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https://issues.apache.org/jira/browse/CLIMATE-643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14647952#comment-14647952
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ASF GitHub Bot commented on CLIMATE-643:
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Github user MJJoyce commented on the pull request:
https://github.com/apache/climate/pull/210#issuecomment-126403057
If the changes build off one another just separate them out into different
feature branches and merge/rebase according during the dev work. Otherwise we
end up with overly complicated pull requests that address multiple tickets and
that just makes reviews and integration more challenging. Small, atomic changes
are always easier. If you need help with the branching/merging let me know. I'm
more than happy to show you a few easy ways to take care of this!
> Updating some of examples
> -------------------------
>
> Key: CLIMATE-643
> URL: https://issues.apache.org/jira/browse/CLIMATE-643
> Project: Apache Open Climate Workbench
> Issue Type: Improvement
> Components: general
> Affects Versions: 1.0.0
> Reporter: Huikyo Lee
> Assignee: Huikyo Lee
> Fix For: 1.0.0
>
>
> Paul L. suggested some ideas to update examples. For example,
> "knmi_to_cru_full_bias.py" needs to be updated with better description. The
> model to model bias could be replaced by model to observation data bias. The
> goal is providing 5 examples all based on an actual published papers.
> Currently, OCW examples generate wrong results when there is missing data in
> observational datasets. It is important to mask those grid points with
> missing values in model datasets so that no metrics calculation is done at
> those grid points. In other words, if any of observation/model dataset has
> missing value at a grid point, we need to propagate the missing information
> to the other datasets.
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