{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "-"
    }
   },
   "source": [
    "# Computing the scattering matrix of an optical device \n",
    "\n",
    "Note: the cost of running the entire notebook is larger than 1 FlexCredit.\n",
    "\n",
    "This notebook will give a demo of the `Tidy3D` [ComponentModeler](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.ComponentModeler.html) plugin used to compute scattering matrix elements.\n",
    "\n",
    "For more integrated photonic examples such as the [8-Channel mode and polarization de-multiplexer](https://www.flexcompute.com/tidy3d/examples/notebooks/8ChannelDemultiplexer/), the [broadband bi-level taper polarization rotator-splitter](https://www.flexcompute.com/tidy3d/examples/notebooks/BilevelPSR/), and the [broadband directional coupler](https://www.flexcompute.com/tidy3d/examples/notebooks/BroadbandDirectionalCoupler/), please visit our [examples page](https://www.flexcompute.com/tidy3d/examples/).\n",
    "\n",
    "If you are new to the finite-difference time-domain (FDTD) method, we highly recommend going through our [FDTD101](https://www.flexcompute.com/fdtd101/) tutorials. FDTD simulations can diverge due to various reasons. If you run into any simulation divergence issues, please follow the steps outlined in our [troubleshooting guide](https://www.flexcompute.com/tidy3d/examples/notebooks/DivergedFDTDSimulation/) to resolve it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import gdstk\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# tidy3D imports\n",
    "import tidy3d as td\n",
    "from tidy3d import web"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "We will simulate a directional coupler, similar to the GDS and Parameter scan tutorials.\n",
    "\n",
    "Let's start by setting up some basic parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# wavelength / frequency\n",
    "lambda0 = 1.550  # all length scales in microns\n",
    "freq0 = td.constants.C_0 / lambda0\n",
    "lambda_range = np.linspace(1.5, 1.6, 40)\n",
    "freqs = td.constants.C_0 / lambda_range\n",
    "fwidth = freq0 / 10  # for the source\n",
    "\n",
    "# Spatial grid specification\n",
    "grid_spec = td.GridSpec.auto(min_steps_per_wvl=14, wavelength=lambda0)\n",
    "\n",
    "# Permittivity of waveguide and substrate\n",
    "wg_n = 3.48\n",
    "sub_n = 1.45\n",
    "mat_wg = td.Medium(permittivity=wg_n**2)\n",
    "mat_sub = td.Medium(permittivity=sub_n**2)\n",
    "\n",
    "# Waveguide dimensions\n",
    "\n",
    "# Waveguide height\n",
    "wg_height = 0.22\n",
    "# Waveguide width\n",
    "wg_width = 0.5\n",
    "# Waveguide separation in the beginning/end\n",
    "wg_spacing_in = 8\n",
    "# length of coupling region (um)\n",
    "coup_length = 5.0\n",
    "# spacing between waveguides in coupling region (um)\n",
    "wg_spacing_coup = 0.07\n",
    "# Total device length along propagation direction\n",
    "device_length = 100\n",
    "# Length of the bend region\n",
    "bend_length = 16\n",
    "# Straight waveguide sections on each side\n",
    "straight_wg_length = 4\n",
    "# space between waveguide and PML\n",
    "pml_spacing = 1.2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define waveguide bends and coupler\n",
    "\n",
    "Here is where we define our directional coupler shape programmatically in terms of the geometric parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def tanh_interp(max_arg):\n",
    "    \"\"\"Interpolator for tanh with adjustable extension\"\"\"\n",
    "    scale = 1 / np.tanh(max_arg)\n",
    "    return lambda u: 0.5 * (1 + scale * np.tanh(max_arg * (u * 2 - 1)))\n",
    "\n",
    "\n",
    "def make_coupler(\n",
    "    length,\n",
    "    wg_spacing_in,\n",
    "    wg_width,\n",
    "    wg_spacing_coup,\n",
    "    coup_length,\n",
    "    bend_length,\n",
    "    npts_bend=30,\n",
    "):\n",
    "    \"\"\"Make an integrated coupler using the gdstk RobustPath object.\"\"\"\n",
    "    # bend interpolator\n",
    "    interp = tanh_interp(3)\n",
    "    delta = wg_width + wg_spacing_coup - wg_spacing_in\n",
    "    offset = lambda u: wg_spacing_in + interp(u) * delta\n",
    "\n",
    "    coup = gdstk.RobustPath(\n",
    "        (-0.5 * length, 0),\n",
    "        (wg_width, wg_width),\n",
    "        wg_spacing_in,\n",
    "        simple_path=True,\n",
    "        layer=1,\n",
    "        datatype=[0, 1],\n",
    "    )\n",
    "    coup.segment((-0.5 * coup_length - bend_length, 0))\n",
    "    coup.segment(\n",
    "        (-0.5 * coup_length, 0),\n",
    "        offset=[lambda u: -0.5 * offset(u), lambda u: 0.5 * offset(u)],\n",
    "    )\n",
    "    coup.segment((0.5 * coup_length, 0))\n",
    "    coup.segment(\n",
    "        (0.5 * coup_length + bend_length, 0),\n",
    "        offset=[lambda u: -0.5 * offset(1 - u), lambda u: 0.5 * offset(1 - u)],\n",
    "    )\n",
    "    coup.segment((0.5 * length, 0))\n",
    "    return coup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Base Simulation\n",
    "\n",
    "The scattering matrix tool requires the \"base\" [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html) (without the modal sources or monitors used to compute S-parameters), so we will construct that now.\n",
    "\n",
    "We generate the structures and add a [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.FieldMonitor.html?highlight=FieldMonitor) so we can inspect the field patterns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Geometry must be placed in GDS cells to import into Tidy3D\n",
    "coup_cell = gdstk.Cell(\"Coupler\")\n",
    "\n",
    "substrate = gdstk.rectangle(\n",
    "    (-device_length / 2, -wg_spacing_in / 2 - 10),\n",
    "    (device_length / 2, wg_spacing_in / 2 + 10),\n",
    "    layer=0,\n",
    ")\n",
    "coup_cell.add(substrate)\n",
    "\n",
    "# Add the coupler to a GDS cell\n",
    "gds_coup = make_coupler(\n",
    "    device_length, wg_spacing_in, wg_width, wg_spacing_coup, coup_length, bend_length\n",
    ")\n",
    "coup_cell.add(gds_coup)\n",
    "\n",
    "# Substrate\n",
    "(oxide_geo,) = td.PolySlab.from_gds(\n",
    "    gds_cell=coup_cell, gds_layer=0, gds_dtype=0, slab_bounds=(-10, 0), axis=2\n",
    ")\n",
    "\n",
    "oxide = td.Structure(geometry=oxide_geo, medium=mat_sub)\n",
    "\n",
    "# Waveguides (import all datatypes if gds_dtype not specified)\n",
    "coupler1_geo, coupler2_geo = td.PolySlab.from_gds(\n",
    "    gds_cell=coup_cell, gds_layer=1, slab_bounds=(0, wg_height), axis=2\n",
    ")\n",
    "\n",
    "coupler1 = td.Structure(geometry=coupler1_geo, medium=mat_wg)\n",
    "\n",
    "coupler2 = td.Structure(geometry=coupler2_geo, medium=mat_wg)\n",
    "\n",
    "# Simulation size along propagation direction\n",
    "sim_length = 2 * straight_wg_length + 2 * bend_length + coup_length\n",
    "\n",
    "# Spacing between waveguides and PML\n",
    "sim_size = [\n",
    "    sim_length,\n",
    "    wg_spacing_in + wg_width + 2 * pml_spacing,\n",
    "    wg_height + 2 * pml_spacing,\n",
    "]\n",
    "\n",
    "# source\n",
    "src_pos = sim_length / 2 - straight_wg_length / 2\n",
    "\n",
    "# in-plane field monitor (optional, increases required data storage)\n",
    "domain_monitor = td.FieldMonitor(\n",
    "    center=[0, 0, wg_height / 2], size=[td.inf, td.inf, 0], freqs=[freq0], name=\"field\"\n",
    ")\n",
    "\n",
    "# initialize the simulation\n",
    "sim = td.Simulation(\n",
    "    size=sim_size,\n",
    "    grid_spec=grid_spec,\n",
    "    structures=[oxide, coupler1, coupler2],\n",
    "    sources=[],\n",
    "    monitors=[domain_monitor],\n",
    "    run_time=50 / fwidth,\n",
    "    boundary_spec=td.BoundarySpec.all_sides(boundary=td.PML()),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
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      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(15, 10))\n",
    "ax1 = sim.plot(z=wg_height / 2, ax=ax1)\n",
    "ax2 = sim.plot(x=src_pos, ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setting up the Scattering Matrix Tool\n",
    "Now, to use the S matrix tool, we need to define the spatial extent of the \"ports\" of our system using [Port](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.Port.html) objects.\n",
    "\n",
    "These ports will be converted into modal sources and monitors later, so they require both some mode specification and a definition of the direction that points into the system.\n",
    "\n",
    "We'll also give them names to refer to later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tidy3d.plugins.smatrix import Port\n",
    "\n",
    "num_modes = 1\n",
    "\n",
    "port_right_top = Port(\n",
    "    center=[src_pos, wg_spacing_in / 2, wg_height / 2],\n",
    "    size=[0, 4, 2],\n",
    "    mode_spec=td.ModeSpec(num_modes=num_modes),\n",
    "    direction=\"-\",\n",
    "    name=\"right_top\",\n",
    ")\n",
    "\n",
    "port_right_bot = Port(\n",
    "    center=[src_pos, -wg_spacing_in / 2, wg_height / 2],\n",
    "    size=[0, 4, 2],\n",
    "    mode_spec=td.ModeSpec(num_modes=num_modes),\n",
    "    direction=\"-\",\n",
    "    name=\"right_bot\",\n",
    ")\n",
    "\n",
    "port_left_top = Port(\n",
    "    center=[-src_pos, wg_spacing_in / 2, wg_height / 2],\n",
    "    size=[0, 4, 2],\n",
    "    mode_spec=td.ModeSpec(num_modes=num_modes),\n",
    "    direction=\"+\",\n",
    "    name=\"left_top\",\n",
    ")\n",
    "\n",
    "port_left_bot = Port(\n",
    "    center=[-src_pos, -wg_spacing_in / 2, wg_height / 2],\n",
    "    size=[0, 4, 2],\n",
    "    mode_spec=td.ModeSpec(num_modes=num_modes),\n",
    "    direction=\"+\",\n",
    "    name=\"left_bot\",\n",
    ")\n",
    "\n",
    "ports = [port_right_top, port_right_bot, port_left_top, port_left_bot]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will add the base simulation and ports to the [ComponentModeler](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.plugins.smatrix.ComponentModeler.html), along with the frequency of interest and a name for saving the batch of simulations that will get created later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tidy3d.plugins.smatrix import ModalComponentModeler\n",
    "\n",
    "modeler = ModalComponentModeler(\n",
    "    simulation=sim,\n",
    "    ports=ports,\n",
    "    freqs=freqs,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot the simulation with all of the ports as sources to check things are set up correctly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(15, 10))\n",
    "ax1 = modeler.plot_sim(z=wg_height / 2, ax=ax1)\n",
    "ax2 = modeler.plot_sim(x=src_pos, ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solving for the S matrix\n",
    "\n",
    "With the component modeler defined, we can use the usual `web` functions to `run` the batch of simulations needed to compute the S matrix. The tool will loop through each port and create one simulation per mode index (as defined by the mode specifications) where a unique modal source is injected. Each of the ports will also be converted to mode monitors to measure the mode amplitudes and normalization. The simulations run asynchronously in a batch, and the final post-processing step assembles all the data into a single [ModalComponentModelerData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.ModalComponentModelerData.html) object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">09:53:12 EDT </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'directional coupler'</span> with resource_id                \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'sid-9ffb7196-975e-42c0-af2e-ead76927cc4c'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'RF'</span>.     \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m09:53:12 EDT\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'directional coupler'\u001b[0m with resource_id                \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'sid-9ffb7196-975e-42c0-af2e-ead76927cc4c'\u001b[0m and task_type \u001b[32m'RF'\u001b[0m.     \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">-42c0-af2e-ead76927cc4c'</span></a>.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=859119;https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=286772;https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=859119;https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=198802;https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\u001b\\\u001b[32msid\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=859119;https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\u001b\\\u001b[32m-9ffb7196-975e\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=859119;https://tidy3d.simulation.cloud/workbench?taskId=sid-9ffb7196-975e-42c0-af2e-ead76927cc4c\u001b\\\u001b[32m-42c0-af2e-ead76927cc4c'\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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-7d2988e3-13d2-49df-8e7b-f9b5036adc0b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=736346;https://tidy3d.simulation.cloud/folders/folder-7d2988e3-13d2-49df-8e7b-f9b5036adc0b\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "62372366e66a4730900dc259605fb45a",
       "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">09:53:14 EDT </span>Child simulation subtasks are being uploaded to                    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- left_bot@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-10dfae46-0e60-4f94-84c3-f20acd1348d9'</span>            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- left_top@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-04e9d2f8-c0e6-41ba-bd84-97f34e5a78c2'</span>            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- right_bot@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-3dc324d3-1253-4c1e-ac5b-e6d8c83bd0e2'</span>           \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- right_top@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-620f7dab-2e90-4961-98c7-b796b80d715d'</span>           \n",
       "</pre>\n"
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       "\u001b[2;36m09:53:14 EDT\u001b[0m\u001b[2;36m \u001b[0mChild simulation subtasks are being uploaded to                    \n",
       "\u001b[2;36m             \u001b[0m- left_bot@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-10dfae46-0e60-4f94-84c3-f20acd1348d9'\u001b[0m            \n",
       "\u001b[2;36m             \u001b[0m- left_top@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-04e9d2f8-c0e6-41ba-bd84-97f34e5a78c2'\u001b[0m            \n",
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       "\u001b[2;36m             \u001b[0m- right_top@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-620f7dab-2e90-4961-98c7-b796b80d715d'\u001b[0m           \n"
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mValidating component modeler and subtask simulations\u001b[33m...\u001b[0m            \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
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       "\u001b[2;36m09:53:15 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.930\u001b[0m. Minimum cost depends on task       \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mComponent modeler batch validation has been successful.            \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\">09:54:35 EDT </span>Modeler has finished running successfully.                         \n",
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       "\u001b[2;36m09:54:35 EDT\u001b[0m\u001b[2;36m \u001b[0mModeler has finished running successfully.                         \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\">09:54:36 EDT </span>Billed FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.013</span>. Minimum cost depends on task        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
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    "## Working with Scattering Matrix\n",
    "\n",
    "The scattering matrix returned by the solve is an xr.DataArray relating the port names and mode_indices.\n",
    "For example `smatrix.loc[dict(port_in=name1, mode_index_in=mode_index1, port_out=name2, mode_index_out=mode_index_2)]` gives the complex scattering matrix element over all computed frequencies."
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       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.ModalPortDataArray ()&gt; Size: 16B\n",
       "array(0.34155477-0.60895295j)\n",
       "Coordinates:\n",
       "    port_out        &lt;U9 36B &#x27;right_bot&#x27;\n",
       "    port_in         &lt;U9 36B &#x27;left_top&#x27;\n",
       "    mode_index_out  int64 8B 0\n",
       "    mode_index_in   int64 8B 0\n",
       "    f               float64 8B 1.933e+14</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.ModalPortDataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a547bc67-15be-44ac-bb57-ce5ba0bddbf8' class='xr-array-in' type='checkbox' checked><label for='section-a547bc67-15be-44ac-bb57-ce5ba0bddbf8' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>(0.34155476827672-0.608952952553459j)</span></div><div class='xr-array-data'><pre>array(0.34155477-0.60895295j)</pre></div></div></li><li class='xr-section-item'><input id='section-8cdc9faf-91c8-442b-ab3f-6cb69f5d71f0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8cdc9faf-91c8-442b-ab3f-6cb69f5d71f0' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>port_out</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;right_bot&#x27;</div><input id='attrs-b7ccce0e-ddea-419e-a8a1-a0e8514bc08f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7ccce0e-ddea-419e-a8a1-a0e8514bc08f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d765341a-7a32-4ac2-8dc2-66fdde4c8990' class='xr-var-data-in' type='checkbox'><label for='data-d765341a-7a32-4ac2-8dc2-66fdde4c8990' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;right_bot&#x27;, dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>port_in</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;left_top&#x27;</div><input id='attrs-9891a8de-c12c-4cab-9337-0f7d3fcbc524' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9891a8de-c12c-4cab-9337-0f7d3fcbc524' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e01a3dd5-6c5c-46ab-a0f0-858a6c29f90b' class='xr-var-data-in' type='checkbox'><label for='data-e01a3dd5-6c5c-46ab-a0f0-858a6c29f90b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;left_top&#x27;, dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mode_index_out</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-932ddc8a-fcdf-4ecf-9ef9-d22d65652b00' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-932ddc8a-fcdf-4ecf-9ef9-d22d65652b00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d19c9e7-ab86-4f7d-b267-63b2863a9806' class='xr-var-data-in' type='checkbox'><label for='data-3d19c9e7-ab86-4f7d-b267-63b2863a9806' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mode_index_in</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-300db195-e5ee-46de-8d0e-71a53e16cd2a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-300db195-e5ee-46de-8d0e-71a53e16cd2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0524fa69-6ecd-4cc1-b5a4-fa3f5a059eae' class='xr-var-data-in' type='checkbox'><label for='data-0524fa69-6ecd-4cc1-b5a4-fa3f5a059eae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>f</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.933e+14</div><input id='attrs-9605c6d4-7ce5-49da-bee7-de5bd9378d0c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9605c6d4-7ce5-49da-bee7-de5bd9378d0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2ce823e-c914-4edf-accb-57ca9c7a53bd' class='xr-var-data-in' type='checkbox'><label for='data-d2ce823e-c914-4edf-accb-57ca9c7a53bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1.93254642e+14)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f0932425-08e9-4906-b465-3059d7b3ec0c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f0932425-08e9-4906-b465-3059d7b3ec0c' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-b28bc3d5-9a27-4492-b253-e28a279554af' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b28bc3d5-9a27-4492-b253-e28a279554af' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.ModalPortDataArray ()> Size: 16B\n",
       "array(0.34155477-0.60895295j)\n",
       "Coordinates:\n",
       "    port_out        <U9 36B 'right_bot'\n",
       "    port_in         <U9 36B 'left_top'\n",
       "    mode_index_out  int64 8B 0\n",
       "    mode_index_in   int64 8B 0\n",
       "    f               float64 8B 1.933e+14"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smatrix = modeler_data.smatrix()\n",
    "smatrix.loc[dict(port_in=\"left_top\", mode_index_in=0, port_out=\"right_bot\", mode_index_out=0)].sel(\n",
    "    f=freq0, method=\"nearest\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, we can convert this into a numpy array. Note that it has the shape of `(port_in, port_out, mode_in, mode_out, frequency)`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of S-matrix numpy array:  (4, 4, 1, 1, 40)\n"
     ]
    }
   ],
   "source": [
    "print(\"Shape of S-matrix numpy array: \", np.array(smatrix).shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can plot the transmission from top left to top right and bottom right as function of wavelength."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "T_top_to_top = (\n",
    "    abs(\n",
    "        smatrix.loc[\n",
    "            dict(port_in=\"left_top\", mode_index_in=0, port_out=\"right_top\", mode_index_out=0)\n",
    "        ]\n",
    "    )\n",
    "    ** 2\n",
    ")\n",
    "T_top_to_bot = (\n",
    "    abs(\n",
    "        smatrix.loc[\n",
    "            dict(port_in=\"left_top\", mode_index_in=0, port_out=\"right_bot\", mode_index_out=0)\n",
    "        ]\n",
    "    )\n",
    "    ** 2\n",
    ")\n",
    "\n",
    "plt.figure(figsize=(8, 5))\n",
    "plt.plot(lambda_range, T_top_to_top, label=\"left_top → right_top\")\n",
    "plt.plot(lambda_range, T_top_to_bot, label=\"left_top → right_bot\")\n",
    "plt.xlabel(\"Wavelength (μm)\")\n",
    "plt.ylabel(\"Transmission\")\n",
    "plt.title(\"Directional Coupler Transmission\")\n",
    "plt.legend()\n",
    "plt.grid(True)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can inspect the matrix `S` at a single frequency `S` and note that the diagonal elements are very small indicating low backscattering. Summing each rows of the matrix should give 1.0 if no power was lost."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.98372448, 0.98372449, 0.98332856, 0.98332859])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S = np.squeeze(smatrix.sel(f=freq0, method=\"nearest\").values)\n",
    "np.sum(abs(S) ** 2, axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is a little power loss since the coupler was not optimized, most likely scattering from the bends and coupling region.\n",
    "\n",
    "Finally, we can check whether `S` is close to unitary as expected. S times its Hermitian conjugate should be the identity matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "mat = S @ (np.conj(S.T))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x350 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(10, 3.5))\n",
    "imabs = ax1.matshow(abs(mat))\n",
    "vmax = np.abs(mat.real).max()\n",
    "imreal = ax2.matshow(mat.real, cmap=\"RdBu\", vmin=-vmax, vmax=vmax)\n",
    "vmax = np.abs(mat.imag).max()\n",
    "imimag = ax3.matshow(mat.imag, cmap=\"RdBu\", vmin=-vmax, vmax=vmax)\n",
    "ax1.set_title(r\"$|S^\\dagger S|$\")\n",
    "ax2.set_title(r\"$\\Re\\{S^\\dagger S\\}$\")\n",
    "ax3.set_title(r\"$\\Im\\{S^\\dagger S\\}$\")\n",
    "plt.colorbar(imabs, ax=ax1)\n",
    "plt.colorbar(imreal, ax=ax2)\n",
    "plt.colorbar(imimag, ax=ax3)\n",
    "ax1.grid(False)\n",
    "ax2.grid(False)\n",
    "ax3.grid(False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It looks pretty close, but there seems to indeed be a bit of loss (expected)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Viewing individual Simulation Data\n",
    "To verify, we may want to take a look the individual simulation data. For that, we can use `modeler_data.data`, which stores a dictionary mapping for each port and mode to a regular FDTD [SimulationData](https://docs.flexcompute.com/projects/tidy3d/en/latest/api/_autosummary/tidy3d.Simulation.html) object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(2, 1, tight_layout=True, figsize=(15, 10))\n",
    "ax1 = modeler_data.data[\"left_top@0\"].plot_field(\n",
    "    \"field\", field_name=\"E\", val=\"abs^2\", z=wg_height / 2, ax=ax1\n",
    ")\n",
    "ax2 = modeler_data.data[\"right_bot@0\"].plot_field(\n",
    "    \"field\", field_name=\"E\", val=\"abs^2\", z=wg_height / 2, ax=ax2\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Element Mappings\n",
    "\n",
    "If we wish, we can specify mappings between scattering matrix elements that we want to be equal up to a multiplicative factor.\n",
    "We can define these as `element_mappings` in the `ComponentModeler`.\n",
    "\n",
    "\"Indices\" are defined as a tuple of `(port_name: str, mode_index: int)`\n",
    "\n",
    "\"Elements\" are defined as a tuple of output and input indices, respectively.\n",
    "\n",
    "The element mappings are therefore defined as a tuple of `(element, element, value)` where the second `element` is set by the value of the 1st `element` times the supplied `value`.\n",
    "\n",
    "As an example, let's define this element mapping from the example above to enforce that the coupling between bottom left to bottom right should be equal to the coupling between top left to top right."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# these are the \"indices\" in our scattering matrix\n",
    "left_top = (\"left_top\", 0)\n",
    "right_top = (\"right_top\", 0)\n",
    "left_bot = (\"left_bot\", 0)\n",
    "right_bot = (\"right_bot\", 0)\n",
    "\n",
    "# we define the scattering matrix elements coupling the top ports and bottom ports as pairs of these indices\n",
    "top_coupling_r2l = (left_top, right_top)\n",
    "bot_coupling_r2l = (left_bot, right_bot)\n",
    "top_coupling_l2r = (right_top, left_top)\n",
    "bot_coupling_l2r = (right_bot, left_bot)\n",
    "\n",
    "# map the top coupling to the bottom coupling with a multiplicative factor of +1\n",
    "map_horizontal_l2r = (top_coupling_l2r, bot_coupling_l2r, +1)\n",
    "map_horizontal_r2l = (top_coupling_r2l, bot_coupling_r2l, +1)\n",
    "\n",
    "element_mappings = (map_horizontal_l2r, map_horizontal_r2l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'sid-c99bec65-c574-47c2-b484-5f46e6d48856'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'RF'</span>.     \n",
       "</pre>\n"
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       "\u001b[2;36m09:54:44 EDT\u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'directional coupler with mappings'\u001b[0m with resource_id  \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'sid-c99bec65-c574-47c2-b484-5f46e6d48856'\u001b[0m and task_type \u001b[32m'RF'\u001b[0m.     \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">-47c2-b484-5f46e6d48856'</span></a>.                                          \n",
       "</pre>\n"
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=871308;https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=919321;https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=871308;https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=520220;https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\u001b\\\u001b[32msid\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=871308;https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\u001b\\\u001b[32m-c99bec65-c574\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=871308;https://tidy3d.simulation.cloud/workbench?taskId=sid-c99bec65-c574-47c2-b484-5f46e6d48856\u001b\\\u001b[32m-47c2-b484-5f46e6d48856'\u001b[0m\u001b]8;;\u001b\\.                                          \n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-7d2988e3-13d2-49df-8e7b-f9b5036adc0b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
       "</pre>\n"
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=794845;https://tidy3d.simulation.cloud/folders/folder-7d2988e3-13d2-49df-8e7b-f9b5036adc0b\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
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       "Output()"
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></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\">09:54:46 EDT </span>Child simulation subtasks are being uploaded to                    \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- left_bot@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-3397c84d-c948-41e3-9229-16fdfe5ec48c'</span>            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- left_top@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-becb9048-b466-4135-b732-648ca327e67b'</span>            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- right_bot@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-1b614bc1-03fe-4900-a5f4-9dbae54cb3a4'</span>           \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- right_top@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-c20a8bec-ce7a-4477-b0ce-3afa968e0d54'</span>           \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m09:54:46 EDT\u001b[0m\u001b[2;36m \u001b[0mChild simulation subtasks are being uploaded to                    \n",
       "\u001b[2;36m             \u001b[0m- left_bot@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-3397c84d-c948-41e3-9229-16fdfe5ec48c'\u001b[0m            \n",
       "\u001b[2;36m             \u001b[0m- left_top@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-becb9048-b466-4135-b732-648ca327e67b'\u001b[0m            \n",
       "\u001b[2;36m             \u001b[0m- right_bot@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-1b614bc1-03fe-4900-a5f4-9dbae54cb3a4'\u001b[0m           \n",
       "\u001b[2;36m             \u001b[0m- right_top@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-c20a8bec-ce7a-4477-b0ce-3afa968e0d54'\u001b[0m           \n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Validating component modeler and subtask simulations<span style=\"color: #808000; text-decoration-color: #808000\">...</span>            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mValidating component modeler and subtask simulations\u001b[33m...\u001b[0m            \n"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">09:54:47 EDT </span>Maximum FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.930</span>. Minimum cost depends on task       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
       "</pre>\n"
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       "\u001b[2;36m09:54:47 EDT\u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m1.930\u001b[0m. Minimum cost depends on task       \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \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>Component modeler batch validation has been successful.            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mComponent modeler batch validation has been successful.            \n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
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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>Subtasks status - directional coupler with mappings                \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Group ID: <span style=\"color: #008000; text-decoration-color: #008000\">'pa-5f1136f7-f978-488e-b706-61e3cc0da9e1'</span>                \n",
       "</pre>\n"
      ],
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mSubtasks status - directional coupler with mappings                \n",
       "\u001b[2;36m             \u001b[0mGroup ID: \u001b[32m'pa-5f1136f7-f978-488e-b706-61e3cc0da9e1'\u001b[0m                \n"
      ]
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       "Output()"
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      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">09:55:48 EDT </span>Modeler has finished running successfully.                         \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m09:55:48 EDT\u001b[0m\u001b[2;36m \u001b[0mModeler has finished running successfully.                         \n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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       "Output()"
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      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"></pre>\n"
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     "metadata": {},
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     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">09:55:55 EDT </span>loading component modeler data from .<span style=\"color: #800080; text-decoration-color: #800080\">/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">cm_data.hdf5</span>                 \n",
       "</pre>\n"
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       "\u001b[2;36m09:55:55 EDT\u001b[0m\u001b[2;36m \u001b[0mloading component modeler data from .\u001b[35m/\u001b[0m\u001b[95mcm_data.hdf5\u001b[0m                 \n"
      ]
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "# run the component modeler again\n",
    "modeler = ModalComponentModeler(\n",
    "    simulation=sim,\n",
    "    ports=ports,\n",
    "    freqs=freqs,\n",
    "    element_mappings=element_mappings,\n",
    ")\n",
    "modeler_data = web.run(modeler, task_name=\"directional coupler with mappings\", verbose=True)\n",
    "smatrix = modeler_data.smatrix()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting scattering matrix will have the element mappings applied, we can check this explicitly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "top to top coupling       = -0.61577-0.34002j\n",
      "bottom to bottom coupling = -0.61577-0.34002j\n"
     ]
    }
   ],
   "source": [
    "# assert that the horizontal coupling elements are exactly equal\n",
    "smatrix_f0 = smatrix.sel(f=freq0, method=\"nearest\")\n",
    "LT_RT = np.squeeze(\n",
    "    smatrix_f0.loc[\n",
    "        dict(port_in=\"left_top\", mode_index_in=0, port_out=\"right_top\", mode_index_out=0)\n",
    "    ]\n",
    ")\n",
    "LB_RB = np.squeeze(\n",
    "    smatrix_f0.loc[\n",
    "        dict(port_in=\"left_bot\", mode_index_in=0, port_out=\"right_bot\", mode_index_out=0)\n",
    "    ]\n",
    ")\n",
    "print(f\"top to top coupling       = {LT_RT:.5f}\")\n",
    "print(f\"bottom to bottom coupling = {LB_RB:.5f}\")\n",
    "\n",
    "assert np.isclose(LT_RT, LB_RB)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Incomplete Scattering Matrix\n",
    "Finally, to exclude some rows of the scattering matrix, one can supply a `run_only` parameter to the `ComponentModeler`.\n",
    "\n",
    "`run_only` contains the scattering matrix indices that the user wants to run as a source. If any indices are excluded, they will not be run.\n",
    "\n",
    "For example, if one wants to compute scattering matrix elements from only the ports on the left hand side, the `run_only` could be defined as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "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\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Created task <span style=\"color: #008000; text-decoration-color: #008000\">'directional coupler run only'</span> with resource_id       \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><span style=\"color: #008000; text-decoration-color: #008000\">'sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4'</span> and task_type <span style=\"color: #008000; text-decoration-color: #008000\">'RF'</span>.     \n",
       "</pre>\n"
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mCreated task \u001b[32m'directional coupler run only'\u001b[0m with resource_id       \n",
       "\u001b[2;36m             \u001b[0m\u001b[32m'sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4'\u001b[0m and task_type \u001b[32m'RF'\u001b[0m.     \n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>View task using web UI at                                          \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span><a href=\"https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">-43c1-bb71-c40a032e87e4'</span></a>.                                          \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mView task using web UI at                                          \n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=352888;https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\u001b\\\u001b[32m'https://tidy3d.simulation.cloud/workbench?\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=149378;https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\u001b\\\u001b[32mtaskId\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=352888;https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\u001b\\\u001b[32m=\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=30699;https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\u001b\\\u001b[32msid\u001b[0m\u001b]8;;\u001b\\\u001b]8;id=352888;https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\u001b\\\u001b[32m-7fd4ac49-7f36\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m             \u001b[0m\u001b]8;id=352888;https://tidy3d.simulation.cloud/workbench?taskId=sid-7fd4ac49-7f36-43c1-bb71-c40a032e87e4\u001b\\\u001b[32m-43c1-bb71-c40a032e87e4'\u001b[0m\u001b]8;;\u001b\\.                                          \n"
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     },
     "metadata": {},
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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>Task folder: <a href=\"https://tidy3d.simulation.cloud/folders/folder-7d2988e3-13d2-49df-8e7b-f9b5036adc0b\" target=\"_blank\"><span style=\"color: #008000; text-decoration-color: #008000\">'default'</span></a>.                                            \n",
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mTask folder: \u001b]8;id=716997;https://tidy3d.simulation.cloud/folders/folder-7d2988e3-13d2-49df-8e7b-f9b5036adc0b\u001b\\\u001b[32m'default'\u001b[0m\u001b]8;;\u001b\\.                                            \n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- left_bot@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-00356e29-6410-45c2-b9f1-4c216f2a72d9'</span>            \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>- left_top@<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'rf-013369f6-0b81-4dd7-bd69-7617095ebb09'</span>            \n",
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       "\u001b[2;36m09:55:56 EDT\u001b[0m\u001b[2;36m \u001b[0mChild simulation subtasks are being uploaded to                    \n",
       "\u001b[2;36m             \u001b[0m- left_bot@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-00356e29-6410-45c2-b9f1-4c216f2a72d9'\u001b[0m            \n",
       "\u001b[2;36m             \u001b[0m- left_top@\u001b[1;36m0\u001b[0m: \u001b[32m'rf-013369f6-0b81-4dd7-bd69-7617095ebb09'\u001b[0m            \n"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">09:55:57 EDT </span>Validating component modeler and subtask simulations<span style=\"color: #808000; text-decoration-color: #808000\">...</span>            \n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m09:55:57 EDT\u001b[0m\u001b[2;36m \u001b[0mValidating component modeler and subtask simulations\u001b[33m...\u001b[0m            \n"
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     "data": {
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mMaximum FlexCredit cost: \u001b[1;36m0.918\u001b[0m. Minimum cost depends on task       \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \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>Component modeler batch validation has been successful.            \n",
       "</pre>\n"
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      "text/plain": [
       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mComponent modeler batch validation has been successful.            \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\">09:55:58 EDT </span>Subtasks status - directional coupler run only                     \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>Group ID: <span style=\"color: #008000; text-decoration-color: #008000\">'pa-6bad4b4a-25ad-4c3c-9941-2f97d4b17126'</span>                \n",
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       "\u001b[2;36m             \u001b[0mGroup ID: \u001b[32m'pa-6bad4b4a-25ad-4c3c-9941-2f97d4b17126'\u001b[0m                \n"
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       "\u001b[2;36m09:57:16 EDT\u001b[0m\u001b[2;36m \u001b[0mModeler has finished running successfully.                         \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>Billed FlexCredit cost: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.460</span>. Minimum cost depends on task        \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>execution details. Use <span style=\"color: #008000; text-decoration-color: #008000\">'web.real_cost(task_id)'</span> to get the billed  \n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">             </span>FlexCredit cost after a simulation run.                            \n",
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       "\u001b[2;36m            \u001b[0m\u001b[2;36m \u001b[0mBilled FlexCredit cost: \u001b[1;36m0.460\u001b[0m. Minimum cost depends on task        \n",
       "\u001b[2;36m             \u001b[0mexecution details. Use \u001b[32m'web.real_cost\u001b[0m\u001b[32m(\u001b[0m\u001b[32mtask_id\u001b[0m\u001b[32m)\u001b[0m\u001b[32m'\u001b[0m to get the billed  \n",
       "\u001b[2;36m             \u001b[0mFlexCredit cost after a simulation run.                            \n"
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       "Output()"
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   "source": [
    "run_only = (left_top, left_bot)\n",
    "modeler = ModalComponentModeler(\n",
    "    simulation=sim,\n",
    "    ports=ports,\n",
    "    freqs=[freq0],\n",
    "    run_only=run_only,\n",
    ")\n",
    "modeler_data = web.run(modeler, task_name=\"directional coupler run only\", verbose=True)\n",
    "smatrix = modeler_data.smatrix()\n",
    "smatrix_f0 = smatrix.sel(f=freq0, method=\"nearest\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The resulting scattering matrix will have all zeros for elements corresponding to ports not included in the in `run_only` inputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "output from run_only port     : \n",
      " [0.70575722 0.69541139 0.02991151 0.02848451]\n"
     ]
    }
   ],
   "source": [
    "s_matrix_left_top = np.squeeze(smatrix_f0.loc[dict(port_in=\"left_top\")])\n",
    "\n",
    "print(\"output from run_only port     : \\n\", np.abs(s_matrix_left_top.values))\n",
    "\n",
    "assert \"right_top\" not in smatrix.coords[\"port_in\"]"
   ]
  }
 ],
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  "description": "This notebook demonstrates how to compute the scattering matrix of a device in Tidy3D FDTD.",
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