I have the following np.array:
my_array=np.array([False, False, False, True, True, True, False, True, False, False, False, False, True])
How can I make a list using list comprehension of the indices corresponding to the True elements. In this case the output I'm looking for would be [3,4,5,7,12]
I've tried the following:
cols = [index if feature_condition==True for index, feature_condition in enumerate(my_array)]
But is not working
why specifically a list comprehension?
>>> np.where(my_array==True)
(array([ 3, 4, 5, 7, 12]),)
this does the job and is quicker. The list solution would be:
>>> [index for index, feature_condition in enumerate(my_array) if feature_condition == True]
[3, 4, 5, 7, 12]
Accepted answer of this explains the confusion of the ordering: if/else in a list comprehension
I was curious of the differences:
def np_time(array):
np.where(my_array==True)
def list_time(array):
[index for index, feature_condition in enumerate(my_array) if feature_condition == True]
timeit.timeit(lambda: list_time(my_array),number = 1000)
0.007574789000500459
timeit.timeit(lambda: np_time(my_array),number = 1000)
0.0010812399996211752