{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Automatic nonuniform grid\n",
    "\n",
    "Here we demonstrate how to use the automatic nonuniform grid generation available in Tidy3D. We will show different possible ways to discretize the air-slot waveguide first introduced in [this reference](https://opg.optica.org/ol/abstract.cfm?uri=ol-29-11-1209)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:49.066009Z",
     "iopub.status.busy": "2023-03-28T01:20:49.065423Z",
     "iopub.status.idle": "2023-03-28T01:20:50.294545Z",
     "shell.execute_reply": "2023-03-28T01:20:50.294004Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# basic imports\n",
    "import numpy as np\n",
    "import matplotlib.pylab as plt\n",
    "\n",
    "# tidy3d imports\n",
    "import tidy3d as td\n",
    "from tidy3d.plugins.mode import ModeSolver\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:50.297073Z",
     "iopub.status.busy": "2023-03-28T01:20:50.296789Z",
     "iopub.status.idle": "2023-03-28T01:20:50.320358Z",
     "shell.execute_reply": "2023-03-28T01:20:50.319738Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# basic parameters (note, all length units are microns)\n",
    "nm = 1e-3\n",
    "wavelength = 1550 * nm\n",
    "freq0 = td.C_0 / wavelength\n",
    "\n",
    "# waveguide parameters\n",
    "slot_width = 50 * nm\n",
    "box_length = 300 * nm\n",
    "box_height = 180 * nm\n",
    "\n",
    "# materials\n",
    "si_med = td.Medium(permittivity=3.48**2)\n",
    "sub_med = td.Medium(permittivity=1.46**2)\n",
    "\n",
    "# structures\n",
    "box1 = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=(0, -box_length / 2 - slot_width / 2, 0),\n",
    "        size=(td.inf, box_length, box_height),\n",
    "    ),\n",
    "    medium=si_med,\n",
    ")\n",
    "box2 = td.Structure(\n",
    "    geometry=td.Box(\n",
    "        center=(0, box_length / 2 + slot_width / 2, 0),\n",
    "        size=(td.inf, box_length, box_height),\n",
    "    ),\n",
    "    medium=si_med,\n",
    ")\n",
    "\n",
    "# boundaries\n",
    "boundary_spec = td.BoundarySpec.all_sides(boundary=td.PML())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define a helper function to show us the various grids as we go along this exmaple."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:50.322477Z",
     "iopub.status.busy": "2023-03-28T01:20:50.322318Z",
     "iopub.status.idle": "2023-03-28T01:20:50.341360Z",
     "shell.execute_reply": "2023-03-28T01:20:50.340763Z"
    },
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Plot simulation and overlay grid in the yz and xy planes\n",
    "def plot_sim_grid(sim):\n",
    "    fig, ax = plt.subplots(1, 2, figsize=(12, 6))\n",
    "    sim.plot(x=0, ax=ax[0])\n",
    "    sim.plot_grid(x=0, ax=ax[0], lw=0.4, colors=\"r\")\n",
    "    ax[0].set_xlim(-0.6, 0.6)\n",
    "    ax[0].set_ylim(-0.4, 0.4)\n",
    "    sim.plot(z=0, ax=ax[1])\n",
    "    sim.plot_grid(z=0, ax=ax[1], lw=0.4, colors=\"r\")\n",
    "    ax[1].set_xlim(-0.6, 0.6)\n",
    "    ax[1].set_ylim(-0.4, 0.4)\n",
    "    print(f\"Total number of grid points (millions): {sim.num_cells / 1e6:1.2}\")\n",
    "\n",
    "    return ax\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Uniform grid\n",
    "\n",
    "The most standard way to define a simulation is to use a constant grid size in each of the three directions. This can be achieved simply using `td.GridSpec.uniform(dl=...)` as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:50.343492Z",
     "iopub.status.busy": "2023-03-28T01:20:50.343325Z",
     "iopub.status.idle": "2023-03-28T01:20:50.745898Z",
     "shell.execute_reply": "2023-03-28T01:20:50.745333Z"
    },
    "scrolled": false
   },
   "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\">[14:06:53] </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[14:06:53]\u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=795664;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=621035;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
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     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 8.3\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_uniform = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.uniform(dl=20 * nm),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_uniform)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: Tidy3D is warning us that our Simulation does not contain sources. In this case, since we are using the simulation as a demonstration of the meshing process and are not running any simulations, we may safely ignore this warning throughout this notebook."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Automatic nonuniform grid\n",
    "\n",
    "By default, Tidy3D uses a more advanced meshing, using an algorithm to automatically define a nonuniform grid in all three directions. The resolution of this grid is specified using the desired minimum steps per wavelength in each material (`min_steps_per_wvl = 10` by default). This specification therefore requires a target wavelength, which can be either provided directly to `grid_spec`, or inferred from any sources present in the simulation. The two simulations below will have the same grid."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:50.747943Z",
     "iopub.status.busy": "2023-03-28T01:20:50.747770Z",
     "iopub.status.idle": "2023-03-28T01:20:51.070234Z",
     "shell.execute_reply": "2023-03-28T01:20:51.069698Z"
    },
    "scrolled": false
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=730118;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=489103;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 0.53\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# provide wavelength directly\n",
    "sim_nonuniform_10 = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(wavelength=wavelength),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "# no grid_spec defined; using default with wavelength taken from source\n",
    "source = td.ModeSource(\n",
    "    center=(-2, 0, 0),\n",
    "    size=(0, 2, 2),\n",
    "    mode_index=0,\n",
    "    direction=\"+\",\n",
    "    source_time=td.GaussianPulse(freq0=freq0, fwidth=freq0 / 10),\n",
    ")\n",
    "sim_nonuniform_10 = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    "    sources=[source],\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_10)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The default grid is somewhat coarse, but it is often good for initial simulations. We can easily refine it by requiring a higher number of steps per wavelength:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:51.072214Z",
     "iopub.status.busy": "2023-03-28T01:20:51.072038Z",
     "iopub.status.idle": "2023-03-28T01:20:51.384549Z",
     "shell.execute_reply": "2023-03-28T01:20:51.384046Z"
    },
    "scrolled": false
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=34240;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=741937;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 2.3\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_nonuniform_20 = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "ax = plot_sim_grid(sim_nonuniform_20)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice how the automatic grid conforms to the structures in the simulation, and the grid steps are high in the high-index regions. \n",
    "\n",
    "### Lower bound of grid size\n",
    "Sometimes the grid size in the automatically generated mesh is too small. A lower bound `dl_min` can be set to increase the minimal grid size. Note that the bound is soft, meaning that the actual grid size might be slightly smaller.\n",
    "\n",
    "The minimal step size along y-direction in the previous setup is,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:51.386463Z",
     "iopub.status.busy": "2023-03-28T01:20:51.386286Z",
     "iopub.status.idle": "2023-03-28T01:20:51.404661Z",
     "shell.execute_reply": "2023-03-28T01:20:51.404175Z"
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimal grid size along y-direction = 16.67nm\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    f\"Minimal grid size along y-direction = {min(sim_nonuniform_20.grid.sizes.y)*1e3:1.2f}nm\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's set a lower bound of 25nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:51.406507Z",
     "iopub.status.busy": "2023-03-28T01:20:51.406367Z",
     "iopub.status.idle": "2023-03-28T01:20:51.719565Z",
     "shell.execute_reply": "2023-03-28T01:20:51.719041Z"
    },
    "scrolled": false
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=294819;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=931166;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 1.9\n",
      "Minimal grid size along y-direction = 24.57nm\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sim_nonuniform_20 = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "        dl_min=25 * nm,\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "ax = plot_sim_grid(sim_nonuniform_20)\n",
    "print(\n",
    "    f\"Minimal grid size along y-direction = {min(sim_nonuniform_20.grid.sizes.y)*1e3:1.2f}nm\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The actual minimal grid size along y-direction is 24.57nm, greater than 16.67nm when `dl_min` is not set."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mesh override structures\n",
    "For this particular problem, we may want to do a final refinement around the slot, where we expect the fields to be strongest. This can be achieved by adding `override_structures` to the simulation `grid_spec`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`override_structures` is a list of Tidy3D structures each with an arbitrary geometry which are used exclusively for the meshing, added on top of any physical simulation structures.\n",
    "\n",
    "There are two types of Tidy3D structures that can be added the `override_structures` list. The first type defines a fictitious medium inside the override structure so that the grid size is decided by the minimum steps per wavelength in the medium; The second type is more straightforward: one can directly define the grid size along each axis inside the override structures.\n",
    "\n",
    "#### Override Structure -- option 1\n",
    "The first type is identical to the [Structure](../_autosummary/tidy3d.Structure.html) object that consists of a [Geometry](../_autosummary/tidy3d.components.geometry.Geometry.html) and a [Medium](../_autosummary/tidy3d.components.medium.AbstractMedium.html). The grid step in the override_structure region is decided by the minimum steps per wavelength in this `medium`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:51.721693Z",
     "iopub.status.busy": "2023-03-28T01:20:51.721519Z",
     "iopub.status.idle": "2023-03-28T01:20:52.038334Z",
     "shell.execute_reply": "2023-03-28T01:20:52.037801Z"
    },
    "scrolled": false
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=19498;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=758700;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 4.0\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Define a \"dummy\" box with refractive index 5 around the central location of the waveguide\n",
    "refine_box = td.Structure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(td.inf, 0.4, 0.4)),\n",
    "    medium=td.Medium(permittivity=5**2),\n",
    ")\n",
    "\n",
    "# Use the box as a grid refinement structure\n",
    "sim_nonuniform_20_refine = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "        override_structures=[refine_box],\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_20_refine)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that the override region is highlighted in the grid plotting. Now this looks pretty good - the grid size of the points around the slot region is `1550 / 20 / 5 = 15.5` nanometers, while overall the simulation has twice fewer total number of grid points (`4.0M`) compared to the simulation with a uniform mesh step of `20` nanometers (`8.3M`). One thing to note, however, is that the override structure made the grid along the x-dimension small, which may not be necessary. To avoid this, we can change that structure to have `size = 0` along that dimension. This would force the non-uniform grid to place a grid boundary at the `center` of the override structure along `x`, but apart from that it will not refine the grid step along `x`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:52.040402Z",
     "iopub.status.busy": "2023-03-28T01:20:52.040201Z",
     "iopub.status.idle": "2023-03-28T01:20:52.412160Z",
     "shell.execute_reply": "2023-03-28T01:20:52.411666Z"
    }
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=371991;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=228567;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 3.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Redefine the box with size 0 along x\n",
    "refine_box = td.Structure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(0, 0.4, 0.4)),\n",
    "    medium=td.Medium(permittivity=5**2),\n",
    ")\n",
    "\n",
    "# Use the box as a grid refinement structure\n",
    "sim_nonuniform_20_refine = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "        override_structures=[refine_box],\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_20_refine)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Override Structure -- option 2\n",
    "The second type is the [MeshOverrideStructure](../_autosummary/tidy3d.MeshOverrideStructure.html) object that consists of a [Geometry](../_autosummary/tidy3d.components.geometry.Geometry.html), and a tuple `dl` specifying the grid sizes along x,y,z directions. We can override the grid sizes just along a few selected directions by setting the value to be `None` in the `dl` tuple along the other directions. E.g. if we only plan to refine the grid size along x-direction with grid size 0.01 micron, we can apply `dl=(0.01, None, None)`. In the following, we override the grid size along `y` and `z` to be 15.5nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:52.414078Z",
     "iopub.status.busy": "2023-03-28T01:20:52.413933Z",
     "iopub.status.idle": "2023-03-28T01:20:52.727802Z",
     "shell.execute_reply": "2023-03-28T01:20:52.727426Z"
    },
    "scrolled": false
   },
   "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\">[14:06:54] </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[14:06:54]\u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=148632;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=922448;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 2.9\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "refine_box = td.MeshOverrideStructure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(td.inf, 0.4, 0.4)),\n",
    "    dl=[None, 15.5 * nm, 15.5 * nm],\n",
    ")\n",
    "\n",
    "# Use the box as a grid refinement structure\n",
    "sim_nonuniform_20_refine = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "        override_structures=[refine_box],\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_20_refine)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Just for fun, we can also have a look at the modes of this structure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:52.729677Z",
     "iopub.status.busy": "2023-03-28T01:20:52.729503Z",
     "iopub.status.idle": "2023-03-28T01:20:55.276741Z",
     "shell.execute_reply": "2023-03-28T01:20:55.276240Z"
    },
    "scrolled": false,
    "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=773786;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=743714;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x1400 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_modes = 3\n",
    "plane = td.Box(center=(0, 0, 0), size=(0, 2, 2))\n",
    "mode_spec = td.ModeSpec(num_modes=num_modes)\n",
    "ms = ModeSolver(\n",
    "    simulation=sim_nonuniform_20_refine, plane=plane, mode_spec=mode_spec, freqs=[freq0]\n",
    ")\n",
    "modes = ms.solve()\n",
    "fig, axs = plt.subplots(num_modes, 2, figsize=(12, 14))\n",
    "for mode_ind in range(num_modes):\n",
    "    ms.plot_field(\n",
    "        \"Ey\", \"abs\", f=freq0, mode_index=mode_ind, ax=axs[mode_ind, 0], robust=False\n",
    "    )\n",
    "    ms.plot_field(\n",
    "        \"Ez\", \"abs\", f=freq0, mode_index=mode_ind, ax=axs[mode_ind, 1], robust=False\n",
    "    )\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Mesh override with coarser grid size\n",
    "Sometimes, instead of refinement, we want to override a region with a coarser mesh. This can be achieved by setting `enforce=True` in [MeshOverrideStructure](../_autosummary/tidy3d.MeshOverrideStructure.html).\n",
    "\n",
    "First, let's see the default behavior where `enforce=False` so that the override structure with coarser mesh will be ignored unless it fully covers the structure of fine mesh. In the following example, we try to override the mesh along x-direction be to 40nm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:55.279070Z",
     "iopub.status.busy": "2023-03-28T01:20:55.278864Z",
     "iopub.status.idle": "2023-03-28T01:20:55.599238Z",
     "shell.execute_reply": "2023-03-28T01:20:55.598706Z"
    },
    "scrolled": false
   },
   "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\">[14:06:55] </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m[14:06:55]\u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=871733;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=32037;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 2.9\n",
      "Minimal grid size along x-direction = 22.22nm\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "refine_box = td.MeshOverrideStructure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(td.inf, 0.4, 0.4)),\n",
    "    dl=[50 * nm, 15.5 * nm, 15.5 * nm],\n",
    ")\n",
    "\n",
    "# Use the box as a grid refinement structure\n",
    "sim_nonuniform_20_coarser = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "        override_structures=[refine_box],\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_20_coarser)\n",
    "print(\n",
    "    f\"Minimal grid size along x-direction = {min(sim_nonuniform_20_coarser.grid.sizes.x)*1e3:1.2f}nm\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The minimal grid size along x-direction is still 22nm, so the `override_structures` doesn't take effect. This is because, by default, the meshing chooses the step size based on the highest-index structure (real or override) at any given cross-section. However, this behavior can be overridden if we set `enforce=True` in an `MeshOverrideStructure`, in which case other structures are ignored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:55.601262Z",
     "iopub.status.busy": "2023-03-28T01:20:55.601087Z",
     "iopub.status.idle": "2023-03-28T01:20:55.975510Z",
     "shell.execute_reply": "2023-03-28T01:20:55.974989Z"
    }
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=123563;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=917028;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 1.4\n",
      "Minimal grid size along x-direction = 40.00nm\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "refine_box = td.MeshOverrideStructure(\n",
    "    geometry=td.Box(center=(0, 0, 0), size=(td.inf, 0.4, 0.4)),\n",
    "    dl=[40 * nm, None, None],\n",
    "    enforce=True,\n",
    ")\n",
    "\n",
    "# Use the box as a grid refinement structure\n",
    "sim_nonuniform_20_coarser = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=td.GridSpec.auto(\n",
    "        wavelength=wavelength,\n",
    "        min_steps_per_wvl=20,\n",
    "        override_structures=[refine_box],\n",
    "    ),\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_20_coarser)\n",
    "print(\n",
    "    f\"Minimal grid size along x-direction = {min(sim_nonuniform_20_coarser.grid.sizes.x)*1e3:1.2f}nm\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the minimal grid size along x-direction is target 40nm. When multiple override structures with `enforce=True` overlap, the grid size in the intersection region is decided by the last such structure in the list."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Combination of uniform and nonuiform grid\n",
    "\n",
    "Finally, we note that Tidy3D allows another easy way to handle the `x` direction in our example, namely applying different grid specifications along each of the three simulation directions. For example, we can set a fixed grid size of `40nm` along the propagation direction, where we expect the field dependence to be smooth, while still using the refined nonuniform mesh in the other two directions. This achieves the same effect as in the plot above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-03-28T01:20:55.977594Z",
     "iopub.status.busy": "2023-03-28T01:20:55.977421Z",
     "iopub.status.idle": "2023-03-28T01:20:56.291490Z",
     "shell.execute_reply": "2023-03-28T01:20:56.290886Z"
    },
    "scrolled": false
   },
   "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\">           </span>WARNING: No sources in simulation.                                       <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: No sources in simulation.                                       \u001b]8;id=678988;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=218105;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\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>WARNING: Override structures take no effect along x-axis. If intending   <a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">log.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">50</span></a>\n",
       "<span style=\"color: #7fbfbf; text-decoration-color: #7fbfbf\">           </span>to apply override structures to this axis, use <span style=\"color: #008000; text-decoration-color: #008000\">'AutoGrid'</span>.               <span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">         </span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0mWARNING: Override structures take no effect along x-axis. If intending   \u001b]8;id=461977;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py\u001b\\\u001b[2mlog.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=826280;file:///home/weiliang/Documents/tidy3d-core/tidy3d_frontend/tidy3d/log.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n",
       "\u001b[2;36m           \u001b[0mto apply override structures to this axis, use \u001b[32m'AutoGrid'\u001b[0m.               \u001b[2m         \u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of grid points (millions): 1.4\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid_spec = td.GridSpec(\n",
    "    grid_x=td.UniformGrid(dl=0.04),\n",
    "    grid_y=td.AutoGrid(min_steps_per_wvl=20),\n",
    "    grid_z=td.AutoGrid(min_steps_per_wvl=20),\n",
    "    wavelength=wavelength,\n",
    "    override_structures=[refine_box],\n",
    ")\n",
    "\n",
    "sim_nonuniform_yz_uniform_x = td.Simulation(\n",
    "    size=[5, 3, 3],\n",
    "    grid_spec=grid_spec,\n",
    "    medium=sub_med,\n",
    "    structures=[box1, box2],\n",
    "    boundary_spec=boundary_spec,\n",
    "    run_time=1e-12,\n",
    ")\n",
    "\n",
    "ax = plot_sim_grid(sim_nonuniform_yz_uniform_x)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: the 2nd warning is just letting us know that we are using uniform grid along x-axis even though the override structures have some extent in these dimensions. We can ignore as this is intended."
   ]
  },
  {
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}