FPCA2D (version 1.0)

FPCA_2D_score_fast: Two Dimensional Functional Principal Component Analysis

Description

Calcualte the two dimensional functional principal component scores by using Fourier Basis

Usage

FPCA_2D_score_fast(X)

Arguments

X

X is the input three dimensional array. The first two dimensions are the dimension of each input image. All the inputs images are organized as the third dimension of the input data array. All the image should be scaled to the rage from 0 to 1 before running this function.

Value

Details

Calcualte the two dimensional functional principal component scores by using Fourier Basis

References

Lin N, Jiang J, Guo S, Xiong M (2015) Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis. PLoS ONE 10(7): e0132945. doi:10.1371/journal.pone.0132945

Examples

   A = array(sample(seq(0,1,0.001),300),dim=c(10,10,3))
   rlt = FPCA_2D_score_fast(A)