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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 137900779268032>"
      ]
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     "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 ... -0.2574 -0.2574 -0.2572\n",
       "    x1       (dim_0) float64 800B -50.0 -50.0 -52.5 ... -0.05883 -0.059 -0.05914\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 5e+03 5.256e+03 5.257e+03 ... 0.2635 0.1999\n",
       "Attributes:\n",
       "    tuid:                             20250320-201318-298-835670\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-3206a23d-e1ed-492b-b1ec-f98c70171095' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3206a23d-e1ed-492b-b1ec-f98c70171095' 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-e74240ef-e064-46aa-b2b8-6c135af2bcc7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e74240ef-e064-46aa-b2b8-6c135af2bcc7' 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 ... -0.2574 -0.2572</div><input id='attrs-6be1dba4-b778-4b7a-862b-d08fc4091384' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6be1dba4-b778-4b7a-862b-d08fc4091384' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6aa8f81-baee-4032-8d26-9c1830a183d8' class='xr-var-data-in' type='checkbox'><label for='data-b6aa8f81-baee-4032-8d26-9c1830a183d8' 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([-50.        , -52.5       , -50.        , -52.5       ,\n",
       "       -50.        , -48.75      , -46.25      , -43.125     ,\n",
       "       -41.875     , -37.8125    , -32.1875    , -23.90625   ,\n",
       "       -18.59375   ,  -6.328125  ,   7.578125  ,  25.15625   ,\n",
       "        11.25      ,  13.0859375 , -18.3984375 ,   1.015625  ,\n",
       "         4.6875    ,  36.171875  ,  -4.75585938, -13.15429688,\n",
       "        -3.7109375 ,  -4.49462891,  13.34716797,  -6.52893066,\n",
       "         2.65319824,  -2.70767212,   8.50875854,  -2.76950836,\n",
       "       -10.16468048,   0.97445488,   1.03629112,   2.93919086,\n",
       "         4.71841812,  -0.85114956,  -0.78931332,   0.53351283,\n",
       "        -1.35392785,   0.43873638,  -0.94592601,   0.16365312,\n",
       "         1.45353906,  -0.2749774 ,  -0.55006066,  -0.3028614 ,\n",
       "        -0.74149193,  -0.06263314,  -0.51520567,  -0.17577627,\n",
       "        -0.20366027,  -0.25714812,  -0.13006299,  -0.2596618 ,\n",
       "        -0.2164622 ,  -0.28000476,  -0.19360556,  -0.23429148,\n",
       "        -0.22091952,  -0.22983416,  -0.22314818,  -0.22537684,\n",
       "        -0.23903382,  -0.2708051 ,  -0.2889194 ,  -0.27526242,\n",
       "        -0.27191943,  -0.27303376,  -0.26397661,  -0.26620527,\n",
       "        -0.25031963,  -0.24126248,  -0.24749818,  -0.25373388,\n",
       "        -0.2616767 ,  -0.26509094,  -0.26225168,  -0.25941241,\n",
       "        -0.255441  ,  -0.25317671,  -0.25488383,  -0.25530171,\n",
       "        -0.25516242,  -0.25629456,  -0.25828027,  -0.25913383,\n",
       "        -0.25842401,  -0.25700438,  -0.2580691 ,  -0.25735928,\n",
       "        -0.25789165,  -0.25771419,  -0.25760861,  -0.25704254,\n",
       "        -0.25721045,  -0.25737837,  -0.25743116,  -0.25720091])</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 ... -0.059 -0.05914</div><input id='attrs-6f7ddbb0-fdf5-461c-8691-05cc70202d51' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f7ddbb0-fdf5-461c-8691-05cc70202d51' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d44ca57-9d56-4870-bdc3-a709aa7bf479' class='xr-var-data-in' type='checkbox'><label for='data-7d44ca57-9d56-4870-bdc3-a709aa7bf479' 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, -4.93750000e+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,  3.98923773e-01,  1.89604997e-01,\n",
       "       -2.29081106e-01,  8.49516771e-02, -1.24403512e-01,  3.26128799e-02,\n",
       "        4.51274708e-01, -5.89739466e-02, -2.15966063e-01,  8.82122317e-02,\n",
       "       -1.31805334e-02,  6.53155251e-02, -1.37470005e-01, -1.83263418e-01,\n",
       "       -5.57012546e-02, -1.40742697e-01, -7.69616152e-02, -9.82219758e-02,\n",
       "       -5.73376006e-02, -1.80895714e-02, -1.97259174e-02, -6.06102926e-02,\n",
       "       -2.87197517e-02, -3.93499320e-02, -3.85317590e-02, -5.97921196e-02,\n",
       "       -7.94161342e-02, -7.85979612e-02, -7.38965008e-02, -6.91950404e-02,\n",
       "       -5.93830331e-02, -4.91619393e-02, -5.41702146e-02, -5.91784898e-02,\n",
       "       -6.40844935e-02, -6.38799502e-02, -5.87694033e-02, -6.27557209e-02,\n",
       "       -6.14269484e-02, -6.15292200e-02, -5.90762182e-02, -5.65209448e-02,\n",
       "       -5.77730136e-02, -6.02771512e-02, -5.83990480e-02, -5.96511168e-02,\n",
       "       -5.87120652e-02, -5.90250824e-02, -5.86864973e-02, -5.86353615e-02,\n",
       "       -5.87327917e-02, -5.88302219e-02, -5.89995145e-02, -5.91432391e-02])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-06035063-bd9e-420c-b266-3b1978721d9e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06035063-bd9e-420c-b266-3b1978721d9e' 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 ... 0.2635 0.1999</div><input id='attrs-8b50a3e0-b962-4ab2-ae05-efa0fd7abafa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b50a3e0-b962-4ab2-ae05-efa0fd7abafa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d800672-57e0-40a6-ab10-8d24c7a6f64b' class='xr-var-data-in' type='checkbox'><label for='data-8d800672-57e0-40a6-ab10-8d24c7a6f64b' 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([5.00020071e+03, 5.25627474e+03, 5.25671347e+03, 5.01289081e+03,\n",
       "       4.75661683e+03, 4.51592465e+03, 4.51591050e+03, 4.29811188e+03,\n",
       "       3.83546163e+03, 3.31686039e+03, 3.20459006e+03, 2.75450219e+03,\n",
       "       2.00914672e+03, 1.37136125e+03, 1.63877796e+03, 1.50504004e+03,\n",
       "       8.15903868e+02, 5.51686729e+02, 1.03823459e+03, 9.04273743e+01,\n",
       "       3.86051227e+01, 1.43015270e+03, 3.14490038e+02, 2.15081530e+02,\n",
       "       7.76857051e+02, 5.55592449e+01, 2.47400829e+02, 5.07476168e+01,\n",
       "       1.69616825e+02, 9.14885946e+00, 7.26499419e+01, 1.21988064e+01,\n",
       "       1.13829937e+02, 6.28086174e+00, 2.54645678e+00, 1.59481417e+01,\n",
       "       2.84080196e+01, 1.17410702e+00, 1.41858462e+01, 1.25111932e+00,\n",
       "       4.50745716e+00, 8.51313797e-01, 3.68459401e+00, 4.96016414e-01,\n",
       "       2.34402362e+00, 2.11694390e-01, 7.28242491e-01, 1.92032093e-01,\n",
       "       7.02905575e-01, 3.69128921e-01, 7.48021219e-01, 1.29223064e-01,\n",
       "       4.43532589e-01, 1.23142751e-01, 3.57924682e-01, 2.18383752e-01,\n",
       "       4.46259511e-01, 5.58236208e-01, 2.20371104e-01, 5.36490732e-01,\n",
       "       2.31359440e-01, 2.64166522e-01, 2.37974648e-01, 4.06260878e-01,\n",
       "       3.61158234e-01, 3.39351215e-01, 2.27269030e-01, 4.64041825e-01,\n",
       "       4.76098556e-01, 2.82053087e-01, 3.19993949e-01, 2.74558194e-01,\n",
       "       2.20464202e-01, 2.58700165e-01, 2.79590262e-01, 4.62175252e-01,\n",
       "       2.26371928e-01, 2.86770668e-01, 3.97921577e-01, 2.53722762e-01,\n",
       "       1.98014136e-01, 1.69195398e-01, 3.49795257e-01, 4.23151975e-01,\n",
       "       4.76114020e-01, 4.65521212e-01, 1.44891452e-01, 3.80879426e-01,\n",
       "       3.57171411e-01, 3.69048061e-01, 3.49872326e-01, 5.23391829e-01,\n",
       "       5.38108491e-01, 2.57727244e-01, 2.11083614e-01, 2.39133843e-01,\n",
       "       4.84148025e-01, 4.98598723e-01, 2.63546857e-01, 1.99911113e-01])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-246856e4-6f83-4a10-af26-236016fd83b0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-246856e4-6f83-4a10-af26-236016fd83b0' 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-60c93e5e-acf8-4478-8fa6-89837e5dd65a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-60c93e5e-acf8-4478-8fa6-89837e5dd65a' 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>20250320-201318-298-835670</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 ... -0.2574 -0.2574 -0.2572\n",
       "    x1       (dim_0) float64 800B -50.0 -50.0 -52.5 ... -0.05883 -0.059 -0.05914\n",
       "Dimensions without coordinates: dim_0\n",
       "Data variables:\n",
       "    y0       (dim_0) float64 800B 5e+03 5.256e+03 5.257e+03 ... 0.2635 0.1999\n",
       "Attributes:\n",
       "    tuid:                             20250320-201318-298-835670\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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/xTWrhSSRgKHs7fCmVFRfT5yZ6OPjY+O2kZGRtbW1p0+fFolEHR0dfD4/IiLCYh2tVtvU1JSVlbV169a+vr5Dhw6Fh4fz+fy+vr4TJ06sWrVKKBSKxeJjx46tX7/efF/t7e1XrlxZs2aNj4/PpUuXBgYG8OWjbahQKBobG5cuXbp48WKrz5DwSObOnbt169aWlpbS0lKRSLR69WoKhXLw4MGbN2/OmDFDp9MdOnRo9uzZ+fn5CoWisLCQy+VGR0eTyeSsrKyAgAAMwy5cuHD69OnVq1cjhIqLi/38/FatWiWXy4uKiuh0+sj94i5fviwWi/G6eOrUqVOnTq1atQohJJVKJRLJ6tWruVxueXn5iRMn7r777iVLlnz55Zd33XUXnU6nUCg6nU4ikeCXrQqF4tatWytXrlyyZMnZs2ePHj0aGhq6adMmqVT6ww8/REVF8fl80zP1WbNm4ecWer3+xx9/xA8Sq+8lMzOztbU1IyMjPDwc/26VyWT4E77Ozs5z586tXr3a39+/qqrq8OHDmzdvptFoUqm0trZ22bJlXC731KlTFy5cWLJkyRiH2TSEn2jiPwsEgs7OTvznuro6kUhkuoU4ms7OTrlcfvv2bTKZbLrAxbf9aHNW1CuFVmdmZLPZSUlJJSUliYmJ+OZr1qyxWAfDMIlE0tzcfM899+j1+kOHDjU0NCQkJIx2/Js21Gg0RUVF8+fPj4mJaWtrKy4uxh8zjbYhnnTp6elbtmyxmpV4JK2trevXr1epVN9//71YLMZrW2lp6cWLF/GD6uTJkwwG47777iORSKdOnaqoqJg/fz5CKCYmZuHChVQqtampqbi4eMuWLTQaDf+62LRpE5lMPn78+NifsNVjW6FQNDQ0rFixYsWKFQ0NDUVFRffff/8YOWLLd4tWq5XJZAghoVB499134wGUl5erVCoymWw1KyMiIvAvH9OsR6bU1mg0hw8fnjdv3owZM7q6uo4ePerl5YXf7b9169by5csXL15cW1t78uTJBx54YOzDzEW4XBsl/KzN9LNer0cIkcnkhx9+2JbzlK6uLq28j44NM1lsfIkt21IolNDQ0M7OzoaGBrFYLBKJzG9TmLDZ7LS0NCqVGhQU5O/v39fXhxCqq6tLSEgIDAw0Go1BQUEikai1tdV8q5s3byYkJPj7+1MolKysLNPp8BgbhoWFRUREUKlU80/DIpKUlBQqlRobG2s0GhMSErhcLovFioiIwKNqbm7mcDgJCQkIIS6XO2vWrFu3buE/45F3dnZ6e3uLxWKEkFQq7evrmzdvHpVK9fHxGftJSUNDw+zZszkcDp1Oz87Obm1tNd1EmjVrFj6dX3Z2dnd3t1wux98s/kZGfqQREREikYhCocTHx8vl8rlz59JoNH9/fz8/v/7+fot/EIPBoNPpZWVlvr6++Dm71fdCoVBIJBKFQqHRaBZPnurr6+Pj4wMDA/HbDBQKxdRKIjk52dvbm0ajJSQk9Pb2jvH2pyfz45BOp+NZiRBavXp1enr6uJv39/d3dnaKxWI+n286DPBtSSSUGeFzsUVidUOhUKhUKhsaGm7duhUQEGC65LUwZ84c/CI4Kipq7OPfpLm52dvbOy4ujkwmR0ZGmu4tjbEhg8HIyMig0+mm04uRsrKyGAyGt7d3UFBQUFBQYGAglUqNj4/Hj+ehoaG2tracnBwqlUqhUGbPnm168cjISLlc3tHRgR+0EokEIdTQ0JCRkcFisRgMRmZm5hif8BjHdmhoKF47ExISeDxeS0vLGDmCbPhuMSGTyQwGg8FgXL9+va+vb8WKFWiUrCT/D41GM30Bmj5wHo+XmJhIJpNDQ0Ojo6NNd6QiIiJCQ0MpFMqsWbMUCsXI9muuyeWuU80bDWq1Wjb7p9I4WjpZwDuk7/1PuaC6OjhIGBoaasu2165du3Xr1saNG6lUqk6n27t3L5fLHXnT1XyuZhqNht+Jksvl7e3t5nUUv3dtolAoTBWdTCab7iuOseHYl+MWkVCpVNOvNBoNPwGUy+VSqXTPnj2m1fB7QQMDA0VFRb6+vl5eXhiG6fV6nU6nUCiYTKbpexO/22YV3tzatAKPxyOTyUNDQ/gnbJodgcFgMJlMhUKB3yoY913QaDQajWa6ODZ9thbOnj2rVqtNz36svpfRzkIQQgqFwnx6QT6fr1Ao8J9Nh9lou57mLLLS9CGPcT/DHD5/HIZhBw4cuHLlCv5M1LTt3Cjf880DWZGWh4pEIjl58uTGjRvx2xLFxcVnz54dedMV3Xkg4f/T0Y5/E4VCYT6Zh+nnMTb08vIat92iKRIqlWo6qPBvFfzFSSTS/v37TeuzWCyDwYBh2KFDh0gkkq+vL5VKxTBMo9FgGKZSqUyBjZGVaMxj2/xtmi8f9y2gUb5bLDQ1NVVXVxcUFOCnGhPISvO3xufzTSe15h8miUTSarWTbKHmHC5XU/ETNNPPI59N2mJmeIC+s00mk+E1dVz4gzT8BAq/VDLdoR0Xi8UKCgoa45E73u7J9KvpbGuMDSc/Qwibzfb19TXdmTGpqqqKj4/HdzowMHD9+nU8EjyH8WuIMXoxkclkJpOpUqnwYqlWqzEMM313mN6awWAYHh42LXeImpqatra2goIC05m11fcyBot/hFKpdGyEHkytVqvVavwbTSKReHt7T+BFyGSyUCgc2aNmTqTPx6VNI9cfGBgwbzkfHBw87r/YZLTj34TFYuFNT3EqlQo/2R1jQ4dkJUJo/fr1FtdqN2/epFAopp02NDSg/10FqlQq/BMYu2/hGMe2+eWdUqnEGxY4yu3bt0+fPp2fn2+q3PZmJZvNxq9lcSqVyt2z0uXu/UqlUvyuRVtb29DQUGRkJELIaDSeO3cOv4mPENLpdPh5H34ShD/eMG/JFs8ZRsNK/MTNYluDwYBvgmGYTqfDn+35+vqKxWL84FMoFGKx2OKsdgyxsbHmXU4VCoVSqTRfITIysqGhYXh4GCFUX19vOsTH3XAywsPDBwYGmpub8V91Ot3g4CBCyGg04tccRqMRbyaAEPLx8fHy8sJbiOh0urHTIDIysrq6Gv/cKisrAwICTKeT169fx/8vNTU1AoGAz+czGAwymTz5Lr+tra2XL1/Oz883P1G1+l4QQiwWy+oe8X8E/tXT0tKiUCgmdsY2DQkEgurqaoSQQqEwNVBCCNXV1ZnuMVrNLIVCYTrCpVJpU1OT6eGrads5Ub6XWvp1Op3BYDAajTqdDr+37Ovrq1Qqu7u78Rdvbm7287N18MLRjn/zFXp6evCbmYODg6Z3Me6GkyEQCHx9fS9evIh/ZRmNRjwA/F3jC+vq6vDvCvS/dh74cvzzH80Yx3Zrayv+7Xf79u2+vj68ye5oOWIXuVx+5MiRvLw880vk0bKSzWZb3WNYWFhvby/+X5bL5Y2Njfh3vvtyuetULpf773//m06n63S6Bx98ED9nMRqN1dXVYWFh+F2CXbt24f+24uJihNDKlSsjIyN7enoqKipoNBqGYSQSuVTu+4Sf38htjx8/3tLSgu+rtrY2OTk5JycnMTGxt7f366+/5nK5CoUiJiYmPj7exoAjIyOHhoZ++OEH022clStXmt8/iY2NFYvFX3/9NYfD4fP5pmo97oaT/BhXrFhx+vTpiooKCoWi0WjmzJnj7e2dmppaWFjY2dlpMBji4uLwlUkk0pIlS44dO3b9+nWDwRAeHm5+5mhh7ty5J06c2LVrF5VKpdPpy5cvN/1JKBTu3buXTCbr9fqVK1fi5/VZWVmFhYUYhuXl5U24exIe2I8//oj/6u/vv2rVKqvvBSGUlpZWVlZ25cqVmJgYvAEILi4urr+/f/fu3RwOR6PRLF261C1uJbkCNptdXFx87NgxnU6Xn59v+tZrbGwUiUT4v9VqZqlUqsLCQqPRSKFQtFptYmKiqce5aVsqmbQ6RL9z5058+c6dO319fTds2ODj45OdnV1UVMRms9VqtY+Pj+0daUY7/k0r8Hi83NzcQ4cO4c9Z8G7utmw4GSQSafny5SUlJV988QWbzVYqlZGRkQsXLoyNjb1x48ZXX31FpVIDAgJMu5s7d+6RI0e++uorCoUydmv8MY7tsLAwvPn90NDQ/Pnz8fc7Wo7Ypbm5WaPRVFRUVFRU4Eu2bNkyWlbGxcW1trZ++umnXC53w4YNpuU8Hm/RokVHjx5lsVhKpTIlJcXdOzG64ni/er1eqVRyOByLOyTjMhgMSqWSQqFwOJxF75V++lBmpJ8dJUqn06nVajabbe9+EUJGo1GhUFAolNFuXAwPD+v1+pElc9wNJ0mlUhkMBg6HY2obgmGYQqFgsVgWDzmMRuPQ0JCNb394eNhgMJjHvHv37pycnODgYPOHQFNttPcyBoPBoFKpxn1iDUzwrMQPD7xNil2bG41GpVJpNBrND0ILfznWwKVTnlgUM/JP+L+YTqfb2KLCwsjj3xz+jWH1QenYG06SVqtVq9UWX3H498DI8zylUkmlUm352Ece26dPn2YwGHPmzBkaGuJwOA4ZL2JcE8hK/Gtwij5tJ3O561SEEJVKHfuB/GgoFIrp2zzSl/v7g9diArgF6aIkER8hVN0hO1DVhRAyLbGAt5SZWMwkEmnsr+nRvozG3XCSRpZqMplsteaRSCTba+FoGU6lUp1WUNHo72UMFAoFCuoE2HV4WGxo3t/XahoGcBn/Lm/uU2hH5uYE/sXmxj5VNf/GsGvDSaLT6SObd43WK9r2e1ejHdsT/t9NzAT+ZVP9NehMrlhTJ6/s5u0Lrf3KYUN5Yx8+jRSGGZ7bWyNRaJFbzQR38ODBoaEh8yWRkZE5OTlO2LVKpTJvoIibO3duTIyViwmEUHR0NAyVAMaGz+9mkYZlN2//v5JGiULrLpO+nT9/3qJnDpvNLigocM7e7fpOCAoKmsBdNzAZrnjvd5IvMnIaKR6TjkhGufrnPhIwsRQANnLUXG9W53d7dU3CHwtvwKRvwGO4/c3rkUZOIyXTaM0LKoKJpQBwOqvzu71dVA+TvgFP4oE1FQDgLiiT7vQJgEvxwJpakC4SsO94/s9j0ryYdzQ+4rPoVmeCAwBMkZGJyWfRX8mfMXIh5CZwXx5YU/FppLw5PyUqn0X71wPpn9yfblpCJpFeXTPD6rDdAIApMjIxP7k/bW2aaORCyE3gvjywjRKutkuKP5VZlybCU9S0JDGYt6ui7cCTzmg9C4C7c2BWIoQutAzc/58LD2ZHmBITWctWANyUxzazThIJLJoOmi+51Dq4+2L7piz3HrADALfDZdDihF6vrrljIuGR2QqAm/LAe7+2eLsg6dUDdQbMha7RAZgO2gaU4b6OGYATABfkctepJSUlpp/xidumyF/uTX5xX837G1KmbhcAeAYHZmW7RBXm494TjwAwBperqVNaR83dkx6y51LHxRbJyIkbAQDmHJiV7QOqWSHwxBR4rGl67xf37r0pv9k31gxKAADHapOowuE6FXgul7tOdaZwX/bq5ODXDlyjUkho9LH1AQCTh4+eX90h1egwomMBYKpM65qKEJobKXjw88tGDCG3GlsfAPdiPnr+r/fVQKIBTzWt7/1Wd8ie21Nj/N9J86By+OlvKmu7pIQGBYCnwRMNL6gIEg14tGldU60O6g3jdwPgWJBoYPqY1jUVAAAAcKBpXVOtDuoN43cD4FiQaGD6mNY11eqg3jDcKACOZZFodCoZEg14qmldUxFCuTF+u7Zlbs+NZFLJn2xJz46GtogAOJ4p0R6cF05BJEg04Kmme18a9L/xu8+3SHgs2vhrAwAmxDRQfr9CW1jbvTopiOiIAHC86X6dahLEZ3bLNERHAYDn25gZuudSB9FRADAlXO461Wlj6FsQCVhdUrXTdgeAG3FsVs6P8//Nvprbck0gjznJlwLA1bhcTXVmHTUXLGCJoaYCYI3DsxK/VH1mSaxjXxYAwsG9358EC5hiKdz7BcAZNmSE7r0Mt3+BB4Ka+hO4TgXAaUK8WWE+7HNNA0QHAoCDQU39SRCf1QAYSeMAACAASURBVC2DmgqAk8ClKvBIBNTU4eFhqVSqUCicv+sxBPGZPXKN0Uh0HAAQAcMwqVQqlTpvXPu700RFtd1aPcz7BjyKs2uq0WgsLCzcvXt3WVmZk3c9LrhUBdPWhQsXdu/evW/fPmfuFC5Vgedxdk2tqalRqVRUqsu1N0bQnQZMV729vbW1tXy+swcLhI6qwPM4tabKZLKLFy/Onz+fTHbF57jQ9BdMQxiGlZSUJCcn+/j4OHnXSSK+DjPWd8udvF8Apo5Ta1tpaWlUVFRYWJgzd2q7YD5LDPd+wTRz+fJlg8GQmZlJyN43ZoTugdu/wIM4r6bW1dVJJJKcnByn7dFe0J0GTDf9/f2VlZULFy6kUCiEBLAhM2TvpU5Cdg3AVHBSTR0aGjp//nxubi6T6bqjkQUJmN1w7xdMG/hd3/j4+ODgYKJi4NCpi2b4H67pJioAABzLSW2FSktLg4KCYmPHH4osLy/PYkl5efnUBGUJ2iiBaaWyslKlUs2bN2/cNUdmJXJcYm7ICN15pmVNMkxTAzyBM2pqc3NzZ2fn0qVLu7t/Ohs1Go3Dw8Pd3d08Ho/D4Ziv7LQKOhL0pQHTh0qlunz5cnJyskQiwZdoNBqj0djd3c1kMr29vc1XntKsnB/n/+K+mh65RghD6gP354yaqlKpEEInTpwwX9jT03PgwIGcnJzk5GQnxGALAZum1WMqrYFNJ+bZEgBOo9FoMAyrqqqqqqoyX37gwIHIyMiVK1c6M5gNmaF7YUh94BGcUVPj4uJCQ0PNl3z33XcBAQELFixgsVhOCMB2eDOlmAAu0YEAMLUEAsHmzZvNl5SVlfX09GzYsIFGozk5mI0ZoRv+XQE1FXgAZ9RUOp1Op9PNl5BIJCqV6vw+5uPCb/9CTQUej0wmWyQgjUYjkUiEZKXImxXuwz7XNJAd7ev8vQPgQK449gKBRAJmFzT9BcDpNmaG7bnUTnQUAEwWMWMEPvLII4Tsd2zVHbKG24r6nqGZwbwkkctdQwMwpZz8DNXC2tTgX39XzWddo5BJBekiSEDgpuA69SdlN28//MXFyvbBqg7p1k8vnbnVT3REAEwjZTdvk8loV0XrZ2dbIAGB+4KaihBC1R2y5/bUSBRa/NdB5fDT31TWdjlv3isApjM8AYd1P837BgkI3BfUVIQQOlDVJVFqzZcMqrQHK8VExQPAtAIJCDwG1FQAAADAMaCmIoRQQbpIwL6jtw+fRV+XJiIqHgCmFUhA4DFcbm7wkpIS08+LFi1yzk6TRPyPNqc9vbtyUKlFCFHIpE/uT5sJLQ8BQAhNfVZaJCCfRYMEBG7K5Wqq0+qohdwYv13bMvFHOPuvdsYEeBESBgAuyAlZaUrAL8+3/ev+2XNh8AfgnlyuphIoSSRIEgkQQpgRHa4Rb8uJJDoiAKYRPAEbbg/pMCPRsQAwQfA81YrVyUGFMKEjAESYJeLXdcmIjgKACYKaasXscO+uQXWPHAYpBMDZkkMENZ3QMxW4K6ip1sGlKgCESBLxa+E6FbgtqKnWrUkOPlwDXc4BcLYQb5ZiWC9V6YgOBICJgJpqXVqYoEc23C1TEx0IANNOkkgAAxMCNwU1dVRrkoMOw+1fAJwuKYRf2wm3f4FbmmBNNRqNSqUSwzDHRuNSoKYCt6NWq/V6PdFRTBY8UgXuy47+qRiGnTt3rqysrLq6uqenB8MwMpns7++fkpKSnZ09f/58Go02dYE6X0qooF8x3DWoFnmziI4FgFHduHHjxIkTlZWVbW1tWq0WIcTn8xMTE7OyspYvX87j8YgO0G7JIv4fCq8THQUAE2FTTcUw7NChQ7t27err6/P19U1ISMjKyuJwOEqlUiKRVFZWFhcXe3t7b9y4ccOGDZ5UWdckBR2u7X50fhTRgQBgxaVLl/7973/X19dzOJz4+Pjly5d7eXnpdDqZTNbY2Pj3v//9k08+Wbly5SOPPOLj40N0sHYQebNUw4ZBldb7zkGAAXB9NtXUZ555pq2tbc2aNStWrIiIiBi5QmdnZ3Fx8ffff3/48OHdu3dPJiBCxvsdzerk4FcP1EJNBS7ov//979dff7106dLHH388NTWVTLZ8jiOTyUpKSg4fPnzfffft3LkzLCxswvtyflbij1Tnx/k7YV8AOBDJaBx/GLDDhw8vWbKExRrnFqhOpyssLLz77rsnHE1eXl55efmEN58KeX8p+Wb7nFAfNtGBAHCHsrKy+Pj4wMDAcdc8c+ZMVFRUcHDwxHZESFa+e6yBTac8uSjGyfsFYJJsaqM0f/58On38mzA0Gm0yBdU1QUsl4Jrmzp3L5XJtWTM3N3fCBZUo0EwJuCmbampZWVlBQcHHH3/c2to6xfG4HBj8Abim3t7etWvXvvXWW1evXrXlbpN7SQ7h10B3GuCGbHqeGhMTExgYuHv37t27dycmJubn5y9dupTD4Ux1cK5gZjBPOWxoHVBG+E6L9wvcBZ/Pz8jIOHnyZHFxsVAozM/PX7VqlVAoJDouxwgWsDQ6g0Sp9eFAMyXgTmx6noprbW0tKioqLi4eGBhgMBgLFizIz89PT08nkUiOisYFn6cieLQDXNjg4GBxcXFRUVFzczOJREpPT8/Pz1+wYAGDwXDULojKyq2fXtyeGwnNlIB7saOm4jAMu3DhQlFR0dmzZ3U6nVAoXLVqVX5+vkNOkF2zpt7olr+wt/rIs3lEBwLAqBoaGo4cOXLixAmZTMbhcJYuXZqfn5+YmDj5VyYqK98rbmBSKU8thnNZ4E7srqkmQ0NDx48fP3LkSH19PYlEuuuuu37zm99MMhrXrKkIoUXvlX76UGakH9z+BS5Np9OdO3euqKjowoULBoMhIiLiiy++GNnNxi5EZeWxaz37r3b964HZzt81ABM28WTz8vIqKCj4zW9+k5GRYTQaW1paHBiWq4HWv8At0Gi0BQsW/PrXv163bh1CqLW11X2bL0HTX+CO7Bib0Jz5UxwymZyVlXXvvfc6NjKXsjo5+LlvK5+G21DAhQ0PD5eVlR05cuTKlSsYhsXExOTn51MoFKLjmiBopgTckX01Va/X43eWzp8/bzAYRCLR9u3b8/Pz/f09vB3BDKGXzmBs6lNE+9vUIxAAZ6qrqysqKjp16pRSqeTxeHfffffq1avj4uKIjmuy8EvVBdBMCbgPW2tqY2NjUVHR8ePHZTIZk8lctmzZ6tWrU1NTpzQ4l4Lf/n12SSzRgQDwk76+vqNHjx45cqSjo4NMJmdkZOTn53vSbBb4CIVQU4EbsammHjt27A9/+ANCaNasWY899tjixYvZ7Kkaq8+lxvs1tzo56KlvKqGmAhfR09OzceNGDMOCg4MfeeSR/Pz8gICAKdoXUVmZLOLvu9rltN0BMHk21VQ2m7158+bVq1dPZhhuG7lUHTUXF+il0Rqe31MtYNMK0kVJIj7REYFpjUQimW4XObCPuFVEZSWFTD7T2P/Gj9ch44C7sK8vjVwuH206xqampujo6ElG47J9aRBCZTdvP/pVpVprQAh5cxh/35SaG+NHdFAAIK1WazQarQ7y0NLSEh4e7qZ9acpu3n5ub41EoUWQccB92Jdsly5dsjqVW1lZ2YcffuigkFxRdYfsuT01eEFFCA0qh5/+prK2S0psVAAghBQKxeuvv45hmMXyzs7O5557zk370uAZhxdUBBkH3Id9NdXPz++f//znyZMnzRdWVFS8/vrrsbGe/KDxQFWXRKk1XzKo0h6shLH1AfGYTGZlZeUHH3xgvrC7u/uZZ57x8/Ob5EUqUSDjgJuyL99SUlK2b9/+xz/+saqqCl9y9erVV199ddGiRU8++eQUhAcAGAebzX777bcLCwu//PJLfElfX9+zzz7r5eX117/+daoftQIAzNl9DvvAAw/k5+e//PLLLS0tNTU1L7300rx58373u9+56emwjQrSRQL2HR3PSYjU1KdouD1EVEgAmKSlpb388ss7d+4sLi6WSCTPPvssjUb74IMP+Hx3bddTkC7iMO5oQcln0deliYiKBwAbTWQcpRdeeKG3t/dXv/qVSqVKS0t7/fXXPbugIoSSRPyPNqc9vbtyUKlFCPFZtE/uT78tH37mm8pgAevxhdFZkT5ExwimtWXLlvX29r799ttCoRDDsI8++sjHx42Pyf1XOxODebd6FWYZlzYTmv4Cl2dTu1+dTmexmlqtfv7559ls9jvvvIN3MCeRSJPvae7K7X4RQrVdUvyJzro0kSm9Sxp6Pylt0huMjy+MXpYYiC+s7pAdqOpCCEEfADBF9Hr9yHZJH3zwQUVFxYcffhgUFIQvodMnO7DfVGelRbIoh/Xr/1WxfnbowzkRVjMOAFdmU00tKCjo6+sbe52kpKSPP/54ktG4eE0dw9X2wU9Km5r6FI8viA7k0aEPAJhqb731VnFx8birlZaWTnLI3ynNSosOM9tyIv55uum7R+clBlvvsweAi7Pp3u/mzZuVSuXY6wQGBjoiHneVHub9n60ZzX3KPxbVn6rvMZ2o4H0Adj2SmSQSEBog8DSLFi2yZQwWV34u81OHGeXPHWb+38nG/U9AQQVuzKaa6tlzzjhQlD8nzIdlceWP9wGAmgocKzc3Nzc3l+goJmVkhxmdAYNkAW7Nppqq0+lsfFZq+5qjcdnxfgFwKXbl2iQTE7ISABvZVFMff/zxxYsXr127lsPhjLaORqMpKiras2fPnj17JhOQu2dsQbroh8ouqerns28vJg36AACH++CDDygUypYtW4RC4WjrYBh2/vz5Tz/99Pnnn585c+aE9zVFWTkyWaDDDHB3NtXU+++//x//+Md///vf3Nzc2bNnx8fH+/r6cjgctVo9MDDQ0NBQWVlZVlbGZrN/+ctfTnXELs6i1w2PRdPqDdBkETjcunXr/va3v23YsCElJSU7OzsxMVEoFHp5eel0OqlU2tTUVFdXV1JSIpfL169fP/mxuKeCtS5q0GEGuDdbx9DXarVHjx794Ycfbt26NfKvkZGRa9euzc/PZ7FYk4nGfdv9WjDvAyBV6z4ubfp6+xyigwIeqKKiYv/+/RcvXhzZr8bHxyc/P3/dunWTnANuqrOytkv63tEGsUzzt42pUFCBu7NvXhqEUE9PT01NTU9Pj0Kh4HK5gYGBycnJps5wk+QxNdXCJ6VNco3upZUziA4EeKahoaGampr29napVEqn0319fWfOnBkdHe2QRr9OyMo9lzqutg++c0/ylO4FACewexwloVA4xvObMeA3ijUaDZPJ9PX1neQVrXt5fGH0o19eOXatZ8XMiXx0AIzNy8srJycnJyfH3g11Ot3AwIBSqaRQKAKBQCAgpsGtATNSyDAuMfAEExmbcAIqKipMw+4jhMhk8qxZs+bNm+fKnecc618PzJ77p5MpoQIhj0l0LAAghFBra+vRo0fN71SFhYUtXrzY+ee7esxIhZoKPIKTaqpQKFy+fLm/vz+LxVKpVJcvX66pqeFyuSkpKc4JwBUcfCrnFx+dvfDKEqIDAQAhhLhc7vz584OCgrhcrk6nu3nzZkVFRWlp6apVq5wcid6AUSnT5fQaeDYnHceRkZHR0dE8Ho9Go/H5/MWLF9NotM7OTufs3UUE8phvrZ35yy+vEB0IAAgh5Ofnl5iY6O3tTaPR2Gx2ampqaGgoIVkJ16nAYxBzbmgwGDAMY7PZhOydQMtnCmMCuB+XWGk7DQDhDAYDIVkJz1OBx3DSvV+cTCbT6/VKpbK6uppGo6Wmpjpz7y7ixRXxW3ZeSAkV5MDA+sAFKJXK4eFhjUbT1NTU3d29dOlS58egM2A0uPcLPIJTa+rhw4flcjlCiMViLV++3Nvb25l7dx1fb58z6/+OnX9lCZfh1M8fgJEuXbp048YNhBCZTM7Ozo6JiXF+DHCdCjzGRL7TMQyrr68Xi8UikSghIQEhZDAYyGQyiTROVqxZs0av1w8NDdXW1h4+fHj58uWRkZEW63z22Wfmvz788MMTiND1HXoq9xcfnTn1q4VEBwI8R3t7e3NzM41GwzvV4KNAjNu0PjMzMzk5WaVStbS0nD17VqlUzps3z2Kdqc5KPWZkU+E6FXgCu2vqjRs33nzzTbwhw/r16xMSEgwGQ0FBwcaNGzdv3jz2tnw+HyHk6+sbFha2d+/ec+fOjaypnlpELUT5c55aFPvC3qq/bpiON8CBYw0ODr711luXLl1CCMXExOA19fe///3w8PC777479rYcDofD4fj4+ISEhBgMhqqqqlmzZnl5eZmvM9VZCdepwGPYd24ok8l+9atf8fn8d999d+HChfhCCoWydOlSu0ZaIZPJfn5+crl85IBq00dBusiLSfviXCvRgQC399prr7W0tLzyyivmA26vXLnyypUrGo3G9tfBRzGUyWSOD3FM8DwVeAz7juMTJ06QyeT3339/7ty5XC7XtDwqKqqjo8P21zEYDL29vWw2e/qM+WDVG7+Yub+yq7pDSnQgwI01NzdXV1e/9dZbq1atCgwMNC2PiorS6XRisdj2l+rp6UEImae2c8B1KvAY9t37FYvFsbGxI2d843A4Q0NDY2z4448/RkdHCwQCOp0ul8tra2tlMtnIxzbT0MEncyJ+W9j659VEBwLclVgsplKpI6dyw/N0jMQsLy/ncDgBAQEsFkutVjc2NjY0NISFhTl/hELonwo8hn01lcfj9fb2jlx+69YtX1/fsbctLy833ellsVjZ2dnTahClMRx8KmftR2cPPmX3YK0AIIR4PJ5erx8cHPTx8TFfjk8h5ec3apctOp1+9epVnU6H/0qhUBITE7Ozs6c0WqtgHCXgMeyrqXPnzt25c+fBgwfXrl1rWtjU1LRv375ly5aNseFdd92l0+mGhoa0Wi2TyeTz+eM2Ep4+UkIE984Oee1g3VtrZxEdC3A/CQkJfD7/448/fvnll00LZTLZJ598Eh4eLhKNOsX3nDlzMjMz5XK5RqOhUqne3t4UCsUpIVuC61TgMeyrqfHx8QUFBe+9915xcbFcLmcyma+88kpFRYWPj8+4LQNpNJrFeTQweWBe+K++q/7+Suc9s0OIjgW4GRqN9sILL7zxxhvXr1/38/OTSCR//OMfKyoqVCrV+++/P/a2ZDKZqLlozMHzVOAx7O5L8/zzz8fGxu7bt6+trc1oNHZ0dCxbtuzRRx+FejlJ769PWfrX0ymhgpgAZ7cQAe5u8eLF3t7en3/+eW1trU6nO3nyZGpq6o4dO/Du464PrlOBx5jImA9r1qxZs2aNTqfTarVsNhvu4jrKwadysv5w8tqbK4gOBLiftLS0tLQ0DMPUajWLxXKvFvXwPBV4DJtqqlKpNJ9k0eJP+A8UCmVaTTM+FTh06n8ezNj8n/Pf7JhLdCzA1Wk0Gr1eb/VPKpXK9LPzO8ZMAFynAo9hU0194IEH+vr6xl4nKSnp448/dkRI01p2tG91h/Sdo/UrZwYdqOpCCBWki5JEfKLjAi7n3XffLS4uHne10tJSoloe2ai6Q3aje2jP5Q4hnwmHOnB3NtXUbdu2mc58Gxsbjx49mpGRkZCQwGKxxGJxaWkpj8e75557HBJQSUmJ6edFixY55DXdy+MLo+/95MyX59sUGj1C6ECV+O+bUnNhEhtwpxUrVsTHx+M/S6XSb7/9NjQ0NDMz09vbWyKRnD17dmBgYPPmzQ65CTx1WVl28/Zze2skCm3noOpKmxQOdeDuSKPd1LXq9u3bDz/88CuvvJKbm2taqFAonnzyyUWLFj300EOTjCYvL8+uMQ49UnWH7OHPL0qUWtMSbzZ91yOZSSLi22cCF4Rh2Pbt2zMzMx977DFT4wYMw/785z/fvn37ww8/nOTrT11WwqEOPI/dYxOGhYWZF1SEEJfLve+++w4cOODQwKavA1Vd5t8yCKFBlfZgpR0jzIFppb6+vqmp6eGHHzZvLUgmk7dt23b16lW7Bg11MjjUgeexr6ZKpVKr17VGo1EqhUFrASAAnnojExNfMjg4SEBMAExX9tXUmJiY+vr606dPmy+UyWTffvstIVMZe6SCdJGATTdfwmfR16WNOhoOmOaioqKMRuPOnTvNyyqGYTt37qTRaBEREcSFNg441IHnsa9/6tKlSw8dOvTqq6+mpqbOmDGDyWT29PSUlZXp9fq//vWvUxTidJMk4n+0Oe3p3ZWDSi1CiMekfXJ/2kxoDwlGIRQKN2/e/PXXX58/fz4zM5PP50skkvPnz/f09DzxxBM8Ho/oAEdlcah7MalwqAN3Z18bJYTQ8PDwN998c/ToUXwOKTabnZGRsW3btujo6MlHA22UTGq7pAcrxeWNfStmBr2wPI7ocICrO3bs2L59+27evIlhGJVKTUhIuO++++bPnz/5V57qrMQP9epOaYQP590NMK8GcG9211QTrVar0+kcO44S1FQLJ2/0fnOx7b8PZhIdCHAPBoNBrVY7dmZi52TlgEK7/G+nr7w61lQcALi+iScenU7ncDgwMOGUWpIQcKq+d6KnPWDaoVAoXC7XvQYmxPly6ckiQUmDlakkAXAj9j1PNRgMWq3W6p/IZDKDwXBESOAOSxMCT9y4vSwxkOhAgIsyGo0ajWa0v7rRiKHrM0K+u9y5KD6A6EAAmDj7amppaenrr79u9U8wNuEUWZYYePw61FQwqsHBQfP5jC24/tiEJvlJQb/5rkap1XPoE5nbAwBXYN+xGxsb+8QTT5gv6e/vP336NJPJLCgocGhg4CfLEgPfLqonOgrguthstkVWKhSKy5cvt7W1bdq0yb3uA+OXqg9lRxAdCAATZF9NDQsLCwsLs1i4Y8eOxx57TCaTOSQgGO/XgjebHuXPudI2ODvcm+hYgCtiMpmbNm2yWLhjx4533nmnsbHRIS0enJaV6zNCX9xXDTUVuC8H3GNhMplr1679+uuvHTKMPtTRkZYmBp64fhtqKrDLxo0bH3jgge7u7qCgoEm+lNOycmYwz2BE9d3yGUGu260WgDE45r4QjUaTSCQOeSkw0rKEwOM3bhMdBXAzVCoVIeR2iblhdsjeK51ERwHABDmgpra1tX377bdRUVGTfylgVUwA14AZW/qVRAcC3IZMJvvXv/5FoVDCw8OJjsU+6zNCv7vsuuP+AzA2++79njlz5t133zVfolar1Wo1k8l87733HBoYuAPeo2ZHHpy4AEtSqfTBBx80X6LX6+VyOZlMfvzxx7lcLlGBTYwXk5od7XfsWs+KmUKiYwHAbvbV1ICAgIULF5ovYTKZQUFBixYt4vNhlM4ptCwx8L3iBqipYCQ6nW6RlVQqNSAgYM6cOa48gP4Y1meEfHuxA2oqcEf21dS4uLi4OBh7lgBZkT43uuVDGr0XE7rugTuw2eznn3+e6CgcaWlC4G++qxlUab3vnLUGANdn3/NUtVrd22tl8LChoaG+vj4HhQSswwd/IDoK4HIwDOvs7MQwzGK5Vqvt7HTXxj54R1WiowDAbvbV1HPnzr300ksjl+/fv////u//HBQSsG5ZovD49R6iowAuRyqVbtq0SaVSWSyvr6/ftGmTwWAgJKpJund2yD5o/QvckGP60uj1evcarsUdQY8aYBe9Xo8QctNZLuICvVg0SnWnlOhAALCPrQ/nlEolPlQ3hmEKhcL8T1Kp9PLlywEBMPL11KJSSDnRfqdv9i2I8yc6FuASNBqNXq9XKpUIIYus1Gg0ZWVl3t7e7nuyi9/+TQkREB0IAHawtabec889eOoihFatWmXxVzKZvHXrVkfGBazBH6lCTQW4N95448yZM/jP69evH7nCli1bnBuRI63PCE1+/dgf7p5FdCAA2MHWmrpjxw6tVnvr1q2rV69u2LDBtJxEIrHZ7JSUFEd1LYfxfsewLDHw76duwbcMwK1evTo5OVmlUn3++efbt2+n039uJUun06Ojo1NTUx2yI0KykkElL58p/LFafFdKsHP2CMDk2XGdihBqbGyMj483r6kOB3V0DIE8ZoAXo7ZLliSC3sAA5ebmIoRUKpVGo9m0aZN5TXUsorJyQ0bIv8taoKYCN2JTTR0aGsIwjM/nR0REBAQEWJ2ChkqlcjgcR4cHLOHj6UNNBWq1WqvVcrlcFot1//334yOajVzNrQdjyYv1//V3NbflmkAek+hYALCJTTX1wQcfHBgYOH36dFlZGcxJTqxlCYG/3lf9/DIYeWO6e++994qLi//xj3+EhIR4xpzkVuGdap5cFEN0IADYxKaaumPHDo1GgxCKj49/7rnnrK7j5+fnyLjAKBKDeVKVTixVBwtYRMcCiLRy5crExESRSMRms0fLSoSQ+7b7xa3PCHno00tQU4G7sKmmmhr6hoSEhISETGU8YHx4698HYd7m6S0zMzMzMxP/2SFTF7umCF+OvxfjUqskM8KH6FgAGJ97n8NOT/gcNURHAYCTwDiFwI3Y0UZpnBeCNkrOkhfrt/2LS8N6jEGFU6LpC2+jNO5qbt1GCbd+duhL39f85d5kogMBYHy2tlEad4h8aKPkTPjYv2uSoY/B9IW3URp3NXdvo4QQIpFQQXrI91c675kND56Aq7O1jdLIEbotQBslZ8IfqUJNnc7wNkrjrububZRwG2aH/PVEI9RU4Prsa6MEXMTSxIBX9tcSHQUgknkbJY83J8q3a7C6c1Ad4g3N3YFLm8gE1319fSdPnmxubtbpdP7+/llZWRkZGQ6PDIyBQ6cmh/IrmgbmRfsSHQtwCWq1uqSk5Pr16wqFgsfjJSUlLViwYOpGVnK+9Rmh313ugJ7ZwMXZXVMPHz78wQcfaLVaJpPJZDJlMtnu3buzsrLeeustNps9+YBgvF8b4VO/QU0FCKEbN2688sor/f39VCqVx+NJpdIffvghODj4nXfeiYiImPzru0JWbsgIKfi4AmoqcHEko9Fo+9qNjY3bt2/Pysp64oknIiMjEUJqtfrHH3/8+OOPV61aZXW6crvk5eWVl5dP8kWm5ayQRQAAIABJREFUiQ6JavPOC+UvwmnHdKfVajdu3MhisZ5//vnZs2eTyWQMw86dO/f++++zWKyvvvpqko9UXScrt+y88MTC6JwYaLoBXJd9yVZWVubr6/unP/0JL6gIIRaLtWHDhi1btpifyQInCPVhs2mUhttDRAcCCFZXV9ff3/+HP/whMzMTL59kMjk3N/d3v/tdR0dHU1MT0QE6zPrZId9dgY6qwKXZV1N1Ol1kZCSNRrNYHhcXp9PpHBcVsAk+nj7RUQCC6XQ6Go1mOs01iYuLw/9KRFBT4u400eEasd5gx601AJzMvpqalpbW0NAwNGR5bXTlypXZs2c7LipgE7xHDdFRAIIlJCSQyeSamhqL5VeuXOHz+TExHjVS7obZoXuvdBAdBQCjsq+mZmZmLl269Nlnny0vL+/r6xsaGmpsbPzggw8uXLjw5JNPav/H6jNarVYrFotv3brV3d3tSefOBEoNFXQOqvsVw0QHAojE4/FefPHFN99884cffujq6lIqlR0dHbt37/7b3/7229/+FiGEZ6XVodAwDOvt7W1qaurs7LQ6VZyruTcjZB+MUwhcmH1tlE6ePDnaXG/m/vGPfyQn3zGQ2NGjR9va2kxZzWKx5s2bFx8fb7Gh67SGcBcv769NDuFvygojOhBAGIlEMsZcbybbt29/8MEHzZdcvXq1qqpqePinczIymZyUlDRv3jwSiWS+mqtl5eL3S3duzYzyh5FQgSuyry9NdHT09u3bx11NKBRaLFEoFPPmzQsPD2ez2RKJpKys7NSpUzweLygoyK4AgIWlCYHfXGyDmjqdsdlsW7IyLS3NYolUKk1MTIyOjhYIBGq1+sKFC9XV1QwGw8Wf4+AdVV9aNYPoQACwwr7r1AkzGo3mJ78DAwN79+5NSkrKzc01X83VzojdQuTLRQ9lRyCECtJFSSK3HzAdOI1FVmIYtmvXLjabvWHDBvPVXC0rBxTaxe+fLkgXITjmgeuZyDhKE2BxN4nL5SKEDAaDc/buwcpu3qZSSJ+dbUEIHagS/31Tai703gO2schKMpnMZrNdPyuviQdVOj0c88A1ETO+9q1btxBCML35JFV3yJ7bU6PT//SUelA5/PQ3lbVdUmKjAm5qcHBwYGDAxbMSjnng4uy+Tu3r6/vuu+9u3rw5ODhoft84Li7u1VdfteUVpFLp+fPng4ODo6Ki7N07MHegqkuivGMGzUGV9mClOEkkICokQAiNRnPo0KHLly/39/fr9XrzP33++ee2jKOk1+tPnDjBYrFc/GEqHPPAxdlXU/v7+7dv3y6TyRISEoKD75hoLCAgwJZXUCqVhYWFTCZz2bJlFreecHl5eRZLXOpZDgCuBsOwF198sbKyMioqKjAwcAKzpWIYVlxcPDg4uGbNGqujdo/MSgSJCYA19tXUEydOqNXqL774Ijw8fAI7U6lUhw4dwjDs7rvvHm3AfUhU2xWki36o7JKqfj5t57Po69JEBIYEnK+xsbGysvLVV19dsWLFBDbHMOz48eMdHR2rVq2yOFE2cZ2shGMeuDj7nqdKpdLY2NiJFVS1Wn3o0CGdTrd27VovL68JvAKwkCTif7Q5zZvz03xeZBLp1TUzZkIzyGlGKpWSSKQlS5ZMYFsMw06cONHa2rpixYqwMDfokWVxzPNZtE/uT4NjHrgO+2pqcnJyZ2fnBEZBUqvVBw8eHB4e/sUvfsHj8ezdHIwmN8Zv17bM7bmR23MjDz6Z/dI+mKh82pkxYwaVSm1ra7N3Q6PRePLkyZaWlmXLljlkSjjnMB3z0f6cX+ZFZUdDo1/gQuzrn2o0Gv/0pz/pdLonn3zS39/f9g337NkjkUhSUlK8vb1NC7lcbmhoqPlqrtYTzu3c6Ja/sLf6yLNWnn4BD/bjjz8eOHDgpZdeio2NtdpMwary8vK6urrw8HDz8ffJZLLFAGcum5VH6noOVXV9cr9LN6oC0419z1NJJNKGDRt+/etfFxQUsNls8wlqEhMT//KXv1jdCsMwiUSCEKqurjZfHh4eblFTwSQlBPF+OT/q+T1VH2xMJToW4Dw5OTnHjh175JFH6HQ6i8Uy/9OhQ4dGa/fb39+PEGprazO/xqXRaCMHDXVNK2YGPvn1VaKjAOAO9tXU9vb2J554gkKhLFq0SCAQmJ8Ri0SjNhMgk8mPP/74xGME9liXJmroGfrn6abHFkQTHQtwBr1e/8wzz3R2ds6ZM0coFNre7nfdunVTGthUI5NISxICjl+/vSwxkOhYAPiJ3e1+qVTqV1995evrO0UBgcn77aoZD392KV7otSjepg5OwK3V1ta2tbW99957c+bMIToWZ1s5S3i0rgdqKnAdE5mTHAqq6/vs4cxX9td1y9xg9i4wSTqdjkQiufhYDVMEr6lERwHAz+yrqbNnz25ra1OpVFMUDXCg4ufnL/+gjOgowJRLTExkMBj19fVEB0IADp2aHi4ob+wnOhAAfmJfTU1PT8/Pz//tb3977do1pVKpNQPTjLsaLyb104cy1/+zguhAwNTicrm//e1v//znP5eXl0ulUu2diI5uysGlKnApDpuTPCkp6eOPP55kNC7bat99fX2h7bp46I/rZhEdCJgqY89JXlpaOoHRCs25eFb2K4ZX/q388qtLiQ4EAIQcOCd5YKBjmgmUlJSYfl60aJFDXnM62zIn/LWDdV9WtD0wbyKjXwHXN/ac5LYMoD8uV85KPy4j3Jd9pW1wdrj3+GsDMMUcNie5RCLx8fGZ5Iu4+Bmx+9rwr4pfL4/PipzsPwi4l8HBQYs+bxPg+ln5n/LmXvnw71YnEB0IAJOeP1WpVB48ePDRRx997bXXHBIQmAp7H523fddluRqeeU8LBoPhzJkzL7/88rp16zAMIzqcKbdypvDoNXikClyC3fOn4oxGY2VlZWFh4enTp4eHh/39/Tds2ODYyIBjHXtu/oq/lVW8PJGR1oG7aG1tLSoqOnbsmEQiYbPZS5Yscci9XxcX6sP2YlKvi+WJwTCWOCCY3TW1p6enqKjoyJEjPT09CKGYmJhnn302JSVlkveXwFQL4jP/fE/yg59e/GJbFtGxAAdTKpUnTpwoLCy8ceMGQojNZr/xxhs5OTkMBoPo0JwEv1SFmgoIZ2tNHR4ePn36dGFhYWVlJYlEysjI+OUvf3no0KGAgIDUVBha1j0siPOv7xl6u+jGy/nw5MkTGI3Gq1evFhUV4beLYmJinnrqqd7e3pKSksWLFxMdnVOtmCV85pvKF5bFER0ImO5sqqkXL178/e9/r1QqIyMjH3vsseXLl/v5+SGEjh49OsXhAQd7dH7UC3ur9l/tKkh3uWmcqztkB6q6EEIF6aIkmBFzPBKJ5NFHH+3p6fHx8Vm7du2qVatiYmIQQl999RXRoTmP+TGjNWAt/cpIPw7RQYFpzaaa2tvbq1QqExMTn3rqqaSkpKmOCUypv25Izf9/5TOEXi51o6zs5u3n9tZIFFqE0IEq8d83pebGwLyYY1GpVD09Pb6+vk8//fT8+fPNJ4maJiyOmdxo36PXeh6HqSMAoWxqv5CRkXHPPfd0dnY+8cQT99133+eff97d3T3VkYGpU/RM3i8+OqPHHNONavKqO2TP7fnpyxEhNKgcfvqbytouKbFRuTh/f/8dO3awWKzXX3997dq177///vXr14kOynlGHjOlN/v2X+0kNioAbLpOFQqFzz333JNPPllWVlZUVPTZZ599+umnycnJfX19AoFgqkMEU+HY8/NXfFB28lcLiA4EIYQOVHVJlHeMojeo0h6sFCeJ4OgaFYPB2Lp169atW6urqwsLC48ePXrgwIGwsDAez4VuP0ydkcfMkEaHGbAeuUbIYxIVFQCU0cYatLIqhRIVFbVixYo1a9Z4eXnV1NSIxeL29vbGxkYKhSISiSY5BBpC6LPPPtu2bdskXwTYwodD9/NifHiicXVyENGxoNM3+6o6LK9KZWqdSmsY0uiZNLIXc9rd2LSdUCjMy8u79957RSJRe3t7XV2dSqW6fPmyTqcLCgpiMidbYFwzK60eM2G+bC6DmhoKp2KAMBMfR8loNOInyKWlpRqNJj09/cMPP5xkNK4/YouH+evxm1Qy6ZklsQTG0CFRvXO0/nBND0I/H4pcBu3xBVEKrb6hZ+hG95BiWDdDyJsR5DVD6DVDyJsh9OIwJti12uO1t7cXFhYeO3ZsYGCASqWePHlykl1UXTMra7tkD/z3olT186UqnUrxZlEHVbq1aaL5sX7z4/z5LDgVA87mgLEJVSrVyZMnW1tbn3766Um+VF5e3ptvvmn61dVGFvVIj355pSBdtGKm0Pm7vtQq+U95y41u+Y68qCh/ztO7KweVWoQQn0X75P707Oif2ygNafT1PfL67qH6nqH6Hnl9z5CATUsQ8uKFXjOEXjOCeLEBXOfH78owDDt//nxhYeFbb701+Zrqmll55la/6Zhh0iifPpSRHe036/VjLy6Pv9Q2WHazL9yXPT/Of36sP4zKCZzGYeP9OoRrnhF7vIXvln6+LTPC13mdEA7XdP+nvJlOIe/Ii1z+v3Je2yU9WClGCK1LE80cry9N16D6Ro+8oWeovmeovlve1KeMF3olBHnFC3kzhF4zhF6B8FDNQVw5K03HzH/PNDe/vYZEQi/uq8mI8N6QEYoQqumUld3sK2vsq+qQLojzz4v1nx/n58zjHExDUFMBGtZjya8fa/jDKifs679nWnaWN88O996RF5XiuOdemNGI3yVu6JHX9wzV9wwN6w3xQl6C0Cte6JUQxIsXerFotj7vh56y5twiK78631bfM/SHu2edqu/96nzbpw9lmv9Vq8dO3+wrb+wru9lvMBrzYv3wEsumWz8k4AAAEwY1FSCEUHWn9PcHrh18KmeKXr9vaPg/5c3/KW/elhO5PS8qiD/lF5FSla6hR36jZ6ihZ+hGt7yhZ8jfizEjiDcDr7JCXpS/9esV816P3hwG9JR1l6xc/kHZR5vT4gK9Yn935Pqb/7+98w5o6uoC+M1mh7CRJQioKLLEgYCgoDjqXlVra6vWbkc/ta6qtc5ql62tttqqdW9RqIAoiAqy9wybAAESAgnZ7/vj2RgTCCGEJMD9/WNyc999h+c777x77rnnTCfgOvd4V7dwEkuaUBM70tYEdQ77OL5+vYM3AKQ3QJsKecXV1OrUCsaRRWPUO2xubevpROqzsua1QS5rg1y0mBa6qoVTSGMVola2nlXVwhnxn6N4uI3JSFtjCyNSVnXr6r9SpDdpUAyI5z7wH8y7evqLViZTm4/HllxZN+HTixkRo61njxnS7SFplQzUOVzS0B7sbhnkZmFlpPe/G1nwBoCoDAyehLxiyViHovq2P5+WfxDorJYBYwsaTieWs3nCtUEuPy7zUcuYvcHRzMDRzECyfCsUIYX/OYqfFJcV0NrECELC4+BO2X7KeBdzC8PK+zm0iNE20bk0ZWyqnxPFz4myMdy9nSdMKKYnljTdzSpg84TSfeANAOkR0KZCXrNrtsfKP5KH2xj30tl1MbnqdCJ1mKXRpjC38S7m6hJPveBxmNF25NFSq2UtbP72W7m01g4tSgXpDd/MGx12/EnKjrANlzN6dKARCT/T03amp60eAXc2qbyPxIMMBqBNhbzBhTXjx+6Pjd4QZGHU4zJhbVzh6UTqH4nUeT52Z97z73fZzM0MiZ+EDntBbZbe9UjWJ873UUO9ARj2ogHMDImrJjqdeFQaMtwqtqAhbKR1T0dY4Gt3K6O2L24ACMqAV4SBX68Y0lMebgye9n1Cjw4pbWzfeiM74FAcHotJ3Rl+YL5nvzOoKJ52ZHMjovF/uQLI+oSTK3263djTLQnFDav/TjmbVH42qXzVmZdPS5t6LSmkczaEuZ97XhHkZhGdW6/C4Z525BPLfSiGRPSrum4ACMpgUAQYowTphOdlzT89Krm0dkK3PZ+WNv2RSK1hdKwNclnq76AB2fqUzy9lhHlYO1sYKL9Ttlv6e9xTv9PKyGxaZHbd05Km3L3TVRsB3fZ6KaXq1xV+k4dbqle8QUt/VwQlgb5fSCdMHGZeWN+2917ePG/7rhw1N9JrTieWWxgS1wS5hAyI586xh0Vu1sZzvIYAANSo57BCgIaZPcb23PMKaxP99RfSbcl6KvgYPe1MPe1M61nctjfjlSC9YZAoArSpkM5ZPWnoe2deLP/zBZsrBFI1TQUi8R+J5acTqaHDrX5Y4jXCdoBUQbmWWl3P4h1V91YiiFaY5227405eGb0N9KIcr68TJb2SMVsHikxA+hE6Z1Pj4+Mln3Uns+ggJKu6Nbu2DTWoAAAGm/fJP+lB7hb/5jasCXKO3TTZ7L81pwFASnnLtbSaqx9O7IvBDUk4ADDSFQL6XdhL/9LKrOrW7x6WIOJXX9FyvCr4GP2cKOgSAEQtLPC1O/+iUigSS1r6nSIog87ZVN3X2EGCvKOmtUPQ0sYv+VYTKQw1Ca2V+8XljOdfTVX7yDWMjo1XModZGmGxgKxPlKoQ0M/CXvqXVqrLx+hlb5pX1yoUI3is9jKVDBS4AtFHF9I2hrmffFLazhWC/qkIyqBzNhWiy3gMGSCeXmmCj8Tn71MxmEUBP8WVXE2t/n6p97JTL0r2z8intaox7gmiGVD3Lyxr00tyalsX//Y8dtNke4p+RXN7BZ3t5WA6UBUB2lRI5wySjXpTjz2J3hDUVW5Y1cioYm66mvmW15CnW6d47I7O2TMdh8WgYS9qPAukK9R46/o5UtKqoE3tFTfTa88mlRd+E4F+rWjibJkxwn/ogL2kcH8qpHMGw0a99/96uWPWyGGW6qy9uutO7r7IvDPv+W8Kd/fe9/DZtqldFT+B9BFqvHXReapapRtcHI4ufFpKv/dZoKTlZUXLADaoAM5TIQoIdLU4977/QPVY7rmbF+xuOWWElboGfJhXv/Fq1raIEd/MHQ0AGH8g7t8NwaYGBHWND1Eedd26fk6UrTey1SraIGLtuVRfR8rWiBGSlgFvUAG0qRDFDFSP5ZmkciwG817AULWM1iEQbbySKUZAyvaphiQ8ACDoSPz19RNhXXQtopZb18yQSNYnlDex+2leMG0hFCFhx5/smDUy3OON9JAvy1v8B7ojHfp+IYOO2IKGZ6XNu9/yUMto/yRX+u6Lmedtd+odP9Sghh1/cvY9fwczA7WMD9Eu0P3bUwpprBG7o/5631/GoAIAUipaxg30eSq0qZDBRUlj++Gowj/eHdv7oapaOAtPPsuvayv4JiJi9KsScjN/SvxpmY+rlTrXaCFaxM+JkgZtqtLcy6rbcDWr9NuZQ807mdm/LGf4O1M0L5Umgb5fyCCCJxTP/imxaL8attj+EFt8M732+6Xefk6vnxHzf036dp7ngNxxNGjxc6L8nVShbSn6B8djisub2NFfBHX6awGN5WhuYEgc4EYHzlMhg4jgI/EJW3qbviCtkhF8JB4ATMKWUGmDuvTUi20RI3wcB+Dy82BmuLVxDbODDRP/dsdHF9LwWMzPb/t01SGlvGUw7Eoa4K8MEIiExb89P7Hcp5dxQ9tv5RTVt11YM97xzeXSd/5M+TR0mM4WYIf0BtT9G+w+EApF9BFhx59snjZ8xn8rIJ3ysqIlYvTAT56scza1f2UWhfQXNl/LWubv0Js4/ujc+o1XMnfN9jgw31Pmp7XnUldNdApyG7DP3EGuldCmKqCksT38+JPYTZO7jSF4WcHYNVs9gYG6jM7Z1EGosZC+5se4EntT/YV+9qodzuYJN1zJxGEx6bvD9QmyCRw++Sd9no+dfIjjQGKQa6WfE+W3x2XalkIXicqtP/6wqOLQrG57VrVwSHjsYNhdpnM2FQJRL7czasub2D8s9Vbt8PPPKw9FF/6w1LtTq7npaubUkdazPAe+R2sw4+tISa+Cob+y/BRXUkBjxWyarEznwbAzFQXGKEEGMulVjHPPK1UzqOVN7Pm/JhU3tuXtnd6pQd12I3ucs/kC34GWAxkigwER52huWEhjaVsQHeKzSxlCMXJypZ+S/QfDzlQUOE+FDFia2/lrz6Wm7QxX4djjMcX3suqOL/HuKo7367t5I21Nlvk79E5GSP8ATaY/whbukgIAgIgfEz8JGfaW1xDlD3lZ0fJh8LC+E0l30PQ8lcViMZlMsVjcfVcIpHcEHXmUuGVKT49KKW8JPPwIj8XEfxnSlUH99n6BPUX/XTWlNtQ6HA6HyWTy+fzuuw5WYOYHlPImtuv2Bz8s8eqRQW1h85kcgYvloMjvqKF5Ko1GS0lJodPpAoEAALB8+XIyeUAlZNciWdWttzNrAQALfO08B1aa+94Q8WPizY8CeloT5qubOWX09svrJtpT9Lvq893DIrI+YW2QS69l1DIdHR3x8fF0Op3D4QAAQkJCRo4cqW2hdBQ/J8qPccVgcKtbTH7DgQcFhftn9LRI+yDZmYqiIZvKZrMBAB4eHiwWq7y8XDMnHQwkFDdsuJrd0s4HANzOrPv5be9AVwttC6V91p1P2xTm1iNP3f0c2qYrmXvmjDq4QHarjDQ/xZVgMZhPp7j2WkbtIxQKORzO0KFDCQRCVlaWtsXRaZzMDdp5wsis2t338genuv0aX5pRzYz/MkSFYwdDORoJGvL9urq6zp07NyAgwNIS7vFSG1nVrRuuvDKoAAAGm/fZxYycWqZ2pdI6394v8B9KmTZK0fZzadq4wjV/pz7IpmXvmf72OEcFPX9PoLJ5wk3h7uoQU/sYGxsvWrRo8uTJzs7O2palH+BmZbLtZu7gVLdNVzPb+aLTq1TMkg1tKqR/cDuztoX9xhoYg8NHa0YOWs4/r+QKRco7Zv96VhFwKG7ZOIdfVviS8IrU4WxSRX1rx1czoXd0kCIUi9vfzFA4SNTtrZ+fBrpabpk+XLXDeUJxUX3bGPvB4ieHcb+QgUNCMT2moOHc++OU6UylszdeyfRxNM3ZM73bzhdTqkoa2g4odAtDBjZWgyBfgQw1jI6w40+urZ/Ym5XjQTVJBdCm9msW+Nrdyqhlcl5PVbEYbEx+g7kRaZ6PnS15cD0CypvYX9/NU3K95+i/RVG5tO+XenvZd5/y/kZaTVol49hir96KCOnPrA92uZ9dJx2cQ9YnzvcZsLuT44sad93OzdwdrieXO6xHDJ5sDyg6Z1PPnj0r/XX16tXakkT38bQjn1ju89mlDAabDwAg4LCrJw1d5Gd/K6N2wa9JTuaG833s5vvYERW6NAcGYgSZeuwJ9eDMbnsmU5s3XMlaOcHx0eYQZUaOzK6LL6KfWN5ltY3BANRKAMAYe7KrlVFjG6+tQwAAQBBwcqXPqAEa+nsqgfq8rPnp1h5vRZMnpaLl8yluvR+nv6BzNnVwqqvKBLpanHvfH13Ume9jdzCqsNGdtzVixNaIES+ozbcyanfdyQ0baT1/oCekDToSn6hEEbct17MrWzg3P55oS+5yq4w0D/Pq72bRTr2jbLKYgQrUSpQQd0sMBgAEAABelDdvuZb9dJsarI6u8b/r2RQDwtnV/moZDc5TIf0MTztTT7tXDswLa8aHfvf4zHv+zhaGE1zMJ7iYH1445kEO7Wpq9YYrmei0Vbrk58Bg+ekXRxd52XW9oxQAEJldt+FK5oH5nkcWjVFy2CfF9H+Sq/5WbnUWMhjwc6JEZtN+XeELABCIxCN2Ra+/kPab0vn5+gXzfklaMd5x8Vj1JAjLrGaOtiP3dD9rv2bgewUHG/Ffhkz7PkEgep2paqan7elVY1O2Tx1hY3zgQUHQkfjjMcXlTWwtCqlGtt3InuNtFzCsy8KlTI7g/b9eRuc2FO6bsUTpJ8XzsubfnpRBgwqRRjqbEgGH/WGpd2Uz53B0oXalUhf1LO7or//dM2eUugwqGGTZHlA0NE/l8XhUKhUAQKfTAQBlZWX6+vokEsnFpd8no9FBnm2bEnDo0csdYdKNhiT8yglOKyc4VbdwbmXUvv/XSxN9AjpzJesTtCVqLzn5uIxiSFSQdPdMUvlPcSXHl3hPGWGl/LDpVYyj/xbd/DhAHTLqNMXFxSKRqLW1FQBAo9HQRnd3dxyuV2EpAxVrEz08DlPL6ECdIm95DYnKrc+sZl5LrVajHdIKiSVN/7uW9WL7VCOSOo3Cy4oW5V9kBwaay6P0+PFjydfk5GQAgJmZGbSpfYGlMen0qrHzfkm6/ckk+V8dzAw+n+r2+VS3rGrmrYza4CPxvo6UBb52PUrgqQtEZtPy6lpPLPft9NeSxvZNVzL9h5pl7p7Wo2Fza1t338mL/CxQHTLqOklJSVwuF/1cVFRUVFQEAHB2doY2tSvQZPqShYZfV/i6fPVAIBQ7WxqN7berKmeSyuMLG19sn6r2kV9WtBxdNLgC5jEIgmhbhtcEBQUlJiZqW4oBQmQ2LTqX1pXJkSa+qPFmeu2DHNo8H7v5Pnb9It1aTm3r9ps597qwfIejC2PzG44v9e7pvrqSxvaPL6QpWRJykAC1Upq/n1VQm9h754yStMTkN1xNrU6rZMRummxmSNSibKqx/WaOHgG3+y0PtY88OLUJrqcOWGaPsfW0Nz34oKDbnqHDrX5+26d4/4wAF/PfHpeN3R974EFBgQ5Xi2ztEKz8I7lTg/qsrHnCgTgTPULMpsk9NaiVzZw1f78cbI8ASI+QL1AT7mFtrIffHD485LvHWhJKdRb/9ny0PbkvDCoYfBG/KDDudyDzYbDL7ju5555Xrpro1G1nHBaz0M9+oZ99UzvvZnrtpqtZYjEyz9duvo+djQ5kkJGuB7Lyj+SEznbOfHktq47ZcfvTSSoIXM/iLv39eV+4vyADCZEY5NNYu+/kLR5rL3lpO77E22N39Nn3xs39JelOZwsuOkhTOy/s+JPTq8b2XZKjlxUtwe6DLsE79P0OfD74++XycU5TR/YgSAelqKHtdnrtrYxaZ8tX6SMIOO04NqTL7+Cw2D1zPN6Z8MZTkFI3AAAgAElEQVRbwp3Muk1XMw8vHLPIz16F8VvY/LDjT9J3qVK9fMADtVKC9H1IMSRJ16VJLKGfSihf4GuXUEz/fqm3VsXsnhfU5k8vZsRummxq0IfxiZMOP7q6bqLiTW4DDzhPHfj8+a5/xA8JdhT9ETbGPTpwuLXx1hkjts4Y8bys+VZG7Y5budM8rOf52FkZ62myhOSr8jv/VQsQicXHHxZ7O5DRXbktbP7GK5mmBoTi/TNwKm2DY/OFQYfj8/Z1n/UXMpiRuQ/RujTnPvBH78MgN8uonPoOgcieov/zo9LPdLga4PnnlfdzaKk7w7rv2gtorR1iMdBxg9oX1XChTR0URG8IHv31vyoHyk8cZj5xmPmRRWPu59B+e1KSXtWKejc0U0Kyq/I7nnamfyRSf31c9v1S78mqupiEIsRr78PSb7tPaggZ5Ci4D9GvBxZ4+n4TE7tp8u47uZHZtNljbLUhZjfsvpOLAHB53YS+PlFKOWOcs04HQvdR8Wmdi1GKl0Lbsgwo0E2rvRzE3tSgvKlDslzAYPPW/J36bz6tt8L1HAaHP/OnxHoWL31XuMoGFQDgvjOqeP8MNQo2IIFaqSS/rfRbfyHtxHLfXx+X5tfpXJTf26dfuFoZfzN3tAbOpePlaPqu+LTOzVNDQ7vP2gpRARN9wpV1E2b8mBj1RZDKg8i/qnMFov9dzT5pSUUXXE36IH2EfPkdIh6XVsH4daWfxxCT3ow8Yld0/r7pWMwgSpymGlArQedloDBz3tzVPc7ZbPQQ8pmk8gefB43cFZ2+O1y/d0Vd1AWTIwg7/uTnt30mdp1xTL28LG95R4nQSG3RrddBZXRungrpO0bammwKd197LlW9wy4Z67BnzihqEzvwSPz7f72MzFZzlWa0/A7lv51/GAAW+dk93hLaS4Pqtfdh8vapvaxjBRk8yNyHZH3C0UVjFvz2LLe2Vbrb7rc8TieU01o74v8XEnr0sRYEleNlRUvId/HRG4I0ZlBZHQIaizvcumcBHAMDaFMHF+Ee1pNcLfbczVPt8AW+dqYGb+xqR0tIejuY7p0zKvvraSsnOEXnNrhuf/Dltayk0iZ1iAzAf+V33KyMSHjslunDD8zvbW1w/29jYzdN7r9JGSFaAb0P1wQ6rwl0vrhm/EI/+9JvZ267mXMjrUa62+/v+H14Ps3GRO/7pd5vn36hLWlRLqVUHYkuytw9zcKIpLGTvqxg+A/V3cXUymZOSWObTKO6quHCvTSDkW/vF1iZkNYGqZIY8npazZYb2WIxAgAg6xNOrvQNGCa7sC8UI7czam9l1BY3tC3wsZvvYzfCtldzylsZtRuvZB5b4tXOFcpksVGBwMOPLq+baK/bEYm6A9TKbtl8LcvMgLhj1khJy+HoQhM9wkchwy4mV+XWtfb+LVA19kXmd/BFBxdo+uyHogpNDQjrJw/T8Hm7JbWS8Wt8aUp5i7EefvUk55NPytDi0109ylQA2tRBysf/pM8eYzvTs8ehiUFH4r9+a+ThqCJbst7WiBGKazLT23g3M2pvZdQCBEETH1r3MBtDUztv45UsCyMiuuevltGx5NTzpF6USp5y7PEfq/xdLA1VHmGwAbVSGU4nUhOKm85/8LqQkaTq4v77BTYmpDUqvcL2hnf+TAkdbvl+oLOGzwsAWPDrs52zR/o66tBUNSq3/lRCWUMrl9kh+Gbu6IV+9gCAnFqmpPi02srLI7pEYGCgtkUYRMz5+WlmNaNHh2y/mXPhRQWCIB9dSLufXaf8gQU01sEHBeO+jX371POrL6sEQrEyR/3+pMzvm5iE4kbpxmnHnxTWs3oktoSIHxLy61pVO3bQArVSSRKKG8fuj2lu56Ffi+pZ4cefoJ/f/yslNr9BY5K0cwUTDsTKKI7GEIrELl/d18qpO+XvZxWTDsXN/ilxxM7oH2KL+/p0cD118HLn00nv//WyuZ3ffVcAAAAx+Q2NbdwV450AAGye0LAnW11H2BhvmzEiefvUT6e4pVQwRuyO+vRiemxBQ1f9C2isiB8Tm9p5qTvDgtze2CozZaTVo4JG5U8tYe4vSYcWeI7snRcaAumKIDfLB58HhR1/8rysGQDgbm08a4zt9zHFAIA/3/Xffz9fM0WLM6uZ4w7E3fx4koziaIzUipaxOrCLpo0rPPawaPjOqMQSOhGHG2lrkrpz6hdT3fr6vNCmDmqebZsacChOmZ48ofjTi+mnV41Fv3L4IgOiKhGzAcPMjy4aU/rtzIjRtpdTqj33/Lv7Tm5G1Rvbwr69X7DpatYPS7y2zxwpP8LUkdZxXRvjrljy+/MdM0d6OfQ2UB4CUYClMSl9V/hPj0rOJlUAAL6Y6vYwvwEtRxH/ZUho3yfZv5ZaveduXt7e6bZkreXoTqlgjNNqgBKVzt52IzvgUBybL5rgYtHBF518x/fIojE9mgaoDLSpgxoSHvvgi6Cpx55023PVmZRz779eK2LzhYbEXt2gs8fY/vHu2GfbprpaGe+LzJt8NP6H2OLrqTV++2OsTEhRXwR1FdY01olS3NjO6hAof653/kz+bIrbuMFXIgOiFS6tnVDVwt52Ixv8FwOMtve1WT3woCClgtFp1WRNklLeoi1dS6Y2f/D3yzXnXo62N53rbRdf2PjeJKcLa8ZrclcPtKmDnWGWRl+/5bHqTIqCPr/Gl/o5Uca7vN7cxuGJDEhq2NlprIdfNdHp1seT/l49PjqvYeed3CFkfRIe18YVKjgqbKRVrNLu3zV/p74bMDTIrR8UhYUMGL5+a5S3I2XeL0mOZgYrJjihJRedLQx3zfZ4/6+XfXHG9/96aWFEOrpoTF8M3iO04vuNzK6bc+Lp8diS5eOcFo912Hcvb4SNcfyXIaHDe1w7pJdAmwoBwe6WEaNttt/M6fTX3NrWB7n1W6YPl27s/TxVmhtpNaHH4tcHuxR+E7Fv7ujSxraAQ3Ef/P0yMrvzrIdTRlg/KlTK/fvxP+kLfO3CRlqrS1QIREmW+TvsmTNqxK7oiFE2KRUt6ALHlBFWk1wtvonMV+OJeEJx0JH4lROc1gVrOrRYntza1mFWRprMHnUmqXziwbjo3Ib98zxXjHfceiObxREU75+xcoJ2sjjpXG5C6YSiMCOaxlg+zvEoo+iX+NJPQmXraaw6kxIrV6ZbXfPUxjbexiuZNmS98oOz0BYfR1MfR9N9c0fHFTTeyqjZcCVjvo/9fB+7AKkUMFbGelG5DXvv5SuuJrHxSma4h7UK+4UgMkCtVA1vB9PM3eHTf0j4NNT1w/Opp1f5o1VQ6lncf5Ir0XC/XpJb27rw5LPYTZMdzAx6P1rvSaloGaeRSSqDwz+VQD2dQF01cejNjyfVMTt23c51MjeI3hCkyewW8sD9qZDXbLiSGeJuOU8qmcjGK5nB7pby6UWGbrtfcWhWL0938knZ2afl3y/1ntR1OQihCLmVUXMro7a0sX2Br/08H7tGFqerGpbSbL2R7etIWerv0EshIVAre8+682n0Vk5+YzuPLwYAUAxJtmTSzlkeAb1LFngro/bPp+WRnwWqSUw1oPLGd+Upbmg7lUCNK2hcF+yyNtiF3sb7JjK/gcXd/ZaHl732gxB1bp4K0SI/LPVe/NtzO4o+WlDidkYtAoC8QVU56FdCXh1r45XMqSOsUnZ0U8QRj8MsHuuweKxDYxvvZnrN+vNp1QyOSPzqRVCmhqWE3XdyRw0hQ4MK0RE+CXFdduo5TyBGvzLYPIAgn19Ku/dZsMoBukf+LaIxO3TKoAIAUspb9s3tVZozBSSVNp1KoNJaueuCXb5b7AUA2H+/4H523a7ZHrrjjoI2FfIG19ZPnHjw0c2PJ5LwuH2R+em7wuX7cPhCg14spn4Tmf+C2nxiuY97T4LxrIxJ6ycPa2DxziaVS7fLV5PYf7/A0cxglQ7XxIAMNm5n1nYIRNItDA7/vYChod89LvwmQoUB155L9XEwRZOL6Q7lTWxjPXxfuF7vZNadSigzNSCuC3ZBazueTar4JjJ/+8wRz7+aqvbT9QZoUyGyPNs2xWX7/VFDyNKbZ6Rh80SGKi2mPi6ib7yS+ekU1/ufq15vTjFH/y2iGBA0nwcOAukpeCzm5kcBM39KfNATdRCJkbDjT7bPHBnuoXORd31RM/WPROqpBOrEYeZHFnmNGmICAIjJb9h7Ly/cw7r0wAwdLNQIbSpEFgwGvDNh6J3M2tFdhP+oME8VipFNVzJZXMGjLydT3qxs0yPka1hKV5P4Ma4Ej8XIh1lBINqlq/vWY4jJxyGun15MP7HcV5lxCuvbZv2UGLtpsrOFLiasfqm+bA/N7fxTCWWnEqkfBLpEfh5kZUwCAOTVsfZF5pvo4XW5BgbcSwORJaW8pbCedeodv6WnOi9TxeaLDHuynnottXrEzqgwD+u/Vo/rjUEFndWwPLnSB01+/duTsg6+aGO4e2/Gh0D6AgX37ewxtsNtTI49LOp2kMjsug2XM8oOzNRNgwoAeFne4t/rbA+FNNamq5nTfnhiZkSiHpi1c9ZIK2MSkyPYdDVzy/WsTWFup1eN1VmDCuA8FSLPqjMpmbvD9Qi4JWM7Nl/NOrbES6YDhyc0UC7LF62Vu+lqpj3FoPTATHWJh9awlKkmcSapvJHF2/2Wh7rOAoGol07vW5TPprhuupp5M712gW+X9Tu/jykuo7OjNwRrQlaVoLfx2HzhUHPV7X1iCf1UApXezl8X5HJ8yeul4mMPi86/qNw9e5R0o84CbSrkDdadT/tpmbceAQcAWOhrX8voOB5TvOnNyZ+S89Rf40vPv6g8vsR7Yu82DMjjaWcqHZR0MbmqtLFdWyUqIRAlkblvpTm+xHveL0kulobenaWk/vif9OE2xieW+/SxgL2iN4upN9JrTidQLY311gUPk055dvll9b57eR+FuGbunqYmMfsc6PuFvOaf5EpLI9K0UTaSls+nujWwuFdeVkt363aeml3TGnb8STtf9PyrqWo3qDJcT6tJr2JAgwrp79z+ZNK7Z1Ja5RJZhx9/MnuMrQYKqvQSFWyqGEF+e1Lm+03Ms9LmH5b5nP9gnMSgJpbQw48/yaxipO4M/2xKf4qQgPNUyCtqGB0nH5c9lSv3fXjhmJV/JNtR9CWpFRTPU/fey0urZPy20s/VyqgPxQUAAHAvq+5JMf3nt3X6/R0CURI0yb5kA1tpY3vY8Scxmya79b0q9Z6U8pZFfsruCG9gcU8lUM8mVawLdondNNnM8HWYBZXO3nsvT4yAX1f69Ys/XAZoUyGveOfP5PMfjO/0pwtrxod+9/jMe/5ocERXyX7jCho3Xc3cEOb+9Vt9telbmn/z6iOzab+/46eBc0EgGsDMkHh61diFJ5/d+CggOrf+u4dFvc9Wphk6BCIqnY3udVFMbm3rqQRqcnnLumAX6sE3wiy4AtG+yPwX1Oav3xqFbkLtj+icTYWZRbXC3nt5qyYOVRBPGP9liNuOqPx90wk4rLzvVyASb7yS2SEQJWwJJesT+l5e8LiIfiml6q/Vne+ghagXqJUaw8+J8vY4x1k/PXUw05fPs62zKBPxG1/UeCqB2sYVrgt2+UnOt/RLfOnPj0p3z/bo7+s4OmdTocZqnviixoomTreTy2fbpgQcevRyRxibL5LeEnP5ZfWu27nfL/WePUZD6cGelTWfSii7uHaCZk4HgVqpSRKK6foE7Jiui0PoIIpT519NrT6VQHWgGHw+xU0+wOJ2Ru2+yPy3xzmqllJK19A5mwrRMCIxsubv1DIl9rrUMbnjnc3H7o/1czJF0wrWMTs2XMl0sTAs+XZG30v6irRKxrGHRTc+CtDYGSGQviOruhUtVoMWWZrxY+JHIcPmeA356EJaVG79jNE23Y6gC6SUt3w5bbhMo0AkPpVAPZVAnT7KptMAi5cVLfvu5Q+zMpJZUu3XQJs62Hn3TMrfXeQglCahuEFSDeZhAd3N2vjnR6WXUqp+WOo9rte7vJUnp7Z1z928ezqWNxwCUQ1ptbqRUcvmCiI/CxxpawIAOLnSL+KHBGcLwxE2PUiLrS1SKxhjpTIo1TE7TiVQ/0muWhfs0ul6UB2zY19kfnM7/8ACTwXlGvsj0KYOak4lUD2GmHRaK02arOrWDVeyW9ivMqshYvGJR6VL/e2fbZMNEu5TihvaNl/NerhRd7e9QyDKI6NWLA6fYkAUisWSDtEbgt13RuXumU7E6/Smx7RKho+jKZp6N6uaeSqBmlHNXBfs0pX7al9kfnRu/e7ZHhH9ZBbeI3T6vwrSpxTWt91Mr9k+c2S3PW9n1ko0X0J1S0ffyNU5Fc3sdefSoEGFDBjk1YrB4V98USUQvTarj78MCfnusaYl6yHoYmpMfsOS35/vvps3c4zts21T3gsYKt/zzNPyodvu25vqP9s2ZUAaVADnqYOZd8+k3P10UrfdKps5hfVt8u01DE5cQePUkVZ9IJostFbu26deSBd1klmF0oAMEIgGuJtVdz29Vp+IszAiWhiRLIxIo4aYBB+JXz95mIUR0cKYZGFEMjcidrqZTVtKcSezlsEWlNLbv5w2vKuVoOjc+n2R+RGjbfrL7iCVgTZ1kPK/69lfTnO3Num8HjJPKE4opieU0BOK6QCAUUPIhiQ8myeUdDAiEU6u8Nt0NcveTH94T8qgqkALmz/rp0TpSq7Sq1C3M+t+ftu7W/c1BKJrdFqs5uKacaPsyKwOQVM7v6md19TOa2rnC0TI2WflzhZGTW28pnZecztfjCAWxiSJ3bUwIrZyeDczae1cIQDgVkbdieV9rhQdAhEagiQQim9+PGm0XeebU3NqW7+JzDczJF5fP3GIqe7mvlcXGARBtC3Da4KCghITE7UtxYBF8hpraUzKr2uVLy+VVcNMLG5KKKFnVTOD3S2D3SyD3S2dzA0AAE9Lmz67lMFg8wEAGAB+Wu791hg7AMCor/9N2T7VULmU+irA5gnHHYjL2ztd+q9Y/VeKtNOMYkA894F/V5lUIb0EamXfIa1WZH3CyZW+AcM6N4T77uXbm+m/P8kZ/dohEDW18SR2N7e27Xp6FU/w2mkMEGBuRLA1NbAwIpobkSyNSOgHCyOSpRHRwphkbkhSufZoVQvnVAL1RlrNumCXkOFWX93Mjt4QLD9LbmHz90XmlzW275rtoclIRu0C56mDBem5HcBgLnzwKta3gcVNKKYnlDQlFNOHmhsGuVt06sCRrqpxOaUq2O2VyxfdtJr1dZ9kuBaIxN77YmQiHTpdhbqTUQdtKqTfoaBYjQy73/J472yKi4VRyHBLAIA+AedgZuBgZoD+uvde/hsGFQCAAdNG2awY79TUzm9u59HbefUsXl4dq6mdR2/nN7Xxmtk8igHR0ohkYUwyNyRaGL9pd42JFkYkAk424CatknEqgVpAY60Ldin4JgIAcOFF5dihZvKuo+dlzZdSqnbP9vhhaT8oJqNGoE0dFMhEGAIEWX8+LczDKr+urbVDEOxuOc3Dev+80YpTIEmqavz1vEKynEPWJ1xaO2HmT4kPPg9Su9juO6OoB16vvhQ1tF1PrbmdUav2E0Eg2kJBsRoZ/lo9bvLR+HPvj0ddR91iSMSPVriq2sLm09t5TW28Zja/qY1Hb+dRm9jN7bymdh69jd/UztMjYC2MSJbGJAsjEocvLG5oJ2AxM8fYrgt2sTAioTlKU8pb3K1NpB8vDDZv5R/J70x0lF6vGTxAmzookJ/btfOENCb3xHIf9x6uhgpEYgzA4HGv3UYeQ0w2hrmvPZd6etXYTg9RLXRi+M6owm9mpFQ030qvSy5vrm7hiBHE0ljPw84ko4rJkVrcJesT5/t0WXgSAhkwPNoc4r4zSj5Di/zSLAGHO/esgiMQLfZz8HHs3GabGRLNDIkK4iHauMKmdt4/yZW3M+osjUmBrhZ4HKaMzk4pL2hq5zW18cUIwheJn5Y2ye8LIOG6LwcJBmKwoc7ZVJhZVGN42pF7alABAGyeyJAkqy3hHtY1jI699/LkExz2NJ6IyREklzd/+k+6mRFp+K4oDIKxp+j5O5vtnTMq+L+02nKrUD4KnGaQ3gO1UkfAYTH/bggOO/5EJhWwpx35xHIfiVKQ8Nizq8f6OZndSKvZF5nX2iFY5Gu/aKyDlTFJ+XOxecI/EqmnEqgL/exvfhzgaNbJ5LiU3v7OH8l+TmaR2XUq/DkDMtgQxigNCnJqW9/5M6XTCMOeDlXH7Fj02/NOsz3sv19gY0JaE+QiaVEynqi8iZ1S3vIgl5ZV3drOEwhFiIO5QbCrxUJfB1+nzl+xc2qZyqxCQXoP1EpdIya/4WpqtbxbSKIUtzNq730eZEt+FdVPpbOvp9dcT60ebmO8yM9hrvcQxeOXN7FPJ1DvZNWtC3ZZF+yiT+hyxnkrozahmP5+oLMKj5eBGmyoc/NUSF8g8xorPbfrqe9FQfHUnbNGfnQhzY7yOkmpgnii9CpGCrUlpqAxr64VAMAXiodZGi3ytbuTXXf7o0l2lG5i7pVfhYJABhjhHtbUJvbBBwVfvZmwRaIUAa4WO27lnHnPH213sTTcMn34lunDE0uarqdVb76WOWW4NR6PtTYmyWh9SnnL6URqaWP72mCXAwu6rw+DlqNR8HhRwEANNoQ2dbDQaYShCr4X+UJv0pxc6TfnxFM7U/0x9uQX1OaU8hb5PjfSa/5MKjcg4jv4whE2xmsCnUNHWPk5UQAAod89vrpuYrcGFQIZ5HwY7LLtRvbll9XL/DspAz5lhNXF5KrYgoawkdbS7UFuFkFuFvO8bT+9nMXmCgEAl15WH1noOcdryP0c2qkEKgmPXRvkEu5hLT9mp6RUtLwf6Ax6EsB8O6P2fk59ZjWD3ia7BDswgDZ1ECEzt5MJBmaweZ9dzOjW96JgngoA4PBFa4NcFv32DIvBmhoQjPXwWAxGLLW+gACMhRHp/UkuAa7mqB2VEPFj4skVvgpquEIgEAmHFo5Z8vtzsRiUNLYBOT/TgQWes39KDNshax2zqls3X8tBDSoAgMsXfnEpY/PVTA9b8r65o7wcejBHZHIETe08SbWZrlxHQjFyK6M2KoeWVcNsYfP18LhhVoaLx9qPdaJsupot4zEeAMGG0KYOXlTzvbB5QvkMD5XNnLiChpiChqxqpo8jxdeB/KKCUd8qrG8FQGpjuSEJf3qVX6e72ueeSDq80HOErQkYiKGAEEhf8Gmoy7t/pSJiAOT8TFbGpLfHOf4YV/LFVDfpQ+S1HgEgyNXC1JA479ekRX4OPg6UTo20PC8rWvy7qJnK5glvZ9b+m9uQU9vK5PD1CThXa+OV451WTnCylIqTUsFjrPto1KZyuVwajYYgiJWVlZGRbC09iC5wO6OWbEAMGPZqEilj3rKqWy+8qKpmcHJqWz3tyKmVjNj8hn/z6tk8oQ1Zjy9EOgSiovq2FjYPSKamCGKsh586wsrCiNSVU2jJ7893zBrpZW8KBmgooC4jEoloNBqXy6VQKObmsvWiIToL6mdC/sv0IO9n2hju7r03htbK1SfgFBtIR3PDPXNGHVvsfeBB7u57OUIhAgC4mVH7y3IfifbJv+mmlLdIJ4dpYfPvZNXF5NXn1rHauAJ9An64jfH7gc4rxjt2VRtVeY9xP0Jzcb+FhYUJCQlisRiDwSAI4u/v7+fnJ9MHRhhqEvlgYH0C3t3KqKCeRSJg27hCZws9GkvA5YsAABRD0rogp9NPK1BrR8DjMBjEhIQXI4ArFNkY6/PF4hoGJ8DZvIUjKKxnyZxrTaDzztkekq/XU2vPJJUDANZOdr6RWrM+ZBiqugM1FFBnodPpUVFRbDYbh8OJRCJnZ+fw8HDcmzsLoVbqJnvv5Z9NKpdptDPVGzvUzNyQZGZIbGZ3XHpZi+qvqQHpxHJvHAZzLKY4vYohFr9+7GMxWLFY5GxpNM/b/u/n5dLah8diPwl12RA2/O9n5Qeji7gCERYDTA1IG8PcypvY97LqPg4ZJhQhsQUN+TQWmy80IOJG2JDDPawW+zmYGw2QGuM9RUM2lU6n37hxY+jQoVOmTMHhcM+fP8/JyZkxY8bQoUOlu0Ht1TBdpRtNKm36J7kqKpf2xt2BAIBBAHjly8VisCQ8liMQWhqTpo+ymes1hITH7bmXl09j8YUimdtKD48bamnobG74ceiwxGLa0ZiyV+/XGMxCH7u3xztmVbcW1rMSiukNLK6MkDL2GKIuhELhxYsXCQTCzJkzyWRySUlJXFzcmDFjAgICpLtBrdRNOrWpM0bZRHjaNrN5hbS2O5m1POHrhIUIAvB4YG2sR8DhqhkckRjBYjBYDGbUEJNFY+0jM2kvK1vkzYG7lVEpvV0MAOp5QgAG88oHhT4KMPpErKcdeZqH9TwfOwujHux/HahoyPebnZ2NxWJDQ0OJRCIAYNKkSeXl5ZmZmTI2FaJhuvK9THK1iC1olNUvzH96BAAGiMUAdAjEGADobfxb6XWJRfQqBhcAgAAEAAwWCxAEoIpoQMDicJhCGquQxorKawCIdKZv5Hpaza3MaiMSwdyQhFU5qzek55SWlrLZ7FmzZpHJZACAm5tbZWVlbm6uv78/gaAoSyVEF+i0rM2nU1xRLd57L1/aoAIAMBjw9ljH0XbGB6KKxWIE1WaRWJxdw8yrZYkAgiAIFoNFEFSFARYLAECqGB1iBCAAYDEAQQAGIAgCMBjkv0cBoofH7Zo9EnqSJGjIptbU1Nja2pJIr95iMBiMo6NjQUGBQCCA2qtdVNroiUEAVrJiigWiDoGoltmBwyAiQMAgAAAgFmMABkE/s/kIBryKM0QQsYzZxGDAKBvyvc+DQBe5KQZAKKBuUlNTg8fj7e3tJS1OTk4lJSU0Gs3R0VGLgkGUQYVdoW1c0ZF/S1gdglffEQRBABYjEgEAEIABAIvwRBgpFQaYDvQfAMTIqxkqBgOA1Nv2wNhUqkZkyw70BQKBgMPhoO/CEkxNTURYfFsAAB1KSURBVBEEYbFkF94gOsICXztTA5kVkVfWEJFWKYBBAA5B8CKEKEIIkl8wAAFiAIAI/SyZsyoGfUxQ/otoGDChgLoJk8k0NjbGYl8/BExNTQEAra2t2hMK0gNQP9OaQOc1gc4X14yXjqiX11+yPhEBiEzQLwaDQQDuP9XEisCbKowgABEiiBgARFqLdSj3nu6hiXkqn88HAKBeXwnoVx6PJ9M5KEi2vAlcy9EK8m/Bn4QOO/mEypANxJcsrgD5CShAsK98xf/5jbEYIEZkemLWSqUzHJChgLoJn8/X03ujKL3yWgmgYuoGXfmZOp3FxuQ3ynRDAIJ5/bkTHxJAsOhvAPNKixGAwSAIwL7qCz1JMmhtfyr6zoORWz+Diqo7yJu3icPM72TUNbXzH+Y3cPjCbkeQB0GAPgHPEwoli7U7Zg2f86ZOwryD2gJq5UBCXn+N9QgyS7AAwQBMD6adCAAYjJhEwKGLtdCTJI8mbCq6jCrz8ot+lXlNhugaMuZN8vVpadP6C2ntXCEWg6oZAACIxW9MQBEEg0Ekc9JXizBodHEDq+NMYgUAYG2Qyxz4kqsl9PT0uNw3oqxRrZTEPUD6O3L6+8bkFQCAxYrFyKt3KCy2ExUGyH9rqP9pNNmAtG/OyJxaFoCepM7QhE3F4/HGxsYMBkO6kcFgYLFYExMTDQgAUTuBrhaX1o7/M7G8rLHdRJ+QWsXkCtBAh1c6iSAAYMSoLuoRcLtmjyinc4CUEs736SRPKUSTUCiU4uJioVCIx796DqBKSqFQFB4H6cdIT1497Uxyalm1zI4nJU0cnhCNx39DhYH4lcsXYBAEYDBisgHx5EqfgGEWc3209zfoNhry/aJRvu3t7Wj6JKFQWFVVZW9vj1Oubi1EB/G0M/1h2SvFyqllHntYlFLe3MEXIggWAIBDAA6H0cPjxg41+3L6cPgyq4M4OjoWFhZWVFS4urqiLVQqlUgk2tjYaFcwSJ8iPXlFTWNOLRN9PyYRMGk1LYgQCwDAIMCQgB03zNzUgIgaWvOuU6FBJGjIpnp5eRUVFcXExAQHB+NwuOTkZC6X6+vrq5mzQ/oaTzvTv1aP17YUkJ7h7OxMoVCSkpJIJBKFQikqKqqsrBw/fjx80x1sSL8fQ3qJhmwqmUyOiIh49OjR1atXAQBEInHKlCm2traaOTsEApEHi8XOnDnz4cOHkZGR6NcxY8b4+MBnKwSiOpqL+3VwcHjnnXdaWloQBDEzM4PvwhCI1jExMVm0aBGTyeTxeGQyGcYMQiC9RKN7abBYrIUFrDECgegWaKoHCATSezSRRwkCgUAgkMEAtKkQCAQCgagHaFMhEAgEAlEP0KZCIBAIBKIedM6mxkuhbVkA6CJ7uC6gs4IBKJtK6KxgQPe0UoIuXzR5+pG0UFSV0VoO/a4IDQ3VtggQCOQNoFZCIEqic/PU3nP27Flti9AlOiubzgoGoGwDhX50raCofUE/EhX0QlpdtKky/iV5d1O3HZTv3O3gvRmtW0eZzo7W02vem4um3tEG8H+oTtHLy67yICpctF7eb0oeohlR1TIs/M9Si6hdoYs2FQKBQCCQ/gi0qRAIBAKBqAcMgvSgyHtfo2sRXBCI1klMTNSuAFArIRAZFGilbtlUCAQCgUD6L9D3C4FAIBCIeoA2FQKBQCAQ9QBtKgQCgUAg6kHn8ijpDmw2WyAQ6Ovrk0gkmZ8aGhra2toMDAxsbW0xGIzGRGIwGEwmE4PBUCgUMpks34HL5dJoNARBrKysjIyMNCaYNNq6ODKw2eyWlhY+n29iYmJhYdGpJDoiKkQ1WltbEQQxNjbG4XDS7bqgBSjd3oQikYhGo3G5XAqFYm5urhUhZdBBkVD4fH5TUxOHwzE0NLSwsCAQCPJ9Wltbm5qa8Hj8kCFDOu2gAaBN7Rw2m33lyhUejzdx4kRvb29JO5fLjYqKqq+vx+FwIpGIQqHMnDnTxMSkr+WpqqpKSEhoa2uTtDg5OYWGhurr60taCgsLExISxGIxBoNBEMTf39/Pz6+vBZNGWxdHhvb29ujoaDqdLmkxMzMLCQmxtrbWNVEhKlNVVXX//n0AwKJFiywtLSXtWtcCFGVuQjqdHhUVxWaz0ZvQ2dk5PDxc5v1Aw+igSCjR0dGVlZVisRj9qq+vP3HixOHDh0v3SUhIyMvLw2KxYrGYRCKFhYU5OjpqXlTcnj17NH9W3ScuLk4sFnO5XAcHBxsbG0l7bGxsfX39zJkzp0yZ4uzsXFBQUF1d7eHh0dfyVFdXAwAmTZoUGBjo5eWlp6eXl5fX1NQkuatQZXByclqwYMHYsWP5fH5GRoalpaWpqWlfyyZBWxdHBhaLVVtbO378+MDAwLFjx1pbWxcXF5eWlo4aNUrydNARUSGqwefz79+/b2hoyOVyPTw8DA0N0XZd0AKUbm9CoVB469YtAoGwYMGCSZMmmZqaZmRkCIVCBwcHDYsqQQdFkpCZment7R0UFDR+/PihQ4fSaLS8vDx7e3tjY2O0Q05OTlpa2vjx42fNmuXp6VlXV5eTkzN8+HAikahhUeF6aieUlJTQaLSAgACZdhaLVV5e7unpid5kFhYW/v7+dDq9pqamr0UaNWpUWFiYvb09iUTS19f38fFxdnauqanh8Xhoh+zsbCwWGxoaSiQScTjcpEmTjIyMMjMz+1owCVq8ODKYm5vPnTvXzc3N0NCQSCQ6Ozv7+/tzuVyJJLojKkQ1nj17ZmRkNHLkSJl2rWuBhG5vwtLSUjabPWnSJHQRx83NzdXVNTc3VyAQaF5anRVJwsKFC8eMGUMmkwkEgrW19ZQpUwAAZWVlkg6ZmZlWVla+vr5YLFZfXz8kJEQgEOTl5WleVGhTZeno6Hj69OnEiRMNDAxkfkL1wcnJSdIydOhQSXufIr8Sgy4UiUQiiWy2traSpV8MBuPo6FhfX68xfdDixZGhq2slcRzpjqgQFaipqSkuLg4JCZH/j9a6FkhQ5ibE4/H29vaSDk5OTuhapsaElEEHRZIgcz1lnn5MJrO9vR3VYhRTU1NTU1OtaDS0qbIkJCSYm5vLvwIDAJhMJgBA2o9kYGBAIBDQdk0iEokqKiooFApq+AUCAYfDkYlaMjU1RRCExWJpRiTduTjylJaWYrFYW1tb9KsuiwpRjEAgePz4sa+vL4VCkf9J61qgAPmb0NjYGIt9/QRGb8jW1lbtyKeTInVFaWkpAEBi/lEJZTz8ZDJZKxoNbeobUKnUqqqqyZMnd/orn88HAMg46IlEItquSZ4+fdrW1hYYGKhYMACAxDnc1+jOxZGhtLS0tLTUx8dHsuqms6JCuuXFixd4PN7X11f+J13Qgq7o9CbUNVF1UKROYTKZL168GDJkiIuLC9qiUxo9eON+mUxmR0cH+plEIpmZmfF4vISEhLFjx3a6TQV05s8BACAIovZtGA0NDRIfkbGxscx+gPT09Pz8/AkTJkh7aToVDHQhc1+gsYvTI2prax89ejR06FB/f39Jo26KCpFBXgvQyJT58+dLz6UUoxktkH+YSP/a6U0oj4YVVhl0UCQ2m33//n09Pb3w8HAZwXQkz+7gtanJyclUKhX97ODgMHv27JcvXwIArK2t0fUD1J/Q1tZGo9HQ7VDoOg2Xy5W8bAIA+Hy+/AbWXvLgwQMul4t+njBhgo+Pj+SnrKys5ORkPz8/6UZUAJnXSfSrnp6eemXrCo1dHOWh0WhRUVG2trbTpk2TVj8dFBUij7wWJCYm2tnZicViVENRj25TU5NYLLa2ttaiFsg/TCQ/dXUT6unpSf46aVG1eBPqoEgycDicu3fvisXiefPmSce7dPVfr7GnnzSD16aGhIRICm6g0e1sNrujo+POnTvS3XJzc3NzcxcvXmxhYYEu4TAYDMmzuK2tTSgUyi/t9JJly5ZJ3rmkdy5nZ2c/e/bMx8dn3Lhx0v3xeLyxsTGDwZBuZDAYWCxWY3suNXZxlKS+vv7+/ftWVlYzZsyQ2WCna6JCOkVeC9hsdnNzs0zgyePHj4lE4gcffKBFLZB/mKAovgmLi4uFQiEej5eICv67ObWCDookTUdHx927dwUCwbx58yRbaFAkGi3dyGAwtCL54LWp8i9fQUFBEyZMkHxlMBhRUVE+Pj4jR45E/wsdHBwwGAyVSpU4XdFgbrXvLJbO5CAhNzc3KSnJy8tLWkgJjo6OBQUF7e3tqKNYKBRWVVXZ29trbL+2xi6OMjQ0NERGRlpYWMyYMUPygJCgU6JCukJeCxYuXCjt3ysqKkpLS4uIiJCk+9GWFnQ6k1N8Ezo6OhYWFlZUVLi6uqItVCqVSCRK74bXMDookgR0tsPj8ebOnSv/hmRsbEyhUKhUqr+/P+oMoNPpbW1to0aN0ryog9emyiOzeQaNv9fT05MsrxoYGIwcOTI/P9/c3Hzo0KENDQ2pqan29vbSuVH6iLKyssTERDKZTKFQCgoKJO3Ozs6of8PLy6uoqCgmJiY4OBiHwyUnJ3O53E5DOfoILV4cGVgsVmRkJIIgLi4uaHwgipWVFfrw1R1RIT1C5mGK3vlGRkaSdq1rgYRub0JnZ2cKhZKUlEQikSgUSlFRUWVl5fjx47WYtEgHRZJw9+5dBoPh5eVFo9Eke3uMjIwk+Sj8/PxiY2MTEhJ8fHw6Ojri4+P19fW1ksUF1k/tkqampmvXrsnkJhQKhY8fPy4pKUG/2tvbh4eHa8Brn5KSkpaWJt8unZiturr60aNHHA4HAEAkEoOCgtzd3ftaMGm0dXFkqKmpuXfvnny79H+ljogK6Q3Z2dlJSUkyuQm1rgUoytyELBbr4cOHaP5CLBY7evTogIAA7QYE6aBIAACxWPz777/Ltzs5Oc2cOVPyNSMjIzU1VSgUAgDIZHJ4eLj0jaExoE1VBQ6Hg+Zel3Hrax2xWNzS0oIgiJmZmbbeLnX24sjTj0SFKI8uaIHyMJlMHo9HJpN155VOB0VSEoFAwGAw8Hi8TOi1JoE2FQKBQCAQ9QBzPkAgEAgEoh6gTYVAIBAIRD1AmwqBQCAQiHqANhUCgUAgEPUAbSoEAoFAIOoB2lQIBAKBQNQDtKkDiqdPn+7Zs0flCszXr18/ceKEasfW1dXV1tbKNAoEgsrKypaWFgUHxsXF/fXXX6qdVCAQHD58WDqxFASim+zfv//hw4eqHdvU1LRnz57c3NyeHkin0ysrKyXlfSRwOJzKysq2trauDoRaqTLQpg4oKioq4uLi0EwiKpCbm/v8+XPVjo2JiVm2bBla20fC77//vmrVqrq6uq6Oam1tPXbsmOKidQpAiwV9//33cJs1RMd59OiRJG9XT2Gz2XFxcQ0NDT09MD8/f+XKldevX5dp37179/r162Wq0EiAWtkboE2FqIeVK1e6u7sfPnyYzWajLTk5OdeuXVuyZMno0aO7Oury5cuGhoZTpkxR+bwrVqwoKip6+vSpyiNAIAOVyZMnh4WFnTp1qrq6WtIYGRmZnJy8YcOGrlL3Qa3sDdCm9iECgYBOp/P5fIFAkJ6e/vTpU3kvKJfLzc3NTUhIyMzMlKn/x+Fw6HQ6giBsNjslJUUyBRSLxSUlJU+fPk1OTmYymZ2euq2t7fnz5ykpKZ2+itbV1aGHK3D+oLS0tGRkZCQkJBQVFcl7kKTB4XA7duxobm5Gvcc8Hu/AgQP29vZr167t6hCBQHDv3r3p06dLSkxLrphQKMzIyHj27BlaxRYAwOfz09LS0tLSJDYbxdLS0sfH59atW4r/EAhEGjqdjt5IRUVFiYmJlZWV8n1qamqSk5OfPn0qU11OcpeKRKKsrKyEhAQ+n6/4EGkUnJHFYqGHS9LEd4WC54YMGzduNDIy+vbbb1H9bWxsPHHiRGBg4PTp0zvtD7Wyl8C6NH1IcXHx+vXrP/7445s3b7a0tAgEAjwe/8UXX8ydOxftcPXq1d9++00gEKDVgMlk8q5du8aPH4/+evPmzd9//3337t1Hjx7t6OiwsbG5du1aTk7Otm3bWCwWegiBQFi9evU777wjfd7Hjx8fP34cAMDlcs3MzA4cOCCpecTn8w8dOhQTE4PH40UiEYFA+PDDD5csWdKp/Lt27Xry5AkGg8Hj8Xw+38XF5dChQ7a2tl39vS4uLu++++6ff/4ZEhLy4sWLurq6X375hUgkdtU/NTW1tbV14sSJMlfss88+u3nzJo1GE4vF+vr6hw8f1tPT27ZtG5PJFIvFFhYWx44dc3FxkRwVEBBw4sQJJpNpamqq+H8EAkFZunTprFmzqqqqMjMzcTicQCCYOXPm1q1bUUPC5XJXrVpFo9GIRKJQKBSLxZMnT/7666/RMq7SdykaQ3Dt2jVTU1MFh6Bwudwvvvii0zMCAC5dunT69GmhUIjD4YRCYURExJYtW6QPl6D4uSGDiYnJli1btm7deunSpRUrVhw+fBiPx//vf//r6spArewtCKTPyM3NDQwMnDp16u3bt4VCIYvF2r59e3BwcF5eHtrhyZMnaWlpXC4XQRAajfb5559Pnz69ra0N/fX8+fOBgYELFy5MSkricDj19fUIghQXFz98+BDt097e/uOPPwYGBqalpUkfMn/+/MzMTARBKioqVqxYMWfOnPb2drTD8ePHg4ODr127xufzWSzW3r17AwMDnzx5gv769ddfL1++XCL/zZs3y8rK0AdETk7O/PnzP/nkE8V/slAoXL169axZs4KCgn755RfFnX/55ZeQkBA+ny9zxaZPn/7vv//y+fy6urply5YtWbJk5cqVz549EwgEZWVls2fP3rx5s/x1jo+PV3w6CERCaGhoaGjowYMHORwOn8+/cOFCYGDgxYsX0V87OjouXbrU2NgoFouFQmFUVNTkyZP/+OMP9Ff0fgsLC7ty5QqTyWxububxeIoP6faM8fHxgYGB33zzTVtbG4/Hu3LlSlBQ0I8//oj+WlFRERgYGBsbi35V/NzolG+//TY0NBSdocbFxSnoCbWyl0Dfb58zYcKEuXPn4nA4Y2Pj7du36+vrX7t2Df0pODjY19cXLWhsY2OzefNmNpstE+azevXqgIAAfX19tLqnm5tbeHg4WnLZ0NDws88+s7CwePz4sfQhK1as8PLyAgA4OTlt3ry5paUlLi4OAMBms+/duxccHLxo0SICgWBsbLxt2zYzM7NLly51Kvn8+fNdXFxwOBwGgxk9evS7776blZXVlbcZBYfDvfvuu62trRQKZc2aNYqvTFVVlZmZmfybeERExLRp0wgEgq2t7bx58+rq6mbMmDFx4kQ8Hu/i4jJt2rT09HREKvwBnTp36kyDQLrC2Nh48+bN+vr6BAJhxYoV3t7eV69eRX/S09NbtmyZpaUlBoPB4XAREREhISEyWjZ58uQlS5aQyWQzMzMikajMIQrOePnyZQsLi61btxoZGRGJxCVLlkyaNOn27dto0ToZlHluyPDFF19QKJTLly9PmTJF8UIp1MpeAn2/fY6/v7/ks6Gh4ahRoyRR5mKx+NGjR8+fP29qahIIBOgd2djYKH24fEXl7OzsmJiY2tpaHo+HIAibzZY5RPqMPj4+RCKxoKBgzpw5paWlAoEgICBA8iuRSPTz80PfJeWrJHI4nLt37+bm5qLuHXTxtbGxUYEzRyQSnTt3DofDtbS0pKenT5gwQcGVaW1t7bTImqenp+Qz+iYhHeVkbW0tEAhYLJakVjxaklqyxgOBKIOPj4+05Rg3blxmZiadTkcjd+rq6iIjI0tLSzkcjlgsrq+vl1kylFfMbg/p6ozm5uaFhYWoxZL8GhAQ8PTp09LS0jFjxsicSJnnhgyGhoZz5849ffr08uXLFV8WqJW9BNrUPkfGApmamhYVFaGfDx48GBsbO3Xq1AkTJujr6wuFwtzcXJndpTKHP3jw4ODBg2PHjvXx8TE2NsZgMHQ6XeYQyW0t+dre3g4AQDVcXh6hUMjj8WRqJXK53HXr1jGZzPDwcC8vLwKBUF5eXlFRoXjz6/nz54uLiw8ePHjmzJkjR46cP3/e0NCwq84kEonFYsm36+vrSz6j9S/lW0QikaQFjdFAX9shECWRUQQKhQIAaG9vt7S0pFKp69evt7a2DgoKMjc3x+FwaDSQgsNVOERyRiMjI5FIJK+Y4D+dlUGZ54Y86MKtZPm2K6BW9hJoU/scmVjflpYW1ObR6fTo6Oh169ZJIoxqamp+/PFHxaOdP39+3Lhxx44dk7ScO3dOpg+DwZCYVbFYzGQy0a/om2Nzc7N05+bmZiKRKH/ro6GJJ0+elLyNRkZGKpaNSqWeO3duxowZgYGBNjY2a9euPXHixNatW7vqb25uXlpaqnhMZUDfhbVYhRjSH5FXTPDf++j169eJROKpU6ckZiMnJ0fxaMoc0tUZ9fT0CASCvGKC/3RWGtWeG8oDtbKXwPXUPkd6kxaTyczJyUG9KKgr1dHRUfJrYmJit6OxWCwHBwfJ14KCAjqdruCML168EAgE6BldXV319PQSEhIkv6K7dDw9PeUdv+i7qrR40gfKIxKJvv32WzKZ/Pnnn6PnWrlyZWRkpIJlHg8Pj9bW1qamJgXDKgP6CJDENkMgyoCG+Ui+JiYmDhkyBLUBLBbL3NxcYh07OjpSU1MVj6bMIV2dEYPBeHp6JicnS++KiY+P19fXd3V1lRlEteeG8kCt7CXQpvY5OTk5f/75J51Op1KpO3fuFIlE6N4Ve3t7Q0PDS5cuodn77t27d+XKlW5HGzFiRGxsbEZGBovFSklJ2bNnj4GBgUyfa9euxcTEMBiMly9ffvfdd7a2tiEhIQAAPT29xYsXP3/+/Pfff6fRaKWlpTt27GCz2TJbcSQnAgD89ttvzc3NdXV1P//8c3Z2tgLBUK/vli1b0PgpAMCqVatcXFyOHDnSaZwFAGDcuHEAABUyrsmQnZ1tYmIyfPjwXo4DGVQIBII9e/ZUVlbW19f/8MMPhYWFkrXGESNGlJeX3717l8VilZSUfPXVV4r3gCp5iIIzrlixorW1ddeuXVQqlUaj/fzzz+np6UuXLpV3IKn23FAeqJW9BPp++5yPPvro7t27aPJMQ0PDPXv2oLu4iETijh07Dh48uHLlSgCApaXlzp07N27cqHi0L7744quvvkLngiQS6ZNPPomOjpbp87///e/QoUOo78XBweHAgQMSzVyzZg2Px7t8+fKFCxcAAGQyeefOnX5+fvInGjVq1HvvvXfu3Ll79+4BAEaPHv3ZZ58dOnSoU6lQr29ERIT0tjYCgfDVV199+OGHJ0+e3Lx5s/xRDg4OXl5esbGxqMlXDTReY8aMGeiKDgSiJDNnzmQwGKj2YbHYlStXSjaOL168OCsr6+jRo0ePHsVisREREW5ubjdu3FAwmjKHKDjjuHHjtm/ffuLEiXfffRcAgMfj33777dWrV8ufSLXnhvJArewtWtzHM+BBd2glJSUhCFJeXp6Xl9fR0SHTp6Ojo6ioqLS0VCQSKTmsUCgsLy/Pz8/ncDhd9eHz+YWFhSUlJZ0O297enpubW1xcjAYNKoDJZObl5dXU1CgpW09JTEwMDQ1tampSeYRnz56FhobW1dWpUSrIgAfdrIkgSENDQ05ODoPBkO9Do9Fyc3Obm5uVH1aZQxScUSAQFBcX5+bmSjaUd4UKzw3lgVrZG+A8VUMMHTq003Y9PT13d/ceDYXD4boaTQKBQFDgdUG39ChzLjKZLBNFrF4CAwM9PDzOnz+/YcMG1UY4e/bsggULFGR3gkAUYGVlZWVl1elPNjY2NjY2PRpNmUMUnBGPx7u5uSlzIhWeG8oDtbI3QJsK0TL79++XiXhUHqFQuGnTpm7fMCAQSI+AWqkyGGRQluPRDE1NTdHR0aGhoXZ2dtqWBQKBvObSpUvDhw+Xz9sAgfQSaFMhEAgEAlEPcC8NBAKBQCDqAdpUCAQCgUDUA7SpEAgEAoGoB2hTIRAIBAJRD9CmQiAQCASiHqBNhUAgEAhEPUCbCoFAIBCIeoA2FQKBQCAQ9QBtKgQCgUAg6gHaVAgEAoFA1MP/ATuujsrgdUn9AAAAAElFTkSuQmCC",
      "text/plain": [
       "<quantify_core.visualization.pyqt_plotmon.QtPlotObjForJupyter at 0x7d6b86f62850>"
      ]
     },
     "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 0x7d6b86f628b0>"
      ]
     },
     "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 137900762810448>"
      ]
     },
     "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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       "  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:                             20250320-201332-588-da07d0\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-36d965a1-cc7d-4a59-9868-c7f4c87fe6f5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-36d965a1-cc7d-4a59-9868-c7f4c87fe6f5' 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-30a3860e-bbd7-4e23-ba11-755bd4c5cae7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-30a3860e-bbd7-4e23-ba11-755bd4c5cae7' 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-b07f15b6-cd5e-43ef-be2f-37119070a9da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b07f15b6-cd5e-43ef-be2f-37119070a9da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7be5e0d2-d96a-4178-8a3e-b2a810ce8d42' class='xr-var-data-in' type='checkbox'><label for='data-7be5e0d2-d96a-4178-8a3e-b2a810ce8d42' 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-4d27568c-756b-496b-a97c-2ef02b347dc7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4d27568c-756b-496b-a97c-2ef02b347dc7' 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-f8ed84cb-7598-4ae9-8c76-9aaa1e0a4cae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8ed84cb-7598-4ae9-8c76-9aaa1e0a4cae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-950073a9-7754-4b59-ae32-582d5d747e6c' class='xr-var-data-in' type='checkbox'><label for='data-950073a9-7754-4b59-ae32-582d5d747e6c' 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-d046d1c2-c7f1-4a76-9b2f-40ff12da6ae1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d046d1c2-c7f1-4a76-9b2f-40ff12da6ae1' 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-351fe0b7-f920-49f1-95d4-bf99c8d29ec5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-351fe0b7-f920-49f1-95d4-bf99c8d29ec5' 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>20250320-201332-588-da07d0</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:                             20250320-201332-588-da07d0\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 0x7d6b86f62850>"
      ]
     },
     "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": "3.9.21"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}