{"action":"created","issue":{"url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/682","repository_url":"https://api.github.com/repos/markovmodel/PyEMMA","labels_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/682/labels{/name}","comments_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/682/comments","events_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/682/events","html_url":"https://github.com/markovmodel/PyEMMA/issues/682","id":131393699,"number":682,"title":"TICA partial fit","user":{"login":"stefdoerr","id":7935362,"avatar_url":"https://avatars.githubusercontent.com/u/7935362?v=3","gravatar_id":"","url":"https://api.github.com/users/stefdoerr","html_url":"https://github.com/stefdoerr","followers_url":"https://api.github.com/users/stefdoerr/followers","following_url":"https://api.github.com/users/stefdoerr/following{/other_user}","gists_url":"https://api.github.com/users/stefdoerr/gists{/gist_id}","starred_url":"https://api.github.com/users/stefdoerr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/stefdoerr/subscriptions","organizations_url":"https://api.github.com/users/stefdoerr/orgs","repos_url":"https://api.github.com/users/stefdoerr/repos","events_url":"https://api.github.com/users/stefdoerr/events{/privacy}","received_events_url":"https://api.github.com/users/stefdoerr/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":4,"created_at":"2016-02-04T16:04:52Z","updated_at":"2016-02-04T18:04:42Z","closed_at":null,"body":"Hello, I was wondering if you could make a [`partial_fit`](http://scikit-learn.org/stable/modules/scaling_strategies.html#incremental-learning) method for the `TICA` class (or if it exists already). So that I can feed it trajectory projections in a for loop and fit it incrementally, without having to give the whole dataset at once."},"comment":{"url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/comments/179971330","html_url":"https://github.com/markovmodel/PyEMMA/issues/682#issuecomment-179971330","issue_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/682","id":179971330,"user":{"login":"franknoe","id":6495810,"avatar_url":"https://avatars.githubusercontent.com/u/6495810?v=3","gravatar_id":"","url":"https://api.github.com/users/franknoe","html_url":"https://github.com/franknoe","followers_url":"https://api.github.com/users/franknoe/followers","following_url":"https://api.github.com/users/franknoe/following{/other_user}","gists_url":"https://api.github.com/users/franknoe/gists{/gist_id}","starred_url":"https://api.github.com/users/franknoe/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/franknoe/subscriptions","organizations_url":"https://api.github.com/users/franknoe/orgs","repos_url":"https://api.github.com/users/franknoe/repos","events_url":"https://api.github.com/users/franknoe/events{/privacy}","received_events_url":"https://api.github.com/users/franknoe/received_events","type":"User","site_admin":false},"created_at":"2016-02-04T18:04:42Z","updated_at":"2016-02-04T18:04:42Z","body":"That's an option, thanks!\n\nAm 04/02/16 um 19:01 schrieb Matthew Harrigan:\n>\n> We use a flag |_is_dirty| that we set every time new data is added\n>\n> https://github.com/msmbuilder/msmbuilder/blob/master/msmbuilder/decomposition/tica.py#L155\n>\n> Any time you use the eigenvectors, it checks this flag and recomputes \n> the eigensystem if necessary\n>\n> https://github.com/msmbuilder/msmbuilder/blob/master/msmbuilder/decomposition/tica.py#L198\n>\n> —\n> Reply to this email directly or view it on GitHub \n> <https://github.com/markovmodel/PyEMMA/issues/682#issuecomment-179969681>.\n>\n\n\n-- \n\n----------------------------------------------\nProf. Dr. Frank Noe\nHead of Computational Molecular Biology group\nFreie Universitaet Berlin\n\nPhone: (+49) (0)30 838 75354\nWeb:   research.franknoe.de\nMail:  Arnimallee 6, 14195 Berlin, Germany\n----------------------------------------------\n\n"}}