示例#1
0
 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)
示例#2
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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
示例#5
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 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)
示例#6
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 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)
示例#7
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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
示例#8
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 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
示例#9
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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
示例#10
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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)
示例#13
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 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
示例#15
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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
示例#16
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    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)
示例#17
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    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
    })
示例#19
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	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)
示例#20
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	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)
示例#21
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    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)
示例#22
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 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)
示例#23
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 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))
示例#24
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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
示例#25
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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)
示例#26
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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)
示例#27
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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
示例#28
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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()
示例#29
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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
示例#30
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 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
示例#32
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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)
示例#33
0
文件: tasks.py 项目: koudev/CoralNet
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)
示例#34
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 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
示例#35
0
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'


示例#36
0
def _generate_indices(bound, count, token):
    random.seed(token)
    return random.sample(range(bound), count)
示例#37
0
文件: moo.py 项目: pujaarajan/CS2043
#   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()
示例#39
0
 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()