{"action":"opened","number":1,"pull_request":{"url":"https://api.github.com/repos/acisops/psmc_check/pulls/1","id":67081497,"html_url":"https://github.com/acisops/psmc_check/pull/1","diff_url":"https://github.com/acisops/psmc_check/pull/1.diff","patch_url":"https://github.com/acisops/psmc_check/pull/1.patch","issue_url":"https://api.github.com/repos/acisops/psmc_check/issues/1","number":1,"state":"open","locked":false,"title":"Roll-aware PSMC model, fit to heater-on&off data; Version 0.3->0.4","user":{"login":"richardjedgar","id":9807359,"avatar_url":"https://avatars.githubusercontent.com/u/9807359?v=3","gravatar_id":"","url":"https://api.github.com/users/richardjedgar","html_url":"https://github.com/richardjedgar","followers_url":"https://api.github.com/users/richardjedgar/followers","following_url":"https://api.github.com/users/richardjedgar/following{/other_user}","gists_url":"https://api.github.com/users/richardjedgar/gists{/gist_id}","starred_url":"https://api.github.com/users/richardjedgar/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/richardjedgar/subscriptions","organizations_url":"https://api.github.com/users/richardjedgar/orgs","repos_url":"https://api.github.com/users/richardjedgar/repos","events_url":"https://api.github.com/users/richardjedgar/events{/privacy}","received_events_url":"https://api.github.com/users/richardjedgar/received_events","type":"User","site_admin":false},"body":"ACIS Ops please review these changes...\r\n\r\nI've added code to psmc_check.py to make it roll aware.\r\n\r\nTom and I have come up with a decent-fitting model, which is rather different in most details from the previous one. This is essentially his fit5_psmc_spec.json file, with minor changes of mine.\r\n\r\nI have bumped the VERSION number from 0.3 to 0.4.\r\n\r\nComparison between the old and new PSMC models can be done on recent weeks by looking at these web pages:\r\n\r\nold: http://cxc.cfa.harvard.edu/acis/PSMC_thermPredic/APR1816/oflsa/\r\nnew: http://cxc.cfa.harvard.edu/acis/tmp/psmc_APR1816/index.html\r\n\r\nold: http://cxc.cfa.harvard.edu/acis/PSMC_thermPredic/APR0416/oflsc/\r\nnew: http://cxc.cfa.harvard.edu/acis/tmp/psmc_APR0416/index.html\r\n\r\nThe Detector Housing Heater was turned on on 2015:223. To assess how much of an overprediction we should expect from the present model (0.4) if we turn the heater off again, I've plotted residuals in guifit (data minus model vs. data) for two time periods, using this model: [a] the 400 days prior to turning the heater on in 2015, and [b] the 245 days after turning the heater on. In the hot case, it appears that the model overpredicts the heater-off case by 1 to 2 degrees C, which we can live with until such time as there's enough heater-off data to recalibrate if need be.\r\n\r\nBefore the heater was turned off: \r\n![guifit_5b_2015_222_400days](https://cloud.githubusercontent.com/assets/9807359/14653896/384dc6c2-0649-11e6-8d64-e8518bfa692c.png)\r\n\r\nAfter the heater was turned 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