analyze-fa-acrobot.ipynb

{"cells":[{"cell_type":"code","execution_count":1,"metadata":{},"outputs":[],"source":["import torch, time, sys\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import scipy.integrate\n","solve_ivp = scipy.integrate.solve_ivp\n","\n","EXPERIMENT_DIR = './experiment-fa-acrobot/'\n","sys.path.append(EXPERIMENT_DIR)\n","\n","from data import get_dataset, arrange_data\n","from nn_models import MLP, PSD, MatrixNet\n","from symoden import SymODEN_T\n","from utils import L2_loss, from_pickle\n","import imageio\n"]},{"cell_type":"code","execution_count":2,"metadata":{},"outputs":[],"source":["DPI = 600\n","FORMAT = 'pdf'\n","LINE_WIDTH = 2\n","\n","def get_args():\n","    return {'num_angle': 2,\n","         'nonlinearity': 'tanh',\n","         'name': 'acrobot',\n","         'seed': 0,\n","         'save_dir': './{}'.format(EXPERIMENT_DIR),\n","         'fig_dir': './figures',\n","         'num_points': 4,\n","         'gpu': 0,\n","         'solver': 'rk4'}\n","\n","class ObjectView(object):\n","    def __init__(self, d): self.__dict__ = d\n","\n","args = ObjectView(get_args())\n","\n"]},{"cell_type":"markdown","metadata":{},"source":[" ## Load models"]},{"cell_type":"code","execution_count":3,"metadata":{},"outputs":[],"source":["device = torch.device('cuda:' + str(args.gpu) if torch.cuda.is_available() else 'cpu')\n","def get_model(args, baseline, structure, naive, damping, num_points):\n","    M_net = PSD(2*args.num_angle, 400, args.num_angle).to(device)\n","    g_net = MatrixNet(2*args.num_angle, 300, 4, shape=(2,2)).to(device)\n","    if structure == False:\n","        if naive and baseline:\n","            raise RuntimeError('argument *baseline* and *naive* cannot both be true')\n","        elif naive:\n","            input_dim = 3 * args.num_angle + 1\n","            output_dim = 3 * args.num_angle\n","            nn_model = MLP(input_dim, 1200, output_dim, args.nonlinearity).to(device)\n","            model = SymODEN_T(args.num_angle, H_net=nn_model, device=device, baseline=baseline, naive=naive, u_dim=2)\n","        elif baseline:\n","            input_dim = 3 * args.num_angle + 1\n","            output_dim = 2 * args.num_angle\n","            nn_model = MLP(input_dim, 800, output_dim, args.nonlinearity).to(device)\n","            model = SymODEN_T(args.num_angle, H_net=nn_model, M_net=M_net, device=device, baseline=baseline, naive=naive, u_dim=2)\n","        else:\n","            input_dim = 3 * args.num_angle\n","            output_dim = 1\n","            nn_model = MLP(input_dim, 600, output_dim, args.nonlinearity).to(device)\n","            model = SymODEN_T(args.num_angle, H_net=nn_model, M_net=M_net, g_net=g_net, device=device, baseline=baseline, naive=naive, u_dim=2)\n","    elif structure == True and baseline ==False and naive==False:\n","        V_net = MLP(2*args.num_angle, 300, 1).to(device)\n","        model = SymODEN_T(args.num_angle, M_net=M_net, V_net=V_net, g_net=g_net, device=device, baseline=baseline, structure=True, u_dim=2).to(device)\n","    else:\n","        raise RuntimeError('argument *structure* is set to true, no *baseline* or *naive*!')\n","\n","    if naive:\n","        label = '-naive_ode'\n","    elif baseline:\n","        label = '-baseline_ode'\n","    else:\n","        label = '-hnn_ode'\n","    struct = '-struct' if structure else ''\n","    path = '{}/{}{}{}-{}-p{}.tar'.format(args.save_dir, args.name, label, struct, args.solver, args.num_points)\n","    model.load_state_dict(torch.load(path, map_location=device))\n","    path = '{}/{}{}{}-{}-p{}-stats.pkl'.format(args.save_dir, args.name, label, struct, args.solver, args.num_points)\n","    stats = from_pickle(path)\n","    return model, stats\n","\n","symoden_ode_struct_model, symoden_ode_struct_stats = get_model(args, baseline=False, structure=True, naive=False, damping=False, num_points=args.num_points)\n","\n"]},{"cell_type":"code","execution_count":4,"metadata":{},"outputs":[],"source":["# time info for simualtion\n","time_step = 400 ; n_eval = 400\n","t_span = [0,time_step*0.05]\n","t_linspace_true = np.linspace(t_span[0], time_step, time_step)*0.05\n","t_linspace_model = np.linspace(t_span[0], t_span[1], n_eval)\n","# angle info for simuation\n","q10 = 0.0 ; q20 = 0.0\n","u10 = 0.0 ; u20 = 0.0\n","\n","# record video\n","import gym\n","from gym import wrappers\n","env = gym.make('My_FA_Acrobot-v0')\n","env = gym.wrappers.Monitor(env, './videos/' + 'acrobot-fa' + '/', force=True) # , video_callable=lambda x: True, force=True\n","\n","env.reset()\n","env.env.state = np.array([q10, q20, 0.0, 0.0], dtype=np.float32)\n","obs = env.env._get_ob()\n","y = torch.tensor([obs[0], obs[2], obs[1], obs[3], obs[4], obs[5], u10, u20], requires_grad=True, device=device, dtype=torch.float32).view(1, 8)\n","\n","t_eval = torch.linspace(t_span[0], t_span[1], n_eval).to(device)\n","\n","y_traj = []\n","y_traj.append(y)\n","frames = []\n","for i in range(len(t_eval)-1):\n","    frames.append(env.render(mode='rgb_array'))\n","\n","    cos_q_sin_q, q_dot, u = torch.split(y, [4, 2, 2], dim=1)\n","    V_q = symoden_ode_struct_model.V_net(cos_q_sin_q)\n","    dV = torch.autograd.grad(V_q, cos_q_sin_q)[0]\n","    dVdcos_q, dVdsin_q= torch.chunk(dV, 2, dim=1)\n","    cos_q, sin_q = torch.chunk(cos_q_sin_q, 2,dim=1)\n","    dV_q = - dVdcos_q * sin_q + dVdsin_q * cos_q # (1, 2)\n","    g_q = symoden_ode_struct_model.g_net(cos_q_sin_q) #(1, 2, 2)\n","    # H, dH = symoden_ode_struct_model.get_H(y)\n","    # dHdcos_q, dHdsin_q, dHdp= torch.split(dH, [2, 2, 2], dim=1)\n","\n","    g_q_T = torch.transpose(g_q, 1, 2)\n","    inv_g_g_T = torch.inverse(torch.matmul(g_q, g_q_T))\n","    g_T_inv_g_g_T = torch.matmul(g_q_T, inv_g_g_T)\n","\n","    energy_shaping = 2 * dV_q.T\n","    damping_injection = -1 * q_dot.T\n","\n","    u = torch.matmul(g_T_inv_g_g_T, energy_shaping+damping_injection)\n","    u = u.squeeze().detach().cpu().numpy()\n","\n","    obs, _, _, _ = env.step(u)\n","    y = torch.tensor([obs[0], obs[2], obs[1], obs[3], obs[4], obs[5], u[0], u[1]], requires_grad=True, device=device, dtype=torch.float32).view(1, 8)\n","\n","    y_traj.append(y)\n","\n","env.close()\n","# imageio.mimsave('./videos/acrobot-fa/acrobot-fa.gif', frames, duration=0.02)\n","\n","y_traj = torch.stack(y_traj).view(-1, 8).detach().cpu().numpy()\n","\n"]},{"cell_type":"code","execution_count":5,"metadata":{},"outputs":[{"data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAG34AAALQCAYAAADbfYewAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAABcRgAAXEYBFJRDQQAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdsW3cShSGUXKxgJ07tTPFTqYA9+BuVIHqUgHTgTPHLsARX+AnQE9P8l1qh3NnyXNSrcAb/iKE/eZlWZYJAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAN52yDwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABid8BsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBA+A0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAg/AYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQfgMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIvwEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAASE3wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALCbwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHhNwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIDwGwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQED4DQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICD8BgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBB+AwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAi/AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABITfAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAsJvAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAeE3AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAgPAbAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQPgNAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIPwGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEH4DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICL8BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEhN8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwm8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB4TcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICA8BsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBA+A0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAg/AYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQfgMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIvwEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAASE3wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALCbwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHhNwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIDwGwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQED4DQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICD8BgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBB+AwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAi/AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABITfAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAsJvAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAeE3AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAgPAbAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQPgNAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIPwGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEH4DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICL8BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEhN8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwm8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB4TcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICA8BsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBA+A0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAg/AYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQfgMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAicsw/Yyq9fv6bHx8eLPvvly5fpw4cPG18EAHDbfv/+Pf38+fOiz3779m369OnTxhcxTXYvAEBrdu+Y7F4AgLbs3jHZvQAAbdm9Y7J7AQDasnvHZPcCALRl947J7gUAaMvuHZPdCwDQlt07JrsXAKAtu3dMdi8AQFt27x+7Db89Pj5O9/f32WcAABzSw8PD9P379+wzDsHuBQDIY/f2Y/cCAOSxe/uxewEA8ti9/di9AAB57N5+7F4AgDx2bz92LwBAHru3H7sXACCP3duP3QsAkMfu7cfuBQDIs+fde8o+AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYHTCbwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHhNwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIDwGwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQED4DQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICD8BgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBB+AwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAi/AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABITfAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAufsA7by+fPniz/78PAw3d3dbXgNAMDt+/Hjx3R/f3/RZ9dsMa5j9wIAtGX3jsnuBQBoy+4dk90LANCW3TsmuxcAoC27d0x2LwBAW3bvmOxeAIC27N4x2b0AAG3ZvWOyewEA2rJ7x2T3AgC0Zff+sdvw28ePHy/+7N3d3fT169cNrwEAOJY1W4zr2L0AAHns3n7sXgCAPHZvP3YvAEAeu7cfuxcAII/d24/dCwCQx+7tx+4FAMhj9/Zj9wIA5LF7+7F7AQDy2L392L0AAHn2vHtP2QcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACMTvgNAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIPwGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQEH4DAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICL8BAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEhN8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACwm8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB4TcAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICA8BsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBA+A0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAg/AYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAQfgMAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIvwEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAASE3wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALCbwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHhNwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgIDwGwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAQED4DQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAICD8BgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEBB+AwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACAi/AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABM7ZBwAAAAAAAAAAAAAAAAAAAAAAAAAAHM1c67SUkn0GAAAAAAADm2vt9izvrAEuI/wGAAAAAAAAAAAAAAAAAAAAAAAAALChnl/MCwAAW3pt24pDAAAAAEci/AYAAAAAAAAAAAAAAAAAAAAAAAAA0IjIGwAAe2LfAgAAAPyX8BsAAAAAAAAAAAAAAAAAAAAAAAAAwDtcG8GYa52WUhpdAwAA1xF5AwAAAIgJvwEAAAAAAAAAAAAAAAAAAAAAAAAABEQwAADYk5b7VtAYAAAAOJJT9gEAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACjO2cfAAAAAAAAAAAAAAAAAAAAAAAAAAAwmrnW7BMAAKAJ2xYAAACgHeE3AAAAAAAAAAAAAAAAAAAAAAAAAIB/iWIAALAXti0AAABAe6fsAwAAAAAAAAAAAAAAAAAAAAAAgHZ8mTMAwG2x3wAAAAAAAOB2nLMPAAAAAAAAAAAAAAAAAAAAAAAA2oriIUspnS4BALg9T1tJkA0AAC73tJ+9ewQAAAD2TvgNAAAAAAAAAAAAAAAAAAAAAAAORhgOAAAAAAAAAABgvVP2AQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAKM7Zx8AAAAAAAAAAAAAAAAAAAAAAACMZa71zZ8tpXS8BAAAAAB4r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visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 4)\n","    ax.imshow(frames[60])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 5)\n","    ax.imshow(frames[80])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 6)\n","    ax.imshow(frames[100])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 7)\n","    ax.imshow(frames[120])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 8)\n","    ax.imshow(frames[140])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 9)\n","    ax.imshow(frames[160])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","    ax = plt.subplot(1, 10, 10)\n","    ax.imshow(frames[180])\n","    plt.setp(ax.get_xticklabels(), visible=False)\n","    plt.setp(ax.get_yticklabels(), visible=False)\n","\n","    plt.tight_layout()\n","\n","    fig.subplots_adjust(hspace=0, wspace=0)\n","\n","    # fig.savefig('{}/fig-fa-acrobot-frame.{}'.format(args.fig_dir, FORMAT))\n"]},{"cell_type":"code","execution_count":6,"metadata":{},"outputs":[{"data":{"image/png":"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wHEmSJEmSJEmSJEmSJKlUhZbxAcybB0OGhOcUmwULwjMs4xPAl74E55wDDYE7t951l2V8rfWXv8Cf/hQn68IL4+RIkiRJkiRJkjaeZXyKobm2gHx9nDV3nFV5mUIlIUmav4/yo2vXlOrqeoYPb2DYsAZqahoYNaqe6uoGOnYcDAwGPl/oMaU25YknKjj66LCMsWNv5LLLro4zUI4cckgvnnsuJKEHr7wynwED0lgjKQcmTOjClVeGZXTqlPLaa7fSvfutcYZSu3TaaSt48MFYhVGd2WKLF/njHxfRq5fPMfm0YgVcdll3Jk7skpfjVVfXc+uty/jEJ84CzsrLMVU4dXXw+ONLmDixC08/XVHocYpIpw+XJEmSJKmt82eokiRJUvv2n//AH/8YntOvHxx8cHiO2r9YZXySJEmSJEmSJEmSJEmSWi9GGd/cuZbxrUt5OfTqFWcWtW0DBsD++8NvfxuW8/zz2fmeo0bFmauUXHVVnJx994VPfCJOliRJkiRJkiRp41nGpxjqmrk9Xx9nHZu5vbk582k+8J88HKcad7TPibKyQk9QWjp1gqFDoaYGttwyWyNGZJeDBiUkSUeafwqQ1FLbbx+eMXduV/r37xoelENbbUVgGR8sWtSPrbeOM49y409/Cs/43OcSqqr6hwepXbvzTnjhBXjnnTh5b7xRzvnn9+PBB33tmS+zZsHhh8NLL+XneCefDDfe2IHu3fvk54AqCiefnK2ZM+Gee2DiRJg9u9BTSXElCfTuDT17Qpcu0LXrR9fq93Xpkn2/X1aW/ZLA+i7TFOrrs7VqVdP1Nd9euRKWL4cPPlj/ZW1tof9mJEmSJEmSJElq2266KU7OCSdkPyOQmjNsWHiGZXySJEmSJEmSJEmSJElSmFhlfO1RaBlf377uK6MmJ58cXsYHcPfd8L3vheeUksmT4dFH42RddFGcHEmSJEmSJElS61jGpxhWNXN7RV6maENlfGmaTgAm5Po4SZK8CozK9XFKUZIUeoL2ZXXZ3vrWgAGeLCDl09Ch4RkzZ4Zn5FpNTXjG9Omw++7hOcqNBQvCCxcBDj00PEPtX9++WanWPvvEy5w0Ca67Di6+OF6m1u3hh+HLX4bFi3N/rJ494Y474Mgjc38sFa9hw+DKK2HcuOxr1cSJcP/9sHRpoSeTPq5vXxg4EAYNyi4HDoR+/aBPn2xtsknT9T59sue5YvwevqEh+xxbvDhbS5Z8/PqiRdlryAULYP78pkuL/CRJkiRJkiRJpW7RouxnWqGSBE4/PTxHpaG6OjyjLZzHJkmSJEmSJEmSJEmSJBUzy/jWL7SMr1+/OHOofTjwwGzPxXnzwnImToSrr4aKfO0C2w6MHx8nZ/vtYfToOFmSJEmSJEmSpNaxjE8xvN/M7d3zMgX0aOb25uaUWswyvpbr1w823TRbgwc3XV/z7b59i3OjfqlUde6cfX6+807rM2bNijdPrgwfHp4xbVp4hnLnkUegsTEso6wMDjoozjxq/0aPhgsugO99L17mpZfCLrvAZz4TL1NN6uvhssvgmmvyc7xPfhJ+9jOoqsrP8VT8yspgjz2yddNNWQnnxInw+ONZcZiUS0mSve7fYouPrsGDm4r3KivbzwnW5eVNhYEba/nyrJRvzYK+NS/nzoU5c5pWXV38+SVJkiRJkiRJKqS77oLa2vCcAw+MU7Cm0tCjB/Tvn/1MprVmzIg3jyRJkiRJkiRJkiRJklSKLONbtzS1jE9xdewIX/5y+N5F8+fD734HhxwSZ6727pVX4MEH42RdeKH7lEqSJEmSJElSoVnGpxjea+b2nnmZovnjNDen1GKlWhyXJNC7d7Zx/SabwIAB2aqsbLq+5urXr/1s2i+VmmHDwsr4FiyAZcuyDZGKVU1NeMb06eEZyp2HHgrP2GOPrDRWaqmrroI//hH++c84eY2N8KUvwQsvuCFhbHPmwFFHwdNP5+d4558P3/lOduKjtC5dusCRR2Zrzhz4+c+zYr5YzycqTX36ZK97a2qyryNVVU2le5tt5vfsLdW1a9PfW3PSFN57L/s8fvfdpss1r6++XLIk97NLkiRJkiRJkhSqvh5uuSVO1tixcXJUOqqrw8r45s0r/vPYJEmSJEmSJEmSJEmSpGJmGd+6LV8OK1aEZfTvH2cWtR8nnxxexgdw112W8bXU+PFxcqqr4Ygj4mRJkiRJkiRJklrPMj7FsLCZ23vnZQro1cztzc0ptViSFHqC1unWDbp3zy5XX+/RI9ucf11rdfHe6tWzZ+kWEUqlpqoKnn02LGPWLNh22zjz5MKwYeEZ06aFZyg3VqyAxx8PzxkzJjxDpaVTJ/jZz2DHHaG2Nk7mwoVw4IHw179mr88U7k9/gmOOyc/Juj17wo9/DIcemvtjqf0YOBDOOy9b06fDr38NDzwAL75Y6MlUjLp3h622airdq6mB4cOzy002KfR0pSdJsjLnvn1h6603fN/a2o8X9K2rvG/ePGhoyM/8kiRJUoi2+jNUSZIkSRv28MPwxhvhOaNGwejR4TkqLdXV8PzzYRkzZ8J228WZR5IkSZIkSZIkSZIkSSo1lvGt24IF4Rn9+oVnqH3Zaiv41KeyfYZCPPoo/Pe/sOmmceZqr6ZOhV/+Mk7WJZdAB3d4liRJkiRJkqSC879qFUNzPwrslCRJ7zRNF+dqgCRJNgEqmrmbZXyKZsCAbEP1JMlWWdnHr7f0fWtf79gRKiqyIpeKinWvdd3WuXO2Af/aZXurL7t0cQNMSS0Xo6hu5sziLuPr1g0GD4Z33ml9xvTpkKY+vxajJ5+EDz4IzznooPAMlZ6ttoLvfx9OPz1e5pQpcMQR8MgjnnQVoqEBrroKrrwye/7Ote22ywrUhg/P/bHUfg0fDhdfnK3Zs5uK+UI3nFTb0717tkntqFHZ/0lsvXV2fcgQX4+2VV26ZEXoVVUbvl9DQ1bOO2dO82vRovzMLkmSJEmSJEkqHddfHydn7Fh/pqGNF+M8thkzLOOTJEmSJEmSJEmSJEmSWmuTTaC8PPud59ayjG/dLOPTupx8cngZX2Mj3HFHtseO1u/qq+PsQbT55nD88eE5kiRJkiRJkqRwbuGvGN5swX0qgZyV8X2Y35yWzCm1yOmnxy1XkaRi01wZREvMnBmekWs1NWFlfMuWwbx5UNmSVyLKq0mTwjO22ir7GJFa47TT4NFH43wsrvaHP2SbE06Y4AaFrTF3Lhx7LDzxRH6Od8opcPPNWdGSFMvQoXD++dl6+234zW+yYr5nn81PwaTyw9I9ra28HAYMyFZzhecrV2Zf89ZV1Dd3bvZLHfPnZ5cLF2Yn0Uv50KFDtjp2bLq+9ttrXy8ry573Wrpg/bc1Nq5/NTS0/P319bBqVdPlmqu+vrB/x5IkSZIkSVIuPPssPPdceE7v3nDcceE5Kj3V1eEZbeE8NkmSJEmSJEmSJEmSJKlYlZVB//7Z7yu3lmV862YZn9blyCPhnHNg+fKwnNtug0sugc6d48zV3rz2Gtx7b5ysiy+Gioo4WZIkSZIkSZKkMJbxKViapu8nSbIQ6LuBu20BTM3hGEObuX1emqYf5PD4kiS1K8OGhWfMmhWekWvDh8PTT4dlTJ9uGV+xSdM4BWhjxoRnqHQlCdx9N+ywA7wZsRb8ttuyosizz46XWQqeegqOPjrsxN6W6twZbr0VTjop98dSadtss6ygc+zYrFjrscfgkUeyy8WLCz2dWmJ9pXubb579QoLUGp06ZcWNQ4Y0f9+Ghuz5Ys2CvnVdLlwIS5Zk9128GOrqcv/nUDxJkpUDd+6crTWvr/12rNs6dvxosV55eWmUiabphsv61i7uW99tdXVNa0Nvb8x9W5IlSZIkSZIkrct3vhMn59RToVu3OFkqLTHK+GbMCM+QJEmSJEmSJEmSJEmSSlllpWV8a5s/PzzDMj6tS48ecMQR8JOfhOXMnw+/+AWceGKMqdqfK66AxsbwnIED4eSTw3MkSZIkSZIkSXFYxqdYZrHhMr4a4Pc5PP7wZm5vA3VAkiQVj6qq8IyZM8Mzcq2mJjzj9ddht93CcxTPSy/BO++E51jGp1B9+8IDD8Duu8ctrTn3XBg0CA4/PF5me9XYCFdfDePGxTn5rTnDh2f/5tttl/tjSWvq3x+OPz5b9fXw/PPw+OPwxBPwt79lhVsqnG7dPl64t/XWlu6p8MrLs9crffvCiBEtf9yKFU3FfIsXf7Sob+3ry5fDBx989HLN6ytX5u7PVyySJCtJ7NQpK6pbfX3tt1cX2sUoxFvzeseOpVGEVwySpKmIsK1ZXSSYj+K/1hQFNjZmr2dWrw29nY/X/e1NkjStsrKPvt0e3gfZx/ial+t63/ouc3HfNM0+Vte+zPX1NeeUJEmSJKkl/v1veOSR8JyyMjjzzPAclSbL+CRJkiRJkiRJkiRJkqTCq6wMe/x772W/L9gWfwdzfRYsCM+wjE/rc8op4WV8ADfcACec4O+br+1f/4L774+TdcEF2e/3S5IkSZIkSZKKg2V8iuVVYKcN3L4R2zm3SnP5r+b4+JIktSuDB0NFRVh51Kw2UIU7vLk63xaYOjU8Q3FNmhSe0b8/7LpreI60887ZSWlnnBEvs7ERjjkGuneHz38+Xm57M28eHHcc/OEP+TneoYfC3XdDr175OZ60Ph06ZCWgu+8O3/42LF0KTz8Nf/xjdvnvf1vCkSu9e8NWWzUtS/fUXnXuDAMHZitUfT3U1n68sG/Vqpav1WVdq1a1boY0zZ47W7MqKpoK9dYs1lvzumV4agvWLBLs1q3Q04RZXXTW0vK+1Y9Z+7Kl5Wsb+9h1lce1pGAuV4/x+an05KoAsKW3r11G2Jq3i/G+6/p7Xt/ff+j7iz3b5xVJkiSpffnud+PkfPGLsMUWcbJUegYOzDapqa1tfYZlfJIkSZIkSZIkSZIkSVKY0DI+yPYB2XTT8JxiYRmfcmm33WDLLeH118Ny/vWvbK+RvfeOMla7MW5cnJy+feFrX4uTJUmSJEmSJEmKwzI+xfIScMIGbv9Ejo+/QzO3/yPHx5ckqV0pK4OhQ8NOxJg1q2mT8WJVUxOeYRlf8YlRxnfggVBeHp4jQXbC1HPPwX33xctctSorf/v977PCLX3Un/8MRx8N77yT+2N16ADXXgvnnlvcX/NUunr2hIMOyhbAkiXw17/CM89ka/LkrPhKLTd48EdL91avykqfB6SN1aED9OiRLUmKYc3iuY4dCz2NVHySxP/zkiRJkiS1zMyZ8MtfxskaOzZOjkpTksCwYfDqq63PeOMNqK/Pfi4hSZIkSZIkSZIkSZIkaePFKOObO9cyvrVZxqf1SRI4+WT4xjfCs2680TK+Nf397/DQQ3Gyvv516NYtTpYkSZIkSZIkKQ5/pVyxvNTM7dsnSVKepmlD7AMnSdIB2K6Zu1nGJ0nSRho2LKyMb8UKmDMHBg2KN1Nsw4eHZ0yZEp6heN58E/75z/CcMWPCM6TVkgRuvz372AzZHG5ttbVwwAHw5JOwQ3P15CVi1Sq44gr47nehsTH3xxs8GO6/H3bbLffHkmLp1Qs+//lsQbbp5JQp2cmiL76YXb7ySvYcU8q6dMleD1dXw8iRTYV7I0dmf4eSJEmSJEmSJEnt2XXXxfmZ67bbwp57hueotFVXh51v0dCQnVM0bFi8mSRJkiRJkiRJkiRJkqRSEquMrz2xjE+5duKJ8L//C3V1YTkPPQQzZ3oO3WqXXx4np1cvOPPMOFmSJEmSJEmSpHgs41MsLwIrgM7rub07sCPwtxwcexeg6wZuXwFMzsFxJUlq16qqwjNmzizuMr6uXWGLLeCNN1qfMWNGVv7UsWO8udR6Dz8cntGpE+y7b3iOtKZu3eCBB2DnneH99+PlLl0K++0HTz8No0bFy22Lpk2DY4/NisTyYfRo+NnPYMCA/BxPypUOHWCbbbJ10knZ+xoastdxL7+crVdeyUqap0+H5csLO29MAwZkG3dWVzcV762+HDgwK1OVJEmSJEmSJEkqNXPmwI9/HCfrwgv9mYvCVVeHZ8yY4UZCkiRJkiRJkiRJkiRJUmtZxvdxoWV8nTpl+9FI61NZCUcdBRMnhuWkKdx8M/zgB3HmasueeQYefzxO1tixWSGfJEmSJEmSJKm4WManKNI0XZEkyXPA6A3cbV9yU8a3TzO3P5Om6YocHFeSpHYtxuZDs2bBbruF5+TSyJFhZXyrVmV/zi23jDeTWm/SpPCMffbxRDXlxsiRcM89cNhhcXMXLIA998xO9Npxx7jZbUGawt13Zyeo5ask7PLLYdw4KC/Pz/GkfCsvh5qabB16aNP70xTeeScrv5w+Hd58E956q2m9/XZxlPV16QKDB8OmmzZdrnl98OBsde5c6EklSZIkSZIkSZKKzw03wMqV4TlbbAFHHhmeI8Uq49t33/AcSZIkSZIkSZIkSZIkqRRZxvdxoWV8/ftDksSZRe3XOeeEl/EB3HUXXHkl9OwZntVWpSlcdlmcrF694Lzz4mRJkiRJkiRJkuKyjE8x/YENl/EdCozPwXEPb+b23+fgmJLTbAsBAAAgAElEQVQktXsxyvhmzgzPyLURI7ICqxBTpljGVwyWLoUnnwzPOfjg8AxpfQ49FK6+Gi69NG7uwoXwmc/Ab3+bFfOVinfegdNOy/7c+bDJJnDvvbD//vk5nlRskqSp2G7vvdd9nw8+gPnzm9aCBbBsWfZ1eunS7Pr770NdXbZWrsxWQ0OWv/pk8SSBjh2hU6dsde6cXfbsCb17Q58+2eXa13v3tmRPkiRJkiRJkiSptRYvhttui5N14YXZz3ukUDHOY5sxIzxDkiRJkiRJkiRJkiRJKlWW8X1caBlfv35x5lD7tsMO2V5Cf/5zWM6yZfCTn8DYsVHGapMefzz873G1Cy7I9jqRJEmSJEmSJBUfy/gU0wPAdzdw+w5JkoxI03RqrAMmSbIN8D8buEv64VySJGkjVVWFZ8yaFZ6RayNHhmdMjfbqRiEefxxWrQrPOfDA8AxpQ77xjazEc+LEuLnLlsF++8Gvfw1f+ELc7GKTpvDTn8I552SbQebDLrvAr34FQ4bk53hSW9WtW7aGDi30JJIkSZIkSZIkSdpY3/8+LF0antO/P5x0UniOBFBdHZ4xc2Z4hiRJkiRJkiRJkiRJklSqLOP7qDS1jE/5c845cUrkfvADOP106NgxPKutqa/PCvRi6Ns3+zeRJEmSJEmSJBWnskIPoPYjTdMZwPPN3O3syIcd28ztf0nTdHbkY0qSVBKGDQvPaAubGMUo45syJTxD4SZNCs/YZRcYNCg8R9qQJIE77oDddoufvWIFHHww/Oxn8bOLxTvvwJgxcMIJ+SviO/tseOYZi/gkSZIkSZIkSZIktV8LFsANN8TJOvdc6No1TpY0dCiUBf7Ww4wZUUaRJEmSJEmSJEmSJEmSSlK/ftl+KSHaUxnfkiXQ0BCWYRmfWurgg7Pz6ELNng0TJ4bntEV33w2vvhon6xvfgB494mRJkiRJkiRJkuKzjE+x3d3M7SclSRKl3iRJks2A45u5209iHEuSpFLUqxf06ROWMWtWnFlyacSI8AzL+Aqvvh5+97vwnDFjwjOklujUCR58EKqq4mfX18Oxx2YnboWeuFlMGhrglltgq63gt7/NzzF79IBf/AJuugkqKvJzTEmSJEmSJEmSJEkqhOuug2XLwnN69IAzzgjPkVarqIDNNw/LmDED0jTOPJIkSZIkSZIkSZIkSVKp6dAhvDxu3rw4sxSDBQvCMyzjU0uVl8PZZ8fJuuoqqKuLk9VWLFsG//u/cbIGDvQcWUmSJEmSJEkqdpbxKbafAhv6UWdX4LuRjnUN0HkDt8/9cB5JktRKw4aFPf7tt2Hlyjiz5MqgQdkmYCGmTo0zi1rvuedg0aLwHMv4lE/9+8PDD0PPnrnJv+YaOPDAOJ8bhfbii7DrrtmJgUuX5ueY228PkyfDkUfm53iSJEmSJEmSJEmSVChz5sDNN8fJ+trXoHfvOFnSatXVYY9//32YPz/OLJIkSZIkSZIkSZIkSVIpqqwMe/zcuXHmKAYxzkWyjE8b4+SToVu38JzZs2HixPCctuTaa+M9/3zzm9C1a5wsSZIkSZIkSVJuWManqNI0XQHc2MzdvpwkySEhx0mS5AjgmGbudkOapkVe/yNJUnGrqgp7fJrCm2/GmSVXkgRGjAjLWLgQFiyIM49a56GHwjOGDoVttgnPkTbG1lvDgw9Cp065yX/sMdhlF3j11dzk59rChXDWWdmfYfLk/B33tNPgr3+Fmpr8HVOSJEmSJEmSJEmSCuW734Xa2vCcigo477zwHGltw4aFZ8yYEZ4hSZIkSZIkSZIkSZIklarQMr4FC6ChIc4shRZjrynL+LQxeveGk06KkzV+PNTVxckqdm+/DddfHydr883h1FPjZEmSJEmSJEmScscyPuXCDcBbzdznniRJdmlNeJIknwTuauZub9B8KaAkSWpGjE2MZs4Mz8i1kSPDM6ZODc9Q66QpTJoUnjNmTFbOKOXbZz8L998P5eW5yZ8+HXbeGW68ERobc3OM2FasgOuug+pqmDAh+zzPh+7d4Wc/gx/+EDp3zs8xJUmSJEmSJEmSJKmQ3noLbrstTtaJJ8KgQXGypDVVV4dnTJsWniFJkiRJkiRJkiRJkiSVqtAyvsbGOCV2xcAyPhXC2LFxcmbPhnvuiZNV7C67DGpr42Rdfjl06hQnS5IkSZIkSZKUO5bxKbo0TZcDX2/mbj2A3ydJcuDGZCdJcjDwONC9mbuen6ZppB97SJJUuqqqwjNKpYxvypTwDLXOa6/BjBnhOWPGhGdIrTVmTHaSWq4KIWtr4dxzYe+943y+5EpjY1aGN3IkXHQRLFmSv2Nvuy28+CIcfXT+jilJkiRJkiRJkiRJhTZ+PNTVheeUlcGFF4bnSOtiGZ8kSZIkSZIkSZIkSZJUWKFlfABz54ZnFIOFC8Mz+vYNz1BpqamBAzdq99b1i3XuaDH7xz9g4sQ4WcOGwYknxsmSJEmSJEmSJOWWZXzKiTRNHwB+1szdegGTkiS5L0mSDVbgJEkyKkmSXwD/B/RsJve+NE1/3fJpJUnS+gwbFp4xa1Z4Rq6NGBGeYRlf4UyaFJ7RqxfsuWd4jhTi2GPhlltye4xnnslK5268EVatyu2xNkZ9Pdx3XzbbscfCG2/k9/inngrPPx/n64EkSZIkSZIkSZIktRUzZ8Jdd8XJOuYYGD48Tpa0tpqa8AzL+CRJkiRJkiRJkiRJkqTWs4yvSYwyvn79wjNUei64IE7OG2/AT34SJ6sYNTbCOedAmsbJGz8eOnaMkyVJkiRJkiRJyi3L+JRLpwFTm7lPAhwDvJYkyUtJktySJMn5SZKcliTJBUmSTEiS5J/Aq8CRLTjmFOBrYWNLkqTVqqrCM9pCGd/IDdYCt8zU5l71KGdilPHtv78nu6g4nHEGfOc7uT3G8uVw7rkwahT88pfZyWOFsnIl3HFHVoJ33HHw6qv5PX63bnDvvdkMXbrk99iSJEmSJEmSJEmSVGhXXgn19eE55eUwblx4jrQ+MYoeLeOTJEmSJEmSJEmSJEmSWm/AgPAMy/ia9O0bnqHSs9desPfecbLGj4e6ujhZxeaee+CZZ+Jk7borHNmSnXAlSZIkSZIkSUXBMj7lTJqm7wP7AW+18CGfAM4Evgf8ELgOOAPYroWPfxPY78PjSpKkCLbYApIkLKMtlPENHw5lga+Mp0yJM4s2zty58Pzz4TljxoRnSLF84xtw2WW5P8706XDUUbDLLvDoo/kt5XvtNfj612HTTeG002DmzPwde7VPfAJefBGOPTb/x5YkSZIkSZIkSZKkQps8GSZOjJN10klxytKk9eneHQYNCsuYNg3SNM48kiRJkiRJkiRJkiRJUqmprAzPsIyviWV8aq1x4+LkvPkmTJgQJ6uYLFgAF14YL+/668P34ZMkSZIkSZIk5Y9lfMqpNE3fAD4LzMjxoaYDn03T9M0cH0eSpJJSUZEVJYVoC2V8nTvD0KFhGTNnQl1dlHG0EX73u/BNsjp0gM9/Ps48Uizf/jZcc01+jjV5MnzhC1BTA9deC/Pm5eY4c+bAj34Ee+wBo0bBD34Q5+TSjZUkcNFFWZHnyJH5P74kSZIkSZIkSZIkFVqawvnnx8mqqIDLL4+TJW1ITU3Y45cty905EZIkSZIkSZIkSZIkSVJ7Zxlfk9D9Ujp3hq5d48yi0rP33tmK4Yor2t95dRdfHG9Po8MOg912i5MlSZIkSZIkScoPy/iUc2maTgd2Bh7P0SEeA3ZO0zTXhX+SJJWkqqqwx7/3HixdGmeWXAotZGpogBm+Gsm7SZPCM/bcE/r0Cc+RYrvoIrj99qw8Lh9mzsxOJttsMxgzBiZMgGnTWl94uXIl/P3vMH48fPKTMGgQnHoqPPts3Lk3xmabwRNPZEWHFRWFm0OSJEmSJEmSJEmSCumhh+Dpp+NkffWrMGRInCxpQ4YPD8+YNi08Q5IkSZIkSZIkSZIkSSpFlvE1CS366ts3zhwqXVdcESdn6VK49NI4WcXgmWfg7rvjZHXsmO1RJEmSJEmSJElqWzoUegCVhjRNFwGfT5LkBOBaYECE2HnAhWmaToyQJUmS1qOqKjvBIMTs2bDttlHGyZkRI+CRR8IypkyBrbaKM4+aV1sLv/99eM6YMeEZUq589avQsyccfzzU1+fnmKtWwcMPZwtg6FDYYQeoqclWdTV065aV2VVUZGWkc+fCnDnZmjoVJk+Gl1/OsorFEUfAD39o+aYkSZIkSZIkSZKk0lZXBxdeGCerc+f2tQmLiltNTXjGtGmw++7hOZIkSZIkSZIkSZIkSVKpGRBh90jL+DKW8SnUXnvBZz4DTz4ZnnX33XDaabDzzuFZhVRXB6efHi/vrLOyfZYkSZIkSZIkSW2LZXzKqzRN70mS5AHgBOAsoDV1Nf8BJgA/SdN0ecz5JEnSx1VVhWfMmlX8ZXwjR4ZnTJ0anqGWe+KJrJAv1EEHhWdIuXTUUdCjBxx+OKxYkf/jz56drbaqXz+49Vb40pcKPYkkSZIkSZIkSZIkFd6tt8L06XGyzjwTBg2KkyU1J1YZnyRJkiRJkiRJkiRJkqSNV1EBffrAokWtz2gPZXxpahmfisMVV8Qp40tTGDsWnnsOysrC8wrlBz+AV1+Nk9WnD1x2WZwsSZIkSZIkSVJ+teH/6lZblabpB2ma3pqm6ShgBHAOcA/wIvAu8D7Q+OHlu8DfP7z9HGDLNE23/vDxFvFJkpQHscr4il2MMr4pU8Iz1HKTJoVnbLMNDBsWniPl2gEHZAWUlZWFnqRtOfzw7CQ5i/gkSZIkSZIkSZIkCd57D771rThZ3brBxRfHyZJawjI+SZIkSZIkSZIkSZIkqbBC9z1pD2V8H3wAdXVhGZbxKYY994TPfjZO1vPPw733xskqhGnT4Mor4+Vdfjlsskm8PEmSJEmSJElS/nQo9AAqbWmavg68Xug5JEnS+pVKGd+IEeEZlvHlT2MjPPxweM6YMeEZUr58+tMweTIccgj8/e+Fnqa49esHEybAEUcUehJJkiRJkiRJkiRJKh7f+hYsWhQn69xzoX//OFlSSwwfHp5hGZ8kSZIkSZIkSZIkSZLUepWVYXsszZuX7RtUVhZvpnxbuDA8wzI+xXLFFfCnP8XJuvhi+OIXoWfPOHn5smoVHHcc1NbGyauuhjPPjJMlSZIkSZIkScq/NvxjKEmSJOVDqZTxDRgAvXuHZUydCmkaZx5t2Isvwpw54TkHHxyeIeXTppvCn/8MJ5xQ6EmK18knw2uvWcQnSZIkSZIkSZIkSWuaMgUmTIiT1acPnH9+nCyppbp2zc6bCDF9uud3SZIkSZIkSZIkSZIkSa1VWRn2+IYGeO+9OLMUimV8KiZ77AGjR8fJmjMHxo2Lk5VP48fD3/4WL2/CBKioiJcnSZIkSZIkScovy/gkSZK0QYMHQ8eOYRltoYwvSWDkyLCMxYth3rw482jDJk0Kzxg4EHbaKTxHyrfOneHHP4Ybb4Ty8kJPUzy23hqeeQbuugv69Sv0NJIkSZIkSZIkSZJUPNIUTj8d6uvj5I0blxXySflWUxP2+A8+yDYMkiRJkiRJkiRJkiRJkrTxQsv4AObODc8oJMv4VGyuuSbbPy2GG2+EJ5+Mk5UPzz8PV10VL+/II2G//eLlSZIkSZIkSZLyzzI+SZIkbVB5OQwZEpYxe3a2qVexGzEiPGPq1PAMNS9GGd9BB0GZ3xGpjUoSGDsWnngi/Dm6revaFa69Fv7xD9h990JPI0mSJEmSJEmSJEnF57774Kmn4mTV1GTFflIhhJbxAUybFp4hSZIkSZIkSZIkSZIklSLL+CzjU/HZcUc45ZQ4WWkKJ5wAixfHycul99+H446DhoY4eT17wve/HydLkiRJkiRJklQ4HQo9gCRJkopfVRXMmNH6x7//fnYSUb9+8WbKhZEjwzOmTIE99wzP0frNmgUvvxyeM2ZMeIZUaHvtlX0+XHgh3HFHoafJrySBE0+Eb38bNt200NNIkiRJkiRJkiRJUnFatAjOPz9e3nXXQUVFvDxpY8Qq4/P8Lunj0jQ7T/T55+Gf/4S33oIlS7L3r14A/fvDFltkm3jtuCMMHZqdxyNJkiRJkiRJkiRJkto/y/gs41NxGj8efvWr7HyfUG+9BWedBffeG56VS1//eti+eGsbPx4GD46XJ0mSJEmSJEkqDMv4JEmS1KyqqvCMWbNKp4xPuTVpUnhGly4wenR4jlQMevaE22+Hww6DU06Bt98u9ES5t99+cO21sO22hZ5EkiRJkiRJkiRJkorbN78J8+bFydp7bxgzJk6W1BqxyvgkZaZMgf/7P3j22ayErzWbxW2yCey0U/Y14pBD4pyHKUmSJEmSJEmSJEmSipNlfJbxqTgNGABXXgnnnhsn77774KCD4Mgj4+TF9pvfwJ13xsvbcUc4/fR4eZIkSZIkSZKkwikr9ACSJEkqfrHK+IrdiBHhGVOnhmdow2KU8X3uc1khn9SefO5z8MorWSFfe7X99vD44/DYYxbxSZIkSZIkSZIkSVJz/vY3+OEP42QlCVx/fXYpFYplfFK4+nr41a9gt91gq63gkkvgd79r/UZx770Hv/89XHpplrf77vDTn0Jtbdy5JUmSJEmSJEmSJElS4VnGZxmfitcZZ8CoUfHyTj8d/vvfeHmxvPwyfPnL8fLKyuD226G8PF6mJEmSJEmSJKlwLOOTJElSs0qljK+6OvyEiClT4syidVu0CJ5+OjxnzJjwDKkY9eoFP/oRPP887LVXoaeJ51Ofgt/+Fl56KSsdlCRJkiRJkiRJkiRtWH09fO1rkKZx8k44AXbYIU6W1FrV1eGFkJbxqVQtXgzXXQfDhsERR8Bf/pKb4zz3XLbZ1eDBcM45fs5JkiRJkiRJkiRJktSexCjjmzcvPKOQLONTserYEW68MV7eokXZeUD19fEyQ82fn+0d9sEH8TLPPBN23DFeniRJkiRJkiSpsCzjkyRJUrNKpYyvoiLbaCbErFlQWxtnHn3cY49BQ0NYRpLAAQfEmUcqVrvuCk8+CY88Av/zP4WepvX23Tf7czz3XPZ5G7qhniRJkiRJkiRJkiSViltvhX/8I05W165w1VVxsqQQnTvD5puHZUyfDo2NceaR2oLaWvj2t2HIELjoInjrrfwcd/FiuOkmGDkSvvIVmDs3P8eVJEmSJEmSJEmSJEm5E6OMr62fQxBaxpck0Lt3nFmkte2zDxx6aLy8P/0Jxo6FNI2X2Vp1dXD44TB7drzMTTfNzq2SJEmSJEmSJLUflvFJkiSpWaVSxgfZxi8h0hReey3OLPq4SZPCMz75yTgn9knFLklg//2zzRUnToSamkJP1DLdumUbcL34Ivz+97D33pbwSZIkSZIkSZIkSdLGmDkTLrkkXt6FF2YbjkjFIPT8h9paeOedOLNIxe4vf4FPfAL+939h2bLCzNDYCHfdBVtuCd//frYpliRJkiRJkiRJkiRJaps6d4aePcMySr2Mr3dvKC+PM4u0Lt/7HnTqFC/vttvghhvi5bVGmsLZZ8Of/xw39557oFevuJmSJEmSJEmSpMKyjE+SJEnN6t8funYNy5g9O8ooORdaxgfwyivhGfq4ujp49NHwnDFjwjOktqS8HI4/PisKfeQROPhgKCvC/w3YaSe4/XZ49124807YccdCTyRJkiRJkiRJkiRJbU9jI5x0EixfHievqgouuihOlhRDaBkfwLRp4RlSMVu+HL7+ddh9d5g6tdDTZJYuhfPPh223hcceK/Q0kiRJkiRJkiRJkiSptSorwx7f1sv43nsv7PF9+8aZQ1qfqiq49NK4meefDw89FDdzY9x4I9xxR9zM886D0aPjZkqSJEmSJEmSCq8It9+XJElSsUkSGDo0LGP27Gyzr2I3alR4xssvh2fo4555BpYsCc+xjE+lqrwc9t8f/u//4I034IorYPPNCzvTttvCN78J//gH/P3v8NWvQo8ehZ1JkiRJkiRJkiRJktqyW26BP/85bl7XrvHypFCW8Ukb9uyzsN128IMfQJoWepqPmzo1O4fp+OOzgj5JkiRJkiRJkiRJktS2xCjjK8ZzGlpq4cKwx1vGp3y45BLYeed4eWkKxxwDkyfHy2ypCROy4ryYttkGrr46bqYkSZIkSZIkqThYxidJkqQWqaoKe3xdHbz7bpxZcmmbbcIzXnklPEMfN2lSeEZ1NWy1VXiO1NZtthmMG5cVpf7lL1kx36c/nRX25VLnzrDvvnDzzTBrFvzrX3DVVbD99rk9riRJkiRJkiRJkiSVgmnT4BvfiJd36KHwhS/Ey5NisIxPWrc0he99D/baC6ZPL/Q0zbv3Xthpp+z8IUmSJEmSJEmSJEmS1HYMGBD2+Lo6WLIkziz5Vl8PixeHZVjGp3zo2DE7P6dr13iZy5fDgQfmd3+1m26Cs86Km1lRAffdl+2DJEmSJEmSJElqfzoUegBJkiS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z15EkSZIkSZIkSZIkSapUNTVw+unwH/+Rrc7LLyfX5u+/fz59ldLMmcm98rIYNqw6gwglSZIkSZIkSZKUP8P4NjcsZX5akfefCpxYYH4oFRjGF0JoA3wsZVkxj93UlPm9QgitY4xri9iDVFIxwrvvJkF68+dv/Th/fhK299ZbsHp1ubutDjvumJyUcu65sMce5e5GkiRJklq2Pn3ghBOSAcnvwfPmJcF8U6fCP/8JU6bA8uXl7bPU1q9Pggmfegp+/GNo3RoOPDAJ5jviCPjkJ6Fdu3J3KUmSJEmSJEmSJFW3UaOyh/E98wy88goMGZJPT9XijjtgbQ5n7Z91VvYakiRJkiRJkiRJkiRJle6MM7KH8QGMHVudYXzTp2evMXRo9hqSJEmSJEmSJElqHgzj29zHU+afKfL+z5AexleJPga0LjBfB7xQxP2fA9YDNY3MtwH2BGYWsQdpu9XVwcqVSYDAsmWwZAksXtz4WLQoCd1bs6bcnVe/jh1hxAgYMwaOPBJqa8vdkSRJkiSpISHATjsl4/OfT16rq4MXX4Qnn6wfL71U3j5Lbe1aeOyxZAC0bZsE8h12GBx+eBLU17FjeXuUJEmSJEmSJEmSqs3w4XDxxbB+fbY6EybAd76TT0/VIEa4+ebsdTp3rn9fWJIkSZIkSZIkSZIkqTnbc08YNgymTctWZ9w4+M//hNaF7ghZgbJ+3ZAcP0mSJEmSJEmSJAkM49vSkJT5V4u8/2sp87sXef/tlXbcZscYixYbFmNcE0KYCwwssGx3DONTjv78Z3jhBVi3Lrnx/bp16c9Xr4YVK5KxfHkyVqyA998v91fTsrRrByecAKNGwYknGkogSZIkSdWqthb22isZF1yQvLZ0KUyZkgTzTZqUPH7wQXn7LKUPP6wP5/v3f4dWrWC//ZJgvsMOg0MOga5dy92lJEmSJEmSJEmSVNn69EneX3v00Wx1WloY31NPwfPPZ68zahR06JC9jiRJkiRJkiRJkiRJUjUYMyZ7KN2iRfDgg/DZz+bTU6k89VT2GobxSZIkSZIkSZIkaSPD+DYIIQRgl5RlaWF5WaXV36XI+2+vXVPmi33cNu5RKIwvrUdpm9x5J4wfX+4u1FTt28Pxx8MXvgCf+xx06lTujiRJkiRJxdC9O3zmM8kAWLs2ufBgY0DdE0/AsmXl7bGU1q1LwgmnTIFrr4WaGth33/pwvkMPhZ49y92lJEmSJEmSJEmSVHlGjswexjd9Orz+Ouy2Wy4tVbybb86nzpln5lNHkiRJkiRJkiRJkiSpGoweDd/4BtTVZaszdmx1hfEtWwbPP5+tRocOMGRIPv1IkiRJkiRJkiSp+tWUu4EK0gdol7Lm7SL3kFa/Ywihd5F72B67pMwX+7g1ZQ/D+JSr1q3L3YHSDBgAX/4y3HsvLFkCd98NX/yiQXySJEmS1JK0bg2f/CRcfjncc0/y++HMmfCzn8GoUdCnT7k7LK3165Mbfl5/PZxyCvTqBXvuCeefn9wY88UXkzWSJEmSJEmSJElSS3fKKRBC9joTJmSvUQ3efx/GjcteZ+BAOPTQ7HUkSZIkSZIkSZIkSZKqRZ8+cOyx2ev8+c+wfHn2OqUyeXL2GvvuC7W12etIkiRJkiRJkiSpeWhV7gYqyI5NWPNOkXtoSv0dgYVF7mNbpR27Yh+3puzRlH9fqcla+dOz4oSQBCx87nPJ2GeffG6CIkmSJElqPmpqkt8X99kHvvIViBFefRUee6x+zJ5d7i5L68UXk3HzzcnH3brBgQfCQQcljwccAJ07l7dHSZIkSZIkSZIkqdT69YNDDoHHH89WZ/x4+Na38umpkk2YACtWZK9zzjnJ+7qSJEmSJEmSJEmSJEktyZgxcN992WqsXg1/+ENy/kU1mDQpe41hw7LXkCRJkiRJkiRJUvNhnFS9Hinzy2OMHxazgRjjByGElUCnAsvS+iyHtJ5KER64IGW+Eo+bqljr1uXuQADdu8ORRybheyecAL17l7sjSZIkSVI1CQGGDEnG+ecnr82eDRMnwt/+lox588rbY6ktW5ZcqLHxYo2NAYabBvQNGpQcO0mSJEmSJEmSJKk5GzUqexjf00/DrFmw66759FSpbrkle40Q4Oyzs9eRJEmSJEmSJEmSJEmqNiefDJ06wcqV2eqMHduywvgOPDB7DUmSJEmSJEmSJDUfhvHV654yv7wkXST7FArjS+uzHCrh2KXtUYnHTVWslT89y6JrVzj88CSA78gjYe+9k1AASZIkSZLyMnBgcoPHs8+GGOG11+qD+SZOhEWLyt1haa1fDzNmJOPGG5PXeveGAw6A/fdPxn77Qd++5e1TkiRJkiRJkiRJytspp8BXv5q9zoQJcPnl2etUqldfhccey17nmGOS92slSZIkSZIkSZIkSZJamg4dYMQIuO22bHUefRTmzoUBA3Jpq2jWrYPJk7PXOfjg7DUkSZIkSZIkSZLUfBgnVW+HlPkVJekifZ9KDJWrhGNXVccthHAxcFEJttqtBHu0SK1bl7uDlqFTp/V86lNrOfjgtRxyyFr22msdtbX180uWlK83SZIkSVLL0K1bcpPNU05JguleeqmWf/yjDY8/3ppJk1qzfHnLS4lfuBD+8pdkbNSvXx377ruOj398Hfvuu459911Lz56xfE1KkiRJKqoePXpQU9Pyfh+SJEmSJLUs/fsnN+z6xz+y1WnuYXy33JJPnfPOy6eOJEmSJEmSJEmSJElSNRozJnsYX4xw553wr/+aT0/F8uyz8P772Wr06wcDB+bTjyRJkiRJkiRJkpoHw/jqtUuZz/h2XZOtTJlP67McKuHYVdtx6wXsWe4mtP1a+dOzSF4BpgCTgSmsXDmDhx+u4+GHy9yWJEmSJEkNqgGGAkcCRwGHAp3K2lG5zJ9fy/z5tdx/f9tNXp0NTAWe3uRxaTnakyRJkpSzhQsX0qtXr3K3IUmSJElS0Y0cmT2M75//hNmzm+fNv9aty34TOIDu3eHzn89eR5IkSZIkSZIkSZIkqVodcQT07w/z5mWrM3YsfOtbEEIubRXFpEnZaxx0UGV/jZIkSZIkSZIkSSq9mnI3UEHapMyvK0kX6fuk9VkOlXDsqvG4qYq1bl3uDpqDd4EHgKuAzwA9gI8AZwI3kNygv65s3UmSJEmSlG49ye+v/wmcAHQHDgb+DZgIrC5faxVhIDAC+CHwILAEmAPcA1wDfIHkbwH+mVqSJEmSJEmSJEmVacSIfOqMH59PnUpz330wf372OmecAW3bZq8jSZIkSZIkSZIkSZJUrWpr4fTTs9d54QWYMSN7nWLKK4xPkiRJkiRJkiRJ2lSrcjdQQSohUK4p+1RiqFwlHLtqPG6qYq386bmN5gMzN4wZwHTgFSCWsylJkiRJknK2Fpi0YVwDtAMOBI7aMA7AP8kO2DA+t8lrq4DngGdI/nbwHPACsKDk3UmSJEmSJEmSJEmbGjAAPvUpmDw5W5277oJvfCOfnirJL3+ZT51zz82njiRJkiRJkiRJkiRJUjUbMwauvTZ7nbFjYejQ7HWKxTA+SZIkSZIkSZIkFUNLv/PzpmpS5utK0kX6PrUl6WLbVMKxq8bjpipmGF9j1gEvsXnw3kxgYTmbkiRJkiSpTFYDEzeM7wGdgUOpD+er4CsYSqo98IkNY1NLSEL5No7nNzzOL2l3kiRJkiRJkiRJatlGjcoexvf00/DKKzBkSD49VYI334S//jV7nf32g333zV5HkiRJkiRJkiRJkiSp2u21V3IexcyZ2er89rdJqF8l3i/v7beT806yaNu2ssMGJUmSJEmSJEmSVB4V+PZY2axLmS/VsUrbZ21Jutg264DWBeZLceyq8bipirUu9B3fAnToEBk8eB277163YSTPd921jrZt+wDHbhiSJEmSJKkxS5YsZtKk1jzxRBsef7w1r73mn2s314MkvPDQzV7t0mU9gwcnf4fYbbc6Bg2qH126xLJ0KkmSJLU0PXr0KHcLkiRJkiSVzIgRcNll2euMGwdXXpm9TqW46SaIObw9d9552WtIkiRJkiRJkiRJkiQ1F2PGZA/jW7AAHn4Yjj8+n57y9OST2Wvsv38SyCdJkiRJkiRJkiRtyrs711uTMl+qY5UW8ZXWZzmsofxhfNV23BYBL5Rgn90A3youglYt4Kdn27aw664waFAyBg+Gj34U9tgDdtopUFPTmvT/9CRJkiRJUmN69Up+zz733OTjefNg4kT429/gkUdgzpzy9lepli+vYdq0GqZN2/rvEr16wZAhsPvuW4+OHcvQrCRJkiRJkiRJkqrewIFwwAHwz39mqzNuHFxxBYSQT1/ltGYN3Hxz9jrt2sHo0dnrSJIkSZIkSZIkSZIkNRennQbf/CasX5+tzh13VGYY3z/+kb3GQQdlryFJkiRJkiRJkqTmpwXESTXZ2pT5NiXpovpC5aAyjl1VHbcY48+Bnxd7nxDC88Cexd6nJWrdDDLoQoAdd4QBA5LQvd12qw/e2223ZK6mptxdSpIkSZLUcvTvD2eckYwYYdasJJhv41iwoNwdVr5Fi5LR0EUY/folf/fYZZetx4AB0LZtSVuVJEmSJKlFCiF0APYA+gJdgHbASmAF8CbweoxxXdkalCRJkhoxcmT2ML6XX4YZM2Do0Hx6Kqe774aFC7PXGTECunXLXkeSJEmSJEmSJEmSJKm56NcPjjkGHnwwW50//hFWroROnfLpKy+TJmWvcfDB2WtIkiRJkiRJkiSp+TGMr97KlPlSvY3YOWU+rc9yWAkUugS+FMeuGo+bqlirCv/pGQL07p2cULHzzskN5QcM2Pz5jjs2j1BBSZIkSZKaoxCS4LhBg+D885NwvhdfhEceSYL5Hn0Uli0rd5fVZf78ZDQU1BdC8reSgQO3DuobOBB22gk6dChtv5IkSZIkNQchhAAcDZwIHA/sDoQCn7ImhDADuBe4O8b4XPG7lCRJktKdeip885vZ64wb1zzC+G68MZ86552XTx1JkiRJkiRJkiRJkqTmZMyY7GF8H3wAf/gDnHVWPj3lYdUqmDYte50DD8xeQ5IkSZIkSZIkSc1PhcdJldTSlPkuJekifZ+0PsthKbBTgflSHLtqPG6qYuUIsQsBuneHnj2hRw/o2zcZ/folY+Pzvn2TIL5KDwyUJEmSJElNFwLsuWcyLrkE1q+H556Dv/8dHnsseVy0qNxdVq8YYd68ZEya1PCaHXaA/v2TsdNOmz9ufN69e/JvJUmSJElSSxdCaAWcD3wNGLINn9oGOGDDuCqEMBH4UYwx460kKksI4VagnLe1uDPGeEYZ95ckSao6O+8MBx8M//hHtjp33QU/+hHU1OTTVzk8/3zyHmVWu+8Ohx+evY4kSZIkSZIkSZIkSVJzM3w4dOwI77+frc6tt1ZWGN/TT8PatdlqDB6c3GdPkiRJkiRJkiRJ2pJRTfWWpMx3K0kX0DVlPq3PcqiEY5e2RyUeN1Wx7Q2669QJOneGLl3qHzd93rkzdO2aBO5tOXbYAWpr8/06JEmSJElSdaqpgX32ScYllyRhci+/vHk437x55e6yeXn33WQ891zja9q1qw/n698f+vZtePTo4d95JEmSJEnNVwjhU8AvgX1yKHckcGQI4W7gkhjj2znUlCRJkrbL6NHZw/jmzoVJk+CQQ/LpqRx+8Yt86nzpS9UdSihJkiRJkiRJkiRJklQsHTsmgXx33JGtzqOPwuuvw2675dJWZpMmZa9x0EHZa0iSJEmSJEmSJKl5Moyv3uKU+bYhhG4xxmXFaiCE0B1ok7KsEkPl0o5d3xL0kLZHJR43VbHhw2G//aB16ySYr1Wr+udbPm58XlMDIZS7c0mSJEmS1ByFAHvskYwLL0zC+WbN2jycb9ascnfZ/K1enVyQ8vrrhdfV1kLv3tCnT+OBfRtHly7+TUmSJEmSVD1CCBcD/w20zrn0KcDBIYQRMcaM8SeSJEnS9hk1Ci69FOrqstUZN656w/hWroTbbstep107OPvs7HUkSZIkSZIkSZIkSZKaqzFjsofxAdx6K1x9dfY6eTCMT5IkSZIkSZIkScVkGF+9OU1Y0wcoWhjfhvppmtJnqaX11JSvK6u0PWaXoAe1IL17J0OSJEmSJKkShQCDBiXjnHOS1+bOhccfhyefTC5UmDkz+41CtX3q6mD+/GSkadeuPrivT5/65w291r17EvQnSZIkSVI5hBCuBS4v4hZ9gIkhhJExxv8t4j6SJElSg3r3hmOOgQceyFZn/Hi4/nponXeEdQn89rewYkX2Oqeemry3JUmSJEmSJEmSJEmSpIYdfTT069e065ELufVW+P73y38NcoyG8UmSJEmSJEmSJKm4DOPbIMa4MoSwBOhRYNlA4OUitrFLyvzCGOP7Rdx/e72ZMj+wBD3skjI/qwQ9SJIkSZIkSRVrwAA47bRkALz/Pjz1VH0436RJsHRpeXvU1lavhjlzkpGmpgZ69Soc3rfpY9u2xe9fkiRJktQyhBCuoLhBfBu1Bn4fQvhcjPHhEuwnSZIkbWb06OxhfIsWwSOPwPHH59NTqcQIN96YT62LLsqnjiRJkiRJkiRJkiRJUnNVW5tcF/5f/5WtzltvwcMPw3HH5dPX9nrtteS8mSy6dIE998ynH0mSJEmSJEmSJDU/hvFtbhaFw/h2Bx4s4v6DU+YrNVAura/dS9BDtR47SZIkSZIkqSw6doQjjkgGJDfPfPXV+mC+J5+E559PXld1WL8eFixIxrPPpq/v2rXhoL6GXuvcGUIo/tcgSZIkSao+IYTPA1c1YWkEHgJ+D0wG3gLeB7oCHwEOBcYAH0up05YkkG9YjPHN7WxbkiRJ2i7Dh8OFF8KHH2arM25c9YXxPfEEzJiRvc6wYfCJT2SvI0mSJEmSJEmSJEmS1NydeWb2MD6A3/ym/GF8jz+evcaBByYhhZIkSZIkSZIkSVJDDOPb3PPA/gXmP1Lk/dPqP1/k/bdXWl89QwjdY4xLi7F5CKEn0D1lWaUeO0mSJEmSJKkihABDhiTj7LOT1957D6ZMSYL5pk6Fp55Kgt7UPLz3XjJeeSV9bbt2Wwf0NRbe16OHF7JIkiRJUksRQtgZ+E0Tlk4FvhRjfLqBuSXAJGBSCOFa4FTgp0DvAvV2AH4XQjg4xrhuG9uudEuAfy3yHq8Vub4kSVKz1aULfPazcPfd2er88Y9w443QoUM+fZXCddflU+fLX07em5QkSZIkSZIkSVLxhRDaAR/bMPba8NgP6LZhdAHWAqtIzl16m+T8omeAKcBTMca60ncuSZIA9tkHhg2DadOy1fnjH2HpUuiedsfGInrggew1Djooew1JkiRJkiRJkiQ1X4bxbW4acFaB+aFF3n9Yyvz0Iu+/XWKMb4YQ3iW5yVVjhgKPFKmFtOO2JMY4t0h7S5IkSZIkSc1W165w7LHJAIgR3n47CeZ7+unkcepUWLSovH2q+FavhjlzkpGmpgZ69mw4qK+hEL+2bYvfvyRJkiSpaP4vyQ2ZCrkDOC/GuCatWIwxAneFEJ4A/grsXWD5AcBFG3poTlbGGH9d7iYkSZLUuNNOyx7Gt2JFUuOMM/Lpqdheew3+/Ofsdbp2hdGjs9eRJEmSJEmSJElSw0IIrUnOrToaOAo4EGiT8mm1QDuS+0cNBg7bZO69EMI9wG3AIxvO8SqJEELJ9mrEp2OMD5e5B0mSOPfc7GF8a9bAb38LX/lKPj1tq7o6eOih7HUM45MkSZIkSZIkSVIhhvFtLu1txo+HEGpjjHV5bxxCaAXsm7KsIsP4NphGcgJWY/ajeGF8+6XMV/JxkyRJkiRJkqpGCNC/fzJOPjl5LUaYO3frgLe/htoAACAASURBVL6lS8vbq8pn/XpYuDAZzz6bvr5r160D+hoL7+vcOfk+lCRJkiSVXwjhWODklGV3A2fFGNdvS+0Y41shhGOAJ4FBBZZeFUIYF2NctC31JUmSpCxOOCF5z2LFimx1brmlesL4rr8+eV8wqzPPhI4ds9eRJEmSJEmSJElSvRBCO+AE4AvAZ4FOOZbvCpyxYTwbQrg6xjg+x/qSJCnF6NFw2WXw4YfZ6txyS/nC+KZOhXffzVajpgYOOCCffiRJkiRJkiRJktQ8Gca3uanAaqBdI/OdSILf/lmEvQ8AOhSYXw08XYR98/IEhcP4jgCuLdLeR6bMP1GkfSVJkiRJkqQWLwTYeedknHJK8lqM8OabyYURzzwDM2cmY86csraqCvXee8l49dX0tW3bNh7U16cP7LhjMvr3hw6F/uIuSZIkScrDD1Lm3wDO2dYgvo1ijAtDCKcCk4DWjSzrBnwd+Pb27CFJkiRtj/btYfhwuP32bHUmToQ33oBBheKnK8DSpfCb3+RT60tfyqeOJEmSJEmSJEmSIIRwIHAJcCL5BvA1Zm/g9yGEvwEXxBjfKMGekiS1eN27J+eq3HVXtjrTp8OMGfDxj+fT17Z44IHsNfbdF7p0yV5HkiRJkiRJkiRJzZdhfJuIMa4OIfyDwqFyn6Y4YXzHpMw/HmNcXYR98/IwcGWB+cNCCG1ijGvy3DSE0A44JGXZQ3nuKUmSJEmSJKmwEGDXXZMxalT968uWJeF8GwP6nnkGnn0WVq0qX6+qLh9+mIQ6NiXYsWvXJJRvYzhfQ499+0Ir3ymRJEmSpG0WQjgc+GTKsq/EGJdn2SfGODWE8D/A1wos+1II4YcxxhVZ9pIkSZK2xejR2cP4IAm5u/rq7HWK6aab4IMPstc5/HDYc8/sdSRJkiRJkiRJkvT/nQWMLsO+RwHTQghnxRj/XIb9JUlqcc45J3sYHyTnqvz0p9nrbKs8wviOPTZ7DUmSJEmSJEmSJDVv3mJ2aw9ROIzvFOCaIuw7MmX+wSLsmafJwAqgcyPzHYHjgHty3vcEoH2B+fcoTniiJEmSJEmSpG3UrRscdlgyNqqrg1mz4IUX6sfzz8OLLxrSp2zeey8ZL7zQ+JoQoE+fwoF9/ftD9+7JWkmSJEnS//fVlPmJMcb7ctrrB8D5NH5eUjfgTODnOe0nSZIkpTr6aOjZExYvzlbn1lvh+9+H2to8usrfmjXws5/lU+uii/KpI0mSJEmSJEmSpIrQFbg7hHBhjPHX5W5GkqTm7uijYcAAmDs3W5077oAf/xjatcunr6ZYtgymTMle57jjsteQJEmSJEmSJElS82YY39YmAD8qMD8shPCRGOPLeW0YQtgL2LvAkrihr4oVY1wXQvgTMKbAstPIP4zvtJT5P8YY1+W8pyRJkiRJkqSc1NbC4MHJOOmk+tfXr4fZszcP6XvlFXj1VVi0qHz9qnmJEd55JxnTpjW+rm3b+mC+nXZKHrd83q8ftGlTut4lSZIkqVxCCN2Az6Ys+0le+8UYl4UQbgb+T4FlZ2AYnyRJkkqodWv44hfhf/4nW5233oKHHoLjj8+nr7z97nfw9tvZ6+y8M5xySvY6kiRJkiRJkiRJymQNMBN4BZgFvAt8AHQEegA7AYcBA5tYrwa4KYSwMsZ4V/7tSpKkjWpr4eyz4eqrs9VZuhTGj4cxhe4YmbNHHoG6umw1OnaEgw/Opx9JkiRJkiRJkiQ1X4bxbSHG+HoIYTLwqQLLLgG+kuO2X02ZnxRjfDPH/YrlTgqH8Y0IIewYY8zhcnwIIewMnNyEniRJkiRJkiRVmZoa2HXXZHx2i9v7L1uWhPJtOV55JZmT8vbhhzBrVjIaEwL07l04sK9/f+jSpXR9S5IkSVKRjALaFpifC9yf8543UTiM71MhhN1ijK/nvK8kSZLUqHPPzR7GB3DLLZUZxhcjXHddPrUuvRRaefWKJEmSJEmSJElSOTwN3EtyTtfTMcY1aZ8QQhhEcn+tC4BOacuBW0MIL8cYp2dtdhvcA/xvkfd4ocj1JUnaJnmE8QHccENpw/geeCB7jSOPhDZtsteRJEmSJEmSJElS8+blzA27hcJhfOeEEK6JMc7PulEIYScKB9gB3Jp1nxJ5mORmWgMamW8NXA58Laf9Lqfw9/AcYGJOe0mSJEmSJEmqEN26wSc+kYxNxQhLlmwezvfqq/DmmzB7NixYUJZ21ULEmHyPLVgA06Y1vq5z54aD+jZ93rt3EkgpSZIkSRXqxJT538cYY54bxhhfDCHMBPYtsOxzwE/z3FeSJEkqZOjQZEzPeEvRP/0JFi+Gnj3z6SsvEyfCjBnZ63TuDOedl72OJEmSJEmSJEmSmuwd4NfA2BjjK9v6yTHGN4CvhxB+CNwMnJTyKW1JAvn2jzGu3eZut8+0GOOvS7SXJEkVYdAgOOIIePTRbHUmT06ugx02LI+uCosxnzC+447LXkOSJEmSJEmSJEnNn2F8DRsL/DvQu5H5DsCPgLNy2OvHQLsC8ws29FPxYox1IYTrgf8qsOziEMIvYowvZ9krhLAn8KWUZf8dY6zLso8kSZIkSZKk6hFCcpPSnj3hwAO3nv/gA5gzJwnn2zhmz65//s47JW1XLdSKFfDSS8loTKtWsOOOhUP7dtwR2hV6d0GSJEmSiiCE0Ao4PGXZvUXa/l4Kh/F9GsP4JEmSVGLnnguXXJKtxtq1cOedcOml+fSUlx//OJ86F1wAXbvmU0uSJEmSJEmSJEkFTQeuBf6QRyhejHExcHII4TvANSnL9wHOBX6ZdV9JktS4c8/NHsYHcOON8KtfZa+T5uWXk2u7szKMT5IkSZIkSZIkSU1hGF8DYoyrQwg/pfAJQGeGEP4UY/zj9u4TQvgCcFrKsutjjB9u7x4b9tkFmJWy7KoY4/ez7LPBTcB3ge6NzLcG7gghHBxjXLM9G4QQ2gJ3UPj7dynw6+2pL0mSJEmSJKl56tAB9tgjGQ1ZtSq5oGP2bJg1C956C+bNS8bG5++9V9qe1TKtW5d8L6ZdYNSzZ8OBfZt+3K1bElQpSZIkSTn5BNClwPwqYFKR9n4I+E6B+cNDCK1ijOuKtL8kSZK0ldNOg8sugzXbdWZ8vZtvhq9+tXL+pv/kk/Dgg9nr1NYmX5ckSZIkSZIkSZKKairJ/aP+UoziMcYfhhC6At9MWfrtEMKvYozri9GHJEmCESPg4othxYpsde68E37yk+Qa1GJ64IHsNXbdFQYPzl5HkiRJkiRJkiRJzZ9hfI27HvgSMKDAmttCCPNijP/c1uIhhE8BN6csmw38dFtrl1OMcWUI4UrgZwWW7Q/8JoQwZltPnAoh1AK3AUNTln4vxrhyW2pLkiRJkiRJatnat4ePfCQZjVm5cvNwvoYeFy6EGEvXt1quxYuTMXNm42vat988qK+h5336QCvfMZIkSZLUNAekzE+NMX5YpL2nAHVAbSPznYCPAs8WaX9JkiRpK927w/Dh8LvfZavz7LMwbRrst18+fWV11VX51Bk5EgYOzKeWJEmSJEmSJEmStvIGMBr4XYxFv5rpX0nOHzuiwJqBwFHAw0XuRZKkFqtDBxg9Gm66KVudVavg9tvhq1/Np6/G5BHGd9xxEEL2OpIkSZIkSZIkSWr+vLVqI2KMH4QQvg6ML7CsM/BgCOGMGONfmlo7hHAycDvJDaAKuSzGuKqpdSvIjcAFwD4F1pwGtA8hnB1jXN6UoiGEriTH7aSUpTOBXzalpiRJkiRJkiRti06d0gP71q1LAtLeeWfzsWDB1q8tW1a63tUyrVoFr76ajMbU1EDfvumhfR06lK5vSZIkSRVrWMr8tGJtHGNcFUJ4Adi7wLKhGMYnSZKkEjvvvOxhfAC//GX2G6XlYfLkfG6EBvD1r+dTR5IkSZIkSZIkSVuLMV5bwr1iCOEyYCpQKA7n8xjGJ0lSUV14YT7nmNxwA1xySfGC7lavhkcfzV7n+OOz15AkSZIkSZIkSVLLYBhfATHGCSGE35IExzWmK/C/IYRxwNUxxpcaWxhC2BO4Aji1CdvfGWP8wzY1XCFijHUhhDHAFKBdgaXDgU+EEL4H3BVjXN3QohBCe5J/g6uA/inbrwLGxBjrtr1zSZIkSZIkScquVask2Kxv3/S1q1cnIX0NBfW98w4sXFg/v2JF8XtXy7R+Pbz9djIK6dat8aC+jc979CjehVeSJEmSKsLHU+afKfL+z5Aexnd7kXuQJEmSNnPUUbDzzjBnTrY6Y8fCNddAr1759LW9rroqnzoHHwwHHJBPLUmSJEmSJEmSJJVfjHFaCOFvwNEFlh1RonYkSWqxhg2DT30KJk/OVufll2HixOTcl2J44glYtSpbjVat4Mgj8+lHkiRJkiRJkiRJzZ9hfOkuBPYDPlJgTSAJizsthDAdmATMAlYCnYFdgYOBfZu450vAl7a34UoQY3wmhHAJ8KuUpTsBvwH+O4QwEZgJLCY5pj1JjtlRQJcmbn1JjPHZ7etakiRJkiRJkkqrXTsYODAZaVatSsL5Ngb0bRrUt+VrixdDjMXvXy3LsmXJeP75xte0bQs77rh5SF+/ftCnz+ajZ0+orS1d75IkSZJys3vK/KtF3v+1lPm0/qpOCKE/sAvQF+hIcl7VKpJz094G3ooxLi5bg5IkSaK2Fs4+G37wg2x1Vq+GX/wCvve9XNraLpMnw/3351PrssvyqSNJkiRJkiRJkqSK8hcKh/F9JITQOsa4tlQNSZLUEl10UfYwPoAbbiheGN8DD2SvcdBB0KWpd6GUJEmSJEmSJElSi2cYX4oY48oQwnHA48CAJnzK0A1je80BjosxrsxQoyLEGH8dQhgAXNGE5d2A4RvG9vp+jPHmDJ8vSZIkSZIkSRWrffumB/fV1SWBfA0F9TX02po1xe9fLcOHH8KsWckopKYmCeTbMqSvTx/o23fzj3v1gla+oyVJkiSVXQihL9A+ZVlaWF5WafV3LfL+pdA+hHAp8Gngk0DPtE8IISwCngaeAO6NMc4obouSJEna0jnnZA/jA/if/4HLL4d27bLX2h5XXZVPnUGD4KST8qklSZIkSZIkSZKkivJYynwrYGfg9RL0IklSizVqFHzta7BkSbY6f/oTzJsH/fvn09em7rsve43jjsteQ5IkSZIkSZIkSS2Hty5tghjj7BDCUcD9wG5F3Oo14PgY45wi7lFSMcYrQwjQtEC+LK6KMeZ06b8kSZIkSZIkVbfa2vogszQxwvLljQf1bRnit3x58ftX87d+ffL9tHAhPPts4bUhQI8eDQf39e6dhPptOrp1S8L+JEmSJOVul5T5OmBBkXt4O2V+lyLvXwq9geu38XN6AcdvGP8eQngNuAn4dYzx3Zz7kyRJUgN22QWOPhoeeSRbnYULYdy4JNyv1KZMgfvvz6fWN76RvF8lSZIkSZIkSZKkZuedJqzpVvQuJElq4dq1g/POg2uvzVanrg5+8Qu4+up8+tromWfg+eez1zGMT5IkSZIkSZIkSdvCML4mijG+FkL4BDAOKMbbcvcDo2OMy4pQu6w2BPI9D9wMdMq5/ErgnBjjhJzrSpIkSZIkSVKLEAJ07ZqMIUPS169aBYsWNRzUt+XjokVJ2J+URYyweHEymnLxVU1NEt63ZUjfpqNXr80/7tQp+W9BkiRJUkE7pswvijGuL3IPaTdy6hBC6NYcz8HaRoOBa4HvhBB+AlwXY1xd5p4kSZKavXPPzR7GB3DddXD22aX/u/VVV+VTZ6edkmMhSZIkSZIkSZKkZmlRE9a0L3oXkiSJCy+En/wk+3W8P/85fPOb0LlzPn0B3HFH9hq9esHQodnrSJIkSZIkSZIkqeUwjG8bxBjfBY4PIZxFcrOi3jmUXQhcHmO8PYdaFSvG+PsQwiTgemBETmUnAF+LMb6VUz1JkiRJkiRJUor27WHnnZORpq4uCVDbMqivofC+BQtgzZri96/mb/36JAhyUVMu796gTZutA/u6d0/GDjtsPjZ9zRA/SZIktTA9UuYXlqCHBU1Y0wNo6WF8G3UDrgHOCCGcFWN8qtwNSZIkNWfDh0O3brAs4/8bfe45eOghOPbYfPpqir//He67L59a3/42tG2bTy1JkiRJkiRJkiRVnA5NWLO66F1IkiQGDYLjj89+zse778JNN8Fll+XTV10d3Hln9jqf/jTU1GSvI0mSJEmSJEmSpJbDML7tEGO8LYQwATgL+Arw0e0o8wLwc+DWGOMHefZXqTaE5o0MIQwDvkYSytd+G8usIgnh++8Y4/ScW5QkSZIkSZIk5ai2Fvr0ScbeexdeGyMsX95wUF9DIX7Ll5fma1DLsGYNvP12MrZFq1Zbh/VtGdjX2GsdOhjkJ0mSpKrTPWW+FL+pNWWP7sDrxW6kynwUeCKE8C8xxtvK3YwkSVJz1b49/Mu/wLXXZq913XWlC+Orq4NLL82nVv/+cN55+dSSJEmSJEmSJElSRRrQhDXvFr0LSZIEwEUXZQ/jg+Rcla98Bdq2zV5r4sRtv1azIccdl72GJEmSJEmSJEmSWhbD+LZTjPF94AbghhDCEOB4YBjwMaA/0BnoAHwArADeIgngmwbcF2N8tYS9vglUzO1cY4zTgDEhhH8BjgIOB/YChgA7kBw7SI7bUuAV4HngUWBijHFVqXuWJEmSJEmSJBVXCNC1azKGDElfv3p1fTDfO+/AvHnJxTnz5m3+fOnS4veulmvdOli0KBnbqrY2+X7v0qX+e7+hUWi+Uyeoqcn/65IkSZIasUPK/IpiNxBjXBtC+BAodJuHtNDAlqoNcGsIoU+MMYd4mOILIVwMXFSCrXYrwR6SJKmFuOSS5OZk69Zlq/PAA/Dcc7DXXvn0Vcgtt8DMmfnU+va387kpmyRJkiRJkiRJkirWsJT5dcDsUjQiSZLgM5+BgQNhdsb/9X37bbj9drjgguw9jR2bvUYIcOyx2etIkiRJkiRJkiTp/7F372GSluWdgH9vz0z3HDjKGQRUBAWJK5IRg1EjeCQmSnRRVBCN8RRB1MBkVMT1hAKJijFBV1eIm4QoKhhRA2pQ10hQIR7wgEFZQREYkAGGOc+7f3w9y4AzXd1TX1V1dd/3db3XdNX79PM+3V7M1/Z8Vb/ZRRhfC2qt16YJjGMKxkP1LhlfAAAAAAAwafPnJ/vs06yJrFrVvAhoYzj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fontsize=14)\n","plt.xlabel('t')\n","plt.legend(fontsize=9)\n","\n","plt.subplot(2, 3, 4)\n","plt.plot(t_eval.numpy(), 1 * np.ones_like(t_eval.numpy()), 'k--', linewidth=0.5)\n","plt.plot(t_eval.numpy(), 0 * np.ones_like(t_eval.numpy()), 'k-', linewidth=0.5)\n","plt.plot(t_eval.numpy(), y_traj[:, 1], 'b--', label=r\"$\\cos(q_2)$\", linewidth=LINE_WIDTH)\n","plt.plot(t_eval.numpy(), y_traj[:, 3], 'b-', label=r\"$\\sin(q_2)$\", linewidth=LINE_WIDTH)\n","plt.title(\"$q_2$\", fontsize=14)\n","plt.xlabel('t')\n","plt.legend(fontsize=9)\n","\n","plt.subplot(2, 3, 2)\n","plt.plot(t_eval.numpy(), 0 * np.ones_like(t_eval.numpy()), 'k-', linewidth=0.5)\n","plt.plot(t_eval.numpy(), y_traj[:, 4], color='b', linewidth=LINE_WIDTH)\n","plt.title(\"$\\dot{q}_1$\", fontsize=14)\n","plt.xlabel('t')\n","\n","plt.subplot(2, 3, 5)\n","plt.plot(t_eval.numpy(), 0 * np.ones_like(t_eval.numpy()), 'k-', linewidth=0.5)\n","plt.plot(t_eval.numpy(), y_traj[:, 5], color='b', linewidth=LINE_WIDTH)\n","plt.title(\"$\\dot{q}_2$\", fontsize=14)\n","plt.xlabel('t')\n","\n","plt.subplot(2, 3, 3)\n","plt.plot(t_eval.numpy(), 0 * np.ones_like(t_eval.numpy()), 'k-', linewidth=0.5)\n","plt.plot(t_eval.numpy(), y_traj[:, 6], color='b', linewidth=LINE_WIDTH)\n","plt.title(\"$u_1$\", fontsize=14)\n","plt.xlabel('t')\n","\n","plt.subplot(2, 3, 6)\n","plt.plot(t_eval.numpy(), 0 * np.ones_like(t_eval.numpy()), 'k-', linewidth=0.5)\n","plt.plot(t_eval.numpy(), y_traj[:, 7], color='b', linewidth=LINE_WIDTH)\n","plt.title(\"$u_2$\", fontsize=14)\n","plt.xlabel('t')\n","\n","plt.tight_layout()\n","# fig.savefig('{}/fig-fa-acrobot-ctrl.{}'.format(args.fig_dir, FORMAT))\n"]},{"cell_type":"code","execution_count":0,"metadata":{},"outputs":[],"source":[""]}],"nbformat":4,"nbformat_minor":2,"metadata":{"language_info":{"name":"python","codemirror_mode":{"name":"ipython","version":3},"version":"3.7.4-final"},"orig_nbformat":2,"file_extension":".py","mimetype":"text/x-python","name":"python","npconvert_exporter":"python","pygments_lexer":"ipython3","version":3,"kernelspec":{"name":"python37464bitembedvenv00bda69ab17746c28ffa9a3e65936c26","display_name":"Python 3.7.4 64-bit ('embed': venv)"}}}