def randint(low, high=None, size=None):
"""
Return random integers from low (inclusive) to high (exclusive).
Return random integers from the “discrete uniform” distribution of the specified dtype in the “half-open”
interval [low, high). If high is None (the default), then results are from [0, low).
:param low: (*int*) Lowest (signed) integer to be drawn from the distribution (unless high=None, in which
case this parameter is one above the highest such integer).
:param high: (*int*) If provided, one above the largest (signed) integer to be drawn from the distribution
(see above for behavior if high=None).
:param size: (*int or tuple*) Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples
are drawn. Default is None, in which case a single value is returned.
:returns: (*int or array*) Random integer array.
"""
if high is None:
high = low
low = 0
else:
high = high - low
if size is None:
r = RandomUtil.randint(high)
r += low
else:
r = NDArray(RandomUtil.randint(high, size))
if low != 0:
r += low
return r
def poisson(lam=1.0, size=None):
"""
Draw samples from a Poisson distribution.
:param lam: (*float*) Expectation of interval, should be >= 0.
:param size: (*int or tuple*) Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples
are drawn. Default is None, in which case a single value is returned.
:returns: (*float or array*) Drawn samples from the parameterized Poisson distribution.
"""
if size is None:
r = RandomUtil.poisson(lam)
else:
r = NDArray(RandomUtil.poisson(lam, size))
return r
def random(size=None):
"""
Random values in a given shape.
Create an array of the given shape and propagate it with random samples from a uniform
distribution over [0, 1).
:param size: (*int or tuple*) Output shape. If the given shape is, e.g., (m, n, k), then m * n * k samples
are drawn. Default is None, in which case a single value is returned.
:returns: Random values array.
"""
if size is None:
return RandomUtil.rand()
else:
return NDArray(RandomUtil.rand(size))
def randn(*args):
"""
Return a sample (or samples) from the “standard normal” distribution.
Create an array of the given shape and propagate it with random samples from a "normal"
(Gaussian) distribution of mean 0 and variance 1.
:param d0, d1, ..., dn: (*int*) optional. The dimensions of the returned array, should all
be positive. If no argument is given a single Python float is returned.
:returns: Random values array.
"""
if len(args) == 0:
return RandomUtil.randn()
elif len(args) == 1:
return NDArray(RandomUtil.randn(args[0]))
else:
return NDArray(RandomUtil.randn(args))
def rand(*args):
"""
Random values in a given shape.
Create an array of the given shape and propagate it with random samples from a uniform
distribution over [0, 1).
:param d0, d1, ..., dn: (*int*) optional. The dimensions of the returned array, should all
be positive. If no argument is given a single Python float is returned.
:returns: Random values array.
"""
if len(args) == 0:
return RandomUtil.rand()
elif len(args) == 1:
return NDArray(RandomUtil.rand(args[0]))
else:
return NDArray(RandomUtil.rand(args))