PolarOnionPeeling

版本 1.7.0.1 (17.4 MB) 作者: Adi Natan
Apply polar onion peeling method for analyzing velocity map imaging (VMI) data.
5.0
(3)
1.0K 次下载
更新时间 2021/10/25
在 GitHub 上查看许可证

The code implements the method shown at "Toward real-time charged-particle image reconstruction using polar onion-peeling" by G.M. Roberts et-al, Rev. Sci. Instr. 80, 053104 (2009). It supports images of up to 4K and accepts arbitrary (even) beta parameters. Specific quadrants of the image can be selected in the analysis in case of image asymmetries. NaN values can be used for masking unwanted pixels or areas.
For more info regarding the method see: https://doi.org/10.1063/1.3126527

引用格式

Adi Natan (2024). PolarOnionPeeling (https://github.com/adinatan/PolarOnionPeeling), GitHub. 检索来源 .

MATLAB 版本兼容性
创建方式 R2013b
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致谢

启发作品: cart2tripolar

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版本 已发布 发行说明
1.7.0.1

Added documentation regarding the tripol function
1.7.0.0

supports negative values (difference images)
1.6.0.0

......
Support in NaN values for masking the raw images was added, the code is restructured for better readability and a sample script to demonstrate how it works was added.
corrected link in the file description and included PESR - the radial projection of the raw data in the output
1.5.0.0

The code supports images of up to 4K. bld_lut.m was added for radial basis set generation of arbitrary size. Code improvements include applying better matrix inversion method, avoiding divergences at the origin artifacts and other minor improvements.
1.4.0.0

Faster code, some minor debugging for the case of all zeros data, improved support in higher Legendre polynomials up to the floating point accuracy limit.
1.3.0.0

added Matlab version control to use the proper interpolator name.
1.2.0.0

Added support in specific image quadrants analysis in case of image asymmetries. Improved documentation and warnings\errors handling.
1.1.0.0

The code now supports higher order Legendre polynomials, this was done with the help of Adam Chatterley.
1.0.0.0

要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。
要查看或报告此来自 GitHub 的附加功能中的问题，请访问其 GitHub 仓库。