    "# K = W-Asys\n",
    "# _, Kodi, _ = TPL.ODI_controller_v2(Asys, Bsys, K)\n",
    "Alqr = Asys - Bsys.dot(Klqr)\n",
    "Aodi = Asys - Bsys.dot(Kodi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Static control inputs\n",
    "y_reference = Csys.dot(X_reference)\n",
    "Mx, Mu = TPL.static_input(Asys, Bsys, Csys)\n",
    "\n",
    "mat = solve(Csys.dot(solve(-Asys, Bsys)), np.eye(total_sensors))\n",
    "mat_o = solve(Csys.dot(solve(-Aodi, Bsys)), np.eye(total_sensors))\n",
    "\n",
    "\n",
    "Force_u = Bsys.dot(mat)\n",
    "Force_lqr = Bsys.dot(Mu + Klqr.dot(Mx))\n",
    "Force_odi = Bsys.dot(mat_o)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "t0 = 0.0\n",
    "h = 0.01\n",
    "Tf = 20.0\n",
    "tspan = np.arange(t0, Tf, h)\n",
    "n = tspan.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def reference_states(t):\n",
    "    return X_reference\n",
    "\n",
    "def percentage(t):\n",
    "    print(\"Completed... {0:.0f} %\".format(t/Tf*100), end='\\r', flush=True)\n",
    "    \n",
    "def reference(t):\n",
    "    return y_reference\n",
    "    \n",
    "def system(X, t):\n",
    "    percentage(t)\n",
    "    return Asys.dot(X) + Force_u.dot(reference(t))\n",
    "\n",
    "def lqr_system(X, t):\n",
    "    percentage(t)\n",
    "    return Alqr.dot(X) + Force_lqr.dot(reference(t))\n",
    "\n",
    "def odi_system(X, t):\n",
    "    percentage(t)\n",
    "    return Aodi.dot(X) + Force_odi.dot(reference(t))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Solving time integration problem...\n",
      "Uncontrolled system...\n",
      "Completed... 100 %ompleted... 48 %\r"
     ]
    }
   ],
   "source": [
    "print(\"Solving time integration problem...\")\n",
    "print(\"Uncontrolled system...\")\n",
    "uncontroller_trajectory = odeint(system, X_initial, tspan)\n",
    "# print(\"LQR controlled system...\")\n",
    "# lqr_trajectory = odeint(lqr_system, X_initial, tspan)\n",
    "print(\"ODI controlled system...\")\n",
    "odi_trajectory = odeint(odi_system, X_initial, tspan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "displacements_u, velocities_u = TPL.splitting_reconstruction(uncontroller_trajectory, non_dof_arrest, tdof, k_size)\n",
    "# displacements_lqr, velocities_lqr = TPL.splitting_reconstruction(lqr_trajectory, non_dof_arrest, tdof, k_size)\n",
    "displacements_odi, velocities_odi = TPL.splitting_reconstruction(odi_trajectory, non_dof_arrest, tdof, k_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "norm_D_u, norm_V_u = TPL.norms(displacements_u), TPL.norms(velocities_u)\n",
    "# norm_D_lqr, norm_V_lqr = TPL.norms(displacements_lqr), TPL.norms(velocities_lqr)\n",
    "norm_D_odi, norm_V_odi = TPL.norms(displacements_odi), TPL.norms(velocities_odi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "static_u = np.asarray([mat.dot(reference(t)) for t in tspan])\n",
    "# control_lqr = lqr_trajectory.dot(-Klqr.T) + np.asarray([(Mu+Klqr.dot(Mx)).dot(reference(t)) for t in tspan])\n",
    "control_odi = odi_trajectory.dot(-Kodi.T) + np.asarray([mat_o.dot(reference(t)) for t in tspan])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.30703169e+04  1.38156372e+03  3.92192326e+03 -1.39265345e+04\n",
      "  1.60965528e+03 -5.32494180e+03  1.42889187e+04  1.33831340e+01\n",
      "  2.28619375e+03 -1.31445578e+04 -2.19534327e+03 -1.69754365e+03]\n",
      "[ 1.30461035e+04  1.37218597e+03  3.92192596e+03 -1.39040303e+04\n",
      "  1.62518666e+03 -5.32859582e+03  1.42689165e+04  1.02394763e+01\n",
      "  2.28694950e+03 -1.31246055e+04 -2.18954411e+03 -1.70110387e+03]\n"
     ]
    }
   ],
   "source": [
    "print(static_u[-1])\n",
    "# print(control_lqr[-1])\n",
    "print(control_odi[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11.381954721860927\n"
     ]
    }
   ],
   "source": [
    "desired_state = np.asarray([reference_states(t) for t in tspan])\n",
    "desired_state_norm = TPL.norms(desired_state)\n",
    "print(desired_state_norm[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "sensor_output = odi_trajectory.dot(Csys.T)\n",
    "sensor_out_static = uncontroller_trajectory.dot(Csys.T)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot file names\n",
    "displacement_fname = directory + \"/displacememt.png\"\n",
    "velocity_fname = directory + \"/velocity.png\"\n",
    "control_fname = directory + \"/control.png\"\n",
    "sensor_fname = directory + \"/sensor.png\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.figure()\n",
    "plt.plot(tspan, norm_D_u, label=\"Uncontrolled\")\n",
    "# plt.plot(tspan, norm_D_lqr, label=\"LQR state\")\n",
    "plt.plot(tspan, norm_D_odi, label=\"ODI state\")\n",
    "plt.plot(tspan, desired_state_norm, ':', label=\"Desired State\")\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.ylabel(\"Displacement Norm (m)\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.savefig(displacement_fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(tspan, norm_V_u, label=\"Uncontrolled\")\n",
    "# plt.plot(tspan, norm_V_lqr, label=\"LQR state\")\n",
    "plt.plot(tspan, norm_V_odi, label=\"ODI state\")\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.ylabel(\"Velocity Norm (m)\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.savefig(velocity_fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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AAQyELAVwPESagSgC2vZcqB3f9ggz3+1SroiAF1Yh6IQgAAEIACBzAnYGr+9xBsB6MJathwIAejCKBSFAAQgAAEIMAUc1AcQgEER5f0UsCMAr2lWTV5lCtiFhSgKAQhAAAIQyEjAVgDHS6wRgC6sZcuB/vvjBvn3l6sEAejCOBSFAAQgAAEIZEHA1vjtJeAIQBfWsuVACEAXRqEoBCAAAQhAgCngoD6AAAyKKO+ngB0B2KVpVXmtWzMXLaQoBCAAAQhAAALpCdgK4HiJNALQhbVsORAC0IVRKAoBCEAAAhAgAhjUBxCAQRERAXSBiKIQgAAEIACBqCNgK4ATdR3NpkEIQBfWsuVARABdGIWiEIAABCAAASKAQX0AARgUUeQigFc3rSqvswbQhYUoCgEIQAACEMhIwFYAx0usEYAurGXLgd77aaM898VKQQC6MA5FIQABCEAAAlkQsDV+ewk4AtCFtWw5EALQhVEoCgEIQAACEGAKOKgPIACDIsr7KWBHAHZuUlWG38QxMC5MRFEIQAACEIBABgK2AjheQo0AdGEtWw70/k8b5dkvVgoC0IVxKAoBCEAAAhBgCjhLH0AAunh7IABdwKMoBCAAAQhAIEIEbI3fEepOri6LAMwVNl8hWw7kRACvalJVRjAF7MJCFIUABCAAAQhkJGBr/PYSawSgC2vZcqDRczbK4KkrBQHowjgUhQAEIAABCGRBwNb47SXgCEAX1rLlQAhAF0ahKAQgAAEIQCAIAVvjt5fAIwBdWMuWAzkCsFPjKvJG9+YuWkhRCEAAAhCAAATSE7A1fnuJNALQhbVsOdCYORtl0NSVggB0YRyKQgACEIAABJgCztIHEIAu3h4IQBfwKAoBCEAAAhCIEAFb43eEupOryyIAc4XNV8iWAzkRwI6Nq8ibTAG7sBBFIQABCEAAAhkJ2Bq/vcQaAejCWrYcCAHowigUhQAEIAABCAQhYGv89hJ4BKALa9lyoA/m/iHPTFkhRABdGIeiEIAABCAAgSwI2Bq/vQQcAejCWrYcCAHowigUhQAEIAABCBABDOoDCMCgiLLOYF0AnlVF3ryZY2BcmIiiEIAABCAAgQwEbI3fXkKNAHRhLVsO9OHPf8jTn6+QjghAF9ahKAQgAAEIQCBzArbGby/xRgC6sJYtB0IAujAKRSEAAQhAAAJMAQf1AQRgUER5PwXsCMArz6osb918tosWUhQCEIAABCAAgfQEbAVwvEQaAejCWrYc6P9+/kOe+nyFIABdGIeiEIAABCAAgSwI2Bq/vQQcAejCWrYcCAHowigUhQAEIAABCDAFHNQHEIBBEeX9FLAjADs0qixv38IUsAsTURQCEIAABCCQgYCtAI6XUCMAXVjLlgP93y+b5KnPlgsC0IVxKAoBCEAAAhBgCjhLH0AAunh7IABdwKMoBCAAAQhAIEIEbI3fEepOri6LAMwVNl8hWw7kRACvaFhZRt7KFLALE1EUAhCAAAQgkIGArfHbS6jzXAC++OKLMmnSJFm9erUUKVJE2rZtKy+99JLUr1/fz+348ePy0EMPybhx4yQxMVEuv/xyeeutt6RSpUr+PJs3b5a+ffvKzJkzpXjx4tKzZ0/RuvPnz+/PM2vWLHnwwQdlxYoVkpCQIE8++aTcdtttaezz5ptvyrBhw2THjh3SpEkTGTFihLRq1SokG9pyoI9+2SRPfrZcEIAhmYFMEIAABCAAgRwRsDV+56gREc6c5wLwiiuukG7duknLli3l1KlT8sQTT8jy5ctl5cqVUqxYMYNDhd2XX34pY8aMkVKlSkm/fv0kPj5e5syZY15PSkqSpk2bSuXKlY142759u/To0UPuuusueeGFF0yejRs3SqNGjaRPnz5y5513yvTp0+WBBx4w9aqg1DR+/HhTbuTIkdK6dWt57bXXZOLEibJmzRqpWLFiUNPYciAEYFD0ZIAABCAAAQjkmoCt8TvXDYpAwTwXgOn7uHv3biO2Zs+eLe3atZMDBw5IhQoV5OOPP5brrrvOZNdoYYMGDeTnn3+Wc845R77++mvp1KmTbNu2zR8VVBE3cOBA0foKFixoHqvYU3HpJBWe+/fvl2nTppmnVPSpEH3jjTfM38nJySZS2L9/f3nssceCmsOWAyEAg6InAwQgAAEIQCDXBGyN37luUAQKRlwArlu3TurWrSvLli0zEbsZM2ZI+/btZd++fVK6dGk/kpo1a5oI3oABA+Tpp5+WKVOmyOLFi/2va8Svdu3asnDhQmnWrJkRk82bNzdRPSeNHj3a1KEi88SJE1K0aFH55JNPpEuXLv48OpWsIvHzzz/PYA6djtabk9SBVDBqfSVLlgyb+RwBeHnDSjLq1hZhq5eKIAABCEAAAhCwt4bfS2wjKgA14ta5c2cjuH766SfDTSN/vXr1SiO09Hldl3fRRReZ9YK9e/eWTZs2yTfffONnffToUTOF/NVXX0mHDh2kXr16pp7HH3/cn0df69ixo2heFZjVqlWTuXPnSps2bfx5Hn30URONnDdvXgY7Dho0SAYPHpzh+XALwP/N2yT/mrxcEIBeeivRVghAAAIQ8AoBIoAiERWAutZPp3NV/FWvXj3qBWBeRQARgF75CKGdEIAABCDgRQIIwAgKQN3YodOsP/zwg9SqVcvvP9E8BZzeyW05kCMALzuzkrzTgylgL3640GYIQAACEIheArbG7+jtccaW5XkEMCUlxWyymDx5sugxLbr+LzA5m0DGjh0r1157rXlJd+WeccYZGTaB6O5fZ7fuO++8I4888ojs2rVLChUqZDaB6JSvri10Uvfu3WXv3r1pNoHo1LIe/aJJp6Rr1Khhdh1HchPIx/M2yxOTlwkC0EtvJdoKAQhAAAJeIYAAjEAE8J577jHr/DT6F3j2nx73oucCatKpYRVvegyMbq5QwahJ1+tpco6BqVq1qgwdOtSc4Xfrrbea417SHwNz7733yu233242l9x3330ZjoHRTR+jRo0yawx1w8iECRPMruPAMwezcmhbDoQA9MpHCO2EAAQgAAEvErA1fnuJRZ5HAOPi4jLlozt0nUOanYOgNQoYeBC0nvvnJN0EokJRo4i6+UOF3JAhQzIcBK27hvWMQV1j+NRTT2U4CFqPgHEOgtazBYcPH26Ohwkl2XIgRwBeemYleZcp4FBMQR4IQAACEIBAyARsjd8hNyAKMua5AIyCPoetCbYcaOyvm+XxScsEARg2U1ERBCAAAQhAwE/A1vjtJcQIQBfWsuVACEAXRqEoBCAAAQhAIAgBW+O3l8AjAF1Yy5YDOQLwkgaV5L892QXswkQUhQAEIAABCGQgYGv89hJqBKALa9lyoHG/bpbHJi0TBKAL41AUAhCAAAQgkAUBW+O3l4AjAF1Yy5YDIQBdGIWiEIAABCAAAaaAg/oAAjAooqwzIABdwKMoBCAAAQhAIEIEbI3fEepOri6LAMwVNl8hWw70dwSwovy3Z0sXLaQoBCAAAQhAAALpCdgav71EGgHowlq2HGj8/M0y8FNdA4gAdGEeikIAAhCAAAQyJWBr/PYSbgSgC2vZciAEoAujUBQCEIAABCAQhICt8dtL4BGALqxly4EcAdj+jIry3m1MAbswEUUhAAEIQAACGQjYGr+9hBoB6MJathxowvwt8uinSwUB6MI4FIUABCAAAQhkQcDW+O0l4AhAF9ay5UAIQBdGoSgEIAABCECAKeCgPoAADIoo6wy2BeDFZ1SU95kCdmEhikIAAhCAAAQyErA1fnuJNQLQhbVsOdCE37bIo58sFQSgC+NQFAIQgAAEIMAUcJY+gAB08fZAALqAR1EIQAACEIBAhAjYGr8j1J1cXRYBmCtsvkK2HMiJAF5Uv4KM7tXKRQspCgEIQAACEIBAegK2xm8vkUYAurCWLQea+NsWeeSTpYIAdGEcikIAAhCAAASyIGBr/PYScASgC2vZciAEoAujUBQCEIAABCAQhICt8dtL4BGALqxly4EQgC6MQlEIQAACEIAAAjCoDyAAgyLKOoNtAXhh/QoyhjWALixEUQhAAAIQgEBGArbGby+xRgC6sJYtB/pkwVZ5eOISQQC6MA5FIQABCEAAAlkQsDV+ewk4AtCFtWw5EALQhVEoCgEIQAACEGAKOKgPIACDIsr7KWBHAF5Qr4J8cDvHwLgwEUUhAAEIQAACGQjYCuB4CTUC0IW1bDnQpwu2ykMTlwgC0IVxKAoBCEAAAhBgCjhLH0AAunh7IABdwKMoBCAAAQhAIEIEbI3fEepOri6LAMwVNl8hWw7kRADb1asgHzIF7MJCFIUABCAAAQhkJGBr/PYSawSgC2vZcqBJC7fKgxOWCALQhXEoCgEIQAACEMiCgK3x20vAEYAurGXLgRCALoxCUQhAAAIQgEAQArbGby+Bz1IAJiYmyrx582TTpk1y9OhRqVChgjRr1kxq1arlpf5ZbastB3IE4Pl1y8v/3dHaah+oHAIQgAAEIBBrBGyN317imEEAzpkzR15//XWZOnWqnDx5UkqVKiVFihSRvXv3iorC2rVrS+/evaVPnz5SokQJL/U17G215UCTF22VAeOXCAIw7CajQghAAAIQgIC1NfxeQptGAHbu3FkWLlwo3bt3l6uuukpatGhhxJ+TNmzYID/++KOMHTtWlixZIh9++KFceumlXupvWNuKAAwrTiqDAAQgAAEI5AkBW+N3njQ+TBdJIwBHjRolt99+uxQoUCBo9StXrpTt27dL+/btg+b9p2aw5UBEAP+pHkO/IAABCEAgGgjYGr+joW+htiHDFHBSUpLky5cv1PIxnc+WAyEAY9qt6DwEIAABCFgmYGv8ttzssFafQQBWrlxZbrvtNhMJrFevXlgv9k+rzJYDfbboT3lg/GLWAP7THIb+QAACEIBAVBCwNX5HRedCbEQGAfjcc8/JBx98IBs3bpS2bdvKHXfcITfccIMULVo0xCpjJ5stB0IAxo4P0VMIQAACEMh7ArbG77zvSe6vmOUxMLNmzZLRo0fLp59+aqaEVQTeeeed0ro1x5I4uG05kCMAzzu9vHx0J7xz796UhAAEIAABCGQkYGv89hLroAdBHz58WMaNGydjxoyRuXPnSoMGDUxU8MEHH/RSP6201ZYDfb74T7l/3GJBAFoxG5VCAAIQgECME7A1fnsJa1ABGNiZL7/8Unr06CH79+8X3SwS68mWAyEAY92z6D8EIAABCNgkYGv8ttnmcNcdVADqr4BMmDDBTAf/9NNPUqdOHbNB5LHHHgt3WzxXny0HcgTguaeXk//deY7nuNBgCEAAAhCAQDQTsDV+R3Of07ctSwGo073vv/++TJw4UU6dOiXXXXedmfpt166dl/pnta22HAgBaNVsVA4BCEAAAjFOwNb47SWsGQTg0KFDTbTv999/N78EoqLvpptuivmffcvMqLYcCAHopbcQbYUABCAAAa8RsDV+e4lDBgFYoUIFueWWW4zwa9SokZf6kudtteVAjgBsW6ecfHwXU8B5blguCAEIQAAC/2gCtsZvL0HLIABPnjwZ0k/BeamTttpqy4GmLNkm941dJAhAW5ajXghAAAIQiGUCtsZvLzFNIwD1uJdu3bqF1P4tW7bI5s2b5dxzzw0pv5Pphx9+kGHDhsmCBQvMbwlPnjxZunTp4q9Df4VED6IOTJdffrlMmzbN/9TevXulf//+MnXqVImPj5drr71WXn/9dSlevLg/z9KlS+Xee++V+fPni0Y1Nf+jjz6apl5d3/jUU0/JH3/8IXXr1pWXXnpJrrzyypD7Y8uBEIAhm4CMEIAABCAAgRwTsDV+57ghESyQRgBecMEFsmvXLunVq5dcddVV5sy/wHTgwAGZM2eOfPTRR/Ldd9/Je++9J507d85R87/++mtTx9lnny1du3bNVADu3LnTrEN0UqFChaRMmTL+vzt06GDE46hRo0Qjltreli1byscff2zyqGH1Z+wuueQSefzxx2XZsmVm5/Jrr70mvXv3Nnl0k4tuaHnxxRelUyZ++/gAACAASURBVKdOpqwKwIULF4Y89W3LgRCAOXIpMkMAAhCAAARyRMDW+J2jRkQ4c4Yp4ClTpsiIESNkxowZUqxYMalUqZIULlxY9u3bJzt27JDy5cub3woeMGCAec1NiouLy1QA6jmDn332WaZVr1q1Ss4880wT2dNNKpo0OqiRu61bt0rVqlXl7bffln/961+mvQULFjR59NgarXP16tXm7xtvvFGOHDkiX3zxhf8655xzjjRt2lRGjhwZUrdsOZAjANvULidje7MGMCRjkAkCEIAABCAQIgFb43eIl4+KbFkeA/PXX3+Zc/82bdokx44dM8KvWbNm5qbTruFIWQlAFWoq3DTqd/HFF8u///1vKVeunLmkHk3z0EMPGUHqJD2mRkWqTulec8015rBqNW6giJw5c6apS6ePtd4aNWqYXzN54IEH/PU888wzpsySJUsy7V5iYqLozUl6jYSEBNHIaMmSJcOBxNQxdck26T92kSAAw4aUiiAAAQhAAAJpxu9SpUqFffz2EuKgB0Hb7ExmAlDXIRYtWlRq1aol69evlyeeeMKs7fv555/NbxK/8MILZo3gmjVr0jStYsWKMnjwYOnbt69cdtllprxOETtp5cqV0rBhQ9F7ndpWgan16BE3TnrrrbdMHToFnVkaNGiQeT19QgDa9BLqhgAEIAABCISXABFAkagTgOlNvGHDBvPrI99//720b98+ogIwryOA59QuK+N6twmv11MbBCAAAQhAIMYJIAA9IADVR3UXr04D33333RGdAk7/frHlQF8s3Sb9Pl4kCMAY/4Si+xCAAAQgYIWArfHbSmMtVRr1EUDd2KHr9XRtnu44djaB/Pbbb2YnsaZvv/1WrrjiigybQHQqt0CBAiaPTiVPmjQpzSYQ/Z1jPUrGSW3btpXGjRtHfBMIAtCSt1MtBCAAAQhAIPW0ENYApqSk5KU3HD58WNatW2cuqRtKXnnlFbnoooukbNmy5qZr7PRcv8qVK5s1gHp236FDh8xRLnocjCY9BkbFne7WdY6B0R3BzjEwuiavfv36Zi3gwIEDZfny5eYYmFdffTXNMTB67M2QIUOkY8eOomsPdX1hNBwD4wjA1rXKyvi7mQLOS//kWhCAAAQg8M8nQAQwmyngZ599Vh5++GGzISMw6Y5gPcj56aefzpWHzJo1ywi+9Klnz57m+BY9FHrRokWiR8HokS4q4p577rk0R87oTt5+/fqlOQh6+PDhWR4ErTuY9SBoFYOBSXcNP/nkk/6DoPV3kKPhIOgvl26Xez9eKAjAXLkYhSAAAQhAAALZEkAAZiMAdcetHrasu2sD0549e8xzSUlJMe9ethwIARjzrgUACEAAAhCwSMDW+G2xyWGvOss1gHrWn06z6gaMwKQHROshyrt37w57Y7xWoS0HcgRgq1plZQJTwF5zC9oLAQhAAAJRTsDW+B3l3U7TvAwCUA9J1vP5nLPt9LGTNOqna/j69Okjb775ppf6aaWtthzoq2Xb5Z7/LRQEoBWzUSkEIAABCMQ4AVvjt5ewZhCAejiy7gtxfjtXd8k4SQ9PPu2006RNGzYmKBNbDoQA9NJbiLZCAAIQgIDXCNgav73EIcsp4NmzZ4sei+Ico+KlTuVVW205EAIwryzIdSAAAQhAIBYJ2Bq/vcQySwG4efPmbPuhZ/PFerLlQH4BeFpZmdCHaGus+xn9hwAEIACB8BKwNX6Ht5V2a8t2E0jg+r/0zWAXsL0p4K+XbZe+ugYwDAJQp/MXb9kvOw4cl7qVSsjpFYuH3aP2HjkhenbhX4dPSIuaZeT8uuXNOlISBCAAAQhAIBoJIACzOQZmyZIlaWymBy7r+Xx6cPPzzz8vXbt2jUab5mmbbDlQuATgpj1HzE/KLfvzgJ/LxWdUlKHXNZbyxX2HartNc9f/ZTas7D960l+VCsARNzWT0kULuq2e8hCAAAQgAIGwE7A1foe9oRYrzPFPwX355ZfmIGg90DnWky0HcgRgy9PKyMQ+bXOFec/hROny1hzZsveYFCuYT06vVEJW/HlATiWnSN2KxeXTe9pKycK+n8nLbVr+5wG5YdTPcvREktSrVFwaVSslOn19/GSynFmlpIy/+xwp4fIaTttW7zgo8zbslcOJp6ROhWJyQb2KUqRgvtw2nXIQgAAEIBDDBGyN315CmmMBqD/j1qRJEzly5IiX+mmlrbYcaNry7dLno4XiRgDeP26RfL54m9QsV1TG924jlUsVlt93HpIe7/0qOw4el6ubVpXXuzXLNZfjJ5Ok04ifZN2uw3Le6eXlvdtaSKH8+WTV9oNy63vzzHRwu3oVZMxtLSU+PvfTwet3H5ZBU1bIj2v/StPW0kULyMArzpBuLROYbs61FSkIAQhAIDYJ2Bq/vUQzSwGocAKTriXTXwYZNGiQrF69WhYvXuylflppqy0HcisANVrW4fUfRX/leWq/8+Ss6n8f5bNg0z4TtUtKTpGP72otbeuUzxWbl79dIyNmrJMKJQrJdwPapZnu1cjgdSPnmkjgo1fUl3suPD1X15iyZJs89ulSE2HMHx8n59UtL2WLFZRfN+6VrfuOmTq7NK0qQ69rIgXzx+fqGhSCAAQgAIHYI2Br/PYSyRxtAlERmJCQIOPGjeMsQIvnADoCUDdUfNI351PAd334m3y3cqd0bFxF3uzePIM/PvP5cvng501yVrVSMqXfuTmOoO06eFzaDZtpBN7bNzeXDmdVyXCNCfO3yKOfLpV88XHm10zOrlkmR++L//tlkzz12XJTpk3tcvLStY2lRjnf71KreH3/p40yZNpq81gjje/2ONtEIHObkpNT5Pddh2T9riNyKjlZEsoWlUZVS4VVWO46dFy+X7lLlm7dL7sPJUpySoqJzDaoUtL0UTfouNk8o+/PA8dOyp/7j8mppBTDvmrpIlKmaAFX9eaWKeUgAAEIRCsBBGA2m0D0HMDApD8Npz8Ld/rpp0v+/Pmj1aZ52i5bDjRt+Q7p89ECs6M2pwJw0eZ9cs1bc0VnXb8dcEGmu351feB5L82UYyeT5H93tpZzT89ZFFCFmQq05jVKy6d922YqLlSM3DdusUxdsk2qlykiX91/fshrDv/74wb595erjC1va3uaPNXpTCNm0qfZv++WPv+3wPTj8oaVjNjNny9nkcBjJ5Jk9NyN8r9fNhvhFJhKFs4vnZpUlT7t6vjFZ24cbMW2A/Lqd2tlxuqdkpySdQ3VShcR3aTTvkFFOad2OSlcIHtBq4zX7Dwkv6zfIz9v2CPz/9gnuiM7fSpVpIBZTtC6VjkTRT2jcomoFoQnk5Jl419HZO3Ow7L3SKLZYHTkRJKoafPFx0uRAvmMqC1TrKCUKaq3AmatabFC+aRowfwZfEU5JZ5KlhNJyXLiVLLvceot8VSSxMfFGd8sUTi/ueXUh3LjE+Eso/07lHhKDhw9ad4LKv71i1FSiu9e3zsF8ukt3tw0mq4Rc70vkD9eCqY+n9l7LJztjNa69Muf+oT6gvpIvrg44wPKx8cu3nyeuvlyFq19j+V22Rq/vcQ0x2sAvdQ522215UBuBOAt/50nP637S647u7r85/omWSJ4+vPl8uHPm+TC+hVkTK9WIaPavOeoXPzyLLOZZFzvc4xQySodPH5Srnz9RzNde1WTqjK8W9OgH6Jj5myUQVNXmirvvaiOPHxZ/WzLzFn3l/QaPd98cOt08Ms3NM1ULGbWxm9W7JBnp670Cz/dLHNGlZLmg3/tLhUfPjGlg8B1zavL/ZfUNRG1UNMffx2RV777XXQq20lNE0rLuaeXk4QyRUW14Pb9x2TB5n3y2x/7zCDkpKIF85m1lZc0qCRNa5QWXfOookWP81HRp9Pgc9btkb8OJ2ZoTvniBU00VOvL7HWdtted2hfUq2DEf6g7wnUDjvZJxdmWfUflaGKSGTRVTKgAUxFVrnhB0euXK1ZIypcoZDYgZTVwnkpKli37jsnanYfM+tQ1Ow/L7zsOyYa/DsvJpGyUchADqEDUAfukiqDUW6g209OLKhQvJFVKF5FqpQtL1VJFzONKJQtJxRKFpWKJQlKxZCEjNLNL2je/0PQLT+WVbPqm7dIIsLkPEGu6bMMRb/q8vs80qrvvyAnZe/SEEcPql/uPnjDPO7fsvliE2nf1cxWDak9zyxcvhfL7RGPgc4GPdSOW2rhYofzmpn5rHhfUv32P9bnihfKbTVtxEicp6vm+/2aZiv6tolXfwyr+1c999ylp/zavp/hfN3kCRH3iyWQ5fipJ9F790ifqkiXxZJIcT713vgDo6zqDofeh+pqKaCMI4+OlUAFlk89/X9j87XvO9zif+Vu/xAXeO+z09fScNZ/znJ+Tn5GyMuTMfWZszJcaZeTcJ6V+8fHz/JtvYpp8qV+IUtmeSGXytx2SxeRPSjb20veWfmnStd3OYxXN+t5xBHP6vmX0n3x+X/P3O9XPAv2tkH45yR9nZknOqFwyVFcOKZ+t8Tuki0dJpmwF4Jo1a2TEiBGyapUvGtOgQQPp16+fnHHGGVHS/Mg2w5YDOQJQp001whZqUjF083/nmW/7Mx660ExjZpX0iJgL/zPLvKG/HdBO6lUqEdJlHpywWCYt/NMIiP+7o3XQMgs375PrR/rWHA67rrFc3yIhyzLjft0sj01aZl7vf/Hp8tBl9YPWrxl0ulsjpnqNrs2qybDrm2QrAlWY6sYS7YcmjbwNuLSedGpcxR9107rmbdwjo2ZvEI00atIPsZ5tapo1jRp9yiqpSBsxY62Mn7/FDOCaOjepKve1r5vlOYwaidQjdb5ftctECncezCjsMrueip0Wp5UxQrxNnXLSoHLJNLujdbPOmh2HTF/mrt8jv2zYYwa+wNSwakk5v24FqVW+qFnLqcJD111u239MNu89Kpv2HjWiT6etc5r0w10FphGFxQuZD/19R0/IniMnRL9M6ICVWSpRKL/UrVTciC6NYKqQUMGk0/PaNhVCWo8jiFScqs1CSY7IcQYerffQ8VOm3lCTI45UCOig5wgYZ9AMsSmhXi6kfNof5eRErrRdTtuUmwodHcT1pu11fDOkyskEgQgSuL99XfMZHc5ka/wOZxtt15WlAPz000+lW7du0qJFC/96v19++UXmz59v1gBee+21ttsW9fXbciCNTN39fwvMurlQBaB+qHca/pOJDum06aDODYPy0+nTaSt2yE2tEuTFro2D5tcdv5e9OttMY+rawcbVSwctoxnenLlOhn2zxkzdadSwSULGcrpmcOCkpUaQ3nV+LXniygZBo4WBF9fjZ+4bu8gMahptHHpt40yPiVGR9cjEpSbqp99ee7erI/rhkt2RMipiX/p6tczbuNdcUsXJHefXkmubV/eLbI34LP3zgHyyYKt8umCrP5qnEdZHLq8vDav+vREnGDT9hr9i20H5ftVOmblmt6hYV6GjA3y5YgXNkT6Nq5Uy07nNapTO0dpHjXhotPGHtbvlx9//kpXb0272CtY2vf5p5YtJzbJFpWSRAkYUq+hRUX3w2Ekj7DTquOfwiZAElUZLapcvLvUrl/DdKpWQepVLSNVShXNkf2ea90jiKTmSmGSiSoHTeIFRhqwikvoe0oiaCnj1DxXAvttx0fWbuw4lyq6DiWaaNSfJiaypWAycbtXn1Qd99z6x5kRW8qU+r89pZFU3P6k4L1usgLnXqW+NCqs4dm7Blgykb7MK/ZOpwtCZElcG6SOXvshSkok6ORE3X/4kOXYyWQzzE6dMRPiwude/k8zzKqp9NjklR08mmfe3c0a8LupQW+i9b3raNzXtTFU7jwumTl+nfc03NWt4aqTNH43LGH3zR+sCInKZPqfT4vnizRcg/RzRLxTKJ0mFs97r86kiOrPooj6nX7ic1/5+nDEq6fD2RSR9U8+ByxMcTg4jtZ1y05v6SCAjJ0rm+JYTvU3P0vf834yd1817I3UZgJ956nO+v31lNI/aS99rOgboEgNlpW3VL1FORDuNj6T2y4lOBi6/yCyfL0L+9xINJyrctXk1uaZZ9Zy87YLmtTV+B71wFGXIUgDWqVNHbr75Znn22WfTNPeZZ56Rjz76SNavXx9F3YhMU2w5UE4FoE4HaUTrs8XbzKAw6+ELQzqEWacRdUewfgD8/Hh7M8hkl/p9vFC+WLpdLjuzkrzTo0XI0PWD87bRv5qjXHS91rs9WkiL08qa8vpmf/37tfLGzHXm71vOqSHPXd0oR4O/0xCNnGob9cNbhcSTnRrIuXX0V0nECKpRP2wwaxI11ShbVF65oYm/HcE6ox96GgkcOm1NGtGk/SleOL/8dehEGmGga+50+rp1NlPkwa4Z+Lpe38YaJBU2GjnWMxZ3Hjwu+46eNBEkFcSVSxY2nHTzzWnlihnhp2Ij1HT0xCkjBB1BqPdqb0fA6BFFGn11c0xQqG0JVz61g0Yb9eabavQNWH8PthmnUb22pjBcrKgHAtFMwNb4Hc19Tt+2LAVg0aJFZenSpWbTR2Bau3atOQfw6NGjXuqnlbbacqBQBaBOyb341SojyvSbkgqdd29tIZecWSmk/upg1vmNOeaXQjRKde9FWR/XokfLXPHaj6ber+8/36zJyEnSAfPmd3+RJVsPGIGh0626tkr7umG370zJey6sY9rhRujMXfeX2XzirH3TtUf6LVoXyWtSRje1qmEijPpaTpN+4526dJuM/XWzWYcXONWnkcGLG1SUbi1ryDm1y7rqR07bRX4IQAACEAidgK3xO/QWRD5nlgLwyiuvlOuvv1569eqVppWjR482U8DffPNN5Fsf4RbYciBHAOou20n3nJtpL3Uh+NVv/mR+6UOT/vLG41eeYdZy5SRNXrRVBoxfYha5//joxVkee3LHmPkyffWuLI+WCeWaOg2ka/ycKJxTRqNoOmV9ddNqoVQTNI+KP5121mllnYrSpNMXlzWsJH0uqGN+sSQcSfuzac9RE/nTyKtGyWJ1J2U4eFIHBCAAgbwiYGv8zqv2h+M6WQrAkSNHytNPPy033HCDnHPOOeZaugZw4sSJMnjwYKlatar/+p07dw5HWzxXhy0H+nbFDun9fwvMMStZCcC7/+83+WbFTkkoW0SGd2smzWrk7Jw9B7auzTj3pRlmgf+rNzbJdJ3F9yt3yp0f/mYid98MaCd1KhR3ZSs9jHr6qp1m4f0ZVUpIp8ZVczS1GOrFdWpO189plE7FGYdFh0qOfBCAAAT+2QRsjd9eopbtQdChdESn65KScrYoOpR6vZDHlgMFE4C6kaH7u/NMtOmL/ufleDo2PVtnk4aKye8GXJDm/LlDepTL8B9NpFGjZ491YAe4F3yTNkIAAhCAQNYEbI3fXmLOOYAurGXLgRwBqDs8J2cyBXzjqJ/NjlQ9kmTw1Y1c9MBXVKcy9Ww/PXrkwUvrmeNKNOkawX4fL5Ivl203i/X1uBg9ZoIEAQhAAAIQ8DIBW+O3l5ggAF1Yy5YD6bl2+nNumQlA/Z3dTiN+MtOxPw282PyUWDjSZ4v+lAfGLzbHUrx6Y1Np36CSDJ6yQiYu2GquNaFPG2mey2nmcLSPOiAAAQhAAALhImBr/A5X+/KinmwF4PTp00Vvu3btkuTktAe2vv/++3nRvqi+hi0HcgSgnoV2Qf0Kct3ZCf7f0h0wfrFMXvSnXN20qrzerVnY+Gi077FPl8n437akqVMFof6iSNfm4T2DKWwNpyIIQAACEIBADgnYGr9z2IyIZs9SAOpGDz0DUA+CrlKlSoYjLSZPnhzRhkfDxW05kCMAnT6qCNvwYkfZdfC42bChJ/p/fu+5mR6o7IaLHmasP102es4fZmdr7QrF5JmrGpqfDCNBAAIQgAAE/ikEbI3fXuKTpQBU0Td06FC59dZbvdSfPG2rLQdydt0GduaHRy6STxZuleHT1+boF0JyA0RPsNdz+/RXH9ycyZeba1MGAhCAAAQgYJuArfHbdrvDWX+WArBcuXLy66+/iv4iCClzArYcKDMB+HSnM+WtWevkr8Mn5I3uzczRKSQIQAACEIAABHJOwNb4nfOWRK5ElgJw4MCBUrx4cXnqqaci17oov7ItB8pMADooqpcpIjMfvtD8FiQJAhCAAAQgAIGcE7A1fue8JZErkaUAvP/+++XDDz+Uxo0bm1uBAml/A/SVV16JXKuj5Mq2HEgPSb7jg98y7eXbNzeXDmdViRICNAMCEIAABCDgPQK2xm8vkchSAF500UVZ9kPXhc2YMcNL/bTSVlsOlF4A9r2wjkxbvkO6tUyQuy9gSt6KMakUAhCAAARihoCt8dtLADkH0IW1bDlQoAAslD9e1vy7g4tWUhQCEIAABCAAgUACtsZvL1FGALqwli0HChSAFUoUkvn/usRFKykKAQhAAAIQgAACMK0PZBCAXbt2DclLJk2aFFK+f3ImWwJwxuqdcvsY3xpAPYtvxkMX/pMx0jcIQAACEIBAnhKwNX7naSdcXiyDAOzVq1dIVY4ePTqkfP/kTLYcKFAANk0oLZ/de+4/GSN9gwAEIAABCOQpAVvjd552wuXFmAJ2AdCWAwUKwHb1KsiHt7dy0UqKQgACEIAABCAQSMDW+O0lyghAF9ay5UAzV++SXmPmm5Z1bFxF3uze3EUrKQoBCEAAAhCAAAIwrQ8gAF28J/JCAN7Uqoa82PUsF62kKAQgAAEIQAACCEAEYNjeBXkhAO++oLY83qFB2NpMRRCAAAQgAIFYJ2Br/PYSVyKALqxly4FmrtklvUb7poAfvqye9Lu4rotWUhQCEIAABCAAASKARADD9i7ICwH4VKcz5Y7zaoWtzVQEAQhAAAIQiHUCtsZvL3FNEwGcMmVKyG3v3LlzyHn/qRltOVBgBFDX/+k6QBIEIAABCEAAAuEhYGv8Dk/r8qaWNAIwPj4+pKvqbwEnJSWFlPefnMmWA81as0tuS50Cfr1bU7m6abV/Mkb6BgEIQAACEMhTArbG7zzthMuL5fkawB9++EGGDRsmCxYskO3bt8vkyZOlS5cu/m6kpKTIM888I++++67s379fzj33XHn77belbt2/18Ht3btX+vfvL1OnThUVrddee628/vrrUrx4cX89S5culXvvvVfmz58vFSpUMPkfffTRNLgmTpwoTz31lPzxxx+m/pdeekmuvPLKkJHacqBAAfjOrWfLZQ0rh9wmMkIAAhCAAAQgkD0BW+O3l7jnuQD8+uuvZc6cOXL22WeL/uxcegGoIuzFF1+UDz74QGrVqmUE2rJly2TlypVSuHBhw7ZDhw5GPI4aNUpOnjwp+uslLVu2lI8//ti8roatV6+eXHLJJfL444+b8rfffru89tpr0rt3b5Nn7ty50q5dO3OtTp06mbJ67YULF0qjRo1CsqEtBwoUgB/d0VrOq1s+pPaQCQIQgAAEIACB4ARsjd/Brxw9ObIVgLNnz5b//Oc/smrVKtPiM888Ux555BE5//zzw9IDnUoOFIAa/atatao89NBD8vDDD5trHDhwQCpVqiRjxoyRbt26mbZoOzSy16JFC5Nn2rRpJnK3detWU14jhv/6179kx44dUrBgQZPnsccek88++0xWr15t/r7xxhvlyJEj8sUXX/j7cs4550jTpk1l5MiRIfXPlgMFCsBP+7aVs2uWCak9ZIIABCAAAQhAIDgBW+N38CtHT44sBeBHH31kImsapdNpWE0auVPBpmKse/furnuRXgBu2LBB6tSpI4sWLTJCzEkXXHCB+Vuned9//30jEPft2+d//dSpUyY6qFO611xzjfTo0cNEAVXwOWnmzJly8cUXi04flylTRmrUqCEPPvigPPDAA/48OvWsZZYsWRJS32w50Ozfd0vP9381bfj6/vOlQZWSIbWHTBCAAAQgAAEIBCdga/wOfuXoyZGlAGzQoIGZLh0wYECa1r7yyitmfZ4TFXTTlfQCUKdlVWxu27ZNqlSp4q/6hhtuEM07fvx4eeGFF8z08Jo1a9JcumLFijJ48GDp27evXHbZZWb6WKeInaRTyA0bNjRTydo3jQxqPTfddJM/z1tvvWXq2LlzZ6bdSkxMFL05SR0oISHBRClLlgyfSAsUgLMfuVBqlivmBjNlIQABCEAAAhAIIIAAFMlSABYqVEhWrFghp59+ehqnWbdunVkjd/z4cdfO5DUBOGjQICMQ06dwC8DAKeBf/9VeKpbwrX0kQQACEIAABCDgngACMBsBqMJP1/vdfffdaUjr+riXX35Z1q5d69oCXpsCzqsI4LTlO6TPRwsM3+WDL5fihfK7Zk0FEIAABCAAAQj4CCAAsxGAupFC18fp7tm2bdsaYLoGUNf/6Vq89MIwN06V1SYQ3QCi6/wcI+n0bvpNIL/99pvZSazp22+/lSuuuCLDJhCdyi1QoIDJ88QTT8ikSZPSbAI5evSoOUrGSdrPxo0bR3wTyJg5G2XQ1JWmWRtfvNJMf5MgAAEIQAACEAgPAQRgNgJQEeuGD432Oev9dO2cRgWvvvrqXFvg8OHDotPImpo1aya6pvCiiy6SsmXLmo0ZehTLkCFD0hwDo2f6pT8GRsWdRiOdY2B0R7BzDIxOydavX9+sBRw4cKAsX77cCNlXX301zTEwurlEr9WxY0cZN26cWV8YDcfAfLVsu9zzv4WG0R9DOuaaNQUhAAEIQAACEMhIAAGYhQDUX/nQaJ9Gw0qXLh1W35k1a5YRfOlTz549TZTPOQj6nXfeMQdBn3feeaKbM/RcPyfpTt5+/fqlOQh6+PDhWR4EXb58eXMQtIrBwKS7hp988kn/QdBDhw6NioOgk5JTZMzcP6RFzTLSJCG8/MNqTCqDAAQgAAEIeJAAAjCbCKAeq6KRP91NS8qcAA6EZ0AAAhCAAAS8R4DxOxsBqFOqOh3bvn1771k2j1qMA+URaC4DAQhAAAIQCCMBxu9sBKD+uob+jNpzzz1nNlsUK5b2LLpwnnsXRpvmaVU4UJ7i5mIQaHnrSQAAIABJREFUgAAEIACBsBBg/M5GAMbHx/shB+5C1TV6+reuE4z1hAPFugfQfwhAAAIQ8CIBxu9sBKD+DnB2SXfQxnrCgWLdA+g/BCAAAQh4kQDjdzYCcPPmzeZnztKfQacRwC1btpgjW2I94UCx7gH0HwIQgAAEvEiA8TsbAZgvXz7Zvn276CHMgWnPnj3mOaaAOUnci2962gwBCEAAAhBAAAZZA6iHLVeoUCGNp2zatEnOPPNMOXLkSMx7EA4U8y4AAAhAAAIQ8CABxu9MBOCDDz5oTKk/93bXXXdJ0aJF/abVqN+8efNEo4N6UHSsJxwo1j2A/kMAAhCAgBcJMH5nIgCdX+nQTSBt2rSRggUL+m2rj0877TTR3+qtW7euF20e1jbjQGHFSWUQgAAEIACBPCHA+J3NFHCvXr1MFJDz/rL2RRwoT96nXAQCEIAABCAQVgKM39kIwLCS/odWhgP9Qw1LtyAAAQhA4B9NgPE7GwGomzyGDBki06dPl127dklycnIaZ9iwYcM/2jlC6RwOFAol8kAAAhCAAASiiwDjdzYC8KabbhJdB3jrrbdKlSpVMpwHeP/990eXNSPQGhwoAtC5JAQgAAEIQMAlAcbvbARg6dKl5csvv5Rzzz3XJeZ/bnEc6J9rW3oGAQhAAAL/XAKM39kIwFq1aslXX30lDRo0+Od6gMue4UAuAVIcAhCAAAQgEAECjN/ZCMCPPvpIPv/8c/nggw/SnAUYATtF7SVxoKg1DQ2DAAQgAAEIZEmA8TsbAdisWTNZv3696G//6tl/BQoUSANy4cKFMe9aOFDMuwAAIAABCEDAgwQYv7MRgIMHD87WpM8884wHTR7eJuNA4eVJbRCAAAQgAIG8IMD4zTmArvwMB3KFj8IQgAAEIACBiBBg/A5BAC5YsEBWrVplDNSwYUPRqWGSjwAOhCdAAAIQgAAEvEeA8TsbAaiHP3fr1k1mzZoleiSMpv3794v+VvC4ceOkQoUK3rN4mFuMA4UZKNVBAAIQgAAE8oAA43c2AvDGG28U/bWPDz/80H8UzMqVK6Vnz55y+umny9ixY/PARNF9CRwouu1D6yAAAQhAAAKZEWD8zkYAlipVSr7//ntp2bJlGna//vqrXHbZZSYaGOsJB4p1D6D/EIAABCDgRQKM39kIwBIlSsiPP/4oTZs2TWPbRYsWyQUXXGDWv8V6woFi3QPoPwQgAAEIeJEA43c2AvDqq682UT6d6q1ataqx759//ik333yzlClTRiZPnuxFm4e1zThQWHFSGQQgAAEIQCBPCDB+ZyMAt2zZIp07d5YVK1ZIQkKCMYg+16hRI5kyZYpUr149T4wUzRfBgaLZOrQNAhCAAAQgkDkBxu8gx8Dor4DoOsDVq1cbgvq7wJdccgn+lEoAB8IVIAABCEAAAt4jwPgdwjmA3jNr3rUYB8o71lwJAhCAAAQgEC4CjN+ZCMAZM2ZIv3795JdffpGSJUumYX3gwAFp27atjBw5Us4///xw2cGz9eBAnjUdDYcABCAAgRgmwPidiQDUdX962POAAQMydY3hw4fLzJkz2QTCL4HE8EcHXYcABCAAAS8TQABmIgBr1qwp06ZN8x/+nN7Auh5QzwHcvHmzl20flrbjQGHBSCUQgAAEIACBPCXA+J2JACxcuLAsX77c/NpHZmndunVy1llnybFjx/LUWNF4MRwoGq1CmyAAAQhAAALZE2D8zkQA1qlTR15++WXp0qVLpvQmTZokDz/8sPmZuFhPOFCsewD9hwAEIAABLxJg/M5EAPbv319mzZol8+fPF40GBiaN+rVq1cqsEdS1gLGecKBY9wD6DwEIQAACXiTA+J2JANy5c6c0b95c8uXLZ3YD169f39hW1/69+eabkpSUJAsXLpRKlSp50eZhbTMOFFacVAYBCEAAAhDIEwKM31mcA7hp0ybp27evfPPNN6KHQWuKi4uTyy+/3IjAWrVq5YmBov0iOFC0W4j2QQACEIAABDISYPwOchD0vn37RDd9qAisW7eu+Q1g0t8EcCC8AQIQgAAEIOA9Aozf/BKIK6/FgVzhozAEIAABCEAgIgQYvxGArhwPB3KFj8IQgAAEIACBiBBg/EYAunI8HMgVPgpDAAIQgAAEIkKA8RsB6MrxcCBX+CgMAQhAAAIQiAgBxm8EoCvHw4Fc4aMwBCAAAQhAICIEGL+jUAAOGjRIBg8enMYh9CxCPYdQ0/Hjx+Whhx6ScePGSWJiojma5q233kpzLqH+TrEeYzNz5kwpXry49OzZU1588UXJnz+/v1497PrBBx+UFStWSEJCgjz55JNy22235cgRcaAc4SIzBCAAAQhAICoIMH5HqQD85JNP5Pvvv/c7iQq38uXLm79V2H355ZcyZswYKVWqlDmsOj4+XubMmWNe14OqmzZtKpUrV5Zhw4bJ9u3bpUePHnLXXXfJCy+8YPJs3LhRGjVqJH369JE777xTpk+fLg888ICpVwVlqAkHCpUU+SAAAQhAAALRQ4DxO0oF4GeffSaLFy/O4CkHDhyQChUqyMcffyzXXXedeV0jgw0aNJCff/5ZzjnnHPn666+lU6dOsm3bNn9UcOTIkTJw4EDZvXu3FCxY0DxWsbd8+XL/Nbp16yb79++XadOmheyhOFDIqMgIAQhAAAIQiBoCjN9RKgA1cqfRPf0t4jZt2pjp2xo1asiMGTOkffv2ogdUly5d2u9INWvWNBG8AQMGyNNPPy1TpkxJIyA14le7dm3zE3bNmjWTdu3amZ+7e+211/x1jB492tShIjOrpFPOenOSOpBOH2uZkiVLRo1j0xAIQAACEIAABLImgACMQgGoEbzDhw+b3yDW6VtdD/jnn3+aaN3UqVOlV69eaUSYmrdVq1Zy0UUXyUsvvSS9e/cW/Sk7/Rk7Jx09elSKFSsmX331lXTo0EHq1atn6nn88cf9efS1jh07iuYtUqRIpl6T2fpEzYgA5GMGAhCAAAQg4B0CCMAoFIDp3UenZTXC98orrxhhFkkBSATQO29uWgoBCEAAAhDIigAC0AMCUI3XsmVLueSSS+TSSy+N6BRwekey5kDrvhdZN0MkoZVIwy68gyEAAQhAAAIQCCMBa+N3GNtou6q4lJSUFNsXcVO/Tgfr+j+dftXjXHQTyNixY+Xaa6811a5Zs0bOOOOMDJtAdPq4YsWKJs8777wjjzzyiOzatUsKFSpkNoHolO+yZcv8Tevevbvs3bs3OjaBzHxRZPYQkRZ3iHR6xQ0+ykIAAhCAAAQgkI4AAjAKI4APP/ywXHXVVWbaV3fyPvPMM2ZDx8qVK43402NgVLzpMTC68aJ///7GrHPnzjX3zjEwVatWlaFDh8qOHTvk1ltvNce9pD8G5t5775Xbb7/dbC657777oucYmFkvicx6QaTF7SKdXuWNCwEIQAACEIBAGAkgAKNQAOpxLD/88IPs2bPHCL7zzjtPnn/+ealTp44xvXMQtEYBAw+C1nP/nKSbQFQo6mHPuvlDI4dDhgzJcBC07hpWYVm9enV56qmnoucg6NnDRGb+W+Ts20Suej2MLk9VEIAABCAAAQggAKNQAHrJLa050A//EZnxnEjzHiKdR3gJCW2FAAQgAAEIRD0Ba+N31Pf87wZG/RrAaGZpzYF+fEVk+mCRZreIXP1mNCOgbRCAAAQgAAHPEbA2fnuIBALQhbGsOdBPr4p8P0ik6c0iXd5y0UKKQgACEIAABCCQnoC18dtDqBGALoxlzYHmvC7y3dMiTbqLXPO2ixZSFAIQgAAEIAABBGBGH0AAunhfWBOAc0eIfPukSONuIl1HuWghRSEAAQhAAAIQQAAiAMP6LrAmAH9+U+SbJ0TOukHk2nfD2mYqgwAEIAABCMQ6AWvjt4fAEgF0YSxrDvTL2yLTHhNpdJ3Ide+5aCFFIQABCEAAAhAgAkgEMKzvAnsCcKTItIEiDbuKXD86rG2mMghAAAIQgECsE7A2fnsILBFAF8ay5kDz3hH5+hGRhteIXD/GRQspCgEIQAACEIAAEUAigGF9F1gTgL++K/LVwyJnXi1yw4dhbTOVQQACEIAABGKdgLXx20NgiQC6MJY1B5r/nsiXD4o0uErkxo9ctJCiEIAABCAAAQgQASQCGNZ3gTUB+NtokS8eEDmjk0i3/4W1zVQGAQhAAAIQiHUC1sZvD4ElAujCWNYcaMEYkan3i9S/UuSmsS5aSFEIQAACEIAABIgAEgEM67vAmgBc+KHIlP4i9TqIdB8X1jZTGQQgAAEIQCDWCVgbvz0ElgigC2NZc6BFH4l8fq9I3ctFbp7gooUUhQAEIAABCECACCARwLC+C6wJwMUfi3zWV+T0S0Vu+SSsbaYyCEAAAhCAQKwTsDZ+ewgsEUAXxrLmQEvGiUy+W6ROe5FbJ7loIUUhAAEIQAACECACSAQwrO8CewJwvMjk3iK1LxLp8VlY20xlEIAABCAAgVgnYG389hBYIoAujGXNgZZOFJl0p0itC0R6TnHRQopCAAIQgAAEIEAEkAhgWN8F1gTgsk9EPr1DpFY7kZ5Tw9pmKoMABCAAAQjEOgFr47eHwBIBdGEsaw60fJLIJ71ETjtf5LYvctbCI3tE5r0tsmGWSPIpkYTWImf3Eql4xt/1pKSI/PW7yK6VIvkKilQ7W6RE5ZxdJ7PcWu/JYyL5C4nE53NfHzVAAAIQgAAELBCwNn5baKutKhGALshac6AVn4lM7ClS81yRXl+F3sI/5vjKHdmdsYzWVecikcO7RdZ8LXJgc0CeOJH6HUTOuUfktPNE4uJCu+aJoyJ//CSy7juf4Ny3SSQp0Ve2YAmRMjVFStcUKXOaSNlaImVr+26lEkTy5Q/tGkmnRPZvEtm/WeTAVt/t6B6RU8dFkk76xGahEr6bitiS1UVKVRMpWU2kcMng11DReuKIr86jf4mogNbHJ4+KpCSLJCf5eBQsJlKwuEih4r6+ad2FSvru9flQmGl7td0nj4ucOpZ6r4/1uWMiKUkiBYr6buZ6xf5+nJ2g1jaeSvSxP3VCJCndzXkuLl4kXwHfLd65z5/6d37fc3qd+IDnlIGp76TvC0X6x/p6Vkmvl+YWF/B3vnSvad7U1yVFRO2iN/9jvY4+lxzwfOC1tazjt5k9Tn3N5HHypbuGcy3Tn/SvBXel7H0gk+sHtiWrtqe5rPIISIaPk7J7LYS2u8kSiu/nqv4QP4dyVXe4C6XjH67q09g4XJWm+nc4q/O7oSUO+vkeyud5DvpkbfzOQRsinRUB6MIC1hxo5RSRCbeK1Ggjcvu0v1uoYmjaQBGNEOprnUeIFCvne339TJGxN/mERYUGIufeL1KgsIhOJ6/5yjdwBqb8hUUqN/YJj53L/n6lajOfEKxzsUix8n8/rwJDxZeKsW2LRf74UWTTXJ94yWlSgaHCUMVguToiJar4RIimY/tEju4VObBFZM963/VUeOQmqTArVsF3K1pWJE6jko7g2ytybO/fYjI39TtlVOSYD6hSIvmL+Nrr3JRboMDL7XW07crNf4v3iTKtP/lkbmulHAQgAIHoJ3Dh4yIXPhbWdlobv8PaSruVIQBd8LXmQKumioy/xTd9e8e3vhbqYD+pt8iKgGNhKp4p0mOKyI4lImO7+yJAdS8TueFDkQJF/u7ZgT9Flk30Tftq1Oo0jQa2FylY1Jdn9+8i80aKLP5fWkGnIlFvGg3TyE9mSaN5p18iUvdSkUqNRIqU8bVVo2gq3vb94bvt3ZB62/h3lDBU9toGFYylNLpXXaR4RV+7dPpaxVXiIZHjB0QObRfRvh7c6vs7JylfIZ/gLVrOd69ROI2GBYrGxMMiJw6lXu+gSOLB3ItTw7aQTzCqUNe/9VrKWm8aXT15JKNwD9qnOF+9ysZ/02hfwdSI5kkR/SKh9lTh6ET2VLBmF83zi918qVHEgqliNP1Uf7romonYpUbtzH1S6t/O86n3ofTLRBNTI3iBjwOjdVpPYORQXwt8LtPrOBHDgHvN579WYNQwaEMzyZBJG5w2+ttmHqS2PfVxVm0NfD5N9C1dxMxaZC6gAV6MUOUFlzS2y8NIZp72LQ/7dcGjInoLY7I2foexjbarQgC6IGzNgVZ/KTKuu69lxSuLlK7hExrbFvqm6S4cKPLrf0UO7/AJFhVAOqDX7yhy/WifAMhNOvKXyK/viqz8XGT3qow1qCjStpSvK1LzPJHaF4pUqB/a9KdTW3KyyKFtAYJwg8jhXb6pVhUIRUr7+qRRQY0OapSwRFWR+Pic9UiZaL06Ha43jSo6Akf7odcoWib1vrxvujWnH57OmkcVgsdTBaFGVM0Ua37fFKcKOyPwivjsosJcxWYo/dH6NcKnU9RGsDmRxSTf4/wq8lREOmJS69Xr5vKDWW2jAi1QFDrTxmZ6WCOQObRDqFYzU74BU+56XZ2qNdPCuexPVtfWa4W7zlD7ST4IQCAqCFgbv6Oid6E1AgEYGqdMc1lzIF2jN7Zb5gLs+jEi9S73TY9+cJXIwT99+c7sItL1XZ8oCEdSAWXW2p34ez2aTnEycIaDLnVAAAIQgEAECVgbvyPYp5xeGgGYU2IB+a050O/fiHx8w99XuvRZ34aBpjf5InBO0ojd6i9806MajUOcubAmRSEAAQhAIFYIWBu/PQQQAejCWNYcaO13Iv+7ztey+leK3DTWRSspCgEIQAACEIBAIAFr47eHMCMAXRjLmgOt/V7kf9f6WtZhqEjru120kqIQgAAEIAABCCAA0/oAAtDFe8KaANTz/MZc6WvZvfNFKtRz0UqKQgACEIAABCCAAEQAhu1dYE0A6o5YPfJFj2m5ajhr+8JmMSqCAAQgAAEIiFgbvz0ElwigC2PhQC7gURQCEIAABCAQIQKM3yIIQBfOhwO5gEdRCEAAAhCAQIQIMH4jAF25Hg7kCh+FIQABCEAAAhEhwPiNAHTleDiQK3wUhgAEIAABCESEAOM3AtCV4+FArvBRGAIQgAAEIBARAozfCEBXjocDucJHYQhAAAIQgEBECDB+IwBdOR4O5AofhSEAAQhAAAIRIcD4jQB05Xg4kCt8FIYABCAAAQhEhADjNwLQlePhQK7wURgCEIAABCAQEQKM3whAV46HA7nCR2EIQAACEIBARAgwfiMAXTkeDuQKH4UhAAEIQAACESHA+I0AdOV4OJArfBSGAAQgAAEIRIQA4zcCUN58800ZNmyY7NixQ5o0aSIjRoyQVq1aheSQOFBImMgEAQhAAAIQiCoCjN8xLgDHjx8vPXr0kJEjR0rr1q3ltddek4kTJ8qaNWukYsWKQZ0VBwqKiAwQgAAEIACBqCPA+B3jAlBFX8uWLeWNN94wzpmcnCwJCQnSv39/eeyxx4I6LA4UFBEZIAABCEAAAlFHgPE7hgXgiRMnpGjRovLJJ59Ily5d/M7Zs2dP2b9/v3z++ecZHDYxMVH05iR1IBWMBw4ckJIlS0adg9MgCEAAAhCAAAQyEkAAxrAA3LZtm1SrVk3mzp0rbdq08XvHo48+KrNnz5Z58+Zl8JhBgwbJ4MGDMzyPAOTjBQIQgAAEIOAdAghABGCOBCARQO+8uWkpBCAAAQhAICsCCMAYFoC5mQJO70g4EB8uEIAABCAAAe8RYPyOYQGo7qqbQPTIFz36RZNuAqlRo4b069ePTSDeez/TYghAAAIQgEBIBBCAMS4A9RgY3fQxatQoIwT1GJgJEybI6tWrpVKlSkGdCAcKiogMEIAABCAAgagjwPgd4wJQPVKPgHEOgm7atKkMHz7cRAZDSThQKJTIAwEIQAACEIguAozfCEBXHokDucJHYQhAAAIQgEBECDB+IwBdOR4O5AofhSEAAQhAAAIRIcD4jQB05Xg4kCt8FIYABCAAAQhEhADjNwLQlePhQK7wURgCEIAABCAQEQKM3whAV46HA7nCR2EIQAACEIBARAgwfiMAXTkeDuQKH4UhAAEIQAACESHA+I0AdOV4OJArfBSGAAQgAAEIRIQA4zcC0JXj4UCu8FEYAhCAAAQgEBECjN8IQFeOZ9OBdhzZYdpWuVhlV22kMAQgAAEIQAACaQnYHL+9wjouJSUlxSuNjbZ22nKg3Ud3S8fJHaVI/iLy3XXfScF8BaOt67QHAhCAAAQg4FkCtsZvLwFBALqwli0HmvPnHOnzfR/Tsk+u+kTql63vopUUhQAEIAABCEAgkICt8dtLlBGALqxly4F++vMn6ft9X9OyF857Qa6qc5WLVlIUAhCAAAQgAAEEYFofQAC6eE/YEoA/bP1B7p1+r2lZ3TJ15f3L3pfShUu7aClFIQABCEAAAhBwCNgav71EGAHowlq2HGj2ltnSb0Y/f8vaVW8nb1z8hhw9dVQmrJlg1gR2rdvVrBEkQQACEIAABCCQMwK2xu+ctSKyuRGALvjbcqCZm2fKfTPvk0L5Conu0TmRfEJub3S7LNi5QJbsXmJaXKdUHRl6wVCpV6ae+ftA4gHZcGCDnEo+JWeUPUNKFCzhomcUhQAEIAABCPxzCdgav71EDAHowlq2HGj65unywMwHpEmFJtK5Tmd57pfn/K0sEF/ACMPDJw9L/rj8Uqt0LdlzbI/sPb7Xn6dwvsJy9elXy51n3ZmjY2RUbC7/a7noGsQVe1bI1kNbZV/iPklMShS9bvECxaVK8SpSpVgVqVO6jtQvU99sUClXuJzExcXliKQKVd3tvDdxrxw6cUjiJE7i4+JNdLNkwZJGwJYqWEoK5CuQo3qdzNqXPcf3mGvsPrbb3B87dcyIab22MtQIqt60X3o9vTnXLlagWLZ9Opl80tR37OQxE5nVx0dP+u6dfug19KZ1Obdo3dHtfNE4fuq4nEg6IceTjkviqUQ5lXLK2CZfXD7TL72Zx/Gp94HPOa8FPCdxYspr0nv1E+c+V4aNUKHklGRJSkkSc5/suzf/kn3Pp8jfhyn4++v0NbXfhkHqc8rR4RD42HkfeJFRuE2jPqmcHbZe9p9ws6E+9wRsjd/uW5Z3NSAAXbC25UDTN02XB2Y9IM0qNpMPO3woIxaNkHeWviMVi1aUERePkEpFK8lTc56SH//8MU3r9cxA/ZDcfmS7eV5FW4daHaRR+UaSUCLBf9MBJzDtO75PvtjwhUxaO0nW7V+XYyJlC5c1UccGZRtIg3IN5MyyZ0r1EtX9AkrF0vr96424XLlnpazas0rW7l9rhGWwpAJN69dbmcJl/I+d50oXKm1EnfZB+73p4CbZfHCzuVdhltukjIwoLFDCiFJtqwojvVeRp33KTVKbBApCFZ9FCxQ1z+nj/PH5zTVUfBkRlpQoKspUtGo/Tyad9N0nnzTiQ/MH3rT+fPH5jEhzxIQRGHFxJpqsdWp9Tj+ca+l9oIjJTd9yW8YvhCTe9EXbb+7jfPemT6mPnef1OSevvpZGoKlQS04VaI5wSxVqRril3vyCLlXYZfd8bvvmtlx24tDta87nQGA92l4jvCTZ3Ju/JVWIpeijFPO8/58+DvhbGaavw/hVivjrTFNH6rV8WXz/nDqCsUsjCNN9uUgvFjP72+l/oP85X1gChboR7qn1O6zS98F572Rgk9r3NLxSvywEcnYYZZUvPfdAXs41HV7pufj7lMkXsCzzZvblJbC8r9K0X+oCv+hInP/zxHlfpe+v//lUn3LEvrkP8EH9u2/TvtK3iW9jZLiSrfE7XO3Li3oQgC4o23Kg7zZ9Jw/OelCaV2wuH3T4wLRQo2QqhnTQcz5gNx7cKDsO75BShUtJrZK1jJDQN878HfNl5NKR5j59UlHTtEJTIy61vnnb58mcbXP8gkYjVhclXCRNKzaVWqVqmehe4fyFjQDRaWYVWRoZVAH3+77fjdDK7ANbBY1G8DSCtPfYXnOfPukgrqJOo26atB4VIgcTD8qhk4dcWMZXVD/cyhUpJxWKVDDiuWj+oiaiqNd1BJBG7Y6cPCIHTxw0jPU+J+JOo7BFCvgiiVq/sy7TCKtU8eZECF13KI8q0EFO/UAjycrKSKlMhFSggMqjpkXtZZyoX6REdNSCoWEQCAOBe5rcY0RgOJOt8TucbbRdFwLQBWFbDvTNH9/Iw7MflhaVWsjoK0bnuoW/7fjNRAk37N8gWw9vNcJNI0CZpTPLnSldT+8qHWp38AuyUC6s0bB1+9bJqr2rZPXe1Sa6p8JQo1SBSaNbDcs1lIblG6aJEqaPRjpldJpNp7lVdOr0tt40yuc8dv7WKWoVK2UKlZEKRStIzZI1pUaJGuZeo5A5nXJVAa3CTcWgIwg18lcov286V+tzhJ4jKEPhpAJahaAKzsMnDsuRU0fkyIkj5t78ffKIuan4VMHtTB+roNRrFowvaO5VkKmI1b81SqGcVFxrZFCvYR5rdDI14uL/Np2SbPIbYZe/sBF32ie9D7ye/q1fMnI6pR8YgQuMpAWeMx8YHXG+xAQKJu2LikrTj2RfPwL/1sf6nPO685rex+u/gGlpZ8raRELj/p7CDnzeye+f4s6kfJpp74Apbo1Smtf0X2qENb0f+PubGiEL7HP6qJoT/TBlAqIfmUXfnOhcmiiJJPtsnjplGlif5s/ytdT8Tl2pE/RppuqdqJf5UhUXZ/rsRMg0ChT4t3+K34kWpYskad7AyJFTVutOH4n0/51aV4aIWeqXxsAIWBqOgdHK9NHL1L/9EUsnCpXKKjDiliFP6nspMHrmsMmMXyj5Mo3SZcHQ+XKbfjmFXidDJDIL3/MzC4i8pnl/Os+ni/YaH04XBfZHI9PldXzFeX+kWfaQ+r5x/Cd9Hiev87x+1mqAI5zJ1vgdzjbargsB6IKwLQeatnGaPPLDI9Kqcit57/L3XLQwbVEdPH/f+7ss2rVIFu9ebAaLuqXryiU1LzHHzYQr6XW2HNxiBI8ThdMIXFZiL1zXpR4IQAACEIBAKARsjd+hXDta8iAAXVjClgN9teErGfjjQGldpbX897L/umi3egHJAAAZdUlEQVQhRSEAAQhAAAIQSE/A1vjtJdIIQBfWsuVAuiHj8R8flzZV2sg7l73jooUUhQAEIAABCEAAAZjRBxCALt4XtgTg1PVT5YmfnpC2VdvKqEtHuWghRSEAAQhAAAIQQAAiAMP6LrAlAKesnyL/+ulfcm61c2XkJSPD2mYqgwAEIAABCMQ6AVvjt5e4EgF0YS1bDvTZus/MOX/nVztf3rrkLRctpCgEIAABCEAAAkQAiQCG9V1gSwBOXjtZnp77tFxQ/QJ5o/0bYW0zlUEAAhCAAARinYCt8dtLXIkAurCWLQf69PdPZdDPg+TChAvNL3+QIAABCEAAAhAIHwFb43f4Wmi/JgSgC8a2HGji7xPl2Z+flYsTLpbXL37dRQspCgEIQAACEIBAegK2xm8vkUYAurCWLQeasGaCPPfLc3JJjUvk1YteddFCikIAAhCAAAQggADM6AMIQBfvC1sCcNzqcfL8vOfl0pqXyisXvuKihRSFAAQgAAEIQAABiAAM67vAlgAcu3qsvDDvBbms5mXy8oUvh7XNVAYBCEAAAhCIdQK2xm8vcSUC6MJathzof6v+J0N+HSJXnHaFDLtgmIsWUhQCEIAABCAAASKARADD+i6wJQA/WvmRvDT/JelQq4MMbTc0rG2mMghAAAIQgECsE7A1fnuJKxFAF9ay5UAfrvhQhv02TDrW7ihDzh/iooUUhQAEIAABCECACCARwLC+C2wJwA9WfCD/+e0/clXtq+SF818Ia5upDAIQgAAEIBDrBGyN317iSgTQhbVsOdDo5aPllQWvSOc6neX585530UKKQgACEIAABCBABJAIYFjfBbYE4HvL3pPXFr4mV9e5Wv593r/D2mYqgwAEIAABCMQ6AVvjt5e4EgF0YS1bDvTfZf+V1xe+Ltecfo08e+6zLlpIUQhAAAIQgAAE/r+98wCuogjj+EcRkCYgvbckIEhTIBTpIlJEagCliRRBkF6DBKUjHQKBGQUVBGEABYRxRAQpw4BAaKICQxcm9CaCivPfmXvz8vLKvffu3btL/t8MwyTZ29v9fbu3//u2HCOAjAAa2gtCJQCXHV0m8w/Pl3YR7SSudpyhZWZmJEACJEACJJDWCYRq/LYTV0YAg/BWqBpQQmKCLDyyUNpHtpcJtSYEUUJeSgIkQAIkQAIkwAggI4CG9oJQCcDFiYsl/ki8dIzsKONrjTe0zMyMBEiABEiABNI6gVCN33biyghgEN4KVQOC+IMIjImKkdjo2CBKyEtJgARIgARIgAQYAbRBBLBkyZJy/vz5ZCWdOnWqjB492vG7o0ePyoABA+TAgQOSL18+GThwoIwcOTLZNWvXrpXx48fLuXPnJCIiQqZPny7Nmzd3pHn69KlMmDBBli1bJrdv35Y6derI4sWLVVq9FioBmJiUKEeTjkpk7kipWaim3uIwHQmQAAmQAAmQgA4CoRq/ddzaMkksFwGEAOzVq5f07t3bASlHjhySLVs29TOcFhkZKU2aNJExY8bIsWPH5J133pG5c+dKnz59VJq9e/dKvXr1BMKxZcuWsmrVKiUADx06JBUrVlRp8DP+vmLFCilVqpQSi8jr5MmTkiVLFl0OYgPShYmJSIAESIAESMBSBDh+i1hSAA4ePFjwz50hSjdu3Di5evWqZMqUSSVBdHDjxo1y6tQp9XNMTIw8ePBANm/e7MgiOjpaqlSpIkuWLBFE/woXLizDhg2T4cOHqzR37tyRAgUKyPLly6VTp066GiobkC5MTEQCJEACJEACliLA8duiAvDRo0fy5MkTKV68uHTp0kWGDBkiGTNmVI2nW7duKgoIwafZjh07pFGjRnLz5k3JnTu3um7o0KHJRCSme3FNYmKinD17VsqUKSOHDx9WolCz+vXrq5/nzZunq6GyAenCxEQkQAIkQAIkYCkCHL8tKABnz54t1apVkzx58qipXEzz9uzZU/B7WNOmTdWUbUJCgqMxYdq2QoUKavq2fPnyKjKIqd3OnTs70sTHx8vEiRPl2rVrKl+s+bty5YoUKlTIkaZjx46SLl06WbNmjduG+vfffwv+aYYGVKxYMRU9zJkzp6UaNwtDAiRAAiRAAiTgngAFoEkCEFO0WHPnzX799VcpV65ciiSffvqp9O3bV+7fvy+ZM2cOqwCMi4tTItLVKAD5iCEBEiABEiAB+xCgADRJACYlJcmNGze8tozSpUs71vQ5Jzxx4oTauIH1fVFRUWGdAmYE0D6dmyUlARIgARIgAU8EKABNEoDBNMGVK1cq0Xf9+nW1vk/bBIKp3GeeeUZlPXbsWFm/fn2yTSAPHz6UTZs2OW5du3ZtqVSpUrJNINgAgo0gMDSG/PnzcxNIMM7itSRAAiRAAiRgAwIUgBYTgPv27ZP9+/dLw4YNBUe/4GdsAHn99dfVmj4YplsRCcRawFGjRsnx48fVMTBz5sxJdgwMNnRMmzZNWrRoIatXr5YpU6akOAYGf3c+BgbnC/IYGBv0XBaRBEiABEiABIIgQAFoMQGIc/r69++vInmYbsVmj65du6odvVj/p5nzQdB58+ZVB0FDDDobDoKOjY11HAQ9Y8YMtwdBL126VB0EXbduXcFGEZwxqNfYgPSSYjoSIAESIAESsA4Bjt8WE4DWaRr6SsIGpI8TU5EACZAACZCAlQhw/KYADKo9sgEFhY8XkwAJkAAJkEBYCHD8pgAMquGxAQWFjxeTAAmQAAmQQFgIcPymAAyq4bEBBYWPF5MACZAACZBAWAhw/KYADKrhsQEFhY8XkwAJkAAJkEBYCHD8pgAMquHhSJpcuXLJxYsX+Sm4oEjyYhIgARIgARIwj4D2KVecAvLcc8+Zd2ML3Snd06dPn1qoPLYqyqVLl9S3gGkkQAIkQAIkQAL2I4AATtGiRe1XcANKTAEYBMT//vtPrly5og6tTpcuXRA5pbxUeztJrdFF1s/Q5hKWzOjDsGA39Kb0oaE4Tc8stfsPQENVR8S+7t27J4ULF5b06dOb7jsr3JAC0ApecFOG1L4+gfWzaMPzo1j0oR+wLJqUPrSoY3QWK7X7TxOAmKLFkqucOXPqJMNkeghQAOqhFIY0qb1js35haFQG35I+NBhoGLKjD8MA3cBbpnb/UQAa2FjcZEUBGFq+Aeee2js26xdw07DMhfShZVwRcEHow4DRWeLC1O4/CsDQNjMKwNDyDTh3fAt56tSpMmbMmGTfQQ44Q4tdyPpZzCEBFIc+DACaxS6hDy3mED+Lk9r9BxxpoY5+ut2w5BSAhqFkRiRAAiRAAiRAAiRgDwIUgPbwE0tJAiRAAiRAAiRAAoYRoAA0DCUzIgESIAESIAESIAF7EKAAtIefWEoSIAESIAESIAESMIwABaBhKJkRCZAACZAACZAACdiDAAVgmPy0aNEimTlzply9elUqV64sCxYskBo1angszdq1a2X8+PFy7tw5iYiIkOnTp0vz5s3DVHrvt8Xu5fXr18upU6fk2Wefldq1a6vyRkVFebxw+fLl0rNnz2R/z5w5szx69MhydYyLi5OJEycmKxfqhvp6Mjv5D3UoWbKknD9/PkV1+vfvL2i7rmZ1/+3atUv1t19++UX+/PNP2bBhg7z55puOauCrABMmTJBly5YJvg1ap04dWbx4sepr3szffhzKxuytjk+ePJHY2Fj57rvv5OzZs+rbp02aNJFp06apLyF4skDaeqjq6MuHPXr0kBUrViS7/WuvvSbbtm2zhQ991c/T16ZmzJghI0aMcFtHK/lPz7iA5/2wYcNk9erVavcv/BcfHy8FChTw6MNA+26o2qmd8qUADIO31qxZI926dZMlS5ZIzZo1Ze7cuQKB8Ntvv0n+/PlTlGjv3r1Sr149dSxMy5YtZdWqVUpQHTp0SCpWrBiGGni/ZbNmzaRTp05SvXp1+eeff2Ts2LFy/PhxOXnypGTLls3txRAQH3zwgWKgGR543jp+uCqOh+q6devkhx9+cBQhY8aMkjdvXrdFspv/UImkpCT5999/HfWB/1599VXZsWOHNGjQwK0AtLL/tm7dKnv27JGXXnpJ2rZtm0IAoj+hf0FAlCpVSr1sHTt2TLXZLFmyuPWrv/041O3VWx3xFYX27dtL79691QvnrVu3VH+Djw8ePOhVAPrT1kNZR18+hAC8du2afPbZZ45i4CUyd+7cHotlJR/6qh+CBc6G9L169ZLTp09L6dKlPQpAq/hPz7jw3nvvyZYtWwTjAV5S3n//ffWZNvRdTxZI3w1lO7VT3hSAYfAWRB/E0cKFC9Xd8U3hYsWKycCBA2X06NEpShQTEyMPHjyQzZs3O/4WHR0tVapUUSLS6gYxAWG7c+dOJWTdGTr84MGDVfTF6gYBuHHjRjly5Iiuotrdf6gkfIP298cff7j97rWd/IcXC+cIICIIiIIh8jB8+HDlUwgmvHygXniZcWf+9mNdjcWgRK51dJftgQMH1KwDIr3Fixf3KCD8aesGFd9nNu7qBwGI5wfKq9es6kM9/kMEG9+y3b59u8fq+vus0svNiHSu4wL6XL58+VSAAy8rMMyqlC9fXvbt2ycY81wt0L5rRPlTQx4UgCZ78fHjx5I1a1YVQXKegurevbt6eH3zzTcpSoSH89ChQ9UgrBmmq/CgS0xMNLkG/t8Ob6iYSkNExVPEEgPtu+++K0WKFFGCuFq1ajJlyhSpUKGC/zcM8RV4qGI6EW+oiA7VqlVLRY88DaJ29x/aLAQS2iCiue7MTv5zHVwxJVqmTBk5fPiweqnSrH79+urnefPmpahyIP04xM0yWfZ6BAQi2E2bNlXPHU/fWPW3rZtVR08CEM/ETJkyqahfo0aNZNKkSfL888+7LZaVfejLf4h0Fi1aVEWsu3Tp4lUA+vOsMst/uI/ruPDjjz9K48aNVXQ6V65cjqKUKFFCjX1DhgxJUbxA+q6ZdbT6vSgATfbQlStXlMjBtCCEg2YjR45UEbL9+/enKBEeaOjonTt3dvwN6yKwDg0PAisbxNwbb7yhBpndu3d7LCre8BBdqlSpkoq+fPLJJ4I1MSdOnFAPOisZpl7u37+v1jRiPRn8cPnyZTXNnSNHjlTlP1Tm66+/VoPMhQsXPK4Xs5P/XAdX9EWs+UPfLFSokMN/HTt2VNFOTBO6WiD92Mw27EtAYK0V6lyuXDlZuXKlx6L529bNqqO7+mHdGF6uMYV/5swZ9bKSPXt2FT3KkCGDrXzoy39Y94f1m2iHnpYooMJW9Z+7cQGRP6wDx9o/Z0OUumHDhmrZk6sF0nfNaqN2uA8FoMleCmTgsLMAxJoOPIQg/vwRcli0jtA/RO/HH39sspf8ux3ELd5SZ8+erdbkuJqd/Ye6YCE26rBp0ybdYKzsv7QuAOGbdu3ayaVLl+Snn37yGP1z52xfbV13AwkyoS+BhOy16BAinYgs2UnE+6ofhDvW5GLzoD9mFf+5GxcoAP3xpDFpKQCN4ag7l0CmHew6hYgFvJjSRiQPb+X+WocOHQSbK7766it/LzU9PdZ0YlclpoJdza7+Qz2wPgwLzLGru3Xr1n5xtar/0vIUMMQfIpsQR5hy8zQ96s3R3tq6Xw0kiMS+BJKWNdaUYRq4b9++Ke4WyLM4iCL7dam3+v38889qLTXWIGNDj78Wbv95Ghc4BeyvJ4NPTwEYPEO/c8DCY4S1tbc3hMMhEtAxPG0CefjwYbIIDI5WwXSpFTeBYGEuNrRgoT0iDL6O0nAHELsTsf4PR90gsmZlw3Qw/If1UoMGDUpRVGwCsZP/nCuAOiUkJMjFixeVGNdrVvafp00g2ACCjSCwu3fvqo1LvjaB+NOP9bIzIp07AaGJPyy1wG5uiCN/zVdb9ze/QNPrEYCIcKJfYl0glqG4M3+fxYGW19/rvNUPm12w3MTb7m1P9wun/3yNC9omELzwI0INw6kQiHb62gTib9/11x+pNT0FYBg8izVF2PSBgRUDCI6BwTor7HjCzkMcEYN1glo0CescsCAdaz5atGihzkjCBgmrHgODs+IQzkf0z/nsP2yawLmAMNc6fvTRR2qXV9myZdV6QSxcxoMb57a98MILYfCS51viYdOqVSs17YspfWzIwds4jgzBoGp3/2k1x4sJIreYhkfbcza7+Q8DHxadw6pWrapeKrCuKE+ePEokYH0R6uh8DMzRo0eTHQODacQ2bdqoFzWYr35sdqP1VkesbcTOSjwzsJvb+XglMMAUP8y1jr7aupl19FY/1AFrcSEcChYsqNYAYl01dsli8xmOg3FXPyv50FcbRfnxYgJfzpo1S/r165cCv5X9p2dcwNQwzqrEixc2JiGQAMMYqBkEIcZG9EWYnr5rZju1070oAMPkLRwBox0EjZ2G8+fPV2cCwnDOGg7iRSfQDOcE4iBX7SBoLAK26kHQng4sxflceHt1V0fs8MI0I866wg4+nNeGqRsM1lYzHAuCae0bN24owVe3bl2ZPHmy2kmaGvyn8f7+++/V+j+8hUdGRiZzg2sbtbr/EImG4HM1vIihn2mHyS5dulS9gMCn2GjlXG/0SbRfREU189aPzW633uqIMntahuF8tqNrHX21dTPr6K1+OLQbpypgJzf8h13r2OGM9cPOYtfKPvTVRsEa7RM7YrH5DC/UrmZl/+kZF7SDoBEFdD4IGqJeM+TjPJbo6btmtlM73YsC0E7eYllJgARIgARIgARIwAACFIAGQGQWJEACJEACJEACJGAnAhSAdvIWy0oCJEACJEACJEACBhCgADQAIrMgARIgARIgARIgATsRoAC0k7dYVhIgARIgARIgARIwgAAFoAEQmQUJkAAJkAAJkAAJ2IkABaCdvMWykgAJkAAJkAAJkIABBCgADYDILEiABEiABEiABEjATgQoAO3kLZaVBEiABEiABEiABAwgQAFoAERmQQIkYB0C2hcVbt26Jbly5TK9YNu3b1efi8P3WjNkyOD1/tu2bVPf/8Yn2tKnT296WXlDEiCBtEuAAjDt+p41JwHbEfD0OSmtIvgu89ixY+XmzZvqE2C+0ocCAD5jOHToUHnrrbd0ZV+9enUZNGiQdO3aVVd6JiIBEiABIwhQABpBkXmQAAmYQgDfitZszZo18uGHH6pvFWuWPXt2wb9w2e7du6Vly5bqm9ZZsmTRVYxFixap7xEfOHBAV3omIgESIAEjCFAAGkGReZAACZhOAKJp8ODBcvv27WT3dp0C1tJ9+eWXMmzYMLl48aI0b95cPv/8c1m7dq0ganjnzh0VgZszZ45j2hYfox83bpzgw/S4R8WKFWX69OnSoEEDj3XF1O+1a9dUvpolJiaqch48eFBFJCMiIiQhIUFefvllleTChQtSokQJOX36tJQpU8Z0jrwhCZBA2iRAAZg2/c5ak4DtCfgjAPv06aOEGwTcvXv3pG3btoKpWqwRhAA8e/astGvXTonCmJgYxaZ3795y8uRJmTZtmhQuXFg2bNggsbGxcuzYMSXi3FnlypWlS5cuMmrUKMefIRyrVq2qxCTWBB45ckQiIyMFaTUrWLCguk+PHj1s7xdWgARIwB4EKADt4SeWkgRIwIWAPwKwZ8+eySJs/fr1ky+++EJF67Qp42bNmknJkiVlyZIlKipXunRp9T/En2ZNmjSRGjVqyJQpU9z6A4JywYIFydbz5cyZU/2ue/fuHn1YrVo1ad26tRKjNBIgARIwgwAFoBmUeQ8SIAHDCfgjAAcMGCAPHjxwlAFCa926dXLixAnH7yDQEB1cv369bNmyRa3ly5YtW7JyY1oY0UOsP3RnmTNnFkw1d+jQwfHnuLg4mTx5stSvX18gIPE316neOnXqSN26dVWEkkYCJEACZhCgADSDMu9BAiRgOAF/BKDrWkGIso0bN6rpWM0w/Yq1fvg9BB528UIguh7lgoghpmzdWZEiRVQUD1POzvb7778rUbl161bZuXOnrF69Wtq0aeNIUr58eenVq5cMHz7ccE7MkARIgATcEaAAZLsgARKwJYFQCkAItqioKNm1a5e88soruvkgali2bFmZO3eux2s6d+6sopHffvutSvPo0SPBNDHEYePGjXXfiwlJgARIIBgCFIDB0OO1JEACYSMQSgGISr399tuyZ88emTVrltrEkZSUJDjkuVKlStKiRQu39cZavxUrVqgdv7C//vpLRowYIe3bt5dSpUrJpUuX1FpAbDjRpnuxa7lVq1ZqPWLWrFnDxpM3JgESSFsEKADTlr9ZWxJINQRCLQCfPHkikyZNUjuDL1++LHnz5pXo6GiZOHGivPjii2454gBqTANjahkRxMePHyvBByEJgYc8sIZw5syZjnMC+/btq46HweYTGgmQAAmYRYAC0CzSvA8JkECaIICI3927d9VZf77s+vXrSigiYogIIY0ESIAEzCJAAWgWad6HBEggTRDARpL4+Hj1jV9f3/eF8Dtz5ozj7ME0AYiVJAESsAQBCkBLuIGFIAESIAESIAESIAHzCFAAmseadyIBEiABEiABEiABSxCgALSEG1gIEiABEiABEiABEjCPAAWgeax5JxIgARIgARIgARKwBAEKQEu4gYUgARIgARIgARIgAfMIUACax5p3IgESIAESIAESIAFLEKAAtIQbWAgSIAESIAESIAESMI8ABaB5rHknEiABEiABEiABErAEAQpAS7iBhSABEiABEiABEiAB8whQAJrHmnciARIgARIgARIgAUsQ+B+rFdds0WEJ+QAAAABJRU5ErkJggg==\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.figure()\n",
    "# plt.plot(tspan, control_lqr)\n",
    "# plt.plot(tspan, static_u, ':')\n",
    "# plt.show()\n",
    "actuator_info = [[0,0], [2,1], [4,1]]\n",
    "lst = [actuator_address.index(i) for i in actuator_info]\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(tspan, control_odi[:, lst])\n",
    "# plt.plot(tspan, static_u[:,lst], ':')\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.ylabel(\"Control Input (V)\")\n",
    "plt.show()\n",
    "plt.savefig(control_fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
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uU2eEvD7CiRJBrTbDJRqodvn8d2YABNgAkwg0RBQbf82YKKsAMpYHNUE6NNzYEVFKQWM9RDg/EygfDfJGuZ8AdjWAsheChh4DXh+BtjRFshRBuh/RevZ+QYEwnL6afwMCoHdyBookj0dXD190GqVPT77BKCJRU6sMFmBJA8PABnySYmnEQIMvA5kL6n186LtQMe+W5tJtY+zlQC6/SfN/chQKc9hijRSwIuunqebUfNdmAATYAJMwEgIqLZ/GzAPVgBlLI5qAvT+IbCmGpA2O2AzQsr1p7G6PfoX2NcDyFcV+POEdFy61la6dsxzrWd38dlHdN90Uxz5XvmrFpIkSSLucfPVZ3TZcB3pgrxwJ9UgJEUQ0O8ycGkeQMfBFXoCzZZo/bxoO9zdBvw3RFL0BtgDmUP9H4ODgH/aAM7nJYW370UguYlunsl3YQJMgAkwgURDQLX924CJsgIoY3FUE6C3d4D1taVSb7ajgSPDgGKNgM67gdubgaPDgeJNgE47gW8ewMJikr/g5E9aVwOZc+Ip1lx8iXYV8mB+O8tIdHbffI07h5djfop18M1cCmmGXgu3QKbOBIx+Lj9II9AfWFoW+OYO1J8JVB0SeYW+fwRWVQZ8PYG60ySFmBsTYAJMgAkwAS0IqLZ/azEmtS9lBVAGcdUEyPUasLmhlAS65njgYG+goC3QPTQQ4+x0oGwXoOUqgKxklBYmntVAum68gcvPP2F26zLoZBUaXRyB0aOFjVD6mz22p+qCLmNXIiklp15UAvD5CPxxACgiM0Dj5nopmbVpbmDoPcn3L2q7vws41F/yDRx0A8iUX8YqclcmwASYABNIbARU278NGCwrgDIWRzUBiujnV3sysLsTkLuC5Ad3ZgpwdSlgPRho8Lc0G03dYDqizWmh1Qwr/W2Hj9/8cWhQNZTNmzFy38AAhMzJhySBP9DIfzaGdWmNhuY5pOTTtzbIijwWDwoOBpaVBb66Ao0XAFZ9oh87+QhuaQq4XgFKNAU67tBqjgnyYi836SieXAB+fAVSZwTMSkuW4qxFEuSUeVJMgAkwgfgSUG3/ju8AVejHCqAMyKoJ0LPTwM52QM6yQL3pUtBHtpLAoOuSrxz5zNWaBNQYI81mtQ3g4Qh0OaBVypRP3/1RcaYdyO3v0fQGSGOSPDKd1zeATfXhmzwjSn1fCcu8mXB4UDXg1SUpaCNNFqkGcbIo/eLK+IWd5OOXMoMU0Wzym+TTH54Aq6tJ5fHia3mk9Dqvr0v3oLJ5mQvFdaSGc93nV4DdNODxYSkYJ7pG/qHVR0rW2VCfTsOZAI+ECTABJqA+AdX2b/WnFucnsgIYZ1S/XqiaAD3+D9jbFchbGWgwC9hQR4rAHeEI7OkKPPkvssVse2vg5VkpDyDlA4xju/riE7psuIECWdLgwphav/aivH9np8O/aBOUedwVAUHBODbUBqXN0gILigI/PgPdjwIFq8fxiVEu290FeHoUqNwfaDQ39nucHA9cXwVkKQIMuBb3gBA/bymQ5h5ZDiMoTYVrSxyzFI792fq+gqyg11cDdlOBoABpNPmrAQUpJZAZQL6Sr68Bry5KVWKo5SovJQeneSZGRZD8S9/cACh10ncPyVKaNBmQIjWQIQ+QqYDEKENufa8uP58JMAGFCai2fys8Dzm3ZwVQBj3VBMhxP3CgF1CgupR0ebW1ZG0b6ywdhVK6lDYbgTJtpdkcGgjc3xFeLSSOc9x45RVmHH2MhqVzYE3XCr/2IuscWekazsHAl1Y47vgePaoWwLTmpYFDg4D7/wBW/YDG8+L4xAiXebsDi80la9zAG0D2ErHfg6qgLK8g+R/W+x9QbVjsfeiolObx8al0bU5LIJkJ8Pau9GyKPG69DijZLPZ7hV5BZfN23HDFHdcvSJUiGWoVz45W5XMjRbKkcb6HVhf++CLxppJ/1ArVlF4M6Mg3aiOu11YCtzcBP32l35JFkBTBAtW0eqzRXUwuBR8eAS/PS8FKrvZA4I/Yp0EJx/NVlhRq+sxRsvOErDDTywR9hijdFOXdpL9//yBVGaKXB/pcUP5NcitIlRFIl12yltNPOrOEzeZ30kLcgn5K+VCTpYz/yUfsEslXKEBAtf1bgbHr6pasAMogqZoAkaXq8EDpCI9q/Eas/LHGBngf5biXjgRFsug4WtJCGYzZ54B9d9wwrE5RjKhXLDKZoEBgbgEg4BvQ7xLOe+dEz823kClNCtyYUBcmL08DuzpI1TpGPAKSaqn8XJgLXJgVns4mruuiYWOSDhh8GzDNGXNPn0/ApoaA53MpcXbbTUD+qtL1dJRKeQbpOJsiqFusAsp2inUU1509MeCfO/jiG5oUO7RHiRzpsa5rReTLouMaym63gX09Aa/XkuJKih9Vh4lNQaENnWTi1kYgyF8aJVkCbUZKDMgSlhAaJRAnqycpffQnKTMRW7ocQH5ryeJHkeukJJJM04vBx2eSwkgBVBFbmqwSI1IGSWkm9wtt5dsQ2JKy4vkS+PRM+vF8ISl99OMvlX3Uupmkl3KO5iorvUyRm0rWosYrT6TUkXX4i0v4j/dbwMdTkiXfT9Lf6UVCY3nXQCMlmazJKdNLSjIpx/QnZW+gAD46WaAfymmaEFpggOSvTawoKwO9MGh+Ar5LAYnEk14g6E8K6DNJKzGiF236/GkYESdKXfY7tx8dM1Nt/9bxuHV5O1YAZdBUTYDIenN0hJTqpfkyYH7oEeWUz8BSSykZc+9zQJ5Qqx0dDZ4cB5RuBbTbEucZNlt+BY5vvbDmj/JoaB5FkSIL2fpakn/eX68QhKSwnn0WH775Y323iqhXNIM0LvrgRxxLXJ5OyiUptfRF23oDYNEuLr2ka2gD31QfcLsFlGkPtFkffV//78DWpoD7PcA0D/DnSSBj3sjX0jgopc697ZLFo9NuoFj9GMdCFr9O668jIDAYxc3So3PlfPD68RNb7F1E0uys6VJiT78qKJwtXfg96GiWvixpE0ifI3bFTdOT5mm/DDg3Q7LKZCoorS1tvNo0r7fA5QWS36jmaDhtNiBfFUmxoS9l+oJOmjx0bEkkhZgUTPqTxkwbvb43MdpoqEIObT60CVGuTLLwkWIcsaVIKylthWoBhWtJicV/pyyTnJCM0PE5Wdbf3PrVapg6c6hCaCNZCcnyakgKNG225N/q8UhSaOlPj8fAJ6dflZYwVkmAjPmkH5IH+iGLX9IUkrJLmzkdmVM1Hvqc0gsTfe9EVZbpfrS5U91ukk3yrTVEpZAYkdJPdcYFJ/rzMfDZOW5WYm0+c1GvJbZZi4X/ZAv9O30vGdqLBX0evrySuNCah/3dBfB2i3795bChly3K6kDuGPSTMfTv9Lkl1xYdNtX2bx2OWde3YgVQBlHVBOj6GuDkX5JCR5apWaHK2Xg3YGFJyYIx5G647xpV6dj/p1bWtKDgEJSachL+gcG4MLomCmRNG5mM/Qrg9ESgaAOgy17xu5lHH2PDlVdoUiYnVnYpLyWkpsTUlJuPcvTFtTmdAHZ1BGhjpeCP6FK//O5eQjmtLfnzddkPFK33q2K3uzPw/JR0dP7nKclKEV2jjYGO0B12ShtZzxPRKlkfvvmhybIrImK6donsWNWlvDj+pfbB2w/dN9/Ck3feyJ8lDQ71tkSmR1uBu9uBzy/Dn0pKFJXsK9EEKNZAshxE1yjg5fgYSSGhVro10GypvPrLpDiRT+fjQ9Jbu7aNotBLNgcsO+n8izlsKGSxIuv2RyfJWkXsNJYZOgaPrpHiTkoHKXuk9OWpFHff0OjuR1YO97sSe5erkg+h5ihdc33yVFJi8hzmgFkZySJGSqES9bGjG6P/N8mFgV6CyEJMf5KlKrpGlnKhfBSVfrKE/kkWqhShdb7jKgvEhqzp7x4A7+5LEej0958+v96BFHFhKSSF0FI6VqdxpIzwchTX52p7XYAvQJ+h9w8keRIK35OYrZ70oqPxCSUlhCx4abMCpJxo/iRLFVngxU8KgPxLA/2kH1KUxTG6h5SX9asL4EkK1Evp/2Jq9H1D/swaNholkayG2n4nxpURfd/RC2kk5S6CohfVgh71vrSulKiflFr6PtP8kJzRSxH9EE8kkRiRbNB6BPhIPuN0MiF+PMJPJqIbe9WhQP0ZcZ1VnK5Tbf+O02j0cxErgDK4qyZAlOaF0r1YdARarQGmZ5KUHTpqXRzq9zX2FZAmszQblyvAlibSscPQu3Ga4cuP31Fn4UWkTpFMRAAnTSpVAAlruzpLPmcRfO0evvVC0+VXkDJ5UtyaVBemL/6TFE+yIgy9H3eryI52wPPTkVPZxGnUES46Pha4uVbyUep9Njz1CVn16GiXfCIpb2CPo0Ceir+/O21sO9tLFUfoSLsv/ZkjUp+BO+4IH8hiZunw78BqSJsycuQzRVS3XHkVBbxuYmnqjcgS9CG0fxLpS9LfO/LbM/kQFSFlsKlU4o6+OOm4jhTqp8ekYxQaPwXHUBnA2I5848qPlCyKhKbNkY4FSZmgL2iy7AjrDh3h0A/9Oyjc8qO5P1mIzFsDVQZIm7vcRhbKRwcleSBlJqqyFfH+wlpAloL80sZJVsw8VsoqFcSLgkhIIXS9ClBkPL2ARddobGbmkuIjlEJz6bMhZ+1oLcgaQ4oorRsxIutV1Ahw2nRJuTMrJSmj2UtLf6fgMSWtTGQpJGWdGJElVSiGMSiFxIzyfQpllBTCohIf+j9SwOhzog0rklthqXKWxuDxUFL46O/RWSrJyh2VkWYMpNQp0SgAjRRBOnanF5uw4/iX4bXVoz6XXmpIlkjGycWFjkrFEXN26YVWHKmGHq3Sywh9ToVvYqBk8aWXJd/PksJFyh5ZPr++Bshdgv6MTmGP9DnLIp04kKJHfp+av9OfNAZt1igmpiTXZF2m8YiXPNfw42X6e7Wh0veeDptq+7cOx6zrW7ECKIOoagJ0cX5o/d/u0hHwrNzSUWuvM8DGUGsXHQdrjqE+vQBWVADIP2eCW5xmeOzBOwzaeReWeTNKqV0iNjp+nF9I+iLpZQfkrSR+GxISgnqLL+HFh++Y19YC7S2yAItKSh/kznslq1ZsjT7cdIxNG1hEK2Zs/aL+nt4uNzcCqGoK+ZU0ni+9uZ+bKUVE04bYfjtQsmnc7kxWsQ11pS9osnb1OCZ90QI4//QDem65hWRJk+DIYBuUymUa7T3dz66G2aXxSJYkBN9T50a6+hOl59PGJixL94BnJwCK8o5oGYzubqQYkr+fISS99n4nvQw47JasTZpGPnJUuaVIPe2UDPKpIkskWa7pGDeiMkMKPSlPtDHTCw1tQpqjITWsR7FJC3026FiMFA1hXQpVOuiYNLpGLhSkkAlrISlloUohKbNRFbOfftJxK1mr6IeUqTc3AR/Ny0SEB5DiRNZOzQ/dV1uLXmxzje/vSSkkhYfGT4ohcaLPVXTziPgMsiKZ5pJe6sg6ThZVelHSvIwI5YasbZ9CffOi+HtGvBfxpZyoGkWcLLZkYTOUUpL0okqKj1AInSR/VI1ySC+LirYkktKt+WyJAB/6nIUqffp291Bo7qrt3wqNXxe3ZQVQBkXVBIiUmEvzAau+kmKzoJhkMqcgBrK4pTQFxr8Jnwm9Zc4J9W+b4C453sbSFp52wvJzL9CxUl7MaRMleTRtPquqSEei4yj4IPzteOX5F5h/yglVC2fBzj5VgNOTAPvlQH4bydoW29vh2RmSTxpFsnajXHYyGh0lbG8lbcIRG20abTdqFdkrupMFjlLukOJLtZfbbEBwCNBgySU8//AdfW0LYULjkr8OmN5mL1JQy2zxu32BtpifvDeOjWqIbOmjqWxC15MVh3L5OV+UNgLiRm/XxLFcl+gjfGWg0llXUrjJRYGsdhqfQtpYrQdJLgsRNg+/n0EgS7Pfz2DkT/MTWd3OSP0oQlfTlwZGUcrUl9IJkWVISYuVzkBEuRFZXMIUwlClkCLPKWI0ukZWHrLmiJe4JKGW2Bgsi3TsSNZWSgtFP6T06dg/Sikske5LjP05wAsAACAASURBVMg6p7GE0d/JOkU/ZK2KTyN50wRciGP5UOursUYra4JSiBFZNjXHpfT9T3+n7yY6diZL+c8f0g9ZNumHvqfpT/LlJPcaOiGiP8m6Sv7Pwuczv6T8GcrLQnzWPJ59VNu/4zk+NbqxAiiDsmoCdHqyFACgqfZBtXLJ6lBvBnBmsvQhHv4gfCb0pfF3TsmZmY5i6W0ultZ7623YPfHA1Gal0LNalOspcvTYyPDycxHu9eazL6rPOy/0lWvj6iAHPgHLykv+HB13Sv5tMTXyA1liIb29t9sKlG4Z2zBj/z05LZNC+WCvZCUlqxRVT4lLWpno7k5RwaRUkoJSexLOZO2GPttuI33K5Lg6vjZMU0U5KqI3+eOjgDtS8E1w9dFo+bgmHrz1RuvyubGovZZBG7HP2DCuoKPbG2ukeWssFrT55LHCV9OisH+fFM4fvJE12BOlk7qgVBJXYRkNa+QXRko2HSfTBpUQG1l9ybojgjIehgdnCL+wGJJ405EeKdSkzNARLil8FFSR0DdsOs4l6yelMSJ5opdack+g7xVSloV/GSk3mSTFmZQbsvhr3GASovzwnHRKQLX9W6ej1u3NWAGUwVM1ATrxl7S5Vh8l5fbTVPqgNC/0/7Qh9LsYeSakWFF0JAU8kG9ULK36vHN48/kHdvWpAuvCWSJffaAP4LgXqPEXUGvCL3dqt8Yet1y+YELjEuhrWxiwmw5cWSQ5TdO4YtrQKT/dqQnSkd7gO4abR0sThQ1grulErP5QGgNqFsZfDaPkKiSFlliJ/HxJJGutVR84vPmKlquuCle6vf2sYVUw1FcztkUxxt/TRk1R1KQI0hHWb5pTcB4cDaqC93kaYVzXZsiSLhrrqDEy0HbM9NJAx6F0lKnxvaQjT41jfWxWdG2fx9czASYA1fZvA2bNCqCMxVFNgI4MB+5sBmpOAGr+BWysLzmBk18YVc6gaMduhyLPZEM9wO0m0H4bUKpF+O9ubwYuLQAq9ZLKgwH45vcTZaadFn+/N7keMqU1iXwvStBMKR+6HpKiK6O0f667YtKhhyiV0xTHh1WXjiHIN5GOwMg62fXfX6trkI/dikrSUXazZUCF7jJWQoWuoUEmviEp0SNoIlb81Q/Z00eImiQLGEUak58THTm32QCUah42sPEHHbHr5muUzGmKo0NshP9gQm7+gUGYs+M4vJ2uoEjStyiRKQRlcmdAlhz5kCRrUXzJUgHbHv3E6osvxJFw7oypsb2XFQpFTJmTkAHx3JgAE9ArAdX2b73O8vcPZwVQxuKoJkCayh6UWoVSrGxrKUWokh8QBRJQWpB2myPPRFNWjUqbWfWRfke+NRRwofG3ovJpZqVwy+Uz2q25hpwZUuHa+DqR70ORYkvMpWMX8v+LxvGeKmFYzbLDz6AQnBpui+I50kvRXFubS0fV5MxN0atlu0i+bWQK+28wcO8fyV9n4HXDccaOSR6CAvFwfn2Y+91BYJIUSE6KOCWKpuASCl6gQB1KpkvHUR13SZUkIjRiVHPBBZEn8O9W5uhSOb8MyTPsrpQXse/227jg9BEpkiXBzJbmaF8xL5JEY8l65vEN/bbfwatPPjAzTYndfa1RMGoKIsOeLo+OCTABIySg2v5twGxYAZSxOKoJ0P5ewMP9QIPZgPVAQKPc0RER5Wmq2AtouijyTI6NAm5tAGzHSGW/qGnSyWiuDM3Xt+2aC6YcfoQ6JbJjYw8pwjesPdgHHOwtKZt9L8RIS+NDGOlolHJgUW7A1xTZCclZnWoTU+QoKX/UKLq2gI2MVVCnK+X0a7v0NBalWIMGySJEvkZ8PEULk+WPouiiaVuuvsK0I49F9ZQLo2shQxqFUk2ogyTapwQHh2Dk3vs4dN9dpBRa27UCbItl++2IKGVO5/XX8czju6hDTWl1frFC63FOSj+akob/e+8tLjh9ACnEX31/IrVJMhTLnh7VimRFmwq5kSeTjivKKD0pvj8TMHACqu3fBsyBFUAZi6OaAO35A3hyBGiyUCr7dbAv8GBP+MirjwbqTI48k4vzgPN/S7mTmi+XfkfBDC+pYoiVdDxM2fr7X8a4Aw+w+9YbDK5VBKMbFI98H6pAQj5wVQYBDWfFSEuTRiaHaSpcHFsTKZOHlhajFBCkeFIUc9Scbg3nSPnjjKAN230Ph++7o2mZHFhRxhm4vlJKaUFWLUq5QVZWy86/9WP8GRSMxksviwjintUKYGqzaGr3GgGL3w1x/qmnWHn+JZInTYIN3SuiZvHscZoRJdRuteoq3L78QOWCmfFP78rK1VKO04iUv+i7fyCW2j3DP9df48fPoBgfSN4CHSrlxaj6xUV1GW5MgAnIJ6Da/i1/qIrdgRVAGWhVE6Ad7aUqFs1XAOW7Ahrrnmbs9f8Gqg6OPBNywj8yLLxyB+Urm5tfiqjrtEeq2xt6rNt8/X08cPMS1Swal4lSAm6VtZSihHLoRfBpi4qNUnzUmH8eHt7+mNGiNLpaF4h8CZWmomhi8l2kyL2KfwKFasigr15XinSm41uqlkL+e+a5Q2t5kvM+Oe1rkUvsyvNP+GPjDeEDeHJYdRQ1i6H6h3rT09mTzjz2EBHS1Ba2s0SbCtpF8zq9/4Y2q+1BilG0QTY6G6n+b0RyMGa/A955+YnBkP8sRYlXLJAZWdKa4JtfIB64fcV/Du6wf+kprsmazgTz21miVhyVav3PkkfABAyXgGr7t+EiACuAMhZHNQHa1kLKldZ6PWDRHjj3N3BpXvjIqTwc5YqL2DTl1TQRwlTncrW1lDGefPmWlRWBHUF/HEbJLT9EPdtfSsBRnq55oSlhRr8A0v3+KE9zlJw9fUrYjarxa4oUGaz12XXK4YfYds1VHGVu+9NK9lBISSJlqXrRrOJ+0fnGyX6Iyjdw9fQRVWFIcfmzWkFMaVYqXiM4+fAd+v8jVa8hNrEdH8frIXrsRMnT111yxtyTT0VOyXyZ02Ba81JCqYtJDshHd9K/D+HkIeUFnNi4JPrYRu9moMepKfZoz+/+4vNy3dkTLz/6iDrbJsmTCoW4TO6MsC2WFTZFsiJ5Mio5xo0JxI2Aavt33Iajl6tYAZSBXTUB2tRQKk6vyZV3fTVwclz4yKPLt0cJeqk+LpUyG/VESstBFkHKi0cJmvf1FEl4P1qNQ6VLFkhrkgyO06KUgHM6KVkKqQTRkDuxkqLIz/qLL8HV0xfNLHNhaYeyv5aUi/UuhnUB+adVm3NO1Eje2acyqhbOKnuALp98BKeAoGBs7F4RdUrqtsi57AFqeQOy/rZeZY/H77xRIX8m7O5bRdbx7cR/HbHjxmuxwZ8cbptgjj3JP3LS4YfYeeO1INy+Yh5Mb24u/P1ia8R4xtHHggu13jYFMbFJyQTx8hDT3CkwaIndMxx3fCcCzH7X6Gi8d/WC6GadH2lMIpdljI0t/z5xElBt/zZgvKwAylgc1QRoXS2pIH2n3UDxRlKS44Ohkb1iNzj7a31bOnJdWFyKUp34HiBfPqqHq/EXvLpMJJF+naMebF16Cr+rPf2sI9Og+sPkv1euK9BiRZxI3XGVIorJutHIPAfGNyqJfFmM14F9wSknrDj/QpTIOzSwqs423DknnmLNxZci6OHUCNtwn8k4UTasi2YefYwNV16Jo8tjQ6sjR4YI6XHiMVRSdlqsuCosXk3K5MTKLuXjcRfD6hIYFIyxBx7g4N23wm10WrPSQlnRxvqrsR7OPvFUTK5/jcIY1yhKLkrDmna8RvMjIEhUF6IThUD6IgFgntsUtUuYiVRC9GJAJxbkL3rn9RecfPheWAWpUST5jBbmqF86cu3ueA3EiDqRfD19/01E03t4S24FlKQ+T+bUwmXll4T1RjQ3pYaq2v6t1AR0cF9WAGVAVE2AVleTKgf8cRAoUgd4bgfsaBM+8hGPgQy5I8+EUq3MySf5/FG6l73dAM/n4TV6qeTYtubwTJETFb4txKBahTGmQZTNRJNLMLoj5t9wO3z/LUbudRA+c9RK5EgvggFalM0l8uAZSyNftKqzz8LbLxBr/qiAhua621To3rUWXAAFP4xvVAL9ahQ2FiyRxmn/8hO6bLghMvts6lFRbNK6aA/feqHFyqtChlZ2Lo8mFlF8U3XxEJXuQYrbXwceYO9tN+H7uai9JVqUjfJ51WIsZEGc8K+j6DGmQXEMqlVEi96GfamjmxeG77knjnqp1SqeDSPrFUeZPKF+t9EMn4KrKEBr6dlnIpk9tdblcuPvVmXiZF01bCIxj44syldefMKe229w+dlH8T0VXaMgInqBbW6ZC63L5UmQ2Qfis4aq7d/xGZxKfVgBlAFaNQFaXlFS3jQpUzTHuzR2svBN+hh99On6OsDb2wDlAjw+Wprp2FdSuSQqok5BIQAs/dZhcY+akTdvSuY8O69Uu3TovRhTm8SEj6pfLDjthKsvPglroBhqEqBn1YKiYogx+Ousv+SMv48/QaFsaWE3oobOj7P333HD6H0OSJcyOc6NrhE5sbQMuVSrq7ffTzRcfAnuXn7oZJUPs1uX0emjNfWpybJ4eoSt0VYKWXTaCcvOvQBtxKTMNooaaBUPahrZpK5LO5aVpVDG4/GKdKEXxzH7HwjrHvkRz2trEecochoQWY6X2D3H+svO4sWBXjwpDVH+LLHXQldkQgrdlF4oTj3yAEXcaxRlepRpquQoZpYeOTOmRrIkwGffn3j16XuYUkzXpEqRFN2tCwjrcWJKtRTdUqi2fyskB7q4LSuAMiiqJkBLykiJlXvZAXkrSQmdF4emEKFcgGNeRD8LTQJpszKAh6NUT3TgtbBrgxZbIpmXCzoHTMCqSSOQMU2ECiChFkKkzwmMfCJpb/FodDRz+flH4cdDX1rUmlrkxLKO5XSuUMVjeDF2oc3Edt55fPjmj3ltLNC+Ul5d3l7ci97gW622F6Xi2lXIIyI8jamN3HMfB++9Rf4saXB8aHWkTalb3ytSBJqvuCKOtsgCSMqTsbUdN1wx8d+HYtikIJOirKs2+/gTrL3kLAIi9vStgnL5Munq1qrehxSaZWdfYLGdVDqwbsnsmN/WMt4KCgWLDN55F5++Bwi3hC09rX5rQVR1sjIf5vzxu7AmU+lNalSTnKLt6XTFIk/GaCsMvf36A2cevRepvuizpOk3tmFxkZA+aQKvShQTctX2b5lrrmR3VgBl0FVNgBYUB76/B/pdAnJSJY9g4H+hX/ZUeWKsc/SzCPXzC/tlpT5AkwVh/3y/oSNyuJ3AOpPu6DthWeR7nP0fcHkhYNEBaL1OBqXwrhThOWTXPeHQbehHV9uvu2LyoYfIlSEVLoypJTZZJdrd119EAAW1w4OqiaMaY2ik0A/ccVdYtfb1ryqCP5RodCRIdZTJorPmj/JoaG48R8F0PN51400x9mF1imJEvWI6RUT37bf9NuyefEC29Cnx3+BqyJkhtU6fofTNSPkjf1hSZKn1sy0kamzLVUree/mh97ZbePjWWwS4retWUSTVNtZGL4tbr7mI6HEqnUhJ1inopa9tIaRPFbeE8sSaqvPMO+UESmxPzapAZmFpLZAIq++otn8bsNCxAihjcVQToLkFgB9fgEE3gWyhiZo1SZ2rjwLqTIl+Fu8cgLW24b+j/H/FG4b9+9yG8ajttgoOGWrDcsS/ke+xoa5UsaPFSql6h47anluv8dcBR1EijAIG6MjC0BpZnsg/j96c/9eCnPWj5DTU8YA1lrTy+TLiwADdBZroeJhht/vwzU9EMVPFimiTh+v4wZrk0hTpaTfSNrKlWsfP0tXt3L/+QLPlV+DpE4BW5XILvz9tAj7iOg7yJW272l5YdsrmzYi9/awVe1mJ65jieh0pJDOPPcHGK69El2nNSqFHtdC0U3G9yW+uoxrnVGaQ8ijSC9yGbhWNMq0QrfGovffDTlAo5c3cthaifnZ8GimT9IJLyqRvQJBwQZnbxsKo/Wzjw0G1/Ts+g1OpDyuAMkCrJkB/55SqaAxzADKFKiNebwGXy1Id4JgSEZNn/opKkv+gaR5g2H0gWfjb4pRFy/E/70n4njYf0o2RnMpF8/MGSOkMCQKGOwIZdXdsRV/6VDbu7NMPsKLI475VFNkYZSwr9t56IyI2yapyeWwtpEoRe5oOOc+jqD1SOOnLeHEHS7Qqp10CZTnP1rYvrR9tqqcfe6B0LlNRtk0p62iYOP4MEjkGX3z4LpIlL2pfVtthq3o9uQ90WHsNDm5eIsHzwYFVFZUhSlROfKjOdI+qBTCtuXFUmNFE2NPiUL3oP6rovj42paYasvOekNeUyZNic49KqGpElsDXnr4iuTpFxJskS4pJTUuiaxXtosdjEn63L74YuccBN10+i0tIdii1UIpEkk9Rtf1b1W8f7R7GCqB2vCJdrZoATc8sKWMjnwKmWh6Beb6U0r9YdASyhR9B0dtxjekHcDdlP2lOlBw6VWik3bNTwM72QKaCktKo40bWEaqsQZa2rX9aoUYstWJ1/Pjf3o42jLqLLgrH6UlNSqJ3dXUS7q48/0Kkvsic1gR2I2uIPw2xHX3gjsE774lSb0eG2KgW1U1H5VQlhN5paBOvVSJuJeb0wVCTxzBjmhQ4MtgGeTMrnwbp7BMP9NoqVWFZ0bkcmlrk0sfU4/xMzUsWdfi7lbnwRVOq0ffMgH/uiJdOOjrd0rMSKhfKotTjdHbfe6+/4M8tt/DF96cIiln9RwWdu1pQ+piFZ55h9YWXYtxkXaS0SxlSx+1YWWeT1cONVNu/9TC3uD6SFcC4kormOlUEiMqNzQj9stJE8MoYs6breacP6Ln5Fq6lHoacIR+B7keBgtWlX5+cINW6rdADaLZUB0/79Raa3HGWeTLg0KBqBmMF3HDZWRxL0RfuhTE1VUsqS5sUHRnSm76hWrmoIkO9xZdEzjUlfNpiEzSNzOTMkEpEBcfV9ym2++ry96cfvUff7XdEzBQFH6j5cjPv5FOsuvBS+LwdHmyDItnT6XJqOrsXlcHrsfmmyPE3pHYRUeNY6UYvdn233cHFZx+RxiSZqDVd3oCDZihwjiztdCpA35Hkw2hmKi+/5u8YU6UVqndOzyucLS029aiU4KKno85flf1bacGWeX9WAGUAVEWAAnyAWaFv8xPcARPdpDTQJCI+kn0NynhfAurPBKoOkWho0s603QyYt5ZBKOauESts7O9vLWqg6rt99Q1AjfkXxFGaUpG/v5sjvfG3DrVybe9lhepFf196T21eFMBzxMFdpNf4b7CN4ke/UedHCYIbLpUqzXSunA+zWuk27YxcnuQb2XDJZaEgk3P+hMYl5d5Sq/5kzaE609edP6OYWTrxYmVoVTGo3jP5LH7zDxSRq0s6lFXt5Y+O5nttvYWrLzyRPlVy7OpTJbyut1aklb2YAqxIGaNgOSoXSTlIdR1hH90MHrt7Cz5UnzpTmhRY27WicNNJqE2V/dvA4bECKGOBVBGgiPV4J3tGn+8vHnNoteoq7r3+iqOW12HutAwwbwu03Qh8fAasrAQkTSFFF6dSLnHzX/sfiCSmhlLtYdp/j7DF3kUoOBSgQkl71W6aMeTNnBqnhtsazAZ+6tF7YZEgJocGVtNbWg1K8dFx3XWxLDt7VzYYfy5yrO+x5RYuPfso/P7+HVRVL9VdSAltsuyKSDCuZPBJfD4XNLZWK+1FcBVFn27vbaU6I9+AQHTbeBO3Xb8INwvyQS5qQIFou29KSb4pdyp9Ly7qYKkqow/efsLnkPxXKVCPgkNalzdcn+T4yKGmjyr7t5wBqtCXFUAZkFURIO93wKISQJJkwFTJWVduI0tBqSmnRC3aG+1DYPZfFym4ZOh94Mpi4Ox0oHAdoOtBuY/6bf+n772FxYSUiit/1YI+U1hE9DH7p1dl2BTVT8oIivhrsPiS2CT7VKd6r6UUXYO43Jwso3T0S0rFgJqFRZoOfTZKz0NRjIakJG+++grTjzwWgQbHhtLxq/6i2284e6Lzhhsi/YwaUexxkQVSvEhxf+DmhYJZ0+LggKrxzvMXl+f97hpKYP7HhhtiLOTqQZHThpAGZdOVV/jf0cdi6JQvkgJj9PESSpb2Ufvu47jjezGWobWLiBRGSkSxy11LOf1V2b/lDFCFvqwAyoCsigB9fgUsKwukSAtMdJcx2vCuLz9+R52FF4VD9KMJVZF0QREgyB/odxnY1wP4/BJotgyo0F0nz/vdTdqvvYabrz7rNS8gHQ2R/93zD9/RpnweLGyv34TM559+QM8tt0SOvcODbPRmbdOs26i9Djhw1034BpFlVOmo6NiELqKS3LNaAUxtpt+oVzrWbLbiighqMhSFS+PLSsE6e/pVQYX8+jvKI0W0/z93QH5mdLRIkeP6Vri++AQIhZR8bimdCjHKk0n5YJ2YZHvVhReYd9JJ/JpyIVKNZ30qXGTRnn/aKSw4hMrIUb5AfX/2Y/tu0Ob3quzf2gxID9eyAigDuioC9NEJWGkFpM4E/OUiY7ThXU84vsOAHXeFczE5i2N3F+DpUYCSSvt6AibpgVFPgZTKO5Hvvf0GY/c/EMoFRb+q/aUXsU4rFZmnMUSqiKIT4trfZOiue/jPwV0cJx4eXE1vqRkomXHn9TdEUMN+BRM+a0uIjlq7bbopxrWvn/58SOnloeXKqyIPH9WtJed5tWU4OnYk14N33cOxB+9gZpoSR4dUF2mN9NH+d+QxNl19JXxG6djeEPx9iQNZtCldj/MnHxTIkkZYArMrGGgR0zottnuOZWefi19TcNXwukUNQoZoPPT9POGgowjYoWTv67pWULUkI708/HvvrXBn0LU1VJX9Wx8fOC2eyQqgFrCiXqqKAGmSOVNJNlLKdNCW2j0XZZfaVsiDBVR+7MVZ4J8IwR7VRwN1JuvgSbHfgtLRVPrbTmS310cljO3XXDD58CNhbaOoTVsDSUlDQTKUjoaSLdORKx29qt0ocrLR0stw/uiDbtb58b8W5moP4bfPG7PPAfvuuKFQ1rQ4Pkw/lskZRx+LRMZUcuzkcFu9KVnRgfKhQIuVV0X+xMoFM2NH78qq1+Deau+Cqf89EsNb3qkcmlkaVnqad14/0G7NNbh9+YGi2dNhd98qqik4Uaug6OtzHtuHml4C+2+/A2+/QOF2QWmY1HBxIAV9xJ77uPLik1CKh9fVbSUdVfbv2ODq+fdGpQCuXLkS8+fPx/v372FpaYnly5fDysoqRoT79u3D5MmT4eLigqJFi2Lu3Llo3Lhx2PX0AZw6dSrWr1+Pr1+/olq1ali9erW4Ni5NFQF6cwvYWBfImB8Y/iAuw4r1mkE77uKY4ztMbFwSfWxD89ydnQHcWi/5/rVcDaRQLuVA1AFSxNvh++6qJ7Glo+fO66+Lt9vxjUqgXw31lazfLdb+O24Yvc9B+JVRQIjax2bLzz4XOcKoAsfZUTUMLjeYl+9P1Ft8UdRr1kcCZErVQaXeqG3sXhF1SprF+tlT+wJy92ix4iro2LyXTUFMbqqeTynlJqSAAgpoMOTSj5RsmVxR3nv7ieTmO/tUUVzWybJFAV/ky0ptarNS6KnDKii6ljOSI8pJSBH4VH94dpsyiuaaPPfUA2P2PRCVdMhVaVZrc50nyFdl/9b1Quj4fkajAO7ZswfdunXDmjVrULlyZSxZsgSk4Dk5OSF79l+Twtrb28PW1hazZ89G06ZNsXPnTqEA3r17F+bmkiWD/k2/37p1KwoWLCiURUdHRzx+/BipUsWuAKkiQK8uA1ubAlmLA4OlzUZuq7foovB3o4SoNYvrP6GuJoltDtNUsB9XW3Yd0LjwoTd/8vujgvFklVjWUb10FHEZH11DLyikYNAbsHWhLNjZp7JqR0Ounj6i3Jt/YDCWdiyLFmVzx3XYql6nyWdJD93UoyJql1BHCSMfsgZLLgnlkyozzGhpWNbRiItw8uF74YNHTamKG1EX/f6br+i07jp+UFWUinkxp00Z1WQ3PgJIVlI6DiaFg0rq0XejUq4g5DYwfPd9nHz0Xrgw/N2yjEhrZOiN0huRHNGLMzUKVCHFVZd+gRSAMufEE2y9JinGxc3SY3nncoqUDFVl/zbwRTUaBZCUvkqVKmHFihUCaXBwMPLmzYshQ4Zg3Lhxv2Du0KEDfHx8cPTo0bDfValSBWXLlhVKJG2uuXLlwqhRozB69GhxjZeXF8zMzLBlyxZ07Ngx1qVTRYBe2AH/tAFylAH6X4l1TLFdQMd6paecElava+NrQ5+Rt5qx0hdihRln4BMQJHKX0Rewki1iqS5K+UKlugwtX5pm/mSdqL/kojgiVys3IX02emy+JZLmViuSBRQVbQh+bTHJxPQjj7D5qos4hj0xrLriflwRy+GR7yr516U2UbZcoNzPg8aaS64OG7srW0nF5ZOPqNpCyhS5VJB11BjKiz155y0CQygPKK0ruYTouooLRdSTVfSWyxdR2o0CzgztWPx3skYZJJbYPcfKCy9EVR6K6KaXimo6KK9HhoAphx+JDAjUyKpPwTC6VDAjzk2V/VvuB1fh/kahAAYEBCBNmjTYv38/WrZsGYake/fu4uj28OHDv2DKly8fRo4cieHDh4f9jo57Dx06BAcHBzg7O6Nw4cK4d++eUAo1rUaNGuLfS5f+WgHD398f9KNpJECkhJLiaGqqu3x5/9vWGed+OqASCmB+tYHA7s5AnkpAbzvZ4qBJvUJm/AfT6hvMxj54510cffAO/WsUFh96JZsm/6CapbrkzGfdpZeYdfypOJY6M9IW2dPHbp2W8zwKHBi0867YoE4Or45C2ZQPBpIzXnqpabnSHrSBU+LcrT2tFLUi77jhion/PhR86OXBPHdoCUU5k1C4LymtFGxFPpNUCWNPX2tFosupWgwpfy6evjDPbYrdfa2RLmVyhWenu9tTRDdVKaFkyBQ0s75bRZ29kD5864UBO+6IMpOUiHpd14qwLmz4Jemio0vVXEbuvS8s4NRIodikcAAAIABJREFUiR1Rt2i8visc3byw6IwTzjt9FPeiqGwqD6j06RQrgIBRKIDu7u7InTs36FjX2to6TB7Hjh2Lixcv4saNG7/IqImJiTja7dSpU9jvVq1ahenTp8PDw0Pci3z+6N45c4bX123fvr1QiujIOWqbNm2a6B+16VoBnLi5Nf5L+hw1/LNgRdWhwP6eQH4boOcx2d90FFlKEaYU0XVgQFXZ99PVDTRKB0XjnR9dUzHFVFODlCwhVIfY0KptRMeT3rpbrrqKh2+90cQiJ1Z2Lq8r7L/ch4JyKPjEw9tfL+Xe4juxFx++oenyK8JSqqS/WcTnqFkrOr5cIvb7GRQsyj+SSwG9/FBQSOlculNe6Vic8g+SIp4nU2qhHCv9sqILLlHv8d7LTyiBFNlNyZDHNyoJSjcUXys4Kd+7br4BWarJpSJf5jRCsSyeQ3+5InXBjfIpLjjlJPwYyRpI36lUg7pDpbzCZSXpbxLp00vb2ScfsPvWG5E8nRqlLKLa60PrFFHlRIYVQFYAtVIA1bIATt3WEQdDHsHGLwNWVx4EHOqvs8TM9IFdcf4FOlnlxezWFrr4HtDJPShisdyMMyKXGlmdSuTQnUVVM0DamChlB30Jj65fDINrxy3YRycTlHkTsh5QRCc5j2/oVhF1Synj66Y5TiVFnKJalTp+kYkj2u5URWHcQUfF6vDSpkWVLB6rZGlUghEp+ORXSj56pATu7F0FpXLJ/6yR8tdlww3BhoKGKK9eYQO3HP+OL3Eii+mJh1IyZJsiWUWOR22t4eTCQZU9SOmmVqdEdixqXxYZ0qRQYnn1ck/6blp85hnOPv0Q9nxKqVW5YBaUzJkeOTKkFoq0/89gvP7si4fuXsKPkOoOUyM9kXyMqS60tnzlTJgVQCNRAA3lCDiqsCklQDN2dMPewHuo9iMd1lTsCxwdDhRvDHTaJUfeRd++227j9GMPg4w66731NuyeeCgS8k/Wj+YrrgrrRE3K19a9kqLHhLIXKpobzD7xBGsvOosjEspXqGu/M/oib77iioja3Pan4aTEiStLsrSMP+gorAp0XP7f4Go6LWg/6ZAj/rn+WpQQO6mCr2Fc563tdWS5ISXQ4c1XcRRJtWbl+HC5f/0hLIuUVJmUv919K6uSJkTbeWt7PcnTtmuu+Pv4E/FiSkf+FKxB0dSx+Qa++eyLdZecsfvWa1HTlyL5R9cvLvr+zjKm7RgN6Xr6/th187XIX/rNLzDWoVF+Skq8TxbD/Fl0U+M+1odGuECp/VubMej7WqM4AiZIFARCKV8o9Qs1CgIhP7/BgwfHGATi6+uLI0eOhDGuWrUqLCwsIgWBUAAIBYJQI4GgiGJ9B4HM3tMbO/1uoMqP1FhfrhdwYixQuhXQbotseak5/7zwzzGkOqqaSWmSQlMqBqo4ocu28vwLzD/lJKwepDzRRmVsjcpp1VsklYmjt+VR9YvrbApkWWy92l4oBU0tcmKFgsfMOht0NDciK12HtdeFhYsCfPYPqKoTHzSNbFLUJr081Cqh/+h5ORwp0KHXlluiJi4dvU1vURqdrfJpfcxJnOmlknzByGeOvlcMqbauHEaavhQRT8EJFBRFjSxWVgUzo3aJ7CiVMwOypjdB0iRJ8MHbX1i3Ljh9wHXn8LKd5JdKOTQpYCIxNPoMOrzxwi2Xz3j1yQd0pB4cEiICgcg1gCzDVQplEZ9PfSrDrAAaiQWQPjTkk0dBH2vXrhWKIKWB2bt3L54+fSoidylFDPkJUloXauTjRwEdc+bMQZMmTbB7927MmjXrlzQw9PuIaWAePHig9zQw8w8Mwrbvl1DZ1wQbLLoBZ6YAFh2B1mux88Zr/HPdVUSPlcyp3dENhdiXmnpS+GvcmljXoJLW0pqRAzklhSYLFNUG1lVpJnobr7PooniLX9jOEm0qGG9xc01KD7JGnBphq7NNhWRq0qGHIseX3agaMFO5IoIuN0bacMgfkJJpUxQzVedImTz+UbqkFLdbe03Iz8h6xTC0jvG4DvyOK0XD/3XggcjBSa1+KTPMal0mTi9H5Je69pKzOPqjjAKUrmNTz0rCOp0QG1kDr77wxJqLL8OOc383T3pRqFY4KwbWKoyqhfVTVzwhroMu58QKoBEpgLTwlAJGkwiaInWXLVsmLIPUatasiQIFCgjrnaZRnsBJkyaFJYKeN29etImg161bJ6KJbWxsQIEixYrFLeO4UgK09PAobPh6Gla+ybCxVBfg/EygfHeg+TIUHH9MKHBVCmUWEXbaNDLR08ZIR1h3JtXV+m1fm2fF91pNbWBdJkbVJJquWjiLcHyPrzN3fOeky34RU7RQio2tPeWXHqOM+7UXXhDHNtOalUIPA05IG1eWD9ykPHSUWqhJmZxY1qlcvEpJUUqTtmvsRb7IuiXNRCksfVot4jr/uF5H8kRHlQtOO4mjSorY7VO9kDjqjK50HLlS2D32EAnCKXceNeJLiYFNUyUcv7bf8aMXylOP3gs/NmJA1tSgkBBkS5dSvJCRdbCheQ6dvcDGdS35Ou0IKLV/azcK/V5tNEfA+sUU/dOVEqBVxydg9ccjqOCbBFuKtQMuLwCs+iKwwVwUmXhCDIbetK+Oq60VlgN33DBqn4MoC7Wnn3bKo1YPknGxpog9RZHt6ltFxp2krpRioNkKKX/i0SE2RpGyI7ZJ07FKg8WXEBAUjDV/lEdD8/Ao9tj6Rvd7KrdE9TYpbcfhQTbxUpTi81yl+1Cqip5bbgrFpmXZXJjfzlKrfHQe3n5C+aO0HVSTmQIb0idQJeeRuxfGHXCE41svsSx0LEyKjGXejMIi+CMgUCg7V154CssqNXKnmNC4JNpVyGPUL1VKyyHf3zAJKLV/G+Zsox8VK4AyVkspAdpwZgaWuu9Fed8QbC3cErBfDlQdgo/Wk8URKbXs6VPi5sS6Wo1eE0RgiHVdNROhqDnb+eeFEnJ7Yl1kSmui1RyjXtxt002RZoCKiS/uEJ7vUdZNDaDzwtNOWH7uBXJlSCWObOObyNr+xSeRuoOOrA4NrCY2/ITUjju+E2mP6JiSfLaoqklclDjnj99BskM1YvNnSYP9/asanMuErtcpODgERx3fYdOVV8KHMqZGEZ4dK+UTZSQp2IYbEzBGAkrt38bEghVAGaullAD9c3EB5rpsRTnfYGzL10iq0Ws7Bk9LDUXDJZfFiMkHzGlmQ63evHtuvimSbVLZKipfZait4ZJLIgeXXH89zZE3OW1fGF0L+bKkMdQpaz0u8uekOrikoAysWRhjG2qfPJvqwxJruscfVfJhZssyWo/DGDqcf/pBJOClHIGU3mZ5p/K/TYJMx3vkG/fV96c40qOI6NiiPo2BgzZjJGvfjVeeImqeOFDy6FwZU6Ni/syoXCizVpZUbZ7L1zIBtQgotX+rNX5dPIcVQBkUlRKgfddW4n/P1qDsj0Bsy1ETSe7vBOpOwxWzrvhjY3jSa4cp9bXKJ1VtzjkRQbq3n7U43jHUtujMMyw7+xwNSpthbdeK8R6mprpIi7K5sLRjuXjfx1A7nnnsIcpKUY4tipouZqZdYllKmUJpGygyj3L+GVPFBm3X5N7rLxi04y7cvfyEtZPST5AlvEzuDOIliqxfd15/wZoLL8PymZE1lMqYGWPEuLZ8+HomkNgIKLV/GxNHVgBlrJZSAnTk7mZMcFwEix8/sS2TFZI9OQw0mo/DKZtg2O77YSOmdCZFssetTBclNi0z7bToe39KPcUKncvAGdZVY7lLlSIp7k2uH698d+S8T4ENFFFM9WG1jZjWxTyUvgc58JMCaPfkg5jfoUFV4xztSlaxnltuiSHu6lPFaEtSacOY6rBSOg/KU6ZpFPWcJZ0JKBCGAkaokftBb5uCIs2OSfKk2jyCr2UCTMBICCi1fxvJ9MUwWQGUsVpKCZDdoz0YcXsmzP0CsC1VaaR4dRZosQpbf1TD1P8ehY14d98qIp9SdI186eafdkLNYtlE2pMbzp7osO668BmzH19HxqyV70qKjc3c88JaSSWT6sWj6gVl36eUObWKZ8PmnlbKD1pPT/jwzQ+NllyGp0+ASDI7uWmpWEdCskGBMRS9SCWupjYrHWufhHTBHdcv2GrvIiI5qSqMppEFlKI3B9QsbNRVLBLSWvFcmIBSBJTav5UarxL3ZQVQBlWlBOjS8yMYZD8Bpf39sTVJQaR8e10kgV71sQzmnXQKGzGlpKhfOke0M6BalhecPorjruNDq+Pqi0+YeeyJUKZIqTL0Nu2/R9hi7yIiDCl6U5v2wdtPKJAUJWvox93azCuma88+8UCvrbfFrxd3sESrcjHnOaQqEO3XXBM+lnTEubdflThbDXUxVkO6B6U0cf7oA7KOUzBDgaxp2bfNkBaIx8IEFCSg1P6t4JB1fmtWAGUgVUqA7F3OoN/FkSjuH4AdP0yR8sszoMt+LHDOJ+r4alpMQRKU4NVi+mmRuJZa6/K5Re5ASvVhLIlsNdGpmdKkEEmrkyeL+1HcnBNPRcLW8vky4sCAqloFysgQB7121UR4kz/g2q4VULvEr7WCSdHpvukm7r7+CorkPDLEBjkzJMzEvXpdDH44E2ACBk9Aqf3b4CceYYCsAMpYLaUE6Mbba+ht1xdFAgKw/6MvkgV4Az2OY7pjRmy+6hI24piS9t5x/Yw2q6+FXUcRw0gCoRBu/dMKNYplkzFrdbqSdabiTDtxTEnJm+Naq5SUnKpzzomkxr+zkKozC/WeQkEMQ3ffw9EH74QPG9Ud7VO9YJjiTNUsRu69j5cffYS1a2efyiidK4N6A+QnMQEmwAQMiIBS+7cBTTHWobACGCuimC9QSoDueNxBj5M9UCDgJ468fScNoO8F/GWfDHtuvwkb0Kh6xTAkmrJU+++4YfQ+B9gUySqOtxzcpOSuFFRxf0p9pEoR/7JYMnBp3VXjx0dJfJfEMYp3/SVnUby9ULa0sBtRI0FVbYgNICnNlL7k4N234lIqtl42b0YR4EBWP2o5TFNhQ/eKCSIhdmw8+PdMgAkwgZgIKLV/GxNxVgBlrJZSAnT/w310PdEVeX7+xAm3UAVw8G0MOfMdRxzcRZZ+Smzbz7YQxjcu+csMqD7n0rPP0ckqLyoVyIyRex3ENfTv2a0tZMxY3a6UjLblyqtImTypSHodW9JZsnDWmH8e77z8MLdNGXSolE/dARvA0yiAZt8dN8w98VQEhmga+YJSMmyq3MBpTQxgoXgITIAJ6JWAUvu3Xiel5cNZAdQSWMTLlRKgh58eotOxTsgZGIjTb0JTVox4jF7/uoscZVQGjiJkO1nlw+zWvybvHbXXAQfuumFMg+LoX6MwVp5/Ac/v/hhZv3isSpQMHDrvSspMgyWX8MzjO2a0KI2u1gV++wxNqTuqYXrlr1qJNriBIPkHBsH+pSdcP/nANHUKES1OiXy5MQEmwASYAKDU/m1MbFkBlLFaSgnQ089P0e5IO2QPDMRZjQI47jU6bnuM686fRXADHek1tciJFZ3L/zKD9muviULlVPaqRdncMmao/64br7zCjKOPUShrWpwZWSPGOrWBQcGov/gSnD/5CMV3UK0i+h88j4AJMAEmwAQMkoBS+7dBTjaGQbECKGO1lBKg51+eo/V/rZE5KAgXX78FkiYHJn9C85VX8cDNC03K5MQxx3cimIOCOqI2TcWPgwOrony+TDJmqP+uVK6s6uyz8PYLxJo/yqOhec5oB7X75muMO+iIzGlNcGlsrQRd1UL/q8IjYAJMgAkYNwGl9m9josIKoIzVUkqAnL2c0eJQC5gGBeEqKYBpswNjnqPOwgsiivPPagWx6eorYQk8OLBapBnQsWmxSSfwMygE9uNqJ4hjvwWnnET6m2Jm6UTJsxRRUsKQklh34UW89/bDpCYl0bt6IRmryl2ZABNgAkwgoRNQav82Jm6sAMpYLaUE6I33GzT+tzHSBgfjuqsbYJobGPkYGsveuEYlQLnuimZPJ45FIzZShsynnhL/9eR/DeNVRk0GEkW6UgmvWgsu4Ivvz2gVvCmHH2LbNVdR05bK4xlLlLMisPimTIAJMAEmECsBpfbvWB9sQBewAihjMZQSIPfv7mhwoAFSBQfjFimA2UsBA6+h4swz+PQ9AAvaWYo0L5TS4/qEyGXd3L74iioYFDnrNLORjNkZVtddN19j/EFHUZt1Xz9rUcWC2rEH7zBo513x9396VYZN0ayGNXAeDRNgAkyACRgcAaX2b4Ob6G8GxAqgjNVSSoA8fDxQd39dJAlJAnu3b0jXZStQ0BZlpp7CN/9AbOlZCT0230Jak2R49L+GkWbw8K0Xmi6/InLA3ZhQV8bsDKsrJTruu/027J58EP59w+oUBZU1W33hpUiJkxhr2hrWCvFomAATYALGQ0Cp/dt4CACsAMpYLaUEyPOHJ2rurSlG1jT9jrDcfUUnHhe+fUeH2Aglj9rLWY0jRcZefv4RXTfeRIkc6XFyuK2M2RleV0pq3WfbbREJHbFRouiF7cvGGCFseDPhETEBJsAEmIA+CSi1f+tzTto+mxVAbYlFuF4pAfLy94LNbhvxpLqptmJxh/IICg5B4QnHxf9dH18HVWafFX9/MK0+TFOlCBvVfw7uGLrrHqoUyozdfa1lzM4wu1K1ix3XXUU+RDrmbmaZC80tcyWKer+GuSI8KibABJiA8RFQav82JhKsAMpYLaUE6HvAd1jvkpQ3m+TrsbpLFfwICELJKSfF/z2a3gDlZpwRtX2vjqstEkNr2rZrLphy+BEamefA6j8qyJgdd2UCTIAJMAEmkDAJKLV/GxMtVgBlrJZSAvQj8Aesdkj5/SpiNTZ3t8EXnwCh9FF78XcjVJ51VpT6OjXcFsVzpA+bxVK751hs9yzGKiEypstdmQATYAJMgAkkCAJK7d/GBIcVQBmrpZQA/Qz+ifLbpQof5oHLsKtXLbz38hPHvlQH+MWsxqLmraunLw4MsEaF/JnDZjH9yCNsvuqCgTULY2zDEjJmx12ZABNgAkyACSRMAkrt38ZEixVAGaullAAFhwTDcpulGFnRHwtxsH99uHr6oMb8C2GRv02XX8bDt97Y3LMSahXPHjaLEXvu4997bzGhcQn0tS0sY3bclQkwASbABJhAwiSg1P5tTLRYAZSxWkoKkMVWS4QgGPm+z8GxQU3g9P4bGiy5JEqd3Z1cDx3XXRPRsMs7lROBEJrWY/NNXHD6iHltLdC+Yl4Zs+OuTIAJMAEmwAQSJgEl929jIcYKoIyVUlKAym0rj8CQnzD7OhN2w1rggdtXNF9xFbkypIL9+DrovZVy4nlgdusywt9P01qsvAqHN1+xvltF1CtlJmN23JUJMAEmwASYQMIkoOT+bSzEWAGUsVJKClDF7VbwD/6BjJ+m4vKotrjl8hnt1lxDwaxpcX50TYzccx8Hoznq1fgG7u9vjYoFwn0DZUyTuzIBJsAEmAATSFAElNy/jQUUK4AyVkpJAaq8wxq+gd+RxmMCbozthKgJnjX1b4fWLoKR9YuHzcJi2il4+wWKmrhFsqeTMTvuygSYABNgAkwgYRJQcv82FmKsAMpYKSUFqNrO6vD++RXJ3cfi3viusHvsgd7bbsMyTwYcHmyDeSefYtWFl5FKoAUGBaPIxBNiRncm1UWWdCllzI67MgEmwASYABNImASU3L+NhRgrgDJWSkkBst1dE1/8PRH0ZgQeT/oTxx68w6Cdd2FVMDP29rPGqgsvMO+kE9pWyIMF7aSI4c8+ASgfIVdg8mRJZcyOuzIBJsAEmAATSJgElNy/jYUYK4AyVkpJAaq1tw4+/fgAf9cheDalLw7cccOofQ6oXjQrtveqjO3XXTH50EM0LJ0Da7pKFT9efvyOOgsvIn2q5HCc1kDGzLgrE2ACTIAJMIGES0DJ/dtYqLECKGOllBSgevsa4L2vO3xeDcSLKf2x+9YbTPjXEXVLmmFD94o4dO8thu+5D5siWfFP78piFndcP6PN6mvIlzkNLo2tJWNm3JUJMAEmwASYQMIloOT+bSzUWAGUsVJKClDjA03w5vtr+Lr0x6MJ/bHr5mtMP/IYTS1yYkXn8r/4BNI0ovoJypgad2UCTIAJMAEmkGAJKLl/Gws0VgBlrJSSAtT83xZ45e0MX9e+uDe2P3Zcf425J5+iTfk8WNjeEjecPdFh3XUUypYW50bVFLPYd/sNxux/gBrFsmHrn1ItYW5MgAkwASbABJhAZAJK7t/GwpoVQBkrpaQAtT7cGs+/Poevay/cHDlA+PwtsXuOzpXzYVarMnjk7oUmy64ge/qUuDmxrpjF+kvO+Pv4E7QsmwtLOpaTMTPuygSYABNgAkwg4RJQcv82FmqsAMpYKSUFqP2R9njy+Ql8X/fElaEDsO2aK1ZHSPvy2tMXtvPPI3WKZHgyo6GYxfxTT7Hy/Ev0qFoA05qXljEz7soEmAATYAJMIOESUHL/NhZqrADKWCklBajzsc5w/OQI3zfdcW7AAGy1d8Wmq6/Qv0ZhjGtUAl98AlAuSsoXChLZeeM1htctiuF1i8mYGXdlAkyACTABJpBwCSi5fxsLtTgrgK9evcLly5fh6uoKX19fZMuWDeXKlYO1tTVSpUplLPPV6TiVFKCux7vi/sf7+OH2B070Hogt9i7YceM1htUpihH1iiEgMBjFJklJnx2m1EeGNCkwcMcdHHd8j+nNS6N71QI6nSvfjAkwASbABJhAQiGg5P5tLIxiVQB37NiBpUuX4vbt2zAzM0OuXLmQOnVqfP78GS9fvhTKX5cuXfDXX38hf/78xjJvnYxTSQHqebInbnvcxg+3zjjUQ1IA999xw9iGxTGwZhEx/uKTTsA/MBhX/qqFPJnSoNO667jm7ImlHcuiRdncOpkj34QJMAEmwASYQEIjoOT+bSysfqsAkoXPxMQE3bt3R7NmzZA3b95I8/L398e1a9ewe/duHDhwAKtWrUK7du2MZe6yx6mkAPU+3Rs33t3Aj7cdse+Pgdh81QX/ObhjctNS6GVTUIy94swz+PQ9ACeGVUfJnKZouOQSnr7/hm1/WsG2WDbZ8+MbMAEmwASYABNIiASU3L+NhddvFcBTp06hQYO4VZTw9PSEi4sLKlSQqlIkhqakAPU/0x9X3a/ih3s77OgwSPj/nXrkgZktzfFHFcnSWmvBBbz65IN9/a1RqUBmVJl1Fu+9/XBksA3K5MmQGJaA58gEmAATYAJMQGsCSu7fWg9GTx1iPQKmo97MmTPraXiG/VglBWjQ2UG45HYJP9zbYHPbQdh45RUuOH3EvLYWaF9RssQ2X3EFD9y8sLF7RdQukR0lJp8UR8KXx9ZC3sxpDBsej44JMAEmwASYgJ4IKLl/62lKWj82VgWQfPxatmyJXr16oV69elo/ICF3UFKAhp0bhnNvzsHvXSusaTEIGy6/+sW/r9umm7j07CPmt7VA4zI5UXrqKYH78f8aII1J8oSMnufGBJgAE2ACTCDeBJTcv+M9KJU7xqoAbt++HVu2bMGFCxeED2CPHj3ET4ECHGWqpACNvDASZ1zPwO99CyxrPAgbrrzCHdcvWPNHBTQ0zyHEZMSe+/j33ltMaFwCjcxzovq8yHkBVZYlfhwTYAJMgAkwAaMgoOT+bRQAAMSqAGomQmlgSBHctm0b3rx5g1q1aqF3795o1aqVCBRJjE1JARp7cSxOuJyA3/umWNBgMP7P3nmAVXF0YfjDblTQ2Av2qKixFxQVFAtYUbC3aKyJGmvU2GvssQVjjAVFsTcUBXvBXrFiC/beG4ro/5whe39A4O5l7y574UweHtru7DnvTpyPmTnnLDhwA+fvvsLiThVRs2g2gXus70VDbsB6JbKjqech5M6YFoFDaiXF18E+MwEmwASYABOQRUDN+VuWATq4SLYAjGzrzp07sXjxYmzcuNGQBmb27Nk6cEdbE9QcQL8d+A2+N3wR+rA+Jtbqhb/338DVR2+womtlVC2URTj6555rmOofjBYV8qBu8RzosvQESuexwaZe1bQFwU9jAkyACTABJmBBBNScvy0FQ7wEoOQcpX7p1q0bXrx4gfDwcEvx2Wx2qjmARgSOwMZrG/HhkQtG1eiF+ftu4Nazd1jXswrK54sIyqGqH1T9o7ZddtQtnh2/rgtCzaJZsbhTJbP5yB0xASbABJgAE0hsBNScvy2FlckCkCqB0Oqfl5eXYSuYAkRatWplKT6bzU41B9DoQ6Ox7uo6fHhUB0Or9sZf+67j4asP2NK7Gkrmjkjxsv38A/TwPolyeTOidvHsmLI9GB7l82Ba89Jm85E7YgJMgAkwASaQ2AioOX9bCitZApASPtNq36JFi0QwSO7cuUUgSKdOnZJ0MIiaA2j8kfFYFbwKHx47Y0DFCAH4/F0YdvSrge+yZxDj69i/z9Bi/mEUyJIOzsWyiUCR7jUKYmh9O0sZf2wnE2ACTIAJMAHNCag5f2vuTDwfaFQA/vTTT6LSB9X/bdKkiSEdjJWVVTwfmXhuU3MATTo2CcsvLceHJzXRp2xveO69jncfw7F/UE3kzRyR4+/aozeoPWMfrNOkEHkAN565JyKCu9UolHggsydMgAkwASbABMxMQM3528ymqtadUQFYqlQpIfratWuHzJkzq2aIJXas5gCaenwqll5cig9PHNHj+974c+91hH/+gqO/OSO7dRqB63VoGL4fHSC+LpnbWkQJz2ldFo1K57JEnGwzE2ACTIAJMAFNCKg5f2vigBkeYlQAmuEZibYLNQfQjJMzsPj8Ynx8Wg0divbGggP/Co6nR9RBpnT/T7tTarQ/XoV+MjBe17MqyufLlGiZs2NMgAkwASbABJQSUHP+VmqbVvfHKQAnTZqEX375BWnTpjVqz9GjR/HkyRM0aNDA6LWJ5QI1B9DsU7Ox4NwCfHxWFU3z/oyVx28LbNGrfLjOOoBL918ZkEZeIUwsnNkPJsAEmAATYALmJKD7cEkDAAAgAElEQVTm/G1OO9XsK04B2KFDB2zbtg3NmzdHo0aNUKFCBWTNmlXY8+nTJ1y8eBEHDx6Et7c37t27J5JE16hRQ017ddW3mgPI84wn5p2dh4/P7FE7e09sDbovfL82wRUpkiczcOi69AR2XHwovk+dIhkujXVBsmR8PlNXA4WNYQJMgAkwAV0RUHP+1pWjcRhjdAv47NmzmDt3LtauXQsCljx5cqROnVoEhVArW7asqAhCUcFUN9jc7dmzZ+jduzd8fX2RLFkyuLu7Y9asWUifPn2sjwoNDcWAAQNE8ApFMNerVw+enp7Inj27uId8otVNEq+0akll7Xr06CFWO01pag6g+WfnY+6Zufj4vBIqW3cXNX9TJLPCtYn1o5g4c+cVzNx5VfyM0sGs/8nBFBf4WibABJgAE2ACSY6AmvO3pcA0KgAlRz5//oygoCBQHsD3798jS5YsKFOmjPisZnN1dcX9+/cxf/58hIWFidQzFStWxIoVK2J9bM+ePbF161ZRus7Gxga9evUS4jEwMFDcQ+lsSAQ2a9ZM1Dc+dOiQSGg9ZcoUca3cpuYAWnhuIWaemomwF+VRPGVXnLr1AulSJceFsS5RzDtw9THaLzwmftbJIT9GNSoh13y+jgkwASbABJhAkiSg5vxtKUBlC8CEcOjSpUsoXrw4jh8/LrafqW3fvh3169fHnTt3kCvX19GuL1++FNvUJBA9PDzEPZcvX4adnR0OHz4Me3v7GF35+eefQc/bvXu3bFfVHEBeF7ww7cQ0hL0oC9vwH0UZuEzfpMTpkXWj2Pfx02e4zzuEkKdvQQEgRf7LESjbCb6QCTABJsAEmEASI6Dm/G0pKHUtAGmljrZynz9/buBJZw9pq3nNmjVo2rTpV5xJwDk7O4t7MmbMaPh9vnz50LdvX/Tr1y/Gd0NpbmjrmLa6Y2u0nUwfUqMBRCuIJDqtra3N+s69L3pj8vHJCHtZGhnfdMKDV6HIYZ0GR35z/uo5X758ESliIp8NNKsx3BkTYAJMgAkwgUREgAUgoGsBOHHiRFFyLjg4OMqwy5YtG8aMGQPa6o3eaOWPtokjCzW6plKlSqhZsyYmT5781T20Bezo6Ci2jevWjbrCFvni0aNHi+dGb2oIwJWXV2LC0QkIe/U9UjzpiDcfPiFf5m+wb1DNRPS/ILvCBJgAE2ACTEB7AiwAE0gADhkyJEYhFnkI0Hbs+vXrVReA58+fF8KQAkCGDx8e5yjUcgVwzZU1GHt4LMJeF0fonQ7CriLZ0yOgn6P2/6fwE5kAE2ACTIAJJCICLAATSAA+fvwYT58+jXMoFSxYUKSXUXMLmNLYkPijKOYJEyaYPLTVHEAbrm7AyEMj8el1Mby/84Ow7fvcNvDtXc1kO/kGJsAEmAATYAJM4P8E1Jy/LYWz7C3gzp07i/QrGTJkiOLb27dvRZoWOq9n7iYFgZw4cQLly5cX3QcEBMDFxcVoEIiPj49IGUONtpCLFSsWJQjkwoULqFWrFjp27Ciif+PT1BxAm69vxrCDw/DpTRG8v91ZmEcVPijQgxsTYAJMgAkwASYQfwJqzt/xt0rbO2ULQMr/R+lY6Pxd5EZ59HLkyCESQ6vRKA3Mw4cP8ddffxnSwFBEsJQG5u7duyLog5JQ0zk/anQ20M/PT6SBoeAMEqjU6KwfNdr2JfFH+QGnTp1qMJt8lBJdy/FFzQHkd8MPgw8Mxqe3hfH+VhdhTtVCmbGia8xRzHLs5WuYABNgAkyACTABiLzGlCZOjTP8lsLXqAAkSBRlmilTJly9ejWKQAoPDxcJmulMH1UCUaNRImjKzRc5EfTs2bMNiaBDQkJQoEAB7NmzB05OTsIEKRE0rQJGTgRNQpVabMEcFClM/cltag4g/xB/DNw3EJ/eFsD7W92FSTWLZsXiThEilxsTYAJMgAkwASYQPwJqzt/xs0j7u4wKQEqgbGUVe2kx+h1Fxg4bNkx76xP4iWoOoF03d6Hv3r4If5cP725GRDu7lMiBv9pHbIVzYwJMgAkwASbABOJHQM35O34WaX+XUQG4b98+sQJIW6br1q3Dt99+a7AyVapUoFWzmBIya++K9k9UcwDtu70PvXb3Qvh7W7wL+Vk417h0LsxuXVZ7R/mJTIAJMAEmwAQSEQE1529LwWRUAEqOUAm4vHnzxrkaaClOm8tONQfQwbsH0XNnT4S/z413IRFnGFtXssXvzUqZy3zuhwkwASbABJhAkiSg5vxtKUBlC8D9+/fH6VONGjUsxWez2anmADp87zC67eiG8NAcePdvX2FzZ4cCGNmouNns546YABNgAkyACSRFAmrO35bCU7YApLOA0Vvks4EUEJLUmpoD6PiD4+js3xnhH7Lh3Y3+Am2vmoUxsF7RpIaZ/WUCTIAJMAEmYFYCas7fZjVUxc5kC0AKlY7cwsLCcPr0aYwYMUIkUaZULEmtqTmATj86jQ7bOuDzhyx4e2OgQPurS1H85FQ4qWFmf5kAE2ACTIAJmJWAmvO3WQ1VsTPZAjA2GyhIpH///jh58qSKZuqzazUHUNDjILT1a4vPHzPh7fXBAsDoRsXxg0MBfcJgq5gAE2ACTIAJWAgBNedvC0EAxQLw8uXLoMTMb968sRSfzWanmgPowtMLaLWlFT6H2eDttaHC5inupdCioq3Z7OeOmAATYAJMgAkkRQJqzt+WwlO2AAwKCoriE6WGocogkyZNElVADh48aCk+m81ONQdQ8LNgePh64MunDHhzNSLH4pzWZdGodC6z2c8dMQEmwASYABNIigTUnL8thadsASglhCbhF7nZ29uLOsBUazepNTUH0PUX1+G2yQ0IT4fXV0YItIt+qIBaxbInNczsLxNgAkyACTABsxJQc/42q6EqdiZbAFIewMiNBCHVzU2TJo2K5um7azUHUMjLEDTa2AhWn9PiVfAoAcKnqz2qFMqsbyhsHRNgAkyACTABnRNQc/7WuesG82QLQEtxSEs71RxAd17fget6V1h9SY1Xl8cItzb97IDSthm1dJGfxQSYABNgAkwg0RFQc/62FFgmCcBdu3bhjz/+wKVLl4R/dnZ26Nu3L2rXrm0p/prVTjUH0IO3D1BnbR1YfUmBV5fHC7v3DXJCvszpzOoDd8YEmAATYAJMIKkRUHP+thSWsgWgp6cnfvnlF3h4eKBKlSrCvyNHjmDt2rVCFP78c0S92qTU1BxAj989Rq01tYAvVnh9+XeBNWh0XVinSZmUELOvTIAJMAEmwATMTkDN+dvsxqrUoWwBmCdPHgwZMgS9evWKYsqff/6JiRMn4u7duyqZqN9u1RxAz0Ofo8aqiPJ6ry9NBJAM//5en2sx63c4sGVMgAkwASZgIQTUnL8tBIH8PIDp06fHmTNnULhw1EoUV69eRdmyZTkPoLW1Wd/5q4+v4ODj8J8AnAAgOUImNTDrM7gzJsAEmAATYAJJkQALQMgXgG3atBFCb9CgQVHGyrRp03DixAmsXLkyyY0hNQfQu7B3qLyismBa9rMnmpcrxDkAk9wIY4eZABNgAkxADQJqzt9q2KtGn7K3gMePHw8Sew4ODlHOAAYGBmLAgAGwjrQC1qdPHzVs1V2fag6gD+EfUMG7gvD5cOvDSJ8qve78Z4OYABNgAkyACVgiATXnb0vhIVsAFiggrwatlZUVbty4YSn+K7JTzQEU/jkcZZaVEfYdbHUQNqltFNnKNzMBJsAEmAATYAIRBNScvy2FsWwBaCkOaWmnmgOIKq6UWlpKuLO3xV5kTssJoLV8t/wsJsAEmAATSLwE1Jy/LYWabAE4duxYDBw4EN98800U396/f4+pU6di5MiRluKz2exUewCVXVoWn758wk6PnciejkvAme3FcUdMgAkwASaQpAmoPX9bAlzZAjB58uS4f/8+smXLFsWvp0+fip+Fh4dbgr9mtVHtAVTRuyJCw0Ph7+6PXOlzmdV27owJMAEmwASYQFIloPb8bQlcZQtAqv378OFDUf83ctu9ezdatmyJx48fW4K/ZrVR7QFkv8Ieb8Pewq+pH2ytbc1qO3fGBJgAE2ACTCCpElB7/rYErkYFYKZMmUTy4ZcvX4pIX/paarTq9+bNG/To0QOUEDqpNbUHEOUBpHyAm9w2oaBNwaSGl/1lAkyACTABJqAKAbXnb1WMNnOnRgWgl5cXKCChc+fOmDlzJmxs/h+NmipVKuTPn9+QFsbMtum+O7UHkOMqRzwLfYb1jdfju0zf6Z4HG8gEmAATYAJMwBIIqD1/WwIDowJQcmLfvn2oWrUqUqbkWrQSE7UHkPNqZzx6/whrGq1BsW+LWcJ4YhuZABNgAkyACeiegNrzt+4BwIRKILdu3YrTn7x581qCv2a1Ue0BVHdtXdx/ex8+DXxQMktJs9rOnTEBJsAEmAATSKoE1J6/LYGr7BVACgKJfP4vunMcBWzeWsDE13WdK+68uYNlrstQJltEUmhuTIAJMAEmwASYgDICLABNWAE8e/ZsFNphYWE4ffo0ZsyYgQkTJqBZs2bK3oYF3q32AGq0oRFCXoVgicsSlM9e3gIJsclMgAkwASbABPRHQO35W38ef22R7BXA2JzZunWrSAS9d+9eS/DXrDaqPYCabmqKay+u4Z+6/6ByzspmtZ07YwJMgAkwASaQVAmoPX9bAlfFAvDatWsoXbo03r59awn+mtVGtQeQx2YPBD8Pxvza81E1d1Wz2s6dMQEmwASYABNIqgTUnr8tgatsAUiwIjdKDUOVQUaPHo3Lly/jzJkzluCvWW1UewC12tIKF55ewJ/Of6JGnhpmtZ07YwJMgAkwASaQVAmoPX9bAlfZAjCmIBASgba2tli5cmWSzAWo9gBq69cWQY+DMLvmbNTMW9MSxhPbyASYABNgAkxA9wTUnr91D8CUNDCUBzByI0FIZeEKFy6MFClSWIKvZrdR7QHUcVtHnHp0CjOcZqBOvjpmt587ZAJMgAkwASaQFAmoPX9bAlPZK4CW4IzWNqo9gH70/xHHHhzD1BpT4VLARWv3+HlMgAkwASbABBIlAbXnb0uAJlsArlmzBj4+Prhy5Yrwq0iRImjTpg08PDwswU9VbFR7AHUL6IbD9w/j9+q/o2HBhqr4wJ0yASbABJgAE0hqBNSevy2Bp1EB+PnzZ7Ru3RokAEn0FSsWUZLs0qVLoAjg5s2bC2EYV5JoSwARHxvVHkA9d/bEwbsHMc5hHNwKu8XHRL6HCTABJsAEmAATiEZA7fnbEoAbFYB//PEHxo8fDy8vLzRsGHUVavPmzejUqRNGjBiBvn37WoK/ZrVR7QHUe1dv7L2zF6OrjIZ7EXez2s6dMQEmwASYABNIqgTUnr8tgatRAViqVCkh7jp37hyjPwsXLsSsWbMQFBRkCf6a1Ua1B1C/Pf2w89ZOjLAfgRZFW5jVdu6MCTABJsAEmEBSJaD2/G0JXI0KwLRp0yI4OBh58+aN0Z+bN2+KbeH3799bgr9mtVHtATRw30D4h/hjSKUhaGvX1qy2c2dMgAkwASbABJIqAbXnb0vgalQAfvvtt6LMG60ExtTOnTuHGjVq4Pnz55bgr1ltVHsADd4/GH7/+mFQhUHoUKKDWW3nzpgAE2ACTIAJJFUCas/flsDVqABs0KCBWP2bN29ejP706NEDt27dgp+fnyX4a1Yb1R5Aww4Ow+brm9G/fH90KtnJrLZzZ0yACTABJsAEkioBtedvS+BqVAAeOnQITk5OcHNzw8CBA8V2L1UAoSjg6dOnY9OmTdizZw8cHBwswV+z2qj2ABp1aBTWX12PX8r9gi7fdzGr7dwZE2ACTIAJMIGkSkDt+dsSuBoVgOTEhg0b0K1bNzx79iyKT5kyZcL8+fPh7p40I1TVHkBjD4/Fmitr8FOZn9CzdE9LGE9sIxNgAkyACTAB3RNQe/7WPQBTSsG9e/cO/v7+uHr1qvCLcgLWrVsX33zzjSX4qYqNag+giUcnwueyD7qX6o5eZXup4gN3ygSYABNgAkwgqRFQe/62BJ6yVgAtwZGEsFHtATT52GR4X/IW27+0DcyNCTABJsAEmAATUE5A7flbuYXq98ACUAFjtQfQ9BPTseTCEvxQ4gcMqDBAgaV8KxNgAkyACTABJiARUHv+tgTSLAAVvCW1B9DMkzOx8PxCtLNrh8GVBiuwlG9lAkyACTABJsAEWAD+fwywAFTw/4PaAnDu6bmYHzQfrYu1xm+Vf1NgKd/KBJgAE2ACTIAJsAA0UQB++vQJK1asQL169ZA9e3YeQf8RUFsAzjs7D55nPNG8SHOMrDKSuTMBJsAEmAATYAJmIKD2/G0GE1XvQvYKIEX7Uu6/fPnyqW6UpTxA7QG0IGgBZp+ejaaFm2Ksw1hLwcJ2MgEmwASYABPQNQG1529dO/+fcbIFICWD7tevH5o0aWIJfmlio9oDaMn5JZh+cjoaF2qMCdUmaOITP4QJMAEmwASYQGInoPb8bQn8ZAvA1atXY+jQoUIEli9fHunSpYviX2y1gi0BQnxtVHsALb+0HJOOTYJLfhdMdZwaXzP5PibABJgAE2ACTCASAbXnb0uALVsAJkuW7Ct/rKysRFk4+hweHm4J/prVRrUH0Org1Rh3ZByc8zpjZs2ZZrWdO2MCTIAJMAEmkFQJqD1/WwJX2QLw5s2bcfqj1tlAKj/Xu3dv+Pr6gkQolZ2bNWsW0qdPH6s9oaGhGDBgAFauXIkPHz6I4BVPT88YA1iePn2K0qVL4+7du3j+/DkyZswo+72pPYA2XN2AkYdGonru6vCs7SnbLr6QCTABJsAEmAATiJ2A2vO3JbCXLQATyhlXV1fcv39f1BwOCwtDp06dULFiRRGVHFvr2bMntm7diiVLlsDGxga9evUS4jEwMPCrW9zc3PDx40ds27ZNdwJwy40tGHpgKOxz2mNB3QUJ9Qr4uUyACTABJsAEEhUBFoCASQLw+vXrmDlzpogGpla8eHH88ssvKFSokCoDg55Dzzh+/DgqVKggnrF9+3bUr18fd+7cQa5cub567suXL5E1a1YhED08PMTvL1++DDs7Oxw+fBj29vaGe+bNm4dVq1Zh5MiRcHZ21p0ADAgJwIB9A1A+e3kscVmiCmPulAkwASbABJhAUiPAAtAEAejv74/GjRujTJkycHBwEGOFVtTOnj0rtmfr1Klj9vGzaNEisZVLW7NSo5yEadKkwZo1a9C0adOvnrl79+4YxRxtUfft21cEsVC7ePGiuO7o0aO4ceMGatasaVQA0nYyfUiNBpCtrS1IdFpbW5vd/z239qDPnj4olaUUljdYbvb+uUMmwASYABNgAkmRAAtAEwRg2bJlxVm6SZMmRRkrQ4YMQUBAAE6dOmX2MTRx4kR4eXkhODg4St/ZsmXDmDFjQFu90Rut/NE2cWShRtdUqlRJiLzJkyeL39H3gwYNQrt27bB3715ZAnD06NHiudGbWgLw4N2D6LmzJ+y+tcPqRqvNzpc7ZAJMgAkwASaQFAmwADRBANKq27lz5/Ddd99FGStXrlwBpYChwAu5jUQjCbG4Gm3/rl+/XhUB2L9/f9y7d08EiVCTKwC1XgE8dv8Yfgz4EYVsCmGj20a5ePk6JsAEmAATYAJMIA4CLABNEIC01Tljxgw0b948ClLKDzhw4EDcunVL9mB7/PgxKPo2rlawYEF4e3ursgVM29gkZil9DTVKZfP582ckT54cw4YNi3GVLyZb1R5Apx+dRodtHZA3Q15sbbZVNl++kAkwASbABJgAE4idgNrztyWwlx0EMnbsWPzxxx+g1buqVasK3+gMIK3k0YraiBEjzO6vFARy4sQJkXyaGm03u7i4GA0C8fHxESljqNEWcrFixQxBIBTM8v79e4O9FGTSuXNnHDp0SAS00BaznKb2ALrw5AJabW2FnOlyIsAjQI5JfA0TYAJMgAkwASZghIDa87clvADZApBWySgCePr06WL7lBpF4dI5uj59+hhW08ztNKWBefjwIf766y9DGhiKCJbSwFD+PgrmWLp0qTjXR43OBvr5+Yk0MBScQXkEqZHAi6nJ3QKOfq/aAyj4WTA8fD2QOU1m7G2519xouT8mwASYABNgAkmSgNrztyVAlS0AIzvz+vVr8W2GDBlU95ESQVMev8iJoGfPnm1IBB0SEoICBQpgz549oHrF1KRE0LQKGDkRdI4cOSxKAN54eQNNNjaBdSprBLb+Ooeh6vD5AUyACTABJsAEEiEBFoAmnAGkLVNaBfzmm2/EUKDKIBs2bBB5+urWrZsIh4dxl9QeQHde34HrelekTZEWx9oeM24QX8EEmAATYAJMgAkYJaD2/G3UAB1cIHsFkERes2bN0KNHD7x48QJFixZFqlSp8OTJExEcElNKFh34p6oJag+gh28fovba2khhlQKnO5xW1RfunAkwASbABJhAUiGg9vxtCRxlC8AsWbJg3759KFGiBP755x/MmTMHp0+fxrp160QlDak6iCU4bS4b1R5Az0Ofo8aqGsLcsx3OIplVMnOZzv0wASbABJgAE0iyBNSevy0BrGwBSFu/VFItb968aNGihRCCo0aNwu3bt8Vq4Lt37yzBX7PaqPYAevPxDar4VBE2n2h3AqmTpzar/dwZE2ACTIAJMIGkSEDt+dsSmMoWgJTsuUuXLqL8WsmSJUVN3ipVquDkyZNo0KABHjx4YAn+mtVGtQfQh/APqOAdUQP5UOtDyJBK/aAbswLizpgAE2ACTIAJ6JCA2vO3Dl3+yiTZAnDt2rVo06YNwsPDRdoVysdH7ffff8f+/fuxbds2S/DXrDaqPYAo6Kb00tL4gi/Y02IPsqTNYlb7uTMmwASYABNgAkmRgNrztyUwlS0AyRla5bt//z5Kly6NZMkizqMdO3ZM5NqjRMtJrWkxgCotr4T3n97Dr5kfbDPYJjXE7C8TYAJMgAkwAbMT0GL+NrvRZu7QJAFo5mdbfHdaDCDHVY54FvoM6xqvQ5FMRSyeGTvABJgAE2ACTCChCWgxfye0j8aeL1sAvn37FpMmTcKuXbvw6NEjUTs3crtx44axZyW632sxgFzWueDum7vwru+N0llLJzqG7BATYAJMgAkwAa0JaDF/a+2Tqc+TLQBbt24t0sC0b98eOXPm/Kr02y+//GLqsy3+ei0GUNNNTXHtxTX8U/cfVM5Z2eKZsQNMgAkwASbABBKagBbzd0L7aOz5sgVgxowZsXXrVjg4OBjrM8n8XosB1HpLa5x/eh5zas2Bk21EqTtuTIAJMAEmwASYQPwJaDF/x986be6ULQCp3q6fnx/s7Oy0scwCnqLFAOrs3xnHHxzHlBpT4FrA1QKosIlMgAkwASbABPRNQIv5W98ETKgF7O3tjU2bNsHLy8tQD1jvzqltnxYD6OddP2P/nf0YW3Usmn7XVG2XuH8mwASYABNgAomegBbzt94hyl4BLFu2LK5fvw7KTZc/f36kTJkyim+nTp3Su69mt0+LATRg7wAE3AzAkEpD0Naurdl9OPXwFEI/haJq7qpm75s7ZAJMgAkwASagRwJazN969DuyTbIF4JgxY+L0hcrCJbWmxQAafnA4Nl3fhF/K/YIu33cxK+LrL66j2eZm+PzlMweZmJUsd8YEmAATYAJ6JqDF/K1n/8k22QJQ744khH1aDKAJRyZgZfBKdCvVDb3L9jarm4vPL8aMkzNEn7S6SKuM3JgAE2ACTIAJJHYCWszfemdokgB88eIFqCQcbQUPGjQI3377LWjrN3v27MidO7fefTW7fVoMoNmnZmPBuQVoVbQVhtkPM6sP/fb0w85bO0WfxTMXx6qGq8zaP3fGBJgAE2ACTECPBLSYv/Xod2SbZAvAoKAg1K5dGzY2NggJCUFwcDAKFiyI4cOH49atW1i6dKnefTW7fVoMoKUXlmLqialwze+KKY5TzOpDk41NcONlRALvNMnT4FjbY1/ldzTrA7kzJsAEmAATYAI6IKDF/K0DN+M0QbYAJPFXrlw5TJkyBRkyZMDZs2eFADx06BDatGkjRGFSa1oMIN/rvvjt4G+wz2mPBXUXmA0xBfPYr7DHu0/vDH3ubr4bWb/JarZncEdMgAkwASbABPRIQIv5W49+x2sFkFb+aLu3UKFCUQTgzZs3UbRoUYSGhurdV7Pbp8UAohQwlArG7ls7rG602mw+vPr4Cg4+EUm9v03zrag37OXihXLZy5ntGdwRE2ACTIAJMAE9EtBi/taj3/ESgNmyZYO/vz8oHUzkFcAdO3agc+fOuH37tt59Nbt9WgygoMdBaOvXFjnT5USAR4DZfLjy/ArcN7vDJrUNimYqimMPjuH36r+jYcGGZnsGd8QEmAATYAJMQI8EtJi/9eh3vARgly5d8PTpU6xevVoEf9CZwOTJk8PNzQ01atTAzJkz9e6r2e3TYgDdfnUb9TfUF2f0jrc7bjYfDtw5gJ92/STEX6GMheD3rx8GVhiIjiU6mu0Z3BETYAJMgAkwAT0S0GL+1qPf8RKAL1++hIeHB06cOIHXr18jV65cePDgAapUqSJKxKVLl07vvprdPi0G0Luwd6i8orKw/UibI0iX0jyc11xZg7GHx8IxjyPyW+eH10UvdCzeEQMrDjQ7J+6QCTABJsAEmICeCGgxf+vJ35hskR0EIt0cGBgoAkDevHkjgkIoOCSpNq0GUOXllUWwhq+bL/Lb5DcL7nln58HzjCfcv3MXAnD6yeloULABJlWfZJb+uRMmwASYABNgAnoloNX8rVf/yS6TBaCendHaNq0GUIP1DXDr9S0sqrcIFXNUNIubk45NwvJLy0V1EdoCHnpgKCrnqIx/6v1jlv65EybABJgAE2ACeiWg1fytV/9lCcDDhw+Ls38NG/4/OIBy/lHpt7dv34ozgHPmzEHq1Kn17Kcqtmk1gDpu64hTj05hSo0pcC3gahZfBu8fbDj3V/Tbouga0BWFbApho9tGsxBYzCcAACAASURBVPTPnTABJsAEmAAT0CsBreZvvfovSwC6urrCyckJgwcPFn6cO3dObP3+8MMPsLOzw9SpU9G9e3eMHj1az36qYptWA2jgvoHwD/HHrxV/Rfvi7c3iS48dPRB4LxDjHMbh+yzfw22TG6xTWSOwdaBZ+udOmAATYAJMgAnolYBW87de/ZclAHPmzAlfX19UqFBB+DFs2DDs27cPBw8eFN+vWbNGrAZevHhRz36qYptWA2jyscnwvuSNTiU7oX/5/mbxpdWWVrjw9ALm1JqDstnKotrKaqLfU+1OIWXylGZ5BnfCBJgAE2ACTECPBLSav/Xou2ST0TOAadKkwdWrV2FrayvuqVatGmhVkIQgNaoA8v3334vI4KTWtBpAC88txMxTM9GoYCNMrD7RLJhd1rng7pu7WOa6DKWylkLZZWXx+ctn7GmxB1nSZjHLM7gTJsAEmAATYAJ6JKDV/K1H32ULwHz58mHZsmUi19/Hjx+RMWNGsSLo7Ows+qAtYUdHRzx79kzPfqpim1YDaN2VdRh9eLRI2TLXea5ZfKmyogrehL0xRBZXX1kdLz68wIbGG1A4U2GzPIM7YQJMgAkwASagRwJazd969F22AOzZs6dI+zJ58mRs3LgRXl5euHfvHlKlSiX6WL58uUgCffy4+ZIU6xlYZNu0GkABIQEYsG8AymUrBy9XL8V4wj6HodyyiJJvB1oeQMY0GdFoQyOEvArB4nqLUSFHxHY/NybABJgAE2ACiZGAVvO3ntkZ3QJ+8uQJmjVrJs78pU+fXgjApk2bGnyilUB7e3tMmDBBz36qYptWA+jQvUPovqM7vsv0HdY3Xq/Ylyfvn6Dm6pqwghVOtz+N5MmSi3JzVHZuptNMOOeLWN3lxgSYABNgAkwgMRLQav7WMzujAlAyniqBkACk8m+RG2390s+lFUE9O2tu27QaQOefnEfrra2RI10O7PDYodiNGy9voMnGJsiQKgMOtT4k+vt518/Yf2c/RlcZDfci7oqfwR0wASbABJgAE9ArAa3mb736T3bJFoB6diKhbNNqAN18dRMNNzQUZeCoHJzSRit9tOKXK10u+Hv4i+6GHRyGzdc3o2+5vvjx+x+VPoLvZwJMgAkwASagWwJazd+6BcACUNmr0WoAPQt9BsdVjsJY2rJNkSyFIsOlLeUimYpgXeN1oq8px6dg2cVl6FSiE/pXME+qGUVG8s1MgAkwASbABFQioNX8rZL5ZumWVwAVYNRqAIWFh6Gcd0TQxsFWB2GT2kaB1cCOmzvQf2//KEElfwf9jTmn56Bp4aYY6zBWUf98MxNgAkyACTABPRPQav7WMwMWgArejpYDqPyy8vj4+SP83f2RK30uBVYDG65uwMhDI1E9d3V41vYUfa0OXo1xR8ahlm0tzKo1S1H/fDMTYAJMgAkwAT0T0HL+1isHFoAK3oyWA4gqdbz88BKbmmxCwYwFFVgNsdVLW76u+V0xxXGK6ItKzVHJOXOlmlFkIN/MBJgAE2ACTEBFAlrO3yq6oahrFoAK8Gk5gGqvqY2H7x5iZYOVKJGlhAKrgXln58HzjCeaF2mOkVVGir6O3j+KLgFdUMimEDa6bVTUf0w3H753WJSea1m0pYg+5sYEmAATYAJMIKEIaDl/J5SPxp7LAtAYoTh+r+UAkhI1L6q3CBVzVFRgNTDt+DR4XfSKEvAR/CwYHr4eyJwmM/a23Kuo/+g3k/jrtqOb+LFzXmfMrDnTrP1zZ0yACTABJsAETCGg5fxtil1aXssCUAFtLQdQC98WuPTsEjydPVE9T3UFVgOjD43Guqvr0KtML3Qv3V309eDtA9RZWwcprFLgVPtTsLKyUvSMyDd3DeiKI/f/n75mk9smFLRRto1tNuO4IybABJgAE0hyBLScv/UKlwWggjej5QDquK0jTj06hemO01E3f10FVkOc9aMzf0MqDUFbu7air/ef3qPS8kri68OtDyN9qvSKniHd/DbsLar5VMOnL5+Q3zq/KDcXWXia5SHcCRNgAkyACTABEwhoOX+bYJaml7IAVIBbywHUY0cPBN4LxIRqE9C4UGMFVgM9dvZA4N1AjHMYB7fCboa+KnhXwIfwD9jWbBvyZMij6BnSzVRdhKqM5EmfBx1LdMSEoxNgn9MeC+ouMEv/3AkTYAJMgAkwAVMJaDl/m2qbVtezAFRAWssB1G9PP+y8tRPDKw9Hy2ItFVgNtPdrjzOPz3xV99d5jTMevXtklkATycAZJ2dg8fnFcP/OHW3s2sB9szvSpkgrStApTWitCALfzASYABNgAkmWgJbzt14hswBU8Ga0HEBDDwzFlhtbMKD8APxQ8gcFVgNNNzXFtRfXxCocrcZJjcTZledXML/2fFTNXVXRM6SbpZXLEfYj4FHEA5TO5vXH11jdcDXsMtuZ5RncCRNgAkyACTABUwhoOX+bYpeW17IAVEBbywE09vBYrLmyBj+V+Qk9S/dUYDVEsAcFffg08EHJLCUNfXX274zjD45jcvXJqF+wvqJnSDc7r3bGo/ePsMx1GcpkK4NO2zvhxMMTmFhtIhoVamSWZ3AnTIAJMAEmwARMIaDl/G2KXVpeywJQAW0tB9DU41Ox9OJSdCrZCf3LK6vVW3VFVbwOe43NbptRwKaAgQCVh6MycUMrDRXbtUrbi9AXqL4qImJZCiyZcGQCVgav5JrDSuHy/UyACTABJhBvAlrO3/E2UuUbWQAqAKzlAJp9ajYWnFuANsXaYGjlofG2+suXLyi9tDS+4Av2tNiDLGmzGPoac3gM1l5Zi59K/4SeZZStMlKntJpIq4q50+fGdvft4jlSyblquathXu158faDb2QCTIAJMAEmEF8CWs7f8bVR7ftYACogrOUA+uvsX/jzzJ/iHN2oKqPibfW7sHeovKKyuP9Y22MiIENqs07Nwj/n/hGpYShFjNLmc9kHE49OhGMeR8x1niu6O/3oNDps64Ac6XJgh8cOpY/g+5kAE2ACTIAJmExAy/nbZOM0uoEFoALQWg4giqSliFpKAUOpYOLbHr59iNprayO5VXKcbn86SsLnJeeXYPrJ6WhQsAEmVZ8U30cY7pO2rdsXb49fK/4qfv7q4ys4+DiIrykSmMvCKcbMHTABJsAEmICJBLScv000TbPLWQAqQK3lAFp+aTkmHZuEevnrYZrjtHhbfePFDTTZ1ATWqawR2DowSj8brm7AyEMj4ZDbAX/V/ivez5Bu7LunL3bd2hUl4TT9zmmVE56GPsXKhitRIrOyusaKjeQOmAATYAJMIMkR0HL+1itcFoAK3oyWA4jO5tEZPSdbJ8ypNSfeVgc9DkJbv7ZRzuVJne25tQd99vRBycwl4dPQJ97PkG5s7tscl59dxtxac+Fo62joj7aAaSt4ao2pcCngovg5YZ/D4HnGE1RzuGququL8YspkKRX3yx0wASbABJhA4iSg5fytV4IsABW8GS0H0ObrmzHs4DA45HLAX3Xivzp36N4hdN/RHUUyFcG6xuuieC+dz7PNYAu/Zn4KyETcKkUbb2i8AYUzFTb0R36QP73L9ka3Ut0UP2fyscnwvuRt6KdV0VYYZj9Mcb/cARNgAkyACSROAlrO33olyAJQwZvRcgBtD9mOQfsGoUL2CljssjjeVgeEBGDAvgEol60cvFy9ovQjbQ/TuTw6n6ekvfzwUiR9pna0zVF8k/IbQ3fzz87H3DNz0aRQE4yvNl7JY3Dt+TW4+7rj85fPaFGkBVZfWS36W15/OUplLaWob76ZCTABJsAEEicBLedvvRLUvQB89uwZevfuDV9fXyRLlgzu7u6YNWsW0qdPHyvT0NBQDBgwACtXrsSHDx9Qr149eHp6Inv27FHuWbJkCWbMmIErV67A2toazZs3x59//in7XWk5gKTt2VJZSmF5g+WybYx+oXTOr3ru6vCs7Rnl10/fP4XTaifxMwoQUVKq7eLTi2i5pSW+TfMt9rXcF+U52/7dhl/3/xqjCDXVsfFHxmNV8CrUtK2J2bVmi1VSWl10yuOEOc7x3yo31Q6+ngkwASbABCyHgJbzt16p6F4Aurq64v79+5g/fz7CwsLQqVMnVKxYEStWrIiVac+ePbF161aQwLOxsUGvXr2EeAwM/H/QAwm/6dOnY+rUqahcuTLevn2LkJAQNG7cWPa70nIABd4NRI+dPVA0U1GsbbxWto3RL1x2cRmmHJ8C1/yumOI4JcqvP33+hLLLyoqf7W+5H5nSZIr3cyihNCWWjkmwXnhyAa22thI5CCkXYXzbh/APqLm6pigt93edv1ElVxX8+/JfNN7YGFawgr+7P3Kmzxnf7vk+JsAEmAATSKQEtJy/9YpQ1wLw0qVLKF68OI4fP44KFSoIhtu3b0f9+vVx584d5MqV6yuuL1++RNasWYVA9PDwEL+/fPky7OzscPjwYdjb2+P58+fInTu3WFV0dnaO97vRcgBJSZWpcgdV8Ihvm3d2ngiYaF6kOUZWGflVN1VWVMGbsDdfVQkx9XlSSpmYhGZc28OmPGfXzV3ou7cvcqbLKRJNJ7NKJm6XStqZ64yhKTbxtUyACTABJqB/AlrO33qloWsBuGjRIrGVS4JNap8+fUKaNGmwZs0aNG3a9Cuuu3fvFqKO7smYMaPh9/ny5UPfvn3Rr18/rF69Gh06dMDff/+N33//Ha9fv0bVqlXFiqCtra3sd6XlAIorele2wQAMJeVKdEL/Cl+XlHNZ54K7b+4aavea0nfka6Wt2S7fd8Ev5X75qpvqK6vjxYcXWNtoLYp+WzRej5Eql0RPXL3x2kaMCByB/Nb54dvUN159801MgAkwASaQeAloOX/rlaKuBeDEiRPh5eWF4ODgKPyyZcuGMWPGgLZ6ozda+aNtYjr7F7lVqlQJNWvWxOTJkzFp0iSMHDkSBQsWFOcJaZt4+PDhYlUxKCgIqVKlivF9UZ+R+6UBRIKRVh3pDKGaLfhZMDx8PRRvm44+NBrrrq5DrzK90L10969MbrWlFS48vSBSzVDKmfi2njt74uDdg6JqCVUvid7abm2LoCdBmOE0A3Xy1TH5MVTSrt66erj/9j48nT1RPU9EzWFqbz6+ETWIaUt7k9smFLQpaHL/0W8I/RSKhecX4tj9YyieuTh+KvMTJ7FWTJU7YAJMgAkkDAEWgECCCMAhQ4YIIRZXo+3f9evXqyIASVgOGzYM/v7+qFu3rjDj8ePHyJEjB/z8/ETQSExt9OjRQnhGb1oIwBsvb6DJxiZCdCiJ0B24byD8Q/y/Ss4s+dRjRw8E3gvEeIfxaFK4Sbz/z6RzeHQeTzqbF72jwfsHw+9fP7E6SKuEpjYpYjlVslQ42PpglJJ21Bedl6Rzk/HtP7I9JCSpv6P3jxp+XDhjYSx1Xcoi0NQXx9czASbABHRAgAVgAglAEltPnz6NcwjQ6py3t7cqW8CLFy9G586dcfv2beTJk8dgB0UJjx8/Hl27do3RtoRcAaRtWdqeTZM8DY63Ox7v/30kYRSbwKPoXIrSHVhhIDqW6Biv59DqXMXlFUFBGn5N/WBr/fW2OtU1pvrG7t+5Y3TV0SY/R6qMYp/THgvqLvjq/tXBqzHuyDiRCoZSwihpXhe8MO3ENHyT4huxakqBNE/eP1Fclk+JTXwvE2ACTIAJxJ8AC8AEEoByX5kUBHLixAmUL19e3BYQEAAXFxejQSA+Pj4iZQw12kIuVqyYIQiE0r4ULVoUO3fuNASBULoZCh7Ztm2bYVXQmJ1aDiASHBTxStGtZzucjVLD15idkX/fzq8dzj4+i5lOM+Gc7+sAmIlHJ8Lnsg+6ft8Vfcr1MaVrw7WP3z1GrTW1RFDGiXYnYqzKISW2rpSjEhbWW2jyc37d9yu2hWyLdSv70btHcF4T4d/u5ruR9ZusJj+DbqCAlTpr6+D9p/cYU3UMmn3XDGcenQFVM/mCL1jisgTls0eMTW5MgAkwASZgGQS0nL/1SiRBtoBNgUFpYB4+fIi//vrLkAaGIoKlNDB3794VIm7p0qWgc37U6GwgbeVSGhg6m0d5BKkdOvT/5MZubm64du2aCASha4YOHYobN27gzJkzSJlSXhkxLQfQq4+v4ODjIPw41e4UUiaXZ2N01k03NcW1F9fEqhmtnkVvFCFMkcKxRQnLeXckkNpvay+icwM8AmK8Rc41cT2r7tq64vxfbH7QvW22tsG5J+cwuspouBeJ+GPA1Lbw3ELMPDVTVE5Z02iNIdJYOksZXwEbmx1U1o7S5NBnqpMcOYG2qbbz9UyACTABJhAzAS3nb72+A90LQFqZozx+kRNBz54925AImnL3FShQAHv27IGTU0TQgpQImlYBIyeCpjN+UqOXTxHBdM6QcgQ6OjqKgBC9RgFTEAJtq1I73Pow0qeKPRF2XIONVrMevH0AnwY+KJml5FeXSlurdfPVxXSn6fEat1tubMHQA0PjrFoSeUWTVglTJY858CYmA6TVPVphpPOQ6VKmi9FO2mKmrWYpSbSpzpAIc13niofvHmKcwzi4FXYzdHH/zX3UX18fn758UhwxLXVKZfpGHRol3g81m9Q26F2mN1oUbRHvFd+YfL7y/AroI22KtCIZt5J8j6Yy5euZABNgAnogwAJQ51vAehgkcdmg5QCiUmell5YW5lBlDaqwEZ8m1eelXIKUUzB6k8Rb5RyV8U+9f+LzCMgp9UbnBO1X2OPdp3cmR+pKSaZjqmcc2eBLTy+hxZYWQugcaHUAqZOnNsmf/Xf24+ddPwvWOzx2fCVSRwaOxIZrG0QUM0UzK2k7b+4UJfroPWdMnVE8i4QutXZ27fBrxV8Vi0AKyqGVy1OPThlMpWovVEKPcibG948KJX7zvUyACTCBhCCg5fydEP7JeabuVwDlOJFQ12g9gMotKye2BkmM5Ej3/9VMuf6TuCiztIw4u0YVOKgSR/RGqVsohYuSiiOSMKJUKT1Lf52qR3qmx2YPBD8Pxtxac+Fo6yjXDUw7Pg1eF72MblOTyKy9pjYevX+EebXnoVruiNrEctuQA0Ow9cZWtCnWBkMrD/3qNlpFc9/sjuRWycVWd7ZvssntOsp1119cF2XzKGimQcEGInUORTdTsMmMkzPE++pfvj86lewUr/7ppiP3j6DP7j7iLGPKZClROmtpkYeRjgNQo5yJfzr/ibzWeeP9DL6RCTABJmApBLSev/XIhQWggrei9QCiFbO3YW+xpekW5LPOZ7LldC/1Qe1Y22NfpU6hn59/ch6tt7YWApOEZnzaj/4/4tiDY5hYbSIaFWoUaxdUKo5W8wZXHIx2xdvJflR7v/Y48/iMrFQ1UrLoVkVbYZj9MNnPIKHkuMpRCKZlrstQJluZGO+lYJDTj07HGoxi7IEk6FtvaS2EsEMuByHCkidLbrhNKt1H292L6y1GuezljHX51e+pigyJehKYFXNUFO9F+gMi8rZzptSZxKovrawqaeGfw8UW8+P3j5E+ZXoUzlQY1qnUzZOpxF6+lwkwgaRHQOv5W4+EWQAqeCtaDyASJM9Cn2Fd43XxmqQfvn2I2mtrixWr0+1Px7ilePv1bXG2jbZLj7c9Hq9tR6maiJeLV5yChVa3Fp9fjNbFWuO3yr/JehNh4WFCxH78/FGWEN57ey967+6NXOlyiXJxVlZWsp6z/d/tGLR/EHKnz41tzbbFep/vdV/8dvA3Iai2N9seRbzJeZCUroa2fTc02RDjquxvB36D7w1fEVRDgSh0NlBuo7OKtLr4/MNzOOVxEuc6o5+3pKht2uq+9OyS2O5e7LI4Xsmz6VwnCda1V9aCgpaklsIqBRxyO4h8j7EJabn+SNfRs048PIFrz6+JWtC0zZ8rfS6xsvldpu8MwTqm9kurxiTGaSWcjhDcen1L9E+rpvSOCmUshBJZSgixTs/jxgSYgGUS0Hr+1iMlFoAK3orWA0gK4FjZYKWYhExttNXotslNrMYEtg6M8XZa8aq0PCKamgIsKPG0KY1WtCp4VxBn2XY13xXntigJBVqho61Z2qKV06SSeLRaRWchjQk68ofKztHq1/rG64U4kNOk1ckfS/6IvuX7xnoL9UvbzLSdamr1lHdh79BgQwORU3BopaFoY9cmxufQym1z3+YgcU61lSfXmGzUb+qIbPth2w84//Q87L61E4mr06RIE+MzKN1N14CuQgRmTZsVi+otQn6b/HJQgUQTpfWZfHyyEEvUaNzkSZ9HcKFobamR/YMrDUbmtJll9R39IlrNpD8aaOUy/Et4jH2Q/bXz1QYFMpXNVtaoKCf7qSoNif49t/eIUohyGiUDpwo0jnkchfCk85SmNFopfRr6FBTg9TH8I1KnSC3EfYaUGWS9X7nPoso4dP6TxCyduf3w6YNgR3/k0Xigj7TJ04qIcxLS9EE5L8kesos+QsNDxe4D9UW1wuk90/fS58g/I38oMMs6tTVsUtmIICN635nTZI7ymVaHjf3/K9dHc15H/9/Q/w+vPrwSflMiePp3jT7TB/3bJrWY7KdUXdSk3xm+/+/n0idxTaRr6Wt6F8RevIP/3gflftUjp8jM6f8hYkRjhfiJcfM54mv6o50+i68/R3wt+U5+0X+0wyHVchdfIxnBET+jBQv6tyRn+pzmfM3Qev42q/Fm6owFoAKQWg+ghhsa4uarmzC2shabS5T/j/IA0qoWrYbF1qqsqCL+kY8tUCQuZLdf3Ub9DfJWEKmyRpeALibV7JW2RGnSnes8V9bbo9UtCuiQWxUk8vbvyoYrRTqWuNr0E9Ox5MISsSr0V52/ZNlEF/0d9DfmnJ4j/nEj1nGl9jn3+JxIrUMT9+/Vf0fDgg2NPkdKVUMrV6sarjK6YvU89Dl+DPgRV59fFSuRlJ/RWBm9p++fYuShkYIvtWLfFsNPpX9CjTw1DMKLqtgsvbBUBMzQ5Ekih4JaGhVsJHtio6MJs07NEmcZpUbnVCmSnVYtSYzQc+gPBBI5UqM/FKikIf2RQbZlT5ddTC60PX352WWxirjr5i7ce3vPcA9NuPa57IV4JJFHfzARd7rnyrMrOPnwpMilGVmA0jW0yklCkLbQiR8JHJoESTTde3NPCDAS8Xde38GdN3eE0CRBEb3R5E9HPOhcJgVqFcxYULwH+j62aHniSn9IkNCjD2JBH/+++FecgdVjo3OukYUhvUcS0XTmlQQFtehfi5/99zshDpIlB60w032RP0g00Pe0cit9Td+TABHi7uMrg8gzfP3xlfi5JFD0wowEUmRBGF0g0vf0b4ckpISksooQVYafRRJakUUXjWEag/THiPj83/eU3UAS/5Kok8Sb9PPoQk9NXnSWnM6Um7NpPX+b03Zz9cUCUAFJrQeQlMMvtvJqxlyh0mhUCcRYgEejDY0Q8ipErALRmTFTGq3MdN/RHYVsCmGj28Y4b6Xtybrr6op/qE+0PWF0pYY6k0rZ9SnbB11LxVyxJfpDpW1WmtBpFcxYI0HQd29f2dvGNKk3WN9ATFZbm26VFUhBYst1vasQLlNqTIFrAVdjZonKKZTWhoTF2sZrhZCPrUk+0yRAq6tVc1U12j9dQIKu646uQgTShExnEmNKF0TXHrhzAMMDh4tjCTSZ9yzTEz+U+CHWlTCqMT0qcJTYYqVGgnlklZFxClMSTiT8qGwgNRorVD2mrV3bGKPYaXIikUjlDmn7P/JWdFwAaBIloVg3f13BiibcuBqJCBrrJHwP3D0gxER8GokTWvUhfrTaRH98xNboXdIfC/Re0qWKSH1Eq20vQl8IQRmXcCFBSqKShCoJXBJOdD09jz6oHxLO0ve0Ok0TPokrWgmk1UJa1aOxR9Hi4nPkryP9jPyhcU3saQX42ftnYozQaieNL/pMv9dzI9bEisaBJCzpXZGglIQV/f8uNelrSZxG9i3KdZGEbUz3Svylz3pmFJdtxInGDP3BQh/0deSfkTClP1okgU+f6XtpdVV8jc9C7JMwpf/fWxVrZVYcWs/fZjXeTJ2xAFQAUusB1GpLK9AkamrUrOTi9pDtGLRvkKhcQRUsYms/bP9BrHJMrTEVLgVcTCIkCQ85K3T0VyflNqSJhlYk4xI0khHSNvjCugtRKWfEVrWxRnn16D76h3tvi71G895J0b/ti7cXK1Vy2k87fxJCoEPxDhhUcZDRWyYfmwzvS95ia5ZWGaXtj7hupH8IO23vJAJgKH8fCfTIASPSvfTuuvh3ETkK5a56Rn4uidNuO7qJFTL6R5v+8qZUNNL2ccjLEFDCcKrEQo1WyUjEytlep3dNpfXmnZknVsdogqUAHfrHXTpTR//o07NXX1mNzdc2i+towqCAIrJFzjghu+hZpx6ewq5bu0T1FloRk0QSTep5M+QV/y9UyVUF1XNXj3V73NjLpPdCCcfpDywSt3QukQQhraLTxEdbeXRGlJ5nm8FWfOTJkEeIOYocj/wOScCS6KU/wKKv5L0Oi9hej62RQCGGtFpIH7R6KH2Ycm5U6p8mYTnj0hifmH5PgtMgCP8ThTTuaMxGbAr+fxtVWtGK3A/9jESDtDUrrWDR/dJWbeQVLVrZkgQtsZC2p8XXqawN39PP6XsSu2r5LpcX+ST9UUCCnEShEOlhEZ8jf02+0f83JJpIlwr5RALri5BYht+J7/+7jj7TmBGrqLSCapXC8DX9PLpwEyIu+X/CLtn/hZ0k8iJfn9Ds5DDWev6WY5PW17AAVEBc6wHUcVtHkcONcs5R7jlTm3Tmzpg4I5FIYpHED4kgU9qMEzOw+MJi8RfbkEpDjN7aeGNjMdHJWdWUhBz940TnE02pkiGlnDEWmUwTMAXb0ORNq4W0aiinSTkD6ewbnX2MawWJtgAbbWwkJqr5debLXp0jO2i1kc4D0goKBc/Q2cHI54No5Y6isCnowyW/ixBm8Tk/RGe7RgSOEOKJGvlDW5v0cxJS1GgSpvdMZyRNzbEYU05CCtShCZkSb9OKG5vCLwAAIABJREFUkdSo2grVprbLbCfnVcR6jTShEnd6T2pPUjTBxod9TA5QX7TFS8KQxCW9B+qb3gv5YpveFjnS54ix7KIiaHwzE0ikBLSev/WIkQWggrei9QCi83J0bk7uGbDori05vwTTT04XueYmVZ8Uq+fS6lTnkp3Rr3w/kwhJwRMk/kgcGGvS+bwR9iNExYu4mrSCSatmqxutNtZ1lN/PPjUbC84tQL389TDNcVqs90pCjgIJdjbfKVsk0F/bFD1N57qkmsGxPURaYaRSfFTKztRG25sk0ukve0riPKDCACEEAu8FgiKGSfwVz1xcpI0xRSRHt0MK7qDSgJEDI0g40YpZr7K9xLm6+DZiRtG2tCJIZ/EiH66nbUoKsKAcjLRKZy4hFV9b+T4mwAQSFwGt52890mMBqOCtaD2AJLFkTGDE5tLc03MxP2g+WhZtieH2w2P1/J9z/4hzV40LNcaEahNMIkSrU7R9J3ebeurxqVh6canYYqTo0LiaJExNSRsj9SdFD5NQom3g2ISRlMTaGKOY7JQENh3Wp5QuMUWFSnkWafWMtn5JqMWnrbq8ChOOThAiUERcprI2RNtSn7SiGp9tv5hskbZkaWuStnmo//hG8cbmK61oBT8LFttadMaNVhtNKQ8YH4Z8DxNgAkmXgNbztx5JswBU8Fa0HkDS6hrlzCMRZGqbdGwSqNYv5WOjs2GxtY3XNortP1OjWkkoVPWpKrZPNzbZKHKmGWsbrm4QUaSVc1bGP3XjLj1HCZMppcnk6pNRv2B9Y11H+T3ZRlHUFIk53mE8mhRu8tX9dC6p1upaoLNWppwxlDqibVnKgUgH30k4k4CO3GiFi87w0TZ+fMR1dIMpCOP3Y7+LbWFqFEhAq6j0bmNL92ISNL6YCTABJpBICWg9f+sRIwtABW9F6wEkbR3SeaiOJTqabPmwg8NEvra+5frix+9/jPV+KVqYDvVT7jy5jSL8nFY7ibNhVGlEjgih9CZt/NqIHGF7W+6N9VF0AJrqGNMhb393f6MpTWLqSEq7QpHNFEARvW37dxt+3f+rSLhMQSnxOSO26Pwi/HHyD2T/JrsQwZHr6/pc9sHEoxNFFCZVc6GUJEobnWu7+uKqSDVC78tcq35K7eL7mQATYAJ6JqD1/K1HFiwAFbwVrQfQqEOjsP7qepiSAiWye7/s/gW7b++GsfN2UsJoSvNAwRZyz19Rkt7O/p1FdOM294gIUWONotsqr6gsLqPEzrT9F1M78eAEOvl3Qra02cTZPLk2Re6L0s7UW1dPbJvGVE6vx44e4hxd91Ldxfm2+DRaRWy2uZlYlatfoL44a0m20tYvrf5RVJ/c85HxeT7fwwSYABNgAsYJaD1/G7dI+ytYACpgrvUAmnBkAlYGr4y3QJFq9JIooUCQ2FrkaiAHWx2Uvaq08vJKcS7NWJRx9OdKpePiyjsord5R9DNFQce3SelaPIp4YFSVUYZuKHVH081Nxeol5fKztbaN7yNAQpiqalDqCbKX8ujRuUo650bb6p61PeO1uhhvg/hGJsAEmAATiEJA6/lbj/hZACp4K1oPoGnHp8HropdItkuRn6a2Fr4tRKkvSu5LlRriak6rnESeLjmVMKR+JIHaqWQn9C/fX7Z5vXf1xt47e0U94NjONkridVjlYYoSglKOPMpzSPntNjXZZBB60va6UoEpOb3p2iZxtjFyZCullKGkzBS0wY0JMAEmwAQSjoDW83fCeRr7k1kAKngrWg8gKZVJfKJgyU2qVkFBEHJKybX1ayvKak13nC6qI8hpkkiLLcgitj4o4phWyKjCw+iqo7+6jFYkHXwcRCJXXzdf2TVqY3serc5RtYjKOSqL0m3HHhwT1UuomSJ4jTGh8420Yks1Ram0GAVokPDkxgSYABNgAglLQOv5O2G9jfnpLAAVvBWtB9D8s/Mx98zcWIWSMVcowTEl2F3XeJ1IsxFXG7x/sCi/RSt5tKJnrFGULQWAUP8+DXxiLR8WUz9S6TWqKEHpU6K3Q3cPofvO7qKaQoB7QLzO/0Xu89arW+KcHlWFoLJ4JIpJZDYv0lyUJuPGBJgAE2ACiZuA1vO3HmmyAFTwVrQeQJQwd9qJaWhYsKFIBm1qK7esnFhFIxGVM33OOG+XVhsp0fCIKiOMPipylY4jbY7IigCWOqUKBzVX1xTn7wJbB4rKBpGbtPXtVtgN4xzGGbVFzgX7bu8TdYUpKIMaJWWe6zzX5IoWcp7F1zABJsAEmIC+CGg9f+vL+whrWAAqeCtaDyApjUh8zqnRalcF7wrCW4rsjS6yomOgaGOKOq6aq6ooV2as7by5E/329hOVIdY0WmPs8q9+LwWCRC+NRiuLVGGDit1TBQ+q5GGuRlHBFBVNK4s1bWtyYIa5wHI/TIAJMAGdE9B6/tYjDhaACt6K1gNIEmWmRtmSi9IqG319tsNZo2LnzKMzaL+tPagk2u4Wu41Sotx3lAMvenSt0Rv/u0Dacu5Wqht6l+1tuI2qilB1EcqdR2lilJQ2k2sLX8cEmAATYAKJm4DW87ceabIAVPBWtB5AW25swdADQ8V2pak1ZENehqDRxkYiApW2aI01qmpRZUUVkTOPSqcZK/3VaksrXHh6IdYqG8aeR1GzwwOHI3qd3xknZ2Dx+cVwzuuMmTVnGuuGf88EmAATYAJMwCgBredvowYlwAUsABVA13oA7bi5A1QOrly2cvBy9TLJ8gtPLqDV1laiQgUlUpbTpKjh6Nuy0e99HvocFGBCYnFX813I9k02Od1HuYaqiNA5QOpDqvRB29a119QWpdVm1ZyFWnlrmdwv38AEmAATYAJMIDoBredvPb4BFoAK3orWA2j/nf34edfPKJG5hEhXYkqjtCeU/iS2SNuY+hqwdwACbgagV5le6F46Ik1KTG3tlbUYc3iMiCymCOP4ti7+XXD0wVFI28Crg1dj3JFxojTbtmbbkDxZ8vh2zfcxASbABJgAEzAQ0Hr+1iN6FoAK3orWA+jo/aPoEtDFJBEnuScFaZTJWgbL6i+T5fWqy6sw/uh4VMheAYtdFsd4DwVptNzSUiSYHlB+AH4o+YOsvmO6KCAkAAP2DQCVoJtda7ZY7aTVPy6dFm+kfCMTYAJMgAnEQEDr+VuPL4EFoIK3ovUAkgIzbDPYwq+Zn0mWb7i6QVSmqJa7mqhGIadRvrwGGxoghVUK7Gu1D9aprL+6TVqloyANfw//WGv5ynle+OdwdNjWAUFPggyXU1TxigYrOIGyHIB8DRNgAkyACcgioPX8LcsojS9iAagAuNYD6OLTi2K1jc7Y0Vk7U9qyi8sw5fgUuOZ3xRTHKbJupdU9d193XH1+FQMrDETHEh3FfWHhYQi8Fwjf676gc4l0bq9vub748fsfZfUb10V3Xt9Bnz19xDNpq5vO/mVPl11xv9wBE2ACTIAJMAGJgNbztx7JswBU8Fa0HkDXX1yH2yY3ZEydEQdaHTDJ8nln58HzjKfJ1S6k830ZUmbAL+V+EVu9JPpefXxleH6bYm0wuNJgo6ll5BpMwpP6pxVHKysrubfxdUyACTABJsAEZBHQev6WZZTGF7EAVABc6wF0+/VtkRQ5bYq0ONb2mEmWTz42Gd6XvEVZNyrvJrdR5RCq8Xv60ekot2RJmwUu+V3QpHATkfyZGxNgAkyACTABSyGg9fytRy4sABW8Fa0H0ON3j1FrTS0kt0qOMx3OmGT5sIPDsPn6ZvQr3w+dS3Y26d6XH17i76C/EfwsGPms86Fu/roiMISjck3CyBczASbABJiATghoPX/rxO0oZrAAVPBWtB5AJMSqrawmLD7d/jRSJEsh2/reu3pj7529GF1lNNyLuMu+jy9kAkyACTABJpDYCGg9f+uRHwtABW9F6wEU+ikUFZdXFBYfbXPUUBbtyvMroGjcjsU7wtbaNkaPKLqWtnFnOM0A1RLmxgSYABNgAkwgqRLQev7WI2cWgAreitYD6POXzyi9tLSweH/L/ciUJpP4uummprj24hoq5qiIRfUWxehRk41NcOPlDSysuxCVclZS4DXfygSYABNgAkzAsgloPX/rkRYLQAVvJSEGULll5UCBGTs8diBHuhy4+eomGm5oaPDiZLuTSJU81VdeUZm1J++fYG2jtSj6bVEFXvOtTIAJMAEmwAQsm0BCzN96I8YCUMEbSYgBVGVFFbwJe4MtTbeIgIzt/27HoP2DDF5QKTYqyRa5UVqV8t7lowhHBW7zrUyACTABJsAELJpAQszfegPGAlDBG0mIAeS0yglPQ5+Kmrsk9Ci3H+X4k9rUGlPhUsAlilfvwt6h8orK4meRzw4qcJ1vZQJMgAkwASZgsQQSYv7WGywWgAreSEIMoHpr6+He23vwaeCDkllKYtC+Qdgest3gRe+yvdGtVLcoXj14+wB11tYRUcOn2p3i5MoK3jnfygSYABNgApZPICHmb71RYwGo4I0kxABqtKERQl6FYInLEpTPXh7t/drjzOMzKGhTUAR5tCzaEsPth0fxivL3efh6IHOazNjbcq8Cj/lWJsAEmAATYAKWTyAh5m+9UWMBqOCNJMQA8tjsgeDnwZhfZz6q5qoKaUWwcaHGItGzk60T5tSaE8Wr4w+Oo7N/ZyESN7ltUuAx38oEmAATYAJMwPIJJMT8rTdqLAAVvJGEGEBtt7ZF0JMgIfJq5Kkhgjs+ff6EYZWHYcLRCSieuThWNVwVxaudN3ei395+KJutLJa6LlXgMd/KBJgAE2ACTMDyCSTE/K03aiwAFbyRhBhAnbZ3womHJzDNcZoox+a02glWsIJ3fW+09WuLrGmzYneL3VG8WndlHUYfHg3HPI6Y6zxXgcd8KxNgAkyACTAByyeQEPO33qixAFTwRhJiAPXc2RMH7x7EOIdxKJqpKFpsaSHO9q1suFIEeqRMlhKUC9DKysrg2eLzizHj5AzQNvGEahMUeMy3MgEmwASYABOwfAIJMX/rjRoLQAVvJCEG0IC9AxBwMwC/Vf4NudLlQq/dvWD3rR28XL1QaXlEhY8jbY4gXcp0Bs9mnpyJhecXop1dOwyuNFiBx3wrE2ACTIAJMAHLJ5AQ87feqLEAVPBGEmIAjQgcgY3XNqJvub7IkCoDxh0ZB6c8TpjjPEcIwPef3mNbs23IkyGPwbMxh8dg7ZW1+LnMz+hRuocCj/lWJsAEmAATYAKWTyAh5m+9UWMBqOCNJMQA+v3o71hxeYUh19/fQX+jRZEWGFFlhNgCppx/Uo5AybX+e/tjx80dYtWwdbHWCjzmW5kAE2ACTIAJWD6BhJi/9UaNBaCCN5IQA2jWqVn459w/Yjv3bdhbbLi2wbCy18K3BS49uwRPZ09Uz1Pd4FmXgC44ev8oJlWfhAYFGyjwmG9lAkyACTABJmD5BBJi/tYbNRaACt5IQgygBUELMPv0bDT7rhkevXskAkLGVB0jvu8W0A2H7x/GxGoT0ahQI4NnkjCcV3sequWupsBjvpUJMAEmwASYgOUTSIj5W2/UWAAqeCMJMYCWX1qOSccmwSW/i6gIcvnZZfzp/KfICfjr/l+x7d9tGFRhEDqU6GDwrO7aurj/9j6W11+OUllLKfCYb2UCTIAJMAEmYPkEEmL+1hs1FoAK3khCDKANVzdg5KGRQvBdeHIBT0OfYnXD1bDLbAfpfGDX77uiT7k+Bs8qeldEaHgo/Jr5wTaDrQKP+VYmwASYABNgApZPICHmb71RYwGo4I0kxADa/u92DNo/SFT1OPPoDL7gC/a02IMsabNg3tl58DzjCY8iHhhVZZTw7F3YO1ReUVl8HT09jALX+VYmwASYABNgAhZLICHmb73BYgGo4I0kxADaf2c/ft71sxB8T94/QTKrZDjV7hSSJ0uOlZdXinJwtfPWxh81/xCe3X1zFy7rXJAqWSqcaHciSoJoBa7zrUyACTABJsAELJZAQszfeoPFAlDBG0mIAUSrfu23tTdYnS1tNuxqsUt8vz1kOwbtG4Ty2ctjicsS8bPzT86j9dbWyP5NduxsvlOBt3wrE2ACTIAJMIHEQSAh5m+9kWMBqOCNJMQAuvXqFhps+H8ql+KZi2NVw1XCC0r1QilfCtkUwka3jeJn0oohVQtZ3Wi1Am/5VibABJgAE2ACiYNAQszfeiPHAlDBG0mIAfTq4ys4+DgYrHbM44i5znPF98HPguHh6yFqA+9tuVf8bNO1TRgeOBxVc1XF/DrzFXjLtzIBJsAEmAATSBwEEmL+1hs53QvAZ8+eoXfv3vD19UWyZMng7u6OWbNmIX369LGyDA0NxYABA7By5Up8+PAB9erVg6enJ7Jnz2645/jx4xgyZAhOnjwpzsVVqlQJU6ZMQenSpWW/o4QYQF++fEHZZWUR/iVc2Bk54IPyAjqvcUZyq+Q43f608GvJ+SWYfnK6SABNiaC5MQEmwASYABNI6gQSYv7WG3PdC0BXV1fcv38f8+fPR1hYGDp16oSKFStixYoVsbLs2bMntm7diiVLlsDGxga9evUS4jEwMFDc8+bNG+TLlw+NGzcWIvDTp08YNWoUDh48iNu3byNlypSy3lNCDSCnVU4i/Qu1/uX7o1PJTuLrj+EfUd67vPg6sHUgrFNZ44+Tf2DR+UWicsjgSoNl+cUXMQEmwASYABNIzAQSav7WE1NdC8BLly6hePHioNW6ChUqCG7bt29H/fr1cefOHeTKlesrli9fvkTWrFmFQPTw8BC/v3z5Muzs7HD48GHY29vjxIkTQkTeunULtrYRefHOnTuHUqVK4erVqyhcuLCsd5RQA8h9szuuPL8ibJxZcyac8zob7LVfYS9KxG1tuhV5rfNiZOBIUS6uT9k+6Fqqqyy/+CImwASYABNgAomZQELN33piqmsBuGjRIrGV+/z5cwMzWq1LkyYN1qxZg6ZNm37Fcvfu3XB2dhb3ZMyY0fB7WvHr27cv+vXrh9evX6NAgQJiZfC3335DeHg4hg4dioCAAAQFBSFFihSy3lFCDaDeu3tj7+2IM34bm2xEoYyFDPZSyhdK/eJd3xuls5ZG7129sffOXpEXkLaLuTEBJsAEmAATSOoEEmr+1hN3XQvAiRMnwsvLC8HBwVGYZcuWDWPGjAFt9UZvtPJH28R09i9yozN+NWvWxOTJk8WPz58/Dzc3N/z777/i+++++w7+/v5iazi2Rn1G7pcGEK0g0qqjtbW1Zu9VKgeX7Zts2OGxQ+QClFrrLa1x/ul5zK01F462jmjr1xZBj4O+WinUzFh+EBNgAkyACTABnRFgAQgkiACkc3eSEIttTND27/r161URgO/fv4eTkxOKFSsmVgFpBXDatGliq5i2m9OmTRujWaNHjxbCM3rTWgCGfw7H1n+34vss36OATYEo5vTc2RMH7x7EOIdxcCvshvrr6+P269tY6rpUVA/hxgSYABNgAkwgqRNgAZhAAvDx48d4+jQiiCG2VrBgQXh7e6uyBbxw4UKx9UvBJRQcQu3jx4/IlCkT6HetWrWK0Sy9rADGxe23A7/B94YvBpQfgB9K/oAqK6rgTdgbbHbb/JVYTOr/ALD/TIAJMAEmkDQJsABMIAEod7hJQSAUtFG+fER0K53Tc3FxMRoE4uPjI1LGUKMtZFrtk4JA5syZA9pevnfvnqE0Gp0tpDODf//9N9q0aSPLRD0OoCnHp2DZxWXoXLIzfirzEyp4RwTPHGx1EDapbWT5xRcxASbABJgAE0jMBPQ4f2vNO0G2gE1xktLAPHz4EH/99ZchDQxFBEtpYO7evSuCPpYuXSpy+VGjs4F+fn4iDQydzaM8gtQOHTokPtNWb5kyZdC5c2fxu8+fP2PSpEki1yCJzpw5c8oyUY8DaEHQAsw+PRvNvmuGLt93EVvAaZKnwbG2x7gOsKy3yhcxASbABJhAYiegx/lba+a6F4CUCJrO6UVOBD179mxDIuiQkBAR0btnzx5xro+alAiaVgEjJ4LOkSOHge+OHTvEeT4KBqFt4LJly2LChAkiTYzcpscBtDp4NcYdGYeatjXxQ4kf0HF7R9hmsIVfMz+5bvF1TIAJMAEmwAQSNQE9zt9aA9e9ANQaiCnP0+MA2nFzB/rv7S8CPtrYtcGgfYNQLls5eLl6meIaX8sEmAATYAJMINES0OP8rTVsFoAKiOtxAB1/cByd/Tsjv3V+tCjaAnQm0CW/C6Y6TlXgKd/KBJgAE2ACTCDxENDj/K01XRaACojrcQBde34NTTc3FWXg3L9zx+ILi9G+eHv8WvFXBZ7yrUyACTABJsAEEg8BPc7fWtNlAaiAuB4H0OuPr1HVp6rwqpZtLey+vduQEkaBq3wrE2ACTIAJMIFEQ0CP87fWcFkAKiCu1wEk1QOmtC8vP7wU27+0DcyNCTABJsAEmAATAPQ6f2v5blgAKqCt1wHkttEN119eN3i2quEqFM9cXIGnfCsTYAJMgAkwgcRDQK/zt5aEWQAqoK3XAdRjZw8E3g00eHao9SFkSJVBgad8KxNgAkyACTCBxENAr/O3loRZACqgrdcBNOPkDCw+v1h4li1tNuxqsUuBl3wrE2ACTIAJMIHERUCv87eWlFkAKqCt1wG0/d/tGLR/kPCsXv56mOY4TYGXfCsTYAJMgAkwgcRFQK/zt5aUWQAqoK3XAfT0/VO4rnfF+0/vMbHaRDQq1EiBl3wrE2ACTIAJMIHERUCv87eWlFkAKqCt5wF09flV3Hx1E855nbkGsIJ3zLcyASbABJhA4iOg5/lbK9osABWQ5gGkAB7fygSYABNgAkwggQjw/A2wAFQw+HgAKYDHtzIBJsAEmAATSCACPH+zAFQ09HgAKcLHNzMBJsAEmAATSBACPH+zAFQ08HgA/a+9cw/WqXrj+IMmcutUKrnkTkpEkaIoKuOS3BJdMBLdJJcuUlGIpJSI+qN0JQZdxDSpiJqGisR0wZRzKKNyS4lK831m9jvvec/e77v3u/e799rnfNfMb36Ts/de6/k8a73ru5/1rLV94ePNJEACJEACJBAJAc7fFIC+Oh47kC98vJkESIAESIAEIiHA+ZsC0FfHYwfyhY83kwAJkAAJkEAkBDh/UwD66njsQL7w8WYSIAESIAESiIQA528KQF8djx3IFz7eTAIkQAIkQAKREOD8TQHoq+OxA/nCx5tJgARIgARIIBICnL8pAH11PHYgX/h4MwmQAAmQAAlEQoDzNwWgr47HDuQLH28mARIgARIggUgIcP6mAPTV8diBfOHjzSRAAiRAAiQQCQHO3xSAvjoeO5AvfLyZBEiABEiABCIhwPmbAtBXx2MH8oWPN5MACZAACZBAJAQ4f1MA+up4+/fvl7y8PMnPz5fKlSv7ehZvJgESIAESIAESCIcABGDNmjVl3759cuKJJ4ZTqWG1lDp27Ngxw9oUm+YUFBRoB2IhARIgARIgARKIHwEEcGrUqBG/hgfQYgpAHxD/++8/2bVrl1SqVElKlSrl40lFb7XeToprdJH2BdpdInkYfRgJ9kArpQ8DxRn6w4q7/wA0VzYi9nXw4EGpVq2alC5dOnTfmVAhBaAJXrBpQ3HPT6B9hnY8D82iDz3AMvRS+tBQx7hsVnH3nyUAsUSLlCumWrnsGC4vowB0CSrsy4r7wKZ9Yfeo4OujD4NnGvYT6cOwiQdbX3H3HwVgsP0l9WkUgLnlm/XTi/vApn1Zdw1jbqQPjXFF1g2hD7NGZ8SNxd1/FIC57WYUgLnlm/XT//77b3nsscfk/vvvl7Jly2b9HFNvpH2mesZ9u+hD96xMvZI+NNUz7tpV3P0HCiXBRnfeDv4qCsDgmfKJJEACJEACJEACJGA0AQpAo93DxpEACZAACZAACZBA8AQoAINnyieSAAmQAAmQAAmQgNEEKACNdg8bRwIkQAIkQAIkQALBE6AADJ4pn0gCJEACJEACJEACRhOgAIzIPbNmzZJp06bJL7/8Is2aNZOZM2dKq1atHFuzcOFCefDBB+XHH3+UBg0ayNSpU6Vz584RtT59tdi9vHjxYvn222/lhBNOkIsvvljb26hRI8cbX3rpJRk0aFChv2P38+HDh42zcfz48TJhwoRC7YJtsNepxMl/sKF27dry008/FTHntttuE/Td1GK6/1avXq3j7YsvvpCff/5ZlixZItdcc03CDHwV4OGHH5YXXnhBvw3apk0bee6553SspStex3EuO3M6G48ePSrjxo2T9957T7Zv367fPu3YsaNMmTJFv4TgVLLp67myMZMPBw4cKPPmzStU/VVXXSUrVqyIhQ8z2ef0tanHH39cxowZY2ujSf5zMy/g937UqFEyf/583f0L/82ePVtOP/10Rx9mO3Zz1U/j9FwKwAi8tWDBArnppptkzpw5cuGFF8qMGTMEAuG7776T0047rUiLPv30U7n00kv1WJiuXbvK66+/roLqyy+/lCZNmkRgQfoqO3XqJNddd520bNlS/vnnHxk7dqx88803smXLFqlQoYLtzRAQd911lzKwCn7w0g38qAzHj+qiRYvkgw8+SDThuOOOkypVqtg2KW7+gxF79uyRf//9N2EP/HfFFVfIRx99JO3bt7cVgCb7b/ny5bJ27Vo5//zzpWfPnkUEIMYTxhcERJ06dfRla9OmTdpny5UrZ+tXr+M41/01nY34ikLv3r1lyJAh+sK5d+9eHW/w8fr169MKQC99PZc2ZvIhBODu3bvlxRdfTDQDL5EnnXSSY7NM8mEm+xAsSC64fvDgwbJ161apW7euowA0xX9u5oVbb71Vli1bJpgP8JJyxx136GfaMHadSjZjN5f9NE7PpgCMwFsQfRBHzz77rNaObwrXrFlT7rzzTrnvvvuKtKhv375y6NAheffddxN/a926tZx33nkqIk0vEBMQtqtWrVIha1cw4EeMGKHRF9MLBODSpUtlw4YNrpoad//BSPgG/e+HH36w/e51nPyHF4vkCCAiCIhHj0fsAAAMh0lEQVSCIfIwevRo9SkEE14+YBdeZuyK13HsqrMEdFGqjXaPXbduna46INJ75plnOgoIL309oOZnfIydfRCA+P1Ae90WU33oxn+IYONbtitXrnQ01+tvlVtuQVyXOi9gzJ166qka4MDLCgpWVRo3biyfffaZYM5LLdmO3SDaXxyeQQEYshePHDki5cuX1whS8hLUgAED9MfrrbfeKtIi/DiPHDlSJ2GrYLkKP3QbN24M2QLv1eENFUtpiKg4RSwx0d58881SvXp1FcQtWrSQyZMnyznnnOO9whzfgR9VLCfiDRXRoYsuukijR06TaNz9hz4LgYQ+iGiuXYmT/1InVyyJ1qtXT7766it9qbJKu3bt9L+ffvrpIiZnM45z3C0LPd6NgEAE+8orr9TfHadvrHrt62HZ6CQA8Zt4/PHHa9Tv8ssvl4kTJ8opp5xi2yyTfZjJf4h01qhRQyPW/fv3TysAvfxWheU/1JM6L3z44YfSoUMHjU7n5eUlmlKrVi2d++6+++4izctm7IZpo+l1UQCG7KFdu3apyMGyIISDVe655x6NkH3++edFWoQfNAz0fv36Jf6GvAjkoeGHwOQCMXf11VfrJLNmzRrHpuIND9Glpk2bavTliSeeEOTEbN68WX/oTCpYevnjjz80pxH5ZPDDzp07dZm7UqVKxcp/MObNN9/USWbHjh2O+WJx8l/q5IqxiJw/jM0zzjgj4b9rr71Wo51YJkwt2YzjMPtwJgGBXCvYfNZZZ8lrr73m2DSvfT0sG+3sQ94YXq6xhL9t2zZ9WalYsaJGj8qUKRMrH2byH/L+kL+JfuiUogCDTfWf3byAyB/ywJH7l1wQpb7ssss07Sm1ZDN2w+qjcaiHAjBkL2UzccRZACKnAz9CEH9ehByS1hH6h+h99NFHQ/aSt+ogbvGW+uSTT2pOTmqJs/9gCxKxYcM777zjGozJ/ivpAhC+6dWrlxQUFMjHH3/sGP2zc3amvu66g/i8MJNAwuOt6BAinYgsxUnEZ7IPwh05udg86KWY4j+7eYEC0Isng7mWAjAYjq6fks2yQ1yXEJHAiyVtRPLwVu619OnTR7C54o033vB6a+jXI6cTuyqxFJxa4uo/2IH8MCSYY1d39+7dPXE11X8leQkY4g+RTYgjLLk5LY+mc3S6vu6pg/i4OJNAsh6NnDIsAw8dOrRIbdn8Fvtosqdb09n3ySefaC41cpCxocdridp/TvMCl4C9etL/9RSA/hl6fgISjxHWtt7eEA6HSMDAcNoE8ueffxaKwOBoFSyXmrgJBIm52NCCRHtEGDIdpWEHELsTkf+Ho24QWTO5YDkY/kO+1PDhw4s0FZtA4uS/ZANg09y5cyU/P1/FuNtisv+cNoFgAwg2gqAcOHBANy5l2gTiZRy7ZRfEdXYCwhJ/SLXAbm6II68lU1/3+rxsr3cjABHhxLhEXiDSUOyK19/ibNvr9b509mGzC9JN0u3edqovSv9lmhesTSB44UeEGgWnQiDamWkTiNex69UfxfV6CsAIPIucImz6wMSKCQTHwCDPCjuesPMQR8QgT9CKJiHPAQnpyPno0qWLnpGEDRKmHgODs+IQzkf0L/nsP2yawLmAKKk2PvLII7rLq379+poviMRl/HDj3Lazzz47Ai85V4kfm27duumyL5b0sSEHb+M4MgSTatz9Z1mOFxNEbrEMj76XXOLmP0x8SDpHad68ub5UIK/o5JNPVpGA/CLYmHwMzNdff13oGBgsI/bo0UNf1FAyjeOwO206G5HbiJ2V+M3Abu7k45XAAEv8KKk2ZurrYdqYzj7YgFxcCIeqVatqDiDyqrFLFpvPcByMnX0m+TBTH0X78WICX06fPl2GDRtWBL/J/nMzL2BpGGdV4sULG5MQSEDBHGgVCELMjRiLKG7Gbpj9NE51UQBG5C0cAWMdBI2dhs8884yeCYiCc9ZwEC8GgVVwTiAOcrUOgkYSsKkHQTsdWIrzufD2amcjdnhhmRFnXWEHH85rw9INJmvTCo4FwbL2b7/9poKvbdu2MmnSJN1JWhz8Z/F+//33Nf8Pb+ENGzYs5IbUPmq6/xCJhuBLLXgRwzizDpN9/vnn9QUEPsVGq2S7MSbRfxEVtUq6cRx2v01nI9rslIaRfLZjqo2Z+nqYNqazD4d241QF7OSG/7BrHTuckT+cLHZN9mGmPgrW6J/YEYvNZ3ihTi0m+8/NvGAdBI0oYPJB0BD1VsFzkucSN2M3zH4ap7ooAOPkLbaVBEiABEiABEiABAIgQAEYAEQ+ggRIgARIgARIgATiRIACME7eYltJgARIgARIgARIIAACFIABQOQjSIAESIAESIAESCBOBCgA4+QttpUESIAESIAESIAEAiBAARgARD6CBEiABEiABEiABOJEgAIwTt5iW0mABEiABEiABEggAAIUgAFA5CNIgARIgARIgARIIE4EKADj5C22lQRIgARIgARIgAQCIEABGABEPoIESMAcAtYXFfbu3St5eXmhN2zlypX6uTh8r7VMmTJp61+xYoV+/xufaCtdunTobWWFJEACJZcABWDJ9T0tJ4HYEXD6nJRlCL7LPHbsWPn999/1E2CZrs8FAHzGcOTIkXL99de7enzLli1l+PDhcuONN7q6nheRAAmQQBAEKACDoMhnkAAJhEIA34q2yoIFC+Shhx7SbxVbpWLFioL/RVXWrFkjXbt21W9alytXzlUzZs2apd8jXrdunavreREJkAAJBEGAAjAIinwGCZBA6AQgmkaMGCH79u0rVHfqErB13auvviqjRo2S/Px86dy5s7z88suycOFCQdRw//79GoF76qmnEsu2+Bj9Aw88IPgwPepo0qSJTJ06Vdq3b+9oK5Z+d+/erc+1ysaNG7Wd69ev14hkgwYNZO7cuXLBBRfoJTt27JBatWrJ1q1bpV69eqFzZIUkQAIlkwAFYMn0O60mgdgT8CIAb7nlFhVuEHAHDx6Unj17CpZqkSMIAbh9+3bp1auXisK+ffsqmyFDhsiWLVtkypQpUq1aNVmyZImMGzdONm3apCLOrjRr1kz69+8v9957b+LPEI7NmzdXMYmcwA0bNkjDhg0F11qlatWqWs/AgQNj7xcaQAIkEA8CFIDx8BNbSQIkkELAiwAcNGhQoQjbsGHD5JVXXtFonbVk3KlTJ6ldu7bMmTNHo3J169bV/4f4s0rHjh2lVatWMnnyZFt/QFDOnDmzUD5f5cqV9d8GDBjg6MMWLVpI9+7dVYyykAAJkEAYBCgAw6DMOkiABAIn4EUA3n777XLo0KFEGyC0Fi1aJJs3b078GwQaooOLFy+WZcuWaS5fhQoVCrUby8KIHiL/0K6ULVtWsNTcp0+fxJ/Hjx8vkyZNknbt2gkEJP6WutTbpk0badu2rUYoWUiABEggDAIUgGFQZh0kQAKBE/AiAFNzBSHKli5dqsuxVsHyK3L98O8QeNjFC4GYepQLIoZYsrUr1atX1ygelpyTy/fff6+icvny5bJq1SqZP3++9OjRI3FJ48aNZfDgwTJ69OjAOfGBJEACJGBHgAKQ/YIESCCWBHIpACHYGjVqJKtXr5ZLLrnENR9EDevXry8zZsxwvKdfv34ajXz77bf1msOHDwuWiSEOO3To4LouXkgCJEACfghQAPqhx3tJgAQiI5BLAQijbrjhBlm7dq1Mnz5dN3Hs2bNHcMhz06ZNpUuXLrZ2I9dv3rx5uuMX5a+//pIxY8ZI7969pU6dOlJQUKC5gNhwYi33Ytdyt27dNB+xfPnykfFkxSRAAiWLAAVgyfI3rSWBYkMg1wLw6NGjMnHiRN0ZvHPnTqlSpYq0bt1aJkyYIOeee64tRxxAjWVgLC0jgnjkyBEVfBCSEHh4BnIIp02bljgncOjQoXo8DDafsJAACZBAWAQoAMMizXpIgARKBAFE/A4cOKBn/WUqv/76qwpFRAwRIWQhARIggbAIUACGRZr1kAAJlAgC2Egye/Zs/cZvpu/7Qvht27YtcfZgiQBEI0mABIwgQAFohBvYCBIgARIgARIgARIIjwAFYHisWRMJkAAJkAAJkAAJGEGAAtAIN7ARJEACJEACJEACJBAeAQrA8FizJhIgARIgARIgARIwggAFoBFuYCNIgARIgARIgARIIDwCFIDhsWZNJEACJEACJEACJGAEAQpAI9zARpAACZAACZAACZBAeAQoAMNjzZpIgARIgARIgARIwAgCFIBGuIGNIAESIAESIAESIIHwCFAAhseaNZEACZAACZAACZCAEQT+BwY1Nx8TSoJPAAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plt.figure()\n",
    "# plt.plot(tspan, control_lqr)\n",
    "# plt.plot(tspan, static_u, ':')\n",
    "# plt.show()\n",
    "\n",
    "plt.figure()\n",
    "plt.plot(tspan, sensor_output[:, lst])\n",
    "# plt.plot(tspan, sensor_out_static[:,lst], ':')\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.ylabel(\"Sensor Output (V)\")\n",
    "plt.show()\n",
    "plt.savefig(sensor_fname)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# # sys.stdout.close()\n",
    "\n",
    "# # storing the data\n",
    "# storage = {\"displacements_u\":displacements_u, \"velocities_u\": velocities_u,\n",
    "# \t\t\t\"displacements_lqr\": displacements_lqr, \"velocities_lqr\": velocities_lqr,\n",
    "# \t\t\t\"time\": tspan, \"norm_D_u\": norm_D_u, \"norm_V_u\":norm_V_u, \"norm_D_lqr\":norm_D_lqr,\n",
    "# \t\t\t\"norm_V_lqr\":norm_V_lqr, \"Frequencies\":Frequencies, \"Xmap\":Xmap,\n",
    "# \t\t\t\"Ymap\":Ymap}\n",
    "\n",
    "# directory = \"Data\"\n",
    "# if not os.path.exists(directory):\n",
    "# \tos.makedirs(directory)\n",
    "# storage_file = \"{}_{}_{}_{}_{}_FEA_plate_storage\".format(controller, now.year, now.month, now.day, now.hour)\n",
    "# filename = os.path.join(directory, storage_file)\n",
    "# # TPL.savemat(filename, storage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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
}