reports/simulData_17mars.R

   1 simulData_17mars = function(ite){
   2   set.seed = 22021989+ite
   3
   4   ###########
   5   ## Modele
   6   ###########
   7   K = 2
   8   p = 20
   9   T = seq(0,1.5,length.out = p)
  10   T2 = seq(0,3, length.out = 2*p)
  11   n = 30
  12   x1 = cos(2*base::pi*T) + 0.2*cos(4*2*base::pi*T) + 0.3*c(rep(0,round(length(T)/7)),rep(1,round(length(T)*(1-1/7))))+1
  13   sigmaX = 0.12
  14   sigmaY = 0.12
  15   beta = list()
  16   p1= 0.5
  17   beta[[1]] =diag(c(rep(p1,5),rep(1,5), rep(p1,5), rep(1, p-15)))
  18   p2 = 1
  19   beta[[2]] = diag(c(rep(p2,5),rep(1,5), rep(p2,5), rep(1, p-15)))
  20   ARI1 = ARI2 = ARI3 = 0
  21
  22   ###########
  23   ## Data + Projection
  24   ###########
  25   require(wavelets)
  26   XY = array(0, dim = c(2*p,n))
  27   Xproj = array(0, dim=c(48,n))
  28   Yproj = array(0, dim=c(48,n))
  29   XYproj = array(0, dim=c(96,n))
  30   x = x1 + matrix(rnorm(n*p, 0, sigmaX), ncol = n)
  31   affec = sample(c(1,2), n, replace = TRUE)
  32   y  = x
  33   xy = matrix(0,ncol=n, nrow= 2*p)
  34   for (i in c(1:n)){
  35     y[,i] = x[,i] %*% beta[[affec[i]]] + rnorm(p, 0, sigmaY)
  36     xy[,i] = c(x[,i],y[,i])
  37     XY[,i] = xy[,i] - mean(xy[,i])
  38     Dx = dwt(x[,i], filter='haar')@W
  39     Dx = rev(unlist(Dx))
  40     Dx = Dx[2:(1+3+6+12+24)]
  41     Ax = dwt(x[,i], filter='haar')@V
  42     Ax = rev(unlist(Ax))
  43     Ax = Ax[2:(1+3)]
  44     Dy = dwt(y[,i], filter='haar')@W
  45     Dy = rev(unlist(Dy))
  46     Dy = Dy[2:(1+3+6+12+24)]
  47     Ay = dwt(y[,i], filter='haar')@V
  48     Ay = rev(unlist(Ay))
  49     Ay = Ay[2:(1+3)]
  50     Xproj[,i] = c(Ax,Dx)
  51     Yproj[,i] = c(Ay,Dy)
  52     XYproj[,i] = c(Ax,Dx,Ay,Dy)
  53   }
  54
  55   res_valse = valse(x,y)
  56   res_valse_proj = valse(Xproj, Yproj)
  57
  58   save(res_valse,file=paste("./Out/Res_",ite, ".RData",sep=""))
  59   save(res_valse_proj,file=paste("./Out/ResProj_",ite, ".RData",sep=""))
  60 }