projects / morpheus.git / blame
| Commit | Line | Data |
|---|---|---|
| 98b8a5dd | 1 | optimBeta <- function(N, n, K, p, beta, b, link, weights, ncores) |
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2 | { |
| 3 | library(morpheus) | |
| 4 | res <- multiRun( | |
| 98b8a5dd | 5 | list(n=n, p=p, beta=beta, b=b, optargs=list(K=K, link=link, weights=weights)), |
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6 | list( |
| 7 | # morpheus | |
| 8 | function(fargs) { | |
| 9 | library(morpheus) | |
| 10 | K <- fargs$optargs$K | |
| 11 | M <- computeMoments(fargs$X, fargs$Y) | |
| 12 | fargs$optargs$M <- M | |
| 13 | mu <- computeMu(fargs$X, fargs$Y, fargs$optargs) | |
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14 | res2 <- NULL |
| 15 | tryCatch({ | |
| 324febd3 | 16 | op <- optimParams(K,fargs$optargs$link,fargs$optargs) |
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17 | x_init <- list(p=rep(1/K,K-1), beta=mu, b=rep(0,K)) |
| 18 | res2 <- do.call(rbind, op$run(x_init)) | |
| 19 | }, error = function(e) { | |
| 20 | res2 <- NA | |
| 21 | }) | |
| 22 | res2 | |
| 23 | } | |
| 24 | # , | |
| 25 | # # flexmix | |
| 26 | # function(fargs) { | |
| 27 | # library(flexmix) | |
| 28 | # source("../patch_Bettina/FLXMRglm.R") | |
| 29 | # K <- fargs$optargs$K | |
| 30 | # dat <- as.data.frame( cbind(fargs$Y,fargs$X) ) | |
| 31 | # res2 <- NULL | |
| 32 | # tryCatch({ | |
| 33 | # fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K, | |
| 34 | # model = FLXMRglm(family = binomial(link = link)) ) | |
| 35 | # p <- mean(fm@posterior[["scaled"]][,1]) | |
| 36 | # out <- refit(fm) | |
| 37 | # beta_b <- sapply( seq_len(K), function(i) { | |
| 38 | # as.double( out@components[[1]][[i]][,1] ) | |
| 39 | # } ) | |
| 40 | # res2 <- rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,]) | |
| 41 | # }, error = function(e) { | |
| 42 | # res2 <- NA | |
| 43 | # }) | |
| 44 | # res2 | |
| 45 | # } | |
| 46 | ), | |
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47 | prepareArgs = function(fargs, index) { |
| 48 | library(morpheus) | |
| 49 | io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link) | |
| 50 | fargs$X = io$X | |
| 51 | fargs$Y = io$Y | |
| 52 | fargs$optargs$K = ncol(fargs$beta) | |
| 53 | fargs$optargs$M = computeMoments(io$X,io$Y) | |
| 54 | fargs | |
| 55 | }, N=N, ncores=ncores, verbose=TRUE) | |
| 56 | p <- c(p, 1-sum(p)) | |
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57 | for (i in 1:length(res)) { |
| 58 | for (j in N:1) { | |
| 59 | if (is.null(res[[i]][[j]]) || is.na(res[[i]][[j]])) | |
| 60 | res[[i]][[j]] <- NULL | |
| 61 | } | |
| 62 | print(paste("Count valid runs for ",i," = ",length(res[[i]]),sep="")) | |
| 1d014a86 | 63 | res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact") |
| 9007ccc1 | 64 | } |
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65 | res |
| 66 | } | |
| 67 | ||
| 68 | #model = binomial; default values: | |
| 69 | link = "logit" | |
| 70 | N <- 10 | |
| 71 | d <- 2 | |
| 72 | n <- 1e4 | |
| 73 | ncores <- 1 | |
| b46623ad | 74 | strw <- "1-1-1" |
| 98b8a5dd | 75 | weights <- c(1,1,1) |
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76 | |
| 77 | cmd_args <- commandArgs() | |
| 78 | for (arg in cmd_args) | |
| 79 | { | |
| 80 | if (substr(arg,1,1)!='-') { | |
| 81 | spl <- strsplit(arg,'=')[[1]] | |
| 82 | if (spl[1] == "nc") { | |
| 83 | ncores <- as.integer(spl[2]) | |
| 84 | } else if (spl[1] == "N") { | |
| 85 | N <- as.integer(spl[2]) | |
| 86 | } else if (spl[1] == "n") { | |
| 87 | n <- as.integer(spl[2]) | |
| 88 | } else if (spl[1] == "d") { | |
| 89 | d <- as.integer(spl[2]) | |
| 90 | } else if (spl[1] == "link") { | |
| 91 | link <- spl[2] | |
| 98b8a5dd | 92 | } else if (spl[1] == "weights") { |
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93 | strw <- spl[2] |
| 94 | weights <- as.numeric(unlist(strsplit(spl[2], ","))) | |
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95 | } |
| 96 | } | |
| 97 | } | |
| 98 | ||
| 99 | if (d == 2) { | |
| 100 | K <- 2 | |
| 101 | p <- .5 | |
| 102 | b <- c(-.2, .5) | |
| 103 | beta <- matrix( c(1,-2, 3,1), ncol=K ) | |
| 104 | } else if (d == 5) { | |
| 105 | K <- 2 | |
| 106 | p <- .5 | |
| 107 | b <- c(-.2, .5) | |
| 108 | beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K ) | |
| 109 | } else if (d == 10) { | |
| 110 | K <- 3 | |
| 111 | p <- c(.3, .3) | |
| 112 | b <- c(-.2, 0, .5) | |
| 113 | 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=K ) | |
| 114 | } else if (d == 20) { | |
| 115 | K <- 3 | |
| 116 | p <- c(.3, .3) | |
| 117 | b <- c(-.2, 0, .5) | |
| 118 | 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,-2,1,2,-1,0,3,4,-1,-3,0,2, 2,-3,0,1,0,-1,-4,3,2,0,1,1,2,2,-2,-2,3,1,0,0), ncol=K ) | |
| 119 | } | |
| 120 | ||
| 98b8a5dd | 121 | mr <- optimBeta(N, n, K, p, beta, b, link, weights, ncores) |
| 1d014a86 | 122 | mr_params <- list("N"=N, "n"=n, "K"=K, "d"=d, "link"=link, |
| 98b8a5dd | 123 | "p"=c(p,1-sum(p)), "beta"=beta, "b"=b, "weights"=weights) |
| 1d014a86 | 124 | |
| b46623ad | 125 | save("mr", "mr_params", file=paste("res_",n,"_",d,"_",link,"_",strw,".RData",sep="")) |