就地执行numpy exp函数 [英] Perform numpy exp function in-place

问题描述

就像标题中一样，我需要在非常大的ndarray上执行numpy.exp，比如说ar，并将结果存储在ar本身中.可以就地执行此操作吗?

As in title, I need to perform numpy.exp on a very large ndarray, let's say ar, and store the result in ar itself. Can this operation be performed in-place?

推荐答案

您可以使用exp的可选out参数:

You can use the optional outargument of exp:

a = np.array([3.4, 5])
res = np.exp(a, a)
print(res is a)
print(a)

输出:

True
[  29.96410005  148.4131591 ]

exp(x [，out])

exp(x[, out])

计算输入数组中所有元素的指数.

Calculate the exponential of all elements in the input array.

out:ndarray 输出数组，x的按元素指数.

out : ndarray Output array, element-wise exponential of x.

a的所有元素都将替换为exp的结果.返回值res与a相同.没有创建新的数组

Here all elements of a will be replaced by the result of exp. The return value res is the same as a. No new array is created

这篇关于就地执行numpy exp函数的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！