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According to a study by Stephan Fegan done in the context of Fermi/LAT analysis, the best way to determine a butterfly diagram is to draw the envelope of the error ellipse of the model parameters. I implemented this method now in ctbutterfly. I also changed the output file, having now two columns giving as function of energy th minimum and maximum intensities.
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Conflicts: examples/show_butterfly.py
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$(abs_top_srcdir) does not exist on all systems.
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This avoids code duplication and makes use to the standard unit tests within the installation.
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For the moment, no test is done (I cannot get the cscript import working correctly).
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… running the science verification).
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This allows to execute the science verification using $ make science-verification
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This initial version tests the spectral power law model.
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The show_pull_evolution.py shows the evolution of the pull distribution mean and standard deviation as function of the number of samples. It is mainly used to assess from how many samples on the pull distributions becomes relatively stable.