reports/multistart.R

   1 library(morpheus)
   2
   3 testMultistart <- function(N, n, p, beta, b, link, nstart, ncores)
   4 {
   5   res <- multiRun(
   6     list(n=n, p=p, beta=beta, b=b, link=link, nstart=nstart),
   7     list(
   8       function(fargs) {
   9         # 1 start
  10         library(morpheus)
  11         K <- ncol(fargs$beta)
  12         op <- optimParams(fargs$X, fargs$Y, K, fargs$link, fargs$M)
  13         x_init <- list(p=rep(1/K,K-1), beta=fargs$mu, b=rep(0,K))
  14                 res2 <- NULL
  15                 tryCatch({
  16           res2 <- do.call(rbind, op$run(x_init))
  17                 }, error = function(e) {})
  18                 res2
  19       },
  20       function(fargs) {
  21         # B starts
  22         library(morpheus)
  23         K <- ncol(fargs$beta)
  24                 d <- nrow(fargs$beta)
  25         op <- optimParams(fargs$X, fargs$Y, K, fargs$link, fargs$M)
  26         best_val <- Inf
  27         best_par <- list()
  28         for (i in 1:fargs$nstart)
  29         {
  30           #x_init <- list(p=rep(1/K,K-1), beta=i*fargs$mu, b=rep(0,K))
  31           M <- matrix(rnorm(d*K), nrow=d, ncol=K)
  32           M <- t(t(M) / sqrt(colSums(M^2)))
  33           x_init <- list(p=rep(1/K,K-1), beta=M, b=rep(0,K))
  34           par <- NULL
  35                     tryCatch({
  36             par <- op$run(x_init)
  37           }, error = function(e) {})
  38           if (!is.null(par))
  39           {
  40             val <- op$f( op$linArgs(par) )
  41             if (val < best_val)
  42             {
  43               best_par <- par
  44               best_val <- val
  45             }
  46           }
  47         }
  48         # Bet that at least one run succeded:
  49         do.call(rbind,best_par)
  50       }
  51     ),
  52     prepareArgs = function(fargs, index) {
  53       library(morpheus)
  54       io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$link)
  55       fargs$M <- computeMoments(io$X, io$Y)
  56       mu <- computeMu(io$X, io$Y, list(M=fargs$M))
  57       fargs$mu <- mu
  58       fargs$X <- io$X
  59       fargs$Y <- io$Y
  60             fargs
  61     }, N=N, ncores=ncores, verbose=TRUE)
  62   for (i in 1:2)
  63     res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
  64   res
  65 }
  66
  67 # Default values:
  68 link = "logit"
  69 N <- 10
  70 n <- 1e4
  71 ncores <- 1
  72 nstart <- 3 #nstart-1 random starting points for each MC run
  73
  74 cmd_args <- commandArgs()
  75 for (arg in cmd_args)
  76 {
  77     if (substr(arg,1,1)!='-')
  78     {
  79         spl <- strsplit(arg,'=')[[1]]
  80         if (spl[1] == "nc") {
  81             ncores <- as.integer(spl[2])
  82         } else if (spl[1] == "N") {
  83             N <- as.integer(spl[2])
  84         } else if (spl[1] == "n") {
  85             n <- as.integer(spl[2])
  86         } else if (spl[1] == "d") {
  87             d <- as.integer(spl[2])
  88         } else if (spl[1] == "link") {
  89             link <- spl[2]
  90         } else if (spl[1] == "nstart") {
  91             nstart <- spl[2]
  92         }
  93     }
  94 }
  95
  96 if (d == 2) {
  97   p <- .5
  98   b <- c(-.2, .5)
  99   beta <- matrix( c(1,-2, 3,1), ncol=2 )
 100 } else if (d == 5) {
 101   p <- .5
 102   b <- c(-.2, .5)
 103   beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 )
 104 } else if (d == 10) {
 105   p <- c(.3, .3)
 106   b <- c(-.2, 0, .5)
 107   beta <- matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0, -1,1,3,-1,0,0,2,0,1,-2), ncol=3 )
 108 }
 109
 110 mr <- testMultistart(N, n, p, beta, b, link, nstart, ncores)
 111 mr_params <- list("N"=N, "nc"=ncores, "n"=n, "link"=link,
 112     "p"=c(p,1-sum(p)), "beta"=beta, "b"=b, "nstart"=nstart)
 113
 114 save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,"_",nstart,".RData",sep=""))