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* More efficient PML BoxArray
If the union of the grids is a single rectangular domain, we can simplify
the process and generate more efficient PML BoxArray.
* Update Source/BoundaryConditions/PML.cpp
Co-authored-by: Edoardo Zoni <59625522+EZoni@users.noreply.github.com>
* Apply suggestions from code review
* reset Python_wrappers benchmark
* fix the computation of sigmas for the new BoxArray
* Revert "reset Python_wrappers benchmark"
This reverts commit 2999304571d525076ba6c1f7cbbcef6e9acafabb.
* fix warning
* fix 1d
* initialize to quiet NaN
* Reset Benchmark: pml_x_psatd
- maximum relative error: 2.50e-06
- new implementation: 10 PML grids
- old implementation: 24 PML grids
* Reset Benchmark: LaserAccelerationMR
- maximum relative error: 2.73e-04
- new implementation: (18,8,8) PML grids
- old implementation: (48,18,18) PML grids
* Reset Benchmark: LaserOnFine
- maximum relative error: 6.44e-05
- new implementation: (2,6,6) PML grids
- old implementation: (2,12,12) PML grids
* Reset Benchmark: PlasmaAccelerationMR
- maximum relative error: 6.84e-04
- new implementation: (10,6,6) PML grids
- old implementation: (24,12,12) PML grids
* Reset Benchmark: RefinedInjection
- maximum relative error: 2.55e-04
- new implementation: (18,8,8) PML grids
- old implementation: (48,18,18) PML grids
* Reset Benchmark: momentum-conserving-gather
- maximum relative error: 7.43e-04
- new implementation: (10,6,6) PML grids
- old implementation: (24,12,12) PML grids
* Reset Benchmark: subcyclingMR
- maximum relative error: 2.41e-05
- new implementation: (6,6,6) PML grids
- old implementation: (12,12,12) PML grids
* Reset Benchmark: Langmuir_multi_2d_MR
- maximum relative error: 1.32e-01 (B numerical artifact)
- new implementation: (0,20,20) PML grids
- old implementation: (0,52,40) PML grids
* Reset Benchmark: Langmuir_multi_2d_MR_psatd
- maximum relative error: 1.05e-01 (B numerical artifact)
- new implementation: (0,20,20) PML grids
- old implementation: (0,52,40) PML grids
* Reset Benchmark: Python_LaserAccelerationMR
- maximum relative error: 2.73e-04
- new implementation: (18,8,8) PML grids
- old implementation: (48,18,18) PML grids
* Reset Benchmark: Python_wrappers
- maximum relative error: 1.07e-08
- new implementation: 8 PML grids
- old implementation: 16 PML grids
* Reset Benchmark: pml_psatd_dive_divb_cleaning
- maximum relative error: 4.91e-03
- new implementation: 24 PML grids
- old implementation: 98 PML grids
* Remove an assertion. We will fix it later
* Reset Benchmark: Langmuir_multi_2d_MR_anisotropic
- maximum relative error: 1.07e-01 (B numerical artifact)
- new implementation: (0,16,16) PML grids
- old implementation: (0,40,34) PML grids
* Reset Benchmark: PEC_field_mr
- maximum relative error: 3.98e-02
- new implementation: (0,2,2) PML grids
- old implementation: (0,2,2) PML grids
(different number of ghost cells on coarse PML patch)
Co-authored-by: Edoardo Zoni <59625522+EZoni@users.noreply.github.com>
Co-authored-by: Edoardo Zoni <ezoni@lbl.gov>
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* Add CI Test for Python Wrappers w/ PML
* Remove Unused Import
* Clean up, Add Link in Docs
* Remove get_data(), Avoid global
* Move Extent and Slicing to plot_data
* Fix Bug
* Set Input Before Importing pywarpx.fields
* Call initialize_inputs() and initialize_warpx(), not step(1)
* Cleaning
* Remove Slicing, Add F,G, Add Annotations
* Better Smoothing of Initial Fields
* Add Values Check, Cleaning
* Improve Comment
* Fix lgtm-com Alerts
* Improve Comment
* Cleaning
* Cleaning
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