|
""" |
|
======================== |
|
Random Number Generation |
|
======================== |
|
|
|
==================== ========================================================= |
|
Utility functions |
|
============================================================================== |
|
random Uniformly distributed values of a given shape. |
|
bytes Uniformly distributed random bytes. |
|
random_integers Uniformly distributed integers in a given range. |
|
random_sample Uniformly distributed floats in a given range. |
|
random Alias for random_sample |
|
ranf Alias for random_sample |
|
sample Alias for random_sample |
|
choice Generate a weighted random sample from a given array-like |
|
permutation Randomly permute a sequence / generate a random sequence. |
|
shuffle Randomly permute a sequence in place. |
|
seed Seed the random number generator. |
|
==================== ========================================================= |
|
|
|
==================== ========================================================= |
|
Compatibility functions |
|
============================================================================== |
|
rand Uniformly distributed values. |
|
randn Normally distributed values. |
|
ranf Uniformly distributed floating point numbers. |
|
randint Uniformly distributed integers in a given range. |
|
==================== ========================================================= |
|
|
|
==================== ========================================================= |
|
Univariate distributions |
|
============================================================================== |
|
beta Beta distribution over ``[0, 1]``. |
|
binomial Binomial distribution. |
|
chisquare :math:`\\chi^2` distribution. |
|
exponential Exponential distribution. |
|
f F (Fisher-Snedecor) distribution. |
|
gamma Gamma distribution. |
|
geometric Geometric distribution. |
|
gumbel Gumbel distribution. |
|
hypergeometric Hypergeometric distribution. |
|
laplace Laplace distribution. |
|
logistic Logistic distribution. |
|
lognormal Log-normal distribution. |
|
logseries Logarithmic series distribution. |
|
negative_binomial Negative binomial distribution. |
|
noncentral_chisquare Non-central chi-square distribution. |
|
noncentral_f Non-central F distribution. |
|
normal Normal / Gaussian distribution. |
|
pareto Pareto distribution. |
|
poisson Poisson distribution. |
|
power Power distribution. |
|
rayleigh Rayleigh distribution. |
|
triangular Triangular distribution. |
|
uniform Uniform distribution. |
|
vonmises Von Mises circular distribution. |
|
wald Wald (inverse Gaussian) distribution. |
|
weibull Weibull distribution. |
|
zipf Zipf's distribution over ranked data. |
|
==================== ========================================================= |
|
|
|
==================== ========================================================= |
|
Multivariate distributions |
|
============================================================================== |
|
dirichlet Multivariate generalization of Beta distribution. |
|
multinomial Multivariate generalization of the binomial distribution. |
|
multivariate_normal Multivariate generalization of the normal distribution. |
|
==================== ========================================================= |
|
|
|
==================== ========================================================= |
|
Standard distributions |
|
============================================================================== |
|
standard_cauchy Standard Cauchy-Lorentz distribution. |
|
standard_exponential Standard exponential distribution. |
|
standard_gamma Standard Gamma distribution. |
|
standard_normal Standard normal distribution. |
|
standard_t Standard Student's t-distribution. |
|
==================== ========================================================= |
|
|
|
==================== ========================================================= |
|
Internal functions |
|
============================================================================== |
|
get_state Get tuple representing internal state of generator. |
|
set_state Set state of generator. |
|
==================== ========================================================= |
|
|
|
""" |
|
from __future__ import division, absolute_import, print_function |
|
|
|
import warnings |
|
|
|
|
|
from .info import __doc__, __all__ |
|
|
|
|
|
with warnings.catch_warnings(): |
|
warnings.filterwarnings("ignore", message="numpy.ndarray size changed") |
|
from .mtrand import * |
|
|
|
|
|
ranf = random = sample = random_sample |
|
__all__.extend(['ranf', 'random', 'sample']) |
|
|
|
def __RandomState_ctor(): |
|
"""Return a RandomState instance. |
|
|
|
This function exists solely to assist (un)pickling. |
|
|
|
Note that the state of the RandomState returned here is irrelevant, as this function's |
|
entire purpose is to return a newly allocated RandomState whose state pickle can set. |
|
Consequently the RandomState returned by this function is a freshly allocated copy |
|
with a seed=0. |
|
|
|
See https://github.com/numpy/numpy/issues/4763 for a detailed discussion |
|
|
|
""" |
|
return RandomState(seed=0) |
|
|
|
from numpy.testing import Tester |
|
test = Tester().test |
|
bench = Tester().bench |
|
|
