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numpy.random._generator.py
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numpy.random._generator.py
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from typing import *
class Generator:
@overload
def beta(self, _0: numpy.ndarray, _1: numpy.ndarray, _2: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
@overload
def beta(self, _0: numpy.float64, _1: numpy.float64, _2: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
def beta(
self,
_0: Union[numpy.float64, numpy.ndarray],
_1: Union[numpy.float64, numpy.ndarray],
_2: Tuple[numpy.int64],
/,
):
"""
usage.scipy: 2
"""
...
@overload
def binomial(self, _0: int, _1: numpy.ndarray, _2: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
@overload
def binomial(self, _0: numpy.ndarray, _1: numpy.ndarray, _2: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
def binomial(
self,
_0: Union[numpy.ndarray, int],
_1: numpy.ndarray,
_2: Tuple[numpy.int64],
/,
):
"""
usage.scipy: 2
"""
...
@overload
def chisquare(self, _0: numpy.ndarray, _1: Tuple[numpy.int64], /):
"""
usage.scipy: 2
"""
...
@overload
def chisquare(self, _0: int, /, *, size: numpy.int64):
"""
usage.scipy: 1
"""
...
def chisquare(
self,
_0: Union[int, numpy.ndarray],
_1: Tuple[numpy.int64] = ...,
/,
*,
size: numpy.int64 = ...,
):
"""
usage.scipy: 3
"""
...
@overload
def choice(self, _0: int, /):
"""
usage.scipy: 1
"""
...
@overload
def choice(self, _0: int, /, *, replace: bool, size: int):
"""
usage.scipy: 1
"""
...
@overload
def choice(self, _0: int, /, *, p: numpy.ndarray, size: int):
"""
usage.scipy: 1
"""
...
def choice(
self,
_0: int,
/,
*,
replace: bool = ...,
size: int = ...,
p: numpy.ndarray = ...,
):
"""
usage.scipy: 3
"""
...
def dirichlet(self, _0: numpy.ndarray, /, *, size: int):
"""
usage.scipy: 1
"""
...
def f(self, _0: numpy.ndarray, _1: numpy.ndarray, _2: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
def gamma(self, _0: numpy.ndarray, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
@overload
def geometric(self, _0: numpy.float64, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 3
"""
...
@overload
def geometric(self, _0: numpy.ndarray, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
def geometric(
self, _0: Union[numpy.ndarray, numpy.float64], /, *, size: Tuple[numpy.int64]
):
"""
usage.scipy: 4
"""
...
@overload
def integers(
self,
_0: int,
/,
*,
dtype: Literal["int64"],
endpoint: bool,
high: int,
size: int,
):
"""
usage.scipy: 1
"""
...
@overload
def integers(
self,
_0: int,
/,
*,
dtype: Literal["int64"],
endpoint: bool,
high: None,
size: int,
):
"""
usage.scipy: 1
"""
...
@overload
def integers(
self,
_0: numpy.ndarray,
/,
*,
dtype: Literal["int64"],
endpoint: bool,
high: numpy.ndarray,
size: Tuple[numpy.int64],
):
"""
usage.scipy: 1
"""
...
@overload
def integers(self, _0: int, _1: int, _2: int, /, *, dtype: Type[numpy.int64]):
"""
usage.seaborn: 3
"""
...
def integers(
self,
_0: Union[int, numpy.ndarray],
_1: int = ...,
_2: int = ...,
/,
*,
dtype: Union[Type[numpy.int64], Literal["int64"]],
endpoint: bool = ...,
high: Union[numpy.ndarray, int, None] = ...,
size: Union[Tuple[numpy.int64], int] = ...,
):
"""
usage.scipy: 3
usage.seaborn: 3
"""
...
def laplace(self, _0: int, _1: int, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
def logistic(self, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
def multinomial(self, _0: numpy.ndarray, _1: numpy.ndarray, _2: int, /):
"""
usage.scipy: 1
"""
...
@overload
def multivariate_normal(
self, _0: numpy.ndarray, _1: numpy.ndarray, /, *, size: int
):
"""
usage.scipy: 1
"""
...
@overload
def multivariate_normal(self, _0: numpy.ndarray, _1: numpy.ndarray, _2: int, /):
"""
usage.scipy: 1
"""
...
def multivariate_normal(
self, _0: numpy.ndarray, _1: numpy.ndarray, _2: int = ..., /, *, size: int = ...
):
"""
usage.scipy: 2
"""
...
def negative_binomial(
self, _0: numpy.ndarray, _1: numpy.ndarray, _2: Tuple[numpy.int64], /
):
"""
usage.scipy: 1
"""
...
def noncentral_chisquare(
self, _0: numpy.ndarray, _1: numpy.ndarray, _2: Tuple[numpy.int64], /
):
"""
usage.scipy: 1
"""
...
def noncentral_f(
self,
_0: numpy.ndarray,
_1: numpy.ndarray,
_2: numpy.ndarray,
_3: Tuple[numpy.int64],
/,
):
"""
usage.scipy: 1
"""
...
@overload
def normal(self, /, *, size: Tuple[int, int]):
"""
usage.scipy: 1
"""
...
@overload
def normal(self, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 2
"""
...
@overload
def normal(self, /, *, size: numpy.int64):
"""
usage.scipy: 1
"""
...
@overload
def normal(self, /, *, size: Tuple[int]):
"""
usage.scipy: 2
"""
...
def normal(
self, /, *, size: Union[Tuple[Union[int, numpy.int64], ...], numpy.int64]
):
"""
usage.scipy: 6
"""
...
def permutation(self, _0: range, /):
"""
usage.scipy: 1
"""
...
def poisson(self, _0: numpy.ndarray, _1: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
def shuffle(self, _0: List[int], /):
"""
usage.scipy: 1
"""
...
def standard_exponential(self, _0: Tuple[numpy.int64], /):
"""
usage.scipy: 2
"""
...
@overload
def standard_gamma(self, _0: numpy.ndarray, _1: Tuple[numpy.int64], /):
"""
usage.scipy: 2
"""
...
@overload
def standard_gamma(self, _0: numpy.ndarray, _1: numpy.int64, /):
"""
usage.scipy: 1
"""
...
def standard_gamma(
self, _0: numpy.ndarray, _1: Union[numpy.int64, Tuple[numpy.int64]], /
):
"""
usage.scipy: 3
"""
...
@overload
def standard_normal(self, _0: int, /):
"""
usage.scipy: 1
"""
...
@overload
def standard_normal(self, _0: Tuple[numpy.int64], /):
"""
usage.scipy: 6
"""
...
@overload
def standard_normal(self, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
@overload
def standard_normal(self, _0: numpy.int64, /):
"""
usage.scipy: 1
"""
...
@overload
def standard_normal(self, /, *, size: Tuple[int, numpy.int64]):
"""
usage.scipy: 1
"""
...
def standard_normal(
self,
_0: Union[numpy.int64, int, Tuple[numpy.int64]] = ...,
/,
*,
size: Tuple[Union[numpy.int64, int], ...] = ...,
):
"""
usage.scipy: 10
"""
...
def standard_t(self, _0: numpy.ndarray, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
def triangular(
self, _0: int, _1: numpy.ndarray, _2: int, _3: Tuple[numpy.int64], /
):
"""
usage.scipy: 1
"""
...
@overload
def uniform(self, _0: float, _1: float, _2: Tuple[int], /):
"""
usage.scipy: 1
"""
...
@overload
def uniform(self, /):
"""
usage.scipy: 4
usage.seaborn: 1
"""
...
@overload
def uniform(self, /, *, size: Tuple[int, int]):
"""
usage.scipy: 2
"""
...
@overload
def uniform(self, _0: float, _1: int, /):
"""
usage.scipy: 1
"""
...
@overload
def uniform(self, /, *, size: int):
"""
usage.scipy: 4
"""
...
@overload
def uniform(self, /, *, size: Tuple[int]):
"""
usage.scipy: 1
"""
...
@overload
def uniform(self, _0: numpy.ndarray, _1: numpy.ndarray, /, *, size: int):
"""
usage.scipy: 1
"""
...
@overload
def uniform(self, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 6
"""
...
@overload
def uniform(self, /, *, size: numpy.int64):
"""
usage.scipy: 2
"""
...
@overload
def uniform(self, _0: float, _1: float, _2: Tuple[numpy.int64], /):
"""
usage.scipy: 1
"""
...
def uniform(
self,
/,
*_args: Union[numpy.ndarray, int, float, Tuple[Union[numpy.int64, int]]],
size: Union[numpy.int64, int, Tuple[Union[numpy.int64, int], ...]] = ...,
):
"""
usage.scipy: 23
usage.seaborn: 1
"""
...
@overload
def wald(self, _0: numpy.ndarray, _1: float, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
@overload
def wald(self, _0: float, _1: float, /, *, size: Tuple[numpy.int64]):
"""
usage.scipy: 1
"""
...
def wald(
self, _0: Union[float, numpy.ndarray], _1: float, /, *, size: Tuple[numpy.int64]
):
"""
usage.scipy: 2
"""
...