In addition to the matching criteria listed in the previous subsections,
you can build your own by combining any of these.
To do this, take the two (or more)
matchers that you want to use, and separate their names with a
+" character. The
of the combined matcher should then hold the concatenation of the
values* entries of the constituent matchers, and the
same for the
So for instance the matcher "
sky+1d" could be used
with the following syntax:
matcher=sky+1d values*='<ra/degrees> <dec/degrees> <x>' params='<max-error/arcsec> <error>' tuning='<healpix-k> <bin-factor>'
This would compare positions on the sky with an additional scalar constraint. Rows are considered to match if both their
ra/degrees: Right Ascension
x: Cartesian co-ordinate #1
max-error/arcsec: Maximum separation along a great circle
error: Maximum Cartesian separation for match
healpix-k: Controls sky pixel size. Legal range 0 - 29. 0 is 60deg, 20 is 0.2".
bin-factor: Scaling factor to adjust bin size; larger values mean larger bins
decpositions are within
max-errorarcseconds of each other along a great circle (as for
matcher=sky) and their
xvalues differ by no more than
This example might be used for instance to identify objects from two catalogues which are within a couple of arcseconds and also 0.5 blue magnitudes of each other. Rolling your own matchers in this way can give you quite flexible match constraints.
When identifying the closest match
the "distance" measure is obtained by
scaling the distances from each of the constituent matchers
and adding these scaled distances in quadrature,
so that each element of the matcher has approximately equal weight.
Scaling is generally done using the maximum permissible match
radius (or equivalent), so the distance measure looks something like
d = sqrt([dA/max(dA)]2
However the details are a bit dependent on which matchers you are combining.
Note that in STILTS v3.0-9 and earlier, a linear unscaled distance measure was used here instead, which did not give very meaningful Best match results.