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139 lines
2.4 KiB
139 lines
2.4 KiB
import sys
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from typing import List, Any
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import numpy as np
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class Index:
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def __index__(self) -> int:
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return 0
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class SubClass(np.ndarray):
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pass
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def func(i: int, j: int, **kwargs: Any) -> SubClass:
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return B
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i8 = np.int64(1)
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A = np.array([1])
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B = A.view(SubClass).copy()
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B_stack = np.array([[1], [1]]).view(SubClass)
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C = [1]
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if sys.version_info >= (3, 8):
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np.ndarray(Index())
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np.ndarray([Index()])
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np.array(1, dtype=float)
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np.array(1, copy=False)
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np.array(1, order='F')
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np.array(1, order=None)
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np.array(1, subok=True)
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np.array(1, ndmin=3)
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np.array(1, str, copy=True, order='C', subok=False, ndmin=2)
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np.asarray(A)
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np.asarray(B)
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np.asarray(C)
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np.asanyarray(A)
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np.asanyarray(B)
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np.asanyarray(B, dtype=int)
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np.asanyarray(C)
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np.ascontiguousarray(A)
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np.ascontiguousarray(B)
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np.ascontiguousarray(C)
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np.asfortranarray(A)
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np.asfortranarray(B)
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np.asfortranarray(C)
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np.require(A)
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np.require(B)
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np.require(B, dtype=int)
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np.require(B, requirements=None)
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np.require(B, requirements="E")
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np.require(B, requirements=["ENSUREARRAY"])
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np.require(B, requirements={"F", "E"})
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np.require(B, requirements=["C", "OWNDATA"])
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np.require(B, requirements="W")
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np.require(B, requirements="A")
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np.require(C)
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np.linspace(0, 2)
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np.linspace(0.5, [0, 1, 2])
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np.linspace([0, 1, 2], 3)
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np.linspace(0j, 2)
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np.linspace(0, 2, num=10)
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np.linspace(0, 2, endpoint=True)
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np.linspace(0, 2, retstep=True)
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np.linspace(0j, 2j, retstep=True)
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np.linspace(0, 2, dtype=bool)
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np.linspace([0, 1], [2, 3], axis=Index())
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np.logspace(0, 2, base=2)
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np.logspace(0, 2, base=2)
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np.logspace(0, 2, base=[1j, 2j], num=2)
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np.geomspace(1, 2)
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np.zeros_like(A)
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np.zeros_like(C)
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np.zeros_like(B)
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np.zeros_like(B, dtype=np.int64)
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np.ones_like(A)
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np.ones_like(C)
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np.ones_like(B)
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np.ones_like(B, dtype=np.int64)
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np.empty_like(A)
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np.empty_like(C)
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np.empty_like(B)
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np.empty_like(B, dtype=np.int64)
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np.full_like(A, i8)
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np.full_like(C, i8)
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np.full_like(B, i8)
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np.full_like(B, i8, dtype=np.int64)
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np.ones(1)
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np.ones([1, 1, 1])
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np.full(1, i8)
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np.full([1, 1, 1], i8)
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np.indices([1, 2, 3])
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np.indices([1, 2, 3], sparse=True)
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np.fromfunction(func, (3, 5))
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np.identity(10)
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np.atleast_1d(C)
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np.atleast_1d(A)
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np.atleast_1d(C, C)
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np.atleast_1d(C, A)
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np.atleast_1d(A, A)
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np.atleast_2d(C)
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np.atleast_3d(C)
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np.vstack([C, C])
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np.vstack([C, A])
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np.vstack([A, A])
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np.hstack([C, C])
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np.stack([C, C])
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np.stack([C, C], axis=0)
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np.stack([C, C], out=B_stack)
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np.block([[C, C], [C, C]])
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np.block(A)
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