Fix default weights, fix reporting scripts

[morpheus.git] / reports / multistart.R

diff --git a/reports/multistart.R b/reports/multistart.R
index 9971cd2..5fa80ad 100644 (file)
--- a/reports/multistart.R
+++ b/reports/multistart.R
@@ -1,12 +1,76 @@
 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
@@ -39,47 +103,8 @@ betas <- list(
        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="multistart.RData")