Query's fast standalone - slow as a subquery.

I have a query that runs quite quickly using a hash join when run
standalone.

When I use this query as a subquery the planner always seems to
pick a differnt plan with an order of magnitude worse performance.

This bad plan is chosen even when the outer sql statement is
a trivial expression like this:
select * from (query) as a;
which I believe should be a no-op.

Should the optimizer have noticed that it could have used a hash
join in this case? Anything I can do to help convince it to?

Explain analyze output follows.
Thanks,
Ron

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fli=# explain analyze SELECT * from (select * from userfeatures.points join icons using (iconid) where the_geom && setSRID('BOX3D(-123.40 25.66,-97.87 43.17)'::BOX3D, -1 )) as upf ;
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Nested Loop (cost=0.00..446.42 rows=1 width=120) (actual time=-0.096..7928.546 rows=15743 loops=1)
Join Filter: ("outer".iconid = "inner".iconid)
-> Seq Scan on points (cost=0.00..444.43 rows=1 width=82) (actual time=0.096..132.255 rows=15743 loops=1)
Filter: (the_geom && '010300000001000000050000009A99999999D95EC0295C8FC2F5A839409A99999999D95EC0F6285C8FC295454048E17A14AE7758C0F6285C8FC295454048E17A14AE7758C0295C8FC2F5A839409A99999999D95EC0295C8FC2F5A83940'::geometry)
-> Seq Scan on icons (cost=0.00..1.44 rows=44 width=42) (actual time=0.006..0.242 rows=44 loops=15743)
Total runtime: 8005.766 ms
(6 rows)

fli=# explain analyze select * from userfeatures.points join icons using (iconid) where the_geom && setSRID('BOX3D(-123.40 25.66,-97.87 43.17)'::BOX3D, -1 );
QUERY PLAN
--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Hash Join (cost=1.55..682.84 rows=15789 width=120) (actual time=0.641..320.002 rows=15743 loops=1)
Hash Cond: ("outer".iconid = "inner".iconid)
-> Seq Scan on points (cost=0.00..444.43 rows=15794 width=82) (actual time=0.067..94.307 rows=15743 loops=1)
Filter: (the_geom && '010300000001000000050000009A99999999D95EC0295C8FC2F5A839409A99999999D95EC0F6285C8FC295454048E17A14AE7758C0F6285C8FC295454048E17A14AE7758C0295C8FC2F5A839409A99999999D95EC0295C8FC2F5A83940'::geometry)
-> Hash (cost=1.44..1.44 rows=44 width=42) (actual time=0.530..0.530 rows=0 loops=1)
-> Seq Scan on icons (cost=0.00..1.44 rows=44 width=42) (actual time=0.026..0.287 rows=44 loops=1)
Total runtime: 397.003 ms
(7 rows)