{"action":"created","issue":{"url":"https://api.github.com/repos/mne-tools/mne-python/issues/2112","labels_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2112/labels{/name}","comments_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2112/comments","events_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2112/events","html_url":"https://github.com/mne-tools/mne-python/issues/2112","id":77706028,"number":2112,"title":"ENH: Denoising options for preprocessing","user":{"login":"teonlamont","id":1578674,"avatar_url":"https://avatars.githubusercontent.com/u/1578674?v=3","gravatar_id":"","url":"https://api.github.com/users/teonlamont","html_url":"https://github.com/teonlamont","followers_url":"https://api.github.com/users/teonlamont/followers","following_url":"https://api.github.com/users/teonlamont/following{/other_user}","gists_url":"https://api.github.com/users/teonlamont/gists{/gist_id}","starred_url":"https://api.github.com/users/teonlamont/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/teonlamont/subscriptions","organizations_url":"https://api.github.com/users/teonlamont/orgs","repos_url":"https://api.github.com/users/teonlamont/repos","events_url":"https://api.github.com/users/teonlamont/events{/privacy}","received_events_url":"https://api.github.com/users/teonlamont/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":{"url":"https://api.github.com/repos/mne-tools/mne-python/milestones/8","html_url":"https://github.com/mne-tools/mne-python/milestones/0.12","labels_url":"https://api.github.com/repos/mne-tools/mne-python/milestones/8/labels","id":1429321,"number":8,"title":"0.12","description":"","creator":{"login":"Eric89GXL","id":2365790,"avatar_url":"https://avatars.githubusercontent.com/u/2365790?v=3","gravatar_id":"","url":"https://api.github.com/users/Eric89GXL","html_url":"https://github.com/Eric89GXL","followers_url":"https://api.github.com/users/Eric89GXL/followers","following_url":"https://api.github.com/users/Eric89GXL/following{/other_user}","gists_url":"https://api.github.com/users/Eric89GXL/gists{/gist_id}","starred_url":"https://api.github.com/users/Eric89GXL/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Eric89GXL/subscriptions","organizations_url":"https://api.github.com/users/Eric89GXL/orgs","repos_url":"https://api.github.com/users/Eric89GXL/repos","events_url":"https://api.github.com/users/Eric89GXL/events{/privacy}","received_events_url":"https://api.github.com/users/Eric89GXL/received_events","type":"User","site_admin":false},"open_issues":15,"closed_issues":1,"state":"open","created_at":"2015-11-25T13:36:18Z","updated_at":"2015-11-26T11:50:42Z","due_on":"2016-04-29T04:00:00Z","closed_at":null},"comments":10,"created_at":"2015-05-18T15:46:14Z","updated_at":"2015-12-01T04:31:57Z","closed_at":null,"body":"It would be nice if we had some denoising options available for preprocessing data. A few options that I was thinking of tsPCA (Cheveigné, 2007), and CALM (Adachi, 2001), which can be a special case of tsPCA.\r\n\r\nthere's a package on git (https://github.com/pealco/python-meg-denoise) that contains an implementation, as well as source code (http://www.isr.umd.edu/Labs/CSSL/simonlab/Denoising.html).\r\n\r\nuse case for those whose lab implement these tools in Matlab, or private software, those don't have license for maxfilter but would like cleaner data."},"comment":{"url":"https://api.github.com/repos/mne-tools/mne-python/issues/comments/160850445","html_url":"https://github.com/mne-tools/mne-python/issues/2112#issuecomment-160850445","issue_url":"https://api.github.com/repos/mne-tools/mne-python/issues/2112","id":160850445,"user":{"login":"Eric89GXL","id":2365790,"avatar_url":"https://avatars.githubusercontent.com/u/2365790?v=3","gravatar_id":"","url":"https://api.github.com/users/Eric89GXL","html_url":"https://github.com/Eric89GXL","followers_url":"https://api.github.com/users/Eric89GXL/followers","following_url":"https://api.github.com/users/Eric89GXL/following{/other_user}","gists_url":"https://api.github.com/users/Eric89GXL/gists{/gist_id}","starred_url":"https://api.github.com/users/Eric89GXL/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/Eric89GXL/subscriptions","organizations_url":"https://api.github.com/users/Eric89GXL/orgs","repos_url":"https://api.github.com/users/Eric89GXL/repos","events_url":"https://api.github.com/users/Eric89GXL/events{/privacy}","received_events_url":"https://api.github.com/users/Eric89GXL/received_events","type":"User","site_admin":false},"created_at":"2015-12-01T04:31:57Z","updated_at":"2015-12-01T04:31:57Z","body":"@kingjr yes, tSSS is now implemented in mne-python. @staulu I don't know much about these systems, but I do know that the FIF file contains information about different forms of compensation matrices that can be applied to the data. So I suspect we can detect whether or not compensation has been done. But it would be good to get input from people who really know (@kingjr if you are one of those people or can ping someone who is it would be very helpful here!)."}}