Beispiel #1
0
    def test_anonymize(self):

        header = highlevel.make_header(technician='tech',
                                       recording_additional='radd',
                                       patientname='name',
                                       patient_additional='padd',
                                       patientcode='42',
                                       equipment='eeg',
                                       admincode='420',
                                       gender='Male',
                                       birthdate='05.09.1980')
        annotations = [[0.01, -1, 'begin'], [0.5, -1, 'middle'],
                       [10, -1, 'end']]
        header['annotations'] = annotations
        signal_headers = highlevel.make_signal_headers(
            ['ch' + str(i) for i in range(3)])
        signals = np.random.rand(3, 256 * 300) * 200  #5 minutes of eeg
        highlevel.write_edf(self.personalized, signals, signal_headers, header)

        highlevel.anonymize_edf(self.personalized,
                                new_file=self.anonymized,
                                to_remove=[
                                    'patientname', 'birthdate', 'admincode',
                                    'patientcode', 'technician'
                                ],
                                new_values=['x', '', 'xx', 'xxx', 'xxxx'],
                                verify=True,
                                verbose=True)
        new_header = highlevel.read_edf_header(self.anonymized)
        self.assertEqual(new_header['birthdate'], '')
        self.assertEqual(new_header['patientname'], 'x')
        self.assertEqual(new_header['admincode'], 'xx')
        self.assertEqual(new_header['patientcode'], 'xxx')
        self.assertEqual(new_header['technician'], 'xxxx')

        highlevel.anonymize_edf(self.personalized,
                                to_remove=[
                                    'patientname', 'birthdate', 'admincode',
                                    'patientcode', 'technician'
                                ],
                                new_values=['x', '', 'xx', 'xxx', 'xxxx'],
                                verify=True)
        new_header = highlevel.read_edf_header(self.personalized[:-4] +
                                               '_anonymized.edf')
        self.assertEqual(new_header['birthdate'], '')
        self.assertEqual(new_header['patientname'], 'x')
        self.assertEqual(new_header['admincode'], 'xx')
        self.assertEqual(new_header['patientcode'], 'xxx')
        self.assertEqual(new_header['technician'], 'xxxx')

        with self.assertRaises(AssertionError):
            highlevel.anonymize_edf(self.personalized,
                                    new_file=self.anonymized,
                                    to_remove=[
                                        'patientname', 'birthdate',
                                        'admincode', 'patientcode',
                                        'technician'
                                    ],
                                    new_values=['x', '', 'xx', 'xxx'],
                                    verify=True)
Beispiel #2
0
"""
Created on Thu Feb 27 14:40:36 2020

add

@author: skjerns
"""
import config
import os
from tqdm import tqdm
import ospath
from pyedflib import highlevel


folder = "Z:/NT1-HRV-data"
new_folder = ospath.join(folder, "new")
os.makedirs(new_folder, exist_ok=True)
mapping = config.mapping_channels


files = ospath.list_files(folder, exts='edf')
for file in tqdm(files):
    name = ospath.basename(file)[:-4]
    new_file = ospath.join(new_folder, name + ".edf")
    if os.path.exists(new_file):
        print(f"{new_file} exists, skipping")
        continue
    
    highlevel.anonymize_edf(file, new_file, to_remove = ['patientcode', 'patientname'],
                            new_values  = [name, name], verify=False)
    highlevel.rename_channels(new_file, mapping=mapping, new_file=new_file)