# wrap.rotation: Prepare Data on Rotation Group In Riemann: Learning with Data on Riemannian Manifolds

## Description

Rotation group, also known as special orthogonal group, is a Riemannian manifold

SO(p) = \lbrace Q \in \mathbf{R}^{p\times p}~\vert~ Q^\top Q = I, \textrm{det}(Q)=1 \rbrace

where the name originates from an observation that when p=2,3 these matrices are rotation of shapes/configurations.

## Usage

 1 wrap.rotation(input) 

## Arguments

 input data matrices to be wrapped as riemdata class. Following inputs are considered, arraya (p\times p\times n) array where each slice along 3rd dimension is a rotation matrix. lista length-n list whose elements are (p\times p) rotation matrices.

## Value

a named riemdata S3 object containing

data

a list of (p\times p) rotation matrices.

size

size of each rotation matrix.

name

name of the manifold of interests, "rotation"

## Examples

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 #------------------------------------------------------------------- # Checker for Two Types of Inputs #------------------------------------------------------------------- ## DATA GENERATION d1 = array(0,c(3,3,5)) d2 = list() for (i in 1:5){ single = qr.Q(qr(matrix(rnorm(9),nrow=3))) d1[,,i] = single d2[[i]] = single } ## RUN test1 = wrap.rotation(d1) test2 = wrap.rotation(d2) 

Riemann documentation built on June 20, 2021, 5:07 p.m.