def _p_tconst(pattern, pwave):
"""P waves temporal constraints"""
BASIC_TCONST(pattern, pwave)
tnet = pattern.last_tnet
tnet.add_constraint(pwave.start, pwave.end, C.PW_DURATION)
#We find the associated QRS.
beats = pattern.evidence[o.QRS]
qidx = qrsidx + len(beats) if qrsidx < 0 else qrsidx
qrs = beats[qidx]
if qidx > 0:
tnet.set_before(beats[qidx - 1].end, pwave.start)
tnet.add_constraint(pwave.start, qrs.start, C.N_PR_INTERVAL)
tnet.set_before(pwave.end, qrs.start)
if len(pattern.evidence[o.PWave]) > 10:
#The mean and standard deviation of the PQ measurements will
#influence the following observations.
if qidx % 2 == 0:
pqmean, pqstd = pattern.hypothesis.meas.pq
else:
pqs = _get_measures(pattern, True)[2]
pqmean, pqstd = np.mean(pqs), np.std(pqs)
if not np.isnan(pqmean) and not np.isnan(pqstd):
interv = Iv(int(pqmean - 2 * pqstd), int(pqmean + 2 * pqstd))
if interv.overlap(C.N_PR_INTERVAL):
tnet.add_constraint(pwave.start, qrs.start, interv)
def _t_tconst(pattern, twave):
"""
Temporal constraints of the T Waves wrt the corresponding QRS complex.
"""
BASIC_TCONST(pattern, twave)
tnet = pattern.last_tnet
obseq = pattern.obs_seq
idx = pattern.get_step(twave)
beats = pattern.evidence[o.QRS]
qidx = qrsidx + len(beats) if qrsidx < 0 else qrsidx
qrs = beats[qidx]
if qidx > 1:
refsq = beats[qidx - 1].earlystart - beats[qidx - 2].lateend
tnet.add_constraint(qrs.time, twave.end,
Iv(0, max(0, refsq - C.TQ_INTERVAL_MIN)))
if idx > 0 and isinstance(obseq[idx - 1], o.PWave):
pwave = obseq[idx - 1]
tnet.add_constraint(
pwave.end, twave.start,
Iv(C.ST_INTERVAL.start, C.PQ_INTERVAL.end + C.QRS_DUR.end))
if qidx < len(beats) - 1:
tnet.set_before(twave.end, beats[qidx + 1].start)
#ST interval
tnet.add_constraint(qrs.end, twave.start, C.ST_INTERVAL)
#QT duration
tnet.add_constraint(qrs.start, twave.end, C.N_QT_INTERVAL)
#RT variation
if qidx % 2 == 0:
rtmean, rtstd = pattern.hypothesis.meas.rt
#We also define a constraint on T wave end based on the last
#distance between normal and ectopic QRS.
if qidx > 0:
tnet.add_constraint(
qrs.end, twave.end,
Iv(0,
beats[qidx - 1].earlystart - beats[qidx - 2].lateend))
else:
rts = _get_measures(pattern, 1)[2]
rtmean, rtstd = np.mean(rts), np.std(rts)
if rtmean > 0:
#The mean and standard deviation of the PQ measurements will
#influence the following observations.
maxdiff = (C.QT_ERR_STD
if len(pattern.evidence[o.TWave]) < 10 else rtstd)
maxdiff = max(maxdiff, C.MIN_QT_STD)
interv = Iv(int(rtmean - 2.5 * maxdiff),
int(rtmean + 2.5 * maxdiff))
#We avoid possible inconsistencies with constraint introduced by
#the rhythm information.
try:
existing = tnet.get_constraint(qrs.time, twave.end).constraint
except KeyError:
existing = Iv(-np.inf, np.inf)
if interv.overlap(existing):
tnet.add_constraint(qrs.time, twave.end, interv)
def _p_qrs_tconst(pattern, pwave):
"""
Temporal constraints of the P Waves wrt the corresponding QRS complex
"""
tnet = pattern.tnet
tnet.add_constraint(pwave.start, pwave.end, C.PW_DURATION)
#We find the QRS observed just before that P wave.
idx = pattern.get_step(pwave)
if idx > 0 and isinstance(pattern.trseq[idx - 1][1], o.QRS):
qrs = pattern.trseq[idx - 1][1]
#PR interval
tnet.add_constraint(pwave.start, qrs.start, C.N_PR_INTERVAL)
tnet.set_before(pwave.end, qrs.start)
if len(pattern.evidence[o.PWave]) > 10:
#The mean and standard deviation of the PQ measurements will
#influence the following observations.
pqmean, pqstd = pattern.hypothesis.meas.pq
interv = Iv(int(pqmean - 2 * pqstd), int(pqmean + 2 * pqstd))
if interv.overlap(C.N_PR_INTERVAL):
tnet.add_constraint(pwave.start, qrs.start, interv)
def _t_tconst(pattern, twave):
"""
Temporal constraints of the T Waves wrt the corresponding QRS complex.
"""
BASIC_TCONST(pattern, twave)
tnet = pattern.last_tnet
#We find the associated QRS.
beats = pattern.evidence[o.QRS]
qidx = qrsidx + len(beats) if qrsidx < 0 else qrsidx
qrs = beats[qidx]
if qidx < len(beats) - 1:
tnet.set_before(twave.end, beats[qidx + 1].start)
#ST interval
tnet.add_constraint(qrs.end, twave.start, C.ST_INTERVAL)
#QT duration
tnet.add_constraint(qrs.start, twave.end, C.N_QT_INTERVAL)
#RT variation
if not _is_ectopic(qidx):
rtmean, rtstd = pattern.hypothesis.meas.rt
else:
rts = _get_measures(pattern, True)[2]
rtmean, rtstd = np.mean(rts), np.std(rts)
if rtmean > 0:
#The mean and standard deviation of the PQ measurements will
#influence the following observations.
maxdiff = (C.QT_ERR_STD
if len(pattern.evidence[o.TWave]) < 10 else rtstd)
maxdiff = max(maxdiff, C.MIN_QT_STD)
interv = Iv(int(rtmean - 2.5 * maxdiff),
int(rtmean + 2.5 * maxdiff))
#We avoid possible inconsistencies with constraint introduced by
#the rhythm information.
try:
existing = tnet.get_constraint(qrs.time, twave.end).constraint
except KeyError:
existing = Iv(-np.inf, np.inf)
if interv.overlap(existing):
tnet.add_constraint(qrs.time, twave.end, interv)
def test_overlap(self):
inter1 = Interval(0, 10)
inter2 = Interval(15, 20)
assert not inter1.overlap(inter2)
assert not inter2.overlap(inter1)
assert inter1.overlap(inter1)
assert inter2.overlap(inter2)
inter2 = Interval(-6, 0)
assert not inter1.overlap(inter2)
assert not inter2.overlap(inter1)
inter2 = Interval(-6, 5)
assert inter1.overlap(inter2)
assert inter2.overlap(inter1)
inter2 = Interval(10, 15)
assert not inter1.overlap(inter2)
assert not inter2.overlap(inter1)
inter2 = Interval(4, 15)
assert inter1.overlap(inter2)
assert inter2.overlap(inter1)