{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2a57e26f",
   "metadata": {},
   "source": [
    "RF control\n",
    "=================\n",
    "\n",
    "In this tutorial, we demonstrate control and calibration of RF modules.\n",
    "\n",
    "- **[Spectroscopy measurements](#Spectroscopy-Measurements)** - in which we measure the transmission parameter (S21) of the device under test;\n",
    "\n",
    "    * Over a large frequency range ($2.0$ - $18.0$ GHz) by sweeping the LO frequency;\n",
    "\n",
    "    * Over a smaller frequency range ($5.0$ - $5.2$ GHz) by sweeping the NCO frequency.\n",
    "\n",
    "\n",
    "\n",
    "To run this tutorial, you will need:\n",
    "\n",
    "* [QRM-RF](https://docs.qblox.com/en/main/cluster/qrm_rf.html)\n",
    "\n",
    "\n",
    "* Device under test: a T-connector\n",
    "\n",
    "* Two SMA-cables"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "95db7727",
   "metadata": {
    "tags": []
   },
   "source": [
    "Setup\n",
    "-----\n",
    "\n",
    "First, we are going to import the required packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "26c508a6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:37.904697Z",
     "iopub.status.busy": "2025-05-07T16:51:37.904548Z",
     "iopub.status.idle": "2025-05-07T16:51:38.487499Z",
     "shell.execute_reply": "2025-05-07T16:51:38.486923Z"
    },
    "tags": [
     "imports"
    ]
   },
   "outputs": [],
   "source": [
    "from __future__ import annotations\n",
    "\n",
    "import json\n",
    "from typing import TYPE_CHECKING, Callable\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from qcodes.instrument import find_or_create_instrument\n",
    "\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "if TYPE_CHECKING:\n",
    "    from numpy.typing import NDArray\n",
    "\n",
    "    from qblox_instruments.qcodes_drivers.module import Module"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "549f3ae3",
   "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://docs.qblox.com/en/main/api_reference/tools.html#api-pnp) for more info)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "005db276",
   "metadata": {},
   "source": [
    "`!qblox-pnp list`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "03bfb6d2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:38.490162Z",
     "iopub.status.busy": "2025-05-07T16:51:38.490010Z",
     "iopub.status.idle": "2025-05-07T16:51:38.492458Z",
     "shell.execute_reply": "2025-05-07T16:51:38.492061Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52f91425",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f69f5672",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:38.493842Z",
     "iopub.status.busy": "2025-05-07T16:51:38.493705Z",
     "iopub.status.idle": "2025-05-07T16:51:39.304076Z",
     "shell.execute_reply": "2025-05-07T16:51:39.303534Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "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",
    "            10: ClusterType.CLUSTER_QTM,\n",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d0231ef",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "8cc2c023",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:39.306518Z",
     "iopub.status.busy": "2025-05-07T16:51:39.306356Z",
     "iopub.status.idle": "2025-05-07T16:51:39.309664Z",
     "shell.execute_reply": "2025-05-07T16:51:39.309265Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, Module]:\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": 5,
   "id": "c91fe1f4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:39.311232Z",
     "iopub.status.busy": "2025-05-07T16:51:39.311096Z",
     "iopub.status.idle": "2025-05-07T16:51:39.328631Z",
     "shell.execute_reply": "2025-05-07T16:51:39.328220Z"
    },
    "tags": [
     "module_select"
    ]
   },
   "outputs": [],
   "source": [
    "# QRM-RF modules\n",
    "modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and mod.is_rf_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "806a2983",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:39.330743Z",
     "iopub.status.busy": "2025-05-07T16:51:39.330605Z",
     "iopub.status.idle": "2025-05-07T16:51:39.332783Z",
     "shell.execute_reply": "2025-05-07T16:51:39.332407Z"
    }
   },
   "outputs": [],
   "source": [
    "# This uses the module of the correct type with the lowest slot index\n",
    "module = list(modules.values())[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6315227",
   "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": 7,
   "id": "8ab856b1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:39.334902Z",
     "iopub.status.busy": "2025-05-07T16:51:39.334767Z",
     "iopub.status.idle": "2025-05-07T16:51:41.886909Z",
     "shell.execute_reply": "2025-05-07T16:51:41.885738Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: BOOTING, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "06587702",
   "metadata": {
    "lines_to_next_cell": 2,
    "title": "BODY"
   },
   "source": [
    "Spectroscopy Measurements\n",
    "-----------------------------------------\n",
    "\n",
    "A common experimental step is to find the resonance frequency of a resonator. To showcase the experience flow in this case we will sweep close to the full frequency range of the QRM-RF module ($2$ - $18$ GHz) and plot the frequency response.\n",
    "\n",
    "We start by defining a function to plot the amplitude and phase of the output signal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1aa7b0c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:41.890830Z",
     "iopub.status.busy": "2025-05-07T16:51:41.890467Z",
     "iopub.status.idle": "2025-05-07T16:51:41.899556Z",
     "shell.execute_reply": "2025-05-07T16:51:41.898607Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_spectrum(freq_sweep_range: NDArray, I_data: NDArray, Q_data: NDArray) -> None:\n",
    "    amplitude = np.sqrt(I_data**2 + Q_data**2)\n",
    "    phase = np.arctan2(Q_data, I_data) * 180 / np.pi\n",
    "\n",
    "    fig, [ax1, ax2] = plt.subplots(2, 1, sharex=True, figsize=(15, 7))\n",
    "\n",
    "    ax1.plot(freq_sweep_range / 1e9, amplitude, color=\"#00839F\", linewidth=2)\n",
    "    ax1.set_ylabel(\"Amplitude (V)\")\n",
    "\n",
    "    ax2.plot(freq_sweep_range / 1e9, phase, color=\"#00839F\", linewidth=2)\n",
    "    ax2.set_ylabel(r\"Phase ($\\circ$)\")\n",
    "    ax2.set_xlabel(\"Frequency (GHz)\")\n",
    "    fig.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52093168",
   "metadata": {},
   "source": [
    "### Setup\n",
    "Connect the output of QRM-RF to its input via a T-connector (one end of the T-connector should be left open so as to produce a resonator) as shown in the figure below.\n",
    "\n",
    "**Note**: this will not work if a splitter is used.\n",
    "\n",
    "![Diagram.png](figures/RF_Tutorial_Diagram.png)\n",
    "\n",
    "Initially, we need to define the waveforms and acquisition memory. As we are using the NCO to generate an IF signal, we can use a constant (DC) waveform. We need to make sure that the waveform is long enough to run during the whole acquisition integration length and to compensate for the delay of output to input (the `holdoff_length`). Finally, we will also add averaging to increase the signal-to-noise ratio (SNR) of the measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "839cc17c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:41.903022Z",
     "iopub.status.busy": "2025-05-07T16:51:41.902670Z",
     "iopub.status.idle": "2025-05-07T16:51:41.907536Z",
     "shell.execute_reply": "2025-05-07T16:51:41.906594Z"
    }
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "no_averages = 10\n",
    "integration_length = 1024\n",
    "holdoff_length = 200\n",
    "waveform_length = integration_length + holdoff_length"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b089a96",
   "metadata": {},
   "source": [
    "For simplicity, a single bin is used in this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d2385bf1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:41.910878Z",
     "iopub.status.busy": "2025-05-07T16:51:41.910532Z",
     "iopub.status.idle": "2025-05-07T16:51:41.915122Z",
     "shell.execute_reply": "2025-05-07T16:51:41.914190Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"acq\": {\"num_bins\": 1, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5828d7dd",
   "metadata": {},
   "source": [
    "Now that the waveform and acquisition have been specified for the sequence, we need a Q1ASM program that sequences the waveforms and triggers the acquisitions. This program plays a DC wave, waits for the specified hold-off time and then acquires the signal. This process is repeated for the specified number of averages, with the average being done within the hardware."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ba414544",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:41.918538Z",
     "iopub.status.busy": "2025-05-07T16:51:41.918169Z",
     "iopub.status.idle": "2025-05-07T16:51:41.946717Z",
     "shell.execute_reply": "2025-05-07T16:51:41.945251Z"
    }
   },
   "outputs": [],
   "source": [
    "seq_prog = f\"\"\"\n",
    "      move    {no_averages},R0           # Average iterator.\n",
    "      nop\n",
    "      reset_ph\n",
    "      set_awg_offs 10000, 10000          # set amplitude of signal\n",
    "      nop\n",
    "loop:\n",
    "      wait     {holdoff_length}          # Wait time of flight\n",
    "      acquire  0,0,{integration_length}  # Acquire data and store them in bin_n0 of acq_index.\n",
    "      loop     R0,@loop                  # Run until number of average iterations is done.\n",
    "      stop                               # Stop the sequencer\n",
    "      \"\"\"\n",
    "\n",
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": {},\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": seq_prog,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()\n",
    "\n",
    "# Upload sequence\n",
    "module.sequencer0.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1a8f85b3",
   "metadata": {},
   "source": [
    "The device and sequencer can now be configured. In the RF modules, there is a switch directly before the output connector, which needs to be turned on to get a signal out of the device. The switch is controlled through the marker interface, first we must enable to override of the marker, then we must set the appropriate bits to enable the signal at the output.\n",
    "\n",
    "Additionally, we set the output paths DC offset to known values. We look into the details of this parameter further on in this tutorial. Additionally, we configure the sequencer, the acquisition and set the NCO frequency. More information on these configurations can be found in the [Basic Sequencing](https://docs.qblox.com/en/main/tutorials/q1asm_tutorials/QRM-RF/010_basic_sequencing.html), [Scope Acquisition](https://docs.qblox.com/en/main/tutorials/q1asm_tutorials/QRM-RF/030_scope_acquisition.html) and [NCO](https://docs.qblox.com/en/main/tutorials/q1asm_tutorials/QRM/nco_control.html) tutorials, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "5a98cb68",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:41.950029Z",
     "iopub.status.busy": "2025-05-07T16:51:41.949800Z",
     "iopub.status.idle": "2025-05-07T16:51:42.083476Z",
     "shell.execute_reply": "2025-05-07T16:51:42.082500Z"
    }
   },
   "outputs": [],
   "source": [
    "module.disconnect_outputs()\n",
    "module.disconnect_inputs()\n",
    "\n",
    "# Configure channel map\n",
    "module.sequencer0.connect_sequencer(\"io0\")\n",
    "\n",
    "module.sequencer0.marker_ovr_en(True)\n",
    "module.sequencer0.marker_ovr_value(3)  # Enables output on QRM-RF\n",
    "\n",
    "# Set input attenuation to avoid reflections\n",
    "module.in0_att(10)\n",
    "# Set offset in mV\n",
    "module.out0_offset_path0(5.5)\n",
    "module.out0_offset_path1(5.5)\n",
    "\n",
    "# Configure scope mode\n",
    "module.scope_acq_sequencer_select(0)\n",
    "module.scope_acq_trigger_mode_path0(\"sequencer\")\n",
    "module.scope_acq_trigger_mode_path1(\"sequencer\")\n",
    "\n",
    "# Configure the sequencer\n",
    "module.sequencer0.mod_en_awg(True)\n",
    "module.sequencer0.demod_en_acq(True)\n",
    "module.sequencer0.nco_freq(100e6)\n",
    "module.sequencer0.integration_length_acq(integration_length)\n",
    "module.sequencer0.sync_en(True)\n",
    "\n",
    "# NCO delay compensation\n",
    "module.sequencer0.nco_prop_delay_comp_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ff6d0b8",
   "metadata": {},
   "source": [
    "Now we are ready to start the spectroscopy measurements."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "705ca976",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:42.086958Z",
     "iopub.status.busy": "2025-05-07T16:51:42.086709Z",
     "iopub.status.idle": "2025-05-07T16:51:52.378020Z",
     "shell.execute_reply": "2025-05-07T16:51:52.375815Z"
    }
   },
   "outputs": [],
   "source": [
    "lo_sweep_range = np.linspace(2e9, 18e9, 161)\n",
    "\n",
    "lo_data_0 = []\n",
    "lo_data_1 = []\n",
    "\n",
    "for lo_val in lo_sweep_range:\n",
    "    # Update the LO frequency.\n",
    "    module.out0_in0_lo_freq(lo_val)\n",
    "\n",
    "    # Clear acquisitions\n",
    "    module.sequencer0.delete_acquisition_data(\"acq\")\n",
    "\n",
    "    module.arm_sequencer(0)\n",
    "    module.start_sequencer()\n",
    "\n",
    "    # Wait for the sequencer to stop with a timeout period of one minute.\n",
    "    module.get_acquisition_status(0)\n",
    "\n",
    "    # Move acquisition data from temporary memory to acquisition list.\n",
    "    module.store_scope_acquisition(0, \"acq\")\n",
    "\n",
    "    # Get acquisition list from instrument.\n",
    "    data = module.get_acquisitions(0)[\"acq\"]\n",
    "\n",
    "    # Store the acquisition data.\n",
    "    lo_data_0.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"][0])\n",
    "    lo_data_1.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"][0])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de4fecbd",
   "metadata": {},
   "source": [
    "We plot the acquired signal's amplitude and phase."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "90988124",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:52.383201Z",
     "iopub.status.busy": "2025-05-07T16:51:52.382751Z",
     "iopub.status.idle": "2025-05-07T16:51:52.724012Z",
     "shell.execute_reply": "2025-05-07T16:51:52.723249Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The result still needs to be divided by the integration length to make sure\n",
    "# the units are correct.\n",
    "lo_data_0 = np.asarray(lo_data_0) / integration_length\n",
    "lo_data_1 = np.asarray(lo_data_1) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(lo_sweep_range, lo_data_0, lo_data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf2ed405",
   "metadata": {},
   "source": [
    "From the spectroscopy measurements, we can see that the resonance dip of the resonator is at roughly $6.5$ GHz.\n",
    "\n",
    "### Frequency sweep using NCO\n",
    "\n",
    "Instead of sweeping the LO frequency, we can instead sweep the NCO. More information on the NCO can be found in the [NCO Control Tutorial](https://docs.qblox.com/en/main/tutorials/q1asm_tutorials/QRM/nco_control.html). We perform a frequency sweep from $5.0$ to $5.2$ GHz by setting the LO frequency to $4.95$ GHz, such that the NCO frequency is swept from $50$ to $250$ MHz. Due to possible LO leakage we avoid NCO frequencies below $\\pm10$ MHz. Additionally, due to the analog filters, which cause a decrease in the output signal as the frequency increases, see [NCO Control Tutorial](https://docs.qblox.com/en/main/tutorials/q1asm_tutorials/QRM/nco_control.html), we choose to remain below $250$ MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "03a204f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:52.725796Z",
     "iopub.status.busy": "2025-05-07T16:51:52.725638Z",
     "iopub.status.idle": "2025-05-07T16:51:52.778754Z",
     "shell.execute_reply": "2025-05-07T16:51:52.777522Z"
    }
   },
   "outputs": [],
   "source": [
    "freq_sweep_range = np.linspace(5.0e9, 5.2e9, 200)\n",
    "\n",
    "# LO settings\n",
    "lo_freq = 4.95e9\n",
    "module.out0_in0_lo_freq(lo_freq)\n",
    "\n",
    "# NCO delay compensation\n",
    "module.sequencer0.nco_prop_delay_comp_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "11a044cc",
   "metadata": {},
   "source": [
    "We run the frequency sweep. This is simply a loop where we set the frequency by updating the QCoDeS NCO frequency parameter and then run the Q1ASM program defined in the previous example. We measure the run time using the `%%time` IPython magic command."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "9c5469f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:51:52.781819Z",
     "iopub.status.busy": "2025-05-07T16:51:52.781416Z",
     "iopub.status.idle": "2025-05-07T16:52:02.387197Z",
     "shell.execute_reply": "2025-05-07T16:52:02.385739Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 1.61 s, sys: 316 ms, total: 1.92 s\n",
      "Wall time: 9.59 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "data_0 = []\n",
    "data_1 = []\n",
    "\n",
    "for freq_val in freq_sweep_range:\n",
    "    # Update the NCO frequency.\n",
    "    module.sequencer0.nco_freq(freq_val - lo_freq)\n",
    "\n",
    "    # Clear acquisitions\n",
    "    module.sequencer0.delete_acquisition_data(\"acq\")\n",
    "\n",
    "    module.arm_sequencer(0)\n",
    "    module.start_sequencer()\n",
    "\n",
    "    # Wait for the sequencer to stop with a timeout period of one minute.\n",
    "    module.get_acquisition_status(0)\n",
    "\n",
    "    # Move acquisition data from temporary memory to acquisition list.\n",
    "    module.store_scope_acquisition(0, \"acq\")\n",
    "\n",
    "    # Get acquisition list from instrument.\n",
    "    data = module.get_acquisitions(0)[\"acq\"]\n",
    "\n",
    "    # Store the acquisition data.\n",
    "    data_0.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"][0])\n",
    "    data_1.append(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"][0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1b3ebecc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.391563Z",
     "iopub.status.busy": "2025-05-07T16:52:02.391102Z",
     "iopub.status.idle": "2025-05-07T16:52:02.631846Z",
     "shell.execute_reply": "2025-05-07T16:52:02.631362Z"
    }
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# The result still needs to be divided by the integration length to make sure\n",
    "# the units are correct.\n",
    "data_0 = np.asarray(data_0) / integration_length\n",
    "data_1 = np.asarray(data_1) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(freq_sweep_range, data_0, data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c8b039c",
   "metadata": {},
   "source": [
    "### Fast frequency sweep\n",
    "\n",
    "The same spectroscopy measurement can be done by sweeping the NCO frequency directly in the Q1ASM sequence, with a considerable time speed-up in comparison with updating the QCoDes parameters.\n",
    "\n",
    "The Q1ASM sequencer program only supports integer values. However, the NCO has a frequency resolution of 0.25 Hz. As such, the frequency values in the sequencer program must be given as integer multiples of $1/4$ Hz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "9bd8f2cf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.635050Z",
     "iopub.status.busy": "2025-05-07T16:52:02.634908Z",
     "iopub.status.idle": "2025-05-07T16:52:02.654913Z",
     "shell.execute_reply": "2025-05-07T16:52:02.654521Z"
    }
   },
   "outputs": [],
   "source": [
    "freq_sweep_range = np.linspace(5.0e9, 5.2e9, 200)\n",
    "\n",
    "lo_freq = 4.95e9\n",
    "module.out0_in0_lo_freq(lo_freq)\n",
    "\n",
    "start_freq = np.min(freq_sweep_range) - lo_freq\n",
    "stop_freq = np.max(freq_sweep_range) - lo_freq\n",
    "n_steps = len(freq_sweep_range)\n",
    "step_freq = (stop_freq - start_freq) / n_steps\n",
    "\n",
    "# NCO frequency range settings\n",
    "nco_int_start_freq = int(4 * start_freq)\n",
    "nco_int_step_freq = int(4 * step_freq)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa9a0fc9",
   "metadata": {},
   "source": [
    "We set up the QRM-RF for continuous wave output, similarly to what was done in the previous example, and binned acquisition with multiple bins - equal to the number of frequency steps. The maximum number of points that can be measured using this method is $131072$ per sequencer, which corresponds to the maximum number of bins."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "ee6807f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.657807Z",
     "iopub.status.busy": "2025-05-07T16:52:02.657581Z",
     "iopub.status.idle": "2025-05-07T16:52:02.660327Z",
     "shell.execute_reply": "2025-05-07T16:52:02.659945Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"multi\": {\"num_bins\": n_steps, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "14dcde13",
   "metadata": {},
   "source": [
    "The Q1ASM sequence program is defined with two loops, one for the averaging and a second one for the frequency sweep, i.e. the measurement itself."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "88a272af",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.662760Z",
     "iopub.status.busy": "2025-05-07T16:52:02.662627Z",
     "iopub.status.idle": "2025-05-07T16:52:02.685046Z",
     "shell.execute_reply": "2025-05-07T16:52:02.684175Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program sequence\n",
    "program = f\"\"\"\n",
    "        move            {no_averages}, R0                   # Include number of averages\n",
    "avg:\n",
    "        move            {nco_int_start_freq}, R1            # Start frequency\n",
    "        move            0, R2                               # Step counter\n",
    "        reset_ph                                         # Reset phase of signal\n",
    "        set_awg_offs    10000, 10000                        # Set amplitude of signal\n",
    "nco_f:\n",
    "        set_freq        R1                               # Set the frequency\n",
    "        add             R1, {nco_int_step_freq}, R1      # Update the frequency register\n",
    "        upd_param       200                              # Update settings and wait for time of flight\n",
    "        acquire         0, R2, {integration_length}      # Acquire data and store them in bin_n0 of acq_index.\n",
    "        add             R2, 1, R2                        # Update the step register\n",
    "        nop\n",
    "        jlt             R2, {n_steps}, @nco_f            # Loop over all frequencies\n",
    "        loop            R0, @avg\n",
    "        stop                                             # Stop\n",
    "\"\"\"\n",
    "\n",
    "# Upload sequence\n",
    "module.sequencer0.sequence(\n",
    "    {\n",
    "        \"waveforms\": {},\n",
    "        \"weights\": {},\n",
    "        \"acquisitions\": acquisitions,\n",
    "        \"program\": program,\n",
    "    }\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "176c45f5",
   "metadata": {},
   "source": [
    "We perform the spectroscopy measurement using `%%time` magic command again, so that we can compare the run time of both measurement methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "876a7e18",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.688821Z",
     "iopub.status.busy": "2025-05-07T16:52:02.688073Z",
     "iopub.status.idle": "2025-05-07T16:52:02.734342Z",
     "shell.execute_reply": "2025-05-07T16:52:02.733209Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 8.48 ms, sys: 562 µs, total: 9.05 ms\n",
      "Wall time: 38.5 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "module.delete_acquisition_data(0, \"multi\")\n",
    "module.arm_sequencer(0)\n",
    "module.start_sequencer()\n",
    "module.get_acquisition_status(0)\n",
    "module.store_scope_acquisition(0, \"multi\")\n",
    "data = module.get_acquisitions(0)[\"multi\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca9e4f49",
   "metadata": {},
   "source": [
    "Comparing the run time of performing the same spectroscopy measurement by updating the QCoDes parameters and by sweeping the frequency within the Q1ASM sequence program, we see that the latter is two orders of magnitude faster. We now plot the results, to verify that they are equal to those measured in the first example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "32d49817",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.737967Z",
     "iopub.status.busy": "2025-05-07T16:52:02.737603Z",
     "iopub.status.idle": "2025-05-07T16:52:02.977294Z",
     "shell.execute_reply": "2025-05-07T16:52:02.976797Z"
    }
   },
   "outputs": [
    {
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Ab9Z5gGuvvVaLFi3SokWLJEm7du3SggULtGrVKo0fP16StGnTJi1dulRr1qw5onN8+eWXWrp0qdauXStJ8ng8Ovvss3X66afr1ltvVUxMTN/s8O7ubm3cuFG//OUv9fe//10ZGRkDHvdgM8DT0tJYBBMAAPhcma1NT28p1JNb9qiwufWgY6KCAjVnbxh+0YR0pUSEDnOVAAAAAMayw1kE86gC8P198MEHevDBB/Xaa68pLi5ON998s2666SZZrVZvHP4A3wzAD+ZoA/COjg7l5uaqqqpKUu/Cm9ddd50+//zzfm1R9vf666/rP//5j5544okhn+dw/oMBAAAMB4/Ho7VltXpyyx69sadCde1dBx1nNBh0dlaSvn/cOH17QpqCzLRKAQAAAHBsHU6e6rXvrs6dO1crV67Unj179L3vfU8PPvigMjIy9L3vfU8bNmzw1mn6DKW/t9PplPko3oSFhISoo6Oj7/HOnTs1bdq0AcNvSZo6deoxuV4AAIDhZDAYdGaGVf+48HTVLL1c229apIfOPVkX5WUoJtjSN87t8ejtoipdsfJDJf35Rd3y1nptqGqQl+ZYAAAAAMBR8XrzxszMTP3+979XeXm5HnroIW3atEmzZs3SySefrOeee049PT1eOU9qaqpqamoGHVNVVaX09PQBty9dunTQ/Ts7OxUcHNz3eChhusFgOGQwDwAA4E8MBoMmxUdpyYkTteKSuaq/8wptumGh7jrjOGVEft3+pKWrW3/5cpdO+sfrSn3wJV3x8ho9vGGHNtU0yuV2+/AKAAAAAIxVx2z1opCQEN14443aunWr3n33XSUlJemqq65SRkaGfv3rX6uuru6ojj916lStXr160DGrV6/W1KlTB9y+YsUK2e32AbcXFBQoOzu773F2drby8/MHPWd+fr6ysrIGHQMAAODPjAaDjkuM0bLZM1S05BK9f9W5+t7UHAWbTX1jqlo79EJ+iW59+zPN+Ntrivnjc1rw3Lv6/fptKh6gtzgAAAAAeJvXeoAPRXFxsR555BH94x//UEdHh6644grdeeedmjZt2mEfy+VyadasWTr//PN122239VuQ0m6366mnntIDDzygzZs3KzT04Asz3XbbbWpra9Mf//hHRUdH9/3e4/GopKRE1113na699lpdc801fb8/88wztWjRIi1ZskQWi6XfPjt27NCVV16pe++9VxdccMGQr4Ue4AAAYDSwO7q1fEepXswv1scVdWrrHvhbcccnxeqSvAxdMjFTuTG8/gEAAAAwdD5ZBPNwNDc366KLLtKHH36oyMhINTc3H9FxbDabfvOb3+jNN99UY2NjX6/JqKgozZ49W3fffXffIpxr1qzRD37wA23cuLHvD6Wjo0P33HOPXnjhBbW3t/cd12g0KiEhQUuWLNH111/fr+d3XV2dfvGLX+j999/v1x/cYDAoJSVFP/7xj3XllVce1nUQgAMAgNHG6XZrS22z1pXXam15rdaW1ap2gIU0pyfG6NKJmbr2uFwlh4cMc6UAAAAA/M2IDcBra2v1l7/8RY899phqa2t1/vnn66c//anOPPPM4SphRCIABwAAo53H41FBk10rd5Zq+c5SfVndeMAYk8GgC8en6aaZ43V2VrJMxmPWrQ8AAACAHxtxAfgXX3yhBx54QC+++KKCgoL0/e9/X0uWLFFubu6xPrVfIAAHAABjTXFzq5bvLNXyHSX6vKrhgO0ZkaG6YcZ4XXfcOCUxKxwAAADAfkZEAO50OrV8+XI9+OCD+uyzz5STk6Nbb71V1157rcLDw4/FKf0WATgAABjLSlpa9Y9Ne/T3zbtV1drRb5vJYNCZ6YlaOD5NF45LUw79wgEAAIAxz6cBeENDgx577DH95S9/UVVVlc455xzddtttWrBgQb9e2vgaATgAAEBv3/A3dlfosY27tKqwUgd7kTo5PkoLx6XpwvFpOiEpTgEm2qQAAAAAY41PAvBNmzbpwQcf1HPPPSeTyaRrrrlGt956q/Ly8rxx+FGNABwAAKC/kpZW/e2r3Xo+v1iFza0HHRNgNGpiXKSmJkR/fYuPVmpECBMvAAAAgFFs2AJwt9utlStX6sEHH9S6deuUkZGhJUuW6Prrr1dkZOSRHnbMIQAHAAA4OI/Ho52NNr1aUK5XC8q1vqLuoDPD9zc+JkK3nTRR10zLVVhgwLDUCQAAAGD4DFsA/qc//Un/9V//pblz5+r222/Xt771LRmNfA31cBGAAwAADE1de6fe2F2hd4qqtKWuWbsabXIN8HI20hKgG2aM160nTlR6ZNgwVwoAAADgWBm2ALy1tVX19fXKzs4+0kMcwOPxjLmvrBKAAwAAHBmH06WdjTZtrWvW1rpmfVJRp3Xldf3GmAwGXZSXoSUn5On09EQZx9hrTQAAAGC0GZYAvL29XcnJyXr77bc1a9asIyr0mxoaGpSdna01a9Zo5syZXjmmPyAABwAA8J4ttU368+f5enZbkbpd7n7brGHBWjguTd+ekK6zMq0KMpt9VCUAAACAI3U4eeoR9ysJCQmR2+3WZ599dqSHOMD27dvV3t6usDC+ogoAAIAjMy0xRv+48HSV3Xqp7j5zuhJDg/q21bR16vGvCnTB8+8p/k/P69IVH+jZrYVq6+7xYcUAAAAAjpWjaoFy2mmnKSAgQB988IFX2pbceeedevzxx2Wz2WQymY76eP6CGeAAAADHjsPp0ks7SrR8R4neKapSp9N1wJjQALMuzsvQNdNyNSfTSpsUAAAAYAQbth7gn3/+uc444wwtWrRIP/3pTzVjxowjWgSzsrJSf/3rX3Xvvffq4Ycf1s0333ykJfklAnAAAIDh0dHj1LtFVXplV5le212uxk7HAWPSI0L1vak5unpajsbHRvqgSgAAAACDGbYAXJJWr16te+65Rx9++KEMBoNiYmIUFhY2pBnhPT09amhoUHd3t9LS0vSzn/1szIXfEgE4AACALzjdbn1cXqfnthfp+e3FsjkObIMyKyVe10zL0eWTshQdbPFBlQAAAAC+aVgD8H0qKytVXl6uqqoqtba2Dmkfs9ksq9WqlJQU5ebmyjxGFyEiAAcAAPCtLqdTrxaU66kthXq7sFKub7xEtpiMWjg+XVdPy9G52SkKMB3xUjoAAAAAjpJPAnAcOQJwAACAkaOmrUPPbivSU1sKtbWu+YDtCaFBumZarm45foIyo8J9UCEAAAAwthGA+xkCcAAAgJHH4/Foc22TntpSqGe3Fam+o6vfdqPBoG+PT9OtJ07UnAyrVxaFBwAAAHBoBOB+hgAcAABgZOtxubWqsFJPbdmjVwvK1eN299s+JT5Kt504Sd+dmq2QgLHZ1g8AAAAYLgTgfoYAHAAAwH/UtXfq8Y0FevTLnapu6+y3LTooUDfMGK9bjs9TRlSYjyoEAAAARjcCcD9DAA4AAOB/ul0uvbyzVA9u2KH1FfX9tu1rj3LbiRM1m/YoAAAAgFcRgPsZAnAAAAD/9kVVgx7asEPP5xer29W/PcrUhGgtOSFPF+dlKDYkyEcVAgAAAKMHAbifIQAHAAAYHWrbOvX4VwX6y0Hao5gMBs3OsGrxhHQtmpCu1IhQH1UJAAAA+DcCcD9DAA4AADC6DNYeZZ+TkuO0eEK6rpqaQxgOAAAAHAYCcD9DAA4AADB6fVndoOe3F2vlrjIVNrcesN1kMOiivAzdeuJEnZ6WQL9wAAAA4BBGRADe0NCg9evXq6SkRPX19QoKCtKSJUsUERGh559/XsnJyTrttNNkMpmOxen9CgE4AADA6OfxeLStvkUrd5bq5V2l2lzbfMCY4xKjdesJE/WdKdkKDjD7oEoAAABg5PN5AP6HP/xBv/71r9Xa2qrw8HBFRESoqqpKr7/+uhYsWKDZs2dr7dq1mjNnjl599VWFhYV5uwS/QgAOAAAw9hQ1t+qpLXv01427VNfe1W9bTLBFN8wYp5tn5ikjamy/VgYAAAC+6XDyVKO3T/7WW2/ppz/9qW655RbV19fLZrNp/fr18ng82pe1f/jhh3r//ff1+eef6+GHH/Z2CQAAAMCIlx0drrtnz1DZrZfqmW+foZOS4/q2NXU69H+fbFP2Iyt00Uvv64OSatG5EAAAADh8Xp8BPn/+fHk8Hq1evbrvd5WVlUpLS9Prr7+u888/v+/31157rTZv3qyvvvrKmyX4HWaAAwAAQJI+q6zXQxt26MX8EvW43f22TYmP0pITJuqqqdkKDQzwUYUAAACA7/l0BnhBQYFOPfXUIY3Ny8tTeXm5t0sAAAAA/NLJKfH616IzVXbbJbr7zOlKCgvu27atvkU/fGu9rH9+Qdf8Z63eKayU8xshOQAAAID+vL6yTkVFhRITE4c0NiwsTM3NBy7+AwAAAIxl1rAQ/c+Z0/X/Tpuql3eW6qENO/VJRZ0kqa3bqae3FurprYVKDA3S5ZOy9N0p2ToxOU4Gg8HHlQMAAAAjyzFZWt5oHNrEcl6gAwAAAAMLNJl0xeRsXTE5WxurG/Xolzv10o4S2R09kqTa9i49uGGHHtywQznR4Vo4Pk3fyk3TGemJCjB5/cueAAAAgN/xegBuNpvV09MzpLFOp1Mmk8nbJQAAAACjzsykWP3tW6fp4fNO1pt7KvXstiK9vrtc3a7eNiiFza26/7N83f9ZviItATovJ0UXjkvTeTkpig0J8nH1AAAAgG94PQDPzMxUZWXlkMbW1tYqIyPD2yUAAAAAo1aQ2ayL8jJ0UV6GWrocenlnmf69rUhrSmvk2ru+vc3RoxfyS/RCfolMBoMuGJeqG2eM13k5KTIN8duaAAAAwGjg9Ve/kydP1quvviqn0znoOI/HozfffFNTpkzxdgkAAADAmBAVZNF108fpvavOVf2dV+jfi87UdyZnKzoosG+My+PRqwXl+tYLq5X50HIt+/ArldnafFg1AAAAMHwMHs/eaSJesmXLFh1//PE65ZRTdPvttysrK0udnZ0644wz9MQTT+iUU05ReXm5Hn30Ub355pv68ssvNW3aNG+W4HfsdrsiIyNls9kUERHh63IAAADg55xutz4ur9Nru8v1/PZiVbZ29NtukHReTopuP2mSzslOZm0eAAAA+JXDyVO9HoBL0urVq3XnnXdq69atfS+m953GYDDI4/Fo8uTJuv/++zV//nxvn97vEIADAADgWHG63XprT6We+KpAb+ypkPsbL/9PTI7Tr04/Tt8al0oQDgAAAL/g8wB8n5aWFpWUlMhms/X9Ljw8XFlZWYqOjj5Wp/U7BOAAAAAYDhX2dv1z8x797asCldnb+22bnhijX54+TYvzMmQkCAcAAMAINmICcAwNATgAAACGk8vt1spdZbpn3WZtrm3ut21yfJR+cdo0XToxUwEmFswEAADAyEMA7mcIwAEAAOALHo9Hr+0u16/XbtYX1Y39tqWEh2jJCXm6ceYExQRbfFQhAAAAcCACcD9DAA4AAABf8ng8WlVYqV+v26z1FfX9tgWbTbpmWq5uP2mi8uKifFMgAAAAsJ9hCcDfeecdVVRUHFGB+0tNTdU555xz1MfxZwTgAAAAGAk8Ho8+LK3Rnz/P16sF5frmG4Vzs5N1w4zxunB8mgJNJp/UCAAAAAxLAJ6bm6uioqIDD2gwaCiH3LfCfHZ2tnbv3n0kJYwaBOAAAAAYafY02fXQhh36x+bdaut29tsWHxKk703N0fXTx2lSfJRvCgQAAMCY5dMWKEajUQ8//LBuueWWAcds3rxZP/rRj2S1WvXCCy/INMZnjxCAAwAAYKSydXXr75t266ENO1Riaztg+6yUeF0/fZwum5SpCEugDyoEAADAWHM4eapPlnU/7rjj9J///Edvvvmm/va3v/miBAAAAABDEBkUqDtnTdaeH12kt688W5dNylSg6eu3EZ9W1uuGNz5R4v0v6PKX1+i1gnL1uNw+rBgAAAD4mtlXJ46NjdX555+vf//737rpppt8VQYAAACAITAZjTonJ0Xn5KSosaNL/9pWpL9v2q2tdc2SpC6nSy/ml+jF/BLFBlt0xeQsXTUlWyenxPe1PwQAAACGm09mgO+Tl5en/Px8X5YAAAAA4DDFhgTp9pMmafMNC/X5dd/SrSdOVFyIpW97Y6dDj3yxU6c8+aZO+PvrWrmzVG7vdl4EAAAAhsSnAXh8fLyam5t9WQIAAACAI2QwGHRicpwePPdkVd1+uV6/fJ6umJSlIPPXa/xsrGnURcs/0PQnXtWL+cVyuWmPAgAAgOHj9RYoRqNRLpdrSGP5KiQAAAAwOgSYjLpgXJouGJcmu6NbL+8s1UMbdmpjTaMkaWtdsy5/+UPlxUbql6dP0+WTs2Q2+nQ+DgAAAMYAr7/iTEtLU3V19ZDG1tXVKS0tzdslAAAAAPChCEugrj1unL64/lt644r5Ojklrm/bzkabrvrPWmU9tFw/Xf2FttQ2+bBSAAAAjHYGj8e7zfgWLFig5uZmffrpp4ccO2vWLEVFRWnVqlXeLMHv2O12RUZGymazKSIiwtflAAAAAF7l8Xj0XnG1fr12s9aW1x6wfWpCtK6akq0rJ2crLTLUBxUCAADAnxxOnur1APyjjz7SnDlzdO211+rOO+9Uenq6wsLC+ra3tbWppKRE999/v55++mmtWbNGZ5xxhjdL8DsE4AAAABgrPiyt0R8/3a63CivkdPd/K2KQdGZ6oi6emKmLJqQrJYIwHAAAAAfyaQAuSU8++aR+/vOfq66u7qDbPR6PEhISdN999+naa689qnO1tLTo3nvv1VtvvaWGhgbtu5yYmBjNnj1by5YtU2Ji4oD7X3PNNXrttdcUGBg44Jh58+bp2Wef7Xu8Z88e/exnP9OGDRvU3d3d93uj0aj09HT96le/0gUXXDDkayAABwAAwFjT0NGlF/NL9K9thVpfUX/QMbNS4nVxXoYuzstQVnT4MFcIAACAkcrnAbgkdXZ2ateuXSopKZHNZuv7fWRkpDIzMzVhwgQFBwcf1TlcLpdOOukkLVy4UEuWLFFMTEzfwpo2m01PPvmkHnroIW3ZskUhISEHPcaiRYu0dOlSzZkzZ0jn7O7u1nHHHadf/OIXuvLKK2U2f72OqMfj0aZNm3TRRRfpjTfe0KRJk4Z0TAJwAAAAjGWFTXb9e3ux/rW1UAVN9oOOOT4pVj+cOUHfnZKt4ADzQccAAABgbBgRAfhwWL58uZ577jmtWLFiwDG33XabsrKydMcddxx0++EG4J988omWLVumd955Z8Axv/71rxUaGqo777xzSMckAAcAAAB6J5Rsq2/Rih0lWrGzVNvqWw4YExts0U0zJ+iW4yfQIgUAAGCMOpw81ThMNR0TW7du1dy5cwcdM3/+fG3dutVr5ywpKVFOTs6gY+bMmaOYmBivnRMAAAAYCwwGg6YmRGvZ7BnaetMi7bp5se6dO1MzrbF9Yxo7Hbr34y3KfHi5rnz5Q31acfC2iwAAAIAk+fV3BysqKjRt2rRBxyQnJ6usrMxr5+zu7pbFYhl0zBlnnDHmF/YEAAAAjtb42Ej9/LRp+vlp07ShqkEPfJ6vF/KL5XR75HR79Hx+sZ7PL9ZMa6xumjleV07OVrglwNdlAwAAYAQ5JjPA3W73kG9Hw+VyyWQyDTrGbDbL6XQOOmblypU655xzlJ2drcTERFmtVqWlpen000/Xc889p292iXG73frd736nM844Q8nJybJarbJarcrJydHChQv1xRdfDHo+h8Mhu93e7wYAAABgYCcmx+lfi85U6a2X6penT1N8SFDfto01jbrpzfVKfuAF/fDNT/RVTaMPKwUAAMBI4vUAPCcnRwEBAUO+5ebmeruEwzJp0iSVlJRo2bJl2rRpk2pra1VTU6Pi4mI9+uijevDBB/X888/32+eFF16QwWDQq6++qsrKStXU1Kimpkbbtm3TD3/4Q1188cUqKSkZ8Jy//e1vFRkZ2XdLS0s7xlcJAAAAjA7J4SH69ZyZKrvtEv3jW6fphKSv26O0dTv12MYCzfzbazrpH6/r8Y271NLl8GG1AAAA8DWvL4L53nvvqbKycsDtTqdTa9eu1fPPP68bb7xRF154oc4+++wjOte1116rRYsWadGiRZKkXbt2acGCBVq1apXGjx8vSdq0aZOWLl2qNWvWHNE5vvzySy1dulRr166VJD355JP65z//qQ8//HDAfX73u9+pra1N//u//3vQ7Q6HQw7H1y/E7Xa70tLSWAQTAAAAOAIbqxv12MZdenZbkdp7+n/702Iy6tsT0nX11Bydk52iAJNfL4MEAAAAHd4imF7vAT5//vxDjrn++uv1rW99S9dff71++tOfeu3cEyZMUFFRkdeOJ0kTJ05UYWFhv9/l5eUNus+UKVP07LPPDrjdYrEcso84AAAAgKGZmRSrxy44VX+Yf6L+va1Ij321S1/VNEmSHC63Xswv0Yv5JUoIDdJ3JmfruunjNDUh2sdVAwAAYDj4bPrDJZdcouzsbP3ud7874mMMpb+30+mU2XzkOX9ISIg6Ojr6/S44OPiQ+7S3tx/xOQEAAAAcvnBLgG46foK+vP5CfXH9t3TbiRMVF/L1xJO69i79+fN8TXv8Pzr72be1qrDigPV+AAAAMLr49Pt/c+fO1apVq454/9TUVNXU1Aw6pqqqSunp6QNuX7p06aD7d3Z29gu8Q0ND1dXVdch9QkJCBh0DAAAA4NgwGAw6PilOD5x7sqpuv1yvXjZPF+dlKHC/9ifvFVdrwXPvadrj/9GTm3fL4XT5sGIAAAAcKz4NwK1W66D9wg9l6tSpWr169aBjVq9eralTpw64fcWKFbLb7QNuLygoUHZ2dt/j7Oxs7d69e9Bz7tixo98+AAAAAHwjwGTUhePTtPySuapeerkePPdk5USH923fVt+i77/2sTIfXq57121RUyeLZgIAAIwmPg3Ag4ODDzmbejCLFi1SRUWF7rrrLjU2Nvb7+qLdbtdDDz2kN954QzfeeOOAx1i8eLGWLl2q5ubmfr/3eDwqLi7W0qVL++0/Y8YMtbe36y9/+Yu6u7v77eN2u7Vu3To9+OCDuvrqq4/4ugAAAAB4X0ywRbeeOFG7bl6sFZfM1ampCX3bato69d9rNirtwZd066pPVdTc6sNKAQAA4C0+DcAbGhqUnJx8xPubTCa999576uzs1OzZs5WcnCyr1Sqr1aqTTjpJ27Zt07p16xQaGipJWrNmjXJzc/vN+L7vvvtktVp1wgkn9O1rtVqVkpKixYsX67vf/W6/MNtoNGrlypXasGGD8vLy+u2TlpamX/7yl3rqqac0fvz4I/+DAQAAAHDMmIxGXZSXoY+vPV8fX3O+LsrLkGHvto4epx7+YqfGPfqyLl3xgT6tqPNprQAAADg6Bo8PV30599xz1d3drQ8++MBXJYwIdrtdkZGRstlsioiI8HU5AAAAwJizp8muP3+er39u3qOOHme/baemJug7U7J0QW6qMqPCBzgCAAAAhsvh5Kk+CcDb2tp0//33a9myZVq+fLkWL1483CWMKATgAAAAwMjQ2NGlv27cpYc27FBt+4HtGifFRemCcam6IDdVp6YmKMDk0y/VAgAAjEk+DcBnz56t4uLiAbe3tbXJZrMpMDBQP/vZz7Rs2TJvnt4vEYADAAAAI0uX06l/byvWHz/drvyGloOOiQoK1OWTMnXnyZM1PjZyeAsEAAAYw3wagP/zn/9UWVnZgNsjIiKUmZmpk08++aj6f48mBOAAAADAyOTxeLS5tklv7KnQG3sq9GlFvb75BsogaeH4NP3XrCk6LS1BBoPhYIcCAACAl4z4FijojwAcAAAA8A8NHV1aVVipN3ZX6PU95Wrr7t8v/KTkOP3XrClanJcus5H2KAAAAMcCAbifIQAHAAAA/E9Ll0NPfLVbD3yer8rWjn7bksKCtXhChi7KS9eZ6VZ6hQMAAHiRTwPwjo4OhYSEHLPxoxEBOAAAAOC/ul0uvbC9RH/4dJu21DUfsD0m2KKF49J0UV6Gzs5OUpDZ7IMqAQAARo/DyVO9Pg0hNTVV//73v4c09plnnlF6erq3SwAAAACAYRNoMul703K06YaFevc752jh+DRZ9pvx3dTp0JNb9mjhi6uVeP8LWrLqU22vPzAoBwAAgPd5fepBS0uLWlpahjS2oKBAoaGh3i4BAAAAAIadwWDQ/Oxkzc9OVqujR28VVmjlzrJ+vcLtjh498sVOPfLFTp2Znqibj5+gi/IyFGgy+bh6AACA0cmn371bs2aNxo0b58sSAAAAAMDrwi0BumxSli6blKUup1Ori6u1fEepXtxRoo6e3jD8o7JafVRWq4TQIF1/3Dh9f/o4jYuhJSIAAIA3eSUAd7vdkqR97cTdbnff776po6ND5eXlevjhh/XJJ59o1apV3igBAAAAAEakILNZF4xL0wXj0nT/OSfq6S2F+suXu7Sz0SZJqmvv0m8/2arffrJVp6TG6+qpObpsUpZigi0+rhwAAMD/HfUimE8++aSuu+46GQwGSb0h+L6fBxMVFaV77rlHN99889GcflRgEUwAAABgbPF4PPqwtEaPfrlLK3eVyunu/7Ys0GTUhePS9L2pOVqQm0KLFAAAgP0cTp561AF4bW2t3n77bXk8Hnk8Hl133XW66qqrNG/evIOODw0NVWZmpvLy8hQWFnY0px41CMABAACAsau6tUPPbivSU1v2aFt9ywHbIywBunBcmi6ZmKFzs1MUHODTTpYAAAA+N6wB+DcZjUY9/PDDuuWWW7x52FGNABwAAACAx+PR5tomPbO1SM9uK1Rte9cBY0IDzDo/N1UX52XognGpCgsM8EGlAAAAvuXTAPyee+7RZZddpvHjx3vzsKMaATgAAACA/Tndbr1bVKV/byvSa7vLZXP0HDAmJMCsiyak6+ppuTor0yqT0eiDSgEAAIafTwNwHD4CcAAAAAAD6Xa5tLq4Wit2luqVXWVq7HQcMCY5PERXTcnW1dNyNDk+2gdVAgAADB8CcD9DAA4AAABgKJxutz4qrdWLO4r1Qn6JWrq6DxhzfFKsrp8+Tt+ZnK3IoEAfVAkAAHBsDVsAftddd+njjz/W5ZdfrhtuuEGSlJ+fr5qamiEfw2q1atKkSUdawqhAAA4AAADgcDmcLr2+u1xPby3Um3sq5HT3f2sXEmDWZRMz9YMZ43RqaoIMBoOPKgUAAPCuYQvAAwMD5XQ6NXXqVG3evFmSlJSUpNra2iEfIzExUdXV1UdawqhAAA4AAADgaNS3d+n5/GI9tWWPvqxuPGD7xLhI/WD6eH1nSpasYSE+qBAAAMB7hi0A//vf/65PPvlEixcv1re+9S1Jks1mU0tLy5CPERUVpcjIyCMtYVQgAAcAAADgLZtqGvW3Tbv1r62FByyeaTQYdE52sq6akq1FE9IVGhjgoyoBAACOHD3A/QwBOAAAAABv6+hxasWOUj3xVYHWlh/4Ld3QALMuysvQVVOyNTczSQEmow+qBAAAOHwE4H6GABwAAADAsbSr0aantxTq2W2FKrW1H7A9whKg+VnJWpCTogU5KUqJCPVBlQAAAEPjNwF4VVWV3n//fV111VW+KmFEIAAHAAAAMBzcHo8+Lq/TM1sL9WJ+8QEtUvaZmhCtBTkpunxSlmYmxQ5zlQAAAIPzmwD8/vvv11133SW73e6rEkYEAnAAAAAAw63L6dSbeyq1fEeJ3imqUmOn46DjTk9L0O0nTdKiCekyG2mTAgAAfO9w8lTzMNV0UBs2bFBWVpYvSwAAAACAMSnI3NsD/KK8DLncbn1R3ai39lTorcJKbahq0L6ZUuvK67SuvE7pEaFacuJE/WD6OEUHW3xaOwAAwFAd8Qzwv/3tbyorKzuikzocDm3btk2rVq3SE088oeuuu+6IjjNaMAMcAAAAwEhS396ll3eW6sENO5Tf0NJvW0iAWd+dkq2rpmTr9PREGQ0G3xQJAADGrGFpgTJ37lyVlJQcya4KCgpSVlaWvv/97+vSSy89omOMJgTgAAAAAEYij8ej94qr9cDn+XpjT8UB21PDQ3TF5Cx9Z0q2pifGyEAYDgAAhoHf9ABHLwJwAAAAACNdQaNND23YoX9u3qP2HucB2/NiI3Xl5CxdOSVb42J4XwMAAI4dAnA/QwAOAAAAwF+0dffoP7vK9Nz2Yr1dVCmn+8C3lCcmx+k7k7N0+aQsJYWH+KBKAAAwmhGA+xkCcAAAAAD+qKGjS8t3lOi57cX6qKz2gO0GSXMzk3Tl5Cydk52s9Miw4S8SAACMOgTgfoYAHAAAAIC/K7e16/n8Yj23vUhf1TQddExmZJjOTE/U7AyrzkxPVE50OH3DAQDAYRsRAXhlZaU+++wzFRcXy2az9f0+MjJSWVlZOvnkk5WSknIsTu13CMABAAAAjCY7Glr03LbeMHxPc+uA45LDQ3RBbqqumJSl2RmJMhmNw1glAADwVz4PwH/1q1/pD3/4gxwOh2JiYhQeHt63rbW1VU1NTbJYLPrJT36i//3f//X26f0OATgAAACA0cjj8eiL6ka9vrtcH5XV6tPKenU5XQcdmxgapEsnZurySVk6NS1BRmaGAwCAAfg0AF+xYoUuvfRSLVu2THfccUe/8HuftrY2/elPf9Ldd9+tF198URdffLE3S/A7BOAAAAAAxgKH06UNVQ36qKxWH5bVaF15nTp6nAeMSw0P0fem5uj2kyYpMSzYB5UCAICRzKcB+Jw5cxQYGKh33nnnkGPPPfdcORwOrVmzxpsl+B0CcAAAAABjUXt3j97YU6EX8kv0xu5yOVzuftuDzCZdP32cfjJrijKiWEATAAD0Opw81esN1vbs2aNZs2YNaeysWbO0Z88eb5cAAAAAAPADoYEBumxSllZcMld1d16hZ759hi7ITZXZ2Nv+pMvp0iNf7FTuoyt07atrtbOhxbcFAwAAv2P29gGrqqqUkJAwpLFxcXGqrq72dgkAAAAAAD8TYQnUVVNzdNXUHFW1duhPn23XX7/cpfYep5xuj57aUqintxTq2xPSdc20HJ2Xk6Igs9ff0gIAgFHG668WzGazenp6hjTWyArfAAAAAIBvSA4P0R/mn6ifnzpVD23YoQc37FBzV7c8kl7ZVaZXdpUpwhKgxRPSdcXkLM3LTFaAifeXAADgQF4PwOPi4lRbW+vtwwIAAAAAxpjYkCAtmz1DP541RY9/tUt//HS7qts6JUl2R4+e2lKop7YUKjbYoovyMnRmeqJOSo5TbkyEjAaDj6sHAAAjgdcD8JNOOkkbN2709mEBAAAAAGNUuCVAP541RbedOEmrS6r0/PZirdxVJruj99vHjZ0OPfFVgZ74qkCSFBUUqBOT4nRySpxOSo7XWZlWhQYG+PISAACAj3g9AL/xxht14YUXaseOHZo4caK3Dw8AAAAAGKMCTEadl5Oq83JS9VenU6sKK/X89mK9WlCuTqerb1xLV7feLa7Su8VVkqRIS4Cumz5Otxyfp9yYCF+VDwAAfMDrAfipp56qq6++Wuecc45+85vf6JRTTpHJZDro2Pr6eklScXGxPB5P3++joqIUExPj7dIAAAAAAKNEkNmsRRMytGhChtq6e7S+ol6fV9Xr86oGfVZZr9r2rr6xNkeP7v8sX3/+LF8LclO15IQ8nZuTQpsUAADGAINn/+TZC6xWq+rq6r4+wSAvKPadev8xHo9HCQkJqqmp8WZZI5rdbldkZKRsNpsiIpiNAAAAAABHw+PxqNzers+rGvT67nI9v71YDpe735jc6HDdOHOCvjM5SykRoT6qFAAAHInDyVO9HoDv2LGjXwB+JBISEsZU+xQCcAAAAAA4dho6uvT3Tbv16Bc7VWZv77fNIGleVpKumpKji/IyFG6hVzgAACOdTwNwHD4CcAAAAAA49lxut17fXaGHv9ih94qrD9gebDZp0YR0XTU1R+dkJ8tsNPqgSgAAcCgE4H6GABwAAAAAhtfuJrue3Vqof20rUmFz6wHbE0KDdMWkLF01NUcnJMUO2t4TAAAMLwJwP0MADgAAAAC+4fF49GllvZ7ZWqgX8kvU1Ok4YMyE2AhdNSVH352SrazocB9UCQAA9kcA7mcIwAEAAADA97pdLq0qrNQzWwv1WkH5AQtnStLxSbG6aEKGFuela2Jc1PAXCQAAfB+Af/zxx/rjH/+orVu3qqqqSl1dXQOOzcnJUUFBgbdL8CsE4AAAAAAwsrR0ObR8R6n+tbVQH5bVHnRMXmykFk9I10V5GTqeNikAAAwbnwbgq1ev1tlnn63MzExddtllSk1NVXBw8IDjU1NTde655x7VOVtaWnTvvffqrbfeUkNDg/ZdUkxMjGbPnq1ly5YpMTFxwP2vueYavfbaawoMDBxwzLx58/Tss88espY//OEPKi8v1wMPPDDk+gnAAQAAAGDkKm1p07+3F+mlHSX6qqbpoGOmxEfpthMn6btTsxUSYB7mCgEAGFt8GoCfccYZstls+vzzzxUUFOTNQx+Uy+XSSSedpIULF2rJkiWKiYnp+9TdZrPpySef1EMPPaQtW7YoJCTkoMdYtGiRli5dqjlz5hxVLatWrdLixYt1+eWX68knnxzyfgTgAAAAAOAfSlpatXJXmVbuLNO68lp98w11dFCgbpgxXrccn6eMqDCf1AgAwGh3OHmq0dsn37lzpy666KJhCb8laeXKlcrMzNRdd92l2Nj+XzmLjIzU7bffrvPPP1+PPfbYMa2jpKREN998s5YtW3ZMzwMAAAAA8J3MqHDdcfJkfXTNAlUvvVyPn3+qTk1N6Nve3NWt363fpuxHVuji5R/o3aIqudwH9hIHAADDw+vfy2psbFR8fLy3DzugrVu3au7cuYOOmT9/vl555ZVjVkNnZ6cuueQS/f73v5fZbNaOHTuO2bkAAAAAACNDYliwbpg5XjfMHK8vqhr00IYdej6/WN0ut9wej17eWaqXd5YqKSxYV0zO0lVTcjTDGkOvcAAAhpHXZ4AHBwertbXV24cdUEVFhZKSkgYdk5ycrLKysmNyfo/HoyVLlmj27Nm65JJLjsk5AAAAAAAj2wnJcXrq22eo7NZLdfeZ02UN+3otrOq2Tt3/Wb6O//trmvTXV/SbdZtV0jJ875sBABjLvB6AT5gwQfn5+d4+7IBcLpdMJtOgY8xms5xO56BjVq5cqXPOOUfZ2dlKTEyU1WpVWlqaTj/9dD333HMaqFX63/72NxUUFOi+++4bcs0Oh0N2u73fDQAAAADg/xLDgvU/Z05X6a2X6KWL52jRhHQFGL9+672z0aZfrvlK2Q+v0MIXVuudwkq5vbs0FwAA2I/XW6Dceeeduu6663TDDTfojDPO8Pbhj4lJkyZp+/btWrZsmaZMmdLXON3pdCo/P1833XSTJOnKK6/st9+GDRt0zz33aP369QoICBjy+X7729/q7rvv9t4FAAAAAABGlECTSZdMzNQlEzPV1OnQ8h0l+tfWIq0tr5UkeSS9trtcr+0u17iYCP3ohDxdOy1XkUGBvi0cAIBRxusB+FVXXSWXy6V58+ZpxowZysrKUkhIyIDjMzIydNddd3nt/Lt27dKCBQu0atUqjR8/fkj73HvvvQf9vdls1rRp0/Twww9r6dKl/QLwhoYGXX755XrqqaeUnJx8WDX+/Oc/15133tn32G63Ky0t7bCOAQAAAADwDzHBFt04c4JunDlBpS1temZroR7buEsVrR2SpN1Ndi1953P99wcb9Z0p2Vo0IV1zMqwKCfD6W3YAAMYcr/9rWl9frz//+c9yOp0qKyuTy+VScHDwgOMP1ZrkcE2YMEFFRUVePebEiRNVWFjY99jlcunKK6/UD3/4Q82ZM+ewj2exWGSxWLxYIQAAAADAH2REhemXZxyn/3faVL1aUK6HN+zQB6U1kqT2Hqee+KpAT3xVIIvJqNkZVi3ISdF5OSmaEBvJ4pkAABwBrwfgP/7xj7V792698847mj9/vrcPf4Ch9Pd2Op0ym4/8UkNCQtTR0dH3+H/+538UGhqqn/zkJ0d8TAAAAADA2GU2GnVRXoYuysvQ9vpmPfLFTj29pVDtPb3vbx0ut94pqtI7RVW6490NyowM0/XTx+mWE/IUE8yEKgAAhsrrAfjbb7+t6667bljCb0lKTU1VTU3NoGOqqqqUnp4+4PalS5fqz3/+84DbOzs7+2axd3Z26q9//asMBoOSkpIOOra7u1tr1qzR5s2bFRkZObQLAQAAAACMSZPjo/XoglP0f2edoPeKq7SqsFJvFVaq3N7eN6bE1qZfffiV7vtkq66fPk53nDxJmVHhPqwaAAD/YDz0kMNTX1+vcePGefuwA5o6dapWr1496JjVq1dr6tSpA25fsWKF7Hb7gNsLCgqUnZ0tSQoODlZjY6MaGhpUU1NzwO2BBx7QTTfdpJKSEsJvAAAAAMCQhVsCtDgvQ49dcKpKb71E229apD/OP1Hzs5Jk3Nv+pL3HqQc37FDuIy/rOys/1Fc1jT6uGgCAkc3rAbjZbJbb7fb2YQe0aNEiVVRU6K677lJjY6M8Hk/fNrvdroceekhvvPGGbrzxxgGPsXjxYi1dulTNzc39fu/xeFRcXKylS5cOuj8AAAAAAN5kMBg0KT5Kd86arHe/e65233KRlpyQp2CzSZLk8nj03PZizfzbazrln2/o/s+2q9zWfoijAgAw9ng9AM/OzlZZWZm3Dzsgk8mk9957T52dnZo9e7aSk5NltVpltVp10kknadu2bVq3bp1CQ0MlSWvWrFFubm6/Gd/33XefrFarTjjhhL59rVarUlJStHjxYn33u9/V1VdfPaR6wsPDFR7O19AAAAAAAN6THR2uh86bpbLbLtXdZ05XXMjXfcA/razXne9uUPpDLxGGAwDwDQbP/lOmveBPf/qTHnjgAe3cubOvbzYGZ7fbFRkZKZvNpoiICF+XAwAAAAAY4Tp6nHpqyx795ctd2lrXfNAxp6Ym6LtTsnXZpEzFhQQNc4UAABw7h5Onej0A37Ztm5YsWaLa2lr96Ec/UmZmpkJCQgYcn5iYqMmTJ3uzBL9DAA4AAAAAOFI7G1r00o5SvbSj5KBhuNlo0IKcVF01NVsXjktTcIDZB1UCAOA9Pg3ArVar6urqhjw+MTFR1dXV3izB7xCAAwAAAAC8YV8Y/kJ+sbbXtxywPTwwQBfnZeiqqdmak2GVyej1zqgAABxzPg3AbTabWlpahjw+KipKkZGR3izB7xCAAwAAAAC8yePxaEtds57dVqR/bytSZWvHAWOSw0N05eQsXTUlW8clxshgMPigUgAADp9PA3AcPgJwAAAAAMCx4nK79WFprZ7dVqTlO0tkd/QcMGZSXJSumpqtq6fmKCUi1AdVAgAwdATgfoYAHAAAAAAwHDp7nHp9d4X+ta1Qb+2pVI/b3W+70WDQBbmp+sGMcTo/N1VmWqQAAEYgvwjAOzs79eKLL6qgoEC/+c1vfFHCiEEADgAAAAAYbo0dXXppR4n+tbVIH1ccuJZXcniIvj8tV9dPH6es6HAfVAgAwMGN6AB8+/bteuyxx/TMM8/Ibrfrkksu0QsvvDCcJYw4BOAAAAAAAF8qbm7Vk1v26B+bdqviIP3CT01N0MLxafr2+DTlxUUNf4EAAOxnxAXgXV1devHFF/X4449r/fr1io6O1vXXX6+bb75ZmZmZx/r0Ix4BOAAAAABgJHC53VpVWKknvirQ67sr5DpIZDA+JkILx6dp4fh0nZoaLxNtUgAAw2zEBOD5+fl6/PHH9fTTT6ulpUUGg0H//d//rV/84hcKCgo6Vqf1OwTgAAAAAICRprq1Q09u2aN/bS1SfkPLQcckhAbpkrxMXT4pU6elJRCGAwCGhU8DcIfDoZdeekmPPfaYPvnkEwUFBem73/2uLrzwQn3729/W66+/rvPPP9+bp/R7BOAAAAAAgJFsT5NdrxaU69WCMq0tr5P7IFFCUliwLp2YqcsnZWlWaryMBoMPKgUAjAU+CcB37tzZN9u7qalJEyZM0M0336xrrrlGkZGRqqysVFpaGgH4QRCAAwAAAAD8RWNHl97cU6mVu0r1VmGlupyuA8YkhQVrbkaS5mRYNSfTqtzocBkIxAEAXnI4ear5aE7U3d2t5cuX67HHHtO6detkNBq1ePFi3XzzzZo7d+7RHBoAAAAAAIxAsSFB+t60HH1vWo5aHT16bXe5Xsgv1qrCSnW73JKk6rZO/Xt7kf69vUiSlBIeojkZVp2VmaTFE9IVHWzx5SUAAMaQo5oBnpeXp927d8tisej//b//pxtuuEFJSUkHHcsM8IExAxwAAAAA4O9sXd36T0GZXtpRog9KatTe4zzouECTUQvHp+nqqbk6LydFASb6hgMADs+wzQC/8MIL9eijj6qzs1P/+te/FBERoWuuuUbR0dFHc1gAAAAAAOBnIoMCdfW0XF09LVc9Lre+rG7QB6U1WlNao3XlderYG4h3u9xavqNUy3eUKiE0SN+ZnK2rp+VoemIMbVIAAF531D3AbTabnnnmGT3++OPatm2bgoODdeWVV+qWW27RzJkz+8YxA3xgzAAHAAAAAIxm3S6XNlQ1aPmOUj27rUj1HV0HjJmaEK2rp+bou1OylRQe4oMqAQD+wieLYErS+vXr9dhjj+nFF1+Uw+HQCSecoB/96Ee67LLL1NjYSAA+AAJwAAAAAMBY0eNy6+2iSj29pVD/KSjr6xu+j9Fg0LnZybp6Wo6+PT5dwQFH9eV1AMAo5LMAfJ+WlhY9/fTTeuKJJ7R9+3bFxMTo29/+tp588km99tprBODfQAAOAAAAABiLmjsdeiG/WE9vLdT6ivoDtkdYArRwXJoW5Kbq7KxkxYcG+aBKAMBI4/MAfH8ff/yxHnvsMb300ktyOBw66aST9OMf/1iLFy+W2cynuBIBOAAAAAAABY02PbO1UE9vKVSZvf2A7QZJJyTH6bzsFJ2Xk6KTUuJkNrKAJgCMRSMqAN+nublZTz/9tB5//HHt2LFDVqtVN910k2644QYlJycPRwkjFgE4AAAAAAC93B6PPiqt0VNbCrV8Z4naup0HHRcbbNG3x6fr4okZmp+VpECTaZgrBQD4yogMwPe3du1aPfbYY1qxYoVCQ0PV0NAw3CWMKATgAAAAAAAcqNvl0ifldXqrsFKrCiu1pa75oOP2tUq5eGKGzs1OoW84AIxyIz4A36epqUmlpaWaMWOGr0oYEQjAAQAAAAA4tKrWDr1dWKk3Cyv01p5KtfccODs8NMCs83NTdXFehi4Yl6qwwAAfVAoAOJb8JgBHLwJwAAAAAAAOT2ePU+8UVWnFzlK9WlAmm6PngDEWk1Hn5aTo4rxMXTg+VVFBFh9UCgDwNgJwP0MADgAAAADAket2ubS6uFordpbqlV1laux0HDDGbDTohKQ4nZ6WoNPTEnVaWoLiQoJ8UC0A4GgRgPsZAnAAAAAAALzD6Xbro9JardhZqpd3laqmrXPAsXmxkTo9LUELclO1IIfe4QDgLwjA/QwBOAAAAAAA3uf2ePRJeZ1W7CzVW4UV2tVoH3BseGCAFk1I1+WTMnV2drICTaZhrBQAcDgIwP0MATgAAAAAAMdefXuXPqmo09ryWq0rr9WX1Y1yug+MRaKDAnVxXoa+PSFdp6YmKCaY3uEAMJIQgPsZAnAAAAAAAIZfR49TH5bW6MX8Eq3cVXrQhTQlaWJcpE5NTdBpqQk6NS1B42MiZDAYhrlaAMA+BOB+hgAcAAAAAADfcjhderuoUs9vL9arBeVq73EOODYuxKLZ6VbNzbRqToZVk+KiCMQBYBgRgPsZAnAAAAAAAEaOjh6n3i6s1Edltfqkok4baw7eKmWf+JAgzc5I1JwMq05MitPUhGgW1ASAY4gA3M8QgAMAAAAAMHJ19Dj1RVWDPq6o08fldVpXXjtguxRJMhkMmhwfpZnWWB2fFNt3bzGzsCYAeAMBuJ8hAAcAAAAAwH+43G5trm3WmtIarSmt0UdlNYMG4pIUbDbpzPREnZ2drPlZyZqaEC0jbVMA4IgQgPsZAnAAAAAAAPyXy+3WptomfVJ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",
      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_0 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) / integration_length\n",
    "data_1 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(freq_sweep_range, data_0, data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddf1a5d2",
   "metadata": {},
   "source": [
    "### Signal Attenuation\n",
    "\n",
    "The QRM-RF module provides the possibility of attenuating both the output and input signals. The attenuation values can be set within the range from $0$ to $60$ dB, in $2$ dB steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c7166171",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:02.980457Z",
     "iopub.status.busy": "2025-05-07T16:52:02.980306Z",
     "iopub.status.idle": "2025-05-07T16:52:03.185009Z",
     "shell.execute_reply": "2025-05-07T16:52:03.184589Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x700 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Output Attenuation (dB)\n",
    "module.out0_att(4)\n",
    "\n",
    "# Input Attenuation (dB)\n",
    "module.in0_att(0)\n",
    "\n",
    "# Fast NCO frequency sweep\n",
    "module.delete_acquisition_data(0, \"multi\")\n",
    "module.arm_sequencer(0)\n",
    "module.start_sequencer()\n",
    "module.get_acquisition_status(0)\n",
    "data = module.get_acquisitions(0)[\"multi\"]\n",
    "\n",
    "data_0 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) / integration_length\n",
    "data_1 = np.asarray(data[\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]) / integration_length\n",
    "\n",
    "# Plot amplitude/phase results\n",
    "plot_spectrum(freq_sweep_range, data_0, data_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8b89c79",
   "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": 24,
   "id": "e62d40fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:52:03.188554Z",
     "iopub.status.busy": "2025-05-07T16:52:03.188410Z",
     "iopub.status.idle": "2025-05-07T16:52:08.940895Z",
     "shell.execute_reply": "2025-05-07T16:52:08.939354Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "\n",
      "Snapshot:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module8:\n",
      "\tparameter                        value\n",
      "--------------------------------------------------------------------------------\n",
      "connected                         :\tTrue \n",
      "in0_att                           :\t0 (dB)\n",
      "in0_offset_path0                  :\t0 (V)\n",
      "in0_offset_path1                  :\t0 (V)\n",
      "marker0_exp0_config               :\tbypassed \n",
      "marker0_exp1_config               :\tbypassed \n",
      "marker0_exp2_config               :\tbypassed \n",
      "marker0_exp3_config               :\tbypassed \n",
      "marker0_fir_config                :\tbypassed \n",
      "marker0_inv_en                    :\tFalse \n",
      "marker1_exp0_config               :\tbypassed \n",
      "marker1_exp1_config               :\tbypassed \n",
      "marker1_exp2_config               :\tbypassed \n",
      "marker1_exp3_config               :\tbypassed \n",
      "marker1_fir_config                :\tbypassed \n",
      "marker1_inv_en                    :\tFalse \n",
      "marker2_exp0_config               :\tbypassed \n",
      "marker2_exp1_config               :\tbypassed \n",
      "marker2_exp2_config               :\tbypassed \n",
      "marker2_exp3_config               :\tbypassed \n",
      "marker2_fir_config                :\tbypassed \n",
      "marker3_exp0_config               :\tbypassed \n",
      "marker3_exp1_config               :\tbypassed \n",
      "marker3_exp2_config               :\tbypassed \n",
      "marker3_exp3_config               :\tbypassed \n",
      "marker3_fir_config                :\tbypassed \n",
      "out0_att                          :\t4 (dB)\n",
      "out0_exp0_config                  :\tbypassed \n",
      "out0_exp1_config                  :\tbypassed \n",
      "out0_exp2_config                  :\tbypassed \n",
      "out0_exp3_config                  :\tbypassed \n",
      "out0_fir_config                   :\tbypassed \n",
      "out0_in0_lo_en                    :\tTrue \n",
      "out0_in0_lo_freq                  :\t4950000000 (Hz)\n",
      "out0_in0_lo_freq_cal_type_default :\toff (Hz)\n",
      "out0_latency                      :\t0 (s)\n",
      "out0_offset_path0                 :\t5.5 (mV)\n",
      "out0_offset_path1                 :\t5.5 (mV)\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_module8_sequencer0:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq                      :\tin0 \n",
      "connect_out0                     :\tIQ \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                     :\tTrue \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tTrue \n",
      "marker_ovr_value                 :\t3 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tTrue \n",
      "nco_freq                         :\t2.5e+08 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tTrue (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",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module8_sequencer1:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq                      :\toff \n",
      "connect_out0                     :\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_freq_cal_type_default        :\toff (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",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module8_sequencer2:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq                      :\toff \n",
      "connect_out0                     :\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_freq_cal_type_default        :\toff (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",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module8_sequencer3:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq                      :\toff \n",
      "connect_out0                     :\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_freq_cal_type_default        :\toff (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",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module8_sequencer4:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq                      :\toff \n",
      "connect_out0                     :\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_freq_cal_type_default        :\toff (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",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module8_sequencer5:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq                      :\toff \n",
      "connect_out0                     :\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_freq_cal_type_default        :\toff (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",
      "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 both sequencers.\n",
    "module.stop_sequencer()\n",
    "\n",
    "# Print status of both sequencers (should now say it is stopped).\n",
    "print(module.get_sequencer_status(0))\n",
    "print(module.get_sequencer_status(1))\n",
    "print()\n",
    "\n",
    "# Print an overview of the instrument parameters.\n",
    "print(\"Snapshot:\")\n",
    "module.print_readable_snapshot(update=True)\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  }
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