如何找到数组中匹配元素的索引？

Question

I have two vectors, vector A is (1298,1), Vector B varies in a for loop but is always just a column vector, I am trying to use numpy.where to find the A-indices of the elements in B. Currently I have a for loop combing through Vector B element-wise and using numpy.isclose but I was wondering if anyone knows a quicker function and/or how to do this without a nested for loop? It works but very slowly. The for loops looks like this

sphere_indices=[]
for k in range(len(A)):
    for j in range(len(B)):
         if np.isclose(B[j,0],A[k,0]):
              sphere_indices.append(k) ```

Answer 1

There was never any reason to iterate through the all 1298 elements of vector A, in order to use numpy.where and numpy.isclose I just needed to use the elements in B one at a time so numpy can broadcast properly. The following code runs much faster. Any further improvements are always welcome.

                    for j in range(len(index)):
                        sphere_indices1=np.where(np.isclose(sphere_index[:,0],index[j,0]))
                        sphere_indices.append(sphere_indices1[0])```