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0_globa_define_activity_subsetl.R
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0_globa_define_activity_subsetl.R
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ac.tac.anal <- function(tacsat, units = "year", storeScheme = storeScheme, analyse.by = "LE_L5MET", identify = "peaks") {
if (!"LE_L5MET" %in% colnames(tacsat))
stop("Provide gear type (as column 'LE_L5MET' and if unknown, provide it as 'MIS'")
if (!analyse.by %in% c("LE_L5MET", "VE_REF"))
warning("Analysing by unknown column variable, please check!")
if (analyse.by %in% colnames(tacsat)) {
if (units == "all") {
yrs <- 0
mths <- 0
wks <- 0
}
if (units == "year") {
yrs <- sort(unique(format(tacsat$SI_DATIM, "%Y")))
mths <- 0
wks <- 0
}
if (units == "month") {
yrs <- sort(unique(format(tacsat$SI_DATIM, "%Y")))
mths <- sort(unique(month(tacsat$SI_DATIM)))
wks <- 0
}
if (units == "week") {
yrs <- sort(unique(format(tacsat$SI_DATIM, "%Y")))
wks <- sort(unique(week(tacsat$SI_DATIM)))
mths <- 0
}
runScheme <- expand.grid(years = yrs, months = mths,
weeks = wks, stringsAsFactors = FALSE)
storeScheme <- expand.grid(years = yrs, months = mths,
weeks = wks, analyse.by = unique(tacsat[, get (analyse.by) ]),
stringsAsFactors = FALSE)
storeScheme$peaks <- NA
storeScheme$fixPeaks <- FALSE
storeScheme$sigma0 <- 0.911
if (identify == "means")
storeScheme$means <- NA
for (iRun in 1:nrow(runScheme)) {
yr <- runScheme[iRun, "years"]
mth <- runScheme[iRun, "months"]
wk <- runScheme[iRun, "weeks"]
if (nrow(runScheme) == 1) {
sTacsat <- tacsat
} else {
if (mth == 0 & wk == 0)
sTacsat <- subset(tacsat, format(tacsat$SI_DATIM, "%Y") == yr)
if (mth == 0 & wk != 0)
sTacsat <- subset(tacsat, format(tacsat$SI_DATIM, "%Y") == yr & week(tacsat$SI_DATIM) == wk)
if (mth != 0 & wk == 0)
sTacsat <- subset(tacsat, format(tacsat$SI_DATIM, "%Y") == yr & month(tacsat$SI_DATIM) == mth)
}
for (iBy in na.omit(unique(sTacsat[, get (analyse.by)]))) {
dat <- subset(sTacsat, sTacsat[, get(analyse.by) ] == iBy)
datmr <- dat
datmr$SI_SP <- -1 * dat$SI_SP
datmr <- rbind(dat, datmr)
xrange <- pmin(20, range(datmr$SI_SP), na.rm = TRUE)
datmr$SI_SP[which(abs(datmr$SI_SP) > 20)] <- NA
hist(datmr$SI_SP, breaks = seq(-20, 20, 0.5),
main = paste(iBy, ifelse(yr > 0, yr, ""),
ifelse(mth > 0, mth, ""),
ifelse(wk > 0, wk, "")), xaxt = "n")
axis(1, at = seq(-20, 20, 1))
# Introduce a delay before calling the callNumberPeak() function
Sys.sleep(1)
# Call the callNumberPeak() function to get user input
pks <- callNumberPeak()
storeScheme[which(storeScheme$years == yr & storeScheme$months == mth & storeScheme$weeks == wk & storeScheme$analyse.by == iBy), "peaks"] <- pks
if (identify == "means") {
valPeaks <- callPeakValue(pks)
if (substr(valPeaks, 1, 1) == " ")
valPeaks <- substr(valPeaks, 2, nchar(valPeaks))
storeScheme[which(storeScheme$years == yr & storeScheme$months == mth & storeScheme$weeks == wk & storeScheme$analyse.by == iBy), "means"] <- valPeaks
}
}
}
} else {
stop("analyse.by statement not found as a column in the specified tacsat dataset")
}
return(storeScheme)
}
act.tac <- function (tacsat, units = "year", analyse.by = "LE_L5MET", storeScheme = NULL,
plot = FALSE, level = "all"){
tacsat = sub_subTacsat |> filter(SI_YEAR == 2023)
require("mixtools")
if (!"SI_DATIM" %in% colnames(tacsat))
tacsat$SI_DATIM <- as.POSIXct(paste(tacsat$SI_DATE, tacsat$SI_TIME, # id datim doesn't exist in eflalo, creates in
sep = " "), tz = "GMT", format = "%d/%m/%Y %H:%M")
if (!analyse.by %in% c("LE_L5MET", "VE_REF"))
stop("Analysing only by level 5 metier or vessel") ## would it be useful to examine speeds at L5 or L6 metier?
tacsat$ID <- 1:nrow(tacsat)
tacsat$SI_STATE <- NA ## creates ID and blank column to receive state
tacsatOrig <- tacsat
idx <- which(is.na(tacsat$SI_SP) == FALSE)
tacsat <- tacsat[idx, ] ## drops rows which do not have a valid speed value
storeScheme$sigma0[which(storeScheme$sigma0 == 0)] <- "d"
if (units == "all") {
yrs <- 0
mths <- 0
wks <- 0
}
if (units == "year") {
yrs <- sort(unique(format(tacsat$SI_DATIM, "%Y")))
mths <- 0
wks <- 0
}
if (units == "month") {
yrs <- sort(unique(format(tacsat$SI_DATIM, "%Y")))
mths <- an(sort(unique(format(tacsat$SI_DATIM, "%m"))))
wks <- 0
}
if (units == "week") {
yrs <- sort(unique(format(tacsat$SI_DATIM, "%Y")))
wks <- an(sort(unique(format(tacsat$SI_DATIM, "%W")))) +
1
mths <- 0
}
runScheme <- expand.grid(years = yrs, months = mths, weeks = wks)
for (iRun in 1:nrow(runScheme)) {
yr <- runScheme[iRun, "years"]
mth <- runScheme[iRun, "months"]
wk <- runScheme[iRun, "weeks"]
if (nrow(runScheme) == 1) {
sTacsat <- tacsat
}
else {
if (mth == 0 & wk == 0)
sTacsat <- subset(tacsat, format(tacsat$SI_DATIM,
"%Y") == yr)
if (mth == 0 & wk != 0)
sTacsat <- subset(tacsat, format(tacsat$SI_DATIM,
"%Y") == yr & (an(format(tacsat$SI_DATIM, "%W")) +
1) == wk)
if (mth != 0 & wk == 0)
sTacsat <- subset(tacsat, format(tacsat$SI_DATIM,
"%Y") == yr & format(tacsat$SI_DATIM, "%m") ==
mth)
}
if (plot == TRUE)
x11()
if ("LE_L5MET" %in% colnames(tacsat) & analyse.by == "LE_L5MET") {
gearList <- names(which((rowSums(table(sTacsat$LE_L5MET,
sTacsat$SI_SP)) - table(sTacsat$LE_L5MET, sTacsat$SI_SP)[,
"0"]) > 40))
tyg <- subset(sTacsat, is.na(LE_L5MET) == FALSE &
LE_L5MET %in% gearList)
tygmr <- tyg
tygmr$SI_SP <- -1 * tygmr$SI_SP
tygmr <- rbind(tyg, tygmr)
tng <- subset(sTacsat, is.na(LE_L5MET) == TRUE | !LE_L5MET %in%
gearList)
tngmr <- tng
tngmr$SI_SP <- -1 * tngmr$SI_SP
tngmr <- rbind(tng, tngmr)
res <- list()
for (iGr in unique(tyg$LE_L5MET)) {
tbl <- table(subset(tygmr, LE_L5MET == iGr)$SI_SP)
spd <- an(names(rev(sort(tbl))[1]))
idx <- which(subset(tygmr, LE_L5MET == iGr)$SI_SP ==
spd)
nxt <- ifelse(names(rev(sort(tbl))[1]) == ac(spd),
ifelse(abs(an(names(rev(sort(tbl))[2]))) ==
abs(spd), names(rev(sort(tbl))[3]), names(rev(sort(tbl))[2])),
names(rev(sort(tbl))[1]))
if (tbl[ac(spd)]/tbl[nxt] > 5) {
idx <- sample(idx, tbl[ac(spd)] - tbl[nxt] *
2, replace = FALSE)
if (length(which(abs(an(names(tbl))) %in% spd)) >
1)
idx <- c(idx, sample(which(subset(tygmr,
LE_L5MET == iGr)$SI_SP == (-1 * spd)), tbl[ac(-1 *
spd)] - tbl[nxt] * 2, replace = FALSE))
}
else {
idx <- -1:-nrow(subset(tygmr, LE_L5MET == iGr))
}
if (is.null(storeScheme) == TRUE) {
res[[iGr]] <- try(normalmixEM(subset(tygmr,
LE_L5MET == iGr)$SI_SP[-idx], maxit = 1000,
k = 5, maxrestarts = 20, mean.constr = c("-b",
"-a", 0, "a", "b"), sd.constr = c("b",
"a", 0.911, "a", "b"), sigma = rep(1, 5)))
} else {
if ("means" %in% colnames(storeScheme)) {
ss <- storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iGr), "means"]
print ( c( yr, '-', mth, '-', wk, '-', iGr))
print( ss )
sigma <- anf(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iGr), "sigma0"])
fixPeaks <- ac(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iGr), "fixPeaks"])
#browser()
if (length(c(na.omit(as.numeric(strsplit(ss,
" ")[[1]])))) == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a", "b")
}
if (length(c(na.omit(as.numeric(strsplit(ss,
" ")[[1]])))) == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", sigma, "a",
"b")
}
if (fixPeaks)
constraintmn <- c(na.omit(anf(unlist(strsplit(ss,
" ")))))
res[[iGr]] <- try(normalmixEM(subset(tygmr,
LE_L5MET == iGr)$SI_SP[-idx], maxit = 1000,
mu = c(na.omit(as.numeric(strsplit(ss,
" ")[[1]]))), sigma = rep(1, length(constraintsd)),
maxrestarts = 20, mean.constr = constraintmn,
sd.constr = constraintsd))
} else {
ss <- storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iGr), "peaks"]
sigma <- anf(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iGr), "sigma0"])
fixPeaks <- ac(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iGr), "fixPeaks"])
if (ss == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a", "b")
}
if (ss == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", sigma, "a",
"b")
}
if (length(ss) > 0) {
if (is.na(ss) == TRUE)
res[[iGr]] <- try(normalmixEM(subset(tygmr,
LE_L5MET == iGr)$SI_SP[-idx], maxit = 1000,
k = 5, maxrestarts = 20, mean.constr = c("-b",
"-a", 0, "a", "b"), sd.constr = c("b",
"a", sigma, "a", "b"), sigma = rep(1,
5)))
if (is.na(ss) == FALSE)
res[[iGr]] <- try(normalmixEM(subset(tygmr,
LE_L5MET == iGr)$SI_SP[-idx], maxit = 1000,
k = ss, maxrestarts = 20, mean.constr = constraintmn,
sd.constr = constraintsd, sigma = rep(1,
length(constraintsd))))
}
else {
res[[iGr]] <- try(normalmixEM(subset(tygmr,
LE_L5MET == iGr)$SI_SP[-idx], maxit = 1000,
k = 5, maxrestarts = 20, mean.constr = c("-b",
"-a", 0, "a", "b"), sd.constr = c("b",
"a", sigma, "a", "b"), sigma = rep(1,
5)))
}
}
}
if (plot == TRUE)
plot(res[[iGr]], 2, breaks = 100, xlim = c(-20,
20))
}
if (level == "vessel") {
for (iGr in unique(tyg$LE_L5MET)) if (!class(res[[iGr]]) ==
"try-error") {
res[[iGr]] <- res[[iGr]]$mu
}
else {
res[[iGr]] <- rep(NA, 5)
}
res <- lapply(res, function(x) {
if (class(x) == "try-error") {
x <- rep(NA, 5)
}
else {
x
}
})
res <- lapply(res, sort)
}
if (level == "vessel") {
if (nrow(tygmr) > 40)
shipList <- names(which((rowSums(table(tygmr$VE_REF,
tygmr$SI_SP)) - table(tygmr$VE_REF, tygmr$SI_SP)[,
"0"]) > 20))
shipFit <- list()
if (exists("shipList")) {
for (iShip in shipList) {
tbl <- table(subset(tygmr, VE_REF == iShip)$SI_SP)
spd <- an(names(rev(sort(tbl))[1]))
idx <- which(subset(tygmr, VE_REF == iShip)$SI_SP ==
spd)
nxt <- ifelse(names(rev(sort(tbl))[1]) ==
ac(spd), ifelse(abs(an(names(rev(sort(tbl))[2]))) ==
abs(spd), names(rev(sort(tbl))[3]), names(rev(sort(tbl))[2])),
names(rev(sort(tbl))[1]))
if (tbl[ac(spd)]/tbl[nxt] > 5) {
idx <- sample(idx, tbl[ac(spd)] - tbl[nxt] *
2, replace = FALSE)
if (length(which(abs(an(names(tbl))) %in%
spd)) > 1)
idx <- c(idx, sample(which(subset(tygmr,
VE_REF == iShip)$SI_SP == (-1 * spd)),
tbl[ac(-1 * spd)] - tbl[nxt] * 2, replace = FALSE))
}
else {
idx <- -1:-nrow(subset(tygmr, VE_REF ==
iShip))
}
shipTacsat <- subset(tygmr, VE_REF == iShip)
if (length(res[[names(which.max(table(shipTacsat$LE_L5MET)))]]) ==
3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a", "b")
}
if (length(res[[names(which.max(table(shipTacsat$LE_L5MET)))]]) ==
3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", 0.911, "a",
"b")
}
shipFit[[iShip]] <- try(normalmixEM(shipTacsat$SI_SP[-idx],
mu = res[[names(which.max(table(shipTacsat$LE_L5MET)))]],
maxit = 2000, sigma = rep(1, length(constraintsd)),
mean.constr = constraintmn, sd.constr = constraintsd))
if (class(shipFit[[iShip]]) != "try-error") {
mu <- shipFit[[iShip]]$mu
sds <- shipFit[[iShip]]$sigma
probs <- dnorm(x = shipTacsat$SI_SP, mean = mu[ceiling(length(mu)/2)],
sd = sds[ceiling(length(mu)/2)])
for (i in (ceiling(length(mu)/2) + 1):length(mu)) probs <- cbind(probs,
dnorm(x = shipTacsat$SI_SP, mean = mu[i],
sd = sds[i]))
SI_STATE <- apply(probs, 1, which.max)
if (length(mu) == 3) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("f", "s")
SI_STATE <- ac(SI_STATE)
}
if (length(mu) == 5) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("h", "f", "s")
SI_STATE <- ac(SI_STATE)
}
tacsat$SI_STATE[which(tacsat$ID %in% shipTacsat$ID)] <- SI_STATE[1:(length(SI_STATE)/2)]
}
else {
tacsat$SI_STATE[which(tacsat$ID %in% shipTacsat$ID)] <- NA
}
}
}
}
else {
for (iGr in unique(tyg$LE_L5MET)) {
if (!class(res[[iGr]]) == "try-error") {
mu <- res[[iGr]]$mu
sds <- res[[iGr]]$sigma
probs <- dnorm(x = subset(tyg, LE_L5MET ==
iGr)$SI_SP, mean = mu[ceiling(length(mu)/2)],
sd = sds[ceiling(length(mu)/2)])
for (i in (ceiling(length(mu)/2) + 1):length(mu)) probs <- cbind(probs,
dnorm(x = subset(tyg, LE_L5MET == iGr)$SI_SP,
mean = mu[i], sd = sds[i]))
SI_STATE <- apply(probs, 1, which.max)
if (length(mu) == 3) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("f", "s")
SI_STATE <- ac(SI_STATE)
}
if (length(mu) == 5) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("h", "f", "s")
SI_STATE <- ac(SI_STATE)
}
tacsat$SI_STATE[which(tacsat$ID %in% subset(tyg,
LE_L5MET == iGr)$ID)] <- SI_STATE
}
}
}
if (nrow(tngmr) > 40)
browser()
nonshipList <- names(which((rowSums(table(tngmr$VE_REF,
tngmr$SI_SP)) - table(tngmr$VE_REF, tngmr$SI_SP)[,
"0"]) > 20))
nonshipFit <- list()
if (exists("nonshipList")) {
for (iShip in nonshipList) {
tbl <- table(subset(tngmr, VE_REF == iShip)$SI_SP)
spd <- an(names(rev(sort(tbl))[1]))
idx <- which(subset(tngmr, VE_REF == iShip)$SI_SP ==
spd)
nxt <- ifelse(names(rev(sort(tbl))[1]) == ac(spd),
ifelse(abs(an(names(rev(sort(tbl))[2]))) ==
abs(spd), names(rev(sort(tbl))[3]), names(rev(sort(tbl))[2])),
names(rev(sort(tbl))[1]))
if (tbl[ac(spd)]/tbl[nxt] > 5) {
idx <- sample(idx, tbl[ac(spd)] - tbl[nxt] *
2, replace = FALSE)
if (length(which(abs(an(names(tbl))) %in%
spd)) > 1)
idx <- c(idx, sample(which(subset(tngmr,
VE_REF == iShip)$SI_SP == (-1 * spd)),
tbl[ac(-1 * spd)] - tbl[nxt] * 2, replace = FALSE))
}
else {
idx <- -1:-nrow(subset(tngmr, VE_REF == iShip))
}
shipTacsat <- subset(tngmr, VE_REF == iShip)
if (exists("shipFit")) {
if (iShip %in% names(shipFit)) {
if (length(shipFit[[iShip]]$mu) == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a",
"b")
}
if (length(shipFit[[iShip]]$mu) == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", 0.911, "a",
"b")
}
nonshipFit[[iShip]] <- try(normalmixEM(shipTacsat$SI_SP[-idx],
k = length(shipFit[[iShip]]$mu), maxit = 2000,
sigma = rep(1, length(constraintsd)),
mean.constr = constraintmn, sd.constr = constraintsd))
}
else {
nonshipFit[[iShip]] <- try(normalmixEM(shipTacsat$SI_SP[-idx],
k = 5, maxit = 2000, mean.constr = c("-b",
"-a", 0, "a", "b"), sd.constr = c("b",
"a", 0.911, "a", "b"), sigma = rep(1,
5)))
}
if (!class(nonshipFit[[iShip]]) == "try-error") {
mu <- nonshipFit[[iShip]]$mu
sds <- nonshipFit[[iShip]]$sds
probs <- dnorm(x = shipTacsat$SI_SP, mean = mu[ceiling(length(mu)/2)],
sd = sds[ceiling(length(mu)/2)])
for (i in (ceiling(length(mu)/2) + 1):length(mu)) probs <- cbind(probs,
dnorm(x = shipTacsat$SI_SP, mean = mu[i],
sd = sds[i]))
SI_STATE <- apply(probs, 1, which.max)
if (length(mu) == 3) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("f", "s")
SI_STATE <- ac(SI_STATE)
}
if (length(mu) == 5) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("h", "f", "s")
SI_STATE <- ac(SI_STATE)
}
tacsat$SI_STATE[which(tacsat$ID %in% shipTacsat$ID)] <- SI_STATE[1:(length(SI_STATE)/2)]
}
}
}
}
}
if ("VE_REF" %in% colnames(tacsat) & analyse.by == "VE_REF") {
vesselList <- names(which((rowSums(table(sTacsat$VE_REF,
sTacsat$SI_SP)) - table(sTacsat$VE_REF, sTacsat$SI_SP)[,
"0"]) > 40))
tyv <- subset(sTacsat, is.na(VE_REF) == FALSE & VE_REF %in%
vesselList)
tyvmr <- tyv
tyvmr$SI_SP <- -1 * tyvmr$SI_SP
tyvmr <- rbind(tyv, tyvmr)
tnv <- subset(sTacsat, is.na(VE_REF) == TRUE | !VE_REF %in%
vesselList)
tnvmr <- tnv
tnvmr$SI_SP <- -1 * tnvmr$SI_SP
tnvmr <- rbind(tnv, tnvmr)
if (nrow(tyv) > 40)
shipList <- names(which((rowSums(table(tyvmr$VE_REF,
tyvmr$SI_SP)) - table(tyvmr$VE_REF, tyvmr$SI_SP)[,
"0"]) > 20))
shipFit <- list()
if (exists("shipList")) {
for (iShip in shipList) {
tbl <- table(subset(tyvmr, VE_REF == iShip)$SI_SP)
spd <- an(names(rev(sort(tbl))[1]))
idx <- which(subset(tyvmr, VE_REF == iShip)$SI_SP ==
spd)
nxt <- ifelse(names(rev(sort(tbl))[1]) == ac(spd),
ifelse(abs(an(names(rev(sort(tbl))[2]))) ==
abs(spd), names(rev(sort(tbl))[3]), names(rev(sort(tbl))[2])),
names(rev(sort(tbl))[1]))
if (tbl[ac(spd)]/tbl[nxt] > 5) {
idx <- sample(idx, tbl[ac(spd)] - tbl[nxt] *
2, replace = FALSE)
if (length(which(abs(an(names(tbl))) %in%
spd)) > 1)
idx <- c(idx, sample(which(subset(tyvmr,
VE_REF == iShip)$SI_SP == (-1 * spd)),
tbl[ac(-1 * spd)] - tbl[nxt] * 2, replace = FALSE))
}
else {
idx <- -1:-nrow(subset(tyvmr, VE_REF == iShip))
}
shipTacsat <- subset(tyvmr, VE_REF == iShip)
if (is.null(storeScheme) == TRUE) {
shipFit[[iShip]] <- try(normalmixEM(subset(tyvmr,
VE_REF == iShip)$SI_SP[-idx], maxit = 2000,
k = 5, mean.constr = c("-b", "-a", 0, "a",
"b"), sd.constr = c("b", "a", 0.911,
"a", "b"), sigma = rep(1, 5)))
} else {
if ("means" %in% colnames(storeScheme)) {
ss <- storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iShip),
"means"]
sigma <- anf(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iShip),
"sigma0"])
fixPeaks <- ac(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iShip),
"fixPeaks"])
if (length(c(na.omit(as.numeric(strsplit(ss,
" ")[[1]])))) == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a",
"b")
}
if (length(c(na.omit(as.numeric(strsplit(ss,
" ")[[1]])))) == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", sigma, "a",
"b")
}
if (fixPeaks)
constraintmn <- c(na.omit(anf(unlist(strsplit(ss,
" ")))))
shipFit[[iShip]] <- try(normalmixEM(subset(tyvmr,
VE_REF == iShip)$SI_SP[-idx], mu = c(na.omit(as.numeric(strsplit(ss,
" ")[[1]]))), maxit = 2000, mean.constr = constraintmn,
sd.constr = constraintsd, sigma = rep(1,
length(constraintsd))))
}
else {
ss <- storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iShip),
"peaks"]
sigma <- anf(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iShip),
"sigma0"])
fixPeaks <- ac(storeScheme[which(storeScheme$years ==
yr & storeScheme$months == mth & storeScheme$weeks ==
wk & storeScheme$analyse.by == iShip),
"fixPeaks"])
if (ss == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a",
"b")
}
if (ss == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", sigma, "a",
"b")
}
if (length(ss) > 0) {
if (is.na(ss) == TRUE)
shipFit[[iShip]] <- try(normalmixEM(subset(tyvmr,
VE_REF == iShip)$SI_SP[-idx], maxit = 2000,
k = 5, mean.constr = c("-b", "-a",
0, "a", "b"), sd.constr = c("b",
"a", sigma, "a", "b"), sigma = rep(1,
5)))
if (is.na(ss) == FALSE)
shipFit[[iShip]] <- try(normalmixEM(subset(tyvmr,
VE_REF == iShip)$SI_SP[-idx], maxit = 2000,
k = ss, mean.constr = constraintmn,
sd.constr = constraintsd, sigma = rep(1,
length(constraintsd))))
}
else {
shipFit[[iShip]] <- try(normalmixEM(subset(tyvmr,
VE_REF == iShip)$SI_SP[-idx], maxit = 2000,
k = 5, mean.constr = c("-b", "-a",
0, "a", "b"), sd.constr = c("b",
"a", sigma, "a", "b"), sigma = rep(1,
5)))
}
}
}
if (plot == TRUE)
plot(shipFit[[iShip]], 2, breaks = 100, xlim = c(-20,
20))
if (!class(shipFit[[iShip]]) == "try-error") {
mu <- shipFit[[iShip]]$mu
sds <- shipFit[[iShip]]$sigma
probs <- dnorm(x = shipTacsat$SI_SP, mean = mu[ceiling(length(mu)/2)],
sd = sds[ceiling(length(mu)/2)])
for (i in (ceiling(length(mu)/2) + 1):length(mu)) probs <- cbind(probs,
dnorm(x = shipTacsat$SI_SP, mean = mu[i],
sd = sds[i]))
SI_STATE <- apply(probs, 1, which.max)
if (length(mu) == 3) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("f", "s")
SI_STATE <- ac(SI_STATE)
}
if (length(mu) == 5) {
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("h", "f", "s")
SI_STATE <- ac(SI_STATE)
}
tacsat$SI_STATE[which(tacsat$ID %in% shipTacsat$ID)] <- SI_STATE[1:(length(SI_STATE)/2)]
}
}
}
if (nrow(tnvmr) > 40)
nonshipList <- names(which((rowSums(table(tnvmr$VE_REF,
tnvmr$SI_SP)) - table(tnvmr$VE_REF, tnvmr$SI_SP)[,
"0"]) > 20))
nonshipFit <- list()
if (exists("nonshipList")) {
for (iShip in nonshipList) {
tbl <- table(subset(tnvmr, VE_REF == iShip)$SI_SP)
spd <- an(names(rev(sort(tbl))[1]))
idx <- which(subset(tnvmr, VE_REF == iShip)$SI_SP ==
spd)
nxt <- ifelse(names(rev(sort(tbl))[1]) == ac(spd),
ifelse(abs(an(names(rev(sort(tbl))[2]))) ==
abs(spd), names(rev(sort(tbl))[3]), names(rev(sort(tbl))[2])),
names(rev(sort(tbl))[1]))
if (tbl[ac(spd)]/tbl[nxt] > 5) {
idx <- sample(idx, tbl[ac(spd)] - tbl[nxt] *
2, replace = FALSE)
if (length(which(abs(an(names(tbl))) %in%
spd)) > 1)
idx <- c(idx, sample(which(subset(tnvmr,
VE_REF == iShip)$SI_SP == (-1 * spd)),
tbl[ac(-1 * spd)] - tbl[nxt] * 2, replace = FALSE))
}
else {
idx <- -1:-nrow(subset(tnvmr, VE_REF == iShip))
}
shipTacsat <- subset(tnvmr, VE_REF == iShip)
if (length(shipFit[[iShip]]$mu) == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a", "b")
}
if (length(shipFit[[iShip]]$mu) == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", 0.911, "a", "b")
}
nonshipFit[[iShip]] <- try(normalmixEM(shipTacsat$SI_SP[-idx],
k = length(shipFit[[iShip]]$mu), maxit = 2000,
mean.constr = constraintmn, sd.constr = constraintsd,
sigma = rep(1, length(constraintsd))))
if (!class(nonshipFit[[iShip]]) == "try-error") {
mu <- nonshipFit[[iShip]]$mu
sds <- nonshipFit[[iShip]]$sigma
probs <- dnorm(x = shipTacsat$SI_SP, mean = mu[ceiling(length(mu)/2)],
sd = sds[ceiling(length(mu)/2)])
for (i in (ceiling(length(mu)/2) + 1):length(mu)) probs <- cbind(probs,
dnorm(x = shipTacsat$SI_SP, mean = mu[i],
sd = sds[i]))
SI_STATE <- apply(probs, 1, which.max)
if (length(mu) == 3)
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("f", "s")
SI_STATE <- ac(SI_STATE)
if (length(mu) == 5)
SI_STATE <- af(SI_STATE)
levels(SI_STATE) <- c("h", "f", "s")
SI_STATE <- ac(SI_STATE)
tacsat$SI_STATE[which(tacsat$ID %in% shipTacsat$ID)] <- SI_STATE[1:(length(SI_STATE)/2)]
}
}
}
}
}
leftOverTacsat <- tacsatOrig[which(!tacsatOrig$ID %in% tacsat$ID),
]
tacsat <- rbind(tacsat, leftOverTacsat)
tacsat <- orderBy(~ID, tacsat)
cat("Note that in case of 5 peaks: no fishing = h, fishing = f, steaming / no fishing = s\n")
cat("Note that in case of 3 peaks: fishing = f, steaming / no fishing = s\n")
return(tacsat$SI_STATE)
}