check for identical rows in different numpy arrays

Question

how do I get a row-wise comparison between two arrays, in the result of a row-wise true/false array?

Given datas:

a = np.array([[1,0],[2,0],[3,1],[         


        

Answer 1

a = np.array([[1,0],[2,0],[3,1],[4,2]])
b = np.array([[1,0],[2,0],[4,2]])

i = 0
j = 0
result = []

We can take advantage of the fact that they are sorted and do this in O(n) time. Using two pointers we just move ahead the pointer that has gotten behind:

while i < len(a) and j < len(b):
    if tuple(a[i])== tuple(b[j]):
        result.append(True)
        i += 1
        j += 1 # get rid of this depending on how you want to handle duplicates
    elif tuple(a[i]) > tuple(b[j]):
        j += 1
    else:
        result.append(False)
        i += 1

Pad with False if it ends early.

if len(result) < len(a):
    result.extend([False] * (len(a) - len(result)))

print(result) # [True, True, False, True]

This answer is adapted from Better way to find matches in two sorted lists than using for loops? (Java)