def parse(self, sentences):
'''
Accepts as arguments a sentence or a list of sentences. Returns the
syntactic structure of the sentences in form of MLN databases
containing the respective atoms.
:param sentences: a sentence or list of sentences in natural language
:return: a list of databases returned by parse_db
'''
#=======================================================================
# Create a temporary file in which nlparse will write its result
#=======================================================================
filepath = None
with NamedTemporaryFile(suffix='.db', delete=False) as f:
filepath = f.name
cmd = [
'python',
os.path.join(self.module_path, 'src', 'nlparse.py'), '--out-file',
filepath
]
cmd.extend([json.dumps(s) for s in sentences])
logger.debug('Calling Stanford Parser: '.format(cmd))
envs = os.environ
envs.update({"PYTHONPATH": locations.code_base})
subprocess.call(
cmd,
env=envs,
)
with open(filepath, 'r') as f:
c = f.read()
return parse_db(self.mln, c)
def update_result_from_dbeditor(self):
dbtext = self.db_container.editor.get("1.0",
END).encode('utf8').strip()
dbobj = parse_db(self.prac.mln,
dbtext,
ignore_unknown_preds=self.config.get(
'ignore_unknown_preds', True))
self.prac_inference.inference_steps[-1].output_dbs = dbobj
def loaddb(self, mln, config, db=None):
if db is None:
if config == 'query': config = self.queryconf
elif config == 'learn': config = self.learnconf
else: raise Exception('Need a database name or config.')
from pracmln.mln.database import parse_db
path = self.path if hasattr(self, 'path') else None
out(db)
out(self.dbs[db])
return parse_db(mln, self.dbs[ifNone(db, config['db'])], ignore_unknown_preds=config['ignore_unknown_preds'], projectpath=path)
def loaddb(self, mln, config, db=None):
if db is None:
if config not in ['query', 'learn']:
raise Exception('Need a database name or config.')
if config == 'query': config = self.queryconf
elif config == 'learn': config = self.learnconf
from pracmln.mln.database import parse_db
path = self.path if hasattr(self, 'path') else None
return parse_db(mln,
self.dbs[ifnone(db, config['db'])],
ignore_unknown_preds=config['ignore_unknown_preds'],
projectpath=path)
def __get_db(self, request, config, mln):
if not request.query.evidence and config.db == "":
raise Exception("No evidence provided!")
if request.query.evidence and config.db != "":
raise Exception(
"Duplicate evidence; provide either a db in the config or an evidence db in the query"
)
if request.query.evidence:
to_return = parse_db(
mln, reduce(lambda x, y: x + "\n" + y, request.query.evidence))
else:
to_return = Database.load(mln, config.db)
if len(to_return) != 1:
raise Exception("Only one db is supported!")
return to_return[0]
def learn(self, savegeometry=True, options=None, *_):
if options is None:
options = {}
mln_content = self.mln_container.editor.get("1.0", END).strip()
db_content = self.db_container.editor.get("1.0", END).strip()
# create conf from current gui settings
self.update_config()
# write gui settings
self.write_gconfig(savegeometry=savegeometry)
# hide gui
self.master.withdraw()
try:
print((headline('PRAC LEARNING TOOL')))
print()
if options.get('mlnarg') is not None:
mlnobj = MLN(mlnfile=os.path.abspath(options.get('mlnarg')),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
else:
mlnobj = parse_mln(mln_content, searchpaths=[self.project_dir],
projectpath=os.path.join(self.project_dir, self.project.name),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
if options.get('dbarg') is not None:
dbobj = Database.load(mlnobj, dbfiles=[options.get('dbarg')], ignore_unknown_preds=self.config.get('ignore_unknown_preds', True))
else:
if self.config.get('pattern'):
local, dblist = self.get_training_db_paths(self.config.get('pattern').strip())
dbobj = []
# build database list from project dbs
if local:
for dbname in dblist:
dbobj.extend(parse_db(mlnobj, self.project.dbs[dbname].strip(),
ignore_unknown_preds=self.config.get('ignore_unknown_preds', True),
projectpath=os.path.join(self.dir, self.project.name)))
out(dbobj)
# build database list from filesystem dbs
else:
for dbpath in dblist:
dbobj.extend(Database.load(mlnobj, dbpath, ignore_unknown_preds= self.config.get('ignore_unknown_preds', True)))
# build single db from currently selected db
else:
dbobj = parse_db(mlnobj, db_content, projectpath=os.path.join(self.dir, self.project.name), dirs=[self.dir])
learning = MLNLearn(config=self.config, mln=mlnobj, db=dbobj)
result = learning.run()
# write to file if run from commandline, otherwise save result
# to project results
if options.get('outputfile') is not None:
output = io.StringIO()
result.write(output)
with open(os.path.abspath(options.get('outputfile')), 'w') as f:
f.write(output.getvalue())
logger.info('saved result to {}'.format(os.path.abspath(options.get('outputfile'))))
elif self.save.get():
output = io.StringIO()
result.write(output)
self.project.add_mln(self.output_filename.get(), output.getvalue())
self.mln_container.update_file_choices()
self.project.save(dirpath=self.project_dir)
logger.info('saved result to file mln/{} in project {}'.format(self.output_filename.get(), self.project.name))
else:
logger.debug("No output file given - results have not been saved.")
except:
traceback.print_exc()
# restore gui
sys.stdout.flush()
self.master.deiconify()
def infer(self, savegeometry=True, options={}, *args):
mln_content = self.mln_container.editor.get("1.0", END).strip()
db_content = self.db_container.editor.get("1.0", END).strip()
# create conf from current gui settings
self.update_config()
# write gui settings
self.write_gconfig(savegeometry=savegeometry)
# hide gui
self.master.withdraw()
try:
print((headline('PRACMLN QUERY TOOL')))
print()
if options.get('mlnarg') is not None:
mlnobj = MLN(mlnfile=os.path.abspath(options.get('mlnarg')),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
else:
mlnobj = parse_mln(
mln_content,
searchpaths=[self.dir],
projectpath=os.path.join(self.dir, self.project.name),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
if options.get('emlnarg') is not None:
emln_content = mlnpath(options.get('emlnarg')).content
else:
emln_content = self.emln_container.editor.get("1.0",
END).strip()
if options.get('dbarg') is not None:
dbobj = Database.load(mlnobj,
dbfiles=[options.get('dbarg')],
ignore_unknown_preds=self.config.get(
'ignore_unknown_preds', True))
else:
out(self.config.get('ignore_unknown_preds', True))
dbobj = parse_db(mlnobj,
db_content,
ignore_unknown_preds=self.config.get(
'ignore_unknown_preds', True))
if options.get('queryarg') is not None:
self.config["queries"] = options.get('queryarg')
infer = MLNQuery(config=self.config,
mln=mlnobj,
db=dbobj,
emln=emln_content)
result = infer.run()
# write to file if run from commandline, otherwise save result to project results
if options.get('outputfile') is not None:
output = io.StringIO()
result.write(output)
with open(os.path.abspath(options.get('outputfile')),
'w') as f:
f.write(output.getvalue())
logger.info('saved result to {}'.format(
os.path.abspath(options.get('outputfile'))))
elif self.save.get():
output = io.StringIO()
result.write(output)
fname = self.output_filename.get()
self.project.add_result(fname, output.getvalue())
self.project.save(dirpath=self.dir)
logger.info(
'saved result to file results/{} in project {}'.format(
fname, self.project.name))
else:
logger.debug(
'No output file given - results have not been saved.')
except:
traceback.print_exc()
# restore main window
sys.stdout.flush()
self.master.deiconify()
def learn(self, savegeometry=True, options={}, *args):
mln_content = self.mln_container.editor.get("1.0", END).encode('utf8').strip()
db_content = self.db_container.editor.get("1.0", END).encode('utf8').strip()
# create conf from current gui settings
self.update_config()
# write gui settings
self.write_gconfig(savegeometry=savegeometry)
# hide gui
self.master.withdraw()
try:
print headline('PRAC LEARNING TOOL')
print
if options.get('mlnarg') is not None:
mlnobj = MLN(mlnfile=os.path.abspath(options.get('mlnarg')),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
else:
mlnobj = parse_mln(mln_content, searchpaths=[self.project_dir],
projectpath=os.path.join(self.project_dir, self.project.name),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
if options.get('dbarg') is not None:
dbobj = Database.load(mlnobj, dbfiles=[options.get('dbarg')], ignore_unknown_preds=self.config.get('ignore_unknown_preds', True))
else:
if self.config.get('pattern'):
local, dblist = self.get_training_db_paths(self.config.get('pattern').strip())
dbobj = []
# build database list from project dbs
if local:
for dbname in dblist:
dbobj.extend(parse_db(mlnobj, self.project.dbs[dbname].strip(),
ignore_unknown_preds=self.config.get('ignore_unknown_preds', True),
projectpath=os.path.join(self.dir, self.project.name)))
out(dbobj)
# build database list from filesystem dbs
else:
for dbpath in dblist:
dbobj.extend(Database.load(mlnobj, dbpath, ignore_unknown_preds= self.config.get('ignore_unknown_preds', True)))
# build single db from currently selected db
else:
dbobj = parse_db(mlnobj, db_content, projectpath=os.path.join(self.dir, self.project.name), dirs=[self.dir])
learning = MLNLearn(config=self.config, mln=mlnobj, db=dbobj)
result = learning.run()
# write to file if run from commandline, otherwise save result
# to project results
if options.get('outputfile') is not None:
output = StringIO.StringIO()
result.write(output)
with open(os.path.abspath(options.get('outputfile')), 'w') as f:
f.write(output.getvalue())
logger.info('saved result to {}'.format(os.path.abspath(options.get('outputfile'))))
elif self.save.get():
output = StringIO.StringIO()
result.write(output)
self.project.add_mln(self.output_filename.get(), output.getvalue())
self.mln_container.update_file_choices()
self.project.save(dirpath=self.project_dir)
logger.info('saved result to file mln/{} in project {}'.format(self.output_filename.get(), self.project.name))
else:
logger.debug("No output file given - results have not been saved.")
except:
traceback.print_exc()
# restore gui
sys.stdout.flush()
self.master.deiconify()
def infer(self, savegeometry=True, options={}, *args):
mln_content = self.mln_container.editor.get("1.0", END).encode('utf8').strip()
db_content = self.db_container.editor.get("1.0", END).encode('utf8').strip()
# create conf from current gui settings
self.update_config()
# write gui settings
self.write_gconfig(savegeometry=savegeometry)
# hide gui
self.master.withdraw()
try:
print headline('PRACMLN QUERY TOOL')
print
if options.get('mlnarg') is not None:
mlnobj = MLN(mlnfile=os.path.abspath(options.get('mlnarg')),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
else:
mlnobj = parse_mln(mln_content, searchpaths=[self.dir],
projectpath=os.path.join(self.dir, self.project.name),
logic=self.config.get('logic', 'FirstOrderLogic'),
grammar=self.config.get('grammar', 'PRACGrammar'))
if options.get('emlnarg') is not None:
emln_content = mlnpath(options.get('emlnarg')).content
else:
emln_content = self.emln_container.editor.get("1.0", END).encode('utf8').strip()
if options.get('dbarg') is not None:
dbobj = Database.load(mlnobj, dbfiles=[options.get('dbarg')], ignore_unknown_preds=self.config.get('ignore_unknown_preds', True))
else:
out(self.config.get('ignore_unknown_preds', True))
dbobj = parse_db(mlnobj, db_content, ignore_unknown_preds=self.config.get('ignore_unknown_preds', True))
if options.get('queryarg') is not None:
self.config["queries"] = options.get('queryarg')
infer = MLNQuery(config=self.config, mln=mlnobj, db=dbobj, emln=emln_content)
result = infer.run()
# write to file if run from commandline, otherwise save result to project results
if options.get('outputfile') is not None:
output = StringIO.StringIO()
result.write(output)
with open(os.path.abspath(options.get('outputfile')), 'w') as f:
f.write(output.getvalue())
logger.info('saved result to {}'.format(os.path.abspath(options.get('outputfile'))))
elif self.save.get():
output = StringIO.StringIO()
result.write(output)
fname = self.output_filename.get()
self.project.add_result(fname, output.getvalue())
self.project.save(dirpath=self.dir)
logger.info('saved result to file results/{} in project {}'.format(fname, self.project.name))
else:
logger.debug('No output file given - results have not been saved.')
except:
traceback.print_exc()
# restore main window
sys.stdout.flush()
self.master.deiconify()
