You can make use of an ARRAY type internally. Argument type can still be any numeric type. Demonstrating with float
(= double precision
):
CREATE OR REPLACE FUNCTION f_circavg (float[], float)
RETURNS float[] LANGUAGE sql STRICT AS
'SELECT ARRAY[$1[1] + sin($2), $1[2] + cos($2), 1]';
CREATE OR REPLACE FUNCTION f_circavg_final (float[])
RETURNS float LANGUAGE sql AS
'SELECT CASE WHEN $1[3] > 0 THEN atan2($1[1], $1[2]) END';
CREATE AGGREGATE circavg (float) (
sfunc = f_circavg
, stype = float[]
, finalfunc = f_circavg_final
, initcond = '{0,0,0}'
);
The transition function f_circavg()
is defined STRICT
, so it ignores rows with NULL
input. It also sets a third array element to identify sets with one or more input rows - else the CASE
the final function returns NULL
.
Temporary table for testing:
CREATE TEMP TABLE t (x float);
INSERT INTO t VALUES (2), (NULL), (3), (4), (5);
I threw in a NULL
value to also test the STRICT
magic. Call:
SELECT circavg(x) FROM t;
circavg
-------------------
-2.78318530717959
Cross check:
SELECT atan2(sum(sin(x)), sum(cos(x))) FROM t;
atan2
-------------------
-2.78318530717959
Returns the same. Seems to work. In test with a bigger table the last expression with regular aggregate functions was 4x faster than the custom aggregate.
Test for zero input rows / only NULL input:
SELECT circavg(x) FROM t WHERE false; -- no input rows
SELECT circavg(x) FROM t WHERE x IS NULL; -- only NULL input
Returns NULL
in both cases.