Display a radial profile (circular annuli) of 2D data, fit, and residuals.
plot_rprofr( [dnum,] min, max, step )
plot_rprofr( [dnum,] modelname, min, max, step )
plot_rprofr( [dnum,] xval, yval, min, max, step )
plot_rprofr( [dnum,] xname, yname, min, max, step )
plot_rprofd( [dnum,] min, max, step )
plot_rprofd( [dnum,] modelname, min, max, step )
plot_rprofd( [dnum,] xval, yval, min, max, step )
plot_rprofd( [dnum,] xname, yname, min, max, step )
plot_rprof() is a synonym for plot_rprofr()
The 'image fit' command shows the data, best-fit model, and
residuals for your 2D dataset.
Sometimes this can be hard to interpret - in particular when
dealing with low-count data as is often the case with Chandra images
- and a different view of the fit may be useful.
The plot_rprofr() and plot_rprofd() functions provide such a view, as
they display two plots; the first is a radial profile of the
data and best-fit model, while
the second is a radial profile of the residual image.
The residual plot created by plot_rprofr() has the y axis in units
of counts, whilst the residual plot from plot_rprofd() uses
counts / error.
These plots are similar to the output of 'lplot fit resid' - for
plot_rprofr() - and 'lplot fit delchi' - for plot_rprofd() - for 1D
data.
The functions provide a usage message if called with either no,
or an incorrect set of, arguments.
The plot_eprofr() and plot_eprofd() functions produce the same
plots but using elliptical, rather than circular, annuli:
see "ahelp plot_eprof" for more information.
The min, max, and step arguments determine the
the minimum and maximum radii of the annuli, and the width
of each annnulus repectively.
The units of these arguments match the current setting of
Sherpa's coordinate command.
If no other arguments - other than the dataset number (dnum) -
are given, then the center of the annuli is taken from the
xpos and ypos parameters of a source component for the
dataset. If no such component exists, or, more likely,
there is more than one component in the source expression,
then you have to specify the center of the annuli. This can
be done in one of three ways:
-
The name of the component to use (the modelname parameter).
This model should have xpos and ypos parameters.
-
The actual coordinates of the center (the xval and yval
parameters) in the same coordinate system as min, max, and
step.
-
The names of model parameters (the xname and yname arguments)
which contain the center position.
The following examples assume that a source model has been fit
to a 2D dataset. See the "NOTES" section below for information on
how to load the function into Sherpa, and the "CHANGING THE PLOTS"
section for information on how to customise the appearance
of the plots.
sherpa> plot_rprofr(0,200,20)
This will plot up a radial profile of the data and model
(top plot) and a radial profile of the residual image
(bottom plot) for dataset 1.
Assuming the values in sherpa.fitplot and sherpa.resplot
have not been changed then the data is plotted using
squares, the best-fit as the red line, and the
residuals as filled circles.
The three arguments in the call
give the minimum and maximum radii - here 0 and 200
respectively - and the width of each annulus (20).
The units are taken to match the current coordinate settings
for the dataset (see 'ahelp coord').
The source expression is assumed to contain only one
component with "xpos" and "ypos" parameters; these
are used to define the center of the profile.
A radial bin will only be displayed if there are any
pixels that contribute to that bin. For instance, if the central
region around the source were excluded from the
fit out to a distance of 30, then the plots created
by plot_rprof(0,200,20) would start at the second bin (i.e.
for radii of 20-40).
sherpa> plot_rprofd(0,200,20)
This creates the same plot as in the previous example
except that the residual plot has units of "sigma"
- i.e. counts divided by the error estimate - rather
than counts.
sherpa> plot_rprofr(2,0,200,20)
This creates the radial profiles for dataset 2.
sherpa> plot_rprof("core",0,200,20)
Here we explicitly list which model should be used
to define the center of the profile;
we assume in this example that
"core" is a model component such as BETA2D (i.e. that
it has xpos and ypos parameters).
This is only necessary when one of the following holds:
-
The source expression contains more than one component
with "xpos" and "ypos" parameters, so you have to specify
which component to use.
-
There is no model component with both "xpos" and
"ypos" parameters so you have to name which
parameters define the center of the profile.
-
You wish to use a center which does not match
any of the model components.
Version 1.27 of sherpa_utils.sl
was released at the same time as CIAO 3.1. The major changes to
the previously-released version (1.19) are:
-
The plot_rprofr() and plot_rprofd() functions have been
added to plot the residuals in units of counts or
sigma (analogous to the "resid" and "delchi" options
of the lplot command). The plot_rprof() command is
kept for backwards compatability, and is the same as
plot_rprofr().
-
The plot_eprofr() and plot_eprofd() functions have
been added to calculate the profiles within elliptical
annuli.
-
The residuals are no longer noramlized by the area
of each annulus.
-
Error bars are now displayed (where the errors are
estimated using the approximations given in
Gehrels, N., 1986, Ap.J., 303, 336).
-
You can give just the model name, rather than the
names of the "xpos" and "ypos" parameters, to distinguish
which model to use to calculate the center of the
profile.
-
The residual plots are now smaller than the main
plot; previously they were the same size.
-
The residual plots now contain a line at "y=0".
This script is not an official part of the CIAO release but is
made available as "contributed" software via the
CIAO scripts page.
Please see the
installation instructions page for help on installing the package.
These functions are not an official part of the CIAO release but
are made available as part of the sherpa_plotfns.sl script
from the
CIAO scripts page.
Since the functions print a usage message if called with no
parameters, the easiest way to see if it has been loaded into
Sherpa is to try:
If the message
Parse Error/Undefined Name: plot_rprofr();
is seen then you need to load the
sherpa_plotfns.sl package into Sherpa.
See the "NOTES" section of the sherpa_plotfns ahelp file -
"ahelp -b ADESC -t NOTES sherpa_plotfns" - for
more information.
The plots produced by the plot_rprof() function
can be configured using the sherpa.fitplot and
sherpa.resplot configuration variables
(see 'ahelp sherpa.fitplot' and 'ahelp sherpa.resplot'
for more information).
This means that you can use the set_log(), set_lin(),
and related functions ('ahelp set_log', 'ahelp set_lin')
to control the scales (linear or log) of the plots.
The main items that are ignored from the sherpa.fitplot and
sherpa.resplot variables are:
-
The y-axis of the residual plot is always linear (sherpa.resplot.y_log
is ignored)
-
No error bars are drawn (the "error_bars" and "errs" variables are
ignored).
-
The prefunc and postfunc hooks are ignored.
The table below lists those fields that are used (the leading 'sherpa.'
has been dropped from all the variable names):
| fitplot.symbolstyle |
symbol used for the data |
| fitplot.symbolcolor |
symbol color for the data |
| fitplot.symbolsize |
symbol color for the data |
| fitplot.curvestyle |
curve style for the data |
| fitplot.curvecolor |
curve style for the data |
| fitplot.fit_symbolstyle |
symbol used for the model |
| fitplot.fit_symbolcolor |
symbol color for the model |
| fitplot.fit_symbolsize |
symbol color for the model |
| fitplot.fit_curvestyle |
curve style for the model |
| fitplot.fit_curvecolor |
curve style for the model |
| resplot.symbolstyle |
symbol used for the residuals |
| resplot.symbolcolor |
symbol color for the residuals |
| resplot.symbolsize |
symbol color for the residuals |
| resplot.curvestyle |
curve style for the residuals |
| resplot.curvecolor |
curve style for the residuals |
| fitplot.title_size |
The size of the title |
| fitplot.ylabel_size |
The size of the y-axis label for the data/fit plot |
| fitplot.tickvals_size |
The size of the axis numbers for the data/fit plot |
| resplot.xlabel_size |
The size of the x-axis label for the residual plot |
| resplot.ylabel_size |
The size of the y-axis label for the residual plot |
| resplot.tickvals_size |
The size of the axis numbers for the residual plot |
| fitplot.x_log |
Should the x-axis be logarithmic for the data/fit plot |
| fitplot.y_log |
Should the y-axis be logarithmic for the data/fit plot |
| resplot.x_log |
Should the x-axis be logarithmic for the residual plot |
The intent of the functions (both the circlular and elliptical annuli
versions) is to provide a quick comparison of the model to the data.
The radial profiles are calculated by looping through
each radial bin and finding all those pixels which lie within
the limits of the bin: for simplicity, only those pixels
whose centers lie within the radial limits of the bin are
used. The error on each bin is then calculated using the
1-sigma upper-limit approximation from
Gehrels, N., 1986 (Ap.J., 303, 336), namely:
error = ( 1 + sqrt(N + 0.75) )
where N is the sum of the pixel values within the bin.
This assumes that the pixel values are Poisson distributed.
The same routine is used to calculate the profiles of the
model and residual data (without calculating any errors).
When displaying the profiles, the data and model curves
are normalised by the number of pixel in each bin,
while the residuals are plotted with no normalisation
(prior to version 1.27 they were also normalised by
the bin area).
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