Quick startΒΆ
Warning
This is now already obsolete and we should revamp it to the latest ximpol versions.
The main purpose of this simulation package is to simulate an observation of a given source model, based on suitable detector response functions.
The main Monte Carlo simulation script is ximpol/bin/xpobssim and its signature is
ximpol/bin/xpobssim.py
usage: xpobssim.py [-h] -o OUTPUT_FILE -c CONFIG_FILE [-r IRF_NAME]
[-d DURATION] [-t START_TIME] [-n TIME_STEPS]
[-s RANDOM_SEED]
Assuming that the current working directory is the ximpol root folder, the command
ximpol/bin/xpobssim.py -c ximpol/srcmodel/config/stationary_point_pl.py -d 100 -o test.fits
should produce an event (FITS) file with a 100 s simulation of a stationary source with a power-law spectrum (with an index of 2 and normalization of 10) with energy- and time-independent polarization degree and angle (correctly folded with all the instrument response functions: effective area, modulation factor, energy dispersion and point-spread function). The format definition for the event file is in ximpol/evt/event.py.
You can take a quick look at the output file by typing
ximpol/bin/xpevtview.py test.fits
We are already fully equipped for a basic spectral analysis with XSPEC. The first step is to bin the event file by running the xpbin tool (which creates a test.pha file):
ximpol/bin/xpbin.py test.fits
Finally we can feed the binned file (along with the corresponding .arf and .rmf response functions) into XSPEC and recover the input parameters of our source.
ximpol/bin/xpxspec.py test.pha
Note that xpspec.py is an example of how to use pyXspec, unfortunately not all of the XSPEC capabilties have been implemented in pyXspec (for example how to save a plot) so it is left to the user to decide whether to use XSPEC or pyXSPEC for the spectral analysis.
Below is the output from XSPEC on test.pha:
Model powerlaw<1> Source No.: 1 Active/On
Model Model Component Parameter Unit Value
par comp
1 1 powerlaw PhoIndex 2.00546 +/- 9.41951E-03
2 1 powerlaw norm 10.0265 +/- 7.12876E-02
Test statistic : Chi-Squared = 196.87 using 220 PHA bins.
Reduced chi-squared = 0.90308 for 218 degrees of freedom
Null hypothesis probability = 8.447913e-01