有一个笨拙的biginteger吗? [英] Is there a numpy biginteger?

问题描述

嗯.在我看来，似乎没有办法将python的bigintegers存储在numpy数组中.要声明一个带有bigints的numpy数组，有什么特别的事情吗?

Hmm. There doesn't seem to me a way to store Python's bigintegers in a numpy array. Is there something special you have to do, to declare a numpy array with bigints?

推荐答案

不是特别的，不是.您可以使用dtype='object'创建一个数组，该数组创建一个Python对象数组(包括但不限于ints).这将为您带来许多类似Numpy数组的功能，但几乎没有性能优势.

Not specifically, no. You can create an array with dtype='object', which creates an array of Python objects (including but not limited to ints). This will get you a lot of Numpy array-like functionality but few to none of the performance benefits.

这就是说，Python对象数组在内存性能方面与Python list并无显着差异.尽管如果必须使用bigints，可能仍然比使用list更可取，因为您仍然可以进行按元素进行算术运算，包括使用其他Numpy数组进行运算时.例如:

Which is to say, an array of Python objects is not significantly different from a Python list in terms of memory performance. Though if you must use bigints it may still be preferable to using a list since you still get element-wise arithmetic operations, including when doing operations with other Numpy arrays. For example:

In [1]: import numpy as np

In [2]: big = np.array([10**100, 10**101, 10**102], dtype='object')

In [3]: big
Out[3]: 
array([ 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000,
       100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000,
       1000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000], dtype=object)

In [4]: big + np.array([1, 2, 3])
Out[4]: 
array([ 10000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001,
       100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000002,
       1000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000003], dtype=object)

尽管我自己从未使用过此功能，所以我不确定是否还会出现其他令人惊讶的局限性.

I've never used this capability myself though, so I'm not entirely sure what other surprising limitations might arise.

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