{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Demo Scripts for the wfdb-python package\n", "\n", "Run this notebook from the base directory of the git repository to access the included demo files" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Documentation Site\n", "\n", "http://wfdb.readthedocs.io/" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from IPython.display import display\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "import numpy as np\n", "import os\n", "import shutil\n", "import posixpath\n", "\n", "import wfdb" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/plain": [ "{'record_name': 'a103l',\n", " 'n_sig': 3,\n", " 'fs': 250,\n", " 'counter_freq': None,\n", " 'base_counter': None,\n", " 'sig_len': 82500,\n", " 'base_time': None,\n", " 'base_date': None,\n", " 'comments': ['Asystole', 'False alarm'],\n", " 'sig_name': ['II', 'V', 'PLETH'],\n", " 'p_signal': array([[-0.02359597, 0.86758555, 0.48220271],\n", " [-0.03698082, 0.98298479, 0.5443735 ],\n", " [-0.06292259, 0.85979087, 0.47821229],\n", " ...,\n", " [-0.04084449, 0.7493346 , 0.5150838 ],\n", " [-0.04719194, 0.7581749 , 0.50957702],\n", " [-0.04677798, 0.7615019 , 0.5028731 ]]),\n", " 'd_signal': None,\n", " 'e_p_signal': None,\n", " 'e_d_signal': None,\n", " 'file_name': ['a103l.mat', 'a103l.mat', 'a103l.mat'],\n", " 'fmt': ['16', '16', '16'],\n", " 'samps_per_frame': [1, 1, 1],\n", " 'skew': [None, None, None],\n", " 'byte_offset': [24, 24, 24],\n", " 'adc_gain': [7247.0, 10520.0, 12530.0],\n", " 'baseline': [0, 0, 0],\n", " 'units': ['mV', 'mV', 'NU'],\n", " 'adc_res': [16, 16, 16],\n", " 'adc_zero': [0, 0, 0],\n", " 'init_value': [-171, 9127, 6042],\n", " 'checksum': [-27403, -301, -17391],\n", " 'block_size': [0, 0, 0]}" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Demo 1 - Read a WFDB record using the 'rdrecord' function into a wfdb.Record object.\n", "# Plot the signals, and show the data.\n", "record = wfdb.rdrecord('sample-data/a103l') \n", "wfdb.plot_wfdb(record=record, title='Record a103l from PhysioNet Challenge 2015') \n", "display(record.__dict__)\n", "\n", "# Can also read the same files hosted on PhysioNet https://physionet.org/content/challenge-2015/1.0.0\n", "# in the /training/ database subdirectory.\n", "record2 = wfdb.rdrecord('a103l', pn_dir='challenge-2015/training/')" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[ 0.0335, -0.167 , -0.237 , 0.1165],\n", " [ 0.0355, -0.1615, -0.2395, 0.119 ],\n", " [ 0.0385, -0.168 , -0.2465, 0.116 ],\n", " ...,\n", " [-0.0445, 0.008 , 0.033 , 0.045 ],\n", " [-0.044 , 0.0175, 0.042 , 0.052 ],\n", " [-0.044 , 0.0245, 0.0365, 0.05 ]])" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "{'fs': 1000,\n", " 'sig_len': 14900,\n", " 'n_sig': 4,\n", " 'base_date': None,\n", " 'base_time': None,\n", " 'units': ['mV', 'mV', 'mV', 'mV'],\n", " 'sig_name': ['vz', 'i', 'avf', 'v5'],\n", " 'comments': ['age: 81',\n", " 'sex: female',\n", " 'ECG date: 01/10/1990',\n", " 'Diagnose:',\n", " 'Reason for admission: Myocardial infarction',\n", " 'Acute infarction (localization): infero-latera',\n", " 'Former infarction (localization): no',\n", " 'Additional diagnoses: Diabetes mellitus',\n", " 'Smoker: no',\n", " 'Number of coronary vessels involved: 1',\n", " 'Infarction date (acute): 29-Sep-90',\n", " 'Previous infarction (1) date: n/a',\n", " 'Previous infarction (2) date: n/a',\n", " 'Hemodynamics:',\n", " 'Catheterization date: 16-Oct-90',\n", " 'Ventriculography: Akinesia inferior wall',\n", " 'Chest X-ray: Heart size upper limit of norm',\n", " 'Peripheral blood Pressure (syst/diast): 140/80 mmHg',\n", " 'Pulmonary artery pressure (at rest) (syst/diast): n/a',\n", " 'Pulmonary artery pressure (at rest) (mean): n/a',\n", " 'Pulmonary capillary wedge pressure (at rest): n/a',\n", " 'Cardiac output (at rest): n/a',\n", " 'Cardiac index (at rest): n/a',\n", " 'Stroke volume index (at rest): n/a',\n", " 'Pulmonary artery pressure (laod) (syst/diast): n/a',\n", " 'Pulmonary artery pressure (laod) (mean): n/a',\n", " 'Pulmonary capillary wedge pressure (load): n/a',\n", " 'Cardiac output (load): n/a',\n", " 'Cardiac index (load): n/a',\n", " 'Stroke volume index (load): n/a',\n", " 'Aorta (at rest) (syst/diast): 160/64 cmH2O',\n", " 'Aorta (at rest) mean: 106 cmH2O',\n", " 'Left ventricular enddiastolic pressure: 11 cmH2O',\n", " 'Left coronary artery stenoses (RIVA): RIVA 70% proximal to ramus diagonalis_2',\n", " 'Left coronary artery stenoses (RCX): No stenoses',\n", " 'Right coronary artery stenoses (RCA): No stenoses',\n", " 'Echocardiography: n/a',\n", " 'Therapy:',\n", " 'Infarction date: 29-Sep-90',\n", " 'Catheterization date: 16-Oct-90',\n", " 'Admission date: 29-Sep-90',\n", " 'Medication pre admission: Isosorbit-Dinitrate Digoxin Glibenclamide',\n", " 'Start lysis therapy (hh.mm): 19:45',\n", " 'Lytic agent: Gamma-TPA',\n", " 'Dosage (lytic agent): 30 mg',\n", " 'Additional medication: Heparin Isosorbit-Mononitrate ASA Diazepam',\n", " 'In hospital medication: ASA Isosorbit-Mononitrate Ca-antagonist Amiloride+Chlorothiazide Glibenclamide Insulin',\n", " 'Medication after discharge: ASA Isosorbit-Mononitrate Amiloride+Chlorothiazide Glibenclamide']}" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Demo 2 - Read certain channels and sections of the WFDB record using the simplified 'rdsamp' function\n", "# which returns a numpy array and a dictionary. Show the data.\n", "signals, fields = wfdb.rdsamp('sample-data/s0010_re', channels=[14, 0, 5, 10], sampfrom=100, sampto=15000)\n", "display(signals)\n", "display(fields)\n", "\n", "# Can also read the same files hosted on Physionet\n", "signals2, fields2 = wfdb.rdsamp('s0010_re', channels=[14, 0, 5, 10], sampfrom=100, sampto=15000, pn_dir='ptbdb/patient001/')" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'record_name': 'drive02',\n", " 'n_sig': 5,\n", " 'fs': 15.5,\n", " 'counter_freq': None,\n", " 'base_counter': None,\n", " 'sig_len': 78056,\n", " 'base_time': None,\n", " 'base_date': None,\n", " 'comments': [],\n", " 'sig_name': ['ECG', 'foot GSR', 'HR', 'marker', 'RESP'],\n", " 'p_signal': None,\n", " 'd_signal': None,\n", " 'e_p_signal': None,\n", " 'e_d_signal': None,\n", " 'file_name': ['drive02.dat',\n", " 'drive02.dat',\n", " 'drive02.dat',\n", " 'drive02.dat',\n", " 'drive02.dat'],\n", " 'fmt': ['16', '16', '16', '16', '16'],\n", " 'samps_per_frame': [32, 2, 1, 1, 2],\n", " 'skew': [None, None, None, None, None],\n", " 'byte_offset': [None, None, None, None, None],\n", " 'adc_gain': [1000.0, 1000.0, 1.0001, 100.0, 500.0],\n", " 'baseline': [0, 0, 0, 0, 0],\n", " 'units': ['mV', 'mV', 'bpm', 'mV', 'mV'],\n", " 'adc_res': [16, 16, 16, 16, 16],\n", " 'adc_zero': [0, 0, 0, 0, 0],\n", " 'init_value': [-1236, 1802, 75, 0, 5804],\n", " 'checksum': [14736, 13501, -19070, -9226, -14191],\n", " 'block_size': [0, 0, 0, 0, 0]}" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Demo 3 - Read a WFDB header file only (without the signals)\n", "record = wfdb.rdheader('sample-data/drive02')\n", "display(record.__dict__)\n", "\n", "# Can also read the same file hosted on Physionet\n", "record2 = wfdb.rdheader('drive02', pn_dir='drivedb')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Demo 4 - Read part of a WFDB annotation file into a wfdb.Annotation object, and plot the samples\n", "annotation = wfdb.rdann('sample-data/100', 'atr', sampfrom=100000, sampto=110000)\n", "annotation.fs = 360\n", "wfdb.plot_wfdb(annotation=annotation, time_units='minutes')\n", "\n", "# Can also read the same file hosted on PhysioNet \n", "annotation2 = wfdb.rdann('100', 'atr', sampfrom=100000, sampto=110000, pn_dir='mitdb')" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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