遍历numpy数组的最快方法是什么 [英] what is the quickest way to iterate through a numpy array

问题描述

我注意到直接"遍历numpy数组与通过tolist方法遍历之间存在有意义的区别.请参阅下面的时间:

I noticed a meaningful difference between iterating through a numpy array "directly" versus iterating through via the tolist method. See timing below:

直接
[i for i in np.arange(10000000)]
通过tolist
[i for i in np.arange(10000000).tolist()]

directly
[i for i in np.arange(10000000)]
via tolist
[i for i in np.arange(10000000).tolist()]

考虑到我发现了一种更快的方法.我想问问还有什么可以使它运行更快?

considering I've discovered one way to go faster. I wanted to ask what else might make it go faster?

什么是最快的遍历numpy数组的方法?

what is fastest way to iterate through a numpy array?

推荐答案

这些是我在速度较慢的计算机上的计时

These are my timings on a slower machine

In [1034]: timeit [i for i in np.arange(10000000)]
1 loop, best of 3: 2.16 s per loop

如果我直接生成范围(Py3，这是一个生成器)，则时间要好得多.以此为基准来理解这种规模的列表.

If I generate the range directly (Py3 so this is a genertor) times are much better. Take this a baseline for a list comprehension of this size.

In [1035]: timeit [i for i in range(10000000)]
1 loop, best of 3: 1.26 s per loop

tolist首先将范围转换为列表；需要更长的时间，但迭代仍在列表中

tolist converts the arange to a list first; takes a bit longer, but the iteration is still on a list

In [1036]: timeit [i for i in np.arange(10000000).tolist()]
1 loop, best of 3: 1.6 s per loop

使用list()-与直接迭代数组相同；这表明直接迭代首先可以做到这一点.

Using list() - same time as direct iteration on the array; that suggests that the direct iteration first does this.

In [1037]: timeit [i for i in list(np.arange(10000000))]
1 loop, best of 3: 2.18 s per loop

In [1038]: timeit np.arange(10000000).tolist()
1 loop, best of 3: 927 ms per loop

在.tolist上重复一次

same times a iterating on the .tolist

In [1039]: timeit list(np.arange(10000000))
1 loop, best of 3: 1.55 s per loop

通常，如果必须循环，则处理列表的速度更快.访问列表元素更简单.

In general if you must loop, working on a list is faster. Access to elements of a list is simpler.

查看通过索引返回的元素.

Look at the elements returned by indexing.

a[0]是另一个numpy对象；它是由a中的值构造的，而不仅仅是获取的值

a[0] is another numpy object; it is constructed from the values in a, but not simply a fetched value

list(a)[0]是相同的类型；列表只是[a[0], a[1], a[2]]]

list(a)[0] is the same type; the list is just [a[0], a[1], a[2]]]

In [1043]: a = np.arange(3)
In [1044]: type(a[0])
Out[1044]: numpy.int32
In [1045]: ll=list(a)
In [1046]: type(ll[0])
Out[1046]: numpy.int32

但是tolist将数组转换为纯列表，在这种情况下为int列表.它比list()做更多的工作，但是是在编译后的代码中完成的.

but tolist converts the array into a pure list, in this case, as list of ints. It does more work than list(), but does it in compiled code.

In [1047]: ll=a.tolist()
In [1048]: type(ll[0])
Out[1048]: int

通常不要使用list(anarray).它很少做任何有用的事情，并且不如tolist()强大.

In general don't use list(anarray). It rarely does anything useful, and is not as powerful as tolist().

迭代数组的最快方法是什么-无.至少不是在Python中；在C代码中有快速的方法.

What's the fastest way to iterate through array - None. At least not in Python; in c code there are fast ways.

a.tolist()是从数组创建列表整数的最快的矢量化方法.它会迭代，但是会在已编译的代码中进行迭代.

a.tolist() is the fastest, vectorized way of creating a list integers from an array. It iterates, but does so in compiled code.

但是您的真正目标是什么?

But what is your real goal?

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