def conectaAleatorio(self):
import random
rand = ceil(i * (90 / 100))
for j in range(rand):
v = random.sample(self.nodos, 1)[0]
u = random.sample(self.nodos, 1)[0]
if v == u:
u = random.sample(self.nodos, 1)[0]
if pesos is 0:
self.aristas[(v, u)] = self.aristas[(u, v)] = pesos
self.vecinos[v].add(u)
self.vecinos[u].add(v)
else:
self.aristas[(v, u)] = self.aristas[(u,
v)] = randint(1, 10)
self.vecinos[v].add(u)
self.vecinos[u].add(v)
else:
if pesos is 0:
self.aristas[(v, u)] = self.aristas[(u, v)] = pesos
self.vecinos[v].add(u)
self.vecinos[u].add(v)
else:
self.aristas[(v, u)] = self.aristas[(u,
v)] = randint(1, 10)
self.vecinos[v].add(u)
self.vecinos[u].add(v)
def generate_key():
'''
生成16位卡密
'''
new_key = ''.join(random.sample(string.ascii_letters + string.digits, 16))
while new_key in key_dict: # 防止生成重复的卡密, 不过概率太低了。。。
new_key = ''.join(
random.sample(string.ascii_letters + string.digits, 16))
return new_key
def password(strength, length):
paswd = list(string.ascii_letters + string.digits + "!@#$%^&*()")
if strength == 'strong':
temp = random.sample(paswd, length)
usrPassword = ''.join(temp)
else:
ranLst = ["Hello", "password", "birthday", "world", "charizma"]
temp = random.sample(ranLst, len(ranLst))
usrPassword = ''.join(temp)
return usrPassword
def propose(self, state: MechanismState) -> Optional["Outcome"]:
if self.ufun_max is None or self.ufun_min is None:
self.on_ufun_changed()
if self.ufun_max < self.reserved_value:
return None
asp = (self.aspiration(state.relative_time) *
(self.ufun_max - self.ufun_min) + self.ufun_min)
if asp < self.reserved_value:
return None
if self.presorted:
if len(self.ordered_outcomes) < 1:
return None
for i, (u, o) in enumerate(self.ordered_outcomes):
if u is None:
continue
if u < asp:
if u < self.reserved_value:
return None
if i == 0:
return self.ordered_outcomes[i][1]
if self.randomize_offer:
return random.sample(self.ordered_outcomes[:i],
1)[0][1]
return self.ordered_outcomes[i - 1][1]
if self.randomize_offer:
return random.sample(self.ordered_outcomes, 1)[0][1]
return self.ordered_outcomes[-1][1]
else:
if asp >= 0.99999999999 and self.best_outcome is not None:
return self.best_outcome
if self.randomize_offer:
return outcome_with_utility(
ufun=self._utility_function,
rng=(asp, float("inf")),
issues=self._ami.issues,
)
tol = self.tolerance
for _ in range(self.n_trials):
rng = self.ufun_max - self.ufun_min
mx = min(asp + tol * rng, self.__last_offer_util)
outcome = outcome_with_utility(
ufun=self._utility_function,
rng=(asp, mx),
issues=self._ami.issues,
)
if outcome is not None:
break
tol = math.sqrt(tol)
else:
outcome = (self.best_outcome
if self.__last_offer is None else self.__last_offer)
self.__last_offer_util = self.utility_function(outcome)
self.__last_offer = outcome
return outcome
def guarda(self):
with open("Tarea3Completo.dat", "w") as crear:
import random
self.s = random.sample(self.nodos, 1)[0]
self.t = random.sample(self.nodos, 1)[0]
for nodos in self.nodos:
if nodos == self.s:
print(self.s[0], self.s[1], 4, file=crear)
if nodos == self.t:
print(self.t[0], self.t[1], 7, file=crear)
if nodos is not self.s and nodos is not self.t:
print(nodos[0], nodos[1], 8, file=crear)
def conectaAleatorioDir(self):
import random
rand = ceil(i * (50 / 100))
for j in range(rand):
v = random.sample(self.nodos, 1)[0]
u = random.sample(self.nodos, 1)[0]
if v == u:
u = random.sample(self.nodos, 1)[0]
self.aristas[(v, u)] = 0
self.vecinos[v].add(u)
else:
self.aristas[(v, u)] = 0
self.vecinos[v].add(u)
def Aproval_randomizer(candidates_num, comittee_size, voters_num):
list = []
for i in range(voters_num):
f = random.sample(range(candidates_num),
random.randint(1, comittee_size))
list.append(f)
return list
def Breath_First_Search(self):
with open("niveles.dat", "w") as crear:
import random
self.nodoInicio = random.sample(self.nodos, 1)[0]
self.niveles = {}
self.explorado = []
self.estado = [self.nodoInicio]
self.niveles[self.nodoInicio] = 0
print(self.nodoInicio[0],
self.nodoInicio[1],
self.niveles[self.nodoInicio] + 1,
file=crear)
self.visitado = [self.nodoInicio]
while self.estado:
self.nodo = self.estado.pop(0)
self.explorado.append(self.nodo)
self.vecino = self.vecinos[self.nodo]
for self.vecino in self.vecino:
if self.vecino not in self.visitado:
self.estado.append(self.vecino)
self.visitado.append(self.vecino)
self.niveles[self.vecino] = self.niveles[self.nodo] + 1
print(self.vecino[0],
self.vecino[1],
self.niveles[self.vecino] + 1,
file=crear)
for (x, y) in self.nodos:
if (x, y) not in self.visitado:
print(x, y, 0, file=crear)
print(self.niveles)
return self.explorado
def get_random_samples(file_names, samples_count_per_category):
"""
get random samples for log testing.
Args:
file_names:
samples_count_per_category:
Returns:
"""
checklist = np.zeros(samples_count_per_category * 10)
final_list = []
iteration_number = 0
# Get a random sample for each category
while 1:
print("Iteration Number:", iteration_number)
sample_names = random.sample(file_names, 10)
for name in sample_names:
category = int(name[0])
if checklist[category] < samples_count_per_category:
checklist[category] += 1
final_list.append(name)
if int(checklist.sum()) == (samples_count_per_category * 10):
break
iteration_number += 1
print(final_list)
return final_list
def generate_data(data, samples, targeted=True, start=0, inception=False):
"""
Generate the input data to the attack algorithm.
data: the images to attack
samples: number of samples to use
targeted: if true, construct targeted attacks, otherwise untargeted attacks
start: offset into data to use
inception: if targeted and inception, randomly sample 100 targets intead of 1000
"""
inputs = []
targets = []
for i in range(samples):
if targeted:
if inception:
seq = random.sample(range(1,1001), 10)
else:
seq = range(data.test_labels.shape[1])
for j in seq:
if (j == np.argmax(data.test_labels[start+i])) and (inception == False):
continue
inputs.append(data.test_data[start+i])
targets.append(np.eye(data.test_labels.shape[1])[j])
else:
inputs.append(data.test_data[start+i])
targets.append(data.test_labels[start+i])
inputs = np.array(inputs)
targets = np.array(targets)
return inputs, targets
def fit(self, data: np.array):
"""
Fits kmeans
"""
n_samples, _ = data.shape
# initialize cluster centers
self.centers = np.array(random.sample(list(data), self.k))
self.ini_centers = np.copy(self.centers)
old_data_point_assignment = None
n_iters = 0
while True:
data_point_assignment = [
self.classify(datapoint) for datapoint in data
]
# If data point assignments stop changing, then we find the model
if data_point_assignment == old_data_point_assignment:
print(f"Training finished.. {n_iters} iterations!")
print(f"Points assignment: {data_point_assignment}")
return
old_data_point_assignment = data_point_assignment
n_iters = n_iters + 1
# recalculate centers
for i in range(self.k):
points_idx = np.where(np.array(data_point_assignment) == i)
datapoints = data[points_idx]
self.centers[i] = datapoints.mean(axis=0)
def split_ids(ids, split):
ids = sorted(ids.unique().tolist())
test_ids = sorted(random.sample(ids, int(split * len(ids))))
training_ids = list_diff(ids, test_ids)
return Series(test_ids), Series(training_ids)
def sample(self, batch_size=None):
# sample all transitions
if batch_size is None:
return Transition(*zip(*self.memory))
else: # sample with size: batch_size
random_batch = random.sample(self.memory, batch_size)
return Transition(*zip(*random_batch))
def getRandomNum(data, sample_size):
random_values = random.sample(data, k=sample_size - 1)
return random_values
#def getSample(data, sample_size):
# random_values = random.sample(data, k=sample_size)
# return random_values
def selection(population, num_of_selection):
_, max_score, where = weight_calculation(population)
pop = population.copy()
out = []
out.append(population[int(where)])
pop.pop(int(where))
out += random.sample(pop, k=num_of_selection - 1)
return out
def balanced_sample(self):
for i in range(self.batchnum):
for j in self.pool:
p = self.pool[j]
imgpath = random.sample(p, 1)[0]
self.cadidates.append([imgpath, j])
random.shuffle(self.cadidates)
def sample(self, count=4):
"""Return a sampling of the album, for use in jumbotron
and as random album cover photos
"""
if count > self.photo_count():
count = self.photo_count()
photo_set = self.photos
return random.sample(set(photo_set), count)
def random_recipes():
for repeat in range(10):
random_recipe = list(
db.soomi_all_recipes.find({'category': '공식레시피'}, {'_id': 0}))
soomi_random_recipe = (random.sample(random_recipe, 10))
# print(soomi_random_recipe)
return jsonify({
'result': 'success',
'recommend_recipes': soomi_random_recipe
})
def CreateTimming(self, t): days = random.sample(self.Days, random.randint(1,3)) for i in days: s = random.randint(6, 17) ss = str(s).zfill(2) e = random.randint(1 , 6 ) + s es = str(e).zfill(2) ss = datetime.strptime(ss, '%H').time() es = datetime.strptime(es, '%H').time() m.Timming.objects.create(Tutor = t, Day = i, TimeStart = ss, TimeEnd = es)
def FillDataBase(self, n): a = random.sample(range(1000000000, 10000000000), n) for i in a: x = random.random() if x<0.3: self.CreateTutor(i) elif x>0.95: self.CreateBroker(i) else: self.CreateStudent(i)
def scheduling(self, agent_list: List[Agent],
func: Callable[[Agent, List[Agent]], None]) -> None:
current_state = copy.deepcopy(agent_list)
order = random.sample(agent_list, len(agent_list))
for a in order:
other_agents = [x for x in current_state if x is not a]
func(a, other_agents)
agent_list[:] = self.__clash_solution(copy.deepcopy(agent_list),
current_state)
def __commerce_purchase_products(self, e_commerce_agents):
""" 厂商从产品种类中采购商品 """
for e_commerce_agent in e_commerce_agents:
product_diversity = random.randint(1, 15)
if product_diversity >= len(self.category_schedule.agents):
for category_agent in self.category_schedule.agents:
self.__generate_product(e_commerce_agent, category_agent)
else:
selected_category_agents = random.sample(
self.category_schedule.agents, product_diversity)
for category_agent in selected_category_agents:
self.__generate_product(e_commerce_agent, category_agent)
def get_str(num=4):
"""
获取随机字符串
:param num:
:return:
"""
return ''.join(
random.sample([
'0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'z', 'y',
'x', 'w', 'v', 'u', 't', 's', 'r', 'q', 'p', 'o', 'n', 'm',
'l', 'k', 'j', 'i', 'h', 'g', 'f', 'e', 'd', 'c', 'b', 'a'
], num))
def randomly_select_K(sorted_c_r_list, perf_thresh, K, slope_thresh=0.0):
import random
while True:
idx_list = random.sample(range(len(sorted_c_r_list)), K)
sorted_idx_list = sorted(idx_list)
selected_c_r_list = []
for idx in sorted_idx_list:
if (sorted_c_r_list[idx][1] >= perf_thresh) or (sorted_c_r_list[idx][0] < slope_thresh): #If we selected one of the best points, then ignore and resample
break
else:
selected_c_r_list.append(sorted_c_r_list[idx])
if len(selected_c_r_list) == K:
return selected_c_r_list
def ruleta(lista, n):
import random
F, NF = [], []
f = len(lista.loc[d.fact == True, ])
nf = len(lista.loc[d.fact == False, ])
for i in range(0, f):
F.append(i)
for j in range(f, (f + nf)):
NF.append(j)
if len(NF) == 0:
for k in range(0, 3):
NF.append(k)
listas = [(random.sample(F, k=2)), (random.sample(NF, k=2))]
results = random.choices(listas, weights=[len(F), len(NF)], k=2)
if results[0] == results[1]:
salida = results[0]
if results[0] != results[1]:
dato1 = results[0]
dato2 = results[1]
salida = [dato1[0], dato2[0]]
return (salida)
def load_video_features(fpath, max_length):
feats = np.load(
fpath, encoding='latin1'
)[0] # encoding='latin1' to handle the inconsistency between python 2 and 3
if feats.shape[0] < max_length:
dis = max_length - feats.shape[0]
feats = np.lib.pad(feats, ((0, dis), (0, 0)),
'constant',
constant_values=0)
elif feats.shape[0] > max_length:
inds = sorted(random.sample(range(feats.shape[0]), max_length))
feats = feats[inds]
assert feats.shape[0] == max_length
return np.float32(feats)
def getsalt(pwd, salt=None):
'''获取密码并变成盐'''
h = hashlib.md5()
if not salt:
l = "gijhskdgjeuirtu658499848609/,./']["
salt = ''.join(random.sample(l, 6)).replace(" ", "")
password = pwd + salt
h.update(password.encode())
mypwd = h.hexdigest()
return mypwd, salt
else:
password = pwd + salt
h.update(password.encode())
mypwd = h.hexdigest()
return mypwd
def captcha(self, path=None, fmt='JPEG'):
image = Image.new('RGB', (self.width, self.height), (255, 255, 255))
image = self.background(image)
image = self.text(image, self.fonts, drawings=['warp', 'rotate', 'offset'])
image = self.curve(image)
image = self.noise(image)
image = self.smooth(image)
name = "".join(random.sample(string.lowercase + string.uppercase + '3456789', 24))
text = "".join(self._text)
out = StringIO()
image.save(out, format=fmt)
if path:
image.save(os.path.join(path, name), fmt)
return name, text, out.getvalue()
def selection_population_function(population: [Genome],distances_avg,distances,cities,dates,fixture):
# TORNEO
random_list = random.sample(range(0, len(population)), len(population))
selected_population = []
population_length = len(population)
for i in range(int(len(population)/2)):
fitness_1 = fitness(population[random_list[i]], distances_avg, distances, cities, dates, fixture)
fitness_2 = fitness(population[random_list[population_length - i - 1]], distances_avg, distances, cities, dates, fixture)
if fitness_1 <= fitness_2:
selected_population.append(population[random_list[i]])
else:
selected_population.append(population[random_list[population_length - i - 1]])
return selected_population
def generate_events(self):
"""
This method should be overridden depending on the input format of input files.
"""
with open(self.input_path, 'r') as source:
event = {
Attr.id: ''.join(random.sample(string.ascii_letters + string.digits, 8)),
Attr.date: ''.join(time.strftime("%Y%m%d", time.localtime())),
Attr.source: 'NULL'
}
content = re.sub(r'\s', '', source.read())
# parse = self.parse(content)
# event[Attr.content] = self.sep_sentence(parse)
event[Attr.content] = self.sep_sentence(content)
print('parse event {0}'.format(event[Attr.id]))
self.events.append(event)
def typicalSampler(filename, percent=.01, sample_col=0):
# Implements the standard non-streaming sampling method
mean, standard_deviation = 0.0, 0.0
# Step 1: read file to pull out unique user_ids from file
unique_ids = set()
for row in filename:
unique_ids.add(row.split(',')[sample_col])
# Step 2: subset to random 1% of user_ids
user_sample = random.sample(unique_ids, int(len(unique_ids) * percent))
# Step 3: read file again to pull out records from the 1% user_id and compute mean withdrawn
n = 0
sum1, sqsum1 = 0.0, 0.0
sum2, sqsum2 = 0.0, 0.0
mod = 10
filename.seek(0)
for row in filename:
record = row.split(',')
uid = record[sample_col]
if uid in user_sample:
n = n + 1
transaction = float(record[3])
sum1 = sum1 + transaction
sqsum1 = sqsum1 + pow(transaction, 2)
# to prevent overflow,calculating means of buckets,
# increasing bucket size by multiple of 10
# after we have 10 elements of size of prev bucket
if (n % mod == 0):
sum2 = sum2 + sum1 / mod
sqsum2 = sqsum2 + sqsum1 / mod
sum1 = 0
sqsum1 = 0
if (n % (mod * 10) == 0):
sum2 = sum2 / 10
sqsum2 = sqsum2 / 10
mod = mod * 10
sum1 = 0
sqsum1 = 0
mean, standard_deviation = calculate(n, mod, sum1, sum2, sqsum1, sqsum2)
##<<COMPLETE>>
return mean, standard_deviation
def register(request):
"""
Display form for registration
**Context**
registration form
**Template:**
:template:`register.html`
"""
if request.method == 'POST':
form = RegistrationForm(request.POST)
if form.is_valid():
try:
salt = hashlib.sha1(str(random()).encode("utf-8")).hexdigest()[:5]
activation_key = hashlib.sha1((salt + form.cleaned_data["email"]).encode("utf-8")).hexdigest()
key_expires = datetime.datetime.now() + datetime.timedelta(2)
email_subject = 'Embigo - Potwierdzenie Rejestracji '
email_body = "Witaj %s, dziękujemy za rejestrację w Embigo. By zakończyć proces rejestracji musisz, w przeciągu" \
" 48 godzin kliknąć w poniższy link:\nhttp://%s/confirm/%s" % (
form.cleaned_data["username"], request.META["HTTP_HOST"], activation_key)
send_mail(email_subject, email_body, '*****@*****.**', [form.cleaned_data["email"]], fail_silently=False)
new_user = form.save()
new_user.is_active = False
new_user.save()
new_space_user = SpaceUser(uid=uuid1(), rights=embigo_default_rights(), space=embigo_main_space(),
user=new_user)
new_space_user.save()
colors = ["#FEE6AA","#FDD777","#FCC845","#FBBA13","#FEAAAA","#FD7777","#FC4545","#FB1313","#EBAAFE","#E077FD","#D545FC","#C913FB","#B9AAFE","#9077FD","#6745FC","#3E13FB","#AAE0FE","#77CEFD","#45BCFC","#13AAFB","#AAFECA","#77FDAB","#45FC8B","#13FB6C"]
color = random.sample(colors, 1)[0];
embigo_user = EmbigoUser(user=new_user, activation_key=activation_key, key_expires=key_expires,
hash_type='ACTIVATE_HASH')
embigo_user.save()
return HttpResponseRedirect(request.GET.get("next", "/"), RequestContext(request))
except SMTPRecipientsRefused:
form.add_error("email","Błąd podczas wysyłania maila. Upewnij się czy wprowadzony adres e-mail jest poprawny.")
except Exception as e:
new_user.delete()
raise e
else:
form = RegistrationForm()
context = {'form': form}
return render(request, 'register.html', context)
def randomSampleImages(origImagesLoc, dirName, destImagesLoc, total):
list = []
imagesDirList = custom_listdir(origImagesLoc)
for dataFilename in custom_listdir(dirName):
dataFile = open(dirName+dataFilename, 'rb') #opens the file for reading
reader = csv.reader(dataFile)
for index,words in enumerate(reader):
#skip table header line
if index and len(words) > 1:
#parse line and store needed data
imageName = str(words[0]).strip() + ".jpg"
#if image not found, skip it
if imagesDirList.count(imageName) and not list.count(imageName):
list.append(imageName)
dataFile.close()
list = random.sample(list, total)
for image in list:
shutil.move(origImagesLoc+image, destImagesLoc+image)
def _recommend(self):
import random
friend_rows = FacebookUser.objects.filter(user_id=self.targetUser.id)
items = []
for fr in friend_rows:
items.extend(FacebookFriendLike.objects.filter(friend_fid=fr.facebook_id))
selected = random.sample(xrange(len(items)), min(len(items),self.config.MAX_ITEMS*self.config.BUFFER_MULTIPLIER*10))
self.arr = []
for i in selected:
item = {}
item['type'] = items[i].category
item['page_id'] = items[i].facebook_id
item['name'] = items[i].name
item['pic'] = items[i].pic
item['page_url'] = items[i].page_url
item['created_time'] = items[i].created_time
self.arr.append(item)
#pprint(self.arr)
return self.arr
p = ["Python","is", "powerful","simple", "and so on..."] shuffle(p) print p print '-' * 50 # ------------------------------------------------------------------------------- # random.sample(sequence, k) # 从指定序列中随机获取指定长度的片断。 # sample函数不会修改原有序列。 from random import sample li = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] #从list中随机获取5个元素，作为一个片断返回 slc = sample(li, 5) print slc print li #原有序列并没有改变。 print '-' * 50 # ------------------------------------------------------------------------------- "".join(random.sample(string.letters, 10)) # 生成指定长度的随机字符串很容易 # 'kMmSgPVWIi' "".join(random.sample(string.letters, 10)) # 'feCTyRZrHv'
def _generate_indices(bound, count, token):
random.seed(token)
return random.sample(range(bound), count)
# 1. The computer selects four random digits (0 to 9).
# 2. The player attempts to guess these digits, in order.
# 3. The computer gives the player information as to the correctness
of his guess.
# a. For every digit guessed in order, a "Bull" is scored.
# b. For every digit guessed out of order, a "Cow" is scored.
# 4. The player continues making guesses until four Bulls are scored
indicating that he has guessed all four digits correctly.#
numbers = []
cows import random
digits = '123456789'
size = 4
chosen = ''.join(random.sample(digits,size))
#print chosen # Debug
print '''I have chosen a number from %s unique digits from 1 to 9 arranged in a random order.
You need to input a %i digit, unique digit number as a guess at what I have chosen''' % (size, size)
guesses = 0
while True:
guesses += 1
while True:
# get a good guess
guess = raw_input('\nNext guess [%i]: ' % guesses).strip()
if len(guess) == size and \
all(char in digits for char in guess) \
and len(set(guess)) == size:
break
print "Problem, try again. You need to enter %i unique digits from 1 to 9" % size
if guess == chosen:
bucket_size=4
# read the input and make list of lists containing baskets
AllItems=[]
for line in input:
line = line.strip().replace(',', "")
smallList=[]
for i in range(0,len(line)):
smallList.append(line[i])
smallList.sort()
AllItems.append(smallList)
# print AllItems
radomset=random.sample(AllItems,(58*len(AllItems))/100)
randomSupport=(.8*.58*support)
# create list if unique Items
uniqueItem = []
for sublist in AllItems:
for each in sublist:
if each not in uniqueItem:
uniqueItem.append(each)
uniqueItem.sort()
def scatter_plot(self, other_feature, obs_nums=None):
if obs_nums is None:
obs_nums = random.sample(range(self.num_rows()), 50)
v = self.view()