Matplotlib has a large number of circular references (between figure and
manager, between axes and figure, axes and artist, figure and canvas, and ...)
so when the user drops their last reference to a `Figure` (and clears it from
pyplot's state), the objects will not immediately deleted.

To account for this we have long (goes back to
e34a333 the "reorganize code" commit in 2004
which is the end of history for much of the code) had a `gc.collect()` in the
close logic in order to promptly clean up after our selves.

However, unconditionally calling `gc.collect` and be a major performance
issue (see matplotlib#3044 and
matplotlib#3045) because if there are a
large number of long-lived user objects Python will spend a lot of time
checking objects that are not going away are never going away.

Instead of doing a full collection we switched to clearing out the lowest two
generations.  However this both not doing what we want (as most of our objects
will actually survive) and due to clearing out the first generation opened us
up to having unbounded memory usage.

In cases with a very tight loop between creating the figure and destroying
it (e.g. `plt.figure(); plt.close()`) the first generation will never grow
large enough for Python to consider running the collection on the higher
generations.  This will lead to un-bounded memory usage as the long-lived
objects are never re-considered to look for reference cycles and hence are
never deleted because their reference counts will never go to zero.

closes matplotlib#23701

Matplotlib has a large number of circular references (between figure and
manager, between axes and figure, axes and artist, figure and canvas, and ...)
so when the user drops their last reference to a `Figure` (and clears it from
pyplot's state), the objects will not immediately deleted.

To account for this we have long (goes back to
e34a333 the "reorganize code" commit in 2004
which is the end of history for much of the code) had a `gc.collect()` in the
close logic in order to promptly clean up after our selves.

However, unconditionally calling `gc.collect` and be a major performance
issue (see matplotlib#3044 and
matplotlib#3045) because if there are a
large number of long-lived user objects Python will spend a lot of time
checking objects that are not going away are never going away.

Instead of doing a full collection we switched to clearing out the lowest two
generations.  However this both not doing what we want (as most of our objects
will actually survive) and due to clearing out the first generation opened us
up to having unbounded memory usage.

In cases with a very tight loop between creating the figure and destroying
it (e.g. `plt.figure(); plt.close()`) the first generation will never grow
large enough for Python to consider running the collection on the higher
generations.  This will lead to un-bounded memory usage as the long-lived
objects are never re-considered to look for reference cycles and hence are
never deleted because their reference counts will never go to zero.

closes matplotlib#23701