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I'm attempting to match objects between multiple dithered images. I've generated coordinate files with daofind using a central 1000 pixel x 1000 pixel region from the center of each image. Approx. 60-90 objects are found in each image (detection threshold = 150 sigma, min good data val = 5000, max good data val = 50000). From just looking at the images, I know that most of these objects are common to all images, yet when I run xyxymatch I get either 0 reference coordinates matched, or possibly 1 (but this is only a fluke, the coordinates are not actually the same star).Here are the params I'm using for xyxymatch:input = 90.dao The input lists
referenc= 91.dao The reference lists
output = 90.xy The output matched coordinate lists
toleranc= 10. The matching tolerance in pixels
(refpoin= ) Optional list of reference points
(xin = INDEF) X origin of input list
(yin = INDEF) Y origin of input list
(xmag = INDEF) X magnification required to match input to refer
(ymag = INDEF) Y magnification required to match input to refer
(xrotati= INDEF) X rotation required to match input to reference
(yrotati= INDEF) Y rotation required to match input to reference
(xref = INDEF) X origin of reference list
(yref = INDEF) Y origin of reference list
(xcolumn= 1) Input list column containing the x coordinate
(ycolumn= 2) Input list column containing the y coordinate
(xrcolum= 1) Reference list column containing the x coordinat
(yrcolum= 2) Reference list column containing the y coordinat
(separat= 9.) The minimum object separation
(matchin= triangles) The matching algorithm
(nmatch = 30) The maximum number of points for triangles algor
(ratio = 10.) The maximum ratio of longest to shortest side of
(nreject= 10) The maximum number of rejection iterations
(xformat= %13.3f) The format of the output x coordinate
(yformat= %13.3f) The format of the output y coordinate
(interac= no) Interactive mode ?
(verbose= yes) Verbose mode ?
(icomman= ) The image display cursor
(mode = ql)The input files are the output files from daofind.I've used xyxymatch in this version of iraf before with no problems, I'm not sure what has changed since the last time I used it.Any help would be appreciated, I have too many images to do this by hand.Thanks,Rachel

Problems like this are usually due to parameter settings playing havoc with the algorithm, e.g. a tolerance set too high and so everything is rejected, a fitting box so big that all sources are included, etc. Without seeing the files in question I can't really comment other than to say the task hasn't changed, my guess is that it is the input data or parameter settings that are new since your last successful run. Please post the data if experimentation with parameters doesn't reveal a clue.-Mike

Hi Mike,I've played around with the parameters of xyxymatch to no avail.I have posted the data files atwww2.ess.ucla.edu/~rachel/*.dao files are output files from daofind with ~30 objects in each.
*xy file is the output from xyxymatch (no objects matched)
*par files are the parameter files for daofind and xyxymatch.Hopefully you can spot what's wrong.Thanks,Rachel

Using a tolerance of 3 or 4 I was able to get the following matches:[code:1:1e5d1042b6]
# Input: 40.dao Reference: 41.dao Number of tie points: 0
# Initial linear transformation
# xref[tie] = 0. + 1. * x[tie] + 0. * y[tie]
# yref[tie] = 0. + 0. * x[tie] + 1. * y[tie]
# dx: 0.00 dy: 0.00 xmag: 1.000 ymag: 1.000 xrot: 0.0 yrot: 0.0
#
# Column definitions
# Column 1: X reference coordinate
# Column 2: Y reference coordinate
# Column 3: X input coordinate
# Column 4: Y input coordinate
# Column 5: Reference line number
# Column 6: Input line number 182.282 493.268 292.102 335.694 54 51
88.264 842.502 198.243 689.235 65 63
776.771 861.261 897.804 699.787 68 65
372.722 901.274 487.523 745.748 70 68
[/code:1:1e5d1042b6]These appear to be real but the points all come from small clusters in the input/reference lists. I think what's happening is that the algorithm is rejecting similar triangles because the 'separation' parameter is rejecting some of the points as being too close. This might mean you need to tweak your DAOFIND parameters to avoid these small clusters, but I haven't seen the images so I don't know whether these are real or just false detections.Hope this helps.-Mike