[jira] [Commented] (CLIMATE-508) Adding statistical downscaling capability

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/CLIMATE-508?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14358080#comment-14358080 ] 

ASF GitHub Bot commented on CLIMATE-508:
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Github user cgoodale commented on the pull request:

    https://github.com/apache/climate/pull/112#issuecomment-78422029
  
    Hey @huikyole I was looking into the open issues and I saw this one and I have to agree with @MJJoyce  that example code would be great.  Even a simple example of how the API you defined in the class would be called.
    
    From what I see in the code I "think" it would be something like the following:
    
    # the basic way a user would import the Class
    >>> from ocw.statistical_downscaling import Downscaling
    # simple class instantiation
    >>> my_downscaler = Downscaling(ref, present, future)
    # Then we use the defined downscaler to return values
    >>> downscaled_present, modeled_future = my_downscaler.Delta_addition()
    >>> 
    
    Am I even close here?  Perhaps a unittest would also help convey how the code would be used.
    
    I am not sure I know enough about Downscaling, but all the return documentation is the same:
    :returns: downscaled model_present and model_future
    



> Adding statistical downscaling capability
> -----------------------------------------
>
>                 Key: CLIMATE-508
>                 URL: https://issues.apache.org/jira/browse/CLIMATE-508
>             Project: Apache Open Climate Workbench
>          Issue Type: Improvement
>          Components: metrics
>    Affects Versions: 0.5
>            Reporter: Huikyo Lee
>            Assignee: Huikyo Lee
>             Fix For: 1.0.0
>
>
> Three metrics will be added for statistically downscaling model outputs with observational data.
> 1. Delta method
> 2. Quantile mapping
> 3. Quantile regression



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