astropy.table.join_distance(distance, kdtree_args=None, query_args=None)[source]#

Helper function to join table columns using distance matching.

This function is intended for use in table.join() to allow performing a table join where the key columns are matched by computing the distance between points and accepting values below distance. This numerical “fuzzy” match can apply to 1-D or 2-D columns, where in the latter case the distance is a vector distance.

The distance cross-matching is done using scipy.spatial.KDTree. If necessary you can tweak the default behavior by providing dict values for the kdtree_args or query_args.

distancefloat or Quantity [:ref: ‘length’]

Maximum distance between points to be considered a join match

kdtree_argsdict, None

Optional extra args for KDTree

query_argsdict, None

Optional extra args for query_ball_tree


Function that accepts (skycoord1, skycoord2) and returns the tuple (ids1, ids2) of pair-matched unique identifiers.


>>> from astropy.table import Table, join_distance
>>> from astropy import table
>>> c1 = [0, 1, 1.1, 2]
>>> c2 = [0.5, 1.05, 2.1]
>>> t1 = Table([c1], names=['col'])
>>> t2 = Table([c2], names=['col'])
>>> t12 = table.join(t1, t2, join_type='outer', join_funcs={'col': join_distance(0.2)})
>>> print(t12)
col_id col_1 col_2
------ ----- -----
     1   1.0  1.05
     1   1.1  1.05
     2   2.0   2.1
     3   0.0    --
     4    --   0.5