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We want to be able to plot multi-frequency records, with each signal
at its native frequency. To see the individual samples, try:
import wfdb
r = wfdb.rdrecord('sample-data/03700181', smooth_frames=False,
sampfrom=5000, sampto=5100)
wfdb.plot_wfdb(r, time_units='seconds', sig_style=['|-'])
Compare to the smoothed version:
r = wfdb.rdrecord('sample-data/03700181',
sampfrom=5000, sampto=5100)
wfdb.plot_wfdb(r, time_units='seconds', sig_style=['|-'])
A more dramatic example:
r = wfdb.rdrecord('sample-data/wave_4', smooth_frames=False,
sampto=10)
wfdb.plot_wfdb(r)
contrasted with:
r = wfdb.rdrecord('sample-data/wave_4', sampto=10)
wfdb.plot_wfdb(r)
To see the signals synchronized with annotations stored at different
frequencies, try:
r = wfdb.rdrecord('sample-data/03700181', smooth_frames=False,
sampfrom=5000, sampto=5625)
for ann, f in (('gqrsh', 500), ('gqrsl', 125), ('sqrs', 250)):
a = wfdb.rdann('sample-data/03700181', ann, shift_samps=True,
sampfrom=(5000*f//125), sampto=(5625*f//125))
wfdb.plot_wfdb(r, a, time_units='seconds',
title='annotator %s' % ann)
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