Waveform plot failing for aligned spins
When creating a summary page for a bilby run with an aligned spin approximant, creating the waveform plot fails with the following error:
XLAL Error - XLALSimInspiralChooseFDWaveform_legacy (/home/conda/feedstock_root/build_artifacts/lalsimulation-split_1698398745173/work/lib/LALSimInspiralGeneratorLegacy.c:1789): Non-zero transverse spins were given, but this is a non-precessing approximant.
XLAL Error - XLALSimInspiralChooseFDWaveform_legacy (/home/conda/feedstock_root/build_artifacts/lalsimulation-split_1698398745173/work/lib/LALSimInspiralGeneratorLegacy.c:1789): Invalid argument
XLAL Error - XLALSimInspiralChooseFDWaveform_legacy (/home/conda/feedstock_root/build_artifacts/lalsimulation-split_1698398745173/work/lib/LALSimInspiralGeneratorLegacy.c:1789): Non-zero transverse spins were given, but this is a non-precessing approximant.
XLAL Error - XLALSimInspiralChooseFDWaveform_legacy (/home/conda/feedstock_root/build_artifacts/lalsimulation-split_1698398745173/work/lib/LALSimInspiralGeneratorLegacy.c:1789): Invalid argument
2023-11-06 19:23:10 PESummary INFO : Failed to generate waveform_fd plot because Invalid argument
In the samples, the transverse spin components S1x
, S1y
, S2x
and S2y
are exactly 0 (I used aligned spin priors). I have narrowed down this issue to be with lalsim.SimInspiralTransformPrecessingNewInitialConditions
in this line which sometimes returns non-zero, but very small, values for S1x
, S1y
, S2x
or S2y
when tilt_1
or tilt_2
is pi due to numerical round off errors. I think this could be prevented by checking if an aligned spin approximant is used and in that case setting S1x
, S1y
, S2x
and S2y
to 0 when calling the waveform.
I also noticed these errors where a check for aligned spin waveforms might be nice to add:
2023-11-06 19:22:29 PESummary INFO : Failed to generate chi_p-chi_eff triangle plot because The data appears to lie in a lower-dimensional subspace of the space in which it is expressed. This has resulted in a singular data covariance matrix, which cannot be treated using the algorithms implemented in `gaussian_kde`. Consider performing principle component analysis / dimensionality reduction and using `gaussian_kde` with the transformed data.
2023-11-06 19:22:30 PESummary INFO : Failed to generate cos_theta_jn-chi_p triangle plot because The data appears to lie in a lower-dimensional subspace of the space in which it is expressed. This has resulted in a singular data covariance matrix, which cannot be treated using the algorithms implemented in `gaussian_kde`. Consider performing principle component analysis / dimensionality reduction and using `gaussian_kde` with the transformed data.
In case it is useful, my error file is located here on cit: /home/elise.sanger/tgrflow-dev/asimov/working/GW200311_115853/fti_dchiMinus2/pesummary.err
and the webpage is here.