def score1q(q, kb, depth, n):
nbest = etcetera.nbest(q.given(), kb, depth, n)
elist = entailedlist(q.given(), nbest, kb)
altaIndex, altaPercent = highestPercent(elist, q.alta())
altbIndex, altbPercent = highestPercent(elist, q.altb())
score = 0
if q.answer() == 'a':
if altaPercent > altbPercent:
score = 1
elif altaIndex < altbIndex:
score = 1
elif altaIndex == altbIndex and altaPercent == altbPercent and altaPercent == 1.0 and len(
q.alta()) > len(q.altb()):
score = 1
elif q.answer() == 'b':
if altbPercent > altaPercent:
score = 1
elif altbIndex < altaIndex:
score = 1
elif altaIndex == altbIndex and altaPercent == altbPercent and altaPercent == 1.0 and len(
q.altb()) > len(q.alta()):
score = 1
else:
print("big problem")
print(q.number(), q.answer(), altaIndex, altaPercent, altbIndex,
altbPercent, score)
return score
def score1q(q, kb, depth, n):
nbest = etcetera.nbest(q.given(), kb, depth, n)
elist = entailedlist(q.given(), nbest, kb)
altaIndex, altaPercent = highestPercent(elist, q.alta())
altbIndex, altbPercent = highestPercent(elist, q.altb())
score = 0
if q.answer() == 'a':
if altaPercent > altbPercent:
score = 1
elif altaIndex < altbIndex:
score = 1
elif altaIndex == altbIndex and altaPercent == altbPercent and altaPercent == 1.0 and len(q.alta()) > len(q.altb()):
score = 1
elif q.answer() == 'b':
if altbPercent > altaPercent:
score = 1
elif altbIndex < altaIndex:
score = 1
elif altaIndex == altbIndex and altaPercent == altbPercent and altaPercent == 1.0 and len(q.altb()) > len(q.alta()):
score = 1
else:
print("big problem")
print(q.number(), q.answer(), altaIndex, altaPercent, altbIndex, altbPercent, score)
return score
if args.all:
solutions = etcetera.etcAbduction(obs, kb, args.depth, skolemize=skolemize)
else:
if args.incremental:
solutions = incremental.incremental(obs,
kb,
args.depth,
args.nbest,
args.window,
args.beam,
skolemize=skolemize)
else:
solutions = etcetera.nbest(obs,
kb,
args.depth,
args.nbest,
skolemize=skolemize)
if args.graph:
solution = solutions[args.solution - 1]
print(forward.graph(solution, forward.forward(solution, kb), targets=obs),
file=args.outfile)
elif args.evalfile:
solution = solutions[args.solution - 1]
precision, recall, f1 = evaluate.evaluate(solution, goldliterals)
print("Precision", precision, "Recall", recall, "F1", f1, sep="\t")
else:
for solution in solutions:
print(parse.display(solution), file=args.outfile)
print(str(len(solutions)) + " solutions.")
if args.all:
solutions = etcetera.etcAbduction(obs, kb, indexed_kb, args.depth)
else:
if args.ilp:
import etcetera_ilp
# import may take a while.
time_start = time.time()
solutions = etcetera_ilp.nbest_ilp(obs, indexed_kb, args.depth,
args.nbest, args.ilp_verbose,
args.ilp_use_cnf,
not args.ilp_no_relreason,
args.ilp_show_nonetc)
else:
solutions = etcetera.nbest(obs, kb, indexed_kb, args.depth, args.nbest)
logging.info(str(len(solutions)) + " solutions.")
logging.info("It took %.2f sec to find the solutions." %
(time.time() - time_start))
if args.graph:
solution = solutions[args.solution - 1]
print(forward.graph(solution, forward.forward(solution, kb), targets=obs),
file=args.outfile)
else:
for solution in solutions:
print("; prob=%s\n%s" %
(etcetera.jointProbability(solution), parse.display(solution)),
file=args.outfile)
# Handle forward
if args.forward:
entailed = forward.forward(obs, kb)
if args.graph:
print(forward.graph(obs, entailed), file=args.outfile)
else:
for e in entailed:
print(parse.display(e[0]), file=args.outfile)
sys.exit()
# Handle abduction
if args.all:
solutions = etcetera.etcAbduction(obs, kb, args.depth)
else:
solutions = etcetera.nbest(obs, kb, args.depth, args.nbest)
if args.graph:
solution = solutions[args.solution - 1]
print(forward.graph(solution, forward.forward(solution, kb), targets=obs),
file=args.outfile)
else:
for solution in solutions:
print(parse.display(solution), file=args.outfile)
print(str(len(solutions)) + " solutions.")
# To do: enable skolemize as an option
def xbestproof(q, kb, depth, x):
xbest = etcetera.nbest(q.given(), kb, depth, x + 1)[x]
return(forward.graph(xbest, forward.forward(xbest, kb), targets=q.given()))
def workflow(q, kb, depth):
best = etcetera.nbest(q.given(), kb, depth, 1)[0]
return(forward.graph(best, forward.forward(best, kb), targets=q.given()))
def xbestproof(q, kb, depth, x):
xbest = etcetera.nbest(q.given(), kb, depth, x + 1)[x]
return (forward.graph(xbest, forward.forward(xbest, kb),
targets=q.given()))
def workflow(q, kb, depth):
best = etcetera.nbest(q.given(), kb, depth, 1)[0]
return (forward.graph(best, forward.forward(best, kb), targets=q.given()))