Python 正在更改Numpy数组子类中的“\uuuu getitem”和“\uuuu setitem”的行为
,但我想修改Python 正在更改Numpy数组子类中的“\uuuu getitem”和“\uuuu setitem”的行为,python,arrays,numpy,getter-setter,Python,Arrays,Numpy,Getter Setter,,但我想修改\uuuu getitem\uuuuuuuu和\uuuuuuu setitem\uuuuuuuuuuu的行为,以便它们可以接受一个日期时间范围,同时保留最大数量的内置机制,如操作、cumsum等。这可以通过\uuuuuu数组\uuuuuuuuunc实现吗 似乎在其中,该方法被重写 这可以用来修改numpy数组的get/set行为吗?在其他情况下,您可以实现\uuu getitem\uuuu和\uuuuu setitem\uuuuu来处理您的特定情况(使用datetime对象),并将其
\uuuu getitem\uuuuuuuu
和\uuuuuuu setitem\uuuuuuuuuuu
的行为,以便它们可以接受一个日期时间范围,同时保留最大数量的内置机制,如操作、cumsum等。这可以通过\uuuuuu数组\uuuuuuuuunc
实现吗
似乎在其中,该方法被重写
这可以用来修改numpy数组的get/set行为吗?在其他情况下,您可以实现
\uuu getitem\uuuu
和\uuuuu setitem\uuuuu
来处理您的特定情况(使用datetime对象),并将其分派到super()。这样,ndarray
的剩余功能将保持不变。例如:
from datetime import date
import numpy as np
class A(np.ndarray):
def __array_finalize__(self, obj):
if obj is not None:
obj.start_date = date.today()
def __getitem__(self, item):
if isinstance(item, slice) and isinstance(item.start, date) and isinstance(item.stop, date):
return super().__getitem__(slice((item.start - self.start_date).days,
(item.stop - self.start_date).days,
item.step))
return super().__getitem__(item)
a = A((10,), buffer=np.arange(10), dtype=int)
print(a[1:8])
print(a[date(2019, 1, 22):date(2019, 1, 29):2])
print(np.cumsum(a))
print(np.add.outer(a, a))
哪些产出:
[1 2 3 4 5 6 7]
[1 3 5 7]
[ 0 1 3 6 10 15 21 28 36 45]
[[ 0 1 2 3 4 5 6 7 8 9]
[ 1 2 3 4 5 6 7 8 9 10]
[ 2 3 4 5 6 7 8 9 10 11]
[ 3 4 5 6 7 8 9 10 11 12]
[ 4 5 6 7 8 9 10 11 12 13]
[ 5 6 7 8 9 10 11 12 13 14]
[ 6 7 8 9 10 11 12 13 14 15]
[ 7 8 9 10 11 12 13 14 15 16]
[ 8 9 10 11 12 13 14 15 16 17]
[ 9 10 11 12 13 14 15 16 17 18]]
好吧,你应该准确地实现\uuu getitem\uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuu
和
,如果你想覆盖它们的。@我的一。只需覆盖\uuuu getitem\uuuuuuuuuu
和\uuuuuuuu setitem\uuuuuuuuuuu
就可以了吗?广播可以被覆盖吗?我希望能够一起广播不同大小的阵列,这样一个分辨率较低的时间序列就可以通过插值进行上采样,然后广播。