AllDielectricStructuralColor.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# All-dielectric structural colors\n",
    "\n",
    "Structural colors are produced through the light manipulation at the nanoscale, where the periodic arrangement of materials dictates light phenomena such as reflection, diffraction, and interference. This approach offers a wide range of bright and vivid colors in various applications, ranging from displays and sensors to optical communication devices, without the need for traditional dyes or pigments. In this notebook we will use [Tidy3D](https://www.flexcompute.com/tidy3d/solver/) to simulate the optical response of an all-dielectric structural color metasurface, as proposed by `Bo Yang, Wenwei Liu, Zhancheng Li, Hua Cheng, Duk-Yong Choi, Shuqi Chen, and Jianguo Tian, \"Ultrahighly Saturated Structural Colors Enhanced by Multipolar-Modulated Metasurfaces,\" Nano Letters 19(7), 4221-4228 (2019)` [DOI: 10.1021/acs.nanolett.8b04923](https://doi.org/10.1021/acs.nanolett.8b04923). \n",
    "\n",
    "Here, we will show how to use the [Design](https://docs.flexcompute.com/projects/tidy3d/en/v2.6.0rc1/api/plugins/design_readme.html) plugin, introduced in `Tidy3d` version 2.6.0, to programmatically define and run a parameter sweep and then use its convenient container for managing the resulting data. See the [Design Space Exploration Plugin](https://www.flexcompute.com/tidy3d/examples/notebooks/Design/) notebook for a detailed example on how to use it.\n",
    "\n",
    "<img src=\"img/all_dielectric.png\" alt=\"MIM\"  width=\"400\"/>\n",
    "\n",
    "You can find related content in [MIM resonator](https://www.flexcompute.com/tidy3d/examples/notebooks/MIMResonator/), [Dielectric metasurface absorber](https://www.flexcompute.com/tidy3d/examples/notebooks/DielectricMetasurfaceAbsorber/), and [CMOS RGB image sensor](https://www.flexcompute.com/tidy3d/examples/notebooks/CMOSRGBSensor/).\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/examples/notebooks/DivergedFDTDSimulation/) to resolve it. \n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we will include all the libraries needed to run the notebook and also include the `Design` plugin as `tdd`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Standard python imports.\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "from scipy.signal import find_peaks\n",
    "import pandas as pd\n",
    "\n",
    "# Import regular tidy3d.\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n",
    "import tidy3d.plugins.design as tdd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation Set Up\n",
    "\n",
    "The device geometry is comprised of a periodic pattern of dielectric multilayer stacks. Each unit cell consists of a 60 nm thick $SiO_{3}N_{4}$ layer, a 140 nm thick $TiO_{2}$ spacer layer, and a 100 nm thick $SiO_{2}$ capping layer. The thin film multilayer was built by successive material depositions into a silica substrate. Below, we will define the device geometric parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "period = 0.35  # Unit cell period (um).\n",
    "gap = 0.15  # Gap between adjacent unit cells (um).\n",
    "sio2_thick = 0.10  # SiO2 dielectric thin film thickness (um).\n",
    "tio2_thick = 0.14  # TiO2 dielectric thin film thickness (um).\n",
    "si3n4_thick = 0.06  # Si3N4 dielectric thin film thickness (um).\n",
    "sub_thick = 0.6  # SiO2 substrate thickness (um).\n",
    "air_thick = 1.0  # Upper air layer thickness (um)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Material definition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_sio2 = 1.45  # SiO2 refractive index.\n",
    "n_tio2 = 2.41  # TiO2 refractive index.\n",
    "n_si3n4 = 2.00  # Si3N4 refractive index.\n",
    "\n",
    "mat_sio2 = td.Medium(permittivity=n_sio2**2)  # SiO2.\n",
    "mat_tio2 = td.Medium(permittivity=n_tio2**2)  # TiO2.\n",
    "mat_si3n4 = td.Medium(permittivity=n_si3n4**2)  # Si3N4.\n",
    "mat_air = td.Medium(permittivity=1)  # Air."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we define the wavelength, frequencies, and other simulation parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "wl_min = 0.400  # Minimum simulation wavelength (um).\n",
    "wl_max = 0.700  # Maximum simulation wavelength (um).\n",
    "n_wl = 151  # Number of wavelength points within the simulation bandwidth.\n",
    "wl_res = np.asarray([0.63, 0.52, 0.45])  # Resonance wavelengths of RGB pixels.\n",
    "run_time = 2e-12  # Simulation run time (s).\n",
    "\n",
    "wl_c = (wl_min + wl_max) / 2  # Central simulation wavelength (um).\n",
    "wl_range = np.linspace(wl_min, wl_max, n_wl)  # Simulation wavelength range (um).\n",
    "freq_c = td.C_0 / wl_c  # Central simulation frequency (Hz).\n",
    "freq_range = td.C_0 / wl_range  # Simulation frequency range (Hz).\n",
    "freq_bw = 0.5 * (freq_range[0] - freq_range[-1])  # Source bandwidth (Hz).\n",
    "freq_res = td.C_0 / wl_res  # Resonance frequencies (Hz).\n",
    "\n",
    "size_z = (\n",
    "    sub_thick + si3n4_thick + tio2_thick + sio2_thick + air_thick\n",
    ")  # Simulation size in the z-direction (um)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The next function defines the device unit cell. Here, we will define the dielectric stack structure, a plane wave source, and include a flux monitor to calculate the reflectance. The function accepts the unit cell `period` as an input parameter and returns a `Simulation` object. We will use it later as a pre-processing function to run the parameter sweep."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_sim(period: float = period) -> td.Simulation:\n",
    "    \"\"\"Builds the device simulation and returns a simulation object.\n",
    "    Parameters:\n",
    "        period: float\n",
    "            Device unit cell period (um).\n",
    "    Returns:\n",
    "        sim: tidy3d.Simulation\n",
    "            FDTD simulation object.\n",
    "    \"\"\"\n",
    "\n",
    "\n",
    "    _inf = 10\n",
    "\n",
    "    # Dielectric stack width (um).\n",
    "    width = period - gap\n",
    "\n",
    "    # Simulation size.\n",
    "    size_x = period\n",
    "    size_y = period\n",
    "\n",
    "    # Substrate.\n",
    "    substrate = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-_inf, -_inf, -_inf), rmax=(_inf, _inf, -size_z / 2 + sub_thick)\n",
    "        ),\n",
    "        medium=mat_sio2,\n",
    "    )\n",
    "\n",
    "    # Si3N4 layer.\n",
    "    si3n4_layer = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-width / 2, -width / 2, -size_z / 2 + sub_thick),\n",
    "            rmax=(width / 2, width / 2, -size_z / 2 + sub_thick + si3n4_thick),\n",
    "        ),\n",
    "        medium=mat_si3n4,\n",
    "    )\n",
    "\n",
    "    # TiO2 layer.\n",
    "    tio2_layer = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(-width / 2, -width / 2, -size_z / 2 + sub_thick + si3n4_thick),\n",
    "            rmax=(\n",
    "                width / 2,\n",
    "                width / 2,\n",
    "                -size_z / 2 + sub_thick + si3n4_thick + tio2_thick,\n",
    "            ),\n",
    "        ),\n",
    "        medium=mat_tio2,\n",
    "    )\n",
    "\n",
    "    # SiO2 layer.\n",
    "    sio2_layer = td.Structure(\n",
    "        geometry=td.Box.from_bounds(\n",
    "            rmin=(\n",
    "                -width / 2,\n",
    "                -width / 2,\n",
    "                -size_z / 2 + sub_thick + si3n4_thick + tio2_thick,\n",
    "            ),\n",
    "            rmax=(\n",
    "                width / 2,\n",
    "                width / 2,\n",
    "                -size_z / 2 + sub_thick + si3n4_thick + tio2_thick + sio2_thick,\n",
    "            ),\n",
    "        ),\n",
    "        medium=mat_sio2,\n",
    "    )\n",
    "\n",
    "    # Plane wave excitation source.\n",
    "    plane_wave = td.PlaneWave(\n",
    "        source_time=td.GaussianPulse(freq0=freq_c, fwidth=freq_bw),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "        center=(0, 0, size_z / 2 - wl_c / 2),\n",
    "        direction=\"-\",\n",
    "        pol_angle=0,\n",
    "        angle_theta=0,\n",
    "    )\n",
    "\n",
    "    # Flux monitor to measure the reflectance.\n",
    "    ref_monitor = td.FluxMonitor(\n",
    "        center=(0, 0, size_z / 2 - wl_c / 4),\n",
    "        size=(td.inf, td.inf, 0),\n",
    "        freqs=freq_range,\n",
    "        name=\"R\",\n",
    "    )\n",
    "\n",
    "    # Simulation\n",
    "    sim = td.Simulation(\n",
    "        size=(size_x, size_y, size_z),\n",
    "        center=(0, 0, 0),\n",
    "        grid_spec=td.GridSpec.auto(\n",
    "            min_steps_per_wvl=40, wavelength=(wl_min + wl_max) / 2\n",
    "        ),\n",
    "        structures=[substrate, si3n4_layer, tio2_layer, sio2_layer],\n",
    "        sources=[plane_wave],\n",
    "        monitors=[ref_monitor],\n",
    "        run_time=run_time,\n",
    "        boundary_spec=td.BoundarySpec(\n",
    "            x=td.Boundary.periodic(), y=td.Boundary.periodic(), z=td.Boundary.pml()\n",
    "        ),\n",
    "        symmetry=(-1, 1, 0),\n",
    "        medium=mat_air,\n",
    "    )\n",
    "    return sim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before running any simulation, we will visually inspect the simulation setup."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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   ],
   "source": [
    "sim = build_sim()\n",
    "sim.plot_3d()"
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Design Set Up\n",
    "\n",
    "Now, we want to visualize how the device reflectance spectrum evolves when we vary the unit cell period from 0.3 $\\mu m$ to 0.4 $\\mu m$. Then, we will use the [Design](https://docs.flexcompute.com/projects/tidy3d/en/v2.6.0rc1/api/plugins/design_readme.html) plugin to perform a parameter sweep. \n",
    "\n",
    "The `Design` plugin uses the concept of [DesignSpace](https://docs.flexcompute.com/projects/tidy3d/en/v2.6.0rc1/api/_autosummary/tidy3d.plugins.design.DesignSpace.html#tidy3d.plugins.design.DesignSpace), which gathers the design method and design parameters in a single object. So, we will start by defining our design parameter as a [tdd.ParameterFloat](https://docs.flexcompute.com/projects/tidy3d/en/v2.6.0rc1/api/_autosummary/tidy3d.plugins.design.ParameterFloat.html#tidy3d.plugins.design.ParameterFloat) instance and give it a range.\n",
    "\n",
    "> Note: we need to ensure that the parameter name argument matches the function argument name in our `build_sim()` function, which we will use to construct the simulations for the parameter sweep."
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "param_p = tdd.ParameterFloat(name=\"period\", span=(0.3, 0.4), num_points=11)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will define a [tdd.MethodGrid](https://docs.flexcompute.com/projects/tidy3d/en/v2.6.0rc1/api/_autosummary/tidy3d.plugins.design.MethodGrid.html#tidy3d.plugins.design.MethodGrid) which allows for a grid search over the parameter space, and then combine everything into a [tdd.DesignSpace](https://docs.flexcompute.com/projects/tidy3d/en/v2.6.0rc1/api/_autosummary/tidy3d.plugins.design.DesignSpace.html#tidy3d.plugins.design.DesignSpace)."
   ]
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  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "method = tdd.MethodGrid()\n",
    "design_space = tdd.DesignSpace(parameters=[param_p], method=method)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To run the parameter sweep, we need to define `pre`- and `post`-processing functions to respectively create the simulations and process their results. That enables the design plugin to take advantage of parallelism to perform `Batch` processing under the hood. \n",
    "\n",
    "Our `pre`-processing function is the `build_sim()` function defined before. In our `post`-processing function, we will illustrate how to return single values, like the reflectance peak value and wavelength, as well as multidimensional data as the raw monitor dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Post-processing function.\n",
    "def fn_post(sim_data: td.SimulationData = None) -> dict:\n",
    "    \"\"\"Pos-processing function to calculate and return the reflectance peak \n",
    "    in addition to the reflectance FluxMonitor.\n",
    "    Parameters:\n",
    "        sim_data: tidy3d.SimulationData\n",
    "            Simulation data object where to get results from.\n",
    "    Returns:\n",
    "        dict:\n",
    "            A dictionary containing the reflectance monitor,\n",
    "            the reflectance peak and wavelength.\n",
    "    \"\"\"    \n",
    "    R_data = sim_data[\"R\"]\n",
    "    R = R_data.flux.values\n",
    "    wavelength = td.C_0 / R_data.flux.f.values\n",
    "    peaks_id, _ = find_peaks(R, height=0.6)\n",
    "    peak_R = R[peaks_id[0]]\n",
    "    peak_wvl = wavelength[peaks_id[0]]\n",
    "    return {\n",
    "        \"Reflectance\": R_data,\n",
    "        \"Peak Reflectance\": peak_R,\n",
    "        \"Peak Wavelength\": peak_wvl,\n",
    "    }"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run Design\n",
    "\n",
    "Finally, we will pass our pre-processing and post-processing functions to the `DesignSpace.run_batch()` method to get our results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "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\">20:29:55 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">9b2a528d-fe89-46d1-add3-2908cafda49b</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
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       "\u001b[2;36m20:29:55 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.3\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m9b2a528d-fe89-46d1-add3-2908cafda49b\u001b[0m' and task_type \u001b[32m'FDTD'\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>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe8</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">9-46d1-add3-2908cafda49b'</span></a>.                                         \n",
       "</pre>\n"
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      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=357543;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=13386;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=357543;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=428105;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=357543;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\u001b\\\u001b[32m-9b2a528d-fe8\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=357543;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9b2a528d-fe89-46d1-add3-2908cafda49b\u001b\\\u001b[32m9-46d1-add3-2908cafda49b'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
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       "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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       "<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\">20:29:57 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.31</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">7d435325-28b0-4f2e-85bd-284cb1608d1e</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
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      "text/plain": [
       "\u001b[2;36m20:29:57 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.31\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b[0m' and task_type \u001b[32m'FDTD'\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>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">0-4f2e-85bd-284cb1608d1e'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=219137;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=747348;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=219137;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=747399;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=219137;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b\\\u001b[32m-7d435325-28b\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=219137;https://tidy3d.simulation.cloud/workbench?taskId=fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e\u001b\\\u001b[32m0-4f2e-85bd-284cb1608d1e'\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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     "metadata": {},
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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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       "<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\">20:29:58 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.32</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
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       "\u001b[2;36m20:29:58 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.32\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b[0m' and task_type \u001b[32m'FDTD'\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>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">b-4ea8-8353-9854d5fccbfc'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=977447;https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=775167;https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=977447;https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=790265;https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=977447;https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b\\\u001b[32m-20fc4a7a-2a2\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=977447;https://tidy3d.simulation.cloud/workbench?taskId=fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc\u001b\\\u001b[32mb-4ea8-8353-9854d5fccbfc'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
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       "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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       "<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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       "<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\">20:30:00 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.33</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">83f30131-b607-4fb4-b034-c8d9e367b275</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
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       "\u001b[2;36m20:30:00 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.33\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m83f30131-b607-4fb4-b034-c8d9e367b275\u001b[0m' and task_type \u001b[32m'FDTD'\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>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b60</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">7-4fb4-b034-c8d9e367b275'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=27904;https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=438414;https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27904;https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=721396;https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=27904;https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\u001b\\\u001b[32m-83f30131-b60\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=27904;https://tidy3d.simulation.cloud/workbench?taskId=fdve-83f30131-b607-4fb4-b034-c8d9e367b275\u001b\\\u001b[32m7-4fb4-b034-c8d9e367b275'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7ee03473f45544139085b5e96f1a29a0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:01 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.34</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">f7685166-e804-4dfa-9e69-f5f69acffc88</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:01 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.34\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93mf7685166-e804-4dfa-9e69-f5f69acffc88\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e80</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">4-4dfa-9e69-f5f69acffc88'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=974702;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=629276;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=974702;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=604112;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=974702;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\u001b\\\u001b[32m-f7685166-e80\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=974702;https://tidy3d.simulation.cloud/workbench?taskId=fdve-f7685166-e804-4dfa-9e69-f5f69acffc88\u001b\\\u001b[32m4-4dfa-9e69-f5f69acffc88'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "79dee1d202154bc3a3b55cc6188c65a4",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:03 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.35</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">d575b9e7-55d3-4458-a3ed-8e06affa8b9f</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:03 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.35\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93md575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">3-4458-a3ed-8e06affa8b9f'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=582426;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=143766;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=582426;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=620524;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=582426;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b\\\u001b[32m-d575b9e7-55d\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=582426;https://tidy3d.simulation.cloud/workbench?taskId=fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f\u001b\\\u001b[32m3-4458-a3ed-8e06affa8b9f'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "e9462edf5a234d5a9a563d9747bdf653",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:04 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.36</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">9bd4073d-9a71-4a67-be4d-755b5aa303b6</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:04 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.36\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a7</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">1-4a67-be4d-755b5aa303b6'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=56780;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=95742;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=56780;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=131759;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=56780;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b\\\u001b[32m-9bd4073d-9a7\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=56780;https://tidy3d.simulation.cloud/workbench?taskId=fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6\u001b\\\u001b[32m1-4a67-be4d-755b5aa303b6'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "d53b8e082d2b4ec7992afe614ea8a4e2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:06 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.37</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">b8876ba3-598a-4ca9-a7b6-59e134e16f51</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:06 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.37\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93mb8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">a-4ca9-a7b6-59e134e16f51'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=432666;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=45163;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=432666;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=513279;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=432666;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b\\\u001b[32m-b8876ba3-598\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=432666;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51\u001b\\\u001b[32ma-4ca9-a7b6-59e134e16f51'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "19ebd2815d0345eda27f00169005d395",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:07 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.38</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">b8880447-2054-4996-8bc0-177b61aaaf73</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:07 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.38\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93mb8880447-2054-4996-8bc0-177b61aaaf73\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-205</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">4-4996-8bc0-177b61aaaf73'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=827012;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=890112;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=827012;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=285578;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=827012;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\u001b\\\u001b[32m-b8880447-205\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=827012;https://tidy3d.simulation.cloud/workbench?taskId=fdve-b8880447-2054-4996-8bc0-177b61aaaf73\u001b\\\u001b[32m4-4996-8bc0-177b61aaaf73'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5f1bc2c9708544dcadb69f3135ee8926",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:09 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.39</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                      \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">55144cae-1c65-4895-9942-bca2ba98ae5c</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:09 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.39\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                      \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m55144cae-1c65-4895-9942-bca2ba98ae5c\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c6</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">5-4895-9942-bca2ba98ae5c'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=947489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=979369;https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=947489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=430947;https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=947489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\u001b\\\u001b[32m-55144cae-1c6\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=947489;https://tidy3d.simulation.cloud/workbench?taskId=fdve-55144cae-1c65-4895-9942-bca2ba98ae5c\u001b\\\u001b[32m5-4895-9942-bca2ba98ae5c'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6fc495ac10b04ae5a9af00bc2bd18ad2",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
      "text/plain": []
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">20:30:10 -03 </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'{'</span>period': <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.4</span><span style=\"font-weight: bold\">}</span><span style=\"color: #008000; text-decoration-color: #008000\">' with task_id </span>                       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'</span>fdve-<span style=\"color: #ffff00; text-decoration-color: #ffff00\">061bc94e-2ef2-405b-8a48-231e3e728d55</span>' and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:10 -03\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'\u001b[0mperiod': \u001b[1;36m0.4\u001b[0m\u001b[1m}\u001b[0m\u001b[32m' with task_id \u001b[0m                       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'\u001b[0mfdve-\u001b[93m061bc94e-2ef2-405b-8a48-231e3e728d55\u001b[0m' and task_type \u001b[32m'FDTD'\u001b[0m.  \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">2-405b-8a48-231e3e728d55'</span></a>.                                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=869376;https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=878861;https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=869376;https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=156447;https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\u001b\\\u001b[32mfdve\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=869376;https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\u001b\\\u001b[32m-061bc94e-2ef\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=869376;https://tidy3d.simulation.cloud/workbench?taskId=fdve-061bc94e-2ef2-405b-8a48-231e3e728d55\u001b\\\u001b[32m2-405b-8a48-231e3e728d55'\u001b[0m\u001b]8;;\u001b\\.                                         \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "version_minor": 0
      },
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       "Output()"
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       "</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\">20:30:18 -03 </span>Started working on Batch.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m20:30:18 -03\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch.                                          \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\">20:31:52 -03 </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.275</span> for the whole batch.                \n",
       "</pre>\n"
      ],
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       "\u001b[2;36m20:31:52 -03\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.275\u001b[0m for the whole batch.                \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Batch has completed.                                               \n",
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mUse \u001b[32m'Batch.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed FlexCredit cost after the\n",
       "\u001b[2;36m             \u001b[0mBatch has completed.                                               \n"
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       "\u001b[2;36m20:32:02 -03\u001b[0m\u001b[2;36m \u001b[0mBatch complete.                                                    \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-9b2a528d-fe89-46d1-add3-2908cafda49b.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:07 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0m.\u001b[35m/\u001b[0m\u001b[95mfdve-9b2a528d-fe89-46d1-add3-2908cafda49b.hdf5\u001b[0m                   \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-7d435325-28b0-4f2e-85bd-284cb1608d1e.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:08 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0m.\u001b[35m/\u001b[0m\u001b[95mfdve-7d435325-28b0-4f2e-85bd-284cb1608d1e.hdf5\u001b[0m                   \n"
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       "</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\">20:32:10 -03 </span>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:10 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0m.\u001b[35m/\u001b[0m\u001b[95mfdve-20fc4a7a-2a2b-4ea8-8353-9854d5fccbfc.hdf5\u001b[0m                   \n"
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       "</pre>\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-83f30131-b607-4fb4-b034-c8d9e367b275.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:12 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-f7685166-e804-4dfa-9e69-f5f69acffc88.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:14 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-d575b9e7-55d3-4458-a3ed-8e06affa8b9f.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:16 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:18 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0m.\u001b[35m/\u001b[0m\u001b[95mfdve-9bd4073d-9a71-4a67-be4d-755b5aa303b6.hdf5\u001b[0m                   \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-b8876ba3-598a-4ca9-a7b6-59e134e16f51.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:20 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \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\">20:32:22 -03 </span>loading simulation from                                            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-b8880447-2054-4996-8bc0-177b61aaaf73.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:22 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
       "\u001b[2;36m             \u001b[0m.\u001b[35m/\u001b[0m\u001b[95mfdve-b8880447-2054-4996-8bc0-177b61aaaf73.hdf5\u001b[0m                   \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-55144cae-1c65-4895-9942-bca2ba98ae5c.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:24 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>.<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">fdve-061bc94e-2ef2-405b-8a48-231e3e728d55.hdf5</span>                   \n",
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       "\u001b[2;36m20:32:26 -03\u001b[0m\u001b[2;36m \u001b[0mloading simulation from                                            \n",
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   "source": [
    "results = design_space.run_batch(fn_pre=build_sim, fn_post=fn_post)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Design Results\n",
    "\n",
    "To analyze the design results we will create a `dataframe` using the `to_dataframe()` method. This dataframe shows the sweep parameter `period` as well as the post-processing function results. As one can see, we can return single values like `Peak Reflectance` and `Peak Wavelength`, or higher dimensional datasets such as `FluxMonitor` dataset included in the `Reflectance` column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>period</th>\n",
       "      <th>Reflectance</th>\n",
       "      <th>Peak Reflectance</th>\n",
       "      <th>Peak Wavelength</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.30</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>1.013392</td>\n",
       "      <td>0.444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.31</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>1.012020</td>\n",
       "      <td>0.464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.32</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.999940</td>\n",
       "      <td>0.482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.33</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.996101</td>\n",
       "      <td>0.502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.34</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.995063</td>\n",
       "      <td>0.520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.35</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.997233</td>\n",
       "      <td>0.538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.36</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.996590</td>\n",
       "      <td>0.556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.37</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.998571</td>\n",
       "      <td>0.572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.38</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.992530</td>\n",
       "      <td>0.588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.39</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.990036</td>\n",
       "      <td>0.606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.40</td>\n",
       "      <td>type='FluxData' monitor=FluxMonitor(type='Flux...</td>\n",
       "      <td>0.989468</td>\n",
       "      <td>0.622</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    period                                        Reflectance  \\\n",
       "0     0.30  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "1     0.31  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "2     0.32  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "3     0.33  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "4     0.34  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "5     0.35  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "6     0.36  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "7     0.37  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "8     0.38  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "9     0.39  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "10    0.40  type='FluxData' monitor=FluxMonitor(type='Flux...   \n",
       "\n",
       "    Peak Reflectance  Peak Wavelength  \n",
       "0           1.013392            0.444  \n",
       "1           1.012020            0.464  \n",
       "2           0.999940            0.482  \n",
       "3           0.996101            0.502  \n",
       "4           0.995063            0.520  \n",
       "5           0.997233            0.538  \n",
       "6           0.996590            0.556  \n",
       "7           0.998571            0.572  \n",
       "8           0.992530            0.588  \n",
       "9           0.990036            0.606  \n",
       "10          0.989468            0.622  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = results.to_dataframe()\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use the built-in dataframe functions to plot and analyze information. For instance, let's plot the peak reflectance values and wavelengths to observe how these values change with respect to device period."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4), tight_layout=True)\n",
    "df.plot(\n",
    "    x=\"period\",\n",
    "    y=\"Peak Reflectance\",\n",
    "    kind=\"scatter\",\n",
    "    ax=ax1,\n",
    "    title=\"Peak Reflectance X Period\",\n",
    "    xlabel=\"Period (um)\",\n",
    "    ylabel=\"R\",\n",
    "    ylim=[0, 1.2],\n",
    "    color=\"Red\",\n",
    ")\n",
    "df.plot(\n",
    "    x=\"period\",\n",
    "    y=\"Peak Wavelength\",\n",
    "    kind=\"scatter\",\n",
    "    ax=ax2,\n",
    "    title=\"Peak Wavelength X Period\",\n",
    "    xlabel=\"Period (um)\",\n",
    "    ylabel=\"Wavelength (um)\",\n",
    "    color=\"Blue\",\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As one can see, the reflectance peak is very robust with respect to device period. On the other hand, an almost linear relationship is shown between the reflectance peak and the device period. These results are in agreement to the ones in the reference paper. \n",
    "\n",
    "Now, we will create another dataframe to plot the reflectance spectrum versus wavelength for the different device periods. Here, we will unpack the `FluxMonitor` dataset and access the flux values and frequencies."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0.3</th>\n",
       "      <th>0.31</th>\n",
       "      <th>0.32</th>\n",
       "      <th>0.33</th>\n",
       "      <th>0.34</th>\n",
       "      <th>0.35</th>\n",
       "      <th>0.36</th>\n",
       "      <th>0.37</th>\n",
       "      <th>0.38</th>\n",
       "      <th>0.39</th>\n",
       "      <th>0.4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wavelength</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.400</th>\n",
       "      <td>0.027893</td>\n",
       "      <td>0.012195</td>\n",
       "      <td>0.006991</td>\n",
       "      <td>0.004796</td>\n",
       "      <td>0.002578</td>\n",
       "      <td>0.002097</td>\n",
       "      <td>0.002713</td>\n",
       "      <td>0.004102</td>\n",
       "      <td>0.006654</td>\n",
       "      <td>0.107062</td>\n",
       "      <td>0.011689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.402</th>\n",
       "      <td>0.029418</td>\n",
       "      <td>0.012601</td>\n",
       "      <td>0.007088</td>\n",
       "      <td>0.005307</td>\n",
       "      <td>0.002887</td>\n",
       "      <td>0.002009</td>\n",
       "      <td>0.002290</td>\n",
       "      <td>0.003307</td>\n",
       "      <td>0.005032</td>\n",
       "      <td>0.334151</td>\n",
       "      <td>0.007038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.404</th>\n",
       "      <td>0.031144</td>\n",
       "      <td>0.012834</td>\n",
       "      <td>0.007161</td>\n",
       "      <td>0.005754</td>\n",
       "      <td>0.003348</td>\n",
       "      <td>0.002062</td>\n",
       "      <td>0.002017</td>\n",
       "      <td>0.002701</td>\n",
       "      <td>0.003981</td>\n",
       "      <td>0.207237</td>\n",
       "      <td>0.009618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.406</th>\n",
       "      <td>0.033140</td>\n",
       "      <td>0.013216</td>\n",
       "      <td>0.007265</td>\n",
       "      <td>0.006089</td>\n",
       "      <td>0.003873</td>\n",
       "      <td>0.002279</td>\n",
       "      <td>0.001882</td>\n",
       "      <td>0.002263</td>\n",
       "      <td>0.003112</td>\n",
       "      <td>0.048685</td>\n",
       "      <td>0.013553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.408</th>\n",
       "      <td>0.035495</td>\n",
       "      <td>0.013779</td>\n",
       "      <td>0.007109</td>\n",
       "      <td>0.006282</td>\n",
       "      <td>0.004485</td>\n",
       "      <td>0.002585</td>\n",
       "      <td>0.001875</td>\n",
       "      <td>0.001946</td>\n",
       "      <td>0.002427</td>\n",
       "      <td>0.016134</td>\n",
       "      <td>0.021842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 0.3      0.31      0.32      0.33      0.34      0.35  \\\n",
       "Wavelength                                                               \n",
       "0.400       0.027893  0.012195  0.006991  0.004796  0.002578  0.002097   \n",
       "0.402       0.029418  0.012601  0.007088  0.005307  0.002887  0.002009   \n",
       "0.404       0.031144  0.012834  0.007161  0.005754  0.003348  0.002062   \n",
       "0.406       0.033140  0.013216  0.007265  0.006089  0.003873  0.002279   \n",
       "0.408       0.035495  0.013779  0.007109  0.006282  0.004485  0.002585   \n",
       "\n",
       "                0.36      0.37      0.38      0.39       0.4  \n",
       "Wavelength                                                    \n",
       "0.400       0.002713  0.004102  0.006654  0.107062  0.011689  \n",
       "0.402       0.002290  0.003307  0.005032  0.334151  0.007038  \n",
       "0.404       0.002017  0.002701  0.003981  0.207237  0.009618  \n",
       "0.406       0.001882  0.002263  0.003112  0.048685  0.013553  \n",
       "0.408       0.001875  0.001946  0.002427  0.016134  0.021842  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_wl = pd.DataFrame({\"Wavelength\": td.C_0 / df.loc[0, \"Reflectance\"].flux.f.values})\n",
    "df_R = pd.DataFrame(\n",
    "    {df.loc[i, \"period\"]: df.loc[i, \"Reflectance\"].flux.values for i in df.index}\n",
    ")\n",
    "df_R_wl = pd.concat([df_wl, df_R], axis=1)\n",
    "df_R_wl.set_index(\"Wavelength\", inplace=True)\n",
    "df_R_wl.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = df_R_wl.plot(\n",
    "    title=\"Reflectance Spectrum for Different Device Period\",\n",
    "    xlabel=\"Wavelength (um)\",\n",
    "    ylabel=\"R\",\n",
    ")\n",
    "ax.legend([f\"period = {p:.2f} $\\\\mu m$\" for p in df_R_wl.columns],\n",
    "          bbox_to_anchor=(1.02, 1.02), \n",
    "          loc='upper left')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "applications": [
   "Metamaterials, gratings, and other periodic structures",
   "Structural color"
  ],
  "description": "This notebook shows how to build and simulate an all-dielectric structural color device using Tidy3D | FDTD design plugin.",
  "feature_image": "./img/all_dielectric.png",
  "features": [
   "Design plugin"
  ],
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "keywords": "structural color, all-dielectric, color filter, design, parameter sweep, design plugin, design of experiments, DoE, Tidy3D, FDTD",
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.12"
  },
  "title": "How to build and simulate an all-dielectric structural color device using Tidy3D | FDTD design plugin"
 },
 "nbformat": 4,
 "nbformat_minor": 4
}