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47 lines
1.0 KiB
47 lines
1.0 KiB
from __future__ import annotations
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from typing import Any
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import numpy as np
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class Object:
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def __ceil__(self) -> Object:
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return self
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def __floor__(self) -> Object:
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return self
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def __ge__(self, value: object) -> bool:
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return True
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def __array__(self) -> np.ndarray[Any, np.dtype[np.object_]]:
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ret = np.empty((), dtype=object)
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ret[()] = self
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return ret
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AR_LIKE_b = [True, True, False]
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AR_LIKE_u = [np.uint32(1), np.uint32(2), np.uint32(3)]
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AR_LIKE_i = [1, 2, 3]
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AR_LIKE_f = [1.0, 2.0, 3.0]
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AR_LIKE_O = [Object(), Object(), Object()]
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AR_U: np.ndarray[Any, np.dtype[np.str_]] = np.zeros(3, dtype="U5")
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np.fix(AR_LIKE_b)
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np.fix(AR_LIKE_u)
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np.fix(AR_LIKE_i)
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np.fix(AR_LIKE_f)
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np.fix(AR_LIKE_O)
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np.fix(AR_LIKE_f, out=AR_U)
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np.isposinf(AR_LIKE_b)
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np.isposinf(AR_LIKE_u)
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np.isposinf(AR_LIKE_i)
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np.isposinf(AR_LIKE_f)
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np.isposinf(AR_LIKE_f, out=AR_U)
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np.isneginf(AR_LIKE_b)
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np.isneginf(AR_LIKE_u)
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np.isneginf(AR_LIKE_i)
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np.isneginf(AR_LIKE_f)
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np.isneginf(AR_LIKE_f, out=AR_U)
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