Open AdityaSavara opened 3 years ago
self.map_logP = max(self.post_burn_in_log_posteriors_un_normed_vec)
self.map_index = list(self.post_burn_in_log_posteriors_un_normed_vec).index(self.map_logP) #This does not have to be a unique answer, just one of them places which gives map_logP.
self.map_parameter_set = self.post_burn_in_samples[self.map_index] #This is the point with the highest probability in the posterior.
right now, to fix this oversight, I am pickling the map_logP and map_logP parameters separately. Perhaps this is not such a bad idea since it means that the value can also be retrieved without unpacking any large arrays.
This should also be exported to pickle and is not right now: mcmc_map_parameter_set
Currently, as of Oct 14th 2020, version 0.1.2, the post_burn_in_statistics looks like this:
[self.map_parameter_set, self.mu_AP_parameter_set, self.stdap_parameter_set, self.evidence, self.info_gain, self.post_burn_in_samples, self.post_burn_in_log_posteriors_un_normed_vec] = current_post_burn_in_statistics_data
There is no map_logP value in there! During gridsearch parallelization, this means the map_logP has (currently) got to be calculated again for each sample in order to compare the final values.
This should be easy to fix, but could break a few past examples.