Bin edges from unequally-spaced centers

For unequal spacing of centers, the algorithm
https://github.com/astropy/specutils/blob/57dd2b28e5122e00e28333043192d30ec9f78a9d/specutils/spectra/spectral_axis.py#L45
produces bins where some bin center locations don't match the input.

This seems potentially problematic, or at least misleading. Maybe a warning should be raised?

#### Examples

Including https://github.com/astropy/specutils/issues/176#issue-318981747

```python
def edges_from_centers(centers):
a = np.insert(centers, 0, 2*centers[0] - centers[1])
b = np.append(centers, 2*centers[-1] - centers[-2])
edges = (a + b) / 2

return edges

cases = [
np.r_[1.0, 2.0, 3.0, 4.0], # ok (equally spaced)
np.r_[1.0, 2.0, 2.3, 3.0],
np.r_[1, 2, 4, 6, 8, 9, 10],
]

for case in cases:
edges = edges_from_centers(case)
print(" input centers:", " "*3 + "".join(f"{x:<6}" for x in case))
print(" computed edges:", "".join(f"{x:<6}" for x in edges))
print("implied centers:", " "*3 + "".join(f"{x:<6}" for x in (edges[:-1] + edges[1:])/2))
print()
```
Output:
```
input centers: 1.0 2.0 3.0 4.0
computed edges: 0.5 1.5 2.5 3.5 4.5
implied centers: 1.0 2.0 3.0 4.0

input centers: 1.0 2.0 2.3 3.0
computed edges: 0.5 1.5 2.15 2.65 3.35
implied centers: 1.0 1.825 2.4 3.0

input centers: 1 2 4 6 8 9 10
computed edges: 0.5 1.5 3.0 5.0 7.0 8.5 9.5 10.5
implied centers: 1.0 2.25 4.0 6.0 7.75 9.0 10.0
```

Start with the bin-edge calculation at specutils/spectra/spectral_axis.py#L45 and reproduce the unequal-spacing examples from the issue. Establish the expected handling for mismatched implied centers, then add regression coverage for the demonstrated cases and verify the chosen behavior.

Written by the indexing model from the issue text.