Fix typo in multistart.R

[morpheus.git] / reports / multistart.R

diff --git a/reports/multistart.R b/reports/multistart.R
index 9971cd2..73df538 100644 (file)
--- a/reports/multistart.R
+++ b/reports/multistart.R
@@ -1,13 +1,77 @@
 library(morpheus)
 
-#model = binomial
-K <- 2
-p <- .5
-b <- c(-.2, .5)
+testMultistart <- function(N, n, p, beta, b, link, nstart, ncores)
+{
+  res <- multiRun(
+    list(n=n, p=p, beta=beta, b=b, link=link, nstart=nstart),
+    list(
+      function(fargs) {
+        # 1 start
+        library(morpheus)
+        K <- ncol(fargs$beta)
+        mu <- computeMu(fargs$X, fargs$Y, list(K=K, M=fargs$M))
+        op <- optimParams(fargs$X, fargs$Y, K, fargs$link, fargs$M)
+        x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K))
+                               res2 <- NULL
+                               tryCatch({
+          res2 <- do.call(rbind, op$run(x_init))
+                               }, error = function(e) {})
+                               res2
+      },
+      function(fargs) {
+        # B starts
+        library(morpheus)
+        K <- ncol(fargs$beta)
+                               d <- nrow(fargs$beta)
+        op <- optimParams(fargs$X, fargs$Y, K, fargs$link, fargs$M)
+        best_val <- Inf
+        best_par <- list()
+        for (i in 1:fargs$nstart)
+        {
+          #x_init <- list(p=rep(1/K,K-1), beta=i*fargs$mu, b=rep(0,K))
+          M <- matrix(rnorm(d*K), nrow=d, ncol=K)
+          M <- t(t(M) / sqrt(colSums(M^2)))
+          x_init <- list(p=rep(1/K,K-1), beta=M, b=rep(0,K))
+          par <- NULL
+                                       tryCatch({
+            par <- op$run(x_init)
+          }, error = function(e) {})
+          if (!is.null(par))
+          {
+            val <- op$f( op$linArgs(par) )
+            if (val < best_val)
+            {
+              best_par <- par
+              best_val <- val
+            }
+          }
+        }
+        do.call(rbind,best_par) #return NULL on empty list
+      }
+    ),
+    prepareArgs = function(fargs, index) {
+      library(morpheus)
+      io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$link)
+      fargs$M <- computeMoments(io$X, io$Y)
+      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 <- 100
-d <- 2
+N <- 10
 n <- 1e4
 ncores <- 1
 nstart <- 3 #nstart-1 random starting points for each MC run
@@ -33,53 +97,23 @@ for (arg in cmd_args)
                }
        }
 }
-betas <- list(
-       matrix( c(1,-2, 3,1), ncol=K ), #d=2
-       matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K ), #d=5
-       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")
+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 )
+}
 
-ms_params <- list("N"=N, "nc"=ncores, "n"=n, "K"=K, "link"=link,
-       "p"=p, "beta"=beta, "b"=b, "nstart"=nstart)
+mr <- testMultistart(N, n, p, beta, b, link, nstart, ncores)
+mr_params <- list("N"=N, "nc"=ncores, "n"=n, "link"=link,
+       "p"=c(p,1-sum(p)), "beta"=beta, "b"=b, "nstart"=nstart)
 
-save(ms, ms_params, file="multistart.RData")
+save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,"_",nstart,".RData",sep=""))