library(morpheus)
+testMultistart <- function(N, n, K, p, beta, b, link, nstart, ncores)
+{
+ ms <- multiRun(
+ list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link,nstart=nstart)),
+ list(
+ function(fargs) {
+ # 1 start
+ library(morpheus)
+ K <- fargs$optargs$K
+ op <- optimParams(K, fargs$optargs$link, fargs$optargs)
+ x_init <- list(p=rep(1/K,K-1), beta=fargs$mu, b=rep(0,K))
+ res <- NULL
+ tryCatch({
+ res <- do.call(rbind, op$run(x_init))
+ }, error = function(e) {
+ res <- NA
+ })
+ res
+ },
+ function(fargs) {
+ # B starts
+ library(morpheus)
+ K <- fargs$optargs$K
+ op <- optimParams(K, fargs$optargs$link, fargs$optargs)
+ best_val <- Inf
+ best_par <- list()
+ for (i in 1:fargs$optargs$nstart)
+ {
+ #x_init <- list(p=rep(1/K,K-1), beta=i*fargs$mu, b=rep(0,K))
+ M <- matrix(rnorm(d*K), nrow=d, ncol=K)
+ M <- t(t(M) / sqrt(colSums(M^2)))
+ x_init <- list(p=rep(1/K,K-1), beta=M, b=rep(0,K))
+ tryCatch({
+ par <- op$run(x_init)
+ }, error = function(e) {
+ par <- NA
+ })
+ if (!is.na(par[0]))
+ {
+ val <- op$f( op$linArgs(par) )
+ if (val < best_val)
+ {
+ best_par <- par
+ best_val <- val
+ }
+ }
+ }
+ # Bet that at least one run succeded:
+ do.call(rbind,best_par)
+ }
+ ),
+ prepareArgs = function(fargs, index) {
+ library(morpheus)
+ io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
+ fargs$optargs$M <- computeMoments(io$X, io$Y)
+ mu <- computeMu(io$X, io$Y, fargs$optargs)
+ fargs$mu <- mu
+ fargs
+ }, N=N, ncores=ncores, verbose=TRUE)
+ for (i in 1:2)
+ ms[[i]] <- alignMatrices(ms[[i]], ref=rbind(p,beta,b), ls_mode="exact")
+ ms
+}
+
#model = binomial
K <- 2
p <- .5
b <- c(-.2, .5)
# Default values:
link = "logit"
-N <- 100
+N <- 10
d <- 2
n <- 1e4
ncores <- 1
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
beta <- betas[[ ifelse( d==2, 1, ifelse(d==5,2,3) ) ]]
-ms <- multiRun(
- list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link,nstart=nstart)), list(
- function(fargs) {
- # 1 start
- library(morpheus)
- K <- fargs$optargs$K
- op <- optimParams(K, fargs$optargs$link, fargs$optargs)
- x_init <- list(p=rep(1/K,K-1), beta=fargs$mu, b=rep(0,K))
- do.call(rbind,op$run(x_init))
- },
- function(fargs) {
- # B starts
- library(morpheus)
- K <- fargs$optargs$K
- op <- optimParams(K, fargs$optargs$link, fargs$optargs)
- best_val <- Inf
- best_par <- list()
- for (i in 1:fargs$optargs$nstart)
- {
- x_init <- list(p=rep(1/K,K-1), beta=i*fargs$mu, b=rep(0,K))
- par <- op$run(x_init)
- val <- op$f( op$linArgs(par) )
- if (val < best_val)
- {
- best_par <- par
- best_val <- val
- }
- }
- do.call(rbind,best_par)
- }),
- prepareArgs = function(fargs) {
- library(morpheus)
- io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
- fargs$optargs$M <- computeMoments(io$X, io$Y)
- mu <- computeMu(io$X, io$Y, fargs$optargs)
- fargs$mu <- mu
- }, N=N, ncores=ncores, verbose=TRUE)
-for (i in 1:2)
- ms[[i]] <- alignMatrices(ms[[i]], ref=rbind(p,beta,b), ls_mode="exact")
-
-ms_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "link"=link,
- "p"=p, "beta"=beta, "b"=b, "nstart"=nstart)
+ms <- testMultistart(N, n, K, p, beta, b, link, nstart, ncores)
+ms_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "d"=d, "link"=link,
+ "p"=c(p,1-sum(p)), "beta"=beta, "b"=b, "nstart"=nstart)
-save(ms, ms_params, file="multistart.RData")
+save("ms", "ms_params", file=paste("res_",n,"_",d,"_",link,"_",nstart,".RData",sep=""))