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    "(adaptive-tutorial)=\n",
    "# Tutorial 4. Adaptive Measurements\n",
    "\n",
    "```{seealso}\n",
    "The complete source code of this tutorial can be found in\n",
    "\n",
    "{nb-download}`Tutorial 4. Adaptive Measurements.ipynb`\n",
    "```\n",
    "\n",
    "This tutorial requires familiarity with the **core concepts** of Quantify.\n",
    "We **highly recommended** to read the {ref}`user guide <user-guide>` and follow {ref}`Tutorial 1. Controlling a basic experiment using MeasurementControl` and {ref}`Tutorial 2. Advanced capabilities of the MeasurementControl` first.\n",
    "\n",
    "In this tutorial, we explore the adaptive functionality of the {class}`.MeasurementControl`.\n",
    "With this mode, instead of predefining a grid of values to sweep through, we provide an optimization function and an initial state to the `meas_ctrl`.\n",
    "The `meas_ctrl` will then use this function to build the sweep. We import our usual modules and set up a `meas_ctrl` with visualization:"
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  {
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   "execution_count": 1,
   "id": "4874e435",
   "metadata": {
    "mystnb": {
     "code_prompt_show": "Imports and auxiliary utilities"
    },
    "tags": [
     "hide-cell"
    ]
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   "outputs": [],
   "source": [
    "import time\n",
    "\n",
    "import adaptive\n",
    "import numpy as np\n",
    "from qcodes import Instrument, ManualParameter\n",
    "from scipy import optimize\n",
    "\n",
    "import quantify_core.analysis.optimization_analysis as oa\n",
    "import quantify_core.visualization.pyqt_plotmon as pqm\n",
    "from quantify_core.analysis.interpolation_analysis import InterpolationAnalysis2D\n",
    "from quantify_core.data.handling import set_datadir, default_datadir\n",
    "from quantify_core.measurement.control import MeasurementControl\n",
    "from quantify_core.visualization.instrument_monitor import InstrumentMonitor"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07057c0a",
   "metadata": {},
   "source": [
    "Before instantiating any instruments or starting a measurement we change the\n",
    "directory in which the experiments are saved using the\n",
    "{meth}`~quantify_core.data.handling.set_datadir`\n",
    "\\[{meth}`~quantify_core.data.handling.get_datadir`\\] functions.\n",
    "\n",
    "----------------------------------------------------------------------------------------\n",
    "\n",
    "⚠️ **Warning!**\n",
    "\n",
    "We recommend always setting the directory at the start of the python kernel and stick\n",
    "to a single common data directory for all notebooks/experiments within your\n",
    "measurement setup/PC.\n",
    "\n",
    "The cell below sets a default data directory (`~/quantify-data` on Linux/macOS or\n",
    "`$env:USERPROFILE\\\\quantify-data` on Windows) for tutorial purposes. Change it to your\n",
    "desired data directory. The utilities to find/search/extract data only work if\n",
    "all the experiment containers are located within the same directory.\n",
    "\n",
    "----------------------------------------------------------------------------------------"
   ]
  },
  {
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   "execution_count": 2,
   "id": "d6778cc3",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data will be saved in:\n",
      "/root/quantify-data\n"
     ]
    }
   ],
   "source": [
    "set_datadir(default_datadir())"
   ]
  },
  {
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   "execution_count": 3,
   "id": "c93ce3d0",
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   "source": [
    "meas_ctrl = MeasurementControl(\"meas_ctrl\")\n",
    "insmon = InstrumentMonitor(\"InstrumentMonitor\")\n",
    "plotmon = pqm.PlotMonitor_pyqt(\"plotmon_meas_ctrl\")\n",
    "meas_ctrl.instr_plotmon(plotmon.name)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57a00112",
   "metadata": {},
   "source": [
    "## Finding a minimum\n",
    "\n",
    "We will create a mock Instrument our `meas_ctrl` will interact with. In this case, it is a simple parabola centered at the origin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "882fd32e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qcodes.parameters.parameter.Parameter: amp at 134115966792800>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
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    "para = Instrument(\"parabola\")\n",
    "\n",
    "para.add_parameter(\"x\", unit=\"m\", label=\"X\", parameter_class=ManualParameter)\n",
    "para.add_parameter(\"y\", unit=\"m\", label=\"Y\", parameter_class=ManualParameter)\n",
    "\n",
    "para.add_parameter(\n",
    "    \"noise\", unit=\"V\", label=\"white noise amplitude\", parameter_class=ManualParameter\n",
    ")\n",
    "para.add_parameter(\n",
    "    \"acq_delay\", initial_value=0.1, unit=\"s\", parameter_class=ManualParameter\n",
    ")\n",
    "\n",
    "\n",
    "def _amp_model():\n",
    "    time.sleep(\n",
    "        para.acq_delay()\n",
    "    )  # for display purposes, just so we can watch the live plot update\n",
    "    return para.x() ** 2 + para.y() ** 2 + para.noise() * np.random.rand(1)\n",
    "\n",
    "\n",
    "para.add_parameter(\"amp\", unit=\"V\", label=\"Amplitude\", get_cmd=_amp_model)"
   ]
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   "id": "1999bc2a",
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    "Next, we will use the `optimize` package from `scipy` to provide our adaptive function.\n",
    "You can of course implement your own functions for this purpose, but for brevity we will use something standard and easily available.\n",
    "\n",
    "Then, we set our {ref}`Settables and Gettables<Settables and Gettables>` as usual, and define a new dictionary `af_pars`.\n",
    "The only required key in this object is `adaptive_function`, the value to be used by the adaptive function.\n",
    "The remaining fields in this dictionary are the arguments to the adaptive function itself. We also add some noise into the parabola to stress our adaptive function.\n",
    "\n",
    "**As such, it is highly recommended to thoroughly read the documentation around the adaptive function you are using.**\n",
    "\n",
    "We will use the `optimize.minimize` function (note this is passed by reference as opposed to calling the `minimize` function), which requires an initial state named `\"x0\"` and an algorithm to use named `\"method\"`.\n",
    "In this case, we are starting at `[-50, -50]` and hope to minimize these values relative to our parabola function.\n",
    "Of course, this parabola has its global minimum at the origin, thus these values will tend towards 0 as our algorithm progresses."
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     "text": [
      "Running adaptively...\n",
      "."
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      "/usr/local/lib/python3.9/site-packages/qcodes_loop/plots/pyqtgraph.py:420: UserWarning: zero setpoint range passed to pyqtgraph. ignoring, using default scaling.\n",
      "  warnings.warn('zero setpoint range passed to pyqtgraph. '\n"
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    "meas_ctrl.settables([para.x, para.y])\n",
    "af_pars = {\n",
    "    \"adaptive_function\": optimize.minimize,  # used by meas_ctrl\n",
    "    \"x0\": [-50, -50],  # used by `optimize.minimize` (in this case)\n",
    "    \"method\": \"Nelder-Mead\",  # used by `optimize.minimize` (in this case)\n",
    "    \"options\": {\"maxfev\": 100},  # limit the maximum evaluations of the gettable(s)\n",
    "}\n",
    "para.noise(0.5)\n",
    "meas_ctrl.gettables(para.amp)\n",
    "dset = meas_ctrl.run_adaptive(\"nelder_mead_optimization\", af_pars)"
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   "cell_type": "code",
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       "  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:  (dim_0: 100)\n",
       "Coordinates:\n",
       "    x0       (dim_0) float64 800B -50.0 -52.5 -50.0 ... -0.04036 -0.04037\n",
       "    x1       (dim_0) float64 800B -50.0 -50.0 -52.5 ... -0.2085 -0.2084 -0.2084\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 5e+03 5.257e+03 5.256e+03 ... 0.2035 0.1494\n",
       "Attributes:\n",
       "    tuid:                             20241014-175702-983-c04a49\n",
       "    name:                             nelder_mead_optimization\n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  True</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-0fdfb1ad-3521-4f3d-905f-be269e5d8813' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0fdfb1ad-3521-4f3d-905f-be269e5d8813' 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>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b0bef164-6eea-4917-8832-f80d1372a307' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b0bef164-6eea-4917-8832-f80d1372a307' 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>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'>-50.0 -52.5 ... -0.04036 -0.04037</div><input id='attrs-32df756a-c5b8-4b15-9f51-0f03204fd7b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32df756a-c5b8-4b15-9f51-0f03204fd7b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d3fb282-5660-4576-b5d3-7a5c29f87573' class='xr-var-data-in' type='checkbox'><label for='data-1d3fb282-5660-4576-b5d3-7a5c29f87573' 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>parabola.x</dd><dt><span>long_name :</span></dt><dd>parabola X</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([-5.00000000e+01, -5.25000000e+01, -5.00000000e+01, -4.75000000e+01,\n",
       "       -4.75000000e+01, -4.62500000e+01, -4.87500000e+01, -4.93750000e+01,\n",
       "       -4.56250000e+01, -4.34375000e+01, -4.65625000e+01, -4.67187500e+01,\n",
       "       -4.07812500e+01, -3.64843750e+01, -3.97656250e+01, -2.95312500e+01,\n",
       "       -2.62500000e+01, -1.94921875e+01, -2.64453125e+01, -9.45312500e+00,\n",
       "        4.06250000e+00,  1.10156250e+01, -1.70800781e+01,  6.47460938e+00,\n",
       "        2.76171875e+01, -5.90576172e+00, -8.31787109e+00,  2.77648926e+00,\n",
       "        1.27447510e+01, -1.24313354e+00,  4.28771973e-02,  2.09308624e+00,\n",
       "       -3.21254730e+00,  2.24373817e+00, -1.09248161e+00, -2.68526554e+00,\n",
       "        2.39439011e+00, -3.33752632e-01, -3.66997242e+00,  7.65310526e-01,\n",
       "        1.52403951e+00, -4.38351333e-01, -1.53741449e+00,  1.89629272e-01,\n",
       "        8.50305706e-02, -2.29056831e-01, -1.96652301e-02, -1.76708931e-01,\n",
       "        4.51271674e-01,  8.49334709e-02, -5.43047134e-01,  2.02691972e-01,\n",
       "       -4.58877301e-02,  1.37281371e-01, -3.59878032e-01, -2.35588182e-01,\n",
       "        1.29915203e-02,  1.43812721e-01, -9.65785180e-02, -1.64481049e-02,\n",
       "       -1.11298331e-01,  4.89624956e-02,  8.89728908e-03, -2.05423361e-02,\n",
       "       -1.95187783e-02, -1.84952205e-02, -3.11679175e-02, -3.32150331e-02,\n",
       "       -3.27032542e-02, -6.00957638e-02, -4.96956280e-02, -2.88953563e-02,\n",
       "       -4.44955601e-02, -3.92954921e-02, -4.77916790e-02, -3.73915432e-02,\n",
       "       -4.51916451e-02, -4.25916111e-02, -4.35435856e-02, -4.02474666e-02,\n",
       "       -4.08335027e-02, -4.14195389e-02, -4.09435516e-02, -3.97714794e-02,\n",
       "       -4.00644974e-02, -4.06505336e-02, -4.02110065e-02, -3.80869598e-02,\n",
       "       -4.05863941e-02, -3.96708798e-02, -4.00759748e-02, -3.99409431e-02,\n",
       "       -4.03987003e-02, -4.01286369e-02, -4.07740879e-02, -4.01492293e-02,\n",
       "       -4.05658017e-02, -4.02533724e-02, -4.03575155e-02, -4.03678117e-02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x1</span></div><div class='xr-var-dims'>(dim_0)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-50.0 -50.0 ... -0.2084 -0.2084</div><input id='attrs-2c3f1281-bfe1-4d65-b8ae-0ce40b9b77e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c3f1281-bfe1-4d65-b8ae-0ce40b9b77e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e03b254e-30a7-4b2f-8b93-75ae4752764a' class='xr-var-data-in' type='checkbox'><label for='data-e03b254e-30a7-4b2f-8b93-75ae4752764a' 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>parabola.y</dd><dt><span>long_name :</span></dt><dd>parabola Y</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([-5.00000000e+01, -5.00000000e+01, -5.25000000e+01, -5.25000000e+01,\n",
       "       -5.00000000e+01, -4.87500000e+01, -4.62500000e+01, -4.31250000e+01,\n",
       "       -4.18750000e+01, -3.78125000e+01, -3.21875000e+01, -2.39062500e+01,\n",
       "       -1.85937500e+01, -6.32812500e+00,  7.57812500e+00,  2.51562500e+01,\n",
       "        1.12500000e+01,  1.30859375e+01, -1.83984375e+01,  1.01562500e+00,\n",
       "        4.68750000e+00,  3.61718750e+01, -4.75585938e+00, -1.31542969e+01,\n",
       "       -3.71093750e+00, -4.49462891e+00,  1.33471680e+01, -6.52893066e+00,\n",
       "        2.65319824e+00, -2.70767212e+00,  8.50875854e+00, -2.76950836e+00,\n",
       "       -1.01646805e+01,  9.74454880e-01,  1.03629112e+00,  2.93919086e+00,\n",
       "        4.71841812e+00, -8.51149559e-01, -7.89313316e-01,  5.33512831e-01,\n",
       "       -1.35392785e+00,  4.38736379e-01, -9.45926011e-01,  1.63653120e-01,\n",
       "        1.45353906e+00, -2.74977405e-01,  8.77366904e-01,  1.31086726e-02,\n",
       "       -2.61974586e-01, -4.12519034e-01, -1.37435775e-01, -2.30839883e-01,\n",
       "       -1.99705181e-01, -1.24432957e-01, -6.21635513e-02, -7.77309027e-02,\n",
       "       -1.08865605e-01, -3.21679459e-01, -7.05883602e-02, -1.54285393e-01,\n",
       "       -9.32982541e-02, -2.60692320e-01, -2.18843803e-01, -2.64263591e-01,\n",
       "       -2.36769041e-01, -2.09274492e-01, -1.76995287e-01, -2.31984386e-01,\n",
       "       -2.18237111e-01, -2.08667800e-01, -2.08819473e-01, -2.09122819e-01,\n",
       "       -2.08895309e-01, -2.08971146e-01, -2.04262327e-01, -2.04414000e-01,\n",
       "       -2.04300245e-01, -2.04338163e-01, -2.06616736e-01, -2.11249719e-01,\n",
       "       -2.09521830e-01, -2.07793941e-01, -2.06654655e-01, -2.10110432e-01,\n",
       "       -2.09246488e-01, -2.07518599e-01, -2.08814516e-01, -2.09991721e-01,\n",
       "       -2.08343386e-01, -2.08500016e-01, -2.08735891e-01, -2.08657266e-01,\n",
       "       -2.08578951e-01, -2.08421701e-01, -2.08107821e-01, -2.08519905e-01,\n",
       "       -2.08245182e-01, -2.08451224e-01, -2.08382544e-01, -2.08431645e-01])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-af66a0cc-1657-4bfd-b30b-150efa774f54' class='xr-section-summary-in' type='checkbox'  checked><label for='section-af66a0cc-1657-4bfd-b30b-150efa774f54' class='xr-section-summary' >Data variables: <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>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'>5e+03 5.257e+03 ... 0.2035 0.1494</div><input id='attrs-a59f3756-91a9-4866-be16-b883bc4b9589' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a59f3756-91a9-4866-be16-b883bc4b9589' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d91c7a7-59b2-4969-8c43-e4e65b86936c' class='xr-var-data-in' type='checkbox'><label for='data-0d91c7a7-59b2-4969-8c43-e4e65b86936c' 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>amp</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([5.00015528e+03, 5.25654972e+03, 5.25636725e+03, 5.01275876e+03,\n",
       "       4.75669354e+03, 4.51605321e+03, 4.51596582e+03, 4.29787374e+03,\n",
       "       3.83517966e+03, 3.31669308e+03, 3.20431669e+03, 2.75464463e+03,\n",
       "       2.00887237e+03, 1.37134424e+03, 1.63891406e+03, 1.50511128e+03,\n",
       "       8.16064696e+02, 5.51455464e+02, 1.03820014e+03, 9.08242783e+01,\n",
       "       3.85469335e+01, 1.42998705e+03, 3.14842583e+02, 2.15161053e+02,\n",
       "       7.76511474e+02, 5.53223888e+01, 2.47361441e+02, 5.05648439e+01,\n",
       "       1.69800752e+02, 9.10898396e+00, 7.27104840e+01, 1.25230265e+01,\n",
       "       1.13738937e+02, 6.09660421e+00, 2.73999292e+00, 1.61785939e+01,\n",
       "       2.84107704e+01, 9.53423760e-01, 1.45544329e+01, 1.26138231e+00,\n",
       "       4.52881725e+00, 4.26428698e-01, 3.66398147e+00, 3.85562779e-01,\n",
       "       2.16317576e+00, 4.32202291e-01, 1.16381981e+00, 1.26744393e-01,\n",
       "       2.83217154e-01, 1.90918512e-01, 3.34315020e-01, 4.92003624e-01,\n",
       "       9.15635060e-02, 4.53577048e-01, 4.37573574e-01, 1.93514117e-01,\n",
       "       1.22099287e-01, 4.14966534e-01, 2.02443836e-01, 4.64158003e-01,\n",
       "       4.95774809e-01, 4.82126330e-01, 2.53261751e-01, 3.77370051e-01,\n",
       "       4.29163015e-01, 3.48107652e-01, 5.21945538e-01, 3.83742316e-01,\n",
       "       1.14439108e-01, 3.13335864e-01, 2.08399441e-01, 3.50173133e-01,\n",
       "       4.64998198e-01, 7.33298292e-02, 1.26414372e-01, 3.11857340e-01,\n",
       "       4.62995890e-01, 3.63768947e-01, 1.02904157e-01, 1.76325943e-01,\n",
       "       3.78075192e-01, 1.74054581e-01, 5.16280539e-01, 3.78463729e-01,\n",
       "       1.82639729e-01, 4.03951256e-01, 9.43591563e-02, 5.20471549e-01,\n",
       "       4.59030974e-02, 1.65038164e-01, 2.92061001e-01, 2.72551178e-01,\n",
       "       4.91207145e-01, 7.92908275e-02, 4.69932838e-01, 1.26067886e-01,\n",
       "       3.84758082e-01, 2.82447036e-01, 2.03535826e-01, 1.49416337e-01])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d2ce2a1b-96f9-4c61-b245-e1ec07124704' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d2ce2a1b-96f9-4c61-b245-e1ec07124704' 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-291dfb63-e73e-478e-b623-bcc28f6ca871' class='xr-section-summary-in' type='checkbox'  checked><label for='section-291dfb63-e73e-478e-b623-bcc28f6ca871' 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>20241014-175702-983-c04a49</dd><dt><span>name :</span></dt><dd>nelder_mead_optimization</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>True</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2kB\n",
       "Dimensions:  (dim_0: 100)\n",
       "Coordinates:\n",
       "    x0       (dim_0) float64 800B -50.0 -52.5 -50.0 ... -0.04036 -0.04037\n",
       "    x1       (dim_0) float64 800B -50.0 -50.0 -52.5 ... -0.2085 -0.2084 -0.2084\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 5e+03 5.257e+03 5.256e+03 ... 0.2035 0.1494\n",
       "Attributes:\n",
       "    tuid:                             20241014-175702-983-c04a49\n",
       "    name:                             nelder_mead_optimization\n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  True"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8733dbaa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<quantify_core.visualization.pyqt_plotmon.QtPlotObjForJupyter at 0x79fa4e8f1cd0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotmon.main_QtPlot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f082765c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<quantify_core.visualization.pyqt_plotmon.QtPlotObjForJupyter at 0x79fa4e8f1d30>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotmon.secondary_QtPlot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dacd3b6c",
   "metadata": {},
   "source": [
    "We can see from the graphs that the values of the settables in the dataset snake towards 0 as expected. Success!\n",
    "\n",
    "### Analysis\n",
    "\n",
    "There are several analysis classes available in `quantify-core` that can be used to visualize and extract relevant information from the results of these adaptive measurements.\n",
    "\n",
    "The {class}`~quantify_core.analysis.optimization_analysis.OptimizationAnalysis` class searches the dataset for the optimal datapoint and provides a number of useful plots to visualize the convergence of the measurement result around the minimum."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "35a9c0d8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_obj = oa.OptimizationAnalysis(dset)\n",
    "a_obj.run()\n",
    "a_obj.display_figs_mpl()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7aaf2250",
   "metadata": {},
   "source": [
    "The analysis generates plots of each of the variables versus the number of iteration steps completed. The figures show the data converging on the optimal value.\n",
    "\n",
    "The {class}`~quantify_core.analysis.interpolation_analysis.InterpolationAnalysis2D` class can be used to generate a 2-dimensional heatmap that interpolates between a set of irregularly spaced datapoints."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8f010339",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a_obj = InterpolationAnalysis2D(dset)\n",
    "a_obj.run()\n",
    "a_obj.display_figs_mpl()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6be8ebb3",
   "metadata": {},
   "source": [
    "## Adaptive Sampling\n",
    "\n",
    "Quantify is designed to be modular and the adaptive functions support is no different. To this end, the `meas_ctrl` has first-class support for the `adaptive` package.\n",
    "Let's see what the same experiment looks like with this module. Note the fields of the `af_pars` dictionary have changed to be compatible with the different adaptive functions that we are using.\n",
    "\n",
    "As a practical example, let's revisit a Resonator Spectroscopy experiment. This time we only know our device has a resonance in 6-7 GHz range.\n",
    "We really don't want to sweep through a million points, so instead let's use an adaptive sampler to quickly locate our peak."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "075258bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qcodes.parameters.parameter.Parameter: S21 at 134115941352544>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = Instrument(\"Resonator\")\n",
    "\n",
    "res.add_parameter(\"freq\", unit=\"Hz\", label=\"Frequency\", parameter_class=ManualParameter)\n",
    "res.add_parameter(\"amp\", unit=\"V\", label=\"Amplitude\", parameter_class=ManualParameter)\n",
    "_fwhm = 15e6  # pretend you don't know what this value is\n",
    "_res_freq = 6.78e9  # pretend you don't know what this value is\n",
    "_noise_level = 0.1\n",
    "\n",
    "\n",
    "def lorenz():\n",
    "    \"\"\"A Lorenz model function.\"\"\"\n",
    "    time.sleep(0.02)  # for display purposes, just so we can watch the graph update\n",
    "    return (\n",
    "        1\n",
    "        - (\n",
    "            res.amp()\n",
    "            * ((_fwhm / 2.0) ** 2)\n",
    "            / ((res.freq() - _res_freq) ** 2 + (_fwhm / 2.0) ** 2)\n",
    "        )\n",
    "        + _noise_level * np.random.rand(1)\n",
    "    )\n",
    "\n",
    "\n",
    "res.add_parameter(\"S21\", unit=\"V\", label=\"Transmission amp. S21\", get_cmd=lorenz)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "312542e3",
   "metadata": {
    "tags": [
     "hide-output"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running adaptively...\n",
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "."
     ]
    }
   ],
   "source": [
    "_noise_level = 0.0\n",
    "res.amp(1)\n",
    "meas_ctrl.settables([res.freq])\n",
    "af_pars = {\n",
    "    \"adaptive_function\": adaptive.learner.Learner1D,\n",
    "    \"goal\": lambda l: l.npoints > 99,\n",
    "    \"bounds\": (6.0e9, 7.0e9),\n",
    "}\n",
    "meas_ctrl.gettables(res.S21)\n",
    "dset = meas_ctrl.run_adaptive(\"adaptive sample\", af_pars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "41581199",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 2kB\n",
       "Dimensions:  (dim_0: 100)\n",
       "Coordinates:\n",
       "    x0       (dim_0) float64 800B 6e+09 7e+09 6.5e+09 ... 6.77e+09 6.754e+09\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 0.9999 0.9988 0.9993 ... 0.6186 0.6391 0.9237\n",
       "Attributes:\n",
       "    tuid:                             20241014-175717-068-fac016\n",
       "    name:                             adaptive sample\n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  True</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-a93ff704-42e9-4b5f-9975-16366698e609' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a93ff704-42e9-4b5f-9975-16366698e609' 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>: 100</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-f282a03b-9660-4188-9347-f9109b37b332' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f282a03b-9660-4188-9347-f9109b37b332' 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'>6e+09 7e+09 ... 6.77e+09 6.754e+09</div><input id='attrs-39c0d864-59f4-4137-99d4-ecc00421ff98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39c0d864-59f4-4137-99d4-ecc00421ff98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-613674e3-d399-4c1c-a5bc-23314739cae5' class='xr-var-data-in' type='checkbox'><label for='data-613674e3-d399-4c1c-a5bc-23314739cae5' 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>Resonator.freq</dd><dt><span>long_name :</span></dt><dd>Resonator Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>batched :</span></dt><dd>False</dd></dl></div><div class='xr-var-data'><pre>array([6.00000000e+09, 7.00000000e+09, 6.50000000e+09, 6.25000000e+09,\n",
       "       6.75000000e+09, 6.62500000e+09, 6.87500000e+09, 6.68750000e+09,\n",
       "       6.81250000e+09, 6.71875000e+09, 6.84375000e+09, 6.73437500e+09,\n",
       "       6.82812500e+09, 6.74218750e+09, 6.82031250e+09, 6.74609375e+09,\n",
       "       6.81640625e+09, 6.37500000e+09, 6.12500000e+09, 6.74804688e+09,\n",
       "       6.72656250e+09, 6.73828125e+09, 6.83593750e+09, 6.81445312e+09,\n",
       "       6.82421875e+09, 6.78125000e+09, 6.79687500e+09, 6.76562500e+09,\n",
       "       6.78906250e+09, 6.77343750e+09, 6.78515625e+09, 6.77734375e+09,\n",
       "       6.76953125e+09, 6.77539062e+09, 6.78320312e+09, 6.78710938e+09,\n",
       "       6.79296875e+09, 6.77148438e+09, 6.78417969e+09, 6.77636719e+09,\n",
       "       6.77441406e+09, 6.79101562e+09, 6.75781250e+09, 6.78613281e+09,\n",
       "       6.77246094e+09, 6.78222656e+09, 6.76757812e+09, 6.93750000e+09,\n",
       "       6.56250000e+09, 6.43750000e+09, 6.31250000e+09, 6.18750000e+09,\n",
       "       6.06250000e+09, 6.78808594e+09, 6.80468750e+09, 6.76171875e+09,\n",
       "       6.77050781e+09, 6.79003906e+09, 6.79492188e+09, 6.77929688e+09,\n",
       "       6.77832031e+09, 6.77587891e+09, 6.78466797e+09, 6.78369141e+09,\n",
       "       6.77490234e+09, 6.80078125e+09, 6.78564453e+09, 6.77685547e+09,\n",
       "       6.77392578e+09, 6.78271484e+09, 6.78662109e+09, 6.76855469e+09,\n",
       "       6.76367188e+09, 6.77294922e+09, 6.79199219e+09, 6.78759766e+09,\n",
       "       6.77783203e+09, 6.65625000e+09, 6.90625000e+09, 6.59375000e+09,\n",
       "       6.96875000e+09, 6.53125000e+09, 6.46875000e+09, 6.40625000e+09,\n",
       "       6.34375000e+09, 6.28125000e+09, 6.21875000e+09, 6.15625000e+09,\n",
       "       6.09375000e+09, 6.03125000e+09, 6.77197266e+09, 6.78857422e+09,\n",
       "       6.78173828e+09, 6.76660156e+09, 6.77099609e+09, 6.79394531e+09,\n",
       "       6.79882812e+09, 6.78955078e+09, 6.77001953e+09, 6.75390625e+09])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7b8ab980-ea1c-4c2c-9f39-251ba2602591' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7b8ab980-ea1c-4c2c-9f39-251ba2602591' class='xr-section-summary' >Data variables: <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>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'>0.9999 0.9988 ... 0.6391 0.9237</div><input id='attrs-1c021a1c-8269-4d22-8ea9-9f53f4653389' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c021a1c-8269-4d22-8ea9-9f53f4653389' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68cd6e37-8779-47bc-ae2d-eacd1b82caae' class='xr-var-data-in' type='checkbox'><label for='data-68cd6e37-8779-47bc-ae2d-eacd1b82caae' 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>S21</dd><dt><span>long_name :</span></dt><dd>Transmission amp. S21</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([0.99990755, 0.99883916, 0.99928304, 0.99979979, 0.94117647,\n",
       "       0.99766416, 0.99380592, 0.9934688 , 0.9494382 , 0.98522774,\n",
       "       0.98634812, 0.97368902, 0.97628849, 0.9621476 , 0.96654469,\n",
       "       0.95335371, 0.95928825, 0.99965718, 0.99986891, 0.94778382,\n",
       "       0.98068216, 0.96869267, 0.9823405 , 0.95475633, 0.97203646,\n",
       "       0.02702703, 0.83505155, 0.78603269, 0.59350741, 0.43362832,\n",
       "       0.32095491, 0.11145391, 0.66082732, 0.27415925, 0.15426264,\n",
       "       0.47328113, 0.74937452, 0.56316064, 0.23697556, 0.19003362,\n",
       "       0.35679514, 0.68326632, 0.89745416, 0.40071204, 0.50259739,\n",
       "       0.08099619, 0.73284633, 0.99773756, 0.99881235, 0.99952072,\n",
       "       0.9997427 , 0.99983979, 0.99989075, 0.53754093, 0.91550535,\n",
       "       0.85593697, 0.61565168, 0.64179453, 0.79832374, 0.00871249,\n",
       "       0.04776173, 0.23190799, 0.27921516, 0.19500811, 0.31599382,\n",
       "       0.88475967, 0.36159877, 0.14950657, 0.3961102 , 0.11584931,\n",
       "       0.43799952, 0.69959173, 0.82577462, 0.46915691, 0.71883795,\n",
       "       0.50646803, 0.07711373, 0.99634035, 0.99648334, 0.99838108,\n",
       "       0.99842361, 0.99909176, 0.9994197 , 0.99959748, 0.99970452,\n",
       "       0.99977392, 0.99982146, 0.99985544, 0.99988057, 0.99989968,\n",
       "       0.53392314, 0.56653154, 0.05097923, 0.76141813, 0.59037383,\n",
       "       0.7756477 , 0.86305482, 0.61855982, 0.63909863, 0.92369092])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6cc62f9f-d9f5-4f76-b550-c026fb01ff2e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6cc62f9f-d9f5-4f76-b550-c026fb01ff2e' 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-9ebd0604-2bc4-45c3-87dc-47a3a173c8b3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9ebd0604-2bc4-45c3-87dc-47a3a173c8b3' 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>20241014-175717-068-fac016</dd><dt><span>name :</span></dt><dd>adaptive sample</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>True</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 2kB\n",
       "Dimensions:  (dim_0: 100)\n",
       "Coordinates:\n",
       "    x0       (dim_0) float64 800B 6e+09 7e+09 6.5e+09 ... 6.77e+09 6.754e+09\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 0.9999 0.9988 0.9993 ... 0.6186 0.6391 0.9237\n",
       "Attributes:\n",
       "    tuid:                             20241014-175717-068-fac016\n",
       "    name:                             adaptive sample\n",
       "    grid_2d:                          False\n",
       "    grid_2d_uniformly_spaced:         False\n",
       "    1d_2_settables_uniformly_spaced:  True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8f2e3381",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<quantify_core.visualization.pyqt_plotmon.QtPlotObjForJupyter at 0x79fa4e8f1cd0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plotmon.main_QtPlot"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e0795fee",
   "metadata": {},
   "source": [
    "## FAQ\n",
    "\n",
    "### Can I return multi-dimensional data from a Gettable in Adaptive Mode?\n",
    "\n",
    "Yes, but only the first dimension (`y0`) will be considered by the adaptive function;\n",
    "the remaining dimensions will merely be saved to the dataset."
   ]
  }
 ],
 "metadata": {
  "file_format": "mystnb",
  "jupytext": {
   "text_representation": {
    "extension": ".md",
    "format_name": "myst"
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  },
  "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": "3.9.20"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}