qtdb-data.ipynb

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    "import os\n",
    "\n",
    "import utils.data_util as du\n",
    "import utils.file_util as fu\n",
    "\n",
    "from utils.Config import Config\n",
    "\n",
    "\n",
    "import numpy as np\n",
    "import random\n",
    "\n",
    "import copy\n",
    "\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import matplotlib.pyplot as plt\n",
    "import wfdb\n",
    "from random import shuffle\n",
    "import random\n",
    "from utils.data_util import denoise\n",
    "import scipy.stats as st\n",
    "\n",
    "import utils.file_util as fu\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import wfdb\n",
    "from random import shuffle\n",
    "from ecgdetectors import Detectors\n",
    "\n",
    "os.environ['KMP_DUPLICATE_LIB_OK']='True'\n"
   ]
  },
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    "def get_data(config):\n",
    "    qtdb_data_dir = Config.QTDB_RECORD_DIR\n",
    "    postfix = 'q1c'\n",
    "    fs = 250\n",
    "    wave_len = config.wave_len\n",
    "    wave_half = int(wave_len/2)\n",
    "    data_type = config.data_type\n",
    "    baseline = config.baseline\n",
    "    normalize = config.normalize\n",
    "    FILENAME = config.fname_data\n",
    "    FILTER = config.filtered\n",
    "    print(FILENAME)\n",
    "    \n",
    "    record_list = du.get_ids(qtdb_data_dir)\n",
    "    data = {}\n",
    "    labels = {}\n",
    "    true_labels = {}\n",
    "    cnt = 0\n",
    "    r_ref = []\n",
    "    r_ans = []\n",
    "    R_errs = []\n",
    "    \n",
    "    for number,pid in enumerate(record_list):\n",
    "        print('{}/{},{}'.format(number+1,len(record_list),pid))\n",
    "        R_all = []\n",
    "        record_path  = os.path.join(qtdb_data_dir,pid)\n",
    "        channel_ = 0\n",
    "        if pid == 'sel114':\n",
    "            channel_ = 1\n",
    "\n",
    "        record, fields=wfdb.rdsamp(record_path,channels= [channel_])\n",
    "        record =record.flatten()\n",
    "\n",
    "        record =np.array(record)\n",
    "  \n",
    "        record = denoise(record)\n",
    "\n",
    "        atr = wfdb.rdann(os.path.join(qtdb_data_dir,pid),extension=postfix)\n",
    "\n",
    "        atr_symbols = np.array(atr.symbol)\n",
    "        atr_points = np.array(np.array(atr.sample), dtype=np.int)\n",
    "        \n",
    "        r_list = np.where(np.array(atr_symbols)=='N')[0]\n",
    "        r_list = atr_points[r_list]\n",
    "        if len(r_list)==0:\n",
    "            data[pid] = []\n",
    "            labels[pid] = []\n",
    "            continue\n",
    "        thr_ = 0.15 \n",
    "        fs_ = 250\n",
    "        \n",
    "        detectors = Detectors(fs_)\n",
    "        r_peaks = detectors.pan_tompkins_detector(record)\n",
    "     \n",
    "        r_ref.append(np.array(r_list))\n",
    "        r_ans.append(np.array(r_peaks))\n",
    "\n",
    "        TOL = 37.5\n",
    "        start = -1\n",
    "        end = -1\n",
    "        for k in range(len(r_peaks)):\n",
    "            if np.abs(r_peaks[k]-r_list[0]) <= TOL:\n",
    "                start = k\n",
    "            if np.abs(r_peaks[k]-r_list[-1]) <= TOL:\n",
    "                end = k + 1\n",
    "\n",
    "\n",
    "        per_data = []\n",
    "        per_label = []\n",
    "        detect_peak_cnt = 0\n",
    "        for j in range(start, end):\n",
    "            \n",
    "            r_idx = r_peaks[j]\n",
    "            if r_idx - wave_half < 0 or r_idx+wave_half >= len(record):\n",
    "                continue\n",
    "            lead_seg = record[r_idx - wave_half: r_idx + wave_half]\n",
    "            include_R_symbols_idx = atr_points[(atr_points>=r_idx-TOL)&(atr_points<=r_idx + TOL)]\n",
    "            \n",
    "            R_seg_symbols = atr_symbols[np.isin(atr_points,include_R_symbols_idx)]\n",
    "            index = -1\n",
    "            tmp_cnt =0\n",
    "            for k in range(len(R_seg_symbols)):\n",
    "                if R_seg_symbols[k] == 'N':\n",
    "                    tmp_cnt +=1\n",
    "                    index = k\n",
    "\n",
    "            if index != -1:\n",
    "                detect_peak_cnt +=1              \n",
    "                true_r_idx =  include_R_symbols_idx[index]\n",
    "                R_all.append(true_r_idx)\n",
    "                R_errs.append(r_idx- true_r_idx)\n",
    "\n",
    "                include_symbols_idx = atr_points[(atr_points>=true_r_idx - wave_half)&(atr_points<true_r_idx + wave_half)]\n",
    "             \n",
    "                seg_symbols = atr_symbols[np.isin(atr_points,include_symbols_idx)]\n",
    "                \n",
    "                index = int(np.where(include_symbols_idx==true_r_idx)[0])\n",
    "                if index >=4 and index+4 <= len(seg_symbols) and (seg_symbols[index-4:index+4] == ['(', 'p', ')', '(', 'N', ')', 't', ')']).all():\n",
    "                    p_start, p_end = include_symbols_idx[index-4]- r_idx + wave_half, include_symbols_idx[index-2]- r_idx + wave_half\n",
    "                    r_start, r_end = include_symbols_idx[index-1]- r_idx + wave_half, include_symbols_idx[index+1]- r_idx + wave_half\n",
    "                    t_peak, t_end =  include_symbols_idx[index+2] - r_idx + wave_half, include_symbols_idx[index+3]- r_idx + wave_half\n",
    "                    label = [p_start, p_end, r_start, r_end, t_peak, t_end]\n",
    "                    per_data.append(lead_seg)\n",
    "                    per_label.append(label)\n",
    "                    cnt+=1\n",
    "                elif index >=4 and index+5 <= len(seg_symbols) and (seg_symbols[index-4:index+5] == ['(', 'p', ')', '(', 'N', ')', '(', 't', ')']).all():          \n",
    "                    p_start, p_end = include_symbols_idx[index-4]- r_idx + wave_half, include_symbols_idx[index-2]- r_idx + wave_half\n",
    "                    r_start, r_end = include_symbols_idx[index-1]- r_idx + wave_half, include_symbols_idx[index+1]- r_idx + wave_half\n",
    "                    t_start, t_end = include_symbols_idx[index+3]- r_idx + wave_half, include_symbols_idx[index+4]- r_idx + wave_half\n",
    "                    label = [p_start, p_end, r_start, r_end, t_start, t_end]\n",
    "                    per_data.append(lead_seg)\n",
    "                    per_label.append(label)\n",
    "                    cnt+=1\n",
    "                \n",
    "        print('record_beat_cnt:', len(per_data))\n",
    "        data[pid] = per_data\n",
    "        labels[pid] =  per_label\n",
    "    \n",
    "\n",
    "    print('test cnt:',cnt)\n",
    "\n",
    "    import utils.file_util as fu\n",
    "    file_name = FILENAME\n",
    "    fu.save((data, labels), file_name)\n",
    "    print('success') \n",
    "    return data,labels\n"
   ]
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    "\n",
    "config  = Config()\n",
    "config.dataset = 'qtdb'\n",
    "config.refresh()\n",
    "get_data(config)\n"
   ]
  },
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