def test_livepoints():
# Test the providing of initial live-points to the sampler
ndim = 2
rstate = get_rstate()
live_u = rstate.uniform(size=(nlive, ndim))
live_v = np.array([prior_transform(_) for _ in live_u])
live_logl = np.array([loglike(_) for _ in live_v])
live_points = [live_u, live_v, live_logl]
sampler = dynesty.NestedSampler(loglike,
prior_transform,
ndim,
nlive=nlive,
live_points=live_points,
rstate=rstate)
sampler.run_nested(print_progress=printing)
dyutil.unravel_run(sampler.results)
def test_livepoints():
# hard test of dynamic sampler with high dlogz_init and small number
# of live points
ndim = 2
rstate = get_rstate()
live_u = rstate.uniform(size=(ndim, 2))
live_v = np.array([prior_transform(_) for _ in live_u])
live_logl = np.array([loglike(_) for _ in live_v])
live_points = [live_u, live_v, live_logl]
sampler = dynesty.NestedSampler(loglike,
prior_transform,
ndim,
nlive=nlive,
live_points=live_points,
rstate=rstate)
sampler.run_nested()
dyutil.unravel_run(sampler.results)
def test_unravel():
# test unravel_run
ndim = 2
rstate = get_rstate()
sampler = dynesty.NestedSampler(loglike,
prior_transform,
ndim,
nlive=nlive,
rstate=rstate)
sampler.run_nested(print_progress=printing)
dyutil.unravel_run(sampler.results)
sampler = dynesty.DynamicNestedSampler(loglike,
prior_transform,
ndim,
nlive=nlive,
rstate=rstate)
sampler.run_nested(dlogz_init=1, maxcall=1000, print_progress=printing)
dyutil.unravel_run(sampler.results)
logps = sampler.results.logl
dyutil.reweight_run(sampler.results, logps / 4.)
def test_unravel():
# hard test of dynamic sampler with high dlogz_init and small number
# of live points
ndim = 2
rstate = get_rstate()
sampler = dynesty.NestedSampler(loglike,
prior_transform,
ndim,
nlive=nlive,
rstate=rstate)
sampler.run_nested()
dyutil.unravel_run(sampler.results)
sampler = dynesty.DynamicNestedSampler(loglike,
prior_transform,
ndim,
nlive=nlive,
rstate=rstate)
sampler.run_nested(dlogz_init=1, maxcall=1000)
dyutil.unravel_run(sampler.results)
logps = sampler.results.logl
dyutil.reweight_run(sampler.results, logps / 4.)
def test_ravel_unravel():
""" Here I test that ravel/unravel preserves things correctly """
rstate = get_rstate()
g = Gaussian()
dsampler = dynesty.DynamicNestedSampler(g.loglikelihood,
g.prior_transform,
g.ndim,
bound='single',
sample='unif',
rstate=rstate,
nlive=nlive)
maxiter = 1800
dsampler.run_nested(maxiter=maxiter,
use_stop=False,
nlive_batch=100,
print_progress=printing)
dres = dsampler.results
dres_list = dyfunc.unravel_run(dres)
dres_merge = dyfunc.merge_runs(dres_list)
assert np.abs(dres.logz[-1] - dres_merge.logz[-1]) < 0.01