{"action":"created","issue":{"url":"https://api.github.com/repos/jwfoley/umi-bayes/issues/2","labels_url":"https://api.github.com/repos/jwfoley/umi-bayes/issues/2/labels{/name}","comments_url":"https://api.github.com/repos/jwfoley/umi-bayes/issues/2/comments","events_url":"https://api.github.com/repos/jwfoley/umi-bayes/issues/2/events","html_url":"https://github.com/jwfoley/umi-bayes/pull/2","id":109547708,"number":2,"title":"Devel","user":{"login":"turgeonmaxime","id":6857788,"avatar_url":"https://avatars.githubusercontent.com/u/6857788?v=3","gravatar_id":"","url":"https://api.github.com/users/turgeonmaxime","html_url":"https://github.com/turgeonmaxime","followers_url":"https://api.github.com/users/turgeonmaxime/followers","following_url":"https://api.github.com/users/turgeonmaxime/following{/other_user}","gists_url":"https://api.github.com/users/turgeonmaxime/gists{/gist_id}","starred_url":"https://api.github.com/users/turgeonmaxime/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/turgeonmaxime/subscriptions","organizations_url":"https://api.github.com/users/turgeonmaxime/orgs","repos_url":"https://api.github.com/users/turgeonmaxime/repos","events_url":"https://api.github.com/users/turgeonmaxime/events{/privacy}","received_events_url":"https://api.github.com/users/turgeonmaxime/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":6,"created_at":"2015-10-02T18:35:59Z","updated_at":"2015-10-12T14:37:38Z","closed_at":"2015-10-11T18:10:09Z","pull_request":{"url":"https://api.github.com/repos/jwfoley/umi-bayes/pulls/2","html_url":"https://github.com/jwfoley/umi-bayes/pull/2","diff_url":"https://github.com/jwfoley/umi-bayes/pull/2.diff","patch_url":"https://github.com/jwfoley/umi-bayes/pull/2.patch"},"body":"We don't need to merge it right now, but I thought we could discuss the following points:\r\n\r\n1. I'm using numpy.arrays as a convenience for myself, but since there is no complicated matrix operations we could easily change them to some other data type and remove that dependency.\r\n\r\n2. To generate random variates, I use the scipy module. Because of the need for a Dirichlet random variable, I need a recent version (>= 0.15.0). If this is too strong a requirement, we could draw from gammas or betas, which are both part of any version of scipy.\r\n\r\n3. As it is set-up right now, the MCMC algorithm is called using the default parameters (i.e. thining parameter, length of burn-in period and number of iterations are fixed). Perhaps we should add something to the parser to allow the user to change these parameters.\r\n\r\nLet me know what you think."},"comment":{"url":"https://api.github.com/repos/jwfoley/umi-bayes/issues/comments/147415378","html_url":"https://github.com/jwfoley/umi-bayes/pull/2#issuecomment-147415378","issue_url":"https://api.github.com/repos/jwfoley/umi-bayes/issues/2","id":147415378,"user":{"login":"turgeonmaxime","id":6857788,"avatar_url":"https://avatars.githubusercontent.com/u/6857788?v=3","gravatar_id":"","url":"https://api.github.com/users/turgeonmaxime","html_url":"https://github.com/turgeonmaxime","followers_url":"https://api.github.com/users/turgeonmaxime/followers","following_url":"https://api.github.com/users/turgeonmaxime/following{/other_user}","gists_url":"https://api.github.com/users/turgeonmaxime/gists{/gist_id}","starred_url":"https://api.github.com/users/turgeonmaxime/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/turgeonmaxime/subscriptions","organizations_url":"https://api.github.com/users/turgeonmaxime/orgs","repos_url":"https://api.github.com/users/turgeonmaxime/repos","events_url":"https://api.github.com/users/turgeonmaxime/events{/privacy}","received_events_url":"https://api.github.com/users/turgeonmaxime/received_events","type":"User","site_admin":false},"created_at":"2015-10-12T14:37:38Z","updated_at":"2015-10-12T14:37:38Z","body":"It's simply a consequence of the change in focus between the two\nalgorithms. Recall that in the R package, we were interested in estimating\nthe proportion of non-duplicates. In the Python implementation, we are\ninterested in the same proportion, but for each tag.\n\nHowever, now that we are estimating up to 1,000 parameters, we should\nprobably increase the default number of iterations. But this can wait until\nafter the optimisation phase is over, I think.\n\n2015-10-12 10:18 GMT-04:00 jwfoley <notifications@github.com>:\n\n> Is there a reason to prefer the way with the multiple medians? Cet. par.\n> it would be nice to minimize the random variation in rerunning the program.\n>\n> —\n> Reply to this email directly or view it on GitHub\n> <https://github.com/jwfoley/umi-bayes/pull/2#issuecomment-147411138>.\n>\n"}}