This HTML automatically generated with rman for NEMO
Table of Contents
tabdist - Compare distances between points in two tables, aka catalog
matching
tabdist [parameter=value]
Given two tables,
each containing specified column(s) that represent a set of 1D, 2D or 3D
points, it will compute the nearest neigbor(s) from each point in the first
table to those from the second table.
The output contains the same number
of rows as the input number of rows in the first dataset.
The
following parameters are recognized in any order if the keyword is also
given:
- in1=
- First dataset, an ascii table. No default.
- in2=
- Second dataset,
an ascii table. No default. The tables do not need to be of the same length.
- col1=
- Coordinate columns from 1st dataset. 1D, 2D and 3D are currently supported
[1,2]
- col2=
- Coordinate columns from 2nd dataset. 1D, 2D and 3D are currently
supported [1,2]
- id1=
- Column in first dataset representing the ID name. By
default a number between 1 and number of sources is used. [0]
- id2=
- Column
in second dataset representing the ID name [0]
- radec=t|f
- Should columns
be interpreted as angular (usually RA/DEC)? Only 2D comparisions are allowed
here. Units must be radians at the moment. See also tabdms(1NEMO)
. Default:
false
The X,Y,Z coordinates of a 3 particle plummer sphere are
perturbed by a small amount and then compared to the original list. Thus
they must match one on one:
% mkplummer - 3 | snapprint - x,y,z > tab11
% tabmath tab11 - ’%1+rang(0,0.01),%2+rang(0,0.01),%3+rang(0,0.01)’ > tab12
First a one dimensional comparison
% tabdist tab12 tab12 1 4
1 0.117073 1 0.122846 0.005773
2 -0.00899587 2 -0.0100997 0.00110383
3 -0.108077 3 -0.0964223 0.0116547
and then a full 3D case:
% tabdist tab12 tab12 1,2,3 4,5,6
1 0.117073 -0.097704 -0.299081 1 0.122846 -0.102288 -0.317648 0.0199768
2 -0.00899587 0.293374 0.12652 2 -0.0100997 0.281876 0.121453 0.0126134
3 -0.108077 -0.19567 0.172561 3 -0.0964223 -0.203288 0.17993 0.0157534
Currently it will display the line number, the coordinate(s) in table1,
then the best matching line number and coordinates(s) from table2, and
finally the distance.
Currently a brute force (quadratic in N) minimum
distance is used.
tabmath(1NEMO)
, tabdms(1NEMO)
, comparecats(SIRTF.map2)
k-d Match: http://arxiv.org/abs/1304.0838
src/kernel/tab/tabdist.c
Peter
Teuben
13-Feb-13 V0.1 Created PJT
13-nov-2013 V0.3 added radec= PJT
18-nov-2013 V0.4 added id1,id2= PJT
Table of Contents