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Phi dependence is completely coded. Changes were required in the packages irfs/handoff_response, Likelihood, map_tools. All parts were separately tested, here we perform an overall check before the tools are considered ready for science analysis.

A new "P6_V5_DIFFUSE" irf was generated, with phi dependence in the aeff. The pruned goodEvents dataset used was the same used to generate "P6_V3_DIFFUSE", so the 2 irf sets should be directly comparable.

Aeff comparison

First, pyIrfLoader was used to compare the olf aeff with the new, averaged over all phi. This should make the 2 results identical. Let's see:

!p6v5d_aeffpanel.gif!Again, second plot is the aeff averaged over phi, the average is calculated by the script I used to make the plots. The P6V3 plot is the usual one.
Same for acceptance:

Obssim simulation

Very little more than above. 1 week, point source at (RA,DEC)=(60,0) spectrum is a power law, index -2. All is ok here: see the PHI-THETA plots below.

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