{"action":"closed","issue":{"url":"https://api.github.com/repos/CubeBrowser/cube-explorer/issues/3","repository_url":"https://api.github.com/repos/CubeBrowser/cube-explorer","labels_url":"https://api.github.com/repos/CubeBrowser/cube-explorer/issues/3/labels{/name}","comments_url":"https://api.github.com/repos/CubeBrowser/cube-explorer/issues/3/comments","events_url":"https://api.github.com/repos/CubeBrowser/cube-explorer/issues/3/events","html_url":"https://github.com/CubeBrowser/cube-explorer/issues/3","id":130324131,"number":3,"title":"Seasonal ensemble","user":{"login":"marqh","id":1557321,"avatar_url":"https://avatars.githubusercontent.com/u/1557321?v=3","gravatar_id":"","url":"https://api.github.com/users/marqh","html_url":"https://github.com/marqh","followers_url":"https://api.github.com/users/marqh/followers","following_url":"https://api.github.com/users/marqh/following{/other_user}","gists_url":"https://api.github.com/users/marqh/gists{/gist_id}","starred_url":"https://api.github.com/users/marqh/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/marqh/subscriptions","organizations_url":"https://api.github.com/users/marqh/orgs","repos_url":"https://api.github.com/users/marqh/repos","events_url":"https://api.github.com/users/marqh/events{/privacy}","received_events_url":"https://api.github.com/users/marqh/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":{"login":"philippjfr","id":1550771,"avatar_url":"https://avatars.githubusercontent.com/u/1550771?v=3","gravatar_id":"","url":"https://api.github.com/users/philippjfr","html_url":"https://github.com/philippjfr","followers_url":"https://api.github.com/users/philippjfr/followers","following_url":"https://api.github.com/users/philippjfr/following{/other_user}","gists_url":"https://api.github.com/users/philippjfr/gists{/gist_id}","starred_url":"https://api.github.com/users/philippjfr/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/philippjfr/subscriptions","organizations_url":"https://api.github.com/users/philippjfr/orgs","repos_url":"https://api.github.com/users/philippjfr/repos","events_url":"https://api.github.com/users/philippjfr/events{/privacy}","received_events_url":"https://api.github.com/users/philippjfr/received_events","type":"User","site_admin":false},"milestone":null,"comments":5,"created_at":"2016-02-01T10:37:58Z","updated_at":"2016-03-31T14:10:04Z","closed_at":"2016-03-31T14:10:04Z","body":"This Iris gallery includes this example\r\nhttp://scitools.org.uk/iris/docs/latest/examples/Meteorology/lagged_ensemble.html\r\nusing data from\r\nhttps://github.com/SciTools/iris-sample-data\r\nhttps://github.com/SciTools/iris-sample-data/tree/master/sample_data/GloSea4\r\n\r\nIf we simplify the load process from this example, using the same data:\r\n```\r\nimport numpy as np\r\nimport iris\r\nimport iris.coords\r\nimport iris.plot as iplt\r\n\r\ndef realization_metadata(cube, field, fname):\r\n    if not cube.coords('realization'):\r\n        realization_number = fname[-6:-3]\r\n        realization_coord = iris.coords.AuxCoord(np.int32(realization_number), 'realization')\r\n        cube.add_aux_coord(realization_coord)\r\n\r\n\r\nsurface_temp = iris.load_cube(iris.sample_data_path('GloSea4', 'ensemble_???.pp'),\r\n              iris.Constraint('surface_temperature', realization=lambda value: True),\r\n              callback=realization_metadata)\r\nprint surface_temp\r\n```\r\nwe get a 4 dimensional cube of surface temperature data:\r\n\r\n```\r\nsurface_temperature / (K)           (realization: 13; time: 6; latitude: 145; longitude: 192)\r\n     Dimension coordinates:\r\n          realization                           x         -            -               -\r\n          time                                  -         x            -               -\r\n          latitude                              -         -            x               -\r\n          longitude                             -         -            -               x\r\n     Auxiliary coordinates:\r\n          forecast_period                       x         x            -               -\r\n          forecast_reference_time               x         x            -               -\r\n     Attributes:\r\n          STASH: m01s00i024\r\n          source: Data from Met Office Unified Model\r\n          um_version: 7.6\r\n     Cell methods:\r\n          mean: time (1 hour)\r\n\r\n```\r\n\r\nA scientific programmer needs to apply this load process, within a notebook session, then explore the realization dimension and the time dimension, looking at 2D filled contour plots over latitude and longitude."}}