Optimized Non-Conservative Zonal Average

[hongyuchen1030]

Closes #1181 #880

Overview

• Introduce specialized helper functions for the optimized non-conservative zonal average routine in zonal.py
• Implement caching and reuse of intermediary computational steps to reduce redundant recalculations
• Retain the general-purpose helper functions (which use data copying) for broader usability
• Improve overall performance of the zonal averaging computation

Expected Usage

import uxarray as ux

grid_path = "/path/to/grid.nc"
data_path = "/path/to/data.nc"

uxds = ux.open_dataset(grid_path, data_path)

# this is how you use this function
some_output = uxds.some_function()

# this is another way to use this function
other_output = uxds.some_function(some_param = True)

PR Checklist

General

• An issue is linked created and linked
• Add appropriate labels
• Filled out Overview and Expected Usage (if applicable) sections

Testing

• Adequate tests are created if there is new functionality
• Tests cover all possible logical paths in your function
• Tests are not too basic (such as simply calling a function and nothing else)

Documentation

• Docstrings have been added to all new functions
• Docstrings have updated with any function changes
• Internal functions have a preceding underscore (_) and have been added to docs/internal_api/index.rst
• User functions have been added to docs/user_api/index.rst

Examples

• Any new notebook examples added to docs/examples/ folder
• Clear the output of all cells before committing
• New notebook files added to docs/examples.rst toctree
• New notebook files added to new entry in docs/gallery.yml with appropriate thumbnail photo in docs/_static/thumbnails/

[hongyuchen1030]

@ philipc2 Can we avoid duplicate normalization here? For example if the nodes are already normalized, we will not normalize them.

For example, set an attributes in the grid node_x,node_y,node_z to indicate if they're already normalized or not.

[rajeeja]

ASV Benchmark failing?

[philipc2]

pre-commit.ci autofix

[hongyuchen1030]

@philipc2

The benchmark still doesn't work out for this PR, can you take a look? Thanks