def drawPicture(filename):
drawing = DrawPricture(filename)
parser = Parser(filename)
parser.parser_program()
sement = Semantics(paramter_list=parser.paramters,drawing=drawing)
sement.Semantic()
drawing.draw()
def writeCUEDFile(self, cued_fn, semantics):
fw = codecs.open(cued_fn, "w", "UTF-8")
try:
for smntcs in semantics:
text = removeConceptsFromSemantics(smntcs.semantics)
smntcsWithoutText = removeTextFromSemantics(smntcs.semantics)
smntcsWithoutText = Semantics("id", smntcsWithoutText, "x")
fw.write(smntcs.text + " <=> " + smntcsWithoutText.getCUEDSemantics() + "\n")
finally:
fw.close()
def writeCUEDFile(self, cued_fn, semantics):
fw = codecs.open(cued_fn, "w", "UTF-8")
try:
for smntcs in semantics:
text = removeConceptsFromSemantics(smntcs.semantics)
smntcsWithoutText = removeTextFromSemantics(smntcs.semantics)
smntcsWithoutText = Semantics('id', smntcsWithoutText, 'x')
fw.write(smntcs.text+' <=> '+smntcsWithoutText.getCUEDSemantics() + '\n')
finally:
fw.close()
def writePTBFile(self, ptb_fn, semantics):
fw = codecs.open(ptb_fn, "w", "UTF-8")
try:
for smntcs in semantics:
smntcsWithoutText = removeTextFromSemantics(smntcs.semantics)
smntcsWithoutText = Semantics("id", smntcsWithoutText, "x")
try:
fw.write(smntcsWithoutText.getPTBSemantics() + "\n")
except ValueError:
fw.write("(TOP x)\n")
finally:
fw.close()
def writePTBFile(self, ptb_fn, semantics):
fw = codecs.open(ptb_fn, "w", "UTF-8")
try:
for smntcs in semantics:
smntcsWithoutText = removeTextFromSemantics(smntcs.semantics)
smntcsWithoutText = Semantics('id', smntcsWithoutText, 'x')
try:
fw.write(smntcsWithoutText.getPTBSemantics() + '\n')
except ValueError:
fw.write("(TOP x)\n")
finally:
fw.close()
def semantic_analysis(sym, sig, ast, device, errorlog):
"""
Perform semantic analysis on an AST.
"""
vmsg(v, "Performing semantic analysis")
sem = Semantics(sym, sig, device, errorlog)
sem.walk_program(ast)
# Check for any errors
if errorlog.any():
raise QuietError()
# Quit if we're only performing semantic analysis
if sem_only:
raise SystemExit()
return sem
def parse(cls, string):
"""Returns a Semantic object"""
string = string.replace(" ", "")
if "|" in string:
quant_str, string = string.split("|")
else:
quant_str, string = "", string
# Parse conjuncted relations
relations = []
while len(string) > 0:
relation, string = RelationParser.parse(string)
relations.append(relation)
sem = Semantics(relations)
# Parse any quantifiers
quantification_dict = QuantificationParser.parse(quant_str)
sem.quantification_dict = quantification_dict
return sem
def readSemantics(self, files, dataSets, parseType, origDataSet, txtInput=False, pdtDir=None, inputChain='none'):
if txtInput:
reader = input.MultiReader(files, input.TXTReader)
if 'lemma' in dataSets or 'pos' in dataSets:
if pdtDir is None:
raise ValueError("Couldn't find PDT-2.0, no directory supplied")
reader = input.PDTReader(pdtDir, reader, online=False)
else:
reader = input.MultiReader(files, input.DXMLReader)
reader = input.InputChain(inputChain, reader)
generator = input.InputGenerator(reader, dataSets, origDataSet)
for da_fn, da_id, da_semantics, da_txts in generator.readInputs():
s = [Semantics(da_id, da_semantics, ' '.join(txt), parseType) for txt in da_txts]
yield s
def fromxml(cls, vn_class, xml, frame_num):
"""Returns a Frame object from the VerbNet XML representation"""
primary = xml.find("DESCRIPTION").attrib.get("primary", "")
secondary = xml.find("DESCRIPTION").attrib.get("secondary", "")
sem_dict, reverse_lookup = Semantics.semdict_fromxml(xml.find("SEMANTICS"))
# Need the order of np vars given in syntax for mapping to subst nodes
nps = xml.find("SYNTAX").findall("NP")
np_order = [np.attrib["value"] for np in nps]
sem_vars = [v for s in sem_dict.values() for v in s.variables()]
np_var_order = []
for np in np_order:
match = [v for v in sem_vars if reverse_lookup[v].name == np]
if len(match) > 0 and not match[0].missing: # Ignore "?" variables
np_var_order.append(match[0])
example = xml.find("EXAMPLES").find("EXAMPLE").text.replace('"', '')
return Frame(vn_class, frame_num, primary, secondary, sem_dict, np_var_order, example)
def __init__(self, semantics=Semantics()):
self.semantics = semantics
def setUp(self):
self.semantics = Semantics()
class TestSemantics(TestCase):
def setUp(self):
self.semantics = Semantics()
def test_generate_sentence_with_keyword(self):
self.semantics._generate_sentence_with_keyworkd(['東京', 'とは'])
from sentence import Sentence
import config as config
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.DEBUG)
if __name__ == '__main__':
# update mimicry model tweet
twitter = Twitter(consumer_key=config.CONSUMER_KEY, consumer_secret=config.CONSUMER_SECRET,
access_token_key=config.ACCESS_TOKEN, access_token_secret=config.ACCESS_TOKEN_SECRET)
twitter.update_status(config.MIMICRY_MODEL)
# setup natural language recognition env.
message = twitter.get_latest_status_text(config.MIMICRY_MODEL)
if message is None:
logging.error("Mimicry target's tweet is None.")
exit()
semantics = Semantics()
similar_words = semantics.get_similar_words(message)
train_posts = twitter.get_all_status_text()
sentence = Sentence()
sentence.learn(train_posts)
generated_message = sentence.generate(similar_words)
twitter.post(generated_message)
