"""Provides IO for the nessai sampler"""
import numpy
from .base_nested_sampler import BaseNestedSamplerFile
from .posterior import read_raw_samples_from_file
from .dynesty import CommonNestedMetadataIO
[docs]class NessaiFile(CommonNestedMetadataIO, BaseNestedSamplerFile):
"""Class to handle file IO for the ``nessai`` sampler."""
name = "nessai_file"
[docs] def read_raw_samples(self, fields, raw_samples=False, seed=0):
"""Reads samples from a nessai file and constructs a posterior.
Using rejection sampling to resample the nested samples
Parameters
----------
fields : list of str
The names of the parameters to load. Names must correspond to
dataset names in the file's ``samples`` group.
raw_samples : bool, optional
Return the raw (unweighted) samples instead of the estimated
posterior samples. Default is False.
Returns
-------
dict :
Dictionary of parameter fields -> samples.
"""
samples = read_raw_samples_from_file(self, fields)
logwt = read_raw_samples_from_file(self, ['logwt'])['logwt']
loglikelihood = read_raw_samples_from_file(
self, ['loglikelihood'])['loglikelihood']
if not raw_samples:
n_samples = len(logwt)
# Rejection sample
rng = numpy.random.default_rng(seed)
logwt -= logwt.max()
logu = numpy.log(rng.random(n_samples))
keep = logwt > logu
post = {'loglikelihood': loglikelihood[keep]}
for param in fields:
post[param] = samples[param][keep]
return post
return samples