Here I plot the bias signal computed from a CCD image using my command line image processing code for computing marginal distributions:
% clip_margdist.sh B.fits col
Usage: clip_margdist.sh a.fits 10.0
arg1 - input FITS image
arg2 - column or row averaging (col,row)
# A table file consisting of two files is made
% cat margdist_col.table
# col averaged marginal distribution
# data
1.0 405.6134 6.8315 0.2460 771.0
2.0 -247.5314 3.7051 0.1334 771.0
3.0 -179.9816 21.6218 0.7787 771.0
.....
.....
.....
769.0 23.5948 5.8612 0.2111 771.0
770.0 38.7725 42.8013 1.5415 771.0
771.0 52.8825 6.2277 0.2243 771.0
% cat margdist_col.parlab
col Column Number
mean Mean signal value (adu)
sig Standard devistion (adu)
me Mean error about mean (adu)
Npix Number of pixels
% ls
margdist_col.parlab margdist_col.table
% xyplotter_auto margdist_col col mean 1
------------------------------------------------------------
Enter plot title:Plot a point (P) or a line (L):
Title = The Plot Title of my Choosing
X: 1.00000 771.00000 Xtitle = Column Number
Y: -247.53140 405.61340 Ytitle = Mean signal value (adu)
To see the plot:
pxy_SM_plot.py STYLE 1.00000 771.00000 -247.53140 405.61340 SHOW
View plot now? (Y/N) Y
Plotting: XY.plot.1
Number of points = 771
------------------------------------------------------------
% ls
Axes.1 figure_1.png List.1 margdist_col.parlab margdist_col.table
Note that in the example above, I used the python show() module to create
a hardcopy of the plot. This is the file named "figure_1.png". In the
next example, we'll see how to modify the appearance of this plot and
how to easily add other data sets.