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readSMISamples.R
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readSMISamples.R
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#memory.limit(2047)
#----
#INPUT
#!никакой кириллицы в пути
workPath<-"e://projects//grants//RSCF2018//dataset//zhegallo//data-et//"
participantIds <- c(
"1_ex-CSB_2015_06_27_1209",
"01_ex-CSB_2015_07_02_1208",
"2_ex-CSB_2015_06_27_1237",
"02_ex-CSB_2015_07_02_1232",
"3_ex-CSB_2015_06_27_1306",
"03_ex-CSB_2015_07_02_1258",
"4_ex-CSB_2015_06_27_1336",
"5_ex-CSB_2015_06_27_1406",
"05_ex-CSB_2015_07_02_1323",
"06_ex-CSB_2015_07_02_1346",
"7_ex-CSB_2015_06_27_1429",
"07_ex-CSB_2015_07_02_1415",
"8_ex-CSB_2015_06_27_1454",
"08_ex-CSB_2015_07_02_1439",
"9_ex-CSB_2015_06_27_1522",
"09_ex-CSB_2015_07_02_1501",
"10_ex-CSB_2015_06_27_1547",
"10_ex-CSB_2015_07_02_1521",
"11_ex-CSB_2015_06_27_1608",
"11_ex-CSB_2015_07_02_1543",
"12_ex-CSB_2015_06_27_1631",
"12_ex-CSB_2015_07_02_1604",
"13_ex-CSB_2015_06_27_1652",
"13_ex-CSB_2015_07_02_1627",
"14_ex-CSB_2015_06_27_1713",
"14_ex-CSB_2015_07_02_1647",
"15_ex-CSB_2015_06_27_1734",
"15_ex-CSB_2015_07_02_1709",
"16_ex-CSB_2015_06_27_1834",
"16_ex-CSB_2015_07_02_1733",
"18_ex-CSB_2015_07_02_1754",
"19_ex-CSB_2015_07_02_1829",
"20_ex-CSB_2015_07_02_1849",
"21_ex-CSB_2015_07_02_1914",
"22_ex-CSB_2015_07_02_1935"
)
samplesFiles <- paste(workPath, paste0(participantIds," Samples.txt"), sep="/")
rdataFiles <- gsub(".txt", ".RData", samplesFiles)
#----
require(geosphere)
require(SphericalCubature)
#расчет угла (между сэмплами) по теореме косинусов
getSeparation <- function(x1, y1, x2, y2, z, mode) {
if (mode=='fromCartesian') {
cartesian1 <- rbind(x1,y1,z)
cartesian2 <- rbind(x2,y2,z)
polar1 <- rect2polar(cartesian1)
polar2 <- rect2polar(cartesian2)
} else if (mode=='fromPolar') {
polar1=list(phi=(rbind(x1,y1)+90)/180*pi)
polar2=list(phi=(rbind(x2,y2)+90)/180*pi)
}
sphericalLength <- distCosine(p1=(t(polar1$phi[1:2,])/pi*180)-90, p2=(t(polar2$phi[1:2,])/pi*180)-90, r=z)
circumcision <- 2*pi*z
separation <- (sphericalLength/circumcision) * 360
return(separation)
}
#----
#metadata
frameRate <- 120
headDistanceMm <- 635
screenWidthPx <- 1280
screenHeightPx <- 1024
screenWidthMm <- 376
screenHeightMm <- 301
screenWidthDeg <- getSeparation(-screenWidthMm/2, 0, screenWidthMm/2, 0, headDistanceMm, 'fromCartesian')
screenHeightDeg <- getSeparation(-screenHeightMm/2, 0, screenHeightMm/2, 0, headDistanceMm, 'fromCartesian')
screenHResMm <- screenWidthMm/screenWidthPx
screenVResMm <- screenHeightMm/screenHeightPx
fixDotPattern <- "Fix"
stimPattern <- ".avi"
#----
#data reader function
require(data.table)
require(signal)
readSamples <- function() {
samplesHeader <- readLines(samplesFile,50)
samplesFileSkip<-grep("\\d+\\t[SMP|MSG]",samplesHeader)[1]-2
samplesColclasses<-strsplit(samplesHeader[samplesFileSkip+1],"\t")[[1]]
samplesColclasses<-gsub("Trial|.*Raw.*|.* CR.*|.*Dia.*|Timing|.*Valid.*|.*Plane|Pupil Confidence|.*EPOS.*|.*GVEC.*|Aux.*", "NULL",samplesColclasses)
samplesColclasses<-gsub("Time|.*POR.*", "numeric",samplesColclasses)
samplesColclasses<-gsub("Latency|Trigger", "integer",samplesColclasses)
samplesColclasses<-gsub("Type|Frame", "character",samplesColclasses)
samplesColclasses[4]<-"character"
zeroTime<<-as.numeric(strsplit(samplesHeader[samplesFileSkip+2],"\t")[[1]][1])
#
print("Reading samples...")
samplesData <- read.delim(samplesFile,skip=samplesFileSkip,row.names=NULL, colClasses=samplesColclasses)
samplesData <- data.table(samplesData)
setnames(samplesData,gsub("\\.","",colnames(samplesData)))
setkey(samplesData,"Type")
samples<<-samplesData[J("SMP")]
samples[,Type:=NULL]
samples[,2:=as.numeric(samples[,2,with=FALSE][[1]])]
samples[,Time:=(Time-zeroTime)/10^6]
#
messages<<-samplesData[J("MSG")]
messages[,Type:=NULL]
messages[,3:ncol(messages) := NULL]
setnames(messages,c("Time","Text"))
messages[,Text:=gsub("# Message: ","",Text)]
messages[,Time:=(Time-zeroTime)/10^6]
messages<<-as.data.frame(messages)
#----
#
trialMessages<-messages[grep(fixDotPattern,messages[,"Text"]),]
smpIndices<<-numeric()
print("Indexing trials...")
for (msgInt in seq_along(trialMessages[,"Time"])){
time<-trialMessages[msgInt,"Time"]
ind<-last(samples[Time %between% c(0,time),which=TRUE])
smpIndices[msgInt]<<-ind
}
smpIndices<<-c(smpIndices,nrow(samples))
#----
#читаем только 1 канал, если они одинаковые (RED-m-HP)
for (chLetter in c('L','R')) {
if (length(grep(paste0(chLetter,"PORXpx"),colnames(samples)))) {
channel<<-chLetter
samples[,paste0(channel,"PORXMm") := (samples[,paste0(channel,"PORXpx"),with=FALSE]-screenWidthPx/2)*screenHResMm]
samples[,paste0(channel,"PORYMm") := -(samples[,paste0(channel,"PORYpx"),with=FALSE]-screenHeightPx/2)*screenVResMm]
xs <- as.data.frame(samples[,paste0(channel,"PORXMm"),with=FALSE])[,1]
ys <- as.data.frame(samples[,paste0(channel,"PORYMm"),with=FALSE])[,1]
samples[,paste0(channel,"PORXDeg") := sign(xs) * getSeparation(xs, 0, 0, 0, headDistanceMm, 'fromCartesian') ]
samples[,paste0(channel,"PORYDeg") := sign(ys) * getSeparation(0, ys, 0, 0, headDistanceMm, 'fromCartesian') ]
#
lastIndex<-1
print(paste0('Smoothing ', channel, '...'))
#using SPLINE, SGOLAY
for (smpInt in seq_along(smpIndices)){
index<-smpIndices[smpInt]
samples[lastIndex:index, paste0(channel,"SplinePORXpx") := smooth.spline(samples[lastIndex:index, paste0(channel,"PORXpx"),with=FALSE], spar=.65,all.knots=TRUE,keep.data=FALSE)$y]
samples[lastIndex:index, paste0(channel,"SplinePORYpx") := smooth.spline(samples[lastIndex:index, paste0(channel,"PORYpx"),with=FALSE], spar=.65,all.knots=TRUE,keep.data=FALSE)$y]
#samples[lastIndex:index, paste0(channel,"SgolayPORXpx") := sgolayfilt(samples[lastIndex:index, paste0(channel,"PORXpx"),with=FALSE][[1]],2,15)]
#samples[lastIndex:index, paste0(channel,"SgolayPORYpx") := sgolayfilt(samples[lastIndex:index, paste0(channel,"PORYpx"),with=FALSE][[1]],2,15)]
lastIndex <- index+1
}
samples[,paste0(channel,"SplinePORXMm") := (samples[,paste0(channel,"SplinePORXpx"),with=FALSE]-screenWidthPx/2)*screenHResMm]
samples[,paste0(channel,"SplinePORYMm") := -(samples[,paste0(channel,"SplinePORYpx"),with=FALSE]-screenHeightPx/2)*screenVResMm]
xs <- as.data.frame(samples[,paste0(channel,"SplinePORXMm"),with=FALSE])[,1]
ys <- as.data.frame(samples[,paste0(channel,"SplinePORYMm"),with=FALSE])[,1]
samples[,paste0(channel,"SplinePORXDeg") := sign(xs) * getSeparation(xs, 0, 0, 0, headDistanceMm, 'fromCartesian') ]
samples[,paste0(channel,"SplinePORYDeg") := sign(ys) * getSeparation(0, ys, 0, 0, headDistanceMm, 'fromCartesian') ]
#
#samples[,paste0(channel,"SgolayPORXMm"):= (samples[,paste0(channel,"SgolayPORXpx"),with=FALSE]-screenWidthPx/2)*screenHResMm]
#samples[,paste0(channel,"SgolayPORYMm"):= -(samples[,paste0(channel,"SgolayPORYpx"),with=FALSE]-screenHeightPx/2)*screenVResMm]
#samples[,paste0(channel,"SgolayPORXDeg"):=atan(samples[,paste0(channel,"SgolayPORXMm"),with=FALSE]/headDistanceMm)/pi*180]
#samples[,paste0(channel,"SgolayPORYDeg"):=atan(samples[,paste0(channel,"SgolayPORYMm"),with=FALSE]/headDistanceMm)/pi*180]
#----
#VELOCITY
#2018.12.05 посчитаем скорость от несглаженного сигнала
veloTmp <- data.table(tmp=rep(0, nrow(samples)))
veloTmp[,separation := c(1, getSeparation(as.data.frame(samples[-1,paste0(channel,"PORXDeg"),with=FALSE])[,1], as.data.frame(samples[-1,paste0(channel,"PORYDeg"),with=FALSE])[,1], as.data.frame(samples[-nrow(samples),paste0(channel,"PORXDeg"),with=FALSE])[,1], as.data.frame(samples[-nrow(samples),paste0(channel,"PORYDeg"),with=FALSE])[,1], headDistanceMm, 'fromPolar')) ]
veloTmp[,timelag := c(1, diff(samples[,Time]))]
samples[,paste0(channel,"Velocity") := veloTmp[,separation] / veloTmp[,timelag] ]
#от сглаженного
veloTmp <- data.table(tmp=rep(0, nrow(samples)))
veloTmp[,separation := c(1, getSeparation(as.data.frame(samples[-1,paste0(channel,"SplinePORXDeg"),with=FALSE])[,1], as.data.frame(samples[-1,paste0(channel,"SplinePORYDeg"),with=FALSE])[,1], as.data.frame(samples[-nrow(samples),paste0(channel,"SplinePORXDeg"),with=FALSE])[,1], as.data.frame(samples[-nrow(samples),paste0(channel,"SplinePORYDeg"),with=FALSE])[,1], headDistanceMm, 'fromPolar')) ]
veloTmp[,timelag := c(1, diff(samples[,Time]))]
samples[,paste0(channel,"SplineVelocity") := veloTmp[,separation] / veloTmp[,timelag] ]
#
#veloTmp <- data.table(tmp=rep(0, nrow(samples)))
#veloTmp[,separation := c(1, getSeparation(as.data.frame(samples[-1,paste0(channel,"SgolayPORXDeg"),with=FALSE])[,1], as.data.frame(samples[-1,paste0(channel,"SgolayPORYDeg"),with=FALSE])[,1], as.data.frame(samples[-nrow(samples),paste0(channel,"SgolayPORXDeg"),with=FALSE])[,1], as.data.frame(samples[-nrow(samples),paste0(channel,"SgolayPORYDeg"),with=FALSE])[,1], headDistanceMm, 'fromPolar')) ]
#veloTmp[,timelag := c(1, diff(samples[,Time]))]
#samples[,paste0(channel,"SgolayVelocity") := veloTmp[,separation] / veloTmp[,timelag] ]
}
}
samples[,c("LRawXpx","Latency","Frame"):=NULL]
}
#----
#PLOTTING functions
spatialPlot <- function() {
plotSamplesSet <<- samples[Time %between% c(plotStartTime, plotStartTime+plotWidthS)]
plotSamplesSet <<- as.data.frame(plotSamplesSet)
#
plot(0, type="n",
main=plotStartTime+plotWidthS, xlab="Gaze X (°)",ylab="Gaze Y (°)",
xlim=c(-screenWidthDeg/2,screenWidthDeg/2), ylim=c(-screenHeightDeg/2,screenHeightDeg/2))
grid()
abline(h=0, v=0, lty='dashed', col='lightgrey')
#lines(plotSamplesSet[,paste0(channel,"SmoothPORXDeg")],plotSamplesSet[,paste0(channel,"SmoothPORYDeg")],lwd=lineWidth*2,col=plotCol)
#
#уходы в угол экрана прорисовываются штрихом
xNans <<- plotSamplesSet[,paste0(channel,"PORXDeg")] == -screenWidthDeg/2
xNansNum <<- unique(c(which(xNans)-1, which(xNans)+1))
yNans <<- plotSamplesSet[,paste0(channel,"PORYDeg")] == screenHeightDeg/2
yNansNum <<- unique(c(which(yNans)-1, which(yNans)+1))
allNansNum <<- unique(c(xNansNum, yNansNum))
lines(plotSamplesSet[allNansNum,paste0(channel,"PORXDeg")], plotSamplesSet[allNansNum,paste0(channel,"PORYDeg")], lwd=lineWidth,lty='dotted',col='chocolate')
#
#plotSamplesSetNanned <<- plotSamplesSet
if (length(xNans)) {
plotSamplesSet[xNans, c(paste0(channel,"PORXDeg"), paste0(channel,"Velocity"), paste0(channel,"SplineVelocity"))] <<- NaN
}
if (length(yNans)) {
plotSamplesSet[yNans, c(paste0(channel,"PORYDeg"), paste0(channel,"Velocity"), paste0(channel,"SplineVelocity"))] <<- NaN
}
#validSmpL <<- plotSamplesSet[,paste0(channel,"PORXDeg")]!=-screenWidthDeg/2 & plotSamplesSet[,paste0(channel,"PORYDeg")]!=screenHeightDeg/2
#plotSamplesSet <<- plotSamplesSet[validSmpL,]
lines(plotSamplesSet[,paste0(channel,"SplinePORXDeg")], plotSamplesSet[,paste0(channel,"SplinePORYDeg")], lwd=lineWidth,col='yellow')
lines(plotSamplesSet[,paste0(channel,"PORXDeg")], plotSamplesSet[,paste0(channel,"PORYDeg")], lwd=lineWidth*2,col='chocolate')
points(tail(plotSamplesSet[,paste0(channel,"PORXDeg")],1), tail(plotSamplesSet[,paste0(channel,"PORYDeg")],1), pch=3)
#points(tail(plotSamplesSet[,paste0(channel,"SmoothPORXDeg")],1),tail(plotSamplesSet[,paste0(channel,"SmoothPORYDeg")],1),pch=3)
plotEvents("messages", "spatial")
}
plotSamples <- function() {
plot(0,type="n",
xlab="Time (s)",ylab="Gaze (°)",
xlim=c(plotStartTime,plotStartTime+plotWidthS), ylim=c(-screenWidthDeg/2,screenWidthDeg/2))
grid()
abline(h=0, lty='dashed', col='lightgrey')
abline(h=c(-screenWidthDeg/2,screenWidthDeg/2), lty='dashed', col='pink',lwd=lineWidth/2)
abline(h=c(-screenHeightDeg/2,screenHeightDeg/2), lty='dashed', col='skyblue',lwd=lineWidth/2)
plotEvents("messages", "full")
lines(plotSamplesSet[,"Time"],plotSamplesSet[,paste0(channel,"SplinePORYDeg")],lwd=lineWidth,col="blue")
lines(plotSamplesSet[,"Time"],plotSamplesSet[,paste0(channel,"SplinePORXDeg")],lwd=lineWidth,col="red")
#
#lines(plotSamplesSet[yNansNum,"Time"], plotSamplesSet[yNansNum,paste0(channel,"PORYDeg")], lwd=lineWidth,lty='dotted',col='skyblue')
#lines(plotSamplesSet[xNansNum,"Time"], plotSamplesSet[xNansNum,paste0(channel,"PORXDeg")], lwd=lineWidth,lty='dotted',col='pink')
points(plotSamplesSet[,"Time"], plotSamplesSet[,paste0(channel,"PORYDeg")],lwd=lineWidth*2,col="skyblue")
points(plotSamplesSet[,"Time"], plotSamplesSet[,paste0(channel,"PORXDeg")],lwd=lineWidth*2,col="pink")
}
plotVelocity <- function() {
plot(0,type="n",
xlab="Time (s)",ylab="Velocity (°/s)",
xlim=c(plotStartTime,plotStartTime+plotWidthS),ylim=c(0,1000))
grid()
#empirical saccade median and maximum limits
abline(h=400, lty='dashed', col='lightgrey')
abline(h=750, lty='dashed', col='grey')
plotEvents("messages","full")
#lines(plotSamplesSet[allNansNum,"Time"], plotSamplesSet[allNansNum,paste0(channel,"Velocity")], lwd=lineWidth,lty='dotted',col='grey')
#lines(plotSamplesSet[allNansNum,"Time"], plotSamplesSet[allNansNum,paste0(channel,"SplineVelocity")], lwd=lineWidth,lty='dotted',col='peachpuff2')
#lines(plotSamplesSet[allNansNum,"Time"], plotSamplesSet[allNansNum,paste0(channel,"SgolayVelocity")], lwd=lineWidth,lty='dotted',col='yellowgreen')
#
lines(plotSamplesSet[,"Time"], plotSamplesSet[,paste0(channel,"Velocity")],col='grey',lwd=lineWidth*4)
lines(plotSamplesSet[,"Time"], plotSamplesSet[,paste0(channel,"SplineVelocity")],col='peachpuff2',lwd=lineWidth*2)
#lines(plotSamplesSet[,"Time"], plotSamplesSet[,paste0(channel,"SgolayVelocity")],col='yellowgreen',lwd=lineWidth*2)
}
plotEvents <- function(type, mode) {
channelEvents<-get(type)
plotEvents <- channelEvents[channelEvents$Time>=plotStartTime & channelEvents$Time<plotStartTime+plotWidthS,]
#
plotEventsLength <- length(plotEvents[,1])
if (plotEventsLength!=0) {
if (type=="messages") {
if (mode=="full") {
abline(v=plotEvents$Time, col="skyblue",lty="dashed",lwd=lineWidth*2)
points(plotEvents$Time, rep(-20,plotEventsLength),col="skyblue",bg="skyblue",pch=2)
} else if (mode=="spatial") {
for (messageInt in 1:plotEventsLength) {
plotMessage <- plotEvents[messageInt,]
messageSample <- plotSamplesSet[tail(which(plotSamplesSet[,"Time"] <= plotMessage[,"Time"]),1),]
points(messageSample[,paste0(channel,"PORXDeg")],messageSample[,paste0(channel,"PORYDeg")], col="skyblue",bg="skyblue",pch=2)
}
}
}
}
}
tempoPlot <- function() {
windows(width=200,height=3, rescale="fixed")
opar<<-par(pty="m",mai=c(.5,.6,.2,.2))
plotSamples()
par(opar)
#dev.copy2pdf(file=paste0(workPath[dirInt],"img/tempo_",plotStartTime,".pdf"),out.type="cairo")
}
imgNum <<- 0
combiPlot <- function(mode='cascade') {
widthPlotted <<- 0
if (mode=='cascade') {
segments <- 5
} else if (mode=='animation') {
segments <- 1
}
while (widthPlotted < cascadeWidthS) {
if (mode=='cascade') {
windows(width=5*segments,height=13,rescale="fixed")
} else if (mode=='animation') {
imgNum <<- imgNum + 1
png(file=paste0(workPath,"img/byFrame_", sprintf('%06d', imgNum),".png"),
width=5*segments,height=13,units='in',res=150,bg="white")
}
opar<<-par(pty="m",mai=c(.5,.6,.2,.2),mfrow=c(3,segments),pin=c(4,3))
for (i in 1:segments) {
opar <<- par(mfg=c(1,i))
spatialPlot()
opar <<- par(mfg=c(2,i))
plotSamples()
opar <<- par(mfg=c(3,i))
plotVelocity()
if (mode=='cascade') {
plotStartTime <<- plotStartTime+plotWidthS
widthPlotted <<- widthPlotted+plotWidthS
} else if (mode=='animation') {
#здесь задается временной шаг каждого кадра анимации
plotStartTime <<- plotStartTime+1/frameRate
widthPlotted <<- widthPlotted+1/frameRate
}
}
par(opar)
#выбор пути для файла
if (mode=='cascade') {
dev.copy2pdf(file=paste0(workPath,"img/combi_",participantIds[dirInt],"_",plotStartTime,".pdf"),out.type="cairo")
}
dev.off()
}
}
#----
#READING data
dirInt <- 15
print(paste0("Record ",dirInt,"/",length(participantIds)))
samplesFile<-samplesFiles[dirInt]
readSamples()
#helper lists
diff(messages[,'Time'])
fixDotMessageInts <- grep(tolower(fixDotPattern),tolower(messages[,"Text"]))
fixDotMessages <- messages[fixDotMessageInts,]
stimMessageInts <- grep(fixDotPattern,messages[,"Text"])+1
stimMessages <- messages[stimMessageInts,]
endMessagesInts <- grep(fixDotPattern,messages[,"Text"])+2
#assuming the experiment was run on a 144 Hz display
fixDurS <- ceiling((stimMessages[,"Time"]-messages[fixDotMessageInts,"Time"]) / (1/144)) * 1/144
stimuliDurS <- ceiling((messages[endMessagesInts,"Time"]-stimMessages[,"Time"]) / (1/144)) * 1/144
#SANITY CHECK routines (optional)
if (all(samples[,"LPORXpx"]==samples[,"RPORXpx"])) {
print("L and R channels EQUIVALENT.")
}
all(stimMessages[,"Time"]>fixDotMessages[,"Time"],na.rm=TRUE)
nrow(fixDotMessages)==length(endMessagesInts)
length(endMessagesInts)==nrow(stimMessages)
#----
#now PLOTTING
require('Cairo')
imgPath<-"e://projects//grants//RSCF2018//dataset//zhegallo//"
dir.create(paste0(workPath,"/img/"))
imgW <- 3.7
imgH <- 6
lineWidth <- 1.0
plotCol <- "black"
plotWidthS<- 50/frameRate
#сколько всего прорисовывать блоков для combiPlot
cascadeWidthS <- 65.0
#----
#channel <- "R"
recordData<-data.frame(fixDotInt=1:nrow(fixDotMessages))
recordData[,"participantId"]<-rep(participantIds[dirInt],nrow(fixDotMessages))
plotData <- recordData
for (plotMessageInt in 1:nrow(plotData)) {
#смотрим участки сразу после появления стимула
plotStartTime <- as.numeric(fixDotMessages[plotMessageInt,"Time"][1])
combiPlot(mode='animation') #cascade, animation
#dev.off()
}