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   "source": [
    "# How to use Plottr with QCoDeS for live plotting?\n",
    "\n",
    "Note: This notebook assumes that the user has a `conda` environment on their system with latest versions of `plottr` installed. It is not necessary to have plottr installed in measurements environment itself. Plottr can be in a separate environment as well. If you do not have plottr installed, please follow [Plottr Quickstart (Installation)](https://github.com/toolsforexperiments/plottr#quickstart) instructions.\n",
    "\n",
    "Let's begin!\n",
    "\n",
    "First, make necessary imports."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-07T12:38:25.294819Z",
     "start_time": "2020-12-07T12:38:21.906894Z"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "import qcodes as qc\n",
    "from qcodes.dataset import (\n",
    "    Measurement,\n",
    "    do1d,\n",
    "    initialise_or_create_database_at,\n",
    "    load_or_create_experiment,\n",
    ")\n",
    "from qcodes.instrument_drivers.mock_instruments import (\n",
    "    DummyInstrument,\n",
    "    DummyInstrumentWithMeasurement,\n",
    ")\n",
    "\n",
    "qc.logger.start_all_logging()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Mock Set-up\n",
    "\n",
    "For this notebook, we create a mock station setup. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-07T12:38:35.103026Z",
     "start_time": "2020-12-07T12:38:35.092493Z"
    }
   },
   "outputs": [],
   "source": [
    "dac = DummyInstrument('dac', gates=['ch1', 'ch2'])\n",
    "dmm = DummyInstrumentWithMeasurement(name='dmm', setter_instr=dac)\n",
    "\n",
    "station = qc.Station(dmm, dac)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize/Create Database\n",
    "\n",
    "Database needs to be initialized or created if it doesn't exist already, using `initialize_or_create_database` method. Furthermore, datasets are associated with experiments and by default the run is appended to the latest existing experiment. We can load or create an experiment using `load_or_create_experiment` function. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-07T12:38:48.235500Z",
     "start_time": "2020-12-07T12:38:48.166689Z"
    }
   },
   "outputs": [],
   "source": [
    "db_file_path = os.path.join(os.getcwd(), 'plottr_for_live_plotting_tutorial.db')\n",
    "initialise_or_create_database_at(db_file_path)\n",
    "exp = load_or_create_experiment(experiment_name='plottr_for_live_plotting_with_subsecond_refresh_rate',\n",
    "                          sample_name=\"no sample\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Launch Plottr Inspectr \n",
    "\n",
    "Open an anaconda prompt and activate your conda environment where plottr is installed. Start Inspectr GUI with `plottr-inspectr` command (more details for launching Inspectr are [here](https://github.com/toolsforexperiments/plottr#inspectr-qcodes-dataset-inspection-and-live-plotting). You will see a window as show below. In this window, set `Refresh interval (s)` to the desired value and check `Auto-plot new`. Using `File` button, load the database initialized/created above (Alternatively, database can be dragged and dropped on the Inspectr window).\n",
    "\n",
    "![Plottr-inspectr Window](../files/plottr.png)\n",
    "\n",
    "On selection, refresh interval and auto-plot new checkbox will look like as follows.\n",
    "\n",
    "![Refresh Interval and Autoplot](../files/plottr_set_refresh_interval_and_autoplot.png)\n",
    "\n",
    "### If plottr is installed in same environment as measurements environment\n",
    "\n",
    "Plottr-inspectr can also be launched with required DB as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-07T12:39:53.719816Z",
     "start_time": "2020-12-07T12:39:52.824390Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<BackgroundJob #0: <function main at 0x0000016A042E9C18>>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import IPython.lib.backgroundjobs as bg\n",
    "from plottr.apps import inspectr\n",
    "\n",
    "jobs = bg.BackgroundJobManager()\n",
    "jobs.new(inspectr.main, db_file_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set refresh interval and auto-plot new as mentioned above. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Measurement\n",
    "\n",
    "Measurements can be run in two ways.\n",
    "\n",
    "### Measurement with run context manager\n",
    "\n",
    "Notice `write_period = 0.1` . This sets the measurement write period to 0.1s and is recommended to be used with sub-second refresh interval for plottr."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-07T12:41:40.283199Z",
     "start_time": "2020-12-07T12:41:40.215924Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting experimental run with id: 3. \n"
     ]
    }
   ],
   "source": [
    "meas = Measurement(exp=exp)\n",
    "meas.register_parameter(dac.ch1)\n",
    "meas.register_parameter(dmm.v1, setpoints=(dac.ch1,))\n",
    "\n",
    "meas.write_period = 0.1\n",
    "\n",
    "with meas.run() as datasaver:\n",
    "\n",
    "    for set_v in np.linspace(0, 25, 100):\n",
    "        dac.ch1.set(set_v)\n",
    "        get_v = dmm.v1.get()\n",
    "        datasaver.add_result((dac.ch1, set_v),\n",
    "                             (dmm.v1, get_v))\n",
    "\n",
    "    dataset = datasaver.dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Measurement with doNd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-12-07T12:42:07.870434Z",
     "start_time": "2020-12-07T12:42:06.117442Z"
    }
   },
   "outputs": [],
   "source": [
    "do1d(dac.ch1, 0, 25, 100, 0.01, dmm.v1, dmm.v2, write_period=0.1, do_plot=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "On starting these measurements, a plottr plot window (as shown below) will open automatically. This plot will keep refreshing at the interval rate set by you till the measurement runs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Live Plot\n",
    "\n",
    "![Live Plot](../files/live_plot.gif)\n",
    "\n",
    "For more details about Plottr, head to [Plottr Documentation](https://plottr.readthedocs.io/en/latest/index.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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