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RG
RADGAL is a module which performs a nonlinear least squares fit to
surface brightness data in a file of type 1 and derives the parameters of
a chosen surface brightness formula and their errors. It can take into
account blurring from the atmosphere by using the actual point spread
function of a star (or averge of many stars).
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Enter an option: 22-OCT-1991 13:59:32.32
OPTION=RG
RADGAL, Version 1
Open the data file
Enter the file name: (default = last entry)
FILE_21=R022152 ....This the data file of type 1 which was
produced by option PR.
Enter the ID of the object: (default = last galaxy entry)
ID=129 ....The data file can hold many different
galaxies
Do you wish to plot the first estimate of the Hubble "a" against radius?
(default = N) ....This is quick way to get a rough value for
the radius parameter
PLOT=
F
Enter the surface brightness law:
G = Gaussian
H = Hubble
HV = Hubble with variable power in denominator
I = Inverse radius
K = Constant
L = Straight line
M = Modified Hubble (default)
MC = Modified Hubble plus modified Hubble for cluster
ML = Fixed modified Hubble with color gradient, linear in log(r)
MR = Fixed modified Hubble with color gradient, linear in r
SI = Sum of K/r and K'/r**2
T = Tapered Hubble
V = de Vaucouleurs
VC = de Vaucouleurs plus de Vaucouleurs for cluster
E3 = Extrafocal photometry of E3 galaxies
....There are lots of choices
CHOICE=V
Do you wish to solve for the sky level also? (default = Y)
SOLVE=
T ....Normally, one does not know the sky ahead
of time. Obtaining an accurate sky level
is important for getting an accurate
total magnitude.
Do you wish to convolve the surface brightness law with a smearing
distribution?
(default = Y)
CONVOLVE=
T ....It is essential to do this for most images.
Open the file containing the smearing function
Enter the file name: (default = last entry)
FILE_22=S022152 ....This was prepared with option PR on stars
in the field
Enter the ID of the smearing object: (default = last smearing entry)
ID=STARS ....Several stars were added together for more
accuracy with option ED
Enter the convolving factor: (default = 75.0)
CONVOLVE_FACTOR=
75.0000 ....This factor controls the stepsize for
convolution. A large factor produces
a smaller stepsize near the center of the
galaxy. This gives more accuraccy, but takes
longer to compute. We choose the default here.
Enter the starting and ending radii for the least squares fit:
(default = the entire range of the data file)
RADII=
0.000000E+00
90.0000
Enter the outer radius to where convolution is to be done:
(default = previous fitting outer radius
RADIUS=40 ....By not convolving out to the edge of the
data file we save computing time and do
not loose accuracy.
Enter the estimates for the surface brightness at 1/2 the total light
(ADU), the corresponding radius (pixels), and the sky level (ADU):
PARAMETERS=100 10 491 ....A reasonable guess
Select the weighting scheme:
R = Weight equal to circumference/(noise)**2 (default)
S = Weight equal to the square root of the circumference
N = Weight equal to 1/(noise)**2
P = Weight equal to weight from file/(constant*noise**2)
WEIGHT_SCHEME=
R
Enter the readout noise in electrons and the gain in electrons per ADU:
(defaults = 63.9 21.3)
NOISE_PARAMETERS=
63.9000
21.3000 ....These will depend on the instrument
Select the iteration scheme:
M = Manual (default)
A = Automatic selection of fractional increment with
maximum searching
B = Automatic selection of fractional increment with
minimum searching
C = Automatic selection of fractional increment with
no searching
ITERATION_SCHEME=
M ....We choose M here so as to illustrate the behavior
of the iteration. Normally, this operation can
be submitted as a batch job and A (for good data)
or B (for noisier data) chosen.
Enter the fractional increment: (default = 1.0)
FRACTIONAL_INCREMENT=
1.00000 ....If the answer starts to oscillate, we can decrease
this value. When A is chosen, the increment is
adjusted downward as needed automatically.
For the initial guess:
Mean error for an observation of average weight =
27.9963 +- 2.11030
For the solution:
Mean error for an observation of average weight =
4.21510 +- 0.317725
and in magnitudes it is =
1.35730 +- 0.102310
Effective surface brightness = 52.48601 +- 4.79713
Effective radius = 8.78313 +- 0.31946
Sky surface brightness = 490.70779 +- 0.47116
Do you wish to iterate 1 more time? (default = Y)
ITERATE=
T
Enter the fractional increment: (default = 0.67xlast value)
FRACTIONAL_INCREMENT=1 ....We'll try keeping this high for now
Enter the new estimates: (default = best values)
PARAMETERS=
52.4860
8.78313
490.708
For the solution:
Mean error for an observation of average weight =
1.01237 +- 0.763099E-01
and in magnitudes it is =
1.32065 +- 0.995480E-01
Effective surface brightness = 58.41388 +- 1.37615
Effective radius = 6.91855 +- 0.14996
Sky surface brightness = 490.73038 +- 0.11192
Do you wish to iterate 1 more time? (default = Y)
ITERATE=
T
Enter the fractional increment: (default = 0.67xlast value)
FRACTIONAL_INCREMENT=1
Enter the new estimates: (default = best values)
PARAMETERS=
58.4139
6.91855
490.730
For the solution:
Mean error for an observation of average weight =
0.886601 +- 0.668301E-01
and in magnitudes it is =
1.30982 +- 0.987316E-01
Effective surface brightness = 69.91505 +- 1.67909
Effective radius = 6.10233 +- 0.12451
Sky surface brightness = 490.79819 +- 0.09649
Do you wish to iterate 1 more time? (default = Y)
ITERATE=
T
Enter the fractional increment: (default = 0.67xlast value)
FRACTIONAL_INCREMENT=
0.670000 ....To prevent the solution from bouncing around
too much, we'll let the fractional increment
decrease on each iteration.
Enter the new estimates: (default = best values)
PARAMETERS=
69.9151
6.10233
490.798
For the solution:
Mean error for an observation of average weight =
0.821715 +- 0.619391E-01
and in magnitudes it is =
1.22094 +- 0.920321E-01
Effective surface brightness = 74.94466 +- 1.86721
Effective radius = 5.88179 +- 0.09985
Sky surface brightness = 490.83908 +- 0.08886
Do you wish to iterate 1 more time? (default = Y)
ITERATE=
T
Enter the fractional increment: (default = 0.67xlast value)
FRACTIONAL_INCREMENT=
0.448900
Enter the new estimates: (default = best values)
PARAMETERS=
74.9447
5.88179
490.839
For the solution:
Mean error for an observation of average weight =
0.887865 +- 0.669254E-01
and in magnitudes it is =
1.20830 +- 0.910789E-01
Effective surface brightness = 77.77221 +- 2.13163
Effective radius = 5.75739 +- 0.10164
Sky surface brightness = 490.85941 +- 0.09585
Do you wish to iterate 1 more time? (default = Y)
ITERATE=
T
Enter the fractional increment: (default = 0.67xlast value)
FRACTIONAL_INCREMENT=
0.300763
Enter the new estimates: (default = best values)
PARAMETERS=
74.9447
5.88179
490.839
For the solution:
Mean error for an observation of average weight =
0.846092 +- 0.637766E-01
and in magnitudes it is =
1.22517 +- 0.923505E-01
Effective surface brightness = 76.83912 +- 2.03134
Effective radius = 5.79844 +- 0.09685
Sky surface brightness = 490.85269 +- 0.09134
.
.
.
.
.
. ....We have let it iterate a few more times
Do you wish to iterate 1 more time? (default = Y)
ITERATE=
T
Enter the fractional increment: (default = 0.67xlast value)
FRACTIONAL_INCREMENT=
0.606071E-01
Enter the new estimates: (default = best values)
PARAMETERS=
74.9447
5.88179
490.839
For the solution:
Mean error for an observation of average weight =
0.822191 +- 0.619750E-01
and in magnitudes it is =
1.22255 +- 0.921532E-01
Effective surface brightness = 75.32642 +- 1.97396
Effective radius = 5.86499 +- 0.09412
Sky surface brightness = 490.84183 +- 0.08876
Do you wish to iterate 1 more time? (default = Y)
ITERATE=N ....The solution seems to have converged
For a perfect fit:
Mean error for an observation of average weight =
0.337123 +- 0.254116E-01
Covariance(1,1) = 3.8965144
Covariance(1,2) = -0.18082026 ....This is expected to be negative
Covariance(2,2) = 0.88583706E-02
Covariance(1,3) = 0.28629743E-01
Covariance(2,3) = -0.16628597E-02
Covariance(3,3) = 0.78780372E-02
The average weight = 0.019394
The reduced chi squared = 5.9480
The integral from radius = 0.0 to radius = 90.0 = 44849.835182
In magnitudes it is 18.370598
The integral from radius = 91.0 to the limit of 2212.5 = 718.027778
In magnitudes it is 22.859648
The total is 45567.862960 and in magnitudes it is 18.353354
....Note that the total magnitude is only slightly
brighter than the aperture magnitude out to
90 pixels.
Do you wish to plot the residuals? (default = Y)
PLOT=
T ....This is a good way to see how good the fit
actually is.
Enter the plot devices:
G = Graphics terminal (VT100/Retrographics and Visual 550, default)
G1 = Graphics terminal (GraphOn)
G2 = Graphics terminal (Codonics)
G3 = Graphics terminal (Micro-term)
F = File
T = Tektronix 4662 flat bed plotter (1200 baud)
DEVICES=
G
....The first plot is in linear units
Enter the plot devices:
G = Graphics terminal (VT100/Retrographics and Visual 550, default)
G1 = Graphics terminal (GraphOn)
G2 = Graphics terminal (Codonics)
G3 = Graphics terminal (Micro-term)
F = File
T = Tektronix 4662 flat bed plotter (1200 baud)
DEVICES=
G
....This plot is in logarithmic units
Do you wish to store the results? (default = N)
STORE=Y
Add the results to an existing file? (default = N)
OLD=
F
Enter the file name: (default = last entry)
FILE_24=RESULTS_FILE
More objects to analyze in this file? (default = N)
MORE=
F
Enter an option: 22-OCT-1991 14:08:47.06
OPTION=EX
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