oce (version 1.0-1)

as.tidem: Create tidem object from fitted harmonic data

Description

This function is intended to provide a bridge to predict.tidem, enabling tidal predictions based on published tables of harmonic fits. CAUTION: this is a provisional function, and its action and argument list may change through the summer of 2018 ... use with caution!

Usage

as.tidem(tRef, latitude, name, amplitude, phase,
  debug = getOption("oceDebug"))

Arguments

tRef

a POSIXt value indicating the mean time of the observations used to develop the harmonic model. This is rounded to the nearest hour in as.tidem, to match tidem.

latitude

Numerical value indicating the latitude of the observations that were used to create the harmonic model.

name

Character vector holding names of constituents, in the notation used within the const element of data(tidedata).

amplitude

Numeric vector of constituent amplitudes.

phase

Numeric vector of constituent Greenwich phases.

debug

an integer specifying whether debugging information is to be printed during the processing. This is a general parameter that is used by many oce functions. Generally, setting debug=0 turns off the printing, while higher values suggest that more information be printed. If one function calls another, it usually reduces the value of debug first, so that a user can often obtain deeper debugging by specifying higher debug values.

Value

An object of tidem-class, with only minimal contents.

Examples

# NOT RUN {
# Simulate a tide table with output from tidem().
data(sealevelTuktoyaktuk)
# 'm0' is model fitted by tidem()
m0 <- tidem(sealevelTuktoyaktuk)
p0 <- predict(m0, sealevelTuktoyaktuk[["time"]])
m1 <- as.tidem(mean(sealevelTuktoyaktuk[["time"]]), sealevelTuktoyaktuk[["latitude"]],
               m0[["name"]], m0[["amplitude"]], m0[["phase"]])
# Test agreement with tidem() result, by comparing predicted sealevels.
p1 <- predict(m1, sealevelTuktoyaktuk[["time"]])
expect_lt(max(abs(p1 - p0), na.rm=TRUE), 1e-10)
# Simplified harmonic model, using large constituents
# > m0[["name"]][which(m[["amplitude"]]>0.05)]
# [1] "Z0"  "MM"  "MSF" "O1"  "K1"  "OO1" "N2"  "M2"  "S2"
h <- "
name  amplitude      phase
  Z0 1.98061875   0.000000
  MM 0.21213065 263.344739
 MSF 0.15605629 133.795004
  O1 0.07641438  74.233130
  K1 0.13473817  81.093134
 OO1 0.05309911 235.749693
  N2 0.08377108  44.521462
  M2 0.49041340  77.703594
  S2 0.22023705 137.475767"
coef <- read.table(text=h, header=TRUE)
m2 <- as.tidem(mean(sealevelTuktoyaktuk[["time"]]),
               sealevelTuktoyaktuk[["latitude"]],
               coef$name, coef$amplitude, coef$phase)
p2 <- predict(m2, sealevelTuktoyaktuk[["time"]])
expect_lt(max(abs(p2 - p0), na.rm=TRUE), 1)
par(mfrow=c(3, 1))
oce.plot.ts(sealevelTuktoyaktuk[["time"]], p0)
ylim <- par("usr")[3:4] # to match scales in other panels
oce.plot.ts(sealevelTuktoyaktuk[["time"]], p1, ylim=ylim)
oce.plot.ts(sealevelTuktoyaktuk[["time"]], p2, ylim=ylim)
# }