{"action":"created","issue":{"url":"https://api.github.com/repos/hmmlearn/hmmlearn/issues/186","repository_url":"https://api.github.com/repos/hmmlearn/hmmlearn","labels_url":"https://api.github.com/repos/hmmlearn/hmmlearn/issues/186/labels{/name}","comments_url":"https://api.github.com/repos/hmmlearn/hmmlearn/issues/186/comments","events_url":"https://api.github.com/repos/hmmlearn/hmmlearn/issues/186/events","html_url":"https://github.com/hmmlearn/hmmlearn/issues/186","id":214735840,"node_id":"MDU6SXNzdWUyMTQ3MzU4NDA=","number":186,"title":"ValueError: startprob_ must sum to 1.0 (got nan)","user":{"login":"Lila14","id":14185475,"node_id":"MDQ6VXNlcjE0MTg1NDc1","avatar_url":"https://avatars0.githubusercontent.com/u/14185475?v=4","gravatar_id":"","url":"https://api.github.com/users/Lila14","html_url":"https://github.com/Lila14","followers_url":"https://api.github.com/users/Lila14/followers","following_url":"https://api.github.com/users/Lila14/following{/other_user}","gists_url":"https://api.github.com/users/Lila14/gists{/gist_id}","starred_url":"https://api.github.com/users/Lila14/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Lila14/subscriptions","organizations_url":"https://api.github.com/users/Lila14/orgs","repos_url":"https://api.github.com/users/Lila14/repos","events_url":"https://api.github.com/users/Lila14/events{/privacy}","received_events_url":"https://api.github.com/users/Lila14/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":4,"created_at":"2017-03-16T15:06:53Z","updated_at":"2018-12-13T09:48:09Z","closed_at":null,"author_association":"NONE","body":"    from hmmlearn.hmm import GMMHMM\r\n    import numpy as np\r\n    scores = np.loadtxt(\"scores.txt\")\r\n    model = GMMHMM(n_components=3).fit(scores)\r\n    hidden_states = model.predict(scores)\r\n\r\nAfter many deprecation warnings, it produces the following error: \r\n\r\n> File \"build/bdist.linux-x86_64/egg/hmmlearn/base.py\", line 336, in predict\r\n>  File \"build/bdist.linux-x86_64/egg/hmmlearn/base.py\", line 296, in decode\r\n > File \"build/bdist.linux-x86_64/egg/hmmlearn/hmm.py\", line 713, in _check\r\n > File \"build/bdist.linux-x86_64/egg/hmmlearn/base.py\", line 519, in _check\r\n> ValueError: startprob_ must sum to 1.0 (got nan)\r\n\r\nMy dependencies are all up to date. \r\n\r\n[scores.txt](https://github.com/hmmlearn/hmmlearn/files/848113/scores.txt)\r\n"},"comment":{"url":"https://api.github.com/repos/hmmlearn/hmmlearn/issues/comments/446906356","html_url":"https://github.com/hmmlearn/hmmlearn/issues/186#issuecomment-446906356","issue_url":"https://api.github.com/repos/hmmlearn/hmmlearn/issues/186","id":446906356,"node_id":"MDEyOklzc3VlQ29tbWVudDQ0NjkwNjM1Ng==","user":{"login":"anntzer","id":1322974,"node_id":"MDQ6VXNlcjEzMjI5NzQ=","avatar_url":"https://avatars0.githubusercontent.com/u/1322974?v=4","gravatar_id":"","url":"https://api.github.com/users/anntzer","html_url":"https://github.com/anntzer","followers_url":"https://api.github.com/users/anntzer/followers","following_url":"https://api.github.com/users/anntzer/following{/other_user}","gists_url":"https://api.github.com/users/anntzer/gists{/gist_id}","starred_url":"https://api.github.com/users/anntzer/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/anntzer/subscriptions","organizations_url":"https://api.github.com/users/anntzer/orgs","repos_url":"https://api.github.com/users/anntzer/repos","events_url":"https://api.github.com/users/anntzer/events{/privacy}","received_events_url":"https://api.github.com/users/anntzer/received_events","type":"User","site_admin":false},"created_at":"2018-12-13T09:48:09Z","updated_at":"2018-12-13T09:48:09Z","author_association":"CONTRIBUTOR","body":"In the original data provided this is because the system only visits state #2 once, at the last data point, so we fail to compute a meaningful transition probability distribution away from that state.  Likely this should be fixed by getting that distribution according to transmat_prior_."}}
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