ENH: implement time marginalization into multiband likelihood #842
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It looks like this was broken by the requirement that we don't have superfluous waveform kwargs. |
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- bilby/gw/likelihood/multiband.py: implement time marginalization and resampling of time - test/gw/likelihood/marginalization_test.py: add marginalization tests for multiband likelihood
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…dev#842) - bilby/gw/likelihood/multiband.py: implement time marginalization and resampling of time - test/gw/likelihood/marginalization_test.py: add marginalization tests for multiband likelihood
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This MR implements time marginalization into multiband likelihood. Time marginalization for multiband may be useful since the slow down factor of time marginalization is not as large as that for ROQ or relative binning. The plots below show the likelihood evaluation time of multiband/standard likelihood and with/without time marginalization for 16s XPHM, 64s XPHM, and 128s Pv2_NRtidalv2. The slow down is less than 2 for the first 2 cases.