From: Benjamin Auder <benjamin.auder@somewhere>
Date: Thu, 12 Jul 2018 14:37:02 +0000 (+0200)
Subject: 'update'
X-Git-Url: https://git.auder.net/variants/current/doc/css/img/mini-custom.min.css?a=commitdiff_plain;h=cc87714e5ad552260857c3abd508155355f10796;p=morpheus.git

'update'
---

diff --git a/reports/SAVE_RES/multirun_10_logit.RData b/reports/SAVE_RES/multirun_10_logit.RData
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diff --git a/reports/SAVE_RES/multirun_10_probit.RData b/reports/SAVE_RES/multirun_10_probit.RData
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diff --git a/reports/SAVE_RES/multirun_2_logit.RData b/reports/SAVE_RES/multirun_2_logit.RData
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diff --git a/reports/SAVE_RES/multirun_2_probit.RData b/reports/SAVE_RES/multirun_2_probit.RData
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diff --git a/reports/SAVE_RES/multirun_5_logit.RData b/reports/SAVE_RES/multirun_5_logit.RData
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diff --git a/reports/SAVE_RES/multirun_5_probit.RData b/reports/SAVE_RES/multirun_5_probit.RData
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diff --git a/reports/accuracy.R b/reports/accuracy.R
deleted file mode 100644
index d646ae3..0000000
--- a/reports/accuracy.R
+++ /dev/null
@@ -1,100 +0,0 @@
-optimBeta <- function(N, n, K, p, beta, b, link, ncores)
-{
-	library(morpheus)
-	res <- multiRun(
-		list(n=n,p=p,beta=beta,b=b,optargs=list(K=K,link=link)),
-		list(
-			# morpheus
-			function(fargs) {
-				library(morpheus)
-				K <- fargs$optargs$K
-				M <- computeMoments(fargs$X, fargs$Y)
-				fargs$optargs$M <- M
-				mu <- computeMu(fargs$X, fargs$Y, fargs$optargs)
-				op <- optimParams(K,link,fargs$optargs)
-				x_init <- c( rep(1/K,K-1), as.double(mu), rep(0,K) )
-				do.call(rbind, op$run(x_init))
-			},
-			# flexmix
-			function(fargs) {
-				library(flexmix)
-				source("../patch_Bettina/FLXMRglm.R")
-				K <- fargs$optargs$K
-				dat <- as.data.frame( cbind(fargs$Y,fargs$X) )
-				fm <- flexmix( cbind(V1, 1-V1) ~ .-V1, data=dat, k=K,
-					model = FLXMRglm(family = binomial(link = link)) )
-				p <- mean(fm@posterior[["scaled"]][,1])
-				out <- refit(fm)
-				beta_b <- sapply( seq_len(K), function(i) {
-					as.double( out@components[[1]][[i]][,1] )
-				} )
-				rbind(p, beta_b[2:nrow(beta_b),], beta_b[1,])
-			} ),
-		prepareArgs = function(fargs, index) {
-			library(morpheus)
-			io = generateSampleIO(fargs$n, fargs$p, fargs$beta, fargs$b, fargs$optargs$link)
-			fargs$X = io$X
-			fargs$Y = io$Y
-			fargs$optargs$K = ncol(fargs$beta)
-			fargs$optargs$M = computeMoments(io$X,io$Y)
-			fargs
-		}, N=N, ncores=ncores, verbose=TRUE)
-	p <- c(p, 1-sum(p))
-	for (i in 1:2)
-		res[[i]] <- alignMatrices(res[[i]], ref=rbind(p,beta,b), ls_mode="exact")
-	res
-}
-
-#model = binomial; default values:
-link = "logit"
-N <- 10
-d <- 2
-n <- 1e4
-ncores <- 1
-
-cmd_args <- commandArgs()
-for (arg in cmd_args)
-{
-	if (substr(arg,1,1)!='-') {
-		spl <- strsplit(arg,'=')[[1]]
-		if (spl[1] == "nc") {
-			ncores <- as.integer(spl[2])
-		} else if (spl[1] == "N") {
-			N <- as.integer(spl[2])
-		} else if (spl[1] == "n") {
-			n <- as.integer(spl[2])
-		} else if (spl[1] == "d") {
-			d <- as.integer(spl[2])
-		} else if (spl[1] == "link") {
-			link <- spl[2]
-		}
-	}
-}
-
-if (d == 2) {
-	K <- 2
-	p <- .5
-	b <- c(-.2, .5)
-	beta <- matrix( c(1,-2, 3,1), ncol=K )
-} else if (d == 5) {
-	K <- 2
-	p <- .5
-	b <- c(-.2, .5)
-	beta <- matrix( c(1,2,-1,0,3, 2,-3,0,1,0), ncol=K )
-} else if (d == 10) {
-	K <- 3
-	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=K )
-} else if (d == 20) {
-	K <- 3
-	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,-2,1,2,-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 )
-}
-
-mr <- optimBeta(N, n, K, p, beta, b, link, ncores)
-mr_params <- list("N"=N, "n"=n, "K"=K, "d"=d, "link"=link,
-	"p"=c(p,1-sum(p)), "beta"=beta, "b"=b)
-
-save("mr", "mr_params", file=paste("multirun_",d,"_",link,".RData",sep=""))
diff --git a/reports/multirun.RData b/reports/multirun.RData
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diff --git a/reports/multirun_10_logit.RData b/reports/multirun_10_logit.RData
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diff --git a/reports/multirun_10_probit.RData b/reports/multirun_10_probit.RData
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diff --git a/reports/multirun_2_logit.RData b/reports/multirun_2_logit.RData
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diff --git a/reports/multirun_2_probit.RData b/reports/multirun_2_probit.RData
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diff --git a/reports/multirun_5_logit.RData b/reports/multirun_5_logit.RData
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diff --git a/reports/multirun_5_probit.RData b/reports/multirun_5_probit.RData
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diff --git a/reports/multistart.R b/reports/multistart.R
deleted file mode 100644
index b3d1e10..0000000
--- a/reports/multistart.R
+++ /dev/null
@@ -1,85 +0,0 @@
-library(morpheus)
-
-#model = binomial
-K <- 2
-p <- .5
-b <- c(-.2, .5)
-# Default values:
-link = "logit"
-N <- 100
-d <- 2
-n <- 1e4
-ncores <- 1
-nstart <- 3 #nstart-1 random starting points for each MC run
-
-cmd_args <- commandArgs()
-for (arg in cmd_args)
-{
-	if (substr(arg,1,1)!='-')
-	{
-		spl <- strsplit(arg,'=')[[1]]
-		if (spl[1] == "nc") {
-			ncores <- as.integer(spl[2])
-		} else if (spl[1] == "N") {
-			N <- as.integer(spl[2])
-		} else if (spl[1] == "n") {
-			n <- as.integer(spl[2])
-		} else if (spl[1] == "d") {
-			d <- as.integer(spl[2])
-		} else if (spl[1] == "link") {
-			link <- spl[2]
-		} else if (spl[1] == "nstart") {
-			nstart <- spl[2]
-		}
-	}
-}
-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$optargs)
-			x_init <- c(rep(1/K,K-1), as.double(fargs$mu), 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 <- c(rep(1/K,K-1), as.double(i*fargs$mu), rep(0,K))
-				par <- op$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)
-
-save(ms, ms_params, file="multistart.RData")
diff --git a/reports/run_accu_cl.sh b/reports/run_accu_cl.sh
deleted file mode 100644
index 11bb5e0..0000000
--- a/reports/run_accu_cl.sh
+++ /dev/null
@@ -1,19 +0,0 @@
-#!/bin/bash
-
-#PBS -l nodes=1:ppn=15,mem=8gb,pmem=512mb
-#PBS -j oe
-
-#PBS -o .output
-rm -f .output
-
-WORKDIR=/workdir2/auder/morpheus/reports
-cd $WORKDIR
-
-module load R
-
-# arg --vanilla maybe possible on cluster
-for d in 10 20; do
-	for link in "logit" "probit"; do
-		R --slave --args N=1000 n=1e5 nc=15 d=$d link=$link <accuracy.R >out$d$link 2>&1
-	done
-done
diff --git a/reports/run_time_cl.sh b/reports/run_time_cl.sh
deleted file mode 100644
index 3055072..0000000
--- a/reports/run_time_cl.sh
+++ /dev/null
@@ -1,15 +0,0 @@
-#!/bin/bash
-
-#PBS -l nodes=1:ppn=16,mem=8gb,pmem=512mb
-#PBS -j oe
-
-#PBS -o .output
-rm -f .output
-
-WORKDIR=/workdir2/auder/morpheus/reports
-cd $WORKDIR
-
-module load R
-
-# arg --vanilla maybe possible on cluster
-R --slave --args N=1000 nc=16 link=logit <timings.R >out 2>&1
diff --git a/reports/timings.R b/reports/timings.R
deleted file mode 100644
index 704fd82..0000000
--- a/reports/timings.R
+++ /dev/null
@@ -1,84 +0,0 @@
-# flexmix optimization to get beta
-fmOptim <- function(X, Y, K, link)
-{
-	dat <- as.data.frame( cbind(Y,X) )
-	fm <- flexmix( cbind(Y, 1-Y) ~ .-Y, data=dat, k=K,
-		model = FLXMRglm(family = binomial(link = link)) )
-	p <- mean(fm@posterior[["scaled"]][,1])
-	out <- refit(fm)
-	beta_b <- sapply( seq_len(K), function(i) as.double( out@components[[1]][[i]][,1] ) )
-	list("p"=p, "beta"=beta_b[2:nrow(beta_b),], "b"=beta_b[1,])
-	NULL
-}
-
-# Our package optimization for beta (using mu as a starting point)
-ourOptim <- function(X, Y, K, link)
-{
-	M <- computeMoments(X, Y)
-	mu <- computeMu(X, Y, list(K=K,M=M))
-	x_init = c(1/2, as.double(mu), c(0,0))
-	optimParams(K, link, list(M=M))$run(x_init)
-	NULL
-}
-
-# Get timings for both methods with the same beta matrix
-getTimings <- function(link)
-{
-	timings <- list('fm'=matrix(0,nrow=10,ncol=7),'our'=matrix(0,nrow=10,ncol=7))
-	K <- 2
-	for (d in c(2,5,10))
-	{
-		beta <- matrix(runif(d*K,min=-5,max=5),ncol=K)
-		for (logn in 4:6)
-		{
-			n <- 10^logn
-			io <- generateSampleIO(n, rep(1/K,K-1), beta, runif(K), link)
-			timings[['fm']][d,logn] <- system.time(fmOptim(io$X,io$Y,K,link))[3]
-			timings[['our']][d,logn] <- system.time(ourOptim(io$X,io$Y,K,link))[3]
-		}
-	}
-	timings
-}
-
-#model = binomial
-link <- "logit"
-ncores <- 1
-N <- 100
-
-cmd_args <- commandArgs()
-for (arg in cmd_args)
-{
-	if (substr(arg,1,1)!='-')
-	{
-		spl <- strsplit(arg,'=')[[1]]
-		if (spl[1] == "link") {
-			link <- spl[2]
-		} else if (spl[1] == "nc") {
-			ncores <- as.integer(spl[2])
-		} else if (spl[1] == "N") {
-			N <- as.integer(spl[2])
-		}
-	}
-}
-
-library(morpheus)
-library(flexmix)
-source("../patch_Bettina/FLXMRglm.R")
-
-tm <-
-	if (ncores == 1) {
-		lapply(1:N, function(i) {
-			print(paste("Run",i))
-			getTimings(link)
-		})
-	} else {
-		library(parallel)
-		mclapply(1:N, function(i) {
-			print(paste("Run",i))
-			getTimings(link)
-		},
-		mc.preschedule=FALSE, mc.cores=ncores)
-	}
-tm_params <- list("link"=link, "N"=N, "nc"=ncores)
-
-save("tm", "tm_params", file="timings.RData")
diff --git a/reports/timings_logit.RData b/reports/timings_logit.RData
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diff --git a/reports/timings_save.RData b/reports/timings_save.RData
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