videos/09/video09_qc_advanced.R

In dankelley/argoFloats: Analysis of Oceanographic Argo Floats

## Video 9: Quality Control Advanced

## Part 1: Overview (from video 08)

## QC Plot
library(argoFloats)
data("index")
index1 <- subset(index, ID='1901584')
profiles <- getProfiles(index1)
argos <- readProfiles(profiles)
plot(argos, which='QC', parameter='temperature')

## showQCTests
index1[['cycle']]
index2 <- subset(index1, cycle='124')
profiles2 <- getProfiles(index2)
argos2 <- readProfiles(profiles2)
showQCTests(argos2[[1]])
##showQCTests(argos2[[1]], style='full')

## applyQC()
clean <- applyQC(argos)
par(mfrow=c(1, 2))
plot(argos, which="TS")
plot(clean, which="TS")


## Part 2: Exploring bad Data

## Identify the bad data
par(mfrow=c(1,1))
plot(clean, which="TS", eos="gsw")
SA <- unlist(clean[["SA"]])
CT <- unlist(clean[["CT"]])
message("Please click a point on the graph that you think is bad")
bad <- identify(SA, CT, n=1)
SAbad <- SA[bad]
CTbad <- CT[bad]
points(SAbad, CTbad) # plot it, to check

## Find the cycle that holds the identified bad data
cycles <- clean[["argos"]]
for (icycle in seq_along(cycles)) {
    thisCycle <- cycles[[icycle]]
    w <- which(SAbad == thisCycle[["SA"]] & CTbad == thisCycle[["CT"]])
    if (length(w)) {
        message(sprintf("Bad point: SA=%.3f, CT=%.3f in the %d-th cycle (i.e. cycle '%s') at %.1f dbar",
                        SAbad, CTbad, icycle,
                        thisCycle[["cycleNumber"]], thisCycle[["pressure"]][w]))
        break
    }
}

## Further analysis of the bad point
clean147 <- subset(clean, cycle='147')
plot(clean147, which="TS")
showQCTests(clean147[[1]], style="full")