Fix bug causing iteration over a 0-d array when numpy.vectorize returns a 0-d array rather than a scalar

Change Summary

This makes the vectorization of spiceypy time functions consistent.

It also fixes a bug that was caused by calling et_to_utc on a 0-d vector. The bug was caused by a 0-d vector being Iterable but not able to be used in list comprehension. This is ultimately due to np.vectorize undesirable behavior of returning a 0-d array instead of a scalar for scalar inputs. I find the fix to be a bit hacky, so if someone has an alternative, cleaner approach, let me know.

Updated Files

• imap_processing/spice/time.py
  • Add the _vectorize method which wraps np.vectorize and returns that result with [()] which converts 0-d vectors to scalars and leaves everything else as is.
  • Use the _vectorize for all functions that were manually vectorizing calls to spiceypy functions.
• imap_processing/tests/spice/test_time.py
  • Add checks that scalar input -> scalar output for vectorized functions.

Closes: #1305