def poisson(lam=1.0, size=None):
'''Return dataset of given shape (or a single number) with samples taken
from a Poisson distribution of parameter lam
'''
if size is None:
return _random.poisson(lam, [1]).getObject([0])
return _random.poisson(lam, _asiter(size))
def exponential(scale=1.0, size=None):
'''Return dataset of given shape (or a single number) with samples taken
from an exponential distribution of parameter scale
'''
if size is None:
return _random.exponential(scale, [1]).getObject([0])
return _random.exponential(scale, _asiter(size))
def poisson(lam=1.0, size=None):
'''Return dataset of given shape (or a single number) with samples taken
from a Poisson distribution of parameter lam
'''
if size is None:
return _random.poisson(lam, [1]).getObject([0])
return _random.poisson(lam, _asiter(size))
def exponential(scale=1.0, size=None):
'''Return dataset of given shape (or a single number) with samples taken
from an exponential distribution of parameter scale
'''
if size is None:
return _random.exponential(scale, [1]).getObject([0])
return _random.exponential(scale, _asiter(size))
def random_integers(low, high=None, size=None):
'''Return dataset of given shape (or a single number) with samples taken
from a discrete distribution of integers in the range [low, high]
'''
if high is None:
high = low
low = 0
if size is None:
return _random.random_integers(low, high, [1]).getObject([0])
return _random.random_integers(low, high, _asiter(size))
def random_integers(low, high=None, size=None):
'''Return dataset of given shape (or a single number) with samples taken
from a discrete distribution of integers in the range [low, high]
'''
if high is None:
high = low
low = 0
if size is None:
return _random.random_integers(low, high, [1]).getObject([0])
return _random.random_integers(low, high, _asiter(size))