umeshu | unstructured mesh generation in 2-D using Delaunay | Service Mesh library
kandi X-RAY | umeshu Summary
kandi X-RAY | umeshu Summary
Umeshu is a small, light-weight C++ library for unstructured triangular mesh generation in two dimensions using Delaunay refinement approach. The library implements the algorithm described in the paper J. R. Shewchuk, Delaunay refinement algorithms for triangular mesh generation, Computational Geometry 22(1-3) (2002), 21-74. The mesh is stored in a half-edge data structure and the implementation relies on generic programming using templates and on containers and tools provided by STL and [Boost] Although other (faster, more sophisticated, complex, general) mesh libraries and mesh generators exist (e.g., [OpenMesh] [CGAL] [Triangle] Triangle])), the principal advantage of Umeshu is its relative simplicity, the implementation is quite straightforward. It can be used as a learning tool for half-edge data structure, for Delaunay refinement techniques and as a basis upon which new mesh generation algorithms can be tested.
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QUESTION
I am currently working on the following:
I have two dataframes. One dataframe contains a number of inventors per company and I would like to know how often their name appears in another dataframe in the same company.The company identifier (df_itemnumber_rounded) in both dataframes is called the same and present in both dataframes.
Example:
First dataframe includes:
...ANSWER
Answered 2022-Feb-10 at 21:41Here's a potential solution. Note that your assignee and citetp variables are messy with whitespaces at the beginning/end taht you might not want to take into account for your string search:
library(tidyverse)
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