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""" |
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======================== |
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Random Number Generation |
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======================== |
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Use ``default_rng()`` to create a `Generator` and call its methods. |
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=============== ========================================================= |
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Generator |
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--------------- --------------------------------------------------------- |
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Generator Class implementing all of the random number distributions |
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default_rng Default constructor for ``Generator`` |
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=============== ========================================================= |
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============================================= === |
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BitGenerator Streams that work with Generator |
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--------------------------------------------- --- |
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MT19937 |
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PCG64 |
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PCG64DXSM |
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Philox |
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SFC64 |
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============================================= === |
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============================================= === |
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Getting entropy to initialize a BitGenerator |
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--------------------------------------------- --- |
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SeedSequence |
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============================================= === |
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Legacy |
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------ |
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For backwards compatibility with previous versions of numpy before 1.17, the |
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various aliases to the global `RandomState` methods are left alone and do not |
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use the new `Generator` API. |
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==================== ========================================================= |
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Utility functions |
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-------------------- --------------------------------------------------------- |
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random Uniformly distributed floats over ``[0, 1)`` |
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bytes Uniformly distributed random bytes. |
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permutation Randomly permute a sequence / generate a random sequence. |
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shuffle Randomly permute a sequence in place. |
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choice Random sample from 1-D array. |
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==================== ========================================================= |
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==================== ========================================================= |
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Compatibility |
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functions - removed |
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in the new API |
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-------------------- --------------------------------------------------------- |
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rand Uniformly distributed values. |
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randn Normally distributed values. |
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ranf Uniformly distributed floating point numbers. |
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random_integers Uniformly distributed integers in a given range. |
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(deprecated, use ``integers(..., closed=True)`` instead) |
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random_sample Alias for `random_sample` |
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randint Uniformly distributed integers in a given range |
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seed Seed the legacy random number generator. |
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==================== ========================================================= |
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==================== ========================================================= |
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Univariate |
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distributions |
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-------------------- --------------------------------------------------------- |
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beta Beta distribution over ``[0, 1]``. |
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binomial Binomial distribution. |
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chisquare :math:`\\chi^2` distribution. |
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exponential Exponential distribution. |
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f F (Fisher-Snedecor) distribution. |
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gamma Gamma distribution. |
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geometric Geometric distribution. |
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gumbel Gumbel distribution. |
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hypergeometric Hypergeometric distribution. |
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laplace Laplace distribution. |
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logistic Logistic distribution. |
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lognormal Log-normal distribution. |
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logseries Logarithmic series distribution. |
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negative_binomial Negative binomial distribution. |
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noncentral_chisquare Non-central chi-square distribution. |
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noncentral_f Non-central F distribution. |
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normal Normal / Gaussian distribution. |
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pareto Pareto distribution. |
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poisson Poisson distribution. |
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power Power distribution. |
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rayleigh Rayleigh distribution. |
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triangular Triangular distribution. |
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uniform Uniform distribution. |
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vonmises Von Mises circular distribution. |
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wald Wald (inverse Gaussian) distribution. |
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weibull Weibull distribution. |
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zipf Zipf's distribution over ranked data. |
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==================== ========================================================= |
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==================== ========================================================== |
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Multivariate |
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distributions |
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-------------------- ---------------------------------------------------------- |
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dirichlet Multivariate generalization of Beta distribution. |
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multinomial Multivariate generalization of the binomial distribution. |
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multivariate_normal Multivariate generalization of the normal distribution. |
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==================== ========================================================== |
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==================== ========================================================= |
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Standard |
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distributions |
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-------------------- --------------------------------------------------------- |
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standard_cauchy Standard Cauchy-Lorentz distribution. |
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standard_exponential Standard exponential distribution. |
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standard_gamma Standard Gamma distribution. |
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standard_normal Standard normal distribution. |
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standard_t Standard Student's t-distribution. |
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==================== ========================================================= |
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==================== ========================================================= |
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Internal functions |
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-------------------- --------------------------------------------------------- |
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get_state Get tuple representing internal state of generator. |
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set_state Set state of generator. |
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==================== ========================================================= |
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""" |
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__all__ = [ |
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'beta', |
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'binomial', |
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'bytes', |
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'chisquare', |
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'choice', |
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'dirichlet', |
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'exponential', |
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'f', |
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'gamma', |
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'geometric', |
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'get_state', |
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'gumbel', |
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'hypergeometric', |
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'laplace', |
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'logistic', |
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'lognormal', |
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'logseries', |
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'multinomial', |
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'multivariate_normal', |
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'negative_binomial', |
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'noncentral_chisquare', |
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'noncentral_f', |
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'normal', |
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'pareto', |
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'permutation', |
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'poisson', |
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'power', |
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'rand', |
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'randint', |
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'randn', |
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'random', |
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'random_integers', |
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'random_sample', |
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'ranf', |
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'rayleigh', |
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'sample', |
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'seed', |
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'set_state', |
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'shuffle', |
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'standard_cauchy', |
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'standard_exponential', |
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'standard_gamma', |
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'standard_normal', |
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'standard_t', |
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'triangular', |
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'uniform', |
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'vonmises', |
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'wald', |
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'weibull', |
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'zipf', |
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] |
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from . import _pickle |
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from . import _common |
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from . import _bounded_integers |
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from ._generator import Generator, default_rng |
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from .bit_generator import SeedSequence, BitGenerator |
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from ._mt19937 import MT19937 |
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from ._pcg64 import PCG64, PCG64DXSM |
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from ._philox import Philox |
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from ._sfc64 import SFC64 |
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from .mtrand import * |
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__all__ += ['Generator', 'RandomState', 'SeedSequence', 'MT19937', |
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'Philox', 'PCG64', 'PCG64DXSM', 'SFC64', 'default_rng', |
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'BitGenerator'] |
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def __RandomState_ctor(): |
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"""Return a RandomState instance. |
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This function exists solely to assist (un)pickling. |
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Note that the state of the RandomState returned here is irrelevant, as this |
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function's entire purpose is to return a newly allocated RandomState whose |
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state pickle can set. Consequently the RandomState returned by this function |
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is a freshly allocated copy with a seed=0. |
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See https://github.com/numpy/numpy/issues/4763 for a detailed discussion |
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""" |
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return RandomState(seed=0) |
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from numpy._pytesttester import PytestTester |
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test = PytestTester(__name__) |
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del PytestTester |
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