measurement_data_preparation.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "pycharm": {
     "name": "#%% md\n"
    }
   },
   "source": [
    "## First I load the 2021 data (json format)\n",
    "    * I need to plot the phase as func of freq to make sure the data looks like the generated data.\n",
    "\n",
    "## Second part, I load the 2022 data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import json\n",
    "import os\n",
    "import numpy as np\n",
    "\n",
    "def load_json(path):\n",
    "    data_dir = {}\n",
    "    # first load all data\n",
    "    for root, dirs, files in os.walk(path):\n",
    "        if 'ClosedLoopResponse_Environment.json' not in files:\n",
    "            continue\n",
    "        file = os.path.join(root, 'ClosedLoopResponse_Environment.json')\n",
    "        print('Reading data from: ', file)\n",
    "        with open(file) as jsonfile:\n",
    "            try:\n",
    "                data = json.load(jsonfile)\n",
    "                beam_line = file.split('/')[-2]\n",
    "                data_dir[beam_line+'_21'] = {\n",
    "                    'y': np.array(data['environment']['prm']['fit_prm']['TF']['H'], dtype=complex),\n",
    "                    'freq': np.array(data['environment']['prm']['fit_prm']['TF']['freq'], dtype=float)\n",
    "                }\n",
    "            except json.JSONDecodeError as e:\n",
    "                print(f'[ERROR] File {file}, produced error: {e}')\n",
    "    return data_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/3B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/5B0/ClosedLoopResponse_Environment.json\n",
      "[ERROR] File /home/kiliakis/work/data-llrf/2021/5B0/ClosedLoopResponse_Environment.json, produced error: Expecting value: line 1 column 1 (char 0)\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/4B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/1B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/5B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/3B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/8B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/2B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/8B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/6B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/7B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/1B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/6B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/4B2/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/7B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/5B1/ClosedLoopResponse_Environment.json\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2021/2B1/ClosedLoopResponse_Environment.json\n"
     ]
    }
   ],
   "source": [
    "data_dir = load_json('/home/kiliakis/work/data-llrf/2021')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['3B2_21', '4B1_21', '1B1_21', '5B2_21', '3B1_21', '8B2_21', '2B2_21', '8B1_21', '6B1_21', '7B2_21', '1B2_21', '6B2_21', '4B2_21', '7B1_21', '5B1_21', '2B1_21'])\n"
     ]
    }
   ],
   "source": [
    "print(data_dir.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# convert to dB\n",
    "for k, v in data_dir.items():\n",
    "    data_dir[k]['amplitude'] = 20 * np.log10(np.abs(v['y']))\n",
    "    data_dir[k]['real'] = v['y'].real\n",
    "    data_dir[k]['imag'] = v['y'].imag\n",
    "    del data_dir[k]['y']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>freq</th>\n",
       "      <th>amplitude</th>\n",
       "      <th>real</th>\n",
       "      <th>imag</th>\n",
       "    </tr>\n",
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       "      <th>4B1_21</th>\n",
       "      <td>[-1619443.359375, -1614550.78125, -1609658.203...</td>\n",
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       "      <th>3B1_21</th>\n",
       "      <td>[-1619443.359375, -1614550.78125, -1609658.203...</td>\n",
       "      <td>[-14.487696517960305, -27.50301068354199, -27....</td>\n",
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      "text/plain": [
       "                                                     freq  \\\n",
       "3B2_21  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "4B1_21  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "1B1_21  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "5B2_21  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "3B1_21  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "\n",
       "                                                amplitude  \\\n",
       "3B2_21  [-21.777909296765575, -15.057012209125634, -14...   \n",
       "4B1_21  [-16.549652269096566, -20.01969655997585, -20....   \n",
       "1B1_21  [-20.2673641620488, -19.779742221907256, -18.4...   \n",
       "5B2_21  [-13.816465626241573, -19.706971066659623, -25...   \n",
       "3B1_21  [-14.487696517960305, -27.50301068354199, -27....   \n",
       "\n",
       "                                                     real  \\\n",
       "3B2_21  [0.08133579725841898, 0.051474840390077534, 0....   \n",
       "4B1_21  [-0.026679795952774418, -0.07647726969086971, ...   \n",
       "1B1_21  [0.09695721712767796, 0.09919239881532062, 0.0...   \n",
       "5B2_21  [0.15931370325321093, 0.06474392932533353, -0....   \n",
       "3B1_21  [0.1625850605118769, 0.01047347697587523, 0.03...   \n",
       "\n",
       "                                                     imag  \n",
       "3B2_21  [0.005011469983590167, -0.16899911501622603, 0...  \n",
       "4B1_21  [-0.1463588317648657, -0.06407789716197017, 0....  \n",
       "1B1_21  [-0.0014954233612149335, -0.026098106680390566...  \n",
       "5B2_21  [-0.12707608641609552, -0.08066121124737649, -...  \n",
       "3B1_21  [-0.09564568737505466, -0.04083323830963009, 0...  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.DataFrame.from_dict(data_dir, orient='index')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "version_major": 2,
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",
      "text/html": [
       "\n",
       "            <div style=\"display: inline-block;\">\n",
       "                <div class=\"jupyter-widgets widget-label\" style=\"text-align: center;\">\n",
       "                    Figure\n",
       "                </div>\n",
       "                <img 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' width=432.0/>\n",
       "            </div>\n",
       "        "
      ],
      "text/plain": [
       "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib widget\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "# visualize the data\n",
    "for index, row in df.sample(n=3).iterrows():\n",
    "    y = row['y']\n",
    "    x = row['x']\n",
    "    plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# save dataframe to file\n",
    "df.to_pickle('./data/tf-measurement-2021.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# freq seems to be a bit off\n",
    "freqs = np.zeros((len(df), len(df.x[0])), dtype=np.float32)\n",
    "index = 0\n",
    "for _, row in df.iterrows():\n",
    "    freqs[index, :] = row.values[1]\n",
    "    index+=1\n",
    "# assert all freqs are equal\n",
    "np.unique(np.diff(freqs), axis=1)\n",
    "x = df.iloc[0].x.astype(np.float32)\n",
    "df = df.drop(columns='x')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3B2</th>\n",
       "      <td>[-21.777909296765575, -15.057012209125634, -14...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4B1</th>\n",
       "      <td>[-16.549652269096566, -20.01969655997585, -20....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1B1</th>\n",
       "      <td>[-20.2673641620488, -19.779742221907256, -18.4...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5B2</th>\n",
       "      <td>[-13.816465626241573, -19.706971066659623, -25...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3B1</th>\n",
       "      <td>[-14.487696517960305, -27.50301068354199, -27....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                     y\n",
       "3B2  [-21.777909296765575, -15.057012209125634, -14...\n",
       "4B1  [-16.549652269096566, -20.01969655997585, -20....\n",
       "1B1  [-20.2673641620488, -19.779742221907256, -18.4...\n",
       "5B2  [-13.816465626241573, -19.706971066659623, -25...\n",
       "3B1  [-14.487696517960305, -27.50301068354199, -27...."
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import numpy as np\n",
    "\n",
    "def load_npz(path):\n",
    "    data_dir = {}\n",
    "    # first load all data\n",
    "    for root, dirs, files in os.walk(path):\n",
    "        for file in files:\n",
    "            if 'closed_loop_response__transfer_function__' not in file:\n",
    "                continue\n",
    "\n",
    "            file = os.path.join(root, file)\n",
    "            print('Reading data from: ', file)\n",
    "            try:\n",
    "                beam_line = file.split('/')[-2]\n",
    "                timestamp = file.split('_function__')[1].split('.npz')[0]\n",
    "                data = np.load(file)\n",
    "                # print(list(data.keys()))\n",
    "                data_dir[beam_line+'_'+timestamp] = {\n",
    "                    'y': np.array(data['h'], dtype=complex),\n",
    "                    'freq': np.array(data['freq'], dtype=float)\n",
    "                }\n",
    "            except Exception as e:\n",
    "                print(f'[ERROR] File {file}, produced error: {e}')\n",
    "\n",
    "    return data_dir"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_173447.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_173834.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_171151.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_174043.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_171806.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_174519.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_173322.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103523.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103009.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_173652.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103428.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_102725.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_171543.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_171956.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103634.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103729.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_171321.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_102926.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_101040.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_104406.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103334.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_103505.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_095902.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_102051.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_104225.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_100650.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_104056.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_174158.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_102252.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_103835.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_102527.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_170934.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220413_103822.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220412_172134.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_100530.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B2/closed_loop_response__transfer_function__220414_100242.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_154713.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_121205.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_120948.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_121043.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_115026.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_154946.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_115442.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_120759.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_115227.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_155232.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_154447.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_115330.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_150054.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_155042.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_120642.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_150212.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220512_155144.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B1/closed_loop_response__transfer_function__220513_115628.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_151332.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_100623.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_151112.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_090756.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_093143.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_151229.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_144155.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_151017.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_150911.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_143915.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_144606.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_100315.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_144449.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_090155.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_093759.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_090430.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_090541.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_100734.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_093337.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_085941.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_100140.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_100855.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220512_150707.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_093936.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B1/closed_loop_response__transfer_function__220513_093557.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_161019.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_111041.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_094216.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_112123.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160534.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160239.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_111640.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_112316.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_094049.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_104715.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_112501.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_111848.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_093612.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_093858.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160159.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160853.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220513_093240.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160759.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_145209.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160930.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/5B2/closed_loop_response__transfer_function__220512_160712.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_153257.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_111900.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_112914.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_113704.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_112033.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_113604.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_145836.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_111739.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_153354.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_113232.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_153718.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_145603.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_112224.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_111540.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_153456.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_154016.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220512_153627.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_113403.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B1/closed_loop_response__transfer_function__220513_113850.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_124152.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_151703.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_151551.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_124035.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_124411.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_152411.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_130814.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_152926.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_123854.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_152108.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_123254.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_153321.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_153119.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_125956.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_124243.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_123419.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_125743.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_151841.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_131213.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_153227.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_130937.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_153411.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_152302.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_152810.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_125858.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_125613.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_130146.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_131404.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220513_131118.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B2/closed_loop_response__transfer_function__220512_152536.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220504_143704.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220502_161645.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220503_164354.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220503_165141.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220429_115246.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220513_145005.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220502_163009.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220429_114245.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220513_145127.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220513_145243.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220502_162220.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220503_164515.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220502_162421.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220513_145423.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220509_150345.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220502_162849.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220502_161517.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/3B0/closed_loop_response__transfer_function__220509_145812.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_121419.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220412_170334.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220412_170157.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_121554.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220412_170623.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_120945.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220413_110452.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220413_110731.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_121324.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220413_110835.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220413_110544.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220412_170000.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220412_165737.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_114752.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220413_110640.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_114455.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_121120.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220413_110926.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_115613.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_115043.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/2B2/closed_loop_response__transfer_function__220414_115136.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_100410.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_092418.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_094252.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_151530.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_151421.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_094848.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_093733.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_090439.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220412_153655.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220412_154103.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_100920.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_092834.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_093419.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_094401.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_101212.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_100826.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_092141.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_151759.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220412_163801.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_150427.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_092637.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_101115.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_094133.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220412_161835.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_150955.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_100742.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_092731.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_093528.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_093637.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_151626.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_150631.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_095046.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_151245.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220412_161709.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_100116.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220413_101006.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_150841.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/8B1/closed_loop_response__transfer_function__220414_150747.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220413_104527.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_145937.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220414_140634.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220414_140755.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220413_104325.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_151316.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220413_104946.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220413_104649.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220413_104851.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220413_104752.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_152146.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_151759.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220414_141229.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220414_141120.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_151923.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_145519.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220414_141400.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B1/closed_loop_response__transfer_function__220412_144950.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_150143.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220520_163219.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_122353.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_154410.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_153730.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_122527.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_150837.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_154225.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_121423.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_154319.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_122744.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_122619.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_121835.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_154012.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_122008.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_154132.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_122223.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_150631.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220513_121538.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/7B2/closed_loop_response__transfer_function__220512_150519.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_124449.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_122543.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_164614.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220413_111847.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_124614.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_165425.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_165004.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_164122.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_123924.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_164405.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220413_111706.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_164811.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_122244.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220413_111800.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_122420.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220412_165208.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220413_111628.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_124350.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_124150.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220413_111538.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_122945.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220414_122757.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/1B2/closed_loop_response__transfer_function__220413_111938.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_120242.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_115414.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_154707.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_154853.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_114345.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_154758.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_145544.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_114142.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_145903.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_154945.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_120656.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_115708.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_120047.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_155040.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220512_154555.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_120518.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/6B2/closed_loop_response__transfer_function__220513_120419.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220414_113411.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_105112.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_162524.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220414_113136.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_104936.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_163933.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_162223.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_164737.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220414_113235.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_164921.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_105259.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220414_112915.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220414_112709.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_164102.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_104849.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_105018.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_164643.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220413_105210.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220412_175302.npz\n",
      "['h', 'freq', 'sp_out_iq', 'q_cl']\n",
      "Reading data from:  /home/kiliakis/work/data-llrf/2022/acquisition_data/4B2/closed_loop_response__transfer_function__220412_175015.npz\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_256987/3345572267.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdata_dir_2022\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_npz\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/home/kiliakis/work/data-llrf/2022'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;31m# convert to dB\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mdata_dir_2022\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mdata_dir_2022\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'amplitude'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m20\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlog10\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mabs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'y'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mdata_dir_2022\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'real'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mv\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'y'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreal\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/tmp/ipykernel_256987/1696390682.py\u001b[0m in \u001b[0;36mload_npz\u001b[0;34m(path)\u001b[0m\n\u001b[1;32m     15\u001b[0m                 \u001b[0mbeam_line\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'/'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     16\u001b[0m                 \u001b[0mtimestamp\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'_function__'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'.npz'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m                 \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mload\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     18\u001b[0m                 \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m                 data_dir[beam_line+'_'+timestamp] = {\n",
      "\u001b[0;32m~/install/anaconda3/lib/python3.9/site-packages/numpy/lib/npyio.py\u001b[0m in \u001b[0;36mload\u001b[0;34m(file, mmap_mode, allow_pickle, fix_imports, encoding)\u001b[0m\n\u001b[1;32m    422\u001b[0m         \u001b[0m_ZIP_SUFFIX\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mb'PK\\x05\\x06'\u001b[0m \u001b[0;31m# empty zip files start with this\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    423\u001b[0m         \u001b[0mN\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mMAGIC_PREFIX\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 424\u001b[0;31m         \u001b[0mmagic\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfid\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mN\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    425\u001b[0m         \u001b[0;31m# If the file size is less than N, we need to make sure not\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    426\u001b[0m         \u001b[0;31m# to seek past the beginning of the file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "data_dir_2022 = load_npz('/home/kiliakis/work/data-llrf/2022')\n",
    "# convert to dB\n",
    "for k, v in data_dir_2022.items():\n",
    "    data_dir_2022[k]['amplitude'] = 20 * np.log10(np.abs(v['y']))\n",
    "    data_dir_2022[k]['real'] = v['y'].real\n",
    "    data_dir_2022[k]['imag'] = v['y'].imag\n",
    "    del data_dir_2022[k]['y']\n",
    "    exit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>freq</th>\n",
       "      <th>amplitude</th>\n",
       "      <th>real</th>\n",
       "      <th>imag</th>\n",
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       "  </thead>\n",
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       "      <td>[-1619443.359375, -1614550.78125, -1609658.203...</td>\n",
       "      <td>[-16.101513872082162, -20.602523606631745, -14...</td>\n",
       "      <td>[0.12378911431373243, 0.07270099721798444, 0.1...</td>\n",
       "      <td>[0.09599369330201799, 0.05847342440315569, -0....</td>\n",
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       "    <tr>\n",
       "      <th>3B2_220412_171806</th>\n",
       "      <td>[-1619443.359375, -1614550.78125, -1609658.203...</td>\n",
       "      <td>[-18.955587103610682, -24.970713252863305, -23...</td>\n",
       "      <td>[0.11269946501388299, 0.05619516329746758, 0.0...</td>\n",
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      "text/plain": [
       "                                                                freq  \\\n",
       "3B2_220412_173447  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "3B2_220412_173834  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "3B2_220412_171151  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "3B2_220412_174043  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "3B2_220412_171806  [-1619443.359375, -1614550.78125, -1609658.203...   \n",
       "\n",
       "                                                           amplitude  \\\n",
       "3B2_220412_173447  [-24.51491888231732, -18.586843008533414, -19....   \n",
       "3B2_220412_173834  [-16.983423382785222, -20.326042606836452, -22...   \n",
       "3B2_220412_171151  [-23.129462016787343, -14.875370553975397, -19...   \n",
       "3B2_220412_174043  [-16.101513872082162, -20.602523606631745, -14...   \n",
       "3B2_220412_171806  [-18.955587103610682, -24.970713252863305, -23...   \n",
       "\n",
       "                                                                real  \\\n",
       "3B2_220412_173447  [0.04803403102605476, 0.07095516661786772, 0.0...   \n",
       "3B2_220412_173834  [0.1208846452155351, 0.08535173379101775, 0.07...   \n",
       "3B2_220412_171151  [0.04122786632321749, 0.10797230864446494, 0.0...   \n",
       "3B2_220412_174043  [0.12378911431373243, 0.07270099721798444, 0.1...   \n",
       "3B2_220412_171806  [0.11269946501388299, 0.05619516329746758, 0.0...   \n",
       "\n",
       "                                                                imag  \n",
       "3B2_220412_173447  [-0.03505279045500576, -0.09386740251265056, 0...  \n",
       "3B2_220412_173834  [-0.07359231304242166, -0.04462991275357435, 0...  \n",
       "3B2_220412_171151  [-0.05625777875663823, -0.14451775700575686, -...  \n",
       "3B2_220412_174043  [0.09599369330201799, 0.05847342440315569, -0....  \n",
       "3B2_220412_171806  [-0.0041819362473564286, -0.005077227372012491...  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df22 = pd.DataFrame.from_dict(data_dir_2022, orient='index')\n",
    "df22.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "from matplotlib import pyplot as plt\n",
    "\n",
    "for index, row in df22.sample(n=3).iterrows():\n",
    "    y = row['y']\n",
    "    x = row['x']\n",
    "    # label = f'm{m}-s{s}'\n",
    "    plt.plot(x, y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# save dataframe to file\n",
    "df22.to_pickle('./data/tf-measurement-2022.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[4892.5    4892.5625 4892.578  4892.5938 4892.625  9785.156 ]\n",
      " [4892.5    4892.5625 4892.578  4892.5938 4892.625  9785.156 ]\n",
      " [4892.5    4892.5625 4892.578  4892.5938 4892.625  9785.156 ]\n",
      " ...\n",
      " [4892.5    4892.5625 4892.578  4892.5938 4892.625  9785.156 ]\n",
      " [4892.5    4892.5625 4892.578  4892.5938 4892.625  9785.156 ]\n",
      " [4892.5    4892.5625 4892.578  4892.5938 4892.625  9785.156 ]]\n"
     ]
    }
   ],
   "source": [
    "# freq seems to be a bit off\n",
    "freqs = np.zeros((len(df22), len(df22.x[0])), dtype=np.float32)\n",
    "index = 0\n",
    "for _, row in df22.iterrows():\n",
    "    freqs[index, :] = row.values[1]\n",
    "    index+=1\n",
    "# assert all freqs are equal\n",
    "print(np.unique(np.diff(freqs), axis=1))\n",
    "x = df22.iloc[0].x.astype(np.float32)\n",
    "\n",
    "df22 = df22.drop(columns='x')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(452, 2)\n"
     ]
    }
   ],
   "source": [
    "print(df22.shape)"
   ]
  }
 ],
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