utilisation de k-means au lieu de hierarchique dans initSmallEM - PB de dimensions...
[valse.git] / R / indicesSelection.R
1 #' Construct the set of relevant indices -> ED: je crois que cette fonction n'est pas utile
2 #'
3 #' @param phi regression matrix, of size p*m
4 #' @param thresh threshold to say a cofficient is equal to zero
5 #'
6 #' @return a list with A, a matrix with relevant indices (size = p*m) and B, a
7 #' matrix with irrelevant indices (size = p*m)
8 #' @export
9 indicesSelection = function(phi, thresh = 1e-6)
10 {
11 dim_phi = dim(phi)
12 p = dim_phi[1]
13 m = dim_phi[2]
14
15 A = matrix(0, p, m)
16 B = matrix(0, p, m)
17
18 for(j in 1:p)
19 {
20 cpt1 = 0
21 cpt2 = 0
22 for(mm in 1:m)
23 {
24 if(max(phi[j,mm,]) > thresh)
25 {
26 cpt1 = cpt1 + 1
27 A[j,cpt] = mm
28 } else
29 {
30 cpt2 = cpt2+1
31 B[j, cpt2] = mm
32 }
33 }
34 }
35 return (list(A=A,B=B))
36 }