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1"""
2========================
3Random Number Generation
4========================
6Use ``default_rng()`` to create a `Generator` and call its methods.
8=============== =========================================================
9Generator
10--------------- ---------------------------------------------------------
11Generator Class implementing all of the random number distributions
12default_rng Default constructor for ``Generator``
13=============== =========================================================
15============================================= ===
16BitGenerator Streams that work with Generator
17--------------------------------------------- ---
18MT19937
19PCG64
20Philox
21SFC64
22============================================= ===
24============================================= ===
25Getting entropy to initialize a BitGenerator
26--------------------------------------------- ---
27SeedSequence
28============================================= ===
31Legacy
32------
34For backwards compatibility with previous versions of numpy before 1.17, the
35various aliases to the global `RandomState` methods are left alone and do not
36use the new `Generator` API.
38==================== =========================================================
39Utility functions
40-------------------- ---------------------------------------------------------
41random Uniformly distributed floats over ``[0, 1)``
42bytes Uniformly distributed random bytes.
43permutation Randomly permute a sequence / generate a random sequence.
44shuffle Randomly permute a sequence in place.
45choice Random sample from 1-D array.
46==================== =========================================================
48==================== =========================================================
49Compatibility
50functions - removed
51in the new API
52-------------------- ---------------------------------------------------------
53rand Uniformly distributed values.
54randn Normally distributed values.
55ranf Uniformly distributed floating point numbers.
56random_integers Uniformly distributed integers in a given range.
57 (deprecated, use ``integers(..., closed=True)`` instead)
58random_sample Alias for `random_sample`
59randint Uniformly distributed integers in a given range
60seed Seed the legacy random number generator.
61==================== =========================================================
63==================== =========================================================
64Univariate
65distributions
66-------------------- ---------------------------------------------------------
67beta Beta distribution over ``[0, 1]``.
68binomial Binomial distribution.
69chisquare :math:`\\chi^2` distribution.
70exponential Exponential distribution.
71f F (Fisher-Snedecor) distribution.
72gamma Gamma distribution.
73geometric Geometric distribution.
74gumbel Gumbel distribution.
75hypergeometric Hypergeometric distribution.
76laplace Laplace distribution.
77logistic Logistic distribution.
78lognormal Log-normal distribution.
79logseries Logarithmic series distribution.
80negative_binomial Negative binomial distribution.
81noncentral_chisquare Non-central chi-square distribution.
82noncentral_f Non-central F distribution.
83normal Normal / Gaussian distribution.
84pareto Pareto distribution.
85poisson Poisson distribution.
86power Power distribution.
87rayleigh Rayleigh distribution.
88triangular Triangular distribution.
89uniform Uniform distribution.
90vonmises Von Mises circular distribution.
91wald Wald (inverse Gaussian) distribution.
92weibull Weibull distribution.
93zipf Zipf's distribution over ranked data.
94==================== =========================================================
96==================== ==========================================================
97Multivariate
98distributions
99-------------------- ----------------------------------------------------------
100dirichlet Multivariate generalization of Beta distribution.
101multinomial Multivariate generalization of the binomial distribution.
102multivariate_normal Multivariate generalization of the normal distribution.
103==================== ==========================================================
105==================== =========================================================
106Standard
107distributions
108-------------------- ---------------------------------------------------------
109standard_cauchy Standard Cauchy-Lorentz distribution.
110standard_exponential Standard exponential distribution.
111standard_gamma Standard Gamma distribution.
112standard_normal Standard normal distribution.
113standard_t Standard Student's t-distribution.
114==================== =========================================================
116==================== =========================================================
117Internal functions
118-------------------- ---------------------------------------------------------
119get_state Get tuple representing internal state of generator.
120set_state Set state of generator.
121==================== =========================================================
124"""
125__all__ = [
126 'beta',
127 'binomial',
128 'bytes',
129 'chisquare',
130 'choice',
131 'dirichlet',
132 'exponential',
133 'f',
134 'gamma',
135 'geometric',
136 'get_state',
137 'gumbel',
138 'hypergeometric',
139 'laplace',
140 'logistic',
141 'lognormal',
142 'logseries',
143 'multinomial',
144 'multivariate_normal',
145 'negative_binomial',
146 'noncentral_chisquare',
147 'noncentral_f',
148 'normal',
149 'pareto',
150 'permutation',
151 'poisson',
152 'power',
153 'rand',
154 'randint',
155 'randn',
156 'random',
157 'random_integers',
158 'random_sample',
159 'ranf',
160 'rayleigh',
161 'sample',
162 'seed',
163 'set_state',
164 'shuffle',
165 'standard_cauchy',
166 'standard_exponential',
167 'standard_gamma',
168 'standard_normal',
169 'standard_t',
170 'triangular',
171 'uniform',
172 'vonmises',
173 'wald',
174 'weibull',
175 'zipf',
176]
178# add these for module-freeze analysis (like PyInstaller)
179from . import _pickle
180from . import _common
181from . import _bounded_integers
183from ._generator import Generator, default_rng
184from .bit_generator import SeedSequence, BitGenerator
185from ._mt19937 import MT19937
186from ._pcg64 import PCG64
187from ._philox import Philox
188from ._sfc64 import SFC64
189from .mtrand import *
191__all__ += ['Generator', 'RandomState', 'SeedSequence', 'MT19937',
192 'Philox', 'PCG64', 'SFC64', 'default_rng', 'BitGenerator']
195def __RandomState_ctor():
196 """Return a RandomState instance.
198 This function exists solely to assist (un)pickling.
200 Note that the state of the RandomState returned here is irrelevant, as this
201 function's entire purpose is to return a newly allocated RandomState whose
202 state pickle can set. Consequently the RandomState returned by this function
203 is a freshly allocated copy with a seed=0.
205 See https://github.com/numpy/numpy/issues/4763 for a detailed discussion
207 """
208 return RandomState(seed=0)
211from numpy._pytesttester import PytestTester
212test = PytestTester(__name__)
213del PytestTester