iraf.net

Applications :: RE: printing with .snap

tonetty — Wed, 28 Jul 2010 22:17:56 GMT

Author: tonetty
Subject: :.snap
Posted: Wed Jul 28, 2010 10:17 pm (GMT 0)

:.snap eps ...does not work

it gives errors and the strange message you can see on the snapshot I insert in the first post

:.snap uhplj gives no error but the printer gives no life signs

I insert here the sections about UNIX default printer in my graphcap file

g-psdump|UNIX generic interface to Postscript file dump:\
D=psdump,tmp$sgk,!{ sgidispatch sgi2uapl $F -l$(XO) -w$(XW) \
-b$(YO) -h$(YW) -p$(PW) > /tmp/irafdmp$$.ps ; rm $F; }&:tc=sgi_apl:
# End of Joe Harrington entries.

# IRAFNET Devices
g-lpr|glpr|UNIX generic interface to default printer device (lpr):\
D=lpr,tmp$sgk,!{ sgidispatch sgi2uapl $F -l$(XO) -w$(XW) \
-b$(YO) -h$(YW) -p$(PW) | lpr ; rm $F ; }&:tc=sgi_apl:

g-lp|glp|UNIX generic interface to default printer device (lp):\
D=lpr,tmp$sgk,!{ sgidispatch sgi2uapl $F -l$(XO) -w$(XW) \
-b$(YO) -h$(YW) -p$(PW) | lp ; rm $F ; }&:tc=sgi_apl:

g-clprl|gclprl|g-clpr|gclpr|Default color printer device (lpr/psikern/land):\
:kf=bin$x_sgikern.e:\
D=psi_def,tmp$psk,!{ lpr $F; rm $F ;}&:tc=psi_land:

g-clprp|gclprp|Default color printer device (lpr/psikern/port):\
:kf=bin$x_sgikern.e:\
D=psi_def,tmp$psk,!{ lpr $F; rm $F ;}&:tc=psi_port:

g-psport|UNIX generic interface to Postscript file dump (portrait):\
:ar#0.762:ys#0.267:xs#0.203:yr#3180:xr#2380:\
:MF#1:YO#55:YW#3180:XO#90:XW#2380:PW#2.3:RO:YF:\
D=psdump,tmp$sgk,!{ sgidispatch sgi2uapl $F -l$(XO) -w$(XW) \
-b$(YO) -h$(YW) -p$(PW) > /tmp/irafdmp$$.ps ; rm $F; }&:tc=sgi_apl:
# End of IRAFNET Devices

is it enough? should I insert the whole file?

thanks for your help

Applications :: fitcoords

donzelli — Wed, 28 Jul 2010 12:58:04 GMT

Author: donzelli
Subject: fitcoords
Posted: Wed Jul 28, 2010 12:58 pm (GMT 0)

Hi all,
I'm trying to understand why I get a bad wavelength calibration using the fitcoord routine and I hope someone out there could help.
The plot for x-y coordinates of the identified lines is here:

http://www.iate.oac.uncor.edu/~charly/fitcoord.png

I previously used the reidentify routine using a 10 pixels step. So I have
13 columns across the image (from column 5 to column 125) where 21
emission lines where identified.

It can be observed a huge tilt from side to side of the image which is not at all observed on the real image. Moreover, 'y' coordinates do not match with the position of the identified lines as it can be seen in the file below, which is the output of the 'reidentify' routine. Note that for each column the wavelength solution is identical and there are not negative values for 'y' (position of the lines, first column of the file below). However, the x-y plot clearly shows negative values for 'y' coordinates.
many thanks in advance.

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[65,*]
id cu1851
task identify
image cu1851[65,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[35,*]
id cu1851
task identify
image cu1851[35,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[25,*]
id cu1851
task identify
image cu1851[25,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[15,*]
id cu1851
task identify
image cu1851[15,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[55,*]
id cu1851
task identify
image cu1851[55,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[45,*]
id cu1851
task identify
image cu1851[45,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[5,*]
id cu1851
task identify
image cu1851[5,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[75,*]
id cu1851
task identify
image cu1851[75,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[85,*]
id cu1851
task identify
image cu1851[85,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[95,*]
id cu1851
task identify
image cu1851[95,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[105,*]
id cu1851
task identify
image cu1851[105,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[115,*]
id cu1851
task identify
image cu1851[115,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[125,*]
id cu1851
task identify
image cu1851[125,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

Applications :: RE: xnregistar problem

emma — Tue, 27 Jul 2010 22:17:01 GMT

Author: emma
Posted: Tue Jul 27, 2010 10:17 pm (GMT 0)

Glad I could help! However, it is a bit strange that for a given task, you need to use a '@' in one parameter and not another ... especially when there is nothing about it in the help file!

Mike, I'm not sure if you can comment on this? I know xdimsum is an external package, but do you know if there is someone working actively on this package who would take suggestions for improvements?

Thanks!

Emma

Applications :: RE: xnregistar problem

ginger — Tue, 27 Jul 2010 21:43:12 GMT

Author: ginger
Posted: Tue Jul 27, 2010 9:43 pm (GMT 0)

Emma,
Thanks! That did work, and led me to find the answer to my problem.

It seems I just was putting @ signs where I didn't need them and not putting them where I did. Here's an epar of the configuration that worked:

PACKAGE = xdimsum,
TASK = xnregistar

inlist = shifts List of sky subtracted images, N and E shifts, a
rmasks = Input rection mask keyword or rejection mask lis
output = firstpassfinal The output combined image name
expmap = expmap The output exposure map image
sections= sections The optional output sections file
(sinlist= @demo.list) The list of image names to be written to section
(blkrep = yes) Use blkrep rather than magnify ?
(mag = 1.) Block replication factor
(fractio= yes) Use fractional pixel shifts if mag = 1?
(pixin = yes) Are input coords in ref object pixels?
(ab_sens= yes) Is A thru B counterclockwise?
(xscale = 1.) X pixels per A coordinate unit
(yscale = 1.) Y pixels per B coordinate unit
(a2x_ang= 0.) Angle in degrees from A CCW to X
(ncoavg = 1) Number of coaverages per image
(secpexp= 1.) Seconds per unit exposure time
(y2n_ang= 0.) Angle in degrees from Y to N N thru E
(rotatio= yes) Is N thru E CCW?
(imglist= )
(nimglis= )
(rimglis= )
(shimgli= )
(cmimgli= )
(mode = ql)

sinlist is just a list of names of images that I would like to end up in the "sections" file. Here's what demo.list contains:
demo01
demo02
demo03
demo04
demo05
demo06
demo07
demo08
demo09
demo10
demo11
demo12
demo13
demo14
demo15
demo16
demo17
demo18
demo19
demo20
demo21
demo22
demo23
demo24
demo25

Emma, thanks a lot for your help. Your suggestion of changing sinlist, was what I needed. I didn't think to include it in my many iterations of @'s and no @'s. The help file is a little confusing about this.

Thanks again!
-Ginger

Applications :: RE: problem with gsflat of gmos gemini package

emma — Tue, 27 Jul 2010 16:54:49 GMT

Author: emma
Posted: Tue Jul 27, 2010 4:54 pm (GMT 0)

Hi Jorge,

Sorry again for my delayed reply, I was travelling again

I started a new iraf session:

Code:

loaded the gemini and gmos packages:

Code:

gemini
gmos

initialised my uparm directory (I ran this command from the directory where my uparm directory is located):

Code:

rm -rf uparm/*

then checked that it was empty:

Code:

dir uparm$

the output of which was:

Code:

no files found

then ran the following command:

Code:

gsflat inflats=<yourfile75>.fits specflat=f<yourfile75>.fits fl_over+ fl_fixpix- bias=<yourbias>.fits

I actually downloaded your raw data from the archive and ran gsflat on the raw data (in place of <yourfile75> above), rather than the data you sent me. I did, however, use the bias frame you sent me (in place of <yourbias> above).

gsflat ran without any errors. However, I did get a:

Code:

WARNING - GIREDUCE: Mismatch detector section or binning of bias

message though, so I don't think the bias frame you sent me is correct for the standard star data you sent me.

The problem might be that you are not running gsflat on the raw data. Other than that, I think it must be something to do with your installation, since I can reduce the data just fine here. You should only need to run mkiraf once so that you have a single login.cl file and a single uparm directory. When you start IRAF, check that everything is set correctly by typing the following:

Code:

show home

Make sure that the output for this is the path to where your login.cl file is located. Then try:

Code:

show uparm

This should return:

Code:

home$uparm

and means that the uparm directory is defined to be in the directory where your login.cl is located.

Also just double check you have write permissions for your uparm directory and also in the directory you are working in.

Emma

Applications :: RE: xnregistar problem

emma — Tue, 27 Jul 2010 15:49:48 GMT

Author: emma
Posted: Tue Jul 27, 2010 3:49 pm (GMT 0)

Hello ginger,

In the helpfile for xnregistar, it says that the sections parameter is 'The optional output sections or corners file suitable for input to the maskdereg task. If defined sections contains the name of the input images in sinlist if it is defined or inlist, the x and y coordinates of the lower left corner of the input image in the combined output image, and the x and y coordinates of the upper right corner of the input image in the output image in columns 1 through 5 respectively.' while the sinlist parameter is 'The list of image names that will be written to the sections file. If sinlist is undefined then the input image names in inlist are used.'

I notice that you have the sinlist parameter set to 'demo.list'. What is contained in this file? Does it exist? I think that if you set sections="" and sinlist="" then the task should run without complaining

Hope that helps?

Many thanks,

Emma

General IRAF :: reidentify - fitcoord

donzelli — Tue, 27 Jul 2010 13:56:18 GMT

Author: donzelli
Subject: reidentify - fitcoord
Posted: Tue Jul 27, 2010 1:56 pm (GMT 0)

Hi all,
I'm still trying to solve why I get a bad wavelength calibration using fitcoord foutine and I hope someone out there could help.
The plot for x-y coordinates of the identified lines is here:

http://www.iate.oac.uncor.edu/~charly/fitcoord.png

It can be observed a huge tilt from side to side of the image. Moreover,
'y' coordinates do not match with the position of the identified lines as it can be seen in the below file, which is the output of the 'reidentify' routine.
Note that for each column the wavelength solution is identical and there are not negative values for 'y' (position of the lines, first column of the file below). However, the x-y plot clearly shows negative values for 'y' coordinates.
many thanks in advance.

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[65,*]
id cu1851
task identify
image cu1851[65,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[35,*]
id cu1851
task identify
image cu1851[35,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
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0.04675295569119971

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[25,*]
id cu1851
task identify
image cu1851[25,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:22:05 07-Jul-2010
begin identify cu1851[15,*]
id cu1851
task identify
image cu1851[15,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[55,*]
id cu1851
task identify
image cu1851[55,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[45,*]
id cu1851
task identify
image cu1851[45,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[5,*]
id cu1851
task identify
image cu1851[5,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[75,*]
id cu1851
task identify
image cu1851[75,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
-0.4458719578337133
0.04675295569119971

# Wed 11:24:05 07-Jul-2010
begin identify cu1851[85,*]
id cu1851
task identify
image cu1851[85,*]
units Angstroms
features 21
21.03 3646.5129 3646.5129 4.0 1 1
140.19 3850.55832 3850.5813 4.0 1 1
270.63 4072.20309 4072.0047 4.0 1 1
305.81 4131.62933 4131.7235 4.0 1 1
321.81 4158.60072 4158.5905 4.0 1 1
335.54 4181.73099 4181.8836 4.0 1 1
381.73 4259.30786 4259.3619 4.0 1 1
406.13 4300.18057 4300.1008 4.0 1 1
426.19 4333.70645 4333.5612 4.0 1 1
466.42 4400.78554 4400.9863 4.0 1 1
553.49 4545.10718 4545.0519 4.0 1 1
592.64 4609.61148 4609.5673 4.0 1 1
622.09 4657.96829 4657.9012 4.0 1 1
687.53 4764.88603 4764.8646 4.0 1 1
712.82 4806.01508 4806.0205 4.0 1 1
738.55 4847.74695 4847.8095 4.0 1 1
758.34 4879.7713 4879.8635 4.0 1 1
811.26 4965.06386 4965.0795 4.0 1 1
843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
950.89 5187.68521 5187.7462 4.0 1 1
function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
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[/img][/url]

Misc :: Differential photometry and PSF

FSBoyden — Tue, 27 Jul 2010 07:59:23 GMT

Author: FSBoyden
Subject: Differential photometry and PSF
Posted: Tue Jul 27, 2010 7:59 am (GMT 0)

Hi

Just want to do a double check if my procedure is acceptable!

I am doing fast photometry on a variable star - problem is that the field I am working in is relatively sparse. My CV is at 11-12 mag, while the only comparison stars bright and stable enough is at 14,15.7,15.9,16.2 mags.

I construct a PSF using the comp stars - because the PSF constructed including the CV results in a swop of the lightcurves - "The comp stars varies and the CV is stable".

I did use normal AppPhot, but the errors in the comp stars was too large. PSF gives me a more stable comparison normalization curve and smaller errors.

Task and method:

Use master.coo file and master.pst file and the use daophot tasks (in sequince - with relevant input in a script - some small stuf in between)
aphot
psf
allstar

Dump the .als files results to file and work from there.

Q! Is the above method acceptable - or is the comp stars to "low" for accurate PSF measurements. When checking the .sub.fits frames there is some small bit of leftover counts for the CV, but it is around the sky-noise region?

I would appreciate some recommendations and help.

Regards
Pat

Applications :: xnregistar problem

ginger — Tue, 27 Jul 2010 03:53:52 GMT

Author: ginger
Subject: xnregistar problem
Posted: Tue Jul 27, 2010 3:53 am (GMT 0)

I am attempting to use xnregistar to combine the xdimsum demo images (subtracted) using offsets computed with xdshifts. However, I continue to be unsuccessful.

Here is the epar for xnregister:
PACKAGE = xdimsum,
TASK = xnregistar

inlist = shifts List of sky subtracted images, N and E shifts, and exposures
rmasks = Input rection mask keyword or rejection mask list
output = firstpassfinal The output combined image name
expmap = expmap The output exposure map image
sections= sections The optional output sections file
(sinlist= demo.list) The list of image names to be written to sections
(blkrep = yes) Use blkrep rather than magnify ?
(mag = 1.) Block replication factor
(fractio= yes) Use fractional pixel shifts if mag = 1?
(pixin = yes) Are input coords in ref object pixels?
(ab_sens= yes) Is A thru B counterclockwise?
(xscale = 1.) X pixels per A coordinate unit
(yscale = 1.) Y pixels per B coordinate unit
(a2x_ang= 0.) Angle in degrees from A CCW to X
(ncoavg = 1) Number of coaverages per image
(secpexp= 1.) Seconds per unit exposure time
(y2n_ang= 0.) Angle in degrees from Y to N N thru E
(rotatio= yes) Is N thru E CCW?
(imglist= )
(nimglis= )
(rimglis= )
(shimgli= )
(cmimgli= )
(mode = ql)

the shifts file is just the output of xdshifts that looks like:

subdemo01 0.000 0.000 1.0
subdemo02 -6.354 -0.133 1.0
subdemo03 -13.224 -0.581 1.0
subdemo04 -19.420 -0.697 1.0
subdemo05 -25.969 -0.504 1.0
subdemo06 -1.375 -7.244 1.0
subdemo07 -7.778 -7.623 1.0
subdemo08 -12.664 -6.165 1.0
subdemo09 -19.014 -6.265 1.0
subdemo10 -25.917 -6.238 1.0
subdemo11 -0.661 -13.033 1.0
subdemo12 -7.332 -13.368 1.0
subdemo13 -13.968 -13.422 1.0
subdemo14 -20.312 -13.922 1.0
subdemo15 -25.416 -12.502 1.0
subdemo16 -0.487 -19.006 1.0
subdemo17 -7.006 -19.019 1.0
subdemo18 -13.347 -19.352 1.0
subdemo19 -20.040 -19.675 1.0
subdemo20 -26.873 -20.209 1.0
subdemo21 -1.772 -26.404 1.0
subdemo22 -6.034 -25.005 1.0
subdemo23 -12.896 -25.258 1.0
subdemo24 -19.155 -25.533 1.0
subdemo25 -26.271 -25.476 1.0

The error message I get is, "The input and sections image lists are not the same size"

Perhaps I misunderstand, but I thought the sections file was an output file, so if it is just the name of a file, why is it necessary to match the input (which I assume is "inlist") to it?

I've also tried: specifying infile=@shifts and/or specifying sections="", but this gives the error messages:

Warning: Cannot open file (subdemo010.0000.0001.0)
Warning: Cannot open file (subdemo02-6.354-0.1331.0)
Warning: Cannot open file (subdemo03-13.224-0.5811.0)
Warning: Cannot open file (subdemo04-19.420-0.6971.0)
Warning: Cannot open file (subdemo05-25.969-0.5041.0)
Warning: Cannot open file (subdemo06-1.375-7.2441.0)
Warning: Cannot open file (subdemo07-7.778-7.6231.0)
Warning: Cannot open file (subdemo08-12.664-6.1651.0)
Warning: Cannot open file (subdemo09-19.014-6.2651.0)
Warning: Cannot open file (subdemo10-25.917-6.2381.0)
Warning: Cannot open file (subdemo11-0.661-13.0331.0)
Warning: Cannot open file (subdemo12-7.332-13.3681.0)
Warning: Cannot open file (subdemo13-13.968-13.4221.0)
Warning: Cannot open file (subdemo14-20.312-13.9221.0)
Warning: Cannot open file (subdemo15-25.416-12.5021.0)
Warning: Cannot open file (subdemo16-0.487-19.0061.0)
Warning: Cannot open file (subdemo17-7.006-19.0191.0)
Warning: Cannot open file (subdemo18-13.347-19.3521.0)
Warning: Cannot open file (subdemo19-20.040-19.6751.0)
Warning: Cannot open file (subdemo20-26.873-20.2091.0)
Warning: Cannot open file (subdemo21-1.772-26.4041.0)
Warning: Cannot open file (subdemo22-6.034-25.0051.0)
Warning: Cannot open file (subdemo23-12.896-25.2581.0)
Warning: Cannot open file (subdemo24-19.155-25.5331.0)
Warning: Cannot open file (subdemo25-26.271-25.4761.0)
The input and sections image lists are not the same size

I am at a loss. I'm not sure if I'm just putting my files in the wrong format, or misunderstanding something else. Any help is greatly appreciated!
-Ginger

Applications :: RE: problem with gsflat of gmos gemini package

jorge — Sun, 25 Jul 2010 04:17:31 GMT

Author: jorge
Posted: Sun Jul 25, 2010 4:17 am (GMT 0)

Hi emma, have you had time to see the frames... have you found the problem?.

Best.
jorge.