distance between vectors

v2 = np.loadtxt("myvector2.txt")
def euclidean_dist(vec1,vec2):
    return np.sqrt(np.sum((vec1-vec2)**2))

def find_closest(word_index, vectors):
    min_dist = 100000
    min_index = -1
    query_vector = vectors[word_index]
    for index, vector in enumerate(vectors):
        if euclidean_dist(vector, query_vector)< min_dist and not np.array_equal(vector, query_vector):
            min_dist = euclidean_dist(vector, query_vector)
            min_index = index
    return min_index

print(int2diag[find_closest(diag2int['I63.4'],v2)])
print(int2diag[find_closest(diag2int['F71.1'],v2)])
print(int2diag[find_closest(diag2int['R00.2'],v2)])

euclidean_dist(v2[diag2int['I63.4']],v2[diag2int['S82.9']])