## ----echo = FALSE-------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

## ----fig.cap="**Figure 2.** An overview of a ctd dataset.", fig.width=6, fig.height=6, dpi=72, dev.args=list(pointsize=14), message=FALSE----
library(oce)
data(ctd)
summary(ctd)
plot(ctd)

## ----fig.cap="**Figure 3.** Scanwise plot of the `ctdRaw` sample data set.  Note the spike at the start, the equilibration phase before the downcast, and the spurious freshening signal near the start of the upcast.", fig.width=5, fig.height=3, dpi=72, dev.args=list(pointsize=12)----
data(ctdRaw)
plotScan(ctdRaw)

## ----eval=FALSE---------------------------------------------------------------
# plotScan(ctdTrim(ctdRaw, "range",
#     parameters = list(item = "scan", from = 140, to = 250)
# ))
# plotScan(ctdTrim(ctdRaw, "range",
#     parameters = list(item = "scan", from = 150, to = 250)
# ))

## ----eval=FALSE---------------------------------------------------------------
# ctdTrimmed <- ctdTrim(ctdRaw)

## ----eval=FALSE---------------------------------------------------------------
# plot(ctdDecimate(ctdTrim(read.ctd("stn123.cnv"))))

## ----eval=FALSE---------------------------------------------------------------
# library(oce)
# # http://cchdo.ucsd.edu/data/7971/ar18_58JH19941029_ct1.zip
# # setwd("~/Downloads/ar18_58JH19941029_ct1")
# files <- list.files(pattern = "*.csv$", full.names = TRUE)
# for (i in seq_along(files)) {
#     x <- read.ctd(files[i])
#     if (i == 1) {
#         plotTS(x, Slim = c(31, 35.5), Tlim = c(-2, 10), type = "o")
#     } else {
#         points(x[["salinity"]], x[["potential temperature"]])
#         lines(x[["salinity"]], x[["potential temperature"]])
#     }
# }

## ----fig.width=5, fig.height=5, fig.keep="none"-------------------------------
library(oce)
data(ctd)
pycnocline <- ctdTrim(ctd, "range",
    parameters = list(item = "pressure", from = 5, to = 12)
)
plotProfile(pycnocline, which = "density+N2")

## ----fig.width=5, fig.height=5, fig.keep="none"-------------------------------
library(oce)
data(ctd)
pycnocline <- subset(ctd, 5 <= pressure & pressure <= 12)
plotProfile(pycnocline, which = "density+N2")

## ----eval=FALSE---------------------------------------------------------------
# library(oce)
# # http://cchdo.ucsd.edu/data/7971/ar18_58JH19941029_ct1.zip
# # setwd("~/Downloads/ar18_58JH19941029_ct1")
# files <- list.files(pattern = "*.csv$", full.names = TRUE)
# n <- length(files)
# ctds <- vector("list", n) # to hold the CTD objects
# station <- vector("list", n)
# for (i in 1:n) {
#     ctds[[i]] <- read.ctd(files[i])
#     station[[i]] <- ctds[[i]][["station"]]
# }
# sal <- unlist(lapply(1:n, function(i) ctds[[i]][["salinity"]]))
# tem <- unlist(lapply(1:n, function(i) ctds[[i]][["temperature"]]))
# pre <- unlist(lapply(1:n, function(i) ctds[[i]][["pressure"]]))
# overall <- as.ctd(sal, tem, pre)
# png("ar18_%02d.png")
# for (i in 1:n) {
#     plotTS(overall, col = "gray")
#     lines(ctds[[i]][["salinity"]], ctds[[i]][["potential temperature"]])
#     mtext(station[i], side = 3, line = 0)
# }
# dev.off()