182 lines
9.1 KiB
Python
182 lines
9.1 KiB
Python
from typing import Any
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import numpy as np
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import numpy.typing as npt
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vectorized_func: np.vectorize
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f8: np.float64
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AR_LIKE_f8: list[float]
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AR_i8: npt.NDArray[np.int64]
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AR_f8: npt.NDArray[np.float64]
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AR_c16: npt.NDArray[np.complex128]
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AR_m: npt.NDArray[np.timedelta64]
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AR_M: npt.NDArray[np.datetime64]
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AR_O: npt.NDArray[np.object_]
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AR_b: npt.NDArray[np.bool_]
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AR_U: npt.NDArray[np.str_]
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CHAR_AR_U: np.chararray[Any, np.dtype[np.str_]]
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def func(*args: Any, **kwargs: Any) -> Any: ...
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reveal_type(vectorized_func.pyfunc) # E: def (*Any, **Any) -> Any
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reveal_type(vectorized_func.cache) # E: bool
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reveal_type(vectorized_func.signature) # E: Union[None, builtins.str]
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reveal_type(vectorized_func.otypes) # E: Union[None, builtins.str]
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reveal_type(vectorized_func.excluded) # E: set[Union[builtins.int, builtins.str]]
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reveal_type(vectorized_func.__doc__) # E: Union[None, builtins.str]
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reveal_type(vectorized_func([1])) # E: Any
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reveal_type(np.vectorize(int)) # E: vectorize
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reveal_type(np.vectorize( # E: vectorize
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int, otypes="i", doc="doc", excluded=(), cache=True, signature=None
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))
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reveal_type(np.add_newdoc("__main__", "blabla", doc="test doc")) # E: None
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reveal_type(np.add_newdoc("__main__", "blabla", doc=("meth", "test doc"))) # E: None
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reveal_type(np.add_newdoc("__main__", "blabla", doc=[("meth", "test doc")])) # E: None
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reveal_type(np.rot90(AR_f8, k=2)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.rot90(AR_LIKE_f8, axes=(0, 1))) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.flip(f8)) # E: {float64}
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reveal_type(np.flip(1.0)) # E: Any
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reveal_type(np.flip(AR_f8, axis=(0, 1))) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.flip(AR_LIKE_f8, axis=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.iterable(1)) # E: bool
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reveal_type(np.iterable([1])) # E: bool
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reveal_type(np.average(AR_f8)) # E: floating[Any]
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reveal_type(np.average(AR_f8, weights=AR_c16)) # E: complexfloating[Any, Any]
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reveal_type(np.average(AR_O)) # E: Any
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reveal_type(np.average(AR_f8, returned=True)) # E: Tuple[floating[Any], floating[Any]]
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reveal_type(np.average(AR_f8, weights=AR_c16, returned=True)) # E: Tuple[complexfloating[Any, Any], complexfloating[Any, Any]]
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reveal_type(np.average(AR_O, returned=True)) # E: Tuple[Any, Any]
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reveal_type(np.average(AR_f8, axis=0)) # E: Any
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reveal_type(np.average(AR_f8, axis=0, returned=True)) # E: Tuple[Any, Any]
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reveal_type(np.asarray_chkfinite(AR_f8)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.asarray_chkfinite(AR_LIKE_f8)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.asarray_chkfinite(AR_f8, dtype=np.float64)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.asarray_chkfinite(AR_f8, dtype=float)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.piecewise(AR_f8, AR_b, [func])) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.piecewise(AR_LIKE_f8, AR_b, [func])) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.select([AR_f8], [AR_f8])) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.copy(AR_LIKE_f8)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.copy(AR_U)) # E: ndarray[Any, dtype[str_]]
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reveal_type(np.copy(CHAR_AR_U)) # E: ndarray[Any, Any]
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reveal_type(np.copy(CHAR_AR_U, "K", subok=True)) # E: chararray[Any, dtype[str_]]
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reveal_type(np.copy(CHAR_AR_U, subok=True)) # E: chararray[Any, dtype[str_]]
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reveal_type(np.gradient(AR_f8, axis=None)) # E: Any
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reveal_type(np.gradient(AR_LIKE_f8, edge_order=2)) # E: Any
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reveal_type(np.diff("bob", n=0)) # E: str
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reveal_type(np.diff(AR_f8, axis=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.diff(AR_LIKE_f8, prepend=1.5)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.angle(f8)) # E: floating[Any]
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reveal_type(np.angle(AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.angle(AR_c16, deg=True)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.angle(AR_O)) # E: ndarray[Any, dtype[object_]]
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reveal_type(np.unwrap(AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.unwrap(AR_O)) # E: ndarray[Any, dtype[object_]]
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reveal_type(np.sort_complex(AR_f8)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.trim_zeros(AR_f8)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.trim_zeros(AR_LIKE_f8)) # E: list[builtins.float]
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reveal_type(np.extract(AR_i8, AR_f8)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.extract(AR_i8, AR_LIKE_f8)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.place(AR_f8, mask=AR_i8, vals=5.0)) # E: None
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reveal_type(np.disp(1, linefeed=True)) # E: None
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with open("test", "w") as f:
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reveal_type(np.disp("message", device=f)) # E: None
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reveal_type(np.cov(AR_f8, bias=True)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.cov(AR_f8, AR_c16, ddof=1)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.cov(AR_f8, aweights=AR_f8, dtype=np.float32)) # E: ndarray[Any, dtype[{float32}]]
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reveal_type(np.cov(AR_f8, fweights=AR_f8, dtype=float)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.corrcoef(AR_f8, rowvar=True)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.corrcoef(AR_f8, AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.corrcoef(AR_f8, dtype=np.float32)) # E: ndarray[Any, dtype[{float32}]]
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reveal_type(np.corrcoef(AR_f8, dtype=float)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.blackman(5)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.bartlett(6)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.hanning(4.5)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.hamming(0)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.i0(AR_i8)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.kaiser(4, 5.9)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.sinc(1.0)) # E: floating[Any]
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reveal_type(np.sinc(1j)) # E: complexfloating[Any, Any]
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reveal_type(np.sinc(AR_f8)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.sinc(AR_c16)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.msort(CHAR_AR_U)) # E: Any
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reveal_type(np.msort(AR_U)) # E: ndarray[Any, dtype[str_]]
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reveal_type(np.msort(AR_LIKE_f8)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.median(AR_f8, keepdims=False)) # E: floating[Any]
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reveal_type(np.median(AR_c16, overwrite_input=True)) # E: complexfloating[Any, Any]
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reveal_type(np.median(AR_m)) # E: timedelta64
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reveal_type(np.median(AR_O)) # E: Any
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reveal_type(np.median(AR_f8, keepdims=True)) # E: Any
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reveal_type(np.median(AR_c16, axis=0)) # E: Any
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reveal_type(np.median(AR_LIKE_f8, out=AR_c16)) # E: ndarray[Any, dtype[{complex128}]]
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reveal_type(np.add_newdoc_ufunc(np.add, "docstring")) # E: None
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reveal_type(np.percentile(AR_f8, 50)) # E: floating[Any]
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reveal_type(np.percentile(AR_c16, 50)) # E: complexfloating[Any, Any]
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reveal_type(np.percentile(AR_m, 50)) # E: timedelta64
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reveal_type(np.percentile(AR_M, 50, overwrite_input=True)) # E: datetime64
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reveal_type(np.percentile(AR_O, 50)) # E: Any
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reveal_type(np.percentile(AR_f8, [50])) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.percentile(AR_c16, [50])) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.percentile(AR_m, [50])) # E: ndarray[Any, dtype[timedelta64]]
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reveal_type(np.percentile(AR_M, [50], method="nearest")) # E: ndarray[Any, dtype[datetime64]]
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reveal_type(np.percentile(AR_O, [50])) # E: ndarray[Any, dtype[object_]]
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reveal_type(np.percentile(AR_f8, [50], keepdims=True)) # E: Any
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reveal_type(np.percentile(AR_f8, [50], axis=[1])) # E: Any
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reveal_type(np.percentile(AR_f8, [50], out=AR_c16)) # E: ndarray[Any, dtype[{complex128}]]
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reveal_type(np.quantile(AR_f8, 0.5)) # E: floating[Any]
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reveal_type(np.quantile(AR_c16, 0.5)) # E: complexfloating[Any, Any]
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reveal_type(np.quantile(AR_m, 0.5)) # E: timedelta64
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reveal_type(np.quantile(AR_M, 0.5, overwrite_input=True)) # E: datetime64
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reveal_type(np.quantile(AR_O, 0.5)) # E: Any
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reveal_type(np.quantile(AR_f8, [0.5])) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.quantile(AR_c16, [0.5])) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.quantile(AR_m, [0.5])) # E: ndarray[Any, dtype[timedelta64]]
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reveal_type(np.quantile(AR_M, [0.5], method="nearest")) # E: ndarray[Any, dtype[datetime64]]
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reveal_type(np.quantile(AR_O, [0.5])) # E: ndarray[Any, dtype[object_]]
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reveal_type(np.quantile(AR_f8, [0.5], keepdims=True)) # E: Any
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reveal_type(np.quantile(AR_f8, [0.5], axis=[1])) # E: Any
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reveal_type(np.quantile(AR_f8, [0.5], out=AR_c16)) # E: ndarray[Any, dtype[{complex128}]]
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reveal_type(np.meshgrid(AR_f8, AR_i8, copy=False)) # E: list[ndarray[Any, dtype[Any]]]
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reveal_type(np.meshgrid(AR_f8, AR_i8, AR_c16, indexing="ij")) # E: list[ndarray[Any, dtype[Any]]]
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reveal_type(np.delete(AR_f8, np.s_[:5])) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.delete(AR_LIKE_f8, [0, 4, 9], axis=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.insert(AR_f8, np.s_[:5], 5)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.insert(AR_LIKE_f8, [0, 4, 9], [0.5, 9.2, 7], axis=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.append(AR_f8, 5)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.append(AR_LIKE_f8, 1j, axis=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.digitize(4.5, [1])) # E: {intp}
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reveal_type(np.digitize(AR_f8, [1, 2, 3])) # E: ndarray[Any, dtype[{intp}]]
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