merge_asof(left_index=True, right_on=...) overwrites left index with right index
Building from an example in the docs...
```
left = pd.DataFrame({'left_val': ['a', 'b', 'c'], 'left_time': [1, 5, 10]}, index=[1, 5, 10])
right = pd.DataFrame({'right_val': [1, 2, 3, 6, 7]}, index=[1, 2, 3, 6, 7])
```

```
>>> pd.merge_asof(left, right, left_index=True, right_index=True)
   left_val  left_time  right_val
1         a          1          1
5         b          5          3
10        c         10          7
```
Returned index is the index of left.

```
>>> pd.merge_asof(left, right, left_on='left_time', right_index=True)
   left_val  left_time  right_val
1         a          1          1
5         b          5          3
10        c         10          7
```
Returned index is the index of left.

```
>>> pd.merge_asof(left, right, left_on='left_time', right_on='right_val')
  left_val  left_time  right_val
0        a          1          1
1        b          5          3
2        c         10          7
```
Return value has index reset (I assume expected?)

```
>>> pd.merge_asof(left, right, left_index=True, right_on='right_val')
  left_val  left_time  right_val
1        a          1          1
3        b          5          3
7        c         10          7
```
Returned index is the index of _right_.

Perhaps I'm misunderstanding something about how this is supposed to work, but it seems to me that the behavior in the last example is incorrect.