############
#CTD plots #
############
CTDplot <- function(station)
{
  #######################################################
  #Example for how to use the function:
  
  #CTDplot(sta0386)
  #where sta0386 is the first name in the cnv-file for which you want to make a CDT-plot.
  #
  #In the import function all the measured variables are included but just four of them
  #are plotted against depth, i.e. temperature, oxygen, salinity (PSU) and light.
  #If the latter is not recorded, it will not show up in the plot.
  
  #If you want to plot other variables you must change the programming below.
  #The only thing you need to understand is the latter part called Plotting.
  #To understand the variable names, you must go into your CTD-file and
  #look at the section where you find lines starting with "name 0 =", "name 1 =", etc.
  #This is where variables are explained. The variable names in the syntax below
  #are the same as in the CTD-file. For example: Depth is called prDM. An exception is
  #that the names with forward slash (/) and dash (-) have been replaced with
  #two dots (..) or one dot (.), respectively. It is done like this to get names
  #that will work under R.
  
  #You must set the correct working directory for the function to work.
  #Example:
  #setwd('bla/bla/rwork')
  ##########################################################
  
  
  #Importing a cnv-file to R #
  ############################
  filename <- paste('data/', deparse(substitute(station)),'.cnv',sep='')
  
  options(warn=-1)
  nlines <- grep('*END*', readLines(filename)) #To skip all lines until *END* and only extract
  # the data from the .cnv file.
  options(warn=0)
  
  ctd.df <-read.table(filename, skip=nlines, header=F, sep="")
  
  #Extract the correct variable names from the CTD-file:
  options(warn=-1)
  nlines.START <- grep('name 0', readLines(filename))-1
  nlines.END <- grep('= flag:', readLines(filename))
  nlines.describing.variables <- nlines.END-nlines.START
  options(warn=0)
  v1 <- scan(filename, what='raw', skip=nlines.START, nlines=nlines.describing.variables, sep='\n')
  v2 <- sub(':.*', "", v1)
  varnames <- as.factor(sub('.*= ', '', v2))
  varnames <- gsub('/', '..', varnames)
  varnames <- gsub('-', '.', varnames)
  
  #varnames <- ifelse(varnames=='c0S/m','c0S.m', ifelse(varnames=='c1S/m','c1S.m', ifelse(varnames=='',''
  
  names(ctd.df) <- varnames
  
  
  #Removing PAR (photosynthetically active radiation) values lower or equal to 1e-12:
  #(Do this if the photon-unit repeats the same low number at a given depth and onwards,
  #indicating that the unit has reached the lower end of its range)
  ctd.df$par <- ifelse(ctd.df$par<=1e-12, NA, ctd.df$par)
  
  
  
  #Clean up
  rm(nlines, nlines.START, nlines.END, nlines.describing.variables, v1, v2, varnames)


# Plotting with ggplot
######################
library(ggplot2)

# Create an object for an expression with special characters (e.g. degrees Celsius symbol,
# to later use as axes labels)
xtekst1 <- expression(paste('Temperature ','(', degree,'C)'))
# Create an object for a plot of temperature (t068C) against depth (prDM). scale_y_reverse()
# reverses the y axis, geom_line() adds the data as a line, xlab() and ylab() create axis labels.
# ylab() has been left blank to later add a common y-label to all graphs.
p1 <- ggplot(data=ctd.df, aes(x=t068C, y=prDM))
p1 <- p1 + scale_y_reverse()
p1 <- p1 + geom_path()
p1 <- p1 + xlab(xtekst1) + ylab('')
p1 <- p1 + theme_bw(base_size=20)

# Plot the other variables.
xtekst2 <- expression(paste('Oxygen (ml ', L^-1, ')'))
p2 <- ggplot(data=ctd.df, aes(x=sbeox0ML..L, y=prDM))
p2 <- p2 + scale_y_reverse()
p2 <- p2 + geom_path()
p2 <- p2 + xlab(xtekst2) + ylab('')
p2 <- p2 + theme_bw(base_size=20)

p3 <- ggplot(data=ctd.df, aes(x=sal00, y=prDM))
p3 <- p3 + scale_y_reverse()
p3 <- p3 + geom_path()
p3 <- p3 + xlab("Salinity (PSU)") + ylab('')
p3 <- p3 + theme_bw(base_size=20)

xtekst3 <- expression(paste('PAR (',mu,'Mole ', m^2, sec^-1, ')'))
p4 <- ggplot(data=ctd.df, aes(x=par, y=prDM)) + ylim(60,0)
p4 <- p4 + geom_path()
p4 <- p4 + xlab(xtekst3) + ylab('')
p4 <- p4 + theme_bw(base_size=20)

# Place multiple figures on one page, using the gridExtra package. ncol= assigns the number of columns,
# top= creates a figure heading, left= creates a common y-axis label.
library(gridExtra)
library(grid)
p5 <- grid.arrange(p1,p2,p3,p4, ncol=2, top=textGrob(paste('Station: ', deparse(substitute(station)),sep=''), gp=gpar(fontsize=20)), left=textGrob('Pressure (dbar)', rot=90, vjust=2, gp=gpar(fontsize=20)))
grid.draw(p5)

#Saving the plot
savename <- paste('figures/', deparse(substitute(station)),'.png',sep='')
ggsave(file=savename, p5)
}