You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
216 lines
7.3 KiB
216 lines
7.3 KiB
"""
|
|
========================
|
|
Random Number Generation
|
|
========================
|
|
|
|
Use ``default_rng()`` to create a `Generator` and call its methods.
|
|
|
|
=============== =========================================================
|
|
Generator
|
|
--------------- ---------------------------------------------------------
|
|
Generator Class implementing all of the random number distributions
|
|
default_rng Default constructor for ``Generator``
|
|
=============== =========================================================
|
|
|
|
============================================= ===
|
|
BitGenerator Streams that work with Generator
|
|
--------------------------------------------- ---
|
|
MT19937
|
|
PCG64
|
|
PCG64DXSM
|
|
Philox
|
|
SFC64
|
|
============================================= ===
|
|
|
|
============================================= ===
|
|
Getting entropy to initialize a BitGenerator
|
|
--------------------------------------------- ---
|
|
SeedSequence
|
|
============================================= ===
|
|
|
|
|
|
Legacy
|
|
------
|
|
|
|
For backwards compatibility with previous versions of numpy before 1.17, the
|
|
various aliases to the global `RandomState` methods are left alone and do not
|
|
use the new `Generator` API.
|
|
|
|
==================== =========================================================
|
|
Utility functions
|
|
-------------------- ---------------------------------------------------------
|
|
random Uniformly distributed floats over ``[0, 1)``
|
|
bytes Uniformly distributed random bytes.
|
|
permutation Randomly permute a sequence / generate a random sequence.
|
|
shuffle Randomly permute a sequence in place.
|
|
choice Random sample from 1-D array.
|
|
==================== =========================================================
|
|
|
|
==================== =========================================================
|
|
Compatibility
|
|
functions - removed
|
|
in the new API
|
|
-------------------- ---------------------------------------------------------
|
|
rand Uniformly distributed values.
|
|
randn Normally distributed values.
|
|
ranf Uniformly distributed floating point numbers.
|
|
random_integers Uniformly distributed integers in a given range.
|
|
(deprecated, use ``integers(..., closed=True)`` instead)
|
|
random_sample Alias for `random_sample`
|
|
randint Uniformly distributed integers in a given range
|
|
seed Seed the legacy random number generator.
|
|
==================== =========================================================
|
|
|
|
==================== =========================================================
|
|
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.
|
|
==================== =========================================================
|
|
|
|
|
|
"""
|
|
__all__ = [
|
|
'beta',
|
|
'binomial',
|
|
'bytes',
|
|
'chisquare',
|
|
'choice',
|
|
'dirichlet',
|
|
'exponential',
|
|
'f',
|
|
'gamma',
|
|
'geometric',
|
|
'get_state',
|
|
'gumbel',
|
|
'hypergeometric',
|
|
'laplace',
|
|
'logistic',
|
|
'lognormal',
|
|
'logseries',
|
|
'multinomial',
|
|
'multivariate_normal',
|
|
'negative_binomial',
|
|
'noncentral_chisquare',
|
|
'noncentral_f',
|
|
'normal',
|
|
'pareto',
|
|
'permutation',
|
|
'poisson',
|
|
'power',
|
|
'rand',
|
|
'randint',
|
|
'randn',
|
|
'random',
|
|
'random_integers',
|
|
'random_sample',
|
|
'ranf',
|
|
'rayleigh',
|
|
'sample',
|
|
'seed',
|
|
'set_state',
|
|
'shuffle',
|
|
'standard_cauchy',
|
|
'standard_exponential',
|
|
'standard_gamma',
|
|
'standard_normal',
|
|
'standard_t',
|
|
'triangular',
|
|
'uniform',
|
|
'vonmises',
|
|
'wald',
|
|
'weibull',
|
|
'zipf',
|
|
]
|
|
|
|
# add these for module-freeze analysis (like PyInstaller)
|
|
from . import _pickle
|
|
from . import _common
|
|
from . import _bounded_integers
|
|
|
|
from ._generator import Generator, default_rng
|
|
from .bit_generator import SeedSequence, BitGenerator
|
|
from ._mt19937 import MT19937
|
|
from ._pcg64 import PCG64, PCG64DXSM
|
|
from ._philox import Philox
|
|
from ._sfc64 import SFC64
|
|
from .mtrand import *
|
|
|
|
__all__ += ['Generator', 'RandomState', 'SeedSequence', 'MT19937',
|
|
'Philox', 'PCG64', 'PCG64DXSM', 'SFC64', 'default_rng',
|
|
'BitGenerator']
|
|
|
|
|
|
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._pytesttester import PytestTester
|
|
test = PytestTester(__name__)
|
|
del PytestTester
|