def api_batch_profile(self):
res = dict(profiles={})
# print self.request.arguments, type(self.request.arguments)
def clb(dic):
# print dic
res["profiles"][dic["user"]] = dic
arguments = tornado.escape.json_decode(self.get_argument("data"))
for agent in arguments:
if not db.user_exists(agent):
print "*** user does not exist:", agent
continue
if self.request.method == "GET":
p = profile(agent, [], self.request.path.split("/"), db.r, clb)
p.get("")
if self.request.method == "POST":
p = profile(agent, arguments[agent].items(), db.r, clb)
# print 'arguments', arguments[agent].items()
p.post()
self.finilize_call(res)
def main():
args = _parse_command_line_args()
print(args)
if args.mode == 'profile':
profile.profile()
else:
test.test()
def main(dex):
#ret = opaque_id("/mnt/test/01_ControlFlow/01_High/sanity_cf.apk")
ret = opaque_id.opaque_id(dex)
if not ret :
return
profile(".stdout")
ret = opaque_location.opaque_locations(dex)
print("location : " + str(ret))
# if not ret :
# return
dexfile(dex)
def main(dex):
'''
Entry Point of deobfuscator
[dex] : APK's path
'''
ret = opaque_id.opaque_id(dex)
if not ret :
return
profile(".stdout")
ret = opaque_location.opaque_locations(dex)
print("location : " + str(ret))
dexfile(dex)
def generate_masks_voronoi(self):
with profile():
print 'generate_masks_voronoi'
centers = [
c_hom(close.center())
for c_hom, close in zip(self.c_homs, self.closes)
]
self.c_voronoi_facets = voronoi(centers, self.establishing.system,
self.establishing.dims)
mask_template = (self.establishing.resize(
scale=self.canvas_scale).pipe(lambda x: np.zeros(x.shape[:2])))
homography_masks = [
mask_template.fill_poly(clip(map(c_hom, close.corners()),
mask_template.corners()),
color=1).erode(3)
for c_hom, close in zip(self.c_homs, self.closes)
]
self.c_masks = [
operate(
lambda x, y: x * y,
mask_template.fill_poly(clip(facet,
mask_template.corners()),
color=1),
homography_mask) for facet, homography_mask in zip(
self.c_voronoi_facets, homography_masks)
]
def __init__(self, filename=None, buffer=None, store_plaintext=False,
features=None, feature_overrides=None, algorithms=None):
"""Primary class for all hashing and profiling modules.
Keyword Arguments:
filename -- Filename to evaluate. If buffer is not defined, this will open the file,
otherwise it will use this value when building the profile
buffer -- Contents to evaluate.
store_plaintext -- Whether or not the plaintext should be included in the resulting output,
this is useful for storing the content in a database.
features -- List of features to use, None for all.
feature_overrides -- Dictionary containing features and values to override the output of the module
algorithms -- List of algorithms to use, None for all.
"""
self.buffer = buffer
if filename and self.buffer is None:
statinfo = os.stat(filename)
size = statinfo.st_size
with open(filename, 'rb') as f:
self.buffer = f.read()
if size >= MAX_SIZE:
self.store_plaintext = False
p = profile(filename=filename, buffer=self.buffer, store_plaintext=store_plaintext,
modules=features, overrides=feature_overrides)
self.result = p.profile.copy()
h = hashes(buffer=self.buffer, modules=algorithms)
self.result.update(h.__dict__)
def detail_transfer_stitch_pt_2(self, detail_transfer_blur_op,
edge_blend_radius):
with profile():
print 'detail_transfer_stitch_pt_2'
canvas = (self.establishing.white_balance().normalize().resize(
scale=self.canvas_scale))
images, full_masks, full_masks_blurred = zip(
*self.detail_transfer_stitch_outputs)
print 'computing outside mask'
print 'step 1'
outside_mask_blurred = sum_subimages(full_masks, canvas.system,
canvas.dims)
print 'step 2'
outside_mask_blurred = outside_mask_blurred.pipe(
lambda x: (x == 0).astype(float))
print 'step 3'
outside_mask_blurred = outside_mask_blurred.blur(edge_blend_radius)
print outside_mask_blurred.array.shape
print full_masks_blurred[0].array.shape
del full_masks # to save some memory
print 'blending'
self.detail_transfer_stitch_output = blend_subimages(
(canvas, ) + images,
(outside_mask_blurred, ) + full_masks_blurred, canvas.system,
canvas.dims)
return self.detail_transfer_stitch_output
def do_insert():
m = Monary()
num_docs = NUM_BATCHES * BATCH_SIZE
params = [MonaryParam(
ma.masked_array(nprand.uniform(0, i + 1, num_docs),
np.zeros(num_docs)), "x%d" % i) for i in range(5)]
wc = WriteConcern(w=MONARY_W_DEFAULT)
with profile("monary insert"):
m.insert("monary_test", "collection", params, write_concern=wc)
def signup(self):
system("clear")
print("@@@ SnapQuick Registration page! ")
connection = sqlite3.connect("../main/data_base.db")
crsr = connection.cursor()
crsr.execute("SELECT * FROM user")
ans = crsr.fetchall()
check = 0
t = 0
while not check:
user_id = input("choose a user Id: ")
for j in ans:
if j[0] == user_id:
print("Already Taken")
t = 1
break
if t:
t = 0
else:
check = 1
print("Available!")
set_password = input("Enter Password: "******"First Name: ")
lname = input("Last Name: ")
gender = input("Gender: ")
email_id = input("Email Id: ")
phone_number = int(input("Phone Number: "))
sql_command = """INSERT INTO user VALUES (?,?,?,?,?,?,?);"""
crsr.execute(sql_command, (
user_id,
fname,
lname,
gender,
email_id,
phone_number,
set_password,
))
connection.commit()
print("account succesfully Created !")
profile().show_profile(entered_id)
def do_insert():
m = Monary()
num_docs = NUM_BATCHES * BATCH_SIZE
params = [
MonaryParam(
ma.masked_array(nprand.uniform(0, i + 1, num_docs),
np.zeros(num_docs)), "x%d" % i) for i in range(5)
]
wc = WriteConcern(w=MONARY_W_DEFAULT)
with profile("monary insert"):
m.insert("monary_test", "collection", params, write_concern=wc)
def createprofile(name):
print name.text
try:
profiles = cPickle.load(open('profilelist', 'r'))
print profiles
except:
profiles = []
#print "did not load profiles"
pass
current = profile(name.text)
load(current)
profiles.append(current)
cPickle.dump(profiles, open('profilelist', 'w'))
def do_monary_query():
with Monary("127.0.0.1") as m:
with profile("monary query"):
arrays = m.query(
"monary_test", # database name
"collection", # collection name
{}, # query spec
["x1", "x2", "x3", "x4", "x5"], # field names
["float64"] * 5 # field types
)
# prove that we did something...
print(numpy.mean(arrays, axis=-1))
def do_monary_query():
with Monary("127.0.0.1") as m:
with profile("monary query"):
arrays = m.query(
"monary_test", # database name
"collection", # collection name
{}, # query spec
["x1", "x2", "x3", "x4", "x5"], # field names
["float64"] * 5 # field types
)
# prove that we did something...
print(numpy.mean(arrays, axis=-1))
def do_pymongo_query():
c = pymongo.MongoClient()
collection = c.monary_test.collection
with profile("pymongo query"):
num = collection.count()
arrays = [ numpy.zeros(num) for i in range(5) ]
fields = [ "x1", "x2", "x3", "x4", "x5" ]
arrays_fields = list(zip(arrays, fields))
for i, record in enumerate(collection.find()):
for array, field in arrays_fields:
array[i] = record[field]
# prove that we did something...
print(numpy.mean(arrays, axis=-1))
def detail_transfer_stitch_pt_1(self, detail_transfer_blur_op,
edge_blend_radius):
with profile():
print 'detail_transfer_stitch_pt_1'
canvas = (self.establishing.white_balance().normalize().resize(
scale=self.canvas_scale))
canvas_blurred = detail_transfer_blur_op(canvas.astype(np.float32))
# TODO: not being used
# pool = multiprocessing.dummy.Pool()
self.detail_transfer_stitch_outputs = map(
self._detail_transfer_stitch_step,
zip(
repeat((canvas, canvas_blurred, detail_transfer_blur_op,
edge_blend_radius)), self.closes, self.c_homs,
self.c_masks))
print 'all details are transferred'
def do_pymongo_query():
c = pymongo.Connection("localhost")
collection = c.monary_test.collection
with profile("pymongo query"):
num = collection.count()
arrays = [numpy.zeros(num) for i in range(5)]
fields = ["x1", "x2", "x3", "x4", "x5"]
arrays_fields = zip(arrays, fields)
for i, record in enumerate(collection.find()):
for array, field in arrays_fields:
array[i] = record[field]
# prove that we did something...
print numpy.mean(arrays, axis=-1)
def do_pymongo_query():
c = pymongo.Connection("localhost")
collection = c.monary_test.collection
with profile("pymongo query"):
num = collection.count()
arrays = [ numpy.zeros(num) for i in range(5) ]
fields = [ "x1", "x2", "x3", "x4", "x5" ]
arrays_fields = zip(arrays, fields)
for i, record in enumerate(collection.find()):
for array, field in arrays_fields:
array[i] = record[field]
for array in arrays: # prove that we did something...
print numpy.mean(array)
def do_monary_block_query():
count = 0
sums = numpy.zeros((5, ))
with Monary("127.0.0.1") as m:
with profile("monary block query"):
for arrays in m.block_query(
"monary_test", # database name
"collection", # collection name
{}, # query spec
["x1", "x2", "x3", "x4", "x5"], # field names
["float64"] * 5, # field types
block_size=32 * 1024,
):
count += len(arrays[0])
sums += [numpy.sum(arr) for arr in arrays]
print "visited %i items" % count
print sums / count # prove that we did something...
def do_insert():
c = pymongo.MongoClient("localhost")
collection = c.monary_test.collection
num_docs = NUM_BATCHES * BATCH_SIZE
arrays = [nprand.uniform(0, i + 1, num_docs) for i in xrange(5)]
with profile("pymongo insert"):
for i in xrange(NUM_BATCHES):
stuff = []
for j in xrange(BATCH_SIZE):
idx = i * BATCH_SIZE + j
record = {"x1": arrays[0][idx],
"x2": arrays[1][idx],
"x3": arrays[2][idx],
"x4": arrays[3][idx],
"x5": arrays[4][idx]}
stuff.append(record)
collection.insert(stuff)
def do_monary_block_query():
count = 0
sums = numpy.zeros((5,))
with Monary("127.0.0.1") as m:
with profile("monary block query"):
for arrays in m.block_query(
"monary_test", # database name
"collection", # collection name
{}, # query spec
["x1", "x2", "x3", "x4", "x5"], # field names
["float64"] * 5, # field types
block_size=32 * 1024,
):
count += len(arrays[0])
sums += [ numpy.sum(arr) for arr in arrays ]
print "visited %i items" % count
print sums / count # prove that we did something...
def do_insert():
NUM_BATCHES = 3500
BATCH_SIZE = 1000
# 3500 batches * 1000 per batch = 3.5 million records
c = pymongo.Connection("localhost")
collection = c.monary_test.collection
with profile("insert"):
for i in xrange(NUM_BATCHES):
stuff = []
for j in xrange(BATCH_SIZE):
record = dict(x1=random.uniform(0, 1),
x2=random.uniform(0, 2),
x3=random.uniform(0, 3),
x4=random.uniform(0, 4),
x5=random.uniform(0, 5))
stuff.append(record)
collection.insert(stuff)
def do_insert():
c = pymongo.MongoClient("localhost")
collection = c.monary_test.collection
num_docs = NUM_BATCHES * BATCH_SIZE
arrays = [nprand.uniform(0, i + 1, num_docs) for i in xrange(5)]
with profile("pymongo insert"):
for i in xrange(NUM_BATCHES):
stuff = []
for j in xrange(BATCH_SIZE):
idx = i * BATCH_SIZE + j
record = {
"x1": arrays[0][idx],
"x2": arrays[1][idx],
"x3": arrays[2][idx],
"x4": arrays[3][idx],
"x5": arrays[4][idx]
}
stuff.append(record)
collection.insert(stuff)
def do_insert():
NUM_BATCHES = 3500
BATCH_SIZE = 1000
# 3500 batches * 1000 per batch = 3.5 million records
c = pymongo.Connection("localhost")
collection = c.monary_test.collection
with profile("insert"):
for i in xrange(NUM_BATCHES):
stuff = [ ]
for j in xrange(BATCH_SIZE):
record = dict(x1=random.uniform(0, 1),
x2=random.uniform(0, 2),
x3=random.uniform(0, 3),
x4=random.uniform(0, 4),
x5=random.uniform(0, 5)
)
stuff.append(record)
collection.insert(stuff)
def do_insert():
NUM_BATCHES = 4500
BATCH_SIZE = 1000
# 4500 batches * 1000 per batch = 4.5 million records
c = pymongo.MongoClient()
collection = c.monary_test.collection
with profile("insert"):
for i in xrange(NUM_BATCHES):
stuff = []
for j in xrange(BATCH_SIZE):
record = dict(x1=random.uniform(0, 1),
x2=random.uniform(0, 2),
x3=random.uniform(0, 3),
x4=random.uniform(0, 4),
x5=random.uniform(0, 5))
stuff.append(record)
collection.insert(stuff)
print "Inserted %d records." % (NUM_BATCHES * BATCH_SIZE)
def do_insert():
NUM_BATCHES = 4500
BATCH_SIZE = 1000
# 4500 batches * 1000 per batch = 4.5 million records
c = pymongo.MongoClient()
collection = c.monary_test.collection
with profile("insert"):
for i in xrange(NUM_BATCHES):
stuff = [ ]
for j in xrange(BATCH_SIZE):
record = dict(x1=random.uniform(0, 1),
x2=random.uniform(0, 2),
x3=random.uniform(0, 3),
x4=random.uniform(0, 4),
x5=random.uniform(0, 5)
)
stuff.append(record)
collection.insert(stuff)
print "Inserted %d records." % (NUM_BATCHES * BATCH_SIZE)
def simple_stitch(self):
with profile():
print 'simple_stitch'
canvas = self.establishing.resize(scale=self.canvas_scale)
def process(inputs):
close, c_hom = inputs
foreground, homography_mask = apply_homography(
close, c_hom, canvas.system, canvas.dims)
print 'processed'
return foreground
pool = multiprocessing.dummy.Pool()
self.simple_stitch_outputs = pool.map(
process, zip(self.closes, self.c_homs))
for foreground, mask in zip(self.simple_stitch_outputs,
self.c_masks):
composite(canvas, foreground, mask, inplace=True)
self.simple_stitch_output = canvas
return self.simple_stitch_output
def find_homographies(self, downsample_scale=0.5, num_threads=None):
with profile():
print 'find_homographies'
# This uses a thread pool (a dummy multiprocessing pool) to pipeline the
# OpenCV work and take better advantage of multicore machines.
pool = multiprocessing.dummy.Pool(processes=num_threads)
self.e_features = find_features(self.establishing)
c_features_results = [
pool.apply_async(
lambda c: find_features(
c.resize(scale=downsample_scale)
if downsample_scale < 1 else c), (c, ))
for c in self.closes
]
self.c_homs = pool.map(
lambda c_features_result: find_homography(
c_features_result.get(), self.e_features),
c_features_results)
print self.c_homs
self.c_features = [
c_features_result.get()
for c_features_result in c_features_results
]
def generate_masks_stacked(self):
with profile():
print 'generate_masks_stacked'
self.calculate_areas()
area_order = sorted(range(len(self.areas)),
key=lambda i: self.areas[i])
mask_template = (self.establishing.resize(
scale=self.canvas_scale).pipe(lambda x: np.zeros(x.shape[:2])))
available = mask_template.pipe(lambda x: x + 1)
self.c_masks = [None] * len(self.closes)
for i in area_order:
c_hom, close = self.c_homs[i], self.closes[i]
homography_boundary = map(c_hom, close.corners())
clipped_homography_boundary = clip(homography_boundary,
mask_template.corners())
c_mask = (mask_template.fill_poly(clipped_homography_boundary,
color=1).erode(3))
c_mask.array *= available.array
c_mask = c_mask
self.c_masks[i] = c_mask
available.array -= c_mask.array
sim_mo_i=sim_Em+sim_Im+sim_noise_EIm #mock noisy data for collecting infected mosquitoes
#pl.figure()
#pl.plot(sim_Em+sim_Im, '-b', label='infected_m')
#pl.plot(sim_noise_EIm,'g', label='noise')
#pl.plot(sim_mo_i,'r', label='data_model_noise_weekly')
#pl.legend()
#pl.show()
sim_adultm=sim_Sm+sim_Em+sim_Im #mock data for collecting adult mosquitoes
sim_iem=sim_Im+sim_Em #mock data for collecting infected mosquitoes
'''==============================calculate parmameter likelihood surface =============================='''
#making range list for parameter profiling
dengue_profile=profile(opt_dengue.model, opt_param, opt_ini, time_step, 15, 80)
param_name=['beta', 'repH', 'x', 'pi_mua', 'beta_m', 'mu_m']
#profile likelihood:
########################
for i in range(len(opt_param)):
proflog={}
param_adj_ls, param_fix_temp, param_test_ind = dengue_profile.fit_fix(i,0)
#iterate through fixed parameter list if there are any
for fix_ind in param_fix_temp:
proflog_temp={}
param_fix=[dengue_profile.param[x] for x in fix_ind]
fit_ind=list(set(param_test_ind)-set(fix_ind))
#param_fit=[dengue_profile.param[p_f] for p_f in fit_ind]
def pf():
return str(make_page(user, logo, profile(user)))
def task():
profile.profile()
shoppingMalls.shop()
icon.icon()
def login(data_base):
name=sign_in(data_base)
id=data_base[name][0]
if name==0:
print(" ")
else:
start=time.time()
while True:
os.system('clear')
print("\n===============================")
print(" Welcome back: ",name)
print("===============================\n")
print("""Select from given options:
1. Profile
2. Bank Account
3. Games
4. Events
5. Memories
6. Settings
7. Help & Support
8. Log out""")
choice=input()
if choice in ['1','profile','Profile','PROFILE']:
profile(data_base,name)
elif choice in ['2','bankaccount','BankAccount','Bank Account','bank account','BANKACCOUNT']:
bank_account(data_base,name)
elif choice in ['3','games','Games','GAMES']:
os.system('clear')
user_game(data_base,id)
elif choice in ['4','Events','events','EVENTS']:
print('events')
elif choice in ['5','memories','Memories','MEMORIES']:
print('memories')
elif choice in ['6','settings','Settings','SETTINGS']:
name=change_detail(data_base,name)
if name==0:
break
elif choice in ['7','Help&Support','help&support','Help & Support','help&support']:
print('help')
elif choice in ['8','Log out','Logout','logout','LOGOUT','log out']:
os.system('clear')
stop=time.time()
t=stop-start
db=pymysql.connect('localhost','nayan','1234','user_database')
cursor=db.cursor()
check=data_base[name][2]
if check==None:
data_base[name][2]=t
cursor.execute('update data set usage_time=%s where username=%s',(t,name))
else:
total_usage=t+check
data_base[name][2]=total_usage
cursor.execute('UPDATE data SET usage_time=%s WHERE username=%s',(total_usage,name))
db.commit()
db.close()
print('You have been successfully logged out')
print('Login duration:',int(t),' seconds')
break
else:
print("chose a valid option")
pl.figure()
#pl.plot(opt_res[:,0],'b', label='SH')
#pl.plot(opt_res[:,1],'r', label='EH')
#pl.plot(opt_res[:,2],'g', label='IH')
pl.plot(opt_res[:,3],'m', label='A')
pl.plot(opt_res[:,4],'y', label='Sm')
#pl.plot(opt_res[:,5],'k', label='Em')
#pl.plot(opt_res[:,6],'c', label='Im')
pl.legend()
pl.show()
#pl.savefig('temp_fig')
'''
'''==============================calculate paried param likelihood surface =============================='''
dengue_profile=profile(opt_temp.model, opt_param, opt_ini, time_step, 10, 60)
param_name=['beta', 'repH', 'x', 'pi_mua', 'beta_m', 'mu_m']
templs=dengue_profile.pert_level
temp_ee=[(a,b) for a in range(len(opt_param)) for b in range(len(opt_param))]
temp_ee2=[]
for j,k in temp_ee: #drawing pairs
temp_ele1=(j,k)
temp_ele2=(k,j)
if temp_ele2 not in temp_ee2 and j!=k:
temp_ee2.append(temp_ele1)
#print temp_ee2
for q,r in temp_ee2:
from BeautifulSoup import BeautifulSoup
from urllib2 import urlopen
from profile import profile
import csv
csv_file = open("email_list.csv", "w+")
url = 'https://scrapebook22.appspot.com'
response = urlopen(url).read()
soup = BeautifulSoup(response)
for link in soup.findAll("a"):
if link.string == "See full profile":
person_html = urlopen(url + link["href"]).read()
person_soup = BeautifulSoup(person_html)
profileData = person_soup.findAll("li")
email = person_soup.find("span", attrs={"class": "email"}).string
name = person_soup.find("div", attrs={"class": "col-md-8"}).h1.string
city = person_soup.find("span", attrs={"data-city": True}).string
profil = profile(email, name, city)
csv_file.write(profil.to_csv() + "\n")
csv_file.close()
async def profile_command(ctx, *args):
response = profile.profile(ctx, args)
if type(response) is discord.embeds.Embed:
await ctx.send(" ", embed=response)
elif type(response) is str:
await ctx.send(response)
num_sync = log_sync(signature, db_path + "profile/")
config["num_sync"] = num_sync
# feel free to customize the repo name you want
name = kernel["tvm_func_name"].replace("_kernel0", "")
operator_path = db_path + op_type + "_db/"
if not os.path.isdir(operator_path):
os.mkdir(operator_path)
with open(operator_path + name + ".json", "w+") as f:
json.dump(config, f)
with open(operator_path + name + ".cu", "w+") as f:
f.write(new_code)
default_tags = ""
if (op_type == "Dot"):
# Todo: move the transpose information into identifier
default_tags += kernel["parameters"]["transpose_A"] * \
",transA" + kernel["parameters"]["transpose_B"]*",transB"
# apply rules that every 32 threads will be formed as a warp
resource = math.ceil(prod(config["blockDim"]) / 32) * 32 * prod(
config["gridDim"])
prepare_file(signature, kernel["code"], config, db_path + "profile/")
profile_info = profile(signature, db_path + "profile/")
print(profile_info, resource, config["num_sync"])
insert_db(operator_path + name,
resource,
tags=default_tags,
profile=profile_info)
print(
"Welcome to Aarush's Basketball Simulator, created in collaboration with Maanav Singh."
)
print(
"This simulator procedurally generates player profiles with statistics, which you can then pit together"
)
print(
"in 1v1 scenarios to determine who is the better basketball player. When you input 2, you will be asked how many players"
)
print("you wish to generate. Any number can be inputted.")
elif userInput == 2:
print("How many players would you like to generate profiles for?")
userInput = int(input())
playerArray = []
for _ in range(userInput):
playerArray.append(profile())
printStats(playerArray)
while (True):
print(
"Would you like to simulate next year? Respond 1 for yes and 2 for no")
userInput = int(input())
if userInput == 1:
for i in playerArray:
i.incrementAge()
i.updateStats()
for k, v in i.getStats().items():
print(k, v)
print("\n")
else:
break
model = pickle.load(f_un)
with open("../data/cols.pkl") as f_un:
events = pickle.load(f_un)
df0 = pd.DataFrame(columns=events)
s_mission = set(sign.columns)
# find common model events in current mission
for i in ['_std', '_md', '_min', '_max', '_cnt']:
event_base = [ e.replace(i,'') for e in events if e.endswith(i)]
mission_events = list(set(event_base) & s_mission)
s1 = profile(sign, mission_events, os.sys.argv[1])
mission_events = list(set(events) & set(s1.columns))
sign = pd.concat([s1[mission_events],df0])
agg_filename = "../data/" + os.sys.argv[1] + "_agg.csv"
sign.to_csv(agg_filename)
X = sign[events].fillna(-9999999.)
X = X.values
preds = np.clip(np.round(model.predict(X)), 1, 5)
print
print
def MessageStatus(self, msg, status):
if status == Skype4Py.cmsReceived or status == Skype4Py.cmsSent:
# I have no idea what this line does other than it makes the bot respond to its own messages, and it only works in private chat
#if not msg.Sender.Handle in self.blacklist:
if msg.Body[0] == "!" and msg.Sender.Handle != "everythingbot":
print "[" + str(datetime.now())[:-7] + "] " + msg.Sender.Handle + ": " + msg.Body
# !help
if re.match("!help(?!\S)", msg.Body):
msg.Chat.SendMessage(help())
# !ping
elif re.match("!ping(?!\S)", msg.Body):
msg.Chat.SendMessage(ping())
# !members
elif re.match("!members(?!\S)", msg.Body):
msg.Chat.SendMessage(members(msg.Chat.Members))
# !profile
elif re.match("!profile(?!\S)", msg.Body):
try:
skypeName = msg.Body[9:]
msg.Chat.SendMessage(profile(skypeName, msg.Chat.Members))
except IndexError:
msg.Chat.SendMessage("Skype username required for profile lookup.")
# !orangecrush
# If you're reading this on the Github repo, congratulations on being the first to figure out that it's been public all along.
elif re.match("!orangecrush(?!\S)", msg.Body):
msg.Chat.SendMessage("!orangecrush")
# !lenny
elif re.match("!lenny(?!\S)", msg.Body):
msg.Chat.SendMessage(self._lenny)
# !friendcodes
elif re.match("!friendcodes(?!\S)", msg.Body) or re.match("!fc(?!\S)", msg.Body):
msg.Chat.SendMessage(friendcodes())
# !gostats
elif re.match("!gostats(?!\S)", msg.Body):
msg.Chat.SendMessage("http://csgo-stats.com/" + msg.Body[9:])
# !tableflip
elif re.match("!tableflip(?!\S)", msg.Body):
msg.Chat.SendMessage(self._tableflip)
# !tableset
elif re.match("!tableset(?!\S)", msg.Body):
msg.Chat.SendMessage(self._tableset)
# !coinflip
elif re.match("!coinflip(?!\S)", msg.Body):
msg.Chat.SendMessage(coinflip())
# URL titles
# This is the opt-into title code.
#elif re.match("!title(?!\S)", msg.Body):
# if re.match('!title http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', msg.Body, re.IGNORECASE):
# url = re.search('http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', msg.Body, re.IGNORECASE)
# msg.Chat.SendMessage(url_get(url.group(0)))
# else:
# msg.Chat.SendMessage("Invalid URL.")
# This is the opt-out of title code.
elif re.search('http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', msg.Body, re.IGNORECASE) and not re.search("!nt(?!\S)", msg.Body) and msg.Sender.Handle != "everythingbot":
url = re.search('http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+', msg.Body, re.IGNORECASE)
msg.Chat.SendMessage(url_get(url.group(0)))
# !removebot
elif re.match("!removebot(?!\S)", msg.Body):
if removebot(msg.Sender.Handle):
msg.Chat.Leave()
# !restartbot
elif re.match("!restartbot(?!\S)", msg.Body):
if removebot(msg.Sender.Handle):
msg.Chat.SendMessage("Restarting bot.")
execfile("~halbrdbot.py")
sys.exit()
# !twitch (channel)
# !gostats
elif re.match("!twitch(?!\S)", msg.Body):
# msg.Chat.SendMessage("http://twitch.tv/" + msg.Body[8:])
msg.Chat.SendMessage(twitch(msg.Body[8:]))
# !requestfunction (string)
#elif re.match("!requestfunction(?!\S)", msg.Body):
# msg.Chat.SendMessage(requestfunction(msg.Sender.Handle, msg.Body[17:]))
#elif msg.Body == "!chatname":
# msg.Chat.SendMessage(msg.Chat.Name)
# !hug
elif re.match("!hug(?!\S)", msg.Body) and msg.Sender.Handle != "everythingbot":
msg.Chat.SendMessage(hug(msg.Sender.FullName, msg.Body[5:]))
# !bothug
elif re.match("!bothug(?!\S)", msg.Body):
msg.Chat.SendMessage(bothug(msg.Body[8:]))
# !blacklist
#elif re.match("!blacklist(?!\S)", msg.Body):
# msg.Chat.SendMessage(blacklist(msg.Sender.Handle, msg.Body[11:]))
# !strats
elif re.match("!strats(?!\S)", msg.Body):
msg.Chat.SendMessage(strats(msg.Body[8:]))
# !lwc
elif re.match("!lwc(?!\S)", msg.Body):
msg.Chat.SendMessage("Literally who cares.\nhttp://lynq.me/lwc.mp4")
# lmao
# Keep this as the last thing that gets checked
elif re.search("l+ *m+ *a+ *o+", msg.Body, re.IGNORECASE) and msg.Sender.Handle != "everythingbot":
msg.Chat.SendMessage("ayyy")
def to_profile(self):
"""Converts the alignment to profile format"""
prf = profile.profile(self.env)
_modeller.mod_profile_from_aln(aln=self.modpt, prf=prf.modpt,
libs=self.env.libs.modpt)
return prf
return count
def ones_mem(num):
nib = 0
if num == 0:
return INT_BITS_NIBBLE[0]
nib = num & 0xf
return INT_BITS_NIBBLE[nib] + ones_mem(num >> 4)
if __name__ == '__main__':
num = int(sys.argv[1])
try:
itr = int(sys.argv[2])
except IndexError:
itr = 1
try:
method = int(sys.argv[3])
except IndexError:
method = ones_1
if method == 1:
method = ones_1
if method == 2:
method = ones_mem
for _ in xrange(itr):
print "1s using : ", profile(method)(num)
def initUi(self):
pf = profile.profile(self.parent)
#로그아웃 버튼
logoutbtn = QPushButton()
logoutbtn.setMaximumHeight(32)
logoutbtn.setMaximumWidth(42)
logoutbtn.setStyleSheet(''' QPushButton{image:url(./icon/logout.png); border: 0px; width:32px; height:42px}
QPushButton:hover{background:rgba(0,0,0,0); border:0px}
''')
alarm_groupbox = QGroupBox('안내설명')
alarm_groupbox.setStyleSheet('font:9pt 나눔스퀘어라운드 Regular;')
alarm_groupbox.setMinimumSize(300,170)
empty = QLabel(" ")
#강의 목록 그리기
setting_label = QLabel('개인 설정')
setting_label.setStyleSheet("font: 16pt 나눔스퀘어라운드 Regular;background:#eef5f6;color:#42808a")
#horizon_line = QLabel('─────────────────────')
#구분선
horizon_line = QLabel()
horizon_img = QPixmap('./ui/afterlogin_ui/horizon_line.png')
horizon_img = horizon_img.scaled(310,12,QtCore.Qt.KeepAspectRatio,QtCore.Qt.FastTransformation)
horizon_line.setPixmap(horizon_img)
horizon_line.setAlignment(Qt.AlignTop)
#사용 설명
self.use_explanation = QGridLayout()
#useicon_list = QListWidget()
# lecture = QLabel()
# lecture_img = QPixmap('./ui/afterlogin_ui/list.png')
# lecture_img = lecture_img.scaled(100,100 , QtCore.Qt.KeepAspectRatio, QtCore.Qt.FastTransformation)
# lecture.setPixmap(lecture_img)
lecture = QPushButton()
lecture.setStyleSheet('''
QPushButton{image:url(./ui/afterlogin_ui/list.png); border:0px; width:40px; height:40px}
QPushButton:hover{background:#cce5e8; border:0px}
''')
lecture.setFocusPolicy(Qt.NoFocus)
lecture.clicked.connect(lambda: self.use_explain(0))
alarm = QPushButton()
alarm.setStyleSheet('''
QPushButton{image:url(./ui/afterlogin_ui/alarm.png); border:0px; width:40px; height:40px}
QPushButton:hover{background:#cce5e8; border:0px}
''')
alarm.setFocusPolicy(Qt.NoFocus)
alarm.clicked.connect(lambda:self.use_explain(1))
rank = QPushButton()
rank.setStyleSheet('''
QPushButton{image:url(./ui/afterlogin_ui/trophy.png); border:0px; width:40px; height:40px}
QPushButton:hover{background:#cce5e8; border:0px}
''')
rank.setFocusPolicy(Qt.NoFocus)
rank.clicked.connect(lambda:self.use_explain(2))
setting = QPushButton()
setting.setStyleSheet('''
QPushButton{image:url(./ui/afterlogin_ui/setting.png); border:0px; width:40px; height:40px}
QPushButton:hover{background:#cce5e8; border:0px}
''')
setting.setFocusPolicy(Qt.NoFocus)
setting.clicked.connect(lambda:self.use_explain(3))
self.use_explanation.addWidget(lecture,0,0)
self.use_explanation.addWidget(alarm,0,1)
self.use_explanation.addWidget(rank,1,0)
self.use_explanation.addWidget(setting,1,1)
alarm_widget_label = QLabel('알림 위젯')
alarm_widget_label.setStyleSheet('font:9pt 나눔스퀘어라운드 Regular;')
alarm_sound_label = QLabel('소리 기능')
alarm_sound_label.setStyleSheet('font:9pt 나눔스퀘어라운드 Regular;')
alarm_sound_label.setAlignment(Qt.AlignLeft)
# 위젯 on/off 버튼
self.widget_on_off_button = QPushButton()
self.widget_on_off_button.setMinimumHeight(50)
self.widget_on_off_button.setMinimumWidth(50)
self.widget_on_off_button.setFocusPolicy(Qt.NoFocus)
self.widget_on_off_button.setStyleSheet('''
QPushButton{image:url(./icon/alarm_on.png); border:0px; width:50px; height:50px;}
''')
self.widget_on_off_button_status = True
self.widget_on_off_button.clicked.connect(self.widget_button_toggle)
# 소리 on/off 버튼
self.sound_on_off_button = QPushButton()
self.sound_on_off_button.setMinimumHeight(50)
self.sound_on_off_button.setMinimumWidth(50)
self.sound_on_off_button.setFocusPolicy(Qt.NoFocus)
self.sound_on_off_button.setStyleSheet('''
QPushButton{image:url(./icon/alarm_on.png); border:0px; width:50px; height:50px;}
''')
self.sound_on_off_button.setCheckable(True)
self.sound_on_off_button_status = True
self.sound_on_off_button.clicked.connect(self.sound_button_toggle)
self.title.addWidget(setting_label)
#self.title.addWidget(logoutbtn)
# self.line.addWidget(alarm_widget_label)
# self.line.addWidget(self.widget_on_off_button,alignment=(QtCore.Qt.AlignLeft|QtCore.Qt.AlignTop))
# self.line.addWidget(alarm_sound_label)
# self.line.addWidget(self.sound_on_off_button,alignment=(QtCore.Qt.AlignLeft|QtCore.Qt.AlignTop))
# #self.line.addWidget(useicon_list)
# self.line.addStretch(1)
#alarm_groupbox.setLayout(self.line)
alarm_groupbox.setLayout(self.use_explanation)
self.mainLayout.addLayout(self.title)
self.mainLayout.addWidget(horizon_line)
self.mainLayout.addWidget(pf, alignment=QtCore.Qt.AlignCenter)
self.mainLayout.addWidget(alarm_groupbox)
self.mainLayout.addWidget(empty)
self.mainLayout.addWidget(empty)
self.mainLayout.addStretch(1)
for f in glob(os.path.join(os.path.dirname(__file__), 'mechmap_archive', options.archive, '*')):
shutil.copy(f, outdir)
from both import geos
from profile import profile
from mech import mechnml, mechinc, mechext
from map import map, trymap
if options.extfiles:
mech = mechext
else:
mech = mechnml
go = geos(tracerpath,
smvpath)
po = profile(profilepath)
if not os.path.exists(convpath):
if os.path.exists(os.path.join(os.path.dirname(__file__), convpath + '.csv')):
convpath = os.path.join(os.path.dirname(__file__), convpath + '.csv')
elif 'Y' == raw_input("Conversion path does not exist; type Y to create it or any other key to abort\n"):
trymap(mech(mechpath), convpath, go)
else:
exit()
mech_info = mechinc(mech(mechpath), convpath)
cspec_info = go.cspec_info()
tracer_info = go.tracer_info()
profile_info = po.profile_info()
try:
mappings, nprof = map(mech(mechpath), convpath, go, po)
except TypeError, err:
