Main Interface¶
- GWDALI.GWDALI(GwPrms, detectors, FreeParams, new_priors=None, approx='TaylorF2', method='Doublet', sampler='nestle', diff_method='autodiff', dali_tensors=None, step_size=[1.e-6], run_sampler=True, hide_info=False, npoints=300, nwalkers=None, ntemps=10, nburn=0., limits=None, pos0=None, npool=None, verbose=True, remove_out=True, output_name=None, save_bilby_path=True, bilby_path='outputs_bilby/', enable_jax_waveforms=True, **kwargs)¶
Main interface of GWDALI v1.0.
Computes:
Detector strains
Signal-to-noise ratios
Fisher Matrix
Doublet tensors
Triplet tensors
Posterior samples
- Parameters:
GwPrms (dictionary) – Dictionary containing GW source parameters.
detectors (list) – Detector network configuration.
FreeParams (list) – Free parameters used in the inference.
new_priors (dictionary) – Redefine default priors.
approx (str) – Waveform approximant.
method (str) – Exact/Fisher/DALI method [
"Exact","Fisher","Singlet","Doublet","Triplet"].sampler (str) – Posterior sampler backend from bilby.
diff_method (str) – Derivative method [
"autodiff","numdiff"].dali_tensors (list) – User-defined DALI tensors (list of arrays).
step_size (float or list) – Numerical derivative step sizes (float or list).
run_sampler (bool) – Run posterior sampling.
hide_info (bool) – Hide terminal outputs.
npoints (int) – Number of posterior samples.
nwalkers (int) – Number of walkers used in MCMC samplers.
ntemps (int) – Number of temperatures in parallel tempering samplers.
nburn (float) – Burn-in fraction.
limits (dictionary) – Parameter limits used in the sampler.
pos0 (array) – Initial walker positions.
npool (int) – Number of multiprocessing pools.
verbose (bool) – Show sampler outputs.
remove_out (bool) – Remove posterior outliers.
output_name (str) – Output filename.
save_bilby_path (bool) – Save bilby outputs.
bilby_path (str) – Output directory for bilby files.
enable_jax_waveforms (bool) – Enable JAX waveform backend.
disable_jit (bool) – Disable
jax.jit().EarthRotation (bool) – Enable Earth rotation corrections.
jitgrad (bool) – Enable
jax.jit()on derivatives.
Supported approximants:
"TaylorF2""TaylorF2_ISCO""TaylorF2_Spinless""TaylorF2_Spinless_0PN""IMRPhenomA""IMRPhenomB""IMRPhenomC""IMRPhenomD""IMRPhenomHM"
- Returns:
Results, Tensors, runtimes- Return type:
tuple