Weighted Average

[philipc2]

Closes #826

Overview

• Implements weighted average functionality for a UxDataArray

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[philipc2]

@rytam2

I've set up the boilerplate for the weighted mean functionality. This should be a good place to get started. We can run over this during today's meeting.

[philipc2]

@rytam2

We have fixed the issue with the quad-hexagon grid. I've added it back to the test case.

[github-actions]

ASV Benchmarking

Benchmark Comparison Results

Benchmarks that have improved:

Change	Before [b11d011]	After [a0be1c1]	Ratio	Benchmark (Parameter)
-	445M	375M	0.84	face_bounds.FaceBounds.peakmem_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/ugrid/quad-hexagon/grid.nc'))
-	467M	373M	0.80	mpas_ocean.Integrate.peakmem_integrate('480km')
	failed	412±7μs	n/a	mpas_ocean.WeightedMean.time_weighted_mean_face_centered('120km')
	failed	341±6μs	n/a	mpas_ocean.WeightedMean.time_weighted_mean_face_centered('480km')

Benchmarks that have stayed the same:

Change	Before [b11d011]	After [a0be1c1]	Ratio	Benchmark (Parameter)
	375M	376M	1.00	face_bounds.FaceBounds.peakmem_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/mpas/QU/oQU480.231010.nc'))
	375M	375M	1.00	face_bounds.FaceBounds.peakmem_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/scrip/outCSne8/outCSne8.nc'))
	400M	379M	0.95	face_bounds.FaceBounds.peakmem_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/ugrid/geoflow-small/grid.nc'))
	1.59±0.02s	1.58±0.01s	1.00	face_bounds.FaceBounds.time_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/mpas/QU/oQU480.231010.nc'))
	224±0.9ms	223±4ms	0.99	face_bounds.FaceBounds.time_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/scrip/outCSne8/outCSne8.nc'))
	2.04±0.02s	2.01±0.02s	0.99	face_bounds.FaceBounds.time_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/ugrid/geoflow-small/grid.nc'))
	7.90±0.3ms	8.07±0.2ms	1.02	face_bounds.FaceBounds.time_face_bounds(PosixPath('/home/runner/work/uxarray/uxarray/test/meshfiles/ugrid/quad-hexagon/grid.nc'))
	3.02±0.03s	3.08±0.03s	1.02	import.Imports.timeraw_import_uxarray
	674±20ms	669±7ms	0.99	mpas_ocean.ConnectivityConstruction.time_face_face_connectivity('120km')
	41.9±0.6ms	42.1±0.5ms	1.01	mpas_ocean.ConnectivityConstruction.time_face_face_connectivity('480km')
	1.83±0.03ms	1.82±0.03ms	0.99	mpas_ocean.ConnectivityConstruction.time_n_nodes_per_face('120km')
	538±10μs	557±20μs	1.03	mpas_ocean.ConnectivityConstruction.time_n_nodes_per_face('480km')
	1.12±0μs	1.06±0μs	0.95	mpas_ocean.ConstructTreeStructures.time_ball_tree('120km')
	280±1ns	270±2ns	0.96	mpas_ocean.ConstructTreeStructures.time_ball_tree('480km')
	770±4ns	759±6ns	0.99	mpas_ocean.ConstructTreeStructures.time_kd_tree('120km')
	270±1ns	257±2ns	0.95	mpas_ocean.ConstructTreeStructures.time_kd_tree('480km')
	432M	432M	1.00	mpas_ocean.GeoDataFrame.peakmem_to_geodataframe('120km', False)
	407M	407M	1.00	mpas_ocean.GeoDataFrame.peakmem_to_geodataframe('120km', True)
	379M	379M	1.00	mpas_ocean.GeoDataFrame.peakmem_to_geodataframe('480km', False)
	393M	377M	0.96	mpas_ocean.GeoDataFrame.peakmem_to_geodataframe('480km', True)
	1.02±0.01s	1.03±0.01s	1.01	mpas_ocean.GeoDataFrame.time_to_geodataframe('120km', False)
	53.2±0.4ms	52.7±0.4ms	0.99	mpas_ocean.GeoDataFrame.time_to_geodataframe('120km', True)
	78.0±0.3ms	79.3±1ms	1.02	mpas_ocean.GeoDataFrame.time_to_geodataframe('480km', False)
	5.50±0.2ms	5.51±0.08ms	1.00	mpas_ocean.GeoDataFrame.time_to_geodataframe('480km', True)
	319M	321M	1.01	mpas_ocean.Gradient.peakmem_gradient('120km')
	296M	296M	1.00	mpas_ocean.Gradient.peakmem_gradient('480km')
	2.79±0.02ms	2.79±0.06ms	1.00	mpas_ocean.Gradient.time_gradient('120km')
	308±5μs	320±6μs	1.04	mpas_ocean.Gradient.time_gradient('480km')
	389M	389M	1.00	mpas_ocean.Integrate.peakmem_integrate('120km')
	182±5ms	177±1ms	0.97	mpas_ocean.Integrate.time_integrate('120km')
	12.0±0.04ms	12.1±0.05ms	1.00	mpas_ocean.Integrate.time_integrate('480km')
	342±7ms	347±4ms	1.01	mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection('120km', 'exclude')
	348±4ms	348±2ms	1.00	mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection('120km', 'include')
	343±3ms	344±4ms	1.00	mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection('120km', 'split')
	22.8±0.6ms	22.7±0.1ms	0.99	mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection('480km', 'exclude')
	22.8±0.4ms	23.0±0.2ms	1.01	mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection('480km', 'include')
	22.6±0.3ms	23.0±0.2ms	1.01	mpas_ocean.MatplotlibConversion.time_dataarray_to_polycollection('480km', 'split')
	56.0±0.1ms	56.5±0.5ms	1.01	mpas_ocean.RemapDownsample.time_inverse_distance_weighted_remapping
	45.7±0.2ms	45.9±0.2ms	1.01	mpas_ocean.RemapDownsample.time_nearest_neighbor_remapping
	360±0.8ms	361±1ms	1.00	mpas_ocean.RemapUpsample.time_inverse_distance_weighted_remapping
	266±2ms	264±0.2ms	0.99	mpas_ocean.RemapUpsample.time_nearest_neighbor_remapping
	294M	294M	1.00	quad_hexagon.QuadHexagon.peakmem_open_dataset
	291M	291M	1.00	quad_hexagon.QuadHexagon.peakmem_open_grid
	5.58±0.2ms	6.24±0.5ms	~1.12	quad_hexagon.QuadHexagon.time_open_grid

Benchmarks that have got worse:

Change	Before [b11d011]	After [a0be1c1]	Ratio	Benchmark (Parameter)
+	6.78±0.4ms	7.93±1ms	1.17	quad_hexagon.QuadHexagon.time_open_dataset

[rytam2]

UXDataset support

[aaronzedwick]

Looks good! Just a few suggestions.

[aaronzedwick]

Can you compute this within Python? I think if you can avoid hard coding in the answer that is ideal, although I know this can't always be avoided.

[erogluorhan]

+1 this! Even if it is inevitable to use constants, they shouldn't be showing up as magic numbers within the code and instead should go into some kind of test constants