prof_model

Context: contrib

Synopsis

Plot a radial or elliptical profile of the model (after any PSF convolution) for imaging data.

Syntax

prof_model( [id], [model=None, rstep=None, rmin=None, rmax=None,
rlo=None, rhi=None, xpos=None, ypos=None, ellip=None, theta=None,
group_counts=None, group_snr=None, label=True, recalc=True,
overplot=False, clearwindow=True] )

Description

The prof_model command calculates the radial - or elliptical - profile of the source model of an imaging dataset and plots it. The profile is defined by the existing model compenents, although it is possible to over-ride these values.

The model values used to calculate the profile are those after convolution by any PSF model. Please use the prof_source() command if you want to plot the un-convolved model values.

Loading the routine

The routine can be loaded into Sherpa by saying:

from sherpa_contrib.profiles import *

Argument options

The argument options are the same as for the prof_data() command, and are described in its ahelp page.

Errors

Errors are not calculated for the model component.

Changing the plot defaults

The get_model_prof_prefs() returns the current plot preferences used by prof_model(). Changing these settings will therefore change the appearance of any new plots created by prof_model(). For example

sherpa> get_model_prof_prefs()["xlog"] = True

will cause any new plots to use logarithmic scaling for the X axis. A full list of the preferences can be found by saying

unix% ahelp get_model_prof_prefs

Examples

Example 1

sherpa> prof_model()
...
sherpa> prefs = get_model_prof_prefs()
sherpa> prefs["xlog"] = True
sherpa> prefs["ylog"] = True
sherpa> prof_model()

The preferences are set so that both the x and y axes should be drawn using log scaling. Setting the get_model_prof_prefs values only affects new plots made after the setting was changed.

Example 2

sherpa> prof_model(group_snr=15)

The source data is plotted after the bins have been grouped so that each bin has a signal to noise ratio of 15 or more, where the calculation is done using the data and not the model values.

Example 3

sherpa> prof_data()
sherpa> prof_source(overplot=True)
sherpa> prof_model(overplot=True)

Plots the profile for the data and then overplots the model profile, for the source and measured profiles.

Bugs

See the bugs pages on the Sherpa website for an up-to-date listing of known bugs.