def findMissingSenses(): for k,v in Senses.items(): for pos,senseList in v.items(): for s in senseList: try: if pos!='see': pywordnet.getSense(k,pos,s-1) except (KeyError,TypeError),err: # Inflected form logger.errror('Trying inflected form b/c of Error %s',err) logger.error('%s',pywordnet.getSense(s[0],pos,s[1][0]-1)) except: logger.error('Cannot find %s, %s, %s', k,pos,s)
def findMissingSenses(): for k, v in Senses.items(): for pos, senseList in v.items(): for s in senseList: try: if pos != "see": pywordnet.getSense(k, pos, s - 1) except (KeyError, TypeError), err: # Inflected form logger.errror("Trying inflected form b/c of Error %s", err) logger.error("%s", pywordnet.getSense(s[0], pos, s[1][0] - 1)) except: logger.error("Cannot find %s, %s, %s", k, pos, s)
def __init__(self, tofPinArray): i2c = busio.I2C(board.SCL, board.SDA) self.senses = Senses(tofPinArray, i2c) motors = MotorKit(i2c=i2c) self.motorL = motors.motor4 self.motorR = motors.motor1 self.moveState = "stationary" self.initDof() self.targetHeading = self.angle # Trim use to have direction like {direction: "right", size: 0} # However, for now, I know that the right motor is more powerful than the left, # and will just always apply the trim as a negative on the right throttle. It # makes it easier when the trim has overcorrect to only worry about one. # Open to other ideas though (looking at you Greg) self.trim = 0
from nltk.tree import Tree from nltk.stemmer.porter import PorterStemmer from nltk.featurestructure import FeatureStructure from nltk_contrib import pywordnet import enchant from Senses import Senses, Senses2, Senses3 from DirectionCorpus import printDirs,constructItemRegexp,DirectionCorpusReader,saveParse from Options import Options from Utility import logger, lstail pywordnet.setCacheCapacity(100) Lexicon = 'Directions/Lexicon2.lex' Corpus2 = True if Corpus2: Senses.update(Senses2) Corpus3 = True if Corpus3: Senses.update(Senses3) class ProximateSensesRule(ProximateTokensRule): PROPERTY_NAME = 'sense' # for printing. TAG='SENSE' def extract_property(token): # [staticmethod] """@return: The given token's C{SENSE} property.""" return token['SENSE'] extract_property = staticmethod(extract_property) class ProximateStemsRule(ProximateTokensRule): PROPERTY_NAME = 'stem' # for printing. TAG='STEM' def extract_property(token): # [staticmethod]
from nltk.stemmer.porter import PorterStemmer from nltk.featurestructure import FeatureStructure from nltk_contrib import pywordnet import enchant from Senses import Senses, Senses2, Senses3 from DirectionCorpus import printDirs, constructItemRegexp, DirectionCorpusReader, saveParse from Options import Options from Utility import logger, lstail pywordnet.setCacheCapacity(100) Lexicon = "Directions/Lexicon2.lex" Corpus2 = True if Corpus2: Senses.update(Senses2) Corpus3 = True if Corpus3: Senses.update(Senses3) class ProximateSensesRule(ProximateTokensRule): PROPERTY_NAME = "sense" # for printing. TAG = "SENSE" def extract_property(token): # [staticmethod] """@return: The given token's C{SENSE} property.""" return token["SENSE"] extract_property = staticmethod(extract_property)