3D orientation tensor, which characterize data distribution using
eigenvalue method. See (Watson 1966, Scheidegger 1965).
Usage
ortensor(x, norm = TRUE, w = NULL)
Arguments
- x
numeric. Can be three element vector, three column array, or an
object of class "line"
or "plane"
- norm
logical. Whether the tensor should be normalized or not.
- w
numeric. weightings
Details
The normalized orientation tensor is given as $$D = \frac{1}{n} (x_i, y_i, z_i) (x_i, y_i, z_i)^T$$
n = 1
Examples
set.seed(1)
x <- rfb(100, mu = Line(120, 50), k = 1, A = diag(c(10, 0, 0)))
ortensor(x)
#> [,1] [,2] [,3]
#> [1,] 0.11636250 -0.14833420 -0.07233721
#> [2,] -0.14833420 0.48850035 0.05426838
#> [3,] -0.07233721 0.05426838 0.39513715