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   "source": [
    "# Plastic biosensor grating\n",
    "\n",
    "Note: the cost of running the entire notebook is larger than 1 FlexUnit.\n",
    "\n",
    "Bragg gratings are structures which involve a periodic variation in the refractive index or geometry of waveguide, so that certain frequencies of light are reflected off the grating while others are transmitted.\n",
    "\n",
    "Since gratings can be designed to be extremely sentitive to a narrow band of frequencies, one possible application is to detect the presence of foreign molecules. If particles such as biomolecules are deposited on the device, it will no longer have the same reflective properties in the narrow band of frequencies for which it was designed. Therefore, carefully-designed Bragg gratings can be used as biosensors.\n",
    "\n",
    "In this example, an optical biosensor grating is modeled to detect the presence of biomolecules. The grating is designed to be reflective over a narrow band around its resonant frequency which is modified by the presence of a biomolecule.\n",
    "\n",
    "Reference:  Brian Cunningham, Bo Lin, Jean Qiu, Peter Li, Jane Pepper, Brenda Hugh, \"A plastic colorimetric resonant optical biosensor for multiparallel detection of label-free biochemical interactions,\" Sensors and Actuators B 85 (2002)"
   ]
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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\">[19:47:03] </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING </span> This version of Tidy3D was pip installed from the <span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d-beta'</span> repository on   <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#103\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">103</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         PyPI. Future releases will be uploaded to the <span style=\"color: #008000; text-decoration-color: #008000\">'tidy3d'</span> repository. From now on, <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         please use <span style=\"color: #008000; text-decoration-color: #008000\">'pip install tidy3d'</span> instead.                                        <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
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       "\u001b[2;36m           \u001b[0m         PyPI. Future releases will be uploaded to the \u001b[32m'tidy3d'\u001b[0m repository. From now on, \u001b[2m               \u001b[0m\n",
       "\u001b[2;36m           \u001b[0m         please use \u001b[32m'pip install tidy3d'\u001b[0m instead.                                        \u001b[2m               \u001b[0m\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Using client version: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.9</span>.0rc1                                                  <a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">121</span></a>\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Using client version: \u001b[1;36m1.9\u001b[0m.0rc1                                                  \u001b]8;id=893126;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=552783;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\u001b\\\u001b[2m121\u001b[0m\u001b]8;;\u001b\\\n"
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   ],
   "source": [
    "# basic imports\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "# tidy3d imports\n",
    "import tidy3d as td\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Structure Setup\n",
    "\n",
    "Create the grating geometry."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
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    },
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   "outputs": [],
   "source": [
    "# materials\n",
    "Si3N4 = td.Medium(permittivity=2.05**2)\n",
    "epoxy = td.Medium(permittivity=1.5**2)\n",
    "water = td.Medium(permittivity=1.333**2)\n",
    "# substrate = td.material_library['Polycarbonate']['Sultanova2009']\n",
    "substrate = td.Medium(permittivity=1.333**2)\n",
    "\n",
    "# set basic geometric parameters (units in microns)\n",
    "nm = 1e-3\n",
    "period = 550 * nm\n",
    "grating_ratio = 0.5\n",
    "num_periods = 10\n",
    "grating_height = 200 * nm\n",
    "film_height = 120 * nm\n",
    "epoxy_height = 400 * nm\n",
    "buffer = 0.1\n",
    "substrate_height = 1.5\n",
    "substrate_width = 7.0\n",
    "sim_size = (num_periods * period, substrate_width, 2 * substrate_height)\n",
    "# sim_size = (num_periods * period + 450 * nm, substrate_width, 2 * substrate_height)\n",
    "grating_size = (period * grating_ratio, td.inf, grating_height)\n",
    "film_high_size = (period * grating_ratio, td.inf, film_height)\n",
    "film_low_size = (period * (1.0 - grating_ratio), td.inf, film_height)\n",
    "\n",
    "# wavelength / frequency setup\n",
    "wavelength_min = 780 * nm\n",
    "wavelength_max = 900 * nm\n",
    "freq_min = td.C_0 / wavelength_max\n",
    "freq_max = td.C_0 / wavelength_min\n",
    "freq0 = (freq_min + freq_max) / 2.0\n",
    "fwidth = freq_max - freq_min\n",
    "run_time = 4e-12\n",
    "\n",
    "# create the substrate\n",
    "substrate = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, -substrate_height / 2.0 - buffer / 2.0],\n",
    "        # size=[num_periods * period + buffer, td.inf, substrate_height + buffer],\n",
    "        size=[td.inf, td.inf, substrate_height + buffer],\n",
    "    ),\n",
    "    medium=substrate,\n",
    "    name=\"substrate\",\n",
    ")\n",
    "\n",
    "# create the epoxy layer\n",
    "epoxy_layer = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=[0.0, 0.0, epoxy_height / 2.0],\n",
    "        # size=[num_periods * period + buffer, td.inf, epoxy_height],\n",
    "        size=[td.inf, td.inf, epoxy_height],\n",
    "    ),\n",
    "    medium=epoxy,\n",
    "    name=\"epoxy_layer\",\n",
    ")\n",
    "\n",
    "# create the grating with the Si3N4 film\n",
    "gratings = []\n",
    "films_high = []\n",
    "films_low = []\n",
    "for i in range(num_periods):\n",
    "    grating_center = [\n",
    "        -sim_size[0] / 2.0 + period * grating_ratio / 2.0 + i * period,\n",
    "        0.0,\n",
    "        epoxy_height + grating_height / 2.0,\n",
    "    ]\n",
    "    size = list(grating_size)\n",
    "    if i == 0:\n",
    "        grating_center[0] -= buffer / 2.0\n",
    "        size[0] += buffer\n",
    "    grating = td.Structure(\n",
    "        geometry=td.Box(center=grating_center, size=size),\n",
    "        medium=epoxy,\n",
    "        name=f\"grating_{i}\",\n",
    "    )\n",
    "\n",
    "    film_high_center = [\n",
    "        -sim_size[0] / 2.0 + period * grating_ratio / 2.0 + i * period,\n",
    "        0.0,\n",
    "        epoxy_height + grating_height + film_height / 2.0,\n",
    "    ]\n",
    "    size = list(film_high_size)\n",
    "    if i == 0:\n",
    "        film_high_center[0] -= buffer / 2.0\n",
    "        size[0] += buffer\n",
    "    film_high = td.Structure(\n",
    "        geometry=td.Box(center=film_high_center, size=size),\n",
    "        medium=Si3N4,\n",
    "        name=f\"film_high_{i}\",\n",
    "    )\n",
    "\n",
    "    film_low_center = [\n",
    "        -sim_size[0] / 2.0\n",
    "        + period * grating_ratio\n",
    "        + period * (1.0 - grating_ratio) / 2.0\n",
    "        + i * period,\n",
    "        0.0,\n",
    "        epoxy_height + film_height / 2.0,\n",
    "    ]\n",
    "    size = list(film_low_size)\n",
    "    if i == num_periods - 1:\n",
    "        film_low_center[0] += buffer / 2.0\n",
    "        size[0] += buffer\n",
    "    film_low = td.Structure(\n",
    "        geometry=td.Box(center=film_low_center, size=size),\n",
    "        medium=Si3N4,\n",
    "        name=f\"film_low_{i}\",\n",
    "    )\n",
    "\n",
    "    gratings.append(grating)\n",
    "    films_high.append(film_high)\n",
    "    films_low.append(film_low)\n",
    "\n",
    "geometry = [substrate, epoxy_layer] + gratings + films_high + films_low\n",
    "\n",
    "# boundary conditions\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.periodic(),\n",
    "    # x=td.Boundary.pml(),\n",
    "    y=td.Boundary.pml(),\n",
    "    z=td.Boundary.pml(),\n",
    ")\n",
    "\n",
    "# grid specification\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=30)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Source Setup\n",
    "\n",
    "Create the plane wave source which excites the structure from underneath."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2023-02-03T01:47:03.820358Z"
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   "source": [
    "source_time = td.GaussianPulse(freq0=freq0, fwidth=fwidth)\n",
    "source = td.PlaneWave(\n",
    "    center=[0, 0, -0.5 * substrate_height],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    source_time=source_time,\n",
    "    pol_angle=0,\n",
    "    direction=\"+\",\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monitor Setup\n",
    "\n",
    "Create field and flux monitors to measure reflecting and transmitted flux."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T01:47:03.822878Z",
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     "shell.execute_reply": "2023-02-03T01:47:03.828450Z"
    }
   },
   "outputs": [],
   "source": [
    "# create field monitor\n",
    "monitor_xy = td.FieldMonitor(\n",
    "    center=[0, 0, epoxy_height + film_height / 2],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    freqs=[freq0],\n",
    "    name=\"fields_xy\",\n",
    ")\n",
    "\n",
    "# create flux monitors\n",
    "freqs = list(np.linspace(freq_min, freq_max, 1000))\n",
    "monitor_flux_refl = td.FluxMonitor(\n",
    "    center=[0, 0, -0.75 * substrate_height],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    freqs=freqs,\n",
    "    name=\"flux_refl\",\n",
    ")\n",
    "monitor_flux_tran = td.FluxMonitor(\n",
    "    center=[0, 0, 0.75 * substrate_height],\n",
    "    size=[td.inf, td.inf, 0.0],\n",
    "    freqs=freqs,\n",
    "    name=\"flux_tran\",\n",
    ")\n",
    "\n",
    "monitors = [monitor_xy, monitor_flux_refl, monitor_flux_tran]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Simulation\n",
    "\n",
    "The final simulation object is created and visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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\n",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create the simulation\n",
    "sim = td.Simulation(\n",
    "    center=[0, 0, 0],\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=geometry,\n",
    "    sources=[source],\n",
    "    monitors=monitors,\n",
    "    run_time=run_time,\n",
    "    boundary_spec=boundary_spec,\n",
    "    medium=water,\n",
    "    shutoff=1e-6,\n",
    ")\n",
    "\n",
    "# plot the simulation domain\n",
    "f, ax = plt.subplots(tight_layout=True, figsize=(8, 6))\n",
    "sim.plot(y=0, ax=ax)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T01:47:04.058587Z",
     "iopub.status.busy": "2023-02-03T01:47:04.058424Z",
     "shell.execute_reply": "2023-02-03T01:53:53.117782Z"
    }
   },
   "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\">[19:47:05] </span><span style=\"color: #000080; text-decoration-color: #000080\">INFO    </span> Created task <span style=\"color: #008000; text-decoration-color: #008000\">'biosensor'</span> with task_id <span style=\"color: #008000; text-decoration-color: #008000\">'2c78763c-d6b8-4c51-a1d3-ff933817669e'</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#120\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">120</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
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       "\n",
       "\u001b[?25h"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = queued                                                                   \u001b]8;id=373037;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=852545;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#262\u001b\\\u001b[2m262\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[2;36m[19:47:11]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = preprocess                                                               \u001b]8;id=738979;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=334622;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#274\u001b\\\u001b[2m274\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[?25h\r",
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       "\u001b[2;36m[19:47:17]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m starting up solver                                                                \u001b]8;id=916207;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=894921;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#278\u001b\\\u001b[2m278\u001b[0m\u001b]8;;\u001b\\\n"
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       "\u001b[2;36m[19:47:27]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m running solver                                                                    \u001b]8;id=380158;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=279648;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#284\u001b\\\u001b[2m284\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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   ],
   "source": [
    "# run simulation\n",
    "import tidy3d.web as web\n",
    "\n",
    "sim_data = web.run(sim, task_name=\"biosensor\", path=\"data/biosensor.hdf5\")\n"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "## Plot Fields\n",
    "\n",
    "The frequency-domain fields recorded are plotted at the center frequency in an `xy` plane cutting through the grating."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T01:53:58.558756Z",
     "iopub.status.busy": "2023-02-03T01:53:58.558247Z",
     "iopub.status.idle": "2023-02-03T01:53:59.643572Z",
     "shell.execute_reply": "2023-02-03T01:53:59.643034Z"
    }
   },
   "outputs": [
    {
     "data": {
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       "\u001b[2;36m[19:53:58]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m0.8357\u001b[0m defined from sources.                     \u001b]8;id=99464;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=81402;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
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    {
     "data": {
      "text/plain": [
       "<AxesSubplot: title={'center': 'cross section at z=0.46'}, xlabel='x', ylabel='y'>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
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\n",
      "text/plain": [
       "<Figure size 900x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot fields on the monitor\n",
    "fig, ax = plt.subplots(tight_layout=True, figsize=(9, 4))\n",
    "sim_data.plot_field(\n",
    "    field_monitor_name=\"fields_xy\", field_name=\"Ey\", val=\"abs\", f=freq0, ax=ax\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Transmission and Reflection\n",
    "\n",
    "To see the effectiveness of the grating, we can compute and plot the reflection and transmission via the flux measured by the flux monitor. As is visible in the plot, the structure is highly reflective in a narrow frequency band around the design frequency, allowing one to detect small variations in the frequency response due to the presence of biological materials."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T01:53:59.645924Z",
     "iopub.status.busy": "2023-02-03T01:53:59.645728Z",
     "iopub.status.idle": "2023-02-03T01:53:59.791791Z",
     "shell.execute_reply": "2023-02-03T01:53:59.791392Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 750x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rcParams.update({\"font.size\": 16})\n",
    "\n",
    "transmission = sim_data[\"flux_tran\"].flux\n",
    "reflection = 1 - transmission\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(7.5, 5))\n",
    "ax.plot(td.C_0 / freqs * 1e3, reflection, \"-k\", label=\"Reflection\")\n",
    "ax.plot(td.C_0 / freqs * 1e3, transmission, \"--r\", label=\"Transmission\")\n",
    "ax.set(\n",
    "    xlabel=\"Wavelength (nm)\",\n",
    "    ylabel=\"Flux\",\n",
    "    yscale=\"linear\",\n",
    "    xscale=\"linear\",\n",
    "    # xlim = [500, 550]\n",
    ")\n",
    "ax.legend()\n",
    "ax.grid(visible=True, which=\"both\", axis=\"both\", linewidth=0.4)\n",
    "plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
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       "msg_id": "497fe98d-c6a60e678d32c2758748c2d6_10989_8",
       "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\">% done (field decay = 2.04e-05) <span style=\"color: #f92672; text-decoration-color: #f92672\">━━━━━━━━━━━━━━━━━━━━━━━━</span><span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">╺━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\"> 60%</span> <span style=\"color: #008080; text-decoration-color: #008080\">-:--:--</span>\n% done (field decay = 2.04e-05) <span style=\"color: #f92672; text-decoration-color: #f92672\">━━━━━━━━━━━━━━━━━━━━━━━━</span><span style=\"color: #3a3a3a; text-decoration-color: #3a3a3a\">╺━━━━━━━━━━━━━━━</span> <span style=\"color: #800080; text-decoration-color: #800080\"> 60%</span> <span style=\"color: #008080; text-decoration-color: #008080\">-:--:--</span></pre>\n",
          "text/plain": "\r\u001b[2K% done (field decay = 2.04e-05) \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;5;237m╺\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 60%\u001b[0m \u001b[36m-:--:--\u001b[0m\n% done (field decay = 2.04e-05) \u001b[38;2;249;38;114m━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[38;5;237m╺\u001b[0m\u001b[38;5;237m━━━━━━━━━━━━━━━\u001b[0m \u001b[35m 60%\u001b[0m \u001b[36m-:--:--\u001b[0m"
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