{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e67f6639",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "# Numerically Controlled Oscillator - Additional Features\n",
    "\n",
    "In this tutorial we will demonstrate the use of the NCO to carry out some novel experiments. This will be a review of some of the more advanced protocols one can carry out with the Q1 sequencer and the NCO. We will demonstrate the following experiments:\n",
    "\n",
    "1. Chirping the frequency of a pulse e.g for rapid spectroscopy measurements\n",
    "2. Phase updates e.g for virtual $Z$ gates\n",
    "\n",
    "We will show these functionalities using a QRM and directly connecting outputs $\\text{O}^{[1-2]}$ to inputs $\\text{I}^{[1-2]}$ respectively. We will then use the QRM's sequencers to sequence waveforms on the outputs and simultaneously acquire the resulting waveforms on the inputs."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66292f41",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "First, we are going to import the required packages and connect to the instrument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f2735ffe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:37.387490Z",
     "iopub.status.busy": "2024-03-28T14:37:37.387490Z",
     "iopub.status.idle": "2024-03-28T14:37:38.961534Z",
     "shell.execute_reply": "2024-03-28T14:37:38.960116Z"
    }
   },
   "outputs": [],
   "source": [
    "\n",
    "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",
    "from scipy.signal import spectrogram, welch\n",
    "from scipy.signal.windows import gaussian\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 QcmQrm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e62e73ec",
   "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": "925f190d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:38.966084Z",
     "iopub.status.busy": "2024-03-28T14:37:38.965083Z",
     "iopub.status.idle": "2024-03-28T14:37:40.996601Z",
     "shell.execute_reply": "2024-03-28T14:37:40.995612Z"
    }
   },
   "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": "908445a1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:41.001143Z",
     "iopub.status.busy": "2024-03-28T14:37:41.001143Z",
     "iopub.status.idle": "2024-03-28T14:37:41.011885Z",
     "shell.execute_reply": "2024-03-28T14:37:41.010864Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "070b5285",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0687cfca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:41.017245Z",
     "iopub.status.busy": "2024-03-28T14:37:41.016241Z",
     "iopub.status.idle": "2024-03-28T14:37:41.941249Z",
     "shell.execute_reply": "2024-03-28T14:37:41.940737Z"
    },
    "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": "57e0b45c",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7f77bd41",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:41.946490Z",
     "iopub.status.busy": "2024-03-28T14:37:41.946490Z",
     "iopub.status.idle": "2024-03-28T14:37:41.957405Z",
     "shell.execute_reply": "2024-03-28T14:37:41.956377Z"
    }
   },
   "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": "9ae60341",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:41.962243Z",
     "iopub.status.busy": "2024-03-28T14:37:41.961263Z",
     "iopub.status.idle": "2024-03-28T14:37:42.079801Z",
     "shell.execute_reply": "2024-03-28T14:37:42.077804Z"
    }
   },
   "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": "1edb55b2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:42.084348Z",
     "iopub.status.busy": "2024-03-28T14:37:42.084348Z",
     "iopub.status.idle": "2024-03-28T14:37:42.095061Z",
     "shell.execute_reply": "2024-03-28T14:37:42.093120Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "readout_module = readout_modules[4]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f30b6a1e",
   "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": 8,
   "id": "5dd27dd8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:42.099784Z",
     "iopub.status.busy": "2024-03-28T14:37:42.099784Z",
     "iopub.status.idle": "2024-03-28T14:37:45.530450Z",
     "shell.execute_reply": "2024-03-28T14:37:45.528865Z"
    },
    "lines_to_next_cell": 2
   },
   "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": "9ff50fce",
   "metadata": {},
   "source": [
    "## Frequency chirps\n",
    "\n",
    "Frequency chirps constitute a fast frequency sweep using the Q1ASM to change the NCO frequency in real time during playback. To do this, we first set up the QRM for continuous wave output and a single scope acquisition. This is significantly faster than a spectroscopy measurement but also limits the maximum number of points we can measure in a single program. The total duration of the sweep must be 16384 ns or less, as that is the maximum length of a scope acquisition."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "753334d3",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "In this tutorial, we will analyze the raw data measured by the scope acquisition of the QRM. For this we will define a simple helper function using [scipy.signal.spectrogram](https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.spectrogram.html) and [scipy.signal.welch](https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.welch.html). The spectrogram shows the frequency spectrum of the QRM output as a function of time, to visualize the frequency sweeps we are doing. Welch's method is used to compute the input power as a function of frequency (power spectral density). This way we obtain the response of the system to find features of interest, e.g. a resonance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b0eab9a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.535538Z",
     "iopub.status.busy": "2024-03-28T14:37:45.534512Z",
     "iopub.status.idle": "2024-03-28T14:37:45.545403Z",
     "shell.execute_reply": "2024-03-28T14:37:45.544310Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# Power as function of frequency and time by chunking the data\n",
    "def plot_spectrogram(time_series: np.ndarray) -> None:\n",
    "    f_sample = 1e9  # All devices have 1 GSPS sample rate\n",
    "    fig, ax = plt.subplots(1, 2)\n",
    "\n",
    "    f, t, Sxx = spectrogram(time_series, f_sample, return_onesided=False, detrend=False)\n",
    "\n",
    "    idx = np.argsort(f)\n",
    "    f = f[idx] / 1e6\n",
    "    Sxx = Sxx[idx]\n",
    "\n",
    "    spec = ax[0].pcolormesh(t, f, Sxx, shading=\"auto\", cmap=\"YlOrRd\")\n",
    "    cb = fig.colorbar(spec)\n",
    "    cb.set_label(\"Power Spectral Density [V$^2$/Hz]\")\n",
    "    ax[0].set_ylabel(\"Frequency [MHz]\")\n",
    "    ax[0].set_xlabel(\"Time [s]\")\n",
    "\n",
    "    f, Pxx = welch(time_series, f_sample, return_onesided=False, detrend=False)\n",
    "\n",
    "    idx = np.argsort(f)\n",
    "    f = f[idx] / 1e6\n",
    "    Pxx = Pxx[idx]\n",
    "\n",
    "    ax[1].semilogy(f, Pxx)\n",
    "    ax[1].set_xlabel(\"Frequency [MHz]\")\n",
    "    ax[1].set_ylabel(\"Power Spectral Density [V$^2$/Hz]\")\n",
    "    fig.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b83f540",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "And two more helper functions for plotting the amplitude of an array of I, Q values and a scope acquisition:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "009028ca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.550559Z",
     "iopub.status.busy": "2024-03-28T14:37:45.549521Z",
     "iopub.status.idle": "2024-03-28T14:37:45.561261Z",
     "shell.execute_reply": "2024-03-28T14:37:45.560235Z"
    }
   },
   "outputs": [],
   "source": [
    "def plot_amplitude(x: NDArray, I_data: NDArray, Q_data: NDArray) -> None:\n",
    "    amplitude = np.abs(I_data + 1j * Q_data)\n",
    "\n",
    "    plt.plot(x / 1e6, amplitude)\n",
    "    plt.xlabel(\"Frequency [MHz]\")\n",
    "    plt.ylabel(\"Integration [V]\")\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def plot_scope(trace: NDArray, t_min: int, t_max: int) -> None:\n",
    "    x = np.arange(t_min, t_max)\n",
    "    plt.plot(x, np.real(trace[t_min:t_max]))\n",
    "    plt.plot(x, np.imag(trace[t_min:t_max]))\n",
    "    plt.ylabel(\"Scope [V]\")\n",
    "    plt.xlabel(\"Time [ns]\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d4d7b8d5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.564183Z",
     "iopub.status.busy": "2024-03-28T14:37:45.564183Z",
     "iopub.status.idle": "2024-03-28T14:37:45.576436Z",
     "shell.execute_reply": "2024-03-28T14:37:45.575449Z"
    }
   },
   "outputs": [],
   "source": [
    "start_freq = -500e6\n",
    "stop_freq = 500e6\n",
    "\n",
    "n_averages = 10\n",
    "MAXIMUM_SCOPE_ACQUISITION_LENGTH = 16384"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfcf606f",
   "metadata": {},
   "source": [
    "### Setting up the QRM\n",
    "We set up a modulated DC offset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "203dedd4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.582131Z",
     "iopub.status.busy": "2024-03-28T14:37:45.581124Z",
     "iopub.status.idle": "2024-03-28T14:37:45.777630Z",
     "shell.execute_reply": "2024-03-28T14:37:45.776432Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# Configure channel map\n",
    "readout_module.sequencer0.connect_sequencer(\"io0_1\")\n",
    "\n",
    "# Set DC Offset\n",
    "readout_module.sequencer0.offset_awg_path0(1)\n",
    "readout_module.sequencer0.offset_awg_path1(1)\n",
    "\n",
    "# Enable modulation and demodulation. Note that the scope is not demodulated\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "\n",
    "# Enable hardware averaging for the scope\n",
    "readout_module.scope_acq_avg_mode_en_path0(True)\n",
    "readout_module.scope_acq_avg_mode_en_path1(True)\n",
    "\n",
    "readout_module.sequencer0.integration_length_acq(MAXIMUM_SCOPE_ACQUISITION_LENGTH)\n",
    "readout_module.sequencer0.nco_prop_delay_comp_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d0b8e4e",
   "metadata": {},
   "source": [
    "The sequencer program can fundamentally only support integer values. However, the NCO has a frequency resolution of 0.25 Hz and supports 10^9 phase values.\n",
    "\n",
    "Therefore, frequencies in the sequencer program must be given as an integer multiple of 0.25 Hz, and phases as an integer multiple of $360/10^9$ degrees."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e84ed5d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.782519Z",
     "iopub.status.busy": "2024-03-28T14:37:45.781312Z",
     "iopub.status.idle": "2024-03-28T14:37:45.792633Z",
     "shell.execute_reply": "2024-03-28T14:37:45.791577Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "372 steps with step size 2.6881720430107525 MHz\n"
     ]
    }
   ],
   "source": [
    "step_time = 44  # Time per frequency step in ns. We can reduce this, but the program needs to be changed. See next section\n",
    "n_steps = int(16384 / step_time)\n",
    "n_averages = 10\n",
    "\n",
    "step_freq = (stop_freq - start_freq) / n_steps\n",
    "print(f\"{n_steps} steps with step size {step_freq/1e6} MHz\")\n",
    "\n",
    "# Convert frequencies to multiples of 0.25 Hz\n",
    "nco_int_start_freq = int(4 * start_freq)\n",
    "nco_int_step_freq = int(4 * step_freq)\n",
    "\n",
    "# For plotting, convert the NCO integer values back to frequencies\n",
    "nco_sweep_range = np.arange(nco_int_start_freq, 4 * stop_freq, nco_int_step_freq) / 4.0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa7afc1d",
   "metadata": {},
   "source": [
    "Now, we write a Q1ASM program that quickly changes the NCO's frequency, converting the continuous sine output into a chirp.\n",
    "\n",
    "Internally, the processor stores negative values using [two's complement](https://en.wikipedia.org/wiki/Two%27s_complement). This has some implications for our program:\n",
    "- We cannot directly store a negative value in a register. Subtracting a larger value from a smaller one works as expected though.\n",
    "- Immediate values are handled by the compiler, i.e. `set_freq -100` gives the expected result of -25 Hz.\n",
    "- Comparisons (`jlt, jge`) with registers storing a negative value do not work as expected, as the smallest negative number is **larger** than the largest positive number. To keep the program general we should therefore use `loop` instead."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "72d8cd3f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.795703Z",
     "iopub.status.busy": "2024-03-28T14:37:45.795703Z",
     "iopub.status.idle": "2024-03-28T14:37:45.807826Z",
     "shell.execute_reply": "2024-03-28T14:37:45.806304Z"
    }
   },
   "outputs": [],
   "source": [
    "acquisitions = {\"acq\": {\"num_bins\": 1, \"index\": 0}}\n",
    "\n",
    "setup = f\"\"\"\n",
    "    move {n_averages}, R2\n",
    "\n",
    "avg_loop:\n",
    "    move    0, R0          # frequency\n",
    "    move {n_steps}, R1     # n_steps\n",
    "\"\"\"\n",
    "\n",
    "# To get a negative starting frequency, we subtract a positive number from 0\n",
    "if start_freq <= 0:\n",
    "    setup += f\"\"\"\n",
    "    sub R0, {-nco_int_start_freq}, R0\n",
    "    \"\"\"\n",
    "else:\n",
    "    setup += f\"\"\"\n",
    "    add R0, {nco_int_start_freq}, R0\n",
    "    \"\"\"\n",
    "\n",
    "# Play a chirped pulse\n",
    "chirp = (\n",
    "    setup\n",
    "    + f\"\"\"\n",
    "    reset_ph\n",
    "    set_freq 0\n",
    "    upd_param 200\n",
    "    acquire 0,0,4                         # Start acquisition. This is not blocking\n",
    "\n",
    "nco_set:\n",
    "    set_freq        R0                    # Set the frequency\n",
    "    add             R0,{nco_int_step_freq}, R0  # Update the frequency register\n",
    "    upd_param       {step_time}\n",
    "    loop            R1, @nco_set          # Loop over all frequencies\n",
    "\n",
    "    wait            10000\n",
    "    loop            R2, @avg_loop\n",
    "\n",
    "    stop                                  # Stop\n",
    "\"\"\"\n",
    ")\n",
    "\n",
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": {},\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": chirp,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "3c96a298",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.812885Z",
     "iopub.status.busy": "2024-03-28T14:37:45.812885Z",
     "iopub.status.idle": "2024-03-28T14:37:45.852348Z",
     "shell.execute_reply": "2024-03-28T14:37:45.851844Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8569e8b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.856437Z",
     "iopub.status.busy": "2024-03-28T14:37:45.856437Z",
     "iopub.status.idle": "2024-03-28T14:37:45.944381Z",
     "shell.execute_reply": "2024-03-28T14:37:45.943370Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_OVERWRITTEN_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_SCOPE_OVERWRITTEN_PATH_1, ACQ_BINNING_DONE\n",
      "CPU times: total: 15.6 ms\n",
      "Wall time: 79.9 ms\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",
      "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": [
    "%%time\n",
    "readout_module.sequencer0.nco_freq(0)\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "\n",
    "\n",
    "# Wait for the sequencer to stop with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0, timeout=1)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"acq\")\n",
    "data = readout_module.get_acquisitions(0)[\"acq\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f64cf8bb",
   "metadata": {},
   "source": [
    "Note that this is significantly faster than standard spectroscopy with Q1ASM with a larger number of points. For this measurement, we only use the scope acquisition data. We can analyze it again with a spectrogram."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "c05c6f61",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:45.948935Z",
     "iopub.status.busy": "2024-03-28T14:37:45.948935Z",
     "iopub.status.idle": "2024-03-28T14:37:46.517719Z",
     "shell.execute_reply": "2024-03-28T14:37:46.516695Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace = np.array(data[\"acquisition\"][\"scope\"][\"path0\"][\"data\"]) + 1j * np.array(\n",
    "    data[\"acquisition\"][\"scope\"][\"path1\"][\"data\"]\n",
    ")\n",
    "plot_spectrogram(trace)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36072823",
   "metadata": {},
   "source": [
    "Note the difference in timescale to before. In the spectrogram we can see the intended spectrum of the chirp.\n",
    "And finally, we can visualize the chirp pulse. For better clarity, we show the low frequency parts around 8400ns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "6c41b92c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:46.522716Z",
     "iopub.status.busy": "2024-03-28T14:37:46.521714Z",
     "iopub.status.idle": "2024-03-28T14:37:46.657182Z",
     "shell.execute_reply": "2024-03-28T14:37:46.656188Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_scope(trace, 8350, 9000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eee851c2",
   "metadata": {},
   "source": [
    "## Timings of the Q1 and realtime processors\n",
    "The sequencer has a real-time pipeline that generates the output and a classical pipeline responsible for logic and filling the queue of the real-time pipeline. This queue is 32 instructions long and starts pre-filled when the sequencer is started. If the runtime of classical instructions is shorter than the corresponding real-time instructions, the sequencer will stop. See also in the documentation of the [sequencer](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/q1_sequence_processor.html#program).\n",
    "\n",
    "We can see this by running the same program as before, but with reduced time between frequency steps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "246a6437",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:46.661710Z",
     "iopub.status.busy": "2024-03-28T14:37:46.661710Z",
     "iopub.status.idle": "2024-03-28T14:37:46.673927Z",
     "shell.execute_reply": "2024-03-28T14:37:46.672003Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "409 steps with step size 2.4449877750611244 MHz\n"
     ]
    }
   ],
   "source": [
    "step_time = 40  # this will cause stalling\n",
    "\n",
    "n_steps = int(16384 / step_time)\n",
    "step_freq = (stop_freq - start_freq) / n_steps\n",
    "print(f\"{n_steps} steps with step size {step_freq/1e6} MHz\")\n",
    "\n",
    "# Convert frequencies to multiples of 0.25 Hz\n",
    "nco_int_start_freq = int(4 * start_freq)\n",
    "nco_int_step_freq = int(4 * step_freq)\n",
    "\n",
    "# For plotting, convert the NCO integer values back to frequencies\n",
    "nco_sweep_range = np.arange(nco_int_start_freq, 4 * stop_freq, nco_int_step_freq) / 4.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8e14d372",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:46.679654Z",
     "iopub.status.busy": "2024-03-28T14:37:46.679654Z",
     "iopub.status.idle": "2024-03-28T14:37:46.687545Z",
     "shell.execute_reply": "2024-03-28T14:37:46.687545Z"
    }
   },
   "outputs": [],
   "source": [
    "acquisitions = {\"acq\": {\"num_bins\": 1, \"index\": 0}}\n",
    "\n",
    "setup = f\"\"\"\n",
    "    move {n_averages}, R2\n",
    "\n",
    "avg_loop:\n",
    "    move {n_steps}, R1  # n_steps\n",
    "    move    0, R0          # frequency\n",
    "    nop\n",
    "\"\"\"\n",
    "\n",
    "# To get a negative starting frequency, we subtract a positive number from 0\n",
    "if start_freq <= 0:\n",
    "    setup += f\"\"\"\n",
    "    sub R0, {-nco_int_start_freq}, R0\n",
    "    \"\"\"\n",
    "else:\n",
    "    setup += f\"\"\"\n",
    "    add R0, {nco_int_start_freq}, R0\n",
    "    \"\"\"\n",
    "\n",
    "# Play a chirped pulse\n",
    "chirp = (\n",
    "    setup\n",
    "    + f\"\"\"\n",
    "    reset_ph\n",
    "    set_freq 0\n",
    "    upd_param 200\n",
    "    acquire 0,0,4                         # Start acquisition. This is not blocking\n",
    "\n",
    "nco_set:\n",
    "    set_freq        R0                    # Set the frequency\n",
    "    add             R0,{nco_int_step_freq}, R0  # Update the frequency register\n",
    "    upd_param       {step_time}\n",
    "    loop            R1, @nco_set          # Loop over all frequencies\n",
    "\n",
    "    wait            10000\n",
    "    loop            R2, @avg_loop\n",
    "\n",
    "    stop                                  # Stop\n",
    "\"\"\"\n",
    ")\n",
    "\n",
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": {},\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": chirp,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "39469601",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:46.691804Z",
     "iopub.status.busy": "2024-03-28T14:37:46.691804Z",
     "iopub.status.idle": "2024-03-28T14:37:46.797438Z",
     "shell.execute_reply": "2024-03-28T14:37:46.796392Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\"sequence.json\")\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer to stop with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0, timeout=1)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"acq\")\n",
    "data = readout_module.get_acquisitions(0)[\"acq\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d863d989",
   "metadata": {},
   "source": [
    "As can be seen from the red LEDs on the front of your Cluster, the Q1 processor has stalled, and the program stopped."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "65a2021b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:46.803099Z",
     "iopub.status.busy": "2024-03-28T14:37:46.802075Z",
     "iopub.status.idle": "2024-03-28T14:37:46.828982Z",
     "shell.execute_reply": "2024-03-28T14:37:46.826834Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, SEQUENCE_PROCESSOR_RT_EXEC_COMMAND_UNDERFLOW\n"
     ]
    }
   ],
   "source": [
    "print(readout_module.sequencer0.get_sequencer_status())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dea959f6",
   "metadata": {},
   "source": [
    "We can also see on the scope that the chirp has been stopped prematurely."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "7cdef018",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:46.832962Z",
     "iopub.status.busy": "2024-03-28T14:37:46.832962Z",
     "iopub.status.idle": "2024-03-28T14:37:47.339558Z",
     "shell.execute_reply": "2024-03-28T14:37:47.337810Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace = np.array(data[\"acquisition\"][\"scope\"][\"path0\"][\"data\"]) + 1j * np.array(\n",
    "    data[\"acquisition\"][\"scope\"][\"path1\"][\"data\"]\n",
    ")\n",
    "plot_spectrogram(trace)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "040cef39",
   "metadata": {},
   "source": [
    "Before continuing, we clear the flags on the qrm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b97c0941",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:47.344088Z",
     "iopub.status.busy": "2024-03-28T14:37:47.343072Z",
     "iopub.status.idle": "2024-03-28T14:37:47.354270Z",
     "shell.execute_reply": "2024-03-28T14:37:47.352690Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster.clear()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "231d050d",
   "metadata": {},
   "source": [
    "If we want to the chirp to use as many updates as possible, we need to unroll the loop. This way, we can reduce the time per frequency step down to 8ns: `set_freq, upd_param` both take 4ns on the Q1 processor."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "9d7f97ef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:47.358956Z",
     "iopub.status.busy": "2024-03-28T14:37:47.358956Z",
     "iopub.status.idle": "2024-03-28T14:37:47.369724Z",
     "shell.execute_reply": "2024-03-28T14:37:47.368259Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2048 steps with step size 0.48828125 MHz\n"
     ]
    }
   ],
   "source": [
    "step_time = 8\n",
    "\n",
    "n_steps = int(16384 / step_time)\n",
    "step_freq = (stop_freq - start_freq) / n_steps\n",
    "print(f\"{n_steps} steps with step size {step_freq/1e6} MHz\")\n",
    "\n",
    "# Convert frequencies to multiples of 0.25 Hz\n",
    "nco_int_start_freq = int(4 * start_freq)\n",
    "nco_int_step_freq = int(4 * step_freq)\n",
    "\n",
    "# For plotting, convert the NCO integer values back to frequencies\n",
    "nco_sweep_range = np.arange(nco_int_start_freq, 4 * stop_freq, nco_int_step_freq) / 4.0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e190c130",
   "metadata": {},
   "source": [
    "This does not leave room for a loop, which would take an additional 24ns. However, we can use the instruction memory of the Q1 processor:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e6602fbe",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:47.375275Z",
     "iopub.status.busy": "2024-03-28T14:37:47.374770Z",
     "iopub.status.idle": "2024-03-28T14:37:47.399592Z",
     "shell.execute_reply": "2024-03-28T14:37:47.398590Z"
    }
   },
   "outputs": [],
   "source": [
    "chirp = f\"\"\"\n",
    "    move {n_averages}, R2\n",
    "\n",
    "avg_loop:\n",
    "    move    0, R0          # frequency\n",
    "    nop\n",
    "\"\"\"\n",
    "\n",
    "# To get a negative starting frequency, we subtract a positive number from 0\n",
    "if start_freq <= 0:\n",
    "    chirp += f\"\"\"\n",
    "    sub R0, {-nco_int_start_freq}, R0\n",
    "    \"\"\"\n",
    "else:\n",
    "    chirp += f\"\"\"\n",
    "    add R0, {nco_int_start_freq}, R0\n",
    "    \"\"\"\n",
    "\n",
    "chirp += \"\"\"\n",
    "    reset_ph\n",
    "    set_freq 0\n",
    "    upd_param 200\n",
    "    acquire 0,0,4                         # Start acquisition. This is not blocking\n",
    "\n",
    "\"\"\"\n",
    "# unroll the loop into individual commands\n",
    "\n",
    "for frequency in nco_sweep_range:\n",
    "    chirp += f\"\"\"\n",
    "    set_freq        {int(4*frequency)}                    # Set the frequency\n",
    "    upd_param       {step_time}\n",
    "\"\"\"\n",
    "\n",
    "chirp += \"\"\"\n",
    "\n",
    "    wait            10000\n",
    "    loop            R2, @avg_loop\n",
    "\n",
    "    stop                                  # Stop\n",
    "\"\"\"\n",
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": {},\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": chirp,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "af364016",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:47.404579Z",
     "iopub.status.busy": "2024-03-28T14:37:47.404579Z",
     "iopub.status.idle": "2024-03-28T14:37:47.598962Z",
     "shell.execute_reply": "2024-03-28T14:37:47.597854Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "552e1d91",
   "metadata": {},
   "source": [
    "Now we execute the program and plot the spectrogram:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "09eb78b7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:47.603655Z",
     "iopub.status.busy": "2024-03-28T14:37:47.602551Z",
     "iopub.status.idle": "2024-03-28T14:37:47.677503Z",
     "shell.execute_reply": "2024-03-28T14:37:47.676497Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 0 ns\n",
      "Wall time: 52.6 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer to stop with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0, timeout=1)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"acq\")\n",
    "data = readout_module.get_acquisitions(0)[\"acq\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecdc0fe9",
   "metadata": {},
   "source": [
    "Note that the execution time is comparable to the other chirped measurements, but with more than double the number of points."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "375f5541",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:47.682496Z",
     "iopub.status.busy": "2024-03-28T14:37:47.681511Z",
     "iopub.status.idle": "2024-03-28T14:37:48.141244Z",
     "shell.execute_reply": "2024-03-28T14:37:48.140163Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace = np.array(data[\"acquisition\"][\"scope\"][\"path0\"][\"data\"]) + 1j * np.array(\n",
    "    data[\"acquisition\"][\"scope\"][\"path1\"][\"data\"]\n",
    ")\n",
    "plot_spectrogram(trace)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8fe2d34",
   "metadata": {},
   "source": [
    "## Phase updates\n",
    "\n",
    "### Virtual Z gates\n",
    "In addition to fast frequency updates, the sequencer also supports real-time changes of the NCO phase. In particular for superconducting qubits, this can be used for a so-called virtual $Z$ gate, see [McKay et al. (2016)](https://arxiv.org/abs/1612.00858).\n",
    "The virtual $Z$ gate is a change of reference frame rather than a physical operation. Therefore, it is instantaneous and near perfect - the dominant error being that the NCO has a finite resolution of $10^9$ different phases. Below, we will demonstrate how to to use a virtual Z to use the same pulse for both $X$ and $Y$ rotations.\n",
    "\n",
    "As the sequencer internally only supports integer values, we must first convert the phase into an integer multiple of $360/10^{9}$ degree:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "e1958fa4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:48.145345Z",
     "iopub.status.busy": "2024-03-28T14:37:48.144321Z",
     "iopub.status.idle": "2024-03-28T14:37:48.156466Z",
     "shell.execute_reply": "2024-03-28T14:37:48.155458Z"
    }
   },
   "outputs": [],
   "source": [
    "int_90 = int(90 * (1e9 / 360))\n",
    "int_270 = int(270 * (1e9 / 360))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "0737caba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:48.161990Z",
     "iopub.status.busy": "2024-03-28T14:37:48.160990Z",
     "iopub.status.idle": "2024-03-28T14:37:48.187748Z",
     "shell.execute_reply": "2024-03-28T14:37:48.186728Z"
    }
   },
   "outputs": [],
   "source": [
    "# Waveforms\n",
    "waveform_len = 1000\n",
    "waveforms = {\n",
    "    \"gaussian\": {\n",
    "        \"data\": gaussian(waveform_len, std=0.133 * waveform_len).tolist(),\n",
    "        \"index\": 0,\n",
    "    },\n",
    "}\n",
    "\n",
    "# Acquisitions\n",
    "acquisitions = {\"scope\": {\"num_bins\": 1, \"index\": 0}}\n",
    "\n",
    "# Program\n",
    "virtual_z = f\"\"\"\n",
    "acquire         0,0,4\n",
    "reset_ph\n",
    "play            0,0,{waveform_len}      # X90\n",
    "# This is equivalent to Y90, but uses the same waveform as X90\n",
    "set_ph_delta    {int_90}     # Z90\n",
    "play            0,0,{waveform_len}      # X90\n",
    "set_ph_delta    {int_270}    # Z-90\n",
    "play            0,0,{waveform_len}      # X90\n",
    "stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file.\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": {},\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": virtual_z,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "93d999fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:48.191746Z",
     "iopub.status.busy": "2024-03-28T14:37:48.191746Z",
     "iopub.status.idle": "2024-03-28T14:37:51.801112Z",
     "shell.execute_reply": "2024-03-28T14:37:51.800087Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program sequencers. But first we reset the cluster\n",
    "cluster.reset()\n",
    "\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")\n",
    "\n",
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# Configure channel map\n",
    "readout_module.sequencer0.connect_sequencer(\"io0_1\")\n",
    "readout_module.sequencer0.nco_freq(3e6)\n",
    "\n",
    "# Enable modulation\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "\n",
    "# Enable hardware averaging for the scope\n",
    "readout_module.scope_acq_avg_mode_en_path0(True)\n",
    "readout_module.scope_acq_avg_mode_en_path1(True)\n",
    "\n",
    "readout_module.sequencer0.integration_length_acq(MAXIMUM_SCOPE_ACQUISITION_LENGTH)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0426fd7",
   "metadata": {},
   "source": [
    "Now we can run the program and look at the scope acquisition."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "74bc41cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:51.805008Z",
     "iopub.status.busy": "2024-03-28T14:37:51.805008Z",
     "iopub.status.idle": "2024-03-28T14:37:51.986008Z",
     "shell.execute_reply": "2024-03-28T14:37:51.984198Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start the sequence\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer to stop\n",
    "readout_module.get_acquisition_status(0, timeout=1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "trace = np.asarray(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"]) + 1j * np.asarray(\n",
    "    acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"]\n",
    ")\n",
    "\n",
    "plot_scope(trace, 0, 4000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "227deb81",
   "metadata": {},
   "source": [
    "### Chirped pulses using the phase update\n",
    "As an exercise combining the concepts from this notebook, we can also create a chirp using only phase updates. This is purely educational and should not be used in an experiment. Again, we do not use a loop, and use the instruction memory instead to make the step size smaller."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "46cacea4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:51.991028Z",
     "iopub.status.busy": "2024-03-28T14:37:51.990027Z",
     "iopub.status.idle": "2024-03-28T14:37:52.017543Z",
     "shell.execute_reply": "2024-03-28T14:37:52.015186Z"
    }
   },
   "outputs": [],
   "source": [
    "n_averages = 100\n",
    "n_steps = int(16384 / (20))\n",
    "\n",
    "acquisitions = {\"acq\": {\"num_bins\": 1, \"index\": 0}}\n",
    "\n",
    "\n",
    "phase_chirp = f\"\"\"\n",
    "    move {n_averages}, R2\n",
    "\n",
    "avg_loop:\n",
    "    move    0, R0                         # phase update step size\n",
    "    reset_ph\n",
    "    set_freq 0\n",
    "    upd_param 200\n",
    "    acquire 0,0,4                         # Start acquisition. This is not blocking\n",
    "\n",
    "nco_set:\n",
    "\"\"\"\n",
    "# step the phase with increasing step size\n",
    "# The order is chosen such that we do not need `nop`\n",
    "for _ in range(n_steps):\n",
    "    phase_chirp += f\"\"\"\n",
    "    set_ph_delta    R0\n",
    "    add             R0, {int(1e9/(4*n_steps))}, R0      # increase the 'frequency'\n",
    "    upd_param       20\n",
    "\"\"\"\n",
    "phase_chirp += \"\"\"\n",
    "    wait            10000\n",
    "    loop            R2, @avg_loop\n",
    "\n",
    "    stop                                  # Stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file.\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": {},\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": phase_chirp,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e6501f7",
   "metadata": {},
   "source": [
    "We can run this with the same settings as the chirps before:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7e068345",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:52.021074Z",
     "iopub.status.busy": "2024-03-28T14:37:52.021074Z",
     "iopub.status.idle": "2024-03-28T14:37:52.233353Z",
     "shell.execute_reply": "2024-03-28T14:37:52.232133Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\"sequence.json\")\n",
    "\n",
    "# Set DC Offset\n",
    "readout_module.sequencer0.offset_awg_path0(1)\n",
    "readout_module.sequencer0.offset_awg_path1(1)\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer to stop with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0, timeout=1)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"acq\")\n",
    "data = readout_module.get_acquisitions(0)[\"acq\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "afdf56c9",
   "metadata": {},
   "source": [
    "In the spectrogram we can see a slow frequency sweep - plus high frequency components. The reason for those is easily visible in the scope, the \"sine\" wave is not smooth, but instead made up of many square pulses (as expected)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "83712ac9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:52.238378Z",
     "iopub.status.busy": "2024-03-28T14:37:52.238378Z",
     "iopub.status.idle": "2024-03-28T14:37:52.663651Z",
     "shell.execute_reply": "2024-03-28T14:37:52.662635Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trace = np.array(data[\"acquisition\"][\"scope\"][\"path0\"][\"data\"]) + 1j * np.array(\n",
    "    data[\"acquisition\"][\"scope\"][\"path1\"][\"data\"]\n",
    ")\n",
    "plot_spectrogram(trace)\n",
    "\n",
    "plot_scope(trace, 0, 2000)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d25571ef",
   "metadata": {},
   "source": [
    "Using registers, we can also do negative phase steps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "f46f3108",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:52.669095Z",
     "iopub.status.busy": "2024-03-28T14:37:52.668575Z",
     "iopub.status.idle": "2024-03-28T14:37:53.387853Z",
     "shell.execute_reply": "2024-03-28T14:37:53.386852Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "n_averages = 100\n",
    "n_steps = int(16384 / (20))\n",
    "\n",
    "acquisitions = {\"acq\": {\"num_bins\": 1, \"index\": 0}}\n",
    "\n",
    "\n",
    "phase_chirp = f\"\"\"\n",
    "    move {n_averages}, R2\n",
    "\n",
    "avg_loop:\n",
    "    move    0, R0                         # phase update step size\n",
    "    reset_ph\n",
    "    upd_param 200\n",
    "    set_freq 0\n",
    "    acquire 0,0,4                         # Start acquisition. This is not blocking\n",
    "\n",
    "nco_set:\n",
    "\"\"\"\n",
    "# step the phase with increasing (negative) step size\n",
    "for _ in range(n_steps):\n",
    "    phase_chirp += f\"\"\"\n",
    "    set_ph_delta    R0\n",
    "    sub             R0, {int(1e9/(4*n_steps))}, R0      # increase the step size ('frequency')\n",
    "    upd_param       20\n",
    "\"\"\"\n",
    "\n",
    "phase_chirp += \"\"\"\n",
    "    wait            10000\n",
    "    loop            R2, @avg_loop\n",
    "\n",
    "    stop                                  # Stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file.\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": {},\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": phase_chirp,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()\n",
    "\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer to stop with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0, timeout=1)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"acq\")\n",
    "data = readout_module.get_acquisitions(0)[\"acq\"]\n",
    "\n",
    "trace = np.array(data[\"acquisition\"][\"scope\"][\"path0\"][\"data\"]) + 1j * np.array(\n",
    "    data[\"acquisition\"][\"scope\"][\"path1\"][\"data\"]\n",
    ")\n",
    "plot_spectrogram(trace)\n",
    "\n",
    "plot_scope(trace, 0, 2500)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20fa02d8",
   "metadata": {},
   "source": [
    "## Stop\n",
    "\n",
    "Finally, let's stop the playback 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": 38,
   "id": "321e4dca",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:37:53.393405Z",
     "iopub.status.busy": "2024-03-28T14:37:53.393405Z",
     "iopub.status.idle": "2024-03-28T14:38:03.891491Z",
     "shell.execute_reply": "2024-03-28T14:38:03.889761Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: STOPPED, Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_OVERWRITTEN_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_SCOPE_OVERWRITTEN_PATH_1, ACQ_BINNING_DONE\n",
      "Status: STOPPED, Flags: FORCED_STOP\n",
      "\n",
      "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   :\tTrue \n",
      "scope_acq_avg_mode_en_path1   :\tTrue \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                     :\tI \n",
      "connect_out1                     :\tQ \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           :\t16384 \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                       :\tTrue \n",
      "nco_freq                         :\t3e+06 (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                 :\t1 \n",
      "offset_awg_path1                 :\t1 \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_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 both sequencers.\n",
    "readout_module.stop_sequencer()\n",
    "\n",
    "# Print status of both sequencers (should now say it is stopped).\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "print(readout_module.get_sequencer_status(1))\n",
    "print()\n",
    "\n",
    "# Print an overview of the instrument parameters.\n",
    "print(\"Snapshot:\")\n",
    "readout_module.print_readable_snapshot(update=True)\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  }
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