Crate kabsch_umeyama

kabsch_umeyama

The Kabsch-Umeyama algorithm is a method for aligning and comparing the similarity between two sets of points. It finds the optimal translation, rotation and scaling by minimizing the root-mean-square deviation (RMSD) of the point pairs.

Structs

Array2

Functions

estimate

Estimate a similarity transformation between two matrices (2 Dimensions) with or without scaling. The None values are returned only if the problem is not well-conditioned.

Type Aliases

NestedArray