Python random.paretovariate() Examples

The following are 6 code examples of random.paretovariate(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module random , or try the search function .
Example #1
Source Project: LSTM_morse   Author: ag1le   File: LSTM.py    License: MIT License 6 votes vote down vote up
def create_random_text(strs,slen,alpha):
    '''
    Create strs number of strings with length of slen 
    Use pareto distribution to pull randomly from 4 different groups 
    if Alpha is large (>10) get almost 100% letters, 
    if Alpha is smaller (1..5) get mixture of letters, numbers and special chars
    See https://en.wikipedia.org/wiki/Pareto_distribution
    '''
    s = []
    chrs = sorted(list(Morsecode))
    groups =[[29,55],[12,22],[0,11],[55,60]] #letters 29-55, numbers 12-22
    for i in range(strs):
        for j in range(slen):
            val = paretovariate(alpha)-1 #pareto distribution 
            gn = int((val, 3)[val > 3])  # select the group characters are pulled from
            s += chrs[randrange(groups[gn][0],groups[gn][1])] #select random char from group 
        s += ' '
    return ''.join(s) 
Example #2
Source Project: slicesim   Author: cerob   File: __main__.py    License: MIT License 6 votes vote down vote up
def get_dist(d):
    return {
        'randrange': random.randrange, # start, stop, step
        'randint': random.randint, # a, b
        'random': random.random,
        'uniform': random, # a, b
        'triangular': random.triangular, # low, high, mode
        'beta': random.betavariate, # alpha, beta
        'expo': random.expovariate, # lambda
        'gamma': random.gammavariate, # alpha, beta
        'gauss': random.gauss, # mu, sigma
        'lognorm': random.lognormvariate, # mu, sigma
        'normal': random.normalvariate, # mu, sigma
        'vonmises': random.vonmisesvariate, # mu, kappa
        'pareto': random.paretovariate, # alpha
        'weibull': random.weibullvariate # alpha, beta
    }.get(d) 
Example #3
Source Project: aiopg   Author: aio-libs   File: sa.py    License: BSD 2-Clause "Simplified" License 5 votes vote down vote up
def fill_data(conn):
    async with conn.begin():
        for name in random.sample(names, len(names)):
            uid = await conn.scalar(
                users.insert().values(name=name, birthday=gen_birthday()))
            emails_count = int(random.paretovariate(2))
            for num in random.sample(range(10000), emails_count):
                is_private = random.uniform(0, 1) < 0.8
                await conn.execute(emails.insert().values(
                    user_id=uid,
                    email='{}+{}@gmail.com'.format(name, num),
                    private=is_private)) 
Example #4
Source Project: qgisSpaceSyntaxToolkit   Author: SpaceGroupUCL   File: random_sequence.py    License: GNU General Public License v3.0 5 votes vote down vote up
def pareto_sequence(n,exponent=1.0):
    """
    Return sample sequence of length n from a Pareto distribution.
    """
    return [random.paretovariate(exponent) for i in range(n)] 
Example #5
Source Project: qgisSpaceSyntaxToolkit   Author: SpaceGroupUCL   File: random_sequence.py    License: GNU General Public License v3.0 5 votes vote down vote up
def powerlaw_sequence(n,exponent=2.0):
    """
    Return sample sequence of length n from a power law distribution.
    """
    return [random.paretovariate(exponent-1) for i in range(n)] 
Example #6
Source Project: aws-kube-codesuite   Author: aws-samples   File: random_sequence.py    License: Apache License 2.0 5 votes vote down vote up
def powerlaw_sequence(n, exponent=2.0):
    """
    Return sample sequence of length n from a power law distribution.
    """
    return [random.paretovariate(exponent - 1) for i in range(n)]