{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Tidy3D first walkthrough\n", "\n", "Our first tutorial focuses on illustrating the basic setup, run, and analysis of a ``Tidy3D`` simulation. In this example, we will simulate a plane wave impinging on dielectric slab with a triangular pillar made of a lossy dielectric sitting on top. First, we import everything needed." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:26.360305Z", "iopub.status.busy": "2023-02-03T06:00:26.360009Z", "iopub.status.idle": "2023-02-03T06:00:27.038883Z", "shell.execute_reply": "2023-02-03T06:00:27.038522Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
[00:00:26] WARNING  This version of Tidy3D was pip installed from the 'tidy3d-beta' repository on   __init__.py:103\n",
       "                    PyPI. Future releases will be uploaded to the 'tidy3d' repository. From now on,                \n",
       "                    please use 'pip install tidy3d' instead.                                                       \n",
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           INFO     Using client version: 1.9.0rc1                                                  __init__.py:121\n",
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\n" ], "text/plain": [ "\u001b[2;36m \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO \u001b[0m Using client version: \u001b[1;36m1.9\u001b[0m.0rc1 \u001b]8;id=625744;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=87606;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/__init__.py#121\u001b\\\u001b[2m121\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# standard python imports\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import h5py\n", "\n", "# tidy3d imports\n", "import tidy3d as td\n", "from tidy3d import web\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "First, we initialize some general simulation parameters. We note that the PML layers extend **beyond** the simulation domain, making the total simulation size larger - as opposed to some solvers in which the PML is covering part of the user-defined simulation domain." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.040612Z", "iopub.status.busy": "2023-02-03T06:00:27.040460Z", "iopub.status.idle": "2023-02-03T06:00:27.042805Z", "shell.execute_reply": "2023-02-03T06:00:27.042547Z" }, "tags": [] }, "outputs": [], "source": [ "# Simulation domain size (in micron)\n", "sim_size = [4, 4, 4]\n", "\n", "# Central frequency and bandwidth of pulsed excitation, in Hz\n", "freq0 = 2e14\n", "fwidth = 1e13\n", "\n", "# # pad the z direction (out of plane) with PML but leave it off x and y for periodic boundary conditions.\n", "# boundary_spec=td.BoundarySpec.pml(x=False, y=False, z=True)\n", "\n", "# apply a PML in all directions\n", "boundary_spec = td.BoundarySpec.all_sides(boundary=td.PML())\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The run time of a simulation depends a lot on whether there are any long-lived resonances. In our example here, there is no strong resonance. Thus, we do not need to run the simulation much longer than after the sources have decayed. We thus set the run time based on the source bandwidth." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.044174Z", "iopub.status.busy": "2023-02-03T06:00:27.044070Z", "iopub.status.idle": "2023-02-03T06:00:27.045859Z", "shell.execute_reply": "2023-02-03T06:00:27.045603Z" }, "tags": [] }, "outputs": [], "source": [ "# Total time to run in seconds\n", "run_time = 2 / fwidth\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Structures and materials\n", "\n", "Next, we initialize the simulated structure. The structure consists of two [Structure](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Structure.html) objects. Each object consists of a [Geometry](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.components.geometry.Geometry.html) and a [Medium](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.components.medium.AbstractMedium.html) to define the spatial extent and material properties, respectively. Note that the size of any object (structure, source, or monitor) can extend beyond the simulation domain, and is truncated at the edges of that domain. \n", "\n", "Note: For best results, structures that intersect with the PML or simulation edges should extend extend all the way through. In many such cases, an \"infinite\" size `td.inf` can be used to define the size along that dimension." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.047218Z", "iopub.status.busy": "2023-02-03T06:00:27.047108Z", "iopub.status.idle": "2023-02-03T06:00:27.049911Z", "shell.execute_reply": "2023-02-03T06:00:27.049630Z" }, "tags": [] }, "outputs": [], "source": [ "# Lossless dielectric specified directly using relative permittivity\n", "material1 = td.Medium(permittivity=6.0)\n", "\n", "# Lossy dielectric defined from the real and imaginary part of the refractive index\n", "material2 = td.Medium.from_nk(n=1.5, k=0.0, freq=freq0)\n", "# material2 = td.Medium(permittivity=2.)\n", "\n", "\n", "# Rectangular slab, extending infinitely in x and y with medium `material1`\n", "box = td.Structure(\n", " geometry=td.Box(center=[0, 0, 0], size=[td.inf, td.inf, 1]), medium=material1\n", ")\n", "\n", "# Triangle in the xy-plane with a finite extent in z\n", "equi_tri_verts = [[-1 / 2, -1 / 4], [1 / 2, -1 / 4], [0, np.sqrt(3) / 2 - 1 / 4]]\n", "\n", "poly = td.Structure(\n", " geometry=td.PolySlab(\n", " vertices=(2 * np.array(equi_tri_verts)).tolist(),\n", " # vertices=equi_tri_verts,\n", " slab_bounds=(0.5, 1.0),\n", " axis=2,\n", " ),\n", " medium=material2,\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Sources\n", "\n", "Next, we define a source injecting a normal-incidence plane-wave from above. The time dependence of the source is a Gaussian pulse. A source can be added to multiple simulations. After we add the source to a specific simulation, such that the total run time is known, we can use in-built plotting tools to visualize its time- and frequency-dependence, which we will show below." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.051218Z", "iopub.status.busy": "2023-02-03T06:00:27.051124Z", "iopub.status.idle": "2023-02-03T06:00:27.053150Z", "shell.execute_reply": "2023-02-03T06:00:27.052855Z" }, "tags": [] }, "outputs": [], "source": [ "psource = td.PlaneWave(\n", " center=(0, 0, 1.5),\n", " direction=\"-\",\n", " size=(td.inf, td.inf, 0),\n", " source_time=td.GaussianPulse(freq0=freq0, fwidth=fwidth),\n", " pol_angle=np.pi / 2,\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Monitors\n", "\n", "Finally, we can also add some monitors that will record the fields that we request during the simulation run. \n", "\n", "The two monitor types for measuring fields are [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) and [FieldTimeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldTimeMonitor.html), which record the frequency-domain and time-domain fields, respectively. \n", "\n", "[FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) objects operate by running a discrete Fourier transform of the fields at a given set of frequencies to perform the calculation \"in-place\" with the time stepping. [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) objects are useful for investigating the steady-state field distribution in 2D or even 3D regions of the simulation.\n", "\n", "[FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) objects are best used to monitor the time dependence of the fields at a single point, but they can also be used to create \"animations\" of the field pattern evolution. Because spatially large [FieldMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html) objects can lead to a very large amount of data that needs to be stored, an optional start and stop time can be supplied, as well as an `interval` specifying the amount of time steps between each measurement (default of 1)." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.054479Z", "iopub.status.busy": "2023-02-03T06:00:27.054388Z", "iopub.status.idle": "2023-02-03T06:00:27.056582Z", "shell.execute_reply": "2023-02-03T06:00:27.056310Z" }, "tags": [] }, "outputs": [], "source": [ "# measure time domain fields at center location, measure every 5 time steps\n", "time_mnt = td.FieldTimeMonitor(\n", " center=[0, 0, 0], size=[0, 0, 0], interval=5, name=\"field_time\"\n", ")\n", "\n", "# measure the steady state fields at central frequency in the xy plane and the xz plane.\n", "freq_mnt1 = td.FieldMonitor(\n", " center=[0, 0, -1], size=[20, 20, 0], freqs=[freq0], name=\"field1\"\n", ")\n", "freq_mnt2 = td.FieldMonitor(\n", " center=[0, 0, 0], size=[20, 0, 20], freqs=[freq0], name=\"field2\"\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Simulation\n", "\n", "Now we can initialize the [Simulation](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Simulation.html) with all the elements defined above. A nonuniform simulation grid is generated automatically based on a given minimum number of cells per wavelength in each material (10 by default), using the frequencies defined in the source." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.058030Z", "iopub.status.busy": "2023-02-03T06:00:27.057935Z", "iopub.status.idle": "2023-02-03T06:00:27.060516Z", "shell.execute_reply": "2023-02-03T06:00:27.060254Z" }, "tags": [] }, "outputs": [], "source": [ "# Initialize simulation\n", "sim = td.Simulation(\n", " size=sim_size,\n", " grid_spec=td.GridSpec.auto(min_steps_per_wvl=20),\n", " structures=[box, poly],\n", " sources=[psource],\n", " monitors=[time_mnt, freq_mnt1, freq_mnt2],\n", " run_time=run_time,\n", " boundary_spec=boundary_spec,\n", ")\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can check the simulation monitors just to make sure everything looks right." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.061844Z", "iopub.status.busy": "2023-02-03T06:00:27.061751Z", "iopub.status.idle": "2023-02-03T06:00:27.093455Z", "shell.execute_reply": "2023-02-03T06:00:27.093184Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
╭───────────── <class 'tidy3d.components.monitor.FieldTimeMonitor'> ─────────────╮\n",
       "│ :class:`Monitor` that records electromagnetic fields in the time domain.       │\n",
       "│                                                                                │\n",
       "│ ╭────────────────────────────────────────────────────────────────────────────╮ │\n",
       "│ │ FieldTimeMonitor(                                                          │ │\n",
       "│ │ │   type='FieldTimeMonitor',                                               │ │\n",
       "│ │ │   center=(0.0, 0.0, 0.0),                                                │ │\n",
       "│ │ │   size=(0.0, 0.0, 0.0),                                                  │ │\n",
       "│ │ │   name='field_time',                                                     │ │\n",
       "│ │ │   start=0.0,                                                             │ │\n",
       "│ │ │   stop=None,                                                             │ │\n",
       "│ │ │   interval=5,                                                            │ │\n",
       "│ │ │   fields=('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz'),                           │ │\n",
       "│ │ │   interval_space=(1, 1, 1),                                              │ │\n",
       "│ │ │   colocate=False                                                         │ │\n",
       "│ │ )                                                                          │ │\n",
       "│ ╰────────────────────────────────────────────────────────────────────────────╯ │\n",
       "│                                                                                │\n",
       "│   bounding_box = Box(type='Box', center=(0.0, 0.0, 0.0), size=(0.0, 0.0, 0.0)) │\n",
       "│         bounds = ((0.0, 0.0, 0.0), (0.0, 0.0, 0.0))                            │\n",
       "│         center = (0.0, 0.0, 0.0)                                               │\n",
       "│       colocate = False                                                         │\n",
       "│         fields = ('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz')                          │\n",
       "│       geometry = Box(type='Box', center=(0.0, 0.0, 0.0), size=(0.0, 0.0, 0.0)) │\n",
       "│       interval = 5                                                             │\n",
       "│ interval_space = (1, 1, 1)                                                     │\n",
       "│           name = 'field_time'                                                  │\n",
       "│    plot_params = PlotParams(                                                   │\n",
       "│                      alpha=0.4,                                                │\n",
       "│                      edgecolor='orange',                                       │\n",
       "│                      facecolor='orange',                                       │\n",
       "│                      fill=True,                                                │\n",
       "│                      hatch=None,                                               │\n",
       "│                      linewidth=3.0,                                            │\n",
       "│                      type='PlotParams'                                         │\n",
       "│                  )                                                             │\n",
       "│           size = (0.0, 0.0, 0.0)                                               │\n",
       "│          start = 0.0                                                           │\n",
       "│           stop = None                                                          │\n",
       "│           type = 'FieldTimeMonitor'                                            │\n",
       "│      zero_dims = [0, 1, 2]                                                     │\n",
       "╰────────────────────────────────────────────────────────────────────────────────╯\n",
       "
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"\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33minterval\u001b[0m=\u001b[1;36m5\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mfields\u001b[0m=\u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mcolocate\u001b[0m=\u001b[3;91mFalse\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m)\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m╰────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mbounding_box\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mbounds\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mcenter\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mcolocate\u001b[0m = \u001b[3;91mFalse\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mfields\u001b[0m = \u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mgeometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33minterval\u001b[0m = \u001b[1;36m5\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33minterval_space\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mname\u001b[0m = \u001b[32m'field_time'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mplot_params\u001b[0m = \u001b[1;35mPlotParams\u001b[0m\u001b[1m(\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33malpha\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.4\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33medgecolor\u001b[0m=\u001b[32m'orange'\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mfacecolor\u001b[0m=\u001b[32m'orange'\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mfill\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mhatch\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mlinewidth\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mtype\u001b[0m=\u001b[32m'PlotParams'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33msize\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mstart\u001b[0m = \u001b[1;36m0.0\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mstop\u001b[0m = \u001b[3;35mNone\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mtype\u001b[0m = \u001b[32m'FieldTimeMonitor'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mzero_dims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1;36m0\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m2\u001b[0m\u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
╭─────────────────────── <class 'tidy3d.components.monitor.FieldMonitor'> ───────────────────────╮\n",
       "│ :class:`Monitor` that records electromagnetic fields in the frequency domain.                  │\n",
       "│                                                                                                │\n",
       "│ ╭────────────────────────────────────────────────────────────────────────────────────────────╮ │\n",
       "│ │ FieldMonitor(                                                                              │ │\n",
       "│ │ │   type='FieldMonitor',                                                                   │ │\n",
       "│ │ │   center=(0.0, 0.0, -1.0),                                                               │ │\n",
       "│ │ │   size=(20.0, 20.0, 0.0),                                                                │ │\n",
       "│ │ │   name='field1',                                                                         │ │\n",
       "│ │ │   freqs=(200000000000000.0,),                                                            │ │\n",
       "│ │ │   apodization=ApodizationSpec(                                                           │ │\n",
       "│ │ │   │   start=None,                                                                        │ │\n",
       "│ │ │   │   end=None,                                                                          │ │\n",
       "│ │ │   │   width=None,                                                                        │ │\n",
       "│ │ │   │   type='ApodizationSpec'                                                             │ │\n",
       "│ │ │   ),                                                                                     │ │\n",
       "│ │ │   fields=('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz'),                                           │ │\n",
       "│ │ │   interval_space=(1, 1, 1),                                                              │ │\n",
       "│ │ │   colocate=False                                                                         │ │\n",
       "│ │ )                                                                                          │ │\n",
       "│ ╰────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
       "│                                                                                                │\n",
       "│    apodization = ApodizationSpec(start=None, end=None, width=None, type='ApodizationSpec')     │\n",
       "│   bounding_box = Box(type='Box', center=(0.0, 0.0, -1.0), size=(20.0, 20.0, 0.0))              │\n",
       "│         bounds = ((-10.0, -10.0, -1.0), (10.0, 10.0, -1.0))                                    │\n",
       "│         center = (0.0, 0.0, -1.0)                                                              │\n",
       "│       colocate = False                                                                         │\n",
       "│         fields = ('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz')                                          │\n",
       "│          freqs = (200000000000000.0,)                                                          │\n",
       "│       geometry = Box(type='Box', center=(0.0, 0.0, -1.0), size=(20.0, 20.0, 0.0))              │\n",
       "│ interval_space = (1, 1, 1)                                                                     │\n",
       "│           name = 'field1'                                                                      │\n",
       "│    plot_params = PlotParams(                                                                   │\n",
       "│                      alpha=0.4,                                                                │\n",
       "│                      edgecolor='orange',                                                       │\n",
       "│                      facecolor='orange',                                                       │\n",
       "│                      fill=True,                                                                │\n",
       "│                      hatch=None,                                                               │\n",
       "│                      linewidth=3.0,                                                            │\n",
       "│                      type='PlotParams'                                                         │\n",
       "│                  )                                                                             │\n",
       "│           size = (20.0, 20.0, 0.0)                                                             │\n",
       "│           type = 'FieldMonitor'                                                                │\n",
       "│      zero_dims = [2]                                                                           │\n",
       "╰────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
       "
\n" ], "text/plain": [ "\u001b[34m╭─\u001b[0m\u001b[34m──────────────────────\u001b[0m\u001b[34m \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'tidy3d.components.monitor.FieldMonitor'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m \u001b[0m\u001b[34m──────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[36m:class:`Monitor` that records electromagnetic fields in the frequency domain.\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m╭────────────────────────────────────────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1;35mFieldMonitor\u001b[0m\u001b[1m(\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'FieldMonitor'\u001b[0m, \u001b[32m│\u001b[0m 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\u001b[0m\u001b[33mapodization\u001b[0m=\u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mfields\u001b[0m=\u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mcolocate\u001b[0m=\u001b[3;91mFalse\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m)\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m╰────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mapodization\u001b[0m = \u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m\u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mbounding_box\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20.0\u001b[0m, \u001b[1;36m20.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mbounds\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-10.0\u001b[0m, \u001b[1;36m-10.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m10.0\u001b[0m, \u001b[1;36m10.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mcenter\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mcolocate\u001b[0m = \u001b[3;91mFalse\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mfields\u001b[0m = \u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mfreqs\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m200000000000000.0\u001b[0m,\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mgeometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m-1.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20.0\u001b[0m, \u001b[1;36m20.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33minterval_space\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mname\u001b[0m = \u001b[32m'field1'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mplot_params\u001b[0m = \u001b[1;35mPlotParams\u001b[0m\u001b[1m(\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33malpha\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.4\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33medgecolor\u001b[0m=\u001b[32m'orange'\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mfacecolor\u001b[0m=\u001b[32m'orange'\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mfill\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mhatch\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mlinewidth\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mtype\u001b[0m=\u001b[32m'PlotParams'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33msize\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m20.0\u001b[0m, \u001b[1;36m20.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mtype\u001b[0m = \u001b[32m'FieldMonitor'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mzero_dims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
╭─────────────────────── <class 'tidy3d.components.monitor.FieldMonitor'> ───────────────────────╮\n",
       "│ :class:`Monitor` that records electromagnetic fields in the frequency domain.                  │\n",
       "│                                                                                                │\n",
       "│ ╭────────────────────────────────────────────────────────────────────────────────────────────╮ │\n",
       "│ │ FieldMonitor(                                                                              │ │\n",
       "│ │ │   type='FieldMonitor',                                                                   │ │\n",
       "│ │ │   center=(0.0, 0.0, 0.0),                                                                │ │\n",
       "│ │ │   size=(20.0, 0.0, 20.0),                                                                │ │\n",
       "│ │ │   name='field2',                                                                         │ │\n",
       "│ │ │   freqs=(200000000000000.0,),                                                            │ │\n",
       "│ │ │   apodization=ApodizationSpec(                                                           │ │\n",
       "│ │ │   │   start=None,                                                                        │ │\n",
       "│ │ │   │   end=None,                                                                          │ │\n",
       "│ │ │   │   width=None,                                                                        │ │\n",
       "│ │ │   │   type='ApodizationSpec'                                                             │ │\n",
       "│ │ │   ),                                                                                     │ │\n",
       "│ │ │   fields=('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz'),                                           │ │\n",
       "│ │ │   interval_space=(1, 1, 1),                                                              │ │\n",
       "│ │ │   colocate=False                                                                         │ │\n",
       "│ │ )                                                                                          │ │\n",
       "│ ╰────────────────────────────────────────────────────────────────────────────────────────────╯ │\n",
       "│                                                                                                │\n",
       "│    apodization = ApodizationSpec(start=None, end=None, width=None, type='ApodizationSpec')     │\n",
       "│   bounding_box = Box(type='Box', center=(0.0, 0.0, 0.0), size=(20.0, 0.0, 20.0))               │\n",
       "│         bounds = ((-10.0, 0.0, -10.0), (10.0, 0.0, 10.0))                                      │\n",
       "│         center = (0.0, 0.0, 0.0)                                                               │\n",
       "│       colocate = False                                                                         │\n",
       "│         fields = ('Ex', 'Ey', 'Ez', 'Hx', 'Hy', 'Hz')                                          │\n",
       "│          freqs = (200000000000000.0,)                                                          │\n",
       "│       geometry = Box(type='Box', center=(0.0, 0.0, 0.0), size=(20.0, 0.0, 20.0))               │\n",
       "│ interval_space = (1, 1, 1)                                                                     │\n",
       "│           name = 'field2'                                                                      │\n",
       "│    plot_params = PlotParams(                                                                   │\n",
       "│                      alpha=0.4,                                                                │\n",
       "│                      edgecolor='orange',                                                       │\n",
       "│                      facecolor='orange',                                                       │\n",
       "│                      fill=True,                                                                │\n",
       "│                      hatch=None,                                                               │\n",
       "│                      linewidth=3.0,                                                            │\n",
       "│                      type='PlotParams'                                                         │\n",
       "│                  )                                                                             │\n",
       "│           size = (20.0, 0.0, 20.0)                                                             │\n",
       "│           type = 'FieldMonitor'                                                                │\n",
       "│      zero_dims = [1]                                                                           │\n",
       "╰────────────────────────────────────────────────────────────────────────────────────────────────╯\n",
       "
\n" ], "text/plain": [ "\u001b[34m╭─\u001b[0m\u001b[34m──────────────────────\u001b[0m\u001b[34m \u001b[0m\u001b[1;34m<\u001b[0m\u001b[1;95mclass\u001b[0m\u001b[39m \u001b[0m\u001b[32m'tidy3d.components.monitor.FieldMonitor'\u001b[0m\u001b[1;34m>\u001b[0m\u001b[34m \u001b[0m\u001b[34m──────────────────────\u001b[0m\u001b[34m─╮\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[36m:class:`Monitor` that records electromagnetic fields in the frequency domain.\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m╭────────────────────────────────────────────────────────────────────────────────────────────╮\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1;35mFieldMonitor\u001b[0m\u001b[1m(\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'FieldMonitor'\u001b[0m, \u001b[32m│\u001b[0m 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\u001b[0m\u001b[33mapodization\u001b[0m=\u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ │ \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mfields\u001b[0m=\u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33minterval_space\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[2;32m│ \u001b[0m\u001b[33mcolocate\u001b[0m=\u001b[3;91mFalse\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m│\u001b[0m \u001b[1m)\u001b[0m \u001b[32m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[32m╰────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mapodization\u001b[0m = \u001b[1;35mApodizationSpec\u001b[0m\u001b[1m(\u001b[0m\u001b[33mstart\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mend\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mwidth\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[33mtype\u001b[0m=\u001b[32m'ApodizationSpec'\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mbounding_box\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m20.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mbounds\u001b[0m = \u001b[1m(\u001b[0m\u001b[1m(\u001b[0m\u001b[1;36m-10.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m-10.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[1m(\u001b[0m\u001b[1;36m10.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m10.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mcenter\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mcolocate\u001b[0m = \u001b[3;91mFalse\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mfields\u001b[0m = \u001b[1m(\u001b[0m\u001b[32m'Ex'\u001b[0m, \u001b[32m'Ey'\u001b[0m, \u001b[32m'Ez'\u001b[0m, \u001b[32m'Hx'\u001b[0m, \u001b[32m'Hy'\u001b[0m, \u001b[32m'Hz'\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mfreqs\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m200000000000000.0\u001b[0m,\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mgeometry\u001b[0m = \u001b[1;35mBox\u001b[0m\u001b[1m(\u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'Box'\u001b[0m, \u001b[33mcenter\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m0.0\u001b[0m\u001b[1m)\u001b[0m, \u001b[33msize\u001b[0m=\u001b[1m(\u001b[0m\u001b[1;36m20.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m20.0\u001b[0m\u001b[1m)\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33minterval_space\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m, \u001b[1;36m1\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mname\u001b[0m = \u001b[32m'field2'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mplot_params\u001b[0m = \u001b[1;35mPlotParams\u001b[0m\u001b[1m(\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33malpha\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.4\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33medgecolor\u001b[0m=\u001b[32m'orange'\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mfacecolor\u001b[0m=\u001b[32m'orange'\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mfill\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mhatch\u001b[0m=\u001b[3;35mNone\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mlinewidth\u001b[0m=\u001b[1;36m3\u001b[0m\u001b[1;36m.0\u001b[0m, \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[33mtype\u001b[0m=\u001b[32m'PlotParams'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33msize\u001b[0m = \u001b[1m(\u001b[0m\u001b[1;36m20.0\u001b[0m, \u001b[1;36m0.0\u001b[0m, \u001b[1;36m20.0\u001b[0m\u001b[1m)\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mtype\u001b[0m = \u001b[32m'FieldMonitor'\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m│\u001b[0m \u001b[3;33mzero_dims\u001b[0m = \u001b[1m[\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1m]\u001b[0m \u001b[34m│\u001b[0m\n", "\u001b[34m╰────────────────────────────────────────────────────────────────────────────────────────────────╯\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for m in sim.monitors:\n", " m.help()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Visualization functions\n", "\n", "We can now use the some in-built plotting functions to make sure that we have set up the simulation as we desire.\n", "\n", "First, let's take a look at the source time dependence." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.094768Z", "iopub.status.busy": "2023-02-03T06:00:27.094682Z", "iopub.status.idle": "2023-02-03T06:00:27.199540Z", "shell.execute_reply": "2023-02-03T06:00:27.199286Z" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Visualize source\n", "psource.source_time.plot(np.linspace(0, run_time, 1001))\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now let's visualize the simulation. \n", "\n", "For this, we will plot three cross sections at `z=0.75`, `y=0`, and `x=0`, respectively. \n", "\n", "The relative permittivity of objects is plotted in greyscale.\n", "\n", "By default, sources are overlayed in green, monitors in yellow, and PML boundaries in grey." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.200958Z", "iopub.status.busy": "2023-02-03T06:00:27.200862Z", "iopub.status.idle": "2023-02-03T06:00:27.535781Z", "shell.execute_reply": "2023-02-03T06:00:27.535461Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
[00:00:27] INFO     Auto meshing using wavelength 1.4990 defined from sources.                     grid_spec.py:510\n",
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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1, 3, figsize=(13, 4))\n", "sim.plot_eps(z=0.75, freq=freq0, ax=ax[0])\n", "sim.plot_eps(y=0.01, freq=freq0, ax=ax[1])\n", "sim.plot_eps(x=0, freq=freq0, ax=ax[2])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, we can also plot the structures with a fake color based on the material they are made of." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.537360Z", "iopub.status.busy": "2023-02-03T06:00:27.537236Z", "iopub.status.idle": "2023-02-03T06:00:27.699159Z", "shell.execute_reply": "2023-02-03T06:00:27.698898Z" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(1, 3, figsize=(12, 3))\n", "sim.plot(z=0.75, ax=ax[0])\n", "sim.plot(y=0.01, ax=ax[1])\n", "sim.plot(x=0, ax=ax[2])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Running through the web API\n", "\n", "Now that the simulation is constructed, we can run it using the [web](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/api.html#submitting-simulations) API of ``Tidy3D``. First, we submit the project. Note that we can give it a custom name." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2023-02-03T06:00:27.700729Z", "iopub.status.busy": "2023-02-03T06:00:27.700631Z", "iopub.status.idle": "2023-02-03T06:00:29.378983Z", "shell.execute_reply": "2023-02-03T06:00:29.378446Z" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "
[00:00:28] INFO     Created task 'Simulation' with task_id '8a74f7b0-d7da-45fa-94f9-76aa43c04e85'.    webapi.py:120\n",
       "
\n" ], "text/plain": [ "\u001b[2;36m[00:00:28]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO \u001b[0m Created task \u001b[32m'Simulation'\u001b[0m with task_id \u001b[32m'8a74f7b0-d7da-45fa-94f9-76aa43c04e85'\u001b[0m. \u001b]8;id=95646;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=345180;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#120\u001b\\\u001b[2m120\u001b[0m\u001b]8;;\u001b\\\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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      ],
      "text/plain": [
       "\u001b[?25l"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "04d4e93e187f4912be146dd1b1f95eb1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n",
       "\u001b[?25h"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "task_id = web.upload(sim, task_name=\"Simulation\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The task is still in draft status and will not run until we call the start function. Before that, we may want to check the estimated cost of the task."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:29.394499Z",
     "iopub.status.busy": "2023-02-03T06:00:29.394382Z",
     "iopub.status.idle": "2023-02-03T06:00:29.706500Z",
     "shell.execute_reply": "2023-02-03T06:00:29.705753Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max flex unit cost:  0.025\n"
     ]
    }
   ],
   "source": [
    "print(\"Max flex unit cost: \", web.estimate_cost(task_id))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now start the task, and if we want to, continously monitor its status, and wait until the run is successful. The [monitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.web.webapi.monitor.html#tidy3d.web.webapi.monitor) function will keep running until either a `'success'` or `'error'` status is returned."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:29.711233Z",
     "iopub.status.busy": "2023-02-03T06:00:29.710881Z",
     "iopub.status.idle": "2023-02-03T06:00:51.828282Z",
     "shell.execute_reply": "2023-02-03T06:00:51.827489Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
[00:00:30] INFO     Maximum FlexUnit cost: 0.025                                                      webapi.py:253\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[00:00:30]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Maximum FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                      \u001b]8;id=397819;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=77844;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#253\u001b\\\u001b[2m253\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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           INFO     status = queued                                                                   webapi.py:262\n",
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = queued                                                                   \u001b]8;id=496373;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=580684;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#262\u001b\\\u001b[2m262\u001b[0m\u001b]8;;\u001b\\\n"
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       "model_id": "3c08e5a547ef414a879ca3634cd838e7",
       "version_major": 2,
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       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[00:00:33] INFO     status = preprocess                                                               webapi.py:274\n",
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       "\u001b[2;36m[00:00:33]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = preprocess                                                               \u001b]8;id=891971;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=59948;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#274\u001b\\\u001b[2m274\u001b[0m\u001b]8;;\u001b\\\n"
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     },
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    },
    {
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[00:00:36] INFO     starting up solver                                                                webapi.py:278\n",
       "
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      ],
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       "\u001b[2;36m[00:00:36]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m starting up solver                                                                \u001b]8;id=230174;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=446683;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#278\u001b\\\u001b[2m278\u001b[0m\u001b]8;;\u001b\\\n"
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[00:00:45] INFO     running solver                                                                    webapi.py:284\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[00:00:45]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m running solver                                                                    \u001b]8;id=491791;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=779599;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#284\u001b\\\u001b[2m284\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
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     },
     "metadata": {},
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    },
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       "model_id": "48adc12cfa324cde81417b681d79d945",
       "version_major": 2,
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      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[00:00:49] INFO     early shutoff detected, exiting.                                                  webapi.py:295\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[00:00:49]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m early shutoff detected, exiting.                                                  \u001b]8;id=267855;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=460403;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#295\u001b\\\u001b[2m295\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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     "metadata": {},
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    {
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           INFO     status = postprocess                                                              webapi.py:301\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = postprocess                                                              \u001b]8;id=354905;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=662935;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#301\u001b\\\u001b[2m301\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
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     },
     "metadata": {},
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    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "97592eb75d744f868dd19beb4f20d399",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[00:00:51] INFO     status = success                                                                  webapi.py:307\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[00:00:51]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m status = success                                                                  \u001b]8;id=141563;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=849000;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#307\u001b\\\u001b[2m307\u001b[0m\u001b]8;;\u001b\\\n"
      ]
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    },
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       "\u001b[?25h\r",
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
           INFO     Billed FlexUnit cost: 0.025                                                       webapi.py:311\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Billed FlexUnit cost: \u001b[1;36m0.025\u001b[0m                                                       \u001b]8;id=31749;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=656290;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#311\u001b\\\u001b[2m311\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "web.start(task_id)\n",
    "web.monitor(task_id)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loading and analyzing data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After a successful run, we can download the results and load them into our simulation model. We use the `download_results` function from our web API, which downloads a single `hdf5` file containing all the monitor data, a log file, and a `json` file defining the original simulation (same as what you'll get if you run `sim.to_json()` on the current object). Optionally, you can provide a folder in which to store the files. In the example below, the results are stored in the `data/` folder. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:52.037061Z",
     "iopub.status.busy": "2023-02-03T06:00:52.036989Z",
     "iopub.status.idle": "2023-02-03T06:00:54.193542Z",
     "shell.execute_reply": "2023-02-03T06:00:54.193211Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
           INFO     downloading file \"output/monitor_data.hdf5\" to \"data/sim_data.hdf5\"               webapi.py:593\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m downloading file \u001b[32m\"output/monitor_data.hdf5\"\u001b[0m to \u001b[32m\"data/sim_data.hdf5\"\u001b[0m               \u001b]8;id=609452;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=169514;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#593\u001b\\\u001b[2m593\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      ],
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     },
     "metadata": {},
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    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7443c3a77f364b0bb815a031ce9998f9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
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       "
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      ],
      "text/plain": [
       "\n",
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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "
[00:00:54] INFO     loading SimulationData from data/sim_data.hdf5                                    webapi.py:415\n",
       "
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      ],
      "text/plain": [
       "\u001b[2;36m[00:00:54]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m loading SimulationData from data/sim_data.hdf5                                    \u001b]8;id=21598;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py\u001b\\\u001b[2mwebapi.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=486988;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/web/webapi.py#415\u001b\\\u001b[2m415\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulation domain Nx, Ny, Nz: [156, 157, 104]\n",
      "Applied symmetries: (0, 0, 0)\n",
      "Number of computational grid points: 2.6629e+06.\n",
      "Using subpixel averaging: True\n",
      "Number of time steps: 3.4930e+03\n",
      "Automatic shutoff factor: 1.00e-05\n",
      "Time step (s): 5.7275e-17\n",
      "\n",
      "\n",
      "Compute source modes time (s):     0.1773\n",
      "Compute monitor modes time (s):    0.0023\n",
      "Rest of setup time (s):            2.2910\n",
      "\n",
      "Running solver for 3493 time steps...\n",
      "- Time step    139 / time 7.96e-15s (  4 % done), field decay: 1.00e+00\n",
      "- Time step    279 / time 1.60e-14s (  8 % done), field decay: 1.00e+00\n",
      "- Time step    419 / time 2.40e-14s ( 12 % done), field decay: 1.00e+00\n",
      "- Time step    558 / time 3.20e-14s ( 16 % done), field decay: 1.00e+00\n",
      "- Time step    698 / time 4.00e-14s ( 20 % done), field decay: 1.00e+00\n",
      "- Time step    838 / time 4.80e-14s ( 24 % done), field decay: 1.00e+00\n",
      "- Time step    978 / time 5.60e-14s ( 28 % done), field decay: 1.00e+00\n",
      "- Time step   1117 / time 6.40e-14s ( 32 % done), field decay: 1.00e+00\n",
      "- Time step   1257 / time 7.20e-14s ( 36 % done), field decay: 1.00e+00\n",
      "- Time step   1389 / time 7.96e-14s ( 39 % done), field decay: 1.00e+00\n",
      "- Time step   1397 / time 8.00e-14s ( 40 % done), field decay: 1.00e+00\n",
      "- Time step   1536 / time 8.80e-14s ( 44 % done), field decay: 1.00e+00\n",
      "- Time step   1676 / time 9.60e-14s ( 48 % done), field decay: 8.05e-01\n",
      "- Time step   1816 / time 1.04e-13s ( 52 % done), field decay: 3.46e-01\n",
      "- Time step   1956 / time 1.12e-13s ( 56 % done), field decay: 1.51e-01\n",
      "- Time step   2095 / time 1.20e-13s ( 60 % done), field decay: 5.29e-02\n",
      "- Time step   2235 / time 1.28e-13s ( 64 % done), field decay: 1.21e-02\n",
      "- Time step   2375 / time 1.36e-13s ( 68 % done), field decay: 2.31e-03\n",
      "- Time step   2514 / time 1.44e-13s ( 72 % done), field decay: 4.89e-04\n",
      "- Time step   2654 / time 1.52e-13s ( 76 % done), field decay: 1.11e-04\n",
      "- Time step   2794 / time 1.60e-13s ( 80 % done), field decay: 2.39e-05\n",
      "- Time step   2934 / time 1.68e-13s ( 84 % done), field decay: 4.75e-06\n",
      "Field decay smaller than shutoff factor, exiting solver.\n",
      "\n",
      "Solver time (s):                   5.0762\n",
      "\n"
     ]
    }
   ],
   "source": [
    "sim_data = web.load(task_id, path=\"data/sim_data.hdf5\")\n",
    "\n",
    "# Show the output of the log file\n",
    "print(sim_data.log)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualization functions\n",
    "\n",
    "Finally, we can now use the in-built visualization tools to examine the results. Below, we plot the `y`-component of the field recorded by the two frequency monitors (this is the dominant component since the source is `y`-polarized)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:54.206039Z",
     "iopub.status.busy": "2023-02-03T06:00:54.205956Z",
     "iopub.status.idle": "2023-02-03T06:00:54.615123Z",
     "shell.execute_reply": "2023-02-03T06:00:54.614849Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "
           INFO     Auto meshing using wavelength 1.4990 defined from sources.                     grid_spec.py:510\n",
       "
\n"
      ],
      "text/plain": [
       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Auto meshing using wavelength \u001b[1;36m1.4990\u001b[0m defined from sources.                     \u001b]8;id=121952;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py\u001b\\\u001b[2mgrid_spec.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=632960;file:///Users/twhughes/Documents/Flexcompute/tidy3d-docs/tidy3d/tidy3d/components/grid/grid_spec.py#510\u001b\\\u001b[2m510\u001b[0m\u001b]8;;\u001b\\\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       ""
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 2, figsize=(10, 4))\n",
    "sim_data.plot_field(\"field1\", \"Ey\", z=-1.0, ax=ax[0], val=\"real\")\n",
    "sim_data.plot_field(\"field2\", \"Ey\", ax=ax[1], val=\"real\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monitor data\n",
    "The raw field data can be accessed through indexing by monitor name directly.\n",
    "\n",
    "For plenty of discussion on accessing and manipulating data, refer to the [data visualization tutorial](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/notebooks/VizData.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:54.616600Z",
     "iopub.status.busy": "2023-02-03T06:00:54.616493Z",
     "iopub.status.idle": "2023-02-03T06:00:54.628376Z",
     "shell.execute_reply": "2023-02-03T06:00:54.628139Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "
<xarray.ScalarFieldDataArray (x: 158, y: 159, z: 1, f: 1)>\n",
       "array([[[[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 9.8186092e-07+4.0431851e-07j]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 9.9795454e-07+1.7111465e-07j]],\n",
       "\n",
       "        [[ 1.2159646e-07+6.0561064e-08j]],\n",
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       "\n",
       "       [[[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 9.8186092e-07+4.0431851e-07j]],\n",
       "...\n",
       "        [[-1.1717159e-07+2.6605029e-08j]],\n",
       "\n",
       "        [[ 8.6237844e-09-7.4280364e-09j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]]],\n",
       "\n",
       "\n",
       "       [[[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[-8.3378872e-08+3.6394130e-08j]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[-1.1717159e-07+2.6605029e-08j]],\n",
       "\n",
       "        [[ 8.6237844e-09-7.4280364e-09j]],\n",
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       "        [[ 0.0000000e+00+0.0000000e+00j]]]], dtype=complex64)\n",
       "Coordinates:\n",
       "  * x        (x) float64 -2.379 -2.348 -2.318 -2.288 ... 2.288 2.318 2.348 2.379\n",
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       "  * f        (f) float64 2e+14\n",
       "Attributes:\n",
       "    long_name:  field value
"
      ],
      "text/plain": [
       "\n",
       "array([[[[ 0.0000000e+00+0.0000000e+00j]],\n",
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       "\n",
       "        [[ 9.8186092e-07+4.0431851e-07j]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 9.9795454e-07+1.7111465e-07j]],\n",
       "\n",
       "        [[ 1.2159646e-07+6.0561064e-08j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]]],\n",
       "\n",
       "\n",
       "       [[[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]],\n",
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       "...\n",
       "        [[-1.1717159e-07+2.6605029e-08j]],\n",
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       "        [[ 0.0000000e+00+0.0000000e+00j]]],\n",
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       "\n",
       "       [[[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]],\n",
       "\n",
       "        [[-8.3378872e-08+3.6394130e-08j]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[-1.1717159e-07+2.6605029e-08j]],\n",
       "\n",
       "        [[ 8.6237844e-09-7.4280364e-09j]],\n",
       "\n",
       "        [[ 0.0000000e+00+0.0000000e+00j]]]], dtype=complex64)\n",
       "Coordinates:\n",
       "  * x        (x) float64 -2.379 -2.348 -2.318 -2.288 ... 2.288 2.318 2.348 2.379\n",
       "  * y        (y) float64 -2.39 -2.36 -2.33 -2.3 ... 2.266 2.295 2.325 2.354\n",
       "  * z        (z) float64 -1.0\n",
       "  * f        (f) float64 2e+14\n",
       "Attributes:\n",
       "    long_name:  field value"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mon1_data = sim_data[\"field1\"]\n",
    "mon1_data.Ex\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:54.629704Z",
     "iopub.status.busy": "2023-02-03T06:00:54.629619Z",
     "iopub.status.idle": "2023-02-03T06:00:54.736210Z",
     "shell.execute_reply": "2023-02-03T06:00:54.735964Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = mon1_data.Ez.real.plot()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use this raw data for example to also plot the time-domain fields recorded in the [FieldTimeMonitor](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.FieldMonitor.html), which look largely like a delayed version of the source input, indicating that no resonant features were excited."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:54.737691Z",
     "iopub.status.busy": "2023-02-03T06:00:54.737591Z",
     "iopub.status.idle": "2023-02-03T06:00:54.813559Z",
     "shell.execute_reply": "2023-02-03T06:00:54.813331Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_data = sim_data[\"field_time\"]\n",
    "fig, ax = plt.subplots(1)\n",
    "time_data.Ey.plot()\n",
    "ax.set_ylabel(\"$E_y(t)$ [V/m]\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Permittivity data\n",
    "\n",
    "We can also query the relative permittivity in the simulation within a volume parameterized by a `td.Box`. The method `Simulation.epsilon(box, coord_key)` returns the permittivity within the specified volume.\n",
    "\n",
    "The `coord_key` specifies at what locations in the yee cell to evaluate the permittivity at (eg. `'centers'`, `'Ey'`, `'Hz'`, etc.)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:54.815032Z",
     "iopub.status.busy": "2023-02-03T06:00:54.814938Z",
     "iopub.status.idle": "2023-02-03T06:00:55.235266Z",
     "shell.execute_reply": "2023-02-03T06:00:55.234893Z"
    }
   },
   "outputs": [],
   "source": [
    "volume = td.Box(center=(0, 0, 0.75), size=(5, 5, 0))\n",
    "\n",
    "# at Yee cell centers\n",
    "eps_centers = sim.epsilon(box=volume, coord_key=\"centers\")\n",
    "\n",
    "# at Ex locations in the yee cell\n",
    "eps_Ex = sim.epsilon(box=volume, coord_key=\"Ex\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Return an xarray DataArray containing the complex-valued permittivity values at the Yee cell centers and the \"Ex\" within the [box](https://docs.flexcompute.com/projects/tidy3d/en/v1.9.0rc2/_autosummary/tidy3d.Box.html).\n",
    "\n",
    "We can then plot or post-process this data as we wish."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-02-03T06:00:55.236735Z",
     "iopub.status.busy": "2023-02-03T06:00:55.236656Z",
     "iopub.status.idle": "2023-02-03T06:00:55.458344Z",
     "shell.execute_reply": "2023-02-03T06:00:55.458077Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(1, 2, tight_layout=True, figsize=(10, 4))\n",
    "\n",
    "eps_centers.real.plot(x=\"x\", y=\"y\", cmap=\"Greys\", ax=ax1)\n",
    "eps_Ex.real.plot(x=\"x\", y=\"y\", cmap=\"Greys\", ax=ax2)\n",
    "ax1.set_title(\"epsilon_r at centers\")\n",
    "ax2.set_title(\"epsilon_r at Ex locations\")\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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        {
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