Nothing
## ----echo=FALSE---------------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
## -----------------------------------------------------------------------------
library(oce)
## ----eval=FALSE---------------------------------------------------------------
# d <- read.oce(f)
## ----eval=FALSE---------------------------------------------------------------
# d <- read.adp(f)
## ----eval=FALSE---------------------------------------------------------------
# f <- "/data/archive/sleiwex/2008/moorings/m09/adp/rdi_2615/raw/adp_rdi_2615.000"
# dall <- read.oce(f)
## ----eval=FALSE---------------------------------------------------------------
# d100 <- read.oce(f, by=100)
## ----eval=FALSE---------------------------------------------------------------
# read.oce(f, from=as.POSIXct("2008-06-26", tz="UTC"),
# to=as.POSIXct("2008-06-27", tz="UTC"),
# by="60:00",
# latitude=47.88126, longitude=-69.73433)
## ----results="hide"-----------------------------------------------------------
data(adp)
summary(adp)
## ----eval=FALSE---------------------------------------------------------------
# beam <- read.oce(f)
# xyx <- beamToXyz(beam)
# enu <- xyzToEnu(xyz, declination=-18.1)
## ----fig.height=7, fig.width=4.5, dev.args=list(pointsize=13)-----------------
plot(adp)
## ----fig.height=7, fig.width=4.5, dev.args=list(pointsize=13)-----------------
plot(subset(adp, distance<20))
## -----------------------------------------------------------------------------
time <- adp[["time"]]
distance <- adp[["distance"]]
## -----------------------------------------------------------------------------
v <- adp[["v"]]
## -----------------------------------------------------------------------------
a <- adp[["a", "numeric"]]
## ----results="hide"-----------------------------------------------------------
sort(names(adp[["metadata"]]))
## -----------------------------------------------------------------------------
adp[["originalCoordinate"]]
adp[["oceCoordinate"]]
## -----------------------------------------------------------------------------
processingLogShow(adp)
## ----fig.width=3, fig.height=3, dev.args=list(pointsize=9)--------------------
plot(adp, which="uv")
## ----eval=FALSE, message=FALSE, warning=FALSE, error=FALSE--------------------
# library(oce)
# adcp <- read.adp("COR2019002_20190818T064815_007_000000.ENS")
# enu <- toEnu(adcp)
# removeShipSpeed <- subtractBottomVelocity(enu)
# plot(removeShipSpeed, which=1:3)
## ----eval=FALSE---------------------------------------------------------------
# plot(subset(adp, time < median(adp[["time"]])))
## ----fig.height=2, dev.args=list(pointsize=9)---------------------------------
time <- adp[["time"]]
v <- adp[["v"]]
# The second index is for bin number, the third for beam number
midIndex <- dim(v)[2]/2
eastMid <- v[, midIndex, 1] # third index is beam
distance <- adp[["distance"]][midIndex]
oce.plot.ts(time, eastMid, ylab="Eastward velocity [m/s]")
# Depth mean; note that na.rm, is passed by apply() to mean()
eastMean <- apply(v[, , 1], 1, mean, na.rm=TRUE)
lines(time, eastMean, col=2)
## -----------------------------------------------------------------------------
u <- adp[["v"]][, , 1]
v <- adp[["v"]][, , 2]
ok <- is.finite(u) & is.finite(v) # remove NA values
u <- u[ok]
v <- v[ok]
eigen(cov(data.frame(u, v)))
## -----------------------------------------------------------------------------
pr <- prcomp(data.frame(u, v))
## -----------------------------------------------------------------------------
pr
## ----fig.height=2, dev.args=list(pointsize=9)---------------------------------
time <- adp[["time"]]
pressure <- adp[["pressure"]]
oce.plot.ts(time, pressure)
## -----------------------------------------------------------------------------
m <- tidem(as.sealevel(pressure, time))
## -----------------------------------------------------------------------------
summary(m)
## ----fig.height=2, dev.args=list(pointsize=9)---------------------------------
oce.plot.ts(time, pressure, type="p", col="blue")
timePredict <- seq(min(time), max(time), length.out=200)
pressurePredict <- predict(m, timePredict)
lines(timePredict, pressurePredict, col="red")
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