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ASF GitHub Bot commented on CLIMATE-508: ---------------------------------------- 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 -- This message was sent by Atlassian JIRA (v6.3.4#6332)