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Update fitter.py #81

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48 changes: 29 additions & 19 deletions astroARIADNE/fitter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -692,21 +692,28 @@ def fit_dynesty(self, out_file=None):
if self._dynamic:
if self._threads > 1:
with Pool(self._threads) as executor:
self.sampler = dynesty.DynamicNestedSampler(
self.sampler = dynesty.NestedSampler(
dynesty_log_like, pt_dynesty, self.ndim,
bound=self._bound, sample=self._sample,
nlive=self._nlive, bound=self._bound,
sample=self._sample,
pool=executor, walks=25,
queue_size=self._threads - 1
queue_size=self._threads - 1,
logl_args=(flux, flux_er, filts, coordinator, fixed, use_norm, wave, interpolator, av_law),
ptform_args=(flux, flux_er, filts, prior_dict, coordinator, use_norm),
)
self.sampler.run_nested(dlogz_init=self._dlogz,
nlive_init=self._nlive,
wt_kwargs={'pfrac': 1})
else:
self.sampler = dynesty.DynamicNestedSampler(
dynesty_log_like, pt_dynesty, self.ndim, walks=25,
bound=self._bound, sample=self._sample

)
self.sampler = dynesty.NestedSampler(
dynesty_log_like, pt_dynesty, self.ndim,
nlive=self._nlive, bound=self._bound,
sample=self._sample,
pool=executor, walks=25,
queue_size=self._threads - 1,
logl_args=(flux, flux_er, filts, coordinator, fixed, use_norm, wave, interpolator, av_law),
ptform_args=(flux, flux_er, filts, prior_dict, coordinator, use_norm),
)
self.sampler.run_nested(dlogz_init=self._dlogz,
nlive_init=self._nlive,
wt_kwargs={'pfrac': 1})
Expand All @@ -719,14 +726,20 @@ def fit_dynesty(self, out_file=None):
sample=self._sample,
pool=executor, walks=25,
queue_size=self._threads - 1,
logl_args=(flux, flux_er, filts, coordinator, fixed, use_norm, wave, interpolator, av_law),
ptform_args=(flux, flux_er, filts, prior_dict, coordinator, use_norm),
)
self.sampler.run_nested(dlogz=self._dlogz)
else:
self.sampler = dynesty.NestedSampler(
dynesty_log_like, pt_dynesty, self.ndim, walks=25,
nlive=self._nlive, bound=self._bound,
sample=self._sample
)
dynesty_log_like, pt_dynesty, self.ndim,
nlive=self._nlive, bound=self._bound,
sample=self._sample,
pool=executor, walks=25,
queue_size=self._threads - 1,
logl_args=(flux, flux_er, filts, coordinator, fixed, use_norm, wave, interpolator, av_law),
ptform_args=(flux, flux_er, filts, prior_dict, coordinator, use_norm),
)
self.sampler.run_nested(dlogz=self._dlogz)
results = self.sampler.results
if out_file is None:
Expand Down Expand Up @@ -1472,16 +1485,13 @@ def dynesty_loglike_bma(cube, interpolator):
return log_likelihood(theta, star, interpolator, use_norm, av_law)


def dynesty_log_like(cube):
def dynesty_log_like(cube, flux, flux_er, filts, coordinator, fixed, use_norm, wave, interpolator, av_law):
"""Dynesty log likelihood wrapper."""
theta = build_params(
cube, flux, flux_er, filts, coordinator, fixed, use_norm
)
return log_likelihood(theta, flux, flux_er, wave,
filts, interpolator, use_norm, av_law)
theta = build_params(cube, flux, flux_er, filts, coordinator, fixed, use_norm)
return log_likelihood(theta, flux, flux_er, wave, filts, interpolator, use_norm, av_law)


def pt_dynesty(cube):
def pt_dynesty(cube, flux, flux_er, filts, prior_dict, coordinator, use_norm):
"""Dynesty prior transform."""
return prior_transform_dynesty(cube, flux, flux_er, filts, prior_dict,
coordinator, use_norm)
Expand Down