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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
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5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
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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
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# 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
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low_reject 3.
high_reject 3.
grow 0.
coefficients 9
1.
5.
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4425.143112306186
771.0320269416059
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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
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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
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843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
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function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
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5.
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# 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
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843.73 5017.13982 5017.0628 4.0 1 1
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order 5
sample *
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grow 0.
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# 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
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712.82 4806.01508 4806.0205 4.0 1 1
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843.73 5017.13982 5017.0628 4.0 1 1
934.89 5162.34733 5162.2846 4.0 1 1
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function chebyshev
order 5
sample *
naverage 1
niterate 1
low_reject 3.
high_reject 3.
grow 0.
coefficients 9
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5.
21.02974700927734
950.8942260742188
4425.143112306186
771.0320269416059
-8.090813278255755
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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
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843.73 5017.13982 5017.0628 4.0 1 1
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function chebyshev
order 5
sample *
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high_reject 3.
grow 0.
coefficients 9
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-8.090813278255755
-0.4458719578337133
0.04675295569119971

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
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# Wed 11:22:05 07-Jul-2010
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# Wed 11:22:05 07-Jul-2010
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# Wed 11:22:05 07-Jul-2010
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# Wed 11:24:05 07-Jul-2010
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# Wed 11:24:05 07-Jul-2010
begin identify cu1851[45,*]
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# Wed 11:24:05 07-Jul-2010
begin identify cu1851[5,*]
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task identify
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# Wed 11:24:05 07-Jul-2010
begin identify cu1851[75,*]
id cu1851
task identify
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# Wed 11:24:05 07-Jul-2010
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# Wed 11:24:05 07-Jul-2010
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# Wed 11:24:05 07-Jul-2010
begin identify cu1851[105,*]
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# Wed 11:24:05 07-Jul-2010
begin identify cu1851[115,*]
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# Wed 11:24:05 07-Jul-2010
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0.04675295569119971
[/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 :: No Love from Invertfit (Photcal) in Calculating Errors

mbriley — Fri, 23 Jul 2010 20:32:13 GMT

Author: mbriley
Subject: No Love from Invertfit (Photcal) in Calculating Errors
Posted: Fri Jul 23, 2010 8:32 pm (GMT 0)

I should begin with the disclaimer that I am for the most part, a spectroscopist... But I have been dabbling with some Stromgren Photometry of late. Working through the process with the noao.digiphot routines, all goes well until the inverting of my instrumental magnitudes. The results appear sane, but no errors are calculated - the error columns all have INDEF values, despite errors being set to "obserrors" in the parameter file.

I'll be the first to admit I've likely messed something up, but darned if I can find it. For the curious, my config file, parameters file, and observations file have been tarred up and can be downloaded from:

http://www.phys.uwosh.edu/mike/photfiles.tar (117K)

Any help would be appreciated.
-Mike

Applications :: psfmeasure for multiple images with different stellar fields

angus — Tue, 20 Jul 2010 21:15:23 GMT

Author: angus
Subject: psfmeasure for multiple images with different stellar fields
Posted: Tue Jul 20, 2010 9:15 pm (GMT 0)

Hi

I have to measure the PSF parameters of stars in a large number of fits images, each image corresponding to a different stellar field. I know the pixel coordinates of the stars on each field. I am trying to use the psfmeasure task for this job, running it non-interactively. I successfully used this task it in the case if the positions of the objects are the same on each image (i.e., the 'mark1' case). But what is the correct form of input in the present case? For the 'images' parameter, I give a list file with the image names preceding by an '@'. But what should the imagecur and the graphcur inputs look like? I think that the help file does not give clear information regarding this (or at least not clear for me..). I think I do not completely understand how these latter two parameters works. I was experimenting with many forms of input, none of them worked so far. The program always tries to perform measurements on the first image alone, but for *all* the positions, also those corresponding to subsequent images. I have no problem in interactive mode, though.
Of course I can write a cl script that calls the psfmeasure task separately for each image. That would help me to get the job done, but not to understand what am I doing wrong with imagecur/graphcur in the above case.
Any help would be highly appreciated.
Best regards,
Steve

General IRAF :: using rd2xy task

navarete — Tue, 20 Jul 2010 15:34:57 GMT

Author: navarete
Subject: using rd2xy task
Posted: Tue Jul 20, 2010 3:34 pm (GMT 0)

Hi there!
I'm using the rd2xy task to get the pixel position of a given RA and Dec in the image. The aim is to develop shifts between different images.
The procedure I'm trying to do is:
1 - read a list of files containing shifted images
2 - get the RA and DEC from the first image
3 - Convert them to X and Y using rd2xy
4 - With the same RA and DEC, get their X,Y position in the other images.

For doing it, I've runned the follow cl script:

Code:

string scifile, ra, dec, x, y

scilist = "scilist" # that's the list containing the files

#read the first 4 entries of the list

for (i=1; fscan(scilist, scifile) != EOF && i<=4; i=i+1) {

   # get RA and DEC for the first image
   if (i == 1) {
      hselect(scifile,"RA,DEC",yes) | scan(ra,dec)
   }

   rd2xy(scifile,ra,dec,hour+) | scan(x,y)
   print("i=",i," ",scifile," ",ra," ",dec," ",x," ",y)
}

when I run it, I get the following message:

ERROR: may not convert string to other types

What should I do?

Applications :: Time stamp problem

fschweizer — Fri, 16 Jul 2010 22:31:41 GMT

Author: fschweizer
Subject: Time stamp problem
Posted: Fri Jul 16, 2010 10:31 pm (GMT 0)

Hi Mike,

IRAF (v2.14) on my Mac Pro XMP seems to have a problem with time stamps
whenever some header update occurs (e.g., in `hedit ... add+'). The
time associated with the FITS file is then PST (standard time) instead
of PDT (daylight saving time) like all other files have.

The weirdest example is when, in IRAF, I `touch' a file as follows:
touch name.fits verbose+
The printed comment claims to modify to "system time" and gives the
correct PDT, but in UNIX the file then lists with PST time, which differs
by one hour from all other FITS files.

Is there any easy way to fix this?

Cheers,
Francois