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0_global.R
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#'------------------------------------------------------------------------------
# READ ME
# The following script is a proposed workflow example to process the ICES
# VMS data call request. It is not an exact template to be applied to data from
# every member state and needs to be adjusted according to the data availability
# and needs of every national data set.
#'------------------------------------------------------------------------------
#'------------------------------------------------------------------------------
# 0.1 Preparations ----
#'------------------------------------------------------------------------------
# Clear the workspace
rm(list=ls())
## Download and install required packages which are not available via CRAN
# Install devtools from CRAN
install.packages("devtools")
## Download and install the library required to interact with the ICES SharePoint site
library(devtools)
install.packages("icesSharePoint", repos = c('https://ices-tools-prod.r-universe.dev', 'https://cloud.r-project.org'))
## set ICES sharepoint username
options(icesSharePoint.username = "your ices login name") ## replace this text with your ICES sharepoint login name
## check it has worked
options("icesSharePoint.username")
# Download the VMStools .tar.gz file from GitHub
url <- "https://github.com/nielshintzen/vmstools/releases/download/0.77/vmstools_0.77.tar.gz"
download.file(url, destfile = "vmstools_0.77.tar.gz", mode = "wb")
# Install the library from the downloaded .tar.gz file
install.packages("vmstools_0.77.tar.gz", repos = NULL, type = "source")
# Clean up by removing the downloaded file
unlink("vmstools_0.77.tar.gz")
# Install required packages using pacman
if (!require("pacman")) install.packages("pacman")
pacman::p_load(vmstools, sf, data.table, raster, terra, mapview, Matrix, dplyr,
doBy, mixtools, tidyr, glue, gt, progressr, geosphere, purrr,
ggplot2, sfdSAR, icesVocab, generics, icesConnect, icesVMS, icesSharePoint,
tidyverse, units, tcltk, lubridate, here)
# Set paths
path <- paste0(getwd(), "/") # Working directory
codePath <- paste0(path, "Scripts/") # Location to store R scripts
dataPath <- paste0(path, "Data/") # Location to store tacsat (VMS) and eflalo (logbook) data
outPath <- paste0(path, "Results/") # Location to store the results
plotPath <- paste0(path, "Plots/")
# Create directories if they don't exist
dir.create(codePath, showWarnings = T)
dir.create(dataPath, showWarnings = T)
dir.create(outPath, showWarnings = T)
dir.create(plotPath, showWarnings = T)
#'------------------------------------------------------------------------------
# 0.2 Settings for analysis ----
#'------------------------------------------------------------------------------
# Setting thresholds
spThres <- 20 # Maximum speed threshold in analyses in nm
intThres <- 5 # Minimum difference in time interval in minutes to prevent pseudo duplicates
intvThres <- 240 # Maximum difference in time interval in minutes to prevent unrealistic intervals
lanThres <- 1.5 # Maximum difference in log10-transformed sorted weights
# Set the years to submit
yearsToSubmit <- c(2009:2023)
# Set the gear names for which automatic fishing activity is wanted
autoDetectionGears <- c("TBB","OTB","OTT", "OTM","SSC","SDN","DRB","PTB","HMD", "MIS")
# Decide if you want to visually analyze speed-histograms to identify fishing activity peaks
visualInspection <- TRUE
# Specify how landings should be distributed over the VMS pings
linkEflaloTacsat <- c("trip")
# Extract valid level 6 metiers
valid_metiers <- fread("https://raw.githubusercontent.com/ices-eg/RCGs/master/Metiers/Reference_lists/RDB_ISSG_Metier_list.csv")$Metier_level6
#'------------------------------------------------------------------------------
# Download the bathymetry and habitat files ----
#'------------------------------------------------------------------------------
#'
#'To access the files needed for the habitat and bathymetry part of the workflow you need to download a zip file
#'containing both as sf objects in .rds formats. The script below should download and unzip the files into the
#'correct directory. If you have problems downloading the files, contact [email protected]
if(!file.exists(paste0(dataPath, "hab_and_bathy_layers.zip"))){
# Download the zip file
icesSharePoint::spgetfile(file = "SEAwise Documents/hab_and_bathy_layers.zip", site = "/ExpertGroups/DataExpports/VMS_Data_call", destdir = dataPath)
## The first time you run this code you will be prompted to enter your ICES Sharepoint password. Type it in the pop-up window to proceed with the download
# Extract the zip archive
unzip(paste0(dataPath, "hab_and_bathy_layers.zip"), exdir = dataPath, overwrite = TRUE, junkpaths = TRUE)
}
# Load the bathymetry and habitat layers into R
eusm <- readRDS(paste0(dataPath, "eusm.rds"))
eusm <- eusm %>% st_transform(4326)
bathy <- readRDS(paste0(dataPath, "ICES_GEBCO.rds"))
bathy <- bathy %>% st_set_crs(4326)
# Necessary setting for spatial operations
sf::sf_use_s2(FALSE)
#'------------------------------------------------------------------------------
# 0.3 Defining functions ----
#'------------------------------------------------------------------------------
# Define function for NOT in data
'%!in%' <- function(x,y)!('%in%'(x,y))
# Define a function to transform spatial data to sf
transform_to_sf <- function(data, coords, crs = 4326) {
data %>%
sf::st_as_sf(coords = coords, remove = F) %>%
sf::st_set_crs(crs)
}
# Define a function to calculate species bounds
get_spec_bounds <- function(specs, eflalo, lanThres) {
lapply(
as.list(specs),
function(x) {
specs_cols <- grep(x, colnames(eflalo))
idx <- specs_cols[grep("KG", colnames(eflalo)[specs_cols])]
wgh <- sort(unique(eflalo[which(eflalo[, idx] > 0), idx]))
difw <- diff(log10(wgh))
ifelse(
any(difw > lanThres),
wgh[rev(which(difw <= lanThres)[1] + 1)], # Return only the first value
ifelse(
length(wgh) == 0,
0,
max(wgh, na.rm = TRUE)
)
)
}
)
}
# Define a function to get the index (column number) of each of the species
get_species_indices <- function(specs, eflalo) {
sapply(specs, function(spec) {
# Find the column indices that contain the current species name and "KG"
grep(spec, colnames(eflalo)[grep("KG", colnames(eflalo))])
})
}
# Define a function to get the indices of KG and EURO columns
kgeur <- function(cols) {
grep("KG|EURO", cols)
}
# Define a function to create a unique trip identifier
create_trip_id <- function(eflalo) {
paste(eflalo$LE_ID, eflalo$LE_CDAT, sep="-")
}
# Define a function to convert date and time columns to POSIXct
convert_to_datetime <- function(date_col, time_col) {
as.POSIXct(paste(date_col, time_col, sep = " "), tz = "GMT", format = "%d/%m/%Y %H:%M")
}
# Define a function to remove records starting before the 1st of January
remove_before_jan <- function(eflalo, year) {
# Convert the start of the year to a POSIXct datetime object
start_of_year <- as.POSIXct(paste(year, "-01-01 00:00:00", sep = ""), format = "%Y-%m-%d %H:%M")
# Ensure FT_DDATIM is in the correct datetime format
eflalo$FT_DDATIM <- as.POSIXct(eflalo$FT_DDATIM, format = "%Y-%m-%d %H:%M")
# Remove records with FT_DDATIM before the start of the year
eflalo <- eflalo[eflalo$FT_DDATIM >= start_of_year,]
return(eflalo)
}
# Define a function to calculate intervals in the TACSAT data
intvTacsat <- function (tacsat, level = "trip", weight = c(1, 0), fill.na = FALSE) {
# Check if 'weight' is a length 2 numeric vector
if (length(weight) != 2)
stop("weight must be specified as a length 2 numeric vector")
# Normalize 'weight' to sum to 1
weight <- weight/sum(weight, na.rm = TRUE)
# Sort 'tacsat' (assuming 'sortTacsat' is a function that sorts 'tacsat')
tacsat <- sortTacsat(tacsat)
# Convert 'SI_DATE' and 'SI_TIME' to POSIXct if 'SI_DATIM' is not already present
if (!"SI_DATIM" %in% colnames(tacsat))
tacsat$SI_DATIM <- as.POSIXct(paste(tacsat$SI_DATE, tacsat$SI_TIME, sep = " "), tz = "GMT", format = "%d/%m/%Y %H:%M")
# If level is 'trip', calculate intervals for each trip
if (level == "trip") {
# Check if 'FT_REF' is present
if (is.null(tacsat$FT_REF))
stop("no trip number available to merge on trip level")
# Split 'tacsat' by 'VE_REF'
sptacsat <- split(tacsat, tacsat$VE_REF)
# Calculate intervals for each trip
tacsat$INTV <- unlist(lapply(sptacsat, function(x) {
# Convert 'FT_REF' to factor
FT_REF <- as.factor(x$FT_REF)
# Calculate intervals for each 'FT_REF'
res <- by(x, FT_REF, function(y) {
# If there is more than one row, calculate intervals
if (nrow(y) > 1) {
# Calculate differences in 'SI_DATIM' for each row
difftime_xmin1 <- c(NA, difftime(y$SI_DATIM[2:nrow(y)], y$SI_DATIM[1:(nrow(y) - 1)], units = "mins"))
difftime_xplus1 <- c(difftime_xmin1[-1], NA)
# Calculate intervals based on 'weight'
if (any(weight == 0)) {
if (weight[1] == 0)
INTV <- difftime_xplus1
if (weight[2] == 0)
INTV <- difftime_xmin1
} else {
INTV <- rowSums(cbind(difftime_xmin1 * weight[1], difftime_xplus1 * weight[2]))
}
# If 'fill.na' is TRUE, fill NA values in 'INTV'
if (fill.na) {
idx <- which(is.na(INTV))
INTV[idx] <- rowSums(cbind(difftime_xmin1[idx], difftime_xplus1[idx]), na.rm = TRUE)
INTV[idx][which(INTV[idx] == 0)] <- NA
}
return(INTV)
} else {
return(NA)
}
})
return(unsplit(res, FT_REF))
}))
# Set 'INTV' to NA where 'FT_REF' equals 0
tacsat$INTV[which(tacsat$FT_REF == "0")] <- NA
}
# If level is 'vessel', calculate intervals for each vessel
if (level == "vessel") {
# Calculate differences in 'SI_DATIM' for each row
difftime_xmin1 <- c(NA, difftime(tacsat$SI_DATIM[2:nrow(tacsat)], tacsat$SI_DATIM[1:(nrow(tacsat) - 1)], units = "mins"))
difftime_xplus1 <- c(difftime_xmin1[-1], NA)
# Calculate intervals based on 'weight'
if (any(weight == 0)) {
if (weight[1] == 0)
INTV <- difftime_xplus1
if (weight[2] == 0)
INTV <- difftime_xmin1
} else {
INTV <- rowSums(cbind(difftime_xmin1 * weight[1], difftime_xplus1 * weight[2]))
}
# If 'fill.na' is TRUE, fill NA values in 'INTV'
if (fill.na) {
idx <- which(is.na(INTV))
INTV[idx] <- rowSums(cbind(difftime_xmin1[idx], difftime_xplus1[idx]), na.rm = TRUE)
INTV[idx][which(INTV[idx] == 0)] <- NA
}
# Assign 'INTV' to 'tacsat'
tacsat$INTV <- INTV
# Get unique vessels
vessels <- unique(tacsat$VE_REF)
# Get first and last rows for each vessel
first.vessels <- unlist(lapply(as.list(vessels), function(x) which(tacsat$VE_REF == x)[1]))
last.vessels <- unlist(lapply(as.list(vessels), function(x) rev(which(tacsat$VE_REF == x))[1]))
# Set 'INTV' to NA for first and last rows of each vessel based on 'weight'
if (weight[1] != 0)
tacsat$INTV[first.vessels] <- NA
if (weight[2] != 0)
tacsat$INTV[last.vessels] <- NA
# If 'fill.na' is TRUE, fill NA values in 'INTV' for first and last rows of each vessel
if (fill.na) {
tacsat$INTV[first.vessels] <- difftime_xplus1[first.vessels]
tacsat$INTV[last.vessels] <- difftime_xmin1[last.vessels]
}
}
return(tacsat)
}
# Define a function to sort Tacsat data
sfsortTacsat <- function(dat) {
if (!"SI_DATIM" %in% colnames(dat)) {
dat$SI_DATIM <- as.POSIXct(paste(dat$SI_DATE, dat$SI_TIME, sep = " "), tz = "GMT", format = "%d/%m/%Y %H:%M")
}
if ("VE_REF" %in% colnames(dat)) {
dat <- arrange(dat, VE_REF, SI_DATIM)
}
if ("OB_REF" %in% colnames(dat)) {
dat <- arrange(dat, OB_REF, SI_DATIM)
}
return(dat)
}
## Define a function to identify peaks in speed distributions
callNumberPeak <- function(){
tt <- tktoplevel()
peaks <- tclVar(5)
f1 <- tkframe(tt)
tkpack(f1, side='top')
tkpack(tklabel(f1, text='peaks: '), side='left')
tkpack(tkentry(f1, textvariable=peaks), side='left')
tkpack(tkbutton(tt, text='Next', command=function() tkdestroy(tt)),
side='right', anchor='s')
tkwait.window(tt)
return(as.numeric(tclvalue(peaks)))}
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$SI_DATIM)))
mths <- 0
}
runScheme <- expand.grid(years = yrs, months = mths,
weeks = wks, stringsAsFactors = FALSE)
storeScheme <- expand.grid(years = yrs, months = mths,
weeks = wks, analyse.by = unique(tacsat[, analyse.by]),
stringsAsFactors = FALSE)
storeScheme$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[, analyse.by]))) {
dat <- subset(sTacsat, sTacsat[, 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"){
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$analyse.by == iGr), "means"]
sigma <- anf(storeScheme[which(storeScheme$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$analyse.by == iGr), "fixPeaks"])
if (length(c(na.omit(as.numeric(strsplit(ss,
" ")[[1]])))) == 3) {
constraintmn <- c("-a", 0, "a")
}
else {
constraintmn <- c("-b", "-a", 0, "a", "b")
}
if (length(c(na.omit(as.numeric(strsplit(ss,
" ")[[1]])))) == 3) {
constraintsd <- c("a", "b", "a")
}
else {
constraintsd <- c("b", "a", sigma, "a",
"b")
}
if (fixPeaks)
constraintmn <- c(na.omit(anf(unlist(strsplit(ss,
" ")))))
res[[iGr]] <- try(normalmixEM(subset(tygmr,
LE_L5MET == iGr)$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)
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]))) ==