def main():
args = docopt(__doc__, version='meTypeset 0.1')
bare_gv = GV(args)
if args['--debug']:
bare_gv.debug.enable_debug(args['--nogit'])
nlm_instance = TeiToNlm(bare_gv)
if args['process']:
# run non-transform portions of teitonlm
TeiToNlm(bare_gv).run(True, False)
# run reference linker
rl = ReferenceLinker(bare_gv)
rl.run(args['--interactive'])
rl.cleanup()
bibliography_classifier = BibliographyClassifier(bare_gv)
# run table classifier
cc = CaptionClassifier(bare_gv)
if int(args['--aggression']) > int(
bare_gv.settings.get_setting(
'tablecaptions', None, domain='aggression')):
cc.run_tables()
if int(args['--aggression']) > int(
bare_gv.settings.get_setting(
'graphiccaptions', None, domain='aggression')):
cc.run_graphics()
if args['--interactive']:
bibliography_classifier.run_prompt(True)
# process any bibliography entries that are possible
BibliographyDatabase(bare_gv).run()
# remove stranded titles
manipulate = NlmManipulate(bare_gv)
manipulate.final_clean()
if args['--identifiers']:
IdGenerator(bare_gv).run()
if args['--chain']:
# construct and run an XSLT chainer
XslChain(bare_gv).run()
if args['--clean']:
ComplianceEnforcer(bare_gv).run()
def main():
args = docopt(__doc__, version='meTypeset 0.1')
bare_gv = GV(args)
if args['--debug']:
bare_gv.debug.enable_debug(args['--nogit'])
nlm_instance = TeiToNlm(bare_gv)
if args['process']:
# run non-transform portions of teitonlm
TeiToNlm(bare_gv).run(True, False)
# run reference linker
rl = ReferenceLinker(bare_gv)
rl.run(args['--interactive'])
rl.cleanup()
bibliography_classifier = BibliographyClassifier(bare_gv)
# run table classifier
cc = CaptionClassifier(bare_gv)
if int(args['--aggression']) > int(bare_gv.settings.get_setting('tablecaptions',
None, domain='aggression')):
cc.run_tables()
if int(args['--aggression']) > int(bare_gv.settings.get_setting('graphiccaptions',
None, domain='aggression')):
cc.run_graphics()
if args['--interactive']:
bibliography_classifier.run_prompt(True)
# process any bibliography entries that are possible
BibliographyDatabase(bare_gv).run()
# remove stranded titles
manipulate = NlmManipulate(bare_gv)
manipulate.final_clean()
if args['--identifiers']:
IdGenerator(bare_gv).run()
if args['--chain']:
# construct and run an XSLT chainer
XslChain(bare_gv).run()
if args['--clean']:
ComplianceEnforcer(bare_gv).run()
