{
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   "source": [
    "# Scattering Matrix Plugin\n",
    "\n",
    "Run this notebook in your browser using [Binder](https://mybinder.org/v2/gh/flexcompute-readthedocs/tidy3d-docs/readthedocs?labpath=docs%2Fsource%2Fnotebooks%2FSMatrix.ipynb).\n",
    "\n",
    "This notebook will give a demo of the tidy3d [ComponentModeler](https://docs.simulation.cloud/projects/tidy3d/en/latest/_autosummary/tidy3d.plugins.ComponentModeler.html) plugin used to compute scattering matrix elements."
   ]
  },
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    "# make sure notebook plots inline\n",
    "%matplotlib inline\n",
    "\n",
    "# standard python imports\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import gdspy\n",
    "\n",
    "# tidy3D imports\n",
    "import tidy3d as td\n",
    "from tidy3d import web\n",
    "\n",
    "# set tidy3d to only print error information to reduce verbosity\n",
    "td.logging_level = 'error'"
   ]
  },
  {
   "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."
   ]
  },
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   "source": [
    "# wavelength / frequency\n",
    "lambda0 = 1.550                     # all length scales in microns\n",
    "freq0 = td.constants.C_0 / lambda0\n",
    "fwidth = freq0 / 10\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 = 1.0\n",
    "# Waveguide separation in the beginning/end\n",
    "wg_spacing_in = 8\n",
    "# length of coupling region (um)\n",
    "coup_length = 6.0\n",
    "# spacing between waveguides in coupling region (um)\n",
    "wg_spacing_coup = 0.05\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 = 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"
   ]
  },
  {
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   "execution_count": 3,
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   "source": [
    "def bend_pts(bend_length, width, npts=10):\n",
    "    \"\"\" Set of points describing a tanh bend from (0, 0) to (length, width)\"\"\"\n",
    "    x = np.linspace(0, bend_length, npts)\n",
    "    y = width*(1 + np.tanh(6*(x/bend_length - 0.5)))/2\n",
    "    return np.stack((x, y), axis=1)\n",
    "\n",
    "def arm_pts(length, width, coup_length, bend_length, npts_bend=30):\n",
    "    \"\"\" Set of points defining one arm of an integrated coupler \"\"\"\n",
    "    ### Make the right half of the coupler arm first\n",
    "    # Make bend and offset by coup_length/2\n",
    "    bend = bend_pts(bend_length, width, npts_bend)\n",
    "    bend[:, 0] += coup_length / 2\n",
    "    # Add starting point as (0, 0)\n",
    "    right_half = np.concatenate(([[0, 0]], bend))\n",
    "    # Add an extra point to make sure waveguide is straight past the bend\n",
    "    right_half = np.concatenate((right_half, [[right_half[-1, 0] + 0.1, width]]))\n",
    "    # Add end point as (length/2, width)\n",
    "    right_half = np.concatenate((right_half, [[length/2, width]]))\n",
    "\n",
    "    # Make the left half by reflecting and omitting the (0, 0) point\n",
    "    left_half = np.copy(right_half)[1:, :]\n",
    "    left_half[:, 0] = -left_half[::-1, 0]\n",
    "    left_half[:, 1] = left_half[::-1, 1]\n",
    "    \n",
    "    return np.concatenate((left_half, right_half), axis=0)\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",
    "    \"\"\" Make an integrated coupler using the gdspy FlexPath object. \"\"\"\n",
    "\n",
    "    # Compute one arm of the coupler\n",
    "    arm_width = (wg_spacing_in - wg_width - wg_spacing_coup)/2\n",
    "    arm = arm_pts(length, arm_width, coup_length, bend_length, npts_bend)\n",
    "    # Reflect and offset bottom arm\n",
    "    coup_bot = np.copy(arm)\n",
    "    coup_bot[:, 1] = -coup_bot[::-1, 1] - wg_width/2 - wg_spacing_coup/2\n",
    "    # Offset top arm\n",
    "    coup_top = np.copy(arm)\n",
    "    coup_top[:, 1] += wg_width/2 + wg_spacing_coup/2\n",
    "    \n",
    "    # Create waveguides as GDS paths\n",
    "    path_bot = gdspy.FlexPath(coup_bot, wg_width, layer=1, datatype=0)\n",
    "    path_top = gdspy.FlexPath(coup_top, wg_width, layer=1, datatype=1)\n",
    "    \n",
    "    return [path_bot, path_top]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create Base Simulation\n",
    "\n",
    "The scattering matrix tool requires the \"base\" [Simulation](https://docs.simulation.cloud/projects/tidy3d/en/latest/_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.simulation.cloud/projects/tidy3d/en/latest/_autosummary/tidy3d.FieldMonitor.html?highlight=FieldMonitor) so we can inspect the field patterns."
   ]
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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\">[17:14:19] </span><span style=\"color: #800000; text-decoration-color: #800000\">WARNING </span> No sources in simulation.                               <a href=\"file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/components/simulation.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">simulation.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/components/simulation.py#406\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">406</span></a>\n",
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       "\u001b[2;36m[17:14:19]\u001b[0m\u001b[2;36m \u001b[0m\u001b[31mWARNING \u001b[0m No sources in simulation.                               \u001b]8;id=588901;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/components/simulation.py\u001b\\\u001b[2msimulation.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=24169;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/components/simulation.py#406\u001b\\\u001b[2m406\u001b[0m\u001b]8;;\u001b\\\n"
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    "gdspy.current_library = gdspy.GdsLibrary()\n",
    "lib = gdspy.GdsLibrary()\n",
    "\n",
    "# Geometry must be placed in GDS cells to import into Tidy3D\n",
    "coup_cell = lib.new_cell('Coupler')\n",
    "\n",
    "substrate = gdspy.Rectangle(\n",
    "    (-device_length/2, -wg_spacing_in/2-10),\n",
    "    (device_length/2, wg_spacing_in/2+10),\n",
    "    layer=0)\n",
    "coup_cell.add(substrate)\n",
    "\n",
    "# Add the coupler to a gdspy cell\n",
    "gds_coup = make_coupler(\n",
    "    device_length,\n",
    "    wg_spacing_in,\n",
    "    wg_width,\n",
    "    wg_spacing_coup,\n",
    "    coup_length,\n",
    "    bend_length)\n",
    "coup_cell.add(gds_coup)\n",
    "\n",
    "# Substrate\n",
    "[oxide_geo] = td.PolySlab.from_gds(\n",
    "    gds_cell=coup_cell,\n",
    "    gds_layer=0,\n",
    "    gds_dtype=0,\n",
    "    slab_bounds=(-10, 0),\n",
    "    axis=2)\n",
    "\n",
    "oxide = td.Structure(\n",
    "    geometry=oxide_geo,\n",
    "    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,\n",
    "    gds_layer=1,\n",
    "    slab_bounds=(0, wg_height),\n",
    "    axis=2)\n",
    "\n",
    "coupler1 = td.Structure(\n",
    "    geometry=coupler1_geo,\n",
    "    medium=mat_wg\n",
    ")\n",
    "\n",
    "coupler2 = td.Structure(\n",
    "    geometry=coupler2_geo,\n",
    "    medium=mat_wg\n",
    ")\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",
    "# 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],\n",
    "    size = [td.inf, td.inf, 0],\n",
    "    freqs = [freq0],\n",
    "    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",
    ")\n"
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     },
     "metadata": {
      "needs_background": "light"
     },
     "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 Scattering Matrix Tool\n",
    "Now, to use the S matrix tool, we need to defing the spatial extent of the \"ports\" of our system using [Port](https://docs.simulation.cloud/projects/tidy3d/en/latest/_autosummary/tidy3d.plugins.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": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:14:19.868849Z",
     "iopub.status.busy": "2022-07-21T21:14:19.868689Z",
     "iopub.status.idle": "2022-07-21T21:14:19.924602Z",
     "shell.execute_reply": "2022-07-21T21:14:19.924285Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tidy3d.plugins.smatrix.smatrix import Port\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=2),\n",
    "    direction='-',\n",
    "    name='right_top')\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=2),\n",
    "    direction='-',\n",
    "    name='right_bot')\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=2),\n",
    "    direction='+',\n",
    "    name='left_top')\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=2),\n",
    "    direction='+',\n",
    "    name='left_bot')\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.simulation.cloud/projects/tidy3d/en/latest/_autosummary/tidy3d.plugins.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": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:14:19.926349Z",
     "iopub.status.busy": "2022-07-21T21:14:19.926204Z",
     "iopub.status.idle": "2022-07-21T21:14:40.810473Z",
     "shell.execute_reply": "2022-07-21T21:14:40.809171Z"
    },
    "tags": []
   },
   "outputs": [
    {
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'c2d84cc1-1881-4e82-b64b-d4a25ab3629b'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001b[2;36m           \u001b[0m         \u001b[32m'c2d84cc1-1881-4e82-b64b-d4a25ab3629b'\u001b[0m.                     \u001b[2m             \u001b[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'d545720b-3ea4-4b6d-bab4-615d110678e5'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'cd232276-724c-4031-bd1c-296999a8ef9a'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'c26ab1f7-8581-4102-ab18-cb54028efaeb'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001b[2;36m           \u001b[0m         \u001b[32m'c26ab1f7-8581-4102-ab18-cb54028efaeb'\u001b[0m.                     \u001b[2m             \u001b[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'790b18b5-39df-4957-816a-e57aaa394fba'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001b[2;36m           \u001b[0m         \u001b[32m'790b18b5-39df-4957-816a-e57aaa394fba'\u001b[0m.                     \u001b[2m             \u001b[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'20f2d02f-8e41-4bc6-8183-e6d5b8a17f72'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
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       "\u001b[2;36m           \u001b[0m         \u001b[32m'20f2d02f-8e41-4bc6-8183-e6d5b8a17f72'\u001b[0m.                     \u001b[2m             \u001b[0m\n"
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       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>         <span style=\"color: #008000; text-decoration-color: #008000\">'65daf231-a203-4b05-aeef-f7607ff82740'</span>.                     <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">             </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[17:14:39]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Uploaded task \u001b[32m'smatrix_portleft_bot_mode1'\u001b[0m with task_id     \u001b]8;id=783719;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=385671;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\u001b\\\u001b[2m120\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0m         \u001b[32m'65daf231-a203-4b05-aeef-f7607ff82740'\u001b[0m.                     \u001b[2m             \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "161a3954a64b46d6b309d30eb544858f",
       "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"
    }
   ],
   "source": [
    "from tidy3d.plugins.smatrix.smatrix import ComponentModeler\n",
    "modeler = ComponentModeler(simulation=sim, ports=ports, freq=freq0)"
   ]
  },
  {
   "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": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:14:40.906222Z",
     "iopub.status.busy": "2022-07-21T21:14:40.906130Z",
     "iopub.status.idle": "2022-07-21T21:14:41.060485Z",
     "shell.execute_reply": "2022-07-21T21:14:41.060200Z"
    },
    "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=\"font-weight: bold\">&lt;</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff; font-weight: bold\">Figure</span><span style=\"color: #000000; text-decoration-color: #000000\"> size 108</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0x720</span><span style=\"color: #000000; text-decoration-color: #000000\"> with </span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2</span><span style=\"color: #000000; text-decoration-color: #000000\"> Axes</span><span style=\"font-weight: bold\">&gt;</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 108\u001b[0m\u001b[1;36m0x720\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m2\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "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 may call it's `.solve()` method to run a batch of simulations to compute the S matrix.\n",
    "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.\n",
    "Each of the ports will also be converted to mode monitors to measure the mode amplitudes and normalization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:14:41.062297Z",
     "iopub.status.busy": "2022-07-21T21:14:41.062126Z",
     "iopub.status.idle": "2022-07-21T21:22:54.641366Z",
     "shell.execute_reply": "2022-07-21T21:22:54.640986Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "\u001b[2;36m[17:14:45]\u001b[0m\u001b[2;36m \u001b[0mStarted working on Batch.                                         \u001b]8;id=161787;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/container.py\u001b\\\u001b[2mcontainer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=995428;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/container.py#384\u001b\\\u001b[2m384\u001b[0m\u001b]8;;\u001b\\\n"
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       "Output()"
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    },
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       "Output()"
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       "\u001b[2;36m[17:22:54]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from                                 \u001b]8;id=249194;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=160362;file:///home/shashwat/flexcompute/repositories/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#398\u001b\\\u001b[2m398\u001b[0m\u001b]8;;\u001b\\\n",
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   ],
   "source": [
    "smatrix = modeler.run(path_dir='data')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Working with Scattering Matrix\n",
    "\n",
    "The scattering matrix returned by the solve is actually a nested dictionarty relating the port names.\n",
    "For example `smatrix[name1][name2]` gives an array of shape `(m, n)` relating the coupling between the `m` modes injected into port `name1` with the `n` modes measured in port `name2`.\n",
    "\n",
    "For example, here each waveguide has 2 modes, so we can compute the coupling between the 2 input modes in `left_top` with the 2 output modes in `right_bot` as:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2022-07-21T21:22:58.049502Z"
    },
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   },
   "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\">\n",
       "<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">array</span><span style=\"font-weight: bold\">([[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.06405768+0.07115856j</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00669322-0.00306965j</span><span style=\"font-weight: bold\">]</span>,\n",
       "       <span style=\"font-weight: bold\">[</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.00574468-0.00463113j</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.35245579+0.43931115j</span><span style=\"font-weight: bold\">]])</span>\n",
       "</pre>\n"
      ],
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       "\n",
       "\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m0.06405768+0.07115856j\u001b[0m, \u001b[1;36m0.00669322-0.00306965j\u001b[0m\u001b[1m]\u001b[0m,\n",
       "       \u001b[1m[\u001b[0m\u001b[1;36m0.00574468-0.00463113j\u001b[0m, \u001b[1;36m0.35245579+0.43931115j\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m\n"
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   ],
   "source": [
    "smatrix['left_top']['right_bot']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, we can convert this into a numpy array:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:22:58.051204Z",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(8, 8)\n"
     ]
    }
   ],
   "source": [
    "blocks_cols = []\n",
    "for port_name_in, val_in in smatrix.items():\n",
    "    blocks_rows = []\n",
    "    for port_name_out, S_in_out in val_in.items():\n",
    "        blocks_rows.append(S_in_out)\n",
    "    blocks_cols.append(np.block(blocks_rows))\n",
    "S = np.concatenate(blocks_cols)\n",
    "print(S.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can inspect `S` and note that the diagonal elements are very small indicating low backscattering."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2022-07-21T21:22:58.057527Z"
    },
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   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[1.19474563e-04 3.84524744e-05 1.30710199e-06 1.71791191e-05\n",
      "  9.88835458e-01 3.45354262e-04 9.16672365e-03 5.51433494e-05]\n",
      " [3.84105732e-05 1.81103843e-04 1.75045775e-05 1.33686022e-04\n",
      "  3.46289767e-04 6.66286303e-01 5.53308841e-05 3.17179490e-01]\n",
      " [1.30942979e-06 1.74195952e-05 1.18416747e-04 3.83326123e-05\n",
      "  9.16690648e-03 5.42348612e-05 9.88832771e-01 3.45066232e-04]\n",
      " [1.74761613e-05 1.33721545e-04 3.70578836e-05 1.78586736e-04\n",
      "  5.44390178e-05 3.17219231e-01 3.46296752e-04 6.66280941e-01]\n",
      " [9.88824386e-01 3.47533504e-04 9.16692743e-03 5.42219524e-05\n",
      "  1.19366910e-04 3.83262152e-05 1.32683404e-06 1.74373165e-05]\n",
      " [3.46757462e-04 6.66369136e-01 5.44486295e-05 3.17219373e-01\n",
      "  3.70781649e-05 1.78675694e-04 1.74779135e-05 1.33136106e-04]\n",
      " [9.16639762e-03 5.51809273e-05 9.88830888e-01 3.45410542e-04\n",
      "  1.32680003e-06 1.71683153e-05 1.20300400e-04 3.84957392e-05]\n",
      " [5.53905501e-05 3.17215450e-01 3.46314313e-04 6.66283607e-01\n",
      "  1.75122371e-05 1.33131540e-04 3.84814298e-05 1.79949441e-04]]\n"
     ]
    }
   ],
   "source": [
    "print(abs(S)**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Summing each rows of the matrix should give 1.0 if no power was lost."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2022-07-21T21:22:58.061685Z"
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    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">\n",
       "<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">array</span><span style=\"font-weight: bold\">([</span><span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.9985696</span> , <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.984358</span>  , <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.99857286</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.9842704</span> , <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.99857838</span>,\n",
       "       <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.98427243</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.99857871</span>, <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.98422966</span><span style=\"font-weight: bold\">])</span>\n",
       "</pre>\n"
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       "\n",
       "\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m0.9985696\u001b[0m , \u001b[1;36m0.984358\u001b[0m  , \u001b[1;36m0.99857286\u001b[0m, \u001b[1;36m0.9842704\u001b[0m , \u001b[1;36m0.99857838\u001b[0m,\n",
       "       \u001b[1;36m0.98427243\u001b[0m, \u001b[1;36m0.99857871\u001b[0m, \u001b[1;36m0.98422966\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m\n"
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   ],
   "source": [
    "np.sum(abs(S)**2, axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we can check whether `S` is close to unitary as expected.\n",
    "\n",
    "S times it's Hermitian conjugate should be the identy matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
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   "outputs": [],
   "source": [
    "mat = S @ (np.conj(S.T))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2, ax3) = plt.subplots(1, 3, tight_layout=True, figsize=(12, 3.5))\n",
    "imabs = ax1.imshow(abs(mat))\n",
    "imreal = ax2.imshow(mat.real)\n",
    "imimag = ax3.imshow(mat.imag)\n",
    "plt.colorbar(imabs, ax=ax1)\n",
    "plt.colorbar(imreal, ax=ax2)\n",
    "plt.colorbar(imimag, ax=ax3)\n",
    "ax1.set_title('abs{$S^\\dagger S$}')\n",
    "ax2.set_title('real{$S^\\dagger S$}')\n",
    "ax3.set_title('imag{$S^\\dagger S$}')\n",
    "plt.show()"
   ]
  },
  {
   "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.\n",
    "For that, we can load up the batch and inspect the [SimulationData](https://docs.simulation.cloud/projects/tidy3d/en/latest/_autosummary/tidy3d.Simulation.html) for each task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:22:58.379625Z",
     "iopub.status.busy": "2022-07-21T21:22:58.379492Z",
     "iopub.status.idle": "2022-07-21T21:22:58.419693Z",
     "shell.execute_reply": "2022-07-21T21:22:58.419299Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "batch_data = modeler.batch.load(path_dir='data')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-07-21T21:22:58.421782Z",
     "iopub.status.busy": "2022-07-21T21:22:58.421643Z",
     "iopub.status.idle": "2022-07-21T21:23:02.848609Z",
     "shell.execute_reply": "2022-07-21T21:23:02.848272Z"
    },
    "tags": []
   },
   "outputs": [
    {
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      "text/plain": [
       "\u001b[1m<\u001b[0m\u001b[1;95mFigure\u001b[0m\u001b[39m size 108\u001b[0m\u001b[1;36m0x720\u001b[0m\u001b[39m with \u001b[0m\u001b[1;36m4\u001b[0m\u001b[39m Axes\u001b[0m\u001b[1m>\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(2, 1, tight_layout=True, figsize=(15, 10))\n",
    "ax1 = batch_data['smatrix_portleft_top_mode0'].plot_field('field', 'int', freq=freq0, z=wg_height/2, ax=ax1)\n",
    "ax2 = batch_data['smatrix_portleft_top_mode1'].plot_field('field', 'int', freq=freq0, z=wg_height/2, ax=ax2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.10"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "161a3954a64b46d6b309d30eb544858f": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/output",
       "_model_module_version": "1.0.0",
       "_model_name": "OutputModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/output",
       "_view_module_version": "1.0.0",
       "_view_name": "OutputView",
       "layout": "IPY_MODEL_6209ec6d4f154160b90ea74e2d0e9297",
       "msg_id": "",
       "outputs": [
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