I know that I can use index expressions to filter a numpy array as shown in this SO answer.
>>> b = a[a>threshold]
But, what if I need the logical condition to be based on a field of the array to be filtered? e.g. with:
>>> arr = np.arange(12).reshape((3, 4))
>>> arr
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
When I try to do a similar filter based on the 3rd field/column:
>>> b = arr[arr[2]>0]
I get an error
Traceback (most recent call last):
File "", line 1, in
IndexError: boolean index did not match indexed array along dimension 0; dimension is 3 but corresponding boolean dimension is 4
I can't get the filtered array. What I need is the same result of the following list comprehension:
[r for r in aa if r[2] > 0]
with
aa = [[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]]
What is the right way to filter based on a field/column?
