Most efficient way of deleting elements from an np array using a condition

Question

I have a numpy array as of right now that looks something like:

A =  [  [5, 8, 6, 2], 
        [5, 8, 6, 2], 
        [...], ...       ]

Let's say I have another 1D numpy array, that looks something like array B, but has at values that correspond to each of the lists inside A.

B = [0.4, 0.6, 0.3, ...]

Now I want to delete any list within the list that has a corresponding value within B that is greater than 0.5 (this could be represented by a variable named thresh). The resulting array should look like (since the second list had a greater value):

C =  [  [5, 8, 6, 2], 
        [...], ...       ]

I am looking for a good numpy based/ pythonic way of achieving this. I am aware of np.delete, but do not understand how to use it here with a condition.

BENY · Accepted Answer · 2019-06-19 01:29:34Z

1

How about condition Boolean slice

A[B<0.5]
Out[197]: 
array([[5, 8, 6, 2],
       [1, 1, 1, 1]])

answered Jun 19, 2019 at 1:29

BENY

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3 Comments

SDG Over a year ago

Cool solution! But is there a numpy way of doing this?

SDG Over a year ago

I tried A[B<thresh] and I got boolean index did not match indexed array along dimension 0;

BENY Over a year ago

@SharanDuggirala is A and B have same len ? , print len(A) and len(B)

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