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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
20PCG64DXSM
21Philox
22SFC64
23============================================= ===
25============================================= ===
26Getting entropy to initialize a BitGenerator
27--------------------------------------------- ---
28SeedSequence
29============================================= ===
32Legacy
33------
35For backwards compatibility with previous versions of numpy before 1.17, the
36various aliases to the global `RandomState` methods are left alone and do not
37use the new `Generator` API.
39==================== =========================================================
40Utility functions
41-------------------- ---------------------------------------------------------
42random Uniformly distributed floats over ``[0, 1)``
43bytes Uniformly distributed random bytes.
44permutation Randomly permute a sequence / generate a random sequence.
45shuffle Randomly permute a sequence in place.
46choice Random sample from 1-D array.
47==================== =========================================================
49==================== =========================================================
50Compatibility
51functions - removed
52in the new API
53-------------------- ---------------------------------------------------------
54rand Uniformly distributed values.
55randn Normally distributed values.
56ranf Uniformly distributed floating point numbers.
57random_integers Uniformly distributed integers in a given range.
58 (deprecated, use ``integers(..., closed=True)`` instead)
59random_sample Alias for `random_sample`
60randint Uniformly distributed integers in a given range
61seed Seed the legacy random number generator.
62==================== =========================================================
64==================== =========================================================
65Univariate
66distributions
67-------------------- ---------------------------------------------------------
68beta Beta distribution over ``[0, 1]``.
69binomial Binomial distribution.
70chisquare :math:`\\chi^2` distribution.
71exponential Exponential distribution.
72f F (Fisher-Snedecor) distribution.
73gamma Gamma distribution.
74geometric Geometric distribution.
75gumbel Gumbel distribution.
76hypergeometric Hypergeometric distribution.
77laplace Laplace distribution.
78logistic Logistic distribution.
79lognormal Log-normal distribution.
80logseries Logarithmic series distribution.
81negative_binomial Negative binomial distribution.
82noncentral_chisquare Non-central chi-square distribution.
83noncentral_f Non-central F distribution.
84normal Normal / Gaussian distribution.
85pareto Pareto distribution.
86poisson Poisson distribution.
87power Power distribution.
88rayleigh Rayleigh distribution.
89triangular Triangular distribution.
90uniform Uniform distribution.
91vonmises Von Mises circular distribution.
92wald Wald (inverse Gaussian) distribution.
93weibull Weibull distribution.
94zipf Zipf's distribution over ranked data.
95==================== =========================================================
97==================== ==========================================================
98Multivariate
99distributions
100-------------------- ----------------------------------------------------------
101dirichlet Multivariate generalization of Beta distribution.
102multinomial Multivariate generalization of the binomial distribution.
103multivariate_normal Multivariate generalization of the normal distribution.
104==================== ==========================================================
106==================== =========================================================
107Standard
108distributions
109-------------------- ---------------------------------------------------------
110standard_cauchy Standard Cauchy-Lorentz distribution.
111standard_exponential Standard exponential distribution.
112standard_gamma Standard Gamma distribution.
113standard_normal Standard normal distribution.
114standard_t Standard Student's t-distribution.
115==================== =========================================================
117==================== =========================================================
118Internal functions
119-------------------- ---------------------------------------------------------
120get_state Get tuple representing internal state of generator.
121set_state Set state of generator.
122==================== =========================================================
125"""
126__all__ = [
127 'beta',
128 'binomial',
129 'bytes',
130 'chisquare',
131 'choice',
132 'dirichlet',
133 'exponential',
134 'f',
135 'gamma',
136 'geometric',
137 'get_state',
138 'gumbel',
139 'hypergeometric',
140 'laplace',
141 'logistic',
142 'lognormal',
143 'logseries',
144 'multinomial',
145 'multivariate_normal',
146 'negative_binomial',
147 'noncentral_chisquare',
148 'noncentral_f',
149 'normal',
150 'pareto',
151 'permutation',
152 'poisson',
153 'power',
154 'rand',
155 'randint',
156 'randn',
157 'random',
158 'random_integers',
159 'random_sample',
160 'ranf',
161 'rayleigh',
162 'sample',
163 'seed',
164 'set_state',
165 'shuffle',
166 'standard_cauchy',
167 'standard_exponential',
168 'standard_gamma',
169 'standard_normal',
170 'standard_t',
171 'triangular',
172 'uniform',
173 'vonmises',
174 'wald',
175 'weibull',
176 'zipf',
177]
179# add these for module-freeze analysis (like PyInstaller)
180from . import _pickle
181from . import _common
182from . import _bounded_integers
184from ._generator import Generator, default_rng
185from .bit_generator import SeedSequence, BitGenerator
186from ._mt19937 import MT19937
187from ._pcg64 import PCG64, PCG64DXSM
188from ._philox import Philox
189from ._sfc64 import SFC64
190from .mtrand import *
192__all__ += ['Generator', 'RandomState', 'SeedSequence', 'MT19937',
193 'Philox', 'PCG64', 'PCG64DXSM', 'SFC64', 'default_rng',
194 'BitGenerator']
197def __RandomState_ctor():
198 """Return a RandomState instance.
200 This function exists solely to assist (un)pickling.
202 Note that the state of the RandomState returned here is irrelevant, as this
203 function's entire purpose is to return a newly allocated RandomState whose
204 state pickle can set. Consequently the RandomState returned by this function
205 is a freshly allocated copy with a seed=0.
207 See https://github.com/numpy/numpy/issues/4763 for a detailed discussion
209 """
210 return RandomState(seed=0)
213from numpy._pytesttester import PytestTester
214test = PytestTester(__name__)
215del PytestTester