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hmeanbatchcoverage.R
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hmeanbatchcoverage.R
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# 10b. batch mean proportion coverage per hour
hmean.batch.coverage <- function(xmin12 = 40.5, xmax12 = 64.5, ymin12 = 40.5, ymax12 = 64.5, xmin14 = 15, xmax14 = 39, ymin14 = 40.5, ymax14 = 64.5, xmin15 = 15, xmax15 = 39, ymin15 = 15, ymax15 = 39, boxsize = 0.3) {
files <- list.files(path = workingdir, pattern = '*.csv', all.files = FALSE, recursive = FALSE)
coverage.P12 <- data.frame(c('P12_mean_coverage', 'P12_sd'))
colnames(coverage.P12) <- 'ID'
rownames(coverage.P12) <- c('P12_mean_coverage', 'P12_sd')
coverage.P14 <- data.frame(c('P14_mean_coverage', 'P14_sd'))
colnames(coverage.P14) <- 'ID'
rownames(coverage.P14) <- c('P14_mean_coverage', 'P14_sd')
coverage.P15 <- data.frame(c('P15_mean_coverage', 'P15_sd'))
colnames(coverage.P15) <- 'ID'
rownames(coverage.P15) <- c('P15_mean_coverage', 'P15_sd')
anova.list <- data.frame('P value')
colnames(anova.list) <- 'ID'
rownames(anova.list) <- 'P value'
for (i in 1:length(files))
{
dayfile.loc <- files[[i]]
dayfile <- read.csv(dayfile.loc, header = TRUE, sep = ",", colClasses = dayfile.classes)
if(length(unique(dayfile$Period)) == 1) { # check if a fish file is loaded
if(unique(dayfile$PEN) == '12'){
fish.id <- subset(dayfile, PEN == '12')
fish.id <- fish.id[order(fish.id$EchoTime, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by time
starttime <- fish.id[1,'EchoTime']-seconds(1)
nhours <- length(unique(hour(fish.id[,'EchoTime'])))-1
fish.id <- fish.id[order(fish.id$Period, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by tag
proportion.P12 <- numeric()
for (j in 1:nhours){
hoursub <- fish.id[fish.id$EchoTime > starttime & fish.id$EchoTime < starttime+hours(1),]
if (nrow(hoursub) > 2){
x.grid <- floor((hoursub$PosX - xmin12) / boxsize) + 1
y.grid <- floor((hoursub$PosY - ymin12) / boxsize) + 1
x.grid.max <- floor((xmax12 - xmin12) / boxsize) + 1
y.grid.max <- floor((ymax12 - ymin12) / boxsize) + 1
t.x <- sort(unique(x.grid))
t.y <- sort(unique(y.grid))
tx.range <- c(min(which(t.x > 0)), max(which(t.x <= x.grid.max)))
ty.range <- c(min(which(t.y > 0)), max(which(t.y <= y.grid.max)))
t <- table(y.grid, x.grid)[ty.range[1]:ty.range[2],tx.range[1]:tx.range[2]]
grid.cov <- matrix(0,nrow=y.grid.max,ncol=x.grid.max)
t.x <- t.x[(t.x > 0) & (t.x <=x.grid.max)]
t.y <- t.y[(t.y > 0) & (t.y <=y.grid.max)]
eg <- expand.grid(t.y,t.x)
grid.cov[cbind(eg$Var1,eg$Var2)] <- as.vector(t)
proportion.P12 <- c(proportion.P12, length(which(grid.cov > 0))/length(grid.cov))
} else {
proportion.P12 <- c(proportion.P12, 0)
}
starttime <- starttime+hours(1)
#print(nrow(hoursub))
}
proportion.P12[proportion.P12 == 0] <- NA
coverage.P12[,as.character(i)] <- c(mean(proportion.P12, na.rm = T), sd(proportion.P12, na.rm = T))
coverage.P14[,as.character(i)] <- c('NA', 'NA')
coverage.P15[,as.character(i)] <- c('NA', 'NA')
}
if(unique(dayfile$PEN) == '14'){
fish.id <- subset(dayfile, PEN == '14')
fish.id <- fish.id[order(fish.id$EchoTime, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by time
starttime <- fish.id[1,'EchoTime']-seconds(1)
nhours <- length(unique(hour(fish.id[,'EchoTime'])))-1
fish.id <- fish.id[order(fish.id$Period, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by tag
proportion.P14 <- numeric()
for (j in 1:nhours){
hoursub <- fish.id[fish.id$EchoTime >starttime & fish.id$EchoTime <starttime+hours(1),]
if (nrow(hoursub) > 2){
x.grid <- floor((hoursub$PosX - xmin14) / boxsize) + 1
y.grid <- floor((hoursub$PosY - ymin14) / boxsize) + 1
x.grid.max <- floor((xmax14 - xmin14) / boxsize) + 1
y.grid.max <- floor((ymax14 - ymin14) / boxsize) + 1
t.x <- sort(unique(x.grid))
t.y <- sort(unique(y.grid))
tx.range <- c(min(which(t.x > 0)), max(which(t.x <= x.grid.max)))
ty.range <- c(min(which(t.y > 0)), max(which(t.y <= y.grid.max)))
t <- table(y.grid, x.grid)[ty.range[1]:ty.range[2],tx.range[1]:tx.range[2]]
grid.cov <- matrix(0,nrow=y.grid.max,ncol=x.grid.max)
t.x <- t.x[(t.x > 0) & (t.x <=x.grid.max)]
t.y <- t.y[(t.y > 0) & (t.y <=y.grid.max)]
eg <- expand.grid(t.y,t.x)
grid.cov[cbind(eg$Var1,eg$Var2)] <- as.vector(t)
proportion.P14 <- c(proportion.P14, length(which(grid.cov > 0))/length(grid.cov))
} else {
proportion.P14 <- c(proportion.P14, 0)
}
starttime <- starttime+hours(1)
}
proportion.P14[proportion.P14 == 0] <- NA
coverage.P14[,as.character(i)] <- c(mean(proportion.P14, na.rm = T), sd(proportion.P14, na.rm = T))
coverage.P12[,as.character(i)] <- c('NA', 'NA')
coverage.P15[,as.character(i)] <- c('NA', 'NA')
}
if(unique(dayfile$PEN) == '15'){
fish.id <- subset(dayfile, PEN == '15')
fish.id <- fish.id[order(fish.id$EchoTime, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by time
starttime <- fish.id[1,'EchoTime']-seconds(1)
nhours <- length(unique(hour(fish.id[,'EchoTime'])))-1
fish.id <- fish.id[order(fish.id$Period, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by tag
proportion.P15 <- numeric()
for (j in 1:nhours){
hoursub <- fish.id[fish.id$EchoTime >starttime & fish.id$EchoTime <starttime+hours(1),]
if (nrow(hoursub) > 2){
x.grid <- floor((hoursub$PosX - xmin15) / boxsize) + 1
y.grid <- floor((hoursub$PosY - ymin15) / boxsize) + 1
x.grid.max <- floor((xmax15 - xmin15) / boxsize) + 1
y.grid.max <- floor((ymax15 - ymin15) / boxsize) + 1
t.x <- sort(unique(x.grid))
t.y <- sort(unique(y.grid))
tx.range <- c(min(which(t.x > 0)), max(which(t.x <= x.grid.max)))
ty.range <- c(min(which(t.y > 0)), max(which(t.y <= y.grid.max)))
t <- table(y.grid, x.grid)[ty.range[1]:ty.range[2],tx.range[1]:tx.range[2]]
grid.cov <- matrix(0,nrow=y.grid.max,ncol=x.grid.max)
t.x <- t.x[(t.x > 0) & (t.x <=x.grid.max)]
t.y <- t.y[(t.y > 0) & (t.y <=y.grid.max)]
eg <- expand.grid(t.y,t.x)
grid.cov[cbind(eg$Var1,eg$Var2)] <- as.vector(t)
proportion.P15 <- c(proportion.P15, length(which(grid.cov > 0))/length(grid.cov))
} else {
proportion.P15 <- c(proportion.P15, 0)
}
starttime <- starttime+hours(1)
}
proportion.P15[proportion.P15 == 0] <- NA
coverage.P15[,as.character(i)] <- c(mean(proportion.P15, na.rm = T), sd(proportion.P15, na.rm = T))
coverage.P12[,as.character(i)] <- c('NA', 'NA')
coverage.P14[,as.character(i)] <- c('NA', 'NA')
}
}
else { # else assume a dayfile is loaded
fish.id <- subset(dayfile, PEN == '12')
fish.id <- fish.id[order(fish.id$EchoTime, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by time
starttime <- fish.id[1,'EchoTime']-seconds(1)
nhours <- length(unique(hour(fish.id[,'EchoTime'])))-1
fish.id <- fish.id[order(fish.id$Period, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by tag
proportion.P12 <- numeric()
for (j in 1:nhours){
hoursub <- fish.id[fish.id$EchoTime > starttime & fish.id$EchoTime < starttime+hours(1),]
if (nrow(hoursub) > 2){
x.grid <- floor((hoursub$PosX - xmin12) / boxsize) + 1
y.grid <- floor((hoursub$PosY - ymin12) / boxsize) + 1
x.grid.max <- floor((xmax12 - xmin12) / boxsize) + 1
y.grid.max <- floor((ymax12 - ymin12) / boxsize) + 1
t.x <- sort(unique(x.grid))
t.y <- sort(unique(y.grid))
tx.range <- c(min(which(t.x > 0)), max(which(t.x <= x.grid.max)))
ty.range <- c(min(which(t.y > 0)), max(which(t.y <= y.grid.max)))
t <- table(y.grid, x.grid)[ty.range[1]:ty.range[2],tx.range[1]:tx.range[2]]
grid.cov <- matrix(0,nrow=y.grid.max,ncol=x.grid.max)
t.x <- t.x[(t.x > 0) & (t.x <=x.grid.max)]
t.y <- t.y[(t.y > 0) & (t.y <=y.grid.max)]
eg <- expand.grid(t.y,t.x)
grid.cov[cbind(eg$Var1,eg$Var2)] <- as.vector(t)
proportion.P12 <- c(proportion.P12, length(which(grid.cov > 0))/length(grid.cov))
} else {
proportion.P12 <- c(proportion.P12, 0)
}
starttime <- starttime+hours(1)
}
proportion.P12[proportion.P12 == 0] <- NA
coverage.P12[,as.character(i)] <- c(mean(proportion.P12, na.rm = T), sd(proportion.P12, na.rm = T))
proportion.P12 <- as.data.frame(proportion.P12)
proportion.P12$pen <- 12
names(proportion.P12) <- c('proportion', 'pen')
fish.id <- subset(dayfile, PEN == '14')
fish.id <- fish.id[order(fish.id$EchoTime, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by time
starttime <- fish.id[1,'EchoTime']-seconds(1)
nhours <- length(unique(hour(fish.id[,'EchoTime'])))-1
fish.id <- fish.id[order(fish.id$Period, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by tag
proportion.P14 <- numeric()
for (j in 1:nhours){
hoursub <- fish.id[fish.id$EchoTime >starttime & fish.id$EchoTime <starttime+hours(1),]
if (nrow(hoursub) > 2){
x.grid <- floor((hoursub$PosX - xmin14) / boxsize) + 1
y.grid <- floor((hoursub$PosY - ymin14) / boxsize) + 1
x.grid.max <- floor((xmax14 - xmin14) / boxsize) + 1
y.grid.max <- floor((ymax14 - ymin14) / boxsize) + 1
t.x <- sort(unique(x.grid))
t.y <- sort(unique(y.grid))
tx.range <- c(min(which(t.x > 0)), max(which(t.x <= x.grid.max)))
ty.range <- c(min(which(t.y > 0)), max(which(t.y <= y.grid.max)))
t <- table(y.grid, x.grid)[ty.range[1]:ty.range[2],tx.range[1]:tx.range[2]]
grid.cov <- matrix(0,nrow=y.grid.max,ncol=x.grid.max)
t.x <- t.x[(t.x > 0) & (t.x <=x.grid.max)]
t.y <- t.y[(t.y > 0) & (t.y <=y.grid.max)]
eg <- expand.grid(t.y,t.x)
grid.cov[cbind(eg$Var1,eg$Var2)] <- as.vector(t)
proportion.P14 <- c(proportion.P14, length(which(grid.cov > 0))/length(grid.cov))
} else {
proportion.P14 <- c(proportion.P14, 0)
}
starttime <- starttime+hours(1)
}
proportion.P14[proportion.P14 == 0] <- NA
coverage.P14[,as.character(i)] <- c(mean(proportion.P14, na.rm = T), sd(proportion.P14, na.rm = T))
proportion.P14 <- as.data.frame(proportion.P14)
proportion.P14$pen <- 14
names(proportion.P14) <- c('proportion', 'pen')
fish.id <- subset(dayfile, PEN == '15')
fish.id <- fish.id[order(fish.id$EchoTime, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by time
starttime <- fish.id[1,'EchoTime']-seconds(1)
nhours <- length(unique(hour(fish.id[,'EchoTime'])))-1
fish.id <- fish.id[order(fish.id$Period, na.last = FALSE, decreasing = FALSE, method = c("shell")),] # sort by tag
proportion.P15 <- numeric()
for (j in 1:nhours){
hoursub <- fish.id[fish.id$EchoTime >starttime & fish.id$EchoTime <starttime+hours(1),]
if (nrow(hoursub) > 2){
x.grid <- floor((hoursub$PosX - xmin15) / boxsize) + 1
y.grid <- floor((hoursub$PosY - ymin15) / boxsize) + 1
x.grid.max <- floor((xmax15 - xmin15) / boxsize) + 1
y.grid.max <- floor((ymax15 - ymin15) / boxsize) + 1
t.x <- sort(unique(x.grid))
t.y <- sort(unique(y.grid))
tx.range <- c(min(which(t.x > 0)), max(which(t.x <= x.grid.max)))
ty.range <- c(min(which(t.y > 0)), max(which(t.y <= y.grid.max)))
t <- table(y.grid, x.grid)[ty.range[1]:ty.range[2],tx.range[1]:tx.range[2]]
grid.cov <- matrix(0,nrow=y.grid.max,ncol=x.grid.max)
t.x <- t.x[(t.x > 0) & (t.x <=x.grid.max)]
t.y <- t.y[(t.y > 0) & (t.y <=y.grid.max)]
eg <- expand.grid(t.y,t.x)
grid.cov[cbind(eg$Var1,eg$Var2)] <- as.vector(t)
proportion.P15 <- c(proportion.P15, length(which(grid.cov > 0))/length(grid.cov))
} else {
proportion.P15 <- c(proportion.P15, 0)
}
starttime <- starttime+hours(1)
}
proportion.P15[proportion.P15 == 0] <- NA
coverage.P15[,as.character(i)] <- c(mean(proportion.P15, na.rm = T), sd(proportion.P15, na.rm = T))
proportion.P15 <- as.data.frame(proportion.P15)
proportion.P15$pen <- 15
names(proportion.P15) <- c('proportion', 'pen')
#prop.perhr <- rbind(proportion.P12, proportion.P14, proportion.P15)
#cov.anova <- aov(proportion~pen, data = prop.perhr)
#anova.sum <- unlist(summary(cov.anova))
#anova.list[,as.character(i)] <- anova.sum[9]
}
}
coverage <- rbind(coverage.P12, coverage.P14, coverage.P15) #, anova.list)
print(coverage)
write.xlsx(coverage, 'CoverageOutput_hmean.xlsx')
}