CODEWITHSUNDEEP
pythonnumpy
Danny
Danny

Reputation: 450

numpy indexing comparing two elements

I have a 1D array and I want to compare two sibling elements where the condition where element is greater than a threshold and previous element is less than or equal to threshold. I have a the current solution that loops thru the array comparing which element. Here is a simple example:

t = np.array([1,2,2,2,2,3,5,4,5,3,4,5,6,8,9,7,8,9,10])
threshold = 5
target_index = -1
for index in range(1, len(t)):
    if t[index] > threshold and t[index-1] <= threshold
        target_index = index
        break

I am trying to figure out if there was some type of fancy indexing solution or a faster way of doing this.

Upvotes: 0

Views: 163

Answers (1)

plasmon360
plasmon360

Reputation: 4199

I use roll, logical_and and where to get the index with the desired condition.

t = np.array([1,2,2,2,2,3,5,4,5,3,4,5,6,8,9,7,8,9,10])
threshold = 5

from numpy import logical_and, roll, where

def ops_func(t, threshold):
    target_index = -1
    for index in range(1, len(t)):
        if (t[index] > threshold) and (t[index-1] <= threshold) :
            target_index = index
            break

    return target_index


def myfunc(t, threshold):
    return where(logical_and(t>threshold,roll(t,1)<=threshold))


print ops_func(t,threshold)
# lists the first index which satisfy the desired condition
print ops_func(t,threshold=3)

print myfunc(t, threshold)
# lists all the indices which satisfy the desired condition
print myfunc(t, threshold=3)

%timeit myfunc
%timeit ops_func

results in

12
6
(array([12], dtype=int64),)
(array([ 6, 10], dtype=int64),)
10000000 loops, best of 3: 23.3 ns per loop
100000000 loops, best of 3: 19.5 ns per loop

Upvotes: 1

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