def get_signals(self, start=0, interval=10, number_of_signals=2):
"""Returns 2D array :
1) dimension: channel_idxes
2) dimension: sample_idxes"""
end = int(start + interval * self.get_frequency())
self._signals = np.zeros((end - start + 1, number_of_signals))
if self._database == "ptb":
parser = ecg_recording_parser_ptb.ECGRecordingPTBDataParser()
index = 0
if number_of_signals != 2:
signal_indexes = range(0, number_of_signals)
else:
signal_indexes = [6, 7]
for signal_index in signal_indexes:
self._signals[:, index] = parser.parse(self._path + ".dat",
channel_no=signal_index,
modulo=12,
from_sample=start,
to_sample=12 *
(end + 1) - 1,
invert=False)
index += 1
elif self._database == "af":
parser = ecg_recording_parser_af.ECGRecordingDataParser()
self._signals[:, :] = parser.parse(self._path + ".dat",
from_sample=start,
to_sample=end)
else:
print("Brak zdefiniowanego rodzaju danych do parsowania")
return (self._signals)
from AF.parsers import ecg_recording_parser_af
import wfdb
import numpy as np
file_path = path.join("downloads", "af", "04048")
record = wfdb.rdsamp(file_path, sampto=556777 + 3000, sampfrom=556777 - 3000)
#a= wfdb.rdann('04746','atr',pbdir='afdb', sampto=103000)
annotation = wfdb.rdann(file_path, 'atr')
annsamp = annotation.__dict__["annsamp"]
names = annotation.__dict__["aux"]
print(annsamp, names)
# SIGNALS
parser = ecg_recording_parser_af.ECGRecordingDataParser()
signals_af = np.array(
parser.parse(dat_file_name=file_path + '.dat',
from_sample=556777 - 3000,
to_sample=556777 + 3000))
signal_0 = signals_af[:, 0]
signal_1 = signals_af[:, 1]
plt.figure(4)
plt.subplot(2, 1, 1)
plt.plot(signal_0)
plt.subplot(2, 1, 2)
plt.plot(signal_1)
#
from AF.parsers import ecg_recording_parser_ptb, ecg_recording_parser_af
from AF.model import record
from matplotlib import pyplot as plt
import numpy as np
from os import path
parser_ptb = ecg_recording_parser_ptb.ECGRecordingPTBDataParser()
parser_mit_bih_af = ecg_recording_parser_af.ECGRecordingDataParser()
file_ptb_name_dat = path.join("downloads", "ptb", "patient104", "s0306lre.dat")
file_af_name_dat = path.join("downloads", "af", "04048.dat")
for channel_no in [0]:
signal_af = np.array(
parser_mit_bih_af.parse(file_af_name_dat,
from_sample=0,
to_sample=3000))
plt.figure(0)
plt.plot(signal_af[:, 0].ravel())
plt.figure(1)
plt.plot(signal_af[:, 1].ravel())
for channel_no in [6, 7]:
signal = parser_ptb.parse(file_ptb_name_dat,
channel_no=channel_no,
invert=False,
modulo=12,