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- import numpy as np
- import numpy.typing as npt
- AR_f8: npt.NDArray[np.float64] = np.array([1.0])
- AR_i4 = np.array([1], dtype=np.int32)
- AR_u1 = np.array([1], dtype=np.uint8)
- AR_LIKE_f = [1.5]
- AR_LIKE_i = [1]
- b_f8 = np.broadcast(AR_f8)
- b_i4_f8_f8 = np.broadcast(AR_i4, AR_f8, AR_f8)
- next(b_f8)
- b_f8.reset()
- b_f8.index
- b_f8.iters
- b_f8.nd
- b_f8.ndim
- b_f8.numiter
- b_f8.shape
- b_f8.size
- next(b_i4_f8_f8)
- b_i4_f8_f8.reset()
- b_i4_f8_f8.ndim
- b_i4_f8_f8.index
- b_i4_f8_f8.iters
- b_i4_f8_f8.nd
- b_i4_f8_f8.numiter
- b_i4_f8_f8.shape
- b_i4_f8_f8.size
- np.inner(AR_f8, AR_i4)
- np.where([True, True, False])
- np.where([True, True, False], 1, 0)
- np.lexsort([0, 1, 2])
- np.can_cast(np.dtype("i8"), int)
- np.can_cast(AR_f8, "f8")
- np.can_cast(AR_f8, np.complex128, casting="unsafe")
- np.min_scalar_type([1])
- np.min_scalar_type(AR_f8)
- np.result_type(int, AR_i4)
- np.result_type(AR_f8, AR_u1)
- np.result_type(AR_f8, np.complex128)
- np.dot(AR_LIKE_f, AR_i4)
- np.dot(AR_u1, 1)
- np.dot(1.5j, 1)
- np.dot(AR_u1, 1, out=AR_f8)
- np.vdot(AR_LIKE_f, AR_i4)
- np.vdot(AR_u1, 1)
- np.vdot(1.5j, 1)
- np.bincount(AR_i4)
- np.copyto(AR_f8, [1.6])
- np.putmask(AR_f8, [True], 1.5)
- np.packbits(AR_i4)
- np.packbits(AR_u1)
- np.unpackbits(AR_u1)
- np.shares_memory(1, 2)
- np.shares_memory(AR_f8, AR_f8, max_work=1)
- np.may_share_memory(1, 2)
- np.may_share_memory(AR_f8, AR_f8, max_work=1)
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