def test_model_general_alt_correlations(nodmx_psrs, caplog):
# caplog.set_level(logging.CRITICAL)
m = models.model_general(
nodmx_psrs,
noisedict=noise_dict,
orf='hd,gw_monopole,gw_dipole,st,gt,dipole,monopole')
assert hasattr(m, 'get_lnlikelihood')
if args.rn_psrs[0] == 'all':
rn_psrs = 'all'
else:
rn_psrs = args.rn_psrs
pta_crn = models.model_general(
psrs,
tm_var=False,
Tspan=None,
common_psd=args.psd,
red_psd='powerlaw',
orf='crn',
common_components=args.n_gwbfreqs,
red_components=args.nfreqs,
dm_components=args.nfreqs,
noisedict=noise,
rn_psrs=rn_psrs,
gamma_common=args.gamma_gw,
delta_common=0.,
upper_limit=False,
bayesephem=args.bayes_ephem,
be_type='setIII',
dm_var=True,
dm_type='gp',
dm_psd='powerlaw',
)
Sampler = sampler.setup_sampler(pta_crn,
outdir=args.outdir,
resume=True,
empirical_distr=args.emp_distr)
pta = models.model_general(
psrs,
common_psd='powerlaw',
red_psd=args.psd,
orf=None,
common_components=args.nfreqs,
red_components=30,
dm_components=30,
modes=None,
wgts=None,
noisedict=noise_dict,
tm_svd=False,
tm_norm=True,
gamma_common=gamma_gw,
upper_limit=args.gwb_ul,
bayesephem=args.bayes_ephem,
wideband=args.wideband,
dm_var=True,
dm_type='gp',
dm_psd='powerlaw',
dm_annual=False,
white_vary=False,
gequad=False,
dm_chrom=False,
dmchrom_psd='powerlaw',
dmchrom_idx=4,
red_select=None,
red_breakflat=False,
red_breakflat_fq=None,
coefficients=False,
)