sds <- c(140, 122, 123, 111, 111,#
	96, 93, 98, 105, 103,#
	98, 93, 95, 107, 103,#
	0.32, 0.35, 0.41, 0.50, 0.46,#
	0.48, 0.47, 0.47, 0.49, 0.46,#
	0.43, 0.39, 0.30, 0.14, 0.10)
sds
SDs Reichle et al.#
sds.r <- c(38.76, 44.81, 40.29, 59.61, 71.11,#
	26.34, 31.65, 31.31, 49.21, 64.75,#
#	147, 123, 132, 122, 130,#
	26.34, 31.65, 31.31, 49.21, 64.75,		## fake#
	0.3000, 0.3363, 0.4142, 0.4975, 0.4702,#
	0.4665, 0.4583, 0.4665, 0.4964, 0.4665,#
	0.43, 0.39, 0.30, 0.14, 0.10#
	)
Model: ###
# head(m)#
m.m1 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","FPRT","FFD","SFD"),#
	variable="Measure", na.rm = T)#
# head(m.m1) # summary(m.m1) # dim(m.m1) # str(m.m1)#
fstat1.m <- data.frame(round(cast(subset(m.m1,value!=0), freq.class ~ Measure, mean)))#
fstat1.m
m.m2 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","skipped","onefix","twofix"),#
	variable="Measure", na.rm = T)#
# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
fstat2.m$frequency <- round(fstat2.m$frequency)#
fstat2.m
head(m)
measure=c("frequency","skipped","onefix","refix"),
m.m2 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","skipped","onefix","refix"),#
	variable="Measure", na.rm = T)#
# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
fstat2.m$frequency <- round(fstat2.m$frequency)#
fstat2.m
m.m2 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","skip","onefix","refix"),#
	variable="Measure", na.rm = T)#
# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
fstat2.m$frequency <- round(fstat2.m$frequency)#
fstat2.m
fstat1.cor <- round(cor(fstat1[,3:5],fstat1.m[,3:5], method="pearson"), digits=2)#
fstat2.cor <- round(cor(fstat2[,3:5],fstat2.m[,3:5], method="pearson"), digits=2)
i <- diag(nrow=length(1:3))==1#
(fstat1.cor <- fstat1.cor[,1:3][i])#
(fstat2.cor <- fstat2.cor[,1:3][i])#
fstat.cor.mean <- mean(c(fstat1.cor,fstat2.cor),na.rm=T)
fstat.cor.mean
rmsd: ###
fstat1.rmsd <- NULL#
fstat2.rmsd <- NULL#
for(i in 3:5){#
	fstat1.rmsd <-	cbind(fstat1.rmsd,nrmsd(fstat1[,i],fstat1.m[,i],fstat1.sd[,i-2]))#
	fstat2.rmsd <-	cbind(fstat2.rmsd,nrmsd(fstat2[,i],fstat2.m[,i],fstat2.sd[,i-2]))#
}#
(fstat1.rmsd <- as.vector(fstat1.rmsd))#
(fstat2.rmsd <- as.vector(fstat2.rmsd))#
fstat.rmsd.mean <- mean(c(fstat1.rmsd,fstat2.rmsd), na.rm=T)
fstat.rmsd.mean
fstat1.rmsd
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix)
fstat.m
fstat.cor <- cor(fstat.d, fstat.m)
fstat.cor
round(cor(fstat1.d[,3:5],fstat1.m[,3:5], method="pearson"), digits=2)
fstat1.cor <- round(cor(fstat1[,3:5],fstat1.m[,3:5], method="pearson"), digits=2)
fstat1
fstat1.cor
fstat.cor <- cor(fstat.d, fstat.m)
fstat.cor
fstat.d
fstat.m
fstat.d
fstat.cor <- NULL#
for (i in c(1,6,11,16)) {#
	fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)]))}
fstat.cor
for (i in c(1,6,11,16,21,26)) {#
	fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)]))}#
fstat.cor
mean(fstat.cor)
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix)
fstat.m
setwd("../model-src-nsp_3-4-135/")
load("m.RData")
DATA#
gaze <- c(293,272,256,234,214)#
FFD <- c(248,233,230,223,208)#
SFD <- c(265, 249, 243, 235, 216)#
SKIP <- c(.10, .13, .22, .55, .67)#
FIX1 <- c(.68, .70, .68, .44, .32)#
FIX2 <- c(.20, .16, .10, .02, .01)#
#
fstat.d <- c(gaze, FFD, SFD, SKIP, FIX1, FIX2)#
#
## SDs from my calculation#
sds <- c(140, 122, 123, 111, 111,#
	96, 93, 98, 105, 103,#
	98, 93, 95, 107, 103,#
	0.32, 0.35, 0.41, 0.50, 0.46,#
	0.48, 0.47, 0.47, 0.49, 0.46,#
	0.43, 0.39, 0.30, 0.14, 0.10)#
## SDs Reichle et al.#
sds.r <- c(38.76, 44.81, 40.29, 59.61, 71.11,#
	26.34, 31.65, 31.31, 49.21, 64.75,#
#	147, 123, 132, 122, 130,#
	26.34, 31.65, 31.31, 49.21, 64.75,		## fake#
	0.3000, 0.3363, 0.4142, 0.4975, 0.4702,#
	0.4665, 0.4583, 0.4665, 0.4964, 0.4665,#
	0.43, 0.39, 0.30, 0.14, 0.10#
	)
Model: ###
# head(m)#
m.m1 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","FPRT","FFD","SFD"),#
	variable="Measure", na.rm = T)#
# head(m.m1) # summary(m.m1) # dim(m.m1) # str(m.m1)#
fstat1.m <- data.frame(round(cast(subset(m.m1,value!=0), freq.class ~ Measure, mean)))#
fstat1.m#
m.m2 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","skip","onefix","refix"),#
	variable="Measure", na.rm = T)#
# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
fstat2.m$frequency <- round(fstat2.m$frequency)#
fstat2.m#
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix)
m.m2 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","skipped","onefix","twofix"),#
	variable="Measure", na.rm = T)#
# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
fstat2.m$frequency <- round(fstat2.m$frequency)#
fstat2.m
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix)
fstat.m
fstat.cor <- NULL#
for (i in c(1,6,11,16,21,26)) {#
	fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)]))}#
fstat.cor
fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}
fstat.cor <- NULL#
for (i in c(1,6,11,16,21,26)) {#
	fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
fstat.cor
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skipped, fstat2.m$onefix, fstat2.m$twofix)
fstat.m
fstat.cor <- NULL#
for (i in c(1,6,11,16,21,26)) {#
	fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
fstat.cor#
mean(fstat.cor)
fstat.cor.mean <- mean(fstat.cor)
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds.r)^2))
fstat.rmsd.mean
fstat.m
fstat.d
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds)^2))
fstat.rmsd.mean
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds.r)^2))
fstat.rmsd.mean
pscore <- mean(1 * fstat.rmsd.mean + (1-mean(c(fstat1.cor, fstat2.cor))))
pscore
round(fstat.cor.mean, digits=2)#
round(fstat.rmsd.mean, digits=3)#
round(pscore,digits=3)
fstat.d
ds
sds
sds.r
fstat.cor
fstat.cor.mean
save(fstat.d, sds, sds.r, fstat1.m, fstat2.m, fstat.rmsd.mean, fstat.cor, fstat.cor.mean, file="fstat.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-src-nsp_3-4-135/")#
file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
source("../scripts/2-f-statistics-SC.R")
source("../scripts/2-f-statistics-SC.R")
pscore <- mean(1 * fstat.rmsd.mean + (1-fstat.cor.mean))
source("../scripts/2-f-statistics-SC.R")
round(fstat.cor.mean, digits=2)
round(fstat.rmsd.mean, digits=3)
fstat.rmsd.mean
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds.r)^2))
fstat.rmsd.mean
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-src-nsp_3-4-135/")#
file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
remove(list=ls())#
library(reshape)	# for aggregating#
library(plyr)#
#
#setwd("/Users/felix/Dropbox/Workspace/ACT-R_EMMA/readsrc98")#
#source("~/Dropbox/FelixE/PSC-Model/helpers.R")#
#
#source("1-analyze.R")#
#
#file <- paste("data/m.",Sys.Date(),".RData",sep="")#
#file <- "data/m.RData"#
#load(file)#
# head(m)#
##################################################
### (0) Exclude Trials with interword regressions#
##################################################
m0 <- m#
m$trial <- paste(m$sn, m$sim, sep=".")  ## add trial variable#
regtrials <- na.omit(m$trial[m$TRC>0])  ## identify trials with regressions#
round(length(unique(regtrials))/length(unique(m$trial))*100)  ## percentage of trials with regressions#
################### <---> ####################
m <- subset(m, !(trial%in%regtrials)) ### COMMENT OUT IF NOT WANTED ####
################### <---> ####################
dim(m0); dim(m)#
round(dim(m)[1]/dim(m0)[1] * 100) ## percentage#
# head(m)#
#################################################
## Frequency Summary Statictics#
#################################################
## Experimentel Data: ###
load('~/Dropbox/FelixE/schilling-model/SRC-CORPUS-DATA/src.fstat.RData')#
#fstat1; fstat1.sd; fstat2; fstat2.sd#
#
## DATA#
gaze <- c(293,272,256,234,214)#
FFD <- c(248,233,230,223,208)#
SFD <- c(265, 249, 243, 235, 216)#
SKIP <- c(.10, .13, .22, .55, .67)#
FIX1 <- c(.68, .70, .68, .44, .32)#
FIX2 <- c(.20, .16, .10, .02, .01)#
#
fstat.d <- c(gaze, FFD, SFD, SKIP, FIX1, FIX2)#
#
## SDs from my calculation#
sds <- c(140, 122, 123, 111, 111,#
	96, 93, 98, 105, 103,#
	98, 93, 95, 107, 103,#
	0.32, 0.35, 0.41, 0.50, 0.46,#
	0.48, 0.47, 0.47, 0.49, 0.46,#
	0.43, 0.39, 0.30, 0.14, 0.10)#
## SDs Reichle et al.#
sds.r <- c(38.76, 44.81, 40.29, 59.61, 71.11,#
	26.34, 31.65, 31.31, 49.21, 64.75,#
	26.34, 31.65, 31.31, 49.21, 64.75,		## fake#
	0.3000, 0.3363, 0.4142, 0.4975, 0.4702,#
	0.4665, 0.4583, 0.4665, 0.4964, 0.4665,#
	0.43, 0.39, 0.30, 0.14, 0.10#
	)
Model: ###
# head(m)#
m.m1 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","FPRT","FFD","SFD"),#
	variable="Measure", na.rm = T)#
# head(m.m1) # summary(m.m1) # dim(m.m1) # str(m.m1)#
fstat1.m <- data.frame(round(cast(subset(m.m1,value!=0), freq.class ~ Measure, mean)))#
fstat1.m#
m.m2 <- melt(m,#
	id=c("sn","roi","freq.class"),#
	measure=c("frequency","skipped","onefix","twofix"),#
	variable="Measure", na.rm = T)#
# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
fstat2.m$frequency <- round(fstat2.m$frequency)#
fstat2.m#
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skipped, fstat2.m$onefix, fstat2.m$twofix)
fstat.m
fstat.cor <- NULL#
for (i in c(1,6,11,16,21,26)) {#
	fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
fstat.cor
fstat.cor.mean <- mean(fstat.cor)
fstat.cor.mean
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds.r)^2))
fstat.rmsd.mean
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds)^2))
fstat.rmsd.mean
fstat.rmsd.mean <- sqrt(mean(((fstat.d-fstat.m)/sds.r)^2))
source("../scripts/2-f-statistics-SC.R")
round(fstat.cor.mean, digits=2)
round(fstat.rmsd.mean, digits=3)
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")
setwd("../model-psc/")
load("m.RData")
m1 <- exclude.regressions(m)
load("~/Dropbox/FelixE/PSC-Model/PSC-CORPUS-DATA/psc.fstat.RData")#
	fstat1#
	fstat2
library(reshape) # for aggregating#
library(plyr)
fstat.d <- c(fstat1$FPRT, fstat1$FFD, fstat1$SFD, fstat2$skip, fstat2$onefix, fstat2$refix)#
	fstat.sds.d <- c(fstat1.sd$FPRT, fstat1.sd$FFD, fstat1.sd$SFD, fstat2.sd$skip, fstat2.sd$onefix, fstat2.sd$refix)
fstat.d
fstat.sds.d
Model: ###
	# head(m)#
	m.m1 <- melt(m, id = c("sn", "roi", "freq.class"), measure = c("frequency", #
		"FPRT", "FFD", "SFD"), variable = "Measure", na.rm = T)#
	# head(m.m1) # summary(m.m1) # dim(m.m1) # str(m.m1)#
	fstat1.m <- data.frame(round(cast(subset(m.m1, value != 0), freq.class ~ #
		Measure, mean)))#
	fstat1.m#
#
	m.m2 <- melt(m, id = c("sn", "roi", "freq.class"), measure = c("frequency", #
		"skip", "onefix", "refix"), variable = "Measure", na.rm = T)#
	# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
	fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean), digits = 2))#
	fstat2.m$frequency <- round(fstat2.m$frequency)#
	fstat2.m#
#
	fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix)
fstat.m
fstat.cor <- NULL#
	for (i in c(1,6,11,16,21,26)) {#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor#
	fstat.cor.mean <- mean(fstat.cor)
fstat.cor.mean <- mean(fstat.cor)
fstat.cor.mean
fstat.rmsd <- sqrt(mean(((fstat.d-fstat.m)/fstat.sds.d)^2))
fstat.rmsd
pscore <- mean(1 * fstat.rmsd + (1-mean(c(fstat1.cor, fstat2.cor))))
pscore <- mean(1 * fstat.rmsd + (1-fstat.cor.mean)))
pscore <- mean(1 * fstat.rmsd + (1-fstat.cor.mean))
pscore
fit <- c(fstat.cor.mean, fstat.rmsd.mean)
pscore <- mean(1 * fstat.rmsd + (1-fstat.cor.mean))
pscore
fit <- c(fstat.cor.mean, fstat.rmsd)
fit
source("2-f-statistics.R")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")
m1 <- exclude.regressions(m)
load("m.RData")
m1 <- exclude.regressions(m)
(fstat1 <- freq.stat.early(m1))
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
m1 <- exclude.regressions(m)
(fstat1 <- freq.stat.early(m1))
save(m1,params,fstat1,regtrials, file="m1.RData")
plot.freq.early("fstat.RData")#
title(main=paste("cor:",round(mean(fstat1[1:2]),digits=2)," rmsd:",round(mean(fstat1[3:4]),digits=3), sep=" "), cex=0.5)
m1 <- exclude.regressions(m)
(fstat1 <- freq.stat.early(m1))
plot.freq.early("fstat.RData")
source("2-f-statistics.R")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
m1 <- exclude.regressions(m)
(fstat1 <- freq.stat.early(m1))
save(m1,params,fstat1,regtrials, file="m1.RData")
plot.freq.early("fstat.RData")
par(mfrow=c(1,2))
plot.freq.early("fstat.RData")
fstat1.m
load('~/Dropbox/FelixE/schilling-model/SRC-CORPUS-DATA/src.fstat.RData')
fstat1
fstat1 <- data.frame(freq.class=c(1:5), frequency=0, FPRT=gaze,FFD=FFD,SFD=SF)
gaze <- c(293,272,256,234,214)#
FFD <- c(248,233,230,223,208)#
SFD <- c(265, 249, 243, 235, 216)#
SKIP <- c(.10, .13, .22, .55, .67)#
FIX1 <- c(.68, .70, .68, .44, .32)#
FIX2 <- c(.20, .16, .10, .02, .01)
fstat1 <- data.frame(freq.class=c(1:5), frequency=0, FPRT=gaze,FFD=FFD,SFD=SF)
fstat1 <- data.frame(freq.class=c(1:5), frequency=0, FPRT=gaze,FFD=FFD,SFD=SFD)
fstat1
fstat2
fstat2 <- data.frame(freq.class=c(1:5), frequency=0, skipped=SKIP,onefix=FIX1,twofix=FIX2)
f
fstat2
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
load("~/Dropbox/FelixE/PSC-Model/PSC-CORPUS-DATA/psc.fstat.alldata.RData")#
	fstat1#
	fstat2#
	fstat.d <- c(fstat1$FPRT, fstat1$FFD, fstat1$SFD, fstat1$RPD, fstat1$TFT, fstat1$RRT, fstat2$skip, fstat2$onefix, fstat2$refix, fstat2$fp_reg, fstat2$reread)#
	fstat.sds.d <- c(fstat1.sd$FPRT, fstat1.sd$FFD, fstat1.sd$SFD, fstat1.sd$RPD, fstat1.sd$TFT, fstat1.sd$RRT, fstat2.sd$skip, fstat2.sd$onefix, fstat2.sd$refix, fstat2.sd$fp_reg, fstat2.sd$reread)
m.m1 <- melt(m,#
		id=c("sn","roi","freq.class"),#
		measure=c("frequency","FPRT","FFD","SFD", "RPD", "TFT", "RRT"),#
		variable="Measure", na.rm = T)#
	# head(m.m1) # summary(m.m1) # dim(m.m1) # str(m.m1)#
	fstat1.m <- data.frame(round(cast(subset(m.m1,value!=0), freq.class ~ Measure, mean)))	#
	if(dim(fstat1.m)[2]==7) fstat1.m$RRT <- 0#
	fstat1.m[, 3:8] <- round(fstat1.m[, 3:8])#
	fstat1.m[, 2] <- round(fstat1.m[, 2], digits = 2)#
	fstat1.m
m.m2 <- melt(m,#
		id=c("sn","roi","freq.class"),#
		measure=c("frequency","skip","onefix","refix", "fp_reg", "reread"),#
		variable="Measure", na.rm = T)#
	# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
	fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
	fstat2.m$frequency <- round(fstat2.m$frequency)#
	fstat2.m
fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat1.m$RPD, fstat1.m$TFT, fstat1.m$RRT, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix, fstat2.m$fp_reg, fstat2.m$reread)
fstat.cor <- NULL#
	for (i in c(1,6,11,16,21,26)) {#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor#
	fstat.cor.mean <- mean(fstat.cor)
fstat.cor
fstat.cor.mean <- mean(fstat.cor)
fstat.cor.mean
(fstat.cor.mean <- mean(fstat.cor, na.rm=T))
fstat.cor
fstat.d
fstat2.m
fstat.m
fstat.cor <- NULL#
	for (i in c(1,6,11,16,21,26)) {#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor
fstat.cor <- NULL#
	for (i in c(1,6,11,16,21,26,31,36,41,46,51)) {#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor#
	(fstat.cor.mean <- mean(fstat.cor, na.rm=T))
fstat.cor[is.na(fstat.cor)] <- 0
fstat.cor
(fstat.cor.mean <- mean(fstat.cor, na.rm=T))
fstat.rmsd <- sqrt(mean(((fstat.d-fstat.m)/fstat.sds.d)^2, na.rm=T))
fstat.rmsd
pscore <- mean(1 * fstat.rmsd + (1-mean(c(fstat1.cor, fstat2.cor))))
pscore <- mean(1 * fstat.rmsd + (1-fstat.cor.mean))
pscore
round(fstat.cor.mean, digits=2)#
	round(fstat.rmsd, digits=3)#
	round(pscore,digits=3)
fit <- rbind(fstat.cor, rep(fstat.rmsd,11))
fit
colnames(fit) <- c("FPRT","FFD","SFD","RPD","TFT","RRT", "skip","onefix","refix","fp_reg","reread")#
	rownames(fit) <- c("cor","rmsd")
fit
fstat.m
((fstat.d-fstat.m)/fstat.sds.d)^2
save(fstat1, fstat2, fstat1.m, fstat2.m, fstat.rmsd, fstat.cor, fstat.cor.mean, file="fstat.alldata.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
(fstat <- freq.stat.all(m))
fstat.rmsd
mean(fstat["rmsd",])
(params <- extract.params())
(regtrials <- reg.trials(m))
save(m,params,fstat,regtrials, file="m.RData")
m1 <- exclude.regressions(m)#
(fstat1 <- freq.stat.early(m1))#
save(m1,params,fstat1,regtrials, file="m1.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
load("~/Dropbox/FelixE/PSC-Model/PSC-CORPUS-DATA/psc.fstat.alldata.RData")#
	fstat1#
	fstat2#
	fstat.d <- c(fstat1$FPRT, fstat1$FFD, fstat1$SFD, fstat1$RPD, fstat1$TFT, fstat1$RRT, fstat2$skip, fstat2$onefix, fstat2$refix, fstat2$fp_reg, fstat2$reread)#
	fstat.sds.d <- c(fstat1.sd$FPRT, fstat1.sd$FFD, fstat1.sd$SFD, fstat1.sd$RPD, fstat1.sd$TFT, fstat1.sd$RRT, fstat2.sd$skip, fstat2.sd$onefix, fstat2.sd$refix, fstat2.sd$fp_reg, fstat2.sd$reread)#
	## Model: ###
	# head(m)#
	m.m1 <- melt(m,#
		id=c("sn","roi","freq.class"),#
		measure=c("frequency","FPRT","FFD","SFD", "RPD", "TFT", "RRT"),#
		variable="Measure", na.rm = T)#
	# head(m.m1) # summary(m.m1) # dim(m.m1) # str(m.m1)#
	fstat1.m <- data.frame(round(cast(subset(m.m1,value!=0), freq.class ~ Measure, mean)))	#
	if(dim(fstat1.m)[2]==7) fstat1.m$RRT <- 0#
	fstat1.m[, 3:8] <- round(fstat1.m[, 3:8])#
	fstat1.m[, 2] <- round(fstat1.m[, 2], digits = 2)#
	fstat1.m#
	m.m2 <- melt(m,#
		id=c("sn","roi","freq.class"),#
		measure=c("frequency","skip","onefix","refix", "fp_reg", "reread"),#
		variable="Measure", na.rm = T)#
	# head(m.m2) # summary(m.m2) # dim(m.m2) # str(m.m2)#
	fstat2.m <- data.frame(round(cast(m.m2, freq.class ~ Measure, mean),digits=2))#
	fstat2.m$frequency <- round(fstat2.m$frequency)#
	fstat2.m#
#
	fstat.m <- c(fstat1.m$FPRT, fstat1.m$FFD, fstat1.m$SFD, fstat1.m$RPD, fstat1.m$TFT, fstat1.m$RRT, fstat2.m$skip, fstat2.m$onefix, fstat2.m$refix, fstat2.m$fp_reg, fstat2.m$reread)
fstat.cor <- NULL#
	for (i in c(1,6,11,16,21,26,31,36,41,46,51)) {#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor#
	fstat.cor[is.na(fstat.cor)] <- 0#
	(fstat.cor.mean <- mean(fstat.cor, na.rm=T))
fstat.cor
fstat.m
fstat1.m
for (i in c(1,6,11,16,21,31,36,41,46,51)) {  ## without RRTs#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor#
	fstat.cor[is.na(fstat.cor)] <- 0#
	(fstat.cor.mean <- mean(fstat.cor, na.rm=T))
for (i in c(1,6,11,16,21,26,31,36,41,46,51)) {#
	#for (i in c(1,6,11,16,21,31,36,41,46,51)) {  ## without RRTs#
		fstat.cor <- c(fstat.cor, cor(fstat.d[i:(i+4)], fstat.m[i:(i+4)], method="pearson"))}#
	fstat.cor#
	fstat.cor[is.na(fstat.cor)] <- 0#
	(fstat.cor.mean <- mean(fstat.cor, na.rm=T))
fstat.d
fstat.d[-c(1:2)]
fstat.d
fstat.d[-c(26:30)]  # no RRT
fstat.m1 <- fstat.m[-c(26:30)]  # no RRT
fstat.m
fstat.m1
fstat.sds.d1 <- fstat.sds.d[-c(26:30)]  # no RRT
fstat.rmsd <- sqrt(mean(((fstat.d1-fstat.m1)/fstat.sds.d)^2, na.rm=T))
fstat.d1 <- fstat.d[-c(26:30)]  # no RRT#
	fstat.m1 <- fstat.m[-c(26:30)]  # no RRT#
	fstat.sds.d1 <- fstat.sds.d[-c(26:30)]  # no RRT
fstat.rmsd <- sqrt(mean(((fstat.d1-fstat.m1)/fstat.sds.d1)^2, na.rm=T))
fstat.rmsd
fstat.rmsd <- mean(c(sqrt(mean(((fstat.d1-fstat.m1)/fstat.sds.d1)^2, na.rm=T)),1))
fstat.rmsd
fstat.m[26:30] <- 0  # no RRT
fstat.rmsd <- sqrt(mean(((fstat.d1-fstat.m1)/fstat.sds.d1)^2, na.rm=T))
fstat.rmsd
fstat.rmsd <- sqrt(mean(((fstat.d-fstat.m)/fstat.sds.d)^2, na.rm=T))
fstat.rmsd
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")
(fstat <- freq.stat.all(m))
(params <- extract.params())
(regtrials <- reg.trials(m))
save(m,params,fstat,regtrials, file="m.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-src-nsp_3-4-135/")#
file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")#
source("../scripts/2-f-statistics-SC.R")
round(fstat.cor.mean, digits=2)
round(fstat.rmsd.mean, digits=3)
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc-s/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")#
(fstat <- freq.stat.all(m))#
#mean(fstat["rmsd",])#
#(gfit <- general.fit(m))#
(params <- extract.params())#
(regtrials <- reg.trials(m))
save(m,params,fstat,regtrials, file="m.RData")
m1 <- exclude.regressions(m)#
(fstat1 <- freq.stat.early(m1))
save(m1,params,fstat1,regtrials, file="m1.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc-r/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")#
(fstat <- freq.stat.all(m))#
#mean(fstat["rmsd",])#
#(gfit <- general.fit(m))#
(params <- extract.params())#
(regtrials <- reg.trials(m))
save(m,params,fstat,regtrials, file="m.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc-sh/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")#
(fstat <- freq.stat.all(m))#
#mean(fstat["rmsd",])#
#(gfit <- general.fit(m))#
(params <- extract.params())#
(regtrials <- reg.trials(m))#
save(m,params,fstat,regtrials, file="m.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
#setwd("../model-psc-sh/")#
setwd("../model-psc-sr/")#
#setwd("../model-src-nsp_3-4-135/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")#
(fstat <- freq.stat.all(m))#
#mean(fstat["rmsd",])#
#(gfit <- general.fit(m))#
(params <- extract.params())#
(regtrials <- reg.trials(m))#
save(m,params,fstat,regtrials, file="m.RData")
remove(list=ls())#
#flush.console()#
#
setwd("~/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts")#
#
source("functions.R")#
source("0-preprocess-fixations.R")#
source("1-generalfit.R")#
source("2-f-statistics.R")#
source("3-spu-statistics.R")#
source("4-rv100-statistics.R")#
#getwd()#
#model <- "model-psc-s"#
#file <- paste(getwd(),"..", model, "fixations.txt", sep="/")#
#mfile <- paste(getwd(),"..", model, "m.RData", sep="/")#
setwd("../model-psc-shr/")#
#file <- "fixations.txt"#
#
#m <- preprocess.fixations(file)#
load("m.RData")#
(fstat <- freq.stat.all(m))#
#mean(fstat["rmsd",])#
#(gfit <- general.fit(m))#
(params <- extract.params())#
(regtrials <- reg.trials(m))#
save(m,params,fstat,regtrials, file="m.RData")
load("/Users/felx/Dropbox/Workspace/TopiCS/post-review-revision/data/scripts/lms.RData")
head(m)
summray(m$FFD)
summary(m$FFD)
summary(-1000/m$FFD)
summary(-1000/subset(m$FFD,m$FFD!=0))
scale(-1000/subset(m$FFD,m$FFD!=0))
summary(m$FFD)
summary(-1000/subset(m$FFD,m$FFD!=0))
summary(scale(subset(m$FFD,m$FFD!=0)))
head(scale(subset(m$FFD,m$FFD!=0)))
summary(scale(subset(m$FFD,m$FFD!=0)))
summary(scale(subset(m$FFD,m$FFD!=0), s=F))
summary(-1000/subset(m$FFD,m$FFD!=0))
summary(scale(subset(m$FFD,m$FFD!=0))-9.81)
?scale
