Selecting a subset of an array based on values in another array with upper and lower bounds

Question

I have two arrays, and I want to select a section of one of them based on values of the other. I know how to do this in a few lines, but I want to know if there is a neater way, in one line, to do this. This is how I do it which is long and ugly.

lower = some_value; upper = another_value
a = [some numpy array]; b = [another numpy array]
b_select = []
for i in range(len(a)):
    if a[i] < lower or a[i] > upper:
        b_select.append(b[i])

So basically my question is, can I get b_select in one line, instead of the last 4 lines?

Any advice would be much appreciated. For info I am doing this in Python 2.7.

Divakar · Accepted Answer · 2019-04-18 07:19:45Z

8

The stated problem is looking to select values that are outside the bounds set by lower and upper bounds. To solve it, we can use boolean indexing -

b[(a < lower) | (a > upper)]

The other scenario to select within the lower and upper bounds, invert the process -

b[(a > lower) & (a < upper)]

To have inclusiveness on the bounds, replace <'s with <= and >'s with >=.

edited Apr 18, 2019 at 7:19

answered Nov 8, 2016 at 16:12

Divakar

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Comments

K. Odie · Accepted Answer · 2016-11-08 16:45:51Z

0

Unless numpy has some strange arrays this should work:

b_select = [x for x in a if (x < lower or x > upper)]

answered Nov 8, 2016 at 16:45

K. Odie

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