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projecten1/lib/python3.6/site-packages/numpy/random/__init__.py

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+"""
+========================
+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
+
+# To get sub-modules
+from .info import __doc__, __all__
+
+
+with warnings.catch_warnings():
+    warnings.filterwarnings("ignore", message="numpy.ndarray size changed")
+    from .mtrand import *
+
+# Some aliases:
+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 _numpy_tester
+test = _numpy_tester().test
+bench = _numpy_tester().bench