{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "9e129b4e",
   "metadata": {},
   "source": [
    "# Data plotting\n",
    "\n",
    "This notebook is a tutorial on working with Tidy3D output data.\n",
    "\n",
    "We will cover:\n",
    "\n",
    "- Accessing data.\n",
    "\n",
    "- Manipulating data.\n",
    "\n",
    "- Visualizing data.\n",
    "\n",
    "First we import the packages we'll need."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a22293a5",
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2023-02-03T04:13:17.798920Z",
     "iopub.status.idle": "2023-02-03T04:13:18.859528Z",
     "shell.execute_reply": "2023-02-03T04:13:18.859114Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[22:13:18] </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING </span> This version of Tidy3D was pip installed from the <span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d-beta'</span> repository on   <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#103\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">103</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         PyPI. Future releases will be uploaded to the <span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d'</span> repository. From now on, <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         please use <span style=\"color: #008000; text-decoration-color: #008000\">'pip install tidy3d'</span> instead.                                        <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[22:13:18]\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING \u001b[0m This version of Tidy3D was pip installed from the \u001b[32m'tidy3d-beta'\u001b[0m repository on   \u001b]8;id=587745;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=646744;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#103\u001b\\\u001b[2m103\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m         PyPI. Future releases will be uploaded to the \u001b[32m'tidy3d'\u001b[0m repository. From now on, \u001b[2m               \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m         please use \u001b[32m'pip install tidy3d'\u001b[0m instead.                                        \u001b[2m               \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Using client version: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9</span>.0rc1                                                  <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">121</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Using client version: \u001b[1;36m1.9\u001b[0m.0rc1                                                  \u001b]8;id=213153;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=999542;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\u001b\\\u001b[2m121\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc1c1323",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "### Creating Simulation\n",
    "\n",
    "First, let's make a [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Simulation.html) so we have data to plot.\n",
    "\n",
    "We will add each possible type of monitor into the simultion to explore their output data separately."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "61c49575",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:18.861941Z",
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     "iopub.status.idle": "2023-02-03T04:13:18.871605Z",
     "shell.execute_reply": "2023-02-03T04:13:18.871235Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# simulation parameters\n",
    "Lx, Ly, Lz = 5, 5, 5\n",
    "min_steps_per_wvl = 32\n",
    "\n",
    "# monitor parameters\n",
    "freq0 = 2e14\n",
    "freqs = np.linspace(1e14, 3e14, 11)\n",
    "num_modes = 3\n",
    "\n",
    "simulation = td.Simulation(\n",
    "    size=(Lx, Ly, Lz),\n",
    "    grid_spec=td.GridSpec.auto(min_steps_per_wvl=min_steps_per_wvl),\n",
    "    run_time=4e-13,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    structures=[\n",
    "        td.Structure(\n",
    "            geometry=td.Box(center=(0, 0, 0), size=(10001, 1.4, 1.5)),\n",
    "            medium=td.Medium(permittivity=2),\n",
    "            name=\"waveguide\",\n",
    "        ),\n",
    "        td.Structure(\n",
    "            geometry=td.Box(center=(0, 0.5, 0.5), size=(1.5, 1.4, 1.5)),\n",
    "            medium=td.Medium(permittivity=2),\n",
    "            name=\"scatterer\",\n",
    "        ),\n",
    "    ],\n",
    "    sources=[\n",
    "        td.ModeSource(\n",
    "            source_time=td.GaussianPulse(freq0=freq0, fwidth=6e13),\n",
    "            center=(-2.0, 0.0, 0.0),\n",
    "            size=(0.0, 3, 3),\n",
    "            direction=\"+\",\n",
    "            mode_spec=td.ModeSpec(),\n",
    "            mode_index=0,\n",
    "        )\n",
    "    ],\n",
    "    monitors=[\n",
    "        td.FieldMonitor(\n",
    "            fields=[\"Ex\", \"Ey\", \"Ez\"],\n",
    "            size=(td.inf, 0, td.inf),\n",
    "            center=(0, 0, 0),\n",
    "            freqs=freqs,\n",
    "            name=\"field\",\n",
    "        ),\n",
    "        td.FieldTimeMonitor(\n",
    "            fields=[\"Ex\", \"Ey\", \"Ez\"],\n",
    "            size=(td.inf, 0, td.inf),\n",
    "            center=(0, 0, 0),\n",
    "            interval=200,\n",
    "            name=\"field_time\",\n",
    "        ),\n",
    "        td.FluxMonitor(size=(0, 3, 3), center=(2, 0, 0), freqs=freqs, name=\"flux\"),\n",
    "        td.FluxTimeMonitor(\n",
    "            size=(0, 3, 3), center=(2, 0, 0), interval=10, name=\"flux_time\"\n",
    "        ),\n",
    "        td.ModeMonitor(\n",
    "            size=(0, 3, 3),\n",
    "            center=(2, 0, 0),\n",
    "            freqs=freqs,\n",
    "            mode_spec=td.ModeSpec(num_modes=num_modes),\n",
    "            name=\"mode\",\n",
    "        ),\n",
    "    ],\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "004348be",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:18.873720Z",
     "iopub.status.busy": "2023-02-03T04:13:18.873561Z",
     "iopub.status.idle": "2023-02-03T04:13:18.909844Z",
     "shell.execute_reply": "2023-02-03T04:13:18.909463Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Auto meshing using wavelength <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.4990</span> defined from sources.                     <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">grid_spec.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">510</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m1.4990\u001b[0m defined from sources.                     \u001b]8;id=140113;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=836177;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "monitor field requires 7.06e+06 bytes of storage.\n",
      "monitor field_time requires 1.06e+07 bytes of storage.\n",
      "monitor flux requires 4.40e+01 bytes of storage.\n",
      "monitor flux_time requires 2.65e+03 bytes of storage.\n",
      "monitor mode requires 7.92e+02 bytes of storage.\n"
     ]
    }
   ],
   "source": [
    "tmesh = simulation.tmesh\n",
    "\n",
    "total_size_bytes = 0\n",
    "for monitor in simulation.monitors:\n",
    "    monitor_grid = simulation.discretize(monitor)\n",
    "    num_cells = np.prod(monitor_grid.num_cells)\n",
    "    monitor_size = monitor.storage_size(num_cells=num_cells, tmesh=tmesh)\n",
    "    print(f\"monitor {monitor.name} requires {monitor_size:.2e} bytes of storage.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3748bef",
   "metadata": {},
   "source": [
    "### Visualize Geometry\n",
    "\n",
    "We've created a simple waveguide with a defect / scattering region defined using a [Box](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Box.html) geometry.\n",
    "\n",
    "A modal source is injected from the -x side of the simulation and we measure the mode amplitudes and flux at the +x side.\n",
    "\n",
    "We've also placed a couple field monitors to visualize the field patterns.\n",
    "\n",
    "Let's take a look at the geometry from a few cross sections."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3f7e72a2",
   "metadata": {
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     "shell.execute_reply": "2023-02-03T04:13:19.200682Z"
    },
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   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1400x400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 4))\n",
    "simulation.plot(x=0.0, ax=ax1)\n",
    "simulation.plot(y=0.01, ax=ax2)\n",
    "simulation.plot(z=0.01, ax=ax3)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db68e728",
   "metadata": {},
   "source": [
    "### Make normalization Simulation\n",
    "\n",
    "For purposes of demonstration, let's create another simulation without the scatterer, so we can compare what the data should look like for just the straight waveguide case.\n",
    "\n",
    "This is as simple as making a copy of the original simulation and removing the scatterer from the list of structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "bf9aedee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:19.203218Z",
     "iopub.status.busy": "2023-02-03T04:13:19.203058Z",
     "iopub.status.idle": "2023-02-03T04:13:19.209460Z",
     "shell.execute_reply": "2023-02-03T04:13:19.209079Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# get rid of scatterer for normalization\n",
    "simulation0 = simulation.copy(update=dict(structures=[simulation.structures[0]]))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "653a3b32",
   "metadata": {},
   "source": [
    "### Running simulations\n",
    "\n",
    "Now we will run both simulations and load them into [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html) objects.\n",
    "\n",
    "Since these will be a short and simple simulations, we can use the [web.run](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.web.webapi.run.html) function to do them all in one line."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "bedb64a3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:13:19.211552Z",
     "iopub.status.busy": "2023-02-03T04:13:19.211391Z",
     "iopub.status.idle": "2023-02-03T04:14:18.982955Z",
     "shell.execute_reply": "2023-02-03T04:14:18.982461Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[22:13:19] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Auto meshing using wavelength <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.4990</span> defined from sources.                     <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">grid_spec.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">510</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[22:13:19]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m1.4990\u001b[0m defined from sources.                     \u001b]8;id=25206;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=78446;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'0e0eb225-cb57-4d75-ace5-e629a3cca53b'</span>.                                           <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Created task \u001b[32m'straight waveguide'\u001b[0m with task_id                                    \u001b]8;id=305125;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=117436;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\u001b\\\u001b[2m120\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m         \u001b[32m'0e0eb225-cb57-4d75-ace5-e629a3cca53b'\u001b[0m.                                           \u001b[2m             \u001b[0m\n"
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       "</pre>\n"
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       "</pre>\n"
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       "\u001b[2;36m           \u001b[0m         \u001b[32m'd5822894-1f5a-442e-b567-758da4a88da1'\u001b[0m.                                           \u001b[2m             \u001b[0m\n"
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       "\u001b[2;36m[22:13:59]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m starting up solver                                                                \u001b]8;id=806902;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=639691;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#278\u001b\\\u001b[2m278\u001b[0m\u001b]8;;\u001b\\\n"
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       "\n",
       "\u001b[?25h\r",
       "\u001b[1A\u001b[2K"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[22:14:16] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Billed FlexUnit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>                                                       <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#311\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">311</span></a>\n",
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       "\u001b[2;36m[22:14:16]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Billed FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                       \u001b]8;id=35296;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=535972;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#311\u001b\\\u001b[2m311\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[2;36m[22:14:18]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/simulation.hdf5                                  \u001b]8;id=322845;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=650089;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#415\u001b\\\u001b[2m415\u001b[0m\u001b]8;;\u001b\\\n"
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   "source": [
    "sim0_data = web.run(\n",
    "    simulation0, task_name=\"straight waveguide\", path=\"data/simulation.hdf5\"\n",
    ")\n",
    "sim_data = web.run(\n",
    "    simulation, task_name=\"scattered waveguide\", path=\"data/simulation.hdf5\"\n",
    ")\n"
   ]
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  {
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   "source": [
    "### Inspecting Log\n",
    "\n",
    "Now let's take a look at the log to see if everything looks ok (fields decayed, etc)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3e528e33",
   "metadata": {
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     "shell.execute_reply": "2023-02-03T04:14:20.028376Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulation domain Nx, Ny, Nz: [176, 152, 152]\n",
      "Applied symmetries: (0, 0, 0)\n",
      "Number of computational grid points: 4.2214e+06.\n",
      "Using subpixel averaging: True\n",
      "Number of time steps: 6.6230e+03\n",
      "Automatic shutoff factor: 1.00e-05\n",
      "Time step (s): 6.0408e-17\n",
      "\n",
      "\n",
      "Compute source modes time (s):     0.5539\n",
      "Compute monitor modes time (s):    2.2783\n",
      "Rest of setup time (s):            2.6144\n",
      "\n",
      "Running solver for 6623 time steps...\n",
      "- Time step    220 / time 1.33e-14s (  3 % done), field decay: 1.00e+00\n",
      "- Time step    264 / time 1.59e-14s (  4 % done), field decay: 1.00e+00\n",
      "- Time step    529 / time 3.20e-14s (  8 % done), field decay: 1.00e+00\n",
      "- Time step    794 / time 4.80e-14s ( 12 % done), field decay: 8.03e-04\n",
      "- Time step   1059 / time 6.40e-14s ( 16 % done), field decay: 1.36e-06\n",
      "Field decay smaller than shutoff factor, exiting solver.\n",
      "\n",
      "Solver time (s):                   2.7127\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(sim_data.log)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce4a54c3",
   "metadata": {},
   "source": [
    "## Post-Processing\n",
    "\n",
    "Now that the simulations have run and their data are loaded into the `sim_data` and `sim0_data` variables, we will explore how to access, manipulate, and visualize the data.  \n",
    "\n",
    "### Accessing Data\n",
    "\n",
    "#### Original Simulation\n",
    "\n",
    "The [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html) objects store a copy of the original [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Simulation.html), so it can be recovered if the [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html) is loaded in a new session and the [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Simulation.html) is no longer in memory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2c3ef22b",
   "metadata": {
    "execution": {
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     "iopub.status.busy": "2023-02-03T04:14:20.031235Z",
     "iopub.status.idle": "2023-02-03T04:14:20.033362Z",
     "shell.execute_reply": "2023-02-03T04:14:20.033040Z"
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5.0, 5.0, 5.0)\n"
     ]
    }
   ],
   "source": [
    "print(sim_data.simulation.size)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "30e26ff6",
   "metadata": {},
   "source": [
    "#### Monitor Data\n",
    "\n",
    "More importantly, the [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html) contains a reference to the data for each of the monitors within the original [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Simulation.html).\n",
    "This data can be accessed directly using the `name` given to the monitors initially.\n",
    "\n",
    "For example, our [FluxMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FluxMonitor.html) was named `'flux'` while our [FluxTimeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FluxTimeMonitor.html) was named `'flux_time'`, each with a `.flux` attribute storing the raw data. Therefore, we can access the data as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "58af7e8c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.035356Z",
     "iopub.status.busy": "2023-02-03T04:14:20.035191Z",
     "iopub.status.idle": "2023-02-03T04:14:20.038552Z",
     "shell.execute_reply": "2023-02-03T04:14:20.038186Z"
    },
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   },
   "outputs": [],
   "source": [
    "# get the flux data from the monitor name\n",
    "flux_data = sim_data[\"flux\"].flux\n",
    "flux_time_data = sim_data[\"flux_time\"].flux\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8f9f3a94",
   "metadata": {},
   "source": [
    "### Structure of Data\n",
    "\n",
    "Now that we have the data loaded, let's inspect it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d672a805",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.040545Z",
     "iopub.status.busy": "2023-02-03T04:14:20.040430Z",
     "iopub.status.idle": "2023-02-03T04:14:20.049440Z",
     "shell.execute_reply": "2023-02-03T04:14:20.049140Z"
    },
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       "\n",
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       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
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       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
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       "  white-space: pre-wrap;\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.FluxDataArray (f: 11)&gt;\n",
       "array([0.591912  , 0.7745048 , 0.8931    , 0.95288116, 0.97218627,\n",
       "       0.9766828 , 0.9795849 , 0.9839063 , 0.9879946 , 0.9901106 ,\n",
       "       0.99019235], dtype=float32)\n",
       "Coordinates:\n",
       "  * f        (f) float64 1e+14 1.2e+14 1.4e+14 1.6e+14 ... 2.6e+14 2.8e+14 3e+14\n",
       "Attributes:\n",
       "    units:      W\n",
       "    long_name:  flux</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.FluxDataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>f</span>: 11</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4a298f86-8e03-4337-a982-335ed1e78506' class='xr-array-in' type='checkbox' checked><label for='section-4a298f86-8e03-4337-a982-335ed1e78506' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.5919 0.7745 0.8931 0.9529 0.9722 ... 0.9839 0.988 0.9901 0.9902</span></div><div class='xr-array-data'><pre>array([0.591912  , 0.7745048 , 0.8931    , 0.95288116, 0.97218627,\n",
       "       0.9766828 , 0.9795849 , 0.9839063 , 0.9879946 , 0.9901106 ,\n",
       "       0.99019235], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-3f7365f7-792f-4c79-915e-6b1220fada71' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3f7365f7-792f-4c79-915e-6b1220fada71' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>f</span></div><div class='xr-var-dims'>(f)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+14 1.2e+14 ... 2.8e+14 3e+14</div><input id='attrs-062c282d-c908-4841-87e2-e2df08197e95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-062c282d-c908-4841-87e2-e2df08197e95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79625c12-0034-4ca3-86c2-e0fb825dfdeb' class='xr-var-data-in' type='checkbox'><label for='data-79625c12-0034-4ca3-86c2-e0fb825dfdeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd></dl></div><div class='xr-var-data'><pre>array([1.0e+14, 1.2e+14, 1.4e+14, 1.6e+14, 1.8e+14, 2.0e+14, 2.2e+14, 2.4e+14,\n",
       "       2.6e+14, 2.8e+14, 3.0e+14])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b19f31d0-0280-4125-8183-f03d92621dfe' class='xr-section-summary-in' type='checkbox'  ><label for='section-b19f31d0-0280-4125-8183-f03d92621dfe' class='xr-section-summary' >Indexes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>f</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ce8800ab-af38-4b58-94d4-cd90f87708ce' class='xr-index-data-in' type='checkbox'/><label for='index-ce8800ab-af38-4b58-94d4-cd90f87708ce' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([100000000000000.0, 120000000000000.0, 140000000000000.0,\n",
       "              160000000000000.0, 180000000000000.0, 200000000000000.0,\n",
       "              220000000000000.0, 240000000000000.0, 260000000000000.0,\n",
       "              280000000000000.0, 300000000000000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;f&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6d17e466-5f02-4390-98f0-9d854e18df88' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6d17e466-5f02-4390-98f0-9d854e18df88' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>W</dd><dt><span>long_name :</span></dt><dd>flux</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.FluxDataArray (f: 11)>\n",
       "array([0.591912  , 0.7745048 , 0.8931    , 0.95288116, 0.97218627,\n",
       "       0.9766828 , 0.9795849 , 0.9839063 , 0.9879946 , 0.9901106 ,\n",
       "       0.99019235], dtype=float32)\n",
       "Coordinates:\n",
       "  * f        (f) float64 1e+14 1.2e+14 1.4e+14 1.6e+14 ... 2.6e+14 2.8e+14 3e+14\n",
       "Attributes:\n",
       "    units:      W\n",
       "    long_name:  flux"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flux_data\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84f11714",
   "metadata": {},
   "source": [
    "The data is stored as a [DataArray](https://xarray.pydata.org/en/stable/generated/xarray.DataArray.html) object using the [xarray](https://xarray.pydata.org/en/stable/) package.\n",
    "You can think of it as a dataset where the flux data is stored as a large, multi-dimensional array (like a numpy array) and the coordinates along each of the dimensions are specified so it is easy to work with.\n",
    "\n",
    "For example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f27c9e1d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.051625Z",
     "iopub.status.busy": "2023-02-03T04:14:20.051454Z",
     "iopub.status.idle": "2023-02-03T04:14:20.054346Z",
     "shell.execute_reply": "2023-02-03T04:14:20.054042Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "shape of flux dataset = (11,)\n",
      ".\n",
      "frequencies in dataset = <bound method Mapping.values of Coordinates:\n",
      "  * f        (f) float64 1e+14 1.2e+14 1.4e+14 1.6e+14 ... 2.6e+14 2.8e+14 3e+14> \n",
      ".\n",
      "flux values in dataset = [0.591912   0.7745048  0.8931     0.95288116 0.97218627 0.9766828\n",
      " 0.9795849  0.9839063  0.9879946  0.9901106  0.99019235]\n",
      ".\n"
     ]
    }
   ],
   "source": [
    "# flux values (W) as numpy array\n",
    "print(f\"shape of flux dataset = {flux_data.shape}\\n.\")\n",
    "print(f\"frequencies in dataset = {flux_data.coords.values} \\n.\")\n",
    "print(f\"flux values in dataset = {flux_data.values}\\n.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "46e4f0da",
   "metadata": {},
   "source": [
    "So we can see the datset stores a 1D array of flux values (Watts) and a 1D array of frequency values (Hz).\n",
    "\n",
    "### Manipulating Data\n",
    "\n",
    "We can now do some useful operations with this data, including:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8774d777",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.056441Z",
     "iopub.status.busy": "2023-02-03T04:14:20.056255Z",
     "iopub.status.idle": "2023-02-03T04:14:20.059008Z",
     "shell.execute_reply": "2023-02-03T04:14:20.058691Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "at central frequency, flux is 9.77e-01 W\n"
     ]
    }
   ],
   "source": [
    "# Selecting data at a specific coordinate\n",
    "flux_central_freq = flux_data.sel(f=freq0)\n",
    "print(f\"at central frequency, flux is {float(flux_central_freq):.2e} W\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0c2defca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.061073Z",
     "iopub.status.busy": "2023-02-03T04:14:20.060899Z",
     "iopub.status.idle": "2023-02-03T04:14:20.063265Z",
     "shell.execute_reply": "2023-02-03T04:14:20.062945Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "at 4th frequency, flux is 9.72e-01 W\n"
     ]
    }
   ],
   "source": [
    "# Selecting data at a specific index\n",
    "flux_4th_freq = flux_data.isel(f=4)\n",
    "print(f\"at 4th frequency, flux is {float(flux_4th_freq):.2e} W\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "e63cfd62",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.065245Z",
     "iopub.status.busy": "2023-02-03T04:14:20.065078Z",
     "iopub.status.idle": "2023-02-03T04:14:20.167113Z",
     "shell.execute_reply": "2023-02-03T04:14:20.166293Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "at an intermediate (not stored) frequency, flux is 9.79e-01 W\n"
     ]
    }
   ],
   "source": [
    "# Interpolating data at a specific coordinate\n",
    "flux_interp_freq = flux_data.interp(f=213.243523142e12)\n",
    "print(\n",
    "    f\"at an intermediate (not stored) frequency, flux is {float(flux_interp_freq):.2e} W\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e1cff990",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.170547Z",
     "iopub.status.busy": "2023-02-03T04:14:20.170176Z",
     "iopub.status.idle": "2023-02-03T04:14:20.174945Z",
     "shell.execute_reply": "2023-02-03T04:14:20.174098Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# arithmetic opertions with numbers\n",
    "flux_times_2_plus_1 = 2 * flux_data + 1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "87f3cc32",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.178383Z",
     "iopub.status.busy": "2023-02-03T04:14:20.177963Z",
     "iopub.status.idle": "2023-02-03T04:14:20.182872Z",
     "shell.execute_reply": "2023-02-03T04:14:20.182257Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# operations with dataset (in this case, dividing by the normlization flux)\n",
    "flux_transmission = flux_data / sim0_data[\"flux\"].flux\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d86475df",
   "metadata": {},
   "source": [
    "There are mny more things you can do with the xarray package that are not covered here, so it is best to take a look at [their documention](http://xarray.pydata.org/en/stable/) for more details.\n",
    "\n",
    "### Plotting Data\n",
    "\n",
    "These datasets have built in plotting methods, which can be handy for quickly producing customizable plots.\n",
    "\n",
    "Let's plot the flux data to get a feeling."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3c2c6760",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.186069Z",
     "iopub.status.busy": "2023-02-03T04:14:20.185672Z",
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     "shell.execute_reply": "2023-02-03T04:14:20.557766Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1000x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(10, 3))\n",
    "flux_data.plot(ax=ax1)\n",
    "ax1.set_title(\"flux vs. frequency\")\n",
    "ax1.set_xlim(150e12, 250e12)\n",
    "\n",
    "# plot the ratio of flux with scatterer to without scatterer with dashed line signifying unity transmission.\n",
    "flux_transmission.plot(ax=ax2, color=\"k\")\n",
    "ax2.plot(flux_data.f, np.ones_like(flux_data.f), \"--\")\n",
    "ax2.set_ylabel(\"flux(f) / flux_normalize(f)\")\n",
    "ax2.set_xlabel(\"frequency (Hz)\")\n",
    "ax2.set_title(\"transmission spectrum\")\n",
    "ax2.set_xlim(150e12, 250e12)\n",
    "ax2.set_ylim(-0.1, 1.1)\n",
    "\n",
    "# plot the time dependence of the flux\n",
    "flux_time_data.plot(color=\"crimson\", ax=ax3)\n",
    "ax3.set_title(\"flux vs. time\")\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca03826c",
   "metadata": {},
   "source": [
    "Conveniently, xarray adds a lot of the plot labels and formatting automatically, which can save some time."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e7f17db",
   "metadata": {},
   "source": [
    "### Complex, Multi-dimensional Data\n",
    "\n",
    "While the flux data is 1D and quite simple, the same approaches apply to more complex data, such as mode amplitude and field data, which can be complex-valued and muli-dimensional.\n",
    "\n",
    "Let's use the [ModeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.ModeMonitor.html) data as an example.  We'll access the data using it's name `'mode'` in the original simulation and print out some of the metadata to examine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "28bd7aaf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.560401Z",
     "iopub.status.busy": "2023-02-03T04:14:20.560229Z",
     "iopub.status.idle": "2023-02-03T04:14:20.564800Z",
     "shell.execute_reply": "2023-02-03T04:14:20.564436Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 11, 3)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mode_data = sim_data[\"mode\"]\n",
    "mode_data.amps.shape\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "877d5042",
   "metadata": {},
   "source": [
    "As we can see, the data is complex-valued and contains three dimensions.\n",
    "- a propagation direction for the mode, which is just positive or negative  (+/-)\n",
    "- an index into the list of modes returned by the solver given our initial [ModeSpec](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.ModeSpec.html) specifications.\n",
    "- the frequency of the mode\n",
    "\n",
    "Let's plot the data just to get a feeling for it, using `.sel()` to split the forward and backward propagating modes onto separate plot axes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "aa9bb765",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.566874Z",
     "iopub.status.busy": "2023-02-03T04:14:20.566723Z",
     "iopub.status.idle": "2023-02-03T04:14:20.790810Z",
     "shell.execute_reply": "2023-02-03T04:14:20.790410Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(8, 3))\n",
    "\n",
    "mode_data.amps.sel(direction=\"+\").abs.plot.line(x=\"f\", ax=ax1)\n",
    "mode_data.amps.sel(direction=\"-\").abs.plot.line(x=\"f\", ax=ax2)\n",
    "ax1.set_xlim(150e12, 250e12)\n",
    "ax2.set_xlim(150e12, 250e12)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48ae969a",
   "metadata": {},
   "source": [
    "As before, we can manipulate the data using basic algebra or xarray built ins, for example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5a2b68fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.793166Z",
     "iopub.status.busy": "2023-02-03T04:14:20.792782Z",
     "iopub.status.idle": "2023-02-03T04:14:20.796378Z",
     "shell.execute_reply": "2023-02-03T04:14:20.796021Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# sum abolute value squared of the mode amplitudes to get powers\n",
    "mode_powers = abs(mode_data.amps) ** 2\n",
    "\n",
    "# select the powers at the central frequency only\n",
    "powers_central_freq = mode_powers.sel(f=freq0)\n",
    "\n",
    "# sum the powers over all of the mode indices\n",
    "powers_sum_modes = powers_central_freq.sum(\"mode_index\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99570157",
   "metadata": {},
   "source": [
    "## Field Data\n",
    "\n",
    "Data from a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) or [FieldTimeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldTimeMonitor.html) is more complicated as it contains data from several field components.\n",
    "\n",
    "As such, when we just grab the data by name, we dont get an xarray object, but rather a [FieldData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldData.html) container holding all of the field components.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "68111c23",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.798436Z",
     "iopub.status.busy": "2023-02-03T04:14:20.798302Z",
     "iopub.status.idle": "2023-02-03T04:14:20.811130Z",
     "shell.execute_reply": "2023-02-03T04:14:20.810778Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tidy3d.components.data.monitor_data.FieldData'>\n"
     ]
    }
   ],
   "source": [
    "field_data = sim_data[\"field\"]\n",
    "field0_data = sim0_data[\"field\"]\n",
    "print(type(field_data))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e8d2385",
   "metadata": {
    "tags": []
   },
   "source": [
    "The field_data object contains data for each of the field components in it's `data_dict` dictionary.\n",
    "\n",
    "Let's look at what field components are contined"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "43efb783",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.813167Z",
     "iopub.status.busy": "2023-02-03T04:14:20.813014Z",
     "iopub.status.idle": "2023-02-03T04:14:20.815990Z",
     "shell.execute_reply": "2023-02-03T04:14:20.815598Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['type', 'Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz', 'monitor', 'symmetry', 'symmetry_center', 'grid_expanded', 'grid_primal_correction', 'grid_dual_correction'])\n"
     ]
    }
   ],
   "source": [
    "print(field_data.dict().keys())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e01b21ff",
   "metadata": {},
   "source": [
    "The individual field components, themselves, can be accessed conveniently using a \"dot\" syntax, and are stored similarly to the flux and mode data as xarray data arrays."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "acd7313a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.818129Z",
     "iopub.status.busy": "2023-02-03T04:14:20.817978Z",
     "iopub.status.idle": "2023-02-03T04:14:20.832678Z",
     "shell.execute_reply": "2023-02-03T04:14:20.832292Z"
    },
    "tags": []
   },
   "outputs": [
    {
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       "\n",
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       "  display: inline-block;\n",
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       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
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       "\n",
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       "\n",
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       "}\n",
       "\n",
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       ".xr-var-attrs,\n",
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       "\n",
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       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.ScalarFieldDataArray (x: 178, y: 1, z: 154, f: 11)&gt;\n",
       "array([[[[ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j],\n",
       "         [ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j],\n",
       "         [ 6.43478160e-08+2.2920256e-08j,\n",
       "          -7.46410151e-08+4.1726917e-08j,\n",
       "          -3.07212815e-08-2.5303006e-09j, ...,\n",
       "           2.56144510e-08+2.5176810e-08j,\n",
       "          -3.49830742e-08+3.8806519e-08j,\n",
       "          -1.45186245e-08-1.9318170e-08j],\n",
       "         ...,\n",
       "         [-5.54970967e-08-1.4926345e-08j,\n",
       "...\n",
       "          -2.41072717e-09+5.2363074e-09j],\n",
       "         ...,\n",
       "         [-6.27467078e-10-7.4389943e-09j,\n",
       "           1.45480961e-09+9.0445926e-09j,\n",
       "           2.89787055e-10-5.5823879e-09j, ...,\n",
       "           1.90179317e-09+1.7743294e-09j,\n",
       "          -9.13492282e-10-2.1816593e-09j,\n",
       "           4.50721593e-09-6.2089284e-10j],\n",
       "         [-6.59422794e-10+8.6273655e-10j,\n",
       "           7.13056489e-11+9.2542590e-10j,\n",
       "          -2.19914156e-11-5.1966337e-11j, ...,\n",
       "           8.63919630e-11+4.0660250e-10j,\n",
       "          -1.42005477e-10+1.8165988e-10j,\n",
       "           4.32076513e-10+1.3890591e-10j],\n",
       "         [ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j]]]], dtype=complex64)\n",
       "Coordinates:\n",
       "  * x        (x) float64 -2.913 -2.88 -2.847 -2.814 ... 2.814 2.847 2.88 2.913\n",
       "  * y        (y) float64 0.0\n",
       "  * z        (z) float64 -3.108 -3.061 -3.015 -2.968 ... 2.922 2.968 3.015 3.062\n",
       "  * f        (f) float64 1e+14 1.2e+14 1.4e+14 1.6e+14 ... 2.6e+14 2.8e+14 3e+14\n",
       "Attributes:\n",
       "    long_name:  field value</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.ScalarFieldDataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 178</li><li><span class='xr-has-index'>y</span>: 1</li><li><span class='xr-has-index'>z</span>: 154</li><li><span class='xr-has-index'>f</span>: 11</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f0ed4a8c-386a-4164-b692-10ce20457a99' class='xr-array-in' type='checkbox' checked><label for='section-f0ed4a8c-386a-4164-b692-10ce20457a99' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0j 0j (-0-0j) (-0-0j) 0j 0j ... 0j (-0-0j) (-0+0j) 0j -0j (-0-0j)</span></div><div class='xr-array-data'><pre>array([[[[ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j],\n",
       "         [ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j],\n",
       "         [ 6.43478160e-08+2.2920256e-08j,\n",
       "          -7.46410151e-08+4.1726917e-08j,\n",
       "          -3.07212815e-08-2.5303006e-09j, ...,\n",
       "           2.56144510e-08+2.5176810e-08j,\n",
       "          -3.49830742e-08+3.8806519e-08j,\n",
       "          -1.45186245e-08-1.9318170e-08j],\n",
       "         ...,\n",
       "         [-5.54970967e-08-1.4926345e-08j,\n",
       "...\n",
       "          -2.41072717e-09+5.2363074e-09j],\n",
       "         ...,\n",
       "         [-6.27467078e-10-7.4389943e-09j,\n",
       "           1.45480961e-09+9.0445926e-09j,\n",
       "           2.89787055e-10-5.5823879e-09j, ...,\n",
       "           1.90179317e-09+1.7743294e-09j,\n",
       "          -9.13492282e-10-2.1816593e-09j,\n",
       "           4.50721593e-09-6.2089284e-10j],\n",
       "         [-6.59422794e-10+8.6273655e-10j,\n",
       "           7.13056489e-11+9.2542590e-10j,\n",
       "          -2.19914156e-11-5.1966337e-11j, ...,\n",
       "           8.63919630e-11+4.0660250e-10j,\n",
       "          -1.42005477e-10+1.8165988e-10j,\n",
       "           4.32076513e-10+1.3890591e-10j],\n",
       "         [ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j]]]], dtype=complex64)</pre></div></div></li><li class='xr-section-item'><input id='section-7c07d85e-0c39-487c-bbaf-164071cf6905' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7c07d85e-0c39-487c-bbaf-164071cf6905' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.913 -2.88 -2.847 ... 2.88 2.913</div><input id='attrs-3cb0df32-7d34-41f0-9101-1334ab864965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cb0df32-7d34-41f0-9101-1334ab864965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bab70a8-7809-42e5-8a34-98b535118eb2' class='xr-var-data-in' type='checkbox'><label for='data-9bab70a8-7809-42e5-8a34-98b535118eb2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>um</dd><dt><span>long_name :</span></dt><dd>x position</dd></dl></div><div class='xr-var-data'><pre>array([-2.912736, -2.879717, -2.846698, -2.813679, -2.78066 , -2.747642,\n",
       "       -2.714623, -2.681604, -2.648585, -2.615566, -2.582547, -2.549528,\n",
       "       -2.516509, -2.483491, -2.450472, -2.417453, -2.384434, -2.351415,\n",
       "       -2.318396, -2.285377, -2.252358, -2.21934 , -2.186321, -2.153302,\n",
       "       -2.120283, -2.087264, -2.054245, -2.021226, -1.988208, -1.955189,\n",
       "       -1.92217 , -1.889151, -1.856132, -1.823113, -1.790094, -1.757075,\n",
       "       -1.724057, -1.691038, -1.658019, -1.625   , -1.591981, -1.558962,\n",
       "       -1.525943, -1.492925, -1.459906, -1.426887, -1.393868, -1.360849,\n",
       "       -1.32783 , -1.294811, -1.261792, -1.228774, -1.195755, -1.162736,\n",
       "       -1.129717, -1.096698, -1.063679, -1.03066 , -0.997642, -0.964623,\n",
       "       -0.931604, -0.898585, -0.865566, -0.832547, -0.799528, -0.766509,\n",
       "       -0.733696, -0.701087, -0.668478, -0.63587 , -0.603261, -0.570652,\n",
       "       -0.538043, -0.505435, -0.472826, -0.440217, -0.407609, -0.375   ,\n",
       "       -0.342391, -0.309783, -0.277174, -0.244565, -0.211957, -0.179348,\n",
       "       -0.146739, -0.11413 , -0.081522, -0.048913, -0.016304,  0.016304,\n",
       "        0.048913,  0.081522,  0.11413 ,  0.146739,  0.179348,  0.211957,\n",
       "        0.244565,  0.277174,  0.309783,  0.342391,  0.375   ,  0.407609,\n",
       "        0.440217,  0.472826,  0.505435,  0.538043,  0.570652,  0.603261,\n",
       "        0.63587 ,  0.668478,  0.701087,  0.733696,  0.766509,  0.799528,\n",
       "        0.832547,  0.865566,  0.898585,  0.931604,  0.964623,  0.997642,\n",
       "        1.03066 ,  1.063679,  1.096698,  1.129717,  1.162736,  1.195755,\n",
       "        1.228774,  1.261792,  1.294811,  1.32783 ,  1.360849,  1.393868,\n",
       "        1.426887,  1.459906,  1.492925,  1.525943,  1.558962,  1.591981,\n",
       "        1.625   ,  1.658019,  1.691038,  1.724057,  1.757075,  1.790094,\n",
       "        1.823113,  1.856132,  1.889151,  1.92217 ,  1.955189,  1.988208,\n",
       "        2.021226,  2.054245,  2.087264,  2.120283,  2.153302,  2.186321,\n",
       "        2.21934 ,  2.252358,  2.285377,  2.318396,  2.351415,  2.384434,\n",
       "        2.417453,  2.450472,  2.483491,  2.516509,  2.549528,  2.582547,\n",
       "        2.615566,  2.648585,  2.681604,  2.714623,  2.747642,  2.78066 ,\n",
       "        2.813679,  2.846698,  2.879717,  2.912736])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-8f4fb103-4df2-480d-a5da-564146da3f0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f4fb103-4df2-480d-a5da-564146da3f0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b2ec84-ddac-4a43-bb3d-86c8a62d8b73' class='xr-var-data-in' type='checkbox'><label for='data-f0b2ec84-ddac-4a43-bb3d-86c8a62d8b73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>um</dd><dt><span>long_name :</span></dt><dd>y position</dd></dl></div><div class='xr-var-data'><pre>array([0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>z</span></div><div class='xr-var-dims'>(z)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.108 -3.061 ... 3.015 3.062</div><input id='attrs-800bff62-884c-4344-a4d3-96466736e4ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-800bff62-884c-4344-a4d3-96466736e4ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dddf9ba-8136-448c-ab9d-290231ed9302' class='xr-var-data-in' type='checkbox'><label for='data-6dddf9ba-8136-448c-ab9d-290231ed9302' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>um</dd><dt><span>long_name :</span></dt><dd>z position</dd></dl></div><div class='xr-var-data'><pre>array([-3.108277, -3.061435, -3.014649, -2.967862, -2.921076, -2.87429 ,\n",
       "       -2.827504, -2.780717, -2.733931, -2.687145, -2.640359, -2.593572,\n",
       "       -2.546786, -2.5     , -2.453214, -2.406428, -2.359641, -2.312855,\n",
       "       -2.266069, -2.219283, -2.172496, -2.12571 , -2.078924, -2.032138,\n",
       "       -1.985351, -1.938565, -1.891779, -1.844993, -1.798206, -1.75142 ,\n",
       "       -1.704634, -1.657848, -1.611062, -1.564275, -1.517489, -1.470703,\n",
       "       -1.423917, -1.37713 , -1.330344, -1.283558, -1.236772, -1.189985,\n",
       "       -1.143199, -1.096413, -1.049627, -1.00284 , -0.956054, -0.909268,\n",
       "       -0.862482, -0.816166, -0.783083, -0.75    , -0.71875 , -0.6875  ,\n",
       "       -0.65625 , -0.625   , -0.59375 , -0.5625  , -0.53125 , -0.5     ,\n",
       "       -0.46875 , -0.4375  , -0.40625 , -0.375   , -0.34375 , -0.3125  ,\n",
       "       -0.28125 , -0.25    , -0.217742, -0.185484, -0.153226, -0.120968,\n",
       "       -0.08871 , -0.056452, -0.024194,  0.008065,  0.040323,  0.072581,\n",
       "        0.104839,  0.137097,  0.169355,  0.201613,  0.233871,  0.266129,\n",
       "        0.298387,  0.330645,  0.362903,  0.395161,  0.427419,  0.459677,\n",
       "        0.491935,  0.524194,  0.556452,  0.58871 ,  0.620968,  0.653226,\n",
       "        0.685484,  0.717742,  0.75    ,  0.78125 ,  0.8125  ,  0.84375 ,\n",
       "        0.875   ,  0.90625 ,  0.9375  ,  0.96875 ,  1.      ,  1.03125 ,\n",
       "        1.0625  ,  1.09375 ,  1.125   ,  1.15625 ,  1.1875  ,  1.21875 ,\n",
       "        1.25    ,  1.283123,  1.329407,  1.375778,  1.422621,  1.469463,\n",
       "        1.516306,  1.563149,  1.609991,  1.656834,  1.703676,  1.750519,\n",
       "        1.797361,  1.844204,  1.891047,  1.937889,  1.984732,  2.031574,\n",
       "        2.078417,  2.125259,  2.172102,  2.218945,  2.265787,  2.31263 ,\n",
       "        2.359472,  2.406315,  2.453157,  2.5     ,  2.546843,  2.593685,\n",
       "        2.640528,  2.68737 ,  2.734213,  2.781055,  2.827898,  2.874741,\n",
       "        2.921583,  2.968426,  3.015268,  3.062111])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>f</span></div><div class='xr-var-dims'>(f)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1e+14 1.2e+14 ... 2.8e+14 3e+14</div><input id='attrs-d47225f5-9aeb-4b68-bf28-bdc7688a8dc5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d47225f5-9aeb-4b68-bf28-bdc7688a8dc5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f4645a8-1f2b-4bd6-a22d-542d504846a8' class='xr-var-data-in' type='checkbox'><label for='data-0f4645a8-1f2b-4bd6-a22d-542d504846a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>frequency</dd></dl></div><div class='xr-var-data'><pre>array([1.0e+14, 1.2e+14, 1.4e+14, 1.6e+14, 1.8e+14, 2.0e+14, 2.2e+14, 2.4e+14,\n",
       "       2.6e+14, 2.8e+14, 3.0e+14])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-040aa9bb-cefa-4597-a2ea-3310068fefde' class='xr-section-summary-in' type='checkbox'  ><label for='section-040aa9bb-cefa-4597-a2ea-3310068fefde' class='xr-section-summary' >Indexes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-54109cb3-1fcb-47c3-8ad5-76cfc3b0a683' class='xr-index-data-in' type='checkbox'/><label for='index-54109cb3-1fcb-47c3-8ad5-76cfc3b0a683' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([  -2.91273584905661,  -2.879716981132077,  -2.846698113207549,\n",
       "                -2.81367924528302,  -2.780660377358492, -2.7476415094339632,\n",
       "               -2.714622641509435, -2.6816037735849063, -2.6485849056603783,\n",
       "              -2.6155660377358494,\n",
       "              ...\n",
       "                2.615566037735879,   2.648584905660416,   2.681603773584953,\n",
       "                 2.71462264150949,  2.7476415094340267,  2.7806603773585636,\n",
       "               2.8136792452831005,  2.8466981132076374,  2.8797169811321743,\n",
       "               2.9127358490567072],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=178))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f3173066-1467-4e92-a1be-8a3c76cb05a7' class='xr-index-data-in' type='checkbox'/><label for='index-f3173066-1467-4e92-a1be-8a3c76cb05a7' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([0.0], dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>z</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3feca325-0d6e-401f-b53b-a884f8a2c4c2' class='xr-index-data-in' type='checkbox'/><label for='index-3feca325-0d6e-401f-b53b-a884f8a2c4c2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-3.1082774035437897, -3.0614348319608258, -3.0146485959640903,\n",
       "               -2.967862359967355, -2.9210761239706193,  -2.874289887973884,\n",
       "              -2.8275036519771484,  -2.780717415980413, -2.7339311799836774,\n",
       "               -2.687144943986942,\n",
       "              ...\n",
       "               2.6405277147488917,  2.6873702863318556,  2.7342128579148195,\n",
       "               2.7810554294977834,  2.8278980010807473,   2.874740572663711,\n",
       "                2.921583144246675,   2.968425715829639,   3.015268287412603,\n",
       "                3.062110858995567],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;z&#x27;, length=154))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>f</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ce1ca000-3cb3-4d24-acc2-52df2aac45af' class='xr-index-data-in' type='checkbox'/><label for='index-ce1ca000-3cb3-4d24-acc2-52df2aac45af' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([100000000000000.0, 120000000000000.0, 140000000000000.0,\n",
       "              160000000000000.0, 180000000000000.0, 200000000000000.0,\n",
       "              220000000000000.0, 240000000000000.0, 260000000000000.0,\n",
       "              280000000000000.0, 300000000000000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;f&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b953a065-50fe-4257-a60d-a2ae20bdaade' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b953a065-50fe-4257-a60d-a2ae20bdaade' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>field value</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.ScalarFieldDataArray (x: 178, y: 1, z: 154, f: 11)>\n",
       "array([[[[ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j],\n",
       "         [ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j],\n",
       "         [ 6.43478160e-08+2.2920256e-08j,\n",
       "          -7.46410151e-08+4.1726917e-08j,\n",
       "          -3.07212815e-08-2.5303006e-09j, ...,\n",
       "           2.56144510e-08+2.5176810e-08j,\n",
       "          -3.49830742e-08+3.8806519e-08j,\n",
       "          -1.45186245e-08-1.9318170e-08j],\n",
       "         ...,\n",
       "         [-5.54970967e-08-1.4926345e-08j,\n",
       "...\n",
       "          -2.41072717e-09+5.2363074e-09j],\n",
       "         ...,\n",
       "         [-6.27467078e-10-7.4389943e-09j,\n",
       "           1.45480961e-09+9.0445926e-09j,\n",
       "           2.89787055e-10-5.5823879e-09j, ...,\n",
       "           1.90179317e-09+1.7743294e-09j,\n",
       "          -9.13492282e-10-2.1816593e-09j,\n",
       "           4.50721593e-09-6.2089284e-10j],\n",
       "         [-6.59422794e-10+8.6273655e-10j,\n",
       "           7.13056489e-11+9.2542590e-10j,\n",
       "          -2.19914156e-11-5.1966337e-11j, ...,\n",
       "           8.63919630e-11+4.0660250e-10j,\n",
       "          -1.42005477e-10+1.8165988e-10j,\n",
       "           4.32076513e-10+1.3890591e-10j],\n",
       "         [ 0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j, ...,\n",
       "           0.00000000e+00+0.0000000e+00j,\n",
       "           0.00000000e+00-0.0000000e+00j,\n",
       "          -0.00000000e+00-0.0000000e+00j]]]], dtype=complex64)\n",
       "Coordinates:\n",
       "  * x        (x) float64 -2.913 -2.88 -2.847 -2.814 ... 2.814 2.847 2.88 2.913\n",
       "  * y        (y) float64 0.0\n",
       "  * z        (z) float64 -3.108 -3.061 -3.015 -2.968 ... 2.922 2.968 3.015 3.062\n",
       "  * f        (f) float64 1e+14 1.2e+14 1.4e+14 1.6e+14 ... 2.6e+14 2.8e+14 3e+14\n",
       "Attributes:\n",
       "    long_name:  field value"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "field_data.Ex\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51efd903",
   "metadata": {},
   "source": [
    "In this case, the dimensions of the data are the spatial locations on the yee lattice (x,y,z) and the frequency."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebeb2dfe",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Centering Field Data\n",
    "\n",
    "For many advanced plots and other manipulations, it is convenient to have the field data co-located at the same positions, since they are naturally defined on separate locations on the yee lattice.  For this, we provide an `.at_centers()` method of [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html) to return the fields co-located at the yee grid centers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "bc53fa35",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.834788Z",
     "iopub.status.busy": "2023-02-03T04:14:20.834631Z",
     "iopub.status.idle": "2023-02-03T04:14:20.972670Z",
     "shell.execute_reply": "2023-02-03T04:14:20.972260Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[22:14:20] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Auto meshing using wavelength <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.4990</span> defined from sources.                     <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">grid_spec.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">510</span></a>\n",
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       "\u001b[2;36m[22:14:20]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m1.4990\u001b[0m defined from sources.                     \u001b]8;id=377861;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=333893;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
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     "metadata": {},
     "output_type": "display_data"
    },
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Auto meshing using wavelength <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.4990</span> defined from sources.                     <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">grid_spec.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">510</span></a>\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m1.4990\u001b[0m defined from sources.                     \u001b]8;id=566494;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=739063;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
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     "metadata": {},
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   ],
   "source": [
    "field0_data_centered = sim0_data.at_centers(\"field\").interp(f=200e12)\n",
    "field_data_centered = sim_data.at_centers(\"field\").interp(f=200e12)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8cd0d9e9",
   "metadata": {},
   "source": [
    "The centered field data is stored as an xarray [Dataset](https://xarray.pydata.org/en/stable/generated/xarray.Dataset.html), which provies similar functionality as the [DataArray](https://xarray.pydata.org/en/stable/generated/xarray.DataArray.html) objects, but is aware of all of the field data and provides more convenience methods, as we will explore in the next section."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "89af5c1f",
   "metadata": {},
   "source": [
    "### Plotting Fields\n",
    "\n",
    "#### Simple \n",
    "Plotting fields requires a little bit of manipulation to get them in the right shape, but then it is straightforward."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "98ba6150",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.975124Z",
     "iopub.status.busy": "2023-02-03T04:14:20.974938Z",
     "iopub.status.idle": "2023-02-03T04:14:20.983392Z",
     "shell.execute_reply": "2023-02-03T04:14:20.983012Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# get the field data on the y=0 plane at frequency 200THz\n",
    "Ez_data = field_data.Ez.isel(y=0).interp(f=2e14)\n",
    "Ez0_data = field0_data.Ez.isel(y=0).interp(f=2e14)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4a5dc0c3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:20.985518Z",
     "iopub.status.busy": "2023-02-03T04:14:20.985339Z",
     "iopub.status.idle": "2023-02-03T04:14:21.651880Z",
     "shell.execute_reply": "2023-02-03T04:14:21.651437Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1000x600 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# amplitude plot rz Ex(x,y) field on plane\n",
    "_, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, tight_layout=True, figsize=(10, 6))\n",
    "\n",
    "Ez0_data.real.plot(x=\"x\", y=\"z\", ax=ax1)\n",
    "Ez_data.real.plot(x=\"x\", y=\"z\", ax=ax2)\n",
    "\n",
    "abs(Ez0_data).plot(x=\"x\", y=\"z\", cmap=\"magma\", ax=ax3)\n",
    "abs(Ez_data).plot(x=\"x\", y=\"z\", cmap=\"magma\", ax=ax4)\n",
    "\n",
    "ax1.set_title(\"without scatterer (real Ez)\")\n",
    "ax2.set_title(\"with scatterer (real Ez)\")\n",
    "ax3.set_title(\"without scatterer (abs Ez)\")\n",
    "ax4.set_title(\"with scatterer (abs Ez)\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1807646a",
   "metadata": {},
   "source": [
    "#### Advanced\n",
    "\n",
    "More advanced plotting is available and is best done with the centered field data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "516493a1",
   "metadata": {
    "tags": []
   },
   "source": [
    "##### Structure Overlay\n",
    "\n",
    "One can overlay the structure permittivity by calling `plot_fields` from the [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html) object as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8fdf17ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:21.654698Z",
     "iopub.status.busy": "2023-02-03T04:14:21.654565Z",
     "iopub.status.idle": "2023-02-03T04:14:22.127121Z",
     "shell.execute_reply": "2023-02-03T04:14:22.126719Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5z3/uum44ysPfdyeeeKJ75ZVXupdddpnb3d3t7rvvvrZ/XddEefT09ET273Ts2rXLXbRokbvPPvu4//qv/+p+5jOfcY855hj3qKOOCrXnX/7lX1wict/97ne7N910k/vf//3f0x4bHH744S4RuYccckhd29fL1Vdf7RKR+6pXvcr98pe/7J577rkuEbmf/OQnA9uhH/zX4romSiOVSrnvfe973euuu849+eST3VQq5d55552B7R544AE3m826xxxzjHvNNde4H/jAB9xcLueeccYZsV6PonQyOqFQWubPf/6ze+6557rLli1zs9msu27dOnfjxo1uPp93XXf6CYXrmjDRgw8+2E2n0+5ee+3lvu1tbwv8sfzTn/7k/r//9//c/fff383lcu7ixYvd008/3b311lvtNj//+c/dv/3bv3VXrVrlZjIZd9WqVe7rXvc69w9/+MO0ba93v0Kh4P7zP/+ze9hhh7nZbNZdtGiRe+yxx7of/ehH3eHh4cC2119/vXvMMcfY7U499VT3lltusd9v27bNPfvss92+vj6XiGwIabUJheu67re+9S17vMWLF7uvf/3r3WeffTawTSsTCtd13Xvuucf9y7/8S7erq8tdtWqV+773vc/96U9/GmrP2NiY+/d///fu4OCgS0R1h5BiIvKpT32qru0b4Utf+pJ70EEHuZlMxt1///3dz372s4EwXdeNnlBMTk6673nPe9wVK1a42WzWPf74492f/OQnVc9z9913uyeffLKby+XcZcuWuRs3bnRHRkZivx5F6VQ09baiKDPO5z73OXr3u99NTz31FK1du3aum6MoygygEwpFUWYU13XpqKOOoiVLltR0kFUUpXPRsFFFUWaE8fFx+u///m+6/fbb6ZFHHqGbb755rpukKMoMogqFoigzwlNPPUX77bcfDQ4O0tvf/nb65Cc/OddNUhRlBtEJhaIoiqIoLaN5KBRFURRFaRmdUCiKoiiK0jILyimzUqnQ1q1bqa+vr6nqj4qiKMrM47oujY6O0qpVq6Yt7qe0Fx0zobjmmmvommuuoaeeeoqIiA477DD68Ic/TC972cvqPsbWrVvbppCToiiKMj3PPPMMrV69eq6bEWB8fJx6l6yixOA6Km97aK6b01Z0jFPmD37wA0omk3TggQeS67r01a9+lT796U/TQw89RIcddlhdxxgeHqbBwUH64+bN1NfXN8MtVhRFUZphdHSUDjzgABoaGqKBgYG5bk6A5Mq/oMruzUSlSXr26ado7733nusmtQ0dM6GoxuLFi+nTn/40velNb6pr+5GRERoYGKBt27dTf3//DLeuNZzOvS0t4aopqmXm09iZr+NhPtyjOO+N7I+RkRHaa8UKGh4ebqvf6u3bt9OKVaspue4Mquz6PVEiRZXn/zDXzWobOtI4VS6X6Zvf/CaNj4/TSSedFLldPp+nkZGRwD9FURRFaYZVh51GTt8qSvTuRcmVx5K750/0yCOPzHWz2oaOmlA88sgj1NvbS9lslt761rfS9773PTr00EMjt9+0aRMNDAzYf+o/oSiKojTDY489RpXdf6TkyuOIiMjJ9lFi6cF01Avr9+Ob73SUyaNQKNDTTz9Nw8PD9N3vfpe+8pWv0J133hk5qcjn85TP5+37kZERWrNmDW3fto36+/vnlZw6HyTU6ZhP96pVOulez+f71kn3oRpzfW+m6792NHkkBvYhJ9NNydWeKu6Wpqj0+/+kW37yI1q/fv0ctq496KgJhWT9+vW0//7703XXXVfX9vCh0AlF5zGf7lWrdNK9ns/3rZPuQzXm+t500oTi7rvvplNOeymlDnklOemuwHflHY9QZc+fqDy2c8GHuHb01VcqlYACoSiKoihx4rounXrWKyix/IjQZIKIKLH0EKJSgTL7nTbrbWs3OiYPxWWXXUYve9nLaO3atTQ6Oko33XQT3XHHHfTTn/606WNihixn6rVWHnM9s69GI23qxJWVbHM73oOZYi7u10Lo3058DiSddJ86tb+/853vkFucoOTy6ukJnESKkiv/gsrPPUCTk5PU1RWedCwUOmZCsWPHDjr33HPpueeeo4GBATryyCPppz/9Kf2f//N/5rppiqIoyjwkn8/T373hHyi54i/ISUT/uXQWrSPa+Vvq3f/FVN56/yy2sL3omAnFv/3bv811ExRFUZQFRPe6U4gSKXIW7z/tdo7jUHLVcVR+8nbatWsXLV26dJZa2F50zIRiNqllAmlGumsnabLetrSzRBllrpqPLIRrbJV2Hqv1MJ/vcafem6GhIaps/w0l9zmFHKe2u2GibxVVepfTXoecSuWdv52FFrYfHe2UqSiKoigzwZKDXkxO1xJy+upPrZ1ceRxVnn+cnnjiiRlsWfuiCkUdzOfVw3Q0e91xrEgWap8r9dGpq14w2+M7ju5aSI/kn//8Z6rs/D2lDjy7ocrUTtcichbtTwcet54qe56cwRa2J6pQKIqiKIqP/Y55KTmD+5LTvaThfZMrjyF35Fn61a9+NQMta290QqEoiqIozIMPPkju0FOUXPkXTe3vpLspsewwOnn9BurgvJFNsSBNHq7jkOs4VjZdSA5+s4H2YzzM59+ihTpEaj0b9d7zSp0bNjKEat4SPlgi4hrkx604r8/Vb4jrunTcqS+nxLJDycn0Nn2cxPIjqPT843TzzTfThg0b4mtgm6MKhaIoiqIQ0e23307u5G5K7HVkS8dxkmlKrDiG/u/r3hhTyzoDnVAoiqIoChE9/fTT5HQtJieZaflYid4V1JMsxtCqzmFBmjwUJU7iMk3UK2PXYjYtJY0K05DLa11qLIq3W4nhIA0wTa6CKAlf9oMcA7KbKhH9NhO2ehndkOC3ZZiKxfYJ/qTjzVmOQ04i2fpx4jhGh6EKhaIoiqIoLaMKhaIoiqJY4lEo3Dqya843dELhQ6M9Fg6zEUHRqAmj2SZFyeCzSaLGI4Ovo/pERg5gs7ojB6Yxbzj1mj5qbVfjD0SoZb7ta/22RJk65L2FaSP0eUSbGhkb8h6GK/yK7/lasB+uAaYP3Lx6oj3a6TfXicnkEYvZpMPQCYWiKIqi+IhnQrHwFIqFd8WKoiiKosSOKhRtwlzWJphLuXE+Jm+aaVNH3CaOahECjdQvIAq3Scrn8gyxjbgqZoqQiaOWKaPe++WW+QQRiZ3k5lW3MWs4+czB5BM1dmqZOqJMI41QFrvIMYCv8WmCP6lQddNHUiSpCptQ2sfMEcBxyEmqyaMZdEKhKIqiKIzjOJSIJWx04RkAdEKhKIqiKBbNQ9EsOqGYJdq53HJU22ZKkmzjroiFqFoHUXJ2VC9HdVOtiIpGTSKNmjdmg5rRHcKMUTWSI2T6aDxCpPr2OKlYgQqTSKBNvK1nNkgEtgWIkLAREzAjwKxA1U0ftWgmxVdC9Jc0bcBEkhSmjyR/LyN12tbEocSGTigURVEUBcQVNuqoQqEoiqIoC5o4Qj6dhDOrafDbgQU9oYjyPm42wVU7mzWaYaa8sv2Hmakum0t1NeqaokwhEsjdjV4CTlvLJNIIUdJ6s+doK9E7wtTRaCKsUEbEqiaRSvDY+C70CtNGY6YPL8KivqbXg+wFmEAq4i7KqA9XRKwkO8zUEWdiq/n1F6E2C88NVVEURVGU2FnQCoWiKIqiBInLh2Lhrdd1QtECsZo4ZrPUcpMDfSZMIPIQjXZpO6qprbYp0aJhII4y6HGbTxo230RECMTyzNUTIVJluyhCZgzsXu2N3YZNIPJrisn0QSgTj/oaHlFXJbtWjmPsB9MHooNkci0H0R8R0R5tjxNX6u2F55S58KZQiqIoiqLEjioUiqIoisI4caXeTi689bpOKKZhRqI2ZtO00WgbGjSFzES597mURdslSsfK4E12hq2h0MLlxGE2mVEwVqtEWtQdpRFFiyaQqu0Qia08GwfMBxHRHyybx2X6aIQoE4g0fciEV+4M/C7MLjFlytQ8FIqiKIqygIktbHThKRQL74oVRVEURYkdVShmgnYwazSDbHedJpCZMH3MFJ0UmeOEIgMa3F+8b+T+NBppMlMmkpaiPYRZpPbJ6ix73sJ9lxEh3lVUj/6AfcERia+aNX0Q+U0VjSHvhTR9dE4Yx/Q4FE+10VgqlnYYOqFQFEVRFBBX2KjmoVAURVGUhUx8qbcXGjqhiJMYJPCWPdSnIVRzoOYOjZlAZqr2Rxw0Zepo8V7Edi8jjtPo/XRkF0yzf72RJq6V1qffrpZJxJPwqx8n0vRBYbMG+iWy/xs1hdgD19h+uu8jkl+FTCDWtOEGNvcSjfG1sS2jXJne9FGu0u1ISCVNH7ZvazwqURYOm9iK3y+8P6eKTigURVEUBcQU5UGqUCiKoijKwsXRWh5NoxOKVmhzE0etczVtAumAB2UmTRxN37OY73VNSb8WUeW3A+eocUyhe9cq3V6v6UPuJ48fafogCl2Xd4RK1UaGtqt1nyot3Ec0M8oEgq/tufhzTnzlJlK8ndkvWcP04YhoEKJwifNgfEnjYD/5JxjnSbaP5bM+YixfvtBo/78MiqIoiqK0PapQNEMccehtQNOKRZ1KRVvnp6jjPtR9r1pO9RxzDge3XP3ziPtQLUV06JChneD4OH2JSvl1vUoFiNoulCfDd15HrJO8Sp72qPYoZoPZc74NbRol/GB7saFTKZnPhVIh+9WmwYZi4evGWmm5m3XOjEq5jTYl2/F3oBoOaS2PJtEJhaIoiqJY4vKhUJOHoiiKoihKw6hCQQ2m822SdjJ1ROHU4aQXoIOcNBuh5r2q2xTS5HiaqbFSTypvmEuEPB1K4y33EyYQ+0zVKZ9HHleehl9Dzpv+FobaHkxzHWX6CH+PRsWXryLUj3ZT/h8UlEJ/Ij9FAj/V1U0fiYjU3DbnhK9no9JyN5uXYr7haHGwptEJhaIoiqJYNA9Fs+iEQlEURVEYxyFKJFp3IK2VPXY+siAnFI7rkuO6jUcfdIDZIg4aNn3UPF4bRXu0cg9rmkLq1fUba0Ps5rJ6onukeUSYQiJNIBGmj5pNivhc5kwA8vc+YAKR6cBFroqGTR+y/yFly3wU9dwnsU2kCUTcEmnisKYPPKvYjlfFMAG5qD7qrzYqKpJKZF6KhWr6UBpn4Rl5FEVRFGUanIQTw7/W2vBP//RP5DgOXXTRRbFc02ywIBUKRVEURamK41hn1tYO0/wx7rvvPrruuuvoyCOPbLkds4lOKGaYTojuiKJu08c8ifaIvFetmjriTuk9kym8xT0MX1n1RM2hREwypXSEbC6PL2V4mXQJoIpmtR9tmEPKiHQQJhDrcIdh650dR+CTR4zrWKN8IvoxyvQhTBwkm+gGoz0cEdFhdgnejKhEVwvV9OFQTD4UTR5jbGyMXv/619OXv/xl+sQnPtFyO2aTzv4LoCiKoihtzMjISOBfPp+fdvuNGzfS2WefTevXr5+lFsaHKhSKoiiKAhzjQ9H6cRwqFAo0MDAQ+Pjyyy+nj3zkI1V3+eY3v0kPPvgg3Xfffa2ffw7QCcUMYysZLgTTRwTNRHfUklVrHTIyWZkj5Ow2oOVEWjN4LY6Q/W1vhpJkme2k6cNGVtS4YbVMHVERCVK2JwqbQ6ykb6V8/gCmDzeYLArXYutl2M9DrQ6+bWZshQa66Edp+uC2ONw27344wbbahFfRtVO8fhHvI2p8gJkM1nKsmWpu7SpxTCichEOZTIZ27doV+DybzVbd/plnnqF3vetddMstt1Aul2v5/HOBTigURVEUhXHIiSWHBI7R399f1/YPPPAA7dixg/7iL/7CflYul+muu+6iL3zhC5TP5ykZQ9GymaRjfCg2bdpExx9/PPX19dHy5ctpw4YN9Pjjj891sxRFURSlZV760pfSI488Qg8//LD9d9xxx9HrX/96evjhh9t+MkHUQQrFnXfeSRs3bqTjjz+eSqUSvf/976czzjiDfve731FPT08s55jJmh7zwfQxkzTa5TWqZjfXhqh71IZmEiKKbk8cybsizFuRJhCKMH00aCaDzA4Zvt5hUa6yoZdci987wWRPiIBIQt4OmTiCpr5QoitOcGW7pInEVl5jMcZwITVMH6743kZ3iO9FoiuicLIrJLqSfWhNRqLGx7wnJh+KRn+T+vr66PDDDw981tPTQ0uWLAl93q50zITiJz/5SeD9jTfeSMuXL6cHHniATjnllDlqlaIoijLfiMuHYqHRMRMKyfDwMBERLV68OHKbfD4fCNEZGRmZ8XYpiqIoShzccccdc92EhujICUWlUqGLLrqIXvjCF04rBW3atIk++tGPzmLLaiMl4IVuAonLuuRaz37x+WxEe9TK+FPjXLGZw6L2lzUn6kKU044glNCKIqR3Wyej+qotytRRb6Krqm2zJg5+H2ECwUngRJeQpg+Z50qacfC2HKOpKcr0IRsj90e0h/083O9R62Z8LqM/QPWUZt7ncWSXbAfiKg62EBWKjnHK9LNx40Z69NFH6Zvf/Oa021122WU0PDxs/z3zzDOz1EJFURSlI3HMvC6OfwuNjlMo3vGOd9APf/hDuuuuu2j16tXTbpvNZiNjfhVFURQlTEy1PCK1oPlLx0woXNelCy+8kL73ve/RHXfcQfvtt9/sN2IGvP0b9YKfSxNJowmuopIZTadaV0vAMx0yXjwq+qOm6YPI3temoz3qNX2I89m3UeawZsedMHU0M3a8XaY3gYRMH0J6t30atpFMf36Z4Mp+Xntfh0/imcOqm0Cg8SP6gaJMHxwWEkp4JcdNqLV1Nth3rMjlLe6ptTOIMuY1oj3MZ3wIkcgqqo2230SNjygW3p9RBXTMhGLjxo1000030c0330x9fX20bds2IiIaGBigrq6uOW6doiiKMh+Y6+JgnUzHTCiuueYaIiI67bTTAp/fcMMNdP75589+gxRFUZT5R1x5KHRC0b404t3d8rlmMMFVq9QyN7Rz1Eicpo6o/aJMIDVNH1WoafqwG8rvaxUaQaMi7mWU6UWaPuo0hYTa38AYCZ27LMxeMIHADIBTQHqH7G+PM322PxndIU0cjUR9QKov8/sEmyySEVEeiP7whS2Yt+LavHreieBrE9Ee8t64oXsaVSulxliwoSwYQ744HPRL6NnhM0mTiDQZteHvYtzEUxys9UN0GgvQD1VRFEVRlLjpGIVCURRFUWYax4m3ONhCYkFPKLxENw3e+FqS9xwyG4mzWi1n7keaLJoVU3EHo0wgdZk+IkwINRNPNdwPNe4JzAJ2fAbbVXO01nvPG5GuXTYcoN9CpwqWzUYEhI2IsFK8uZYo2d1rWvXy5TYBVmj78DEcMZqs2YTPnUwEo0CSIc0fB0IZdESqCJOUuD+tJCqr+9lCtEcywvRRx/Ga/XMXFVIprQS2REoH/mFVH4rmUJOHoiiKoigts6AVCkVRFEUJoFEeTaMTijhopxyr0yRLmqsIEClHV4vokJ9Ib/5ayGdXmkBqmT6IfOaPGqaPlqlVGtx+gBMHPf7rN4FE1XuQoRLedlFjxDun3dC8OEFThj0ymzpCUQcy0VKN++xGmDq8qA83+jC4nfYaYK7hfdiKEzZ1BN97wRzBCJXQeLH3tYr5ASdrlIhoj8iInxkgqrZHre07FYeceGp5dKCpp1V0QqEoiqIowIlnMrAQJxRttLRWFEVRFKVTUYWizakVgTJtbQqigJxd0/u8lkmkRVl1OlNHlJxaK4kOVgGhUsui22qZPoiqRH60Gs3TYH+FTCpCzvYiJYQJBKeT+3HSKXuYiARXgc8jrjEquZdtM0wgOIxok32P/SgZbLMAZ5MJrsqVoInDi/6IOBB59xgRJUlp7oo0dSAShb+2YwbXzGNJRnsg2Zc/wZW1sUW3M9DmGCOpZhp023xaj8fR7R1w62JHJxSKoiiKwjiO1vJoFp1QTMNspOBuOAdGnftXXWU3q0zI7WSFw0ZX4r7/r5VKuZYjWCJiyYcKigmxMIxSKojqSM/dsOIwfSXUmnA+Cq9Cp3DGFA6P3u3hxxrVMCPyXoQVD9//16lWOcIhsaYygbZXjJNiInSNUXkpgsfDuKiWxyL0kXTEdYN5KGxrhVLhiJPZlTi+F+pMI8yWg7RrlSS/FBd4aZqov5eOdX6tn3YrcxBLlMfCm0+oD4WiKIqiKK2jCoWiKIqiWJx4IjQWoEShE4pZplETR9NK4DTmmtrOmREntZpxROx7xOcyV0A1M4bNMyBNINVbYoHDnOxVmEKk6UO2Kc60wFEmjlrpxaPMOglhN7DFMGEm4LwIMB/ItBUhJ0FrMhE5EaqYPJxySWwjzT/Iqxx0zrRmMFdUHxWmEbRN5naQRJnAYOqoVoW05vCFiaKCa6hu+rCXKBx/rflFpOIO56NogFoVbaNo4lyh8SievUZzwnjjMvjaqagPRfPohEJRFEVRfMTjQ7HwJhTqQ6EoiqIoSsuoQjFL1GvqiJJr663KaeVH/J8/tTTPH1EJMiSzWi03ygNdzj+DqZ9ltEc95pooubXZ1Nteym3+PML0EefaoZapI5wzoTHzjpSUHSEtJ9kEkuDKkw4VAsermXfEn3obpg5uox0rch9ED1REtEcyeMxQjgyRvwIRKbXuS1imx+fm1R/tEWnysN8LU4cwfTgiAijqviXiSDQQV7SHNLfI6Bu/SYhfK/L6xCEbfQYlMBV12kLdcXzp2FsgjmN0GjqhUBRFURTGISeWycBC9KFQk4eiKIqiKC2jCkUdtJLgaqZMHVKGlSShQJPf5FHj5NVSMVc5t8c01RWrUK3NUaYOWV0yCq8FwatrZXEQus9RsnTE9UaZOqLTRjd2rY41dfBxEsH3qWTGbMemD+KIC9cp8efBKI9g6m2W/cvYl7/jSBK3EmylgwgSRGtU+CclGdzO9Xbga+D9Kma/ZCJNRERljsCIGklRpg7/LUP/l0WH4plwrV2suukD1UhD/Y0EYhFt8xpZ5U6iX6MSh8kIKXd6c6IllAI9mA4cvz+VSviZqzUeo4hyNmwmoVU7Ep/JI4bGdBg6oVAURVEUENOEIs6Q9E5BJxSKoiiKwjikTpnNohMK8iTuVutqzCSh8gTC47xQCUq/XVCek75rknKr9OSv4XHuSA9/+0Uy8H2t2h6BJET8CvkVLZCqqywICSDeS5maRDKihCzoUAVHmH68z4V8H5Klq9RLoLCELK8VSbkaNX3gllqzFu+fxsVzJ6VQ0wP3OSlrfKChvigPfFcuml1L/FoshLYlInLZ5OEk2eSRYnNLOjjGvBNwX9m2cAKspDF5eHJ6ddm9QsFxjtdi2dvemjxCSbFEkjPk1IKpI4n7xGMHLYmIgqjJdDVSakXe1DBx2GRl8nP0L5ug5Fir9lmjJjdrEqlVCbl9f06VGUInFIqiKIrCOI5DKVUomkInFIqiKIrCxGbyWIASjU4o2gSvtHLE9/xqEwXxDpDyM4mgnIsZtr+8txNl6qjT5OEdKJiUyHW9WIvAcdgUghZI6Z8obOooV4LbSspSQbf9wC1AgqQIE0noUvzfV2RZ8BplvyNMPxLpVY9rKOK98LaX0QnhNpstYfpI80WW+YMMrj2FCIoatVcCIRJmLLiFKfOa51eYPjjaA1EfiO6wdUVSxnRB2Zx5n+sRjec2lJJopPnYljNHFIhMihRhArGmP+/7It9H2Y8VjubwnOVsKBS3ITiWkvX+PZCmskq4X0NjKiKiKmQuFOY1z04jvkd0h30mzcdlMfYCn01TD6UaiI6x0UVu8L1XyyPYcZ1gUvYTV5SH5qFQFEVRFEVpAlUoFEVRFIUxmTJbX2urD8UCwXUcch2n7kRVzSS0kvs2K/d5pZPZTGE/xwnM/0AItQ7svIHD3vrmIFzmGkmLrMmjPqk/7KGPREm8WyI4nKTDvqwdQBQ2dVRLVGT2CX5g6wQIr39ct1sjqsPuP50sXameAMpLIsT3xAn2F8qLl4WJx7tW80nJmjzM59YEEtEHth1Wejb/U+LmwNSBpzrBB86yGSLBY8GJMn1Q2NRRmRoPvIfpI2zyYFNFtsu88nZOmU0ZsHxwNIgdKxhDMAFw26J+i608T7LvvGtAxEfNKA97R8w50Z84tjdeazy70oyBa/JH08jPKtWfMWvhkMeOMIXIsvD4nSkLc1qpmsmjRmRV+NEJmqGiCs/je/m7KX8LW/ldnVE0D0XTLMgJhaIoiqJUQ/NQNI/6UCiKoiiK0jKqUMwSUt6LMoHIj7FbvfKZlRulNz75TB2lAm8TLFVds5YHPPIh/UO2lomebOnq6qKoP4JDmjqi6guEjsFbIJrD9mcFSZycwPfSY992p196hklIRr1ISdseBEmGgo8RyojLBYr0vIeJo8AfFErmNc9mgqIMacHxufFpvqhcKsHHNa+eRM9SfgKRQGxuQCQFLsMnzVeEqaMyPmr2EaYPaQ4iNqvA5JHIdfOxuU+TMI0gkZVJgOWiXDqiPHAcJCqrZfqoUrcDY0lG16DmSQKDwpo6giaSZA0Th+w3+7yIa/EnEPMShvF38lmxzxDGL97WCvlBIivTr7hWjB2YOopV+qfWsxYqKS9CqRKogSJqeIQSxAlzTduaOhjH0WqjzaITCkVRFEVhHIonh8RCzEOhJg9FURRFUVpGFQofs+mFHHVsaQppdJKL4yK6w5o5iDxTB76LSGwVlWzHbi8kfrcSLEktZVpZojxQV0DIryUEWIjojdB1IokOC62Q9ZEQye4nTR14lcm9/P9fRj8JCTuiEdIUBJLJLJ9TSPB87hIfdor16NGCOV+eO2GKX4tCi7YJrdi00p02+nhvxrz2ZXB/Krw9m0jSXGcjKR57XyQQojxg6qiM7jGbjI+Z1ynTN+VC0X8ESrBJI5kz50j19prPEUHE5pZkJsdN42gQSP78mqhh6gAwdSC6o1qUh+w3vE/bg3P/8K5pFxFViBQK4kVYwbyGwcqmD/HMOSXv2bPRVhGRROgfPFtesjR+tqwZMfi5rVnDrStxm0rCnFZsIrEVugnjx0ZO2Xxgdf441apP4t/Ull+fu9V9bImtFqBCoRMKRVEURfERT5RHDA3pMHRCoSiKoiiMFgdrHp1QVGEuvZBbPXcoqY5f0peSLMwhZRHdEDoo3OM5SiApoh0Y66nOpaglMtmO//9h6qg3uRNkWMcJ2jZgXrAyrbB9WBnShbe9P8sW9x1MQ6V88PNysH+Q4MvWNBH9l+DPpfQpkzHB1DE8ZV7HCqZtE8VyYLuy0KRzXKsDJo+BnDmfFx1i7kOaa3lg+6yQnm2yKiKqTHJ0B5s6ikNDREQ09fyweT9uTCKlKZ8pjYiSaXNumDyyg5NERNRlJX2OfOnpMzv0BBMzSdMHMhUiAsPrw2AfoC/9XVO0kQ5RERLB67dRHghKEsFJXo0K7C3MiqXg8xQaP0TkFvn/S8F+804SrIXiwA4jzGoWGd1hTUAkXtn04esgmNq8aJhgpEzSRsOwORH1gXBqfi3btolriYpgUeY9OqFQFEVRFCa2xFbqQ6F0DLXi07FKKPsVCqFMlITjJq8mXZEWGKtLqzxY51WRh6Fa9UryVAIc1X90mZOhJOLoZcptgBwMePAREg9HMalMyOqVtl+q9KNdeRanAu+9VOXIrWD6w+WcCtL5DLkW4JyJ/AdwOIXT5QQvJ6FMDOfN+YYnzOskf14oYfVuLiLD+Sd6oUxUMoHrQB8h9XZ3GfkoxGPvczqFUyacMKFMTD4/Ys4xYhSM4njefwSb9yPTb/JPVIqmr+CsmesyubfdIlctTXdxI+GkGXRsTKa4WmlNZSKsRuD/MaawjadyBFNup8VKPdoRGOpW0BlTprTHNVhVgojcvFFsSFRt9Zwxk8Fj4VaGni0xXnms4ZG1Dr9CmSj4PKGR7wTKV5RCkebnHuMITtdldIPtN+FILtvaYQqFVhttHp1QKArz4MO/ISIipzBhXu2EApMPkSyMTR5ugicWKf4rwH8sKxnzR7TIE4/JovkBHmNTxmjevA6xqWMkD5MHv/LneZ5w4A8lfuxSiPLg6I7RLnOeIZ5g7Ob3g/y+n7frcs0fusTEbnN9IzttH5R2beXX7UTkTSjyw2YiURo3fxhLk0Hp3uE2padMn6UnzDm6OBokM2muNTXKP7K7zOfHnHASKUo7oam3m0cnFLNFLUUh7vNUK3CFFRWUiaL54wAbuluEUsH7WmWCV08pmSkSRmX4EEDBiMi0KTIXEvnCRt2gMoFskVFm8DKvirCKSqS4KBIi+iIWRTZzI1QInjyYncSEAf3AEwmZ1dGGoMImbxUekQ3Rnrx6m4Ar+gCvUzwBQbfh83QF/iLm86m0accUVwvDqtRmT+TjdyFsFKvilOfzgpDSRCpY9CuKCh/bJlHktrol01eVUnDM2dDlvFFAkrufNtvnjG9FhQWLRCobuLYo9dgbP95nVu3iwYPvkjJDZqJ6OG/FqiFBVctmjrThxVBVgoqfW+Dniv1RzGcorhaciNkzYTIqi65xP0RlzPSKgcHPxnzu9YF5D1WCKOybIzOy4g9hmvsn6yLzK1RBs125VtE0XJv6UiwYdEKhKIqiKExsqbfVh0KJnZiUiaj6GuHzYbklVk9EvpLS5jNZqtqNsO+6KE2dCiYzsomsYDtOBhUKxw2uAL2VoHcMuYKqd/Vk7bY8gpGUCJu7YvVkV5e27kLYE9+qF3h1TR/CFo5Vt6UiFAis+F0cp8jnNstum7RJRpwIsOqvCH+SovBtKVew0jbHgWlkKoXEWOhLjgSAXwpHZCRsXQ3vZ8BGGeAVPiriB7Yibqr1j+FzlvHK/iAVJMyaMqv3FPe7u/s5c57FfH60iX0okgn2P6EgFTG2/D4UJeFDYdUv/j4tfCSQ6KpYnn4FbXtA1HyRvkk2UmbKp1CgBgorFK5N+MXPED9bTpbHCvo/E6wXgqa7Nokc8TXy4YUvEvx0YEbzf5ZHPwkZEOPSqxETjJxKcqGRSgI+J0FFJ+RL1YF/VzUPRXPohEJRFEVRGHXKbB6dUMwETagSdSsQdZ67eh4KXh2hkiSvpKRSYQ+F/ThlM1ZRmHhjdWWjHYTvQKhpwl+CyFt1Q5nwFIrquQQ8+y4UieqrJ88eHqyEaFeXNleA75qF175VbArI14H0yYhy4YgSvoYEFJ0yr7JZJUrwcRPcNrglJMTSTRYX9aIVOJ2y9Yng94ngDnDSzFpfiiS/muvpSiM9M/cZ2+3hVMofmldEqqQQhVB9uRVSKhLs78HKhFUo8kH/Aoy98h6zX4pX5k6a05WXjUOrTV8uc3mI6A5/aumpclDdCkUK8SUmebgWK4nAdnJzXDlW7o6ISLG+E1NBZcIdH7HH8Hwogiqfa30lxOesULhcvZVSVfKm+Nrs5aEIRnXI54qIaJSjhqSSY6+Xr9NTeMznScfsl7XKBdJ+R2CVioX3h3WhohMKRVEURWEciseHQvNQKLNOw8pEje0dYb/056GAL4C18XIBKLt64tewpznsuWYViRY4adjbeRXJKzfpkY71jy1K5Pta2nOxksqLVSaA17+3SjLvkQ0Sn8vYeODI3AG+XAGebRx2f7bz86oafikut81JIssjr2yh2CCMNBmMBkihgBZ8KGxGwmAbvbwAQV+KKc7t4OULCPZzOs+2bygUmWCRsZKNHjHbZ6BM+H0oWCFA5AfySERFe7h8TNcqFKwccVsrHDZayhuVJ4W+5H4vD5v3ib5F5rXHvMLXIJGFv0nwvBWxIkdBNf//F7ijZP6OsljlZyPyVgCoI/CBIVlEjqOlynieWJmoTIzaYyDiwxW5XqzKl4GfDW/P/e7y5062h7+IeLb4Y6hPeI7gOzGc934H7DMm+glkeFwXRaiUfPayKeR8oSD47bF+H/At6oy8FGryaJ72vrOKoiiKsgDYtGkTHX/88dTX10fLly+nDRs20OOPPz7XzWoIVSjipAG1oaYy0aJPRcjOSz6fiSmTe8GdGAl8LrP42WOxrd3hbIc25wCvYmVJatn2UNlun80Wq6RRm9QJq6egLwX2Rd4Jad+FT0UuYvWUEFkOvUiXSe86keEQSo31LeG8AiJPh1UkSsK3BHkdoOyUzao/ZSMXRJZPlGAPrcLNa1GoNcVSsH+xwMSCKMe1PSaz0i8lza+sKmTgG+Nl2IS/DF69fBTVGwdlAkpFmSNNErwyLsGXArU/CsEIo1LZvCa5dkhy0TJzvjL6VPoMoE+CPhQYL0REk3y9URlGuzjBFyTpfDJYKyUq94kja71A8UOpdygTY0PmOOOeQlHiGiiy7Hsyw89QTkQQQR3Mmcyj8MORvxtlEdVRFAoF/CVQJ4aIaGSqegZWIDOwQiHD+ETtGFsTRNY9l7lw5rA2UjPMVWKrO++8kzZu3EjHH388lUolev/7309nnHEG/e53v6Oenp6W2zMb6IRCURRFUUBcJo8GfSh+8pOfBN7feOONtHz5cnrggQfolFNOabk9s0FHTSjuuusu+vSnP00PPPAAPffcc/S9732PNmzY0PTx4KU/m9VFY1Mmotos6wz48izA+9yupHgFVRozWQuxiqxwlkrYzxMZM0xSIsufjf5g5cLJwj9B2HlFrQC/vRsrqUlh8x1jxQKrJ6yCsHrCKtNTLsy9xOqpp8Kx8rKbxCrTn83QKg+8ikbOhAorOoR6DCKTqAu/A0R72GyT5vNKiv0BOKdAivdLIZWGrZUgIhlEpEu+CO/86p7+iHsfneIqpFnz2st9MsF+Dd0c7VFm23Yy4fehYIUClVRFxkzpS2GVCb5P1jeArylVCEZ7lKY47Tf7p+TzZgyml7FqxsqF9XWRK3JXrsTN9+O+KAZZAwWrd5Sklitq+ATAb0fmuLB/W2SWVVa5yniu2GeiNMLpyoc8hQJVWiuFoBKBZyvdY9SrDLchjWerYDKI2rogwg9Bqn9Toi4M1Ig9E96zu3vM/P8EFIoIHwr0X7mXnzGkek8Hc8VUhOU8VMujw3DIicWhstVjDA+bcbR48eKW2zJbdJQPxfj4OB111FF09dVXz3VTFEVRFKUmIyMjgX/5fL7mPpVKhS666CJ64QtfSIcffvgstDIeOkqheNnLXkYve9nL5roZM0NN5aJOFUXkobD+AOStxqFQFEfMa8FWkGSfAbFiSXWZ1VKGV1ewuNvoD7bzJrsHAucGOBpWUdVi4uGFvnvcrJ6wysxHKBR9bN/F5/CtwOppgLNDutJjvxz0LSn7shl60R3sMyHyCUDBkR76iSyv/lA8jPNyYLVPNrcCV9J0gr4UKeTQoCCyCqTNQ1FCpABvx2rABB8nnTTn6WGlYjxn2jNRYF+MbDDaI+3zoSCukOpkOEMlFArh4FGxPhS8SoVBnfukPMWr2xz6NPgKf5TCCCsT40F/Hkf4DFTcYGZIr1Irj58JzzdhCApFsboPRW8p+LPXm+VqrSLvB7A1W0R0h1X6RofMx8PPm7ahoNrQmD0GnjFUYQXJnOlnO7ZQAC7HPizdRqFA1EtYsSFus4ju4Odpz6Tpix0j3h+xnaPmOR+dCqqAsortZDFYvdb6VmSQ3yT4bFpCPhSdpVQ4FE/a7IRDVCgUaGBgIPD55ZdfTh/5yEem3Xfjxo306KOP0i9+8YuW2zGbdNSEQlEURVFmEscJO0g3Q8IhymQytGvXrsDn2Wx22v3e8Y530A9/+EO66667aPXq1a03ZBaZ1xOKfD4fkJdGRkam2XqOiJq9N6hIhN6zH0TF5yPg2XhNP9iV1B6zkipO8MpcZqfkVZQsWZ3llW2ip998AH8N0XZZAdGvUMBnAsoEVlLDk7CDc7QA7wt791g+zccOKhdYPVllwxXrfvQPakn4sxmipgmiYbi/imMo2c1e/VzTAwpFMmvakuLrSnFGTIejKJK5XrMfl0NPd+V4O5QhZx+KCEcwrJwrqJ5ZCuanSFTMflNk2pXmvsAKtJ9XqxOs6uTLQT8EN+n9wLnISWF9KFDTIyJTJtpSRGbSYIRQkduQZt+JMuejcLn/C6NGoSjx2EuxopYQKheUprxQJsZ5fAz5FIrd4/nA9WOMYAVeKAXbCH+cAatUBDNmej4U8L9hdYvHR4UjVPJ7zPvJHUPmlZ8vIqIit6nEbUIOk2TajLVsf1egTSl+5hI9nNsiL3xLGPQLLkkqfjv5edo27EUz4RnL8zNWET45qbTwoRDP2CArXt4zxm0hQaWzlAk/ceSQwDH6+/vr2t51Xbrwwgvpe9/7Ht1xxx203377tdyG2aajfCgaZdOmTTQwMGD/rVmzZq6bpCiKoighNm7cSF//+tfppptuor6+Ptq2bRtt27aNJicna+/cJsxrheKyyy6jiy++2L4fGRmZ2UkFMsDNpM2w1rFh37d1Oya8XceDysQEr6TgjV5klaBcCK7gMj1mpV2eCjoTwUM90WeOG/LQx3l5FSUrihIRDQkbL1ZSz7MneqkIfwFejfPKrrc7uPq0vhXcJmvflUpPJajcBLIZYpWNHAm8ai6Mmm1tLgGxwkUugUwRVVpZcUDlSNjBs8bXJMW+Fkle9cOrHlEI0n5rq4/aXA+8cuT3OB+2G+cMncjJMTZl2jfZXea+YS/9MmdjTHu1PJCTwsuYyUqFrdsi28bRHaye2BUz+oZ9KaBuWZWLI2m8sWf6Oot6MrKyqvCdsMoWjxP4BRD5VuC8SkcESjIVXHmDblYoJnic24yZcs0N/xuu/4LnCYrf5M4hc5ydRrEY3+6pg/kRoVDAf6YrFfgcwIciM8h+GuzPk6yzX3aOmvM9x8/Tc7u9P0oT6B+OACkV4BPEbWKFopAPKhRQchb3mrZNsI9F+BkTOTNEpdR2x5g8Zj9s9JprriEiotNOOy3w+Q033EDnn39+y+2ZDeb1hCKbzda0VymKoiiKhxOPU2aDddulA3kn0lETirGxMdq8ebN9/+STT9LDDz9MixcvprVr185hy2KkVn6JGtj8+TaLn+cjUBg2q8Gp53lFxQrF2A6O8hhj23AxuIJL95gVbPfSoP0XsfNpXkXZaqVCocAqyqsv4B1f2ni37zGvk6NBhcJm6+NVZmGqukIx0J3mc+D7oKe6jX5h5aYS8KHgyBD+LD88xq/cP2zvr4j+QRSMVYeQCTPHtU9ynGEUUTAc7ZFOsC8FVoZQKIT91uZFQCZHEe1h28+5N4qsJoymzLXClwC5GhDtkc9xjQ+f5TOZDGbKRMRKgnNZyDoMoTwUJfh7sKLEOS/SkxyVM4WVunmd2gMVKJiHwqvoipotQd8JZFbdwStxfxTDmPARsOoWj5FiNthvvewTMMLHxGofj6IjqozaqqKcEXMSisRzJspj5FkzfvwKxdQec11FXvXjDxYUiuI4t5X7DQpFbtCoW6llfCyRxbYs/JKQERP9sZWVidE9nkIxNmTaMoXcGCK/TJqjttBW8BwrFMv7zCJttC/HbaAgUFFE9WH729TutTwoHqfMOI7RaXTUhOL++++n008/3b6HOeO8886jG2+8cY5apSiKoihKR00oTjvttDmVhVwhg81Khs16q4uK7VF/wr8Ch9c5bLyjz5kV+OhWXonzqqbAqx3YETO86scqCiD6I7fErLxT1s4rFYrgKmpoyjsOVphQJkZ5RTXObSnyqhGr8xSvlHNs764IhWIJf76SV0+hCpLcNvhQTPk88SucHwJRHVAm8ruNslMYR+VMoeB08TFFLoZUF+ef6Db7JwpmFe4g2iOHfBRmNygUcmWDFWAFfiF8HkR72HoaWFHjOFx9dIyzVI7x6nWiGxkkzfZ+wSVjFYlgxkwSY9+rMsrvUdGU+8YpIWuo2a84Yc6NXCelSfM6scv0dXFEKhTBjJCFcjCTKpStHSNm+5Ehz4cCK/ACohiEupXr8XxGiIh2cPQLVt6oCyLTK0BZshlmR4K+SGPPmc+H/2w+3/28pwrsZlVoUizne7mNKyaCzxZUwa7l5pg5VtTgG4X+keofMmLCd2KEn6vhXZ4v1fiubeY6R3ebYxSCTn/pHvM8F/qX8amWEJHnW7Fj0ESk7LMkGIGF/gplyuy0PBROPFEeUVFb85mOmlAoiqIoykwTT2IrnVAoVZDKhPw8pFT4bYQxz85r1wLhlSOv9MrjXrY++E7AxjvEK6kdrArIVRQUigFe2WIVhZl3hldRU8sGzXteuSXLQdspFmVYRe302buf3W1WTlAmhnYaVWByzw4iIipMmDa6fMxk1qyOpnpNfvtS0bwmeZn/XK9ZZe67xNiBsXrCHUKmTFRahWc+EZHbb+zViOoosA/FxG5e8Y4il0IwmqPItuVKEatq2MfNKj/dz7kEoBb1LDLfC98J1PiIWh1BnYNpulQI+pdURARAUuSjgEIxKeqnFDJero7uJCqQGvUEvhTJNEd7JIPRHq7NjcG+E5A7eMEN63ySz2EVignzOs7+O4j2sPkWkCGTHdsKvBRHfoXnhs12u1gFGPGtwMds5IgZO/ARSGbM2Mn3mTGDR+l5rnny/ID5HvVBoKzJPBQVES0FXyQoE1t2mLY87VMddqFuhpA9ehGJw/13wNPm2FAoelayfxKf0y0FlQy0EcoNfCd2CcVveOuTXv9se4qIiEpT3m9DgOe3EhFRcclw4ON0zvTTc4v42HnzvORL1VVS63PSYQqF0jw6oVAURVEURp0ym0cnFDEwI1VLm5zVY1WACpn+iofjzxmb6cgz5rNneVX3FK+kdgrfANDFT4ZdRT1lVi4ZjkfvWWFWT3286rd2XgZ+DIjugN8EkWf7hjIxvOWPREQ0scuskqJWUbkBY9+tlPYnIs+34tk+06Y9K/v4nNwfLiIxeFXP9RfgmU/k5U6YYp+JSV79TvEqz+YS4BUsJM0kr3ChICTY1pzu5SyIA+xDwa9JjsBJsE0+5QTzUFilgo9vlQm4gSBzZiWoDriVYNXSEkd5TLIygcgIG+1RDNeucDOI7hCZMkU+CgnUGfQNfFZS7OeBNqU5qiHL/ilj7EOx/HmOnPDVnjFtEytwHjtW2YKPwPYddp/xnU8TEVGBx2OF64akWN3KDizlLQ8wbeL7t3PRVOBcyJsCUKEWuUug+A2z4reNfZL+wLkxdheqP09+8ExhH/hEZP5sjjmwesi0hSO0Mv7quOSpf3i2EC01YpWJZ8z7Z/9g95FRHVFMsFKBei2pLpPx9flFph+hNHpRMXaA4kT82lm+FHHV8liA8wmdUCiKoiiKxXFsmvZWiOMYncaCnFA4rkuO60b6RjRLVaUipuyZkb4TEVEeXhSDF+WBqI4dbLfGqmi4OH3bJnnZhO1BF6/MBvYxUSPwes8Ugxk1Yecd5mgDrC6JPNv3yHN/Mq++ldR0TA3vNOfkaJYEZ3jsZtXkWcTfrzB59BGvj37Eim/oyT3eMZExcSfnEeC2TbIPxQiv7FELA78X3aj+yctFVOjM9Jj+Liwyakl6wrxPFU3bkHExlTR5KjLJ6lVHgSuUiRJXrqwUOOcIwkWIo0e4HUVevY5NBaM9bMZMn12/zOuqJBQKzpiJPBS4Ntsm+OzYSp1ccwORFVCEeDWbZPUm02/6GGNqP+5rW3XTRnfw2OE2P8eK1jDf3z3bOPfDFm/cYGxIEM2A6AaQyR5MREQ7eOWNujKhqqOsKMGfYZzPPfzn4LXUo0xE8QSfe/EezqvCz9gSVhp7CkEfE/T3KKsq26Xix89TvapENSb3mKiQ0edMDqDRpcY/CWrRhMjLYivFIrNoh2XKVJpnQU4o6kVOOKIsGo3MS/BDWdO5suaBpp9gWKfDHd4fTPnDV2siEQX2H+DEPfZHj53UuvLBMLQpPg/SJA/7QvwgVQ8//fum2gKTyNCfHyUiou7BQSIienaP+QO1h/+IWmc47h+Ygnb+1qsEOJXjP7w88RrfycfgPxAjMBGIgTDJf8grbDRJQQoeMpObLiRtmjTHrUxyCGAfpHgjJdsU3JhYRKxwbLgowhj5FXW5HC5OVipiQmEe8zHpnFlACm7v2Pj/DDtnEgrAsXMmJhRwHIUpw9ZcQxGvMtJXG6bYqTbPk9ky9+U2JN3azknD+A8jJYJF3naxWe5PO00f7tluXjFuoiYR04HJa4YTjo3xH0qkfZd/KFFQLr/bjPOxrWYMPc2Tm20ifXYr4Blb/aw5B0JTB1HeHU3icQ3zA0Jm8cc/0vGyCdBfwyuNqQghu+gnOy+1Ewoel5XmJ1hzQWwmD43yUBRFUZSFizplNo9OKGLAS9HL730zU8fLNsRfzpAygfPx6qDMIZzjOzynzC174l1JYRW1lsPlYF7xFyQj8py2ENI24itUNPxMc8qEBDL2nmeN6WTb3sbUsYsT/eSxqk8g1bFZXd3vS0mcuNus5rK8+oYiMcKmgbES5PxgWC189yAodPF1ZvuNucAr0c0mDk4ABudVjhy0igTKmuN4WOlU7BKQV/8cQlgRJiZbmIuLfiE5WKGA1NsoElbhV28FWeRy7ygSlshxWW12yvRMH9WdM+FUCBWnKJIe7czzinrIKGfLyPQRCtMhLNVNG7PNJHfuNi7+tZMVDtxnyPGtMMQqR/+KVeZc7Ng4YR1MzXYIxZ5idWuE1QNpCowDqIdwnF7DCgWURyicUHCgqgw/zybEOk2HzQD14/k9JuHVmDDxwNRhnTJtgqsOMXo4moeiWRbkhOI3v/kN9fT01IzOCPlY1Hoeqoyf8LGDtvzQQ+YGpXnv0NU/lyTGzR/W/JPGQ/uZPZ4PxVNss99J+fCOTTDpmh//P/AEovCcMR9sfewJIiIql4w3/eO7OKvhE0aWnty23R6jPGr+350Ixrw3S3HIeLWPbTHy9dOPmUnCIxMm98P2cRMBsGsrt7Xi9cXqhfk4zCkYi3/MmzHU9efnzOv/Z0xYW5NmfDz7pBnX41s4RwLfZ3fCM1k1S6Vkzj21w/yh3P2kGYubu82kp+954+PSxX4ae7YYM92TbH7Y7rIvAbW4WKjCU/w3uf/5ISIiGvqjGb+J7t8QEdEfxs2Y3fHEdr6GLUQUT79EURoy/THGk5Ynf28mYA+PGdNR74hpo8MmokrXdn4137vJYKZSP/jNHR8fj9xGaV/0F7Qe6p1Y2+xJvo8iJi3Wl4IiJhZRikadSoctaOTT3eIoyesnjbBJXq3akMIGzpNIzcwQxGq+yEtm2PZddjLsWWUmOy88ei+7z8gWXnnyanmCHQ2hTIyUpC04uArHmr03Zfbr5uMUxjmNOKsiGVYoUiUoFFAmzP5I0pURKoBMeIVwPutDISghuVnR/IAjpHOC/RQmS0GlgoiohJTaSYSL8isnhUKpdqtUsJMlXpNisW5DXSnoyLqEy8xn+RIH9h0kIqJUt1EmMM4xlLIIxeXkSulcb9VrboZ0l/kDmeLkXV1Z8wqlSA5nW8qd7w8UrYkZcBXI8fNri7PheYkosJWwZebNfXIjxkYrJPkZwnNvi9rNkwW5Q/FEaKhCoSiKoigLGMeJZ3I0XyZYjaATilkHo0wqEtK8EvS9QPpaa/qQKxRbGphXVYmgNz4RUTrmqsF2BWcViumfIMz6E77IQ2emShnz0riE1NBYKqfNSju92CgUg+sW212KHEmAstfYJV+ZXg2Cv8BkBYqGeR1kuzbKwpcmjVJh00uzD0WCbc3oH4SPplAmPsq7q4KEVngNLpHhY4HEV0XhQyF9KYg8tcXNcgpuUc48yZ9DqUhm4VvBSgUfB+pVhT+AbwWSpCHl9JJFRpHoZ58Xp8e8Ekeq4LFAsi+oCJnuPm6HMW2VC0G/nUZAwqZ0houHcSQLom1k70OhwAo9M4N/Obp4DKC/UazNFa3CGEnY7Y2KUJqcAYWCE4Sl00GFYv4syJ1Y1NyFqFC0d2F6RVEURVE6AlUomqAi1IWEXMP4vxaRH54vBcfvy7wUdSoV3uGFYoFXpG/22eGzMa+koHgkpJ3XShCOvymhqAUiz9Y7UxSxOkcJcF5dJfqNkyZKrxMR5QaNM16aizslnMaiYSb4XJPsQ4GoiiLnwihx0ibiqAxb6Im94lOO6Qus+Oyq0+u4ac9vfSr4uG6JI35E4q08ioNVUyhYSrAJrjjaw+F+S+ZYoeDS7ClOW53ipGBZXiEXxTjFaq0bCgWXme9fZdQB3IdErpt3CCbQymI/LjWeyZm+yvQOmmvZ3YRCwedIdxtVBOnbc1h5I9oGDzGeqTT2S/M1xb8uw7Oa5utNZIM+LfgVQdugbiXZESfFPi+lyfjyUIAU+69kuR9qKhQdtlKPKw/FQlQodEKhKIqiKIzjEMUxR5yBeWbbs6AnFHEV87Ie7NXiRkXkR1xKhfWZEOe0q3/kDch4tzjNtmGsqBDF0CxZ2JJ5depFeYjoBG4TohYSvicNtt64SDjBlS1s9wW+Vi+/Aqe77uux26Z74RfAK9DxxlYY6M08/w/8EcpTnEmwwMWluFiVyymznYpRFJIJ07aM9Z0IviatL0VwxQxcF0WZ+IU9/MucpbIEtYblGmQwzfvzUNjoGOK2sEKBKI+c8XlIsVKR4mJfqS7Td+mcOWc32+7TaCqPgS7u2y72nehabI6bGTD3AUqIy+qBA9cX7oMe9tlAQa9sr1Ga/Jky641syECZ4BW3VVkwTuUfBG6T9R/h7XsjcnK0Qr9N345zsZInlEi0EWpBEq/Z7tjbBH+VDKsm3Xz9GUSWyB1C4TELb8W+0FjQEwpFURRFkWi10ebQCUWMSN8KIp9qEZdS4TtyALs90i7yyibt3WKsvLtiUyjYbisLR0WUuMZDmvKt6BDTHheyvDbyUZQQCcH9lshyAS1eaRMRpdguD78Am2fD3oP6FC2U7i7y5oiyKLEvRYWLpMGXApkFE7wIhe0ePhSI+kAWSdjJo0qJe+2AYoF8FZy1shLMkIm6G0SekoPIlVDGTFYQUvChQJ+xUoEVNfw10mJYIntott8cN93LikeXeUUxMrQIfY9VcC8rFLke7D/Ix/Oidab2eInTqsJKA/wvsOKGQpG2+RVQo4WT0SWh+rEaw4pWP/tcxKX8EXmqB5SfVBcrRdKHQoyVNK4hxjwdIN3DRe6yUCi43+DrE/oT2pmavxNTlEfceX86AZ1QKIqiKAqjTpnNoxOKGSbkXyEzbYtBB5uxK/wQnJppfROBV7uaynpRFGleRXa1GO2BM3XzStn6UKSELwW2F6uopK8EdiJmhcIeT1wjUkmUcQPYNwA+AUTeahtKDiILUg3+MNh6FjZNJG4qanAg6oKrMnL+iJTwNclwP1n7OKIMYLNGrgb2l3FK1Qufw7fCRV0NDl5BVsySL88GyoXbjJkp7k/O35HImP5K9/BrL/tA9Bq1pTRZCpwL6gxyNqR7EJ3BPhjdyMBZPQMkxk6O9/eiPHgs93ItkL6l3vVyv+bHhswH3L+IKMqyMoHoDqy4c9KHQq64ub8xZjI9rLb0mWsZFBlWmwGq2CLOiZHpMW2zPhRJ9FMwssJGXCBChfN54HmQ9V6aAf4qnkLBSg98e6Tbl/X3WHh/WBcqOqFQFEVRFBBTlEcNi+S8RCcUVQgVBWOq+UjUS2TuikjfCtmmCMVCljq1NTzEyoY8e2yrXum9qaAvRjIHD3MeTvZJMm2zeRX4vMm017/wsG814yFWYgm2MXur+epKBaIIyKeQJDLIAgkfCvN5q/k7sFqHX0GFoy6Qf4JYQcBCz9b2sPkokFOE24n3HCGTLLBdPRXMmyEjXmx7UIMEPhRFn0IBfw/4UKAmBGp6cN0L5KFId2O1bvquNBGMsEjyOeBfkxZRITYDJB/fjh32CcJtgkIxwPsPstIxya+FQc+HAoqMzSoJJSiJLJsm50W216zis6x29OC+i78mtsYr1AH2I8n0mTGbGzB9sGS3yYA6hJopTSgVg6w09LJiY5Uc7m+rUDAYmeifHKsHWfa5yPaZiqCTu7c23BZgM4myQoH+smqRjciROXE6pLqoQE0ezbMA51CKoiiKEo3jxPBvri+iBnfffTedc845dNJJJ9GWLaZK7de+9jX6xS9+0fQxF6RC4ToOuY4TWx6KRo6CQRZSLNzg8IvyrfC+F9VK7Ya8XzLoHW7+n1cW7PsApWKs1NhKCvunhXe8E1E5FDN12KYzGW/lnOaVGDzIm1UoUhx3n2IbP1SQqDIYWPo6vhWfrE/RBR+GhFnxwr5drDFucE7p5e0KXwooFvChwOIcWQ+hjKDf4HuCKI9k0rwv2cqgrA6wDOMIXwuAyJcyfDp811PgfUvYBteEc3A+ikQX9zeiPXicZXqDCkUFfh1QXbqDyoTNrioVOOFXAnt9H9+bRd3mvHt6uKJr3lNn3Irxp5AVN9EP8C9Atk34BMgqo1YswW3j4yGbZ5oViq7FZswt3m72H+YkHs9Nef1aa8zY2iZ8nblB7tdujrKxSk7wGcNYswoO9+8uVoCy/UahyI8+b/dp1J8iN7CMiIi62G+mGxlCM8GaJ/gltCqrVU113dpu/Od//ie94Q1voNe//vX00EMPUT5vxsTw8DB96lOfov/5n/9p6rh6pxVFURSFcciYpFv957SxRvGJT3yCrr32Wvryl79M6bRnFn/hC19IDz74YNPHXZAKRRRRvhMAfg9QF5rRN+Q+rSoW0rfCZhjMBKtCEhFlerGyMLe9n23u9SoUWDH3Cns4snGGa3nwW246oha6/Nk7s0G79tTwLvOFqJxZC1uPIYNVfDCnAFabViQQGUWJPGUC14Voj+4ps3NXietUlKq3DQoGqk+i1klkNVbkiWB/gSQhqoQCbc9xv2asD0qwfkYJ2UaRa8MNRjVEeYfBxF/03X/4mNioGHyFjJmcjwJKBaI9EK2RQq4NRJQUoZY4gTYjIsjmLoHfgmgAhhQibnrYT2cpR1bsmWDfjYJ3DRADkinjV4FaJrYN6M8csm5ylEdKrrhFH3CikAT7FGQHzGvXYqNUdC81ryvy4fGxm1UL1HuBegU/JCgTy7hNuUH2TelnnxWOLLGKGl8kfIWy3PZejurq4giUHNesKU6ssG2Z3LONiGorFblFe5nXgeXmlf05BrqDvyORKiDqDwn/rrbHiaep7Xy5jz/+OJ1yyimhzwcGBmhoaKjp46pCoSiKoig+Ek48/9qVFStW0ObNm0Of/+IXv6B169Y1fVxVKGaYKNMpZq9RKke9ikXIkRq+FWnYtr0oBnjiI0vhINdbGCuZg4xErLwB6gv0w4eiJ+iBnuDVk2PbhtWY2d+uMrPesMt0wYeCPe45R0B+xLP5Tof1QBc5BbqRSwIKBezi6Eb0k8+HIpEKKhM2b8eYsdN3cftLrtl3Snjx4/qg5FhbvMh0KfG84ynQVkR5ZJGJkds1JlQY+I3AJwMKhY14YV8LGx0yzS8dojuQSwPiBSIcEpyXwtb2QLQHKxWlSV718nFK7NuAc0LNSqF6puwTZHzl+ia4O8hh0s8r+EH2LVjKmTanfJEqiGJBRtaSUOBsVVFeaSNaQVYZBVbVSgV9KFJ9xu8HlVJ7VkwSEVGZq7gmd3n+QFFZNPE58k7AHwM+FIiisdFIEeoffCgWc9RLD6uRk6zklIqr7D7wrSlOjJj2slKRgN8V17mB/0U311np4mMv4r7vltVGRbZel4LvlfbhggsuoHe96110/fXXk+M4tHXrVrr33nvpPe95D33oQx9q+rg6oVAURVEUxqH5b/K49NJLqVKp0Etf+lKamJigU045hbLZLL3nPe+hCy+8sOnj6oRiBqgneKRR5SJKsQj5fWAFgzwUPoUixaudLK9+Fu0xcfOTvByFkiBXUfCZWMQr4x7En/cgpwCfg/02wqsoRCvAzusNO8S0Z7vNKqjIcfOVklnZFieGqRrIW4E4eygUWVkJEat4uUqCipLyfEzs6hn1KRBvjyyN/IoVq1zJQsHAqhO+D8hrYf0FQpVk2c8AuRe4qahfgSyItnYCVtL8WubjVypcqRPHc4LRIbgtUAuqCSYVEfmBzKIu+w9YpSIXjPZI5saJiCjd0xW4Jnmt6FsbrYDvMeaQMwKRGSWzes5yTZF+HjuDfG+Wc22QYpWcD+OspJVLqGESVC5yrEBBMeuyVXPZV0pmV4U6w7lTEr1GmcgtNmOve9QoEvAb8Wve2VGjchWngrlCcA9R46R7qem/7ABHkrAC43DtGe8HwpwjxZErUAv6WXVZ2meONyl8WoiIksm9iYioMGHa7fKzhoEH1S/HkTTd8J3grKTWh4LbHhpH1mciYry3PU71ytENH6V9r9txHPrABz5A733ve2nz5s00NjZGhx56KPX2tlYDRicUiqIoirIAyWQydOihh8Z2PJ1QtEAw+roxpEJhFx5Rn4v9bY0Q4VthfQPY8x+1F4i81WOWVy/dizjDX9msrLCg6iqzvZuvsJtXdINiNeVl8WNlAlEF4mKwIkbOf9isibxVYg4ZD/OsUCB7ZNocu1ws8OXxKgp2XlYoUNMBPhnwdrf1OODHIHwo/JkHU1m+HuQn4OvL8IpsAJku+WakeQmLfsK5UOMk1Q2fjGAUjM0oKvJDOCLaA1EdXUKhQB6PDB/Xv/ok8lbkCRFZ4SkV7AMzTX5hGe1B3GbkYiAeV/ClQLXQ8pS5T3bVi36GaoK6IxF+HG7JrKgTVqkwx8vxeEYfD/I9muToiWoKxW6+vrzdxvQL/DH6oEAhuySq5jrBaK4yqrRmg/4jCa5wmlk6SkREPflC4FoTaa9/CyOsUIhMotgG/k1dSzgL5wCyUxqlwmF1xHW4/7htSTvmTNsHeIws5edhooDaKt45odAU2Beignwo8N1hf44sf9/Pz/te/eYew38FUTFJoZqQg2eqM30oFoLJ4/TTT/fyhFThtttua+q4OqFQFEVRFBBThEY7R3kcffTRgffFYpEefvhhevTRR+m8885r+rg6oaiHVqQI7Fpj33qTdkrFIqpGiCNqLxARZfpgn2VfilFjn+7juPm0rZYYXFF08yqoi1cqNka+j3MQsA+Fk0ZWzmCKwSS/x4rGr1As4pXZZI9ZSZWst76JfS+lzDkqsKlLO28vKxWsIvTw6gmrz6xdRZmjykl5IMqDVQ3kVMj0jpljcFRMr80vYNo6VQ4eLAcFBkqCrawJnwzuJ6zSQxEOrCwgn0VSKB+ZYP/lOYKiLBSKZMrla2VfiVR1pSI9TdQHxhV8KVyoKQlkzAyu1nFtpRyvelkV8BKAVALvodYkOAIFq1urbLAy4XAEQjrLERXICMl9MFUy7SlXeX5wfVilQ8VA7gZP+UF/iEggxka+EPKAsELRN2jeTxn/ka5CIbAf+oSIaGrIjKUKtwWqklWRkGmUs29mB1EzhRUK+CdJHwqbTTWoukjfEn/W1t2syBTzwbbA5o8ss92cbRPKBHJ/wI8FqkhKdpg9V1CBkzlz2pk45gJtPJ+gz372s1U//8hHPkJjY2NNH7dz7rCiKIqiKDPGOeecQ9dff33T+6tC0QQyY2YcYJEZSqZY6xRyGsyu/K5dSXbZr9J9ZtWTGzSr+9IE27t5eZfiPAc5kekPn2d4hWLrDPQEV6eenTc4T0VtihxWUb4oD8S0D3MNCJvVEHUz2K+hYo35bP/nVSWUCcTIL2bFo194omOh7HUXfCj8UR5QXHi12INVo7kum/XRhO9TVzFot4fHPnxLsD9qnqAeQxKZQkXlSC/7IRSKYBZE5KHoZf+BCb5PrggqKIvlOmzmadjGuZ1Ywft9KWSFRFvHAj2HXCNQwLByzsKXwigKrshp4laCfeVE1XZmJcplnxkqc46EkolI6mLFqlAJ+lKUKuEHxVMoWNEplqt+D8UnC/UEz7eNeDHbc3oJSmVY9eM2JRYZNQ15QLqSIvqJvLofpUl+5kR/IKMtojrgQwGF0T7HIYXCvIVCgf4olIL9Af8Qc72sRErlBtFYqHjKz+liHs9Le4IKBc4ZErgSUpmoXvW2XXEonkqh7exDEcW9995LuVyu9oYR6IRCURRFUXzE4pTZ+iFmjFe84hWB967r0nPPPUf333+/JrZSFEVRlDhwKB5fgHb2JxgYGAi8TyQSdNBBB9HHPvYxOuOMM5o+rk4oGiHCObMZn80qCu20n0NWrJUQC/9jExCxUxcRUarHyKeQU3NTweJACG8s50tVP4dzIZLuwMkTToyhZEUiUZN1yvSVL4ecOgYHMTgmspZbZLnaLUvzApthOEx0MTuhweTRJws+IfWzWDcEykFnUDLaSH6QqXPoDzjSIaGUMA0hZTdMHTZ9Mh8H6amRFt06hAoTEe61ZypiaZ6vCdeWZ7MO+gyHqQRvHyX4NFnerydT3RnRf24JkjslI0xqSLwE85d1riS0KdhXSPJlw0dtYTN+RZgwh5ESl7XPINkS0mpnYJbwma5E6vLujDn3FKfglg6R6N9wITl2xuTtC2xKyrGZx8lyEiAuZJc0VdM9p9usz9zYbxw3y1NT3D8wVwXDaa0jJ5s6EtbkAafMoMOzdcpk801P2ny+mEOWvWfPG2MD/MzkuT+KIjU5+gGJvuBkjGRi/fzec2IVZjJZtryDnDEXCjfccMOMHFcnFIqiKIoCHJo2R0Pdh+lEJ4oW0QlFC8yEc2YUUrmIUiysA1QyHDbq9JjQu+wiThEskg+luszqqSQVCqzg2GEszaGaGXbyhEOeDRtFCXWsakXip15f+XI4ZaK4E1aNe1iBgOOhTb4Dh0VuE8LklnAinyWseEAFwcrMpskWSg6lwk6ZNgEYF0WSq+0Ur/BKUqFAP/Hq0FNyoFBgNc8rV75HrlB0EL6HMuY5keAKqY+LwvlylFepJaHmYAUpnTqztiy6pxhFKTl2nEGhgHMmr5wTfE3lrBlDyXKwz8oFdrbEfbQKhVi9cl+7xaAzplviRG1FU4Arl2YnxwrCTikE7vkY90sXnxsOnC5ScSeDioZNbMXdCP/GIn8wWYLywSm4cUKb6pyfvZz37LkcWprIT/L1BUNM7SH4GbJhuXwMqFoVqf6xHJXl8NuyVSJYVUwEU3MTeQoXFJeK+BGRYcvYF69dHFaaQcgrTinGiKdQdN4f1jhySLTbZS9atKjuSc7u3bubOodOKBRFURRlnnPllVfO+Dl0QjENToTDgreiFNuH/qf+hFV2+1pt4lcZZmrD+/BBAitILwQo0W0UimSfWfXlYEtm+21x3HyO1aTdD8mhENrGvhOZfl6hcTlnlFiWBcuwgklZhcJbLcEeW+LQzLRYFU1wqF+pjKRPZj+EUvbwqnsQIW28+oYKYhUKW2IZpcKDCcCIPOUgyQVysnZVzT4K3E9lLtENvwC56k7Zkt7oJy533R30N8DqXobZRvlQIJFQH18jbPu2T7jPZHgkEjllhapjy3b77Ot2lV4955ZVwBwoYDYFd7CIVaIUHENQItBn1ndCnMj6UHCSqErejEmHw0UpOcntRFgw7p8vNBHiE5Q3HlPwoSiIFOr22kWJe+g8RZYooBjlnWDxtRwn3UryM1dJZoJtJp/SUsBrME03/DBkcT8oFaE07diew2ytymQLdnF4dZJDWdPeOC9WONSWx3XJra5opRLB17RIoR9KBGYVCvZ7wo3wHLyoFng+o357ZwOH5mfq7VYyYNaLTigURVEUxcd8j/LwMzU1RQWR5bW/v7+pY+mEohWwyHJr+1JEFf8C9c7HsV2UUoENUMTJTYUVChL2baRBRhRCuVgKNhYrFhTPwkqbjwc/jQSvTiuiIBQWoWk+TpdvRTyYCw7BrCgglmffCi9tMrclGfQr6JGrbxTQ4uN5qYdxTWZ71/HOD3t1ostcV7pfRrvwyk4oFMAqObxdktNQZ5GkiPsrwWnDYRd3Q+XezStWzF020RD7AIhB5CVwMu2RCgXIilTTvfCh8CW2wv8nhRG5Iu3jWIUi2oPVnQT7BsA/J/SjKhSJUJEwWzOcFQ72pXCsLwWfr8g+Ahxp4ab8fchpvVljSPGzMMHjusCp5aOUCpnYqsBqQKrCY6WMiBRuMj//WX7W0lBvSl6Uh1M07acsR6/gGUQRNKsS4BXjk19tZjaRypzLu6NXM5xcLmmjP0xfFH0XiaAOm1bdTfKZq6fxl4pZ0ioYwe1shJkoW95JKbfBfHfKHB8fp0suuYS+/e1v0/PPPx/6vlyu/htSi86704qiKIqiNM373vc+uu222+iaa66hbDZLX/nKV+ijH/0orVq1iv793/+96eOqQlGFsP3OFd/zp2IGWjXqI0KZsHZaN7BZy0pFxZY1DisUTlc/txMfcKlz2L17zeopXQjmp7BkgkXAEvBAhzd7MhjlAZLWa5yjEHyd0Y+01IiXLyCenu3dyE8gC2DxsaI80XuQXjoRXGVhJYh75y8O5uR4lV0Kyn1p5AjoNvb7MkpCi+gP+AnAlyLJKWyt8sFRNij9jdW9nNejL5LCix7XVhLRHbJ4GNQcWTALNm+kmO4SkTBEXn9Gra1cm4ciaOtHlIdj80cIFQyvSZTTFiugKF+KYtCXIsFjrCIiCbIZL9+KY8uQI68EK2WsRiEtdSFp2uBFOwSbhPdY0U+xIlVx2R8kAcXI9FaxjHHOyk/alwOG/99BkTtOKQ6lwoVi4Qp1UGJ/cyqB/W1hOT5+IoH8KxzR41OhoOa4fFfwm4Ez1jo1WmALEWJ//J5AoLTKRPuu1KvhOPFEebRztdEf/OAH9O///u902mmn0Rvf+EZ68YtfTAcccADts88+9I1vfINe//rXN3VcVSgURVEUxYcTw792Zvfu3bRu3ToiMv4SCBN90YteRHfddVfTx1WFYlqi9AJ4IvO7iKiPatTypWgUqVTYVQbSI6azvo3ZXgtvdsTLT6HYERcugoc+7LpYaWAFng4qFQ5HebgpZPMTHul8HLtC9s1jEzYDI7I4ms+Rxa9UQXbD4HVjQYs4+zRKdKNYUiKoYFgTu+2wRLDNRORwWWqHEyAmhKe9y4Wv4CfgCu94exzsh/7B6j0XzH5YQYSJWJ0jb0daXAtM+MSqjhe9EMyzgMyH0goqvfahGPlzFKA/Zbl3O64wFlBULcl9w8qD9adhBcL2EF9DKANmFFCmWOlAGXOXM2Y602RhzECtSAVVDIdQBIu/5g5NOMFIopIoCoa8FfA5wHbo/0yFs7pyv+b5+4yvvD22TTscKYVCcfgt4WfPqUDBQHZWvosuXkVUCO4yv3iRZqwe2P7x9ZPwx7C/X6H8Efy99ZEQeSUifCTgQyEV3OmYy6gOiUMxKRStH2LGWLduHT355JO0du1aOvjgg+nb3/42nXDCCfSDH/yABgcHmz5uO1+zoiiKoigx88Y3vpF+85vfEBHRpZdeSldffTXlcjl697vfTe9973ubPq4qFD6iZsmOWIl6M/LqSgWiPoh8/hR1+lK0ipePAiWyvRU44X8R2ZBCVj6278rVUMjOLb232dOfV+SeQoGLrQSOC297f3FcuxrnPsNqsCsFT/tk4LqAWCTZ40i/A/hQJOUNENEKREQucimgjDUrCC6vul34lshIBEkyqDzYrIco745+gp+L8DmxeRRwDegLeN1b9SUYrVCAqiNW0hKbGRK+LT4firQtSR1conkRDaiDwdcIlcXla0QegS5zz+2Twm21Y0WqPOhTmQBDljNHFla8TrMKzqSDNWYS3JqEfSbxXJtjTRGysgav1apkIqIqUcL9MN8jcyT60x89A7XJqhrloI8PojNSxP1Ygo8FokJ4rJWD+SugZNhnF5pQPSt+8RyTUCpsNlR8j3tn/WcwzvF5MP+EHStW4YhuivVpagulwpn3UR7vfve77f+vX7+eHnvsMXrggQfogAMOoCOPPLLp43acQnH11VfTvvvuS7lcjk488UT63//937lukqIoijJPgMkjjn/tyjPPPBN4v88++9ArXvGKliYTRB2mUHzrW9+iiy++mK699lo68cQT6corr6QzzzyTHn/8cVq+fPmstcOLFBAx9Yjr9s1MQzkqxCALrbzxeYNtkh7aMN8mUz4fCrmyqAQ97u0qxzosVPcR8B2QGy1WNnJmXgmuVtO+FXmKl242SoX7y1sR83XVaAnOmBRNgjLhyGup5kNhY/5ZOXBzgfY7OWHHrrWawgpQRkaIFZ+MisH4srkEoEwg6ycrD+mEeUWugVIKXvvB5slaDQAqhP+HD/1nzexiH3s/sHplZYJsTgM3sJ8jxxyuGbkaoEBYnwGhBqKv2YdC2v/tefzXaO8P++5kOBoJVUCxlw1ECSoVFfY18vI18ObCx0Ji84dAdfCpLYikQfXbbIr9LFgRKrIfBiJ2smmOvBI5XRzezqkEfS5CGThr9Ksfmy02GRyXyCsDlbNiq+Sy0mYPEHzuS1JudYRS0QHMZUuvvvpq+vSnP03btm2jo446iq666io64YQTYj3HvvvuSy960YvonHPOoVe96lW0aNGiWI7bUQrFZz7zGbrgggvojW98Ix166KF07bXXUnd3N11//fVz3TRFURRFaQksmi+//HJ68MEH6aijjqIzzzyTduzYEet57r//fjrhhBPoYx/7GK1cuZI2bNhA3/3udymfj0gZUCdNKRQveclL6NRTT6XLL7888PmePXvola98Jd12220tNaoahUKBHnjgAbrsssvsZ4lEgtavX0/33ntv1X3y+Xygg0ZGRpo7eZRvBUmlogGvZrEpjtBsXgpgFwdYXfnO47CNMwn7N0yb9vp4dWl9KbAcDa5uEHcuP7eI6BAHPhmcfc3xu2agQqNtgegY6cUfZZeUn4dSiQQ/8KqyeuqAlxeCDymuMxTVESr1WkPRibqWRPAxRP8neXWfSCKfgvkedne4SNioBJEBsQzVgIKqj0iAWrVJVtmBysJ9UeYBlUC+iqTsMz6HE9w/Yf1s4Hcjqm4Wg/4pob7G5yJFsFehNdwGSYqVCkoJWz/7QlRQfRQ+NA7yTiBjZjBrKxSLWtE0RJ4/RS5ltkZkDTK6llJQeIJRGTmr5Ag/G9xbjpZxJ00108qkiYJxC6J/XV8rRTVaK0vxuVB115XRSZxHxU3DmQR+MazyQR2VYmAoworaGyfsQ9QMzRzDv2gmIrr22mvpRz/6EV1//fV06aWXttwmcMwxx9AxxxxD//Iv/0J33HEH3XTTTfTmN7+ZKpUKveIVr2h6kd6UQnHHHXfQF77wBdqwYQONj4/bzwuFAt15551NNaQWu3btonK5THvttVfg87322ou2bdtWdZ9NmzbRwMCA/bdmzZoZaZuiKIoyP3DITKzj+NcIWDSvX7/eflZr0dwqjuPQ6aefTl/+8pfp1ltvpf3224+++tWvNn28pn0obr31VnrLW95Cf/mXf0k/+MEPaN999226ETPFZZddRhdffLF9PzIyEphURHsWI3ojYkUqkklIpcLxHU5GfsisdMAuVvl9qxk0Yf91q+45/dEcgne3eS/9EqyXu+2/YDSH9TkQ0SKe8uHrV+GvYZ9B2fehfAM1/DdkzQkS29kMmd5TL/OJyNoGoXsWalHQmz2k/EjfiwgFSPYXfDvsisf6ZgTrPWAlDT+UslUs0IpgfgX7eR2e9WihI1ehyFuRgk8DjwnhL+KWkfOBP4fdfmqSj8P3EzZ/jqhxpTrE0Q9eJJLMy0BehImL6Izg9UGpyLJSYTNf8vZFqDDiLwJ8A5BnosCZM5EzBdVf4fvi3z+bDvpQTNk8K2YfVN2ljKxZY17TqJmCcQ+FgvsJykRlctR8z4pFaYq/91UQrogsprJWD2rQOFxzJgH1CLV5+nj8IUoM40qML3s+vkXJjjKwx4dUxrPZLGWz2dB20y2aH3vssRlp27PPPks33XQT3XTTTfToo4/SSSedRFdffXXTx2v6Fq9cuZLuvPNOOuKII+j444+nO+64o+lG1MPSpUspmUzS9u3bA59v376dVqxYUXWfbDZL/f39gX+KoiiKMh2O68byr1AoBFTygYEB2rRp01xfHl133XV06qmn0r777kv//u//Tn/3d39HTzzxBN1999301re+tenjNqVQwC6azWbppptuok984hN01lln0SWXXNJ0Q2qRyWTo2GOPpZ///Oe0YcMGIiKqVCr085//nN7xjnc0dCzc7EYyuQWo26fCW9FFKRVx1/qwUR6wo/urDFqbOh+7lslfKBJelUGH35vP0zYbJdtgcYCyUCZshUXPryUURy9UDbl6trHdsMkjYiIRtAMTIjWQDTQV9EzHPSr7jl8qBX0PKnY1Huy3KB8EL9IkGD2RsP2G+gqIPIHPSjArolR2onwz7Onhh2JVGqgzUGOCtRvKhDwVfBpf3pSy9RsRJ3OD36NJZRdjgVfSXDsmIaM5uDpoReSRwHYV3D+OVrBAqRAVcl2OcpAZNYmIEja8hVfU/LntRe6vFFcqhU9KSfg+yNUWxiKUCVR3neRX5AEJVQAmohxqzWS53koW6gj8X4L5PdKc2wIRUWmRA8ZGmtkMouwzMW5Ww8Ux874wykrFpOd7EqqSi+vl7J2pLvOsZPrMPikej4gGcRH9AZ8U9A+/lsXg8efl6Qhct7Y/VF3HqVAmk6Fdu3YFPq6mThA1t2hulk984hP0ute9jj7/+c/TUUcdFdtxm5pQyB/5D37wg3TIIYfQeeedF0ujorj44ovpvPPOo+OOO45OOOEEuvLKK2l8fNw6sCiKoihKq4TM3U0dg81ZdSrjcS6aa/H000/PSOKtpiYUTz75JC1btizw2Stf+Uo6+OCD6f7774+lYdX4u7/7O9q5cyd9+MMfpm3bttHRRx9NP/nJT0I2p9iJsnU7QXum/diX80D6VdRSKuQpo5QKu11Ek7GqLvgUiiK80vkjZFgsRUgVdmXN1yDrZaRtngSOoefjZthvwa68bTZEroRY9BQKl23iFdjSRT2RUEVP65GOehkcG4+KqfBQT+UC+8nsftZz33d49EdRZJosCaUiqq5IUqxssdJFP1klB3VI0CSs2qUPSkl46AvFQvr+uDJ7JFQaoRagYmeKP/f3cIkTmJSFPVyqNAAqC669yNvZlTWyVGJM2NwbrCQVzX2XKoJV5OCsYX0oOHcKVuhQuJLeVVRc4YMilQo8g9zGbNqstIv8TKbLQf8FPAd4bvAcQZkYz7NSUTSv5SrPUxp1Uwrm+qeKqAgb7FFk2bTPFkd/5JJBhQI9heuHQlGaMApPfmjMvA6b19Kk98xVeNB7qggUCtO2TD9nhhXZS6HyIerD6eJnFL4qUK24f2yEUBIt5vO1fZjH3DFbi+aZyuLZ1IRin332qfr5YYcdRocddlhLDarFO97xjthna4qiKIpiiM/k0ShztmiOiY7KlDnr1PJ+l9U4q2wfFQHSqlLhHT8IjgN/iaKvnsMk23gneCUFT3OszOWxZeY/eKh3p4NVKl2+RmRyTFofgWAUDVbcqBhJROROmBVUZdK8unnO+Adv/pBHOooisG0eygRWTYiZ54qhVplwg3ZLLHyLvouG9z5eJ4rm3FMsURRE/gEAhUJW8UR2xC7upyzf62wyGBGRRE4H+FSIug22EiW/d2UlSl4aogaJVQFYiZC1VhxWb1zOxpjyZ1Pltri8Sq9IfxIoF1Ksw2qXx0zRCV5blhWKTIYjB5B7Q6yUrIqAa0pBqQpGfdg6KnxPXPKpXqhoyv2UQC0OtNVWz2XFhl+z/Jq3ChKia8z7pH0GoW6ZI0KZGM+b8+WLMjOFpwJMsDpQLGcC3yP3RS5lvrf5KXisuaJyqucshagYc83FcfP8FMbMM1YYNj4UhXEvyqM0CYWCn1s+d6qL/ToKyKCL55p9f7pNXgr4bThiEMjoIYxnt9N8KIhq//bXd5Cm9urkRbNOKBRFURQFxOiUudDQCUU92Gx81WecrlQqgl/yvjOrVEjwfb7kbTjGNt8RXkl5SoV5LYqVtxfFEVxpy9VTf84Mo5QD+3nQ98L2Aa+oK3nPk7/CXumVsWEiIipzPH15yqy4EDMPWzp8KJLwSO/m1XaP2T4J2zrqNmCVLuqvwNG94FtlQcFB/4yxbXyclQooF7b6pLBBZxNCmeB+6kU/ZZHfw+yfEnkkPF8Tvlb4UBSQY8CsNt08e/RDvYGPBUd32JoVaVYkOONhItfNh0c0SdC3gIgoyRU6S9KHwkaGBP1KQlVIoUzwWEix0lFK4pX9bVglSXGb5ZPj5PjaoM6gzgo2wLiAr41vRenAR4e/qwgfCqvkCEUn3TVo2sZtnOJaKSlZAZXB8zLF42NsyryWS+EIJdis80VzvTKbZI5Vvx4eO4gggRqI/k8KRQfXX2aFAr4SxVEzZvIj5vP8qBflUZrkfdiPA1lPU/wcV/h3wcFznDMKVrqP/V14/DmuiLzhV7TVqfEbpcw/dEKhKIqiKD7iiPKIx2wSH8ccc0zdzpgPPvhgU+fQCUUMeLZCmz7Q92Vj9kN4QNerVABrv+T38Mqf8sWcj7FtFCvwoQmzaoG3uvU8Fxn/sHrq5RXMVI4jJYJO4DabH4faU9Y2EnZv9gHgFQ6Rl9mvNGpeC7yygi24zBn+YM9Nsj0XMfPpHrMiy5SCWSUR/ZHIGZu9jaAgeOzDDh5WcIZ4pTk8Zc49zCu6RvtpkPsJ2RAxKpKcOyODD+TvDkfDwGfCqjgTpo8qU+yDwjkaSORosFUjM+gDo0wkuk0thkTvgDkOtvdVO00gEsTxPiPy7jVfuh1XhTKUDOFX4sDvBopEgvdHpBFUL76PnNMA/g5Omq8pw9eIKCCaCjSoDHu/9LUhIof9EVLloM8ABmwSCg77liSgmiR4RW6rhkJxCz50FeGnBGWixJ1UKYX/KCU5amPUxdgxn3dDzWIVq6+EiBGOxOHhm5EqKNQyfk5KU1AqzHsoE1PDnipYmmAlhWUSG83VFVRWEqxIQpkoTZpjpG19EBFlhN8gCLbIsdMxRTzA/DR5IBSViGhqaoq++MUv0qGHHkonnXQSERH96le/ot/+9rf09re/velz6IRCURRFUfzMwwmFv5jnP/zDP9A73/lO+vjHPx7a5plnnmn6HDqhaIaIfBRhpYJIWodr+VLI1aoT+h/RFKlYwObNr1O+VZJdgbMysYtXLyOcRW+cv5e+AVh5D3SZldxUD6sFfNwM56fo4Th2G1sv7b2ImQ8oFGzr5Xj5qT1mFY5Mf1Ex8ylui79GARFRMsOfI9qjHKxOiX5GrgB/lAcUHCgTO0bM6ng399cYfw6FQrapB6tMViaKvcFxgqgBrEZtBAXs4/Bt4AgG+ExYZWJkDxERlcaR/RARMcGoAgde+V284u5mnwuhZNgslUkvysNNIa8DR/AgJ4dQvOBfYiOFhMc/Vr2ZZDBCqF+OER5FUJTSWUSusErDKgv8Qmw7kUmVlYmybxx4/jbBXCYpqFTCdwJRL4mU6acc99skFApEL9moj+C4LiJDJj90RX6OytWiPUqISjHbDvOxujOmrQPdZuxMdfEYshlJ8aAH81FY3yDkSEG0B6sQxXF+P+b1zzjfw6ly0C+jSzh2IOoDuS3g1xSKMmJsBBDyTVi/MOJrVtqF73znO1VzRp1zzjl03HHHzW61UUVRFEWZlyDKo+V/7TuF6urqonvuuSf0+T333EO5XK7KHvWhCkUcTBvlUcWvghqP+pBKRUThU0ulikIxyr4TUCZ2jJqVx9iEWb1gZWVtv8jwyMb+CV6VYrWUTgbt5Ihi6E0jeiFoh8dKseKr11AYMatteKUXOMPf1JBRB8pitZdMY/XNq/hScNVp6xD0ilW5zXZqXpCnA970RJ6Cs2cc/WPasIv7aYrj90voH1G0YZz7abw72E9W6eF+mmInk56MiFxANBFs/lOsUIybCBj4mUztMT4VqM9QlioNqwFJ651v2p+DvR3jlFUB4sgOIiLH7Q4cy3ru8/9M8JJ5TOZegOJjV718aBEhBIVjsCJ+enis9KXN+ZNF02abnRH+DqKyapkjLAKZIIUykMymA9vmeJVfYYUiyVEw6I8E+3Mgyyf8P6C2JKQDE84L/xBkzPT551Tgr5CUOUzMsUangpEikyICq1Rhxcj6uwR/TxANhWvHc1PkMTvuU7GGi2F1zrznLJ38e5BmVcNGheR5nEXUV7FVem3Cj+Az11HUKnRUD21m8vBz0UUX0dve9jZ68MEH6YQTTiAiol//+td0/fXX04c+9KGmj6sTCkVRFEVZQFx66aW0bt06+tznPkdf//rXiYjokEMOoRtuuIFe85rXNH1cnVDMAP58Fa6VFOJRKux+EUqFXYEj66M/yoNXP/CZGBkzK40p2Ft5tYn4dBuHjlj4UrANsIsPsL0XaoitauqIa7dZ/bzVJOyyiO6AMjE1xBn/xoN5BpK8WkTMPEBeimKfWeGmUX2xEPRIRz/CXBz0MTHt283nhDIxxopOnn0pSoVKoE0JXoVnWHmoiIUbMooOdrMPCvdjKNukzX7Itmr2oSiPwb/EKBNTu9nPhPusXAiuyJGxFH4mUsHIwXegi/1Megbtd/BNwK2z0TDcYVgxQ5kYYr8SjK2CiGzIiJwc6AMbcGHzViCXh9kulzH30WZVtVVkWdVBhkxEQ+S9TpeRQYh8SAvlIgdfClYokhwN4/K5c1kTDWNrr4g8I9KXomJrvQSjPog8/4qKuOnIJIr+G5e+KTKKxlaUrW6thmJXgprIrxO+Z3eS+y6Pe+DtTURE2RLfC24T/DGsv5L1oYjIlIkPOlGZIOJq1K2rC7GEns4gr3nNa1qaPFRDJxSKoiiK4mce5qGYDXRCESdVfCls5EdUQgm7XWNKhY3sjvChKLlYhfiiGKaCK3AoE5PsK5BnW6m1jcIvIY28E/DnMCfdlTUr+EU95vuJHrP6RESAzE2AlY3fh8LWHoCfAisTk3umAm2CDd/mBmBveGTOTLE6kBngyAfkLUDNB/Qv3rmIWvB+OEbYdrxnwvTHBPfTJBQKVnZKeWTx5OqpXFekkDU2eBvfz0/XHlZTlubN97Z2ilzCIXKB4/zRT8UxRMIYxWJqj/AzyaP2gjlMIs191MN+JrY9weiPRK85nlPxFAxHeO5j+Ni6FSLbKvxxhrlvbASM8LNB5Eu+KNQdUTcDWSozNrqDfSc4eocS0ncAPgO+WhXjk4Hv8JBUisEaFck036CsiZ6xVTSzJndJOmcUCpkBFX4huDavMfxs8n1APgr/OSXFAmcQRbZN9lOAb4/NYotjw4cC6opQKqDcWKWiEv4dmIR6GUq3y9eJbKjIVwE/JmQAxTiNuCbrrlRnVt/2w41nMtBmE4pFixbVndhq9+7dTZ1DJxSKoiiKMs+58sorZ/wcOqGYCfxyWVSOCmkDbbLmh1QqAHwoir7Y8jFeVRbY8zvPK/IpzvlQnOB6GkXPx4GIKAV7dmWRaQOrBEM5s1oanghmksQp5coEKxu/Fz6886dQc2CMcz5wpMUY236LWPHyhfbaXANYjZuhXOTVKTIoIkuidTGxUR7m1e9jAk/7ISg43IapcVZwOA9EcWoscD1QKNLd/Xwktr1zzoXRbq6dUkB2SeSxCPYPanLYPB3sQ1EYYYWCfSemdgfVHHjyIxdBAj4vUyLagVfk6R7OT7FoKng+IqKeYKPQXwU+9jgrFYiE2cN9A9WrKNUS/oUZhhrG30PBSNmMmmYsdaWClWwTHOWR4AgMuSLHWEL+BSIv+qUkfEuQ08RG0yBjJkcGVbpMJtFU76DZLGf6PZsyPhbIH5IV+Slk1AfUF/8KvlwM+rEAVPos8r3CGPEUimBWVpdVBKlUSGxOjArUCK8tUCamRN4JXEYX118pCn8MG6Ul8p4AXDfubb2r4bZkHia2Ou+882b8HDqhmGkiJxDCSbPGw+cIR8eoiQXA0f1hkTbEjx3p4GQ4NbqLiIiKY0NEVGVCwVIwSKaWEhFRrgcyLcp8syNZCZMnNJ6vUaQJJvIVMxoLFjHag/BE6+jJbUF5bE7dnIU5YiRYHAlJn7Ll4B8R6/doEzVVmXDxxALmFkwkpoZ3mGMXIKmb75NcBhzvHQ6BzLOpY4KPM8HHL9rkRtw9aIAweZQmzHk8h1VzTeM7+T0n3oKTnTUL8QF7poLeoUhUlGUzUxeKjfnTVrvBe+eZhoLOmEhH/jzftyl+LWDCAPMYtyXDIcVl8ccohbBSOG0ivXsZKbs5tBUhyOycaRM54Y/epDehgCOvLNOdQkKxUvCZhPNqosvIvJUJM3F2uszEMNPNjr4oAseTn6wwgch8+BXfjLpii5iVA68I8S3xxAih2RPimcL4h8NzKoFCcOysGvH7gdHtr/uHSYb8c4fid/lk0CSCPsbkzbXel2LyScGP0R1ekbQOmWAsEKfMJ554gm644QZ64okn6HOf+xwtX76cfvzjH9PatWvpsMMOa+qYmthKURRFUfzEkdiqjcNc7rzzTjriiCPo17/+Nf3Xf/0XjXEk2W9+85tAiu5GUYWiHmx56epSX0OHkk6adYaT1prdy2/hGJn3mRfglFnkVVCeS4ZDmciPPF/12CW/JE5EyZyRgKfGzerIFs/CatENrpiBTZOc98nTUyhqxCGtrEzYV+GUhlUiFkndSbNdDqvSCTg0BstbO8JBqlRFCobJowBlglfyUHDy3E9uOShfV1jRCTlp9hhlB855KBdfinDW8sq7swmKzTcID50ahnnIvO60IYFBJ084ERa5vLTDDq7pXrMSzy0yxytNmeOkSt79kI5kWBljpTzCfbN7PKhMTECh4PtZ5u1hDihkSoHPd/Lxs2zagGPvSN689rOa4HJSKhehrknhhMhjquQLG4UyUeA2Vrj/C9wWawpBWDSfI93HYbS9RpFK9i0mIqJM96Bpa0oUPOO2RyW88qfgr5Th8BwMaS2yAlMssMmOr2OiGDR55KFU2J8LVia4XxKcKl32T9kqTf7Pqo8/mBVxz+FTWrHFzpAWnb+IWIFXwtqb0mZceuml9IlPfIIuvvhi6uvrs5+/5CUvoS984QtNH1cnFIqiKIpiceelD4WfRx55hG666abQ58uXL6ddu3Y1fVydUEyHiMmEqmAdwxoZMMKXYqbCSQHst0WfTIDQNPgGFCdMoiSsvCPhlXN+xNiYU10mrK7QZ17Hp6TTofChsNeG1N6eaoLEOwU4Y5aCyoQMbcN7fN9VNNe/CE6BCHXLixBYXAps0Qin84X2TbKqUeA2wUm1OD7Kx6ruWGevhZMwoV+LHLpamOric7FCgf7h/VCyHv1sw0VZIbElqDlM9Hlu3/Pc32OwcfMBs6zaFDldc9ox++c4PBjFnuDLAhWHyDfeInxNoOKMsxI0yf0+McolrrnUeqlkzoEy6EhvXS4N8InMNe9gJWJpr1mpL+XEV3kOC644XE4dia2kUyaSSOW9MQVlAn41+M4+tlY9Qcixub9pToqWGjD3PZnnsNqiubZs0igY3ZlgkTcoFY58ln3qF8ZOmV9Rpr3MalSJfUegnsB5dVIoFTZpHBQbpAtPBYuGSSoR/18NqIE2VBWvSCYmvYmFf5I9T5uFTTbEPJ9QDA4O0nPPPUf77bdf4POHHnqI9t5776aPqz4UiqIoigLYKbP1f+07oXrta19Ll1xyCW3bto0cx6FKpUL33HMPvec976Fzzz236eMuaIWi7hseUVqcmlEqopiuwBh5HsO1lAo0EiuZKZ8PRZFTRpeKQYVCliGObCKvrqzPxeQK855D3hA2iiRI5VDiJrbFFv0KBasCdrUdTsRTDXw/yttPsLrQDxs+IkmEvRdHhS3a72OCNiDKo8CrbSgP9YL9SpPG0alUNKtyJH2SvQ21yiaY4tTkRVYS8uwzgVBaKBPPF4LqCyiKFOndJTNm+njFjhU8ImL8UR4YZ56SEww/Rgl3G3rM0RUF9r/Jj5pXRAo5VqHIBc6VSJhIoQyvzHdxGvhVA2a7vAh7TMkwSTuWoEh51wCVqoBwZhEe2VUMvk+y0pDuM0pFdtGQOSf7GDm9y8zn3UaRQ4irTHSFENlq4ZJY1dvQywTaz6pRwagjiPYYF0qFLRIGxTEpfCjYDwShwUhRL3Nv1QPUThshgqgkoVhE/W5UOi2qYwHyqU99ijZu3Ehr1qyhcrlMhx56KJXLZfr7v/97+uAHP9j0cRf0hEJRFEVRQsRRbTSOY8wQmUyGvvzlL9OHPvQhevTRR2lsbIyOOeYYOvDAA1s6rk4oqhIxs2Z1AN7btghYZI6Jes5UX9RHrTwVEqwS/D4UWGlg5VyAQtEgdgU+hRU4+1LAH8KqAsH90G9+HwrYjCe4nePlxh5CKBrYH8mccI5QiWUG/ZP35aEoF1ndKSLyZLyhtgAoOYiOQbE1rPLdsHOJ+S/7Mngpt5GHgou5sfIwVKxPUULf7OE+XjaBSBhRjrqKbwhaWLAKkDkGfCjy/Do1MmTeszIRFSkEfxT8yDooDd5tXnePG18ApPTG+Ypc5ryLl/+OLd/N7cTK3Zdvpch+HSMilwmYSPDV7UGJdI7a6Gf/jUVmfKfhM7TYjINMr1FVssnq+Sjgk1FNZKxY/yHR1/DjgGpYMP0wKfyS4ENh/Ro4kgjKTwI+FalgtAea0ohtGwIEokFcW9iMX8vc120s6beGG9O1tX//rF27ltauXRvb8XRCoSiKoijznIsvvpg+/vGPU09PD1188cXTbvuZz3ymqXPohGIarL9CyC86QqkA/iWKVCsifCXiivoAEAn8qaXLiDKAT0CdvhMS60vBCgWyI+ZtQSKk4MUe1XMHEHmKAgoWTTSoUCB2Hvsjn4VNxVyOyEPB2/vLbZesPX4icH3NguNYZchmtGSfCd7OZtTj1WsZ2T6R0ZR9H4b5/hUbXD0hIgYr9cFJFH2qEgkjMmXCF8eulEX69sLYHm5jdWVCMjVsMlAglfZkr/EvQdQI8lxM2LHEzUJmSB7n8Eko8z1D7gkiz28I/TUuSoBnRL6IJKcynxg0r7mlRpHoYR8KmjK+FQmOXMkmOZ8H0oRnkQsCBbuqXDh8KGQOk4LZp2THiomGKRWCypBVKBAhZH0ouGgaF09DTg0Uy0PelkQDAifGZ8iNCR/MW2WCcWleRnk89NBDVGQl7MEHH4xMjd5KynSdUCiKoigK41Bcqbfba+L1uc99jvr7+4mI6I477piRc+iEohWifCqqbNMwNaI+amE9tf0Z8krwM5istkvDwBcDx7V5FmDnDQWm86rSr5pgBdagMiGBsoFCRljdE9QQ8QOB/gn4mMAPA5lBm1Rw7PFQhhzXHXWJWL3y9lAOimMoZW2uYbTUXB8hIgYKRVEoFNWcx1xEC5WD9xY5OgpcK6U4Mdpcm9g/oTCwnI9nVubw0ZBFseRzYCMOUL7cl4di0vrjcM4SoeygwBwOjVV8bre57/ndxoeiMGLGd2rCvDqs7KW5tDoUilwamTOhUESv8Dw/IpEfBdEeeIaK8KEI9gd8KLB3ypZ3N/2XyHDeDs7qmWIfjbSvTejJekeTrZsiJAsUx7OFDedTUMc8VCiOOeYYeu6552j58uW0bt06uu+++2jJkiWxnkPzUCiKoijKPGdwcJCefPJJIiJ66qmn7EInTlShmBa210b5UrjB1ZNbZUZaVbWY9oyt+VLI3Yp+NQAZFUvBaqLNUs6bVWpJ2HmtQiF3sHZkf2RFfXknajFp1QWUWpZ1B4K+AThd0V9iGqvdYjz9A49+G8cfuof8ihoxZfgDcB4KVllQwr1R/xKJrUoqylFXi4TBmaQPBe411CkbvdEgyO1RGGcfjClT4RN5LmRmSEoGozsQaQCFq+RTKKDEIIOo9DnBe+TxQDnyQVsWnsvVD5lrzHLelSQ/N9mcqOkh81HAYcFXWtzmoUD+DBHtgTFX4jo3iPawmUll9Es5zedmhSJtXpPIRwG/DlYq0j4nCvx/s8+cK8ehVVPNS6LjpQp3XioUr3zlK+nUU0+llStXkuM4dNxxx1FSPFfgT3/6U1Pn0AmFoiiKogDXbdncSURtl4fiS1/6Er3iFa+gzZs30zvf+U664IILAoXB4kAnFD5kpIQjMr7Vq1T4Z6a2/kezMckNZtAEWHwUfD4CFaziY1qBl4tmRYeVfVGsxKULBRQct4oPRaFFhQJVQ6HIQBWoYPUdYef124XxGxLKFdAkZV7R2usW12gXjRVWCvi+IOsjIhdkHoVmsSoO97nNWFqtii6iPOBDAcUA/ggtRsAAW/eErxkZIjGWyvLZsu3DWEZuFU9lgZJTawWOXt3N17SIz907xBlKh801ulzLJVEwPhbW54JzPmRSwaqj0zkToOpoRUR7ICII0R6loqkbMoU8LUIFtM81R3k4XCslmYNSwRlKORNpesw7X6MKha3hgQgTmymTfccinq1OVSpct0q9kqaO014TCiKis846i4iIHnjgAXrXu96lEwpFURRFUZrnhhtumJHj6oRiGqBYNK1UEPlqSDSmVNTrS1HLtdpf8a8SYb9tFniml8uw6wYjA2QFVBJ2ZHMMVhZaDLHCagte8BWoJRF+B5UqsfZWWalRVbRuKsjWWQwc32LLrwQzZdooD65JMdmiegMmhA+FzVhapY9sLQ9kXBUZKUtxKRTI2orojgKqzPJYtUlX8fzw+zJqYbAa4buGyXJj/YV+QUbRpcPswzLKasG4yUuRZr+PBNdc4aAOmzkzzUpFMimqEpMXEeGt9vle8+9DosjVVW1tj2B/T+RltAcfR0R5pLLIR2F+2lNcpyTl+5lIx6UcYAWOKDfUFRK/Wa3kNZgb5qfJYzbQCYWiKIqigNh8KGI4RoehE4o6CPtW4PMaSgVRyK+iaZ+KKF8Km3UxWAMEK/Cyb3Vr48kj6ls0i2vtwrwCDm2BlYxYGRNRGfbuBleVUeT5VFi5wl8jKlFN2a+WYNUbc/9EgZWcU4FPA+etKCAfBbKIxrPSgYpTklVfq/QN1BTcHxt1gYqpcUXCWL8RrntSCqpdkak74CtjFQ1v/DTbXyN8jVNcjTXPNVRKE6Zt7qRRKpyy+TyZMJEYiO5IWWViujwU4umoILKII6aQpZUjUKxCwfcK2WhtTQ/OkJnICR8KzkeBSqo5X9nRlFUSuAmijcmI9nvVRoPqHxRcGdzSccKExSW33PpkwF2AEwrNQ6EoiqIoSsuoQjEdEYtmz7cC76NqflBkBEjr0R84bnAZMN0M0UY0xDxzhk9GuIpmdfx+DbYqakxpaq0PBa/oPH+N+letcXh4B44nVsxYAdpbZ+3rvCqdQjXQeLKISooRmQ+rgZFiI3gqyEgaT7ZVAKWCA15s3ZMQbnCVjPo0foWr2bGEmifDrMIsYaWiOGbUA5erwDol83k6YSp9phLI9cBPX5XCGTIPhcRev+0HZM7sJiKiSUTB2FwvvB/X9EiljFricI2UZJd5TbCjR8r3OwHfj6hoj1p1P+w1QG2xv0XYP+jv0kgdkbbApZjKl7dX6u3ZQCcUiqIoimKJyYeiWjj2PEcnFNWQwQn8gfVetsrEzCsVoWiPGr4UEv8qdKbiouWqK1KpgIe7r03FmGfxWJ3aRZSokCgXS8H+Qf6MmfkhkLZ1+xb9hWiQElbd7OsQczuKuGSRT8APNkHW06LNYYL6HzGrXIh6sHVPInKZWH8TvMaTadUP8n4UOHdDeYpVA1ZlkqwkJZKol2Fek3UsxWtFEKH+C+rtFAsDROTl55i0vhTBrLTppPkpt/koMsGMmdmk93sBtaLefBQ2mAN5KMpy3JjXJAUrm3aaMKG0zoKcUBx11FG26pofTBBCNa2s01H1Pwg2rBThU/4/3PZpDP0yBo9V44+9TFxlJxSiTcNlc0ufHxwiIqKB4QH7XXanSZbjdP9x2nM1SmbxPkRE1LfmICIiWnuweX/EAabwzJriNiIiKow9QUREix59wu5bSZuy139u1vQjWJs0Uu8hAyZhy4FrVxAR0cDhBxMR0dBeRxIR0dgzJqHS/ZPP2H1zu01fJZ55loiIHCcXS5syS/YlIqK+NetMGw9eS0S+/intICKi0qRJd/vUo5vNjtw3T8Y8pdgvZa7r0MXmevdft7fX1iMPIyKirV1riIhoe/9uIiLq53GU2WX+YDnPePcwDtKLzPl6934BERHt/QLz/tBD9iIiooN62bk2s4eIiHY+bc7f27udiIjGk1P2WGMt/ilbw8miDurpJSKidSuWEhHR8gP3JSKi5JGHExHRjqwZW8XnTOKrP6dMafbegrmfY8U99phTnE7dmSpMe+5k32IiIkovNmOka4V5HdzHfL7mIFNM7RB+/4Il5l727jJtLSaGiIho1+5dRES09RmTGn1H2uufCk8uMpx6fViMrwH+bVnF5pQDuBjaikHzm7ly72VERLTkBfuaNh9m+mNPjxlHO8bNcfHTtChnHEN7M2x+mWbihd/SkZGRyG1mHNeNxaEybtNpJ7AgJxQSGcUxI+AcUUpFvVVFo7aDOsLn6c2YW7t6cbfdZOty80d2bLX50R559g/1nTOC7iWriIiof4X5YV0yYH7cBlBHABO0BL/vM/UaulcutsfYa6354TtkyjzAvx9tLnpgFWcEPGCpud7+1ebHLzNofmhd/iOB37Je9n5fvcjrnz8tMxOusX3MD+TOx35l9m3yx2Vg7SFERLR4b/NHYDW3bUk35woQP6xOzpy/a7nppyWrTNv3Hzer2ifGp/9jVIt9u80fiJV7meP2rBgkIqJE36C3Ed+rZMQ42rncbDse0xjKDZg/Tn38h7N/kMcQt9VGHPD4TnSbMdzNfdS/xtznA571qp4O8yp+61Rj0ToreAzt12PO3bvcXHO637w6KfM5Jv85Tu6wlNu6D9/fZ1eY/kVWUSKiRMJM1LI8YSiMmz/0GFtJVhayveb7vuWmXwaWmGOuHDTfD3aZc6WTWPwg2sNslxgwk9Re/qO/+AA+j8/HJPWnISIi2pufNZmJtZdrkwzyvRjcx0wmB9eZY/esNK94nl2eeICkWOs4naZYxOZDoRMKRVEURVmwuKQKRbPohGIG8KsNdlZufR+mVypaBeHmfbwCXzngyfZY7YytMatLVIyceH5rQ+fAKmtg7aGB464cMKuorrQ5txV+EuZ9osesLntWeArF4D5mhfmCXVx9ku25T02wLbmGJQSrykP7jSw7wMfrXmZWT1hFoQ1QcLq5jSsGvf5ZzCvMsZVGZi8XjiIiomFehdfKDunwOfpW7W+ubfUB5nWZOe4+S4wCAQUnk6yuUGRZVelbaV4PeM6cd5x9KrY1ufI+qM8oI+hzKCFOt2f+s2qSGEfL+0z/9i0y93hg7wOJqPkxlO4xq95+NnEMLA2uxPtYGbGmf/gr8UoeylPvSl497+Pdm4M4IgLqxnZ+L+vFoPuX8f2AgjOw3NyHbm5TuofHCN9fhKJAYerj/Vf0mj7af5lp21iV+5RjdSqPSB5WB1I8HrOsQPTyuFy0yLyi/zFu4a9hXYQ4yiPJCkWWFY6+tUa58UcapXg89PAzVxLtxPfdVu0zfQzVI7OEFQp+nstizKDfce+i8loo8w+dUCiKoigKiCtTpkZ5KNMR5Zxpoz1oGrVBKhFRSkW9RMz6PR8Bc2vX8IqSiGi/lWYlWuD8BsnkcURENLLNOCFO7jHOk8UpkxEQ2eLSXWbFlR0wzmk9y4y9e8lKs0JZwTZj2JAHckE7POoNYPXUs2q5bdPiFwwREVG5YPrl6M3GCXDt88bLfWc+WI0UxxzgYPplvKpctG6QiIiWHoSV2V6Bc9o22JV3cFVJRHQw90+ePepTGeNEmVtkfETyw8bprjAxTH5SXEchC3+AxeY4i/YyK92D1pi27ctKzlJepaatOzz7B3TxypiVA9isC+xD8Rd/MH3z9IR5j5W3rF0BG/hSVhf27THnW3KwUYYWHWjaiRVn0udD4fIqHP2Ee7n3YnONa1k1QXVQJ/EXREQ0tt0ca3KPcZJEjQ7bR1AWWDHCGFrEfhxL2K9jH+6jRbxSt34meMa4r5OLzBjqW2Puc2FkgiS9fzb3afek6a+xEkeq8DPXxRe5mPsJygTGEnx9soNmnDtZVir4Gc7yI9vLY3EFqwgv4Gvx82cepzu4kilqlyDKKMHXmeH+XsyKG3x8oKThuUbEGW69m+a29Zoxk9zL9G8fP8PIoElElFsyRERE+SGjXpSEo2iKt830wafH9Aee2+Qy43zpdLPDdyoT3N+m4whGfXRU9VH1oWgKnVAoiqIoCnDjSb29ECcUmnpbURRFUZSWUYVihrHJrqKcLqXpo0XgdNjFMixCFImI1nFY5CQXHkqy11SOJfGJUSNllmzaakj/Rq6FQxkcxuDE+IK9jCS8nM0HIYc6l/ugy2yXWOSZPPrWGlm6XGRHty52GNtuzC7LRzgF8RQkdo6h7zVt6l7CTnxwHGNTR3a5Mc8gzJCs45jpnyyH/AX6hyXvAjvK/ZG12y6+rqnxHu6fYIKuFMfXo396WK7ed7mRvg+GaajP9FsPbx9yysyY79ODg2Y7NkksGueUz7x9Fztprh0yfSOLYfVwGe0cO/T1cfjp4H7G3AAzQWqxOb7T4zllVpAgSTivLuNrW8cOh6N8PxKp4LVP7WXyRxSnvLwHZjvzPcYa+ggOvQfyGFrFTplwXLVmISR449TSCHXt5hDGwqhn8kCIpB1Le0xbihx2W+Hv02xeSCNMlE1UfavNsbuWmH5Jcj4KhI0CFAnLpcxxluE5QgE13yPdxWaVxTyWxtgpE2MNTpZd/Ows4WMt435anOPxzs81ni0bNspOmW7WXENqiTHTwRegJ+2Nc5hwCiPmGasUg06ZiTT6hUuic86e5JKV5pXNiBU+Fxx5cadwzxxrCu40tNpos+iEQlEURVFAbOXLF57JQycUiqIoigLceHJIaB6KNuaTn/wk/ehHP6KHH36YMpkMDQ0Nzdi56rVCRBT8DEZsSFNHVN6Jek9aw1MaCjHk9MVdnky7miM+pMy6naXh/KT5Hh789pgsa2d5O2TEhAc6IgDgmQ+Z3LN4mP1krDwRUW6lSbHbxzUikiy35gaNKaQ4bmT9MsvItn4Cy9XI2YCcCjZygc8BOb8CWXaa/lneY9pXWG7OleHr3tZr5OIhjq5AFAjIspw9yJ78y9i0sZr7ZVW/eY+Mil18XBmfjyiCBLcZ0R4la/Jg8wLL4FNsDqoUgmMJUn+2n80LnCEVJhSYCRK9g+a4GS8SCOMT1pgctxX3dm8eQxPcB+ij5/mcUxyRUir2BNoE81qGt+vjiAhk4ESEEPoI0QwpafKA6YpzZ9jIoRV+kwePbzYT5BaZiKHSZCn4Pd83mDxyiziqgXOY5JZwKnaOvnFENIPDdTmyyeB93YvNFRXfs4zMlsgAihwVBZGlEqaRXh7fg3wNvWwC6hY5Xmw1DVQbZTMElQfNNS6phNoOM2BqMfcZV0+FI6LD5hGY4DAeE/2cP6aHM2SmRH4OvtykNXnw151n81CapGOcMguFAr361a+mt73tbXPdFEVRFGXewiaPVv/NUDHGdqZjFIqPfvSjRER04403zm1DFEVRlPlLbD4U6pQ5r8jn85TPe8WmZrqCnVfOPGy2CEV71DJ92B2j7CrVwVaQ9CEdE3kJlYqLOUlUAjKs+XyY012jNDJKSGdZyu1l+RUe6Ei2sxd7ri/i7znIwFfO2eyP5Dv+YlSJcSNZd6+EyYOLH3FBpjIn3akUgmYYJOrJ8HaQpxG5gJTbVs4X9wae6D0sMZv+MeeGVA05f1DI1BPC5CG3W8wmEvT3cu6vfpFyOyEy6UmJGdEe3Su4UiWbDdI9JiFRF5tCXBHlgcREKfbSzy0JmlBSi4IJrQLFnZBki28dTA5IcIWomAKbKPD9YDfMQuZ+TUb0UR8SN7F5aSWPIUTADPAYQpRS2trN+BphumIzBOT77GKvqm6FpXtEK2T6jbSPMuToL/RnMmfakunDWOL+72VTB6dEd3hs2qeb24T7CZNHgccUxhORF10Ek8VEl2ljUSQlg6kpm0KFzmRgvzRHOSGxFX4eUMY8kTbX4GbMfXB62Lzji1BxclxIrMDjpyRK0iNVPo9H9LWTM+bFCj9TdtxgzIhrsFEeDSS0shWfOykJlmLpGJNHM2zatIkGBgbsvzVr1sx1kxRFUZQ2x61UYvm30JjTCcWll15KjuNM+++xxx5r+viXXXYZDQ8P23/PPPNMjK1XFEVR5h2u+lA0y5yaPP7xH/+Rzj///Gm3WbduXdPHz2azlM1ma284k7RaTbRB6Q/SKiT9rrQ3Z4RJoggvd9T9YBl6bIqjHITJA3I1PNDhqY5kOzhuX9Z8n4GXt7gG66Gf82od2IgPlluzLOmmuMIjTB5S1k8gCqAbZpRFgeOhEqKUZXEfINX7k0sh4gMVHKVMDVNQQbQlw9I5toNMDfkex82lgud0ZPEgyPmQpPmauliSTiQRlWCuuTTJfSNWQl5iIrMdEhmlFwUrsELKdv3RCzDNiXEE09lA1rS5VObaKPgeJhE27+RF9EI2YgzBhIIoEowl9FVShAjAdJhAgis2D7lcf4aIKMdjKdRfYizB5AETERI5wdyGCCFbw0NEeaDqaFKMJbQdVUj9oD8xVvAswvKB4ZjmtmXt2GITEMYOojx4PzyrGO9uppu/d3l7XwXkpLmOBCfmsiYPARJ5ubx9hfvcRndwf1hzLlWP7hDlWDqA9veheOqpp+jjH/843XbbbbRt2zZatWoVnXPOOfSBD3yAMplM7QPMEHM6oVi2bBktW7ZsLpugKIqiKB3FY489RpVKha677jo64IAD6NFHH6ULLriAxsfH6YorrpizdnWMU+bTTz9Nu3fvpqeffprK5TI9/PDDRER0wAEHUG9vuLqfoiiKojSKG1NxsJn0oTjrrLPorLPOsu/XrVtHjz/+OF1zzTU6oaiHD3/4w/TVr37Vvj/mmGOIiOj222+n0047bVbbElXGvB7qjvZo+MAs43KTvMREXhvhqV/kge7VtWBJH57nlWCZZ3iWp0XkSJ+V9hG9gDoDwbLFFsixvqgCyMoJyK7wMGc5PgVPdPGARybfYa9/eOZXIMsmg0Md/eM3edgkTiy7o/2eycO0QTjmWxkb+2N79AvMTpCvbbImSKLSJARTBF87Eg9luW8aNgehbziRle2jbHfgvIFjiCgP9BOuyT4DuHa+tqleNgsJkwfMZjlhHuq3ZqFgX8Fs5vUVop0SgTbDPOR0e/VIEhWUF+dS7GzSQM0K2V/4Hq+hsYRoB5gAnKDrmcP3EeMA9zlwmmywlgxMQvZZqwQHFZ41PHvZJMrKCxOQi2fVfF5it7h0uiuwXcDewCYMl00e9rdI/AFEXReY4mD6QD0VO27sbxgfXpo6qAOJsXy5jC6cKVP88PAwLV68OPbjNkLHRHnceOONZuYo/s32ZEJRFEWZx8TllFkpU6FQCEQaDgwM0KZNm2Jv8ubNm+mqq66it7zlLbEfuxE6RqFQFEVRlE4ik8nQrl27Ap9Np05ceuml9M///M/THvP3v/89HXzwwfb9li1b6KyzzqJXv/rVdMEFF7TW4BZZ0BOKuJKnNJh7qrWTgIiTIXFTSkrG5JXsRtQB5FNI9VMlI6tWrIxKvJ15TQu5Gp7nSA6VsTKtTGjDMjXkak5wRUSU4HoINtkVS7wue9a7eZb9RdIdvNr6F5Cl4fVv6wwEZVnIu8mELI/ttb9iS0Qj4gBJiJLcLzIZEUxHwf6xXv9ISJXA9lQdlrWtGYfNNlZ+FdecLBaC3zNIwGSlej4O+tjrIyFdk99jn5vEbca14F5Lsx9k/jzr/BUh4SeEOQB9hMigPpH0K8Wvtq+kSdD2hZH2YSYyJzf3C3ukkNSJzWouf+9gLPH39lgwoyChU6b6WAKOjfbgaJGEG7gW0xZrY+NtzDFgfqyIMYV+xdiS0R0SmEzK3M9JNismqphSXTahOTBBRkUj4DqFSS6qH/AouSKxVcfhutF90shh+N729/fX2NKj0cjHrVu30umnn04nn3wyfelLX2qqnXGyoCcUiqIoiiKJpdpoE35xjUQ+btmyhU4//XQ69thj6YYbbqBEYu49GHRCoSiKoigdxJYtW+i0006jffbZh6644grauXOn/W7FihVz1i6dUMwAflNKtboejR0sYv8oE4iV9Nlb3ie7lissXbI0TygBzu9tDQ8+tpfgybxCpoWJJJcOngPmA+nlbYsfsNd4QGJnj3GYIhIsQ7v5SW5jUKa2lxshV6N2RwUe+TXkWb9JCJEFFVhVUMqbP7eyslh4pJNBeRq1TDIiQgLnssmaEAkhIxdQihr1Kmyjebu8qMEgQDSCjYRBoiwr4XMfWS/+JEmk5C6jPRDpkxBmM0QtFEUnpa3Zp7p5CGah0FiSoUI2a1IieK18jURe1IUtAwKTB38uV5/2GHhFv8NkxGMraizZ4/Br0pobve/SbvA6UIsDn4dqevC+8j7IZFG2fDm/2poeGN88lhL+NuM62FTjvUqzEkwewVfP9BEcN7hCJ9TWDjN9uG4oEqgpZDhYjNxyyy20efNm2rx5M61evTrwndvq35wWmHuNRFEURVHaBNc1ocUt/5vBPBTnn39+1ajHuZxMEKlCoSiKoig+3Hh8KBZgcTCdUMwXkLMfpgPI9T65EYmnXEISLMjQMGWghkf1U9SS9qWkHxI6IZ36pFIky6FUsE02iRDL+o70uoaXv6g3YOVtHBfnkp75/OqPuEBkATLhQ7LF9ZYT1U1BjtjOS5oVTGRl+0WsImxkhU0gBDNOd2A7aw5iKT7S5JEIRosgKgTvbWKxZLAWA+8srsm8wgRRtlo6rp1NFjB5lINJ0YCMVsCYs2MIfS+iOxwxroE1D+E16yVyQmIr7AHTj8tRMXJc4nuYz0Jlu5HIiaNwZGIre16U62YbX9K3WYpNGzb4JcnXVZk+eiMh6mPI7dDNeGbRbzDP2c19yeSsKcg+j9yHNZwI3SrPb6CttnFzu0pW5g6dUCiKoigKcMPZVJs6TGXhTax0QqEoiqIoICanzFgcOzsMnVDMFo3W7GjRucZKzAnvODik6wZNEpBJU26VGgQ+pAkAXuyeRz4FjhtCeokTWenX9gs8y8tBSVtik2ShXyFHQ8a35oPq+yesJ7rXP16fiWZDwo64Mpu+S0REoD+STvA1nKRJ9AvKZEPuR2I9mDJKbOaJKGDkJBEBw1EeVrKHWSjYRxTRR+aagm3HvUavQZIvOqj7Yj6vCNkb23l9Uj0CJi3MZ6G+iog4gOmLiIiQ7Izf2kROMPnIxFY2YgT9FUwMJseUbINtmojA8H/rmcPQL9iI31emj4Twjjn9djA1JRBVUm2VDJOaSPZm8yZE/fZYu4t49sTXso2dF+ThUiWO4mAxHKPT0CgPRVEURVFaRhUKRVEURfERT6ZM9aFQZolQGfO6d6yxPUudCetp7umNqVAuLPbcR+0OKJ6QrWU0A+F90BM/JaI/vPLlkMeDErHjl9ghtyIqw8rJnGzHre5RbncXMrQbEd0RMpEw/noDMH8kvQs1L/w2qufxveMEZf207QccDjK+OIComWDLRadEAiZsJ5KBheqcSLOALRsvajFUi4BxpFwtTBXcdkTCFPlisJ33G1pd9g6bzYJmpqToK6eMcRBh+oCpy814X2XEpumgicipBM1r1kQkomPsWLLfT9NvgWsNR27YsQWTUaW66aOWtSEK/PGCOdNGeSA6x39cm/wqya9Bc2zDv0l1thURO3HVUJopXPWhaBqdUCiKoigKiC3KQycUSgvMaNVRsWqIWkXgY4dX+Clf/HmVrYnIc+BK2lUm51sQW0etxGX+BZkt2Wt02JkNq2brGGbzIPDqOmq1JBUHESMfWo1H5g7wHRKvuB4KSjROxOoxKh+FPF7UNYScVeGMyZvZa0ROcOnsZW+6VDpkquRgngvbRxF9E7g2wrWJL/A5mgIfQ1GN1G6HPhJp2mWujkSNXAahHAoJ3zhx+TNUCYWCE/ED78AROCnStWMsod/wKsdcPWNLOGp6+WGCygI6OsqpNWoo2Zwb4jfIKhN+50yZEx/jFcqLG1Qs7DVEPYtQNup0yesUpUJpHJ1QKIqiKIolrkyZ6kOhKIqiKAsW1yWqxGDyiOMYnYZOKFogStb1A1mv5aqjTEh2lLKk/Zgd0HxybJKdsCoyz4LNTwFTh3Sw4+2EbOtEmDocsX2kE6Lv/92ENH3AgbFGv8FMY2XqoBTuSjNAHfK+VYmRO8E6HkbsZ5sinTCDr1Ft9xwMU4Hze9tJsw68Z6c3B0VVhww5sla5H/YtBa/BOvlWIsxB4rZJc4+tomnfB00d1hTgloMHYqRJzHM8rfJTZlOa13A2lP2UFKYO6eibDI4t+1rHI+6IcR16VpiEqE7arHXArWJekJ/Z3zG0xprsgqYP6UgeSoce1YhpnjllfqETCkVRFEUBcZUvV6dMRVEURVnAxBXlUVYfigWB6zhz52EclYK74dTcleqvOJz9H1+ehSQqkOIDluiRh8KtLl9LwnkpzGsyUtsPtsUvscvU2jaqozK9TO15+Vf3uK+VJnnaZvKrVfcp2E+h7YWpo+bIikofLTazt6FiInbciDEiI2TC5xFmoTojYAKHEqY7afoIP07BD2qZyZJBtd3LFRHdICIKm8qIfJFDeO/WuD4cS0S9SFNHrTweFZsLovYfEmkOlJakSPNanWPMneYZtucQ526VkAlEjteOMX3E5JTZYj6PTqRT7rCiKIqiKG3MglQoFEVRFKUamimzeXRCMQP4Fc+aKXOjUnDXG+UAj+tiPvDezQajHfzfJSHVsvZZltEM05/R4iV0EvJ2zUROvgqo9iskdYI8Wgl8HymbSvNBVKIr+z17tleJEZce+N71mNdK3T0zPa6I7nAc4UUvzUAw60SYgULSquwLaRaKioDxfyawETBCmk/KKI8IapnJEsKkEn0gyOhiLFUZ51EmohD1RsVEJLaqOyKpCgkZaSGGmEx/3yz+4Z6MOBbakIx4fmtFmIW2x2YdY+pgNFNm0+iEQlEURVEsLlU0sVVTdNjUUVEURVGUdkQVihhoKsFVo9EekFfxFp9Dhs2IuWEi+tY6ofYGE93IRFeh/UMmDtGmWgT2j7iuWh7i4n0tU4ftvwYWDTIvV0ROp7qRCYQcIbHLqAR7+FpmoFDD6zQLVa02Ov0aw0a0cCus6UMkBbPbi/fS1FEzCVqNa7DmoiomDyciAkoes+bYQSIraQoRY0qWzZhugYpeFlVZIsec/F7+1szqyjBk+ojIgFcjusNv3mqnuh5ubGGjavJQFEVRlIWL69pS9y0dRn0oFEVRFGVhE09xMJ1QKDEjS5pHmT6s5B+SCasXEbdiYZRELWXtOpAe+GQ90EULasiwNogh6hoDe+P6xHXZg9dKSlS9Vke0J35wd/+11ZOQiKgZU0dwP5g+HCv7R9QzsQ2rUUa6hrQcLrcd0VcNIE0fIMocFFXCPWQmrDciA6XZKZzYCqEoNRNaeY0LHDtU1j0iSZrLzxYihprxwfPq4wSjPeodYpEBVeLzesbsdCbbqlhbT/XfKFsTJCrxmjLv0AmFoiiKooC48lCoQqEoiqIoCxdNbNU8OqGIkemiPRo1fYDwkSBv1zBlTFOa2p6bP46SW2t5mseCNO3guuosWy6PE2XqwOFsvYWmG9w8oYgIawMSpg98jK4RpazrlvJBnX1lPgv2lyRccwLbV0/M1HJEkG2XiHyx5gj+3v/bHZUsLuKYUfVgaiW6ktEdrhhb9ZrQ/MhEV/Jz4JlK8B4JwkhsF+7pWs+zI0wZoWiZqO8Zr+Xox1ATlHmKTigURVEUBbhElVhMHgsvsZVOKBRFURSFceOqNqo+FAsTSHxxJVfxy5VSqqzX9BGqR4C21tmGODyq66/p0Vi/BcqXywgF+75GPZAqx/J/3w6mDhvxgBopaJP9PqiZ2ygZROa41fT82lJ+FLX6iqixxF+BQ0VGcYjt7OcREUHhA2MP0z58HFH7xf+ZWyvdU5SJo8F6MPUksqqFLAcS9UzVMnXI7+1+VY4VNo/w/9jy5o2ZOuxxOj2qQxNbNU2H3nFFURRFUdoJVSgURVEUBbhEbrl1LbNJIbGj0QlFE1RP0FSdqMiPKNMHcCLEo5rDfBqZUZ5DqsxRHuaSWnKsPN909UtC5dtryKSRMmqEqSMKyNPTeeI3+5Mix4c0faAMerhUdbDWh2cPMJK7Z5oTfVBvTQ9sXmMc+NsShYz2iPo+dqZNkhbcpu5j1Zn4C4msoqI7wLQ1PNBvGAMuxkTw1JH72+0ai/rw3w98FzI/RSWqqhX1IYnq/zqf8bnGdd1YnDLjOEanoRMKRVEURfERS4RGsw5JHUx7TxUVRVEURekIVKFogdpJqDyiEtVEVv6NMivUOQdsJWKl4Zz+MdCwR3go2qN6mxuJ7qh3UVKvzF+v6UPuHxX94dqy5+LEtZKcCaZbOMlxWqtL6jVt1NrMS7YWZdJovKZNKOFSVFl3+16YOpDASjyrZZgpROe0sh6td/TXiuoIfS8+938nI22oUqdJQxK1nf289viMO9KuJVyiSgw+FHEco9PQCYWiKIqiMLGl3tbEVoqiKIqygIkrykMVCqUV4oz+kNQyhdTDTPkINdwkv9Rcr6zaYMRCVJTCTC4aokp31zJ92P1rRH/IAzZrmqoVweE7xYwjo51C38saHqHEZ9NFNUVFBLVWB8Zre3XTRyNEJQSLolFTR9UoD7sPv4bGV41EVs2aRNo8ukNpHZ1QKIqiKIqPOPwf1OShxEK1YRS1DolaLdarXLQzkemUAxs1t2qpJ5cC0eym2q5FpFJh0y5P76wpqUdpaKRd7YB0zpQp6ENdYdNF17Fajiltexx/J8Iq1PTf2yY2qEwkE8GcE+a76nknnEaViUbzUHQIWr68eTr7ziuKoiiK0haoQqEoiqIowPUKv7VCHMfoNBb0hKIuST4mGslZQVS/KWQumYumtEOceq20040SZfqAnB0lh3fCz1XLd0uaKerYru5ql1WqrRLVNnVIZ8xG7kMoPX2EI6/cLlQ9tEFTh/93o2beibicMDsUl9yYanl0whMaLx1h8njqqafoTW96E+23337U1dVF+++/P11++eVUKBTmummKoijKfMI1dTha/7fwJhQdoVA89thjVKlU6LrrrqMDDjiAHn30UbrgggtofHycrrjiirlunqIoiqIseDpiQnHWWWfRWWedZd+vW7eOHn/8cbrmmms6dkIRNXdt1hQSxUyYSGodcjZNSXEiTRk2gKDG9o0Sla8kyvQBokwgrbanHahZfVdWrA0dwFfBNjH9z1qtCKEZieoQ72tVF61l4rCf8ytMHGETSDhdu1Mpm9eQSaPOC5UmDTadUKIjBO/axJTYakaT3rQpHTGhqMbw8DAtXrx4rpuhKIqizCNM2KhmymyGjpxQbN68ma666qqa6kQ+n6d8Pm/fj4yMzHTTFEVRlE6GfShapVLpbOfUZphTjerSSy8lx3Gm/ffYY48F9tmyZQudddZZ9OpXv5ouuOCCaY+/adMmGhgYsP/WrFkTS7sdisF7PQJX/GuViuuG/jWL40xv7nBct+3MHfJeJRyRhtg31iK3Ef/iblO9uK4bMoP4qbjBf+1M1Fh03erKu+s4gX8hnIT3L2Ifua88F9oU9ezV6v9Qk6qMLZCI+Jd0HEr69ksmzD+MSYydpMP/Ir5POA4lHMc+s3g2zb+KMXfYf9wR/D78vfhnO6zimTtiwt9OpfOYU4XiH//xH+n888+fdpt169bZ/9+6dSudfvrpdPLJJ9OXvvSlmse/7LLL6OKLL7bvR0ZGYptUKIqiKPOTOEI+Ozx6tinmdEKxbNkyWrZsWV3bbtmyhU4//XQ69thj6YYbbqBEHQ5A2WyWstlsq81UFEVRFgiu62otjybpCB+KLVu20GmnnUb77LMPXXHFFbRz50773YoVK2b8/PCUjqt2QiM0mhBrJminqA6cq1aCK3nPakVsEHme9JC1oxJYyTPXuvq5Cr6Iqn7aCdSuQtr4RUVFc9jvSX5f33Hl2Ko2buqtKhoVxSG/j05sFYzqwPPiVEreQVqtJjrffQPceOpwLMRaHh0xobjlllto8+bNtHnzZlq9enXgu0ZsmoqiKIqizAwdETh8/vnnW4co+U9RFEVRYoPzUMTxbzbI5/N09NFHk+M49PDDD8/KOaPoCIWiXalHRo+b2TSBxGbqaMU7KSKRkTR92IRINZokax74sQmtIkwfcjt5zGap1yRRr2ze6HHjJO5TRt3Peu93NWbKdBll+mhkX0mUiUPuV9PU4X8Ga5k6JK16F3ZYOXOX4vGhmK3iYO973/to1apV9Jvf/GZWzjcdnXWnFUVRFEUhIqIf//jH9LOf/axtMkarQqEoiqIowCVyY3A8nekoj+3bt9MFF1xA3//+96m7u3tGz1UvOqGIgbkwfcwkbWHqiDqGkE9rmT5kLZPpoj5CtTxCNR+qm0BmioVo4qiXOE0dzUZ31BsF1Mix7DHEva83miO6JHkDHbbATBySuMNGZYbmONIZuK5L559/Pr31rW+l4447jp566qmWjhcXnX3nFUVRFCVm4nLKLBQKgWzNAwMDtGnTpsjz1ps9+qqrrqLR0VG67LLLZrFXaqMKhaIoiqLMAJlMhnbt2hX4bDp1ot7s0bfddhvde++9oWMdd9xx9PrXv56++tWvNt3mVtAJxTREyedR0mk1qXO+mEGI6jB1zEauWZyjTtOH3S3iHla7Z1Gmg0qDYnZUWHOjpgxJXKaNucx3JU1RM0GtaI5aZelDpgwR/SO3b4aosSBNHN7nEaaOeiM2Gtm23ucZWYulqaPW+3YlrsRWbH7q7++ve596s0d//vOfp0984hP2/datW+nMM8+kb33rW3TiiSc23tiY0AmFoiiKojBx+VDEcYwo1q5dG3jf29tLRET7779/KPnjbKITCkVRFEUBnNiq5cMsvMzbC3NCIcvjNloXoJHaHo3WfaiX5jzJp9+raRW6zifHaeEJc6VcGhH9Ic0yUSaQRJUenM4MQlS/tB0VJRLFfDBhRDEbpo3ZplWTlZ/atTuqj9+6TR1iu+m3bdDEEUWnmDbmEfvuu29bZI5ekBMKRVEURamGS/FkU22HP/CzjU4oFEVRFMVHOYbJQBzH6DR0QlEHUXUDopImTXusiM9nqgR2PZJz04msakikrZg46j2WNYW0aAIhqm4GIaptCgkdp0VFfKaMBPPR/NAKtRLSRUb7NJj4qp42ePsEPwlFc4AGTR1xPoshnIgojw7FdYni8KecpVIebcX8GAGKoiiKoswpqlAoiqIoCuOSqyaPJtEJRQPUKpncSPRH6NjNNiqCjjV1RCSuqvdcjZpAgttEJBlq8O7EVR5bTRSzQ6ORWHWXm69jmygTh31fJUrDfN6CqaPe6I4mTRj2GUQisA4zhbikJo9m6aw7rSiKoihKW6IKhaIoiqIwRqGIweQxrwov1IdOKJqgXtOHn7hk8FrEIZPXXZ48tF+dpo56tqv3WKGaHnWaQKrsH3ndjSY+i9mAtRAtH3E8Ls1EYRHNTJRN1HMZaeIAUaaLqLLks5meMapWR6dHfWiUR9PohEJRFEVRmNgUCnXKVPxE5TCw30dUtKxG1AqlVeWiGUUi7hTbNZWJmVw11VAeGs5fUe1QjboazbCk0KyCNBM0mra+XmodtpkuiPsZbOTZi9o0SpHwvm9OmYjcr2oj6lfxpvu+05wvlfjRCYWiKIqiMBrl0Tw6oVAURVEUJq5MmTNYvbxt0QlFFaIkZXweJfNW+7iWmjqbuQZmKu9EWxKRh8K+reOaGjGL+M/RTiaJmabZa23VVDLd7o02Ka5ncLrD1Pts1TRVNGrqaIQ6TRsSN+SM6VT/vEOIz4ei9bZ0Gp11pxVFURRFaUtUoVAURVEUH7H5UCywkG+dUDRBreiPwLYNRILMBPWouTOWd6IZ+bXZDqoZFlBHW5owixA1YRqZjzQoa9cac62YROrdtdZQa7YJ015bvZFSDZo6ajfKd39q7VvjXoaiOYSpo9NMHJLYankswMRWnX3nFUVRFEVpC1ShUBRFURQmrigPNXkscJqX/ps3gdh9YlLHFmKaZiKK7sBGOqRJKbglz/o2p+5kRS3K6KHNI+5nnIm0Wj1Uzd+LafokcszUMnXEQYP3ItLEYd8HTR0yuiMyKq5No6E0U2bz6IRCURRFURhNbNU86kOhKIqiKErLLGiFom75tEaSJEk1Ka/WuebCVNGq5OjaRE41agDMpUlAXmMrHd2ppo0WvO5rmXNaNonEHB1CFEPSrGafizhMHPbzZhOG1Xgmp9knkigTh/i+XlOHd17v+3Yzf6jJozkW9IRCURRFUfy4RBTH0mHhTSd0QqEoiqIoFhPloQpFM+iEohkaNIEQNRYJ0mnUbfqwO0xXSnn+9EvbEHMERmBXceyGS1g38SzVYtbk8xr92lpdDX4OIqOXpjcnNnQfapo8qps4Queq09ShzF90QqEoiqIoPmKJ8mj9EB2HTigURVEUhYkt9baaPJTZolYp9NkA564pEddpsoiSWUPSbzOy9mxGWLRbLYJmr30Wr6NhU4ek3fp8Ohqt8UItmANr/j400W/1/ubUKlcutpsvpo648lBo+XJFURRFUZQmUIVCURRFUZi4ojwqavJQqjKDcmw7mT5AwyaQyANX+Pgx9F8nSeJx00SyonqI5b7Uy3y6f1HXMs39qbevG/4VmIGfjYYTXcVyzjrNr7OAmjyaZx495YqiKIqizBWqUCiKoiiKj3hMHjE0pMPQCQXNrczWjp7RDZtAophPMncb0HLSqHrokHvWynMzY897DH0XuscLObppjojN5NH6IToOHUGKoiiKQkQrV66k3VSgYgxpqbZTnlLj+Rha1TnohEJRFEVRiOiMM86gAUrTb2ikpeMUqUL30xBd+x9fi6llnYGaPOaIdjR1RBHV1nbwyFamoYMl7Jl8Ppo99pyM9w6+h82AezNXv4+O49B//fJ2OuXkF9Ih1Es9Tf6JfIRGqZuS9JrXvCbmFrY3C2u0KoqiKMo0nHTSSbSGuuh+Gm5q/0kq08M0TN+542eUSCysP7EL62oVRVEUpQY//cPD9Ecap91UaHjfB2iYVlGOTj311BloWXuzIE0eruOQ6zizImF2kmmjUdopGU0nEvfYmE/3oda1zMVz1ZaRJXPAfP5NAwceeCAdQr30axqil9HyuvcboiI9RmP0yO9+O4Ota186RqH4m7/5G1q7di3lcjlauXIlveENb6CtW7fOdbMURVGUecjtO/9E22iKttJU3fv8Lw3RC6iHDjnkkBlsWfvSMROK008/nb797W/T448/Tv/5n/9JTzzxBL3qVa+a62YpiqIo85ClS5fS0TRA99Iecqm2wrSNpuhZmqTbnvvjLLSuPXFctzO1uP/+7/+mDRs2UD6fp3Q6Xdc+IyMjNDAwQNu3baP+/v7Y2rIQJMDpmE9y7lzQzuNnPt7bdu7vKDrxPrTSzyMjI7Rir71oeHg41t/qRpmcnKTl3X10Ai2iA6kncjuXXLqZttNqytH97tDsNbDN6BiFws/u3bvpG9/4Bp188sl1TyYURVEUpRG6urro6q9eT/9Le6g8jUrxJE3QKJXojtFnZ7F17UdHTSguueQS6unpoSVLltDTTz9NN99887Tb5/N5GhkZCfxrBThzyn8LFcd1O3Ll1G6gH6P+zSVRY77ef+1Irf7W+xAP7diPzfD617+espSgR2m06vdlcunXNERXfuka6u3tneXWtRdzOqG49NJLyXGcaf899thjdvv3vve99NBDD9HPfvYzSiaTdO6559J0FptNmzbRwMCA/bdmzZrZuCxFURRlnpBMJuk/fvYjepCGaapKhY7f0yglyaE3vvGNc9C69mJOfSh27txJzz///LTbrFu3jjKZTOjzZ599ltasWUO//OUv6aSTTqq6bz6fp3zey6U+MjJCa9asadqHol1XXHNFJ642OpFOHnfzaYzofYiHevqxXXwo/KxxumgxpekkWmw/y1OFvklb6Ds/uJle/vKXz2Hr2oM5zUOxbNkyWrZsWVP7ViqmeIt/wiDJZrOUzWZDn7ezHNtJaB8qtdAx0h7ofWidH/3m1/QXRx1Nh1Ef9ZPx3XuYhmkxpenss8+e49a1Bx2R2OrXv/413XffffSiF72IFi1aRE888QR96EMfov333z9SnVAURVGUuDjyyCPpAOqm+2iIXkrLaIxK9CiN0q/uv48cnbARUYc4ZXZ3d9N//dd/0Utf+lI66KCD6E1vehMdeeSRdOedd1ZVIBRFURQlbm595jF6iiZpJ+XpPhqifamLjj322LluVtvQEQrFEUccQbfddttcN0NRFEVZwKxevZqOoD66nZ6nUSrRH5/801w3qa3oiAlFXMD/dHS0eviPoiiKMvfgN7od8y7eMfwMrRhYRIdSH+27775z3Zy2YkFNKDBIDzzggDluiaIoilKL0dFRGhgYmOtmBOjv76cJNxw+qnRw6u1mqFQqtHXrVurr65u3TjQIjX3mmWfaJtxqNtDrXljXTbRwr30hXLfrujQ6OkqrVq2iRKIjXP0UWmAKRSKRoNWrV891M2aF/v7+eftjMx163QuPhXrt8/26202ZUGqjUz9FURRFUVpGJxSKoiiKorSMTijmGdlsli6//PIFl59Dr3thXTfRwr32hXrdSvuzoJwyFUVRFEWZGVShUBRFURSlZXRCoSiKoihKy+iEQlEURVGUltEJxTzlqaeeoje96U203377UVdXF+2///50+eWXU6FQmOumzTif/OQn6eSTT6bu7m4aHByc6+bMKFdffTXtu+++lMvl6MQTT6T//d//nesmzTh33XUX/fVf/zWtWrWKHMeh73//+3PdpBln06ZNdPzxx1NfXx8tX76cNmzYQI8//vhcN0tRAuiEYp7y2GOPUaVSoeuuu45++9vf0mc/+1m69tpr6f3vf/9cN23GKRQK9OpXv5re9ra3zXVTZpRvfetbdPHFF9Pll19ODz74IB111FF05pln0o4dO+a6aTPK+Pg4HXXUUXT11VfPdVNmjTvvvJM2btxIv/rVr+iWW26hYrFIZ5xxBo2Pj8910xTFolEeC4hPf/rTdM0119Cf/rQwKuTdeOONdNFFF9HQ0NBcN2VGOPHEE+n444+nL3zhC0RkUsuvWbOGLrzwQrr00kvnuHWzg+M49L3vfY82bNgw102ZVXbu3EnLly+nO++8k0455ZS5bo6iEJEqFAuK4eFhWrx48Vw3Q4mBQqFADzzwAK1fv95+lkgkaP369XTvvffOYcuU2WB4eJiISJ9npa3QCcUCYfPmzXTVVVfRW97ylrluihIDu3btonK5THvttVfg87322ou2bds2R61SZoNKpUIXXXQRvfCFL6TDDz98rpujKBadUHQYl156KTmOM+2/xx57LLDPli1b6KyzzqJXv/rVdMEFF8xRy1ujmetWlPnIxo0b6dFHH6VvfvObc90URQmwoKqNzgf+8R//kc4///xpt1m3bp39/61bt9Lpp59OJ598Mn3pS1+a4dbNHI1e93xn6dKllEwmafv27YHPt2/fTitWrJijVikzzTve8Q764Q9/SHfdddeCqZysdA46oegwli1bRsuWLatr2y1bttDpp59Oxx57LN1www2USHSuINXIdS8EMpkMHXvssfTzn//cOiRWKhX6+c9/Tu94xzvmtnFK7LiuSxdeeCF973vfozvuuIP222+/uW6SooTQCcU8ZcuWLXTaaafRPvvsQ1dccQXt3LnTfjffV7BPP/007d69m55++mkql8v08MMPExHRAQccQL29vXPbuBi5+OKL6bzzzqPjjjuOTjjhBLryyitpfHyc3vjGN85102aUsbEx2rx5s33/5JNP0sMPP0yLFy+mtWvXzmHLZo6NGzfSTTfdRDfffDP19fVZP5mBgQHq6uqa49YpCuMq85IbbrjBJaKq/+Y75513XtXrvv322+e6abFz1VVXuWvXrnUzmYx7wgknuL/61a/mukkzzu233171/p533nlz3bQZI+pZvuGGG+a6aYpi0TwUiqIoiqK0TOca1RVFURRFaRt0QqEoiqIoSsvohEJRFEVRlJbRCYWiKIqiKC2jEwpFURRFUVpGJxSKoiiKorSMTigURVEURWkZnVAoiqIoitIyOqFQFEVRFKVldEKhKIqiKErL6IRCURRFUZSW0QmFonQgO3fupBUrVtCnPvUp+9kvf/lLymQy9POf/3wOW6YoykJFi4MpSofyP//zP7Rhwwb65S9/SQcddBAdffTR9Ld/+7f0mc98Zq6bpijKAkQnFIrSwWzcuJFuvfVWOu644+iRRx6h++67j7LZ7Fw3S1GUBYhOKBSlg5mcnKTDDz+cnnnmGXrggQfoiCOOmOsmKYqyQFEfCkXpYJ544gnaunUrVSoVeuqpp+a6OYqiLGBUoVCUDqVQKNAJJ5xARx99NB100EF05ZVX0iOPPELLly+f66YpirIA0QmFonQo733ve+m73/0u/eY3v6He3l469dRTaWBggH74wx/OddMURVmAqMlDUTqQO+64g6688kr62te+Rv39/ZRIJOhrX/sa3X333XTNNdfMdfMURVmAqEKhKIqiKErLqEKhKIqiKErL6IRCURRFUZSW0QmFoiiKoigtoxMKRVEURVFaRicUiqIoiqK0jE4oFEVRFEVpGZ1QKIqiKIrSMjqhUBRFURSlZXRCoSiKoihKy+iEQlEURVGUltEJhaIoiqIoLaMTCkVRFEVRWub/B3d0ZAVKjVKtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sim_data.plot_field(\"field\", \"Ex\", y=0.0, f=200e12, eps_alpha=0.2)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc2936a5",
   "metadata": {},
   "source": [
    "##### Quiver Plots\n",
    "\n",
    "Quiver plotting can be done through the centered field Dataset.\n",
    "We first should spatially downsample the data to be quivered to reduce clutter on the plot, which can be done by `.sel()` with `slice(None, None, skip)` range to select every `skip` data point along that axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "12b2b76d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:22.129554Z",
     "iopub.status.busy": "2023-02-03T04:14:22.129282Z",
     "iopub.status.idle": "2023-02-03T04:14:22.312733Z",
     "shell.execute_reply": "2023-02-03T04:14:22.312313Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# downsample the field data for more clear quiver plotting\n",
    "field0_data_resampled = field0_data_centered.sel(\n",
    "    x=slice(None, None, 7), z=slice(None, None, 7)\n",
    ")\n",
    "\n",
    "# quiver plot of \\vec{E}_{x,y}(x,y) on plane with Ez(x,y) underlying.\n",
    "f, ax = plt.subplots(figsize=(8, 5))\n",
    "field0_data_centered.isel(y=0).Ez.real.plot.imshow(x=\"x\", y=\"z\", ax=ax, robust=True)\n",
    "field0_data_resampled.isel(y=0).real.plot.quiver(\"x\", \"z\", \"Ex\", \"Ez\", ax=ax)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27630dee",
   "metadata": {},
   "source": [
    "##### Stream Plots\n",
    "Stream plots can be another useful feature, although they do not take the amplitude into account, so use with caution."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffde187e",
   "metadata": {},
   "source": [
    "##### Time Lapse Fields\n",
    "\n",
    "For time-domain data, it can be convenient to see the fields at various snapshots of the simulation.  For this, it is convenient to supply the `row` and `col` keyword arguments to plot, which expand all plots on a row or column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3b49c1f1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:22.315310Z",
     "iopub.status.busy": "2023-02-03T04:14:22.315144Z",
     "iopub.status.idle": "2023-02-03T04:14:22.653891Z",
     "shell.execute_reply": "2023-02-03T04:14:22.653417Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6Zz/7mX7kkUf0O9/5Tj1v3jz93HPPaa3Zv8nwMoj+vXnzZn3eeefpO++8Uz/xxBP6vvvu06effrquVqv64Ycf9o6L9u977rlHl0olfeGFF+rf//73+rrrrtMzZszQ//mf/6m1Ti83gsRlbnzwwQf1+Pi4Xrp0qV65cqX+3e9+p3/wgx/opUuXJt5XGtnS7tqE9JNBjc+jxGWLi/bvU089Ve+yyy76hhtu0I8//rj+r//6L73TTjvpj3zkI1rrdHLjrrvu0pdeeqleuXKlfuKJJ/TNN9+sjzjiCL3XXnvpyclJrTX7NyFFg8ololevXq0PP/xwPT4+3tdUpytWrGhKqwpAX3DBBd4xRx11lD711FO9z7vvvnvb3yil9Pnnn6/nz5+vq9Wq/uu//mu9evXq0LXvvfdefdxxx+kddthBz549Wx9++OH6xz/+ceiY3/3ud/rv/u7v9HbbbafHx8f1vvvuq88++2ytlJrWPUXh5JMMkkH0bzMoi9tuvfVW77jdd989sW/EKZcuuOCC2POuWLHCO6ZWq+kPfvCDet68eXr27Nn62GOPDU16tWb/JsPJIPr3tm3b9N/93d/pnXfeWVcqFb1w4UL9ute9Tt9zzz2h4+L6949+9CP90pe+VFerVb3vvvvqr3zlK96+tHIjSKsJ4D333KP/5m/+Rs+aNUvPnDlTv+xlL9MXXnhh4n2lkS1prk1IvxjU+DxKnHIp2r83btyozzrrLL3bbrvpsbExvXjxYv3Rj37UUwynkRu/+tWv9DHHHKN32GEHXa1W9R577KHf85736D/96U+ha7N/E1IchNZaT9P4iRBCCCGEEEIIIYSMKLL9IYQQQgghhBBCCCGExEPlEiGEEEIIIYQQQgjpGiqXCCGEEEIIIYQQQkjXULlECCGEEEIIIYQQQrqGyiVCCCGEEEIIIYQQ0jVULhFCCCGEEEIIIYSQrillXYC0XHHFFbjiiivwxBNPAAD2339/fPzjH8eJJ56Y+hxKKTz11FOYPXs2hBB9KikhpBu01ti0aRN23nlnSNm53pv9m5D8wv5NyPDC/k3I8DLd/l1UJicnUavV2h5XqVQwNjY2gBIVA6G11lkXIg0/+tGPYFkW9tlnH2itce211+Lzn/88Vq5cif333z/VOf70pz9h0aJFfS4pIWQ6rFmzBrvuumvHv2P/JiT/sH8TMrywfxMyvHTbv4vI5OQkdhyfha2w2x67YMECPP7441QwuRTGcumkk04Kfb7wwgtxxRVX4K677kqtXJo9ezYA4NHf/977nxCSDzZt2oS999mn677J/k1IfmH/JiRf6DYWQqKDtWf2b0KGl+n27yJSq9WwFTbegV1QSYgiVIPC19etRa1Wo3LJpTDKpSC2beM73/kOtmzZgiVLlqT+nTG1nT17NubMmdOv4hFCpkG3JvHs34TkH/ZvQvJBL5VL3m/YvwkZWkbRZXVcWKiI1solSwugED5gg6NQyqWHHnoIS5YsweTkJGbNmoXvf//72G+//VoePzU1hampKe/zxo0bB1FMQsgAYP8mrWg3aeoV3Uy+umHY7icNRevfvX5GeXoWxH++eXgu/ZYHg7jHbvt3PxRihBDSCikAK0HsSIDKpQiFisr14he/GKtWrcLdd9+N9773vTj11FPxm9/8puXxy5cvx8TEhLfRn5uQ4YH9m5Dhhf2bkOGF/ZsQUgQqUrTdSJjCBPSO49hjj8Vee+2Fq666KnZ/3MrIokWLsH7dOprdEpIzNm7ciPkLFmDDhg2p+me/+vegrESKRp5WhAf9jAZ578NqpZSX/t0P8iQz8tRP+0me6rwV3TyLft5XP9tGv/r3MMv66ZJlHxBaQwtRqPrKirzIquk8q0779zCwceNGTExM4JzyHqgmuMVNaYUv1J8YqbppR6Hc4qIopUIvpyjVahXVanWAJSKEDAr2b0KGF/ZvQoYX9m9CSBGw2rjFWYMrSmEojHLpvPPOw4knnojddtsNmzZtwvXXX4/bbrsNP/vZz7IuWqbkRSOeBFc2SFZE+wfbYmfkob6G0ZJnWFfjB9Xf8hZ3Je56Wb2b466bh37cLUUY47SimzhNeX1WWbSrvPXzPJCX/mDKkVV58vTs8/JMouSpjoqMJQSshGdsIZ/PP0sKo1x65pln8I53vANPP/00JiYm8LKXvQw/+9nP8Dd/8zdZF21g5FWAFY1+1SMFef5JY8Yd3T9q/S7LdjyIuh70/WXRfvKiKBuE24Rxz0gqUxZtOu8KJyC/76yiyNy81l9a8lrPacvVSfmL/qwMoz4+MWTpkpeXOh+WNp13SkKgnPDMbSqXmihMQO+vfvWreOKJJzA1NYVnnnkGN91000gplgghhBBCCCGEENJ/jFtc0tYJy5cvxyte8QrMnj0b8+bNw8knn4zVq1eHjpmcnMTSpUux4447YtasWXjjG9+I9evX9/Cu+kthlEukeAitc6VZ10L0dcXBnL/f1yGDJU9teNgxMmO6dR48T3TrJ1EZMEg5MKh7DFIUOZcXuZzFM0oiL/USJQ91lCRD8lC+KHGyp902SgxrXeS1PQ6CPLxrs3DBHtXnnRWOAkkkbJ2d7/bbb8fSpUtx11134cYbb0S9Xsdxxx2HLVu2eMd84AMfwI9+9CN85zvfwe23346nnnoKb3jDG3p8Z/2jMG5xJN78n6Qji3rrJt4C6S2tXGY6eSaj1ufykgEmD2XohKwz95B05Kl9j5ps6RTznPpdT3loD2npti66ucWkSxWpztIwDOO1UZcpwXsf5HNMe63pPJsit8ui0+uA3j/96U9Dn6+55hrMmzcP999/P1796ldjw4YN+OpXv4rrr78er3nNawAAK1aswEte8hLcddddOPzwwzu84uCh5RIhhBBCCCGEEEKIS1kKVBK2spyeQnfDhg0AgB122AEAcP/996Ner+PYY4/1jtl3332x22674c4775zWtQYFLZcKxqivTHRLlvU2DCtiw0aaZ8J+RtLAdkJIf+mXBVOR3smpg1z38Ja0bm29NGxyr0htIcqwPYtekBcL1SDB8hThmRWhjIMgbba4jRs3hr6vVquoVquJ51ZK4eyzz8YrX/lKvPSlLwUArFu3DpVKBdttt13o2Pnz52PdunVd3MHgoeVSASmKv23RfdnJcBDXV9r1IbZbMii09jdCsqAI44l+MExjlCQZorTuamt33mGhqO1/mNpvP8hz/XQSt6mo7XNYSBvQe9GiRZiYmPC25cuXtz330qVL8fDDD+Ob3/xmn+9isNByiRBCCCGEEEIIIcQlbcylNWvWYM6cOd737ayWzjzzTNxwww244447sOuuu3rfL1iwALVaDS+88ELIemn9+vVYsGBBN7cwcGi5VGCKos3Oy8pB1hZfeakH0p6i9K1+kecVv7zRjVxpZa1UNCuBIvaTvJQ5L/0rL/WRxKAyvfbn5Kr9loJu5EzQAomEKWLWrWHJcDdoilBfRclKOYokZ4rzXebmzJkT2lopl7TWOPPMM/H9738ft9xyC/bcc8/Q/oMPPhjlchk333yz993q1avx5JNPYsmSJf270R5CyyVCCCGEEEIIIYQQl7JwAne3oqE6U1wuXboU119/PX74wx9i9uzZXhyliYkJjI+PY2JiAu985ztxzjnnYIcddsCcOXPwvve9D0uWLClEpjiAyqXCU5QAcXkKrpd1cO+81MMoEQwIy/pPD+srG0yVpxVTo/6cBpWyvlfkpZyj3GbiyKwfBa2XRLJDQb/GLxpA9KxKa8ictNVeUqR2nxdZMQwE67JIbYBkS1u3uA676BVXXAEAOProo0Pfr1ixAqeddhoA4Itf/CKklHjjG9+IqakpHH/88fj3f//3zi6UIVQuDRF5H2CP+gSIZA/bX+cw22E6Opn0mcPaVWlStibSOVm34by8m7OuhzyTubwziqYEJVOcrImTKUYx1Mo1Lvpt8HM+WmrvKUrbz4usGFY4HyFpaZstrsO+qlO0u7GxMVx++eW4/PLLOzp3XqByiRBCCCGEEEIIIcSl15ZLowCVS0NInl3lMl8VdMnaNc6UgZCi0Pd2q1VblxDSmqzkShYWs3m30s0zfO+kI/P3dBtXuVZ9QIjeJAWIc5MrMkVo95Rng4VuciQNZSlRlq3HpuUmG1BC5dKQk1dFUx5MUrOeoOShDgjplJ5PuoKTqGjmpIIpm/qhtKZr3HCQh/dvUd83Wb6rM1cyAYmK9zQyRwox7axxRZVDeW/zeZALgyTueeShDnLRz0kuEZaASAjoLXLQfvMGlUuEEEIIIYQQQgghLtISkAnKpWFMejBdqFwaIbJ0BYuDljuEFJeBrPSlCG5bZHrlwhKEcrWZrOsjT+/dIpO1O3tX7UjIZovMrgrQWhZG66WXcsVYPBVtApV1n2/HsMuETuo/6dhB11PeXeXyXr6hxJIQCW5xEHwOUahc6gNxwjAvQiBvbnJ5MEUt5ICV9JU89I2iMFAlE5B7RVM/XHhM1ea5WeZt8YL4DNM7JmsXuczrsoWSKVovvVAwFTXuUubPqAXDLB/7VedZ9/doObIi7v7zVL5hxipLWFbrcadls+6jULlECCGEEEIIIYQQ4iJksuUSFXvNULk0DTrRpDdl9MhBY+RKMyGkVwxsVb9AVkxp6IdrHMkHeXi/5mGs0Q+i9zWouu7KUtPIqV64x3kF6cxluBdBvYtA3tp7HmRAvxhkXechAU+wHHmDVkz9Q1oC0kqIuVRI+87+QuVSB/TUzSEngiovCqaszc3pGkcMeegPRaWrAc50Jl4JWZSyJsvMcZQp2ZMHOTJKbWDQyqbc9LGIDAzKHVMFeSjmIMjF8wiQBxnQL7Kq66znLEVQ4uRGNg0JwhIQCcolQeVSE1QuEUIIIYQQQgghhLhYFQnLslrvZ8ylJqhcSkE/teR50IJnvRJgyFrbnrXZLekdebEMHGUG6iaXU+slQkg2DMKSqWMZ16vMcU0FaW29FMRkfGvnHqe0Ob53ReyETsdieXvPD+sYMi/1zDlLe/IwtxwWhBAQCcJQqOzbYt6gcokQQgghhBBCCCHERVoSMiFbnNRc3IwyssqltJYNg9SOZ6kFz4vVzqhanIzqfeeJrNt+HNNpD3m4n4G164JbLw1LbJS8rChnTdZ1wPdIM8E6yXv8TJFg3aS7kHOtkgaYWihya8lTW8+63/eLPNWxIS/vmiJYCOXZwqoItI25pLNvh3mjMKPx5cuX4xWveAVmz56NefPm4eSTT8bq1aunfd444aSF8LZBk9V1DRRArAOSHULr0NaLc+WBVDJtusohrTp2OQnK+ujWC/JS/2R0YJtrTz9kY2qZMU05J7SKVz5F5B/bwWDJg6Kj1+RpDBFH3sqX5zaQ57LlHaNcStpImMIol26//XYsXboUd911F2688UbU63Ucd9xx2LJlS9ZFI4QQQgghhBBCyJAgKxashE1WWgf7HlUK4xb305/+NPT5mmuuwbx583D//ffj1a9+9bTOnUeNbtYuclnXCc04ySDJur33s633yx2kU/IW4LtdXWRh7t7KfSWI1r4bXeJxdLX1GFRdDLMcGUbyIhu7wVgvNbnJtZB/QdkihYgN6q0K1nzy0t6L1nbakZd6LSJ5dpPrtGx5K39WSCEgEwJ6yyHr/72gMMqlKBs2bAAA7LDDDi2PmZqawtTUlPd548aNfS9XL8lawWTKQAYHlWrpSdO/09TnKLmh9kpxHBu/I08Kjx7HYJpOuSlLu6Po7+9RJqmt5/X91ot+msX7W2jVUsGUZ9kznf6dhzaUxzqdDnmo027Jw4J4HHkez+e5bHlDWBIiIaC3UIVxAhsYhawRpRTOPvtsvPKVr8RLX/rSlsctX74cExMT3rZo0aIBlpIQ0k/YvwkZXti/CRle2L8JIUVAWqLtRsIUUrm0dOlSPPzww/jmN7+ZeNx5552HDRs2eNuaNWsGVMLeMcoBvkf1vkk6ity/8xaIMg1a+1u7/W1duwbRt7sI8N32lANI9pDDBdhMKFr/zvp9lfW7Om3fyHpM045eJVRIvojsqWVlUna56aC0k0muHzVRtP4dJM/tt1Oylh3DzjC1lVFFunGVkjYSpnBucWeeeSZuuOEG3HHHHdh1110Tj61Wq6hWqwMqWX/J2kWOApLkjV7070G36zwM4rrpz90UO/ibuMvFyjQhExVCrSZR3aTnni6dyuRO6t0cloPmkhlp+/eom/dnde/TlZ1FeG5dycqM7qspBlPANdjcR57kSjfv76zby7CMg7Oux36Q53lKXuMfFkEG5wFpIdE6SfZHt19oCqNc0lrjfe97H77//e/jtttuw5577pl1kQghhBBCCCGEEDJkCCkgEgJ6J+0bVQqjXFq6dCmuv/56/PCHP8Ts2bOxbt06AMDExATGx8czLt1gGEUtM++Z9IMsVrhG+ZmmzXDWinZuH8H9abMn9YJ+99W47HE5XZwdKN3232GTrUW1WgqeJ+/PI89BseOIDfAdQ6uMcXkjLxYpeShDt+S9j/WKvPfVPMq7vFpV5QkpJWRCQG9pFzLCUF8pjHLpiiuuAAAcffTRoe9XrFiB0047bfAFIoQQQgghhBBCyNDRLq6SBP3iohRGuaSpVQWQpT9/vlcE+kFeVsxI8SnyqlCvih5nvZRGnnUarDbtyn2v6GTlrxuZUjQRNIrviiwYtEzp1/PM42p+HINq123lXXR/kqwzxwrJ8cwIUoR+1Q/Y1kkvEVJCyNZyNmnfqFIY5RLx6diMMWmw0uEkLAuhTbNNQoaDuCDfXfXvoEyLkWFNCqaUrnFJRWgn9vI6Sc5ruUh3ZPEsOVHzyUx52mocF1AgGQatYO83WcuvIrX/rOuKJJPX93Fey5UHpNXGLS5h36hC5RIhhBBCCCGEEEKIwZIQSQokKpeaoHKpwKTSNKc1sR6iVS5CgmS5IjMKK0Fpg8LKyOpvmiDfTS4icfKshZtIU2ruNrQVpe7+pDKnc/OjyT7pjmG1WiqidfJA+3Ea1+DIWG661ktaa4gRl1NFkdNF6jeDIs/vWVoJFQshk5VLdItrhsqlHJMmS1CikOokVkkbN5NQOXIstAlpx6Da7rAPHjrNNBQ8Pqpoaks3siw6yUpQpHfkkRfj2hfan2KizLhE2VHUgf2wxFhqd80iPZtgWXPTl+NcgCPfxWWhDB0es1NpDWvA95hlW8jN80wg730lbR326z5y2T+7hGOG7JDlEmS53Hq/ync/zAIqlwghhBBCCCGEEEJcRBu3uESXuRGFyqWMiGrqjTY6eTXJ/W1MxqW4c3ZNyuC3g6Zoq5rToYhuAmT4aNX8OrVaivu9FCLkGuf1byN7WgawTXFtISKZkjpzEYm7vzhrqzSufUnQCnR46Nez5DugGPStL7eTg7Hmk52P4eIW3/V0BRzpOXmXB930geBv+mnFxHdtMqM0x+oEKSVkgutb0r5RhcqlAdNJx23lRpIm9se0YSwmADRFLSpZP7c8v6D7llK8g2MFwgomIEGeBSdX5uB2GTBDWqv0E60kpZnZFxc7CohX+qdpBxz0klZkJUeybI9FnuAMpNzRayTET+g87px/LqUBKXylk0URlRlF6Q+9kBv97P9815JuoOVS51C5RAghhBBCCCGEEOIiSyXIcmt1ibQ7iAk6IlC5lCVaQaiG82+pCq1br5zHWTF1Y7HclH0JbVa1Wqz6Z20ZQkheKcoqYy9pdcdBVwsZEBUaYeslwF2Ab7VqGfwuIMNi5Zl/RfcgETpWA55MC542KnujpRAxx0UtSrsVh5Snw0EvA8iOotVStAyjJktD8qwpU2bKujCCKGbsllbOjHp82jz0AUNR+kAv66zf1kvmGkWE1leDh5ZLnUPl0oAJCgUNC3Xz8rd1aPLVCjMhA9A6Zkmr37ZwJQl+P53UtcMIhfjwwZdzetplFYqSNCmJ7jPyrpW7WSxaJU/A4CuBwkqmZNc4U4akWzX7gqUMKsdif9PhILkfbbMok5Nho9NnyefUTJFd5HpKrMI9IvuC8i1O0x1RNimtPZmmtOMSF5XRSmfjDjeqysUgo3zvJBmOYQcLlUudwxohhBBCCCGEEEIIcZGWbLt1yh133IGTTjoJO++8M4QQ+MEPfhDar7XGxz/+cSxcuBDj4+M49thj8fvf/75Hd9R/qFzKECGAshQou0v4SidvQHhl3Vtt18nWBSK62p9UprjjUv6WkFFGaJ371cZ+rHYFV79D32uduBm5pt1zKK0dWSZEy3IKrRx5lLSphmfh5B+v/f1t7sPcS5IM1gjetw7J4uli2lHe21Irkp7fqBF8lu22rMnrczPlymv5ovSkrHFJDIL7Wo3TmlzpVLO1Z8wpm06FzhI0DBtZ9se8yIO0FKVfRilSHQ+Soj7PfiLLFmS5lLBZHZ9zy5YtePnLX47LL788dv/nPvc5fPnLX8aVV16Ju+++GzNnzsTxxx+PycnJ6d7OQKBbHCGEEEIIIYQQQohLP9ziTjzxRJx44omx+7TWuOSSS/Cxj30Mr3/96wEAX//61zF//nz84Ac/wFve8paOrzdoaLmUMUIEYiZ1uNIPJKfO7rpMtFQiQwJXpxwGvRplUlonWWLaqlmuheRZKIZIYFXeWCe5FkqwG+EtYskkIiv6SfItZKEUkb/R+wH6v7rP9puOTts3V2bDFKk+opZMeVppj5ajp+WKkWPBrem4DmSHkcO+FWlgrBmQf6R/FM1iqd8Mol9nVd+9uC7byuAQQkLIhK3HsYoff/xxrFu3Dscee6z33cTEBA477DDceeedPb1Wv6DlUk4ITl5aId2pjHJDykoRDi4LNAfAbJpItZpYNWUVcTMrme/N7zIM+D1KwnSU7pX0l2lnrUoR1DuokAl9jjnGIIXzXVCuycC1vFJHM8VpBShHHkUVR84x0pFb0mSLkxCyBK3N52CZ/EDeJqhtK8w+IXw3ZinCin6TZME5ruWpOoLBO9tT9AxAZPpEn/2g36Gt2l7XQck7yJAZ/T5tYpa4AN7OpX2ZHAzoPZ2MmEWjl5kf016HEJI/hGVBWq1d34S7b+PGjaHvq9UqqtVqx9dbt24dAGD+/Pmh7+fPn+/tyzu0XCKEEEIIIYQQQghxkZVS2w0AFi1ahImJCW9bvnx5xiXPDlouDYg0qxPGDDlpv7OyH17p91J5QySvKiW5uwX3ZWidlCe4Ck7SksfVx1623zTWS03XR/NKeBBbO1ZAZo/QjoAz3wgpHKsj2P6qvGu1JFTDnNhzffNX623HTFk7q0naKkXc6gSgFTT8lahWqbjjMJZWQghPJvvncayX2pKURjyGbixz8tgmSf7I6j2Xpn1Op2xZWzIFMWVpKoOQ8UG4Yz43ub4lIGDGkkauqCYZE7UqNS5w7tHOr7WG0qLp+FGjH9ajlM/5oMhWr0Uue5Ew7m9J+wFgzZo1mDNnjvd9N1ZLALBgwQIAwPr167Fw4ULv+/Xr1+PAAw/s6pyDhsqlPtLJy8OPOdL6GM+NpFM50jRYiQ5wWp8wPGkjZDjgS9mhnYwK1o8fGw6QQjTFewsqZ6JuZgrxyikBHXAjCws4qYOucb5ySagGoGznNybuEgLHCgkI6Sut3PIYv/igUskcE4w5EvxNc3l9GS2hPQUT0Oym3NKFpF1GzgR5Sxc50ksG3ZY6nVD3sr137Z6W4rz9LkNsTKWWBzsKK4H27nFGPntxlrzvnb9KxMvBUaRXbnJUKo02/Xj+HBf0l7QBvefMmRNSLnXLnnvuiQULFuDmm2/2lEkbN27E3Xffjfe+973TPv8goHKpT3QqQNLE/PAtlZzPErrJJ779hWLOH50F6eZVrlb7BiHUsngZU1APD6M2mEvTdtPWSZwSzvxruf9oDVgibHnpWyxFPkfPH/hfCkfBFJJnQgLSghbuCpAqAbLkTa50IP5SCCl9OSUktCwB0vLP6e4zl7KkgIjIX1vHx4kymHhRoteyIkn+ggNJMn2yaD/dyuFeK5imU5ZW5+s5seM0Ff83jqZYmVbbhUIncLfzv5F7HY0te0je39ndLk7l/b4IMfRLGV9EhBTJyqWOLT6AzZs349FHH/U+P/7441i1ahV22GEH7Lbbbjj77LPx6U9/Gvvssw/23HNPnH/++dh5551x8sknd3MLA4fKpT7QbYcMTmzihg1Sa0/BFPpd+gu035ezSQsVS4Skp19tN9oP01wnzpIpuA9ASDGjAVjQsD2Vj/Zd44ylklm1txvhz6EscwJeUG8AsEoQquF/DurR3b9Rt7i48kbd4Mwx0YDknptyXB2lzcTZJoFCuwl3VoNCys78M8hn1Kt2OEyWpqknbUF3uCTXOaNcl7J5n6dk0ohmfwlmvTRWS1E3Zq1F6JislE15pRNrJk7U8w0XbUgr0rrFdcJ9992HY445xvt8zjnnAABOPfVUXHPNNfjIRz6CLVu24F3vehdeeOEFHHnkkfjpT3+KsbGxzm8gA6hcygneC9z9HPceUsJRMBkFULuXfeygBEiO92HOH5jcjIprHF8sZBToVRpczwqgRTymqCWT1rpZaR4cnGsAUsBCwkTSlWmem4iyw5/NYUJCuJZKGgAs39oJuvm8WusmS6VoeWUg1h3QhXtyjxmmCXcW9NqKJc8UyVJpEPRiVX7gdRqJO2fwMvuGhFVkX2T8FufSrCNuzO6BKGUt6ApCK+VEnvsBGSz9bAtUjvUPUapAlCoJ+1MuGgY4+uijEz2VhBD45Cc/iU9+8pMdnzsPULnUQ6YjOFpNboIr+xKOgkkEYnzouMAeSTGWWimbRkB5lESehDIHI8VjqEyI01jXCJmo3PAmKYGV8GDcpdjYchKhmEuOm1rTgrszsYrGXAoq0oWEiMZcktILAq5NEF1hhVfuYyZXwUdqwxG1QSVT1E2555afKWRz9DkMTTsk0ybPwbqzpluZ3Ys67bivBuWbiijTozHnzFfS3+f8bU6l7Sn/EY65ZAcCyfkToPyMkfJKEdo9IWnJ07woU6T0LUNb7SchClUjd9xxB0466STsvPPOEELgBz/4QdZFIoQQQgghhBBCyBAhLKvtRsIUSrm0ZcsWvPzlL8fll1+edVF6jlk5csyTNWx3pd92//eyGQWOaTpHu1WTJIuEdhlIWv2sj5ptrgIRkp6e9MUYGSBctzMRdD8LWAsJrWMNdoK9VwGwlbMibivtybXQpvwg2n4MJB1x21WBOEsKUA0IuwbRqEHYDWdr1Pzv7RqgbAi7kSjjNHzrKmNhZSu/LH6ZEDhGN1lgJWX7TKrTUN02FS6dXBZaj7zMzMoSJW9oIYbyvnrdvk09pa2rTutU6/AWS8u4agFZF/k+ZK1pTq7ssJuwilh0Rl2HXfkVHFca+azhyOKovCOEdM6g3s0cA/QJabXfSIhCucWdeOKJOPHEE7MuRiwdd+imF304xofWjrLIBIW14QS7VRDeRE64LiPGTS42/pLWoWvFTWCa4inFudoNMcM4CCekI+ImMC1oFcdDCgE7JpaH8zcs3+w4LYwMix6pRYwjh1NW4+LmBPcOx13SxmXP8rPDea5wgXtVASW9cQmxg94m0ZhLcF3h3M8mBp6RHyYG3nSGdqMS3y5vDJNba5bvsyLXYTtXtdQKqIQq6HpoFc2KmRjqwEgqONk04cqViDQNuQFrV5nk7jNy0FnY5PiIEDK6iFIJolRO2N8YYGmKAUexg6bF6rl5uQdX9p3VI9eKyY3J5AdeTLGS1GrCGClDnP8+yYYiD85HnWGxFmhSLDWtlPtBtYX3f3y7NavevvImvDIe3BpKuzIwbDXUVKdGYa6VY6mknA3u5lks2bazefuVF6+kKQB4IKCtsRy1PTnrWjJpVx6be9CBewvElvLuPVonwexPndR/8BnkmKK3/WHov0Uvfx4IWjN1bNmU4vUd0gu1Om9cTKWI1aaReyL4vyfrbF8h5VkwxVi7w7dK8qxHVXDcGZZveaDTZ5IFRSgjCTNMz4rziB4j2lgtieJbLv385z/H29/+dixZsgRr164FAHzjG9/AL37xi67OVyjLpU6ZmprC1NSU93njxo0ZlgaJk4OgAgloHgc4cs8J8B20VIqKEMcsMjwwCSmV4sqTw5XyQQjHYXqZjCK5699FpZ27LBAvkAKBZLWQjoxq0W095Y372VaAgg6t5GstAKk9+WYUTVqKwEERVw/lKI90o+4F+QYAUSr74WeFgJYlP6C3+1spREgBFBfQNng7AoCEgApYjkoAOim7XYR2iqXocaNsxZTUv/uZKa+IgdHz8C4bVH3lNStSJ7dvjk19Gyos80LucjHjOiFL0Fr6ciSqTDdbRNbWXblnLFCFSRoDQPXYgqmb93cen3uQ2OQWBZQnpHfwuQ8B7VzfCu4W973vfQ+nnHIK3va2t2HlypWeXN6wYQM+85nP4Mc//nHH5xzqkevy5csxMTHhbYsWLcq6SC2xzap9XCySwEq6s2Ku49N6RzFCLToQiU7Q2sX8COJOdrgqQ7Imr/27yP0i1roxKkeCcT6C++C66brnUpFDVHRl3P2/YTub/52xDnImQHGx5IJxinSjDjRq0PXAVpsE7Dpg1yHsuhd7yVvRj8g6b/U+almlAps2biLGkkl7Cqng2VKt9LewBiM+WfdvvuPSwwlUPMpdNAxuQbSxzBSyeZEvYiVqBI+nWDKWmjGbZ62ZIGeCVknRsWat4WyOXPZd5trG9eyArPt3r2knKyhLCCkmQsq2W5H59Kc/jSuvvBJXX301ymXf/e+Vr3wlHnjgga7OWewaacN5552HDRs2eNuaNWuyLlJLjFuImWjVlUZd6cjkxpn0+KbM4SDgHtFBScz3LVe9pkFwvpn3sWbeXvQMxNc5Sf0764lh3tpXR4Rkhg7JkqhrRnif335F5P4V3MkJNBR0yPXCbJ7Mi7igacCffAnpB6tV7gSrUYOemoSuBbbAZ6gGYNt+2e1Gk4DSgQmUBmLL5wcd1wElU8TyKU0XTmMpZuqxAAqnfvW1bt/f/Qr6nFfyXLZRIG68E6dIiu6L29/SUjEqc1XDS2AA2wYadX+z7YCbsKtQV/GLhyG5puAplaZsG1O27VnU91KpZCjS+Lwd/QoIT0i3cD7RQ0ploFRJ2FrHYyoCq1evxqtf/eqm7ycmJvDCCy90dc6hdourVquoVqtZFyMVwYkL4K/yW9L5bEkBKCeYrHDdMKzIi0oKAeiAa0icIkkpwGhZtXImbMFBR5duGL2SYxSIJC1F6t/9pBcD1uY4SxGLpKirbehQJ4AstIJ0fc9trSFF8Bh3hdx4dsC3TjJYEoAEGu53lgBsKdy4S45cEsETAtCNOnS97vxt1PzrSctfOZGW4ybiusUJrZrcRBzFkF8eY5UUFEdCAFpoeH5x0nFT9qoKOt7PJViHSW6GweOTJpkj4iqXt/5N95ZmWBfNNFknxRzjW3dqSPhuvyLuYBWRwW6sOeMG3JRRTkhorSBK8GWFsppd41wFOQBXua8wZTvnnHSFcFkqzChLt6zJ990peevf3dDNu5dyJF8w4zVph7AsCKu161vSviKwYMECPProo9hjjz1C3//iF7/A4sWLuzpnoZRLmzdvxqOPPup9fvzxx7Fq1SrssMMO2G233TIsWfeYAYPj765Qd4Mu1d0BhXQnMmUpUSkBUgOWOzTxBwcxAW8BX7Fk+5HshVbhxXGJ0GTFySqCUICy6GpaVBgXTX5y9YgMgrxmoEosV0zg16bJS9S6RjWcmEZaQbi+5zJOxxJQ1thKo25rT84BjqwrSwlZcjNkSt9FDqUYlxEAUDZ0o+Zs9br3HaTluapJaUFUxvyYS27MEhGJWee4wrkxR5QfE8q7T8CLC+XUi/CUZkAHmeLi6r7jICwkCcZk6j+jfv9AvMVSaH+r37l/Y1unkHDyA0cuZJTUrkWSlzHTrkMH5KjjpmH5Fp8AoCshS3YF6SRYCMi7yYbC1rqzP6hcMsc4VpqUTwaOI0ne6ed7cKSQ0jfKaLW/wJxxxhk466yz8LWvfQ1CCDz11FO488478aEPfQjnn39+V+cslHLpvvvuwzHHHON9PueccwAAp556Kq655pqMSuUw3YlkQ2lMNhSm3Je6eaEb6yRlaQAWZElAmcWomPM0BXq0G00BvUNWBwpNCqZYWuxPuuVO50ujOlgd1fseBQo7EY1a28S51wZlglaAbi0DldaeSxwAT7FUt3VI1ilLOxZMACwlYUvhuKsZIWIsmEygWmU7VktTk07sJcBTLnlFk5bjHlcaC5c/eLtah9zabO0ov4KTRSkEyhY8yyUhtKPsdw9REIiuX4XqI6i4i1qKeZNAHQqWbtwA8xrYO+tBa5bBnfOqPB4EWd93XoN6G6K108rqR4qA9RIAEbUkR4wMNm5vtiPvHOtN32oTlhN8VlTgyxVZg9bVgFxxXYHdj3XljD231h2l1ta67cg7KdCwHZeP/DvoEtIZeZYhJEcMeUDvZcuWQSmFv/7rv8bWrVvx6le/GtVqFR/60Ifwvve9r6tzFkq5dPTRR4djCw0RW+s2ttbtgHLJ+d5yZV9VS+dlr0Ugo5wIvfCdbE3KX9EyK1Uqugpmez9wEjzJ0GQmCSOMi/gY+CIZXaJKnkG3haJNRJsCexuX2iABUSFUw1GAeAps2bTGHbJc0o4yPajAkULA1sJx74XjClwJxDdyThyxoqw7cUZ0o+4okIBm5ZJlQU9NQlZrflndGFFh9z5fqT/VUKgr1eS2p7RE1bWiEkrAEv6kK/p4pZs+z69L3TRx9C+eTv62Iq49F6m9FZXCKo+nwSjdaxLtrJac76K/ca0ezaKh9hVMACCkMyaLygERGdfB9uWdnpqEduMqAYCWEqJUca/jJmBRZQi7EVJ6OUlknG8mXcXS5innGkbJVJYiYLmU0jKzD+Rt7NaL8hRtTECKS96V8XlHWGWIhLhKwip2zCUhBD760Y/iwx/+MB599FFs3rwZ++23H2bNmtX1OQulXMo70xlobq3b2FyzPXNkM9gou/4lRqFUlhIl9zslHTNlEbxu0Hza+OVH4qb4q+DSMWNSCp65QJr77MP7cFRfsqN634MiTwO4LMrSKrRPoqyKs1KKCwhrB+SJVXImP8YtTlqQQjdZLRq5VreNW1zQOkhDaeFZa5alRMUKx6KzPAufgFucmx1OT21zv1MhM2UtJXRlzFvpdwJ8u5mUXPWSgh8HCnAmW1O28j4DQNkSsIMKtbL0Mso55W0RbylQb60CdOvQfclCuMdxsOrTk74d1zZ6ZLHWqmidPMK8yNFe0E8v1GgtRRdElQZk4CgF4bkRa+3IAtHkFucr94VqeEkLAEDVJh0Fux2It1kuQwaU7MKqQJftwI07Mq/uyretdRubas4GABsn67CkQLVkeQuevY65VEQo84YHxloiaRHS8kI+tNo/DFQqFey33349OReVS4MkxuTZsLWusHmqgUl3pqLcN3nZVfrY2rFimirZGHNXzpvEl1ndMjGWjF9+0ApB+BYFGgC0aB7ABj5rN0NTK4uloNVB0+3m6D2cx0EBX0CDIfjss1Y2DdLSoVVon8SuEHXbMsFj4wJ+m3sBoO2GIzdMkFmr7Cq9A5OoiBtGXWlMNWxPcQ44AbyNLClbNsZsCbvkK30cWRSQTyYbUqPmr+R78er8lXwvcxwAUW34meMCjmxBN5HNtQYmGyok38pKYqzk6+HLSkBL4d1hNFucEIBQvitcSBZH8GRyF8qEVrJtVKxqku5vkCu2XcuWdtkDp6lg6qXretGJ1kU0YH+vMHLAKJaCckHDXywUcBRNJkWCgIYUEeVyQJEOALo+BV2vQ01ucT5PmayYrnJJWkCjDKUUpFH2l6tN8seRd0a5pLC51sDzWx3rzg1bHUV8pSQ9KyY7IzmSF6vMPI4hCUkLrZemgZRt3OLyGbYgLcccc0xThucgt9xyS8fnpHKpDyQO6puCYzufF28/joYa8wJ6e5ZLlu8iUpYCFUug4i5zVSzns7diruEE1i07sUW0VXIyhATdWYKdwCiOZMkvlxDhCVxAsWR2B28rTqnUCQOZZOdMoA77ZC/v5KE9DGLin+Y2tRAQgXV0IQFo4fd/WQJkA2jUAm4ZrnWk9yMNIRS0ks7xAISyIYVE9JWrApOtuu0omIIyrxGw/ilbAjPKCg3luwI3m0IpL2OcPelMjFS9ARG0xJQSojLmrfTLGXXPotNkt5Puqc3PdppRQbUkvctJCFjunM/IW0sIlKSAm0zJ+d/yLa+cwZyEEEbJlfC6Dd5XVLkf+c7fl64d90Ohmoc+lEe66td9jqfVi0c1LO+sXjZbzwrUrRozFlJae+EMIBzls5mWJMVeMmghHDlqxIWQ0KUKRMnJrCbGZgOzarDcRURh15ssJL1xnevKoUpjUNWZXluzBDBeEsCYc5GKJbFwVhWbt3fOaSzoJ8ZK2HHcOcd4qdnVeVSgvBseRvlZMsB3lwx5QO8DDzww9Ller2PVqlV4+OGHceqpp3Z1TiqX+kgnA80trkvclB1exTQTmRllCyg7kx0vyLd7jBfr1m64lks173OzxUFAceQG8o4NGBtVghXUFS5PQnRYBuikd0xXydSufXftDhPKTOQmBWhlgeMqo4XdcBRRAKDLXrwPwJl4ae3H+DCKpamG8iYyAGBbfsHKlsSMssJ4WfqWSyUZsgA1Ab1VbdJTLtlu1jhtm4xHjuWSci2XpGr4GZesSuzt21pja932ZK0TzNsojsxs0gnmbawOYi1Jk4J4B+qvUxOSLINYk/ZkbSHZS/J6H0WYKGlErJZaJTyAkTPGKDRmsmJ+qxoQjTqEO87T9SnHctNkywQchXp1HEKPO8cICdEoQ5ukBgi7xdVshQ1TdWyYdOT3NtdaSWmN2ZVSoOz5rWtC2pFnWTFIiiA784SwLAgrwS0uYV8R+OIXvxj7/b/+679i8+bNXZ2TyqUBkGYCuanWwNa6wlTD95t3JjTGLU4DKEHCgi1NgMWIYNDaGXgE3OKasxJpfyUdJUCosLuesMJuJ0KEJqhxQStNWUk8eR2ck/zQD0umtO4wxnrJ2RGjAFHKd7k1xwRXyoWEMNaOypc9slQOmNqGLTJtDTRsR7E06co8W2lUStJzCS5ZElMNCw3bdyNxrCwDssZ1iVO1BhqTUwCAhqtkMsolYUmIyhaIGa7bXG0SGHcUZsZiIGoSrLRvUQUYtzjhuiQ7dSUB2MLPFmcI3XKgnkSkzhA4LJQtDsmuUN0MCHuh7OBAtDOGScFE0mHkW9BVFmh2jwu2CuEc4HyQAgLaCewdlAHKl79CNSDsGvTUVudc27Y41puNQMY4aUE26r6bspCAVQnFfLOVk6UYADZN2dgw2cDzk3X3cwOWFJBSoK5MkpliT6C6gTJveBjUsyySzKerXEpKFWdrub/eel+Befvb345DDz0UF198cce/pXJpgCQNNjfXotniNCwhvMxEQAmWsFEtSSjtZxoBAsJMKyfekhlQGAuD4ITGmEvDmezouLTiMbRSKgX3d6Jg6rcAzovALNKLhmRPL5RMabIYmb4aG4NJBzOcBTJOerE/XEumgLuttkrOBMZ2JyBWAxIa0RjXXswlW2HSdhRL29wgsrWGQqUkYVecc5QtJ96HE5/JkU8KAqEpjlLQtg17suYplewY5ZI1VoEMZFfyLLIi9eaXzwk2biymLCk8uWvempZ0AnoH5XEo5pJrtdSUeS9CKDJVH12kptO28iJPu6FQA+g+BPWO9c5PUR18d7UnTRVprZuUSlH3OD+gd3xbDSmmG3Un7tI2J+aSmtzixF1qmIQFNkSpDNWoe27JsjIG3RRzSaNmm5hLNjZONfCXLeGYS2UZiLmkSplliyP5pChytSjlzAJaMbVHSAmR4PqWtK/I3HnnnRgbG2t/YAxULg2YVgP8rXVn5Si6il8PpCcqS4GphkK1FLVY8l1YQilr3cFEKEucLHn7tRBuZqXW5dQ6PDmNDi46FUej4ArHQTmZLmmsHuLaeRrFUvD7tgphd1LjKJNMjA9fgW0QWoctcIzsMYFqRfi6JtbStpqNza4rRq2hYEnhKXQqrnJpsqG8FXZba5QCMeK0bQONOuxAzKX6FkeJZJVdJbolUZ45DssEwK1NQjScOCXR+w+WLxjQG3Y41hIAlCWgZNDVJUYuByeFLZRLwV86ddhfC4G0FjVZy9G05NlCqCOFXiu3yRhrt9TXb3HZfgWyzoK8KQ+DrnBGsRRUKsW5xqmA7BA68ty8jJ2+5ZKa2ua5+eptW6AmtwINo1S3IcoVR8a5kx5RHYOozvTakoZjDWoWMzfXGthUa+C5zc45jJJp1lgJW+tukplp1Up3ZBnMO09tinQHnyHpCcJKDujd5zFbv3nDG94Q+qy1xtNPP4377rsP559/flfnpHIpI6ID4s1TDWycrHur+Ea5VKuY1N4CVUtiRtnCTOV81+QDbywMAoMQBLMVCeUMckxg2XaxQILlTfg+T+I765dJXic5pHhMd9KcRimstIb0VEDBixsrJVd+BJTUTVkoAUem2MKLuaTd+G+WDJsSm5hLSmvUlcK2mo1NRrlkK1gioFwqScyqlLC1bsNWTlBZW+mm4ImqUY9YLk3BrjVQGneuLSyJ+pZtKM/x3eKE6z4c8rDT8F1AlPbiQgFwA/RKTDZ8hVS15FoumZhLrjwOPjMRVS4Za6/gLUSVBsY1Dq5VUx+smdq1razlaC/J/b2keP96x/U5+HfHJJV9gGXNg4Ipybo7pGwKfG8sR6WRixCeQio0XQlaQNp1x3rJs1za6iiYXGUTAIjaJKSyod2A3npsJoQdDpNga+3Fu9taV3hucw3PbHJci/+yeQqWFNhxZsU7hkMbMkimZb2dkSwo8vg/DzI0t7iJrhL3F5iJiYnQZyklXvziF+OTn/wkjjvuuK7OSeVShgQH+FvqNjZsrWNrQLlULcnQRGtG2UJdKX+C5p6nye3CG4REYy5J3xXOPV5olWjqrIxFQtJ9wJkEpbaG6AN5EIpFfrGQfBKnBGiZer6VlULCd+16jQiumtsBd1u7Dh1wixPSds5lVsrtCrSyPT22eS2bSZaxWtpWs73gsdtqjpLJ1s6EqLJVYs5YGVMNX8lja4Rf8sqGthXsWgO2G3OpvmUSds2GqrtKdilR2jIGe5sTo8Sa2uZM0JTdVLeeW5zSmLKVF/+pAT/uk8ngWbc1KpZoPelylXJBRZ1nRWqqTsqwjB7ghDwPMrNXDCL7YpHopBpiXWNT/bCNUiyPyrA+Y6yWgjGWgo9CwViDh39kPG4taN/9NnRi5clfk8BAByyX7G1bQ+7AslJyBvdunBBRm0TJLDa62ApeApmtdRsvbK3jL5sdGfrCpikIIfCXWVUvDqgdcO8jpJ/vj34lOCGkG7QsJWb7TcwEXABWrFjR83MWu0YIIYQQQgghhBBCeokbrzhxPwlB5VIL0loL9IrNkw1smmxg85S7eu+6xTUClkuzKyXUbe17s5kVMM/HRXnuHkCLlOHuXwBhK6YgQsbEbokvdzRgbxLDuqo8rPdFuqddk+hEnHQqe+Lc4VoGkI1cw7tSQC4I18LRi+Vm153sRPVAdiLLci2X3DhHynGLM+cz2diMJabSGrWGwtaajc1uhqKg1SbgxFzaOFnH1hll1GzfXS1quaTqDdiTNS/WUm1LHapmw66bgN5bUZ457q/sm1X/gFWRSQHuxVyylRvU26+Hsnbc40wcvLpSsJX0fqNa2YGp5mxxXowlBcesKyiTe5wpjgwRMdZAmbgz5NCVb9CBadO+9oOWTGbMFo27pAKx6TTczcgE74Ku1WO95gTwdi2XVG0SjS2TXrZMbSuISee35co257eNup+IwS2Tgu8Wt6XWwIZtdWxwYy5NbqlDSIHNk3UvLhOtlsgg+hatlkjuECJ50F7Atrf99ts3ZUluxXPPPdfx+alciiFOuPV7ALd50nm5b3InWsYtzjC7VsJkQ2HKnfQAgUlkcKCn/RhLjil1IEWiVQ7FTom6xwGARvECk2X5UqFiiURJl0HI+dvPpttKsRT8TgpHjljBgjTJEzdWkJERjbqbnSic+hoAhOXG+FBVQDnprM11gtRthVpDYVvdj7m0rWZDBzK0VUp1bDdZxta68iZBdQVoqxSasGpbwa430NjmyLr65hrsuoLlKqukJVDfsg31Lc5Eq1qbhK7XvQQI7g0A8GNC1ZWjWArJ2hIw1QCqJaOA0lDQ0K2USsFg6N5n76k49WWqWwSCNmuVKkBktJ0VcHwzMuQ56HjfmUZA8m4YtLItKdZSuLe730XiLgF+zCXdwiVOBMdojTrQcBRMANDYMon6lm1ezDltKwhLQlgSpRlOph89tS2UhEFr7bjFuS5vmycbeGFrDTVXFk9urUEIgRe21jFpM+bSMJFHJcx0ZWPW9zQssp1xl1ogZVOsz6b9BeOSSy7p6/mpXMoJmyYb2DRZ9zIn2UqjVpLe5GxTtYTJho267WcwagrSayYzQQuDYFwU1CGE9L+Tqu2IwcQQ8D5rHdJ2Kt2Z9dIwMSwvFJIdvVAyBZthdKITDCQbxPRhpU2wavc4IcOqEhM3SNmeolrXa9CNWij1tZaWo54xMT5KVSdgtjuhiWaLszXcmEsNL4lBfaoBpbQX56hSktg02cDWuu2tntvasVwKWvfYtTpUrY6GKzvrkw00tjVgVYzCS6KyZdKzbDKr/mHLTgkFP6aI0k42O5O902AJgbptFF0qFD9FexYJrRR1OnQ990rhSbex9PAaBlIzCIVl3ojNmDjsFdAHZU3XcZdySpaTJBOQO/hZe3LFj7sURHkxl9xjImIkmC1OK9uLuwQAjckpNCZraLjyTSkFq1yCXSl51ppWw7E2jQb0NrHsNk82sGFrHZNbfMsly5LYNtnwLZfaRt/sHVn34ayv32vydj+9Gjvn7b7IcDKMMZdOPfXUvp6/eDXSZ5KEXidm152m+t081cDmyQYm3dV3pTTssoWKa720re4EvzUr6kCMRYJZ3fKCxiovPS0A6FLF3d+5YA9OTqMKplGEiiXSS3o5uWsSCzFt1XwnhIifMkSsl4RWvjKpUXdcy+q+cgnSggIg3exEojrTDZjtup0hPBGuK4Up1y2u7roCT21rQCsN5VoLbShJbJhRx5Zaw7NcaigdSgmrlYJWCqruKJQAoL6ljsa2RsAtTqC+ZcqbaNlTUyg1apB2o0kWGqsp4xJXa4RtDMpSeBMypZ3jtPsWbek2ErRcin4nrLB7cg8UBnlSFAxaTnKy0Tt6HiR9wAG+B61gii7EAb4yyTsmkC0ziBVQ9jcpqAFfwQ/XcrRRhzIJEFzFkucWp5QT1Ltc8pIa6EY9ZLmktCPrjOJo01QD9akGalPOMVPb6rBKEvUp23NJjlWek1yTF3k4zOPlYb434jJCMZcmJydRq9VC382ZM6fj81C5lBO21RqYCrzctdLQCthc8l1Gag3HTcNkNGqSaVqH3FfQqEHb/oBCSNf6wGhZgy4vHXrDBSenANBuyNEvAZyXlych06UbpUAaq6Xo/0EknIu2NJQxCmvV8GIsOfGW6p7i2rGEdBVNFccNQ9g1xzLIs1xyBIzJuGYrjZqtsK1mo+EqgTzLJZN10nJifmyebHhZjWzlrhJF3eJqvjKpsa2B2pY6rHrQLa7uucXZk65LifKzaUYtq0xMqKhyqWJJNIzlkmtF2smKvufaYsqvdZOFQijuUosJOcezhLQnOO4YtKIpiGcRiXDfNf96kQziRlLBxULAiZ/UqHmKI7vWQGPSV54rW8GyFexyyVM4VZUdGgtqOLLUKO231WzUpmzUjGvxlg2wyxXUp2Y3yUCSf/IwLu630iUP9ziMDDp2XSEYcuXSli1bcO655+Lb3/42/vKXvzTtt2075lfJULk0ANJMGrfWbDRqCo26r1wCgEbdtVxy3UfqSoWCzGpzgeDFzAqXbYdSzzrfl0MxQFqJ/6Q4AqMMVylIP+nEtSmuKcZZLamYyUzw9FHXuCDCKJ+VL0t0o+York0qbKUgXJ9046oh3ACyocDgIuAWp1zlTc1GzbVcatQV7IbyLJcsy3GL21azsdWVi3XlWiMEKkjbEcsl1y3OrrmWF1KitqXuTb4ak1PQjXoojonBKL/qtvLKaMoLALWS8iyXjBWp1lagrv1yeXVnFPFxAb0BQAtfTlu9GaTkyXqJ5AdPcRvnTjjkbpVZuMoZl7ig9ajSOhQPTwbkoiVEUzwm50QqNK7T9bqnOLInHUWTH3NJQysFa6wKbayO6uGVaKURGktuqxnLJVcWT26GbFTQqNueDGRAb9KOURsfD/P9Mv6SjxZiqBOtfOQjH8Gtt96KK664Aqeccgouv/xyrF27FldddRU++9nPdnVOKpdcOhESvep0wWs6K/i+i4gzD9EolZ2Jy9aaE3ekbgfigkSnku7kxVvhUv6ABAC0LZ2McpFMUEl3HpfZZFQZ5hcJKS5p4iw1KZ0Cx8YqloJKae1MVkwAb12ve64ZzucaYLmmj27MJT21DWJmw4v/JiOWkY5VkA1lKzTcmEu1qQZUQ8F2s7GVyk7Mj02BuB+29gN+e8VTCnbNhu0qoBrbGtjSsGHZbjDxLTXUNtdQ3+JPxnRtMqT8imaLszWaLJfM53ogc52twlYJhLSi50G9p+FmlqRk6isDdo2LMghLpiQljNbN7nPBuJXKOy5s0SgCyiUo24l5Z+RQveFYbtbCC5OqXvesm5yxYFhCGetMwF3crNtobNsMAKhv2wyrOo5G3ZeBozL8KfpEsejlJ+lp9ax79Z7hnMdFWs2D2Oj+AvOjH/0IX//613H00Ufj9NNPx6te9Srsvffe2H333XHdddfhbW97W8fnpHJpAKSR9XbDsVpq1IwJtLFccide7sRGBSZXLft9cBASUC4JZYWUTcEU2e1ESHAwFA3gPQpBvSlkySBJsjzppCkqHVYsBbPEhY9zJ5tNFzOuswErSNdqyWQrghtgFgCE6xaHRh2wA25nkdMaq6BGXYXc4uyGguUql2plC/UpG5un/JhLttKOdVEgO4eyFey68iyXanUb22wNc+eVKRuNyQbqbsDvxjbX8ioY4DamPuxA5rqGsVxqKN+6yXXha/s8QtniwhM8AUBrGc7gGTzOxGTqYkKetSUKZWZ+aGWJrLQevIIpJ0TbZy8n5UGFczDuUvQ5eB+TLh1RCjnjOuUpjlTNUSIZt2CjdFK1BpSJoaDCbg3aTVhgFEe1hkKjpmDXXNdh92+jZjcp80lvGDb5OGz3k0Qe7jVJXo10dtJ+MORucc899xwWL14MwImv9NxzzwEAjjzySLz3ve/t6pxULuWERt1ZObLNwKChIKTwlEuNhkLNdrbgACWaVURo5SmUtIpxiwvEGQkR910LRkGZBOTjBUK6Yxj8xuMUTElNsp0FYtxnx2In2YfKyBTPcqlR9zLGAYCqNyAsCSkt35qpUYdUDcB2LZfKzrXMRMUEkzVKdQBo1Oqwp7ZBlR3rp1LZQn2qgW21hpe1bbKhHFeTSMwlbSvPcmmbrV3lksPmhsL4pO82p+oNP2aUF3NJNFVBMOCtKfd4KKGChh2IuWSsEkYdys3ekVax2Et5FxUHozJRibvHfrw/HGvw5u8AV4bEVbVSXswkE7DbKI6M5aZyLZeUrSEsCWUrL+i3u8ObBCk4VqBGudRoKNi2QsNTLjkLB7brHkwIcciDLEyVVGpE5PYg0JEMxXH7i8zixYvx+OOPY7fddsO+++6Lb3/72zj00EPxox/9CNttt11X56RyqUvaucYJ0aGFga1hN7TnIqK1hqjbsBtuIFzbsVzyVu7RPGH0Vr+DgRtDlkoSsG1fF6V1rFJJd1r4jOin4oBCmXRLL7tPu/PEucT5GYmaXTCigfibcF+SwbhsQCR+m6u09lbO6w0IW0LIQBymRg1QDe880esZqyA74BZnT22DXdvmyax6pYpG3cbWmh/3o2678i/yMrdrCrZr9VlTGttsX65VpOMq1zCWS5M1163EvyejLPeUXxHLJfPZyGAAbvBx/xmpmAl+NKZTk7wV0v0unVl13uMgUG72nqYg8HnAa7dd0MPMiP2mUze6TkMIKGjItNnXAvLXKNQBV7keyLKpbQVVs/3wCIiMA83pdEDe2QqqoaDcBQO7XoOQFnRABrayb2efJ4Mmz+/AfjPK954ZQoas5WP3F5jTTz8dDz74II466igsW7YMJ510Ei677DLU63V84Qtf6OqcVC6hfy/HTmSAUtp5uRvLJaUhhPAGDHZDwVbOxMabxMQVOzjgMzGXov6gMQONbtFat56oElIg+ukmkTXRSY+ngIJwXLMSf6zCK+eNOnQgW5GqOZZLwpIQdT8uU9BKMmrpaBQ1QZln17ahUdsG6U5wnJgf49hWs7GtZgJ6K9das9lyyUy2akqjFtCo1RRQn7K9mCReLJJG3YsJFcVTfgUDkENFFE4IyWMgosgTkWljK4vRNBP1Ak3ISWuMTBn0hNy4vsW5x42ya1wn9EKxa2o/qKhR0LDSKpjMeVRYuaRs7bvDKQ3hftZRlzrze42wLHMtl5Qrv1WjBtuyoJT2XIKHnUG97/vd9we9ADFKysUs77WbZ5rV+2boGHK3uA984APe/8ceeyweeeQR3H///dh7773xspe9rKtzUrmUE5T7crcbJqC3DSWrUGbVyPZX0tuaKZusToHYS85fq9l/nzRBQTw8TGeglVUa607ppLWa3p/6VRiKuRSM5aYCAWXrjuWSJWEFV9cDmdK86wc+G8slI/NUo+a4xbnBwUtT29CozQ5lLKrbOtY6QCkdslyqKe3da8VWqCntK5dqDcc1Ttle+eKebmjyFfjrZ08KK5Z6IjWU6uDhpIOZ44aYFgGyzfPu9lU2qq5xnRBnoSpamK22q7qw9WNnnVW5inUzVtS2BsrpfuvF73QTyJgxo2rUIEsVJnMhxKVoiiXSQ2TJ2ZL2F5g1a9Zg0aJF3ufdd98du++++7TOWWx12xChtPZe7lrZUPWab83UcAYOqRRLTSeOcXtT7opWxPWFEBJPpwOLQYwFWmWJUzrsEqe1o2iZTi/XRrmkbGjbhqo1YNfqsGt1Z2JTb0DVGo67mQmWbWIaaRUb0FsrxxVYNWpQjRoatW3O/3V3a9Rc5ZMKJzQwlkvupFqrsLKnpjTq7t/gZteVuzWcVX0T0FurljHkggp9O7KKb7tlsZWzAQikHnc/t1rRignuHdrn/V+cyR2VD12SsCoabD9NLpZZU/DV2m7oRRtv7+qcnHHOO49qbZnUDuca4TGlCow/nfPbXmIZUiyE1pTHPSLruuxJHD0qp6aFFsKLuxS/Fbt+99hjDxx11FG4+uqr8fzzz/fknIUbHVx++eXYY489MDY2hsMOOwz33HNP1kUihBBCCCGEEELIsGAWgJK2LsiLPuO+++7DoYceik9+8pNYuHAhTj75ZHz3u9/F1NRU1+cslHLpW9/6Fs455xxccMEFeOCBB/Dyl78cxx9/PJ555pmsizZttNKhlSPPgsldjdfuqrmJ8aHcLEVNZstxq5vKjZkSF2spb6uhhJCuSevG0JElkwpkKfJkSWAzbhm2HTgmOa6b7ck77VkqaduGatQ9SybVqKFRt6FsJ2vbVEOhboJouytGwg2yqG3tWhK51kQa3mfPTc7NqKRqNuyaExNKaOVZhEQD64aslJSfNc5snsuykcc9XNwMlos046wkFnu1sFM6yRpXCEaofQvhW7OG3A3TPK4WgWSF9OVfWlplPRp197dhibc06OsVSt50QdYWS71sl6P2vuwpRoAnbR2SJ33GQQcdhM9//vN48skn8ZOf/ARz587Fu971LsyfPx//9E//1NU5u1IuveY1r8EnPvGJpu+ff/55vOY1r+mqIGn4whe+gDPOOAOnn3469ttvP1x55ZWYMWMGvva1r/XtmoNCK0dRpG07kHI2PEFr6xIXHaz1KHA3LaMJ6dw8Oq/v8uAtpJ5UxLnXmkDaMYomZ7+dqCTRUVdgT6lUh2rUYTdqntI9qNRpV+aoksmk3Va22XwlmSFNUoJg3CU7oFgiDkUZvJp+nLW7Q1rapUHuhFaBu9O049jJzjRWbUeRaO0ndplg3Urpb0BIqSTdZArTKleLgohW/sIZ0Y/+WhS51S1FkHF5ZBjrbRQXZXqBlqW2W6fkUZ8hhMAxxxyDq6++GjfddBP23HNPXHvttV2dq6soVLfddhseeughrFy5Etdddx1mzpwJAKjVarj99tu7Kkg7arUa7r//fpx33nned1JKHHvssbjzzjtjfzM1NRUy69q4cWNfytZLwv7uvs97R77vPcwGR0heyap/5z0dfBKpx0uuQiikGAoG9LbbWB1EZJCZ1Nox1w/KPKVsb8XD+ezGZtIRZU7MhDZ4bmO55PzvKJq0l+jAzaRkh7PZCQFYbSZTQQV/9F60jliD5WTSXdCm2pf+HTdhyKI/DypAdov40qnwulpB20+/MM9NCwEhfItHI5uk8IP7aw30fDQmLS87JwAIS0JaAtKVXQqAtIRzTNCyKZo1OHpaKSDcY4S0vP9L7nmjlp3TpYjj86LSDxk3jMoXIB/31e/3EbPIdUjKbHFRGVatVlGtVpsO70afMQj+9Kc/4frrr8f111+Phx9+GEuWLMHll1/e1bm6Hv3edNNNWLduHQ4//HA88cQT3Z4mNX/+859h2zbmz58f+n7+/PlYt25d7G+WL1+OiYkJbwtGQy8qHQf0jtJDayZaNJEs6XX/7seqTpcWs4VCtVM0xdBoYfljrDbN/0bBHrIWCv5AWi1dQ4zlkvnft1zy03YnBdYupVy1N5ZShmgWOY/g4GSaFh/D3qaA4Xx/J9Jte+jQvSzOeqmVRVNqcqJIzZo4kRH7HUSiskYj8D4yLsCW5WxSesolb5PC+19KAWGFzy1iFEtSCFjS2RxxJDylkpAWrHKlrUXndCanWffvQVtxZD2R76W1Ztb30i/ycF9FXbgcZoysSNoAYNGiRSGZtnz58tjzdaPP6CdXXXUVjjrqKOyxxx74+te/jn/4h3/AY489hp///Od4z3ve09U5ux4RLFy4ELfffjsOOOAAvOIVr8Btt93W7an6xnnnnYcNGzZ425o1a7IuUluCK0ZxA4J2K+sAnBWqVqtUbVav0iJF/KCJkEFRxP7dC1oqLzJCpnDJ6KS8yrVgisOzForR2lnC2dJfyL+GgJFpwpt0RTETsY6QkYCPnISnZpD9Ow+Til6R5l5MO++GlpOfEWvbSfUsEHaBk2YTovNxk5EfZlznKtStcglWuQQhJaQlYVXMZnlWS6KFy5wpg5FpUgoIISDLFWcrVRwFU0l2J/dSkOX7e9Qn8N0qmoriStwNWd9XFi5ro94P0mIyACdtALBmzZqQTAtaJuWZT3/60zjssMNw//334+GHH8Z5552H3XfffVrn7MotzqxmVKtVXH/99fj0pz+NE044Aeeee+60CpPETjvtBMuysH79+tD369evx4IFC2J/08okLY9Efdt9BZPw/nY+sbFiY6V0ihS0UiL5o1/9O43LSqdm5tNxT8kNRjHtumWkOrZDhGVBdvhbZwLlPwvLfS6pFE06GHfJ/40VWNUHAKvDwLmJtJuE9yjGThbjxl66e/Wyf6cpU9DdaZhIkj3TtlgaduKswiJ901ShhICttTM+ditcCAGB1m1PQkBF9jsx5UT4mRnlEuDI31LFk8GyUoasWLDqzn67ZkNaAlal5MtpM54M3I8lBSol9xyWhFWSkKWKs69cgSyVYVnSk4GOPr937WXQ4/Nh69e9Iiob4+opa8VLkGF072PbzDdR6/S4/QAwZ84czJkzp+35utFn9JMnn3yyp7Id6NJyKRpQ9WMf+xiuu+46/Nu//VtPChVHpVLBwQcfjJtvvtn7TimFm2++GUuWLOnbdQeJECJg+uxsZoUxqHxquerYZkISZwlFmqGgJ/0gD80qavDT8oXirpYnKTl8l4zAFooFYrUMRuzF8RBhVwwZ+N/IwSih14+7X0rhKISE8CyY/M+iraIpTp4a5VLLrcU5tbs1PfA4t7ho3fRSiUVyTex7JofWP3Fj6kTrpbQunzm81xCt3A0DrrTRiampFWPZbYZtQgh3c62aAnJYQjTJZRVVLAkJUSo7W7kMSAlZLkG61kuOBZMzTrQqFqyy5cZikrGWpUIA5aAsK0mUyhZKlXGUKuOwKmOwKuOQJYmKu2VJNxYzcW4rWVA0a59owoMilb1T8nBvnG/kHxMGJmnrhLzpM3qtWAK6tFx6/PHHMXfu3NB3b3zjG7Hvvvvivvvu60nB4jjnnHNw6qmn4pBDDsGhhx6KSy65BFu2bMHpp5/et2sOCmFMkwOTKWeS5U7CpEApYr3kDEoSJjDegZGVNpO+u5OB4IjBgHejTVrrJXPsIDGKkOm4xnXU46UFBNNeB5RJAPwVdCsQ/yjJNddFuErzaBDZ4GdpJkzGgshMwoSvwDIKLcudAFlCoCIFau4bX7q/k642SLbQCkn4SnsvHomxgnLLEJXB5nqGpkciZESbJ5snrX2QwVmOV4suO4scsL8V5nYG+kji2rr5fhjQylH6BCOfa0ehFAz2LwFot/7N9zLyOQ7lvV+kP1YDHKulcgVWpeycq1yCrJRQGnc+q5oNWbEgy+WQzA6OA42LnlEajVdcF7jKOADAqozDqo7DKvnyLq9hEIatr5LBkPX7ie22OGidnKU4ddblAMOszwC6VC618sXbf//9sf/++0+rQEn8wz/8A5599ll8/OMfx7p163DggQfipz/9aVNQrCJiWRIyYJaslQ2rJH23OBFeNU/ES1drQUs7dh9JR/QFkPULiXTGdF7g/ZgkZzLJg69M6tZJVgSURUahIy3ns1bKiftRKUG48kuUys7x7oTI3K7nduYp0504HwCcWB+NmqdcskoVz13DSniO0mRLck9ekQJlJ42T97kiBayy72ocdeszlgNGtpYtEXIbsbVucpWTsrO4NVpIxy0lMFFs6/6WcP5WbSkvY9ZBZURrRx7K0BGmTXQYqDt0iry4+BVRkdRJvZv+7CKFgDKucXCtQAJuco6iSXhuFK1cFrXW0MYOynWJM+mujQWTNebIzdJ4BdZYFarW8H5vlUtNVqTBexNCoGz58q1SkiiVJayqq1yqOhZMpbLlHZN1U4oj8/ZNBkavnnUe3gdst8WinXVSN2FjhlmfAXSpXMqSM888E2eeeWZPz5mHQbCQwvFvd1/kWpnP7sp5SaBSskKKpVTyKWg9QMXStCn6qjzpnH7Ih37FYBJCQMJkYnPjpUF4KytRCWBcN1qKkqBVTSDmh1ktDx8aWB03WdySlCNSwCoJT6EuS34gWcBdPS85iiN/9TxyPteCSlYsyIrzu4p0FEqW9pVNlUAGJWkmXRHLqqAbi+Wu6hv3vYolm5T7bd3tmixD7fjJthDTirHEcSpJSy/lTh7GTXlCaB2yXgIciyVb+33UxGASgWqL9l+j2vImLEZJb+RVqQxRGYMsO/LXuMYpV9nkWXK6bnPeOQJIAZSlxFjJ+X5GxUK5WkK56pyjPDbLsVwKxFzKirg2xsn5aNGL550XWcW2W0z60Xr6oc/IC4VTLhWJoLV0O4xiyXJXmpTQkIHPMjC5SVwtd1PWAoCWElB22O3ECrirtDhPJ0K4H76aqa+dofsCB9ZkuvRawdRJ4P2W/bbVqr2RHXBXzl0FU+iQSgnCtUJy4oL4lkvRchmrIEfuOecpVcahA/JKliqeXKy6SveyJcMKMmlBVkqwytKzTBq3JMYt7bnFjVvSUTa5yidZCbjvmfpwH4SxkDJucdFYI5WSbFJ0tbNeMoojIRy1n9DKVyZFlUp0U05Fvy1zBvVuSXyPtHIrI5kgYp6FDj4jt9/KgGWS89mX80bZFNwXJ7ODV9JCQlslaMu1XCpXgFIFojIGACiNVWGNVaBt51e2sSwtlzzrUm/M58k5xzqz7GrHxysllKsWKlXnGrXxWShVqihVfMsl2XoJom9wjEV6QV7aERVLxcRWGnbC4Dpp36hC5VKXtBMSncoyq+S4dZTcCZLS2gmwWDYuIn5gRbNaHlxpd8oUja1kAbLN4JQpsruGCqb80uuXeL+e9aDc5IwySQdcNtL90KTBDlsloVSGVL7LrbAkZGXMcYeDExcEsuTJJM9yyr22UdJIN5As4FgqaWV7lkyl8VkoVSxYlh9QNs5SSEgn/XZp3HmdjVsC45ZvVTRuCVTKFkpjzn7LnXR5riLmPIA32TIuI1HlkiUFKpb0jnGUUO7vBZr19aEg3o5VQ5OVUqw1E+VxLyi8fJ6mgilOSdZr6yVznaEgpq7jlErBfV5/1goCjrWm8BYWhe8aBwBae65xgDPOa2UY5MXxkGELSFEqQ1THPEW+NVZBaawCVffd4hx57FuXNinT3UQHY67wmlUtoVS2UB5zrT/HHavRctVC2YRZ4LyYDJBhsVaiQqn4KCSHlCjiEtBBBx2Uei7wwAMPdHx+KpdygpOpw4Jyl7WU0iiVnThMgDMZq1hO7BEzQYtrFzqSshbBmEsmbkpk4pLGJcMMgIyrDXEIvjjy8CIj/aOfE6loX05zCS++h/lN0/6Aa1xgsmP2AXAzFzV3aM/axv1flCuheEqiXAGU80qVcK0iy2XAPQbSDUIrm5Uz5m/FZCgyyiU33odR+jj7JKrB1XMRTmIgpAWrUoYsl1B2lUeVsoXxhkLFvda4JVAaL3nKJ2/SFSlbMAtn2VUixVkuRYN+R1GelYK71m+uoxBjqWRWCoZTyU8FfD7JKvbbMGKUT8FxlJERGjpkreQooB3XOPeAWLQOyhEByJKzAYDlZo1zLZessYqzucolk7XTySAXcFO2LGi3rFIAloRnETqjYmHWjDI2u5ZLlartKf7LAY1+VNyxf5N+MCwKmWG5j1FH6+R3ZRFF4Mknn+z9Pzk5iX//93/Hfvvt52Wru+uuu/DrX/8a/9//9/91dX4qlwaAccVPouS+yFXDefkrpVGqOJMrwJnUVEsSZSlCL/sQnpWBUS7JcCpvKcPKpRQxmJoyn8RcmsomBw60RoNBDBiCl+i0SQWtlAztlMOea1dstjPpZYwD4LhklMqAsVwKfu9OeERlLNYtLmi5NMOVbyXXXa1crXgZ4gCgUi2hXC1hvGJh3BxjiXD53ZTcpfGKpzwqjZcwq257cmvMkiiP+cona6zquPRFFO1C+G5xZcuRtXHKJSN/LeEooWREYRfEUzCZuoQKvxBMJqjIb0j2DCoodluldQ8CfLcijRVTmtsfqXdfXLZHuFZMAJyod+FK82Iw6bBrnFkgiKs58512rR1NQG9tOXI2KGtL45Oe5ZJyrZGssYofF082W2laQqDqxlyaNVbC7LESnh9zLE8bNSehzKyxkme5NMhx3si0JdLEMATuplJpuOhHQO+sueCCC7z///mf/xnvf//78alPfarpmDVr1nR1fo5iCSGEEEIIIYQQQlxsrdtuReY73/kO3vGOdzR9//a3vx3f+973ujonLZdcOnF56VQr3TJ2bmC1b7xiYWtZQjXiYy7NcF1DypaflttbEw9eQAjfFNqyoJW/yiascCBbHbNqHl9+EbKCyBNZBvWOg25ypNd04sISDRBrPuvAZwDeunrL1eigVaMrUzy3uHIZcFfNAQCNuuN2URlz9sENOmtihQQwRpeOW5wj38pVN85HrQTpxmECgPKYs29GwC2uLKVjbWGC57oBvWW57MVUqswsQ9Vsz8W4NF5CeWbZs2wyWZRCVp1aQcKPuSTdVf3xQGVaUmCs5McgKVvSddNrUYde/blxpzwrpnD68lA9xcRj6rUlU27S1PeRoZS9rSyY2rSPdu/IOJfcbprGMFovNcVbirMeiwT0BgKGidqPu+R8L7y4SwBgghZEqzsow5XWsIIW6ZbluClXXcul6jissa0ouwG9G5NTzmGVMqSJgSd96yoAbnIYYMyVq7PGSpg1VkbVlZGNehlCCieLnCsTh1dakKzp9buIVkvpGDZ53S802rjFDawk/WF8fBy//OUvsc8++4S+/+Uvf4mxsbEWv0qGyqWcMKNiYVO15I1TtNaQlkDFdQcZrzjuIUE3DCEiL3wvfkc45pIIZgyRVsoYS865WmlkO80SN4wDz3aM4j2T/hHnwmLcKgA3PlLoeF8pnNRbk9wdtJDOxMQq+4qjUgW6VPdiLglXroRcNUplKFnyXTkC5QUc97LxsoWKmwIbAOyGgixJzy2uOlZGpepMekzK7LIlwua2JWcCVRqroDLLKV9lZgXa1p5yyapIVGZV/IDeY078KFEqRyaE4ZhLZUugbCqn7F/fC/rtTtCMyqipGo1LYdAN2Q4rllpnjYucbZoKpjg5FPyuSAPikafPbpNsCt1jXOMg3MyUQkBDww4eI/zxk4CGhC/Dg3gxlwBn3OZmi9Oy5CRPCLjFybEZsOyw4kuWS4CrXPLibXrl1I5bnOtCN2ZJzKqWMHuG6xZXtyGkwKyxsicD22XFJKQbhundM0z3QnyU1rEyOri/yJx99tl473vfiwceeACHHnooAODuu+/G1772NZx//vldnZPKpQ7oRHB0KmNmjZXxQqUO5Y4otNawLMfnHYAzEStJlCwZWF2POVFwFVxaXkYR8zk02QlmgpomWYrUvFkvBaGCifSSNDFSgvGVzOeoT7hnwdSu37iWMyKwcm6yFXko25U1Zc+6CVbZCUAbjWkkjWLGibk0a6yESddySTVKsEoKwsRcGi9hxlgJs6slb4XdsVwKWAdaTua60swxlGc6167Ocf7adWdKVxoroTqngvJMk7q74ijKInFIZCDm0pgb387EJJGuIm3Mkt6EzInLJH2dvhBt/cybFPsx1l29Vh6kkT+jYM2Ud/r5rshN/Kg80y6mVZr9Xvwlt74RHqtphGNYJp7OPYfSwpfBgBfc27MkrYw51kuNeuj3slzyxn+OJWnYUtMSvuXSjLKF7WaUsd0M5/htNRuWFJhVLXkyMC+ioWgyqtB9os8U7VmS0UQj2Tqp6D172bJlWLx4Mb70pS/hP//zPwEAL3nJS7BixQq8+c1v7uqcVC5FyEoZMF62MHvMfxy20l7QW8CxbDKWS1YrgWxcKKRJP1sPWzKYlfpAMNm0dGqpRHw4uCD9xKwom8xxcdZLSdZJAoGJg0ZEAS0cuSJLjvwAoEtlCBVYizfKpYDSSRurpUigcFOOsZLEeMXC7LEyNo+7gWiVY20kXeV5dbyM7WaUMWus5GU1akpmIC2I6jhKY77yqDpR884HAFbZQmVmBaWZTjY6a6ziufDpJuUXvOtUS5Y3EbTc23WU+0bRJdwMc63r1tSf879sjnIYsW7qpQtcN/JmGJRMvZazeV68IPnHka++b7OEE9Tb/QglAiEOYtBau8lYfMslLUsBt7gxiNoY0HDkniUtRyaXyp7Mji4gCq1gSenJ1fGyo+ifGHeOrzUcgTd7rORbb7YqH/sG6ZB+tZmsxtjsA8ONUo7RedL+ovPmN7+5a0VSHFQupaTfwmP2WAmbp8re54bSqJYkZrnZO2aNlZysRwHLpXAWIvirW2aCYpUhZKDVi5j04G3uSyDe8sGQl0xxRZgU0YqJ9IK0MZhMv42LmWYmO237r6f8EI41EpwYH84uR/Gtle38H5jMaGmFFSvamUB58YqkwHjFwqxqCdvNCMi9hm+5NDGjjInxiqNcMhmQjDLHxBBxr1meOY7K7JnOOba5yiXjFleWqMwZR3mGMxkrzxwHSpWQi7DQChJ+PLuylBgrSc/cue55x0lvsmVc5Mxvgu4ugNvf4SuMRFrFUbDeumS6coYKleFkUM91GN51TfGW4ogJUCW0CvR5hLT9RtEkEI7B1PYyQvjnlBZ0qQzpusXJyhh0ZSyQvXPSVS5VnA2OK7OQ0i+KVrCERMmVZTPKFuYEZHHNnUnNGiv5lvLI1kKdDAfD9l4ZtvshzShoqAT7pKR9owqVSzFEB0aDEB6zxkqYqJU9txFjuTTbjUcyXrFQLVmR1NfNabkdVxRncqVlCUI1/P3uRLEpzkcXQWPzolSKkncl0zAMukk+MfGXgkZIQQVTRwTjAskSYJW8yYsoKed/E8vNduO6lSpAqer8plRxVtjd8yh3DmYmKlU3zfXssRJqtu+621Dam/DMGnMsl2ZWfLc4S0YmOG6sJ2usgpJruVSZMxPSklDuBMmqlFCZPROVOTMAAKUZ447lUqkcPJMz6XNPXi1JVBsStqtVD8ZiCrroWYHfxEpQIeGF7W0lY+Nkskuvg3l3QhEVTEWXrcP0fhime0mNVh0rhiUc66VWKO3qn4KLiK5rHBCwXIpak5YqoRh4Ybc47QX1BhxL0hllCxNGudRwlUsBl+S8WK8XUS4BI9ofIhTxuQ0raZNXjXqbBRz5mxjQu4BVtP3226eW6c8991zH56dyqQWDFoKzxkrYVrO9iZVvueQ8Isf3XTatlIcwkxQ38KPQ2guoa/bDssIuGHEDIa38TEoRd5Y4zK52AR8HKajyHKyWbnKkF7Rb9DaL5okxl5Dcb0PWkJ5MKEFUxqDdGB+iBC/ot7aMG4arkPLki+OaZyyXqiXLm8wYBY4lBWoN5WWGm10tYWJGGTPKzrFAwHLJuxHHPcQan4HKbEd5pGoNCMuXa1a55MZkci2uqmOOS4kVDujtxFyCd52g5ZLlltGJw+S76FkyRfwqI2/d+o5OQFvK4cjv00K50nsGOaHt9/uhqJPzXNIq8L6XQc7ygnoDjjtcMPOQFoCCgDTxlRCvpFZuAG4AgOW4xRlZKypjkJUxKM9yyfJdlU1svFLZU0Z5RQU8K8wZZceKdI4bp86epb3vjczO64IiIVkxCnJ0FO6xHUq39t4x+4vGJZdc0tfzU7mUIcHBo5lomYmVrZyVJaNcmlG2MFZyXDWiK+Uht4tAzCVYKrwkJmV4IpPCYslYQxSw73hEB+l5EZZcFSDTJapgCmaPA8IKpo5OGsxwpgQgS9BW2MU25OblxmUKZjSKKkUEfMslb6V83FcuVUrSk3uAo3CfM1bGrIrlKXQs6SpxjMJGOoouOXM2KnO2Ot8pBVnxX23SkqjMnomyq3wSYzMhSuVwTCi3fObaJUujqqWXLbOsfQsm37XPkcVm0idFcz07yjlTb9JXMAX2t6z7HJB3S1DSHYMM8F2Id1waF7g+EHWbk4CbtTLu4HAiFiNrhVWGGJ/pjQeVcYtz4+ABgChXoIPjPa1gWcJbzKy68niWydzplikoeykCpk9h+kOPGbb3R9HvZxTb4HSwtW6ZOd3sLxqnnnpqX89P5VJGRDv3jLIF5brCAb5yyazYj5ctVN3sRGZRvmml3FgXKH/iBREZNAXSg3cS2DvoahP3fVryYLWTpwnTqA42SP8IBvgG0BzkO+Y3zQrYsMJay5IXg8QoSEKKESGcyY7lurhJy3WL8yWHFL7VZdVyJjNTDQW4Wd62VeyQcmlmpYTZFctTrAMByyUvrpzjFifGZsKaOcs5N4DSWBXadYsTlkRp5hjkzDnO57GZjrtIUNGuFaSwvPJZQqAk4cnfuonfJH0FlCURcovzlP7uX63duvauYTt1Gap4Gf5xpP7zQp5kZlYMug4G8W6gFVMHCJlKCdXOEtHEXXIOdiw6VYqRVEgmS8sP8G1VICrKc4uTxnIJcCyWAFeZbqHZUtO5bsUSmFGWmBVQyiulMaNseQqofEmk4pKHMTAZTTppc3wv+AyjW1yUxx57DCtWrMBjjz2GL33pS5g3bx5+8pOfYLfddsP+++/f8fmoXBowrTq3eamXXV93W2uUA9k8jGtItSRDK+XOSQNubsHYKEDzYChiuRTNItJUTiEgIUIT1TjaucRFyYNSJS+uc3moC1JcWgX4DloxJfXb6Op5+OTOCrnQylNKe4olHbZkQsBVQ7sucaZMUiCUjc1YLtVt5cmOaklCKQ3pCrYxS2LOmOMWV/ECeoeLp2UJcnwm1PhMyMb2TlEsC1Z1EtqLEVWBqI5BzpjtlGV8phOU3LJC53JikPjub8H6tISAgoaEH6fEEgKW8CddsQFvg/XkyZgYa6VgfUcswtIyCBlCJdNgGZSCyVyL+Ggh0wX1NqRZpIuYmpp4S9FfRpMDBM/vjfNsd/heKjuhDCrNbnGeK3Op6srkqKWmu1sKzKqUPCW6YValFFrM7HScR8ig5MqgxtBFlJOcX0wPpXXIIyBuf5G5/fbbceKJJ+KVr3wl7rjjDlx44YWYN28eHnzwQXz1q1/Fd7/73Y7PSeXSAEnq4LMrziCg6rqeKO2s9JsV+6rrEleSzSbT3kpIJDaKBlool4T7OxlWNiUQtYaI29cpeVKqZK1o4moWmS5xMZji+m2q/hp1wZAl33rRVZgEJ17alTueVaTlZGNTkYmUFVAkzVAStiqh7Mq8uq1gawSysUnMrliYXbW87ywpwtZAsgSUqo7iyFUmaSmhK5OBSnCtm8adbHJibAZEuQoVCDgOuJMtt3wl6dSZmeA5Zs++VZPz1yikjPyNr1fP4gBw4y21iNOSgrwMbEfZ4mXQ9z6od0PW78BC0KavprU4NGM4E28pGtBbBo5pcpGLxsCTJaDk5ysSVtkf93nWTW7MpZDlkghkxxSoWMJb5DQLE07MpchiJukJeRr/kuGA7ak/2MrZkvYXmWXLluHTn/40zjnnHMyePdv7/jWveQ0uu+yyrs5J5dIASNPhZ1VKkEKgroxyCaEAuGMlibGy9FwxgBgfeBGJjSJkOFuc+503AJIRKyavvIFUum6qXd8CId0II+3YNI9KlSwnThxwkOnQKsh3q34b+7WQjgsXAgG9rZI/edEK0AIaVug3Wkgv9bWOKG6ca/mWQaWAy++Y7RxX9zKzOcePlSSqlmO1VLF8hY4UflpuE9jWuLwBcDLVNWqAMhMs6SiXTOru8ZnQpaoz2ZLRyZbv/lbWAm5xYWnfHVAG5G8oW5yIi7kkIBAJ6B1Dc+yl/DuhUME02HvPKiFG8Pq9OE+R6MR6qVXGxyjBBAvGJU4G6skoqUXkc+AAT+EPwBFOgeO1HXZXBtCUvdPsMpagJVe5pMp+bDtbwVvQDJ6f9I5gnyp6XxkF8vq+Y9vpL8NuufTQQw/h+uuvb/p+3rx5+POf/9zVOalc6iOddPjxspMJzpglm8ZqAuBaUqDsbmZA4AX0NplHZAkIpCKHaEBL6U+ygLAbXNDMOopWoWNaud70irwpmahgIp2Qp1X/4OXjmlHTXCXxoIAC2gTrjptsBSycnJ9Z0NKCDqTRCMf4cM5tSeEF9LaVb7EJAJWS8FbUSwHLpSDaKkOXx5zYJTPd78oVQNnQtusWZ1me9RIA6NKYN9ny4yFpCOHLW+3cuRfYNrgyZSZ7nqufiJ98mQxPnmyDTJcYoQCKJQMVTINXMAWvP0iG+p2UEE9JRxbeWu0Lf+/KEZ088XCU1WgSyt73LjLiu6xlCcIsImoFjUrAmjOwoBhQwkNangw33xt5WpYathauXAYs6bg0l9wxZ/DYPDCMrpzDOO4bNpe4vDGq9z1oGkp7hh+t9heZ7bbbDk8//TT23HPP0PcrV67ELrvs0tU5qVzqA4kdPjI4MYOVPzy/DZtrDWx1U8Eqk/radXgfL1uYXbEwMVbCRLXsficwAxLCXW2vCjiWSnXHJUTYdeez9gchQTc448ripQ0HvIDfJsOR4w4jm14SSQMmKUSqSW1s9eRoJSdrBZMpA8kfSc8lS0VTmubiGiMCcMsadHHTTmBY77NqAHbDlSPaO6aVS5wo+1Y6ttKoudqZbXWFLQ2FbXXndxsmG9hUs7G1bjtBvQHv5W2sNU2A2R3Gy9jOzZppSYlxAMKuAQDk5AaIzc/Bfv4ZqE0vONfeuhF6KhBzyU3JLcYc7ZOcOQdyzg6wZu8AZTsmwGrccSdR2reiqtl++W2tvdv3LJXc+Eue4ksIlKVnSOB8r3xlWbAlJE5SjZwO7W/fjrKSGcM40UtLlvfOd0SHtLFAirVQSvObQF/1LCrdR6K0hq0BrY0cceSiOaut/H3eOYVwFfHO55J0rSLNr5QNUdsK0ZgCAMj6Voj6FOB+1o16IKC3Y0kqy1XoUhXKfC8kRKnqTYq2NTS21BW21Jz9m2oN1G2N2VULc2dU3HI4C5vWCPbzQZGn8S8Jk7f3G9vH4Bh2t7i3vOUtOPfcc/Gd73wHQggopfDLX/4SH/rQh/COd7yjq3NSuTRIEgYqJuaSWSWqK5NdydlfLbkBvS3LnxhGT2JioxhFkVahuEtetqdIPJUkjItcMMC31t3HWeqEYVzJIYMnqCSczmSwm7Y4aEVTK7e44P72JwkGoXaC/muUAgqo1i5xxnJJu1nRggs6lvDjE1VLErbWsIQv84xixyjUnSQGjjtwySzKm3sIxFwSlfHYmEvaVVYJ6ZRNBmMuVcfDlktwZJ3lfjYBvT13YB2+F8C3xJKBz0BYLgd/4rnIBdyOYymQ5VIQWjHR0nXoSMoQ16QAdq03hUCSiWIwqHdcpjhjERmykIyeJBDSQMsSYPlnEcFscV6ChQp0qeLHaXIJusWVpcBY2dxTCXWlMKtS8mWvGMy4jziwX7eH9UMGwbC7xX3mM5/B0qVLsWjRIti2jf322w+2beOtb30rPvaxj3V1TiqXesh0BJ0Xf8R9k9ddVaiZaJXdGCXGVQRwzJQl/JUvJz6KCARxdAcc2phoe2k/3L/upFBGlExaAcKKfA776g+qL2X9gs16VT7r+y86reouizrtVRyTttdJccp29x8KQi1LgFC+O1wglpFzUMAlziQTkBZUIPOQsxqvPdll5J2TETMcZy4U9LtsYcySLV0zvJhLruIIiIm5BAClMqTrFieqYxDlKrRlNVkMSc8KSXsWSYDrsoew3BPCDVLuBfT2J4RBzMBDwpk1ig6Teo+qwoakh1ZMKUhSFCEhvlKCsrddZsdWT8McqVwLpahVpCX8xC1eljYv6F1zQG8dHMnLUlNYA12KBPQ2SRk89zjtxFzyVFQSVe3EuvPkW8tayI5hV2gXuV8Py3PJ430UsT0UGVtrN6lL6/1FplKp4Oqrr8b555+Phx9+GJs3b8ZBBx2EffbZp+tzUrlECCGEEEIIIYQQ4lJX2ouH3Gr/MLDbbrtht91268m5CqNcuvDCC/E///M/WLVqFSqVCl544YWsixRiuprkGWULZUtgsmFW8Z0VJWOGXJbSs1qyAi4iQbT2g3o7ZXLd4lTYLc47Ps5qCUhcqTMrRf0O8B2kyKs3JB/kte20Klc/V8tC12zj8hHKcOatekdiAnkWkJbvFtfChcy4WCgNzKxYsJVGPZDdSApfvpWlRMlyYo5YnkWRW34vyHjZcffQMyGN1VS5Al2vNSUyENVxp7jlquMmErC0MoU2Ibct6aTiRsAqSUdc43zLArcoAWuDJNLE1cjjamkaht2SIIk8BPXnu3J6JAXvjjvGOTAYc0kkBvE2gbqNhZCXJS7QXKIxl2JlSjDrr1WGAHzrpUBMPC/BgmtZGi27OXdZCtgSqLhW7hICCtpLItOyHGQgMBZTM6wHMih0G7e4aNy8InDOOefgU5/6FGbOnIlzzjkn8dgvfOELHZ+/MMqlWq2GN73pTViyZAm++tWvZl2cnmFe9hXLMVE2kygzQDHKJUv4wWO97ERCxLpheOlnZckZs5jg3AlZnhIzxwFNZtbBSxWwXxGSa/rljtl2QCYkABXw03DVLUGXkaisENKJxSZLXnmV0qEXrkl7rQKTGan9INhBjHLJKKMqViAdtpFtwWtblZCSTAjpZIYzcUcAP3EBXFe6qJuIwT2PJSwoiYA2SUDDiRFlrmR+GY2N0moSprSGhAi5LfZDCZG1Ky2DXGevZMtLPeSOqPt/Aolx0WLO18nzNjIiGm/J7Es8kxCu3AvE1gzIMqEDLswtssWZe7O88aV25bBZ1NRQ2lGyGyVX7FgzB2Td1wZN9F7z1scHEltyQPecx3aVt+c9Ctjazxzcan/RWLlyJer1OgDggQceaCnfu5X7hVEufeITnwAAXHPNNdkWhBBCCCGEEEIIIUPLMAb0/tKXvoQ5c+YAAG677baen78wyqVumJqawtTUlPd548aNGZYmGcddxFnNB8yCuQi5XljCpIJ1vrOkySziWgtoDRnMACc0ou4rTat1KVbnRCS7UXSlKI2LXC8WALJckR+11bEikNS/h2V1p1ftruP6CHbqVlaNgXKZlXNzGXM1I79s7cgpyzuFhtAiVmaYYwTguQGb83hWQZ5LSAlQDcCq+MFzjTllUNa51lUAoK2SEwQ36CYSWPV3PlqOnDUuIVrD1sYaxD9t0EopyWopSDQoOImnSO/vOPLwzsjaii3XtAnwnfi7AMFnnOQS5/0czfIxuj84rhNw5UTQm1lILxi3tkrNiVuiluZCNMlvoZWTWQ6+bFZ+1HBo13IpZJnZw+Zc9P6dF/JkyTQwd/4RZNTvP0vqtvKSbLXaXzQOOuggPP3005g3bx4WL16Me++9FzvuuGPPzl/MnMcpWb58OSYmJrxt0aJF2RYoQZFTlsYFRHib853w0sRawn/ZCxGfc0i7gwhtXFWCbm8Jm/eb6dxejwcfhCSRu/7dJ4TW0xpYpPltqP+HFNIiYQtkiTMpuFsg4cddclx8hSfzmreAzHPdgI1SvekKJpaILDnucW7KbV0qA4FNl8ru9xVPseSke5N+1rtInUk39omZ6Jnrm7KYz2YLZndKa0o8zOPF6bbbpP7tvOda13G7/YNiunXQC0xd5KE+ckd0LNThMVHFkvc/4jPFeTIiYTPyxsieNGUPj/OE6wbsb45bXOv79GWa8EMwWCIk63pNL9/feehneSHY3wfZ74dNsUR5SQzGLS5pKxrbbbcdHn/8cQDAE088AaV6qyDLVLm0bNkybyDeanvkkUe6Pv95552HDRs2eNuaNWt6WHpCSJawfxMyvLB/EzK8sH8TQoqAcYtL2orGG9/4Rhx11FHYc889IYTAIYccgsWLF8du3ZCpW9wHP/hBnHbaaYnHdHtjAFCtVlGtVrv+fV8wq0YRc2wTyNtoQAV0aJleuhnazKoS4K6Qp7hesNnHHR+yWEppvZQUtLWfCv9RNPMfxXtOQy77d87out3EBbpuWrVvlhXRl6znxSYErIgkcgJkCwQloYTvDmJJ57MVcBGRxj/ECBkT2FargFucDAe1jdxPKLNdnLWWe79CWrC8O9BQcFbyW2UGiVorxVkdBJM0eJfqgzvxMMiMXvTvvNRDHlzkgPzUR27pwHq7k+fpJSLQ2skW1+IRBN3h/O8i1xHS8c0Nur5ZJV/eKdUUyqDJaslzA9beNZzxpe8WFyxT+Jve0I/3d176Wd5IqpPpyINhs1bKK6yLbFFKQ7US2u7+ovGVr3wFb3jDG/Doo4/i/e9/P8444wzMnj27Z+fPVLk0d+5czJ07N8siEEIIIYQQQgghhHg0lEY9QYHUKKByCQBOOOEEAMD999+Ps846a3iUS53w5JNP4rnnnsOTTz4J27axatUqAMDee++NWbNmZVs4dLEiGA2uKJRjveQ2UrOiL0PHCG81H4Dnk9/SL9+kFYdvLdUyrlI0zkorYiwYCCH9J+2q7PRWIsOBrf2TyqZjgvu0aA7OLUxgbTgySsG3XnJ2hQNkB5MXAK7VkkyOPWIC23pBbZ0vnaC23mfVLN9EfKyloDWA0BoaflBdSzhxVOLShxvSBPTuhLhHyYX5zsiLtU5erCryUh9FJO75BasyrXtEKzkRCp7dtiyurAbCMk4COhrxIimmVLBMpmBKQ7vn7jYVNSkGeZBJhjzIpTzVB5CPOhl1bK1hJzyHpH1FYMWKFT0/Z2GUSx//+Mdx7bXXep8POuggAMCtt96Ko48+OqNS9Q5LCNjQnnsc4Ey6QtmIRNhtJPri98yno6533jHxLnmxg46kySQhJBOCAw0zCJrW4KNFxqRUfd7LItde2aK0r2ACnOxryt0XDBYblG9mghV0/xUCgApMpExGTFfB5FzMcQvx5Z8VKa9MDG4bukVP0SWgtE6dEc77ffpDU6MDXoEkHT3pKz0gyZ18kOSlPopEO8VSGoLucdHvDEbumfGcECmeU1COtxrPxSVtCWTHDI43tfBltl+uYgidvChxSXsof1rDuskPw+gW128KozW45pproLVu2oZBsUQIIYQQQgghhJB8YKNNtrisC5hDCmO5VASmsxrorBA5QW4Bx5ktuqIPwEuJ7f+m9eq4FtI3mQ6StFrfbsWHVkwDhysYJI7M2kWMDEhbFM+SCQJWm2OMlVA7SyHjGuefwBV5rWRV0GopaM0UQLgBwoWRvEKErJe8a8ecfhBr5mmsl2id0kxeXMLyYl1RlDbSb3fgbq4ZvVwrl7i4AN6tXM1SW0UKATMqNO5r4cIlWDG1QArhuXcIISChnb/ZN9OOyUv/Is3kXdbkAdZRvmiXEa6I2eL6DTUFfUAL0fGLzUykhBCuAim8OfGWHMWSmXB1/OIXIn5GYr6PutURQoaftC5wETeyqJxLesF6Lm4IK42imyXCxwSzxMW6ZQRlVnCzSo4SKW5L4Q4XWwXCL4fnshKzkXyTl0lnniYQeamTKJ2MpcyxcVs3v+8lSUryaOzMoEtcR0SzwUWyACe5Opu2GCd7CZkuQmtvyzN5kIN5qaO8lCMP1G2FWsJWt5tDS/SSCy+8EEcccQRmzJiB7bbbLvaYJ598Eq997WsxY8YMzJs3Dx/+8IfRaDT6Wq4kaLlECCGEEEIIIYQQ4mIrDTshrlLSvl5Qq9Xwpje9CUuWLMFXv/rV5uvbNl772tdiwYIF+L//+z88/fTTeMc73oFyuYzPfOYzfS1bK6hc6iNBLXg7LbAxnU6yROo0mKz/w1YBvhOOdWEwb1J08uIKk2s67OdB2ZZUtcEAtkH3kFYSKJzAQKTKmgQh411DEo73fhdc6U/6SYybhRSiY3PoXgbFNZfOwWJr4ejk3dxP8uS+kycXuV7XSS/Pl6Z6zNWih7YbvwV3e0aZKS6ohfQzfCaGPfDdfJt2CSdxAeBYobYLu5B38hI8f5TJgywpCqyr/JK1cukTn/gEACf2dBz/+7//i9/85je46aabMH/+fBx44IH41Kc+hXPPPRf/+q//ikql0tfyxUHNwYBIMtk2L7+o60h0C7rNBSdexk2j7Tu03aCDiiRCSBvSDtajiiLzXdJmjo3KN89zN2EApo2yKOoa0mJrUpyniesSOSToJtdKcdRuP8kWTj7D9MMtrNPr55V+zP+iLrWxciImo6d/Aj9uXKvFwFFeJOSkPRuKVu9Zyp2i1dWoYStfwRS/Ocdt3LgxtE1NTQ2kfHfeeScOOOAAzJ8/3/vu+OOPx8aNG/HrX/96IGWIMrpvHEIIIYQQQgghhJAItYZquwHAokWLMDEx4W3Lly8fSPnWrVsXUiwB8D6vW7duIGWIQre4nCCE8FxHko4BkrPERTXgIXNpILV1UvOqPvWQhIwy0ZW9ThfbjIxL2g904fprMie5cs7LkplAS3e46OcYVxNTDXG3QuukYpKl62xe3XeycB3MWx1Ml1buca3dgl3XxLjcBUnWSwFaWil1OIYbridBBgWtcDqD9ZV/VBu3OOXuW7NmDebMmeN9X61WW/5m2bJluOiiixKv+9vf/hb77rtvh6XNB1QuEUIIIYQQQgghhLjYuk3MJVdBOGfOnJByKYkPfvCDOO200xKPWbx4capzLViwAPfcc0/ou/Xr13v7soDKpYwJKq3bpX6Ns1jqx0r5KPvnk+Fi2FbCs6LbejQyywvknVLGASlTcgvZbF2kVbPFJtpYY6aJtxQJvixEf2KwkGzIOqB1noJ7R+m3FVNe77sTkgL8t7s7GZErQIp6DppQBuVgmt+kKE+nyQryTJ77FhlNaLFUHPoR0Hvu3LmYO3fudIrlsWTJElx44YV45plnMG/ePADAjTfeiDlz5mC//fbryTU6hcqlDNEaqAcaZRp3kDjFUrt3pplUpTGrjlUsUdlEyMgSNyhvO+9B2BUkmCkuSlTuRa/W7ZwgUUneI5mWBwWT1swY10uydpHL+yS414qmvN9vv2mrQE/pDpdISnkX5/I7LK6+eXU/HSaKqDDJoj0UpZ6K8D4aBFMNBTRay+GphH294Mknn8Rzzz2HJ598ErZtY9WqVQCAvffeG7NmzcJxxx2H/fbbD6eccgo+97nPYd26dfjYxz6GpUuXJrrm9RMqlwghhBBCCCGEEEJc+mG51Akf//jHce2113qfDzroIADArbfeiqOPPhqWZeGGG27Ae9/7XixZsgQzZ87Eqaeeik9+8pN9LVcSVC4NmKDGWmiFMd0AAGirAoV0pshxJtTRc8cR5ypivm9d4HxZLWWl8af2nowiadt9OrnV/jytXH5TuYiYYwLuceFj4qwyRez+TlyDkwJ8k2KStfWSKUPeaVXGNHVXhPvrFCOz2snDVtZAqV3iYn/cRma1kHWjBq0x+kNRrHGC0GqJpCFtQO9+cc011+Caa65JPGb33XfHj3/8476WoxOoXMoSIaGtCgB3MAsgmOcoOECJG4x0Ixd7FU+JL+fBwBcRGTTt+nbaJhl1jUs6Lkgr5blz8Q7MjzuZbKU9ZcLEJA8ucqR3MAZT9xS13L2iU1eyPFZXNO5SHsvYLUXuW3mjqGNUKpZIWmytvaDdrfaTMFQuEUIIIYQQQgghhLjU2sRcqvU55lIRoXJpwHSyGtrOdNr73A+t6QibTZPiw1XJ7uh1vZmzxUmouCt1lTUp+oO0WZZC37WQdx3KQVovDR9Zu8hRluWHfvTvluO5tFaaaQrlCdPuXH+HkSK5n5LeMejnTWul4pN1zKUiQuVSRiS5VnjH6Nb7+sqIDzoIGSXSDramM0ZKc4WeZSWKUzK1OndE1vViwsUYTMNH1gomUwYyXKRdKEyT6TfVBTpkWDLFJUEFbvcUTXFCxVLnDMM9TBdbK9iqtQy2e5HRc8igcokQQgghhBBCCCHEJeuA3kWEyqUck0bJnqhVFrID0+r0K/ZZrfJkoUHnihYZRjpt1/3qeu0SFaRyEWkl59rdYx+slqKX56Lf8MAA3wSYvmViXx5hqsFijEscrdQBsG91Q9EsWgb5fItWNyQZW2lIusV1BJVLBSaVAGunYOLgIpfw5dQ7WJc+/RpgRTMLpf1NlFjFUj9II/d65CLX7+bHOdFgXceydpEbxUlwu/rOJPNTF327pXdu9ER0sxg4dD9NT1HGVMwIR3rBVENDJQTtrjf4zKNQuUQIIYQQQgghhBDiQsulzqFyqYB0rBnvoXUSVwIIKRbT7bNpu18766V2wWFb7o6s4scGt03jApwgB0c9cxLpjKytl4LlGEY6rdvo8YOql04StbXcP4h2lFK+cag1eOvANM8/L/0872PxrOsp7/VDuoPKpc6hcokQQgghhBBCCCHEhQG9O6cQy7VPPPEE3vnOd2LPPffE+Pg49tprL1xwwQWo1WpZF23gZKUZ10JkvipACGmP6atZ9FkpRMstDiH8zftO6+7knJDJWwxayHirpR5aMkXvb5QY5ndGHu5t2FbKu+77fTpPqmuJ5K1dOZvoZbyliOwLybvQ99m35TwxsLaT8jqmPbfb+lnOPMuarOcnea8fMj0atkKjkbDZjJEXpRCWS4888giUUrjqqquw99574+GHH8YZZ5yBLVu24OKLL866eAODwmuwjFJWPFJ8+tFe+xpTO6a4gwxs22+l0qgzMNekDOVl1hnkzLWpHBheeuUGTNffzihiv+pGDuVBhnVC3p5JUeqNdI9SOtE6iZZLzRRCuXTCCSfghBNO8D4vXrwYq1evxhVXXDFSyiVCCCGEEEIIIYT0F601dIISMWnfqFII5VIcGzZswA477JB1MQZGHlZns4CrAoTEk7cVvDQkFXlQfT2rFfxuUpdP63qUnQMjywDfQPHTqI9aW215v51Yaho5Fv1NGvnmHlPU9jIo+h08P2u5AeS37xWhbea17khv0UpDJ1gnJe0bVQqpXHr00Udx6aWXtrVampqawtTUlPd548aN/S5az8laeI2qYqkIL7ZRZxj6dycMsk32o+u1Kn5PJlopaKtUSjEpy5NcyFFR+kJS/26lTMlSyZKniWKe2mk7+lVnea2Dnt9vKrmV4phIsZTWbTN8Toeivb/75SZXNLe0XpLXPtqOUXxWo4zd0BCNhGxxCftGlUydsJctWwYhROL2yCOPhH6zdu1anHDCCXjTm96EM844I/H8y5cvx8TEhLctWrSon7dDCBkg7N+EDC/s34QML+zfhJAiYNzikjYSRugMa+XZZ5/FX/7yl8RjFi9ejEqlAgB46qmncPTRR+Pwww/HNddcAymTdWNxKyOLFi3C+nXrMHtiYvo30GdG3XJnFO9/lFdENm7ciPkLFmDDhg2YM2dO2+PT9O+i1mfW/a9X1daPbEmxAW4TSOUGl9JVbrrPpZfNsau6HQCtrIl62b/T/D6uLIMiL3InazmShn7UVV7vuxsrzU7lXei0UbnWFOTbr6d2lkvtqnTThg0D799Z0a/2lRe50Qvy2gd7wTA9p7R0+v4eBjZu3IiJiQkccv4PURqb2fK4xuQW3Pep149U3bQjU7e4uXPnYu7cuamOXbt2LY455hgcfPDBWLFiRVvFEgBUq1VUq9W2x0UFRR6E4igqVoKM+v2T9qTt30VgWNpcJ7fRbR/XQiZOuFLHVMog9tKg4y4VmV7076wyPuXBRQ4oppvcdMnjvWbRFjpRLLWin65xRX5/96tf5UVudEMe+12vKeqzIdODMZc6pxAxl9auXYujjz4au+++Oy6++GI8++yz3r4FCxZkWDJCCCGEEEIIIYQMFW2US6ByqYlCKJduvPFGPProo3j00Uex6667hvZN16svThPd7wwRSWStGR+F1Yc8kvVzJ4OhKP3LFDNts0x7W23beUoXkGlnfMsoY1yvKEgzygVZvs/zwjDXQeHvp4XM66k7XLvjOfzoin5YMAXPlfdxYeH7Xgfk/VlMl1EOLN8OWynAbi2PbdXb5DPDQCFG2KeddhqDaBFCCCGEEEIIIaTvGLe4pI2EKYTlUj9Iq50dZMwGxhliHZDhouhtqpfF75XVUvcFKMRaSk/ISzDvvDHIGER5jZ+SNyumTuopD+XtlEG3gVirpQ7jLakctts80695Ql5lSBH7Ybfksf57SfRZ0oKpGaUAkaBAouFSMyOrXOqEfg5I89CB8/KiyENdZMGo3nc/oZIyXyQ+j34rlYCeKZayChBNesugFCx5H6jnRdE0rH1qkAr1bpRK7YrXr2DeacmrciWOfvWlVtk3s2BY+2kritL2umXUnme3tPOUohdVM1QuEUIIIYQQQgghhLjYDQ1YrRVIdoPKpShULnVAVIs9Xa1vHrTiedFcZ10XeakHUjzYduLJuk8Pqxscm1tvGaSrXJ7p9fhmlBmk7GsZvHtI5F+RAlwb+mnhmkV9jKIsKEpb65Z2z7RIVoP9pl1cJcZcaobKpWnQyWAsj510FF8YeSOP7YIkw37TntTtuh8ucUMyqeoWypTuyIuLWF6gsqk7UvW/FHLPKI3issa1zQYXs79Tl7g8UqQJ7yCU1nHn7lX9jGJ/L0rbmi6j+GynA5VLnUPlEiGEEEIIIYQQQoiL0jpR8cgECM1QudRDiqD1zpvGOg91lrc6IfmC7SMdHfflXlotDdBaKUs3qjw3xWHqJ722YiqSxUUraNnVnl5ZLYUO71S2pbBaakVeJknD1L4G/b5od524NjpM9d0pRZfLaRnlZzxdlK0gGq3ltrKZLi4KlUsjRN6Ey6gI9VaM+v1nQavMK3nrG0Ui03Y8Ii5waZon5Ul/oHtYM8ya2Ezm/a8DWZh1UadDURW1eekzeShDXihiO+qE6T7rova1XqOVhqJbXEdQuUQIIYQQQgghhBDiorWGTlCyJe0bVahcGnLyukqRB214XuuGDA62ge6Ydv+djktcga2VciD2yDShtSMJ0pEs7EcCA6ClTBzWNmruKw/jyE6ga2m2FK29dAvbVm9hQO/OoXJpCMmzYMmLcM+yjvJSB4R0At3fsiHH4hxAvt83/YTucqNNLpRKQEeKpXZFlu5vlNbe/3mmyG47VFIPjqK2kU5hW+oPdqMBLRst96tG632jCpVLhBBCCCGEEEIIIS5a2dDKTtxPwlC5NETkXWudl9WDvNcT6T185t2TWb8dYWulTsmLbB1lRsnlZdjvL4nc9LUE+Tjd51MEqyVD8F5z82w6gBZMvaeI7WA6sO30F61UG+USs8VF4eidEEIIIYQQQgghxEXbdtutXzzxxBN45zvfiT333BPj4+PYa6+9cMEFF6BWq4WO+9WvfoVXvepVGBsbw6JFi/C5z32ub2VKAy2XCk5RNNajtpLQCtYDKQJ9b6e0SkpF3sV7Ud4/g2YY5TyfdZfPtR/xlrqwWhrCJtkEYzCNJkV95tNhUO2E7RHQuo1bnO6fcumRRx6BUgpXXXUV9t57bzz88MM444wzsGXLFlx88cUAgI0bN+K4447DscceiyuvvBIPPfQQ/umf/gnbbbcd3vWud/WtbElQuVRgitLp8yL4s66vvNQDIa1gG23PIORIJ5cYxWdWxGxRRXbfyfrdmSW5eVZtFPL9ekZFe/RFVjABo+Ve2w1Ffra9gG1i8KhGDRBW8v4+ccIJJ+CEE07wPi9evBirV6/GFVdc4SmXrrvuOtRqNXzta19DpVLB/vvvj1WrVuELX/hCZsolLh8TQgghhBBCCCGEuJiA3kkb4FgQBbepqam+lGfDhg3YYYcdvM933nknXv3qV6NSqXjfHX/88Vi9ejWef/75vpShHVQuFQwthLflHaF1blYZilBfpD/w2bcnT30170ynrto1RSGKZymQJUXp29FyFuE9XoQy9ptcyEQh6UbcIcPSZvle9utg1Oti1GVxlpiA3q03x/V50aJFmJiY8Lbly5f3vCyPPvooLr30Urz73e/2vlu3bh3mz58fOs58XrduXc/LkAa6xRWIIgmWUX4JRGFdkDzD9jlYCiTGE8nT+yivbnJp6ih6TFb3kKfnmQd69hwGoBhK8+yCh6S9tSI3ibzKhG4YlXhMw/Cs+sGwP/e8o5QNJMRcUu6+NWvWYM6cOd731Wq15W+WLVuGiy66KPG6v/3tb7Hvvvt6n9euXYsTTjgBb3rTm3DGGWekLX4mULlECCGEEEIIIYQQ4uLEXGq9SGBiLs2ZMyekXErigx/8IE477bTEYxYvXuz9/9RTT+GYY47BEUccga985Suh4xYsWID169eHvjOfFyxYkKo8vYbKpYJAzXX3ZFl3XInJFvabZNg+u0dozfZFYplOuxi0JRPbcPHpVBaN0iMveoDvIMNowTQsz4YMMbYNLRMywtmdZ4ubO3cu5s6dm+rYtWvX4phjjsHBBx+MFStWQMqwomvJkiX46Ec/inq9jnK5DAC48cYb8eIXvxjbb799x2XrBXTkJkNPVi8vvjQJ6ZxgrJdutkGSh1gQWU008ijfspx09boNZt2uRp2ixTiJxqZh2yF5hW20M1hf2aJ1m4DeunPlUlrWrl2Lo48+GrvtthsuvvhiPPvss1i3bl0oltJb3/pWVCoVvPOd78Svf/1rfOtb38KXvvQlnHPOOX0rVztouUQIIYQQQgghhBDiopVKjLlkAnr3gxtvvBGPPvooHn30Uey6667h67rKxomJCfzv//4vli5dioMPPhg77bQTPv7xj+Nd73pX38rVjsIol173utdh1apVeOaZZ7D99tvj2GOPxUUXXYSdd94566KRGPJmitxPF5Y83SdxKNKKc5bkrZ/24rm1Oke/7zPu/INqh8HrDPJ55sE1MKt7b1WGTshD3xtGV5te0q5e8vAMWzHdsqUKFJ7T+89ruabLMPTTYQq2PmiyHGeMKqpRh0hw9NKNet+ufdppp7WNzQQAL3vZy/Dzn/+8b+XolMK4xR1zzDH49re/jdWrV+N73/seHnvsMfz93/991sUaGEUzec5j+eLqsBcbIUUmTynH+9mvsnCly0JeDNpVMOneRl0+FundUYQy5pG8uOj2gyK2h6KUMy3D1qZI7+lnPx22/tQNiS5x7kbCFMZy6QMf+ID3/+67745ly5bh5JNPDgWwIoQQQgghhBBCCJkOWtlt3OKoXIpSGOVSkOeeew7XXXcdjjjiiETF0tTUFKamprzPGzduHETxBsaoa5PJaJPUv4N9g6t96cmTuXqrMvTjeQ7SlS7pnP1qq4PKQBZ0k5vuNdL27zyQt/L0km7vbZTlbi/awyAsDgf5uyhp+neRXRKnSxbJKcjwkPZ5ZhVGoEgoZUNQudQRhXGLA4Bzzz0XM2fOxI477ognn3wSP/zhDxOPX758OSYmJrxt0aJFAyopIaTfsH8TMrywfxMyvLB/E0KKgGrUoeq11lsfYy4VFaF1durJZcuW4aKLLko85re//S323XdfAMCf//xnPPfcc/jjH/+IT3ziE5iYmMANN9wA0ULzGrcysmjRIqxftw5z5szp3Y0QQqbNxo0bMX/BAmzYsCFV/2T/JnHkdcV/OgxiFbvf98X+TYpA2r6W5cp+HuUB+zchw0un/XsY2LhxIyYmJlA56HQIq9LyOG3XUFu5YqTqph2ZusV98IMfbBsFffHixd7/O+20E3baaSe86EUvwkte8hIsWrQId911F5YsWRL722q1imq12ssiE0JyAvs3IcML+zchwwv7NyGkCGhlA4JucZ2QqXJp7ty5mDt3ble/VUoBQGjlox3GSGvTpk1dXZMQ0j9Mv+zWmJL9mwC0XOqWft8X+zcpArRccuj0/ti/CRleptu/i4yuTyYrkGy6xUUpREDvu+++G/feey+OPPJIbL/99njsscdw/vnnY6+99mpptRSH6Rx777NPv4pKCJkmmzZtwsTERFe/A9i/Cckz7N+EDC/s34QML9327yJSqVSwYMECrPvNt9seu2DBAlQqrV3nRo1MYy6l5aGHHsJZZ52FBx98EFu2bMHChQtxwgkn4GMf+xh22WWX1OdRSuGpp57C7NmzW8ZpGjTGz3zNmjX01ewQ1t30yFv9aa2xadMm7LzzzpCy81wD7N/DB+uve/JWd+zfJArrr3vyVnfs3yQK66978lZ30+3fRWVychK1Wq3tcZVKBWNjYwMoUTEohOXSAQccgFtuuWXa55FSYtddd+1BiXrPnDlzciFAigjrbnrkqf6msyLC/j28sP66J091x/5N4mD9dU+e6o79m8TB+uuePNXdqFgsBRkbG6PSqAtGR/1ICCGEEEIIIYQQQnoOlUuEEEIIIYQQQgghpGuoXMqYarWKCy64gClZu4B1Nz1Yf/2HdTw9WH/dw7rrP6zj6cH66x7WXf9hHU8P1l/3sO5IkSlEQG9CCCGEEEIIIYQQkk9ouUQIIYQQQgghhBBCuobKJUIIIYQQQgghhBDSNVQuEUIIIYQQQgghhJCuoXIpRzzxxBN45zvfiT333BPj4+PYa6+9cMEFF6BWq2VdtFxy+eWXY4899sDY2BgOO+ww3HPPPVkXKfcsX74cr3jFKzB79mzMmzcPJ598MlavXp11sUYC9u/OYP/uHPbv7GD/7gz2785h/84O9u/OYP/uHPZvMixQuZQjHnnkESilcNVVV+HXv/41vvjFL+LKK6/Ev/zLv2RdtNzxrW99C+eccw4uuOACPPDAA3j5y1+O448/Hs8880zWRcs1t99+O5YuXYq77roLN954I+r1Oo477jhs2bIl66INPezf6WH/7g727+xg/04P+3d3sH9nB/t3eti/u4P9mwwLzBaXcz7/+c/jiiuuwB/+8Iesi5IrDjvsMLziFa/AZZddBgBQSmHRokV43/veh2XLlmVcuuLw7LPPYt68ebj99tvx6le/OuvijBzs3/Gwf/cG9u9sYf+Oh/27N7B/Zwv7dzzs372B/ZsUFVou5ZwNGzZghx12yLoYuaJWq+H+++/Hscce630npcSxxx6LO++8M8OSFY8NGzYAANtYRrB/N8P+3TvYv7OF/bsZ9u/ewf6dLezfzbB/9w72b1JUqFzKMY8++iguvfRSvPvd7866KLniz3/+M2zbxvz580Pfz58/H+vWrcuoVMVDKYWzzz4br3zlK/HSl7406+KMHOzf8bB/9wb272xh/46H/bs3sH9nC/t3POzfvYH9mxQZKpcGwLJlyyCESNweeeSR0G/Wrl2LE044AW9605twxhlnZFRyMswsXboUDz/8ML75zW9mXZRCw/5N8gj7d29g/yZ5hP27N7B/kzzC/k2KTCnrAowCH/zgB3HaaaclHrN48WLv/6eeegrHHHMMjjjiCHzlK1/pc+mKx0477QTLsrB+/frQ9+vXr8eCBQsyKlWxOPPMM3HDDTfgjjvuwK677pp1cQoN+3dvYf+ePuzfvYP9u7ewf08f9u/ewf7dW9i/pw/7Nyk6VC4NgLlz52Lu3Lmpjl27di2OOeYYHHzwwVixYgWkpHFZlEqlgoMPPhg333wzTj75ZACOCenNN9+MM888M9vC5RytNd73vvfh+9//Pm677TbsueeeWRep8LB/9xb27+5h/+497N+9hf27e9i/ew/7d29h/+4e9m8yLFC5lCPWrl2Lo48+GrvvvjsuvvhiPPvss94+avzDnHPOOTj11FNxyCGH4NBDD8Ull1yCLVu24PTTT8+6aLlm6dKluP766/HDH/4Qs2fP9nzgJyYmMD4+nnHphhv27/Swf3cH+3d2sH+nh/27O9i/s4P9Oz3s393B/k2GBk1yw4oVKzSA2I00c+mll+rddttNVyoVfeihh+q77ror6yLlnlbta8WKFVkXbehh/+4M9u/OYf/ODvbvzmD/7hz27+xg/+4M9u/OYf8mw4LQWuveq6wIIYQQQgghhBBCyChAh2FCCCGEEEIIIYQQ0jVULhFCCCGEEEIIIYSQrqFyiRBCCCGEEEIIIYR0DZVLhBBCCCGEEEIIIaRrqFwihBBCCCGEEEIIIV1D5RIhhBBCCCGEEEII6RoqlwghhBBCCCGEEEJI11C5RAghhBBCCCGEEEK6hsolQgghhBBCCCGEENI1VC4RQgghhBBCCCGEkK6hcokQQgghhBBCCCGEdA2VS6RQPPvss1iwYAE+85nPeN/93//9HyqVCm6++eYMS0YImS7s34QML+zfhAwv7N+EEAAQWmuddSEI6YQf//jHOPnkk/F///d/ePGLX4wDDzwQr3/96/GFL3wh66IRQqYJ+zchwwv7NyHDC/s3IYTKJVJIli5diptuugmHHHIIHnroIdx7772oVqtZF4sQ0gPYvwkZXti/CRle2L8JGW2oXCKFZNu2bXjpS1+KNWvW4P7778cBBxyQdZEIIT2C/ZuQ4YX9m5Dhhf2bkNGGMZdIIXnsscfw1FNPQSmFJ554IuviEEJ6CPs3IcML+zchwwv7NyGjDS2XSOGo1Wo49NBDceCBB+LFL34xLrnkEjz00EOYN29e1kUjhEwT9m9Chhf2b0KGF/ZvQgiVS6RwfPjDH8Z3v/tdPPjgg5g1axaOOuooTExM4IYbbsi6aISQacL+Tcjwwv5NyPDC/k0IoVscKRS33XYbLrnkEnzjG9/AnDlzIKXEN77xDfz85z/HFVdckXXxCCHTgP2bkOGF/ZuQ4YX9mxAC0HKJEEIIIYQQQgghhEwDWi4RQgghhBBCCCGEkK6hcokQQgghhBBCCCGEdA2VS4QQQgghhBBCCCGka6hcIoQQQgghhBBCCCFdQ+USIYQQQgghhBBCCOkaKpcIIYQQQgghhBBCSNdQuUQIIYQQQgghhBBCuobKJUIIIYQQQgghhBDSNVQuEUIIIYQQQgghhJCuoXKJEEIIIYQQQgghhHQNlUuEEEIIIYQQQgghpGuoXCKEEEIIIYQQQgghXfP/A1ftvnMg88jSAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1300x300 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "field_time_data = sim_data[\"field_time\"]\n",
    "\n",
    "# select the data and downsample and window the time coordinate to reduce number of plots.\n",
    "time_data = field_time_data.Ez.isel(y=0).sel(t=slice(1e-14, 5e-14, 1))\n",
    "\n",
    "time_data.plot(x=\"x\", y=\"z\", col=\"t\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4104ee6d-8118-4498-a943-00b4c1b48d4a",
   "metadata": {},
   "source": [
    "## Export data to csv\n",
    "\n",
    "You can also export [xarray.DataArray](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.html) to csv file using its [to_dataframe()](https://docs.xarray.dev/en/stable/generated/xarray.DataArray.to_dataframe.html) method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "6c4e1eab-9ff3-47bd-bd45-b66e428d238a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:22.656296Z",
     "iopub.status.busy": "2023-02-03T04:14:22.656121Z",
     "iopub.status.idle": "2023-02-03T04:14:22.990451Z",
     "shell.execute_reply": "2023-02-03T04:14:22.990035Z"
    }
   },
   "outputs": [],
   "source": [
    "df = time_data.to_dataframe(\"value\")\n",
    "df.to_csv(\"./data/time_data.csv\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff38ffe5-b6d1-4de2-a626-0a7aaebfa3dd",
   "metadata": {},
   "source": [
    "It will stack the array coordinates to generate a 2D table. Import the csv file to check the content:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "329574aa-ce1b-4d09-9a21-556bd7c795ea",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T04:14:22.992800Z",
     "iopub.status.busy": "2023-02-03T04:14:22.992635Z",
     "iopub.status.idle": "2023-02-03T04:14:23.056998Z",
     "shell.execute_reply": "2023-02-03T04:14:23.056598Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>z</th>\n",
       "      <th>t</th>\n",
       "      <th>y</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-2.929245</td>\n",
       "      <td>-3.084856</td>\n",
       "      <td>1.208153e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-2.929245</td>\n",
       "      <td>-3.084856</td>\n",
       "      <td>2.416306e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-2.929245</td>\n",
       "      <td>-3.084856</td>\n",
       "      <td>3.624459e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-2.929245</td>\n",
       "      <td>-3.084856</td>\n",
       "      <td>4.832612e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-2.929245</td>\n",
       "      <td>-3.038042</td>\n",
       "      <td>1.208153e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109643</th>\n",
       "      <td>2.896226</td>\n",
       "      <td>3.038690</td>\n",
       "      <td>4.832612e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109644</th>\n",
       "      <td>2.896226</td>\n",
       "      <td>3.085504</td>\n",
       "      <td>1.208153e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109645</th>\n",
       "      <td>2.896226</td>\n",
       "      <td>3.085504</td>\n",
       "      <td>2.416306e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109646</th>\n",
       "      <td>2.896226</td>\n",
       "      <td>3.085504</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109647</th>\n",
       "      <td>2.896226</td>\n",
       "      <td>3.085504</td>\n",
       "      <td>4.832612e-14</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>109648 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               x         z             t    y  value\n",
       "0      -2.929245 -3.084856  1.208153e-14  0.0    0.0\n",
       "1      -2.929245 -3.084856  2.416306e-14  0.0    0.0\n",
       "2      -2.929245 -3.084856  3.624459e-14  0.0    0.0\n",
       "3      -2.929245 -3.084856  4.832612e-14  0.0    0.0\n",
       "4      -2.929245 -3.038042  1.208153e-14  0.0    0.0\n",
       "...          ...       ...           ...  ...    ...\n",
       "109643  2.896226  3.038690  4.832612e-14  0.0    0.0\n",
       "109644  2.896226  3.085504  1.208153e-14  0.0    0.0\n",
       "109645  2.896226  3.085504  2.416306e-14  0.0    0.0\n",
       "109646  2.896226  3.085504  3.624459e-14  0.0    0.0\n",
       "109647  2.896226  3.085504  4.832612e-14  0.0    0.0\n",
       "\n",
       "[109648 rows x 5 columns]"
      ]
     },
     "metadata": {},
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    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_csv(\"./data/time_data.csv\")\n",
    "display(df)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f52001cc",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Conclusion\n",
    "\n",
    "This hopefully gives some sense of what kind of data post processing and visualization can be done in Tidy3D.\n",
    "\n",
    "For more detailed information and reference, the best places to check out are\n",
    "\n",
    "* API reference for [SimulationData](https://docs.flexcompute.com/en/v1.9.0rc2/_autosummary/tidy3d.SimulationData.html).\n",
    "\n",
    "* [Xarray documentation](http://xarray.pydata.org)."
   ]
  }
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          "text/html": "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">% done (field decay = 6.16e-06) <span style=\"color: #f92672; text-decoration-color: #f92672\">━━━━╸</span><span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\"> 12%</span> <span style=\"color: #008080; text-decoration-color: #008080\">-:--:--</span>\n% done (field decay = 6.16e-06) <span style=\"color: #f92672; text-decoration-color: #f92672\">━━━━╸</span><span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\"> 12%</span> <span style=\"color: #008080; text-decoration-color: #008080\">-:--:--</span></pre>\n",
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