Difference between revisions of "MC Routines"
From magneticfields
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To generate synthetic data, we adopt the fiducial model that the diffuse gamma ray background is isotropic. | To generate synthetic data, we adopt the fiducial model that the diffuse gamma ray background is isotropic. | ||
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== Ferrer's MC Python routines == | == Ferrer's MC Python routines == | ||
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The script [[Media:mc.py]] generates 10000 synthetic samples with the same number of events in the real data. The events are uniformly distributed in the spherical caps and do not fall close to a Fermi source. The samples are saved to disk in numpy array format. Their statistics (average and standard deviation is computed using this script [[Media:qstat.py]]. For b>80deg we obtain the following MC samples [[Media:mc80.tar.gz]]. | The script [[Media:mc.py]] generates 10000 synthetic samples with the same number of events in the real data. The events are uniformly distributed in the spherical caps and do not fall close to a Fermi source. The samples are saved to disk in numpy array format. Their statistics (average and standard deviation is computed using this script [[Media:qstat.py]]. For b>80deg we obtain the following MC samples [[Media:mc80.tar.gz]]. | ||
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+ | == Tashiro's MC routines in Fortran == | ||
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+ | Tashiro's MC routines in Fortran are included in |
Revision as of 11:33, 20 May 2014
To generate synthetic data, we adopt the fiducial model that the diffuse gamma ray background is isotropic.
Ferrer's MC Python routines
Here are Ferrer's MC routines in Python:
The script Media:mc.py generates 10000 synthetic samples with the same number of events in the real data. The events are uniformly distributed in the spherical caps and do not fall close to a Fermi source. The samples are saved to disk in numpy array format. Their statistics (average and standard deviation is computed using this script Media:qstat.py. For b>80deg we obtain the following MC samples Media:mc80.tar.gz.
Tashiro's MC routines in Fortran
Tashiro's MC routines in Fortran are included in