How to filter a numpy array using a condition in python

Question

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))

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?

Your indenting is a bit strange

Mateen Ulhaq
– Mateen Ulhaq

2018-02-11 23:21:43 +00:00
Commented Feb 11, 2018 at 23:21 — Mateen Ulhaq
– Mateen Ulhaq, Commented Feb 11, 2018 at 23:21
What about v[v > 1]?

Mateen Ulhaq
– Mateen Ulhaq

2018-02-11 23:24:32 +00:00
Commented Feb 11, 2018 at 23:24 — Mateen Ulhaq
– Mateen Ulhaq, Commented Feb 11, 2018 at 23:24
@MateenUlhaq Edited the question.

J Cena
– J Cena

2018-02-11 23:28:45 +00:00
Commented Feb 11, 2018 at 23:28 — J Cena
– J Cena, Commented Feb 11, 2018 at 23:28

Mateen Ulhaq · Accepted Answer · 2018-02-11 23:28:21Z

4

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

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

answered Feb 11, 2018 at 23:28

Mateen Ulhaq

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