def main():
argv = parse_args(__doc__, version='version 2')
print(argv)
lemmatizer = Lemmatizer()
ptb2dep = NegBioPtb2DepConverter(lemmatizer, universal=True)
splitter = NegBioSSplitter(newline=argv['--newline_is_sentence_break'])
parser = NegBioParser(model_dir=argv['--bllip-model'])
argv = get_absolute_path(argv, '--neg-patterns',
'negbio/patterns/neg_patterns.txt')
argv = get_absolute_path(argv, '--uncertainty-patterns',
'negbio/patterns/uncertainty_patterns.txt')
mm = pymetamap.MetaMap.get_instance(argv['--metamap'])
neg_detector = negdetect.Detector(argv['--neg-patterns'],
argv['--uncertainty-patterns'])
if argv['--cuis'] == 'None':
cuis = None
else:
cuis = read_cuis(argv['--cuis'])
if argv['text']:
collection = text2bioc.text2collection(argv['SOURCES'])
elif argv['bioc']:
with open(argv['SOURCE']) as fp:
collection = bioc.load(fp)
else:
raise KeyError
pipeline(collection, mm, splitter, parser, ptb2dep, neg_detector, cuis)
with open(os.path.expanduser(argv['--output']), 'w') as fp:
bioc.dump(collection, fp)
def main():
argv = parse_args(__doc__, version='version 2')
print(argv)
lemmatizer = Lemmatizer()
ptb2dep = NegBioPtb2DepConverter(lemmatizer, universal=True)
ssplitter = NegBioSSplitter(newline=argv['--newline_is_sentence_break'])
parser = NegBioParser(model_dir=argv['--bllip-model'])
argv = get_absolute_path(argv, '--mention_phrases_dir',
'negbio/chexpert/phrases/mention')
argv = get_absolute_path(argv, '--unmention_phrases_dir',
'negbio/chexpert/phrases/unmention')
argv = get_absolute_path(
argv, '--pre-negation-uncertainty-patterns',
'negbio/chexpert/patterns/pre_negation_uncertainty.txt')
argv = get_absolute_path(
argv, '--post-negation-uncertainty-patterns',
'negbio/chexpert/patterns/post_negation_uncertainty.txt')
argv = get_absolute_path(argv, '--neg-patterns',
'negbio/chexpert/patterns/negation.txt')
# chexpert
loader = NegBioLoader()
extractor = NegBioExtractor(Path(argv['--mention_phrases_dir']),
Path(argv['--unmention_phrases_dir']),
verbose=argv['--verbose'])
neg_detector = ModifiedDetector(
argv['--pre-negation-uncertainty-patterns'], argv['--neg-patterns'],
argv['--post-negation-uncertainty-patterns'])
aggregator = NegBioAggregator(CATEGORIES, verbose=argv['--verbose'])
if argv['text']:
collection = text2bioc.text2collection(argv['SOURCES'])
elif argv['bioc']:
with open(argv['SOURCE']) as fp:
collection = bioc.load(fp)
else:
raise KeyError
pipeline(collection,
loader,
ssplitter,
extractor,
parser,
ptb2dep,
neg_detector,
aggregator,
verbose=argv['--verbose'])
with open(os.path.expanduser(argv['--output']), 'w') as fp:
bioc.dump(collection, fp)
def main(argv):
argv = docopt.docopt(__doc__, argv=argv)
print(argv)
splitter = ssplit.NltkSSplitter(newline=argv['--newline_is_sentence_break'])
parser = parse.Bllip(model_dir=argv['--bllip-model'])
ptb2dep = ptb2ud.Ptb2DepConverter(universal=True)
lemmatizer = ptb2ud.Lemmatizer()
mm = pymetamap.MetaMap.get_instance(argv['--metamap'])
neg_detector = negdetect.Detector(argv['--neg-patterns'], argv['--uncertainty-patterns'])
if argv['--cuis'] == 'None':
cuis = None
else:
cuis = dner_mm.read_cuis(argv['--cuis'])
collection = text2bioc.text2collection(argv['SOURCE'], split_document=argv['--split-document'])
pipeline(collection, mm, splitter, parser, ptb2dep, lemmatizer, neg_detector, cuis)
with open(os.path.expanduser(argv['--out']), 'w') as fp:
bioc.dump(collection, fp)
def process_text(sources, metamap, splitter, parser, ptb2dep, lemmatizer, neg_detector, cuis, sec_title_patterns):
collection = text2bioc.text2collection(*sources)
return process_collection(collection, metamap, splitter, parser, ptb2dep, lemmatizer, neg_detector, cuis, sec_title_patterns)
"""
Convert text FILEs to the BioC output file
Usage:
negbio_pipeline text2bioc [options] --output=<file> <file> ...
Options:
--output=<file> Specify the output file name.
--verbose Print more information about progress.
"""
import bioc
from negbio.cli_utils import parse_args
from negbio.pipeline.text2bioc import text2collection
if __name__ == '__main__':
argv = parse_args(__doc__)
collection = text2collection(argv['<file>'])
with open(argv['--output'], 'w') as fp:
bioc.dump(collection, fp)