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Add notebook to validate spatial averaging #23
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Hi @lee1043, I noticed you already started work on this issue so I assigned you to it. Steve and I can review the PR whenever you're ready to open one. |
Hi @tomvothecoder, yes I started playing with it in this notebook, which eventually can be used for demo. I'd be happy to take lead on that. I will probably write a separate (but similar) notebook that is dedicated for the validation. I have some questions.
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Yes - you can create a new masked dataset and then call the spatial averager.
xcdat - weights data (by area) by default [Note - I now see the confusion; if you do not pass in a weighting matrix (i.e., default |
To avoid confusion, we can either rename the method param from I'm lean towards |
Issue opened to address this: xCDAT/xcdat#147 |
This issue is from almost 3 years ago and does not need to be addressed anymore. |
Validation Checklist
Compare below APIs against CDAT equivalent.
ds.xcdat.spatial_average()
ords.spatial.avg()
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