{"action":"created","issue":{"url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/issues/1","repository_url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples","labels_url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/issues/1/labels{/name}","comments_url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/issues/1/comments","events_url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/issues/1/events","html_url":"https://github.com/pangeo-data/pangeo-astro-examples/pull/1","id":378989916,"node_id":"MDExOlB1bGxSZXF1ZXN0MjI5NTY0MTY2","number":1,"title":"Mostly polished version of AIA timelags notebook","user":{"login":"wtbarnes","id":8676141,"node_id":"MDQ6VXNlcjg2NzYxNDE=","avatar_url":"https://avatars1.githubusercontent.com/u/8676141?v=4","gravatar_id":"","url":"https://api.github.com/users/wtbarnes","html_url":"https://github.com/wtbarnes","followers_url":"https://api.github.com/users/wtbarnes/followers","following_url":"https://api.github.com/users/wtbarnes/following{/other_user}","gists_url":"https://api.github.com/users/wtbarnes/gists{/gist_id}","starred_url":"https://api.github.com/users/wtbarnes/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/wtbarnes/subscriptions","organizations_url":"https://api.github.com/users/wtbarnes/orgs","repos_url":"https://api.github.com/users/wtbarnes/repos","events_url":"https://api.github.com/users/wtbarnes/events{/privacy}","received_events_url":"https://api.github.com/users/wtbarnes/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":4,"created_at":"2018-11-09T01:45:48Z","updated_at":"2018-11-09T16:00:35Z","closed_at":null,"author_association":"CONTRIBUTOR","pull_request":{"url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/pulls/1","html_url":"https://github.com/pangeo-data/pangeo-astro-examples/pull/1","diff_url":"https://github.com/pangeo-data/pangeo-astro-examples/pull/1.diff","patch_url":"https://github.com/pangeo-data/pangeo-astro-examples/pull/1.patch"},"body":"Regarding pangeo-data/astro.pangeo.io-deploy#15 \r\n\r\n@Cadair can you take a look at this and let me know if you have any suggestions? \r\n\r\n@rabernat @martindurant I'd also be interested to see how any of the data viz could be improved with holoviews or the data import simplified with intake."},"comment":{"url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/issues/comments/437405109","html_url":"https://github.com/pangeo-data/pangeo-astro-examples/pull/1#issuecomment-437405109","issue_url":"https://api.github.com/repos/pangeo-data/pangeo-astro-examples/issues/1","id":437405109,"node_id":"MDEyOklzc3VlQ29tbWVudDQzNzQwNTEwOQ==","user":{"login":"rabernat","id":1197350,"node_id":"MDQ6VXNlcjExOTczNTA=","avatar_url":"https://avatars1.githubusercontent.com/u/1197350?v=4","gravatar_id":"","url":"https://api.github.com/users/rabernat","html_url":"https://github.com/rabernat","followers_url":"https://api.github.com/users/rabernat/followers","following_url":"https://api.github.com/users/rabernat/following{/other_user}","gists_url":"https://api.github.com/users/rabernat/gists{/gist_id}","starred_url":"https://api.github.com/users/rabernat/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/rabernat/subscriptions","organizations_url":"https://api.github.com/users/rabernat/orgs","repos_url":"https://api.github.com/users/rabernat/repos","events_url":"https://api.github.com/users/rabernat/events{/privacy}","received_events_url":"https://api.github.com/users/rabernat/received_events","type":"User","site_admin":false},"created_at":"2018-11-09T16:00:35Z","updated_at":"2018-11-09T16:00:35Z","author_association":"MEMBER","body":"Wow, this is awesome! Thanks @wtbarnes! I will definitely have something cool to demo at the [heliophysics workshop](https://www.earthcube.org/event/earthcube-rcn-towards-integration-heliophysics-data-modeling-analysis-tools). I especially appreciate the details comments and explanations.\r\n\r\nA couple points in terms of the notebook readability / useability. Note that this are just intended as nerdy tech-talk, not a criticism of your excellent contribution.\r\n\r\n- There are some conda / pip install commands up front. Instead of doing this at the user level, let's make sure the astro.pangeo.io or binder environment is configured correctly from the beginning.\r\n- Would it make sense to offload cell 8 (\"a data structure for stacking multiple FITS files to create an AIA data cube\") into a more general-purpose library? It seems like everyone who wants to work with this data would essentially have to copy / paste this cell into each notebook. This is a stark contrast from the situation we have with our climate datasets, where we can just say `ds = intake.cat.ECCOv4r3.to_dask()` and obtain a full xarray dataset with many different variables / coordinates. (see [this example notebook](http://binder.pangeo.io/v2/gh/rabernat/pangeo_ecco_examples/master))\r\n- Why do you cal `.rechunk` in your average routine? It seems like this would slow things down. 100x100 chunks are very small. Why not just use the full image? It still has to be read as a full image, so as far as I understand, you are not saving any I/O here (which usually is the main bottleneck)"}}
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