{"action":"created","issue":{"url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/951","repository_url":"https://api.github.com/repos/markovmodel/PyEMMA","labels_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/951/labels{/name}","comments_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/951/comments","events_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/951/events","html_url":"https://github.com/markovmodel/PyEMMA/issues/951","id":180489970,"number":951,"title":"Continuous time MSM","user":{"login":"MamtaMohan","id":16194813,"avatar_url":"https://avatars.githubusercontent.com/u/16194813?v=3","gravatar_id":"","url":"https://api.github.com/users/MamtaMohan","html_url":"https://github.com/MamtaMohan","followers_url":"https://api.github.com/users/MamtaMohan/followers","following_url":"https://api.github.com/users/MamtaMohan/following{/other_user}","gists_url":"https://api.github.com/users/MamtaMohan/gists{/gist_id}","starred_url":"https://api.github.com/users/MamtaMohan/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/MamtaMohan/subscriptions","organizations_url":"https://api.github.com/users/MamtaMohan/orgs","repos_url":"https://api.github.com/users/MamtaMohan/repos","events_url":"https://api.github.com/users/MamtaMohan/events{/privacy}","received_events_url":"https://api.github.com/users/MamtaMohan/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":18,"created_at":"2016-10-02T01:45:05Z","updated_at":"2016-11-17T12:40:45Z","closed_at":null,"body":"Hi,\n\nIs it possible to generate continuous time MSM with pyEMMA.\n\nMamta\n"},"comment":{"url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/comments/261236995","html_url":"https://github.com/markovmodel/PyEMMA/issues/951#issuecomment-261236995","issue_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/951","id":261236995,"user":{"login":"marscher","id":170287,"avatar_url":"https://avatars.githubusercontent.com/u/170287?v=3","gravatar_id":"","url":"https://api.github.com/users/marscher","html_url":"https://github.com/marscher","followers_url":"https://api.github.com/users/marscher/followers","following_url":"https://api.github.com/users/marscher/following{/other_user}","gists_url":"https://api.github.com/users/marscher/gists{/gist_id}","starred_url":"https://api.github.com/users/marscher/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/marscher/subscriptions","organizations_url":"https://api.github.com/users/marscher/orgs","repos_url":"https://api.github.com/users/marscher/repos","events_url":"https://api.github.com/users/marscher/events{/privacy}","received_events_url":"https://api.github.com/users/marscher/received_events","type":"User","site_admin":false},"created_at":"2016-11-17T12:40:45Z","updated_at":"2016-11-17T12:40:45Z","body":"On 11/16/2016 03:46 AM, Frank Noe wrote:\n> Hi,\n> \n> you may need to update msmtools:\n> conda install msmtools\n> \n> then your import statement should work as this:\n> from msmtools.estimation import estimate_rate_matrix\nThe function is just called rate_matrix, in analogy to the function transition_matrix.\n\nTo easily get a correct (connected count matrix) you can first estimate an msm via\npyemma and re-use the count_matrix_active property:\n\nmsmtools.estimation.rate_matrix(msm.count_matrix_active)\n\n\n"}}
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