{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "a4718a30",
   "metadata": {},
   "source": [
    "Synchronization\n",
    "===============\n",
    "\n",
    "In this tutorial we will demonstrate how to synchronize two Qblox instruments using the SYNQ technology (see section\n",
    "[Synchronization](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/cluster/synchronization.html)).\n",
    "For this tutorial we will use one QCM and one QRM and we will be acquiring waveforms sequenced by the QCM using the QRM.\n",
    "By synchronizing the two instruments using the SYNQ technology, timing the acquisition of the waveforms becomes trivial.\n",
    "\n",
    "The Cluster QCM and QRM are internally connected for SYNQ capability and therefore no new connections need to be made if one is using a Cluster.\n",
    "To run the tutorial, we connect $\\text{O}^{[1-2]}$ of the QCM to $\\text{I}^{[1-2]}$ of the QRM respectively.\n",
    "\n",
    "To run this tutorial please make sure you have installed and enabled ipywidgets:\n",
    "```\n",
    "pip install ipywidgets\n",
    "jupyter nbextension enable --py widgetsnbextension\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a2caf50",
   "metadata": {
    "tags": []
   },
   "source": [
    "Setup\n",
    "-----\n",
    "\n",
    "First, we are going to import the required packages and connect to the instrument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5ee4e1af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:02.327573Z",
     "iopub.status.busy": "2023-12-06T16:54:02.326474Z",
     "iopub.status.idle": "2023-12-06T16:54:03.709281Z",
     "shell.execute_reply": "2023-12-06T16:54:03.707624Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Import ipython widgets\n",
    "import contextlib\n",
    "import json\n",
    "import math\n",
    "\n",
    "import ipywidgets as widgets\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Set up the environment.\n",
    "import scipy.signal\n",
    "from IPython.display import display\n",
    "from qcodes import Instrument\n",
    "\n",
    "from qblox_instruments import Cluster, PlugAndPlay"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9208bd3",
   "metadata": {},
   "source": [
    "### Scan For Clusters\n",
    "\n",
    "We scan for the available devices connected via ethernet using the Plug & Play functionality of the Qblox Instruments package (see [Plug & Play](https://qblox-qblox-instruments.readthedocs-hosted.com/en/master/api_reference/tools.html#api-pnp) for more info)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8007e38b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:03.713827Z",
     "iopub.status.busy": "2023-12-06T16:54:03.712803Z",
     "iopub.status.idle": "2023-12-06T16:54:05.670907Z",
     "shell.execute_reply": "2023-12-06T16:54:05.668905Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Devices:\n",
      " - 10.10.200.13: cluster_mm 0.6.2 with name \"QSE_1\" and serial number 00015_2321_005\n",
      " - 10.10.200.42: cluster_mm 0.6.2 with name \"QAE_1\" and serial number 00015_2320_004\n",
      " - 10.10.200.43: cluster_mm 0.6.2 with name \"QAE_2\" and serial number 00015_2206_003\n",
      " - 10.10.200.50: cluster_mm 0.6.1 with name \"dd0\" and serial number 00015_2219_003\n",
      " - 10.10.200.53: cluster_mm 0.6.1 with name \"dd1\" and serial number 00015_2320_003\n",
      " - 10.10.200.70: cluster_mm 0.6.1 with name \"cluster-mm\" and serial number 123-456-789\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "57997aba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:05.675100Z",
     "iopub.status.busy": "2023-12-06T16:54:05.673586Z",
     "iopub.status.idle": "2023-12-06T16:54:05.684325Z",
     "shell.execute_reply": "2023-12-06T16:54:05.683821Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "658af655",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "567ebc69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:05.690449Z",
     "iopub.status.busy": "2023-12-06T16:54:05.689450Z",
     "iopub.status.idle": "2023-12-06T16:54:06.087901Z",
     "shell.execute_reply": "2023-12-06T16:54:06.086852Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "try:  # Close the chosen QCodes instrument to prevent name clash\n",
    "    Cluster.find_instrument(cluster_name).close()\n",
    "except KeyError:\n",
    "    pass\n",
    "\n",
    "cluster = Cluster(\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg={\n",
    "        2: ClusterType.CLUSTER_QCM,\n",
    "        4: ClusterType.CLUSTER_QRM,\n",
    "        6: ClusterType.CLUSTER_QCM_RF,\n",
    "        8: ClusterType.CLUSTER_QRM_RF,\n",
    "    }\n",
    "    if cluster_ip is None\n",
    "    else None,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f48b9f0",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "31fc916f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:06.092435Z",
     "iopub.status.busy": "2023-12-06T16:54:06.092435Z",
     "iopub.status.idle": "2023-12-06T16:54:06.102542Z",
     "shell.execute_reply": "2023-12-06T16:54:06.102542Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster, filter_fn=None):\n",
    "    def checked_filter_fn(mod):\n",
    "        if filter_fn is not None:\n",
    "            return filter_fn(mod)\n",
    "        return True\n",
    "\n",
    "    return {\n",
    "        mod.slot_idx: mod for mod in cluster.modules if mod.present() and checked_filter_fn(mod)\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8ca37e46",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:06.107186Z",
     "iopub.status.busy": "2023-12-06T16:54:06.106180Z",
     "iopub.status.idle": "2023-12-06T16:54:06.180667Z",
     "shell.execute_reply": "2023-12-06T16:54:06.179949Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4: <QcmQrm: cluster0_module4 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QRM baseband modules\n",
    "readout_modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and not mod.is_rf_type)\n",
    "readout_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "87beb71b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:06.185854Z",
     "iopub.status.busy": "2023-12-06T16:54:06.184845Z",
     "iopub.status.idle": "2023-12-06T16:54:06.196246Z",
     "shell.execute_reply": "2023-12-06T16:54:06.195052Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module = readout_modules[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d6b4afc1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:06.202114Z",
     "iopub.status.busy": "2023-12-06T16:54:06.201084Z",
     "iopub.status.idle": "2023-12-06T16:54:06.276683Z",
     "shell.execute_reply": "2023-12-06T16:54:06.274957Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2: <QcmQrm: cluster0_module2 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QCM baseband modules\n",
    "control_modules = get_connected_modules(\n",
    "    cluster, lambda mod: not mod.is_qrm_type and not mod.is_rf_type\n",
    ")\n",
    "control_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0d46cd34",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:06.280691Z",
     "iopub.status.busy": "2023-12-06T16:54:06.280691Z",
     "iopub.status.idle": "2023-12-06T16:54:06.291717Z",
     "shell.execute_reply": "2023-12-06T16:54:06.290070Z"
    }
   },
   "outputs": [],
   "source": [
    "control_module = control_modules[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c516871a",
   "metadata": {},
   "source": [
    "### Reset the Cluster\n",
    "\n",
    "We reset the Cluster to enter a well-defined state. Note that resetting will clear all stored parameters, so resetting between experiments is usually not desirable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5aae758e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:06.296275Z",
     "iopub.status.busy": "2023-12-06T16:54:06.295286Z",
     "iopub.status.idle": "2023-12-06T16:54:09.435643Z",
     "shell.execute_reply": "2023-12-06T16:54:09.433553Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "cluster.reset()\n",
    "print(cluster.get_system_state())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5105c963",
   "metadata": {},
   "source": [
    "Generate waveforms<a id='gen_wf'></a>\n",
    "------------------\n",
    "\n",
    "Next, we need to create the waveforms for the sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b082111b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.440523Z",
     "iopub.status.busy": "2023-12-06T16:54:09.440523Z",
     "iopub.status.idle": "2023-12-06T16:54:09.451143Z",
     "shell.execute_reply": "2023-12-06T16:54:09.449545Z"
    }
   },
   "outputs": [],
   "source": [
    "# Waveform parameters\n",
    "waveform_length = 120  # nanoseconds\n",
    "\n",
    "# Waveform dictionary (data will hold the samples and index will be used to select the waveforms in the instrument).\n",
    "waveforms = {\n",
    "    \"gaussian\": {\n",
    "        \"data\": scipy.signal.windows.gaussian(waveform_length, std=0.12 * waveform_length).tolist(),\n",
    "        \"index\": 0,\n",
    "    },\n",
    "    \"sine\": {\n",
    "        \"data\": [math.sin((2 * math.pi / waveform_length) * i) for i in range(0, waveform_length)],\n",
    "        \"index\": 1,\n",
    "    },\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98d78361",
   "metadata": {},
   "source": [
    "Let's plot the waveforms to see what we have created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "95addc09",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.458156Z",
     "iopub.status.busy": "2023-12-06T16:54:09.457157Z",
     "iopub.status.idle": "2023-12-06T16:54:09.637084Z",
     "shell.execute_reply": "2023-12-06T16:54:09.636084Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621.118 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time = np.arange(0, max(map(lambda d: len(d[\"data\"]), waveforms.values())), 1)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 10 / 1.61))\n",
    "\n",
    "for wf, d in waveforms.items():\n",
    "    ax.plot(time[: len(d[\"data\"])], d[\"data\"], \".-\", linewidth=0.5, label=wf)\n",
    "\n",
    "ax.legend(loc=4)\n",
    "ax.grid(alpha=1 / 10)\n",
    "ax.set_ylabel(\"Waveform primitive amplitude\")\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "\n",
    "plt.draw()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9076644c",
   "metadata": {},
   "source": [
    "Specify acquisitions\n",
    "--------------------\n",
    "\n",
    "We also need to specify the acquisitions so that the instrument can allocate the required memory for it's acquisition list. In this case we will create one acquisition specification that creates a single bin. However, we will not be using the bin in this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "3bf1fee7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.642085Z",
     "iopub.status.busy": "2023-12-06T16:54:09.641087Z",
     "iopub.status.idle": "2023-12-06T16:54:09.652598Z",
     "shell.execute_reply": "2023-12-06T16:54:09.651597Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"measurement\": {\"num_bins\": 1, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35be0f37",
   "metadata": {},
   "source": [
    "Create Q1ASM programs\n",
    "---------------------\n",
    "\n",
    "Now that we have the waveforms and acquisition specifications for the sequence, we need a simple Q1ASM program that sequences the waveforms in the QCM and\n",
    "acquires the waveforms in the QRM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a0282dac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.656108Z",
     "iopub.status.busy": "2023-12-06T16:54:09.656108Z",
     "iopub.status.idle": "2023-12-06T16:54:09.667617Z",
     "shell.execute_reply": "2023-12-06T16:54:09.666615Z"
    }
   },
   "outputs": [],
   "source": [
    "# QCM sequence program.\n",
    "qcm_seq_prog = \"\"\"\n",
    "wait_sync 4         #Synchronize sequencers over multiple instruments.\n",
    "play      0,1,16384 #Play waveforms and wait remaining duration of scope acquisition.\n",
    "stop                #Stop.\n",
    "\"\"\"\n",
    "\n",
    "# QRM sequence program.\n",
    "qrm_seq_prog = \"\"\"\n",
    "wait_sync 4         #Synchronize sequencers over multiple instruments.\n",
    "acquire   0,0,16384 #Acquire waveforms and wait remaining duration of scope acquisition.\n",
    "stop                #Stop.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01767313",
   "metadata": {},
   "source": [
    "Upload sequences\n",
    "----------------\n",
    "\n",
    "Now that we have the waveforms and Q1ASM programs, we can combine them in the sequences stored in JSON files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "afb477cb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.671616Z",
     "iopub.status.busy": "2023-12-06T16:54:09.671616Z",
     "iopub.status.idle": "2023-12-06T16:54:09.698703Z",
     "shell.execute_reply": "2023-12-06T16:54:09.697700Z"
    }
   },
   "outputs": [],
   "source": [
    "# Add QCM sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": waveforms,\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": qcm_seq_prog,\n",
    "}\n",
    "with open(\"qcm_sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()\n",
    "\n",
    "# Add QRM sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": waveforms,\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": qrm_seq_prog,\n",
    "}\n",
    "with open(\"qrm_sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd3e4332",
   "metadata": {},
   "source": [
    "Let's write the JSON file to the instruments. We will use sequencer 0 of both QCM and QRM, which will drive outputs $\\text{O}^{[1-2]}$\n",
    "of the QCM and acquire on inputs $\\text{I}^{[1-2]}$ of the QRM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "fca9deee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.703234Z",
     "iopub.status.busy": "2023-12-06T16:54:09.703234Z",
     "iopub.status.idle": "2023-12-06T16:54:09.794302Z",
     "shell.execute_reply": "2023-12-06T16:54:09.792297Z"
    }
   },
   "outputs": [],
   "source": [
    "# Upload waveforms and programs to QCM.\n",
    "control_module.sequencer0.sequence(\"qcm_sequence.json\")\n",
    "\n",
    "# Upload waveforms and programs to QRM.\n",
    "readout_module.sequencer0.sequence(\"qrm_sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3c8e2592",
   "metadata": {},
   "source": [
    "Play sequences\n",
    "--------------\n",
    "\n",
    "The sequence has been uploaded to the instruments. Now we need to configure the sequencers of both the QCM and QRM to use the `wait_sync` instruction\n",
    "to synchronize and we need to configure the sequencer of the QRM to trigger the acquisition with the `acquire` instruction.\n",
    "Furthermore we also need to attenuate the QCM's outputs to 40% to be able to capture the full range of the waveforms on the QRM's inputs.\n",
    "\n",
    "$\\text{Attenuation}={Input}/{Output}={2V}/{5V}={0.4}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c661276d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.799421Z",
     "iopub.status.busy": "2023-12-06T16:54:09.799421Z",
     "iopub.status.idle": "2023-12-06T16:54:09.964819Z",
     "shell.execute_reply": "2023-12-06T16:54:09.963825Z"
    }
   },
   "outputs": [],
   "source": [
    "# Configure the sequencer of the QCM.\n",
    "control_module.sequencer0.sync_en(True)\n",
    "control_module.sequencer0.gain_awg_path0(0.35)  # Adding a bit of margin to the 0.4\n",
    "control_module.sequencer0.gain_awg_path1(0.35)\n",
    "\n",
    "# Map sequencer of the QCM to specific outputs (but first disable all sequencer connections)\n",
    "control_module.disconnect_outputs()\n",
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "control_module.sequencer0.connect_sequencer(\"out0_1\")\n",
    "\n",
    "# Also map inputs\n",
    "readout_module.sequencer0.connect_sequencer(\"in0_1\")\n",
    "\n",
    "# Configure the scope acquisition of the QRM.\n",
    "readout_module.scope_acq_sequencer_select(0)\n",
    "readout_module.scope_acq_trigger_mode_path0(\"sequencer\")\n",
    "readout_module.scope_acq_trigger_mode_path1(\"sequencer\")\n",
    "\n",
    "# Configure the sequencer of the QRM.\n",
    "readout_module.sequencer0.sync_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "317bc73c",
   "metadata": {},
   "source": [
    "Now let's start the sequences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1334af86",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:09.968821Z",
     "iopub.status.busy": "2023-12-06T16:54:09.968821Z",
     "iopub.status.idle": "2023-12-06T16:54:10.013275Z",
     "shell.execute_reply": "2023-12-06T16:54:10.011886Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QCM status:\n",
      "Status: Q1_STOPPED, Flags: NONE\n",
      "\n",
      "QRM status:\n",
      "Status: STOPPED, Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\n"
     ]
    }
   ],
   "source": [
    "# Arm and start sequencer of the QCM (only sequencer 0).\n",
    "control_module.arm_sequencer(0)\n",
    "control_module.start_sequencer()\n",
    "\n",
    "# Print status of sequencer of the QCM.\n",
    "print(\"QCM status:\")\n",
    "print(control_module.get_sequencer_state(0))\n",
    "print()\n",
    "\n",
    "# Arm and start sequencer of the QRM (only sequencer 0).\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Print status of sequencer of the QRM.\n",
    "print(\"QRM status:\")\n",
    "print(readout_module.get_sequencer_state(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "512ac854",
   "metadata": {},
   "source": [
    "Retrieve acquisition\n",
    "--------------------\n",
    "\n",
    "The waveforms have now been sequenced on the outputs and acquired on the inputs by both instruments. And as you might have noticed, timing these operations was simplified\n",
    "significantly by the SYNQ technology. Lets retrieve the resulting data, but first let's make sure the sequencers have finished."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8d3b7c14",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:10.017452Z",
     "iopub.status.busy": "2023-12-06T16:54:10.016204Z",
     "iopub.status.idle": "2023-12-06T16:54:10.074735Z",
     "shell.execute_reply": "2023-12-06T16:54:10.073722Z"
    }
   },
   "outputs": [],
   "source": [
    "# Wait for the QCM sequencer to stop with a timeout period of one minute.\n",
    "control_module.get_sequencer_state(0, 1)\n",
    "\n",
    "# Wait for the QRM acquisition to finish with a timeout period of one minute.\n",
    "readout_module.get_acquisition_state(0, 1)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"measurement\")\n",
    "\n",
    "# Get acquisition list from instrument.\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "be720003",
   "metadata": {},
   "source": [
    "Let's plot the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "3608c38a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:10.080316Z",
     "iopub.status.busy": "2023-12-06T16:54:10.080316Z",
     "iopub.status.idle": "2023-12-06T16:54:10.213824Z",
     "shell.execute_reply": "2023-12-06T16:54:10.213824Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot acquired signal on both inputs.\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "ax.plot(acq[\"measurement\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][130:290])\n",
    "ax.plot(acq[\"measurement\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][130:290])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6f03c475",
   "metadata": {},
   "source": [
    "Stop\n",
    "----\n",
    "\n",
    "Finally, let's stop the sequencers if they haven't already and close the instrument connection. One can also display a detailed snapshot containing the instrument parameters before\n",
    "closing the connection by uncommenting the corresponding lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "49a24c8a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-12-06T16:54:10.217212Z",
     "iopub.status.busy": "2023-12-06T16:54:10.217212Z",
     "iopub.status.idle": "2023-12-06T16:54:13.377329Z",
     "shell.execute_reply": "2023-12-06T16:54:13.375367Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QCM:\n",
      "Status: STOPPED, Flags: FORCED_STOP\n",
      "\n",
      "QRM:\n",
      "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "# Stop sequencers.\n",
    "control_module.stop_sequencer()\n",
    "readout_module.stop_sequencer()\n",
    "\n",
    "# Print status of sequencers.\n",
    "print(\"QCM:\")\n",
    "print(control_module.get_sequencer_state(0))\n",
    "print()\n",
    "\n",
    "print(\"QRM:\")\n",
    "print(readout_module.get_sequencer_state(0))\n",
    "print()\n",
    "\n",
    "# Uncomment the following to print an overview of the instrument parameters.\n",
    "# Print an overview of instrument parameters.\n",
    "# print(\"QCM snapshot:\")\n",
    "# qcm.print_readable_snapshot(update=True)\n",
    "# print()\n",
    "\n",
    "# print(\"QRM snapshot:\")\n",
    "# readout_module.print_readable_snapshot(update=True)\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_state())"
   ]
  }
 ],
 "metadata": {
  "jupytext": {
   "formats": "ipynb,py:percent"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "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": "3.8.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}