def main():
#### Parse command-line arguments
parser = argparse.ArgumentParser(description = \
'Phonological CorpusTools: corpus object creation CL interface')
parser.add_argument('csv_file_name', help='Name of input CSV file')
parser.add_argument('-f', '--feature_file_name', default = '', type=str, help='Name of input feature file')
parser.add_argument('-d', '--delimiter', default='\t', type=str, help='Character that delimits columns in the input file')
parser.add_argument('-t', '--trans_delimiter', default='', type=str, help='Character that delimits segments in the input file')
args = parser.parse_args()
####
delimiter = codecs.getdecoder("unicode_escape")(args.delimiter)[0]
try: # Full path specified
filename, extension = os.path.splitext(args.csv_file_name)
filename = path_leaf(filename)
corpus = load_corpus_csv(args.csv_file_name, args.csv_file_name,
delimiter, args.trans_delimiter, args.feature_file_name)
save_binary(corpus, filename+'.corpus')
except FileNotFoundError:
#FIXME! os.path.join takes care of os specific paths
try: # Unix filepaths
filename, extension = os.path.splitext(os.path.dirname(os.path.realpath(__file__))+'/'+args.csv_file_name)
corpus = load_corpus_csv(args.csv_file_name, os.path.dirname(os.path.realpath(__file__))+'/'+args.csv_file_name,
delimiter, args.trans_delimiter, os.path.dirname(os.path.realpath(__file__))+'/'+args.feature_file_name)
save_binary(corpus, filename+'.corpus')
except FileNotFoundError: # Windows filepaths
filename, extension = os.path.splitext(os.path.dirname(os.path.realpath(__file__))+'\\'+args.csv_file_name)
corpus = load_corpus_csv(args.csv_file_name, os.path.dirname(os.path.realpath(__file__))+'\\'+args.csv_file_name,
delimiter, args.trans_delimiter, os.path.dirname(os.path.realpath(__file__))+'\\'+args.feature_file_name)
save_binary(corpus, filename+'.corpus')
def test_corpus_csv(csv_test_dir, unspecified_test_corpus):
example_path = os.path.join(csv_test_dir, 'example.txt')
with pytest.raises(DelimiterError):
load_corpus_csv('example',example_path,delimiter='\t')
#with pytest.raises(DelimiterError):
# load_corpus_csv('example',example_path,delimiter=',')
c = load_corpus_csv('example',example_path,delimiter=',')
assert(isinstance(c, Corpus))
assert(c == unspecified_test_corpus)
def test_stressed(csv_test_dir):
stressed_path = os.path.join(csv_test_dir, 'stressed.txt')
ats,_ = inspect_csv(stressed_path, coldelim = ',')
print(ats)
ats[1].number_behavior = 'stress'
c = load_corpus_csv('stressed',stressed_path,',', ats)
assert(c.inventory['uw'].symbol == 'uw')
assert(c.inventory.stresses == {'1': set(['uw','iy']),
'0': set(['uw','iy','ah'])})
def run(self):
time.sleep(0.1)
textType = self.kwargs.pop('text_type')
isDirectory = self.kwargs.pop('isDirectory')
logging.info('Importing {} corpus named {}'.format(
textType, self.kwargs['corpus_name']))
logging.info('Path: '.format(self.kwargs['path']))
log_annotation_types(self.kwargs['annotation_types'])
try:
if textType == 'spelling':
if isDirectory:
corpus = load_directory_spelling(**self.kwargs)
else:
corpus = load_discourse_spelling(**self.kwargs)
elif textType == 'transcription':
if isDirectory:
corpus = load_directory_transcription(**self.kwargs)
else:
corpus = load_discourse_transcription(**self.kwargs)
elif textType == 'ilg':
if isDirectory:
corpus = load_directory_ilg(**self.kwargs)
else:
corpus = load_discourse_ilg(**self.kwargs)
elif textType == 'textgrid':
if isDirectory:
corpus = load_directory_textgrid(**self.kwargs)
else:
corpus = load_discourse_textgrid(**self.kwargs)
elif textType == 'csv':
corpus = load_corpus_csv(**self.kwargs)
elif textType in ['buckeye', 'timit']:
self.kwargs['dialect'] = textType
if isDirectory:
corpus = load_directory_multiple_files(**self.kwargs)
else:
corpus = load_discourse_multiple_files(**self.kwargs)
except PCTError as e:
self.errorEncountered.emit(e)
return
except Exception as e:
e = PCTPythonError(e)
self.errorEncountered.emit(e)
return
if self.stopped:
time.sleep(0.1)
self.finishedCancelling.emit()
return
self.dataReady.emit(corpus)
def run(self):
time.sleep(0.1)
textType = self.kwargs.pop('text_type')
isDirectory = self.kwargs.pop('isDirectory')
logging.info('Importing {} corpus named {}'.format(textType, self.kwargs['corpus_name']))
logging.info('Path: '.format(self.kwargs['path']))
log_annotation_types(self.kwargs['annotation_types'])
try:
if textType == 'spelling':
if isDirectory:
corpus = load_directory_spelling(**self.kwargs)
else:
corpus = load_discourse_spelling(**self.kwargs)
elif textType == 'transcription':
if isDirectory:
corpus = load_directory_transcription(**self.kwargs)
else:
corpus = load_discourse_transcription(**self.kwargs)
elif textType == 'ilg':
if isDirectory:
corpus = load_directory_ilg(**self.kwargs)
else:
corpus = load_discourse_ilg(**self.kwargs)
elif textType == 'textgrid':
if isDirectory:
corpus = load_directory_textgrid(**self.kwargs)
else:
corpus = load_discourse_textgrid(**self.kwargs)
elif textType == 'csv':
corpus = load_corpus_csv(**self.kwargs)
elif textType in ['buckeye', 'timit']:
self.kwargs['dialect'] = textType
if isDirectory:
corpus = load_directory_multiple_files(**self.kwargs)
else:
corpus = load_discourse_multiple_files(**self.kwargs)
except PCTError as e:
self.errorEncountered.emit(e)
return
except Exception as e:
e = PCTPythonError(e)
self.errorEncountered.emit(e)
return
if self.stopped:
time.sleep(0.1)
self.finishedCancelling.emit()
return
self.dataReady.emit(corpus)
def main():
#### Parse command-line arguments
parser = argparse.ArgumentParser(description = \
'Phonological CorpusTools: corpus object creation CL interface')
parser.add_argument('csv_file_name', help='Name of input CSV file')
parser.add_argument('-f', '--feature_file_name', default = '', type=str, help='Name of input feature file')
parser.add_argument('-d', '--delimiter', default=None, type=str, help='Character that delimits columns in the input file')
parser.add_argument('-t', '--trans_delimiter', default=None, type=str, help='Character that delimits segments in the input file')
args = parser.parse_args()
####
if args.delimiter:
delimiter = codecs.getdecoder("unicode_escape")(args.delimiter)[0]
else:
delimiter = args.delimiter
try: # Full path specified
filename, extension = os.path.splitext(args.csv_file_name)
filename = path_leaf(filename)
corpus = load_corpus_csv(args.csv_file_name, args.csv_file_name,
delimiter, args.trans_delimiter, annotation_types=None, feature_system_path=args.feature_file_name)
save_binary(corpus, filename+'.corpus')
except FileNotFoundError:
#TO-DO: os.path.join takes care of os specific paths
try: # Unix filepaths
filename, extension = os.path.splitext(os.path.dirname(os.path.realpath(__file__))+'/'+args.csv_file_name)
corpus = load_corpus_csv(args.csv_file_name, os.path.dirname(os.path.realpath(__file__))+'/'+args.csv_file_name,
delimiter, args.trans_delimiter, annotation_types=None, feature_system_path=os.path.dirname(os.path.realpath(__file__))+'/'+args.feature_file_name)
save_binary(corpus, filename+'.corpus')
except FileNotFoundError: # Windows filepaths
filename, extension = os.path.splitext(os.path.dirname(os.path.realpath(__file__))+'\\'+args.csv_file_name)
corpus = load_corpus_csv(args.csv_file_name, os.path.dirname(os.path.realpath(__file__))+'\\'+args.csv_file_name,
delimiter, args.trans_delimiter, annotation_types=None, feature_system_path=os.path.dirname(os.path.realpath(__file__))+'\\'+args.feature_file_name)
save_binary(corpus, filename+'.corpus')
