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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 137451122221008>"
      ]
     },
     "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",
   "execution_count": 6,
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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 ... -0.1761 -0.176 -0.1758\n",
       "    x1       (dim_0) float64 800B -50.0 -50.0 -52.5 ... 0.02318 0.02316 0.02339\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 5e+03 5.256e+03 5.257e+03 ... 0.08805 0.2016\n",
       "Attributes:\n",
       "    tuid:                             20241106-153045-743-6aaf85\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-35fa5af9-2629-4c53-a7af-23e7628f9635' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-35fa5af9-2629-4c53-a7af-23e7628f9635' 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-9a6fe9ce-8772-4ceb-a461-4a5e7042aa74' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9a6fe9ce-8772-4ceb-a461-4a5e7042aa74' 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 ... -0.176 -0.1758</div><input id='attrs-046fadfa-d1c6-46a3-9cc6-73980b68ab5b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-046fadfa-d1c6-46a3-9cc6-73980b68ab5b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-942d17d6-b921-42ed-8901-172062c175e5' class='xr-var-data-in' type='checkbox'><label for='data-942d17d6-b921-42ed-8901-172062c175e5' 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, -5.25000000e+01,\n",
       "       -5.00000000e+01, -4.87500000e+01, -4.62500000e+01, -4.50000000e+01,\n",
       "       -4.25000000e+01, -4.50000000e+01, -3.87500000e+01, -3.37500000e+01,\n",
       "       -3.12500000e+01, -2.43750000e+01, -1.56250000e+01, -2.18750000e+00,\n",
       "        7.18750000e+00,  2.93750000e+01,  1.59375000e+01, -1.09375000e+01,\n",
       "        9.21875000e+00, -1.56250000e-01, -3.82812500e+00, -1.15625000e+01,\n",
       "        4.02343750e+00,  6.05468750e+00,  3.99414062e+00, -1.85546875e-01,\n",
       "       -2.29003906e+00, -4.33593750e+00,  1.91162109e+00,  1.88232422e+00,\n",
       "        3.53393555e-01, -1.74377441e+00, -8.29925537e-01, -1.36886597e+00,\n",
       "       -7.71713257e-02,  5.67207336e-01, -4.80642319e-01, -3.72266769e-01,\n",
       "       -2.32226849e-01, -6.35697842e-01, -2.16802955e-01, -4.96066213e-01,\n",
       "       -2.86618769e-01, -3.82032990e-02,  1.83016211e-01, -9.25952196e-02,\n",
       "       -1.97318941e-01, -1.62411034e-01, -1.35215074e-01, -6.53992593e-02,\n",
       "       -1.17761120e-01, -1.00307167e-01, -1.48813054e-01, -1.13905147e-01,\n",
       "       -1.76009014e-01, -2.13859938e-01, -2.24514902e-01, -1.41557585e-01,\n",
       "       -1.69210024e-01, -1.44957080e-01, -1.51756071e-01, -1.64846536e-01,\n",
       "       -1.60483047e-01, -1.72609519e-01, -1.88135486e-01, -1.91534981e-01,\n",
       "       -1.86803616e-01, -1.82072250e-01, -1.74309267e-01, -1.68246031e-01,\n",
       "       -1.69945778e-01, -1.71036650e-01, -1.78799634e-01, -1.70884432e-01,\n",
       "       -1.76161233e-01, -1.72203632e-01, -1.73522832e-01, -1.73446723e-01,\n",
       "       -1.75932905e-01, -1.78495196e-01, -1.77233078e-01, -1.75970960e-01,\n",
       "       -1.74727869e-01, -1.74765923e-01, -1.75669700e-01, -1.76950846e-01,\n",
       "       -1.75283613e-01, -1.75839357e-01, -1.75368441e-01, -1.75538098e-01,\n",
       "       -1.75613413e-01, -1.75688728e-01, -1.75924186e-01, -1.76244472e-01,\n",
       "       -1.76329301e-01, -1.76093843e-01, -1.76018528e-01, -1.75773556e-01])</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 ... 0.02316 0.02339</div><input id='attrs-b31dc21a-b639-46b3-88c4-5a2a6b71fbda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b31dc21a-b639-46b3-88c4-5a2a6b71fbda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-886c9ac5-ed4d-4255-94b8-aa1b86fe95cf' class='xr-var-data-in' type='checkbox'><label for='data-886c9ac5-ed4d-4255-94b8-aa1b86fe95cf' 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, -4.75000000e+01,\n",
       "       -4.75000000e+01, -4.62500000e+01, -4.87500000e+01, -4.50000000e+01,\n",
       "       -4.25000000e+01, -4.00000000e+01, -3.62500000e+01, -3.12500000e+01,\n",
       "       -3.37500000e+01, -3.06250000e+01, -1.93750000e+01, -7.81250000e+00,\n",
       "       -7.18750000e+00,  1.56250000e+01,  4.06250000e+00, -1.90625000e+01,\n",
       "       -1.71875000e+00, -2.34375000e+00,  7.81250000e-02, -8.43750000e+00,\n",
       "       -3.39843750e+00,  2.07031250e+00, -4.00390625e-01,  6.54296875e-01,\n",
       "        2.68066406e+00, -1.28906250e+00, -6.22558594e-01,  2.37548828e+00,\n",
       "       -1.16394043e+00,  1.12915039e-01, -7.09533691e-02,  1.74728394e+00,\n",
       "       -4.36134338e-01,  2.89115906e-01,  1.90639496e-02, -1.07136726e+00,\n",
       "        2.22880840e-01,  6.78079128e-01, -1.57580972e-01,  3.99525762e-01,\n",
       "       -1.83042884e-02,  1.85512602e-01,  2.68736929e-01, -5.56725264e-02,\n",
       "        1.53242499e-01,  8.36041570e-02,  2.04196721e-01,  6.49200380e-02,\n",
       "        1.69377550e-01,  1.34558380e-01,  1.43900439e-01,  7.42620975e-02,\n",
       "        2.33078748e-02, -3.23173776e-02,  3.26499343e-02,  6.38590567e-02,\n",
       "        5.34560159e-02,  4.87849861e-02,  1.86368451e-02,  4.47512232e-02,\n",
       "        3.60464305e-02,  3.83819453e-02,  2.56433897e-02,  1.05693191e-02,\n",
       "        1.75224757e-02,  2.44756322e-02,  3.08449101e-02,  2.96771526e-02,\n",
       "        2.21401174e-02,  2.43163155e-02,  1.79470377e-02,  2.67446239e-02,\n",
       "        2.08795664e-02,  2.52783595e-02,  2.38120952e-02,  2.50262494e-02,\n",
       "        2.45220290e-02,  2.28036544e-02,  2.33593032e-02,  2.39149519e-02,\n",
       "        2.41670621e-02,  2.35599850e-02,  2.38262102e-02,  2.29670229e-02,\n",
       "        2.38670523e-02,  2.35670425e-02,  2.37374684e-02,  2.34783008e-02,\n",
       "        2.35004862e-02,  2.35226716e-02,  2.34374586e-02,  2.32226618e-02,\n",
       "        2.30930780e-02,  2.31782910e-02,  2.31561055e-02,  2.33930878e-02])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e228f87f-61d8-42cc-801c-ea4a145bb974' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e228f87f-61d8-42cc-801c-ea4a145bb974' 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 5.256e+03 ... 0.08805 0.2016</div><input id='attrs-8f9ebf25-bde4-4b10-a6dc-67487b1b29de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8f9ebf25-bde4-4b10-a6dc-67487b1b29de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f60e70b1-e086-49e7-8819-abade260acd0' class='xr-var-data-in' type='checkbox'><label for='data-f60e70b1-e086-49e7-8819-abade260acd0' 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([5.00047924e+03, 5.25647326e+03, 5.25661139e+03, 5.01292391e+03,\n",
       "       4.75634768e+03, 4.51574552e+03, 4.51593181e+03, 4.05017761e+03,\n",
       "       3.61255618e+03, 3.62549814e+03, 2.81582379e+03, 2.11598676e+03,\n",
       "       2.11569456e+03, 1.53234231e+03, 6.19731633e+02, 6.58708130e+01,\n",
       "       1.03686824e+02, 1.10752896e+03, 2.70816621e+02, 4.83288740e+02,\n",
       "       8.83681575e+01, 5.53468311e+00, 1.48466157e+01, 2.05365030e+02,\n",
       "       2.79702713e+01, 4.14268447e+01, 1.65862667e+01, 7.18290248e-01,\n",
       "       1.27083095e+01, 2.07112676e+01, 4.09230560e+00, 9.62980366e+00,\n",
       "       1.88322385e+00, 3.05910221e+00, 7.18565901e-01, 5.03652423e+00,\n",
       "       4.73808677e-01, 8.70776079e-01, 2.75789572e-01, 1.57794407e+00,\n",
       "       1.99772056e-01, 1.10929042e+00, 4.46799158e-01, 8.00623491e-01,\n",
       "       1.58030458e-01, 1.25859913e-01, 3.28289424e-01, 3.36121097e-01,\n",
       "       3.58575129e-01, 9.52908659e-02, 3.25976037e-01, 3.49293745e-01,\n",
       "       3.42393849e-01, 2.54914666e-01, 4.00066855e-01, 1.52467797e-01,\n",
       "       6.54214223e-02, 7.23555307e-02, 4.61269975e-01, 3.35611362e-01,\n",
       "       3.07098136e-01, 1.40972190e-01, 3.16654454e-01, 4.81461798e-01,\n",
       "       2.55979294e-01, 2.35424838e-01, 1.26499924e-01, 1.55755892e-01,\n",
       "       4.43121765e-01, 4.60441241e-01, 3.66634638e-01, 2.70045657e-01,\n",
       "       2.91773563e-01, 1.30058060e-01, 4.38246334e-01, 1.69546915e-01,\n",
       "       2.93947106e-01, 3.06947469e-01, 4.66203433e-01, 3.31630892e-01,\n",
       "       1.36540141e-01, 1.38204602e-01, 3.73999736e-01, 1.60677769e-01,\n",
       "       9.08783727e-02, 4.11819313e-01, 7.35608892e-02, 1.17668396e-01,\n",
       "       3.75415410e-01, 3.44623974e-01, 1.68301830e-01, 2.02611349e-01,\n",
       "       4.66700025e-01, 2.34369699e-01, 2.21051030e-01, 2.10895958e-01,\n",
       "       1.58475690e-01, 5.51852983e-02, 8.80503647e-02, 2.01552362e-01])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-84e246bd-d2ac-43e9-99ab-d6855b54ed4f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-84e246bd-d2ac-43e9-99ab-d6855b54ed4f' 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-16b36111-90da-40bc-9c84-ad8c83e2e8f0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-16b36111-90da-40bc-9c84-ad8c83e2e8f0' 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>20241106-153045-743-6aaf85</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 ... -0.1761 -0.176 -0.1758\n",
       "    x1       (dim_0) float64 800B -50.0 -50.0 -52.5 ... 0.02318 0.02316 0.02339\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 5e+03 5.256e+03 5.257e+03 ... 0.08805 0.2016\n",
       "Attributes:\n",
       "    tuid:                             20241106-153045-743-6aaf85\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 0x7d02d557dca0>"
      ]
     },
     "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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hwwUFBQkJCWaz+dixYzKZbODAgfZvdTpdSEiIQPDrUK6wsDBCiF6v905zAQDAV7G/96tUKs20sagxf1vF23R782TY8JVMHThwoM1mO3ToUF5eHiEkODh4+vTpoaGh9m/NZrNMJnMuL5FICCEmUzvb7gAAQKDhvuYDRXhaztBXMvXYsWOnTp1KTk6Oi4szm83nz5/fvn37PffcExUVdcvyDMMQQhyjgh3S09PbFrbnNAAABAL2/VS9Xi8RyPqFju6vHHOg6osj/nHvt6Gh4dSpUwMGDHCM442Li/vmm28OHz587733EkJkMpnRaHQ+xd5DlUpbb2WH+AQACHDsF0iyE1BCQsiYqIeGR963vfzd4qbjblftE2sT3rx5k2GYmJgYxxGRSBQZGVlbW2v/qFKpGhsbrVaro0B9fb39eCc3FQAAfBzNUCxfzmeJBbIgoXJm7NLH1G+GSWJud3HXfCJT7c9K7TFpxzCMTqdzPEONi4ujabq0tNRRoKSkRCKROMcwAAAAIYQmApavtufKhIqeQXc80ef9aT0Wu1G1T9z7jY6OViqVZ86cUSgUsbGxFovlzJkzer0+NTXVXkCtVqtUqsOHD0ulUpVKVVhYWFZWNnz48LbrKAEAQIBjuN78bY2SCOQDwyYOUk3O0X50oi6L/Zk+kakCgWDatGl5eXkHDx60HxGJRKmpqUOHDnUUyMzMzMnJycrKsn9MTk5OSUnxWosBAMBX8bLer31Pt/HRj46MnLWt4q0yw3k2Z/lEphJClErl9OnTTSaTfQ390NDQVn3Q0NDQWbNm6XQ6k8mkVCpbTa1xwBr6AAABjuFvT3KJQC4RyGf1ekVrLNpW/la75X0lU+2kUuntJs/Y2Zd6cAE5CgAQ4Hjfk1wmVCQEDXom6ROKaueBo29lKgAAgIc8fZx6KxRFianWszfbQqYCAAA3vr6GPn/3frlCpgIAADc+laBt8TJGyT3IVAAA8Cs8jlHiCpkKAAB+Bf1U3mAuDQBAgOu4fqqFtogFYhcF/C1TkaMAAAGuI/qpRpuxydqkFCtdF/OJ9X4BAAD4wjAUyxebq1kZK83Qm37+/vmzLzLtzdPxt34qAAB4Tq/XMwwTEhLSFZdV56ufyhDGTJuP1B79rPRLlqcgUwEA4H9cv359x44dhJBZs2a5XtvON/EyP7XZ1lLeXP5Ryb9rTTfZn4VMBQCAX5nN5oMHD6pUKuf9N7sWxrN+qok2G20tn5T855y+gOu5/papGPcLAOCJI0eOBAcH9+7d+8iRI95ui5vc7qfSDE1R1JaKrdnane5dwd8yFTkKAOC28vLyK1euPPDAAz///LO32+I+956nGm3GU7ozH1/9pN2BSC74W6YCAIB7LBbLgQMHhgwZolKpunSmcr3322JrqTbVfHj14xstWg+rRqYCAAAhhPz0008ikWjIkCHeboin2N/7jY6OttCWT6+tP153kpeqkakAAEC0Wu2FCxfuu+8+gaD9dQuWLEl3XWD16jye2uUO9uso6XQ6mtCPJcy30tbTurOeV41MBQAAkpeX17NnT5qmtVotIaShoYEQUltbS9N0dHR0q8Lejcx20axLmkwmqUAqFUif7LNQ21L5Ucm/q4zVnlTtb5mKcb8AAG4wGAw3b94sLy93PnjgwAGJRPK73/3OW61yjxvr/QYJg3oHq5ff9bf8uuP/ufaZ21X7W6YiRwEA3HD//fczzK/jXQsLC0+ePDl16tSIiAgvtso97s1PpQglE8pGR478TdSYr8s27q7a48ZF/C1TAQDADaGhoc4fZTIZISQ4OLjV8S7Bk3WURJSIEDIr9r7M7lM/LvnkUsNlTqdjDX0AAPArDOvX7ciEsnCJ6tmk379459Kw9vaicYZ+KgAAtJacnJycnOztVriJr/1Tg4RB/ULvfGPQP/dXH/zm+kY2pyBTAQDAr3i43q8zilASgWRCt3ETuo37nMXuNMhUAADwK4z7awvemlggJoQ8HD/Xxthcl/S3TF2/fr3zxwULFnirJQAA4BV87Z/ailwoa7eMv2UqQhQAIMDx9TzVDW5mKsMwzc3NcrmczSpWAAAAnYaXPcndwyFTaZo+cuRIbm7u2bNnKysraZoWCARRUVGDBg0aNWrUb37zG7FY3HENBQAAYIPvx6kcsMpUmqa3bdv2xRdf1NTURERE9OvXb9iwYQqFwmAw1NXVnT59OicnR6VSPfjgg7Nnz0ayAgCAF/n6vd9nn322rKxs+vTpU6ZMSUhIaFugvLw8Jyfnhx9+yMrK2rBhA89tBAAAX3LmzP5WRwYP9qF1YTtojJKVtlkYq1wodVGGVaZOnTp14sSJcrn8dgViY2Mff/zxRx55ZMeOHZybySusoQ8A0NF8KkFvge+bvwxhTDbLTu2Ju3ukuS7JKlOnT5/OpphYLL733nvZlOw4yFEAgADHbz/VYDVebbqx4sI31UYdP5kKAADQVfD1PLXFZm6xmV6/sPF4XSHLUzhnak1NzXfffXflypX6+nrnjYH69u37yiuvcL0aAAAAvzzvp1oZWkQJPivZten6QU4ncsvU2trahQsX6vX6fv369ejRw/mrbt26cboUAABAR/BwbcJmm+lQdcHrFzcy3B/McsvUPXv2tLS0fP755/Hx8VxrAgAA6ARur6FvsBorWmpXXPjmuqHavStwy1SdTpeUlOTLgYpxvwAAAc6NdZRMtMVCW1dd+ja3+rwnVXPL1OTkZI1GY7FYfHZhB+QoAECAY3/HViQS2RiaIczGsgPrS3Z5XjW31XpHjhw5bNiw1157raamxvO6AQAAeMcwFMtXeHh4i8301PHVvAQq4dpPpShq9uzZS5cu/e1vfxsUFOTcW+3fv/+qVat4aRMAAIDb2M+luXnzZrBI/l7q7w9Wn/vXxU2eV80tU69fv/7MM88IhcLx48eHhYVR1K/t7tmzp+etAQAA8BD7e782m40QEiSUTooeMrX70LVXtn3/c54nVXMe9ysSib766quIiAhPagUAAOggbqz5IBYICSGP95n6UPy4lRc2nKovdq9qbplqsVjUajUCFQAgkPn4GvpuT08NEkqDhNLlyY8WNVa8dmFDrUnP9QrcMjU1NXXbtm3Nzc1BQUFca+ocmEsDANDRfCpB2/JwbcJgkXxwWJ+vRr6YfePYe1e2cDqXW6YOGTIkMzNz2bJlixYtSkhIcB6jRFGUL0ywQY4CAAQ4D9dRIoRQFCUTSqb3HHFPzxHvFm7ecSOf5YncMnX//v0bN24khDz11FOtvho4cOC6des4XQ0AAIB3bq+j1IpEICKEPJN0z9yE8a9d2HBRX9buKdwytU+fPgsXLrzlV9HR0ZwuBQAA0BH42pfGTiGSKUSyVYMXntNda7cwt0xNSEhISEhws10AANCJbDabyWTy2eEvHYfvLckJISRYJB8R0c9Im10Xw/6pAAD+o7m5effu3fn5+QUFBTqdjmEYsVjcq1evwYMHT5gwYdCgQd5uYGfgt5/qIKCoIKHUdRlWmcp+gV/PlwKurq5uaGgQi8VRUVGt/nlls9m0Wq3RaFSpVLebz4NxvwAQmJqamj7//POtW7cajcZevXoNGTIkLCxMKpU2NDRUV1fn5OT8+OOPCQkJCxcuHDt2rLcb27E8H6PkNlaZ+vTTT0+YMGHmzJkKheJ2ZYxGY3Z29qZNmzZtcnN5p5s3b+7Zs6eurs5xZMaMGY7lmWpqajQajcFgEAqFNptNrVZnZGQIhcJWF0GOAkAA0ul08+bNU6lUCxcuzMjIUKlUrQowDHPhwoVdu3atWLEiPz//T3/6k1fa2Tn4GqPkBlaZOm/evLVr13766adjxoxJTU294447IiIiFApFS0vLzZs3CwsLT58+nZubGxQU9OSTT7rXjqampm3btsnl8nvuuSc6OtpkMlVVVTki3Gq1ajQasVg8d+5cpVJZVFS0d+/e/Pz8UaNGuVcdAIA/oShqyZIlEydOFAhuvTMKRVEDBgwYMGDAggULTp061cnN62S+3k8dN27cqFGjdu7cuXnz5n379rUtoFarn3rqqczMTLlc7l478vPzrVbr9OnTg4ODCSFisdj+xq64uNhgMEybNk2pVBJCkpKSysrKCgoK0tLSfGFSLACAdymVytTU1NsFqrPw8PBJkyZ1QpO8yNf7qYQQiUQyY8aMGTNmVFZWnjt3rrKysqmpKTg4ODo6Ojk5uXv37p40wmazXb16tU+fPvYcpWm61X8Z5eXlIpEoNjbWcSQ+Pr6oqEir1cbFxXlSNQCAf1i7dm1RUVFmZuaUKVPa3vsNKB3UT220mAQUUYhcDVPiPO43JiYmJibGg1bdQl1dnc1mCw8PP3DgQFFRkdVqDQ8PT0tL6927t72ATqcLCQlxDtqwsDBCiF7PeTFGAAC/lJaWdu7cubVr13744YcjR46cNm3ayJEj2w46CQw891ObrWaD1fTiyS3rRjzkuqRPzKVpaWkhhJw+fTo4ONg+IO3cuXO7du2aOnWqWq0mhJjNZplM5nyKRCIhhJhMplaXSk9Pb3v9vDyP9u4BAPB9U6dOnTJlyunTp7Ozsw8ePHjo0KHw8PDJkydPmzYt0NYVoPnrp1ppWiQQvH/pwGfFR9mU94lMtWMYZsaMGfbsTEhI+Prrr0+cOGHP1FsWJoQ4b+Bqh/gEgIBFUdSQIUOGDBny3HPP7du3T6PRbNy4cePGjf369cvMzMzIyHAxd4MTX9+Xhqf5qQarefeNS38+yWEZfZ/IVKlUSgjp3r27ozMqkUh69ux59epV+7NVmUxmNBqdT7H3UO0nAgCAs6CgoOnTp0+fPr2iokKj0ezcufOtt95as2bNc889l5mZ6fn1fSpBO0KTxVRmuPnC8R+vNd3kdKJPZKpKpaIoqtW4JPtjAHt/VKVSXblyxWq1ikS/NLi+vt5+vNMbCwDQZfTs2fPxxx+/66673n333Rs3blRUVHi7RZ3Bk36q0WYx2awvn9q2V3vZjdNZZarZbLY/v+wgEomke/fu1dXVNpvNHqU0TVdWViqVSvvHuLi4y5cvl5aWJiYm2k8pKSmRSCS8j5YCAPAbpaWl2dnZOTk5N2/elMlkd99998SJE73dqM7g3lwammFowvz7yuF1lw+6XTWrTM3JySkoKFi8eDFf9+LbGjp06Pbt2/fu3Tt06FBCyKlTpxoaGhwLaKnVapVKdfjwYalUqlKpCgsLy8rKhg8fHqhD2gAAbquxsXHPnj0ajebSpUuEkAEDBixcuHDixIlurx/Q5bgxRqnJajpSdfXFk1uMNosnVbPK1O7du7/99tsnTpxYtmyZPfN417NnzwkTJhw6dOjq1auEEJFINGLEiP79+9u/FQgEmZmZOTk5WVlZ9o/JyckpKSkd0RIAgK6Ipuljx45pNJq8vDyLxRIREfHwww9nZmYG4iR+1vd+g4KCDFZTZUvDCyd+vKSr9LxmVpmampr66aefvvbaa88999zMmTN///vft5rZwou+ffv26dOnrq6OYZjw8HDHo1O70NDQWbNm6XQ6k8mkVCpv1wCsoQ8AgWnVqlU7duwQiUSjR4/OzMwcMWIEm2WV/BL7bmpQUJBCJP2+9DQvgUrYj1FSq9UfffTR119//dlnnx07duyll17qiD2DhEJhVFSUiwL2pR5cQI4CQGDq0aPH4sWLp0yZYl/DNZCxX0eptraWEPKHfuMeTxq57OSWI9UlHlbNYdyvUCicP3/+mDFjli9fvnjx4tDQUOdv+/fvv2rVKg9bAwAA7pk/f779TUNDQ6vfzw4lJSWO9en8GrcxSgqRRCGSvDPsgSv6qj+d3Kxtdn+FPs5zaYqLi6urq4OCghxDcO169erldiMAAIAvn3/++dixY5OTk1sdX7NmjVQqDYhMdWsdpVCxLDUiLmviM1uun/3H2Wz3auaQqXV1dW+++WZeXt6wYcOWLVvm+iYtAAB4RUhIyLJlyz744IP4+HjHwX//+9/ffvvta6+95sWGdRq319CnKCpIJJmVkDI7IXXFuexN105yve0BJ0QAACAASURBVALbJ9j79u2bP3/+iRMnli5d+tZbbyFQAQB80yOPPHLXXXctXbq0rq7OfuTLL7/84osvnn/++VuuiO6PKNavW5AIRCKBYOmAjN2Tnx0Swe0WLKtM3bdv39/+9rfevXt/8cUXM2fO5FRBJ9vvxNttAQDwAqFQuHz5cqVSuXTp0paWlm+//fbjjz9evHixj//25hPD+nV7wSJprEL1wci5H496WCUJYlkzq3u/NE0vWbLk/vvvb7tmva/BuF8AALlcvmrVqkWLFj3xxBNlZWVPPvnk7Nmzvd2ozsPj9qmhYtnobn32T/2/L6/mv3VhT7vlWWWq328KDwDQpTEMY7H8zwJAwcHBK1euXLx48Zw5cx588EGz2UwIEQqFvCw/5+P70rBf84ENAUVJhaJ5fYY93DtN0F7H0ifW0AcAAE9UVFTMmTPnll9t2LBhw4YN9vfz589/4oknPK/OtxK0DR77qQ4yoZgQYqVp18WQqQAAXZ5SqVy4cGG7xTpirR5f1BGhSgghRNTe0lTIVACALi8kJOTRRx/1dit8Bq/3fjnxt0zFer8AEIBsNlvbXahvx2KxiMXijm6SF3VYN7V9/papyFEACEA1NTVLly59/PHHx44d62IUUm1t7bfffltRUeHniz94L1T9LVMBAAJQZGTk5MmT//nPf77zzjvjx49PTk5OTEwMCwuTSqWNjY1VVVWXLl366aefTp48mZiYuGTJkltehKbpurq6xsZGmqZDQ0MjIyN9f/7kbXRUsxmGcf1nwjlTaZret2/fyZMndTqdzWZzHFer1U8//bQ7bQQAAM+IRKL58+dPnz598+bNWVlZmzdvblWAoqjU1NTly5f/5je/uWUqGI3GL7/80mq1Oo6oVKrx48dHR0d3bNM7gNtrE7pgoWmRQGBlaDHlajISt0ylaXrZsmVHjx7t3r27Vqvt1atXXV2dwWCIiIiIiIjwrMEAAOCR8PDw3/3udwsWLCgpKbl48WJtba19w+levXoNGjTodpvV2AkEgrS0tB49eoSGhlIUdePGjQMHDmg0mkceeYSXKa2diu9MNVjM2WWFLxzOvjzvedcPorllan5+/tGjR1999dUJEyakp6evWLFCrVbv3r37vffemzFjhictBgAAXggEgsTExFZbh7VLIpEMHjzY8VGtVut0up9++unmzZvdunXju40di+Hv3m+jxVSir/tj3vZrDfVsynPL1PPnz/fp02fChAmOIxRFTZ48ubS0dO3atWvWrOHWWAAA8FX2+8ByudzbDeGOj35qi9VistleOJy9++ci9mdxy1Sr1eq4xysWixsbG+3v+/fvv2nTJk6X6iCYSwMA4Daz2dzU1GSxWKqqqs6cOTNgwICQkBBvN6qz0QxDM8wHBT+9d/YI13O5ZWpkZGR+fr79fWxs7Llz5+yrchQXF8tkMq51dwTkKACA20pLS/fu3Wt/37dv31GjRnm3Pe5hPFjzodFiyrtR+lxeltFmbb90G9wyNSUlZe3atVVVVdHR0RkZGZ9++umNGzcIITt37szIyHCjegAA8B0JCQn2Bfe1Wu2pU6e2bds2c+bMtktJ7Ny5/panT526oOPbyIJb936bLCatoXFJ3vaLddVu18wtU5OSkpYvX84wDCFk7ty5Op0uJyeHEJKRkfHss8+63QgAAPAFEokkPDycEBITExMcHLxnz57i4uK+ffu2KuYr2XkbXMcomWxWmmFeOZqz5dpFD6vmPD917Nix9jdCoXDx4sWLFy/2sAUAAOCD7MN9dTqdtxvCHet+anh4uIW2fXbp5OsnD/BSM6tMtS+r0c6FRCKFQsFHkwAAwFNGo7GgoKCurm7QoEHR0dEMw9A0zWmmqVarJYQEBwd3WBu9z2w2m6y2lKge3RWhWkOD5xdklamPPvpoTU2N6zIDBw5ct26d5w3y0Pr1/3OXf8ECn75BAQDQETQazerVqw0GAyFk5cqV0dHR165de/TRRz/++ON+/frd8pSLFy/W1dXFxsYGBwdbLJaKioozZ84oFAqu81x9Aut+alNTU7BEkhbda++9C78vPv/X/N0e1swqU5944onm5mbXZSIjIz1sCi8QogAQ4E6cOPH6669PmTJl5syZr776qv1g7969k5KS8vLybpepMpmspKTk/PnzjiO9evVKT0+XSCSd0Wh+cRyjRBESJBI/lDRobt/Bf83f/c2VM27XzCpT7777brcrAACAzrRly5ahQ4e+/PLLhBDnm729e/e+fv367c7q3bt37969m5qaDAYDRVFKpVIqlXZGczuEO3NpJEIhIeSloeOfGjj8//KyTlZXuHERN/el0el0paWlZrM5KioqPj6e5aZ9AADQ0W7cuDFu3Li2xxUKRbtP8YKDg/3hAaoH6ygFiyXBYslnEx84WVPxf3lZ9aYWTqdzztTa2tq33nrr8OHDzH9X/o+Jifn9739/y79CAADoZKGhodXVt5hhWVxcHBMT0/nt6YpCJNLf9FD/9MAz6y+d/CeXIcHc+pcWi+WPf/xjfn7+tGnTli1b9uqrrz755JMikeivf/3rkSOc13ACAADejRw5cteuXUVF/7NKrUajOXfu3OjRo73Vqs5EMWxfLggoSioULeiXeunh5+5V92dZNbd+6v79+ysqKlavXp2cnOw4+NBDDz377LPr16/voqtYAQD4k3vvvXfPnj2LFi0aPny4Xq/Pzs7etGnT2bNnhw8fHig3FPnb600qFBFCVoyc/EzyyD/mbW+3PLdMLS4uvvPOO50DlRAiFotnzJjxxhtvcLpUB8Ea+gAQ4KRS6fvvv//555/v2rWrqanp0KFDUVFRCxYseOSRRwJl7Avf+6cGi6V9w6Sbps5l2tvunFumikSilpZbPLA1Go0+smktchQAQCaTLVq0aNGiRUaj0f7R2y3qZLztn+osRNz+QGhu/2ZJTk6+evXqtm3bnA/W1NRs2LChVecVAAA6DU3TTbditVqtVqvjo9ls9nZLOwXD+sU3bv3U4cOHjxgx4o033ti6detdd90ll8tv3Lhx5MgRoVD42muv8d86AABg4caNG3PmzGm32Pz585944gnPqztzZn+rI4MH4x4hIVwzlaKolStXbtiwITs7e/PmzYQQuVw+cuTIhQsXJiQkdEgDAQCgPSqVynlHk/379xcWFo4bNy4uLs5ms127du3QoUODBw8eOXIkL9X5eoJ2QAeUJc7zU8Vi8fz58+fPn282my0WS1BQEEV1yJ1rAABgSaFQzJ492/4+Ly/vxo0bX331VY8ePRwFioqKnn32WavVnX22u54ulKkOEonEB9eBxLhfAAhwW7duzczMdA5UQkhSUlJ6evrWrVsHDx7srYb5gRaLRS4WuyjgTqbW1NTs3bu3pKTEYrFERUUNGzZs6NCh7raQZ8hRAAhwOp3ullM+GIapr6/v/PZ4AcP/3dNGk+lqfV2/yCjXxThnalZW1jvvvGM2m2UymUwm0+v1GzZsGDZs2D/+8Y+goCB3WwsAAPxITEzcsWPH9OnTY2NjHQcvX7588ODBmTNnerFhXVSLxWK0WV/cvWvPtasXn1niujC3TC0qKnrjjTeGDRv2zDPPqNVqQkhLS8v27dvXrVv3/vvvv/jii+63GgAA+PDYY48dPXp0/vz5o0aNio+Pp2n62rVrR48e7dat28MPP+zt1nUKnp6n2miaUNS6E8fWHv+J5SncMjU3NzciImLlypXi/95Qlsvls2fP1uv1P/zwAzIVAMDrYmJiPvnkk08//fTQoUMHDx4khISHh993332PPfZYWFiYt1vXGVwv5MtSo9mUW1b6fI7GbLOxP4tbplosFrVaLW7zhLZv374Wi4XTpQAAoINERUUtW7aMENLc3CwQCAJvHSWPNJnNFY0Nz+3KvlTbztZ4bXHL1JSUlKysrMbGxpCQEOfjJ0+eTE1N5Vp3R8C4XwAAhwAd5uJuP9VotdoY+uV9OduvFLp3BVaZarFY7KPIUlJSJk2atGTJkgULFtx5550ymayysjIrKys/P//NN990rwX8Qo4CQICzWCy3m4cqEona3mj0Q9zH/dIMY6Xpz86cWnUkz5OaWWXqgw8+2Gp3+JdeeqlVmddff33dunWeNAUAADy3evXqrVu33vIrvtYm9Bv2jXoazaYTNyqe26XRm4weXpBVps6dO9dgMLguEx0d7WFTAADAc+PGjevZs6fjI03T5eXle/bsGTJkyIgRI7zYsM7D+t5vZGRkk9m8YOuPp7Q3eKmZVabOmjWLl8oAAKCjDR06tO06PA899NDTTz/N1+J3vr6GPutM1el0UqFw06yHXj2w76vzZzyv2f21CQEAoKuIj48fOnTo999///LLL3t+Nd9KUA+YzWaxUEgIeXF0+qLUtOd3a45VlHtyQc6ZStP0vn37Tp48qdPpbE6zdtRq9dNPP+1JUxwMBoPFYpHL5VLp/2wAa7PZtFqt0WhUqVQRERG81AUAECDEYnFdXZ23W9EZ3JifqpBIFBLJx9PvPVtV+dyu7Jstze5VzS1TaZpetmzZ0aNHu3fvrtVqe/XqVVdXZzAYIiIi+Ao5g8GwadMmk8k0cuRI57Wea2pqNBqNwWAQCoU2m02tVmdkZAiFwlanYy4NAEArDMMcO3bs4MGD9913n7fb4tNCpdLRveLyFjzx1bkzKw8ddOMK3DI1Pz//6NGjr7766oQJE9LT01esWKFWq3fv3v3ee+/NmDHDjerbys3NDQoKMplMzgetVqtGoxGLxXPnzlUqlUVFRXv37s3Pzx81alSr05GjABDgPvjgg507dzofaWxstFgsPXv2nDdvnrda1ak8WEdJQFEykWhe8uB5yYNf3r9786WLnE7nlqnnz5/v06fPhAkTHEcoipo8eXJpaenatWvXrFnD6WptFRUVabXaSZMm7dixw/l4cXGxwWCYNm2aUqkkhCQlJZWVlRUUFKSlpQXEXCsAANb69u1rNP46J4SiqJCQkPj4+LFjxwbKL0yP1yaUiUSEkL+PnfjM0OHP7co+X13F8kRumWq1Wh33eMVicWNjo/19//79N23axOlSbbW0tBw6dGjkyJFtF/4oLy8XiUTOeyzEx8fbAzguLs7DegEA/ElqaurQoUPtPRBntbW1EokkNDTUK63qXPzs9RYikYRIwr+674Ej5defz9E0s1iCV8CpgsjIyNraWvv72NjYc+fO2d8XFxd7vp6kfYH+fv36tf1Kp9OFhITYJ+fa2VeC1uv1HlYKAOBnPvnkk88//7zt8RUrVnje+ekSKIbti40QqXSSus/pRX9YMnxku4U5r/e7du3aqqqq6OjojIyMTz/99MaNG4SQnTt3ZmRkcLpUKyUlJdevX589e/Ytv7Vv1+p8xD7LqtVjVwAAuB2r1ercM/FnPO315iAUCISEPJmaZqVp1yW5ZWpSUtLy5cvta//OnTtXp9Pl5OQQQjIyMp599lm3m2symXJzc295s+J27G2gqNYd/PT09LaF8/I8Wr8RAMD30TTd3NxMCLFYLBRFNTU1OX9148aNq1evTpo0yXsN7PLkovafRnOenzp27Fj7G6FQuHjx4sWLF3NuVxvHjx8nhERHR2u1WvLfO7qNjY1arTYyMlIsFstkMudH7uS/PdRWE1gJ4hMAAtXVq1cff/xxx8ctW7a0KhASEjJmzJjObZSX8N1PZY9bpn755ZdHjx7lfa18g8HQ0tLSatHngoKCgoKCBx54IDIyUqVSXblyxWq1ikS/NLi+vp4QolKp+G0JAEAXFRUV9cwzzxBCDh48KBKJRo8e7fhKIBAolcrhw4cHyO9MXvYkdw+3TDUaja36i7xIT093Xtm5vr5eo9GkpKT069fPvlFrXFzc5cuXS0tLExMT7WVKSkokEklMTAzvjQEA6IrCwsLmzJlDCOnRo4dQKAyULqmP4ZapQ4cO3bhxY319Pb//2Gk1ecZisRBCZDKZ4/GqWq1WqVSHDx+WSqUqlaqwsLCsrGz48OFt11ECAAhwjid0gaur9FMHDRr029/+dunSpYsWLUpKSlIoFI6vKIrquNnEAoEgMzMzJycnKyvL/jE5OTklJaWDqgMA6Fpomm5sbBSJRAqFwmg03m5OhFQq9XzeI/H9fWk6RovFYqOZYKmrvX24Zer+/fs3btxICHn++edbfTVw4EC+nrNGRka2XY4/NDR01qxZOp3OZDIplcrb/WeB9X4BIADduHFjzpw5qamp77777po1azp6T3JfT1C++6lWmhZQ1Nrcn/7wm3amqHLL1D59+ixcuPCWX3XOnuT2pR5cQI4CQABSqVR//OMf7b+HJ06cqFarb1nslovq+B9+xyg1mcwHikr+tHWXjaZ5ztSEhISEhAT3mwYAAB1AoVDcf//99vcpKSkB/2iMn7UJm0zmcp1+6RZNUfVNlqdgT3IAAPAvHvdTjVar1Ua/sj1Hc6mI04m+uCc5AABwYh+j1G4xvsYo+TGaYWw0/Z+jJ1cfOOLG6T63JzkAAHBlH6PUbjG+xij5Onf7qU0m07Gyihe2aJpMZveu4HN7kgMAAFf2MUrtFsMYpdsxmMw1BsMLm3eeu1HpSdW+tSe55zCXBgACkPMYJWBPIpGYbTbCkBW7Dvx49oLnF/ShPcl5gRwFACCEFBYW5uXlabVaiqJiY2PHjRsXQLM2WPdTVSqV1UYv2rjlWFk5LzVzy9TIyMj8/Hz7e/ue5IMGDSI87UkOAACeo2n67bffti/7EBoaarPZDAbDf/7zn7lz5z711FPebl2nYJ2p1dXVQRLx2tkzCrRVL2zZWdtk8LBmX9mTHAAAePHjjz9u3bp1zpw5c+bMsa/NXlNT85///Ofrr7/u3bv35MmTvd1AH2LfijtUJh2R0GvvHx7feOrc6zkHPbmgT+xJDgAAfDlw4MDYsWPt+77ZRUVFvfjii9evX9+/f38gZKobY5QEFCUTi+akJs9JTf7bjr2bz110r2qf2JMcAAD4YrFY7rjjjrbHk5KSysv5eWro69ydSyMViQghr0wdv2jMsBe2aM7fqOJ6BX9bRwnjfgEgwKWkpJw6dWrevHkU9esSfVar9ezZs3x1Un19XxrP1lEKlkqCpZL18+7PLy3/05adBjOHuaruZGpNTc3evXtLSkosFktUVNSwYcOGDh3qxnU6AnIUAALcvHnzXnjhhb/85S+zZ8+Oj4+32WylpaVffvmlSqWaMWOG2WwmHu/O6VsJ2gYvq/2GSKXj+/bOX/rUx4ePv3fwKMuzOGdqVlbWO++8YzabZTKZTCbT6/UbNmwYNmzYP/7xj1ZbiwMAQOf78MMPCwoKCCEHD7YebjN16lT7G4FA0PZb/8HTvjRCihIKhY+PHDp/WMpL23fnXG5/7V9umVpUVPTGG28MGzbsmWeese8l1NLSsn379nXr1r3//vsvvviimw0HAACejBkzJioqynUZgUDQOY3xDl73epOLRUQsWnlPxtPpw6j2usDcMjU3NzciImLlypWOmwZyuXz27Nl6vf6HH35ApgIAeN2IESNGjBjh7Vb4mxCZtH9MtxaLxXUxbplqsVjUanXbu/B9+/a1tFcTAABAJ+B3T3Jn8vYeQnNe8yErK6uxsTEkJMT5+MmTJ1NTUzm3rgNg3C8AwOXLlzdv3lxeXt7U1GRfUcBu5syZAbEscIdlaru4ZWpaWtqkSZOWLFmyYMGCO++8UyaTVVZWZmVl5efnr1q1yvzfAcdisZhq965zx0COAkCAO3bs2AsvvCCXy/v27dujRw/nr0JDQ12fW19fr9PpKIpSqVRKpbIjm+mfuGXq/v37f/jhB0LISy+91OqrefPmOd6vXbs2OTnZ88YBAABXP/zwQ58+fdasWcNpLsb169dzc3OdNzaPj48fP368XC7vgDZ2sK7ST+3Tp8/ChQvbLRYTE+NuewAAwCM6nW7UqFFcJzc2NDTExMSMGzcuKiqKpunLly//9NNPe/bsueeeezqonR2n456ntotbpiYkJATQbkEAAF1QcnLytWvXuJ511113DRgwwPExJSWlqqrq2rVrJpNJKpXy2sCuymAyiwQCqdhVbvr1FCUAgMDz6KOPVlRUfPXVVy0tLezPajsIJjg4mBBis9n4bFznYFi/2Gkymi9XVM9dvaHdM/xtvV8AgAAXHBw8Z86clStXfvTRRyEhIc7LOzz44IOPPPIIm4vYVzRUqVRdcoE8/u79Gi1Wi832102795xrfxEl4n+Zun79euePCxYs8FZLApfzv3YZ7z3WAAhUOTk5K1as6N69+8CBA+19TYc+ffqwvMihQ4caGxtv9zB1yZJ016evXp3HsqKOwMu0E5phbDTz2YGTa3ceYX+Wv2UqQhQAAtz27dsHDhy4Zs0atxcgPHXq1MWLF0eMGBEbG3vLAt6NzPZ5/I/5JqP5+NWf//z1ToOJw6Y0xP8yFQAgwFksltTUVLcD9ezZs/n5+ampqSkpKfw2rPN4kKkGk7lGb/jzN5qCnzlvnkqQqcA/3O8F8KrU1NRLly65d+65c+eOHDmSkpIybNgwflvl+8xWG8Mwr2/ev/X4RbcvgnG/AAB+Ze7cuVar9a233iorKzMajWYnrgfxFhQUHD58eNCgQV19CX6KYfuyYxjGaLFuOnJ26LL3PQlUgn4qAICf+eCDD06fPn369OktW7a0+mr+/PlPPPHELc+6evVqXl6eUqlUqVTO3Vy1Wi2TyTqwuR2B9c2y4OBgg9Fc8HPlsq931jYaPK/Z3zIVa+gDQIBzsX/qoEGDbnfWzZs3CSF6vf7AgQPOxyMjI7teprImkUjEImGR9iYvgUr8L1ORowAQ4NzbP3XYsGH+8wyVdT+1rq5OIhLOHjVw9qjk5d/v8fDGL8HzVACAAMEwjE6n83YrOgPF+mUnEYkkIuGf7x2fteyxgXEerVePTAUA8HOVlZXr16+fPXv2d9995+22dAq31iZUyCTxUaqPFv32vcdnBMsk7tXsb/d+AQDAzmQyHTx4MDs7+9SpUwzDJCUluXie6lc8mNAXIpOO7d87d/lT6/efeF/DYQUlO2QqAIC/uXTp0o4dO/bs2WMwGAghEydOXLBgQXx8vLfb1Uk83OtNQFECoXD+b1Lnjkn527c5OWdZrfRr52+ZinG/ABCw6urqdu3alZ2dXVpaKpPJxo0bd/fddy9dunTo0KGBE6h8kUlEhJC/z854ctLwZV9riitvsjnL3zIVOdohnBc5o2nvtQMAbuvzzz9fv349wzCDBw9++OGHx40b58dzYNrB32JuITLpHT2ivlz80MGLJS9v2NVueX/LVACAwHT9+nWbzXb33XfPnz//dmvf8+XMmf2tjgwe7EP9GV72pXEWLJNMGdz37pQ7bLZ2OhXIVAAAf3DfffeZTKY9e/ZoNJoBAwZMnTp14sSJrfZ644tPJegtdMCi4yKBgBBCCduZLINMhdtw3gYV93sBfN6AAQNWrFih1+tzcnKys7PffPPN1atXp6en0wH4/2+HbeRBUe30gZGpAAD+Q6lUPvDAAw888EBhYWF2dvbu3bttNtuHH35YWFg4efLkAQMGtJsK4AlkKgCAH7rjjjvuuOOOP/zhD7m5uTt27Ni2bduWLVt+97vfPfbYY95uWoejvLfjpL9lKubSeELg9OiFbmryYksAgBdisXjixIkTJ06srq7Ozs4ODw/3dov8nL9lKnIUAKCtbt26BUIP9Rcd1k212miRy2FK/papAAAQ4DxcR+mWjGarxWqTikVE6KoY1tAHAAC4LRvNWG30l7uOj392LdPek1r0U+FXeIYKAP6Av35qU4v5xOXrf/1E02yysCmPTAUAAP/CR6YajOYaXdNf/q25VFbF/iwfylSDwVBXV2c2m0NDQyMjI9tOorLZbFqt1mg0qlSqiIiIW14E434BAAKchzNwzRYrzZBV3+zbceQi13N9IlObmpp27txZU1PjOBIeHj5u3Ljo6GjHkZqaGo1GYzAYhEKhzWZTq9UZGRlCYeuHxchRAIBA524/lWEYs9X23f6z73570L0r+ESmGo1GsVg8adKkHj16iMXiioqK/fv3Z2dnP/zwwxKJhBBitVo1Go1YLJ47d65SqSwqKtq7d29+fv6oUaO83XYAAPAxbmVqU4vpwrXKv/xbU9fY7HbNPpGpERERM2fOdHxUq9VNTU2HDh0qLy/v3bs3IaS4uNhgMEybNk2pVBJCkpKSysrKCgoK0tLSxGKx19oNABCQ/GxfmmaTRd/U8tdPNKeLKjys2icyte2jU/teCo6ln8vLy0UikfPuRfHx8UVFRVqtNi4urtPa2dVRTv/+YCysxrABALTlUwl6C6z7qd26daMZ5v3v877bf4aXmn10fmpxcbFAIOjevbv9o06nCwkJETjtjB0WFkYI0ev13mkfAAB0fQ0NDS1Gy9yMIQN7d+flgr6YqcXFxcXFxSkpKQqFwn7EbDbbH6w62D+aTCYvtA8AAHwYxbB9GY1GhVzSq1vYe3/87TuL7w0JknpYtU/c+3VWUVGxb9++hISEtLQ0F8Xsi1m0vWmcnp7etnBeXh6PLexahAm9HO9tpT97sSUAAJ2E+xilkCDp6GT1rref+mrXiXWbD7tds29lqlar1Wg03bt3nzx5snNeymQyo9HoXNLeQ5VKW/+bIpDjEwAACHFz3K+AoiQi4dyM1Acnpqz4fPfu44XuXMSdmjtGZWXljh07unXrdvfdd7eaeKpSqRobG61Wq+NIfX29/XhntxIAAHwbxfrVlkwiUsgkL8+ftOHvjyTGRnKt2lcytaqqKisrKzIy8u677xaJWvee4+LiaJouLS11HCkpKZFIJDExMZ3ayq5DGK6yv2ylPzte3m4UAECnYFi/biNYLk2KjfrkxQdfezLT9eZurfjEvd+GhoasrCyGYXr37l1cXOw43q1bN/sahGq1WqVSHT58WCqVqlSqwsLCsrKy4cOHt11HCQAAAl17OjhT2wAAIABJREFUu8ewFCyXThzaNyPtjnU/HvpMc5zNKb6SqWazmRBy+PD/PBkeOXKkPVMFAkFmZmZOTk5WVpb9Y3JyckpKildaCwAAvozH/VNFAgEh5HfTRzw8OfXv/9nVfnneavZAbGzs008/7bpMaGjorFmzdDqdyWRSKpUymeyWxQJ5DX3LpNRfP+w56b2GAAD4FblULJeKX3sy00rTrmfb+ESmsmdf6sGFQMtRAABojb9+qrNgefuzV7tYpgIAALjG471frpCpAADAjY+voe9FyNSujZL+umSjGM9QAaBT+HqCop8KAADAC9z75U0gj/sFAICOQ9OMyWyVy1xt2u1vmRoQOeq0zhRjMnuxIQAAvqgD+qmGZvPxc6Ujh/R2XczfMhUAAAIcv/d+m1vM1Tcbl7+748q16r0b/ui6MDIVAAD8C0+ZarZYaZp56+M9u3IvsjwFmdplCPsl2t/YLhW7LgkAENg8DVWGYcwW24+aM2u/OMDpRGQqAAD4FQ/v/TY1my5e0S5fna1raOZ6LjIVAAD8i7uZ2txibmg0Ln9vx7lLFe5dwd8y1c/m0jQ8PMLxPvTrn7zYEgCALoN7plqtNkpAffBl7uZdZzyp2d8y1Q9yFAAAPEGxLikUChmGGE2WnNyLb3y02/Oq/S1TAQAg0LHup0ZERDQ1mxb/dVNxaTUvNSNTfU7FslGO9z3/ecSLLQEA6JJYZ2pdXZ1CLvn4nw9v2n7io6/zPK8ZmQoAANz4+L407Mf9Wq1WgYCSCISzp6fef3fKqg9z9hy67EnVyFQAAODGpxL0VjgPUpJKRISQFxZlzL9/xKvv7rhaVuNexf6WqV103C/u9wIA8MbduTSKIGnvOOm6FXN+Ol2y4n2NxWLjegV/y9QulKMAANAhPFvzQREkGTey7/iRd3yy8fAXP3CbxCjwqGYAAAAfQ7F+3Y5QIBAIqPn3D9/x2e/HDO3DvmpkKgAA+BeG9cslmVSsDJG/siTz438+HBsTxqZmf7v324UUfZjmeJ/0FJ6hAgDwhOFzs7fgIGn/pO7/eWv+vsOF7RZGpgIAwK/MZnNzc7NEIgkKCvJ2W9zE7/6pdkEyyZSx/a1W2nUxf8vU9evXO39csGCBt1oCANC15ObmlpeX6/V6QkhSUtKkSZO83SLfIhYJxSKh6zL+lqm+H6KW3fH2N0kZx73bEgAAZzqdrlu3bnfdddfRo0e93RbPdEA/lSV/y1QAAHDPjBkz7G+6eqZSvD5P5QSZCgAA/gX9VP9myol3vJdmlHmxJQAA0HGQqQAAwM3OnetveXzqVN8Y0dIx/dRmg4khRKGQuiiDTAUAAG58JTtvg/e5NCaTlWGYd9/d9fzSTNcl/S1TfWcN/aTjEsf7ojTc7wUA6Cz8jVFiGMZisW3ZfOLjj/YTQgIuU7GGPgBAoOMpUg0G08ULFa+v3KbXt7A8xd8yFQAAApyLxfFZamk26xtaXn9tW0FBOacTkal8mnf51z/9r+6M9WJLAAC4Ki8vb2xstL9vaGi4dOkSISQ2NjYkJMSr7eLOg36q1WqjCPXhh/uytp9243RkKgAAEELIhQsXSkpK7O+rqqqqqqoIIZMnTw6QTGUYYjJZcnadX/3uLrdrRqYCAAAhhEyZMsXbTeAJ9zFKBoOp5Gr1yte2VVc3eFKzv2Wq74z7BQAAr2D/PFUmkxmNluZm879e337ixDXPq/a3TPVKjjoeo+IZKgCA97HupoaGhoqEgg8/2MtLoBJCBLxcBQAAwFcwDMtXdXW1SCx8dsmUT9c/kZgU7XnNyFQAAPAvDOsXIYSQ4GBpQkLk2+88/Le/3yeVij2p2d/u/Xaal6+edbx/rc8gL7YEAACcuTc/VaGQjknvu33Mc19+cejLLw67VzX6qQAA4F9Y3/ttdZ5AIBAKBQ/NGbll2x9Hj0lyo2Z/66di3C8AQEc7c2Z/qyODB/vS71vP1iaUycQymfhPL06vmFf/+mvbf/75Jvtz/S1TOzRHP73+k+P97+JGdFxFAAC+zLcStC0+1tAPDpbdcUf3dR8+eijvyr/+mcXyLNz7BQAAv0IxbF/tCgqSTpjYf+/+P896YBibqv2tnwoAAIGOv73eCCEikZAQ8tiC9NkPDqfaG/6ETG3Hrhu/ju+d0gP3ewEAApFcLpHLJWaz1XUxZCoAAPgXXvupziSSdkKzK2WqzWbTarVGo1GlUkVERHi7OQAA4JM6KlLb12UytaamRqPRGAwGoVBos9nUanVGRoZQKGxVjK+5NI5bvlN6YD0HAICuhOqwfmq7ukamWq1WjUYjFovnzp2rVCqLior27t2bn58/atSoViUxJxUAALyla8ylKS4uNhgMo0ePViqVhJCkpKTExMSCggKLxeLtpgEAgI9xdx0lz3WNfmp5eblIJIqN/XUntfj4+KKiIq1WGxcXx1ct/y476ng/pcdIvi4LAACdqgNu/TIMY7XSFCEicetnjs66Rj9Vp9OFhIQIBL+2NiwsjBCi1+u91ygAAPBJHPelaZehyXQ878qcca/bbLTrkl2jn2o2m2UymfMRiURCCDGZTF5qEQAA+Cgexyi1NJt1N5v+9efvLp/7mU35rpGpbTEMQwih2qxpkZ6e3rZwXl5eZ7QJAAB8AR+RarHYCCEfrcre+eMJ9md1jUyVyWRGo9H5iL2HKpVKW5X0JD4TepU73u9up38PABC4fH1fGs9ClWEYs8m6a/PJda+zXTrfoWtkqkqlunLlitVqFYl+aXB9fb39uFfbBQAQiHwsQdvwIFKbm4zFl7T/WvbtzZpGN07vGpkaFxd3+fLl0tLSxMRE+5GSkhKJRBITE+PdhgEAgM9x63mqscVsaDS+8fIPZ/Kvul1z18hUtVqtUqkOHz4slUpVKlVhYWFZWdnw4cPbrqMEAAABjs0mbs5sVlogpD57f8+Wr454WHXXyFSBQJCZmZmTk5OVlWX/mJycnJKS4u12AQCAD2IbqmFhYSaj5eCu82//5UdeKu4amUoICQ0NnTVrlk6nM5lMSqWy1dQaB77W+wUAgK6KdT+VpmnaRgcHy+RBkpZms+c1d5lMtbMv9eACchQAINCxfp7a0NAgV0iHj7vzu7yXN35y8KsP9nlYc9dYRwkAAIAtjuv9CoUCkVg4a0H694deGTWxvyc1I1MBAMC/uLU2oUwmDg6VPb/8t+9vfCaud5R7NSNTAQDAv3iwL40iRJbUv8e7Xz/1wmuz2i7V1y5kKgAA+BeP93oLUkjH3j1Qc/Yf988fzalmZOovbrlQsJ/x+58RP6Af8Puf0e9/QJ/Ax/6pIpGQEDLvmYnf7HtxyMhEljV3sXG/7cJcGgCAQMff/qnyIIk8SPLymw+VXKlc9efv2i3vb/3U8U683ZZ2rF+/3ttN6Fh+/wOSAPgZ/f4HJIHxM/LuzJn9rV7ebtH/4qOf6kwRIhswJP7fW5cIRe2Epr9lqjPnPiub4+wLc7oyp+o6v0ZertzJf6SdX2NX/CPt/BrxR8p7jVx/e3SawYPHt3p5u0Wt8L0pOSEURcnkEvsNYRf87d4vAAAEOv7u/XKFTAUAAP/i1r40vKAY79XNOwyoAwD/lpeX5+0mkPT09NWrvd8Mh7q6uvDwcMfH1FRqau/nWJ67s+RtfkPQr/qpvvBfGwAAeBnu/QIAAPCjw+6/mk1WidRVbvrzuF8AAAhEfM+lIYS0NBkrSqrbLYZMBQAAP8PnXBqL2WoxWT945fuFo19t9+Er7v0SQoher6+trRWJRD169BCLxd5ujqcMBkNdXZ3ZbA4NDY2MjGy7DLTNZtNqtUajUaVSRUREeKWRvDCZTC0tLSKRKDg4uNVXfvB3arPZKisrm5ub5XJ5dHR0q5/CaDRqtVqGYbp169b2x+8SamtrGxoaRCJRRESEQqFoW6CqqqqxsTEoKKh79+5urGbuFQ0NDTRNh4aGCgS36LG4/on85n9M7+Pp1i/DMGajZefXhz/8y/csT0Gmktzc3AsXLggEApqmpVLppEmT4uLivN0oNzU1Ne3cubOmpsZxJDw8fNy4cdHR0Y4jNTU1Go3GYDAIhUKbzaZWqzMyMoTCdiYy+yCGYXbs2FFVVRUfH5+Zmen8lR/8nV69ejU3N9doNNo/CgSChQsXOv6aLl++nJubS9M0RVEMw6SlpaWmpnqvsZzp9fo9e/ZUV1fb/44EAsFdd901evRoR8z8f3vnHtXkkTbwN8mbe0IICQgaEBCoKOBt0QoLarWAUut3qEoRrd2tuq79qtvtRWvraU+Pp9jit5XVdT1eurbV9bLWugql5X5AKiAqCraIAQSDCYSEJJAbb5L3+2PatzGBEC5KEuZ3+CPvZJ6ZeZhMnszMM88YDIb8/HyZTAY+pXw+f8WKFV5eXuPbbAdIpdKamhq5XI5hGIIg69at4/F41hmG1MhjBqZLMBb7qVqNXlz/8LPXTyo71c5LTXSbWl9ff/fu3QULFsyePdtoNP7www8FBQUZGRkD/mp2fQwGA5VKXbZsGZicdXR0lJaWfvfdd5mZmTQaDUEQk8mUn59PpVLBmL9//35xcXF1dXVcXNx4t33Y3LlzR6fToajtZ9gD+rStra2wsHDq1Knz58/38vLS6XTt7e2EvZHL5WVlZcHBwc899xyFQrl27VpNTY1AIAgODh7XVg+D4uJihUKRmpoaGBhoMpmuXbtWX1/v4+MzY8Yv10GXlZV1d3e/8MILgYGB3d3deXl5BQUFq1evHt9mO0Cr1SIIMmPGDI1G09raap/BsUaeNDBdgtHZVL3WqNXo97/x5e3KpuHKTvT91Lq6Oj8/v7lz55LJZCaTuXjxYgzD7t69O97tGiECgWDVqlXh4eFsNptGo4WEhMTGxhoMBolEAjKIxWKtVhsfHw9+RIeHh4eFhTU0NIAf126EWq2uqalJTEy0X2Fz9z7FcbyiokIgEKSkpAgEAiqVyuPxoqOjCU3v3LlDJpOXLFlCo9EoFEp8fDyHw6mrqxvfZjuP2Wzu7OwMCQkJCgoikUhUKhXMUDs6OkAGYJaio6MDAwMRBBEKhbGxsXK5nPgYuyBhYWGrVq2Ki4vz9R3gLushNfKYgekqjNRHyYyZcRw/mXV5w9z3R2BQkQluU1UqVV9fn/Wve29vb29vb1ceuo6x36EBO20WiwU8SiQSFEVFIhGRYerUqWAX56k1ckwoKysLDQ21X9H1gD6VSqW9vb1RUVFgXdc+g0QiCQgIoNPp4JFEIgUFBclkMnf5/qVQKHQ63Ww2EylmsxnHcRaLBR5BZ02dOpXIADrUjTrRhiE18piB6SqMyEVJrzUWXahZMfl/L58oG3HNE3rtV61WIwji7e1tncjj8WQy2Ti1aOwRi8VkMjkgIAA8qlQqLpdrPbcD6oN/hbvQ0NCgVCqTk5Pt3/KAPu3q6kIQhMFgXLlypaOjg0QiTZ48OS4uDjitYBim0+lCQkKsRby9vXEc12g07uLYEhsbW1lZ2dDQEBwc3N/fX1NTw2AwoqOjwbsqlQp5vBNZLBaVSgXp7siQGrndwLS/iMa1wugPc+1Xq9FLmjs/e/3ko1b50LkdMqFtan9/P4IgYKORgEajgXQPQCwWi8XiefPmEVuJ/f39DAbDOg9Q32g0jkP7RkRvb29VVdWiRYtsFAF4QJ8Cv6TS0tIpU6YkJSXpdLra2tr//ve/a9as4XK5gymIuFUnRkdHm83mq1evgthnHA7nhRdeIBx2PKATbRhSI7cbmK5lQe1x2qZOmjSp34Blv/FldUH9mNQ8odd+AZ4U8diajo6OkpKS4ODg2NhYB9mA+u5yUAFBkLKysoCAgPDwcAd53LpPQeN9fHySk5NDQ0OjoqJSUlKMRmN9/aBj3u06saampqqqKiYmZuXKlcnJyV5eXleuXCH81QdUBMdxN1LQhhFo5HZ96lo4vZ+qUqlwHH/n4Mb41NljUvOEtqlgR8rml6DRaBxwAuReSKXS/Pz8gICApKQk62HJYDCI4xkAoD6xOefitLS0SCSSiIgI6a/gOG40GqVSKXC89IA+BU213hL29/dnMplgTXgwBQlB10ej0dy8eTMqKiouLk4kEoWGhqampqIoWllZCTIAHW0+qP39/e7yKbVnSI3cfWC6HE7bVKPRSGfS2F7MN/+2/mDBrqCIgFHWPKHXfvl8PoIgPT091ok9PT0g3X2RyWR5eXl+fn7Lly+3Od/G5/ObmppMJhNxBAWo7y4q63Q6BEGKioqsE2Uy2aVLl+Lj42NiYjygT8ENGzYdR6FQgKMZiqJcLtdeQTKZ7MrHN61RKBQ4jvv7+xMpKIoKhcJHjx6BR6ITiT2L3t5ek8nkRp1ow5AaufvA9ADYXsyw6MDPc9+uKrizf/tXuGWEa10Tep7K5XL5fH5LSwuxVCiXy3t7e90uPoA1nZ2dubm5QqFw+fLl9mc3g4KCLBbLgwcPiJSWlhYajWb9BefKRERErHscKpU6ZcqUdevWTZ8+HfGIPp08eTKKotYOn2q1uq+vj/A/CgoK6uzs7OvrA48mk6m9vV0kErlLfAAwn7b+WYDjuEqlIubZgYGBJBKppaWFyNDc3IwgiBt1og1DauTuA9PVwC24k382giwuI3HVvDzJwZf+vGxkVU/oeSqCIPPmzSsqKiovL58zZ45ery8tLWUymcTBc7dDo9Hk5ubiOB4aGioWi4l0Pz8/8I0cEhLC5/MrKyvpdDqfz793715bW9uCBQvc5euYRqPZOHqQSCQURa1j1rh7n1Kp1Dlz5ly/fv3GjRvh4eE6na6iooJCoRBusbNmzbp3715hYWFiYiKFQqmurjYYDHPnzh3fZjvPpEmTeDxeXV0dm80WiUQYhtXV1anVaiIUFIvFioyM/Omnn0Agi87OztraWpFIZB0OzNUwGo3AZIJd4ebmZiaTSafTQ0NDESc0cveB6XKMwqMCRSkIgqx/e8VLf176tx1f15b+NCxxj7qTfGTcunWrtrbWZDIhCMLj8Z5//vkBT227BRKJ5MqVK/bpCxcunD37lx14jUZTUFAARj6ZTAbbWu7rCnHixImAgACb2ITu3qc4joPQQmC9l81mL1682HqW9vDhw5KSErASTqPREhISIiIixq25w0etVldUVDx8+BA8oig6a9as3/3ud8RhEpPJVFZWdv/+ffAoEomef/55V94wViqV586ds0n08fFJT08Hr4fUyHUG5pBhll3/TvJkwWYnZX9QHHNgBLUa/YOfH2W/8WXnQwVIudR6gM5wFD8c2lQEQRAMw3p6elAUte4Yz0alUhmNRh6P58rfU6PBA/rUaDSqVCqggv1Xm8ViUSqVOI77+Pi46WzGaDSCGPpeXl4DqqDT6cCXO5fLffrNexIMqdH4Dkwnwyy7gU312eSk7A/K446NII7jBl1/yTc1h3aeRZywqRN97RdApVL9/PzGuxVPFZuoCJ6HB/QpnU53sNpJJpOFQuHTbM+YQ6fTHa8fsFgsIriSZzCkRuM7MN0uzPKgjN1ckUQiMdn0pPSFKZnx/9x9fsj8E9pHCQKBQCAAdwyzPCgW3Nk/56DSUQqF/McP/sfUb3KcE9pUCAQCgXhUmGWnI+gPbzrL4jLYXkzHeeDaLwQCgUA8K8zy+PkJQZsKgUAgkCcYZlmpVI6yhAHJy/slSEhq6mTb96BNhUAgEMg4MqygxDt2JDgubf/+6cTrJ+S1/fLLv722vecQ2lQIBAKBjCNEUGIigCIyeJhlcKHQaKiuHvQI6YIFx0ZX9vFxtKnQRwkyQdm7d29BQcHIZLu7uz/66KOGhoYRyCqVyra2NhCPwhqJREIEvB0QsViclZU14oW4r7/+Oj8/f2SykImAfazsJxpmeTDDOWqDiiDIMGLoD6vUfgOm69U7zgNtKmSCUlJSQgS1GS5arba4uLizs3MEsg8fPtywYcO//vUv68TKysqMjIzSUtt7nq3JyclBUdRmu8t5goKCPv/88ye0swXxAJ5+mGVgPjs7tXo9Zp0yenCncb5Ao64/90gBBR0ivgq0qRDIU2XWrFlpaWmnT59ubGwEKRqNJjs7OzIyMiMjYzCpmpqaurq6devWjbjexMREoVB46tSpEZcA8WyIoMR3797VarUtLS1PIczyrFkHa2sfFRa25OeLlcq0mpqa5uZmcKfpqMrFnf5zAq1aV1fS8ErY6//868khM8P9VIhLIJfLWSwWm82+d+9eV1dXUFCQ9Tk5gEQi6ejowDAsODhYJBIR6RiGqVQqHo9HoVAaGhrUavWzzz4L5nODiVjjoEaNRvPzzz9jGDZt2rSAAEcXKxoMBrFYrFQqvby8IiMjHV97uXXr1qqqqk8++eTEiRNUKvXAgQMajSYnJ4eIdmvPxYsXY2JipkyZQqQQ/7H79+93dnaGhISAd3Ecb2xsVKlU4eHh1oGWSCRScnLy2bNnt2zZ4qkBKSGjJD4+HsOw8vLy8vJy5NegxE+0RoVCERHxUnj4HYOBrddf7ehgisUcg4FNodB8fHwEAoFQKBQIBHw+38HoGIAx2k/V9xn6erSfbjx4u+yukyLQpkJcgvT09NTU1Pb29rq6OgqFgmHYihUrdu7cCQaSwWB45ZVXpFIpjUYzmUwWi2XRokUffvghlUpFEKSpqWnr1q1vvPHGxYsXOzo6EAT5z3/+4+3t7UAEYDAYduzYMWCNCIKcOXPm2LFjJpOJQqGYTKaUlJR3333XWpzg/PnzR44cwTAM3CzN4/H27NmzYMGCwZRlMBi7du3avn37iRMnZs6cWVhYuG3bNnuLTqDVaq9du7Z582M+Henp6StXrpRIJNevX0cQhEQi/elPfwIqNDY2WiwWKpW6e/fuZct+u7IqLi7u+PHj1dXVixYtcq5bIBMLFEWXLVsWFxf31MIsk8lkgSCsqcmbRFIymVomU+/trWAwtBhG1+vZXV2s9na2Xs/BcSqfzydMrI+Pz4Aj8TdGbVNN/SYKSvli978vHRqeFwK0qRBXIS8vLykpad++fSiKAisVHBxMLIempaUtXbpUKBRaLJbCwsJ9+/Z99dVXr732GiF+7NixzZs3Jycnm81mDodjsViGFHFQY1lZ2eHDh5OTk//yl7/QaLRLly4dOnSIy+Vu377dvuX+/v779++fOXMmnU6XyWRZWVkffvjhhQsXOBzOYMrOnj07LS3tzJkzHA5nxowZxO0lA3Lnzh2LxWJ/XV1ubm5aWtrHH39MIpH27t179OjR8vLyxYsX5+TkGI3G3bt3Hzhw4Pe//z0xK502bRqDwbh58ya0qRAHPM0wywEBAWAFqK+vT6FQdHd3KxQKmUxhMimYTC2TqeNypUxmn8WC6nQslYotlbL0erbZTPfy8gL2FWC79DI6m6rvM5Serfx8y5ERyEKbCnEVuFzuW2+9BX5+ZmZmVlVVnT9/Hlg4BoPx8q+H0SgUSkpKSlVVVVlZmbWBXLRo0dq1a60LHFLEQY1nz54VCoU7d+4E765du/bWrVuXLl3atGmT/ddNYmIi8drf3/+tt97KzMy8fv36kiVLHOi7cePGb7/9VqPRvP32247Xtdrb20HJNumBgYHbtm0DxwdfffXViooKLpdL/McyMjLee+89sVgcFRUF8pPJ5EmTJrW1tTmoCwIZFzgcDofDIVZr9Hq94lc6OhR6vZzJ1DIYWoFAzmQ+QBDcYGD39bG6u9l6Pau/n8HhcMASMTgIZMYxR5U9jlarpdFoYKRr1br2nyVZ6/8ubRmJByICbSrEdZgzZ471es78+fPr6urkcjm4uuTRo0e5ublisVin01ksFplMptVqrcXtL+UeUmSwGgUCQWNjY1JSkvW7cXFxV69eFYvFMTExNhVZLJaSkpJr1651d3djGAbcK7q6uhzr++WXXyIIQiKRioqKwsPDHeRUq9UIgtgvxEVFRRHn8YEjCWE+iZTu7m5rES6XC0qDQFwZJpMpEokIHwgMw4hZbGenoq9PTqP1slg6Hk/h7/8QRU16PUuvZzc1oTdutPj6suWkn7gkp2748bWwz507FRsbFz4twqg1Zv/xH9V5N0fTcmhTIa6CzS1X4FRcX1+fr69vS0vL1q1bJ02alJCQIBAIKBRKeXl5XV2dA/ERiBA1cjgcs9ls8y54tLHKgKysrKKioqVLlz777LNMJtNkMjU0NGC2kV0e4/bt2xcvXszIyDAajWfPnl28eHFkZORgmYHHk32BTOZv4bzB/aP2KWaz2VrEaDQ69p+CQFwQKpXq7+9PLNWYzWalUklMZFWqLipVw2RqeTxNcjKalra2p8fgdNnBRqPCYrGc3vvN2X3fjr6p0KZCXAWbo5PgkcfjIQhy4cIFGo129OhRwmbU19c7Ls0ZkcFqZDAYVCpVoVBYvwse7e9nlsvl33///ZYtWzZs2ABSJBJJTk6Og7YZDIasrKygoKDXXnvNYrH8+OOPWVlZwAd4wPwCgQBBEJVKNfr71dVq9TPPPDPKQiCQ8YVCofj6+hKX7+I4rlKpFArFgwcPCgoKtNo+H58p9v4Hg2HUGbMyDioax2b9BtpUiKtw48YNg8FA+BpUVFRMnjwZWBGNRiMQCAjrqNfra2trHZfmjIiDGqOjo6urq61ndaWlpUwmMywszKaQ3t5e5PFz8UOGbTty5IhUKj18+DA48LNr164dO3acPHnSxrOXAHw7NDc3h4aGOi7ZMRqNpqurKy0tbTSFQCCuBolE4vP5fD4/LCwMOLpjGDaEY/DjrFmztjr3xmev/sNsMg+d2yEw5gPEVcAw7KOPPmpra5PJZAcOHGhsbCRCHEyfPr21tfXy5csajeb+/fvvvfee0Wh0XJozIg5qzMzMVKvVe/bsaWlpkUqlBw8evHnzZnp6uv3CqUgkYrPZZ86caWtrUyqVV65cOXfunIOGgVXf9PT0mTNngpS5c+e++OKLp0+fbmpqGlAkJCTE19d3ZKEQrQEz9fnz54+yHAik1I7xbtFjDMugIghOX06zAAACqElEQVTC9mIlronLN5xJf3fVKKuG81SIq7BixYqenp7169cjCEImk9evX79q1S+f7zVr1ty+fTs7Ozs7O5tMJqekpISHh3/zzTcOSnNGxEGN8+fP371796FDhzZu3IggCIqiGRkZf/jDH+wrotFo77//flZWFijH19f3gw8+ePPNNwdsFVj1DQwM3LRpk3X6tm3bQBSI48ePo6jtqCSRSKmpqZcvX96xY8fwTr4/TnFxcUREhGN/KAjEGRz7tLsjKJWCIEjmB6tX/3Vl9qv/qPn+1sjKIY02BBQEMhY899xzL7300uuvv97V1dXV1SUSiWxchBAEkclkCoUiICDA+W1FZ0Qc1GgymVpbW/v7+4ODg60v67DHYDC0t7dTKJSQkJDRmL3B6O7uzsjI2LNnj/W5nWGhVqtXr179zjvvJCUljW3bIBONhISE0d9L48r0qbRtP0n2bfi7rNXWez9Xe5rOdBRzG85TIa6Fn5+fn5/fgG9ZO/45iTMiDmpEUdTJWR2DwYiIiBhW24aFUCh8+eWXv/jii4SEhAHvsxySU6dOBQcHP+lQcxCIB8DxZs9YGHH09v8V/7siZ+vRYcnC/VQIxD3YsGHDrl277C+Jc5Lly5d/+umnI7PHEMhEg0QiMTmM5I1LfsDOrfxzsvOC0KZCXILNmzcvXLhwvFvh0tBotOnTpw/X+YIgNDR09EdxIJAJBZWOkinkTfsyT7Uejk4Y9AS5NXA/FQKBQCDDwOP3UwdEq9L+XCOOToh0vJ8K56kQCAQCgQwB25s9b1mMxWxxnA3OUyEQCAQCGRvgPBUCgUAgkLEB2lQIBAKBQMYGaFMhEAgEAhkboE2FQCAQCGRsgDYVAoFAIJCxAdpUCAQCgUDGBmhTIRAIBAIZG6BNhUAgEAhkbPh/19Bi3YAl1S4AAAAASUVORK5CYII=",
      "text/plain": [
       "<quantify_core.visualization.pyqt_plotmon.QtPlotObjForJupyter at 0x7d02d557dd00>"
      ]
     },
     "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 137451107041872>"
      ]
     },
     "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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       "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:  (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:                             20241106-153059-605-d8ef79\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-409d7471-6d80-43a9-b31e-40ca6a976d74' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-409d7471-6d80-43a9-b31e-40ca6a976d74' 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-e8921938-58a4-46a5-bbbd-47a03da8683d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e8921938-58a4-46a5-bbbd-47a03da8683d' 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-e243e422-6649-49ad-a113-7fe126405f90' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e243e422-6649-49ad-a113-7fe126405f90' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-955d90d8-bf08-473d-9f61-f3a179f80efb' class='xr-var-data-in' type='checkbox'><label for='data-955d90d8-bf08-473d-9f61-f3a179f80efb' 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-181388d2-2a55-4699-8d34-9987e6cc622e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-181388d2-2a55-4699-8d34-9987e6cc622e' 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-fd40e5ff-9f1d-4d8c-84fe-62565782357d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fd40e5ff-9f1d-4d8c-84fe-62565782357d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e638d45f-ce31-426b-bea9-3fd874235e14' class='xr-var-data-in' type='checkbox'><label for='data-e638d45f-ce31-426b-bea9-3fd874235e14' 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-932fe668-4d45-4e9d-96a3-4c2d07081a6f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-932fe668-4d45-4e9d-96a3-4c2d07081a6f' 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-76a33ce4-2f26-4e4b-8810-c85e3c512698' class='xr-section-summary-in' type='checkbox'  checked><label for='section-76a33ce4-2f26-4e4b-8810-c85e3c512698' 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>20241106-153059-605-d8ef79</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:                             20241106-153059-605-d8ef79\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 0x7d02d557dca0>"
      ]
     },
     "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",
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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
}