{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Parameter scan\n",
    "\n",
    "<img src=\"img/splitter.png\" alt=\"diagram\" width=\"400\"/>\n",
    "\n",
    "Note: the cost of running the entire notebook is larger than 1 FlexCredit.\n",
    "\n",
    "In this notebook, we will show an example of using tidy3d to evaluate device performance over a set of many design parameters.\n",
    "\n",
    "This example will also provide a walkthrough of Tidy3D's [Job](../_autosummary/tidy3d.web.container.Job.html) and [Batch](../_autosummary/tidy3d.web.container.Batch.html) features for managing both individual simulations and sets of simulations.\n",
    "\n",
    "> Note: as of version `1.8`, the [tidy3d.web.run_async](../_autosummary/tidy3d.web.run_async.html) function handles the same functionality as the batch, with a simpler syntax. As such, it could be a good alternative for parameter scan depending on how your script is set up.\n",
    "\n",
    "For demonstration, we look at the splitting ratio of a directional coupler as we vary the coupling length between two waveguides. The sidewall of the waveguides is slanted, deviating from the vertical direction by `sidewall_angle`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# standard python imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import gdstk\n",
    "\n",
    "# tidy3D imports\n",
    "import tidy3d as td\n",
    "from tidy3d import web\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "First we set up some global parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# wavelength / frequency\n",
    "lambda0 = 1.550  # all length scales in microns\n",
    "freq0 = td.constants.C_0 / lambda0\n",
    "fwidth = freq0 / 10\n",
    "\n",
    "# Permittivity of waveguide and substrate\n",
    "wg_n = 3.48\n",
    "sub_n = 1.45\n",
    "mat_wg = td.Medium(permittivity=wg_n**2)\n",
    "mat_sub = td.Medium(permittivity=sub_n**2)\n",
    "\n",
    "# Waveguide dimensions\n",
    "\n",
    "# Waveguide height\n",
    "wg_height = 0.22\n",
    "# Waveguide width\n",
    "wg_width = 0.45\n",
    "# Waveguide separation in the beginning/end\n",
    "wg_spacing_in = 8\n",
    "# Reference plane where the cross section of the device is defined\n",
    "reference_plane = \"bottom\"\n",
    "# Angle of the sidewall deviating from the vertical ones, positive values for the base larger than the top\n",
    "sidewall_angle = np.pi / 6\n",
    "# Total device length along propagation direction\n",
    "device_length = 100\n",
    "# Length of the bend region\n",
    "bend_length = 16\n",
    "# space between waveguide and PML\n",
    "pml_spacing = 1\n",
    "# resolution control: minimum number of grid cells per wavelength in each material\n",
    "grid_cells_per_wvl = 16\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define waveguide bends and coupler\n",
    "\n",
    "Here is where we define our directional coupler shape programmatically in terms of the geometric parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def tanh_interp(max_arg):\n",
    "    \"\"\"Interpolator for tanh with adjustable extension\"\"\"\n",
    "    scale = 1 / np.tanh(max_arg)\n",
    "    return lambda u: 0.5 * (1 + scale * np.tanh(max_arg * (u * 2 - 1)))\n",
    "\n",
    "\n",
    "def make_coupler(\n",
    "    length,\n",
    "    wg_spacing_in,\n",
    "    wg_width,\n",
    "    wg_spacing_coup,\n",
    "    coup_length,\n",
    "    bend_length,\n",
    "    npts_bend=30,\n",
    "):\n",
    "    \"\"\"Make an integrated coupler using the gdstk RobustPath object.\"\"\"\n",
    "    # bend interpolator\n",
    "    interp = tanh_interp(3)\n",
    "    delta = wg_width + wg_spacing_coup - wg_spacing_in\n",
    "    offset = lambda u: wg_spacing_in + interp(u) * delta\n",
    "\n",
    "    coup = gdstk.RobustPath(\n",
    "        (-0.5 * length, 0),\n",
    "        (wg_width, wg_width),\n",
    "        wg_spacing_in,\n",
    "        simple_path=True,\n",
    "        layer=1,\n",
    "        datatype=[0, 1],\n",
    "    )\n",
    "    coup.segment((-0.5 * coup_length - bend_length, 0))\n",
    "    coup.segment(\n",
    "        (-0.5 * coup_length, 0),\n",
    "        offset=[lambda u: -0.5 * offset(u), lambda u: 0.5 * offset(u)],\n",
    "    )\n",
    "    coup.segment((0.5 * coup_length, 0))\n",
    "    coup.segment(\n",
    "        (0.5 * coup_length + bend_length, 0),\n",
    "        offset=[lambda u: -0.5 * offset(1 - u), lambda u: 0.5 * offset(1 - u)],\n",
    "    )\n",
    "    coup.segment((0.5 * length, 0))\n",
    "    return coup\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Simulation and Submit Job\n",
    "\n",
    "The following function creates a tidy3d simulation object for a set of design parameters.\n",
    "\n",
    "Note that the simulation has not been run yet, just created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def make_sim(coup_length, wg_spacing_coup, domain_field=False):\n",
    "    \"\"\"Make a simulation with a given length of the coupling region and\n",
    "    distance between the waveguides in that region. If ``domain_field``\n",
    "    is True, a 2D in-plane field monitor will be added.\n",
    "    \"\"\"\n",
    "\n",
    "    # Geometry must be placed in GDS cells to import into Tidy3D\n",
    "    coup_cell = gdstk.Cell(\"Coupler\")\n",
    "\n",
    "    substrate = gdstk.rectangle(\n",
    "        (-device_length / 2, -wg_spacing_in / 2 - 10),\n",
    "        (device_length / 2, wg_spacing_in / 2 + 10),\n",
    "        layer=0,\n",
    "    )\n",
    "    coup_cell.add(substrate)\n",
    "\n",
    "    # Add the coupler to a gdstk cell\n",
    "    gds_coup = make_coupler(\n",
    "        device_length,\n",
    "        wg_spacing_in,\n",
    "        wg_width,\n",
    "        wg_spacing_coup,\n",
    "        coup_length,\n",
    "        bend_length,\n",
    "    )\n",
    "    coup_cell.add(gds_coup)\n",
    "\n",
    "    # Substrate\n",
    "    (oxide_geo,) = td.PolySlab.from_gds(\n",
    "        gds_cell=coup_cell,\n",
    "        gds_layer=0,\n",
    "        gds_dtype=0,\n",
    "        slab_bounds=(-10, 0),\n",
    "        reference_plane=reference_plane,\n",
    "        axis=2,\n",
    "    )\n",
    "\n",
    "    oxide = td.Structure(geometry=oxide_geo, medium=mat_sub)\n",
    "\n",
    "    # Waveguides (import all datatypes if gds_dtype not specified)\n",
    "    coupler1_geo, coupler2_geo = td.PolySlab.from_gds(\n",
    "        gds_cell=coup_cell,\n",
    "        gds_layer=1,\n",
    "        slab_bounds=(0, wg_height),\n",
    "        sidewall_angle=sidewall_angle,\n",
    "        reference_plane=reference_plane,\n",
    "        axis=2,\n",
    "    )\n",
    "\n",
    "    coupler1 = td.Structure(geometry=coupler1_geo, medium=mat_wg)\n",
    "\n",
    "    coupler2 = td.Structure(geometry=coupler2_geo, medium=mat_wg)\n",
    "\n",
    "    # Simulation size along propagation direction\n",
    "    sim_length = 2 + 2 * bend_length + coup_length\n",
    "\n",
    "    # Spacing between waveguides and PML\n",
    "    sim_size = [\n",
    "        sim_length,\n",
    "        wg_spacing_in + wg_width + 2 * pml_spacing,\n",
    "        wg_height + 2 * pml_spacing,\n",
    "    ]\n",
    "\n",
    "    # source\n",
    "    src_pos = -sim_length / 2 + 0.5\n",
    "    msource = td.ModeSource(\n",
    "        center=[src_pos, wg_spacing_in / 2, wg_height / 2],\n",
    "        size=[0, 3, 2],\n",
    "        source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n",
    "        direction=\"+\",\n",
    "        mode_spec=td.ModeSpec(),\n",
    "        mode_index=0,\n",
    "    )\n",
    "\n",
    "    mon_in = td.ModeMonitor(\n",
    "        center=[(src_pos + 0.5), wg_spacing_in / 2, wg_height / 2],\n",
    "        size=[0, 3, 2],\n",
    "        freqs=[freq0],\n",
    "        mode_spec=td.ModeSpec(),\n",
    "        name=\"in\",\n",
    "    )\n",
    "    mon_ref_bot = td.ModeMonitor(\n",
    "        center=[(src_pos + 0.5), -wg_spacing_in / 2, wg_height / 2],\n",
    "        size=[0, 3, 2],\n",
    "        freqs=[freq0],\n",
    "        mode_spec=td.ModeSpec(),\n",
    "        name=\"refect_bottom\",\n",
    "    )\n",
    "    mon_top = td.ModeMonitor(\n",
    "        center=[-(src_pos + 0.5), wg_spacing_in / 2, wg_height / 2],\n",
    "        size=[0, 3, 2],\n",
    "        freqs=[freq0],\n",
    "        mode_spec=td.ModeSpec(),\n",
    "        name=\"top\",\n",
    "    )\n",
    "    mon_bot = td.ModeMonitor(\n",
    "        center=[-(src_pos + 0.5), -wg_spacing_in / 2, wg_height / 2],\n",
    "        size=[0, 3, 2],\n",
    "        freqs=[freq0],\n",
    "        mode_spec=td.ModeSpec(),\n",
    "        name=\"bottom\",\n",
    "    )\n",
    "    monitors = [mon_in, mon_ref_bot, mon_top, mon_bot]\n",
    "\n",
    "    if domain_field == True:\n",
    "        domain_monitor = td.FieldMonitor(\n",
    "            center=[0, 0, wg_height / 2],\n",
    "            size=[td.inf, td.inf, 0],\n",
    "            freqs=[freq0],\n",
    "            name=\"field\",\n",
    "        )\n",
    "        monitors.append(domain_monitor)\n",
    "\n",
    "    # initialize the simulation\n",
    "    sim = td.Simulation(\n",
    "        size=sim_size,\n",
    "        grid_spec=td.GridSpec.auto(min_steps_per_wvl=grid_cells_per_wvl),\n",
    "        structures=[oxide, coupler1, coupler2],\n",
    "        sources=[msource],\n",
    "        monitors=monitors,\n",
    "        run_time=50 / fwidth,\n",
    "        boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    "    )\n",
    "\n",
    "    return sim\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inspect Simulation\n",
    "\n",
    "Let's create and inspect a single simulation to make sure it was defined correctly before doing the full scan. The sidewalls of the waveguides deviate from the vertical direction by 30 degree. We also add an in-plane field monitor to have a look at the fields evolution in this one simulation. We will not use such a monitor in the batch to avoid storing unnecesarrily large amounts of data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Length of the coupling region\n",
    "coup_length = 10\n",
    "\n",
    "# Waveguide separation in the coupling region\n",
    "wg_spacing_coup = 0.10\n",
    "\n",
    "sim = make_sim(coup_length, wg_spacing_coup, domain_field=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualize geometry\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(14, 4))\n",
    "sim.plot(z=wg_height / 2 + 0.01, ax=ax1)\n",
    "sim.plot(x=0.1, ax=ax2)\n",
    "ax2.set_xlim([-3, 3])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create and Submit Job\n",
    "\n",
    "The [Job](../_autosummary/tidy3d.web.container.Job.html) object provides an interface for managing simulations.\n",
    "\n",
    "`job = Job(simulation)` will create a job and upload the simulation to our server to run.\n",
    "\n",
    "Then, one may call various methods of `job` to monitor progress, download results, and get information.\n",
    "\n",
    "For more information, refer to the API reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "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\">[15:22:11] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'CouplerVerify'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'fdve-a7d65229-ccfd-4276-b1c8-472241acd3e6v1'</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#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[15:22:11]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'CouplerVerify'\u001b[0m with task_id \u001b[32m'fdve-a7d65229-ccfd-4276-b1c8-472241acd3e6v1'\u001b[0m.   \u001b]8;id=492261;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=281388;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dc6c8960379b40869b44c730c0b254a1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
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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\"></pre>\n"
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
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    {
     "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\">[15:22:14] </span>status = queued                                                                            <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#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[15:22:14]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                                            \u001b]8;id=995491;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=577142;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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     "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\">[15:22:19] </span>status = preprocess                                                                        <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#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[15:22:19]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                                        \u001b]8;id=974119;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=45908;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#263\u001b\\\u001b[2m263\u001b[0m\u001b]8;;\u001b\\\n"
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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\"></pre>\n"
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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\">[15:22:26] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.570</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed FlexCredit cost <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#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>after a simulation run.                                                                    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
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       "\u001b[2;36m[15:22:26]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.570\u001b[0m. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost \u001b]8;id=577282;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=631706;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mafter a simulation run.                                                                    \u001b[2m             \u001b[0m\n"
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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>starting up solver                                                                         <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#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                                         \u001b]8;id=140147;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=255226;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
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       "\u001b[2;36m[15:22:27]\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                                             \u001b]8;id=879217;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=877536;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
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       "\u001b[2;36m[15:24:16]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                                           \u001b]8;id=988568;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=364577;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#313\u001b\\\u001b[2m313\u001b[0m\u001b]8;;\u001b\\\n"
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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>status = postprocess                                                                       <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#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                                       \u001b]8;id=570235;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=990096;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#330\u001b\\\u001b[2m330\u001b[0m\u001b]8;;\u001b\\\n"
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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\">[15:24:36] </span>status = success                                                                           <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#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[15:24:36]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                                           \u001b]8;id=774772;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=587136;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#337\u001b\\\u001b[2m337\u001b[0m\u001b]8;;\u001b\\\n"
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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\">[15:24:50] </span>loading SimulationData from data/sim_data.hdf5                                             <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#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
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       "\u001b[2;36m[15:24:50]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/sim_data.hdf5                                             \u001b]8;id=283475;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=234352;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
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   ],
   "source": [
    "# create job, upload sim to server to begin running\n",
    "job = web.Job(simulation=sim, task_name=\"CouplerVerify\", verbose=True)\n",
    "\n",
    "# download the results and load them into a simulation\n",
    "sim_data = job.run(path=\"data/sim_data.hdf5\")\n"
   ]
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   "source": [
    "## Postprocessing\n",
    "\n",
    "The following function takes a completed simulation (with data loaded into it) and computes the quantities of interest.\n",
    "\n",
    "For this case, we measure both the total transmission in the right ports and also the ratio of power between the top and bottom ports."
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
    "tags": []
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   "source": [
    "def measure_transmission(sim_data):\n",
    "    \"\"\"Constructs a \"row\" of the scattering matrix when sourced from top left port\"\"\"\n",
    "\n",
    "    input_amp = sim_data[\"in\"].amps.sel(direction=\"+\")\n",
    "\n",
    "    amps = np.zeros(4, dtype=complex)\n",
    "    directions = (\"-\", \"-\", \"+\", \"+\")\n",
    "    for i, (monitor, direction) in enumerate(\n",
    "        zip(sim_data.simulation.monitors[:4], directions)\n",
    "    ):\n",
    "        amp = sim_data[monitor.name].amps.sel(direction=direction)\n",
    "        amp_normalized = amp / input_amp\n",
    "        amps[i] = np.squeeze(amp_normalized.values)\n",
    "\n",
    "    return amps\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mode amplitudes in each port:\n",
      "\n",
      "\tmonitor     = \"in\"\n",
      "\tamplitude^2 = 0.00\n",
      "\tphase       = 0.78 (rad)\n",
      "\n",
      "\tmonitor     = \"refect_bottom\"\n",
      "\tamplitude^2 = 0.00\n",
      "\tphase       = -2.37 (rad)\n",
      "\n",
      "\tmonitor     = \"top\"\n",
      "\tamplitude^2 = 0.95\n",
      "\tphase       = -0.37 (rad)\n",
      "\n",
      "\tmonitor     = \"bottom\"\n",
      "\tamplitude^2 = 0.04\n",
      "\tphase       = 1.20 (rad)\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# monitor and test out the measure_transmission function the results of the single run\n",
    "amps_arms = measure_transmission(sim_data)\n",
    "print(\"mode amplitudes in each port:\\n\")\n",
    "for amp, monitor in zip(amps_arms, sim_data.simulation.monitors[:-1]):\n",
    "    print(f'\\tmonitor     = \"{monitor.name}\"')\n",
    "    print(f\"\\tamplitude^2 = {abs(amp)**2:.2f}\")\n",
    "    print(f\"\\tphase       = {(np.angle(amp)):.2f} (rad)\\n\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "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\">[15:24:50] </span>WARNING: <span style=\"color: #008000; text-decoration-color: #008000\">'freq'</span> supplied to <span style=\"color: #008000; text-decoration-color: #008000\">'plot_field'</span>, frequency selection key renamed to <span style=\"color: #008000; text-decoration-color: #008000\">'f'</span> and <span style=\"color: #008000; text-decoration-color: #008000\">'freq'</span>    <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>will error in future release, please update your local script to use <span style=\"color: #008000; text-decoration-color: #008000\">'f=value'</span>.                <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[15:24:50]\u001b[0m\u001b[2;36m \u001b[0mWARNING: \u001b[32m'freq'\u001b[0m supplied to \u001b[32m'plot_field'\u001b[0m, frequency selection key renamed to \u001b[32m'f'\u001b[0m and \u001b[32m'freq'\u001b[0m    \u001b]8;id=849023;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=362310;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mwill error in future release, please update your local script to use \u001b[32m'\u001b[0m\u001b[32mf\u001b[0m\u001b[32m=\u001b[0m\u001b[32mvalue\u001b[0m\u001b[32m'\u001b[0m.                \u001b[2m         \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1600x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(16, 3))\n",
    "sim_data.plot_field(\"field\", \"Ey\", z=wg_height / 2, freq=freq0, ax=ax)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1D Parameter Scan\n",
    "\n",
    "Now we will scan through the coupling length parameter to see the effect on splitting ratio.\n",
    "\n",
    "To do this, we will create a list of simulations corresponding to each parameter combination.\n",
    "\n",
    "We will use this list to create a [Batch](../_autosummary/tidy3d.web.container.Batch.html) object, which has similar functionality to [Job](../_autosummary/tidy3d.web.container.Job.html) but allows one to manage a *set* of jobs.\n",
    "\n",
    "First, we create arrays to store the input and output values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# create variables to store parameters, simulation information, results\n",
    "Nl = 11\n",
    "\n",
    "ls = np.linspace(5, 12, Nl)\n",
    "split_ratios = np.zeros(Nl)\n",
    "efficiencies = np.zeros(Nl)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Batch\n",
    "\n",
    "We now create our list of simulations and use them to initialize a [Batch](../_autosummary/tidy3d.web.container.Batch.html).\n",
    "\n",
    "For more information, refer to the API reference."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "tags": []
   },
   "outputs": [
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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\">[15:24:55] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'l=6.40'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'fdve-f07e684d-d28f-454f-b21d-4e81bfd4a40dv1'</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#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
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       "\u001b[2;36m[15:24:55]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m6\u001b[0m\u001b[32m.40'\u001b[0m with task_id \u001b[32m'fdve-f07e684d-d28f-454f-b21d-4e81bfd4a40dv1'\u001b[0m.          \u001b]8;id=971707;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=165884;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[2;36m[15:24:57]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m7\u001b[0m\u001b[32m.10'\u001b[0m with task_id \u001b[32m'fdve-b7c3ea8a-6c5f-4d38-af2f-ce934ddd0e4cv1'\u001b[0m.          \u001b]8;id=517453;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=143695;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
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       "\u001b[2;36m[15:24:58]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m7\u001b[0m\u001b[32m.80'\u001b[0m with task_id \u001b[32m'fdve-6e76b39b-6876-4e55-9afc-4698f31d3010v1'\u001b[0m.          \u001b]8;id=889486;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=580963;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[2;36m[15:25:00]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m8\u001b[0m\u001b[32m.50'\u001b[0m with task_id \u001b[32m'fdve-dcb18d30-ee8d-42b8-87eb-e8a663212ce5v1'\u001b[0m.          \u001b]8;id=39833;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=924060;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
      ],
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       "\u001b[2;36m[15:25:01]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m9\u001b[0m\u001b[32m.20'\u001b[0m with task_id \u001b[32m'fdve-24f87506-a26f-43d6-8647-d69935aa1472v1'\u001b[0m.          \u001b]8;id=544047;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=816508;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[15:25:02]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m9\u001b[0m\u001b[32m.90'\u001b[0m with task_id \u001b[32m'fdve-c278ed7f-1df6-44ba-85de-436c6c8ac503v1'\u001b[0m.          \u001b]8;id=516042;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=895572;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
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      "text/plain": [
       "\u001b[2;36m[15:25:04]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m10\u001b[0m\u001b[32m.60'\u001b[0m with task_id \u001b[32m'fdve-ffdd9e10-457c-4a17-8792-6c3eaa51badev1'\u001b[0m.         \u001b]8;id=201188;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=253611;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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     "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\">\n",
       "</pre>\n"
      ],
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       "\n"
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     "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\">[15:25:05] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'l=11.30'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'fdve-5751c516-c108-4818-8a66-90856cba8317v1'</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#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[15:25:05]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m11\u001b[0m\u001b[32m.30'\u001b[0m with task_id \u001b[32m'fdve-5751c516-c108-4818-8a66-90856cba8317v1'\u001b[0m.         \u001b]8;id=911516;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=702054;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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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\"></pre>\n"
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      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
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     "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\">\n",
       "</pre>\n"
      ],
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       "\n"
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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\">[15:25:06] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'l=12.00'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'fdve-5fd146c7-b302-4276-93e5-53e75ba63ba7v1'</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#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[15:25:06]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32ml\u001b[0m\u001b[32m=\u001b[0m\u001b[32m12\u001b[0m\u001b[32m.00'\u001b[0m with task_id \u001b[32m'fdve-5fd146c7-b302-4276-93e5-53e75ba63ba7v1'\u001b[0m.         \u001b]8;id=839157;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=939599;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n"
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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\"></pre>\n"
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       "</pre>\n"
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      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
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   ],
   "source": [
    "# submit all jobs\n",
    "sims = {f\"l={l:.2f}\": make_sim(l, wg_spacing_coup) for l in ls}\n",
    "batch = web.Batch(simulations=sims, verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monitor Batch\n",
    "\n",
    "Here we can perform real-time monitoring of how many of the jobs in the batch have completed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "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\">[15:25:15] </span>Started working on Batch.                                                               <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#402\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">402</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[15:25:15]\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch.                                                               \u001b]8;id=55720;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001b\\\u001b[2mcontainer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=860774;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#402\u001b\\\u001b[2m402\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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     "metadata": {},
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    },
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     "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\">[15:29:36] </span>Batch complete.                                                                         <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">container.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#436\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">436</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[15:29:36]\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                                         \u001b]8;id=651710;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001b\\\u001b[2mcontainer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=480946;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/container.py#436\u001b\\\u001b[2m436\u001b[0m\u001b]8;;\u001b\\\n"
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       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "batch_results = batch.run(path_dir=\"data\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load and visualize Results\n",
    "\n",
    "Finally, we can compute the output quantities and load them into the arrays we created initally.\n",
    "\n",
    "Then we may plot the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
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       "Output()"
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     "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\"></pre>\n"
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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\">\n",
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       "\n"
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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\">[15:29:39] </span>loading SimulationData from data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f8553594-57cd-4b0a-8102-1cd3df134924</span>v1.hdf5          <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#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[15:29:39]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/fdve-\u001b[93mf8553594-57cd-4b0a-8102-1cd3df134924\u001b[0mv1.hdf5          \u001b]8;id=369296;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=457197;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
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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\"></pre>\n"
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     },
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    {
     "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\">\n",
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      ],
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       "\n"
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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\">[15:29:41] </span>loading SimulationData from data/fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">faa42847-8ed7-4f39-974e-820f6b44a6e4</span>v1.hdf5          <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#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[15:29:41]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/fdve-\u001b[93mfaa42847-8ed7-4f39-974e-820f6b44a6e4\u001b[0mv1.hdf5          \u001b]8;id=277337;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=256406;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
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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\"></pre>\n"
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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\">\n",
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       "</pre>\n"
      ],
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       "\u001b[2;36m[15:29:42]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/fdve-\u001b[93mf07e684d-d28f-454f-b21d-4e81bfd4a40d\u001b[0mv1.hdf5          \u001b]8;id=768296;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=416775;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
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      ],
      "text/plain": [
       "\u001b[2;36m[15:29:57]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/fdve-\u001b[93m5fd146c7-b302-4276-93e5-53e75ba63ba7\u001b[0mv1.hdf5          \u001b]8;id=536633;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=454860;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(4, 11)\n",
      "[[ 9.32660088e-03-7.68083873e-04j -4.59595367e-04+2.69994380e-03j\n",
      "   8.37040903e-03+8.20768240e-04j  2.37986526e-03-3.87142288e-03j\n",
      "   4.97633888e-03+9.84196707e-03j  6.30758817e-03-4.15473485e-03j\n",
      "   1.71191510e-03+3.41521925e-03j  6.82371318e-03+2.25454434e-04j\n",
      "   1.66651459e-03+1.52869562e-03j  7.04234980e-03+5.27028750e-04j\n",
      "   1.90538505e-03-2.87642868e-03j]\n",
      " [-7.53013301e-03+1.51040665e-03j  3.56804163e-03-3.22005295e-03j\n",
      "  -2.63847220e-03-2.54007332e-03j -1.24888326e-03-9.15337392e-04j\n",
      "  -1.08607331e-03-8.01508908e-03j -2.07632115e-03+2.71375464e-03j\n",
      "   1.76179969e-03-8.09665204e-03j -4.14957609e-03+1.17583460e-03j\n",
      "   2.55484244e-03-2.11666514e-03j -2.59056027e-03-7.47507198e-03j\n",
      "   5.47408845e-04+3.76850561e-03j]\n",
      " [ 4.47049937e-01+4.22592826e-01j  6.77077433e-01-2.61317135e-01j\n",
      "   2.84107866e-02-8.19598010e-01j -8.13541567e-01-3.74902932e-01j\n",
      "  -7.02605331e-01+6.40683534e-01j  3.29485337e-01+9.27071505e-01j\n",
      "   9.91291660e-01+6.20715656e-02j  4.60259499e-01-8.64875357e-01j\n",
      "  -5.90996284e-01-7.34227731e-01j -8.50786816e-01+2.35290285e-01j\n",
      "  -9.93543887e-02+7.95952043e-01j]\n",
      " [ 5.36463307e-01-5.62986316e-01j -2.40941041e-01-6.31690878e-01j\n",
      "  -5.57454361e-01-2.16363298e-02j -1.80201173e-01+3.86478464e-01j\n",
      "   1.90802101e-01+2.11088069e-01j  1.28264763e-01-4.50723041e-02j\n",
      "  -9.51535635e-04+1.64265730e-02j  1.47629949e-01+7.87643978e-02j\n",
      "   2.45271423e-01-1.97499804e-01j -1.21816572e-01-4.38475083e-01j\n",
      "  -5.80485303e-01-7.11220501e-02j]]\n"
     ]
    }
   ],
   "source": [
    "amps_batch = []\n",
    "for task_name, sim_data in batch_results.items():\n",
    "    amps_arms_i = np.array(measure_transmission(sim_data))\n",
    "    amps_batch.append(amps_arms_i)\n",
    "amps_batch = np.stack(amps_batch, axis=1)\n",
    "print(amps_batch.shape)  # (4, Nl)\n",
    "print(amps_batch)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "powers = abs(amps_batch) ** 2\n",
    "power_top = powers[2]\n",
    "power_bot = powers[3]\n",
    "power_out = power_top + power_bot\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1a9Zk+/btWXpiAXz55Zd8+eWXBAQEUKVKFbZv346zs7NGqYWxCo9Vp3bY5P/f1A4d6rgx4aVqVHEpqXE6kR/MTE0Y0KwCHet6MOfPINb7hfLryRvsORfBqDaVGfZcJWl0LvKcTlEeN0Ve8fGkKeJTUlIICQmhYsWKWFkZ/2n0K1euULFiRU6cOEH9+vW1jmMUitvPUHZE353aYdV9Uzu0qlaaie2qU6esvcbpREE6cz2WT349i/+VO4A6j9nUV2vyUk1X6aounupJx+/7yZkdIUSBSUjNYNm/l1n2bwgJ903tMKl9dWm3UUzVLmPPj282Y/vJG8z4/Txh0cmMWHOM56o6M61TTTnDJ/KEFDtCiHz32KkdXq5O62oytUNxp9Pp6Fy/DG29XPnu72CW/hPCvxejeHnevwxqXoGxbavKDOvimUixI7KoUKECcmVT5JX0TD0/Hb3G/L0XCY9LAaBSaVvefak6r9R2kxmyRRa2lmZMal+DHo08+WxHIHsCI1h2IIStAdd57+UadGtQVn5mRK5IsSOEyHOPmtqhjIM149pW5Q1vmdpBPFl5J1uWDWzE30GRfLrjHJdvJfLez6dYd+Qq01+rhXe5UlpHFEWMFDtCiDyjKAp7AiOZc9/UDs4lLBjVpgp9fMphaSa9bET2ta7uQvPKzqw6dIVv9l7k5LVYXv/uEN0aluW9l6vL2Esi26TYEULkiUPBUczaFURAWAygTu3wVqvKDGpeQaZ2ELlmYWbC8Ocr0dnbg1k7g/j52DV+PnaNnWfCGfdiVQY2r4CFmZwpFE8mf4GEEM/kROgdZv8ZxMHg24A6rcngFhV48/nK2NtIo1KRN1xKWjG7ez36+pRj+vaznLwWyxe/B7LBP5SPO9akdXUXrSOKQkyKHSFErjxqaoe+PuV5u01lubwg8o13uVJsebsFPx+/xqyd57l8K5FBK/xp6+XK1I5elHey1TqiKISk2BFC5Mijpnbo2qAsY2VqB1FATEx09Gjkycu13Zi/5yIrD11hT2AE/1y4xfDnK/J26ypy6VRkIT8NQohsiU1KZ9au81mmdni1jjvvvFSNKi4lNE4niiM7K3M+6liTXk08+eTXc/x7MYqF+y7xy7HrvN+hBq/V85AxnAQA0qrLSA0aNAidTme4OTk58fLLL3Pq1KkcbaNLly5Zll25cgWdTkdAQEDeBhaF2qVbCXT57iDrfEPJ0Cu0qlaaHWNasrBvAyl0hOaquJRk9ZAmLOnfEE9Ha8LjUhi3MYAe3x/m7I1YreOJQkCKHSP28ssvc/PmTW7evMnevXsxMzOjY8eOWscSRcy/F2/x+sKDhEQlUsbBmo0jmrJqSBNql5E5rEThodPpaFfLjd3vtGJiu2pYm5vif+UOnb49wIdbThtG7hbFkxQ7RszS0hI3Nzfc3NyoX78+U6ZMISwsjFu3bgFw+vRpXnjhBaytrXFycmLEiBEkJCQAMH36dFatWsW2bdsMZ4f+/vtvKlasCIC3tzc6nY7WrVsDoNfr+fTTTylbtiyWlpbUr1+fnTt3GrLcOyP0448/8txzz2FtbU3jxo25cOEC/v7+NGrUiBIlSvDKK68Y8gntrT58hUEr/IlLyaBh+VJsG92CpjKHlSjErMxNGf1CVf6a2IrX6nmgV2CdbyhtZv/N6sNXyMjUax1RaECKnZxSFEhL1Ob2DNM4JCQksHbtWqpUqYKTkxOJiYm0b9+eUqVK4e/vz08//cSePXsYPXo0ABMnTqRHjx5Zzg41b94cPz8/APbs2cPNmzfZvHkzAN988w1z5sxh9uzZnDp1ivbt2/Paa69x8eLFLDmmTZvGRx99xPHjxzEzM6NPnz689957fPPNN/z7778EBwfz8ccf5/p9iryRnqln6tYzfLztLJl6hTcalGH9cB+cS1hqHU2IbHG3t2Z+b282jWiKl7sdscnpfLztLB2/PcDhS7e1jicKmDRQzqn0JPifhzb7/uAGWGS/W+WOHTsoUUJtT5GYmIi7uzs7duzAxMSE9evXk5KSwurVq7G1Vbe5YMECOnXqxMyZM3F1dcXa2prU1FTc3NwM2yxdujQATk5OWZbPnj2byZMn06tXLwBmzpzJvn37mDdvHgsXLjSsN3HiRNq3bw/AuHHj6N27N3v37qVFixYADB06lJUrV+biwxF5JTYpnbfXH+Ng8G10Opj8cg3efL6SNPQURZJPJSd2jGnJBr9QZt8d2bv30iO8WtedDzp4UcbBWuuIogDImR0j1qZNGwICAggICMDPz4/27dvzyiuvcPXqVQIDA6lXr56h0AFo0aIFer2eoKCgHO0nLi6OGzduGAqW+7cXGBiYZVndunUN911dXQGoU6dOlmWRkZE52r/IO5dvJfD6dwc5GHwbGwtTlvRvxFutKkuhI4o0UxMd/ZqW5++JrRnQrDwmOvjt1E1enPM33++/JJMfFwNyZienzG3UMyxa7TsHbG1tqVKliuHxsmXLsLe3Z+nSpXmdLNvMzf8bUffeAfTBZXq9XFPXwoGLUby97hhxKRmUcbBm2cBGeLnbaR1LiDzjYGPBp51r07uJOgqzb0g0M/44T0hUIp93qS0T1Box+ZfNKZ1OvZSkxe0Zv13rdDpMTExITk7Gy8uLkydPkpiYaHj+4MGDmJiYUL16dQAsLCzIzMzMsg0LCwuALMvt7Ozw8PDg4MGDWdY9ePAgNWvWfKbMomCsOXyFgSv8DA2Rt45qIYWOMFpe7nZsHNGUzzrXwkQHG/3DeHPNMZLSMrSOJvKJFDtGLDU1lfDwcMLDwwkMDGTMmDEkJCTQqVMn+vbti5WVFQMHDuTMmTPs27ePMWPG0L9/f8PlpQoVKnDq1CmCgoKIiooiPT0dFxcXrK2t2blzJxEREcTGqmNYTJo0iZkzZ7Jp0yaCgoKYMmUKAQEBjBs3TsuPQDxFRqaej7edYeq9hsjeZVg3zIfSJaUhsjBuOp2O/s0qsLhfQyzNTNh7PpI+S32li7qRkmLHiO3cuRN3d3fc3d3x8fEx9Lpq3bo1NjY27Nq1i+joaBo3bky3bt148cUXWbBggeH1w4cPp3r16jRq1IjSpUtz8OBBzMzMmD9/Pt9//z0eHh507twZgLFjxzJhwgTeffdd6tSpw86dO9m+fTtVq1bV6u2Lp4hNSmfQCn9WH75qaIg8p0c9rMxNtY4mRIFpV8uN9cN9cLAxJyAshm6LDhEWnaR1LJHHdIq0zCIuLg57e3tiY2Oxs8t66j4lJYWQkBAqVqyIlZVMbihyrjD+DF2+lcCwVUe5HJWIjYUp83rWp10tt6e/UAgjFRwZz8Af/Lkek0zpkpasGNRYBs4sAp50/L6fnNkRopg5GBxFl4UHuXx3ROSf32ouhY4o9qq4lGTz282p4VaSW/Gp9FpyhAMXo7SOJfKIFDtCFCNrjlxlwA9qQ+QG5RzYOqoFNT2kIbIQAK52Vvz4VjOaVnIkITWDwSv92BZwXetYIg9IsSNEMWBoiLz1jKEh8vrhTaUhshAPsLMyZ9WQJrxa1530TIVxGwNY+s9lrWOJZyTj7Ahh5GKT0hm94Tj/XoxCp4NJ7aszUgYKFOKxLM1M+baXN64lrfjhYAhf/B5IeFwKH3bwwsREfm+KIil2hDBiIVGJDF3pb2iI/HXP+rSX9jlCPJWJiY6pHb1ws7fkf7+fZ/mBECLjU5ndvS6WZtJjsaiRYkcII3UoOIqR644Tm5yOh70VywY2lvY5QuSATqdjxPOVcSlpxaSfT/LryRtExafy/YCG2FmZP30DotCQNjtCGKG1R67S/wc/YpPT8S7nwNbR0hBZiNzq4l2GFYOaYGthyuHLt+mx+DARcSlaxxI5IMWOEEYkI1PPtG1n+OhuQ+TXvcuwYXhTXEoWjvF9hCiqWlZ1ZtObzXAuYcn58Hje+O4QwZEJWscS2STFjhBGIjY5ncEr/Vl1+CqgNkSeKyMiC5FnapexZ8vbzanobMv1mGS6LT7EsavRWscS2SDFjhBGICQqkde/O8i/F6OwNjdlcb+GjGpTRXpcCZHHPB1t+GVkc+p7OhCTlE6fpb7sPhehdSzxFFLsGCGdTvfE2/Tp07WO+JDWrVtnyejq6kr37t25evVqjrczfvz4LMv+/vtvdDodMTExeRe4EDl0b0TkW4l42Fvx88hmvFxbelwJkV8cbS1YP9yHF2q4kJqh5801R1nvG6p1LPEEUuwYoZs3bxpu8+bNw87OLsuyiRMn5nuGChUq8Pfff+foNcOHD+fmzZvcuHGDbdu2ERYWRr9+/fInoJFY56uOiBybnE59T7Uhci0Pmc9HiPxmY2HGkv4N6dGoLHoFPthymrm7LyDTTRZOUuwYITc3N8PN3t4enU5neOzi4sLcuXMpW7YslpaW1K9fn507dxpee+XKFXQ6HRs3bqR58+ZYWVlRu3Zt9u/fn++5bWxscHNzw93dnaZNmzJ69GiOHz+eZZ39+/fTpEkTLC0tcXd3Z8qUKWRkZAAwaNAg9u/fzzfffGM4Q3TlyhXatGkDQKlSpdDpdAwaNAiA1NRUxo4di4uLC1ZWVrRs2RJ/f3/Dvu6dEdq1axfe3t5YW1vzwgsvEBkZyR9//IGXlxd2dnb06dOHpKSCnSU5I1PP9O1n+XDLGTL0Cl3qe7BxhDREFqIgmZmaMLNrXca+UAWA+Xsv8v7m02Rk6jVOJh4k4+zkkKIoJGcka7JvazPrZ26D8c033zBnzhy+//57vL29+eGHH3jttdc4e/YsVatWNaw3adIk5s2bR82aNZk7dy6dOnUiJCQEJyenZ30b2RIdHc2PP/6Ij4+PYdn169fp0KEDgwYNYvXq1Zw/f57hw4djZWXF9OnT+eabb7hw4QK1a9fm008/BaB06dL88ssvdO3alaCgIOzs7LC2tgbgvffe45dffmHVqlWUL1+eWbNm0b59e4KDg3F0dDTsd/r06SxYsAAbGxt69OhBjx49sLS0ZP369SQkJPD666/z7bffMnny5AL5bGKT0xm9Xh0RGdSGyG+3lhGRhdCCTqdjQrvquNpbMXXrGTb6h3ErPpUFfRpgbSGdAwoLKXZyKDkjGZ/1Pk9fMR/49vHFxtzmmbYxe/ZsJk+eTK9evQCYOXMm+/btY968eSxcuNCw3ujRo+natSsAixYtYufOnSxfvpz33nvvmfb/JN999x3Lli1DURSSkpKoVq0au3btyvK8p6cnCxYsQKfTUaNGDW7cuMHkyZP5+OOPsbe3x8LCwnCG6J57hYuLiwsODg4AJCYmsmjRIlauXMkrr7wCwNKlS9m9ezfLly9n0qRJhtd//vnntGjRAoChQ4fy/vvvc+nSJSpVqgRAt27d2LdvX4EUO1eiEhmyyp/LtxKxNldHRJb2OUJor69PeZxLWDJ2wwn2no+kz7IjLB/YGEdbC62jCeQyVrESFxfHjRs3DAfue1q0aEFgYGCWZc2aNTPcNzMzo1GjRg+tc7+33nqLEiVKGG6hoaG88sorWZY9Td++fQkICODkyZMcOHCAKlWq0K5dO+Lj4wEIDAykWbNmWc5gtGjRgoSEBK5du5atz+CeS5cukZ6enuWzMDc3p0mTJg+9z7p16xruu7q6YmNjYyh07i2LjIzM0f5z49ClKDrfbYjsbm/FT29JQ2QhCpP2tdxYN8wHe2tzToTG0G3RIcKiC/YSt3g0ObOTQ9Zm1vj28dVs34XVp59+mqXhc+vWrZk5c2aWy1BPY29vT5Uq6rXvKlWqsHz5ctzd3dm0aRPDhg3L88zZZW7+37DwOp0uy+N7y/T6/L1Gv873KtO2nSVDr1Df04ElAxpK+xwhCqFGFRz5ZWQzBv6gzkn3xqJDrBzcWDoOaEzO7OSQTqfDxtxGk9uztsmws7PDw8ODgwcPZll+8OBBatasmWXZkSNHDPczMjI4duwYXl5ej922i4sLVapUMdzMzMwoU6ZMlmU5ZWqqXu9OTlbbSHl5eXH48OEsvR0OHjxIyZIlKVu2LAAWFhZkZmZm2Y6FhXoa+f7llStXxsLCIstnkZ6ejr+//0OfhZYebIjcWRoiC1HoVXEpyea3m1PDrSS34lPp+f0RDgZHaR2rWJNip5iZNGkSM2fOZNOmTQQFBTFlyhQCAgIYN25clvUWLlzIli1bOH/+PKNGjeLOnTsMGTIkX7MlJSURHh5OeHg4J0+eZOTIkVhZWdGuXTsA3n77bcLCwhgzZgznz59n27ZtTJs2jQkTJmBiov4oV6hQAV9fX65cuUJUVBR6vZ7y5cuj0+nYsWMHt27dIiEhAVtbW0aOHMmkSZPYuXMn586dY/jw4SQlJTF06NB8fZ/ZFZuczpBVR1l56AqgNkSe17O+jIgsRBHgamfFj281o2klRxJSMxi0wo9tAde1jlVsSbFTzIwdO5YJEybw7rvvUqdOHXbu3Mn27duz9MQC+PLLL/nyyy+pV68eBw4cYPv27Tg7O+drtqVLl+Lu7o67uztt2rQhKiqK33//nerVqwNQpkwZfv/9d/z8/KhXrx5vvfUWQ4cO5aOPPjJsY+LEiZiamlKzZk1Kly5NaGgoZcqU4ZNPPmHKlCm4uroyevRow3vs2rUr/fv3p0GDBgQHB7Nr1y5KlSqVr+8zO65EJfLGdwf558KtuyMiN5ARkYUoYuyszFk1pAmv1nUnPVNh3MYAlv5zWetYxZJOkRGQiIuLw97entjYWOzsss4MnZKSQkhICBUrVsTKyvgvHVy5coWKFSty4sQJ6tevr3Uco5DTn6FDl6J4e91xYpLScbe3YumARtQuI9f7hSiq9HqFz38L5IeDIQAMbVmRDzt4YWIiX16e1ZOO3/eTMztCFCLrfUMZsNyPmCR1RORto1pIoSNEEWdiomNqRy8+6FADgOUHQhi3KYDUjMynvFLkFemNJUQhkJGp54vfA1lx8AoAr9XzYFa3utI+RwgjodPpGPF8ZVxKWjHxp5P8evIGUfGpfD+gIXZW5k/fgHgmcmZHZFGhQgUURZFLWAUoLkVtiHyv0JnYrhrf9JKGyEIYoy7eZVgxuDG2FqYcvnybHosPExGXonUso1eoi53MzEymTp1KxYoVsba2pnLlynz22WdZuh4risLHH3+Mu7s71tbWtG3blosXL2qYWojsu3o7kTe+O2RoiLyobwNGv1BVGiILYcSeq1qaTW82w7mEJefD43nju0MERyZoHcuoFepiZ+bMmSxatIgFCxYQGBjIzJkzmTVrFt9++61hnVmzZjF//nwWL16Mr68vtra2tG/fnpSUvK2UpR23yK3H/ewcvnSbzgsPEhyZgJudOiLyK3XcCzidEEILtcvYs3lkcyo623I9Jpluiw9x7OodrWMZrUJd7Bw6dIjOnTvz6quvUqFCBbp160a7du3w8/MD1IPIvHnz+Oijj+jcuTN169Zl9erV3Lhxg61bt+ZJhnsD26WlpeXJ9kTxc29G9PtHXt4WcJ3+y32JSUqnnqcD20dLQ2QhiptyTjb8/FYz6nk6EJOUTt9lR9h9LkLrWEapUDdQbt68OUuWLOHChQtUq1bNMGfS3LlzAQgJCSE8PJy2bdsaXmNvb4+Pjw+HDx82THb5oNTUVFJTUw2P4+LiHpvBzMwMGxsbbt26hbm5uWHwOiGe5t6EppGRkTg4OBgK593nIpjw40ky9Qqd6nnwlTREFqLYciphyYbhPoxef4K/zkfy5pqjfPF6HXo3Kad1NKNSqIudKVOmEBcXR40aNTA1NSUzM5MvvviCvn37AhAeHg6oEzHez9XV1fDco8yYMYNPPvkkWxl0Oh3u7u6EhIRw9erVXL4TUZw5ODgYZmE/GBzFqPXHydQrvNGgDLO71ZOxNoQo5mwszFjSvyEfbDnNj0ev8f7m04THpjC+rbTfyyuFutj58ccfWbduHevXr6dWrVoEBAQwfvx4PDw8GDhwYK63+/777zNhwgTD47i4ODw9PR+7voWFBVWrVpVLWSLHzM3NDWd0ToTeYfjqo6Rl6GlX05VZXetKoSOEAMDM1ISZXeviZmfF/L+C+WbvRSLjU/isc23MTOWKwrMq1MXOpEmTmDJliuFyVJ06dbh69SozZsxg4MCBhm/LERERuLv/17AzIiLiiV2nLS0tsbS0zFEWExOTYjGCssgfgTfjGLTCn6S0TFpWcebbPt7yB0wIkYVOp2NCu+q42lsxdesZNviFcSs+lW97N8DaQi51P4tC/dc2KSnpoTYypqam6PV6ACpWrIibmxt79+41PB8XF4evry/NmjUr0KxCPM6VqET6L/cjNjmdBuUcWDKgIZZm8odLCPFofX3Ks6hfQyzNTNgTGEmfZUeITpQrC8+iUBc7nTp14osvvuC3337jypUrbNmyhblz5/L6668DahU8fvx4Pv/8c7Zv387p06cZMGAAHh4edOnSRdvwQgA3YpLpu8yXqIRUvNztWDGoCTYWhfqEqhCiEGhfy411w3ywtzbnRGgM3RYdIiw6SetYRVahngg0Pj6eqVOnsmXLFiIjI/Hw8KB37958/PHHWFhYAGqPl2nTprFkyRJiYmJo2bIl3333HdWqVcv2frI7kZgQOXE7IZXu3x/m8q1EKjrb8uObzShdMmeXT4UQxVtwZDwDf/DnekwypUtasnJwY2p5yDAV92T3+F2oi52CIsWOyGuxyen0WXqEszfi8LC34qeRzSnjYK11LCFEERQem8KgFX6cD4+nhKUZ3/dvSIsqzlrHKhRk1nMhNJKclsnQlf6cvRGHk60Fa4f5SKEjhMg1N3srNr3ZjKaVHElIzWDwSn98L9/WOlaRIsWOEHkoNSOTN9ce4+jVO5S0MmP10CZUKl1C61hCiCLO3tqcVUOa0NbLlbQMPcNWH+V8+OMHxBVZSbEjRB7JyNQzfmOAYVJPubYuhMhLlmamLOjjTeMKpYhPyWDQ3bY84umk2BEiD+j1Cu9vPs0fZ8KxMDVhyYCGNCzvqHUsIYSRsTI3ZdmAxlRzLUF4XAoDf/AjJkm6pT+NFDtCPCNFUfjst3P8dOwaJjqY39ub56qW1jqWEMJI2duYs3JwE9ztrQiOTGDoqqOkpGdqHatQk2JHiGc0b89FVhy8AsCsbvV4ubabtoGEEEbPw8GaVUOaYGdlxrGrdxi9/gQZmXqtYxVaUuwI8QyW/XuZb/ZeBGB6p5p0a1hW40RCiOKimmtJlg9qfHek5QimbjuLjCbzaFLsCJFLP/qH8flvgQC8+1I1BrWoqHEiIURx07iCI/N7e2Oigw1+oYYvXyIrKXaEyIXfTt1kyuZTAIx4vhKjX6iicSIhRHHVvpYbn3auDaiX1df7hmqcqPCRYkeIHPo7KJLxm06gV6B3E0/ef6UGOp1O61hCiGKsX9PyjH2xKgAfbT3Nn2fDNU5UuEixI0QO+IVE89baY6RnKnSs687nXepIoSOEKBTeaVuVXo090SswZsMJjl6J1jpSoSHFjhDZdOZ6LENX+pOSrqdN9dLM7VEfUxMpdIQQhYNOp+PzLrVp6+VCaoaeoauOcjEiXutYhYIUO0JkQ3BkPAN+8CM+NQOfio4s6tcQCzP59RFCFC5mpiZ827sBDco5EJuczsAf/LgZK6Msy19rIZ4iLDqJfsv8iE5Mo25Ze5YNbISVuanWsYQQ4pGsLUxZPrAxlUvbciM2hUE/+BOblK51LE1JsSPEE0TGpdBvuS/hcSlUdSnBqsFNKGllrnUsIYR4olK2Fqwa0gRXO0uCIuIZvrp4j7IsxY4QjxGTlEb/5X5cvZ2Ep6M1a4f5UMrWQutYQgiRLWVL2bBqSBNKWpnhdyWa8RsDyNQXz0EHpdgR4hESUjMYuMKfoIh4XO0sWTe0Ka52VlrHEkKIHKnhZsfSAY2wMDVh59lwpm8vnqMsS7EjxANS0jMZvuooJ8NiKGVjztqhPpRzstE6lhBC5ErTSk7M61UfnQ7WHLnKwn3BWkcqcFLsCHGf9Ew9o9cf5/Dl25SwNGPVkCZUdS2pdSwhhHgmHeq4M71TLQBm/3mBH/3DNE5UsKTYEeIuvV5h4k8n2RMYiaWZCcsGNqJuWQetYwkhRJ4Y2LwCo9pUBuD9LafZGxihcaKCI8WOEICiKEzddoZtATcwM9GxuF9DmlZy0jqWEELkqYntqtOtYVky9Qqj1h/neOgdrSMVCCl2hABm7gxinW8oOh183bM+bWq4aB1JCCHynE6nY8YbdWhTvTQp6XqGrPQnODJB61j5ToodUewt3BfM4v2XAPjf63XoVM9D40RCCJF/zE1NWNi3AfU8HYhJUkdZjohL0TpWvpJiRxRraw5f4atdQQB82MGL3k3KaZxICCHyn42FGSsGNaaSsy3XY5IZ+IMfcSnGO8qyFDui2Npy4hpTt50FYMwLVRj+fCWNEwkhRMFxvDvKcumSlpwPj2fE6qOkZhjnKMtS7Ihi6c+z4Uz86RQAg5pXYMJL1TROJIQQBc/T0YaVgxtTwtKMI5ejmbDpJHojHGVZih1R7BwMjmL0+hNk6hW6NijLxx1rotPptI4lhBCaqOVhz5L+DTE31fHb6Zt8uuOc0Y2yLMWOKFaOh95h+OqjpGXqaV/LlZld62BiIoWOEKJ4a17Fmbk96gOw8tAVFu+/rG2gPCbFjig2Am/GMegHP5LSMnmuqjPze3tjZiq/AkIIAdCpngcfd6wJwMyd5/n52DWNE+Ud+UsvioWQqET6L/cjLiWDhuVL8X3/hliamWodSwghCpUhLSvyZiu1s8bkX06xLyhS40R5Q4odYfRuxCTTb5kvUQmpeLnb8cOgxthYmGkdSwghCqXJ7WvwhncZMvUKb689TkBYjNaRnpkUO8KoRSWk0m+5L9djkqnkbMuaoU2wtzbXOpYQQhRaJiY6Znary/PVSpOcnsmQlf6ERCVqHeuZSLEjjFZscjoDlvtx+VYiHvZWrBnmg3MJS61jCSFEoWduasKivg2oW9ae6MQ0BvzgS2R80R1lWYodYZSS0jIYutKfczfjcC5hwdphPpRxsNY6lhBCFBm2lmb8MKgx5Z1sCItOZvAKf+KL6CjLUuwIo5Oakcmba45x9Ood7KzMWD3Eh0qlS2gdSwghihznEpasHtIE5xIWnL0Rx1trj5GWodc6Vo5JsSOMSkamnvEbA/j3YhTW5qasGNyEmh52WscSQogiq7yTLSsGNcHWwpSDwbeZ+FPRG2VZih1hNPR6hSmbT/PHmXAsTE1YOqARDcuX0jqWEEIUeXXK2rO4f0PMTHRsP3mD//0eqHWkHJFiRxgFRVH4dMc5fj52DVMTHfN7e9OyqrPWsYQQwmg8V7U0s7vXA2DZgRCW/lN0RlmWYkcYha/3XGTloSsAzOpal5dru2kbSAghjFAX7zJ82MELgC9+D2TriesaJ8oeKXZEkbfiYAjz914E4NPOtejasKzGiYQQwngNf74Sw1pWBGDiTyf558ItjRM9nRQ7okjbdz6Sz3acA2Biu2oMaFZB20BCCFEMfNDBi9fqeZChVxi59hinr8VqHemJpNgRRdaFiHjGbDiBXoFejT0Z1aaK1pGEEKJYMDHRMbt7PVpWcSYxLZPBK/24ervwjrIsxY4okm4npDJ0lT8JqRn4VHTk08610el0WscSQohiw8LMhEX9GlDLw46ohDQG/OBHVEKq1rEeSYodUeSkZmTy1tpjhEUnU97JhsX9GmJhJj/KQghR0EpambNicGM8Ha25ejuJwSv8SUzN0DrWQ+QIIYoURVH4cMsZ/K/coaSVGcsHNqKUrYXWsYQQothyKWnF6iE+ONpacPp6bKEcZVmKHVGkLPnnsmEsnYV9GlDFpaTWkYQQotir6GzLikGNsTY35d+LUUz+5VShGmVZih1RZOw+F8GXO88D8HHHmjxfrbTGiYQQQtxTz9OBRf0aYGaiY8uJ68zcdV7rSAZS7IgiIfBmHOM2nkBRoF/TcgxoVl7rSEIIIR7QuroLM7vWBeD7/ZdZfiBE40QqKXZEoXcrPpVhq46SlJZJiypOTOtUS3peCSFEIdW1YVkmv1wDgM92nGP7yRsaJ5JiRxRyKemZvLnmKNdjkqnkbMt3fRpibio/tkIIUZi91aoSg5pXAODdHwM4FBylaR45aohCS1EUpvxyiuOhMdhbm7NsYCPsbcy1jiWEEOIpdDodH3esyat13UnPVBix5hhnrms3yrKZZnsW4im++/sSWwNuYGaiY1HfBlQqXULrSEIIIbLJxETH3B71uJ2QyrU7ydhYmGqWRYodUSjtPHOTr3YFAfBJ51o0r+KscSIhhBA5ZWlmypIBjUhJz8SlpJVmOXJc7MTExLBlyxb+/fdfrl69SlJSEqVLl8bb25v27dvTvHnz/MgpipEz12N5Z9NJAAY1r0BfH+l5JYQQRZWdlTl2Vto2Qch2m50bN24wbNgw3N3d+fzzz0lOTqZ+/fq8+OKLlC1bln379vHSSy9Rs2ZNNm3alJ+ZhRGLjEth2KqjJKdn8ny10nz0qpfWkYQQQhRx2T6z4+3tzcCBAzl27Bg1a9Z85DrJycls3bqVefPmERYWxsSJE/MsqDB+KemZDF99lPC4FKq4lGBBH2/MpOeVEEKIZ6RTFCVb4znfvn0bJyenbG84p+trKS4uDnt7e2JjY7Gzs9M6TrGkKApjNpxgx6mblLIxZ+uoFpR3stU6lhBCiEIsu8fvbH9tzmnhUlQKHVE4fLP3IjtO3cTcVMfifg2l0BFCCJFnnukaQXx8PJMmTaJx48Y0aNCAMWPGEBWl7cBBouj59eQN5u25CMDnXWrjU0kKZSGEEHnnmYqd4cOHExUVxSeffMK0adO4fPkyffv2zatsohg4GRbDxJ/UnlfDn6tIz8blNE4khBDC2OSo6/nXX3/N+PHjDfMS+fv7c+HCBUxN1YGCqlevTtOmTfM+pTBKN2OTGb76KKkZel6o4cKUV6TnlRBCiLyXo2Ln0qVL+Pj48P333+Pt7c1LL73Eq6++SpcuXUhPT2fNmjW0b98+v7IKI5KUlsHw1UeJjE+lumtJvulVH1MTmdxTCCFE3stRsbNgwQKOHDnCkCFDaNOmDTNmzGDt2rXs3r2bzMxMunfvzujRo/MrqzASer3ChE0nOXM9DidbC5YNbERJjQecEkIIYbxy3GanadOm+Pv74+TkRLNmzahQoQK//PILW7duZdKkSVhbW+dpwOvXr9OvXz+cnJywtramTp06HD161PC8oih8/PHHuLu7Y21tTdu2bbl48WKeZngmSdFaJyh05u6+wM6z4ViYmvB9/4Z4OtpoHUkIIYQRy1UDZTMzMz788EN+/fVX5s2bR7du3QgPD8/rbNy5c4cWLVpgbm7OH3/8wblz55gzZw6lSpUyrDNr1izmz5/P4sWL8fX1xdbWlvbt25OSkpLneXIkMwN+fw++fx4SbmmbpRDZeuI6C/YFAzDjjTo0quCocSIhhBDGLkfFzsmTJ2ncuDElS5akRYsW6PV69u7dy6uvvkrz5s1ZtGhRnoabOXMmnp6erFixgiZNmlCxYkXatWtH5cqVAfWszrx58/joo4/o3LkzdevWZfXq1dy4cYOtW7fmaZYcS0uA4D0QGwab+kFGqrZ5CoFjV+/w3i+nABjZujJdG5bVOJEQQojiIEfFzpAhQ3juuefw9/ene/fuvPXWWwAMHjwYX19fDh48SLNmzfIs3Pbt22nUqBHdu3fHxcUFb29vli5dang+JCSE8PBw2rZta1hmb2+Pj48Phw8ffux2U1NTiYuLy3LLc9YO0HsjWNpD2BHYMQGyN1i1Ubp2J4k31xwlLUNPu5quTGpXXetIQgghiokcFTsXLlzg7bffpkaNGowZM4aQkBDDc6VLl2bt2rV88skneRbu8uXLLFq0iKpVq7Jr1y5GjhzJ2LFjWbVqFYDh0pmrq2uW17m6uj7xstqMGTOwt7c33Dw9PfMscxalq0H3H0BnAgFr4ch3+bOfQi4xNYNhq44SlZCGl7sdX/esj4n0vBJCCFFAsj03FkCnTp1ITEykV69e/PXXX5iamrJu3bp8C2dhYUGjRo04dOiQYdnYsWPx9/fn8OHDHDp0iBYtWnDjxg3c3d0N6/To0QOdTvfY2ddTU1NJTf3vslJcXByenp75NzfW4e9g1/tq0dPnJ6ja9umvMRKZeoU31xxjT2AEziUs2T66BR4OeduIXQghRPGU53NjAaxevZoGDRqwbds2KlWqlOdtdB7k7u7+0AzrXl5ehIaGAuDm5gZARERElnUiIiIMzz2KpaUldnZ2WW75qulI8O4Hih5+Hgy3LuTv/gqRWbvOsycwAgszE5YOaCiFjhBCiAKXo3F2SpUqxezZs/Mry0NatGhBUFBQlmUXLlygfPnyAFSsWBE3Nzf27t1L/fr1AbXK8/X1ZeTIkQWW86l0Onh1Lty+BKGHYUNPGLYXbIy7J9JPR8P4fv9lAL7qVhfvcqWe8gohhBAi72X7zM69synZdf369RyHedA777zDkSNH+N///kdwcDDr169nyZIljBo1CgCdTsf48eP5/PPP2b59O6dPn2bAgAF4eHjQpUuXZ95/njKzhB5rwN4Toi+rZ3gyM7ROlW/8r0TzwZbTAIx9oQqd65fROJEQQojiKtvFTuPGjXnzzTfx9/d/7DqxsbEsXbqU2rVr88svvzxzuMaNG7NlyxY2bNhA7dq1+eyzz5g3b16WyUbfe+89xowZw4gRI2jcuDEJCQns3LkTKyurZ95/nitRGnpvAHNbuPw37PpA60T5Iiw6iTfXHCM9U6FDHTfGt62mdSQhhBDFWLYbKN++fZsvvviCH374ASsrKxo2bIiHhwdWVlbcuXOHc+fOcfbsWRo0aMDUqVPp0KFDfmfPM9lt4JRnAn9Vx94B6DgPGg3O/30WkPiUdLouOsSFiATqlLHnxzebYW1hqnUsIYQQRii7x+8c9cYCSE5O5rfffuPAgQNcvXqV5ORknJ2d8fb2pn379tSuXfuZwxe0Ai92AP75Cv76HEzMYMA2qNCyYPabjzL1CsNW+bMv6BaudpZsG9USN/tCeIZNCCGEUci3YscYaVLsKAr8MhTO/ALWjjD8L3CsWDD7zief7TjH8gMhWJmb8OObzahb1kHrSEIIIYxYvnQ9F3lIp4POC8HDG5KjYUNvSMmHkZwLyAa/UJYfUAeZnNO9vhQ6QgghCg0pdrRkbg291kMJN7gVCJtHgD5T61Q5dvjSbaZuPQPAhJeq8Wpd96e8QgghhCg4Uuxozc5DLXhMLeHCH/DXZ1onypErUYmMXHeMDL3Ca/U8GPNCFa0jCSGEEFlIsVMYlG2oXtICOPA1nHz0NBeFTWxyOkNX+ROTlE59TwdmdauLTidzXgkhhChcpNgpLOp2h5YT1Pvbx8C1o9rmeYqMTD2j1x/n0q1EPOytWDKgIVbm0sVcCCFE4ZPrYufSpUuMGTOGtm3b0rZtW8aOHculS5fyMlvx88JUqP4qZKbCxj4Q++yjUOeXz3ac49+LUVibm7J0YCNcSkoXcyGEEIVTroqdXbt2UbNmTfz8/Khbty5169bF19eXWrVqsXv37rzOWHyYmMAb34NLTUiIUAuetCStUz1kzeErrDp8FYB5vepTy8Ne40RCCCHE4+VqnJ17Awh++eWXWZZPmTKFP//8k+PHj+dZwIKgyTg7T3LnCix9AZJuQ603oNsPalf1QuDAxSgGrvAjU6/w3svVebu1NEgWQgihjXwdZycwMJChQ4c+tHzIkCGcO3cuN5sU9ytVQZ001MQMzm6GfwpupvknuXQrgbfXHSNTr/BGgzKMbFVZ60hCCCHEU+Wq2CldujQBAQEPLQ8ICMDFxeVZMwmACi3g1bnq/X2fw7ntmsaJSUpj2KqjxKVk0Kh8KWa8UUd6XgkhhCgSzHLzouHDhzNixAguX75M8+bNATh48CAzZ85kwoQJeRqwWGs4ECLPge9i2PKmesbHvW6Bx0jP1PP2uuOERCVSxsGaxf0bYmkmPa+EEEIUDblqs6MoCvPmzWPOnDncuHEDAA8PDyZNmsTYsWOL3Df+Qtdm536ZGbCuG1zeB3ZlYcQ+KFFwZ88UReGDLWfY4BeKrYUpv7zdnBpuhewzEkIIUSwV2ESg8fHxAJQsWfJZNqOpQl3sACTfgWVt4XYwePrAwF/BzLJAdr3iYAif/HoOnQ6WDWjEi16uBbJfIYQQ4mkKbCLQkiVLFulCp0iwLgW9N4KlPYT5wo4J6qzp+ezvoEg+26E2OP/gFS8pdIQQQhRJ2W6z06BBA/bu3UupUqXw9vZ+4qWqotb1vEhwrgrdV6iXtALWgosXNB+db7u7GBHPmPUn0CvQs5Enw56rmG/7EkIIIfJTtoudzp07Y2lpabhf1NrlGIUqL0L7/8HOKbB7KpSuDlVfyvPdRCemMXTVUeJTM2hS0ZHPutSWf28hhBBF1jO32TEGhb7Nzv0URZ0768QasLSDYXvUoiePpGXo6bfcF7+QaMo52rB1VAscbS3ybPtCCCFEXsnXNjuVKlXi9u3bDy2PiYmhUqVKudmkyC6dTh1/p1xzSI2DDb0gKTpPNq0oCh9tPY1fSDQlLc1YPrCRFDpCCCGKvFwVO1euXCEzM/Oh5ampqVy7du2ZQ4mnMLOAnmvAvhxEX4afBkFm+jNvdsXBK/x49BomOvi2jzdVXaXhuRBCiKIvR4MKbt/+3yi+u3btwt7+vwkgMzMz2bt3LxUrSkPWAmHrDL03wPJ2ELIfdn0AHb7K9eb+uXCLz3+72/Oqgxetq8tI2EIIIYxDjtrsmJioJ4J0Oh0Pvszc3JwKFSowZ84cOnbsmLcp81mRarPzoMAdsKmver/j19BoSI43cflWAl0WHiQuJYPuDcsyq1tdaZAshBCi0MuXNjt6vR69Xk+5cuWIjIw0PNbr9aSmphIUFFTkCp0iz6sjvDBVvf/7JAj5N0cvj01OZ9hqdc6rhuVL8fnr0vNKCCGEcclVm52QkBCcnZ3zOovIrefehdrdQJ8BP/aH6JBsvSxTrzB2wwku30rEw96Kxf1kzishhBDGJ1cTgQIkJiayf/9+QkNDSUtLy/Lc2LFjnzmYyAGdDjovgOhLcOMEbOgNQ/8Eqydfkvvyj0D2X7iFtbkpSwY0onTJgpmCQgghhChIuRpn58SJE3To0IGkpCQSExNxdHQkKioKGxsbXFxcuHz5cn5kzTdFus3O/eJuwtI2EH8Tqr0MvdaDyaPP1Px87BoTfzoJwMI+DXi1rntBJhVCCCGeWb6Os/POO+/QqVMn7ty5g7W1NUeOHOHq1as0bNiQ2bNn5zq0eEZ27tBrHZhZwYWdsPfTR6527Go0H2w+DcDYF6tKoSOEEMKo5arYCQgI4N1338XExARTU1NSU1Px9PRk1qxZfPDBB3mdUeREmYbQeaF6/+A8OLkxy9M3YpJ5c81x0jL1vFzLjfEvVi34jEIIIUQBylWxY25ubuiG7uLiQmhoKAD29vaEhYXlXTqRO3W6qY2WAbaPhTB/AJLTMhmx5ihRCanUcCvJnB71MDGRnldCCCGMW64aKHt7e+Pv70/VqlVp1aoVH3/8MVFRUaxZs4batWvndUaRG20+gsjzEPQbbOyDMmIfE3+L5Mz1OJxsLVg2sBG2lrluny6EEEIUGbk6s/O///0Pd3e1nccXX3xBqVKlGDlyJLdu3WLJkiV5GlDkkokJvLEEXGpBYiS3lnZl76krmJvqWNy/IWVL2WidUAghhCgQOe6NpSgKYWFhuLi4YGVllV+5CpTR9MZ6lDtXSVvUCou0O+zIbEpCxyX08imvdSohhBDimeVbbyxFUahSpYq0zSkiAlNKMTRlHGmKKR1Nj9ArZZPWkYQQQogCleNix8TEhKpVq3L79u38yCPy0O2EVIatOsq/adVY5Xh3oMd9X8C5bdoGE0IIIQpQrtrsfPnll0yaNIkzZ87kdR6RR9Iy9Ixce5zrMclUcLKh+/APwGek+uSWt+DmKW0DCiGEEAUkVyMolypViqSkJDIyMrCwsMDa2jrL89HR0XkWsCAYW5sdRVH4YMtpNviFUdLSjC2jmlPFpSRkZsD67nDpL7ArCyP2QQkXreMKIYQQuZLd43eu+h7Pmzcvt7lEAVh9+Cob/MLQ6WB+b2+10AEwNYNuK2DZi3A7GDb2hUE7wEzmxBJCCGG8cnVmx9gY05mdg8FRDPjBj0y9wgcdajDi+coPrxQVDMtegJRYqN9XHXFZJ4MLCiGEKFrydW4sUThdiUrk7XXHydQrvNGgDMOfq/ToFZ2rqGd4dCYQsA4OLyjYoEIIIUQBkmLHSMSlpDNs9VFik9PxLufA/16vg+5JZ2uqvAjtZ6j3d38MF/4smKBCCCFEAZNixwhk6hXGbThBcGQCbnZWfN+vIVbmpk9/oc+b0GAAKHr4ZSjcCsr/sEIIIUQBk2LHCMzadZ59QbewNDNh6YBGuNhlc2RrnQ46zIFyzSE1Dtb3hKSi1ZNOCCGEeJocFzvp6emYmZnJGDuFxObj1/h+/2UAZnevR52y9jnbgJkF9FwDDuXgTgj8NBAy0/MhqRBCCKGNHBc75ubmlCtXjszMzPzII3LgROgdpmw+DcDoNlXoVM8jdxuydYbeG8GiBIT8Azvfz8OUQgghhLZydRnrww8/5IMPPihygwcak/DYFEasOUZahp6Xaroy4aVqz7ZB11rqLOnowH8p+C/Lk5xCCCGE1nI1zo63tzfBwcGkp6dTvnx5bG1tszx//PjxPAtYEIraODsp6Zn0+P4wp67FUt21JL+83ZwSlrkaH/Jh/86BvZ+CzhT6/QKV2+TNdoUQQog8lq8jKHfp0iW3ucQzUhSFST+f4tS1WErZmLNsYKO8K3QAWk6AWxfg1Ea1/c6wveBcNe+2L4QQQhQwGUGZonVmZ+G+YL7aFYSZiY61w3xoWskp73eSkQqrOkGYLzhWhmF7wMYx7/cjhBBCPIN8H0E5JiaGZcuW8f777xva7hw/fpzr16/ndpPiKXafi2D2n+pYOJ90rpU/hQ6oc2X1XAf2nhB9SXpoCSGEKNJyVeycOnWKatWqMXPmTGbPnk1MTAwAmzdv5v33pSdPfjgfHsf4jSdQFBjQrDx9fcrn7w5LlM7aQ+v3SSAnAYUQQhRBuSp2JkyYwKBBg7h48SJWVv8NYNehQwf++eefPAsnVNGJaQxffZTEtEyaVXJiaseaBbNjt9rQdRmgg2MrwG9JwexXCCGEyEO5Knb8/f158803H1pepkwZwsPDnzmU+E96pp631x0jLDqZco42fNe3AeamBTjwdfVX4KVP1fs7p8DFPQW3byGEECIP5OqoaWlpSVxc3EPLL1y4QOnSpZ85lPjP9O1nOXI5mhKWZiwb2IhSthYFH6L5GKjfT51D6+fBEHm+4DMIIYQQuZSrYue1117j008/JT1dbbSq0+kIDQ1l8uTJdO3aNU8DFmdrjlxlnW8oOh1806s+1VxLahNEp4OOc/+bQ2tDT0i8rU0WIYQQIodyVezMmTOHhIQEXFxcSE5OplWrVlSpUoWSJUvyxRdf5HXGYunQpSimbz8LwHvta/Cil6u2gcws786hVR7uXIEf+0NGmraZhBBCiGx4pnF2Dhw4wKlTp0hISKBBgwa0bds2L7MVmMI2zk7o7SReW3iAmKR0utT34Oue9dHpdFrHUkUGwvJ26hke737w2gL1zI8QQghRwLJ7/M5VsZOSkpKlF1ZRV5iKnfiUdLouOsSFiATqlbVn05vNsDI31TTTQy7uhvU91DY87b6A5qO1TiSEEKIYytdBBR0cHHj++eeZOnUqf/31F8nJybkOKv6TqVd4Z1MAFyIScClpyZIBjQpfoQNQ9SVo/z/1/p8fQdBObfMIIYQQT5CrYmfPnj28/PLL+Pr68tprr1GqVClatmzJhx9+yO7du/M6Y7Ex588g9gRGYmFmwpIBjXC1K8Rnz3zegoaDAAV+GQoR57ROJIQQQjzSM8+NlZGRgb+/P99//z3r1q1Dr9eTmZmZV/kKRGG4jLUt4DrjNgYAMK9nfbp4l9EkR45kpsOa1+HKv2BfDob/pY68LIQQQhSAfJ31HNQxdf7++2/DLTU1lY4dO9K6devcbrLYOhkWw3s/nwLgrVaVi0ahA2BqDj1Ww7IXIfoybOoLA39Ve24JIYQQhUSuzuyUKVOG5ORkWrduTevWrWnVqhV169YtPD2GckjLMzsRcSm8tuAAEXGpvFjDhSUDGmFqUsQ+x1sXYFlbSI2Fer2hyyLpoSWEECLf5WsD5dKlS5OUlER4eDjh4eFEREQUSCPlL7/8Ep1Ox/jx4w3LUlJSGDVqFE5OTpQoUYKuXbsSERGR71nyQkp6JiPWHCMiLpWqLiWY16t+0St0AEpXgx4rQWcKJzfAwXlaJxJCCCEMclXsBAQEEB4ezpQpU0hNTeWDDz7A2dmZ5s2b8+GHH+Z1RgBDu6C6detmWf7OO+/w66+/8tNPP7F//35u3LjBG2+8kS8Z8pKiKEz55RQnw2JwsDFn2cBGlLQy1zpW7lV+AV6Zqd7f8wkE7tA2jxBCCHHXMzdQvn37Nn///Tfbtm1jw4YN+dJA+d6ghd999x2ff/459evXZ968ecTGxlK6dGnWr19Pt27dADh//jxeXl4cPnyYpk2bZmv7WlzGWrz/El/+cR5TEx1rhjSheRXnAtlvvvttIvgvBXNbGLIT3Os+/TVCCCFELuTrZazNmzczduxY6tati6urKyNHjiQhIYE5c+Zw/PjxXId+nFGjRvHqq68+NELzsWPHSE9Pz7K8Ro0alCtXjsOHDz92e6mpqcTFxWW5FaS9gRHM3KlOpjm9U03jKXQAXv4SKrWG9ETY0Bvii8YlRSGEEMYrV72x3nrrLZ5//nlGjBhBq1atqFOnTl7nMti4cSPHjx/H39//oefCw8OxsLDAwcEhy3JXV1fCw8Mfu80ZM2bwySef5HXUbLkQEc+4jQEoCvTxKUe/puU1yZFvTM2g+0pY9hLcvggb+8Cg38C8EI8ZJIQQwqjlqtiJjIzM6xyPFBYWxrhx49i9e3eeTk/x/vvvM2HCBMPjuLg4PD0982z7j3MnMY1hq46SkJqBT0VHpneqVWR7sD2RdSnoswmWvgDXj8K2UdB1mfTQEkIIoYlcj7OTmZnJ1q1bCQwMBKBmzZp07twZU9O8m97g2LFjREZG0qBBgyz7/eeff1iwYAG7du0iLS2NmJiYLGd3IiIicHNze+x2LS0tsbQs2LFg0jP1jFp/nNDoJMqWsmZRv4ZYmOXqKmLR4FRZnSV9zetw5mcoXQNaTdI6lRBCiGIoV8VOcHAwHTp04Pr161SvXh1QLw15enry22+/Ubly5TwJ9+KLL3L69OksywYPHkyNGjWYPHkynp6emJubs3fvXrp27QpAUFAQoaGhNGvWLE8y5JXPdpzj0KXb2FqYsmxgIxxtLbSOlP8qPg8dvoId78C+z8G5KtTqonUqIYQQxUyuip2xY8dSuXJljhw5gqOjI6D2yurXrx9jx47lt99+y5NwJUuWpHbt2lmW2dra4uTkZFg+dOhQJkyYgKOjI3Z2dowZM4ZmzZpluydWQVjne5XVh68C8HXP+tRw03Zm9QLVaIg66KDvItjyFpQqDx7eWqcSQghRjOSq2Nm/f3+WQgfAycmJL7/8khYtWuRZuOz4+uuvMTExoWvXrqSmptK+fXu+++67As3wJEcu32batrMATGxXjXa1Hn95zWi1+1xtrBy8R+2hNXwf2LlrnUoIIUQxkatix9LSkvj4+IeWJyQkYGGRv5dn/v777yyPraysWLhwIQsXLszX/eZGWHQSI9ceI0Ov0KmeB6PaVNE6kjZMzaDbD7C8Hdw6Dxt7w6DfwcJG62RCCCGKgVy1kO3YsSMjRozA19cXRVFQFIUjR47w1ltv8dprr+V1xiIpMTWD4auPcicpnTpl7JnVtejOHZYnrOyh90awdoQbJ2DrSNDrtU4lhBCiGMhVsTN//nwqV65Ms2bNsLKywsrKihYtWlClShW++eabvM5YJJma6KjpYUfpkpYsGdAQa4u866VWZDlWhJ5rwcQczm2F/TO1TiSEEKIYeKbpIoKDgw1dz728vKhSpWhepsmv6SIURSEyPhVXOxlQL4vja2D7aPV+1+VQp5u2eYQQQhRJ2T1+56jNjl6v56uvvmL79u2kpaXx4osvMm3aNKytrZ85sDHS6XRS6DxKg/4QFQSHvoWtb0OpClC2kdaphBBCGKkcXcb64osv+OCDDyhRogRlypThm2++YdSoUfmVTRiztp9AtZchM1WdUiL2mtaJhBBCGKkcFTurV6/mu+++Y9euXWzdupVff/2VdevWoZeGpiKnTEzVKSRcakJCBGzoBWmJWqcSQghhhHJU7ISGhtKhQwfD47Zt26LT6bhx40aeBxPFgGVJtYeWjTOEn4bNI6SHlhBCiDyXo2InIyPjoQk5zc3NSU9Pz9NQohgpVR56rQNTCzi/Q51WQgghhMhDOWqgrCgKgwYNyjKJZkpKCm+99Ra2traGZZs3b867hML4lWsKr30LW96Ef+eAc3Wo11PrVEIIIYxEjoqdgQMHPrSsX79+eRZGFGP1esGtIDgwV+2WXqoClPPROpUQQggj8Ezj7BiL/BpnR+SQXg8/9lcvZ9k4w4h94FBO61RCCCEKqewev3M1grIQ+cLEBF7/HtzqQFIUrO8FqQ/PwSaEEELkhBQ7onCxLKH20LJ1gciz8Msw0GdqnUoIIURu6fWQqW1HJil2ROFjXxZ6bwBTS7iwE/ZM1zqREEKI3FAU2PU+rO8JqQmaxZBiRxROZRtBl+/U+4fmw4m12uYRQgiRcwe+Bt/FcGkvXD2oWQwpdkThVacbPP+eev/X8XD1kKZxhBBC5MCJtbD3E/V++xlQrb1mUaTYEYVb6/ehZhfQp8PGvhAdonUiIYQQTxO0E7aPVe+3GA/N3tY0jhQ7onAzMYEui8C9PiRHq3NopcRqnUoIIcTjhPnBT4NAyYR6faDtdK0TSbEjigALG7XBckl3uHUefh4CmRlapxJCCPGgyPOwrjtkJEPVdvDafNDptE4lxY4oIuw8oNd6MLOG4D2we6rWiYQQQtwv9jqsfQNSYqBMI+i+EkzNtU4FSLEjipIyDeD1Rer9I9/B0RXa5hFCCKFKilYLnbjr4FwN+v4EFrZPf10BkWJHFC21Xoc2H6r3f58IIf9om0cIIYq79GTY0FttZlDSHfptBhtHrVNlIcWOKHqenwS1u4I+Azb1h9uXtE4khBDFU2aG2o4y7AhY2auFjoOn1qkeIsWOKHp0Oui8EMo0VK8Nr+8JyTFapxJCiOJFUWDHeAj6XR3xvvdGcK2pdapHkmJHFE3m1mqDZbsycPui2s1RemgJIUTB2fcFnFgDOhPo9gOUb651oseSYkcUXSXd1G8S5jZweR9sH61OOCeEECJ/+S2Ff75S73f8Grw6apvnKaTYEUWbe13ouhx0pnByA+ycrJ5aFUIIkT/OboHfJ6n323wIDQdpGic7pNgRRV+NDuooywB+S+Cvz7XNI4QQxirkH9g8AlCg8TC1w0gRIMWOMA71ekKH2er9f2fDgXmaxhFCCKNz8xRs6AOZaeD1Grwyq1CMjpwdUuwI49Fk+H9zsOyZBv7LNY0jhBBGIzoE1nWDtHgo3xLeWAomplqnyjYpdoRxafkOtJyg3v/tXTj1o7Z5hBCiqEu4pY6OnBABrnWg93owt9I6VY5IsSOMz4sfQ+PhgAJb3oLzv2mdSAghiqbUeFjfHaIvg0M56PezOnhgESPFjjA+Op16LbluL1Ay1TF4Lv+tdSohhChaMtLUUepvnAAbJ+i3RR3yowiSYkcYJxMTdZTlGh3VxnQb+kCYn9aphBCiaNDrYdvb6hhm5rbqxJ7OVbROlWtS7AjjZWqmjupZqQ2kJ6qN68JPa51KCCEKN0WBPz+C0z+BiRn0XK1Oz1OESbEjjJuZJfRaB55NISUW1rwOUcFapxJCiMLr0Hw4slC932URVGmrbZ48IMWOMH4WttBnE7jVgcRbsLozxIRqnUoIIQqfgA2w+2P1frsvoG4PbfPkESl2RPFg7QD9t4JzNYi7phY88RFapxJCiMLjwp+wbZR6v/kYaD5a2zx5SIodUXzYOqsFj305tRvlmtchKVrrVEIIob1rR+GngWoP1rq9oO2nWifKU1LsiOLFvgwM3AYl3CDyrNpoOTVe61RCCKGdWxdgXXdIT1Lb53ReoPZoNSLG9W6EyA7HSjBgK1iXguvHYENvSE/ROpUQQhS8uBvq6MjJ0WqPq+6rwNRc61R5ToodUTy5eEG/X8CiJFz5Vz19m5mudSohhCg4yTGwtivEhoFTFejzE1iW0DpVvpBiRxRfZRpCn41gZgUXdsKWN0GfqXUqIYTIf+nJ6lntyHPqZf1+m8HWSetU+UaKHVG8VWgJPdaoA2ed+QV2vKMOqCWEEMZKnwm/DIPQQ2Bpr57lLlVe61T5SoodIaq1g67LQGcCx1epI4dKwSOEMEaKAr9NgPM7wNRSncHcrbbWqfKdFDtCANR6HTrNV+8fXgD/fKVtHiGEyA9/fwnHVqpf7rouU89uFwNS7AhxT4P+0H6Gen/fF3BkkbZ5hBAiL/kvh/1fqvc7zIaar2mbpwBJsSPE/Zq9Da0/UO/vnAIn1mqbRwgh8sK5bfDbu+r9VlOg8VBt8xQwKXaEeFCr96DZ3WHSt4+Bs1u0zSOEEM/iygG1QTIKNBwMradonajASbEjxIN0Omj3OTQYAIoefhkOF3drnUoIIXIu/LTaxTwzDWp0hFfnqH/jihkpdoR4FJ0OOs6DWm+APh029YMrB7VOJYQQ2XfnqjpoYGoclG8BXZeDianWqTQhxY4Qj2NiCm8sgartISMF1veE68e1TiWEEE+XGKVOA5EQAS61oNd6MLfSOpVmpNgR4klMzaHHKqjwHKTFq9+SIgO1TiWEEI+XmqBO7Hk7GOzLqYMGWjtonUpTUuwI8TTm1tB7gzq9RHI0rO4C0SFapxJCiIdlpsOPA+DGcbB2hP6bwc5d61Sak2JHiOywLAl9fwaXmpAQDqtfU2cLFkKIwkKvh22j4NJeMLeBvj+Bc1WtUxUKUuwIkV02jtB/CzhWgphQ9QxPYpTWqYQQQrXnYzi1SZ3rr8dqKNtI60SFhhQ7QuRESTcYsA3sykBUEKx5HVJitU4lhCjuDn2r3gBeWwBVX9I2TyEjxY4QOeVQTi14bJwh/JTaSystSetUQoji6uQmdQJjgJc+hfq9tc1TCEmxI0RuOFdVL2lZ2kPoYdjUFzJStU4lhChuLu6BbW+r95uOguZjtc1TSEmxI0RuuddVGwCa28Clv+CXoZCZoXUqIURxce2Y2vNKnwF1uqsjvxfD0ZGzQ4odIZ5FOR91sC5TCwj8VZ1LS6/XOpUQwthFBcP67pCeCJVfgM7fgYkc0h9HPhkhnlXlNtB9JehM4eR62DkZFEXrVEIIYxV3U+0ckXQbPLzVnldmFlqnKtSk2BEiL9R4FbosAnTgtwT++lzrREIIY5QSC+u6QWyoOgxGn5/UccDEExXqYmfGjBk0btyYkiVL4uLiQpcuXQgKCsqyTkpKCqNGjcLJyYkSJUrQtWtXIiIiNEosirV6PdUZhQH+nQ0H5mkaRwhhZFJiYX0viDgDJVzVThIlSmudqkgo1MXO/v37GTVqFEeOHGH37t2kp6fTrl07EhMTDeu88847/Prrr/z000/s37+fGzdu8MYbb2iYWhRrjYdC2+nq/T3TwH+5pnGEEEYi9jr88AqEHgJLO3VE91IVtE5VZOgUpeg0Lrh16xYuLi7s37+f559/ntjYWEqXLs369evp1q0bAOfPn8fLy4vDhw/TtGnTbG03Li4Oe3t7YmNjsbOzy8+3IIqLvZ/Cv3MAHbyxFOp21zqREKKoijinXrqKu66e0en7E7jX0zpVoZDd43ehPrPzoNhYdaRaR0dHAI4dO0Z6ejpt27Y1rFOjRg3KlSvH4cOHH7ud1NRU4uListyEyFMvTIUmIwAFtrwJ53/TOpEQoigK+Rd+eFktdJyrwdDdUujkQpEpdvR6PePHj6dFixbUrl0bgPDwcCwsLHBwcMiyrqurK+Hh4Y/d1owZM7C3tzfcPD098zO6KI50Onh5JtTrDUom/DQILv+tdSohRFFy+mdY+wakxkK5ZjBkF5Qqr3WqIqnIFDujRo3izJkzbNy48Zm39f777xMbG2u4hYWF5UFCIR5gYqLOUePVCTLTYEMfCPPTOpUQorBTFDg4/+5ApWng9Rr036pORixypUgUO6NHj2bHjh3s27ePsmXLGpa7ubmRlpZGTExMlvUjIiJwc3N77PYsLS2xs7PLchMiX5iaQdfl6qBf6Ynqdffw01qnEkIUVvpM2DkFdk9VH/uMVMfxMrfSNFZRV6iLHUVRGD16NFu2bOGvv/6iYsWKWZ5v2LAh5ubm7N2717AsKCiI0NBQmjVrVtBxhXg0M0vouRY8m6pdR9e8ro5+KoQQ90tPVi95+y5WH7f7Al75EkxMNY1lDAp1b6y3336b9evXs23bNqpXr25Ybm9vj7W1NQAjR47k999/Z+XKldjZ2TFmzBgADh06lO39SG8sUSBSYmFlR3WmdLuyMOQPdQZ1IYRIioYNvSHsiDr9zOuLoXZXrVMVetk9fhfqYkf3mAnNVqxYwaBBgwB1UMF3332XDRs2kJqaSvv27fnuu++eeBnrQVLsiAKTGAUrXoGoC+rop4N+Bzt3rVMJIbR05yqs7Qq3L4KVvTrfXoWWWqcqEoyi2CkoUuyIAhV7HVa8DDGhUNIDeq9X57cRQhQ/NwJgfQ9IiFDP+Pb7GVy8tE5VZBjlODtCGAX7MjDwV3CuDvE31FFRz2zWOpUQoqAF74GVr6qFjmttGLZbCp18IsWOEFooVUH9w1a1HWQkw8+D4a8vQK/XOpkQoiCcWAvrekBaAlRsBYN/BzsPrVMZLSl2hNCKlT303gjN1Ub1/DMLfhoAaYlPfp0QouhSFPh7JmwbpQ44WrenOs+Vlb3WyYyaFDtCaMnEFNp9Dl0WqT0wAn+FH9pDjAx0KYTRycyAX8fB3/9TH7d8B17/HswstM1VDEixI0RhUL8PDNwBtqXVQQeXtoFQX61TCSHySmoCbOwNx1eBzgQ6zIa209WpZUS+k2JHiMKinA8M3weudSDxFqzqCAHrtU4lhHhWCZHq7/PFP8HMWh1ktMlwrVMVK1LsCFGYOHjC0F3qXDiZabB1JOz6UB1CXghR9EQFw/KX4MYJsHZUe2LWeFXrVMWOFDtCFDYWttB9FbSarD4+vAA29FJHYBZCFB1h/mqhc+eK2gNz6G7wbKx1qmJJih0hCiMTE2jzAXRboZ72vvgnLHsJbl/SOpkQIjvO/6ZeukqOVgcNHbobnKtonarYkmJHiMKs9hvqHFolPSAqCJa9CJf3a51KCPEk/stgUz/ISFHH0hr0G5Rw0TpVsSbFjhCFnYc3jNgHZRpC8h111nT/ZVqnEkI8SK+HPdPht3dB0UODgdBrg3ppWmhKih0hioKSbuqkoXV7qgOR/fauestM1zqZEAIgIw22vAkHvlYft/kQOn0Dpmba5hKAFDtCFB3mVuoAZG2nAzr17M7aNyApWutkQhRvKbGwrhuc/hF0ptB5IbR6T8bQKUSk2BGiKNHp1FFXe28AixIQ8g8sfQFuBWmdTIjiKe4GrOgAIfvV38m+P4J3P61TiQdIsSNEUVT9FbV3h0M5uBMCy9rChT+1TiVE8RIZqP7uRZyBEq5qQ+QqbbVOJR5Bih0hiirXmuqIy+VbQGocrO8Bh75VJxoUQuSvKwdgeXuIuw5OVdUvHx71tU4lHkOKHSGKMltn6L9V7fWBAn9+pM6mnJGqdTIhjNeZX9Rekamx4NkUhv4JpcprnUo8gRQ7QhR1ZhZqr49XZqkTDAasg1Wd1Pl4hBB5R1HUs6c/D1Gnc/HqBAO2go2j1snEU0ixI4Qx0OnA503o9wtY2UOYLyxpAzdPaZ1MCOOgz4Sd76tnTwF83lKndTG31jaXyBYpdoQwJpVfgGF/gVMViLsGP7SHc9u1TiVE0ZaeDD8NAt9F6uN2n8PLX4KJqaaxRPZJsSOEsXGuAsP2qIVPehL82B/2z5KGy0LkRlI0rO4CgdvB1AK6LofmY2QMnSJGih0hjJF1KejzE/iMVB/v+0JtZ5CWpG0uIYqSO1fVs6NhR8DSHvpthjrdtE4lckGKHSGMlakZvPIldJoPJuZwdjOseAVir2udTIjC7+ZJWP4SRF0AuzIwZCdUfE7rVCKXpNgRwtg1HAgDtoGNE9wMgKVt4NpRrVMJUXgF71FHRU6IAJda6mVh15papxLPQIodIYqDCi3UAQhdaqp/wFd0gFM/ap1KiMLnxDpY3xPSEqDi8zDkD7Dz0DqVeEZS7AhRXJQqrw5+Vr0DZKbC5uGwZzro9VonE0J7iqI25N/2NugzoE4P6Ht3KAdR5EmxI0RxYlkSeq6DlhPUxwe+hk19ITVe21xCaCkzA34dpzbkB3Wy3de/VwfsFEZBih0hihsTE2g7Dd5YCqaWEPQ7LG8Hd65onUyIgpeWCBv7wPFVgA46zIa209XfE2E05F9TiOKqbg8Y/AeUcIPIc+qIy1cOap1KiIKTcAtWvgoXd4GZFfRcC02Ga51K5AMpdoQozso2hBH7wL0+JEfD6tfg2EqtUwmRvxQFzv8GS1+AGyfA2hEG/gpeHbVOJvKJFDtCFHd2HuoZnlpvqA0zfx0Hf0xW2zEIYWxuBcHaN9RLV7GhUKoCDN0Nnk20TibykZnWAYQQhYCFDXT7Qe2avu9z8F2sHhS6r1BHYxaiqEuOgf0zwW+JWtSbWkCz0fDcu2BZQut0Ip9JsSOEUOl00GoSlK4OW96Ey/tgWVvovRGcq2qdTojc0WfCibWw91NIilKXVe+gTubpVFnbbKLASLEjhMiq5mvqqf2NfeB2MCx9UT3DU+VFrZMJkTOhR+CP99SpHwCcq8HLM6BKW21ziQInbXaEEA9zr6uOuOzZFFJjYV03OLJIZk4XRUPcDfhluDqJ582TYGkH7f8HIw9JoVNMSbEjhHi0EqVh4Hao3w8UPeycAr+OhYxUrZMJ8WjpKfDPbPi2EZz+EdCBd38YcxyajQJTc60TCo3IZSwhxOOZWULnBeDiBbunwvHVcPlveP49qNdbnVldCK0pCgT9Abve/29wzLJNoMMs8PDWNJooHHSKIuel4+LisLe3JzY2Fjs7O63jCFE4XdwN20apE4kCOFaCVlOgTjcwMdU2myi+bgWpZx0v/aU+LukOL30Kdbqrje6FUcvu8VuKHaTYESLb0pLAfxkcnAdJt9VlztWhzfvg1VmG2BcFR7qSC6TYyREpdoTIodR48P0eDn0LKTHqMtfa0OYDtVuvfKMW+eVxXcnbf6GebRTFihQ7OSDFjhC5lBILh7+DI99Bapy6zMMb2nyo9nqRokfkJelKLh4gxU4OSLEjxDNKilbP8vh+D+mJ6rKyTeCFD6FiKyl6xLOJuwG7p93tYYXalbz1FGgyQnpYFXNS7OSAFDtC5JGEW2p7Hv9lkJGiLivfUi16yjfXNJoogtJT4MhC+GfO3SJaB9794MVp6tAIotiTYicHpNgRIo/Fh8O/c+HYCshMU5dVagMvfARlG2mbTRR+0pVcZJMUOzkgxY4Q+ST2GvzzldqgVH93FvVqL6sNmd3raZtNFE7SlVzkgBQ7OSDFjhD5LDpELXpOblBHYwbw6gStPwDXmtpmE4WDdCUXuSDFTg5IsSNEAYkKhv1fwumfAQXQQe03oPX7MrN6cSVdycUzkGInB6TYEaKARQbC3zPg3Db1sc4E6vaEVu/JAa44eWRX8i+hyova5hJFhhQ7OSDFjhAauXlKLXqCflcfm5hB/T7q3FsOntpmE/nnkV3J34cmw6UrucgRKXZyQIodITR2/Rjs+x8E71Efm1pAg4Fqew07d22zibwjXclFHpNiJwek2BGikAg9Avu+gJB/1MdmVtBoKLR8Rw6GRZl0JRf5RIqdHJBiR4hCJuQf+OsLCDuiPja3UUfLbTEObBy1zSZyRrqSi3wkxU4OSLEjRCGkKHBpr1r03DiuLrMoCc3ehqZvg7WDpvHEU0hXclEApNjJASl2hCjEFAUu7FQvb4WfVpdZ2UPzMeDzFliW1DafyEq6kosCJMVODkixI0QRoNfD+V9h3wy4Fagus3aEluOh8XCwsNE0ngBCfe92JQ9QH0tXcpHPpNjJASl2hChC9JlwdovaZf12sLrM1gWemwANB4O5lbb5ihO9HqIuQJgvBO+GwF/V5dKVXBQQKXZyQIodIYqgzAw4tUltFxJzVV1W0gOenwje/cHMQtt8xig1QR0mIMxPLXCu+UFK7H0r6KBBf3jhY+k9JwqEFDs5IMWOEEVYZrraRuSf2RB3TV3mUE4dmLBebzA10zZfUaUoEBv2X2ET5gvhZ0DJzLqeuQ2UaQiePlDzNZngVRQoKXZyQIodIYxARiocWwX/zoGEcHWZYyVoNQW8OoKFrbb5CruMNLUB+L3CJswX4m8+vJ5dWSjnoxY3nk3AtbZcqhKakWInB6TYEcKIpCeD/3I48PV/vYEA7MqAU2VwqnL3VlV97FC+eJ79SbytXoYKPaKevblxHDJSsq5jYgZudf8rbDybgH1ZbfIK8QhS7OSAFDtCGKHUBHWMF9/v/zvT8ygmZlCqoloAOVe5rxiqAiVcjWPgO0ND4iP/XZa617j7ftal7itsfMCjgfRyE4WaFDs5IMWOEEYuKRpuX1IP8Lcv3v3/JfWWkfz411mUfOBsUJX/HlsV4r8VT21IfJdzdbWwKddULW6cqhhHcSeKjewev4vhuVshRLFj46jePBtnXa7XQ/wNiLq/ALpbEMWEQlq8OmbMvXFj7lfC9b7ip+p/xVCpCgXbEyw3DYk9faBsI5l6QxQbRlPsLFy4kK+++orw8HDq1avHt99+S5MmTbSOJYQozExM1DYo9mWhcpusz2WkqpNW3g5Wb1EX/yuGEiMhIUK9XT2Y9XU6E7UdkHPVrGeCnKqoXeNNTJ4tc5aGxHcvSz2qIbG953+Xo6QhsSjmjOIy1qZNmxgwYACLFy/Gx8eHefPm8dNPPxEUFISLi8tTXy+XsYQQOZISe99ZoPtvlyAt4fGvM7cBx8pZCyDnuw2lrUs9+jWJt+/rIZXdhsQ+YF8m796vEIVUsWqz4+PjQ+PGjVmwYAEAer0eT09PxowZw5QpU576eil2hBB5QlEgPvwRRVCwepZIn/H419o4Zb0UdudKNhsSNwUPb2lILIqlYtNmJy0tjWPHjvH+++8blpmYmNC2bVsOHz78yNekpqaSmppqeBwbqzbci4uLy9+wQohiwBac6qm3+2Wmq21roi+rZ4CiL9+9hai9xVKj4E4UBB95eJOOVaFsQyjbWG1r41gpa0PilAxIkb9fovi5d9x+2nmbIl/sREVFkZmZiaura5blrq6unD9//pGvmTFjBp988slDyz09PfMloxBCPJvjd29LtQ4iRKEUHx+Pvb39Y58v8sVObrz//vtMmDDB8Fiv1xMdHY2TkxO6POx2GRcXh6enJ2FhYcX28lhx/wzk/Rfv9w/yGRT39w/yGeTn+1cUhfj4eDw8PJ64XpEvdpydnTE1NSUiIiLL8oiICNzc3B75GktLSywtLbMsc3BwyK+I2NnZFcsf8PsV989A3n/xfv8gn0Fxf/8gn0F+vf8nndG55xn7QGrPwsKChg0bsnfvXsMyvV7P3r17adasmYbJhBBCCFEYFPkzOwATJkxg4MCBNGrUiCZNmjBv3jwSExMZPHiw1tGEEEIIoTGjKHZ69uzJrVu3+PjjjwkPD6d+/frs3LnzoUbLBc3S0pJp06Y9dMmsOCnun4G8/+L9/kE+g+L+/kE+g8Lw/o1inB0hhBBCiMcp8m12hBBCCCGeRIodIYQQQhg1KXaEEEIIYdSk2BFCCCGEUZNiJx9Mnz4dnU6X5VajRg2tYxWo69ev069fP5ycnLC2tqZOnTocPXpU61gFpkKFCg/9DOh0OkaNGqV1tAKRmZnJ1KlTqVixItbW1lSuXJnPPvvsqfPXGJP4+HjGjx9P+fLlsba2pnnz5vj7+2sdK9/8888/dOrUCQ8PD3Q6HVu3bs3yvKIofPzxx7i7u2NtbU3btm25ePGiNmHzwdPe/+bNm2nXrp1hpP6AgABNcuanJ30G6enpTJ48mTp16mBra4uHhwcDBgzgxo0bBZJNip18UqtWLW7evGm4HThwQOtIBebOnTu0aNECc3Nz/vjjD86dO8ecOXMoVaqU1tEKjL+/f5Z//927dwPQvXt3jZMVjJkzZ7Jo0SIWLFhAYGAgM2fOZNasWXz77bdaRysww4YNY/fu3axZs4bTp0/Trl072rZty/Xr17WOli8SExOpV68eCxcufOTzs2bNYv78+SxevBhfX19sbW1p3749KSkpBZw0fzzt/ScmJtKyZUtmzpxZwMkKzpM+g6SkJI4fP87UqVM5fvw4mzdvJigoiNdee61gwikiz02bNk2pV6+e1jE0M3nyZKVly5ZaxyhUxo0bp1SuXFnR6/VaRykQr776qjJkyJAsy9544w2lb9++GiUqWElJSYqpqamyY8eOLMsbNGigfPjhhxqlKjiAsmXLFsNjvV6vuLm5KV999ZVhWUxMjGJpaals2LBBg4T568H3f7+QkBAFUE6cOFGgmQrakz6De/z8/BRAuXr1ar7nkTM7+eTixYt4eHhQqVIl+vbtS2hoqNaRCsz27dtp1KgR3bt3x8XFBW9vb5YuLb6zNaelpbF27VqGDBmSpxPNFmbNmzdn7969XLhwAYCTJ09y4MABXnnlFY2TFYyMjAwyMzOxsrLKstza2rpYneW9JyQkhPDwcNq2bWtYZm9vj4+PD4cPH9YwmdBSbGwsOp0uX+emvEeKnXzg4+PDypUr2blzJ4sWLSIkJITnnnuO+Ph4raMViMuXL7No0SKqVq3Krl27GDlyJGPHjmXVqlVaR9PE1q1biYmJYdCgQVpHKTBTpkyhV69e1KhRA3Nzc7y9vRk/fjx9+/bVOlqBKFmyJM2aNeOzzz7jxo0bZGZmsnbtWg4fPszNmze1jlfgwsPDAR4a1d7V1dXwnCheUlJSmDx5Mr179y6QyVGNYrqIwub+b69169bFx8eH8uXL8+OPPzJ06FANkxUMvV5Po0aN+N///geAt7c3Z86cYfHixQwcOFDjdAVv+fLlvPLKK3h4eGgdpcD8+OOPrFu3jvXr11OrVi0CAgIYP348Hh4exeZnYM2aNQwZMoQyZcpgampKgwYN6N27N8eOHdM6mhCaSk9Pp0ePHiiKwqJFiwpkn3JmpwA4ODhQrVo1goODtY5SINzd3alZs2aWZV5eXsXqUt49V69eZc+ePQwbNkzrKAVq0qRJhrM7derUoX///rzzzjvMmDFD62gFpnLlyuzfv5+EhATCwsLw8/MjPT2dSpUqaR2twLm5uQEQERGRZXlERIThOVE83Ct0rl69yu7duwvkrA5IsVMgEhISuHTpEu7u7lpHKRAtWrQgKCgoy7ILFy5Qvnx5jRJpZ8WKFbi4uPDqq69qHaVAJSUlYWKS9c+Lqakper1eo0TasbW1xd3dnTt37rBr1y46d+6sdaQCV7FiRdzc3Ni7d69hWVxcHL6+vjRr1kzDZKIg3St0Ll68yJ49e3ByciqwfctlrHwwceJEOnXqRPny5blx4wbTpk3D1NSU3r17ax2tQLzzzjs0b96c//3vf/To0QM/Pz+WLFnCkiVLtI5WoPR6PStWrGDgwIGYmRWvX7VOnTrxxRdfUK5cOWrVqsWJEyeYO3cuQ4YM0Tpagdm1axeKolC9enWCg4OZNGkSNWrUYPDgwVpHyxcJCQlZzl6HhIQQEBCAo6Mj5cqVY/z48Xz++edUrVqVihUrMnXqVDw8POjSpYt2ofPQ095/dHQ0oaGhhnFl7n0hdHNzM5qzW0/6DNzd3enWrRvHjx9nx44dZGZmGtprOTo6YmFhkb/h8r2/VzHUs2dPxd3dXbGwsFDKlCmj9OzZUwkODtY6VoH69ddfldq1ayuWlpZKjRo1lCVLlmgdqcDt2rVLAZSgoCCtoxS4uLg4Zdy4cUq5cuUUKysrpVKlSsqHH36opKamah2twGzatEmpVKmSYmFhobi5uSmjRo1SYmJitI6Vb/bt26cAD90GDhyoKIra/Xzq1KmKq6urYmlpqbz44otG9bvxtPe/YsWKRz4/bdo0TXPnpSd9Bve63D/qtm/fvnzPplOUYjSkqRBCCCGKHWmzI4QQQgijJsWOEEIIIYyaFDtCCCGEMGpS7AghhBDCqEmxI4QQQgijJsWOEEIIIYyaFDtCCCGEMGpS7Agh8lSFChWYN2+e4bFOp2Pr1q35us8rV66g0+kICAjI1/1k16BBg3I9MvDzzz/P+vXr8zbQI/Tq1Ys5c+bk+36EKAyk2BHCCISHhzNmzBgqVaqEpaUlnp6edOrUKctcRFq5efMmr7zyitYx8kVeF1nbt28nIiKCXr165cn2nuSjjz7iiy++IDY2Nt/3JYTWpNgRooi7cuUKDRs25K+//uKrr77i9OnT7Ny5kzZt2jBq1Cit4+Hm5oalpaXWMYqE+fPnM3jw4IcmUc0PtWvXpnLlyqxduzbf9yWE1qTYEaKIe/vtt9HpdPj5+dG1a1eqVatGrVq1mDBhAkeOHDGsFxoaSufOnSlRogR2dnb06NGDiIgIw/OPuvQyfvx4WrdubXjcunVrRo8ezejRo7G3t8fZ2ZmpU6fypFln7r+Mde9MyObNm2nTpg02NjbUq1ePw4cPZ3nN0qVL8fT0xMbGhtdff525c+fi4OCQo8/lzJkzvPLKK5QoUQJXV1f69+9PVFRUlvcyduxY3nvvPRwdHXFzc2P69OlZtnH+/HlatmyJlZUVNWvWZM+ePVneT8WKFQHw9vZGp9Nl+awAZs+ejbu7O05OTowaNYr09PTH5r116xZ//fUXnTp1Mix71JmjmJgYdDodf//9NwB///03Op2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      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(ls, 100 * power_top, label=\"Top\")\n",
    "plt.plot(ls, 100 * power_bot, label=\"Bottom\")\n",
    "plt.plot(ls, 100 * power_out, label=\"Top + Bottom\")\n",
    "plt.xlabel(\"Coupling length (\u00b5m)\")\n",
    "plt.ylabel(\"Power ratio (%)\")\n",
    "plt.ylim(0, 100)\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Final Remarks\n",
    "\n",
    "Batches provide some other convenient functionality for managing large numbers of jobs.\n",
    "\n",
    "For example, one can save the batch information to file and load the batch at a later time, if needing to disconnect from the service while the jobs are running."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# save batch metadata\n",
    "batch.to_file(\"data/batch_data.json\")\n",
    "\n",
    "# load batch metadata into a new batch\n",
    "loaded_batch = web.Batch.from_file(\"data/batch_data.json\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For more reference, refer to our documentation."
   ]
  }
 ],
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text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=9.90: status = success  <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=10.60: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=11.30: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\nl=12.00: status = success <span style=\"color: #729c1f; text-decoration-color: #729c1f\">\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501\u2501</span> <span style=\"color: #800080; text-decoration-color: #800080\">100%</span> <span style=\"color: #008080; text-decoration-color: #008080\">0:00:00</span>\n</pre>\n",
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