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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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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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* 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
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WARNING: The philosophy behind the ctbin tool changed fundamentally! ctbin now always produces a single counts cube on output. If a single event list is specified on input, the functionnality is basically unchanged. If multiple event lists are specified, however, events are now merged into a single counts cube file. No observation definition XML file is written anymore! So far, ctbin still writes pointing information in the counts cube, although this is not necessarily meaningful if merging event lists with different pointings. In the long run, pointing information will be summarized in a pointings definition file, and will be removed from the counts cube header. The logic is that the pointing definition is set to the map centre. This is only identical to the pointing in case of binning a single event list and using the usepnt=yes option (or specifying the pointing manually as the xref and yref parameters).
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Conflicts: scripts/obsutils.py
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The ctexpcube tool is now functional, a unit test has been added.
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…ions without corresponding input file names. Also changed code so that an XML is always written even if just one observation.
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ctobssim was not fully thread save as the models were shared among the threads which led to concurrent memory access when evaluating the Monte Carlo cache. The models are now copied within the parallel section, avoiding concurrent memory access (#1258).
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Conflicts: ChangeLog scripts/cta_root2caldb.py src/ctlike/ctlike.par src/ctobssim/ctobssim.par