Adding support for SEOBNRv5EHM#332
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Monkey-hack of bilby_pipe.create_injections.py.
Ensure everything but the inference parameters are stripped from theta. For samples coming from Result, existing values for log_prob were being added to new ones.
This is needed for models with DeltaFunction ra priors.
Adapted from Bilby. Also added parameter names to default priors, so that they pick up latex labels for plotting.
To use, set plot-pp = true in INI file.
Set dingo-injections = true in INI file. Noise is still generated using bilby_pipe.
Co-authored-by: Nihar Gupte <40392612+nihargupte-ph@users.noreply.github.com>
…g to change it via args.injection-waveform-arguments
Adding BLAS and MKL threading options so that the scipy/numpy svd function doesn't segfault
…nto injections-pipe-stephen
Adding BLAS and MKL threading options so that the scipy/numpy svd function doesn't segfault
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Looks good! I left a few small comments. On a longer term, I would love for this code not to have any line like but to look up relevant information from the gwsignal metadata, using and Still, I realize things are not too polished on the gwsignal side so it's probably not worth thinking now about these kind of changes (TEOBResumS has a few more info, but SEOBNRv5EHM is still lacking some of these); I'm leaving this comment anyway to keep this in mind, one can update this in the future. |
- Consolidate TEOB mode generation into generate_TD_modes_L0 with return_lal parameter (True by default, False for TEOB gwpy pipeline). Fixes incorrect negative distance rescaling sign for TEOB. - Fix typo in TEOB branch condition: "TEOBREsumSDALI" -> "TEOBResumSDALI" - Remove dead code from wfg_utils.py: lalseries_to_gwpy_timeseries_in_place, gwpyseries_to_lalseries_in_place, and the entire Stage 1/2 TEOB conditioning chain (get_conditioning_params_for_TEOB, condition_td_modes_for_TEOB_in_place, _high_pass_complex, _condition_stage1_complex, _condition_stage2_complex) which was superseded by the sigmoid taper approach. - Clean up unused imports (butter, sosfiltfilt, astropy.units). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Use parameters["phase"] instead of self.spin_conversion_phase for TEOB epoch computation and spherical harmonics, consistent with SEOBNRv5EHM. Pass deferred_timeshift_data in test for correct phase-dependent epoch. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Remove leftover debug raise that broke CI when EOBRun_module isn't installed. Restructure approximant detection so pyseobnr and EOBRun_module are checked independently and contribute their approximants additively. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The debug branch was enabled and tried to savefig to a hardcoded local path that does not exist on CI runners, causing the CI failure. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Replace dingo's reimplementation of the sigmoid taper (_compute_sigmoid_taper_params, _compute_sigmoid_window) with a get_tapering_window_for_real_array helper that calls cond.taper_gwpy_timeseries on a copy and recovers the window via |tapered|/|original|, mirroring the LAL-side get_tapering_window_for_complex_time_series trick. TEOB mode-resum output is bit-identical to the previous implementation. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
PESummary's standard_names dictionary maps spin_1z/spin_2z but not chi_1/chi_2, so without this rename the spin conversion path is skipped and a_1, chi_eff, chi_p, final_spin etc. collapse to zero in the generated webpages. Apply the rename in get_pesummary_samples and the matching pesummary_prior so derived spin quantities are computed from the actual posterior. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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This PR adds support for SEOBNRv5EHM through the new waveform interface. Note that unlike SEOBNRv5PHM and SEOBNRv5HM, SEOBNRv5EHM uses different conditioning routines. In particular, it doesn't use the stepping back of the starting frequency since the reference frequency is equal to the starting freqeuncy. This is why different routines are use when doing the summation in the m modes.