def count_synonyms(candidate, reference, model, n):
matches = 0.0
ng_refs = ngram_counter(reference, n)
for cand in ngram_list(candidate, n):
if tuple(cand) in ng_refs.keys():
matches += 1.0
ng_refs[tuple(cand)] -= 1.0
if ng_refs[tuple(cand)] <= 0.0:
del ng_refs[tuple(cand)]
elif tuple(cand) not in ng_refs.keys():
try:
sims = Counter()
for ii in range(1, n + 1):
ngrs = ngram_counter(reference, ii)
for rr in ngrs.keys():
if rr:
sims[rr] = math.fabs(n_similarity(model, cand, rr))
if sims:
matches += np.max(sims.values())
logging.info(
'candidate %s reference %s similarity%f',\
cand, rr, sims[rr])
ngrs[max(sims)] -= sims[rr]
if ngrs[max(sims)] <= 0.0:
del ngrs[max(sims)]
except KeyError:
matches += 0.0
return matches
def count_s_synonyms(candidate, reference, model, n, threshold):
matches = 0.0
ng_refs = ngram_counter(reference, n)
for cand in ngram_list(candidate, n):
if tuple(cand) in ng_refs.keys():
matches += 1.0
ng_refs[tuple(cand)] -= 1.0
if ng_refs[tuple(cand)] <= 0.0:
del ng_refs[tuple(cand)]
elif tuple(cand) not in ng_refs.keys():
if n == 1:
try:
sims = Counter()
for rr in ng_refs.keys():
sims[rr] = math.fabs(n_similarity(model, cand, rr))
if sims:
if float(np.max(sims.values())) > float(threshold):
matches += np.max(sims.values())
ng_refs[max(sims)] -= sims[rr]
if ng_refs[max(sims)] == 0.0:
del ng_refs[max(sims)]
except KeyError:
matches += 0.0
elif n > 1:
matches += 0.0
return matches
def count_synonyms(candidate, reference, model, n):
matches = 0.0
ng_refs = ngram_counter(reference, n)
for cand in ngram_list(candidate, n):
if tuple(cand) in ng_refs.keys():
matches += 1.0
ng_refs[tuple(cand)] -= 1.0
if ng_refs[tuple(cand)] <= 0.0:
del ng_refs[tuple(cand)]
elif tuple(cand) not in ng_refs.keys():
try:
sims = Counter()
for rr in ng_refs.keys():
sims[rr] = math.fabs(n_similarity(model, cand, rr))
if sims:
matches += np.max(sims.values())
logging.info(
"n %i cand %s ref %s sim %f cnt %f",
n, cand, rr, sims[rr], matches)
ng_refs[max(sims)] -= sims[rr]
if ng_refs[max(sims)] <= 0.0:
del ng_refs[max(sims)]
except KeyError:
matches += 0.0
return matches
def count_matches(candidate, reference, n):
matches = 0.0
ng_refs = ngram_counter(reference, n)
for cand in ngram_list(candidate, n):
if tuple(cand )in ng_refs.keys():
matches += 1.0
ng_refs[tuple(cand)] -= 1.0
if ng_refs[tuple(cand)] == 0.0:
del ng_refs[tuple(cand)]
elif tuple(cand) not in ng_refs.keys():
matches += 0.0
return matches
def count_x_synonyms(candidate, reference, model, n, total_precision, threshold):
matches = 0.0
xng_refs = Counter()
ng_refs = ngram_counter(reference, n)
for ii in range(1, total_precision+1):
xng_refs += ngram_counter(reference, ii)
for cand in ngram_list(candidate, n):
if tuple(cand) in ng_refs.keys():
matches += 1.0
ng_refs[tuple(cand)] -= 1.0
xng_refs[tuple(cand)] -= 1.0
if ng_refs[tuple(cand)] <= 0.0:
del ng_refs[tuple(cand)]
if xng_refs[tuple(cand)] <= 0.0:
del xng_refs[tuple(cand)]
elif tuple(cand) not in ng_refs.keys():
try:
sims = Counter()
for rr in xng_refs.keys():
if rr:
sims[rr] = n_similarity(model, cand, rr)
if sims:
if float(np.max(sims.values())) > float(threshold):
matches += np.max(sims.values())
logging.info(
'%s %s %f',\
cand, max(sims), np.max(sims.values()))
xng_refs[max(sims)] -= sims[rr]
ng_refs[max(sims)] -= sims[rr]
if xng_refs[max(sims)] <= 0.0:
del xng_refs[max(sims)]
if ng_refs[max(sims)] <= 0.0:
del ng_refs[max(sims)]
except KeyError:
matches += 0.0
return matches
def count_synonyms(candidate, reference, model, n):
matches = 0.0
ng_refs = ngram_counter(reference, n)
for cand in ngram_list(candidate, n):
if tuple(cand) in ng_refs.keys():
matches += 1.0
ng_refs[tuple(cand)] -= 1.0
if ng_refs[tuple(cand)] <= 0.0:
del ng_refs[tuple(cand)]
elif tuple(cand) not in ng_refs.keys():
if n == 1:
logging.info(
"no exact match for %s in %s",\
str(cand), str(ng_refs.keys()))
try:
sims = Counter()
for rr in ng_refs.keys():
sims[rr] = math.fabs(n_similarity(model, cand, rr))
logging.info(
"similarity between %s and %s is %f",\
cand, rr, sims[rr])
if sims:
logging.info(
"match count for %s before incrementing is %f",\
str(cand[0]), matches)
matches += np.max(sims.values())
logging.info(
"%s matched %s count incremented by %f yield %f",\
str(cand[0]), str(max(sims)), sims[rr], matches)
ng_refs[max(sims)] -= sims[rr]
if ng_refs[max(sims)] == 0.0:
logging.info(
"removing %s from %s", str(max(sims)), ng_refs)
del ng_refs[max(sims)]
logging.info(
"yields %s", ng_refs)
except KeyError:
matches += 0.0
elif n > 1:
matches += 0.0
return matches