{"action":"created","issue":{"url":"https://api.github.com/repos/pycroscopy/pyUSID/issues/5","repository_url":"https://api.github.com/repos/pycroscopy/pyUSID","labels_url":"https://api.github.com/repos/pycroscopy/pyUSID/issues/5/labels{/name}","comments_url":"https://api.github.com/repos/pycroscopy/pyUSID/issues/5/comments","events_url":"https://api.github.com/repos/pycroscopy/pyUSID/issues/5/events","html_url":"https://github.com/pycroscopy/pyUSID/issues/5","id":369940262,"node_id":"MDU6SXNzdWUzNjk5NDAyNjI=","number":5,"title":"Two process classes feature request","user":{"login":"DancingQuanta","id":8419157,"node_id":"MDQ6VXNlcjg0MTkxNTc=","avatar_url":"https://avatars3.githubusercontent.com/u/8419157?v=4","gravatar_id":"","url":"https://api.github.com/users/DancingQuanta","html_url":"https://github.com/DancingQuanta","followers_url":"https://api.github.com/users/DancingQuanta/followers","following_url":"https://api.github.com/users/DancingQuanta/following{/other_user}","gists_url":"https://api.github.com/users/DancingQuanta/gists{/gist_id}","starred_url":"https://api.github.com/users/DancingQuanta/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/DancingQuanta/subscriptions","organizations_url":"https://api.github.com/users/DancingQuanta/orgs","repos_url":"https://api.github.com/users/DancingQuanta/repos","events_url":"https://api.github.com/users/DancingQuanta/events{/privacy}","received_events_url":"https://api.github.com/users/DancingQuanta/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":1,"created_at":"2018-10-14T20:27:39Z","updated_at":"2018-10-18T19:59:57Z","closed_at":null,"author_association":"NONE","body":"This library is amazing. I work with Raman images (3D dataset; 2 positions and one spectroscopic)\r\n\r\nI really liked the idea of `Process` class that writes results to the h5 file.\r\nWhat I really like is to be able to is with `Process` class is to:\r\n* perform slicing and save to the h5 file. Helps with recording sites of interest.\r\n* Data reduction such as sum or any function along a dimension to close that dimension. This is similar to `numpy.ufunc.reduce`,  `pandas.DataFrame.apply` or `xarray.DataArray.reduce`. My use case for this operation is with Raman images  where I wanted to sum all of the spectra together and collapse the position axes away. This way, I am able to see what is going on spectroscopically in a sample. I was able to write a Process class for this specific summing use case. However I wanted to ask if there were any thougths in pyUSID's team about data reduction or general function `apply`."},"comment":{"url":"https://api.github.com/repos/pycroscopy/pyUSID/issues/comments/431142260","html_url":"https://github.com/pycroscopy/pyUSID/issues/5#issuecomment-431142260","issue_url":"https://api.github.com/repos/pycroscopy/pyUSID/issues/5","id":431142260,"node_id":"MDEyOklzc3VlQ29tbWVudDQzMTE0MjI2MA==","user":{"login":"DancingQuanta","id":8419157,"node_id":"MDQ6VXNlcjg0MTkxNTc=","avatar_url":"https://avatars3.githubusercontent.com/u/8419157?v=4","gravatar_id":"","url":"https://api.github.com/users/DancingQuanta","html_url":"https://github.com/DancingQuanta","followers_url":"https://api.github.com/users/DancingQuanta/followers","following_url":"https://api.github.com/users/DancingQuanta/following{/other_user}","gists_url":"https://api.github.com/users/DancingQuanta/gists{/gist_id}","starred_url":"https://api.github.com/users/DancingQuanta/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/DancingQuanta/subscriptions","organizations_url":"https://api.github.com/users/DancingQuanta/orgs","repos_url":"https://api.github.com/users/DancingQuanta/repos","events_url":"https://api.github.com/users/DancingQuanta/events{/privacy}","received_events_url":"https://api.github.com/users/DancingQuanta/received_events","type":"User","site_admin":false},"created_at":"2018-10-18T19:59:57Z","updated_at":"2018-10-18T19:59:57Z","author_association":"NONE","body":"Glad you ilked the `.reduce` idea.\r\n\r\nMy slicing idea is about saving the results of a `USIDataset.slice` to its own dataset. I haven't thought this through probably yet. Also I do not like the inflexibility of the current `USIDataset.slice` function where the result of the function returns a reshaped numpy array. I was expecting a `USIDataset` instead. Maybe a keyword switch can be added to control the outptu of the `USIDataset.slice`?"}}
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