{"action":"created","issue":{"url":"https://api.github.com/repos/hplgit/chaospy/issues/6","labels_url":"https://api.github.com/repos/hplgit/chaospy/issues/6/labels{/name}","comments_url":"https://api.github.com/repos/hplgit/chaospy/issues/6/comments","events_url":"https://api.github.com/repos/hplgit/chaospy/issues/6/events","html_url":"https://github.com/hplgit/chaospy/issues/6","id":127476743,"number":6,"title":"PCE of a set of data points","user":{"login":"phauseux","id":16780640,"avatar_url":"https://avatars.githubusercontent.com/u/16780640?v=3","gravatar_id":"","url":"https://api.github.com/users/phauseux","html_url":"https://github.com/phauseux","followers_url":"https://api.github.com/users/phauseux/followers","following_url":"https://api.github.com/users/phauseux/following{/other_user}","gists_url":"https://api.github.com/users/phauseux/gists{/gist_id}","starred_url":"https://api.github.com/users/phauseux/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/phauseux/subscriptions","organizations_url":"https://api.github.com/users/phauseux/orgs","repos_url":"https://api.github.com/users/phauseux/repos","events_url":"https://api.github.com/users/phauseux/events{/privacy}","received_events_url":"https://api.github.com/users/phauseux/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"milestone":null,"comments":2,"created_at":"2016-01-19T15:54:53Z","updated_at":"2016-01-19T16:24:49Z","closed_at":"2016-01-19T16:24:49Z","body":"Hi, I am a postdoc researcher at Université du Luxembourg.\r\n\r\nI have a vector which contains a set of data points (Monte-Carlo realisations).\r\n\r\nI would like to use chaospy to compute the PCE of the data points by choosing the order and the type of polynomials (Hermite, Jacobi, etc.).\r\n\r\nSincerely,\r\nPaul."},"comment":{"url":"https://api.github.com/repos/hplgit/chaospy/issues/comments/172906185","html_url":"https://github.com/hplgit/chaospy/issues/6#issuecomment-172906185","issue_url":"https://api.github.com/repos/hplgit/chaospy/issues/6","id":172906185,"user":{"login":"jonathf","id":1167317,"avatar_url":"https://avatars.githubusercontent.com/u/1167317?v=3","gravatar_id":"","url":"https://api.github.com/users/jonathf","html_url":"https://github.com/jonathf","followers_url":"https://api.github.com/users/jonathf/followers","following_url":"https://api.github.com/users/jonathf/following{/other_user}","gists_url":"https://api.github.com/users/jonathf/gists{/gist_id}","starred_url":"https://api.github.com/users/jonathf/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jonathf/subscriptions","organizations_url":"https://api.github.com/users/jonathf/orgs","repos_url":"https://api.github.com/users/jonathf/repos","events_url":"https://api.github.com/users/jonathf/events{/privacy}","received_events_url":"https://api.github.com/users/jonathf/received_events","type":"User","site_admin":false},"created_at":"2016-01-19T16:24:49Z","updated_at":"2016-01-19T16:24:49Z","body":"If you choose higher order polynomials, proper use of normalizing constants become important.\r\nThis can be implemented as follows:\r\n\r\n    orth_poly, norms = cp.orth_ttr(polyOrder, dist, retall=True)\r\n    func_approx = cp.fit_regression(orth_poly, dataPoints, evaluations, norms=norms)"}}