Given a numpy array:
x = np.array([False, True, True, False, False, False, False, False, True, False])
How do I find the number of times the values transitions from False to True? For the above example, the answer would be 2. I don't want to include transitions from True to False in the count.
From the answers to How do I identify sequences of values in a boolean array?, the following produces the indices at which the values are about to change, which is not what I want as this includes True-False transitions.
np.argwhere(np.diff(x)).squeeze()
# [0 2 7 8]
I know that this can be done by looping through the array, however I was wondering if there was a faster way to do this?