def _reg_nae_tconst(pattern, qrs):
"""
Temporal constraints for regular beats not coming after ectopic beats.
"""
beats = pattern.evidence[o.QRS]
idx = beats.index(qrs)
assert not _is_ectopic(idx)
hyp = pattern.hypothesis
tnet = pattern.last_tnet
prev = beats[idx - 1]
if idx > 3:
#We create a new temporal network for the new trigeminy cycle.
tnet.remove_constraint(hyp.end, prev.time)
tnet = ConstraintNetwork()
pattern.temporal_constraints.append(tnet)
rrev = beats[idx - 3].time.start - beats[idx - 4].time.start
##RR evolution constraint.
else:
rrev = pattern.evidence[o.Cardiac_Rhythm][0].meas.rr[0]
tnet.add_constraint(prev.time, qrs.time,
Iv(rrev - C.RR_MAX_DIFF, rrev + C.RR_MAX_DIFF))
BASIC_TCONST(pattern, qrs)
tnet.add_constraint(qrs.start, qrs.end, C.NQRS_DUR)
tnet.set_before(qrs.time, hyp.end)
#Constraints with the precedent T Wave
_qrs_after_twave(pattern, qrs)
#Morphology should be similar to the previous QRS, since both are normal
qrs.shape = prev.shape
qrs.paced = prev.paced
def test_set_before(self):
v0, v1 = [Interval(-1, x) for x in range(2)]
nw = ConstraintNetwork()
nw.set_before(v0, v1)
nw.minimize_network()
assert v0 < v1
assert v0.start == v1.start
assert v0.start == -1
nw.set_before(v1, v0)
nw.minimize_network()
assert v0 == v1
assert v0 == v1
assert v0.start == -1
def _deflection_tconst(pattern, defl):
"""Temporal constraints of the posterior deflections"""
defls = pattern.evidence[o.Deflection]
idx = defls.index(defl)
hyp = pattern.hypothesis
tnet = pattern.last_tnet
prev = defls[idx - 1]
tnet.remove_constraint(hyp.end, prev.time)
#We create a new temporal network for the cyclic observations
tnet = ConstraintNetwork()
tnet.add_constraint(prev.time, defl.time, C.VFLUT_WW_INTERVAL)
pattern.temporal_constraints.append(tnet)
BASIC_TCONST(pattern, defl)
tnet.add_constraint(defl.start, defl.end, Iv(0, C.VFLUT_WW_INTERVAL.end))
tnet.set_before(defl.time, hyp.end)
def _ect_qrs_tconst(pattern, qrs):
"""
Temporal constraints for ectopic beats, which appear after every regular
beat.
"""
beats = pattern.evidence[o.QRS]
idx = beats.index(qrs)
tnet = pattern.last_tnet
hyp = pattern.hypothesis
if idx > 0:
prev = beats[idx - 1]
#After the second couplet, every ectopic beat introduces a new temporal
#network in the pattern to make it easier the minimization.
if idx > 3:
tnet.remove_constraint(hyp.end, prev.time)
#We create a new temporal network for the cyclic observations
tnet = ConstraintNetwork()
pattern.temporal_constraints.append(tnet)
#The duration of each couplet should not have high instantaneous
#variations.
refrr = beats[idx - 2].time.end - beats[idx - 3].time.start
tnet.add_constraint(
prev.time, qrs.time,
Iv(refrr - C.RR_MAX_DIFF, refrr + C.RR_MAX_DIFF))
#We guide the morphology search to be similar to the previous
#ectopic QRS complex.
qrs.shape = beats[idx - 2].shape
#The reference RR varies from an upper limit to the last measurement,
#through the contextual previous rhythm.
refrr = C.BRADY_RR.end
stdrr = 0.1 * refrr
if pattern.evidence[o.Cardiac_Rhythm] and idx == 1:
mrr, srr = pattern.evidence[o.Cardiac_Rhythm][0].meas.rr
if mrr > 0:
refrr, stdrr = mrr, srr
elif idx > 1:
refrr, stdrr = hyp.meas.rr
#Ectopic beats must be advanced wrt the reference RR
tnet.add_constraint(
prev.time, qrs.time,
Iv(C.TACHY_RR.start, max(C.TACHY_RR.start, refrr - stdrr)))
#Beats cannot overlap
tnet.add_constraint(prev.end, qrs.start, Iv(C.TQ_INTERVAL_MIN, np.Inf))
BASIC_TCONST(pattern, qrs)
tnet.add_constraint(qrs.start, qrs.end, C.QRS_DUR)
tnet.set_before(qrs.time, hyp.end)
#Constraints with the precedent T Wave
_qrs_after_twave(pattern, qrs)
def _qrsn_tconst(pattern, qrs):
"""
Temporal constraints for the QRS complexes.
"""
beats = pattern.evidence[o.QRS]
idx = beats.index(qrs)
hyp = pattern.hypothesis
tnet = pattern.last_tnet
obseq = pattern.obs_seq
oidx = pattern.get_step(qrs)
prev = beats[idx-1]
#In cyclic observations, we have to introduce more networks to simplify
#the minimization operation.
tnet.remove_constraint(hyp.end, prev.time)
tnet = ConstraintNetwork()
pattern.temporal_constraints.append(tnet)
meanrr, stdrr = pattern.hypothesis.meas.rr
rr_bounds = Iv(min(C.ASYSTOLE_RR.start, meanrr-stdrr+C.RR_MAX_DIFF),
C.ASYSTOLE_RR.start)
tnet.add_constraint(prev.time, qrs.time, rr_bounds)
tnet.add_constraint(prev.start, qrs.start, rr_bounds)
tnet.add_constraint(prev.end, qrs.end, rr_bounds)
tnet.set_before(prev.end, qrs.start)
#If there is a prior T Wave, it must finish before the start
#of the QRS complex.
if isinstance(obseq[oidx-1], o.TWave):
prevt = obseq[oidx-1]
tnet.set_before(prevt.end, qrs.start)
BASIC_TCONST(pattern, qrs)
tnet.add_constraint(qrs.start, qrs.end, C.QRS_DUR)
tnet.set_before(qrs.time, hyp.end)
#We can introduce constraints on the morphology of the new QRS complex.
if hyp.morph and not qrs.frozen:
qrs.shape = hyp.morph
def _qrs_tconst(pattern, qrs):
"""
Temporal constraints to observe a new QRS complex.
"""
beats = pattern.evidence[o.QRS]
idx = beats.index(qrs)
hyp = pattern.hypothesis
tnet = pattern.last_tnet
obseq = pattern.obs_seq
oidx = pattern.get_step(qrs)
#The environment complex sets the start of the rhythm observation.
if pattern.get_evidence_type(qrs)[1] is ENVIRONMENT:
tnet.set_equal(hyp.start, qrs.time)
else:
if idx > 0:
prev = beats[idx - 1]
tnet.remove_constraint(hyp.end, prev.time)
#We create a new temporal network for the cyclic observations
tnet = ConstraintNetwork()
tnet.add_constraint(prev.time, qrs.time, rr_bounds)
if rr_bounds is not C.TACHY_RR:
#Also bounding on begin and end, but with relaxed variation
#margin.
rlx_rrb = Iv(rr_bounds.start - C.TMARGIN,
rr_bounds.end + C.TMARGIN)
tnet.add_constraint(prev.start, qrs.start, rlx_rrb)
tnet.add_constraint(prev.end, qrs.end, rlx_rrb)
tnet.set_before(prev.end, qrs.start)
#If there is a prior T Wave, it must finish before the start
#of the QRS complex.
if isinstance(obseq[oidx - 1], o.TWave):
prevt = obseq[oidx - 1]
tnet.set_before(prevt.end, qrs.start)
##RR evolution constraint. We combine the statistical limits
#with a dynamic evolution.
if idx > 1:
prev2 = beats[idx - 2]
rrev = prev.time.start - prev2.time.start
if hyp.meas.rr[0] > 0:
meanrr, stdrr = hyp.meas.rr
const = Iv(
min(0.8 * rrev, rrev - C.RR_MAX_DIFF,
meanrr - 2 * stdrr),
max(1.2 * rrev, rrev + C.RR_MAX_DIFF,
meanrr + 2 * stdrr))
else:
const = Iv(min(0.8 * rrev, rrev - C.RR_MAX_DIFF),
max(1.2 * rrev, rrev + C.RR_MAX_DIFF))
tnet.add_constraint(prev.time, qrs.time, const)
pattern.temporal_constraints.append(tnet)
#TODO improve
if not qrs.frozen and hyp.morph:
nullsh = o.QRSShape()
refbeat = next((b for b in reversed(beats[:idx])
if not b.clustered and all(
b.shape.get(lead, nullsh).tag ==
hyp.morph[lead].tag
for lead in hyp.morph)), None)
if refbeat is not None:
qrs.shape = refbeat.shape
qrs.paced = refbeat.paced
BASIC_TCONST(pattern, qrs)
tnet.add_constraint(qrs.start, qrs.end, C.QRS_DUR)
tnet.set_before(qrs.time, hyp.end)