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   "source": [
    "(howto-measurement-control)=\n",
    "# Measurement Control"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b2e8468-e728-4b11-80b4-1c28996f6e28",
   "metadata": {},
   "source": [
    "We first prepare some utilities necessarily for the examples."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "65323c9f-9091-4072-a131-0a4d53378325",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "from qcodes import ManualParameter, Parameter\n",
    "\n",
    "import quantify_core.data.handling as dh\n",
    "from quantify_core.measurement import MeasurementControl\n",
    "\n",
    "dh.set_datadir(Path.home() / \"quantify-data\")\n",
    "meas_ctrl = MeasurementControl(\"meas_ctrl\")\n",
    "\n",
    "par0 = ManualParameter(name=\"x0\", label=\"X0\", unit=\"s\")\n",
    "par1 = ManualParameter(name=\"x1\", label=\"X1\", unit=\"s\")\n",
    "par2 = ManualParameter(name=\"x2\", label=\"X2\", unit=\"s\")\n",
    "par3 = ManualParameter(name=\"x3\", label=\"X3\", unit=\"s\")\n",
    "sig = Parameter(name=\"sig\", label=\"Signal\", unit=\"V\", get_cmd=lambda: np.exp(par0()))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "510fc568-e50e-41d0-9f2e-c123d709ad68",
   "metadata": {},
   "source": [
    "## Comparing iterative and batched execution loop"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3c18895-ff87-4966-bb07-834a81877a46",
   "metadata": {},
   "source": [
    "### Iterative settables only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "47e22edf-598f-47f0-a10a-0329ce520174",
   "metadata": {},
   "outputs": [],
   "source": [
    "par0.batched = False\n",
    "par1.batched = False\n",
    "par2.batched = False\n",
    "\n",
    "sig.batched = False\n",
    "\n",
    "meas_ctrl.settables([par0, par1, par2])\n",
    "meas_ctrl.setpoints_grid(\n",
    "    [\n",
    "        np.linspace(0, 1, 4),\n",
    "        np.linspace(1, 2, 5),\n",
    "        np.linspace(2, 3, 6),\n",
    "    ]\n",
    ")\n",
    "meas_ctrl.gettables(sig)\n",
    "dset = meas_ctrl.run(\"demo\")\n",
    "list(xr.plot.line(xi, label=name) for name, xi in dset.coords.items())\n",
    "plt.gca().legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6deac28e-9f1b-43ca-bfe2-39c82c343caa",
   "metadata": {},
   "source": [
    "### Batched settables only\n",
    "\n",
    "Note that the settable with lowest `.batch_size`  will be correspond to the innermost loop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b6f46886-545d-4073-8199-8de065834071",
   "metadata": {},
   "outputs": [],
   "source": [
    "par0.batched = True\n",
    "par1.batch_size = 8\n",
    "par1.batched = True\n",
    "par1.batch_size = 8\n",
    "par2.batched = True\n",
    "par2.batch_size = 4\n",
    "\n",
    "sig = Parameter(name=\"sig\", label=\"Signal\", unit=\"V\", get_cmd=lambda: np.exp(par2()))\n",
    "sig.batched = True\n",
    "sig.batch_size = 32\n",
    "\n",
    "meas_ctrl.settables([par0, par1, par2])\n",
    "meas_ctrl.setpoints_grid(\n",
    "    [\n",
    "        np.linspace(0, 1, 3),\n",
    "        np.linspace(1, 2, 5),\n",
    "        np.linspace(2, 3, 4),\n",
    "    ]\n",
    ")\n",
    "meas_ctrl.gettables(sig)\n",
    "dset = meas_ctrl.run(\"demo\")\n",
    "list(xr.plot.line(xi, label=name) for name, xi in dset.coords.items())\n",
    "plt.gca().legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5c4d10c-2875-4bd4-a5b4-fe2fe9d8e37b",
   "metadata": {},
   "source": [
    "### Mixed batched and iterative settables\n",
    "\n",
    "Note that the settable with lowest `.batch_size`  will be correspond to the innermost loop.\n",
    "Furthermore, the iterative settables will be the outermost loops."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b86b1bbf-d17c-49d2-8995-3f1c12412df5",
   "metadata": {},
   "outputs": [],
   "source": [
    "par0.batched = False\n",
    "par1.batched = True\n",
    "par1.batch_size = 8\n",
    "par2.batched = False\n",
    "par3.batched = True\n",
    "par3.batch_size = 4\n",
    "\n",
    "sig = Parameter(name=\"sig\", label=\"Signal\", unit=\"V\", get_cmd=lambda: np.exp(par3()))\n",
    "sig.batched = True\n",
    "sig.batch_size = 32\n",
    "\n",
    "meas_ctrl.settables([par0, par1, par2, par3])\n",
    "meas_ctrl.setpoints_grid(\n",
    "    [\n",
    "        np.linspace(0, 1, 3),\n",
    "        np.linspace(1, 2, 5),\n",
    "        np.linspace(2, 3, 4),\n",
    "        np.linspace(3, 4, 6),\n",
    "    ]\n",
    ")\n",
    "meas_ctrl.gettables(sig)\n",
    "dset = meas_ctrl.run(\"demo\")\n",
    "list(xr.plot.line(xi, label=name) for name, xi in dset.coords.items())\n",
    "plt.gca().legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdc49b08-6f1a-4a69-98bc-5def597987dc",
   "metadata": {},
   "source": [
    "(howto-measurement-control-insmon)=\n",
    "## Instrument Monitor\n",
    "\n",
    "You can instantiate an instrument monitor in the following way:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b3a74661-0723-4393-babf-064828c831a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from quantify_core.measurement import MeasurementControl\n",
    "from quantify_core.visualization import InstrumentMonitor\n",
    "\n",
    "instrument_monitor = InstrumentMonitor(\"instrument_monitor\")\n",
    "# Set True if you want to query the instruments about each parameter\n",
    "# before updating the window. Can be slow due to communication overhead.\n",
    "instrument_monitor.update_snapshot(False)"
   ]
  }
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