* Add a test case for OPTICS bug (closes #12134)

* ENH Fix processing order in OPTICS. See #12090

The current code may expand the wrong point, because it only considers
the neighbors of the current point, not all currently unprocessed points
(which may have a better reachability).

Using the distance from the latest point as tiebreaker then does not
work anymore, because it might not yet be computed for all unprocessed
points when using an index.

If we choose the first on ties, we get the same result same as R and ELKI.

But the order of points in "unproc" is also unstable, so we cannot rely
on the first smallest to have the smallest index.

Instead of the cython quick_scan, we now use numpy masked arrays.

* Add a test case for OPTICS bug (closes scikit-learn#12134)

* ENH Fix processing order in OPTICS. See scikit-learn#12090

The current code may expand the wrong point, because it only considers
the neighbors of the current point, not all currently unprocessed points
(which may have a better reachability).

Using the distance from the latest point as tiebreaker then does not
work anymore, because it might not yet be computed for all unprocessed
points when using an index.

If we choose the first on ties, we get the same result same as R and ELKI.

But the order of points in "unproc" is also unstable, so we cannot rely
on the first smallest to have the smallest index.

Instead of the cython quick_scan, we now use numpy masked arrays.

* Add a test case for OPTICS bug (closes scikit-learn#12134)

* ENH Fix processing order in OPTICS. See scikit-learn#12090

The current code may expand the wrong point, because it only considers
the neighbors of the current point, not all currently unprocessed points
(which may have a better reachability).

Using the distance from the latest point as tiebreaker then does not
work anymore, because it might not yet be computed for all unprocessed
points when using an index.

If we choose the first on ties, we get the same result same as R and ELKI.

But the order of points in "unproc" is also unstable, so we cannot rely
on the first smallest to have the smallest index.

Instead of the cython quick_scan, we now use numpy masked arrays.