{"action":"opened","issue":{"url":"https://api.github.com/repos/aimalz/SNeLightcurveQualityMetric/issues/4","repository_url":"https://api.github.com/repos/aimalz/SNeLightcurveQualityMetric","labels_url":"https://api.github.com/repos/aimalz/SNeLightcurveQualityMetric/issues/4/labels{/name}","comments_url":"https://api.github.com/repos/aimalz/SNeLightcurveQualityMetric/issues/4/comments","events_url":"https://api.github.com/repos/aimalz/SNeLightcurveQualityMetric/issues/4/events","html_url":"https://github.com/aimalz/SNeLightcurveQualityMetric/issues/4","id":148571684,"number":4,"title":"MCMC runs too expensive to throw away","user":{"login":"rbiswas4","id":2281358,"avatar_url":"https://avatars.githubusercontent.com/u/2281358?v=3","gravatar_id":"","url":"https://api.github.com/users/rbiswas4","html_url":"https://github.com/rbiswas4","followers_url":"https://api.github.com/users/rbiswas4/followers","following_url":"https://api.github.com/users/rbiswas4/following{/other_user}","gists_url":"https://api.github.com/users/rbiswas4/gists{/gist_id}","starred_url":"https://api.github.com/users/rbiswas4/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/rbiswas4/subscriptions","organizations_url":"https://api.github.com/users/rbiswas4/orgs","repos_url":"https://api.github.com/users/rbiswas4/repos","events_url":"https://api.github.com/users/rbiswas4/events{/privacy}","received_events_url":"https://api.github.com/users/rbiswas4/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":0,"created_at":"2016-04-15T06:54:14Z","updated_at":"2016-04-15T06:54:14Z","closed_at":null,"body":"The computational time that we are spending on MCMC is considerable, since we are running a number of MCMC chains for a single SN to obtain the expectation over realizations of $t_0.$ While our current calculations only involve an estimate of the width, it would be good if we keep the samples and not throw them away after the evaluation. A good method of storing the samples is in hdf files that are easy to right to from astropy Tables/ pandas DataFrames. What needs a bit more thought is to have a good way of arranging this in an hdf file.\r\n "}}