def rkick(word, word_eol, userdata):
#try:
reason = select((
'Goodbye!','See you later.','Cya.','Bye.','Later!',
'Kindergarden is elsewhere!','Ugh. BYE!','G\'day',
'Seeya later!','Be gone!','This is awkward. Bye.',
'I didn\'t do it!'
))
if len(word) == 2:
# Assume they supplied a username
return xchat.command('kick %s %s' % (word[1], reason))
elif len(word) == 1:
# Assume they want a random user
list = xchat.get_list("users")
if not list:
return xchat.prnt(help)
user = select((list))
return xchat.command('kick %s %s' % (user.nick, reason))
else:
# Assume they entered some weird stuff
return xchat.prnt(help)
#except:
# xchat.prnt(help)
return xchat.EAT_ALL
def define_action(act_a, ac, phrase):
action = act_a
selection = select(players)
if action == ac:
killer = select(players)
while killer == selection:
killer = select(players)
print(phrase.replace("$k", killer).replace("$s", selection), end = ' ')
async def steal(self, ctx, *, message):
"""Steal something! Be careful not to get caught..."""
possibleactions = ["steal", "steal", "getcaught"]
action = select(possibleactions)
if action == "steal":
message = "You successfully stole " + message + "!"
elif action == "getcaught":
punishments = ["fine", "comserv", "prison", "serverban"]
punishment = select(punishments)
if punishment == "fine":
fines = [
"10", "50", "100", "250", "500", "1000", "2500", "5000",
"10000", "25000", "50000", "100000", "250000", "500000"
]
amount = select(fines)
message = "You got caught! Your punishment is a fine of $" + amount + "!"
elif punishment == "comserv":
possiblehours = [
"50", "100", "250", "500", "1000", "2500", "5000"
]
hours = select(possiblehours)
message = "You got caught! Your punishment is " + hours + " hours of community service!"
elif punishment == "prison":
possibleyears = [
"1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11",
"12", "13", "14", "15", "16", "17", "18", "19", "20", "21",
"22", "23", "24", "25"
]
years = select(possibleyears)
message = "You got caught! Your punishment is " + years + " years in prison!"
elif punishment == "serverban":
units = ["d", "w", "m", "i"]
unit = select(units)
if unit == "d":
possibledays = ["1", "2", "3", "4", "5", "6", "7"]
days = select(possibledays)
message = "You got caught! Your punishment is a ban from this server for " + days + " days!\n*Note: This is only a joke, you won't actually get banned.*"
elif unit == "w":
possibleweeks = ["1", "2", "3", "4"]
weeks = select(possibleweeks)
message = "You got caught! Your punishment is a ban from this server for " + weeks + " weeks!\n*Note: This is only a joke, you won't actually get banned.*"
elif unit == "m":
possiblemonths = [
"1", "2", "3", "4", "5", "6", "7", "8", "9", "10",
"11", "12"
]
months = select(possiblemonths)
message = "You got caught! Your punishment is a ban from this server for " + months + " months!\n*Note: This is only a joke, you won't actually get banned.*"
elif unit == "i":
message = "You got caught! Your punishment is a permanent ban from this server!\n*Note: This is only a joke, you won't actually get banned.*"
await ctx.send(
message.replace("@everyone",
"@.everyone").replace("@here", "@.here"))
async def yes(self, ctx, *, message):
"""Similar to echo, but repeats the output several times."""
loopcount = select(1,10)
final = message
for i in range(1,loopcount):
final = final + "\n" + message
await ctx.send(final.replace("@everyone", "@\u200beveryone").replace("@here", "@\u200bhere"))
def define_gun(zgun_a, ac, gun):
if rint(1, 10) != 5:
action = zgun_a
selection = select(players)
if action == ac:
killer = select(players)
while killer == selection:
killer = select(players)
print(killer + ' killed ' + selection + " with a", gun, end = ' ')
players.remove(selection)
else:
action = gun_a
selection = select(players)
if action == ac:
print(selection + " commited suicide with a", gun, end = ' ')
players.remove(selection)
def dostuff(samplertt,counter,congwin): ring = select([0.25,0.5,0.75,1]) temp = 0 if ring == 0.25: temp = formalize(1.85*samplertt[-1]) samplertt.append(temp) counter += 1 elif ring == 0.5: temp = formalize(0.65*samplertt[-1]) samplertt.append(temp) counter += 1 elif ring == 0.75: temp2 = formalize(1.6*samplertt[-1]) samplertt.append(temp2) counter += 1 if counter+1 <200: temp3 = formalize(0.7*samplertt[-1]) samplertt.append(temp3) counter += 1 coin = bell(0,1) probability = 0.6*(1-exp(-congwin/25.0)) if (coin - probability)<=0: state = False congwin = congevo(congwin,state) #here we have segment loss else: state = True congwin = congevo(congwin,state) #here we pass it else: samplertt,counter = normalestimation(samplertt,counter) return samplertt,counter,congwin
def hug(word, word_eol, userdata):
response = select((
'a nice warm hug','a nice warm cuddle','a bear hug',
'a snuggly hug','a huge hug','a hug','a small hug',
'a weird hug','an awkward hug'
))
try:
xchat.command('me gives \x02%s\x02 %s' % (word[1], response))
except:
xchat.prnt(help)
return xchat.EAT_ALL
def meme_callback(message):
tmp = yield from client.send_message(message.channel, "Getting memes")
headerData = {"User-Agent": "Part of a discord bot", "From": "CUB3D"}
redditResponce = requests.get("http://reddit.com/r/dankmemes/hot.json", headerData)
json = redditResponce.json()
if "error" in json:
if int(json["error"]) == 429:
print("Too many requests")
yield from client.edit_message(tmp, "Error: Too dank, much request (try again later)")
return
children = json["data"]["children"]
selected = select(children)
url = selected["data"]["url"]
print("Image URL:", url)
yield from client.edit_message(tmp, str(url))
def dostuff(samplertt,counter): ring = select([0.25,0.5,0.75,1]) temp = 0 if ring == 0.25: temp = formalize(1.85*samplertt[-1]) samplertt.append(temp) counter += 1 elif ring == 0.5: temp = formalize(0.65*samplertt[-1]) samplertt.append(temp) counter += 1 elif ring == 0.75: temp2 = formalize(1.6*samplertt[-1]) samplertt.append(temp2) counter += 1 if counter+1 <200: temp3 = formalize(0.7*samplertt[-1]) samplertt.append(temp3) counter += 1 else: samplertt,counter = normalestimation(samplertt,counter) return samplertt,counter
def switch_quiz(self, quiz_filer=None):
"""
Set the Userinterface to test a different Quiz (represented by a
Quiz_Filer object or randomly selected).
"""
# disconnect old listeners #
quiz_filer.quiz.disconnect('question_changed', self.update_gui)
quiz_filer.quiz.disconnect('break_time', self.start_relax_time)
# replace #
if quiz_filer == None:
quiz_filer = random.select(self.quiz_filer_list)
self.quiz_filer = quiz_filer
self.quiz = quiz_filer.quiz
self.update_gui()
# show and hide notebookpanels #
if not quiz_filer.type in self.SHOW_TABS:
print _('Warning: unknown quiz type "%s".') % quiz_filer.type
type = "all"
else:
type = self.quiz_filer.type
for tab, visi in zip(self.main_notbook_tabs.itervalues(),
self.SHOW_TABS[type]):
for widget in tab: # tab is tab-label + tab-content
if visi:
widget.show()
else:
widget.hide()
# show, hide and settext of combobox #
if quiz_filer.all_subquizzes == []:
self.subquiz_combobox.hide()
else:
for i in range(2): # dirty clear combobox
self.subquiz_combobox.remove_text(0)
for subquiz in quiz_filer.all_subquizzes:
self.subquiz_combobox.append_text(subquiz)
self.subquiz_combobox.set_active(self.quiz.ask_from)
self.subquiz_combobox.show()
#
for label in self.question_topic_labels:
label.set_markup("<b>%s</b>" %
quiz_filer.question_topic[self.quiz.ask_from])
# treeview #
## Question/Answer-Columns ##
for column in self.word_treeview.get_columns():
self.word_treeview.remove_column(column)
for i, title in enumerate(quiz_filer.data_name):
tvcolumn = gtk.TreeViewColumn(title,
gtk.CellRendererText(),
text=i)
self.word_treeview.append_column(tvcolumn)
## toggler ##
toggler = gtk.CellRendererToggle()
toggler.connect('toggled', self.on_treeview_toogled)
tvcolumn = gtk.TreeViewColumn(_("test"), toggler)
tvcolumn.add_attribute(toggler, "active", 2)
self.word_treeview.append_column(tvcolumn)
self.word_treeview.set_model(quiz_filer.treestore)
# clean statusbar #
self.statusbar1.pop(self.statusbar_contextid["last_answer"])
# connect listeners #
quiz_filer.quiz.connect('question_changed', self.update_gui)
quiz_filer.quiz.connect('break_time', self.start_relax_time)
print 'decision tree prediction: ' + str(d_tree)
#print '\tprob:' + str(fit_dtree.predict_proba(test_X))
print 'KNN prediciton: ' + str(knn)
#print '\tprob:' + str(fit_neigh.predict_proba(test_X))
#print OvO
print 'One vs.Rest prediction: ' + str(OvR)
#print '\tprob:' + str(fit_OvR.predict_proba(test_X))
if OvR == knn:
guess = OvR
else:
guess = d_tree
if str(guess) == 'test':
y_copy = list(y_words)
while 'test' in y_words:
y_copy.remove('test')
guess = random.select(y_copy)
os.system('espeak ' + str(guess) + ' &> /dev/null')
print 'best guess: ' + str(guess)
else:
print 'Letters excluded...'
OneVone = OneVsOneClassifier(LinearSVC(random_state=0))
OneVrest = OneVsRestClassifier(RandomForestClassifier(random_state=0))
DTree = DecisionTreeClassifier(random_state=0)
neigh = KNeighborsClassifier(n_neighbors=3)
fit_dtree = DTree.fit(train_X_words, y_words)
fit_neigh = neigh.fit(train_X_words, y_words)
OvR = " "
#fit_OvO = OneVone.fit(train_X_words, y_words)
try:
fit_OvR = OneVrest.fit(train_X_words, y_words)
OvR = fit_OvR.predict(test_X)
def __getitem__(self, idx):
if type( self.augmentation) is str and 'affine' in self.augmentation:
strech = (self.max_strech*2)*np.random.random() - self.max_strech +1
#self.max_rot_rad = self.max_rot_deg/180 * np.pi
skew = (self.max_rot_rad*2)*np.random.random() - self.max_rot_rad
if self.include_stroke_aug:
thickness_change= np.random.randint(-4,5)
fg_shade = np.random.random()*0.25 + 0.75
bg_shade = np.random.random()*0.2
blur_size = np.random.randint(2,4)
noise_sigma = np.random.random()*0.02
batch=[]
if self.triplet=='hard':
authors = random.sample(self.authors.keys(),self.triplet_author_size)
alines=[]
for author in authors:
if len(self.authors[author])>=self.triplet_sample_size*self.batch_size:
lines = random.sample(range(len(self.authors[author])),self.triplet_sample_size*self.batch_size)
else:
lines = list(range(len(self.authors[author])))
random.shuffle(lines)
dif = self.triplet_sample_size*self.batch_size-len(self.authors[author])
lines += lines[:dif]
alines += [(author,l) for l in lines]
else:
inst = self.lineIndex[idx]
author=inst[0]
lines=inst[1]
alines = [(author,l) for l in lines]
used_lines = set(lines)
if self.triplet:
if len(self.authors[author])<=2*self.batch_size:
for l in range(len(self.authors[author])):
if l not in used_lines:
alines.append((author,l))
if len(alines)<2*self.batch_size:
dif = 2*self.batch_size - len(alines)
for i in range(dif):
alines.append(alines[self.batch_size+i])
else:
unused_lines = set(range(len(self.authors[author])))-used_lines
for i in range(self.batch_size):
l = random.select(unused_lines)
unused_lines.remove(l)
alines.append((author,l))
other_authors = set(range(len(self.authors)))
other_authors.remove(author)
author = random.select(other_authors)
unused_lines = set(range(len(self.authors[author])))-used_lines
for i in range(self.batch_size):
l = random.select(unused_lines)
unused_lines.remove(l)
alines.append((author,l))
images=[]
for author,line in alines:
if line>=len(self.authors[author]):
line = (line+37)%len(self.authors[author])
img_path, lb, gt = self.authors[author][line]
img_path = os.path.join(self.dirPath,'images_gray',img_path)
if self.no_spaces:
gt = gt.replace(' ','')
if type(self.augmentation) is str and 'normalization' in self.augmentation and self.normalized_dir is not None and os.path.exists(os.path.join(self.normalized_dir,'{}_{}.png'.format(author,line))):
img = cv2.imread(os.path.join(self.normalized_dir,'{}_{}.png'.format(author,line)),0)
readNorm=True
else:
img = cv2.imread(img_path,0)
if img is None:
print('Error, could not read image: {}'.format(img_path))
return None
lb[0] = max(lb[0],0)
lb[2] = max(lb[2],0)
lb[1] = min(lb[1],img.shape[0])
lb[3] = min(lb[3],img.shape[1])
img = img[lb[0]:lb[1],lb[2]:lb[3]] #read as grayscale, crop line
readNorm=False
if img.shape[0] != self.img_height:
if img.shape[0] < self.img_height and not self.warning:
self.warning = True
print("WARNING: upsampling image to fit size")
percent = float(self.img_height) / img.shape[0]
if img.shape[1]*percent > self.max_width:
percent = self.max_width/img.shape[1]
img = cv2.resize(img, (0,0), fx=percent, fy=percent, interpolation = cv2.INTER_CUBIC)
if img.shape[0]<self.img_height:
diff = self.img_height-img.shape[0]
img = np.pad(img,((diff//2,diff//2+diff%2),(0,0)),'constant',constant_values=255)
elif img.shape[1]> self.max_width:
percent = self.max_width/img.shape[1]
img = cv2.resize(img, (0,0), fx=percent, fy=percent, interpolation = cv2.INTER_CUBIC)
if img.shape[0]<self.img_height:
diff = self.img_height-img.shape[0]
img = np.pad(img,((diff//2,diff//2+diff%2),(0,0)),'constant',constant_values=255)
if self.augmentation=='affine':
if img.shape[1]*strech > self.max_width:
strech = self.max_width/img.shape[1]
images.append( (line,gt,img,author) )
#we split the processing here so that strech will be adjusted for longest image in author batch
for line,gt,img,author in images:
if self.fg_masks_dir is not None:
fg_path = os.path.join(self.fg_masks_dir,'{}_{}.png'.format(author,line))
fg_mask = cv2.imread(fg_path,0)
fg_mask = fg_mask/255
if fg_mask.shape!=img[:,:].shape:
print('Error, fg_mask ({}, {}) not the same size as image ({})'.format(fg_path,fg_mask.shape,img[:,:,0].shape))
th,fg_mask = cv2.threshold(img,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
fg_mask = 255-fg_mask
ele = cv2.getStructuringElement( cv2.MORPH_ELLIPSE, (9,9) )
fg_mask = cv2.dilate(fg_mask,ele)
fg_mask = fg_mask/255
else:
fg_mask=None
if type(self.augmentation) is str and 'normalization' in self.augmentation and not readNorm:
img = normalize_line.deskew(img)
img = normalize_line.skeletonize(img)
if self.normalized_dir is not None:
cv2.imwrite(os.path.join(self.normalized_dir,'{}_{}.png'.format(author,line)),img)
if type(self.augmentation) is str and 'affine' in self.augmentation:
img,fg_mask = augmentation.affine_trans(img,fg_mask,skew,strech)
elif self.augmentation is not None and (type(self.augmentation) is not None or 'warp' in self.augmentation):
#img = augmentation.apply_random_color_rotation(img)
img = augmentation.apply_tensmeyer_brightness(img)
img = grid_distortion.warp_image(img)
assert(fg_mask is None)
if self.include_stroke_aug:
new_img = augmentation.change_thickness(img,thickness_change,fg_shade,bg_shade,blur_size,noise_sigma)
if len(new_img.shape)==2:
new_img = new_img[...,None]
new_img = new_img*2 -1.0
if len(img.shape)==2:
img = img[...,None]
img = img.astype(np.float32)
if self.remove_bg:
img = 1.0 - img / 256.0
#kernel = torch.FloatTensor(7,7).fill_(1/49)
#blurred_mask = F.conv2d(fg_mask,kernel,padding=3)
blurred_mask = cv2.blur(fg_mask,(7,7))
img *= blurred_mask[...,None]
img = 2*img -1
else:
img = 1.0 - img / 128.0
if len(gt) == 0:
return None
gt_label = string_utils.str2label_single(gt, self.char_to_idx)
if self.styles:
style_i = self.npr.choice(len(self.styles[author][id]))
style = self.styles[author][id][style_i]
else:
style=None
name = '{}_{}'.format(author,line)
if self.identity_spaced:
spaced_label = gt_label[:,None].astype(np.long)
else:
spaced_label = None if self.spaced_by_name is None else self.spaced_by_name[name]
if spaced_label is not None:
assert(spaced_label.shape[1]==1)
toAppend= {
"image": img,
"gt": gt,
"style": style,
"gt_label": gt_label,
"spaced_label": spaced_label,
"name": name,
"center": self.center,
"author": author,
"author_idx": self.author_list.index(author)
}
if self.fg_masks_dir is not None:
toAppend['fg_mask'] = fg_mask
if self.include_stroke_aug:
toAppend['changed_image'] = new_img
batch.append(toAppend)
#batch = [b for b in batch if b is not None]
#These all should be the same size or error
assert len(set([b['image'].shape[0] for b in batch])) == 1
assert len(set([b['image'].shape[2] for b in batch])) == 1
dim0 = batch[0]['image'].shape[0]
dim1 = max([b['image'].shape[1] for b in batch])
dim2 = batch[0]['image'].shape[2]
all_labels = []
label_lengths = []
if self.spaced_by_name is not None or self.identity_spaced:
spaced_labels = []
else:
spaced_labels = None
max_spaced_len=0
input_batch = np.full((len(batch), dim0, dim1, dim2), PADDING_CONSTANT).astype(np.float32)
if self.fg_masks_dir is not None:
fg_masks = np.full((len(batch), dim0, dim1, 1), 0).astype(np.float32)
if self.include_stroke_aug:
changed_batch = np.full((len(batch), dim0, dim1, dim2), PADDING_CONSTANT).astype(np.float32)
for i in range(len(batch)):
b_img = batch[i]['image']
toPad = (dim1-b_img.shape[1])
if 'center' in batch[0] and batch[0]['center']:
toPad //=2
else:
toPad = 0
input_batch[i,:,toPad:toPad+b_img.shape[1],:] = b_img
if self.fg_masks_dir is not None:
fg_masks[i,:,toPad:toPad+b_img.shape[1],0] = batch[i]['fg_mask']
if self.include_stroke_aug:
changed_batch[i,:,toPad:toPad+b_img.shape[1],:] = batch[i]['changed_image']
l = batch[i]['gt_label']
all_labels.append(l)
label_lengths.append(len(l))
if spaced_labels is not None:
sl = batch[i]['spaced_label']
spaced_labels.append(sl)
max_spaced_len = max(max_spaced_len,sl.shape[0])
#all_labels = np.concatenate(all_labels)
label_lengths = torch.IntTensor(label_lengths)
max_len = label_lengths.max()
all_labels = [np.pad(l,((0,max_len-l.shape[0]),),'constant') for l in all_labels]
all_labels = np.stack(all_labels,axis=1)
if self.spaced_by_name is not None or self.identity_spaced:
spaced_labels = [np.pad(l,((0,max_spaced_len-l.shape[0]),(0,0)),'constant') for l in spaced_labels]
ddd = spaced_labels
spaced_labels = np.concatenate(spaced_labels,axis=1)
spaced_labels = torch.from_numpy(spaced_labels)
assert(spaced_labels.size(1) == len(batch))
images = input_batch.transpose([0,3,1,2])
images = torch.from_numpy(images)
labels = torch.from_numpy(all_labels.astype(np.int32))
#label_lengths = torch.from_numpy(label_lengths.astype(np.int32))
if self.fg_masks_dir is not None:
fg_masks = fg_masks.transpose([0,3,1,2])
fg_masks = torch.from_numpy(fg_masks)
if batch[0]['style'] is not None:
styles = np.stack([b['style'] for b in batch], axis=0)
styles = torch.from_numpy(styles).float()
else:
styles=None
mask, top_and_bottom, center_line = makeMask(images,self.mask_post, self.mask_random)
##DEBUG
#for i in range(5):
# mask2, top_and_bottom2 = makeMask(images,self.mask_post, self.mask_random)
# #extra_masks.append(mask2)
# mask2 = ((mask2[0,0]+1)/2).numpy().astype(np.uint8)*255
# cv2.imshow('mask{}'.format(i),mask2)
#mask = ((mask[0,0]+1)/2).numpy().astype(np.uint8)*255
#cv2.imshow('mask'.format(i),mask)
#cv2.waitKey()
toRet= {
"image": images,
"mask": mask,
"top_and_bottom": top_and_bottom,
"center_line": center_line,
"label": labels,
"style": styles,
"label_lengths": label_lengths,
"gt": [b['gt'] for b in batch],
"spaced_label": spaced_labels,
"name": [b['name'] for b in batch],
"author": [b['author'] for b in batch],
"author_idx": [b['author_idx'] for b in batch],
}
if self.fg_masks_dir is not None:
toRet['fg_mask'] = fg_masks
if self.include_stroke_aug:
changed_images = changed_batch.transpose([0,3,1,2])
changed_images = torch.from_numpy(changed_images)
toRet['changed_image']=changed_images
return toRet
def player2(self):
if choices != []:
player2 = select(choices)
return player2
elif choices == []:
return "Stalemate"
import random
while True:
pdf = input("どれか選んでね (R, P, S) 終了するときは(e)")
tsp = random.select(["R","P","S"])
if pdf == tsp:
print ("あいこ")
elif (pdf == "R" and tsp == "P") or (pdf == "P" and tsp == "S") or (pdf == "S" and tsp == "R"):
print("負け")
elif (pdf == "P" and tsp == "R") or (pdf == "R" and tsp == "S") or (pdf == "S" and tsp == "P"):
print("勝ち")
play = input("Enter a number between 1 and 9 : ")
if int(play) not in choices:
play = input(f'''
That number has already been played.
Available numbers are ; {choices}
Enter a number fom the available choices : ''')
for i in board:
for j in i:
j = (i.index(j))
if int(play) == i[j]:
i[j] = "x"
choices.remove(int(play))
comp = select(choices)
for i in board:
for j in i:
j = (i.index(j))
if comp == i[j]:
i[j] = "o"
choices.remove(comp)
game = f"""
{board[0][0]} | {board[0][1]} | {board[0][2]}
--+---+--
{board[1][0]} | {board[1][1]} | {board[1][2]}
--+---+--
{board[2][0]} | {board[2][1]} | {board[2][2]}
"""
def switch_quiz(self, quiz_filer=None):
"""
Set the Userinterface to test a different Quiz (represented by a
Quiz_Filer object or randomly selected).
"""
# disconnect old listeners #
quiz_filer.quiz.disconnect('question_changed', self.update_gui)
quiz_filer.quiz.disconnect('break_time', self.start_relax_time)
# replace #
if quiz_filer == None:
quiz_filer = random.select(self.quiz_filer_list)
self.quiz_filer = quiz_filer
self.quiz = quiz_filer.quiz
self.update_gui()
# show and hide notebookpanels #
if not quiz_filer.type in self.SHOW_TABS:
print _('Warning: unknown quiz type "%s".') % quiz_filer.type
type = "all"
else:
type = self.quiz_filer.type
for tab, visi in zip(self.main_notbook_tabs.itervalues(),
self.SHOW_TABS[type]):
for widget in tab: # tab is tab-label + tab-content
if visi:
widget.show()
else:
widget.hide()
# show, hide and settext of combobox #
if quiz_filer.all_subquizzes == []:
self.subquiz_combobox.hide()
else:
for i in range(2): # dirty clear combobox
self.subquiz_combobox.remove_text(0)
for subquiz in quiz_filer.all_subquizzes:
self.subquiz_combobox.append_text(subquiz)
self.subquiz_combobox.set_active(self.quiz.ask_from)
self.subquiz_combobox.show()
#
for label in self.question_topic_labels:
label.set_markup("<b>%s</b>" %
quiz_filer.question_topic[self.quiz.ask_from])
# treeview #
## Question/Answer-Columns ##
for column in self.word_treeview.get_columns():
self.word_treeview.remove_column(column)
for i, title in enumerate(quiz_filer.data_name):
tvcolumn = gtk.TreeViewColumn(title,
gtk.CellRendererText(), text=i)
self.word_treeview.append_column(tvcolumn)
## toggler ##
toggler = gtk.CellRendererToggle()
toggler.connect( 'toggled', self.on_treeview_toogled )
tvcolumn = gtk.TreeViewColumn(_("test"), toggler)
tvcolumn.add_attribute(toggler, "active", 2)
self.word_treeview.append_column(tvcolumn)
self.word_treeview.set_model(quiz_filer.treestore)
# clean statusbar #
self.statusbar1.pop(self.statusbar_contextid["last_answer"])
# connect listeners #
quiz_filer.quiz.connect('question_changed', self.update_gui)
quiz_filer.quiz.connect('break_time', self.start_relax_time)
