def print_targets(self, targets, output_filename=None, trs=None):
""" Print the set of selected targets.
:param targets:
:param output_filename: (str)
:param trs: (Transcription)
"""
if output_filename is not None:
if output_filename is "STDOUT":
output = sys.stdout
self.__print_tgts(targets, output)
elif output_filename.lower().endswith('momel') is True:
output = open(output_filename, "w")
self.__print_tgts(targets, output)
output.close()
if trs is not None:
# Attention: time in targets is in milliseconds!
tier = trs.NewTier(name="Momel")
for i in range(len(targets)):
_time = targets[i].get_x() * (0.001 * self.PAS_TRAME)
_label = str("%d" % (targets[i].get_y()))
try:
tier.Append(Annotation(TimePoint(_time), Label(_label)))
except Exception:
if self.logfile is not None:
self.logfile.print_message("Ignore target: time=" +
str(_time) + " and value=" +
_label,
indent=2,
status=3)
if output_filename is not None and output_filename.lower(
).endswith('.pitchtier'):
trsp = Transcription()
trsp.Add(tier)
try:
sppas.src.annotationdata.aio.write(output_filename, trsp)
except Exception:
if self.logfile is not None:
self.logfile.print_message(
"Can't write PitchTier output file.", status=-1)
return tier
if tieridx < 0 or tieridx > trs.GetSize():
print('Error: Bad tier number.\n')
sys.exit(1)
tier = trs[tieridx]
if not mode:
mode.append(0)
d = {0: 'exact', 1: 'contains', 2: 'startswith', 3: 'endswith', 4: 'regexp'}
prefix = "" if "CASE_SENSITIVE" in options else "i"
bools = [Sel(**{prefix + d[key]: p}) for key in mode for p in patterns]
pred = functools.reduce(operator.or_, bools)
pred = ~pred if "REVERSE" in options else pred
filtered_annotations = filter(pred, tier)
if not filtered_annotations:
print("NO RESULT")
sys.exit(0)
filteredtier = Tier(tier.Name)
for a in filtered_annotations:
filteredtier.Add(a)
if fileoutput is None:
for a in filteredtier:
print(a)
else:
trs = Transcription()
trs.Add(filteredtier)
sppas.src.annotationdata.aio.write(fileoutput, trs)
label = Label(max_dist, data_type="float")
a = Annotation(TimeInterval(begin, end), label)
filtered_tier.Append(a)
# for i in range(idxbegin,idxend+1):
# print windows[i],distances[i]
# for j in range (w):
# print tier[i+j].GetLocation().GetDuration().GetValue(),tier[i+j].GetLabel().GetValue(), "/",
# print " -> maxdist=",maxdist
# print a
# print
# ----------------------------------------------------------------------------
# Save result
if file_output is None:
for a in filtered_tier:
print(a)
else:
trs = Transcription()
trs.Add(filtered_tier)
# t = Tier('PhonAlign30')
# for v,a in zip(values,tier):
# if v == 1:
# t.Append(a)
# trs.Add(t)
sppas.src.annotationdata.aio.write(file_output, trs)
# ----------------------------------------------------------------------------
# Read
trs_input = sppas.src.annotationdata.aio.read(args.i)
trs_out = Transcription()
# ----------------------------------------------------------------------------
# Transform the PhonAlign tier to a Phonetization tier
try:
align_tier = sppasSearchTier.aligned_phones(trs_input)
logging.info("PhonAlign tier found.")
phon_tier = unalign(align_tier)
phon_tier.SetName("Phones")
trs_out.Add(phon_tier)
except IOError:
logging.info("PhonAlign tier not found.")
# ----------------------------------------------------------------------------
# Transform the TokensAlign tier to a Tokenization tier
if args.tok:
try:
align_tier = sppasSearchTier.aligned_tokens(trs_input)
logging.info("TokensAlign tier found.")
token_tier = unalign(align_tier)
token_tier.SetName("Tokens")
trs_out.Add(token_tier)
except IOError:
logging.info("TokensAlign tier not found.")