Calculate the number of items in a vector that appear at the same index in each vector, with the same value. 
```python
   vector_affinity([1, 2, 3, 4, 5], [1, 2, 2, 4, 3]) # => 0.6
   vector_affinity([1, 2, 3], [1, 2, 3]) # => 1.0
```
Affinity value should be realized on a scale of 0.0 to 1.0, with 1.0 being absolutely identical. Two identical sets should always be evaulated as having an affinity or 1.0.
Hint: The last example test case holds a significant clue to calculating the affinity correctly.
def vector_affinity(a, b):
    return 1.0 if a == b else sum(1 for (m, n) in zip(a, b) if m == n) / max(len(a), len(b))
def vector_affinity(a, b):
    return 1.0 if a == b else sum(1 for (m, n) in zip(a, b) if m == n) / max(len(a), len(b))