def testEqual(self):
sis = SpanningIntervalSet([
SpanningInterval(OP, Interval(OP, NINF, 3.0, OP),
Interval(CL, 1.0, PINF, OP), CL)
])
self.assertEqual(sis, sis, True)
def normalized(self):
if self.isNormalized:
return self
jPrime = min_inf([self.j, self.l])
kPrime = max_inf([self.k, self.i])
gammaPrime = self.gamma and self.i != NINF
deltaPrime = (self.delta and jPrime != PINF
and (lt_inf(self.j, self.l) or
(self.zeta and self.alpha and self.beta)))
epsilonPrime = (self.epsilon and kPrime != NINF
and (gt_inf(self.k, self.i) or
(self.gamma and self.beta and self.alpha)))
zetaPrime = self.zeta and self.l != PINF
if (le_inf(self.i, jPrime) and le_inf(kPrime, self.l)
and implies(eq_inf(self.i, jPrime), gammaPrime and deltaPrime)
and implies(eq_inf(kPrime, self.l), epsilonPrime and zetaPrime)
and implies(eq_inf(self.i, self.l),
(self.alpha and self.beta)) and self.i != PINF
and jPrime != NINF and kPrime != PINF and self.l != NINF):
return SpanningInterval(self.alpha,
Interval(gammaPrime, self.i, jPrime,
deltaPrime),
Interval(epsilonPrime, kPrime, self.l,
zetaPrime),
self.beta,
isNormalized=True)
else:
return emptySpanningInterval
def destIntersect(self):
"""
erased intersect because it's hard to implement correctly
"""
sis = SpanningIntervalSet([
SpanningInterval(OP, Interval(OP, NINF, 3.0, OP),
Interval(CL, 1.0, PINF, OP), CL)
])
self.assertEqual(sis, sis.intersect(sis))
def run():
results = inference(model, approach("figure", "landmark"))
print "results", results
self.assertEqual(
results,
SpanningIntervalSet([
SpanningInterval(CL, Interval(CL, 0.0, 3600.0, CL),
Interval(CL, 3600.0, 6300.0, CL), OP),
SpanningInterval(CL, Interval(CL, 6300.0, 24800.0, CL),
Interval(CL, 24800.0, 31800.0, CL), OP)
]))
def testSomething(self):
si1 = SpanningInterval(CL, Interval(OP, NINF, 1.0, OP),
Interval(CL, 1.0, 1.0, CL), OP)
si2 = SpanningInterval(OP, Interval(OP, NINF, 1.0, OP),
Interval(CL, 1.0, 1.0, CL), OP)
self.assertEquals(si1.containsInterval(Interval(CL, 0, 1, OP)), True)
self.assertNotEqual(si1, emptySpanningInterval)
self.assertNotEqual(si1.normalized(), emptySpanningInterval)
print "si1", si1.normalized()
sis = SpanningIntervalSet([si1, si2])
def union(si1, si2):
if si1.alpha == si2.alpha and si1.beta == si2.beta:
bigUnion = SpanningInterval(si1.alpha,
Interval.span(si1.i1, si2.i1),
Interval.span(si1.i2,
si2.i2), si1.beta)
bigUnionNotInSi1 = si1.complement().intersectInterval(bigUnion)
bigUnionNotInSi2 = si2.complement().intersectInterval(bigUnion)
if (all([i.subset(si2) for i in bigUnionNotInSi1])
and all([i.subset(si1) for i in bigUnionNotInSi2])):
return SpanningIntervalSet([bigUnion])
return SpanningIntervalSet([si1, si2])
def intersection(i1, i2):
if i1.alpha == i2.alpha and i1.beta == i2.beta:
if gt_inf(i1.i, i2.i):
gamma = i1.gamma
elif i1.i == i2.i:
gamma = i1.gamma and i2.gamma
elif lt_inf(i1.i, i2.i):
gamma = i2.gamma
else:
raise ValueError()
if lt_inf(i1.j, i2.j):
delta = i1.delta
elif i1.j == i2.j:
delta = i1.delta and i2.delta
elif gt_inf(i1.j, i2.j):
delta = i2.delta
else:
raise ValueError()
if gt_inf(i1.k, i2.k):
epsilon = i1.epsilon
elif i1.k == i2.k:
epsilon = i1.epsilon and i2.epsilon
elif lt_inf(i1.k, i2.k):
epsilon = i2.epsilon
else:
raise ValueError()
if lt_inf(i1.l, i2.l):
zeta = i1.zeta
elif i1.l == i2.l:
zeta = i1.zeta and i2.zeta
elif gt_inf(i1.l, i2.l):
zeta = i2.zeta
else:
raise ValueError()
return SpanningInterval(
i1.alpha,
Interval(gamma, max_inf([i1.i, i2.i]), min_inf([i1.j, i2.j]),
delta),
Interval(epsilon, max_inf([i1.k, i2.k]), min_inf([i1.l, i2.l]),
zeta), i1.beta).normalized()
else:
return emptySpanningInterval
def testFollow(self):
map_fn = "%s/data/directions/direction_floor_3/direction_floor_3_small_filled.cmf" % TKLIB_HOME
cluster_fn = "%s/data/directions/direction_floor_3/skels/direction_floor_3_skel.pck" % TKLIB_HOME
gtruth_tag_fn = "%s/data/directions/direction_floor_3/tags/df3_small_tags.tag" % TKLIB_HOME
assignment_fn = "%s/nlp/data/aaai_2010_smv/stefie10/assignment1.1.yaml" % TKLIB_HOME
tagFile = tag_util.tag_file(gtruth_tag_fn, map_fn)
tagFile.get_map()
tagFile.get_tag_names()
skeleton = carmen_map_skeletonizer.load(cluster_fn, map_fn)
assignment = Assignment.load(assignment_fn, tagFile, skeleton)
slowEntry = assignment.entries[0]
model = modelForSituation(slowEntry.situation)
print "model", model
results = inference(model, following("figure", "landmark"))
self.assertEqual(
results,
SpanningIntervalSet([
SpanningInterval(CL, Interval(CL, 1100.0, 5700.0, OP),
Interval(OP, 1100.0, 5700.0, CL), OP),
SpanningInterval(CL, Interval(CL, 6200.0, 15900.0, OP),
Interval(OP, 6200.0, 15900.0, CL), OP),
SpanningInterval(CL, Interval(CL, 16000.0, 21000.0, OP),
Interval(OP, 16000.0, 21000.0, CL), OP)
]))
def complement(self):
return SpanningIntervalSet([
SpanningInterval(self.alpha, everything,
Interval(CL, NINF, self.k, not self.epsilon),
self.beta),
SpanningInterval(self.alpha, everything,
Interval(not self.zeta, self.l, PINF, CL),
self.beta),
SpanningInterval(self.alpha,
Interval(CL, NINF, self.i, not self.gamma),
everything, self.beta),
SpanningInterval(self.alpha,
Interval(not self.delta, self.j, PINF, CL),
everything, self.beta),
SpanningInterval(not self.alpha, everything, everything,
self.beta),
SpanningInterval(self.alpha, everything, everything,
not self.beta),
SpanningInterval(not self.alpha, everything, everything,
not self.beta),
])
def span(i1, i2):
j = min_inf([i1.j, i2.j])
k = max_inf([i1.k, i2.k])
delta = ((i1.delta and le_inf(i1.j, i2.j))
or (i2.delta and ge_inf(i1.j, i2.j)))
epsilon = ((i1.epsilon and ge_inf(i1.k, i2.k))
or (i2.epsilon and le_inf(i1.k, i2.k)))
return SpanningIntervalSet([
SpanningInterval(i1.alpha, Interval(i1.gamma, i1.i, i1.j,
i1.delta),
Interval(i1.epsilon, i1.k, i1.l, i1.zeta),
i1.beta),
SpanningInterval(i1.alpha, Interval(i1.gamma, i1.i, j, delta),
Interval(epsilon, k, i1.l, i1.zeta), i1.beta),
SpanningInterval(i1.alpha, Interval(i1.gamma, i1.i, j, delta),
Interval(epsilon, k, i2.l, i2.zeta), i2.beta),
SpanningInterval(i2.alpha, Interval(i2.gamma, i2.i, j, delta),
Interval(epsilon, k, i1.l, i1.zeta), i1.beta),
SpanningInterval(i2.alpha, Interval(i2.gamma, i2.i, j, delta),
Interval(epsilon, k, i2.l, i2.zeta), i2.beta)
])
def largestInterval(self):
return Interval(self.alpha, self.i1.i, self.i2.j, self.beta)
elif allenRelation == allenRelations.iDuring:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(self.alpha and alpha2 and self.gamma,
self.i, PINF, CL),
Interval(CL, NINF, self.l, self.beta and not beta2
and self.zeta), beta2))
return SpanningIntervalSet(result)
else:
raise ValueError("Bad relation: " + ` allenRelation `)
emptySpanningInterval = SpanningInterval(OP,
Interval(OP, 0, 0, OP),
Interval(OP, 0, 0, OP),
OP,
isNormalized=True)
allIntervals = SpanningIntervalSet([
SpanningInterval(OP, Interval(OP, NINF, PINF, OP),
Interval(OP, NINF, PINF, OP), OP),
SpanningInterval(OP, Interval(OP, NINF, PINF, OP),
Interval(OP, NINF, PINF, OP), CL),
SpanningInterval(CL, Interval(OP, NINF, PINF, OP),
Interval(OP, NINF, PINF, OP), OP),
SpanningInterval(CL, Interval(OP, NINF, PINF, OP),
Interval(OP, NINF, PINF, OP), CL),
])
def testCenter(self):
self.assertEqual(Interval(OP, 1, 4, OP).center, 2.5)
self.assertEqual(Interval(OP, -1, 3, OP).center, 1)
self.assertEqual(Interval(OP, NINF, PINF, OP).center, 0)
def testSubsetAndSuperset(self):
self.containment(Interval(CL, 0, 1, CL),
Interval(CL, -1, 2, CL),
isSubset=True,
isSuperset=False)
self.containment(Interval(CL, -1, 2, CL),
Interval(CL, 0, 1, CL),
isSubset=False,
isSuperset=True)
self.containment(Interval(OP, 0, 1, OP),
Interval(CL, 0, 1, CL),
isSubset=True,
isSuperset=False)
self.containment(Interval(CL, 0, 1, CL),
Interval(OP, 0, 1, OP),
isSubset=False,
isSuperset=True)
self.containment(Interval(OP, 0, 1, OP),
Interval(CL, 0, 1, CL),
isSubset=True,
isSuperset=False)
self.containment(Interval(CL, 0, 1, OP),
Interval(CL, 0, 1, CL),
isSubset=True,
isSuperset=False)
self.containment(Interval(OP, 0, 1, CL),
Interval(CL, 0, 1, CL),
isSubset=True,
isSuperset=False)
self.containment(Interval(CL, 0, 1, CL),
Interval(CL, 0, 1, CL),
isSubset=False,
isSuperset=True)
self.containment(Interval(CL, 0, 1, CL),
Interval(CL, 0.5, 1.5, CL),
isSubset=False,
isSuperset=False)
self.containment(Interval(CL, 0, 1, CL),
Interval(CL, 10, 11, CL),
isSubset=False,
isSuperset=False)
self.containment(Interval(CL, 0.0, 1.0, CL),
Interval(CL, 0.0, 2.0, CL),
isSubset=True,
isSuperset=False)
def testLength(self):
self.assertEqual(Interval(OP, 1, 4, OP).length, 3)
self.assertEqual(Interval(OP, -1, 3, OP).length, 4)
self.assertEqual(Interval(OP, NINF, PINF, OP).length, PINF)
def D(self, allenRelation):
if allenRelation == allenRelations.equals:
return SpanningIntervalSet([self])
elif allenRelation == allenRelations.lessThan:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(
not self.beta and not alpha2 and self.epsilon,
self.k, PINF, CL), everything, beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.greaterThan:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2, everything,
Interval(
CL, NINF, self.j, not self.alpha and not beta2
and self.delta), beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.meets:
result = []
for beta2 in endStatus:
result.append(
SpanningInterval(not self.beta, self.i2, everything,
beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.iMeets:
result = []
for alpha2 in endStatus:
result.append(
SpanningInterval(alpha2, everything, self.i1,
not self.alpha))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.overlaps:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(self.alpha and not alpha2 and self.gamma,
self.i, self.l, self.beta and alpha2
and self.zeta),
Interval(not self.beta and beta2 and self.epsilon,
self.k, PINF, CL), beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.iOverlaps:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(CL, NINF, self.j, not self.alpha
and alpha2 and self.delta),
Interval(self.alpha and beta2 and self.gamma,
self.i, self.l, self.beta and not beta2
and self.zeta), beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.starts:
result = []
for beta2 in endStatus:
result.append(
SpanningInterval(
self.alpha, self.i1,
Interval(not self.beta and beta2 and self.epsilon,
self.k, PINF, CL), beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.iStarts:
result = []
for beta2 in endStatus:
result.append(
SpanningInterval(
self.alpha, self.i1,
Interval(CL, NINF, self.l, self.beta and not beta2
and self.zeta), beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.finishes:
result = []
for alpha2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(CL, NINF, self.j, not self.alpha and alpha2
and self.delta), self.i2, self.beta))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.iFinishes:
result = []
for alpha2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(self.alpha and not alpha2 and self.gamma,
self.i, PINF, CL), self.i2, self.beta))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.during:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(CL, NINF, self.j, not self.alpha
and alpha2 and self.delta),
Interval(not self.beta and beta2 and self.epsilon,
self.k, PINF, CL), beta2))
return SpanningIntervalSet(result)
elif allenRelation == allenRelations.iDuring:
result = []
for alpha2 in endStatus:
for beta2 in endStatus:
result.append(
SpanningInterval(
alpha2,
Interval(self.alpha and alpha2 and self.gamma,
self.i, PINF, CL),
Interval(CL, NINF, self.l, self.beta and not beta2
and self.zeta), beta2))
return SpanningIntervalSet(result)
else:
raise ValueError("Bad relation: " + ` allenRelation `)
def testSpan(self):
self.assertEqual(
Interval.span(Interval(OP, 1, 4, OP), Interval(CL, 2, 6, CL)),
Interval(OP, 1, 6, CL))
