def unparsed(words):
out = []
for actuaword in words:
if any(letter in actuaword for letter in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'):
werd = word.loanword(actuaword)
else:
werd = word.rootword(actuaword)
out.append(phrase.phrase(werd))
return out
def unparsed(words): out = [] for actuaword in words: if any(letter in actuaword for letter in 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'): werd = word.loanword(actuaword) else: werd = word.rootword(actuaword) out.append(phrase.phrase(werd)) return out
def attempt(sentence, i):
part = sentence[i].part
if (i < len(sentence) - 1) & (i >= 0):
post = sentence[i + 1].part
if (post == 'cj'):
sentence[i - 1].part = ':cj' + part
return True
if (part == 'dn'):
if post[:3] == ':dn':
kind = post[3:]
else:
kind = post
sentence[i].part = ':dn' + kind
return True
if (part not in ['dn', ':dnn']) & (post == 'ed'):
sentence.insert(i + 1, phrase.phrase(dummy))
return True
if part[:3] == ':dn':
return False
if (i < len(sentence) - 1) & (i >= 1):
pre = sentence[i - 1].part
post = sentence[i + 1].part
if (pre == 'pr') & (part == 'n'):
if (post[:3] == ':dn') and\
(describes(part,post[3:])):
sentence[i - 1].desc.append(sentence.pop(i))
sentence.pop(i)
return True
if not describes('n', post):
sentence[i - 1].desc.append(sentence.pop(i))
sentence[i - 1].part = 'av'
return True
if (describes(pre, part)):
if (post[:3] == ':dn') and\
(describes(part,post[3:])):
sentence[i - 1].desc.append(sentence.pop(i))
sentence.pop(i)
return True
if (not describes(part, post)):
sentence[i - 1].desc.append(sentence.pop(i))
return True
return False
def attempt(sentence,i):
part = sentence[i].part
if (i < len(sentence)-1) & (i >= 0):
post = sentence[i+1].part
if (post == 'cj'):
sentence[i-1].part = ':cj'+part
return True
if (part == 'dn'):
if post[:3] == ':dn':
kind = post[3:]
else:
kind = post
sentence[i].part = ':dn' + kind
return True
if (part not in ['dn',':dnn']) & (post == 'ed'):
sentence.insert(i+1,phrase.phrase(dummy))
return True
if part[:3] == ':dn':
return False
if (i < len(sentence)-1) & (i >= 1):
pre = sentence[i-1].part
post = sentence[i+1].part
if (pre == 'pr') & (part == 'n'):
if (post[:3] == ':dn') and\
(describes(part,post[3:])):
sentence[i-1].desc.append(sentence.pop(i))
sentence.pop(i)
return True
if not describes('n',post):
sentence[i-1].desc.append(sentence.pop(i))
sentence[i-1].part = 'av'
return True
if (describes(pre,part)):
if (post[:3] == ':dn') and\
(describes(part,post[3:])):
sentence[i-1].desc.append(sentence.pop(i))
sentence.pop(i)
return True
if (not describes(part,post)):
sentence[i-1].desc.append(sentence.pop(i))
return True
return False
"il campanello/doorbell",
"la serratura/lock",
"la maniglia/handle",
"l'ascensore/lift",
"il piano/floor level",
"il pavimento/floor",
"il soffitto/ceiling",
"il caminetto/fireplace",
"la tappezzeria/wallpaper"
]
house_verbs = ["affitare/rent", "abitare/live"]
q1 = 20*[ phrase.noun_phrase(rooms+house_parts,kind=['sd','sd','si','pd']) ]+\
[ phrase.phrase(["affitare/rent","possedere/own"],person=persons,tempus='present',dobj=houses),
phrase.phrase("abitare/live",person=persons,tempus='present',iobj=phrase.prep_phrase(prep='in',noun=houses) )]
systems = [
"il calorifero/radiator", "lo scaldaacqua/bolier", "l'acquaio/sink",
"il rubinetto/tap", "la leva/lever", "lo scolo/drain", "il tappo/plug",
"la vasca/bathtub", "la doccia/shower", "il lavandino/sink",
"il water/water closet", "la lampadina/light bulb", "la presa/socket",
"l'interruttore/switch", "l'elettricità/electricity", "la spina/plug",
"il filo/wire", "il tubo/pipe"
]
furniture = [
"il quadro/painting", "la lampada/lamp", "lo specchio/mirror",
"il vaso/vase", "il divano/sofa", "la tenda/curtain",
"la veneziana/venetian blind", "il tavolino/coffee table",
#adjective
adjs = [
"cortese/polite", "scortese|rozzo/rude", "amichevole/friendly",
"ostile/hostile", "popolare/popular", "famoso/famous", "infame/infamous",
"importante/important", "timido/shy", "loquace|ciarliero/talkative",
"solitario/lonely", "solo/alone", "simpatico|gentile/nice",
"occupato/busy", "fidato/reliable", "imparentato/related"
]
#verb.eng_verbs['raise'] = {'imperfect':'rose', 'perfect': 'risen' }
persons = ['1s', '2s', '3sm', '3sf', '1p', '2p', '3pm', '3pf']
subjv_q = phrase.phrase(subj_verbs,person=persons,tempus=['present','perfect'],\
post=[phrase.phrase(['parlare','lavorare/work',"combattere/fight","rispondere/answer","ubbidire/obey","mentire|dire_bugie/lie(false)"],\
conj='che',subject=other_people,tempus='subjunctive present'),
phrase.phrase(['parlare','lavorare/work',"combattere/fight","rispondere/answer","ubbidire/obey","mentire|dire_bugie/lie(false)"],\
conj='che',person=persons,tempus='subjunctive present')])
intransv_q= phrase.phrase(intrans_verbs,subject=relatives,\
tempus=['present','perfect','future','conditional','imperfect'])
pluralv_q= phrase.phrase(plural_verbs,person=['1p','2p','3p'],\
tempus=['present','perfect','future','conditional','imperfect'])
transv_q=phrase.phrase(trans_verbs,tempus=['present','perfect','future','conditional','imperfect'],\
person=persons,dobj=relatives)
specialv_q =\
[phrase.phrase("raccontare/tell",tempus=['present','perfect','future','conditional','imperfect'],
def dictate():
# load
loader = Loader.loader()
res = loader.load_phrase()
if res == -1:
print('短语表为空！')
exit()
zh, en = res
test, right = loader.load_record()
# generate
phrz_lst = []
for i in range(len(zh)):
phrz = phrase.phrase(zh[i], en[i], test[i], right[i], i)
phrz_lst.append(phrz)
random.shuffle(phrz_lst)
phrz_lst = sorted(phrz_lst, key=phrase.custom_key, reverse=True)
print("输入要测试的词组数量：\033[34m")
try:
lines = int(input())
while not (lines > 0 and lines < len(zh) + 1):
print("\033[37m输入范围内数字！")
print("输入要测试的词组数量：\033[34m")
lines = int(input())
phrz_lst = phrz_lst[:lines]
random.shuffle(phrz_lst)
print("\n\033[32m--start--\033[37m")
cnt = 0
wrong = []
ans = []
for i in phrz_lst:
print("\n\033[0m%s\033[34m" % (i.zh))
answer = input().rstrip()
if not i.is_true(answer):
cnt += 1
wrong.append(i)
ans.append(answer)
print("\n\033[32m--end--\033[37m")
grade = 100 * (1 - cnt / lines)
print("\n\033[37m最终成绩：\033[32m %.2f" % grade)
if not len(wrong) == 0:
print("\033[31m错误：")
for i in range(len(wrong)):
print("\033[37m%s\t\033[32m%s" % (wrong[i].zh, wrong[i].en))
print("\033[37mYour answer:\t\033[31m", ans[i])
print('\033[0m')
for i in phrz_lst:
test[i.id] = i.test
right[i.id] = i.right
loader.store_record(test, right)
except ValueError:
print("\033[37m输入数字！")
except KeyboardInterrupt:
print('\n\033[34mBye~')
if __name__ == "__main__":
# initialize weight for running average
aWeight = 0.5
# get the reference to the webcam
camera = cv2.VideoCapture(camera)
# region of interest (ROI) coordinates
top, right, bottom, left = 100, 250, 300, 450
# initialize num of frames
num_frames = 0
# keep looping, until interrupted
sentence = phrase()
while (True):
# get the current frame
(grabbed, frame) = camera.read()
# resize the frame
frame = cv2.resize(frame, (700, 700))
# flip the frame so that it is not the mirror view
viewFrame = cv2.flip(frame, 1)
# clone the frame
clone = frame.copy()
# get the height and width of the frame
f"Welcome {const.PLAYERS[0].name}, {const.PLAYERS[1].name}, {const.PLAYERS[2].name}!"
)
return const.PLAYERS
def start_game(player_list: list, phrase: str):
wheel_img_folder_path = os.path.join(__location__, const.IMG_FOLDER,
const.IMG_BASE_NAME)
#Call game constructor and pass the phrase for game instance variable
ready = game(phrase)
#Load up wheel image
w = wheel(wheel_img_folder_path)
#Shows wheel image and pointer
w.start()
#Words constructor
wor = words(phrase)
#Print out blank words
wor.start(w)
#Call start_wof from game object
ready.start_wof(player_list, w, wor)
if __name__ == "__main__":
#List of players
players = start()
p = phrase()
#Get phrase from phile
phrase = p.random(os.path.join(__location__, 'WofFPhrases.txt'))
#Go to start game function
start_game(players, phrase)
def keywords(self, NE, Gram, Col, Chunk, log):
'''
This selects the most likly keyterms from potential candidates
passed in.
@param NE: list of pos tagged Named Entities
@param Gram: list of pos tagged n-grams
@param Col: list of pos tagged collocations
@param Chunk: list of pos tagged chunks
@param log: loglikly hood directory passed
@return: selected keywords.
'''
self.log = log
master = []
fdist = FreqDist()
for word in Gram + NE + Col + Chunk:
if word:
fdist.inc(tuple(word))
for key in fdist.keys():
if fdist[key] > 1:
master.append(list(key))
input = filter(None, Gram + NE + Col + Chunk)
tmplist = []
phrasearray = []
#Strips phrases which have stop words within them.
for grams in input:
boolean = False
for word in grams:
if word[0].lower() in self.stopwords:
boolean = True
if grams[0][0] == "The":
boolean = False
#If capital The at end of phrase then remove it form the word.
if grams[-1][0] == "The":
tmp = []
for tupple in grams[:-1]:
tmp.append(tupple)
grams = tuple(tmp)
if (self.all_same(grams) == True) & (len(grams) > 1):
boolean = True
if boolean == False:
tmplist.append(grams)
#parses the list into phrase objects
for w in tmplist:
phrasearray.append(phrase(w, tmplist, self.log))
#Retrives there intercepts for each word.
intercepts = []
for a in phrasearray:
b = a.getSet()
if b:
intercepts.append(list(b))
oneword = []
for w in phrasearray:
if w.getNumberCapitals() >= (w.getLength()):
oneword.append(w.getPhrase())
ma = self.duplicates(oneword + intercepts)
master = self.du(ma)
master = self.lookforjoins(master)
tmp1 = []
for grams in master:
tmp = []
avrage = 0
i = 0
for words in grams:
tmp.append(words[0])
try:
avrage = avrage + log[words[0].lower()]
except:
avrage = avrage + 0
i = i + 1
try:
avrage = avrage / i
except:
avrage = 0
tmp.append(avrage)
tmp1.append(tmp)
tmp3 = self.bubbleSort(tmp1)
tmp1 = []
for grams in tmp3:
tmp1.append(' '.join(grams[0:-1]))
#The number of items which is the x%
x = int(
round(float(float(float(len(tmp1)) / float(100)) *
self.percentil)))
return tmp1[-x:]
def keywords(self, NE, Gram, Col, Chunk, log):
'''
This selects the most likly keyterms from potential candidates
passed in.
@param NE: list of pos tagged Named Entities
@param Gram: list of pos tagged n-grams
@param Col: list of pos tagged collocations
@param Chunk: list of pos tagged chunks
@param log: loglikly hood directory passed
@return: selected keywords.
'''
self.log = log
master = []
fdist = FreqDist()
for word in Gram + NE + Col + Chunk:
if word:
fdist.inc(tuple(word))
for key in fdist.keys():
if fdist[key] > 1:
master.append(list(key))
input = filter(None, Gram + NE + Col + Chunk)
tmplist = []
phrasearray = []
#Strips phrases which have stop words within them.
for grams in input:
boolean = False
for word in grams:
if word[0].lower() in self.stopwords:
boolean = True
if grams[0][0] == "The":
boolean = False
#If capital The at end of phrase then remove it form the word.
if grams[-1][0] == "The":
tmp = []
for tupple in grams[:-1]:
tmp.append(tupple)
grams = tuple(tmp)
if (self.all_same(grams) == True) & (len(grams) > 1):
boolean = True
if boolean == False:
tmplist.append(grams)
#parses the list into phrase objects
for w in tmplist:
phrasearray.append(phrase(w, tmplist, self.log))
#Retrives there intercepts for each word.
intercepts = []
for a in phrasearray:
b = a.getSet()
if b:
intercepts.append(list(b))
oneword = []
for w in phrasearray:
if w.getNumberCapitals() >= (w.getLength()):
oneword.append(w.getPhrase())
ma = self.duplicates(oneword + intercepts)
master = self.du(ma)
master = self.lookforjoins(master)
tmp1 = []
for grams in master:
tmp = []
avrage = 0
i = 0
for words in grams:
tmp.append(words[0])
try:
avrage = avrage + log[words[0].lower()]
except:
avrage = avrage + 0
i = i + 1
try:
avrage = avrage / i
except:
avrage = 0
tmp.append(avrage)
tmp1.append(tmp)
tmp3 = self.bubbleSort(tmp1)
tmp1 = []
for grams in tmp3:
tmp1.append(' '.join(grams[0:-1]))
#The number of items which is the x%
x = int(round(float(float(float(len(tmp1))/float(100))*self.percentil)))
return tmp1[-x:]
