{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Quickstart\n",
        "\n",
        "This is a minimal Tidy3D script showing the FDTD simulation of a\n",
        "dielectric cube in the presence of a point dipole.\n",
        "\n",
        "Before running this notebook, make sure to have:\n",
        "\n",
        "1.  [Installed\n",
        "    tidy3d](../quickstart.html#installation-of-tidy3d-python-api)\n",
        "2.  [Generate your free API\n",
        "    key](https://tidy3d.simulation.cloud/account)\n",
        "3.  [Optional - Configured your API\n",
        "    key](../quickstart.html#installation-of-tidy3d-python-api#linking-registration)"
      ],
      "id": "bc2419af-209f-451e-b756-bda6d01a92da"
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [],
      "source": [
        "# import packages and authenticate (if needed)\n",
        "import matplotlib.pylab as plt\n",
        "import numpy as np\n",
        "import tidy3d as td\n",
        "import tidy3d.web as web\n",
        "\n",
        "# web.configure(\"YOUR API KEY GOES HERE\")"
      ],
      "id": "a09f76fa"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "First, we use the convenience class\n",
        "[FreqRange](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FreqRange.html)\n",
        "to define the basic frequency-related parameters of the simulation."
      ],
      "id": "6685966c-a852-4063-b95c-5994ac126f4c"
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "lda0 = 0.75  # wavelength of interest (length scales are micrometers in Tidy3D)\n",
        "freq0 = td.C_0 / lda0  # frequency of interest\n",
        "fwidth = freq0 / 10.0  # desired freq. bandwidth\n",
        "\n",
        "freq_range = td.FreqRange(freq0=freq0, fwidth=fwidth)  # set frequency range"
      ],
      "id": "9dc4d8ad"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a\n",
        "[Structure](../api/_autosummary/tidy3d.Structure.html#tidy3d.Structure)\n",
        "from a [Geometry](../api/geometry.html) like this rectangular prism\n",
        "[Box](../api/_autosummary/tidy3d.Box.html#tidy3d.Box) and assign a\n",
        "[Medium](../api/_autosummary/tidy3d.Medium.html#tidy3d.Medium) to\n",
        "represent its optical properties."
      ],
      "id": "c7f7c2f2-74e3-4d85-9d07-d9198f013f02"
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {},
      "outputs": [],
      "source": [
        "square = td.Structure(\n",
        "    geometry=td.Box(center=(0, 0, 0), size=(1.5, 1.5, 1.5)), medium=td.Medium(permittivity=2.0)\n",
        ")"
      ],
      "id": "aa54ca25"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a [Source](../api/sources.html). In this case, it is a\n",
        "[PointDipole](../api/_autosummary/tidy3d.PointDipole.html#tidy3d.PointDipole),\n",
        "which is a uniform current source with a zero size."
      ],
      "id": "7aacc269-f072-4385-beec-19b787909152"
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {},
      "outputs": [],
      "source": [
        "# create source\n",
        "source = td.PointDipole(\n",
        "    center=(-1.5, 0, 0),  # position of the dipole\n",
        "    source_time=freq_range.to_gaussian_pulse(),  # time profile of the source\n",
        "    polarization=\"Ey\",  # polarization of the dipole\n",
        ")"
      ],
      "id": "7d5b2e16"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Create a [Monitor](../api/monitors.html) like a\n",
        "[FieldMonitor](../api/_autosummary/tidy3d.FieldMonitor.html#tidy3d.FieldMonitor)\n",
        "to record electromagnetic fields in the frequency domain at `freq0`."
      ],
      "id": "c759266b-a82f-4bd0-8ad5-5f08bda78181"
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {},
      "outputs": [],
      "source": [
        "# create monitor\n",
        "monitor = td.FieldMonitor(\n",
        "    center=(0, 0, 0),  # center of the monitor\n",
        "    size=(td.inf, td.inf, 0),  # size of the monitor\n",
        "    freqs=freq_range.freqs(num_points=1),  # frequency points to record the fields at\n",
        "    name=\"fields\",\n",
        ")"
      ],
      "id": "ee3fed07"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "All these components are used to create a Tidy3D\n",
        "[Simulation](../api/_autosummary/tidy3d.Simulation.html):"
      ],
      "id": "b469a3c7-6f88-4b30-a0b6-4fbf0d0a5fde"
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {},
      "outputs": [],
      "source": [
        "sim = td.Simulation(\n",
        "    size=(4, 3, 3),  # simulation domain size\n",
        "    grid_spec=td.GridSpec.auto(\n",
        "        min_steps_per_wvl=25\n",
        "    ),  # automatic nonuniform FDTD grid with 25 grids per wavelength in the material\n",
        "    structures=[square],\n",
        "    sources=[source],\n",
        "    monitors=[monitor],\n",
        "    run_time=3e-13,  # physical simulation time in second\n",
        ")"
      ],
      "id": "7d989344"
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "\n",
              "    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"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\" ></div>\n",
              "    <script>\n",
              "        \n",
              "        /**\n",
              "        * Simulation Viewer Injector\n",
              "        *\n",
              "        * Monitors the document for elements being added in the form:\n",
              "        *\n",
              "        *    <div class=\"simulation-viewer\" data-width=\"800\" data-height=\"800\" data-simulation=\"{...}\" />\n",
              "        *\n",
              "        * This script will then inject an iframe to the viewer application, and pass it the simulation data\n",
              "        * via the postMessage API on request. The script may be safely included multiple times, with only the\n",
              "        * configuration of the first started script (e.g. viewer URL) applying.\n",
              "        *\n",
              "        */\n",
              "        (function() {\n",
              "            const TARGET_CLASS = \"simulation-viewer\";\n",
              "            const ACTIVE_CLASS = \"simulation-viewer-active\";\n",
              "            const VIEWER_URL = \"https://tidy3d.simulation.cloud/simulation-viewer\";\n",
              "\n",
              "            class SimulationViewerInjector {\n",
              "                constructor() {\n",
              "                    for (var node of document.getElementsByClassName(TARGET_CLASS)) {\n",
              "                        this.injectViewer(node);\n",
              "                    }\n",
              "\n",
              "                    // Monitor for newly added nodes to the DOM\n",
              "                    this.observer = new MutationObserver(this.onMutations.bind(this));\n",
              "                    this.observer.observe(document.body, {childList: true, subtree: true});\n",
              "                }\n",
              "\n",
              "                onMutations(mutations) {\n",
              "                    for (var mutation of mutations) {\n",
              "                        if (mutation.type === 'childList') {\n",
              "                            /**\n",
              "                            * Have found that adding the element does not reliably trigger the mutation observer.\n",
              "                            * It may be the case that setting content with innerHTML does not trigger.\n",
              "                            *\n",
              "                            * It seems to be sufficient to re-scan the document for un-activated viewers\n",
              "                            * whenever an event occurs, as Jupyter triggers multiple events on cell evaluation.\n",
              "                            */\n",
              "                            var viewers = document.getElementsByClassName(TARGET_CLASS);\n",
              "                            for (var node of viewers) {\n",
              "                                this.injectViewer(node);\n",
              "                            }\n",
              "                        }\n",
              "                    }\n",
              "                }\n",
              "\n",
              "                injectViewer(node) {\n",
              "                    // (re-)check that this is a valid simulation container and has not already been injected\n",
              "                    if (node.classList.contains(TARGET_CLASS) && !node.classList.contains(ACTIVE_CLASS)) {\n",
              "                        // Mark node as injected, to prevent re-runs\n",
              "                        node.classList.add(ACTIVE_CLASS);\n",
              "\n",
              "                        var uuid;\n",
              "                        if (window.crypto && window.crypto.randomUUID) {\n",
              "                            uuid = window.crypto.randomUUID();\n",
              "                        } else {\n",
              "                            uuid = \"\" + Math.random();\n",
              "                        }\n",
              "\n",
              "                        var frame = document.createElement(\"iframe\");\n",
              "                        frame.width = node.dataset.width || 800;\n",
              "                        frame.height = node.dataset.height || 800;\n",
              "                        frame.style.cssText = `width:${frame.width}px;height:${frame.height}px;max-width:none;border:0;display:block`\n",
              "                        frame.src = VIEWER_URL + \"?uuid=\" + uuid;\n",
              "\n",
              "                        var postMessageToViewer;\n",
              "                        postMessageToViewer = event => {\n",
              "                            if(event.data.type === 'viewer' && event.data.uuid===uuid){\n",
              "                                frame.contentWindow.postMessage({ type: 'jupyter', uuid, value: node.dataset.simulation, fileType: 'hdf5'}, '*');\n",
              "\n",
              "                                // Run once only\n",
              "                                window.removeEventListener('message', postMessageToViewer);\n",
              "                            }\n",
              "                        };\n",
              "                        window.addEventListener(\n",
              "                            'message',\n",
              "                            postMessageToViewer,\n",
              "                            false\n",
              "                        );\n",
              "\n",
              "                        node.appendChild(frame);\n",
              "                    }\n",
              "                }\n",
              "            }\n",
              "\n",
              "            if (!window.simulationViewerInjector) {\n",
              "                window.simulationViewerInjector = new SimulationViewerInjector();\n",
              "            }\n",
              "        })();\n",
              "    \n",
              "    </script>\n",
              "    "
            ]
          }
        }
      ],
      "source": [
        "# visualize in 3D\n",
        "sim.plot_3d()"
      ],
      "id": "c3782a77"
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "simulation grid is shaped [179, 147, 147] for 3 million cells."
          ]
        }
      ],
      "source": [
        "print(\n",
        "    f\"simulation grid is shaped {sim.grid.num_cells} for {int(np.prod(sim.grid.num_cells) / 1e6)} million cells.\"\n",
        ")"
      ],
      "id": "d9ba33b3"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "The [python web API](../api/submit_simulations.html) is used to\n",
        "[run](../api/_autosummary/tidy3d.web.run.html#tidy3d.web.run) your\n",
        "simulation quickly in the cloud. The output data is stored in a\n",
        "[SimulationData](../api/_autosummary/tidy3d.SimulationData.html#tidy3d.SimulationData)\n",
        "container."
      ],
      "id": "a70662aa-094b-4e8c-9dad-0eb1bc726bd1"
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:23:40 UTC </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'quickstart'</span> with resource_id                         \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-fe74f8ae-8cde-476c-8db1-ca4e7c7c7a6a'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'FDTD'</span>.  \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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-fe74f8ae-8cde-476c-8db1-ca4e7c7c7a6a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-fe74f8ae-8cd</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fe74f8ae-8cde-476c-8db1-ca4e7c7c7a6a\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">e-476c-8db1-ca4e7c7c7a6a'</span></a>.                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/9b36e144-ddb6-41f8-8dd8-30b62b26a870\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"3f72d9eb62994edf977a126a6b7699e9\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:23:42 UTC </span>Estimated FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. This assumes the FDTD solver runs\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>for the full simulation time; if early shutoff is reached, the     \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed cost can be lower. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the  \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>billed FlexCredit cost after a simulation run.                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>status = queued                                                    \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>To cancel the simulation, use <span style=\"color: #008000; text-decoration-color: #008000\">'web.abort(task_id)'</span> or              \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'web.delete(task_id)'</span> or abort/delete the task in the web UI.      \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Terminating the Python script will not stop the job running on the \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>cloud.                                                             \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"7c9384e95f944f388d7958be2bff2d68\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:23:56 UTC </span>starting up solver                                                 \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>running solver                                                     \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"49e6a87443ef4b84872fc0a765bf2858\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:23:58 UTC </span>early shutoff detected at <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">31</span>%, exiting.                            \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>status = postprocess                                               \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"47b29a81e7d347cebfc23e49a2b61906\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:24:01 UTC </span>status = success                                                   \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:24:03 UTC </span>View simulation result at                                          \n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fe74f8ae-8cde-476c-8db1-ca4e7c7c7a6a\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">'https://tidy3d.simulation.cloud/workbench?taskId=fdve-fe74f8ae-8cd</span></a>\n",
              "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=fdve-fe74f8ae-8cde-476c-8db1-ca4e7c7c7a6a\" target=\"_blank\"><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">e-476c-8db1-ca4e7c7c7a6a'</span></a><span style=\"color: #000080; text-decoration-color: #000080; text-decoration: underline\">.</span>                                         \n",
              "</pre>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
            "text/html": [
              "<script type=\"application/vnd.jupyter.widget-view+json\">\n",
              "{\"model_id\":\"9b1397dbd9f74a99b91c45de595bf554\",\"version_major\":2,\"version_minor\":0,\"quarto_mimetype\":\"application/vnd.jupyter.widget-view+json\"}\n",
              "</script>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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>"
            ]
          }
        },
        {
          "output_type": "display_data",
          "metadata": {},
          "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\">07:24:04 UTC </span>Loading results from data/data.hdf5                                \n",
              "</pre>"
            ]
          }
        }
      ],
      "source": [
        "# run simulation\n",
        "data = td.web.run(sim, task_name=\"quickstart\", path=\"data/data.hdf5\", verbose=True)"
      ],
      "id": "3989708f"
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[07:23:51] INFO: Auto meshing using wavelength 0.7519 defined from sources.     \n",
            "           INFO: Auto meshing using wavelength 0.7519 defined from sources.     \n",
            "           INFO: Auto meshing using wavelength 0.7519 defined from sources.     \n",
            "[07:23:52] USER: Simulation domain Nx, Ny, Nz: [179, 147, 147]                  \n",
            "           USER: Applied symmetries: (0, 0, 0)                                  \n",
            "           USER: Number of computational grid points: 4.0184e+06.               \n",
            "           USER: Subpixel averaging method: SubpixelSpec()                      \n",
            "           USER: Number of time steps: 7.5090e+03                               \n",
            "           USER: Automatic shutoff factor: 1.00e-05                             \n",
            "           USER: Time step (s): 3.9959e-17                                      \n",
            "           USER:                                                                \n",
            "                                                                                \n",
            "           USER: Compute source modes time (s):     0.2004                      \n",
            "           USER: Rest of setup time (s):            0.2214                      \n",
            "[07:23:53] USER: Compute monitor modes time (s):    0.0002                      \n",
            "[07:23:56] USER: Solver time (s):                   2.6350                      \n",
            "           USER: Time-stepping speed (cells/s):     4.87e+09                    \n",
            "           USER: Loading data for monitor fields                                \n",
            "           USER: Post-processing time (s):          0.2674                      \n",
            "\n",
            " ====== SOLVER LOG ====== \n",
            "\n",
            "Processing grid and structures...\n",
            "Building FDTD update coefficients...\n",
            "Solver setup time (s):             0.6459\n",
            "\n",
            "Running solver for 7509 time steps...\n",
            "- Time step    300 / time 1.20e-14s (  4 % done), field decay: 1.00e+00\n",
            "- Time step    600 / time 2.40e-14s (  8 % done), field decay: 1.00e+00\n",
            "- Time step    901 / time 3.60e-14s ( 12 % done), field decay: 1.00e+00\n",
            "- Time step   1201 / time 4.80e-14s ( 16 % done), field decay: 3.09e-01\n",
            "- Time step   1501 / time 6.00e-14s ( 20 % done), field decay: 3.09e-01\n",
            "- Time step   1802 / time 7.20e-14s ( 24 % done), field decay: 1.73e-03\n",
            "- Time step   2102 / time 8.40e-14s ( 28 % done), field decay: 1.25e-05\n",
            "- Time step   2400 / time 9.59e-14s ( 31 % done), field decay: 1.81e-07\n",
            "Field decay smaller than shutoff factor, exiting solver.\n",
            "Time-stepping time (s):            1.9824\n",
            "Data write time (s):               0.0043\n"
          ]
        }
      ],
      "source": [
        "# see the log\n",
        "print(data.log)"
      ],
      "id": "bfaee059"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "This monitor data can be easily plotted through available [plot\n",
        "methods](../api/_autosummary/tidy3d.SimulationData.html#tidy3d.SimulationData.plot_field).\n",
        "You can also save, modify, and custom plot the raw\n",
        "[FieldData](../api/_autosummary/tidy3d.FieldData.html) and more."
      ],
      "id": "15978926-a4e5-49c7-ba89-abdd8197a426"
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [
        {
          "output_type": "display_data",
          "metadata": {},
          "data": {
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R/eu9yqaZmcbqHTPy++47Bk17QsGzXtSwXj/NyqaWnVojeWvVUW0qoj6auF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\nkU0nTwIKvWu5PMnqLZLjfI6sAHucadTOrsvSt7vNL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/Bv/zfJ5Ohfv89tz5LtWiIhhCXS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\nP2i0PbyPbVXcwB47IlNRuWorKjeoytxMZdm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          }
        }
      ],
      "source": [
        "# plot the field data stored in the monitor\n",
        "ax = data.plot_field(\"fields\", \"Ey\", z=0)"
      ],
      "id": "f29efaf6"
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "See all our\n",
        "[examples](https://www.flexcompute.com/tidy3d/learning-center/example-library/)\n",
        "to help you with your own designs!"
      ],
      "id": "1f9a158b-2fc2-4159-bfb4-9ef3cd66ddc8"
    }
  ],
  "nbformat": 4,
  "nbformat_minor": 5,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  }
}