{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Qcodes example with Keysight N9030B"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook shows how to use Keysight N9030B instrument driver in Spectrum Analyzer and Phase Noise Modes for Swept SA and Log Plot measurements respectively.\n",
    "\n",
    "Let's begin!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-14T15:11:25.180448Z",
     "start_time": "2021-01-14T15:11:21.379687Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "from qcodes.dataset import (\n",
    "    Measurement,\n",
    "    initialise_or_create_database_at,\n",
    "    load_or_create_experiment,\n",
    "    plot_by_id,\n",
    "    plot_dataset,\n",
    ")\n",
    "from qcodes.instrument_drivers.Keysight import KeysightN9030B"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to: Keysight Technologies N9030B (serial:MY56320646, firmware:A.24.57) in 0.35s\n"
     ]
    }
   ],
   "source": [
    "driver = KeysightN9030B(\"n9030b\",\"driver_address\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'vendor': 'Keysight Technologies',\n",
       " 'model': 'N9030B',\n",
       " 'serial': 'MY56320646',\n",
       " 'firmware': 'A.24.57'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "driver.IDN()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Spectrum Analyzer mode with Swept SA measurement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sa = driver.sa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "sa.setup_swept_sa_sweep(start=200, stop= 10e3, npts=20001)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With QCoDeS Measurement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initialize database and begin experiment..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Upgrading database; v0 -> v1: : 0it [00:00, ?it/s]\n",
      "Upgrading database; v1 -> v2: 100%|█████████████████████████████████████████████████████| 1/1 [00:00<00:00, 334.71it/s]\n",
      "Upgrading database; v2 -> v3: : 0it [00:00, ?it/s]\n",
      "Upgrading database; v3 -> v4: : 0it [00:00, ?it/s]\n",
      "Upgrading database; v4 -> v5: 100%|█████████████████████████████████████████████████████| 1/1 [00:00<00:00, 167.42it/s]\n",
      "Upgrading database; v5 -> v6: : 0it [00:00, ?it/s]\n",
      "Upgrading database; v6 -> v7: 100%|██████████████████████████████████████████████████████| 1/1 [00:00<00:00, 91.64it/s]\n",
      "Upgrading database; v7 -> v8: 100%|█████████████████████████████████████████████████████| 1/1 [00:00<00:00, 202.59it/s]\n",
      "Upgrading database; v8 -> v9: 100%|█████████████████████████████████████████████████████| 1/1 [00:00<00:00, 202.59it/s]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "tutorial_exp#no sample#1@C:\\Users\\asic\\Documents\\tutorial.db\n",
       "------------------------------------------------------------"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tutorial_db_path = os.path.join(os.getcwd(), 'tutorial.db')\n",
    "initialise_or_create_database_at(tutorial_db_path)\n",
    "load_or_create_experiment(experiment_name='tutorial_exp', sample_name=\"no sample\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qcodes.dataset.measurements.Measurement at 0x25fc9145e48>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meas1 = Measurement()\n",
    "meas1.register_parameter(sa.trace)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting experimental run with id: 1. \n"
     ]
    }
   ],
   "source": [
    "with meas1.run() as datasaver:\n",
    "    datasaver.add_result((sa.trace, sa.trace.get()))\n",
    "\n",
    "dataset = datasaver.dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot_dataset(dataset)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Phase Noise mode with Log Plot measurement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "pn = driver.pn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "pn.setup_log_plot_sweep(start_offset=10, stop_offset=200, npts=1001)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### With QCoDeS Measurement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<qcodes.dataset.measurements.Measurement at 0x25fca246c08>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meas2 = Measurement()\n",
    "meas2.register_parameter(pn.trace)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting experimental run with id: 2. \n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[n9030b_pn(PhaseNoiseMode)] Carrier(s) Incorrect or Missing!\n"
     ]
    }
   ],
   "source": [
    "with meas2.run() as datasaver:\n",
    "    datasaver.add_result((pn.trace, pn.trace.get()))\n",
    "\n",
    "run_id = datasaver.run_id"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Plot data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYwAAAEWCAYAAAB1xKBvAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAfCElEQVR4nO3debwcVZ338c/XRAiShCgJS0jCBQIijBDilUVReAAZibI8wIg8simCIooIOC6oRMcZHgR0dEQEQQEHMMAIRMERZNhcAiQhIDsRgmQjF0jCKkL4zR91blJpum+fkFR3k/t9v179ulV1TlX9+nTd+vWpqq5SRGBmZtbMm9odgJmZvTE4YZiZWRYnDDMzy+KEYWZmWZwwzMwsixOGmZllccKwNxRJYyQ9J2lAu2PpFKk9Ns2o1yUpJA1sRVw5JF0qab92x1EFSUdI+n1m3TMlHVN1TCvLCaMikmZJejH9M8+XdIGkwS1Y7xxJa0naTdIvS9PXS/+ccyUtlvQHSTuswHJvkvS39H56X7+q5l00FhF/jYjBEbGk1etOO9uxfZRn7yByl5kjtccjK7OMdpC0DbAtcHW7Y+kAZwBflbRGuwPpixNGtfaOiMHAOGA74CtVrkzSaOCpiHgReBcwvVQ8GLgjTX8bcCFwzQomsc+mnVPva+9VFXuOTvpm3AlWg/b4FHBx+NfDRMQ84AFgn3bH0hcnjBaIiPnAbykSB5J2lTS7XCf1SPZIwxMlXSbpIknPSrpXUnfGqrqBaaXhpQkjIh6JiO9GxLyIWBIR5wJrAG9f2fcn6UuSbuvdgUk6JsU8qHQY5OjUu5kn6aTSvG+S9GVJf5H0VHrfb0tlvfMeKemvwP/UHlZJPZ9vS/pjb69H0rqSLpb0jKQ7JHWV1relpOslPS3pQUkfKZVdIOksSdekdr9N0map7JZU7a60noNq2uAdwI+BnVL5olJ8nyzVW9oLabRMSUdJmplinCxpZGn+kHSspIeBh0vTxqbhD0m6M733xyVNfB2f5zqSzk+f1ZzUvgMkrSFphqTPpXoDUk/1G2l8oqQrJE1K7Tdd0rZ9rGov4ObatpF0hqSFkh6VtFepfGRqj6dT+xzVx3uYIOm+FMec3m1O0lsl/VpST1rHryWNKs23ottTSDpO0iOSnpR0uqS6+9W+tr3kJuBDfbRX+0WEXxW8gFnAHml4FPBn4PtpfFdgdh/1JwJ/AyYAA4BTgSl9rOsUYFGa54U0vARYnIYH1JlnXKq/Tub7uQn4ZIOyNwG3pLg3BxYC26WyLiCAS4G1gXcCPaX3+nlgSmqjNYFzgEtr5r0ozbtWadrAUlwzgc2AdYD7gIeAPYCBad6fpbprA48DH09l2wFPAlul8guAp4DtU/nFwC9K7zOAsX200RHA7/tqt9o6tcsEdksxjU/t8R/ALTX1r6foJa5VuwyKbeud6TPZBngC2K+mPQc2+ayvTJ/D2sB6wO3Ap1LZP6TP9x3AyemzG1Dabl8GDgTeDJwEPAq8uc461k6xjKhpm5eBoyi2+2OAuYBS+S3Aj4BBFNtvD7Bbg/cwD3hfGn4rMD4NrwscALwFGAJcDlxV83llbU+ltr8xfR5jUt1P1n7WNNn2Up39gent3nf1uW20O4DV9UWRAJ4Dnk0b1Q3AsFS2K80Txu9KZVsBLzZZ30DgfmB94D3ANX3UHUqRwL6yAu/nJpYlo97Xv5TKu4CnUwxfqZkewJalad8Bzk/D9wO7l8o2TDuNgaV5N62zvHLCOLlUfibwm9L43sCMNHwQcGvN+zoHOCUNXwCcVyqbADxQGm9Fwjgf+E5pfHBqj65S/d1q1tEwLuDfge/Va7sG9dcHXiIlozTtYODG0viJwIMUiWPz0vSJlL7YUCStpTvumvVslGIZVNM2M0vjb0l1NgBGU3wJGlIqPxW4oMH7+CvFIa+hTbbrccDCms8ra3sqtf0HS+OfAW6o/aybbXtp/APAI7n/k+14+ZBUtfaLiCEUCWJLYPgKzDu/NPwCMEh1jllLGpcOfywExlL8I98I7CppkaT9a+qvBfyK4h/71BWIB+C4iBhWen29tyAiZqX1dgFn1Zn38dLwY0DvYZaNgStTrIsoEsgSih1XvXnreaI0/GKd8d7zNBsDO/SuK63vYxQ7pF617V75hQo1RlK0DwAR8RxFr2ejUp2G7SFpB0k3pkMui4FPs2Lb3cYUvYN5pTY6h6Kn0evCVO/aiHi4Zv6lsUXEq8Bsln3WZYvS3yE105e2f0S8kAYHp2U8HRHPluo+xvLtUnYARcJ/TNLNknYCkPQWSedIekzSMxS9lmFa/qq73O2pV6Ntuyxn2xvCsnbpSE4YLRARN1N8ez0jTXqe4tsTUBwLBka8zmXPiIhhwL8C30jD9wHbpp16+UqpNYGrKP6JP/V61teIpA8BO1H0pE6vU2V0aXgMxaEGKP7Z9qpJRIMiYk6pfqyiMB8Hbq5Z1+CIWFWXM9aLc7nPmuV3EPXMpdi5ACBpbYrDKLntcQkwGRgdEetQnFdRk3WWPU7RwxheaqOhEbF1qc6PgF8D/yhp55r5l37O6Vj+KJZ91sveQMTzwF+ALTLjmgu8TVI5wYxh+XYpL/+OiNiXItFdBVyWik6kOG+3Q0QMBd7fG25mHPU02rbLcra9dwB3rUQclXPCaJ1/Bz6QTgI+RNFj+JCkNwNfozhevTLeBUxXcVneyIiYWS5M67mC4hvS4enbX7m892Ry14quWNJw4Dzgk8DhwN6SJtRU+3r6drc1xXHcSWn6j4F/lbRxWtYISfuuaAyZfg1sIelQSW9Or3erOGGd4wmgr987PAGM0vKXRs4A9k/vfSxwZJNlXgp8PPUc1wT+Dbgt9eByDKH4Jv43SdsD/y9zPmDp1TrXAWdKGqriooTNJO0CIOlQim3tCOA44EItf6XduyTtn3rDx1MknykNVnctsEtmXI8DfwROVXExxTYUbfmftXVVnJz/mKR1IuJl4Bmgd3sfQvE/sEjFxRWn5Ky/iS+mk+mjKc7JTapTJ2fb2wX4zSqIpzJOGC0SET0UJ8y+ERGLKY51nkfxDel5im/9K6P3Mtp3AvfUKX8P8GFgT4p/lt7fUrwvlY+m6E7X/caW/FDL/w6j94qsc4GrI+LaiHiK4h/5PEnrlua9meJk4g3AGRFxXZr+fYpvxNdJepZi55L9+5AVkQ5n7Al8lOJb4HzgNPKT9USKHeSiOle4APwPcC8wX9KTadr3gL9TJIYLKU6kN1xmRPwO+DrwXxTH/zdL8eb6DPCt1JbfYNk36xVxGMUVdPdRHOq8AthQ0hiKLz6HRcRzEXEJMDW9x15XUxyvXwgcCuyfdtr1nAt8TFLut/uDKQ55zqU4MX9Kaq96DgVmpcNOn6Y4/EOKfy2KE85TgP/OXHdfrqa4OnEGcA3FeajlNNv2JG1Ica7yqlUQT2V6rz6wfk7S14CeiDhnFS+3i2VXyryyKpdtnUXFJbxjI+KQFZjnEuCyiLiqqriqJCkoTvzPbFq57+WcCfwlIn60aiKrxhv9hz+2ikTEt9sdg/U/EbFCh8xWVxFxYrtjyOGEYdYPSXquQdFeEXFrS4OxNwwfkjIzsyw+6W1mZllW20NSw4cPj66urnaHYWb2hjJt2rQnI6Lu78JW24TR1dXF1KlT2x2GmdkbiqTHGpX5kJSZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVpScJQ4QeSZkq6W9L4BvUOSuX3Sjqtpuwjku5LZZe0Im4zM1umVT2MvYDN0+to4OzaCpLWBU4Hdo+IrYENJO2eyjYHvgK8N5Ud36K4zcwsaVXC2Be4KApTgGGSNqypsynwcET0pPHfAQek4aOAsyJiIUBELGhF0GZmtkyrEsZGwOOl8dlpWtlM4O2SuiQNBPYDRqeyLYAtJP1B0hRJH6y3EklHS5oqaWpPT0+9KmZm9jp1zEnv1Hs4BpgE3ArMApak4oEUh7N2BQ4GfiJpWJ1lnBsR3RHRPWLEiBZEbWbWf1SWMCQdK2mGpBnAPJb1FgBGAXNq54mIX0XEDhGxE/Ag8FAqmg1MjoiXI+LRNH3zqmI3M7PXqixhRMRZETEuIsYBVwGHpauldgQWR8S82nkkrZf+vhX4DHBeKrqKoneBpOEUh6geqSp2MzN7rYEtWs+1wASK8xQvAB/vLZA0IyUVgO9L2jYNfysiensYvwX2lHQfxWGqL0bEUy2J3MzMAFBEtDuGSnR3d8fUqVPbHYaZ2RuKpGkR0V2vrGNOepuZWWdzwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL0pKEocIPJM2UdLek8Q3qHZTK75V0Wmn6GEk3SrozlU9oRdxmZrZMq3oYewGbp9fRwNm1FSStC5wO7B4RWwMbSNo9FX8NuCwitgM+CvyoJVGbmdlSrUoY+wIXRWEKMEzShjV1NgUejoieNP474IA0HMDQNLwOMLfqgM3MbHkDW7SejYDHS+Oz07R5pWkzgbdL6krl+wFrpLKJwHWSPgesDexRbbhmZlarY056R8RC4BhgEnArMAtYkooPBi6IiFHABODnkl4Tu6SjJU2VNLWnp6e22MzMVkJlCUPSsZJmSJpB0ZMYXSoeBcypnScifhURO0TETsCDwEOp6EjgslTnT8AgYHid+c+NiO6I6B4xYsQqfT9mZv1dZQkjIs6KiHERMQ64CjgsXS21I7A4IubVziNpvfT3rcBngPNS0V+B3VPZOygShrsQZmYt1KpzGNdSHEqaCbwAfLy3QNKMlFQAvi9p2zT8rYjo7WGcCPxE0hcoToAfERHRksjNzAxoUcJIO/djG5SNKw0f3KDOfcB7KwnOzMyydMxJbzMz62xOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjS9l5SkQcCHgfcBI4EXgXuAayLi3mrDMzOzTtFnwpD0TYpkcRNwG7CA4tbiWwD/PyWTEyPi7orjNDOzNmvWw7g9Ik5pUPbd9PyKMas4JjMz60B9JoyIuKZJ+QKKXoeZma3m+jzpLWm4pFMkHSdpsKSzJd0j6WpJY1sVpJmZtV+zq6QuAdYENgduBx4BDgR+zbLHp5qZWT/Q7BzG+hHxVUkCHouI09P0ByTVfYKemZmtnpr1MJbA0kesPllT9molEZmZWUdq1sPYVNJkQKVh0vgmlUZmZmYdpVnC2Lc0fEZNWe24mZmtxppdVntzqwIxM7PO1uyX3n8GolF5RGyzyiMyM7OO1OyQ1IfT394ron6e/h5CH4nEzMxWP80OST0GIOkDEbFdqehLkqYDX64yODMz6xy5tzeXpPeWRt6zAvOamdlqoOntzZMjgZ9KWieNLwI+UUlEZmbWkbISRkRMA7btTRgRsbjSqMzMrOM0u/ngIZKW1omIxeVkIWkzSTtXGaCZmXWGZj2MdYE7JU0DpgE9FA9QGgvsQnG7EJ/4NjPrB5pdJfV9ST8EdgPeC2xD8YjW+4FDI+Kv1YdoZmadoOk5jIhYAlyfXm0haUvgZ8B44OSI8G1JzMxaLPcqqXZ7GjgO2K/NcZiZ9VtviITR+yhYSR+qel3f/NW93Df3mapXY2ZWma1GDuWUvbde5ctdrX58J+loSVMlTe3p6Wl3OGZmq5WsHoak9YF/A0ZGxF6StgJ2iojzK41uBUXEucC5AN3d3a/rXldVZGUzs9VBbg/jAuC3wMg0/hBwfAXxLCXpWEkz0mtk8znMzKxKuQljeERcRnosa0S8Qnp8a1Ui4qyIGJdec6tcl5mZNZd70vt5SeuSbmkuaUegZbcHkbQBMBUYCrwq6Xhgq4jw2WkzsxbJTRgnAJOBzST9ARgBHFhZVDUiYj4wqlXrMzOz18q9+eB0SbsAbwcEPBgRL1camZmZdZSscxiSjgUGR8S9EXEPMFjSZ6oNzczMOknuSe+jImJR70hELASOqiQiMzPrSLkJY4Ak9Y5IGgCsUU1IZmbWiXJPev83MEnSOWn8U2mamZn1E7kJ40sUSeKYNH49cF4lEZmZWUfKvUrqVeDs9DIzs34o915SmwOnAltRPHEPgIjYtKK4zMysw+Se9P4ZRe/iFeD/ABcB/1lVUGZm1nlyE8ZaEXEDoIh4LCImApU/m8LMzDpH7knvlyS9CXhY0meBOcDg6sIyM7NOk9vD+DzwForHpL4LOAQ4vKqgzMys8zTtYaQf6R0UEScBzwEfrzwqMzPrOH32MCQNjIglwM4tisfMzDpUsx7G7cB44E5Jk4HLged7CyPilxXGZmZmHST3pPcg4ClgN4qHKCn9dcIwM+snmiWM9SSdANzDskTRKyqLyszMOk6zhDGA4vJZ1SlzwjAz60eaJYx5EfGtlkRiZmYdrdnvMOr1LMzMrB9qljB2b0kUZmbW8fpMGBHxdKsCMTOzzpZ7axAzM+vnnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL0pKEIWlLSX+S9JKkk/qot4mk2yTNlDRJ0hpp+gmS7pN0t6QbJG3cirjNzGyZVvUwnqZ4HvgZTeqdBnwvIsYCC4Ej0/Q7ge6I2Aa4AvhOVYGamVl9LUkYEbEgIu4AXm5UR5IoHtB0RZp0IbBfmv/GiHghTZ8CjKouWjMzq6eTzmGsCyyKiFfS+Gxgozr1jgR+07KozMwMyH9Ea0eQdAjQDezSoPxo4GiAMWPGtDAyM7PVX2U9DEnHSpqRXiMzZnkKGCapN4mNAuaUlrcHcDKwT0S8VG8BEXFuRHRHRPeIESNW9i2YmVlJZQkjIs6KiHHpNTejfgA3AgemSYcDVwNI2g44hyJZLKgqZjMza6xVl9VuIGk2cALwNUmzJQ1NZdeWeiBfAk6QNJPinMb5afrpFM8Wvzz1WCa3Im4zM1umJecwImI+Da5siogJpeFHgO3r1NmjuujMzCxHJ10lZWZmHcwJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVpScKQtKWkP0l6SdJJfdTbRNJtkmZKmiRpjZryAySFpO7qozYzs7JW9TCeBo4DzmhS7zTgexExFlgIHNlbIGkI8HngtqqCNDOzxlqSMCJiQUTcAbzcqI4kAbsBV6RJFwL7lar8C0VC+VtFYZqZWR866RzGusCiiHgljc8GNgKQNB4YHRHX9LUASUdLmippak9PT7XRmpn1M52UMOqS9Cbgu8CJzepGxLkR0R0R3SNGjKg+ODOzfqSyhCHpWEkz0mtkxixPAcMkDUzjo4A5wBDgH4CbJM0CdgQm+8S3mVlrVZYwIuKsiBiXXnMz6gdwI3BgmnQ4cHVELI6I4RHRFRFdwBRgn4iYWlXsZmb2Wq26rHYDSbOBE4CvSZotaWgqu7bUA/kScIKkmRTnNM5vRXxmZtbcwOZVVl5EzKc4xFSvbEJp+BFg+ybL2nWVBmdmZlk6/qS3mZl1BicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDDMzCyLE4aZmWVxwjAzsyxOGGZmlsUJw8zMsigi2h1DJST1AI+1O44GhgNPtjuIPji+ldPp8UHnx+j4Vs7KxLdxRIyoV7DaJoxOJmlqRHS3O45GHN/K6fT4oPNjdHwrp6r4fEjKzMyyOGGYmVkWJ4z2OLfdATTh+FZOp8cHnR+j41s5lcTncxhmZpbFPQwzM8vihGFmZlmcMComabSkGyXdJ+leSZ9P0ydKmiNpRnpNaGOMsyT9OcUxNU17m6TrJT2c/r61TbG9vdRGMyQ9I+n4drafpJ9KWiDpntK0uu2lwg8kzZR0t6TxbYrvdEkPpBiulDQsTe+S9GKpHX/cpvgafp6SvpLa70FJ/9im+CaVYpslaUaa3o72a7RPqX4bjAi/KnwBGwLj0/AQ4CFgK2AicFK740txzQKG10z7DvDlNPxl4LQOiHMAMB/YuJ3tB7wfGA/c06y9gAnAbwABOwK3tSm+PYGBafi0Unxd5XptbL+6n2f6X7kLWBPYBPgLMKDV8dWUnwl8o43t12ifUvk26B5GxSJiXkRMT8PPAvcDG7U3qiz7Ahem4QuB/doXylK7A3+JiLb+gj8ibgGerpncqL32BS6KwhRgmKQNWx1fRFwXEa+k0SnAqCpj6EuD9mtkX+AXEfFSRDwKzAS2ryw4+o5PkoCPAJdWGUNf+tinVL4NOmG0kKQuYDvgtjTps6mL+NN2HfJJArhO0jRJR6dp60fEvDQ8H1i/PaEt56Ms/4/aKe0HjdtrI+DxUr3ZtP8LwycovnH22kTSnZJulvS+dgVF/c+z09rvfcATEfFwaVrb2q9mn1L5NuiE0SKSBgP/BRwfEc8AZwObAeOAeRTd3HbZOSLGA3sBx0p6f7kwin5tW6+/lrQGsA9weZrUSe23nE5or0YknQy8AlycJs0DxkTEdsAJwCWShrYhtI79PGsczPJfWtrWfnX2KUtVtQ06YbSApDdTfLAXR8QvASLiiYhYEhGvAj+h4m52XyJiTvq7ALgyxfJEb7c1/V3QrviSvYDpEfEEdFb7JY3aaw4wulRvVJrWcpKOAD4MfCztUEiHep5Kw9MozhFs0erY+vg8O6n9BgL7A5N6p7Wr/ertU2jBNuiEUbF0zPN84P6I+G5pevkY4v8F7qmdtxUkrS1pSO8wxcnRe4DJwOGp2uHA1e2Ir2S5b3ad0n4ljdprMnBYulJlR2Bx6bBBy0j6IPDPwD4R8UJp+ghJA9LwpsDmwCNtiK/R5zkZ+KikNSVtkuK7vdXxJXsAD0TE7N4J7Wi/RvsUWrENtvLsfn98ATtTdA3vBmak1wTg58Cf0/TJwIZtim9TiqtQ7gLuBU5O09cFbgAeBn4HvK2Nbbg28BSwTmla29qPInHNA16mOB58ZKP2orgy5SyKb55/BrrbFN9MiuPYvdvgj1PdA9LnPgOYDuzdpvgafp7Ayan9HgT2akd8afoFwKdr6raj/RrtUyrfBn1rEDMzy+JDUmZmlsUJw8zMsjhhmJlZFicMMzPL4oRhZmZZnDBstSdpiZa/421Xu2NaVSRtJ+n8NHyEpB/WlN8kqbuP+X8hafOq47TVw8B2B2DWAi9GxLh6BelHUIriF8ZvRF8Fvr0S859N8YO+o1ZNOLY6cw/D+p30DIMHJV1E8Yvi0ZK+KOmOdPO7b5bqnizpIUm/l3SppJPS9KXf3CUNlzQrDQ9Q8eyJ3mV9Kk3fNc1zhYrnUlyckhWS3i3pj5LuknS7pCGSbpE0rhTH7yVtW/M+hgDbRMRdGe95n1IP60FJj6aiW4E90m0vzPrkjcT6g7WUHngDPAp8geIWDodHxBRJe6bx7Sl+FTs53YDxeYo75I6j+F+ZDkxrsq4jKW698G5JawJ/kHRdKtsO2BqYC/wBeK+k2ynuTXRQRNyRblz3IsWtH44Ajpe0BTCoTmLo5rW3RDlI0s6l8bEAETGZ4hfUSLoMuDlNf1XSTGDbjPdm/ZwThvUHyx2SSucwHovi2QBQ3D9rT+DOND6YIoEMAa6MdO8lSZMz1rUnsI2kA9P4OmlZfwduj3QfopTAuoDFwLyIuAMg0l1HJV0OfF3SFyluR35BnXVtCPTUTJsUEZ8tvdebyoWS/pmiPc4qTV4AjMQJw5pwwrD+6vnSsIBTI+KccgVJx/cx/yssO6Q7qGZZn4uI39Ysa1fgpdKkJfTx/xcRL0i6nuLhNx8B3lWn2os16+6TpD2Af6J4olzZoLQssz75HIYZ/Bb4RHq+AJI2krQecAuwn6S10vmCvUvzzGLZTvzAmmUdk24/jaQt0l2AG3kQ2FDSu1P9IaXzCecBPwDuiIiFdea9n3TIqRlJG1PcgO6fIqI2OWxB++/2a28A7mFYvxcR10l6B/CndB76OeCQiJguaRLFnXwXAHeUZjsDuEzFEwqvKU0/j+JQ0/R0UruHPh5vGxF/l3QQ8B+S1qL4pr8H8FxETJP0DPCzBvM+IGkdSUOieFRnX46guJvpVek9zo2ICZLWpzhENb/J/Ga+W61ZLkkTKXbkZ7RofSOBm4AtG132K+kLwLMRcd7rXMcXgGci4vzXHaj1Gz4kZdaBJB1G8Zzmk5v8RuRslj83sqIWAReuxPzWj7iHYWZmWdzDMDOzLE4YZmaWxQnDzMyyOGGYmVkWJwwzM8vyv2Mmhwecb5oJAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_ = plot_by_id(run_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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