def _itergroundings(self, simplify=False, unsatfailure=False):
if self.verbose:
bar = ProgressBar(width=100, color='green')
for i, formula in enumerate(self.formulas):
if self.verbose: bar.update((i+1) / float(len(self.formulas)))
for gndformula in formula.itergroundings(self.mrf, simplify=simplify):
if unsatfailure and gndformula.weight == HARD and gndformula(self.mrf.evidence) != 1:
print
gndformula.print_structure(self.mrf.evidence)
raise SatisfiabilityException('MLN is unsatisfiable due to hard constraint violation %s (see above)' % self.mrf.formulas[gndformula.idx])
yield gndformula
def _itergroundings(self, simplify=False, unsatfailure=False):
if self.verbose:
bar = ProgressBar(width=100, color='green')
for i, formula in enumerate(self.formulas):
if self.verbose: bar.update((i + 1) / float(len(self.formulas)))
for gndformula in formula.itergroundings(self.mrf,
simplify=simplify):
if unsatfailure and gndformula.weight == HARD and gndformula(
self.mrf.evidence) != 1:
print
gndformula.print_structure(self.mrf.evidence)
raise SatisfiabilityException(
'MLN is unsatisfiable due to hard constraint violation %s (see above)'
% self.mrf.formulas[gndformula.idx])
yield gndformula
def _run(self):
"""
verbose: whether to print results (or anything at all, in fact)
details: (given that verbose is true) whether to output additional
status information
debug: (given that verbose is true) if true, outputs debug
information, in particular the distribution over possible
worlds
debugLevel: level of detail for debug mode
"""
# check consistency with hard constraints:
self._watch.tag('check hard constraints', verbose=self.verbose)
hcgrounder = FastConjunctionGrounding(self.mrf, simplify=False, unsatfailure=True,
formulas=[f for f in self.mrf.formulas if f.weight == HARD],
**(self._params + {'multicore': False, 'verbose': False}))
for gf in hcgrounder.itergroundings():
if isinstance(gf, Logic.TrueFalse) and gf.truth() == .0:
raise SatisfiabilityException('MLN is unsatisfiable due to hard constraint violation by evidence: {} ({})'.format(str(gf), str(self.mln.formula(gf.idx))))
self._watch.finish('check hard constraints')
# compute number of possible worlds
worlds = 1
for variable in self.mrf.variables:
values = variable.valuecount(self.mrf.evidence)
worlds *= values
numerators = [0.0 for i in range(len(self.queries))]
denominator = 0.
# start summing
logger.debug("Summing over %d possible worlds..." % worlds)
if worlds > 500000 and self.verbose:
print colorize('!!! %d WORLDS WILL BE ENUMERATED !!!' % worlds, (None, 'red', True), True)
k = 0
self._watch.tag('enumerating worlds', verbose=self.verbose)
global global_enumAsk
global_enumAsk = self
bar = None
if self.verbose:
bar = ProgressBar(width=100, steps=worlds, color='green')
if self.multicore:
pool = Pool()
logger.debug('Using multiprocessing on {} core(s)...'.format(pool._processes))
try:
for num, denum in pool.imap(with_tracing(eval_queries), self.mrf.worlds()):
denominator += denum
k += 1
for i, v in enumerate(num):
numerators[i] += v
if self.verbose: bar.inc()
except Exception as e:
logger.error('Error in child process. Terminating pool...')
pool.close()
raise e
finally:
pool.terminate()
pool.join()
else: # do it single core
for world in self.mrf.worlds():
# compute exp. sum of weights for this world
num, denom = eval_queries(world)
denominator += denom
for i, _ in enumerate(self.queries):
numerators[i] += num[i]
k += 1
if self.verbose:
bar.update(float(k) / worlds)
logger.debug("%d worlds enumerated" % k)
self._watch.finish('enumerating worlds')
if 'grounding' in self.grounder.watch.tags:
self._watch.tags['grounding'] = self.grounder.watch['grounding']
if denominator == 0:
raise SatisfiabilityException(
'MLN is unsatisfiable. All probability masses returned 0.')
# normalize answers
dist = map(lambda x: float(x) / denominator, numerators)
result = {}
for q, p in zip(self.queries, dist):
result[str(q)] = p
return result
