{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7570717c",
   "metadata": {},
   "source": [
    "(sec-tutorial-schedulegettable)=\n",
    "\n",
    "# Tutorial: ScheduleGettable\n",
    "\n",
    "```{seealso}\n",
    "The complete source code of this tutorial can be found in\n",
    "\n",
    "{nb-download}`ScheduleGettable.ipynb`\n",
    "```\n",
    "\n",
    "This tutorial covers the {class}`~quantify_scheduler.gettables.ScheduleGettable` in-depth. If you're looking for more information on how to set up an experiment in general, please see {ref}`sec-tutorial-experiment`.\n",
    "\n",
    "The {class}`~quantify_scheduler.gettables.ScheduleGettable` forms the top-level interface to {mod}`quantify_scheduler`. Under the hood, it uses `quantify-scheduler` modules to compile {ref}`Schedules <sec-user-guide-creating-a-schedule>`, run them on your hardware and retrieve measurement data from the hardware. As the {class}`~quantify_scheduler.gettables.ScheduleGettable` uses functions that return {class}`~quantify_scheduler.schedules.schedule.Schedule`s, you can dynamically set function parameters during experiments.\n",
    "\n",
    "For those familiar with [quantify-core](https://quantify-os.org/docs/quantify-core), the interface of the {class}`~quantify_scheduler.gettables.ScheduleGettable` is also designed to be used as a [gettable](https://quantify-os.org/docs/quantify-core/dev/user/concepts.html#settables-and-gettables) for [MeasurementControl](https://quantify-os.org/docs/quantify-core/dev/user/concepts.html#measurement-control). This is convenient for large, possibly multi-dimensional measurement loops, as is demonstrated in {ref}`2D (and ND) measurement loops`.\n",
    "\n",
    "Two things are always required when using a {class}`~quantify_scheduler.gettables.ScheduleGettable`: a {ref}`QuantumDevice <sec-user-guide-quantum-device-elements>` and a function that returns a {class}`~quantify_scheduler.schedules.schedule.Schedule`. We will set these up in a few example scenarios below and show how to use the {class}`~quantify_scheduler.gettables.ScheduleGettable`. More commonly used schedule functions are also included in `quantify-scheduler` out of the box. You can find them in {mod}`~.quantify_scheduler.schedules.spectroscopy_schedules`, {mod}`~.quantify_scheduler.schedules.timedomain_schedules` and {mod}`~.quantify_scheduler.schedules.trace_schedules`.\n",
    "\n",
    "(sec-schedulegettable-1dsweep-usage)=\n",
    "\n",
    "## 1D iterative measurement loop\n",
    "\n",
    "\n",
    "```{admonition} Setup and hardware configuration\n",
    "The device setup and hardware configuration for this tutorial can be viewed in the collapsed code cells. In places where you would communicate with actual hardware, dummy objects have been used. If you want to learn more about how to set up the {class}`~quantify_scheduler.device_under_test.quantum_device.QuantumDevice` and hardware configuration, please see our other tutorials, in particular {ref}`sec-tutorial-experiment` and {ref}`sec-tutorial-compiling`.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9e7b2acc",
   "metadata": {
    "mystnb": {
     "code_prompt_show": "Set up the quantum device, dummy hardware and hardware configuration"
    },
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data will be saved in:\n",
      "/root/quantify-data\n"
     ]
    }
   ],
   "source": [
    "from qblox_instruments import Cluster, ClusterType\n",
    "from quantify_core.data import handling as dh\n",
    "\n",
    "from quantify_scheduler import BasicTransmonElement, InstrumentCoordinator, QuantumDevice\n",
    "from quantify_scheduler.qblox import ClusterComponent, start_dummy_cluster_armed_sequencers\n",
    "\n",
    "# First, don't forget to set the data directory!\n",
    "dh.set_datadir()  # change me!\n",
    "\n",
    "# We define a single transmon qubit as an element (BasicTransmonElement) of the\n",
    "# QuantumDevice, and populate the parameters with some reasonable values.\n",
    "\n",
    "# Device parameters\n",
    "ACQ_DELAY = 100e-9\n",
    "FREQ_01 = 4e9\n",
    "READOUT_AMP = 0.1\n",
    "READOUT_FREQ = 4.3e9\n",
    "PI_PULSE_AMP = 0.15\n",
    "LO_FREQ_QUBIT = 3.9e9\n",
    "LO_FREQ_READOUT = 4.5e9\n",
    "\n",
    "single_qubit_device = QuantumDevice(\"single_qubit_device\")\n",
    "\n",
    "q0 = BasicTransmonElement(\"q0\")\n",
    "single_qubit_device.add_element(q0)\n",
    "\n",
    "# Assign device parameters to transmon element\n",
    "q0.measure.pulse_amp(READOUT_AMP)\n",
    "q0.clock_freqs.readout(READOUT_FREQ)\n",
    "q0.clock_freqs.f01(FREQ_01)\n",
    "q0.measure.acq_delay(ACQ_DELAY)\n",
    "q0.rxy.amp180(PI_PULSE_AMP)\n",
    "\n",
    "# For this example, we will set up a Qblox cluster hardware setup with two modules: a\n",
    "# QRM-RF and a QCM-RF.\n",
    "\n",
    "# Note: if you are connecting to an actual cluster, you would provide the\n",
    "# 'identifier' argument (the ip address, device name or serial number) instead\n",
    "# of the 'dummy_cfg' argument.\n",
    "cluster = Cluster(\n",
    "    \"cluster\",\n",
    "    dummy_cfg={\n",
    "        1: ClusterType.CLUSTER_QRM_RF,\n",
    "        2: ClusterType.CLUSTER_QCM_RF,\n",
    "    },\n",
    ")\n",
    "\n",
    "ic_cluster = ClusterComponent(cluster)\n",
    "\n",
    "# Temporarily fixing dummy cluster's deficiency.\n",
    "cluster.start_sequencer = lambda : start_dummy_cluster_armed_sequencers(ic_cluster)\n",
    "\n",
    "# We create an InstrumentCoordinator to control the cluster and add it to the\n",
    "# QuantumDevice.\n",
    "\n",
    "instrument_coordinator = InstrumentCoordinator(\"instrument_coordinator\")\n",
    "instrument_coordinator.add_component(ic_cluster)\n",
    "\n",
    "single_qubit_device.instr_instrument_coordinator(instrument_coordinator.name)\n",
    "\n",
    "# A basic hardware configuration will be used for the two cluster modules.\n",
    "\n",
    "hardware_cfg = {\n",
    "    \"version\": \"0.2\",\n",
    "    \"config_type\": \"quantify_scheduler.backends.qblox_backend.QbloxHardwareCompilationConfig\",\n",
    "    \"hardware_description\": {\n",
    "        f\"{cluster.name}\": {\n",
    "            \"instrument_type\": \"Cluster\",\n",
    "            \"modules\": {\n",
    "                \"1\": {\n",
    "                    \"instrument_type\": \"QRM_RF\"\n",
    "                },\n",
    "                \"2\": {\n",
    "                    \"instrument_type\": \"QCM_RF\"\n",
    "                }\n",
    "            },\n",
    "            \"ref\": \"internal\"\n",
    "        }\n",
    "    },\n",
    "    \"hardware_options\": {\n",
    "        \"modulation_frequencies\": {\n",
    "            \"q0:res-q0.ro\": {\n",
    "                \"lo_freq\": LO_FREQ_READOUT\n",
    "            },\n",
    "            \"q0:mw-q0.01\": {\n",
    "                \"lo_freq\": LO_FREQ_QUBIT\n",
    "            }\n",
    "        }\n",
    "    },\n",
    "    \"connectivity\": {\n",
    "        \"graph\": [\n",
    "            [f\"{cluster.name}.module1.complex_output_0\", \"q0:res\"],\n",
    "            [f\"{cluster.name}.module1.complex_input_0\", \"q0:res\"],\n",
    "            [f\"{cluster.name}.module2.complex_output_0\", \"q0:mw\"]\n",
    "        ]\n",
    "    }\n",
    "}\n",
    "\n",
    "\n",
    "# This hardware configuration should also be added to the quantum device.\n",
    "single_qubit_device.hardware_config(hardware_cfg)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "80225ea1",
   "metadata": {},
   "source": [
    "For this experiment, we have set up a basic {class}`~quantify_scheduler.device_under_test.quantum_device.QuantumDevice` called `single_qubit_device`, representing a single transmon qubit.\n",
    "\n",
    "We'll now define the schedule function. A valid schedule function must contain a `repetitions` (integer) parameter (see {ref}`Repetitions`), and can contain any number of additional parameters. It must return a {class}`~quantify_scheduler.schedules.schedule.Schedule` object.\n",
    "\n",
    "The schedule function can be parameterized to loop over different values. The parameters can be scalars or arrays. For example, the schedule function defined below takes an array of values for the parameter `times`. This is called a _batched_ measurement, as will be explained further in this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "da634faf",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_scheduler import Schedule\n",
    "from quantify_scheduler.operations import Measure, Reset, X\n",
    "\n",
    "def t1_sched(times, repetitions=1):\n",
    "    schedule = Schedule(\"T1\", repetitions)\n",
    "    for i, tau in enumerate(times):\n",
    "        schedule.add(Reset(\"q0\"), label=f\"Reset {i}\")\n",
    "        schedule.add(X(\"q0\"), label=f\"pi {i}\")\n",
    "        # Measure tau seconds after the start of the X gate\n",
    "        schedule.add(\n",
    "            Measure(\"q0\", acq_index=i),\n",
    "            ref_pt=\"start\",\n",
    "            rel_time=tau,\n",
    "            label=f\"Measurement {i}\",\n",
    "        )\n",
    "    return schedule"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19cf4237",
   "metadata": {},
   "source": [
    "Now, let's create the {class}`~quantify_scheduler.gettables.ScheduleGettable`. The {class}`~quantify_scheduler.gettables.ScheduleGettable` provides a convenient way to compile and execute schedules in just a few lines of code. The parameters can be set directly, with arrays and scalars, or through QCoDeS parameters, as shown below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7cd5d5f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "from qcodes.instrument.parameter import ManualParameter\n",
    "\n",
    "from quantify_scheduler import ScheduleGettable\n",
    "\n",
    "# The points we want to measure.\n",
    "times = np.linspace(start=1.6e-7, stop=4.976e-5, num=125)\n",
    "\n",
    "# As QCoDeS parameter:\n",
    "time = ManualParameter(\"sample\", label=\"Sample time\", unit=\"s\")\n",
    "# Set the parameter. This can be done even after defining the gettable!\n",
    "time(times)\n",
    "\n",
    "# Or as array:\n",
    "time = times\n",
    "\n",
    "# Configure the gettable\n",
    "gettable = ScheduleGettable(\n",
    "    quantum_device=single_qubit_device,\n",
    "    schedule_function=t1_sched,\n",
    "    schedule_kwargs={\"times\": time},\n",
    "    batched=True\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "099138dd",
   "metadata": {},
   "source": [
    "Note that `batched=True` here. This means we are doing a _batched_ measurement, which simply means that we tell the {class}`~quantify_scheduler.gettables.ScheduleGettable` to expect an array of values in the acquisition result. In this case, our schedule function creates one schedule for an array of times, and it includes an acquisition (the {class}`~quantify_scheduler.operations.gate_library.Measure` operation) for each point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6ab320de",
   "metadata": {
    "mystnb": {
     "code_prompt_show": "Provide the dummy hardware with acquisition data"
    },
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "import xarray\n",
    "\n",
    "from quantify_scheduler.waveforms import soft_square\n",
    "\n",
    "from qblox_instruments import DummyScopeAcquisitionData, DummyBinnedAcquisitionData\n",
    "\n",
    "\n",
    "soft_sq_samples = round(q0.measure.integration_time() * 1e9)\n",
    "soft_sq_times = np.arange(soft_sq_samples)\n",
    "soft_sq = soft_square(t=soft_sq_times, amp=0.5)\n",
    "scope_data_real = np.zeros(16384)  # Scope trace acquires 16384 points\n",
    "scope_data_real[:soft_sq_samples] = soft_sq\n",
    "scope_data_real += np.random.randn(16384) / 500  # add some \"noise\"\n",
    "\n",
    "# Create dummy scope data with the soft square pulse on the I path and noise on\n",
    "# the Q path\n",
    "scope_data = list(zip(scope_data_real, np.random.randn(16384) / 500))\n",
    "\n",
    "dummy_scope_acquisition_data = DummyScopeAcquisitionData(\n",
    "        data=scope_data, out_of_range=(False, False), avg_cnt=(0, 0)\n",
    "    )\n",
    "\n",
    "ic_cluster.instrument.set_dummy_scope_acquisition_data(\n",
    "    slot_idx=1, sequencer=None, data=dummy_scope_acquisition_data\n",
    ")\n",
    "\n",
    "\n",
    "# Dataset with T1 experiment data\n",
    "example_dataset = xarray.open_dataset(\"../examples/dataset.hdf5\")\n",
    "\n",
    "def get_dummy_binned_acquisition_data(real: float, imag: float):\n",
    "    return DummyBinnedAcquisitionData(data=(real, imag), thres=0, avg_cnt=0)\n",
    "\n",
    "ic_cluster.instrument.set_dummy_binned_acquisition_data(\n",
    "    slot_idx=1,\n",
    "    sequencer=0,\n",
    "    acq_index_name=\"0\",\n",
    "    data=[\n",
    "        get_dummy_binned_acquisition_data(float(re) * 1024, float(im) * 1024)\n",
    "        for re, im in zip(example_dataset[\"y0\"], example_dataset[\"y1\"])\n",
    "    ],\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "057e7589",
   "metadata": {},
   "source": [
    "Let's now run the experiment and retrieve the acquisitions using the {meth}`~quantify_scheduler.gettables.ScheduleGettable.get` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4183c9ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "data = gettable.get()\n",
    "\n",
    "plt.plot(times, data[0], '.', label=\"real\")\n",
    "plt.plot(times, data[1], '.', label=\"imaginary\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Idle time (s)\")\n",
    "plt.ylabel(\"Voltage (V)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13056e77",
   "metadata": {},
   "source": [
    "Note that the data used here is the same as in {ref}`sec-tutorial-experiment`. The example dataset can be downloaded {download}`here <../examples/dataset.hdf5>`.\n",
    "\n",
    "As we defined 125 points in our `times` array which were measured in 125 different `acq_index`es, the acquisition result also contains 125 _I_ values (in `data[0][:]`) and 125 _Q_ values (in `data[1][:]`). The general format of the data returned by the {class}`~quantify_scheduler.gettables.ScheduleGettable` is also explained in the {ref}`user guide <sec-user-guide-acquisition-data-schedulegettable>`.\n",
    "\n",
    "## Trace measurement\n",
    "\n",
    "The previous experiment's acquisition results had one data point for each acquisition in the schedule. For a trace measurement, the data format is slightly different. To illustrate this, let us set up an experiment with a trace measurement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cf64df1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_scheduler.operations import IdlePulse, SoftSquarePulse\n",
    "\n",
    "\n",
    "def trace_schedule(pulse_amp, acq_delay, port=\"q0:res\", clock=\"q0.ro\", repetitions=1):\n",
    "    schedule = Schedule(\"Trace a pulse\", repetitions=repetitions)\n",
    "\n",
    "    schedule.add(\n",
    "        SoftSquarePulse(\n",
    "            duration=q0.measure.integration_time(),\n",
    "            amp=pulse_amp,\n",
    "            port=port,\n",
    "            clock=clock,\n",
    "        ),\n",
    "        label=\"trace_pulse\",\n",
    "    )\n",
    "\n",
    "    # Add acq_delay to compensate for time-of-flight of the pulse\n",
    "    schedule.add(\n",
    "        Measure(q0.name, acq_protocol=\"Trace\"),\n",
    "        ref_pt=\"start\",\n",
    "        rel_time=acq_delay,\n",
    "        label=\"acquisition\"\n",
    "    )\n",
    "\n",
    "    return schedule"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae674709",
   "metadata": {},
   "source": [
    "Again, we define the gettable and run the experiment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9586179c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.9/site-packages/quantify_scheduler/backends/qblox/compiler_abc.py:703: RuntimeWarning: Operation is interrupting previous Pulse because it starts before the previous ends, offending operation: Pulse \"SquarePulse\" (t0=1.0000000000000001e-07, duration=3e-07)\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAjcAAAGwCAYAAABVdURTAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjkuNCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8ekN5oAAAACXBIWXMAAA9hAAAPYQGoP6dpAABYbElEQVR4nO3deVxU5f4H8M+Agiw6oiibgyCiqCAgCuK+UKZpWZakJeot85ZZSnWTFm27oqllKWVaLvUr4Vrq9ZZLiZqilogb7ooopIDiMiiSGHN+f4wzMnBmmAFmO3zerxcZz3nmnO88c+acL+c853lkgiAIICIiIpIIB2sHQERERFSfmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSlEbWDsDSVCoVLl26hKZNm0Imk1k7HCIiIjKCIAi4efMmfH194eBg+NpMg0tuLl26BIVCYe0wiIiIqBby8/PRpk0bg3UaXHLTtGlTAOrGadasmZWjISIiImOUlJRAoVBoz+OGNLjkRnMrqlmzZkxuiIiI7IwxXUrYoZiIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEdVCgLMOenGIUKMsMlpFlSLntpfbepPZ+yLY0uIkzierLlztzMGfTSQgC4CADkh8PAwAkrc2GqlJZfA9/s8VQoCxDbnEpAj3d4CN3qfZ7Q1GgLMPyjFx8nZFrsba3pLTMvFrvV/r2iZr2FbHl9bV/iX13pPJZkW2QCYIgWDsISyopKYFcLodSqeSs4BJl7AFYU8/NyRGl5RXa+ofzr2PriSK0btoEcZ29qiUNAPBZ+hms3pevsz7Zvf9U/kY5AFg3pRcAYN/5a4gOaIFwhQcAiG6npvdQuXzn6SvaE54MwNBQb2w+VgjVve0PD/PGpH7t0LpZkxrbo6btuTk5Iu/abchkMig8XFBaXqHTbgBE27ImBcoy7D9/DTKZDFFtPQyeRKt+Xpp/sy8qMWfjSVQ9kMkATB3cHoNDWiNc4VHtM6y8/sP513U+H7G4NGU3yu7Cw9UJUW3Vn2PlMoWHi7adKr+fmt6vvs9BU/+V1EPazxVQ71efjY0UXUfl/er23QrM3XRSu4+8OCAIvYM9kX1RqS0XSy4qJ1Oa15VXqLTJowzAmGgFerX31Gkfsc+n6r4wb8tJpGzPqfZZvf9oF9Hvwa/HC1F8qxzhbeRwcWpkcB81Zd8j+2PK+dsmkpuUlBTMmzcPhYWFCA8Px6JFixAdHS1ad+XKlZg4caJOmbOzM/766y+jtsXkRno0B7ey8r/x3R952H7yivZE1zuoBR4K9al20Kx88K4szLcZsi+V6JQN7NgKO06p1ykDqp1ETTWqmx/K7lZgY3ahTvmUAUF4JrYtlmfk4qtdudrtzRgagrA2cuw5W4zFlU4KpsYiAzCpbyAe7uqjk5RUvuIBAGOjFZg6OBgbDl9C8saTRq0XVWKpfPKresIH1IlF1fejaYPrt8uxel++dn1TBgTBv6UrZvyYXeu2D/VthmMFJah6tHOQAV18dD/z4NbuOHv5ls62ItrIcehPpcnbTbr32bk5OSItMx/fV0mIx0YrMLhTa5wrLsXF62VYtfeC9mrGY5F+WHvgYo3veWy0AvE9FMi7dhtfZ+TiUL7pcWqS8MN/3sDRiyVYs/9Pk9q6X7Andp0trta+VWNMzcyv9keBWN2pg4Ox8/QVvPFjdrXllfetkwUlSNmRo/sHBa8ESZZdJTdpaWlISEjAkiVLEBMTg4ULF2LNmjU4deoUWrduXa3+ypUr8corr+DUqVPaMplMBi8vL6O2x+RGGjR/0e49dw2p+/KqJSliurdtDrlLY1SoBPx2Rv+BmIjs34iu3ogObImubeTVrug01Nu39s6ukpuYmBj06NEDixcvBgCoVCooFApMnToVM2bMqFZ/5cqVmDZtGm7cuFGr7TG5sT9VbydUvrJBRGSswSGt0LRJY2w4fEmSfbOkzpTzt1U7FJeXlyMrKwtJSUnaMgcHB8TFxWHv3r16X3fr1i20bdsWKpUK3bp1w+zZs9GlSxfRunfu3MGdO3e0v5eUlIjWI9uk7/YREZGp0k9e0fldJQBv/JiN4pt38HhUGwDgFR2JsGpyU1xcjIqKimq3lLy8vHDypPi9/o4dO2L58uXo2rUrlEol5s+fj169euHYsWNo06ZNtfrJycl47733zBI/mY/mttOMtdm8fUREZjXvl9OY98tpbT82XtGxf3Y3zk1sbCwSEhIQERGB/v37Y+3atWjVqhW+/PJL0fpJSUlQKpXan/x8w53ZyPrmbzmJXsnbMHX1ISY2RGQxmsONSgDeXHuUY/DYMateufH09ISjoyOKiop0youKiuDt7W3UOho3bozIyEicPXtWdLmzszOcnZ3rHCuZT+U+NW+uy8b2KpeObV1ASxecv8qDIJGUVAgCss5fx/Bw3p6yR1a9cuPk5ISoqCikp6dry1QqFdLT0xEbG2vUOioqKpCdnQ0fHx9zhUlmlJaZh95ztmHssj8Qm7yt3hKb/sGeJtUf2LGV9pFmU0wZEIQdrw/CqG5+NdZt5+kqWl6b7Zqik7e7mbdQN+Z+/7U1pJMXPhwp3pfPloXU8fP2b+Fi1s8k3E9uxrXXr5dWH8Ss9Uc5krIdsvoIxYmJiRg/fjy6d++O6OhoLFy4EKWlpdqxbBISEuDn54fk5GQAwPvvv4+ePXuiffv2uHHjBubNm4cLFy7gueees+bboFooUJaZpbNw0tAQTO4fhLTMPJ2xUWQy4PFIP6w7eFG7zZHhvnhjWIh2ELLzxbex++wVfL4jR6fOxD4ByL9Whhtl5QAAD1cndKs0gNqC0RFIiG2LbScuw6mxAwJauqFbWw9cLvkL+89fR/cAD4QrPPDlzpz7g6cBeGNoCJq7Nsaba4+iQhDgAOCFAUHoE9wKAZ6u2tefLCzBmqyLou93ZIQPuge0gIerE/68UYaPNp1ChSDAUSbD7MdDEd/DX2e7MgDhCjkO5yu1bVN5HW08XHC7XAVXJwedf49cvKFdtwxAv+CW2Hnmaq2fWtPEB0D7/jVlId5NMfLzPXpvSzoAEKoMmFh1+ZgYf3z3R57o8ikDg+DfwlW7XRmARyu1QeXPtrGjA5J+zIaqSuz/eqgjurZpXq2dXJ0c8Njne0T3a834NesPXtJuNzrQA5nnr2vri41f9OHILhjcyQvf/X6h2rguABDq0xRDu/rg8W7qfoe952wz+L0a2LEVfjt9RaeOZrC+1x8KweH869XaX3av3T7fngNVlThlAPoGe2LXmWKd2IeFemPLsSLtvv3Gve/ml7/lIHmTbr9KR5kMj3fzFd3PHWTAGw+FwK+5C/53+BK2HC+qVqdP+5bYnXMVglA/41FprPr9Alb9foH9cOyM1R8FB4DFixdrB/GLiIjAZ599hpiYGADAgAEDEBAQgJUrVwIApk+fjrVr16KwsBAeHh6IiorChx9+iMjISKO2xUfBbUOBsgwf/nQcP1cZyK4uZADWT+mlHQFYs52s89chk0F7wtIkMQGergZH7K2pTm2JrdvYmFZknMdXGed0kqPJ/YOMir1qeW3eY9XXpGXm6SQm/3qoI/yau+BGWTlm/vdYtZPnByO7IMxPjtvlqhrff+V1Vx79WSwpElse38MfBcoyLEo/i9TMPNE2M7YNNPU0CUxN9cXapWub5nrbvvLvO09fqZbsVT6hGhOLvrar/P5rWk/V91C5TTWxAqj2Poz9vlVOuPUl4g4AnusXiIm9A/W+tnLSUTW2rPPXsXpfHnbnXNX7WZnCUSZDxoyBfJLKSuxqnBtLY3JjfVWvqNTG2BgFZJBh9b0B/MROAlJlzsSrPuPRd3Ks7boBGEwKxZbXFKM51WWb9RGvsW1j7jhqs/76/AOkQFmGXsnb6u1KzupJPREb1LKe1kamYHJjAJMb6xK73G2MIZ290LeDZ7VbBrZ2oidd/HzIFuj7g2psjALf/2HaE7RvDQtBFz85x8KxAiY3BjC5sQ717YEz1ebWMcaUgUF4fUiIGaIiooZCc8vsRlm5zh9JdbmSnCRyW5jMh8mNAUxuLC8tM090Arya6OtTQkRUnyonPgBw7koplu8+b9RrH43wxYyhIbyKYwFMbgxgcmNZpt7vHhnhi4m9A4zqtElEZA6mHrdkAOaM4pNU5mbK+dvuRigm+1GgLMOr/zlk9AFiQmxbLHwqEuEKD8QGtWRiQ0RW4SN3wZxRYUbXF6Ceo4pj4dgOJjdU7wqUZfj3z8cRm7wNe3KuGfWaoaHeePfRUDNHRkRknPge/tibNAgxgS2Mfs3EFZlMcGwEb0tRvTK1c15QKzd8PDpcZ2waIiJbkn6iEM+uyjK6PjsamwdvS5FVaEYcNqV/TfqrA5jYEJFNG9zJG3NHhRk9LUXyppOYt+VkzRXJbJjcUL0oUJbh7XXGT6Ugg/pJKCIiexDfwx/rp/SCzMgMJ2V7Dr7cmWPeoEgvJjdUZ2mZeYhN3oZ0Iye9lMnUTxawwzAR2ZNwhQfmPB4GRyMznOSNJ9kHx0rY54bqpEBZhtjkbUbVndgrAN0DPHRGGCYisjeakbcPXLiGeb+cNlg3JsADaf/sZaHIpI19bshitorMzivGQQY8378dHu7qy8SGiOyaj9wFsUEt8XhUmxrr/nH+Ot7971ELREWVMbmhWkvLzMM7/z1WYz0Z1LP2MqkhIinxkbtg7qgwONRwl2rl3gvsf2NhTG6oVgqUZZhh5JQK66f04sidRCRJ8T38sXvGILz9cCeD9eZuYv8bS2JyQ7WSW1xa4yPfMgBzR4XxUW8ikjQfuQse7upj8AqOSgCyzl+3XFANHJMbMlmBsgxXb92psR6v2BBRQ+Ejd0Hy44bHwnlp9UGMXfY7DuczyTG3RtYOgOzLlztzMGfTSRh6xk4ziRyv2BBRQxLfwx9uzo3w0vcH9dbZk3MVj6bswahuflgwOsJywTUwvHJDRvvytxwkbzSc2AwOaY09SYN4xYaIGqSoth5GjWT844GLvIJjRkxuyCgFyjLM2WR4OHEZgA8fC+VTUUTUYJkyo/h+9sExGyY3ZJQVGbk1diB+OMyHiQ0RNXjxPfzx3yk1D9zXzIU9Q8yFyQ3V6HD+dSzdlVtjvUn9Ai0QDRGR7QtXeNQ42ebrP2Tjy984/o05MLkhg9Iy8zAyZU+N9UZ182MHYiKiSuJ7+GNP0iB88GgXvXWSN53kAH9mwOSG9CpQliFpbXaNt6M+eLQLe/0TEYnwkbtgXGwAxkYr9NaZwwk26x2TG9Irt7gUqhoyGwcZENfZyzIBERHZqV7tPfUuEwCs/iOPCU49YnJDemX/qTS4nHNGEREZJ6qt4dv2n207i17J25CWmWehiKSNyQ2JMubRb45ATERkHB+5C57va/ihCwHAjB+zeQWnHjC5IVFzN5002NeGc0YREZlmYp/AGmcQF8A5qOoDkxuqZuLKfVh/6JLe5V+Pj+IVGyIiExkz/xQAyIwZ4pgMYnJDOuZtPontJ68YrOPq1NhC0RARSUt8D3+8P1L/o+EA8OcN3paqKyY3pFWgLEPKDsPjLTjIgABPVwtFREQkPR6uTgaXz+Wj4XXG5Ia0/vXDkRrrvDE0hE9HERHVQU1PTqkALEo/a5lgJIrJDQFQT7Gw60yxwTpTBgZhcr8gC0VERCRNPnKXGqdm+H5fHkcurgMmNwQAWLbznN5lMgBJQ0Pw+pAQywVERCRhmqkZFo+JRIh3U9E6HLm49pjcEAqUZfgpu1Dv8kVjIjG5P6/YEBHVJx+5C6ICPHCy8KbocgHAiozzFo1JKpjcEFZk6J/x20EGRAVwPBsiInPILS41uHzZrnM4nM9xb0zF5KaBK1CWYeku/cnNc33asQMxEZGZBHq6Gex7IwAY+fkeTstgIiY3DZyhvxpkACb2CbBYLEREDY2P3AVzRoUZrCMIwJtrj7L/jQmY3DRwgZ5uepfNGMbHvomIzC2+hz/+O6WXwToVgoDzxbctFJH9Y3JDopdE+dg3EZHlhCs8kDTU8BOprk48ZRuLLdXAvfh/WaITZPZp38risRARNWST+wdhcIj+Y++CX05bMBr7xuSmARuzbC8O5iurlXOKBSIi63h5cLDeZTvPFPPJKSMxuWmACpRleCX1APbmXBNdPizUh31tiIisIFzhgVHd/PQu33+eyY0xGlk7ALKstMw8zPgxW/RWlMakfoEWi4eIiHQtGB2Bnu1a4PUfsqst685xx4zCKzcNSIGyDElrDSc2gzq2QriCXx4iImvqEyze9+b3XPEr7qSLyU0DkltcCpWhzAbAvx83PN4CERGZn74xyJI3nmS/GyMwuWlAdtcw6zcAjqNARGQDDI1B9mjKHnz5G2cMN4TJTQNRoCzD5zsMfxkcZTI+JUVEZAN85C4YG63Quzx500nM23LSghHZFyY3DURucanBvjYOMmD246F8SoqIyEZMNfBYOACkbM/Blzt5BUcMk5sG4tu9F/Qu6xfsid0zBiG+h78FIyIiIkN85C6YMsDwSPFzN53knFMi+Ch4A3A4/zo2HS2sVt6jrQfeHt6JT0cREdmo1x8KwfHCEmw/eUV0uUpQ95XkVXddvHLTAOw7L/7o4EOh3kxsiIhs3IoJ0ZgQ21bv8t1nxROfhozJTQMQHdBCtPz67XILR0JERLXxYKi33mUp23N4a6oKJjcNwO/nxK/cfL6DXwgiInsQ6OkGmZ5lAoAsTsugg8mNxBUoyzBnk/jjgpp7tUREZNt85C6YM0r/IKsyfZlPA8XkRuKyLlzX+wg4Z/8mIrIf/Tq00nv15s8bvApfmU0kNykpKQgICECTJk0QExODffv2GfW61NRUyGQyjBw50rwB2qm0zDy89P1B0WUyAMmPh7GHPRGRnTA0XtkcPhKuw+rJTVpaGhITEzFr1iwcOHAA4eHhGDJkCC5fvmzwdefPn8drr72Gvn37WihS+1KgLMMbP1afUVZj0ZhIjmtDRGRHAj3d4KDn0o0gAOkniiwbkA2zenLz8ccfY9KkSZg4cSI6d+6MJUuWwNXVFcuXL9f7moqKCjz99NN477330K5dO4Prv3PnDkpKSnR+GoJF6Wf0LpPJgKgAPgJORGRPfOQuSH48TO+tqbfXH0NaZp5FY7JVVk1uysvLkZWVhbi4OG2Zg4MD4uLisHfvXr2ve//999G6dWs8++yzNW4jOTkZcrlc+6NQ6J+rQyoKlGX4fl++3uVTBgTxdhQRkR2K7+GP9VN66V3+xo/ZvD0FKyc3xcXFqKiogJeXl065l5cXCgurj6gLABkZGfj666+xbNkyo7aRlJQEpVKp/cnP13/Sl4qtx/VfmhwY0gqvDQmxYDRERFSfwhUeBifVnJZ6yHLB2Cir35Yyxc2bNzFu3DgsW7YMnp6eRr3G2dkZzZo10/mRsrTMPLzz32Oiy4Z09sKKCdEWjoiIiOpbr/b6z4F/5F7D4fyGPe6NVeeW8vT0hKOjI4qKdK80FBUVwdu7+miMOTk5OH/+PEaMGKEtU6lUAIBGjRrh1KlTCAoyPMmYlBUoyzDDQCfidx/tYsFoiIjIXKLaGu43uf/89QY9vY5Vr9w4OTkhKioK6enp2jKVSoX09HTExsZWqx8SEoLs7GwcOnRI+/PII49g4MCBOHToUIPoT2PIioxcvY8JPh3jz342REQS4SN3wVwDg/o1c2nY82Jb/d0nJiZi/Pjx6N69O6Kjo7Fw4UKUlpZi4sSJAICEhAT4+fkhOTkZTZo0QWhoqM7rmzdvDgDVyhuaAmUZlu3K1bu8k09TC0ZDRETmFt/DH27OjUTHM3v9h2yoBDTYIT+sntzEx8fjypUrmDlzJgoLCxEREYHNmzdrOxnn5eXBwcGuugZZhaHBnQCguYuTxWIhIiLLMHR7KmltNvp1aNUgr9rLBEEwdE6UnJKSEsjlciiVSkl1Li5QliE2eZvoMhmAPUmDGuQOTkQkdS99l4WfssWfMF49qSdig1paOCLzMOX8zUsiEnG55C+9yyb1bcfEhohIoib10z+YbcbZKxaMxHYwuZGAtMw8jEzZI7pMBmBinwCLxkNERJYTrvDA0NDqTxgDQMr2HHy5M8fCEVkfkxs7V6AsQ9LabL39bWYMC+FVGyIiiRsX21bvsrkNcFJNJjd2Lre4FCo9mc2E2LaY3K/hjvtDRNRQBHq66V2mEoDzxbctGI31Mbmxc25OjnqXKVq4WjASIiKyFh+5C57vGyi6TAYgwLNhnQ+Y3Ni5f/98Qu+y7pz5m4iowZjYJxAOIlOGCwB2nm5YHYuZ3Nixw/nXse+8+PwhMYEtGvTQ20REDY2P3AUv9BfvijCjgc0WzuTGju07f03vsoVPRVguECIisgnN3RqLlgsAsvT8MSxFTG7sWHRAC9HylwYG8QkpIqIGSN95AQC+/f2CBSOxLiY3duz33OpXboaGeuO1ISFWiIaIiKzN0Jg3f+Rew+H8hnH1hsmNnfrytxwkbzxZrXzmiM5WiIaIiGzFF89EobeeKRf2N5BbU0xu7FCBsgzJm6onNgBw4ELD2HGJiEi/fz3UUbT8+u1yC0diHUxu7NCKjFy9yxrWNKhERCRG3+2plO05DeKpKSY3dqZAWYalu8STGxmAKI5tQ0REAIaFVU9uBABbjxdZPhgLY3JjZ3KLS/Uu4+zfRESkIZOJjOgH4J3/HkNaZp6Fo7EsJjd2ZveZYtFyzv5NRESVRbXVfyVf6oP6MbmxIwXKMqTsEJ+6nldtiIioMh+5C8ZGK0SXCQBWZJy3aDyWxOTGjixKPyNazqs2REQkpld7T73Llu06J9mrN0xu7ESBsgzf78sXXTYm2p9XbYiIqBpDt6akPCUDkxs7kWVg/Jr4Hm0sGAkREdkLQ7emAEBPn2O7x+TGTuw5K96RGABul6ssGAkREdmTqYOD9S778wZvS5GVFCjLsFrPLSkHGRDg6WrhiIiIyF74yF0wd1SY6LKPNp2SZL8bJjd2YEVGLsQGHpYBSH48jP1tiIjIoPge/lg8NrJaeYUg4HzxbStEZF5MbmycoRGJvxofhfge/haOiIiI7JHCQ/wP4d1nr1g4EvNjcmPj9D3+DQCuTo0tGAkREdmz0vIK0fLPd0hvvikmNzbM0OPf7GtDRESmCPR0g9jDUSpBeo+EM7mxYYbmkXpjaAj72hARkdF85C6YMTREdNnLqQclNd8UkxsbFujpBgeRNHvKwCBM7hdk+YCIiMiuTe4fJDpbuEoA3lx7VDK3p5jc2LCdp69AVeUxqaGh3nh9iHjmTUREZEiBsgybsgtFl0npySkmNzaqQFmGN37Mrla+5VihZDJrIiKyrNziUtGhRTRcnaSRFkjjXUjQ1uNFouUqAZLJrImIyLICPd0MLpfKiPdMbmzU5Zt/iZbLwKekiIiodnzkLkjS06kYADIkMuYNkxsbVVL2t2j5lIFBfEqKiIhqbXL/ICQNE09wUrbn4MudORaOqP4xubFB87acxKq9F6qVDwxphdfYmZiIiOrokXBf0TFvAGDOxpN237eTyY2N+fK3HKRsF8+an+/Lx7+JiKjuDHUsFgCsyDhvwWjqH5MbG1KgLMOcTSf1LpdKL3YiIrIufaMVa3yVcc6ur97wbGlDanpETyq92ImIyLp85C6Y1DdQ73J7fzKXyY0Nyf5TqXcZ55IiIqL6NLFPoN6rN/b+ZC6TGxtR0y0pziVFRET1yUfugjmjwkQTHAHqUfLtFZMbG2HoltTYaH/OJUVERPUuvoc/9iQNwsgI32rLZvyYbbf9bpjc2Ah9o0bKAEwd3N6ywRARUYOy/tClamUCgKzz1y0fTD1gcmMj3v/fcdHyGcN4O4qIiMwnt7hU7zKZoUeqbBiTGxtwOP86Nh0Vn6W1q19zywZDREQNiqH5pk4UlFgwkvrD5MYG7Dt/TbTc3nurExGR7fORu+B5PY+Fp2zPsct+N0xubEB0QAtrh0BERA2YvsfC7XW0YiY3NuBk4U3RcgH2PYgSERHZBx+5C14cIP5U7rJd9jdaMZMbKytQlmHGj9miyxxlMt6WIiIii+gd7Clabo9PTTG5sbJF6WdEx7dxkAGzHw/lk1JERGQRhjoW29tTU0xurKhAWYbv9+WLLnv/0S6I7+Fv4YiIiKih8pG7IGloiOiybm09LBxN3TC5saJpqQdFy2UABnfysmwwRETU4E3uH4SkYdUTnPlbTlkhmtpjcmMl8zafxB+54vcwpwwM4u0oIiKyip6B1Z/g/fHARRzOt59+N0xurKBAWYaUHTl6l/du38qC0RAREd2nb+y1z9LPWjiS2mNyYwWGhrp2kHHgPiIish59Y6+ln7yML3fq/8PcljC5sYJATzc46Ol5nvx4GG9JERGR1YQrPBAdIN6BeM7Gk3Yx5o1NJDcpKSkICAhAkyZNEBMTg3379umtu3btWnTv3h3NmzeHm5sbIiIi8O2331ow2rrzkbugi28znTKFRxPsTRrEJ6SIiMjqxsW2FS23lzFvGplS+caNG1i3bh127dqFCxcu4Pbt22jVqhUiIyMxZMgQ9OrVy+QA0tLSkJiYiCVLliAmJgYLFy7EkCFDcOrUKbRu3bpa/RYtWuCtt95CSEgInJyc8NNPP2HixIlo3bo1hgwZYvL2rWHWf48i+6LuZGT51//C5ZK/eNWGiIisrruBaYHsYcwbo67cXLp0Cc899xx8fHzw4YcfoqysDBERERg8eDDatGmD7du344EHHkDnzp2RlpZmUgAff/wxJk2ahIkTJ6Jz585YsmQJXF1dsXz5ctH6AwYMwGOPPYZOnTohKCgIr7zyCrp27YqMjAyTtmstX/6Wg1V7L4gu228H2TAREUmfj9wFU/RMx2APM4UbdeUmMjIS48ePR1ZWFjp37ixap6ysDOvXr8fChQuRn5+P1157rcb1lpeXIysrC0lJSdoyBwcHxMXFYe/evTW+XhAEbNu2DadOncLcuXNF69y5cwd37tzR/l5SYr0PpUBZhjmbTupd3l3PPU4iIiJL6x3sKfpkb8r2HDzds61N32kwKrk5fvw4WrZsabCOi4sLxowZgzFjxuDq1atGbby4uBgVFRXw8tIdsM7LywsnT+pPApRKJfz8/HDnzh04Ojri888/xwMPPCBaNzk5Ge+9955R8ZhbbnGp6FQLADAszBvhCiY3RERkGwI93SADqp23NDOFv/lwJytEZRyjbku1bNkSP/30E1QqlVErrSkRqqumTZvi0KFDyMzMxL///W8kJiZix44donWTkpKgVCq1P/n54tMdWIJmR6kqNqgFPn86yuLxEBER6WPPM4Ub/bTUyJEjoVAo8NZbb+Hs2foZyMfT0xOOjo4oKirSKS8qKoK3t7fe1zk4OKB9+/aIiIjAq6++iieeeALJycmidZ2dndGsWTOdH2vZcOiS6JWbP85ds+mdhIiIGiZ7nSnc6OQmNzcXkydPRmpqKjp27Ij+/fvj22+/RVlZ7U/KTk5OiIqKQnp6urZMpVIhPT0dsbGxRq9HpVLp9KuxRYb626gE4HzxbQtHREREZJihmcL3njOuC4o1GJ3cKBQKzJw5Ezk5Odi6dSsCAgLwwgsvwMfHB//85z+RmZlZqwASExOxbNkyrFq1CidOnMALL7yA0tJSTJw4EQCQkJCg0+E4OTkZv/76K86dO4cTJ05gwYIF+Pbbb/HMM8/UavuWYqi/DUclJiIiW2RopvDv/8iz2bsOJo1zozFw4EAMHDgQixcvRmpqKlauXImePXsiNDQUhw8fNmld8fHxuHLlCmbOnInCwkJERERg8+bN2k7GeXl5cHC4n4OVlpbixRdfxJ9//gkXFxeEhITg//7v/xAfH1+bt2IxmlGJVVUyHBk4KjEREdmuyf2DcLygBP89dEmnXABw4MJ1PNzV9s5fMkEQ9F1QMMq5c+ewfPlyfPHFFygpKcHdu3frKzazKCkpgVwuh1KptHj/my935mDOppPQtPjYaAWmDg5mYkNERDbtf4cvYurqQ9XKYwJbIG2y8d1I6sKU83etpl8oKyvDN998gwEDBiA4OBipqalITEzE+fPna7O6BiEtMw9zNt5PbAAgXNGciQ0REdk8fSMW/5F7DYfzba9jsUnJze+//47nn39e28+mTZs22Lp1K86ePYu33noLfn5+5orTrhUoy/DGj9nV+twkrc222fuVREREGj5yFwwPE3+KednOXAtHUzOj+9x07twZp06dQmRkJJKTkzF27FjI5XJzxiYZi9LPiJZrnpLi1RuyhIqKCpu/bUymcXJy0umTSGROk/q1w0/ZhdXKf84uwFvKMps6lxmd3MTFxWH16tUIDw83ZzySU6Asw/f7xAcO5FNSZAmCIKCwsBA3btywdihUzxwcHBAYGAgnJydrh0INQLjCA9EBHthXZXwbzZg3w8PtMLn57LPPzBmHZK3I0H+57o2hITaV6ZI0aRKb1q1bw9XVFTJ7mNKXaqRSqXDp0iUUFBTA39+fnytZxIhw32rJDQDcKCu3QjT6GZXcPPTQQ3j33XfRs2dPg/Vu3ryJzz//HO7u7pgyZUq9BGjPCpRlWLpLPLmZENsWk/uJD2tNVF8qKiq0iY25p0Uhy2vVqhUuXbqEv//+G40bN7Z2ONQANHcV38+au9jW1UOjkpsnn3wSo0aNglwux4gRI9C9e3f4+vqiSZMmuH79Oo4fP46MjAxs3LgRDz/8MObNm2fuuO1CbnGp3mU9AsV7nhPVJ00fG1dX3v6UIs3tqIqKCiY3ZBHdA1qITqa58WgBhof7WiMkUUYlN88++yyeeeYZrFmzBmlpaVi6dCmUSiUAQCaToXPnzhgyZAgyMzPRqZPtzhJqaYaGra7b6EJEpuEtC2ni50qWpplMM2VHjk75xuxCHM6/jnCFh5Ui02V0nxtnZ2c888wz2mkOlEolysrK0LJlS/7FYCIZgKgA29gBiIiITNHcTfycv2xnLhY/bRvntlo/QyiXy+Ht7c3ExgB9nYkn9W3HjsREVnD+/HnIZDIcOnTI2qEQ2a1oPQP6/ZxdYDNjt3GABDMpUJZhmUhnYhmAiX0CLB4PERFRfdA8El6VAGDr8SLLBySCyY2ZrMjIFZ0FnFdtiGqnvNy2HjUlasgSegWIls/87zGkZeZZNhgRTG7MwNAj4A93FR++msgeFCjLsCen2CKXngcMGICXXnoJ06ZNg6enJ4YMGYKjR49i6NChcHd3h5eXF8aNG4fi4mLtazZv3ow+ffqgefPmaNmyJYYPH46cnBwDWyGi2ohq6wGx7uwCgDfXHrX67SkmN2Zg6BHw2+UqC0ZCVH/SMvPQe842jF32B3rP2WaRv85WrVoFJycn7N69G3PmzMGgQYMQGRmJ/fv3Y/PmzSgqKsLo0aO19UtLS5GYmIj9+/cjPT0dDg4OeOyxx6BS8XtHVJ985C6YMypMdFmFIOB88W0LR6TL6KelKrtx4wZ++OEH5OTk4PXXX0eLFi1w4MABeHl5cfJMAGXlf4uWc7oFslcFyjIkrc2G6t69VpWg/uusX4dWZr3NGhwcjI8++ggA8OGHHyIyMhKzZ8/WLl++fDkUCgVOnz6NDh06YNSoUTqvX758OVq1aoXjx48jNDTUbHESNUQh3k1Fy2Ww/rnO5Cs3R44cQYcOHTB37lzMnz9fO1/N2rVrkZSUVN/x2Z20zDw8uypLdNlzfdjfhuxTbnGpNrHRsMRfZ1FRUdr/P3z4MLZv3w53d3ftT0hICABobz2dOXMGY8aMQbt27dCsWTMEBAQAAPLyrN8HgEhq9p2/JlpuC8O4mXzlJjExERMmTMBHH32Epk3vZ23Dhg3D2LFj6zU4e1OgLMOMH7NFl/EpKbJngZ5ucJBBJ8FxlMnM/teZm9v9gTBv3bqFESNGYO7cudXq+fj4AABGjBiBtm3bYtmyZfD19YVKpUJoaCg7IxOZgb5HwgHrT6Rp8pWbzMxMTJ48uVq5n58fCgurT4XekOQWl+rNWPmUFNkzH7kLkh8Pg+O9EXEdZTLMfjzUovt0t27dcOzYMQQEBKB9+/Y6P25ubrh69SpOnTqFt99+G4MHD0anTp1w/Xr1Cf6IqH7oeyQcAPaeu2rhaHSZnNw4OzujpKSkWvnp06fRqlWregnKXhmabiGmnW2M2khUW/E9/JExYyBWT+qJjBkDEd/D36LbnzJlCq5du4YxY8YgMzMTOTk52LJlCyZOnIiKigp4eHigZcuWWLp0Kc6ePYtt27YhMTHRojESNTSfjokULV+9L8+qT0yZnNw88sgjeP/997UT8slkMuTl5eGNN96o1pmvodlw+JLeZdbuOU5UH3zkLogNammVq5C+vr7YvXs3Kioq8OCDDyIsLAzTpk1D8+bN4eDgAAcHB6SmpiIrKwuhoaGYPn06J/ElMjMfuQue7xtYrVwlWPe8JxME06ZwVCqVeOKJJ7B//37cvHkTvr6+KCwsRGxsLDZu3Khzj9wWlZSUQC6XQ6lUolmzZvW23i9/y0HyppN6l/93Si+bmVCMGo6//voLubm5CAwMRJMmTawdDtUzfr5kCwqUZeg9Z1u1PnkZMwbW6x9Cppy/Te5QLJfL8euvvyIjIwNHjhzBrVu30K1bN8TFxdU6YHtXoCzDHAOJTb9gTyY2REQkST5yFzwW6YcfD1zUloW2qb+LB7VRq3FuAKBPnz7o06dPfcZitwx1JAaAuU90tVgsREREllSgLMO6gxd1yg7nKxGbvA1zR4VZvH8eUIvk5rPPPhMtl8lkaNKkCdq3b49+/frB0dGxzsHZi0BPN8gg/mx/0rAQPiVFRESSJTYOlkbS2myzD/YpxuTk5pNPPsGVK1dw+/ZteHiob7Vcv34drq6ucHd3x+XLl9GuXTts374dCoWi3gO2RT5yF/QJ9sSuM8XVlnX1a275gIiIiCzE0JPCmo7Flk5uTH5aavbs2ejRowfOnDmDq1ev4urVqzh9+jRiYmLw6aefIi8vD97e3pg+fbo54rVJBcoyZIgkNpxugYiIpM5H7oIpA4JEl1nrPGjylZu3334bP/74I4KC7r+R9u3bY/78+Rg1ahTOnTuHjz76qEE9Fq6vzw2nWyAioobg9YdCkHu1FBuz7w/mKwOQ/HiYVc6DJic3BQUF+Pvv6hND/v3339oRin19fXHz5s26R2cnxIamdwCnWyAioobj86ejcDj/OraduIxWzZwxuJOX1f7AN/m21MCBAzF58mQcPHhQW3bw4EG88MILGDRoEAAgOzsbgYHVB/WRKrGh6ZNHWSdbJSIispZwhQemP9gRz/QMsOo50OQrN19//TXGjRuHqKgoNG7cGID6qs3gwYPx9ddfAwDc3d2xYMGC+o3UxsX38Ee/Dq1wvvg2AjxdmdgQERFZicnJjbe3N3799VecPHkSp0+fBgB07NgRHTt21NYZOHBg/UVoR3zkLkxqiOrJgAEDEBERgYULF1o1joCAAEybNg3Tpk2zahxEZLxaD+IXEhKCkJCQ+oyFiEhr7dq12qvD1pSZmWnz08oQka5aJTd//vknNmzYgLy8PJSXl+ss+/jjj+slMCJq2Fq0aGHtEAAArVq1Mvs2ysvL4eTkZPbtEDUUJncoTk9PR8eOHfHFF19gwYIF2L59O1asWIHly5fj0KFDZgiRiGyG8iKQu1P9r5kNGDBAeysoICAAH374IRISEuDu7o62bdtiw4YNuHLlCh599FG4u7uja9eu2L9/v/b1V69exZgxY+Dn5wdXV1eEhYVh9erVOtu4efMmnn76abi5ucHHxweffPKJznY12658a0wmk+Grr77CY489BldXVwQHB2PDhg3a5RUVFXj22WcRGBgIFxcXdOzYEZ9++qnOdidMmICRI0fi3//+N3x9fdGxY0e8//77CA0NrdYOEREReOedd+rQkkQNj8nJTVJSEl577TVkZ2ejSZMm+PHHH5Gfn4/+/fvjySefNEeMRGQLDnwDLAwFVo1Q/3vgG4tu/pNPPkHv3r1x8OBBPPzwwxg3bhwSEhLwzDPP4MCBAwgKCkJCQgIEQT0mw19//YWoqCj8/PPPOHr0KJ5//nmMGzcO+/bt064zMTERu3fvxoYNG/Drr79i165dOHDgQI2xvPfeexg9ejSOHDmCYcOG4emnn8a1a9cAACqVCm3atMGaNWtw/PhxzJw5E2+++Sb+85//6KwjPT0dp06dwq+//oqffvoJ//jHP3DixAlkZmZq6xw8eBBHjhzBxIkT66MJiRoOwUTu7u7C2bNnBUEQhObNmwtHjx4VBEEQDh06JLRt29bU1VmcUqkUAAhKpdLaoRCZXVlZmXD8+HGhrKysbiu68acgvNtcEGY1u//zroe63Ez69+8vvPLKK4IgCELbtm2FZ555RrusoKBAACC888472rK9e/cKAISCggK963z44YeFV199VRAEQSgpKREaN24srFmzRrv8xo0bgqurq3a7mm1/8skn2t8BCG+//bb291u3bgkAhE2bNund7pQpU4RRo0Zpfx8/frzg5eUl3LlzR6fe0KFDhRdeeEH7+9SpU4UBAwboXW+9fb5EdsCU87fJV27c3Ny0/Wx8fHyQk5OjXVZcXH0KAiKSgGs5gKDSLRMqgGvnLBZC165dtf/v5eUFAAgLC6tWdvnyZQDq20MffPABwsLC0KJFC7i7u2PLli3Iy8sDAJw7dw53795FdHS0dh1yuVznyU9jYnFzc0OzZs202wWAlJQUREVFoVWrVnB3d8fSpUu129UICwur1s9m0qRJWL16Nf766y+Ul5fj+++/xz/+8Y8a4yEiXSZ3KO7ZsycyMjLQqVMnDBs2DK+++iqys7Oxdu1a9OzZ0xwxEpG1tQgCZA66CY7MEWjRzmIhVH5ySnZvwEyxMpVKHeO8efPw6aefYuHChQgLC4ObmxumTZtW7SGIusai2bZmu6mpqXjttdewYMECxMbGomnTppg3bx7++OMPndeIPYE1YsQIODs7Y926dXBycsLdu3fxxBNP1DleoobG5OTm448/xq1btwCo7zvfunULaWlpCA4O5pNSRFIl9wNGfAr8b5r6io3MERixUF1uo3bv3o1HH30UzzzzDAB10nP69Gl07twZANCuXTs0btwYmZmZ8Pf3BwAolUqcPn0a/fr1q9N2e/XqhRdffFFbVvkKtyGNGjXC+PHjsWLFCjg5OeGpp56CiwvHziIylcnJTbt29/9Sc3Nzw5IlS+o1ICKyUd0SgKDB6ltRLdrZdGIDAMHBwfjhhx+wZ88eeHh44OOPP0ZRUZE2uWnatCnGjx+P119/HS1atEDr1q0xa9YsODg4aK8C1Xa733zzDbZs2YLAwEB8++23yMzMNHpKmueeew6dOnUCoE6UiMh0Jve5adeuHa5evVqt/MaNGzqJDxFJkNwPCOxr84kNALz99tvo1q0bhgwZggEDBsDb2xsjR47UqfPxxx8jNjYWw4cPR1xcHHr37o1OnTqhSZMmtd7u5MmT8fjjjyM+Ph4xMTG4evWqzlWcmgQHB6NXr14ICQlBTExMreMgashkgiAINVe7z8HBAYWFhWjdurVOeVFREfz9/XHnzp16DbC+lZSUQC6XQ6lUolmzZtYOh8is/vrrL+Tm5iIwMLBOJ+yGorS0FH5+fliwYAGeffZZq8QgCAKCg4Px4osvIjEx0WBdfr7UkJhy/jb6tlTlQaq2bNkCuVyu/b2iogLp6ekICAgwPVoiIis5ePAgTp48iejoaCiVSrz//vsAgEcffdQq8Vy5cgWpqakoLCzk2DZEdWB0cqO5nCuTyTB+/HidZY0bN0ZAQECDmwmciOzf/PnzcerUKTg5OSEqKgq7du2Cp6enVWJp3bo1PD09sXTpUnh4eFglBiIpMDq50TzmGBgYiMzMTKt9+YmI6ktkZCSysrKsHYaWib0EiEgPk5+Wys3NNUccRERERPXCqOTms88+M3qFL7/8cq2DISLz4BUBaeLnSiTOqOTmk08+MWplMpmMyQ2RDdGMpHv79m0OBidBmtGWHR0drRwJkW0xKrnhrSgi++To6IjmzZtr5z1ydXWt0wB1ZDtUKhWuXLkCV1dXNGpkcg8DIkmr0zdCc0mUB0si2+Xt7Q0AOhM7kjQ4ODjA39+fx2CiKmqV3HzzzTeYN28ezpw5AwDo0KEDXn/9dYwbN65egyOiupPJZPDx8UHr1q1x9+5da4dD9cjJyQkODiYPNE8kebWaOPOdd97BSy+9hN69ewMAMjIy8M9//hPFxcWYPn16vQdJRHXn6OjIvhlE1CCYPP1CYGAg3nvvPSQkJOiUr1q1Cu+++67N98/h9AtERET2x5Tzt8nXMwsKCtCrV69q5b169UJBQYGpqyMiIiKqVyYnN+3bt8d//vOfauVpaWkIDg6ul6CIiIiIasvkPjfvvfce4uPjsXPnTm2fm927dyM9PV006TFGSkoK5s2bh8LCQoSHh2PRokWIjo4Wrbts2TJ88803OHr0KAAgKioKs2fP1lufiIiIGhajr9xokolRo0bhjz/+gKenJ9avX4/169fD09MT+/btw2OPPWZyAGlpaUhMTMSsWbNw4MABhIeHY8iQIXofW92xYwfGjBmD7du3Y+/evVAoFHjwwQdx8eJFk7dNRERE0mN0h2IHBwf06NEDzz33HJ566ik0bdq0XgKIiYlBjx49sHjxYgDqgakUCgWmTp2KGTNm1Pj6iooKeHh4YPHixdU6OYthh2IiIiL7Y5YOxb/99hu6dOmCV199FT4+PpgwYQJ27dpVp0DLy8uRlZWFuLi4+wE5OCAuLg579+41ah23b9/G3bt30aJFC9Hld+7cQUlJic4PERERSZfRyU3fvn2xfPlyFBQUYNGiRcjNzUX//v3RoUMHzJ07F4WFhSZvvLi4GBUVFfDy8tIp9/LyMnp9b7zxBnx9fXUSpMqSk5Mhl8u1PwqFwuQ4iYiIyH6Y/LSUm5sbJk6ciN9++w2nT5/Gk08+iZSUFPj7++ORRx4xR4x6zZkzB6mpqVi3bh2aNGkiWicpKQlKpVL7k5+fb9EYiYiIyLLqNLdU+/bt8eabb6Jt27ZISkrCzz//bNLrPT094ejoiKKiIp3yoqIi7Xw4+syfPx9z5szB1q1b0bVrV731nJ2d4ezsbFJcREREZL9qPSnJzp07MWHCBHh7e+P111/H448/jt27d5u0DicnJ0RFRSE9PV1bplKpkJ6ejtjYWL2v++ijj/DBBx9g8+bN6N69e23fAhEREUmQSVduLl26hJUrV2LlypU4e/YsevXqhc8++wyjR4+Gm5tbrQJITEzE+PHj0b17d0RHR2PhwoUoLS3FxIkTAQAJCQnw8/NDcnIyAGDu3LmYOXMmvv/+ewQEBGj75ri7u8Pd3b1WMRAREZF0GJ3cDB06FFu3boWnpycSEhLwj3/8Ax07dqxzAPHx8bhy5QpmzpyJwsJCREREYPPmzdpOxnl5eTqz3n7xxRcoLy/HE088obOeWbNm4d13361zPERERGTfjB7n5pFHHsGzzz6L4cOH2/XMwhznhoiIyP6Ycv42+srNhg0b6hwYERERkbnVukMxERERkS1ickNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClMboiIiEhSmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClMboiIiEhSmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClMboiIiEhSmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClMboiIiEhSmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClMboiIiEhSmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClMboiIiEhSmNwQERGRpDC5ISIiIklhckNERESSwuSGiIiIJIXJDREREUkKkxsiIiKSFCY3REREJClWT25SUlIQEBCAJk2aICYmBvv27dNb99ixYxg1ahQCAgIgk8mwcOFCywVKREREdsGqyU1aWhoSExMxa9YsHDhwAOHh4RgyZAguX74sWv/27dto164d5syZA29vbwtHS0RERPZAJgiCYK2Nx8TEoEePHli8eDEAQKVSQaFQYOrUqZgxY4bB1wYEBGDatGmYNm2awXp37tzBnTt3tL+XlJRAoVBAqVSiWbNmdX4PREREZH4lJSWQy+VGnb+tduWmvLwcWVlZiIuLux+MgwPi4uKwd+/eettOcnIy5HK59kehUNTbuomIiMj2WC25KS4uRkVFBby8vHTKvby8UFhYWG/bSUpKglKp1P7k5+fX27qJiIjI9jSydgDm5uzsDGdnZ2uHQURERBZitSs3np6ecHR0RFFRkU55UVEROwsTERFRrVktuXFyckJUVBTS09O1ZSqVCunp6YiNjbVWWERERGTnrHpbKjExEePHj0f37t0RHR2NhQsXorS0FBMnTgQAJCQkwM/PD8nJyQDUnZCPHz+u/f+LFy/i0KFDcHd3R/v27a32PoiIiMh2WDW5iY+Px5UrVzBz5kwUFhYiIiICmzdv1nYyzsvLg4PD/YtLly5dQmRkpPb3+fPnY/78+ejfvz927Nhh6fCJiIjIBll1nBtrMOU5eSIiIrINdjHODREREZE5MLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiSWFyQ7ZHeRHI3an+l4iIyESNrB1Ag6S8CFzLAVoEAXI/a0djWw58A/zvFUBQATIHYMSnQLcEa0dFZJitf6dtPT4yjJ+fyZjc1Lc/s4C8vYB/LNAmqvpyY07e9rwja2Jv7AbcuKAuU8QY9z7+zAL+9zIgCOrfBRXwv2lA0GDDr9fXXpVjuVt6/98WQerl9dHGhj6rqts3dlvm+PxNWacx76nyMlveX42Jra7vqTYJeU37bE3bNeV9XToEbJ1V9/jM+Tmbum7lRSD/D/X/K2LU/9Ymtsrbre06TNmWJubmbasfi8SOE8qLwB9fAHtT1J8fZMAD7wG9X6m/mIz5rmtitMXvuB5MburTuheAw9/f/z1oMPDIIvX/X8sBym9XP3lveAVwaw04uap3nJz0+wdKyIC+iYBXqLq+5gsh9iUQS6qq7rj6DlhVv3A1nYz/zAKy16j/P+zJ+9urfJDXIQMe+ez+AVUsjt2fAb++U31bQgWwZ5F6O5pkqfKBoWp79XoJiHkBOPojsHXm/bauRgZAUB/s494FfCPFk5+qiVHlOjnpwIaX1esBgF5Tgc6PqZef+w3IWFBl+wYOTDWdiMQSJUD3AF/5M66cXBYdqxSLDIiaAAT2E086q56o494F5Ip7Mf55PzYAiH4eaOR8/8BbNd5Tm9Tvp7wUcHIDfCOAjkPvt63YibPqvid2Eqv6nqu2o2Z55XirntQ12zv3G7Brwb3P8N7+4+is+9l1eQzo+pT6O1o1aQd093nNd9pQQl71e9LlMSB2KnD5WPUkqXUX4PRmwN1L3XZyvyqv17NP6fsuCir1Pvt3+f31VW67qvsgoN5fWgRVKrt3XGo3wPAxomrc+v7YMLTPiyUDVb93AHS+z1W/M5W/z+W3gYtZ6riKTwP7lt7/7NUNpNumVfc/fcfRysTe5/F1wJ7FVWLWxA3dcs337loukLWiSn0B+HWmehvN/asf7/P/AG5fA1xbqNus6r5a+dhwatO943iVdvszS33MPfHf+5935bbRHGPr6485M5EJgt6jv8WkpKRg3rx5KCwsRHh4OBYtWoTo6Gi99desWYN33nkH58+fR3BwMObOnYthw4YZta2SkhLI5XIolUo0a9asvt6Ceof4alA9rOjel9TYulET1NsuOnK/OGiw+sBT+YDR9Sng8GronIgdnYFd8w1vIuxJwDMEqLgDdHgI2PMZcHy9bp3wsUCP54CvBuuPXeYAPLsVOPgtkLXyfr0OQ4DmAcC+L418z9VWrH+btipwABDQF3BpDpTdAM7vAnJ/g973ETb6/kFILxnQ+RHgxAYDCZ2IB94H2vZRr//OLeDwdyLJqYnCRgPZ/zEcq+ZAGTVBXXRgVfXteocBhdmGtxX9vPoAf/saUHRUd9+qxgEYsxq4kFHpL+E6atEeuHa2ennYaMAn/P7Jp/KB/+u42m87+nkgc1n1z1jRE+gzXZ2Ald8GUp8ybj/QJOTH19WuTcT+ONizGDizRbde8IPAmV+MX6+iJ5D/u2mxaGNyVMf060zU6djg1x24uF+kLOv+ejX7H6BOIPYvr5QsW0inkUDwYGDD1Boq1nSslAF+UdXfsz6ac8PtYuD2VeDoD1X2n3q+ygTTzt9WT27S0tKQkJCAJUuWICYmBgsXLsSaNWtw6tQptG7dulr9PXv2oF+/fkhOTsbw4cPx/fffY+7cuThw4ABCQ0Nr3J7Zkps1E4Bj6+pvfUQkDe7ewK1Ca0dBZB0PfAD0frleVmVXyU1MTAx69OiBxYsXAwBUKhUUCgWmTp2KGTNmVKsfHx+P0tJS/PTTT9qynj17IiIiAkuWLKlxe2ZJbpQXgU8618+6iIiIpELmAEw7Wi+3qEw5f1v1UfDy8nJkZWUhLi5OW+bg4IC4uDjs3btX9DV79+7VqQ8AQ4YM0Vv/zp07KCkp0fmpd5p7skRERHSfoAKunbP4Zq2a3BQXF6OiogJeXl465V5eXigsFL+MW1hYaFL95ORkyOVy7Y9Coaif4ImIiMgwmQPQop3FNyv5QfySkpKgVCq1P/n5+fW/EUUM7vcoJyIiIgBA3HtWeWrKqsmNp6cnHB0dUVRUpFNeVFQEb29v0dd4e3ubVN/Z2RnNmjXT+al3cj/1o85McIiIiNT6vlZvnYlNZdXkxsnJCVFRUUhPT9eWqVQqpKenIzY2VvQ1sbGxOvUB4Ndff9Vb32K6JQDTjwFREw1UMjL5aRls2rajJqp7pNc2uQoZDsROq91rxfR9FXhwdv2tz5YFP4ga2z3mBcArXLfMtzsw7GP1ZycT+Rq2aF8/8UWMqzk+a/CJVD/ua7Sq78HM78m7q5EVHe61cR3496nb6/u+BgycCYt+zu3iaq5jFFmVfysJGgwED6mn7ejjoN5Ofbddq061eJGRMYQ8Wo/tXxsmtFW7AWaLoiZWH8QvMTER48ePR/fu3REdHY2FCxeitLQUEyeqk4SEhAT4+fkhOTkZAPDKK6+gf//+WLBgAR5++GGkpqZi//79WLp0qTXfhprcDxixUH1/UWeMhXuD2AUNBv5YAuxdfG/8GUegazxwJE09WJ3MUf36bgnqQe0qD6RVmcwRiJsF+HZTb0tzyS90FJC/Dzi1sdKYAzL1eAQdhwGK6HuD3k1Tbw8OwAPv3h+HoFWQegAyqNTLOo8ATvyvUgyagbLuxX049V5dqMf10GxDM9DVr2/rGTdDM5Bcf/VAVDfy7g88pYgGbhaqx7i4fQ3I+ORerPdeEzkOuHv7/j3cqu2paZfSK8APIolml8eB2JfU62jsqh6zZ88i6B9jJh7IThNf9ty2+2OYVI6j8uek+TwB9XhE+b+rT+qVR6/u97q6w115qXosFM3yP7OArweLj1cicwSe+l5dv+gYcOg78ToDkwD/6PufeeU2auyq2/aVP4urZ9Qjo4rp+yrQ/Vn1vlb5tZU/l/x96n+LjoqMpeQAPPWdej8RG7wxfOz974RmH3Xx0H0PIxaqv0+aGDa9pn9fG5MK3C1T/9rcX2ScGRkgk90rq/SdqPa5ar4TP1WPQ2x8IO0YMPe+p7s/rT6ek0wGjFqq22Z5e3XryWRA1zGV2qRS3JXHEWnaqtJ3u5IODwGnt0B3H3cAosaLjy+k+S4r86uPFSOTASPuDcj5v2kig8xVDq/KvnZ8vW5bPvAuEPqEet/X7DenNgO3itTjX2m+I5W/N5eP6R6/IPaZV+IVChQdF6nnADyx/P7xytB3DbJ7h757YzOFPXl/HJ5qY7tU2n/SP9Azjlil42jl4zigbovGrvePT1X3VZkjMDRZHXNN66/6XpX5wNZ3dfcPmSPQZ5r6GKLZRyrv1zvn3d9HNOVA9XPIXyXVY5E5WqWvjXbz1n4UHAAWL16sHcQvIiICn332GWJi1CMqDhgwAAEBAVi5cqW2/po1a/D2229rB/H76KOPrD+IX1XKi/cPVpovUOVlmi+0dsTLc7qJSuV6lXd2zQnEqCH0RdZp6rLKvwPGxa1x4BvdL0Hf6UC7gcbFb0yshuooLwILQ6sfeKaLPJKoef2lg5W+/JUOUge+0R0RtfIBXmw9pnxONdFpw3uqJk2abVdN9CrXMaYdq74XsfZ7bqv4tCKGVE7U9cVe9bui7zPV9x6MbaeqdSsfyGvzndDUrbqv93oJiPln9XXptIWBqRAMtYmh/UtfHbH3rB3F18A6NXFU/uOjpu/Yc1trjq8u343KMdc0IOJz24Cm3oa/Gxo6n6EMiJ4EdHpE/NgnFovYe9b5I1UkoTNqao9p1T83Q+sX+0Og6nFALN6azkM11a3pe14P7GqcG0uzWHJDavVxMKutmg4MYgx9wfUlq+ZmStJUn+1dm/bTxxL7gbXaydR1Wus7YY7t1uc+UtftVxU+Fnis0tXH2v6hVFd1XWdNrzf1DwFzMvN2mdwYwOSmgbFmciUFbD+qibX3kcrb19zSrnrrlySByY0BTG6IiIjsj92MUExERERU35jcEBERkaQwuSEiIiJJYXJDREREksLkhoiIiCSFyQ0RERFJCpMbIiIikhQmN0RERCQpTG6IiIhIUpjcEBERkaQwuSEiIiJJaWTtACxNM5VWSUmJlSMhIiIiY2nO28ZMidngkpubN28CABQKhZUjISIiIlPdvHkTcrncYJ0GNyu4SqXCpUuX0LRpU8hksnpdd0lJCRQKBfLz8znjuBmxnS2D7Ww5bGvLYDtbhrnaWRAE3Lx5E76+vnBwMNyrpsFduXFwcECbNm3Muo1mzZrxi2MBbGfLYDtbDtvaMtjOlmGOdq7pio0GOxQTERGRpDC5ISIiIklhclOPnJ2dMWvWLDg7O1s7FEljO1sG29ly2NaWwXa2DFto5wbXoZiIiIikjVduiIiISFKY3BAREZGkMLkhIiIiSWFyQ0RERJLC5MZEKSkpCAgIQJMmTRATE4N9+/YZrL9mzRqEhISgSZMmCAsLw8aNGy0UqX0zpZ2XLVuGvn37wsPDAx4eHoiLi6vxcyE1U/dnjdTUVMhkMowcOdK8AUqIqW1948YNTJkyBT4+PnB2dkaHDh14/DCCqe28cOFCdOzYES4uLlAoFJg+fTr++usvC0Vrn3bu3IkRI0bA19cXMpkM69evr/E1O3bsQLdu3eDs7Iz27dtj5cqV5g1SIKOlpqYKTk5OwvLly4Vjx44JkyZNEpo3by4UFRWJ1t+9e7fg6OgofPTRR8Lx48eFt99+W2jcuLGQnZ1t4cjti6ntPHbsWCElJUU4ePCgcOLECWHChAmCXC4X/vzzTwtHbl9MbWeN3Nxcwc/PT+jbt6/w6KOPWiZYO2dqW9+5c0fo3r27MGzYMCEjI0PIzc0VduzYIRw6dMjCkdsXU9v5u+++E5ydnYXvvvtOyM3NFbZs2SL4+PgI06dPt3Dk9mXjxo3CW2+9Jaxdu1YAIKxbt85g/XPnzgmurq5CYmKicPz4cWHRokWCo6OjsHnzZrPFyOTGBNHR0cKUKVO0v1dUVAi+vr5CcnKyaP3Ro0cLDz/8sE5ZTEyMMHnyZLPGae9Mbeeq/v77b6Fp06bCqlWrzBWiJNSmnf/++2+hV69ewldffSWMHz+eyY2RTG3rL774QmjXrp1QXl5uqRAlwdR2njJlijBo0CCdssTERKF3795mjVNKjElu/vWvfwldunTRKYuPjxeGDBlitrh4W8pI5eXlyMrKQlxcnLbMwcEBcXFx2Lt3r+hr9u7dq1MfAIYMGaK3PtWunau6ffs27t69ixYtWpgrTLtX23Z+//330bp1azz77LOWCFMSatPWGzZsQGxsLKZMmQIvLy+EhoZi9uzZqKiosFTYdqc27dyrVy9kZWVpb12dO3cOGzduxLBhwywSc0NhjXNhg5s4s7aKi4tRUVEBLy8vnXIvLy+cPHlS9DWFhYWi9QsLC80Wp72rTTtX9cYbb8DX17fal4nuq007Z2Rk4Ouvv8ahQ4csEKF01Katz507h23btuHpp5/Gxo0bcfbsWbz44ou4e/cuZs2aZYmw7U5t2nns2LEoLi5Gnz59IAgC/v77b/zzn//Em2++aYmQGwx958KSkhKUlZXBxcWl3rfJKzckKXPmzEFqairWrVuHJk2aWDscybh58ybGjRuHZcuWwdPT09rhSJ5KpULr1q2xdOlSREVFIT4+Hm+99RaWLFli7dAkZceOHZg9ezY+//xzHDhwAGvXrsXPP/+MDz74wNqhUR3xyo2RPD094ejoiKKiIp3yoqIieHt7i77G29vbpPpUu3bWmD9/PubMmYOtW7eia9eu5gzT7pnazjk5OTh//jxGjBihLVOpVACARo0a4dSpUwgKCjJv0HaqNvu0j48PGjduDEdHR21Zp06dUFhYiPLycjg5OZk1ZntUm3Z+5513MG7cODz33HMAgLCwMJSWluL555/HW2+9BQcH/v1fH/SdC5s1a2aWqzYAr9wYzcnJCVFRUUhPT9eWqVQqpKenIzY2VvQ1sbGxOvUB4Ndff9Vbn2rXzgDw0Ucf4YMPPsDmzZvRvXt3S4Rq10xt55CQEGRnZ+PQoUPan0ceeQQDBw7EoUOHoFAoLBm+XanNPt27d2+cPXtWm0ACwOnTp+Hj48PERo/atPPt27erJTCahFLgtIv1xirnQrN1VZag1NRUwdnZWVi5cqVw/Phx4fnnnxeaN28uFBYWCoIgCOPGjRNmzJihrb97926hUaNGwvz584UTJ04Is2bN4qPgRjC1nefMmSM4OTkJP/zwg1BQUKD9uXnzprXegl0wtZ2r4tNSxjO1rfPy8oSmTZsKL730knDq1Cnhp59+Elq3bi18+OGH1noLdsHUdp41a5bQtGlTYfXq1cK5c+eEX375RQgKChJGjx5trbdgF27evCkcPHhQOHjwoABA+Pjjj4WDBw8KFy5cEARBEGbMmCGMGzdOW1/zKPjrr78unDhxQkhJSeGj4LZm0aJFgr+/v+Dk5CRER0cLv//+u3ZZ//79hfHjx+vU/89//iN06NBBcHJyErp06SL8/PPPFo7YPpnSzm3bthUAVPuZNWuW5QO3M6buz5UxuTGNqW29Z88eISYmRnB2dhbatWsn/Pvf/xb+/vtvC0dtf0xp57t37wrvvvuuEBQUJDRp0kRQKBTCiy++KFy/ft3ygduR7du3ix5zNW07fvx4oX///tVeExERITg5OQnt2rUTVqxYYdYYZYLAa29EREQkHexzQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGkMLkhIiIiUTt37sSIESPg6+sLmUyG9evXm32bFy9exDPPPIOWLVvCxcUFYWFh2L9/v0nrYHJDRFY3YcIEjBw50mrbHzduHGbPnm1U3aeeegoLFiwwc0REtqG0tBTh4eFISUmxyPauX7+O3r17o3Hjxti0aROOHz+OBQsWwMPDw6T1cIRiIjIrmUxmcPmsWbMwffp0CIKA5s2bWyaoSg4fPoxBgwbhwoULcHd3r7H+0aNH0a9fP+Tm5kIul1sgQiLbIJPJsG7dOp0/RO7cuYO33noLq1evxo0bNxAaGoq5c+diwIABtdrGjBkzsHv3buzatatOsfLKDRGZVUFBgfZn4cKFaNasmU7Za6+9BrlcbpXEBgAWLVqEJ5980qjEBgBCQ0MRFBSE//u//zNzZES276WXXsLevXuRmpqKI0eO4Mknn8RDDz2EM2fO1Gp9GzZsQPfu3fHkk0+idevWiIyMxLJly0xeD5MbIjIrb29v7Y9cLodMJtMpc3d3r3ZbasCAAZg6dSqmTZsGDw8PeHl5YdmyZSgtLcXEiRPRtGlTtG/fHps2bdLZ1tGjRzF06FC4u7vDy8sL48aNQ3Fxsd7YKioq8MMPP2DEiBE65Z9//jmCg4PRpEkTeHl54YknntBZPmLECKSmpta9cYjsWF5eHlasWIE1a9agb9++CAoKwmuvvYY+ffpgxYoVtVrnuXPn8MUXXyA4OBhbtmzBCy+8gJdffhmrVq0yaT1MbojIJq1atQqenp7Yt28fpk6dihdeeAFPPvkkevXqhQMHDuDBBx/EuHHjcPv2bQDAjRs3MGjQIERGRmL//v3YvHkzioqKMHr0aL3bOHLkCJRKJbp3764t279/P15++WW8//77OHXqFDZv3ox+/frpvC46Ohr79u3DnTt3zPPmiexAdnY2Kioq0KFDB7i7u2t/fvvtN+Tk5AAATp48CZlMZvBnxowZ2nWqVCp069YNs2fPRmRkJJ5//nlMmjQJS5YsMSm2RvX6TomI6kl4eDjefvttAEBSUhLmzJkDT09PTJo0CQAwc+ZMfPHFFzhy5Ah69uyJxYsXIzIyUqdj8PLly6FQKHD69Gl06NCh2jYuXLgAR0dHtG7dWluWl5cHNzc3DB8+HE2bNkXbtm0RGRmp8zpfX1+Ul5ejsLAQbdu2NcfbJ7J5t27dgqOjI7KysuDo6KizTHObt127djhx4oTB9bRs2VL7/z4+PujcubPO8k6dOuHHH380KTYmN0Rkk7p27ar9f0dHR7Rs2RJhYWHaMi8vLwDA5cuXAag7Bm/fvl2070xOTo5oclNWVgZnZ2edTs8PPPAA2rZti3bt2uGhhx7CQw89hMceewyurq7aOi4uLgCgvWpE1BBFRkaioqICly9fRt++fUXrODk5ISQkxOh19u7dG6dOndIpO336tMl/RDC5ISKb1LhxY53fZTKZTpkmIVGpVADUf0WOGDECc+fOrbYuHx8f0W14enri9u3bKC8vh5OTEwCgadOmOHDgAHbs2IFffvkFM2fOxLvvvovMzExtp+dr164BAFq1alW3N0lk427duoWzZ89qf8/NzcWhQ4fQokULdOjQAU8//TQSEhKwYMECREZG4sqVK0hPT0fXrl3x8MMPm7y96dOno1evXpg9ezZGjx6Nffv2YenSpVi6dKlJ62GfGyKShG7duuHYsWMICAhA+/btdX7c3NxEXxMREQEAOH78uE55o0aNEBcXh48++ghHjhzB+fPnsW3bNu3yo0ePok2bNvD09DTb+yGyBfv370dkZKT21mxiYiIiIyMxc+ZMAMCKFSuQkJCAV199FR07dsTIkSORmZkJf3//Wm2vR48eWLduHVavXo3Q0FB88MEHWLhwIZ5++mmT1sMrN0QkCVOmTMGyZcswZswY/Otf/0KLFi1w9uxZpKam4quvvqrWJwBQX3np1q0bMjIytInOTz/9hHPnzqFfv37w8PDAxo0boVKp0LFjR+3rdu3ahQcffNBSb43IagYMGABDw+E1btwY7733Ht5777162+bw4cMxfPjwOq2DV26ISBJ8fX2xe/duVFRU4MEHH0RYWBimTZuG5s2bw8FB/6Huueeew3fffaf9vXnz5li7di0GDRqETp06YcmSJVi9ejW6dOkCAPjrr7+wfv16bcdmIrI9HKGYiBq0srIydOzYEWlpaYiNja2x/hdffIF169bhl19+sUB0RFQbvHJDRA2ai4sLvvnmG4OD/VXWuHFjLFq0yMxREVFd8MoNERERSQqv3BAREZGkMLkhIiIiSWFyQ0RERJLC5IaIiIgkhckNERERSQqTGyIiIpIUJjdEREQkKUxuiIiISFKY3BAREZGk/D8BNcqI1fp0dAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gettable = ScheduleGettable(\n",
    "    quantum_device=single_qubit_device,\n",
    "    schedule_function=trace_schedule,\n",
    "    schedule_kwargs={\n",
    "        \"pulse_amp\": 0.5,\n",
    "        \"acq_delay\": 100e-9,\n",
    "        },\n",
    "    batched=True,\n",
    ")\n",
    "\n",
    "data = gettable.get()\n",
    "\n",
    "plt.plot(np.arange(1000)/1e9, data[0], '.', label=\"real\")\n",
    "plt.plot(np.arange(1000)/1e9, data[1], '.', label=\"imaginary\")\n",
    "plt.legend()\n",
    "plt.xlabel(\"Time (s)\")\n",
    "plt.ylabel(\"Voltage (V)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d12d35b4",
   "metadata": {},
   "source": [
    "This time, there is only one acquisition operation in the schedule. The measurement result contains two arrays: one for the _I_ values (`data[0][:]`), and one for the _Q_ values (`data[1][:]`) of the acquired trace.\n",
    "\n",
    "## MeasurementControl\n",
    "\n",
    "Iterating through different parameters can be done with some help from `quantify-core` as well, through the {class}`~quantify_core.measurement.control.MeasurementControl` class. The {class}`~quantify_core.measurement.control.MeasurementControl` uses settables (parameters to vary in an experiment) and gettables (in this case, our {class}`~quantify_scheduler.gettables.ScheduleGettable`). The settable must be a class that implements `set()`, such as a QCoDeS {class}`~qcodes.parameters.ManualParameter`.\n",
    "\n",
    "In this example, the settable is the `time` object, and the setpoints are a numpy array of values (`times`). These are added to the {class}`~quantify_core.measurement.control.MeasurementControl` as shown, together with the {class}`~quantify_scheduler.gettables.ScheduleGettable`. The {class}`~quantify_core.measurement.control.MeasurementControl` object will be in charge of setting the setpoints, and retrieving the measurement results through the gettable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6656e9de",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_core.measurement.control import MeasurementControl\n",
    "\n",
    "\n",
    "measurement_control = MeasurementControl(\"measurement_control\")\n",
    "\n",
    "# Configure the settable\n",
    "time = ManualParameter(\"sample\", label=\"Sample time\", unit=\"s\")\n",
    "time.batched = True\n",
    "\n",
    "times = np.linspace(start=1.6e-7, stop=4.976e-5, num=125)\n",
    "\n",
    "# Configure the gettable\n",
    "gettable = ScheduleGettable(\n",
    "    quantum_device=single_qubit_device,\n",
    "    schedule_function=t1_sched,\n",
    "    schedule_kwargs={\"times\": time},\n",
    "    batched=True\n",
    ")\n",
    "\n",
    "# Configure MeasurementControl\n",
    "measurement_control.settables(time)\n",
    "measurement_control.setpoints(times)\n",
    "measurement_control.gettables(gettable)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3142e78",
   "metadata": {},
   "source": [
    "The experiment is set to run fully in _batched_ mode. When using {class}`~quantify_core.measurement.control.MeasurementControl`, settables and gettables can be either batched (an array of points is set for each measurement iteration) or iterative (only one point is set per iteration). Combinations of batched and iterative settables are possible, as explained in detail in the [quantify-core documentation](https://quantify-os.org/docs/quantify-core/dev/user/concepts.html#mixing-iterative-and-batched-settables).\n",
    "\n",
    "Settables and gettables are batched if they have the attribute `batched=True`. In {class}`~quantify_scheduler.gettables.ScheduleGettable`, this can be controlled through the `batched` argument when creating the class. For other classes, the attribute can be added dynamically if needed, as shown above for the `time` parameter.\n",
    "\n",
    "With both the gettable and the settable having `batched=True`, the {class}`~quantify_core.measurement.control.MeasurementControl` knows that it should set the entire `times` array as the settable's value (instead of repeating the experiment for each value in the array). All data points are measured without interruption and all measurement results are returned in one go. Now, let's run the experiment and retrieve the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "499a3903",
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting batched measurement...\n",
      "Iterative settable(s) [outer loop(s)]:\n",
      "\t --- (None) --- \n",
      "Batched settable(s):\n",
      "\t sample \n",
      "Batch size limit: 125\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9e100de4a25d42a495303ee5bac4e617",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Completed:   0%|           [ elapsed time: 00:00 | time left: ? ] it"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dataset = measurement_control.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c53d6037",
   "metadata": {},
   "source": [
    "The {class}`~quantify_core.measurement.control.MeasurementControl` class processes the data returned by the {class}`~quantify_scheduler.gettables.ScheduleGettable`, and turns it into a {class}`~xarray.Dataset`. More information on the format of this dataset can be found in the [quantify-core documentation](https://quantify-os.org/docs/quantify-core/dev/user/concepts.html#dataset)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a077a24b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "html[data-theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 3kB\n",
       "Dimensions:  (dim_0: 125)\n",
       "Coordinates:\n",
       "    x0       (dim_0) float64 1kB 1.6e-07 5.6e-07 9.6e-07 ... 4.936e-05 4.976e-05\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 1kB -1.166 -1.141 -1.109 ... -0.737 -0.7305 -1.164\n",
       "    y1       (dim_0) float64 1kB 0.2569 0.2138 0.2035 ... -0.2533 -0.247 0.2671\n",
       "Attributes:\n",
       "    tuid:                             20250316-041331-743-6a202a\n",
       "    name:                             \n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  False</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9a0a1c6a-9395-497e-84d5-a9ade461437b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9a0a1c6a-9395-497e-84d5-a9ade461437b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span>dim_0</span>: 125</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-52b91efb-a21c-4665-bd17-8999b96f18fb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-52b91efb-a21c-4665-bd17-8999b96f18fb' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>x0</span></div><div class='xr-var-dims'>(dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.6e-07 5.6e-07 ... 4.976e-05</div><input id='attrs-af944075-f879-433a-8097-ac330345f4c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af944075-f879-433a-8097-ac330345f4c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd414c16-bdf2-4349-97bb-50edc72365d6' class='xr-var-data-in' type='checkbox'><label for='data-fd414c16-bdf2-4349-97bb-50edc72365d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>sample</dd><dt><span>long_name :</span></dt><dd>Sample time</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>batched :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>array([1.600e-07, 5.600e-07, 9.600e-07, 1.360e-06, 1.760e-06, 2.160e-06,\n",
       "       2.560e-06, 2.960e-06, 3.360e-06, 3.760e-06, 4.160e-06, 4.560e-06,\n",
       "       4.960e-06, 5.360e-06, 5.760e-06, 6.160e-06, 6.560e-06, 6.960e-06,\n",
       "       7.360e-06, 7.760e-06, 8.160e-06, 8.560e-06, 8.960e-06, 9.360e-06,\n",
       "       9.760e-06, 1.016e-05, 1.056e-05, 1.096e-05, 1.136e-05, 1.176e-05,\n",
       "       1.216e-05, 1.256e-05, 1.296e-05, 1.336e-05, 1.376e-05, 1.416e-05,\n",
       "       1.456e-05, 1.496e-05, 1.536e-05, 1.576e-05, 1.616e-05, 1.656e-05,\n",
       "       1.696e-05, 1.736e-05, 1.776e-05, 1.816e-05, 1.856e-05, 1.896e-05,\n",
       "       1.936e-05, 1.976e-05, 2.016e-05, 2.056e-05, 2.096e-05, 2.136e-05,\n",
       "       2.176e-05, 2.216e-05, 2.256e-05, 2.296e-05, 2.336e-05, 2.376e-05,\n",
       "       2.416e-05, 2.456e-05, 2.496e-05, 2.536e-05, 2.576e-05, 2.616e-05,\n",
       "       2.656e-05, 2.696e-05, 2.736e-05, 2.776e-05, 2.816e-05, 2.856e-05,\n",
       "       2.896e-05, 2.936e-05, 2.976e-05, 3.016e-05, 3.056e-05, 3.096e-05,\n",
       "       3.136e-05, 3.176e-05, 3.216e-05, 3.256e-05, 3.296e-05, 3.336e-05,\n",
       "       3.376e-05, 3.416e-05, 3.456e-05, 3.496e-05, 3.536e-05, 3.576e-05,\n",
       "       3.616e-05, 3.656e-05, 3.696e-05, 3.736e-05, 3.776e-05, 3.816e-05,\n",
       "       3.856e-05, 3.896e-05, 3.936e-05, 3.976e-05, 4.016e-05, 4.056e-05,\n",
       "       4.096e-05, 4.136e-05, 4.176e-05, 4.216e-05, 4.256e-05, 4.296e-05,\n",
       "       4.336e-05, 4.376e-05, 4.416e-05, 4.456e-05, 4.496e-05, 4.536e-05,\n",
       "       4.576e-05, 4.616e-05, 4.656e-05, 4.696e-05, 4.736e-05, 4.776e-05,\n",
       "       4.816e-05, 4.856e-05, 4.896e-05, 4.936e-05, 4.976e-05])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fab28abc-f951-4b5c-b238-876a42f3e9e7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fab28abc-f951-4b5c-b238-876a42f3e9e7' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.166 -1.141 ... -0.7305 -1.164</div><input id='attrs-c87479da-11a2-4b41-8239-309ee1f8a31c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c87479da-11a2-4b41-8239-309ee1f8a31c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0fd2db4f-75ce-4731-9f86-fab0d40b70cf' class='xr-var-data-in' type='checkbox'><label for='data-0fd2db4f-75ce-4731-9f86-fab0d40b70cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>I</dd><dt><span>long_name :</span></dt><dd>Voltage I0</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([-1.16569321, -1.14084856, -1.10898388, -1.10403762, -1.06113874,\n",
       "       -1.05803615, -1.0368637 , -1.02280362, -1.00904152, -1.00490132,\n",
       "       -0.98481534, -0.96191939, -0.96987543, -0.93633268, -0.92411969,\n",
       "       -0.92415877, -0.91095506, -0.89565022, -0.8951275 , -0.87275916,\n",
       "       -0.89093698, -0.87184025, -0.86481925, -0.86167562, -0.84944016,\n",
       "       -0.84135222, -0.83854714, -0.82813337, -0.82280508, -0.8382384 ,\n",
       "       -0.83033854, -0.81962482, -0.8125872 , -0.82112262, -0.80093307,\n",
       "       -0.80675232, -0.79224524, -0.80147142, -0.79313776, -0.78761651,\n",
       "       -0.78571373, -0.78500928, -0.79312164, -0.7795105 , -0.78222325,\n",
       "       -0.77661553, -0.7694978 , -0.7685491 , -0.7679062 , -0.76788471,\n",
       "       -0.75885833, -0.77414411, -0.74793552, -0.76220176, -0.76308549,\n",
       "       -0.74886126, -0.76515681, -0.75730044, -0.74937128, -0.7403703 ,\n",
       "       -0.76344358, -0.74619883, -0.75322423, -0.75255838, -0.75474206,\n",
       "       -0.7496849 , -0.7523659 , -0.73461212, -0.74488911, -0.73940352,\n",
       "       -0.73763752, -0.74374206, -0.73742452, -0.73655496, -0.74355252,\n",
       "       -0.73813483, -0.73866439, -0.73922814, -0.74246165, -0.74106888,\n",
       "       -0.73580313, -0.74422667, -0.73224084, -0.73754861, -0.73365071,\n",
       "       -0.75568051, -0.74332633, -0.73524475, -0.7500767 , -0.72881436,\n",
       "       -0.72753004, -0.74495896, -0.74218319, -0.7452809 , -0.73353933,\n",
       "       -0.73829507, -0.73532975, -0.73351295, -0.73659062, -0.73925256,\n",
       "       -0.74109086, -0.73307084, -0.74139863, -0.73536932, -0.73001612,\n",
       "       -0.73090327, -0.73810015, -0.72099951, -0.74512897, -0.73231607,\n",
       "       -0.73485589, -0.73125305, -0.73872887, -0.72901856, -0.73721886,\n",
       "       -0.7289448 , -0.74436981, -0.73118857, -0.74186273, -0.73086859,\n",
       "       -0.73491988, -0.72868246, -0.73703078, -0.73053298, -1.16396385])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y1</span></div><div class='xr-var-dims'>(dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2569 0.2138 ... -0.247 0.2671</div><input id='attrs-144a6525-c3f1-424c-82ca-15736d2700fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-144a6525-c3f1-424c-82ca-15736d2700fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-941d4c7b-3ab0-408d-ac5a-14f3a4d550f1' class='xr-var-data-in' type='checkbox'><label for='data-941d4c7b-3ab0-408d-ac5a-14f3a4d550f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>Q</dd><dt><span>long_name :</span></dt><dd>Voltage Q0</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([ 0.25686566,  0.21384465,  0.20350855,  0.19038593,  0.15224768,\n",
       "        0.13808891,  0.10529751,  0.09498876,  0.07786566,  0.07036102,\n",
       "        0.04861895,  0.03310699,  0.02891744, -0.00998241, -0.0289658 ,\n",
       "       -0.01719345, -0.03966194, -0.05226087, -0.0646126 , -0.0842511 ,\n",
       "       -0.06383977, -0.0779321 , -0.07970347, -0.08425794, -0.0935999 ,\n",
       "       -0.12724915, -0.13106204, -0.12002931, -0.13371715, -0.1303361 ,\n",
       "       -0.13216268, -0.14181436, -0.14275916, -0.14277235, -0.14491549,\n",
       "       -0.14763752, -0.17155056, -0.16616268, -0.17774499, -0.18483097,\n",
       "       -0.17180606, -0.19226527, -0.17967513, -0.18765413, -0.1916424 ,\n",
       "       -0.18724035, -0.1865447 , -0.20026575, -0.20063605, -0.19493405,\n",
       "       -0.21084709, -0.21526136, -0.21092281, -0.21215388, -0.21999902,\n",
       "       -0.22285833, -0.20664729, -0.22982022, -0.22637909, -0.22789155,\n",
       "       -0.20748705, -0.23320811, -0.23400684, -0.22432535, -0.22459257,\n",
       "       -0.21908305, -0.22634099, -0.23508989, -0.22248559, -0.23386419,\n",
       "       -0.24084856, -0.23708354, -0.23170542, -0.23450855, -0.23596873,\n",
       "       -0.24795848, -0.23428969, -0.24185589, -0.23504152, -0.24550904,\n",
       "       -0.23792037, -0.23227455, -0.24492379, -0.22591891, -0.2378681 ,\n",
       "       -0.22679971, -0.22749047, -0.24913434, -0.23028774, -0.23791402,\n",
       "       -0.24002149, -0.23414314, -0.23387689, -0.23870054, -0.22947875,\n",
       "       -0.24837567, -0.23775476, -0.23567123, -0.23493258, -0.23616219,\n",
       "       -0.23269614, -0.24493649, -0.23801075, -0.24519297, -0.2407406 ,\n",
       "       -0.24728969, -0.23906888, -0.24578896, -0.23322716, -0.23254519,\n",
       "       -0.24571519, -0.24905423, -0.23596873, -0.24317342, -0.24296825,\n",
       "       -0.23990425, -0.22876649, -0.22692526, -0.23137665, -0.25627943,\n",
       "       -0.23939766, -0.2548339 , -0.25334538, -0.24703957,  0.2671192 ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fab50e71-e27b-4d17-83a0-96b64068f3d8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-fab50e71-e27b-4d17-83a0-96b64068f3d8' class='xr-section-summary'  title='Expand/collapse section'>Indexes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-deef1132-fbc2-46c6-bc6a-ea15da66c4ed' class='xr-section-summary-in' type='checkbox'  checked><label for='section-deef1132-fbc2-46c6-bc6a-ea15da66c4ed' class='xr-section-summary' >Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>tuid :</span></dt><dd>20250316-041331-743-6a202a</dd><dt><span>name :</span></dt><dd></dd><dt><span>grid_2d :</span></dt><dd>False</dd><dt><span>grid_2d_uniformly_spaced :</span></dt><dd>False</dd><dt><span>1d_2_settables_uniformly_spaced :</span></dt><dd>False</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 3kB\n",
       "Dimensions:  (dim_0: 125)\n",
       "Coordinates:\n",
       "    x0       (dim_0) float64 1kB 1.6e-07 5.6e-07 9.6e-07 ... 4.936e-05 4.976e-05\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 1kB -1.166 -1.141 -1.109 ... -0.737 -0.7305 -1.164\n",
       "    y1       (dim_0) float64 1kB 0.2569 0.2138 0.2035 ... -0.2533 -0.247 0.2671\n",
       "Attributes:\n",
       "    tuid:                             20250316-041331-743-6a202a\n",
       "    name:                             \n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  False"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b17634b",
   "metadata": {},
   "source": [
    "The dataset coordinates and data variables are named as generic `x` and `y` parameters. You can click on the 'Show/Hide attributes' button next to the coordinates and variables to see what they refer to.\n",
    "\n",
    "(sec-tutorial-schedulegettable-repetitions)=\n",
    "## Repetitions\n",
    "\n",
    "Repetition defines how many times the defined schedule will run on the hardware. Running the schedule multiple times can be useful for example if the user would like to reduce errors of acquisitions by averaging the result of multiple measurements.\n",
    "\n",
    "There are multiple ways the repetitions can be set. They are not completely independent of each other, and which setting will be taken into account depends on how you create and use the schedule.\n",
    "\n",
    "1. {class}`~quantify_scheduler.device_under_test.quantum_device.QuantumDevice`: via `cfg_sched_repetitions` (by default it is `1024`),\n",
    "2. schedule function: via the `repetitions` function argument,\n",
    "3. {class}`~quantify_scheduler.schedules.schedule.Schedule` object: via the `repetitions` function argument of its constructor, or via its `repetitions` attribute directly,\n",
    "4. ({class}`~quantify_scheduler.gettables.ScheduleGettable`: currently, it is not possible to supply `repetitions` via `schedule_kwargs`).\n",
    "\n",
    "Ultimately, the {class}`~quantify_scheduler.schedules.schedule.Schedule` object is what governs the repetitions, via its `repetitions` attribute.\n",
    "\n",
    "When using a schedule function, the `repetitions` function argument sets the repetitions, provided that the schedule function passes it to the `Schedule` object. This is true for the pre-defined schedules, see {mod}`!quantify_scheduler.schedules`.\n",
    "\n",
    "However, if the experiment is run using `ScheduleGettable`, this `repetitions` function argument is set to `QuantumDevice.cfg_sched_repetitions`. Hence, typically, the schedule will run `QuantumDevice.cfg_sched_repetitions` times.\n",
    "\n",
    "### Possible mistake: ignoring `repetitions` argument\n",
    "\n",
    "Keep in mind that the schedule function should pass the `repetitions` argument to the `Schedule` initializer, otherwise both `QuantumDevice.cfg_sched_repetitions` and the `repetitions` argument of the schedule function will be ignored. For example, in the following setup, the `repetitions` will always be `1` (default for the `Schedule` object), even if `cfg_sched_repetitions` is set to `2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c7e230cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_scheduler import QuantumDevice, ScheduleGettable\n",
    "\n",
    "def schedule_function(q0: str, repetitions: int):\n",
    "    schedule = Schedule(\"Example schedule\")\n",
    "    schedule.add(Measure(q0, acq_index=0))\n",
    "    return schedule\n",
    "\n",
    "quantum_device = QuantumDevice(name=\"quantum_sample\")\n",
    "quantum_device.cfg_sched_repetitions(2)\n",
    "\n",
    "schedule_gettable = ScheduleGettable(\n",
    "    quantum_device=quantum_device,\n",
    "    schedule_function=schedule_function,\n",
    "    schedule_kwargs={\"q0\": \"q0\"},\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d01c34b",
   "metadata": {},
   "source": [
    "### Possible mistake: ignoring `cfg_sched_repetitions` default value\n",
    "\n",
    "Also note, that the default value of the `repetitions` argument of the schedule function will be ignored if `ScheduleGettable` is used, and it will be set to `QuantumDevice.cfg_sched_repetitions`. For example, in the following setup, `repetitions` will be `1024` (default for `QuantumDevice`), even if the default argument for `repetitions` is `2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "be7e15b3",
   "metadata": {
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "quantum_device.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "9ab05b53",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_scheduler import QuantumDevice, ScheduleGettable\n",
    "\n",
    "def schedule_function(q0: str, repetitions: int = 2):\n",
    "    schedule = Schedule(\"Example schedule\", repetitions=repetitions)\n",
    "    schedule.add(Measure(q0, acq_index=0))\n",
    "    return schedule\n",
    "\n",
    "quantum_device = QuantumDevice(name=\"quantum_sample\")\n",
    "\n",
    "schedule_gettable = ScheduleGettable(\n",
    "    quantum_device=quantum_device,\n",
    "    schedule_function=schedule_function,\n",
    "    schedule_kwargs={\"q0\": \"q0\"},\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5592c080",
   "metadata": {},
   "source": [
    "(sec-schedulegettable-2dsweep-usage)=\n",
    "\n",
    "## 2D (and ND) measurement loops"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "58496a71",
   "metadata": {
    "mystnb": {
     "code_prompt_show": "Set up the quantum device, dummy hardware and hardware configuration"
    },
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "from qblox_instruments import Cluster, ClusterType, DummyBinnedAcquisitionData\n",
    "\n",
    "from quantify_scheduler import BasicTransmonElement, InstrumentCoordinator, QuantumDevice\n",
    "from quantify_scheduler.qblox import ClusterComponent\n",
    "\n",
    "\n",
    "single_qubit_device.close_all()\n",
    "\n",
    "# Device parameters\n",
    "Q0_ACQ_DELAY = 100e-9\n",
    "Q0_FREQ_01 = 4e9\n",
    "Q0_READOUT_AMP = 0.1\n",
    "Q0_READOUT_FREQ = 4.3e9\n",
    "Q0_PI_PULSE_AMP = 0.15\n",
    "Q0_LO_FREQ_QUBIT = 3.9e9\n",
    "Q0_LO_FREQ_READOUT = 4.5e9\n",
    "\n",
    "Q1_ACQ_DELAY = 120e-9\n",
    "Q1_FREQ_01 = 4.1e9\n",
    "Q1_READOUT_AMP = 0.1\n",
    "Q1_READOUT_FREQ = 3.8e9\n",
    "Q1_PI_PULSE_AMP = 0.15\n",
    "Q1_LO_FREQ_QUBIT = 4.1e9\n",
    "Q1_LO_FREQ_READOUT = 3.8e9\n",
    "\n",
    "two_qubit_device = QuantumDevice(\"two_qubit_device\")\n",
    "\n",
    "q0 = BasicTransmonElement(\"q0\")\n",
    "q0.measure.acq_channel(0)\n",
    "q0.measure.pulse_amp(Q0_READOUT_AMP)\n",
    "q0.clock_freqs.readout(Q0_READOUT_FREQ)\n",
    "q0.clock_freqs.f01(Q0_FREQ_01)\n",
    "q0.measure.acq_delay(Q0_ACQ_DELAY)\n",
    "q0.rxy.amp180(Q0_PI_PULSE_AMP)\n",
    "\n",
    "q1 = BasicTransmonElement(\"q1\")\n",
    "q1.measure.acq_channel(1)  # Note that we're specifying that measurements on q1 should use a different measurement channel\n",
    "q1.measure.pulse_amp(Q1_READOUT_AMP)\n",
    "q1.clock_freqs.readout(Q1_READOUT_FREQ)\n",
    "q1.clock_freqs.f01(Q1_FREQ_01)\n",
    "q1.measure.acq_delay(Q1_ACQ_DELAY)\n",
    "q1.rxy.amp180(Q1_PI_PULSE_AMP)\n",
    "\n",
    "two_qubit_device.add_element(q0)\n",
    "two_qubit_device.add_element(q1)\n",
    "\n",
    "# We will need to adjust the hardware configuration.\n",
    "\n",
    "# Note: if you are connecting to an actual cluster, you would provide the\n",
    "# 'identifier' argument (the ip address, device name or serial number) instead\n",
    "# of the 'dummy_cfg' argument.\n",
    "cluster = Cluster(\n",
    "    \"cluster\",\n",
    "    dummy_cfg={\n",
    "        1: ClusterType.CLUSTER_QRM_RF,\n",
    "        2: ClusterType.CLUSTER_QCM_RF,\n",
    "        3: ClusterType.CLUSTER_QRM_RF,\n",
    "        4: ClusterType.CLUSTER_QCM_RF,\n",
    "    },\n",
    ")\n",
    "\n",
    "ic_cluster = ClusterComponent(cluster)\n",
    "\n",
    "# Temporarily fixing dummy cluster's deficiency.\n",
    "cluster.start_sequencer = lambda : start_dummy_cluster_armed_sequencers(ic_cluster)\n",
    "\n",
    "instrument_coordinator = InstrumentCoordinator(\"instrument_coordinator\")\n",
    "instrument_coordinator.add_component(ic_cluster)\n",
    "\n",
    "two_qubit_device.instr_instrument_coordinator(instrument_coordinator.name)\n",
    "\n",
    "hardware_cfg = {\n",
    "    \"version\": \"0.2\",\n",
    "    \"config_type\": \"quantify_scheduler.backends.qblox_backend.QbloxHardwareCompilationConfig\",\n",
    "    \"hardware_description\": {\n",
    "        f\"{cluster.name}\": {\n",
    "            \"instrument_type\": \"Cluster\",\n",
    "            \"modules\": {\n",
    "                \"1\": {\n",
    "                    \"instrument_type\": \"QRM_RF\"\n",
    "                },\n",
    "                \"2\": {\n",
    "                    \"instrument_type\": \"QCM_RF\"\n",
    "                },\n",
    "                \"3\": {\n",
    "                    \"instrument_type\": \"QRM_RF\"\n",
    "                },\n",
    "                \"4\": {\n",
    "                    \"instrument_type\": \"QCM_RF\"\n",
    "                }\n",
    "            },\n",
    "            \"ref\": \"internal\"\n",
    "        }\n",
    "    },\n",
    "    \"hardware_options\": {\n",
    "        \"modulation_frequencies\": {\n",
    "            \"q0:res-q0.ro\": {\n",
    "                \"lo_freq\": Q0_LO_FREQ_READOUT\n",
    "            },\n",
    "            \"q0:mw-q0.01\": {\n",
    "                \"lo_freq\": Q0_LO_FREQ_QUBIT\n",
    "            },\n",
    "            \"q1:res-q1.ro\": {\n",
    "                \"lo_freq\": Q1_LO_FREQ_READOUT\n",
    "            },\n",
    "            \"q1:mw-q1.01\": {\n",
    "                \"lo_freq\": Q1_LO_FREQ_QUBIT\n",
    "            }\n",
    "        }\n",
    "    },\n",
    "    \"connectivity\": {\n",
    "        \"graph\": [\n",
    "            [f\"{cluster.name}.module1.complex_output_0\", \"q0:res\"],\n",
    "            [f\"{cluster.name}.module1.complex_input_0\", \"q0:res\"],\n",
    "            [f\"{cluster.name}.module2.complex_output_0\", \"q0:mw\"],\n",
    "            [f\"{cluster.name}.module3.complex_output_0\", \"q1:res\"],\n",
    "            [f\"{cluster.name}.module3.complex_input_0\", \"q1:res\"],\n",
    "            [f\"{cluster.name}.module4.complex_output_0\", \"q1:mw\"]\n",
    "        ]\n",
    "    }\n",
    "}\n",
    "\n",
    "\n",
    "two_qubit_device.hardware_config(hardware_cfg)\n",
    "\n",
    "ic_cluster.instrument.set_dummy_binned_acquisition_data(\n",
    "    slot_idx=1, sequencer=0, acq_index_name=\"0\", data=[DummyBinnedAcquisitionData(data=(0.0, 0.0), thres=0, avg_cnt=0)]\n",
    ")\n",
    "ic_cluster.instrument.set_dummy_binned_acquisition_data(\n",
    "    slot_idx=3, sequencer=0, acq_index_name=\"0\", data=[DummyBinnedAcquisitionData(data=(0.0, 0.0), thres=0, avg_cnt=0)]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "308caa32",
   "metadata": {},
   "source": [
    "2D and higher-dimensional measurement loops are easy to realize. Below we show an example Chevron experiment, which is a type of two-qubit experiment often performed on transmon qubits. The experiment includes a square pulse, and we want to vary both its amplitude and duration in a 2D grid. We have already set up a two-qubit {class}`~quantify_scheduler.device_under_test.quantum_device.QuantumDevice` under the variable name `two_qubit_device`.\n",
    "\n",
    "We define simple schedule below with a parameterized amplitude and duration of the square pulse. `duration` and `amp` are scalars, so for each measurement point the schedule will be recompiled."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "552c8df6",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_scheduler import Schedule\n",
    "from quantify_scheduler.operations import Measure, Reset, SquarePulse, X, X90\n",
    "\n",
    "def chevron_schedule_not_batched(duration, amp, repetitions=1):\n",
    "    sched = Schedule(\"Chevron Experiment\", repetitions=repetitions)\n",
    "\n",
    "    acq_idx = 0\n",
    "\n",
    "    reset = sched.add(Reset(\"q0\", \"q1\"))\n",
    "    sched.add(X(\"q0\"), ref_op=reset, ref_pt=\"end\")  # Start at the end of the reset\n",
    "    # We specify a clock for tutorial purposes, Chevron experiments do not necessarily use modulated square pulses\n",
    "    square = sched.add(SquarePulse(amp=amp, duration=duration, port=\"q0:mw\", clock=\"q0.01\"))\n",
    "    sched.add(X90(\"q0\"), ref_op=square)  # Start at the end of the square pulse\n",
    "    sched.add(X90(\"q1\"), ref_op=square)\n",
    "    sched.add(Measure(\"q0\", acq_index=acq_idx), label=f\"M q0 {acq_idx}\")\n",
    "    sched.add(\n",
    "        Measure(\"q1\", acq_index=acq_idx),\n",
    "        label=f\"M q1 {acq_idx}\",\n",
    "        ref_pt=\"start\",  # Start at the same time as the other measure\n",
    "    )\n",
    "\n",
    "    return sched"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2af165a3",
   "metadata": {},
   "source": [
    "We set up a non-batched measurement with {class}`~quantify_core.measurement.control.MeasurementControl` and a {class}`~quantify_scheduler.gettables.ScheduleGettable`. For this {class}`~quantify_scheduler.gettables.ScheduleGettable`, notice the keyword argument `num_channels=2`, which is needed since we specified in the quantum device elements that the measurements on `\"q0\"` and `\"q1\"` should end up in two different channels.\n",
    "\n",
    "In addition, we used another new argument in the {class}`~quantify_scheduler.gettables.ScheduleGettable`: `real_imag=False`. `real_imag` can be used to transform the acquisition data. If it is `True` (the default), the I and Q values will be returned, and if it is `False`, the data will be transformed to the absolute value and the phase (in degrees, in the interval `(-180, 180]`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "92d63076",
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting iterative measurement...\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "dc43604374d74ce385bbe4ef9616a04e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Completed:   0%|           [ elapsed time: 00:00 | time left: ? ] it"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "measurement_control = MeasurementControl(\"measurement_control\")\n",
    "\n",
    "# Configure the settables\n",
    "duration = ManualParameter(\"duration\", label=\"Duration\", unit=\"s\")\n",
    "duration.batched = False\n",
    "\n",
    "durations = np.linspace(start=20e-9, stop=60e-9, num=6)\n",
    "\n",
    "amplitude = ManualParameter(\"amplitude\", label=\"Amplitude\", unit=\"V\")\n",
    "amplitude.batched = False\n",
    "\n",
    "amplitudes = np.linspace(start=0.1, stop=1.0, num=10)\n",
    "\n",
    "# Configure the gettable\n",
    "gettable = ScheduleGettable(\n",
    "    quantum_device=two_qubit_device,\n",
    "    schedule_function=chevron_schedule_not_batched,\n",
    "    schedule_kwargs={\"duration\": duration, \"amp\": amplitude},\n",
    "    batched=False,\n",
    "    real_imag=False,\n",
    "    num_channels=2,\n",
    ")\n",
    "\n",
    "# Configure MeasurementControl\n",
    "measurement_control.settables([duration, amplitude])\n",
    "measurement_control.setpoints_grid([durations, amplitudes])  # note: setpoints_grid instead of setpoints\n",
    "measurement_control.gettables(gettable)\n",
    "\n",
    "# Run!\n",
    "dataset = measurement_control.run()\n",
    "dset_grid = dh.to_gridded_dataset(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "12a3921d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "html[data-theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2kB\n",
       "Dimensions:  (x0: 6, x1: 10)\n",
       "Coordinates:\n",
       "  * x0       (x0) float64 48B 2e-08 2.8e-08 3.6e-08 4.4e-08 5.2e-08 6e-08\n",
       "  * x1       (x1) float64 80B 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0\n",
       "Data variables:\n",
       "    y0       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    y1       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    y2       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    y3       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "Attributes:\n",
       "    tuid:                             20250316-041332-833-bd8c27\n",
       "    name:                             \n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         True\n",
       "    1d_2_settables_uniformly_spaced:  False\n",
       "    xlen:                             6\n",
       "    ylen:                             10</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-bf5bdb7d-806d-4f45-9521-c01c5d136664' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-bf5bdb7d-806d-4f45-9521-c01c5d136664' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x0</span>: 6</li><li><span class='xr-has-index'>x1</span>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f49edb4b-c358-49da-8a27-581d7c0d23c2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f49edb4b-c358-49da-8a27-581d7c0d23c2' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x0</span></div><div class='xr-var-dims'>(x0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e-08 2.8e-08 ... 5.2e-08 6e-08</div><input id='attrs-2e97f502-ca46-49a2-a562-d8a3546cef48' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e97f502-ca46-49a2-a562-d8a3546cef48' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da31b1b9-1617-4047-9425-56cefb65c69b' class='xr-var-data-in' type='checkbox'><label for='data-da31b1b9-1617-4047-9425-56cefb65c69b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>duration</dd><dt><span>long_name :</span></dt><dd>Duration</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([2.0e-08, 2.8e-08, 3.6e-08, 4.4e-08, 5.2e-08, 6.0e-08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1 0.2 0.3 0.4 ... 0.7 0.8 0.9 1.0</div><input id='attrs-1b057112-03d0-4c23-8bc6-2c6a37bde7ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b057112-03d0-4c23-8bc6-2c6a37bde7ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d626546e-4928-40e7-90fe-8ed4b36f658c' class='xr-var-data-in' type='checkbox'><label for='data-d626546e-4928-40e7-90fe-8ed4b36f658c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>amplitude</dd><dt><span>long_name :</span></dt><dd>Amplitude</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dbeec049-4fe8-418a-b3a1-2c37bd22d62c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dbeec049-4fe8-418a-b3a1-2c37bd22d62c' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-aacf2c8e-7d67-498a-97ee-4ef7272c4030' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aacf2c8e-7d67-498a-97ee-4ef7272c4030' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eaaf603-00a6-492a-a8e0-743df0dd5491' class='xr-var-data-in' type='checkbox'><label for='data-5eaaf603-00a6-492a-a8e0-743df0dd5491' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>magn</dd><dt><span>long_name :</span></dt><dd>Magnitude0</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y1</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-1e4b8a02-efaa-40ca-9640-9b5c72010950' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e4b8a02-efaa-40ca-9640-9b5c72010950' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52faca8b-233a-495c-b978-ebdc350b3869' class='xr-var-data-in' type='checkbox'><label for='data-52faca8b-233a-495c-b978-ebdc350b3869' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>phase</dd><dt><span>long_name :</span></dt><dd>Phase0</dd><dt><span>units :</span></dt><dd>deg</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y2</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-4819246a-9b34-420c-bbe7-947d07c79496' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4819246a-9b34-420c-bbe7-947d07c79496' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-805f790c-44dc-44a5-9804-9da5a0e8595a' class='xr-var-data-in' type='checkbox'><label for='data-805f790c-44dc-44a5-9804-9da5a0e8595a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>magn</dd><dt><span>long_name :</span></dt><dd>Magnitude1</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y3</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-55f146b2-ec30-4267-a196-d106516b0724' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55f146b2-ec30-4267-a196-d106516b0724' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e4c06bd-ecc4-4cc4-b966-f1273ff7034b' class='xr-var-data-in' type='checkbox'><label for='data-1e4c06bd-ecc4-4cc4-b966-f1273ff7034b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>phase</dd><dt><span>long_name :</span></dt><dd>Phase1</dd><dt><span>units :</span></dt><dd>deg</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],\n",
       "       [0., 0., 0., 0., 0., 0., 0., 0., 0., 0.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63bdb7c8-b3a0-4c57-8112-9c5307ee1658' class='xr-section-summary-in' type='checkbox'  ><label for='section-63bdb7c8-b3a0-4c57-8112-9c5307ee1658' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ece9690f-3394-47ab-abf8-8f870b3e002c' class='xr-index-data-in' type='checkbox'/><label for='index-ece9690f-3394-47ab-abf8-8f870b3e002c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([2e-08, 2.8e-08, 3.6e-08, 4.4e-08, 5.1999999999999996e-08, 6e-08], dtype=&#x27;float64&#x27;, name=&#x27;x0&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b4a20daa-b6eb-42ed-9698-79d7682cc3f1' class='xr-index-data-in' type='checkbox'/><label for='index-b4a20daa-b6eb-42ed-9698-79d7682cc3f1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.1, 0.2, 0.30000000000000004, 0.4, 0.5, 0.6, 0.7000000000000001, 0.8,\n",
       "       0.9, 1.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x1&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f91c8760-2384-4188-9dcc-d52a97f794f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f91c8760-2384-4188-9dcc-d52a97f794f8' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>tuid :</span></dt><dd>20250316-041332-833-bd8c27</dd><dt><span>name :</span></dt><dd></dd><dt><span>grid_2d :</span></dt><dd>False</dd><dt><span>grid_2d_uniformly_spaced :</span></dt><dd>True</dd><dt><span>1d_2_settables_uniformly_spaced :</span></dt><dd>False</dd><dt><span>xlen :</span></dt><dd>6</dd><dt><span>ylen :</span></dt><dd>10</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2kB\n",
       "Dimensions:  (x0: 6, x1: 10)\n",
       "Coordinates:\n",
       "  * x0       (x0) float64 48B 2e-08 2.8e-08 3.6e-08 4.4e-08 5.2e-08 6e-08\n",
       "  * x1       (x1) float64 80B 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0\n",
       "Data variables:\n",
       "    y0       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    y1       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    y2       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    y3       (x0, x1) float64 480B 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
       "Attributes:\n",
       "    tuid:                             20250316-041332-833-bd8c27\n",
       "    name:                             \n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         True\n",
       "    1d_2_settables_uniformly_spaced:  False\n",
       "    xlen:                             6\n",
       "    ylen:                             10"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset_grid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17ee19c4",
   "metadata": {},
   "source": [
    "As expected, this dataset contains double the amount of coordinates and data variables (note that the actual data has been mocked and set to 0.0). The two coordinates refer to the settables, `duration` and `amplitude`. With `real_imag` now set to `False`, the data variables contain the magnitude and phase (as opposed to the I and Q voltages) for measurements on `\"q0\"` and `\"q1\"`.\n",
    "\n",
    "### Batched 2D experiment\n",
    "\n",
    "Since this measurement is not batched, it's rather slow. Let's make this faster with (partial) batching.\n",
    "\n",
    "We will batch the amplitudes together, so we change the amplitudes parameter in the schedule function to an array."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "2291634f",
   "metadata": {
    "mystnb": {
     "code_prompt_show": "Provide the dummy hardware with acquisition data"
    },
    "tags": [
     "hide-cell"
    ]
   },
   "outputs": [],
   "source": [
    "from qblox_instruments import DummyBinnedAcquisitionData\n",
    "\n",
    "\n",
    "def get_dummy_binned_acquisition_data(real: float, imag: float):\n",
    "    return DummyBinnedAcquisitionData(data=(real, imag), thres=0, avg_cnt=0)\n",
    "\n",
    "ic_cluster.instrument.set_dummy_binned_acquisition_data(\n",
    "    slot_idx=1, sequencer=0, acq_index_name=\"0\", data=[get_dummy_binned_acquisition_data(re * 10, im * 10) for re, im in zip(range(-5, 5), range(5, -5, -1))]\n",
    ")\n",
    "ic_cluster.instrument.set_dummy_binned_acquisition_data(\n",
    "    slot_idx=3, sequencer=0, acq_index_name=\"0\", data=[get_dummy_binned_acquisition_data(re * 10, im * 10) for re, im in zip(range(-5, 5), range(5, -5, -1))]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2151e2c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def chevron_schedule_batched(duration, amps, repetitions=1):\n",
    "    sched = Schedule(\"Chevron Experiment\", repetitions=repetitions)\n",
    "\n",
    "    acq_idx = 0\n",
    "\n",
    "    for amp in amps:\n",
    "        reset = sched.add(Reset(\"q0\", \"q1\"))\n",
    "        sched.add(X(\"q0\"), ref_op=reset, ref_pt=\"end\")\n",
    "        square = sched.add(SquarePulse(amp=amp, duration=duration, port=\"q0:mw\", clock=\"q0.01\"))\n",
    "        sched.add(X90(\"q0\"), ref_op=square)\n",
    "        sched.add(X90(\"q1\"), ref_op=square)\n",
    "        sched.add(Measure(\"q0\", acq_index=acq_idx), label=f\"M q0 {acq_idx}\")\n",
    "        sched.add(\n",
    "            Measure(\"q1\", acq_index=acq_idx),\n",
    "            label=f\"M q1 {acq_idx}\",\n",
    "            ref_pt=\"start\",\n",
    "        )\n",
    "\n",
    "        acq_idx += 1\n",
    "\n",
    "    return sched"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2803f70b",
   "metadata": {},
   "source": [
    "We specify that we want to batch the amplitudes by setting ``amplitude.batched = True`` and ``batched=True``as keyword argument for the gettable. Finally, we run this experiment just as before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1cc7a8b0",
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting batched measurement...\n",
      "Iterative settable(s) [outer loop(s)]:\n",
      "\t duration \n",
      "Batched settable(s):\n",
      "\t amplitude \n",
      "Batch size limit: 60\n",
      "\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "945ed98138954af2b375cf2570c87bde",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Completed:   0%|           [ elapsed time: 00:00 | time left: ? ] it"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the settables\n",
    "duration = ManualParameter(\"duration\", label=\"Duration\", unit=\"s\")\n",
    "duration.batched = False\n",
    "\n",
    "durations = np.linspace(start=20e-9, stop=60e-9, num=6)\n",
    "\n",
    "amplitude = ManualParameter(\"amplitude\", label=\"Amplitude\", unit=\"V\")\n",
    "amplitude.batched = True\n",
    "\n",
    "amplitudes = np.linspace(start=0.1, stop=1.0, num=10)\n",
    "\n",
    "# Configure the gettable\n",
    "gettable = ScheduleGettable(\n",
    "    quantum_device=two_qubit_device,\n",
    "    schedule_function=chevron_schedule_batched,\n",
    "    schedule_kwargs={\"duration\": duration, \"amps\": amplitude},\n",
    "    batched=True,\n",
    "    real_imag=False,\n",
    "    data_labels=[\"Magnitude Q0\", \"Phase Q0\", \"Magnitude Q1\", \"Phase Q1\"],\n",
    "    num_channels=2,\n",
    ")\n",
    "\n",
    "# Configure MeasurementControl\n",
    "measurement_control.settables([duration, amplitude])\n",
    "measurement_control.setpoints_grid([durations, amplitudes])\n",
    "measurement_control.gettables(gettable)\n",
    "\n",
    "# Run!\n",
    "dataset = measurement_control.run()\n",
    "dset_grid = dh.to_gridded_dataset(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "25ce52b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
       "<defs>\n",
       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
       "</symbol>\n",
       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
       "<style>/* CSS stylesheet for displaying xarray objects in jupyterlab.\n",
       " *\n",
       " */\n",
       "\n",
       ":root {\n",
       "  --xr-font-color0: var(--jp-content-font-color0, rgba(0, 0, 0, 1));\n",
       "  --xr-font-color2: var(--jp-content-font-color2, rgba(0, 0, 0, 0.54));\n",
       "  --xr-font-color3: var(--jp-content-font-color3, rgba(0, 0, 0, 0.38));\n",
       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "html[data-theme=dark],\n",
       "body[data-theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2kB\n",
       "Dimensions:  (x0: 6, x1: 10)\n",
       "Coordinates:\n",
       "  * x0       (x0) float64 48B 2e-08 2.8e-08 3.6e-08 4.4e-08 5.2e-08 6e-08\n",
       "  * x1       (x1) float64 80B 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0\n",
       "Data variables:\n",
       "    y0       (x0, x1) float64 480B 0.07071 0.05657 0.04243 ... 0.04243 0.05657\n",
       "    y1       (x0, x1) float64 480B 135.0 135.0 135.0 135.0 ... -45.0 -45.0 -45.0\n",
       "    y2       (x0, x1) float64 480B 0.07071 0.05657 0.04243 ... 0.04243 0.05657\n",
       "    y3       (x0, x1) float64 480B 135.0 135.0 135.0 135.0 ... -45.0 -45.0 -45.0\n",
       "Attributes:\n",
       "    tuid:                             20250316-041337-301-b1f7f0\n",
       "    name:                             \n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         True\n",
       "    1d_2_settables_uniformly_spaced:  False\n",
       "    xlen:                             6\n",
       "    ylen:                             10</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9385767e-bfca-4597-b232-491489690816' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9385767e-bfca-4597-b232-491489690816' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x0</span>: 6</li><li><span class='xr-has-index'>x1</span>: 10</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-42300f3e-5490-47f0-9d59-7f92ab4d699b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-42300f3e-5490-47f0-9d59-7f92ab4d699b' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x0</span></div><div class='xr-var-dims'>(x0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2e-08 2.8e-08 ... 5.2e-08 6e-08</div><input id='attrs-538c4403-b85b-47ba-a1ce-2dd292fcc000' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-538c4403-b85b-47ba-a1ce-2dd292fcc000' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c6e42b7-c9ae-4091-b1f0-5c972e375915' class='xr-var-data-in' type='checkbox'><label for='data-0c6e42b7-c9ae-4091-b1f0-5c972e375915' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>duration</dd><dt><span>long_name :</span></dt><dd>Duration</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([2.0e-08, 2.8e-08, 3.6e-08, 4.4e-08, 5.2e-08, 6.0e-08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.1 0.2 0.3 0.4 ... 0.7 0.8 0.9 1.0</div><input id='attrs-1300c964-21a8-4d3a-8209-3b4070973404' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1300c964-21a8-4d3a-8209-3b4070973404' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad2135fb-407b-44bb-af90-064e6563ad1f' class='xr-var-data-in' type='checkbox'><label for='data-ad2135fb-407b-44bb-af90-064e6563ad1f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>amplitude</dd><dt><span>long_name :</span></dt><dd>Amplitude</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>array([0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1. ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4681f520-6ee6-442a-a568-f2eab7c84259' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4681f520-6ee6-442a-a568-f2eab7c84259' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y0</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07071 0.05657 ... 0.04243 0.05657</div><input id='attrs-d99eb668-00f7-4145-ac47-3e25f0f62846' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d99eb668-00f7-4145-ac47-3e25f0f62846' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d598c3e4-4039-480d-8fcb-5c9b847e7193' class='xr-var-data-in' type='checkbox'><label for='data-d598c3e4-4039-480d-8fcb-5c9b847e7193' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>magn</dd><dt><span>long_name :</span></dt><dd>Magnitude Q0</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([[0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y1</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>135.0 135.0 135.0 ... -45.0 -45.0</div><input id='attrs-9fc9f1bc-bf93-4be3-9e82-48b573202dae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fc9f1bc-bf93-4be3-9e82-48b573202dae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20b951c3-47bd-4878-81fa-43418d634a44' class='xr-var-data-in' type='checkbox'><label for='data-20b951c3-47bd-4878-81fa-43418d634a44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>phase</dd><dt><span>long_name :</span></dt><dd>Phase Q0</dd><dt><span>units :</span></dt><dd>deg</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([[135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y2</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07071 0.05657 ... 0.04243 0.05657</div><input id='attrs-e73aaf70-b151-4b7f-b974-e9a0a6d3f1a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e73aaf70-b151-4b7f-b974-e9a0a6d3f1a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb6c5942-9fe7-444b-b61d-76086e328da7' class='xr-var-data-in' type='checkbox'><label for='data-cb6c5942-9fe7-444b-b61d-76086e328da7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>magn</dd><dt><span>long_name :</span></dt><dd>Magnitude Q1</dd><dt><span>units :</span></dt><dd>V</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([[0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854],\n",
       "       [0.07071068, 0.05656854, 0.04242641, 0.02828427, 0.01414214,\n",
       "        0.        , 0.01414214, 0.02828427, 0.04242641, 0.05656854]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y3</span></div><div class='xr-var-dims'>(x0, x1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>135.0 135.0 135.0 ... -45.0 -45.0</div><input id='attrs-6bc05da8-435f-4407-9e85-396fba47d140' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bc05da8-435f-4407-9e85-396fba47d140' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74bed0c9-8a2b-4b83-847e-e94d89870ecf' class='xr-var-data-in' type='checkbox'><label for='data-74bed0c9-8a2b-4b83-847e-e94d89870ecf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>name :</span></dt><dd>phase</dd><dt><span>long_name :</span></dt><dd>Phase Q1</dd><dt><span>units :</span></dt><dd>deg</dd><dt><span>batched :</span></dt><dd>True</dd><dt><span>batch_size :</span></dt><dd>1024</dd></dl></div><div class='xr-var-data'><pre>array([[135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.],\n",
       "       [135., 135., 135., 135., 135.,   0., -45., -45., -45., -45.]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-90ae583a-ead5-406b-ac5f-9d65af3106ec' class='xr-section-summary-in' type='checkbox'  ><label for='section-90ae583a-ead5-406b-ac5f-9d65af3106ec' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x0</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-191cbf2c-dad6-48b2-8ccb-0671885499b3' class='xr-index-data-in' type='checkbox'/><label for='index-191cbf2c-dad6-48b2-8ccb-0671885499b3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([2e-08, 2.8e-08, 3.6e-08, 4.4e-08, 5.1999999999999996e-08, 6e-08], dtype=&#x27;float64&#x27;, name=&#x27;x0&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8ace625b-4438-4ffa-9246-bbe0c632192d' class='xr-index-data-in' type='checkbox'/><label for='index-8ace625b-4438-4ffa-9246-bbe0c632192d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([0.1, 0.2, 0.30000000000000004, 0.4, 0.5, 0.6, 0.7000000000000001, 0.8,\n",
       "       0.9, 1.0],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;x1&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b07c37dc-0d79-4dc1-8222-eb695ff70cd7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b07c37dc-0d79-4dc1-8222-eb695ff70cd7' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>tuid :</span></dt><dd>20250316-041337-301-b1f7f0</dd><dt><span>name :</span></dt><dd></dd><dt><span>grid_2d :</span></dt><dd>False</dd><dt><span>grid_2d_uniformly_spaced :</span></dt><dd>True</dd><dt><span>1d_2_settables_uniformly_spaced :</span></dt><dd>False</dd><dt><span>xlen :</span></dt><dd>6</dd><dt><span>ylen :</span></dt><dd>10</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2kB\n",
       "Dimensions:  (x0: 6, x1: 10)\n",
       "Coordinates:\n",
       "  * x0       (x0) float64 48B 2e-08 2.8e-08 3.6e-08 4.4e-08 5.2e-08 6e-08\n",
       "  * x1       (x1) float64 80B 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0\n",
       "Data variables:\n",
       "    y0       (x0, x1) float64 480B 0.07071 0.05657 0.04243 ... 0.04243 0.05657\n",
       "    y1       (x0, x1) float64 480B 135.0 135.0 135.0 135.0 ... -45.0 -45.0 -45.0\n",
       "    y2       (x0, x1) float64 480B 0.07071 0.05657 0.04243 ... 0.04243 0.05657\n",
       "    y3       (x0, x1) float64 480B 135.0 135.0 135.0 135.0 ... -45.0 -45.0 -45.0\n",
       "Attributes:\n",
       "    tuid:                             20250316-041337-301-b1f7f0\n",
       "    name:                             \n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         True\n",
       "    1d_2_settables_uniformly_spaced:  False\n",
       "    xlen:                             6\n",
       "    ylen:                             10"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset_grid"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e676d884",
   "metadata": {},
   "source": [
    "The shape of the dataset is no different from the previous (non-batched) experiment, but the metadata is a little different. Some coordinates and data variables now have the `batched=True` attribute. We also introduced another keyword argument: the `data_labels`. These `data_labels` are picked up by the {class}`~quantify_core.measurement.control.MeasurementControl`and end up in the {class}`xarray.Dataset` as the \"long_name\" of attributes. For example, `\"y0\"`s label can be accessed through `dataset[\"y0\"].attrs[\"long_name\"]`. The various plotting features of `quantify-core` will use this name to get labels for the figure axes."
   ]
  }
 ],
 "metadata": {
  "file_format": "mystnb",
  "kernelspec": {
   "display_name": "python3",
   "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": "3.9.21"
  },
  "source_map": [
   6,
   34,
   141,
   149,
   166,
   170,
   195,
   199,
   247,
   251,
   263,
   273,
   299,
   303,
   322,
   332,
   356,
   364,
   369,
   373,
   375,
   401,
   417,
   423,
   430,
   445,
   451,
   588,
   594,
   617,
   623,
   660,
   662,
   672,
   692,
   714,
   718,
   754,
   756
  ],
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "044204a8b2bd47da8c91e1db738e8e9f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_3bfa67ec983a4e348b778d4443a08758",
       "max": 100.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_90d47763e6c94be19a58d37b0c7323b9",
       "tabbable": null,
       "tooltip": null,
       "value": 100.0
      }
     },
     "1455e2cbc78e4c35b8169d4f4fa32c4e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "background": null,
       "description_width": "",
       "font_size": null,
       "text_color": null
      }
     },
     "2a3fac78a9b94775a1d67544e425cd45": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "background": null,
       "description_width": "",
       "font_size": null,
       "text_color": null
      }
     },
     "2b046e1baf4a4d99afaa0b6d8ceef85e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "2f3b5d8b3daa49f8aec4841b43d3f547": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "340cf62c1ab34a6898019a0a5992f577": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_95a71388192946db886e809b51f06a86",
       "placeholder": "​",
       "style": "IPY_MODEL_3f53a6ff2f0f4f31bae8da490cd8e6e8",
       "tabbable": null,
       "tooltip": null,
       "value": "Completed: 100%"
      }
     },
     "3bfa67ec983a4e348b778d4443a08758": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "3e9a9304fe9e4fe292162dd8073e1026": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "background": null,
       "description_width": "",
       "font_size": null,
       "text_color": null
      }
     },
     "3f53a6ff2f0f4f31bae8da490cd8e6e8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "background": null,
       "description_width": "",
       "font_size": null,
       "text_color": null
      }
     },
     "46cc2cbd3d4d4f8d9b69bf3c67d710cd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_c4fc2fecb9c9445c8b2d09b8c660027a",
       "placeholder": "​",
       "style": "IPY_MODEL_2a3fac78a9b94775a1d67544e425cd45",
       "tabbable": null,
       "tooltip": null,
       "value": "Completed: 100%"
      }
     },
     "48476132d16a4ffcb9dabb02722bf9bc": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_b149c914dff04931b4376ec55edb334b",
       "placeholder": "​",
       "style": "IPY_MODEL_3e9a9304fe9e4fe292162dd8073e1026",
       "tabbable": null,
       "tooltip": null,
       "value": " [ elapsed time: 00:03 | time left: 00:00 ] "
      }
     },
     "4ddb91e8679e45d2bcd8b1e25becc92e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "5669e5ab13e34cb6a95b6cb83d89f75f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "80d2cd38f379484681e7e0c7b446b9ef": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_fe4d05227ae04518a72f09f08fce7773",
       "placeholder": "​",
       "style": "IPY_MODEL_ec133518b76843a981d96e34c750fb2b",
       "tabbable": null,
       "tooltip": null,
       "value": " [ elapsed time: 00:00 | time left: 00:00 ]  last batch size: 125"
      }
     },
     "8a527303a7bc4cb795dee34be5742db8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_2b046e1baf4a4d99afaa0b6d8ceef85e",
       "placeholder": "​",
       "style": "IPY_MODEL_1455e2cbc78e4c35b8169d4f4fa32c4e",
       "tabbable": null,
       "tooltip": null,
       "value": " [ elapsed time: 00:00 | time left: 00:00 ]  last batch size: 10"
      }
     },
     "90d47763e6c94be19a58d37b0c7323b9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "945ed98138954af2b375cf2570c87bde": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_f7bf370564e748639e8754b67f08b8df",
        "IPY_MODEL_044204a8b2bd47da8c91e1db738e8e9f",
        "IPY_MODEL_8a527303a7bc4cb795dee34be5742db8"
       ],
       "layout": "IPY_MODEL_f7dbc75289f04e47a32d51d72a2d00c1",
       "tabbable": null,
       "tooltip": null
      }
     },
     "95a71388192946db886e809b51f06a86": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "9daddafc69ad49a7ae4f08454dc1c019": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "9e100de4a25d42a495303ee5bac4e617": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_340cf62c1ab34a6898019a0a5992f577",
        "IPY_MODEL_db2d43edd9d54e4d86260cf563f8c29d",
        "IPY_MODEL_80d2cd38f379484681e7e0c7b446b9ef"
       ],
       "layout": "IPY_MODEL_2f3b5d8b3daa49f8aec4841b43d3f547",
       "tabbable": null,
       "tooltip": null
      }
     },
     "b149c914dff04931b4376ec55edb334b": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "b877a86f54b346f6be8c0fc4a330f085": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "background": null,
       "description_width": "",
       "font_size": null,
       "text_color": null
      }
     },
     "c4fc2fecb9c9445c8b2d09b8c660027a": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "d50b25adbc5f4f5ea8db9578216f8aa1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "db2d43edd9d54e4d86260cf563f8c29d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_4ddb91e8679e45d2bcd8b1e25becc92e",
       "max": 100.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_d50b25adbc5f4f5ea8db9578216f8aa1",
       "tabbable": null,
       "tooltip": null,
       "value": 100.0
      }
     },
     "dc43604374d74ce385bbe4ef9616a04e": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_46cc2cbd3d4d4f8d9b69bf3c67d710cd",
        "IPY_MODEL_de2db7677ffe42fc933ad797448e21fd",
        "IPY_MODEL_48476132d16a4ffcb9dabb02722bf9bc"
       ],
       "layout": "IPY_MODEL_f3e4ad05f4694573a416626fb84b32cf",
       "tabbable": null,
       "tooltip": null
      }
     },
     "de2db7677ffe42fc933ad797448e21fd": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_9daddafc69ad49a7ae4f08454dc1c019",
       "max": 100.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_5669e5ab13e34cb6a95b6cb83d89f75f",
       "tabbable": null,
       "tooltip": null,
       "value": 100.0
      }
     },
     "def1460f26df468c98a2846395a82e28": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "ec133518b76843a981d96e34c750fb2b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "StyleView",
       "background": null,
       "description_width": "",
       "font_size": null,
       "text_color": null
      }
     },
     "f3e4ad05f4694573a416626fb84b32cf": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "f7bf370564e748639e8754b67f08b8df": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "2.0.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "2.0.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "2.0.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_allow_html": false,
       "layout": "IPY_MODEL_def1460f26df468c98a2846395a82e28",
       "placeholder": "​",
       "style": "IPY_MODEL_b877a86f54b346f6be8c0fc4a330f085",
       "tabbable": null,
       "tooltip": null,
       "value": "Completed: 100%"
      }
     },
     "f7dbc75289f04e47a32d51d72a2d00c1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "fe4d05227ae04518a72f09f08fce7773": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "2.0.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "2.0.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "2.0.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border_bottom": null,
       "border_left": null,
       "border_right": null,
       "border_top": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}