6f322bf685999590653f344a99105b9bab7bb564
[morpheus.git] / reports / accuracy.R
1 optimBeta <- function(N, n, p, beta, b, link, ncores)
2 {
3 library(morpheus)
4 res <- multiRun(
5 list(n=n, p=p, beta=beta, b=b, link=link),
6 list(
7 # morpheus
8 function(fargs) {
9 library(morpheus)
10 K <- ncol(fargs$beta)
11 M <- computeMoments(fargs$X, fargs$Y)
12 mu <- computeMu(fargs$X, fargs$Y, list(K=K, M=M))
13 op <- optimParams(fargs$X, fargs$Y, K, fargs$link, M)
14 x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K))
15 res2 <- NULL
16 tryCatch({
17 res2 <- do.call(rbind, op$run(x_init))
18 }, error = function(e) {})
19 res2
20 },
21 # flexmix
22 function(fargs) {
23 library(flexmix)
24 source("../patch_Bettina/FLXMRglm.R")
25 K <- ncol(fargs$beta)
26 dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
27 res2 <- NULL
28 tryCatch({
29 fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K,
30 model = FLXMRglm(family = binomial(link = link)) )
31 p <- mean(fm@posterior[["scaled"]][,1])
32 out <- refit(fm)
33 beta_b <- sapply( seq_len(K), function(i) {
34 as.double( out@components[[1]][[i]][,1] )
35 } )
36 res2 <- rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,])
37 }, error = function(e) {
38 res2 <- NA
39 })
40 res2
41 }
42 ),
43 prepareArgs = function(fargs, index) {
44 library(morpheus)
45 io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$link)
46 fargs$X = io$X
47 fargs$Y = io$Y
48 fargs
49 }, N=N, ncores=ncores, verbose=TRUE)
50 p <- c(p, 1-sum(p))
51 for (i in 1:length(res)) {
52 for (j in N:1) {
53 if (is.null(res[[i]][[j]]) || is.na(res[[i]][[j]]))
54 res[[i]][[j]] <- NULL
55 }
56 print(paste("Count valid runs for ",i," = ",length(res[[i]]),sep=""))
57 res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
58 }
59 res
60 }
61
62 # Default values:
63 link = "logit"
64 N <- 10
65 d <- 2
66 n <- 1e4
67 ncores <- 1
68
69 cmd_args <- commandArgs()
70 for (arg in cmd_args)
71 {
72 if (substr(arg,1,1)!='-') {
73 spl <- strsplit(arg,'=')[[1]]
74 if (spl[1] == "nc") {
75 ncores <- as.integer(spl[2])
76 } else if (spl[1] == "N") {
77 N <- as.integer(spl[2])
78 } else if (spl[1] == "n") {
79 n <- as.integer(spl[2])
80 } else if (spl[1] == "d") {
81 d <- as.integer(spl[2])
82 } else if (spl[1] == "link") {
83 link <- spl[2]
84 }
85 }
86 }
87
88 if (d == 2) {
89 p <- .5
90 b <- c(-.2, .5)
91 beta <- matrix( c(1,-2, 3,1), ncol=2 )
92 } else if (d == 5) {
93 p <- .5
94 b <- c(-.2, .5)
95 beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=2 )
96 } else if (d == 10) {
97 p <- c(.3, .3)
98 b <- c(-.2, 0, .5)
99 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 )
100 }
101
102 mr <- optimBeta(N, n, p, beta, b, link, ncores)
103 mr_params <- list("N"=N, "nc"=ncores, "n"=n, "link"=link,
104 "p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
105
106 save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,".RData",sep=""))