Say I have two numpy array's, for example:

arr1 = np.array([[0,1],[0,2],[1,2],[2,3]])

and

arr2 = np.array([[0,1],[1,2]])

What I want now is a function that compares the rows of arr1 with the rows of arr2 and outputs a list of the following shape

[True,False,True,False]

Where the first and second to last place are true since they represent a row in arr1 that also appears in arr2.

I tried using numpy.isin(arr1,arr2) however that gives an array of shape arr1 with the elements of arr1 compared with the elements arr2.

Thanks in advance.

CodePudding user response：

You can use broadcasting:

(arr1==arr2[:,None]).all(2).any(0)

output: array([ True, False, True, False])

explanation:

• expand arr2 to an extra dimension:arr2[:,None]
• compare element-wise
• are all values True on the last dimension? (i.e, [0,1]==[0,1] needs to be [True, True])
• is any of those aggregates True? (one of [0,1]==[0,1] (True) or [0,1]!=[0,2] (False) is sufficient)