Question

i have two 1D numpy arrays. The lengths are unequal. I want to make pairs (array1_elemnt,array2_element) of the elements which are close to each other. Lets consider following example

    a = [1,2,3,8,20,23]
    b = [1,2,3,5,7,21,35]

The expected result is

    [(1,1), 
    (2,2), 
    (3,3), 
    (8,7),
    (20,21),
    (23,25)]

It is important to note that 5 is left alone. It could easily be done by loops but I have very large arrays. I considered using nearest neighbor. But felt like killing a sparrow with a canon.

Can anybody please suggest any elegant solution.

Thanks a lot.

Answer 1

You could use the built in map function to vectorize a function that does this. For example:

ar1 = np.array([1,2,3,8,20,23])
ar2 = np.array([1,2,3,5,7,21,35])
def closest(ar1, ar2, iter):
    x = np.abs(ar1[iter] - ar2)
    index = np.where(x==x.min())
    value = ar2[index]
    return value

def find(x):
    return closest(ar1, ar2, x)
c = np.array(map(find, range(ar1.shape[0])))

In the example above, it looked like you wanted to exclude values once they had been paired. In that case, you could include a removal process in the first function like this, but be very careful about how array 1 is sorted:

 def closest(ar1, ar2, iter):
    x = np.abs(ar1[iter] - ar2)
    index = np.where(x==x.min())
    value = ar2[index]
    ar2[ar2==value] = -10000000
    return value