simTrueTrack: Simulate a known movement track for subsequent estimation...

In yaps: Track Estimation using YAPS (Yet Another Positioning Solver)

Description

Produces a simulated regular time-spaced track following the specified movement model. Linear movement between consecutive observations is assumed. The output contains x, y, time and sound speed at each simulated position.

Usage

simTrueTrack(
  model = "rw",
  n,
  deltaTime = 1,
  D = NULL,
  shape = NULL,
  scale = NULL,
  addDielPattern = TRUE,
  ss = "rw",
  start_pos = NULL
)

Arguments

model	Movement model: 'rw': Two-dimension random walk (X,Y)
n	Number of steps in the simulated track
deltaTime	Number of time units (seconds) between each location
D	Diffusivity of the animal movement - only used if model='rw'
shape	Shape of the Weibull distribution - only used when model='crw'.
scale	Scale of the Weibull distribution - only used when model='crw'.
addDielPattern	Adds a realistic(?) diel pattern to movement. Periods of both low and high movement
ss	Simulations model for Speed of Sound - defaults to 'rw' = RW-model.
start_pos	Specify the starting position of the track with c(x0, y0)

Value

data.frame containing a simulated track

Examples

library(yaps)
set.seed(42)
# Simulate true track of animal movement of n seconds
trueTrack <- simTrueTrack(model='crw', n = 1000, deltaTime=1, shape=1, 
	scale=0.5, addDielPattern=TRUE, ss='rw')

# Simulate telemetry observations from true track.
# Format and parameters depend on type of transmitter burst interval (BI).
pingType <- 'sbi'

if(pingType == 'sbi') { # stable BI
    sbi_mean <- 30; sbi_sd <- 1e-4;
    teleTrack <- simTelemetryTrack(trueTrack, pingType=pingType, sbi_mean=sbi_mean, sbi_sd=sbi_sd)
} else if(pingType == 'rbi'){ # random BI
    pingType <- 'rbi'; rbi_min <- 20; rbi_max <- 40;
    teleTrack <- simTelemetryTrack(trueTrack, pingType=pingType, rbi_min=rbi_min, rbi_max=rbi_max)
}

# Simulate hydrophone array
hydros <- simHydros(auto=TRUE, trueTrack=trueTrack)
toa_list <- simToa(teleTrack, hydros, pingType, sigmaToa=1e-4, pNA=0.25, pMP=0.01)
toa <- toa_list$toa

# Specify whether to use ss_data from measured water temperature (ss_data_what <- 'data') or 
#	to estimate ss in the model (ss_data_what <- 'est')
ss_data_what <- 'data'
if(ss_data_what == 'data') {ss_data <- teleTrack$ss} else {ss_data <- 0}


if(pingType == 'sbi'){
    inp <- getInp(hydros, toa, E_dist="Mixture", n_ss=10, pingType=pingType, sdInits=0, 
		ss_data_what=ss_data_what, ss_data=ss_data)
} else if(pingType == 'rbi'){
    inp <- getInp(hydros, toa, E_dist="Mixture", n_ss=10, pingType=pingType, sdInits=0, 
		rbi_min=rbi_min, rbi_max=rbi_max, ss_data_what=ss_data_what, ss_data=ss_data)
} 

pl <- c()
maxIter <- ifelse(pingType=="sbi", 500, 5000)
outTmb <- runYaps(inp, maxIter=maxIter, getPlsd=TRUE, getRep=TRUE)

# Estimates in pl
pl <- outTmb$pl
# Correcting for hydrophone centering
pl$X <- outTmb$pl$X + inp$inp_params$Hx0
pl$Y <- outTmb$pl$Y + inp$inp_params$Hy0


# Error estimates in plsd
plsd <- outTmb$plsd

# plot the resulting estimated track
plot(y~x, data=trueTrack, type="l", xlim=range(hydros$hx), ylim=range(hydros$hy), asp=1)
lines(y~x, data=teleTrack)
points(hy~hx, data=hydros, col="green", pch=20, cex=3)
lines(pl$Y~pl$X, col="red")

yaps documentation built on April 14, 2021, 1:06 a.m.