对于1-D return condition? this.function1(): this.function2();
数组numpy，我认为a和np.sum(a)是等效函数，但我只做了一个简单的实验，似乎后者总是快一点：
a.sum()为什么会有区别？
这是否意味着我们应该始终使用In [1]: import numpy as np
In [2]: a = np.arange(10000)
In [3]: %timeit np.sum(a)
The slowest run took 16.85 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, best of 3: 6.46 µs per loop
In [4]: %timeit a.sum()
The slowest run took 19.80 times longer than the fastest. This could mean that an intermediate result is being cached.
100000 loops, best of 3: 5.25 µs per loop
，numpy.ndarray，sum等函数的mean版本？
答案 0 :(得分：2)
我认为它是因为np.sum()而类似需要首先将输入显式转换为 {{ 3}}在确定ndarray（使用np.asanyarray）ndarray.sum方法之前，允许对列表，元组等进行操作。
另一方面，ndarray.sum()是ndarray类的一种方法，因此无需进行任何检查。