reports/multistart.R

   1 library(morpheus)
   2
   3 testMultistart <- function(N, n, d, K, p, beta, b, link, nstart, ncores)
   4 {
   5   res <- multiRun(
   6     list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,d=d,link=link,nstart=nstart)),
   7     list(
   8       function(fargs) {
   9         # 1 start
  10         library(morpheus)
  11         K <- fargs$optargs$K
  12         op <- optimParams(K, fargs$optargs$link, fargs$optargs)
  13         x_init <- list(p=rep(1/K,K-1), beta=fargs$mu, b=rep(0,K))
  14                 res2 <- NULL
  15                 tryCatch({
  16           res2 <- do.call(rbind, op$run(x_init))
  17                 }, error = function(e) {})
  18                 res2
  19       },
  20       function(fargs) {
  21         # B starts
  22         library(morpheus)
  23         K <- fargs$optargs$K
  24                 d <- fargs$optargs$d
  25         op <- optimParams(K, fargs$optargs$link, fargs$optargs)
  26         best_val <- Inf
  27         best_par <- list()
  28         for (i in 1:fargs$optargs$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$optargs$link)
  55       fargs$optargs$M <- computeMoments(io$X, io$Y)
  56       mu <- computeMu(io$X, io$Y, fargs$optargs)
  57       fargs$mu <- mu
  58             fargs
  59     }, N=N, ncores=ncores, verbose=TRUE)
  60   for (i in 1:2)
  61     res[[i]] <- alignMatrices(mr[[i]], ref=rbind(p,beta,b), ls_mode="exact")
  62   res
  63 }
  64
  65 #model = binomial
  66 K <- 2
  67 p <- .5
  68 b <- c(-.2, .5)
  69 # Default values:
  70 link = "logit"
  71 N <- 10
  72 d <- 2
  73 n <- 1e4
  74 ncores <- 1
  75 nstart <- 3 #nstart-1 random starting points for each MC run
  76
  77 cmd_args <- commandArgs()
  78 for (arg in cmd_args)
  79 {
  80     if (substr(arg,1,1)!='-')
  81     {
  82         spl <- strsplit(arg,'=')[[1]]
  83         if (spl[1] == "nc") {
  84             ncores <- as.integer(spl[2])
  85         } else if (spl[1] == "N") {
  86             N <- as.integer(spl[2])
  87         } else if (spl[1] == "n") {
  88             n <- as.integer(spl[2])
  89         } else if (spl[1] == "d") {
  90             d <- as.integer(spl[2])
  91         } else if (spl[1] == "link") {
  92             link <- spl[2]
  93         } else if (spl[1] == "nstart") {
  94             nstart <- spl[2]
  95         }
  96     }
  97 }
  98 betas <- list(
  99     matrix( c(1,-2, 3,1), ncol=K ), #d=2
 100     matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K ), #d=5
 101     matrix( c(1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0), ncol=K ) ) #d=10
 102 beta <- betas[[ ifelse( d==2, 1, ifelse(d==5,2,3) ) ]]
 103
 104 mr <- testMultistart(N, n, d, K, p, beta, b, link, nstart, ncores)
 105 mr_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "d"=d, "link"=link,
 106     "p"=c(p,1-sum(p)), "beta"=beta, "b"=b, "nstart"=nstart)
 107
 108 save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,"_",nstart,".RData",sep=""))