{"action":"created","issue":{"url":"https://api.github.com/repos/spacetx/starfish/issues/489","repository_url":"https://api.github.com/repos/spacetx/starfish","labels_url":"https://api.github.com/repos/spacetx/starfish/issues/489/labels{/name}","comments_url":"https://api.github.com/repos/spacetx/starfish/issues/489/comments","events_url":"https://api.github.com/repos/spacetx/starfish/issues/489/events","html_url":"https://github.com/spacetx/starfish/issues/489","id":354100498,"node_id":"MDU6SXNzdWUzNTQxMDA0OTg=","number":489,"title":"Add channel scaling to PerRoundMaxChannelDecoder","user":{"login":"ambrosejcarr","id":5239152,"node_id":"MDQ6VXNlcjUyMzkxNTI=","avatar_url":"https://avatars1.githubusercontent.com/u/5239152?v=4","gravatar_id":"","url":"https://api.github.com/users/ambrosejcarr","html_url":"https://github.com/ambrosejcarr","followers_url":"https://api.github.com/users/ambrosejcarr/followers","following_url":"https://api.github.com/users/ambrosejcarr/following{/other_user}","gists_url":"https://api.github.com/users/ambrosejcarr/gists{/gist_id}","starred_url":"https://api.github.com/users/ambrosejcarr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ambrosejcarr/subscriptions","organizations_url":"https://api.github.com/users/ambrosejcarr/orgs","repos_url":"https://api.github.com/users/ambrosejcarr/repos","events_url":"https://api.github.com/users/ambrosejcarr/events{/privacy}","received_events_url":"https://api.github.com/users/ambrosejcarr/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-08-26T14:46:05Z","updated_at":"2018-08-27T17:28:45Z","closed_at":null,"author_association":"MEMBER","body":"the `PerRoundMaxChannelDecoder` simply picks the highest-intensity channel in each round and uses that to decode an experiment. However, it doesn't enforce any scaling of the channels beforehand, which could lead to odd results where one channel has higher overall intensity. "},"comment":{"url":"https://api.github.com/repos/spacetx/starfish/issues/comments/416302900","html_url":"https://github.com/spacetx/starfish/issues/489#issuecomment-416302900","issue_url":"https://api.github.com/repos/spacetx/starfish/issues/489","id":416302900,"node_id":"MDEyOklzc3VlQ29tbWVudDQxNjMwMjkwMA==","user":{"login":"dganguli","id":2704460,"node_id":"MDQ6VXNlcjI3MDQ0NjA=","avatar_url":"https://avatars3.githubusercontent.com/u/2704460?v=4","gravatar_id":"","url":"https://api.github.com/users/dganguli","html_url":"https://github.com/dganguli","followers_url":"https://api.github.com/users/dganguli/followers","following_url":"https://api.github.com/users/dganguli/following{/other_user}","gists_url":"https://api.github.com/users/dganguli/gists{/gist_id}","starred_url":"https://api.github.com/users/dganguli/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/dganguli/subscriptions","organizations_url":"https://api.github.com/users/dganguli/orgs","repos_url":"https://api.github.com/users/dganguli/repos","events_url":"https://api.github.com/users/dganguli/events{/privacy}","received_events_url":"https://api.github.com/users/dganguli/received_events","type":"User","site_admin":false},"created_at":"2018-08-27T17:28:45Z","updated_at":"2018-08-27T17:28:45Z","author_association":"COLLABORATOR","body":"I view the filters as the place to implement intensity scaling operations, not the decoders. \r\n\r\nI like the decoders as being 'dumb' and the magic in signal processing as being done by the 'filters', or, eventually, by some learned model of which the final 'soft-max' or equivalent layers is one of the 'dumb' decoders.\r\n\r\nthe scale_by_percentile, clip, and zero_channel_by_magnitude filters, or some perhaps more flexible variants of these, can always be applied to the images (before decoding) to handle the issues you mentioned above.\r\n\r\nthoughts?"}}
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