Generator

Standard library class numpy.random.bitgen.Generator View source

class Generator

@tuple

class Generator[G]

Fields 4

lock Lock

bit_generator BitGenerator[G]

G type

T type

Constructors 3

__new__

__new__(g: G)

Defined in numpy.random.bitgen

__new__

@pure @derives @llvm

__new__(ptr: cobj)

Added by internal.types.generator

ret ptr %ptr

__new__

@overload

__new__()

Added by internal.types.generator

Methods 45

spawn

spawn(self, n_children: int)

Defined in numpy.random.bitgen

random

random(self, size = None, dtype: type = float, out = None)

Defined in numpy.random.bitgen

beta

beta(self, a, b, size = None)

Defined in numpy.random.bitgen

exponential

exponential(self, scale = 1.0, size = None)

Defined in numpy.random.bitgen

standard_exponential

standard_exponential(self, size = None, dtype: type = float, method: str = "zig", out = None)

Defined in numpy.random.bitgen

integers

integers(self, low, high = None, size = None, dtype: type = int, endpoint: bool = False)

Defined in numpy.random.bitgen

bytes

bytes(self, length: int)

Defined in numpy.random.bitgen

choice

choice(self, a, size = None, replace: bool = True, p = None, axis: int = 0, shuffle: bool = True)

Defined in numpy.random.bitgen

uniform

uniform(self, low = 0.0, high = 1.0, size = None)

Defined in numpy.random.bitgen

standard_normal

standard_normal(self, size = None, dtype: type = float, out = None)

Defined in numpy.random.bitgen

normal

normal(self, loc = 0.0, scale = 1.0, size = None)

Defined in numpy.random.bitgen

standard_gamma

standard_gamma(self, shape, size = None, dtype: type = float, out = None)

Defined in numpy.random.bitgen

gamma

gamma(self, shape, scale = 1.0, size = None)

Defined in numpy.random.bitgen

f

f(self, dfnum, dfden, size = None)

Defined in numpy.random.bitgen

noncentral_f

noncentral_f(self, dfnum, dfden, nonc, size = None)

Defined in numpy.random.bitgen

chisquare

chisquare(self, df, size = None)

Defined in numpy.random.bitgen

noncentral_chisquare

noncentral_chisquare(self, df, nonc, size = None)

Defined in numpy.random.bitgen

standard_cauchy

standard_cauchy(self, size = None)

Defined in numpy.random.bitgen

standard_t

standard_t(self, df, size = None)

Defined in numpy.random.bitgen

vonmises

vonmises(self, mu, kappa, size = None)

Defined in numpy.random.bitgen

pareto

pareto(self, a, size = None)

Defined in numpy.random.bitgen

weibull

weibull(self, a, size = None)

Defined in numpy.random.bitgen

power

power(self, a, size = None)

Defined in numpy.random.bitgen

laplace

laplace(self, loc = 0.0, scale = 1.0, size = None)

Defined in numpy.random.bitgen

gumbel

gumbel(self, loc = 0.0, scale = 1.0, size = None)

Defined in numpy.random.bitgen

logistic

logistic(self, loc = 0.0, scale = 1.0, size = None)

Defined in numpy.random.bitgen

lognormal

lognormal(self, mean = 0.0, sigma = 1.0, size = None)

Defined in numpy.random.bitgen

rayleigh

rayleigh(self, scale = 1.0, size = None)

Defined in numpy.random.bitgen

wald

wald(self, mean, scale, size = None)

Defined in numpy.random.bitgen

triangular

triangular(self, left, mode, right, size = None)

Defined in numpy.random.bitgen

binomial

binomial(self, n, p, size = None)

Defined in numpy.random.bitgen

negative_binomial

negative_binomial(self, n, p, size = None)

Defined in numpy.random.bitgen

poisson

poisson(self, lam = 1.0, size = None)

Defined in numpy.random.bitgen

zipf

zipf(self, a, size = None)

Defined in numpy.random.bitgen

geometric

geometric(self, p, size = None)

Defined in numpy.random.bitgen

hypergeometric

hypergeometric(self, ngood, nbad, nsample, size = None)

Defined in numpy.random.bitgen

logseries

logseries(self, p, size = None)

Defined in numpy.random.bitgen

multivariate_normal

multivariate_normal(self, mean, cov, size = None, check_valid: Literal[str] = "warn", tol: float = 1e-8, method: Literal[str] = "svd")

Defined in numpy.random.bitgen

multinomial

multinomial(self, n, pvals, size = None)

Defined in numpy.random.bitgen

multivariate_hypergeometric

multivariate_hypergeometric(self, colors, nsample: int, size = None, method: str = "marginals")

Defined in numpy.random.bitgen

dirichlet

dirichlet(self, alpha, size = None)

Defined in numpy.random.bitgen

permuted

permuted(self, x, axis = None, out = None)

Defined in numpy.random.bitgen

shuffle

shuffle(self, x, axis: int = 0)

Defined in numpy.random.bitgen

permutation

permutation(self, x, axis: int = 0)

Defined in numpy.random.bitgen

send

send(self, what: T)

Added by internal.types.generator

Special methods 8

__str__

__str__(self)

Defined in numpy.random.bitgen

__promise__

@__internal__

__promise__(self)

Added by internal.types.generator

__next__

__next__(self: Generator[T])

Added by internal.types.generator

__iter__

__iter__(self)

Added by internal.types.generator

__raw__

@pure @derives @llvm

__raw__(self)

Added by internal.types.generator

ret ptr %self

__done__

@pure @llvm

__done__(self)

Added by internal.types.generator

declare i1 @llvm.coro.done(ptr nocapture readonly)
%0 = call i1 @llvm.coro.done(ptr %self)
%1 = zext i1 %0 to i8
ret i8 %1

__resume__

@nocapture @llvm

__resume__(self)

Added by internal.types.generator

declare void @llvm.coro.resume(ptr)
call void @llvm.coro.resume(ptr %self)
ret {} {}

__repr__

__repr__(self)

Added by internal.types.generator