Add loglikelihood evaluations to pymultinest

Once the run is complete, read in the log likelihood from the
post_equal_weights.dat file and store it. This also reads in the samples
from the same place to avoid any mismatch in ordering between the two.
For a description of the post_equal_weights file see
https://github.com/JohannesBuchner/MultiNest

bilby/core/sampler/pymultinest.py

 from __future__ import absolute_import
 
+import os
+
+import numpy as np
+
 from ..utils import check_directory_exists_and_if_not_mkdir
 from ..utils import logger
 from .base_sampler import NestedSampler
@@ -78,8 +82,12 @@ class Pymultinest(NestedSampler):
             LogLikelihood=self.log_likelihood, Prior=self.prior_transform,
             n_dims=self.ndim, **self.kwargs)
 
+        post_equal_weights = os.path.join(
+            self.kwargs['outputfiles_basename'], 'post_equal_weights.dat')
+        post_equal_weights_data = np.loadtxt(post_equal_weights)
+        self.result.log_likelihood_evaluations = post_equal_weights_data[:, -1]
         self.result.sampler_output = out
-        self.result.samples = out['samples']
+        self.result.samples = post_equal_weights_data[:, :-1]
         self.result.log_evidence = out['logZ']
         self.result.log_evidence_err = out['logZerr']
         self.result.outputfiles_basename = self.kwargs['outputfiles_basename']