{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "marked-capability",
   "metadata": {},
   "source": [
    "# Example with CopperMountain Model M5180 vector network analyzer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "placed-maldives",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logging hadn't been started.\n",
      "Activating auto-logging. Current session state plus future input saved.\n",
      "Filename       : C:\\Users\\G-GRE-GRE058050\\.qcodes\\logs\\command_history.log\n",
      "Mode           : append\n",
      "Output logging : True\n",
      "Raw input log  : False\n",
      "Timestamping   : True\n",
      "State          : active\n",
      "Qcodes Logfile : C:\\Users\\G-GRE-GRE058050\\.qcodes\\logs\\210330-113772-qcodes.log\n"
     ]
    }
   ],
   "source": [
    "import qcodes as qc\n",
    "from qcodes import Station, load_or_create_experiment, \\\n",
    "    initialise_database, Measurement\n",
    "from qcodes.dataset.plotting import plot_by_id\n",
    "from qcodes.utils.dataset.doNd import do1d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ready-suffering",
   "metadata": {},
   "outputs": [],
   "source": [
    "from qcodes_contrib_drivers.drivers.CopperMountain.M5180 import M5180"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "likely-steps",
   "metadata": {},
   "source": [
    "## Connecting to device"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "statewide-carroll",
   "metadata": {},
   "source": [
    "- Install connection software S2VN, download here: https://coppermountaintech.com/download-free-vna-software-and-documentation/\n",
    "- Run the software and go to System > Misc Setup > Network Remote Control Settings and turn on HiSLIP Server"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "first-bacon",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Connected to: CMT M5180 (serial:20107935, firmware:20.3.3/1) in 0.09s\n"
     ]
    }
   ],
   "source": [
    "vna = M5180(name='vna', address='TCPIP0::localhost::hislip0::INSTR')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "expected-chorus",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "vna:\n",
      "\tparameter               value\n",
      "--------------------------------------------------------------------------------\n",
      "IDN                      :\t{'vendor': 'CMT', 'model': 'M5180', 'serial': '201...\n",
      "averages                 :\t1 \n",
      "averages_enabled         :\tTrue \n",
      "averages_trigger_enabled :\tTrue \n",
      "center                   :\t1.0005e+09 (Hz)\n",
      "data_transfer_format     :\tASC \n",
      "if_bandwidth             :\t10000 (Hz)\n",
      "nb_traces                :\t4 \n",
      "npts                     :\t2001 \n",
      "output                   :\tTrue \n",
      "point_s11                :\tNot available (('dB', 'rad'))\n",
      "point_s12                :\tNot available (('dB', 'rad'))\n",
      "point_s21                :\tNot available (('dB', 'rad'))\n",
      "point_s22                :\tNot available (('dB', 'rad'))\n",
      "power                    :\t-20 (dBm)\n",
      "s11                      :\tNot available (('dB', 'rad'))\n",
      "s12                      :\tNot available (('dB', 'rad'))\n",
      "s21                      :\tNot available (('dB', 'rad'))\n",
      "s22                      :\tNot available (('dB', 'rad'))\n",
      "span                     :\t1.999e+09 (Hz)\n",
      "start                    :\t1e+06 (Hz)\n",
      "stop                     :\t2e+09 (Hz)\n",
      "timeout                  :\t1e+05 (s)\n",
      "trigger_source           :\tbus \n"
     ]
    }
   ],
   "source": [
    "# Let's look at all parameters\n",
    "vna.print_readable_snapshot(update=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "emerging-improvement",
   "metadata": {},
   "source": [
    "# Setup db and station for test measurerment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "rural-genealogy",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create an empty database based on the config file\n",
    "qc.initialise_or_create_database_at('./test_copper_mountain.db')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "recreational-fight",
   "metadata": {},
   "outputs": [],
   "source": [
    "exp = load_or_create_experiment(experiment_name='testing_coppermountain_driver',\n",
    "                          sample_name=\"band_pass_filter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "marine-dependence",
   "metadata": {},
   "outputs": [],
   "source": [
    "station = qc.Station(vna)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "boring-router",
   "metadata": {},
   "source": [
    "## Measure a trace"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "southeast-client",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Turn on the RF output\n",
    "vna.output('on')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "stretch-survey",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting experimental run with id: 2. \n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# define sweep parameters\n",
    "vna.power(-20)\n",
    "vna.start(1e6)\n",
    "vna.stop(2e9)\n",
    "vna.if_bandwidth(10e3)\n",
    "vna.npts(2001)\n",
    "vna.averages(1)\n",
    "# do measurement\n",
    "meas = Measurement()\n",
    "meas.register_parameter(vna.s12)\n",
    "with meas.run() as datasaver:\n",
    "    datasaver.add_result((vna.s12, vna.s12()))\n",
    "ax, cbax = plot_by_id(datasaver.run_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "exterior-moderator",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-0.0477012 , -0.09391321, -0.17265479, ..., -0.03038562,\n",
       "        -0.03399903, -0.0214076 ]),\n",
       " array([-0.01097229, -0.01708669, -0.01996385, ..., -3.17442979,\n",
       "        -3.17352842, -3.17585808]))"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Similarly, other S-paramters can be queried\n",
    "vna.s11()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "least-blond",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-64.03521817, -72.72068274, -74.92402692, ..., -77.23523101,\n",
       "        -77.87500527, -86.19919018]),\n",
       " array([ -1.46406748,  -3.23681928,  -2.86312445, ..., -47.37145838,\n",
       "        -48.20720528, -45.34542698]))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s12()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "interesting-patio",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([-77.09130151, -72.57583366, -74.71111513, ..., -69.62992638,\n",
       "        -86.6484703 , -72.85211098]),\n",
       " array([-1.80363488, -0.96240925, -0.83102692, ..., 32.98620611,\n",
       "        34.25529117, 36.06598604]))"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s21()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "australian-train",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0.00305115, -0.06177799, -0.15385378, ..., -0.02385243,\n",
       "        -0.02926526, -0.02279546]),\n",
       " array([-0.01547223, -0.02163175, -0.02391645, ..., -3.18152415,\n",
       "        -3.18361572, -3.18402174]))"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s22()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "future-airplane",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1.0000000e+06, 1.9995000e+06, 2.9990000e+06, ..., 1.9980010e+09,\n",
       "        1.9990005e+09, 2.0000000e+09]),\n",
       " array([-0.03160302, -0.10392121, -0.17598948, ..., -0.02083835,\n",
       "        -0.02544277, -0.02948864]),\n",
       " array([-0.01215209, -0.01844561, -0.01988006, ...,  3.11017192,\n",
       "         3.10721224,  3.10526495]),\n",
       " array([-68.03181706, -69.96986101, -84.366874  , ..., -70.94278538,\n",
       "        -79.11469549, -77.38634014]),\n",
       " array([ 2.24117547,  2.60915241,  0.78312326, ..., -2.20522653,\n",
       "        -2.38599278, -1.49447507]),\n",
       " array([-83.2538078 , -67.23946765, -73.17241871, ..., -75.89235284,\n",
       "        -80.80017483, -81.72715481]),\n",
       " array([ 3.1331486 ,  2.56154342, -0.36192594, ...,  0.23860211,\n",
       "        -1.37759455,  2.75163547]),\n",
       " array([ 0.00655536, -0.06872062, -0.14529468, ..., -0.02987041,\n",
       "        -0.01884765, -0.02839042]),\n",
       " array([-0.01384824, -0.02119365, -0.02357165, ...,  3.10193855,\n",
       "         3.10032872,  3.09917688]))"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# or all S-parameters at once. Attention this is not a qcodes parameter\n",
    "vna.get_s()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unnecessary-coordinate",
   "metadata": {},
   "source": [
    "# Look at the names and the labels of the Sxx parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "burning-tuition",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('vna s11 magnitude', 'vna s11 phase')"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s11.labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "plain-frederick",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('vna_s11_magnitude', 'vna_s11_phase')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s11.names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "circular-attack",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(('vna frequency',), ('vna frequency',))"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s11.setpoint_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "comparable-salem",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(('vna_frequency',), ('vna_frequency',))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vna.s11.setpoint_names"
   ]
  }
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