SPEX User's Manual - SRON

2.27 Step: Grid search for spectral fits 41
Examples
simulate - This simulates a new spectrum/dataset with Poissonian noise and background subtraction
with the same exposure time and background as the original data set.
simulate noise f - As above, but without Poissonian noise. The nominal error bars are still plotted.
simulate back f - As first example, but now no background is subtracted.
simulate time 10000 1. - Simulate for 10 4 s exposure time and the same background as the template
spectrum.
simulate time 10000 0.2 - Simulate for 10 4 s exposure time but with a 5 times more accurate subtracted
background (the background errors are 5 times smaller).
simulate syserr 0.1 0.2 - As before but with a systematic error of 10 % of the source spectrum and
20 % of the subtracted background spectrum added in quadrature.
simulate instrument 2:4 region 3 time 5000 1 syserr 0.05 0.01 noise f back f - Simulate a
spectrum for region 3 of instruments 2–4, with 5000 s exposure time t, the nominal background error
scaleng f b = 1, a systematic error of 5 % of the source and 1 % of the background, no Poissonian noise
and no background subtraction.
2.27 Step: Grid search for spectral fits
Overview
A grid search can be performed of χ 2 versus 1, 2, 3 or 4 parameters. The minimum, maximum and
number of steps for each parameter may be adjusted. Steps may be linear or logarithmic. For each set of
parameters, a spectral fit is made, using the last spectral fit executed before this command as the starting
point. For each step, the parameters and χ 2 are displayed. This option is useful in case of doubt about
the position of the best fit in the parameter space, or in cases where the usual error search is complicated.
Further it can be useful incases of complicated correlations between parameters.
Warning: Take care to do a spectral fit first!
Warning: Beware of the cpu-time if you have a fine grid or many dimensions!
Syntax
The following syntax rules apply:
step dimension #i - Define the number of axes for the search (between 1–4).
step axis #i1 parameter [[#i2] #i3] #a range #r1 #r2 n #i4 - Set for axis #i1, optional sector #i2,
optional component #i3 and parameter with name #a the range to the number specified by #r1 and
#r2, with a number of steps n given by #i4. If n > 0, a linear mesh between #r1 and #r2 will be taken,
for n < 0, a logarithmic grid will be taken.
step - Do the step search. Take care to do first the ”step dimension” command, followed by as many
”step axis” commands as you entered the number of dimensions.
Examples
Below we give a worked out example for a CIE model where we took as free parameters the normalization
”norm”, temperature ”t”, Si abundance ”14” and Fe abundance ”26”. To do a 3-dimensional grid search
on the temperature (logarithmic between 0.1 and 10 keV with 21 steps), Fe abundace (linear between 0.0
and 1.0 with 11 steps) and Si abundance (linear between 0.0 and 2.0 with 5 steps, i.e. values 0.0, 0.4,
0.8, 1.2, 1.6 and 2.0) the following commands should be issued:
fit - Do not forget to do first a fit
step dimension 3 - We will do a three-dimensional grid search
step axis 1 parameter 1 1 t range 0.1 10.0 n -21 - The logarithmic grid for the first axis, temperature;
note the − before the 21!