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| author | Kevin Sheppard <kevin.k.sheppard@gmail.com> | 2021-02-12 16:31:19 +0000 |
|---|---|---|
| committer | Kevin Sheppard <kevin.k.sheppard@gmail.com> | 2021-02-13 22:58:12 +0000 |
| commit | 6b30f484dd0b22f65f07901f378c422ff1036092 (patch) | |
| tree | cf3a7724550904475f2eb449e7a48b51c7a78a1f /numpy | |
| parent | 5296a1a8f5fa2465610d38fa81297c18464ecf72 (diff) | |
| download | numpy-6b30f484dd0b22f65f07901f378c422ff1036092.tar.gz | |
ENH: Fix additional missed types
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/random/_generator.pyi | 25 |
1 files changed, 17 insertions, 8 deletions
diff --git a/numpy/random/_generator.pyi b/numpy/random/_generator.pyi index dcd761e24..cb326ce76 100644 --- a/numpy/random/_generator.pyi +++ b/numpy/random/_generator.pyi @@ -92,11 +92,13 @@ class Generator: size: Optional[_ShapeLike] = ..., dtype: Union[_DTypeLikeFloat32, _DTypeLikeFloat64] = ..., out: Optional[ndarray[Any, dtype[Union[float32, float64]]]] = ..., - ): ... + ) -> Union[float, ndarray[Any, dtype[Union[float32, float64]]]]: ... def beta( self, a: _ArrayLikeFloat_co, b: _ArrayLikeFloat_co, size: Optional[_ShapeLike] = ... - ): ... - def exponential(self, scale: _ArrayLikeFloat_co = ..., size: Optional[_ShapeLike] = ...): ... + ) -> Union[float, ndarray[Any, dtype[float64]]]: ... + def exponential( + self, scale: _ArrayLikeFloat_co = ..., size: Optional[_ShapeLike] = ... + ) -> Union[float, ndarray[Any, dtype[float64]]]: ... def integers( self, low: _ArrayLikeInt_co, @@ -159,9 +161,16 @@ class Generator: def noncentral_chisquare( self, df: _ArrayLikeFloat_co, nonc: _ArrayLikeFloat_co, size: Optional[_ShapeLike] = ... ) -> Union[float, ndarray[Any, dtype[float64]]]: ... + @overload + def standard_t(self, df: float, size: None = ...) -> float: ... # type: ignore[misc] + @overload def standard_t( - self, df: _ArrayLikeFloat_co, size: Optional[_ShapeLike] = ... - ) -> Union[float, ndarray[Any, dtype[float64]]]: ... + self, df: _ArrayLikeFloat_co, size: None = ... + ) -> ndarray[Any, dtype[float64]]: ... + @overload + def standard_t( + self, df: _ArrayLikeFloat_co, size: _ShapeLike = ... + ) -> ndarray[Any, dtype[float64]]: ... def vonmises( self, mu: _ArrayLikeFloat_co, kappa: _ArrayLikeFloat_co, size: Optional[_ShapeLike] = ... ) -> Union[float, ndarray[Any, dtype[float64]]]: ... @@ -250,17 +259,17 @@ class Generator: tol: float = ..., *, method: Literal["svd", "eigh", "cholesky"] = ... - ): ... + ) -> ndarray[Any, dtype[float64]]: ... def multinomial( self, n: _ArrayLikeInt_co, pvals: _ArrayLikeFloat_co, size: Optional[_ShapeLike] = ... - ): ... + ) -> ndarray[Any, dtype[int64]]: ... def multivariate_hypergeometric( self, colors: _ArrayLikeInt_co, nsample: int, size: Optional[_ShapeLike] = ..., method: Literal["marginals", "count"] = ..., - ): ... + ) -> ndarray[Any, dtype[int64]]: ... def dirichlet( self, alpha: _ArrayLikeFloat_co, size: Optional[_ShapeLike] = ... ) -> ndarray[Any, dtype[float64]]: ... |