numpy自除的意外行为 [英] Unexpected behavior for numpy self division

问题描述

def f(x):
    x=x/5.
    return x
def g(x):
    x/=5.
    return x

x_var = np.arange(5,dtype=np.double)
f(x_var)
print x_var
g(x_var)
print x_var

Output:
[ 0.  1.  2.  3.  4.]
[ 0.   0.2  0.4  0.6  0.8]

这种行为对我来说有点奇怪，我一直以为x / = 5。等于x = x / 5。 。但显然g（x）函数不会使用/ =操作创建新的引用。有人可以为此提供解释吗？

This behavior is a little bit strange to me, I always thought x/=5. was equivalent to x=x/5. . But clearly the g(x) function does not create a new reference with /= operation. Could anyone offer an explanation for this?

推荐答案

我一直认为x / = 5。等价于x = x / 5

I always thought x/=5. was equivalent to x=x/5

就是这样，除非该类覆盖了 __ idiv __ 运算符，就像 numpy.ndarray 一样。
numpy.ndarray 会覆盖它以就地修改数组，这很好，因为当不需要复制时，它避免了创建数组的新副本。如您所料，它还会覆盖其余的 __ i * __ 运算符。

It is, unless the class overrides the __idiv__ operator, like numpy.ndarray does. numpy.ndarray overrides it to modify the array in-place, which is good because it avoids creating a new copy of the array, when copying is not required. As you can guess, it also overrides the rest of the __i*__ operators.

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