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Posted to dev@climate.apache.org by "Paul Ramirez (JIRA)" <ji...@apache.org> on 2013/07/31 22:37:48 UTC

[jira] [Commented] (CLIMATE-236) Add Dataset Ensemble Support to the ocw.dataset_processor module

    [ https://issues.apache.org/jira/browse/CLIMATE-236?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13725689#comment-13725689 ] 

Paul Ramirez commented on CLIMATE-236:
--------------------------------------

Instead of "private" what about just have it take in the datasets and return a dataset. That way this utility function is available to others.
                
> Add Dataset Ensemble Support to the ocw.dataset_processor module
> ----------------------------------------------------------------
>
>                 Key: CLIMATE-236
>                 URL: https://issues.apache.org/jira/browse/CLIMATE-236
>             Project: Apache Open Climate Workbench
>          Issue Type: Sub-task
>          Components: rcmet
>    Affects Versions: 0.1-incubating
>         Environment: *nix
>            Reporter: Cameron Goodale
>            Assignee: Cameron Goodale
>             Fix For: 0.2-incubating
>
>   Original Estimate: 4h
>  Remaining Estimate: 4h
>
> Currently within the rcmes code base there is an ability to take in multiple datasets and return an 'ensemble' dataset.  This ensemble is just the mean of all the input datasets.
> The plan is to grab this code block (around line 250) from do_data_prep:
> {code}
>     # TODO:  Refactor this into a function within the toolkit module
>     # compute the simple multi-obs ensemble if multiple obs are used
>     if numOBSs > 1:
>         print 'numOBSs = ', numOBSs
>         oData = obsData
>         print 'oData shape = ', oData.shape
>         obsData = ma.zeros((numOBSs + 1, nT, ngrdY, ngrdX))
>         print 'obsData shape = ', obsData.shape
>         avg = ma.zeros((nT, ngrdY, ngrdX))
>         
>         for i in np.arange(numOBSs):
>             obsData[i, :, :, :] = oData[i, :, :, :]
>             avg[:, :, :] = avg[:, :, :] + oData[i, :, :, :]
>         avg = avg / float(numOBSs)
>         obsData[numOBSs, :, :, :] = avg[:, :, :]     # store the model-ensemble data
>         numOBSs = numOBSs + 1                     # update the number of obs data to include the model ensemble
>         obsList.append('ENS-OBS')
> {code}
> Port all of that into a private function in dataset_processor called _rcmes_make_dataset_ensemble() and setup the dataset_processor.ensemble() function use it initially.
> Once the code move, documentation, unit tests are all complete, then I will resolve this issue.

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