Discussed in #591
Originally posted by tomvothecoder January 29, 2024
Is your feature request related to a problem?
I'm running into a case where I need to average over the Z axis. The CDAT code being used is cdutil.averager(tvar, axis="z"), which I need to replace.
xCDAT's spatial averager, which is based on cdutil.averager(), only supports rectilinear grids ("X" and "Y"). However, we do mention that the get_weights() method can be extended to support other axes:
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Notes |
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----- |
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This method was developed for rectilinear grids only. ``get_weights()`` |
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recognizes and operate on latitude and longitude, but could be extended |
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to work with other standard geophysical dimensions (e.g., time, depth, |
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and pressure). |
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""" |
Are there are any possible answers you came across?
No response
Describe alternatives you've considered
No response
Additional context
For the short-term, I might be able to use xarray.DataArray.weighted directly. However, I still need to generate the weights xr.DataArray beforehand.
datarray.weighted(weights).mean("height") 
Discussed in #591
Originally posted by tomvothecoder January 29, 2024
Is your feature request related to a problem?
I'm running into a case where I need to average over the Z axis. The CDAT code being used is
cdutil.averager(tvar, axis="z"), which I need to replace.xCDAT's spatial averager, which is based on
cdutil.averager(), only supports rectilinear grids ("X" and "Y"). However, we do mention that theget_weights()method can be extended to support other axes:xcdat/xcdat/spatial.py
Lines 246 to 252 in fbf1db6
Are there are any possible answers you came across?
No response
Describe alternatives you've considered
No response
Additional context
For the short-term, I might be able to use xarray.DataArray.weighted directly. However, I still need to generate the weights xr.DataArray beforehand.