| | """ |
| | ======================== |
| | 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', |
| | ] |
| |
|
| | |
| | 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 |
| |
|
