73 lines
3.2 KiB
Python
73 lines
3.2 KiB
Python
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from typing import Any, TypeVar
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import numpy as np
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import numpy.typing as npt
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_SCT = TypeVar("_SCT", bound=np.generic)
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def func1(ar: npt.NDArray[_SCT], a: int) -> npt.NDArray[_SCT]:
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pass
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def func2(ar: npt.NDArray[np.number[Any]], a: str) -> npt.NDArray[np.float64]:
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pass
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AR_b: npt.NDArray[np.bool_]
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AR_u: npt.NDArray[np.uint64]
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AR_i: npt.NDArray[np.int64]
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AR_f: npt.NDArray[np.float64]
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AR_c: npt.NDArray[np.complex128]
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AR_O: npt.NDArray[np.object_]
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AR_LIKE_b: list[bool]
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reveal_type(np.fliplr(AR_b)) # E: ndarray[Any, dtype[bool_]]
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reveal_type(np.fliplr(AR_LIKE_b)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.flipud(AR_b)) # E: ndarray[Any, dtype[bool_]]
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reveal_type(np.flipud(AR_LIKE_b)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.eye(10)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.eye(10, M=20, dtype=np.int64)) # E: ndarray[Any, dtype[{int64}]]
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reveal_type(np.eye(10, k=2, dtype=int)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.diag(AR_b)) # E: ndarray[Any, dtype[bool_]]
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reveal_type(np.diag(AR_LIKE_b, k=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.diagflat(AR_b)) # E: ndarray[Any, dtype[bool_]]
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reveal_type(np.diagflat(AR_LIKE_b, k=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.tri(10)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.tri(10, M=20, dtype=np.int64)) # E: ndarray[Any, dtype[{int64}]]
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reveal_type(np.tri(10, k=2, dtype=int)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.tril(AR_b)) # E: ndarray[Any, dtype[bool_]]
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reveal_type(np.tril(AR_LIKE_b, k=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.triu(AR_b)) # E: ndarray[Any, dtype[bool_]]
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reveal_type(np.triu(AR_LIKE_b, k=0)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.vander(AR_b)) # E: ndarray[Any, dtype[signedinteger[Any]]]
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reveal_type(np.vander(AR_u)) # E: ndarray[Any, dtype[signedinteger[Any]]]
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reveal_type(np.vander(AR_i, N=2)) # E: ndarray[Any, dtype[signedinteger[Any]]]
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reveal_type(np.vander(AR_f, increasing=True)) # E: ndarray[Any, dtype[floating[Any]]]
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reveal_type(np.vander(AR_c)) # E: ndarray[Any, dtype[complexfloating[Any, Any]]]
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reveal_type(np.vander(AR_O)) # E: ndarray[Any, dtype[object_]]
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reveal_type(np.histogram2d(AR_i, AR_b)) # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[floating[Any]]], ndarray[Any, dtype[floating[Any]]]]
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reveal_type(np.histogram2d(AR_f, AR_f)) # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[floating[Any]]], ndarray[Any, dtype[floating[Any]]]]
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reveal_type(np.histogram2d(AR_f, AR_c, weights=AR_LIKE_b)) # E: Tuple[ndarray[Any, dtype[{float64}]], ndarray[Any, dtype[complexfloating[Any, Any]]], ndarray[Any, dtype[complexfloating[Any, Any]]]]
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reveal_type(np.mask_indices(10, func1)) # E: Tuple[ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
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reveal_type(np.mask_indices(8, func2, "0")) # E: Tuple[ndarray[Any, dtype[{intp}]], ndarray[Any, dtype[{intp}]]]
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reveal_type(np.tril_indices(10)) # E: Tuple[ndarray[Any, dtype[{int_}]], ndarray[Any, dtype[{int_}]]]
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reveal_type(np.tril_indices_from(AR_b)) # E: Tuple[ndarray[Any, dtype[{int_}]], ndarray[Any, dtype[{int_}]]]
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reveal_type(np.triu_indices(10)) # E: Tuple[ndarray[Any, dtype[{int_}]], ndarray[Any, dtype[{int_}]]]
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reveal_type(np.triu_indices_from(AR_b)) # E: Tuple[ndarray[Any, dtype[{int_}]], ndarray[Any, dtype[{int_}]]]
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