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The purpose of the make_cube_analysis.py script is to provide an end-to-end test fur stacked cube analysis. It uses 4 CTA observations to illustrate the usage of stacked cube analysis and to demonstrate that the fitting results are okay.
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We do not want to fill cube bins outside the RoI to be consistent with the response and modelling part.
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The background models are now livetime weighted before addition, and only event bins are filled that fall within the RoI of the corresponding event list.
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…bservation::hasresponse()
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Still needs to be seen how the error computation can be switched off for recomputation.
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…o demonstrate its usage.
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The ctbkgcube tool generates a background model for cube-style analysis.
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In the adaption to cube-style analysis, response and model information was lost in the observation container. Now, model information is conserved, and in case of a single CTA observation, response information is carried over. This provides support for the original binned analysis.
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This sets up the system completly. From then on, unit test can be implemented.
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The GammaLib Test Suite is now used by the ctools Python unit test. Reports are written into reports/ctools.xml.
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* Checked the code for coding conventions. * Renamed the angular seperation user parameters to amax and anumbins. "a" stands for angular separation, "d" for delta is less explicit. * Add ctpsfcube executable unit test