{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Total-Field Scattered-Field Plane Wave Source\n",
    "\n",
    "This tutorial demonstrates the use of the [total-field scattered-field (TFSF) source](../_autosummary/tidy3d.TFSF.html) in `Tidy3D`.\n",
    "\n",
    "The TFSF source allows specifying a box region into which a plane wave is injected. Fields inside this region can be interpreted as the superposition of the incident field and the scattered field due to any scatterers present in the simulation domain. The fields at the edges of the TFSF box are modified at each time step such that the incident field is cancelled out, so that all fields _outside_ the TFSF box are scattered fields only. This is useful in scenarios where one is interested in computing scattered fields only, for example when computing scattered cross sections of various objects. For an application example of radar cross section calculation using the TFSF technique, see [this notebook](../notebooks/Near2FarSphereRCS.html).\n",
    "\n",
    "In this notebook, various situations in which the TFSF source can be applied will be discussed through several examples, including the use of finite- or infinite-extent TFSF regions, angled plane wave injection, and layered substrates.\n",
    "\n",
    "Note that unlike standard `Tidy3D` [PlaneWave sources](../_autosummary/tidy3d.PlaneWave.html), the [TFSF source](../_autosummary/tidy3d.TFSF.html) injects $1 \\mathrm{W}\\mu\\mathrm{m}^{-2}$ of power in the TFSF source injection axis (note: this is **different** from the direction of propagation of the plane wave for angled incidence). This allows computing scattering and absorption cross sections without the need for additional normalization. For example, see [this notebook](../notebooks/Near2FarSphereRCS.html) for radar cross section validation, and [this notebook](../notebooks/PlasmonicNanoparticle.html) for absorption by a plasmonic nanoparticle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:28:51.765692Z",
     "iopub.status.busy": "2023-03-27T20:28:51.765101Z",
     "iopub.status.idle": "2023-03-27T20:28:52.953317Z",
     "shell.execute_reply": "2023-03-27T20:28:52.952753Z"
    }
   },
   "outputs": [],
   "source": [
    "# standard python imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# tidy3d imports\n",
    "import tidy3d as td\n",
    "import tidy3d.web as web\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulation setup\n",
    "Here we define the basic simulation parameters that will be used throughout this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:28:52.955609Z",
     "iopub.status.busy": "2023-03-27T20:28:52.955360Z",
     "iopub.status.idle": "2023-03-27T20:28:52.974305Z",
     "shell.execute_reply": "2023-03-27T20:28:52.973745Z"
    }
   },
   "outputs": [],
   "source": [
    "# basic simulation parameters\n",
    "sim_size = (6, 6, 8)  # um\n",
    "wavelength = 1.0  # um\n",
    "f0 = td.C_0 / wavelength  # Hz\n",
    "fwidth = f0 / 60.0  # Hz\n",
    "run_time = 20.0 / fwidth  # s\n",
    "\n",
    "# grid resolution\n",
    "cells_per_wvl = 10\n",
    "\n",
    "# time dependence of the sources used in this notebook\n",
    "source_time = td.GaussianPulse(freq0=f0, fwidth=fwidth)\n",
    "\n",
    "# simulation grid specification\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=cells_per_wvl)\n",
    "\n",
    "# boundary conditions: PML on all sides\n",
    "boundary_spec = td.BoundarySpec.all_sides(td.PML())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Source definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll define a TFSF source region with angled injection similarly to the way in which any source in `Tidy3D` is defined."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:28:52.976369Z",
     "iopub.status.busy": "2023-03-27T20:28:52.976204Z",
     "iopub.status.idle": "2023-03-27T20:28:52.994609Z",
     "shell.execute_reply": "2023-03-27T20:28:52.993099Z"
    }
   },
   "outputs": [],
   "source": [
    "# make the TFSF source specifying angled injection of a plane wave\n",
    "source = td.TFSF(\n",
    "    center=(0, 0, 0),\n",
    "    size=(4, 3, 4),\n",
    "    source_time=source_time,\n",
    "    injection_axis=2,  # inject along the z axis...\n",
    "    direction=\"+\",  # ...in the positive direction, i.e. along z+\n",
    "    name=\"tfsf1\",\n",
    "    pol_angle=0,\n",
    "    angle_theta=np.pi / 6,  # with respect to the injection plane's normal vector\n",
    "    angle_phi=np.pi / 5,  # with respect to the injection plane's normal vector\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monitor definition\n",
    "We'll define a set of monitors to\n",
    "- measure the flux that is injected into the simulation and make sure it is properly normalized,\n",
    "- measure the flux outside the TFSF region to make sure the incident field does not escape out side the TFSF region, and,\n",
    "- visualize the fields on cross sectional cuts through the simulation domain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:28:52.999889Z",
     "iopub.status.busy": "2023-03-27T20:28:52.999540Z",
     "iopub.status.idle": "2023-03-27T20:28:53.029203Z",
     "shell.execute_reply": "2023-03-27T20:28:53.028652Z"
    }
   },
   "outputs": [],
   "source": [
    "# make a box flux monitor surrounding the source to measure the flux escaping the TFSF box\n",
    "monitor_out = td.FluxMonitor(\n",
    "    center=source.center,\n",
    "    size=[size * 1.2 for size in source.size],\n",
    "    freqs=[f0],\n",
    "    name=f\"flux_out\",\n",
    ")\n",
    "\n",
    "# make a surface flux monitor across the simulation domain to measure the total injected flux\n",
    "monitor_inj = td.FluxMonitor(\n",
    "    center=source.center,\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    freqs=[f0],\n",
    "    name=f\"flux_inj\",\n",
    ")\n",
    "\n",
    "# make field monitors along each cardinal plane to look at the fields\n",
    "monitor_freq_xy = td.FieldMonitor(\n",
    "    center=[0, 0, 0],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    freqs=[f0],\n",
    "    name=\"freq_xy\",\n",
    ")\n",
    "\n",
    "monitor_freq_xz = td.FieldMonitor(\n",
    "    center=[0, 0, 0],\n",
    "    size=[td.inf, 0, td.inf],\n",
    "    freqs=[f0],\n",
    "    name=\"freq_xz\",\n",
    ")\n",
    "\n",
    "monitor_freq_yz = td.FieldMonitor(\n",
    "    center=[0, 0, 0],\n",
    "    size=[0, td.inf, td.inf],\n",
    "    freqs=[f0],\n",
    "    name=\"freq_yz\",\n",
    ")\n",
    "\n",
    "# collect all monitors together\n",
    "monitors = [monitor_out, monitor_inj, monitor_freq_xy, monitor_freq_xz, monitor_freq_yz]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:28:53.031142Z",
     "iopub.status.busy": "2023-03-27T20:28:53.031000Z",
     "iopub.status.idle": "2023-03-27T20:28:53.483100Z",
     "shell.execute_reply": "2023-03-27T20:28:53.482557Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 792x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make the simulation instance\n",
    "sim = td.Simulation(\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    medium=td.Medium(),  # air is the background medium\n",
    "    structures=[],  # no structures\n",
    "    sources=[source],\n",
    "    monitors=monitors,\n",
    "    run_time=run_time,\n",
    "    boundary_spec=boundary_spec,\n",
    ")\n",
    "\n",
    "# visualize and check that everything was defined as expected\n",
    "_, ax = plt.subplots(1, 3, figsize=(11, 4))\n",
    "sim.plot(x=0, ax=ax[0])\n",
    "sim.plot(y=0, ax=ax[1])\n",
    "sim.plot(z=source.center[2] - source.size[2] / 2, ax=ax[2])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run the simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:28:53.485108Z",
     "iopub.status.busy": "2023-03-27T20:28:53.484941Z",
     "iopub.status.idle": "2023-03-27T20:29:17.463130Z",
     "shell.execute_reply": "2023-03-27T20:29:17.462541Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:14:14] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'tfsf1'</span> with task_id                                    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-4b27791c-9652-429f-a8d8-9538f5cc3c41v1'</span>.                       <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:14:14]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tfsf1'\u001b[0m with task_id                                    \u001b]8;id=917343;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=414331;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-4b27791c-9652-429f-a8d8-9538f5cc3c41v1'\u001b[0m.                       \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f07b647692a24859a04c33e349682a84",
       "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\">[17:14:18] </span>status = queued                                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:14:18]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                      \u001b]8;id=240919;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=124022;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "model_id": "",
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      },
      "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:14:28] </span>status = preprocess                                                  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:14:28]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                  \u001b]8;id=859820;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=83664;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\u001b\\\u001b[2m263\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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    },
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
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     },
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:14:32] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>the billed FlexCredit cost after a simulation run.                   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:14:32]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get  \u001b]8;id=769132;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=52802;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mthe billed FlexCredit cost after a simulation run.                   \u001b[2m             \u001b[0m\n"
      ]
     },
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    {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                                   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                   \u001b]8;id=263023;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=802398;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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    {
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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>running solver                                                       <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                       \u001b]8;id=268007;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=663311;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\u001b\\\u001b[2m300\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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:14:38] </span>early shutoff detected, exiting.                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:14:38]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                     \u001b]8;id=510755;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=130231;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\u001b\\\u001b[2m313\u001b[0m\u001b]8;;\u001b\\\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\">           </span>status = postprocess                                                 <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                 \u001b]8;id=240521;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=424662;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\u001b\\\u001b[2m330\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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:14:41] </span>status = success                                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[17:14:41]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                     \u001b]8;id=393305;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=683159;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\u001b\\\u001b[2m337\u001b[0m\u001b]8;;\u001b\\\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\">[17:14:42] </span>loading SimulationData from data/tfsf1.hdf5                          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[17:14:42]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/tfsf1.hdf5                          \u001b]8;id=109994;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=339779;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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   ],
   "source": [
    "sim_data = web.run(sim, task_name=\"tfsf1\", path=\"data/tfsf1.hdf5\", verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flux results\n",
    "If $1 \\mathrm{W}\\mu\\mathrm{m}^{-2}$ is injected by the source, then the total injected flux captured should equal the area of the injection surface. To check that this is the case, we divide the computed injected flux by the area of the injection surface, and expect to obtain $1 \\mathrm{W}\\mu\\mathrm{m}^{-2}$. We notice that the actual number is close to 1, but only within 1.5% accuracy. The reason for this is that the TFSF box actually snaps to the nearest FDTD grid cells. So, the actual area over which the source is injected is slightly different from the analytical area computed using `source.size`.\n",
    "\n",
    "We notice that the flux escaping the box is about ten orders of magnitude lower than the injected flux, and therefore negligible, as expected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:17.967996Z",
     "iopub.status.busy": "2023-03-27T20:29:17.967748Z",
     "iopub.status.idle": "2023-03-27T20:29:17.988047Z",
     "shell.execute_reply": "2023-03-27T20:29:17.987551Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "flux_inj per unit area:  1.015394687652588\n",
      "flux_box:  5.025972e-10\n"
     ]
    }
   ],
   "source": [
    "# print the escaped and injected flux\n",
    "print(\n",
    "    \"flux_inj per unit area: \",\n",
    "    sim_data[f\"flux_inj\"].flux.values[0] / source.size[0] / source.size[1],\n",
    ")\n",
    "print(\"flux_box: \", sim_data[f\"flux_out\"].flux.values[0])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Field plots\n",
    "Here we'll visualize the frequency-domain fields and check that the plane wave is injected at the expected angle inside the TFSF box. As shown in the figures, the injected fields look correct inside the TFSF box, and are zero outside the box because there are no scatterers in this example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:17.989890Z",
     "iopub.status.busy": "2023-03-27T20:29:17.989745Z",
     "iopub.status.idle": "2023-03-27T20:29:18.997878Z",
     "shell.execute_reply": "2023-03-27T20:29:18.997354Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# helper plot the fields for each cross section of the simulation for given simulation data\n",
    "def plot_results_freq(sim_data, field_name=\"Ex\", val=\"real\"):\n",
    "    \"\"\"Helper for plotting frequency domain fields.\"\"\"\n",
    "\n",
    "    _, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(12, 3))\n",
    "\n",
    "    sim_data.plot_field(\n",
    "        field_monitor_name=\"freq_xz\", field_name=field_name, val=val, f=f0, ax=ax1\n",
    "    )\n",
    "    sim_data.plot_field(\n",
    "        field_monitor_name=\"freq_yz\", field_name=field_name, val=val, f=f0, ax=ax2\n",
    "    )\n",
    "    sim_data.plot_field(\n",
    "        field_monitor_name=\"freq_xy\", field_name=field_name, val=val, f=f0, ax=ax3\n",
    "    )\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "plot_results_freq(sim_data, field_name=\"Ex\", val=\"real\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Infinite slab\n",
    "We can also make the TFSF box a slab which is infinite in the transverse directions ($x$ and $y$ in this example). However, in this case we must ensure that the boundary conditions in those directions are compatible with the injected plane wave. For angled incidence, this implies that Bloch periodic boundaries ([BlochBoundary](../_autosummary/tidy3d.BlochBoundary.html)) must be used along $x$ and $y$. For normal incidence, either standard [Periodic](../_autosummary/tidy3d.Periodic.html) or Bloch boundaries can be used.\n",
    "\n",
    "**Important**: the TFSF box must not touch or protrude beyond the simulation domain along the injection axis. In this example, the TFSF box must not touch or go past the simulation domain in the $-z$ or $+z$ directions, because our `injection_axis` is `2`, i.e. $z$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:18.999961Z",
     "iopub.status.busy": "2023-03-27T20:29:18.999811Z",
     "iopub.status.idle": "2023-03-27T20:29:19.022085Z",
     "shell.execute_reply": "2023-03-27T20:29:19.021600Z"
    }
   },
   "outputs": [],
   "source": [
    "# make a TFSF source infinite along x and y\n",
    "source = td.TFSF(\n",
    "    center=(0, 0, 0),\n",
    "    size=(td.inf, td.inf, 4),\n",
    "    source_time=source_time,\n",
    "    injection_axis=2,  # inject along the z axis...\n",
    "    direction=\"+\",  # ...in the positive direction, i.e. along z+\n",
    "    name=\"tfsf2\",\n",
    "    pol_angle=0,\n",
    "    angle_theta=np.pi / 4,\n",
    "    angle_phi=np.pi / 4,\n",
    ")\n",
    "\n",
    "# specify boundaries compatible with this source\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.bloch_from_source(source=source, domain_size=sim_size[0], axis=0),\n",
    "    y=td.Boundary.bloch_from_source(source=source, domain_size=sim_size[1], axis=1),\n",
    "    z=td.Boundary.pml(),\n",
    ")\n",
    "\n",
    "# make flux monitors above and below the source to measure the escaped flux\n",
    "center = [source.center[0], source.center[1], source.center[2]]\n",
    "center[source.injection_axis] += 1.2 * source.size[source.injection_axis] / 2.0\n",
    "monitor_above = td.FluxMonitor(\n",
    "    center=[\n",
    "        source.center[0],\n",
    "        source.center[1],\n",
    "        source.center[2] + 1.2 * source.size[2] / 2.0,\n",
    "    ],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    freqs=[f0],\n",
    "    name=f\"flux_above\",\n",
    ")\n",
    "\n",
    "center = [source.center[0], source.center[1], source.center[2]]\n",
    "center[source.injection_axis] -= 1.2 * source.size[source.injection_axis] / 2.0\n",
    "monitor_below = td.FluxMonitor(\n",
    "    center=[\n",
    "        source.center[0],\n",
    "        source.center[1],\n",
    "        source.center[2] - 1.2 * source.size[2] / 2.0,\n",
    "    ],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    freqs=[f0],\n",
    "    name=f\"flux_below\",\n",
    ")\n",
    "\n",
    "# collect all the monitors together again\n",
    "monitors = [\n",
    "    monitor_above,\n",
    "    monitor_below,\n",
    "    monitor_inj,\n",
    "    monitor_freq_xy,\n",
    "    monitor_freq_xz,\n",
    "    monitor_freq_yz,\n",
    "]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:19.024044Z",
     "iopub.status.busy": "2023-03-27T20:29:19.023850Z",
     "iopub.status.idle": "2023-03-27T20:29:19.358001Z",
     "shell.execute_reply": "2023-03-27T20:29:19.357494Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# update the simulation object with the new source, boundaries, and monitors\n",
    "sim = sim.copy(\n",
    "    update={\n",
    "        \"sources\": [source],\n",
    "        \"boundary_spec\": boundary_spec,\n",
    "        \"monitors\": monitors,\n",
    "    }\n",
    ")\n",
    "\n",
    "# visualize\n",
    "_, ax = plt.subplots(1, 3, figsize=(11, 4))\n",
    "sim.plot(x=0, ax=ax[0])\n",
    "sim.plot(y=0, ax=ax[1])\n",
    "sim.plot(z=source.center[2] - source.size[2] / 2, ax=ax[2])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run the simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:19.360039Z",
     "iopub.status.busy": "2023-03-27T20:29:19.359866Z",
     "iopub.status.idle": "2023-03-27T20:29:43.372101Z",
     "shell.execute_reply": "2023-03-27T20:29:43.371597Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-90b24972-e746-4bc5-a806-d2efddfc473cv1'</span>.                       <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:15:50]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tfsf2'\u001b[0m with task_id                                    \u001b]8;id=582954;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=999430;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-90b24972-e746-4bc5-a806-d2efddfc473cv1'\u001b[0m.                       \u001b[2m             \u001b[0m\n"
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     "metadata": {},
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       "Output()"
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     "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\">[17:15:52] </span>status = queued                                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:15:52]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                      \u001b]8;id=341188;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=708295;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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       "model_id": "",
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       "version_minor": 0
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      "text/plain": [
       "Output()"
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     },
     "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\">[17:15:56] </span>status = preprocess                                                  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:15:56]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                  \u001b]8;id=809371;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=932245;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\u001b\\\u001b[2m263\u001b[0m\u001b]8;;\u001b\\\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\"></pre>\n"
      ],
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     },
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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\">[17:16:00] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.025</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>the billed FlexCredit cost after a simulation run.                   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:16:00]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.025\u001b[0m. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get  \u001b]8;id=86495;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=126335;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mthe billed FlexCredit cost after a simulation run.                   \u001b[2m             \u001b[0m\n"
      ]
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    {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                                   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                   \u001b]8;id=916767;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=151890;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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    {
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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\">[17:16:01] </span>running solver                                                       <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:16:01]\u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                       \u001b]8;id=466008;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=805396;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:16:05] </span>early shutoff detected, exiting.                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:16:05]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                     \u001b]8;id=187155;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=270124;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\u001b\\\u001b[2m313\u001b[0m\u001b]8;;\u001b\\\n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\n"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>status = postprocess                                                 <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                 \u001b]8;id=610082;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=297373;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\u001b\\\u001b[2m330\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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    {
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:16:09] </span>status = success                                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[17:16:09]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                     \u001b]8;id=157019;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=789004;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\u001b\\\u001b[2m337\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>\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\">[17:16:10] </span>loading SimulationData from data/tfsf2.hdf5                          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:16:10]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/tfsf2.hdf5                          \u001b]8;id=354047;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=353113;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_data = web.run(sim, task_name=\"tfsf2\", path=\"data/tfsf2.hdf5\", verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flux results\n",
    "Here, the flux injected by the source is extremely close to $1 \\mathrm{W}\\mu\\mathrm{m}^{-2}$ as there are no finite-size effects at the source boundaries. As expected, the flux escaping above and below the TFSF slab is negligibly small."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:43.712453Z",
     "iopub.status.busy": "2023-03-27T20:29:43.712314Z",
     "iopub.status.idle": "2023-03-27T20:29:43.733687Z",
     "shell.execute_reply": "2023-03-27T20:29:43.733183Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "flux_inj per unit area:  0.9999941719902886\n",
      "flux_above:  1.098945e-08\n",
      "flux_below:  -1.29929244e-11\n"
     ]
    }
   ],
   "source": [
    "# print the escaped and injected flux\n",
    "print(\n",
    "    \"flux_inj per unit area: \",\n",
    "    sim_data[f\"flux_inj\"].flux.values[0] / sim.size[0] / sim.size[1],\n",
    ")  # using sim.size because the TFSF slab extends to sim edges\n",
    "print(\"flux_above: \", sim_data[f\"flux_above\"].flux.values[0])\n",
    "print(\"flux_below: \", sim_data[f\"flux_below\"].flux.values[0])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Field plots\n",
    "In plotting the fields, we can see that the plane wave is injected at the desired angle without leakage into the scattered-field region."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:43.735665Z",
     "iopub.status.busy": "2023-03-27T20:29:43.735522Z",
     "iopub.status.idle": "2023-03-27T20:29:44.634412Z",
     "shell.execute_reply": "2023-03-27T20:29:44.633909Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_results_freq(sim_data, field_name=\"Ex\", val=\"real\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### TFSF source in a layered substrate\n",
    "A TFSF source can be set up in a layered substrate as long as the following condition is satisfied: **all four side walls of the TFSF box must see the same material profile along the injection axis**. In other words, any scatterers in the domain must either:\n",
    "\n",
    " - intersect each of the 4 side walls of the TFSF box in exactly the same way, e.g., a layered substrate, or,\n",
    " \n",
    " - be entirely inside or entirely outside the TFSF box.\n",
    "\n",
    "This example shows how to set up a TFSF source in a layered substrate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:44.638367Z",
     "iopub.status.busy": "2023-03-27T20:29:44.638222Z",
     "iopub.status.idle": "2023-03-27T20:29:44.660050Z",
     "shell.execute_reply": "2023-03-27T20:29:44.659557Z"
    }
   },
   "outputs": [],
   "source": [
    "# parameters of the layered substrate\n",
    "epsrs = [4, 1.5, 5.5, 2.8]  # permittivities\n",
    "zsizes = [0.3, 0.6, 0.7, 1.2]  # thicknesses\n",
    "zpos = -1.5  # starting position of the first layer\n",
    "\n",
    "# make the layer structures\n",
    "layers = []\n",
    "for idx, epsr in enumerate(epsrs):\n",
    "    medium = td.Medium(permittivity=epsr)\n",
    "    size = (td.inf, td.inf, zsizes[idx])\n",
    "    center = (0, 0, zpos + zsizes[idx] / 2)\n",
    "    layers.append(\n",
    "        td.Structure(geometry=td.Box(center=center, size=size), medium=medium)\n",
    "    )\n",
    "    zpos += zsizes[idx]\n",
    "\n",
    "# make a TFSF box\n",
    "source = td.TFSF(\n",
    "    center=(0, 0, 0),\n",
    "    size=(4, 3, 4),\n",
    "    source_time=source_time,\n",
    "    injection_axis=2,  # inject along the z axis...\n",
    "    direction=\"+\",  # ...in the positive direction, i.e. along z+\n",
    "    name=\"tfsf3\",\n",
    "    pol_angle=0,\n",
    "    angle_theta=np.pi / 6,\n",
    "    angle_phi=np.pi / 7,\n",
    ")\n",
    "\n",
    "# specify boundaries compatible with the source for the scattered fields to obey;\n",
    "# note that the source plane goes through the first layer of the substrate,\n",
    "# so we should use that medium when specifying the Bloch boundaries\n",
    "boundary_spec = td.BoundarySpec(\n",
    "    x=td.Boundary.bloch_from_source(\n",
    "        source=source,\n",
    "        domain_size=sim_size[0],\n",
    "        axis=0,\n",
    "        medium=td.Medium(permittivity=epsrs[0]),\n",
    "    ),\n",
    "    y=td.Boundary.bloch_from_source(\n",
    "        source=source,\n",
    "        domain_size=sim_size[1],\n",
    "        axis=1,\n",
    "        medium=td.Medium(permittivity=epsrs[0]),\n",
    "    ),\n",
    "    z=td.Boundary.pml(),\n",
    ")\n",
    "\n",
    "# reuse the monitors from the first simulation\n",
    "monitors = [monitor_out, monitor_inj, monitor_freq_xy, monitor_freq_xz, monitor_freq_yz]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Make simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:44.663296Z",
     "iopub.status.busy": "2023-03-27T20:29:44.663142Z",
     "iopub.status.idle": "2023-03-27T20:29:44.995929Z",
     "shell.execute_reply": "2023-03-27T20:29:44.995425Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 792x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# update the simulation object with the new source, boundaries, monitors, and structures\n",
    "sim = sim.copy(\n",
    "    update={\n",
    "        \"sources\": [source],\n",
    "        \"boundary_spec\": boundary_spec,\n",
    "        \"monitors\": monitors,\n",
    "        \"structures\": layers,\n",
    "    }\n",
    ")\n",
    "\n",
    "# visualize\n",
    "_, ax = plt.subplots(1, 3, figsize=(11, 4))\n",
    "sim.plot(x=0, ax=ax[0])\n",
    "sim.plot(y=0, ax=ax[1])\n",
    "sim.plot(z=source.center[2] - source.size[2] / 2, ax=ax[2])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run the simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:29:44.998069Z",
     "iopub.status.busy": "2023-03-27T20:29:44.997898Z",
     "iopub.status.idle": "2023-03-27T20:30:08.506827Z",
     "shell.execute_reply": "2023-03-27T20:30:08.506199Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:17:47] </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'tfsf3'</span> with task_id                                    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">139</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span><span style=\"color: #008000; text-decoration-color: #008000\">'fdve-993bae33-9c29-49b6-92c4-3f983372bd32v1'</span>.                       <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:17:47]\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'tfsf3'\u001b[0m with task_id                                    \u001b]8;id=795469;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=260046;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#139\u001b\\\u001b[2m139\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m\u001b[32m'fdve-993bae33-9c29-49b6-92c4-3f983372bd32v1'\u001b[0m.                       \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "858dc12c80b34d89a682624f62766b2c",
       "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\">[17:17:49] </span>status = queued                                                      <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">269</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:17:49]\u001b[0m\u001b[2;36m \u001b[0mstatus = queued                                                      \u001b]8;id=220804;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=248181;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#269\u001b\\\u001b[2m269\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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      "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:17:51] </span>status = preprocess                                                  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">263</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:17:51]\u001b[0m\u001b[2;36m \u001b[0mstatus = preprocess                                                  \u001b]8;id=681606;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=158848;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#263\u001b\\\u001b[2m263\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
      ],
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     },
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    {
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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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:17:55] </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.083</span>. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get  <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">286</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>the billed FlexCredit cost after a simulation run.                   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:17:55]\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.083\u001b[0m. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get  \u001b]8;id=701268;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=237930;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#286\u001b\\\u001b[2m286\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mthe billed FlexCredit cost after a simulation run.                   \u001b[2m             \u001b[0m\n"
      ]
     },
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    {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>starting up solver                                                   <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">290</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstarting up solver                                                   \u001b]8;id=117641;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=632698;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#290\u001b\\\u001b[2m290\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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    {
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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>running solver                                                       <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">300</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mrunning solver                                                       \u001b]8;id=510051;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=26307;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#300\u001b\\\u001b[2m300\u001b[0m\u001b]8;;\u001b\\\n"
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     },
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       "Output()"
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    },
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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\">[17:18:09] </span>early shutoff detected, exiting.                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">313</span></a>\n",
       "</pre>\n"
      ],
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       "\u001b[2;36m[17:18:09]\u001b[0m\u001b[2;36m \u001b[0mearly shutoff detected, exiting.                                     \u001b]8;id=492392;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=443206;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#313\u001b\\\u001b[2m313\u001b[0m\u001b]8;;\u001b\\\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\">           </span>status = postprocess                                                 <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">330</span></a>\n",
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       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mstatus = postprocess                                                 \u001b]8;id=255829;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=632687;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#330\u001b\\\u001b[2m330\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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:18:14] </span>status = success                                                     <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">337</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[17:18:14]\u001b[0m\u001b[2;36m \u001b[0mstatus = success                                                     \u001b]8;id=611234;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=666865;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#337\u001b\\\u001b[2m337\u001b[0m\u001b]8;;\u001b\\\n"
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       "</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\">[17:18:15] </span>loading SimulationData from data/tfsf3.hdf5                          <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">webapi.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">512</span></a>\n",
       "</pre>\n"
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       "\u001b[2;36m[17:18:15]\u001b[0m\u001b[2;36m \u001b[0mloading SimulationData from data/tfsf3.hdf5                          \u001b]8;id=469842;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=417278;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/web/webapi.py#512\u001b\\\u001b[2m512\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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   ],
   "source": [
    "sim_data = web.run(sim, task_name=\"tfsf3\", path=\"data/tfsf3.hdf5\", verbose=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Flux results\n",
    "Despite the elaborate stack-up of dielectric layers considered above, we again see that the incident field is effectively confined within the TFSF box, while taking into account the presence of the layered substrate, with negligible leakage to the scattered field region."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:30:08.917044Z",
     "iopub.status.busy": "2023-03-27T20:30:08.916909Z",
     "iopub.status.idle": "2023-03-27T20:30:08.936076Z",
     "shell.execute_reply": "2023-03-27T20:30:08.935655Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "flux_box:  3.725109e-09\n"
     ]
    }
   ],
   "source": [
    "# print the escaped flux\n",
    "print(\"flux_box: \", sim_data[f\"flux_out\"].flux.values[0])\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Field plots\n",
    "The frequency-domain field plots confirm that the incident field is injected at the expected angle, takes into account the layer interfaces, and remains confined to the total field region."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:30:08.938407Z",
     "iopub.status.busy": "2023-03-27T20:30:08.938230Z",
     "iopub.status.idle": "2023-03-27T20:30:10.103126Z",
     "shell.execute_reply": "2023-03-27T20:30:10.102484Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_results_freq(sim_data, field_name=\"Ex\", val=\"real\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example with a scatterer\n",
    "Finally, we'll simulate the presence of a scatterer inside the TFSF box, as would be the case in scattering cross section problems. To validate the result, we'll also simulate the same scatterer using a standard plane wave source, and then compute the scattered field by subtracting out the incident field manually. This will require an additional simulation of the same domain but without the scatterer, to compute the incident field. This example will demonstrate the usefulness of TFSF in obtaining scattered fields without the need to run two simulations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:30:10.107330Z",
     "iopub.status.busy": "2023-03-27T20:30:10.107095Z",
     "iopub.status.idle": "2023-03-27T20:30:10.128278Z",
     "shell.execute_reply": "2023-03-27T20:30:10.127785Z"
    }
   },
   "outputs": [],
   "source": [
    "# make a TFSF box\n",
    "source = td.TFSF(\n",
    "    center=(0, 0, 0.2),\n",
    "    size=(5, 5, 3.5),\n",
    "    source_time=source_time,\n",
    "    injection_axis=2,  # inject along the z axis...\n",
    "    direction=\"+\",  # ...in the positive direction, i.e. along z+\n",
    "    name=\"tfsf4\",\n",
    "    pol_angle=0,\n",
    ")\n",
    "\n",
    "# set up scatterers: two boxes and a sphere inside the TFSF box\n",
    "box1 = td.Structure(\n",
    "    geometry=td.Box(center=[0, 0, 0.3], size=[4, 4, 0.6]),\n",
    "    medium=td.material_library[\"SiO2\"][\"Horiba\"],\n",
    ")\n",
    "\n",
    "box2 = td.Structure(\n",
    "    geometry=td.Box(center=[0, 0, 1], size=[3, 3, 0.8]),\n",
    "    medium=td.material_library[\"SiN\"][\"Horiba\"],\n",
    ")\n",
    "\n",
    "sphere = td.Structure(\n",
    "    geometry=td.Sphere(center=[-1, 0, -0.8], radius=0.6),\n",
    "    medium=td.Medium(permittivity=2.4),\n",
    ")\n",
    "\n",
    "# collect all objects\n",
    "structures = [box1, box2, sphere]\n",
    "\n",
    "# make a field monitor above the TFSF box to compare fields between the two cases\n",
    "monitor_freq = td.FieldMonitor(\n",
    "    center=[0, 0, 2.5],\n",
    "    size=[td.inf, td.inf, 0],\n",
    "    freqs=[f0],\n",
    "    name=\"freq\",\n",
    ")\n",
    "\n",
    "# specify PML boundaries on all sides\n",
    "boundary_spec = td.BoundarySpec.all_sides(td.PML())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Simulation with TFSF source\n",
    "\n",
    "It is important to note that when a non-uniform grid is used in the directions transverse to the `injection_axis` of the TFSF source, the suppression of the incident field outside the TFSF box may not be as close to zero as in the case of a uniform grid. Because of this, Tidy3D issues a warning when nonuniform grid TFSF setup is detected. In some cases, however, the accuracy may be only weakly affected, and the warnings can be ignored. In this example, the presence of scatterers does cause the auto-generated FDTD grid to be non-uniform in the $x$ and $y$ directions, but as we'll see, the results are still in excellent agreement with the reference simulation. To force a uniform grid in the TFSF region and avoid the warnings, a mesh override structure can be used, as illustrated in our [nanoparticle scattering example](../notebooks/PlasmonicNanoparticle.html).\n",
    "\n",
    "The presence of a non-uniform grid _along_ the `injection_axis` is not a problem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:30:10.131496Z",
     "iopub.status.busy": "2023-03-27T20:30:10.131301Z",
     "iopub.status.idle": "2023-03-27T20:30:10.556488Z",
     "shell.execute_reply": "2023-03-27T20:30:10.555967Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:19:13] </span>WARNING: The grid is nonuniform along the <span style=\"color: #008000; text-decoration-color: #008000\">'x'</span> axis, which may lead to    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>sub-optimal cancellation of the incident field in the scattered-field    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>region for the total-field scattered-field <span style=\"font-weight: bold\">(</span>TFSF<span style=\"font-weight: bold\">)</span> source <span style=\"color: #008000; text-decoration-color: #008000\">'tfsf4'</span>. For    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>best results, we recomended ensuring a uniform grid in both directions   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>tangential to the TFSF injection axis, <span style=\"color: #008000; text-decoration-color: #008000\">'z'</span>.                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:19:13]\u001b[0m\u001b[2;36m \u001b[0mWARNING: The grid is nonuniform along the \u001b[32m'x'\u001b[0m axis, which may lead to    \u001b]8;id=446751;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=283974;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0msub-optimal cancellation of the incident field in the scattered-field    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mregion for the total-field scattered-field \u001b[1m(\u001b[0mTFSF\u001b[1m)\u001b[0m source \u001b[32m'tfsf4'\u001b[0m. For    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mbest results, we recomended ensuring a uniform grid in both directions   \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mtangential to the TFSF injection axis, \u001b[32m'z'\u001b[0m.                              \u001b[2m         \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>WARNING: The grid is nonuniform along the <span style=\"color: #008000; text-decoration-color: #008000\">'y'</span> axis, which may lead to    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>sub-optimal cancellation of the incident field in the scattered-field    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>region for the total-field scattered-field <span style=\"font-weight: bold\">(</span>TFSF<span style=\"font-weight: bold\">)</span> source <span style=\"color: #008000; text-decoration-color: #008000\">'tfsf4'</span>. For    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>best results, we recomended ensuring a uniform grid in both directions   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>tangential to the TFSF injection axis, <span style=\"color: #008000; text-decoration-color: #008000\">'z'</span>.                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: The grid is nonuniform along the \u001b[32m'y'\u001b[0m axis, which may lead to    \u001b]8;id=839945;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=988041;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0msub-optimal cancellation of the incident field in the scattered-field    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mregion for the total-field scattered-field \u001b[1m(\u001b[0mTFSF\u001b[1m)\u001b[0m source \u001b[32m'tfsf4'\u001b[0m. For    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mbest results, we recomended ensuring a uniform grid in both directions   \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mtangential to the TFSF injection axis, \u001b[32m'z'\u001b[0m.                              \u001b[2m         \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 792x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make the TFSF simulation by updating the previous one with the new structures and monitor\n",
    "sim = sim.copy(\n",
    "    update={\n",
    "        \"boundary_spec\": boundary_spec,\n",
    "        \"monitors\": [monitor_freq],\n",
    "        \"structures\": structures,\n",
    "        \"sources\": [source],\n",
    "    }\n",
    ")\n",
    "\n",
    "# visualize\n",
    "_, ax = plt.subplots(1, 3, figsize=(11, 4))\n",
    "sim.plot(x=0, ax=ax[0])\n",
    "sim.plot(y=0, ax=ax[1])\n",
    "sim.plot(z=source.center[2] - source.size[2] / 2, ax=ax[2])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Reference simulation\n",
    "\n",
    "We will compare the results with a simulation that uses a regular plane wave source, where we compute scattered fields by also running an empty simulation and subtracting the results of the empty simulation from the results of the full one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:30:10.558502Z",
     "iopub.status.busy": "2023-03-27T20:30:10.558346Z",
     "iopub.status.idle": "2023-03-27T20:30:11.003410Z",
     "shell.execute_reply": "2023-03-27T20:30:11.002903Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# make the two reference simulation with a standard plane wave source, one of them without the scatterer\n",
    "source_planewave = td.PlaneWave(\n",
    "    center=(0, 0, -1.55),\n",
    "    size=(td.inf, td.inf, 0),\n",
    "    source_time=source_time,\n",
    "    direction=\"+\",\n",
    "    name=\"planewave\",\n",
    "    pol_angle=0,\n",
    ")\n",
    "\n",
    "sim_ref = sim.copy(\n",
    "    update={\n",
    "        \"sources\": [source_planewave],\n",
    "    }\n",
    ")\n",
    "\n",
    "# for the empty simulation, we need to make sure the grid is identical to the one with objects,\n",
    "# so we use override structures to create \"phantoms\" of the objects, so that the grid is generated\n",
    "# as though the objects were there, even though they're not\n",
    "grid_spec_empty = td.GridSpec.auto(\n",
    "    min_steps_per_wvl=cells_per_wvl,\n",
    "    override_structures=[box1, box2, sphere],\n",
    ")\n",
    "\n",
    "sim_ref_empty = sim.copy(\n",
    "    update={\n",
    "        \"sources\": [source_planewave],\n",
    "        \"structures\": [],\n",
    "        \"grid_spec\": grid_spec_empty,\n",
    "    }\n",
    ")\n",
    "\n",
    "# visualize both simulations\n",
    "_, ax = plt.subplots(1, 2, figsize=(8, 4))\n",
    "sim_ref.plot(x=0, ax=ax[0])\n",
    "sim_ref.plot(y=0, ax=ax[1])\n",
    "plt.show()\n",
    "\n",
    "_, ax = plt.subplots(1, 2, figsize=(8, 4))\n",
    "sim_ref_empty.plot(x=0, ax=ax[0])\n",
    "sim_ref_empty.plot(y=0, ax=ax[1])\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run all three simulations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:30:11.005502Z",
     "iopub.status.busy": "2023-03-27T20:30:11.005333Z",
     "iopub.status.idle": "2023-03-27T20:31:16.266781Z",
     "shell.execute_reply": "2023-03-27T20:31:16.266223Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">[17:20:46] </span>WARNING: The grid is nonuniform along the <span style=\"color: #008000; text-decoration-color: #008000\">'x'</span> axis, which may lead to    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>sub-optimal cancellation of the incident field in the scattered-field    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>region for the total-field scattered-field <span style=\"font-weight: bold\">(</span>TFSF<span style=\"font-weight: bold\">)</span> source <span style=\"color: #008000; text-decoration-color: #008000\">'tfsf4'</span>. For    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>best results, we recomended ensuring a uniform grid in both directions   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>tangential to the TFSF injection axis, <span style=\"color: #008000; text-decoration-color: #008000\">'z'</span>.                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:20:46]\u001b[0m\u001b[2;36m \u001b[0mWARNING: The grid is nonuniform along the \u001b[32m'x'\u001b[0m axis, which may lead to    \u001b]8;id=928504;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=281054;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0msub-optimal cancellation of the incident field in the scattered-field    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mregion for the total-field scattered-field \u001b[1m(\u001b[0mTFSF\u001b[1m)\u001b[0m source \u001b[32m'tfsf4'\u001b[0m. For    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mbest results, we recomended ensuring a uniform grid in both directions   \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mtangential to the TFSF injection axis, \u001b[32m'z'\u001b[0m.                              \u001b[2m         \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>WARNING: The grid is nonuniform along the <span style=\"color: #008000; text-decoration-color: #008000\">'y'</span> axis, which may lead to    <a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>sub-optimal cancellation of the incident field in the scattered-field    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>region for the total-field scattered-field <span style=\"font-weight: bold\">(</span>TFSF<span style=\"font-weight: bold\">)</span> source <span style=\"color: #008000; text-decoration-color: #008000\">'tfsf4'</span>. For    <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>best results, we recomended ensuring a uniform grid in both directions   <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>tangential to the TFSF injection axis, <span style=\"color: #008000; text-decoration-color: #008000\">'z'</span>.                              <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: The grid is nonuniform along the \u001b[32m'y'\u001b[0m axis, which may lead to    \u001b]8;id=331426;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=179953;file:///home/momchil/Drive/flexcompute/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0msub-optimal cancellation of the incident field in the scattered-field    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mregion for the total-field scattered-field \u001b[1m(\u001b[0mTFSF\u001b[1m)\u001b[0m source \u001b[32m'tfsf4'\u001b[0m. For    \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mbest results, we recomended ensuring a uniform grid in both directions   \u001b[2m         \u001b[0m\n",
       "\u001b[2;36m           \u001b[0mtangential to the TFSF injection axis, \u001b[32m'z'\u001b[0m.                              \u001b[2m         \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TFSF simulation\n",
    "sim_data = web.run(sim, task_name=\"tfsf4\", path=\"data/tfsf4.hdf5\")\n",
    "\n",
    "# planewave simulation\n",
    "sim_data_ref = web.run(sim_ref, task_name=\"planewave\", path=\"data/planewave.hdf5\")\n",
    "\n",
    "# planewave simulation without objects\n",
    "sim_data_ref_empty = web.run(\n",
    "    sim_ref_empty, task_name=\"planewave_empty\", path=\"data/planewave_empty.hdf5\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the reference simulation, compute the scattered fields by subtracting the results of the empty simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:31:17.291819Z",
     "iopub.status.busy": "2023-03-27T20:31:17.291684Z",
     "iopub.status.idle": "2023-03-27T20:31:17.320552Z",
     "shell.execute_reply": "2023-03-27T20:31:17.319985Z"
    }
   },
   "outputs": [],
   "source": [
    "# for the plane wave simulations, we need to manually compute the scattered fields\n",
    "# by subtracting out the incident fields computed in the empty simulation\n",
    "data_ref = sim_data_ref[monitor_freq.name]\n",
    "data_ref_empty = sim_data_ref_empty[monitor_freq.name]\n",
    "\n",
    "for field, field_empty in zip(\n",
    "    data_ref.field_components.values(), data_ref_empty.field_components.values()\n",
    "):\n",
    "    field.values -= field_empty.values\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plot and compare\n",
    "Notice the excellent agreement in the scattered field distribution for the TFSF and reference cases. Note, however, that the field magnitudes are different in the two cases. The reason is that the sources are normalized differently, as discussed above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-27T20:31:17.322951Z",
     "iopub.status.busy": "2023-03-27T20:31:17.322808Z",
     "iopub.status.idle": "2023-03-27T20:31:18.277813Z",
     "shell.execute_reply": "2023-03-27T20:31:18.277392Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 864x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(12, 3))\n",
    "\n",
    "im1 = ax1.pcolormesh(\n",
    "    np.real(sim_data[monitor_freq.name].Ex.isel(z=0, f=0)), cmap=\"RdBu\", shading=\"auto\"\n",
    ")\n",
    "im2 = ax2.pcolormesh(\n",
    "    np.real(sim_data[monitor_freq.name].Ey.isel(z=0, f=0)), cmap=\"RdBu\", shading=\"auto\"\n",
    ")\n",
    "im3 = ax3.pcolormesh(\n",
    "    np.real(sim_data[monitor_freq.name].Ez.isel(z=0, f=0)), cmap=\"RdBu\", shading=\"auto\"\n",
    ")\n",
    "fig.colorbar(im1, ax=ax1)\n",
    "fig.colorbar(im2, ax=ax2)\n",
    "fig.colorbar(im3, ax=ax3)\n",
    "plt.show()\n",
    "\n",
    "fig, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(12, 3))\n",
    "\n",
    "im1 = ax1.pcolormesh(np.real(data_ref.Ex.isel(z=0, f=0)), cmap=\"RdBu\", shading=\"auto\")\n",
    "im2 = ax2.pcolormesh(np.real(data_ref.Ey.isel(z=0, f=0)), cmap=\"RdBu\", shading=\"auto\")\n",
    "im3 = ax3.pcolormesh(np.real(data_ref.Ez.isel(z=0, f=0)), cmap=\"RdBu\", shading=\"auto\")\n",
    "fig.colorbar(im1, ax=ax1)\n",
    "fig.colorbar(im2, ax=ax2)\n",
    "fig.colorbar(im3, ax=ax3)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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   "language": "python",
   "name": "python3"
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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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: #008000; text-decoration-color: #008000\">🏃 </span> <span style=\"color: #008000; text-decoration-color: #008000; font-weight: bold\">Finishing 'tfsf3'...</span>\n</pre>\n",
          "text/plain": "\u001b[32m🏃 \u001b[0m \u001b[1;32mFinishing 'tfsf3'...\u001b[0m\n"
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