{"action":"opened","issue":{"url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/474","labels_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/474/labels{/name}","comments_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/474/comments","events_url":"https://api.github.com/repos/markovmodel/PyEMMA/issues/474/events","html_url":"https://github.com/markovmodel/PyEMMA/issues/474","id":98617611,"number":474,"title":"Please check phi/psi featurizer in 1.2.2 release","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},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":{"url":"https://api.github.com/repos/markovmodel/PyEMMA/milestones/5","html_url":"https://github.com/markovmodel/PyEMMA/milestones/v1.3","labels_url":"https://api.github.com/repos/markovmodel/PyEMMA/milestones/5/labels","id":1063219,"number":5,"title":"v1.3","description":"A number of functionality improvements are planned. Let us see how many really go into this release:\r\n\r\n* Include Hidden Markov models (discrete and Gaussian) from bhmm (via dependency, no code duplication). The discrete HMM should have an identical API like the MSM object and can go into the msm package (msm = discrete Markovian state models, including hidden and direct).\r\n* Include dTRAM from pytram package (via dependency, no code duplication). Think about how to make use of estimation / counting functionality of pyemma for TRAM. Think about how to extend the coordinates package so as to allow input generation for TRAM (e.g. we need energy trajectories). Connectivity functionalities can probably be used. MSM analysis functionality can be used. TRAM could generate a list of Markov models with the pyEMMA signature.\r\n* Incorporate Bayesian methods for MSM and HMM estimation. @franknoe has worked out a concept to unify the API with the existing maximum likelihood estimators.\r\n* Explicit sparse matrix support for msms.","creator":{"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},"open_issues":10,"closed_issues":19,"state":"open","created_at":"2015-04-11T16:21:44Z","updated_at":"2015-08-02T15:47:07Z","due_on":null,"closed_at":null},"comments":0,"created_at":"2015-08-02T15:47:07Z","updated_at":"2015-08-02T15:47:07Z","closed_at":null,"body":"In this notebook:\r\n\r\n    http://www.emma-project.org/latest/generated/md2msm_penta_peptide.html\r\n\r\nthe featurizer description that shows up is this:\r\n\r\n```\r\n['COS(PHI 0 LEU 2 )',\r\n 'SIN(PHI 0 LEU 2 )',\r\n 'COS(PHI 0 ALA 3 )',\r\n 'SIN(PHI 0 ALA 3 )',\r\n 'COS(PHI 0 LEU 4 )',\r\n 'SIN(PHI 0 LEU 4 )',\r\n 'COS(PHI 0 LEU 5 )',\r\n 'SIN(PHI 0 LEU 5 )',\r\n 'COS(PHI 0 TRP 1 )',\r\n 'SIN(PHI 0 TRP 1 )',\r\n 'COS(PHI 0 LEU 2 )',\r\n 'SIN(PHI 0 LEU 2 )',\r\n 'COS(PHI 0 ALA 3 )',\r\n 'SIN(PHI 0 ALA 3 )',\r\n 'COS(PHI 0 LEU 4 )',\r\n 'SIN(PHI 0 LEU 4 )']\r\n```\r\n\r\nwhich is wrong because PSI angles are missing. I don't think this is an issue in dev_release_1.3, so be careful when merging because I don't know if this was a problem not fixed before or a problem introduced by some redundancy checking in 1.2.2.\r\n\r\nPlease check and write unit tests in such a way that for all test cases the dimension of the featurizer and the number of features and the number of description labels are the same. "}}