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"level": 0, "target": null }, "see_also": [], "signature": null, "references": null, "qa": "numpy.random", "arbitrary": [ { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "Use " }, { "__type": "InlineCode", "__tag": 4051, "value": "default_rng()" }, { "__type": "Text", "__tag": 4046, "value": " to create a " }, { "__type": "CrossRef", "__tag": 4002, "value": "Generator", "reference": { "__type": "LocalRef", "__tag": 4022, "kind": "module", "path": "numpy.random._generator:Generator" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " and call its methods." } ] }, { "__type": "Code", "__tag": 4050, "value": "=============== =========================================================\nGenerator\n--------------- ---------------------------------------------------------\nGenerator Class implementing all of the random number distributions\ndefault_rng Default constructor for ``Generator``\n=============== =========================================================", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "============================================= ===\nBitGenerator Streams that work with Generator\n--------------------------------------------- ---\nMT19937\nPCG64\nPCG64DXSM\nPhilox\nSFC64\n============================================= ===", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "============================================= ===\nGetting entropy to initialize a BitGenerator\n--------------------------------------------- ---\nSeedSequence\n============================================= ===", "execution_status": null } ], "title": [ { "__type": "Text", "__tag": 4046, "value": "Random Number Generation" } ], "level": 0, "target": null }, { "__type": "Section", "__tag": 4015, "children": [ { "__type": "Paragraph", "__tag": 4045, "children": [ { "__type": "Text", "__tag": 4046, "value": "For backwards compatibility with previous versions of numpy before 1.17, the various aliases to the global " }, { "__type": "CrossRef", "__tag": 4002, "value": "RandomState", "reference": { "__type": "LocalRef", "__tag": 4022, "kind": "module", "path": "numpy.random.mtrand:RandomState" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " methods are left alone and do not use the new " }, { "__type": "CrossRef", "__tag": 4002, "value": "Generator", "reference": { "__type": "LocalRef", "__tag": 4022, "kind": "module", "path": "numpy.random._generator:Generator" }, "kind": "module" }, { "__type": "Text", "__tag": 4046, "value": " API." } ] }, { "__type": "Code", "__tag": 4050, "value": "==================== =========================================================\nUtility functions\n-------------------- ---------------------------------------------------------\nrandom Uniformly distributed floats over ``[0, 1)``\nbytes Uniformly distributed random bytes.\npermutation Randomly permute a sequence / generate a random sequence.\nshuffle Randomly permute a sequence in place.\nchoice Random sample from 1-D array.\n==================== =========================================================", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "==================== =========================================================\nCompatibility\nfunctions - removed\nin the new API\n-------------------- ---------------------------------------------------------\nrand Uniformly distributed values.\nrandn Normally distributed values.\nranf Uniformly distributed floating point numbers.\nrandom_integers Uniformly distributed integers in a given range.\n (deprecated, use ``integers(..., closed=True)`` instead)\nrandom_sample Alias for `random_sample`\nrandint Uniformly distributed integers in a given range\nseed Seed the legacy random number generator.\n==================== =========================================================", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "==================== =========================================================\nUnivariate\ndistributions\n-------------------- ---------------------------------------------------------\nbeta Beta distribution over ``[0, 1]``.\nbinomial Binomial distribution.\nchisquare :math:`\\chi^2` distribution.\nexponential Exponential distribution.\nf F (Fisher-Snedecor) distribution.\ngamma Gamma distribution.\ngeometric Geometric distribution.\ngumbel Gumbel distribution.\nhypergeometric Hypergeometric distribution.\nlaplace Laplace distribution.\nlogistic Logistic distribution.\nlognormal Log-normal distribution.\nlogseries Logarithmic series distribution.\nnegative_binomial Negative binomial distribution.\nnoncentral_chisquare Non-central chi-square distribution.\nnoncentral_f Non-central F distribution.\nnormal Normal / Gaussian distribution.\npareto Pareto distribution.\npoisson Poisson distribution.\npower Power distribution.\nrayleigh Rayleigh distribution.\ntriangular Triangular distribution.\nuniform Uniform distribution.\nvonmises Von Mises circular distribution.\nwald Wald (inverse Gaussian) distribution.\nweibull Weibull distribution.\nzipf Zipf's distribution over ranked data.\n==================== =========================================================", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "==================== ==========================================================\nMultivariate\ndistributions\n-------------------- ----------------------------------------------------------\ndirichlet Multivariate generalization of Beta distribution.\nmultinomial Multivariate generalization of the binomial distribution.\nmultivariate_normal Multivariate generalization of the normal distribution.\n==================== ==========================================================", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "==================== =========================================================\nStandard\ndistributions\n-------------------- ---------------------------------------------------------\nstandard_cauchy Standard Cauchy-Lorentz distribution.\nstandard_exponential Standard exponential distribution.\nstandard_gamma Standard Gamma distribution.\nstandard_normal Standard normal distribution.\nstandard_t Standard Student's t-distribution.\n==================== =========================================================", "execution_status": null }, { "__type": "Code", "__tag": 4050, "value": "==================== =========================================================\nInternal functions\n-------------------- ---------------------------------------------------------\nget_state Get tuple representing internal state of generator.\nset_state Set state of generator.\n==================== =========================================================", "execution_status": null } ], "title": [ { "__type": "Text", "__tag": 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