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https://issues.apache.org/jira/browse/CLIMATE-88?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13679716#comment-13679716
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Alex Goodman commented on CLIMATE-88:
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Actually, I am not allocating a completely new array in my function. I am using
what's called a view which just constructs a new ndarray object that shares the
same data in memory with another one, but can have different attributes (eg
shape).
http://wiki.scipy.org/Tentative_NumPy_Tutorial#head-4306be2ef34ad134f9fa0b87d426fa711119c167
This is done in the line:
data = dataset1[:]
The main reason I wanted this all in one helper function is because if I didn't
I would have to manually calculate the new shape for every routine in
metrics.py, so I would be saving several lines of code.
I think I should perhaps add a comment or two in the function that explains
this so people who are unfamiliar with this don't get confused by it in the
future.
> Performance improvements for metrics.py
> ---------------------------------------
>
> Key: CLIMATE-88
> URL: https://issues.apache.org/jira/browse/CLIMATE-88
> Project: Apache Open Climate Workbench
> Issue Type: Improvement
> Components: metrics
> Affects Versions: 0.1-incubating
> Reporter: Alex Goodman
> Assignee: Chris A. Mattmann
> Fix For: 0.1-incubating
>
> Attachments: benchmark_metrics.py,
> benchmark_metrics_with_resize_method.py
>
>
> The performance for many of the functions in metrics.py can be improved by
> removing some unnecessary loops and utilizing shape manipulation.
> I have attached some example code that benchmarks the differences between the
> original and proposed methodology if you did not see it in the mailing list.
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