{
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   "source": [
    "Multiplexed sequencing\n",
    "======================\n",
    "\n",
    "The Cluster QRM/QCM supports six sequencers. The output of each sequencer is multiplexed, accumulated and connected to the output ports of the instrument.\n",
    "\n",
    "- In the first part of the tutorial we will demonstrate how to connect multiple sequencers to a single pair of output ports.\n",
    "- In the second part of the tutorial we will demonstrate frequency multiplexing by assigning different unique modulation frequencies (frequency of the carrier) to the sequencers. We will then show how to acquire, demodulate, and integrate the received frequency multiplexed waveforms.\n",
    "- In the third part of the tutorial we will demonstrate \\\"real mode\\\", where we will output real signals on each individual output port of the instrument.\n",
    "\n",
    "We will show this by using a [QRM](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/qrm.html) and 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\n",
    "the outputs and simultaneously acquire the resulting waveforms on the inputs (using the same sequencers)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "75422c84",
   "metadata": {
    "tags": []
   },
   "source": [
    "Setup\n",
    "-----\n",
    "\n",
    "First, we are going to import the required packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "446e6f69",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:18.735249Z",
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     "iopub.status.idle": "2024-03-28T14:31:23.051643Z",
     "shell.execute_reply": "2024-03-28T14:31:23.050429Z"
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   "outputs": [],
   "source": [
    "\n",
    "from __future__ import annotations\n",
    "\n",
    "import json\n",
    "import math\n",
    "from typing import TYPE_CHECKING, Callable\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.signal\n",
    "from qcodes.instrument import find_or_create_instrument\n",
    "from scipy.fft import rfft, rfftfreq\n",
    "\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "if TYPE_CHECKING:\n",
    "    from qblox_instruments.qcodes_drivers.module import QcmQrm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2efd33b7",
   "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": "501d1427",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:23.058267Z",
     "iopub.status.busy": "2024-03-28T14:31:23.057258Z",
     "iopub.status.idle": "2024-03-28T14:31:25.271967Z",
     "shell.execute_reply": "2024-03-28T14:31:25.270454Z"
    }
   },
   "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": "20493d20",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:25.276504Z",
     "iopub.status.busy": "2024-03-28T14:31:25.275474Z",
     "iopub.status.idle": "2024-03-28T14:31:25.287272Z",
     "shell.execute_reply": "2024-03-28T14:31:25.286019Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7209fe9f",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fa7c19ab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:25.292437Z",
     "iopub.status.busy": "2024-03-28T14:31:25.292437Z",
     "iopub.status.idle": "2024-03-28T14:31:26.315190Z",
     "shell.execute_reply": "2024-03-28T14:31:26.313579Z"
    },
    "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": "1d86d512",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6eaa72f5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:26.319194Z",
     "iopub.status.busy": "2024-03-28T14:31:26.319194Z",
     "iopub.status.idle": "2024-03-28T14:31:26.329911Z",
     "shell.execute_reply": "2024-03-28T14:31:26.328841Z"
    }
   },
   "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": "0581893b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:26.334469Z",
     "iopub.status.busy": "2024-03-28T14:31:26.334469Z",
     "iopub.status.idle": "2024-03-28T14:31:26.436974Z",
     "shell.execute_reply": "2024-03-28T14:31:26.435813Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4: <Module: cluster0_module4 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QRM baseband modules\n",
    "modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and not mod.is_rf_type)\n",
    "modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a2d2b924",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:26.442120Z",
     "iopub.status.busy": "2024-03-28T14:31:26.441095Z",
     "iopub.status.idle": "2024-03-28T14:31:26.452901Z",
     "shell.execute_reply": "2024-03-28T14:31:26.450898Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "readout_module = modules[4]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6de66689",
   "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": "c00bee9c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:26.457065Z",
     "iopub.status.busy": "2024-03-28T14:31:26.457065Z",
     "iopub.status.idle": "2024-03-28T14:31:29.887143Z",
     "shell.execute_reply": "2024-03-28T14:31:29.885687Z"
    }
   },
   "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_state())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5313e2e0",
   "metadata": {},
   "source": [
    "Generate waveforms <a id='gen_wf'></a>\n",
    "------------------\n",
    "\n",
    "Next, we need to create the gaussian and block waveforms for the sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "86693723",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:29.891862Z",
     "iopub.status.busy": "2024-03-28T14:31:29.890859Z",
     "iopub.status.idle": "2024-03-28T14:31:29.902222Z",
     "shell.execute_reply": "2024-03-28T14:31:29.900951Z"
    }
   },
   "outputs": [],
   "source": [
    "# Waveforms\n",
    "waveform_len = 1000\n",
    "waveforms = {\n",
    "    \"gaussian\": {\n",
    "        \"data\": scipy.signal.windows.gaussian(waveform_len, std=0.133 * waveform_len).tolist(),\n",
    "        \"index\": 0,\n",
    "    },\n",
    "    \"sine\": {\n",
    "        \"data\": [math.sin((2 * math.pi / waveform_len) * i) for i in range(0, waveform_len)],\n",
    "        \"index\": 1,\n",
    "    },\n",
    "    \"sawtooth\": {\n",
    "        \"data\": [(1.0 / waveform_len) * i for i in range(0, waveform_len)],\n",
    "        \"index\": 2,\n",
    "    },\n",
    "    \"block\": {\"data\": [1.0 for i in range(0, waveform_len)], \"index\": 3},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8cdde8e",
   "metadata": {},
   "source": [
    "Let's plot the waveforms to see what we have created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e00d4549",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:29.905753Z",
     "iopub.status.busy": "2024-03-28T14:31:29.905753Z",
     "iopub.status.idle": "2024-03-28T14:31:30.151929Z",
     "shell.execute_reply": "2024-03-28T14:31:30.149886Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621.118 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time = np.arange(0, max(map(lambda d: len(d[\"data\"]), waveforms.values())), 1)\n",
    "fig, ax = plt.subplots(1, 1, figsize=(10, 10 / 1.61))\n",
    "\n",
    "for wf, d in waveforms.items():\n",
    "    ax.plot(time[: len(d[\"data\"])], d[\"data\"], \".-\", linewidth=0.5, label=wf)\n",
    "\n",
    "ax.legend(loc=4)\n",
    "ax.grid(alpha=1 / 10)\n",
    "ax.set_ylabel(\"Waveform primitive amplitude\")\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "\n",
    "plt.draw()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b714ae3",
   "metadata": {},
   "source": [
    "Specify the acquisitions\n",
    "--------------------\n",
    "\n",
    "We will only use a single bin in this tutorial, so we can keep it simple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e1b5f3f6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:30.155653Z",
     "iopub.status.busy": "2024-03-28T14:31:30.155150Z",
     "iopub.status.idle": "2024-03-28T14:31:30.166973Z",
     "shell.execute_reply": "2024-03-28T14:31:30.165783Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"scope\": {\"num_bins\": 1, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e166e856",
   "metadata": {},
   "source": [
    "Create Q1ASM program and upload the sequence\n",
    "--------------------\n",
    "\n",
    "Now that we have the waveform and acquisition specifications for the sequence, we need a simple Q1ASM program that sequences the waveforms and triggers the acquisitions. In this case we will play a gaussian and a sinusoid wave for path 0 and 1 respectively per sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9191db7c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:30.170534Z",
     "iopub.status.busy": "2024-03-28T14:31:30.170534Z",
     "iopub.status.idle": "2024-03-28T14:31:31.144493Z",
     "shell.execute_reply": "2024-03-28T14:31:31.143428Z"
    }
   },
   "outputs": [],
   "source": [
    "# Number of sequencers per instrument\n",
    "num_seq = 6\n",
    "\n",
    "# Program\n",
    "program = \"\"\"\n",
    "wait_sync 4\n",
    "play      0,1,4\n",
    "wait      140\n",
    "acquire   0,0,16380\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\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()\n",
    "\n",
    "# Program sequencers.\n",
    "for sequencer in readout_module.sequencers:\n",
    "    sequencer.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53012279",
   "metadata": {},
   "source": [
    "Multiplexed sequencer output control\n",
    "------------------------------------\n",
    "Each sequencer has two output paths. The output paths of each sequencer are physically connected to the instrument's outputs. It is possible to map any sequencer output path to any output port by using the sequencer's channel map.\n",
    "\n",
    "We can do so by calling `sequencerX.connect_outY(Z)` where `X`, `Y` and `Z` represents sequencer ID $\\in[0,..,5]$, output port number, and `Z`$\\in \\{$`\"off\"`, `\"I\"`, `\"Q\"`$\\}$.\n",
    "\n",
    "For most common sequencer configurations, the convenience function `sequencerX.connect_sequencer(config)` can be used to easily set the channel map. Some examples:\n",
    "\n",
    "Multiplexed sequencers on a QRM baseband\n",
    "```python\n",
    "instrument.disconnect_inputs()\n",
    "instrument.disconnect_outputs()\n",
    "for seq in instrument.sequencers:\n",
    "    seq.connect_sequencer(\"io0_1\")\n",
    "```\n",
    "\n",
    "Multiplexed sequencers on a QRM-RF\n",
    "```python\n",
    "instrument.disconnect_inputs()\n",
    "instrument.disconnect_outputs()\n",
    "for seq in instrument.sequencers:\n",
    "    seq.connect_sequencer(\"io0\")\n",
    "```\n",
    "\n",
    "Sequencers 1:1 on a QCM baseband\n",
    "```python\n",
    "instrument.disconnect_outputs()\n",
    "for idx in range(4):\n",
    "    instrument[f\"sequencer{idx}\"].connect_sequencer(f\"out{idx}\")\n",
    "```\n",
    "\n",
    "Sequencers 1:1 on a QCM-RF\n",
    "```python\n",
    "instrument.disconnect_outputs()\n",
    "for idx in range(2):\n",
    "    instrument[f\"sequencer{idx}\"].connect_sequencer(f\"out{idx}\")\n",
    "```\n",
    "\n",
    "For the sake of this tutorial we will map the <span style=\"color:#ed1c24\">in-phase path</span> of each sequencer to the ports with the even output port numbers (indexed from 0) and the <span style=\"color:#37b5b9\">quadrature path</span> of each sequencer to the ports with the odd output port numbers.\n",
    "<!---\n",
    ", like is shown in the figure below. Note that this figure is for the [QCM](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/qcm.html), so it has 4 outputs.\n",
    "\n",
    "<img src=\"https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/figures/QBLOX_MULTIPLEXING_DIAGRAM.svg\" alt=\"drawing\" width=\"1000\"/>\n",
    "-->"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b54cec99",
   "metadata": {},
   "source": [
    "Now lets configure the first sequencer to output its <span style=\"color:#ed1c24\">in-phase</span> and <span style=\"color:#37b5b9\">quadrature</span> paths on $\\text{O}^{1}$ and $\\text{O}^{2}$ respectively. We will scale the amplitude of the signal such that we are able the show what happens when other sequencers are added and eventually output overflow occurs.\n",
    "\n",
    "We will also configure the channel map so that inputs $\\text{I}^{[1-2]}$ of the QRM are mapped to the <span style=\"color:#ed1c24\">in-phase</span> and <span style=\"color:#37b5b9\">quadrature</span> input paths of the same sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "63c2b147",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:31.149603Z",
     "iopub.status.busy": "2024-03-28T14:31:31.149603Z",
     "iopub.status.idle": "2024-03-28T14:31:31.562455Z",
     "shell.execute_reply": "2024-03-28T14:31:31.560333Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\work\\code\\qblox_instruments_install\\qblox_instruments\\native\\generic_func.py:3210: FutureWarning: \n",
      "        After June 2024, this feature is subject to removal in future releases.\n",
      "        Transition to an alternative is advised.\n",
      "        See https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/getting_started/deprecated.html\n",
      "        \n",
      "  warnings.warn(\n",
      "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"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer to trigger the scope acquisition.\n",
    "readout_module.scope_acq_sequencer_select(0)\n",
    "readout_module.scope_acq_trigger_mode_path0(\"sequencer\")\n",
    "readout_module.scope_acq_trigger_mode_path1(\"sequencer\")\n",
    "\n",
    "# Configure sequencer\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "readout_module.sequencer0.gain_awg_path0(\n",
    "    1.1 / num_seq\n",
    ")  # The output range is 1.0 to -1.0, but we want to show what happens when the signals go out of range.\n",
    "readout_module.sequencer0.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# connect output paths of the sequencer\n",
    "readout_module.sequencer0.connect_out0(\"I\")\n",
    "readout_module.sequencer0.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer0.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer0.connect_acq_Q(\"in1\")\n",
    "\n",
    "# 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_state(0, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5f510aa",
   "metadata": {},
   "source": [
    "Let's add the second sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "cb1742cc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:31.568238Z",
     "iopub.status.busy": "2024-03-28T14:31:31.567724Z",
     "iopub.status.idle": "2024-03-28T14:31:31.934614Z",
     "shell.execute_reply": "2024-03-28T14:31:31.933613Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer1.sync_en(True)\n",
    "readout_module.sequencer1.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer1.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer1.connect_out0(\"I\")\n",
    "readout_module.sequencer1.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer1.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer1.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 2):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 2):\n",
    "    readout_module.get_acquisition_state(seq, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4b5e31e",
   "metadata": {},
   "source": [
    "Let's add the third sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c4f087ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:31.939615Z",
     "iopub.status.busy": "2024-03-28T14:31:31.938615Z",
     "iopub.status.idle": "2024-03-28T14:31:32.262111Z",
     "shell.execute_reply": "2024-03-28T14:31:32.260604Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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7KbLZAfD2sDLg1zXf9meVcEVSPH7eKk9FREQaE5VubqTSTaSR2zMPDiyGte9BZemx8wFRcPFbxu6jfuEQ2dq8jPL3uFyQsxfKC2DNVNj9s3EbjCmnnS4xpgi3PhsCIszNKnXO9LUpPPfzLnJ/txvmXWe14Yw2kezJKKZzXDBdm4WaF1D+tpxiG/N3ZvDhikPsPFpY7b7+iRG8fk1PwrXhgoiISKOh0s2NVLqJNELlBeDlb0xF/Oyy6vcFNoF//GzsTioNk6PSWKNvx0w4uvnYeb8wuH7+sZ1pvQNMiyjmyyqy8dnqQ0yev6fqnK+XlTev7cWwdhod2RC5XC52Hi3iho/WklZQXnU+wNuD8QMTuHVoawK06YKIiEiDp9LNjVS6iTQy276Bb28Gq1f1Nb86XAAXTjHKOA8tpt0ouFxwaDnsmQs7voe8A8bIRk9fY9TjxW8bRVzz/toFtRF5Y9Felu3JZltqAYXlx6YcXtuvBVf2iadtTJDJCaW25ZZUsCu9CD9vDx7+divb04zRbx2aBnPHma05s300vl6acioiItJQqXRzI5VuIg1ceQHs+A42fWFsiJC1C/jdt8WINnDzEu1q2dgVZcA7w6Aw9fj72pwDfW+BxKFg1S/aDdkXa1J48Jvq6/+d37Upj57fkZhgX5NSiZlcLhdzd2TwwFdbKCgzdkbuFBvMu+OSaBqi9ftEREQaIpVubqTSTaSBqSyH7N3gcsK2r2Hl6+ByVL+m5zjoezNUlEBUe/DVv30ByvKMNf5sRcZ/N7n7qt8f0Roi28HhVTDwLuOP1Gsul4tXFuyhuNxOud3Bp6tSqu6zWOCVK3twQbdYExNKXbE9rYCX5+1mQXImv72zPr9rU7alFhAW4M2DIzvQp2W4uSFFRETELVS6uZFKN5EGorIc1n8Iy16G4vTq94W3gh7XQpOuENMJgpuaElHqEVuxUbpZrLDqLUieDeX51a+59D3octkJHy71w49bj3LrZxuqnbvhjJb865x2HC0oIzEq0KRkUlftySji/q+2sPlIPr9/h+3rZeXnuwaTEKm1IEVEROo7lW5upNJNpAGoKIUPRsLRTcaxbwh4Bxr/O+wh6DDa1HjSAJQXGtOUs5Jh73zjfwFaD4egpsZxbE8Y+ZwxRErqJKfTxdbUAjysFv47dxcLd2VV3TekbRQ3DU5kYOtIExNKfTFnezp3frGRqCAfAn08SU4vAmB0t1ieubgz/l4eeHpoLUgREZH6SKWbG6l0E6mnXC7YPM0oQvYvAnuZsej9WY9B92vB09vshNJQOeww7zFY9frx9138NnS78vRnkr+Ull/GPz5cW1WO/CYu1I959w7G31u7UkrNFNvs+Ht5kFZQxshXllL068YbABEB3nwwoTddm4WaF1BEREROiUo3N1LpJlIPleXD97fDzlnHzlm9YOxMSDjDrFTS2GTsgANLjDXgdn4H6VvB088ofjtfAkFNzE4oGOu27c0s5o4vNpKcXoS3h5UKh5Mmwb48cUFH+idGEuKvHYvl78kqsrFkdxZPztpeteutr5eVIW2jeGRUR+LDtVmPiIhIfaHSzY1UuonUA04HrH0P1rwNcb3g8GrIO2gUbYPuhbgkiOkIIc3MTiqNlcMO066CPXONY68AuOBVY8fTAE1XNMu21AIenrmNzYfzAaME+emuwZRXOogN8VPZJm6XUVjOgewS/jt3F2sP5gEQ6OPJ8A7RPHJ+RyIDfUxOKCIiIn9FpZsbqXQTqeOcDvjudtj8efXzIc3hig+NEk6kLnA6YM1U2PAxZO44dr5pN2PThcg25mVrZFwuF5+uTuGpWTuocDjxtFpoGurLnWe24fKkeLPjSSPgdLrYllbA499vZ2NKPgBnto/mvXFJWLTuo4iISJ2m0s2NVLqJ1EGOSmPEUOoG2PcLpG0Aiwd0vAAytkOTLjDqv8YabiJ1TWU5fH8H7PoRKkoAFwREQ/erIGEQNO8HPkFmp2ywtqUW8PQPO1i1PxeAszvG8J+LuxAVpBFGcvo5nC7mbE/nrmkbqXS4GNWlKY+P7kh0sK/Z0UREROQPqHRzI5VuInVM3iH4agKkrj92zsvfWKC+4wXm5RI5FYVH4dNLqo98s3pB/9uMdd+iO4GHFvB3ly/XHebhb7dR4XDi7WHl/hHtuGFQS40sEtN9sPwAT84yvg+0jAzg8xv70jTEz+RUIiIiciIq3dxIpZtIHeGohC3TYc5DUF4AviHQ8SJjPayuV0JUW7MTipyaihJj04+DS+HgMmM9wt+EtYTzX4ZWw0yLV9+VVzpYcyCXhbsy+WD5QQCGd4jhyQs7EReqUkPqju1pBdz08XpS88sI8vFkcLsoruvXgn6JEWZHExERkd9R6eZGKt1ETFZZDvOfgA0fQWWpcS6uF1z+IYQ2NzOZSO3YPB2WvWSM6rSXgYePselClyvAajU7Xb2y6XA+t322gdT8sqpzEwYm8Nj5HTW6Teqkw7ml3PTJenYeLQTAajFK4vTCcoa2jeLec9qZnFBERERUurmRSjcRk1SWwbzHYcs0Y2QbGOte9b8N+t0Knt7m5hOpbRUl8O3Nxig4AL9w6HkdDHtE//2fhF3pRVz8xnJKKxxEBvowpG0UZ7aP5rwuTVS4SZ1WXulgzvZ0Pll5iHWH8qrd99Ut/UlKCDcpmYiIiIBKN7dS6SZymlWUwIJ/w7avoSTLOBcQbYz0aTNCI32kcXFUwtKXYNXrx8rnoKbQawIMeQBUHlVTXunghTm72JZawMaUfCocTvolhjN1bBLBvl5mxxOpkUqHk+82pZFRWM77yw6QU1IBQN+W4bx1bS/CAlS+i4iImEGlmxupdBM5TfIPw1f/gCNrjp0LjIHRr0Lr4VpMXho3RyUk/wCz74EyY9dNOl4IZ9wDsT3MzVZHZBaW89h32/l5e3rVuVZRAXx5ywDCVU5IPZdZWM6o15aRVWQDoF1MEG9d14uWkQEmJxMREWl8VLq5kUo3kdOg4Ah8cB7kHzKOg5rCqJeg1Zng5WtuNpG6pLIMlrwAS/977FxIPIS3hAvfgNB487KZaPPhfK56ZxWlFQ4sFrhlSCvOah9N12aheHtqdKw0DJUOJ1uOFHDzJ+vJLjbKt94JYTx7aVdaRQWanE5ERKTxUOnmRirdRGpRUTqsfQ82fQ6FRyAsAS56E+KStGaVyB9xuWDNO7DiVSg4fOx8WAKM/wFCmpkW7XRyuVws25vN+kN5TJ6/B4DIQG8eH92J0d1iTU4nUnuOFpRx/5dbWLY3GwAPq4UBrSKYPKY7EYE+JqcTERFp+FS6uZFKN5Fa4HLBuvdhzsPG7ozQ6AoDkb/NXgEzxsKBJVBZYpwLS4BznobIthDVsHc5fO7nZN5ctK/q2N/bg0X3DSU6WKNjpXFIzS/j/746Vr4BXNQ9lv8b2Z6mIX4mJhMREWnYVLq5kUo3ETdxueDoJkjbBLt/Nv4ANOttLArf4XzwDTEzoUj9lX8YPhx1bIo2wIWvQ49rzctUC75cd5hnftyJ3eGi2GYH4OyOMZTY7FyRFM9FPeJMTihy+i3bk834D9Zgdxpv6Qe2juDT6/tql14REZFaotLNjVS6ibhBSQ58ezPsnXfsnMUDhj8BA+7QDowi7lCcBUtfhNVvHTvX52boNR5iOpoWy11yim0MfXERReVG2WaxwB3DWnPvOQ17RJ/Iyfhs9SH+O3c3ub/ucHpVn3gePb8j/t7ahEhERMTdVLq5kUo3kb/pyHqYcR0UpoKHDyScAQGR0PsGiO9jdjqRhqeyHF7pBsW/7uLp6QudLzP+7XW8ELz9zc13Cjak5PH4d9vZmlpAx6bBvHFNT/x9PIgO0lRSkd/7Yk0KD327FZcLIgK8eebizmQU2hjeMYa4UE05FRERcQeVbm6k0k3kb9i3EKZfCxXFENEaLv8ImnQ2O5VIw7fta/jxfijNqX4+rheM/7Fe7Ar86apD7EovIibYh5fn78HhdOHn5cGnN/SlV4sws+OJ1FmLd2fx6MxtpOSWVp1rEx3IT3cNwtNDu/mKiIj8XSrd3Eilm0gN2Ctg5j+N9dpcrmOLuycMgis/B1/9GxI5rZxO2L/Q2Gxh/YdQng8tB8OAuyBhIHjVzZEvW47kc8GU5dXOje4Wy6Pnd9DoNpGTYLM7uGrqKjak5Fede3Bke24e0sq8UCIiIg2ESjc3UukmcpKcDph9D2z46Ng5qyf0uA5GPAPeAeZlExFj5Olnl4Oz0jj2j4SBdxpTvevQv88tR/K5/8st7MooAsDH08pjoztydZ/mWhhepAZyim18vjqF7GIbH600NlkZ3S2WM9tH0S8xQjucioiInCKVbm6k0k3kJBxZD/Meg0PLjONL3zOmsfmFgp+mgYnUGTn7YMVrsHsOFKUZ58IT4fr5EBBhbjZgwc4Mbvl0PZUOF8G+nvx092BC/bwI8NFi8CKnyul08fL83UxZuJff3vUH+Xjy8fV96NFcP6NFRERqSqWbG6l0E/kT5QXw7T9h1w/GsZc/jH4Ful5hbi4R+XMOO2yZDr88bZRvLYfAZR8Yo+CCmpz2OE6ni6lL9/PCnF04nC6Gd4jh8dEdiQ+vf5s+iNRV21ILeG/ZAZbsziKnpIIQPy9m3X4GzSP070xERKQmVLq5kUo3kRPI2Qefj4GcPcaxxQO6XQmD74fwluZmE5GTl7ED3h1+bP1FD2+49mtj3bfTwGZ38MOWo3y94QjL9xqbPlzSM47nL+2qBd9FakmJzc7V765m8+F8ANo3CeKes9syotPpL9xFRETqI5VubqTSTeQEPr0M9s4zbvuFwXXfQmwPczOJyKnZv8go0e3lxrFfOJw7CbqOgVpcQy0lp5Sr313FkbwyALw9rTwxuhNX9YnX2m0itSy9oJwr3l5ZbYfTGTf3p2fzUBXeIiIif0GlmxupdBP51a6fYel/oTDV+ANw5qPQ+VKNbhOp7zJ3Qt5BWDQJjm42zrU7Dy55B3wC3f5yheWVXPPOaramFhAd5MMVSfFc1COW1tFBbn8tETmxSoeTQzmlvDxvNz9sPQpAsK8nX94ygHZN9G9RRETkj6h0cyOVbiLA2vfgh3urnxv+JJxxtylxRKSWVJTA6rdg0bPgqICQeOh/G3S7ytgY5W9wuVwcyStjX1YxN32yngq7E39vD+bcPVhrt4mYKLvYxtAXFlFsswNwRutIPrm+j0acioiI/AGVbm6k0k0avZRV8OEocNqhx7XQ5XKI6VIndjoUkVpyaAV8dIGxsQJA025w/ssQ2/OUp5w+93Myby7aV3Uc6u/Fc5d21TpSInXAxpQ85u7IqPo3On5AAg+d1wFvT001FRER+V8q3dxIpZs0WkfWw6bPYN17xnHnS+HS92p1jScRqUO2fAlLXoDsXcfONekCF74BTbue9NPkFNtYvi+HO7/YWHUuMSqAH+8chK+XhzsTi8jf9O7S/Tz9w04AujULYerYJGKCfU1OJSIiUreodHMjlW7S6LhccHgNfHY52AqMcyHx8M8V4Kt/AyKNTtYuWPBv2LfQ2OU0ojX8cyV4ev/5w4ps3DtjE0v3ZFed6xwXTJ+ECK7t15zEKPevFScif9+CnRncO2MzBWWVJEYGcP+IdpzdMUYbLIiIiPxKpZsbqXSTRqUoHb65CQ4sPnYuMAYuex8SzjAvl4iYrzgL3uwPJVngGwLDHoE+N55w9Guxzc4lbyxnd0YxAIE+nlzVJ557z26Hn7dGt4nUdSk5pVz1zipS843dhYe1i+Kt63qRX1pJRIC3CjgREWnUVLq5kUo3aTRWTDF2LqwoBqsXtBwMF70BQVpvSUR+teFj+P6OY8fdroKL3qxWvLlcLm77fAM/bk0nOsiHz27oS5sY7YQoUt8cLShj6pL9fLEmhfJKJ3GhfqTml3F5r2a8cHk3s+OJiIiYpiY9Ub37mOr1118nISEBX19f+vbty5o1a/7w2nfeeYdBgwYRFhZGWFgYw4cP/9PrRRqtzdNg7sNG4RbbA25dCdd9o8JNRKrrcR2MmwVD/g+snrD5C5g6BDZPB4zC7ZUFe/hxazpeHhbevLaXCjeReqppiB+Pj+7E++N6E+TrWTXq7cv1R/hx61GyimwmJxQREan76tVIt+nTpzN27Fjeeust+vbty+TJk/nyyy/ZtWsX0dHRx11/zTXXMHDgQAYMGICvry/PPfcc3377Ldu3bycuLu6kXlMj3aTBcjrBXg575hhTSh0VcMa9cNZj2ixBRP7a2nfhh38B4MLCwgEf89aBKNYcyAXgPxd34eq+zc1MKCJukpJTyvvLD/DhioNV52KCfZh1xxlEB2mjBRERaVwa7PTSvn370rt3b6ZMmQKA0+kkPj6eO+64g4kTJ/7l4x0OB2FhYUyZMoWxY8ee8BqbzYbNduyTu8LCQuLj41W6ScOSu9/YKCFn77FzHS+Eyz4Ea70bACsiZnC5YO8CHD/9Hx65xveSL+zDeM55LbeP7MkNgxJNDigi7vb1+iP868vNVceJkQE8cUEnBreNMjGViIjI6dUgp5dWVFSwfv16hg8fXnXOarUyfPhwVq5ceVLPUVpaSmVlJeHh4X94zaRJkwgJCan6Ex8f/7ezi9QZhUfh4HKYds2xws03FHrfCJe+p8JNRE6excJWv96MLnuC3U5j9PhVngtZH/IANxS9BXZNPRNpaC7pGcfLY7rx2lU9iAjwZn92CTd8tI7dGUVmRxMREamT6s1It7S0NOLi4lixYgX9+/evOv/AAw+wePFiVq9e/ZfPceuttzJnzhy2b9+Or++Jh8JrpJs0WHvmw2eXAb/+k/ePhAk/QURrlW0ictKyimxsTc2nrMLJvTM2YbM7aRHqxftDK2i16kHITzEu7HQJjPov+P/xB10iUn8VlFVy++cbWLonG4CzO8bw4mXdCPH3MjmZiIhI7arJSDfP05TJdM8++yzTpk1j0aJFf1i4Afj4+ODj43Mak4mcBvYK+Pn/qCrcOl0CZz4CEa1MjSUi9cv6Q7mMeXsVduexz+sGtYlkylU9jV+0k86GTZ/D7Htg+zeQPBvOfgr63qy1IkUamBA/L164rBsjX1lCXmkl83ZkMGbqSp68oBN9EyPMjiciIlIn1JvSLTIyEg8PDzIyMqqdz8jIoEmTP99h8cUXX+TZZ59l/vz5dO3atTZjitQtpbmw/kPYM9eYThoQBXdsAF+N2hSRmnt/2cFqhVub6EDeuKYnQb6/jmzx9IGkCeDlB8tehqxko/A/tBwunAK+ISYlF5Ha0CTEl4X3DWXlvhwenrmN5PQixkxdxfldm3JG60gu7dUMLw+NphcRkcar3kwvBWMjhT59+vDaa68BxkYKzZs35/bbb//DjRSef/55nnnmGebMmUO/fv1q/JravVTqtS/Hw/ZvjduevnDZB9D+PFMjiUj9szeziCe+38GyvcY0sh/vHIS/twdRQT4E+PzB53cuF6x+G+Y+As5KCGsJl38Isd1PW24ROX0yCsuZPH83X6w5XHXu3E5NeO3qHireRESkQWmwu5dOnz6dcePG8fbbb9OnTx8mT57MjBkzSE5OJiYmhrFjxxIXF8ekSZMAeO6553jsscf4/PPPGThwYNXzBAYGEhgYeFKvqdJN6qXN0+G7W8FpN447XQKD74eYjubmEpF6ZX9WMVOX7GfmplTKK50AdIsP5bvbBv7FI3/nyHrjA4CCFPDwhv63Q9cxEN2+dkKLiKkW7crk242pzNqchtMFIzs34eUx3fH18jA7moiIiFs02NINYMqUKbzwwgukp6fTvXt3Xn31Vfr27QvA0KFDSUhI4MMPPwQgISGBQ4cOHfccjz/+OE888cRJvZ5KN6l3cvfDGwPAXmYc9xwHF7xqbiYRqXdyim2Mfm0ZaQXlAAT7ejKyc1PGD0ygQ9Ma/jwszYWZt8Lun46dG3QfnPWoGxOLSF2yMDmTmz9ZT4XDSZCvJy0i/HlidCeSErS5ioiI1G8NunQ73VS6Sb1it8EH50HqOmPtpHOegS6XGesriYicpF3pRdzy6XoOZJcQ5u/F3cPbcnHPOIJ9/8auhC4XJP8AK1+HlBWABcbNgpaD3JZbROqWxbuzeOibraTmGx8EdooNZvYdZ2DRxioiIlKPqXRzI5VuUi+U5MCP9xm7BQL4hsLNiyEswcxUIlLPbD1SwLydGXyw7ABFNjtNQ3z55Pq+tI4+uSUZTtp3t8HGT421JpOuNz4ciOvp3tcQkTqhwu5kye4sbvh4HQCJUQE8MqoDZ7aPMTmZiIjIqVHp5kYq3aROs9vgu9th21fgMtZbwicYLv8AWg83N5uI1BuVDicTv97K1xuOVJ3rFh/KB+N7Ex7g7f4XtBUZ67ztnX/sXPdrYPSr4FFvNlYXkRp4YU4yry/cV3V879ltufOsNiYmEhEROTUq3dxIpZvUWWV58NX1sG+BcRzTGc55Gpr1Bh83j0oRkQbL5XJx17RNfL85DasFBrWJon3TIG4d2poQv78xnfSvOJ2w83vYOcsYpetyQudL4eKpKt5EGqAKu5N5OzJYuCuTr9YbBf+YpHj+NaIt0UG+JqcTERE5eSrd3Eilm9RJtiKYOhRy9hrTs676AlqdaXYqEaln7A4nk+fvYcrCvXh5WHjr2l6c1cGEKV/JP8KMseCshLYj4dxJEN7y9OcQkdPinSX7eebHnQA0D/fn+9sHEupfC6NqRUREaoFKNzdS6SZ1zq6fYMG/IXMHBMXCVZ9DbA+zU4lIPeJ0unhx7i6+Wn+EzCIbAP+5uAtX921uXqjkH34t3uzgEwL/XA6h8eblEZFatWp/Dvd9uZkjecYmC93iQ3lwZHv6JUaYnExEROTP1aQnsp6mTCLiDsk/wBdXGoUbwCVvq3ATkRpZuS+H/87bxRuL9pFZZCPU34vHR3c0t3ADaD8KblgAMV3AVmBstlBZbm4mEak1/RIjmHpdEpGBPgBsPpzP2PfWkJJTanIyERER99FIt7+gkW5SJxSkwuy7Yc9c4zi4GQz9P+g51tRYIlJ/FNvsvLVoH1MW7q06N7Z/Cx46rwO+Xh4mJvsf2XvgrTPAXm4UcMMehMSh4B1gdjIRqQXllQ5S88t48OutrDmYy1nto3nt6h74e2ttRxERqZs0vdSNVLqJqSpKYMPHsOxlKM4wzkV1gJsWgZcWHRaRk7NiXzY3fbyeYpu96lyrqAB+vGsQPp51qHD7zb5fjI1iynKNY/9IGP8DRLc3N5eI1Jrk9ELOe2UpThf4eXkwtF0UT1zQiZhgvd8REZG6RaWbG6l0E9NUlMBnl8Oh5caxTzCc/zK0OQd89d+iiJycQzklXPT6cvJKK4kI8Oaes9tyVodoAn08CfKtxd1J/67iLFg+GdZMBUcFJA6D674Fi8XsZCJSS+ZsT2fSjzs5+OsU08hAbz65vi8dmup9j4iI1B0q3dxIpZuY5ucHYdUb4OED3a+GPjdBTEezU4lIPbLuYC53TdtEan4ZneOC+eqWAXVrKunJyD0Ar/cxirc2I+CCVyGoidmpRKSWOJ0utqUV8MBXW0hOLyLI15PzuzblgRHtCQvQDqciImI+lW5upNJNTrs982DWXVCYahxf8xW0OdvcTCJSr6TklPLQt1tZtjcbgMSoAKbd2I/o+jpNa+UbMPcRcDkgsi2M/xECo8xOJSK1qKCskrHvr2Hz4XwAOjYN5qN/9CEqyMfcYCIi0uipdHMjlW5yWh1ZBx9fCBXFxnGbc+CaL83NJCL1xoHsEr5ef4S3l+yj0uHC02rh8qR4/nVO26odAuutrF3wySVQeARaDobhT0BEa/ANMTuZiNSSSoeTZXuzuf/LLWQX24gK8uHVK3vQv1WE2dFERKQRU+nmRird5LRwuWDeY7DiVePYLxzOuBt6XAf+4aZGE5H6IbvYxujXlnG0oByA2BBfpt3Un+YR/iYnc6OM7fD2EHBWGscWD2N308H3m5tLRGrV/qxibvl0PbszirFaYEzv5tw/oh3hmm4qIiImqElPZD1NmUTkj1SWw+y7jxVuXS6HO9bDwLtUuInISdmdUcQ176yuKtx6Ng9l6tikhlW4AcR0guGPG7d9Q43ppr88Dcsmm5lKRGpZYlQgM28byGW9muF0wRdrUhjz9kqOFpSZHU1ERORPaaTbX9BIN6k1i5411m8rTIWio8a58ydD0gRTY4lI/TFvRwYfrzzI8r3ZOF3GTn/TbupH6+ggs6PVropS8PaH5a/CvEcBizHard8/9WGFSAO35kAud36xkfTCcnw8rTw8qgNj+yeYHUtERBoRTS91I5VuUiuKM+G/7cDlNI4DouCiN7VhgoictKV7shj3/hqcv/4UH9Ephqcu7Fx/N0s4VbPuhvUfGLfDE+HGheAXamYiEallB7NLuHfGJjak5ANw/4h2/HNIK6xWi7nBRESkUVDp5kYq3cTtbEWw9j2Y/+sUqQtfh04Xg3eAublEpN6YtTmNiV9voaTCwfAO0Uwc2YHW0YFmxzKHvQLWvgOLn4fyfEgcBldNA69GVj6KNDIul4v/zt3NlIV7AUiMDOD8brFcP7AlIf5eJqcTEZGGTKWbG6l0E7eqKIU3+kH+IeP47H8ba7eJiPyFEpudnOIK5mxP55kfdwIwsHUE743rja+Xh8np6oC0TfD+uWD/dY2nThcbH2roAw2RBsvlcvH5mhT+PWsHNrsxeyAu1I+Xx3SnR/NQvDy0fLWIiLifSjc3UukmbrXpc5j5T+O21QvuWAdhCaZGEpG6b/raFB7/fjvllc6qc+MHJPDIqA546pfKYw4sgS+uhooi47jlYLjma/DUDociDVlBaSWLdmfy37m7ScktBYzy7aN/9Gm8o4BFRKTWqHRzI5Vu4haH18KqN2D7N8Zxm3NgyP9BsyRzc4lInTd7Sxq3f76x6rh1dCCX9WrGzYMTsVi0ftFxbEWwZy58f9ex8q37tXD+S+DpY242EalVGYXl3PbZBtYdygPAx9PK6G6x/OfiLnh76gMKERFxD5VubqTSTf4WWxF8fSPs/unYOasn3LMdgpqYl0tE6rzDuaU8P2cXszanAfCPgS15ZFQHLRR+spJ/hGlXHTs+52kYcId5eUTktMktqWDCB2vYfKQAgP9c3IWr+zY3OZWIiDQUNemJ9JGPSG2a+6hRuFk8oOsYGPYwXPm5CjcR+VOHc0u5cuqqqsKtQ9NgJo5sr8KtJtqfB2M+haj2xvHiF+DIenMzichpER7gzczbBnL7sNYAvL5wLwVllSanEhGRxkgj3f6CRrrJKdvyJXxzg3F77HeQONTUOCJSP2w5ks8/P91Aan4ZzcL8uG1Ya87uGENkoKZGnhKnA947G1LXGx+AdL8aznkK/MLMTiYitay80sGQFxaSUWijSbAvg9pEEh7oze3DWhPkqx1ORUTk1Gh6qRupdJMaydkH8x4DiwWSfwCXE/rfDiOeMTuZiNRxW48U8MqC3czfmQlAy8gApt3Uj5hgX5OTNQDlBTDrLtj+rXEc0hzGz9JGNiKNwLbUAm75dD1H8sqqzg3vEM1dZ7Wlc1yw1sYUEZEaU+nmRirdpEamXws7Zx077nEdjH4VrJrJLSIndiinhKdm72T+zgwArBa4qHscE0e2J1qFm3ulrIJvb4G8A9CsN0z4CTw02kWkoSutsLNkdxbzd2by1fojVefHD0jgiQs6mZhMRETqI5VubqTSTU5aUTr8t92x414TYNRLKtxE5ITsDie5JRVc8fZKDuaUYrXAhd3juP3M1rSKCjQ7XsOVdxDeGACVJeAdBFd+qun/Io3IS/N28+qCPVXH/RLDeerCzrSJCTIxlYiI1Ccq3dxIpZv8JZcL1rwDP91vHDfrA+N/AE9vc3OJSJ1VXung2ndXs+5QHgBNgn359Ia+tI5W2XZabP8WvrkZHDYIiIKx30NMR7NTichpUl7p4J0l+/nvvN0AtIkO5Ke7BuHpoQ9KRUTkr6l0cyOVbvKnygvgu9th5/fGsVcAXP4htD3H1FgiUjct2Z1Fhd3J3B3pzFhnTHGyWuD98b0Z2i7a5HSNTEUJvHUG5O43jvvfDuc8bazJKSKNwoaUPK57dzUlFQ6CfDx5bHRHLk+KNzuWiIjUcSrd3Eilm/whpxM+vgAOLgWrl7EbXtL1GuEmIie05kAuV7y9surYaoFXruxBzxZhxIX6mZisEcvYDrPvhcOrjOM2I+DcSRDRytxcInLafLrqEI/M3FZ1fNuwVvxzaGsCfTxNTCUiInWZSjc3UukmJzT3EVjxmnHbyx/GzYJmSeZmEpE6K7vYxqVvruBQTmnVuf87tz3/HKpyp05Y/xHMvtvYcdo/0vierummIo2Cy+ViQ0oen61K4ZuNqQDEhfoxbkALzunYhITIAJMTiohIXaPSzY1UuslxUlbB+yOOHY98AfreZF4eEamzktMLCfHzYsIHa0lOLyI2xJfbz2yDw+nk2n4tsGgqY92RtRu+uQGObjaKt/GzIbqD2alE5DRxuVzM3nKU5+ckczi3DABfLytf/3MAnWJDTE4nIiJ1iUo3N1LpJlVcLpj/BCyfbByHtzLW/2k3UmsAichxfknO4PqP1vHbT9moIB+m39SPRO1MWneV5sLHF0L6FmODhaunQ2xPfY8XaUQKyyt5bcEeZqw7QkFZJQCX9IjjmYu74OftYXI6ERGpC1S6uZFKN6my7GWjdAOjcJvwEwTFmBpJROqmbakFjP9gLdnFtqpzH/+jD4PbRpmYSk5Kaa6xXmf6VuO43Xkw5jOwaldDkcYkv7SCq99ZzY6jhVXn4kL9eG98Eu2b6HcCEZHGTKWbG6l0E1wu+PlBWP2mcXzmozDwbvDQArsiUt2+rGLeX3aAz1anAMYAqTPbRdO/VQQ3DEo0OZ2ctNJcmHkr7P7JOB7zGXQ439xMInLaOZ0ulu/L5pZP1lNS4QAgzN+Lf53Tjqv7NMdq1ShYEZHGSKWbG6l0EzZ9ATNvMW4P+T8Y+qCmGolINeWVDh7/bjvT1x2uOje0XRR3D29L9/hQ84LJ3zP/SVj2krFD9bmToPcN+v4v0ggdyilhe1ohk+fvZndGMQB3D2/D3cPbmpxMRETMoNLNjVS6NXJ5B+HtwVBeAGc9BoP+ZXYiEaljth4p4P6vNpOcXoTFAv1aRvDPoa00lbQhKMmBN/tDcYZxrJHOIo2aze7g3aUHeGHOLgCuSGrGHWe2IT7c3+RkIiJyOp2W0q2iooIDBw7QqlUrPD0b7ptPlW6N1K6fjCmleQeM47he8I+5+kVLRKoUllfynx92Mm2tMbotMtCbV67swcDWkSYnE7cqyYbFz8Oat43jiDYw7ntj6YGQOHOziYgp/vPjTqYu2Q+Ap9XCPWe35YZBLfHx1EYLIiKNQa2WbqWlpdxxxx189NFHAOzevZvExETuuOMO4uLimDhx4qknr4NUujVCa9+FH343os0/Em5eDCHNzMskInXGwewSJv20k/k7M3E4XVgscFH3OB4c2Z7oYF+z40lt+N/dqwEsHjDhR2jez6xUImKi9YfymDx/N0v3ZAPg5+XBvy/sxOVJ8SYnExGR2laTnqjGW3E9+OCDbN68mUWLFuHre+yXi+HDhzN9+vSapxWpS7Z9faxw63YVXP2lCjcRqVJhd3Ld+6uZsz0Dh9NFYlQAn17fl5fHdFfh1pBZLHD2k8bPhN+4HLD0JfMyiYiperUI45Pr+/L8ZV0JD/CmrNLBg99sZcnuLFbvzyG/tMLsiCIiUgfUeK7czJkzmT59Ov369cPyu8WEO3XqxL59+9waTuS0ytwJ391u3O5zM4x8TgtmiwgALpeLvZnFvL5wL4dzy4gM9OGLG/vSJibI7GhyOrU5G1oMhEPLjeM9c+DQSmjR39xcImKaK5LiubxXM277fAM/bk1n7PtrAGgXE8T3dwzUlFMRkUauxiPdsrKyiI6OPu58SUlJtRJOpN5wuSBtE3x2BVSWQuJQY5c6/fcsIsCejCJGvrKUs19ewsxNaQDcMiRRhVtjZLHAtV/Dv3ZBh9HGuY9GG6OkRaTRslgs/Pfy7lzQLbbq3K6MIvo8s4DXF+7F7nCamE5ERMxU49ItKSmJH374oer4t6Lt3XffpX9/fdIr9dAvT8PUIVCQAr4hcPHbYNWnkiKNXWp+GQ9+s5WRrywlOb0IH08rHZoGM6pLU67t18LseGIWLz8IagIXvm4Ub85K+PpGmPso2IrNTiciJvHz9uCVK7vzw51n8OLl3QAoKKvkhTm7GP/BWkor7CYnFBERM9R4eul//vMfRo4cyY4dO7Db7bzyyivs2LGDFStWsHjx4trIKFI7Kkpg1Ruw9EXj2D8CRr9i/DIlIo3SpsP5tIwI4KdtR3n8++3Y7MbohDPbR/P8ZV2JDPQxOaHUGb4hcPnHMOsO2PgprHgV0jbCFR+Df7jZ6UTEBBaLhU6xIXSKDaFFhD9rDuTyxsK9LNubzQVTlnNR91iu659AiJ+X2VFFROQ0qfFItzPOOINNmzZht9vp0qULc+fOJTo6mpUrV9KrV6/ayFjN66+/TkJCAr6+vvTt25c1a9b84bXbt2/n0ksvJSEhAYvFwuTJk2s9n9QT9gr45BJjlBtA58vggf3HpguJSKPzzYYjXPT6cvpNWsDEb7ZiszvpkxDOl7f05/3xvVW4yfGsVrhgClz5BXj6wcGl8HxLWPyC2clExGS9E8K5bVhrPr6+L0E+nuzNLObFubvp/fR8bvlkPSU2jXwTEWkMaly6AbRq1Yp33nmHNWvWsGPHDj799FO6dOni7mzHmT59Ovfeey+PP/44GzZsoFu3bowYMYLMzMwTXl9aWkpiYiLPPvssTZpo9JL8zpwH4fAq8PSFYY/ABa+ZnUhETFRe6eC5n5MBKKt04GG18MC57Zh2Uz96J2jUkvwJiwXanweXvH3s3IpXwVZkXiYRqTN6tQhj4f1Dee7SLrSLCaLC4eTn7en8e9YOnE6X2fFERKSWWVwu119+ty8sLDzpJwwODv5bgf5M37596d27N1OmTAHA6XQSHx/PHXfcwcSJE//0sQkJCdx9993cfffdNXrNwsJCQkJCKCgoqNWvTU4Dlws2fwFrphpTgACumg7tzjU3l4iYxuVy8enqFJ78fjt2p4sAbw9uO7M1/RMj6NE8zOx4Ut84nfB6b8jZCwPuhLMeAw9NIxMRg8vlYtaWo9z5hfE+tEmwL5Mu7cKwdsdvUiciInVXTXqik1rTLTQ09KR3JnU4HCd1XU1VVFSwfv16HnzwwapzVquV4cOHs3LlSre9js1mw2azVR3XpHCUOu6He2Hd+8eOhz6kwk2kkZq2JoXP16SQXWQjraAcgDB/L567tCvndNLIaDlFVisMuANm3WWMdsveA1d9od2wRQQw1ny7oFssKTklvL5wH+mF5Uz4YC0jOsWQEBHA+IEJNA3xMzumiIi40UmVbgsXLqy6ffDgQSZOnMj48eOrditduXIlH330EZMmTaqdlEB2djYOh4OYmJhq52NiYkhOTnbb60yaNIknn3zSbc8ndcSO743CzWKFvrdA6+HQ6kyzU4mICT5eeZDHvtte7dyDI9tz46BErFaVI/I39RwHleUw/3HY/RN8OAqGPQQJZ5idTETqiNvPbMMNgxJ5ctZ2vlhzmDnbMwD4aVs6027qR2yoijcRkYbipEq3IUOGVN3+97//zUsvvcRVV11Vde6CCy6gS5cuTJ06lXHjxrk/5Wn04IMPcu+991YdFxYWEh8fb2Ii+du2fwvf3W7cPuMeY7qPiDQ6LpeLd5ce4Jkfd1adiwz04YFz23FFkr7Pi5tYLNDvFnDYYN5jcGg5fDQaLn0XOl9qdjoRqSN8vTz4z8VdCPX35oPlByivdJKSW8qAZ3/Bx9PKgyPbM35gS7NjiojI33RSpdvvrVy5krfeeuu480lJSdxwww1uCXUikZGReHh4kJGRUe18RkaGWzdJ8PHxwcdHO9Q1GPsWwlf/AJcTWg6BIf9ndiIROc1cLhcfrzzEF2tSSE43Fre/eXAiE0e2P+mlE0RqrP/txmY9276Gw6vhm5shpDnE9zY7mYjUERaLhf87tz3/d2570vLLuHLqKlJyS7HZnTwxawdtmwTRJyEcT49T2vtORETqgBp/B4+Pj+edd9457vy7775bqyPCvL296dWrFwsWLKg653Q6WbBgQdU0V5Fqkn+EGeOMwq3rGLj2G/BUoSrSWBTb7Ly1eB8XTFnO499vJzm9CG8PK4+P7qjCTWqf1QP63gwTfoYOo8FZCdOvgey9ZicTkTooNtSP6Tf347ZhrarOXf3Oaob9dxEz1h6m0uE0MZ2IiJyqGo90e/nll7n00kv56aef6Nu3LwBr1qxhz549fP31124P+Hv33nsv48aNIykpiT59+jB58mRKSkqYMGECAGPHjiUuLq5qbbmKigp27NhRdTs1NZVNmzYRGBhI69atazWrmMjlMtbSWf6Kcdy8P4x+BTxq/J+7iNRDxTY7//fVFubtzKDCbvyS4u1p5YER7bioRxyRgSrf5TSyWuGiNyH3AGRsg4/Oh/E/QESrv36siDQqTUP8uH9Ee0Z3i+XGj9eRXlDO4dwyHvh6C28t3sfZHWPo0TyMcztrwx8RkfrC4nK5XDV90OHDh3nzzTerNjDo0KEDt9xyy2lZ+2zKlCm88MILpKen0717d1599dWq8m/o0KEkJCTw4YcfAsamDy1bHr8WwpAhQ1i0aNFJvV5NtoKVOmL9h8bOcQD9boXhT4Knt6mRRKR2OZwuZm9JY19WCfN3ZLDjqLHzdGJkANcPaslZ7WNoEuJrckpp1EqyjbXdMndAUCzctBCC9IuziPyxsgoHn60+xBuL9pFbUlF1/r1xSZzVIeZPHikiIrWpJj3RKZVujYlKt3om7yC8eQZUFMHwJ4yNE0SkQXO5XDz7czJvL95fdS7Y15P3xvcmqUWYppFK3VGcBR+eB9m7oVkfuOZL8As1O5WI1HGZheW8OHcXX64/gssFgT6efHx9H3o2DzM7mohIo1SrpduSJUv+9P7BgwfX5OnqPJVu9UT2Xvj6eji6yTiO7wsTfjLW1BGRBiklp5RXFuxh+d5s0gvLARjcNoqBrSI4v1sscaF+JicUOYGcfTB1GNgKIKwlXD8XAqPNTiUi9UClw8m499ewYl8O3p5WEiMDCA/w5qHzOtA5LsTseCIijUatlm5W6/F7L/x+FIHD4ajJ09V5Kt3qAYcdPjgXjqw1jgOi4KbFEBJnbi4RqRVbjuTzxZrDzN6cRpHNDoC3h5W7hrfhtmFar1PqgbSNMH0sFKRA4jC48nPw9jc7lYjUA6UVdm79bAOLdmVVnfP2sPLwqA5c3DMOfy8P7XYqIlLLarV0KygoqHZcWVnJxo0befTRR3nmmWc466yzap64DlPpVselrILv74TsXcbx0Aeh86UQ2cbcXCLidj9tPcpL83azJ7O46lyvFmHce3ZbejYPw89bI1ulHjm6Bd4ZBk47ePrB0InQ+iyI6QyaEi0if8LlcrH6QC7JRwuZuyODFftyqu7z9rTy7tgkBreNMjGhiEjDZsqabosXL+bee+9l/fr17ni6OkOlWx22cxbMGAcuB/iGwoWvQ4fzzU4lIrXgu02p3DN9E04XWC1wYfc4RndryuA2UfpEX+qvTZ/DL09DYeqxcyOfh743m5dJROoVl8vFB8sP8t6yA6TmlwEQHeTDxJHtaRkZQPf4UK1tKiLiZqaUbsnJySQlJVFcXPzXF9cjKt3qqOIseL0PlOVCp4th9Cvgq7UsRBqSQzklrD+Ux4HsEl5fuBenC65IasaDIzsQFqAdiaWBcDph5RRY+AzYy8EnBO7cCAERZicTkXrmSF4pZ/53MRV2Z9W5UV2bMnlMd7z0AZWIiNvUaum2ZcuWascul4ujR4/y7LPPYrfbWbZsWc0T12Eq3eoYuw22fQNLXoDcfRDTBW5aCB5eZicTETex2R18uiqF535OrvaLwxVJzXj2kq5YrfrEXhogpwOmDoH0rRDdEa74WEsliEiNvbFoL8//vIsmwb7klNiodLjoEhfCFb3jyS+poF+rCHonhJsdU0SkXqv1jRQsFgv/+7B+/frx/vvv0759+5onrsNUutUxn18Ju38ybgc3g2u/huiG9d+cSGNVYXfy1fojTPllD2kFxm6kraICaN80mCFto7isZzMVbtKwHd0Mn14GJZngFQBnPgy9bwBPH7OTiUg94XK5yCyyER3kwy/JmdzxxUZKK45tdBfi58XKB8/E39vTxJQiIvVbrZZuhw4dqnZstVqJiorC19e35knrAZVudcie+fDZpcbt/rfDoH+Bvz6pE6nPyisdTF97mHeX7edIXhm//USKDvLhzrPacE3f5lqLRhqXogz4+no4uNQ4bjcKrvxMmyuIyCnJLrbx+eoU1hzIZdnebAD6J0bw8KgOdI7T0iwiIqeiVku3jz/+mDFjxuDjU/1T14qKCqZNm8bYsWNrnrgOU+lWB2yfCTu+g+TZ4KgwCrcRz5idSkT+psO5pVw5dVXVws8AUUE+/HNIK67u2xxfL+1GKo2Uww4bP4GfHjB+7o1+BXqNNzuViNRzHyw/wJOzdlQdX923OZf2bEavFmEmphIRqX9qtXTz8PDg6NGjREdHVzufk5NDdHQ0DofjDx5ZP6l0M9mGT+D7248dN+kC438EX/1diNRXDqeLnUcLeejbrWw5UkCTYF9uG9aKoe2iaRLiq8WeRX6z5AVjd1OAnmNhyEQIiTM3k4jUWyU2Ozd+vI6dRwvJK62sOn9tv+Zc1iue7vGh5oUTEalHan1Nt4yMDKKioqqd37x5M8OGDSM3N7fmieswlW4myjsIU3obn/KHtoCWg+DspzSlVKSesjucrNyfw9Ql+1m6x5ji4mG1MOfuQbSODjI5nUgd5HTAvMeM3U3B2KX7kneg7Qhzc4lIvbdoVyZfb0hl1ua0qnPjByRw/RktKSq30zo6EG9PfQgmInIitVK69ejRA4vFwubNm+nUqROenscW33Q4HBw4cIBzzz2XGTNm/L30dYxKN5MseRF+ecq43XIIjP1O69mI1EPllQ5ySirYl1nMY99t42BOabX7bx/WmvtGtDMpnUg9cWglzHkI0jaApy/cshwiW5udSkQagIW7Mvly3WF+3Jpe7byflwf9EsP594WdiQ/3NymdiEjdVJOe6KS3rbnooosA2LRpEyNGjCAwMLDqPm9vbxISErj00ktPLbHI7x1cdqxws3jAuZNUuInUM+WVDv7z406mrT1Mhd1ZdT7M34uzOsRw8+BEWkcHapMEkZPRoj/8Yw58dhkcWGxstHD1DAiKMTuZiNRzw9pFM6xdNAuTM3nmx53szSwm0MeTYpudhbuyuP+rzXxxYz/9vBYROUU1nl760UcfMWbMmAa7W+n/0ki308xWBJ9dDikrIbwVXDIVmiWZnUpETkJafhk2u5MdaYU893MyKbnGqDarBZwuY8Hmh8/rQIDPSX/eIyK/l58Cb54BtgIIjIFL3zOWXhARcQOXy0VZpQNfTw82H8lnzNRVVNidtIwMwMvDQrsmwVzSI46h7aJUwolIo1ara7o1NirdThOnE1a9DktfgrJcsHrBnRshNN7sZCJyEjKLyhn+38UUlturzkUF+fDCZV3plxhBeaWDUH9vExOKNBBZu2HGWMjaCRYrDHsYBv1LI8JFxO1enrebVxbsOe78oDaR3DAoka5xIYQF6Ge7iDQ+bi/dwsPD2b17N5GRkYSFhf3pJxvaSEFOye/XcItoDSMmQdtzzM0kIn8os6icrCIbO9IKKSirZNnebBbtygKM3/1vG9qaW4e1wt9bo9pE3K6iFH68HzZ9ahyPfAH63mRuJhFpcJxOF1tSCyivdGCzO1m8K4vPVh/C9uuyEX5eHlzUI5bRXWMZ0DrS5LQiIqeP20u3jz76iCuvvBIfHx8+/PDDPy3dxo0bV/PEdZhKt9Pg4HL4cBTggrP/Df1uAw/9oi5SFzmdLibP381rC/dyop8ek8d0p2NsMG1jtBupSK1b+hIseBKsnjBuFrQYYHYiEWngdmcU8e9ZO9iTWURGoa3q/GW9mnFh91jOaB2pqaci0uBpeqkbqXSrRbYiWPUWLHzaOO5+LVz0urmZROQ4FXYnW1Pz6RIXyuT5u3lj0T4Agnw9aRcTRFyYHwB9WoZzTd8WZkYVaVxcLmNThW1fg5c/DLjTmGrqqeleIlK7XC4Xy/fm8P3mVGasO1J1vluzEG4d1ppBbSI12l1EGiy3l26FhYUn/eINrZhS6VZLnE6YdhXs/tk4Do6DW1eCb4i5uUSESoeTrCIbsaF+HM4t5bbPN7DlSEG1ayZd0oWr+jQ3KaGIVKkogfdHQPpW4/isx4ziTUTkNFmxL5tZm9OYuTGNskoHAL5eVvolRuBptXBh9zjO79pUI+BEpMFwe+lmtVr/8puky+XCYrHgcDhqlraOU+lWC2xF8O0tkDzbOE66HvrcCNEdzM0lIjicLq5+ZxWrD+TSJjqQ9MJyin63OQLArUNb8cC57U1KKCLHqSiFeY/C2nfBLxzu3go+gWanEpFGJrvYxjtL9jNrcxppBeXV7hvUJpKmIb5c1y+BLs30IbuI1G9uL90WL1580i8+ZMiQk762PlDpVgu+vxM2fAQe3nDxW9D5UrMTiQjw49ajvDh3F/uzSqqd79E8lEdGdWDJ7mwGt42kV4twkxKKyB9y2OH1PpBrTP8msh2c9wIkNqz3ZSJS97lcLhbvzmJDSj65JTY+XZVS7f6RnZtw/RktSUrQ+wkRqZ+0ppsbqXRzo91z4bvboCTTOB77HSQONTWSSGNndzh5ZOY2FiRnklV0bEHkFhH++Hp6cEXveK7r1wJvT6uJKUXkpBxcBp9eCvZfR5gENjGWbvDXL7YiYp4X5iTz+sJ91c4F+Xjy7rgkOscZo978vT00/VRE6o1aL93y8vJ477332LlzJwAdO3ZkwoQJhIc3vDd1Kt3cxFYEr/WC4gzjuNMlcPkH5mYSaUTKKx18uzGV3glhLN+bw9I9WTQJ8SW7qIKft6dXXTeiUwwXdIvjvC5N9OZXpD46uBzWTIUdM43jgCi47H1oOdjUWCLSuOWVVFBa6eD5n5P5blPacfd3jgvm2Uu60ik2WO8/RKTOq9XSbcmSJYwePZqQkBCSkpIAWL9+Pfn5+cyaNYvBgxvWmzqVbm7gcsEP/4J17xnHw5+EpAnaNEHkNCircPD95lQ+XnmI7WmFWC3gPMF3/eEdYhjdrSkXdIvVm12RhuDoZph+HeQfguBmcMc68PIzO5WICJlF5Uz8eivL9mZTYXdWu8/DaiE8wJu+LcMZ1aUpI7s0NSmliMgfq9XSrUuXLvTv358333wTDw8PABwOB7feeisrVqxg69atp568DlLp9jfZbfDzRFj3vnF81XRod665mUQaOKfTxe7MIrYcLuD95QdITi+qdr+H1cI/BiZwILuECoeLS3vGcWH3OJPSikitqSiFKb2h8AgMfgDOfNjsRCIiVewOJ5UOF3mlFTw5azsLk7OocFQv4V67qgcJEQEcyi2hW7NQ4sP9TUorInJMrZZufn5+bNq0iXbt2lU7v2vXLrp3705ZWVnNE9dhKt3+BlsxfH4FHFpuHI/6L/S+wdxMIg3UuoO5LNqVRU6JjTnbM8gtqai6z8vDwqguTbkiKZ5V+3Po0zKCM9pEmphWRE6bbV/DV/8ALHDtV9B6uNmJREROqLzSQX5pJYdySvhiTQozTzANdfyABG4d2oroYF8TEoqIGGrSE3nW9Ml79uzJzp07jyvddu7cSbdu3Wr6dNJQ7ZkHcx+BrGTwCYFL34W255idSqTBmL8jg6MFZXh5WLE7XTz/czKF5faq+/28POgWH0JkoA+3DGlVtVDxgNYq20Qalc6Xwv7Fxq7hX10PNy2C8JZmpxIROY6vlwdNQjxoEuJL12ahrD6Qy9GCcgK8PUiIDGB7WiEfrjjIRysPcmXveLrEhdI2JpBAX09iQ/0I9vUy+0sQETlOjUe6TZ8+nQceeIA77riDfv36AbBq1Spef/11nn32WTp06FB1bdeuXd2b1gQa6VZDLhfMfwKWTzaO/cLgmq+hWS8zU4k0CHaHk5fm7WZ3RjHzd2ac8JpzOsZwZZ94zmgdpR1HRcRgt8EH50HqOmN9txFPQ5tzwDvA7GQiIn9ob2Yxaw/mcl6XpoT4efFLcgYvz9vD1tSC46718rAQ4udF0xA/WkT40zo6kLvOaqN1akWkVtTq9FKr9c9/ibNYLLhcLiwWCw6HoyZPXSepdKsBlwt++j9Y87Zx3PcWGDrRKN5EpMaO5JXywfKDdGwazGerD5GcXkRpRfXvq+2bBLE7owinCz65vg+D2kSZlFZE6rTCNPjwfMjdZxyHJcC42RAab2osEZGa+mD5AZ7+YSeJkQHszy7BcaIdooD7R7TjtmGtT3M6EWkMarV0O3To0Elf26JFi5o8dZ2k0q0Gfn4IVr0OWOCC16DndWYnEqnTXC4XLhdYrcaHFcU2O1tTC9ibWcy0NYdJTi884U6jAImRAcy8fSDBvl6k5ZeRU1xBl2baEVhE/kR5ISx+DrZ+BcXpRvE2/gcIaWZ2MhGRGimvdODr5UGF3YnVAusO5XG0oIwv1x1hxb6cquuGtI2ib2I4vZqH4WG10KtFWLVBIiIip6JWS7fGRqXbSdq3ED65yLh9wWvQc6ypcUTqOrvDyT8/28CGQ3l0aBrMmoO5VNidf/m4rs1C+OLGfnhYLfh6eZyGpCLS4BSkwoejIO8AhLeCm5eAT6DZqURE3ObJWdv5YPnB4873SQgn2M+ThbuyaBUVQP/ECK7oHU+nWH1wKSInr9ZLt7S0NJYtW0ZmZiZOZ/VfEu+8886aPl2dptLtJGTthunXQvYuY0rpyOfMTiRSp1Q6nMzZnk5afhnBvl7sySzmhy1HSS8sP+5ab08rvp5WLk+KZ3S3WNrFBPHD1qP0bRmOv7cHAT6eKttE5O8rOALvjYDCI9D+fBj1EgTFmJ1KRMQtXC4Xry7Yy5Yj+RwtKGfH0cI/vd7TamFQm0iu7tuCga0j8Peu8X6DItKI1Grp9uGHH3LzzTfj7e1NREREtWG5FouF/fv3n1rqOkql259wuWDVmzDvUXDawS8c7lgP/uFmJxMxzXebUnntl72M6BTDxT2asfZgLm8u2kdKbukJr2/fJIjoYF/GD2hBmL83XZuF4mHVdAcROQ32/QKfXGzc9vKHq76AxKGmRhIRqS3T16Ywbe1hujUL5ZKecaTmlfHjtnRmb0nj978Rh/l7cdPgVlzXvwWBPirfROR4tVq6xcfHc8stt/Dggw/+5aYKDYFKtz+x6i34+f+M223OgXOehqh25mYSOY1+Ww/kUE4Jn69OYcfRQpbuyT7htREB3gxoHUlKTglBvl6M7NKEHvFhdIzV9xURMdHGz2DlFMjcAZ6+xoi3HteYnUpE5LQpKq8kJbeU6WsPs2BnJqn5ZYCxI2r3+FD6J0bQLzGCUH9v8kor6BYfqjJOpJGr1dItIiKCNWvW0KpVq78Vsr5Q6fYHDi6Hj0aDywHDHoHB94EWI5UGLr2gnIW7MkkvKGfFvmw2HymgQ9NgNh/Or7rGYoFLejRjxb5s8ksraR0dyOhuTbm2XwtNVRCRuslugy/Hw64fjeMrPoGOF5gaSUTEDHaHk+83pzFl4V72Z5Wc8BoPq4U20YFEBvpw0+BEHE4XO9MLubhHHE1D/E5zYhExQ62Wbg888ADh4eFMnDjxb4WsL1S6nUDWbvjwPCjJgi6XwyXvqHCTBiO9oJxgP0/ySiuJCPDGw2rhlfl7WHMwl40peVQ6/vhb5pC2UdwwqCWD2kSdxsQiIm7gdMLPE2HN2xAQZRRvLfqbnUpExBQul4uU3FJW7sth1f4cVu7PoajcTpi/d9VIuBMJ9PFkUJtItqcV0i8xnPtGtCOz0EZ8mD8h/l6n8SsQkdpUq6Wbw+Hg/PPPp6ysjC5duuDlVf2bx0svvVTzxHWYSrf/cXA5fHY5VJZATGe4fh54+5udSqTGXC4X6YXlWC0WCssqeXfpAfZkFrEhJb/qmjB/L4J8vaqtx9Y9PpSoIB88LBbG9Iln2poUluzO5tWrenB2Ry1CLiL1mN0GU4caU00BEofBxW9rgwURkd9JzS9jZ1ohMzel8tO2dOLD/Cgst5NbUvGHj/H1sjJhYEvuHt4GH8/qG2KVVTjw89YmWSL1Sa2Wbk8//TSPPfYY7dq1IyYm5riNFH755ZdTS11HqXT7nfwUmDoMSrMhYRBc9j4ERpudSuRPfb3+CIdySxneIZquzUIBWHMglydnbWd72p/vZPUbbw8rtwxJZFj7aHo0Dzvu/kqHEy+Phr/GpYg0AkUZsGgSbPzE2CSp1Vlw7dca0S4icgJ2hxNPDyubD+fz+Pfb6dUijHWH8tifVUxRuR0wRr8V247dTowKoHdCOP0SI5i9JY2ftqbz2OiOtIoKpHdCGJ56TylS59Vq6RYWFsbLL7/M+PHj/07GekOl26/yU4w13PIOQpMu8I+5GuEmptqXVcyszWnY7E68PaxcntQMpxNemrcLu9PFVX2aszEljxfn7q56TNMQX0L8vEhOL6o652G14HC66J0QxgXdYhnaLhofTysBPp4s3ZNNRmE5/RIjaNckyIwvU0TEHBnbjQ/aHDZjc4Xe15udSESkXlm6J4tgXy+6NgthzvYM/u/rLRSUVf7pY5oE+9KlWQgRAd70b2Vs4BAT7IvL5WL2lqME+3nRs3koZRUOooN9T9NXIiL/q1ZLtyZNmrB06VLatGnzt0LWFyrdgANLYMZYKMuDsAQY/wOENDM7lTQCReWVLNuTTaXTRXG5ndUHcgjz92ZjSh5bUguqbe8eE+xDaYWj6lNFi4Wq+0P9vcgvrf4m55IecTxyfkf8vT3IKrLRLMyv2shdEZFGb8VrMPcRsHrBhB8hPBH8IzTqTUTkFBSWV7Ino5gjeaWs2p/L6v05ZBbZKK90YHfW6Fdy/L09mHRJF9ILynEBfl4e9GoRRuvoQDIKy2ke7q/3tSK1qFZLt0mTJnH06FFeffXVvxWyvmj0pdvuuTDjOrCXQ2wPGPOpCjepVYXllazZn8vuzCI+WH6QrCLbH147rF0UiVGBzNuRUbXuWvsmQTQN8WXhriwA7h/Rjn8OacXL83ezLbWAC7rH0ioqkC5xIXozIiLyZ1wu40O3nd8fO9f/dhjxjHmZREQaGLvDyba0QrYeyeepH3ZyXucmRAf7snJfDtvTCqhhHwfA1X2bc36Xpjz63Ta6x4dxz9ltaBbmz4p92UQF+tAmJojySgdeHlY8rHo/LFJTtVq6XXzxxfzyyy9ERETQqVOn4zZS+Oabb2qeuA5r1KXbqreMncxwQZsRMOYT8PQxO5XUMQ6nq+qHtd3hpNhm51BOKSU2O+2aBBHg44mPp5WPVx7iu02phAd4sz+7BKfTRYemwXRsGsyC5ExySyoI8fNib2YxZZWOqudvGuKLze6ksKySszvGEBPsS9dmIfRvFVG1LfvezCIe/GYrfVqGc/fwtnhYLHy08iDhAd5c2D3OlP9fREQaBFsRvDscspKPnbtvLwRql2YREXf733WCSyvsFJfb2ZtZTNNQP15dsIcjeaWsP5SH0wVntI6kSYgvOcU21h7Mq1o77n8F+njSJiaQjSn5eFotdIoNZntaIYG+njx5QSfO7hiDv7cnReWVbE8rJCEigGA/T/y9PU/Xly5Sr9Rq6TZhwoQ/vf+DDz6oydPVeY2ydHO5YPs38NX1gAt6TYCRz6lwa6AO55bi5WGlScjx60LkFNv4esMRlu7J5rp+LUjJLWVY+2h+2ZlJpdPJsj3ZrD2YS3y4P83C/Fl3MJfSCke15/CwWgjz9ya7+I9HrP2vFhH+tIkOom1MIHec2QZPDwslNjuh/t5/++sVEZEayjsIy1+Fde8Zx31ugpHPa5qpiIhJ9mcVk15QTv9WEVUzN+wOJ9nFFazan8MjM7dRbLMTGehDTLDPX24e5uVhoVuzUFLzyzhaUA4Y3+K7NgtlT0YR3ZqF0qFpMMnphUQF+TBuQAI9f91cLL+0gqwiG62iArFq1Jw0ErVaujU2ja50s9vgq39A8mzjuOc4uKBxTCWuK1wuF+mF5TQJ9j3p6Y8Vdie7M4qIDPSpKs/KKx3M2Z7OnO3pXNAtjs1H8vly3WHC/L25qEccwX5eLNmdxfydGfh4GtuYrz+Ux5oDuX/6Wr9fK+2PBPl6EuTjSdqvP7TB2Cr9sl7NSIgIoE1MEF5WCxsP57PlSD6dY0PomxjB3sxi4sL8GNwmUlM/RUTqmh3fGdNNATpfBhe/DR4aBSEiUtdU2J0czCmhVVQgTpeLbzekkllUzqA2UeSWVJBTUkFSizC+Wn+EbzYcqfae/WT1TgjD29PK2gN5VDicRAf50C0+lMhAHy7rFUeP+DCsVgtOp4s9mcXYnU4O55bx0LdbiQz0ZtyABK7u0xyLxUJ5pYNXFuyh0u7knrPbEuBj/GwpttmxVTqICNTgD6lbGnTp9vrrr/PCCy+Qnp5Ot27deO211+jTp88fXv/ll1/y6KOPcvDgQdq0acNzzz3Heeedd9Kv16hKN5cLvhwPO2aCh7fxSfZZj9V4hJvD6cLudOLj6VErMf9IQVklwb6ex5U1uzOKKK1w0D0+tOqcy+WipMJRtYX3ol2ZDGgVSXiAMZLKZndgwYK35/FbdtsdTiodLvy8Paqeq8hmJ9jX67hrAUpsdvy9PVhzIBd/b0+6NAuhwu7E4XTh42ll0k87WX0gl8ljutM83J/7vtzMzE1pBHh7EBbgzfVntGR0t1henLOLNQdy6doshMwiG7klFfRtGU7PFmG8Mn8P+7NLAIgI8MbpclFss1Pp+Pv/vBMjA6qe+/c6xQbTPzGCi3rEsfFwPnaHk36JEbSKCsTLw4LFYqHS4SSzyMbR/DI6xgZriLqISH3mcsHad+HnB8FZCZ0vhYunqngTEanHXC4Xh3PLWLU/h7JKB5f2aoavp5U9mcUs35tN25gg1h3Ko6zCTsvIQKavO8zmw/l/+bx+Xh5V5dkfzXjx9rTSt2U4afll7Msyft9IiPAnITKAjSn5FNvsOJwuxg9I4KHzOlQ9psJuLGnz9pJ9nNU+hq7NQvD2sB430s7ucFJW6SDoD35Pq6mMwnK2pRZwZvtoDRBo5Gq9dPvqq6+YMWMGKSkpVFRUVLtvw4YNNX26kzZ9+nTGjh3LW2+9Rd++fZk8eTJffvklu3btIjo6+rjrV6xYweDBg5k0aRLnn38+n3/+Oc899xwbNmygc+fOJ/WaDbF0W3swlx6xAXh6eR+bGuKoxLXuAyw/3Q8e3hRe8hkbvXrQrVnIn07pq7A7Ka2w43TB3sxiPKzw0DfbyCutYPrN/UmI8GdPZjEFZZX0Tgivetzc7em8sWgfo7vFMn5AAtvTCogO8q0apbUnowiHy0WAtydF5XYyi8rZnlbI9We0xNfLg2KbnY0pebSODsRqsfDv2Tv4cetResSH8u8LO9OxaTAWC+zLKmbUq8uw2Z1c168F3eJDSS8oY29mMTM3pTGoTSR7M4s5WlBOgLcHNw5OxNNq4ZUFe/C0WokM8iY+zB+b3UmonxctIwP4bnMaFXYnD45sz5bUAtYdzGVvZjETBrYkItCbRclZtP51zYS8kgrSC6t/ctS+SRCp+WVUOpzEhvqx/9cfMDHBPkQH+bI1tcBtf9dRQT54WCykF5bTKTaY689oidMFX6xJwdvDSv9WEQzvEMOaAzn8sPUoIX5e/OucdkQFGUWrr5cHgT6e2OwO1h/MIz7cny/XHebczk3pGNsw/j2IiEgNJf9gjHhz2qHL5caIN+vp/aBNRETMkVdSwZ3TNuLr5UHLyABaRQUwsktTnp69g72ZxcSH+zN3e0a1NZq9Paz4+3iQX1rJgFYRDGwdyeT5u6sNEIgM9MbDaiGj8M+XpEmI8OdgTulx57vFh3JBt1iyimzszSwmvbCMtPxycksq6BQbzI2DEvH2tJJXWsHh3DKSWoThYbWQXWzj8zUpdGwazA2DElm0K5PSCgfNw/0BOJhdQrndQbdmofx79g6O5JXx2Pkd+ccZLYHq61sDpBeUM21tCkktwumXGE6xzU6Qr1fVNQ6nix+3HmVPZjHXD2xJiP+JC8Hfr++3LbWAgzkltI0Jom1M0Mn8NeFwutiYkkfnuBB8vYyf0bvSiwjy9SQ21K/atdnFNo7kldE9PhS7w4mnx/EDT36fy9NqDLBwOF1YLTTKArJWS7dXX32Vhx9+mPHjxzN16lQmTJjAvn37WLt2LbfddhvPPFN7O1r17duX3r17M2XKFACcTifx8fHccccdTJw48bjrx4wZQ0lJCbNnz646169fP7p3785bb711Uq/Z0Eq3dQdz+ezdF3na6wMqfMKx+TfFs7KI4JJDeDvLAFjR4lb+lT6cowXl+HpZGZMUz46jhVQ6jIXvg/088bAYo8A+WnGQvNLKE75WZKA3Pp4epOYbz3th91jS8svIKrKd8Bulp9VCm1+/iew8aqw78L9TGfsnRtClWQgz1h0m/9fX9fawUuFwVnuuLnEh5JZUVL12feLtaeXmwYlkFJazNbWw6v+L1tGBjEmK59uNqcSG+nFRj1jWHshl1f5cvD2tvHVdLzam5LF8bzYXdIsjPtyPuFA/LBYLuSUVhPl7NcpviCIiUgt2zjJGxzvt0O0quOhNrfEmIiKAUcwcySsjr7SCI3llDG4TSYifF1lFNqKCfLBYLBSUVnIot4Sft6UT4OPJtX1bYLXCZ6tTyC+tZESnGGJD/diWWsC9MzZTUHbi3znN4ONp5e7hbfly/WEOZJfQtVkonlYLReWV7M0sPm7H2eggH3y9PCitsBPs51U16CLQx5OOscEktQhj85F8EiMDObdzE+ZsT2fa2sN0ig2mZWQA32xIrXquC7rFEhdm/P8yqE0kvVqEMW3NYdILyxnZuSktIwMI8vXkuZ+TWbonm74tw/nixn4s3JXJDR+vw8fTysPndaBPywjWHMhhd0Yx321KpbDc2ITD39uD6/q1IMTfiwq7k+V7s6l0uLiweyxBvl48OWs7McG+NAn2Zd2hXEL8vLj9zDaM7NyEjMJyMgrLmfLLXnalFzG6WyyD20Yxfe1hrurTnHM7Nzltf0e1rVZLt/bt2/P4449z1VVXERQUxObNm0lMTOSxxx4jNze3qhBzt4qKCvz9/fnqq6+46KKLqs6PGzeO/Px8vvvuu+Me07x5c+69917uvvvuqnOPP/44M2fOZPPmzSd8HZvNhs12rF0vLCwkPj6+wZRuyTOfo/2m/5zwvlxXILMc/XnKfh12aj5VJMDbg5IKB/7exlDirKI//pTCaoERnZqwaFcWZZWOqmHCJ3KiUg2MUi+3pAKnyxg9dvfwtny94QjL9mRX+2Ql2NeTh0d14PM1h9mWWoDj1++CwzvE0KtFGL5eVi7qHse3G1N5Y9E+IgK8+ccZCfRqEUZBWSW7M4qxO5xVI/ZaRwUyZeFebHYnPZuHcmH3OA7mlPD56hQ6xQYzvGMMezOK6RQXQs/moQT5ejJ1yX46Ng1mROcmLNuTjdVi4duNqRzKLeG5S7sSF+rHhysOkl9ayY2DEquNIkvJKSW/rIIOTYOr7WYkIiJiqh3fw1cTjOJt+JNwxt1mJxIRkQYoLb+MBTsz6BYfyu6MYtpEB7ItrYC4UD+e+H47FXYnaQXl+HhaSUoIo2VkAO2aBBPs60mfluFM+jGZxbuzqgopq8XC+kN5RAf5kFNSwVntozlaUM7K/Tn4e3vQo3ko9l9H4UUG+eDv5cGqAzmUVzpxuf54uuzJCvb1JMjXq0YDRBKjAjiQXfKXa2vXZdef0ZJHRnVoEANBarV08/f3Z+fOnbRo0YLo6GjmzZtHt27d2LNnD/369SMnJ+dvhf8jaWlpxMXFsWLFCvr37191/oEHHmDx4sWsXr36uMd4e3vz0UcfcdVVV1Wde+ONN3jyySfJyMg44es88cQTPPnkk8edbyilG4VHsb85iCU+g8nyaEq5A/J8YsnziKQivB2Bft4s25tDfJgfj57fkbunb2L9oTyGtovi0p7N2Hm0kEqHk5ziCmZvOcqQdlG8cmV3vD2seHpYSc0vwwJYLRbeWLSX1Lwy/m9ke276eB0Hc0ppGxPII6M60q1ZKCH+XpRVONidUURCZACpeWVkFJazL6uYhIgAujYLofLXdc/ySiqw2Z28v+wAmUU2Lu0VxwXd4iipsJOSU0rbmKCq9ddS88t4evYOmob4MbpbU5qE+NI05NgQ2p1HC9mQksflveJPuGbbydiWWsDW1AIu79XsT4ff/hWXy9UgvumIiEgjteYd+PE+43bvG2HEM9rtXERETpvffp86nFtKgI9n1Rrdp2Ln0UKaBPsS9ifPUVReycRvtjJ3ezo3D27F8I4xLN+bTVyoH2EB3rSNCSTQx5OHv91G01Bf/jmkFQt3ZWJ3uAjw8SSvtILR3WLxtFrYcCifjSl5bDycT+fYYA7klDJ3ezrdmoVyTb/mzN2egQsXlyfFM6xdNCv2ZXP9h+soq3RwVvto1h3Ko6DMGBXYIiKAVftzqqbPDmoTSWJkAB+tPFSVfUjbKAa2jmDqkv0U2+wktQinXZMg4sOM35UX7sqiqLySTYfz6dk8DE8PC4PbRlFW4eD9ZQfw8/bk4h6xxIb64WG10KdlOCv25vDsz8lVA2h8vaxc3acFg9pG8tSsHdXWBr99WGvuG9HulP9+6pJaLd0SExP5+uuv6dGjB0lJSdx4443cfPPNzJ07lyuvvJLc3D/f+fBUna7SraGPdAOgvAB8Q07u0koH21IL6NE8rNpcdag+n/uv7DxayOwtadw4KPFP14gTERGResTlgoX/gSXPG8dxvWDcbPD2NzeXiIhILaqwO095AMffcSSvlBKbg3ZNgsgqsnEgu4TeCWHVfif/bV02l8vFqv3GFNAmIb5VhaTL5cLhdP3h4JHfryf3G6fTheUP1m87mF1CbmkF3ZuFAlRtaFFaYWfz4QJ6J4Sx7lAeSS3C/taAlbqkJqVbjecQnnnmmXz//ff06NGDCRMmcM899/DVV1+xbt06LrnkklMO/VciIyPx8PA4rizLyMigSZMTzw1u0qRJja4H8PHxwcengX9Ce5KFGxgL6Sf9bgOE36vJVMcOTYPp0LSBlJYiIiJisFjgzIchvg98cyOkrodfnoJzJ5mdTEREpNaYUbgBNAs79qFWVJBP1QZ4v/dbsWWxWOjfKuK4+y0WC54efzxw5kS/5//vzrC/lxAZQAIBx5339/asev1+icfnaCxq/F/K1KlTefjhhwG47bbbeP/99+nQoQP//ve/efPNN90e8Dfe3t706tWLBQsWVJ1zOp0sWLCg2si33+vfv3+16wHmzZv3h9eLiIiIyCloczZcPNW4veoN+OwKKC80N5OIiIjUDbn7zU5gmhpPLzXT9OnTGTduHG+//TZ9+vRh8uTJzJgxg+TkZGJiYhg7dixxcXFMmmR8urpixQqGDBnCs88+y6hRo5g2bRr/+c9/2LBhA507dz6p12xou5eKiIiI1JqF/4ElL4LLAVZP6DUeznwU/ELNTiYiIiJmSP4Rpl8DQx+Ewfc3iN3Oa3V6qZnGjBlDVlYWjz32GOnp6XTv3p2ff/6ZmJgYAFJSUrBajw3eGzBgAJ9//jmPPPIIDz30EG3atGHmzJknXbiJiIiISA0Mewhanw0fngeOClj7LriccP7LZicTERGR06miFDZ9BvMeN94LFGc2iMKtpurVSDczaKSbiIiISA3t+hnmPwFZO8FihQteg+7XNMo32yIiIo1OeQF8ehkcWWMcN+8PY78Hz4axqWJNeqKGsXWEiIiIiNQd7c6F21ZBp0uMT7e/uw1Wvm52KhEREaltu+fAqz2Nws031JhWetW0BlO41ZRKNxERERGpHRe9CQPuNG4veBIyd4ImWYiIiDRMZXnw7S1Qmg1hLWHsdzB0YqNe2/WUSje73c78+fN5++23KSoqAiAtLY3i4mK3hhMRERGReszLF856HMITjTXe3ugH7wyD9G1mJxMRERF3Kkg1CreyXIhqD7etgdjuZqcyXY1Lt0OHDtGlSxcuvPBCbrvtNrKysgB47rnnuO+++9weUERERETqMQ9PGDEJAqIBC6RtNHYxqygxO5mIiIi4Q0WJsYnS7p+NtVzPndRop5P+rxqXbnfddRdJSUnk5eXh5+dXdf7iiy9mwYIFbg0nIiIiIg1Au3Ph/j1w324IbgZ5B+Gbm8BWZHYyERER+TtS18NHFxg/24ObwfXzoNWZZqeqM2pcui1dupRHHnkEb+/qrWVCQgKpqaluCyYiIiIiDUxgNFw4BSwekDwbPr0U7BVmpxIREZFTUZAKH4yC1HWABS54FZolmZ2qTqlx6eZ0OnE4HMedP3LkCEFBQW4JJSIiIiINVKthMOFH8AmBw6th9j3gdJqdSkRERGrCVgQ/PQD2MghtATfMh9ZnmZ2qzqlx6XbOOecwefLkqmOLxUJxcTGPP/445513njuziYiIiEhD1LwfXPouYIFNn8KP92lXUxERkfqgKB2mXQPPtzJGrWOByz/UCLc/YHG5avYO58iRI4wYMQKXy8WePXtISkpiz549REZGsmTJEqKjo2srqykKCwsJCQmhoKCA4OBgs+OIiIiINBybvoCZ/wRc0PsGOO9FsFjMTiUiIiInkrEDPr4QSjKN44jWMPxJ6HC+ublOs5r0RDUu3QDsdjvTpk1jy5YtFBcX07NnT6655ppqGys0FCrdRERERGrRps9h5q2AC/r+E0Y+a3YiERER+V95B+Hd4VCSBdEd4eK3oEnXRvlhWU16Is+aPnl5eTm+vr5ce+21pxxQRERERASA7leDywnf3Q6r34SotpD0D7NTiYiIyG8qy2DatUbh1qQLjJsFfmFmp6oXarymW3R0NOPGjWPevHk4teitiIiIiPxdPa6Fsx4zbs++FxY8BbZiczOJiIiIYfkrkLEVAqLgqukq3GqgxqXbRx99RGlpKRdeeCFxcXHcfffdrFu3rjayiYiIiEhjccY9kHQ94IKlL8LrfaDwqNmpREREGq8j62DRc0bpBjDyeQiJMzdTPXNKa7oBFBUV8dVXX/HFF1/wyy+/kJiYyLXXXstjjz3m7oym0ppuIiIiIqfR9m9h7mNQkAIhzeGcp6DjhY1yzRgRERHTrH0XfvjXseMWA2H8D/p5zGnYSOF/7dixg2uuuYYtW7bgcDj+7tPVKSrdRERERE6zjB3w9mBwVhrHl74HXS4zN5OIiEhjUZoLr3aH8gJoMwLangNdrwSfQLOT1Qk16YlqPL30N+Xl5cyYMYOLLrqInj17kpuby/3333+qTyciIiIiYojpCJe+C74hxvHi58HZsD7YFRERqbOW/tco3GK6wFVfQO8bVLidohqXbnPmzGHcuHHExMTwz3/+k5iYGObOncuhQ4d49llt8S4iIiIibtDpIrh7K/iGQvYu+OZGsBWZnUpERKRhyz0Aa6Yat4c/AVYPU+PUdzUu3S6++GLKysr4+OOPSU9P5+2332bw4MG1kU1EREREGjPfEBj5HFg9YdvXMHUo5B0yO5WIiEjDtOxlY1qpowLikqD1WWYnqvc8a/qAjIwMgoKCaiOLiIiIiEh13a6EsJbw1QTI2Qs/3g/XzDA7lYiISMPhsMOCJ2HFq8ZxWEs4/yVtmuAGJ7WRQmFhYdXicIWFhX96bUPbbEAbKYiIiIjUAdl74I1+4LRDUCxc9Aa0GmZ2KhERkfqt8Ch8fT0cWm4cD38CBt6twu1PuH0jhbCwMDIzMwEIDQ0lLCzsuD+/nRcRERERcbvINtD3FuN2UZqxxlv+YXMziYiI1Gd2G3xysVG4eQfBZR/AGfeocHOjk5pe+ssvvxAeHg7AwoULazWQiIiIiMgJDX8S2o6ALydASRZM7gznvwxJ/zA7mYiISP2y/kP45RkoyYSAKJjwM0S2NjtVg3NS00t/LyUlhfj4eCz/03y6XC4OHz5M8+bN3RrQbJpeKiIiIlLHHN0CX1wFhUfAO9DY5dQ/3OxUIiIi9UPOPpiSBC6ncXzFJ9DxAnMz1SNun176ey1btiQrK+u487m5ubRs2bKmTyciIiIiUjNNu8I92yC6E1QUw3vnwP5FZqcSERGp++w2Y9MElxP8wuC6mSrcalGNSzeXy3XcKDeA4uJifH193RJKRERERORPWSzGYs8WK+TsgY8vhOWvmJ1KRESk7tr4GbzaA3Z8Zxxf+7U2JaplJ7WmG8C9994LgMVi4dFHH8Xf37/qPofDwerVq+nevbvbA4qIiIiInFDbc+CmxbD2HdjwMcx/EtqMgOj2ZicTERGpWxY/DwufMW4HNYWzHoe4XuZmagROunTbuHEjYIx027p1K97e3lX3eXt7061bN+677z73JxQRERER+SNNu8IFr0FpLiTPhvdHwLmToPvVZicTERGpGzZ9caxwG/wADPoXeGmm4ulw0qXbb7uWTpgwgVdeeUWbCoiIiIhI3XHOU3BwGZTnw8x/QnAcJA4xO5WIiIi5Nn0Bs+4ybg+6D8582Nw8jUyN13T74IMPVLiJiIiISN0Sngi3r4V25xnHX18Pa98De4W5uURERMyy9CWYeQs4bNBhNAxT4Xa6WVwul6umD1q3bh0zZswgJSWFiorqb2S++eYbt4WrC2qyFayIiIiImMxWBO8Oh6xk4zg8Ea79BsJbmptLRETkdLFXwE8PwPoPjONB98Gwh8DqYW6uBqImPVGNR7pNmzaNAQMGsHPnTr799lsqKyvZvn07v/zyCyEhIaccWkRERETkb/MJMjZXGPkCBDaB3P3w0WgoyTY7mYiIyOnx432/Fm6/7vR91qMq3ExS49LtP//5Dy+//DKzZs3C29ubV155heTkZK644gqaN29eGxlFRERERE6ely/0vQluXgzhraDgsPELiIiISEO36QvY8BFggTGfwBn3mJ2oUatx6bZv3z5GjRoFGLuWlpSUYLFYuOeee5g6darbA4qIiIiInJKgJnDZ+2DxgO3fGmvb1HxlFRERkbrPUQk7voMf/mUcD3vIWMdNTFXj0i0sLIyioiIA4uLi2LZtGwD5+fmUlpa6N52IiIiIyN8R292YWgOw4El4/1xY9SZUlpmZSkRExH3SNsKUJJgxFipLILYHnHGv2akE8KzpAwYPHsy8efPo0qULl19+OXfddRe//PIL8+bN46yzzqqNjCIiIiIip27gnYALfnkGDq8y/uz6Ea6aDt7+ZqcTERE5dS4XzLob8g6CfwS0HwVDJoJHjeseqQU13r00NzeX8vJyYmNjcTqdPP/886xYsYI2bdrwyCOPEBYWVltZTaHdS0VEREQaiMI02PoVLH4OKoohcShcNQ28/MxOJiIiUjPlhbB1hvFzLWUlePrC3dsgMMrsZA1eTXqiGpdujY1KNxEREZEGJmUVfHKJMQWn9w0w6r9mJxIRETl5Tge8cyYc3XTsXM9xcMGrpkVqTGrSE53UeMPCwsKTfnEVUyIiIiJSpzXvZ+zo9uklsO596HGdsfabiIhIXVdRCr88daxw63Y12Aph6ERTY8mJnVTpFhoaisVi+dNrXC4XFosFh8PhlmAiIiIiIrWm9VnQ/nxIng3vngXdr4Zhj0BQjNnJRERETqwsH947B7J3GccjJkH/W02NJH/upEq3hQsX1nYOEREREZHTa9RLUFkK+36BDR9D6ka48Rfw9DY7mYiISHWZO2H2PUbh5hVglG19bjQ7lfwFren2F7Smm4iIiEgDl7Iapl0FpTnQ/RoY+iCExpudSkRExFCSDa/2MKaRevrBP37WsggmqklPZD2VF1i6dCnXXnstAwYMIDU1FYBPPvmEZcuWncrTiYiIiIiYp3lfOO8F4/amz2ByZ5h5m7mZREREfrPkBaNwi+4ItyxV4VaP1Lh0+/rrrxkxYgR+fn5s2LABm80GQEFBAf/5z3/cHlBEREREpNZ1vhSu/hLi+xnHmz6Fg/pAWURETLTjO3jzDFj9lnF81uMQ2cbcTFIjNS7dnn76ad566y3eeecdvLy8qs4PHDiQDRs2uDWciIiIiMhp0/YcuH4O9JpgHM97zFi0WkRE5HRb8iLMGAsZW8Fihe7XQtsRZqeSGqpx6bZr1y4GDx583PmQkBDy8/PdkemEcnNzueaaawgODiY0NJTrr7+e4uLiP33M1KlTGTp0KMHBwVgsllrNJyIiIiINxKB/gZc/pK6HtwdD2kazE4mISGOy8TP45Snjdv/b4f59cNHrYLGYm0tqrMalW5MmTdi7d+9x55ctW0ZiYqJbQp3INddcw/bt25k3bx6zZ89myZIl3HTTTX/6mNLSUs4991weeuihWsslIiIiIg1MaDyM/wFCm0P+IfjgPEjfanYqERFp6MryYMY4+O5W43jw/TDiGfAPNzeXnDLPmj7gxhtv5K677uL999/HYrGQlpbGypUrue+++3j00UdrIyM7d+7k559/Zu3atSQlJQHw2muvcd555/Hiiy8SGxt7wsfdfffdACxatOikX8tms1WtUwfGrhQiIiIi0sjE9YSbl8D06+DgUvjiarhmBkR3MDuZiIg0VItfgB0zjdsdL4KhGkBU39V4pNvEiRO5+uqrOeussyguLmbw4MHccMMN3Hzzzdxxxx21kZGVK1cSGhpaVbgBDB8+HKvVyurVq936WpMmTSIkJKTqT3y8tosXERERaZT8wuCKjyGsJRSkGFNN5zwMjkqzk4mISENTXggbPjZuj3weLv8QrDWubKSOqfHfoMVi4eGHHyY3N5dt27axatUqsrKyeOqppygrK6uNjKSnpxMdHV3tnKenJ+Hh4aSnp7v1tR588EEKCgqq/hw+fNitzy8iIiIi9Yh/ONwwH1qfDY4KWDkFlr5kdioREWlI9v0Cbw2EiiKIbAu9b9T6bQ3EKdem3t7edOzYkT59+uDl5cVLL71Ey5Yta/QcEydOxGKx/Omf5OTkU414Snx8fAgODq72R0REREQasYBIuOZLGP2qcbzkhf9v777jq67vPY6/MiAEQhJ2QFkCgggiQyiK2gpl1oogKiIV3AoO9Dpbx623IlrtrXUAtnVUcIDiqlgRKIogIFMQ40JAphghzJDxu3/8SiBXZOghv4zX8/E4D8/v+/uecz4n9UvJ2++AZa9EWpIkqQzY9g28Mgz+0Q82r4IqtaHPQ85wK0MOeU+3nJwc7r77bqZMmULFihW5+eab6du3L08++SS//e1vSUhIYMSIEYf14TfeeCNDhgw5YJ9jjjmGjIwMNm7cWKQ9Ly+PrKwsMjIyDuszJUmSpMMWFwftfgNfTodlk2DCRfD5YGj2S2jeGxIqRF2hJKk0yd0J4/rDusXhdfsh0GMkVKwcaVmKrUMO3e68807GjBlDt27dmDVrFgMGDGDo0KF88MEHPPTQQwwYMICEhITD+vBatWpRq1atg/br3LkzmzdvZv78+bRv3x6AadOmUVBQQKdOnQ7rMyVJkqQfJS4O+j0BqUeFy0wX/iN8/GwY9Lw36uokSaXFVzNh8q2w4SNIrg4XvAD1O0ZdlY6AQ56zOGHCBJ555hkmTpzI22+/TX5+Pnl5eSxevJjzzz//sAO3w3HcccfRs2dPLrvsMubOncv777/P8OHDOf/88wtPLl2zZg0tWrRg7ty5ha9bv349ixYt4vPPPwfgo48+YtGiRWRlZR2xWiVJklSGJVSAHn+AM+7Y2zZ3DHyTGV1NkqTSY85YePrMMHCrWBXOfdrArQw75NDt66+/Lpxl1qpVK5KSkhgxYgRxxbS537hx42jRogVdu3ald+/edOnShbFjxxbez83NJTMzkx07dhS2jR49mrZt23LZZZcBcNppp9G2bVtee+21YqlZkiRJZdRp/wV3b4Fm3aEgD/7eA1a8G3VVkqSS7LN3YPLNEBTAiYPg+iXQ+LSoq9IRFBcEQXAoHRMSEli/fn3hctCqVauyZMmSwz48obTJzs4mLS2NLVu2eKiCJEmSispeB88PhLULITEZznsWmnWLuipJUkmzfRM82hF2fBvu33bmn6OuSD/S4eREh7ynWxAEDBkyhKSkJAB27drFlVdeSZUqVYr0e/nll39EyZIkSVIplFoXhr4FLw6Gz96GcefA6TfD6bdA/JHbfkWSVIoEAfzzhjBwq3089Lo/6opUTA45dLvooouKXF944YUxL0aSJEkqdSpUCme4Tb4Z5j8FM0aFe7yd8yTEH/JuLpKksmbTZzDzT7D8dcjJhrgE6PsoJCZFXZmKySEvLy2vXF4qSZKkQ7bkRXh1GOTvhq53wqk3Rl2RJCkK2zfBX9rBri1723rdD52uiK4mxcQRWV4qSZIk6SBOOBdyd8Dr18HU30N+bnjYwlHtoq5MklRcvpoJc8aEgVuNpnDC+VA1A9q6YrC8cabbQTjTTZIkSYclCMI93pa/vrftuDOh3xNQITm6uiRJR97i52HSPrPZ+v0VThgQXT2KucPJidxkQpIkSYqluDjo8xDUbQNp9cM9fJa/Ds9fEM58kySVTUsmhDOd96h5LBzfN7JyFD2Xl0qSJEmxllIbrng3fL5yFjx7DnwxDabcCT1HRlubJCn2Pn4VXr40fN7iV/Cr/w0PTEioEGlZipYz3SRJkqQjqeHJ0G9M+PyDx2DFu5CzNdqaJEmxs2YBvHFD+PykS+HcZyClFlRyi6ryztBNkiRJOtKOOxPaDwmfP30mPNAMPn070pIkSTEw6xF44hewYxPUbgk9RkJ8QtRVqYQwdJMkSZKKwy9+B0n/mfWQtzPc423yLZC7M9q6JEmHb/VceKwzvP3b8Lr1ALjwJUisGG1dKlHc002SJEkqDim1YMgbsHF5eLDCJ2/AnNGwIwv6jQ0PYJAklXybV8Nz58OOb4E4+PltcPrN/jmu7zF0kyRJkopL3Tbh44TzIPNNeGEwfPRiuNF2n4egQqWoK5QkHcju7fDCoDBwq9MaLpwIVTOirkollMtLJUmSpOIWFwct+kCfByEuHhaNg2n3RF2VJOlAFo6D+5vAusWQXB0Gjjdw0wE5002SJEmKSoehULk6vPgbmP0I5O2C026GqnWirkyStMfXH8LcsbDkhfC6Unp4Qml6g0jLUsnnTDdJkiQpSi3Pgqbdwufz/hqebrp9U7Q1SZJC2evg2X57A7djfg43fwmNT420LJUOhm6SJElS1M56FE6+FhKSYFMm/LEZvP/nqKuSpPJt4bMw+hTYtSW8btYdzh4D8QnR1qVSw+WlkiRJUtSqZkD3e6BlX3jpYvjuK5hyZzjjrfMw9wySpOL21Ux4dVj4vFIaDH0L6rSMtiaVOs50kyRJkkqKo9vDtYug4+Xh9ayHYcxpsOmzSMuSpHJlzXx4+T9/DjfvHf65bOCmH8HQTZIkSSpJ4uKgx0jo8xDUaAbbNsD4cyEvJ+rKJKlsK8gPZ7c90RWy10CNpnD26PDAG+lHMHSTJEmSSpqERDjpErj4LUipA1lfwjN9Yc2CqCuTpLJr5p/CfdwIoPUAuHRquLRU+pEM3SRJkqSSqkpNOOOO8PmqWfBkL9j0ebQ1SVJZEgSw9CV4vAtMuydsO/Nh6P9XSE6PtDSVfoZukiRJUkl24gVw2k3hyaZ5u+CVKyF3Z9RVSVLpFwRh0DbxYtjwERAHbQdDu99EXZnKiLggCIKoiyjJsrOzSUtLY8uWLaSmpkZdjiRJksqrzavhsc6we2t4XaMZ9HkQjjk92rokqTTK3QmvXQMfTQivu9wAJ1/j/m06qMPJiZzpJkmSJJUG6fXhghegQuXw+tvP4B994aOJkZYlSaVOEOwN3OISoPcfodtdBm6KOUM3SZIkqbRodApc9T4MegmO+zUEBfDyZeHm3y5gkaRD8++RYeAWnwgXToSOl0VdkcqoxKgLkCRJknQYqh8TPpqcAf8cAfOfgnfuhuy10HMUxPvf1SXpe/JzYeX7sGQCLHo2bOt5X/hnqXSEGLpJkiRJpVF8PPzqfyGjNfzzv2DuWFjxHvz6YajfMerqJKnkyNkK4wbAqtl727r/jzPcdMT5n8EkSZKk0iouDk66FM4eA5XS4Jvl8GQvmP2oy00lCeDbL+DvPfcGbg1OhgsmhIcmSEeYM90kSZKk0q7NeXBsd3hjBCybBP+6HXZuhjN+G3VlkhSdDR/DM2fB9o1QuSZc8CIc3T7qqlSOONNNkiRJKguSq8E5T0KPkeH1uw/ArEcgZ1u0dUlSFKbfC6O7hIFbnVZw5UwDNxU7QzdJkiSprIiLg85Xw/H9gADe/i2MORXWL426MkkqHkEAc8bCjFEQ5EOz7vCb1yC1btSVqRxyeakkSZJU1vz6L1CjCSwaD1lfhvu8dR4Gx58NtZpHXZ0kHRmbV8FLl8HqD8Lrn98OP78l2ppUrsUFgTusHkh2djZpaWls2bKF1NTUqMuRJEmSDt2OLBh/Hnw9N7yuXBOGzYUqNaKtS5JiaeVsWPYyLBwHuduhQpXwoITTbwlPepZi6HByIv/tkyRJksqqytXhwpfg5GvD6x2b4JWrYPeOaOuSpFiZ9zd4sifMHRsGbkd3hKtnwy9uM3BT5JzpdhDOdJMkSVKZsGYB/O2XUJAH1RrD8X2h0anQtGvUlUnSj7P8DXhhUPj8uF9D28HQ7Jfh/pbSEeJMN0mSJElFHdUOBr8CKRnw3QqY+Sd4th98NDHqyiTp8AQBfDYFJl0ZXp90KZz7DBzb3cBNJYqhmyRJklReND4VrpkPPUZCRuuw7dXhnm4qqfRYNQf+3AbGnQO7t4YzdnveZ9imEsnQTZIkSSpPklKg89Vw+Qxocgbk7Qx/eZ1yF6ycFXV1krR/278N9297tj9sXgkJFaHj5TBoIiRUiLo6ab/c0+0g3NNNkiRJZdaOLHjijHC56R69/wgdL4uuJkn6/5a9Ai9dEu5JCeHstoHPQVLVSMtS+eSebpIkSZIOrnJ1uGIG9B0NLc8K2966Fab9D+z8LtraJCkIYNs3MOXOMHBLrgY9R4WnMhu4qRRwpttBONNNkiRJ5UIQwKQrYMkL4XXFqtCsW7j/W2rdaGuTVD69dTt88Gj4PLkajPgYKlaOtiaVe850kyRJknR44uLCGW/nPgO1W4YblC+bBP+8IerKJJU3a+bD69fvDdwAOlxi4KZSx9BNkiRJUig+PlxmeuX70O+vYVvmm7D4ecjdFW1tksqHrRvgH/1g/pPhdfUm0P9v8PNbo61L+hFKTeiWlZXFoEGDSE1NJT09nUsuuYRt27YdsP8111xD8+bNSU5OpkGDBlx77bVs2bKlGKuWJEmSSqH4eDhhADTrHl5PugIePhE+mhhpWZLKsIJ8eP/P8Fgn2LU5bKuUDuf8DVqf4wmlKpUSoy7gUA0aNIh169YxZcoUcnNzGTp0KJdffjnjx4/fb/+1a9eydu1a/vjHP9KyZUtWrlzJlVdeydq1a5k40b8sSJIkSQfV9U7YtjE83XTruvD0wG8+gTN+F3VlksqSNQvgX7fDqtnhdaU0GPImZLSKti7pJyoVByksX76cli1bMm/ePDp06ADAW2+9Re/evfn666+pV6/eIb3PhAkTuPDCC9m+fTuJiYeWN3qQgiRJksq9vBx470GYMSq8bnIG/OxqaPbLaOuSVLoFQRjsP9wWcrdDYjJ0vwda9Q9PV5ZKoMPJiUrFTLfZs2eTnp5eGLgBdOvWjfj4eObMmcPZZ599SO+z5wdyoMAtJyeHnJycwuvs7OwfX7gkSZJUFiQmwS9uD2e7LXgGvpgWPtoMDB/HnB51hZJKm53fwd97wTfLw+uME+D88ZBeP9q6pBgqFXu6rV+/ntq1axdpS0xMpHr16qxfv/6Q3mPTpk3cc889XH755QfsN3LkSNLS0gof9es74CVJkiQAuv8BWg/Ye734OXi2P2z/NrqaJJU+27+FGQ/sDdwAut1l4KYyJ9LQ7dZbbyUuLu6Aj08++eQnf052djZ9+vShZcuW3H333Qfse9ttt7Fly5bCx+rVq3/y50uSJEllQqVU6P9XuH1teMopQEEuPHAMPNMXcn74oDNJYudmeOnS8M+MDx4N2xKTofNwaNI10tKkIyHS5aU33ngjQ4YMOWCfY445hoyMDDZu3FikPS8vj6ysLDIyMg74+q1bt9KzZ0+qVq3KpEmTqFDhwCeeJCUlkZSUdEj1S5IkSeVSxSpw7jPw7h9h2j1h25fT4fXr4KxHoEJytPVJKnl2bYFn+8Ga+XvbjuoAl0wJT0yWyqBIQ7datWpRq1atg/br3LkzmzdvZv78+bRv3x6AadOmUVBQQKdOnX7wddnZ2fTo0YOkpCRee+01KlWqFLPaJUmSpHLv+LP3hm4ASyfCVzPhoteAOKh1bGSlSSpBvpoJU+4KA7fkajBoIqQ3gKRUAzeVaaXi9FKAXr16sWHDBkaPHk1ubi5Dhw6lQ4cOjB8/HoA1a9bQtWtXnnnmGTp27Eh2djbdu3dnx44dTJo0iSpVqhS+V61atUhISDikz/X0UkmSJOkAZtwfzmBJrQdv3wFB/t57F0yAY7tHV5uk6O07Iza5GvzmNah7QrQ1ST9BmTu9FGDcuHEMHz6crl27Eh8fT//+/Xn44YcL7+fm5pKZmcmOHTsAWLBgAXPmzAGgadOmRd5rxYoVNGrUqNhqlyRJksqs02/e+7xpN3i0497r8QOgZnPo+xgc3aH4a5MUnQ0fh2Fb5pvhdbMe8MvfQ+0W0dYlFaNSM9MtKs50kyRJkg7DnLEw80+wde3etqM6wGVTo6tJUvHZsAw+mgCz/gIFeWFbi1/Bec9CXFy0tUkxcDg5kYunJUmSJMVOp8vhxuXQ5Iy9bWs+hD8eC5+/E11dko6sXdnw1fvwzFlh8F6QB/GJ8Mt7oO/jBm4ql0rN8lJJkiRJpcivH4HP/gWfTQmXl23bAM8NhP5/hZZnRV2dpFjalQ1/+yV888netgqVw9ltTbtGV5cUMUM3SZIkSbGXdhR0uBhanAl1jodlr8C3n8GLv4Gud8GpN0RdoaRY2PkdTLx4b+CWmAy/eRUadIq2LqkEcE+3g3BPN0mSJCkG8nPhnbth9iPhdfPe0OUGqH9SpGVJ+pG++wq+/De89yBsXgUJSTDkDchoDRWSo65OOmLK5OmlkiRJkkqxhArQ4w+Qvxvmjg2XnGa+CW0HQ5vzoVGXqCuUdCi2fA1LX4apv4eC3LCtWiMY8BTUaxtlZVKJ40y3g3CmmyRJkhRD+bnhyYYzRoUzZSCcIXP5dKhSC1JqR1qepB+w7RtY8gJMuROC/LCtSm047lfhkvHk9EjLk4rL4eREhm4HYegmSZIkHQE7v4NXrg5nu+2rfqdw83XDN6nk+OSfMGFIOFMVoFI6nDgIfvnf4SxWqRw5nJwovphqkiRJkqS9kqvBwOfgivcgbp9fS1bPgafPhJ2bIytN0n8UFMDCZ+HlK/YGbp2Hw81fQs97Ddykg3BPN0mSJEnRqXsCXPyvcNlp1Qx46lfhKYijGoaHLZx0CTTtFnWVUvk07fcw80/h84Zd4DevGLRJh8HlpQfh8lJJkiSpGK1dBH/vAXm79rb1eSgM3yQdeVs3wPT/gYXj9u7d9ovfwcnDPZVUwtNLJUmSJJVW9U6EC1+Cr2bCt1/ARy/C5FvC5ait+kVdnVQ2FRRA9ppwefdbt8H2jWF7XDycdhOcflO09UmllKGbJEmSpJKlUZfwEQRQkAfLXoaJQ+HDv0NGa2h3EdRuEXWVUtkx6fLwVOE9areEXqPC8ZZcLbq6pFLO5aUH4fJSSZIkKUL5eTD9D/D+n/cudUtMhn5joOVZ0dYmlXYrZ8PsR+CTN8Lr5GrQ8Qo45TqoWDna2qQS6nByIkO3gzB0kyRJkkqAb7+A5a9B5uRwCVxcAnS8HE4cCHXbRF2dVHp8+W9Y8mJ4YMma+XvbT7oU+jwYWVlSaWHoFkOGbpIkSVIJUpAPrw6HxeP3th3VHjoPd8836UB274ClE+G1a4F9YoAazaBGU+j7GFSuHll5Umlh6BZDhm6SJElSCVNQAJ+8DstegY9fgaAgbG9yBrToA20ucGmctK9VH8D482DX5vC6aTdoPSAM3I5uH2lpUmlj6BZDhm6SJElSCbZlDUy+ee+eVADVGsGZf4aazSG1bmSlSZHKXhvOCt22IVxKWpAXth9/Npw9BhKToq1PKqUM3WLI0E2SJEkq4XJ3wVu3wPZN4R5VW9eF7XHx8Ivb4dT/gri4aGuUisuaBTDrYVg2qWh7sx4w4ClngUo/kaFbDBm6SZIkSaVI9lp4pi9syizaXrcN9P8b1GwWSVnSEbfsFXjzv2D7N/s0xkGv+6FZN6jW2PBZigFDtxgydJMkSZJKmfy8cJ+3OaNhyh1722sfD/3GhMvtGp8OCRWiq1GKpa8/hH+cDTnZ4XWVWpCSAZ2vhhMviLY2qYw5nJwosZhqkiRJkqTikfCfX3NOvga2b4QF/wg3kN+4DEZ3Ce816wHn/cN9rVR6BQGsmAH/vg9WzQ7bajSFQROheuNoa5MEONPtoJzpJkmSJJUBn0+Ft+8Ig7c9ju0F5z5t8KbSZVc2fP4OzH0CVs0K2+IToeHJ4QEi1Y+Jtj6pjHN5aQwZukmSJEllzBfT4bnzIW8XVG8CbQeF+2G16gddRkRdnfTDVrwHL10SLpEGSKgI7YeE/96m1ou0NKm8cHmpJEmSJP2QJr+Agc+H4UXWFzD192H7+iWQVh8a/AzSjo62RmmPFe/C7Edh7SLYtj5sS28ILX8Nna6CtKMiLU/SD3Om20E4002SJEkqo3K2wdyxMP8p2Lxyb3ulNDj/uXC5nqc9KiprF8GCp+HDvxdtP+5MOHssVKwcSVlSeefy0hgydJMkSZLKga8/hL/3gIK8vW3Vj4GKVSB3F1zwAtRoEl19Kh92ZMHy1+HL6bBs0t729kPD03YTk6DrXZ68K0XI0C2GDN0kSZKkciLrS4iLh3f+GzLfDPd826NKbTj9Zmjey6WnOjJWfQDjBkBO9t62Y3vCSZdBs27R1SWpCEO3GDJ0kyRJksqhnG2w+DnIXgOLX4Cta/9zIy48cOH0W6BW80hLVBmw6XNY+A+o2wbe/l3471vq0eES5+P7wmk3ucRZKmEM3WLI0E2SJEkq53J3wodPwtKXYM2HYVtcfBiItLsItq6HOi2hQnK0dap02Lk5nEm5bjHMGV30Xlp9uGoWVPJ3T6mkMnSLIUM3SZIkSYXWLYF/jwxDk32lZMCZ/xsuP5X+vyCAWQ/DlzPC/QNzthS9n5AEGa2h9wNwVLtoapR0SAzdYsjQTZIkSdL3LHkR/n0fZH2xty0+EXreB+1+A3k5kFTVpYHlXRDAB4/D4vGw/qO97dUawVEdYMcm6HW/S5WlUsTQLYYM3SRJkiT9oNxd4VLTV6+GjyaEbQkVIX93ePrpOU9CvRMjLVHFbOv6cNnoF9NhwzIoyN17r9Gp0Kw7dLgYklKiq1HSj3Y4OVFiMdUkSZIkSWVPhUrhP/uOhnrtYNZf9h66kPUlPPGLcNlg3RPhxAsguTrUOjaychVjBfmwcTmk1Iat62DyrbD6AwgK9ukUByddAq3PhQadIitVUvFzpttBONNNkiRJ0iELAvhuBRAH//otZP7z/3WIg7NHQ6v+sGEpVKjs0sLSakcWTBgCK2Z8/179TnDSZeGMx7Sj4JifF3d1ko4Ql5fGkKGbJEmSpB8lCODjV8NTKjMnwzfL/3MjDtKOhi2rw8v+f4PW50RWpg5RXg6smQ8r3gv3Yvtsyn8C1n0c2wt6jYJqDaOpUdIRZ+gWQ4ZukiRJkmKiIB/euhXmjv3+vTqtoMkZ8NVMaDcYqjcJl6VWrl78daqo3J3w9u9g4bOQt6vovfgKcNnU8H+vIB8qpUVTo6Ri455ukiRJklTSxCdA7weg4cmwag50uhzG/BxytoRLTTcsDfutXRD+s0ot6Hh52D/taEhIgtS6kZVfpu3Ign/eALWPh02Z4Um0QQFkrw335steE/arUhsadYFtG2Dl+9DtbqjbJtLSJZVcznQ7CGe6SZIkSTpiFr8A79wNDTvDl/+GHd/+cN8qteCaBVDJ30tiZs18GH8+bN944H4pdaDvY9CkK8TFhUuHt22AqhnFU6ekEsPlpTFk6CZJkiSpWG34ONwz7MXfwM7vvn+/Tis45Tpo0SeciQVQsQqk1gvDoF2bIblasZZc6nw+FV4dFp44uj8ZJ4TLe2seC8np0HpA+DOWVO4ZusWQoZskSZKkSBTkw+5tYTi0cnYYxB1Io1Nh9/ZweWqPe6HTVbBqVhgelbe9xvJyYPFzYShZry2snBXOIvxqZrhH2/+f2dbpSmjZN/w5Va4BVetEUrakks/QLYYM3SRJkiRFriAfXroEcrbC0SfBnNHhLLiKKeH+YznZ4R5k+6r/M1j9AVRrBL/6E6TVhxpNw+WRpdGOLFg0Dpr3hhpNwll96xaFy26n/h5Sjwp/JqvnwOZVYWB5IHEJ0PZCaH8RHNW+WL6CpNLP0C2GDN0kSZIklTi7d8DOrDBoiouDb7+AzMkQFw8zRoVLTPenRrNwyWSFSv9ZnrouDK46XBIeGPDZ23DaTZDRqji/TVHrlsA3n0Crc8LgbPs3UP0YeLY/fDE1DBrPuAOWvRwGbD8kMRnydobPj+oQho8tzwqXi276FFr1dxmupMNm6BZDhm6SJEmSSpXP34HnL4QGP4Pj+8Lbd0BCBcjZBvk5B399QhLUOT48KOCo9pBYCao3hronwhfTIDEJTjgXarUA4qAgD777Kvzc1XOgUjq0OQ/SG4anrm5YCmsWhDPxmnaDCsnwzn+HB0ckVQ1rqtYYTr0hDMGe7L03NIyLD1+XWAnydh289gqVodt/hye+1m4Judth63qo2exH/jAlqShDtxgydJMkSZJU6gTB3mWkBflheLVrCyx8Npz9lbMNZj8SBmaJyRCfEO6DVuf4cObbodqzvPWHZtbFV4CC3H0a9ixt/ZG/hva8L5z5NvNP0KgL/Op/4ZN/Qt0TIPXocAZf2tE/7r0l6RCUydAtKyuLa665htdff534+Hj69+/Pn//8Z1JSUn7wNVdccQXvvPMOa9euJSUlhZNPPplRo0bRokWLQ/5cQzdJkiRJZdI3meEeaA1+Bvm54YyyhIrhzLRvMsPrVR9ASh349rNwtlqNpkAQLkPdV2JyOBuu9QDY+DF8MT3cZy5/N1SsCvVPCvej+3pe2L9mc+h1395lsktfgrWLwvCuQmVocgZsXgnd/wdqHRfuTVf7eKjZNHx9ztYw8Cut+9NJKrXKZOjWq1cv1q1bx5gxY8jNzWXo0KGcdNJJjB8//gdfM3bsWFq0aEGDBg3Iysri7rvvZtGiRaxYsYKEhIRD+lxDN0mSJEnaRxBA5pvhMlGA/Dxo2jWcLbevvBzY8nW4zDQhMWzL+jIM2mq12Nu2rx1ZYdhXpeaR/Q6S9COVudBt+fLltGzZknnz5tGhQwcA3nrrLXr37s3XX39NvXr1Dul9lixZQps2bfj8889p0qTJfvvk5OSQk7N3n4Ps7Gzq169v6CZJkiRJklTOHU7oFl9MNf0ks2fPJj09vTBwA+jWrRvx8fHMmXOA02r2sX37dp588kkaN25M/fr1f7DfyJEjSUtLK3wcqK8kSZIkSZK0P6UidFu/fj21a9cu0paYmEj16tVZv379AV/72GOPkZKSQkpKCpMnT2bKlClUrFjxB/vfdtttbNmypfCxevXqmHwHSZIkSZIklR+Rhm633norcXFxB3x88sknP+kzBg0axMKFC5kxYwbHHnss5557Lrt2/fBR00lJSaSmphZ5SJIkSZIkSYdjPztXFp8bb7yRIUOGHLDPMcccQ0ZGBhs3bizSnpeXR1ZWFhkZGQd8/Z5los2aNeNnP/sZ1apVY9KkSQwcOPCnli9JkiRJkiTtV6ShW61atahVq9ZB+3Xu3JnNmzczf/582rdvD8C0adMoKCigU6dOh/x5QRAQBEGRgxIkSZIkSZKkWCsVe7odd9xx9OzZk8suu4y5c+fy/vvvM3z4cM4///zCk0vXrFlDixYtmDt3LgBffvklI0eOZP78+axatYpZs2YxYMAAkpOT6d27d5RfR5IkSZIkSWVcqQjdAMaNG0eLFi3o2rUrvXv3pkuXLowdO7bwfm5uLpmZmezYsQOASpUq8d5779G7d2+aNm3KeeedR9WqVZk1a9b3DmWQJEmSJEmSYikuCIIg6iJKsuzsbNLS0tiyZYuHKkiSJEmSJJVjh5MTlZqZbpIkSZIkSVJpYegmSZIkSZIkxZihmyRJkiRJkhRjhm6SJEmSJElSjBm6SZIkSZIkSTGWGHUBJd2ew12zs7MjrkSSJEmSJElR2pMP7cmLDsTQ7SC2bt0KQP369SOuRJIkSZIkSSXB1q1bSUtLO2CfuOBQorlyrKCggLVr11K1alXi4uKiLicmsrOzqV+/PqtXryY1NTXqcqRSy7EkxY7jSYoNx5IUO44nKXbK0ngKgoCtW7dSr1494uMPvGubM90OIj4+nqOPPjrqMo6I1NTUUv8vu1QSOJak2HE8SbHhWJJix/EkxU5ZGU8Hm+G2hwcpSJIkSZIkSTFm6CZJkiRJkiTFmKFbOZSUlMRdd91FUlJS1KVIpZpjSYodx5MUG44lKXYcT1LslNfx5EEKkiRJkiRJUow5002SJEmSJEmKMUM3SZIkSZIkKcYM3SRJkiRJkqQYM3STJEmSJEmSYszQrZx59NFHadSoEZUqVaJTp07MnTs36pKkEmXkyJGcdNJJVK1aldq1a9O3b18yMzOL9Nm1axfDhg2jRo0apKSk0L9/fzZs2FCkz6pVq+jTpw+VK1emdu3a3HTTTeTl5RXnV5FKlPvuu4+4uDiuv/76wjbHknTo1qxZw4UXXkiNGjVITk6mdevWfPjhh4X3gyDgzjvvpG7duiQnJ9OtWzc+++yzIu+RlZXFoEGDSE1NJT09nUsuuYRt27YV91eRIpWfn88dd9xB48aNSU5OpkmTJtxzzz3se76g40nav3fffZczzzyTevXqERcXxyuvvFLkfqzGzpIlSzj11FOpVKkS9evX5/777z/SX+2IMXQrR1544QVuuOEG7rrrLhYsWECbNm3o0aMHGzdujLo0qcSYMWMGw4YN44MPPmDKlCnk5ubSvXt3tm/fXthnxIgRvP7660yYMIEZM2awdu1a+vXrV3g/Pz+fPn36sHv3bmbNmsXTTz/NU089xZ133hnFV5IiN2/ePMaMGcMJJ5xQpN2xJB2a7777jlNOOYUKFSowefJkPv74Yx588EGqVatW2Of+++/n4YcfZvTo0cyZM4cqVarQo0cPdu3aVdhn0KBBLFu2jClTpvDGG2/w7rvvcvnll0fxlaTIjBo1iscff5xHHnmE5cuXM2rUKO6//37+8pe/FPZxPEn7t337dtq0acOjjz663/uxGDvZ2dl0796dhg0bMn/+fB544AHuvvtuxo4de8S/3xERqNzo2LFjMGzYsMLr/Pz8oF69esHIkSMjrEoq2TZu3BgAwYwZM4IgCILNmzcHFSpUCCZMmFDYZ/ny5QEQzJ49OwiCIHjzzTeD+Pj4YP369YV9Hn/88SA1NTXIyckp3i8gRWzr1q1Bs2bNgilTpgSnn356cN111wVB4FiSDsctt9wSdOnS5QfvFxQUBBkZGcEDDzxQ2LZ58+YgKSkpeO6554IgCIKPP/44AIJ58+YV9pk8eXIQFxcXrFmz5sgVL5Uwffr0CS6++OIibf369QsGDRoUBIHjSTpUQDBp0qTC61iNncceeyyoVq1akb/r3XLLLUHz5s2P8Dc6MpzpVk7s3r2b+fPn061bt8K2+Ph4unXrxuzZsyOsTCrZtmzZAkD16tUBmD9/Prm5uUXGUosWLWjQoEHhWJo9ezatW7emTp06hX169OhBdnY2y5YtK8bqpegNGzaMPn36FBkz4FiSDsdrr71Ghw4dGDBgALVr16Zt27Y88cQThfdXrFjB+vXri4yntLQ0OnXqVGQ8paen06FDh8I+3bp1Iz4+njlz5hTfl5EidvLJJzN16lQ+/fRTABYvXszMmTPp1asX4HiSfqxYjZ3Zs2dz2mmnUbFixcI+PXr0IDMzk++++66Yvk3sJEZdgIrHpk2byM/PL/KLC0CdOnX45JNPIqpKKtkKCgq4/vrrOeWUU2jVqhUA69evp2LFiqSnpxfpW6dOHdavX1/YZ39jbc89qbx4/vnnWbBgAfPmzfvePceSdOi+/PJLHn/8cW644QZuv/125s2bx7XXXkvFihW56KKLCsfD/sbLvuOpdu3aRe4nJiZSvXp1x5PKlVtvvZXs7GxatGhBQkIC+fn5/OEPf2DQoEEAjifpR4rV2Fm/fj2NGzf+3nvsubfv1gqlgaGbJP2AYcOGsXTpUmbOnBl1KVKps3r1aq677jqmTJlCpUqVoi5HKtUKCgro0KED9957LwBt27Zl6dKljB49mosuuiji6qTS5cUXX2TcuHGMHz+e448/nkWLFnH99ddTr149x5OkmHN5aTlRs2ZNEhISvncq3IYNG8jIyIioKqnkGj58OG+88QbTp0/n6KOPLmzPyMhg9+7dbN68uUj/fcdSRkbGfsfanntSeTB//nw2btxIu3btSExMJDExkRkzZvDwww+TmJhInTp1HEvSIapbty4tW7Ys0nbcccexatUqYO94ONDf8zIyMr53eFZeXh5ZWVmOJ5UrN910E7feeivnn38+rVu3ZvDgwYwYMYKRI0cCjifpx4rV2Clrf/8zdCsnKlasSPv27Zk6dWphW0FBAVOnTqVz584RViaVLEEQMHz4cCZNmsS0adO+N7W5ffv2VKhQochYyszMZNWqVYVjqXPnznz00UdF/g9lypQppKamfu+XJqms6tq1Kx999BGLFi0qfHTo0IFBgwYVPncsSYfmlFNOITMzs0jbp59+SsOGDQFo3LgxGRkZRcZTdnY2c+bMKTKeNm/ezPz58wv7TJs2jYKCAjp16lQM30IqGXbs2EF8fNFfgxMSEigoKAAcT9KPFaux07lzZ959911yc3ML+0yZMoXmzZuXuqWlgKeXlifPP/98kJSUFDz11FPBxx9/HFx++eVBenp6kVPhpPLuqquuCtLS0oJ///vfwbp16wofO3bsKOxz5ZVXBg0aNAimTZsWfPjhh0Hnzp2Dzp07F97Py8sLWrVqFXTv3j1YtGhR8NZbbwW1atUKbrvttii+klRi7Ht6aRA4lqRDNXfu3CAxMTH4wx/+EHz22WfBuHHjgsqVKwfPPvtsYZ/77rsvSE9PD1599dVgyZIlwVlnnRU0btw42LlzZ2Gfnj17Bm3btg3mzJkTzJw5M2jWrFkwcODAKL6SFJmLLrooOOqoo4I33ngjWLFiRfDyyy8HNWvWDG6++ebCPo4naf+2bt0aLFy4MFi4cGEABA899FCwcOHCYOXKlUEQxGbsbN68OahTp04wePDgYOnSpcHzzz8fVK5cORgzZkyxf99YMHQrZ/7yl78EDRo0CCpWrBh07Ngx+OCDD6IuSSpRgP0+nnzyycI+O3fuDK6++uqgWrVqQeXKlYOzzz47WLduXZH3+eqrr4JevXoFycnJQc2aNYMbb7wxyM3NLeZvI5Us/z90cyxJh+71118PWrVqFSQlJQUtWrQIxo4dW+R+QUFBcMcddwR16tQJkpKSgq5duwaZmZlF+nz77bfBwIEDg5SUlCA1NTUYOnRosHXr1uL8GlLksrOzg+uuuy5o0KBBUKlSpeCYY44Jfvvb3wY5OTmFfRxP0v5Nnz59v78rXXTRRUEQxG7sLF68OOjSpUuQlJQUHHXUUcF9991XXF8x5uKCIAiimWMnSZIkSZIklU3u6SZJkiRJkiTFmKGbJEmSJEmSFGOGbpIkSZIkSVKMGbpJkiRJkiRJMWboJkmSJEmSJMWYoZskSZIkSZIUY4ZukiRJkiRJUowZukmSJEmSJEkxZugmSZJUhgwZMoS+fftG9vmDBw/m3nvvjcl77d69m0aNGvHhhx/G5P0kSZKKU1wQBEHURUiSJOng4uLiDnj/rrvuYsSIEQRBQHp6evEUtY/FixdzxhlnsHLlSlJSUmLyno888giTJk1i6tSpMXk/SZKk4mLoJkmSVEqsX7++8PkLL7zAnXfeSWZmZmFbSkpKzMKuH+PSSy8lMTGR0aNHx+w9v/vuOzIyMliwYAHHH398zN5XkiTpSHN5qSRJUimRkZFR+EhLSyMuLq5IW0pKyveWl/785z/nmmuu4frrr6datWrUqVOHJ554gu3btzN06FCqVq1K06ZNmTx5cpHPWrp0Kb169SIlJYU6deowePBgNm3a9IO15efnM3HiRM4888wi7Y0aNeLee+/l4osvpmrVqjRo0ICxY8cW3t+9ezfDhw+nbt26VKpUiYYNGzJy5MjC+9WqVeOUU07h+eef/4k/PUmSpOJl6CZJklTGPf3009SsWZO5c+dyzTXXcNVVVzFgwABOPvlkFixYQPfu3Rk8eDA7duwAYPPmzZxxxhm0bduWDz/8kLfeeosNGzZw7rnn/uBnLFmyhC1bttChQ4fv3XvwwQfp0KEDCxcu5Oqrr+aqq64qnKH38MMP89prr/Hiiy+SmZnJuHHjaNSoUZHXd+zYkffeey92PxBJkqRiYOgmSZJUxrVp04bf/e53NGvWjNtuu41KlSpRs2ZNLrvsMpo1a8add97Jt99+y5IlS4BwH7W2bdty77330qJFC9q2bcvf//53pk+fzqeffrrfz1i5ciUJCQnUrl37e/d69+7N1VdfTdOmTbnllluoWbMm06dPB2DVqlU0a9aMLl260LBhQ7p06cLAgQOLvL5evXqsXLkyxj8VSZKkI8vQTZIkqYw74YQTCp8nJCRQo0YNWrduXdhWp04dADZu3AiEByJMnz69cI+4lJQUWrRoAcAXX3yx38/YuXMnSUlJ+z3sYd/P37Mkds9nDRkyhEWLFtG8eXOuvfZa3n777e+9Pjk5uXAWniRJUmmRGHUBkiRJOrIqVKhQ5DouLq5I256grKCgAIBt27Zx5plnMmrUqO+9V926dff7GTVr1mTHjh3s3r2bihUrHvTz93xWu3btWLFiBZMnT+add97h3HPPpVu3bkycOLGwf1ZWFrVq1TrUrytJklQiGLpJkiSpiHbt2vHSSy/RqFEjEhMP7a+LJ554IgAff/xx4fNDlZqaynnnncd5553HOeecQ8+ePcnKyqJ69epAeKhD27ZtD+s9JUmSoubyUkmSJBUxbNgwsrKyGDhwIPPmzeOLL77gX//6F0OHDiU/P3+/r6lVqxbt2rVj5syZh/VZDz30EM899xyffPIJn376KRMmTCAjI4P09PTCPu+99x7du3f/KV9JkiSp2Bm6SZIkqYh69erx/vvvk5+fT/fu3WndujXXX3896enpxMf/8F8fL730UsaNG3dYn1W1alXuv/9+OnTowEknncRXX33Fm2++Wfg5s2fPZsuWLZxzzjk/6TtJkiQVt7ggCIKoi5AkSVLpt3PnTpo3b84LL7xA586dY/Ke5513Hm3atOH222+PyftJkiQVF2e6SZIkKSaSk5N55pln2LRpU0zeb/fu3bRu3ZoRI0bE5P0kSZKKkzPdJEmSJEmSpBhzppskSZIkSZIUY4ZukiRJkiRJUowZukmSJEmSJEkxZugmSZIkSZIkxZihmyRJkiRJkhRjhm6SJEmSJElSjBm6SZIkSZIkSTFm6CZJkiRJkiTFmKGbJEmSJEmSFGP/B9GM3ObSXUYAAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer2.sync_en(True)\n",
    "readout_module.sequencer2.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer2.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer2.connect_out0(\"I\")\n",
    "readout_module.sequencer2.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer2.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer2.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 3):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 3):\n",
    "    readout_module.get_acquisition_state(seq, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf24497d",
   "metadata": {},
   "source": [
    "Let's add the fourth sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7d6b5b28",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:32.266833Z",
     "iopub.status.busy": "2024-03-28T14:31:32.266833Z",
     "iopub.status.idle": "2024-03-28T14:31:32.601782Z",
     "shell.execute_reply": "2024-03-28T14:31:32.600630Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer3.sync_en(True)\n",
    "readout_module.sequencer3.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer3.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer3.connect_out0(\"I\")\n",
    "readout_module.sequencer3.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer3.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer3.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 4):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 4):\n",
    "    readout_module.get_acquisition_state(seq, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b394b37c",
   "metadata": {},
   "source": [
    "Let's add the fifth sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "52ecdfd7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:32.607410Z",
     "iopub.status.busy": "2024-03-28T14:31:32.607410Z",
     "iopub.status.idle": "2024-03-28T14:31:32.928664Z",
     "shell.execute_reply": "2024-03-28T14:31:32.927663Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer4.sync_en(True)\n",
    "readout_module.sequencer4.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer4.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer4.connect_out0(\"I\")\n",
    "readout_module.sequencer4.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer4.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer4.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 5):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 5):\n",
    "    readout_module.get_acquisition_state(seq, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b6e3e7ab",
   "metadata": {},
   "source": [
    "Let's add the sixth sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "11d4186b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:32.934170Z",
     "iopub.status.busy": "2024-03-28T14:31:32.933167Z",
     "iopub.status.idle": "2024-03-28T14:31:33.268275Z",
     "shell.execute_reply": "2024-03-28T14:31:33.267137Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer5.sync_en(True)\n",
    "readout_module.sequencer5.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer5.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer5.connect_out0(\"I\")\n",
    "readout_module.sequencer5.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer5.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer5.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 6):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 6):\n",
    "    readout_module.get_acquisition_state(seq, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "873b726b",
   "metadata": {},
   "source": [
    "Note that now the outputs overflow and the output signal is clipped as intended. Also note that the output range of a QRM is 1 Vpp, while it's input range is 2 Vpp. This causes the signal in the figure to be clipped at 0.5 and -0.5."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb88739b",
   "metadata": {},
   "source": [
    "Frequency multiplexing\n",
    "----------------------\n",
    "Next, we will show frequency multiplexing. We will connect the outputs of various sequencers to a single output port pair, modulate their waveforms on unique carrier frequencies and in turn acquire, demodulate and integrate the results fed back into the inputs to validate the acquired signals. In this case, for simplicity, we will modulate a square wave pulse on each sequencer and we will play with the output gain. In order to visualize the frequency multiplexing, we will preform an FFT over the acquired scope acquisitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7cc8adef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:33.273124Z",
     "iopub.status.busy": "2024-03-28T14:31:33.271689Z",
     "iopub.status.idle": "2024-03-28T14:31:36.720949Z",
     "shell.execute_reply": "2024-03-28T14:31:36.719320Z"
    }
   },
   "outputs": [],
   "source": [
    "# Reset\n",
    "if cluster:\n",
    "    cluster.reset()\n",
    "else:\n",
    "    readout_module.reset()\n",
    "# Program\n",
    "program = \"\"\"\n",
    "      wait_sync 4\n",
    "loop: play      3,3,4\n",
    "      wait      140\n",
    "      acquire   0,0,16380\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\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "650d0fa8",
   "metadata": {},
   "source": [
    "Lets start with a single sequencer with an AWG gain of 1.0 (only on path 0 to create a \"real\" pulse). Let's modulate it's output with a carrier frequency of 20MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b4330f59",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:36.727224Z",
     "iopub.status.busy": "2024-03-28T14:31:36.727224Z",
     "iopub.status.idle": "2024-03-28T14:31:37.089585Z",
     "shell.execute_reply": "2024-03-28T14:31:37.088564Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program sequencer\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")\n",
    "\n",
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# connect output paths of the sequencer\n",
    "readout_module.sequencer0.connect_out0(\"I\")\n",
    "readout_module.sequencer0.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer0.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer0.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Configure sequencer\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "readout_module.sequencer0.gain_awg_path0(1.0)\n",
    "readout_module.sequencer0.gain_awg_path1(0.0)\n",
    "readout_module.sequencer0.nco_freq(20e6)\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "readout_module.sequencer0.integration_length_acq(waveform_len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f0d47172",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:37.094009Z",
     "iopub.status.busy": "2024-03-28T14:31:37.092998Z",
     "iopub.status.idle": "2024-03-28T14:31:37.166292Z",
     "shell.execute_reply": "2024-03-28T14:31:37.164239Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Start the sequencer\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer(0)\n",
    "\n",
    "# Wait for the sequencer to stop\n",
    "readout_module.get_acquisition_state(0, 1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5211b2e7",
   "metadata": {},
   "source": [
    "Now lets have a look at the FFT of the scope acquisition to verify the presence of one tone at 20MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "50d21abf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:37.171977Z",
     "iopub.status.busy": "2024-03-28T14:31:37.170970Z",
     "iopub.status.idle": "2024-03-28T14:31:37.351931Z",
     "shell.execute_reply": "2024-03-28T14:31:37.350856Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the FFT\n",
    "fig, bx = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "yf = abs(rfft(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len]))\n",
    "xf = rfftfreq(1000, 1 / 1e3)\n",
    "norm_fact = readout_module.sequencer0.gain_awg_path0() / 2 / np.max(yf)\n",
    "bx.plot(xf[0:100], yf[0:100] * norm_fact)\n",
    "bx.set_xlabel(\"Frequency (MHz)\")\n",
    "bx.set_ylabel(\"Amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17887faf",
   "metadata": {},
   "source": [
    "Now let's have a look at the hardware demodulated and integrated results and check if it matches our expectations. Don't forget that we need to divide the integration results by the integration length. In this case, the integration length is the same as the waveform length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "d5372de1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:37.356916Z",
     "iopub.status.busy": "2024-03-28T14:31:37.355828Z",
     "iopub.status.idle": "2024-03-28T14:31:37.367243Z",
     "shell.execute_reply": "2024-03-28T14:31:37.366040Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Integration results:\n",
      "I = 0.5321441133365902\n",
      "Q = 0.06458524670249145\n",
      "R = sqrt(I^2 + Q^2) = 0.536049075598874\n"
     ]
    }
   ],
   "source": [
    "bins = acq[\"scope\"][\"acquisition\"][\"bins\"]\n",
    "I_data = bins[\"integration\"][\"path0\"][0] / waveform_len\n",
    "Q_data = bins[\"integration\"][\"path1\"][0] / waveform_len\n",
    "print(\"Integration results:\")\n",
    "print(f\"I = {I_data}\")\n",
    "print(f\"Q = {Q_data}\")\n",
    "print(f\"R = sqrt(I^2 + Q^2) = {math.sqrt(I_data**2 + Q_data**2)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e68f62f2",
   "metadata": {},
   "source": [
    "The pulse acquired at the inputs is automatically demodulated at 20MHz, but due to phase rotation caused by output-to-input latency the result is not purely real. However the amplitude of the IQ vector is 0.5 as expected because: 1Vpp output range / 2Vpp input range = 0.5.\n",
    "\n",
    "Now lets increase the number of sequencers to three, each with a slightly different AWG gain. We will modulate the signals of sequencer 0 to 2 with a carrier frequencies at 20MHz, 30MHz and 40MHz respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e3fbe551",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:37.374455Z",
     "iopub.status.busy": "2024-03-28T14:31:37.372989Z",
     "iopub.status.idle": "2024-03-28T14:31:38.286329Z",
     "shell.execute_reply": "2024-03-28T14:31:38.284309Z"
    }
   },
   "outputs": [],
   "source": [
    "num_seq = 3\n",
    "for seq in range(0, num_seq):\n",
    "    # Program sequencers\n",
    "    readout_module.sequencers[seq].sequence(\"sequence.json\")\n",
    "\n",
    "    # Configure the channel map\n",
    "    readout_module.sequencers[seq].connect_out0(\"I\")\n",
    "    readout_module.sequencers[seq].connect_out1(\"Q\")\n",
    "\n",
    "    # Connect input paths of the same sequencer.\n",
    "    readout_module.sequencers[seq].connect_acq_I(\"in0\")\n",
    "    readout_module.sequencers[seq].connect_acq_Q(\"in1\")\n",
    "\n",
    "    # Configure the sequencers\n",
    "    readout_module.sequencers[seq].sync_en(True)\n",
    "    readout_module.sequencers[seq].mod_en_awg(True)\n",
    "    readout_module.sequencers[seq].demod_en_acq(True)\n",
    "    readout_module.sequencers[seq].integration_length_acq(waveform_len)\n",
    "\n",
    "# Set the gains\n",
    "readout_module.sequencer0.gain_awg_path0(0.5)\n",
    "readout_module.sequencer0.gain_awg_path1(0.0)\n",
    "readout_module.sequencer1.gain_awg_path0(0.25)\n",
    "readout_module.sequencer1.gain_awg_path1(0.0)\n",
    "readout_module.sequencer2.gain_awg_path0(0.125)\n",
    "readout_module.sequencer2.gain_awg_path1(0.0)\n",
    "\n",
    "# Set the frequencies\n",
    "readout_module.sequencer0.nco_freq(20e6)\n",
    "readout_module.sequencer1.nco_freq(30e6)\n",
    "readout_module.sequencer2.nco_freq(40e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "caf9c6c7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:38.290265Z",
     "iopub.status.busy": "2024-03-28T14:31:38.290265Z",
     "iopub.status.idle": "2024-03-28T14:31:38.378148Z",
     "shell.execute_reply": "2024-03-28T14:31:38.376947Z"
    }
   },
   "outputs": [],
   "source": [
    "# Start the sequencers\n",
    "for seq in range(0, 3):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 3):\n",
    "    readout_module.get_acquisition_state(seq, timeout=1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9391d22",
   "metadata": {},
   "source": [
    "Now lets have a look at the FFT of the scope acquisition to verify the presence of three tones at 20MHz, 30Mhz and 40MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d624e250",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:38.384820Z",
     "iopub.status.busy": "2024-03-28T14:31:38.383296Z",
     "iopub.status.idle": "2024-03-28T14:31:38.532859Z",
     "shell.execute_reply": "2024-03-28T14:31:38.531519Z"
    }
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the FFT\n",
    "fig, bx = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "yf = abs(rfft(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len]))\n",
    "xf = rfftfreq(1000, 1 / 1e3)\n",
    "bx.plot(xf[0:100], yf[0:100] * norm_fact)\n",
    "bx.set_xlabel(\"Frequency (MHz)\")\n",
    "bx.set_ylabel(\"Amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "859af721",
   "metadata": {},
   "source": [
    "Now let's check if the hardware demodulated and integrated results match our expectations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8223db5d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:38.537440Z",
     "iopub.status.busy": "2024-03-28T14:31:38.537440Z",
     "iopub.status.idle": "2024-03-28T14:31:38.656716Z",
     "shell.execute_reply": "2024-03-28T14:31:38.655717Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sequencer 0\n",
      "Integration results:\n",
      "I = 0.2668216902784563\n",
      "Q = 0.03181729360039082\n",
      "R = sqrt(I^2 + Q^2) = 0.2687120290852383\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 1\n",
      "Integration results:\n",
      "I = -0.13065754763067902\n",
      "Q = -0.025364435759648266\n",
      "R = sqrt(I^2 + Q^2) = 0.1330967668813502\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 2\n",
      "Integration results:\n",
      "I = 0.0650591108939912\n",
      "Q = 0.016877381533952126\n",
      "R = sqrt(I^2 + Q^2) = 0.0672126023730612\n",
      "---------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for seq in range(0, num_seq):\n",
    "    readout_module.store_scope_acquisition(seq, \"scope\")\n",
    "    acq = readout_module.get_acquisitions(seq)\n",
    "    bins = acq[\"scope\"][\"acquisition\"][\"bins\"]\n",
    "    I_data = bins[\"integration\"][\"path0\"][0] / waveform_len\n",
    "    Q_data = bins[\"integration\"][\"path1\"][0] / waveform_len\n",
    "    print(f\"Sequencer {seq}\")\n",
    "    print(\"Integration results:\")\n",
    "    print(f\"I = {I_data}\")\n",
    "    print(f\"Q = {Q_data}\")\n",
    "    print(f\"R = sqrt(I^2 + Q^2) = {math.sqrt(I_data**2 + Q_data**2)}\")\n",
    "    print(\"---------------------------------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01317f5a",
   "metadata": {},
   "source": [
    "Again, the acquired signals on the input are automatically demodulated at 20MHz, 30MHz and 40MHz and we see that the amplitude of the IQ vectors match the gain values we set divided by two, which matches our expectations.\n",
    "\n",
    "Now, let's try it one final time with six sequencers, each with 0.15 AWG gain. We will modulate the outputs of sequencer 0 to 5 with carrier frequencies at 20MHz, 30Mhz, 40MHz, 50MHz, 60MHz and 70MHz respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ff05b120",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:38.662223Z",
     "iopub.status.busy": "2024-03-28T14:31:38.662223Z",
     "iopub.status.idle": "2024-03-28T14:31:40.409892Z",
     "shell.execute_reply": "2024-03-28T14:31:40.408289Z"
    }
   },
   "outputs": [],
   "source": [
    "num_seq = 6\n",
    "for seq in range(0, num_seq):\n",
    "    # Program sequencers\n",
    "    readout_module.sequencers[seq].sequence(\"sequence.json\")\n",
    "\n",
    "    # Configure the channel map\n",
    "    readout_module.sequencers[seq].connect_out0(\"I\")\n",
    "    readout_module.sequencers[seq].connect_out1(\"Q\")\n",
    "\n",
    "    # Connect input paths of the same sequencer.\n",
    "    readout_module.sequencers[seq].connect_acq_I(\"in0\")\n",
    "    readout_module.sequencers[seq].connect_acq_Q(\"in1\")\n",
    "\n",
    "    # Configure the sequencers\n",
    "    readout_module.sequencers[seq].sync_en(True)\n",
    "    readout_module.sequencers[seq].gain_awg_path0(0.15)\n",
    "    readout_module.sequencers[seq].gain_awg_path1(0.0)\n",
    "    readout_module.sequencers[seq].mod_en_awg(True)\n",
    "    readout_module.sequencers[seq].demod_en_acq(True)\n",
    "    readout_module.sequencers[seq].integration_length_acq(waveform_len)\n",
    "\n",
    "# Set the frequencies\n",
    "readout_module.sequencer0.nco_freq(20e6)\n",
    "readout_module.sequencer1.nco_freq(30e6)\n",
    "readout_module.sequencer2.nco_freq(40e6)\n",
    "readout_module.sequencer3.nco_freq(50e6)\n",
    "readout_module.sequencer4.nco_freq(60e6)\n",
    "readout_module.sequencer5.nco_freq(70e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c2631ef7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:40.415450Z",
     "iopub.status.busy": "2024-03-28T14:31:40.414450Z",
     "iopub.status.idle": "2024-03-28T14:31:40.533316Z",
     "shell.execute_reply": "2024-03-28T14:31:40.531639Z"
    }
   },
   "outputs": [],
   "source": [
    "# Start the sequencers\n",
    "for seq in range(0, 6):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 6):\n",
    "    readout_module.get_acquisition_state(seq, timeout=1)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa5585a2",
   "metadata": {},
   "source": [
    "Now lets have a look at the FFT of the scope acquisition to verify the presence of six tones at 20MHz, 30Mhz, 40MHz, 50MHz, 60MHz and 70MHz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "307990e1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:40.537339Z",
     "iopub.status.busy": "2024-03-28T14:31:40.537339Z",
     "iopub.status.idle": "2024-03-28T14:31:40.671383Z",
     "shell.execute_reply": "2024-03-28T14:31:40.669849Z"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the FFT\n",
    "fig, bx = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "yf = abs(rfft(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len]))\n",
    "xf = rfftfreq(1000, 1 / 1e3)\n",
    "bx.plot(xf[0:100], yf[0:100] * norm_fact)\n",
    "bx.set_xlabel(\"Frequency (MHz)\")\n",
    "bx.set_ylabel(\"Amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a851847",
   "metadata": {},
   "source": [
    "Note that we lose a little bit of power over the frequency range, but that is to be expected due to frequency dependant components in the output and input path. Now let's check if the hardware demodulated and integrated results match our expectations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b2323e30",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:40.675381Z",
     "iopub.status.busy": "2024-03-28T14:31:40.675381Z",
     "iopub.status.idle": "2024-03-28T14:31:40.884703Z",
     "shell.execute_reply": "2024-03-28T14:31:40.883325Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sequencer 0\n",
      "Integration results:\n",
      "I = 0.08027552515876893\n",
      "Q = 0.009718612603810454\n",
      "R = sqrt(I^2 + Q^2) = 0.08086168048253194\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 1\n",
      "Integration results:\n",
      "I = -0.07886712261846604\n",
      "Q = -0.014643869076697607\n",
      "R = sqrt(I^2 + Q^2) = 0.08021512283635561\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 2\n",
      "Integration results:\n",
      "I = 0.07708500244259892\n",
      "Q = 0.01970981924767953\n",
      "R = sqrt(I^2 + Q^2) = 0.07956490794534786\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 3\n",
      "Integration results:\n",
      "I = -0.07487933561309233\n",
      "Q = -0.024299951148021495\n",
      "R = sqrt(I^2 + Q^2) = 0.07872358304634228\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 4\n",
      "Integration results:\n",
      "I = 0.07215388373229116\n",
      "Q = 0.028684416218856864\n",
      "R = sqrt(I^2 + Q^2) = 0.07764649812753702\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 5\n",
      "Integration results:\n",
      "I = -0.06887396189545676\n",
      "Q = -0.0330742550073278\n",
      "R = sqrt(I^2 + Q^2) = 0.07640372354451436\n",
      "---------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for seq in range(0, num_seq):\n",
    "    readout_module.store_scope_acquisition(seq, \"scope\")\n",
    "    acq = readout_module.get_acquisitions(seq)\n",
    "    bins = acq[\"scope\"][\"acquisition\"][\"bins\"]\n",
    "    I_data = bins[\"integration\"][\"path0\"][0] / waveform_len\n",
    "    Q_data = bins[\"integration\"][\"path1\"][0] / waveform_len\n",
    "    print(f\"Sequencer {seq}\")\n",
    "    print(\"Integration results:\")\n",
    "    print(f\"I = {I_data}\")\n",
    "    print(f\"Q = {Q_data}\")\n",
    "    print(f\"R = sqrt(I^2 + Q^2) = {math.sqrt(I_data**2 + Q_data**2)}\")\n",
    "    print(\"---------------------------------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a056dea7",
   "metadata": {},
   "source": [
    "Taking the power loss over frequency into account, the amplitudes of the IQ vectors match our expectations again."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68f04bdc",
   "metadata": {},
   "source": [
    "Real mode\n",
    "---------------\n",
    "\n",
    "Many applications require multiple outputs to be controlled independently and only output real signals instead of a modulated IQ pair. To achieve this we will connect one sequencer to each output and only use path 0 to control an even numbered output and path 1 to control an odd numbered output. To demonstrate this, we will simply output an independently timed sine on output $\\text{O}^{1}$ and a sawtooth on output $\\text{O}^{2}$, which we will then acquire on the inputs.\n",
    "\n",
    "Lets create a Q1ASM program to sequence the waveforms for sequencer 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "80fc99ec",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:40.889801Z",
     "iopub.status.busy": "2024-03-28T14:31:40.888796Z",
     "iopub.status.idle": "2024-03-28T14:31:44.337510Z",
     "shell.execute_reply": "2024-03-28T14:31:44.336505Z"
    }
   },
   "outputs": [],
   "source": [
    "# Reset\n",
    "cluster.reset()\n",
    "\n",
    "# Program\n",
    "program = \"\"\"\n",
    "wait_sync 4\n",
    "play      1,1,4\n",
    "wait      140\n",
    "acquire   0,0,16380\n",
    "stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file\n",
    "with open(\"sequence0.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a802bbc",
   "metadata": {},
   "source": [
    "Lets create a Q1ASM program to sequence the waveforms for sequencer 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "e032ba23",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:44.343994Z",
     "iopub.status.busy": "2024-03-28T14:31:44.343994Z",
     "iopub.status.idle": "2024-03-28T14:31:44.400456Z",
     "shell.execute_reply": "2024-03-28T14:31:44.398949Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program\n",
    "program = \"\"\"\n",
    "wait_sync 4\n",
    "wait      500\n",
    "play      2,2,1000\n",
    "stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file\n",
    "with open(\"sequence1.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c17c20ae",
   "metadata": {},
   "source": [
    "Let's configure both sequencers and connect them to their respective outputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "c0e9e757",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:44.407116Z",
     "iopub.status.busy": "2024-03-28T14:31:44.405966Z",
     "iopub.status.idle": "2024-03-28T14:31:44.937072Z",
     "shell.execute_reply": "2024-03-28T14:31:44.935928Z"
    }
   },
   "outputs": [],
   "source": [
    "# Configure scope mode\n",
    "readout_module.scope_acq_sequencer_select(0)\n",
    "readout_module.scope_acq_trigger_mode_path0(\"sequencer\")\n",
    "readout_module.scope_acq_trigger_mode_path1(\"sequencer\")\n",
    "\n",
    "# Program sequencer\n",
    "num_seq = 2\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.sequencers[seq].sequence(f\"sequence{seq}.json\")\n",
    "\n",
    "# Configure the channel map\n",
    "readout_module.sequencer0.connect_out0(\"I\")\n",
    "readout_module.sequencer0.connect_acq_I(\"in0\")\n",
    "\n",
    "readout_module.sequencer1.connect_out1(\"I\")\n",
    "readout_module.sequencer1.connect_acq_I(\"in1\")\n",
    "\n",
    "# Configure sequencer\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.sequencers[seq].sync_en(True)\n",
    "    readout_module.sequencers[seq].mod_en_awg(False)\n",
    "\n",
    "readout_module.sequencer0.gain_awg_path1(\n",
    "    0.0\n",
    ")  # Disable sequencer 0 path 1, because we will not use it.\n",
    "readout_module.sequencer1.gain_awg_path0(\n",
    "    0.0\n",
    ")  # Disable sequencer 1 path 0, because we will not use it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c0b3f2c",
   "metadata": {},
   "source": [
    "Now, let start the sequencers and visualize the resulting sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "81639fcc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:44.943245Z",
     "iopub.status.busy": "2024-03-28T14:31:44.943245Z",
     "iopub.status.idle": "2024-03-28T14:31:45.295283Z",
     "shell.execute_reply": "2024-03-28T14:31:45.294779Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start sequencers\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop (only sequencer 0 will acquire)\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.get_sequencer_state(seq, timeout=1)\n",
    "readout_module.get_acquisition_state(0, timeout=1)\n",
    "\n",
    "# Get acquisition\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot result\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:2000])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:2000])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e4fd53c",
   "metadata": {},
   "source": [
    "As expected, we see a sine and sawtooth that are independently sequenced on the outputs."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c652324",
   "metadata": {},
   "source": [
    "Stop\n",
    "----\n",
    "\n",
    "Finally, let's 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": 36,
   "id": "6b94142c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-03-28T14:31:45.303220Z",
     "iopub.status.busy": "2024-03-28T14:31:45.302052Z",
     "iopub.status.idle": "2024-03-28T14:31:55.080911Z",
     "shell.execute_reply": "2024-03-28T14:31:55.078187Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Snapshot:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4:\n",
      "\tparameter                    value\n",
      "--------------------------------------------------------------------------------\n",
      "in0_gain                      :\t-6 (dB)\n",
      "in0_offset                    :\t0 (V)\n",
      "in1_gain                      :\t-6 (dB)\n",
      "in1_offset                    :\t0 (V)\n",
      "marker0_inv_en                :\tFalse \n",
      "marker1_inv_en                :\tFalse \n",
      "marker2_inv_en                :\tFalse \n",
      "marker3_inv_en                :\tFalse \n",
      "out0_offset                   :\t0 (V)\n",
      "out1_offset                   :\t0 (V)\n",
      "present                       :\tTrue \n",
      "scope_acq_avg_mode_en_path0   :\tFalse \n",
      "scope_acq_avg_mode_en_path1   :\tFalse \n",
      "scope_acq_sequencer_select    :\t0 \n",
      "scope_acq_trigger_level_path0 :\t0 \n",
      "scope_acq_trigger_level_path1 :\t0 \n",
      "scope_acq_trigger_mode_path0  :\tsequencer \n",
      "scope_acq_trigger_mode_path1  :\tsequencer \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer0:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\tin0 \n",
      "connect_acq_Q                    :\tin1 \n",
      "connect_out0                     :\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                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t0 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tTrue \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer1:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\tin1 \n",
      "connect_acq_Q                    :\tin1 \n",
      "connect_out0                     :\tI \n",
      "connect_out1                     :\tI \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                   :\t0 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tTrue \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer2:\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                     :\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                    :\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                     :\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                    :\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                     :\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                    :\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                     :\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": [
    "# 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_state())"
   ]
  }
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}