29 lines
1.5 KiB
Python
29 lines
1.5 KiB
Python
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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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AR_f8: npt.NDArray[np.float64]
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AR_LIKE_f: list[float]
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interface_dict: dict[str, Any]
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reveal_type(np.lib.stride_tricks.DummyArray(interface_dict)) # E: lib.stride_tricks.DummyArray
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reveal_type(np.lib.stride_tricks.as_strided(AR_f8)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.lib.stride_tricks.as_strided(AR_LIKE_f)) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.lib.stride_tricks.as_strided(AR_f8, strides=(1, 5))) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.lib.stride_tricks.as_strided(AR_f8, shape=[9, 20])) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.lib.stride_tricks.sliding_window_view(AR_f8, 5)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.lib.stride_tricks.sliding_window_view(AR_LIKE_f, (1, 5))) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.lib.stride_tricks.sliding_window_view(AR_f8, [9], axis=1)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.broadcast_to(AR_f8, 5)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.broadcast_to(AR_LIKE_f, (1, 5))) # E: ndarray[Any, dtype[Any]]
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reveal_type(np.broadcast_to(AR_f8, [4, 6], subok=True)) # E: ndarray[Any, dtype[{float64}]]
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reveal_type(np.broadcast_shapes((1, 2), [3, 1], (3, 2))) # E: tuple[builtins.int, ...]
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reveal_type(np.broadcast_shapes((6, 7), (5, 6, 1), 7, (5, 1, 7))) # E: tuple[builtins.int, ...]
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reveal_type(np.broadcast_arrays(AR_f8, AR_f8)) # E: list[ndarray[Any, dtype[Any]]]
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reveal_type(np.broadcast_arrays(AR_f8, AR_LIKE_f)) # E: list[ndarray[Any, dtype[Any]]]
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