optimBeta <- function(N, n, p, beta, b, link, ncores) { 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, 1) #only 1 OpenMP core 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 } # Default values: link = "logit" N <- 10 d <- 2 n <- 1e4 ncores <- 1 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 (d == 2) { p <- .5 b <- c(-.2, .5) beta <- matrix( c(1,-2, 3,1), ncol=2 ) } else if (d == 5) { 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) { 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, 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("res_",n,"_",d,"_",link,".RData",sep=""))