reports/multistart.R

   1 library(morpheus)
   2
   3 #model = binomial
   4 K <- 2
   5 p <- .5
   6 b <- c(-.2, .5)
   7 # Default values:
   8 link = "logit"
   9 N <- 100
  10 d <- 2
  11 n <- 1e4
  12 ncores <- 1
  13 nstart <- 3 #nstart-1 random starting points for each MC run
  14
  15 cmd_args <- commandArgs()
  16 for (arg in cmd_args)
  17 {
  18     if (substr(arg,1,1)!='-')
  19     {
  20         spl <- strsplit(arg,'=')[[1]]
  21         if (spl[1] == "nc") {
  22             ncores <- as.integer(spl[2])
  23         } else if (spl[1] == "N") {
  24             N <- as.integer(spl[2])
  25         } else if (spl[1] == "n") {
  26             n <- as.integer(spl[2])
  27         } else if (spl[1] == "d") {
  28             d <- as.integer(spl[2])
  29         } else if (spl[1] == "link") {
  30             link <- spl[2]
  31         } else if (spl[1] == "nstart") {
  32             nstart <- spl[2]
  33         }
  34     }
  35 }
  36 betas <- list(
  37     matrix( c(1,-2, 3,1), ncol=K ), #d=2
  38     matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K ), #d=5
  39     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
  40 beta <- betas[[ ifelse( d==2, 1, ifelse(d==5,2,3) ) ]]
  41
  42 ms <- multiRun(
  43     list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link,nstart=nstart)), list(
  44         function(fargs) {
  45             # 1 start
  46             library(morpheus)
  47             K <- fargs$optargs$K
  48             op <- optimParams(K, fargs$optargs$link, fargs$optargs)
  49             x_init <- c(rep(1/K,K-1), as.double(fargs$mu), rep(0,K))
  50             do.call(rbind,op$run(x_init))
  51         },
  52         function(fargs) {
  53             # B starts
  54             library(morpheus)
  55             K <- fargs$optargs$K
  56             op <- optimParams(K, fargs$optargs$link, fargs$optargs)
  57             best_val <- Inf
  58             best_par <- list()
  59             for (i in 1:fargs$optargs$nstart)
  60             {
  61                 x_init <- c(rep(1/K,K-1), as.double(i*fargs$mu), rep(0,K))
  62                 par <- op$run(x_init)
  63                 val <- op$f( op$linArgs(par) )
  64                 if (val < best_val)
  65                 {
  66                     best_par <- par
  67                     best_val <- val
  68                 }
  69             }
  70             do.call(rbind,best_par)
  71         }),
  72         prepareArgs = function(fargs) {
  73             library(morpheus)
  74             io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
  75             fargs$optargs$M <- computeMoments(io$X, io$Y)
  76             mu <- computeMu(io$X, io$Y, fargs$optargs)
  77             fargs$mu <- mu
  78         }, N=N, ncores=ncores, verbose=TRUE)
  79 for (i in 1:2)
  80     ms[[i]] <- alignMatrices(ms[[i]], ref=rbind(p,beta,b), ls_mode="exact")
  81
  82 ms_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "link"=link,
  83     "p"=p, "beta"=beta, "b"=b, "nstart"=nstart)
  84
  85 save(ms, ms_params, file="multistart.RData")