{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "71ca50a7",
   "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/main/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."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7b658ac",
   "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": "53a808aa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:16.333770Z",
     "iopub.status.busy": "2024-03-28T14:33:16.332768Z",
     "iopub.status.idle": "2024-03-28T14:33:17.948299Z",
     "shell.execute_reply": "2024-03-28T14:33:17.947299Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "\n",
    "from __future__ import annotations\n",
    "\n",
    "import json\n",
    "import math\n",
    "from typing import TYPE_CHECKING, Callable\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.signal\n",
    "from qcodes.instrument import find_or_create_instrument\n",
    "\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "if TYPE_CHECKING:\n",
    "    from qblox_instruments.qcodes_drivers.module import QcmQrm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8648f5e",
   "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/main/api_reference/tools.html#api-pnp) for more info)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2290b19a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:17.954144Z",
     "iopub.status.busy": "2024-03-28T14:33:17.953126Z",
     "iopub.status.idle": "2024-03-28T14:33:20.007150Z",
     "shell.execute_reply": "2024-03-28T14:33:20.005749Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Devices:\n",
      " - 10.10.200.13 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.2 with name \"QSE_1\" and serial number 00015_2321_005\n",
      " - 10.10.200.42 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"QAE-I\" and serial number 00015_2321_004\n",
      " - 10.10.200.43 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.2 with name \"QAE-2\" and serial number 00015_2206_003\n",
      " - 10.10.200.50 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"cluster-mm\" and serial number 00015_2219_003\n",
      " - 10.10.200.53 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.7.0 with name \"cluster-mm\" and serial number 00015_2320_004\n",
      " - 10.10.200.70 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.1 with name \"cluster-mm\" and serial number 123-456-789\n",
      " - 10.10.200.80 via 192.168.207.146/24 (reconfiguration needed!): cluster_mm 0.6.1 with name \"cluster-mm\" and serial number not_valid\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f39b19ee",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:20.011227Z",
     "iopub.status.busy": "2024-03-28T14:33:20.011227Z",
     "iopub.status.idle": "2024-03-28T14:33:20.022721Z",
     "shell.execute_reply": "2024-03-28T14:33:20.020551Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7c4596ab",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "1be45f0d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:20.025789Z",
     "iopub.status.busy": "2024-03-28T14:33:20.025789Z",
     "iopub.status.idle": "2024-03-28T14:33:20.947793Z",
     "shell.execute_reply": "2024-03-28T14:33:20.946352Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "\n",
    "cluster = find_or_create_instrument(\n",
    "    Cluster,\n",
    "    recreate=True,\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg=(\n",
    "        {\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",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efb1233c",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9a62cfd0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:20.952330Z",
     "iopub.status.busy": "2024-03-28T14:33:20.951334Z",
     "iopub.status.idle": "2024-03-28T14:33:20.963077Z",
     "shell.execute_reply": "2024-03-28T14:33:20.961915Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, QcmQrm]:\n",
    "    def checked_filter_fn(mod: ClusterType) -> bool:\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": "50d461b8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:20.968120Z",
     "iopub.status.busy": "2024-03-28T14:33:20.968120Z",
     "iopub.status.idle": "2024-03-28T14:33:21.101217Z",
     "shell.execute_reply": "2024-03-28T14:33:21.100134Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4: <Module: 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": "aed04d03",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:21.106814Z",
     "iopub.status.busy": "2024-03-28T14:33:21.105834Z",
     "iopub.status.idle": "2024-03-28T14:33:21.116846Z",
     "shell.execute_reply": "2024-03-28T14:33:21.115420Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module = readout_modules[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c39a40e9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:21.121069Z",
     "iopub.status.busy": "2024-03-28T14:33:21.121069Z",
     "iopub.status.idle": "2024-03-28T14:33:21.252546Z",
     "shell.execute_reply": "2024-03-28T14:33:21.252546Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2: <Module: 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": "607a627a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:21.259208Z",
     "iopub.status.busy": "2024-03-28T14:33:21.259208Z",
     "iopub.status.idle": "2024-03-28T14:33:21.269424Z",
     "shell.execute_reply": "2024-03-28T14:33:21.267921Z"
    }
   },
   "outputs": [],
   "source": [
    "control_module = control_modules[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f4d06f0",
   "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": "dcab4f45",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:21.276046Z",
     "iopub.status.busy": "2024-03-28T14:33:21.276046Z",
     "iopub.status.idle": "2024-03-28T14:33:24.681465Z",
     "shell.execute_reply": "2024-03-28T14:33:24.678957Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:1033: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:77: FutureWarning: \n",
      "            After June 2024, this feature is subject to removal in future releases.\n",
      "            Transition to an alternative is advised.\n",
      "            See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "            \n",
      "  self._deprecation_warning()\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:129: FutureWarning: \n",
      "            After June 2024, this feature is subject to removal in future releases.\n",
      "            Transition to an alternative is advised.\n",
      "            See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "            \n",
      "  self._deprecation_warning()\n"
     ]
    }
   ],
   "source": [
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a1d400b",
   "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": "76380a31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:24.686801Z",
     "iopub.status.busy": "2024-03-28T14:33:24.685771Z",
     "iopub.status.idle": "2024-03-28T14:33:24.695331Z",
     "shell.execute_reply": "2024-03-28T14:33:24.694035Z"
    }
   },
   "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": "52e1595f",
   "metadata": {},
   "source": [
    "Let's plot the waveforms to see what we have created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "65c3c269",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:24.699892Z",
     "iopub.status.busy": "2024-03-28T14:33:24.699365Z",
     "iopub.status.idle": "2024-03-28T14:33:24.913829Z",
     "shell.execute_reply": "2024-03-28T14:33:24.912246Z"
    }
   },
   "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": "48427d8c",
   "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": "1980b460",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:24.919008Z",
     "iopub.status.busy": "2024-03-28T14:33:24.919008Z",
     "iopub.status.idle": "2024-03-28T14:33:24.929675Z",
     "shell.execute_reply": "2024-03-28T14:33:24.928656Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"measurement\": {\"num_bins\": 1, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67b0ac2c",
   "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": "6ba1a46a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:24.933866Z",
     "iopub.status.busy": "2024-03-28T14:33:24.933866Z",
     "iopub.status.idle": "2024-03-28T14:33:24.944737Z",
     "shell.execute_reply": "2024-03-28T14:33:24.943224Z"
    }
   },
   "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": "007eeb6b",
   "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": "b47b4555",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:24.949904Z",
     "iopub.status.busy": "2024-03-28T14:33:24.948865Z",
     "iopub.status.idle": "2024-03-28T14:33:24.974261Z",
     "shell.execute_reply": "2024-03-28T14:33:24.973261Z"
    }
   },
   "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": "45e301b3",
   "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": "bdd49636",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:24.979597Z",
     "iopub.status.busy": "2024-03-28T14:33:24.979071Z",
     "iopub.status.idle": "2024-03-28T14:33:25.080747Z",
     "shell.execute_reply": "2024-03-28T14:33:25.079695Z"
    }
   },
   "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": "1de98bf3",
   "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": "35c9e28b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:25.085140Z",
     "iopub.status.busy": "2024-03-28T14:33:25.085140Z",
     "iopub.status.idle": "2024-03-28T14:33:25.280383Z",
     "shell.execute_reply": "2024-03-28T14:33:25.279390Z"
    }
   },
   "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": "6e32d21f",
   "metadata": {},
   "source": [
    "Now let's start the sequences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1277ab91",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:25.285749Z",
     "iopub.status.busy": "2024-03-28T14:33:25.285749Z",
     "iopub.status.idle": "2024-03-28T14:33:25.326769Z",
     "shell.execute_reply": "2024-03-28T14:33:25.325625Z"
    }
   },
   "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"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:2414: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n",
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:85: FutureWarning: \n",
      "            After June 2024, this feature is subject to removal in future releases.\n",
      "            Transition to an alternative is advised.\n",
      "            See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "            \n",
      "  self._deprecation_warning()\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_status(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_status(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ad63875",
   "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": "203792e2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:25.331334Z",
     "iopub.status.busy": "2024-03-28T14:33:25.331334Z",
     "iopub.status.idle": "2024-03-28T14:33:25.405695Z",
     "shell.execute_reply": "2024-03-28T14:33:25.404013Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:3210: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "# Wait for the QCM sequencer to stop with a timeout period of one minute.\n",
    "control_module.get_sequencer_status(0, 1)\n",
    "\n",
    "# Wait for the QRM acquisition to finish with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(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": "72fe44bb",
   "metadata": {},
   "source": [
    "Let's plot the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b40edd2c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:25.410718Z",
     "iopub.status.busy": "2024-03-28T14:33:25.409714Z",
     "iopub.status.idle": "2024-03-28T14:33:25.576097Z",
     "shell.execute_reply": "2024-03-28T14:33:25.574695Z"
    }
   },
   "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": "27f8662a",
   "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": "8eb4c82a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:33:25.579635Z",
     "iopub.status.busy": "2024-03-28T14:33:25.579635Z",
     "iopub.status.idle": "2024-03-28T14:33:40.431990Z",
     "shell.execute_reply": "2024-03-28T14:33:40.430280Z"
    }
   },
   "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",
      "QCM snapshot:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2:\n",
      "\tparameter     value\n",
      "--------------------------------------------------------------------------------\n",
      "marker0_inv_en :\tFalse \n",
      "marker1_inv_en :\tFalse \n",
      "marker2_inv_en :\tFalse \n",
      "marker3_inv_en :\tFalse \n",
      "out0_offset    :\t0 (V)\n",
      "out1_offset    :\t0 (V)\n",
      "out2_offset    :\t0 (V)\n",
      "out3_offset    :\t0 (V)\n",
      "present        :\tTrue \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2_sequencer0:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_out0                     :\tI \n",
      "connect_out1                     :\tQ \n",
      "connect_out2                     :\toff \n",
      "connect_out3                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "gain_awg_path0                   :\t0.34999 \n",
      "gain_awg_path1                   :\t0.34999 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tTrue \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2_sequencer1:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "connect_out2                     :\toff \n",
      "connect_out3                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2_sequencer2:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "connect_out2                     :\toff \n",
      "connect_out3                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2_sequencer3:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "connect_out2                     :\toff \n",
      "connect_out3                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2_sequencer4:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "connect_out2                     :\toff \n",
      "connect_out3                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module2_sequencer5:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "connect_out2                     :\toff \n",
      "connect_out3                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n",
      "\n",
      "QRM snapshot:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4:\n",
      "\tparameter                    value\n",
      "--------------------------------------------------------------------------------\n",
      "in0_gain                      :\t-6 (dB)\n",
      "in0_offset                    :\t0 (V)\n",
      "in1_gain                      :\t-6 (dB)\n",
      "in1_offset                    :\t0 (V)\n",
      "marker0_inv_en                :\tFalse \n",
      "marker1_inv_en                :\tFalse \n",
      "marker2_inv_en                :\tFalse \n",
      "marker3_inv_en                :\tFalse \n",
      "out0_offset                   :\t0 (V)\n",
      "out1_offset                   :\t0 (V)\n",
      "present                       :\tTrue \n",
      "scope_acq_avg_mode_en_path0   :\tFalse \n",
      "scope_acq_avg_mode_en_path1   :\tFalse \n",
      "scope_acq_sequencer_select    :\t0 \n",
      "scope_acq_trigger_level_path0 :\t0 \n",
      "scope_acq_trigger_level_path1 :\t0 \n",
      "scope_acq_trigger_mode_path0  :\tsequencer \n",
      "scope_acq_trigger_mode_path1  :\tsequencer \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer0:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\tin0 \n",
      "connect_acq_Q                    :\tin1 \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tTrue \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer1:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer2:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer3:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer4:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer5:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \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_status(0))\n",
    "print()\n",
    "\n",
    "print(\"QRM:\")\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "print()\n",
    "\n",
    "# Print an overview of instrument parameters.\n",
    "print(\"QCM snapshot:\")\n",
    "control_module.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_status())"
   ]
  }
 ],
 "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": "3.8.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}