How to truncate a numpy array for values greater than a specified value?

Question

Similar to this Matlab question, I am wondering how to truncate a numpy array by cutting off the values greater than a certain threshold value. The values of the array in question are in ascending order.

import numpy as np
a=np.linspace(1,10,num=10)
truncatevalue = 5.5

How would I produce an array that has the values of a that are less than truncatevalue and would only include those values? In this case, the resulting array would be

a_truncated=([1., 2., 3., 4., 5.])

Bonus: I actually have two arrays I would like to truncate based on the values in one of the arrays.

import numpy as np
a=np.linspace(1,10,num=10)
b=np.array([19, 17, 15, 14, 29, 33, 28, 4, 90, 6])
truncatevalue = 5.5

b is an arbitrary array, I just chose some numbers for a definite example. I would like to truncate b in the same way that a gets truncated, so that the result would be

a_truncated=([1., 2., 3., 4., 5.])
b_truncated=([19, 17, 15, 14, 29])

I don't know if it will be as simple as just repeating what needs to be done to get a_truncated or not, so I wanted to include it as well in case there is something different that needs to be done.

Answer 1

You can use boolean indexing:

>>> a = np.linspace(1, 10, num=10)
>>> truncatevalue = 5.5
>>> a_truncated = a[a < truncatevalue]
>>> a_truncated
array([ 1.,  2.,  3.,  4.,  5.])

Essentially, a < truncatevalue returns a boolean array indicating whether or not the element of a meets the condition. Using this boolean array to index a returns a view of a in which each element's index is True.

So for the second part of your question, all you need to do is this:

>>> b = np.array([19, 17, 15, 14, 29, 33, 28, 4, 90, 6])
>>> b_truncated = b[a < truncatevalue]
>>> b_truncated
array([19, 17, 15, 14, 29])