Bilby-MCMC unable to handle calibration parameters when using the ensemble sampler

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We get a "RuntimeError: Invalid argument" in the analysis when we try to use calibration-model=CubicSpline with spline-calibration-envelope-dict=[our list], spline-calibration-nodes=10, spline-calibration-amplitude-uncertainty-dict=None and spline-calibration-phase-uncertainty-dict=None.

Seems it starts after this XAL Error: XLAL Error - XLALSimInspiralTransformPrecessingNewInitialConditions: chi1,2=0 must be between 0 and 1, values -0.0533 -- 0.5992 passed. XLAL Error - XLALSimInspiralTransformPrecessingNewInitialConditions (../../../lalsuite/lalsimulation/lib/LALSimInspiral.c:5896): Invalid argument

Maite has just hacked the code https://git.ligo.org/lscsoft/bilby/-/blob/master/bilby/bilby_mcmc/proposals.py#L986 to make that list empty. ->

def get_proposal_cycle(string, priors, L1steps=1, warn=True): big_weight = 10 small_weight = 5 tiny_weight = 0.1

if "gwA" in string:
    # Parameters for learning proposals
    learning_kwargs = dict(
        first_fit=1000, nsamples_for_density=10000, fit_multiplier=2
    )

    plist = []
       # AdaptiveGaussianProposal(priors, weight=small_weight),
       # DifferentialEvolutionProposal(priors, weight=small_weight),
    #]

But we still get the same error.

bilby_mcmc_test_IMRPhenomTPHM_n_1000_new_config_complete.ini

bilby_mcmc_test_IMRPhenomTPHM_n_1000_new_data0_1242442967-447266_analysis_H1L1V1_bilby_mcmc.err

We found that this issue was related with using nensemble>1 and calibration-model=CubicSpline. Meanwhile we do not find the bug you can not use both at the same time.

changed title from Bilby-MCMC unable to handle calibration parameters to Bilby-MCMC unable to handle calibration parameters when using the ensemble sampler

created merge request !1079 (merged) to address this issue

mentioned in merge request !1079 (merged)

mentioned in commit 84016656

closed with merge request !1079 (merged)