-optimBeta <- function(N, n, K, p, beta, b, link, ncores)
+optimBeta <- function(N, n, p, beta, b, link, ncores)
{
- library(morpheus)
- res <- multiRun(
- list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link)),
- list(
- # morpheus
- function(fargs) {
- library(morpheus)
- K <- fargs$optargs$K
- M <- computeMoments(fargs$X, fargs$Y)
- fargs$optargs$M <- M
- mu <- computeMu(fargs$X, fargs$Y, fargs$optargs)
- op <- optimParams(K,link,fargs$optargs)
- x_init <- c( rep(1/K,K-1), as.double(mu), rep(0,K) )
- do.call(rbind, op$run(x_init))
- },
- # flexmix
- function(fargs) {
- library(flexmix)
- source("../patch_Bettina/FLXMRglm.R")
- K <- fargs$optargs$K
- dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
- fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K,
- model = FLXMRglm(family = binomial(link = link)) )
- p <- mean(fm@posterior[["scaled"]][,1])
- out <- refit(fm)
- beta_b <- sapply( seq_len(K), function(i) {
- as.double( out@components[[1]][[i]][,1] )
- } )
- rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,])
- } ),
- prepareArgs = function(fargs, index) {
- library(morpheus)
- io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
- fargs$X = io$X
- fargs$Y = io$Y
- fargs$optargs$K = ncol(fargs$beta)
- fargs$optargs$M = computeMoments(io$X,io$Y)
- fargs
- }, N=N, ncores=ncores, verbose=TRUE)
- p <- c(p, 1-sum(p))
- for (i in 1:2)
- res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
- res
+ library(morpheus)
+ res <- multiRun(
+ list(n=n, p=p, beta=beta, b=b, link=link),
+ list(
+ # morpheus
+ function(fargs) {
+ library(morpheus)
+ K <- ncol(fargs$beta)
+ M <- computeMoments(fargs$X, fargs$Y)
+ mu <- computeMu(fargs$X, fargs$Y, list(K=K, M=M))
+ op <- optimParams(fargs$X, fargs$Y, K, fargs$link, M)
+ x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K))
+ res2 <- NULL
+ tryCatch({
+ res2 <- do.call(rbind, op$run(x_init))
+ }, error = function(e) {})
+ res2
+ }
+ ,
+ # flexmix
+ function(fargs) {
+ library(flexmix)
+ source("../patch_Bettina/FLXMRglm.R")
+ K <- ncol(fargs$beta)
+ dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
+ res2 <- NULL
+ tryCatch({
+ fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K,
+ model = FLXMRglm(family = binomial(link = link)) )
+ pf <- mean(fm@posterior[["scaled"]][,1])
+ out <- refit(fm)
+ beta_b <- sapply( seq_len(K), function(i) {
+ as.double( out@components[[1]][[i]][,1] )
+ } )
+ res2 <- rbind(pf, beta_b[2:nrow(beta_b),], beta_b[1,])
+ }, error = function(e) {
+ res2 <- NA
+ })
+ res2
+ }
+ ),
+ prepareArgs = function(fargs, index) {
+ library(morpheus)
+ io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$link)
+ fargs$X = io$X
+ fargs$Y = io$Y
+ fargs
+ }, N=N, ncores=ncores, verbose=TRUE)
+ p <- c(p, 1-sum(p))
+ for (i in 1:length(res)) {
+ for (j in N:1) {
+ if (is.null(res[[i]][[j]]) || is.na(res[[i]][[j]]))
+ res[[i]][[j]] <- NULL
+ }
+ print(paste("Count valid runs for ",i," = ",length(res[[i]]),sep=""))
+ res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
+ }
+ res
}
-#model = binomial; default values:
+# Default values:
link = "logit"
N <- 10
d <- 2
cmd_args <- commandArgs()
for (arg in cmd_args)
{
- if (substr(arg,1,1)!='-') {
- spl <- strsplit(arg,'=')[[1]]
- if (spl[1] == "nc") {
- ncores <- as.integer(spl[2])
- } else if (spl[1] == "N") {
- N <- as.integer(spl[2])
- } else if (spl[1] == "n") {
- n <- as.integer(spl[2])
- } else if (spl[1] == "d") {
- d <- as.integer(spl[2])
- } else if (spl[1] == "link") {
- link <- spl[2]
- }
- }
+ if (substr(arg,1,1)!='-') {
+ spl <- strsplit(arg,'=')[[1]]
+ if (spl[1] == "nc") {
+ ncores <- as.integer(spl[2])
+ } else if (spl[1] == "N") {
+ N <- as.integer(spl[2])
+ } else if (spl[1] == "n") {
+ n <- as.integer(spl[2])
+ } else if (spl[1] == "d") {
+ d <- as.integer(spl[2])
+ } else if (spl[1] == "link") {
+ link <- spl[2]
+ }
+ }
}
if (d == 2) {
- K <- 2
- p <- .5
- b <- c(-.2, .5)
- beta <- matrix( c(1,-2, 3,1), ncol=K )
+ p <- .5
+ b <- c(-.2, .5)
+ beta <- matrix( c(1,-2, 3,1), ncol=2 )
} else if (d == 5) {
- K <- 2
- p <- .5
- b <- c(-.2, .5)
- beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K )
+ p <- .5
+ b <- c(-.2, .5)
+ beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 )
} else if (d == 10) {
- K <- 3
- p <- c(.3, .3)
- b <- c(-.2, 0, .5)
- 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=K )
-} else if (d == 20) {
- K <- 3
- p <- c(.3, .3)
- b <- c(-.2, 0, .5)
- 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,-2,1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0,1,1,2,2,-2,-2,3,1,0,0), ncol=K )
+ p <- c(.3, .3)
+ b <- c(-.2, 0, .5)
+ 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 )
}
-mr <- optimBeta(N, n, K, p, beta, b, link, ncores)
-mr_params <- list("N"=N, "n"=n, "K"=K, "d"=d, "link"=link,
- "p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
+mr <- optimBeta(N, n, p, beta, b, link, ncores)
+mr_params <- list("N"=N, "nc"=ncores, "n"=n, "link"=link,
+ "p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
-save("mr", "mr_params", file=paste("multirun_",d,"_",link,".RData",sep=""))
+save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,".RData",sep=""))