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multiarray.py
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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