如何在python中使用条件过滤numpy数组 [英] How to filter a numpy array using a condition in python

问题描述

我正在如下使用我的numpy数组v来删除< = 1的元素，然后选择numpy数组中前3个元素的索引.

I am using my numpy array v as follows to remove elements that are <=1 and then select the indexes of the top 3 elements in the numpy array.

 for ele in v.toarray()[0].tolist():
        if ele <= 1:
            useless_index = v.toarray()[0].tolist().index(ele)
            temp_list.append(useless_index)

 #take top 3 words from each document
 indexes =v.toarray()[0].argsort()[-3:]
 useful_list = list(set(indexes) - set(temp_list))

但是，我正在使用的当前代码非常慢(因为我有数百万个numpy数组)并且需要几天的时间才能运行.有什么有效的方法可以在python中做同样的事情?

However, the current code I am using is very slow (as I have millions of numpy arrays) and take days to run. Is there any efficient way of doing the same thing in python?

推荐答案

v = v[v > 1]
indices = np.argpartition(v, -3)[-3:]
values = v[indices]

如此处所述，argpartition在O(n + k log k)时间运行.您的情况是n = 1e6，k=3.

As mentioned here, argpartition runs in O(n + k log k) time. In your case, n = 1e6, k=3.

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